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Use .multiplyMatrices( a, b ) instead.\\\\\\\"),this.multiplyMatrices(t,e)):this.multiplyMatrices(this,t)}premultiply(t){return this.multiplyMatrices(t,this)}multiplyMatrices(t,e){const s=t.elements,i=e.elements,r=this.elements,n=s[0],a=s[4],o=s[8],h=s[12],u=s[1],c=s[5],l=s[9],d=s[13],p=s[2],m=s[6],f=s[10],y=s[14],g=s[3],x=s[7],b=s[11],M=s[15],w=i[0],v=i[4],_=i[8],T=i[12],S=i[1],A=i[5],E=i[9],z=i[13],R=i[2],I=i[6],k=i[10],L=i[14],O=i[3],P=i[7],B=i[11],N=i[15];return r[0]=n*w+a*S+o*R+h*O,r[4]=n*v+a*A+o*I+h*P,r[8]=n*_+a*E+o*k+h*B,r[12]=n*T+a*z+o*L+h*N,r[1]=u*w+c*S+l*R+d*O,r[5]=u*v+c*A+l*I+d*P,r[9]=u*_+c*E+l*k+d*B,r[13]=u*T+c*z+l*L+d*N,r[2]=p*w+m*S+f*R+y*O,r[6]=p*v+m*A+f*I+y*P,r[10]=p*_+m*E+f*k+y*B,r[14]=p*T+m*z+f*L+y*N,r[3]=g*w+x*S+b*R+M*O,r[7]=g*v+x*A+b*I+M*P,r[11]=g*_+x*E+b*k+M*B,r[15]=g*T+x*z+b*L+M*N,this}multiplyScalar(t){const e=this.elements;return e[0]*=t,e[4]*=t,e[8]*=t,e[12]*=t,e[1]*=t,e[5]*=t,e[9]*=t,e[13]*=t,e[2]*=t,e[6]*=t,e[10]*=t,e[14]*=t,e[3]*=t,e[7]*=t,e[11]*=t,e[15]*=t,this}determinant(){const t=this.elements,e=t[0],s=t[4],i=t[8],r=t[12],n=t[1],a=t[5],o=t[9],h=t[13],u=t[2],c=t[6],l=t[10],d=t[14];return t[3]*(+r*o*c-i*h*c-r*a*l+s*h*l+i*a*d-s*o*d)+t[7]*(+e*o*d-e*h*l+r*n*l-i*n*d+i*h*u-r*o*u)+t[11]*(+e*h*c-e*a*d-r*n*c+s*n*d+r*a*u-s*h*u)+t[15]*(-i*a*u-e*o*c+e*a*l+i*n*c-s*n*l+s*o*u)}transpose(){const t=this.elements;let e;return e=t[1],t[1]=t[4],t[4]=e,e=t[2],t[2]=t[8],t[8]=e,e=t[6],t[6]=t[9],t[9]=e,e=t[3],t[3]=t[12],t[12]=e,e=t[7],t[7]=t[13],t[13]=e,e=t[11],t[11]=t[14],t[14]=e,this}setPosition(t,e,s){const i=this.elements;return t.isVector3?(i[12]=t.x,i[13]=t.y,i[14]=t.z):(i[12]=t,i[13]=e,i[14]=s),this}invert(){const t=this.elements,e=t[0],s=t[1],i=t[2],r=t[3],n=t[4],a=t[5],o=t[6],h=t[7],u=t[8],c=t[9],l=t[10],d=t[11],p=t[12],m=t[13],f=t[14],y=t[15],g=c*f*h-m*l*h+m*o*d-a*f*d-c*o*y+a*l*y,x=p*l*h-u*f*h-p*o*d+n*f*d+u*o*y-n*l*y,b=u*m*h-p*c*h+p*a*d-n*m*d-u*a*y+n*c*y,M=p*c*o-u*m*o-p*a*l+n*m*l+u*a*f-n*c*f,w=e*g+s*x+i*b+r*M;if(0===w)return this.set(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0);const v=1/w;return t[0]=g*v,t[1]=(m*l*r-c*f*r-m*i*d+s*f*d+c*i*y-s*l*y)*v,t[2]=(a*f*r-m*o*r+m*i*h-s*f*h-a*i*y+s*o*y)*v,t[3]=(c*o*r-a*l*r-c*i*h+s*l*h+a*i*d-s*o*d)*v,t[4]=x*v,t[5]=(u*f*r-p*l*r+p*i*d-e*f*d-u*i*y+e*l*y)*v,t[6]=(p*o*r-n*f*r-p*i*h+e*f*h+n*i*y-e*o*y)*v,t[7]=(n*l*r-u*o*r+u*i*h-e*l*h-n*i*d+e*o*d)*v,t[8]=b*v,t[9]=(p*c*r-u*m*r-p*s*d+e*m*d+u*s*y-e*c*y)*v,t[10]=(n*m*r-p*a*r+p*s*h-e*m*h-n*s*y+e*a*y)*v,t[11]=(u*a*r-n*c*r-u*s*h+e*c*h+n*s*d-e*a*d)*v,t[12]=M*v,t[13]=(u*m*i-p*c*i+p*s*l-e*m*l-u*s*f+e*c*f)*v,t[14]=(p*a*i-n*m*i-p*s*o+e*m*o+n*s*f-e*a*f)*v,t[15]=(n*c*i-u*a*i+u*s*o-e*c*o-n*s*l+e*a*l)*v,this}scale(t){const e=this.elements,s=t.x,i=t.y,r=t.z;return e[0]*=s,e[4]*=i,e[8]*=r,e[1]*=s,e[5]*=i,e[9]*=r,e[2]*=s,e[6]*=i,e[10]*=r,e[3]*=s,e[7]*=i,e[11]*=r,this}getMaxScaleOnAxis(){const t=this.elements,e=t[0]*t[0]+t[1]*t[1]+t[2]*t[2],s=t[4]*t[4]+t[5]*t[5]+t[6]*t[6],i=t[8]*t[8]+t[9]*t[9]+t[10]*t[10];return Math.sqrt(Math.max(e,s,i))}makeTranslation(t,e,s){return this.set(1,0,0,t,0,1,0,e,0,0,1,s,0,0,0,1),this}makeRotationX(t){const e=Math.cos(t),s=Math.sin(t);return this.set(1,0,0,0,0,e,-s,0,0,s,e,0,0,0,0,1),this}makeRotationY(t){const e=Math.cos(t),s=Math.sin(t);return this.set(e,0,s,0,0,1,0,0,-s,0,e,0,0,0,0,1),this}makeRotationZ(t){const e=Math.cos(t),s=Math.sin(t);return this.set(e,-s,0,0,s,e,0,0,0,0,1,0,0,0,0,1),this}makeRotationAxis(t,e){const s=Math.cos(e),i=Math.sin(e),r=1-s,n=t.x,a=t.y,o=t.z,h=r*n,u=r*a;return this.set(h*n+s,h*a-i*o,h*o+i*a,0,h*a+i*o,u*a+s,u*o-i*n,0,h*o-i*a,u*o+i*n,r*o*o+s,0,0,0,0,1),this}makeScale(t,e,s){return this.set(t,0,0,0,0,e,0,0,0,0,s,0,0,0,0,1),this}makeShear(t,e,s,i,r,n){return this.set(1,s,r,0,t,1,n,0,e,i,1,0,0,0,0,1),this}compose(t,e,s){const i=this.elements,r=e._x,n=e._y,a=e._z,o=e._w,h=r+r,u=n+n,c=a+a,l=r*h,d=r*u,p=r*c,m=n*u,f=n*c,y=a*c,g=o*h,x=o*u,b=o*c,M=s.x,w=s.y,v=s.z;return i[0]=(1-(m+y))*M,i[1]=(d+b)*M,i[2]=(p-x)*M,i[3]=0,i[4]=(d-b)*w,i[5]=(1-(l+y))*w,i[6]=(f+g)*w,i[7]=0,i[8]=(p+x)*v,i[9]=(f-g)*v,i[10]=(1-(l+m))*v,i[11]=0,i[12]=t.x,i[13]=t.y,i[14]=t.z,i[15]=1,this}decompose(t,e,s){const i=this.elements;let r=n.set(i[0],i[1],i[2]).length();const o=n.set(i[4],i[5],i[6]).length(),h=n.set(i[8],i[9],i[10]).length();this.determinant()<0&&(r=-r),t.x=i[12],t.y=i[13],t.z=i[14],a.copy(this);const u=1/r,c=1/o,l=1/h;return a.elements[0]*=u,a.elements[1]*=u,a.elements[2]*=u,a.elements[4]*=c,a.elements[5]*=c,a.elements[6]*=c,a.elements[8]*=l,a.elements[9]*=l,a.elements[10]*=l,e.setFromRotationMatrix(a),s.x=r,s.y=o,s.z=h,this}makePerspective(t,e,s,i,r,n){void 0===n&&console.warn(\\\\\\\"THREE.Matrix4: .makePerspective() has been redefined and has a new signature. Please check the docs.\\\\\\\");const a=this.elements,o=2*r/(e-t),h=2*r/(s-i),u=(e+t)/(e-t),c=(s+i)/(s-i),l=-(n+r)/(n-r),d=-2*n*r/(n-r);return a[0]=o,a[4]=0,a[8]=u,a[12]=0,a[1]=0,a[5]=h,a[9]=c,a[13]=0,a[2]=0,a[6]=0,a[10]=l,a[14]=d,a[3]=0,a[7]=0,a[11]=-1,a[15]=0,this}makeOrthographic(t,e,s,i,r,n){const a=this.elements,o=1/(e-t),h=1/(s-i),u=1/(n-r),c=(e+t)*o,l=(s+i)*h,d=(n+r)*u;return a[0]=2*o,a[4]=0,a[8]=0,a[12]=-c,a[1]=0,a[5]=2*h,a[9]=0,a[13]=-l,a[2]=0,a[6]=0,a[10]=-2*u,a[14]=-d,a[3]=0,a[7]=0,a[11]=0,a[15]=1,this}equals(t){const e=this.elements,s=t.elements;for(let t=0;t<16;t++)if(e[t]!==s[t])return!1;return!0}fromArray(t,e=0){for(let s=0;s<16;s++)this.elements[s]=t[s+e];return this}toArray(t=[],e=0){const s=this.elements;return t[e]=s[0],t[e+1]=s[1],t[e+2]=s[2],t[e+3]=s[3],t[e+4]=s[4],t[e+5]=s[5],t[e+6]=s[6],t[e+7]=s[7],t[e+8]=s[8],t[e+9]=s[9],t[e+10]=s[10],t[e+11]=s[11],t[e+12]=s[12],t[e+13]=s[13],t[e+14]=s[14],t[e+15]=s[15],t}}r.prototype.isMatrix4=!0;const n=new i.a,a=new r,o=new i.a(0,0,0),h=new i.a(1,1,1),u=new i.a,c=new i.a,l=new i.a},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return c}));var i=s(3);const r={aliceblue:15792383,antiquewhite:16444375,aqua:65535,aquamarine:8388564,azure:15794175,beige:16119260,bisque:16770244,black:0,blanchedalmond:16772045,blue:255,blueviolet:9055202,brown:10824234,burlywood:14596231,cadetblue:6266528,chartreuse:8388352,chocolate:13789470,coral:16744272,cornflowerblue:6591981,cornsilk:16775388,crimson:14423100,cyan:65535,darkblue:139,darkcyan:35723,darkgoldenrod:12092939,darkgray:11119017,darkgreen:25600,darkgrey:11119017,darkkhaki:12433259,darkmagenta:9109643,darkolivegreen:5597999,darkorange:16747520,darkorchid:10040012,darkred:9109504,darksalmon:15308410,darkseagreen:9419919,darkslateblue:4734347,darkslategray:3100495,darkslategrey:3100495,darkturquoise:52945,darkviolet:9699539,deeppink:16716947,deepskyblue:49151,dimgray:6908265,dimgrey:6908265,dodgerblue:2003199,firebrick:11674146,floralwhite:16775920,forestgreen:2263842,fuchsia:16711935,gainsboro:14474460,ghostwhite:16316671,gold:16766720,goldenrod:14329120,gray:8421504,green:32768,greenyellow:11403055,grey:8421504,honeydew:15794160,hotpink:16738740,indianred:13458524,indigo:4915330,ivory:16777200,khaki:15787660,lavender:15132410,lavenderblush:16773365,lawngreen:8190976,lemonchiffon:16775885,lightblue:11393254,lightcoral:15761536,lightcyan:14745599,lightgoldenrodyellow:16448210,lightgray:13882323,lightgreen:9498256,lightgrey:13882323,lightpink:16758465,lightsalmon:16752762,lightseagreen:2142890,lightskyblue:8900346,lightslategray:7833753,lightslategrey:7833753,lightsteelblue:11584734,lightyellow:16777184,lime:65280,limegreen:3329330,linen:16445670,magenta:16711935,maroon:8388608,mediumaquamarine:6737322,mediumblue:205,mediumorchid:12211667,mediumpurple:9662683,mediumseagreen:3978097,mediumslateblue:8087790,mediumspringgreen:64154,mediumturquoise:4772300,mediumvioletred:13047173,midnightblue:1644912,mintcream:16121850,mistyrose:16770273,moccasin:16770229,navajowhite:16768685,navy:128,oldlace:16643558,olive:8421376,olivedrab:7048739,orange:16753920,orangered:16729344,orchid:14315734,palegoldenrod:15657130,palegreen:10025880,paleturquoise:11529966,palevioletred:14381203,papayawhip:16773077,peachpuff:16767673,peru:13468991,pink:16761035,plum:14524637,powderblue:11591910,purple:8388736,rebeccapurple:6697881,red:16711680,rosybrown:12357519,royalblue:4286945,saddlebrown:9127187,salmon:16416882,sandybrown:16032864,seagreen:3050327,seashell:16774638,sienna:10506797,silver:12632256,skyblue:8900331,slateblue:6970061,slategray:7372944,slategrey:7372944,snow:16775930,springgreen:65407,steelblue:4620980,tan:13808780,teal:32896,thistle:14204888,tomato:16737095,turquoise:4251856,violet:15631086,wheat:16113331,white:16777215,whitesmoke:16119285,yellow:16776960,yellowgreen:10145074},n={h:0,s:0,l:0},a={h:0,s:0,l:0};function o(t,e,s){return s<0&&(s+=1),s>1&&(s-=1),s<1/6?t+6*(e-t)*s:s<.5?e:s<2/3?t+6*(e-t)*(2/3-s):t}function h(t){return t<.04045?.0773993808*t:Math.pow(.9478672986*t+.0521327014,2.4)}function u(t){return t<.0031308?12.92*t:1.055*Math.pow(t,.41666)-.055}class c{constructor(t,e,s){return void 0===e&&void 0===s?this.set(t):this.setRGB(t,e,s)}set(t){return t&&t.isColor?this.copy(t):\\\\\\\"number\\\\\\\"==typeof t?this.setHex(t):\\\\\\\"string\\\\\\\"==typeof t&&this.setStyle(t),this}setScalar(t){return this.r=t,this.g=t,this.b=t,this}setHex(t){return t=Math.floor(t),this.r=(t>>16&255)/255,this.g=(t>>8&255)/255,this.b=(255&t)/255,this}setRGB(t,e,s){return this.r=t,this.g=e,this.b=s,this}setHSL(t,e,s){if(t=i.f(t,1),e=i.d(e,0,1),s=i.d(s,0,1),0===e)this.r=this.g=this.b=s;else{const i=s<=.5?s*(1+e):s+e-s*e,r=2*s-i;this.r=o(r,i,t+1/3),this.g=o(r,i,t),this.b=o(r,i,t-1/3)}return this}setStyle(t){function e(e){void 0!==e&&parseFloat(e)<1&&console.warn(\\\\\\\"THREE.Color: Alpha component of \\\\\\\"+t+\\\\\\\" will be ignored.\\\\\\\")}let s;if(s=/^((?:rgb|hsl)a?)\\\\(([^\\\\)]*)\\\\)/.exec(t)){let t;const i=s[1],r=s[2];switch(i){case\\\\\\\"rgb\\\\\\\":case\\\\\\\"rgba\\\\\\\":if(t=/^\\\\s*(\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(r))return this.r=Math.min(255,parseInt(t[1],10))/255,this.g=Math.min(255,parseInt(t[2],10))/255,this.b=Math.min(255,parseInt(t[3],10))/255,e(t[4]),this;if(t=/^\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(r))return this.r=Math.min(100,parseInt(t[1],10))/100,this.g=Math.min(100,parseInt(t[2],10))/100,this.b=Math.min(100,parseInt(t[3],10))/100,e(t[4]),this;break;case\\\\\\\"hsl\\\\\\\":case\\\\\\\"hsla\\\\\\\":if(t=/^\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(r)){const s=parseFloat(t[1])/360,i=parseInt(t[2],10)/100,r=parseInt(t[3],10)/100;return e(t[4]),this.setHSL(s,i,r)}}}else if(s=/^\\\\#([A-Fa-f\\\\d]+)$/.exec(t)){const t=s[1],e=t.length;if(3===e)return this.r=parseInt(t.charAt(0)+t.charAt(0),16)/255,this.g=parseInt(t.charAt(1)+t.charAt(1),16)/255,this.b=parseInt(t.charAt(2)+t.charAt(2),16)/255,this;if(6===e)return this.r=parseInt(t.charAt(0)+t.charAt(1),16)/255,this.g=parseInt(t.charAt(2)+t.charAt(3),16)/255,this.b=parseInt(t.charAt(4)+t.charAt(5),16)/255,this}return t&&t.length>0?this.setColorName(t):this}setColorName(t){const e=r[t.toLowerCase()];return void 0!==e?this.setHex(e):console.warn(\\\\\\\"THREE.Color: Unknown color \\\\\\\"+t),this}clone(){return new this.constructor(this.r,this.g,this.b)}copy(t){return this.r=t.r,this.g=t.g,this.b=t.b,this}copyGammaToLinear(t,e=2){return this.r=Math.pow(t.r,e),this.g=Math.pow(t.g,e),this.b=Math.pow(t.b,e),this}copyLinearToGamma(t,e=2){const s=e>0?1/e:1;return this.r=Math.pow(t.r,s),this.g=Math.pow(t.g,s),this.b=Math.pow(t.b,s),this}convertGammaToLinear(t){return this.copyGammaToLinear(this,t),this}convertLinearToGamma(t){return this.copyLinearToGamma(this,t),this}copySRGBToLinear(t){return this.r=h(t.r),this.g=h(t.g),this.b=h(t.b),this}copyLinearToSRGB(t){return this.r=u(t.r),this.g=u(t.g),this.b=u(t.b),this}convertSRGBToLinear(){return this.copySRGBToLinear(this),this}convertLinearToSRGB(){return this.copyLinearToSRGB(this),this}getHex(){return 255*this.r<<16^255*this.g<<8^255*this.b<<0}getHexString(){return(\\\\\\\"000000\\\\\\\"+this.getHex().toString(16)).slice(-6)}getHSL(t){const e=this.r,s=this.g,i=this.b,r=Math.max(e,s,i),n=Math.min(e,s,i);let a,o;const h=(n+r)/2;if(n===r)a=0,o=0;else{const t=r-n;switch(o=h<=.5?t/(r+n):t/(2-r-n),r){case e:a=(s-i)/t+(s65535?o.i:o.h)(t,1):this.index=t,this}getAttribute(t){return this.attributes[t]}setAttribute(t,e){return this.attributes[t]=e,this}deleteAttribute(t){return delete this.attributes[t],this}hasAttribute(t){return void 0!==this.attributes[t]}addGroup(t,e,s=0){this.groups.push({start:t,count:e,materialIndex:s})}clearGroups(){this.groups=[]}setDrawRange(t,e){this.drawRange.start=t,this.drawRange.count=e}applyMatrix4(t){const e=this.attributes.position;void 0!==e&&(e.applyMatrix4(t),e.needsUpdate=!0);const s=this.attributes.normal;if(void 0!==s){const e=(new l.a).getNormalMatrix(t);s.applyNormalMatrix(e),s.needsUpdate=!0}const i=this.attributes.tangent;return void 0!==i&&(i.transformDirection(t),i.needsUpdate=!0),null!==this.boundingBox&&this.computeBoundingBox(),null!==this.boundingSphere&&this.computeBoundingSphere(),this}applyQuaternion(t){return f.makeRotationFromQuaternion(t),this.applyMatrix4(f),this}rotateX(t){return f.makeRotationX(t),this.applyMatrix4(f),this}rotateY(t){return f.makeRotationY(t),this.applyMatrix4(f),this}rotateZ(t){return f.makeRotationZ(t),this.applyMatrix4(f),this}translate(t,e,s){return f.makeTranslation(t,e,s),this.applyMatrix4(f),this}scale(t,e,s){return f.makeScale(t,e,s),this.applyMatrix4(f),this}lookAt(t){return y.lookAt(t),y.updateMatrix(),this.applyMatrix4(y.matrix),this}center(){return this.computeBoundingBox(),this.boundingBox.getCenter(g).negate(),this.translate(g.x,g.y,g.z),this}setFromPoints(t){const e=[];for(let s=0,i=t.length;s0&&(t.userData=this.userData),void 0!==this.parameters){const e=this.parameters;for(const s in e)void 0!==e[s]&&(t[s]=e[s]);return t}t.data={attributes:{}};const e=this.index;null!==e&&(t.data.index={type:e.array.constructor.name,array:Array.prototype.slice.call(e.array)});const s=this.attributes;for(const e in s){const i=s[e];t.data.attributes[e]=i.toJSON(t.data)}const i={};let r=!1;for(const e in this.morphAttributes){const s=this.morphAttributes[e],n=[];for(let e=0,i=s.length;e0&&(i[e]=n,r=!0)}r&&(t.data.morphAttributes=i,t.data.morphTargetsRelative=this.morphTargetsRelative);const n=this.groups;n.length>0&&(t.data.groups=JSON.parse(JSON.stringify(n)));const a=this.boundingSphere;return null!==a&&(t.data.boundingSphere={center:a.center.toArray(),radius:a.radius}),t}clone(){return(new this.constructor).copy(this)}copy(t){this.index=null,this.attributes={},this.morphAttributes={},this.groups=[],this.boundingBox=null,this.boundingSphere=null;const e={};this.name=t.name;const s=t.index;null!==s&&this.setIndex(s.clone(e));const i=t.attributes;for(const t in i){const s=i[t];this.setAttribute(t,s.clone(e))}const r=t.morphAttributes;for(const t in r){const s=[],i=r[t];for(let t=0,r=i.length;t=0?1:-1,i=1-e*e;if(i>Number.EPSILON){const r=Math.sqrt(i),n=Math.atan2(r,e*s);t=Math.sin(t*n)/r,a=Math.sin(a*n)/r}const r=a*s;if(o=o*t+l*r,h=h*t+d*r,u=u*t+p*r,c=c*t+m*r,t===1-a){const t=1/Math.sqrt(o*o+h*h+u*u+c*c);o*=t,h*=t,u*=t,c*=t}}t[e]=o,t[e+1]=h,t[e+2]=u,t[e+3]=c}static multiplyQuaternionsFlat(t,e,s,i,r,n){const a=s[i],o=s[i+1],h=s[i+2],u=s[i+3],c=r[n],l=r[n+1],d=r[n+2],p=r[n+3];return t[e]=a*p+u*c+o*d-h*l,t[e+1]=o*p+u*l+h*c-a*d,t[e+2]=h*p+u*d+a*l-o*c,t[e+3]=u*p-a*c-o*l-h*d,t}get x(){return this._x}set x(t){this._x=t,this._onChangeCallback()}get y(){return this._y}set y(t){this._y=t,this._onChangeCallback()}get z(){return this._z}set z(t){this._z=t,this._onChangeCallback()}get w(){return this._w}set w(t){this._w=t,this._onChangeCallback()}set(t,e,s,i){return this._x=t,this._y=e,this._z=s,this._w=i,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._w)}copy(t){return this._x=t.x,this._y=t.y,this._z=t.z,this._w=t.w,this._onChangeCallback(),this}setFromEuler(t,e){if(!t||!t.isEuler)throw new Error(\\\\\\\"THREE.Quaternion: .setFromEuler() now expects an Euler rotation rather than a Vector3 and order.\\\\\\\");const s=t._x,i=t._y,r=t._z,n=t._order,a=Math.cos,o=Math.sin,h=a(s/2),u=a(i/2),c=a(r/2),l=o(s/2),d=o(i/2),p=o(r/2);switch(n){case\\\\\\\"XYZ\\\\\\\":this._x=l*u*c+h*d*p,this._y=h*d*c-l*u*p,this._z=h*u*p+l*d*c,this._w=h*u*c-l*d*p;break;case\\\\\\\"YXZ\\\\\\\":this._x=l*u*c+h*d*p,this._y=h*d*c-l*u*p,this._z=h*u*p-l*d*c,this._w=h*u*c+l*d*p;break;case\\\\\\\"ZXY\\\\\\\":this._x=l*u*c-h*d*p,this._y=h*d*c+l*u*p,this._z=h*u*p+l*d*c,this._w=h*u*c-l*d*p;break;case\\\\\\\"ZYX\\\\\\\":this._x=l*u*c-h*d*p,this._y=h*d*c+l*u*p,this._z=h*u*p-l*d*c,this._w=h*u*c+l*d*p;break;case\\\\\\\"YZX\\\\\\\":this._x=l*u*c+h*d*p,this._y=h*d*c+l*u*p,this._z=h*u*p-l*d*c,this._w=h*u*c-l*d*p;break;case\\\\\\\"XZY\\\\\\\":this._x=l*u*c-h*d*p,this._y=h*d*c-l*u*p,this._z=h*u*p+l*d*c,this._w=h*u*c+l*d*p;break;default:console.warn(\\\\\\\"THREE.Quaternion: .setFromEuler() encountered an unknown order: \\\\\\\"+n)}return!1!==e&&this._onChangeCallback(),this}setFromAxisAngle(t,e){const s=e/2,i=Math.sin(s);return this._x=t.x*i,this._y=t.y*i,this._z=t.z*i,this._w=Math.cos(s),this._onChangeCallback(),this}setFromRotationMatrix(t){const e=t.elements,s=e[0],i=e[4],r=e[8],n=e[1],a=e[5],o=e[9],h=e[2],u=e[6],c=e[10],l=s+a+c;if(l>0){const t=.5/Math.sqrt(l+1);this._w=.25/t,this._x=(u-o)*t,this._y=(r-h)*t,this._z=(n-i)*t}else if(s>a&&s>c){const t=2*Math.sqrt(1+s-a-c);this._w=(u-o)/t,this._x=.25*t,this._y=(i+n)/t,this._z=(r+h)/t}else if(a>c){const t=2*Math.sqrt(1+a-s-c);this._w=(r-h)/t,this._x=(i+n)/t,this._y=.25*t,this._z=(o+u)/t}else{const t=2*Math.sqrt(1+c-s-a);this._w=(n-i)/t,this._x=(r+h)/t,this._y=(o+u)/t,this._z=.25*t}return this._onChangeCallback(),this}setFromUnitVectors(t,e){let s=t.dot(e)+1;return sMath.abs(t.z)?(this._x=-t.y,this._y=t.x,this._z=0,this._w=s):(this._x=0,this._y=-t.z,this._z=t.y,this._w=s)):(this._x=t.y*e.z-t.z*e.y,this._y=t.z*e.x-t.x*e.z,this._z=t.x*e.y-t.y*e.x,this._w=s),this.normalize()}angleTo(t){return 2*Math.acos(Math.abs(i.d(this.dot(t),-1,1)))}rotateTowards(t,e){const s=this.angleTo(t);if(0===s)return this;const i=Math.min(1,e/s);return this.slerp(t,i),this}identity(){return this.set(0,0,0,1)}invert(){return this.conjugate()}conjugate(){return this._x*=-1,this._y*=-1,this._z*=-1,this._onChangeCallback(),this}dot(t){return this._x*t._x+this._y*t._y+this._z*t._z+this._w*t._w}lengthSq(){return this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w}length(){return Math.sqrt(this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w)}normalize(){let t=this.length();return 0===t?(this._x=0,this._y=0,this._z=0,this._w=1):(t=1/t,this._x=this._x*t,this._y=this._y*t,this._z=this._z*t,this._w=this._w*t),this._onChangeCallback(),this}multiply(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Quaternion: .multiply() now only accepts one argument. Use .multiplyQuaternions( a, b ) instead.\\\\\\\"),this.multiplyQuaternions(t,e)):this.multiplyQuaternions(this,t)}premultiply(t){return this.multiplyQuaternions(t,this)}multiplyQuaternions(t,e){const s=t._x,i=t._y,r=t._z,n=t._w,a=e._x,o=e._y,h=e._z,u=e._w;return this._x=s*u+n*a+i*h-r*o,this._y=i*u+n*o+r*a-s*h,this._z=r*u+n*h+s*o-i*a,this._w=n*u-s*a-i*o-r*h,this._onChangeCallback(),this}slerp(t,e){if(0===e)return this;if(1===e)return this.copy(t);const s=this._x,i=this._y,r=this._z,n=this._w;let a=n*t._w+s*t._x+i*t._y+r*t._z;if(a<0?(this._w=-t._w,this._x=-t._x,this._y=-t._y,this._z=-t._z,a=-a):this.copy(t),a>=1)return this._w=n,this._x=s,this._y=i,this._z=r,this;const o=1-a*a;if(o<=Number.EPSILON){const t=1-e;return this._w=t*n+e*this._w,this._x=t*s+e*this._x,this._y=t*i+e*this._y,this._z=t*r+e*this._z,this.normalize(),this._onChangeCallback(),this}const h=Math.sqrt(o),u=Math.atan2(h,a),c=Math.sin((1-e)*u)/h,l=Math.sin(e*u)/h;return this._w=n*c+this._w*l,this._x=s*c+this._x*l,this._y=i*c+this._y*l,this._z=r*c+this._z*l,this._onChangeCallback(),this}slerpQuaternions(t,e,s){this.copy(t).slerp(e,s)}random(){const t=Math.random(),e=Math.sqrt(1-t),s=Math.sqrt(t),i=2*Math.PI*Math.random(),r=2*Math.PI*Math.random();return this.set(e*Math.cos(i),s*Math.sin(r),s*Math.cos(r),e*Math.sin(i))}equals(t){return t._x===this._x&&t._y===this._y&&t._z===this._z&&t._w===this._w}fromArray(t,e=0){return this._x=t[e],this._y=t[e+1],this._z=t[e+2],this._w=t[e+3],this._onChangeCallback(),this}toArray(t=[],e=0){return t[e]=this._x,t[e+1]=this._y,t[e+2]=this._z,t[e+3]=this._w,t}fromBufferAttribute(t,e){return this._x=t.getX(e),this._y=t.getY(e),this._z=t.getZ(e),this._w=t.getW(e),this}_onChange(t){return this._onChangeCallback=t,this}_onChangeCallback(){}}r.prototype.isQuaternion=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return i}));class i{constructor(t=0,e=0,s=0,i=1){this.x=t,this.y=e,this.z=s,this.w=i}get width(){return this.z}set width(t){this.z=t}get height(){return this.w}set height(t){this.w=t}set(t,e,s,i){return this.x=t,this.y=e,this.z=s,this.w=i,this}setScalar(t){return this.x=t,this.y=t,this.z=t,this.w=t,this}setX(t){return this.x=t,this}setY(t){return this.y=t,this}setZ(t){return this.z=t,this}setW(t){return this.w=t,this}setComponent(t,e){switch(t){case 0:this.x=e;break;case 1:this.y=e;break;case 2:this.z=e;break;case 3:this.w=e;break;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}return this}getComponent(t){switch(t){case 0:return this.x;case 1:return this.y;case 2:return this.z;case 3:return this.w;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}}clone(){return new this.constructor(this.x,this.y,this.z,this.w)}copy(t){return this.x=t.x,this.y=t.y,this.z=t.z,this.w=void 0!==t.w?t.w:1,this}add(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector4: .add() now only accepts one argument. Use .addVectors( a, b ) instead.\\\\\\\"),this.addVectors(t,e)):(this.x+=t.x,this.y+=t.y,this.z+=t.z,this.w+=t.w,this)}addScalar(t){return this.x+=t,this.y+=t,this.z+=t,this.w+=t,this}addVectors(t,e){return this.x=t.x+e.x,this.y=t.y+e.y,this.z=t.z+e.z,this.w=t.w+e.w,this}addScaledVector(t,e){return this.x+=t.x*e,this.y+=t.y*e,this.z+=t.z*e,this.w+=t.w*e,this}sub(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector4: .sub() now only accepts one argument. Use .subVectors( a, b ) instead.\\\\\\\"),this.subVectors(t,e)):(this.x-=t.x,this.y-=t.y,this.z-=t.z,this.w-=t.w,this)}subScalar(t){return this.x-=t,this.y-=t,this.z-=t,this.w-=t,this}subVectors(t,e){return this.x=t.x-e.x,this.y=t.y-e.y,this.z=t.z-e.z,this.w=t.w-e.w,this}multiply(t){return this.x*=t.x,this.y*=t.y,this.z*=t.z,this.w*=t.w,this}multiplyScalar(t){return this.x*=t,this.y*=t,this.z*=t,this.w*=t,this}applyMatrix4(t){const e=this.x,s=this.y,i=this.z,r=this.w,n=t.elements;return this.x=n[0]*e+n[4]*s+n[8]*i+n[12]*r,this.y=n[1]*e+n[5]*s+n[9]*i+n[13]*r,this.z=n[2]*e+n[6]*s+n[10]*i+n[14]*r,this.w=n[3]*e+n[7]*s+n[11]*i+n[15]*r,this}divideScalar(t){return this.multiplyScalar(1/t)}setAxisAngleFromQuaternion(t){this.w=2*Math.acos(t.w);const e=Math.sqrt(1-t.w*t.w);return e<1e-4?(this.x=1,this.y=0,this.z=0):(this.x=t.x/e,this.y=t.y/e,this.z=t.z/e),this}setAxisAngleFromRotationMatrix(t){let e,s,i,r;const n=.01,a=.1,o=t.elements,h=o[0],u=o[4],c=o[8],l=o[1],d=o[5],p=o[9],m=o[2],f=o[6],y=o[10];if(Math.abs(u-l)o&&t>g?tg?o1){for(let t=0;t1){for(let t=0;t0){i.children=[];for(let e=0;e0){i.animations=[];for(let e=0;e0&&(s.geometries=e),i.length>0&&(s.materials=i),r.length>0&&(s.textures=r),a.length>0&&(s.images=a),o.length>0&&(s.shapes=o),h.length>0&&(s.skeletons=h),u.length>0&&(s.animations=u)}return s.object=i,s;function n(t){const e=[];for(const s in t){const i=t[s];delete i.metadata,e.push(i)}return e}}clone(t){return(new this.constructor).copy(this,t)}copy(t,e=!0){if(this.name=t.name,this.up.copy(t.up),this.position.copy(t.position),this.rotation.order=t.rotation.order,this.quaternion.copy(t.quaternion),this.scale.copy(t.scale),this.matrix.copy(t.matrix),this.matrixWorld.copy(t.matrixWorld),this.matrixAutoUpdate=t.matrixAutoUpdate,this.matrixWorldNeedsUpdate=t.matrixWorldNeedsUpdate,this.layers.mask=t.layers.mask,this.visible=t.visible,this.castShadow=t.castShadow,this.receiveShadow=t.receiveShadow,this.frustumCulled=t.frustumCulled,this.renderOrder=t.renderOrder,this.userData=JSON.parse(JSON.stringify(t.userData)),!0===e)for(let e=0;e0&&console.error(\\\\\\\"THREE.Matrix3: the constructor no longer reads arguments. use .set() instead.\\\\\\\")}set(t,e,s,i,r,n,a,o,h){const u=this.elements;return u[0]=t,u[1]=i,u[2]=a,u[3]=e,u[4]=r,u[5]=o,u[6]=s,u[7]=n,u[8]=h,this}identity(){return this.set(1,0,0,0,1,0,0,0,1),this}copy(t){const e=this.elements,s=t.elements;return e[0]=s[0],e[1]=s[1],e[2]=s[2],e[3]=s[3],e[4]=s[4],e[5]=s[5],e[6]=s[6],e[7]=s[7],e[8]=s[8],this}extractBasis(t,e,s){return t.setFromMatrix3Column(this,0),e.setFromMatrix3Column(this,1),s.setFromMatrix3Column(this,2),this}setFromMatrix4(t){const e=t.elements;return this.set(e[0],e[4],e[8],e[1],e[5],e[9],e[2],e[6],e[10]),this}multiply(t){return this.multiplyMatrices(this,t)}premultiply(t){return this.multiplyMatrices(t,this)}multiplyMatrices(t,e){const s=t.elements,i=e.elements,r=this.elements,n=s[0],a=s[3],o=s[6],h=s[1],u=s[4],c=s[7],l=s[2],d=s[5],p=s[8],m=i[0],f=i[3],y=i[6],g=i[1],x=i[4],b=i[7],M=i[2],w=i[5],v=i[8];return r[0]=n*m+a*g+o*M,r[3]=n*f+a*x+o*w,r[6]=n*y+a*b+o*v,r[1]=h*m+u*g+c*M,r[4]=h*f+u*x+c*w,r[7]=h*y+u*b+c*v,r[2]=l*m+d*g+p*M,r[5]=l*f+d*x+p*w,r[8]=l*y+d*b+p*v,this}multiplyScalar(t){const e=this.elements;return e[0]*=t,e[3]*=t,e[6]*=t,e[1]*=t,e[4]*=t,e[7]*=t,e[2]*=t,e[5]*=t,e[8]*=t,this}determinant(){const t=this.elements,e=t[0],s=t[1],i=t[2],r=t[3],n=t[4],a=t[5],o=t[6],h=t[7],u=t[8];return e*n*u-e*a*h-s*r*u+s*a*o+i*r*h-i*n*o}invert(){const t=this.elements,e=t[0],s=t[1],i=t[2],r=t[3],n=t[4],a=t[5],o=t[6],h=t[7],u=t[8],c=u*n-a*h,l=a*o-u*r,d=h*r-n*o,p=e*c+s*l+i*d;if(0===p)return this.set(0,0,0,0,0,0,0,0,0);const m=1/p;return t[0]=c*m,t[1]=(i*h-u*s)*m,t[2]=(a*s-i*n)*m,t[3]=l*m,t[4]=(u*e-i*o)*m,t[5]=(i*r-a*e)*m,t[6]=d*m,t[7]=(s*o-h*e)*m,t[8]=(n*e-s*r)*m,this}transpose(){let t;const e=this.elements;return t=e[1],e[1]=e[3],e[3]=t,t=e[2],e[2]=e[6],e[6]=t,t=e[5],e[5]=e[7],e[7]=t,this}getNormalMatrix(t){return this.setFromMatrix4(t).invert().transpose()}transposeIntoArray(t){const e=this.elements;return t[0]=e[0],t[1]=e[3],t[2]=e[6],t[3]=e[1],t[4]=e[4],t[5]=e[7],t[6]=e[2],t[7]=e[5],t[8]=e[8],this}setUvTransform(t,e,s,i,r,n,a){const o=Math.cos(r),h=Math.sin(r);return this.set(s*o,s*h,-s*(o*n+h*a)+n+t,-i*h,i*o,-i*(-h*n+o*a)+a+e,0,0,1),this}scale(t,e){const s=this.elements;return s[0]*=t,s[3]*=t,s[6]*=t,s[1]*=e,s[4]*=e,s[7]*=e,this}rotate(t){const e=Math.cos(t),s=Math.sin(t),i=this.elements,r=i[0],n=i[3],a=i[6],o=i[1],h=i[4],u=i[7];return i[0]=e*r+s*o,i[3]=e*n+s*h,i[6]=e*a+s*u,i[1]=-s*r+e*o,i[4]=-s*n+e*h,i[7]=-s*a+e*u,this}translate(t,e){const s=this.elements;return s[0]+=t*s[2],s[3]+=t*s[5],s[6]+=t*s[8],s[1]+=e*s[2],s[4]+=e*s[5],s[7]+=e*s[8],this}equals(t){const e=this.elements,s=t.elements;for(let t=0;t<9;t++)if(e[t]!==s[t])return!1;return!0}fromArray(t,e=0){for(let s=0;s<9;s++)this.elements[s]=t[s+e];return this}toArray(t=[],e=0){const s=this.elements;return t[e]=s[0],t[e+1]=s[1],t[e+2]=s[2],t[e+3]=s[3],t[e+4]=s[4],t[e+5]=s[5],t[e+6]=s[6],t[e+7]=s[7],t[e+8]=s[8],t}clone(){return(new this.constructor).fromArray(this.elements)}}i.prototype.isMatrix3=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return o}));var i=s(15),r=s(1),n=s(3);let a=0;class o extends i.a{constructor(){super(),Object.defineProperty(this,\\\\\\\"id\\\\\\\",{value:a++}),this.uuid=n.h(),this.name=\\\\\\\"\\\\\\\",this.type=\\\\\\\"Material\\\\\\\",this.fog=!0,this.blending=r.xb,this.side=r.H,this.vertexColors=!1,this.opacity=1,this.format=r.Ib,this.transparent=!1,this.blendSrc=r.Nc,this.blendDst=r.Db,this.blendEquation=r.b,this.blendSrcAlpha=null,this.blendDstAlpha=null,this.blendEquationAlpha=null,this.depthFunc=r.T,this.depthTest=!0,this.depthWrite=!0,this.stencilWriteMask=255,this.stencilFunc=r.h,this.stencilRef=0,this.stencilFuncMask=255,this.stencilFail=r.R,this.stencilZFail=r.R,this.stencilZPass=r.R,this.stencilWrite=!1,this.clippingPlanes=null,this.clipIntersection=!1,this.clipShadows=!1,this.shadowSide=null,this.colorWrite=!0,this.precision=null,this.polygonOffset=!1,this.polygonOffsetFactor=0,this.polygonOffsetUnits=0,this.dithering=!1,this.alphaToCoverage=!1,this.premultipliedAlpha=!1,this.visible=!0,this.toneMapped=!0,this.userData={},this.version=0,this._alphaTest=0}get alphaTest(){return this._alphaTest}set alphaTest(t){this._alphaTest>0!=t>0&&this.version++,this._alphaTest=t}onBuild(){}onBeforeRender(){}onBeforeCompile(){}customProgramCacheKey(){return this.onBeforeCompile.toString()}setValues(t){if(void 0!==t)for(const e in t){const s=t[e];if(void 0===s){console.warn(\\\\\\\"THREE.Material: '\\\\\\\"+e+\\\\\\\"' parameter is undefined.\\\\\\\");continue}if(\\\\\\\"shading\\\\\\\"===e){console.warn(\\\\\\\"THREE.\\\\\\\"+this.type+\\\\\\\": .shading has been removed. Use the boolean .flatShading instead.\\\\\\\"),this.flatShading=s===r.F;continue}const i=this[e];void 0!==i?i&&i.isColor?i.set(s):i&&i.isVector3&&s&&s.isVector3?i.copy(s):this[e]=s:console.warn(\\\\\\\"THREE.\\\\\\\"+this.type+\\\\\\\": '\\\\\\\"+e+\\\\\\\"' is not a property of this material.\\\\\\\")}}toJSON(t){const e=void 0===t||\\\\\\\"string\\\\\\\"==typeof t;e&&(t={textures:{},images:{}});const s={metadata:{version:4.5,type:\\\\\\\"Material\\\\\\\",generator:\\\\\\\"Material.toJSON\\\\\\\"}};function i(t){const e=[];for(const s in t){const i=t[s];delete i.metadata,e.push(i)}return e}if(s.uuid=this.uuid,s.type=this.type,\\\\\\\"\\\\\\\"!==this.name&&(s.name=this.name),this.color&&this.color.isColor&&(s.color=this.color.getHex()),void 0!==this.roughness&&(s.roughness=this.roughness),void 0!==this.metalness&&(s.metalness=this.metalness),void 0!==this.sheen&&(s.sheen=this.sheen),this.sheenTint&&this.sheenTint.isColor&&(s.sheenTint=this.sheenTint.getHex()),void 0!==this.sheenRoughness&&(s.sheenRoughness=this.sheenRoughness),this.emissive&&this.emissive.isColor&&(s.emissive=this.emissive.getHex()),this.emissiveIntensity&&1!==this.emissiveIntensity&&(s.emissiveIntensity=this.emissiveIntensity),this.specular&&this.specular.isColor&&(s.specular=this.specular.getHex()),void 0!==this.specularIntensity&&(s.specularIntensity=this.specularIntensity),this.specularTint&&this.specularTint.isColor&&(s.specularTint=this.specularTint.getHex()),void 0!==this.shininess&&(s.shininess=this.shininess),void 0!==this.clearcoat&&(s.clearcoat=this.clearcoat),void 0!==this.clearcoatRoughness&&(s.clearcoatRoughness=this.clearcoatRoughness),this.clearcoatMap&&this.clearcoatMap.isTexture&&(s.clearcoatMap=this.clearcoatMap.toJSON(t).uuid),this.clearcoatRoughnessMap&&this.clearcoatRoughnessMap.isTexture&&(s.clearcoatRoughnessMap=this.clearcoatRoughnessMap.toJSON(t).uuid),this.clearcoatNormalMap&&this.clearcoatNormalMap.isTexture&&(s.clearcoatNormalMap=this.clearcoatNormalMap.toJSON(t).uuid,s.clearcoatNormalScale=this.clearcoatNormalScale.toArray()),this.map&&this.map.isTexture&&(s.map=this.map.toJSON(t).uuid),this.matcap&&this.matcap.isTexture&&(s.matcap=this.matcap.toJSON(t).uuid),this.alphaMap&&this.alphaMap.isTexture&&(s.alphaMap=this.alphaMap.toJSON(t).uuid),this.lightMap&&this.lightMap.isTexture&&(s.lightMap=this.lightMap.toJSON(t).uuid,s.lightMapIntensity=this.lightMapIntensity),this.aoMap&&this.aoMap.isTexture&&(s.aoMap=this.aoMap.toJSON(t).uuid,s.aoMapIntensity=this.aoMapIntensity),this.bumpMap&&this.bumpMap.isTexture&&(s.bumpMap=this.bumpMap.toJSON(t).uuid,s.bumpScale=this.bumpScale),this.normalMap&&this.normalMap.isTexture&&(s.normalMap=this.normalMap.toJSON(t).uuid,s.normalMapType=this.normalMapType,s.normalScale=this.normalScale.toArray()),this.displacementMap&&this.displacementMap.isTexture&&(s.displacementMap=this.displacementMap.toJSON(t).uuid,s.displacementScale=this.displacementScale,s.displacementBias=this.displacementBias),this.roughnessMap&&this.roughnessMap.isTexture&&(s.roughnessMap=this.roughnessMap.toJSON(t).uuid),this.metalnessMap&&this.metalnessMap.isTexture&&(s.metalnessMap=this.metalnessMap.toJSON(t).uuid),this.emissiveMap&&this.emissiveMap.isTexture&&(s.emissiveMap=this.emissiveMap.toJSON(t).uuid),this.specularMap&&this.specularMap.isTexture&&(s.specularMap=this.specularMap.toJSON(t).uuid),this.specularIntensityMap&&this.specularIntensityMap.isTexture&&(s.specularIntensityMap=this.specularIntensityMap.toJSON(t).uuid),this.specularTintMap&&this.specularTintMap.isTexture&&(s.specularTintMap=this.specularTintMap.toJSON(t).uuid),this.envMap&&this.envMap.isTexture&&(s.envMap=this.envMap.toJSON(t).uuid,void 0!==this.combine&&(s.combine=this.combine)),void 0!==this.envMapIntensity&&(s.envMapIntensity=this.envMapIntensity),void 0!==this.reflectivity&&(s.reflectivity=this.reflectivity),void 0!==this.refractionRatio&&(s.refractionRatio=this.refractionRatio),this.gradientMap&&this.gradientMap.isTexture&&(s.gradientMap=this.gradientMap.toJSON(t).uuid),void 0!==this.transmission&&(s.transmission=this.transmission),this.transmissionMap&&this.transmissionMap.isTexture&&(s.transmissionMap=this.transmissionMap.toJSON(t).uuid),void 0!==this.thickness&&(s.thickness=this.thickness),this.thicknessMap&&this.thicknessMap.isTexture&&(s.thicknessMap=this.thicknessMap.toJSON(t).uuid),void 0!==this.attenuationDistance&&(s.attenuationDistance=this.attenuationDistance),void 0!==this.attenuationTint&&(s.attenuationTint=this.attenuationTint.getHex()),void 0!==this.size&&(s.size=this.size),null!==this.shadowSide&&(s.shadowSide=this.shadowSide),void 0!==this.sizeAttenuation&&(s.sizeAttenuation=this.sizeAttenuation),this.blending!==r.xb&&(s.blending=this.blending),this.side!==r.H&&(s.side=this.side),this.vertexColors&&(s.vertexColors=!0),this.opacity<1&&(s.opacity=this.opacity),this.format!==r.Ib&&(s.format=this.format),!0===this.transparent&&(s.transparent=this.transparent),s.depthFunc=this.depthFunc,s.depthTest=this.depthTest,s.depthWrite=this.depthWrite,s.colorWrite=this.colorWrite,s.stencilWrite=this.stencilWrite,s.stencilWriteMask=this.stencilWriteMask,s.stencilFunc=this.stencilFunc,s.stencilRef=this.stencilRef,s.stencilFuncMask=this.stencilFuncMask,s.stencilFail=this.stencilFail,s.stencilZFail=this.stencilZFail,s.stencilZPass=this.stencilZPass,this.rotation&&0!==this.rotation&&(s.rotation=this.rotation),!0===this.polygonOffset&&(s.polygonOffset=!0),0!==this.polygonOffsetFactor&&(s.polygonOffsetFactor=this.polygonOffsetFactor),0!==this.polygonOffsetUnits&&(s.polygonOffsetUnits=this.polygonOffsetUnits),this.linewidth&&1!==this.linewidth&&(s.linewidth=this.linewidth),void 0!==this.dashSize&&(s.dashSize=this.dashSize),void 0!==this.gapSize&&(s.gapSize=this.gapSize),void 0!==this.scale&&(s.scale=this.scale),!0===this.dithering&&(s.dithering=!0),this.alphaTest>0&&(s.alphaTest=this.alphaTest),!0===this.alphaToCoverage&&(s.alphaToCoverage=this.alphaToCoverage),!0===this.premultipliedAlpha&&(s.premultipliedAlpha=this.premultipliedAlpha),!0===this.wireframe&&(s.wireframe=this.wireframe),this.wireframeLinewidth>1&&(s.wireframeLinewidth=this.wireframeLinewidth),\\\\\\\"round\\\\\\\"!==this.wireframeLinecap&&(s.wireframeLinecap=this.wireframeLinecap),\\\\\\\"round\\\\\\\"!==this.wireframeLinejoin&&(s.wireframeLinejoin=this.wireframeLinejoin),!0===this.flatShading&&(s.flatShading=this.flatShading),!1===this.visible&&(s.visible=!1),!1===this.toneMapped&&(s.toneMapped=!1),\\\\\\\"{}\\\\\\\"!==JSON.stringify(this.userData)&&(s.userData=this.userData),e){const e=i(t.textures),r=i(t.images);e.length>0&&(s.textures=e),r.length>0&&(s.images=r)}return s}clone(){return(new this.constructor).copy(this)}copy(t){this.name=t.name,this.fog=t.fog,this.blending=t.blending,this.side=t.side,this.vertexColors=t.vertexColors,this.opacity=t.opacity,this.format=t.format,this.transparent=t.transparent,this.blendSrc=t.blendSrc,this.blendDst=t.blendDst,this.blendEquation=t.blendEquation,this.blendSrcAlpha=t.blendSrcAlpha,this.blendDstAlpha=t.blendDstAlpha,this.blendEquationAlpha=t.blendEquationAlpha,this.depthFunc=t.depthFunc,this.depthTest=t.depthTest,this.depthWrite=t.depthWrite,this.stencilWriteMask=t.stencilWriteMask,this.stencilFunc=t.stencilFunc,this.stencilRef=t.stencilRef,this.stencilFuncMask=t.stencilFuncMask,this.stencilFail=t.stencilFail,this.stencilZFail=t.stencilZFail,this.stencilZPass=t.stencilZPass,this.stencilWrite=t.stencilWrite;const e=t.clippingPlanes;let s=null;if(null!==e){const t=e.length;s=new Array(t);for(let i=0;i!==t;++i)s[i]=e[i].clone()}return this.clippingPlanes=s,this.clipIntersection=t.clipIntersection,this.clipShadows=t.clipShadows,this.shadowSide=t.shadowSide,this.colorWrite=t.colorWrite,this.precision=t.precision,this.polygonOffset=t.polygonOffset,this.polygonOffsetFactor=t.polygonOffsetFactor,this.polygonOffsetUnits=t.polygonOffsetUnits,this.dithering=t.dithering,this.alphaTest=t.alphaTest,this.alphaToCoverage=t.alphaToCoverage,this.premultipliedAlpha=t.premultipliedAlpha,this.visible=t.visible,this.toneMapped=t.toneMapped,this.userData=JSON.parse(JSON.stringify(t.userData)),this}dispose(){this.dispatchEvent({type:\\\\\\\"dispose\\\\\\\"})}set needsUpdate(t){!0===t&&this.version++}}o.prototype.isMaterial=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return r}));var i=s(28);class r{constructor(t){this.manager=void 0!==t?t:i.a,this.crossOrigin=\\\\\\\"anonymous\\\\\\\",this.withCredentials=!1,this.path=\\\\\\\"\\\\\\\",this.resourcePath=\\\\\\\"\\\\\\\",this.requestHeader={}}load(){}loadAsync(t,e){const s=this;return new Promise((function(i,r){s.load(t,i,e,r)}))}parse(){}setCrossOrigin(t){return this.crossOrigin=t,this}setWithCredentials(t){return this.withCredentials=t,this}setPath(t){return this.path=t,this}setResourcePath(t){return this.resourcePath=t,this}setRequestHeader(t){return this.requestHeader=t,this}}},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return I}));var i=s(0),r=s(2),n=s(18),a=s(39),o=s(5),h=s(10),u=s(40),c=s(1),l=s(29),d=s(7);const p=new o.a,m=new a.a,f=new n.a,y=new i.a,g=new i.a,x=new i.a,b=new i.a,M=new i.a,w=new i.a,v=new i.a,_=new i.a,T=new i.a,S=new r.a,A=new r.a,E=new r.a,z=new i.a,R=new i.a;class I extends h.a{constructor(t=new d.a,e=new l.a){super(),this.type=\\\\\\\"Mesh\\\\\\\",this.geometry=t,this.material=e,this.updateMorphTargets()}copy(t){return super.copy(t),void 0!==t.morphTargetInfluences&&(this.morphTargetInfluences=t.morphTargetInfluences.slice()),void 0!==t.morphTargetDictionary&&(this.morphTargetDictionary=Object.assign({},t.morphTargetDictionary)),this.material=t.material,this.geometry=t.geometry,this}updateMorphTargets(){const t=this.geometry;if(t.isBufferGeometry){const e=t.morphAttributes,s=Object.keys(e);if(s.length>0){const t=e[s[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,s=t.length;e0&&console.error(\\\\\\\"THREE.Mesh.updateMorphTargets() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}}raycast(t,e){const s=this.geometry,i=this.material,r=this.matrixWorld;if(void 0===i)return;if(null===s.boundingSphere&&s.computeBoundingSphere(),f.copy(s.boundingSphere),f.applyMatrix4(r),!1===t.ray.intersectsSphere(f))return;if(p.copy(r).invert(),m.copy(t.ray).applyMatrix4(p),null!==s.boundingBox&&!1===m.intersectsBox(s.boundingBox))return;let n;if(s.isBufferGeometry){const r=s.index,a=s.attributes.position,o=s.morphAttributes.position,h=s.morphTargetsRelative,u=s.attributes.uv,c=s.attributes.uv2,l=s.groups,d=s.drawRange;if(null!==r)if(Array.isArray(i))for(let s=0,p=l.length;ss.far?null:{distance:u,point:R.clone(),object:t}}(t,e,s,n,y,g,x,z);if(k){l&&(S.fromBufferAttribute(l,p),A.fromBufferAttribute(l,m),E.fromBufferAttribute(l,f),k.uv=u.a.getUV(z,y,g,x,S,A,E,new r.a)),d&&(S.fromBufferAttribute(d,p),A.fromBufferAttribute(d,m),E.fromBufferAttribute(d,f),k.uv2=u.a.getUV(z,y,g,x,S,A,E,new r.a));const t={a:p,b:m,c:f,normal:new 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i=t.elements,r=i[0],n=i[4],o=i[8],h=i[1],u=i[5],c=i[9],l=i[2],d=i[6],p=i[10];switch(e){case\\\\\\\"XYZ\\\\\\\":this._y=Math.asin(Object(a.d)(o,-1,1)),Math.abs(o)<.9999999?(this._x=Math.atan2(-c,p),this._z=Math.atan2(-n,r)):(this._x=Math.atan2(d,u),this._z=0);break;case\\\\\\\"YXZ\\\\\\\":this._x=Math.asin(-Object(a.d)(c,-1,1)),Math.abs(c)<.9999999?(this._y=Math.atan2(o,p),this._z=Math.atan2(h,u)):(this._y=Math.atan2(-l,r),this._z=0);break;case\\\\\\\"ZXY\\\\\\\":this._x=Math.asin(Object(a.d)(d,-1,1)),Math.abs(d)<.9999999?(this._y=Math.atan2(-l,p),this._z=Math.atan2(-n,u)):(this._y=0,this._z=Math.atan2(h,r));break;case\\\\\\\"ZYX\\\\\\\":this._y=Math.asin(-Object(a.d)(l,-1,1)),Math.abs(l)<.9999999?(this._x=Math.atan2(d,p),this._z=Math.atan2(h,r)):(this._x=0,this._z=Math.atan2(-n,u));break;case\\\\\\\"YZX\\\\\\\":this._z=Math.asin(Object(a.d)(h,-1,1)),Math.abs(h)<.9999999?(this._x=Math.atan2(-c,u),this._y=Math.atan2(-l,r)):(this._x=0,this._y=Math.atan2(o,p));break;case\\\\\\\"XZY\\\\\\\":this._z=Math.asin(-Object(a.d)(n,-1,1)),Math.abs(n)<.9999999?(this._x=Math.atan2(d,u),this._y=Math.atan2(o,r)):(this._x=Math.atan2(-c,p),this._y=0);break;default:console.warn(\\\\\\\"THREE.Euler: 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this._onChangeCallback=t,this}_onChangeCallback(){}}u.prototype.isEuler=!0,u.DefaultOrder=\\\\\\\"XYZ\\\\\\\",u.RotationOrders=[\\\\\\\"XYZ\\\\\\\",\\\\\\\"YZX\\\\\\\",\\\\\\\"ZXY\\\\\\\",\\\\\\\"XZY\\\\\\\",\\\\\\\"YXZ\\\\\\\",\\\\\\\"ZYX\\\\\\\"]},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return r})),s.d(e,\\\\\\\"b\\\\\\\",(function(){return i}));class i{constructor(t,e,s){const i=this;let r,n=!1,a=0,o=0;const h=[];this.onStart=void 0,this.onLoad=t,this.onProgress=e,this.onError=s,this.itemStart=function(t){o++,!1===n&&void 0!==i.onStart&&i.onStart(t,a,o),n=!0},this.itemEnd=function(t){a++,void 0!==i.onProgress&&i.onProgress(t,a,o),a===o&&(n=!1,void 0!==i.onLoad&&i.onLoad())},this.itemError=function(t){void 0!==i.onError&&i.onError(t)},this.resolveURL=function(t){return r?r(t):t},this.setURLModifier=function(t){return r=t,this},this.addHandler=function(t,e){return h.push(t,e),this},this.removeHandler=function(t){const e=h.indexOf(t);return-1!==e&&h.splice(e,2),this},this.getHandler=function(t){for(let e=0,s=h.length;e1?null:e.copy(s).multiplyScalar(r).add(t.start)}intersectsLine(t){const e=this.distanceToPoint(t.start),s=this.distanceToPoint(t.end);return e<0&&s>0||s<0&&e>0}intersectsBox(t){return t.intersectsPlane(this)}intersectsSphere(t){return t.intersectsPlane(this)}coplanarPoint(t){return t.copy(this.normal).multiplyScalar(-this.constant)}applyMatrix4(t,e){const s=e||o.getNormalMatrix(t),i=this.coplanarPoint(n).applyMatrix4(t),r=this.normal.applyMatrix3(s).normalize();return this.constant=-i.dot(r),this}translate(t){return this.constant-=t.dot(this.normal),this}equals(t){return t.normal.equals(this.normal)&&t.constant===this.constant}clone(){return(new this.constructor).copy(this)}}h.prototype.isPlane=!0},,function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return n}));var i=s(10),r=s(6);class n extends i.a{constructor(t,e=1){super(),this.type=\\\\\\\"Light\\\\\\\",this.color=new r.a(t),this.intensity=e}dispose(){}copy(t){return super.copy(t),this.color.copy(t.color),this.intensity=t.intensity,this}toJSON(t){const e=super.toJSON(t);return e.object.color=this.color.getHex(),e.object.intensity=this.intensity,void 0!==this.groundColor&&(e.object.groundColor=this.groundColor.getHex()),void 0!==this.distance&&(e.object.distance=this.distance),void 0!==this.angle&&(e.object.angle=this.angle),void 0!==this.decay&&(e.object.decay=this.decay),void 0!==this.penumbra&&(e.object.penumbra=this.penumbra),void 0!==this.shadow&&(e.object.shadow=this.shadow.toJSON()),e}}n.prototype.isLight=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return n}));var i=s(23),r=s(1);class n extends i.a{constructor(t=null,e=1,s=1,i,n,a,o,h,u=r.ob,c=r.ob,l,d){super(null,a,o,h,u,c,i,n,l,d),this.image={data:t,width:e,height:s},this.magFilter=u,this.minFilter=c,this.generateMipmaps=!1,this.flipY=!1,this.unpackAlignment=1,this.needsUpdate=!0}}n.prototype.isDataTexture=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return h}));var i=s(41),r=s(0),n=s(4);const a=new r.a,o=new r.a;class h extends i.a{constructor(t,e){super(t,e),this.type=\\\\\\\"LineSegments\\\\\\\"}computeLineDistances(){const t=this.geometry;if(t.isBufferGeometry)if(null===t.index){const e=t.attributes.position,s=[];for(let t=0,i=e.count;t=r)break t;{const a=e[1];t=r)break e}n=s,s=0}}for(;s>>1;t0)if(p=h*c-u,m=h*u-c,y=r*d,p>=0)if(m>=-y)if(m<=y){const t=1/d;p*=t,m*=t,f=p*(p+h*m+2*u)+m*(h*p+m+2*c)+l}else m=r,p=Math.max(0,-(h*m+u)),f=-p*p+m*(m+2*c)+l;else m=-r,p=Math.max(0,-(h*m+u)),f=-p*p+m*(m+2*c)+l;else m<=-y?(p=Math.max(0,-(-h*r+u)),m=p>0?-r:Math.min(Math.max(-r,-c),r),f=-p*p+m*(m+2*c)+l):m<=y?(p=0,m=Math.min(Math.max(-r,-c),r),f=m*(m+2*c)+l):(p=Math.max(0,-(h*r+u)),m=p>0?r:Math.min(Math.max(-r,-c),r),f=-p*p+m*(m+2*c)+l);else m=h>0?-r:r,p=Math.max(0,-(h*m+u)),f=-p*p+m*(m+2*c)+l;return s&&s.copy(this.direction).multiplyScalar(p).add(this.origin),i&&i.copy(a).multiplyScalar(m).add(n),f}intersectSphere(t,e){r.subVectors(t.center,this.origin);const s=r.dot(this.direction),i=r.dot(r)-s*s,n=t.radius*t.radius;if(i>n)return null;const a=Math.sqrt(n-i),o=s-a,h=s+a;return o<0&&h<0?null:o<0?this.at(h,e):this.at(o,e)}intersectsSphere(t){return this.distanceSqToPoint(t.center)<=t.radius*t.radius}distanceToPlane(t){const e=t.normal.dot(this.direction);if(0===e)return 0===t.distanceToPoint(this.origin)?0:null;const s=-(this.origin.dot(t.normal)+t.constant)/e;return s>=0?s:null}intersectPlane(t,e){const s=this.distanceToPlane(t);return null===s?null:this.at(s,e)}intersectsPlane(t){const e=t.distanceToPoint(this.origin);if(0===e)return!0;return t.normal.dot(this.direction)*e<0}intersectBox(t,e){let s,i,r,n,a,o;const h=1/this.direction.x,u=1/this.direction.y,c=1/this.direction.z,l=this.origin;return h>=0?(s=(t.min.x-l.x)*h,i=(t.max.x-l.x)*h):(s=(t.max.x-l.x)*h,i=(t.min.x-l.x)*h),u>=0?(r=(t.min.y-l.y)*u,n=(t.max.y-l.y)*u):(r=(t.max.y-l.y)*u,n=(t.min.y-l.y)*u),s>n||r>i?null:((r>s||s!=s)&&(s=r),(n=0?(a=(t.min.z-l.z)*c,o=(t.max.z-l.z)*c):(a=(t.max.z-l.z)*c,o=(t.min.z-l.z)*c),s>o||a>i?null:((a>s||s!=s)&&(s=a),(o=0?s:i,e)))}intersectsBox(t){return null!==this.intersectBox(t,r)}intersectTriangle(t,e,s,i,r){h.subVectors(e,t),u.subVectors(s,t),c.crossVectors(h,u);let n,a=this.direction.dot(c);if(a>0){if(i)return null;n=1}else{if(!(a<0))return null;n=-1,a=-a}o.subVectors(this.origin,t);const l=n*this.direction.dot(u.crossVectors(o,u));if(l<0)return null;const d=n*this.direction.dot(h.cross(o));if(d<0)return null;if(l+d>a)return null;const p=-n*o.dot(c);return p<0?null:this.at(p/a,r)}applyMatrix4(t){return this.origin.applyMatrix4(t),this.direction.transformDirection(t),this}equals(t){return t.origin.equals(this.origin)&&t.direction.equals(this.direction)}clone(){return(new this.constructor).copy(this)}}},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return m}));var i=s(0);const r=new i.a,n=new i.a,a=new i.a,o=new i.a,h=new i.a,u=new i.a,c=new i.a,l=new i.a,d=new i.a,p=new i.a;class m{constructor(t=new i.a,e=new i.a,s=new i.a){this.a=t,this.b=e,this.c=s}static getNormal(t,e,s,i){i.subVectors(s,e),r.subVectors(t,e),i.cross(r);const n=i.lengthSq();return n>0?i.multiplyScalar(1/Math.sqrt(n)):i.set(0,0,0)}static getBarycoord(t,e,s,i,o){r.subVectors(i,e),n.subVectors(s,e),a.subVectors(t,e);const h=r.dot(r),u=r.dot(n),c=r.dot(a),l=n.dot(n),d=n.dot(a),p=h*l-u*u;if(0===p)return o.set(-2,-1,-1);const m=1/p,f=(l*c-u*d)*m,y=(h*d-u*c)*m;return o.set(1-f-y,y,f)}static containsPoint(t,e,s,i){return this.getBarycoord(t,e,s,i,o),o.x>=0&&o.y>=0&&o.x+o.y<=1}static getUV(t,e,s,i,r,n,a,h){return this.getBarycoord(t,e,s,i,o),h.set(0,0),h.addScaledVector(r,o.x),h.addScaledVector(n,o.y),h.addScaledVector(a,o.z),h}static isFrontFacing(t,e,s,i){return r.subVectors(s,e),n.subVectors(t,e),r.cross(n).dot(i)<0}set(t,e,s){return this.a.copy(t),this.b.copy(e),this.c.copy(s),this}setFromPointsAndIndices(t,e,s,i){return this.a.copy(t[e]),this.b.copy(t[s]),this.c.copy(t[i]),this}setFromAttributeAndIndices(t,e,s,i){return this.a.fromBufferAttribute(t,e),this.b.fromBufferAttribute(t,s),this.c.fromBufferAttribute(t,i),this}clone(){return(new this.constructor).copy(this)}copy(t){return this.a.copy(t.a),this.b.copy(t.b),this.c.copy(t.c),this}getArea(){return r.subVectors(this.c,this.b),n.subVectors(this.a,this.b),.5*r.cross(n).length()}getMidpoint(t){return t.addVectors(this.a,this.b).add(this.c).multiplyScalar(1/3)}getNormal(t){return m.getNormal(this.a,this.b,this.c,t)}getPlane(t){return t.setFromCoplanarPoints(this.a,this.b,this.c)}getBarycoord(t,e){return m.getBarycoord(t,this.a,this.b,this.c,e)}getUV(t,e,s,i,r){return m.getUV(t,this.a,this.b,this.c,e,s,i,r)}containsPoint(t){return m.containsPoint(t,this.a,this.b,this.c)}isFrontFacing(t){return m.isFrontFacing(this.a,this.b,this.c,t)}intersectsBox(t){return t.intersectsTriangle(this)}closestPointToPoint(t,e){const s=this.a,i=this.b,r=this.c;let n,a;h.subVectors(i,s),u.subVectors(r,s),l.subVectors(t,s);const o=h.dot(l),m=u.dot(l);if(o<=0&&m<=0)return e.copy(s);d.subVectors(t,i);const f=h.dot(d),y=u.dot(d);if(f>=0&&y<=f)return e.copy(i);const g=o*y-f*m;if(g<=0&&o>=0&&f<=0)return n=o/(o-f),e.copy(s).addScaledVector(h,n);p.subVectors(t,r);const x=h.dot(p),b=u.dot(p);if(b>=0&&x<=b)return e.copy(r);const M=x*m-o*b;if(M<=0&&m>=0&&b<=0)return a=m/(m-b),e.copy(s).addScaledVector(u,a);const w=f*b-x*y;if(w<=0&&y-f>=0&&x-b>=0)return c.subVectors(r,i),a=(y-f)/(y-f+(x-b)),e.copy(i).addScaledVector(c,a);const v=1/(w+M+g);return n=M*v,a=g*v,e.copy(s).addScaledVector(h,n).addScaledVector(u,a)}equals(t){return t.a.equals(this.a)&&t.b.equals(this.b)&&t.c.equals(this.c)}}},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return y}));var i=s(18),r=s(39),n=s(5),a=s(10),o=s(0),h=s(24),u=s(7),c=s(4);const l=new o.a,d=new o.a,p=new n.a,m=new r.a,f=new i.a;class y extends a.a{constructor(t=new u.a,e=new h.a){super(),this.type=\\\\\\\"Line\\\\\\\",this.geometry=t,this.material=e,this.updateMorphTargets()}copy(t){return super.copy(t),this.material=t.material,this.geometry=t.geometry,this}computeLineDistances(){const t=this.geometry;if(t.isBufferGeometry)if(null===t.index){const e=t.attributes.position,s=[0];for(let t=1,i=e.count;th)continue;d.applyMatrix4(this.matrixWorld);const o=t.ray.origin.distanceTo(d);ot.far||e.push({distance:o,point:l.clone().applyMatrix4(this.matrixWorld),index:s,face:null,faceIndex:null,object:this})}}else{for(let s=Math.max(0,n.start),i=Math.min(r.count,n.start+n.count)-1;sh)continue;d.applyMatrix4(this.matrixWorld);const i=t.ray.origin.distanceTo(d);it.far||e.push({distance:i,point:l.clone().applyMatrix4(this.matrixWorld),index:s,face:null,faceIndex:null,object:this})}}}else s.isGeometry&&console.error(\\\\\\\"THREE.Line.raycast() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}updateMorphTargets(){const t=this.geometry;if(t.isBufferGeometry){const e=t.morphAttributes,s=Object.keys(e);if(s.length>0){const t=e[s[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,s=t.length;e0&&console.error(\\\\\\\"THREE.Line.updateMorphTargets() does not support THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}}}y.prototype.isLine=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return n}));var i=s(12),r=s(6);class n extends i.a{constructor(t){super(),this.type=\\\\\\\"PointsMaterial\\\\\\\",this.color=new r.a(16777215),this.map=null,this.alphaMap=null,this.size=1,this.sizeAttenuation=!0,this.setValues(t)}copy(t){return super.copy(t),this.color.copy(t.color),this.map=t.map,this.alphaMap=t.alphaMap,this.size=t.size,this.sizeAttenuation=t.sizeAttenuation,this}}n.prototype.isPointsMaterial=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return i}));class i{static decodeText(t){if(\\\\\\\"undefined\\\\\\\"!=typeof TextDecoder)return(new TextDecoder).decode(t);let e=\\\\\\\"\\\\\\\";for(let s=0,i=t.length;s0){const t=e[s[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,s=t.length;e0&&console.error(\\\\\\\"THREE.Points.updateMorphTargets() does not support THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}}}function f(t,e,s,i,r,n,a){const h=l.distanceSqToPoint(t);if(hr.far)return;n.push({distance:u,distanceToRay:Math.sqrt(h),point:s,index:e,face:null,object:a})}}m.prototype.isPoints=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return r}));var i=s(26);class r extends i.a{}r.prototype.ValueTypeName=\\\\\\\"number\\\\\\\"},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return r}));var i=s(26);class r extends i.a{}r.prototype.ValueTypeName=\\\\\\\"vector\\\\\\\"},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return r}));var i=s(10);class r extends i.a{constructor(){super(),this.type=\\\\\\\"Bone\\\\\\\"}}r.prototype.isBone=!0},,function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return h}));var i=s(1),r=s(26),n=s(38),a=s(8);class o extends n.a{constructor(t,e,s,i){super(t,e,s,i)}interpolate_(t,e,s,i){const r=this.resultBuffer,n=this.sampleValues,o=this.valueSize,h=(s-e)/(i-e);let u=t*o;for(let t=u+o;u!==t;u+=4)a.a.slerpFlat(r,0,n,u-o,n,u,h);return r}}class h extends r.a{InterpolantFactoryMethodLinear(t){return new o(this.times,this.values,this.getValueSize(),t)}}h.prototype.ValueTypeName=\\\\\\\"quaternion\\\\\\\",h.prototype.DefaultInterpolation=i.P,h.prototype.InterpolantFactoryMethodSmooth=void 0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return o}));var i=s(1),r=s(12),n=s(2),a=s(6);class o extends r.a{constructor(t){super(),this.defines={STANDARD:\\\\\\\"\\\\\\\"},this.type=\\\\\\\"MeshStandardMaterial\\\\\\\",this.color=new a.a(16777215),this.roughness=1,this.metalness=0,this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new a.a(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=i.Uc,this.normalScale=new n.a(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.roughnessMap=null,this.metalnessMap=null,this.alphaMap=null,this.envMap=null,this.envMapIntensity=1,this.refractionRatio=.98,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap=\\\\\\\"round\\\\\\\",this.wireframeLinejoin=\\\\\\\"round\\\\\\\",this.flatShading=!1,this.setValues(t)}copy(t){return super.copy(t),this.defines={STANDARD:\\\\\\\"\\\\\\\"},this.color.copy(t.color),this.roughness=t.roughness,this.metalness=t.metalness,this.map=t.map,this.lightMap=t.lightMap,this.lightMapIntensity=t.lightMapIntensity,this.aoMap=t.aoMap,this.aoMapIntensity=t.aoMapIntensity,this.emissive.copy(t.emissive),this.emissiveMap=t.emissiveMap,this.emissiveIntensity=t.emissiveIntensity,this.bumpMap=t.bumpMap,this.bumpScale=t.bumpScale,this.normalMap=t.normalMap,this.normalMapType=t.normalMapType,this.normalScale.copy(t.normalScale),this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this.roughnessMap=t.roughnessMap,this.metalnessMap=t.metalnessMap,this.alphaMap=t.alphaMap,this.envMap=t.envMap,this.envMapIntensity=t.envMapIntensity,this.refractionRatio=t.refractionRatio,this.wireframe=t.wireframe,this.wireframeLinewidth=t.wireframeLinewidth,this.wireframeLinecap=t.wireframeLinecap,this.wireframeLinejoin=t.wireframeLinejoin,this.flatShading=t.flatShading,this}}o.prototype.isMeshStandardMaterial=!0},,,function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return m}));var i=s(33),r=s(45),n=s(30),a=s(5),o=s(2),h=s(0),u=s(9);const c=new a.a,l=new h.a,d=new h.a;class p extends r.a{constructor(){super(new n.a(90,1,.5,500)),this._frameExtents=new o.a(4,2),this._viewportCount=6,this._viewports=[new u.a(2,1,1,1),new u.a(0,1,1,1),new u.a(3,1,1,1),new u.a(1,1,1,1),new u.a(3,0,1,1),new u.a(1,0,1,1)],this._cubeDirections=[new h.a(1,0,0),new h.a(-1,0,0),new h.a(0,0,1),new h.a(0,0,-1),new h.a(0,1,0),new h.a(0,-1,0)],this._cubeUps=[new h.a(0,1,0),new h.a(0,1,0),new h.a(0,1,0),new h.a(0,1,0),new h.a(0,0,1),new h.a(0,0,-1)]}updateMatrices(t,e=0){const s=this.camera,i=this.matrix,r=t.distance||s.far;r!==s.far&&(s.far=r,s.updateProjectionMatrix()),l.setFromMatrixPosition(t.matrixWorld),s.position.copy(l),d.copy(s.position),d.add(this._cubeDirections[e]),s.up.copy(this._cubeUps[e]),s.lookAt(d),s.updateMatrixWorld(),i.makeTranslation(-l.x,-l.y,-l.z),c.multiplyMatrices(s.projectionMatrix,s.matrixWorldInverse),this._frustum.setFromProjectionMatrix(c)}}p.prototype.isPointLightShadow=!0;class m extends i.a{constructor(t,e,s=0,i=1){super(t,e),this.type=\\\\\\\"PointLight\\\\\\\",this.distance=s,this.decay=i,this.shadow=new p}get power(){return 4*this.intensity*Math.PI}set power(t){this.intensity=t/(4*Math.PI)}dispose(){this.shadow.dispose()}copy(t){return super.copy(t),this.distance=t.distance,this.decay=t.decay,this.shadow=t.shadow.clone(),this}}m.prototype.isPointLight=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return o}));var i=s(2),r=s(55),n=s(6),a=s(3);class o extends r.a{constructor(t){super(),this.defines={STANDARD:\\\\\\\"\\\\\\\",PHYSICAL:\\\\\\\"\\\\\\\"},this.type=\\\\\\\"MeshPhysicalMaterial\\\\\\\",this.clearcoatMap=null,this.clearcoatRoughness=0,this.clearcoatRoughnessMap=null,this.clearcoatNormalScale=new i.a(1,1),this.clearcoatNormalMap=null,this.ior=1.5,Object.defineProperty(this,\\\\\\\"reflectivity\\\\\\\",{get:function(){return a.d(2.5*(this.ior-1)/(this.ior+1),0,1)},set:function(t){this.ior=(1+.4*t)/(1-.4*t)}}),this.sheenTint=new n.a(0),this.sheenRoughness=1,this.transmissionMap=null,this.thickness=.01,this.thicknessMap=null,this.attenuationDistance=0,this.attenuationTint=new n.a(1,1,1),this.specularIntensity=1,this.specularIntensityMap=null,this.specularTint=new n.a(1,1,1),this.specularTintMap=null,this._sheen=0,this._clearcoat=0,this._transmission=0,this.setValues(t)}get sheen(){return this._sheen}set sheen(t){this._sheen>0!=t>0&&this.version++,this._sheen=t}get clearcoat(){return this._clearcoat}set clearcoat(t){this._clearcoat>0!=t>0&&this.version++,this._clearcoat=t}get transmission(){return this._transmission}set transmission(t){this._transmission>0!=t>0&&this.version++,this._transmission=t}copy(t){return super.copy(t),this.defines={STANDARD:\\\\\\\"\\\\\\\",PHYSICAL:\\\\\\\"\\\\\\\"},this.clearcoat=t.clearcoat,this.clearcoatMap=t.clearcoatMap,this.clearcoatRoughness=t.clearcoatRoughness,this.clearcoatRoughnessMap=t.clearcoatRoughnessMap,this.clearcoatNormalMap=t.clearcoatNormalMap,this.clearcoatNormalScale.copy(t.clearcoatNormalScale),this.ior=t.ior,this.sheen=t.sheen,this.sheenTint.copy(t.sheenTint),this.sheenRoughness=t.sheenRoughness,this.transmission=t.transmission,this.transmissionMap=t.transmissionMap,this.thickness=t.thickness,this.thicknessMap=t.thicknessMap,this.attenuationDistance=t.attenuationDistance,this.attenuationTint.copy(t.attenuationTint),this.specularIntensity=t.specularIntensity,this.specularIntensityMap=t.specularIntensityMap,this.specularTint.copy(t.specularTint),this.specularTintMap=t.specularTintMap,this}}o.prototype.isMeshPhysicalMaterial=!0},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return h}));var i=s(0),r=s(18),n=s(31);const a=new r.a,o=new i.a;class h{constructor(t=new n.a,e=new n.a,s=new n.a,i=new n.a,r=new n.a,a=new n.a){this.planes=[t,e,s,i,r,a]}set(t,e,s,i,r,n){const a=this.planes;return a[0].copy(t),a[1].copy(e),a[2].copy(s),a[3].copy(i),a[4].copy(r),a[5].copy(n),this}copy(t){const e=this.planes;for(let s=0;s<6;s++)e[s].copy(t.planes[s]);return this}setFromProjectionMatrix(t){const e=this.planes,s=t.elements,i=s[0],r=s[1],n=s[2],a=s[3],o=s[4],h=s[5],u=s[6],c=s[7],l=s[8],d=s[9],p=s[10],m=s[11],f=s[12],y=s[13],g=s[14],x=s[15];return e[0].setComponents(a-i,c-o,m-l,x-f).normalize(),e[1].setComponents(a+i,c+o,m+l,x+f).normalize(),e[2].setComponents(a+r,c+h,m+d,x+y).normalize(),e[3].setComponents(a-r,c-h,m-d,x-y).normalize(),e[4].setComponents(a-n,c-u,m-p,x-g).normalize(),e[5].setComponents(a+n,c+u,m+p,x+g).normalize(),this}intersectsObject(t){const e=t.geometry;return null===e.boundingSphere&&e.computeBoundingSphere(),a.copy(e.boundingSphere).applyMatrix4(t.matrixWorld),this.intersectsSphere(a)}intersectsSprite(t){return a.center.set(0,0,0),a.radius=.7071067811865476,a.applyMatrix4(t.matrixWorld),this.intersectsSphere(a)}intersectsSphere(t){const e=this.planes,s=t.center,i=-t.radius;for(let t=0;t<6;t++){if(e[t].distanceToPoint(s)0?t.max.x:t.min.x,o.y=i.normal.y>0?t.max.y:t.min.y,o.z=i.normal.z>0?t.max.z:t.min.z,i.distanceToPoint(o)<0)return!1}return!0}containsPoint(t){const e=this.planes;for(let s=0;s<6;s++)if(e[s].distanceToPoint(t)<0)return!1;return!0}clone(){return(new this.constructor).copy(this)}}},,,function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return a}));var i=s(17),r=s(13),n=s(20);class a extends r.a{constructor(t){super(t)}load(t,e,s,r){void 0!==this.path&&(t=this.path+t),t=this.manager.resolveURL(t);const a=this,o=i.a.get(t);if(void 0!==o)return a.manager.itemStart(t),setTimeout((function(){e&&e(o),a.manager.itemEnd(t)}),0),o;const h=Object(n.b)(\\\\\\\"img\\\\\\\");function u(){h.removeEventListener(\\\\\\\"load\\\\\\\",u,!1),h.removeEventListener(\\\\\\\"error\\\\\\\",c,!1),i.a.add(t,this),e&&e(this),a.manager.itemEnd(t)}function c(e){h.removeEventListener(\\\\\\\"load\\\\\\\",u,!1),h.removeEventListener(\\\\\\\"error\\\\\\\",c,!1),r&&r(e),a.manager.itemError(t),a.manager.itemEnd(t)}return h.addEventListener(\\\\\\\"load\\\\\\\",u,!1),h.addEventListener(\\\\\\\"error\\\\\\\",c,!1),\\\\\\\"data:\\\\\\\"!==t.substr(0,5)&&void 0!==this.crossOrigin&&(h.crossOrigin=this.crossOrigin),a.manager.itemStart(t),h.src=t,h}}},function(t,e,s){\\\\\\\"use strict\\\\\\\";s.d(e,\\\\\\\"a\\\\\\\",(function(){return p}));var i=s(19),r=s(26),n=s(1);class a extends r.a{}a.prototype.ValueTypeName=\\\\\\\"bool\\\\\\\",a.prototype.ValueBufferType=Array,a.prototype.DefaultInterpolation=n.O,a.prototype.InterpolantFactoryMethodLinear=void 0,a.prototype.InterpolantFactoryMethodSmooth=void 0;class o extends r.a{}o.prototype.ValueTypeName=\\\\\\\"color\\\\\\\";var h=s(50),u=s(54);class c extends r.a{}c.prototype.ValueTypeName=\\\\\\\"string\\\\\\\",c.prototype.ValueBufferType=Array,c.prototype.DefaultInterpolation=n.O,c.prototype.InterpolantFactoryMethodLinear=void 0,c.prototype.InterpolantFactoryMethodSmooth=void 0;var l=s(51),d=s(3);class p{constructor(t,e=-1,s,i=n.wb){this.name=t,this.tracks=s,this.duration=e,this.blendMode=i,this.uuid=d.h(),this.duration<0&&this.resetDuration()}static parse(t){const e=[],s=t.tracks,i=1/(t.fps||1);for(let t=0,r=s.length;t!==r;++t)e.push(m(s[t]).scale(i));const r=new this(t.name,t.duration,e,t.blendMode);return r.uuid=t.uuid,r}static toJSON(t){const e=[],s=t.tracks,i={name:t.name,duration:t.duration,tracks:e,uuid:t.uuid,blendMode:t.blendMode};for(let t=0,i=s.length;t!==i;++t)e.push(r.a.toJSON(s[t]));return i}static CreateFromMorphTargetSequence(t,e,s,r){const n=e.length,a=[];for(let t=0;t1){const t=n[1];let e=i[t];e||(i[t]=e=[]),e.push(s)}}const n=[];for(const t in i)n.push(this.CreateFromMorphTargetSequence(t,i[t],e,s));return n}static parseAnimation(t,e){if(!t)return console.error(\\\\\\\"THREE.AnimationClip: No animation in JSONLoader data.\\\\\\\"),null;const s=function(t,e,s,r,n){if(0!==s.length){const a=[],o=[];i.a.flattenJSON(s,a,o,r),0!==a.length&&n.push(new t(e,a,o))}},r=[],n=t.name||\\\\\\\"default\\\\\\\",a=t.fps||30,o=t.blendMode;let c=t.length||-1;const d=t.hierarchy||[];for(let t=0;t=2.0 are supported.\\\\\\\")));const h=new Wt(o,{path:e||this.resourcePath||\\\\\\\"\\\\\\\",crossOrigin:this.crossOrigin,requestHeader:this.requestHeader,manager:this.manager,ktx2Loader:this.ktx2Loader,meshoptDecoder:this.meshoptDecoder});h.fileLoader.setRequestHeader(this.requestHeader);for(let t=0;t=0&&void 0===a[e]&&console.warn('THREE.GLTFLoader: Unknown extension \\\\\\\"'+e+'\\\\\\\".')}}h.setExtensions(n),h.setPlugins(a),h.parse(s,i)}}function K(){let t={};return{get:function(e){return t[e]},add:function(e,s){t[e]=s},remove:function(e){delete t[e]},removeAll:function(){t={}}}}const Q={KHR_BINARY_GLTF:\\\\\\\"KHR_binary_glTF\\\\\\\",KHR_DRACO_MESH_COMPRESSION:\\\\\\\"KHR_draco_mesh_compression\\\\\\\",KHR_LIGHTS_PUNCTUAL:\\\\\\\"KHR_lights_punctual\\\\\\\",KHR_MATERIALS_CLEARCOAT:\\\\\\\"KHR_materials_clearcoat\\\\\\\",KHR_MATERIALS_IOR:\\\\\\\"KHR_materials_ior\\\\\\\",KHR_MATERIALS_PBR_SPECULAR_GLOSSINESS:\\\\\\\"KHR_materials_pbrSpecularGlossiness\\\\\\\",KHR_MATERIALS_SPECULAR:\\\\\\\"KHR_materials_specular\\\\\\\",KHR_MATERIALS_TRANSMISSION:\\\\\\\"KHR_materials_transmission\\\\\\\",KHR_MATERIALS_UNLIT:\\\\\\\"KHR_materials_unlit\\\\\\\",KHR_MATERIALS_VOLUME:\\\\\\\"KHR_materials_volume\\\\\\\",KHR_TEXTURE_BASISU:\\\\\\\"KHR_texture_basisu\\\\\\\",KHR_TEXTURE_TRANSFORM:\\\\\\\"KHR_texture_transform\\\\\\\",KHR_MESH_QUANTIZATION:\\\\\\\"KHR_mesh_quantization\\\\\\\",EXT_TEXTURE_WEBP:\\\\\\\"EXT_texture_webp\\\\\\\",EXT_MESHOPT_COMPRESSION:\\\\\\\"EXT_meshopt_compression\\\\\\\"};class ${constructor(t){this.parser=t,this.name=Q.KHR_LIGHTS_PUNCTUAL,this.cache={refs:{},uses:{}}}_markDefs(){const t=this.parser,e=this.parser.json.nodes||[];for(let s=0,i=e.length;s=0)throw new Error(\\\\\\\"THREE.GLTFLoader: setKTX2Loader must be called before loading KTX2 textures\\\\\\\");return null}return e.loadTextureImage(t,n,a)}}class ot{constructor(t){this.parser=t,this.name=Q.EXT_TEXTURE_WEBP,this.isSupported=null}loadTexture(t){const e=this.name,s=this.parser,i=s.json,r=i.textures[t];if(!r.extensions||!r.extensions[e])return null;const n=r.extensions[e],a=i.images[n.source];let o=s.textureLoader;if(a.uri){const t=s.options.manager.getHandler(a.uri);null!==t&&(o=t)}return this.detectSupport().then((function(r){if(r)return s.loadTextureImage(t,a,o);if(i.extensionsRequired&&i.extensionsRequired.indexOf(e)>=0)throw new Error(\\\\\\\"THREE.GLTFLoader: WebP required by asset but unsupported.\\\\\\\");return s.loadTexture(t)}))}detectSupport(){return this.isSupported||(this.isSupported=new Promise((function(t){const e=new Image;e.src=\\\\\\\"data:image/webp;base64,UklGRiIAAABXRUJQVlA4IBYAAAAwAQCdASoBAAEADsD+JaQAA3AAAAAA\\\\\\\",e.onload=e.onerror=function(){t(1===e.height)}}))),this.isSupported}}class ht{constructor(t){this.name=Q.EXT_MESHOPT_COMPRESSION,this.parser=t}loadBufferView(t){const e=this.parser.json,s=e.bufferViews[t];if(s.extensions&&s.extensions[this.name]){const t=s.extensions[this.name],i=this.parser.getDependency(\\\\\\\"buffer\\\\\\\",t.buffer),r=this.parser.options.meshoptDecoder;if(!r||!r.supported){if(e.extensionsRequired&&e.extensionsRequired.indexOf(this.name)>=0)throw new Error(\\\\\\\"THREE.GLTFLoader: setMeshoptDecoder must be called before loading compressed files\\\\\\\");return null}return Promise.all([i,r.ready]).then((function(e){const s=t.byteOffset||0,i=t.byteLength||0,n=t.count,a=t.byteStride,o=new ArrayBuffer(n*a),h=new Uint8Array(e[0],s,i);return r.decodeGltfBuffer(new Uint8Array(o),n,a,h,t.mode,t.filter),o}))}return null}}const ut=\\\\\\\"glTF\\\\\\\",ct=1313821514,lt=5130562;class dt{constructor(t){this.name=Q.KHR_BINARY_GLTF,this.content=null,this.body=null;const e=new DataView(t,0,12);if(this.header={magic:_.a.decodeText(new Uint8Array(t.slice(0,4))),version:e.getUint32(4,!0),length:e.getUint32(8,!0)},this.header.magic!==ut)throw new Error(\\\\\\\"THREE.GLTFLoader: Unsupported glTF-Binary header.\\\\\\\");if(this.header.version<2)throw new Error(\\\\\\\"THREE.GLTFLoader: Legacy binary file detected.\\\\\\\");const s=this.header.length-12,i=new DataView(t,12);let r=0;for(;r\\\\\\\",e).replace(\\\\\\\"#include \\\\\\\",s).replace(\\\\\\\"#include \\\\\\\",i).replace(\\\\\\\"#include \\\\\\\",r).replace(\\\\\\\"#include \\\\\\\",n)},Object.defineProperties(this,{specular:{get:function(){return a.specular.value},set:function(t){a.specular.value=t}},specularMap:{get:function(){return a.specularMap.value},set:function(t){a.specularMap.value=t,t?this.defines.USE_SPECULARMAP=\\\\\\\"\\\\\\\":delete this.defines.USE_SPECULARMAP}},glossiness:{get:function(){return a.glossiness.value},set:function(t){a.glossiness.value=t}},glossinessMap:{get:function(){return a.glossinessMap.value},set:function(t){a.glossinessMap.value=t,t?(this.defines.USE_GLOSSINESSMAP=\\\\\\\"\\\\\\\",this.defines.USE_UV=\\\\\\\"\\\\\\\"):(delete this.defines.USE_GLOSSINESSMAP,delete this.defines.USE_UV)}}}),delete this.metalness,delete this.roughness,delete this.metalnessMap,delete this.roughnessMap,this.setValues(t)}copy(t){return super.copy(t),this.specularMap=t.specularMap,this.specular.copy(t.specular),this.glossinessMap=t.glossinessMap,this.glossiness=t.glossiness,delete this.metalness,delete this.roughness,delete this.metalnessMap,delete this.roughnessMap,this}}class yt{constructor(){this.name=Q.KHR_MATERIALS_PBR_SPECULAR_GLOSSINESS,this.specularGlossinessParams=[\\\\\\\"color\\\\\\\",\\\\\\\"map\\\\\\\",\\\\\\\"lightMap\\\\\\\",\\\\\\\"lightMapIntensity\\\\\\\",\\\\\\\"aoMap\\\\\\\",\\\\\\\"aoMapIntensity\\\\\\\",\\\\\\\"emissive\\\\\\\",\\\\\\\"emissiveIntensity\\\\\\\",\\\\\\\"emissiveMap\\\\\\\",\\\\\\\"bumpMap\\\\\\\",\\\\\\\"bumpScale\\\\\\\",\\\\\\\"normalMap\\\\\\\",\\\\\\\"normalMapType\\\\\\\",\\\\\\\"displacementMap\\\\\\\",\\\\\\\"displacementScale\\\\\\\",\\\\\\\"displacementBias\\\\\\\",\\\\\\\"specularMap\\\\\\\",\\\\\\\"specular\\\\\\\",\\\\\\\"glossinessMap\\\\\\\",\\\\\\\"glossiness\\\\\\\",\\\\\\\"alphaMap\\\\\\\",\\\\\\\"envMap\\\\\\\",\\\\\\\"envMapIntensity\\\\\\\",\\\\\\\"refractionRatio\\\\\\\"]}getMaterialType(){return ft}extendParams(t,e,s){const i=e.extensions[this.name];t.color=new u.a(1,1,1),t.opacity=1;const r=[];if(Array.isArray(i.diffuseFactor)){const e=i.diffuseFactor;t.color.fromArray(e),t.opacity=e[3]}if(void 0!==i.diffuseTexture&&r.push(s.assignTexture(t,\\\\\\\"map\\\\\\\",i.diffuseTexture)),t.emissive=new u.a(0,0,0),t.glossiness=void 0!==i.glossinessFactor?i.glossinessFactor:1,t.specular=new u.a(1,1,1),Array.isArray(i.specularFactor)&&t.specular.fromArray(i.specularFactor),void 0!==i.specularGlossinessTexture){const e=i.specularGlossinessTexture;r.push(s.assignTexture(t,\\\\\\\"glossinessMap\\\\\\\",e)),r.push(s.assignTexture(t,\\\\\\\"specularMap\\\\\\\",e))}return Promise.all(r)}createMaterial(t){const e=new ft(t);return e.fog=!0,e.color=t.color,e.map=void 0===t.map?null:t.map,e.lightMap=null,e.lightMapIntensity=1,e.aoMap=void 0===t.aoMap?null:t.aoMap,e.aoMapIntensity=1,e.emissive=t.emissive,e.emissiveIntensity=1,e.emissiveMap=void 0===t.emissiveMap?null:t.emissiveMap,e.bumpMap=void 0===t.bumpMap?null:t.bumpMap,e.bumpScale=1,e.normalMap=void 0===t.normalMap?null:t.normalMap,e.normalMapType=h.Uc,t.normalScale&&(e.normalScale=t.normalScale),e.displacementMap=null,e.displacementScale=1,e.displacementBias=0,e.specularMap=void 0===t.specularMap?null:t.specularMap,e.specular=t.specular,e.glossinessMap=void 0===t.glossinessMap?null:t.glossinessMap,e.glossiness=t.glossiness,e.alphaMap=null,e.envMap=void 0===t.envMap?null:t.envMap,e.envMapIntensity=1,e.refractionRatio=.98,e}}class gt{constructor(){this.name=Q.KHR_MESH_QUANTIZATION}}class xt extends x.a{constructor(t,e,s,i){super(t,e,s,i)}copySampleValue_(t){const e=this.resultBuffer,s=this.sampleValues,i=this.valueSize,r=t*i*3+i;for(let t=0;t!==i;t++)e[t]=s[r+t];return e}}xt.prototype.beforeStart_=xt.prototype.copySampleValue_,xt.prototype.afterEnd_=xt.prototype.copySampleValue_,xt.prototype.interpolate_=function(t,e,s,i){const r=this.resultBuffer,n=this.sampleValues,a=this.valueSize,o=2*a,h=3*a,u=i-e,c=(s-e)/u,l=c*c,d=l*c,p=t*h,m=p-h,f=-2*d+3*l,y=d-l,g=1-f,x=y-l+c;for(let t=0;t!==a;t++){const e=n[m+t+a],s=n[m+t+o]*u,i=n[p+t+a],h=n[p+t]*u;r[t]=g*e+x*s+f*i+y*h}return r};const bt=new V.a;class Mt extends xt{interpolate_(t,e,s,i){const r=super.interpolate_(t,e,s,i);return bt.fromArray(r).normalize().toArray(r),r}}const wt=0,vt=1,_t=2,Tt=3,St=4,At=5,Et=6,zt={5120:Int8Array,5121:Uint8Array,5122:Int16Array,5123:Uint16Array,5125:Uint32Array,5126:Float32Array},Rt={9728:h.ob,9729:h.V,9984:h.sb,9985:h.Z,9986:h.rb,9987:h.Y},It={33071:h.n,33648:h.kb,10497:h.wc},kt={SCALAR:1,VEC2:2,VEC3:3,VEC4:4,MAT2:4,MAT3:9,MAT4:16},Lt={POSITION:\\\\\\\"position\\\\\\\",NORMAL:\\\\\\\"normal\\\\\\\",TANGENT:\\\\\\\"tangent\\\\\\\",TEXCOORD_0:\\\\\\\"uv\\\\\\\",TEXCOORD_1:\\\\\\\"uv2\\\\\\\",COLOR_0:\\\\\\\"color\\\\\\\",WEIGHTS_0:\\\\\\\"skinWeight\\\\\\\",JOINTS_0:\\\\\\\"skinIndex\\\\\\\"},Ot={scale:\\\\\\\"scale\\\\\\\",translation:\\\\\\\"position\\\\\\\",rotation:\\\\\\\"quaternion\\\\\\\",weights:\\\\\\\"morphTargetInfluences\\\\\\\"},Pt={CUBICSPLINE:void 0,LINEAR:h.P,STEP:h.O},Bt=\\\\\\\"OPAQUE\\\\\\\",Nt=\\\\\\\"MASK\\\\\\\",Ct=\\\\\\\"BLEND\\\\\\\";function Ft(t,e){return\\\\\\\"string\\\\\\\"!=typeof t||\\\\\\\"\\\\\\\"===t?\\\\\\\"\\\\\\\":(/^https?:\\\\/\\\\//i.test(e)&&/^\\\\//.test(t)&&(e=e.replace(/(^https?:\\\\/\\\\/[^\\\\/]+).*/i,\\\\\\\"$1\\\\\\\")),/^(https?:)?\\\\/\\\\//i.test(t)||/^data:.*,.*$/i.test(t)||/^blob:.*$/i.test(t)?t:e+t)}function Vt(t,e,s){for(const i in s.extensions)void 0===t[i]&&(e.userData.gltfExtensions=e.userData.gltfExtensions||{},e.userData.gltfExtensions[i]=s.extensions[i])}function Ht(t,e){void 0!==e.extras&&(\\\\\\\"object\\\\\\\"==typeof e.extras?Object.assign(t.userData,e.extras):console.warn(\\\\\\\"THREE.GLTFLoader: Ignoring primitive type .extras, \\\\\\\"+e.extras))}function Ut(t,e){if(t.updateMorphTargets(),void 0!==e.weights)for(let s=0,i=e.weights.length;s{const s=this.associations.get(t);null!=s&&this.associations.set(e,s);for(const[s,i]of t.children.entries())r(i,e.children[s])};return r(s,i),i.name+=\\\\\\\"_instance_\\\\\\\"+t.uses[e]++,i}_invokeOne(t){const e=Object.values(this.plugins);e.push(this);for(let s=0;s=2&&m.setY(e,l[t*n+1]),n>=3&&m.setZ(e,l[t*n+2]),n>=4&&m.setW(e,l[t*n+3]),n>=5)throw new Error(\\\\\\\"THREE.GLTFLoader: Unsupported itemSize in sparse BufferAttribute.\\\\\\\")}}return m}))}loadTexture(t){const e=this.json,s=this.options,i=e.textures[t],r=e.images[i.source];let n=this.textureLoader;if(r.uri){const t=s.manager.getHandler(r.uri);null!==t&&(n=t)}return this.loadTextureImage(t,r,n)}loadTextureImage(t,e,s){const i=this,r=this.json,n=this.options,a=r.textures[t],o=(e.uri||e.bufferView)+\\\\\\\":\\\\\\\"+a.sampler;if(this.textureCache[o])return this.textureCache[o];const u=self.URL||self.webkitURL;let c=e.uri||\\\\\\\"\\\\\\\",l=!1;if(void 0!==e.bufferView)c=i.getDependency(\\\\\\\"bufferView\\\\\\\",e.bufferView).then((function(t){l=!0;const s=new Blob([t],{type:e.mimeType});return c=u.createObjectURL(s),c}));else if(void 0===e.uri)throw new Error(\\\\\\\"THREE.GLTFLoader: Image \\\\\\\"+t+\\\\\\\" is missing URI and bufferView\\\\\\\");const d=Promise.resolve(c).then((function(t){return new Promise((function(e,i){let r=e;!0===s.isImageBitmapLoader&&(r=function(t){const s=new W.a(t);s.needsUpdate=!0,e(s)}),s.load(Ft(t,n.path),r,void 0,i)}))})).then((function(e){!0===l&&u.revokeObjectURL(c),e.flipY=!1,a.name&&(e.name=a.name);const s=(r.samplers||{})[a.sampler]||{};return e.magFilter=Rt[s.magFilter]||h.V,e.minFilter=Rt[s.minFilter]||h.Y,e.wrapS=It[s.wrapS]||h.wc,e.wrapT=It[s.wrapT]||h.wc,i.associations.set(e,{textures:t}),e})).catch((function(){return console.error(\\\\\\\"THREE.GLTFLoader: Couldn't load texture\\\\\\\",c),null}));return this.textureCache[o]=d,d}assignTexture(t,e,s){const i=this;return this.getDependency(\\\\\\\"texture\\\\\\\",s.index).then((function(r){if(void 0===s.texCoord||0==s.texCoord||\\\\\\\"aoMap\\\\\\\"===e&&1==s.texCoord||console.warn(\\\\\\\"THREE.GLTFLoader: Custom UV set 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t=i[Q.KHR_MATERIALS_UNLIT];n=t.getMaterialType(),c.push(t.extendParams(a,r,e))}else{const s=r.pbrMetallicRoughness||{};if(a.color=new u.a(1,1,1),a.opacity=1,Array.isArray(s.baseColorFactor)){const t=s.baseColorFactor;a.color.fromArray(t),a.opacity=t[3]}void 0!==s.baseColorTexture&&c.push(e.assignTexture(a,\\\\\\\"map\\\\\\\",s.baseColorTexture)),a.metalness=void 0!==s.metallicFactor?s.metallicFactor:1,a.roughness=void 0!==s.roughnessFactor?s.roughnessFactor:1,void 0!==s.metallicRoughnessTexture&&(c.push(e.assignTexture(a,\\\\\\\"metalnessMap\\\\\\\",s.metallicRoughnessTexture)),c.push(e.assignTexture(a,\\\\\\\"roughnessMap\\\\\\\",s.metallicRoughnessTexture))),n=this._invokeOne((function(e){return e.getMaterialType&&e.getMaterialType(t)})),c.push(Promise.all(this._invokeAll((function(e){return e.extendMaterialParams&&e.extendMaterialParams(t,a)}))))}!0===r.doubleSided&&(a.side=h.z);const l=r.alphaMode||Bt;if(l===Ct?(a.transparent=!0,a.depthWrite=!1):(a.format=h.ic,a.transparent=!1,l===Nt&&(a.alphaTest=void 0!==r.alphaCutoff?r.alphaCutoff:.5)),void 0!==r.normalTexture&&n!==z.a&&(c.push(e.assignTexture(a,\\\\\\\"normalMap\\\\\\\",r.normalTexture)),a.normalScale=new X.a(1,1),void 0!==r.normalTexture.scale)){const t=r.normalTexture.scale;a.normalScale.set(t,t)}return void 0!==r.occlusionTexture&&n!==z.a&&(c.push(e.assignTexture(a,\\\\\\\"aoMap\\\\\\\",r.occlusionTexture)),void 0!==r.occlusionTexture.strength&&(a.aoMapIntensity=r.occlusionTexture.strength)),void 0!==r.emissiveFactor&&n!==z.a&&(a.emissive=(new u.a).fromArray(r.emissiveFactor)),void 0!==r.emissiveTexture&&n!==z.a&&c.push(e.assignTexture(a,\\\\\\\"emissiveMap\\\\\\\",r.emissiveTexture)),Promise.all(c).then((function(){let s;return s=n===ft?i[Q.KHR_MATERIALS_PBR_SPECULAR_GLOSSINESS].createMaterial(a):new 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t.array.constructor(t.array),this.itemSize=t.itemSize,this.count=t.count,this.normalized=t.normalized,this.usage=t.usage,this}copyAt(t,e,n){t*=this.itemSize,n*=e.itemSize;for(let i=0,s=this.itemSize;i0&&console.error(\\\\\\\"THREE.Matrix4: the constructor no longer reads arguments. use .set() instead.\\\\\\\")}set(t,e,n,i,s,r,o,a,l,c,h,u,d,p,_,m){const f=this.elements;return f[0]=t,f[4]=e,f[8]=n,f[12]=i,f[1]=s,f[5]=r,f[9]=o,f[13]=a,f[2]=l,f[6]=c,f[10]=h,f[14]=u,f[3]=d,f[7]=p,f[11]=_,f[15]=m,this}identity(){return this.set(1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1),this}clone(){return(new s).fromArray(this.elements)}copy(t){const e=this.elements,n=t.elements;return e[0]=n[0],e[1]=n[1],e[2]=n[2],e[3]=n[3],e[4]=n[4],e[5]=n[5],e[6]=n[6],e[7]=n[7],e[8]=n[8],e[9]=n[9],e[10]=n[10],e[11]=n[11],e[12]=n[12],e[13]=n[13],e[14]=n[14],e[15]=n[15],this}copyPosition(t){const e=this.elements,n=t.elements;return e[12]=n[12],e[13]=n[13],e[14]=n[14],this}setFromMatrix3(t){const e=t.elements;return 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t=r*c,n=r*h,i=o*c,s=o*h;e[0]=a*c,e[4]=-a*h,e[8]=l,e[1]=n+i*l,e[5]=t-s*l,e[9]=-o*a,e[2]=s-t*l,e[6]=i+n*l,e[10]=r*a}else if(\\\\\\\"YXZ\\\\\\\"===t.order){const t=a*c,n=a*h,i=l*c,s=l*h;e[0]=t+s*o,e[4]=i*o-n,e[8]=r*l,e[1]=r*h,e[5]=r*c,e[9]=-o,e[2]=n*o-i,e[6]=s+t*o,e[10]=r*a}else if(\\\\\\\"ZXY\\\\\\\"===t.order){const t=a*c,n=a*h,i=l*c,s=l*h;e[0]=t-s*o,e[4]=-r*h,e[8]=i+n*o,e[1]=n+i*o,e[5]=r*c,e[9]=s-t*o,e[2]=-r*l,e[6]=o,e[10]=r*a}else if(\\\\\\\"ZYX\\\\\\\"===t.order){const t=r*c,n=r*h,i=o*c,s=o*h;e[0]=a*c,e[4]=i*l-n,e[8]=t*l+s,e[1]=a*h,e[5]=s*l+t,e[9]=n*l-i,e[2]=-l,e[6]=o*a,e[10]=r*a}else if(\\\\\\\"YZX\\\\\\\"===t.order){const t=r*a,n=r*l,i=o*a,s=o*l;e[0]=a*c,e[4]=s-t*h,e[8]=i*h+n,e[1]=h,e[5]=r*c,e[9]=-o*c,e[2]=-l*c,e[6]=n*h+i,e[10]=t-s*h}else if(\\\\\\\"XZY\\\\\\\"===t.order){const t=r*a,n=r*l,i=o*a,s=o*l;e[0]=a*c,e[4]=-h,e[8]=l*c,e[1]=t*h+s,e[5]=r*c,e[9]=n*h-i,e[2]=i*h-n,e[6]=o*c,e[10]=s*h+t}return e[3]=0,e[7]=0,e[11]=0,e[12]=0,e[13]=0,e[14]=0,e[15]=1,this}makeRotationFromQuaternion(t){return this.compose(a,t,l)}lookAt(t,e,n){const i=this.elements;return u.subVectors(t,e),0===u.lengthSq()&&(u.z=1),u.normalize(),c.crossVectors(n,u),0===c.lengthSq()&&(1===Math.abs(n.z)?u.x+=1e-4:u.z+=1e-4,u.normalize(),c.crossVectors(n,u)),c.normalize(),h.crossVectors(u,c),i[0]=c.x,i[4]=h.x,i[8]=u.x,i[1]=c.y,i[5]=h.y,i[9]=u.y,i[2]=c.z,i[6]=h.z,i[10]=u.z,this}multiply(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Matrix4: .multiply() now only accepts one argument. Use .multiplyMatrices( a, b ) instead.\\\\\\\"),this.multiplyMatrices(t,e)):this.multiplyMatrices(this,t)}premultiply(t){return this.multiplyMatrices(t,this)}multiplyMatrices(t,e){const n=t.elements,i=e.elements,s=this.elements,r=n[0],o=n[4],a=n[8],l=n[12],c=n[1],h=n[5],u=n[9],d=n[13],p=n[2],_=n[6],m=n[10],f=n[14],g=n[3],v=n[7],y=n[11],x=n[15],b=i[0],w=i[4],T=i[8],A=i[12],M=i[1],E=i[5],S=i[9],C=i[13],N=i[2],L=i[6],O=i[10],P=i[14],R=i[3],I=i[7],F=i[11],D=i[15];return s[0]=r*b+o*M+a*N+l*R,s[4]=r*w+o*E+a*L+l*I,s[8]=r*T+o*S+a*O+l*F,s[12]=r*A+o*C+a*P+l*D,s[1]=c*b+h*M+u*N+d*R,s[5]=c*w+h*E+u*L+d*I,s[9]=c*T+h*S+u*O+d*F,s[13]=c*A+h*C+u*P+d*D,s[2]=p*b+_*M+m*N+f*R,s[6]=p*w+_*E+m*L+f*I,s[10]=p*T+_*S+m*O+f*F,s[14]=p*A+_*C+m*P+f*D,s[3]=g*b+v*M+y*N+x*R,s[7]=g*w+v*E+y*L+x*I,s[11]=g*T+v*S+y*O+x*F,s[15]=g*A+v*C+y*P+x*D,this}multiplyScalar(t){const e=this.elements;return e[0]*=t,e[4]*=t,e[8]*=t,e[12]*=t,e[1]*=t,e[5]*=t,e[9]*=t,e[13]*=t,e[2]*=t,e[6]*=t,e[10]*=t,e[14]*=t,e[3]*=t,e[7]*=t,e[11]*=t,e[15]*=t,this}determinant(){const t=this.elements,e=t[0],n=t[4],i=t[8],s=t[12],r=t[1],o=t[5],a=t[9],l=t[13],c=t[2],h=t[6],u=t[10],d=t[14];return t[3]*(+s*a*h-i*l*h-s*o*u+n*l*u+i*o*d-n*a*d)+t[7]*(+e*a*d-e*l*u+s*r*u-i*r*d+i*l*c-s*a*c)+t[11]*(+e*l*h-e*o*d-s*r*h+n*r*d+s*o*c-n*l*c)+t[15]*(-i*o*c-e*a*h+e*o*u+i*r*h-n*r*u+n*a*c)}transpose(){const t=this.elements;let e;return e=t[1],t[1]=t[4],t[4]=e,e=t[2],t[2]=t[8],t[8]=e,e=t[6],t[6]=t[9],t[9]=e,e=t[3],t[3]=t[12],t[12]=e,e=t[7],t[7]=t[13],t[13]=e,e=t[11],t[11]=t[14],t[14]=e,this}setPosition(t,e,n){const i=this.elements;return t.isVector3?(i[12]=t.x,i[13]=t.y,i[14]=t.z):(i[12]=t,i[13]=e,i[14]=n),this}invert(){const t=this.elements,e=t[0],n=t[1],i=t[2],s=t[3],r=t[4],o=t[5],a=t[6],l=t[7],c=t[8],h=t[9],u=t[10],d=t[11],p=t[12],_=t[13],m=t[14],f=t[15],g=h*m*l-_*u*l+_*a*d-o*m*d-h*a*f+o*u*f,v=p*u*l-c*m*l-p*a*d+r*m*d+c*a*f-r*u*f,y=c*_*l-p*h*l+p*o*d-r*_*d-c*o*f+r*h*f,x=p*h*a-c*_*a-p*o*u+r*_*u+c*o*m-r*h*m,b=e*g+n*v+i*y+s*x;if(0===b)return this.set(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0);const w=1/b;return t[0]=g*w,t[1]=(_*u*s-h*m*s-_*i*d+n*m*d+h*i*f-n*u*f)*w,t[2]=(o*m*s-_*a*s+_*i*l-n*m*l-o*i*f+n*a*f)*w,t[3]=(h*a*s-o*u*s-h*i*l+n*u*l+o*i*d-n*a*d)*w,t[4]=v*w,t[5]=(c*m*s-p*u*s+p*i*d-e*m*d-c*i*f+e*u*f)*w,t[6]=(p*a*s-r*m*s-p*i*l+e*m*l+r*i*f-e*a*f)*w,t[7]=(r*u*s-c*a*s+c*i*l-e*u*l-r*i*d+e*a*d)*w,t[8]=y*w,t[9]=(p*h*s-c*_*s-p*n*d+e*_*d+c*n*f-e*h*f)*w,t[10]=(r*_*s-p*o*s+p*n*l-e*_*l-r*n*f+e*o*f)*w,t[11]=(c*o*s-r*h*s-c*n*l+e*h*l+r*n*d-e*o*d)*w,t[12]=x*w,t[13]=(c*_*i-p*h*i+p*n*u-e*_*u-c*n*m+e*h*m)*w,t[14]=(p*o*i-r*_*i-p*n*a+e*_*a+r*n*m-e*o*m)*w,t[15]=(r*h*i-c*o*i+c*n*a-e*h*a-r*n*u+e*o*u)*w,this}scale(t){const e=this.elements,n=t.x,i=t.y,s=t.z;return e[0]*=n,e[4]*=i,e[8]*=s,e[1]*=n,e[5]*=i,e[9]*=s,e[2]*=n,e[6]*=i,e[10]*=s,e[3]*=n,e[7]*=i,e[11]*=s,this}getMaxScaleOnAxis(){const t=this.elements,e=t[0]*t[0]+t[1]*t[1]+t[2]*t[2],n=t[4]*t[4]+t[5]*t[5]+t[6]*t[6],i=t[8]*t[8]+t[9]*t[9]+t[10]*t[10];return Math.sqrt(Math.max(e,n,i))}makeTranslation(t,e,n){return this.set(1,0,0,t,0,1,0,e,0,0,1,n,0,0,0,1),this}makeRotationX(t){const e=Math.cos(t),n=Math.sin(t);return this.set(1,0,0,0,0,e,-n,0,0,n,e,0,0,0,0,1),this}makeRotationY(t){const e=Math.cos(t),n=Math.sin(t);return this.set(e,0,n,0,0,1,0,0,-n,0,e,0,0,0,0,1),this}makeRotationZ(t){const e=Math.cos(t),n=Math.sin(t);return this.set(e,-n,0,0,n,e,0,0,0,0,1,0,0,0,0,1),this}makeRotationAxis(t,e){const n=Math.cos(e),i=Math.sin(e),s=1-n,r=t.x,o=t.y,a=t.z,l=s*r,c=s*o;return this.set(l*r+n,l*o-i*a,l*a+i*o,0,l*o+i*a,c*o+n,c*a-i*r,0,l*a-i*o,c*a+i*r,s*a*a+n,0,0,0,0,1),this}makeScale(t,e,n){return this.set(t,0,0,0,0,e,0,0,0,0,n,0,0,0,0,1),this}makeShear(t,e,n,i,s,r){return this.set(1,n,s,0,t,1,r,0,e,i,1,0,0,0,0,1),this}compose(t,e,n){const i=this.elements,s=e._x,r=e._y,o=e._z,a=e._w,l=s+s,c=r+r,h=o+o,u=s*l,d=s*c,p=s*h,_=r*c,m=r*h,f=o*h,g=a*l,v=a*c,y=a*h,x=n.x,b=n.y,w=n.z;return i[0]=(1-(_+f))*x,i[1]=(d+y)*x,i[2]=(p-v)*x,i[3]=0,i[4]=(d-y)*b,i[5]=(1-(u+f))*b,i[6]=(m+g)*b,i[7]=0,i[8]=(p+v)*w,i[9]=(m-g)*w,i[10]=(1-(u+_))*w,i[11]=0,i[12]=t.x,i[13]=t.y,i[14]=t.z,i[15]=1,this}decompose(t,e,n){const i=this.elements;let s=r.set(i[0],i[1],i[2]).length();const a=r.set(i[4],i[5],i[6]).length(),l=r.set(i[8],i[9],i[10]).length();this.determinant()<0&&(s=-s),t.x=i[12],t.y=i[13],t.z=i[14],o.copy(this);const c=1/s,h=1/a,u=1/l;return o.elements[0]*=c,o.elements[1]*=c,o.elements[2]*=c,o.elements[4]*=h,o.elements[5]*=h,o.elements[6]*=h,o.elements[8]*=u,o.elements[9]*=u,o.elements[10]*=u,e.setFromRotationMatrix(o),n.x=s,n.y=a,n.z=l,this}makePerspective(t,e,n,i,s,r){void 0===r&&console.warn(\\\\\\\"THREE.Matrix4: .makePerspective() has been redefined and has a new signature. Please check the docs.\\\\\\\");const o=this.elements,a=2*s/(e-t),l=2*s/(n-i),c=(e+t)/(e-t),h=(n+i)/(n-i),u=-(r+s)/(r-s),d=-2*r*s/(r-s);return o[0]=a,o[4]=0,o[8]=c,o[12]=0,o[1]=0,o[5]=l,o[9]=h,o[13]=0,o[2]=0,o[6]=0,o[10]=u,o[14]=d,o[3]=0,o[7]=0,o[11]=-1,o[15]=0,this}makeOrthographic(t,e,n,i,s,r){const o=this.elements,a=1/(e-t),l=1/(n-i),c=1/(r-s),h=(e+t)*a,u=(n+i)*l,d=(r+s)*c;return o[0]=2*a,o[4]=0,o[8]=0,o[12]=-h,o[1]=0,o[5]=2*l,o[9]=0,o[13]=-u,o[2]=0,o[6]=0,o[10]=-2*c,o[14]=-d,o[3]=0,o[7]=0,o[11]=0,o[15]=1,this}equals(t){const e=this.elements,n=t.elements;for(let t=0;t<16;t++)if(e[t]!==n[t])return!1;return!0}fromArray(t,e=0){for(let n=0;n<16;n++)this.elements[n]=t[n+e];return this}toArray(t=[],e=0){const n=this.elements;return t[e]=n[0],t[e+1]=n[1],t[e+2]=n[2],t[e+3]=n[3],t[e+4]=n[4],t[e+5]=n[5],t[e+6]=n[6],t[e+7]=n[7],t[e+8]=n[8],t[e+9]=n[9],t[e+10]=n[10],t[e+11]=n[11],t[e+12]=n[12],t[e+13]=n[13],t[e+14]=n[14],t[e+15]=n[15],t}}s.prototype.isMatrix4=!0;const r=new i.a,o=new s,a=new i.a(0,0,0),l=new i.a(1,1,1),c=new i.a,h=new i.a,u=new i.a},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return h}));var i=n(3);const s={aliceblue:15792383,antiquewhite:16444375,aqua:65535,aquamarine:8388564,azure:15794175,beige:16119260,bisque:16770244,black:0,blanchedalmond:16772045,blue:255,blueviolet:9055202,brown:10824234,burlywood:14596231,cadetblue:6266528,chartreuse:8388352,chocolate:13789470,coral:16744272,cornflowerblue:6591981,cornsilk:16775388,crimson:14423100,cyan:65535,darkblue:139,darkcyan:35723,darkgoldenrod:12092939,darkgray:11119017,darkgreen:25600,darkgrey:11119017,darkkhaki:12433259,darkmagenta:9109643,darkolivegreen:5597999,darkorange:16747520,darkorchid:10040012,darkred:9109504,darksalmon:15308410,darkseagreen:9419919,darkslateblue:4734347,darkslategray:3100495,darkslategrey:3100495,darkturquoise:52945,darkviolet:9699539,deeppink:16716947,deepskyblue:49151,dimgray:6908265,dimgrey:6908265,dodgerblue:2003199,firebrick:11674146,floralwhite:16775920,forestgreen:2263842,fuchsia:16711935,gainsboro:14474460,ghostwhite:16316671,gold:16766720,goldenrod:14329120,gray:8421504,green:32768,greenyellow:11403055,grey:8421504,honeydew:15794160,hotpink:16738740,indianred:13458524,indigo:4915330,ivory:16777200,khaki:15787660,lavender:15132410,lavenderblush:16773365,lawngreen:8190976,lemonchiffon:16775885,lightblue:11393254,lightcoral:15761536,lightcyan:14745599,lightgoldenrodyellow:16448210,lightgray:13882323,lightgreen:9498256,lightgrey:13882323,lightpink:16758465,lightsalmon:16752762,lightseagreen:2142890,lightskyblue:8900346,lightslategray:7833753,lightslategrey:7833753,lightsteelblue:11584734,lightyellow:16777184,lime:65280,limegreen:3329330,linen:16445670,magenta:16711935,maroon:8388608,mediumaquamarine:6737322,mediumblue:205,mediumorchid:12211667,mediumpurple:9662683,mediumseagreen:3978097,mediumslateblue:8087790,mediumspringgreen:64154,mediumturquoise:4772300,mediumvioletred:13047173,midnightblue:1644912,mintcream:16121850,mistyrose:16770273,moccasin:16770229,navajowhite:16768685,navy:128,oldlace:16643558,olive:8421376,olivedrab:7048739,orange:16753920,orangered:16729344,orchid:14315734,palegoldenrod:15657130,palegreen:10025880,paleturquoise:11529966,palevioletred:14381203,papayawhip:16773077,peachpuff:16767673,peru:13468991,pink:16761035,plum:14524637,powderblue:11591910,purple:8388736,rebeccapurple:6697881,red:16711680,rosybrown:12357519,royalblue:4286945,saddlebrown:9127187,salmon:16416882,sandybrown:16032864,seagreen:3050327,seashell:16774638,sienna:10506797,silver:12632256,skyblue:8900331,slateblue:6970061,slategray:7372944,slategrey:7372944,snow:16775930,springgreen:65407,steelblue:4620980,tan:13808780,teal:32896,thistle:14204888,tomato:16737095,turquoise:4251856,violet:15631086,wheat:16113331,white:16777215,whitesmoke:16119285,yellow:16776960,yellowgreen:10145074},r={h:0,s:0,l:0},o={h:0,s:0,l:0};function a(t,e,n){return n<0&&(n+=1),n>1&&(n-=1),n<1/6?t+6*(e-t)*n:n<.5?e:n<2/3?t+6*(e-t)*(2/3-n):t}function l(t){return t<.04045?.0773993808*t:Math.pow(.9478672986*t+.0521327014,2.4)}function c(t){return t<.0031308?12.92*t:1.055*Math.pow(t,.41666)-.055}class h{constructor(t,e,n){return void 0===e&&void 0===n?this.set(t):this.setRGB(t,e,n)}set(t){return t&&t.isColor?this.copy(t):\\\\\\\"number\\\\\\\"==typeof t?this.setHex(t):\\\\\\\"string\\\\\\\"==typeof t&&this.setStyle(t),this}setScalar(t){return this.r=t,this.g=t,this.b=t,this}setHex(t){return t=Math.floor(t),this.r=(t>>16&255)/255,this.g=(t>>8&255)/255,this.b=(255&t)/255,this}setRGB(t,e,n){return this.r=t,this.g=e,this.b=n,this}setHSL(t,e,n){if(t=i.f(t,1),e=i.d(e,0,1),n=i.d(n,0,1),0===e)this.r=this.g=this.b=n;else{const i=n<=.5?n*(1+e):n+e-n*e,s=2*n-i;this.r=a(s,i,t+1/3),this.g=a(s,i,t),this.b=a(s,i,t-1/3)}return this}setStyle(t){function e(e){void 0!==e&&parseFloat(e)<1&&console.warn(\\\\\\\"THREE.Color: Alpha component of \\\\\\\"+t+\\\\\\\" will be ignored.\\\\\\\")}let n;if(n=/^((?:rgb|hsl)a?)\\\\(([^\\\\)]*)\\\\)/.exec(t)){let t;const i=n[1],s=n[2];switch(i){case\\\\\\\"rgb\\\\\\\":case\\\\\\\"rgba\\\\\\\":if(t=/^\\\\s*(\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(s))return this.r=Math.min(255,parseInt(t[1],10))/255,this.g=Math.min(255,parseInt(t[2],10))/255,this.b=Math.min(255,parseInt(t[3],10))/255,e(t[4]),this;if(t=/^\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(s))return this.r=Math.min(100,parseInt(t[1],10))/100,this.g=Math.min(100,parseInt(t[2],10))/100,this.b=Math.min(100,parseInt(t[3],10))/100,e(t[4]),this;break;case\\\\\\\"hsl\\\\\\\":case\\\\\\\"hsla\\\\\\\":if(t=/^\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(s)){const n=parseFloat(t[1])/360,i=parseInt(t[2],10)/100,s=parseInt(t[3],10)/100;return e(t[4]),this.setHSL(n,i,s)}}}else if(n=/^\\\\#([A-Fa-f\\\\d]+)$/.exec(t)){const t=n[1],e=t.length;if(3===e)return this.r=parseInt(t.charAt(0)+t.charAt(0),16)/255,this.g=parseInt(t.charAt(1)+t.charAt(1),16)/255,this.b=parseInt(t.charAt(2)+t.charAt(2),16)/255,this;if(6===e)return this.r=parseInt(t.charAt(0)+t.charAt(1),16)/255,this.g=parseInt(t.charAt(2)+t.charAt(3),16)/255,this.b=parseInt(t.charAt(4)+t.charAt(5),16)/255,this}return t&&t.length>0?this.setColorName(t):this}setColorName(t){const e=s[t.toLowerCase()];return void 0!==e?this.setHex(e):console.warn(\\\\\\\"THREE.Color: Unknown color \\\\\\\"+t),this}clone(){return new this.constructor(this.r,this.g,this.b)}copy(t){return this.r=t.r,this.g=t.g,this.b=t.b,this}copyGammaToLinear(t,e=2){return this.r=Math.pow(t.r,e),this.g=Math.pow(t.g,e),this.b=Math.pow(t.b,e),this}copyLinearToGamma(t,e=2){const n=e>0?1/e:1;return this.r=Math.pow(t.r,n),this.g=Math.pow(t.g,n),this.b=Math.pow(t.b,n),this}convertGammaToLinear(t){return this.copyGammaToLinear(this,t),this}convertLinearToGamma(t){return this.copyLinearToGamma(this,t),this}copySRGBToLinear(t){return this.r=l(t.r),this.g=l(t.g),this.b=l(t.b),this}copyLinearToSRGB(t){return this.r=c(t.r),this.g=c(t.g),this.b=c(t.b),this}convertSRGBToLinear(){return this.copySRGBToLinear(this),this}convertLinearToSRGB(){return this.copyLinearToSRGB(this),this}getHex(){return 255*this.r<<16^255*this.g<<8^255*this.b<<0}getHexString(){return(\\\\\\\"000000\\\\\\\"+this.getHex().toString(16)).slice(-6)}getHSL(t){const e=this.r,n=this.g,i=this.b,s=Math.max(e,n,i),r=Math.min(e,n,i);let o,a;const l=(r+s)/2;if(r===s)o=0,a=0;else{const t=s-r;switch(a=l<=.5?t/(s+r):t/(2-s-r),s){case e:o=(n-i)/t+(n65535?a.i:a.h)(t,1):this.index=t,this}getAttribute(t){return this.attributes[t]}setAttribute(t,e){return this.attributes[t]=e,this}deleteAttribute(t){return delete this.attributes[t],this}hasAttribute(t){return void 0!==this.attributes[t]}addGroup(t,e,n=0){this.groups.push({start:t,count:e,materialIndex:n})}clearGroups(){this.groups=[]}setDrawRange(t,e){this.drawRange.start=t,this.drawRange.count=e}applyMatrix4(t){const e=this.attributes.position;void 0!==e&&(e.applyMatrix4(t),e.needsUpdate=!0);const n=this.attributes.normal;if(void 0!==n){const e=(new u.a).getNormalMatrix(t);n.applyNormalMatrix(e),n.needsUpdate=!0}const i=this.attributes.tangent;return void 0!==i&&(i.transformDirection(t),i.needsUpdate=!0),null!==this.boundingBox&&this.computeBoundingBox(),null!==this.boundingSphere&&this.computeBoundingSphere(),this}applyQuaternion(t){return m.makeRotationFromQuaternion(t),this.applyMatrix4(m),this}rotateX(t){return m.makeRotationX(t),this.applyMatrix4(m),this}rotateY(t){return m.makeRotationY(t),this.applyMatrix4(m),this}rotateZ(t){return m.makeRotationZ(t),this.applyMatrix4(m),this}translate(t,e,n){return m.makeTranslation(t,e,n),this.applyMatrix4(m),this}scale(t,e,n){return m.makeScale(t,e,n),this.applyMatrix4(m),this}lookAt(t){return f.lookAt(t),f.updateMatrix(),this.applyMatrix4(f.matrix),this}center(){return this.computeBoundingBox(),this.boundingBox.getCenter(g).negate(),this.translate(g.x,g.y,g.z),this}setFromPoints(t){const e=[];for(let n=0,i=t.length;n0&&(t.userData=this.userData),void 0!==this.parameters){const e=this.parameters;for(const n in e)void 0!==e[n]&&(t[n]=e[n]);return t}t.data={attributes:{}};const e=this.index;null!==e&&(t.data.index={type:e.array.constructor.name,array:Array.prototype.slice.call(e.array)});const n=this.attributes;for(const e in n){const i=n[e];t.data.attributes[e]=i.toJSON(t.data)}const i={};let s=!1;for(const e in this.morphAttributes){const n=this.morphAttributes[e],r=[];for(let e=0,i=n.length;e0&&(i[e]=r,s=!0)}s&&(t.data.morphAttributes=i,t.data.morphTargetsRelative=this.morphTargetsRelative);const r=this.groups;r.length>0&&(t.data.groups=JSON.parse(JSON.stringify(r)));const o=this.boundingSphere;return null!==o&&(t.data.boundingSphere={center:o.center.toArray(),radius:o.radius}),t}clone(){return(new this.constructor).copy(this)}copy(t){this.index=null,this.attributes={},this.morphAttributes={},this.groups=[],this.boundingBox=null,this.boundingSphere=null;const e={};this.name=t.name;const n=t.index;null!==n&&this.setIndex(n.clone(e));const i=t.attributes;for(const t in i){const n=i[t];this.setAttribute(t,n.clone(e))}const s=t.morphAttributes;for(const t in s){const n=[],i=s[t];for(let t=0,s=i.length;t=0?1:-1,i=1-e*e;if(i>Number.EPSILON){const s=Math.sqrt(i),r=Math.atan2(s,e*n);t=Math.sin(t*r)/s,o=Math.sin(o*r)/s}const s=o*n;if(a=a*t+u*s,l=l*t+d*s,c=c*t+p*s,h=h*t+_*s,t===1-o){const t=1/Math.sqrt(a*a+l*l+c*c+h*h);a*=t,l*=t,c*=t,h*=t}}t[e]=a,t[e+1]=l,t[e+2]=c,t[e+3]=h}static multiplyQuaternionsFlat(t,e,n,i,s,r){const o=n[i],a=n[i+1],l=n[i+2],c=n[i+3],h=s[r],u=s[r+1],d=s[r+2],p=s[r+3];return t[e]=o*p+c*h+a*d-l*u,t[e+1]=a*p+c*u+l*h-o*d,t[e+2]=l*p+c*d+o*u-a*h,t[e+3]=c*p-o*h-a*u-l*d,t}get x(){return this._x}set x(t){this._x=t,this._onChangeCallback()}get y(){return this._y}set y(t){this._y=t,this._onChangeCallback()}get z(){return this._z}set z(t){this._z=t,this._onChangeCallback()}get w(){return this._w}set w(t){this._w=t,this._onChangeCallback()}set(t,e,n,i){return this._x=t,this._y=e,this._z=n,this._w=i,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._w)}copy(t){return this._x=t.x,this._y=t.y,this._z=t.z,this._w=t.w,this._onChangeCallback(),this}setFromEuler(t,e){if(!t||!t.isEuler)throw new Error(\\\\\\\"THREE.Quaternion: .setFromEuler() now expects an Euler rotation rather than a Vector3 and order.\\\\\\\");const n=t._x,i=t._y,s=t._z,r=t._order,o=Math.cos,a=Math.sin,l=o(n/2),c=o(i/2),h=o(s/2),u=a(n/2),d=a(i/2),p=a(s/2);switch(r){case\\\\\\\"XYZ\\\\\\\":this._x=u*c*h+l*d*p,this._y=l*d*h-u*c*p,this._z=l*c*p+u*d*h,this._w=l*c*h-u*d*p;break;case\\\\\\\"YXZ\\\\\\\":this._x=u*c*h+l*d*p,this._y=l*d*h-u*c*p,this._z=l*c*p-u*d*h,this._w=l*c*h+u*d*p;break;case\\\\\\\"ZXY\\\\\\\":this._x=u*c*h-l*d*p,this._y=l*d*h+u*c*p,this._z=l*c*p+u*d*h,this._w=l*c*h-u*d*p;break;case\\\\\\\"ZYX\\\\\\\":this._x=u*c*h-l*d*p,this._y=l*d*h+u*c*p,this._z=l*c*p-u*d*h,this._w=l*c*h+u*d*p;break;case\\\\\\\"YZX\\\\\\\":this._x=u*c*h+l*d*p,this._y=l*d*h+u*c*p,this._z=l*c*p-u*d*h,this._w=l*c*h-u*d*p;break;case\\\\\\\"XZY\\\\\\\":this._x=u*c*h-l*d*p,this._y=l*d*h-u*c*p,this._z=l*c*p+u*d*h,this._w=l*c*h+u*d*p;break;default:console.warn(\\\\\\\"THREE.Quaternion: .setFromEuler() encountered an unknown order: \\\\\\\"+r)}return!1!==e&&this._onChangeCallback(),this}setFromAxisAngle(t,e){const n=e/2,i=Math.sin(n);return this._x=t.x*i,this._y=t.y*i,this._z=t.z*i,this._w=Math.cos(n),this._onChangeCallback(),this}setFromRotationMatrix(t){const e=t.elements,n=e[0],i=e[4],s=e[8],r=e[1],o=e[5],a=e[9],l=e[2],c=e[6],h=e[10],u=n+o+h;if(u>0){const t=.5/Math.sqrt(u+1);this._w=.25/t,this._x=(c-a)*t,this._y=(s-l)*t,this._z=(r-i)*t}else if(n>o&&n>h){const t=2*Math.sqrt(1+n-o-h);this._w=(c-a)/t,this._x=.25*t,this._y=(i+r)/t,this._z=(s+l)/t}else if(o>h){const t=2*Math.sqrt(1+o-n-h);this._w=(s-l)/t,this._x=(i+r)/t,this._y=.25*t,this._z=(a+c)/t}else{const t=2*Math.sqrt(1+h-n-o);this._w=(r-i)/t,this._x=(s+l)/t,this._y=(a+c)/t,this._z=.25*t}return this._onChangeCallback(),this}setFromUnitVectors(t,e){let n=t.dot(e)+1;return nMath.abs(t.z)?(this._x=-t.y,this._y=t.x,this._z=0,this._w=n):(this._x=0,this._y=-t.z,this._z=t.y,this._w=n)):(this._x=t.y*e.z-t.z*e.y,this._y=t.z*e.x-t.x*e.z,this._z=t.x*e.y-t.y*e.x,this._w=n),this.normalize()}angleTo(t){return 2*Math.acos(Math.abs(i.d(this.dot(t),-1,1)))}rotateTowards(t,e){const n=this.angleTo(t);if(0===n)return this;const i=Math.min(1,e/n);return this.slerp(t,i),this}identity(){return this.set(0,0,0,1)}invert(){return this.conjugate()}conjugate(){return this._x*=-1,this._y*=-1,this._z*=-1,this._onChangeCallback(),this}dot(t){return this._x*t._x+this._y*t._y+this._z*t._z+this._w*t._w}lengthSq(){return this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w}length(){return Math.sqrt(this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w)}normalize(){let t=this.length();return 0===t?(this._x=0,this._y=0,this._z=0,this._w=1):(t=1/t,this._x=this._x*t,this._y=this._y*t,this._z=this._z*t,this._w=this._w*t),this._onChangeCallback(),this}multiply(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Quaternion: .multiply() now only accepts one argument. Use .multiplyQuaternions( a, b ) instead.\\\\\\\"),this.multiplyQuaternions(t,e)):this.multiplyQuaternions(this,t)}premultiply(t){return this.multiplyQuaternions(t,this)}multiplyQuaternions(t,e){const n=t._x,i=t._y,s=t._z,r=t._w,o=e._x,a=e._y,l=e._z,c=e._w;return this._x=n*c+r*o+i*l-s*a,this._y=i*c+r*a+s*o-n*l,this._z=s*c+r*l+n*a-i*o,this._w=r*c-n*o-i*a-s*l,this._onChangeCallback(),this}slerp(t,e){if(0===e)return this;if(1===e)return this.copy(t);const n=this._x,i=this._y,s=this._z,r=this._w;let o=r*t._w+n*t._x+i*t._y+s*t._z;if(o<0?(this._w=-t._w,this._x=-t._x,this._y=-t._y,this._z=-t._z,o=-o):this.copy(t),o>=1)return this._w=r,this._x=n,this._y=i,this._z=s,this;const a=1-o*o;if(a<=Number.EPSILON){const t=1-e;return this._w=t*r+e*this._w,this._x=t*n+e*this._x,this._y=t*i+e*this._y,this._z=t*s+e*this._z,this.normalize(),this._onChangeCallback(),this}const l=Math.sqrt(a),c=Math.atan2(l,o),h=Math.sin((1-e)*c)/l,u=Math.sin(e*c)/l;return this._w=r*h+this._w*u,this._x=n*h+this._x*u,this._y=i*h+this._y*u,this._z=s*h+this._z*u,this._onChangeCallback(),this}slerpQuaternions(t,e,n){this.copy(t).slerp(e,n)}random(){const t=Math.random(),e=Math.sqrt(1-t),n=Math.sqrt(t),i=2*Math.PI*Math.random(),s=2*Math.PI*Math.random();return this.set(e*Math.cos(i),n*Math.sin(s),n*Math.cos(s),e*Math.sin(i))}equals(t){return t._x===this._x&&t._y===this._y&&t._z===this._z&&t._w===this._w}fromArray(t,e=0){return this._x=t[e],this._y=t[e+1],this._z=t[e+2],this._w=t[e+3],this._onChangeCallback(),this}toArray(t=[],e=0){return t[e]=this._x,t[e+1]=this._y,t[e+2]=this._z,t[e+3]=this._w,t}fromBufferAttribute(t,e){return this._x=t.getX(e),this._y=t.getY(e),this._z=t.getZ(e),this._w=t.getW(e),this}_onChange(t){return this._onChangeCallback=t,this}_onChangeCallback(){}}s.prototype.isQuaternion=!0},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return i}));class i{constructor(t=0,e=0,n=0,i=1){this.x=t,this.y=e,this.z=n,this.w=i}get width(){return this.z}set width(t){this.z=t}get height(){return this.w}set height(t){this.w=t}set(t,e,n,i){return this.x=t,this.y=e,this.z=n,this.w=i,this}setScalar(t){return this.x=t,this.y=t,this.z=t,this.w=t,this}setX(t){return this.x=t,this}setY(t){return this.y=t,this}setZ(t){return this.z=t,this}setW(t){return this.w=t,this}setComponent(t,e){switch(t){case 0:this.x=e;break;case 1:this.y=e;break;case 2:this.z=e;break;case 3:this.w=e;break;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}return this}getComponent(t){switch(t){case 0:return this.x;case 1:return this.y;case 2:return this.z;case 3:return this.w;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}}clone(){return new this.constructor(this.x,this.y,this.z,this.w)}copy(t){return this.x=t.x,this.y=t.y,this.z=t.z,this.w=void 0!==t.w?t.w:1,this}add(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector4: .add() now only accepts one argument. Use .addVectors( a, b ) instead.\\\\\\\"),this.addVectors(t,e)):(this.x+=t.x,this.y+=t.y,this.z+=t.z,this.w+=t.w,this)}addScalar(t){return this.x+=t,this.y+=t,this.z+=t,this.w+=t,this}addVectors(t,e){return this.x=t.x+e.x,this.y=t.y+e.y,this.z=t.z+e.z,this.w=t.w+e.w,this}addScaledVector(t,e){return this.x+=t.x*e,this.y+=t.y*e,this.z+=t.z*e,this.w+=t.w*e,this}sub(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector4: .sub() now only accepts one argument. Use .subVectors( a, b ) instead.\\\\\\\"),this.subVectors(t,e)):(this.x-=t.x,this.y-=t.y,this.z-=t.z,this.w-=t.w,this)}subScalar(t){return this.x-=t,this.y-=t,this.z-=t,this.w-=t,this}subVectors(t,e){return this.x=t.x-e.x,this.y=t.y-e.y,this.z=t.z-e.z,this.w=t.w-e.w,this}multiply(t){return this.x*=t.x,this.y*=t.y,this.z*=t.z,this.w*=t.w,this}multiplyScalar(t){return this.x*=t,this.y*=t,this.z*=t,this.w*=t,this}applyMatrix4(t){const e=this.x,n=this.y,i=this.z,s=this.w,r=t.elements;return this.x=r[0]*e+r[4]*n+r[8]*i+r[12]*s,this.y=r[1]*e+r[5]*n+r[9]*i+r[13]*s,this.z=r[2]*e+r[6]*n+r[10]*i+r[14]*s,this.w=r[3]*e+r[7]*n+r[11]*i+r[15]*s,this}divideScalar(t){return this.multiplyScalar(1/t)}setAxisAngleFromQuaternion(t){this.w=2*Math.acos(t.w);const e=Math.sqrt(1-t.w*t.w);return e<1e-4?(this.x=1,this.y=0,this.z=0):(this.x=t.x/e,this.y=t.y/e,this.z=t.z/e),this}setAxisAngleFromRotationMatrix(t){let e,n,i,s;const r=.01,o=.1,a=t.elements,l=a[0],c=a[4],h=a[8],u=a[1],d=a[5],p=a[9],_=a[2],m=a[6],f=a[10];if(Math.abs(c-u)a&&t>g?tg?a1){for(let t=0;t1){for(let t=0;t0){i.children=[];for(let e=0;e0){i.animations=[];for(let e=0;e0&&(n.geometries=e),i.length>0&&(n.materials=i),s.length>0&&(n.textures=s),o.length>0&&(n.images=o),a.length>0&&(n.shapes=a),l.length>0&&(n.skeletons=l),c.length>0&&(n.animations=c)}return n.object=i,n;function r(t){const e=[];for(const n in t){const i=t[n];delete i.metadata,e.push(i)}return e}}clone(t){return(new this.constructor).copy(this,t)}copy(t,e=!0){if(this.name=t.name,this.up.copy(t.up),this.position.copy(t.position),this.rotation.order=t.rotation.order,this.quaternion.copy(t.quaternion),this.scale.copy(t.scale),this.matrix.copy(t.matrix),this.matrixWorld.copy(t.matrixWorld),this.matrixAutoUpdate=t.matrixAutoUpdate,this.matrixWorldNeedsUpdate=t.matrixWorldNeedsUpdate,this.layers.mask=t.layers.mask,this.visible=t.visible,this.castShadow=t.castShadow,this.receiveShadow=t.receiveShadow,this.frustumCulled=t.frustumCulled,this.renderOrder=t.renderOrder,this.userData=JSON.parse(JSON.stringify(t.userData)),!0===e)for(let e=0;e0&&console.error(\\\\\\\"THREE.Matrix3: the constructor no longer reads arguments. use .set() instead.\\\\\\\")}set(t,e,n,i,s,r,o,a,l){const c=this.elements;return c[0]=t,c[1]=i,c[2]=o,c[3]=e,c[4]=s,c[5]=a,c[6]=n,c[7]=r,c[8]=l,this}identity(){return this.set(1,0,0,0,1,0,0,0,1),this}copy(t){const e=this.elements,n=t.elements;return e[0]=n[0],e[1]=n[1],e[2]=n[2],e[3]=n[3],e[4]=n[4],e[5]=n[5],e[6]=n[6],e[7]=n[7],e[8]=n[8],this}extractBasis(t,e,n){return t.setFromMatrix3Column(this,0),e.setFromMatrix3Column(this,1),n.setFromMatrix3Column(this,2),this}setFromMatrix4(t){const e=t.elements;return this.set(e[0],e[4],e[8],e[1],e[5],e[9],e[2],e[6],e[10]),this}multiply(t){return this.multiplyMatrices(this,t)}premultiply(t){return this.multiplyMatrices(t,this)}multiplyMatrices(t,e){const n=t.elements,i=e.elements,s=this.elements,r=n[0],o=n[3],a=n[6],l=n[1],c=n[4],h=n[7],u=n[2],d=n[5],p=n[8],_=i[0],m=i[3],f=i[6],g=i[1],v=i[4],y=i[7],x=i[2],b=i[5],w=i[8];return s[0]=r*_+o*g+a*x,s[3]=r*m+o*v+a*b,s[6]=r*f+o*y+a*w,s[1]=l*_+c*g+h*x,s[4]=l*m+c*v+h*b,s[7]=l*f+c*y+h*w,s[2]=u*_+d*g+p*x,s[5]=u*m+d*v+p*b,s[8]=u*f+d*y+p*w,this}multiplyScalar(t){const e=this.elements;return e[0]*=t,e[3]*=t,e[6]*=t,e[1]*=t,e[4]*=t,e[7]*=t,e[2]*=t,e[5]*=t,e[8]*=t,this}determinant(){const t=this.elements,e=t[0],n=t[1],i=t[2],s=t[3],r=t[4],o=t[5],a=t[6],l=t[7],c=t[8];return e*r*c-e*o*l-n*s*c+n*o*a+i*s*l-i*r*a}invert(){const t=this.elements,e=t[0],n=t[1],i=t[2],s=t[3],r=t[4],o=t[5],a=t[6],l=t[7],c=t[8],h=c*r-o*l,u=o*a-c*s,d=l*s-r*a,p=e*h+n*u+i*d;if(0===p)return this.set(0,0,0,0,0,0,0,0,0);const _=1/p;return t[0]=h*_,t[1]=(i*l-c*n)*_,t[2]=(o*n-i*r)*_,t[3]=u*_,t[4]=(c*e-i*a)*_,t[5]=(i*s-o*e)*_,t[6]=d*_,t[7]=(n*a-l*e)*_,t[8]=(r*e-n*s)*_,this}transpose(){let t;const e=this.elements;return t=e[1],e[1]=e[3],e[3]=t,t=e[2],e[2]=e[6],e[6]=t,t=e[5],e[5]=e[7],e[7]=t,this}getNormalMatrix(t){return this.setFromMatrix4(t).invert().transpose()}transposeIntoArray(t){const e=this.elements;return t[0]=e[0],t[1]=e[3],t[2]=e[6],t[3]=e[1],t[4]=e[4],t[5]=e[7],t[6]=e[2],t[7]=e[5],t[8]=e[8],this}setUvTransform(t,e,n,i,s,r,o){const a=Math.cos(s),l=Math.sin(s);return this.set(n*a,n*l,-n*(a*r+l*o)+r+t,-i*l,i*a,-i*(-l*r+a*o)+o+e,0,0,1),this}scale(t,e){const n=this.elements;return n[0]*=t,n[3]*=t,n[6]*=t,n[1]*=e,n[4]*=e,n[7]*=e,this}rotate(t){const e=Math.cos(t),n=Math.sin(t),i=this.elements,s=i[0],r=i[3],o=i[6],a=i[1],l=i[4],c=i[7];return i[0]=e*s+n*a,i[3]=e*r+n*l,i[6]=e*o+n*c,i[1]=-n*s+e*a,i[4]=-n*r+e*l,i[7]=-n*o+e*c,this}translate(t,e){const n=this.elements;return n[0]+=t*n[2],n[3]+=t*n[5],n[6]+=t*n[8],n[1]+=e*n[2],n[4]+=e*n[5],n[7]+=e*n[8],this}equals(t){const e=this.elements,n=t.elements;for(let t=0;t<9;t++)if(e[t]!==n[t])return!1;return!0}fromArray(t,e=0){for(let n=0;n<9;n++)this.elements[n]=t[n+e];return this}toArray(t=[],e=0){const n=this.elements;return t[e]=n[0],t[e+1]=n[1],t[e+2]=n[2],t[e+3]=n[3],t[e+4]=n[4],t[e+5]=n[5],t[e+6]=n[6],t[e+7]=n[7],t[e+8]=n[8],t}clone(){return(new this.constructor).fromArray(this.elements)}}i.prototype.isMatrix3=!0},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return a}));var i=n(15),s=n(1),r=n(3);let o=0;class a extends i.a{constructor(){super(),Object.defineProperty(this,\\\\\\\"id\\\\\\\",{value:o++}),this.uuid=r.h(),this.name=\\\\\\\"\\\\\\\",this.type=\\\\\\\"Material\\\\\\\",this.fog=!0,this.blending=s.xb,this.side=s.H,this.vertexColors=!1,this.opacity=1,this.format=s.Ib,this.transparent=!1,this.blendSrc=s.Nc,this.blendDst=s.Db,this.blendEquation=s.b,this.blendSrcAlpha=null,this.blendDstAlpha=null,this.blendEquationAlpha=null,this.depthFunc=s.T,this.depthTest=!0,this.depthWrite=!0,this.stencilWriteMask=255,this.stencilFunc=s.h,this.stencilRef=0,this.stencilFuncMask=255,this.stencilFail=s.R,this.stencilZFail=s.R,this.stencilZPass=s.R,this.stencilWrite=!1,this.clippingPlanes=null,this.clipIntersection=!1,this.clipShadows=!1,this.shadowSide=null,this.colorWrite=!0,this.precision=null,this.polygonOffset=!1,this.polygonOffsetFactor=0,this.polygonOffsetUnits=0,this.dithering=!1,this.alphaToCoverage=!1,this.premultipliedAlpha=!1,this.visible=!0,this.toneMapped=!0,this.userData={},this.version=0,this._alphaTest=0}get alphaTest(){return this._alphaTest}set alphaTest(t){this._alphaTest>0!=t>0&&this.version++,this._alphaTest=t}onBuild(){}onBeforeRender(){}onBeforeCompile(){}customProgramCacheKey(){return this.onBeforeCompile.toString()}setValues(t){if(void 0!==t)for(const e in t){const n=t[e];if(void 0===n){console.warn(\\\\\\\"THREE.Material: '\\\\\\\"+e+\\\\\\\"' parameter is undefined.\\\\\\\");continue}if(\\\\\\\"shading\\\\\\\"===e){console.warn(\\\\\\\"THREE.\\\\\\\"+this.type+\\\\\\\": .shading has been removed. Use the boolean .flatShading instead.\\\\\\\"),this.flatShading=n===s.F;continue}const i=this[e];void 0!==i?i&&i.isColor?i.set(n):i&&i.isVector3&&n&&n.isVector3?i.copy(n):this[e]=n:console.warn(\\\\\\\"THREE.\\\\\\\"+this.type+\\\\\\\": '\\\\\\\"+e+\\\\\\\"' is not a property of this material.\\\\\\\")}}toJSON(t){const e=void 0===t||\\\\\\\"string\\\\\\\"==typeof t;e&&(t={textures:{},images:{}});const n={metadata:{version:4.5,type:\\\\\\\"Material\\\\\\\",generator:\\\\\\\"Material.toJSON\\\\\\\"}};function i(t){const e=[];for(const n in t){const i=t[n];delete i.metadata,e.push(i)}return e}if(n.uuid=this.uuid,n.type=this.type,\\\\\\\"\\\\\\\"!==this.name&&(n.name=this.name),this.color&&this.color.isColor&&(n.color=this.color.getHex()),void 0!==this.roughness&&(n.roughness=this.roughness),void 0!==this.metalness&&(n.metalness=this.metalness),void 0!==this.sheen&&(n.sheen=this.sheen),this.sheenTint&&this.sheenTint.isColor&&(n.sheenTint=this.sheenTint.getHex()),void 0!==this.sheenRoughness&&(n.sheenRoughness=this.sheenRoughness),this.emissive&&this.emissive.isColor&&(n.emissive=this.emissive.getHex()),this.emissiveIntensity&&1!==this.emissiveIntensity&&(n.emissiveIntensity=this.emissiveIntensity),this.specular&&this.specular.isColor&&(n.specular=this.specular.getHex()),void 0!==this.specularIntensity&&(n.specularIntensity=this.specularIntensity),this.specularTint&&this.specularTint.isColor&&(n.specularTint=this.specularTint.getHex()),void 0!==this.shininess&&(n.shininess=this.shininess),void 0!==this.clearcoat&&(n.clearcoat=this.clearcoat),void 0!==this.clearcoatRoughness&&(n.clearcoatRoughness=this.clearcoatRoughness),this.clearcoatMap&&this.clearcoatMap.isTexture&&(n.clearcoatMap=this.clearcoatMap.toJSON(t).uuid),this.clearcoatRoughnessMap&&this.clearcoatRoughnessMap.isTexture&&(n.clearcoatRoughnessMap=this.clearcoatRoughnessMap.toJSON(t).uuid),this.clearcoatNormalMap&&this.clearcoatNormalMap.isTexture&&(n.clearcoatNormalMap=this.clearcoatNormalMap.toJSON(t).uuid,n.clearcoatNormalScale=this.clearcoatNormalScale.toArray()),this.map&&this.map.isTexture&&(n.map=this.map.toJSON(t).uuid),this.matcap&&this.matcap.isTexture&&(n.matcap=this.matcap.toJSON(t).uuid),this.alphaMap&&this.alphaMap.isTexture&&(n.alphaMap=this.alphaMap.toJSON(t).uuid),this.lightMap&&this.lightMap.isTexture&&(n.lightMap=this.lightMap.toJSON(t).uuid,n.lightMapIntensity=this.lightMapIntensity),this.aoMap&&this.aoMap.isTexture&&(n.aoMap=this.aoMap.toJSON(t).uuid,n.aoMapIntensity=this.aoMapIntensity),this.bumpMap&&this.bumpMap.isTexture&&(n.bumpMap=this.bumpMap.toJSON(t).uuid,n.bumpScale=this.bumpScale),this.normalMap&&this.normalMap.isTexture&&(n.normalMap=this.normalMap.toJSON(t).uuid,n.normalMapType=this.normalMapType,n.normalScale=this.normalScale.toArray()),this.displacementMap&&this.displacementMap.isTexture&&(n.displacementMap=this.displacementMap.toJSON(t).uuid,n.displacementScale=this.displacementScale,n.displacementBias=this.displacementBias),this.roughnessMap&&this.roughnessMap.isTexture&&(n.roughnessMap=this.roughnessMap.toJSON(t).uuid),this.metalnessMap&&this.metalnessMap.isTexture&&(n.metalnessMap=this.metalnessMap.toJSON(t).uuid),this.emissiveMap&&this.emissiveMap.isTexture&&(n.emissiveMap=this.emissiveMap.toJSON(t).uuid),this.specularMap&&this.specularMap.isTexture&&(n.specularMap=this.specularMap.toJSON(t).uuid),this.specularIntensityMap&&this.specularIntensityMap.isTexture&&(n.specularIntensityMap=this.specularIntensityMap.toJSON(t).uuid),this.specularTintMap&&this.specularTintMap.isTexture&&(n.specularTintMap=this.specularTintMap.toJSON(t).uuid),this.envMap&&this.envMap.isTexture&&(n.envMap=this.envMap.toJSON(t).uuid,void 0!==this.combine&&(n.combine=this.combine)),void 0!==this.envMapIntensity&&(n.envMapIntensity=this.envMapIntensity),void 0!==this.reflectivity&&(n.reflectivity=this.reflectivity),void 0!==this.refractionRatio&&(n.refractionRatio=this.refractionRatio),this.gradientMap&&this.gradientMap.isTexture&&(n.gradientMap=this.gradientMap.toJSON(t).uuid),void 0!==this.transmission&&(n.transmission=this.transmission),this.transmissionMap&&this.transmissionMap.isTexture&&(n.transmissionMap=this.transmissionMap.toJSON(t).uuid),void 0!==this.thickness&&(n.thickness=this.thickness),this.thicknessMap&&this.thicknessMap.isTexture&&(n.thicknessMap=this.thicknessMap.toJSON(t).uuid),void 0!==this.attenuationDistance&&(n.attenuationDistance=this.attenuationDistance),void 0!==this.attenuationTint&&(n.attenuationTint=this.attenuationTint.getHex()),void 0!==this.size&&(n.size=this.size),null!==this.shadowSide&&(n.shadowSide=this.shadowSide),void 0!==this.sizeAttenuation&&(n.sizeAttenuation=this.sizeAttenuation),this.blending!==s.xb&&(n.blending=this.blending),this.side!==s.H&&(n.side=this.side),this.vertexColors&&(n.vertexColors=!0),this.opacity<1&&(n.opacity=this.opacity),this.format!==s.Ib&&(n.format=this.format),!0===this.transparent&&(n.transparent=this.transparent),n.depthFunc=this.depthFunc,n.depthTest=this.depthTest,n.depthWrite=this.depthWrite,n.colorWrite=this.colorWrite,n.stencilWrite=this.stencilWrite,n.stencilWriteMask=this.stencilWriteMask,n.stencilFunc=this.stencilFunc,n.stencilRef=this.stencilRef,n.stencilFuncMask=this.stencilFuncMask,n.stencilFail=this.stencilFail,n.stencilZFail=this.stencilZFail,n.stencilZPass=this.stencilZPass,this.rotation&&0!==this.rotation&&(n.rotation=this.rotation),!0===this.polygonOffset&&(n.polygonOffset=!0),0!==this.polygonOffsetFactor&&(n.polygonOffsetFactor=this.polygonOffsetFactor),0!==this.polygonOffsetUnits&&(n.polygonOffsetUnits=this.polygonOffsetUnits),this.linewidth&&1!==this.linewidth&&(n.linewidth=this.linewidth),void 0!==this.dashSize&&(n.dashSize=this.dashSize),void 0!==this.gapSize&&(n.gapSize=this.gapSize),void 0!==this.scale&&(n.scale=this.scale),!0===this.dithering&&(n.dithering=!0),this.alphaTest>0&&(n.alphaTest=this.alphaTest),!0===this.alphaToCoverage&&(n.alphaToCoverage=this.alphaToCoverage),!0===this.premultipliedAlpha&&(n.premultipliedAlpha=this.premultipliedAlpha),!0===this.wireframe&&(n.wireframe=this.wireframe),this.wireframeLinewidth>1&&(n.wireframeLinewidth=this.wireframeLinewidth),\\\\\\\"round\\\\\\\"!==this.wireframeLinecap&&(n.wireframeLinecap=this.wireframeLinecap),\\\\\\\"round\\\\\\\"!==this.wireframeLinejoin&&(n.wireframeLinejoin=this.wireframeLinejoin),!0===this.flatShading&&(n.flatShading=this.flatShading),!1===this.visible&&(n.visible=!1),!1===this.toneMapped&&(n.toneMapped=!1),\\\\\\\"{}\\\\\\\"!==JSON.stringify(this.userData)&&(n.userData=this.userData),e){const e=i(t.textures),s=i(t.images);e.length>0&&(n.textures=e),s.length>0&&(n.images=s)}return n}clone(){return(new this.constructor).copy(this)}copy(t){this.name=t.name,this.fog=t.fog,this.blending=t.blending,this.side=t.side,this.vertexColors=t.vertexColors,this.opacity=t.opacity,this.format=t.format,this.transparent=t.transparent,this.blendSrc=t.blendSrc,this.blendDst=t.blendDst,this.blendEquation=t.blendEquation,this.blendSrcAlpha=t.blendSrcAlpha,this.blendDstAlpha=t.blendDstAlpha,this.blendEquationAlpha=t.blendEquationAlpha,this.depthFunc=t.depthFunc,this.depthTest=t.depthTest,this.depthWrite=t.depthWrite,this.stencilWriteMask=t.stencilWriteMask,this.stencilFunc=t.stencilFunc,this.stencilRef=t.stencilRef,this.stencilFuncMask=t.stencilFuncMask,this.stencilFail=t.stencilFail,this.stencilZFail=t.stencilZFail,this.stencilZPass=t.stencilZPass,this.stencilWrite=t.stencilWrite;const e=t.clippingPlanes;let n=null;if(null!==e){const t=e.length;n=new Array(t);for(let i=0;i!==t;++i)n[i]=e[i].clone()}return this.clippingPlanes=n,this.clipIntersection=t.clipIntersection,this.clipShadows=t.clipShadows,this.shadowSide=t.shadowSide,this.colorWrite=t.colorWrite,this.precision=t.precision,this.polygonOffset=t.polygonOffset,this.polygonOffsetFactor=t.polygonOffsetFactor,this.polygonOffsetUnits=t.polygonOffsetUnits,this.dithering=t.dithering,this.alphaTest=t.alphaTest,this.alphaToCoverage=t.alphaToCoverage,this.premultipliedAlpha=t.premultipliedAlpha,this.visible=t.visible,this.toneMapped=t.toneMapped,this.userData=JSON.parse(JSON.stringify(t.userData)),this}dispose(){this.dispatchEvent({type:\\\\\\\"dispose\\\\\\\"})}set needsUpdate(t){!0===t&&this.version++}}a.prototype.isMaterial=!0},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return s}));var i=n(28);class s{constructor(t){this.manager=void 0!==t?t:i.a,this.crossOrigin=\\\\\\\"anonymous\\\\\\\",this.withCredentials=!1,this.path=\\\\\\\"\\\\\\\",this.resourcePath=\\\\\\\"\\\\\\\",this.requestHeader={}}load(){}loadAsync(t,e){const n=this;return new Promise((function(i,s){n.load(t,i,e,s)}))}parse(){}setCrossOrigin(t){return this.crossOrigin=t,this}setWithCredentials(t){return this.withCredentials=t,this}setPath(t){return this.path=t,this}setResourcePath(t){return this.resourcePath=t,this}setRequestHeader(t){return this.requestHeader=t,this}}},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return L}));var i=n(0),s=n(2),r=n(18),o=n(39),a=n(5),l=n(10),c=n(40),h=n(1),u=n(29),d=n(7);const p=new a.a,_=new o.a,m=new r.a,f=new i.a,g=new i.a,v=new i.a,y=new i.a,x=new i.a,b=new i.a,w=new i.a,T=new i.a,A=new i.a,M=new s.a,E=new s.a,S=new s.a,C=new i.a,N=new i.a;class L extends l.a{constructor(t=new d.a,e=new u.a){super(),this.type=\\\\\\\"Mesh\\\\\\\",this.geometry=t,this.material=e,this.updateMorphTargets()}copy(t){return super.copy(t),void 0!==t.morphTargetInfluences&&(this.morphTargetInfluences=t.morphTargetInfluences.slice()),void 0!==t.morphTargetDictionary&&(this.morphTargetDictionary=Object.assign({},t.morphTargetDictionary)),this.material=t.material,this.geometry=t.geometry,this}updateMorphTargets(){const t=this.geometry;if(t.isBufferGeometry){const e=t.morphAttributes,n=Object.keys(e);if(n.length>0){const t=e[n[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,n=t.length;e0&&console.error(\\\\\\\"THREE.Mesh.updateMorphTargets() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}}raycast(t,e){const n=this.geometry,i=this.material,s=this.matrixWorld;if(void 0===i)return;if(null===n.boundingSphere&&n.computeBoundingSphere(),m.copy(n.boundingSphere),m.applyMatrix4(s),!1===t.ray.intersectsSphere(m))return;if(p.copy(s).invert(),_.copy(t.ray).applyMatrix4(p),null!==n.boundingBox&&!1===_.intersectsBox(n.boundingBox))return;let r;if(n.isBufferGeometry){const s=n.index,o=n.attributes.position,a=n.morphAttributes.position,l=n.morphTargetsRelative,c=n.attributes.uv,h=n.attributes.uv2,u=n.groups,d=n.drawRange;if(null!==s)if(Array.isArray(i))for(let n=0,p=u.length;nn.far?null:{distance:c,point:N.clone(),object:t}}(t,e,n,r,f,g,v,C);if(O){u&&(M.fromBufferAttribute(u,p),E.fromBufferAttribute(u,_),S.fromBufferAttribute(u,m),O.uv=c.a.getUV(C,f,g,v,M,E,S,new s.a)),d&&(M.fromBufferAttribute(d,p),E.fromBufferAttribute(d,_),S.fromBufferAttribute(d,m),O.uv2=c.a.getUV(C,f,g,v,M,E,S,new s.a));const t={a:p,b:_,c:m,normal:new 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y(t){this._y=t,this._onChangeCallback()}get z(){return this._z}set z(t){this._z=t,this._onChangeCallback()}get order(){return this._order}set order(t){this._order=t,this._onChangeCallback()}set(t,e,n,i=this._order){return this._x=t,this._y=e,this._z=n,this._order=i,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._order)}copy(t){return this._x=t._x,this._y=t._y,this._z=t._z,this._order=t._order,this._onChangeCallback(),this}setFromRotationMatrix(t,e=this._order,n=!0){const i=t.elements,s=i[0],r=i[4],a=i[8],l=i[1],c=i[5],h=i[9],u=i[2],d=i[6],p=i[10];switch(e){case\\\\\\\"XYZ\\\\\\\":this._y=Math.asin(Object(o.d)(a,-1,1)),Math.abs(a)<.9999999?(this._x=Math.atan2(-h,p),this._z=Math.atan2(-r,s)):(this._x=Math.atan2(d,c),this._z=0);break;case\\\\\\\"YXZ\\\\\\\":this._x=Math.asin(-Object(o.d)(h,-1,1)),Math.abs(h)<.9999999?(this._y=Math.atan2(a,p),this._z=Math.atan2(l,c)):(this._y=Math.atan2(-u,s),this._z=0);break;case\\\\\\\"ZXY\\\\\\\":this._x=Math.asin(Object(o.d)(d,-1,1)),Math.abs(d)<.9999999?(this._y=Math.atan2(-u,p),this._z=Math.atan2(-r,c)):(this._y=0,this._z=Math.atan2(l,s));break;case\\\\\\\"ZYX\\\\\\\":this._y=Math.asin(-Object(o.d)(u,-1,1)),Math.abs(u)<.9999999?(this._x=Math.atan2(d,p),this._z=Math.atan2(l,s)):(this._x=0,this._z=Math.atan2(-r,c));break;case\\\\\\\"YZX\\\\\\\":this._z=Math.asin(Object(o.d)(l,-1,1)),Math.abs(l)<.9999999?(this._x=Math.atan2(-h,c),this._y=Math.atan2(-u,s)):(this._x=0,this._y=Math.atan2(a,p));break;case\\\\\\\"XZY\\\\\\\":this._z=Math.asin(-Object(o.d)(r,-1,1)),Math.abs(r)<.9999999?(this._x=Math.atan2(d,c),this._y=Math.atan2(a,s)):(this._x=Math.atan2(-h,p),this._y=0);break;default:console.warn(\\\\\\\"THREE.Euler: .setFromRotationMatrix() encountered an unknown order: \\\\\\\"+e)}return this._order=e,!0===n&&this._onChangeCallback(),this}setFromQuaternion(t,e,n){return a.makeRotationFromQuaternion(t),this.setFromRotationMatrix(a,e,n)}setFromVector3(t,e=this._order){return this.set(t.x,t.y,t.z,e)}reorder(t){return l.setFromEuler(this),this.setFromQuaternion(l,t)}equals(t){return t._x===this._x&&t._y===this._y&&t._z===this._z&&t._order===this._order}fromArray(t){return this._x=t[0],this._y=t[1],this._z=t[2],void 0!==t[3]&&(this._order=t[3]),this._onChangeCallback(),this}toArray(t=[],e=0){return t[e]=this._x,t[e+1]=this._y,t[e+2]=this._z,t[e+3]=this._order,t}toVector3(t){return t?t.set(this._x,this._y,this._z):new s.a(this._x,this._y,this._z)}_onChange(t){return this._onChangeCallback=t,this}_onChangeCallback(){}}c.prototype.isEuler=!0,c.DefaultOrder=\\\\\\\"XYZ\\\\\\\",c.RotationOrders=[\\\\\\\"XYZ\\\\\\\",\\\\\\\"YZX\\\\\\\",\\\\\\\"ZXY\\\\\\\",\\\\\\\"XZY\\\\\\\",\\\\\\\"YXZ\\\\\\\",\\\\\\\"ZYX\\\\\\\"]},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return s})),n.d(e,\\\\\\\"b\\\\\\\",(function(){return i}));class i{constructor(t,e,n){const i=this;let s,r=!1,o=0,a=0;const l=[];this.onStart=void 0,this.onLoad=t,this.onProgress=e,this.onError=n,this.itemStart=function(t){a++,!1===r&&void 0!==i.onStart&&i.onStart(t,o,a),r=!0},this.itemEnd=function(t){o++,void 0!==i.onProgress&&i.onProgress(t,o,a),o===a&&(r=!1,void 0!==i.onLoad&&i.onLoad())},this.itemError=function(t){void 0!==i.onError&&i.onError(t)},this.resolveURL=function(t){return s?s(t):t},this.setURLModifier=function(t){return s=t,this},this.addHandler=function(t,e){return l.push(t,e),this},this.removeHandler=function(t){const e=l.indexOf(t);return-1!==e&&l.splice(e,2),this},this.getHandler=function(t){for(let e=0,n=l.length;e1?null:e.copy(n).multiplyScalar(s).add(t.start)}intersectsLine(t){const e=this.distanceToPoint(t.start),n=this.distanceToPoint(t.end);return e<0&&n>0||n<0&&e>0}intersectsBox(t){return t.intersectsPlane(this)}intersectsSphere(t){return t.intersectsPlane(this)}coplanarPoint(t){return t.copy(this.normal).multiplyScalar(-this.constant)}applyMatrix4(t,e){const n=e||a.getNormalMatrix(t),i=this.coplanarPoint(r).applyMatrix4(t),s=this.normal.applyMatrix3(n).normalize();return this.constant=-i.dot(s),this}translate(t){return this.constant-=t.dot(this.normal),this}equals(t){return t.normal.equals(this.normal)&&t.constant===this.constant}clone(){return(new this.constructor).copy(this)}}l.prototype.isPlane=!0},function(t,e,n){\\\\\\\"use strict\\\\\\\";function i(t,e,n,i,s){const r=.5*(i-e),o=.5*(s-n),a=t*t;return(2*n-2*i+r+o)*(t*a)+(-3*n+3*i-2*r-o)*a+r*t+n}function s(t,e,n,i){return function(t,e){const n=1-t;return n*n*e}(t,e)+function(t,e){return 2*(1-t)*t*e}(t,n)+function(t,e){return t*t*e}(t,i)}function r(t,e,n,i,s){return function(t,e){const n=1-t;return n*n*n*e}(t,e)+function(t,e){const n=1-t;return 3*n*n*t*e}(t,n)+function(t,e){return 3*(1-t)*t*t*e}(t,i)+function(t,e){return t*t*t*e}(t,s)}n.d(e,\\\\\\\"a\\\\\\\",(function(){return i})),n.d(e,\\\\\\\"c\\\\\\\",(function(){return s})),n.d(e,\\\\\\\"b\\\\\\\",(function(){return r}))},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return r}));var i=n(10),s=n(6);class r extends i.a{constructor(t,e=1){super(),this.type=\\\\\\\"Light\\\\\\\",this.color=new s.a(t),this.intensity=e}dispose(){}copy(t){return super.copy(t),this.color.copy(t.color),this.intensity=t.intensity,this}toJSON(t){const e=super.toJSON(t);return e.object.color=this.color.getHex(),e.object.intensity=this.intensity,void 0!==this.groundColor&&(e.object.groundColor=this.groundColor.getHex()),void 0!==this.distance&&(e.object.distance=this.distance),void 0!==this.angle&&(e.object.angle=this.angle),void 0!==this.decay&&(e.object.decay=this.decay),void 0!==this.penumbra&&(e.object.penumbra=this.penumbra),void 0!==this.shadow&&(e.object.shadow=this.shadow.toJSON()),e}}r.prototype.isLight=!0},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return r}));var i=n(23),s=n(1);class r extends i.a{constructor(t=null,e=1,n=1,i,r,o,a,l,c=s.ob,h=s.ob,u,d){super(null,o,a,l,c,h,i,r,u,d),this.image={data:t,width:e,height:n},this.magFilter=c,this.minFilter=h,this.generateMipmaps=!1,this.flipY=!1,this.unpackAlignment=1,this.needsUpdate=!0}}r.prototype.isDataTexture=!0},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return l}));var i=n(41),s=n(0),r=n(4);const o=new s.a,a=new s.a;class l extends i.a{constructor(t,e){super(t,e),this.type=\\\\\\\"LineSegments\\\\\\\"}computeLineDistances(){const t=this.geometry;if(t.isBufferGeometry)if(null===t.index){const e=t.attributes.position,n=[];for(let t=0,i=e.count;t=s)break t;{const o=e[1];t=s)break e}r=n,n=0}}for(;n>>1;t0)if(p=l*h-c,_=l*c-h,f=s*d,p>=0)if(_>=-f)if(_<=f){const t=1/d;p*=t,_*=t,m=p*(p+l*_+2*c)+_*(l*p+_+2*h)+u}else _=s,p=Math.max(0,-(l*_+c)),m=-p*p+_*(_+2*h)+u;else _=-s,p=Math.max(0,-(l*_+c)),m=-p*p+_*(_+2*h)+u;else _<=-f?(p=Math.max(0,-(-l*s+c)),_=p>0?-s:Math.min(Math.max(-s,-h),s),m=-p*p+_*(_+2*h)+u):_<=f?(p=0,_=Math.min(Math.max(-s,-h),s),m=_*(_+2*h)+u):(p=Math.max(0,-(l*s+c)),_=p>0?s:Math.min(Math.max(-s,-h),s),m=-p*p+_*(_+2*h)+u);else _=l>0?-s:s,p=Math.max(0,-(l*_+c)),m=-p*p+_*(_+2*h)+u;return n&&n.copy(this.direction).multiplyScalar(p).add(this.origin),i&&i.copy(o).multiplyScalar(_).add(r),m}intersectSphere(t,e){s.subVectors(t.center,this.origin);const n=s.dot(this.direction),i=s.dot(s)-n*n,r=t.radius*t.radius;if(i>r)return null;const o=Math.sqrt(r-i),a=n-o,l=n+o;return a<0&&l<0?null:a<0?this.at(l,e):this.at(a,e)}intersectsSphere(t){return this.distanceSqToPoint(t.center)<=t.radius*t.radius}distanceToPlane(t){const e=t.normal.dot(this.direction);if(0===e)return 0===t.distanceToPoint(this.origin)?0:null;const n=-(this.origin.dot(t.normal)+t.constant)/e;return n>=0?n:null}intersectPlane(t,e){const n=this.distanceToPlane(t);return null===n?null:this.at(n,e)}intersectsPlane(t){const e=t.distanceToPoint(this.origin);if(0===e)return!0;return t.normal.dot(this.direction)*e<0}intersectBox(t,e){let n,i,s,r,o,a;const l=1/this.direction.x,c=1/this.direction.y,h=1/this.direction.z,u=this.origin;return l>=0?(n=(t.min.x-u.x)*l,i=(t.max.x-u.x)*l):(n=(t.max.x-u.x)*l,i=(t.min.x-u.x)*l),c>=0?(s=(t.min.y-u.y)*c,r=(t.max.y-u.y)*c):(s=(t.max.y-u.y)*c,r=(t.min.y-u.y)*c),n>r||s>i?null:((s>n||n!=n)&&(n=s),(r=0?(o=(t.min.z-u.z)*h,a=(t.max.z-u.z)*h):(o=(t.max.z-u.z)*h,a=(t.min.z-u.z)*h),n>a||o>i?null:((o>n||n!=n)&&(n=o),(a=0?n:i,e)))}intersectsBox(t){return null!==this.intersectBox(t,s)}intersectTriangle(t,e,n,i,s){l.subVectors(e,t),c.subVectors(n,t),h.crossVectors(l,c);let r,o=this.direction.dot(h);if(o>0){if(i)return null;r=1}else{if(!(o<0))return null;r=-1,o=-o}a.subVectors(this.origin,t);const u=r*this.direction.dot(c.crossVectors(a,c));if(u<0)return null;const d=r*this.direction.dot(l.cross(a));if(d<0)return null;if(u+d>o)return null;const p=-r*a.dot(h);return p<0?null:this.at(p/o,s)}applyMatrix4(t){return this.origin.applyMatrix4(t),this.direction.transformDirection(t),this}equals(t){return t.origin.equals(this.origin)&&t.direction.equals(this.direction)}clone(){return(new this.constructor).copy(this)}}},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return _}));var i=n(0);const s=new i.a,r=new i.a,o=new i.a,a=new i.a,l=new i.a,c=new i.a,h=new i.a,u=new i.a,d=new i.a,p=new i.a;class _{constructor(t=new i.a,e=new i.a,n=new i.a){this.a=t,this.b=e,this.c=n}static getNormal(t,e,n,i){i.subVectors(n,e),s.subVectors(t,e),i.cross(s);const r=i.lengthSq();return r>0?i.multiplyScalar(1/Math.sqrt(r)):i.set(0,0,0)}static getBarycoord(t,e,n,i,a){s.subVectors(i,e),r.subVectors(n,e),o.subVectors(t,e);const l=s.dot(s),c=s.dot(r),h=s.dot(o),u=r.dot(r),d=r.dot(o),p=l*u-c*c;if(0===p)return a.set(-2,-1,-1);const _=1/p,m=(u*h-c*d)*_,f=(l*d-c*h)*_;return a.set(1-m-f,f,m)}static containsPoint(t,e,n,i){return this.getBarycoord(t,e,n,i,a),a.x>=0&&a.y>=0&&a.x+a.y<=1}static getUV(t,e,n,i,s,r,o,l){return this.getBarycoord(t,e,n,i,a),l.set(0,0),l.addScaledVector(s,a.x),l.addScaledVector(r,a.y),l.addScaledVector(o,a.z),l}static isFrontFacing(t,e,n,i){return s.subVectors(n,e),r.subVectors(t,e),s.cross(r).dot(i)<0}set(t,e,n){return this.a.copy(t),this.b.copy(e),this.c.copy(n),this}setFromPointsAndIndices(t,e,n,i){return this.a.copy(t[e]),this.b.copy(t[n]),this.c.copy(t[i]),this}setFromAttributeAndIndices(t,e,n,i){return this.a.fromBufferAttribute(t,e),this.b.fromBufferAttribute(t,n),this.c.fromBufferAttribute(t,i),this}clone(){return(new this.constructor).copy(this)}copy(t){return this.a.copy(t.a),this.b.copy(t.b),this.c.copy(t.c),this}getArea(){return s.subVectors(this.c,this.b),r.subVectors(this.a,this.b),.5*s.cross(r).length()}getMidpoint(t){return t.addVectors(this.a,this.b).add(this.c).multiplyScalar(1/3)}getNormal(t){return _.getNormal(this.a,this.b,this.c,t)}getPlane(t){return t.setFromCoplanarPoints(this.a,this.b,this.c)}getBarycoord(t,e){return _.getBarycoord(t,this.a,this.b,this.c,e)}getUV(t,e,n,i,s){return _.getUV(t,this.a,this.b,this.c,e,n,i,s)}containsPoint(t){return _.containsPoint(t,this.a,this.b,this.c)}isFrontFacing(t){return _.isFrontFacing(this.a,this.b,this.c,t)}intersectsBox(t){return t.intersectsTriangle(this)}closestPointToPoint(t,e){const n=this.a,i=this.b,s=this.c;let r,o;l.subVectors(i,n),c.subVectors(s,n),u.subVectors(t,n);const a=l.dot(u),_=c.dot(u);if(a<=0&&_<=0)return e.copy(n);d.subVectors(t,i);const m=l.dot(d),f=c.dot(d);if(m>=0&&f<=m)return e.copy(i);const g=a*f-m*_;if(g<=0&&a>=0&&m<=0)return r=a/(a-m),e.copy(n).addScaledVector(l,r);p.subVectors(t,s);const v=l.dot(p),y=c.dot(p);if(y>=0&&v<=y)return e.copy(s);const x=v*_-a*y;if(x<=0&&_>=0&&y<=0)return o=_/(_-y),e.copy(n).addScaledVector(c,o);const b=m*y-v*f;if(b<=0&&f-m>=0&&v-y>=0)return h.subVectors(s,i),o=(f-m)/(f-m+(v-y)),e.copy(i).addScaledVector(h,o);const w=1/(b+x+g);return r=x*w,o=g*w,e.copy(n).addScaledVector(l,r).addScaledVector(c,o)}equals(t){return t.a.equals(this.a)&&t.b.equals(this.b)&&t.c.equals(this.c)}}},function(t,e,n){\\\\\\\"use strict\\\\\\\";n.d(e,\\\\\\\"a\\\\\\\",(function(){return f}));var i=n(18),s=n(39),r=n(5),o=n(10),a=n(0),l=n(24),c=n(7),h=n(4);const u=new a.a,d=new a.a,p=new r.a,_=new s.a,m=new i.a;class f extends o.a{constructor(t=new c.a,e=new l.a){super(),this.type=\\\\\\\"Line\\\\\\\",this.geometry=t,this.material=e,this.updateMorphTargets()}copy(t){return super.copy(t),this.material=t.material,this.geometry=t.geometry,this}computeLineDistances(){const t=this.geometry;if(t.isBufferGeometry)if(null===t.index){const e=t.attributes.position,n=[0];for(let t=1,i=e.count;tl)continue;d.applyMatrix4(this.matrixWorld);const a=t.ray.origin.distanceTo(d);at.far||e.push({distance:a,point:u.clone().applyMatrix4(this.matrixWorld),index:n,face:null,faceIndex:null,object:this})}}else{for(let n=Math.max(0,r.start),i=Math.min(s.count,r.start+r.count)-1;nl)continue;d.applyMatrix4(this.matrixWorld);const i=t.ray.origin.distanceTo(d);it.far||e.push({distance:i,point:u.clone().applyMatrix4(this.matrixWorld),index:n,face:null,faceIndex:null,object:this})}}}else n.isGeometry&&console.error(\\\\\\\"THREE.Line.raycast() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}updateMorphTargets(){const t=this.geometry;if(t.isBufferGeometry){const e=t.morphAttributes,n=Object.keys(e);if(n.length>0){const t=e[n[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,n=t.length;e0&&console.error(\\\\\\\"THREE.Line.updateMorphTargets() does not support THREE.Geometry. 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e.set((t.x-this.min.x)/(this.max.x-this.min.x),(t.y-this.min.y)/(this.max.y-this.min.y))}intersectsBox(t){return!(t.max.xthis.max.x||t.max.ythis.max.y)}clampPoint(t,e){return e.copy(t).clamp(this.min,this.max)}distanceToPoint(t){return s.copy(t).clamp(this.min,this.max).sub(t).length()}intersect(t){return this.min.max(t.min),this.max.min(t.max),this}union(t){return this.min.min(t.min),this.max.max(t.max),this}translate(t){return this.min.add(t),this.max.add(t),this}equals(t){return t.min.equals(this.min)&&t.max.equals(this.max)}}r.prototype.isBox2=!0;var o=n(7),a=n(22),l=n(4),c=n(13),h=n(11),u=n(47),d=n(46),p=n(48),_=n(53),m=n(0);class f extends c.a{constructor(t){super(t),this.defaultDPI=90,this.defaultUnit=\\\\\\\"px\\\\\\\"}load(t,e,n,i){const s=this,r=new a.a(s.manager);r.setPath(s.path),r.setRequestHeader(s.requestHeader),r.setWithCredentials(s.withCredentials),r.load(t,(function(n){try{e(s.parse(n))}catch(e){i?i(e):console.error(e),s.manager.itemError(t)}}),n,i)}parse(t){const e=this;function n(t,e,n,i,r,o,a,l){if(0==e||0==n)return void t.lineTo(l.x,l.y);i=i*Math.PI/180,e=Math.abs(e),n=Math.abs(n);const c=(a.x-l.x)/2,h=(a.y-l.y)/2,u=Math.cos(i)*c+Math.sin(i)*h,d=-Math.sin(i)*c+Math.cos(i)*h;let p=e*e,_=n*n;const m=u*u,f=d*d,g=m/p+f/_;if(g>1){const t=Math.sqrt(g);p=(e*=t)*e,_=(n*=t)*n}const v=p*f+_*m,y=(p*_-v)/v;let x=Math.sqrt(Math.max(0,y));r===o&&(x=-x);const b=x*e*d/n,w=-x*n*u/e,T=Math.cos(i)*b-Math.sin(i)*w+(a.x+l.x)/2,A=Math.sin(i)*b+Math.cos(i)*w+(a.y+l.y)/2,M=s(1,0,(u-b)/e,(d-w)/n),E=s((u-b)/e,(d-w)/n,(-u-b)/e,(-d-w)/n)%(2*Math.PI);t.currentPath.absellipse(T,A,e,n,M,M+E,0===o,i)}function s(t,e,n,i){const s=t*n+e*i,r=Math.sqrt(t*t+e*e)*Math.sqrt(n*n+i*i);let o=Math.acos(Math.max(-1,Math.min(1,s/r)));return t*i-e*n<0&&(o=-o),o}function r(t,e){e=Object.assign({},e);let n={};if(t.hasAttribute(\\\\\\\"class\\\\\\\")){const e=t.getAttribute(\\\\\\\"class\\\\\\\").split(/\\\\s/).filter(Boolean).map((t=>t.trim()));for(let t=0;t=0;t--){const s=i[t].trim();if(\\\\\\\"\\\\\\\"===s)continue;const r=s.indexOf(\\\\\\\"(\\\\\\\"),o=s.length;if(r>0&&r=1){const t=e[0];let i=t;e.length>=2&&(i=e[1]),n.translate(t,i)}break;case\\\\\\\"rotate\\\\\\\":if(e.length>=1){let t=0,i=0,s=0;t=-e[0]*Math.PI/180,e.length>=3&&(i=e[1],s=e[2]),b.identity().translate(-i,-s),w.identity().rotate(t),T.multiplyMatrices(w,b),b.identity().translate(i,s),n.multiplyMatrices(b,T)}break;case\\\\\\\"scale\\\\\\\":if(e.length>=1){const t=e[0];let i=t;e.length>=2&&(i=e[1]),n.scale(t,i)}break;case\\\\\\\"skewX\\\\\\\":1===e.length&&n.set(1,Math.tan(e[0]*Math.PI/180),0,0,1,0,0,0,1);break;case\\\\\\\"skewY\\\\\\\":1===e.length&&n.set(1,0,0,Math.tan(e[0]*Math.PI/180),1,0,0,0,1);break;case\\\\\\\"matrix\\\\\\\":6===e.length&&n.set(e[0],e[2],e[4],e[1],e[3],e[5],0,0,1)}}e.premultiply(n)}}return e}(t);y.length>0&&e.premultiply(y[y.length-1]);return E.copy(e),y.push(e),e}(e);let c=!0,m=null;switch(e.nodeName){case\\\\\\\"svg\\\\\\\":break;case\\\\\\\"style\\\\\\\":!function(t){if(!t.sheet||!t.sheet.cssRules||!t.sheet.cssRules.length)return;for(let e=0;et.trim()));for(let t=0;t0&&(s.copy(l),e.currentPath.currentPoint.copy(s),c=!0);break;default:console.warn(i)}h=!1}return e}(e));break;case\\\\\\\"rect\\\\\\\":s=r(e,s),m=function(t){const e=d(t.getAttribute(\\\\\\\"x\\\\\\\")||0),n=d(t.getAttribute(\\\\\\\"y\\\\\\\")||0),i=d(t.getAttribute(\\\\\\\"rx\\\\\\\")||t.getAttribute(\\\\\\\"ry\\\\\\\")||0),s=d(t.getAttribute(\\\\\\\"ry\\\\\\\")||t.getAttribute(\\\\\\\"rx\\\\\\\")||0),r=d(t.getAttribute(\\\\\\\"width\\\\\\\")),o=d(t.getAttribute(\\\\\\\"height\\\\\\\")),a=.448084975506,l=new p.a;l.moveTo(e+i,n),l.lineTo(e+r-i,n),(0!==i||0!==s)&&l.bezierCurveTo(e+r-i*a,n,e+r,n+s*a,e+r,n+s);l.lineTo(e+r,n+o-s),(0!==i||0!==s)&&l.bezierCurveTo(e+r,n+o-s*a,e+r-i*a,n+o,e+r-i,n+o);l.lineTo(e+i,n+o),(0!==i||0!==s)&&l.bezierCurveTo(e+i*a,n+o,e,n+o-s*a,e,n+o-s);l.lineTo(e,n+s),(0!==i||0!==s)&&l.bezierCurveTo(e,n+s*a,e+i*a,n,e+i,n);return l}(e);break;case\\\\\\\"polygon\\\\\\\":s=r(e,s),m=function(t){function e(t,e,n){const r=d(e),o=d(n);0===s?i.moveTo(r,o):i.lineTo(r,o),s++}const n=/(-?[\\\\d\\\\.?]+)[,|\\\\s](-?[\\\\d\\\\.?]+)/g,i=new p.a;let s=0;return t.getAttribute(\\\\\\\"points\\\\\\\").replace(n,e),i.currentPath.autoClose=!0,i}(e);break;case\\\\\\\"polyline\\\\\\\":s=r(e,s),m=function(t){function e(t,e,n){const r=d(e),o=d(n);0===s?i.moveTo(r,o):i.lineTo(r,o),s++}const n=/(-?[\\\\d\\\\.?]+)[,|\\\\s](-?[\\\\d\\\\.?]+)/g,i=new p.a;let s=0;return t.getAttribute(\\\\\\\"points\\\\\\\").replace(n,e),i.currentPath.autoClose=!1,i}(e);break;case\\\\\\\"circle\\\\\\\":s=r(e,s),m=function(t){const e=d(t.getAttribute(\\\\\\\"cx\\\\\\\")||0),n=d(t.getAttribute(\\\\\\\"cy\\\\\\\")||0),i=d(t.getAttribute(\\\\\\\"r\\\\\\\")||0),s=new u.a;s.absarc(e,n,i,0,2*Math.PI);const r=new p.a;return r.subPaths.push(s),r}(e);break;case\\\\\\\"ellipse\\\\\\\":s=r(e,s),m=function(t){const e=d(t.getAttribute(\\\\\\\"cx\\\\\\\")||0),n=d(t.getAttribute(\\\\\\\"cy\\\\\\\")||0),i=d(t.getAttribute(\\\\\\\"rx\\\\\\\")||0),s=d(t.getAttribute(\\\\\\\"ry\\\\\\\")||0),r=new u.a;r.absellipse(e,n,i,s,0,2*Math.PI);const o=new p.a;return o.subPaths.push(r),o}(e);break;case\\\\\\\"line\\\\\\\":s=r(e,s),m=function(t){const e=d(t.getAttribute(\\\\\\\"x1\\\\\\\")||0),n=d(t.getAttribute(\\\\\\\"y1\\\\\\\")||0),i=d(t.getAttribute(\\\\\\\"x2\\\\\\\")||0),s=d(t.getAttribute(\\\\\\\"y2\\\\\\\")||0),r=new p.a;return r.moveTo(e,n),r.lineTo(i,s),r.currentPath.autoClose=!1,r}(e);break;case\\\\\\\"defs\\\\\\\":c=!1;break;case\\\\\\\"use\\\\\\\":s=r(e,s);const l=e.href.baseVal.substring(1),h=e.viewportElement.getElementById(l);h?t(h,s):console.warn(\\\\\\\"SVGLoader: 'use node' references non-existent node id: \\\\\\\"+l)}if(m&&(void 0!==s.fill&&\\\\\\\"none\\\\\\\"!==s.fill&&m.color.setStyle(s.fill),function(t,e){function n(t){M.set(t.x,t.y,1).applyMatrix3(e),t.set(M.x,M.y)}const i=function(t){return 0!==t.elements[1]||0!==t.elements[3]}(e),s=t.subPaths;for(let t=0,r=s.length;t0?E.copy(y[y.length-1]):E.identity())}(S.documentElement,{fill:\\\\\\\"#000\\\\\\\",fillOpacity:1,strokeOpacity:1,strokeWidth:1,strokeLineJoin:\\\\\\\"miter\\\\\\\",strokeLineCap:\\\\\\\"butt\\\\\\\",strokeMiterLimit:4});return{paths:g,xml:S.documentElement}}static createShapes(t){const e=999999999,n=0,s=1,o=2,a=3,l=4,c=5,h=6,p={loc:n,t:0};function m(t,e,i,s){const r=t.x,a=e.x,l=i.x,c=s.x,h=t.y,u=e.y,d=i.y,_=s.y,m=(c-l)*(h-d)-(_-d)*(r-l),g=(_-d)*(a-r)-(c-l)*(u-h),v=m/g,y=((a-r)*(h-d)-(u-h)*(r-l))/g;if(0===g&&0!==m||v<=0||v>=1||y<0||y>1)return null;if(0===m&&0===g){for(let l=0;l<2;l++){if(f(0===l?i:s,t,e),p.loc==n){const t=0===l?i:s;return{x:t.x,y:t.y,t:p.t}}if(p.loc==o){return{x:+(r+p.t*(a-r)).toPrecision(10),y:+(h+p.t*(u-h)).toPrecision(10),t:p.t}}}return null}for(let r=0;r<2;r++)if(f(0===r?i:s,t,e),p.loc==n){const t=0===r?i:s;return{x:t.x,y:t.y,t:p.t}}return{x:+(r+v*(a-r)).toPrecision(10),y:+(h+v*(u-h)).toPrecision(10),t:v}}function f(t,e,i){const r=i.x-e.x,u=i.y-e.y,d=t.x-e.x,_=t.y-e.y,m=r*_-d*u;if(t.x===e.x&&t.y===e.y)return p.loc=n,void(p.t=0);if(t.x===i.x&&t.y===i.y)return p.loc=s,void(p.t=1);if(m<-Number.EPSILON)return void(p.loc=a);if(m>Number.EPSILON)return void(p.loc=l);if(r*d<0||u*_<0)return void(p.loc=c);if(Math.sqrt(r*r+u*u){if(e.boundingBox.containsPoint(s)){(function(t,e){const n=[],s=[];for(let 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null!=this._nodes_by_id.get(t.graphNodeId())}addNode(t){this._nodes_by_id.set(t.graphNodeId(),t),this._nodesCount+=1,this._debugging&&this._addedNodesDuringDebugging.set(t.graphNodeId(),t)}removeNode(t){this._nodes_by_id.delete(t.graphNodeId()),this._successors.delete(t.graphNodeId()),this._predecessors.delete(t.graphNodeId()),this._nodesCount-=1,this._debugging&&this._addedNodesDuringDebugging.delete(t.graphNodeId())}nodesCount(){return this._nodesCount}connect(t,e,n=!0){const i=t.graphNodeId(),s=e.graphNodeId();if(this.hasNode(t)&&this.hasNode(e)){if(n){n=!(!this._scene||this._scene.loadingController.isLoading())}let e=!1;return n&&(e=this._hasPredecessor(i,s)),!e&&(this._createConnection(i,s),t.dirtyController.clearSuccessorsCacheWithPredecessors(),!0)}return console.warn(`attempt to connect non existing node ${i} or ${s}`),!1}disconnect(t,e){this._remove_connection(t.graphNodeId(),e.graphNodeId()),t.dirtyController.clearSuccessorsCacheWithPredecessors()}disconnectPredecessors(t){const e=this.predecessors(t);for(let n of e)this.disconnect(n,t)}disconnectSuccessors(t){const e=this.successors(t);for(let n of e)this.disconnect(t,n)}predecessorIds(t){const e=this._predecessors.get(t);if(e){const t=[];return e.forEach(((e,n)=>{t.push(n)})),t}return[]}predecessors(t){const e=this.predecessorIds(t.graphNodeId());return this.nodesFromIds(e)}successorIds(t){const e=this._successors.get(t);if(e){const t=[];return e.forEach(((e,n)=>{t.push(n)})),t}return[]}successors(t){const e=this.successorIds(t.graphNodeId())||[];return this.nodesFromIds(e)}allPredecessorIds(t){return this.allNextIds(t,\\\\\\\"predecessorIds\\\\\\\")}allSuccessorIds(t){return this.allNextIds(t,\\\\\\\"successorIds\\\\\\\")}allPredecessors(t){const e=this.allPredecessorIds(t);return this.nodesFromIds(e)}allSuccessors(t){const 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c{constructor(t){this._node=t,this._cooks_count=0,this._total_cook_time=0,this._total_inputs_time=0,this._total_params_time=0}update_cook_data(t){this._cooks_count+=1,this._total_cook_time+=t.cookTime,this._total_inputs_time+=t.inputsTime,this._total_params_time+=t.paramsTime}total_time(){return this._total_cook_time+this._total_inputs_time+this._total_params_time}total_cook_time(){return this._total_cook_time}cook_time_per_iteration(){return this._cooks_count>0?this._total_cook_time/this._cooks_count:0}total_inputs_time(){return this._total_inputs_time}inputs_time_per_iteration(){return this._cooks_count>0?this._total_inputs_time/this._cooks_count:0}total_params_time2(){return this._total_params_time}params_time_per_iteration2(){return this._cooks_count>0?this._total_params_time/this._cooks_count:0}cooks_count(){return 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NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t\\\\tuniform sampler2D directionalShadowMap[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t\\\\tstruct DirectionalLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t};\\\\n\\\\n\\\\t\\\\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t\\\\tuniform sampler2D spotShadowMap[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vSpotShadowCoord[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t\\\\tstruct SpotLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t};\\\\n\\\\n\\\\t\\\\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t\\\\tuniform sampler2D pointShadowMap[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t\\\\tstruct PointLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t\\\\tfloat shadowCameraNear;\\\\n\\\\t\\\\t\\\\tfloat shadowCameraFar;\\\\n\\\\t\\\\t};\\\\n\\\\n\\\\t\\\\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t/*\\\\n\\\\t#if NUM_RECT_AREA_LIGHTS > 0\\\\n\\\\n\\\\t\\\\t// TODO (abelnation): create uniforms for area light shadows\\\\n\\\\n\\\\t#endif\\\\n\\\\t*/\\\\n\\\\n\\\\tfloat texture2DCompare( sampler2D depths, vec2 uv, float compare ) {\\\\n\\\\n\\\\t\\\\treturn step( compare, unpackRGBAToDepth( 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softness_probability ), 0.0, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\treturn occlusion;\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tfloat getShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord ) {\\\\n\\\\n\\\\t\\\\tfloat shadow = 1.0;\\\\n\\\\n\\\\t\\\\tshadowCoord.xyz /= shadowCoord.w;\\\\n\\\\t\\\\tshadowCoord.z += shadowBias;\\\\n\\\\n\\\\t\\\\t// if ( something && something ) breaks ATI OpenGL shader compiler\\\\n\\\\t\\\\t// if ( all( something, something ) ) using this instead\\\\n\\\\n\\\\t\\\\tbvec4 inFrustumVec = bvec4 ( shadowCoord.x >= 0.0, shadowCoord.x <= 1.0, shadowCoord.y >= 0.0, shadowCoord.y <= 1.0 );\\\\n\\\\t\\\\tbool inFrustum = all( inFrustumVec );\\\\n\\\\n\\\\t\\\\tbvec2 frustumTestVec = bvec2( inFrustum, shadowCoord.z <= 1.0 );\\\\n\\\\n\\\\t\\\\tbool frustumTest = all( frustumTestVec );\\\\n\\\\n\\\\t\\\\tif ( frustumTest ) {\\\\n\\\\n\\\\t\\\\t#if defined( SHADOWMAP_TYPE_PCF )\\\\n\\\\n\\\\t\\\\t\\\\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\\\\n\\\\n\\\\t\\\\t\\\\tfloat dx0 = - texelSize.x * shadowRadius;\\\\n\\\\t\\\\t\\\\tfloat dy0 = - texelSize.y * shadowRadius;\\\\n\\\\t\\\\t\\\\tfloat dx1 = + texelSize.x * shadowRadius;\\\\n\\\\t\\\\t\\\\tfloat dy1 = + texelSize.y * shadowRadius;\\\\n\\\\t\\\\t\\\\tfloat dx2 = dx0 / 2.0;\\\\n\\\\t\\\\t\\\\tfloat dy2 = dy0 / 2.0;\\\\n\\\\t\\\\t\\\\tfloat dx3 = dx1 / 2.0;\\\\n\\\\t\\\\t\\\\tfloat dy3 = dy1 / 2.0;\\\\n\\\\n\\\\t\\\\t\\\\tshadow = (\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy2 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy2 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy2 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy3 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy3 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy3 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy1 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy1 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy1 ), shadowCoord.z )\\\\n\\\\t\\\\t\\\\t) * ( 1.0 / 17.0 );\\\\n\\\\n\\\\t\\\\t#elif defined( SHADOWMAP_TYPE_PCF_SOFT )\\\\n\\\\n\\\\t\\\\t\\\\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\\\\n\\\\t\\\\t\\\\tfloat dx = texelSize.x;\\\\n\\\\t\\\\t\\\\tfloat dy = texelSize.y;\\\\n\\\\n\\\\t\\\\t\\\\tvec2 uv = shadowCoord.xy;\\\\n\\\\t\\\\t\\\\tvec2 f = fract( uv * shadowMapSize + 0.5 );\\\\n\\\\t\\\\t\\\\tuv -= f * texelSize;\\\\n\\\\n\\\\t\\\\t\\\\tshadow = (\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, uv, shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, uv + vec2( dx, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, uv + vec2( 0.0, dy ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, uv + texelSize, shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, 0.0 ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 0.0 ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.x ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.x ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( texture2DCompare( shadowMap, uv + vec2( 0.0, -dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 0.0, 2.0 * dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.y ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( texture2DCompare( shadowMap, uv + vec2( dx, -dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( dx, 2.0 * dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.y ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( mix( texture2DCompare( shadowMap, uv + vec2( -dx, -dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, -dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t f.x ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t mix( texture2DCompare( shadowMap, uv + vec2( -dx, 2.0 * dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 2.0 * dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t f.x ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.y )\\\\n\\\\t\\\\t\\\\t) * ( 1.0 / 9.0 );\\\\n\\\\n\\\\t\\\\t#elif defined( SHADOWMAP_TYPE_VSM )\\\\n\\\\n\\\\t\\\\t\\\\tshadow = VSMShadow( shadowMap, shadowCoord.xy, shadowCoord.z );\\\\n\\\\n\\\\t\\\\t#else // no percentage-closer filtering:\\\\n\\\\n\\\\t\\\\t\\\\tshadow = texture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\treturn shadow;\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\t// cubeToUV() maps a 3D direction vector suitable for cube texture mapping to a 2D\\\\n\\\\t// vector suitable for 2D texture mapping. This code uses the following layout for the\\\\n\\\\t// 2D texture:\\\\n\\\\t//\\\\n\\\\t// xzXZ\\\\n\\\\t// y Y\\\\n\\\\t//\\\\n\\\\t// Y - Positive y direction\\\\n\\\\t// y - Negative y direction\\\\n\\\\t// X - Positive x direction\\\\n\\\\t// x - Negative x direction\\\\n\\\\t// Z - Positive z direction\\\\n\\\\t// z - Negative z direction\\\\n\\\\t//\\\\n\\\\t// Source and test bed:\\\\n\\\\t// https://gist.github.com/tschw/da10c43c467ce8afd0c4\\\\n\\\\n\\\\tvec2 cubeToUV( vec3 v, float texelSizeY ) {\\\\n\\\\n\\\\t\\\\t// Number of texels to avoid at the edge of each square\\\\n\\\\n\\\\t\\\\tvec3 absV = abs( v );\\\\n\\\\n\\\\t\\\\t// Intersect unit cube\\\\n\\\\n\\\\t\\\\tfloat scaleToCube = 1.0 / max( absV.x, max( absV.y, absV.z ) );\\\\n\\\\t\\\\tabsV *= scaleToCube;\\\\n\\\\n\\\\t\\\\t// Apply scale to avoid seams\\\\n\\\\n\\\\t\\\\t// two texels less per square (one texel will do for NEAREST)\\\\n\\\\t\\\\tv *= scaleToCube * ( 1.0 - 2.0 * texelSizeY );\\\\n\\\\n\\\\t\\\\t// Unwrap\\\\n\\\\n\\\\t\\\\t// space: -1 ... 1 range for each square\\\\n\\\\t\\\\t//\\\\n\\\\t\\\\t// #X##\\\\t\\\\tdim := ( 4 , 2 )\\\\n\\\\t\\\\t// # #\\\\t\\\\tcenter := ( 1 , 1 )\\\\n\\\\n\\\\t\\\\tvec2 planar = v.xy;\\\\n\\\\n\\\\t\\\\tfloat almostATexel = 1.5 * texelSizeY;\\\\n\\\\t\\\\tfloat almostOne = 1.0 - almostATexel;\\\\n\\\\n\\\\t\\\\tif ( absV.z >= almostOne ) {\\\\n\\\\n\\\\t\\\\t\\\\tif ( v.z > 0.0 )\\\\n\\\\t\\\\t\\\\t\\\\tplanar.x = 4.0 - v.x;\\\\n\\\\n\\\\t\\\\t} else if ( absV.x >= almostOne ) {\\\\n\\\\n\\\\t\\\\t\\\\tfloat signX = sign( v.x );\\\\n\\\\t\\\\t\\\\tplanar.x = v.z * signX + 2.0 * signX;\\\\n\\\\n\\\\t\\\\t} else if ( absV.y >= almostOne ) {\\\\n\\\\n\\\\t\\\\t\\\\tfloat signY = sign( v.y );\\\\n\\\\t\\\\t\\\\tplanar.x = v.x + 2.0 * signY + 2.0;\\\\n\\\\t\\\\t\\\\tplanar.y = v.z * signY - 2.0;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t// Transform to UV space\\\\n\\\\n\\\\t\\\\t// scale := 0.5 / dim\\\\n\\\\t\\\\t// translate := ( center + 0.5 ) / dim\\\\n\\\\t\\\\treturn vec2( 0.125, 0.25 ) * planar + vec2( 0.375, 0.75 );\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tfloat getPointShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord, float shadowCameraNear, float shadowCameraFar ) {\\\\n\\\\n\\\\t\\\\tvec2 texelSize = vec2( 1.0 ) / ( shadowMapSize * vec2( 4.0, 2.0 ) );\\\\n\\\\n\\\\t\\\\t// for point lights, the uniform @vShadowCoord is re-purposed to hold\\\\n\\\\t\\\\t// the vector from the light to the world-space position of the fragment.\\\\n\\\\t\\\\tvec3 lightToPosition = shadowCoord.xyz;\\\\n\\\\n\\\\t\\\\t// dp = normalized distance from light to fragment position\\\\n\\\\t\\\\tfloat dp = ( length( lightToPosition ) - shadowCameraNear ) / ( shadowCameraFar - shadowCameraNear ); // need to clamp?\\\\n\\\\t\\\\tdp += shadowBias;\\\\n\\\\n\\\\t\\\\t// bd3D = base direction 3D\\\\n\\\\t\\\\tvec3 bd3D = normalize( lightToPosition );\\\\n\\\\n\\\\t\\\\t#if defined( SHADOWMAP_TYPE_PCF ) || defined( SHADOWMAP_TYPE_PCF_SOFT ) || defined( SHADOWMAP_TYPE_VSM )\\\\n\\\\n\\\\t\\\\t\\\\tvec2 offset = vec2( - 1, 1 ) * shadowRadius * texelSize.y;\\\\n\\\\n\\\\t\\\\t\\\\treturn (\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyy, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyy, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyx, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyx, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxy, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxy, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxx, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxx, texelSize.y ), dp )\\\\n\\\\t\\\\t\\\\t) * ( 1.0 / 9.0 );\\\\n\\\\n\\\\t\\\\t#else // no percentage-closer filtering\\\\n\\\\n\\\\t\\\\t\\\\treturn texture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\\\\",k=\\\\\\\"\\\\n#ifdef USE_TRANSMISSION\\\\n\\\\n\\\\tfloat transmissionAlpha = 1.0;\\\\n\\\\tfloat transmissionFactor = transmission;\\\\n\\\\tfloat thicknessFactor = thickness;\\\\n\\\\n\\\\t#ifdef USE_TRANSMISSIONMAP\\\\n\\\\n\\\\t\\\\ttransmissionFactor *= texture2D( transmissionMap, vUv ).r;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef USE_THICKNESSMAP\\\\n\\\\n\\\\t\\\\tthicknessFactor *= texture2D( thicknessMap, vUv ).g;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tvec3 pos = vWorldPosition;\\\\n\\\\tvec3 v = normalize( cameraPosition - pos );\\\\n\\\\tvec3 n = inverseTransformDirection( normal, viewMatrix );\\\\n\\\\n\\\\tvec4 transmission = getIBLVolumeRefraction(\\\\n\\\\t\\\\tn, v, roughnessFactor, material.diffuseColor, material.specularColor, material.specularF90,\\\\n\\\\t\\\\tpos, modelMatrix, viewMatrix, projectionMatrix, ior, thicknessFactor,\\\\n\\\\t\\\\tattenuationTint, attenuationDistance );\\\\n\\\\n\\\\ttotalDiffuse = mix( totalDiffuse, transmission.rgb, transmissionFactor );\\\\n\\\\ttransmissionAlpha = mix( transmissionAlpha, transmission.a, transmissionFactor );\\\\n#endif\\\\n\\\\\\\";const U={alphamap_fragment:\\\\\\\"\\\\n#ifdef USE_ALPHAMAP\\\\n\\\\n\\\\tdiffuseColor.a *= texture2D( alphaMap, vUv ).g;\\\\n\\\\n#endif\\\\n\\\\\\\",alphamap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_ALPHAMAP\\\\n\\\\n\\\\tuniform sampler2D alphaMap;\\\\n\\\\n#endif\\\\n\\\\\\\",alphatest_fragment:\\\\\\\"\\\\n#ifdef USE_ALPHATEST\\\\n\\\\n\\\\tif ( diffuseColor.a < alphaTest ) discard;\\\\n\\\\n#endif\\\\n\\\\\\\",alphatest_pars_fragment:\\\\\\\"\\\\n#ifdef USE_ALPHATEST\\\\n\\\\tuniform float alphaTest;\\\\n#endif\\\\n\\\\\\\",aomap_fragment:\\\\\\\"\\\\n#ifdef USE_AOMAP\\\\n\\\\n\\\\t// reads channel R, compatible with a combined OcclusionRoughnessMetallic (RGB) texture\\\\n\\\\tfloat ambientOcclusion = ( texture2D( aoMap, vUv2 ).r - 1.0 ) * aoMapIntensity + 1.0;\\\\n\\\\n\\\\treflectedLight.indirectDiffuse *= ambientOcclusion;\\\\n\\\\n\\\\t#if defined( USE_ENVMAP ) && defined( STANDARD )\\\\n\\\\n\\\\t\\\\tfloat dotNV = saturate( dot( geometry.normal, geometry.viewDir ) );\\\\n\\\\n\\\\t\\\\treflectedLight.indirectSpecular *= computeSpecularOcclusion( dotNV, ambientOcclusion, material.roughness );\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",aomap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_AOMAP\\\\n\\\\n\\\\tuniform sampler2D aoMap;\\\\n\\\\tuniform float aoMapIntensity;\\\\n\\\\n#endif\\\\n\\\\\\\",begin_vertex:\\\\\\\"\\\\nvec3 transformed = vec3( position );\\\\n\\\\\\\",beginnormal_vertex:\\\\\\\"\\\\nvec3 objectNormal = vec3( normal );\\\\n\\\\n#ifdef USE_TANGENT\\\\n\\\\n\\\\tvec3 objectTangent = vec3( tangent.xyz );\\\\n\\\\n#endif\\\\n\\\\\\\",bsdfs:'\\\\n\\\\nvec3 BRDF_Lambert( const in vec3 diffuseColor ) {\\\\n\\\\n\\\\treturn RECIPROCAL_PI * diffuseColor;\\\\n\\\\n} // validated\\\\n\\\\nvec3 F_Schlick( const in vec3 f0, const in float f90, const in float dotVH ) {\\\\n\\\\n\\\\t// Original approximation by Christophe Schlick \\\\'94\\\\n\\\\t// float fresnel = pow( 1.0 - dotVH, 5.0 );\\\\n\\\\n\\\\t// Optimized variant (presented by Epic at SIGGRAPH \\\\'13)\\\\n\\\\t// https://cdn2.unrealengine.com/Resources/files/2013SiggraphPresentationsNotes-26915738.pdf\\\\n\\\\tfloat fresnel = exp2( ( - 5.55473 * dotVH - 6.98316 ) * dotVH );\\\\n\\\\n\\\\treturn f0 * ( 1.0 - fresnel ) + ( f90 * fresnel );\\\\n\\\\n} // validated\\\\n\\\\n// Moving Frostbite to Physically Based Rendering 3.0 - page 12, listing 2\\\\n// https://seblagarde.files.wordpress.com/2015/07/course_notes_moving_frostbite_to_pbr_v32.pdf\\\\nfloat V_GGX_SmithCorrelated( const in float alpha, const in float dotNL, const in float dotNV ) {\\\\n\\\\n\\\\tfloat a2 = pow2( alpha );\\\\n\\\\n\\\\tfloat gv = dotNL * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNV ) );\\\\n\\\\tfloat gl = dotNV * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNL ) );\\\\n\\\\n\\\\treturn 0.5 / max( gv + gl, EPSILON );\\\\n\\\\n}\\\\n\\\\n// Microfacet Models for Refraction through Rough Surfaces - equation (33)\\\\n// http://graphicrants.blogspot.com/2013/08/specular-brdf-reference.html\\\\n// alpha is \\\\\\\"roughness squared\\\\\\\" in Disney’s reparameterization\\\\nfloat D_GGX( const in float alpha, const in float dotNH ) {\\\\n\\\\n\\\\tfloat a2 = pow2( alpha );\\\\n\\\\n\\\\tfloat denom = pow2( dotNH ) * ( a2 - 1.0 ) + 1.0; // avoid alpha = 0 with dotNH = 1\\\\n\\\\n\\\\treturn RECIPROCAL_PI * a2 / pow2( denom );\\\\n\\\\n}\\\\n\\\\n// GGX Distribution, Schlick Fresnel, GGX_SmithCorrelated Visibility\\\\nvec3 BRDF_GGX( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in vec3 f0, const in float f90, const in float roughness ) {\\\\n\\\\n\\\\tfloat alpha = pow2( roughness ); // UE4\\\\'s roughness\\\\n\\\\n\\\\tvec3 halfDir = normalize( lightDir + viewDir );\\\\n\\\\n\\\\tfloat dotNL = saturate( dot( normal, lightDir ) );\\\\n\\\\tfloat dotNV = saturate( dot( normal, viewDir ) );\\\\n\\\\tfloat dotNH = saturate( dot( normal, halfDir ) );\\\\n\\\\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\\\\n\\\\n\\\\tvec3 F = F_Schlick( f0, f90, dotVH );\\\\n\\\\n\\\\tfloat V = V_GGX_SmithCorrelated( alpha, dotNL, dotNV );\\\\n\\\\n\\\\tfloat D = D_GGX( alpha, dotNH );\\\\n\\\\n\\\\treturn F * ( V * D );\\\\n\\\\n}\\\\n\\\\n// Rect Area Light\\\\n\\\\n// Real-Time Polygonal-Light Shading with Linearly Transformed Cosines\\\\n// by Eric Heitz, Jonathan Dupuy, Stephen Hill and David Neubelt\\\\n// code: https://github.com/selfshadow/ltc_code/\\\\n\\\\nvec2 LTC_Uv( const in vec3 N, const in vec3 V, const in float roughness ) {\\\\n\\\\n\\\\tconst float LUT_SIZE = 64.0;\\\\n\\\\tconst float LUT_SCALE = ( LUT_SIZE - 1.0 ) / LUT_SIZE;\\\\n\\\\tconst float LUT_BIAS = 0.5 / LUT_SIZE;\\\\n\\\\n\\\\tfloat dotNV = saturate( dot( N, V ) );\\\\n\\\\n\\\\t// texture parameterized by sqrt( GGX alpha ) and sqrt( 1 - cos( theta ) )\\\\n\\\\tvec2 uv = vec2( roughness, sqrt( 1.0 - dotNV ) );\\\\n\\\\n\\\\tuv = uv * LUT_SCALE + LUT_BIAS;\\\\n\\\\n\\\\treturn uv;\\\\n\\\\n}\\\\n\\\\nfloat LTC_ClippedSphereFormFactor( const in vec3 f ) {\\\\n\\\\n\\\\t// Real-Time Area Lighting: a Journey from Research to Production (p.102)\\\\n\\\\t// An approximation of the form factor of a horizon-clipped rectangle.\\\\n\\\\n\\\\tfloat l = length( f );\\\\n\\\\n\\\\treturn max( ( l * l + f.z ) / ( l + 1.0 ), 0.0 );\\\\n\\\\n}\\\\n\\\\nvec3 LTC_EdgeVectorFormFactor( const in vec3 v1, const in vec3 v2 ) {\\\\n\\\\n\\\\tfloat x = dot( v1, v2 );\\\\n\\\\n\\\\tfloat y = abs( x );\\\\n\\\\n\\\\t// rational polynomial approximation to theta / sin( theta ) / 2PI\\\\n\\\\tfloat a = 0.8543985 + ( 0.4965155 + 0.0145206 * y ) * y;\\\\n\\\\tfloat b = 3.4175940 + ( 4.1616724 + y ) * y;\\\\n\\\\tfloat v = a / b;\\\\n\\\\n\\\\tfloat theta_sintheta = ( x > 0.0 ) ? v : 0.5 * inversesqrt( max( 1.0 - x * x, 1e-7 ) ) - v;\\\\n\\\\n\\\\treturn cross( v1, v2 ) * theta_sintheta;\\\\n\\\\n}\\\\n\\\\nvec3 LTC_Evaluate( const in vec3 N, const in vec3 V, const in vec3 P, const in mat3 mInv, const in vec3 rectCoords[ 4 ] ) {\\\\n\\\\n\\\\t// bail if point is on back side of plane of light\\\\n\\\\t// assumes ccw winding order of light vertices\\\\n\\\\tvec3 v1 = rectCoords[ 1 ] - rectCoords[ 0 ];\\\\n\\\\tvec3 v2 = rectCoords[ 3 ] - rectCoords[ 0 ];\\\\n\\\\tvec3 lightNormal = cross( v1, v2 );\\\\n\\\\n\\\\tif( dot( lightNormal, P - rectCoords[ 0 ] ) < 0.0 ) return vec3( 0.0 );\\\\n\\\\n\\\\t// construct orthonormal basis around N\\\\n\\\\tvec3 T1, T2;\\\\n\\\\tT1 = normalize( V - N * dot( V, N ) );\\\\n\\\\tT2 = - cross( N, T1 ); // negated from paper; possibly due to a different handedness of world coordinate system\\\\n\\\\n\\\\t// compute transform\\\\n\\\\tmat3 mat = mInv * transposeMat3( mat3( T1, T2, N ) );\\\\n\\\\n\\\\t// transform rect\\\\n\\\\tvec3 coords[ 4 ];\\\\n\\\\tcoords[ 0 ] = mat * ( rectCoords[ 0 ] - P );\\\\n\\\\tcoords[ 1 ] = mat * ( rectCoords[ 1 ] - P );\\\\n\\\\tcoords[ 2 ] = mat * ( rectCoords[ 2 ] - P );\\\\n\\\\tcoords[ 3 ] = mat * ( rectCoords[ 3 ] - P );\\\\n\\\\n\\\\t// project rect onto sphere\\\\n\\\\tcoords[ 0 ] = normalize( coords[ 0 ] );\\\\n\\\\tcoords[ 1 ] = normalize( coords[ 1 ] );\\\\n\\\\tcoords[ 2 ] = normalize( coords[ 2 ] );\\\\n\\\\tcoords[ 3 ] = normalize( coords[ 3 ] );\\\\n\\\\n\\\\t// calculate vector form factor\\\\n\\\\tvec3 vectorFormFactor = vec3( 0.0 );\\\\n\\\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 0 ], coords[ 1 ] );\\\\n\\\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 1 ], coords[ 2 ] );\\\\n\\\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 2 ], coords[ 3 ] );\\\\n\\\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 3 ], coords[ 0 ] );\\\\n\\\\n\\\\t// adjust for horizon clipping\\\\n\\\\tfloat result = LTC_ClippedSphereFormFactor( vectorFormFactor );\\\\n\\\\n/*\\\\n\\\\t// alternate method of adjusting for horizon clipping (see referece)\\\\n\\\\t// refactoring required\\\\n\\\\tfloat len = length( vectorFormFactor );\\\\n\\\\tfloat z = vectorFormFactor.z / len;\\\\n\\\\n\\\\tconst float LUT_SIZE = 64.0;\\\\n\\\\tconst float LUT_SCALE = ( LUT_SIZE - 1.0 ) / LUT_SIZE;\\\\n\\\\tconst float LUT_BIAS = 0.5 / LUT_SIZE;\\\\n\\\\n\\\\t// tabulated horizon-clipped sphere, apparently...\\\\n\\\\tvec2 uv = vec2( z * 0.5 + 0.5, len );\\\\n\\\\tuv = uv * LUT_SCALE + LUT_BIAS;\\\\n\\\\n\\\\tfloat scale = texture2D( ltc_2, uv ).w;\\\\n\\\\n\\\\tfloat result = len * scale;\\\\n*/\\\\n\\\\n\\\\treturn vec3( result );\\\\n\\\\n}\\\\n\\\\n// End Rect Area Light\\\\n\\\\n\\\\nfloat G_BlinnPhong_Implicit( /* const in float dotNL, const in float dotNV */ ) {\\\\n\\\\n\\\\t// geometry term is (n dot l)(n dot v) / 4(n dot l)(n dot v)\\\\n\\\\treturn 0.25;\\\\n\\\\n}\\\\n\\\\nfloat D_BlinnPhong( const in float shininess, const in float dotNH ) {\\\\n\\\\n\\\\treturn RECIPROCAL_PI * ( shininess * 0.5 + 1.0 ) * pow( dotNH, shininess );\\\\n\\\\n}\\\\n\\\\nvec3 BRDF_BlinnPhong( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in vec3 specularColor, const in float shininess ) {\\\\n\\\\n\\\\tvec3 halfDir = normalize( lightDir + viewDir );\\\\n\\\\n\\\\tfloat dotNH = saturate( dot( normal, halfDir ) );\\\\n\\\\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\\\\n\\\\n\\\\tvec3 F = F_Schlick( specularColor, 1.0, dotVH );\\\\n\\\\n\\\\tfloat G = G_BlinnPhong_Implicit( /* dotNL, dotNV */ );\\\\n\\\\n\\\\tfloat D = D_BlinnPhong( shininess, dotNH );\\\\n\\\\n\\\\treturn F * ( G * D );\\\\n\\\\n} // validated\\\\n\\\\n#if defined( USE_SHEEN )\\\\n\\\\n// https://github.com/google/filament/blob/master/shaders/src/brdf.fs\\\\nfloat D_Charlie( float roughness, float dotNH ) {\\\\n\\\\n\\\\tfloat alpha = pow2( roughness );\\\\n\\\\n\\\\t// Estevez and Kulla 2017, \\\\\\\"Production Friendly Microfacet Sheen BRDF\\\\\\\"\\\\n\\\\tfloat invAlpha = 1.0 / alpha;\\\\n\\\\tfloat cos2h = dotNH * dotNH;\\\\n\\\\tfloat sin2h = max( 1.0 - cos2h, 0.0078125 ); // 2^(-14/2), so sin2h^2 > 0 in fp16\\\\n\\\\n\\\\treturn ( 2.0 + invAlpha ) * pow( sin2h, invAlpha * 0.5 ) / ( 2.0 * PI );\\\\n\\\\n}\\\\n\\\\n// https://github.com/google/filament/blob/master/shaders/src/brdf.fs\\\\nfloat V_Neubelt( float dotNV, float dotNL ) {\\\\n\\\\n\\\\t// Neubelt and Pettineo 2013, \\\\\\\"Crafting a Next-gen Material Pipeline for The Order: 1886\\\\\\\"\\\\n\\\\treturn saturate( 1.0 / ( 4.0 * ( dotNL + dotNV - dotNL * dotNV ) ) );\\\\n\\\\n}\\\\n\\\\nvec3 BRDF_Sheen( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, vec3 sheenTint, const in float sheenRoughness ) {\\\\n\\\\n\\\\tvec3 halfDir = normalize( lightDir + viewDir );\\\\n\\\\n\\\\tfloat dotNL = saturate( dot( normal, lightDir ) );\\\\n\\\\tfloat dotNV = saturate( dot( normal, viewDir ) );\\\\n\\\\tfloat dotNH = saturate( dot( normal, halfDir ) );\\\\n\\\\n\\\\tfloat D = D_Charlie( sheenRoughness, dotNH );\\\\n\\\\tfloat V = V_Neubelt( dotNV, dotNL );\\\\n\\\\n\\\\treturn sheenTint * ( D * V );\\\\n\\\\n}\\\\n\\\\n#endif\\\\n',bumpmap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_BUMPMAP\\\\n\\\\n\\\\tuniform sampler2D bumpMap;\\\\n\\\\tuniform float bumpScale;\\\\n\\\\n\\\\t// Bump Mapping Unparametrized Surfaces on the GPU by Morten S. Mikkelsen\\\\n\\\\t// http://api.unrealengine.com/attachments/Engine/Rendering/LightingAndShadows/BumpMappingWithoutTangentSpace/mm_sfgrad_bump.pdf\\\\n\\\\n\\\\t// Evaluate the derivative of the height w.r.t. screen-space using forward differencing (listing 2)\\\\n\\\\n\\\\tvec2 dHdxy_fwd() {\\\\n\\\\n\\\\t\\\\tvec2 dSTdx = dFdx( vUv );\\\\n\\\\t\\\\tvec2 dSTdy = dFdy( vUv );\\\\n\\\\n\\\\t\\\\tfloat Hll = bumpScale * texture2D( bumpMap, vUv ).x;\\\\n\\\\t\\\\tfloat dBx = bumpScale * texture2D( bumpMap, vUv + dSTdx ).x - Hll;\\\\n\\\\t\\\\tfloat dBy = bumpScale * texture2D( bumpMap, vUv + dSTdy ).x - Hll;\\\\n\\\\n\\\\t\\\\treturn vec2( dBx, dBy );\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tvec3 perturbNormalArb( vec3 surf_pos, vec3 surf_norm, vec2 dHdxy, float faceDirection ) {\\\\n\\\\n\\\\t\\\\t// Workaround for Adreno 3XX dFd*( vec3 ) bug. See #9988\\\\n\\\\n\\\\t\\\\tvec3 vSigmaX = vec3( dFdx( surf_pos.x ), dFdx( surf_pos.y ), dFdx( surf_pos.z ) );\\\\n\\\\t\\\\tvec3 vSigmaY = vec3( dFdy( surf_pos.x ), dFdy( surf_pos.y ), dFdy( surf_pos.z ) );\\\\n\\\\t\\\\tvec3 vN = surf_norm;\\\\t\\\\t// normalized\\\\n\\\\n\\\\t\\\\tvec3 R1 = cross( vSigmaY, vN );\\\\n\\\\t\\\\tvec3 R2 = cross( vN, vSigmaX );\\\\n\\\\n\\\\t\\\\tfloat fDet = dot( vSigmaX, R1 ) * faceDirection;\\\\n\\\\n\\\\t\\\\tvec3 vGrad = sign( fDet ) * ( dHdxy.x * R1 + dHdxy.y * R2 );\\\\n\\\\t\\\\treturn normalize( abs( fDet ) * surf_norm - vGrad );\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\\\\",clipping_planes_fragment:\\\\\\\"\\\\n#if NUM_CLIPPING_PLANES > 0\\\\n\\\\n\\\\tvec4 plane;\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < UNION_CLIPPING_PLANES; i ++ ) {\\\\n\\\\n\\\\t\\\\tplane = clippingPlanes[ i ];\\\\n\\\\t\\\\tif ( dot( vClipPosition, plane.xyz ) > plane.w ) discard;\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t#if UNION_CLIPPING_PLANES < NUM_CLIPPING_PLANES\\\\n\\\\n\\\\t\\\\tbool clipped = true;\\\\n\\\\n\\\\t\\\\t#pragma unroll_loop_start\\\\n\\\\t\\\\tfor ( int i = UNION_CLIPPING_PLANES; i < NUM_CLIPPING_PLANES; i ++ ) {\\\\n\\\\n\\\\t\\\\t\\\\tplane = clippingPlanes[ i ];\\\\n\\\\t\\\\t\\\\tclipped = ( dot( vClipPosition, plane.xyz ) > plane.w ) && clipped;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t\\\\tif ( clipped ) discard;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",clipping_planes_pars_fragment:\\\\\\\"\\\\n#if NUM_CLIPPING_PLANES > 0\\\\n\\\\n\\\\tvarying vec3 vClipPosition;\\\\n\\\\n\\\\tuniform vec4 clippingPlanes[ NUM_CLIPPING_PLANES ];\\\\n\\\\n#endif\\\\n\\\\\\\",clipping_planes_pars_vertex:\\\\\\\"\\\\n#if NUM_CLIPPING_PLANES > 0\\\\n\\\\n\\\\tvarying vec3 vClipPosition;\\\\n\\\\n#endif\\\\n\\\\\\\",clipping_planes_vertex:\\\\\\\"\\\\n#if NUM_CLIPPING_PLANES > 0\\\\n\\\\n\\\\tvClipPosition = - mvPosition.xyz;\\\\n\\\\n#endif\\\\n\\\\\\\",color_fragment:\\\\\\\"\\\\n#if defined( USE_COLOR_ALPHA )\\\\n\\\\n\\\\tdiffuseColor *= vColor;\\\\n\\\\n#elif defined( USE_COLOR )\\\\n\\\\n\\\\tdiffuseColor.rgb *= vColor;\\\\n\\\\n#endif\\\\n\\\\\\\",color_pars_fragment:\\\\\\\"\\\\n#if defined( USE_COLOR_ALPHA )\\\\n\\\\n\\\\tvarying vec4 vColor;\\\\n\\\\n#elif defined( USE_COLOR )\\\\n\\\\n\\\\tvarying vec3 vColor;\\\\n\\\\n#endif\\\\n\\\\\\\",color_pars_vertex:\\\\\\\"\\\\n#if defined( USE_COLOR_ALPHA )\\\\n\\\\n\\\\tvarying vec4 vColor;\\\\n\\\\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )\\\\n\\\\n\\\\tvarying vec3 vColor;\\\\n\\\\n#endif\\\\n\\\\\\\",color_vertex:\\\\\\\"\\\\n#if defined( USE_COLOR_ALPHA )\\\\n\\\\n\\\\tvColor = vec4( 1.0 );\\\\n\\\\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )\\\\n\\\\n\\\\tvColor = vec3( 1.0 );\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_COLOR\\\\n\\\\n\\\\tvColor *= color;\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_INSTANCING_COLOR\\\\n\\\\n\\\\tvColor.xyz *= instanceColor.xyz;\\\\n\\\\n#endif\\\\n\\\\\\\",common:\\\\\\\"\\\\n#define PI 3.141592653589793\\\\n#define PI2 6.283185307179586\\\\n#define PI_HALF 1.5707963267948966\\\\n#define RECIPROCAL_PI 0.3183098861837907\\\\n#define RECIPROCAL_PI2 0.15915494309189535\\\\n#define EPSILON 1e-6\\\\n\\\\n#ifndef saturate\\\\n// may have defined saturate() already\\\\n#define saturate( a ) clamp( a, 0.0, 1.0 )\\\\n#endif\\\\n#define whiteComplement( a ) ( 1.0 - saturate( a ) )\\\\n\\\\nfloat pow2( const in float x ) { return x*x; }\\\\nfloat pow3( const in float x ) { return x*x*x; }\\\\nfloat pow4( const in float x ) { float x2 = x*x; return x2*x2; }\\\\nfloat max3( const in vec3 v ) { return max( max( v.x, v.y ), v.z ); }\\\\nfloat average( const in vec3 color ) { return dot( color, vec3( 0.3333 ) ); }\\\\n\\\\n// expects values in the range of [0,1]x[0,1], returns values in the [0,1] range.\\\\n// do not collapse into a single function per: http://byteblacksmith.com/improvements-to-the-canonical-one-liner-glsl-rand-for-opengl-es-2-0/\\\\nhighp float rand( const in vec2 uv ) {\\\\n\\\\n\\\\tconst highp float a = 12.9898, b = 78.233, c = 43758.5453;\\\\n\\\\thighp float dt = dot( uv.xy, vec2( a,b ) ), sn = mod( dt, PI );\\\\n\\\\n\\\\treturn fract( sin( sn ) * c );\\\\n\\\\n}\\\\n\\\\n#ifdef HIGH_PRECISION\\\\n\\\\tfloat precisionSafeLength( vec3 v ) { return length( v ); }\\\\n#else\\\\n\\\\tfloat precisionSafeLength( vec3 v ) {\\\\n\\\\t\\\\tfloat maxComponent = max3( abs( v ) );\\\\n\\\\t\\\\treturn length( v / maxComponent ) * maxComponent;\\\\n\\\\t}\\\\n#endif\\\\n\\\\nstruct IncidentLight {\\\\n\\\\tvec3 color;\\\\n\\\\tvec3 direction;\\\\n\\\\tbool visible;\\\\n};\\\\n\\\\nstruct ReflectedLight {\\\\n\\\\tvec3 directDiffuse;\\\\n\\\\tvec3 directSpecular;\\\\n\\\\tvec3 indirectDiffuse;\\\\n\\\\tvec3 indirectSpecular;\\\\n};\\\\n\\\\nstruct GeometricContext {\\\\n\\\\tvec3 position;\\\\n\\\\tvec3 normal;\\\\n\\\\tvec3 viewDir;\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\tvec3 clearcoatNormal;\\\\n#endif\\\\n};\\\\n\\\\nvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\\\\n\\\\n\\\\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\\\\n\\\\n}\\\\n\\\\nvec3 inverseTransformDirection( in vec3 dir, in mat4 matrix ) {\\\\n\\\\n\\\\t// dir can be either a direction vector or a normal vector\\\\n\\\\t// upper-left 3x3 of matrix is assumed to be orthogonal\\\\n\\\\n\\\\treturn normalize( ( vec4( dir, 0.0 ) * matrix ).xyz );\\\\n\\\\n}\\\\n\\\\nmat3 transposeMat3( const in mat3 m ) {\\\\n\\\\n\\\\tmat3 tmp;\\\\n\\\\n\\\\ttmp[ 0 ] = vec3( m[ 0 ].x, m[ 1 ].x, m[ 2 ].x );\\\\n\\\\ttmp[ 1 ] = vec3( m[ 0 ].y, m[ 1 ].y, m[ 2 ].y );\\\\n\\\\ttmp[ 2 ] = vec3( m[ 0 ].z, m[ 1 ].z, m[ 2 ].z );\\\\n\\\\n\\\\treturn tmp;\\\\n\\\\n}\\\\n\\\\n// https://en.wikipedia.org/wiki/Relative_luminance\\\\nfloat linearToRelativeLuminance( const in vec3 color ) {\\\\n\\\\n\\\\tvec3 weights = vec3( 0.2126, 0.7152, 0.0722 );\\\\n\\\\n\\\\treturn dot( weights, color.rgb );\\\\n\\\\n}\\\\n\\\\nbool isPerspectiveMatrix( mat4 m ) {\\\\n\\\\n\\\\treturn m[ 2 ][ 3 ] == - 1.0;\\\\n\\\\n}\\\\n\\\\nvec2 equirectUv( in vec3 dir ) {\\\\n\\\\n\\\\t// dir is assumed to be unit length\\\\n\\\\n\\\\tfloat u = atan( dir.z, dir.x ) * RECIPROCAL_PI2 + 0.5;\\\\n\\\\n\\\\tfloat v = asin( clamp( dir.y, - 1.0, 1.0 ) ) * RECIPROCAL_PI + 0.5;\\\\n\\\\n\\\\treturn vec2( u, v );\\\\n\\\\n}\\\\n\\\\\\\",cube_uv_reflection_fragment:\\\\\\\"\\\\n#ifdef ENVMAP_TYPE_CUBE_UV\\\\n\\\\n\\\\t#define cubeUV_maxMipLevel 8.0\\\\n\\\\t#define cubeUV_minMipLevel 4.0\\\\n\\\\t#define cubeUV_maxTileSize 256.0\\\\n\\\\t#define cubeUV_minTileSize 16.0\\\\n\\\\n\\\\t// These shader functions convert between the UV coordinates of a single face of\\\\n\\\\t// a cubemap, the 0-5 integer index of a cube face, and the direction vector for\\\\n\\\\t// sampling a textureCube (not generally normalized ).\\\\n\\\\n\\\\tfloat getFace( vec3 direction ) {\\\\n\\\\n\\\\t\\\\tvec3 absDirection = abs( direction );\\\\n\\\\n\\\\t\\\\tfloat face = - 1.0;\\\\n\\\\n\\\\t\\\\tif ( absDirection.x > absDirection.z ) {\\\\n\\\\n\\\\t\\\\t\\\\tif ( absDirection.x > absDirection.y )\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tface = direction.x > 0.0 ? 0.0 : 3.0;\\\\n\\\\n\\\\t\\\\t\\\\telse\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tface = direction.y > 0.0 ? 1.0 : 4.0;\\\\n\\\\n\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\tif ( absDirection.z > absDirection.y )\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tface = direction.z > 0.0 ? 2.0 : 5.0;\\\\n\\\\n\\\\t\\\\t\\\\telse\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tface = direction.y > 0.0 ? 1.0 : 4.0;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\treturn face;\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\t// RH coordinate system; PMREM face-indexing convention\\\\n\\\\tvec2 getUV( vec3 direction, float face ) {\\\\n\\\\n\\\\t\\\\tvec2 uv;\\\\n\\\\n\\\\t\\\\tif ( face == 0.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv = vec2( direction.z, direction.y ) / abs( direction.x ); // pos x\\\\n\\\\n\\\\t\\\\t} else if ( face == 1.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv = vec2( - direction.x, - direction.z ) / abs( direction.y ); // pos y\\\\n\\\\n\\\\t\\\\t} else if ( face == 2.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv = vec2( - direction.x, direction.y ) / abs( direction.z ); // pos z\\\\n\\\\n\\\\t\\\\t} else if ( face == 3.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv = vec2( - direction.z, direction.y ) / abs( direction.x ); // neg x\\\\n\\\\n\\\\t\\\\t} else if ( face == 4.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv = vec2( - direction.x, direction.z ) / abs( direction.y ); // neg y\\\\n\\\\n\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\tuv = vec2( direction.x, direction.y ) / abs( direction.z ); // neg z\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\treturn 0.5 * ( uv + 1.0 );\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tvec3 bilinearCubeUV( sampler2D envMap, vec3 direction, float mipInt ) {\\\\n\\\\n\\\\t\\\\tfloat face = getFace( direction );\\\\n\\\\n\\\\t\\\\tfloat filterInt = max( cubeUV_minMipLevel - mipInt, 0.0 );\\\\n\\\\n\\\\t\\\\tmipInt = max( mipInt, cubeUV_minMipLevel );\\\\n\\\\n\\\\t\\\\tfloat faceSize = exp2( mipInt );\\\\n\\\\n\\\\t\\\\tfloat texelSize = 1.0 / ( 3.0 * cubeUV_maxTileSize );\\\\n\\\\n\\\\t\\\\tvec2 uv = getUV( direction, face ) * ( faceSize - 1.0 );\\\\n\\\\n\\\\t\\\\tvec2 f = fract( uv );\\\\n\\\\n\\\\t\\\\tuv += 0.5 - f;\\\\n\\\\n\\\\t\\\\tif ( face > 2.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv.y += faceSize;\\\\n\\\\n\\\\t\\\\t\\\\tface -= 3.0;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tuv.x += face * faceSize;\\\\n\\\\n\\\\t\\\\tif ( mipInt < cubeUV_maxMipLevel ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv.y += 2.0 * cubeUV_maxTileSize;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tuv.y += filterInt * 2.0 * cubeUV_minTileSize;\\\\n\\\\n\\\\t\\\\tuv.x += 3.0 * max( 0.0, cubeUV_maxTileSize - 2.0 * faceSize );\\\\n\\\\n\\\\t\\\\tuv *= texelSize;\\\\n\\\\n\\\\t\\\\tvec3 tl = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\\\n\\\\n\\\\t\\\\tuv.x += texelSize;\\\\n\\\\n\\\\t\\\\tvec3 tr = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\\\n\\\\n\\\\t\\\\tuv.y += texelSize;\\\\n\\\\n\\\\t\\\\tvec3 br = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\\\n\\\\n\\\\t\\\\tuv.x -= texelSize;\\\\n\\\\n\\\\t\\\\tvec3 bl = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\\\n\\\\n\\\\t\\\\tvec3 tm = mix( tl, tr, f.x );\\\\n\\\\n\\\\t\\\\tvec3 bm = mix( bl, br, f.x );\\\\n\\\\n\\\\t\\\\treturn mix( tm, bm, f.y );\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\t// These defines must match with PMREMGenerator\\\\n\\\\n\\\\t#define r0 1.0\\\\n\\\\t#define v0 0.339\\\\n\\\\t#define m0 - 2.0\\\\n\\\\t#define r1 0.8\\\\n\\\\t#define v1 0.276\\\\n\\\\t#define m1 - 1.0\\\\n\\\\t#define r4 0.4\\\\n\\\\t#define v4 0.046\\\\n\\\\t#define m4 2.0\\\\n\\\\t#define r5 0.305\\\\n\\\\t#define v5 0.016\\\\n\\\\t#define m5 3.0\\\\n\\\\t#define r6 0.21\\\\n\\\\t#define v6 0.0038\\\\n\\\\t#define m6 4.0\\\\n\\\\n\\\\tfloat roughnessToMip( float roughness ) {\\\\n\\\\n\\\\t\\\\tfloat mip = 0.0;\\\\n\\\\n\\\\t\\\\tif ( roughness >= r1 ) {\\\\n\\\\n\\\\t\\\\t\\\\tmip = ( r0 - roughness ) * ( m1 - m0 ) / ( r0 - r1 ) + m0;\\\\n\\\\n\\\\t\\\\t} else if ( roughness >= r4 ) {\\\\n\\\\n\\\\t\\\\t\\\\tmip = ( r1 - roughness ) * ( m4 - m1 ) / ( r1 - r4 ) + m1;\\\\n\\\\n\\\\t\\\\t} else if ( roughness >= r5 ) {\\\\n\\\\n\\\\t\\\\t\\\\tmip = ( r4 - roughness ) * ( m5 - m4 ) / ( r4 - r5 ) + m4;\\\\n\\\\n\\\\t\\\\t} else if ( roughness >= r6 ) {\\\\n\\\\n\\\\t\\\\t\\\\tmip = ( r5 - roughness ) * ( m6 - m5 ) / ( r5 - r6 ) + m5;\\\\n\\\\n\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\tmip = - 2.0 * log2( 1.16 * roughness ); // 1.16 = 1.79^0.25\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\treturn mip;\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tvec4 textureCubeUV( sampler2D envMap, vec3 sampleDir, float roughness ) {\\\\n\\\\n\\\\t\\\\tfloat mip = clamp( roughnessToMip( roughness ), m0, cubeUV_maxMipLevel );\\\\n\\\\n\\\\t\\\\tfloat mipF = fract( mip );\\\\n\\\\n\\\\t\\\\tfloat mipInt = floor( mip );\\\\n\\\\n\\\\t\\\\tvec3 color0 = bilinearCubeUV( envMap, sampleDir, mipInt );\\\\n\\\\n\\\\t\\\\tif ( mipF == 0.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\treturn vec4( color0, 1.0 );\\\\n\\\\n\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\tvec3 color1 = bilinearCubeUV( envMap, sampleDir, mipInt + 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\treturn vec4( mix( color0, color1, mipF ), 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\\\\",defaultnormal_vertex:\\\\\\\"\\\\nvec3 transformedNormal = objectNormal;\\\\n\\\\n#ifdef USE_INSTANCING\\\\n\\\\n\\\\t// this is in lieu of a per-instance normal-matrix\\\\n\\\\t// shear transforms in the instance matrix are not supported\\\\n\\\\n\\\\tmat3 m = mat3( instanceMatrix );\\\\n\\\\n\\\\ttransformedNormal /= vec3( dot( m[ 0 ], m[ 0 ] ), dot( m[ 1 ], m[ 1 ] ), dot( m[ 2 ], m[ 2 ] ) );\\\\n\\\\n\\\\ttransformedNormal = m * transformedNormal;\\\\n\\\\n#endif\\\\n\\\\ntransformedNormal = normalMatrix * transformedNormal;\\\\n\\\\n#ifdef FLIP_SIDED\\\\n\\\\n\\\\ttransformedNormal = - transformedNormal;\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_TANGENT\\\\n\\\\n\\\\tvec3 transformedTangent = ( modelViewMatrix * vec4( objectTangent, 0.0 ) ).xyz;\\\\n\\\\n\\\\t#ifdef FLIP_SIDED\\\\n\\\\n\\\\t\\\\ttransformedTangent = - transformedTangent;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",displacementmap_pars_vertex:\\\\\\\"\\\\n#ifdef USE_DISPLACEMENTMAP\\\\n\\\\n\\\\tuniform sampler2D displacementMap;\\\\n\\\\tuniform float displacementScale;\\\\n\\\\tuniform float displacementBias;\\\\n\\\\n#endif\\\\n\\\\\\\",displacementmap_vertex:\\\\\\\"\\\\n#ifdef USE_DISPLACEMENTMAP\\\\n\\\\n\\\\ttransformed += normalize( objectNormal ) * ( texture2D( displacementMap, vUv ).x * displacementScale + displacementBias );\\\\n\\\\n#endif\\\\n\\\\\\\",emissivemap_fragment:\\\\\\\"\\\\n#ifdef USE_EMISSIVEMAP\\\\n\\\\n\\\\tvec4 emissiveColor = texture2D( emissiveMap, vUv );\\\\n\\\\n\\\\temissiveColor.rgb = emissiveMapTexelToLinear( emissiveColor ).rgb;\\\\n\\\\n\\\\ttotalEmissiveRadiance *= emissiveColor.rgb;\\\\n\\\\n#endif\\\\n\\\\\\\",emissivemap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_EMISSIVEMAP\\\\n\\\\n\\\\tuniform sampler2D emissiveMap;\\\\n\\\\n#endif\\\\n\\\\\\\",encodings_fragment:\\\\\\\"\\\\ngl_FragColor = linearToOutputTexel( gl_FragColor );\\\\n\\\\\\\",encodings_pars_fragment:\\\\\\\"\\\\n// For a discussion of what this is, please read this: http://lousodrome.net/blog/light/2013/05/26/gamma-correct-and-hdr-rendering-in-a-32-bits-buffer/\\\\n\\\\nvec4 LinearToLinear( in vec4 value ) {\\\\n\\\\treturn value;\\\\n}\\\\n\\\\nvec4 GammaToLinear( in vec4 value, in float gammaFactor ) {\\\\n\\\\treturn vec4( pow( value.rgb, vec3( gammaFactor ) ), value.a );\\\\n}\\\\n\\\\nvec4 LinearToGamma( in vec4 value, in float gammaFactor ) {\\\\n\\\\treturn vec4( pow( value.rgb, vec3( 1.0 / gammaFactor ) ), value.a );\\\\n}\\\\n\\\\nvec4 sRGBToLinear( in vec4 value ) {\\\\n\\\\treturn vec4( mix( pow( value.rgb * 0.9478672986 + vec3( 0.0521327014 ), vec3( 2.4 ) ), value.rgb * 0.0773993808, vec3( lessThanEqual( value.rgb, vec3( 0.04045 ) ) ) ), value.a );\\\\n}\\\\n\\\\nvec4 LinearTosRGB( in vec4 value ) {\\\\n\\\\treturn vec4( mix( pow( value.rgb, vec3( 0.41666 ) ) * 1.055 - vec3( 0.055 ), value.rgb * 12.92, vec3( lessThanEqual( value.rgb, vec3( 0.0031308 ) ) ) ), value.a );\\\\n}\\\\n\\\\nvec4 RGBEToLinear( in vec4 value ) {\\\\n\\\\treturn vec4( value.rgb * exp2( value.a * 255.0 - 128.0 ), 1.0 );\\\\n}\\\\n\\\\nvec4 LinearToRGBE( in vec4 value ) {\\\\n\\\\tfloat maxComponent = max( max( value.r, value.g ), value.b );\\\\n\\\\tfloat fExp = clamp( ceil( log2( maxComponent ) ), -128.0, 127.0 );\\\\n\\\\treturn vec4( value.rgb / exp2( fExp ), ( fExp + 128.0 ) / 255.0 );\\\\n\\\\t// return vec4( value.brg, ( 3.0 + 128.0 ) / 256.0 );\\\\n}\\\\n\\\\n// reference: http://iwasbeingirony.blogspot.ca/2010/06/difference-between-rgbm-and-rgbd.html\\\\nvec4 RGBMToLinear( in vec4 value, in float maxRange ) {\\\\n\\\\treturn vec4( value.rgb * value.a * maxRange, 1.0 );\\\\n}\\\\n\\\\nvec4 LinearToRGBM( in vec4 value, in float maxRange ) {\\\\n\\\\tfloat maxRGB = max( value.r, max( value.g, value.b ) );\\\\n\\\\tfloat M = clamp( maxRGB / maxRange, 0.0, 1.0 );\\\\n\\\\tM = ceil( M * 255.0 ) / 255.0;\\\\n\\\\treturn vec4( value.rgb / ( M * maxRange ), M );\\\\n}\\\\n\\\\n// reference: http://iwasbeingirony.blogspot.ca/2010/06/difference-between-rgbm-and-rgbd.html\\\\nvec4 RGBDToLinear( in vec4 value, in float maxRange ) {\\\\n\\\\treturn vec4( value.rgb * ( ( maxRange / 255.0 ) / value.a ), 1.0 );\\\\n}\\\\n\\\\nvec4 LinearToRGBD( in vec4 value, in float maxRange ) {\\\\n\\\\tfloat maxRGB = max( value.r, max( value.g, value.b ) );\\\\n\\\\tfloat D = max( maxRange / maxRGB, 1.0 );\\\\n\\\\t// NOTE: The implementation with min causes the shader to not compile on\\\\n\\\\t// a common Alcatel A502DL in Chrome 78/Android 8.1. Some research suggests \\\\n\\\\t// that the chipset is Mediatek MT6739 w/ IMG PowerVR GE8100 GPU.\\\\n\\\\t// D = min( floor( D ) / 255.0, 1.0 );\\\\n\\\\tD = clamp( floor( D ) / 255.0, 0.0, 1.0 );\\\\n\\\\treturn vec4( value.rgb * ( D * ( 255.0 / maxRange ) ), D );\\\\n}\\\\n\\\\n// LogLuv reference: http://graphicrants.blogspot.ca/2009/04/rgbm-color-encoding.html\\\\n\\\\n// M matrix, for encoding\\\\nconst mat3 cLogLuvM = mat3( 0.2209, 0.3390, 0.4184, 0.1138, 0.6780, 0.7319, 0.0102, 0.1130, 0.2969 );\\\\nvec4 LinearToLogLuv( in vec4 value ) {\\\\n\\\\tvec3 Xp_Y_XYZp = cLogLuvM * value.rgb;\\\\n\\\\tXp_Y_XYZp = max( Xp_Y_XYZp, vec3( 1e-6, 1e-6, 1e-6 ) );\\\\n\\\\tvec4 vResult;\\\\n\\\\tvResult.xy = Xp_Y_XYZp.xy / Xp_Y_XYZp.z;\\\\n\\\\tfloat Le = 2.0 * log2(Xp_Y_XYZp.y) + 127.0;\\\\n\\\\tvResult.w = fract( Le );\\\\n\\\\tvResult.z = ( Le - ( floor( vResult.w * 255.0 ) ) / 255.0 ) / 255.0;\\\\n\\\\treturn vResult;\\\\n}\\\\n\\\\n// Inverse M matrix, for decoding\\\\nconst mat3 cLogLuvInverseM = mat3( 6.0014, -2.7008, -1.7996, -1.3320, 3.1029, -5.7721, 0.3008, -1.0882, 5.6268 );\\\\nvec4 LogLuvToLinear( in vec4 value ) {\\\\n\\\\tfloat Le = value.z * 255.0 + value.w;\\\\n\\\\tvec3 Xp_Y_XYZp;\\\\n\\\\tXp_Y_XYZp.y = exp2( ( Le - 127.0 ) / 2.0 );\\\\n\\\\tXp_Y_XYZp.z = Xp_Y_XYZp.y / value.y;\\\\n\\\\tXp_Y_XYZp.x = value.x * Xp_Y_XYZp.z;\\\\n\\\\tvec3 vRGB = cLogLuvInverseM * Xp_Y_XYZp.rgb;\\\\n\\\\treturn vec4( max( vRGB, 0.0 ), 1.0 );\\\\n}\\\\n\\\\\\\",envmap_fragment:\\\\\\\"\\\\n#ifdef USE_ENVMAP\\\\n\\\\n\\\\t#ifdef ENV_WORLDPOS\\\\n\\\\n\\\\t\\\\tvec3 cameraToFrag;\\\\n\\\\n\\\\t\\\\tif ( isOrthographic ) {\\\\n\\\\n\\\\t\\\\t\\\\tcameraToFrag = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\\\\n\\\\n\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\tcameraToFrag = normalize( vWorldPosition - cameraPosition );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t// Transforming Normal Vectors with the Inverse Transformation\\\\n\\\\t\\\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\\\n\\\\n\\\\t\\\\t#ifdef ENVMAP_MODE_REFLECTION\\\\n\\\\n\\\\t\\\\t\\\\tvec3 reflectVec = reflect( cameraToFrag, worldNormal );\\\\n\\\\n\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\tvec3 reflectVec = refract( cameraToFrag, worldNormal, refractionRatio );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tvec3 reflectVec = vReflect;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef ENVMAP_TYPE_CUBE\\\\n\\\\n\\\\t\\\\tvec4 envColor = textureCube( envMap, vec3( flipEnvMap * reflectVec.x, reflectVec.yz ) );\\\\n\\\\n\\\\t\\\\tenvColor = envMapTexelToLinear( envColor );\\\\n\\\\n\\\\t#elif defined( ENVMAP_TYPE_CUBE_UV )\\\\n\\\\n\\\\t\\\\tvec4 envColor = textureCubeUV( envMap, reflectVec, 0.0 );\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tvec4 envColor = vec4( 0.0 );\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef ENVMAP_BLENDING_MULTIPLY\\\\n\\\\n\\\\t\\\\toutgoingLight = mix( outgoingLight, outgoingLight * envColor.xyz, specularStrength * reflectivity );\\\\n\\\\n\\\\t#elif defined( ENVMAP_BLENDING_MIX )\\\\n\\\\n\\\\t\\\\toutgoingLight = mix( outgoingLight, envColor.xyz, specularStrength * reflectivity );\\\\n\\\\n\\\\t#elif defined( ENVMAP_BLENDING_ADD )\\\\n\\\\n\\\\t\\\\toutgoingLight += envColor.xyz * specularStrength * reflectivity;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",envmap_common_pars_fragment:\\\\\\\"\\\\n#ifdef USE_ENVMAP\\\\n\\\\n\\\\tuniform float envMapIntensity;\\\\n\\\\tuniform float flipEnvMap;\\\\n\\\\tuniform int maxMipLevel;\\\\n\\\\n\\\\t#ifdef ENVMAP_TYPE_CUBE\\\\n\\\\t\\\\tuniform samplerCube envMap;\\\\n\\\\t#else\\\\n\\\\t\\\\tuniform sampler2D envMap;\\\\n\\\\t#endif\\\\n\\\\t\\\\n#endif\\\\n\\\\\\\",envmap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_ENVMAP\\\\n\\\\n\\\\tuniform float reflectivity;\\\\n\\\\n\\\\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG )\\\\n\\\\n\\\\t\\\\t#define ENV_WORLDPOS\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef ENV_WORLDPOS\\\\n\\\\n\\\\t\\\\tvarying vec3 vWorldPosition;\\\\n\\\\t\\\\tuniform float refractionRatio;\\\\n\\\\t#else\\\\n\\\\t\\\\tvarying vec3 vReflect;\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",envmap_pars_vertex:\\\\\\\"\\\\n#ifdef USE_ENVMAP\\\\n\\\\n\\\\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) ||defined( PHONG )\\\\n\\\\n\\\\t\\\\t#define ENV_WORLDPOS\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef ENV_WORLDPOS\\\\n\\\\t\\\\t\\\\n\\\\t\\\\tvarying vec3 vWorldPosition;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tvarying vec3 vReflect;\\\\n\\\\t\\\\tuniform float refractionRatio;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",envmap_physical_pars_fragment:\\\\\\\"\\\\n#if defined( USE_ENVMAP )\\\\n\\\\n\\\\t#ifdef ENVMAP_MODE_REFRACTION\\\\n\\\\n\\\\t\\\\tuniform float refractionRatio;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tvec3 getIBLIrradiance( const in vec3 normal ) {\\\\n\\\\n\\\\t\\\\t#if defined( ENVMAP_TYPE_CUBE_UV )\\\\n\\\\n\\\\t\\\\t\\\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\\\n\\\\n\\\\t\\\\t\\\\tvec4 envMapColor = textureCubeUV( envMap, worldNormal, 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\treturn PI * envMapColor.rgb * envMapIntensity;\\\\n\\\\n\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\treturn vec3( 0.0 );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tvec3 getIBLRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness ) {\\\\n\\\\n\\\\t\\\\t#if defined( ENVMAP_TYPE_CUBE_UV )\\\\n\\\\n\\\\t\\\\t\\\\tvec3 reflectVec;\\\\n\\\\n\\\\t\\\\t\\\\t#ifdef ENVMAP_MODE_REFLECTION\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treflectVec = reflect( - viewDir, normal );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t// Mixing the reflection with the normal is more accurate and keeps rough objects from gathering light from behind their tangent plane.\\\\n\\\\t\\\\t\\\\t\\\\treflectVec = normalize( mix( reflectVec, normal, roughness * roughness) );\\\\n\\\\n\\\\t\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treflectVec = refract( - viewDir, normal, refractionRatio );\\\\n\\\\n\\\\t\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\t\\\\treflectVec = inverseTransformDirection( reflectVec, viewMatrix );\\\\n\\\\n\\\\t\\\\t\\\\tvec4 envMapColor = textureCubeUV( envMap, reflectVec, roughness );\\\\n\\\\n\\\\t\\\\t\\\\treturn envMapColor.rgb * envMapIntensity;\\\\n\\\\n\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\treturn vec3( 0.0 );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\\\\",envmap_vertex:\\\\\\\"\\\\n#ifdef USE_ENVMAP\\\\n\\\\n\\\\t#ifdef ENV_WORLDPOS\\\\n\\\\n\\\\t\\\\tvWorldPosition = worldPosition.xyz;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tvec3 cameraToVertex;\\\\n\\\\n\\\\t\\\\tif ( isOrthographic ) {\\\\n\\\\n\\\\t\\\\t\\\\tcameraToVertex = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\\\\n\\\\n\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\tcameraToVertex = normalize( worldPosition.xyz - cameraPosition );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvec3 worldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\\\\n\\\\n\\\\t\\\\t#ifdef ENVMAP_MODE_REFLECTION\\\\n\\\\n\\\\t\\\\t\\\\tvReflect = reflect( cameraToVertex, worldNormal );\\\\n\\\\n\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\tvReflect = refract( cameraToVertex, worldNormal, refractionRatio );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",fog_vertex:\\\\\\\"\\\\n#ifdef USE_FOG\\\\n\\\\n\\\\tvFogDepth = - mvPosition.z;\\\\n\\\\n#endif\\\\n\\\\\\\",fog_pars_vertex:\\\\\\\"\\\\n#ifdef USE_FOG\\\\n\\\\n\\\\tvarying float vFogDepth;\\\\n\\\\n#endif\\\\n\\\\\\\",fog_fragment:\\\\\\\"\\\\n#ifdef USE_FOG\\\\n\\\\n\\\\t#ifdef FOG_EXP2\\\\n\\\\n\\\\t\\\\tfloat fogFactor = 1.0 - exp( - fogDensity * fogDensity * vFogDepth * vFogDepth );\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tfloat fogFactor = smoothstep( fogNear, fogFar, vFogDepth );\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tgl_FragColor.rgb = mix( gl_FragColor.rgb, fogColor, fogFactor );\\\\n\\\\n#endif\\\\n\\\\\\\",fog_pars_fragment:\\\\\\\"\\\\n#ifdef USE_FOG\\\\n\\\\n\\\\tuniform vec3 fogColor;\\\\n\\\\tvarying float vFogDepth;\\\\n\\\\n\\\\t#ifdef FOG_EXP2\\\\n\\\\n\\\\t\\\\tuniform float fogDensity;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tuniform float fogNear;\\\\n\\\\t\\\\tuniform float fogFar;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",gradientmap_pars_fragment:\\\\\\\"\\\\n\\\\n#ifdef USE_GRADIENTMAP\\\\n\\\\n\\\\tuniform sampler2D gradientMap;\\\\n\\\\n#endif\\\\n\\\\nvec3 getGradientIrradiance( vec3 normal, vec3 lightDirection ) {\\\\n\\\\n\\\\t// dotNL will be from -1.0 to 1.0\\\\n\\\\tfloat dotNL = dot( normal, lightDirection );\\\\n\\\\tvec2 coord = vec2( dotNL * 0.5 + 0.5, 0.0 );\\\\n\\\\n\\\\t#ifdef USE_GRADIENTMAP\\\\n\\\\n\\\\t\\\\treturn texture2D( gradientMap, coord ).rgb;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\treturn ( coord.x < 0.7 ) ? vec3( 0.7 ) : vec3( 1.0 );\\\\n\\\\n\\\\t#endif\\\\n\\\\n}\\\\n\\\\\\\",lightmap_fragment:\\\\\\\"\\\\n#ifdef USE_LIGHTMAP\\\\n\\\\n\\\\tvec4 lightMapTexel = texture2D( lightMap, vUv2 );\\\\n\\\\tvec3 lightMapIrradiance = lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\\\n\\\\n\\\\t#ifndef PHYSICALLY_CORRECT_LIGHTS\\\\n\\\\n\\\\t\\\\tlightMapIrradiance *= PI;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\treflectedLight.indirectDiffuse += lightMapIrradiance;\\\\n\\\\n#endif\\\\n\\\\\\\",lightmap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_LIGHTMAP\\\\n\\\\n\\\\tuniform sampler2D lightMap;\\\\n\\\\tuniform float lightMapIntensity;\\\\n\\\\n#endif\\\\n\\\\\\\",lights_lambert_vertex:\\\\\\\"\\\\nvec3 diffuse = vec3( 1.0 );\\\\n\\\\nGeometricContext geometry;\\\\ngeometry.position = mvPosition.xyz;\\\\ngeometry.normal = normalize( transformedNormal );\\\\ngeometry.viewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( -mvPosition.xyz );\\\\n\\\\nGeometricContext backGeometry;\\\\nbackGeometry.position = geometry.position;\\\\nbackGeometry.normal = -geometry.normal;\\\\nbackGeometry.viewDir = geometry.viewDir;\\\\n\\\\nvLightFront = vec3( 0.0 );\\\\nvIndirectFront = vec3( 0.0 );\\\\n#ifdef DOUBLE_SIDED\\\\n\\\\tvLightBack = vec3( 0.0 );\\\\n\\\\tvIndirectBack = vec3( 0.0 );\\\\n#endif\\\\n\\\\nIncidentLight directLight;\\\\nfloat dotNL;\\\\nvec3 directLightColor_Diffuse;\\\\n\\\\nvIndirectFront += getAmbientLightIrradiance( ambientLightColor );\\\\n\\\\nvIndirectFront += getLightProbeIrradiance( lightProbe, geometry.normal );\\\\n\\\\n#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\tvIndirectBack += getAmbientLightIrradiance( ambientLightColor );\\\\n\\\\n\\\\tvIndirectBack += getLightProbeIrradiance( lightProbe, backGeometry.normal );\\\\n\\\\n#endif\\\\n\\\\n#if NUM_POINT_LIGHTS > 0\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\tgetPointLightInfo( pointLights[ i ], geometry, directLight );\\\\n\\\\n\\\\t\\\\tdotNL = dot( geometry.normal, directLight.direction );\\\\n\\\\t\\\\tdirectLightColor_Diffuse = directLight.color;\\\\n\\\\n\\\\t\\\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\\\n\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\t\\\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n#endif\\\\n\\\\n#if NUM_SPOT_LIGHTS > 0\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\tgetSpotLightInfo( spotLights[ i ], geometry, directLight );\\\\n\\\\n\\\\t\\\\tdotNL = dot( geometry.normal, directLight.direction );\\\\n\\\\t\\\\tdirectLightColor_Diffuse = directLight.color;\\\\n\\\\n\\\\t\\\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\\\n\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\t\\\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n#endif\\\\n\\\\n#if NUM_DIR_LIGHTS > 0\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\tgetDirectionalLightInfo( directionalLights[ i ], geometry, directLight );\\\\n\\\\n\\\\t\\\\tdotNL = dot( geometry.normal, directLight.direction );\\\\n\\\\t\\\\tdirectLightColor_Diffuse = directLight.color;\\\\n\\\\n\\\\t\\\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\\\n\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\t\\\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n#endif\\\\n\\\\n#if NUM_HEMI_LIGHTS > 0\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\tvIndirectFront += getHemisphereLightIrradiance( hemisphereLights[ i ], geometry.normal );\\\\n\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\t\\\\tvIndirectBack += getHemisphereLightIrradiance( hemisphereLights[ i ], backGeometry.normal );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n#endif\\\\n\\\\\\\",lights_pars_begin:\\\\\\\"\\\\nuniform bool receiveShadow;\\\\nuniform vec3 ambientLightColor;\\\\nuniform vec3 lightProbe[ 9 ];\\\\n\\\\n// get the irradiance (radiance convolved with cosine lobe) at the point 'normal' on the unit sphere\\\\n// source: https://graphics.stanford.edu/papers/envmap/envmap.pdf\\\\nvec3 shGetIrradianceAt( in vec3 normal, in vec3 shCoefficients[ 9 ] ) {\\\\n\\\\n\\\\t// normal is assumed to have unit length\\\\n\\\\n\\\\tfloat x = normal.x, y = normal.y, z = normal.z;\\\\n\\\\n\\\\t// band 0\\\\n\\\\tvec3 result = shCoefficients[ 0 ] * 0.886227;\\\\n\\\\n\\\\t// band 1\\\\n\\\\tresult += shCoefficients[ 1 ] * 2.0 * 0.511664 * y;\\\\n\\\\tresult += shCoefficients[ 2 ] * 2.0 * 0.511664 * z;\\\\n\\\\tresult += shCoefficients[ 3 ] * 2.0 * 0.511664 * x;\\\\n\\\\n\\\\t// band 2\\\\n\\\\tresult += shCoefficients[ 4 ] * 2.0 * 0.429043 * x * y;\\\\n\\\\tresult += shCoefficients[ 5 ] * 2.0 * 0.429043 * y * z;\\\\n\\\\tresult += shCoefficients[ 6 ] * ( 0.743125 * z * z - 0.247708 );\\\\n\\\\tresult += shCoefficients[ 7 ] * 2.0 * 0.429043 * x * z;\\\\n\\\\tresult += shCoefficients[ 8 ] * 0.429043 * ( x * x - y * y );\\\\n\\\\n\\\\treturn result;\\\\n\\\\n}\\\\n\\\\nvec3 getLightProbeIrradiance( const in vec3 lightProbe[ 9 ], const in vec3 normal ) {\\\\n\\\\n\\\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\\\n\\\\n\\\\tvec3 irradiance = shGetIrradianceAt( worldNormal, lightProbe );\\\\n\\\\n\\\\treturn irradiance;\\\\n\\\\n}\\\\n\\\\nvec3 getAmbientLightIrradiance( const in vec3 ambientLightColor ) {\\\\n\\\\n\\\\tvec3 irradiance = ambientLightColor;\\\\n\\\\n\\\\treturn irradiance;\\\\n\\\\n}\\\\n\\\\nfloat getDistanceAttenuation( const in float lightDistance, const in float cutoffDistance, const in float decayExponent ) {\\\\n\\\\n\\\\t#if defined ( PHYSICALLY_CORRECT_LIGHTS )\\\\n\\\\n\\\\t\\\\t// based upon Frostbite 3 Moving to Physically-based Rendering\\\\n\\\\t\\\\t// page 32, equation 26: E[window1]\\\\n\\\\t\\\\t// https://seblagarde.files.wordpress.com/2015/07/course_notes_moving_frostbite_to_pbr_v32.pdf\\\\n\\\\t\\\\tfloat distanceFalloff = 1.0 / max( pow( lightDistance, decayExponent ), 0.01 );\\\\n\\\\n\\\\t\\\\tif ( cutoffDistance > 0.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\tdistanceFalloff *= pow2( saturate( 1.0 - pow4( lightDistance / cutoffDistance ) ) );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\treturn distanceFalloff;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tif ( cutoffDistance > 0.0 && decayExponent > 0.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\treturn pow( saturate( - lightDistance / cutoffDistance + 1.0 ), decayExponent );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\treturn 1.0;\\\\n\\\\n\\\\t#endif\\\\n\\\\n}\\\\n\\\\nfloat getSpotAttenuation( const in float coneCosine, const in float penumbraCosine, const in float angleCosine ) {\\\\n\\\\n\\\\treturn smoothstep( coneCosine, penumbraCosine, angleCosine );\\\\n\\\\n}\\\\n\\\\n#if NUM_DIR_LIGHTS > 0\\\\n\\\\n\\\\tstruct DirectionalLight {\\\\n\\\\t\\\\tvec3 direction;\\\\n\\\\t\\\\tvec3 color;\\\\n\\\\t};\\\\n\\\\n\\\\tuniform DirectionalLight directionalLights[ NUM_DIR_LIGHTS ];\\\\n\\\\n\\\\tvoid getDirectionalLightInfo( const in DirectionalLight directionalLight, const in GeometricContext geometry, out IncidentLight light ) {\\\\n\\\\n\\\\t\\\\tlight.color = directionalLight.color;\\\\n\\\\t\\\\tlight.direction = directionalLight.direction;\\\\n\\\\t\\\\tlight.visible = true;\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\n\\\\n#if NUM_POINT_LIGHTS > 0\\\\n\\\\n\\\\tstruct PointLight {\\\\n\\\\t\\\\tvec3 position;\\\\n\\\\t\\\\tvec3 color;\\\\n\\\\t\\\\tfloat distance;\\\\n\\\\t\\\\tfloat decay;\\\\n\\\\t};\\\\n\\\\n\\\\tuniform PointLight pointLights[ NUM_POINT_LIGHTS ];\\\\n\\\\n\\\\t// light is an out parameter as having it as a return value caused compiler errors on some devices\\\\n\\\\tvoid getPointLightInfo( const in PointLight pointLight, const in GeometricContext geometry, out IncidentLight light ) {\\\\n\\\\n\\\\t\\\\tvec3 lVector = pointLight.position - geometry.position;\\\\n\\\\n\\\\t\\\\tlight.direction = normalize( lVector );\\\\n\\\\n\\\\t\\\\tfloat lightDistance = length( lVector );\\\\n\\\\n\\\\t\\\\tlight.color = pointLight.color;\\\\n\\\\t\\\\tlight.color *= getDistanceAttenuation( lightDistance, pointLight.distance, pointLight.decay );\\\\n\\\\t\\\\tlight.visible = ( light.color != vec3( 0.0 ) );\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\n\\\\n#if NUM_SPOT_LIGHTS > 0\\\\n\\\\n\\\\tstruct SpotLight {\\\\n\\\\t\\\\tvec3 position;\\\\n\\\\t\\\\tvec3 direction;\\\\n\\\\t\\\\tvec3 color;\\\\n\\\\t\\\\tfloat distance;\\\\n\\\\t\\\\tfloat decay;\\\\n\\\\t\\\\tfloat coneCos;\\\\n\\\\t\\\\tfloat penumbraCos;\\\\n\\\\t};\\\\n\\\\n\\\\tuniform SpotLight spotLights[ NUM_SPOT_LIGHTS ];\\\\n\\\\n\\\\t// light is an out parameter as having it as a return value caused compiler errors on some devices\\\\n\\\\tvoid getSpotLightInfo( const in SpotLight spotLight, const in GeometricContext geometry, out IncidentLight light ) {\\\\n\\\\n\\\\t\\\\tvec3 lVector = spotLight.position - geometry.position;\\\\n\\\\n\\\\t\\\\tlight.direction = normalize( lVector );\\\\n\\\\n\\\\t\\\\tfloat angleCos = dot( light.direction, spotLight.direction );\\\\n\\\\n\\\\t\\\\tfloat spotAttenuation = getSpotAttenuation( spotLight.coneCos, spotLight.penumbraCos, angleCos );\\\\n\\\\n\\\\t\\\\tif ( spotAttenuation > 0.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\tfloat lightDistance = length( lVector );\\\\n\\\\n\\\\t\\\\t\\\\tlight.color = spotLight.color * spotAttenuation;\\\\n\\\\t\\\\t\\\\tlight.color *= getDistanceAttenuation( lightDistance, spotLight.distance, spotLight.decay );\\\\n\\\\t\\\\t\\\\tlight.visible = ( light.color != vec3( 0.0 ) );\\\\n\\\\n\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\tlight.color = vec3( 0.0 );\\\\n\\\\t\\\\t\\\\tlight.visible = false;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\n\\\\n#if NUM_RECT_AREA_LIGHTS > 0\\\\n\\\\n\\\\tstruct RectAreaLight {\\\\n\\\\t\\\\tvec3 color;\\\\n\\\\t\\\\tvec3 position;\\\\n\\\\t\\\\tvec3 halfWidth;\\\\n\\\\t\\\\tvec3 halfHeight;\\\\n\\\\t};\\\\n\\\\n\\\\t// Pre-computed values of LinearTransformedCosine approximation of BRDF\\\\n\\\\t// BRDF approximation Texture is 64x64\\\\n\\\\tuniform sampler2D ltc_1; // RGBA Float\\\\n\\\\tuniform sampler2D ltc_2; // RGBA Float\\\\n\\\\n\\\\tuniform RectAreaLight rectAreaLights[ NUM_RECT_AREA_LIGHTS ];\\\\n\\\\n#endif\\\\n\\\\n\\\\n#if NUM_HEMI_LIGHTS > 0\\\\n\\\\n\\\\tstruct HemisphereLight {\\\\n\\\\t\\\\tvec3 direction;\\\\n\\\\t\\\\tvec3 skyColor;\\\\n\\\\t\\\\tvec3 groundColor;\\\\n\\\\t};\\\\n\\\\n\\\\tuniform HemisphereLight hemisphereLights[ NUM_HEMI_LIGHTS ];\\\\n\\\\n\\\\tvec3 getHemisphereLightIrradiance( const in HemisphereLight hemiLight, const in vec3 normal ) {\\\\n\\\\n\\\\t\\\\tfloat dotNL = dot( normal, hemiLight.direction );\\\\n\\\\t\\\\tfloat hemiDiffuseWeight = 0.5 * dotNL + 0.5;\\\\n\\\\n\\\\t\\\\tvec3 irradiance = mix( hemiLight.groundColor, hemiLight.skyColor, hemiDiffuseWeight );\\\\n\\\\n\\\\t\\\\treturn irradiance;\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\\\\",lights_toon_fragment:\\\\\\\"\\\\nToonMaterial material;\\\\nmaterial.diffuseColor = diffuseColor.rgb;\\\\n\\\\\\\",lights_toon_pars_fragment:\\\\\\\"\\\\nvarying vec3 vViewPosition;\\\\n\\\\nstruct ToonMaterial {\\\\n\\\\n\\\\tvec3 diffuseColor;\\\\n\\\\n};\\\\n\\\\nvoid RE_Direct_Toon( const in IncidentLight directLight, const in GeometricContext geometry, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\n\\\\tvec3 irradiance = getGradientIrradiance( geometry.normal, directLight.direction ) * directLight.color;\\\\n\\\\n\\\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n\\\\n}\\\\n\\\\nvoid RE_IndirectDiffuse_Toon( const in vec3 irradiance, const in GeometricContext geometry, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\n\\\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n\\\\n}\\\\n\\\\n#define RE_Direct\\\\t\\\\t\\\\t\\\\tRE_Direct_Toon\\\\n#define RE_IndirectDiffuse\\\\t\\\\tRE_IndirectDiffuse_Toon\\\\n\\\\n#define Material_LightProbeLOD( material )\\\\t(0)\\\\n\\\\\\\",lights_phong_fragment:\\\\\\\"\\\\nBlinnPhongMaterial material;\\\\nmaterial.diffuseColor = diffuseColor.rgb;\\\\nmaterial.specularColor = specular;\\\\nmaterial.specularShininess = shininess;\\\\nmaterial.specularStrength = specularStrength;\\\\n\\\\\\\",lights_phong_pars_fragment:\\\\\\\"\\\\nvarying vec3 vViewPosition;\\\\n\\\\nstruct BlinnPhongMaterial {\\\\n\\\\n\\\\tvec3 diffuseColor;\\\\n\\\\tvec3 specularColor;\\\\n\\\\tfloat specularShininess;\\\\n\\\\tfloat specularStrength;\\\\n\\\\n};\\\\n\\\\nvoid RE_Direct_BlinnPhong( const in IncidentLight directLight, const in GeometricContext geometry, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\n\\\\tfloat dotNL = saturate( dot( geometry.normal, directLight.direction ) );\\\\n\\\\tvec3 irradiance = dotNL * directLight.color;\\\\n\\\\n\\\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n\\\\n\\\\treflectedLight.directSpecular += irradiance * BRDF_BlinnPhong( directLight.direction, geometry.viewDir, geometry.normal, material.specularColor, material.specularShininess ) * material.specularStrength;\\\\n\\\\n}\\\\n\\\\nvoid RE_IndirectDiffuse_BlinnPhong( const in vec3 irradiance, const in GeometricContext geometry, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\n\\\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n\\\\n}\\\\n\\\\n#define RE_Direct\\\\t\\\\t\\\\t\\\\tRE_Direct_BlinnPhong\\\\n#define RE_IndirectDiffuse\\\\t\\\\tRE_IndirectDiffuse_BlinnPhong\\\\n\\\\n#define Material_LightProbeLOD( material )\\\\t(0)\\\\n\\\\\\\",lights_physical_fragment:\\\\\\\"\\\\nPhysicalMaterial material;\\\\nmaterial.diffuseColor = diffuseColor.rgb * ( 1.0 - metalnessFactor );\\\\n\\\\nvec3 dxy = max( abs( dFdx( geometryNormal ) ), abs( dFdy( geometryNormal ) ) );\\\\nfloat geometryRoughness = max( max( dxy.x, dxy.y ), dxy.z );\\\\n\\\\nmaterial.roughness = max( roughnessFactor, 0.0525 );// 0.0525 corresponds to the base mip of a 256 cubemap.\\\\nmaterial.roughness += geometryRoughness;\\\\nmaterial.roughness = min( material.roughness, 1.0 );\\\\n\\\\n#ifdef IOR\\\\n\\\\n\\\\t#ifdef SPECULAR\\\\n\\\\n\\\\t\\\\tfloat specularIntensityFactor = specularIntensity;\\\\n\\\\t\\\\tvec3 specularTintFactor = specularTint;\\\\n\\\\n\\\\t\\\\t#ifdef USE_SPECULARINTENSITYMAP\\\\n\\\\n\\\\t\\\\t\\\\tspecularIntensityFactor *= texture2D( specularIntensityMap, vUv ).a;\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\t#ifdef USE_SPECULARTINTMAP\\\\n\\\\n\\\\t\\\\t\\\\tspecularTintFactor *= specularTintMapTexelToLinear( texture2D( specularTintMap, vUv ) ).rgb;\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\tmaterial.specularF90 = mix( specularIntensityFactor, 1.0, metalnessFactor );\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tfloat specularIntensityFactor = 1.0;\\\\n\\\\t\\\\tvec3 specularTintFactor = vec3( 1.0 );\\\\n\\\\t\\\\tmaterial.specularF90 = 1.0;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tmaterial.specularColor = mix( min( pow2( ( ior - 1.0 ) / ( ior + 1.0 ) ) * specularTintFactor, vec3( 1.0 ) ) * specularIntensityFactor, diffuseColor.rgb, metalnessFactor );\\\\n\\\\n#else\\\\n\\\\n\\\\tmaterial.specularColor = mix( vec3( 0.04 ), diffuseColor.rgb, metalnessFactor );\\\\n\\\\tmaterial.specularF90 = 1.0;\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\n\\\\tmaterial.clearcoat = clearcoat;\\\\n\\\\tmaterial.clearcoatRoughness = clearcoatRoughness;\\\\n\\\\tmaterial.clearcoatF0 = vec3( 0.04 );\\\\n\\\\tmaterial.clearcoatF90 = 1.0;\\\\n\\\\n\\\\t#ifdef USE_CLEARCOATMAP\\\\n\\\\n\\\\t\\\\tmaterial.clearcoat *= texture2D( clearcoatMap, vUv ).x;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef USE_CLEARCOAT_ROUGHNESSMAP\\\\n\\\\n\\\\t\\\\tmaterial.clearcoatRoughness *= texture2D( clearcoatRoughnessMap, vUv ).y;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tmaterial.clearcoat = saturate( material.clearcoat ); // Burley clearcoat model\\\\n\\\\tmaterial.clearcoatRoughness = max( material.clearcoatRoughness, 0.0525 );\\\\n\\\\tmaterial.clearcoatRoughness += geometryRoughness;\\\\n\\\\tmaterial.clearcoatRoughness = min( material.clearcoatRoughness, 1.0 );\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_SHEEN\\\\n\\\\n\\\\tmaterial.sheenTint = sheenTint;\\\\n\\\\tmaterial.sheenRoughness = clamp( sheenRoughness, 0.07, 1.0 );\\\\n\\\\n#endif\\\\n\\\\\\\",lights_physical_pars_fragment:'\\\\nstruct PhysicalMaterial {\\\\n\\\\n\\\\tvec3 diffuseColor;\\\\n\\\\tfloat roughness;\\\\n\\\\tvec3 specularColor;\\\\n\\\\tfloat specularF90;\\\\n\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\t\\\\tfloat clearcoat;\\\\n\\\\t\\\\tfloat clearcoatRoughness;\\\\n\\\\t\\\\tvec3 clearcoatF0;\\\\n\\\\t\\\\tfloat clearcoatF90;\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef USE_SHEEN\\\\n\\\\t\\\\tvec3 sheenTint;\\\\n\\\\t\\\\tfloat sheenRoughness;\\\\n\\\\t#endif\\\\n\\\\n};\\\\n\\\\n// temporary\\\\nvec3 clearcoatSpecular = vec3( 0.0 );\\\\n\\\\n// Analytical approximation of the DFG LUT, one half of the\\\\n// split-sum approximation used in indirect specular lighting.\\\\n// via \\\\'environmentBRDF\\\\' from \\\\\\\"Physically Based Shading on Mobile\\\\\\\"\\\\n// https://www.unrealengine.com/blog/physically-based-shading-on-mobile\\\\nvec2 DFGApprox( const in vec3 normal, const in vec3 viewDir, const in float roughness ) {\\\\n\\\\n\\\\tfloat dotNV = saturate( dot( normal, viewDir ) );\\\\n\\\\n\\\\tconst vec4 c0 = vec4( - 1, - 0.0275, - 0.572, 0.022 );\\\\n\\\\n\\\\tconst vec4 c1 = vec4( 1, 0.0425, 1.04, - 0.04 );\\\\n\\\\n\\\\tvec4 r = roughness * c0 + c1;\\\\n\\\\n\\\\tfloat a004 = min( r.x * r.x, exp2( - 9.28 * dotNV ) ) * r.x + r.y;\\\\n\\\\n\\\\tvec2 fab = vec2( - 1.04, 1.04 ) * a004 + r.zw;\\\\n\\\\n\\\\treturn fab;\\\\n\\\\n}\\\\n\\\\nvec3 EnvironmentBRDF( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness ) {\\\\n\\\\n\\\\tvec2 fab = DFGApprox( normal, viewDir, roughness );\\\\n\\\\n\\\\treturn specularColor * fab.x + specularF90 * fab.y;\\\\n\\\\n}\\\\n\\\\n// Fdez-Agüera\\\\'s \\\\\\\"Multiple-Scattering Microfacet Model for Real-Time Image Based Lighting\\\\\\\"\\\\n// Approximates multiscattering in order to preserve energy.\\\\n// http://www.jcgt.org/published/0008/01/03/\\\\nvoid computeMultiscattering( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness, inout vec3 singleScatter, inout vec3 multiScatter ) {\\\\n\\\\n\\\\tvec2 fab = DFGApprox( normal, viewDir, roughness );\\\\n\\\\n\\\\tvec3 FssEss = specularColor * fab.x + specularF90 * fab.y;\\\\n\\\\n\\\\tfloat Ess = fab.x + fab.y;\\\\n\\\\tfloat Ems = 1.0 - Ess;\\\\n\\\\n\\\\tvec3 Favg = specularColor + ( 1.0 - specularColor ) * 0.047619; // 1/21\\\\n\\\\tvec3 Fms = FssEss * Favg / ( 1.0 - Ems * Favg );\\\\n\\\\n\\\\tsingleScatter += FssEss;\\\\n\\\\tmultiScatter += Fms * Ems;\\\\n\\\\n}\\\\n\\\\n#if NUM_RECT_AREA_LIGHTS > 0\\\\n\\\\n\\\\tvoid RE_Direct_RectArea_Physical( const in RectAreaLight rectAreaLight, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\n\\\\t\\\\tvec3 normal = geometry.normal;\\\\n\\\\t\\\\tvec3 viewDir = geometry.viewDir;\\\\n\\\\t\\\\tvec3 position = geometry.position;\\\\n\\\\t\\\\tvec3 lightPos = rectAreaLight.position;\\\\n\\\\t\\\\tvec3 halfWidth = rectAreaLight.halfWidth;\\\\n\\\\t\\\\tvec3 halfHeight = rectAreaLight.halfHeight;\\\\n\\\\t\\\\tvec3 lightColor = rectAreaLight.color;\\\\n\\\\t\\\\tfloat roughness = material.roughness;\\\\n\\\\n\\\\t\\\\tvec3 rectCoords[ 4 ];\\\\n\\\\t\\\\trectCoords[ 0 ] = lightPos + halfWidth - halfHeight; // counterclockwise; light shines in local neg z direction\\\\n\\\\t\\\\trectCoords[ 1 ] = lightPos - halfWidth - halfHeight;\\\\n\\\\t\\\\trectCoords[ 2 ] = lightPos - halfWidth + halfHeight;\\\\n\\\\t\\\\trectCoords[ 3 ] = lightPos + halfWidth + halfHeight;\\\\n\\\\n\\\\t\\\\tvec2 uv = LTC_Uv( normal, viewDir, roughness );\\\\n\\\\n\\\\t\\\\tvec4 t1 = texture2D( ltc_1, uv );\\\\n\\\\t\\\\tvec4 t2 = texture2D( ltc_2, uv );\\\\n\\\\n\\\\t\\\\tmat3 mInv = mat3(\\\\n\\\\t\\\\t\\\\tvec3( t1.x, 0, t1.y ),\\\\n\\\\t\\\\t\\\\tvec3( 0, 1, 0 ),\\\\n\\\\t\\\\t\\\\tvec3( t1.z, 0, t1.w )\\\\n\\\\t\\\\t);\\\\n\\\\n\\\\t\\\\t// LTC Fresnel Approximation by Stephen Hill\\\\n\\\\t\\\\t// http://blog.selfshadow.com/publications/s2016-advances/s2016_ltc_fresnel.pdf\\\\n\\\\t\\\\tvec3 fresnel = ( material.specularColor * t2.x + ( vec3( 1.0 ) - material.specularColor ) * t2.y );\\\\n\\\\n\\\\t\\\\treflectedLight.directSpecular += lightColor * fresnel * LTC_Evaluate( normal, viewDir, position, mInv, rectCoords );\\\\n\\\\n\\\\t\\\\treflectedLight.directDiffuse += lightColor * material.diffuseColor * LTC_Evaluate( normal, viewDir, position, mat3( 1.0 ), rectCoords );\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\nvoid RE_Direct_Physical( const in IncidentLight directLight, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\n\\\\tfloat dotNL = saturate( dot( geometry.normal, directLight.direction ) );\\\\n\\\\n\\\\tvec3 irradiance = dotNL * directLight.color;\\\\n\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\n\\\\t\\\\tfloat dotNLcc = saturate( dot( geometry.clearcoatNormal, directLight.direction ) );\\\\n\\\\n\\\\t\\\\tvec3 ccIrradiance = dotNLcc * directLight.color;\\\\n\\\\n\\\\t\\\\tclearcoatSpecular += ccIrradiance * BRDF_GGX( directLight.direction, geometry.viewDir, geometry.clearcoatNormal, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef USE_SHEEN\\\\n\\\\n\\\\t\\\\treflectedLight.directSpecular += irradiance * BRDF_Sheen( directLight.direction, geometry.viewDir, geometry.normal, material.sheenTint, material.sheenRoughness );\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\treflectedLight.directSpecular += irradiance * BRDF_GGX( directLight.direction, geometry.viewDir, geometry.normal, material.specularColor, material.specularF90, material.roughness );\\\\n\\\\n\\\\n\\\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n}\\\\n\\\\nvoid RE_IndirectDiffuse_Physical( const in vec3 irradiance, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\n\\\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n\\\\n}\\\\n\\\\nvoid RE_IndirectSpecular_Physical( const in vec3 radiance, const in vec3 irradiance, const in vec3 clearcoatRadiance, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight) {\\\\n\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\n\\\\t\\\\tclearcoatSpecular += clearcoatRadiance * EnvironmentBRDF( geometry.clearcoatNormal, geometry.viewDir, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t// Both indirect specular and indirect diffuse light accumulate here\\\\n\\\\n\\\\tvec3 singleScattering = vec3( 0.0 );\\\\n\\\\tvec3 multiScattering = vec3( 0.0 );\\\\n\\\\tvec3 cosineWeightedIrradiance = irradiance * RECIPROCAL_PI;\\\\n\\\\n\\\\tcomputeMultiscattering( geometry.normal, geometry.viewDir, material.specularColor, material.specularF90, material.roughness, singleScattering, multiScattering );\\\\n\\\\n\\\\tvec3 diffuse = material.diffuseColor * ( 1.0 - ( singleScattering + multiScattering ) );\\\\n\\\\n\\\\treflectedLight.indirectSpecular += radiance * singleScattering;\\\\n\\\\treflectedLight.indirectSpecular += multiScattering * cosineWeightedIrradiance;\\\\n\\\\n\\\\treflectedLight.indirectDiffuse += diffuse * cosineWeightedIrradiance;\\\\n\\\\n}\\\\n\\\\n#define RE_Direct\\\\t\\\\t\\\\t\\\\tRE_Direct_Physical\\\\n#define RE_Direct_RectArea\\\\t\\\\tRE_Direct_RectArea_Physical\\\\n#define RE_IndirectDiffuse\\\\t\\\\tRE_IndirectDiffuse_Physical\\\\n#define RE_IndirectSpecular\\\\t\\\\tRE_IndirectSpecular_Physical\\\\n\\\\n// ref: https://seblagarde.files.wordpress.com/2015/07/course_notes_moving_frostbite_to_pbr_v32.pdf\\\\nfloat computeSpecularOcclusion( const in float dotNV, const in float ambientOcclusion, const in float roughness ) {\\\\n\\\\n\\\\treturn saturate( pow( dotNV + ambientOcclusion, exp2( - 16.0 * roughness - 1.0 ) ) - 1.0 + ambientOcclusion );\\\\n\\\\n}\\\\n',lights_fragment_begin:\\\\\\\"\\\\n/**\\\\n * This is a template that can be used to light a material, it uses pluggable\\\\n * RenderEquations (RE)for specific lighting scenarios.\\\\n *\\\\n * Instructions for use:\\\\n * - Ensure that both RE_Direct, RE_IndirectDiffuse and RE_IndirectSpecular are defined\\\\n * - If you have defined an RE_IndirectSpecular, you need to also provide a Material_LightProbeLOD. <---- ???\\\\n * - Create a material parameter that is to be passed as the third parameter to your lighting functions.\\\\n *\\\\n * TODO:\\\\n * - Add area light support.\\\\n * - Add sphere light support.\\\\n * - Add diffuse light probe (irradiance cubemap) support.\\\\n */\\\\n\\\\nGeometricContext geometry;\\\\n\\\\ngeometry.position = - vViewPosition;\\\\ngeometry.normal = normal;\\\\ngeometry.viewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( vViewPosition );\\\\n\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\n\\\\tgeometry.clearcoatNormal = clearcoatNormal;\\\\n\\\\n#endif\\\\n\\\\nIncidentLight directLight;\\\\n\\\\n#if ( NUM_POINT_LIGHTS > 0 ) && defined( RE_Direct )\\\\n\\\\n\\\\tPointLight pointLight;\\\\n\\\\t#if defined( USE_SHADOWMAP ) && NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\tPointLightShadow pointLightShadow;\\\\n\\\\t#endif\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\tpointLight = pointLights[ i ];\\\\n\\\\n\\\\t\\\\tgetPointLightInfo( pointLight, geometry, directLight );\\\\n\\\\n\\\\t\\\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_POINT_LIGHT_SHADOWS )\\\\n\\\\t\\\\tpointLightShadow = pointLightShadows[ i ];\\\\n\\\\t\\\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getPointShadow( pointShadowMap[ i ], pointLightShadow.shadowMapSize, pointLightShadow.shadowBias, pointLightShadow.shadowRadius, vPointShadowCoord[ i ], pointLightShadow.shadowCameraNear, pointLightShadow.shadowCameraFar ) : 1.0;\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\tRE_Direct( directLight, geometry, material, reflectedLight );\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n#endif\\\\n\\\\n#if ( NUM_SPOT_LIGHTS > 0 ) && defined( RE_Direct )\\\\n\\\\n\\\\tSpotLight spotLight;\\\\n\\\\t#if defined( USE_SHADOWMAP ) && NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\tSpotLightShadow spotLightShadow;\\\\n\\\\t#endif\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\tspotLight = spotLights[ i ];\\\\n\\\\n\\\\t\\\\tgetSpotLightInfo( spotLight, geometry, directLight );\\\\n\\\\n\\\\t\\\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\\\\n\\\\t\\\\tspotLightShadow = spotLightShadows[ i ];\\\\n\\\\t\\\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getShadow( spotShadowMap[ i ], spotLightShadow.shadowMapSize, spotLightShadow.shadowBias, spotLightShadow.shadowRadius, vSpotShadowCoord[ i ] ) : 1.0;\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\tRE_Direct( directLight, geometry, material, reflectedLight );\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n#endif\\\\n\\\\n#if ( NUM_DIR_LIGHTS > 0 ) && defined( RE_Direct )\\\\n\\\\n\\\\tDirectionalLight directionalLight;\\\\n\\\\t#if defined( USE_SHADOWMAP ) && NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\tDirectionalLightShadow directionalLightShadow;\\\\n\\\\t#endif\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\tdirectionalLight = directionalLights[ i ];\\\\n\\\\n\\\\t\\\\tgetDirectionalLightInfo( directionalLight, geometry, directLight );\\\\n\\\\n\\\\t\\\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_DIR_LIGHT_SHADOWS )\\\\n\\\\t\\\\tdirectionalLightShadow = directionalLightShadows[ i ];\\\\n\\\\t\\\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getShadow( directionalShadowMap[ i ], directionalLightShadow.shadowMapSize, directionalLightShadow.shadowBias, directionalLightShadow.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\tRE_Direct( directLight, geometry, material, reflectedLight );\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n#endif\\\\n\\\\n#if ( NUM_RECT_AREA_LIGHTS > 0 ) && defined( RE_Direct_RectArea )\\\\n\\\\n\\\\tRectAreaLight rectAreaLight;\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_RECT_AREA_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\trectAreaLight = rectAreaLights[ i ];\\\\n\\\\t\\\\tRE_Direct_RectArea( rectAreaLight, geometry, material, reflectedLight );\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n#endif\\\\n\\\\n#if defined( RE_IndirectDiffuse )\\\\n\\\\n\\\\tvec3 iblIrradiance = vec3( 0.0 );\\\\n\\\\n\\\\tvec3 irradiance = getAmbientLightIrradiance( ambientLightColor );\\\\n\\\\n\\\\tirradiance += getLightProbeIrradiance( lightProbe, geometry.normal );\\\\n\\\\n\\\\t#if ( NUM_HEMI_LIGHTS > 0 )\\\\n\\\\n\\\\t\\\\t#pragma unroll_loop_start\\\\n\\\\t\\\\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\\\\n\\\\n\\\\t\\\\t\\\\tirradiance += getHemisphereLightIrradiance( hemisphereLights[ i ], geometry.normal );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\n#if defined( RE_IndirectSpecular )\\\\n\\\\n\\\\tvec3 radiance = vec3( 0.0 );\\\\n\\\\tvec3 clearcoatRadiance = vec3( 0.0 );\\\\n\\\\n#endif\\\\n\\\\\\\",lights_fragment_maps:\\\\\\\"\\\\n#if defined( RE_IndirectDiffuse )\\\\n\\\\n\\\\t#ifdef USE_LIGHTMAP\\\\n\\\\n\\\\t\\\\tvec4 lightMapTexel = texture2D( lightMap, vUv2 );\\\\n\\\\t\\\\tvec3 lightMapIrradiance = lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\\\n\\\\n\\\\t\\\\t#ifndef PHYSICALLY_CORRECT_LIGHTS\\\\n\\\\n\\\\t\\\\t\\\\tlightMapIrradiance *= PI;\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\tirradiance += lightMapIrradiance;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if defined( USE_ENVMAP ) && defined( STANDARD ) && defined( ENVMAP_TYPE_CUBE_UV )\\\\n\\\\n\\\\t\\\\tiblIrradiance += getIBLIrradiance( geometry.normal );\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\n#if defined( USE_ENVMAP ) && defined( RE_IndirectSpecular )\\\\n\\\\n\\\\tradiance += getIBLRadiance( geometry.viewDir, geometry.normal, material.roughness );\\\\n\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\n\\\\t\\\\tclearcoatRadiance += getIBLRadiance( geometry.viewDir, geometry.clearcoatNormal, material.clearcoatRoughness );\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",lights_fragment_end:\\\\\\\"\\\\n#if defined( RE_IndirectDiffuse )\\\\n\\\\n\\\\tRE_IndirectDiffuse( irradiance, geometry, material, reflectedLight );\\\\n\\\\n#endif\\\\n\\\\n#if defined( RE_IndirectSpecular )\\\\n\\\\n\\\\tRE_IndirectSpecular( radiance, iblIrradiance, clearcoatRadiance, geometry, material, reflectedLight );\\\\n\\\\n#endif\\\\n\\\\\\\",logdepthbuf_fragment:\\\\\\\"\\\\n#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )\\\\n\\\\n\\\\t// Doing a strict comparison with == 1.0 can cause noise artifacts\\\\n\\\\t// on some platforms. See issue #17623.\\\\n\\\\tgl_FragDepthEXT = vIsPerspective == 0.0 ? gl_FragCoord.z : log2( vFragDepth ) * logDepthBufFC * 0.5;\\\\n\\\\n#endif\\\\n\\\\\\\",logdepthbuf_pars_fragment:\\\\\\\"\\\\n#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )\\\\n\\\\n\\\\tuniform float logDepthBufFC;\\\\n\\\\tvarying float vFragDepth;\\\\n\\\\tvarying float vIsPerspective;\\\\n\\\\n#endif\\\\n\\\\\\\",logdepthbuf_pars_vertex:\\\\\\\"\\\\n#ifdef USE_LOGDEPTHBUF\\\\n\\\\n\\\\t#ifdef USE_LOGDEPTHBUF_EXT\\\\n\\\\n\\\\t\\\\tvarying float vFragDepth;\\\\n\\\\t\\\\tvarying float vIsPerspective;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tuniform float logDepthBufFC;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",logdepthbuf_vertex:\\\\\\\"\\\\n#ifdef USE_LOGDEPTHBUF\\\\n\\\\n\\\\t#ifdef USE_LOGDEPTHBUF_EXT\\\\n\\\\n\\\\t\\\\tvFragDepth = 1.0 + gl_Position.w;\\\\n\\\\t\\\\tvIsPerspective = float( isPerspectiveMatrix( projectionMatrix ) );\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tif ( isPerspectiveMatrix( projectionMatrix ) ) {\\\\n\\\\n\\\\t\\\\t\\\\tgl_Position.z = log2( max( EPSILON, gl_Position.w + 1.0 ) ) * logDepthBufFC - 1.0;\\\\n\\\\n\\\\t\\\\t\\\\tgl_Position.z *= gl_Position.w;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",map_fragment:\\\\\\\"\\\\n#ifdef USE_MAP\\\\n\\\\n\\\\tvec4 texelColor = texture2D( map, vUv );\\\\n\\\\n\\\\ttexelColor = mapTexelToLinear( texelColor );\\\\n\\\\tdiffuseColor *= texelColor;\\\\n\\\\n#endif\\\\n\\\\\\\",map_pars_fragment:\\\\\\\"\\\\n#ifdef USE_MAP\\\\n\\\\n\\\\tuniform sampler2D map;\\\\n\\\\n#endif\\\\n\\\\\\\",map_particle_fragment:\\\\\\\"\\\\n#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\\\\n\\\\n\\\\tvec2 uv = ( uvTransform * vec3( gl_PointCoord.x, 1.0 - gl_PointCoord.y, 1 ) ).xy;\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_MAP\\\\n\\\\n\\\\tvec4 mapTexel = texture2D( map, uv );\\\\n\\\\tdiffuseColor *= mapTexelToLinear( mapTexel );\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_ALPHAMAP\\\\n\\\\n\\\\tdiffuseColor.a *= texture2D( alphaMap, uv ).g;\\\\n\\\\n#endif\\\\n\\\\\\\",map_particle_pars_fragment:\\\\\\\"\\\\n#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\\\\n\\\\n\\\\tuniform mat3 uvTransform;\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_MAP\\\\n\\\\n\\\\tuniform sampler2D map;\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_ALPHAMAP\\\\n\\\\n\\\\tuniform sampler2D alphaMap;\\\\n\\\\n#endif\\\\n\\\\\\\",metalnessmap_fragment:\\\\\\\"\\\\nfloat metalnessFactor = metalness;\\\\n\\\\n#ifdef USE_METALNESSMAP\\\\n\\\\n\\\\tvec4 texelMetalness = texture2D( metalnessMap, vUv );\\\\n\\\\n\\\\t// reads channel B, compatible with a combined OcclusionRoughnessMetallic (RGB) texture\\\\n\\\\tmetalnessFactor *= texelMetalness.b;\\\\n\\\\n#endif\\\\n\\\\\\\",metalnessmap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_METALNESSMAP\\\\n\\\\n\\\\tuniform sampler2D metalnessMap;\\\\n\\\\n#endif\\\\n\\\\\\\",morphnormal_vertex:\\\\\\\"\\\\n#ifdef USE_MORPHNORMALS\\\\n\\\\n\\\\t// morphTargetBaseInfluence is set based on BufferGeometry.morphTargetsRelative value:\\\\n\\\\t// When morphTargetsRelative is false, this is set to 1 - sum(influences); this results in normal = sum((target - base) * influence)\\\\n\\\\t// When morphTargetsRelative is true, this is set to 1; as a result, all morph targets are simply added to the base after weighting\\\\n\\\\tobjectNormal *= morphTargetBaseInfluence;\\\\n\\\\n\\\\t#ifdef MORPHTARGETS_TEXTURE\\\\n\\\\n\\\\t\\\\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\\\\n\\\\n\\\\t\\\\t\\\\tif ( morphTargetInfluences[ i ] > 0.0 ) objectNormal += getMorph( gl_VertexID, i, 1, 2 ) * morphTargetInfluences[ i ];\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tobjectNormal += morphNormal0 * morphTargetInfluences[ 0 ];\\\\n\\\\t\\\\tobjectNormal += morphNormal1 * morphTargetInfluences[ 1 ];\\\\n\\\\t\\\\tobjectNormal += morphNormal2 * morphTargetInfluences[ 2 ];\\\\n\\\\t\\\\tobjectNormal += morphNormal3 * morphTargetInfluences[ 3 ];\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",morphtarget_pars_vertex:\\\\\\\"\\\\n#ifdef USE_MORPHTARGETS\\\\n\\\\n\\\\tuniform float morphTargetBaseInfluence;\\\\n\\\\n\\\\t#ifdef MORPHTARGETS_TEXTURE\\\\n\\\\n\\\\t\\\\tuniform float morphTargetInfluences[ MORPHTARGETS_COUNT ];\\\\n\\\\t\\\\tuniform sampler2DArray morphTargetsTexture;\\\\n\\\\t\\\\tuniform vec2 morphTargetsTextureSize;\\\\n\\\\n\\\\t\\\\tvec3 getMorph( const in int vertexIndex, const in int morphTargetIndex, const in int offset, const in int stride ) {\\\\n\\\\n\\\\t\\\\t\\\\tfloat texelIndex = float( vertexIndex * stride + offset );\\\\n\\\\t\\\\t\\\\tfloat y = floor( texelIndex / morphTargetsTextureSize.x );\\\\n\\\\t\\\\t\\\\tfloat x = texelIndex - y * morphTargetsTextureSize.x;\\\\n\\\\n\\\\t\\\\t\\\\tvec3 morphUV = vec3( ( x + 0.5 ) / morphTargetsTextureSize.x, y / morphTargetsTextureSize.y, morphTargetIndex );\\\\n\\\\t\\\\t\\\\treturn texture( morphTargetsTexture, morphUV ).xyz;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\t#ifndef USE_MORPHNORMALS\\\\n\\\\n\\\\t\\\\t\\\\tuniform float morphTargetInfluences[ 8 ];\\\\n\\\\n\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\tuniform float morphTargetInfluences[ 4 ];\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",morphtarget_vertex:\\\\\\\"\\\\n#ifdef USE_MORPHTARGETS\\\\n\\\\n\\\\t// morphTargetBaseInfluence is set based on BufferGeometry.morphTargetsRelative value:\\\\n\\\\t// When morphTargetsRelative is false, this is set to 1 - sum(influences); this results in position = sum((target - base) * influence)\\\\n\\\\t// When morphTargetsRelative is true, this is set to 1; as a result, all morph targets are simply added to the base after weighting\\\\n\\\\ttransformed *= morphTargetBaseInfluence;\\\\n\\\\n\\\\t#ifdef MORPHTARGETS_TEXTURE\\\\n\\\\n\\\\t\\\\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\\\\n\\\\n\\\\t\\\\t\\\\t#ifndef USE_MORPHNORMALS\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tif ( morphTargetInfluences[ i ] > 0.0 ) transformed += getMorph( gl_VertexID, i, 0, 1 ) * morphTargetInfluences[ i ];\\\\n\\\\n\\\\t\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tif ( morphTargetInfluences[ i ] > 0.0 ) transformed += getMorph( gl_VertexID, i, 0, 2 ) * morphTargetInfluences[ i ];\\\\n\\\\n\\\\t\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\ttransformed += morphTarget0 * morphTargetInfluences[ 0 ];\\\\n\\\\t\\\\ttransformed += morphTarget1 * morphTargetInfluences[ 1 ];\\\\n\\\\t\\\\ttransformed += morphTarget2 * morphTargetInfluences[ 2 ];\\\\n\\\\t\\\\ttransformed += morphTarget3 * morphTargetInfluences[ 3 ];\\\\n\\\\n\\\\t\\\\t#ifndef USE_MORPHNORMALS\\\\n\\\\n\\\\t\\\\t\\\\ttransformed += morphTarget4 * morphTargetInfluences[ 4 ];\\\\n\\\\t\\\\t\\\\ttransformed += morphTarget5 * morphTargetInfluences[ 5 ];\\\\n\\\\t\\\\t\\\\ttransformed += morphTarget6 * morphTargetInfluences[ 6 ];\\\\n\\\\t\\\\t\\\\ttransformed += morphTarget7 * morphTargetInfluences[ 7 ];\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",normal_fragment_begin:\\\\\\\"\\\\nfloat faceDirection = gl_FrontFacing ? 1.0 : - 1.0;\\\\n\\\\n#ifdef FLAT_SHADED\\\\n\\\\n\\\\t// Workaround for Adreno GPUs not able to do dFdx( vViewPosition )\\\\n\\\\n\\\\tvec3 fdx = vec3( dFdx( vViewPosition.x ), dFdx( vViewPosition.y ), dFdx( vViewPosition.z ) );\\\\n\\\\tvec3 fdy = vec3( dFdy( vViewPosition.x ), dFdy( vViewPosition.y ), dFdy( vViewPosition.z ) );\\\\n\\\\tvec3 normal = normalize( cross( fdx, fdy ) );\\\\n\\\\n#else\\\\n\\\\n\\\\tvec3 normal = normalize( vNormal );\\\\n\\\\n\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\tnormal = normal * faceDirection;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\n\\\\t\\\\tvec3 tangent = normalize( vTangent );\\\\n\\\\t\\\\tvec3 bitangent = normalize( vBitangent );\\\\n\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\t\\\\ttangent = tangent * faceDirection;\\\\n\\\\t\\\\t\\\\tbitangent = bitangent * faceDirection;\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\t#if defined( TANGENTSPACE_NORMALMAP ) || defined( USE_CLEARCOAT_NORMALMAP )\\\\n\\\\n\\\\t\\\\t\\\\tmat3 vTBN = mat3( tangent, bitangent, normal );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\n// non perturbed normal for clearcoat among others\\\\n\\\\nvec3 geometryNormal = normal;\\\\n\\\\n\\\\\\\",normal_fragment_maps:\\\\\\\"\\\\n\\\\n#ifdef OBJECTSPACE_NORMALMAP\\\\n\\\\n\\\\tnormal = texture2D( normalMap, vUv ).xyz * 2.0 - 1.0; // overrides both flatShading and attribute normals\\\\n\\\\n\\\\t#ifdef FLIP_SIDED\\\\n\\\\n\\\\t\\\\tnormal = - normal;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\tnormal = normal * faceDirection;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tnormal = normalize( normalMatrix * normal );\\\\n\\\\n#elif defined( TANGENTSPACE_NORMALMAP )\\\\n\\\\n\\\\tvec3 mapN = texture2D( normalMap, vUv ).xyz * 2.0 - 1.0;\\\\n\\\\tmapN.xy *= normalScale;\\\\n\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\n\\\\t\\\\tnormal = normalize( vTBN * mapN );\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tnormal = perturbNormal2Arb( - vViewPosition, normal, mapN, faceDirection );\\\\n\\\\n\\\\t#endif\\\\n\\\\n#elif defined( USE_BUMPMAP )\\\\n\\\\n\\\\tnormal = perturbNormalArb( - vViewPosition, normal, dHdxy_fwd(), faceDirection );\\\\n\\\\n#endif\\\\n\\\\\\\",normal_pars_fragment:\\\\\\\"\\\\n#ifndef FLAT_SHADED\\\\n\\\\n\\\\tvarying vec3 vNormal;\\\\n\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\n\\\\t\\\\tvarying vec3 vTangent;\\\\n\\\\t\\\\tvarying vec3 vBitangent;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",normal_pars_vertex:\\\\\\\"\\\\n#ifndef FLAT_SHADED\\\\n\\\\n\\\\tvarying vec3 vNormal;\\\\n\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\n\\\\t\\\\tvarying vec3 vTangent;\\\\n\\\\t\\\\tvarying vec3 vBitangent;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",normal_vertex:\\\\\\\"\\\\n#ifndef FLAT_SHADED // normal is computed with derivatives when FLAT_SHADED\\\\n\\\\n\\\\tvNormal = normalize( transformedNormal );\\\\n\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\n\\\\t\\\\tvTangent = normalize( transformedTangent );\\\\n\\\\t\\\\tvBitangent = normalize( cross( vNormal, vTangent ) * tangent.w );\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",normalmap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_NORMALMAP\\\\n\\\\n\\\\tuniform sampler2D normalMap;\\\\n\\\\tuniform vec2 normalScale;\\\\n\\\\n#endif\\\\n\\\\n#ifdef OBJECTSPACE_NORMALMAP\\\\n\\\\n\\\\tuniform mat3 normalMatrix;\\\\n\\\\n#endif\\\\n\\\\n#if ! defined ( USE_TANGENT ) && ( defined ( TANGENTSPACE_NORMALMAP ) || defined ( USE_CLEARCOAT_NORMALMAP ) )\\\\n\\\\n\\\\t// Normal Mapping Without Precomputed Tangents\\\\n\\\\t// http://www.thetenthplanet.de/archives/1180\\\\n\\\\n\\\\tvec3 perturbNormal2Arb( vec3 eye_pos, vec3 surf_norm, vec3 mapN, float faceDirection ) {\\\\n\\\\n\\\\t\\\\t// Workaround for Adreno 3XX dFd*( vec3 ) bug. See #9988\\\\n\\\\n\\\\t\\\\tvec3 q0 = vec3( dFdx( eye_pos.x ), dFdx( eye_pos.y ), dFdx( eye_pos.z ) );\\\\n\\\\t\\\\tvec3 q1 = vec3( dFdy( eye_pos.x ), dFdy( eye_pos.y ), dFdy( eye_pos.z ) );\\\\n\\\\t\\\\tvec2 st0 = dFdx( vUv.st );\\\\n\\\\t\\\\tvec2 st1 = dFdy( vUv.st );\\\\n\\\\n\\\\t\\\\tvec3 N = surf_norm; // normalized\\\\n\\\\n\\\\t\\\\tvec3 q1perp = cross( q1, N );\\\\n\\\\t\\\\tvec3 q0perp = cross( N, q0 );\\\\n\\\\n\\\\t\\\\tvec3 T = q1perp * st0.x + q0perp * st1.x;\\\\n\\\\t\\\\tvec3 B = q1perp * st0.y + q0perp * st1.y;\\\\n\\\\n\\\\t\\\\tfloat det = max( dot( T, T ), dot( B, B ) );\\\\n\\\\t\\\\tfloat scale = ( det == 0.0 ) ? 0.0 : faceDirection * inversesqrt( det );\\\\n\\\\n\\\\t\\\\treturn normalize( T * ( mapN.x * scale ) + B * ( mapN.y * scale ) + N * mapN.z );\\\\n\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\\\\",clearcoat_normal_fragment_begin:\\\\\\\"\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\n\\\\tvec3 clearcoatNormal = geometryNormal;\\\\n\\\\n#endif\\\\n\\\\\\\",clearcoat_normal_fragment_maps:\\\\\\\"\\\\n#ifdef USE_CLEARCOAT_NORMALMAP\\\\n\\\\n\\\\tvec3 clearcoatMapN = texture2D( clearcoatNormalMap, vUv ).xyz * 2.0 - 1.0;\\\\n\\\\tclearcoatMapN.xy *= clearcoatNormalScale;\\\\n\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\n\\\\t\\\\tclearcoatNormal = normalize( vTBN * clearcoatMapN );\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tclearcoatNormal = perturbNormal2Arb( - vViewPosition, clearcoatNormal, clearcoatMapN, faceDirection );\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",clearcoat_pars_fragment:\\\\\\\"\\\\n\\\\n#ifdef USE_CLEARCOATMAP\\\\n\\\\n\\\\tuniform sampler2D clearcoatMap;\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\\\\n\\\\n\\\\tuniform sampler2D clearcoatRoughnessMap;\\\\n\\\\n#endif\\\\n\\\\n#ifdef USE_CLEARCOAT_NORMALMAP\\\\n\\\\n\\\\tuniform sampler2D clearcoatNormalMap;\\\\n\\\\tuniform vec2 clearcoatNormalScale;\\\\n\\\\n#endif\\\\n\\\\\\\",output_fragment:\\\\\\\"\\\\n#ifdef OPAQUE\\\\ndiffuseColor.a = 1.0;\\\\n#endif\\\\n\\\\n// https://github.com/mrdoob/three.js/pull/22425\\\\n#ifdef USE_TRANSMISSION\\\\ndiffuseColor.a *= transmissionAlpha + 0.1;\\\\n#endif\\\\n\\\\ngl_FragColor = vec4( outgoingLight, diffuseColor.a );\\\\n\\\\\\\",packing:\\\\\\\"\\\\nvec3 packNormalToRGB( const in vec3 normal ) {\\\\n\\\\treturn normalize( normal ) * 0.5 + 0.5;\\\\n}\\\\n\\\\nvec3 unpackRGBToNormal( const in vec3 rgb ) {\\\\n\\\\treturn 2.0 * rgb.xyz - 1.0;\\\\n}\\\\n\\\\nconst float PackUpscale = 256. / 255.; // fraction -> 0..1 (including 1)\\\\nconst float UnpackDownscale = 255. / 256.; // 0..1 -> fraction (excluding 1)\\\\n\\\\nconst vec3 PackFactors = vec3( 256. * 256. * 256., 256. * 256., 256. );\\\\nconst vec4 UnpackFactors = UnpackDownscale / vec4( PackFactors, 1. );\\\\n\\\\nconst float ShiftRight8 = 1. / 256.;\\\\n\\\\nvec4 packDepthToRGBA( const in float v ) {\\\\n\\\\tvec4 r = vec4( fract( v * PackFactors ), v );\\\\n\\\\tr.yzw -= r.xyz * ShiftRight8; // tidy overflow\\\\n\\\\treturn r * PackUpscale;\\\\n}\\\\n\\\\nfloat unpackRGBAToDepth( const in vec4 v ) {\\\\n\\\\treturn dot( v, UnpackFactors );\\\\n}\\\\n\\\\nvec4 pack2HalfToRGBA( vec2 v ) {\\\\n\\\\tvec4 r = vec4( v.x, fract( v.x * 255.0 ), v.y, fract( v.y * 255.0 ) );\\\\n\\\\treturn vec4( r.x - r.y / 255.0, r.y, r.z - r.w / 255.0, r.w );\\\\n}\\\\n\\\\nvec2 unpackRGBATo2Half( vec4 v ) {\\\\n\\\\treturn vec2( v.x + ( v.y / 255.0 ), v.z + ( v.w / 255.0 ) );\\\\n}\\\\n\\\\n// NOTE: viewZ/eyeZ is < 0 when in front of the camera per OpenGL conventions\\\\n\\\\nfloat viewZToOrthographicDepth( const in float viewZ, const in float near, const in float far ) {\\\\n\\\\treturn ( viewZ + near ) / ( near - far );\\\\n}\\\\nfloat orthographicDepthToViewZ( const in float linearClipZ, const in float near, const in float far ) {\\\\n\\\\treturn linearClipZ * ( near - far ) - near;\\\\n}\\\\n\\\\n// NOTE: https://twitter.com/gonnavis/status/1377183786949959682\\\\n\\\\nfloat viewZToPerspectiveDepth( const in float viewZ, const in float near, const in float far ) {\\\\n\\\\treturn ( ( near + viewZ ) * far ) / ( ( far - near ) * viewZ );\\\\n}\\\\nfloat perspectiveDepthToViewZ( const in float invClipZ, const in float near, const in float far ) {\\\\n\\\\treturn ( near * far ) / ( ( far - near ) * invClipZ - far );\\\\n}\\\\n\\\\\\\",premultiplied_alpha_fragment:\\\\\\\"\\\\n#ifdef PREMULTIPLIED_ALPHA\\\\n\\\\n\\\\t// Get get normal blending with premultipled, use with CustomBlending, OneFactor, OneMinusSrcAlphaFactor, AddEquation.\\\\n\\\\tgl_FragColor.rgb *= gl_FragColor.a;\\\\n\\\\n#endif\\\\n\\\\\\\",project_vertex:\\\\\\\"\\\\nvec4 mvPosition = vec4( transformed, 1.0 );\\\\n\\\\n#ifdef USE_INSTANCING\\\\n\\\\n\\\\tmvPosition = instanceMatrix * mvPosition;\\\\n\\\\n#endif\\\\n\\\\nmvPosition = modelViewMatrix * mvPosition;\\\\n\\\\ngl_Position = projectionMatrix * mvPosition;\\\\n\\\\\\\",dithering_fragment:\\\\\\\"\\\\n#ifdef DITHERING\\\\n\\\\n\\\\tgl_FragColor.rgb = dithering( gl_FragColor.rgb );\\\\n\\\\n#endif\\\\n\\\\\\\",dithering_pars_fragment:\\\\\\\"\\\\n#ifdef DITHERING\\\\n\\\\n\\\\t// based on https://www.shadertoy.com/view/MslGR8\\\\n\\\\tvec3 dithering( vec3 color ) {\\\\n\\\\t\\\\t//Calculate grid position\\\\n\\\\t\\\\tfloat grid_position = rand( gl_FragCoord.xy );\\\\n\\\\n\\\\t\\\\t//Shift the individual colors differently, thus making it even harder to see the dithering pattern\\\\n\\\\t\\\\tvec3 dither_shift_RGB = vec3( 0.25 / 255.0, -0.25 / 255.0, 0.25 / 255.0 );\\\\n\\\\n\\\\t\\\\t//modify shift acording to grid position.\\\\n\\\\t\\\\tdither_shift_RGB = mix( 2.0 * dither_shift_RGB, -2.0 * dither_shift_RGB, grid_position );\\\\n\\\\n\\\\t\\\\t//shift the color by dither_shift\\\\n\\\\t\\\\treturn color + dither_shift_RGB;\\\\n\\\\t}\\\\n\\\\n#endif\\\\n\\\\\\\",roughnessmap_fragment:\\\\\\\"\\\\nfloat roughnessFactor = roughness;\\\\n\\\\n#ifdef USE_ROUGHNESSMAP\\\\n\\\\n\\\\tvec4 texelRoughness = texture2D( roughnessMap, vUv );\\\\n\\\\n\\\\t// reads channel G, compatible with a combined OcclusionRoughnessMetallic (RGB) texture\\\\n\\\\troughnessFactor *= texelRoughness.g;\\\\n\\\\n#endif\\\\n\\\\\\\",roughnessmap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_ROUGHNESSMAP\\\\n\\\\n\\\\tuniform sampler2D roughnessMap;\\\\n\\\\n#endif\\\\n\\\\\\\",shadowmap_pars_fragment:z,shadowmap_pars_vertex:\\\\\\\"\\\\n#ifdef USE_SHADOWMAP\\\\n\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t\\\\tuniform mat4 directionalShadowMatrix[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t\\\\tstruct DirectionalLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t};\\\\n\\\\n\\\\t\\\\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t\\\\tuniform mat4 spotShadowMatrix[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vSpotShadowCoord[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t\\\\tstruct SpotLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t};\\\\n\\\\n\\\\t\\\\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t\\\\tuniform mat4 pointShadowMatrix[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t\\\\tstruct PointLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t\\\\tfloat shadowCameraNear;\\\\n\\\\t\\\\t\\\\tfloat shadowCameraFar;\\\\n\\\\t\\\\t};\\\\n\\\\n\\\\t\\\\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t/*\\\\n\\\\t#if NUM_RECT_AREA_LIGHTS > 0\\\\n\\\\n\\\\t\\\\t// TODO (abelnation): uniforms for area light shadows\\\\n\\\\n\\\\t#endif\\\\n\\\\t*/\\\\n\\\\n#endif\\\\n\\\\\\\",shadowmap_vertex:\\\\\\\"\\\\n#ifdef USE_SHADOWMAP\\\\n\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0 || NUM_SPOT_LIGHT_SHADOWS > 0 || NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t\\\\t// Offsetting the position used for querying occlusion along the world normal can be used to reduce shadow acne.\\\\n\\\\t\\\\tvec3 shadowWorldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\\\\n\\\\t\\\\tvec4 shadowWorldPosition;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\n\\\\t\\\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * directionalLightShadows[ i ].shadowNormalBias, 0 );\\\\n\\\\t\\\\tvDirectionalShadowCoord[ i ] = directionalShadowMatrix[ i ] * shadowWorldPosition;\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\n\\\\t\\\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * spotLightShadows[ i ].shadowNormalBias, 0 );\\\\n\\\\t\\\\tvSpotShadowCoord[ i ] = spotShadowMatrix[ i ] * shadowWorldPosition;\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\n\\\\t\\\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * pointLightShadows[ i ].shadowNormalBias, 0 );\\\\n\\\\t\\\\tvPointShadowCoord[ i ] = pointShadowMatrix[ i ] * shadowWorldPosition;\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t/*\\\\n\\\\t#if NUM_RECT_AREA_LIGHTS > 0\\\\n\\\\n\\\\t\\\\t// TODO (abelnation): update vAreaShadowCoord with area light info\\\\n\\\\n\\\\t#endif\\\\n\\\\t*/\\\\n\\\\n#endif\\\\n\\\\\\\",shadowmask_pars_fragment:\\\\\\\"\\\\nfloat getShadowMask() {\\\\n\\\\n\\\\tfloat shadow = 1.0;\\\\n\\\\n\\\\t#ifdef USE_SHADOWMAP\\\\n\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\tDirectionalLightShadow directionalLight;\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\n\\\\t\\\\tdirectionalLight = directionalLightShadows[ i ];\\\\n\\\\t\\\\tshadow *= receiveShadow ? getShadow( directionalShadowMap[ i ], directionalLight.shadowMapSize, directionalLight.shadowBias, directionalLight.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\tSpotLightShadow spotLight;\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\n\\\\t\\\\tspotLight = spotLightShadows[ i ];\\\\n\\\\t\\\\tshadow *= receiveShadow ? getShadow( spotShadowMap[ i ], spotLight.shadowMapSize, spotLight.shadowBias, spotLight.shadowRadius, vSpotShadowCoord[ i ] ) : 1.0;\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\n\\\\tPointLightShadow pointLight;\\\\n\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\n\\\\t\\\\tpointLight = pointLightShadows[ i ];\\\\n\\\\t\\\\tshadow *= receiveShadow ? getPointShadow( pointShadowMap[ i ], pointLight.shadowMapSize, pointLight.shadowBias, pointLight.shadowRadius, vPointShadowCoord[ i ], pointLight.shadowCameraNear, pointLight.shadowCameraFar ) : 1.0;\\\\n\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t/*\\\\n\\\\t#if NUM_RECT_AREA_LIGHTS > 0\\\\n\\\\n\\\\t\\\\t// TODO (abelnation): update shadow for Area light\\\\n\\\\n\\\\t#endif\\\\n\\\\t*/\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\treturn shadow;\\\\n\\\\n}\\\\n\\\\\\\",skinbase_vertex:\\\\\\\"\\\\n#ifdef USE_SKINNING\\\\n\\\\n\\\\tmat4 boneMatX = getBoneMatrix( skinIndex.x );\\\\n\\\\tmat4 boneMatY = getBoneMatrix( skinIndex.y );\\\\n\\\\tmat4 boneMatZ = getBoneMatrix( skinIndex.z );\\\\n\\\\tmat4 boneMatW = getBoneMatrix( skinIndex.w );\\\\n\\\\n#endif\\\\n\\\\\\\",skinning_pars_vertex:\\\\\\\"\\\\n#ifdef USE_SKINNING\\\\n\\\\n\\\\tuniform mat4 bindMatrix;\\\\n\\\\tuniform mat4 bindMatrixInverse;\\\\n\\\\n\\\\t#ifdef BONE_TEXTURE\\\\n\\\\n\\\\t\\\\tuniform highp sampler2D boneTexture;\\\\n\\\\t\\\\tuniform int boneTextureSize;\\\\n\\\\n\\\\t\\\\tmat4 getBoneMatrix( const in float i ) {\\\\n\\\\n\\\\t\\\\t\\\\tfloat j = i * 4.0;\\\\n\\\\t\\\\t\\\\tfloat x = mod( j, float( boneTextureSize ) );\\\\n\\\\t\\\\t\\\\tfloat y = floor( j / float( boneTextureSize ) );\\\\n\\\\n\\\\t\\\\t\\\\tfloat dx = 1.0 / float( boneTextureSize );\\\\n\\\\t\\\\t\\\\tfloat dy = 1.0 / float( boneTextureSize );\\\\n\\\\n\\\\t\\\\t\\\\ty = dy * ( y + 0.5 );\\\\n\\\\n\\\\t\\\\t\\\\tvec4 v1 = texture2D( boneTexture, vec2( dx * ( x + 0.5 ), y ) );\\\\n\\\\t\\\\t\\\\tvec4 v2 = texture2D( boneTexture, vec2( dx * ( x + 1.5 ), y ) );\\\\n\\\\t\\\\t\\\\tvec4 v3 = texture2D( boneTexture, vec2( dx * ( x + 2.5 ), y ) );\\\\n\\\\t\\\\t\\\\tvec4 v4 = texture2D( boneTexture, vec2( dx * ( x + 3.5 ), y ) );\\\\n\\\\n\\\\t\\\\t\\\\tmat4 bone = mat4( v1, v2, v3, v4 );\\\\n\\\\n\\\\t\\\\t\\\\treturn bone;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tuniform mat4 boneMatrices[ MAX_BONES ];\\\\n\\\\n\\\\t\\\\tmat4 getBoneMatrix( const in float i ) {\\\\n\\\\n\\\\t\\\\t\\\\tmat4 bone = boneMatrices[ int(i) ];\\\\n\\\\t\\\\t\\\\treturn bone;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",skinning_vertex:\\\\\\\"\\\\n#ifdef USE_SKINNING\\\\n\\\\n\\\\tvec4 skinVertex = bindMatrix * vec4( transformed, 1.0 );\\\\n\\\\n\\\\tvec4 skinned = vec4( 0.0 );\\\\n\\\\tskinned += boneMatX * skinVertex * skinWeight.x;\\\\n\\\\tskinned += boneMatY * skinVertex * skinWeight.y;\\\\n\\\\tskinned += boneMatZ * skinVertex * skinWeight.z;\\\\n\\\\tskinned += boneMatW * skinVertex * skinWeight.w;\\\\n\\\\n\\\\ttransformed = ( bindMatrixInverse * skinned ).xyz;\\\\n\\\\n#endif\\\\n\\\\\\\",skinnormal_vertex:\\\\\\\"\\\\n#ifdef USE_SKINNING\\\\n\\\\n\\\\tmat4 skinMatrix = mat4( 0.0 );\\\\n\\\\tskinMatrix += skinWeight.x * boneMatX;\\\\n\\\\tskinMatrix += skinWeight.y * boneMatY;\\\\n\\\\tskinMatrix += skinWeight.z * boneMatZ;\\\\n\\\\tskinMatrix += skinWeight.w * boneMatW;\\\\n\\\\tskinMatrix = bindMatrixInverse * skinMatrix * bindMatrix;\\\\n\\\\n\\\\tobjectNormal = vec4( skinMatrix * vec4( objectNormal, 0.0 ) ).xyz;\\\\n\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\n\\\\t\\\\tobjectTangent = vec4( skinMatrix * vec4( objectTangent, 0.0 ) ).xyz;\\\\n\\\\n\\\\t#endif\\\\n\\\\n#endif\\\\n\\\\\\\",specularmap_fragment:\\\\\\\"\\\\nfloat specularStrength;\\\\n\\\\n#ifdef USE_SPECULARMAP\\\\n\\\\n\\\\tvec4 texelSpecular = texture2D( specularMap, vUv );\\\\n\\\\tspecularStrength = texelSpecular.r;\\\\n\\\\n#else\\\\n\\\\n\\\\tspecularStrength = 1.0;\\\\n\\\\n#endif\\\\n\\\\\\\",specularmap_pars_fragment:\\\\\\\"\\\\n#ifdef USE_SPECULARMAP\\\\n\\\\n\\\\tuniform sampler2D specularMap;\\\\n\\\\n#endif\\\\n\\\\\\\",tonemapping_fragment:\\\\\\\"\\\\n#if defined( TONE_MAPPING )\\\\n\\\\n\\\\tgl_FragColor.rgb = toneMapping( gl_FragColor.rgb );\\\\n\\\\n#endif\\\\n\\\\\\\",tonemapping_pars_fragment:\\\\\\\"\\\\n#ifndef saturate\\\\n// may have defined saturate() already\\\\n#define saturate( a ) clamp( a, 0.0, 1.0 )\\\\n#endif\\\\n\\\\nuniform float toneMappingExposure;\\\\n\\\\n// exposure only\\\\nvec3 LinearToneMapping( vec3 color ) {\\\\n\\\\n\\\\treturn toneMappingExposure * color;\\\\n\\\\n}\\\\n\\\\n// source: https://www.cs.utah.edu/~reinhard/cdrom/\\\\nvec3 ReinhardToneMapping( vec3 color ) {\\\\n\\\\n\\\\tcolor *= toneMappingExposure;\\\\n\\\\treturn saturate( color / ( vec3( 1.0 ) + color ) );\\\\n\\\\n}\\\\n\\\\n// source: http://filmicworlds.com/blog/filmic-tonemapping-operators/\\\\nvec3 OptimizedCineonToneMapping( vec3 color ) {\\\\n\\\\n\\\\t// optimized filmic operator by Jim Hejl and Richard Burgess-Dawson\\\\n\\\\tcolor *= toneMappingExposure;\\\\n\\\\tcolor = max( vec3( 0.0 ), color - 0.004 );\\\\n\\\\treturn pow( ( color * ( 6.2 * color + 0.5 ) ) / ( color * ( 6.2 * color + 1.7 ) + 0.06 ), vec3( 2.2 ) );\\\\n\\\\n}\\\\n\\\\n// source: https://github.com/selfshadow/ltc_code/blob/master/webgl/shaders/ltc/ltc_blit.fs\\\\nvec3 RRTAndODTFit( vec3 v ) {\\\\n\\\\n\\\\tvec3 a = v * ( v + 0.0245786 ) - 0.000090537;\\\\n\\\\tvec3 b = v * ( 0.983729 * v + 0.4329510 ) + 0.238081;\\\\n\\\\treturn a / b;\\\\n\\\\n}\\\\n\\\\n// this implementation of ACES is modified to accommodate a brighter viewing environment.\\\\n// the scale factor of 1/0.6 is subjective. see discussion in #19621.\\\\n\\\\nvec3 ACESFilmicToneMapping( vec3 color ) {\\\\n\\\\n\\\\t// sRGB => XYZ => D65_2_D60 => AP1 => RRT_SAT\\\\n\\\\tconst mat3 ACESInputMat = mat3(\\\\n\\\\t\\\\tvec3( 0.59719, 0.07600, 0.02840 ), // transposed from source\\\\n\\\\t\\\\tvec3( 0.35458, 0.90834, 0.13383 ),\\\\n\\\\t\\\\tvec3( 0.04823, 0.01566, 0.83777 )\\\\n\\\\t);\\\\n\\\\n\\\\t// ODT_SAT => XYZ => D60_2_D65 => sRGB\\\\n\\\\tconst mat3 ACESOutputMat = mat3(\\\\n\\\\t\\\\tvec3( 1.60475, -0.10208, -0.00327 ), // transposed from source\\\\n\\\\t\\\\tvec3( -0.53108, 1.10813, -0.07276 ),\\\\n\\\\t\\\\tvec3( -0.07367, -0.00605, 1.07602 )\\\\n\\\\t);\\\\n\\\\n\\\\tcolor *= toneMappingExposure / 0.6;\\\\n\\\\n\\\\tcolor = ACESInputMat * color;\\\\n\\\\n\\\\t// Apply RRT and ODT\\\\n\\\\tcolor = RRTAndODTFit( color );\\\\n\\\\n\\\\tcolor = ACESOutputMat * color;\\\\n\\\\n\\\\t// Clamp to [0, 1]\\\\n\\\\treturn saturate( color );\\\\n\\\\n}\\\\n\\\\nvec3 CustomToneMapping( vec3 color ) { return color; }\\\\n\\\\\\\",transmission_fragment:k,transmission_pars_fragment:\\\\\\\"\\\\n#ifdef USE_TRANSMISSION\\\\n\\\\n\\\\t// Transmission code is based on glTF-Sampler-Viewer\\\\n\\\\t// https://github.com/KhronosGroup/glTF-Sample-Viewer\\\\n\\\\n\\\\tuniform float transmission;\\\\n\\\\tuniform float thickness;\\\\n\\\\tuniform float attenuationDistance;\\\\n\\\\tuniform vec3 attenuationTint;\\\\n\\\\n\\\\t#ifdef USE_TRANSMISSIONMAP\\\\n\\\\n\\\\t\\\\tuniform sampler2D transmissionMap;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef USE_THICKNESSMAP\\\\n\\\\n\\\\t\\\\tuniform sampler2D thicknessMap;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tuniform vec2 transmissionSamplerSize;\\\\n\\\\tuniform sampler2D transmissionSamplerMap;\\\\n\\\\n\\\\tuniform mat4 modelMatrix;\\\\n\\\\tuniform mat4 projectionMatrix;\\\\n\\\\n\\\\tvarying vec3 vWorldPosition;\\\\n\\\\n\\\\tvec3 getVolumeTransmissionRay( vec3 n, vec3 v, float thickness, float ior, mat4 modelMatrix ) {\\\\n\\\\n\\\\t\\\\t// Direction of refracted light.\\\\n\\\\t\\\\tvec3 refractionVector = refract( - v, normalize( n ), 1.0 / ior );\\\\n\\\\n\\\\t\\\\t// Compute rotation-independant scaling of the model matrix.\\\\n\\\\t\\\\tvec3 modelScale;\\\\n\\\\t\\\\tmodelScale.x = length( vec3( modelMatrix[ 0 ].xyz ) );\\\\n\\\\t\\\\tmodelScale.y = length( vec3( modelMatrix[ 1 ].xyz ) );\\\\n\\\\t\\\\tmodelScale.z = length( vec3( modelMatrix[ 2 ].xyz ) );\\\\n\\\\n\\\\t\\\\t// The thickness is specified in local space.\\\\n\\\\t\\\\treturn normalize( refractionVector ) * thickness * modelScale;\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tfloat applyIorToRoughness( float roughness, float ior ) {\\\\n\\\\n\\\\t\\\\t// Scale roughness with IOR so that an IOR of 1.0 results in no microfacet refraction and\\\\n\\\\t\\\\t// an IOR of 1.5 results in the default amount of microfacet refraction.\\\\n\\\\t\\\\treturn roughness * clamp( ior * 2.0 - 2.0, 0.0, 1.0 );\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tvec4 getTransmissionSample( vec2 fragCoord, float roughness, float ior ) {\\\\n\\\\n\\\\t\\\\tfloat framebufferLod = log2( transmissionSamplerSize.x ) * applyIorToRoughness( roughness, ior );\\\\n\\\\n\\\\t\\\\t#ifdef TEXTURE_LOD_EXT\\\\n\\\\n\\\\t\\\\t\\\\treturn texture2DLodEXT( transmissionSamplerMap, fragCoord.xy, framebufferLod );\\\\n\\\\n\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\treturn texture2D( transmissionSamplerMap, fragCoord.xy, framebufferLod );\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tvec3 applyVolumeAttenuation( vec3 radiance, float transmissionDistance, vec3 attenuationColor, float attenuationDistance ) {\\\\n\\\\n\\\\t\\\\tif ( attenuationDistance == 0.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t// Attenuation distance is +∞ (which we indicate by zero), i.e. the transmitted color is not attenuated at all.\\\\n\\\\t\\\\t\\\\treturn radiance;\\\\n\\\\n\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\t// Compute light attenuation using Beer's law.\\\\n\\\\t\\\\t\\\\tvec3 attenuationCoefficient = -log( attenuationColor ) / attenuationDistance;\\\\n\\\\t\\\\t\\\\tvec3 transmittance = exp( - attenuationCoefficient * transmissionDistance ); // Beer's law\\\\n\\\\t\\\\t\\\\treturn transmittance * radiance;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tvec4 getIBLVolumeRefraction( vec3 n, vec3 v, float roughness, vec3 diffuseColor, vec3 specularColor, float specularF90,\\\\n\\\\t\\\\tvec3 position, mat4 modelMatrix, mat4 viewMatrix, mat4 projMatrix, float ior, float thickness,\\\\n\\\\t\\\\tvec3 attenuationColor, float attenuationDistance ) {\\\\n\\\\n\\\\t\\\\tvec3 transmissionRay = getVolumeTransmissionRay( n, v, thickness, ior, modelMatrix );\\\\n\\\\t\\\\tvec3 refractedRayExit = position + transmissionRay;\\\\n\\\\n\\\\t\\\\t// Project refracted vector on the framebuffer, while mapping to normalized device coordinates.\\\\n\\\\t\\\\tvec4 ndcPos = projMatrix * viewMatrix * vec4( refractedRayExit, 1.0 );\\\\n\\\\t\\\\tvec2 refractionCoords = ndcPos.xy / ndcPos.w;\\\\n\\\\t\\\\trefractionCoords += 1.0;\\\\n\\\\t\\\\trefractionCoords /= 2.0;\\\\n\\\\n\\\\t\\\\t// Sample framebuffer to get pixel the refracted ray hits.\\\\n\\\\t\\\\tvec4 transmittedLight = getTransmissionSample( refractionCoords, roughness, ior );\\\\n\\\\n\\\\t\\\\tvec3 attenuatedColor = applyVolumeAttenuation( transmittedLight.rgb, length( transmissionRay ), attenuationColor, attenuationDistance );\\\\n\\\\n\\\\t\\\\t// Get the specular component.\\\\n\\\\t\\\\tvec3 F = EnvironmentBRDF( n, v, specularColor, specularF90, roughness );\\\\n\\\\n\\\\t\\\\treturn vec4( ( 1.0 - F ) * attenuatedColor * diffuseColor, transmittedLight.a );\\\\n\\\\n\\\\t}\\\\n#endif\\\\n\\\\\\\",uv_pars_fragment:\\\\\\\"\\\\n#if ( defined( USE_UV ) && ! defined( UVS_VERTEX_ONLY ) )\\\\n\\\\n\\\\tvarying vec2 vUv;\\\\n\\\\n#endif\\\\n\\\\\\\",uv_pars_vertex:\\\\\\\"\\\\n#ifdef USE_UV\\\\n\\\\n\\\\t#ifdef UVS_VERTEX_ONLY\\\\n\\\\n\\\\t\\\\tvec2 vUv;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tuniform mat3 uvTransform;\\\\n\\\\n#endif\\\\n\\\\\\\",uv_vertex:\\\\\\\"\\\\n#ifdef USE_UV\\\\n\\\\n\\\\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\\\\n\\\\n#endif\\\\n\\\\\\\",uv2_pars_fragment:\\\\\\\"\\\\n#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\\\n\\\\n\\\\tvarying vec2 vUv2;\\\\n\\\\n#endif\\\\n\\\\\\\",uv2_pars_vertex:\\\\\\\"\\\\n#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\\\n\\\\n\\\\tattribute vec2 uv2;\\\\n\\\\tvarying vec2 vUv2;\\\\n\\\\n\\\\tuniform mat3 uv2Transform;\\\\n\\\\n#endif\\\\n\\\\\\\",uv2_vertex:\\\\\\\"\\\\n#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\\\n\\\\n\\\\tvUv2 = ( uv2Transform * vec3( uv2, 1 ) ).xy;\\\\n\\\\n#endif\\\\n\\\\\\\",worldpos_vertex:\\\\\\\"\\\\n#if defined( USE_ENVMAP ) || defined( DISTANCE ) || defined ( USE_SHADOWMAP ) || defined ( USE_TRANSMISSION )\\\\n\\\\n\\\\tvec4 worldPosition = vec4( transformed, 1.0 );\\\\n\\\\n\\\\t#ifdef USE_INSTANCING\\\\n\\\\n\\\\t\\\\tworldPosition = instanceMatrix * worldPosition;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tworldPosition = modelMatrix * worldPosition;\\\\n\\\\n#endif\\\\n\\\\\\\",background_vert:\\\\\\\"\\\\nvarying vec2 vUv;\\\\nuniform mat3 uvTransform;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\\\\n\\\\n\\\\tgl_Position = vec4( position.xy, 1.0, 1.0 );\\\\n\\\\n}\\\\n\\\\\\\",background_frag:\\\\\\\"\\\\nuniform sampler2D t2D;\\\\n\\\\nvarying vec2 vUv;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec4 texColor = texture2D( t2D, vUv );\\\\n\\\\n\\\\tgl_FragColor = mapTexelToLinear( texColor );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",cube_vert:\\\\\\\"\\\\nvarying vec3 vWorldDirection;\\\\n\\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvWorldDirection = transformDirection( position, modelMatrix );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tgl_Position.z = gl_Position.w; // set z to camera.far\\\\n\\\\n}\\\\n\\\\\\\",cube_frag:\\\\\\\"\\\\n#include \\\\nuniform float opacity;\\\\n\\\\nvarying vec3 vWorldDirection;\\\\n\\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec3 vReflect = vWorldDirection;\\\\n\\\\t#include \\\\n\\\\n\\\\tgl_FragColor = envColor;\\\\n\\\\tgl_FragColor.a *= opacity;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",depth_vert:\\\\\\\"\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\n// This is used for computing an equivalent of gl_FragCoord.z that is as high precision as possible.\\\\n// Some platforms compute gl_FragCoord at a lower precision which makes the manually computed value better for\\\\n// depth-based postprocessing effects. Reproduced on iPad with A10 processor / iPadOS 13.3.1.\\\\nvarying vec2 vHighPrecisionZW;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\t#ifdef USE_DISPLACEMENTMAP\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tvHighPrecisionZW = gl_Position.zw;\\\\n\\\\n}\\\\n\\\\\\\",depth_frag:\\\\\\\"\\\\n#if DEPTH_PACKING == 3200\\\\n\\\\n\\\\tuniform float opacity;\\\\n\\\\n#endif\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvarying vec2 vHighPrecisionZW;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 diffuseColor = vec4( 1.0 );\\\\n\\\\n\\\\t#if DEPTH_PACKING == 3200\\\\n\\\\n\\\\t\\\\tdiffuseColor.a = opacity;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\t// Higher precision equivalent of gl_FragCoord.z. This assumes depthRange has been left to its default values.\\\\n\\\\tfloat fragCoordZ = 0.5 * vHighPrecisionZW[0] / vHighPrecisionZW[1] + 0.5;\\\\n\\\\n\\\\t#if DEPTH_PACKING == 3200\\\\n\\\\n\\\\t\\\\tgl_FragColor = vec4( vec3( 1.0 - fragCoordZ ), opacity );\\\\n\\\\n\\\\t#elif DEPTH_PACKING == 3201\\\\n\\\\n\\\\t\\\\tgl_FragColor = packDepthToRGBA( fragCoordZ );\\\\n\\\\n\\\\t#endif\\\\n\\\\n}\\\\n\\\\\\\",distanceRGBA_vert:\\\\\\\"\\\\n#define DISTANCE\\\\n\\\\nvarying vec3 vWorldPosition;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\t#ifdef USE_DISPLACEMENTMAP\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tvWorldPosition = worldPosition.xyz;\\\\n\\\\n}\\\\n\\\\\\\",distanceRGBA_frag:\\\\\\\"\\\\n#define DISTANCE\\\\n\\\\nuniform vec3 referencePosition;\\\\nuniform float nearDistance;\\\\nuniform float farDistance;\\\\nvarying vec3 vWorldPosition;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main () {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 diffuseColor = vec4( 1.0 );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tfloat dist = length( vWorldPosition - referencePosition );\\\\n\\\\tdist = ( dist - nearDistance ) / ( farDistance - nearDistance );\\\\n\\\\tdist = saturate( dist ); // clamp to [ 0, 1 ]\\\\n\\\\n\\\\tgl_FragColor = packDepthToRGBA( dist );\\\\n\\\\n}\\\\n\\\\\\\",equirect_vert:\\\\\\\"\\\\nvarying vec3 vWorldDirection;\\\\n\\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvWorldDirection = transformDirection( position, modelMatrix );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",equirect_frag:\\\\\\\"\\\\nuniform sampler2D tEquirect;\\\\n\\\\nvarying vec3 vWorldDirection;\\\\n\\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec3 direction = normalize( vWorldDirection );\\\\n\\\\n\\\\tvec2 sampleUV = equirectUv( direction );\\\\n\\\\n\\\\tvec4 texColor = texture2D( tEquirect, sampleUV );\\\\n\\\\n\\\\tgl_FragColor = mapTexelToLinear( texColor );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",linedashed_vert:\\\\\\\"\\\\nuniform float scale;\\\\nattribute float lineDistance;\\\\n\\\\nvarying float vLineDistance;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvLineDistance = scale * lineDistance;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",linedashed_frag:\\\\\\\"\\\\nuniform vec3 diffuse;\\\\nuniform float opacity;\\\\n\\\\nuniform float dashSize;\\\\nuniform float totalSize;\\\\n\\\\nvarying float vLineDistance;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tif ( mod( vLineDistance, totalSize ) > dashSize ) {\\\\n\\\\n\\\\t\\\\tdiscard;\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tvec3 outgoingLight = vec3( 0.0 );\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\toutgoingLight = diffuseColor.rgb; // simple shader\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",meshbasic_vert:\\\\\\\"\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#if defined ( USE_ENVMAP ) || defined ( USE_SKINNING )\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",meshbasic_frag:\\\\\\\"\\\\nuniform vec3 diffuse;\\\\nuniform float opacity;\\\\n\\\\n#ifndef FLAT_SHADED\\\\n\\\\n\\\\tvarying vec3 vNormal;\\\\n\\\\n#endif\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\n\\\\t// accumulation (baked indirect lighting only)\\\\n\\\\t#ifdef USE_LIGHTMAP\\\\n\\\\n\\\\t\\\\tvec4 lightMapTexel= texture2D( lightMap, vUv2 );\\\\n\\\\t\\\\treflectedLight.indirectDiffuse += lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\treflectedLight.indirectDiffuse += vec3( 1.0 );\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t// modulation\\\\n\\\\t#include \\\\n\\\\n\\\\treflectedLight.indirectDiffuse *= diffuseColor.rgb;\\\\n\\\\n\\\\tvec3 outgoingLight = reflectedLight.indirectDiffuse;\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",meshlambert_vert:\\\\\\\"\\\\n#define LAMBERT\\\\n\\\\nvarying vec3 vLightFront;\\\\nvarying vec3 vIndirectFront;\\\\n\\\\n#ifdef DOUBLE_SIDED\\\\n\\\\tvarying vec3 vLightBack;\\\\n\\\\tvarying vec3 vIndirectBack;\\\\n#endif\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\n\\\\\\\",meshlambert_frag:\\\\\\\"\\\\nuniform vec3 diffuse;\\\\nuniform vec3 emissive;\\\\nuniform float opacity;\\\\n\\\\nvarying vec3 vLightFront;\\\\nvarying vec3 vIndirectFront;\\\\n\\\\n#ifdef DOUBLE_SIDED\\\\n\\\\tvarying vec3 vLightBack;\\\\n\\\\tvarying vec3 vIndirectBack;\\\\n#endif\\\\n\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\tvec3 totalEmissiveRadiance = emissive;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t// accumulation\\\\n\\\\n\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\treflectedLight.indirectDiffuse += ( gl_FrontFacing ) ? vIndirectFront : vIndirectBack;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\treflectedLight.indirectDiffuse += vIndirectFront;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\treflectedLight.indirectDiffuse *= BRDF_Lambert( diffuseColor.rgb );\\\\n\\\\n\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\n\\\\t\\\\treflectedLight.directDiffuse = ( gl_FrontFacing ) ? vLightFront : vLightBack;\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\treflectedLight.directDiffuse = vLightFront;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\treflectedLight.directDiffuse *= BRDF_Lambert( diffuseColor.rgb ) * getShadowMask();\\\\n\\\\n\\\\t// modulation\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\n\\\\\\\",meshmatcap_vert:\\\\\\\"\\\\n#define MATCAP\\\\n\\\\nvarying vec3 vViewPosition;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n\\\\n}\\\\n\\\\\\\",meshmatcap_frag:\\\\\\\"\\\\n#define MATCAP\\\\n\\\\nuniform vec3 diffuse;\\\\nuniform float opacity;\\\\nuniform sampler2D matcap;\\\\n\\\\nvarying vec3 vViewPosition;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tvec3 viewDir = normalize( vViewPosition );\\\\n\\\\tvec3 x = normalize( vec3( viewDir.z, 0.0, - viewDir.x ) );\\\\n\\\\tvec3 y = cross( viewDir, x );\\\\n\\\\tvec2 uv = vec2( dot( x, normal ), dot( y, normal ) ) * 0.495 + 0.5; // 0.495 to remove artifacts caused by undersized matcap disks\\\\n\\\\n\\\\t#ifdef USE_MATCAP\\\\n\\\\n\\\\t\\\\tvec4 matcapColor = texture2D( matcap, uv );\\\\n\\\\t\\\\tmatcapColor = matcapTexelToLinear( matcapColor );\\\\n\\\\n\\\\t#else\\\\n\\\\n\\\\t\\\\tvec4 matcapColor = vec4( 1.0 );\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tvec3 outgoingLight = diffuseColor.rgb * matcapColor.rgb;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",meshnormal_vert:\\\\\\\"\\\\n#define NORMAL\\\\n\\\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\\\n\\\\n\\\\tvarying vec3 vViewPosition;\\\\n\\\\n#endif\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\\\n\\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n\\\\n#endif\\\\n\\\\n}\\\\n\\\\\\\",meshnormal_frag:\\\\\\\"\\\\n#define NORMAL\\\\n\\\\nuniform float opacity;\\\\n\\\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\\\n\\\\n\\\\tvarying vec3 vViewPosition;\\\\n\\\\n#endif\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tgl_FragColor = vec4( packNormalToRGB( normal ), opacity );\\\\n\\\\n}\\\\n\\\\\\\",meshphong_vert:\\\\\\\"\\\\n#define PHONG\\\\n\\\\nvarying vec3 vViewPosition;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",meshphong_frag:\\\\\\\"\\\\n#define PHONG\\\\n\\\\nuniform vec3 diffuse;\\\\nuniform vec3 emissive;\\\\nuniform vec3 specular;\\\\nuniform float shininess;\\\\nuniform float opacity;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\tvec3 totalEmissiveRadiance = emissive;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t// accumulation\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t// modulation\\\\n\\\\t#include \\\\n\\\\n\\\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + reflectedLight.directSpecular + reflectedLight.indirectSpecular + totalEmissiveRadiance;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",meshphysical_vert:\\\\\\\"\\\\n#define STANDARD\\\\n\\\\nvarying vec3 vViewPosition;\\\\n\\\\n#ifdef USE_TRANSMISSION\\\\n\\\\n\\\\tvarying vec3 vWorldPosition;\\\\n\\\\n#endif\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n#ifdef USE_TRANSMISSION\\\\n\\\\n\\\\tvWorldPosition = worldPosition.xyz;\\\\n\\\\n#endif\\\\n}\\\\n\\\\\\\",meshphysical_frag:\\\\\\\"\\\\n#define STANDARD\\\\n\\\\n#ifdef PHYSICAL\\\\n\\\\t#define IOR\\\\n\\\\t#define SPECULAR\\\\n#endif\\\\n\\\\nuniform vec3 diffuse;\\\\nuniform vec3 emissive;\\\\nuniform float roughness;\\\\nuniform float metalness;\\\\nuniform float opacity;\\\\n\\\\n#ifdef IOR\\\\n\\\\tuniform float ior;\\\\n#endif\\\\n\\\\n#ifdef SPECULAR\\\\n\\\\tuniform float specularIntensity;\\\\n\\\\tuniform vec3 specularTint;\\\\n\\\\n\\\\t#ifdef USE_SPECULARINTENSITYMAP\\\\n\\\\t\\\\tuniform sampler2D specularIntensityMap;\\\\n\\\\t#endif\\\\n\\\\n\\\\t#ifdef USE_SPECULARTINTMAP\\\\n\\\\t\\\\tuniform sampler2D specularTintMap;\\\\n\\\\t#endif\\\\n#endif\\\\n\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\tuniform float clearcoat;\\\\n\\\\tuniform float clearcoatRoughness;\\\\n#endif\\\\n\\\\n#ifdef USE_SHEEN\\\\n\\\\tuniform vec3 sheenTint;\\\\n\\\\tuniform float sheenRoughness;\\\\n#endif\\\\n\\\\nvarying vec3 vViewPosition;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\tvec3 totalEmissiveRadiance = emissive;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t// accumulation\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t// modulation\\\\n\\\\t#include \\\\n\\\\n\\\\tvec3 totalDiffuse = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse;\\\\n\\\\tvec3 totalSpecular = reflectedLight.directSpecular + reflectedLight.indirectSpecular;\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec3 outgoingLight = totalDiffuse + totalSpecular + totalEmissiveRadiance;\\\\n\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\n\\\\t\\\\tfloat dotNVcc = saturate( dot( geometry.clearcoatNormal, geometry.viewDir ) );\\\\n\\\\n\\\\t\\\\tvec3 Fcc = F_Schlick( material.clearcoatF0, material.clearcoatF90, dotNVcc );\\\\n\\\\n\\\\t\\\\toutgoingLight = outgoingLight * ( 1.0 - clearcoat * Fcc ) + clearcoatSpecular * clearcoat;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",meshtoon_vert:\\\\\\\"\\\\n#define TOON\\\\n\\\\nvarying vec3 vViewPosition;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",meshtoon_frag:\\\\\\\"\\\\n#define TOON\\\\n\\\\nuniform vec3 diffuse;\\\\nuniform vec3 emissive;\\\\nuniform float opacity;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\tvec3 totalEmissiveRadiance = emissive;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t// accumulation\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t// modulation\\\\n\\\\t#include \\\\n\\\\n\\\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",points_vert:\\\\\\\"\\\\nuniform float size;\\\\nuniform float scale;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\tgl_PointSize = size;\\\\n\\\\n\\\\t#ifdef USE_SIZEATTENUATION\\\\n\\\\n\\\\t\\\\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\\\\n\\\\n\\\\t\\\\tif ( isPerspective ) gl_PointSize *= ( scale / - mvPosition.z );\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",points_frag:\\\\\\\"\\\\nuniform vec3 diffuse;\\\\nuniform float opacity;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec3 outgoingLight = vec3( 0.0 );\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\toutgoingLight = diffuseColor.rgb;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",shadow_vert:\\\\\\\"\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",shadow_frag:\\\\\\\"\\\\nuniform vec3 color;\\\\nuniform float opacity;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tgl_FragColor = vec4( color, opacity * ( 1.0 - getShadowMask() ) );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",sprite_vert:\\\\\\\"\\\\nuniform float rotation;\\\\nuniform vec2 center;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec4 mvPosition = modelViewMatrix * vec4( 0.0, 0.0, 0.0, 1.0 );\\\\n\\\\n\\\\tvec2 scale;\\\\n\\\\tscale.x = length( vec3( modelMatrix[ 0 ].x, modelMatrix[ 0 ].y, modelMatrix[ 0 ].z ) );\\\\n\\\\tscale.y = length( vec3( modelMatrix[ 1 ].x, modelMatrix[ 1 ].y, modelMatrix[ 1 ].z ) );\\\\n\\\\n\\\\t#ifndef USE_SIZEATTENUATION\\\\n\\\\n\\\\t\\\\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\\\\n\\\\n\\\\t\\\\tif ( isPerspective ) scale *= - mvPosition.z;\\\\n\\\\n\\\\t#endif\\\\n\\\\n\\\\tvec2 alignedPosition = ( position.xy - ( center - vec2( 0.5 ) ) ) * scale;\\\\n\\\\n\\\\tvec2 rotatedPosition;\\\\n\\\\trotatedPosition.x = cos( rotation ) * alignedPosition.x - sin( rotation ) * alignedPosition.y;\\\\n\\\\trotatedPosition.y = sin( rotation ) * alignedPosition.x + cos( rotation ) * alignedPosition.y;\\\\n\\\\n\\\\tmvPosition.xy += rotatedPosition;\\\\n\\\\n\\\\tgl_Position = projectionMatrix * mvPosition;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\",sprite_frag:\\\\\\\"\\\\nuniform vec3 diffuse;\\\\nuniform float opacity;\\\\n\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvec3 outgoingLight = vec3( 0.0 );\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\toutgoingLight = diffuseColor.rgb;\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n}\\\\n\\\\\\\"};var G=n(11);const V={common:{diffuse:{value:new D.a(16777215)},opacity:{value:1},map:{value:null},uvTransform:{value:new G.a},uv2Transform:{value:new G.a},alphaMap:{value:null},alphaTest:{value:0}},specularmap:{specularMap:{value:null}},envmap:{envMap:{value:null},flipEnvMap:{value:-1},reflectivity:{value:1},ior:{value:1.5},refractionRatio:{value:.98},maxMipLevel:{value:0}},aomap:{aoMap:{value:null},aoMapIntensity:{value:1}},lightmap:{lightMap:{value:null},lightMapIntensity:{value:1}},emissivemap:{emissiveMap:{value:null}},bumpmap:{bumpMap:{value:null},bumpScale:{value:1}},normalmap:{normalMap:{value:null},normalScale:{value:new d.a(1,1)}},displacementmap:{displacementMap:{value:null},displacementScale:{value:1},displacementBias:{value:0}},roughnessmap:{roughnessMap:{value:null}},metalnessmap:{metalnessMap:{value:null}},gradientmap:{gradientMap:{value:null}},fog:{fogDensity:{value:25e-5},fogNear:{value:1},fogFar:{value:2e3},fogColor:{value:new D.a(16777215)}},lights:{ambientLightColor:{value:[]},lightProbe:{value:[]},directionalLights:{value:[],properties:{direction:{},color:{}}},directionalLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{}}},directionalShadowMap:{value:[]},directionalShadowMatrix:{value:[]},spotLights:{value:[],properties:{color:{},position:{},direction:{},distance:{},coneCos:{},penumbraCos:{},decay:{}}},spotLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{}}},spotShadowMap:{value:[]},spotShadowMatrix:{value:[]},pointLights:{value:[],properties:{color:{},position:{},decay:{},distance:{}}},pointLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{},shadowCameraNear:{},shadowCameraFar:{}}},pointShadowMap:{value:[]},pointShadowMatrix:{value:[]},hemisphereLights:{value:[],properties:{direction:{},skyColor:{},groundColor:{}}},rectAreaLights:{value:[],properties:{color:{},position:{},width:{},height:{}}},ltc_1:{value:null},ltc_2:{value:null}},points:{diffuse:{value:new D.a(16777215)},opacity:{value:1},size:{value:1},scale:{value:1},map:{value:null},alphaMap:{value:null},alphaTest:{value:0},uvTransform:{value:new G.a}},sprite:{diffuse:{value:new D.a(16777215)},opacity:{value:1},center:{value:new d.a(.5,.5)},rotation:{value:0},map:{value:null},alphaMap:{value:null},alphaTest:{value:0},uvTransform:{value:new G.a}}},H={basic:{uniforms:R([V.common,V.specularmap,V.envmap,V.aomap,V.lightmap,V.fog]),vertexShader:U.meshbasic_vert,fragmentShader:U.meshbasic_frag},lambert:{uniforms:R([V.common,V.specularmap,V.envmap,V.aomap,V.lightmap,V.emissivemap,V.fog,V.lights,{emissive:{value:new D.a(0)}}]),vertexShader:U.meshlambert_vert,fragmentShader:U.meshlambert_frag},phong:{uniforms:R([V.common,V.specularmap,V.envmap,V.aomap,V.lightmap,V.emissivemap,V.bumpmap,V.normalmap,V.displacementmap,V.fog,V.lights,{emissive:{value:new D.a(0)},specular:{value:new 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Tt{constructor(t){this._renderer=t,this._pingPongRenderTarget=null,this._blurMaterial=function(t){const e=new Float32Array(t),n=new p.a(0,1,0);return new at({name:\\\\\\\"SphericalGaussianBlur\\\\\\\",defines:{n:t},uniforms:{envMap:{value:null},samples:{value:1},weights:{value:e},latitudinal:{value:!1},dTheta:{value:0},mipInt:{value:0},poleAxis:{value:n},inputEncoding:{value:pt[w.U]},outputEncoding:{value:pt[w.U]}},vertexShader:Lt(),fragmentShader:`\\\\n\\\\n\\\\t\\\\t\\\\tprecision mediump float;\\\\n\\\\t\\\\t\\\\tprecision mediump int;\\\\n\\\\n\\\\t\\\\t\\\\tvarying vec3 vOutputDirection;\\\\n\\\\n\\\\t\\\\t\\\\tuniform sampler2D envMap;\\\\n\\\\t\\\\t\\\\tuniform int samples;\\\\n\\\\t\\\\t\\\\tuniform float weights[ n ];\\\\n\\\\t\\\\t\\\\tuniform bool latitudinal;\\\\n\\\\t\\\\t\\\\tuniform float dTheta;\\\\n\\\\t\\\\t\\\\tuniform float mipInt;\\\\n\\\\t\\\\t\\\\tuniform vec3 poleAxis;\\\\n\\\\n\\\\t\\\\t\\\\t${Ot()}\\\\n\\\\n\\\\t\\\\t\\\\t#define 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s=this._allocateTargets();return this._sceneToCubeUV(t,n,i,s),e>0&&this._blur(s,0,0,e),this._applyPMREM(s),this._cleanup(s),s}fromEquirectangular(t){return this._fromTexture(t)}fromCubemap(t){return this._fromTexture(t)}compileCubemapShader(){null===this._cubemapShader&&(this._cubemapShader=Nt(),this._compileMaterial(this._cubemapShader))}compileEquirectangularShader(){null===this._equirectShader&&(this._equirectShader=Ct(),this._compileMaterial(this._equirectShader))}dispose(){this._blurMaterial.dispose(),null!==this._cubemapShader&&this._cubemapShader.dispose(),null!==this._equirectShader&&this._equirectShader.dispose();for(let t=0;t2?ct:0,ct,ct),a.setRenderTarget(i),p&&a.render(d,s),a.render(t,s)}d.geometry.dispose(),d.material.dispose(),a.toneMapping=h,a.outputEncoding=c,a.autoClear=l,t.background=_}_setEncoding(t,e){!0===this._renderer.capabilities.isWebGL2&&e.format===w.Ib&&e.type===w.Zc&&e.encoding===w.ld?t.value=pt[w.U]:t.value=pt[e.encoding]}_textureToCubeUV(t,e){const n=this._renderer;t.isCubeTexture?null==this._cubemapShader&&(this._cubemapShader=Nt()):null==this._equirectShader&&(this._equirectShader=Ct());const i=t.isCubeTexture?this._cubemapShader:this._equirectShader,s=new B.a(mt[0],i),r=i.uniforms;r.envMap.value=t,t.isCubeTexture||r.texelSize.value.set(1/t.image.width,1/t.image.height),this._setEncoding(r.inputEncoding,t),this._setEncoding(r.outputEncoding,e.texture),St(e,0,0,3*ct,2*ct),n.setRenderTarget(e),n.render(s,_t)}_applyPMREM(t){const e=this._renderer,n=e.autoClear;e.autoClear=!1;for(let e=1;edt&&console.warn(`sigmaRadians, ${s}, is too large and will clip, as it requested ${_} samples when the maximum is set to 20`);const m=[];let f=0;for(let t=0;t4?i-8+4:0),3*g,2*g),a.setRenderTarget(e),a.render(c,_t)}}function At(t){return void 0!==t&&t.type===w.Zc&&(t.encoding===w.U||t.encoding===w.ld||t.encoding===w.J)}function Mt(){const t=[],e=[],n=[];let i=8;for(let s=0;s4?o=ht[s-8+4-1]:0==s&&(o=0),n.push(o);const a=1/(r-1),l=-a/2,c=1+a/2,h=[l,l,c,l,c,c,l,l,c,c,l,c],u=6,d=6,p=3,_=2,m=1,f=new Float32Array(p*d*u),g=new Float32Array(_*d*u),v=new Float32Array(m*d*u);for(let t=0;t2?0:-1,i=[e,n,0,e+2/3,n,0,e+2/3,n+1,0,e,n,0,e+2/3,n+1,0,e,n+1,0];f.set(i,p*d*t),g.set(h,_*d*t);const s=[t,t,t,t,t,t];v.set(s,m*d*t)}const y=new S.a;y.setAttribute(\\\\\\\"position\\\\\\\",new C.a(f,p)),y.setAttribute(\\\\\\\"uv\\\\\\\",new C.a(g,_)),y.setAttribute(\\\\\\\"faceIndex\\\\\\\",new C.a(v,m)),t.push(y),i>4&&i--}return{_lodPlanes:t,_sizeLods:e,_sigmas:n}}function Et(t){const e=new Q(3*ct,3*ct,t);return e.texture.mapping=w.q,e.texture.name=\\\\\\\"PMREM.cubeUv\\\\\\\",e.scissorTest=!0,e}function St(t,e,n,i,s){t.viewport.set(e,n,i,s),t.scissor.set(e,n,i,s)}function Ct(){const t=new d.a(1,1);return new at({name:\\\\\\\"EquirectangularToCubeUV\\\\\\\",uniforms:{envMap:{value:null},texelSize:{value:t},inputEncoding:{value:pt[w.U]},outputEncoding:{value:pt[w.U]}},vertexShader:Lt(),fragmentShader:`\\\\n\\\\n\\\\t\\\\t\\\\tprecision mediump float;\\\\n\\\\t\\\\t\\\\tprecision mediump int;\\\\n\\\\n\\\\t\\\\t\\\\tvarying vec3 vOutputDirection;\\\\n\\\\n\\\\t\\\\t\\\\tuniform sampler2D envMap;\\\\n\\\\t\\\\t\\\\tuniform vec2 texelSize;\\\\n\\\\n\\\\t\\\\t\\\\t${Ot()}\\\\n\\\\n\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvec3 outputDirection = normalize( vOutputDirection );\\\\n\\\\t\\\\t\\\\t\\\\tvec2 uv = equirectUv( outputDirection );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvec2 f = fract( uv / texelSize - 0.5 );\\\\n\\\\t\\\\t\\\\t\\\\tuv -= f * texelSize;\\\\n\\\\t\\\\t\\\\t\\\\tvec3 tl = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tuv.x += texelSize.x;\\\\n\\\\t\\\\t\\\\t\\\\tvec3 tr = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tuv.y += texelSize.y;\\\\n\\\\t\\\\t\\\\t\\\\tvec3 br = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tuv.x -= texelSize.x;\\\\n\\\\t\\\\t\\\\t\\\\tvec3 bl = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvec3 tm = mix( tl, tr, f.x );\\\\n\\\\t\\\\t\\\\t\\\\tvec3 bm = mix( bl, br, f.x );\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb = mix( tm, bm, f.y );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = linearToOutputTexel( gl_FragColor );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t`,blending:w.ub,depthTest:!1,depthWrite:!1})}function Nt(){return new at({name:\\\\\\\"CubemapToCubeUV\\\\\\\",uniforms:{envMap:{value:null},inputEncoding:{value:pt[w.U]},outputEncoding:{value:pt[w.U]}},vertexShader:Lt(),fragmentShader:`\\\\n\\\\n\\\\t\\\\t\\\\tprecision mediump float;\\\\n\\\\t\\\\t\\\\tprecision mediump int;\\\\n\\\\n\\\\t\\\\t\\\\tvarying vec3 vOutputDirection;\\\\n\\\\n\\\\t\\\\t\\\\tuniform samplerCube envMap;\\\\n\\\\n\\\\t\\\\t\\\\t${Ot()}\\\\n\\\\n\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb = envMapTexelToLinear( textureCube( envMap, vec3( - vOutputDirection.x, vOutputDirection.yz ) ) ).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = linearToOutputTexel( gl_FragColor );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t`,blending:w.ub,depthTest:!1,depthWrite:!1})}function Lt(){return\\\\\\\"\\\\n\\\\n\\\\t\\\\tprecision mediump float;\\\\n\\\\t\\\\tprecision mediump int;\\\\n\\\\n\\\\t\\\\tattribute vec3 position;\\\\n\\\\t\\\\tattribute vec2 uv;\\\\n\\\\t\\\\tattribute float faceIndex;\\\\n\\\\n\\\\t\\\\tvarying vec3 vOutputDirection;\\\\n\\\\n\\\\t\\\\t// RH coordinate system; PMREM face-indexing convention\\\\n\\\\t\\\\tvec3 getDirection( vec2 uv, float face ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv = 2.0 * uv - 1.0;\\\\n\\\\n\\\\t\\\\t\\\\tvec3 direction = vec3( uv, 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\tif ( face == 0.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection = direction.zyx; // ( 1, v, u ) pos x\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 1.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection = direction.xzy;\\\\n\\\\t\\\\t\\\\t\\\\tdirection.xz *= -1.0; // ( -u, 1, -v ) pos y\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 2.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection.x *= -1.0; // ( -u, v, 1 ) pos z\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 3.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection = direction.zyx;\\\\n\\\\t\\\\t\\\\t\\\\tdirection.xz *= -1.0; // ( -1, v, -u ) neg x\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 4.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection = direction.xzy;\\\\n\\\\t\\\\t\\\\t\\\\tdirection.xy *= -1.0; // ( -u, -1, v ) neg y\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 5.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection.z *= -1.0; // ( u, v, -1 ) neg z\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\treturn direction;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvOutputDirection = getDirection( uv, faceIndex );\\\\n\\\\t\\\\t\\\\tgl_Position = vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\\\\"}function Ot(){return\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform int inputEncoding;\\\\n\\\\t\\\\tuniform int outputEncoding;\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\tvec4 inputTexelToLinear( vec4 value ) {\\\\n\\\\n\\\\t\\\\t\\\\tif ( inputEncoding == 0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn value;\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 1 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn sRGBToLinear( value );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 2 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn RGBEToLinear( value );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 3 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn RGBMToLinear( value, 7.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 4 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn RGBMToLinear( value, 16.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 5 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn RGBDToLinear( value, 256.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn GammaToLinear( value, 2.2 );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvec4 linearToOutputTexel( vec4 value ) {\\\\n\\\\n\\\\t\\\\t\\\\tif ( outputEncoding == 0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn value;\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 1 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearTosRGB( value );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 2 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToRGBE( value );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 3 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToRGBM( value, 7.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 4 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToRGBM( value, 16.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 5 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToRGBD( value, 256.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToGamma( value, 2.2 );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvec4 envMapTexelToLinear( vec4 color ) {\\\\n\\\\n\\\\t\\\\t\\\\treturn inputTexelToLinear( color );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\\\\"}function Pt(t){let e=new WeakMap,n=null;function i(t){const n=t.target;n.removeEventListener(\\\\\\\"dispose\\\\\\\",i);const s=e.get(n);void 0!==s&&(e.delete(n),s.dispose())}return{get:function(s){if(s&&s.isTexture&&!1===s.isRenderTargetTexture){const r=s.mapping,o=r===w.D||r===w.E,a=r===w.o||r===w.p;if(o||a){if(e.has(s))return e.get(s).texture;{const r=s.image;if(o&&r&&r.height>0||a&&r&&function(t){let e=0;const n=6;for(let i=0;i65535?C.i:C.h)(n,1);a.version=o;const l=r.get(t);l&&e.remove(l),r.set(t,a)}return{get:function(t,e){return!0===s[e.id]||(e.addEventListener(\\\\\\\"dispose\\\\\\\",o),s[e.id]=!0,n.memory.geometries++),e},update:function(n){const i=n.attributes;for(const n in i)e.update(i[n],t.ARRAY_BUFFER);const s=n.morphAttributes;for(const n in s){const i=s[n];for(let n=0,s=i.length;ne.maxTextureSize&&(u=Math.ceil(h/e.maxTextureSize),h=e.maxTextureSize);const p=new Float32Array(h*u*4*i),_=new zt(p,h,u,i);_.format=w.Ib,_.type=w.G;const m=4*l;for(let e=0;e0)return t;const s=e*n;let r=Jt[s];if(void 0===r&&(r=new Float32Array(s),Jt[s]=r),0!==e){i.toArray(r,0);for(let i=1,s=0;i!==e;++i)s+=n,t[i].toArray(r,s)}return r}function ne(t,e){if(t.length!==e.length)return!1;for(let n=0,i=t.length;n/gm;function on(t){return t.replace(rn,an)}function an(t,e){const n=U[e];if(void 0===n)throw new Error(\\\\\\\"Can not resolve #include <\\\\\\\"+e+\\\\\\\">\\\\\\\");return on(n)}const ln=/#pragma unroll_loop[\\\\s]+?for \\\\( int i \\\\= (\\\\d+)\\\\; i < (\\\\d+)\\\\; i \\\\+\\\\+ \\\\) \\\\{([\\\\s\\\\S]+?)(?=\\\\})\\\\}/g,cn=/#pragma unroll_loop_start\\\\s+for\\\\s*\\\\(\\\\s*int\\\\s+i\\\\s*=\\\\s*(\\\\d+)\\\\s*;\\\\s*i\\\\s*<\\\\s*(\\\\d+)\\\\s*;\\\\s*i\\\\s*\\\\+\\\\+\\\\s*\\\\)\\\\s*{([\\\\s\\\\S]+?)}\\\\s+#pragma unroll_loop_end/g;function hn(t){return t.replace(cn,dn).replace(ln,un)}function un(t,e,n,i){return console.warn(\\\\\\\"WebGLProgram: #pragma unroll_loop shader syntax is deprecated. Please use #pragma unroll_loop_start syntax instead.\\\\\\\"),dn(t,e,n,i)}function dn(t,e,n,i){let s=\\\\\\\"\\\\\\\";for(let t=parseInt(e);t0?t.gammaFactor:1,p=n.isWebGL2?\\\\\\\"\\\\\\\":function(t){return[t.extensionDerivatives||t.envMapCubeUV||t.bumpMap||t.tangentSpaceNormalMap||t.clearcoatNormalMap||t.flatShading||\\\\\\\"physical\\\\\\\"===t.shaderID?\\\\\\\"#extension GL_OES_standard_derivatives : enable\\\\\\\":\\\\\\\"\\\\\\\",(t.extensionFragDepth||t.logarithmicDepthBuffer)&&t.rendererExtensionFragDepth?\\\\\\\"#extension GL_EXT_frag_depth : enable\\\\\\\":\\\\\\\"\\\\\\\",t.extensionDrawBuffers&&t.rendererExtensionDrawBuffers?\\\\\\\"#extension GL_EXT_draw_buffers : require\\\\\\\":\\\\\\\"\\\\\\\",(t.extensionShaderTextureLOD||t.envMap||t.transmission)&&t.rendererExtensionShaderTextureLod?\\\\\\\"#extension GL_EXT_shader_texture_lod : enable\\\\\\\":\\\\\\\"\\\\\\\"].filter(en).join(\\\\\\\"\\\\n\\\\\\\")}(n),_=function(t){const e=[];for(const n in t){const i=t[n];!1!==i&&e.push(\\\\\\\"#define \\\\\\\"+n+\\\\\\\" \\\\\\\"+i)}return e.join(\\\\\\\"\\\\n\\\\\\\")}(r),m=s.createProgram();let f,g,v=n.glslVersion?\\\\\\\"#version \\\\\\\"+n.glslVersion+\\\\\\\"\\\\n\\\\\\\":\\\\\\\"\\\\\\\";n.isRawShaderMaterial?(f=[_].filter(en).join(\\\\\\\"\\\\n\\\\\\\"),f.length>0&&(f+=\\\\\\\"\\\\n\\\\\\\"),g=[p,_].filter(en).join(\\\\\\\"\\\\n\\\\\\\"),g.length>0&&(g+=\\\\\\\"\\\\n\\\\\\\")):(f=[pn(n),\\\\\\\"#define SHADER_NAME \\\\\\\"+n.shaderName,_,n.instancing?\\\\\\\"#define USE_INSTANCING\\\\\\\":\\\\\\\"\\\\\\\",n.instancingColor?\\\\\\\"#define USE_INSTANCING_COLOR\\\\\\\":\\\\\\\"\\\\\\\",n.supportsVertexTextures?\\\\\\\"#define VERTEX_TEXTURES\\\\\\\":\\\\\\\"\\\\\\\",\\\\\\\"#define GAMMA_FACTOR \\\\\\\"+d,\\\\\\\"#define MAX_BONES \\\\\\\"+n.maxBones,n.useFog&&n.fog?\\\\\\\"#define USE_FOG\\\\\\\":\\\\\\\"\\\\\\\",n.useFog&&n.fogExp2?\\\\\\\"#define FOG_EXP2\\\\\\\":\\\\\\\"\\\\\\\",n.map?\\\\\\\"#define USE_MAP\\\\\\\":\\\\\\\"\\\\\\\",n.envMap?\\\\\\\"#define USE_ENVMAP\\\\\\\":\\\\\\\"\\\\\\\",n.envMap?\\\\\\\"#define \\\\\\\"+h:\\\\\\\"\\\\\\\",n.lightMap?\\\\\\\"#define USE_LIGHTMAP\\\\\\\":\\\\\\\"\\\\\\\",n.aoMap?\\\\\\\"#define USE_AOMAP\\\\\\\":\\\\\\\"\\\\\\\",n.emissiveMap?\\\\\\\"#define USE_EMISSIVEMAP\\\\\\\":\\\\\\\"\\\\\\\",n.bumpMap?\\\\\\\"#define USE_BUMPMAP\\\\\\\":\\\\\\\"\\\\\\\",n.normalMap?\\\\\\\"#define USE_NORMALMAP\\\\\\\":\\\\\\\"\\\\\\\",n.normalMap&&n.objectSpaceNormalMap?\\\\\\\"#define OBJECTSPACE_NORMALMAP\\\\\\\":\\\\\\\"\\\\\\\",n.normalMap&&n.tangentSpaceNormalMap?\\\\\\\"#define TANGENTSPACE_NORMALMAP\\\\\\\":\\\\\\\"\\\\\\\",n.clearcoatMap?\\\\\\\"#define USE_CLEARCOATMAP\\\\\\\":\\\\\\\"\\\\\\\",n.clearcoatRoughnessMap?\\\\\\\"#define USE_CLEARCOAT_ROUGHNESSMAP\\\\\\\":\\\\\\\"\\\\\\\",n.clearcoatNormalMap?\\\\\\\"#define USE_CLEARCOAT_NORMALMAP\\\\\\\":\\\\\\\"\\\\\\\",n.displacementMap&&n.supportsVertexTextures?\\\\\\\"#define USE_DISPLACEMENTMAP\\\\\\\":\\\\\\\"\\\\\\\",n.specularMap?\\\\\\\"#define USE_SPECULARMAP\\\\\\\":\\\\\\\"\\\\\\\",n.specularIntensityMap?\\\\\\\"#define USE_SPECULARINTENSITYMAP\\\\\\\":\\\\\\\"\\\\\\\",n.specularTintMap?\\\\\\\"#define USE_SPECULARTINTMAP\\\\\\\":\\\\\\\"\\\\\\\",n.roughnessMap?\\\\\\\"#define USE_ROUGHNESSMAP\\\\\\\":\\\\\\\"\\\\\\\",n.metalnessMap?\\\\\\\"#define USE_METALNESSMAP\\\\\\\":\\\\\\\"\\\\\\\",n.alphaMap?\\\\\\\"#define USE_ALPHAMAP\\\\\\\":\\\\\\\"\\\\\\\",n.transmission?\\\\\\\"#define USE_TRANSMISSION\\\\\\\":\\\\\\\"\\\\\\\",n.transmissionMap?\\\\\\\"#define USE_TRANSMISSIONMAP\\\\\\\":\\\\\\\"\\\\\\\",n.thicknessMap?\\\\\\\"#define USE_THICKNESSMAP\\\\\\\":\\\\\\\"\\\\\\\",n.vertexTangents?\\\\\\\"#define USE_TANGENT\\\\\\\":\\\\\\\"\\\\\\\",n.vertexColors?\\\\\\\"#define USE_COLOR\\\\\\\":\\\\\\\"\\\\\\\",n.vertexAlphas?\\\\\\\"#define USE_COLOR_ALPHA\\\\\\\":\\\\\\\"\\\\\\\",n.vertexUvs?\\\\\\\"#define USE_UV\\\\\\\":\\\\\\\"\\\\\\\",n.uvsVertexOnly?\\\\\\\"#define UVS_VERTEX_ONLY\\\\\\\":\\\\\\\"\\\\\\\",n.flatShading?\\\\\\\"#define FLAT_SHADED\\\\\\\":\\\\\\\"\\\\\\\",n.skinning?\\\\\\\"#define USE_SKINNING\\\\\\\":\\\\\\\"\\\\\\\",n.useVertexTexture?\\\\\\\"#define BONE_TEXTURE\\\\\\\":\\\\\\\"\\\\\\\",n.morphTargets?\\\\\\\"#define USE_MORPHTARGETS\\\\\\\":\\\\\\\"\\\\\\\",n.morphNormals&&!1===n.flatShading?\\\\\\\"#define USE_MORPHNORMALS\\\\\\\":\\\\\\\"\\\\\\\",n.morphTargets&&n.isWebGL2?\\\\\\\"#define MORPHTARGETS_TEXTURE\\\\\\\":\\\\\\\"\\\\\\\",n.morphTargets&&n.isWebGL2?\\\\\\\"#define MORPHTARGETS_COUNT \\\\\\\"+n.morphTargetsCount:\\\\\\\"\\\\\\\",n.doubleSided?\\\\\\\"#define DOUBLE_SIDED\\\\\\\":\\\\\\\"\\\\\\\",n.flipSided?\\\\\\\"#define FLIP_SIDED\\\\\\\":\\\\\\\"\\\\\\\",n.shadowMapEnabled?\\\\\\\"#define USE_SHADOWMAP\\\\\\\":\\\\\\\"\\\\\\\",n.shadowMapEnabled?\\\\\\\"#define \\\\\\\"+l:\\\\\\\"\\\\\\\",n.sizeAttenuation?\\\\\\\"#define USE_SIZEATTENUATION\\\\\\\":\\\\\\\"\\\\\\\",n.logarithmicDepthBuffer?\\\\\\\"#define USE_LOGDEPTHBUF\\\\\\\":\\\\\\\"\\\\\\\",n.logarithmicDepthBuffer&&n.rendererExtensionFragDepth?\\\\\\\"#define USE_LOGDEPTHBUF_EXT\\\\\\\":\\\\\\\"\\\\\\\",\\\\\\\"uniform mat4 modelMatrix;\\\\\\\",\\\\\\\"uniform mat4 modelViewMatrix;\\\\\\\",\\\\\\\"uniform mat4 projectionMatrix;\\\\\\\",\\\\\\\"uniform mat4 viewMatrix;\\\\\\\",\\\\\\\"uniform mat3 normalMatrix;\\\\\\\",\\\\\\\"uniform vec3 cameraPosition;\\\\\\\",\\\\\\\"uniform bool isOrthographic;\\\\\\\",\\\\\\\"#ifdef USE_INSTANCING\\\\\\\",\\\\\\\"\\\\tattribute mat4 instanceMatrix;\\\\\\\",\\\\\\\"#endif\\\\\\\",\\\\\\\"#ifdef USE_INSTANCING_COLOR\\\\\\\",\\\\\\\"\\\\tattribute vec3 instanceColor;\\\\\\\",\\\\\\\"#endif\\\\\\\",\\\\\\\"attribute vec3 position;\\\\\\\",\\\\\\\"attribute vec3 normal;\\\\\\\",\\\\\\\"attribute vec2 uv;\\\\\\\",\\\\\\\"#ifdef USE_TANGENT\\\\\\\",\\\\\\\"\\\\tattribute vec4 tangent;\\\\\\\",\\\\\\\"#endif\\\\\\\",\\\\\\\"#if defined( USE_COLOR_ALPHA )\\\\\\\",\\\\\\\"\\\\tattribute vec4 color;\\\\\\\",\\\\\\\"#elif defined( USE_COLOR )\\\\\\\",\\\\\\\"\\\\tattribute vec3 color;\\\\\\\",\\\\\\\"#endif\\\\\\\",\\\\\\\"#if ( defined( USE_MORPHTARGETS ) && ! defined( MORPHTARGETS_TEXTURE ) )\\\\\\\",\\\\\\\"\\\\tattribute vec3 morphTarget0;\\\\\\\",\\\\\\\"\\\\tattribute vec3 morphTarget1;\\\\\\\",\\\\\\\"\\\\tattribute vec3 morphTarget2;\\\\\\\",\\\\\\\"\\\\tattribute vec3 morphTarget3;\\\\\\\",\\\\\\\"\\\\t#ifdef USE_MORPHNORMALS\\\\\\\",\\\\\\\"\\\\t\\\\tattribute vec3 morphNormal0;\\\\\\\",\\\\\\\"\\\\t\\\\tattribute vec3 morphNormal1;\\\\\\\",\\\\\\\"\\\\t\\\\tattribute vec3 morphNormal2;\\\\\\\",\\\\\\\"\\\\t\\\\tattribute vec3 morphNormal3;\\\\\\\",\\\\\\\"\\\\t#else\\\\\\\",\\\\\\\"\\\\t\\\\tattribute vec3 morphTarget4;\\\\\\\",\\\\\\\"\\\\t\\\\tattribute vec3 morphTarget5;\\\\\\\",\\\\\\\"\\\\t\\\\tattribute vec3 morphTarget6;\\\\\\\",\\\\\\\"\\\\t\\\\tattribute vec3 morphTarget7;\\\\\\\",\\\\\\\"\\\\t#endif\\\\\\\",\\\\\\\"#endif\\\\\\\",\\\\\\\"#ifdef USE_SKINNING\\\\\\\",\\\\\\\"\\\\tattribute vec4 skinIndex;\\\\\\\",\\\\\\\"\\\\tattribute vec4 skinWeight;\\\\\\\",\\\\\\\"#endif\\\\\\\",\\\\\\\"\\\\n\\\\\\\"].filter(en).join(\\\\\\\"\\\\n\\\\\\\"),g=[p,pn(n),\\\\\\\"#define SHADER_NAME \\\\\\\"+n.shaderName,_,\\\\\\\"#define GAMMA_FACTOR \\\\\\\"+d,n.useFog&&n.fog?\\\\\\\"#define USE_FOG\\\\\\\":\\\\\\\"\\\\\\\",n.useFog&&n.fogExp2?\\\\\\\"#define FOG_EXP2\\\\\\\":\\\\\\\"\\\\\\\",n.map?\\\\\\\"#define USE_MAP\\\\\\\":\\\\\\\"\\\\\\\",n.matcap?\\\\\\\"#define USE_MATCAP\\\\\\\":\\\\\\\"\\\\\\\",n.envMap?\\\\\\\"#define USE_ENVMAP\\\\\\\":\\\\\\\"\\\\\\\",n.envMap?\\\\\\\"#define \\\\\\\"+c:\\\\\\\"\\\\\\\",n.envMap?\\\\\\\"#define \\\\\\\"+h:\\\\\\\"\\\\\\\",n.envMap?\\\\\\\"#define \\\\\\\"+u:\\\\\\\"\\\\\\\",n.lightMap?\\\\\\\"#define USE_LIGHTMAP\\\\\\\":\\\\\\\"\\\\\\\",n.aoMap?\\\\\\\"#define USE_AOMAP\\\\\\\":\\\\\\\"\\\\\\\",n.emissiveMap?\\\\\\\"#define USE_EMISSIVEMAP\\\\\\\":\\\\\\\"\\\\\\\",n.bumpMap?\\\\\\\"#define USE_BUMPMAP\\\\\\\":\\\\\\\"\\\\\\\",n.normalMap?\\\\\\\"#define USE_NORMALMAP\\\\\\\":\\\\\\\"\\\\\\\",n.normalMap&&n.objectSpaceNormalMap?\\\\\\\"#define OBJECTSPACE_NORMALMAP\\\\\\\":\\\\\\\"\\\\\\\",n.normalMap&&n.tangentSpaceNormalMap?\\\\\\\"#define TANGENTSPACE_NORMALMAP\\\\\\\":\\\\\\\"\\\\\\\",n.clearcoat?\\\\\\\"#define USE_CLEARCOAT\\\\\\\":\\\\\\\"\\\\\\\",n.clearcoatMap?\\\\\\\"#define USE_CLEARCOATMAP\\\\\\\":\\\\\\\"\\\\\\\",n.clearcoatRoughnessMap?\\\\\\\"#define USE_CLEARCOAT_ROUGHNESSMAP\\\\\\\":\\\\\\\"\\\\\\\",n.clearcoatNormalMap?\\\\\\\"#define USE_CLEARCOAT_NORMALMAP\\\\\\\":\\\\\\\"\\\\\\\",n.specularMap?\\\\\\\"#define USE_SPECULARMAP\\\\\\\":\\\\\\\"\\\\\\\",n.specularIntensityMap?\\\\\\\"#define USE_SPECULARINTENSITYMAP\\\\\\\":\\\\\\\"\\\\\\\",n.specularTintMap?\\\\\\\"#define USE_SPECULARTINTMAP\\\\\\\":\\\\\\\"\\\\\\\",n.roughnessMap?\\\\\\\"#define USE_ROUGHNESSMAP\\\\\\\":\\\\\\\"\\\\\\\",n.metalnessMap?\\\\\\\"#define USE_METALNESSMAP\\\\\\\":\\\\\\\"\\\\\\\",n.alphaMap?\\\\\\\"#define USE_ALPHAMAP\\\\\\\":\\\\\\\"\\\\\\\",n.alphaTest?\\\\\\\"#define USE_ALPHATEST\\\\\\\":\\\\\\\"\\\\\\\",n.sheen?\\\\\\\"#define USE_SHEEN\\\\\\\":\\\\\\\"\\\\\\\",n.transmission?\\\\\\\"#define USE_TRANSMISSION\\\\\\\":\\\\\\\"\\\\\\\",n.transmissionMap?\\\\\\\"#define USE_TRANSMISSIONMAP\\\\\\\":\\\\\\\"\\\\\\\",n.thicknessMap?\\\\\\\"#define USE_THICKNESSMAP\\\\\\\":\\\\\\\"\\\\\\\",n.vertexTangents?\\\\\\\"#define USE_TANGENT\\\\\\\":\\\\\\\"\\\\\\\",n.vertexColors||n.instancingColor?\\\\\\\"#define USE_COLOR\\\\\\\":\\\\\\\"\\\\\\\",n.vertexAlphas?\\\\\\\"#define USE_COLOR_ALPHA\\\\\\\":\\\\\\\"\\\\\\\",n.vertexUvs?\\\\\\\"#define USE_UV\\\\\\\":\\\\\\\"\\\\\\\",n.uvsVertexOnly?\\\\\\\"#define UVS_VERTEX_ONLY\\\\\\\":\\\\\\\"\\\\\\\",n.gradientMap?\\\\\\\"#define USE_GRADIENTMAP\\\\\\\":\\\\\\\"\\\\\\\",n.flatShading?\\\\\\\"#define FLAT_SHADED\\\\\\\":\\\\\\\"\\\\\\\",n.doubleSided?\\\\\\\"#define DOUBLE_SIDED\\\\\\\":\\\\\\\"\\\\\\\",n.flipSided?\\\\\\\"#define FLIP_SIDED\\\\\\\":\\\\\\\"\\\\\\\",n.shadowMapEnabled?\\\\\\\"#define USE_SHADOWMAP\\\\\\\":\\\\\\\"\\\\\\\",n.shadowMapEnabled?\\\\\\\"#define \\\\\\\"+l:\\\\\\\"\\\\\\\",n.premultipliedAlpha?\\\\\\\"#define PREMULTIPLIED_ALPHA\\\\\\\":\\\\\\\"\\\\\\\",n.physicallyCorrectLights?\\\\\\\"#define PHYSICALLY_CORRECT_LIGHTS\\\\\\\":\\\\\\\"\\\\\\\",n.logarithmicDepthBuffer?\\\\\\\"#define USE_LOGDEPTHBUF\\\\\\\":\\\\\\\"\\\\\\\",n.logarithmicDepthBuffer&&n.rendererExtensionFragDepth?\\\\\\\"#define USE_LOGDEPTHBUF_EXT\\\\\\\":\\\\\\\"\\\\\\\",(n.extensionShaderTextureLOD||n.envMap)&&n.rendererExtensionShaderTextureLod?\\\\\\\"#define TEXTURE_LOD_EXT\\\\\\\":\\\\\\\"\\\\\\\",\\\\\\\"uniform mat4 viewMatrix;\\\\\\\",\\\\\\\"uniform vec3 cameraPosition;\\\\\\\",\\\\\\\"uniform bool isOrthographic;\\\\\\\",n.toneMapping!==w.vb?\\\\\\\"#define TONE_MAPPING\\\\\\\":\\\\\\\"\\\\\\\",n.toneMapping!==w.vb?U.tonemapping_pars_fragment:\\\\\\\"\\\\\\\",n.toneMapping!==w.vb?tn(\\\\\\\"toneMapping\\\\\\\",n.toneMapping):\\\\\\\"\\\\\\\",n.dithering?\\\\\\\"#define DITHERING\\\\\\\":\\\\\\\"\\\\\\\",n.format===w.ic?\\\\\\\"#define OPAQUE\\\\\\\":\\\\\\\"\\\\\\\",U.encodings_pars_fragment,n.map?Qe(\\\\\\\"mapTexelToLinear\\\\\\\",n.mapEncoding):\\\\\\\"\\\\\\\",n.matcap?Qe(\\\\\\\"matcapTexelToLinear\\\\\\\",n.matcapEncoding):\\\\\\\"\\\\\\\",n.envMap?Qe(\\\\\\\"envMapTexelToLinear\\\\\\\",n.envMapEncoding):\\\\\\\"\\\\\\\",n.emissiveMap?Qe(\\\\\\\"emissiveMapTexelToLinear\\\\\\\",n.emissiveMapEncoding):\\\\\\\"\\\\\\\",n.specularTintMap?Qe(\\\\\\\"specularTintMapTexelToLinear\\\\\\\",n.specularTintMapEncoding):\\\\\\\"\\\\\\\",n.lightMap?Qe(\\\\\\\"lightMapTexelToLinear\\\\\\\",n.lightMapEncoding):\\\\\\\"\\\\\\\",Ke(\\\\\\\"linearToOutputTexel\\\\\\\",n.outputEncoding),n.depthPacking?\\\\\\\"#define DEPTH_PACKING \\\\\\\"+n.depthPacking:\\\\\\\"\\\\\\\",\\\\\\\"\\\\n\\\\\\\"].filter(en).join(\\\\\\\"\\\\n\\\\\\\")),o=on(o),o=nn(o,n),o=sn(o,n),a=on(a),a=nn(a,n),a=sn(a,n),o=hn(o),a=hn(a),n.isWebGL2&&!0!==n.isRawShaderMaterial&&(v=\\\\\\\"#version 300 es\\\\n\\\\\\\",f=[\\\\\\\"precision mediump sampler2DArray;\\\\\\\",\\\\\\\"#define attribute in\\\\\\\",\\\\\\\"#define varying out\\\\\\\",\\\\\\\"#define texture2D texture\\\\\\\"].join(\\\\\\\"\\\\n\\\\\\\")+\\\\\\\"\\\\n\\\\\\\"+f,g=[\\\\\\\"#define varying in\\\\\\\",n.glslVersion===w.I?\\\\\\\"\\\\\\\":\\\\\\\"out highp vec4 pc_fragColor;\\\\\\\",n.glslVersion===w.I?\\\\\\\"\\\\\\\":\\\\\\\"#define gl_FragColor pc_fragColor\\\\\\\",\\\\\\\"#define gl_FragDepthEXT gl_FragDepth\\\\\\\",\\\\\\\"#define texture2D texture\\\\\\\",\\\\\\\"#define textureCube texture\\\\\\\",\\\\\\\"#define texture2DProj textureProj\\\\\\\",\\\\\\\"#define texture2DLodEXT textureLod\\\\\\\",\\\\\\\"#define texture2DProjLodEXT textureProjLod\\\\\\\",\\\\\\\"#define textureCubeLodEXT textureLod\\\\\\\",\\\\\\\"#define texture2DGradEXT textureGrad\\\\\\\",\\\\\\\"#define texture2DProjGradEXT textureProjGrad\\\\\\\",\\\\\\\"#define textureCubeGradEXT textureGrad\\\\\\\"].join(\\\\\\\"\\\\n\\\\\\\")+\\\\\\\"\\\\n\\\\\\\"+g);const y=v+f+o,x=v+g+a,b=Ye(s,s.VERTEX_SHADER,y),T=Ye(s,s.FRAGMENT_SHADER,x);if(s.attachShader(m,b),s.attachShader(m,T),void 0!==n.index0AttributeName?s.bindAttribLocation(m,0,n.index0AttributeName):!0===n.morphTargets&&s.bindAttribLocation(m,0,\\\\\\\"position\\\\\\\"),s.linkProgram(m),t.debug.checkShaderErrors){const t=s.getProgramInfoLog(m).trim(),e=s.getShaderInfoLog(b).trim(),n=s.getShaderInfoLog(T).trim();let i=!0,r=!0;if(!1===s.getProgramParameter(m,s.LINK_STATUS)){i=!1;const e=Ze(s,b,\\\\\\\"vertex\\\\\\\"),n=Ze(s,T,\\\\\\\"fragment\\\\\\\");console.error(\\\\\\\"THREE.WebGLProgram: Shader Error \\\\\\\"+s.getError()+\\\\\\\" - VALIDATE_STATUS \\\\\\\"+s.getProgramParameter(m,s.VALIDATE_STATUS)+\\\\\\\"\\\\n\\\\nProgram Info Log: \\\\\\\"+t+\\\\\\\"\\\\n\\\\\\\"+e+\\\\\\\"\\\\n\\\\\\\"+n)}else\\\\\\\"\\\\\\\"!==t?console.warn(\\\\\\\"THREE.WebGLProgram: Program Info 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0!==r.depthPacking&&r.depthPacking,index0AttributeName:r.index0AttributeName,extensionDerivatives:r.extensions&&r.extensions.derivatives,extensionFragDepth:r.extensions&&r.extensions.fragDepth,extensionDrawBuffers:r.extensions&&r.extensions.drawBuffers,extensionShaderTextureLOD:r.extensions&&r.extensions.shaderTextureLOD,rendererExtensionFragDepth:l||i.has(\\\\\\\"EXT_frag_depth\\\\\\\"),rendererExtensionDrawBuffers:l||i.has(\\\\\\\"WEBGL_draw_buffers\\\\\\\"),rendererExtensionShaderTextureLod:l||i.has(\\\\\\\"EXT_shader_texture_lod\\\\\\\"),customProgramCacheKey:r.customProgramCacheKey()}},getProgramCacheKey:function(e){const n=[];if(e.shaderID?n.push(e.shaderID):(n.push(e.fragmentShader),n.push(e.vertexShader)),void 0!==e.defines)for(const t in e.defines)n.push(t),n.push(e.defines[t]);if(!1===e.isRawShaderMaterial){for(let t=0;t0?s.push(h):!0===n.transparent?r.push(h):i.push(h)},unshift:function(t,e,n,o,l,c){const h=a(t,e,n,o,l,c);n.transmission>0?s.unshift(h):!0===n.transparent?r.unshift(h):i.unshift(h)},finish:function(){for(let t=n,i=e.length;t1&&i.sort(t||gn),s.length>1&&s.sort(e||vn),r.length>1&&r.sort(e||vn)}}}function xn(t){let e=new WeakMap;return{get:function(n,i){let s;return!1===e.has(n)?(s=new yn(t),e.set(n,[s])):i>=e.get(n).length?(s=new yn(t),e.get(n).push(s)):s=e.get(n)[i],s},dispose:function(){e=new WeakMap}}}function bn(){const t={};return{get:function(e){if(void 0!==t[e.id])return t[e.id];let n;switch(e.type){case\\\\\\\"DirectionalLight\\\\\\\":n={direction:new p.a,color:new D.a};break;case\\\\\\\"SpotLight\\\\\\\":n={position:new p.a,direction:new p.a,color:new D.a,distance:0,coneCos:0,penumbraCos:0,decay:0};break;case\\\\\\\"PointLight\\\\\\\":n={position:new p.a,color:new D.a,distance:0,decay:0};break;case\\\\\\\"HemisphereLight\\\\\\\":n={direction:new p.a,skyColor:new D.a,groundColor:new D.a};break;case\\\\\\\"RectAreaLight\\\\\\\":n={color:new D.a,position:new p.a,halfWidth:new p.a,halfHeight:new p.a}}return t[e.id]=n,n}}}let wn=0;function Tn(t,e){return(e.castShadow?1:0)-(t.castShadow?1:0)}function An(t,e){const n=new bn,i=function(){const t={};return{get:function(e){if(void 0!==t[e.id])return t[e.id];let n;switch(e.type){case\\\\\\\"DirectionalLight\\\\\\\":case\\\\\\\"SpotLight\\\\\\\":n={shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new d.a};break;case\\\\\\\"PointLight\\\\\\\":n={shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new d.a,shadowCameraNear:1,shadowCameraFar:1e3}}return t[e.id]=n,n}}}(),s={version:0,hash:{directionalLength:-1,pointLength:-1,spotLength:-1,rectAreaLength:-1,hemiLength:-1,numDirectionalShadows:-1,numPointShadows:-1,numSpotShadows:-1},ambient:[0,0,0],probe:[],directional:[],directionalShadow:[],directionalShadowMap:[],directionalShadowMatrix:[],spot:[],spotShadow:[],spotShadowMap:[],spotShadowMatrix:[],rectArea:[],rectAreaLTC1:null,rectAreaLTC2:null,point:[],pointShadow:[],pointShadowMap:[],pointShadowMatrix:[],hemi:[]};for(let t=0;t<9;t++)s.probe.push(new p.a);const r=new p.a,o=new A.a,a=new A.a;return{setup:function(r,o){let a=0,l=0,c=0;for(let t=0;t<9;t++)s.probe[t].set(0,0,0);let h=0,u=0,d=0,p=0,_=0,m=0,f=0,g=0;r.sort(Tn);const v=!0!==o?Math.PI:1;for(let t=0,e=r.length;t0&&(e.isWebGL2||!0===t.has(\\\\\\\"OES_texture_float_linear\\\\\\\")?(s.rectAreaLTC1=V.LTC_FLOAT_1,s.rectAreaLTC2=V.LTC_FLOAT_2):!0===t.has(\\\\\\\"OES_texture_half_float_linear\\\\\\\")?(s.rectAreaLTC1=V.LTC_HALF_1,s.rectAreaLTC2=V.LTC_HALF_2):console.error(\\\\\\\"THREE.WebGLRenderer: Unable to use RectAreaLight. Missing WebGL extensions.\\\\\\\")),s.ambient[0]=a,s.ambient[1]=l,s.ambient[2]=c;const y=s.hash;y.directionalLength===h&&y.pointLength===u&&y.spotLength===d&&y.rectAreaLength===p&&y.hemiLength===_&&y.numDirectionalShadows===m&&y.numPointShadows===f&&y.numSpotShadows===g||(s.directional.length=h,s.spot.length=d,s.rectArea.length=p,s.point.length=u,s.hemi.length=_,s.directionalShadow.length=m,s.directionalShadowMap.length=m,s.pointShadow.length=f,s.pointShadowMap.length=f,s.spotShadow.length=g,s.spotShadowMap.length=g,s.directionalShadowMatrix.length=m,s.pointShadowMatrix.length=f,s.spotShadowMatrix.length=g,y.directionalLength=h,y.pointLength=u,y.spotLength=d,y.rectAreaLength=p,y.hemiLength=_,y.numDirectionalShadows=m,y.numPointShadows=f,y.numSpotShadows=g,s.version=wn++)},setupView:function(t,e){let n=0,i=0,l=0,c=0,h=0;const u=e.matrixWorldInverse;for(let e=0,d=t.length;e=n.get(i).length?(r=new Mn(t,e),n.get(i).push(r)):r=n.get(i)[s],r},dispose:function(){n=new WeakMap}}}class Sn extends O.a{constructor(t){super(),this.type=\\\\\\\"MeshDepthMaterial\\\\\\\",this.depthPacking=w.j,this.map=null,this.alphaMap=null,this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.wireframe=!1,this.wireframeLinewidth=1,this.fog=!1,this.setValues(t)}copy(t){return super.copy(t),this.depthPacking=t.depthPacking,this.map=t.map,this.alphaMap=t.alphaMap,this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this.wireframe=t.wireframe,this.wireframeLinewidth=t.wireframeLinewidth,this}}Sn.prototype.isMeshDepthMaterial=!0;class Cn extends O.a{constructor(t){super(),this.type=\\\\\\\"MeshDistanceMaterial\\\\\\\",this.referencePosition=new p.a,this.nearDistance=1,this.farDistance=1e3,this.map=null,this.alphaMap=null,this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.fog=!1,this.setValues(t)}copy(t){return super.copy(t),this.referencePosition.copy(t.referencePosition),this.nearDistance=t.nearDistance,this.farDistance=t.farDistance,this.map=t.map,this.alphaMap=t.alphaMap,this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this}}Cn.prototype.isMeshDistanceMaterial=!0;function Nn(t,e,n){let i=new T.a;const s=new d.a,r=new d.a,o=new _.a,a=new Sn({depthPacking:w.Hb}),l=new Cn,c={},h=n.maxTextureSize,u={0:w.i,1:w.H,2:w.z},p=new F({uniforms:{shadow_pass:{value:null},resolution:{value:new d.a},radius:{value:4},samples:{value:8}},vertexShader:\\\\\\\"\\\\nvoid main() {\\\\n\\\\n\\\\tgl_Position = vec4( position, 1.0 );\\\\n\\\\n}\\\\n\\\\\\\",fragmentShader:\\\\\\\"\\\\nuniform sampler2D shadow_pass;\\\\nuniform vec2 resolution;\\\\nuniform float radius;\\\\nuniform float samples;\\\\n\\\\n#include \\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tfloat mean = 0.0;\\\\n\\\\tfloat squared_mean = 0.0;\\\\n\\\\n\\\\t// This seems totally useless but it's a crazy work around for a Adreno compiler bug\\\\n\\\\t// float depth = unpackRGBAToDepth( texture2D( shadow_pass, ( gl_FragCoord.xy ) / resolution ) );\\\\n\\\\n\\\\tfloat uvStride = samples <= 1.0 ? 0.0 : 2.0 / ( samples - 1.0 );\\\\n\\\\tfloat uvStart = samples <= 1.0 ? 0.0 : - 1.0;\\\\n\\\\tfor ( float i = 0.0; i < samples; i ++ ) {\\\\n\\\\n\\\\t\\\\tfloat uvOffset = uvStart + i * uvStride;\\\\n\\\\n\\\\t\\\\t#ifdef HORIZONTAL_PASS\\\\n\\\\n\\\\t\\\\t\\\\tvec2 distribution = unpackRGBATo2Half( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( uvOffset, 0.0 ) * radius ) / resolution ) );\\\\n\\\\t\\\\t\\\\tmean += distribution.x;\\\\n\\\\t\\\\t\\\\tsquared_mean += distribution.y * distribution.y + distribution.x * distribution.x;\\\\n\\\\n\\\\t\\\\t#else\\\\n\\\\n\\\\t\\\\t\\\\tfloat depth = unpackRGBAToDepth( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( 0.0, uvOffset ) * radius ) / resolution ) );\\\\n\\\\t\\\\t\\\\tmean += depth;\\\\n\\\\t\\\\t\\\\tsquared_mean += depth * depth;\\\\n\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t}\\\\n\\\\n\\\\tmean = mean / samples;\\\\n\\\\tsquared_mean = squared_mean / samples;\\\\n\\\\n\\\\tfloat std_dev = sqrt( squared_mean - mean * mean );\\\\n\\\\n\\\\tgl_FragColor = pack2HalfToRGBA( vec2( mean, std_dev ) );\\\\n\\\\n}\\\\n\\\\\\\"}),m=p.clone();m.defines.HORIZONTAL_PASS=1;const f=new S.a;f.setAttribute(\\\\\\\"position\\\\\\\",new C.a(new Float32Array([-1,-1,.5,3,-1,.5,-1,3,.5]),3));const g=new B.a(f,p),v=this;function y(n,i){const s=e.update(g);p.uniforms.shadow_pass.value=n.map.texture,p.uniforms.resolution.value=n.mapSize,p.uniforms.radius.value=n.radius,p.uniforms.samples.value=n.blurSamples,t.setRenderTarget(n.mapPass),t.clear(),t.renderBufferDirect(i,null,s,p,g,null),m.uniforms.shadow_pass.value=n.mapPass.texture,m.uniforms.resolution.value=n.mapSize,m.uniforms.radius.value=n.radius,m.uniforms.samples.value=n.blurSamples,t.setRenderTarget(n.map),t.clear(),t.renderBufferDirect(i,null,s,m,g,null)}function x(e,n,i,s,r,o,h){let d=null;const p=!0===s.isPointLight?e.customDistanceMaterial:e.customDepthMaterial;if(d=void 0!==p?p:!0===s.isPointLight?l:a,t.localClippingEnabled&&!0===i.clipShadows&&0!==i.clippingPlanes.length||i.displacementMap&&0!==i.displacementScale||i.alphaMap&&i.alphaTest>0){const t=d.uuid,e=i.uuid;let n=c[t];void 0===n&&(n={},c[t]=n);let s=n[e];void 0===s&&(s=d.clone(),n[e]=s),d=s}return 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l=0,c=e.length;lh||s.y>h)&&(s.x>h&&(r.x=Math.floor(h/p.x),s.x=r.x*p.x,u.mapSize.x=r.x),s.y>h&&(r.y=Math.floor(h/p.y),s.y=r.y*p.y,u.mapSize.y=r.y)),null===u.map&&!u.isPointLightShadow&&this.type===w.gd){const t={minFilter:w.V,magFilter:w.V,format:w.Ib};u.map=new Q(s.x,s.y,t),u.map.texture.name=c.name+\\\\\\\".shadowMap\\\\\\\",u.mapPass=new Q(s.x,s.y,t),u.camera.updateProjectionMatrix()}if(null===u.map){const t={minFilter:w.ob,magFilter:w.ob,format:w.Ib};u.map=new Q(s.x,s.y,t),u.map.texture.name=c.name+\\\\\\\".shadowMap\\\\\\\",u.camera.updateProjectionMatrix()}t.setRenderTarget(u.map),t.clear();const _=u.getViewportCount();for(let t=0;t<_;t++){const e=u.getViewport(t);o.set(r.x*e.x,r.y*e.y,r.x*e.z,r.y*e.w),d.viewport(o),u.updateMatrices(c,t),i=u.getFrustum(),b(n,a,u.camera,c,this.type)}u.isPointLightShadow||this.type!==w.gd||y(u,a),u.needsUpdate=!1}v.needsUpdate=!1,t.setRenderTarget(l,c,u)}}function Ln(t,e,n){const i=n.isWebGL2;const s=new function(){let e=!1;const n=new _.a;let 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function(){let e=!1,n=null,i=null,s=null,r=null,o=null,a=null,l=null,c=null;return{setTest:function(n){e||(n?k(t.STENCIL_TEST):U(t.STENCIL_TEST))},setMask:function(i){n===i||e||(t.stencilMask(i),n=i)},setFunc:function(e,n,o){i===e&&s===n&&r===o||(t.stencilFunc(e,n,o),i=e,s=n,r=o)},setOp:function(e,n,i){o===e&&a===n&&l===i||(t.stencilOp(e,n,i),o=e,a=n,l=i)},setLocked:function(t){e=t},setClear:function(e){c!==e&&(t.clearStencil(e),c=e)},reset:function(){e=!1,n=null,i=null,s=null,r=null,o=null,a=null,l=null,c=null}}};let a={},l=null,c={},h=null,u=!1,d=null,p=null,m=null,f=null,g=null,v=null,y=null,x=!1,b=null,T=null,A=null,M=null,E=null;const S=t.getParameter(t.MAX_COMBINED_TEXTURE_IMAGE_UNITS);let C=!1,N=0;const L=t.getParameter(t.VERSION);-1!==L.indexOf(\\\\\\\"WebGL\\\\\\\")?(N=parseFloat(/^WebGL (\\\\d)/.exec(L)[1]),C=N>=1):-1!==L.indexOf(\\\\\\\"OpenGL ES\\\\\\\")&&(N=parseFloat(/^OpenGL ES (\\\\d)/.exec(L)[1]),C=N>=2);let O=null,P={};const 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0!==s&&(s.isWebGLRenderTarget&&(s=s.texture),!0===s.matrixAutoUpdate&&s.updateMatrix(),e.uvTransform.value.copy(s.matrix)),n.aoMap?r=n.aoMap:n.lightMap&&(r=n.lightMap),void 0!==r&&(r.isWebGLRenderTarget&&(r=r.texture),!0===r.matrixAutoUpdate&&r.updateMatrix(),e.uv2Transform.value.copy(r.matrix))}function n(e,n){e.roughness.value=n.roughness,e.metalness.value=n.metalness,n.roughnessMap&&(e.roughnessMap.value=n.roughnessMap),n.metalnessMap&&(e.metalnessMap.value=n.metalnessMap),n.emissiveMap&&(e.emissiveMap.value=n.emissiveMap),n.bumpMap&&(e.bumpMap.value=n.bumpMap,e.bumpScale.value=n.bumpScale,n.side===w.i&&(e.bumpScale.value*=-1)),n.normalMap&&(e.normalMap.value=n.normalMap,e.normalScale.value.copy(n.normalScale),n.side===w.i&&e.normalScale.value.negate()),n.displacementMap&&(e.displacementMap.value=n.displacementMap,e.displacementScale.value=n.displacementScale,e.displacementBias.value=n.displacementBias);t.get(n).envMap&&(e.envMapIntensity.value=n.envMapIntensity)}return{refreshFogUniforms:function(t,e){t.fogColor.value.copy(e.color),e.isFog?(t.fogNear.value=e.near,t.fogFar.value=e.far):e.isFogExp2&&(t.fogDensity.value=e.density)},refreshMaterialUniforms:function(t,i,s,r,o){i.isMeshBasicMaterial?e(t,i):i.isMeshLambertMaterial?(e(t,i),function(t,e){e.emissiveMap&&(t.emissiveMap.value=e.emissiveMap)}(t,i)):i.isMeshToonMaterial?(e(t,i),function(t,e){e.gradientMap&&(t.gradientMap.value=e.gradientMap);e.emissiveMap&&(t.emissiveMap.value=e.emissiveMap);e.bumpMap&&(t.bumpMap.value=e.bumpMap,t.bumpScale.value=e.bumpScale,e.side===w.i&&(t.bumpScale.value*=-1));e.normalMap&&(t.normalMap.value=e.normalMap,t.normalScale.value.copy(e.normalScale),e.side===w.i&&t.normalScale.value.negate());e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isMeshPhongMaterial?(e(t,i),function(t,e){t.specular.value.copy(e.specular),t.shininess.value=Math.max(e.shininess,1e-4),e.emissiveMap&&(t.emissiveMap.value=e.emissiveMap);e.bumpMap&&(t.bumpMap.value=e.bumpMap,t.bumpScale.value=e.bumpScale,e.side===w.i&&(t.bumpScale.value*=-1));e.normalMap&&(t.normalMap.value=e.normalMap,t.normalScale.value.copy(e.normalScale),e.side===w.i&&t.normalScale.value.negate());e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isMeshStandardMaterial?(e(t,i),i.isMeshPhysicalMaterial?function(t,e,i){n(t,e),t.ior.value=e.ior,e.sheen>0&&(t.sheenTint.value.copy(e.sheenTint).multiplyScalar(e.sheen),t.sheenRoughness.value=e.sheenRoughness);e.clearcoat>0&&(t.clearcoat.value=e.clearcoat,t.clearcoatRoughness.value=e.clearcoatRoughness,e.clearcoatMap&&(t.clearcoatMap.value=e.clearcoatMap),e.clearcoatRoughnessMap&&(t.clearcoatRoughnessMap.value=e.clearcoatRoughnessMap),e.clearcoatNormalMap&&(t.clearcoatNormalScale.value.copy(e.clearcoatNormalScale),t.clearcoatNormalMap.value=e.clearcoatNormalMap,e.side===w.i&&t.clearcoatNormalScale.value.negate()));e.transmission>0&&(t.transmission.value=e.transmission,t.transmissionSamplerMap.value=i.texture,t.transmissionSamplerSize.value.set(i.width,i.height),e.transmissionMap&&(t.transmissionMap.value=e.transmissionMap),t.thickness.value=e.thickness,e.thicknessMap&&(t.thicknessMap.value=e.thicknessMap),t.attenuationDistance.value=e.attenuationDistance,t.attenuationTint.value.copy(e.attenuationTint));t.specularIntensity.value=e.specularIntensity,t.specularTint.value.copy(e.specularTint),e.specularIntensityMap&&(t.specularIntensityMap.value=e.specularIntensityMap);e.specularTintMap&&(t.specularTintMap.value=e.specularTintMap)}(t,i,o):n(t,i)):i.isMeshMatcapMaterial?(e(t,i),function(t,e){e.matcap&&(t.matcap.value=e.matcap);e.bumpMap&&(t.bumpMap.value=e.bumpMap,t.bumpScale.value=e.bumpScale,e.side===w.i&&(t.bumpScale.value*=-1));e.normalMap&&(t.normalMap.value=e.normalMap,t.normalScale.value.copy(e.normalScale),e.side===w.i&&t.normalScale.value.negate());e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isMeshDepthMaterial?(e(t,i),function(t,e){e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isMeshDistanceMaterial?(e(t,i),function(t,e){e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias);t.referencePosition.value.copy(e.referencePosition),t.nearDistance.value=e.nearDistance,t.farDistance.value=e.farDistance}(t,i)):i.isMeshNormalMaterial?(e(t,i),function(t,e){e.bumpMap&&(t.bumpMap.value=e.bumpMap,t.bumpScale.value=e.bumpScale,e.side===w.i&&(t.bumpScale.value*=-1));e.normalMap&&(t.normalMap.value=e.normalMap,t.normalScale.value.copy(e.normalScale),e.side===w.i&&t.normalScale.value.negate());e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isLineBasicMaterial?(function(t,e){t.diffuse.value.copy(e.color),t.opacity.value=e.opacity}(t,i),i.isLineDashedMaterial&&function(t,e){t.dashSize.value=e.dashSize,t.totalSize.value=e.dashSize+e.gapSize,t.scale.value=e.scale}(t,i)):i.isPointsMaterial?function(t,e,n,i){t.diffuse.value.copy(e.color),t.opacity.value=e.opacity,t.size.value=e.size*n,t.scale.value=.5*i,e.map&&(t.map.value=e.map);e.alphaMap&&(t.alphaMap.value=e.alphaMap);e.alphaTest>0&&(t.alphaTest.value=e.alphaTest);let s;e.map?s=e.map:e.alphaMap&&(s=e.alphaMap);void 0!==s&&(!0===s.matrixAutoUpdate&&s.updateMatrix(),t.uvTransform.value.copy(s.matrix))}(t,i,s,r):i.isSpriteMaterial?function(t,e){t.diffuse.value.copy(e.color),t.opacity.value=e.opacity,t.rotation.value=e.rotation,e.map&&(t.map.value=e.map);e.alphaMap&&(t.alphaMap.value=e.alphaMap);e.alphaTest>0&&(t.alphaTest.value=e.alphaTest);let n;e.map?n=e.map:e.alphaMap&&(n=e.alphaMap);void 0!==n&&(!0===n.matrixAutoUpdate&&n.updateMatrix(),t.uvTransform.value.copy(n.matrix))}(t,i):i.isShadowMaterial?(t.color.value.copy(i.color),t.opacity.value=i.opacity):i.isShaderMaterial&&(i.uniformsNeedUpdate=!1)}}}function Un(t={}){const e=void 0!==t.canvas?t.canvas:function(){const t=Object(It.b)(\\\\\\\"canvas\\\\\\\");return t.style.display=\\\\\\\"block\\\\\\\",t}(),n=void 0!==t.context?t.context:null,i=void 0!==t.alpha&&t.alpha,s=void 0===t.depth||t.depth,r=void 0===t.stencil||t.stencil,o=void 0!==t.antialias&&t.antialias,a=void 0===t.premultipliedAlpha||t.premultipliedAlpha,l=void 0!==t.preserveDrawingBuffer&&t.preserveDrawingBuffer,c=void 0!==t.powerPreference?t.powerPreference:\\\\\\\"default\\\\\\\",h=void 0!==t.failIfMajorPerformanceCaveat&&t.failIfMajorPerformanceCaveat;let u=null,d=null;const m=[],f=[];this.domElement=e,this.debug={checkShaderErrors:!0},this.autoClear=!0,this.autoClearColor=!0,this.autoClearDepth=!0,this.autoClearStencil=!0,this.sortObjects=!0,this.clippingPlanes=[],this.localClippingEnabled=!1,this.gammaFactor=2,this.outputEncoding=w.U,this.physicallyCorrectLights=!1,this.toneMapping=w.vb,this.toneMappingExposure=1;const g=this;let v=!1,y=0,x=0,b=null,S=-1,C=null;const N=new _.a,L=new _.a;let O=null,P=e.width,R=e.height,I=1,F=null,D=null;const B=new _.a(0,0,P,R),z=new _.a(0,0,P,R);let k=!1;const U=[],G=new T.a;let V=!1,H=!1,Y=null;const J=new A.a,Z=new p.a,K={background:null,fog:null,environment:null,overrideMaterial:null,isScene:!0};function tt(){return null===b?I:1}let et,nt,it,st,ot,at,lt,ct,ht,ut,dt,pt,_t,mt,ft,gt,vt,yt,xt,bt,wt,Tt,At,Mt=n;function Et(t,n){for(let i=0;i0&&function(t,e,n){if(null===Y){const t=!0===o&&!0===nt.isWebGL2;Y=new(t?Ht:Q)(1024,1024,{generateMipmaps:!0,type:null!==Tt.convert(w.M)?w.M:w.Zc,minFilter:w.Y,magFilter:w.ob,wrapS:w.n,wrapT:w.n})}const i=g.getRenderTarget();g.setRenderTarget(Y),g.clear();const s=g.toneMapping;g.toneMapping=w.vb,Xt(t,e,n),g.toneMapping=s,at.updateMultisampleRenderTarget(Y),at.updateRenderTargetMipmap(Y),g.setRenderTarget(i)}(s,e,n),i&&it.viewport(N.copy(i)),s.length>0&&Xt(s,e,n),r.length>0&&Xt(r,e,n),a.length>0&&Xt(a,e,n)}function Xt(t,e,n){const i=!0===e.isScene?e.overrideMaterial:null;for(let s=0,r=t.length;s0?f[f.length-1]:null,m.pop(),u=m.length>0?m[m.length-1]:null},this.getActiveCubeFace=function(){return y},this.getActiveMipmapLevel=function(){return x},this.getRenderTarget=function(){return b},this.setRenderTarget=function(t,e=0,n=0){b=t,y=e,x=n,t&&void 0===ot.get(t).__webglFramebuffer&&at.setupRenderTarget(t);let i=null,s=!1,r=!1;if(t){const n=t.texture;(n.isDataTexture3D||n.isDataTexture2DArray)&&(r=!0);const o=ot.get(t).__webglFramebuffer;t.isWebGLCubeRenderTarget?(i=o[e],s=!0):i=t.isWebGLMultisampleRenderTarget?ot.get(t).__webglMultisampledFramebuffer:o,N.copy(t.viewport),L.copy(t.scissor),O=t.scissorTest}else N.copy(B).multiplyScalar(I).floor(),L.copy(z).multiplyScalar(I).floor(),O=k;if(it.bindFramebuffer(Mt.FRAMEBUFFER,i)&&nt.drawBuffers){let e=!1;if(t)if(t.isWebGLMultipleRenderTargets){const n=t.texture;if(U.length!==n.length||U[0]!==Mt.COLOR_ATTACHMENT0){for(let t=0,e=n.length;t=0&&e<=t.width-i&&n>=0&&n<=t.height-s&&Mt.readPixels(e,n,i,s,Tt.convert(a),Tt.convert(l),r):console.error(\\\\\\\"THREE.WebGLRenderer.readRenderTargetPixels: readPixels from renderTarget failed. Framebuffer not complete.\\\\\\\")}finally{const t=null!==b?ot.get(b).__webglFramebuffer:null;it.bindFramebuffer(Mt.FRAMEBUFFER,t)}}},this.copyFramebufferToTexture=function(t,e,n=0){const i=Math.pow(2,-n),s=Math.floor(e.image.width*i),r=Math.floor(e.image.height*i);let o=Tt.convert(e.format);nt.isWebGL2&&(o===Mt.RGB&&(o=Mt.RGB8),o===Mt.RGBA&&(o=Mt.RGBA8)),at.setTexture2D(e,0),Mt.copyTexImage2D(Mt.TEXTURE_2D,n,o,t.x,t.y,s,r,0),it.unbindTexture()},this.copyTextureToTexture=function(t,e,n,i=0){const s=e.image.width,r=e.image.height,o=Tt.convert(n.format),a=Tt.convert(n.type);at.setTexture2D(n,0),Mt.pixelStorei(Mt.UNPACK_FLIP_Y_WEBGL,n.flipY),Mt.pixelStorei(Mt.UNPACK_PREMULTIPLY_ALPHA_WEBGL,n.premultiplyAlpha),Mt.pixelStorei(Mt.UNPACK_ALIGNMENT,n.unpackAlignment),e.isDataTexture?Mt.texSubImage2D(Mt.TEXTURE_2D,i,t.x,t.y,s,r,o,a,e.image.data):e.isCompressedTexture?Mt.compressedTexSubImage2D(Mt.TEXTURE_2D,i,t.x,t.y,e.mipmaps[0].width,e.mipmaps[0].height,o,e.mipmaps[0].data):Mt.texSubImage2D(Mt.TEXTURE_2D,i,t.x,t.y,o,a,e.image),0===i&&n.generateMipmaps&&Mt.generateMipmap(Mt.TEXTURE_2D),it.unbindTexture()},this.copyTextureToTexture3D=function(t,e,n,i,s=0){if(g.isWebGL1Renderer)return void console.warn(\\\\\\\"THREE.WebGLRenderer.copyTextureToTexture3D: can only be used with WebGL2.\\\\\\\");const r=t.max.x-t.min.x+1,o=t.max.y-t.min.y+1,a=t.max.z-t.min.z+1,l=Tt.convert(i.format),c=Tt.convert(i.type);let h;if(i.isDataTexture3D)at.setTexture3D(i,0),h=Mt.TEXTURE_3D;else{if(!i.isDataTexture2DArray)return void console.warn(\\\\\\\"THREE.WebGLRenderer.copyTextureToTexture3D: only supports THREE.DataTexture3D and THREE.DataTexture2DArray.\\\\\\\");at.setTexture2DArray(i,0),h=Mt.TEXTURE_2D_ARRAY}Mt.pixelStorei(Mt.UNPACK_FLIP_Y_WEBGL,i.flipY),Mt.pixelStorei(Mt.UNPACK_PREMULTIPLY_ALPHA_WEBGL,i.premultiplyAlpha),Mt.pixelStorei(Mt.UNPACK_ALIGNMENT,i.unpackAlignment);const u=Mt.getParameter(Mt.UNPACK_ROW_LENGTH),d=Mt.getParameter(Mt.UNPACK_IMAGE_HEIGHT),p=Mt.getParameter(Mt.UNPACK_SKIP_PIXELS),_=Mt.getParameter(Mt.UNPACK_SKIP_ROWS),m=Mt.getParameter(Mt.UNPACK_SKIP_IMAGES),f=n.isCompressedTexture?n.mipmaps[0]:n.image;Mt.pixelStorei(Mt.UNPACK_ROW_LENGTH,f.width),Mt.pixelStorei(Mt.UNPACK_IMAGE_HEIGHT,f.height),Mt.pixelStorei(Mt.UNPACK_SKIP_PIXELS,t.min.x),Mt.pixelStorei(Mt.UNPACK_SKIP_ROWS,t.min.y),Mt.pixelStorei(Mt.UNPACK_SKIP_IMAGES,t.min.z),n.isDataTexture||n.isDataTexture3D?Mt.texSubImage3D(h,s,e.x,e.y,e.z,r,o,a,l,c,f.data):n.isCompressedTexture?(console.warn(\\\\\\\"THREE.WebGLRenderer.copyTextureToTexture3D: untested support for compressed srcTexture.\\\\\\\"),Mt.compressedTexSubImage3D(h,s,e.x,e.y,e.z,r,o,a,l,f.data)):Mt.texSubImage3D(h,s,e.x,e.y,e.z,r,o,a,l,c,f),Mt.pixelStorei(Mt.UNPACK_ROW_LENGTH,u),Mt.pixelStorei(Mt.UNPACK_IMAGE_HEIGHT,d),Mt.pixelStorei(Mt.UNPACK_SKIP_PIXELS,p),Mt.pixelStorei(Mt.UNPACK_SKIP_ROWS,_),Mt.pixelStorei(Mt.UNPACK_SKIP_IMAGES,m),0===s&&i.generateMipmaps&&Mt.generateMipmap(h),it.unbindTexture()},this.initTexture=function(t){at.setTexture2D(t,0),it.unbindTexture()},this.resetState=function(){y=0,x=0,b=null,it.reset(),At.reset()},\\\\\\\"undefined\\\\\\\"!=typeof __THREE_DEVTOOLS__&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent(\\\\\\\"observe\\\\\\\",{detail:this}))}const Gn={};var Vn,Hn,jn;!function(t){t.WEBGL=\\\\\\\"webgl\\\\\\\",t.WEBGL2=\\\\\\\"webgl2\\\\\\\",t.EXPERIMENTAL_WEBGL=\\\\\\\"experimental-webgl\\\\\\\",t.EXPERIMENTAL_WEBGL2=\\\\\\\"experimental-webgl2\\\\\\\"}(Vn||(Vn={}));class Wn{constructor(){this._next_renderer_id=0,this._renderers={},this._printDebug=!1,this._require_webgl2=!1,this._resolves=[]}setPrintDebug(t=!0){this._printDebug=t}printDebug(){return this._printDebug}printDebugMessage(t){this._printDebug&&console.warn(\\\\\\\"[Poly debug]\\\\\\\",t)}setRequireWebGL2(){this._require_webgl2||(this._require_webgl2=!0)}webgl2Available(){return void 0===this._webgl2_available&&(this._webgl2_available=this._set_webgl2_available()),this._webgl2_available}_set_webgl2_available(){const t=document.createElement(\\\\\\\"canvas\\\\\\\");return null!=(window.WebGL2RenderingContext&&t.getContext(Vn.WEBGL2))}createWebGLRenderer(t){const e=new Un(t);return this.printDebugMessage([\\\\\\\"create renderer:\\\\\\\",t]),e}createRenderingContext(t){let e=null;return this._require_webgl2&&(e=this._getRenderingContextWebgl(t,!0),e||console.warn(\\\\\\\"failed to create webgl2 context\\\\\\\")),e||(e=this._getRenderingContextWebgl(t,!1)),e}_getRenderingContextWebgl(t,e){let n;n=this.webgl2Available()||e?Vn.WEBGL2:Vn.WEBGL;let i=t.getContext(n,Gn);return i?this.printDebugMessage(`create gl context: ${n}.`):(n=e?Vn.EXPERIMENTAL_WEBGL2:Vn.EXPERIMENTAL_WEBGL,this.printDebugMessage(`create gl context: ${n}.`),i=t.getContext(n,Gn)),i}registerRenderer(t){if(t._polygon_id)throw new Error(\\\\\\\"render already registered\\\\\\\");t._polygon_id=this._next_renderer_id+=1,this._renderers[t._polygon_id]=t,1==Object.keys(this._renderers).length&&this.flush_callbacks_with_renderer(t)}deregisterRenderer(t){delete this._renderers[t._polygon_id],t.dispose()}firstRenderer(){const t=Object.keys(this._renderers)[0];return t?this._renderers[t]:null}renderers(){return Object.values(this._renderers)}flush_callbacks_with_renderer(t){let e;for(;e=this._resolves.pop();)e(t)}async waitForRenderer(){const t=this.firstRenderer();return t||new Promise(((t,e)=>{this._resolves.push(t)}))}renderTarget(t,e,n){return this.webgl2Available()?new Ht(t,e,n):new Q(t,e,n)}}class qn{constructor(){this._root=\\\\\\\"/three/js/libs\\\\\\\",this._BASISPath=\\\\\\\"/basis\\\\\\\",this._DRACOPath=\\\\\\\"/draco\\\\\\\",this._DRACOGLTFPath=\\\\\\\"/draco/gltf\\\\\\\"}root(){return this._root}setRoot(t){this._root=t}BASISPath(){return this._BASISPath}DRACOPath(){return this._DRACOPath}DRACOGLTFPath(){return this._DRACOGLTFPath}}class Xn{constructor(t){this.poly=t,this._node_register=new Map,this._node_register_categories=new Map,this._node_register_options=new Map}static type(t){return this.filterType(t.type())}static filterType(t){return t.toLowerCase()}register(t,e,n){const i=t.context(),s=Xn.type(t);let r=this._node_register.get(i);r||(r=new Map,this._node_register.set(i,r));if(r.get(s))console.error(`node ${i}/${s} already registered`);else{if(r.set(s,t),e){let t=this._node_register_categories.get(i);t||(t=new Map,this._node_register_categories.set(i,t)),t.set(s,e)}if(n){let t=this._node_register_options.get(i);t||(t=new Map,this._node_register_options.set(i,t)),t.set(s,n)}this.poly.pluginsRegister.registerNode(t)}}deregister(t,e){var n,i,s;e=Xn.filterType(e),null===(n=this._node_register.get(t))||void 0===n||n.delete(e),null===(i=this._node_register_categories.get(t))||void 0===i||i.delete(e),null===(s=this._node_register_options.get(t))||void 0===s||s.delete(e)}isRegistered(t,e){const n=this._node_register.get(t);return!!n&&(e=Xn.filterType(e),null!=n.get(e))}nodeOptions(t,e){var n;return e=Xn.filterType(e),null===(n=this._node_register_options.get(t))||void 0===n?void 0:n.get(e)}registeredNodesForContextAndParentType(t,e){var n;if(this._node_register.get(t)){const i=[];return null===(n=this._node_register.get(t))||void 0===n||n.forEach(((t,e)=>{i.push(t)})),i.filter((n=>{var i;const s=Xn.type(n),r=null===(i=this._node_register_options.get(t))||void 0===i?void 0:i.get(s);if(r){const n=r.only,i=r.except,s=`${t}/${e}`;return n?n.includes(s):!i||!i.includes(s)}return!0}))}return[]}registeredNodes(t,e){const n={},i=this.registeredNodesForContextAndParentType(t,e);for(let t of i){n[Xn.type(t)]=t}return n}registeredCategory(t,e){var n;return e=Xn.filterType(e),null===(n=this._node_register_categories.get(t))||void 0===n?void 0:n.get(e)}map(){return this._node_register}}class Yn{constructor(t){this.poly=t,this._operation_register=new Map}static type(t){return this.filterType(t.type())}static filterType(t){return t.toLowerCase()}register(t){const e=t.context();let n=this._operation_register.get(e);n||(n=new Map,this._operation_register.set(e,n));const i=Yn.type(t);if(n.get(i)){const t=`operation ${e}/${i} already registered`;console.error(t)}else n.set(i,t),this.poly.pluginsRegister.registerOperation(t)}registeredOperationsForContextAndParentType(t,e){var n;if(this._operation_register.get(t)){const e=[];return null===(n=this._operation_register.get(t))||void 0===n||n.forEach(((t,n)=>{e.push(t)})),e}return[]}registeredOperation(t,e){const n=this._operation_register.get(t);if(n)return e=Yn.filterType(e),n.get(e)}}class $n extends class{constructor(){this._methods_names=[],this._methods_by_name=new Map}register(t,e){this._methods_names.push(e),this._methods_by_name.set(e,t)}getMethod(t){return this._methods_by_name.get(t)}availableMethods(){return this._methods_names}}{getMethod(t){return super.getMethod(t)}}!function(t){t.BasisTextureLoader=\\\\\\\"BasisTextureLoader\\\\\\\",t.DRACOLoader=\\\\\\\"DRACOLoader\\\\\\\",t.EXRLoader=\\\\\\\"EXRLoader\\\\\\\",t.FBXLoader=\\\\\\\"FBXLoader\\\\\\\",t.GLTFLoader=\\\\\\\"GLTFLoader\\\\\\\",t.OBJLoader=\\\\\\\"OBJLoader\\\\\\\",t.PDBLoader=\\\\\\\"PDBLoader\\\\\\\",t.PLYLoader=\\\\\\\"PLYLoader\\\\\\\",t.RGBELoader=\\\\\\\"RGBELoader\\\\\\\",t.SVGLoader=\\\\\\\"SVGLoader\\\\\\\",t.STLLoader=\\\\\\\"STLLoader\\\\\\\",t.TTFLoader=\\\\\\\"TTFLoader\\\\\\\"}(Hn||(Hn={}));class Jn extends class{constructor(){this._module_by_name=new Map}register(t,e){this._module_by_name.set(t,e)}moduleNames(){const t=[];return this._module_by_name.forEach(((e,n)=>{t.push(n)})),t}module(t){return this._module_by_name.get(t)}}{}!function(t){t.GL_MESH_BASIC=\\\\\\\"GL_MESH_BASIC\\\\\\\",t.GL_MESH_LAMBERT=\\\\\\\"GL_MESH_LAMBERT\\\\\\\",t.GL_MESH_STANDARD=\\\\\\\"GL_MESH_STANDARD\\\\\\\",t.GL_MESH_PHONG=\\\\\\\"GL_MESH_PHONG\\\\\\\",t.GL_MESH_PHYSICAL=\\\\\\\"GL_MESH_PHYSICAL\\\\\\\",t.GL_PARTICLES=\\\\\\\"GL_PARTICLES\\\\\\\",t.GL_POINTS=\\\\\\\"GL_POINTS\\\\\\\",t.GL_LINE=\\\\\\\"GL_LINE\\\\\\\",t.GL_TEXTURE=\\\\\\\"GL_TEXTURE\\\\\\\",t.GL_VOLUME=\\\\\\\"GL_VOLUME\\\\\\\"}(jn||(jn={}));class Zn extends class{constructor(){this._controller_assembler_by_name=new Map}register(t,e,n){this._controller_assembler_by_name.set(t,{controller:e,assembler:n})}unregister(t){this._controller_assembler_by_name.delete(t)}}{assembler(t,e){const n=this._controller_assembler_by_name.get(e);if(n){return new(0,n.controller)(t,n.assembler)}return n}unregister(t){const e=this._controller_assembler_by_name.get(t);return super.unregister(t),e}}class Qn{constructor(t){this.poly=t,this._plugins_by_name=new Map,this._plugin_name_by_node_context_by_type=new Map,this._plugin_name_by_operation_context_by_type=new Map}register(t){this._current_plugin=t,this._plugins_by_name.set(t.name(),t),t.init(this.poly),this._current_plugin=void 0}pluginByName(t){return this._plugins_by_name.get(t)}registerNode(t){if(!this._current_plugin)return;const e=t.context(),n=t.type();let i=this._plugin_name_by_node_context_by_type.get(e);i||(i=new Map,this._plugin_name_by_node_context_by_type.set(e,i)),i.set(n,this._current_plugin.name())}registerOperation(t){if(!this._current_plugin)return;const e=t.context(),n=t.type();let i=this._plugin_name_by_operation_context_by_type.get(e);i||(i=new Map,this._plugin_name_by_operation_context_by_type.set(e,i)),i.set(n,this._current_plugin.name())}toJson(){const t={plugins:{},nodes:{},operations:{}};return this._plugins_by_name.forEach(((e,n)=>{t.plugins[n]=e.toJSON()})),this._plugin_name_by_node_context_by_type.forEach(((e,n)=>{t.nodes[n]={},e.forEach(((e,i)=>{t.nodes[n][i]=e}))})),this._plugin_name_by_operation_context_by_type.forEach(((e,n)=>{t.operations[n]={},e.forEach(((e,i)=>{t.operations[n][i]=e}))})),t}}class Kn{constructor(t){this._camera_types=[]}register(t){const e=t.type();this._camera_types.includes(e)||this._camera_types.push(e)}registeredTypes(){return this._camera_types}}var ti=n(86);class ei{constructor(){this._blobUrlsByStoredUrl=new Map,this._blobsByStoredUrl=new Map,this._blobDataByNodeId=new Map,this._globalBlobsByStoredUrl=new Map}registerBlobUrl(t){li.playerMode()&&this._blobUrlsByStoredUrl.set(t.storedUrl,t.blobUrl)}deregisterUrl(t){this._blobUrlsByStoredUrl.delete(t)}blobUrl(t){return this._blobUrlsByStoredUrl.get(t)}clear(){this._blobUrlsByStoredUrl.clear(),this._blobsByStoredUrl.clear(),this._blobDataByNodeId.clear()}_clearBlobForNode(t){const e=this._blobDataByNodeId.get(t.graphNodeId());e&&(this._blobsByStoredUrl.delete(e.storedUrl),this._blobUrlsByStoredUrl.delete(e.storedUrl)),this._blobDataByNodeId.delete(t.graphNodeId())}_assignBlobToNode(t,e){this._clearBlobForNode(t),this._blobDataByNodeId.set(t.graphNodeId(),{storedUrl:e.storedUrl,fullUrl:e.fullUrl})}async fetchBlobGlobal(t){if(li.playerMode())return{};try{if(this._blobUrlsByStoredUrl.get(t.storedUrl))return{};const e=li.assetUrls.remapedUrl(t.fullUrl),n=await fetch(e||t.fullUrl);if(n.ok){const e=await n.blob();return this._blobsByStoredUrl.set(t.storedUrl,e),this._blobUrlsByStoredUrl.set(t.storedUrl,this.createBlobUrl(e)),this._globalBlobsByStoredUrl.set(t.storedUrl,e),{blobData:{storedUrl:t.storedUrl,fullUrl:t.fullUrl}}}return{error:`failed to fetch ${t.fullUrl}`}}catch(e){return{error:`failed to fetch ${t.fullUrl}`}}}async fetchBlobForNode(t){if(li.playerMode())return{};try{if(this._blobUrlsByStoredUrl.get(t.storedUrl))return{};const e=li.assetUrls.remapedUrl(t.fullUrl),n=await fetch(e||t.fullUrl);if(n.ok){const e=await n.blob();return this._blobsByStoredUrl.set(t.storedUrl,e),this._blobUrlsByStoredUrl.set(t.storedUrl,this.createBlobUrl(e)),this._scene=t.node.scene(),this._assignBlobToNode(t.node,{storedUrl:t.storedUrl,fullUrl:t.fullUrl}),{blobData:{storedUrl:t.storedUrl,fullUrl:t.fullUrl}}}return{error:`failed to fetch ${t.fullUrl}`}}catch(e){return{error:`failed to fetch ${t.fullUrl}`}}}forEachBlob(t){this._blobDataByNodeId.forEach(((e,n)=>{if(this._scene){if(this._scene.graph.nodeFromId(n)){const{storedUrl:n}=e,i=this._blobsByStoredUrl.get(n);i&&t(i,n)}}}));let e=[];const n=new Map;this._globalBlobsByStoredUrl.forEach(((t,i)=>{e.push(i),n.set(i,t)})),e=e.sort(),e.forEach((e=>{const n=this._globalBlobsByStoredUrl.get(e);n&&t(n,e)}))}createBlobUrl(t){return Object(ti.a)(t)}}class ni{setMap(t){this._map=t}remapedUrl(t){if(!this._map)return;const e=t.split(\\\\\\\"?\\\\\\\"),n=e[0],i=e[1],s=this._map[n];return s?i?`${s}?${i}`:s:void 0}}var ii=n(91),si=n(83);class ri{markAsLoaded(t,e){this._sceneJsonImporterContructor=e,t()}load(t){if(!this._sceneJsonImporterContructor)return;const e=[];t.forEach(((t,n)=>{e.push(n)}));for(let n of e){const e=t.get(n);e&&(this._loadElement(n,e,this._sceneJsonImporterContructor),t.delete(n))}}async _loadElement(t,e,n){const{sceneData:i,assetsManifest:s,unzippedData:r}=e,o=Object.keys(s);for(let t of o){const e=r[`assets/${s[t]}`];if(!e)return void console.error(t,e);const n=new Blob([e]),i={storedUrl:t,blobUrl:li.blobs.createBlobUrl(n)};li.blobs.registerBlobUrl(i)}li.setPlayerMode(!0),li.libs.setRoot(null);const a=`${Math.random()}`.replace(\\\\\\\".\\\\\\\",\\\\\\\"_\\\\\\\"),l={Poly:`___POLY_polyConfig_configurePolygonjs_${a}`,scriptElementId:`___POLY_polyConfig_scriptElement_${a}`,loadSceneArgs:`___POLY_polyConfig_loadSceneArgs_${a}`};window[l.Poly]=li;const c={method:this._loadScene.bind(this),element:t,sceneData:i,sceneJsonImporterContructor:n};window[l.loadSceneArgs]=c;this._loadPolyConfig(l,r)||this._loadScene(t,i,n)}_loadPolyConfig(t,e){const n=e[si.a.POLY_CONFIG];if(!n)return!1;const i=this._createJsBlob(n,\\\\\\\"polyConfig\\\\\\\");let s=document.getElementById(t.scriptElementId);const r=[];return r.push(`import {configurePolygonjs, configureScene} from '${i}';`),r.push(`configurePolygonjs(window.${t.Poly});`),r.push(`window.${t.loadSceneArgs}.method(window.${t.loadSceneArgs}.element, window.${t.loadSceneArgs}.sceneData, window.${t.loadSceneArgs}.sceneJsonImporterContructor, configureScene);`),r.push(`delete window.${t.loadSceneArgs};`),s||(s=document.createElement(\\\\\\\"script\\\\\\\"),s.setAttribute(\\\\\\\"type\\\\\\\",\\\\\\\"module\\\\\\\"),s.text=r.join(\\\\\\\"\\\\n\\\\\\\"),document.body.append(s)),!0}async _loadScene(t,e,n,i){this._fadeOutPoster(t);const s=new n(e),r=await s.scene();i&&i(r);const o=r.mainCameraNode();if(!o)return void console.warn(\\\\\\\"no master camera found\\\\\\\");const a=o.createViewer(t);r.play(),t.scene=r,t.viewer=a}_fadeOutPoster(t){const e=t.firstElementChild;e&&(e.style.pointerEvents=\\\\\\\"none\\\\\\\",ii.a.fadeOut(e).then((()=>{var t;null===(t=e.parentElement)||void 0===t||t.removeChild(e)})))}_createJsBlob(t,e){const n=new Blob([t]),i=new File([n],`${e}.js`,{type:\\\\\\\"application/javascript\\\\\\\"});return Object(ti.a)(i)}}class oi{setPerformanceManager(t){this._performanceManager=t}performanceManager(){return this._performanceManager||window.performance}}class ai{constructor(){this.renderersController=new Wn,this.nodesRegister=new Xn(this),this.operationsRegister=new Yn(this),this.expressionsRegister=new $n,this.modulesRegister=new Jn,this.assemblersRegister=new Zn,this.pluginsRegister=new Qn(this),this.camerasRegister=new Kn(this),this.blobs=new ei,this.assetUrls=new ni,this.selfContainedScenesLoader=new ri,this.performance=new oi,this.scenesByUuid={},this._player_mode=!0,this._logger=null}static _instance_(){if(window.__POLYGONJS_POLY_INSTANCE__)return window.__POLYGONJS_POLY_INSTANCE__;{const t=new ai;return window.__POLYGONJS_POLY_INSTANCE__=t,window.__POLYGONJS_POLY_INSTANCE__}}setPlayerMode(t){this._player_mode=t}playerMode(){return this._player_mode}registerNode(t,e,n){this.nodesRegister.register(t,e,n)}registerOperation(t){this.operationsRegister.register(t)}registerCamera(t){this.camerasRegister.register(t)}registerPlugin(t){this.pluginsRegister.register(t)}registeredNodes(t,e){return this.nodesRegister.registeredNodes(t,e)}registeredOperation(t,e){return this.operationsRegister.registeredOperation(t,e)}registeredCameraTypes(){return this.camerasRegister.registeredTypes()}inWorkerThread(){return!1}desktopController(){}get libs(){return this._libs_controller=this._libs_controller||new qn}setEnv(t){this._env=t}env(){return this._env}setLogger(t){this._logger=t}log(t,...e){var n;null===(n=this._logger)||void 0===n||n.log(t,...e)}warn(t,...e){var n;null===(n=this._logger)||void 0===n||n.warn(t,...e)}error(t,...e){var n;null===(n=this._logger)||void 0===n||n.error(t,...e)}}const li=ai._instance_();class ci{constructor(){this._started=!1,this._start_time=0,this._previous_timestamp=0,this._nodes_cook_data={},this._durations_by_name={},this._durations_count_by_name={}}profile(t,e){const n=li.performance.performanceManager(),i=n.now();e();const s=n.now()-i;console.log(`${t}: ${s}`)}start(){if(!this._started){this.reset(),this._started=!0;const t=li.performance.performanceManager();this._start_time=t.now(),this._nodes_cook_data={},this._previous_timestamp=this._start_time}}stop(){this.reset()}reset(){this._started=!1,this._start_time=null,this._durations_by_name={},this._durations_count_by_name={},this._nodes_cook_data={}}started(){return this._started}record_node_cook_data(t,e){const n=t.graphNodeId();null==this._nodes_cook_data[n]&&(this._nodes_cook_data[n]=new c(t)),this._nodes_cook_data[n].update_cook_data(e)}record(t){this.started()||this.start();const e=performance.now();return null==this._durations_by_name[t]&&(this._durations_by_name[t]=0),this._durations_by_name[t]+=e-this._previous_timestamp,null==this._durations_count_by_name[t]&&(this._durations_count_by_name[t]=0),this._durations_count_by_name[t]+=1,this._previous_timestamp=e}print(){this.print_node_cook_data(),this.print_recordings()}print_node_cook_data(){let t=Object.values(this._nodes_cook_data);t=f.sortBy(t,(t=>t.total_cook_time()));const e=t.map((t=>t.print_object()));console.log(\\\\\\\"--------------- NODES COOK TIME -----------\\\\\\\");const n=[],i=f.sortBy(e,(t=>-t.total_cook_time));for(let t of i)n.push(t);return console.table(n),e}print_recordings(){const t=b.clone(this._durations_by_name),e=b.clone(this._durations_count_by_name),n=[],i={};for(let e of Object.keys(t)){const s=t[e];n.push(s),null==i[s]&&(i[s]=[]),i[s].push(e)}n.sort(((t,e)=>t-e));const s=f.uniq(n);console.log(\\\\\\\"--------------- PERF RECORDINGS -----------\\\\\\\");const r=[];for(let t of s){const n=i[t];for(let i of n){const n=e[i],s={duration:t,name:i,count:n,duration_per_iteration:t/n};r.push(s)}}return console.table(r),r}}class hi{constructor(t){this.scene=t}setListener(t){this._events_listener?console.warn(\\\\\\\"scene already has a listener\\\\\\\"):(this._events_listener=t,this.run_on_add_listener_callbacks())}onAddListener(t){this._events_listener?t():(this._on_add_listener_callbacks=this._on_add_listener_callbacks||[],this._on_add_listener_callbacks.push(t))}run_on_add_listener_callbacks(){if(this._on_add_listener_callbacks){let t;for(;t=this._on_add_listener_callbacks.pop();)t();this._on_add_listener_callbacks=void 0}}get eventsListener(){return this._events_listener}dispatch(t,e,n){var i;null===(i=this._events_listener)||void 0===i||i.process_events(t,e,n)}emitAllowed(){return null!=this._events_listener&&this.scene.loadingController.loaded()&&this.scene.loadingController.autoUpdating()}}class ui{constructor(){this._params_by_id=new Map}registerParam(t){this._params_by_id.set(t.graphNodeId(),t)}deregisterParam(t){this._params_by_id.delete(t.graphNodeId())}regenerateReferringExpressions(t){t.nameController.graph_node.setSuccessorsDirty(t)}}class di{constructor(t){this.scene=t,this._lifecycle_on_create_allowed=!0}onCreateHookAllowed(){return this.scene.loadingController.loaded()&&this._lifecycle_on_create_allowed}onCreatePrevent(t){this._lifecycle_on_create_allowed=!1,t(),this._lifecycle_on_create_allowed=!0}}class pi{constructor(t){this.dispatcher=t,this._nodes_by_graph_node_id=new Map,this._require_canvas_event_listeners=!1,this._activeEventDatas=[]}registerNode(t){this._nodes_by_graph_node_id.set(t.graphNodeId(),t),this.updateViewerEventListeners()}unregisterNode(t){this._nodes_by_graph_node_id.delete(t.graphNodeId()),this.updateViewerEventListeners()}processEvent(t){0!=this._activeEventDatas.length&&this._nodes_by_graph_node_id.forEach((e=>e.processEvent(t)))}updateViewerEventListeners(){this._update_active_event_types(),this._require_canvas_event_listeners&&this.dispatcher.scene.viewersRegister.traverseViewers((t=>{t.eventsController.updateEvents(this)}))}activeEventDatas(){return this._activeEventDatas}_update_active_event_types(){const t=new Map;this._nodes_by_graph_node_id.forEach((e=>{if(e.parent()){const n=e.activeEventDatas();for(let e of n)t.set(e,!0)}})),this._activeEventDatas=[],t.forEach(((t,e)=>{this._activeEventDatas.push(e)}))}}var _i;!function(t){t.LOADED=\\\\\\\"sceneLoaded\\\\\\\",t.PLAY=\\\\\\\"play\\\\\\\",t.PAUSE=\\\\\\\"pause\\\\\\\",t.TICK=\\\\\\\"tick\\\\\\\"}(_i||(_i={}));const mi=[_i.LOADED,_i.PLAY,_i.PAUSE,_i.TICK];class fi extends pi{type(){return\\\\\\\"scene\\\\\\\"}acceptedEventTypes(){return mi.map((t=>`${t}`))}}class gi{constructor(t){this.scene=t,this._loading_state=!1,this._auto_updating=!0,this._first_object_loaded=!1}get LOADED_EVENT_CONTEXT(){return this._LOADED_EVENT_CONTEXT=this._LOADED_EVENT_CONTEXT||{event:new Event(_i.LOADED)}}markAsLoading(){this._set_loading_state(!0)}async markAsLoaded(){this.scene.missingExpressionReferencesController.resolveMissingReferences(),await this._set_loading_state(!1),this.trigger_loaded_event()}trigger_loaded_event(){globalThis.Event&&this.scene.eventsDispatcher.sceneEventsController.processEvent(this.LOADED_EVENT_CONTEXT)}async _set_loading_state(t){this._loading_state=t,await this.set_auto_update(!this._loading_state)}isLoading(){return this._loading_state}loaded(){return!this._loading_state}autoUpdating(){return this._auto_updating}async set_auto_update(t){if(this._auto_updating!==t&&(this._auto_updating=t,this._auto_updating)){const t=this.scene.root();t&&await t.processQueue()}}on_first_object_loaded(){var t;if(!this._first_object_loaded){this._first_object_loaded=!0;const e=document.getElementById(\\\\\\\"scene_loading_container\\\\\\\");e&&(null===(t=e.parentElement)||void 0===t||t.removeChild(e))}}}const vi={EMPTY:\\\\\\\"\\\\\\\",UV:\\\\\\\"/COP/imageUv\\\\\\\",ENV_MAP:\\\\\\\"/COP/envMap\\\\\\\",CUBE_MAP:\\\\\\\"/COP/cubeCamera\\\\\\\"};class yi{constructor(t=\\\\\\\"\\\\\\\"){this._path=t,this._node=null}set_path(t){this._path=t}set_node(t){this._node=t}path(){return this._path}node(){return this._node}resolve(t){this._node=bi.findNode(t,this._path)}clone(){const t=new yi(this._path);return t.set_node(this._node),t}nodeWithContext(t,e){const n=this.node();if(!n)return void(null==e||e.set(`no node found at ${this.path()}`));const i=n.context();return i==t?n:void(null==e||e.set(`expected ${t} node, but got a ${i}`))}}class xi{constructor(t=\\\\\\\"\\\\\\\"){this._path=t,this._param=null}set_path(t){this._path=t}set_param(t){this._param=t}path(){return this._path}param(){return this._param}resolve(t){this._param=bi.findParam(t,this._path)}clone(){const t=new xi(this._path);return t.set_param(this._param),t}paramWithType(t,e){const n=this.param();if(n)return n.type()==t?n:void(null==e||e.set(`expected ${t} node, but got a ${n.type()}`));null==e||e.set(`no param found at ${this.path()}`)}}class bi{static split_parent_child(t){const e=t.split(bi.SEPARATOR).filter((t=>t.length>0)),n=e.pop();return{parent:e.join(bi.SEPARATOR),child:n}}static findNode(t,e,n){if(!t)return null;const i=e.split(bi.SEPARATOR).filter((t=>t.length>0)),s=i[0];let r=null;if(e[0]!==bi.SEPARATOR){switch(s){case bi.PARENT:null==n||n.add_path_element(s),r=t.parent();break;case bi.CURRENT:null==n||n.add_path_element(s),r=t;break;default:r=t.node(s),r&&(null==n||n.add_node(s,r))}if(null!=r&&i.length>1){const t=i.slice(1).join(bi.SEPARATOR);r=this.findNode(r,t,n)}return r}{const i=e.substr(1);r=this.findNode(t.root(),i,n)}return r}static findParam(t,e,n){if(!t)return null;const i=e.split(bi.SEPARATOR);if(1===i.length)return t.params.get(i[0]);{const e=i.slice(0,+(i.length-2)+1||void 0).join(bi.SEPARATOR),s=this.findNode(t,e,n);if(null!=s){const t=i[i.length-1],e=s.params.get(t);return n&&e&&n.add_node(t,e),e}return null}}static relativePath(t,e){const n=this.closestCommonParent(t,e);if(n){const i=this.distanceToParent(t,n);let s=\\\\\\\"\\\\\\\";if(i>0){let t=0;const e=[];for(;t++t.length>0)),o=e.path().split(bi.SEPARATOR).filter((t=>t.length>0)),a=[];let l=0;for(let t of o)r[l]||a.push(t),l++;return`${s}${a.join(bi.SEPARATOR)}`}return e.path()}static closestCommonParent(t,e){const n=this.parents(t).reverse().concat([t]),i=this.parents(e).reverse().concat([e]),s=Math.min(n.length,i.length);let r=null;for(let t=0;t{for(let n of e)this._is_reference_resolvable(n)&&t.push(n)}));for(let e of t)e.resolveMissingDependencies()}_is_reference_resolvable(t){const e=t.absolutePath();if(e){if(this.scene.node(e))return!0;{const t=bi.split_parent_child(e);if(t.child){const e=this.scene.node(t.parent);if(e){if(e.params.get(t.child))return!0}}}}}checkForMissingReferences(t){this._checkForMissingReferencesForNode(t);for(let e of t.params.all)this._checkForMissingReferencesForParam(e)}_checkForMissingReferencesForNode(t){const e=t.graphNodeId();this.references.forEach(((n,i)=>{let s=!1;for(let e of n)e.matchesPath(t.path())&&(s=!0,e.resolveMissingDependencies());s&&this.references.delete(e)}))}_checkForMissingReferencesForParam(t){const e=t.graphNodeId();this.references.forEach(((n,i)=>{let s=!1;for(let e of n)e.matchesPath(t.path())&&(s=!0,e.resolveMissingDependencies());s&&this.references.delete(e)}))}}class Ai{constructor(t){this.node=t,this._dirty_count=0,this._dirty=!0}dispose(){this._cached_successors=void 0,this._post_dirty_hooks=void 0,this._post_dirty_hook_names=void 0}isDirty(){return!0===this._dirty}dirtyTimestamp(){return this._dirty_timestamp}dirtyCount(){return this._dirty_count}addPostDirtyHook(t,e){this._post_dirty_hook_names=this._post_dirty_hook_names||[],this._post_dirty_hooks=this._post_dirty_hooks||[],this._post_dirty_hook_names.includes(t)?console.warn(`hook with name ${t} already exists`,this.node):(this._post_dirty_hook_names.push(t),this._post_dirty_hooks.push(e))}removePostDirtyHook(t){if(this._post_dirty_hook_names&&this._post_dirty_hooks){const e=this._post_dirty_hook_names.indexOf(t);e>=0&&(this._post_dirty_hook_names.splice(e,1),this._post_dirty_hooks.splice(e,1))}}hasHook(t){return!!this._post_dirty_hook_names&&this._post_dirty_hook_names.includes(t)}removeDirtyState(){this._dirty=!1}setForbiddenTriggerNodes(t){this._forbidden_trigger_nodes=t.map((t=>t.graphNodeId()))}setDirty(t,e){if(null==e&&(e=!0),t&&this._forbidden_trigger_nodes&&this._forbidden_trigger_nodes.includes(t.graphNodeId()))return;null==t&&(t=this.node),this._dirty=!0;const n=li.performance.performanceManager();this._dirty_timestamp=n.now(),this._dirty_count+=1,this.runPostDirtyHooks(t),!0===e&&this.setSuccessorsDirty(t)}runPostDirtyHooks(t){if(this._post_dirty_hooks){const e=this.node.scene().cooker;if(e.blocked)e.enqueue(this.node,t);else for(let e of this._post_dirty_hooks)e(t)}}setSuccessorsDirty(t){this._cached_successors=this._cached_successors||this.node.graphAllSuccessors();for(let e of this._cached_successors)e.dirtyController.setDirty(t,false)}clearSuccessorsCache(){this._cached_successors=void 0}clearSuccessorsCacheWithPredecessors(){this.clearSuccessorsCache();for(let t of this.node.graphAllPredecessors())t.dirtyController.clearSuccessorsCache()}}class Mi{constructor(t,e){this._scene=t,this._name=e,this._dirty_controller=new Ai(this),this._graph_node_id=t.graph.nextId(),t.graph.addNode(this),this._graph=t.graph}dispose(){this._dirty_controller.dispose(),this.graphRemove()}name(){return this._name}setName(t){this._name=t}scene(){return this._scene}graphNodeId(){return this._graph_node_id}get dirtyController(){return this._dirty_controller}setDirty(t){t=t||this,this._dirty_controller.setDirty(t)}setSuccessorsDirty(t){this._dirty_controller.setSuccessorsDirty(t)}removeDirtyState(){this._dirty_controller.removeDirtyState()}isDirty(){return this._dirty_controller.isDirty()}addPostDirtyHook(t,e){this._dirty_controller.addPostDirtyHook(t,e)}graphRemove(){this._graph.removeNode(this)}addGraphInput(t,e=!0){return this._graph.connect(t,this,e)}removeGraphInput(t){this._graph.disconnect(t,this)}graphDisconnectPredecessors(){this._graph.disconnectPredecessors(this)}graphDisconnectSuccessors(){this._graph.disconnectSuccessors(this)}graphPredecessorIds(){return this._graph.predecessorIds(this._graph_node_id)||[]}graphPredecessors(){return this._graph.predecessors(this)}graphSuccessors(){return this._graph.successors(this)}graphAllPredecessors(){return this._graph.allPredecessors(this)}graphAllSuccessors(){return this._graph.allSuccessors(this)}}var Ei;!function(t){t.CREATED=\\\\\\\"node_created\\\\\\\",t.DELETED=\\\\\\\"node_deleted\\\\\\\",t.NAME_UPDATED=\\\\\\\"node_name_update\\\\\\\",t.OVERRIDE_CLONABLE_STATE_UPDATE=\\\\\\\"node_override_clonable_state_update\\\\\\\",t.NAMED_OUTPUTS_UPDATED=\\\\\\\"node_named_outputs_updated\\\\\\\",t.NAMED_INPUTS_UPDATED=\\\\\\\"node_named_inputs_updated\\\\\\\",t.INPUTS_UPDATED=\\\\\\\"node_inputs_updated\\\\\\\",t.PARAMS_UPDATED=\\\\\\\"node_params_updated\\\\\\\",t.UI_DATA_POSITION_UPDATED=\\\\\\\"node_ui_data_position_updated\\\\\\\",t.UI_DATA_COMMENT_UPDATED=\\\\\\\"node_ui_data_comment_updated\\\\\\\",t.ERROR_UPDATED=\\\\\\\"node_error_updated\\\\\\\",t.FLAG_BYPASS_UPDATED=\\\\\\\"bypass_flag_updated\\\\\\\",t.FLAG_DISPLAY_UPDATED=\\\\\\\"display_flag_updated\\\\\\\",t.FLAG_OPTIMIZE_UPDATED=\\\\\\\"optimize_flag_updated\\\\\\\",t.SELECTION_UPDATED=\\\\\\\"selection_updated\\\\\\\"}(Ei||(Ei={}));class Si{constructor(t,e=0,n=0){this.node=t,this._position=new d.a,this._width=50,this._color=new D.a(.75,.75,.75),this._layout_vertical=!0,this._json={x:0,y:0},this._position.x=e,this._position.y=n}setComment(t){this._comment=t,this.node.emit(Ei.UI_DATA_COMMENT_UPDATED)}comment(){return this._comment}setColor(t){this._color=t}color(){return this._color}setLayoutHorizontal(){this._layout_vertical=!1}isLayoutVertical(){return this._layout_vertical}copy(t){this._position.copy(t.position()),this._color.copy(t.color())}position(){return this._position}setPosition(t,e=0){if(m.isNumber(t)){const n=t;this._position.set(n,e)}else this._position.copy(t);this.node.emit(Ei.UI_DATA_POSITION_UPDATED)}translate(t,e=!1){this._position.add(t),e&&(this._position.x=Math.round(this._position.x),this._position.y=Math.round(this._position.y)),this.node.emit(Ei.UI_DATA_POSITION_UPDATED)}toJSON(){return this._json.x=this._position.x,this._json.y=this._position.y,this._json.comment=this._comment,this._json}}class Ci{constructor(t){this.node=t,this._state=!0,this._hooks=null}onUpdate(t){this._hooks=this._hooks||[],this._hooks.push(t)}_on_update(){}set(t){this._state!=t&&(this._state=t,this._on_update(),this.runHooks())}active(){return this._state}toggle(){this.set(!this._state)}runHooks(){if(this._hooks)for(let t of this._hooks)t()}}class Ni extends Ci{constructor(){super(...arguments),this._state=!1}_on_update(){this.node.emit(Ei.FLAG_BYPASS_UPDATED),this.node.setDirty()}}class Li extends Ci{_on_update(){this.node.emit(Ei.FLAG_DISPLAY_UPDATED)}}class Oi extends Ci{constructor(){super(...arguments),this._state=!1}_on_update(){this.node.emit(Ei.FLAG_OPTIMIZE_UPDATED)}}class Pi{constructor(t){this.node=t}hasDisplay(){return!1}hasBypass(){return!1}hasOptimize(){return!1}}function Ri(t){return class extends t{constructor(){super(...arguments),this.display=new Li(this.node)}hasDisplay(){return!0}}}function Ii(t){return class extends t{constructor(){super(...arguments),this.bypass=new Ni(this.node)}hasBypass(){return!0}}}function Fi(t){return class extends t{constructor(){super(...arguments),this.optimize=new Oi(this.node)}hasOptimize(){return!0}}}class Di extends(Ri(Pi)){}class Bi extends(Ii(Pi)){}class zi extends(Ii(Ri(Pi))){}class ki extends(Fi(Ii(Pi))){}class Ui extends(Fi(Ii(Ri(Pi)))){}class Gi{constructor(t){this.node=t}}class Vi extends Gi{active(){return this.paramsTimeDependent()||this.inputsTimeDependent()}paramsTimeDependent(){const t=this.node.params.names;for(let e of t){const t=this.node.params.get(e);if(t&&t.states.timeDependent.active())return!0}return!1}inputsTimeDependent(){const t=this.node.io.inputs.inputs();for(let e of t)if(e&&e.states.timeDependent.active())return!0;return!1}forceTimeDependent(){const t=this.node.graphPredecessors().map((t=>t.graphNodeId())),e=this.node.scene().timeController.graphNode;t.includes(e.graphNodeId())||this.node.addGraphInput(e,!1)}unforceTimeDependent(){const t=this.node.scene().timeController.graphNode;this.node.removeGraphInput(t)}}class Hi extends Gi{set(t){this._message!=t&&(t&&li.error(`[${this.node.path()}] error: '${t}'`),this._message=t,this.onUpdate())}message(){return this._message}clear(){this.set(void 0)}active(){return null!=this._message}onUpdate(){null!=this._message&&this.node._setContainer(null,`from error '${this._message}'`),this.node.emit(Ei.ERROR_UPDATED)}}class ji{constructor(t){this.node=t,this.timeDependent=new Vi(this.node),this.error=new Hi(this.node)}}class Wi{constructor(t){this.node=t,this._graph_node=new Mi(t.scene(),\\\\\\\"node_name_controller\\\\\\\")}dispose(){this._graph_node.dispose(),this._on_set_name_hooks=void 0,this._on_set_fullPath_hooks=void 0}get graph_node(){return this._graph_node}static base_name(t){let e=t.type();const n=e[e.length-1];return m.isNaN(parseInt(n))||(e+=\\\\\\\"_\\\\\\\"),`${e}1`}request_name_to_parent(t){const e=this.node.parent();e&&e.childrenAllowed()&&e.childrenController?e.childrenController.set_child_name(this.node,t):console.warn(\\\\\\\"request_name_to_parent failed, no parent found\\\\\\\")}setName(t){t!=this.node.name()&&this.request_name_to_parent(t)}update_name_from_parent(t){var e;if(this.node._set_core_name(t),this.post_setName(),this.run_post_set_fullPath_hooks(),this.node.childrenAllowed()){const t=null===(e=this.node.childrenController)||void 0===e?void 0:e.children();if(t)for(let e of t)e.nameController.run_post_set_fullPath_hooks()}this.node.lifecycle.creationCompleted()&&(this.node.scene().missingExpressionReferencesController.checkForMissingReferences(this.node),this.node.scene().expressionsController.regenerateReferringExpressions(this.node)),this.node.scene().referencesController.notifyNameUpdated(this.node),this.node.emit(Ei.NAME_UPDATED)}add_post_set_name_hook(t){this._on_set_name_hooks=this._on_set_name_hooks||[],this._on_set_name_hooks.push(t)}add_post_set_fullPath_hook(t){this._on_set_fullPath_hooks=this._on_set_fullPath_hooks||[],this._on_set_fullPath_hooks.push(t)}post_setName(){if(this._on_set_name_hooks)for(let t of this._on_set_name_hooks)t()}run_post_set_fullPath_hooks(){if(this._on_set_fullPath_hooks)for(let t of this._on_set_fullPath_hooks)t()}}class qi{constructor(t){this.node=t,this._parent=null}parent(){return this._parent}setParent(t){t!=this.node.parentController.parent()&&(this._parent=t,this._parent&&this.node.nameController.request_name_to_parent(Wi.base_name(this.node)))}firstAncestorWithContext(t){return this._parent?this._parent.context()==t?this._parent:this._parent.parentController.firstAncestorWithContext(t):null}path(t){const e=bi.SEPARATOR;if(null!=this._parent){if(this._parent==t)return this.node.name();{const n=this._parent.path(t);return n===e?n+this.node.name():n+e+this.node.name()}}return e}onSetParent(){if(this._on_set_parent_hooks)for(let t of this._on_set_parent_hooks)t()}findNode(t){if(null==t)return null;if(t==bi.CURRENT||t==bi.CURRENT_WITH_SLASH)return this.node;if(t==bi.PARENT||t==bi.PARENT_WITH_SLASH)return this.node.parent();const e=bi.SEPARATOR;if(t===e)return this.node.scene().root();if(t[0]===e)return t=t.substring(1,t.length),this.node.scene().root().node(t);if(t.split){const n=t.split(e);if(1===n.length){const t=n[0];return this.node.childrenController?this.node.childrenController.child_by_name(t):null}return bi.findNode(this.node,t)}return console.error(\\\\\\\"unexpected path given:\\\\\\\",t),null}}const Xi=/[, ]/,Yi=/\\\\d+$/,$i=/^0+/,Ji=/,| /,Zi=/^-?\\\\d+\\\\.?\\\\d*$/;var Qi,Ki,ts,es,ns,is;!function(t){t.TRUE=\\\\\\\"true\\\\\\\",t.FALSE=\\\\\\\"false\\\\\\\"}(Qi||(Qi={}));class ss{static isBoolean(t){return t==Qi.TRUE||t==Qi.FALSE}static toBoolean(t){return t==Qi.TRUE}static isNumber(t){return Zi.test(t)}static tailDigits(t){const e=t.match(Yi);return e?parseInt(e[0]):0}static increment(t){const e=t.match(Yi);if(e){let n=e[0],i=\\\\\\\"\\\\\\\";const s=n.match($i);s&&(i=s[0]);const r=parseInt(n);0==r&&i.length>0&&\\\\\\\"0\\\\\\\"==i[i.length-1]&&(i=i.slice(0,-1));return`${t.substring(0,t.length-e[0].length)}${i}${r+1}`}return`${t}1`}static pluralize(t){return\\\\\\\"s\\\\\\\"!==t[t.length-1]?`${t}s`:t}static camelCase(t){const e=t.replace(/_/g,\\\\\\\" \\\\\\\").split(\\\\\\\" \\\\\\\");let n=\\\\\\\"\\\\\\\";for(let t=0;t0&&(i=this.upperFirst(i)),n+=i}return n}static upperFirst(t){return t[0].toUpperCase()+t.substr(1)}static titleize(t){return t.split(/\\\\s|_/g).map((t=>this.upperFirst(t))).join(\\\\\\\" \\\\\\\")}static precision(t,e=2){e=Math.max(e,0);const n=`${t}`.split(\\\\\\\".\\\\\\\");if(e<=0)return n[0];let i=n[1];if(void 0!==i)return i.length>e&&(i=i.substring(0,e)),i=i.padEnd(e,\\\\\\\"0\\\\\\\"),`${n[0]}.${i}`;{const n=`${t}.`,i=n.length+e;return n.padEnd(i,\\\\\\\"0\\\\\\\")}}static ensureFloat(t){const e=`${t}`;return e.indexOf(\\\\\\\".\\\\\\\")>=0?e:`${e}.0`}static ensureInteger(t){const e=`${t}`;return e.indexOf(\\\\\\\".\\\\\\\")>=0?e.split(\\\\\\\".\\\\\\\")[0]:e}static matchMask(t,e){if(\\\\\\\"*\\\\\\\"===e)return!0;if(t==e)return!0;const n=e.split(\\\\\\\" \\\\\\\");if(n.length>1){for(let e of n){if(this.matchMask(t,e))return!0}return!1}e=`^${e=e.split(\\\\\\\"*\\\\\\\").join(\\\\\\\".*\\\\\\\")}$`;return new RegExp(e).test(t)}static matchesOneMask(t,e){let n=!1;for(let i of e)ss.matchMask(t,i)&&(n=!0);return n}static attribNames(t){const e=t.split(Xi),n=new Set;for(let t of e)t=t.trim(),t.length>0&&n.add(t);const i=new Array(n.size);let s=0;return n.forEach((t=>{i[s]=t,s++})),i}static indices(t){const e=t.split(Ji);if(e.length>1){const t=e.flatMap((t=>this.indices(t)));return f.uniq(t).sort(((t,e)=>t-e))}{const t=e[0];if(t){const e=\\\\\\\"-\\\\\\\";if(t.indexOf(e)>0){const n=t.split(e);return f.range(parseInt(n[0]),parseInt(n[1])+1)}{const e=parseInt(t);return m.isNumber(e)?[e]:[]}}return[]}}static escapeLineBreaks(t){return t.replace(/(\\\\r\\\\n|\\\\n|\\\\r)/gm,\\\\\\\"\\\\\\\\n\\\\\\\")}static sanitizeName(t){return t=(t=t.replace(/[^A-Za-z0-9]/g,\\\\\\\"_\\\\\\\")).replace(/^[0-9]/,\\\\\\\"_\\\\\\\")}}class rs{constructor(t){this._node=t,this._node_ids=[],this._json=[]}node(){return this._node}nodes(){return this._node.scene().graph.nodesFromIds(this._node_ids)}contains(t){return this._node_ids.includes(t.graphNodeId())}equals(t){const e=t.map((t=>t.graphNodeId())).sort();return f.isEqual(e,this._node_ids)}clear(){this._node_ids=[],this.send_update_event()}set(t){this._node_ids=[],this.add(t)}add(t){const e=t.map((t=>t.graphNodeId()));this._node_ids=f.union(this._node_ids,e),this.send_update_event()}remove(t){const e=t.map((t=>t.graphNodeId()));this._node_ids=f.difference(this._node_ids,e),this.send_update_event()}send_update_event(){this._node.emit(Ei.SELECTION_UPDATED)}toJSON(){return this._json=this._json||[],this._json=this._node_ids.map((t=>t)),this._json}}!function(t){t.ALWAYS=\\\\\\\"always\\\\\\\",t.NEVER=\\\\\\\"never\\\\\\\",t.FROM_NODE=\\\\\\\"from_node\\\\\\\"}(Ki||(Ki={}));class os{static unreachable(t){throw new Error(\\\\\\\"Didn't expect to get here\\\\\\\")}}class as{constructor(t){this.inputs_controller=t,this._clone_required_states=[],this._overridden=!1}init_inputs_cloned_state(t){m.isArray(t)?this._cloned_states=t:this._cloned_state=t,this._update_clone_required_state()}override_cloned_state_allowed(){if(this._cloned_states)for(let t of this._cloned_states)if(t==Ki.FROM_NODE)return!0;return!!this._cloned_state&&this._cloned_state==Ki.FROM_NODE}clone_required_state(t){return this._clone_required_states[t]}clone_required_states(){return this._clone_required_states}_get_clone_required_state(t){const e=this._cloned_states;if(e){const n=e[t];if(null!=n)return this.clone_required_from_state(n)}return!this._cloned_state||this.clone_required_from_state(this._cloned_state)}clone_required_from_state(t){switch(t){case Ki.ALWAYS:return!0;case Ki.NEVER:return!1;case Ki.FROM_NODE:return!this._overridden}return os.unreachable(t)}override_cloned_state(t){this._overridden=t,this._update_clone_required_state()}overriden(){return this._overridden}_update_clone_required_state(){if(this._cloned_states){const t=[];for(let e=0;e=1:e;if(m.isString(e)){if(n){if(n instanceof yi)return n.set_path(e);if(n instanceof xi)return n.set_path(e)}return e}m.isArray(e)&&this.params[t].fromArray(e)}setInput(t,e){this._inputs=this._inputs||[],this._inputs[t]=e}inputs_count(){return this._inputs?this._inputs.length:0}inputsController(){return this._inputs_controller=this._inputs_controller||new ls(this)}_init_cloned_states(){const t=this.operation.constructor.INPUT_CLONED_STATE;this.inputsController().init_inputs_cloned_state(t)}input_clone_required(t){return!this._inputs_controller||this._inputs_controller.clone_required(t)}override_input_clone_state(t){this.inputsController().override_cloned_state(t)}cook(t){return this.operation.cook(t,this.params)}}{constructor(t,e,n){super(t,e,n),this.operation=t,this.name=e,this.init_params=n,this._inputs=[],this._current_input_index=0,this._dirty=!0}add_input(t){super.setInput(this._current_input_index,t),this.increment_input_index()}increment_input_index(){this._current_input_index++}current_input_index(){return this._current_input_index}setDirty(){if(!this._dirty){this._compute_result=void 0;for(let t=0;t{n[i]=t[e]}));for(let i=0;i=0&&(this._children_by_type[n].splice(t,1),0==this._children_by_type[n].length&&delete this._children_by_type[n])}this.remove_from_children_and_grandchildren_by_context(t)}add_to_children_and_grandchildren_by_context(t){var e;const n=t.graphNodeId(),i=t.context();this._children_and_grandchildren_by_context[i]=this._children_and_grandchildren_by_context[i]||[],this._children_and_grandchildren_by_context[i].includes(n)||this._children_and_grandchildren_by_context[i].push(n);const s=this.node.parent();s&&s.childrenAllowed()&&(null===(e=s.childrenController)||void 0===e||e.add_to_children_and_grandchildren_by_context(t))}remove_from_children_and_grandchildren_by_context(t){var e;const n=t.graphNodeId(),i=t.context();if(this._children_and_grandchildren_by_context[i]){const t=this._children_and_grandchildren_by_context[i].indexOf(n);t>=0&&(this._children_and_grandchildren_by_context[i].splice(t,1),0==this._children_and_grandchildren_by_context[i].length&&delete this._children_and_grandchildren_by_context[i])}const s=this.node.parent();s&&s.childrenAllowed()&&(null===(e=s.childrenController)||void 0===e||e.remove_from_children_and_grandchildren_by_context(t))}nodesByType(t){const e=this._children_by_type[t]||[],n=this.node.scene().graph,i=[];for(let t of e){const e=n.nodeFromId(t);e&&i.push(e)}return i}child_by_name(t){return this._children[t]}has_children_and_grandchildren_with_context(t){return null!=this._children_and_grandchildren_by_context[t]}children(){return Object.values(this._children)}children_names(){return Object.keys(this._children).sort()}traverse_children(t){var e;for(let n of this.children())t(n),null===(e=n.childrenController)||void 0===e||e.traverse_children(t)}}class us{constructor(t){this.node=t,this._creation_completed=!1}dispose(){this._on_child_add_hooks=void 0,this._on_child_remove_hooks=void 0,this._on_create_hooks=void 0,this._on_add_hooks=void 0,this._on_delete_hooks=void 0}setCreationCompleted(){this._creation_completed||(this._creation_completed=!0)}creationCompleted(){return this.node.scene().loadingController.loaded()&&this._creation_completed}add_on_child_add_hook(t){this._on_child_add_hooks=this._on_child_add_hooks||[],this._on_child_add_hooks.push(t)}run_on_child_add_hooks(t){this.execute_hooks_with_child_node(this._on_child_add_hooks,t)}add_on_child_remove_hook(t){this._on_child_remove_hooks=this._on_child_remove_hooks||[],this._on_child_remove_hooks.push(t)}run_on_child_remove_hooks(t){this.execute_hooks_with_child_node(this._on_child_remove_hooks,t)}add_on_create_hook(t){this._on_create_hooks=this._on_create_hooks||[],this._on_create_hooks.push(t)}run_on_create_hooks(){this.execute_hooks(this._on_create_hooks)}add_on_add_hook(t){this._on_add_hooks=this._on_add_hooks||[],this._on_add_hooks.push(t)}run_on_add_hooks(){this.execute_hooks(this._on_add_hooks)}add_delete_hook(t){this._on_delete_hooks=this._on_delete_hooks||[],this._on_delete_hooks.push(t)}run_on_delete_hooks(){this.execute_hooks(this._on_delete_hooks)}execute_hooks(t){if(t){let e;for(e of t)e()}}execute_hooks_with_child_node(t,e){if(t){let n;for(n of t)n(e)}}}!function(t){t.ANIM=\\\\\\\"anim\\\\\\\",t.COP=\\\\\\\"cop\\\\\\\",t.EVENT=\\\\\\\"event\\\\\\\",t.GL=\\\\\\\"gl\\\\\\\",t.JS=\\\\\\\"js\\\\\\\",t.MANAGER=\\\\\\\"manager\\\\\\\",t.MAT=\\\\\\\"mat\\\\\\\",t.OBJ=\\\\\\\"obj\\\\\\\",t.POST=\\\\\\\"post\\\\\\\",t.ROP=\\\\\\\"rop\\\\\\\",t.SOP=\\\\\\\"sop\\\\\\\"}(ts||(ts={})),function(t){t.ANIM=\\\\\\\"animationsNetwork\\\\\\\",t.COP=\\\\\\\"copNetwork\\\\\\\",t.EVENT=\\\\\\\"eventsNetwork\\\\\\\",t.MAT=\\\\\\\"materialsNetwork\\\\\\\",t.POST=\\\\\\\"postProcessNetwork\\\\\\\",t.ROP=\\\\\\\"renderersNetwork\\\\\\\"}(es||(es={})),function(t){t.INPUT=\\\\\\\"subnetInput\\\\\\\",t.OUTPUT=\\\\\\\"subnetOutput\\\\\\\"}(ns||(ns={})),function(t){t.PERSPECTIVE=\\\\\\\"perspectiveCamera\\\\\\\",t.ORTHOGRAPHIC=\\\\\\\"orthographicCamera\\\\\\\"}(is||(is={}));const ds=[is.ORTHOGRAPHIC,is.PERSPECTIVE];var ps,_s;!function(t){t.ATTRIBUTE=\\\\\\\"attribute\\\\\\\"}(ps||(ps={})),function(t){t.DEVICE_ORIENTATION=\\\\\\\"cameraDeviceOrientationControls\\\\\\\",t.MAP=\\\\\\\"cameraMapControls\\\\\\\",t.ORBIT=\\\\\\\"cameraOrbitControls\\\\\\\",t.FIRST_PERSON=\\\\\\\"firstPersonControls\\\\\\\",t.PLAYER=\\\\\\\"playerControls\\\\\\\",t.MOBILE_JOYSTICK=\\\\\\\"mobileJoystickControls\\\\\\\"}(_s||(_s={}));const ms=[_s.DEVICE_ORIENTATION,_s.MAP,_s.ORBIT,_s.FIRST_PERSON,_s.MOBILE_JOYSTICK];class fs{constructor(t){this._node=t}set_node(t){this._node=t}node(){return this._node}set_content(t){this._content=t,this._post_set_content()}has_content(){return null!=this._content}content(){return this._content}_post_set_content(){}coreContent(){return this._content}coreContentCloned(){return this._content}infos(){return[]}}var gs=n(69);class vs extends K.a{constructor(){super(),this.type=\\\\\\\"Scene\\\\\\\",this.background=null,this.environment=null,this.fog=null,this.overrideMaterial=null,this.autoUpdate=!0,\\\\\\\"undefined\\\\\\\"!=typeof __THREE_DEVTOOLS__&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent(\\\\\\\"observe\\\\\\\",{detail:this}))}copy(t,e){return super.copy(t,e),null!==t.background&&(this.background=t.background.clone()),null!==t.environment&&(this.environment=t.environment.clone()),null!==t.fog&&(this.fog=t.fog.clone()),null!==t.overrideMaterial&&(this.overrideMaterial=t.overrideMaterial.clone()),this.autoUpdate=t.autoUpdate,this.matrixAutoUpdate=t.matrixAutoUpdate,this}toJSON(t){const e=super.toJSON(t);return null!==this.fog&&(e.object.fog=this.fog.toJSON()),e}}vs.prototype.isScene=!0;var ys=n(49),xs=n(52),bs=n(42),ws=n(55),Ts=n(62),As=n(24),Ms=n(35);const Es=new p.a,Ss=new p.a;class Cs extends K.a{constructor(){super(),this._currentLevel=0,this.type=\\\\\\\"LOD\\\\\\\",Object.defineProperties(this,{levels:{enumerable:!0,value:[]},isLOD:{value:!0}}),this.autoUpdate=!0}copy(t){super.copy(t,!1);const e=t.levels;for(let t=0,n=e.length;t0){let n,i;for(n=1,i=e.length;n0){Es.setFromMatrixPosition(this.matrixWorld);const n=t.ray.origin.distanceTo(Es);this.getObjectForDistance(n).raycast(t,e)}}update(t){const e=this.levels;if(e.length>1){Es.setFromMatrixPosition(t.matrixWorld),Ss.setFromMatrixPosition(this.matrixWorld);const n=Es.distanceTo(Ss)/t.zoom;let i,s;for(e[0].object.visible=!0,i=1,s=e.length;i=e[i].distance;i++)e[i-1].object.visible=!1,e[i].object.visible=!0;for(this._currentLevel=i-1;in?n:t}static fit01(t,e,n){return this.fit(t,0,1,e,n)}static fit(t,e,n,i,s){return(t-e)/(n-e)*(s-i)+i}static blend(t,e,n){return(1-n)*t+n*e}static degrees_to_radians(t){return t*rr}static radians_to_degrees(t){return t/rr}static deg2rad(t){return this.degrees_to_radians(t)}static rad2deg(t){return this.radians_to_degrees(t)}static rand(t){return m.isNumber(t)?this.randFloat(t):this.randVec2(t)}static round(t,e){const n=t/e;return(t<0?Math.ceil(n):Math.floor(n))*e}static highest_even(t){return 2*Math.ceil(.5*t)}static randFloat(t,e=136574){return this._vec.x=t,this._vec.y=e,this.randVec2(this._vec)}static randVec2(t){const e=(12.9898*t.x+78.233*t.y)%Math.PI;return this.fract(43758.5453*Math.sin(e))}static geodesic_distance(t,e){var n=this.deg2rad(t.lat),i=this.deg2rad(e.lat),s=this.deg2rad(e.lat-t.lat),r=this.deg2rad(e.lng-t.lng),o=Math.sin(s/2)*Math.sin(s/2)+Math.cos(n)*Math.cos(i)*Math.sin(r/2)*Math.sin(r/2);return 6371e3*(2*Math.atan2(Math.sqrt(o),Math.sqrt(1-o)))}static expand_triangle(t,e){t.getMidpoint(this._triangle_mid),this._triangle_mid_to_corner.copy(t.a).sub(this._triangle_mid),this._triangle_mid_to_corner.normalize().multiplyScalar(e),t.a.add(this._triangle_mid_to_corner),this._triangle_mid_to_corner.copy(t.b).sub(this._triangle_mid),this._triangle_mid_to_corner.normalize().multiplyScalar(e),t.b.add(this._triangle_mid_to_corner),this._triangle_mid_to_corner.copy(t.c).sub(this._triangle_mid),this._triangle_mid_to_corner.normalize().multiplyScalar(e),t.c.add(this._triangle_mid_to_corner)}static nearestPower2(t){return Math.pow(2,Math.ceil(Math.log(t)/Math.log(2)))}}or.Easing=sr,or.fract=t=>t-Math.floor(t),or._vec={x:0,y:136574},or._triangle_mid=new p.a,or._triangle_mid_to_corner=new p.a;class ar{constructor(t,e){this._coreGeometry=t,this._index=e,this._geometry=this._coreGeometry.geometry()}index(){return this._index}points(){return this._points=this._points||this._get_points()}applyMatrix4(t){for(let e of this.points())e.applyMatrix4(t)}_get_points(){var t;const e=(null===(t=this._geometry.index)||void 0===t?void 0:t.array)||[],n=3*this._index;return[new Ks(this._coreGeometry,e[n+0]),new Ks(this._coreGeometry,e[n+1]),new Ks(this._coreGeometry,e[n+2])]}positions(){return this._positions=this._positions||this._getPositions()}_getPositions(){const t=this.points();return[t[0].position(),t[1].position(),t[2].position()]}triangle(){return this._triangle=this._triangle||this._get_triangle()}_get_triangle(){const t=this.positions();return new tr.a(t[0],t[1],t[2])}deltas(){return this._deltas=this._deltas||this._getDeltas()}_getDeltas(){const t=this.positions();return[t[1].clone().sub(t[0]),t[2].clone().sub(t[0])]}area(){return this.triangle().getArea()}center(t){const e=this.positions();return t.x=(e[0].x+e[1].x+e[2].x)/3,t.y=(e[0].y+e[1].y+e[2].y)/3,t.z=(e[0].z+e[1].z+e[2].z)/3,t}randomPosition(t){let e=[or.randFloat(t),or.randFloat(6541*t)];return e[0]+e[1]>1&&(e[0]=1-e[0],e[1]=1-e[1]),this.positions()[0].clone().add(this.deltas()[0].clone().multiplyScalar(e[0])).add(this.deltas()[1].clone().multiplyScalar(e[1]))}attribValueAtPosition(t,e){const n=new p.a;this.triangle().getBarycoord(e,n);const i=n.toArray(),s=this._geometry.attributes[t].itemSize,r=this.points().map((e=>e.attribValue(t)));let o,a,l=0;switch(s){case 1:a=0;for(let t of r)a+=t*i[l],l++;o=a;break;default:for(let t of r){const e=t.multiplyScalar(i[l]);a?a.add(e):a=e,l++}o=a}return o}static interpolatedValue(t,e,n,i){const s=[e.a,e.b,e.c],r=t.getAttribute(\\\\\\\"position\\\\\\\").array,o=s.map((t=>new p.a(r[3*t+0],r[3*t+1],r[3*t+2]))),a=i.itemSize,l=i.array;let c=[];switch(a){case 1:c=s.map((t=>l[t]));break;case 2:c=s.map((t=>new d.a(l[2*t+0],l[2*t+1])));break;case 3:c=s.map((t=>new p.a(l[3*t+0],l[3*t+1],l[3*t+2])))}const h=s.map(((t,e)=>n.distanceTo(o[e]))),u=f.sum([h[0]*h[1],h[0]*h[2],h[1]*h[2]]),_=[h[1]*h[2]/u,h[0]*h[2]/u,h[0]*h[1]/u];let m;switch(a){case 1:m=f.sum(s.map(((t,e)=>_[e]*c[e])));break;default:var g=s.map(((t,e)=>c[e].multiplyScalar(_[e])));m=null;for(let t of g)m?m.add(t):m=t}return m}}class lr{from_points(t){t=this._filter_points(t);const e=new S.a,n=new fr(e),i=t[0];if(null!=i){const s=i.geometry(),r=i.coreGeometry(),o={};for(let e=0;et.indexedAttribValue(i)))),r={};s.forEach(((t,e)=>r[t]=e)),n.userDataAttribs()[i]=s;const o=[];for(let e of t){const t=r[e.indexedAttribValue(i)];o.push(t)}e.setAttribute(i,new C.c(o,1))}else{const n=l[i].itemSize,s=new Array(t.length*n);switch(n){case 1:for(let e=0;enew fr(t))),n=e[0].indexedAttributeNames(),i={};for(let t of n){const n={},s=[];for(let i of e){const e=i.points();for(let i of e){s.push(i);const e=i.indexedAttribValue(t);null!=n[e]?n[e]:n[e]=Object.keys(n).length}}const r=Object.keys(n);for(let e of s){const i=n[e.indexedAttribValue(t)];e.setAttribIndex(t,i)}i[t]=r}const s=ur(t),r=new fr(s);return Object.keys(i).forEach((t=>{const e=i[t];r.setIndexedAttributeValues(t,e)})),s&&delete s.userData.mergedUserData,s}}const mr=\\\\\\\"indexed_attrib_values\\\\\\\";class fr{constructor(t){this._geometry=t}geometry(){return this._geometry}uuid(){return this._geometry.uuid}boundingBox(){return this._bounding_box=this._bounding_box||this._create_bounding_box()}_create_bounding_box(){if(this._geometry.computeBoundingBox(),this._geometry.boundingBox)return this._geometry.boundingBox}markAsInstance(){this._geometry.userData.isInstance=!0}static markedAsInstance(t){return!0===t.userData.isInstance}markedAsInstance(){return fr.markedAsInstance(this._geometry)}positionAttribName(){let t=\\\\\\\"position\\\\\\\";return this.markedAsInstance()&&(t=\\\\\\\"instancePosition\\\\\\\"),t}computeVertexNormals(){this._geometry.computeVertexNormals()}userDataAttribs(){return this._geometry.userData[mr]=this._geometry.userData[mr]||{}}indexedAttributeNames(){return Object.keys(this.userDataAttribs()||{})}userDataAttrib(t){return t=Xs.remapName(t),this.userDataAttribs()[t]}isAttribIndexed(t){return t=Xs.remapName(t),null!=this.userDataAttrib(t)}hasAttrib(t){return\\\\\\\"ptnum\\\\\\\"===t||(t=Xs.remapName(t),null!=this._geometry.attributes[t])}attribType(t){return this.isAttribIndexed(t)?zs.STRING:zs.NUMERIC}static attribNames(t){return Object.keys(t.attributes)}attribNames(){return fr.attribNames(this._geometry)}static attribNamesMatchingMask(t,e){const n=ss.attribNames(e),i=[];for(let e of this.attribNames(t))for(let t of n)ss.matchMask(e,t)&&i.push(e);return f.uniq(i)}attribSizes(){const t={};for(let e of this.attribNames())t[e]=this._geometry.attributes[e].itemSize;return t}attribSize(t){let e;return t=Xs.remapName(t),null!=(e=this._geometry.attributes[t])?e.itemSize:\\\\\\\"ptnum\\\\\\\"===t?1:0}setIndexedAttributeValues(t,e){this.userDataAttribs()[t]=e}setIndexedAttribute(t,e,n){this.setIndexedAttributeValues(t,e),this._geometry.setAttribute(t,new C.f(n,1))}addNumericAttrib(t,e=1,n=0){const i=[];let s=!1;if(m.isNumber(n)){for(let t=0;t1)if(m.isArray(n)){for(let t=0;tnew ar(this,t)))}}var gr;fr._mesh_builder=new class extends lr{_filter_points(t){var e;const n=t[0];if(n){const i=null===(e=n.geometry().getIndex())||void 0===e?void 0:e.array;if(i){const e={};for(let n of t)e[n.index()]=n;const n=[],s=i.length;let r,o,a;for(let t=0;t{};class yr{static node(t,e){return t.node(e.name)}static clone(t){const e=t.clone(),n=t.uniforms;return n&&(e.uniforms=I.clone(n)),e}static add_user_data_render_hook(t,e){t.userData.POLY_render_hook=e}static apply_render_hook(t,e){if(e.userData){const n=e.userData.POLY_render_hook;if(n)return void(t.onBeforeRender=(e,i,s,r,o,a)=>{n(e,i,s,r,o,a,t)})}t.onBeforeRender=vr}static applyCustomMaterials(t,e){const n=e;if(n.customMaterials)for(let e of Object.keys(n.customMaterials)){const i=e,s=n.customMaterials[i];s&&(t[i]=s,s.needsUpdate=!0)}}static assign_custom_uniforms(t,e,n){const i=t;if(i.customMaterials)for(let t of Object.keys(i.customMaterials)){const s=t,r=i.customMaterials[s];r&&(r.uniforms[e].value=n)}}static init_custom_material_uniforms(t,e,n){const i=t;if(i.customMaterials)for(let t of Object.keys(i.customMaterials)){const s=t,r=i.customMaterials[s];r&&(r.uniforms[e]=r.uniforms[e]||n)}}}const xr=\\\\\\\"name\\\\\\\";class br extends Ys{constructor(t,e){super(e),this._object=t,null==this._object.userData.attributes&&(this._object.userData.attributes={})}object(){return this._object}geometry(){return this._object.geometry}coreGeometry(){const t=this.geometry();return t?new fr(t):null}points(){var t;return(null===(t=this.coreGeometry())||void 0===t?void 0:t.points())||[]}pointsFromGroup(t){if(t){const e=ss.indices(t);if(e){const t=this.points();return e.map((e=>t[e]))}return[]}return this.points()}static isInGroup(t,e){const n=t.trim();if(0==n.length)return!0;const i=n.split(\\\\\\\"=\\\\\\\"),s=i[0];if(\\\\\\\"@\\\\\\\"==s[0]){const t=s.substr(1);return i[1]==this.attribValue(e,t)}return!1}computeVertexNormals(){var t;null===(t=this.coreGeometry())||void 0===t||t.computeVertexNormals()}static _convert_array_to_vector(t){switch(t.length){case 1:return t[0];case 2:return new d.a(t[0],t[1]);case 3:return new p.a(t[0],t[1],t[2]);case 4:return new _.a(t[0],t[1],t[2],t[3])}}static addAttribute(t,e,n){if(m.isArray(n)){if(!this._convert_array_to_vector(n)){const t=\\\\\\\"attribute_value invalid\\\\\\\";throw console.error(t,n),new Error(t)}}const i=n,s=t.userData;s.attributes=s.attributes||{},s.attributes[e]=i}addAttribute(t,e){br.addAttribute(this._object,t,e)}addNumericAttrib(t,e){this.addAttribute(t,e)}setAttribValue(t,e){this.addAttribute(t,e)}addNumericVertexAttrib(t,e,n){var i;null==n&&(n=Xs.default_value(e)),null===(i=this.coreGeometry())||void 0===i||i.addNumericAttrib(t,e,n)}attributeNames(){return Object.keys(this._object.userData.attributes)}attribNames(){return this.attributeNames()}hasAttrib(t){return this.attributeNames().includes(t)}renameAttrib(t,e){const n=this.attribValue(t);null!=n?(this.addAttribute(e,n),this.deleteAttribute(t)):console.warn(`attribute ${t} not found`)}deleteAttribute(t){delete this._object.userData.attributes[t]}static attribValue(t,e,n=0,i){if(\\\\\\\"ptnum\\\\\\\"===e)return n;if(t.userData&&t.userData.attributes){const n=t.userData.attributes[e];if(null==n){if(e==xr)return t.name}else if(m.isArray(n)&&i)return i.fromArray(n),i;return n}return e==xr?t.name:void 0}static stringAttribValue(t,e,n=0){const i=this.attribValue(t,e,n);if(null!=i)return m.isString(i)?i:`${i}`}attribValue(t,e){return br.attribValue(this._object,t,this._index,e)}stringAttribValue(t){return br.stringAttribValue(this._object,t,this._index)}name(){return this.attribValue(xr)}humanType(){return js.CONSTRUCTOR_NAMES_BY_CONSTRUCTOR_NAME[this._object.constructor.name]}attribTypes(){const t={};for(let e of this.attribNames()){const n=this.attribType(e);null!=n&&(t[e]=n)}return t}attribType(t){const e=this.attribValue(t);return m.isString(e)?zs.STRING:zs.NUMERIC}attribSizes(){const t={};for(let e of this.attribNames()){const n=this.attribSize(e);null!=n&&(t[e]=n)}return t}attribSize(t){const e=this.attribValue(t);return null==e?null:Xs.attribSizeFromValue(e)}clone(){return br.clone(this._object)}static clone(t){const e=t.clone();var n=new Map,i=new Map;return br.parallelTraverse(t,e,(function(t,e){n.set(e,t),i.set(t,e)})),e.traverse((function(e){const s=n.get(e),r=e;if(r.geometry){const t=s.geometry;r.geometry=fr.clone(t);const e=r.geometry;e.userData&&(e.userData=b.cloneDeep(t.userData))}if(r.material){r.material=s.material,yr.applyCustomMaterials(e,r.material);const t=r.material;null==t.color&&(t.color=new D.a(1,1,1))}t.userData&&(e.userData=b.cloneDeep(s.userData));const o=s;o.animations&&(e.animations=o.animations.map((t=>t.clone())));const a=e;if(a.isSkinnedMesh){var l=a,c=s,h=c.skeleton.bones;l.skeleton=c.skeleton.clone(),l.bindMatrix.copy(c.bindMatrix);const t=h.map((function(t){return i.get(t)}));l.skeleton.bones=t,l.bind(l.skeleton,l.bindMatrix)}})),e}static parallelTraverse(t,e,n){n(t,e);for(var i=0;i{const i=e.attributes[n];t[n]=i.itemSize})),t}objectAttributeSizesByName(){let t={};const e=this.firstCoreObject();if(e){const n=e.attribNames();for(let i of n){const n=e.attribSize(i);null!=n&&(t[i]=n)}}return t}pointAttributeTypesByName(){let t={};const e=this.firstGeometry();if(e){const n=new fr(e);Object.keys(e.attributes).forEach((e=>{t[e]=n.attribType(e)}))}return t}objectAttributeTypesByName(){let t={};const e=this.firstCoreObject();if(e)for(let n of e.attribNames())t[n]=e.attribType(n);return t}objectAttributeNames(){let t=[];const e=this.firstObject();return e&&(t=Object.keys(e.userData.attributes||{})),t}pointsCount(){return this._content?this._content.pointsCount():0}totalPointsCount(){return this._content?this._content.totalPointsCount():0}objectsData(){return this._content?this._content.objectsData():[]}boundingBox(t=!1){return this._content.boundingBox(t)}center(){return this._content.center()}size(){return this._content.size()}}};class Tr{constructor(t){this.node=t,this._callbacks=[],this._callbacks_tmp=[];const e=wr[t.context()];this._container=new e(this.node)}container(){return this._container}async compute(){var t,e;if(null===(e=null===(t=this.node.flags)||void 0===t?void 0:t.bypass)||void 0===e?void 0:e.active()){const t=await this.requestInputContainer(0)||this._container;return this.node.cookController.endCook(),t}return this.node.isDirty()?new Promise(((t,e)=>{this._callbacks.push(t),this.node.cookController.cookMain()})):this._container}async requestInputContainer(t){const e=this.node.io.inputs.input(t);return e?await e.compute():(this.node.states.error.set(`input ${t} required`),this.notifyRequesters(),null)}notifyRequesters(t){let e;for(this._callbacks_tmp=this._callbacks.slice(),this._callbacks.splice(0,this._callbacks.length),t||(t=this.node.containerController.container());e=this._callbacks_tmp.pop();)e(t);this.node.scene().cookController.removeNode(this.node)}}const Ar=li.performance.performanceManager();class Mr{constructor(t){this.cookController=t,this._inputs_start=0,this._params_start=0,this._cook_start=0,this._cooksCount=0,this._data={inputsTime:0,paramsTime:0,cookTime:0}}cooksCount(){return this._cooksCount}data2(){return this._data}active(){return this.cookController.performanceRecordStarted()}recordInputsStart(){this.active()&&(this._inputs_start=Ar.now())}recordInputsEnd(){this.active()&&(this._data.inputsTime=Ar.now()-this._inputs_start)}recordParamsStart(){this.active()&&(this._params_start=Ar.now())}recordParamsEnd(){this.active()&&(this._data.paramsTime=Ar.now()-this._params_start)}recordCookStart(){this.active()&&(this._cook_start=Ar.now())}recordCookEnd(){this.active()&&(this._data.cookTime=Ar.now()-this._cook_start,this._cooksCount+=1)}}class Er{constructor(t){this.node=t,this._cooking=!1,this._performanceController=new Mr(this),this._inputs_evaluation_required=!0,this._core_performance=this.node.scene().performance}performanceRecordStarted(){return this._core_performance.started()}disallowInputsEvaluation(){this._inputs_evaluation_required=!1}isCooking(){return!0===this._cooking}_start_cook_if_no_errors(t){if(this.node.states.error.active())this.endCook();else try{this._performanceController.recordCookStart(),this.node.cook(t)}catch(t){this.node.states.error.set(`node internal error: '${t}'.`),li.warn(t),this.endCook()}}async cookMain(){if(this.isCooking())return;let t;this._initCookingState(),this.node.states.error.clear(),this.node.scene().cookController.addNode(this.node),t=this._inputs_evaluation_required?await this._evaluateInputs():[],this.node.params.paramsEvalRequired()&&await this._evaluateParams(),this._start_cook_if_no_errors(t)}async cookMainWithoutInputs(){this.node.scene().cookController.addNode(this.node),this.isCooking()?li.warn(\\\\\\\"cook_main_without_inputs already cooking\\\\\\\",this.node.path()):(this._initCookingState(),this.node.states.error.clear(),this.node.params.paramsEvalRequired()&&await this._evaluateParams(),this._start_cook_if_no_errors([]))}endCook(t){this._finalizeCookPerformance();const e=this.node.dirtyController.dirtyTimestamp();null==e||e===this._cooking_dirty_timestamp?(this.node.removeDirtyState(),this._terminateCookProcess()):(li.log(\\\\\\\"COOK AGAIN\\\\\\\",e,this._cooking_dirty_timestamp,this.node.path()),this._cooking=!1,this.cookMain())}_initCookingState(){this._cooking=!0,this._cooking_dirty_timestamp=this.node.dirtyController.dirtyTimestamp()}_terminateCookProcess(){this.isCooking()&&(this._cooking=!1,this.node.containerController.notifyRequesters(),this._run_on_cook_complete_hooks())}async _evaluateInputs(){this._performanceController.recordInputsStart();let t=[];const e=this.node.io.inputs;this._inputs_evaluation_required&&(t=e.is_any_input_dirty()?await e.eval_required_inputs():await e.containers_without_evaluation());const n=e.inputs(),i=[];let s;for(let r=0;rt.graphNodeId()))}maxInputsCount(){return this.node.io.inputs.maxInputsCount()}inputIds(){return this.node.io.inputs.inputs().map((t=>null!=t?t.graphNodeId():void 0))}inputConnectionOutputIndices(){var t;return null===(t=this.node.io.connections.inputConnections())||void 0===t?void 0:t.map((t=>null!=t?t.output_index:void 0))}namedInputConnectionPoints(){return this.node.io.inputs.namedInputConnectionPoints().map((t=>t.toJSON()))}namedOutputConnectionPoints(){return this.node.io.outputs.namedOutputConnectionPoints().map((t=>t.toJSON()))}to_json_params_from_names(t,e=!1){return t.map((t=>this.node.params.get(t).graphNodeId()))}to_json_params(t=!1){return this.to_json_params_from_names(this.node.params.names,t)}}var Cr,Nr;!function(t){t.BOOLEAN=\\\\\\\"boolean\\\\\\\",t.BUTTON=\\\\\\\"button\\\\\\\",t.COLOR=\\\\\\\"color\\\\\\\",t.FLOAT=\\\\\\\"float\\\\\\\",t.FOLDER=\\\\\\\"folder\\\\\\\",t.INTEGER=\\\\\\\"integer\\\\\\\",t.OPERATOR_PATH=\\\\\\\"operator_path\\\\\\\",t.PARAM_PATH=\\\\\\\"param_path\\\\\\\",t.NODE_PATH=\\\\\\\"node_path\\\\\\\",t.RAMP=\\\\\\\"ramp\\\\\\\",t.STRING=\\\\\\\"string\\\\\\\",t.VECTOR2=\\\\\\\"vector2\\\\\\\",t.VECTOR3=\\\\\\\"vector3\\\\\\\",t.VECTOR4=\\\\\\\"vector4\\\\\\\"}(Cr||(Cr={})),function(t){t.VISIBLE_UPDATED=\\\\\\\"param_visible_updated\\\\\\\",t.RAW_INPUT_UPDATED=\\\\\\\"raw_input_updated\\\\\\\",t.VALUE_UPDATED=\\\\\\\"param_value_updated\\\\\\\",t.EXPRESSION_UPDATED=\\\\\\\"param_expression_update\\\\\\\",t.ERROR_UPDATED=\\\\\\\"param_error_updated\\\\\\\",t.DELETED=\\\\\\\"param_deleted\\\\\\\"}(Nr||(Nr={}));const Lr=\\\\\\\"dependentOnFoundNode\\\\\\\",Or=\\\\\\\"visibleIf\\\\\\\";var Pr,Rr;!function(t){t.TYPESCRIPT=\\\\\\\"typescript\\\\\\\"}(Pr||(Pr={})),function(t){t.AUDIO=\\\\\\\"audio\\\\\\\",t.TEXTURE_IMAGE=\\\\\\\"texture_image\\\\\\\",t.TEXTURE_VIDEO=\\\\\\\"texture_video\\\\\\\",t.GEOMETRY=\\\\\\\"geometry\\\\\\\",t.FONT=\\\\\\\"font\\\\\\\",t.SVG=\\\\\\\"svg\\\\\\\",t.JSON=\\\\\\\"json\\\\\\\"}(Rr||(Rr={}));class Ir{constructor(t){this._param=t,this._programatic_visible_state=!0,this._callbackAllowed=!1,this._updateVisibilityAndRemoveDirtyBound=this.updateVisibilityAndRemoveDirty.bind(this),this._ui_data_dependency_set=!1}dispose(){var t;try{this._options.callback=void 0,this._options.callbackString=void 0}catch(t){}null===(t=this._visibility_graph_node)||void 0===t||t.dispose()}set(t){this._default_options=t,this._options=b.cloneDeep(this._default_options),this.post_set_options()}copy(t){this._default_options=b.cloneDeep(t.default()),this._options=b.cloneDeep(t.current()),this.post_set_options()}setOption(t,e){if(this._options[t]=e,this._param.components)for(let n of this._param.components)n.options.setOption(t,e)}post_set_options(){this._handleComputeOnDirty()}param(){return this._param}node(){return this._param.node}default(){return this._default_options}current(){return this._options}hasOptionsOverridden(){return!b.isEqual(this._options,this._default_options)}overriddenOptions(){const t={},e=Object.keys(this._options);for(let n of e)if(!b.isEqual(this._options[n],this._default_options[n])){const e=b.cloneDeep(this._options[n]);Object.assign(t,{[n]:e})}return t}overriddenOptionNames(){return Object.keys(this.overriddenOptions())}computeOnDirty(){return this._options.computeOnDirty||!1}_handleComputeOnDirty(){this.computeOnDirty()&&(this._computeOnDirty_callback_added||(this.param().addPostDirtyHook(\\\\\\\"computeOnDirty\\\\\\\",this._computeParam.bind(this)),this._computeOnDirty_callback_added=!0))}async _computeParam(){await this.param().compute()}hasCallback(){return null!=this._options.callback||null!=this._options.callbackString}allowCallback(){this._callbackAllowed=!0}executeCallback(){if(!this._callbackAllowed)return;if(!this.node())return;const t=this.getCallback();if(!t)return;if(!this.node().scene().loadingController.loaded())return;const e=this.param().parent_param;e?e.options.executeCallback():t(this.node(),this.param())}getCallback(){if(this.hasCallback())return this._options.callback=this._options.callback||this.createCallbackFromString()}createCallbackFromString(){const t=this._options.callbackString;if(t){const e=new Function(\\\\\\\"node\\\\\\\",\\\\\\\"scene\\\\\\\",\\\\\\\"window\\\\\\\",\\\\\\\"location\\\\\\\",t);return()=>{e(this.node(),this.node().scene(),null,null)}}}colorConversion(){return this._options.conversion}makesNodeDirtyWhenDirty(){let t;if(null!=this.param().parent_param)return!1;let e=!0;return null!=(t=this._options.cook)&&(e=t),e}fileBrowseOption(){return this._options.fileBrowse}fileBrowseAllowed(){return null!=this.fileBrowseOption()}fileBrowseType(){const t=this.fileBrowseOption();return t?t.type:null}separatorBefore(){return this._options.separatorBefore}separatorAfter(){return this._options.separatorAfter}isExpressionForEntities(){const t=this._options.expression;return t&&t.forEntities||!1}level(){return this._options.level||0}hasMenu(){return null!=this.menuOptions()||null!=this.menuStringOptions()}menuOptions(){return this._options.menu}menuStringOptions(){return this._options.menuString}menuEntries(){const t=this.menuOptions()||this.menuStringOptions();return t?t.entries:[]}isMultiline(){return!0===this._options.multiline}language(){return this._options.language}isCode(){return null!=this.language()}nodeSelectionOptions(){return this._options.nodeSelection}nodeSelectionContext(){const t=this.nodeSelectionOptions();if(t)return t.context}nodeSelectionTypes(){const t=this.nodeSelectionOptions();if(t)return t.types}dependentOnFoundNode(){return!(Lr in this._options)||this._options.dependentOnFoundNode}isSelectingParam(){return null!=this.paramSelectionOptions()}paramSelectionOptions(){return this._options.paramSelection}paramSelectionType(){const t=this.paramSelectionOptions();if(t){const e=t;if(!m.isBoolean(e))return e}}range(){return this._options.range||[0,1]}step(){return this._options.step}rangeLocked(){return this._options.rangeLocked||[!1,!1]}ensureInRange(t){const e=this.range();return t>=e[0]&&t<=e[1]?t:tObject.keys(t))).flat()):Object.keys(t);const n=this.param().node;return f.compact(e.map((t=>{const e=n.params.get(t);if(e)return e;console.error(`param ${t} not found as visibility condition for ${this.param().name()} in node ${this.param().node.type()}`)})))}setUiDataDependency(){if(this._ui_data_dependency_set)return;this._ui_data_dependency_set=!0;const t=this.visibilityPredecessors();if(t.length>0){this._visibility_graph_node=new Mi(this.param().scene(),\\\\\\\"param_visibility\\\\\\\");for(let e of t)this._visibility_graph_node.addGraphInput(e);this._visibility_graph_node.addPostDirtyHook(\\\\\\\"_update_visibility_and_remove_dirty\\\\\\\",this._updateVisibilityAndRemoveDirtyBound)}}updateVisibilityAndRemoveDirty(){this.updateVisibility(),this.param().removeDirtyState()}async updateVisibility(){const t=this._options.visibleIf;if(t){const e=this.visibilityPredecessors(),n=e.map((t=>{if(t.isDirty())return t.compute()}));if(this._programatic_visible_state=!1,await Promise.all(n),m.isArray(t))for(let n of t){e.filter((t=>t.value==n[t.name()])).length==e.length&&(this._programatic_visible_state=!0)}else{const n=e.filter((e=>e.value==t[e.name()]));this._programatic_visible_state=n.length==e.length}this.param().emit(Nr.VISIBLE_UPDATED)}}}class Fr{constructor(t){this.param=t,this._blocked_emit=!1,this._blocked_parent_emit=!1,this._count_by_event_name={}}emitAllowed(){return!0!==this._blocked_emit&&(!this.param.scene().loadingController.isLoading()&&this.param.scene().dispatchController.emitAllowed())}blockEmit(){if(this._blocked_emit=!0,this.param.isMultiple()&&this.param.components)for(let t of this.param.components)t.emitController.blockEmit();return!0}unblockEmit(){if(this._blocked_emit=!1,this.param.isMultiple()&&this.param.components)for(let t of this.param.components)t.emitController.unblockEmit();return!0}blockParentEmit(){return this._blocked_parent_emit=!0,!0}unblockParentEmit(){return this._blocked_parent_emit=!1,!0}incrementCount(t){this._count_by_event_name[t]=this._count_by_event_name[t]||0,this._count_by_event_name[t]+=1}eventsCount(t){return this._count_by_event_name[t]||0}emit(t){this.emitAllowed()&&(this.param.emit(t),null!=this.param.parent_param&&!0!==this._blocked_parent_emit&&this.param.parent_param.emit(t))}}class Dr{constructor(t){this.param=t}toJSON(){const t={name:this.param.name(),type:this.param.type(),raw_input:this.rawInput(),value:this.value(),value_pre_conversion:this.value_pre_conversion(),expression:this.expression(),graph_node_id:this.param.graphNodeId(),error_message:this.error_message(),is_visible:this.is_visible(),components:void 0};return this.param.isMultiple()&&this.param.components&&(t.components=this.param.components.map((t=>t.graphNodeId()))),t}rawInput(){return this.param.rawInputSerialized()}value(){return this.param.valueSerialized()}value_pre_conversion(){return this.param.valuePreConversionSerialized()}expression(){var t;return this.param.hasExpression()?null===(t=this.param.expressionController)||void 0===t?void 0:t.expression():void 0}error_message(){return this.param.states.error.message()}is_visible(){return this.param.options.isVisible()}}class Br{constructor(t){this.param=t}active(){const t=this.param.scene().timeController.graphNode.graphNodeId();return this.param.graphPredecessorIds().includes(t)}}class zr{constructor(t){this.param=t}set(t){this._message!=t&&(this._message=t,this._message&&li.warn(this.param.path(),this._message),this.param.emitController.emit(Nr.ERROR_UPDATED))}message(){return this._message}clear(){this.set(void 0)}active(){return null!=this._message}}class kr{constructor(t){this.param=t,this.timeDependent=new Br(this.param),this.error=new zr(this.param)}}class Ur extends Mi{constructor(t,e,n){var i;super(t.scene(),\\\\\\\"MethodDependency\\\\\\\"),this.param=t,this.path_argument=e,this.decomposed_path=n,this._update_from_name_change_bound=this._update_from_name_change.bind(this),null===(i=t.expressionController)||void 0===i||i.registerMethodDependency(this),this.addPostDirtyHook(\\\\\\\"_update_from_name_change\\\\\\\",this._update_from_name_change_bound)}_update_from_name_change(t){if(t&&this.decomposed_path){const e=t;this.decomposed_path.update_from_name_change(e);const n=this.decomposed_path.to_path(),i=this.jsep_node;i&&(i.value=`${i.value}`.replace(`${this.path_argument}`,n),i.raw=i.raw.replace(`${this.path_argument}`,n)),this.param.expressionController&&this.param.expressionController.updateFromMethodDependencyNameChange()}}reset(){this.graphDisconnectPredecessors()}listen_for_name_changes(){if(this.jsep_node&&this.decomposed_path)for(let t of this.decomposed_path.named_nodes())if(t){const e=t;e.nameController&&this.addGraphInput(e.nameController.graph_node)}}set_jsep_node(t){this.jsep_node=t}set_resolved_graph_node(t){this.resolved_graph_node=t}set_unresolved_path(t){this.unresolved_path=t}static create(t,e,n,i){const s=m.isNumber(e),r=new Ur(t,e,i);if(n)r.set_resolved_graph_node(n);else if(!s){const t=e;r.set_unresolved_path(t)}return r}}const Gr=[];class Vr extends Mi{constructor(t,e){super(t,\\\\\\\"BaseParam\\\\\\\"),this._options=new Ir(this),this._emit_controller=new Fr(this),this._is_computing=!1,this._node=e,this.initialize_param()}get options(){return this._options=this._options||new Ir(this)}get emitController(){return this._emit_controller=this._emit_controller||new Fr(this)}get expressionController(){return this._expression_controller}get serializer(){return this._serializer=this._serializer||new Dr(this)}get states(){return this._states=this._states||new kr(this)}dispose(){var t,e;const n=this.graphPredecessors();for(let t of n)t instanceof Ur&&t.dispose();this.scene().missingExpressionReferencesController.deregisterParam(this),null===(t=this._expression_controller)||void 0===t||t.dispose(),super.dispose(),null===(e=this._options)||void 0===e||e.dispose()}initialize_param(){}static type(){return Cr.FLOAT}type(){return this.constructor.type()}isNumeric(){return!1}setName(t){super.setName(t)}get value(){return this._value}copy_value(t){t.type()==this.type()?this._copy_value(t):console.warn(`cannot copy value from ${t.type()} to ${this.type()}`)}_copy_value(t){throw\\\\\\\"abstract method param._copy_value\\\\\\\"}valuePreConversionSerialized(){}convert(t){return null}static are_raw_input_equal(t,e){return!1}is_raw_input_equal(t){return this.constructor.are_raw_input_equal(this._raw_input,t)}static are_values_equal(t,e){return!1}is_value_equal(t){return this.constructor.are_values_equal(this.value,t)}_clone_raw_input(t){return t}set(t){this._raw_input=this._clone_raw_input(this._prefilter_invalid_raw_input(t)),this.emitController.emit(Nr.RAW_INPUT_UPDATED),this.processRawInput()}_prefilter_invalid_raw_input(t){return t}defaultValue(){return this._default_value}isDefault(){return this._raw_input==this._default_value}rawInput(){return this._raw_input}processRawInput(){}async compute(){if(this.scene().loadingController.isLoading()&&console.warn(`param attempt to compute ${this.path()}`),this.isDirty()){if(this._is_computing)return new Promise(((t,e)=>{this._compute_resolves=this._compute_resolves||[],this._compute_resolves.push(t)}));if(this._is_computing=!0,await this.processComputation(),this._is_computing=!1,this._compute_resolves){let t;for(;t=this._compute_resolves.pop();)t()}}}async processComputation(){}setInitValue(t){this._default_value=this._clone_raw_input(this._prefilter_invalid_raw_input(t))}_setupNodeDependencies(t){var e,n;if(t?(this.options.allowCallback(),this.parent_param||(this.options.makesNodeDirtyWhenDirty()?null===(n=t.params.params_node)||void 0===n||n.addGraphInput(this,!1):this.dirtyController.addPostDirtyHook(\\\\\\\"run callback\\\\\\\",(async()=>{await this.compute(),this.options.executeCallback()})))):this._node&&(null===(e=this._node.params.params_node)||void 0===e||e.removeGraphInput(this)),this.components)for(let e of this.components)e._setupNodeDependencies(t)}get node(){return this._node}parent(){return this.node}set_parent_param(t){t.addGraphInput(this,!1),this._parent_param=t}get parent_param(){return this._parent_param}has_parent_param(){return null!=this._parent_param}path(){var t;return(null===(t=this.node)||void 0===t?void 0:t.path())+\\\\\\\"/\\\\\\\"+this.name()}pathRelativeTo(t){const e=bi.relativePath(t,this.node);return e.length>0?`${e}${bi.SEPARATOR}${this.name()}`:this.name()}emit(t){this.emitController.emitAllowed()&&(this.emitController.incrementCount(t),this.scene().dispatchController.dispatch(this,t))}get components(){return this._components}componentNames(){return Gr}isMultiple(){return this.componentNames().length>0}initComponents(){}hasExpression(){return null!=this.expressionController&&this.expressionController.active()}toJSON(){return this.serializer.toJSON()}}var Hr=n(94),jr=n.n(Hr);jr.a.addUnaryOp(\\\\\\\"@\\\\\\\");jr.a.addBinaryOp(\\\\\\\"**\\\\\\\",10);class Wr{constructor(){}parse_expression(t){try{this.reset(),this.node=jr()(t)}catch(e){const n=`could not parse the expression '${t}' (error: ${e})`;this.error_message=n}}parse_expression_for_string_param(t){try{this.reset();const e=Wr.string_value_elements(t),n=[];for(let t=0;t0){const e=\\\\\\\"const coreGeometry = entities[0].coreGeometry();\\\\\\\";t.push(e)}for(let e of this._attributeNames)t.push(Xr.assignItemSizeLine(e)),t.push(Xr.assignArrayLine(e));return t.join(\\\\\\\";\\\\n\\\\\\\")}return\\\\\\\"\\\\\\\"}attributePresenceCheckLine(){if(this._attributeNames){const t=[];for(let e of this._attributeNames){const n=Xr._varAttribute(e);t.push(n)}if(t.length>0)return t.join(\\\\\\\" && \\\\\\\")}return\\\\\\\"true\\\\\\\"}add(t){this._attributeNames=this._attributeNames||new Set,this._attributeNames.add(t)}static assignAttributeLine(t){return`const ${this._varAttribute(t)} = entities[0].geometry().attributes['${t}']`}static assignItemSizeLine(t){const e=this._varAttribute(t);return`const ${this._varAttribSize(t)} = ${e}.itemSize`}static assignArrayLine(t){const e=this._varAttribute(t);return`const ${this._varArray(t)} = ${`coreGeometry.isAttribIndexed('${t}')`} ? ${`entities.map(e=>e.indexedAttribValue('${t}'))`} : ${`${e}.array`}`}static _varAttribute(t){return`attrib_${t}`}static _varAttribSize(t){return`attrib_size_${t}`}static _varArray(t){return`array_${t}`}varAttributeSize(t){return Xr._varAttribSize(t)}varArray(t){return Xr._varArray(t)}}const Yr={math_random:\\\\\\\"random\\\\\\\"},$r=Object.keys(sr),Jr={};[\\\\\\\"abs\\\\\\\",\\\\\\\"acos\\\\\\\",\\\\\\\"acosh\\\\\\\",\\\\\\\"asin\\\\\\\",\\\\\\\"asinh\\\\\\\",\\\\\\\"atan\\\\\\\",\\\\\\\"atan2\\\\\\\",\\\\\\\"atanh\\\\\\\",\\\\\\\"ceil\\\\\\\",\\\\\\\"cos\\\\\\\",\\\\\\\"cosh\\\\\\\",\\\\\\\"exp\\\\\\\",\\\\\\\"expm1\\\\\\\",\\\\\\\"floor\\\\\\\",\\\\\\\"log\\\\\\\",\\\\\\\"log1p\\\\\\\",\\\\\\\"log2\\\\\\\",\\\\\\\"log10\\\\\\\",\\\\\\\"max\\\\\\\",\\\\\\\"min\\\\\\\",\\\\\\\"pow\\\\\\\",\\\\\\\"round\\\\\\\",\\\\\\\"sign\\\\\\\",\\\\\\\"sin\\\\\\\",\\\\\\\"sinh\\\\\\\",\\\\\\\"sqrt\\\\\\\",\\\\\\\"tan\\\\\\\",\\\\\\\"tanh\\\\\\\"].forEach((t=>{Jr[t]=`Math.${t}`})),[\\\\\\\"cbrt\\\\\\\",\\\\\\\"hypot\\\\\\\",\\\\\\\"log10\\\\\\\",\\\\\\\"trunc\\\\\\\"].forEach((t=>{Jr[t]=`Math.${t}`})),Object.keys(Yr).forEach((t=>{const e=Yr[t];Jr[t]=`Math.${e}`})),[\\\\\\\"fit\\\\\\\",\\\\\\\"fit01\\\\\\\",\\\\\\\"fract\\\\\\\",\\\\\\\"deg2rad\\\\\\\",\\\\\\\"rad2deg\\\\\\\",\\\\\\\"rand\\\\\\\",\\\\\\\"clamp\\\\\\\"].forEach((t=>{Jr[t]=`Core.Math.${t}`})),$r.forEach((t=>{Jr[t]=`Core.Math.Easing.${t}`})),[\\\\\\\"precision\\\\\\\"].forEach((t=>{Jr[t]=`Core.String.${t}`}));const Zr={if:class{static if(t){return`(${t[0]}) ? (${t[1]}) : (${t[2]})`}}.if},Qr={};[\\\\\\\"E\\\\\\\",\\\\\\\"LN2\\\\\\\",\\\\\\\"LN10\\\\\\\",\\\\\\\"LOG10E\\\\\\\",\\\\\\\"LOG2E\\\\\\\",\\\\\\\"PI\\\\\\\",\\\\\\\"SQRT1_2\\\\\\\",\\\\\\\"SQRT2\\\\\\\"].forEach((t=>{Qr[t]=`Math.${t}`}));const Kr={x:0,y:1,z:2,w:3,r:0,g:1,b:2};class to extends qr{constructor(t){super(t),this.param=t,this._attribute_requirements_controller=new Xr,this.methods=[],this.method_index=-1,this.method_dependencies=[],this.immutable_dependencies=[]}parse_tree(t){if(this.reset(),null==t.error_message){try{if(this._attribute_requirements_controller=new Xr,t.node){const e=this.traverse_node(t.node);e&&!this.is_errored()&&(this.function_main_string=e)}else console.warn(\\\\\\\"no parsed_tree.node\\\\\\\")}catch(t){console.warn(`error in expression for param ${this.param.path()}`),console.warn(t)}if(this.function_main_string)try{const t=this._functionBody();this.function=new Function(\\\\\\\"Core\\\\\\\",\\\\\\\"param\\\\\\\",\\\\\\\"methods\\\\\\\",\\\\\\\"_set_error_from_error\\\\\\\",`\\\\n\\\\t\\\\t\\\\t\\\\t\\\\ttry {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t${t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t} catch(e) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t_set_error_from_error(e)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\treturn null;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t}`)}catch(t){console.warn(t),this.set_error(\\\\\\\"cannot generate function\\\\\\\")}else this.set_error(\\\\\\\"cannot generate function body\\\\\\\")}else this.set_error(\\\\\\\"cannot parse expression\\\\\\\")}reset(){super.reset(),this.function_main_string=void 0,this.methods=[],this.method_index=-1,this.function=void 0,this.method_dependencies=[],this.immutable_dependencies=[]}_functionBody(){return this.param.options.isExpressionForEntities()?`\\\\n\\\\t\\\\t\\\\tconst entities = param.expressionController.entities();\\\\n\\\\t\\\\t\\\\tif(entities){\\\\n\\\\t\\\\t\\\\t\\\\treturn new Promise( async (resolve, reject)=>{\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tlet entity;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tconst entity_callback = param.expressionController.entity_callback();\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t// assign_attributes_lines\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t${this._attribute_requirements_controller.assignAttributesLines()}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t// check if attributes are present\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tif( ${this._attribute_requirements_controller.attributePresenceCheckLine()} ){\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t// assign_arrays_lines\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t${this._attribute_requirements_controller.assignArraysLines()}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tfor(let index=0; index < entities.length; index++){\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tentity = entities[index];\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tresult = ${this.function_main_string};\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tentity_callback(entity, result);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tresolve()\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tconst error = new Error('attribute not found')\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t_set_error_from_error(error)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\treject(error)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t})\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\treturn []`:`\\\\n\\\\t\\\\t\\\\treturn new Promise( async (resolve, reject)=>{\\\\n\\\\t\\\\t\\\\t\\\\ttry {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tconst value = ${this.function_main_string}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tresolve(value)\\\\n\\\\t\\\\t\\\\t\\\\t} catch(e) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t_set_error_from_error(e)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\treject()\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t})\\\\n\\\\t\\\\t\\\\t`}evalAllowed(){return null!=this.function}evalFunction(){if(this.function){this.clear_error();const t={Math:or,String:ss};return this.function(t,this.param,this.methods,this._set_error_from_error_bound)}}traverse_CallExpression(t){const e=t.arguments.map((t=>this.traverse_node(t))),n=t.callee.name;if(n){const i=Zr[n];if(i)return i(e);const s=`${e.join(\\\\\\\", \\\\\\\")}`,r=Jr[n];if(r)return`${r}(${s})`;const o=li.expressionsRegister;if(o.getMethod(n)){const i=t.arguments[0],r=`return ${e[0]}`;let o,a=[];try{o=new Function(r),a=o()}catch{}return this._create_method_and_dependencies(n,a,i),`(await methods[${this.method_index}].processArguments([${s}]))`}{const t=`method not found (${n}), available methods are: ${o.availableMethods().join(\\\\\\\", \\\\\\\")}`;li.warn(t)}}this.set_error(`unknown method: ${n}`)}traverse_BinaryExpression(t){return`(${this.traverse_node(t.left)} ${t.operator} ${this.traverse_node(t.right)})`}traverse_LogicalExpression(t){return`(${this.traverse_node(t.left)} ${t.operator} ${this.traverse_node(t.right)})`}traverse_MemberExpression(t){return`${this.traverse_node(t.object)}.${this.traverse_node(t.property)}`}traverse_UnaryExpression(t){if(\\\\\\\"@\\\\\\\"===t.operator){let e,n,i=t.argument;switch(i.type){case\\\\\\\"Identifier\\\\\\\":e=i.name;break;case\\\\\\\"MemberExpression\\\\\\\":{const t=i,s=t.object,r=t.property;e=s.name,n=r.name;break}}if(e){if(e=Xs.remapName(e),\\\\\\\"ptnum\\\\\\\"==e)return\\\\\\\"((entity != null) ? entity.index() : 0)\\\\\\\";{const t=this._attribute_requirements_controller.varAttributeSize(e),i=this._attribute_requirements_controller.varArray(e);if(this._attribute_requirements_controller.add(e),n){return`${i}[entity.index()*${t}+${Kr[n]}]`}return`${i}[entity.index()*${t}]`}}return console.warn(\\\\\\\"attribute not found\\\\\\\"),\\\\\\\"\\\\\\\"}return`${t.operator}${this.traverse_node(t.argument)}`}traverse_Literal(t){return`${t.raw}`}traverse_Identifier(t){if(\\\\\\\"$\\\\\\\"!=t.name[0])return t.name;{const e=t.name.substr(1),n=Qr[e];if(n)return n;const i=`traverse_Identifier_${e}`;if(this[i])return this[i]();this.set_error(`identifier unknown: ${t.name}`)}}traverse_Identifier_F(){return this.immutable_dependencies.push(this.param.scene().timeController.graphNode),\\\\\\\"param.scene().timeController.frame()\\\\\\\"}traverse_Identifier_T(){return this.immutable_dependencies.push(this.param.scene().timeController.graphNode),\\\\\\\"param.scene().timeController.time()\\\\\\\"}traverse_Identifier_OS(){return`'${this.param.node.name()}'`}traverse_Identifier_CH(){return`'${this.param.name()}'`}traverse_Identifier_CEX(){return this._method_centroid(\\\\\\\"x\\\\\\\")}traverse_Identifier_CEY(){return this._method_centroid(\\\\\\\"y\\\\\\\")}traverse_Identifier_CEZ(){return this._method_centroid(\\\\\\\"z\\\\\\\")}_method_centroid(t){const e=[0,`'${t}'`].join(\\\\\\\", \\\\\\\");return this._create_method_and_dependencies(\\\\\\\"centroid\\\\\\\",0),`(await methods[${this.method_index}].processArguments([${e}]))`}_create_method_and_dependencies(t,e,n){const i=li.expressionsRegister,s=i.getMethod(t);if(!s){const e=`method not found (${t}), available methods are: ${i.availableMethods().join(\\\\\\\", \\\\\\\")}`;return this.set_error(e),void li.warn(e)}const r=new s(this.param);if(this.method_index+=1,this.methods[this.method_index]=r,r.require_dependency()){const t=r.findDependency(e);t?(n&&t.set_jsep_node(n),this.method_dependencies.push(t)):n&&m.isString(e)&&this.param.scene().missingExpressionReferencesController.register(this.param,e)}}}class eo extends qr{constructor(t){super(t),this.param=t}parse_tree(t){if(null==t.error_message&&t.node)try{return this.traverse_node(t.node)}catch(t){this.set_error(\\\\\\\"could not traverse tree\\\\\\\")}else this.set_error(\\\\\\\"cannot parse tree\\\\\\\")}traverse_CallExpression(t){const e=`${t.arguments.map((t=>this.traverse_node(t))).join(\\\\\\\", \\\\\\\")}`;return`${t.callee.name}(${e})`}traverse_UnaryExpression(t){return`${t.operator}${this.traverse_node(t.argument)}`}traverse_Identifier(t){return`${t.name}`}}class no{constructor(t){this.param=t,this.cyclic_graph_detected=!1,this.method_dependencies=[]}set_error(t){this.error_message=this.error_message||t}reset(){this.param.graphDisconnectPredecessors(),this.method_dependencies.forEach((t=>{t.reset()})),this.method_dependencies=[]}update(t){this.cyclic_graph_detected=!1,this.connect_immutable_dependencies(t),this.method_dependencies=t.method_dependencies,this.handle_method_dependencies(),this.listen_for_name_changes()}connect_immutable_dependencies(t){t.immutable_dependencies.forEach((t=>{if(0==this.cyclic_graph_detected&&0==this.param.addGraphInput(t))return this.cyclic_graph_detected=!0,this.set_error(\\\\\\\"cannot create expression, infinite graph detected\\\\\\\"),void this.reset()}))}handle_method_dependencies(){this.method_dependencies.forEach((t=>{0==this.cyclic_graph_detected&&this.handle_method_dependency(t)}))}handle_method_dependency(t){const e=t.resolved_graph_node;if(e&&!this.param.addGraphInput(e))return this.cyclic_graph_detected=!0,this.set_error(\\\\\\\"cannot create expression, infinite graph detected\\\\\\\"),void this.reset()}listen_for_name_changes(){this.method_dependencies.forEach((t=>{t.listen_for_name_changes()}))}}class io{constructor(t){this.param=t,this.parse_completed=!1,this.parse_started=!1,this.parsed_tree=new Wr,this._functionGenerator=new to(this.param),this.dependencies_controller=new no(this.param)}parseExpression(t){if(this.parse_started)throw new Error(`parse in progress for param ${this.param.path()}`);this.parse_started=!0,this.parse_completed=!1,this.parsed_tree=this.parsed_tree||new Wr,this.reset(),this.param.type()==Cr.STRING?this.parsed_tree.parse_expression_for_string_param(t):this.parsed_tree.parse_expression(t),this._functionGenerator.parse_tree(this.parsed_tree),null==this._functionGenerator.error_message()&&(this.dependencies_controller.update(this._functionGenerator),this.dependencies_controller.error_message?this.param.states.error.set(this.dependencies_controller.error_message):(this.parse_completed=!0,this.parse_started=!1))}async computeFunction(){if(!this._computeAllowed())return new Promise(((t,e)=>{t(null)}));try{return await this._functionGenerator.evalFunction()}catch(t){return}}reset(){this.parse_completed=!1,this.parse_started=!1,this.dependencies_controller.reset(),this._functionGenerator.reset()}is_errored(){return this._functionGenerator.is_errored()}error_message(){return this._functionGenerator.error_message()}_computeAllowed(){return this._functionGenerator.evalAllowed()}updateFromMethodDependencyNameChange(){this.expression_string_generator=this.expression_string_generator||new eo(this.param);const t=this.expression_string_generator.parse_tree(this.parsed_tree);t?this.param.set(t):console.warn(\\\\\\\"failed to regenerate expression\\\\\\\")}}class so{constructor(t){this.param=t}dispose(){this.param.scene().expressionsController.deregisterParam(this.param),this._resetMethodDependencies()}_resetMethodDependencies(){var t,e;null===(t=this._method_dependencies_by_graph_node_id)||void 0===t||t.forEach((t=>{t.dispose()})),null===(e=this._method_dependencies_by_graph_node_id)||void 0===e||e.clear()}registerMethodDependency(t){this._method_dependencies_by_graph_node_id=this._method_dependencies_by_graph_node_id||new Map,this._method_dependencies_by_graph_node_id.set(t.graphNodeId(),t)}active(){return null!=this._expression}expression(){return this._expression}is_errored(){return!!this._manager&&this._manager.is_errored()}error_message(){return this._manager?this._manager.error_message():null}requires_entities(){return this.param.options.isExpressionForEntities()}set_expression(t,e=!0){var n;this.param.scene().missingExpressionReferencesController.deregisterParam(this.param),this.param.scene().expressionsController.deregisterParam(this.param),this._expression!=t&&(this._resetMethodDependencies(),this._expression=t,this._expression?(this._manager=this._manager||new io(this.param),this._manager.parseExpression(this._expression)):null===(n=this._manager)||void 0===n||n.reset(),e&&this.param.setDirty())}updateFromMethodDependencyNameChange(){this._manager&&this.active()&&this._manager.updateFromMethodDependencyNameChange()}async computeExpression(){if(this._manager&&this.active()){return await this._manager.computeFunction()}}async computeExpressionForEntities(t,e){var n,i;this.set_entities(t,e),await this.computeExpression(),(null===(n=this._manager)||void 0===n?void 0:n.error_message())&&this.param.node.states.error.set(`expression evalution error: ${null===(i=this._manager)||void 0===i?void 0:i.error_message()}`),this.reset_entities()}computeExpressionForPoints(t,e){return this.computeExpressionForEntities(t,e)}computeExpressionForObjects(t,e){return this.computeExpressionForEntities(t,e)}entities(){return this._entities}entity_callback(){return this._entity_callback}set_entities(t,e){this._entities=t,this._entity_callback=e}reset_entities(){this._entities=void 0,this._entity_callback=void 0}}class ro extends Vr{isNumeric(){return!0}isDefault(){return this._raw_input==this._default_value}_prefilter_invalid_raw_input(t){return m.isArray(t)?t[0]:t}processRawInput(){this.states.error.clear();const t=this.convert(this._raw_input);null!=t?(this._expression_controller&&(this._expression_controller.set_expression(void 0,!1),this.emitController.emit(Nr.EXPRESSION_UPDATED)),t!=this._value&&(this._update_value(t),this.setSuccessorsDirty(this))):m.isString(this._raw_input)?(this._expression_controller=this._expression_controller||new so(this),this._raw_input!=this._expression_controller.expression()&&(this._expression_controller.set_expression(this._raw_input),this.emitController.emit(Nr.EXPRESSION_UPDATED))):this.states.error.set(`param input is invalid (${this.path()})`)}async processComputation(){var t;if((null===(t=this.expressionController)||void 0===t?void 0:t.active())&&!this.expressionController.requires_entities()){const t=await this.expressionController.computeExpression();if(this.expressionController.is_errored())this.states.error.set(`expression error: \\\\\\\"${this.expressionController.expression()}\\\\\\\" (${this.expressionController.error_message()})`);else{const e=this.convert(t);null!=e?(this.states.error.active()&&this.states.error.clear(),this._update_value(e)):this.states.error.set(`expression returns an invalid type (${t}) (${this.expressionController.expression()})`)}}}_update_value(t){this._value=t,this.parent_param&&this.parent_param.set_value_from_components(),this.options.executeCallback(),this.emitController.emit(Nr.VALUE_UPDATED),this.removeDirtyState()}}class oo extends ro{static type(){return Cr.FLOAT}defaultValueSerialized(){return this._default_value}rawInputSerialized(){return this._raw_input}valueSerialized(){return this.value}_copy_value(t){this.set(t.valueSerialized())}_prefilter_invalid_raw_input(t){return m.isArray(t)?t[0]:m.isString(t)&&ss.isNumber(t)?parseFloat(t):t}static are_raw_input_equal(t,e){return t==e}static are_values_equal(t,e){return t==e}static convert(t){if(m.isNumber(t))return t;if(m.isBoolean(t))return t?1:0;if(ss.isNumber(t)){const e=parseFloat(t);if(m.isNumber(e))return e}return null}convert(t){const e=oo.convert(t);return e?this.options.ensureInRange(e):e}}class ao extends Vr{constructor(){super(...arguments),this._components_contructor=oo}get components(){return this._components}isNumeric(){return!0}isDefault(){for(let t of this.components)if(!t.isDefault())return!1;return!0}rawInput(){return this._components.map((t=>t.rawInput()))}rawInputSerialized(){return this._components.map((t=>t.rawInputSerialized()))}_copy_value(t){for(let e=0;ee))}}processRawInput(){const t=this.scene().cooker;t.block();const e=this.components;for(let t of e)t.emitController.blockParentEmit();const n=this._raw_input;let i=0;if(m.isArray(n))for(let t=0;t linear\\\\\\\",t.LINEAR_TO_GAMMA=\\\\\\\"linear -> gamma\\\\\\\",t.SRGB_TO_LINEAR=\\\\\\\"sRGB -> linear\\\\\\\",t.LINEAR_TO_SRGB=\\\\\\\"linear -> sRGB\\\\\\\"}(lo||(lo={}));lo.NONE,lo.GAMMA_TO_LINEAR,lo.LINEAR_TO_GAMMA,lo.SRGB_TO_LINEAR,lo.LINEAR_TO_SRGB;class co{static set_hsv(t,e,n,i){t=Object(On.f)(t,1),e=Object(On.d)(e,0,1),n=Object(On.d)(n,0,1),i.setHSL(t,e*n/((t=(2-e)*n)<1?t:2-t),.5*t)}}const ho=[\\\\\\\"r\\\\\\\",\\\\\\\"g\\\\\\\",\\\\\\\"b\\\\\\\"];class uo extends ro{static type(){return Cr.INTEGER}defaultValueSerialized(){return this._default_value}rawInputSerialized(){return this._raw_input}valueSerialized(){return this.value}_copy_value(t){this.set(t.valueSerialized())}_prefilter_invalid_raw_input(t){return m.isArray(t)?t[0]:m.isString(t)&&ss.isNumber(t)?parseInt(t):t}static are_raw_input_equal(t,e){return t==e}static are_values_equal(t,e){return t==e}static convert(t){if(m.isNumber(t))return Math.round(t);if(m.isBoolean(t))return t?1:0;if(ss.isNumber(t)){const e=parseInt(t);if(m.isNumber(e))return e}return null}convert(t){const e=uo.convert(t);return e?this.options.ensureInRange(e):e}}class po{constructor(){this._index=-1,this._path_elements=[],this._named_nodes=[],this._graph_node_ids=[],this._node_element_by_graph_node_id=new Map}reset(){this._index=-1,this._path_elements=[],this._named_nodes=[],this._graph_node_ids=[],this._node_element_by_graph_node_id.clear()}add_node(t,e){this._index+=1,t==e.name()&&(this._named_nodes[this._index]=e),this._graph_node_ids[this._index]=e.graphNodeId(),this._node_element_by_graph_node_id.set(e.graphNodeId(),t)}add_path_element(t){this._index+=1,this._path_elements[this._index]=t}named_graph_nodes(){return this._named_nodes}named_nodes(){const t=[];for(let e of this._named_nodes)if(e){const n=e;n.nameController&&t.push(n)}return t}update_from_name_change(t){this._named_nodes.map((t=>null==t?void 0:t.graphNodeId())).includes(t.graphNodeId())&&this._node_element_by_graph_node_id.set(t.graphNodeId(),t.name())}to_path(){const t=new Array(this._index);for(let e=0;e<=this._index;e++){const n=this._named_nodes[e];if(n){const i=this._node_element_by_graph_node_id.get(n.graphNodeId());i&&(t[e]=i)}else{const n=this._path_elements[e];n&&(t[e]=n)}}let e=t.join(bi.SEPARATOR);const n=e[0];return n&&(bi.NON_LETTER_PREFIXES.includes(n)||(e=`${bi.SEPARATOR}${e}`)),e}}class _o extends Vr{constructor(){super(...arguments),this.decomposed_path=new po}_handleReferences(t,e){this.scene().referencesController.setNamedNodesFromParam(this),t?this.scene().referencesController.setReferenceFromParam(this,t):this.scene().missingExpressionReferencesController.register(this,e)}}var mo;!function(t){t.NODE=\\\\\\\"NODE\\\\\\\",t.PARAM=\\\\\\\"PARAM\\\\\\\"}(mo||(mo={}));class fo extends _o{constructor(){super(...arguments),this._found_node=null,this._found_node_with_expected_type=null,this._found_param=null,this._found_param_with_expected_type=null}static type(){return Cr.OPERATOR_PATH}defaultValueSerialized(){return this._default_value}rawInputSerialized(){return`${this._raw_input}`}valueSerialized(){return`${this.value}`}_copy_value(t){this.set(t.valueSerialized())}static are_raw_input_equal(t,e){return t==e}static are_values_equal(t,e){return t==e}isDefault(){return this._value==this._default_value}setNode(t){this.set(t.path())}processRawInput(){this._value!=this._raw_input&&(this._value=this._raw_input,this.setDirty(),this.emitController.emit(Nr.VALUE_UPDATED))}async processComputation(){this.find_target()}find_target(){if(!this.node)return;const t=this._value;let e=null,n=null;const i=null!=t&&\\\\\\\"\\\\\\\"!==t,s=this.options.paramSelectionOptions()?mo.PARAM:mo.NODE;this.scene().referencesController.resetReferenceFromParam(this),this.decomposed_path.reset(),i&&(s==mo.PARAM?n=bi.findParam(this.node,t,this.decomposed_path):e=bi.findNode(this.node,t,this.decomposed_path));const r=s==mo.PARAM?this._found_param:this._found_node,o=s==mo.PARAM?n:e;if(this._handleReferences(e,t),(null==r?void 0:r.graphNodeId())!==(null==o?void 0:o.graphNodeId())){const t=this.options.dependentOnFoundNode();this._found_node&&t&&this.removeGraphInput(this._found_node),s==mo.PARAM?(this._found_param=n,this._found_node=null):(this._found_node=e,this._found_param=null),e&&this._assign_found_node(e),n&&this._assign_found_param(n),this.options.executeCallback()}this.removeDirtyState()}_assign_found_node(t){const e=this.options.dependentOnFoundNode();this._is_node_expected_context(t)?this._is_node_expected_type(t)?(this._found_node_with_expected_type=t,e&&this.addGraphInput(t)):this.states.error.set(`node type is ${t.type()} but the params expects one of ${(this._expected_node_types()||[]).join(\\\\\\\", \\\\\\\")}`):this.states.error.set(`node context is ${t.context()} but the params expects a ${this._expected_context()}`)}_assign_found_param(t){this._is_param_expected_type(t)?this._found_param_with_expected_type=t:this.states.error.set(`param type is ${t.type()} but the params expects a ${this._expected_param_type()}`)}found_node(){return this._found_node}found_param(){return this._found_param}found_node_with_context(t){return this._found_node_with_expected_type}found_node_with_context_and_type(t,e){const n=this.found_node_with_context(t);if(n)if(m.isArray(e)){for(let t of e)if(n.type()==t)return n;this.states.error.set(`expected node type to be ${e.join(\\\\\\\", \\\\\\\")}, but was instead ${n.type()}`)}else{const t=e;if(n.type()==t)return n;this.states.error.set(`expected node type to be ${t}, but was instead ${n.type()}`)}}found_param_with_type(t){if(this._found_param_with_expected_type)return this._found_param_with_expected_type}found_node_with_expected_type(){return this._found_node_with_expected_type}_expected_context(){return this.options.nodeSelectionContext()}_is_node_expected_context(t){var e,n;const i=this._expected_context();if(null==i)return!0;return i==(null===(n=null===(e=t.parent())||void 0===e?void 0:e.childrenController)||void 0===n?void 0:n.context)}_expected_node_types(){return this.options.nodeSelectionTypes()}_expected_param_type(){return this.options.paramSelectionType()}_is_node_expected_type(t){const e=this._expected_node_types();return null==e||(null==e?void 0:e.includes(t.type()))}_is_param_expected_type(t){const e=this._expected_node_types();return null==e||e.includes(t.type())}notifyPathRebuildRequired(t){this.decomposed_path.update_from_name_change(t);const e=this.decomposed_path.to_path();this.set(e)}notifyTargetParamOwnerParamsUpdated(t){this.setDirty()}}var go,vo=n(34),yo=n(70);class xo{constructor(t=0,e=0){this._position=t,this._value=e}toJSON(){return{position:this._position,value:this._value}}position(){return this._position}value(){return this._value}copy(t){this._position=t.position(),this._value=t.value()}clone(){const t=new xo;return t.copy(this),t}isEqual(t){return this._position==t.position()&&this._value==t.value()}isEqualJSON(t){return this._position==t.position&&this._value==t.value}fromJSON(t){this._position=t.position,this._value=t.value}static areEqualJSON(t,e){return t.position==e.position&&t.value==e.value}static fromJSON(t){return new xo(t.position,t.value)}}!function(t){t.LINEAR=\\\\\\\"linear\\\\\\\"}(go||(go={}));class bo{constructor(t=go.LINEAR,e=[]){this._interpolation=t,this._points=e,this._uuid=Object(On.h)()}uuid(){return this._uuid}interpolation(){return this._interpolation}points(){return this._points}static fromJSON(t){const e=[];for(let n of t.points)e.push(xo.fromJSON(n));return new bo(t.interpolation,e)}toJSON(){return{interpolation:this._interpolation,points:this._points.map((t=>t.toJSON()))}}clone(){const t=new bo;return t.copy(this),t}copy(t){this._interpolation=t.interpolation();let e=0;for(let n of t.points()){const t=this._points[e];t?t.copy(n):this._points.push(n.clone()),e+=1}}is_equal(t){if(this._interpolation!=t.interpolation())return!1;const e=t.points();if(this._points.length!=e.length)return!1;let n=0;for(let t of this._points){const i=e[n];if(!t.isEqual(i))return!1;n+=1}return!0}is_equal_json(t){if(this._interpolation!=t.interpolation)return!1;if(this._points.length!=t.points.length)return!1;let e=0;for(let n of this._points){const i=t.points[e];if(!n.isEqualJSON(i))return!1;e+=1}return!0}static are_json_equal(t,e){if(t.interpolation!=e.interpolation)return!1;if(t.points.length!=e.points.length)return!1;let n=0;for(let i of t.points){const t=e.points[n];if(!xo.areEqualJSON(i,t))return!1;n+=1}return!0}from_json(t){this._interpolation=t.interpolation;let e=0;for(let n of t.points){const t=this._points[e];t?t.fromJSON(n):this._points.push(xo.fromJSON(n)),e+=1}}}const wo=1024,To=255;class Ao extends Vr{constructor(){super(...arguments),this._texture_data=new Uint8Array(3072),this._ramp_texture=new vo.a(this._texture_data,wo,1,w.ic)}static type(){return Cr.RAMP}defaultValueSerialized(){return this._default_value instanceof bo?this._default_value.toJSON():this._default_value}_clone_raw_input(t){return t instanceof bo?t.clone():bo.fromJSON(t).toJSON()}rawInputSerialized(){return this._raw_input instanceof bo?this._raw_input.toJSON():bo.fromJSON(this._raw_input).toJSON()}valueSerialized(){return this.value.toJSON()}_copy_value(t){this.set(t.valueSerialized())}static are_raw_input_equal(t,e){return t instanceof bo?e instanceof bo?t.is_equal(e):t.is_equal_json(e):e instanceof bo?e.is_equal_json(t):bo.are_json_equal(t,e)}static are_values_equal(t,e){return t.is_equal(e)}isDefault(){return this._default_value instanceof bo?this.value.is_equal(this._default_value):this.value.is_equal_json(this._default_value)}processRawInput(){this._raw_input instanceof bo?this._value?this._value.copy(this._raw_input):this._value=this._raw_input:this._value?this._value.from_json(this._raw_input):this._value=bo.fromJSON(this._raw_input),this._resetRampInterpolant(),this._updateRampTexture(),this.options.executeCallback(),this.emitController.emit(Nr.VALUE_UPDATED),this.setSuccessorsDirty(this)}hasExpression(){return!1}_resetRampInterpolant(){this._ramp_interpolant=void 0}rampTexture(){return this._ramp_texture}_updateRampTexture(){this._updateRampTextureData(),this.rampTexture().needsUpdate=!0}_updateRampTextureData(){let t=0,e=0,n=0;for(var i=0;i<1024;i++)t=3*i,e=i/wo,n=this.valueAtPosition(e),n<=0?(this._texture_data[t+0]=(Object(On.d)(n,-1,0)+1)*To,this._texture_data[t+1]=0,this._texture_data[t+2]=0):n<=1?(this._texture_data[t+0]=To,this._texture_data[t+1]=Object(On.d)(n,0,1)*To,this._texture_data[t+2]=0):(this._texture_data[t+0]=To,this._texture_data[t+1]=To,this._texture_data[t+2]=(Object(On.d)(n,1,2)-1)*To)}static createInterpolant(t,e){const n=new Float32Array(1);return new yo.a(t,e,1,n)}interpolant(){return this._ramp_interpolant=this._ramp_interpolant||this._createInterpolant()}_createInterpolant(){const t=this.value.points(),e=f.sortBy(t,(t=>t.position())),n=new Float32Array(e.length),i=new Float32Array(e.length);let s=0;for(let t of e)n[s]=t.position(),i[s]=t.value(),s++;return Ao.createInterpolant(n,i)}valueAtPosition(t){return this.interpolant().evaluate(t)[0]}}Ao.DEFAULT_VALUE=new bo(go.LINEAR,[new xo(0,0),new xo(1,1)]),Ao.DEFAULT_VALUE_JSON=Ao.DEFAULT_VALUE.toJSON();class Mo extends Vr{static type(){return Cr.STRING}defaultValueSerialized(){return this._default_value}_clone_raw_input(t){return`${t}`}rawInputSerialized(){return`${this._raw_input}`}valueSerialized(){return`${this.value}`}_copy_value(t){this.set(t.value)}static are_raw_input_equal(t,e){return t==e}static are_values_equal(t,e){return t==e}isDefault(){return this._raw_input==this._default_value}convert(t){return m.isString(t)?t:`${t}`}rawInput(){return this._raw_input}processRawInput(){this.states.error.clear(),this._value_elements(this._raw_input).length>=3?(this._expression_controller=this._expression_controller||new so(this),this._raw_input!=this._expression_controller.expression()&&(this._expression_controller.set_expression(this._raw_input),this.setDirty(),this.emitController.emit(Nr.EXPRESSION_UPDATED))):this._raw_input!=this._value&&(this._value=this._raw_input,this.removeDirtyState(),this.setSuccessorsDirty(this),this.emitController.emit(Nr.VALUE_UPDATED),this.options.executeCallback(),this._expression_controller&&(this._expression_controller.set_expression(void 0,!1),this.emitController.emit(Nr.EXPRESSION_UPDATED)))}async processComputation(){var t;if((null===(t=this.expressionController)||void 0===t?void 0:t.active())&&!this.expressionController.requires_entities()){const t=await this.expressionController.computeExpression();if(this.expressionController.is_errored())this.states.error.set(`expression error: ${this.expressionController.error_message()}`);else{const e=this.convert(t);null!=e?(this._value=e,this.emitController.emit(Nr.VALUE_UPDATED),this.options.executeCallback()):this.states.error.set(`expression returns an invalid type (${t})`),this.removeDirtyState()}}}_value_elements(t){return Wr.string_value_elements(t)}}const Eo=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\"];const So=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\"];const Co=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\",\\\\\\\"w\\\\\\\"];const No={[Cr.BOOLEAN]:class extends ro{static type(){return Cr.BOOLEAN}defaultValueSerialized(){return m.isString(this._default_value)?this._default_value:this.convert(this._default_value)||!1}rawInputSerialized(){return this._raw_input}valueSerialized(){return this.value}_copy_value(t){this.set(t.value)}static are_raw_input_equal(t,e){return t==e}static are_values_equal(t,e){return t==e}convert(t){if(m.isBoolean(t))return t;if(m.isNumber(t))return t>=1;if(m.isString(t)){if(ss.isBoolean(t))return ss.toBoolean(t);if(ss.isNumber(t)){return parseFloat(t)>=1}}return null}},[Cr.BUTTON]:class extends Vr{static type(){return Cr.BUTTON}defaultValueSerialized(){return this._default_value}rawInputSerialized(){return this._raw_input}valueSerialized(){return this.value}_copy_value(t){}static are_raw_input_equal(t,e){return!0}static are_values_equal(t,e){return!0}async pressButton(){(this.node.isDirty()||this.node.cookController.isCooking())&&await this.node.compute(),this.options.executeCallback()}},[Cr.COLOR]:class extends ao{constructor(){super(...arguments),this._value=new D.a,this._value_pre_conversion=new D.a,this._value_serialized_dirty=!1,this._value_serialized=[0,0,0],this._value_pre_conversion_serialized=[0,0,0],this._copied_value=[0,0,0]}static type(){return Cr.COLOR}componentNames(){return ho}defaultValueSerialized(){return m.isArray(this._default_value)?this._default_value:this._default_value.toArray()}valueSerialized(){return this._update_value_serialized_if_required(),this._value_serialized}valuePreConversionSerialized(){return this._update_value_serialized_if_required(),this._value_pre_conversion_serialized}_copy_value(t){t.value.toArray(this._copied_value),this.set(this._copied_value)}_clone_raw_input(t){if(t instanceof D.a)return t.clone();{const e=[t[0],t[1],t[2]];return null==e[0]&&(e[0]=e[0]||0),null==e[1]&&(e[1]=e[1]||e[0]),null==e[2]&&(e[2]=e[2]||e[1]),e}}static are_raw_input_equal(t,e){return t instanceof D.a?e instanceof D.a?t.equals(e):t.r==e[0]&&t.g==e[1]&&t.b==e[2]:e instanceof D.a?t[0]==e.r&&t[1]==e.g&&t[2]==e.b:t[0]==e[0]&&t[1]==e[1]&&t[2]==e[2]}static are_values_equal(t,e){return t.equals(e)}initComponents(){super.initComponents(),this.r=this.components[0],this.g=this.components[1],this.b=this.components[2],this._value_serialized_dirty=!0}_update_value_serialized_if_required(){this._value_serialized_dirty&&(this._value_serialized[0]=this._value.r,this._value_serialized[1]=this._value.g,this._value_serialized[2]=this._value.b,this._value_pre_conversion_serialized[0]=this._value_pre_conversion.r,this._value_pre_conversion_serialized[1]=this._value_pre_conversion.g,this._value_pre_conversion_serialized[2]=this._value_pre_conversion.b)}valuePreConversion(){return this._value_pre_conversion}set_value_from_components(){this._value_pre_conversion.r=this.r.value,this._value_pre_conversion.g=this.g.value,this._value_pre_conversion.b=this.b.value,this._value.copy(this._value_pre_conversion);const t=this.options.colorConversion();if(null!=t&&t!=lo.NONE){switch(t){case lo.GAMMA_TO_LINEAR:return void this._value.convertGammaToLinear();case lo.LINEAR_TO_GAMMA:return void this._value.convertLinearToGamma();case lo.SRGB_TO_LINEAR:return void this._value.convertSRGBToLinear();case lo.LINEAR_TO_SRGB:return void this._value.convertLinearToSRGB()}os.unreachable(t)}this._value_serialized_dirty=!0}},[Cr.FLOAT]:oo,[Cr.FOLDER]:class extends Vr{static type(){return Cr.FOLDER}defaultValueSerialized(){return this._default_value}rawInputSerialized(){return this._raw_input}valueSerialized(){return this.value}_copy_value(t){}static are_raw_input_equal(t,e){return!0}static are_values_equal(t,e){return!0}},[Cr.INTEGER]:uo,[Cr.OPERATOR_PATH]:fo,[Cr.PARAM_PATH]:class extends _o{static type(){return Cr.PARAM_PATH}initialize_param(){this._value=new xi}defaultValueSerialized(){return this._default_value}rawInputSerialized(){return`${this._raw_input}`}valueSerialized(){return`${this.value}`}_copy_value(t){this.set(t.valueSerialized())}static are_raw_input_equal(t,e){return t==e}static are_values_equal(t,e){return t==e}isDefault(){return this._raw_input==this._default_value}setParam(t){this.set(t.path())}processRawInput(){this._value.path()!=this._raw_input&&(this._value.set_path(this._raw_input),this.find_target(),this.setDirty(),this.emitController.emit(Nr.VALUE_UPDATED))}async processComputation(){this.find_target()}find_target(){if(!this.node)return;const t=this._raw_input;let e=null;const n=null!=t&&\\\\\\\"\\\\\\\"!==t;this.scene().referencesController.resetReferenceFromParam(this),this.decomposed_path.reset(),n&&(e=bi.findParam(this.node,t,this.decomposed_path));const i=this._value.param(),s=e;if(this._handleReferences(e,t),(null==i?void 0:i.graphNodeId())!==(null==s?void 0:s.graphNodeId())){const t=this.options.dependentOnFoundNode(),n=this._value.param();n&&t&&this.removeGraphInput(n),e?this._assign_found_node(e):this._value.set_param(null),this.options.executeCallback()}this.removeDirtyState()}_assign_found_node(t){const e=this.options.dependentOnFoundNode();this._value.set_param(t),e&&this.addGraphInput(t)}notifyPathRebuildRequired(t){this.decomposed_path.update_from_name_change(t);const e=this.decomposed_path.to_path();this.set(e)}notifyTargetParamOwnerParamsUpdated(t){this.setDirty()}},[Cr.NODE_PATH]:class extends _o{static type(){return Cr.NODE_PATH}initialize_param(){this._value=new yi}defaultValueSerialized(){return this._default_value}rawInputSerialized(){return`${this._raw_input}`}valueSerialized(){return`${this.value}`}_copy_value(t){this.set(t.valueSerialized())}static are_raw_input_equal(t,e){return t==e}static are_values_equal(t,e){return t==e}isDefault(){return this._raw_input==this._default_value}setNode(t){this.set(t.path())}processRawInput(){this._value.path()!=this._raw_input&&(this._value.set_path(this._raw_input),this._findTarget(),this.setDirty(),this.emitController.emit(Nr.VALUE_UPDATED))}async processComputation(){this._findTarget()}_findTarget(){if(!this.node)return;const t=this._raw_input;let e=null;const n=null!=t&&\\\\\\\"\\\\\\\"!==t;this.scene().referencesController.resetReferenceFromParam(this),this.decomposed_path.reset(),n&&(e=bi.findNode(this.node,t,this.decomposed_path));const i=this._value.node(),s=e;if(this._handleReferences(e,t),(null==i?void 0:i.graphNodeId())!==(null==s?void 0:s.graphNodeId())){const t=this.options.dependentOnFoundNode(),n=this._value.node();n&&t&&this.removeGraphInput(n),e?this._assign_found_node(e):this._value.set_node(null),this.options.executeCallback()}n&&!e&&this.scene().loadingController.loaded()&&n&&this.states.error.set(`no node found at path '${t}'`),this.removeDirtyState()}_assign_found_node(t){const e=this.options.dependentOnFoundNode();this._isNodeExpectedContext(t)?this._is_node_expected_type(t)?(this.states.error.clear(),this._value.set_node(t),e&&this.addGraphInput(t)):this.states.error.set(`node type is ${t.type()} but the params expects one of ${(this._expected_node_types()||[]).join(\\\\\\\", \\\\\\\")}`):this.states.error.set(`node context is ${t.context()} but the params expects a ${this._expectedContext()}`)}_expectedContext(){return this.options.nodeSelectionContext()}_isNodeExpectedContext(t){var e,n;const i=this._expectedContext();if(null==i)return!0;return i==(null===(n=null===(e=t.parent())||void 0===e?void 0:e.childrenController)||void 0===n?void 0:n.context)}_expected_node_types(){return this.options.nodeSelectionTypes()}_is_node_expected_type(t){const e=this._expected_node_types();return null==e||(null==e?void 0:e.includes(t.type()))}notifyPathRebuildRequired(t){this.decomposed_path.update_from_name_change(t);const e=this.decomposed_path.to_path();this.set(e)}notifyTargetParamOwnerParamsUpdated(t){this.setDirty()}},[Cr.RAMP]:Ao,[Cr.STRING]:Mo,[Cr.VECTOR2]:class extends ao{constructor(){super(...arguments),this._value=new d.a,this._copied_value=[0,0]}static type(){return Cr.VECTOR2}componentNames(){return Eo}defaultValueSerialized(){return m.isArray(this._default_value)?this._default_value:this._default_value.toArray()}valueSerialized(){return this.value.toArray()}_copy_value(t){t.value.toArray(this._copied_value),this.set(this._copied_value)}_clone_raw_input(t){if(t instanceof d.a)return t.clone();{const e=[t[0],t[1]];return null==e[0]&&(e[0]=e[0]||0),null==e[1]&&(e[1]=e[1]||e[0]),e}}static are_raw_input_equal(t,e){return t instanceof d.a?e instanceof d.a?t.equals(e):t.x==e[0]&&t.y==e[1]:e instanceof d.a?t[0]==e.x&&t[1]==e.y:t[0]==e[0]&&t[1]==e[1]}static are_values_equal(t,e){return t.equals(e)}initComponents(){super.initComponents(),this.x=this.components[0],this.y=this.components[1]}set_value_from_components(){this._value.x=this.x.value,this._value.y=this.y.value}},[Cr.VECTOR3]:class extends ao{constructor(){super(...arguments),this._value=new p.a,this._copied_value=[0,0,0]}static type(){return Cr.VECTOR3}componentNames(){return So}defaultValueSerialized(){return m.isArray(this._default_value)?this._default_value:this._default_value.toArray()}valueSerialized(){return this.value.toArray()}_copy_value(t){t.value.toArray(this._copied_value),this.set(this._copied_value)}_clone_raw_input(t){if(t instanceof p.a)return t.clone();{const e=[t[0],t[1],t[2]];return null==e[0]&&(e[0]=e[0]||0),null==e[1]&&(e[1]=e[1]||e[0]),null==e[2]&&(e[2]=e[2]||e[1]),e}}static are_raw_input_equal(t,e){return t instanceof p.a?e instanceof p.a?t.equals(e):t.x==e[0]&&t.y==e[1]&&t.z==e[2]:e instanceof p.a?t[0]==e.x&&t[1]==e.y&&t[2]==e.z:t[0]==e[0]&&t[1]==e[1]&&t[2]==e[2]}static are_values_equal(t,e){return t.equals(e)}initComponents(){super.initComponents(),this.x=this.components[0],this.y=this.components[1],this.z=this.components[2]}set_value_from_components(){this._value.x=this.x.value,this._value.y=this.y.value,this._value.z=this.z.value}},[Cr.VECTOR4]:class extends ao{constructor(){super(...arguments),this._value=new _.a,this._copied_value=[0,0,0,0]}static type(){return Cr.VECTOR4}componentNames(){return Co}defaultValueSerialized(){return m.isArray(this._default_value)?this._default_value:this._default_value.toArray()}valueSerialized(){return this.value.toArray()}_copy_value(t){t.value.toArray(this._copied_value),this.set(this._copied_value)}_clone_raw_input(t){if(t instanceof _.a)return t.clone();{const e=[t[0],t[1],t[2],t[3]];return null==e[0]&&(e[0]=e[0]||0),null==e[1]&&(e[1]=e[1]||e[0]),null==e[2]&&(e[2]=e[2]||e[1]),null==e[3]&&(e[3]=e[3]||e[2]),e}}static are_raw_input_equal(t,e){return t instanceof _.a?e instanceof _.a?t.equals(e):t.x==e[0]&&t.y==e[1]&&t.z==e[2]&&t.w==e[3]:e instanceof _.a?t[0]==e.x&&t[1]==e.y&&t[2]==e.z&&t[3]==e.w:t[0]==e[0]&&t[1]==e[1]&&t[2]==e[2]&&t[3]==e[3]}static are_values_equal(t,e){return t.equals(e)}initComponents(){super.initComponents(),this.x=this.components[0],this.y=this.components[1],this.z=this.components[2],this.w=this.components[3]}set_value_from_components(){this._value.x=this.x.value,this._value.y=this.y.value,this._value.z=this.z.value,this._value.w=this.w.value}}};class Lo{dispose(){this._callback=void 0}params(){return this._params}callback(){return this._callback}init(t,e){if(this._params=t,e)this._callback=e;else{const t=this._params[0];switch(t.type()){case Cr.STRING:return this._handle_string_param(t);case Cr.OPERATOR_PATH:return this._handle_operator_path_param(t);case Cr.NODE_PATH:return this._handle_node_path_param(t);case Cr.PARAM_PATH:return this._handle_param_path_param(t);case Cr.FLOAT:case Cr.INTEGER:return this._handle_number_param(t)}}}_handle_string_param(t){this._callback=()=>t.value}_handle_operator_path_param(t){this._callback=()=>t.value}_handle_node_path_param(t){this._callback=()=>t.value.path()}_handle_param_path_param(t){this._callback=()=>t.value.path()}_handle_number_param(t){this._callback=()=>`${t.value}`}}class Oo{constructor(t){this.node=t,this._param_create_mode=!1,this._params_created=!1,this._params_by_name={},this._params_list=[],this._param_names=[],this._non_spare_params=[],this._spare_params=[],this._non_spare_param_names=[],this._spare_param_names=[],this._params_added_since_last_params_eval=!1}get label(){return this._label_controller=this._label_controller||new Lo}hasLabelController(){return null!=this._label_controller}dispose(){var t;this._params_node&&this._params_node.dispose();for(let t of this.all)t.dispose();this._post_create_params_hook_names=void 0,this._post_create_params_hooks=void 0,this._on_scene_load_hooks=void 0,this._on_scene_load_hook_names=void 0,null===(t=this._label_controller)||void 0===t||t.dispose()}initDependencyNode(){this._params_node||(this._params_node=new Mi(this.node.scene(),\\\\\\\"params\\\\\\\"),this.node.addGraphInput(this._params_node,!1))}init(){this.initDependencyNode(),this._param_create_mode=!0,this._initFromParamsConfig(),this.node.createParams(),this._postCreateParams()}_postCreateParams(){this._updateCaches(),this._initParamAccessors(),this._param_create_mode=!1,this._params_created=!0,this._runPostCreateParamsHooks()}postCreateSpareParams(){this._updateCaches(),this._initParamAccessors(),this.node.scene().referencesController.notifyParamsUpdated(this.node),this.node.emit(Ei.PARAMS_UPDATED)}updateParams(t){let e=!1,n=!1;if(t.namesToDelete)for(let e of t.namesToDelete)this.has(e)&&(this._deleteParam(e),n=!0);if(t.toAdd)for(let n of t.toAdd){const t=this.addParam(n.type,n.name,n.init_value,n.options);t&&(null!=n.raw_input&&t.set(n.raw_input),e=!0)}(n||e)&&this.postCreateSpareParams()}_initFromParamsConfig(){const t=this.node.paramsConfig;let e=!1;if(t)for(let n of Object.keys(t)){const i=t[n];let s;this.node.params_init_value_overrides&&(s=this.node.params_init_value_overrides[n],e=!0),this.addParam(i.type,n,i.init_value,i.options,s)}e&&this.node.setDirty(),this.node.params_init_value_overrides=void 0}_initParamAccessors(){let t=Object.getOwnPropertyNames(this.node.pv);this._removeUnneededAccessors(t),t=Object.getOwnPropertyNames(this.node.pv);for(let e of this.all){const n=e.options.isSpare();(!t.includes(e.name())||n)&&(Object.defineProperty(this.node.pv,e.name(),{get:()=>e.value,configurable:n}),Object.defineProperty(this.node.p,e.name(),{get:()=>e,configurable:n}))}}_removeUnneededAccessors(t){const e=this._param_names,n=[];for(let i of t)e.includes(i)||n.push(i);for(let t of n)Object.defineProperty(this.node.pv,t,{get:()=>{},configurable:!0}),Object.defineProperty(this.node.p,t,{get:()=>{},configurable:!0})}get params_node(){return this._params_node}get all(){return this._params_list}get non_spare(){return this._non_spare_params}get spare(){return this._spare_params}get names(){return this._param_names}get non_spare_names(){return this._non_spare_param_names}get spare_names(){return this._spare_param_names}set_with_type(t,e,n){const i=this.param_with_type(t,n);i?i.set(e):li.warn(`param ${t} not found with type ${n}`)}set_float(t,e){this.set_with_type(t,e,Cr.FLOAT)}set_vector3(t,e){this.set_with_type(t,e,Cr.VECTOR3)}has_param(t){return null!=this._params_by_name[t]}has(t){return this.has_param(t)}get(t){return this.param(t)}param_with_type(t,e){const n=this.param(t);if(n&&n.type()==e)return n}get_float(t){return this.param_with_type(t,Cr.FLOAT)}get_operator_path(t){return this.param_with_type(t,Cr.OPERATOR_PATH)}value(t){var e;return null===(e=this.param(t))||void 0===e?void 0:e.value}value_with_type(t,e){var n;return null===(n=this.param_with_type(t,e))||void 0===n?void 0:n.value}boolean(t){return this.value_with_type(t,Cr.BOOLEAN)}float(t){return this.value_with_type(t,Cr.FLOAT)}integer(t){return this.value_with_type(t,Cr.INTEGER)}string(t){return this.value_with_type(t,Cr.STRING)}vector2(t){return this.value_with_type(t,Cr.VECTOR2)}vector3(t){return this.value_with_type(t,Cr.VECTOR3)}color(t){return this.value_with_type(t,Cr.COLOR)}param(t){const e=this._params_by_name[t];return null!=e?e:(li.warn(`tried to access param '${t}' in node ${this.node.path()}, but existing params are: ${this.names} on node ${this.node.path()}`),null)}_deleteParam(t){const e=this._params_by_name[t];if(!e)throw new Error(`param '${t}' does not exist on node ${this.node.path()}`);if(this._params_node&&this._params_node.removeGraphInput(this._params_by_name[t]),e._setupNodeDependencies(null),delete this._params_by_name[t],e.isMultiple()&&e.components)for(let t of e.components){const e=t.name();delete this._params_by_name[e]}}addParam(t,e,n,i={},s){const r=i.spare||!1;!1!==this._param_create_mode||r||li.warn(`node ${this.node.path()} (${this.node.type()}) param '${e}' cannot be created outside of create_params`),null==this.node.scene()&&li.warn(`node ${this.node.path()} (${this.node.type()}) has no scene assigned`);const o=No[t];if(null!=o){const a=this._params_by_name[e];a&&(r?a.type()!=t&&this._deleteParam(a.name()):li.warn(`a param named ${e} already exists`,this.node));const l=new o(this.node.scene(),this.node);if(l.options.set(i),l.setName(e),l.setInitValue(n),l.initComponents(),null==s)l.set(n);else if(l.options.isExpressionForEntities()&&l.set(n),null!=s.raw_input)l.set(s.raw_input);else if(null!=s.simple_data)l.set(s.simple_data);else if(null!=s.complex_data){const t=s.complex_data.raw_input;t?l.set(t):l.set(n);const e=s.complex_data.overriden_options;if(null!=e){const t=Object.keys(e);for(let n of t)l.options.setOption(n,e[n])}}if(l._setupNodeDependencies(this.node),this._params_by_name[l.name()]=l,l.isMultiple()&&l.components)for(let t of l.components)this._params_by_name[t.name()]=t;return this._params_added_since_last_params_eval=!0,l}}_updateCaches(){this._params_list=Object.values(this._params_by_name),this._param_names=Object.keys(this._params_by_name),this._non_spare_params=Object.values(this._params_by_name).filter((t=>!t.options.isSpare())),this._spare_params=Object.values(this._params_by_name).filter((t=>t.options.isSpare())),this._non_spare_param_names=Object.values(this._params_by_name).filter((t=>!t.options.isSpare())).map((t=>t.name())),this._spare_param_names=Object.values(this._params_by_name).filter((t=>t.options.isSpare())).map((t=>t.name()))}async _evalParam(t){t.isDirty()&&(await t.compute(),t.states.error.active()&&this.node.states.error.set(`param '${t.name()}' error: ${t.states.error.message()}`))}async evalParams(t){const e=[];for(let n of t)n.isDirty()&&e.push(this._evalParam(n));await Promise.all(e),this.node.states.error.active()&&this.node._setContainer(null)}paramsEvalRequired(){return null!=this._params_node&&(this._params_node.isDirty()||this._params_added_since_last_params_eval)}async evalAll(){var t;this.paramsEvalRequired()&&(await this.evalParams(this._params_list),null===(t=this._params_node)||void 0===t||t.removeDirtyState(),this._params_added_since_last_params_eval=!1)}onParamsCreated(t,e){if(this._params_created)e();else{if(this._post_create_params_hook_names&&this._post_create_params_hook_names.includes(t))return void li.error(`hook name ${t} already exists`);this._post_create_params_hook_names=this._post_create_params_hook_names||[],this._post_create_params_hook_names.push(t),this._post_create_params_hooks=this._post_create_params_hooks||[],this._post_create_params_hooks.push(e)}}addOnSceneLoadHook(t,e){this._on_scene_load_hook_names=this._on_scene_load_hook_names||[],this._on_scene_load_hooks=this._on_scene_load_hooks||[],this._on_scene_load_hook_names.includes(t)?li.warn(`hook with name ${t} already exists`,this.node):(this._on_scene_load_hook_names.push(t),this._on_scene_load_hooks.push(e))}_runPostCreateParamsHooks(){if(this._post_create_params_hooks)for(let t of this._post_create_params_hooks)t()}runOnSceneLoadHooks(){if(this._on_scene_load_hooks)for(let t of this._on_scene_load_hooks)t()}}class Po{constructor(){}}class Ro{constructor(t,e,n=0,i=0){if(this._node_src=t,this._node_dest=e,this._output_index=n,this._input_index=i,null==this._output_index)throw\\\\\\\"bad output index\\\\\\\";if(null==this._input_index)throw\\\\\\\"bad input index\\\\\\\";this._id=Ro._next_id++,this._node_src.io.connections&&this._node_dest.io.connections&&(this._node_src.io.connections.addOutputConnection(this),this._node_dest.io.connections.addInputConnection(this))}get id(){return this._id}get node_src(){return this._node_src}get node_dest(){return this._node_dest}get output_index(){return this._output_index}get input_index(){return this._input_index}src_connection_point(){const t=this._node_src,e=this._output_index;return t.io.outputs.namedOutputConnectionPoints()[e]}dest_connection_point(){const t=this._node_dest,e=this._input_index;return t.io.inputs.namedInputConnectionPoints()[e]}disconnect(t={}){this._node_src.io.connections&&this._node_dest.io.connections&&(this._node_src.io.connections.removeOutputConnection(this),this._node_dest.io.connections.removeInputConnection(this)),!0===t.setInput&&this._node_dest.io.inputs.setInput(this._input_index,null)}}Ro._next_id=0;class Io{constructor(t){this.inputs_controller=t,this._clone_required_states=[],this._overridden=!1,this.node=t.node}initInputsClonedState(t){m.isArray(t)?this._cloned_states=t:this._cloned_state=t,this._update_clone_required_state()}overrideClonedStateAllowed(){if(this._cloned_states)for(let t of this._cloned_states)if(t==Ki.FROM_NODE)return!0;return!!this._cloned_state&&this._cloned_state==Ki.FROM_NODE}cloneRequiredState(t){return this._clone_required_states[t]}cloneRequiredStates(){return this._clone_required_states}_get_clone_required_state(t){const e=this._cloned_states;if(e){const n=e[t];if(null!=n)return this.clone_required_from_state(n)}return!this._cloned_state||this.clone_required_from_state(this._cloned_state)}clone_required_from_state(t){switch(t){case Ki.ALWAYS:return!0;case Ki.NEVER:return!1;case Ki.FROM_NODE:return!this._overridden}return os.unreachable(t)}overrideClonedState(t){this._overridden=t,this._update_clone_required_state(),this.node.emit(Ei.OVERRIDE_CLONABLE_STATE_UPDATE),this.node.setDirty()}overriden(){return this._overridden}_update_clone_required_state(){if(this._cloned_states){const t=[];for(let e=0;e=t.length&&n.disconnect({setInput:!0});this._named_input_connection_points=t,this.setMinCount(0),this.setMaxCount(t.length),this._initGraphNodeInputs(),this.node.emit(Ei.NAMED_INPUTS_UPDATED)}hasNamedInputs(){return this._has_named_inputs}namedInputConnectionPoints(){return this._named_input_connection_points||[]}_initGraphNodeInputs(){for(let t=0;t0)for(let e=0;e0){const n=this.existing_input_indices();if(n.length0){const n=[];let i;for(let t=0;tt.name()));return void console.warn(`node ${e.path()} does not have an output named ${n}. inputs are: ${t.join(\\\\\\\", \\\\\\\")}`)}const r=this._graph_node_inputs[i];if(null==r){const t=`graph_input_node not found at index ${i}`;throw console.warn(t),new Error(t)}if(e&&this.node.parent()!=e.parent())return;const o=this._inputs[i];let a,l=null;this.node.io.connections&&(a=this.node.io.connections.inputConnection(i)),a&&(l=a.output_index),e===o&&s==l||(null!=o&&this._depends_on_inputs&&r.removeGraphInput(o),null!=e?r.addGraphInput(e)?(this._depends_on_inputs||r.removeGraphInput(e),a&&a.disconnect({setInput:!1}),this._inputs[i]=e,new Ro(e,this.node,s,i)):console.warn(`cannot connect ${e.path()} to ${this.node.path()}`):(this._inputs[i]=null,a&&a.disconnect({setInput:!1})),this._run_on_set_input_hooks(),r.setSuccessorsDirty(),this.node.emit(Ei.INPUTS_UPDATED))}remove_input(t){const e=this.inputs();let n;for(let i=0;i=0}has_input(t){return null!=this._inputs[t]}inputs(){return this._inputs}initInputsClonedState(t){this._cloned_states_controller||(this._cloned_states_controller=new Io(this),this._cloned_states_controller.initInputsClonedState(t))}overrideClonedStateAllowed(){var t;return(null===(t=this._cloned_states_controller)||void 0===t?void 0:t.overrideClonedStateAllowed())||!1}overrideClonedState(t){var e;null===(e=this._cloned_states_controller)||void 0===e||e.overrideClonedState(t)}clonedStateOverriden(){var t;return(null===(t=this._cloned_states_controller)||void 0===t?void 0:t.overriden())||!1}cloneRequired(t){var e;const n=null===(e=this._cloned_states_controller)||void 0===e?void 0:e.cloneRequiredState(t);return null==n||n}cloneRequiredStates(){var t;const e=null===(t=this._cloned_states_controller)||void 0===t?void 0:t.cloneRequiredStates();return null==e||e}add_on_set_input_hook(t,e){this._on_update_hooks=this._on_update_hooks||[],this._on_update_hook_names=this._on_update_hook_names||[],this._on_update_hook_names.includes(t)?console.warn(`hook with name ${t} already exists`,this.node):(this._on_update_hooks.push(e),this._on_update_hook_names.push(t))}_run_on_set_input_hooks(){if(this._on_update_hooks)for(let t of this._on_update_hooks)t()}}class Do{constructor(t){this.node=t,this._has_outputs=!1,this._has_named_outputs=!1}setHasOneOutput(){this._has_outputs=!0}setHasNoOutput(){this._has_outputs=!1}hasOutputs(){return this._has_outputs}hasNamedOutputs(){return this._has_named_outputs}hasNamedOutput(t){return this.getNamedOutputIndex(t)>=0}namedOutputConnectionPoints(){return this._named_output_connection_points||[]}namedOutputConnection(t){if(this._named_output_connection_points)return this._named_output_connection_points[t]}getNamedOutputIndex(t){var e;if(this._named_output_connection_points)for(let n=0;n=t.length&&e.disconnect({setInput:!0});this._named_output_connection_points=t,e&&this.node.scene()&&this.node.setDirty(this.node),this.node.emit(Ei.NAMED_OUTPUTS_UPDATED)}used_output_names(){var t;const e=this.node.io.connections;if(e){let n=e.outputConnections().map((t=>t?t.output_index:null));n=f.uniq(n);const i=[];n.forEach((t=>{m.isNumber(t)&&i.push(t)}));const s=[];for(let e of i){const n=null===(t=this.namedOutputConnectionPoints()[e])||void 0===t?void 0:t.name();n&&s.push(n)}return s}return[]}}class Bo{constructor(t){this._node=t,this._output_connections=new Map}initInputs(){const t=this._node.io.inputs.maxInputsCount();for(this._input_connections=this._input_connections||new Array(t);this._input_connections.length1&&void 0===t[t.length-1];)t.pop();return t}addOutputConnection(t){const e=t.output_index,n=t.id;let i=this._output_connections.get(e);i||(i=new Map,this._output_connections.set(e,i)),i.set(n,t)}removeOutputConnection(t){const e=t.output_index,n=t.id;let i=this._output_connections.get(e);i&&i.delete(n)}outputConnections(){let t=[];return this._output_connections.forEach(((e,n)=>{e.forEach(((e,n)=>{e&&t.push(e)}))})),t}}class zo{constructor(t){this._node=t}set_in(t){this._in=t}set_out(t){this._out=t}clear(){this._in=void 0,this._out=void 0}in(){return this._in}out(){return this._out}}class ko{constructor(t,e,n){this._name=t,this._type=e,this._init_value=n}get init_value(){return this._init_value}name(){return this._name}type(){return this._type}are_types_matched(t,e){return!0}toJSON(){return this._json=this._json||this._create_json()}_create_json(){return{name:this._name,type:this._type}}}var Uo;!function(t){t.BOOL=\\\\\\\"bool\\\\\\\",t.INT=\\\\\\\"int\\\\\\\",t.FLOAT=\\\\\\\"float\\\\\\\",t.VEC2=\\\\\\\"vec2\\\\\\\",t.VEC3=\\\\\\\"vec3\\\\\\\",t.VEC4=\\\\\\\"vec4\\\\\\\",t.SAMPLER_2D=\\\\\\\"sampler2D\\\\\\\",t.SSS_MODEL=\\\\\\\"SSSModel\\\\\\\"}(Uo||(Uo={}));const Go=[Uo.BOOL,Uo.INT,Uo.FLOAT,Uo.VEC2,Uo.VEC3,Uo.VEC4],Vo={[Uo.BOOL]:Cr.BOOLEAN,[Uo.INT]:Cr.INTEGER,[Uo.FLOAT]:Cr.FLOAT,[Uo.VEC2]:Cr.VECTOR2,[Uo.VEC3]:Cr.VECTOR3,[Uo.VEC4]:Cr.VECTOR4,[Uo.SAMPLER_2D]:Cr.RAMP,[Uo.SSS_MODEL]:Cr.STRING},Ho={[Cr.BOOLEAN]:Uo.BOOL,[Cr.COLOR]:Uo.VEC3,[Cr.INTEGER]:Uo.INT,[Cr.FLOAT]:Uo.FLOAT,[Cr.FOLDER]:void 0,[Cr.VECTOR2]:Uo.VEC2,[Cr.VECTOR3]:Uo.VEC3,[Cr.VECTOR4]:Uo.VEC4,[Cr.BUTTON]:void 0,[Cr.OPERATOR_PATH]:void 0,[Cr.PARAM_PATH]:void 0,[Cr.NODE_PATH]:void 0,[Cr.RAMP]:void 0,[Cr.STRING]:void 0},jo={[Uo.BOOL]:!1,[Uo.INT]:0,[Uo.FLOAT]:0,[Uo.VEC2]:[0,0],[Uo.VEC3]:[0,0,0],[Uo.VEC4]:[0,0,0,0],[Uo.SAMPLER_2D]:Ao.DEFAULT_VALUE_JSON,[Uo.SSS_MODEL]:\\\\\\\"SSSModel()\\\\\\\"},Wo={[Uo.BOOL]:1,[Uo.INT]:1,[Uo.FLOAT]:1,[Uo.VEC2]:2,[Uo.VEC3]:3,[Uo.VEC4]:4,[Uo.SAMPLER_2D]:1,[Uo.SSS_MODEL]:1};class qo extends ko{constructor(t,e,n){super(t,e),this._name=t,this._type=e,this._init_value=n,this._init_value=this._init_value||jo[this._type]}type(){return this._type}are_types_matched(t,e){return t==e}get param_type(){return Vo[this._type]}get init_value(){return this._init_value}toJSON(){return this._json=this._json||this._create_json()}_create_json(){return{name:this._name,type:this._type}}}var Xo;!function(t){t.BOOL=\\\\\\\"bool\\\\\\\",t.INT=\\\\\\\"int\\\\\\\",t.FLOAT=\\\\\\\"float\\\\\\\",t.VEC2=\\\\\\\"vec2\\\\\\\",t.VEC3=\\\\\\\"vec3\\\\\\\",t.VEC4=\\\\\\\"vec4\\\\\\\"}(Xo||(Xo={}));const Yo=[Xo.BOOL,Xo.INT,Xo.FLOAT,Xo.VEC2,Xo.VEC3,Xo.VEC4],$o={[Xo.BOOL]:Cr.BOOLEAN,[Xo.INT]:Cr.INTEGER,[Xo.FLOAT]:Cr.FLOAT,[Xo.VEC2]:Cr.VECTOR2,[Xo.VEC3]:Cr.VECTOR3,[Xo.VEC4]:Cr.VECTOR4},Jo={[Cr.BOOLEAN]:Xo.BOOL,[Cr.COLOR]:Xo.VEC3,[Cr.INTEGER]:Xo.INT,[Cr.FLOAT]:Xo.FLOAT,[Cr.FOLDER]:void 0,[Cr.VECTOR2]:Xo.VEC2,[Cr.VECTOR3]:Xo.VEC3,[Cr.VECTOR4]:Xo.VEC4,[Cr.BUTTON]:void 0,[Cr.OPERATOR_PATH]:void 0,[Cr.PARAM_PATH]:void 0,[Cr.NODE_PATH]:void 0,[Cr.RAMP]:void 0,[Cr.STRING]:void 0},Zo={[Xo.BOOL]:!1,[Xo.INT]:0,[Xo.FLOAT]:0,[Xo.VEC2]:[0,0],[Xo.VEC3]:[0,0,0],[Xo.VEC4]:[0,0,0,0]};Xo.BOOL,Xo.INT,Xo.FLOAT,Xo.VEC2,Xo.VEC3,Xo.VEC4;class Qo extends ko{constructor(t,e){super(t,e),this._name=t,this._type=e,this._init_value=Zo[this._type]}type(){return this._type}are_types_matched(t,e){return t==e}get param_type(){return $o[this._type]}get init_value(){return this._init_value}toJSON(){return this._json=this._json||this._create_json()}_create_json(){return{name:this._name,type:this._type}}}var Ko;!function(t){t.BASE=\\\\\\\"base\\\\\\\",t.DRAG=\\\\\\\"drag\\\\\\\",t.KEYBOARD=\\\\\\\"keyboard\\\\\\\",t.MOUSE=\\\\\\\"mouse\\\\\\\",t.POINTER=\\\\\\\"pointer\\\\\\\"}(Ko||(Ko={}));class ta extends ko{constructor(t,e,n){super(t,e),this._name=t,this._type=e,this._event_listener=n}type(){return this._type}get param_type(){return Cr.FLOAT}are_types_matched(t,e){return e==Ko.BASE||t==e}get event_listener(){return this._event_listener}toJSON(){return this._json=this._json||this._create_json()}_create_json(){return{name:this._name,type:this._type}}}const ea={[ts.ANIM]:void 0,[ts.COP]:void 0,[ts.EVENT]:Ko.BASE,[ts.GL]:Uo.FLOAT,[ts.JS]:Xo.FLOAT,[ts.MANAGER]:void 0,[ts.MAT]:void 0,[ts.OBJ]:void 0,[ts.POST]:void 0,[ts.ROP]:void 0,[ts.SOP]:void 0};function na(t,e,n){switch(t){case ts.EVENT:return new ta(e,n);case ts.GL:return new qo(e,n);case ts.JS:return new Qo(e,n);default:return}}class ia{constructor(t,e){this.node=t,this._context=e,this._raw_input_serialized_by_param_name=new Map,this._default_value_serialized_by_param_name=new Map,this._initialized=!1}initializeNode(){this._initialized?console.warn(\\\\\\\"already initialized\\\\\\\",this.node):(this._initialized=!0,this.node.params.onParamsCreated(\\\\\\\"create_inputs_from_params\\\\\\\",this.create_inputs_from_params.bind(this)))}initialized(){return this._initialized}create_inputs_from_params(){const t=function(t){switch(t){case ts.EVENT:return;case ts.GL:return Ho;case ts.JS:return Jo;default:return}}(this._context);if(!t)return;const e=[];for(let n of this.node.params.names){let i=!0;if(this._inputless_param_names&&this._inputless_param_names.length>0&&this._inputless_param_names.includes(n)&&(i=!1),i&&this.node.params.has(n)){const i=this.node.params.get(n);if(i&&!i.parent_param){const n=t[i.type()];if(n){const t=na(this._context,i.name(),n);t&&e.push(t)}}}}this.node.io.inputs.setNamedInputConnectionPoints(e)}set_inputless_param_names(t){return this._inputless_param_names=t}createSpareParameters(){if(this.node.scene().loadingController.isLoading())return;const t=this.node.params.spare_names,e={};for(let n of t)if(this.node.params.has(n)){const t=this.node.params.get(n);t&&(this._raw_input_serialized_by_param_name.set(n,t.rawInputSerialized()),this._default_value_serialized_by_param_name.set(n,t.defaultValueSerialized()),e.namesToDelete=e.namesToDelete||[],e.namesToDelete.push(n))}for(let t of this.node.io.inputs.namedInputConnectionPoints())if(t){const n=t.name(),i=t.param_type;let s=t.init_value;const r=this._default_value_serialized_by_param_name.get(n);let o=this.node.paramDefaultValue(n);if(s=null!=o?o:null!=r?r:t.init_value,m.isArray(t.init_value))if(m.isNumber(s)){const e=new Array(t.init_value.length);e.fill(s),s=e}else m.isArray(s)&&s.length==t.init_value.length&&null!=r&&(s=t.init_value);null!=s&&(e.toAdd=e.toAdd||[],e.toAdd.push({name:n,type:i,init_value:b.clone(s),raw_input:b.clone(s),options:{spare:!0}}))}this.node.params.updateParams(e);for(let t of this.node.params.spare)if(!t.parent_param){const e=this._raw_input_serialized_by_param_name.get(t.name());e&&t.set(e)}}}class sa{constructor(t,e){this.node=t,this._context=e,this._create_spare_params_from_inputs=!0,this._functions_overridden=!1,this._input_name_function=t=>`in${t}`,this._output_name_function=t=>0==t?\\\\\\\"val\\\\\\\":`val${t}`,this._expected_input_types_function=()=>{const t=this.first_input_connection_type()||this.default_connection_type();return[t,t]},this._expected_output_types_function=()=>[this._expected_input_types_function()[0]],this._update_signature_if_required_bound=this.update_signature_if_required.bind(this),this._initialized=!1,this._spare_params_controller=new ia(this.node,this._context)}default_connection_type(){return ea[this._context]}create_connection_point(t,e){return na(this._context,t,e)}functions_overridden(){return this._functions_overridden}initialized(){return this._initialized}set_create_spare_params_from_inputs(t){this._create_spare_params_from_inputs=t}set_input_name_function(t){this._initialize_if_required(),this._input_name_function=t}set_output_name_function(t){this._initialize_if_required(),this._output_name_function=t}set_expected_input_types_function(t){this._initialize_if_required(),this._functions_overridden=!0,this._expected_input_types_function=t}set_expected_output_types_function(t){this._initialize_if_required(),this._functions_overridden=!0,this._expected_output_types_function=t}input_name(t){return this._wrapped_input_name_function(t)}output_name(t){return this._wrapped_output_name_function(t)}initializeNode(){this._initialized?console.warn(\\\\\\\"already initialized\\\\\\\",this.node):(this._initialized=!0,this.node.io.inputs.add_on_set_input_hook(\\\\\\\"_update_signature_if_required\\\\\\\",this._update_signature_if_required_bound),this.node.params.addOnSceneLoadHook(\\\\\\\"_update_signature_if_required\\\\\\\",this._update_signature_if_required_bound),this.node.params.onParamsCreated(\\\\\\\"_update_signature_if_required_bound\\\\\\\",this._update_signature_if_required_bound),this.node.addPostDirtyHook(\\\\\\\"_update_signature_if_required\\\\\\\",this._update_signature_if_required_bound),this._spare_params_controller.initialized()||this._spare_params_controller.initializeNode())}_initialize_if_required(){this._initialized||this.initializeNode()}get spare_params(){return this._spare_params_controller}update_signature_if_required(t){this.node.lifecycle.creationCompleted()&&this._connections_match_inputs()||(this.update_connection_types(),this.node.removeDirtyState(),this.node.scene().loadingController.isLoading()||this.make_successors_update_signatures())}make_successors_update_signatures(){const t=this.node.graphAllSuccessors();if(this.node.childrenAllowed()){const e=this.node.nodesByType(ns.INPUT),n=this.node.nodesByType(ns.OUTPUT);for(let n of e)t.push(n);for(let e of n)t.push(e)}for(let e of t){const t=e;t.io&&t.io.has_connection_points_controller&&t.io.connection_points.initialized()&&t.io.connection_points.update_signature_if_required(this.node)}}update_connection_types(){const t=this._wrapped_expected_input_types_function(),e=this._wrapped_expected_output_types_function(),n=[];for(let e=0;enull==t?void 0:t.type())),e=this.node.io.outputs.namedOutputConnectionPoints().map((t=>null==t?void 0:t.type())),n=this._wrapped_expected_input_types_function(),i=this._wrapped_expected_output_types_function();if(n.length!=t.length)return!1;if(i.length!=e.length)return!1;for(let e=0;et.type))}return this._expected_input_types_function()}_wrapped_expected_output_types_function(){if(this.node.scene().loadingController.isLoading()){const t=this.node.io.saved_connection_points_data.out();if(t)return t.map((t=>t.type))}return this._expected_output_types_function()}_wrapped_input_name_function(t){if(this.node.scene().loadingController.isLoading()){const e=this.node.io.saved_connection_points_data.in();if(e)return e[t].name}return this._input_name_function(t)}_wrapped_output_name_function(t){if(this.node.scene().loadingController.isLoading()){const e=this.node.io.saved_connection_points_data.out();if(e)return e[t].name}return this._output_name_function(t)}first_input_connection_type(){return this.input_connection_type(0)}input_connection_type(t){const e=this.node.io.connections.inputConnections();if(e){const n=e[t];if(n)return n.src_connection_point().type()}}}class ra{constructor(t){this.node=t,this._connections=new Bo(this.node)}get connections(){return this._connections}get inputs(){return this._inputs=this._inputs||new Fo(this.node)}has_inputs(){return null!=this._inputs}get outputs(){return this._outputs=this._outputs||new Do(this.node)}has_outputs(){return null!=this._outputs}get connection_points(){return this._connection_points=this._connection_points||new sa(this.node,this.node.context())}get has_connection_points_controller(){return null!=this._connection_points}get saved_connection_points_data(){return this._saved_connection_points_data=this._saved_connection_points_data||new zo(this.node)}clear_saved_connection_points_data(){this._saved_connection_points_data&&(this._saved_connection_points_data.clear(),this._saved_connection_points_data=void 0)}}class oa{constructor(){}}class aa extends Mi{constructor(t,e=\\\\\\\"BaseNode\\\\\\\",n){super(t,e),this.params_init_value_overrides=n,this.containerController=new Tr(this),this.pv=new Po,this.p=new oa,this._initialized=!1}copy_param_values(t){const e=this.params.non_spare;for(let n of e){const e=t.params.get(n.name());e&&n.copy_value(e)}}get parentController(){return this._parent_controller=this._parent_controller||new qi(this)}static displayedInputNames(){return[]}get childrenControllerContext(){return this._children_controller_context}_create_children_controller(){if(this._children_controller_context)return new hs(this,this._children_controller_context)}get childrenController(){return this._children_controller=this._children_controller||this._create_children_controller()}childrenAllowed(){return null!=this._children_controller_context}get uiData(){return this._ui_data=this._ui_data||new Si(this)}get states(){return this._states=this._states||new ji(this)}get lifecycle(){return this._lifecycle=this._lifecycle||new us(this)}get serializer(){return this._serializer=this._serializer||new Sr(this)}get cookController(){return this._cook_controller=this._cook_controller||new Er(this)}get io(){return this._io=this._io||new ra(this)}get nameController(){return this._name_controller=this._name_controller||new Wi(this)}setName(t){this.nameController.setName(t)}_set_core_name(t){this._name=t}get params(){return this._params_controller=this._params_controller||new Oo(this)}initialize_base_and_node(){var t;this._initialized?console.warn(\\\\\\\"node already initialized\\\\\\\"):(this._initialized=!0,null===(t=this.displayNodeController)||void 0===t||t.initializeNode(),this.initializeBaseNode(),this.initializeNode(),this.polyNodeController&&this.polyNodeController.initializeNode())}initializeBaseNode(){}initializeNode(){}static type(){throw\\\\\\\"type to be overriden\\\\\\\"}type(){return this.constructor.type()}static context(){throw console.error(\\\\\\\"node has no node_context\\\\\\\",this),\\\\\\\"context requires override\\\\\\\"}context(){return this.constructor.context()}static require_webgl2(){return!1}require_webgl2(){return this.constructor.require_webgl2()}setParent(t){this.parentController.setParent(t)}parent(){return this.parentController.parent()}firstAncestorWithContext(t){return this.parentController.firstAncestorWithContext(t)}root(){return this._scene.root()}path(t){return this.parentController.path(t)}createParams(){}addParam(t,e,n,i){var s;return null===(s=this._params_controller)||void 0===s?void 0:s.addParam(t,e,n,i)}paramDefaultValue(t){return null}cook(t){return null}onCookEnd(t,e){this.cookController.registerOnCookEnd(t,e)}async compute(){var t,e;return this.isDirty()||(null===(e=null===(t=this.flags)||void 0===t?void 0:t.bypass)||void 0===e?void 0:e.active())?await this.containerController.compute():this.containerController.container()}_setContainer(t,e=null){this.containerController.container().set_content(t),null!=t&&(t.name||(t.name=this.path()),t.node||(t.node=this)),this.cookController.endCook(e)}createNode(t,e){var n;return null===(n=this.childrenController)||void 0===n?void 0:n.createNode(t,e)}create_operation_container(t,e,n){var i;return null===(i=this.childrenController)||void 0===i?void 0:i.create_operation_container(t,e,n)}removeNode(t){var e;null===(e=this.childrenController)||void 0===e||e.removeNode(t)}dispose(){var t,e;super.dispose(),this.setParent(null),this.io.inputs.dispose(),this.lifecycle.dispose(),null===(t=this.displayNodeController)||void 0===t||t.dispose(),this.nameController.dispose(),null===(e=this.childrenController)||void 0===e||e.dispose(),this.params.dispose()}children(){var t;return(null===(t=this.childrenController)||void 0===t?void 0:t.children())||[]}node(t){var e;return(null===(e=this.parentController)||void 0===e?void 0:e.findNode(t))||null}nodeSibbling(t){var e;const n=this.parent();if(n){const i=null===(e=n.childrenController)||void 0===e?void 0:e.child_by_name(t);if(i)return i}return null}nodesByType(t){var e;return(null===(e=this.childrenController)||void 0===e?void 0:e.nodesByType(t))||[]}setInput(t,e,n=0){this.io.inputs.setInput(t,e,n)}emit(t,e=null){this.scene().dispatchController.dispatch(this,t,e)}toJSON(t=!1){return this.serializer.toJSON(t)}async requiredModules(){}usedAssembler(){}integrationData(){}}class la extends aa{static context(){return ts.MANAGER}}class ca{constructor(t,e,n){this.type=t,this.init_value=e,this.options=n}}class ha{static BUTTON(t,e){return new ca(Cr.BUTTON,t,e)}static BOOLEAN(t,e){return new ca(Cr.BOOLEAN,t,e)}static COLOR(t,e){return t instanceof D.a&&(t=t.toArray()),new ca(Cr.COLOR,t,e)}static FLOAT(t,e){return new ca(Cr.FLOAT,t,e)}static FOLDER(t=null,e){return new ca(Cr.FOLDER,t,e)}static INTEGER(t,e){return new ca(Cr.INTEGER,t,e)}static RAMP(t=Ao.DEFAULT_VALUE,e){return new ca(Cr.RAMP,t,e)}static STRING(t=\\\\\\\"\\\\\\\",e){return new ca(Cr.STRING,t,e)}static VECTOR2(t,e){return t instanceof d.a&&(t=t.toArray()),new ca(Cr.VECTOR2,t,e)}static VECTOR3(t,e){return t instanceof p.a&&(t=t.toArray()),new ca(Cr.VECTOR3,t,e)}static VECTOR4(t,e){return t instanceof _.a&&(t=t.toArray()),new ca(Cr.VECTOR4,t,e)}static OPERATOR_PATH(t,e){return new ca(Cr.OPERATOR_PATH,t,e)}static NODE_PATH(t,e){return new ca(Cr.NODE_PATH,t,e)}static PARAM_PATH(t,e){return new ca(Cr.PARAM_PATH,t,e)}}class ua{}class da{constructor(t){this.scene=t}findObjectByMask(t){return this.findObjectByMaskInObject(t,this.scene.threejsScene())}findObjectByMaskInObject(t,e,n=\\\\\\\"\\\\\\\"){for(let i of e.children){const e=this._removeTrailingOrHeadingSlash(i.name),s=`${n=this._removeTrailingOrHeadingSlash(n)}/${e}`;if(ss.matchMask(s,t))return i;const r=this.findObjectByMaskInObject(t,i,s);if(r)return r}}objectsByMask(t){return this.objectsByMaskInObject(t,this.scene.threejsScene(),[],\\\\\\\"\\\\\\\")}objectsByMaskInObject(t,e,n=[],i=\\\\\\\"\\\\\\\"){for(let s of e.children){const e=this._removeTrailingOrHeadingSlash(s.name),r=`${i=this._removeTrailingOrHeadingSlash(i)}/${e}`;ss.matchMask(r,t)&&n.push(s),this.objectsByMaskInObject(t,s,n,r)}return n}_removeTrailingOrHeadingSlash(t){return\\\\\\\"/\\\\\\\"==t[0]&&(t=t.substr(1)),\\\\\\\"/\\\\\\\"==t[t.length-1]&&(t=t.substr(0,t.length-1)),t}}const pa={computeOnDirty:!1,callback:t=>{ma.update(t)}};function _a(t){return class extends t{constructor(){super(...arguments),this.autoUpdate=ha.BOOLEAN(1,pa)}}}_a(ua);class ma{constructor(t){this.node=t}async update(){const t=this.node.object,e=this.node.pv;e.autoUpdate!=t.autoUpdate&&(t.autoUpdate=e.autoUpdate)}static async update(t){t.sceneAutoUpdateController.update()}}var fa;!function(t){t.NONE=\\\\\\\"none\\\\\\\",t.COLOR=\\\\\\\"color\\\\\\\",t.TEXTURE=\\\\\\\"texture\\\\\\\"}(fa||(fa={}));const ga=[fa.NONE,fa.COLOR,fa.TEXTURE],va={computeOnDirty:!1,callback:t=>{xa.update(t)}};function ya(t){return class extends t{constructor(){super(...arguments),this.backgroundMode=ha.INTEGER(ga.indexOf(fa.NONE),{menu:{entries:ga.map(((t,e)=>({name:t,value:e})))},...va}),this.bgColor=ha.COLOR([0,0,0],{visibleIf:{backgroundMode:ga.indexOf(fa.COLOR)},...va}),this.bgTexture=ha.NODE_PATH(\\\\\\\"\\\\\\\",{visibleIf:{backgroundMode:ga.indexOf(fa.TEXTURE)},nodeSelection:{context:ts.COP},dependentOnFoundNode:!1,...va})}}}ya(ua);class xa{constructor(t){this.node=t}update(){const t=this.node.object,e=this.node.pv;if(e.backgroundMode==ga.indexOf(fa.NONE))t.background=null;else if(e.backgroundMode==ga.indexOf(fa.COLOR))t.background=e.bgColor;else{const n=e.bgTexture.nodeWithContext(ts.COP);n?n.compute().then((e=>{t.background=e.texture()})):this.node.states.error.set(\\\\\\\"bgTexture node not found\\\\\\\")}}static update(t){t.sceneBackgroundController.update()}}const ba={computeOnDirty:!1,callback:t=>{Ta.update(t)}};function wa(t){return class extends t{constructor(){super(...arguments),this.useEnvironment=ha.BOOLEAN(0,ba),this.environment=ha.NODE_PATH(\\\\\\\"\\\\\\\",{visibleIf:{useEnvironment:1},nodeSelection:{context:ts.COP},dependentOnFoundNode:!1,...ba})}}}wa(ua);class Ta{constructor(t){this.node=t}async update(){const t=this.node.object,e=this.node.pv;if(e.useEnvironment){const n=e.environment.nodeWithContext(ts.COP);n?n.compute().then((e=>{t.environment=e.texture()})):this.node.states.error.set(\\\\\\\"bgTexture node not found\\\\\\\")}else t.environment=null}static async update(t){t.sceneEnvController.update()}}class Aa{constructor(t,e=1,n=1e3){this.name=\\\\\\\"\\\\\\\",this.color=new D.a(t),this.near=e,this.far=n}clone(){return new Aa(this.color,this.near,this.far)}toJSON(){return{type:\\\\\\\"Fog\\\\\\\",color:this.color.getHex(),near:this.near,far:this.far}}}Aa.prototype.isFog=!0;class Ma{constructor(t,e=25e-5){this.name=\\\\\\\"\\\\\\\",this.color=new D.a(t),this.density=e}clone(){return new Ma(this.color,this.density)}toJSON(){return{type:\\\\\\\"FogExp2\\\\\\\",color:this.color.getHex(),density:this.density}}}Ma.prototype.isFogExp2=!0;const Ea={computeOnDirty:!1,callback:t=>{La.update(t)}};var Sa;!function(t){t.LINEAR=\\\\\\\"linear\\\\\\\",t.EXPONENTIAL=\\\\\\\"exponential\\\\\\\"}(Sa||(Sa={}));const Ca=[Sa.LINEAR,Sa.EXPONENTIAL];function Na(t){return class extends t{constructor(){super(...arguments),this.useFog=ha.BOOLEAN(0,Ea),this.fogType=ha.INTEGER(Ca.indexOf(Sa.EXPONENTIAL),{visibleIf:{useFog:1},menu:{entries:Ca.map(((t,e)=>({name:t,value:e})))},...Ea}),this.fogColor=ha.COLOR([1,1,1],{visibleIf:{useFog:1},...Ea}),this.fogNear=ha.FLOAT(1,{range:[0,100],rangeLocked:[!0,!1],visibleIf:{useFog:1,fogType:Ca.indexOf(Sa.LINEAR)},...Ea}),this.fogFar=ha.FLOAT(100,{range:[0,100],rangeLocked:[!0,!1],visibleIf:{useFog:1,fogType:Ca.indexOf(Sa.LINEAR)},...Ea}),this.fogDensity=ha.FLOAT(25e-5,{visibleIf:{useFog:1,fogType:Ca.indexOf(Sa.EXPONENTIAL)},...Ea})}}}Na(ua);class La{constructor(t){this.node=t}async update(){const t=this.node.object,e=this.node.pv;if(e.useFog)if(e.fogType==Ca.indexOf(Sa.LINEAR)){const n=this.fog2(e);t.fog=n,n.color=e.fogColor,n.near=e.fogNear,n.far=e.fogFar}else{const n=this.fogExp2(e);t.fog=this.fogExp2(e),n.color=e.fogColor,n.density=e.fogDensity}else{t.fog&&(t.fog=null)}}fog2(t){return this._fog=this._fog||new Aa(16777215,t.fogNear,t.fogFar)}fogExp2(t){return this._fogExp2=this._fogExp2||new Ma(16777215,t.fogDensity)}static async update(t){t.sceneFogController.update()}}const Oa={computeOnDirty:!1,callback:t=>{Ra.update(t)}};function Pa(t){return class extends t{constructor(){super(...arguments),this.useOverrideMaterial=ha.BOOLEAN(0,Oa),this.overrideMaterial=ha.NODE_PATH(\\\\\\\"\\\\\\\",{visibleIf:{useOverrideMaterial:1},nodeSelection:{context:ts.MAT},dependentOnFoundNode:!1,...Oa})}}}Pa(ua);class Ra{constructor(t){this.node=t}async update(){const t=this.node.object,e=this.node.pv;if(e.useOverrideMaterial){const n=e.overrideMaterial.nodeWithContext(ts.MAT);n?n.compute().then((e=>{t.overrideMaterial=e.material()})):this.node.states.error.set(\\\\\\\"bgTexture node not found\\\\\\\")}else t.overrideMaterial=null}static async update(t){t.SceneMaterialOverrideController.update()}}class Ia extends(Pa(wa(Na(ya(_a(ua)))))){}const Fa=new Ia;class Da extends la{constructor(){super(...arguments),this.paramsConfig=Fa,this._object=this._createScene(),this._queued_nodes_by_id=new Map,this.sceneAutoUpdateController=new ma(this),this.sceneBackgroundController=new xa(this),this.sceneEnvController=new Ta(this),this.sceneFogController=new La(this),this.sceneMaterialOverrideController=new Ra(this),this._children_controller_context=ts.OBJ}static type(){return\\\\\\\"obj\\\\\\\"}initializeNode(){this._object.matrixAutoUpdate=!1,this.lifecycle.add_on_child_add_hook(this._on_child_add.bind(this)),this.lifecycle.add_on_child_remove_hook(this._on_child_remove.bind(this))}_createScene(){const t=new vs;return t.name=\\\\\\\"/\\\\\\\",t.matrixAutoUpdate=!1,t}get object(){return this._object}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}_updateScene(){this.sceneAutoUpdateController.update(),this.sceneBackgroundController.update(),this.sceneEnvController.update(),this.sceneFogController.update(),this.sceneMaterialOverrideController.update()}_addToQueue(t){const e=t.graphNodeId();return this._queued_nodes_by_id.has(e)||this._queued_nodes_by_id.set(e,t),t}async processQueue(){this._updateScene();const t=new Map,e=[];this._queued_nodes_by_id.forEach(((n,i)=>{const s=`_____${n.renderOrder}__${n.path()}`;e.push(s),t.set(s,n)})),this._queued_nodes_by_id.clear();for(let n of e){const e=t.get(n);e&&(t.delete(n),this._addToScene(e))}}_update_object(t){return this.scene().loadingController.autoUpdating()?this._addToScene(t):this._addToQueue(t)}getParentForNode(t){if(t.attachableToHierarchy()){const e=t.io.inputs.input(0);return e?e.children_group:this._object}return null}_addToScene(t){var e;if(t.attachableToHierarchy()){const n=this.getParentForNode(t);n&&(t.usedInScene()?(null===(e=t.childrenDisplayController)||void 0===e||e.request_display_node_container(),t.addObjectToParent(n)):t.removeObjectFromParent())}}_removeFromScene(t){t.removeObjectFromParent()}areChildrenCooking(){const t=this.children();for(let e of t)if(e.cookController.isCooking()||e.isDisplayNodeCooking())return!0;return!1}addToParentTransform(t){this._update_object(t)}removeFromParentTransform(t){this._update_object(t)}_on_child_add(t){t&&this._update_object(t)}_on_child_remove(t){t&&this._removeFromScene(t)}}class Ba{constructor(t){this.scene=t,this._node_context_signatures={},this._instanciated_nodes_by_context_and_type={}}init(){this._root=new Da(this.scene),this._root.initialize_base_and_node(),this._root.params.init(),this._root._set_core_name(\\\\\\\"RootNode\\\\\\\")}root(){return this._root}_traverseNode(t,e){const n=t.children();if(n&&0!=n.length)for(let t of n)e(t),t.childrenController&&this._traverseNode(t,e)}clear(){var t;const e=this.root().children();for(let n of e)null===(t=this.root().childrenController)||void 0===t||t.removeNode(n)}node(t){return\\\\\\\"/\\\\\\\"===t?this.root():this.root().node(t)}allNodes(){let t=[this.root()],e=[this.root()],n=0;for(;e.length>0&&n<10;){const i=e.map((t=>t.childrenAllowed()?t.children():[])).flat();t=t.concat(i),e=i,n+=1}return t.flat()}nodesFromMask(t){const e=this.allNodes(),n=[];for(let i of e){const e=i.path();ss.matchMask(e,t)&&n.push(i)}return n}reset_node_context_signatures(){this._node_context_signatures={}}register_node_context_signature(t){t.childrenAllowed()&&t.childrenController&&(this._node_context_signatures[t.childrenController.node_context_signature()]=!0)}node_context_signatures(){return Object.keys(this._node_context_signatures).sort().map((t=>t.toLowerCase()))}addToInstanciatedNode(t){const e=t.context(),n=t.type();this._instanciated_nodes_by_context_and_type[e]=this._instanciated_nodes_by_context_and_type[e]||{},this._instanciated_nodes_by_context_and_type[e][n]=this._instanciated_nodes_by_context_and_type[e][n]||{},this._instanciated_nodes_by_context_and_type[e][n][t.graphNodeId()]=t}removeFromInstanciatedNode(t){const e=t.context(),n=t.type();delete this._instanciated_nodes_by_context_and_type[e][n][t.graphNodeId()]}nodesByType(t){const e=[];return this._traverseNode(this.scene.root(),(n=>{n.type()==t&&e.push(n)})),e}nodesByContextAndType(t,e){const n=[],i=this._instanciated_nodes_by_context_and_type[t];if(i){const t=i[e];if(t)for(let e of Object.keys(t))n.push(t[e])}return n}}class za{constructor(t){this.scene=t}toJSON(t=!1){const e={},n={};for(let i of this.scene.nodesController.allNodes()){const s=new Sr(i);e[i.graphNodeId()]=s.toJSON(t);const r=i.params.all;for(let t of r)n[t.graphNodeId()]=t.toJSON()}return{nodes_by_graph_node_id:e,params_by_graph_node_id:n}}}var ka;!function(t){t.auxclick=\\\\\\\"auxclick\\\\\\\",t.click=\\\\\\\"click\\\\\\\",t.contextmenu=\\\\\\\"contextmenu\\\\\\\",t.dblclick=\\\\\\\"dblclick\\\\\\\",t.mousedown=\\\\\\\"mousedown\\\\\\\",t.mouseenter=\\\\\\\"mouseenter\\\\\\\",t.mouseleave=\\\\\\\"mouseleave\\\\\\\",t.mousemove=\\\\\\\"mousemove\\\\\\\",t.mouseover=\\\\\\\"mouseover\\\\\\\",t.mouseout=\\\\\\\"mouseout\\\\\\\",t.mouseup=\\\\\\\"mouseup\\\\\\\",t.pointerlockchange=\\\\\\\"pointerlockchange\\\\\\\",t.pointerlockerror=\\\\\\\"pointerlockerror\\\\\\\",t.select=\\\\\\\"select\\\\\\\",t.wheel=\\\\\\\"wheel\\\\\\\"}(ka||(ka={}));const Ua=[ka.auxclick,ka.click,ka.contextmenu,ka.dblclick,ka.mousedown,ka.mouseenter,ka.mouseleave,ka.mousemove,ka.mouseover,ka.mouseout,ka.mouseup,ka.pointerlockchange,ka.pointerlockerror,ka.select,ka.wheel];class Ga extends pi{constructor(){super(...arguments),this._require_canvas_event_listeners=!0}type(){return\\\\\\\"mouse\\\\\\\"}acceptedEventTypes(){return Ua.map((t=>`${t}`))}}class Va extends aa{constructor(){super(...arguments),this._cook_without_inputs_bound=this._cook_without_inputs.bind(this)}static context(){return ts.EVENT}initializeBaseNode(){this.uiData.setLayoutHorizontal(),this.addPostDirtyHook(\\\\\\\"cook_without_inputs_on_dirty\\\\\\\",this._cook_without_inputs_bound),this.io.inputs.set_depends_on_inputs(!1),this.io.connections.initInputs(),this.io.connection_points.spare_params.initializeNode()}_cook_without_inputs(){this.cookController.cookMainWithoutInputs()}cook(){this.cookController.endCook()}processEventViaConnectionPoint(t,e){e.event_listener?e.event_listener(t):this.processEvent(t)}processEvent(t){}async dispatchEventToOutput(t,e){this.run_on_dispatch_hook(t,e);const n=this.io.outputs.getOutputIndex(t);if(n>=0){const t=this.io.connections.outputConnections().filter((t=>t.output_index==n));let i;for(let n of t){i=n.node_dest;const t=i.io.inputs.namedInputConnectionPoints()[n.input_index];i.processEventViaConnectionPoint(e,t)}}else console.warn(`requested output '${t}' does not exist on node '${this.path()}'`)}onDispatch(t,e){this._on_dispatch_hooks_by_output_name=this._on_dispatch_hooks_by_output_name||new Map,h.pushOnArrayAtEntry(this._on_dispatch_hooks_by_output_name,t,e)}run_on_dispatch_hook(t,e){if(this._on_dispatch_hooks_by_output_name){const n=this._on_dispatch_hooks_by_output_name.get(t);if(n)for(let t of n)t(e)}}}var Ha;!function(t){t.CANVAS=\\\\\\\"canvas\\\\\\\",t.DOCUMENT=\\\\\\\"document\\\\\\\"}(Ha||(Ha={}));const ja=[Ha.CANVAS,Ha.DOCUMENT];class Wa{constructor(t){this.viewer=t,this._bound_listener_map_by_event_controller_type=new Map}updateEvents(t){const e=this.canvas();if(!e)return;const n=t.type();let i=this._bound_listener_map_by_event_controller_type.get(n);i||(i=new Map,this._bound_listener_map_by_event_controller_type.set(n,i)),i.forEach(((t,n)=>{this._eventOwner(t.data,e).removeEventListener(n,t.listener)})),i.clear();const s=e=>{this.processEvent(e,t)};for(let n of t.activeEventDatas()){this._eventOwner(n,e).addEventListener(n.type,s),i.set(n.type,{listener:s,data:n})}}_eventOwner(t,e){return\\\\\\\"resize\\\\\\\"==t.type?window:t.emitter==Ha.CANVAS?e:document}cameraNode(){return this.viewer.camerasController.cameraNode()}canvas(){return this.viewer.canvas()}init(){this.canvas&&this.viewer.scene().eventsDispatcher.traverseControllers((t=>{this.updateEvents(t)}))}registeredEventTypes(){const t=[];return this._bound_listener_map_by_event_controller_type.forEach((e=>{e.forEach(((e,n)=>{t.push(n)}))})),t}dispose(){const t=this.canvas();this._bound_listener_map_by_event_controller_type.forEach((e=>{t&&e.forEach(((e,n)=>{this._eventOwner(e.data,t).removeEventListener(n,e.listener)}))}))}processEvent(t,e){if(!this.canvas())return;const n={viewer:this.viewer,event:t,cameraNode:this.cameraNode()};e.processEvent(n)}}const qa={visibleIf:{active:1},callback:t=>{Ya.PARAM_CALLBACK_updateRegister(t)}};class Xa extends Va{constructor(){super(...arguments),this._activeEventDatas=[]}initializeBaseNode(){super.initializeBaseNode();this.lifecycle.add_on_add_hook((()=>{this.scene().eventsDispatcher.registerEventNode(this)})),this.lifecycle.add_delete_hook((()=>{this.scene().eventsDispatcher.unregisterEventNode(this)})),this.params.onParamsCreated(\\\\\\\"update_register\\\\\\\",(()=>{this._updateRegister()}))}processEvent(t){this.pv.active&&t.event&&this.dispatchEventToOutput(t.event.type,t)}static PARAM_CALLBACK_updateRegister(t){t._updateRegister()}_updateRegister(){this._updateActiveEventDatas(),this.scene().eventsDispatcher.updateViewerEventListeners(this)}_updateActiveEventDatas(){if(this._activeEventDatas=[],this.pv.active){const t=this.acceptedEventTypes();for(let e of t){const t=this.params.get(e);t&&t.value&&this._activeEventDatas.push({type:e,emitter:ja[this.pv.element]})}}}activeEventDatas(){return this._activeEventDatas}}class Ya extends Xa{acceptedEventTypes(){return[]}}const $a=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(!0,{callback:t=>{Ja.PARAM_CALLBACK_updateRegister(t)},separatorAfter:!0}),this.element=ha.INTEGER(ja.indexOf(Ha.CANVAS),{menu:{entries:ja.map(((t,e)=>({name:t,value:e})))},separatorAfter:!0}),this.auxclick=ha.BOOLEAN(0,qa),this.click=ha.BOOLEAN(0,qa),this.contextmenu=ha.BOOLEAN(0,qa),this.dblclick=ha.BOOLEAN(0,qa),this.mousedown=ha.BOOLEAN(1,qa),this.mouseenter=ha.BOOLEAN(0,qa),this.mouseleave=ha.BOOLEAN(0,qa),this.mousemove=ha.BOOLEAN(1,qa),this.mouseover=ha.BOOLEAN(0,qa),this.mouseout=ha.BOOLEAN(0,qa),this.mouseup=ha.BOOLEAN(1,qa),this.pointerlockchange=ha.BOOLEAN(0,qa),this.pointerlockerror=ha.BOOLEAN(0,qa),this.select=ha.BOOLEAN(0,qa),this.wheel=ha.BOOLEAN(0,qa),this.ctrlKey=ha.BOOLEAN(0,{...qa,separatorBefore:!0}),this.altKey=ha.BOOLEAN(0,qa),this.shiftKey=ha.BOOLEAN(0,qa),this.metaKey=ha.BOOLEAN(0,qa)}};class Ja extends Xa{constructor(){super(...arguments),this.paramsConfig=$a}static type(){return\\\\\\\"mouse\\\\\\\"}acceptedEventTypes(){return Ua.map((t=>`${t}`))}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints(Ua.map((t=>new ta(t,Ko.MOUSE)))),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{const t=[this.p.auxclick,this.p.click,this.p.dblclick,this.p.mousedown,this.p.mouseenter,this.p.mouseleave,this.p.mousemove,this.p.mouseout,this.p.mouseout,this.p.mouseup,this.p.pointerlockchange,this.p.pointerlockerror,this.p.select,this.p.wheel];this.params.label.init(t,(()=>t.map((t=>t.value?t.name():void 0)).filter((t=>t)).join(\\\\\\\", \\\\\\\")))}))}))}processEvent(t){if(!this.pv.active)return;if(!t.event)return;const e=t.event;e.ctrlKey==this.pv.ctrlKey&&e.shiftKey==this.pv.shiftKey&&e.altKey==this.pv.altKey&&e.metaKey==this.pv.metaKey&&this.dispatchEventToOutput(t.event.type,t)}}var Za;!function(t){t.pointerdown=\\\\\\\"pointerdown\\\\\\\",t.pointermove=\\\\\\\"pointermove\\\\\\\",t.pointerup=\\\\\\\"pointerup\\\\\\\"}(Za||(Za={}));const Qa=[Za.pointerdown,Za.pointermove,Za.pointerup];class Ka extends pi{constructor(){super(...arguments),this._require_canvas_event_listeners=!0}type(){return\\\\\\\"pointer\\\\\\\"}acceptedEventTypes(){return Qa.map((t=>`${t}`))}}const tl=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(!0,{callback:t=>{el.PARAM_CALLBACK_updateRegister(t)},separatorAfter:!0}),this.element=ha.INTEGER(ja.indexOf(Ha.CANVAS),{menu:{entries:ja.map(((t,e)=>({name:t,value:e})))},separatorAfter:!0}),this.pointerdown=ha.BOOLEAN(1,qa),this.pointermove=ha.BOOLEAN(0,qa),this.pointerup=ha.BOOLEAN(0,qa),this.ctrlKey=ha.BOOLEAN(0,{...qa,separatorBefore:!0}),this.altKey=ha.BOOLEAN(0,qa),this.shiftKey=ha.BOOLEAN(0,qa),this.metaKey=ha.BOOLEAN(0,qa)}};class el extends Xa{constructor(){super(...arguments),this.paramsConfig=tl}static type(){return\\\\\\\"pointer\\\\\\\"}acceptedEventTypes(){return Qa.map((t=>`${t}`))}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints(Qa.map((t=>new ta(t,Ko.POINTER)))),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{const t=[this.p.pointerdown,this.p.pointermove,this.p.pointerup];this.params.label.init(t,(()=>t.map((t=>t.value?t.name():void 0)).filter((t=>t)).join(\\\\\\\", \\\\\\\")))}))}))}processEvent(t){if(!this.pv.active)return;if(!t.event)return;const e=t.event;e.ctrlKey==this.pv.ctrlKey&&e.shiftKey==this.pv.shiftKey&&e.altKey==this.pv.altKey&&e.metaKey==this.pv.metaKey&&this.dispatchEventToOutput(t.event.type,t)}}var nl,il;!function(t){t.SET_FRAME=\\\\\\\"setFrame\\\\\\\"}(nl||(nl={})),function(t){t.TIME_REACHED=\\\\\\\"timeReached\\\\\\\"}(il||(il={}));const sl=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(!0,{callback:(t,e)=>{rl.PARAM_CALLBACK_updateRegister(t)},separatorAfter:!0}),this.element=ha.INTEGER(0,{hidden:!0}),this.sceneLoaded=ha.BOOLEAN(1,qa),this.play=ha.BOOLEAN(1,qa),this.pause=ha.BOOLEAN(1,qa),this.tick=ha.BOOLEAN(1,{separatorAfter:!0,...qa}),this.treachedTime=ha.BOOLEAN(0,{callback:t=>{rl.PARAM_CALLBACK_update_time_dependency(t)}}),this.reachedTime=ha.INTEGER(10,{visibleIf:{treachedTime:1},range:[0,100],separatorAfter:!0}),this.setFrameValue=ha.INTEGER(1,{range:[0,100]}),this.setFrame=ha.BUTTON(null,{callback:t=>{rl.PARAM_CALLBACK_setFrame(t)}})}};class rl extends Xa{constructor(){super(...arguments),this.paramsConfig=sl}static type(){return\\\\\\\"scene\\\\\\\"}acceptedEventTypes(){return mi.map((t=>`${t}`))}dispose(){var t;null===(t=this.graph_node)||void 0===t||t.dispose(),super.dispose()}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(nl.SET_FRAME,Ko.BASE,this._onSetFrame.bind(this)),new ta(_i.PLAY,Ko.BASE,this._play.bind(this)),new ta(_i.PAUSE,Ko.BASE,this._pause.bind(this))]);const t=mi.map((t=>new ta(t,Ko.BASE)));t.push(new ta(il.TIME_REACHED,Ko.BASE)),this.io.outputs.setNamedOutputConnectionPoints(t),this.params.onParamsCreated(\\\\\\\"update_time_dependency\\\\\\\",(()=>{this.update_time_dependency()}))}_onSetFrame(t){this.scene().setFrame(this.pv.setFrameValue)}_play(t){this.scene().play()}_pause(t){this.scene().pause()}_onFrameUpdate(){this.scene().time()>=this.pv.reachedTime&&this.dispatchEventToOutput(il.TIME_REACHED,{})}update_time_dependency(){this.pv.treachedTime?(this.graph_node=this.graph_node||new Mi(this.scene(),\\\\\\\"scene_node_time_graph_node\\\\\\\"),this.graph_node.addGraphInput(this.scene().timeController.graphNode),this.graph_node.addPostDirtyHook(\\\\\\\"time_update\\\\\\\",this._onFrameUpdate.bind(this))):this.graph_node&&this.graph_node.graphDisconnectPredecessors()}static PARAM_CALLBACK_setFrame(t){t._onSetFrame({})}static PARAM_CALLBACK_update_time_dependency(t){t.update_time_dependency()}}var ol;!function(t){t.keydown=\\\\\\\"keydown\\\\\\\",t.keypress=\\\\\\\"keypress\\\\\\\",t.keyup=\\\\\\\"keyup\\\\\\\"}(ol||(ol={}));const al=[ol.keydown,ol.keypress,ol.keyup];class ll extends pi{constructor(){super(...arguments),this._require_canvas_event_listeners=!0}type(){return\\\\\\\"keyboard\\\\\\\"}acceptedEventTypes(){return al.map((t=>`${t}`))}}const cl=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(!0,{callback:(t,e)=>{hl.PARAM_CALLBACK_updateRegister(t)},separatorAfter:!0}),this.element=ha.INTEGER(ja.indexOf(Ha.CANVAS),{menu:{entries:ja.map(((t,e)=>({name:t,value:e})))},separatorAfter:!0}),this.keydown=ha.BOOLEAN(1,qa),this.keypress=ha.BOOLEAN(0,qa),this.keyup=ha.BOOLEAN(0,qa),this.keyCodes=ha.STRING(\\\\\\\"Digit1 KeyE ArrowDown\\\\\\\",qa),this.ctrlKey=ha.BOOLEAN(0,qa),this.altKey=ha.BOOLEAN(0,qa),this.shiftKey=ha.BOOLEAN(0,qa),this.metaKey=ha.BOOLEAN(0,qa)}};class hl extends Xa{constructor(){super(...arguments),this.paramsConfig=cl}static type(){return\\\\\\\"keyboard\\\\\\\"}acceptedEventTypes(){return al.map((t=>`${t}`))}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints(al.map((t=>new ta(t,Ko.KEYBOARD)))),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{const t=[this.p.keydown,this.p.keypress,this.p.keyup];this.params.label.init(t.concat([this.p.keyCodes]),(()=>`${t.map((t=>t.value?t.name():void 0)).filter((t=>t)).join(\\\\\\\", \\\\\\\")} (${this.pv.keyCodes})`))}))}))}processEvent(t){if(!this.pv.active)return;if(!t.event)return;const e=t.event;if(e.ctrlKey!=this.pv.ctrlKey)return;if(e.shiftKey!=this.pv.shiftKey)return;if(e.altKey!=this.pv.altKey)return;if(e.metaKey!=this.pv.metaKey)return;if(this.pv.keyCodes.trim().length>0){if(!this.pv.keyCodes.split(\\\\\\\" \\\\\\\").includes(e.code))return}this.dispatchEventToOutput(t.event.type,t)}}var ul;!function(t){t.resize=\\\\\\\"resize\\\\\\\"}(ul||(ul={}));const dl=[ul.resize];class pl extends pi{constructor(){super(...arguments),this._require_canvas_event_listeners=!0}type(){return\\\\\\\"window\\\\\\\"}acceptedEventTypes(){return dl.map((t=>`${t}`))}}const _l=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(!0,{callback:t=>{ml.PARAM_CALLBACK_updateRegister(t)},separatorAfter:!0}),this.element=ha.INTEGER(0,{hidden:!0}),this.resize=ha.BOOLEAN(1,qa)}};class ml extends Xa{constructor(){super(...arguments),this.paramsConfig=_l}static type(){return\\\\\\\"window\\\\\\\"}acceptedEventTypes(){return dl.map((t=>`${t}`))}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints(dl.map((t=>new ta(t,Ko.POINTER)))),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{const t=[this.p.resize];this.params.label.init(t,(()=>t.map((t=>t.value?t.name():void 0)).filter((t=>t)).join(\\\\\\\", \\\\\\\")))}))}))}processEvent(t){this.pv.active&&t.event&&this.dispatchEventToOutput(t.event.type,t)}}var fl;!function(t){t.dragover=\\\\\\\"dragover\\\\\\\"}(fl||(fl={}));const gl=[fl.dragover];class vl extends pi{constructor(){super(...arguments),this._require_canvas_event_listeners=!0}type(){return\\\\\\\"drag\\\\\\\"}acceptedEventTypes(){return gl.map((t=>`${t}`))}}var yl;!function(t){t.touchstart=\\\\\\\"touchstart\\\\\\\",t.touchmove=\\\\\\\"touchmove\\\\\\\",t.touchend=\\\\\\\"touchend\\\\\\\"}(yl||(yl={}));const xl=[yl.touchstart,yl.touchmove,yl.touchend];class bl extends pi{constructor(){super(...arguments),this._require_canvas_event_listeners=!0}type(){return\\\\\\\"touch\\\\\\\"}acceptedEventTypes(){return xl.map((t=>`${t}`))}}const wl=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(!0,{callback:t=>{Tl.PARAM_CALLBACK_updateRegister(t)},separatorAfter:!0}),this.element=ha.INTEGER(ja.indexOf(Ha.CANVAS),{menu:{entries:ja.map(((t,e)=>({name:t,value:e})))},separatorAfter:!0}),this.dragover=ha.BOOLEAN(1,qa),this.ctrlKey=ha.BOOLEAN(0,{...qa,separatorBefore:!0}),this.altKey=ha.BOOLEAN(0,qa),this.shiftKey=ha.BOOLEAN(0,qa),this.metaKey=ha.BOOLEAN(0,qa)}};class Tl extends Xa{constructor(){super(...arguments),this.paramsConfig=wl}static type(){return\\\\\\\"drag\\\\\\\"}acceptedEventTypes(){return gl.map((t=>`${t}`))}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints(gl.map((t=>new ta(t,Ko.DRAG)))),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{const t=[this.p.dragover];this.params.label.init(t,(()=>t.map((t=>t.value?t.name():void 0)).filter((t=>t)).join(\\\\\\\", \\\\\\\")))}))}))}processEvent(t){if(!this.pv.active)return;if(!t.event)return;const e=t.event;e.ctrlKey==this.pv.ctrlKey&&e.shiftKey==this.pv.shiftKey&&e.altKey==this.pv.altKey&&e.metaKey==this.pv.metaKey&&this.dispatchEventToOutput(t.event.type,t)}}const Al=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(!0,{callback:t=>{Ml.PARAM_CALLBACK_updateRegister(t)},separatorAfter:!0}),this.element=ha.INTEGER(ja.indexOf(Ha.CANVAS),{menu:{entries:ja.map(((t,e)=>({name:t,value:e})))},separatorAfter:!0}),this.touchstart=ha.BOOLEAN(1,qa),this.touchmove=ha.BOOLEAN(0,qa),this.touchend=ha.BOOLEAN(0,qa)}};class Ml extends Xa{constructor(){super(...arguments),this.paramsConfig=Al}static type(){return\\\\\\\"touch\\\\\\\"}acceptedEventTypes(){return xl.map((t=>`${t}`))}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints(xl.map((t=>new ta(t,Ko.DRAG)))),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{const t=[this.p.touchstart,this.p.touchmove,this.p.touchend];this.params.label.init(t,(()=>t.map((t=>t.value?t.name():void 0)).filter((t=>t)).join(\\\\\\\", \\\\\\\")))}))}))}processEvent(t){this.pv.active&&t.event&&this.dispatchEventToOutput(t.event.type,t)}}class El{constructor(t){this.scene=t,this._controllers=[]}registerEventNode(t){const e=this._find_or_create_controller_for_node(t);e&&e.registerNode(t)}unregisterEventNode(t){const e=this._find_or_create_controller_for_node(t);e&&e.unregisterNode(t)}updateViewerEventListeners(t){const e=this._find_or_create_controller_for_node(t);e&&e.updateViewerEventListeners()}traverseControllers(t){for(let e of this._controllers)t(e)}_find_or_create_controller_for_node(t){switch(t.type()){case hl.type():return this.keyboardEventsController;case Ja.type():return this.mouseEventsController;case Tl.type():return this.dragEventsController;case el.type():return this.pointerEventsController;case rl.type():return this.sceneEventsController;case Ml.type():return this.touchEventsController;case ml.type():return this.windowEventsController}}get keyboardEventsController(){return this._keyboard_events_controller=this._keyboard_events_controller||this._create_controller(ll)}get mouseEventsController(){return this._mouse_events_controller=this._mouse_events_controller||this._create_controller(Ga)}get dragEventsController(){return this._drag_events_controller=this._drag_events_controller||this._create_controller(vl)}get pointerEventsController(){return this._pointer_events_controller=this._pointer_events_controller||this._create_controller(Ka)}get sceneEventsController(){return this._scene_events_controller=this._scene_events_controller||this._create_controller(fi)}get windowEventsController(){return this._window_events_controller=this._window_events_controller||this._create_controller(pl)}get touchEventsController(){return this._touch_events_controller=this._touch_events_controller||this._create_controller(bl)}_create_controller(t){const e=new t(this);return this._controllers.includes(e)||this._controllers.push(e),e}}class Sl{constructor(t){this.scene=t,this._referenced_nodes_by_src_param_id=new Map,this._referencing_params_by_referenced_node_id=new Map,this._referencing_params_by_all_named_node_ids=new Map}setReferenceFromParam(t,e){this._referenced_nodes_by_src_param_id.set(t.graphNodeId(),e),h.pushOnArrayAtEntry(this._referencing_params_by_referenced_node_id,e.graphNodeId(),t)}setNamedNodesFromParam(t){const e=t.decomposed_path.named_nodes();for(let n of e)h.pushOnArrayAtEntry(this._referencing_params_by_all_named_node_ids,n.graphNodeId(),t)}resetReferenceFromParam(t){const e=this._referenced_nodes_by_src_param_id.get(t.graphNodeId());if(e){h.popFromArrayAtEntry(this._referencing_params_by_referenced_node_id,e.graphNodeId(),t);const n=t.decomposed_path.named_nodes();for(let e of n)h.popFromArrayAtEntry(this._referencing_params_by_all_named_node_ids,e.graphNodeId(),t);this._referenced_nodes_by_src_param_id.delete(t.graphNodeId())}}referencing_params(t){return this._referencing_params_by_referenced_node_id.get(t.graphNodeId())}referencing_nodes(t){const e=this._referencing_params_by_referenced_node_id.get(t.graphNodeId());if(e){const t=new Map;for(let n of e){const e=n.node;t.set(e.graphNodeId(),e)}const n=[];return t.forEach((t=>{n.push(t)})),n}}nodes_referenced_by(t){const e=new Set([Cr.OPERATOR_PATH,Cr.NODE_PATH]),n=[];for(let i of t.params.all)e.has(i.type())&&n.push(i);const i=new Map,s=[];for(let t of n)this._check_param(t,i,s);for(let t of s)i.set(t.node.graphNodeId(),t.node);const r=[];return i.forEach((t=>{r.push(t)})),r}_check_param(t,e,n){if(t instanceof fo){const i=t.found_node(),s=t.found_param();return i&&e.set(i.graphNodeId(),i),void(s&&n.push(s))}}notifyNameUpdated(t){const e=this._referencing_params_by_all_named_node_ids.get(t.graphNodeId());if(e){const n=f.shallowClone(e);for(let e of n)e.notifyPathRebuildRequired(t)}}notifyParamsUpdated(t){const e=this._referencing_params_by_all_named_node_ids.get(t.graphNodeId());if(e){const n=f.shallowClone(e);for(let e of n)e.options.isSelectingParam()&&e.notifyTargetParamOwnerParamsUpdated(t)}}}var Cl;!function(t){t.MAX_FRAME_UPDATED=\\\\\\\"scene_maxFrameUpdated\\\\\\\",t.REALTIME_STATUS_UPDATED=\\\\\\\"scene_realtime_status_updated\\\\\\\",t.FRAME_UPDATED=\\\\\\\"scene_frame_updated\\\\\\\",t.PLAY_STATE_UPDATED=\\\\\\\"scene_play_state_updated\\\\\\\"}(Cl||(Cl={}));class Nl{constructor(t){this.scene=t,this._frame=0,this._time=0,this._realtimeState=!0,this._maxFrame=600,this._maxFrameLocked=!1,this._playing=!1,this._delta=0,this._graph_node=new Mi(t,\\\\\\\"time controller\\\\\\\")}get PLAY_EVENT_CONTEXT(){return this._PLAY_EVENT_CONTEXT=this._PLAY_EVENT_CONTEXT||{event:new Event(_i.PLAY)}}get PAUSE_EVENT_CONTEXT(){return this._PAUSE_EVENT_CONTEXT=this._PAUSE_EVENT_CONTEXT||{event:new Event(_i.PAUSE)}}get TICK_EVENT_CONTEXT(){return this._TICK_EVENT_CONTEXT=this._TICK_EVENT_CONTEXT||{event:new Event(_i.TICK)}}get graphNode(){return this._graph_node}frame(){return this._frame}time(){return this._time}maxFrame(){return this._maxFrame}maxFrameLocked(){return this._maxFrameLocked}realtimeState(){return this._realtimeState}setMaxFrame(t){this._maxFrame=Math.floor(t),this.scene.dispatchController.dispatch(this._graph_node,Cl.MAX_FRAME_UPDATED)}setMaxFrameLocked(t){this._maxFrameLocked=t,this.scene.dispatchController.dispatch(this._graph_node,Cl.MAX_FRAME_UPDATED)}setRealtimeState(t){this._realtimeState=t,this.scene.dispatchController.dispatch(this._graph_node,Cl.REALTIME_STATUS_UPDATED)}setTime(t,e=!0){var n,i;if(t!=this._time){if(this._time=t,null===(n=this._onBeforeTickCallbacks)||void 0===n||n.forEach((t=>t(this._delta))),e){const t=Math.floor(60*this._time),e=this._ensureFrameWithinBounds(t);t!=e?this.setFrame(e,!0):this._frame=t}this.scene.dispatchController.dispatch(this._graph_node,Cl.FRAME_UPDATED),this.scene.uniformsController.updateTimeDependentUniformOwners(),this.scene.cooker.block(),this.graphNode.setSuccessorsDirty(),this.scene.cooker.unblock(),this.scene.eventsDispatcher.sceneEventsController.processEvent(this.TICK_EVENT_CONTEXT),null===(i=this._onAfterTickCallbacks)||void 0===i||i.forEach((t=>t(this._delta)))}}setFrame(t,e=!0){t!=this._frame&&(t=this._ensureFrameWithinBounds(t))!=this._frame&&(this._frame=t,e&&this.setTime(this._frame/60,!1))}setFrameToStart(){this.setFrame(Nl.START_FRAME,!0)}incrementTimeIfPlaying(t){this._playing&&(this.scene.root().areChildrenCooking()||this.incrementTime(t))}incrementTime(t){if(this._realtimeState){this._delta=t;const e=this._time+this._delta;this.setTime(e)}else this.setFrame(this.frame()+1)}_ensureFrameWithinBounds(t){if(this._playing){if(this._maxFrameLocked&&t>this._maxFrame)return Nl.START_FRAME}else{if(this._maxFrameLocked&&t>this._maxFrame)return this._maxFrame;if(t=0&&this._time_dependent_uniform_owners_ids.splice(e,1)}}updateTimeDependentUniformOwners(){const t=this.scene.time();if(this._time_dependent_uniform_owners_ids)for(let e of this._time_dependent_uniform_owners_ids){this._time_dependent_uniform_owners[e].time.value=t}}addResolutionDependentUniformOwner(t,e){this._resolution_dependent_uniform_owners[t]=e,this._resolution_dependent_uniform_owners_ids||(this._resolution_dependent_uniform_owners_ids=[]),this._resolution_dependent_uniform_owners_ids.includes(t)||this._resolution_dependent_uniform_owners_ids.push(t),this._resolution&&this.updateResolutionDependentUniforms(e)}removeResolutionDependentUniformOwner(t){if(delete this._resolution_dependent_uniform_owners[t],this._resolution_dependent_uniform_owners_ids){const e=this._resolution_dependent_uniform_owners_ids.indexOf(t);e>=0&&this._resolution_dependent_uniform_owners_ids.splice(e,1)}}updateResolutionDependentUniformOwners(t){this._resolution.copy(t);for(let t of this._resolution_dependent_uniform_owners_ids){const e=this._resolution_dependent_uniform_owners[t];this.updateResolutionDependentUniforms(e)}}updateResolutionDependentUniforms(t){t.resolution.value.x=this._resolution.x,t.resolution.value.y=this._resolution.y}}class Ol{constructor(t){this.scene=t,this._viewers_by_id=new Map}registerViewer(t){this._viewers_by_id.set(t.id(),t)}unregisterViewer(t){this._viewers_by_id.delete(t.id())}traverseViewers(t){this._viewers_by_id.forEach(t)}}class Pl{constructor(){this._require_webgl2=!1}require_webgl2(){return this._require_webgl2}set_require_webgl2(){this._require_webgl2||(this._require_webgl2=!0,li.renderersController.setRequireWebGL2())}}class Rl{constructor(t){this._scene=t,this._onWindowResizeBound=this._onWindowResize.bind(this)}graphNode(){return this._coreGraphNode=this._coreGraphNode||this._createGraphNode()}_createGraphNode(){const t=new Mi(this._scene,\\\\\\\"SceneWindowController\\\\\\\");return window.addEventListener(\\\\\\\"resize\\\\\\\",this._onWindowResizeBound),t}_onWindowResize(){this.graphNode().setSuccessorsDirty()}dispose(){window.removeEventListener(\\\\\\\"resize\\\\\\\",this._onWindowResizeBound)}}class Il{constructor(){this._params_by_id=new Map,this._assets_root=null}register_param(t){this._params_by_id.set(t.graphNodeId(),t)}deregister_param(t){this._params_by_id.delete(t.graphNodeId())}traverse_params(t){this._params_by_id.forEach(((e,n)=>{t(e)}))}root(){return this._assets_root}setRoot(t){\\\\\\\"\\\\\\\"==t&&(t=null),this._assets_root=t}}class Fl{constructor(){this._cameras_controller=new r(this),this._cooker=new o(this),this.cookController=new a,this._graph=new l,this._missing_expression_references_controller=new Ti(this),this._expressions_controller=new ui,this._nodes_controller=new Ba(this),this._objects_controller=new da(this),this._references_controller=new Sl(this),this._time_controller=new Nl(this),this._read_only=!1,this._graph.setScene(this),this.nodesController.init()}threejsScene(){return this.root().object}setUuid(t){return this._uuid=t}get uuid(){return this._uuid}setName(t){return t=ss.sanitizeName(t),this._name=t}name(){return this._name}get camerasController(){return this._cameras_controller}mainCameraNode(){return this.camerasController.mainCameraNode()}get cooker(){return this._cooker}get assets(){return this._assets_controller=this._assets_controller||new Il}async waitForCooksCompleted(){return this.cookController.waitForCooksCompleted()}get dispatchController(){return this._dispatch_controller=this._dispatch_controller||new hi(this)}get eventsDispatcher(){return this._events_dispatcher=this._events_dispatcher||new El(this)}get graph(){return this._graph}get lifecycleController(){return this._lifecycle_controller=this._lifecycle_controller||new di(this)}get loadingController(){return this._loading_controller=this._loading_controller||new gi(this)}get missingExpressionReferencesController(){return this._missing_expression_references_controller}get expressionsController(){return this._expressions_controller}get nodesController(){return this._nodes_controller}createNode(t,e){return this.root().createNode(t,e)}nodesByType(t){return this.nodesController.nodesByType(t)}get objectsController(){return this._objects_controller}findObjectByMask(t){return this._objects_controller.findObjectByMask(t)}objectsByMask(t){return this._objects_controller.objectsByMask(t)}get referencesController(){return this._references_controller}get performance(){return this._performance=this._performance||new ci}get viewersRegister(){return this._viewers_register=this._viewers_register||new Ol(this)}get timeController(){return this._time_controller}setFrame(t){this.timeController.setFrame(t)}setFrameToStart(){this.timeController.setFrameToStart()}frame(){return this.timeController.frame()}time(){return this.timeController.time()}maxFrame(){return this.timeController.maxFrame()}play(){this.timeController.play()}pause(){this.timeController.pause()}get serializer(){return this._serializer=this._serializer||new za(this)}toJSON(){return this.serializer.toJSON()}markAsReadOnly(t){this._read_only||(this._read_only_requester=t,this._read_only=!0)}readOnly(){return this._read_only}readOnlyRequester(){return this._read_only_requester}get uniformsController(){return this._uniformsController=this._uniformsController||new Ll(this)}get webgl_controller(){return this._webgl_controller=this._webgl_controller||new Pl}get windowController(){return this._windowController=this._windowController||new Rl(this)}dispose(){var t;null===(t=this._windowController)||void 0===t||t.dispose()}batchUpdates(t){this._cooker.block(),t(),this._cooker.unblock()}node(t){return this.nodesController.node(t)}root(){return this.nodesController.root()}registerOnBeforeTick(t,e){this.timeController.registerOnBeforeTick(t,e)}unRegisterOnBeforeTick(t){this.timeController.unRegisterOnBeforeTick(t)}registeredBeforeTickCallbacks(){return this.timeController.registeredBeforeTickCallbacks()}registerOnAfterTick(t,e){this.timeController.registerOnAfterTick(t,e)}unRegisterOnAfterTick(t){this.timeController.unRegisterOnAfterTick(t)}registeredAfterTickCallbacks(){return this.timeController.registeredAfterTickCallbacks()}}class Dl{constructor(t){this._param=t}process_data(t){const e=t.raw_input;void 0!==e&&this._param.set(e),this.add_main(t)}add_main(t){}static spare_params_data(t){return this.params_data(!0,t)}static non_spare_params_data_value(t){return this.params_data_value(!1,t)}static params_data(t,e){let n;if(e){n={};const t=Object.keys(e);let i;for(let s of t)i=e[s],i&&(n[s]=e)}return n}static params_data_value(t,e){let n;if(e){n={};const i=Object.keys(e);let s;for(let r of i)if(s=e[r],null!=s){const e=s.options,i=s.overriden_options;if(e||i){const o=s;e&&e.spare==t?null!=o.raw_input&&(n[r]={complex_data:o}):i&&(n[r]={complex_data:o})}else{const t=s;(i||null!=t)&&(n[r]={simple_data:t})}}}return n}}const Bl=\\\\\\\"operationsComposer\\\\\\\";class zl{constructor(t,e,n){this._scene=t,this.states=e,this._node=n}static type(){throw\\\\\\\"type to be overriden\\\\\\\"}type(){return this.constructor.type()}static context(){throw console.error(\\\\\\\"operation has no node_context\\\\\\\",this),\\\\\\\"context requires override\\\\\\\"}context(){return this.constructor.context()}scene(){return this._scene}cook(t,e){}}zl.DEFAULT_PARAMS={},zl.INPUT_CLONED_STATE=[];class kl{constructor(t){this._node=t,this._nodes=[],this._optimized_root_node_names=new Set,this._operation_containers_by_name=new Map,this._node_inputs=[]}nodes(){return this._nodes}process_data(t,e){var n,i,s;if(!e)return;if(!this._node.childrenAllowed()||!this._node.childrenController)return;const{optimized_names:r}=kl.child_names_by_optimized_state(e);this._nodes=[],this._optimized_root_node_names=new Set;for(let t of r)kl.is_optimized_root_node(e,t)&&this._optimized_root_node_names.add(t);for(let r of this._optimized_root_node_names){const o=e[r],a=this._node.createNode(Bl);if(a){a.setName(r),this._nodes.push(a),(null===(n=o.flags)||void 0===n?void 0:n.display)&&(null===(s=null===(i=a.flags)||void 0===i?void 0:i.display)||void 0===s||s.set(!0));const e=this._create_operation_container(t,a,o,a.name());a.set_output_operation_container(e)}}for(let n of this._nodes){const i=n.output_operation_container();if(i){this._node_inputs=[],this._add_optimized_node_inputs(t,n,e,n.name(),i),n.io.inputs.setCount(this._node_inputs.length);for(let t=0;t0}static is_optimized_root_node(t,e){const n=this.node_outputs(t,e);let i=0;return n.forEach((e=>{const n=t[e];this.is_node_optimized(n)||i++})),this.is_optimized_root_node_generic({outputs_count:n.size,non_optimized_count:i})}static is_optimized_root_node_from_node(t){var e,n,i,s;if(!(null===(n=null===(e=t.flags)||void 0===e?void 0:e.optimize)||void 0===n?void 0:n.active()))return!1;const r=t.io.connections.outputConnections().map((t=>t.node_dest));let o=0;for(let t of r)(null===(s=null===(i=t.flags)||void 0===i?void 0:i.optimize)||void 0===s?void 0:s.active())||o++;return this.is_optimized_root_node_generic({outputs_count:r.length,non_optimized_count:o})}static node_outputs(t,e){const n=Object.keys(t),i=new Set;for(let s of n)if(s!=e){const n=t[s].inputs;if(n)for(let t of n)if(m.isString(t)){t==e&&i.add(s)}}return i}_create_operation_container(t,e,n,i){const s=Dl.non_spare_params_data_value(n.params),r=kl.operation_type(n),o=this._node.create_operation_container(r,i,s);return o&&(this._operation_containers_by_name.set(i,o),o.path_param_resolve_required()&&(e.add_operation_container_with_path_param_resolve_required(o),t.add_operations_composer_node_with_path_param_resolve_required(e))),o}static operation_type(t){return kl.is_node_bypassed(t)?\\\\\\\"null\\\\\\\":t.type}static is_node_optimized(t){const e=t.flags;return!(!e||!e.optimize)}static is_node_bypassed(t){const e=t.flags;return!(!e||!e.bypass)}}class Ul{constructor(t){this._node=t}process_data(t,e){var n;if(!e)return;if(!this._node.childrenAllowed()||!this._node.childrenController)return;const{optimized_names:i,non_optimized_names:s}=kl.child_names_by_optimized_state(e),r=[];for(let n of s){const i=e[n],s=i.type.toLowerCase(),o=Dl.non_spare_params_data_value(i.params);try{const t=this._node.createNode(s,o);t&&(t.setName(n),r.push(t))}catch(e){console.error(`error importing node: cannot create with type ${s}`,e);const i=ss.camelCase(s);try{const t=this._node.createNode(i,o);t&&(t.setName(n),r.push(t))}catch(e){const a=`${s}Network`;try{const t=this._node.createNode(a,o);t&&(t.setName(n),r.push(t))}catch(e){const n=`failed to create node with type '${s}', '${i}' or '${a}'`;t.report.addWarning(n),li.warn(n,e)}}}}if(i.length>0){const i=new kl(this._node);if(i.process_data(t,e),this._node.childrenController.context==ts.SOP){const t=Object.keys(e);let s;for(let i of t){(null===(n=e[i].flags)||void 0===n?void 0:n.display)&&(s=i)}if(s){const t=r.map((t=>t.name())),e=i.nodes();for(let n of e)t.push(n.name());if(!t.includes(s)){const t=`node '${`${this._node.path()}/${s}`}' with display flag has been optimized and does not exist in player mode`;console.error(t)}}}}const o=new Map;for(let n of r){if(e[n.name()]){const i=Yl.dispatch_node(n);o.set(n.name(),i),i.process_data(t,e[n.name()])}else li.warn(`possible import error for node ${n.name()}`)}for(let t of r){const n=o.get(t.name());n&&n.process_inputs_data(e[t.name()])}}}const Gl=[\\\\\\\"overriden_options\\\\\\\",\\\\\\\"type\\\\\\\"];class Vl{constructor(t){this._node=t}process_data(t,e){if(this.set_connection_points(e.connection_points),this._node.childrenAllowed()&&this.create_nodes(t,e.nodes),this.set_selection(e.selection),this._node.io.inputs.overrideClonedStateAllowed()){const t=e.cloned_state_overriden;t&&this._node.io.inputs.overrideClonedState(t)}this.set_flags(e),this.set_params(e.params),e.persisted_config&&this.set_persisted_config(e.persisted_config),this.from_data_custom(e)}process_inputs_data(t){const e=t.maxInputsCount;if(null!=e){const t=this._node.io.inputs.minCount();this._node.io.inputs.setCount(t,e)}this.setInputs(t.inputs)}process_ui_data(t,e){if(!e)return;if(li.playerMode())return;const n=this._node.uiData,i=e.pos;if(i){const t=(new d.a).fromArray(i);n.setPosition(t)}const s=e.comment;s&&n.setComment(s),this._node.childrenAllowed()&&this.process_nodes_ui_data(t,e.nodes)}create_nodes(t,e){if(!e)return;new Ul(this._node).process_data(t,e)}set_selection(t){if(this._node.childrenAllowed()&&this._node.childrenController&&t&&t.length>0){const e=[];t.forEach((t=>{const n=this._node.node(t);n&&e.push(n)})),this._node.childrenController.selection.set(e)}}set_flags(t){var e,n,i,s,r,o;const a=t.flags;if(a){const t=a.bypass;null!=t&&(null===(n=null===(e=this._node.flags)||void 0===e?void 0:e.bypass)||void 0===n||n.set(t));const l=a.display;null!=l&&(null===(s=null===(i=this._node.flags)||void 0===i?void 0:i.display)||void 0===s||s.set(l));const c=a.optimize;null!=c&&(null===(o=null===(r=this._node.flags)||void 0===r?void 0:r.optimize)||void 0===o||o.set(c))}}set_connection_points(t){t&&(t.in&&this._node.io.saved_connection_points_data.set_in(t.in),t.out&&this._node.io.saved_connection_points_data.set_out(t.out),this._node.io.has_connection_points_controller&&this._node.io.connection_points.update_signature_if_required())}setInputs(t){if(!t)return;let e;for(let n=0;n0,s=n.toAdd&&n.toAdd.length>0;if(i||s){this._node.params.updateParams(n);for(let e of this._node.params.spare){const n=t[e.name()];!e.parent_param&&n&&(this._is_param_data_complex(n)?this._process_param_data_complex(e.name(),n):this._process_param_data_simple(e.name(),n))}}this._node.params.runOnSceneLoadHooks()}_process_param_data_simple(t,e){var n;null===(n=this._node.params.get(t))||void 0===n||n.set(e)}_process_param_data_complex(t,e){const n=this._node.params.get(t);n&&Yl.dispatch_param(n).process_data(e)}_is_param_data_complex(t){if(m.isString(t)||m.isNumber(t)||m.isArray(t)||m.isBoolean(t))return!1;if(m.isObject(t)){const e=Object.keys(t);for(let t of Gl)if(e.includes(t))return!0}return!1}set_persisted_config(t){this._node.persisted_config&&this._node.persisted_config.load(t)}from_data_custom(t){}}class Hl extends Dl{add_main(t){}}const jl=/\\\\\\\\n+/g;class Wl extends Dl{add_main(t){let e=t.raw_input;void 0!==e&&(e=e.replace(jl,\\\\\\\"\\\\n\\\\\\\"),this._param.set(e))}}class ql extends Dl{add_main(t){const e=t.raw_input;e&&this._param.set(e)}}class Xl extends Vl{create_nodes(t,e){const n=this._node.polyNodeController;n&&n.createChildNodesFromDefinition()}}class Yl{static dispatch_node(t){return t.polyNodeController?new Xl(t):new Vl(t)}static dispatch_param(t){return t instanceof ao?new Hl(t):t instanceof Mo?new Wl(t):t instanceof Ao?new ql(t):new Dl(t)}}class $l{constructor(t){this._warnings=[]}warnings(){return this._warnings}reset(){this._warnings=[]}addWarning(t){this._warnings.push(t)}}class Jl{constructor(t){this._data=t,this.report=new $l(this)}static async loadData(t){const e=new Jl(t);return await e.scene()}async scene(){const t=new Fl;t.loadingController.markAsLoading();const e=this._data.properties;if(e){const n=e.maxFrame||600;t.timeController.setMaxFrame(n);const i=e.maxFrameLocked;i&&t.timeController.setMaxFrameLocked(i);const s=e.realtimeState;null!=s&&t.timeController.setRealtimeState(s),t.setFrame(e.frame||Nl.START_FRAME),e.mainCameraNodePath&&t.camerasController.setMainCameraNodePath(e.mainCameraNodePath)}t.cooker.block(),this._base_operations_composer_nodes_with_resolve_required=void 0;const n=Yl.dispatch_node(t.root());return this._data.root&&n.process_data(this,this._data.root),this._data.ui&&n.process_ui_data(this,this._data.ui),this._resolve_operation_containers_with_path_param_resolve(),await t.loadingController.markAsLoaded(),t.cooker.unblock(),t}add_operations_composer_node_with_path_param_resolve_required(t){this._base_operations_composer_nodes_with_resolve_required||(this._base_operations_composer_nodes_with_resolve_required=[]),this._base_operations_composer_nodes_with_resolve_required.push(t)}_resolve_operation_containers_with_path_param_resolve(){if(this._base_operations_composer_nodes_with_resolve_required)for(let t of this._base_operations_composer_nodes_with_resolve_required)t.resolve_operation_containers_path_params()}}class Zl{static async importSceneData(t){null==t.editorMode&&(t.editorMode=!1);const{manifest:e,urlPrefix:n}=t,i=Object.keys(e.nodes),s=[];for(let t of i){const i=`${n}/root/${t}.json?t=${e.nodes[t]}`;s.push(i)}const r=[`${n}/root.json?t=${e.root}`,`${n}/properties.json?t=${e.properties}`];if(t.editorMode){const t=Date.now();r.push(`${n}/ui.json?t=${t}`)}for(let t of s)r.push(t);let o=0;const a=r.length,l=r.map((async e=>{const n=await fetch(e);return t.onProgress&&(o++,t.onProgress({count:o,total:a})),n})),c=await Promise.all(l),h=[];for(let t of c)h.push(await t.json());const u={root:h[0],properties:h[1]};let d=2;t.editorMode&&(u.ui=h[2],d+=1);const p={},_=Object.keys(e.nodes);for(let t=0;t<_.length;t++){const e=_[t],n=h[t+d];p[e]=n}return this.assemble(u,_,p)}static async assemble(t,e,n){const i={root:t.root,properties:t.properties,ui:t.ui};for(let t=0;t{r.matrixAutoUpdate=!0},c.onComplete=()=>{r.matrixAutoUpdate=t,r.matrixAutoUpdate||r.updateMatrix()}}if(o instanceof hh.a&&this._targetValue instanceof hh.a){const t={value:0},e=o,n=(new hh.a).copy(o),i=this._targetValue;c.onUpdate=()=>{e.slerpQuaternions(n,i,t.value)},a=t,c.value=1}if(m.isNumber(this._targetValue)){if(m.isNumber(o))for(let t of l)c[t]=this.withOp(o,this._targetValue,i)}else if(!m.isNumber(o))for(let t of l)c[t]=this.withOp(o[t],this._targetValue[t],i);a&&this._startTimeline(e,n,c,a)}}}_sceneGraphProps(t,e){const n=e.split(\\\\\\\".\\\\\\\");if(!(n.length>1)){const n=t[e];let i=null;const s=[];return m.isNumber(n)?(i=t,s.push(e)):(i=n,this._targetValue instanceof d.a&&s.push(\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\"),this._targetValue instanceof p.a&&s.push(\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\"),this._targetValue instanceof _.a&&s.push(\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\",\\\\\\\"w\\\\\\\"),this._targetValue,hh.a),{targetProperty:n,toTarget:i,propertyNames:s}}{const e=t[n.shift()];if(e){const t=n.join(\\\\\\\".\\\\\\\");return this._sceneGraphProps(e,t)}}}_populateWithNode(t,e,n){this._printDebug([\\\\\\\"_populateWithNode\\\\\\\",t]);const i=t.p[this._propertyName];this._printDebug([\\\\\\\"targetParam\\\\\\\",i]),i?i&&this._populateVarsForParam(i,e,n):li.warn(`${this._propertyName} not found on node ${t.path()}`)}_populateVarsForParam(t,e,n){switch(this._printDebug([\\\\\\\"_populateVarsForParam\\\\\\\",t]),t.type()){case Cr.INTEGER:return this._populateVarsForParamInteger(t,e,n);case Cr.FLOAT:return this._populateVarsForParamFloat(t,e,n);case Cr.VECTOR2:return this._populateVarsForParamVector2(t,e,n);case Cr.VECTOR3:return this._populateVarsForParamVector3(t,e,n);case Cr.COLOR:return this._populateVarsForParamColor(t,e,n);case Cr.VECTOR4:return this._populateVarsForParamVector4(t,e,n)}li.warn(`param type cannot be animated (yet): '${t.type()}' '${t.path()}'`)}_populateVarsForParamInteger(t,e,n){if(!m.isNumber(this._targetValue))return void li.warn(`TimelineBuilderProperty error: cannot animate integer param '${t.path()}' with targetValue`,this._targetValue);const i=this._commonVars(e),s={num:t.value};i.onUpdate=()=>{t.set(s.num)};const r=e.operation();i.num=this.withOp(t.value,this._targetValue,r),this._startTimeline(e,n,i,s)}_populateVarsForParamFloat(t,e,n){if(!m.isNumber(this._targetValue))return void li.warn(`TimelineBuilderProperty error: cannot animate float param '${t.path()}' with targetValue`,this._targetValue);const i=this._commonVars(e),s={num:t.value};i.onUpdate=()=>{t.set(s.num)};const r=e.operation();i.num=this.withOp(t.value,this._targetValue,r),this._startTimeline(e,n,i,s)}_populateVarsForParamVector2(t,e,n){if(!(this._targetValue instanceof d.a))return void li.warn(`TimelineBuilderProperty error: cannot animate vector2 param '${t.path()}' with targetValue`,this._targetValue);const i=this._commonVars(e),s=t.value.clone(),r=[0,0];i.onUpdate=()=>{s.toArray(r),t.set(r)};const o=e.operation();i.x=this.withOp(t.value.x,this._targetValue.x,o),i.y=this.withOp(t.value.y,this._targetValue.y,o),this._startTimeline(e,n,i,s)}_populateVarsForParamVector3(t,e,n){if(!(this._targetValue instanceof p.a))return void li.warn(`TimelineBuilderProperty error: cannot animate vector3 param '${t.path()}' with targetValue`,this._targetValue);const i=this._commonVars(e),s=t.value.clone(),r=[0,0,0];i.onUpdate=()=>{s.toArray(r),t.set(r)};const o=e.operation();i.x=this.withOp(t.value.x,this._targetValue.x,o),i.y=this.withOp(t.value.y,this._targetValue.y,o),i.z=this.withOp(t.value.z,this._targetValue.z,o),this._startTimeline(e,n,i,s)}_populateVarsForParamVector4(t,e,n){if(!(this._targetValue instanceof _.a))return void li.warn(`TimelineBuilderProperty error: cannot animate vector4 param '${t.path()}' with targetValue`,this._targetValue);const i=this._commonVars(e),s=t.value.clone(),r=[0,0,0,0];i.onUpdate=()=>{s.toArray(r),t.set(r)};const o=e.operation();i.x=this.withOp(t.value.x,this._targetValue.x,o),i.y=this.withOp(t.value.y,this._targetValue.y,o),i.z=this.withOp(t.value.z,this._targetValue.z,o),i.w=this.withOp(t.value.w,this._targetValue.w,o),this._startTimeline(e,n,i,s)}_populateVarsForParamColor(t,e,n){if(!(this._targetValue instanceof p.a))return void li.warn(`TimelineBuilderProperty error: cannot animate color param '${t.path()}' with targetValue`,this._targetValue);const i=this._commonVars(e),s=t.valuePreConversion(),r=new p.a(s.r,s.g,s.b),o=[0,0,0];i.onUpdate=()=>{r.toArray(o),t.set(o)};const a=e.operation();i.x=this.withOp(t.value.r,this._targetValue.x,a),i.y=this.withOp(t.value.g,this._targetValue.y,a),i.z=this.withOp(t.value.b,this._targetValue.z,a),this._startTimeline(e,n,i,r)}withOp(t,e,n){switch(n){case I_.SET:return e;case I_.ADD:return t+e;case I_.SUBSTRACT:return t-e}os.unreachable(n)}_commonVars(t){const e={duration:t.duration()},n=t.easing()||ch.NONE;n&&(e.ease=n);const i=t.delay();null!=i&&(e.delay=i);const s=t.repeatParams();return s&&(e.repeat=s.count,e.repeatDelay=s.delay,e.yoyo=s.yoyo),e}_startTimeline(t,e,n,i){const s=t.position(),r=s?s.toParameter():void 0;e.to(i,n,r)}}function mh(t){if(void 0===t)throw new ReferenceError(\\\\\\\"this hasn't been initialised - super() hasn't been called\\\\\\\");return t}function fh(t,e){t.prototype=Object.create(e.prototype),t.prototype.constructor=t,t.__proto__=e}var gh,vh,yh,xh,bh,wh,Th,Ah,Mh,Eh,Sh,Ch,Nh,Lh={autoSleep:120,force3D:\\\\\\\"auto\\\\\\\",nullTargetWarn:1,units:{lineHeight:\\\\\\\"\\\\\\\"}},Oh={duration:.5,overwrite:!1,delay:0},Ph=1e8,Rh=1e-8,Ih=2*Math.PI,Fh=Ih/4,Dh=0,Bh=Math.sqrt,zh=Math.cos,kh=Math.sin,Uh=function(t){return\\\\\\\"string\\\\\\\"==typeof t},Gh=function(t){return\\\\\\\"function\\\\\\\"==typeof t},Vh=function(t){return\\\\\\\"number\\\\\\\"==typeof 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oh{constructor(){super(...arguments),this.paramsConfig=rm}static type(){return\\\\\\\"position\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,1),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.mode,this.p.relativeTo,this.p.offset],(()=>{switch(X_[this.pv.mode]){case q_.RELATIVE:return this._relative_label();case q_.ABSOLUTE:return this._absolute_label()}}))}))}))}_relative_label(){const t=this.pv.offset>0?\\\\\\\"after\\\\\\\":\\\\\\\"before\\\\\\\",e=$_[this.pv.relativeTo];return`${Math.abs(this.pv.offset)} ${t} ${e}`}_absolute_label(){return\\\\\\\"absolute\\\\\\\"}cook(t){const e=t[0]||new B_,n=new J_;n.setMode(X_[this.pv.mode]),n.setRelativeTo($_[this.pv.relativeTo]),n.setOffset(this.pv.offset),e.setPosition(n),this.setTimelineBuilder(e)}}const am=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(\\\\\\\"position\\\\\\\")}};class lm extends oh{constructor(){super(...arguments),this.paramsConfig=am}static type(){return\\\\\\\"propertyName\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,1),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name])}))}))}cook(t){const e=t[0]||new B_;e.setPropertyName(this.pv.name),this.setTimelineBuilder(e)}}var cm;!function(t){t.CUSTOM=\\\\\\\"custom\\\\\\\",t.FROM_SCENE_GRAPH=\\\\\\\"from scene graph\\\\\\\",t.FROM_NODE=\\\\\\\"from node\\\\\\\"}(cm||(cm={}));const hm=[cm.CUSTOM,cm.FROM_SCENE_GRAPH,cm.FROM_NODE],um=hm.indexOf(cm.CUSTOM),dm=hm.indexOf(cm.FROM_SCENE_GRAPH),pm=hm.indexOf(cm.FROM_NODE);const _m=new class extends ua{constructor(){super(...arguments),this.mode=ha.INTEGER(um,{menu:{entries:hm.map(((t,e)=>({name:t,value:e})))}}),this.nodePath=ha.NODE_PATH(\\\\\\\"\\\\\\\",{visibleIf:{mode:pm}}),this.objectMask=ha.STRING(\\\\\\\"*geo1\\\\\\\",{visibleIf:{mode:dm}}),this.printResolve=ha.BUTTON(null,{visibleIf:{mode:dm},callback:t=>{mm.PARAM_CALLBACK_printResolve(t)}}),this.overridePropertyName=ha.BOOLEAN(0,{visibleIf:[{mode:dm},{mode:pm}]}),this.propertyName=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:[{overridePropertyName:!0,mode:dm},{overridePropertyName:!0,mode:pm}]}),this.size=ha.INTEGER(3,{range:[1,4],rangeLocked:[!0,!0],visibleIf:{mode:um}}),this.value1=ha.FLOAT(0,{visibleIf:{mode:um,size:1}}),this.value2=ha.VECTOR2([0,0],{visibleIf:{mode:um,size:2}}),this.value3=ha.VECTOR3([0,0,0],{visibleIf:{mode:um,size:3}}),this.value4=ha.VECTOR4([0,0,0,0],{visibleIf:{mode:um,size:4}})}};class mm extends oh{constructor(){super(...arguments),this.paramsConfig=_m}static type(){return\\\\\\\"propertyValue\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,1)}async cook(t){const e=t[0]||new B_;await this._prepareTimelineBuilder(e),this.setTimelineBuilder(e)}setMode(t){this.p.mode.set(hm.indexOf(t))}async _prepareTimelineBuilder(t){const e=hm[this.pv.mode];switch(e){case cm.CUSTOM:return this._prepareTimebuilderCustom(t);case cm.FROM_SCENE_GRAPH:return this._prepareTimebuilderFromSceneGraph(t);case cm.FROM_NODE:return await this._prepareTimebuilderFromNode(t)}os.unreachable(e)}_prepareTimebuilderCustom(t){const e=[this.pv.value1,this.pv.value2.clone(),this.pv.value3.clone(),this.pv.value4.clone()][this.pv.size-1];t.setPropertyValue(e)}_prepareTimebuilderFromSceneGraph(t){const e=this.pv.overridePropertyName?this.pv.propertyName:t.propertyName();if(!e)return;const n=this._foundObjectFromSceneGraph();if(n){const i=n[e];i&&(m.isNumber(i)||m.isVector(i)||i instanceof hh.a)&&t.setPropertyValue(i)}}async _prepareTimebuilderFromNode(t){const e=this.pv.overridePropertyName?this.pv.propertyName:t.propertyName();if(!e)return;const n=this.pv.nodePath.node();if(!n)return;const i=n.params.get(e);if(!i)return;i.isDirty()&&await i.compute();const s=i.value;s&&(m.isNumber(s)||m.isVector(s))&&t.setPropertyValue(s)}static PARAM_CALLBACK_printResolve(t){t.printResolve()}_foundObjectFromSceneGraph(){return this.scene().findObjectByMask(this.pv.objectMask)}printResolve(){const t=this._foundObjectFromSceneGraph();console.log(t)}}const fm=new class extends ua{constructor(){super(...arguments),this.unlimited=ha.BOOLEAN(0),this.count=ha.INTEGER(1,{range:[0,10],visibleIf:{unlimited:0}}),this.delay=ha.FLOAT(0),this.yoyo=ha.BOOLEAN(0)}};class gm extends oh{constructor(){super(...arguments),this.paramsConfig=fm}static type(){return\\\\\\\"repeat\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,1),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.unlimited,this.p.count,this.p.yoyo],(()=>`${`${this.p.unlimited?\\\\\\\"unlimited\\\\\\\":this.pv.count}`} (yoyo: ${this.pv.yoyo})`))}))}))}_repeat_params(){return{count:this.pv.unlimited?-1:this.pv.count,delay:this.pv.delay,yoyo:this.pv.yoyo}}cook(t){const e=t[0]||new B_;e.setRepeatParams(this._repeat_params()),this.setTimelineBuilder(e)}}const vm=new class extends ua{constructor(){super(...arguments),this.input=ha.INTEGER(0,{range:[0,3],rangeLocked:[!0,!0]})}};class ym extends oh{constructor(){super(...arguments),this.paramsConfig=vm}static type(){return\\\\\\\"switch\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,4)}cook(t){const e=t[this.pv.input];e?this.setTimelineBuilder(e):this.states.error.set(`input ${this.pv.input} is not valid`)}}class xm{constructor(t,e){this._scene=t,this._options=e}clone(){return new xm(this._scene,this._options)}objects(){const t=this._options.objectMask;if(t)return this._scene.objectsByMask(t)}node(){if(!this._options.node)return;const t=this._options.node;return t.relativeTo.node(t.path)}}class bm{constructor(){this._update_matrix=!1}clone(){const t=new bm;return t.setUpdateMatrix(this._update_matrix),t}setUpdateMatrix(t){this._update_matrix=t}updateMatrix(){return this._update_matrix}}var wm;!function(t){t.SCENE_GRAPH=\\\\\\\"scene graph\\\\\\\",t.NODE=\\\\\\\"node\\\\\\\"}(wm||(wm={}));const Tm=[wm.SCENE_GRAPH,wm.NODE],Am=Tm.indexOf(wm.SCENE_GRAPH),Mm=Tm.indexOf(wm.NODE);const Em=new class extends ua{constructor(){super(...arguments),this.type=ha.INTEGER(Am,{menu:{entries:Tm.map(((t,e)=>({name:t,value:e})))}}),this.nodePath=ha.OPERATOR_PATH(\\\\\\\"\\\\\\\",{visibleIf:{type:Mm}}),this.objectMask=ha.STRING(\\\\\\\"/geo*\\\\\\\",{visibleIf:{type:Am}}),this.updateMatrix=ha.BOOLEAN(0,{visibleIf:{type:Am}}),this.printResolve=ha.BUTTON(null,{callback:(t,e)=>{Sm.PARAM_CALLBACK_print_resolve(t)}})}};class Sm extends oh{constructor(){super(...arguments),this.paramsConfig=Em}static type(){return\\\\\\\"target\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,1),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.type,this.p.nodePath,this.p.objectMask],(()=>{const t=Tm[this.pv.type];switch(t){case wm.NODE:return this.pv.nodePath;case wm.SCENE_GRAPH:return this.pv.objectMask}os.unreachable(t)}))}))}))}cook(t){const e=t[0]||new B_,n=this._create_target(e);e.setTarget(n),this._set_update_callback(e),this.setTimelineBuilder(e)}setTargetType(t){this.p.type.set(Tm.indexOf(t))}_create_target(t){const e=Tm[this.pv.type];switch(e){case wm.NODE:return new xm(this.scene(),{node:{path:this.pv.nodePath,relativeTo:this}});case wm.SCENE_GRAPH:return new xm(this.scene(),{objectMask:this.pv.objectMask})}os.unreachable(e)}_set_update_callback(t){const e=Tm[this.pv.type];let n=t.updateCallback();switch(e){case wm.NODE:return;case wm.SCENE_GRAPH:return void(this.pv.updateMatrix&&(n=n||new bm,n.setUpdateMatrix(this.pv.updateMatrix),t.setUpdateCallback(n)))}os.unreachable(e)}static PARAM_CALLBACK_print_resolve(t){t.print_resolve()}print_resolve(){const t=Tm[this.pv.type],e=new B_,n=this._create_target(e);switch(t){case wm.NODE:return console.log(n.node());case wm.SCENE_GRAPH:return console.log(n.objects())}}}class Cm extends aa{static context(){return ts.ANIM}cook(){this.cookController.endCook()}}class Nm extends Cm{}class Lm extends Nm{constructor(){super(...arguments),this._children_controller_context=ts.ANIM}static type(){return es.ANIM}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class Om extends Nm{constructor(){super(...arguments),this._children_controller_context=ts.COP}static type(){return es.COP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class Pm extends Nm{constructor(){super(...arguments),this._children_controller_context=ts.EVENT}static type(){return es.EVENT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class Rm extends Nm{constructor(){super(...arguments),this._children_controller_context=ts.MAT}static type(){return es.MAT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}const Im={dependsOnDisplayNode:!0};class Fm{constructor(t,e,n=Im){this.node=t,this.options=n,this._initialized=!1,this._display_node=void 0,this._graph_node=new Mi(t.scene(),\\\\\\\"DisplayNodeController\\\\\\\"),this._graph_node.node=t,this._on_display_node_remove_callback=e.onDisplayNodeRemove,this._on_display_node_set_callback=e.onDisplayNodeSet,this._on_display_node_update_callback=e.onDisplayNodeUpdate}dispose(){this._graph_node.dispose()}displayNode(){return this._display_node}initializeNode(){this._initialized?console.error(\\\\\\\"display node controller already initialed\\\\\\\",this.node):(this._initialized=!0,this.node.lifecycle.add_on_child_add_hook((t=>{var e,n;this._display_node||null===(n=null===(e=t.flags)||void 0===e?void 0:e.display)||void 0===n||n.set(!0)})),this.node.lifecycle.add_on_child_remove_hook((t=>{var e,n,i;if(t.graphNodeId()==(null===(e=this._display_node)||void 0===e?void 0:e.graphNodeId())){const t=this.node.children(),e=t[t.length-1];e?null===(i=null===(n=e.flags)||void 0===n?void 0:n.display)||void 0===i||i.set(!0):this.setDisplayNode(void 0)}})),this._graph_node.dirtyController.addPostDirtyHook(\\\\\\\"_request_display_node_container\\\\\\\",(()=>{this._on_display_node_update_callback&&this._on_display_node_update_callback()})))}async setDisplayNode(t){if(this._initialized||console.error(\\\\\\\"display node controller not initialized\\\\\\\",this.node),this._display_node!=t){const e=this._display_node;e&&(e.flags.display.set(!1),this.options.dependsOnDisplayNode&&this._graph_node.removeGraphInput(e),this._on_display_node_remove_callback&&this._on_display_node_remove_callback()),this._display_node=t,this._display_node&&(this.options.dependsOnDisplayNode&&this._graph_node.addGraphInput(this._display_node),this._on_display_node_set_callback&&this._on_display_node_set_callback())}}}class Dm{constructor(t=!0){this.autoStart=t,this.startTime=0,this.oldTime=0,this.elapsedTime=0,this.running=!1}start(){this.startTime=Bm(),this.oldTime=this.startTime,this.elapsedTime=0,this.running=!0}stop(){this.getElapsedTime(),this.running=!1,this.autoStart=!1}getElapsedTime(){return this.getDelta(),this.elapsedTime}getDelta(){let t=0;if(this.autoStart&&!this.running)return this.start(),0;if(this.running){const e=Bm();t=(e-this.oldTime)/1e3,this.oldTime=e,this.elapsedTime+=t}return t}}function Bm(){return(\\\\\\\"undefined\\\\\\\"==typeof performance?Date:performance).now()}var zm={uniforms:{tDiffuse:{value:null},opacity:{value:1}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform float opacity;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 texel = texture2D( tDiffuse, vUv );\\\\n\\\\t\\\\t\\\\tgl_FragColor = opacity * texel;\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};class km{constructor(){this.enabled=!0,this.needsSwap=!0,this.clear=!1,this.renderToScreen=!1}setSize(){}render(){console.error(\\\\\\\"THREE.Pass: .render() must be implemented in derived pass.\\\\\\\")}}const Um=new ot.a(-1,1,1,-1,0,1),Gm=new S.a;Gm.setAttribute(\\\\\\\"position\\\\\\\",new C.c([-1,3,0,-1,-1,0,3,-1,0],3)),Gm.setAttribute(\\\\\\\"uv\\\\\\\",new C.c([0,2,0,0,2,0],2));class Vm{constructor(t){this._mesh=new B.a(Gm,t)}dispose(){this._mesh.geometry.dispose()}render(t){t.render(this._mesh,Um)}get material(){return this._mesh.material}set material(t){this._mesh.material=t}}class Hm extends km{constructor(t,e){super(),this.textureID=void 0!==e?e:\\\\\\\"tDiffuse\\\\\\\",t instanceof F?(this.uniforms=t.uniforms,this.material=t):t&&(this.uniforms=I.clone(t.uniforms),this.material=new F({defines:Object.assign({},t.defines),uniforms:this.uniforms,vertexShader:t.vertexShader,fragmentShader:t.fragmentShader})),this.fsQuad=new Vm(this.material)}render(t,e,n){this.uniforms[this.textureID]&&(this.uniforms[this.textureID].value=n.texture),this.fsQuad.material=this.material,this.renderToScreen?(t.setRenderTarget(null),this.fsQuad.render(t)):(t.setRenderTarget(e),this.clear&&t.clear(t.autoClearColor,t.autoClearDepth,t.autoClearStencil),this.fsQuad.render(t))}}class jm extends km{constructor(t,e){super(),this.scene=t,this.camera=e,this.clear=!0,this.needsSwap=!1,this.inverse=!1}render(t,e,n){const i=t.getContext(),s=t.state;let r,o;s.buffers.color.setMask(!1),s.buffers.depth.setMask(!1),s.buffers.color.setLocked(!0),s.buffers.depth.setLocked(!0),this.inverse?(r=0,o=1):(r=1,o=0),s.buffers.stencil.setTest(!0),s.buffers.stencil.setOp(i.REPLACE,i.REPLACE,i.REPLACE),s.buffers.stencil.setFunc(i.ALWAYS,r,4294967295),s.buffers.stencil.setClear(o),s.buffers.stencil.setLocked(!0),t.setRenderTarget(n),this.clear&&t.clear(),t.render(this.scene,this.camera),t.setRenderTarget(e),this.clear&&t.clear(),t.render(this.scene,this.camera),s.buffers.color.setLocked(!1),s.buffers.depth.setLocked(!1),s.buffers.stencil.setLocked(!1),s.buffers.stencil.setFunc(i.EQUAL,1,4294967295),s.buffers.stencil.setOp(i.KEEP,i.KEEP,i.KEEP),s.buffers.stencil.setLocked(!0)}}class Wm extends km{constructor(){super(),this.needsSwap=!1}render(t){t.state.buffers.stencil.setLocked(!1),t.state.buffers.stencil.setTest(!1)}}class qm{constructor(t,e){if(this.renderer=t,void 0===e){const n={minFilter:w.V,magFilter:w.V,format:w.Ib},i=t.getSize(new d.a);this._pixelRatio=t.getPixelRatio(),this._width=i.width,this._height=i.height,(e=new Q(this._width*this._pixelRatio,this._height*this._pixelRatio,n)).texture.name=\\\\\\\"EffectComposer.rt1\\\\\\\"}else this._pixelRatio=1,this._width=e.width,this._height=e.height;this.renderTarget1=e,this.renderTarget2=e.clone(),this.renderTarget2.texture.name=\\\\\\\"EffectComposer.rt2\\\\\\\",this.writeBuffer=this.renderTarget1,this.readBuffer=this.renderTarget2,this.renderToScreen=!0,this.passes=[],void 0===zm&&console.error(\\\\\\\"THREE.EffectComposer relies on CopyShader\\\\\\\"),void 0===Hm&&console.error(\\\\\\\"THREE.EffectComposer relies on ShaderPass\\\\\\\"),this.copyPass=new Hm(zm),this.clock=new Dm}swapBuffers(){const t=this.readBuffer;this.readBuffer=this.writeBuffer,this.writeBuffer=t}addPass(t){this.passes.push(t),t.setSize(this._width*this._pixelRatio,this._height*this._pixelRatio)}insertPass(t,e){this.passes.splice(e,0,t),t.setSize(this._width*this._pixelRatio,this._height*this._pixelRatio)}removePass(t){const e=this.passes.indexOf(t);-1!==e&&this.passes.splice(e,1)}isLastEnabledPass(t){for(let e=t+1;e({name:Object.keys(t)[0],value:Object.values(t)[0]}))),tf=Jm.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})));class ef extends ua{constructor(){super(...arguments),this.prependRenderPass=ha.BOOLEAN(1),this.useRenderTarget=ha.BOOLEAN(1),this.tmagFilter=ha.BOOLEAN(0,{visibleIf:{useRenderTarget:1}}),this.magFilter=ha.INTEGER(Zm,{visibleIf:{useRenderTarget:1,tmagFilter:1},menu:{entries:Km}}),this.tminFilter=ha.BOOLEAN(0,{visibleIf:{useRenderTarget:1}}),this.minFilter=ha.INTEGER(Qm,{visibleIf:{useRenderTarget:1,tminFilter:1},menu:{entries:tf}}),this.stencilBuffer=ha.BOOLEAN(0,{visibleIf:{useRenderTarget:1}}),this.sampling=ha.INTEGER(1,{range:[1,4],rangeLocked:[!0,!1]})}}class nf{constructor(t){this.node=t,this._renderer_size=new d.a}displayNodeControllerCallbacks(){return{onDisplayNodeRemove:()=>{},onDisplayNodeSet:()=>{this.node.setDirty()},onDisplayNodeUpdate:()=>{this.node.setDirty()}}}createEffectsComposer(t){const e=t.renderer;let n;if(this.node.pv.useRenderTarget){const t=this._create_render_target(e);n=new qm(e,t)}else n=new qm(e);return n.setPixelRatio(window.devicePixelRatio*this.node.pv.sampling),this._build_passes(n,t),n}_create_render_target(t){let e;t.autoClear=!1;const n={format:w.ic,stencilBuffer:this.node.pv.stencilBuffer};return this.node.pv.tminFilter&&(n.minFilter=this.node.pv.minFilter),this.node.pv.tmagFilter&&(n.magFilter=this.node.pv.magFilter),t.getDrawingBufferSize(this._renderer_size),e=li.renderersController.renderTarget(this._renderer_size.x,this._renderer_size.y,n),e}_build_passes(t,e){if(this.node.pv.prependRenderPass){const n=new Ym(e.scene,e.camera);t.addPass(n)}const n=this.node.displayNodeController.displayNode();n&&n.setupComposer({composer:t,camera:e.camera,resolution:e.resolution,camera_node:e.camera_node,scene:e.scene,requester:e.requester})}}class sf extends Cm{constructor(){super(...arguments),this.paramsConfig=new ef,this.effectsComposerController=new nf(this),this.displayNodeController=new Fm(this,this.effectsComposerController.displayNodeControllerCallbacks()),this._children_controller_context=ts.POST}static type(){return es.POST}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class rf extends Nm{constructor(){super(...arguments),this._children_controller_context=ts.ROP}static type(){return es.ROP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}var of=n(44);const af=\\\\\\\"input texture\\\\\\\",lf=[af,af,af,af];for(var cf=new Uint16Array(32),hf=0;hf<32;hf++)cf[hf]=28898;const uf=new vo.a(cf,32,1,w.gb,w.M);class df extends aa{constructor(t){super(t,\\\\\\\"BaseCopNode\\\\\\\"),this.flags=new ki(this)}static context(){return ts.COP}static displayedInputNames(){return lf}initializeBaseNode(){this.io.outputs.setHasOneOutput()}setTexture(t){t.name=this.path();const e=this.containerController.container().texture();if(e){if(e.uuid!=t.uuid){const n=Object.keys(t);for(let i of n)e[i]=t[i];e.needsUpdate=!0}this._setContainer(e)}else this._setContainer(t)}_clearTexture(){this._setContainer(uf)}}class pf extends df{}class _f{constructor(){this._id=_f.__next_id++}id(){return this._id}handle_globals_node(t,e,n){}}_f.__next_id=0;class mf{static any(t){return m.isString(t)?t:m.isBoolean(t)?`${t}`:m.isNumber(t)?`${ss.ensureFloat(t)}`:m.isArray(t)?this.numeric_array(t):t instanceof d.a||t instanceof p.a||t instanceof _.a||t instanceof D.a?this.numeric_array(t.toArray()):`ThreeToGl error: unknown value type '${t}'`}static numeric_array(t){const e=new Array(t.length);for(let n=0;n`${ss.ensureFloat(t)}`)).join(\\\\\\\", \\\\\\\")})`}static vector3(t){if(m.isString(t))return t;return`vec3(${t.toArray().map((t=>`${ss.ensureFloat(t)}`)).join(\\\\\\\", \\\\\\\")})`}static vector2(t){if(m.isString(t))return t;return`vec2(${t.toArray().map((t=>`${ss.ensureFloat(t)}`)).join(\\\\\\\", \\\\\\\")})`}static vector3_float(t,e){return m.isNumber(e)&&(e=ss.ensureFloat(e)),`vec4(${this.vector3(t)}, ${e})`}static float4(t,e,n,i){return m.isNumber(t)&&(t=ss.ensureFloat(t)),m.isNumber(e)&&(e=ss.ensureFloat(e)),m.isNumber(n)&&(n=ss.ensureFloat(n)),m.isNumber(i)&&(i=ss.ensureFloat(i)),`vec4(${t}, ${e}, ${n}, ${i})`}static float3(t,e,n){return m.isNumber(t)&&(t=ss.ensureFloat(t)),m.isNumber(e)&&(e=ss.ensureFloat(e)),m.isNumber(n)&&(n=ss.ensureFloat(n)),`vec3(${t}, ${e}, ${n})`}static float2(t,e){return m.isNumber(t)&&(t=ss.ensureFloat(t)),m.isNumber(e)&&(e=ss.ensureFloat(e)),`vec2(${t}, ${e})`}static float(t){if(m.isNumber(t))return ss.ensureFloat(t);{const e=parseFloat(t);return m.isNaN(e)?t:ss.ensureFloat(e)}}static integer(t){if(m.isNumber(t))return ss.ensureInteger(t);{const e=parseInt(t);return m.isNaN(e)?t:ss.ensureInteger(e)}}static bool(t){return m.isBoolean(t)?`${t}`:t}}const ff=/\\\\/+/g;class gf extends aa{static context(){return ts.GL}initializeBaseNode(){this.uiData.setLayoutHorizontal(),this.io.connections.initInputs(),this.io.connection_points.spare_params.initializeNode()}cook(){console.warn(\\\\\\\"gl nodes should never cook\\\\\\\")}_set_mat_to_recompile(){var t,e;null===(e=null===(t=this.material_node)||void 0===t?void 0:t.assemblerController)||void 0===e||e.set_compilation_required_and_dirty(this)}get material_node(){var t;const e=this.parent();if(e)return e.context()==ts.GL?null===(t=e)||void 0===t?void 0:t.material_node:e}glVarName(t){return`v_POLY_${this.path(this.material_node).replace(ff,\\\\\\\"_\\\\\\\")}_${t}`}variableForInputParam(t){return this.variableForInput(t.name())}variableForInput(t){var e;const n=this.io.inputs.get_input_index(t),i=this.io.connections.inputConnection(n);if(i){const e=i.node_src,n=e.io.outputs.namedOutputConnectionPoints()[i.output_index];if(n){const t=n.name();return e.glVarName(t)}throw console.warn(`no output called '${t}' for gl node ${e.path()}`),\\\\\\\"variable_for_input ERROR\\\\\\\"}if(this.params.has(t))return mf.any(null===(e=this.params.get(t))||void 0===e?void 0:e.value);{const t=this.io.inputs.namedInputConnectionPoints()[n];return mf.any(t.init_value)}}setLines(t){}reset_code(){var t;null===(t=this._param_configs_controller)||void 0===t||t.reset()}setParamConfigs(){}param_configs(){var t;return null===(t=this._param_configs_controller)||void 0===t?void 0:t.list()}paramsGenerating(){return!1}paramDefaultValue(t){return null}}const vf=new class extends ua{};class yf extends gf{constructor(){super(...arguments),this.paramsConfig=vf}}const xf=[Uo.FLOAT,Uo.VEC2,Uo.VEC3,Uo.VEC4];const bf=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(\\\\\\\"\\\\\\\"),this.type=ha.INTEGER(0,{menu:{entries:xf.map(((t,e)=>({name:t,value:e})))}}),this.texportWhenConnected=ha.BOOLEAN(0,{hidden:!0}),this.exportWhenConnected=ha.BOOLEAN(0,{visibleIf:{texportWhenConnected:1}})}};class wf extends gf{constructor(){super(...arguments),this.paramsConfig=bf,this._on_create_set_name_if_none_bound=this._on_create_set_name_if_none.bind(this),this._bound_setExportWhenConnectedStatus=this._setExportWhenConnectedStatus.bind(this)}static type(){return ps.ATTRIBUTE}initializeNode(){this.addPostDirtyHook(\\\\\\\"_set_mat_to_recompile\\\\\\\",this._set_mat_to_recompile_if_is_exporting.bind(this)),this.lifecycle.add_on_create_hook(this._on_create_set_name_if_none_bound),this.io.connection_points.initializeNode(),this.io.connection_points.set_expected_input_types_function((()=>{var t,e;return(null===(e=null===(t=this.material_node)||void 0===t?void 0:t.assemblerController)||void 0===e?void 0:e.allow_attribute_exports())?[xf[this.pv.type]]:[]})),this.io.connection_points.set_input_name_function((t=>wf.INPUT_NAME)),this.io.connection_points.set_expected_output_types_function((()=>[xf[this.pv.type]])),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name,this.p.exportWhenConnected],(()=>this.pv.exportWhenConnected?`${this.pv.name} (EXPORTED)`:this.pv.name))}))})),this.lifecycle.add_on_add_hook(this._bound_setExportWhenConnectedStatus),this.params.addOnSceneLoadHook(\\\\\\\"prepare params\\\\\\\",this._bound_setExportWhenConnectedStatus)}_setExportWhenConnectedStatus(){var t,e;(null===(e=null===(t=this.material_node)||void 0===t?void 0:t.assemblerController)||void 0===e?void 0:e.allow_attribute_exports())&&this.p.texportWhenConnected.set(1)}setAttribSize(t){this.p.type.set(t-1)}get input_name(){return wf.INPUT_NAME}get output_name(){return wf.OUTPUT_NAME}setLines(t){t.assembler().set_node_lines_attribute(this,t)}get attribute_name(){return this.pv.name.trim()}gl_type(){return this.io.outputs.namedOutputConnectionPoints()[0].type()}set_gl_type(t){this.p.type.set(xf.indexOf(t))}connected_input_node(){return this.io.inputs.named_input(wf.INPUT_NAME)}connected_input_connection_point(){return this.io.inputs.named_input_connection_point(wf.INPUT_NAME)}output_connection_point(){return this.io.outputs.namedOutputConnectionPointsByName(this.output_name)}isImporting(){return this.io.outputs.used_output_names().length>0}isExporting(){if(this.pv.exportWhenConnected){return null!=this.io.inputs.named_input(wf.INPUT_NAME)}return!1}_set_mat_to_recompile_if_is_exporting(){this.isExporting()&&this._set_mat_to_recompile()}_on_create_set_name_if_none(){\\\\\\\"\\\\\\\"==this.pv.name&&this.p.name.set(this.name())}}wf.INPUT_NAME=\\\\\\\"in\\\\\\\",wf.OUTPUT_NAME=\\\\\\\"val\\\\\\\";class Tf{constructor(t=[]){this._definitions=t,this._errored=!1}get errored(){return this._errored}get error_message(){return this._error_message}uniq(){const t=new Map,e=[];for(let n of this._definitions)if(!this._errored){const i=n.name(),s=t.get(i);s?s.data_type!=n.data_type&&(this._errored=!0,this._error_message=`attempt to create '${n.name()}' with types '${n.data_type}' by node '${n.node.path()}', when there is already an existing with type ${s.data_type} from node '${s.node.path()}'`,console.warn(\\\\\\\"emitting error message:\\\\\\\",this._error_message)):(t.set(i,n),e.push(i))}const n=[];for(let i of e){const e=t.get(i);e&&n.push(e)}return n}}var Af,Mf;!function(t){t.ATTRIBUTE=\\\\\\\"attribute\\\\\\\",t.FUNCTION=\\\\\\\"function\\\\\\\",t.UNIFORM=\\\\\\\"uniform\\\\\\\",t.VARYING=\\\\\\\"varying\\\\\\\"}(Af||(Af={}));class Ef{constructor(t,e,n,i){this._definition_type=t,this._data_type=e,this._node=n,this._name=i}get definition_type(){return this._definition_type}get data_type(){return this._data_type}get node(){return this._node}name(){return this._name}collection_instance(){return new Tf}}class Sf extends Ef{constructor(t,e,n){super(Af.ATTRIBUTE,e,t,n),this._node=t,this._data_type=e,this._name=n}get line(){return`attribute ${this.data_type} ${this.name()}`}}class Cf extends Ef{constructor(t,e){super(Af.FUNCTION,Uo.FLOAT,t,e),this._node=t,this._name=e}get line(){return this.name()}}class Nf extends Ef{constructor(t,e,n){super(Af.UNIFORM,e,t,n),this._node=t,this._data_type=e,this._name=n}get line(){return`uniform ${this.data_type} ${this.name()}`}}class Lf extends Ef{constructor(t,e,n){super(Af.VARYING,e,t,n),this._node=t,this._data_type=e,this._name=n}get line(){return`varying ${this.data_type} ${this.name()}`}}!function(t){t.VERTEX=\\\\\\\"vertex\\\\\\\",t.FRAGMENT=\\\\\\\"fragment\\\\\\\",t.LEAVES_FROM_NODES_SHADER=\\\\\\\"leaves_from_nodes_shader\\\\\\\"}(Mf||(Mf={}));const Of={position:\\\\\\\"vec3( position )\\\\\\\"};class Pf extends _f{handle_globals_node(t,e,n){var i,s;const r=t.io.outputs.namedOutputConnectionPointsByName(e);if(!r)return;const o=t.glVarName(e),a=r.type(),l=new Lf(t,a,o);n.addDefinitions(t,[l]);const c=null===(s=null===(i=t.material_node)||void 0===i?void 0:i.assemblerController)||void 0===s?void 0:s.assembler;if(!c)return;const h=c.shader_config(n.current_shader_name);if(!h)return;const u=h.dependencies(),d=[],p=`${o} = modelMatrix * vec4( position, 1.0 )`,_=`${o} = normalize( mat3( modelMatrix[0].xyz, modelMatrix[1].xyz, modelMatrix[2].xyz ) * normal )`;switch(e){case\\\\\\\"worldPosition\\\\\\\":d.push(p);break;case\\\\\\\"worldNormal\\\\\\\":d.push(_);break;default:d.push(`${o} = ${a}(${e})`)}for(let e of u)n.addDefinitions(t,[l],e),n.addBodyLines(t,d,e);0==u.length&&n.addBodyLines(t,d)}static variable_config_default(t){return Of[t]}variable_config_default(t){return Pf.variable_config_default(t)}read_attribute(t,e,n,i){return Pf.read_attribute(t,e,n,i)}static read_attribute(t,e,n,i){var s,r;Pf.PRE_DEFINED_ATTRIBUTES.indexOf(n)<0&&i.addDefinitions(t,[new Sf(t,e,n)],Mf.VERTEX);const o=i.current_shader_name;switch(o){case Mf.VERTEX:return n;case Mf.FRAGMENT:{if(!(t instanceof wf))return;const a=\\\\\\\"varying_\\\\\\\"+t.glVarName(t.output_name),l=new Lf(t,e,a),c=new Map;c.set(Mf.FRAGMENT,[]);const u=new Map;u.set(Mf.FRAGMENT,[]),h.pushOnArrayAtEntry(c,o,l);const d=`${a} = ${e}(${n})`,p=null===(r=null===(s=t.material_node)||void 0===s?void 0:s.assemblerController)||void 0===r?void 0:r.assembler.shader_config(o);if(p){const e=p.dependencies();for(let t of e)h.pushOnArrayAtEntry(c,t,l),h.pushOnArrayAtEntry(u,t,d);c.forEach(((e,n)=>{i.addDefinitions(t,e,n)})),u.forEach(((e,n)=>{i.addBodyLines(t,e,n)}))}return a}}}handle_attribute_node(t,e,n,i){return Pf.read_attribute(t,e,n,i)}}Pf.PRE_DEFINED_ATTRIBUTES=[\\\\\\\"position\\\\\\\",\\\\\\\"color\\\\\\\",\\\\\\\"normal\\\\\\\",\\\\\\\"uv\\\\\\\",\\\\\\\"uv2\\\\\\\",\\\\\\\"morphTarget0\\\\\\\",\\\\\\\"morphTarget1\\\\\\\",\\\\\\\"morphTarget2\\\\\\\",\\\\\\\"morphTarget3\\\\\\\",\\\\\\\"skinIndex\\\\\\\",\\\\\\\"skinWeight\\\\\\\"],Pf.IF_RULE={uv:\\\\\\\"defined( USE_MAP ) || defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( USE_SPECULARMAP ) || defined( USE_ALPHAMAP ) || defined( USE_EMISSIVEMAP ) || defined( USE_ROUGHNESSMAP ) || defined( USE_METALNESSMAP )\\\\\\\"};const Rf=[Uo.FLOAT,Uo.VEC2,Uo.VEC3,Uo.VEC4];const If=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(\\\\\\\"\\\\\\\"),this.type=ha.INTEGER(0,{menu:{entries:Rf.map(((t,e)=>({name:t,value:e})))}})}};class Ff extends gf{constructor(){super(...arguments),this.paramsConfig=If,this._on_create_set_name_if_none_bound=this._on_create_set_name_if_none.bind(this)}static type(){return\\\\\\\"varyingWrite\\\\\\\"}initializeNode(){this.addPostDirtyHook(\\\\\\\"_set_mat_to_recompile\\\\\\\",this._set_mat_to_recompile.bind(this)),this.lifecycle.add_on_create_hook(this._on_create_set_name_if_none_bound),this.io.connection_points.initializeNode(),this.io.connection_points.set_input_name_function((()=>this.input_name)),this.io.connection_points.set_expected_input_types_function((()=>[Rf[this.pv.type]])),this.io.connection_points.set_expected_output_types_function((()=>[])),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name])}))}))}get input_name(){return Ff.INPUT_NAME}setLines(t){if(t.current_shader_name==Mf.VERTEX){const e=this.gl_type();if(!e)return;const n=this.pv.name,i=new Lf(this,e,n),s=`${n} = ${mf.any(this.variableForInput(Ff.INPUT_NAME))}`;t.addDefinitions(this,[i],Mf.VERTEX),t.addBodyLines(this,[s],Mf.VERTEX)}}get attribute_name(){return this.pv.name.trim()}gl_type(){const t=this.io.inputs.namedInputConnectionPoints()[0];if(t)return t.type()}set_gl_type(t){this.p.type.set(Rf.indexOf(t))}_on_create_set_name_if_none(){\\\\\\\"\\\\\\\"==this.pv.name&&this.p.name.set(this.name())}}Ff.INPUT_NAME=\\\\\\\"vertex\\\\\\\";class Df{static findOutputNodes(t){return t.nodesByType(\\\\\\\"output\\\\\\\")}static findParamGeneratingNodes(t){var e;const n=[];return null===(e=t.childrenController)||void 0===e||e.traverse_children((t=>{const e=t;e.paramsGenerating()&&n.push(e)})),n}static findVaryingNodes(t){return t.nodesByType(Ff.type())}static findAttributeExportNodes(t){return t.nodesByType(wf.type()).filter((t=>t.isExporting()))}}class Bf{static overlay(t,e){return new Promise(((n,i)=>{let s=document.createElement(\\\\\\\"canvas\\\\\\\");s.width=Math.max(t.width,e.width),s.height=Math.max(t.height,e.height);let r=s.getContext(\\\\\\\"2d\\\\\\\");r.drawImage(t,0,0,t.width,t.height),r.drawImage(e,0,0,e.width,e.height);const o=s.toDataURL(\\\\\\\"image/png\\\\\\\"),a=new Image;a.onload=()=>{n(a)},a.src=o}))}static create_white_image(t,e){return new Promise(((n,i)=>{let s=document.createElement(\\\\\\\"canvas\\\\\\\");s.width=t,s.height=e;let r=s.getContext(\\\\\\\"2d\\\\\\\");r.beginPath(),r.rect(0,0,t,e),r.fillStyle=\\\\\\\"white\\\\\\\",r.fill();const o=s.toDataURL(\\\\\\\"image/png\\\\\\\"),a=new Image;a.onload=()=>{n(a)},a.src=o}))}static make_square(t){return new Promise(((e,n)=>{let i=document.createElement(\\\\\\\"canvas\\\\\\\");const s=Math.min(t.width,t.height),r=t.width/t.height;i.width=s,i.height=s;let o=i.getContext(\\\\\\\"2d\\\\\\\");const a=r>1,l=a?(t.width-s)/2:(t.height-s)/2;a?o.drawImage(t,l,0,s,s,0,0,s,s):o.drawImage(t,0,l,s,s,0,0,s,s);const c=i.toDataURL(\\\\\\\"image/png\\\\\\\"),h=new Image;h.onload=()=>{e(h)},h.src=c}))}static async image_to_blob(t){return new Promise((function(e,n){try{let i=new XMLHttpRequest;i.open(\\\\\\\"GET\\\\\\\",t.src),i.responseType=\\\\\\\"blob\\\\\\\",i.onerror=function(){n(\\\\\\\"Network error.\\\\\\\")},i.onload=function(){200===i.status?e(i.response):n(\\\\\\\"Loading error:\\\\\\\"+i.statusText)},i.send()}catch(t){n(t.message)}}))}static data_from_url(t){return new Promise(((e,n)=>{const i=new Image;i.crossOrigin=\\\\\\\"Anonymous\\\\\\\",i.onload=()=>{const t=this.data_from_image(i);e(t)},i.src=t}))}static data_from_image(t){const e=document.createElement(\\\\\\\"canvas\\\\\\\");e.width=t.width,e.height=t.height;const n=e.getContext(\\\\\\\"2d\\\\\\\");return n.drawImage(t,0,0,t.width,t.height),n.getImageData(0,0,t.width,t.height)}}var zf;!function(t){t.Uint8Array=\\\\\\\"Uint8Array\\\\\\\",t.Uint8ClampedArray=\\\\\\\"Uint8ClampedArray\\\\\\\",t.Float32Array=\\\\\\\"Float32Array\\\\\\\"}(zf||(zf={}));class kf{constructor(t){this.buffer_type=t}from_render_target(t,e){return this._data_texture&&this._same_dimensions(e.texture)||(this._data_texture=this._create_data_texture(e.texture)),this._copy_to_data_texture(t,e),this._data_texture}from_texture(t){const e=Bf.data_from_image(t.image);this._data_texture&&this._same_dimensions(t)||(this._data_texture=this._create_data_texture(t));const n=e.width*e.height,i=e.data,s=this._data_texture.image.data,r=4*n;for(let t=0;t0:s.vertexColors=t.vertexColors),void 0!==t.uniforms)for(const e in t.uniforms){const i=t.uniforms[e];switch(s.uniforms[e]={},i.type){case\\\\\\\"t\\\\\\\":s.uniforms[e].value=n(i.value);break;case\\\\\\\"c\\\\\\\":s.uniforms[e].value=(new D.a).setHex(i.value);break;case\\\\\\\"v2\\\\\\\":s.uniforms[e].value=(new d.a).fromArray(i.value);break;case\\\\\\\"v3\\\\\\\":s.uniforms[e].value=(new p.a).fromArray(i.value);break;case\\\\\\\"v4\\\\\\\":s.uniforms[e].value=(new _.a).fromArray(i.value);break;case\\\\\\\"m3\\\\\\\":s.uniforms[e].value=(new G.a).fromArray(i.value);break;case\\\\\\\"m4\\\\\\\":s.uniforms[e].value=(new A.a).fromArray(i.value);break;default:s.uniforms[e].value=i.value}}if(void 0!==t.defines&&(s.defines=t.defines),void 0!==t.vertexShader&&(s.vertexShader=t.vertexShader),void 0!==t.fragmentShader&&(s.fragmentShader=t.fragmentShader),void 0!==t.extensions)for(const e in t.extensions)s.extensions[e]=t.extensions[e];if(void 0!==t.shading&&(s.flatShading=1===t.shading),void 0!==t.size&&(s.size=t.size),void 0!==t.sizeAttenuation&&(s.sizeAttenuation=t.sizeAttenuation),void 0!==t.map&&(s.map=n(t.map)),void 0!==t.matcap&&(s.matcap=n(t.matcap)),void 0!==t.alphaMap&&(s.alphaMap=n(t.alphaMap)),void 0!==t.bumpMap&&(s.bumpMap=n(t.bumpMap)),void 0!==t.bumpScale&&(s.bumpScale=t.bumpScale),void 0!==t.normalMap&&(s.normalMap=n(t.normalMap)),void 0!==t.normalMapType&&(s.normalMapType=t.normalMapType),void 0!==t.normalScale){let e=t.normalScale;!1===Array.isArray(e)&&(e=[e,e]),s.normalScale=(new d.a).fromArray(e)}return void 0!==t.displacementMap&&(s.displacementMap=n(t.displacementMap)),void 0!==t.displacementScale&&(s.displacementScale=t.displacementScale),void 0!==t.displacementBias&&(s.displacementBias=t.displacementBias),void 0!==t.roughnessMap&&(s.roughnessMap=n(t.roughnessMap)),void 0!==t.metalnessMap&&(s.metalnessMap=n(t.metalnessMap)),void 0!==t.emissiveMap&&(s.emissiveMap=n(t.emissiveMap)),void 0!==t.emissiveIntensity&&(s.emissiveIntensity=t.emissiveIntensity),void 0!==t.specularMap&&(s.specularMap=n(t.specularMap)),void 0!==t.specularIntensityMap&&(s.specularIntensityMap=n(t.specularIntensityMap)),void 0!==t.specularTintMap&&(s.specularTintMap=n(t.specularTintMap)),void 0!==t.envMap&&(s.envMap=n(t.envMap)),void 0!==t.envMapIntensity&&(s.envMapIntensity=t.envMapIntensity),void 0!==t.reflectivity&&(s.reflectivity=t.reflectivity),void 0!==t.refractionRatio&&(s.refractionRatio=t.refractionRatio),void 0!==t.lightMap&&(s.lightMap=n(t.lightMap)),void 0!==t.lightMapIntensity&&(s.lightMapIntensity=t.lightMapIntensity),void 0!==t.aoMap&&(s.aoMap=n(t.aoMap)),void 0!==t.aoMapIntensity&&(s.aoMapIntensity=t.aoMapIntensity),void 0!==t.gradientMap&&(s.gradientMap=n(t.gradientMap)),void 0!==t.clearcoatMap&&(s.clearcoatMap=n(t.clearcoatMap)),void 0!==t.clearcoatRoughnessMap&&(s.clearcoatRoughnessMap=n(t.clearcoatRoughnessMap)),void 0!==t.clearcoatNormalMap&&(s.clearcoatNormalMap=n(t.clearcoatNormalMap)),void 0!==t.clearcoatNormalScale&&(s.clearcoatNormalScale=(new d.a).fromArray(t.clearcoatNormalScale)),void 0!==t.transmissionMap&&(s.transmissionMap=n(t.transmissionMap)),void 0!==t.thicknessMap&&(s.thicknessMap=n(t.thicknessMap)),s}setTextures(t){return this.textures=t,this}}class Qf{constructor(t){this.node=t,this._found_uniform_texture_by_id=new Map,this._found_uniform_textures_id_by_uniform_name=new Map,this._found_param_texture_by_id=new Map,this._found_param_textures_id_by_uniform_name=new Map}toJSON(){}load(t){}_materialToJson(t,e){let n;this._unassignTextures(t);try{n=t.toJSON({}),n&&(n.shadowSide=t.shadowSide,n.colorWrite=t.colorWrite)}catch(e){console.error(\\\\\\\"failed to save material data\\\\\\\"),console.log(t)}return n&&null!=t.lights&&(n.lights=t.lights),n&&(n.uuid=`${e.node.path()}-${e.suffix}`),this._reassignTextures(t),n}_unassignTextures(t){this._found_uniform_texture_by_id.clear(),this._found_uniform_textures_id_by_uniform_name.clear(),this._found_param_texture_by_id.clear(),this._found_param_textures_id_by_uniform_name.clear();const e=t.uniforms,n=Object.keys(e);for(let t of n){const n=e[t].value;if(n&&n.uuid){const i=n;this._found_uniform_texture_by_id.set(i.uuid,n),this._found_uniform_textures_id_by_uniform_name.set(t,i.uuid),e[t].value=null}}const i=Object.keys(t);for(let e of i){const n=t[e];if(n&&n.uuid){const i=n;this._found_param_texture_by_id.set(i.uuid,i),this._found_param_textures_id_by_uniform_name.set(e,i.uuid),t[e]=null}}}_reassignTextures(t){const e=[],n=[];this._found_uniform_textures_id_by_uniform_name.forEach(((t,n)=>{e.push(n)})),this._found_param_textures_id_by_uniform_name.forEach(((t,e)=>{n.push(e)}));const i=t.uniforms;for(let t of e){const e=this._found_uniform_textures_id_by_uniform_name.get(t);if(e){const n=this._found_uniform_texture_by_id.get(e);n&&(i[t].value=n)}}for(let e of n){const n=this._found_param_textures_id_by_uniform_name.get(e);if(n){const i=this._found_param_texture_by_id.get(n);i&&(t[e]=i)}}}_loadMaterial(t){t.color=void 0;const e=(new Zf).parse(t);t.shadowSide&&(e.shadowSide=t.shadowSide),null!=t.lights&&(e.lights=t.lights);const n=e.uniforms.uv2Transform;n&&this.mat4ToMat3(n);const i=e.uniforms.uvTransform;return i&&this.mat4ToMat3(i),e}mat4ToMat3(t){const e=t.value;if(null==e.elements[e.elements.length-1]){const n=new G.a;for(let t=0;t{const n=t.texture();e.value=n}));else{const t=n.containerController.container().texture();e.value=t}else e.value=null}static async set_uniform_value_from_texture_from_node_path_param(t,e){t.isDirty()&&await t.compute();const n=t.value.nodeWithContext(ts.COP);if(n)if(n.isDirty())n.compute().then((t=>{const n=t.texture();e.value=n}));else{const t=n.containerController.container().texture();e.value=t}else e.value=null}set_uniform_value_from_ramp(t,e){e.value=t.rampTexture()}}class eg extends Qf{constructor(t){super(t),this.node=t}toJSON(){const t=this.node.assemblerController;if(!t)return;const e=[],n=t.assembler.param_configs();for(let t of n)e.push([t.name(),t.uniform_name]);return{fragment_shader:this.node.texture_material.fragmentShader,uniforms:this.node.texture_material.uniforms,param_uniform_pairs:e,uniforms_time_dependent:t.assembler.uniformsTimeDependent(),uniforms_resolution_dependent:t.assembler.uniforms_resolution_dependent()}}load(t){this.node.texture_material.fragmentShader=t.fragment_shader,this.node.texture_material.uniforms=t.uniforms,rg.handleDependencies(this.node,t.uniforms_time_dependent||!1,t.uniforms);for(let e of t.param_uniform_pairs){const n=this.node.params.get(e[0]),i=t.uniforms[e[1]];n&&i&&n.options.set({callback:()=>{tg.callback(n,i)}})}}}class ng{static isChrome(){return navigator&&null!=navigator.userAgent&&-1!=navigator.userAgent.indexOf(\\\\\\\"Chrome\\\\\\\")}static isMobile(){return/Android|webOS|iPhone|iPad|iPod|BlackBerry|IEMobile|Opera Mini/i.test(navigator.userAgent)}static isiOS(){return/(iPad|iPhone|iPod)/g.test(navigator.userAgent)}static isAndroid(){return/(Android)/g.test(navigator.userAgent)}static isTouchDevice(){var t=document.createElement(\\\\\\\"div\\\\\\\");return t.setAttribute(\\\\\\\"ongesturestart\\\\\\\",\\\\\\\"return;\\\\\\\"),\\\\\\\"function\\\\\\\"==typeof t.ongesturestart}}const ig=[256,256];const sg=new class extends ua{constructor(){super(...arguments),this.resolution=ha.VECTOR2(ig),this.useCameraRenderer=ha.BOOLEAN(0)}};class rg extends df{constructor(){super(...arguments),this.paramsConfig=sg,this.persisted_config=new eg(this),this._assembler_controller=this._create_assembler_controller(),this._texture_mesh=new B.a(new L(2,2)),this.texture_material=new F({uniforms:{},vertexShader:\\\\\\\"\\\\nvoid main()\\\\t{\\\\n\\\\tgl_Position = vec4( position, 1.0 );\\\\n}\\\\n\\\\\\\",fragmentShader:\\\\\\\"\\\\\\\"}),this._texture_scene=new vs,this._texture_camera=new of.a,this._children_controller_context=ts.GL,this._cook_main_without_inputs_when_dirty_bound=this._cook_main_without_inputs_when_dirty.bind(this),this._boundRenderOnTarget=this.renderOnTarget.bind(this)}static type(){return\\\\\\\"builder\\\\\\\"}usedAssembler(){return jn.GL_TEXTURE}_create_assembler_controller(){const t=li.assemblersRegister.assembler(this,this.usedAssembler());if(t){const e=new Pf;return t.set_assembler_globals_handler(e),t}}get assemblerController(){return this._assembler_controller}initializeNode(){this._texture_mesh.material=this.texture_material,this._texture_mesh.scale.multiplyScalar(.25),this._texture_scene.add(this._texture_mesh),this._texture_camera.position.z=1,this.addPostDirtyHook(\\\\\\\"_cook_main_without_inputs_when_dirty\\\\\\\",(()=>{setTimeout(this._cook_main_without_inputs_when_dirty_bound,0)}))}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}childrenAllowed(){return this.assemblerController?super.childrenAllowed():(this.scene().markAsReadOnly(this),!1)}async _cook_main_without_inputs_when_dirty(){await this.cookController.cookMainWithoutInputs()}async cook(){this.compileIfRequired(),this.renderOnTarget()}shaders_by_name(){return{fragment:this._fragment_shader}}compileIfRequired(){var t;(null===(t=this.assemblerController)||void 0===t?void 0:t.compileRequired())&&this.compile()}compile(){const t=this.assemblerController;if(!t)return;const e=Df.findOutputNodes(this);if(e.length>1)return void this.states.error.set(\\\\\\\"only one output node allowed\\\\\\\");if(e[0]){const n=e;t.assembler.set_root_nodes(n),t.assembler.update_fragment_shader();const i=t.assembler.fragment_shader(),s=t.assembler.uniforms();i&&s&&(this._fragment_shader=i,this._uniforms=s),rg.handleDependencies(this,t.assembler.uniformsTimeDependent())}this._fragment_shader&&this._uniforms&&(this.texture_material.fragmentShader=this._fragment_shader,this.texture_material.uniforms=this._uniforms,this.texture_material.needsUpdate=!0,this.texture_material.uniforms.resolution={value:this.pv.resolution}),t.post_compile()}static handleDependencies(t,e,n){const i=t.scene();if(e){n&&i.uniformsController.addTimeDependentUniformOwner(t._uniformCallbackName(),n);const e=t._callbackName();i.registeredBeforeTickCallbacks().has(e)||i.registerOnBeforeTick(e,t._boundRenderOnTarget)}else t._removeCallbacks()}_callbackName(){return`cop/builder_${this.graphNodeId()}`}_uniformCallbackName(){return`cop/builder_uniforms_${this.graphNodeId()}`}dispose(){super.dispose(),this._removeCallbacks()}_removeCallbacks(){const t=this.scene();t.uniformsController.removeTimeDependentUniformOwner(this._uniformCallbackName()),t.unRegisterOnBeforeTick(this._callbackName())}async renderOnTarget(){if(this.createRenderTargetIfRequired(),!this._render_target)return;this._renderer_controller=this._renderer_controller||new Uf(this);const t=await this._renderer_controller.renderer(),e=t.getRenderTarget();if(t.setRenderTarget(this._render_target),t.clear(),t.render(this._texture_scene,this._texture_camera),t.setRenderTarget(e),this._render_target.texture)if(this.pv.useCameraRenderer)this.setTexture(this._render_target.texture);else{this._data_texture_controller=this._data_texture_controller||new kf(zf.Float32Array);const e=this._data_texture_controller.from_render_target(t,this._render_target);this.setTexture(e)}else this.cookController.endCook()}renderTarget(){return this._render_target=this._render_target||this._createRenderTarget(this.pv.resolution.x,this.pv.resolution.y)}createRenderTargetIfRequired(){var t;this._render_target&&this._renderTargetResolutionValid()||(this._render_target=this._createRenderTarget(this.pv.resolution.x,this.pv.resolution.y),null===(t=this._data_texture_controller)||void 0===t||t.reset())}_renderTargetResolutionValid(){if(this._render_target){const t=this._render_target.texture.image;return t.width==this.pv.resolution.x&&t.height==this.pv.resolution.y}return!1}_createRenderTarget(t,e){if(this._render_target){const n=this._render_target.texture.image;if(n.width==t&&n.height==e)return this._render_target}const n=w.n,i=w.n,s=w.V,r=w.ob;var o=new Q(t,e,{wrapS:n,wrapT:i,minFilter:s,magFilter:r,format:w.Ib,type:ng.isiOS()?w.M:w.G,stencilBuffer:!1,depthBuffer:!1});return li.warn(\\\\\\\"created render target\\\\\\\",this.path(),t,e),o}}const og=[{LinearEncoding:w.U},{sRGBEncoding:w.ld},{GammaEncoding:w.J},{RGBEEncoding:w.gc},{LogLuvEncoding:w.bb},{RGBM7Encoding:w.lc},{RGBM16Encoding:w.kc},{RGBDEncoding:w.fc},{BasicDepthPacking:w.j},{RGBADepthPacking:w.Hb}],ag=[{ClampToEdgeWrapping:w.n},{RepeatWrapping:w.wc},{MirroredRepeatWrapping:w.kb}],lg=[{UVMapping:w.Yc},{CubeReflectionMapping:w.o},{CubeRefractionMapping:w.p},{EquirectangularReflectionMapping:w.D},{EquirectangularRefractionMapping:w.E},{CubeUVReflectionMapping:w.q},{CubeUVRefractionMapping:w.r}],cg=[{UnsignedByteType:w.Zc},{ByteType:w.l},{ShortType:w.Mc},{UnsignedShortType:w.fd},{IntType:w.N},{UnsignedIntType:w.bd},{FloatType:w.G},{HalfFloatType:w.M},{UnsignedShort4444Type:w.cd},{UnsignedShort5551Type:w.dd},{UnsignedShort565Type:w.ed},{UnsignedInt248Type:w.ad}],hg=[{AlphaFormat:w.f},{RedFormat:w.tc},{RedIntegerFormat:w.uc},{RGFormat:w.rc},{RGIntegerFormat:w.sc},{RGBFormat:w.ic},{RGBIntegerFormat:w.jc},{RGBAFormat:w.Ib},{RGBAIntegerFormat:w.Jb},{LuminanceFormat:w.gb},{LuminanceAlphaFormat:w.fb},{DepthFormat:w.x},{DepthStencilFormat:w.y}];function ug(t){return{cook:!1,callback:e=>{Sg[t](e)}}}const dg={ENCODING:w.U,FORMAT:w.Ib,MAPPING:w.Yc,MIN_FILTER:w.V,MAG_FILTER:w.V,TYPE:w.Zc,WRAPPING:w.wc},pg=ug(\\\\\\\"PARAM_CALLBACK_update_encoding\\\\\\\"),_g=ug(\\\\\\\"PARAM_CALLBACK_update_mapping\\\\\\\"),mg=ug(\\\\\\\"PARAM_CALLBACK_update_wrap\\\\\\\"),fg=ug(\\\\\\\"PARAM_CALLBACK_update_filter\\\\\\\"),gg=ug(\\\\\\\"PARAM_CALLBACK_update_anisotropy\\\\\\\"),vg=ug(\\\\\\\"PARAM_CALLBACK_update_flipY\\\\\\\"),yg=ug(\\\\\\\"PARAM_CALLBACK_update_transform\\\\\\\"),xg=ug(\\\\\\\"PARAM_CALLBACK_update_repeat\\\\\\\"),bg=ug(\\\\\\\"PARAM_CALLBACK_update_offset\\\\\\\"),wg=ug(\\\\\\\"PARAM_CALLBACK_update_rotation\\\\\\\"),Tg=ug(\\\\\\\"PARAM_CALLBACK_update_center\\\\\\\"),Ag=ug(\\\\\\\"PARAM_CALLBACK_update_advanced\\\\\\\");function Mg(t){return class extends t{constructor(){super(...arguments),this.tencoding=ha.BOOLEAN(0,{...pg}),this.encoding=ha.INTEGER(dg.ENCODING,{visibleIf:{tencoding:1},menu:{entries:og.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))},...pg}),this.tmapping=ha.BOOLEAN(0,{..._g}),this.mapping=ha.INTEGER(dg.MAPPING,{visibleIf:{tmapping:1},menu:{entries:lg.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))},..._g}),this.twrap=ha.BOOLEAN(0,{...mg}),this.wrapS=ha.INTEGER(dg.WRAPPING,{visibleIf:{twrap:1},menu:{entries:ag.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))},...mg}),this.wrapT=ha.INTEGER(dg.WRAPPING,{visibleIf:{twrap:1},menu:{entries:ag.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))},separatorAfter:!0,...mg}),this.tminFilter=ha.BOOLEAN(0,{...fg}),this.minFilter=ha.INTEGER(Qm,{visibleIf:{tminFilter:1},menu:{entries:tf},...fg}),this.tmagFilter=ha.BOOLEAN(0,{...fg}),this.magFilter=ha.INTEGER(Zm,{visibleIf:{tmagFilter:1},menu:{entries:Km},...fg}),this.tanisotropy=ha.BOOLEAN(0,{...gg}),this.useRendererMaxAnisotropy=ha.BOOLEAN(0,{visibleIf:{tanisotropy:1},...gg}),this.anisotropy=ha.INTEGER(2,{visibleIf:{tanisotropy:1,useRendererMaxAnisotropy:0},range:[0,32],rangeLocked:[!0,!1],...gg}),this.tflipY=ha.BOOLEAN(0,{...vg}),this.flipY=ha.BOOLEAN(0,{visibleIf:{tflipY:1},...vg}),this.ttransform=ha.BOOLEAN(0,{...yg}),this.offset=ha.VECTOR2([0,0],{visibleIf:{ttransform:1},...bg}),this.repeat=ha.VECTOR2([1,1],{visibleIf:{ttransform:1},...xg}),this.rotation=ha.FLOAT(0,{range:[-1,1],visibleIf:{ttransform:1},...wg}),this.center=ha.VECTOR2([0,0],{visibleIf:{ttransform:1},...Tg}),this.tadvanced=ha.BOOLEAN(0,{...Ag}),this.tformat=ha.BOOLEAN(0,{visibleIf:{tadvanced:1},...Ag}),this.format=ha.INTEGER(dg.FORMAT,{visibleIf:{tadvanced:1,tformat:1},menu:{entries:hg.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))},...Ag}),this.ttype=ha.BOOLEAN(0,{visibleIf:{tadvanced:1},...Ag}),this.type=ha.INTEGER(dg.TYPE,{visibleIf:{tadvanced:1,ttype:1},menu:{entries:cg.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))},...Ag})}}}class Eg extends(Mg(ua)){}new Eg;class Sg{constructor(t){this.node=t}async update(t){const e=this.node.pv;this._updateEncoding(t,e),this._updateAdvanced(t,e),this._updateMapping(t,e),this._updateWrap(t,e),this._updateFilter(t,e),this._updateFlip(t,e),await this._updateAnisotropy(t,e),this._updateTransform(t)}_updateEncoding(t,e){e.tencoding?t.encoding=e.encoding:t.encoding=dg.ENCODING,t.needsUpdate=!0}_updateAdvanced(t,e){e.tadvanced&&(e.tformat?t.format=e.format:t.format=dg.FORMAT,e.ttype?t.type=e.type:t.type=dg.TYPE),t.needsUpdate=!0}_updateMapping(t,e){e.tmapping?t.mapping=e.mapping:t.mapping=dg.MAPPING,t.needsUpdate=!0}_updateWrap(t,e){e.twrap?(t.wrapS=e.wrapS,t.wrapT=e.wrapT):(t.wrapS=dg.WRAPPING,t.wrapT=dg.WRAPPING),t.needsUpdate=!0}_updateFilter(t,e){e.tminFilter?t.minFilter=e.minFilter:t.minFilter=w.V,e.tmagFilter?t.magFilter=e.magFilter:t.magFilter=w.V,t.needsUpdate=!0}_updateFlip(t,e){t.flipY=e.tflipY&&e.flipY,t.needsUpdate=!0}async _updateAnisotropy(t,e){if(e.tanisotropy){if(e.useRendererMaxAnisotropy)t.anisotropy=await this._maxRendererAnisotropy();else{const n=e.anisotropy;t.anisotropy=n<=2?n:Math.min(n,await this._maxRendererAnisotropy())}t.needsUpdate=!0}else t.anisotropy=1}async _maxRendererAnisotropy(){this._renderer_controller=this._renderer_controller||new Uf(this.node);return(await this._renderer_controller.renderer()).capabilities.getMaxAnisotropy()}_updateTransform(t){if(!this.node.pv.ttransform)return t.offset.set(0,0),t.rotation=0,t.repeat.set(1,1),void t.center.set(0,0);this._updateTransformOffset(t,!1),this._updateTransformRepeat(t,!1),this._updateTransformRotation(t,!1),this._updateTransformCenter(t,!1),t.updateMatrix()}async _updateTransformOffset(t,e){t.offset.copy(this.node.pv.offset),e&&t.updateMatrix()}async _updateTransformRepeat(t,e){t.repeat.copy(this.node.pv.repeat),e&&t.updateMatrix()}async _updateTransformRotation(t,e){t.rotation=this.node.pv.rotation,e&&t.updateMatrix()}async _updateTransformCenter(t,e){t.center.copy(this.node.pv.center),e&&t.updateMatrix()}static PARAM_CALLBACK_update_encoding(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateEncoding(e,t.pv)}static PARAM_CALLBACK_update_mapping(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateMapping(e,t.pv)}static PARAM_CALLBACK_update_wrap(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateWrap(e,t.pv)}static PARAM_CALLBACK_update_filter(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateFilter(e,t.pv)}static PARAM_CALLBACK_update_anisotropy(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateAnisotropy(e,t.pv)}static PARAM_CALLBACK_update_flipY(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateFlip(e,t.pv)}static PARAM_CALLBACK_update_transform(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateTransform(e)}static PARAM_CALLBACK_update_offset(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateTransformOffset(e,!0)}static PARAM_CALLBACK_update_repeat(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateTransformRepeat(e,!0)}static PARAM_CALLBACK_update_rotation(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateTransformRotation(e,!0)}static PARAM_CALLBACK_update_center(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateTransformCenter(e,!0)}static PARAM_CALLBACK_update_advanced(t){const e=t.containerController.container().texture();e&&t.textureParamsController._updateAdvanced(e,t.pv)}static copyTextureAttributes(t,e){t.encoding=e.encoding,t.mapping=e.mapping,t.wrapS=e.wrapS,t.wrapT=e.wrapT,t.minFilter=e.minFilter,t.magFilter=e.magFilter,t.magFilter=e.magFilter,t.anisotropy=e.anisotropy,t.flipY=e.flipY,t.repeat.copy(e.repeat),t.offset.copy(e.offset),t.center.copy(e.center),t.rotation=e.rotation,t.type=e.type,t.format=e.format,t.needsUpdate=!0}paramLabelsParams(){const t=this.node.p;return[t.tencoding,t.encoding,t.tmapping,t.mapping,t.twrap,t.wrapS,t.wrapT,t.tminFilter,t.minFilter,t.tmagFilter,t.magFilter,t.tflipY,t.flipY]}paramLabels(){const t=[],e=this.node.pv;if(e.tencoding)for(let n of og){const i=Object.keys(n)[0];n[i]==e.encoding&&t.push(`encoding: ${i}`)}if(e.tmapping)for(let n of lg){const i=Object.keys(n)[0];n[i]==e.mapping&&t.push(`mapping: ${i}`)}if(e.twrap){function n(n){for(let i of ag){const s=Object.keys(i)[0];i[s]==e[n]&&t.push(`${n}: ${s}`)}}n(\\\\\\\"wrapS\\\\\\\"),n(\\\\\\\"wrapT\\\\\\\")}if(e.tminFilter)for(let n of Jm){const i=Object.keys(n)[0];n[i]==e.minFilter&&t.push(`minFilter: ${i}`)}if(e.tmagFilter)for(let n of $m){const i=Object.keys(n)[0];n[i]==e.magFilter&&t.push(`magFilter: ${i}`)}return e.tflipY&&t.push(`flipY: ${e.flipY}`),t}}class Cg extends Z.a{constructor(t,e,n,i,s,r,o,a,l){super(t,e,n,i,s,r,o,a,l),this.needsUpdate=!0}}Cg.prototype.isCanvasTexture=!0;class Ng extends(Mg(function(t){return class extends t{constructor(){super(...arguments),this.canvasId=ha.STRING(\\\\\\\"canvas-id\\\\\\\"),this.update=ha.BUTTON(null,{cook:!1,callback:t=>{Og.PARAM_CALLBACK_update(t)}})}}}(ua))){}const Lg=new Ng;class Og extends df{constructor(){super(...arguments),this.paramsConfig=Lg,this.textureParamsController=new Sg(this)}static type(){return\\\\\\\"canvas\\\\\\\"}async cook(){const t=this.pv.canvasId,e=document.getElementById(t);if(!e)return this.states.error.set(`element with id '${t}' not found`),void this.cookController.endCook();if(!(e instanceof HTMLCanvasElement))return this.states.error.set(\\\\\\\"element found is not a canvas\\\\\\\"),void this.cookController.endCook();const n=new Cg(e);await this.textureParamsController.update(n),this.setTexture(n)}static PARAM_CALLBACK_update(t){t.markTextureNeedsUpdate()}markTextureNeedsUpdate(){const t=this.containerController.container().texture();t&&(t.needsUpdate=!0)}}const Pg=new class extends ua{constructor(){super(...arguments),this.resolution=ha.VECTOR2([256,256],{callback:t=>{Rg.PARAM_CALLBACK_reset(t)}}),this.color=ha.COLOR([1,1,1])}};class Rg extends df{constructor(){super(...arguments),this.paramsConfig=Pg}static type(){return\\\\\\\"color\\\\\\\"}cook(){const t=this.pv.resolution.x,e=this.pv.resolution.y;this._data_texture=this._data_texture||this._create_data_texture(t,e);const n=e*t,i=this.pv.color.toArray(),s=255*i[0],r=255*i[1],o=255*i[2],a=this._data_texture.image.data;for(let t=0;t({name:t,value:e})))}})}};class kg extends df{constructor(){super(...arguments),this.paramsConfig=zg}static type(){return Fg.CUBE_CAMERA}async cook(){const t=this.pv.cubeCamera.nodeWithContext(ts.OBJ,this.states.error);if(!t)return this.states.error.set(`cubeCamera not found at '${this.pv.cubeCamera.path()}'`),this.cookController.endCook();const e=t.renderTarget();if(!e)return this.states.error.set(\\\\\\\"cubeCamera has no render target'\\\\\\\"),this.cookController.endCook();const n=e.texture;Bg[this.pv.mode]==Dg.REFLECTION?n.mapping=w.o:n.mapping=w.p,this.setTexture(n)}}var Ug;!function(t){t.REFLECTION=\\\\\\\"reflection\\\\\\\",t.REFRACTION=\\\\\\\"refraction\\\\\\\"}(Ug||(Ug={}));const Gg=[Ug.REFLECTION,Ug.REFRACTION];const Vg=new class extends ua{constructor(){super(...arguments),this.useCameraRenderer=ha.BOOLEAN(1),this.mode=ha.INTEGER(0,{menu:{entries:Gg.map(((t,e)=>({name:t,value:e})))}})}};class Hg extends df{constructor(){super(...arguments),this.paramsConfig=Vg}static type(){return\\\\\\\"envMap\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Ki.NEVER)}async cook(t){const e=t[0];this.convert_texture_to_env_map(e)}async convert_texture_to_env_map(t){this._renderer_controller=this._renderer_controller||new Uf(this);const e=await this._renderer_controller.renderer();if(e){const n=new Tt(e).fromEquirectangular(t);if(this.pv.useCameraRenderer)this._set_mapping(n.texture),this.setTexture(n.texture);else{this._data_texture_controller=this._data_texture_controller||new kf(zf.Uint8Array);const t=this._data_texture_controller.from_render_target(e,n);this._set_mapping(t),this.setTexture(t)}}else this.states.error.set(\\\\\\\"no renderer found to convert the texture to an env map\\\\\\\"),this.cookController.endCook()}_set_mapping(t){Gg[this.pv.mode]==Ug.REFLECTION?t.mapping=w.q:t.mapping=w.r}}class jg extends Z.a{constructor(t,e,n,i,s,r,o,a,l){super(t,e,n,i,s,r,o,a,l),this.format=void 0!==o?o:w.ic,this.minFilter=void 0!==r?r:w.V,this.magFilter=void 0!==s?s:w.V,this.generateMipmaps=!1;const c=this;\\\\\\\"requestVideoFrameCallback\\\\\\\"in t&&t.requestVideoFrameCallback((function e(){c.needsUpdate=!0,t.requestVideoFrameCallback(e)}))}clone(){return new this.constructor(this.image).copy(this)}update(){const t=this.image;!1===\\\\\\\"requestVideoFrameCallback\\\\\\\"in t&&t.readyState>=t.HAVE_CURRENT_DATA&&(this.needsUpdate=!0)}}jg.prototype.isVideoTexture=!0;var Wg=n(80);const qg=\\\\\\\"https://raw.githubusercontent.com/polygonjs/polygonjs-assets/master/\\\\\\\";var Xg=n(28);const Yg=new Xg.b;Yg.setURLModifier((t=>{const e=li.assetUrls.remapedUrl(t);if(e)return e;const n=li.blobs.blobUrl(t);return n||t}));class $g{constructor(t,e,n){this._url=t,this._scene=e,this._node=n,this.loadingManager=Yg}static extension(t){let e=null;try{e=new URL(t).searchParams.get(\\\\\\\"ext\\\\\\\")}catch(t){}if(!e){const n=t.split(\\\\\\\"?\\\\\\\")[0].split(\\\\\\\".\\\\\\\");e=n[n.length-1].toLowerCase()}return e}extension(){return $g.extension(this._url)}async _urlToLoad(){const{storedUrl:t,fullUrl:e}=this._urlData();this._node&&await li.blobs.fetchBlobForNode({storedUrl:t,fullUrl:e,node:this._node});return li.blobs.blobUrl(t)||e}deregisterUrl(){const{storedUrl:t}=this._urlData();li.blobs.deregisterUrl(t)}_urlData(){let t=this._url;const e=this._url.split(\\\\\\\"?\\\\\\\")[0];if(\\\\\\\"h\\\\\\\"!=t[0]){const e=this._scene.assets.root();e&&(t=`${e}${t}`)}return{fullUrl:t,storedUrl:e}}static async _loadMultipleBlobGlobal(t){const e=[];for(let n of t.files){const i=n.storedUrl,s=n.fullUrl,r=t.node;e.push(li.blobs.fetchBlobGlobal({storedUrl:i,fullUrl:s,node:r}))}const n=await Promise.all(e);for(let e of n)e.error&&t.node.states.error.set(t.error)}}$g.loadingManager=Yg;const Jg=[\\\\\\\"mp4\\\\\\\",\\\\\\\"ogv\\\\\\\",\\\\\\\"ogg\\\\\\\"];var Zg;!function(t){t.JPG=\\\\\\\"jpg\\\\\\\",t.JPEG=\\\\\\\"jpeg\\\\\\\",t.PNG=\\\\\\\"png\\\\\\\",t.EXR=\\\\\\\"exr\\\\\\\",t.BASIS=\\\\\\\"basis\\\\\\\",t.HDR=\\\\\\\"hdr\\\\\\\"}(Zg||(Zg={}));const Qg=[Zg.JPEG,Zg.JPG,Zg.PNG,Zg.EXR,Zg.BASIS,Zg.HDR];function Kg(t){const e=t.split(\\\\\\\"?\\\\\\\")[0].split(\\\\\\\".\\\\\\\");return e[e.length-1]}class tv extends $g{constructor(t,e,n,i,s){super(t,i,n),this._param=e,this._node=n,this._scene=i,this._forceVideo=!1,this._forceImage=!1,this._forceVideo=(null==s?void 0:s.forceVideo)||this._forceVideo,this._forceImage=(null==s?void 0:s.forceImage)||this._forceImage}static onTextureLoaded(t){this._onTextureLoadedCallback=t}async load_texture_from_url_or_op(t){let e=null,n=null;if(\\\\\\\"op:\\\\\\\"==this._url.substring(0,3)){const t=this._url.substring(3);if(n=bi.findNode(this._node,t),n)if(n instanceof pf){e=(await n.compute()).texture()}else this._node.states.error.set(\\\\\\\"found node is not a texture node\\\\\\\");else this._node.states.error.set(`no node found in path '${t}'`)}else e=await this._loadUrl(t),e||this._node.states.error.set(`could not load texture ${this._url}`);return n&&this._param.graphPredecessors()[0]!=n&&(this._param.graphDisconnectPredecessors(),this._param.addGraphInput(n)),e}async _loadUrl(t){return new Promise((async(e,n)=>{const i=this.extension(),s=await this._urlToLoad();if(this._forceVideo||Jg.includes(i)){e(await this._loadVideo(s))}else if(this._forceImage||Qg.includes(i))try{e(await this._loadImage(s,t))}catch(t){n()}}))}_loadImage(t,e){return new Promise((async(n,i)=>{const s=this.extension();this.loader_for_ext(s,e).then((async e=>{e?(tv.incrementInProgressLoadsCount(),await tv.waitForMaxConcurrentLoadsQueueFreed(),e.load(t,(e=>{tv.decrementInProgressLoadsCount();const i=tv._onTextureLoadedCallback;i&&i(t,e),n(e)}),void 0,(t=>{tv.decrementInProgressLoadsCount(),li.warn(\\\\\\\"error\\\\\\\",t),i()}))):i()}))}))}_loadVideo(t){return new Promise((async(e,n)=>{tv.incrementInProgressLoadsCount(),await tv.waitForMaxConcurrentLoadsQueueFreed();const i=document.createElement(\\\\\\\"video\\\\\\\");i.setAttribute(\\\\\\\"crossOrigin\\\\\\\",\\\\\\\"anonymous\\\\\\\"),i.setAttribute(\\\\\\\"autoplay\\\\\\\",\\\\\\\"true\\\\\\\"),i.setAttribute(\\\\\\\"loop\\\\\\\",\\\\\\\"true\\\\\\\"),i.onloadedmetadata=function(){i.pause();const n=new jg(i);tv.decrementInProgressLoadsCount();const s=tv._onTextureLoadedCallback;s&&s(t,n),e(n)};const s=document.createElement(\\\\\\\"source\\\\\\\"),r=$g.extension(t);let o=tv.VIDEO_SOURCE_TYPE_BY_EXT[r];o=o||tv._default_video_source_type(t),s.setAttribute(\\\\\\\"type\\\\\\\",o),s.setAttribute(\\\\\\\"src\\\\\\\",t),i.appendChild(s);let a=t;a=\\\\\\\"mp4\\\\\\\"==r?tv.replaceExtension(t,\\\\\\\"ogv\\\\\\\"):tv.replaceExtension(t,\\\\\\\"mp4\\\\\\\");const l=document.createElement(\\\\\\\"source\\\\\\\"),c=$g.extension(a);o=tv.VIDEO_SOURCE_TYPE_BY_EXT[c],o=o||tv._default_video_source_type(t),l.setAttribute(\\\\\\\"type\\\\\\\",o),l.setAttribute(\\\\\\\"src\\\\\\\",t),i.appendChild(l)}))}static module_names(t){switch(t){case Zg.EXR:return[Hn.EXRLoader];case Zg.HDR:return[Hn.RGBELoader];case Zg.BASIS:return[Hn.BasisTextureLoader]}}async loader_for_ext(t,e){switch(t.toLowerCase()){case Zg.EXR:return await this._exr_loader(e);case Zg.HDR:return await this._hdr_loader(e);case Zg.BASIS:return await tv._basis_loader(this._node)}return new Wg.a(this.loadingManager)}async _exr_loader(t){const e=await li.modulesRegister.module(Hn.EXRLoader);if(e){const n=new e(this.loadingManager);return t.tdataType&&n.setDataType(t.dataType),n}}async _hdr_loader(t){const e=await li.modulesRegister.module(Hn.RGBELoader);if(e){const n=new e(this.loadingManager);return t.tdataType&&n.setDataType(t.dataType),n}}static async _basis_loader(t){const e=await li.modulesRegister.module(Hn.BasisTextureLoader);if(e){const n=new e(this.loadingManager),i=li.libs.root(),s=li.libs.BASISPath();if(i||s){const e=`${i||\\\\\\\"\\\\\\\"}${s||\\\\\\\"\\\\\\\"}/`;if(t){const n=[\\\\\\\"basis_transcoder.js\\\\\\\",\\\\\\\"basis_transcoder.wasm\\\\\\\"];await this._loadMultipleBlobGlobal({files:n.map((t=>({storedUrl:`${s}/${t}`,fullUrl:`${e}${t}`}))),node:t,error:\\\\\\\"failed to load basis libraries. Make sure to install them to load .basis files\\\\\\\"})}n.setTranscoderPath(e)}else n.setTranscoderPath(void 0);const r=await li.renderersController.waitForRenderer();return r?n.detectSupport(r):li.warn(\\\\\\\"texture loader found no renderer for basis texture loader\\\\\\\"),n}}static _default_video_source_type(t){return`video/${$g.extension(t)}`}static pixel_data(t){const e=t.image,n=document.createElement(\\\\\\\"canvas\\\\\\\");n.width=e.width,n.height=e.height;const i=n.getContext(\\\\\\\"2d\\\\\\\");if(i)return i.drawImage(e,0,0,e.width,e.height),i.getImageData(0,0,e.width,e.height)}static replaceExtension(t,e){const n=t.split(\\\\\\\"?\\\\\\\"),i=n[0].split(\\\\\\\".\\\\\\\");return i.pop(),i.push(e),[i.join(\\\\\\\".\\\\\\\"),n[1]].join(\\\\\\\"?\\\\\\\")}static setMaxConcurrentLoadsCount(t){this._maxConcurrentLoadsCountMethod=t}static _init_max_concurrent_loads_count(){return this._maxConcurrentLoadsCountMethod?this._maxConcurrentLoadsCountMethod():ng.isChrome()?10:4}static _init_concurrent_loads_delay(){return ng.isChrome()?0:10}static incrementInProgressLoadsCount(){this.in_progress_loads_count++}static decrementInProgressLoadsCount(){this.in_progress_loads_count--;const t=this._queue.pop();if(t){const e=this.CONCURRENT_LOADS_DELAY;setTimeout((()=>{t()}),e)}}static async waitForMaxConcurrentLoadsQueueFreed(){return this.in_progress_loads_count<=this.MAX_CONCURRENT_LOADS_COUNT?void 0:new Promise((t=>{this._queue.push(t)}))}}tv.PARAM_DEFAULT=`${qg}/textures/uv.jpg`,tv.PARAM_ENV_DEFAULT=`${qg}/textures/piz_compressed.exr`,tv.VIDEO_SOURCE_TYPE_BY_EXT={ogg:'video/ogg; codecs=\\\\\\\"theora, vorbis\\\\\\\"',ogv:'video/ogg; codecs=\\\\\\\"theora, vorbis\\\\\\\"',mp4:'video/mp4; codecs=\\\\\\\"avc1.42E01E, mp4a.40.2\\\\\\\"'},tv.MAX_CONCURRENT_LOADS_COUNT=tv._init_max_concurrent_loads_count(),tv.CONCURRENT_LOADS_DELAY=tv._init_concurrent_loads_delay(),tv.in_progress_loads_count=0,tv._queue=[];var ev=n(114);class nv extends(Mg(function(t){return class extends t{constructor(){super(...arguments),this.url=ha.STRING(tv.PARAM_DEFAULT,{fileBrowse:{type:[Rr.TEXTURE_IMAGE]}}),this.reload=ha.BUTTON(null,{callback:(t,e)=>{sv.PARAM_CALLBACK_reload(t)}}),this.play=ha.BOOLEAN(1,{cook:!1,callback:t=>{sv.PARAM_CALLBACK_gifUpdatePlay(t)}}),this.gifFrame=ha.INTEGER(0,{cook:!1,range:[0,100],rangeLocked:[!0,!1],callback:t=>{sv.PARAM_CALLBACK_gifUpdateFrameIndex(t)}})}}}(ua))){}const iv=new nv;class sv extends df{constructor(){super(...arguments),this.paramsConfig=iv,this.textureParamsController=new Sg(this),this._gifCanvasContext=null,this._tmpCanvasContext=null,this._parsedFrames=[],this._frameDelay=100,this._frameIndex=0}static type(){return\\\\\\\"gif\\\\\\\"}async requiredModules(){this.p.url.isDirty()&&await this.p.url.compute();const t=$g.extension(this.pv.url||\\\\\\\"\\\\\\\");return tv.module_names(t)}static displayedInputNames(){return[\\\\\\\"optional texture to copy attributes from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(Ki.NEVER),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{let t=[this.p.url];t=t.concat(this.textureParamsController.paramLabelsParams()),this.params.label.init(t,(()=>{const t=this.p.url.rawInput();if(t){const e=t.split(\\\\\\\"/\\\\\\\"),n=e[e.length-1],i=this.textureParamsController.paramLabels();return[n].concat(i)}return\\\\\\\"\\\\\\\"}))}))}))}async cook(t){if(\\\\\\\"gif\\\\\\\"!=Kg(this.pv.url).toLowerCase())this.states.error.set(\\\\\\\"url is not an image\\\\\\\");else{tv.incrementInProgressLoadsCount(),await tv.waitForMaxConcurrentLoadsQueueFreed();const t=await fetch(this.pv.url),e=await t.arrayBuffer(),n=await Object(ev.parseGIF)(e),i=!0;this._parsedFrames=await Object(ev.decompressFrames)(n,i);const s=this._parsedFrames[0];if(this._frameDelay=s.delay,this._frameIndex=this.pv.gifFrame-1,this._createCanvas(),tv.decrementInProgressLoadsCount(),this._gifCanvasElement){const t=new Cg(this._gifCanvasElement);await this.textureParamsController.update(t),this.setTexture(t)}else this.states.error.set(\\\\\\\"failed to create canvas\\\\\\\")}}_createCanvas(){const t=this._parsedFrames[0];this._gifCanvasElement=document.createElement(\\\\\\\"canvas\\\\\\\"),this._tmpCanvasElement=document.createElement(\\\\\\\"canvas\\\\\\\"),this._gifCanvasElement.width=t.dims.width,this._gifCanvasElement.height=t.dims.height,this._tmpCanvasElement.width=t.dims.width,this._tmpCanvasElement.height=t.dims.height,this._gifCanvasContext=this._gifCanvasElement.getContext(\\\\\\\"2d\\\\\\\"),this._tmpCanvasContext=this._tmpCanvasElement.getContext(\\\\\\\"2d\\\\\\\"),this._drawNextFrame()}_drawOnCanvas(){if(!(this._gifCanvasContext&&this._tmpCanvasElement&&this._tmpCanvasContext))return;let t=this._parsedFrames[this._frameIndex];if(t||(console.warn(`no frame at index ${this._frameIndex}, using last frame`),t=this._parsedFrames[this._parsedFrames.length-1]),t){const e=t.dims;this._frameImageData&&e.width==this._frameImageData.width&&e.height==this._frameImageData.height||(this._tmpCanvasElement.width=e.width,this._tmpCanvasElement.height=e.height,this._frameImageData=this._tmpCanvasContext.createImageData(e.width,e.height)),this._frameImageData.data.set(t.patch),this._tmpCanvasContext.putImageData(this._frameImageData,0,0),this._gifCanvasContext.drawImage(this._tmpCanvasElement,e.left,e.top);const n=this.containerController.container().texture();if(!n)return;n.needsUpdate=!0}}_drawNextFrame(){this._frameIndex++,this._frameIndex>=this._parsedFrames.length&&(this._frameIndex=0),this._drawOnCanvas(),this.pv.play&&setTimeout((()=>{this._drawNextFrame()}),this._frameDelay)}gifUpdateFrameIndex(){this._frameIndex=this.pv.gifFrame,this._drawOnCanvas()}static PARAM_CALLBACK_reload(t){t.paramCallbackReload()}paramCallbackReload(){this.p.url.setDirty()}static PARAM_CALLBACK_gifUpdatePlay(t){t.gifUpdatePlay()}gifUpdatePlay(){this.pv.play&&this._drawNextFrame()}static PARAM_CALLBACK_gifUpdateFrameIndex(t){t.gifUpdateFrameIndex()}}function rv(t){return class extends t{constructor(){super(...arguments),this.checkFileType=ha.BOOLEAN(!0)}}}class ov extends(rv(Mg(function(t){return class extends t{constructor(){super(...arguments),this.url=ha.STRING(tv.PARAM_DEFAULT,{fileBrowse:{type:[Rr.TEXTURE_IMAGE]}}),this.reload=ha.BUTTON(null,{callback:(t,e)=>{lv.PARAM_CALLBACK_reload(t,e)}})}}}(ua)))){}const av=new ov;class lv extends df{constructor(){super(...arguments),this.paramsConfig=av,this.textureParamsController=new Sg(this)}static type(){return\\\\\\\"image\\\\\\\"}async requiredModules(){this.p.url.isDirty()&&await this.p.url.compute();const t=$g.extension(this.pv.url||\\\\\\\"\\\\\\\");return tv.module_names(t)}static displayedInputNames(){return[\\\\\\\"optional texture to copy attributes from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(Ki.NEVER),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{let t=[this.p.url];t=t.concat(this.textureParamsController.paramLabelsParams()),this.params.label.init(t,(()=>{const t=this.p.url.rawInput();if(t){const e=t.split(\\\\\\\"/\\\\\\\"),n=e[e.length-1],i=this.textureParamsController.paramLabels();return[n].concat(i)}return\\\\\\\"\\\\\\\"}))}))}))}async cook(t){if(this.pv.checkFileType&&(e=this.pv.url,!Qg.includes(Kg(e).toLowerCase())))this.states.error.set(\\\\\\\"url is not an image\\\\\\\");else{const e=await this._loadTexture();if(e){const n=t[0];n&&Sg.copyTextureAttributes(e,n),await this.textureParamsController.update(e),this.setTexture(e)}else this._clearTexture()}var e}static PARAM_CALLBACK_reload(t,e){t.paramCallbackReload()}paramCallbackReload(){this.clearLoadedBlob(),this.p.url.setDirty()}_loader(){return new tv(this.pv.url,this.p.url,this,this.scene(),{forceImage:!this.pv.checkFileType})}async _loadTexture(){let t=null;try{t=await this._loader().load_texture_from_url_or_op({tdataType:this.pv.ttype&&this.pv.tadvanced,dataType:this.pv.type}),t&&(t.matrixAutoUpdate=!1)}catch(t){}return t||this.states.error.set(`could not load texture '${this.pv.url}'`),t}clearLoadedBlob(){this._loader().deregisterUrl()}}var cv=n(33);const hv=.005;class uv{constructor(t,e=1024){this.renderer=t,this.res=e,this.objectTargets=[],this.lights=[],this.scene=new vs,this.buffer1Active=!1,this._params={lightRadius:1,iterations:1,iterationBlend:hv,blur:!1,blurAmount:0},this._objectStateByObject=new WeakMap,this._previousRenderTarget=null,this._lightHierarchyStateByLight=new WeakMap,this._lightMatrixStateByLight=new WeakMap,this._t=new p.a,this._q=new hh.a,this._s=new p.a;const n=ng.isAndroid()||ng.isiOS()?w.M:w.G;this.progressiveLightMap1=new Q(this.res,this.res,{type:n}),this.progressiveLightMap2=new Q(this.res,this.res,{type:n}),this.uvMat=this._createUVMat()}textureRenderTarget(){return this.progressiveLightMap2}texture(){return this.textureRenderTarget().texture}setParams(t){this._params.lightRadius=t.lightRadius,this._params.iterations=t.iterations,this._params.iterationBlend=t.iterationBlend,this._params.blur=t.blur,this._params.blurAmount=t.blurAmount}init(t,e){this._setObjects(t),this._setLights(e)}_setObjects(t){this.objectTargets=[];for(let e of t)null==this.blurringPlane&&this._initializeBlurPlane(this.res,this.progressiveLightMap1),this.objectTargets.push(e);this._saveObjectsState()}_setLights(t){this.lights=t;for(let e of t)this._saveLightHierarchyState(e),this.scene.attach(e),this._saveLightMatrixState(e)}_saveLightHierarchyState(t){this._lightHierarchyStateByLight.set(t,{parent:t.parent,matrixAutoUpdate:t.matrixAutoUpdate}),t.matrixAutoUpdate=!0}_saveLightMatrixState(t){t.updateMatrix(),t.matrix.decompose(this._t,this._q,this._s),this._lightMatrixStateByLight.set(t,{matrix:t.matrix.clone(),position:this._t.clone()})}_saveObjectsState(){let t=0;for(let e of this.objectTargets)this._objectStateByObject.set(e,{frustumCulled:e.frustumCulled,material:e.material,parent:e.parent,castShadow:e.castShadow,receiveShadow:e.receiveShadow}),e.material=this.uvMat,e.frustumCulled=!1,e.castShadow=!0,e.receiveShadow=!0,e.renderOrder=1e3+t,this.scene.attach(e),t++;this._previousRenderTarget=this.renderer.getRenderTarget()}_moveLights(){const t=this._params.lightRadius;for(let e of this.lights){const n=this._lightMatrixStateByLight.get(e);if(n){const i=n.position;e.position.x=i.x+t*(Math.random()-.5),e.position.y=i.y+t*(Math.random()-.5),e.position.z=i.z+t*(Math.random()-.5)}}}restoreState(){this._restoreObjectsState(),this._restoreLightsState(),this.renderer.setRenderTarget(this._previousRenderTarget)}_restoreObjectsState(){for(let t of this.objectTargets){const e=this._objectStateByObject.get(t);if(e){t.frustumCulled=e.frustumCulled,t.castShadow=e.castShadow,t.receiveShadow=e.receiveShadow,t.material=e.material;const n=e.parent;n&&n.add(t)}}}_restoreLightsState(){var t;for(let e of this.lights){const n=this._lightHierarchyStateByLight.get(e),i=this._lightMatrixStateByLight.get(e);n&&i&&(e.matrixAutoUpdate=n.matrixAutoUpdate,e.matrix.copy(i.matrix),e.matrix.decompose(e.position,e.quaternion,e.scale),e.updateMatrix(),null===(t=n.parent)||void 0===t||t.attach(e))}}runUpdates(t){if(!this.blurMaterial)return;if(null==this.blurringPlane)return;const e=this._params.iterations;this.blurMaterial.uniforms.pixelOffset.value=this._params.blurAmount/this.res,this.blurringPlane.visible=this._params.blur,this.uvMat.uniforms.iterationBlend.value=this._params.iterationBlend,this._clear(t);for(let n=0;n{i.vertexShader=\\\\\\\"#define USE_UV\\\\n\\\\\\\"+i.vertexShader.slice(0,-2)+\\\\\\\"\\\\tgl_Position = vec4((uv - 0.5) * 2.0, 1.0, 1.0); }\\\\\\\";const s=i.fragmentShader.indexOf(\\\\\\\"void main() {\\\\\\\");i.fragmentShader=\\\\\\\"#define USE_UV\\\\n\\\\\\\"+i.fragmentShader.slice(0,s)+\\\\\\\"\\\\tuniform sampler2D previousShadowMap;\\\\n\\\\tuniform float pixelOffset;\\\\n\\\\\\\"+i.fragmentShader.slice(s-1,-2)+\\\\\\\"\\\\tgl_FragColor.rgb = (\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ttexture2D(previousShadowMap, vUv + vec2( pixelOffset, 0.0 )).rgb +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ttexture2D(previousShadowMap, vUv + vec2( 0.0 , pixelOffset)).rgb +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ttexture2D(previousShadowMap, vUv + vec2( 0.0 , -pixelOffset)).rgb +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ttexture2D(previousShadowMap, vUv + vec2(-pixelOffset, 0.0 )).rgb +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ttexture2D(previousShadowMap, vUv + vec2( pixelOffset, pixelOffset)).rgb +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ttexture2D(previousShadowMap, vUv + vec2(-pixelOffset, pixelOffset)).rgb +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ttexture2D(previousShadowMap, vUv + vec2( pixelOffset, -pixelOffset)).rgb +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ttexture2D(previousShadowMap, vUv + vec2(-pixelOffset, -pixelOffset)).rgb)/8.0;\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\";const r={previousShadowMap:{value:e.texture},pixelOffset:{value:.5/t}};i.uniforms.previousShadowMap=r.previousShadowMap,i.uniforms.pixelOffset=r.pixelOffset,n.uniforms.previousShadowMap=r.previousShadowMap,n.uniforms.pixelOffset=r.pixelOffset,n.userData.shader=i},n}_createUVMat(){const t=new qf.a;return t.uniforms={previousShadowMap:{value:null},iterationBlend:{value:hv}},t.name=\\\\\\\"uvMat\\\\\\\",t.onBeforeCompile=e=>{e.vertexShader=\\\\\\\"#define USE_LIGHTMAP\\\\n\\\\\\\"+e.vertexShader.slice(0,-2)+\\\\\\\"\\\\tgl_Position = vec4((uv2 - 0.5) * 2.0, 1.0, 1.0); }\\\\\\\";const n=e.fragmentShader.indexOf(\\\\\\\"void main() {\\\\\\\");e.fragmentShader=\\\\\\\"varying vec2 vUv2;\\\\n\\\\\\\"+e.fragmentShader.slice(0,n)+\\\\\\\"\\\\tuniform sampler2D previousShadowMap;\\\\n\\\\tuniform float iterationBlend;\\\\n\\\\\\\"+e.fragmentShader.slice(n-1,-2)+\\\\\\\"\\\\nvec3 texelOld = texture2D(previousShadowMap, vUv2).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb = mix(texelOld, gl_FragColor.rgb, iterationBlend);\\\\n\\\\t\\\\t\\\\t\\\\t// gl_FragColor.rgb = vec3(vUv2,1.0);\\\\n\\\\t\\\\t\\\\t}\\\\\\\";const i={previousShadowMap:{value:this.progressiveLightMap1.texture},iterationBlend:{value:hv}};e.uniforms.previousShadowMap=i.previousShadowMap,e.uniforms.iterationBlend=i.iterationBlend,t.uniforms.previousShadowMap=i.previousShadowMap,t.uniforms.iterationBlend=i.iterationBlend,t.userData.shader=e},t}}const dv=new class extends ua{constructor(){super(...arguments),this.update=ha.BUTTON(null,{callback:t=>{pv.PARAM_CALLBACK_updateManual(t)}}),this.useCameraRenderer=ha.BOOLEAN(1),this.lightMapRes=ha.INTEGER(1024,{range:[1,2048],rangeLocked:[!0,!1]}),this.iterations=ha.INTEGER(512,{range:[1,2048],rangeLocked:[!0,!1]}),this.iterationBlend=ha.FLOAT(hv,{range:[0,1],rangeLocked:[!0,!0]}),this.blur=ha.BOOLEAN(1),this.blurAmount=ha.FLOAT(1,{visibleIf:{blur:1},range:[0,1],rangeLocked:[!0,!1]}),this.lightRadius=ha.FLOAT(1,{range:[0,10]}),this.objectsMask=ha.STRING(\\\\\\\"\\\\\\\"),this.lightsMask=ha.STRING(\\\\\\\"*\\\\\\\"),this.printResolveObjectsList=ha.BUTTON(null,{callback:t=>{pv.PARAM_CALLBACK_printResolveObjectsList(t)}})}};class pv extends df{constructor(){super(...arguments),this.paramsConfig=dv,this._includedObjects=[],this._includedLights=[]}static type(){return\\\\\\\"lightMap\\\\\\\"}async cook(){this._updateManual()}async _createLightMapController(){const t=await li.renderersController.firstRenderer();if(!t)return void console.warn(\\\\\\\"no renderer found\\\\\\\");return new uv(t,this.pv.lightMapRes)}static PARAM_CALLBACK_update_updateMode(t){}async _updateManual(){if(this.lightMapController=this.lightMapController||await this._createLightMapController(),!this.lightMapController)return;const t=this.scene().mainCameraNode();if(!t)return;this._updateObjectsAndLightsList(),this.lightMapController.init(this._includedObjects,this._includedLights);const e=t.camera();this.lightMapController.setParams({lightRadius:this.pv.lightRadius,iterations:this.pv.iterations,iterationBlend:this.pv.iterationBlend,blur:this.pv.blur,blurAmount:this.pv.blurAmount}),this.lightMapController.runUpdates(e),this.lightMapController.restoreState();const n=this.lightMapController.textureRenderTarget();if(this.pv.useCameraRenderer)this.setTexture(n.texture);else{this._data_texture_controller=this._data_texture_controller||new kf(zf.Float32Array),this._renderer_controller=this._renderer_controller||new Uf(this);const t=await this._renderer_controller.renderer(),e=this._data_texture_controller.from_render_target(t,n);this.setTexture(e)}}static PARAM_CALLBACK_updateManual(t){t._updateManual()}_updateObjectsAndLightsList(){let t=[],e=[];this._includedLights=[],this._includedObjects=[];const n=new WeakSet;if(\\\\\\\"\\\\\\\"!=this.pv.lightsMask){e=this.scene().objectsByMask(this.pv.lightsMask);for(let t of e)t instanceof cv.a&&(this._includedLights.push(t),n.add(t))}if(\\\\\\\"\\\\\\\"!=this.pv.objectsMask){t=this.scene().objectsByMask(this.pv.objectsMask);for(let e of t)e instanceof cv.a||!n.has(e)&&e instanceof B.a&&this._includedObjects.push(e)}}static PARAM_CALLBACK_printResolveObjectsList(t){t._printResolveObjectsList()}_printResolveObjectsList(){this._updateObjectsAndLightsList(),console.log(\\\\\\\"included objects:\\\\\\\"),console.log(this._includedObjects),console.log(\\\\\\\"included lights:\\\\\\\"),console.log(this._includedLights)}}const _v=new ua;class mv extends df{constructor(){super(...arguments),this.paramsConfig=_v}static type(){return\\\\\\\"null\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Ki.NEVER)}async cook(t){const e=t[0];this.setTexture(e)}}class fv extends(Mg(function(t){return class extends t{constructor(){super(...arguments),this.camera=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.OBJ,types:ds}}),this.resolution=ha.VECTOR2([1024,1024]),this.useCameraRenderer=ha.BOOLEAN(1),this.render=ha.BUTTON(null,{callback:t=>{vv.PARAM_CALLBACK_render(t)}})}}}(ua))){}const gv=new fv;class vv extends df{constructor(){super(...arguments),this.paramsConfig=gv,this.textureParamsController=new Sg(this)}static type(){return\\\\\\\"render\\\\\\\"}async cook(){this._texture_scene=this.scene().threejsScene(),this._camera_node=this.pv.camera.nodeWithContext(ts.OBJ),this._camera_node&&ds.includes(this._camera_node.type())?(this._texture_camera=this._camera_node.object,await this._camera_node.compute(),this.renderOnTarget()):this._texture_camera=void 0}async renderOnTarget(){if(await this.createRenderTargetIfRequired(),!(this._render_target&&this._texture_scene&&this._texture_camera))return;this._renderer_controller=this._renderer_controller||new Uf(this);const t=await this._renderer_controller.renderer(),e=t.getRenderTarget();if(t.setRenderTarget(this._render_target),t.clear(),t.render(this._texture_scene,this._texture_camera),t.setRenderTarget(e),this._render_target.texture)if(this.pv.useCameraRenderer)this.setTexture(this._render_target.texture);else{this._data_texture_controller=this._data_texture_controller||new kf(zf.Float32Array);const e=this._data_texture_controller.from_render_target(t,this._render_target);await this.textureParamsController.update(e),this.setTexture(e)}else this.cookController.endCook()}async renderTarget(){return this._render_target=this._render_target||await this._createRenderTarget(this.pv.resolution.x,this.pv.resolution.y)}async createRenderTargetIfRequired(){var t;this._render_target&&this._renderTargetResolutionValid()||(this._render_target=await this._createRenderTarget(this.pv.resolution.x,this.pv.resolution.y),null===(t=this._data_texture_controller)||void 0===t||t.reset())}_renderTargetResolutionValid(){if(this._render_target){const t=this._render_target.texture.image;return t.width==this.pv.resolution.x&&t.height==this.pv.resolution.y}return!1}async _createRenderTarget(t,e){if(this._render_target){const n=this._render_target.texture.image;if(n.width==t&&n.height==e)return this._render_target}const n=w.n,i=w.n,s=w.V,r=w.ob;var o=new Q(t,e,{wrapS:n,wrapT:i,minFilter:s,magFilter:r,format:w.Ib,generateMipmaps:!0,type:ng.isiOS()?w.M:w.G,stencilBuffer:!1,depthBuffer:!1});return await this.textureParamsController.update(o.texture),li.warn(\\\\\\\"created render target\\\\\\\",this.path(),t,e),o}static PARAM_CALLBACK_render(t){t.renderOnTarget()}}const yv=new class extends ua{constructor(){super(...arguments),this.input=ha.INTEGER(0,{range:[0,3],rangeLocked:[!0,!0]})}};class xv extends df{constructor(){super(...arguments),this.paramsConfig=yv}static type(){return\\\\\\\"switch\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,4),this.io.inputs.initInputsClonedState(Ki.NEVER),this.cookController.disallowInputsEvaluation()}async cook(){const t=this.pv.input;if(this.io.inputs.has_input(t)){const e=await this.containerController.requestInputContainer(t);if(e)return void this.setTexture(e.texture())}else this.states.error.set(`no input ${t}`);this.cookController.endCook()}}class bv extends(Mg(ua)){}const wv=new bv;class Tv extends df{constructor(){super(...arguments),this.paramsConfig=wv,this.textureParamsController=new Sg(this)}static type(){return\\\\\\\"textureProperties\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState([Ki.FROM_NODE])}async cook(t){const e=t[0];this.textureParamsController.update(e),this.setTexture(e)}}class Av extends(rv(Mg(function(t){return class extends t{constructor(){super(...arguments),this.url=ha.STRING(tv.PARAM_DEFAULT,{fileBrowse:{type:[Rr.TEXTURE_VIDEO]}}),this.reload=ha.BUTTON(null,{callback:(t,e)=>{Ev.PARAM_CALLBACK_reload(t,e)}}),this.play=ha.BOOLEAN(1,{cook:!1,callback:t=>{Ev.PARAM_CALLBACK_video_update_play(t)}}),this.muted=ha.BOOLEAN(1,{cook:!1,callback:t=>{Ev.PARAM_CALLBACK_video_update_muted(t)}}),this.loop=ha.BOOLEAN(1,{cook:!1,callback:t=>{Ev.PARAM_CALLBACK_video_update_loop(t)}}),this.videoTime=ha.FLOAT(0,{cook:!1}),this.setVideoTime=ha.BUTTON(null,{cook:!1,callback:t=>{Ev.PARAM_CALLBACK_video_update_time(t)}})}}}(ua)))){}const Mv=new Av;class Ev extends df{constructor(){super(...arguments),this.paramsConfig=Mv,this.textureParamsController=new Sg(this)}static type(){return Fg.VIDEO}async requiredModules(){this.p.url.isDirty()&&await this.p.url.compute();const t=$g.extension(this.pv.url||\\\\\\\"\\\\\\\");return tv.module_names(t)}HTMLVideoElement(){return this._video}static displayedInputNames(){return[\\\\\\\"optional texture to copy attributes from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(Ki.NEVER),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.url],(()=>{const t=this.p.url.rawInput();if(t){const e=t.split(\\\\\\\"/\\\\\\\");return e[e.length-1]}return\\\\\\\"\\\\\\\"}))}))}))}async cook(t){if(this.pv.checkFileType&&(e=this.pv.url,!Jg.includes(Kg(e).toLowerCase())))this.states.error.set(\\\\\\\"url is not a video\\\\\\\");else{const e=await this._load_texture(this.pv.url);if(e){this._video=e.image,this._video&&document.body.appendChild(this._video);const n=t[0];n&&Sg.copyTextureAttributes(e,n),this.video_update_loop(),this.video_update_muted(),this.video_update_play(),this.video_update_time(),await this.textureParamsController.update(e),this.setTexture(e)}else this.cookController.endCook()}var e}dispose(){var t;super.dispose(),this._video&&(null===(t=this._video.parentElement)||void 0===t||t.removeChild(this._video))}static PARAM_CALLBACK_video_update_time(t){t.video_update_time()}static PARAM_CALLBACK_video_update_play(t){t.video_update_play()}static PARAM_CALLBACK_video_update_muted(t){t.video_update_muted()}static PARAM_CALLBACK_video_update_loop(t){t.video_update_loop()}async video_update_time(){if(this._video){const t=this.p.videoTime;t.isDirty()&&await t.compute(),this._video.currentTime=t.value}}video_update_muted(){this._video&&(this._video.muted=this.pv.muted)}video_update_loop(){this._video&&(this._video.loop=this.pv.loop)}video_update_play(){this._video&&(this.pv.play?this._video.play():this._video.pause())}static PARAM_CALLBACK_reload(t,e){t.paramCallbackReload()}paramCallbackReload(){this.p.url.setDirty()}async _load_texture(t){let e=null;const n=this.p.url;this._texture_loader=this._texture_loader||new tv(t,n,this,this.scene(),{forceVideo:!this.pv.checkFileType});try{e=await this._texture_loader.load_texture_from_url_or_op({tdataType:this.pv.ttype&&this.pv.tadvanced,dataType:this.pv.type}),e&&(e.matrixAutoUpdate=!1)}catch(t){}return e||this.states.error.set(`could not load texture '${t}'`),e}}class Sv extends(Mg(function(t){return class extends t{constructor(){super(...arguments),this.res=ha.VECTOR2([1024,1024])}}}(ua))){}const Cv=new Sv;class Nv extends df{constructor(){super(...arguments),this.paramsConfig=Cv,this.textureParamsController=new Sg(this)}static type(){return Fg.WEB_CAM}HTMLVideoElement(){return this._video}static displayedInputNames(){return[\\\\\\\"optional texture to copy attributes from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(Ki.NEVER)}_createHTMLVideoElement(){this._video&&document.body.removeChild(this._video);const t=document.createElement(\\\\\\\"video\\\\\\\");return t.style.display=\\\\\\\"none\\\\\\\",t.width=this.pv.res.x,t.height=this.pv.res.y,t.autoplay=!0,t.setAttribute(\\\\\\\"autoplay\\\\\\\",\\\\\\\"true\\\\\\\"),t.setAttribute(\\\\\\\"muted\\\\\\\",\\\\\\\"true\\\\\\\"),t.setAttribute(\\\\\\\"playsinline\\\\\\\",\\\\\\\"true\\\\\\\"),document.body.appendChild(t),t}async cook(t){this._video=this._createHTMLVideoElement();const e=new jg(this._video),n=t[0];if(n&&Sg.copyTextureAttributes(e,n),await this.textureParamsController.update(e),navigator&&navigator.mediaDevices&&navigator.mediaDevices.getUserMedia){const t={video:{width:this.pv.res.x,height:this.pv.res.y,facingMode:\\\\\\\"user\\\\\\\"}};navigator.mediaDevices.getUserMedia(t).then((t=>{this._video&&(this._video.srcObject=t,this._video.play(),this.setTexture(e))})).catch((t=>{this.states.error.set(\\\\\\\"Unable to access the camera/webcam\\\\\\\")}))}else this.states.error.set(\\\\\\\"MediaDevices interface not available.\\\\\\\")}}class Lv extends aa{static context(){return ts.COP}cook(){this.cookController.endCook()}}class Ov extends Lv{}class Pv extends Ov{constructor(){super(...arguments),this._children_controller_context=ts.ANIM}static type(){return es.ANIM}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class Rv extends Ov{constructor(){super(...arguments),this._children_controller_context=ts.EVENT}static type(){return es.EVENT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class Iv extends Ov{constructor(){super(...arguments),this._children_controller_context=ts.COP}static type(){return es.COP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class Fv extends Ov{constructor(){super(...arguments),this._children_controller_context=ts.MAT}static type(){return es.MAT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class Dv extends Lv{constructor(){super(...arguments),this.paramsConfig=new ef,this.effectsComposerController=new nf(this),this.displayNodeController=new Fm(this,this.effectsComposerController.displayNodeControllerCallbacks()),this._children_controller_context=ts.POST}static type(){return es.POST}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class Bv extends Ov{constructor(){super(...arguments),this._children_controller_context=ts.ROP}static type(){return es.ROP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}var zv,kv;!function(t){t.START=\\\\\\\"start\\\\\\\",t.STOP=\\\\\\\"stop\\\\\\\",t.UPDATE=\\\\\\\"update\\\\\\\"}(zv||(zv={})),function(t){t.START=\\\\\\\"start\\\\\\\",t.COMPLETE=\\\\\\\"completed\\\\\\\"}(kv||(kv={}));const Uv=new class extends ua{constructor(){super(...arguments),this.animation=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.ANIM},dependentOnFoundNode:!1}),this.play=ha.BUTTON(null,{callback:t=>{Gv.PARAM_CALLBACK_play(t)}}),this.pause=ha.BUTTON(null,{callback:t=>{Gv.PARAM_CALLBACK_pause(t)}})}};class Gv extends Va{constructor(){super(...arguments),this.paramsConfig=Uv}static type(){return\\\\\\\"animation\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(zv.START,Ko.BASE,this._play.bind(this)),new ta(zv.STOP,Ko.BASE,this._pause.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(kv.START,Ko.BASE),new ta(kv.COMPLETE,Ko.BASE)]),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.animation],(()=>this.pv.animation.path()))}))}))}processEvent(t){}static PARAM_CALLBACK_play(t){t._play({})}static PARAM_CALLBACK_pause(t){t._pause()}async _play(t){const e=this.p.animation;e.isDirty()&&await e.compute();const n=e.value.nodeWithContext(ts.ANIM);if(!n)return;const i=await n.compute();i&&(this._timelineBuilder=i.coreContent(),this._timelineBuilder&&(this._timeline&&this._timeline.kill(),this._timeline=F_.timeline(),this._timelineBuilder.populate(this._timeline),this._timeline.vars.onStart=()=>{this._triggerAnimationStarted(t)},this._timeline.vars.onComplete=()=>{this._timeline&&this._timeline.kill(),this._triggerAnimationCompleted(t)}))}_pause(){this._timeline&&this._timeline.pause()}_triggerAnimationStarted(t){this.dispatchEventToOutput(kv.START,t)}_triggerAnimationCompleted(t){this.dispatchEventToOutput(kv.COMPLETE,t)}}const Vv=\\\\\\\"event\\\\\\\";const Hv=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(1),this.inputsCount=ha.INTEGER(5,{range:[1,10],rangeLocked:[!0,!1]})}};class jv extends Va{constructor(){super(...arguments),this.paramsConfig=Hv}static type(){return\\\\\\\"any\\\\\\\"}initializeNode(){this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_input_name_function(this._input_name.bind(this)),this.io.connection_points.set_output_name_function((()=>Vv)),this.io.connection_points.set_expected_output_types_function((()=>[Ko.BASE]))}_expected_input_types(){const t=new Array(this.pv.inputsCount);return t.fill(Ko.BASE),t}_input_name(t){return`trigger${t}`}async processEvent(t){this.p.active.isDirty()&&await this.p.active.compute(),this.pv.active&&this.dispatchEventToOutput(Vv,t)}}const Wv=new class extends ua{constructor(){super(...arguments),this.blocking=ha.BOOLEAN(1)}};class qv extends Va{constructor(){super(...arguments),this.paramsConfig=Wv}static type(){return\\\\\\\"block\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(\\\\\\\"in\\\\\\\",Ko.BASE,this._process_incoming_event.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(qv.OUTPUT,Ko.BASE)]),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.blocking],(()=>this.pv.blocking?\\\\\\\"blocking (X)\\\\\\\":\\\\\\\"pass-through (--\\\\x3e)\\\\\\\"))}))}))}trigger_output(t){this.dispatchEventToOutput(qv.OUTPUT,t)}_process_incoming_event(t){this.pv.blocking||this.trigger_output(t)}}var Xv;qv.OUTPUT=\\\\\\\"output\\\\\\\",function(t){t.OUT=\\\\\\\"out\\\\\\\"}(Xv||(Xv={}));const Yv=new class extends ua{constructor(){super(...arguments),this.dispatch=ha.BUTTON(null,{callback:t=>{$v.PARAM_CALLBACK_execute(t)}})}};class $v extends Va{constructor(){super(...arguments),this.paramsConfig=Yv}static type(){return\\\\\\\"button\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new ta(Xv.OUT,Ko.BASE)])}processEvent(t){}process_event_execute(t){this.dispatchEventToOutput(Xv.OUT,t)}static PARAM_CALLBACK_execute(t){t.process_event_execute({})}}class Jv extends Va{constructor(){super(...arguments),this._controls_by_viewer=new Map}async apply_controls(t,e){var n;null===(n=e.controlsController)||void 0===n||n.dispose_controls();const i=e.canvas();if(!i)return;const s=await this.createControlsInstance(t,i),r=this._controls_by_viewer.get(e);r&&r.dispose(),this._controls_by_viewer.set(e,s);const o=li.performance.performanceManager().now();return s.name=`${this.path()}:${t.name}:${o}:${this.controls_id()}`,await this.params.evalAll(),this.setupControls(s),s}controls_id(){return JSON.stringify(this.params.all.map((t=>t.valueSerialized())))}}var Zv=n(27);const Qv=new p.a(0,0,1),Kv=new Zv.a,ty=new hh.a,ey=new hh.a(-Math.sqrt(.5),0,0,Math.sqrt(.5)),ny={type:\\\\\\\"change\\\\\\\"};class iy extends J.a{constructor(t){super(),!1===window.isSecureContext&&console.error(\\\\\\\"THREE.DeviceOrientationControls: DeviceOrientationEvent is only available in secure contexts (https)\\\\\\\");const e=this,n=new hh.a;this.object=t,this.object.rotation.reorder(\\\\\\\"YXZ\\\\\\\"),this.enabled=!0,this.deviceOrientation={},this.screenOrientation=0,this.alphaOffset=0;const i=function(t){e.deviceOrientation=t},s=function(){e.screenOrientation=window.orientation||0};this.connect=function(){s(),void 0!==window.DeviceOrientationEvent&&\\\\\\\"function\\\\\\\"==typeof window.DeviceOrientationEvent.requestPermission?window.DeviceOrientationEvent.requestPermission().then((function(t){\\\\\\\"granted\\\\\\\"==t&&(window.addEventListener(\\\\\\\"orientationchange\\\\\\\",s),window.addEventListener(\\\\\\\"deviceorientation\\\\\\\",i))})).catch((function(t){console.error(\\\\\\\"THREE.DeviceOrientationControls: Unable to use DeviceOrientation API:\\\\\\\",t)})):(window.addEventListener(\\\\\\\"orientationchange\\\\\\\",s),window.addEventListener(\\\\\\\"deviceorientation\\\\\\\",i)),e.enabled=!0},this.disconnect=function(){window.removeEventListener(\\\\\\\"orientationchange\\\\\\\",s),window.removeEventListener(\\\\\\\"deviceorientation\\\\\\\",i),e.enabled=!1},this.update=function(){if(!1===e.enabled)return;const t=e.deviceOrientation;if(t){const i=t.alpha?On.e(t.alpha)+e.alphaOffset:0,s=t.beta?On.e(t.beta):0,r=t.gamma?On.e(t.gamma):0,o=e.screenOrientation?On.e(e.screenOrientation):0;!function(t,e,n,i,s){Kv.set(n,e,-i,\\\\\\\"YXZ\\\\\\\"),t.setFromEuler(Kv),t.multiply(ey),t.multiply(ty.setFromAxisAngle(Qv,-s))}(e.object.quaternion,i,s,r,o),8*(1-n.dot(e.object.quaternion))>1e-6&&(n.copy(e.object.quaternion),e.dispatchEvent(ny))}},this.dispose=function(){e.disconnect()},this.connect()}}const sy=new class extends ua{constructor(){super(...arguments),this.enabled=ha.BOOLEAN(1)}};class ry extends Jv{constructor(){super(...arguments),this.paramsConfig=sy,this._controls_by_element_id=new Map}static type(){return _s.DEVICE_ORIENTATION}endEventName(){return\\\\\\\"end\\\\\\\"}async createControlsInstance(t,e){const n=new iy(t);return this._controls_by_element_id.set(e.id,n),n}setupControls(t){t.enabled=this.pv.enabled}updateRequired(){return!0}disposeControlsForHtmlElementId(t){const e=this._controls_by_element_id.get(t);e&&(e.dispose(),this._controls_by_element_id.delete(t))}}class oy{constructor(t=1,e=0,n=0){return this.radius=t,this.phi=e,this.theta=n,this}set(t,e,n){return this.radius=t,this.phi=e,this.theta=n,this}copy(t){return this.radius=t.radius,this.phi=t.phi,this.theta=t.theta,this}makeSafe(){const t=1e-6;return this.phi=Math.max(t,Math.min(Math.PI-t,this.phi)),this}setFromVector3(t){return this.setFromCartesianCoords(t.x,t.y,t.z)}setFromCartesianCoords(t,e,n){return this.radius=Math.sqrt(t*t+e*e+n*n),0===this.radius?(this.theta=0,this.phi=0):(this.theta=Math.atan2(t,n),this.phi=Math.acos(On.d(e/this.radius,-1,1))),this}clone(){return(new this.constructor).copy(this)}}const ay={type:\\\\\\\"change\\\\\\\"},ly={type:\\\\\\\"start\\\\\\\"},cy={type:\\\\\\\"end\\\\\\\"};class hy extends J.a{constructor(t,e){super(),void 0===e&&console.warn('THREE.OrbitControls: The second parameter \\\\\\\"domElement\\\\\\\" is now mandatory.'),e===document&&console.error('THREE.OrbitControls: \\\\\\\"document\\\\\\\" should not be used as the target \\\\\\\"domElement\\\\\\\". Please use \\\\\\\"renderer.domElement\\\\\\\" instead.'),this.object=t,this.domElement=e,this.domElement.style.touchAction=\\\\\\\"none\\\\\\\",this.enabled=!0,this.target=new p.a,this.minDistance=0,this.maxDistance=1/0,this.minZoom=0,this.maxZoom=1/0,this.minPolarAngle=0,this.maxPolarAngle=Math.PI,this.minAzimuthAngle=-1/0,this.maxAzimuthAngle=1/0,this.enableDamping=!1,this.dampingFactor=.05,this.enableZoom=!0,this.zoomSpeed=1,this.enableRotate=!0,this.rotateSpeed=1,this.enablePan=!0,this.panSpeed=1,this.screenSpacePanning=!0,this.keyPanSpeed=7,this.autoRotate=!1,this.autoRotateSpeed=2,this.enableKeys=!0,this.keyMode=\\\\\\\"pan\\\\\\\",this.keyRotateSpeedVertical=1,this.keyRotateSpeedHorizontal=1,this.keys={LEFT:\\\\\\\"ArrowLeft\\\\\\\",UP:\\\\\\\"ArrowUp\\\\\\\",RIGHT:\\\\\\\"ArrowRight\\\\\\\",BOTTOM:\\\\\\\"ArrowDown\\\\\\\"},this.mouseButtons={LEFT:w.hb.ROTATE,MIDDLE:w.hb.DOLLY,RIGHT:w.hb.PAN},this.touches={ONE:w.Tc.ROTATE,TWO:w.Tc.DOLLY_PAN},this.target0=this.target.clone(),this.position0=this.object.position.clone(),this.zoom0=this.object.zoom,this._domElementKeyEvents=null,this.getPolarAngle=function(){return o.phi},this.getAzimuthalAngle=function(){return o.theta},this.getDistance=function(){return this.object.position.distanceTo(this.target)},this.listenToKeyEvents=function(t){t.addEventListener(\\\\\\\"keydown\\\\\\\",q),this._domElementKeyEvents=t},this.saveState=function(){n.target0.copy(n.target),n.position0.copy(n.object.position),n.zoom0=n.object.zoom},this.reset=function(){n.target.copy(n.target0),n.object.position.copy(n.position0),n.object.zoom=n.zoom0,n.object.updateProjectionMatrix(),n.dispatchEvent(ay),n.update(),s=i.NONE},this.update=function(){const e=new p.a,u=(new hh.a).setFromUnitVectors(t.up,new p.a(0,1,0)),d=u.clone().invert(),_=new p.a,m=new hh.a,f=2*Math.PI;let g=!1;return function(){const t=n.object.position;if(e.copy(t).sub(n.target),e.applyQuaternion(u),o.setFromVector3(e),n.autoRotate&&s===i.NONE&&E(2*Math.PI/60/60*n.autoRotateSpeed),n.enableDamping){const t=a.theta*n.dampingFactor,e=a.phi*n.dampingFactor;tMath.PI&&(p-=f),v<-Math.PI?v+=f:v>Math.PI&&(v-=f),o.theta=p(p+v)/2?Math.max(p,o.theta):Math.min(v,o.theta)),o.phi=Math.max(n.minPolarAngle,Math.min(n.maxPolarAngle,o.phi)),o.makeSafe(),o.radius*=l,o.radius=Math.max(n.minDistance,Math.min(n.maxDistance,o.radius)),!0===n.enableDamping?n.target.addScaledVector(c,n.dampingFactor):n.target.add(c),e.setFromSpherical(o),e.applyQuaternion(d),t.copy(n.target).add(e),n.object.lookAt(n.target),!0===n.enableDamping?(a.theta*=1-n.dampingFactor,a.phi*=1-n.dampingFactor,c.multiplyScalar(1-n.dampingFactor)):(a.set(0,0,0),c.set(0,0,0)),l=1,!!(h||_.distanceToSquared(n.object.position)>r||8*(1-m.dot(n.object.quaternion))>r)&&(n.dispatchEvent(ay),_.copy(n.object.position),m.copy(n.object.quaternion),h=!1,!0)}}(),this.dispose=function(){n.domElement.removeEventListener(\\\\\\\"contextmenu\\\\\\\",X,!1),n.domElement.removeEventListener(\\\\\\\"pointerdown\\\\\\\",G,!1),n.domElement.removeEventListener(\\\\\\\"pointercancel\\\\\\\",j),n.domElement.removeEventListener(\\\\\\\"wheel\\\\\\\",W,!1),n.domElement.ownerDocument.removeEventListener(\\\\\\\"pointermove\\\\\\\",V,!1),n.domElement.ownerDocument.removeEventListener(\\\\\\\"pointerup\\\\\\\",H,!1),null!==n._domElementKeyEvents&&n._domElementKeyEvents.removeEventListener(\\\\\\\"keydown\\\\\\\",q)};const n=this,i={NONE:-1,ROTATE:0,DOLLY:1,PAN:2,TOUCH_ROTATE:3,TOUCH_PAN:4,TOUCH_DOLLY_PAN:5,TOUCH_DOLLY_ROTATE:6};let s=i.NONE;const r=1e-6,o=new oy,a=new oy;let l=1;const c=new p.a;let h=!1;const u=new d.a,_=new d.a,m=new d.a,f=new d.a,g=new d.a,v=new d.a,y=new d.a,x=new d.a,b=new d.a,T=[],A={};function M(){return Math.pow(.95,n.zoomSpeed)}function E(t){a.theta-=t}function S(t){a.phi-=t}const C=function(){const t=new p.a;return function(e,n){t.setFromMatrixColumn(n,0),t.multiplyScalar(-e),c.add(t)}}(),N=function(){const t=new p.a;return function(e,i){!0===n.screenSpacePanning?t.setFromMatrixColumn(i,1):(t.setFromMatrixColumn(i,0),t.crossVectors(n.object.up,t)),t.multiplyScalar(e),c.add(t)}}(),L=function(){const t=new p.a;return function(e,i){const s=n.domElement;if(n.object.isPerspectiveCamera){const r=n.object.position;t.copy(r).sub(n.target);let o=t.length();o*=Math.tan(n.object.fov/2*Math.PI/180),C(2*e*o/s.clientHeight,n.object.matrix),N(2*i*o/s.clientHeight,n.object.matrix)}else n.object.isOrthographicCamera?(C(e*(n.object.right-n.object.left)/n.object.zoom/s.clientWidth,n.object.matrix),N(i*(n.object.top-n.object.bottom)/n.object.zoom/s.clientHeight,n.object.matrix)):(console.warn(\\\\\\\"WARNING: OrbitControls.js encountered an unknown camera type - pan disabled.\\\\\\\"),n.enablePan=!1)}}();function O(t){n.object.isPerspectiveCamera?l/=t:n.object.isOrthographicCamera?(n.object.zoom=Math.max(n.minZoom,Math.min(n.maxZoom,n.object.zoom*t)),n.object.updateProjectionMatrix(),h=!0):(console.warn(\\\\\\\"WARNING: OrbitControls.js encountered an unknown camera type - dolly/zoom disabled.\\\\\\\"),n.enableZoom=!1)}function P(t){n.object.isPerspectiveCamera?l*=t:n.object.isOrthographicCamera?(n.object.zoom=Math.max(n.minZoom,Math.min(n.maxZoom,n.object.zoom/t)),n.object.updateProjectionMatrix(),h=!0):(console.warn(\\\\\\\"WARNING: OrbitControls.js encountered an unknown camera type - dolly/zoom disabled.\\\\\\\"),n.enableZoom=!1)}function R(t){u.set(t.clientX,t.clientY)}function I(t){f.set(t.clientX,t.clientY)}function F(){if(1===T.length)u.set(T[0].pageX,T[0].pageY);else{const t=.5*(T[0].pageX+T[1].pageX),e=.5*(T[0].pageY+T[1].pageY);u.set(t,e)}}function D(){if(1===T.length)f.set(T[0].pageX,T[0].pageY);else{const t=.5*(T[0].pageX+T[1].pageX),e=.5*(T[0].pageY+T[1].pageY);f.set(t,e)}}function B(){const t=T[0].pageX-T[1].pageX,e=T[0].pageY-T[1].pageY,n=Math.sqrt(t*t+e*e);y.set(0,n)}function z(t){if(1==T.length)_.set(t.pageX,t.pageY);else{const e=J(t),n=.5*(t.pageX+e.x),i=.5*(t.pageY+e.y);_.set(n,i)}m.subVectors(_,u).multiplyScalar(n.rotateSpeed);const e=n.domElement;E(2*Math.PI*m.x/e.clientHeight),S(2*Math.PI*m.y/e.clientHeight),u.copy(_)}function k(t){if(1===T.length)g.set(t.pageX,t.pageY);else{const e=J(t),n=.5*(t.pageX+e.x),i=.5*(t.pageY+e.y);g.set(n,i)}v.subVectors(g,f).multiplyScalar(n.panSpeed),L(v.x,v.y),f.copy(g)}function U(t){const e=J(t),i=t.pageX-e.x,s=t.pageY-e.y,r=Math.sqrt(i*i+s*s);x.set(0,r),b.set(0,Math.pow(x.y/y.y,n.zoomSpeed)),O(b.y),y.copy(x)}function G(t){!1!==n.enabled&&(0===T.length&&(n.domElement.setPointerCapture(t.pointerId),n.domElement.ownerDocument.addEventListener(\\\\\\\"pointermove\\\\\\\",V),n.domElement.ownerDocument.addEventListener(\\\\\\\"pointerup\\\\\\\",H)),function(t){T.push(t)}(t),\\\\\\\"touch\\\\\\\"===t.pointerType?function(t){switch($(t),T.length){case 1:switch(n.touches.ONE){case w.Tc.ROTATE:if(!1===n.enableRotate)return;F(),s=i.TOUCH_ROTATE;break;case w.Tc.PAN:if(!1===n.enablePan)return;D(),s=i.TOUCH_PAN;break;default:s=i.NONE}break;case 2:switch(n.touches.TWO){case w.Tc.DOLLY_PAN:if(!1===n.enableZoom&&!1===n.enablePan)return;n.enableZoom&&B(),n.enablePan&&D(),s=i.TOUCH_DOLLY_PAN;break;case w.Tc.DOLLY_ROTATE:if(!1===n.enableZoom&&!1===n.enableRotate)return;n.enableZoom&&B(),n.enableRotate&&F(),s=i.TOUCH_DOLLY_ROTATE;break;default:s=i.NONE}break;default:s=i.NONE}s!==i.NONE&&n.dispatchEvent(ly)}(t):function(t){let e;switch(t.button){case 0:e=n.mouseButtons.LEFT;break;case 1:e=n.mouseButtons.MIDDLE;break;case 2:e=n.mouseButtons.RIGHT;break;default:e=-1}switch(e){case w.hb.DOLLY:if(!1===n.enableZoom)return;!function(t){y.set(t.clientX,t.clientY)}(t),s=i.DOLLY;break;case w.hb.ROTATE:if(t.ctrlKey||t.metaKey||t.shiftKey){if(!1===n.enablePan)return;I(t),s=i.PAN}else{if(!1===n.enableRotate)return;R(t),s=i.ROTATE}break;case w.hb.PAN:if(t.ctrlKey||t.metaKey||t.shiftKey){if(!1===n.enableRotate)return;R(t),s=i.ROTATE}else{if(!1===n.enablePan)return;I(t),s=i.PAN}break;default:s=i.NONE}s!==i.NONE&&n.dispatchEvent(ly)}(t))}function V(t){!1!==n.enabled&&(\\\\\\\"touch\\\\\\\"===t.pointerType?function(t){switch($(t),s){case i.TOUCH_ROTATE:if(!1===n.enableRotate)return;z(t),n.update();break;case i.TOUCH_PAN:if(!1===n.enablePan)return;k(t),n.update();break;case i.TOUCH_DOLLY_PAN:if(!1===n.enableZoom&&!1===n.enablePan)return;!function(t){n.enableZoom&&U(t),n.enablePan&&k(t)}(t),n.update();break;case i.TOUCH_DOLLY_ROTATE:if(!1===n.enableZoom&&!1===n.enableRotate)return;!function(t){n.enableZoom&&U(t),n.enableRotate&&z(t)}(t),n.update();break;default:s=i.NONE}}(t):function(t){if(!1===n.enabled)return;switch(s){case i.ROTATE:if(!1===n.enableRotate)return;!function(t){_.set(t.clientX,t.clientY),m.subVectors(_,u).multiplyScalar(n.rotateSpeed);var e=n.domElement;E(2*Math.PI*m.x/e.clientHeight),S(2*Math.PI*m.y/e.clientHeight),u.copy(_),n.update()}(t);break;case i.DOLLY:if(!1===n.enableZoom)return;!function(t){x.set(t.clientX,t.clientY),b.subVectors(x,y),b.y>0?O(M()):b.y<0&&P(M()),y.copy(x),n.update()}(t);break;case i.PAN:if(!1===n.enablePan)return;!function(t){g.set(t.clientX,t.clientY),v.subVectors(g,f).multiplyScalar(n.panSpeed),L(v.x,v.y),f.copy(g),n.update()}(t)}}(t))}function H(t){!1!==n.enabled&&(t.pointerType,n.dispatchEvent(cy),s=i.NONE,Y(t),0===T.length&&(n.domElement.releasePointerCapture(t.pointerId),n.domElement.ownerDocument.removeEventListener(\\\\\\\"pointermove\\\\\\\",V),n.domElement.ownerDocument.removeEventListener(\\\\\\\"pointerup\\\\\\\",H)))}function j(t){Y(t)}function W(t){!1===n.enabled||!1===n.enableZoom||s!==i.NONE&&s!==i.ROTATE||(t.preventDefault(),n.dispatchEvent(ly),function(t){t.deltaY<0?P(M()):t.deltaY>0&&O(M()),n.update()}(t),n.dispatchEvent(cy))}function q(t){!1!==n.enabled&&!1!==n.enablePan&&function(t){let e=!1;if(\\\\\\\"pan\\\\\\\"==n.keyMode)switch(t.code){case n.keys.UP:L(0,n.keyPanSpeed),e=!0;break;case n.keys.BOTTOM:L(0,-n.keyPanSpeed),e=!0;break;case n.keys.LEFT:L(n.keyPanSpeed,0),e=!0;break;case n.keys.RIGHT:L(-n.keyPanSpeed,0),e=!0}else switch(t.code){case n.keys.UP:S(n.keyRotateSpeedVertical),e=!0;break;case n.keys.BOTTOM:S(-n.keyRotateSpeedVertical),e=!0;break;case n.keys.LEFT:E(n.keyRotateSpeedHorizontal),e=!0;break;case n.keys.RIGHT:E(-n.keyRotateSpeedHorizontal),e=!0}e&&(t.preventDefault(),n.update())}(t)}function X(t){!1!==n.enabled&&t.preventDefault()}function Y(t){delete A[t.pointerId];for(let e=0;e{gy.PARAM_CALLBACK_update_target(t)}}),this.enableKeys=ha.BOOLEAN(0),this.keysMode=ha.INTEGER(my.indexOf(_y.PAN),{visibleIf:{enableKeys:1},menu:{entries:my.map(((t,e)=>({name:t,value:e})))}}),this.keysPanSpeed=ha.FLOAT(7,{range:[0,10],rangeLocked:[!1,!1],visibleIf:{enableKeys:1,keysMode:my.indexOf(_y.PAN)}}),this.keysRotateSpeedVertical=ha.FLOAT(1,{range:[0,1],rangeLocked:[!1,!1],visibleIf:{enableKeys:1,keysMode:my.indexOf(_y.ROTATE)}}),this.keysRotateSpeedHorizontal=ha.FLOAT(1,{range:[0,1],rangeLocked:[!1,!1],visibleIf:{enableKeys:1,keysMode:my.indexOf(_y.ROTATE)}})}};class gy extends Jv{constructor(){super(...arguments),this.paramsConfig=fy,this._controls_by_element_id=new Map,this._target_array=[0,0,0]}static type(){return _s.ORBIT}endEventName(){return\\\\\\\"end\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new ta(dy,Ko.BASE),new ta(py,Ko.BASE),new ta(\\\\\\\"end\\\\\\\",Ko.BASE)])}async createControlsInstance(t,e){const n=new hy(t,e);return n.addEventListener(\\\\\\\"end\\\\\\\",(()=>{this._on_controls_end(n)})),this._controls_by_element_id.set(e.id,n),this._bind_listeners_to_controls_instance(n),n}_bind_listeners_to_controls_instance(t){t.addEventListener(\\\\\\\"start\\\\\\\",(()=>{this.dispatchEventToOutput(dy,{})})),t.addEventListener(\\\\\\\"change\\\\\\\",(()=>{this.dispatchEventToOutput(py,{})})),t.addEventListener(\\\\\\\"end\\\\\\\",(()=>{this.dispatchEventToOutput(\\\\\\\"end\\\\\\\",{})}))}setupControls(t){t.enabled=this.pv.enabled,t.enablePan=this.pv.allowPan,t.enableRotate=this.pv.allowRotate,t.enableZoom=this.pv.allowZoom,t.enableDamping=this.pv.tdamping,t.dampingFactor=this.pv.damping,t.rotateSpeed=this.pv.rotateSpeed,t.screenSpacePanning=this.pv.screenSpacePanning,t.minDistance=this.pv.minDistance,t.maxDistance=this.pv.maxDistance,this._set_azimuth_angle(t),t.minPolarAngle=this.pv.polarAngleRange.x,t.maxPolarAngle=this.pv.polarAngleRange.y,t.target.copy(this.pv.target),t.enabled&&t.update(),t.enableKeys=this.pv.enableKeys,t.enableKeys&&(t.keyMode=my[this.pv.keysMode],t.keyRotateSpeedVertical=this.pv.keysRotateSpeedVertical,t.keyRotateSpeedHorizontal=this.pv.keysRotateSpeedHorizontal,t.keyPanSpeed=this.pv.keysPanSpeed)}_set_azimuth_angle(t){this.pv.limitAzimuthAngle?(t.minAzimuthAngle=this.pv.azimuthAngleRange.x,t.maxAzimuthAngle=this.pv.azimuthAngleRange.y):(t.minAzimuthAngle=1/0,t.maxAzimuthAngle=1/0)}updateRequired(){return this.pv.tdamping}_on_controls_end(t){this.pv.allowPan&&(t.target.toArray(this._target_array),this.p.target.set(this._target_array))}static PARAM_CALLBACK_update_target(t){t._update_target()}_update_target(){const t=this.pv.target;this._controls_by_element_id.forEach(((e,n)=>{const i=e.target;i.equals(t)||(i.copy(t),e.update())}))}disposeControlsForHtmlElementId(t){this._controls_by_element_id.get(t)&&this._controls_by_element_id.delete(t)}}class vy extends gy{static type(){return _s.MAP}async create_controls_instance(t,e){const n=new uy(t,e);return this._bind_listeners_to_controls_instance(n),n}}const yy=new class extends ua{constructor(){super(...arguments),this.delay=ha.INTEGER(1e3,{range:[0,1e3],rangeLocked:[!0,!1]})}};class xy extends Va{constructor(){super(...arguments),this.paramsConfig=yy}static type(){return\\\\\\\"delay\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(\\\\\\\"in\\\\\\\",Ko.BASE,this._process_input.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(\\\\\\\"out\\\\\\\",Ko.BASE)])}_process_input(t){setTimeout((()=>{this.dispatchEventToOutput(\\\\\\\"out\\\\\\\",t)}),this.pv.delay)}}const by={type:\\\\\\\"change\\\\\\\"},wy={type:\\\\\\\"lock\\\\\\\"},Ty={type:\\\\\\\"unlock\\\\\\\"},Ay=Math.PI/2,My=new p.a,Ey=new oy;class Sy extends J.a{constructor(t,e,n){super(),this.camera=t,this.domElement=e,this.player=n,this.isLocked=!1,this.minPolarAngle=0,this.maxPolarAngle=Math.PI,this.rotateSpeed=1,this.euler=new Zv.a(0,0,0,\\\\\\\"YXZ\\\\\\\"),this.boundMethods={onMouseMove:this.onMouseMove.bind(this),onPointerlockChange:this.onPointerlockChange.bind(this),onPointerlockError:this.onPointerlockError.bind(this)},this._azimuthalAngle=0,this.connect()}onMouseMove(t){if(!1!==this.isLocked){var e=t.movementX||t.mozMovementX||t.webkitMovementX||0,n=t.movementY||t.mozMovementY||t.webkitMovementY||0;this.euler.setFromQuaternion(this.camera.quaternion),this.euler.y-=.002*e*this.rotateSpeed,this.euler.x-=.002*n*this.rotateSpeed,this.euler.x=Math.max(Ay-this.maxPolarAngle,Math.min(Ay-this.minPolarAngle,this.euler.x)),this.camera.quaternion.setFromEuler(this.euler),this._computeAzimuthalAngle(),this.dispatchEvent(by)}}_computeAzimuthalAngle(){this.camera.updateMatrixWorld(),My.set(0,0,1),this.camera.localToWorld(My),My.sub(this.camera.position),Ey.setFromVector3(My),this._azimuthalAngle=Ey.theta}onPointerlockChange(){this.domElement.ownerDocument.pointerLockElement===this.domElement?(this.dispatchEvent(wy),this.isLocked=!0):(this.dispatchEvent(Ty),this.isLocked=!1)}onPointerlockError(){console.error(\\\\\\\"THREE.PointerLockControls: Unable to use Pointer Lock API (Note that you need to wait for 2 seconds to lock the pointer after having just unlocked it)\\\\\\\")}connect(){this.domElement.ownerDocument.addEventListener(\\\\\\\"mousemove\\\\\\\",this.boundMethods.onMouseMove),this.domElement.ownerDocument.addEventListener(\\\\\\\"pointerlockchange\\\\\\\",this.boundMethods.onPointerlockChange),this.domElement.ownerDocument.addEventListener(\\\\\\\"pointerlockerror\\\\\\\",this.boundMethods.onPointerlockError)}disconnect(){this.domElement.ownerDocument.removeEventListener(\\\\\\\"mousemove\\\\\\\",this.boundMethods.onMouseMove),this.domElement.ownerDocument.removeEventListener(\\\\\\\"pointerlockchange\\\\\\\",this.boundMethods.onPointerlockChange),this.domElement.ownerDocument.removeEventListener(\\\\\\\"pointerlockerror\\\\\\\",this.boundMethods.onPointerlockError)}dispose(){this.disconnect()}getObject(){return this.camera}lock(){this.domElement.requestPointerLock()}unlock(){this.domElement.ownerDocument.exitPointerLock()}update(t){this.player&&(this.player.setAzimuthalAngle(this._azimuthalAngle),this.player.update(t))}}var Cy=n(16);const Ny=new p.a,Ly=new p.a;class Oy{constructor(t=new p.a,e=new p.a){this.start=t,this.end=e}set(t,e){return this.start.copy(t),this.end.copy(e),this}copy(t){return this.start.copy(t.start),this.end.copy(t.end),this}getCenter(t){return t.addVectors(this.start,this.end).multiplyScalar(.5)}delta(t){return t.subVectors(this.end,this.start)}distanceSq(){return this.start.distanceToSquared(this.end)}distance(){return this.start.distanceTo(this.end)}at(t,e){return this.delta(e).multiplyScalar(t).add(this.start)}closestPointToPointParameter(t,e){Ny.subVectors(t,this.start),Ly.subVectors(this.end,this.start);const n=Ly.dot(Ly);let i=Ly.dot(Ny)/n;return e&&(i=On.d(i,0,1)),i}closestPointToPoint(t,e,n){const i=this.closestPointToPointParameter(t,e);return this.delta(n).multiplyScalar(i).add(this.start)}applyMatrix4(t){return this.start.applyMatrix4(t),this.end.applyMatrix4(t),this}equals(t){return t.start.equals(this.start)&&t.end.equals(this.end)}clone(){return(new this.constructor).copy(this)}}const Py=new p.a;function Ry(t,e,n,i,s,r){const o=2*Math.PI*s/4,a=Math.max(r-2*s,0),l=Math.PI/4;Py.copy(e),Py[i]=0,Py.normalize();const c=.5*o/(o+a),h=1-Py.angleTo(t)/l;if(1===Math.sign(Py[n]))return h*c;return a/(o+a)+c+c*(1-h)}class Iy extends N{constructor(t=1,e=1,n=1,i=2,s=.1){if(i=2*i+1,s=Math.min(t/2,e/2,n/2,s),super(1,1,1,i,i,i),1===i)return;const r=this.toNonIndexed();this.index=null,this.attributes.position=r.attributes.position,this.attributes.normal=r.attributes.normal,this.attributes.uv=r.attributes.uv;const o=new p.a,a=new p.a,l=new p.a(t,e,n).divideScalar(2).subScalar(s),c=this.attributes.position.array,h=this.attributes.normal.array,u=this.attributes.uv.array,d=c.length/6,_=new p.a,m=.5/i;for(let i=0,r=0;ithis.object.position.y<-25,this.object=t.object,this.object.matrixAutoUpdate=!0,this.collider=t.collider,t.meshName&&(this._mesh=new B.a,this._mesh.geometry=Fy({radius:this.capsuleInfo.radius,height:1}),this._mesh.name=t.meshName,this._mesh.receiveShadow=!0,this._mesh.castShadow=!0)}setCollider(t){this.collider=t}setCapsule(t){this.capsuleInfo.radius=t.radius,this.capsuleInfo.segment.end.y=-t.height,this._mesh&&(this._mesh.geometry=Fy(t))}setUsePlayerMesh(t){t?(this._mesh=this._mesh||this._createMesh(),this.object.add(this._mesh)):this._mesh&&this.object.remove(this._mesh)}_createMesh(){const t=new B.a;return t.geometry=Fy({radius:this.capsuleInfo.radius,height:1}),t.name=this._meshName||\\\\\\\"defaultPlayerMeshName\\\\\\\",t.receiveShadow=!0,t.castShadow=!0,t}setMaterial(t){this._mesh&&(this._mesh.material=t)}reset(){this.stop(),this.object.position.copy(this.startPosition),Hy.copy(this.startRotation).multiplyScalar(On.a),this.object.rotation.setFromVector3(Hy)}stop(){this._pressed.forward=!1,this._pressed.backward=!1,this._pressed.left=!1,this._pressed.right=!1,this._running=!1}setResetRequiredCallback(t){this._resetRequiredCallback=t}setAzimuthalAngle(t){this._azimuthalAngle=t}update(t){const e=Math.min(t,.1);for(let t=0;tt.intersectsBox(Uy),intersectsTriangle:t=>{const e=zy,n=ky,s=t.closestPointToSegment(Vy,e,n);if(sMath.abs(t*this._velocity.y*.25);const o=Math.max(0,r.length()-1e-5);r.normalize().multiplyScalar(o),this.object.position.add(r),this._onGround?this._velocity.set(0,0,0):(r.normalize(),this._velocity.addScaledVector(r,-r.dot(this._velocity))),this._resetRequiredCallback()&&this.reset()}setForward(t){this._pressed.forward=t}setBackward(t){this._pressed.backward=t}setLeft(t){this._pressed.left=t}setRight(t){this._pressed.right=t}jump(){this._onGround&&this.jumpAllowed&&(this._velocity.y=this.jumpStrength)}setRun(t){t?this._onGround&&this.runAllowed&&(this._running=!0):this._running=!1}running(){return this._running}}function Wy(t){t.preventDefault()}class qy{constructor(t){this.player=t,this._bounds={keydown:this._onKeyDown.bind(this),keyup:this._onKeyUp.bind(this)}}_onKeyDown(t){if(!t.ctrlKey)switch(t.code){case\\\\\\\"ArrowUp\\\\\\\":case\\\\\\\"KeyW\\\\\\\":this.player.setForward(!0),Wy(t);break;case\\\\\\\"ArrowDown\\\\\\\":case\\\\\\\"KeyS\\\\\\\":this.player.setBackward(!0),Wy(t);break;case\\\\\\\"ArrowRight\\\\\\\":case\\\\\\\"KeyD\\\\\\\":this.player.setRight(!0),Wy(t);break;case\\\\\\\"ArrowLeft\\\\\\\":case\\\\\\\"KeyA\\\\\\\":this.player.setLeft(!0),Wy(t);break;case\\\\\\\"Space\\\\\\\":this.player.jump(),Wy(t);break;case\\\\\\\"ShiftLeft\\\\\\\":case\\\\\\\"ShiftRight\\\\\\\":this.player.setRun(!0),Wy(t)}}_onKeyUp(t){switch(t.code){case\\\\\\\"ArrowUp\\\\\\\":case\\\\\\\"KeyW\\\\\\\":this.player.setForward(!1);break;case\\\\\\\"ArrowDown\\\\\\\":case\\\\\\\"KeyS\\\\\\\":this.player.setBackward(!1);break;case\\\\\\\"ArrowRight\\\\\\\":case\\\\\\\"KeyD\\\\\\\":this.player.setRight(!1);break;case\\\\\\\"ArrowLeft\\\\\\\":case\\\\\\\"KeyA\\\\\\\":this.player.setLeft(!1);break;case\\\\\\\"ShiftLeft\\\\\\\":case\\\\\\\"ShiftRight\\\\\\\":this.player.setRun(!1),Wy(t)}}addEvents(){document.addEventListener(\\\\\\\"keydown\\\\\\\",this._bounds.keydown),document.addEventListener(\\\\\\\"keyup\\\\\\\",this._bounds.keyup)}removeEvents(){document.removeEventListener(\\\\\\\"keydown\\\\\\\",this._bounds.keydown),document.removeEventListener(\\\\\\\"keyup\\\\\\\",this._bounds.keyup)}}Xy=ua;var Xy;class Yy extends Va{static PARAM_CALLBACK_updateCollider(t){}}class $y{constructor(t){this.node=t}_colliderNodeGraphNode(){return this.__colliderNodeGraphNode=this.__colliderNodeGraphNode||new Mi(this.node.scene(),\\\\\\\"colliderGraphNode\\\\\\\")}async getCollider(){var t;const e=this.node.pv.colliderObject.nodeWithContext(ts.SOP);if(!e)return void this.node.states.error.set(\\\\\\\"collider node not found\\\\\\\");(null===(t=this._colliderNode)||void 0===t?void 0:t.graphNodeId())!=e.graphNodeId()&&(this._colliderNode&&this._colliderNodeGraphNode().removeGraphInput(this._colliderNode),this._colliderNodeGraphNode().addGraphInput(e),this._colliderNodeGraphNode().addPostDirtyHook(\\\\\\\"onColliderDirty\\\\\\\",(()=>{this.updateCollider()})),this._colliderNode=e);const n=(await e.compute()).coreContent();if(!n)return void this.node.states.error.set(\\\\\\\"invalid collider node\\\\\\\");return n.objects()[0]}async updateCollider(){var t;const e=await this.getCollider();e?null===(t=this.node.player())||void 0===t||t.setCollider(e):this.node.states.error.set(\\\\\\\"invalid collider\\\\\\\")}}const Jy=\\\\\\\"lock\\\\\\\",Zy=\\\\\\\"change\\\\\\\",Qy=\\\\\\\"unlock\\\\\\\";function Ky(){return{cook:!1,callback:t=>{ex.PARAM_CALLBACK_updatePlayerParams(t)}}}const tx=new class extends ua{constructor(){super(...arguments),this.main=ha.FOLDER(),this.colliderObject=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.SOP},dependentOnFoundNode:!1,callback:t=>{ex.PARAM_CALLBACK_updateCollider(t)}}),this.lock=ha.BUTTON(null,{callback:t=>{ex.PARAM_CALLBACK_lockControls(t)}}),this.unlock=ha.BUTTON(null,{callback:t=>{ex.PARAM_CALLBACK_unlockControls(t)}}),this.capsuleRadius=ha.FLOAT(.5,{range:[0,1],rangeLocked:[!0,!1],...Ky()}),this.capsuleHeight=ha.FLOAT(1,{range:[0,2],rangeLocked:[!0,!1],...Ky()}),this.physics=ha.FOLDER(),this.physicsSteps=ha.INTEGER(5,{range:[1,10],rangeLocked:[!0,!1],...Ky()}),this.gravity=ha.VECTOR3([0,-30,0],{...Ky()}),this.translateSpeed=ha.FLOAT(1,{range:[0,10],rangeLocked:[!0,!1],...Ky()}),this.rotateSpeed=ha.FLOAT(1,{range:[0,10],rangeLocked:[!0,!1]}),this.jumpAllowed=ha.BOOLEAN(!0,{...Ky()}),this.jumpStrength=ha.FLOAT(10,{range:[0,100],rangeLocked:[!0,!1],...Ky()}),this.runAllowed=ha.BOOLEAN(!0,{...Ky()}),this.runSpeedMult=ha.FLOAT(2,{range:[0,10],rangeLocked:[!0,!1],...Ky()}),this.updateCollider=ha.BUTTON(null,{callback:t=>{ex.PARAM_CALLBACK_updateCollider(t)}}),this.init=ha.FOLDER(),this.startPosition=ha.VECTOR3([0,2,0],{...Ky()}),this.startRotation=ha.VECTOR3([0,0,0],{...Ky()}),this.reset=ha.BUTTON(null,{callback:t=>{ex.PARAM_CALLBACK_resetPlayer(t)}}),this.minPolarAngle=ha.FLOAT(0,{range:[0,Math.PI],rangeLocked:[!0,!0]}),this.maxPolarAngle=ha.FLOAT(\\\\\\\"$PI\\\\\\\",{range:[0,Math.PI],rangeLocked:[!0,!0]})}};class ex extends Jv{constructor(){super(...arguments),this.paramsConfig=tx,this._controls_by_element_id=new Map}static type(){return _s.FIRST_PERSON}endEventName(){return\\\\\\\"unlock\\\\\\\"}collisionController(){return this._collisionController=this._collisionController||new $y(this)}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(Jy,Ko.BASE,this.lockControls.bind(this)),new ta(ex.INPUT_UPDATE_COLLIDER,Ko.BASE,this._updateCollider.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(Jy,Ko.BASE),new ta(Zy,Ko.BASE),new ta(Qy,Ko.BASE)])}async createControlsInstance(t,e){await this._initPlayer(t);const n=new Sy(t,e,this._player);return this._controls_by_element_id.set(e.id,n),this._bind_listeners_to_controls_instance(n),n}async _initPlayer(t){this._player=this._player||await this._createPlayer(t),this._player&&(this._updatePlayerParams(),this._player.reset())}player(){return this._player}async _updatePlayerParams(){this._player&&(this._player.startPosition.copy(this.pv.startPosition),this._player.startRotation.copy(this.pv.startRotation),this._player.physicsSteps=this.pv.physicsSteps,this._player.jumpAllowed=this.pv.jumpAllowed,this._player.jumpStrength=this.pv.jumpStrength,this._player.runAllowed=this.pv.runAllowed,this._player.runSpeedMult=this.pv.runSpeedMult,this._player.gravity.copy(this.pv.gravity),this._player.speed=this.pv.translateSpeed,this._player.setCapsule({radius:this.pv.capsuleRadius,height:this.pv.capsuleHeight}))}async _createPlayer(t){const e=t,n=await this.collisionController().getCollider();if(!n)return void this.states.error.set(\\\\\\\"invalid collider\\\\\\\");return new jy({object:e,collider:n})}_resetPlayer(){var t;null===(t=this._player)||void 0===t||t.reset()}async _updateCollider(){await this.collisionController().updateCollider()}_bind_listeners_to_controls_instance(t){t.addEventListener(Jy,(()=>{this.dispatchEventToOutput(Jy,{})})),t.addEventListener(Zy,(()=>{this.dispatchEventToOutput(Zy,{})})),t.addEventListener(Qy,(()=>{this.dispatchEventToOutput(Qy,{})}))}updateRequired(){return!0}setupControls(t){t.minPolarAngle=this.pv.minPolarAngle,t.maxPolarAngle=this.pv.maxPolarAngle,t.rotateSpeed=this.pv.rotateSpeed}disposeControlsForHtmlElementId(t){const e=this._controls_by_element_id.get(t);e&&(e.dispose(),this._controls_by_element_id.delete(t))}unlockControls(){const t=this._firstControls();t&&t.unlock()}lockControls(){const t=this._firstControls();if(t){if(this._player){this._corePlayerKeyEvents=this._corePlayerKeyEvents||new qy(this._player),this._corePlayerKeyEvents.addEvents();const e=()=>{var n,i;t&&t.domElement.ownerDocument.pointerLockElement!=t.domElement&&(t.domElement.ownerDocument.removeEventListener(\\\\\\\"pointerlockchange\\\\\\\",e),null===(n=this._corePlayerKeyEvents)||void 0===n||n.removeEvents(),null===(i=this._player)||void 0===i||i.stop())};t.domElement.ownerDocument.addEventListener(\\\\\\\"pointerlockchange\\\\\\\",e)}t.lock()}}_firstControls(){let t;return this._controls_by_element_id.forEach(((e,n)=>{t=t||e})),t}static PARAM_CALLBACK_lockControls(t){t.lockControls()}static PARAM_CALLBACK_unlockControls(t){t.unlockControls()}static PARAM_CALLBACK_updateCollider(t){t._updateCollider()}static PARAM_CALLBACK_updatePlayerParams(t){t._updatePlayerParams()}static PARAM_CALLBACK_resetPlayer(t){t._resetPlayer()}}var nx,ix;ex.INPUT_UPDATE_COLLIDER=\\\\\\\"updateCollider\\\\\\\",function(t){t.TRIGGER=\\\\\\\"trigger\\\\\\\",t.RESET=\\\\\\\"reset\\\\\\\"}(nx||(nx={})),function(t){t.OUT=\\\\\\\"out\\\\\\\",t.LAST=\\\\\\\"last\\\\\\\"}(ix||(ix={}));const sx=new class extends ua{constructor(){super(...arguments),this.maxCount=ha.INTEGER(5,{range:[0,10],rangeLocked:[!0,!1]}),this.reset=ha.BUTTON(null,{callback:t=>{rx.PARAM_CALLBACK_reset(t)}})}};class rx extends Va{constructor(){super(...arguments),this.paramsConfig=sx,this._process_count=0,this._last_dispatched=!1}static type(){return\\\\\\\"limit\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(nx.TRIGGER,Ko.BASE,this.processEventTrigger.bind(this)),new ta(nx.RESET,Ko.BASE,this.process_event_reset.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(ix.OUT,Ko.BASE),new ta(ix.LAST,Ko.BASE)])}processEvent(t){}processEventTrigger(t){this._process_count(t.preventDefault(),!1);class cx{static disableContextMenu(){document.addEventListener(\\\\\\\"contextmenu\\\\\\\",lx)}static reEstablishContextMenu(){document.removeEventListener(\\\\\\\"contextmenu\\\\\\\",lx)}}const hx=100,ux=301,dx=302,px=303,_x=304,mx=306,fx=307,gx=1e3,vx=1001,yx=1002,xx=1003,bx=1004,wx=1005,Tx=1006,Ax=1007,Mx=1008,Ex=1009,Sx=1012,Cx=1014,Nx=1015,Lx=1016,Ox=1020,Px=1022,Rx=1023,Ix=1026,Fx=1027,Dx=2300,Bx=2301,zx=2302,kx=2400,Ux=2401,Gx=2402,Vx=2500,Hx=3e3,jx=3001,Wx=3007,qx=3002,Xx=7680,Yx=35044,$x=35048,Jx=\\\\\\\"300 es\\\\\\\";class Zx{addEventListener(t,e){void 0===this._listeners&&(this._listeners={});const n=this._listeners;void 0===n[t]&&(n[t]=[]),-1===n[t].indexOf(e)&&n[t].push(e)}hasEventListener(t,e){if(void 0===this._listeners)return!1;const n=this._listeners;return void 0!==n[t]&&-1!==n[t].indexOf(e)}removeEventListener(t,e){if(void 0===this._listeners)return;const n=this._listeners[t];if(void 0!==n){const t=n.indexOf(e);-1!==t&&n.splice(t,1)}}dispatchEvent(t){if(void 0===this._listeners)return;const e=this._listeners[t.type];if(void 0!==e){t.target=this;const n=e.slice(0);for(let e=0,i=n.length;e>8&255]+eb[t>>16&255]+eb[t>>24&255]+\\\\\\\"-\\\\\\\"+eb[255&e]+eb[e>>8&255]+\\\\\\\"-\\\\\\\"+eb[e>>16&15|64]+eb[e>>24&255]+\\\\\\\"-\\\\\\\"+eb[63&n|128]+eb[n>>8&255]+\\\\\\\"-\\\\\\\"+eb[n>>16&255]+eb[n>>24&255]+eb[255&i]+eb[i>>8&255]+eb[i>>16&255]+eb[i>>24&255]).toUpperCase()}function sb(t,e,n){return Math.max(e,Math.min(n,t))}function rb(t,e){return(t%e+e)%e}function ob(t,e,n){return(1-n)*t+n*e}function ab(t){return 0==(t&t-1)&&0!==t}function lb(t){return Math.pow(2,Math.ceil(Math.log(t)/Math.LN2))}function cb(t){return Math.pow(2,Math.floor(Math.log(t)/Math.LN2))}var hb=Object.freeze({__proto__:null,DEG2RAD:Kx,RAD2DEG:tb,generateUUID:ib,clamp:sb,euclideanModulo:rb,mapLinear:function(t,e,n,i,s){return i+(t-e)*(s-i)/(n-e)},inverseLerp:function(t,e,n){return t!==e?(n-t)/(e-t):0},lerp:ob,damp:function(t,e,n,i){return ob(t,e,1-Math.exp(-n*i))},pingpong:function(t,e=1){return e-Math.abs(rb(t,2*e)-e)},smoothstep:function(t,e,n){return t<=e?0:t>=n?1:(t=(t-e)/(n-e))*t*(3-2*t)},smootherstep:function(t,e,n){return t<=e?0:t>=n?1:(t=(t-e)/(n-e))*t*t*(t*(6*t-15)+10)},randInt:function(t,e){return t+Math.floor(Math.random()*(e-t+1))},randFloat:function(t,e){return t+Math.random()*(e-t)},randFloatSpread:function(t){return t*(.5-Math.random())},seededRandom:function(t){return void 0!==t&&(Qx=t%2147483647),Qx=16807*Qx%2147483647,(Qx-1)/2147483646},degToRad:function(t){return t*Kx},radToDeg:function(t){return t*tb},isPowerOfTwo:ab,ceilPowerOfTwo:lb,floorPowerOfTwo:cb,setQuaternionFromProperEuler:function(t,e,n,i,s){const r=Math.cos,o=Math.sin,a=r(n/2),l=o(n/2),c=r((e+i)/2),h=o((e+i)/2),u=r((e-i)/2),d=o((e-i)/2),p=r((i-e)/2),_=o((i-e)/2);switch(s){case\\\\\\\"XYX\\\\\\\":t.set(a*h,l*u,l*d,a*c);break;case\\\\\\\"YZY\\\\\\\":t.set(l*d,a*h,l*u,a*c);break;case\\\\\\\"ZXZ\\\\\\\":t.set(l*u,l*d,a*h,a*c);break;case\\\\\\\"XZX\\\\\\\":t.set(a*h,l*_,l*p,a*c);break;case\\\\\\\"YXY\\\\\\\":t.set(l*p,a*h,l*_,a*c);break;case\\\\\\\"ZYZ\\\\\\\":t.set(l*_,l*p,a*h,a*c);break;default:console.warn(\\\\\\\"THREE.MathUtils: .setQuaternionFromProperEuler() encountered an unknown order: \\\\\\\"+s)}}});class ub{constructor(t=0,e=0){this.x=t,this.y=e}get width(){return this.x}set width(t){this.x=t}get height(){return this.y}set height(t){this.y=t}set(t,e){return this.x=t,this.y=e,this}setScalar(t){return this.x=t,this.y=t,this}setX(t){return this.x=t,this}setY(t){return this.y=t,this}setComponent(t,e){switch(t){case 0:this.x=e;break;case 1:this.y=e;break;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}return this}getComponent(t){switch(t){case 0:return this.x;case 1:return this.y;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}}clone(){return new this.constructor(this.x,this.y)}copy(t){return this.x=t.x,this.y=t.y,this}add(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector2: .add() now only accepts one argument. Use .addVectors( a, b ) instead.\\\\\\\"),this.addVectors(t,e)):(this.x+=t.x,this.y+=t.y,this)}addScalar(t){return this.x+=t,this.y+=t,this}addVectors(t,e){return this.x=t.x+e.x,this.y=t.y+e.y,this}addScaledVector(t,e){return this.x+=t.x*e,this.y+=t.y*e,this}sub(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector2: .sub() now only accepts one argument. Use .subVectors( a, b ) instead.\\\\\\\"),this.subVectors(t,e)):(this.x-=t.x,this.y-=t.y,this)}subScalar(t){return this.x-=t,this.y-=t,this}subVectors(t,e){return this.x=t.x-e.x,this.y=t.y-e.y,this}multiply(t){return this.x*=t.x,this.y*=t.y,this}multiplyScalar(t){return this.x*=t,this.y*=t,this}divide(t){return this.x/=t.x,this.y/=t.y,this}divideScalar(t){return this.multiplyScalar(1/t)}applyMatrix3(t){const e=this.x,n=this.y,i=t.elements;return this.x=i[0]*e+i[3]*n+i[6],this.y=i[1]*e+i[4]*n+i[7],this}min(t){return this.x=Math.min(this.x,t.x),this.y=Math.min(this.y,t.y),this}max(t){return this.x=Math.max(this.x,t.x),this.y=Math.max(this.y,t.y),this}clamp(t,e){return this.x=Math.max(t.x,Math.min(e.x,this.x)),this.y=Math.max(t.y,Math.min(e.y,this.y)),this}clampScalar(t,e){return this.x=Math.max(t,Math.min(e,this.x)),this.y=Math.max(t,Math.min(e,this.y)),this}clampLength(t,e){const n=this.length();return this.divideScalar(n||1).multiplyScalar(Math.max(t,Math.min(e,n)))}floor(){return this.x=Math.floor(this.x),this.y=Math.floor(this.y),this}ceil(){return this.x=Math.ceil(this.x),this.y=Math.ceil(this.y),this}round(){return this.x=Math.round(this.x),this.y=Math.round(this.y),this}roundToZero(){return this.x=this.x<0?Math.ceil(this.x):Math.floor(this.x),this.y=this.y<0?Math.ceil(this.y):Math.floor(this.y),this}negate(){return this.x=-this.x,this.y=-this.y,this}dot(t){return this.x*t.x+this.y*t.y}cross(t){return this.x*t.y-this.y*t.x}lengthSq(){return this.x*this.x+this.y*this.y}length(){return Math.sqrt(this.x*this.x+this.y*this.y)}manhattanLength(){return Math.abs(this.x)+Math.abs(this.y)}normalize(){return this.divideScalar(this.length()||1)}angle(){return Math.atan2(-this.y,-this.x)+Math.PI}distanceTo(t){return Math.sqrt(this.distanceToSquared(t))}distanceToSquared(t){const e=this.x-t.x,n=this.y-t.y;return e*e+n*n}manhattanDistanceTo(t){return Math.abs(this.x-t.x)+Math.abs(this.y-t.y)}setLength(t){return this.normalize().multiplyScalar(t)}lerp(t,e){return this.x+=(t.x-this.x)*e,this.y+=(t.y-this.y)*e,this}lerpVectors(t,e,n){return this.x=t.x+(e.x-t.x)*n,this.y=t.y+(e.y-t.y)*n,this}equals(t){return t.x===this.x&&t.y===this.y}fromArray(t,e=0){return this.x=t[e],this.y=t[e+1],this}toArray(t=[],e=0){return t[e]=this.x,t[e+1]=this.y,t}fromBufferAttribute(t,e,n){return void 0!==n&&console.warn(\\\\\\\"THREE.Vector2: offset has been removed from .fromBufferAttribute().\\\\\\\"),this.x=t.getX(e),this.y=t.getY(e),this}rotateAround(t,e){const n=Math.cos(e),i=Math.sin(e),s=this.x-t.x,r=this.y-t.y;return this.x=s*n-r*i+t.x,this.y=s*i+r*n+t.y,this}random(){return this.x=Math.random(),this.y=Math.random(),this}*[Symbol.iterator](){yield this.x,yield this.y}}ub.prototype.isVector2=!0;class db{constructor(){this.elements=[1,0,0,0,1,0,0,0,1],arguments.length>0&&console.error(\\\\\\\"THREE.Matrix3: the constructor no longer reads arguments. use .set() instead.\\\\\\\")}set(t,e,n,i,s,r,o,a,l){const c=this.elements;return c[0]=t,c[1]=i,c[2]=o,c[3]=e,c[4]=s,c[5]=a,c[6]=n,c[7]=r,c[8]=l,this}identity(){return this.set(1,0,0,0,1,0,0,0,1),this}copy(t){const e=this.elements,n=t.elements;return e[0]=n[0],e[1]=n[1],e[2]=n[2],e[3]=n[3],e[4]=n[4],e[5]=n[5],e[6]=n[6],e[7]=n[7],e[8]=n[8],this}extractBasis(t,e,n){return t.setFromMatrix3Column(this,0),e.setFromMatrix3Column(this,1),n.setFromMatrix3Column(this,2),this}setFromMatrix4(t){const e=t.elements;return this.set(e[0],e[4],e[8],e[1],e[5],e[9],e[2],e[6],e[10]),this}multiply(t){return this.multiplyMatrices(this,t)}premultiply(t){return this.multiplyMatrices(t,this)}multiplyMatrices(t,e){const n=t.elements,i=e.elements,s=this.elements,r=n[0],o=n[3],a=n[6],l=n[1],c=n[4],h=n[7],u=n[2],d=n[5],p=n[8],_=i[0],m=i[3],f=i[6],g=i[1],v=i[4],y=i[7],x=i[2],b=i[5],w=i[8];return s[0]=r*_+o*g+a*x,s[3]=r*m+o*v+a*b,s[6]=r*f+o*y+a*w,s[1]=l*_+c*g+h*x,s[4]=l*m+c*v+h*b,s[7]=l*f+c*y+h*w,s[2]=u*_+d*g+p*x,s[5]=u*m+d*v+p*b,s[8]=u*f+d*y+p*w,this}multiplyScalar(t){const e=this.elements;return e[0]*=t,e[3]*=t,e[6]*=t,e[1]*=t,e[4]*=t,e[7]*=t,e[2]*=t,e[5]*=t,e[8]*=t,this}determinant(){const t=this.elements,e=t[0],n=t[1],i=t[2],s=t[3],r=t[4],o=t[5],a=t[6],l=t[7],c=t[8];return e*r*c-e*o*l-n*s*c+n*o*a+i*s*l-i*r*a}invert(){const t=this.elements,e=t[0],n=t[1],i=t[2],s=t[3],r=t[4],o=t[5],a=t[6],l=t[7],c=t[8],h=c*r-o*l,u=o*a-c*s,d=l*s-r*a,p=e*h+n*u+i*d;if(0===p)return this.set(0,0,0,0,0,0,0,0,0);const _=1/p;return t[0]=h*_,t[1]=(i*l-c*n)*_,t[2]=(o*n-i*r)*_,t[3]=u*_,t[4]=(c*e-i*a)*_,t[5]=(i*s-o*e)*_,t[6]=d*_,t[7]=(n*a-l*e)*_,t[8]=(r*e-n*s)*_,this}transpose(){let t;const e=this.elements;return t=e[1],e[1]=e[3],e[3]=t,t=e[2],e[2]=e[6],e[6]=t,t=e[5],e[5]=e[7],e[7]=t,this}getNormalMatrix(t){return this.setFromMatrix4(t).invert().transpose()}transposeIntoArray(t){const e=this.elements;return t[0]=e[0],t[1]=e[3],t[2]=e[6],t[3]=e[1],t[4]=e[4],t[5]=e[7],t[6]=e[2],t[7]=e[5],t[8]=e[8],this}setUvTransform(t,e,n,i,s,r,o){const a=Math.cos(s),l=Math.sin(s);return this.set(n*a,n*l,-n*(a*r+l*o)+r+t,-i*l,i*a,-i*(-l*r+a*o)+o+e,0,0,1),this}scale(t,e){const n=this.elements;return n[0]*=t,n[3]*=t,n[6]*=t,n[1]*=e,n[4]*=e,n[7]*=e,this}rotate(t){const e=Math.cos(t),n=Math.sin(t),i=this.elements,s=i[0],r=i[3],o=i[6],a=i[1],l=i[4],c=i[7];return i[0]=e*s+n*a,i[3]=e*r+n*l,i[6]=e*o+n*c,i[1]=-n*s+e*a,i[4]=-n*r+e*l,i[7]=-n*o+e*c,this}translate(t,e){const n=this.elements;return n[0]+=t*n[2],n[3]+=t*n[5],n[6]+=t*n[8],n[1]+=e*n[2],n[4]+=e*n[5],n[7]+=e*n[8],this}equals(t){const e=this.elements,n=t.elements;for(let t=0;t<9;t++)if(e[t]!==n[t])return!1;return!0}fromArray(t,e=0){for(let n=0;n<9;n++)this.elements[n]=t[n+e];return this}toArray(t=[],e=0){const n=this.elements;return t[e]=n[0],t[e+1]=n[1],t[e+2]=n[2],t[e+3]=n[3],t[e+4]=n[4],t[e+5]=n[5],t[e+6]=n[6],t[e+7]=n[7],t[e+8]=n[8],t}clone(){return(new this.constructor).fromArray(this.elements)}}function pb(t){if(0===t.length)return-1/0;let e=t[0];for(let n=1,i=t.length;ne&&(e=t[n]);return e}db.prototype.isMatrix3=!0;Int8Array,Uint8Array,Uint8ClampedArray,Int16Array,Uint16Array,Int32Array,Uint32Array,Float32Array,Float64Array;function _b(t){return document.createElementNS(\\\\\\\"http://www.w3.org/1999/xhtml\\\\\\\",t)}let mb;class fb{static getDataURL(t){if(/^data:/i.test(t.src))return t.src;if(\\\\\\\"undefined\\\\\\\"==typeof HTMLCanvasElement)return t.src;let e;if(t instanceof HTMLCanvasElement)e=t;else{void 0===mb&&(mb=_b(\\\\\\\"canvas\\\\\\\")),mb.width=t.width,mb.height=t.height;const n=mb.getContext(\\\\\\\"2d\\\\\\\");t instanceof ImageData?n.putImageData(t,0,0):n.drawImage(t,0,0,t.width,t.height),e=mb}return e.width>2048||e.height>2048?(console.warn(\\\\\\\"THREE.ImageUtils.getDataURL: Image converted to jpg for performance reasons\\\\\\\",t),e.toDataURL(\\\\\\\"image/jpeg\\\\\\\",.6)):e.toDataURL(\\\\\\\"image/png\\\\\\\")}}let gb=0;class vb extends Zx{constructor(t=vb.DEFAULT_IMAGE,e=vb.DEFAULT_MAPPING,n=1001,i=1001,s=1006,r=1008,o=1023,a=1009,l=1,c=3e3){super(),Object.defineProperty(this,\\\\\\\"id\\\\\\\",{value:gb++}),this.uuid=ib(),this.name=\\\\\\\"\\\\\\\",this.image=t,this.mipmaps=[],this.mapping=e,this.wrapS=n,this.wrapT=i,this.magFilter=s,this.minFilter=r,this.anisotropy=l,this.format=o,this.internalFormat=null,this.type=a,this.offset=new ub(0,0),this.repeat=new ub(1,1),this.center=new ub(0,0),this.rotation=0,this.matrixAutoUpdate=!0,this.matrix=new db,this.generateMipmaps=!0,this.premultiplyAlpha=!1,this.flipY=!0,this.unpackAlignment=4,this.encoding=c,this.version=0,this.onUpdate=null,this.isRenderTargetTexture=!1}updateMatrix(){this.matrix.setUvTransform(this.offset.x,this.offset.y,this.repeat.x,this.repeat.y,this.rotation,this.center.x,this.center.y)}clone(){return(new this.constructor).copy(this)}copy(t){return this.name=t.name,this.image=t.image,this.mipmaps=t.mipmaps.slice(0),this.mapping=t.mapping,this.wrapS=t.wrapS,this.wrapT=t.wrapT,this.magFilter=t.magFilter,this.minFilter=t.minFilter,this.anisotropy=t.anisotropy,this.format=t.format,this.internalFormat=t.internalFormat,this.type=t.type,this.offset.copy(t.offset),this.repeat.copy(t.repeat),this.center.copy(t.center),this.rotation=t.rotation,this.matrixAutoUpdate=t.matrixAutoUpdate,this.matrix.copy(t.matrix),this.generateMipmaps=t.generateMipmaps,this.premultiplyAlpha=t.premultiplyAlpha,this.flipY=t.flipY,this.unpackAlignment=t.unpackAlignment,this.encoding=t.encoding,this}toJSON(t){const e=void 0===t||\\\\\\\"string\\\\\\\"==typeof t;if(!e&&void 0!==t.textures[this.uuid])return t.textures[this.uuid];const n={metadata:{version:4.5,type:\\\\\\\"Texture\\\\\\\",generator:\\\\\\\"Texture.toJSON\\\\\\\"},uuid:this.uuid,name:this.name,mapping:this.mapping,repeat:[this.repeat.x,this.repeat.y],offset:[this.offset.x,this.offset.y],center:[this.center.x,this.center.y],rotation:this.rotation,wrap:[this.wrapS,this.wrapT],format:this.format,type:this.type,encoding:this.encoding,minFilter:this.minFilter,magFilter:this.magFilter,anisotropy:this.anisotropy,flipY:this.flipY,premultiplyAlpha:this.premultiplyAlpha,unpackAlignment:this.unpackAlignment};if(void 0!==this.image){const i=this.image;if(void 0===i.uuid&&(i.uuid=ib()),!e&&void 0===t.images[i.uuid]){let e;if(Array.isArray(i)){e=[];for(let t=0,n=i.length;t1)switch(this.wrapS){case gx:t.x=t.x-Math.floor(t.x);break;case vx:t.x=t.x<0?0:1;break;case yx:1===Math.abs(Math.floor(t.x)%2)?t.x=Math.ceil(t.x)-t.x:t.x=t.x-Math.floor(t.x)}if(t.y<0||t.y>1)switch(this.wrapT){case gx:t.y=t.y-Math.floor(t.y);break;case vx:t.y=t.y<0?0:1;break;case yx:1===Math.abs(Math.floor(t.y)%2)?t.y=Math.ceil(t.y)-t.y:t.y=t.y-Math.floor(t.y)}return this.flipY&&(t.y=1-t.y),t}set needsUpdate(t){!0===t&&this.version++}}function yb(t){return\\\\\\\"undefined\\\\\\\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\\\\\\\"undefined\\\\\\\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\\\\\\\"undefined\\\\\\\"!=typeof ImageBitmap&&t instanceof ImageBitmap?fb.getDataURL(t):t.data?{data:Array.prototype.slice.call(t.data),width:t.width,height:t.height,type:t.data.constructor.name}:(console.warn(\\\\\\\"THREE.Texture: Unable to serialize Texture.\\\\\\\"),{})}vb.DEFAULT_IMAGE=void 0,vb.DEFAULT_MAPPING=300,vb.prototype.isTexture=!0;class xb{constructor(t=0,e=0,n=0,i=1){this.x=t,this.y=e,this.z=n,this.w=i}get width(){return this.z}set width(t){this.z=t}get height(){return this.w}set height(t){this.w=t}set(t,e,n,i){return this.x=t,this.y=e,this.z=n,this.w=i,this}setScalar(t){return this.x=t,this.y=t,this.z=t,this.w=t,this}setX(t){return this.x=t,this}setY(t){return this.y=t,this}setZ(t){return this.z=t,this}setW(t){return this.w=t,this}setComponent(t,e){switch(t){case 0:this.x=e;break;case 1:this.y=e;break;case 2:this.z=e;break;case 3:this.w=e;break;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}return this}getComponent(t){switch(t){case 0:return this.x;case 1:return this.y;case 2:return this.z;case 3:return this.w;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}}clone(){return new this.constructor(this.x,this.y,this.z,this.w)}copy(t){return this.x=t.x,this.y=t.y,this.z=t.z,this.w=void 0!==t.w?t.w:1,this}add(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector4: .add() now only accepts one argument. Use .addVectors( a, b ) instead.\\\\\\\"),this.addVectors(t,e)):(this.x+=t.x,this.y+=t.y,this.z+=t.z,this.w+=t.w,this)}addScalar(t){return this.x+=t,this.y+=t,this.z+=t,this.w+=t,this}addVectors(t,e){return this.x=t.x+e.x,this.y=t.y+e.y,this.z=t.z+e.z,this.w=t.w+e.w,this}addScaledVector(t,e){return this.x+=t.x*e,this.y+=t.y*e,this.z+=t.z*e,this.w+=t.w*e,this}sub(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector4: .sub() now only accepts one argument. Use .subVectors( a, b ) instead.\\\\\\\"),this.subVectors(t,e)):(this.x-=t.x,this.y-=t.y,this.z-=t.z,this.w-=t.w,this)}subScalar(t){return this.x-=t,this.y-=t,this.z-=t,this.w-=t,this}subVectors(t,e){return this.x=t.x-e.x,this.y=t.y-e.y,this.z=t.z-e.z,this.w=t.w-e.w,this}multiply(t){return this.x*=t.x,this.y*=t.y,this.z*=t.z,this.w*=t.w,this}multiplyScalar(t){return this.x*=t,this.y*=t,this.z*=t,this.w*=t,this}applyMatrix4(t){const e=this.x,n=this.y,i=this.z,s=this.w,r=t.elements;return this.x=r[0]*e+r[4]*n+r[8]*i+r[12]*s,this.y=r[1]*e+r[5]*n+r[9]*i+r[13]*s,this.z=r[2]*e+r[6]*n+r[10]*i+r[14]*s,this.w=r[3]*e+r[7]*n+r[11]*i+r[15]*s,this}divideScalar(t){return this.multiplyScalar(1/t)}setAxisAngleFromQuaternion(t){this.w=2*Math.acos(t.w);const e=Math.sqrt(1-t.w*t.w);return e<1e-4?(this.x=1,this.y=0,this.z=0):(this.x=t.x/e,this.y=t.y/e,this.z=t.z/e),this}setAxisAngleFromRotationMatrix(t){let e,n,i,s;const r=.01,o=.1,a=t.elements,l=a[0],c=a[4],h=a[8],u=a[1],d=a[5],p=a[9],_=a[2],m=a[6],f=a[10];if(Math.abs(c-u)a&&t>g?tg?a=0?1:-1,i=1-e*e;if(i>Number.EPSILON){const s=Math.sqrt(i),r=Math.atan2(s,e*n);t=Math.sin(t*r)/s,o=Math.sin(o*r)/s}const s=o*n;if(a=a*t+u*s,l=l*t+d*s,c=c*t+p*s,h=h*t+_*s,t===1-o){const t=1/Math.sqrt(a*a+l*l+c*c+h*h);a*=t,l*=t,c*=t,h*=t}}t[e]=a,t[e+1]=l,t[e+2]=c,t[e+3]=h}static multiplyQuaternionsFlat(t,e,n,i,s,r){const o=n[i],a=n[i+1],l=n[i+2],c=n[i+3],h=s[r],u=s[r+1],d=s[r+2],p=s[r+3];return t[e]=o*p+c*h+a*d-l*u,t[e+1]=a*p+c*u+l*h-o*d,t[e+2]=l*p+c*d+o*u-a*h,t[e+3]=c*p-o*h-a*u-l*d,t}get x(){return this._x}set x(t){this._x=t,this._onChangeCallback()}get y(){return this._y}set y(t){this._y=t,this._onChangeCallback()}get z(){return this._z}set z(t){this._z=t,this._onChangeCallback()}get w(){return this._w}set w(t){this._w=t,this._onChangeCallback()}set(t,e,n,i){return this._x=t,this._y=e,this._z=n,this._w=i,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._w)}copy(t){return this._x=t.x,this._y=t.y,this._z=t.z,this._w=t.w,this._onChangeCallback(),this}setFromEuler(t,e){if(!t||!t.isEuler)throw new Error(\\\\\\\"THREE.Quaternion: .setFromEuler() now expects an Euler rotation rather than a Vector3 and order.\\\\\\\");const n=t._x,i=t._y,s=t._z,r=t._order,o=Math.cos,a=Math.sin,l=o(n/2),c=o(i/2),h=o(s/2),u=a(n/2),d=a(i/2),p=a(s/2);switch(r){case\\\\\\\"XYZ\\\\\\\":this._x=u*c*h+l*d*p,this._y=l*d*h-u*c*p,this._z=l*c*p+u*d*h,this._w=l*c*h-u*d*p;break;case\\\\\\\"YXZ\\\\\\\":this._x=u*c*h+l*d*p,this._y=l*d*h-u*c*p,this._z=l*c*p-u*d*h,this._w=l*c*h+u*d*p;break;case\\\\\\\"ZXY\\\\\\\":this._x=u*c*h-l*d*p,this._y=l*d*h+u*c*p,this._z=l*c*p+u*d*h,this._w=l*c*h-u*d*p;break;case\\\\\\\"ZYX\\\\\\\":this._x=u*c*h-l*d*p,this._y=l*d*h+u*c*p,this._z=l*c*p-u*d*h,this._w=l*c*h+u*d*p;break;case\\\\\\\"YZX\\\\\\\":this._x=u*c*h+l*d*p,this._y=l*d*h+u*c*p,this._z=l*c*p-u*d*h,this._w=l*c*h-u*d*p;break;case\\\\\\\"XZY\\\\\\\":this._x=u*c*h-l*d*p,this._y=l*d*h-u*c*p,this._z=l*c*p+u*d*h,this._w=l*c*h+u*d*p;break;default:console.warn(\\\\\\\"THREE.Quaternion: .setFromEuler() encountered an unknown order: \\\\\\\"+r)}return!1!==e&&this._onChangeCallback(),this}setFromAxisAngle(t,e){const n=e/2,i=Math.sin(n);return this._x=t.x*i,this._y=t.y*i,this._z=t.z*i,this._w=Math.cos(n),this._onChangeCallback(),this}setFromRotationMatrix(t){const e=t.elements,n=e[0],i=e[4],s=e[8],r=e[1],o=e[5],a=e[9],l=e[2],c=e[6],h=e[10],u=n+o+h;if(u>0){const t=.5/Math.sqrt(u+1);this._w=.25/t,this._x=(c-a)*t,this._y=(s-l)*t,this._z=(r-i)*t}else if(n>o&&n>h){const t=2*Math.sqrt(1+n-o-h);this._w=(c-a)/t,this._x=.25*t,this._y=(i+r)/t,this._z=(s+l)/t}else if(o>h){const t=2*Math.sqrt(1+o-n-h);this._w=(s-l)/t,this._x=(i+r)/t,this._y=.25*t,this._z=(a+c)/t}else{const t=2*Math.sqrt(1+h-n-o);this._w=(r-i)/t,this._x=(s+l)/t,this._y=(a+c)/t,this._z=.25*t}return this._onChangeCallback(),this}setFromUnitVectors(t,e){let n=t.dot(e)+1;return nMath.abs(t.z)?(this._x=-t.y,this._y=t.x,this._z=0,this._w=n):(this._x=0,this._y=-t.z,this._z=t.y,this._w=n)):(this._x=t.y*e.z-t.z*e.y,this._y=t.z*e.x-t.x*e.z,this._z=t.x*e.y-t.y*e.x,this._w=n),this.normalize()}angleTo(t){return 2*Math.acos(Math.abs(sb(this.dot(t),-1,1)))}rotateTowards(t,e){const n=this.angleTo(t);if(0===n)return this;const i=Math.min(1,e/n);return this.slerp(t,i),this}identity(){return this.set(0,0,0,1)}invert(){return this.conjugate()}conjugate(){return this._x*=-1,this._y*=-1,this._z*=-1,this._onChangeCallback(),this}dot(t){return this._x*t._x+this._y*t._y+this._z*t._z+this._w*t._w}lengthSq(){return this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w}length(){return Math.sqrt(this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w)}normalize(){let t=this.length();return 0===t?(this._x=0,this._y=0,this._z=0,this._w=1):(t=1/t,this._x=this._x*t,this._y=this._y*t,this._z=this._z*t,this._w=this._w*t),this._onChangeCallback(),this}multiply(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Quaternion: .multiply() now only accepts one argument. Use .multiplyQuaternions( a, b ) instead.\\\\\\\"),this.multiplyQuaternions(t,e)):this.multiplyQuaternions(this,t)}premultiply(t){return this.multiplyQuaternions(t,this)}multiplyQuaternions(t,e){const n=t._x,i=t._y,s=t._z,r=t._w,o=e._x,a=e._y,l=e._z,c=e._w;return this._x=n*c+r*o+i*l-s*a,this._y=i*c+r*a+s*o-n*l,this._z=s*c+r*l+n*a-i*o,this._w=r*c-n*o-i*a-s*l,this._onChangeCallback(),this}slerp(t,e){if(0===e)return this;if(1===e)return this.copy(t);const n=this._x,i=this._y,s=this._z,r=this._w;let o=r*t._w+n*t._x+i*t._y+s*t._z;if(o<0?(this._w=-t._w,this._x=-t._x,this._y=-t._y,this._z=-t._z,o=-o):this.copy(t),o>=1)return this._w=r,this._x=n,this._y=i,this._z=s,this;const a=1-o*o;if(a<=Number.EPSILON){const t=1-e;return this._w=t*r+e*this._w,this._x=t*n+e*this._x,this._y=t*i+e*this._y,this._z=t*s+e*this._z,this.normalize(),this._onChangeCallback(),this}const l=Math.sqrt(a),c=Math.atan2(l,o),h=Math.sin((1-e)*c)/l,u=Math.sin(e*c)/l;return this._w=r*h+this._w*u,this._x=n*h+this._x*u,this._y=i*h+this._y*u,this._z=s*h+this._z*u,this._onChangeCallback(),this}slerpQuaternions(t,e,n){this.copy(t).slerp(e,n)}random(){const t=Math.random(),e=Math.sqrt(1-t),n=Math.sqrt(t),i=2*Math.PI*Math.random(),s=2*Math.PI*Math.random();return this.set(e*Math.cos(i),n*Math.sin(s),n*Math.cos(s),e*Math.sin(i))}equals(t){return t._x===this._x&&t._y===this._y&&t._z===this._z&&t._w===this._w}fromArray(t,e=0){return this._x=t[e],this._y=t[e+1],this._z=t[e+2],this._w=t[e+3],this._onChangeCallback(),this}toArray(t=[],e=0){return t[e]=this._x,t[e+1]=this._y,t[e+2]=this._z,t[e+3]=this._w,t}fromBufferAttribute(t,e){return this._x=t.getX(e),this._y=t.getY(e),this._z=t.getZ(e),this._w=t.getW(e),this}_onChange(t){return this._onChangeCallback=t,this}_onChangeCallback(){}}Tb.prototype.isQuaternion=!0;class Ab{constructor(t=0,e=0,n=0){this.x=t,this.y=e,this.z=n}set(t,e,n){return void 0===n&&(n=this.z),this.x=t,this.y=e,this.z=n,this}setScalar(t){return this.x=t,this.y=t,this.z=t,this}setX(t){return this.x=t,this}setY(t){return this.y=t,this}setZ(t){return this.z=t,this}setComponent(t,e){switch(t){case 0:this.x=e;break;case 1:this.y=e;break;case 2:this.z=e;break;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}return this}getComponent(t){switch(t){case 0:return this.x;case 1:return this.y;case 2:return this.z;default:throw new Error(\\\\\\\"index is out of range: \\\\\\\"+t)}}clone(){return new this.constructor(this.x,this.y,this.z)}copy(t){return this.x=t.x,this.y=t.y,this.z=t.z,this}add(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector3: .add() now only accepts one argument. Use .addVectors( a, b ) instead.\\\\\\\"),this.addVectors(t,e)):(this.x+=t.x,this.y+=t.y,this.z+=t.z,this)}addScalar(t){return this.x+=t,this.y+=t,this.z+=t,this}addVectors(t,e){return this.x=t.x+e.x,this.y=t.y+e.y,this.z=t.z+e.z,this}addScaledVector(t,e){return this.x+=t.x*e,this.y+=t.y*e,this.z+=t.z*e,this}sub(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector3: .sub() now only accepts one argument. Use .subVectors( a, b ) instead.\\\\\\\"),this.subVectors(t,e)):(this.x-=t.x,this.y-=t.y,this.z-=t.z,this)}subScalar(t){return this.x-=t,this.y-=t,this.z-=t,this}subVectors(t,e){return this.x=t.x-e.x,this.y=t.y-e.y,this.z=t.z-e.z,this}multiply(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector3: .multiply() now only accepts one argument. Use .multiplyVectors( a, b ) instead.\\\\\\\"),this.multiplyVectors(t,e)):(this.x*=t.x,this.y*=t.y,this.z*=t.z,this)}multiplyScalar(t){return this.x*=t,this.y*=t,this.z*=t,this}multiplyVectors(t,e){return this.x=t.x*e.x,this.y=t.y*e.y,this.z=t.z*e.z,this}applyEuler(t){return t&&t.isEuler||console.error(\\\\\\\"THREE.Vector3: .applyEuler() now expects an Euler rotation rather than a Vector3 and order.\\\\\\\"),this.applyQuaternion(Eb.setFromEuler(t))}applyAxisAngle(t,e){return this.applyQuaternion(Eb.setFromAxisAngle(t,e))}applyMatrix3(t){const e=this.x,n=this.y,i=this.z,s=t.elements;return this.x=s[0]*e+s[3]*n+s[6]*i,this.y=s[1]*e+s[4]*n+s[7]*i,this.z=s[2]*e+s[5]*n+s[8]*i,this}applyNormalMatrix(t){return this.applyMatrix3(t).normalize()}applyMatrix4(t){const e=this.x,n=this.y,i=this.z,s=t.elements,r=1/(s[3]*e+s[7]*n+s[11]*i+s[15]);return this.x=(s[0]*e+s[4]*n+s[8]*i+s[12])*r,this.y=(s[1]*e+s[5]*n+s[9]*i+s[13])*r,this.z=(s[2]*e+s[6]*n+s[10]*i+s[14])*r,this}applyQuaternion(t){const e=this.x,n=this.y,i=this.z,s=t.x,r=t.y,o=t.z,a=t.w,l=a*e+r*i-o*n,c=a*n+o*e-s*i,h=a*i+s*n-r*e,u=-s*e-r*n-o*i;return this.x=l*a+u*-s+c*-o-h*-r,this.y=c*a+u*-r+h*-s-l*-o,this.z=h*a+u*-o+l*-r-c*-s,this}project(t){return this.applyMatrix4(t.matrixWorldInverse).applyMatrix4(t.projectionMatrix)}unproject(t){return this.applyMatrix4(t.projectionMatrixInverse).applyMatrix4(t.matrixWorld)}transformDirection(t){const e=this.x,n=this.y,i=this.z,s=t.elements;return this.x=s[0]*e+s[4]*n+s[8]*i,this.y=s[1]*e+s[5]*n+s[9]*i,this.z=s[2]*e+s[6]*n+s[10]*i,this.normalize()}divide(t){return this.x/=t.x,this.y/=t.y,this.z/=t.z,this}divideScalar(t){return this.multiplyScalar(1/t)}min(t){return this.x=Math.min(this.x,t.x),this.y=Math.min(this.y,t.y),this.z=Math.min(this.z,t.z),this}max(t){return this.x=Math.max(this.x,t.x),this.y=Math.max(this.y,t.y),this.z=Math.max(this.z,t.z),this}clamp(t,e){return this.x=Math.max(t.x,Math.min(e.x,this.x)),this.y=Math.max(t.y,Math.min(e.y,this.y)),this.z=Math.max(t.z,Math.min(e.z,this.z)),this}clampScalar(t,e){return this.x=Math.max(t,Math.min(e,this.x)),this.y=Math.max(t,Math.min(e,this.y)),this.z=Math.max(t,Math.min(e,this.z)),this}clampLength(t,e){const n=this.length();return this.divideScalar(n||1).multiplyScalar(Math.max(t,Math.min(e,n)))}floor(){return this.x=Math.floor(this.x),this.y=Math.floor(this.y),this.z=Math.floor(this.z),this}ceil(){return this.x=Math.ceil(this.x),this.y=Math.ceil(this.y),this.z=Math.ceil(this.z),this}round(){return this.x=Math.round(this.x),this.y=Math.round(this.y),this.z=Math.round(this.z),this}roundToZero(){return this.x=this.x<0?Math.ceil(this.x):Math.floor(this.x),this.y=this.y<0?Math.ceil(this.y):Math.floor(this.y),this.z=this.z<0?Math.ceil(this.z):Math.floor(this.z),this}negate(){return this.x=-this.x,this.y=-this.y,this.z=-this.z,this}dot(t){return this.x*t.x+this.y*t.y+this.z*t.z}lengthSq(){return this.x*this.x+this.y*this.y+this.z*this.z}length(){return Math.sqrt(this.x*this.x+this.y*this.y+this.z*this.z)}manhattanLength(){return Math.abs(this.x)+Math.abs(this.y)+Math.abs(this.z)}normalize(){return this.divideScalar(this.length()||1)}setLength(t){return this.normalize().multiplyScalar(t)}lerp(t,e){return this.x+=(t.x-this.x)*e,this.y+=(t.y-this.y)*e,this.z+=(t.z-this.z)*e,this}lerpVectors(t,e,n){return this.x=t.x+(e.x-t.x)*n,this.y=t.y+(e.y-t.y)*n,this.z=t.z+(e.z-t.z)*n,this}cross(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Vector3: .cross() now only accepts one argument. Use .crossVectors( a, b ) instead.\\\\\\\"),this.crossVectors(t,e)):this.crossVectors(this,t)}crossVectors(t,e){const n=t.x,i=t.y,s=t.z,r=e.x,o=e.y,a=e.z;return this.x=i*a-s*o,this.y=s*r-n*a,this.z=n*o-i*r,this}projectOnVector(t){const e=t.lengthSq();if(0===e)return this.set(0,0,0);const n=t.dot(this)/e;return this.copy(t).multiplyScalar(n)}projectOnPlane(t){return Mb.copy(this).projectOnVector(t),this.sub(Mb)}reflect(t){return this.sub(Mb.copy(t).multiplyScalar(2*this.dot(t)))}angleTo(t){const e=Math.sqrt(this.lengthSq()*t.lengthSq());if(0===e)return Math.PI/2;const n=this.dot(t)/e;return Math.acos(sb(n,-1,1))}distanceTo(t){return Math.sqrt(this.distanceToSquared(t))}distanceToSquared(t){const e=this.x-t.x,n=this.y-t.y,i=this.z-t.z;return e*e+n*n+i*i}manhattanDistanceTo(t){return Math.abs(this.x-t.x)+Math.abs(this.y-t.y)+Math.abs(this.z-t.z)}setFromSpherical(t){return this.setFromSphericalCoords(t.radius,t.phi,t.theta)}setFromSphericalCoords(t,e,n){const i=Math.sin(e)*t;return this.x=i*Math.sin(n),this.y=Math.cos(e)*t,this.z=i*Math.cos(n),this}setFromCylindrical(t){return this.setFromCylindricalCoords(t.radius,t.theta,t.y)}setFromCylindricalCoords(t,e,n){return this.x=t*Math.sin(e),this.y=n,this.z=t*Math.cos(e),this}setFromMatrixPosition(t){const e=t.elements;return this.x=e[12],this.y=e[13],this.z=e[14],this}setFromMatrixScale(t){const e=this.setFromMatrixColumn(t,0).length(),n=this.setFromMatrixColumn(t,1).length(),i=this.setFromMatrixColumn(t,2).length();return this.x=e,this.y=n,this.z=i,this}setFromMatrixColumn(t,e){return this.fromArray(t.elements,4*e)}setFromMatrix3Column(t,e){return this.fromArray(t.elements,3*e)}equals(t){return t.x===this.x&&t.y===this.y&&t.z===this.z}fromArray(t,e=0){return this.x=t[e],this.y=t[e+1],this.z=t[e+2],this}toArray(t=[],e=0){return t[e]=this.x,t[e+1]=this.y,t[e+2]=this.z,t}fromBufferAttribute(t,e,n){return void 0!==n&&console.warn(\\\\\\\"THREE.Vector3: offset has been removed from .fromBufferAttribute().\\\\\\\"),this.x=t.getX(e),this.y=t.getY(e),this.z=t.getZ(e),this}random(){return this.x=Math.random(),this.y=Math.random(),this.z=Math.random(),this}randomDirection(){const t=2*(Math.random()-.5),e=Math.random()*Math.PI*2,n=Math.sqrt(1-t**2);return this.x=n*Math.cos(e),this.y=n*Math.sin(e),this.z=t,this}*[Symbol.iterator](){yield this.x,yield this.y,yield this.z}}Ab.prototype.isVector3=!0;const Mb=new Ab,Eb=new Tb;class Sb{constructor(t=new Ab(1/0,1/0,1/0),e=new Ab(-1/0,-1/0,-1/0)){this.min=t,this.max=e}set(t,e){return this.min.copy(t),this.max.copy(e),this}setFromArray(t){let e=1/0,n=1/0,i=1/0,s=-1/0,r=-1/0,o=-1/0;for(let a=0,l=t.length;as&&(s=l),c>r&&(r=c),h>o&&(o=h)}return this.min.set(e,n,i),this.max.set(s,r,o),this}setFromBufferAttribute(t){let e=1/0,n=1/0,i=1/0,s=-1/0,r=-1/0,o=-1/0;for(let a=0,l=t.count;as&&(s=l),c>r&&(r=c),h>o&&(o=h)}return this.min.set(e,n,i),this.max.set(s,r,o),this}setFromPoints(t){this.makeEmpty();for(let e=0,n=t.length;ethis.max.x||t.ythis.max.y||t.zthis.max.z)}containsBox(t){return this.min.x<=t.min.x&&t.max.x<=this.max.x&&this.min.y<=t.min.y&&t.max.y<=this.max.y&&this.min.z<=t.min.z&&t.max.z<=this.max.z}getParameter(t,e){return e.set((t.x-this.min.x)/(this.max.x-this.min.x),(t.y-this.min.y)/(this.max.y-this.min.y),(t.z-this.min.z)/(this.max.z-this.min.z))}intersectsBox(t){return!(t.max.xthis.max.x||t.max.ythis.max.y||t.max.zthis.max.z)}intersectsSphere(t){return this.clampPoint(t.center,Nb),Nb.distanceToSquared(t.center)<=t.radius*t.radius}intersectsPlane(t){let e,n;return t.normal.x>0?(e=t.normal.x*this.min.x,n=t.normal.x*this.max.x):(e=t.normal.x*this.max.x,n=t.normal.x*this.min.x),t.normal.y>0?(e+=t.normal.y*this.min.y,n+=t.normal.y*this.max.y):(e+=t.normal.y*this.max.y,n+=t.normal.y*this.min.y),t.normal.z>0?(e+=t.normal.z*this.min.z,n+=t.normal.z*this.max.z):(e+=t.normal.z*this.max.z,n+=t.normal.z*this.min.z),e<=-t.constant&&n>=-t.constant}intersectsTriangle(t){if(this.isEmpty())return!1;this.getCenter(Bb),zb.subVectors(this.max,Bb),Ob.subVectors(t.a,Bb),Pb.subVectors(t.b,Bb),Rb.subVectors(t.c,Bb),Ib.subVectors(Pb,Ob),Fb.subVectors(Rb,Pb),Db.subVectors(Ob,Rb);let e=[0,-Ib.z,Ib.y,0,-Fb.z,Fb.y,0,-Db.z,Db.y,Ib.z,0,-Ib.x,Fb.z,0,-Fb.x,Db.z,0,-Db.x,-Ib.y,Ib.x,0,-Fb.y,Fb.x,0,-Db.y,Db.x,0];return!!Gb(e,Ob,Pb,Rb,zb)&&(e=[1,0,0,0,1,0,0,0,1],!!Gb(e,Ob,Pb,Rb,zb)&&(kb.crossVectors(Ib,Fb),e=[kb.x,kb.y,kb.z],Gb(e,Ob,Pb,Rb,zb)))}clampPoint(t,e){return e.copy(t).clamp(this.min,this.max)}distanceToPoint(t){return Nb.copy(t).clamp(this.min,this.max).sub(t).length()}getBoundingSphere(t){return this.getCenter(t.center),t.radius=.5*this.getSize(Nb).length(),t}intersect(t){return this.min.max(t.min),this.max.min(t.max),this.isEmpty()&&this.makeEmpty(),this}union(t){return this.min.min(t.min),this.max.max(t.max),this}applyMatrix4(t){return this.isEmpty()||(Cb[0].set(this.min.x,this.min.y,this.min.z).applyMatrix4(t),Cb[1].set(this.min.x,this.min.y,this.max.z).applyMatrix4(t),Cb[2].set(this.min.x,this.max.y,this.min.z).applyMatrix4(t),Cb[3].set(this.min.x,this.max.y,this.max.z).applyMatrix4(t),Cb[4].set(this.max.x,this.min.y,this.min.z).applyMatrix4(t),Cb[5].set(this.max.x,this.min.y,this.max.z).applyMatrix4(t),Cb[6].set(this.max.x,this.max.y,this.min.z).applyMatrix4(t),Cb[7].set(this.max.x,this.max.y,this.max.z).applyMatrix4(t),this.setFromPoints(Cb)),this}translate(t){return this.min.add(t),this.max.add(t),this}equals(t){return t.min.equals(this.min)&&t.max.equals(this.max)}}Sb.prototype.isBox3=!0;const Cb=[new Ab,new Ab,new Ab,new Ab,new Ab,new Ab,new Ab,new Ab],Nb=new Ab,Lb=new Sb,Ob=new Ab,Pb=new Ab,Rb=new Ab,Ib=new Ab,Fb=new Ab,Db=new Ab,Bb=new Ab,zb=new Ab,kb=new Ab,Ub=new Ab;function Gb(t,e,n,i,s){for(let r=0,o=t.length-3;r<=o;r+=3){Ub.fromArray(t,r);const o=s.x*Math.abs(Ub.x)+s.y*Math.abs(Ub.y)+s.z*Math.abs(Ub.z),a=e.dot(Ub),l=n.dot(Ub),c=i.dot(Ub);if(Math.max(-Math.max(a,l,c),Math.min(a,l,c))>o)return!1}return!0}const Vb=new Sb,Hb=new Ab,jb=new Ab,Wb=new Ab;class qb{constructor(t=new Ab,e=-1){this.center=t,this.radius=e}set(t,e){return this.center.copy(t),this.radius=e,this}setFromPoints(t,e){const n=this.center;void 0!==e?n.copy(e):Vb.setFromPoints(t).getCenter(n);let i=0;for(let e=0,s=t.length;ethis.radius*this.radius&&(e.sub(this.center).normalize(),e.multiplyScalar(this.radius).add(this.center)),e}getBoundingBox(t){return this.isEmpty()?(t.makeEmpty(),t):(t.set(this.center,this.center),t.expandByScalar(this.radius),t)}applyMatrix4(t){return this.center.applyMatrix4(t),this.radius=this.radius*t.getMaxScaleOnAxis(),this}translate(t){return this.center.add(t),this}expandByPoint(t){Wb.subVectors(t,this.center);const e=Wb.lengthSq();if(e>this.radius*this.radius){const t=Math.sqrt(e),n=.5*(t-this.radius);this.center.add(Wb.multiplyScalar(n/t)),this.radius+=n}return this}union(t){return jb.subVectors(t.center,this.center).normalize().multiplyScalar(t.radius),this.expandByPoint(Hb.copy(t.center).add(jb)),this.expandByPoint(Hb.copy(t.center).sub(jb)),this}equals(t){return t.center.equals(this.center)&&t.radius===this.radius}clone(){return(new this.constructor).copy(this)}}const Xb=new Ab,Yb=new Ab,$b=new Ab,Jb=new Ab,Zb=new Ab,Qb=new Ab,Kb=new Ab;class tw{constructor(t=new Ab,e=new Ab(0,0,-1)){this.origin=t,this.direction=e}set(t,e){return this.origin.copy(t),this.direction.copy(e),this}copy(t){return this.origin.copy(t.origin),this.direction.copy(t.direction),this}at(t,e){return e.copy(this.direction).multiplyScalar(t).add(this.origin)}lookAt(t){return this.direction.copy(t).sub(this.origin).normalize(),this}recast(t){return this.origin.copy(this.at(t,Xb)),this}closestPointToPoint(t,e){e.subVectors(t,this.origin);const n=e.dot(this.direction);return n<0?e.copy(this.origin):e.copy(this.direction).multiplyScalar(n).add(this.origin)}distanceToPoint(t){return Math.sqrt(this.distanceSqToPoint(t))}distanceSqToPoint(t){const e=Xb.subVectors(t,this.origin).dot(this.direction);return e<0?this.origin.distanceToSquared(t):(Xb.copy(this.direction).multiplyScalar(e).add(this.origin),Xb.distanceToSquared(t))}distanceSqToSegment(t,e,n,i){Yb.copy(t).add(e).multiplyScalar(.5),$b.copy(e).sub(t).normalize(),Jb.copy(this.origin).sub(Yb);const s=.5*t.distanceTo(e),r=-this.direction.dot($b),o=Jb.dot(this.direction),a=-Jb.dot($b),l=Jb.lengthSq(),c=Math.abs(1-r*r);let h,u,d,p;if(c>0)if(h=r*a-o,u=r*o-a,p=s*c,h>=0)if(u>=-p)if(u<=p){const t=1/c;h*=t,u*=t,d=h*(h+r*u+2*o)+u*(r*h+u+2*a)+l}else u=s,h=Math.max(0,-(r*u+o)),d=-h*h+u*(u+2*a)+l;else u=-s,h=Math.max(0,-(r*u+o)),d=-h*h+u*(u+2*a)+l;else u<=-p?(h=Math.max(0,-(-r*s+o)),u=h>0?-s:Math.min(Math.max(-s,-a),s),d=-h*h+u*(u+2*a)+l):u<=p?(h=0,u=Math.min(Math.max(-s,-a),s),d=u*(u+2*a)+l):(h=Math.max(0,-(r*s+o)),u=h>0?s:Math.min(Math.max(-s,-a),s),d=-h*h+u*(u+2*a)+l);else u=r>0?-s:s,h=Math.max(0,-(r*u+o)),d=-h*h+u*(u+2*a)+l;return n&&n.copy(this.direction).multiplyScalar(h).add(this.origin),i&&i.copy($b).multiplyScalar(u).add(Yb),d}intersectSphere(t,e){Xb.subVectors(t.center,this.origin);const n=Xb.dot(this.direction),i=Xb.dot(Xb)-n*n,s=t.radius*t.radius;if(i>s)return null;const r=Math.sqrt(s-i),o=n-r,a=n+r;return o<0&&a<0?null:o<0?this.at(a,e):this.at(o,e)}intersectsSphere(t){return this.distanceSqToPoint(t.center)<=t.radius*t.radius}distanceToPlane(t){const e=t.normal.dot(this.direction);if(0===e)return 0===t.distanceToPoint(this.origin)?0:null;const n=-(this.origin.dot(t.normal)+t.constant)/e;return n>=0?n:null}intersectPlane(t,e){const n=this.distanceToPlane(t);return null===n?null:this.at(n,e)}intersectsPlane(t){const e=t.distanceToPoint(this.origin);if(0===e)return!0;return t.normal.dot(this.direction)*e<0}intersectBox(t,e){let n,i,s,r,o,a;const l=1/this.direction.x,c=1/this.direction.y,h=1/this.direction.z,u=this.origin;return l>=0?(n=(t.min.x-u.x)*l,i=(t.max.x-u.x)*l):(n=(t.max.x-u.x)*l,i=(t.min.x-u.x)*l),c>=0?(s=(t.min.y-u.y)*c,r=(t.max.y-u.y)*c):(s=(t.max.y-u.y)*c,r=(t.min.y-u.y)*c),n>r||s>i?null:((s>n||n!=n)&&(n=s),(r=0?(o=(t.min.z-u.z)*h,a=(t.max.z-u.z)*h):(o=(t.max.z-u.z)*h,a=(t.min.z-u.z)*h),n>a||o>i?null:((o>n||n!=n)&&(n=o),(a=0?n:i,e)))}intersectsBox(t){return null!==this.intersectBox(t,Xb)}intersectTriangle(t,e,n,i,s){Zb.subVectors(e,t),Qb.subVectors(n,t),Kb.crossVectors(Zb,Qb);let r,o=this.direction.dot(Kb);if(o>0){if(i)return null;r=1}else{if(!(o<0))return null;r=-1,o=-o}Jb.subVectors(this.origin,t);const a=r*this.direction.dot(Qb.crossVectors(Jb,Qb));if(a<0)return null;const l=r*this.direction.dot(Zb.cross(Jb));if(l<0)return null;if(a+l>o)return null;const c=-r*Jb.dot(Kb);return c<0?null:this.at(c/o,s)}applyMatrix4(t){return this.origin.applyMatrix4(t),this.direction.transformDirection(t),this}equals(t){return t.origin.equals(this.origin)&&t.direction.equals(this.direction)}clone(){return(new this.constructor).copy(this)}}class ew{constructor(){this.elements=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],arguments.length>0&&console.error(\\\\\\\"THREE.Matrix4: the constructor no longer reads arguments. use .set() instead.\\\\\\\")}set(t,e,n,i,s,r,o,a,l,c,h,u,d,p,_,m){const f=this.elements;return f[0]=t,f[4]=e,f[8]=n,f[12]=i,f[1]=s,f[5]=r,f[9]=o,f[13]=a,f[2]=l,f[6]=c,f[10]=h,f[14]=u,f[3]=d,f[7]=p,f[11]=_,f[15]=m,this}identity(){return this.set(1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1),this}clone(){return(new ew).fromArray(this.elements)}copy(t){const e=this.elements,n=t.elements;return e[0]=n[0],e[1]=n[1],e[2]=n[2],e[3]=n[3],e[4]=n[4],e[5]=n[5],e[6]=n[6],e[7]=n[7],e[8]=n[8],e[9]=n[9],e[10]=n[10],e[11]=n[11],e[12]=n[12],e[13]=n[13],e[14]=n[14],e[15]=n[15],this}copyPosition(t){const e=this.elements,n=t.elements;return e[12]=n[12],e[13]=n[13],e[14]=n[14],this}setFromMatrix3(t){const e=t.elements;return this.set(e[0],e[3],e[6],0,e[1],e[4],e[7],0,e[2],e[5],e[8],0,0,0,0,1),this}extractBasis(t,e,n){return t.setFromMatrixColumn(this,0),e.setFromMatrixColumn(this,1),n.setFromMatrixColumn(this,2),this}makeBasis(t,e,n){return this.set(t.x,e.x,n.x,0,t.y,e.y,n.y,0,t.z,e.z,n.z,0,0,0,0,1),this}extractRotation(t){const e=this.elements,n=t.elements,i=1/nw.setFromMatrixColumn(t,0).length(),s=1/nw.setFromMatrixColumn(t,1).length(),r=1/nw.setFromMatrixColumn(t,2).length();return e[0]=n[0]*i,e[1]=n[1]*i,e[2]=n[2]*i,e[3]=0,e[4]=n[4]*s,e[5]=n[5]*s,e[6]=n[6]*s,e[7]=0,e[8]=n[8]*r,e[9]=n[9]*r,e[10]=n[10]*r,e[11]=0,e[12]=0,e[13]=0,e[14]=0,e[15]=1,this}makeRotationFromEuler(t){t&&t.isEuler||console.error(\\\\\\\"THREE.Matrix4: .makeRotationFromEuler() now expects a Euler rotation rather than a Vector3 and order.\\\\\\\");const e=this.elements,n=t.x,i=t.y,s=t.z,r=Math.cos(n),o=Math.sin(n),a=Math.cos(i),l=Math.sin(i),c=Math.cos(s),h=Math.sin(s);if(\\\\\\\"XYZ\\\\\\\"===t.order){const t=r*c,n=r*h,i=o*c,s=o*h;e[0]=a*c,e[4]=-a*h,e[8]=l,e[1]=n+i*l,e[5]=t-s*l,e[9]=-o*a,e[2]=s-t*l,e[6]=i+n*l,e[10]=r*a}else if(\\\\\\\"YXZ\\\\\\\"===t.order){const t=a*c,n=a*h,i=l*c,s=l*h;e[0]=t+s*o,e[4]=i*o-n,e[8]=r*l,e[1]=r*h,e[5]=r*c,e[9]=-o,e[2]=n*o-i,e[6]=s+t*o,e[10]=r*a}else if(\\\\\\\"ZXY\\\\\\\"===t.order){const t=a*c,n=a*h,i=l*c,s=l*h;e[0]=t-s*o,e[4]=-r*h,e[8]=i+n*o,e[1]=n+i*o,e[5]=r*c,e[9]=s-t*o,e[2]=-r*l,e[6]=o,e[10]=r*a}else if(\\\\\\\"ZYX\\\\\\\"===t.order){const t=r*c,n=r*h,i=o*c,s=o*h;e[0]=a*c,e[4]=i*l-n,e[8]=t*l+s,e[1]=a*h,e[5]=s*l+t,e[9]=n*l-i,e[2]=-l,e[6]=o*a,e[10]=r*a}else if(\\\\\\\"YZX\\\\\\\"===t.order){const t=r*a,n=r*l,i=o*a,s=o*l;e[0]=a*c,e[4]=s-t*h,e[8]=i*h+n,e[1]=h,e[5]=r*c,e[9]=-o*c,e[2]=-l*c,e[6]=n*h+i,e[10]=t-s*h}else if(\\\\\\\"XZY\\\\\\\"===t.order){const t=r*a,n=r*l,i=o*a,s=o*l;e[0]=a*c,e[4]=-h,e[8]=l*c,e[1]=t*h+s,e[5]=r*c,e[9]=n*h-i,e[2]=i*h-n,e[6]=o*c,e[10]=s*h+t}return e[3]=0,e[7]=0,e[11]=0,e[12]=0,e[13]=0,e[14]=0,e[15]=1,this}makeRotationFromQuaternion(t){return this.compose(sw,t,rw)}lookAt(t,e,n){const i=this.elements;return lw.subVectors(t,e),0===lw.lengthSq()&&(lw.z=1),lw.normalize(),ow.crossVectors(n,lw),0===ow.lengthSq()&&(1===Math.abs(n.z)?lw.x+=1e-4:lw.z+=1e-4,lw.normalize(),ow.crossVectors(n,lw)),ow.normalize(),aw.crossVectors(lw,ow),i[0]=ow.x,i[4]=aw.x,i[8]=lw.x,i[1]=ow.y,i[5]=aw.y,i[9]=lw.y,i[2]=ow.z,i[6]=aw.z,i[10]=lw.z,this}multiply(t,e){return void 0!==e?(console.warn(\\\\\\\"THREE.Matrix4: .multiply() now only accepts one argument. Use .multiplyMatrices( a, b ) instead.\\\\\\\"),this.multiplyMatrices(t,e)):this.multiplyMatrices(this,t)}premultiply(t){return this.multiplyMatrices(t,this)}multiplyMatrices(t,e){const n=t.elements,i=e.elements,s=this.elements,r=n[0],o=n[4],a=n[8],l=n[12],c=n[1],h=n[5],u=n[9],d=n[13],p=n[2],_=n[6],m=n[10],f=n[14],g=n[3],v=n[7],y=n[11],x=n[15],b=i[0],w=i[4],T=i[8],A=i[12],M=i[1],E=i[5],S=i[9],C=i[13],N=i[2],L=i[6],O=i[10],P=i[14],R=i[3],I=i[7],F=i[11],D=i[15];return s[0]=r*b+o*M+a*N+l*R,s[4]=r*w+o*E+a*L+l*I,s[8]=r*T+o*S+a*O+l*F,s[12]=r*A+o*C+a*P+l*D,s[1]=c*b+h*M+u*N+d*R,s[5]=c*w+h*E+u*L+d*I,s[9]=c*T+h*S+u*O+d*F,s[13]=c*A+h*C+u*P+d*D,s[2]=p*b+_*M+m*N+f*R,s[6]=p*w+_*E+m*L+f*I,s[10]=p*T+_*S+m*O+f*F,s[14]=p*A+_*C+m*P+f*D,s[3]=g*b+v*M+y*N+x*R,s[7]=g*w+v*E+y*L+x*I,s[11]=g*T+v*S+y*O+x*F,s[15]=g*A+v*C+y*P+x*D,this}multiplyScalar(t){const e=this.elements;return e[0]*=t,e[4]*=t,e[8]*=t,e[12]*=t,e[1]*=t,e[5]*=t,e[9]*=t,e[13]*=t,e[2]*=t,e[6]*=t,e[10]*=t,e[14]*=t,e[3]*=t,e[7]*=t,e[11]*=t,e[15]*=t,this}determinant(){const t=this.elements,e=t[0],n=t[4],i=t[8],s=t[12],r=t[1],o=t[5],a=t[9],l=t[13],c=t[2],h=t[6],u=t[10],d=t[14];return t[3]*(+s*a*h-i*l*h-s*o*u+n*l*u+i*o*d-n*a*d)+t[7]*(+e*a*d-e*l*u+s*r*u-i*r*d+i*l*c-s*a*c)+t[11]*(+e*l*h-e*o*d-s*r*h+n*r*d+s*o*c-n*l*c)+t[15]*(-i*o*c-e*a*h+e*o*u+i*r*h-n*r*u+n*a*c)}transpose(){const t=this.elements;let e;return e=t[1],t[1]=t[4],t[4]=e,e=t[2],t[2]=t[8],t[8]=e,e=t[6],t[6]=t[9],t[9]=e,e=t[3],t[3]=t[12],t[12]=e,e=t[7],t[7]=t[13],t[13]=e,e=t[11],t[11]=t[14],t[14]=e,this}setPosition(t,e,n){const i=this.elements;return t.isVector3?(i[12]=t.x,i[13]=t.y,i[14]=t.z):(i[12]=t,i[13]=e,i[14]=n),this}invert(){const t=this.elements,e=t[0],n=t[1],i=t[2],s=t[3],r=t[4],o=t[5],a=t[6],l=t[7],c=t[8],h=t[9],u=t[10],d=t[11],p=t[12],_=t[13],m=t[14],f=t[15],g=h*m*l-_*u*l+_*a*d-o*m*d-h*a*f+o*u*f,v=p*u*l-c*m*l-p*a*d+r*m*d+c*a*f-r*u*f,y=c*_*l-p*h*l+p*o*d-r*_*d-c*o*f+r*h*f,x=p*h*a-c*_*a-p*o*u+r*_*u+c*o*m-r*h*m,b=e*g+n*v+i*y+s*x;if(0===b)return this.set(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0);const w=1/b;return t[0]=g*w,t[1]=(_*u*s-h*m*s-_*i*d+n*m*d+h*i*f-n*u*f)*w,t[2]=(o*m*s-_*a*s+_*i*l-n*m*l-o*i*f+n*a*f)*w,t[3]=(h*a*s-o*u*s-h*i*l+n*u*l+o*i*d-n*a*d)*w,t[4]=v*w,t[5]=(c*m*s-p*u*s+p*i*d-e*m*d-c*i*f+e*u*f)*w,t[6]=(p*a*s-r*m*s-p*i*l+e*m*l+r*i*f-e*a*f)*w,t[7]=(r*u*s-c*a*s+c*i*l-e*u*l-r*i*d+e*a*d)*w,t[8]=y*w,t[9]=(p*h*s-c*_*s-p*n*d+e*_*d+c*n*f-e*h*f)*w,t[10]=(r*_*s-p*o*s+p*n*l-e*_*l-r*n*f+e*o*f)*w,t[11]=(c*o*s-r*h*s-c*n*l+e*h*l+r*n*d-e*o*d)*w,t[12]=x*w,t[13]=(c*_*i-p*h*i+p*n*u-e*_*u-c*n*m+e*h*m)*w,t[14]=(p*o*i-r*_*i-p*n*a+e*_*a+r*n*m-e*o*m)*w,t[15]=(r*h*i-c*o*i+c*n*a-e*h*a-r*n*u+e*o*u)*w,this}scale(t){const e=this.elements,n=t.x,i=t.y,s=t.z;return e[0]*=n,e[4]*=i,e[8]*=s,e[1]*=n,e[5]*=i,e[9]*=s,e[2]*=n,e[6]*=i,e[10]*=s,e[3]*=n,e[7]*=i,e[11]*=s,this}getMaxScaleOnAxis(){const t=this.elements,e=t[0]*t[0]+t[1]*t[1]+t[2]*t[2],n=t[4]*t[4]+t[5]*t[5]+t[6]*t[6],i=t[8]*t[8]+t[9]*t[9]+t[10]*t[10];return Math.sqrt(Math.max(e,n,i))}makeTranslation(t,e,n){return this.set(1,0,0,t,0,1,0,e,0,0,1,n,0,0,0,1),this}makeRotationX(t){const e=Math.cos(t),n=Math.sin(t);return this.set(1,0,0,0,0,e,-n,0,0,n,e,0,0,0,0,1),this}makeRotationY(t){const e=Math.cos(t),n=Math.sin(t);return this.set(e,0,n,0,0,1,0,0,-n,0,e,0,0,0,0,1),this}makeRotationZ(t){const e=Math.cos(t),n=Math.sin(t);return this.set(e,-n,0,0,n,e,0,0,0,0,1,0,0,0,0,1),this}makeRotationAxis(t,e){const n=Math.cos(e),i=Math.sin(e),s=1-n,r=t.x,o=t.y,a=t.z,l=s*r,c=s*o;return this.set(l*r+n,l*o-i*a,l*a+i*o,0,l*o+i*a,c*o+n,c*a-i*r,0,l*a-i*o,c*a+i*r,s*a*a+n,0,0,0,0,1),this}makeScale(t,e,n){return this.set(t,0,0,0,0,e,0,0,0,0,n,0,0,0,0,1),this}makeShear(t,e,n,i,s,r){return this.set(1,n,s,0,t,1,r,0,e,i,1,0,0,0,0,1),this}compose(t,e,n){const i=this.elements,s=e._x,r=e._y,o=e._z,a=e._w,l=s+s,c=r+r,h=o+o,u=s*l,d=s*c,p=s*h,_=r*c,m=r*h,f=o*h,g=a*l,v=a*c,y=a*h,x=n.x,b=n.y,w=n.z;return i[0]=(1-(_+f))*x,i[1]=(d+y)*x,i[2]=(p-v)*x,i[3]=0,i[4]=(d-y)*b,i[5]=(1-(u+f))*b,i[6]=(m+g)*b,i[7]=0,i[8]=(p+v)*w,i[9]=(m-g)*w,i[10]=(1-(u+_))*w,i[11]=0,i[12]=t.x,i[13]=t.y,i[14]=t.z,i[15]=1,this}decompose(t,e,n){const i=this.elements;let s=nw.set(i[0],i[1],i[2]).length();const r=nw.set(i[4],i[5],i[6]).length(),o=nw.set(i[8],i[9],i[10]).length();this.determinant()<0&&(s=-s),t.x=i[12],t.y=i[13],t.z=i[14],iw.copy(this);const a=1/s,l=1/r,c=1/o;return iw.elements[0]*=a,iw.elements[1]*=a,iw.elements[2]*=a,iw.elements[4]*=l,iw.elements[5]*=l,iw.elements[6]*=l,iw.elements[8]*=c,iw.elements[9]*=c,iw.elements[10]*=c,e.setFromRotationMatrix(iw),n.x=s,n.y=r,n.z=o,this}makePerspective(t,e,n,i,s,r){void 0===r&&console.warn(\\\\\\\"THREE.Matrix4: .makePerspective() has been redefined and has a new signature. Please check the docs.\\\\\\\");const o=this.elements,a=2*s/(e-t),l=2*s/(n-i),c=(e+t)/(e-t),h=(n+i)/(n-i),u=-(r+s)/(r-s),d=-2*r*s/(r-s);return o[0]=a,o[4]=0,o[8]=c,o[12]=0,o[1]=0,o[5]=l,o[9]=h,o[13]=0,o[2]=0,o[6]=0,o[10]=u,o[14]=d,o[3]=0,o[7]=0,o[11]=-1,o[15]=0,this}makeOrthographic(t,e,n,i,s,r){const o=this.elements,a=1/(e-t),l=1/(n-i),c=1/(r-s),h=(e+t)*a,u=(n+i)*l,d=(r+s)*c;return o[0]=2*a,o[4]=0,o[8]=0,o[12]=-h,o[1]=0,o[5]=2*l,o[9]=0,o[13]=-u,o[2]=0,o[6]=0,o[10]=-2*c,o[14]=-d,o[3]=0,o[7]=0,o[11]=0,o[15]=1,this}equals(t){const e=this.elements,n=t.elements;for(let t=0;t<16;t++)if(e[t]!==n[t])return!1;return!0}fromArray(t,e=0){for(let n=0;n<16;n++)this.elements[n]=t[n+e];return this}toArray(t=[],e=0){const n=this.elements;return t[e]=n[0],t[e+1]=n[1],t[e+2]=n[2],t[e+3]=n[3],t[e+4]=n[4],t[e+5]=n[5],t[e+6]=n[6],t[e+7]=n[7],t[e+8]=n[8],t[e+9]=n[9],t[e+10]=n[10],t[e+11]=n[11],t[e+12]=n[12],t[e+13]=n[13],t[e+14]=n[14],t[e+15]=n[15],t}}ew.prototype.isMatrix4=!0;const nw=new Ab,iw=new ew,sw=new Ab(0,0,0),rw=new Ab(1,1,1),ow=new Ab,aw=new Ab,lw=new Ab,cw=new ew,hw=new Tb;class uw{constructor(t=0,e=0,n=0,i=uw.DefaultOrder){this._x=t,this._y=e,this._z=n,this._order=i}get x(){return this._x}set x(t){this._x=t,this._onChangeCallback()}get y(){return this._y}set y(t){this._y=t,this._onChangeCallback()}get z(){return this._z}set z(t){this._z=t,this._onChangeCallback()}get order(){return this._order}set order(t){this._order=t,this._onChangeCallback()}set(t,e,n,i=this._order){return this._x=t,this._y=e,this._z=n,this._order=i,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._order)}copy(t){return this._x=t._x,this._y=t._y,this._z=t._z,this._order=t._order,this._onChangeCallback(),this}setFromRotationMatrix(t,e=this._order,n=!0){const i=t.elements,s=i[0],r=i[4],o=i[8],a=i[1],l=i[5],c=i[9],h=i[2],u=i[6],d=i[10];switch(e){case\\\\\\\"XYZ\\\\\\\":this._y=Math.asin(sb(o,-1,1)),Math.abs(o)<.9999999?(this._x=Math.atan2(-c,d),this._z=Math.atan2(-r,s)):(this._x=Math.atan2(u,l),this._z=0);break;case\\\\\\\"YXZ\\\\\\\":this._x=Math.asin(-sb(c,-1,1)),Math.abs(c)<.9999999?(this._y=Math.atan2(o,d),this._z=Math.atan2(a,l)):(this._y=Math.atan2(-h,s),this._z=0);break;case\\\\\\\"ZXY\\\\\\\":this._x=Math.asin(sb(u,-1,1)),Math.abs(u)<.9999999?(this._y=Math.atan2(-h,d),this._z=Math.atan2(-r,l)):(this._y=0,this._z=Math.atan2(a,s));break;case\\\\\\\"ZYX\\\\\\\":this._y=Math.asin(-sb(h,-1,1)),Math.abs(h)<.9999999?(this._x=Math.atan2(u,d),this._z=Math.atan2(a,s)):(this._x=0,this._z=Math.atan2(-r,l));break;case\\\\\\\"YZX\\\\\\\":this._z=Math.asin(sb(a,-1,1)),Math.abs(a)<.9999999?(this._x=Math.atan2(-c,l),this._y=Math.atan2(-h,s)):(this._x=0,this._y=Math.atan2(o,d));break;case\\\\\\\"XZY\\\\\\\":this._z=Math.asin(-sb(r,-1,1)),Math.abs(r)<.9999999?(this._x=Math.atan2(u,l),this._y=Math.atan2(o,s)):(this._x=Math.atan2(-c,d),this._y=0);break;default:console.warn(\\\\\\\"THREE.Euler: .setFromRotationMatrix() encountered an unknown order: \\\\\\\"+e)}return this._order=e,!0===n&&this._onChangeCallback(),this}setFromQuaternion(t,e,n){return cw.makeRotationFromQuaternion(t),this.setFromRotationMatrix(cw,e,n)}setFromVector3(t,e=this._order){return this.set(t.x,t.y,t.z,e)}reorder(t){return hw.setFromEuler(this),this.setFromQuaternion(hw,t)}equals(t){return t._x===this._x&&t._y===this._y&&t._z===this._z&&t._order===this._order}fromArray(t){return this._x=t[0],this._y=t[1],this._z=t[2],void 0!==t[3]&&(this._order=t[3]),this._onChangeCallback(),this}toArray(t=[],e=0){return t[e]=this._x,t[e+1]=this._y,t[e+2]=this._z,t[e+3]=this._order,t}toVector3(t){return t?t.set(this._x,this._y,this._z):new Ab(this._x,this._y,this._z)}_onChange(t){return this._onChangeCallback=t,this}_onChangeCallback(){}}uw.prototype.isEuler=!0,uw.DefaultOrder=\\\\\\\"XYZ\\\\\\\",uw.RotationOrders=[\\\\\\\"XYZ\\\\\\\",\\\\\\\"YZX\\\\\\\",\\\\\\\"ZXY\\\\\\\",\\\\\\\"XZY\\\\\\\",\\\\\\\"YXZ\\\\\\\",\\\\\\\"ZYX\\\\\\\"];class dw{constructor(){this.mask=1}set(t){this.mask=1<1){for(let t=0;t1){for(let t=0;t0){i.children=[];for(let e=0;e0){i.animations=[];for(let e=0;e0&&(n.geometries=e),i.length>0&&(n.materials=i),s.length>0&&(n.textures=s),o.length>0&&(n.images=o),a.length>0&&(n.shapes=a),l.length>0&&(n.skeletons=l),c.length>0&&(n.animations=c)}return n.object=i,n;function r(t){const e=[];for(const n in t){const i=t[n];delete i.metadata,e.push(i)}return e}}clone(t){return(new this.constructor).copy(this,t)}copy(t,e=!0){if(this.name=t.name,this.up.copy(t.up),this.position.copy(t.position),this.rotation.order=t.rotation.order,this.quaternion.copy(t.quaternion),this.scale.copy(t.scale),this.matrix.copy(t.matrix),this.matrixWorld.copy(t.matrixWorld),this.matrixAutoUpdate=t.matrixAutoUpdate,this.matrixWorldNeedsUpdate=t.matrixWorldNeedsUpdate,this.layers.mask=t.layers.mask,this.visible=t.visible,this.castShadow=t.castShadow,this.receiveShadow=t.receiveShadow,this.frustumCulled=t.frustumCulled,this.renderOrder=t.renderOrder,this.userData=JSON.parse(JSON.stringify(t.userData)),!0===e)for(let e=0;e0?i.multiplyScalar(1/Math.sqrt(s)):i.set(0,0,0)}static getBarycoord(t,e,n,i,s){Sw.subVectors(i,e),Cw.subVectors(n,e),Nw.subVectors(t,e);const r=Sw.dot(Sw),o=Sw.dot(Cw),a=Sw.dot(Nw),l=Cw.dot(Cw),c=Cw.dot(Nw),h=r*l-o*o;if(0===h)return s.set(-2,-1,-1);const u=1/h,d=(l*a-o*c)*u,p=(r*c-o*a)*u;return s.set(1-d-p,p,d)}static containsPoint(t,e,n,i){return this.getBarycoord(t,e,n,i,Lw),Lw.x>=0&&Lw.y>=0&&Lw.x+Lw.y<=1}static getUV(t,e,n,i,s,r,o,a){return this.getBarycoord(t,e,n,i,Lw),a.set(0,0),a.addScaledVector(s,Lw.x),a.addScaledVector(r,Lw.y),a.addScaledVector(o,Lw.z),a}static isFrontFacing(t,e,n,i){return Sw.subVectors(n,e),Cw.subVectors(t,e),Sw.cross(Cw).dot(i)<0}set(t,e,n){return this.a.copy(t),this.b.copy(e),this.c.copy(n),this}setFromPointsAndIndices(t,e,n,i){return this.a.copy(t[e]),this.b.copy(t[n]),this.c.copy(t[i]),this}setFromAttributeAndIndices(t,e,n,i){return this.a.fromBufferAttribute(t,e),this.b.fromBufferAttribute(t,n),this.c.fromBufferAttribute(t,i),this}clone(){return(new this.constructor).copy(this)}copy(t){return this.a.copy(t.a),this.b.copy(t.b),this.c.copy(t.c),this}getArea(){return Sw.subVectors(this.c,this.b),Cw.subVectors(this.a,this.b),.5*Sw.cross(Cw).length()}getMidpoint(t){return t.addVectors(this.a,this.b).add(this.c).multiplyScalar(1/3)}getNormal(t){return Bw.getNormal(this.a,this.b,this.c,t)}getPlane(t){return t.setFromCoplanarPoints(this.a,this.b,this.c)}getBarycoord(t,e){return Bw.getBarycoord(t,this.a,this.b,this.c,e)}getUV(t,e,n,i,s){return Bw.getUV(t,this.a,this.b,this.c,e,n,i,s)}containsPoint(t){return Bw.containsPoint(t,this.a,this.b,this.c)}isFrontFacing(t){return Bw.isFrontFacing(this.a,this.b,this.c,t)}intersectsBox(t){return t.intersectsTriangle(this)}closestPointToPoint(t,e){const n=this.a,i=this.b,s=this.c;let r,o;Ow.subVectors(i,n),Pw.subVectors(s,n),Iw.subVectors(t,n);const a=Ow.dot(Iw),l=Pw.dot(Iw);if(a<=0&&l<=0)return e.copy(n);Fw.subVectors(t,i);const c=Ow.dot(Fw),h=Pw.dot(Fw);if(c>=0&&h<=c)return e.copy(i);const u=a*h-c*l;if(u<=0&&a>=0&&c<=0)return r=a/(a-c),e.copy(n).addScaledVector(Ow,r);Dw.subVectors(t,s);const d=Ow.dot(Dw),p=Pw.dot(Dw);if(p>=0&&d<=p)return e.copy(s);const _=d*l-a*p;if(_<=0&&l>=0&&p<=0)return o=l/(l-p),e.copy(n).addScaledVector(Pw,o);const m=c*p-d*h;if(m<=0&&h-c>=0&&d-p>=0)return Rw.subVectors(s,i),o=(h-c)/(h-c+(d-p)),e.copy(i).addScaledVector(Rw,o);const f=1/(m+_+u);return r=_*f,o=u*f,e.copy(n).addScaledVector(Ow,r).addScaledVector(Pw,o)}equals(t){return t.a.equals(this.a)&&t.b.equals(this.b)&&t.c.equals(this.c)}}let zw=0;class kw extends Zx{constructor(){super(),Object.defineProperty(this,\\\\\\\"id\\\\\\\",{value:zw++}),this.uuid=ib(),this.name=\\\\\\\"\\\\\\\",this.type=\\\\\\\"Material\\\\\\\",this.fog=!0,this.blending=1,this.side=0,this.vertexColors=!1,this.opacity=1,this.format=Rx,this.transparent=!1,this.blendSrc=204,this.blendDst=205,this.blendEquation=hx,this.blendSrcAlpha=null,this.blendDstAlpha=null,this.blendEquationAlpha=null,this.depthFunc=3,this.depthTest=!0,this.depthWrite=!0,this.stencilWriteMask=255,this.stencilFunc=519,this.stencilRef=0,this.stencilFuncMask=255,this.stencilFail=Xx,this.stencilZFail=Xx,this.stencilZPass=Xx,this.stencilWrite=!1,this.clippingPlanes=null,this.clipIntersection=!1,this.clipShadows=!1,this.shadowSide=null,this.colorWrite=!0,this.precision=null,this.polygonOffset=!1,this.polygonOffsetFactor=0,this.polygonOffsetUnits=0,this.dithering=!1,this.alphaToCoverage=!1,this.premultipliedAlpha=!1,this.visible=!0,this.toneMapped=!0,this.userData={},this.version=0,this._alphaTest=0}get alphaTest(){return this._alphaTest}set alphaTest(t){this._alphaTest>0!=t>0&&this.version++,this._alphaTest=t}onBuild(){}onBeforeRender(){}onBeforeCompile(){}customProgramCacheKey(){return this.onBeforeCompile.toString()}setValues(t){if(void 0!==t)for(const e in t){const n=t[e];if(void 0===n){console.warn(\\\\\\\"THREE.Material: '\\\\\\\"+e+\\\\\\\"' parameter is undefined.\\\\\\\");continue}if(\\\\\\\"shading\\\\\\\"===e){console.warn(\\\\\\\"THREE.\\\\\\\"+this.type+\\\\\\\": .shading has been removed. Use the boolean .flatShading instead.\\\\\\\"),this.flatShading=1===n;continue}const i=this[e];void 0!==i?i&&i.isColor?i.set(n):i&&i.isVector3&&n&&n.isVector3?i.copy(n):this[e]=n:console.warn(\\\\\\\"THREE.\\\\\\\"+this.type+\\\\\\\": '\\\\\\\"+e+\\\\\\\"' is not a property of this material.\\\\\\\")}}toJSON(t){const e=void 0===t||\\\\\\\"string\\\\\\\"==typeof t;e&&(t={textures:{},images:{}});const n={metadata:{version:4.5,type:\\\\\\\"Material\\\\\\\",generator:\\\\\\\"Material.toJSON\\\\\\\"}};function i(t){const e=[];for(const n in t){const i=t[n];delete i.metadata,e.push(i)}return e}if(n.uuid=this.uuid,n.type=this.type,\\\\\\\"\\\\\\\"!==this.name&&(n.name=this.name),this.color&&this.color.isColor&&(n.color=this.color.getHex()),void 0!==this.roughness&&(n.roughness=this.roughness),void 0!==this.metalness&&(n.metalness=this.metalness),void 0!==this.sheen&&(n.sheen=this.sheen),this.sheenTint&&this.sheenTint.isColor&&(n.sheenTint=this.sheenTint.getHex()),void 0!==this.sheenRoughness&&(n.sheenRoughness=this.sheenRoughness),this.emissive&&this.emissive.isColor&&(n.emissive=this.emissive.getHex()),this.emissiveIntensity&&1!==this.emissiveIntensity&&(n.emissiveIntensity=this.emissiveIntensity),this.specular&&this.specular.isColor&&(n.specular=this.specular.getHex()),void 0!==this.specularIntensity&&(n.specularIntensity=this.specularIntensity),this.specularTint&&this.specularTint.isColor&&(n.specularTint=this.specularTint.getHex()),void 0!==this.shininess&&(n.shininess=this.shininess),void 0!==this.clearcoat&&(n.clearcoat=this.clearcoat),void 0!==this.clearcoatRoughness&&(n.clearcoatRoughness=this.clearcoatRoughness),this.clearcoatMap&&this.clearcoatMap.isTexture&&(n.clearcoatMap=this.clearcoatMap.toJSON(t).uuid),this.clearcoatRoughnessMap&&this.clearcoatRoughnessMap.isTexture&&(n.clearcoatRoughnessMap=this.clearcoatRoughnessMap.toJSON(t).uuid),this.clearcoatNormalMap&&this.clearcoatNormalMap.isTexture&&(n.clearcoatNormalMap=this.clearcoatNormalMap.toJSON(t).uuid,n.clearcoatNormalScale=this.clearcoatNormalScale.toArray()),this.map&&this.map.isTexture&&(n.map=this.map.toJSON(t).uuid),this.matcap&&this.matcap.isTexture&&(n.matcap=this.matcap.toJSON(t).uuid),this.alphaMap&&this.alphaMap.isTexture&&(n.alphaMap=this.alphaMap.toJSON(t).uuid),this.lightMap&&this.lightMap.isTexture&&(n.lightMap=this.lightMap.toJSON(t).uuid,n.lightMapIntensity=this.lightMapIntensity),this.aoMap&&this.aoMap.isTexture&&(n.aoMap=this.aoMap.toJSON(t).uuid,n.aoMapIntensity=this.aoMapIntensity),this.bumpMap&&this.bumpMap.isTexture&&(n.bumpMap=this.bumpMap.toJSON(t).uuid,n.bumpScale=this.bumpScale),this.normalMap&&this.normalMap.isTexture&&(n.normalMap=this.normalMap.toJSON(t).uuid,n.normalMapType=this.normalMapType,n.normalScale=this.normalScale.toArray()),this.displacementMap&&this.displacementMap.isTexture&&(n.displacementMap=this.displacementMap.toJSON(t).uuid,n.displacementScale=this.displacementScale,n.displacementBias=this.displacementBias),this.roughnessMap&&this.roughnessMap.isTexture&&(n.roughnessMap=this.roughnessMap.toJSON(t).uuid),this.metalnessMap&&this.metalnessMap.isTexture&&(n.metalnessMap=this.metalnessMap.toJSON(t).uuid),this.emissiveMap&&this.emissiveMap.isTexture&&(n.emissiveMap=this.emissiveMap.toJSON(t).uuid),this.specularMap&&this.specularMap.isTexture&&(n.specularMap=this.specularMap.toJSON(t).uuid),this.specularIntensityMap&&this.specularIntensityMap.isTexture&&(n.specularIntensityMap=this.specularIntensityMap.toJSON(t).uuid),this.specularTintMap&&this.specularTintMap.isTexture&&(n.specularTintMap=this.specularTintMap.toJSON(t).uuid),this.envMap&&this.envMap.isTexture&&(n.envMap=this.envMap.toJSON(t).uuid,void 0!==this.combine&&(n.combine=this.combine)),void 0!==this.envMapIntensity&&(n.envMapIntensity=this.envMapIntensity),void 0!==this.reflectivity&&(n.reflectivity=this.reflectivity),void 0!==this.refractionRatio&&(n.refractionRatio=this.refractionRatio),this.gradientMap&&this.gradientMap.isTexture&&(n.gradientMap=this.gradientMap.toJSON(t).uuid),void 0!==this.transmission&&(n.transmission=this.transmission),this.transmissionMap&&this.transmissionMap.isTexture&&(n.transmissionMap=this.transmissionMap.toJSON(t).uuid),void 0!==this.thickness&&(n.thickness=this.thickness),this.thicknessMap&&this.thicknessMap.isTexture&&(n.thicknessMap=this.thicknessMap.toJSON(t).uuid),void 0!==this.attenuationDistance&&(n.attenuationDistance=this.attenuationDistance),void 0!==this.attenuationTint&&(n.attenuationTint=this.attenuationTint.getHex()),void 0!==this.size&&(n.size=this.size),null!==this.shadowSide&&(n.shadowSide=this.shadowSide),void 0!==this.sizeAttenuation&&(n.sizeAttenuation=this.sizeAttenuation),1!==this.blending&&(n.blending=this.blending),0!==this.side&&(n.side=this.side),this.vertexColors&&(n.vertexColors=!0),this.opacity<1&&(n.opacity=this.opacity),this.format!==Rx&&(n.format=this.format),!0===this.transparent&&(n.transparent=this.transparent),n.depthFunc=this.depthFunc,n.depthTest=this.depthTest,n.depthWrite=this.depthWrite,n.colorWrite=this.colorWrite,n.stencilWrite=this.stencilWrite,n.stencilWriteMask=this.stencilWriteMask,n.stencilFunc=this.stencilFunc,n.stencilRef=this.stencilRef,n.stencilFuncMask=this.stencilFuncMask,n.stencilFail=this.stencilFail,n.stencilZFail=this.stencilZFail,n.stencilZPass=this.stencilZPass,this.rotation&&0!==this.rotation&&(n.rotation=this.rotation),!0===this.polygonOffset&&(n.polygonOffset=!0),0!==this.polygonOffsetFactor&&(n.polygonOffsetFactor=this.polygonOffsetFactor),0!==this.polygonOffsetUnits&&(n.polygonOffsetUnits=this.polygonOffsetUnits),this.linewidth&&1!==this.linewidth&&(n.linewidth=this.linewidth),void 0!==this.dashSize&&(n.dashSize=this.dashSize),void 0!==this.gapSize&&(n.gapSize=this.gapSize),void 0!==this.scale&&(n.scale=this.scale),!0===this.dithering&&(n.dithering=!0),this.alphaTest>0&&(n.alphaTest=this.alphaTest),!0===this.alphaToCoverage&&(n.alphaToCoverage=this.alphaToCoverage),!0===this.premultipliedAlpha&&(n.premultipliedAlpha=this.premultipliedAlpha),!0===this.wireframe&&(n.wireframe=this.wireframe),this.wireframeLinewidth>1&&(n.wireframeLinewidth=this.wireframeLinewidth),\\\\\\\"round\\\\\\\"!==this.wireframeLinecap&&(n.wireframeLinecap=this.wireframeLinecap),\\\\\\\"round\\\\\\\"!==this.wireframeLinejoin&&(n.wireframeLinejoin=this.wireframeLinejoin),!0===this.flatShading&&(n.flatShading=this.flatShading),!1===this.visible&&(n.visible=!1),!1===this.toneMapped&&(n.toneMapped=!1),\\\\\\\"{}\\\\\\\"!==JSON.stringify(this.userData)&&(n.userData=this.userData),e){const e=i(t.textures),s=i(t.images);e.length>0&&(n.textures=e),s.length>0&&(n.images=s)}return n}clone(){return(new this.constructor).copy(this)}copy(t){this.name=t.name,this.fog=t.fog,this.blending=t.blending,this.side=t.side,this.vertexColors=t.vertexColors,this.opacity=t.opacity,this.format=t.format,this.transparent=t.transparent,this.blendSrc=t.blendSrc,this.blendDst=t.blendDst,this.blendEquation=t.blendEquation,this.blendSrcAlpha=t.blendSrcAlpha,this.blendDstAlpha=t.blendDstAlpha,this.blendEquationAlpha=t.blendEquationAlpha,this.depthFunc=t.depthFunc,this.depthTest=t.depthTest,this.depthWrite=t.depthWrite,this.stencilWriteMask=t.stencilWriteMask,this.stencilFunc=t.stencilFunc,this.stencilRef=t.stencilRef,this.stencilFuncMask=t.stencilFuncMask,this.stencilFail=t.stencilFail,this.stencilZFail=t.stencilZFail,this.stencilZPass=t.stencilZPass,this.stencilWrite=t.stencilWrite;const e=t.clippingPlanes;let n=null;if(null!==e){const t=e.length;n=new Array(t);for(let i=0;i!==t;++i)n[i]=e[i].clone()}return this.clippingPlanes=n,this.clipIntersection=t.clipIntersection,this.clipShadows=t.clipShadows,this.shadowSide=t.shadowSide,this.colorWrite=t.colorWrite,this.precision=t.precision,this.polygonOffset=t.polygonOffset,this.polygonOffsetFactor=t.polygonOffsetFactor,this.polygonOffsetUnits=t.polygonOffsetUnits,this.dithering=t.dithering,this.alphaTest=t.alphaTest,this.alphaToCoverage=t.alphaToCoverage,this.premultipliedAlpha=t.premultipliedAlpha,this.visible=t.visible,this.toneMapped=t.toneMapped,this.userData=JSON.parse(JSON.stringify(t.userData)),this}dispose(){this.dispatchEvent({type:\\\\\\\"dispose\\\\\\\"})}set needsUpdate(t){!0===t&&this.version++}}kw.prototype.isMaterial=!0;const Uw={aliceblue:15792383,antiquewhite:16444375,aqua:65535,aquamarine:8388564,azure:15794175,beige:16119260,bisque:16770244,black:0,blanchedalmond:16772045,blue:255,blueviolet:9055202,brown:10824234,burlywood:14596231,cadetblue:6266528,chartreuse:8388352,chocolate:13789470,coral:16744272,cornflowerblue:6591981,cornsilk:16775388,crimson:14423100,cyan:65535,darkblue:139,darkcyan:35723,darkgoldenrod:12092939,darkgray:11119017,darkgreen:25600,darkgrey:11119017,darkkhaki:12433259,darkmagenta:9109643,darkolivegreen:5597999,darkorange:16747520,darkorchid:10040012,darkred:9109504,darksalmon:15308410,darkseagreen:9419919,darkslateblue:4734347,darkslategray:3100495,darkslategrey:3100495,darkturquoise:52945,darkviolet:9699539,deeppink:16716947,deepskyblue:49151,dimgray:6908265,dimgrey:6908265,dodgerblue:2003199,firebrick:11674146,floralwhite:16775920,forestgreen:2263842,fuchsia:16711935,gainsboro:14474460,ghostwhite:16316671,gold:16766720,goldenrod:14329120,gray:8421504,green:32768,greenyellow:11403055,grey:8421504,honeydew:15794160,hotpink:16738740,indianred:13458524,indigo:4915330,ivory:16777200,khaki:15787660,lavender:15132410,lavenderblush:16773365,lawngreen:8190976,lemonchiffon:16775885,lightblue:11393254,lightcoral:15761536,lightcyan:14745599,lightgoldenrodyellow:16448210,lightgray:13882323,lightgreen:9498256,lightgrey:13882323,lightpink:16758465,lightsalmon:16752762,lightseagreen:2142890,lightskyblue:8900346,lightslategray:7833753,lightslategrey:7833753,lightsteelblue:11584734,lightyellow:16777184,lime:65280,limegreen:3329330,linen:16445670,magenta:16711935,maroon:8388608,mediumaquamarine:6737322,mediumblue:205,mediumorchid:12211667,mediumpurple:9662683,mediumseagreen:3978097,mediumslateblue:8087790,mediumspringgreen:64154,mediumturquoise:4772300,mediumvioletred:13047173,midnightblue:1644912,mintcream:16121850,mistyrose:16770273,moccasin:16770229,navajowhite:16768685,navy:128,oldlace:16643558,olive:8421376,olivedrab:7048739,orange:16753920,orangered:16729344,orchid:14315734,palegoldenrod:15657130,palegreen:10025880,paleturquoise:11529966,palevioletred:14381203,papayawhip:16773077,peachpuff:16767673,peru:13468991,pink:16761035,plum:14524637,powderblue:11591910,purple:8388736,rebeccapurple:6697881,red:16711680,rosybrown:12357519,royalblue:4286945,saddlebrown:9127187,salmon:16416882,sandybrown:16032864,seagreen:3050327,seashell:16774638,sienna:10506797,silver:12632256,skyblue:8900331,slateblue:6970061,slategray:7372944,slategrey:7372944,snow:16775930,springgreen:65407,steelblue:4620980,tan:13808780,teal:32896,thistle:14204888,tomato:16737095,turquoise:4251856,violet:15631086,wheat:16113331,white:16777215,whitesmoke:16119285,yellow:16776960,yellowgreen:10145074},Gw={h:0,s:0,l:0},Vw={h:0,s:0,l:0};function Hw(t,e,n){return n<0&&(n+=1),n>1&&(n-=1),n<1/6?t+6*(e-t)*n:n<.5?e:n<2/3?t+6*(e-t)*(2/3-n):t}function jw(t){return t<.04045?.0773993808*t:Math.pow(.9478672986*t+.0521327014,2.4)}function Ww(t){return t<.0031308?12.92*t:1.055*Math.pow(t,.41666)-.055}class qw{constructor(t,e,n){return void 0===e&&void 0===n?this.set(t):this.setRGB(t,e,n)}set(t){return t&&t.isColor?this.copy(t):\\\\\\\"number\\\\\\\"==typeof t?this.setHex(t):\\\\\\\"string\\\\\\\"==typeof t&&this.setStyle(t),this}setScalar(t){return this.r=t,this.g=t,this.b=t,this}setHex(t){return t=Math.floor(t),this.r=(t>>16&255)/255,this.g=(t>>8&255)/255,this.b=(255&t)/255,this}setRGB(t,e,n){return this.r=t,this.g=e,this.b=n,this}setHSL(t,e,n){if(t=rb(t,1),e=sb(e,0,1),n=sb(n,0,1),0===e)this.r=this.g=this.b=n;else{const i=n<=.5?n*(1+e):n+e-n*e,s=2*n-i;this.r=Hw(s,i,t+1/3),this.g=Hw(s,i,t),this.b=Hw(s,i,t-1/3)}return this}setStyle(t){function e(e){void 0!==e&&parseFloat(e)<1&&console.warn(\\\\\\\"THREE.Color: Alpha component of \\\\\\\"+t+\\\\\\\" will be ignored.\\\\\\\")}let n;if(n=/^((?:rgb|hsl)a?)\\\\(([^\\\\)]*)\\\\)/.exec(t)){let t;const i=n[1],s=n[2];switch(i){case\\\\\\\"rgb\\\\\\\":case\\\\\\\"rgba\\\\\\\":if(t=/^\\\\s*(\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(s))return this.r=Math.min(255,parseInt(t[1],10))/255,this.g=Math.min(255,parseInt(t[2],10))/255,this.b=Math.min(255,parseInt(t[3],10))/255,e(t[4]),this;if(t=/^\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(s))return this.r=Math.min(100,parseInt(t[1],10))/100,this.g=Math.min(100,parseInt(t[2],10))/100,this.b=Math.min(100,parseInt(t[3],10))/100,e(t[4]),this;break;case\\\\\\\"hsl\\\\\\\":case\\\\\\\"hsla\\\\\\\":if(t=/^\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(s)){const n=parseFloat(t[1])/360,i=parseInt(t[2],10)/100,s=parseInt(t[3],10)/100;return e(t[4]),this.setHSL(n,i,s)}}}else if(n=/^\\\\#([A-Fa-f\\\\d]+)$/.exec(t)){const t=n[1],e=t.length;if(3===e)return this.r=parseInt(t.charAt(0)+t.charAt(0),16)/255,this.g=parseInt(t.charAt(1)+t.charAt(1),16)/255,this.b=parseInt(t.charAt(2)+t.charAt(2),16)/255,this;if(6===e)return this.r=parseInt(t.charAt(0)+t.charAt(1),16)/255,this.g=parseInt(t.charAt(2)+t.charAt(3),16)/255,this.b=parseInt(t.charAt(4)+t.charAt(5),16)/255,this}return t&&t.length>0?this.setColorName(t):this}setColorName(t){const e=Uw[t.toLowerCase()];return void 0!==e?this.setHex(e):console.warn(\\\\\\\"THREE.Color: Unknown color \\\\\\\"+t),this}clone(){return new this.constructor(this.r,this.g,this.b)}copy(t){return this.r=t.r,this.g=t.g,this.b=t.b,this}copyGammaToLinear(t,e=2){return this.r=Math.pow(t.r,e),this.g=Math.pow(t.g,e),this.b=Math.pow(t.b,e),this}copyLinearToGamma(t,e=2){const n=e>0?1/e:1;return this.r=Math.pow(t.r,n),this.g=Math.pow(t.g,n),this.b=Math.pow(t.b,n),this}convertGammaToLinear(t){return this.copyGammaToLinear(this,t),this}convertLinearToGamma(t){return this.copyLinearToGamma(this,t),this}copySRGBToLinear(t){return this.r=jw(t.r),this.g=jw(t.g),this.b=jw(t.b),this}copyLinearToSRGB(t){return this.r=Ww(t.r),this.g=Ww(t.g),this.b=Ww(t.b),this}convertSRGBToLinear(){return this.copySRGBToLinear(this),this}convertLinearToSRGB(){return this.copyLinearToSRGB(this),this}getHex(){return 255*this.r<<16^255*this.g<<8^255*this.b<<0}getHexString(){return(\\\\\\\"000000\\\\\\\"+this.getHex().toString(16)).slice(-6)}getHSL(t){const e=this.r,n=this.g,i=this.b,s=Math.max(e,n,i),r=Math.min(e,n,i);let o,a;const l=(r+s)/2;if(r===s)o=0,a=0;else{const t=s-r;switch(a=l<=.5?t/(s+r):t/(2-s-r),s){case e:o=(n-i)/t+(n65535?Qw:Zw)(t,1):this.index=t,this}getAttribute(t){return this.attributes[t]}setAttribute(t,e){return this.attributes[t]=e,this}deleteAttribute(t){return delete this.attributes[t],this}hasAttribute(t){return void 0!==this.attributes[t]}addGroup(t,e,n=0){this.groups.push({start:t,count:e,materialIndex:n})}clearGroups(){this.groups=[]}setDrawRange(t,e){this.drawRange.start=t,this.drawRange.count=e}applyMatrix4(t){const e=this.attributes.position;void 0!==e&&(e.applyMatrix4(t),e.needsUpdate=!0);const n=this.attributes.normal;if(void 0!==n){const e=(new db).getNormalMatrix(t);n.applyNormalMatrix(e),n.needsUpdate=!0}const i=this.attributes.tangent;return void 0!==i&&(i.transformDirection(t),i.needsUpdate=!0),null!==this.boundingBox&&this.computeBoundingBox(),null!==this.boundingSphere&&this.computeBoundingSphere(),this}applyQuaternion(t){return eT.makeRotationFromQuaternion(t),this.applyMatrix4(eT),this}rotateX(t){return eT.makeRotationX(t),this.applyMatrix4(eT),this}rotateY(t){return eT.makeRotationY(t),this.applyMatrix4(eT),this}rotateZ(t){return eT.makeRotationZ(t),this.applyMatrix4(eT),this}translate(t,e,n){return eT.makeTranslation(t,e,n),this.applyMatrix4(eT),this}scale(t,e,n){return eT.makeScale(t,e,n),this.applyMatrix4(eT),this}lookAt(t){return nT.lookAt(t),nT.updateMatrix(),this.applyMatrix4(nT.matrix),this}center(){return this.computeBoundingBox(),this.boundingBox.getCenter(iT).negate(),this.translate(iT.x,iT.y,iT.z),this}setFromPoints(t){const e=[];for(let n=0,i=t.length;n0&&(t.userData=this.userData),void 0!==this.parameters){const e=this.parameters;for(const n in e)void 0!==e[n]&&(t[n]=e[n]);return t}t.data={attributes:{}};const e=this.index;null!==e&&(t.data.index={type:e.array.constructor.name,array:Array.prototype.slice.call(e.array)});const n=this.attributes;for(const e in n){const i=n[e];t.data.attributes[e]=i.toJSON(t.data)}const i={};let s=!1;for(const e in this.morphAttributes){const n=this.morphAttributes[e],r=[];for(let e=0,i=n.length;e0&&(i[e]=r,s=!0)}s&&(t.data.morphAttributes=i,t.data.morphTargetsRelative=this.morphTargetsRelative);const r=this.groups;r.length>0&&(t.data.groups=JSON.parse(JSON.stringify(r)));const o=this.boundingSphere;return null!==o&&(t.data.boundingSphere={center:o.center.toArray(),radius:o.radius}),t}clone(){return(new this.constructor).copy(this)}copy(t){this.index=null,this.attributes={},this.morphAttributes={},this.groups=[],this.boundingBox=null,this.boundingSphere=null;const e={};this.name=t.name;const n=t.index;null!==n&&this.setIndex(n.clone(e));const i=t.attributes;for(const t in i){const n=i[t];this.setAttribute(t,n.clone(e))}const s=t.morphAttributes;for(const t in s){const n=[],i=s[t];for(let t=0,s=i.length;t0){const t=e[n[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,n=t.length;e0&&console.error(\\\\\\\"THREE.Mesh.updateMorphTargets() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}}raycast(t,e){const n=this.geometry,i=this.material,s=this.matrixWorld;if(void 0===i)return;if(null===n.boundingSphere&&n.computeBoundingSphere(),hT.copy(n.boundingSphere),hT.applyMatrix4(s),!1===t.ray.intersectsSphere(hT))return;if(lT.copy(s).invert(),cT.copy(t.ray).applyMatrix4(lT),null!==n.boundingBox&&!1===cT.intersectsBox(n.boundingBox))return;let r;if(n.isBufferGeometry){const s=n.index,o=n.attributes.position,a=n.morphAttributes.position,l=n.morphTargetsRelative,c=n.attributes.uv,h=n.attributes.uv2,u=n.groups,d=n.drawRange;if(null!==s)if(Array.isArray(i))for(let n=0,p=u.length;nn.far?null:{distance:c,point:AT.clone(),object:t}}(t,e,n,i,uT,dT,pT,TT);if(p){a&&(xT.fromBufferAttribute(a,c),bT.fromBufferAttribute(a,h),wT.fromBufferAttribute(a,u),p.uv=Bw.getUV(TT,uT,dT,pT,xT,bT,wT,new ub)),l&&(xT.fromBufferAttribute(l,c),bT.fromBufferAttribute(l,h),wT.fromBufferAttribute(l,u),p.uv2=Bw.getUV(TT,uT,dT,pT,xT,bT,wT,new ub));const t={a:c,b:h,c:u,normal:new Ab,materialIndex:0};Bw.getNormal(uT,dT,pT,t.normal),p.face=t}return p}MT.prototype.isMesh=!0;class ST extends aT{constructor(t=1,e=1,n=1,i=1,s=1,r=1){super(),this.type=\\\\\\\"BoxGeometry\\\\\\\",this.parameters={width:t,height:e,depth:n,widthSegments:i,heightSegments:s,depthSegments:r};const o=this;i=Math.floor(i),s=Math.floor(s),r=Math.floor(r);const a=[],l=[],c=[],h=[];let u=0,d=0;function p(t,e,n,i,s,r,p,_,m,f,g){const v=r/m,y=p/f,x=r/2,b=p/2,w=_/2,T=m+1,A=f+1;let M=0,E=0;const S=new Ab;for(let r=0;r0?1:-1,c.push(S.x,S.y,S.z),h.push(a/m),h.push(1-r/f),M+=1}}for(let t=0;t0&&(e.defines=this.defines),e.vertexShader=this.vertexShader,e.fragmentShader=this.fragmentShader;const n={};for(const t in this.extensions)!0===this.extensions[t]&&(n[t]=!0);return Object.keys(n).length>0&&(e.extensions=n),e}}OT.prototype.isShaderMaterial=!0;class PT extends Ew{constructor(){super(),this.type=\\\\\\\"Camera\\\\\\\",this.matrixWorldInverse=new ew,this.projectionMatrix=new ew,this.projectionMatrixInverse=new ew}copy(t,e){return super.copy(t,e),this.matrixWorldInverse.copy(t.matrixWorldInverse),this.projectionMatrix.copy(t.projectionMatrix),this.projectionMatrixInverse.copy(t.projectionMatrixInverse),this}getWorldDirection(t){this.updateWorldMatrix(!0,!1);const e=this.matrixWorld.elements;return t.set(-e[8],-e[9],-e[10]).normalize()}updateMatrixWorld(t){super.updateMatrixWorld(t),this.matrixWorldInverse.copy(this.matrixWorld).invert()}updateWorldMatrix(t,e){super.updateWorldMatrix(t,e),this.matrixWorldInverse.copy(this.matrixWorld).invert()}clone(){return(new this.constructor).copy(this)}}PT.prototype.isCamera=!0;class RT extends PT{constructor(t=50,e=1,n=.1,i=2e3){super(),this.type=\\\\\\\"PerspectiveCamera\\\\\\\",this.fov=t,this.zoom=1,this.near=n,this.far=i,this.focus=10,this.aspect=e,this.view=null,this.filmGauge=35,this.filmOffset=0,this.updateProjectionMatrix()}copy(t,e){return super.copy(t,e),this.fov=t.fov,this.zoom=t.zoom,this.near=t.near,this.far=t.far,this.focus=t.focus,this.aspect=t.aspect,this.view=null===t.view?null:Object.assign({},t.view),this.filmGauge=t.filmGauge,this.filmOffset=t.filmOffset,this}setFocalLength(t){const e=.5*this.getFilmHeight()/t;this.fov=2*tb*Math.atan(e),this.updateProjectionMatrix()}getFocalLength(){const t=Math.tan(.5*Kx*this.fov);return.5*this.getFilmHeight()/t}getEffectiveFOV(){return 2*tb*Math.atan(Math.tan(.5*Kx*this.fov)/this.zoom)}getFilmWidth(){return this.filmGauge*Math.min(this.aspect,1)}getFilmHeight(){return this.filmGauge/Math.max(this.aspect,1)}setViewOffset(t,e,n,i,s,r){this.aspect=t/e,null===this.view&&(this.view={enabled:!0,fullWidth:1,fullHeight:1,offsetX:0,offsetY:0,width:1,height:1}),this.view.enabled=!0,this.view.fullWidth=t,this.view.fullHeight=e,this.view.offsetX=n,this.view.offsetY=i,this.view.width=s,this.view.height=r,this.updateProjectionMatrix()}clearViewOffset(){null!==this.view&&(this.view.enabled=!1),this.updateProjectionMatrix()}updateProjectionMatrix(){const t=this.near;let e=t*Math.tan(.5*Kx*this.fov)/this.zoom,n=2*e,i=this.aspect*n,s=-.5*i;const r=this.view;if(null!==this.view&&this.view.enabled){const t=r.fullWidth,o=r.fullHeight;s+=r.offsetX*i/t,e-=r.offsetY*n/o,i*=r.width/t,n*=r.height/o}const o=this.filmOffset;0!==o&&(s+=t*o/this.getFilmWidth()),this.projectionMatrix.makePerspective(s,s+i,e,e-n,t,this.far),this.projectionMatrixInverse.copy(this.projectionMatrix).invert()}toJSON(t){const e=super.toJSON(t);return e.object.fov=this.fov,e.object.zoom=this.zoom,e.object.near=this.near,e.object.far=this.far,e.object.focus=this.focus,e.object.aspect=this.aspect,null!==this.view&&(e.object.view=Object.assign({},this.view)),e.object.filmGauge=this.filmGauge,e.object.filmOffset=this.filmOffset,e}}RT.prototype.isPerspectiveCamera=!0;const IT=90;class FT extends Ew{constructor(t,e,n){if(super(),this.type=\\\\\\\"CubeCamera\\\\\\\",!0!==n.isWebGLCubeRenderTarget)return void console.error(\\\\\\\"THREE.CubeCamera: The constructor now expects an instance of WebGLCubeRenderTarget as third parameter.\\\\\\\");this.renderTarget=n;const i=new RT(IT,1,t,e);i.layers=this.layers,i.up.set(0,-1,0),i.lookAt(new Ab(1,0,0)),this.add(i);const s=new RT(IT,1,t,e);s.layers=this.layers,s.up.set(0,-1,0),s.lookAt(new Ab(-1,0,0)),this.add(s);const r=new RT(IT,1,t,e);r.layers=this.layers,r.up.set(0,0,1),r.lookAt(new Ab(0,1,0)),this.add(r);const o=new RT(IT,1,t,e);o.layers=this.layers,o.up.set(0,0,-1),o.lookAt(new Ab(0,-1,0)),this.add(o);const a=new RT(IT,1,t,e);a.layers=this.layers,a.up.set(0,-1,0),a.lookAt(new Ab(0,0,1)),this.add(a);const l=new RT(IT,1,t,e);l.layers=this.layers,l.up.set(0,-1,0),l.lookAt(new Ab(0,0,-1)),this.add(l)}update(t,e){null===this.parent&&this.updateMatrixWorld();const n=this.renderTarget,[i,s,r,o,a,l]=this.children,c=t.xr.enabled,h=t.getRenderTarget();t.xr.enabled=!1;const u=n.texture.generateMipmaps;n.texture.generateMipmaps=!1,t.setRenderTarget(n,0),t.render(e,i),t.setRenderTarget(n,1),t.render(e,s),t.setRenderTarget(n,2),t.render(e,r),t.setRenderTarget(n,3),t.render(e,o),t.setRenderTarget(n,4),t.render(e,a),n.texture.generateMipmaps=u,t.setRenderTarget(n,5),t.render(e,l),t.setRenderTarget(h),t.xr.enabled=c}}class DT extends vb{constructor(t,e,n,i,s,r,o,a,l,c){super(t=void 0!==t?t:[],e=void 0!==e?e:ux,n,i,s,r,o,a,l,c),this.flipY=!1}get images(){return this.image}set images(t){this.image=t}}DT.prototype.isCubeTexture=!0;class BT extends bb{constructor(t,e,n){Number.isInteger(e)&&(console.warn(\\\\\\\"THREE.WebGLCubeRenderTarget: constructor signature is now WebGLCubeRenderTarget( size, options )\\\\\\\"),e=n),super(t,t,e),e=e||{},this.texture=new DT(void 0,e.mapping,e.wrapS,e.wrapT,e.magFilter,e.minFilter,e.format,e.type,e.anisotropy,e.encoding),this.texture.isRenderTargetTexture=!0,this.texture.generateMipmaps=void 0!==e.generateMipmaps&&e.generateMipmaps,this.texture.minFilter=void 0!==e.minFilter?e.minFilter:Tx,this.texture._needsFlipEnvMap=!1}fromEquirectangularTexture(t,e){this.texture.type=e.type,this.texture.format=Rx,this.texture.encoding=e.encoding,this.texture.generateMipmaps=e.generateMipmaps,this.texture.minFilter=e.minFilter,this.texture.magFilter=e.magFilter;const n={uniforms:{tEquirect:{value:null}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvarying vec3 vWorldDirection;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvWorldDirection = transformDirection( position, modelMatrix );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D tEquirect;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvarying vec3 vWorldDirection;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec3 direction = normalize( vWorldDirection );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec2 sampleUV = equirectUv( direction );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor = texture2D( tEquirect, sampleUV );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\\\\"},i=new ST(5,5,5),s=new OT({name:\\\\\\\"CubemapFromEquirect\\\\\\\",uniforms:CT(n.uniforms),vertexShader:n.vertexShader,fragmentShader:n.fragmentShader,side:1,blending:0});s.uniforms.tEquirect.value=e;const r=new MT(i,s),o=e.minFilter;e.minFilter===Mx&&(e.minFilter=Tx);return new FT(1,10,this).update(t,r),e.minFilter=o,r.geometry.dispose(),r.material.dispose(),this}clear(t,e,n,i){const s=t.getRenderTarget();for(let s=0;s<6;s++)t.setRenderTarget(this,s),t.clear(e,n,i);t.setRenderTarget(s)}}BT.prototype.isWebGLCubeRenderTarget=!0;const zT=new Ab,kT=new Ab,UT=new db;class GT{constructor(t=new Ab(1,0,0),e=0){this.normal=t,this.constant=e}set(t,e){return this.normal.copy(t),this.constant=e,this}setComponents(t,e,n,i){return this.normal.set(t,e,n),this.constant=i,this}setFromNormalAndCoplanarPoint(t,e){return this.normal.copy(t),this.constant=-e.dot(this.normal),this}setFromCoplanarPoints(t,e,n){const i=zT.subVectors(n,e).cross(kT.subVectors(t,e)).normalize();return this.setFromNormalAndCoplanarPoint(i,t),this}copy(t){return this.normal.copy(t.normal),this.constant=t.constant,this}normalize(){const t=1/this.normal.length();return this.normal.multiplyScalar(t),this.constant*=t,this}negate(){return this.constant*=-1,this.normal.negate(),this}distanceToPoint(t){return this.normal.dot(t)+this.constant}distanceToSphere(t){return this.distanceToPoint(t.center)-t.radius}projectPoint(t,e){return e.copy(this.normal).multiplyScalar(-this.distanceToPoint(t)).add(t)}intersectLine(t,e){const n=t.delta(zT),i=this.normal.dot(n);if(0===i)return 0===this.distanceToPoint(t.start)?e.copy(t.start):null;const s=-(t.start.dot(this.normal)+this.constant)/i;return s<0||s>1?null:e.copy(n).multiplyScalar(s).add(t.start)}intersectsLine(t){const e=this.distanceToPoint(t.start),n=this.distanceToPoint(t.end);return e<0&&n>0||n<0&&e>0}intersectsBox(t){return t.intersectsPlane(this)}intersectsSphere(t){return t.intersectsPlane(this)}coplanarPoint(t){return t.copy(this.normal).multiplyScalar(-this.constant)}applyMatrix4(t,e){const n=e||UT.getNormalMatrix(t),i=this.coplanarPoint(zT).applyMatrix4(t),s=this.normal.applyMatrix3(n).normalize();return this.constant=-i.dot(s),this}translate(t){return this.constant-=t.dot(this.normal),this}equals(t){return t.normal.equals(this.normal)&&t.constant===this.constant}clone(){return(new this.constructor).copy(this)}}GT.prototype.isPlane=!0;const VT=new qb,HT=new Ab;class jT{constructor(t=new GT,e=new GT,n=new GT,i=new GT,s=new GT,r=new GT){this.planes=[t,e,n,i,s,r]}set(t,e,n,i,s,r){const o=this.planes;return o[0].copy(t),o[1].copy(e),o[2].copy(n),o[3].copy(i),o[4].copy(s),o[5].copy(r),this}copy(t){const e=this.planes;for(let n=0;n<6;n++)e[n].copy(t.planes[n]);return this}setFromProjectionMatrix(t){const e=this.planes,n=t.elements,i=n[0],s=n[1],r=n[2],o=n[3],a=n[4],l=n[5],c=n[6],h=n[7],u=n[8],d=n[9],p=n[10],_=n[11],m=n[12],f=n[13],g=n[14],v=n[15];return e[0].setComponents(o-i,h-a,_-u,v-m).normalize(),e[1].setComponents(o+i,h+a,_+u,v+m).normalize(),e[2].setComponents(o+s,h+l,_+d,v+f).normalize(),e[3].setComponents(o-s,h-l,_-d,v-f).normalize(),e[4].setComponents(o-r,h-c,_-p,v-g).normalize(),e[5].setComponents(o+r,h+c,_+p,v+g).normalize(),this}intersectsObject(t){const e=t.geometry;return null===e.boundingSphere&&e.computeBoundingSphere(),VT.copy(e.boundingSphere).applyMatrix4(t.matrixWorld),this.intersectsSphere(VT)}intersectsSprite(t){return VT.center.set(0,0,0),VT.radius=.7071067811865476,VT.applyMatrix4(t.matrixWorld),this.intersectsSphere(VT)}intersectsSphere(t){const e=this.planes,n=t.center,i=-t.radius;for(let t=0;t<6;t++){if(e[t].distanceToPoint(n)0?t.max.x:t.min.x,HT.y=i.normal.y>0?t.max.y:t.min.y,HT.z=i.normal.z>0?t.max.z:t.min.z,i.distanceToPoint(HT)<0)return!1}return!0}containsPoint(t){const e=this.planes;for(let n=0;n<6;n++)if(e[n].distanceToPoint(t)<0)return!1;return!0}clone(){return(new this.constructor).copy(this)}}function WT(){let t=null,e=!1,n=null,i=null;function s(e,r){n(e,r),i=t.requestAnimationFrame(s)}return{start:function(){!0!==e&&null!==n&&(i=t.requestAnimationFrame(s),e=!0)},stop:function(){t.cancelAnimationFrame(i),e=!1},setAnimationLoop:function(t){n=t},setContext:function(e){t=e}}}function qT(t,e){const n=e.isWebGL2,i=new WeakMap;return{get:function(t){return t.isInterleavedBufferAttribute&&(t=t.data),i.get(t)},remove:function(e){e.isInterleavedBufferAttribute&&(e=e.data);const n=i.get(e);n&&(t.deleteBuffer(n.buffer),i.delete(e))},update:function(e,s){if(e.isGLBufferAttribute){const t=i.get(e);return void((!t||t.version 0.0 ) ? v : 0.5 * inversesqrt( max( 1.0 - x * x, 1e-7 ) ) - v;\\\\n\\\\treturn cross( v1, v2 ) * theta_sintheta;\\\\n}\\\\nvec3 LTC_Evaluate( const in vec3 N, const in vec3 V, const in vec3 P, const in mat3 mInv, const in vec3 rectCoords[ 4 ] ) {\\\\n\\\\tvec3 v1 = rectCoords[ 1 ] - rectCoords[ 0 ];\\\\n\\\\tvec3 v2 = rectCoords[ 3 ] - rectCoords[ 0 ];\\\\n\\\\tvec3 lightNormal = cross( v1, v2 );\\\\n\\\\tif( dot( lightNormal, P - rectCoords[ 0 ] ) < 0.0 ) return vec3( 0.0 );\\\\n\\\\tvec3 T1, T2;\\\\n\\\\tT1 = normalize( V - N * dot( V, N ) );\\\\n\\\\tT2 = - cross( N, T1 );\\\\n\\\\tmat3 mat = mInv * transposeMat3( mat3( T1, T2, N ) );\\\\n\\\\tvec3 coords[ 4 ];\\\\n\\\\tcoords[ 0 ] = mat * ( rectCoords[ 0 ] - P );\\\\n\\\\tcoords[ 1 ] = mat * ( rectCoords[ 1 ] - P );\\\\n\\\\tcoords[ 2 ] = mat * ( rectCoords[ 2 ] - P );\\\\n\\\\tcoords[ 3 ] = mat * ( rectCoords[ 3 ] - P );\\\\n\\\\tcoords[ 0 ] = normalize( coords[ 0 ] );\\\\n\\\\tcoords[ 1 ] = normalize( coords[ 1 ] );\\\\n\\\\tcoords[ 2 ] = normalize( coords[ 2 ] );\\\\n\\\\tcoords[ 3 ] = normalize( coords[ 3 ] );\\\\n\\\\tvec3 vectorFormFactor = vec3( 0.0 );\\\\n\\\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 0 ], coords[ 1 ] );\\\\n\\\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 1 ], coords[ 2 ] );\\\\n\\\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 2 ], coords[ 3 ] );\\\\n\\\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 3 ], coords[ 0 ] );\\\\n\\\\tfloat result = LTC_ClippedSphereFormFactor( vectorFormFactor );\\\\n\\\\treturn vec3( result );\\\\n}\\\\nfloat G_BlinnPhong_Implicit( ) {\\\\n\\\\treturn 0.25;\\\\n}\\\\nfloat D_BlinnPhong( const in float shininess, const in float dotNH ) {\\\\n\\\\treturn RECIPROCAL_PI * ( shininess * 0.5 + 1.0 ) * pow( dotNH, shininess );\\\\n}\\\\nvec3 BRDF_BlinnPhong( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in vec3 specularColor, const in float shininess ) {\\\\n\\\\tvec3 halfDir = normalize( lightDir + viewDir );\\\\n\\\\tfloat dotNH = saturate( dot( normal, halfDir ) );\\\\n\\\\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\\\\n\\\\tvec3 F = F_Schlick( specularColor, 1.0, dotVH );\\\\n\\\\tfloat G = G_BlinnPhong_Implicit( );\\\\n\\\\tfloat D = D_BlinnPhong( shininess, dotNH );\\\\n\\\\treturn F * ( G * D );\\\\n}\\\\n#if defined( USE_SHEEN )\\\\nfloat D_Charlie( float roughness, float dotNH ) {\\\\n\\\\tfloat alpha = pow2( roughness );\\\\n\\\\tfloat invAlpha = 1.0 / alpha;\\\\n\\\\tfloat cos2h = dotNH * dotNH;\\\\n\\\\tfloat sin2h = max( 1.0 - cos2h, 0.0078125 );\\\\n\\\\treturn ( 2.0 + invAlpha ) * pow( sin2h, invAlpha * 0.5 ) / ( 2.0 * PI );\\\\n}\\\\nfloat V_Neubelt( float dotNV, float dotNL ) {\\\\n\\\\treturn saturate( 1.0 / ( 4.0 * ( dotNL + dotNV - dotNL * dotNV ) ) );\\\\n}\\\\nvec3 BRDF_Sheen( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, vec3 sheenTint, const in float sheenRoughness ) {\\\\n\\\\tvec3 halfDir = normalize( lightDir + viewDir );\\\\n\\\\tfloat dotNL = saturate( dot( normal, lightDir ) );\\\\n\\\\tfloat dotNV = saturate( dot( normal, viewDir ) );\\\\n\\\\tfloat dotNH = saturate( dot( normal, halfDir ) );\\\\n\\\\tfloat D = D_Charlie( sheenRoughness, dotNH );\\\\n\\\\tfloat V = V_Neubelt( dotNV, dotNL );\\\\n\\\\treturn sheenTint * ( D * V );\\\\n}\\\\n#endif\\\\\\\",bumpmap_pars_fragment:\\\\\\\"#ifdef USE_BUMPMAP\\\\n\\\\tuniform sampler2D bumpMap;\\\\n\\\\tuniform float bumpScale;\\\\n\\\\tvec2 dHdxy_fwd() {\\\\n\\\\t\\\\tvec2 dSTdx = dFdx( vUv );\\\\n\\\\t\\\\tvec2 dSTdy = dFdy( vUv );\\\\n\\\\t\\\\tfloat Hll = bumpScale * texture2D( bumpMap, vUv ).x;\\\\n\\\\t\\\\tfloat dBx = bumpScale * texture2D( bumpMap, vUv + dSTdx ).x - Hll;\\\\n\\\\t\\\\tfloat dBy = bumpScale * texture2D( bumpMap, vUv + dSTdy ).x - Hll;\\\\n\\\\t\\\\treturn vec2( dBx, dBy );\\\\n\\\\t}\\\\n\\\\tvec3 perturbNormalArb( vec3 surf_pos, vec3 surf_norm, vec2 dHdxy, float faceDirection ) {\\\\n\\\\t\\\\tvec3 vSigmaX = vec3( dFdx( surf_pos.x ), dFdx( surf_pos.y ), dFdx( surf_pos.z ) );\\\\n\\\\t\\\\tvec3 vSigmaY = vec3( dFdy( surf_pos.x ), dFdy( surf_pos.y ), dFdy( surf_pos.z ) );\\\\n\\\\t\\\\tvec3 vN = surf_norm;\\\\n\\\\t\\\\tvec3 R1 = cross( vSigmaY, vN );\\\\n\\\\t\\\\tvec3 R2 = cross( vN, vSigmaX );\\\\n\\\\t\\\\tfloat fDet = dot( vSigmaX, R1 ) * faceDirection;\\\\n\\\\t\\\\tvec3 vGrad = sign( fDet ) * ( dHdxy.x * R1 + dHdxy.y * R2 );\\\\n\\\\t\\\\treturn normalize( abs( fDet ) * surf_norm - vGrad );\\\\n\\\\t}\\\\n#endif\\\\\\\",clipping_planes_fragment:\\\\\\\"#if NUM_CLIPPING_PLANES > 0\\\\n\\\\tvec4 plane;\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < UNION_CLIPPING_PLANES; i ++ ) {\\\\n\\\\t\\\\tplane = clippingPlanes[ i ];\\\\n\\\\t\\\\tif ( dot( vClipPosition, plane.xyz ) > plane.w ) discard;\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\t#if UNION_CLIPPING_PLANES < NUM_CLIPPING_PLANES\\\\n\\\\t\\\\tbool clipped = true;\\\\n\\\\t\\\\t#pragma unroll_loop_start\\\\n\\\\t\\\\tfor ( int i = UNION_CLIPPING_PLANES; i < NUM_CLIPPING_PLANES; i ++ ) {\\\\n\\\\t\\\\t\\\\tplane = clippingPlanes[ i ];\\\\n\\\\t\\\\t\\\\tclipped = ( dot( vClipPosition, plane.xyz ) > plane.w ) && clipped;\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\t#pragma unroll_loop_end\\\\n\\\\t\\\\tif ( clipped ) discard;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",clipping_planes_pars_fragment:\\\\\\\"#if NUM_CLIPPING_PLANES > 0\\\\n\\\\tvarying vec3 vClipPosition;\\\\n\\\\tuniform vec4 clippingPlanes[ NUM_CLIPPING_PLANES ];\\\\n#endif\\\\\\\",clipping_planes_pars_vertex:\\\\\\\"#if NUM_CLIPPING_PLANES > 0\\\\n\\\\tvarying vec3 vClipPosition;\\\\n#endif\\\\\\\",clipping_planes_vertex:\\\\\\\"#if NUM_CLIPPING_PLANES > 0\\\\n\\\\tvClipPosition = - mvPosition.xyz;\\\\n#endif\\\\\\\",color_fragment:\\\\\\\"#if defined( USE_COLOR_ALPHA )\\\\n\\\\tdiffuseColor *= vColor;\\\\n#elif defined( USE_COLOR )\\\\n\\\\tdiffuseColor.rgb *= vColor;\\\\n#endif\\\\\\\",color_pars_fragment:\\\\\\\"#if defined( USE_COLOR_ALPHA )\\\\n\\\\tvarying vec4 vColor;\\\\n#elif defined( USE_COLOR )\\\\n\\\\tvarying vec3 vColor;\\\\n#endif\\\\\\\",color_pars_vertex:\\\\\\\"#if defined( USE_COLOR_ALPHA )\\\\n\\\\tvarying vec4 vColor;\\\\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )\\\\n\\\\tvarying vec3 vColor;\\\\n#endif\\\\\\\",color_vertex:\\\\\\\"#if defined( USE_COLOR_ALPHA )\\\\n\\\\tvColor = vec4( 1.0 );\\\\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )\\\\n\\\\tvColor = vec3( 1.0 );\\\\n#endif\\\\n#ifdef USE_COLOR\\\\n\\\\tvColor *= color;\\\\n#endif\\\\n#ifdef USE_INSTANCING_COLOR\\\\n\\\\tvColor.xyz *= instanceColor.xyz;\\\\n#endif\\\\\\\",common:\\\\\\\"#define PI 3.141592653589793\\\\n#define PI2 6.283185307179586\\\\n#define PI_HALF 1.5707963267948966\\\\n#define RECIPROCAL_PI 0.3183098861837907\\\\n#define RECIPROCAL_PI2 0.15915494309189535\\\\n#define EPSILON 1e-6\\\\n#ifndef saturate\\\\n#define saturate( a ) clamp( a, 0.0, 1.0 )\\\\n#endif\\\\n#define whiteComplement( a ) ( 1.0 - saturate( a ) )\\\\nfloat pow2( const in float x ) { return x*x; }\\\\nfloat pow3( const in float x ) { return x*x*x; }\\\\nfloat pow4( const in float x ) { float x2 = x*x; return x2*x2; }\\\\nfloat max3( const in vec3 v ) { return max( max( v.x, v.y ), v.z ); }\\\\nfloat average( const in vec3 color ) { return dot( color, vec3( 0.3333 ) ); }\\\\nhighp float rand( const in vec2 uv ) {\\\\n\\\\tconst highp float a = 12.9898, b = 78.233, c = 43758.5453;\\\\n\\\\thighp float dt = dot( uv.xy, vec2( a,b ) ), sn = mod( dt, PI );\\\\n\\\\treturn fract( sin( sn ) * c );\\\\n}\\\\n#ifdef HIGH_PRECISION\\\\n\\\\tfloat precisionSafeLength( vec3 v ) { return length( v ); }\\\\n#else\\\\n\\\\tfloat precisionSafeLength( vec3 v ) {\\\\n\\\\t\\\\tfloat maxComponent = max3( abs( v ) );\\\\n\\\\t\\\\treturn length( v / maxComponent ) * maxComponent;\\\\n\\\\t}\\\\n#endif\\\\nstruct IncidentLight {\\\\n\\\\tvec3 color;\\\\n\\\\tvec3 direction;\\\\n\\\\tbool visible;\\\\n};\\\\nstruct ReflectedLight {\\\\n\\\\tvec3 directDiffuse;\\\\n\\\\tvec3 directSpecular;\\\\n\\\\tvec3 indirectDiffuse;\\\\n\\\\tvec3 indirectSpecular;\\\\n};\\\\nstruct GeometricContext {\\\\n\\\\tvec3 position;\\\\n\\\\tvec3 normal;\\\\n\\\\tvec3 viewDir;\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\tvec3 clearcoatNormal;\\\\n#endif\\\\n};\\\\nvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\\\\n\\\\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\\\\n}\\\\nvec3 inverseTransformDirection( in vec3 dir, in mat4 matrix ) {\\\\n\\\\treturn normalize( ( vec4( dir, 0.0 ) * matrix ).xyz );\\\\n}\\\\nmat3 transposeMat3( const in mat3 m ) {\\\\n\\\\tmat3 tmp;\\\\n\\\\ttmp[ 0 ] = vec3( m[ 0 ].x, m[ 1 ].x, m[ 2 ].x );\\\\n\\\\ttmp[ 1 ] = vec3( m[ 0 ].y, m[ 1 ].y, m[ 2 ].y );\\\\n\\\\ttmp[ 2 ] = vec3( m[ 0 ].z, m[ 1 ].z, m[ 2 ].z );\\\\n\\\\treturn tmp;\\\\n}\\\\nfloat linearToRelativeLuminance( const in vec3 color ) {\\\\n\\\\tvec3 weights = vec3( 0.2126, 0.7152, 0.0722 );\\\\n\\\\treturn dot( weights, color.rgb );\\\\n}\\\\nbool isPerspectiveMatrix( mat4 m ) {\\\\n\\\\treturn m[ 2 ][ 3 ] == - 1.0;\\\\n}\\\\nvec2 equirectUv( in vec3 dir ) {\\\\n\\\\tfloat u = atan( dir.z, dir.x ) * RECIPROCAL_PI2 + 0.5;\\\\n\\\\tfloat v = asin( clamp( dir.y, - 1.0, 1.0 ) ) * RECIPROCAL_PI + 0.5;\\\\n\\\\treturn vec2( u, v );\\\\n}\\\\\\\",cube_uv_reflection_fragment:\\\\\\\"#ifdef ENVMAP_TYPE_CUBE_UV\\\\n\\\\t#define cubeUV_maxMipLevel 8.0\\\\n\\\\t#define cubeUV_minMipLevel 4.0\\\\n\\\\t#define cubeUV_maxTileSize 256.0\\\\n\\\\t#define cubeUV_minTileSize 16.0\\\\n\\\\tfloat getFace( vec3 direction ) {\\\\n\\\\t\\\\tvec3 absDirection = abs( direction );\\\\n\\\\t\\\\tfloat face = - 1.0;\\\\n\\\\t\\\\tif ( absDirection.x > absDirection.z ) {\\\\n\\\\t\\\\t\\\\tif ( absDirection.x > absDirection.y )\\\\n\\\\t\\\\t\\\\t\\\\tface = direction.x > 0.0 ? 0.0 : 3.0;\\\\n\\\\t\\\\t\\\\telse\\\\n\\\\t\\\\t\\\\t\\\\tface = direction.y > 0.0 ? 1.0 : 4.0;\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tif ( absDirection.z > absDirection.y )\\\\n\\\\t\\\\t\\\\t\\\\tface = direction.z > 0.0 ? 2.0 : 5.0;\\\\n\\\\t\\\\t\\\\telse\\\\n\\\\t\\\\t\\\\t\\\\tface = direction.y > 0.0 ? 1.0 : 4.0;\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\treturn face;\\\\n\\\\t}\\\\n\\\\tvec2 getUV( vec3 direction, float face ) {\\\\n\\\\t\\\\tvec2 uv;\\\\n\\\\t\\\\tif ( face == 0.0 ) {\\\\n\\\\t\\\\t\\\\tuv = vec2( direction.z, direction.y ) / abs( direction.x );\\\\n\\\\t\\\\t} else if ( face == 1.0 ) {\\\\n\\\\t\\\\t\\\\tuv = vec2( - direction.x, - direction.z ) / abs( direction.y );\\\\n\\\\t\\\\t} else if ( face == 2.0 ) {\\\\n\\\\t\\\\t\\\\tuv = vec2( - direction.x, direction.y ) / abs( direction.z );\\\\n\\\\t\\\\t} else if ( face == 3.0 ) {\\\\n\\\\t\\\\t\\\\tuv = vec2( - direction.z, direction.y ) / abs( direction.x );\\\\n\\\\t\\\\t} else if ( face == 4.0 ) {\\\\n\\\\t\\\\t\\\\tuv = vec2( - direction.x, direction.z ) / abs( direction.y );\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tuv = vec2( direction.x, direction.y ) / abs( direction.z );\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\treturn 0.5 * ( uv + 1.0 );\\\\n\\\\t}\\\\n\\\\tvec3 bilinearCubeUV( sampler2D envMap, vec3 direction, float mipInt ) {\\\\n\\\\t\\\\tfloat face = getFace( direction );\\\\n\\\\t\\\\tfloat filterInt = max( cubeUV_minMipLevel - mipInt, 0.0 );\\\\n\\\\t\\\\tmipInt = max( mipInt, cubeUV_minMipLevel );\\\\n\\\\t\\\\tfloat faceSize = exp2( mipInt );\\\\n\\\\t\\\\tfloat texelSize = 1.0 / ( 3.0 * cubeUV_maxTileSize );\\\\n\\\\t\\\\tvec2 uv = getUV( direction, face ) * ( faceSize - 1.0 );\\\\n\\\\t\\\\tvec2 f = fract( uv );\\\\n\\\\t\\\\tuv += 0.5 - f;\\\\n\\\\t\\\\tif ( face > 2.0 ) {\\\\n\\\\t\\\\t\\\\tuv.y += faceSize;\\\\n\\\\t\\\\t\\\\tface -= 3.0;\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\tuv.x += face * faceSize;\\\\n\\\\t\\\\tif ( mipInt < cubeUV_maxMipLevel ) {\\\\n\\\\t\\\\t\\\\tuv.y += 2.0 * cubeUV_maxTileSize;\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\tuv.y += filterInt * 2.0 * cubeUV_minTileSize;\\\\n\\\\t\\\\tuv.x += 3.0 * max( 0.0, cubeUV_maxTileSize - 2.0 * faceSize );\\\\n\\\\t\\\\tuv *= texelSize;\\\\n\\\\t\\\\tvec3 tl = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\\\n\\\\t\\\\tuv.x += texelSize;\\\\n\\\\t\\\\tvec3 tr = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\\\n\\\\t\\\\tuv.y += texelSize;\\\\n\\\\t\\\\tvec3 br = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\\\n\\\\t\\\\tuv.x -= texelSize;\\\\n\\\\t\\\\tvec3 bl = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\\\n\\\\t\\\\tvec3 tm = mix( tl, tr, f.x );\\\\n\\\\t\\\\tvec3 bm = mix( bl, br, f.x );\\\\n\\\\t\\\\treturn mix( tm, bm, f.y );\\\\n\\\\t}\\\\n\\\\t#define r0 1.0\\\\n\\\\t#define v0 0.339\\\\n\\\\t#define m0 - 2.0\\\\n\\\\t#define r1 0.8\\\\n\\\\t#define v1 0.276\\\\n\\\\t#define m1 - 1.0\\\\n\\\\t#define r4 0.4\\\\n\\\\t#define v4 0.046\\\\n\\\\t#define m4 2.0\\\\n\\\\t#define r5 0.305\\\\n\\\\t#define v5 0.016\\\\n\\\\t#define m5 3.0\\\\n\\\\t#define r6 0.21\\\\n\\\\t#define v6 0.0038\\\\n\\\\t#define m6 4.0\\\\n\\\\tfloat roughnessToMip( float roughness ) {\\\\n\\\\t\\\\tfloat mip = 0.0;\\\\n\\\\t\\\\tif ( roughness >= r1 ) {\\\\n\\\\t\\\\t\\\\tmip = ( r0 - roughness ) * ( m1 - m0 ) / ( r0 - r1 ) + m0;\\\\n\\\\t\\\\t} else if ( roughness >= r4 ) {\\\\n\\\\t\\\\t\\\\tmip = ( r1 - roughness ) * ( m4 - m1 ) / ( r1 - r4 ) + m1;\\\\n\\\\t\\\\t} else if ( roughness >= r5 ) {\\\\n\\\\t\\\\t\\\\tmip = ( r4 - roughness ) * ( m5 - m4 ) / ( r4 - r5 ) + m4;\\\\n\\\\t\\\\t} else if ( roughness >= r6 ) {\\\\n\\\\t\\\\t\\\\tmip = ( r5 - roughness ) * ( m6 - m5 ) / ( r5 - r6 ) + m5;\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tmip = - 2.0 * log2( 1.16 * roughness );\\\\t\\\\t}\\\\n\\\\t\\\\treturn mip;\\\\n\\\\t}\\\\n\\\\tvec4 textureCubeUV( sampler2D envMap, vec3 sampleDir, float roughness ) {\\\\n\\\\t\\\\tfloat mip = clamp( roughnessToMip( roughness ), m0, cubeUV_maxMipLevel );\\\\n\\\\t\\\\tfloat mipF = fract( mip );\\\\n\\\\t\\\\tfloat mipInt = floor( mip );\\\\n\\\\t\\\\tvec3 color0 = bilinearCubeUV( envMap, sampleDir, mipInt );\\\\n\\\\t\\\\tif ( mipF == 0.0 ) {\\\\n\\\\t\\\\t\\\\treturn vec4( color0, 1.0 );\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tvec3 color1 = bilinearCubeUV( envMap, sampleDir, mipInt + 1.0 );\\\\n\\\\t\\\\t\\\\treturn vec4( mix( color0, color1, mipF ), 1.0 );\\\\n\\\\t\\\\t}\\\\n\\\\t}\\\\n#endif\\\\\\\",defaultnormal_vertex:\\\\\\\"vec3 transformedNormal = objectNormal;\\\\n#ifdef USE_INSTANCING\\\\n\\\\tmat3 m = mat3( instanceMatrix );\\\\n\\\\ttransformedNormal /= vec3( dot( m[ 0 ], m[ 0 ] ), dot( m[ 1 ], m[ 1 ] ), dot( m[ 2 ], m[ 2 ] ) );\\\\n\\\\ttransformedNormal = m * transformedNormal;\\\\n#endif\\\\ntransformedNormal = normalMatrix * transformedNormal;\\\\n#ifdef FLIP_SIDED\\\\n\\\\ttransformedNormal = - transformedNormal;\\\\n#endif\\\\n#ifdef USE_TANGENT\\\\n\\\\tvec3 transformedTangent = ( modelViewMatrix * vec4( objectTangent, 0.0 ) ).xyz;\\\\n\\\\t#ifdef FLIP_SIDED\\\\n\\\\t\\\\ttransformedTangent = - transformedTangent;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",displacementmap_pars_vertex:\\\\\\\"#ifdef USE_DISPLACEMENTMAP\\\\n\\\\tuniform sampler2D displacementMap;\\\\n\\\\tuniform float displacementScale;\\\\n\\\\tuniform float displacementBias;\\\\n#endif\\\\\\\",displacementmap_vertex:\\\\\\\"#ifdef USE_DISPLACEMENTMAP\\\\n\\\\ttransformed += normalize( objectNormal ) * ( texture2D( displacementMap, vUv ).x * displacementScale + displacementBias );\\\\n#endif\\\\\\\",emissivemap_fragment:\\\\\\\"#ifdef USE_EMISSIVEMAP\\\\n\\\\tvec4 emissiveColor = texture2D( emissiveMap, vUv );\\\\n\\\\temissiveColor.rgb = emissiveMapTexelToLinear( emissiveColor ).rgb;\\\\n\\\\ttotalEmissiveRadiance *= emissiveColor.rgb;\\\\n#endif\\\\\\\",emissivemap_pars_fragment:\\\\\\\"#ifdef USE_EMISSIVEMAP\\\\n\\\\tuniform sampler2D emissiveMap;\\\\n#endif\\\\\\\",encodings_fragment:\\\\\\\"gl_FragColor = linearToOutputTexel( gl_FragColor );\\\\\\\",encodings_pars_fragment:\\\\\\\"\\\\nvec4 LinearToLinear( in vec4 value ) {\\\\n\\\\treturn value;\\\\n}\\\\nvec4 GammaToLinear( in vec4 value, in float gammaFactor ) {\\\\n\\\\treturn vec4( pow( value.rgb, vec3( gammaFactor ) ), value.a );\\\\n}\\\\nvec4 LinearToGamma( in vec4 value, in float gammaFactor ) {\\\\n\\\\treturn vec4( pow( value.rgb, vec3( 1.0 / gammaFactor ) ), value.a );\\\\n}\\\\nvec4 sRGBToLinear( in vec4 value ) {\\\\n\\\\treturn vec4( mix( pow( value.rgb * 0.9478672986 + vec3( 0.0521327014 ), vec3( 2.4 ) ), value.rgb * 0.0773993808, vec3( lessThanEqual( value.rgb, vec3( 0.04045 ) ) ) ), value.a );\\\\n}\\\\nvec4 LinearTosRGB( in vec4 value ) {\\\\n\\\\treturn vec4( mix( pow( value.rgb, vec3( 0.41666 ) ) * 1.055 - vec3( 0.055 ), value.rgb * 12.92, vec3( lessThanEqual( value.rgb, vec3( 0.0031308 ) ) ) ), value.a );\\\\n}\\\\nvec4 RGBEToLinear( in vec4 value ) {\\\\n\\\\treturn vec4( value.rgb * exp2( value.a * 255.0 - 128.0 ), 1.0 );\\\\n}\\\\nvec4 LinearToRGBE( in vec4 value ) {\\\\n\\\\tfloat maxComponent = max( max( value.r, value.g ), value.b );\\\\n\\\\tfloat fExp = clamp( ceil( log2( maxComponent ) ), -128.0, 127.0 );\\\\n\\\\treturn vec4( value.rgb / exp2( fExp ), ( fExp + 128.0 ) / 255.0 );\\\\n}\\\\nvec4 RGBMToLinear( in vec4 value, in float maxRange ) {\\\\n\\\\treturn vec4( value.rgb * value.a * maxRange, 1.0 );\\\\n}\\\\nvec4 LinearToRGBM( in vec4 value, in float maxRange ) {\\\\n\\\\tfloat maxRGB = max( value.r, max( value.g, value.b ) );\\\\n\\\\tfloat M = clamp( maxRGB / maxRange, 0.0, 1.0 );\\\\n\\\\tM = ceil( M * 255.0 ) / 255.0;\\\\n\\\\treturn vec4( value.rgb / ( M * maxRange ), M );\\\\n}\\\\nvec4 RGBDToLinear( in vec4 value, in float maxRange ) {\\\\n\\\\treturn vec4( value.rgb * ( ( maxRange / 255.0 ) / value.a ), 1.0 );\\\\n}\\\\nvec4 LinearToRGBD( in vec4 value, in float maxRange ) {\\\\n\\\\tfloat maxRGB = max( value.r, max( value.g, value.b ) );\\\\n\\\\tfloat D = max( maxRange / maxRGB, 1.0 );\\\\n\\\\tD = clamp( floor( D ) / 255.0, 0.0, 1.0 );\\\\n\\\\treturn vec4( value.rgb * ( D * ( 255.0 / maxRange ) ), D );\\\\n}\\\\nconst mat3 cLogLuvM = mat3( 0.2209, 0.3390, 0.4184, 0.1138, 0.6780, 0.7319, 0.0102, 0.1130, 0.2969 );\\\\nvec4 LinearToLogLuv( in vec4 value ) {\\\\n\\\\tvec3 Xp_Y_XYZp = cLogLuvM * value.rgb;\\\\n\\\\tXp_Y_XYZp = max( Xp_Y_XYZp, vec3( 1e-6, 1e-6, 1e-6 ) );\\\\n\\\\tvec4 vResult;\\\\n\\\\tvResult.xy = Xp_Y_XYZp.xy / Xp_Y_XYZp.z;\\\\n\\\\tfloat Le = 2.0 * log2(Xp_Y_XYZp.y) + 127.0;\\\\n\\\\tvResult.w = fract( Le );\\\\n\\\\tvResult.z = ( Le - ( floor( vResult.w * 255.0 ) ) / 255.0 ) / 255.0;\\\\n\\\\treturn vResult;\\\\n}\\\\nconst mat3 cLogLuvInverseM = mat3( 6.0014, -2.7008, -1.7996, -1.3320, 3.1029, -5.7721, 0.3008, -1.0882, 5.6268 );\\\\nvec4 LogLuvToLinear( in vec4 value ) {\\\\n\\\\tfloat Le = value.z * 255.0 + value.w;\\\\n\\\\tvec3 Xp_Y_XYZp;\\\\n\\\\tXp_Y_XYZp.y = exp2( ( Le - 127.0 ) / 2.0 );\\\\n\\\\tXp_Y_XYZp.z = Xp_Y_XYZp.y / value.y;\\\\n\\\\tXp_Y_XYZp.x = value.x * Xp_Y_XYZp.z;\\\\n\\\\tvec3 vRGB = cLogLuvInverseM * Xp_Y_XYZp.rgb;\\\\n\\\\treturn vec4( max( vRGB, 0.0 ), 1.0 );\\\\n}\\\\\\\",envmap_fragment:\\\\\\\"#ifdef USE_ENVMAP\\\\n\\\\t#ifdef ENV_WORLDPOS\\\\n\\\\t\\\\tvec3 cameraToFrag;\\\\n\\\\t\\\\tif ( isOrthographic ) {\\\\n\\\\t\\\\t\\\\tcameraToFrag = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tcameraToFrag = normalize( vWorldPosition - cameraPosition );\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\\\n\\\\t\\\\t#ifdef ENVMAP_MODE_REFLECTION\\\\n\\\\t\\\\t\\\\tvec3 reflectVec = reflect( cameraToFrag, worldNormal );\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\tvec3 reflectVec = refract( cameraToFrag, worldNormal, refractionRatio );\\\\n\\\\t\\\\t#endif\\\\n\\\\t#else\\\\n\\\\t\\\\tvec3 reflectVec = vReflect;\\\\n\\\\t#endif\\\\n\\\\t#ifdef ENVMAP_TYPE_CUBE\\\\n\\\\t\\\\tvec4 envColor = textureCube( envMap, vec3( flipEnvMap * reflectVec.x, reflectVec.yz ) );\\\\n\\\\t\\\\tenvColor = envMapTexelToLinear( envColor );\\\\n\\\\t#elif defined( ENVMAP_TYPE_CUBE_UV )\\\\n\\\\t\\\\tvec4 envColor = textureCubeUV( envMap, reflectVec, 0.0 );\\\\n\\\\t#else\\\\n\\\\t\\\\tvec4 envColor = vec4( 0.0 );\\\\n\\\\t#endif\\\\n\\\\t#ifdef ENVMAP_BLENDING_MULTIPLY\\\\n\\\\t\\\\toutgoingLight = mix( outgoingLight, outgoingLight * envColor.xyz, specularStrength * reflectivity );\\\\n\\\\t#elif defined( ENVMAP_BLENDING_MIX )\\\\n\\\\t\\\\toutgoingLight = mix( outgoingLight, envColor.xyz, specularStrength * reflectivity );\\\\n\\\\t#elif defined( ENVMAP_BLENDING_ADD )\\\\n\\\\t\\\\toutgoingLight += envColor.xyz * specularStrength * reflectivity;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",envmap_common_pars_fragment:\\\\\\\"#ifdef USE_ENVMAP\\\\n\\\\tuniform float envMapIntensity;\\\\n\\\\tuniform float flipEnvMap;\\\\n\\\\tuniform int maxMipLevel;\\\\n\\\\t#ifdef ENVMAP_TYPE_CUBE\\\\n\\\\t\\\\tuniform samplerCube envMap;\\\\n\\\\t#else\\\\n\\\\t\\\\tuniform sampler2D envMap;\\\\n\\\\t#endif\\\\n\\\\t\\\\n#endif\\\\\\\",envmap_pars_fragment:\\\\\\\"#ifdef USE_ENVMAP\\\\n\\\\tuniform float reflectivity;\\\\n\\\\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG )\\\\n\\\\t\\\\t#define ENV_WORLDPOS\\\\n\\\\t#endif\\\\n\\\\t#ifdef ENV_WORLDPOS\\\\n\\\\t\\\\tvarying vec3 vWorldPosition;\\\\n\\\\t\\\\tuniform float refractionRatio;\\\\n\\\\t#else\\\\n\\\\t\\\\tvarying vec3 vReflect;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",envmap_pars_vertex:\\\\\\\"#ifdef USE_ENVMAP\\\\n\\\\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) ||defined( PHONG )\\\\n\\\\t\\\\t#define ENV_WORLDPOS\\\\n\\\\t#endif\\\\n\\\\t#ifdef ENV_WORLDPOS\\\\n\\\\t\\\\t\\\\n\\\\t\\\\tvarying vec3 vWorldPosition;\\\\n\\\\t#else\\\\n\\\\t\\\\tvarying vec3 vReflect;\\\\n\\\\t\\\\tuniform float refractionRatio;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",envmap_physical_pars_fragment:\\\\\\\"#if defined( USE_ENVMAP )\\\\n\\\\t#ifdef ENVMAP_MODE_REFRACTION\\\\n\\\\t\\\\tuniform float refractionRatio;\\\\n\\\\t#endif\\\\n\\\\tvec3 getIBLIrradiance( const in vec3 normal ) {\\\\n\\\\t\\\\t#if defined( ENVMAP_TYPE_CUBE_UV )\\\\n\\\\t\\\\t\\\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\\\n\\\\t\\\\t\\\\tvec4 envMapColor = textureCubeUV( envMap, worldNormal, 1.0 );\\\\n\\\\t\\\\t\\\\treturn PI * envMapColor.rgb * envMapIntensity;\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\treturn vec3( 0.0 );\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n\\\\tvec3 getIBLRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness ) {\\\\n\\\\t\\\\t#if defined( ENVMAP_TYPE_CUBE_UV )\\\\n\\\\t\\\\t\\\\tvec3 reflectVec;\\\\n\\\\t\\\\t\\\\t#ifdef ENVMAP_MODE_REFLECTION\\\\n\\\\t\\\\t\\\\t\\\\treflectVec = reflect( - viewDir, normal );\\\\n\\\\t\\\\t\\\\t\\\\treflectVec = normalize( mix( reflectVec, normal, roughness * roughness) );\\\\n\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\treflectVec = refract( - viewDir, normal, refractionRatio );\\\\n\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\treflectVec = inverseTransformDirection( reflectVec, viewMatrix );\\\\n\\\\t\\\\t\\\\tvec4 envMapColor = textureCubeUV( envMap, reflectVec, roughness );\\\\n\\\\t\\\\t\\\\treturn envMapColor.rgb * envMapIntensity;\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\treturn vec3( 0.0 );\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n#endif\\\\\\\",envmap_vertex:\\\\\\\"#ifdef USE_ENVMAP\\\\n\\\\t#ifdef ENV_WORLDPOS\\\\n\\\\t\\\\tvWorldPosition = worldPosition.xyz;\\\\n\\\\t#else\\\\n\\\\t\\\\tvec3 cameraToVertex;\\\\n\\\\t\\\\tif ( isOrthographic ) {\\\\n\\\\t\\\\t\\\\tcameraToVertex = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tcameraToVertex = normalize( worldPosition.xyz - cameraPosition );\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\tvec3 worldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\\\\n\\\\t\\\\t#ifdef ENVMAP_MODE_REFLECTION\\\\n\\\\t\\\\t\\\\tvReflect = reflect( cameraToVertex, worldNormal );\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\tvReflect = refract( cameraToVertex, worldNormal, refractionRatio );\\\\n\\\\t\\\\t#endif\\\\n\\\\t#endif\\\\n#endif\\\\\\\",fog_vertex:\\\\\\\"#ifdef USE_FOG\\\\n\\\\tvFogDepth = - mvPosition.z;\\\\n#endif\\\\\\\",fog_pars_vertex:\\\\\\\"#ifdef USE_FOG\\\\n\\\\tvarying float vFogDepth;\\\\n#endif\\\\\\\",fog_fragment:\\\\\\\"#ifdef USE_FOG\\\\n\\\\t#ifdef FOG_EXP2\\\\n\\\\t\\\\tfloat fogFactor = 1.0 - exp( - fogDensity * fogDensity * vFogDepth * vFogDepth );\\\\n\\\\t#else\\\\n\\\\t\\\\tfloat fogFactor = smoothstep( fogNear, fogFar, vFogDepth );\\\\n\\\\t#endif\\\\n\\\\tgl_FragColor.rgb = mix( gl_FragColor.rgb, fogColor, fogFactor );\\\\n#endif\\\\\\\",fog_pars_fragment:\\\\\\\"#ifdef USE_FOG\\\\n\\\\tuniform vec3 fogColor;\\\\n\\\\tvarying float vFogDepth;\\\\n\\\\t#ifdef FOG_EXP2\\\\n\\\\t\\\\tuniform float fogDensity;\\\\n\\\\t#else\\\\n\\\\t\\\\tuniform float fogNear;\\\\n\\\\t\\\\tuniform float fogFar;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",gradientmap_pars_fragment:\\\\\\\"#ifdef USE_GRADIENTMAP\\\\n\\\\tuniform sampler2D gradientMap;\\\\n#endif\\\\nvec3 getGradientIrradiance( vec3 normal, vec3 lightDirection ) {\\\\n\\\\tfloat dotNL = dot( normal, lightDirection );\\\\n\\\\tvec2 coord = vec2( dotNL * 0.5 + 0.5, 0.0 );\\\\n\\\\t#ifdef USE_GRADIENTMAP\\\\n\\\\t\\\\treturn texture2D( gradientMap, coord ).rgb;\\\\n\\\\t#else\\\\n\\\\t\\\\treturn ( coord.x < 0.7 ) ? vec3( 0.7 ) : vec3( 1.0 );\\\\n\\\\t#endif\\\\n}\\\\\\\",lightmap_fragment:\\\\\\\"#ifdef USE_LIGHTMAP\\\\n\\\\tvec4 lightMapTexel = texture2D( lightMap, vUv2 );\\\\n\\\\tvec3 lightMapIrradiance = lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\\\n\\\\t#ifndef PHYSICALLY_CORRECT_LIGHTS\\\\n\\\\t\\\\tlightMapIrradiance *= PI;\\\\n\\\\t#endif\\\\n\\\\treflectedLight.indirectDiffuse += lightMapIrradiance;\\\\n#endif\\\\\\\",lightmap_pars_fragment:\\\\\\\"#ifdef USE_LIGHTMAP\\\\n\\\\tuniform sampler2D lightMap;\\\\n\\\\tuniform float lightMapIntensity;\\\\n#endif\\\\\\\",lights_lambert_vertex:\\\\\\\"vec3 diffuse = vec3( 1.0 );\\\\nGeometricContext geometry;\\\\ngeometry.position = mvPosition.xyz;\\\\ngeometry.normal = normalize( transformedNormal );\\\\ngeometry.viewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( -mvPosition.xyz );\\\\nGeometricContext backGeometry;\\\\nbackGeometry.position = geometry.position;\\\\nbackGeometry.normal = -geometry.normal;\\\\nbackGeometry.viewDir = geometry.viewDir;\\\\nvLightFront = vec3( 0.0 );\\\\nvIndirectFront = vec3( 0.0 );\\\\n#ifdef DOUBLE_SIDED\\\\n\\\\tvLightBack = vec3( 0.0 );\\\\n\\\\tvIndirectBack = vec3( 0.0 );\\\\n#endif\\\\nIncidentLight directLight;\\\\nfloat dotNL;\\\\nvec3 directLightColor_Diffuse;\\\\nvIndirectFront += getAmbientLightIrradiance( ambientLightColor );\\\\nvIndirectFront += getLightProbeIrradiance( lightProbe, geometry.normal );\\\\n#ifdef DOUBLE_SIDED\\\\n\\\\tvIndirectBack += getAmbientLightIrradiance( ambientLightColor );\\\\n\\\\tvIndirectBack += getLightProbeIrradiance( lightProbe, backGeometry.normal );\\\\n#endif\\\\n#if NUM_POINT_LIGHTS > 0\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\\\\n\\\\t\\\\tgetPointLightInfo( pointLights[ i ], geometry, directLight );\\\\n\\\\t\\\\tdotNL = dot( geometry.normal, directLight.direction );\\\\n\\\\t\\\\tdirectLightColor_Diffuse = directLight.color;\\\\n\\\\t\\\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\t\\\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n#endif\\\\n#if NUM_SPOT_LIGHTS > 0\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\\\\n\\\\t\\\\tgetSpotLightInfo( spotLights[ i ], geometry, directLight );\\\\n\\\\t\\\\tdotNL = dot( geometry.normal, directLight.direction );\\\\n\\\\t\\\\tdirectLightColor_Diffuse = directLight.color;\\\\n\\\\t\\\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\t\\\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n#endif\\\\n#if NUM_DIR_LIGHTS > 0\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\\\\n\\\\t\\\\tgetDirectionalLightInfo( directionalLights[ i ], geometry, directLight );\\\\n\\\\t\\\\tdotNL = dot( geometry.normal, directLight.direction );\\\\n\\\\t\\\\tdirectLightColor_Diffuse = directLight.color;\\\\n\\\\t\\\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\t\\\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n#endif\\\\n#if NUM_HEMI_LIGHTS > 0\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\\\\n\\\\t\\\\tvIndirectFront += getHemisphereLightIrradiance( hemisphereLights[ i ], geometry.normal );\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\t\\\\tvIndirectBack += getHemisphereLightIrradiance( hemisphereLights[ i ], backGeometry.normal );\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n#endif\\\\\\\",lights_pars_begin:\\\\\\\"uniform bool receiveShadow;\\\\nuniform vec3 ambientLightColor;\\\\nuniform vec3 lightProbe[ 9 ];\\\\nvec3 shGetIrradianceAt( in vec3 normal, in vec3 shCoefficients[ 9 ] ) {\\\\n\\\\tfloat x = normal.x, y = normal.y, z = normal.z;\\\\n\\\\tvec3 result = shCoefficients[ 0 ] * 0.886227;\\\\n\\\\tresult += shCoefficients[ 1 ] * 2.0 * 0.511664 * y;\\\\n\\\\tresult += shCoefficients[ 2 ] * 2.0 * 0.511664 * z;\\\\n\\\\tresult += shCoefficients[ 3 ] * 2.0 * 0.511664 * x;\\\\n\\\\tresult += shCoefficients[ 4 ] * 2.0 * 0.429043 * x * y;\\\\n\\\\tresult += shCoefficients[ 5 ] * 2.0 * 0.429043 * y * z;\\\\n\\\\tresult += shCoefficients[ 6 ] * ( 0.743125 * z * z - 0.247708 );\\\\n\\\\tresult += shCoefficients[ 7 ] * 2.0 * 0.429043 * x * z;\\\\n\\\\tresult += shCoefficients[ 8 ] * 0.429043 * ( x * x - y * y );\\\\n\\\\treturn result;\\\\n}\\\\nvec3 getLightProbeIrradiance( const in vec3 lightProbe[ 9 ], const in vec3 normal ) {\\\\n\\\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\\\n\\\\tvec3 irradiance = shGetIrradianceAt( worldNormal, lightProbe );\\\\n\\\\treturn irradiance;\\\\n}\\\\nvec3 getAmbientLightIrradiance( const in vec3 ambientLightColor ) {\\\\n\\\\tvec3 irradiance = ambientLightColor;\\\\n\\\\treturn irradiance;\\\\n}\\\\nfloat getDistanceAttenuation( const in float lightDistance, const in float cutoffDistance, const in float decayExponent ) {\\\\n\\\\t#if defined ( PHYSICALLY_CORRECT_LIGHTS )\\\\n\\\\t\\\\tfloat distanceFalloff = 1.0 / max( pow( lightDistance, decayExponent ), 0.01 );\\\\n\\\\t\\\\tif ( cutoffDistance > 0.0 ) {\\\\n\\\\t\\\\t\\\\tdistanceFalloff *= pow2( saturate( 1.0 - pow4( lightDistance / cutoffDistance ) ) );\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\treturn distanceFalloff;\\\\n\\\\t#else\\\\n\\\\t\\\\tif ( cutoffDistance > 0.0 && decayExponent > 0.0 ) {\\\\n\\\\t\\\\t\\\\treturn pow( saturate( - lightDistance / cutoffDistance + 1.0 ), decayExponent );\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\treturn 1.0;\\\\n\\\\t#endif\\\\n}\\\\nfloat getSpotAttenuation( const in float coneCosine, const in float penumbraCosine, const in float angleCosine ) {\\\\n\\\\treturn smoothstep( coneCosine, penumbraCosine, angleCosine );\\\\n}\\\\n#if NUM_DIR_LIGHTS > 0\\\\n\\\\tstruct DirectionalLight {\\\\n\\\\t\\\\tvec3 direction;\\\\n\\\\t\\\\tvec3 color;\\\\n\\\\t};\\\\n\\\\tuniform DirectionalLight directionalLights[ NUM_DIR_LIGHTS ];\\\\n\\\\tvoid getDirectionalLightInfo( const in DirectionalLight directionalLight, const in GeometricContext geometry, out IncidentLight light ) {\\\\n\\\\t\\\\tlight.color = directionalLight.color;\\\\n\\\\t\\\\tlight.direction = directionalLight.direction;\\\\n\\\\t\\\\tlight.visible = true;\\\\n\\\\t}\\\\n#endif\\\\n#if NUM_POINT_LIGHTS > 0\\\\n\\\\tstruct PointLight {\\\\n\\\\t\\\\tvec3 position;\\\\n\\\\t\\\\tvec3 color;\\\\n\\\\t\\\\tfloat distance;\\\\n\\\\t\\\\tfloat decay;\\\\n\\\\t};\\\\n\\\\tuniform PointLight pointLights[ NUM_POINT_LIGHTS ];\\\\n\\\\tvoid getPointLightInfo( const in PointLight pointLight, const in GeometricContext geometry, out IncidentLight light ) {\\\\n\\\\t\\\\tvec3 lVector = pointLight.position - geometry.position;\\\\n\\\\t\\\\tlight.direction = normalize( lVector );\\\\n\\\\t\\\\tfloat lightDistance = length( lVector );\\\\n\\\\t\\\\tlight.color = pointLight.color;\\\\n\\\\t\\\\tlight.color *= getDistanceAttenuation( lightDistance, pointLight.distance, pointLight.decay );\\\\n\\\\t\\\\tlight.visible = ( light.color != vec3( 0.0 ) );\\\\n\\\\t}\\\\n#endif\\\\n#if NUM_SPOT_LIGHTS > 0\\\\n\\\\tstruct SpotLight {\\\\n\\\\t\\\\tvec3 position;\\\\n\\\\t\\\\tvec3 direction;\\\\n\\\\t\\\\tvec3 color;\\\\n\\\\t\\\\tfloat distance;\\\\n\\\\t\\\\tfloat decay;\\\\n\\\\t\\\\tfloat coneCos;\\\\n\\\\t\\\\tfloat penumbraCos;\\\\n\\\\t};\\\\n\\\\tuniform SpotLight spotLights[ NUM_SPOT_LIGHTS ];\\\\n\\\\tvoid getSpotLightInfo( const in SpotLight spotLight, const in GeometricContext geometry, out IncidentLight light ) {\\\\n\\\\t\\\\tvec3 lVector = spotLight.position - geometry.position;\\\\n\\\\t\\\\tlight.direction = normalize( lVector );\\\\n\\\\t\\\\tfloat angleCos = dot( light.direction, spotLight.direction );\\\\n\\\\t\\\\tfloat spotAttenuation = getSpotAttenuation( spotLight.coneCos, spotLight.penumbraCos, angleCos );\\\\n\\\\t\\\\tif ( spotAttenuation > 0.0 ) {\\\\n\\\\t\\\\t\\\\tfloat lightDistance = length( lVector );\\\\n\\\\t\\\\t\\\\tlight.color = spotLight.color * spotAttenuation;\\\\n\\\\t\\\\t\\\\tlight.color *= getDistanceAttenuation( lightDistance, spotLight.distance, spotLight.decay );\\\\n\\\\t\\\\t\\\\tlight.visible = ( light.color != vec3( 0.0 ) );\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tlight.color = vec3( 0.0 );\\\\n\\\\t\\\\t\\\\tlight.visible = false;\\\\n\\\\t\\\\t}\\\\n\\\\t}\\\\n#endif\\\\n#if NUM_RECT_AREA_LIGHTS > 0\\\\n\\\\tstruct RectAreaLight {\\\\n\\\\t\\\\tvec3 color;\\\\n\\\\t\\\\tvec3 position;\\\\n\\\\t\\\\tvec3 halfWidth;\\\\n\\\\t\\\\tvec3 halfHeight;\\\\n\\\\t};\\\\n\\\\tuniform sampler2D ltc_1;\\\\tuniform sampler2D ltc_2;\\\\n\\\\tuniform RectAreaLight rectAreaLights[ NUM_RECT_AREA_LIGHTS ];\\\\n#endif\\\\n#if NUM_HEMI_LIGHTS > 0\\\\n\\\\tstruct HemisphereLight {\\\\n\\\\t\\\\tvec3 direction;\\\\n\\\\t\\\\tvec3 skyColor;\\\\n\\\\t\\\\tvec3 groundColor;\\\\n\\\\t};\\\\n\\\\tuniform HemisphereLight hemisphereLights[ NUM_HEMI_LIGHTS ];\\\\n\\\\tvec3 getHemisphereLightIrradiance( const in HemisphereLight hemiLight, const in vec3 normal ) {\\\\n\\\\t\\\\tfloat dotNL = dot( normal, hemiLight.direction );\\\\n\\\\t\\\\tfloat hemiDiffuseWeight = 0.5 * dotNL + 0.5;\\\\n\\\\t\\\\tvec3 irradiance = mix( hemiLight.groundColor, hemiLight.skyColor, hemiDiffuseWeight );\\\\n\\\\t\\\\treturn irradiance;\\\\n\\\\t}\\\\n#endif\\\\\\\",lights_toon_fragment:\\\\\\\"ToonMaterial material;\\\\nmaterial.diffuseColor = diffuseColor.rgb;\\\\\\\",lights_toon_pars_fragment:\\\\\\\"varying vec3 vViewPosition;\\\\nstruct ToonMaterial {\\\\n\\\\tvec3 diffuseColor;\\\\n};\\\\nvoid RE_Direct_Toon( const in IncidentLight directLight, const in GeometricContext geometry, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\tvec3 irradiance = getGradientIrradiance( geometry.normal, directLight.direction ) * directLight.color;\\\\n\\\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n}\\\\nvoid RE_IndirectDiffuse_Toon( const in vec3 irradiance, const in GeometricContext geometry, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n}\\\\n#define RE_Direct\\\\t\\\\t\\\\t\\\\tRE_Direct_Toon\\\\n#define RE_IndirectDiffuse\\\\t\\\\tRE_IndirectDiffuse_Toon\\\\n#define Material_LightProbeLOD( material )\\\\t(0)\\\\\\\",lights_phong_fragment:\\\\\\\"BlinnPhongMaterial material;\\\\nmaterial.diffuseColor = diffuseColor.rgb;\\\\nmaterial.specularColor = specular;\\\\nmaterial.specularShininess = shininess;\\\\nmaterial.specularStrength = specularStrength;\\\\\\\",lights_phong_pars_fragment:\\\\\\\"varying vec3 vViewPosition;\\\\nstruct BlinnPhongMaterial {\\\\n\\\\tvec3 diffuseColor;\\\\n\\\\tvec3 specularColor;\\\\n\\\\tfloat specularShininess;\\\\n\\\\tfloat specularStrength;\\\\n};\\\\nvoid RE_Direct_BlinnPhong( const in IncidentLight directLight, const in GeometricContext geometry, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\tfloat dotNL = saturate( dot( geometry.normal, directLight.direction ) );\\\\n\\\\tvec3 irradiance = dotNL * directLight.color;\\\\n\\\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n\\\\treflectedLight.directSpecular += irradiance * BRDF_BlinnPhong( directLight.direction, geometry.viewDir, geometry.normal, material.specularColor, material.specularShininess ) * material.specularStrength;\\\\n}\\\\nvoid RE_IndirectDiffuse_BlinnPhong( const in vec3 irradiance, const in GeometricContext geometry, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n}\\\\n#define RE_Direct\\\\t\\\\t\\\\t\\\\tRE_Direct_BlinnPhong\\\\n#define RE_IndirectDiffuse\\\\t\\\\tRE_IndirectDiffuse_BlinnPhong\\\\n#define Material_LightProbeLOD( material )\\\\t(0)\\\\\\\",lights_physical_fragment:\\\\\\\"PhysicalMaterial material;\\\\nmaterial.diffuseColor = diffuseColor.rgb * ( 1.0 - metalnessFactor );\\\\nvec3 dxy = max( abs( dFdx( geometryNormal ) ), abs( dFdy( geometryNormal ) ) );\\\\nfloat geometryRoughness = max( max( dxy.x, dxy.y ), dxy.z );\\\\nmaterial.roughness = max( roughnessFactor, 0.0525 );material.roughness += geometryRoughness;\\\\nmaterial.roughness = min( material.roughness, 1.0 );\\\\n#ifdef IOR\\\\n\\\\t#ifdef SPECULAR\\\\n\\\\t\\\\tfloat specularIntensityFactor = specularIntensity;\\\\n\\\\t\\\\tvec3 specularTintFactor = specularTint;\\\\n\\\\t\\\\t#ifdef USE_SPECULARINTENSITYMAP\\\\n\\\\t\\\\t\\\\tspecularIntensityFactor *= texture2D( specularIntensityMap, vUv ).a;\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t#ifdef USE_SPECULARTINTMAP\\\\n\\\\t\\\\t\\\\tspecularTintFactor *= specularTintMapTexelToLinear( texture2D( specularTintMap, vUv ) ).rgb;\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\tmaterial.specularF90 = mix( specularIntensityFactor, 1.0, metalnessFactor );\\\\n\\\\t#else\\\\n\\\\t\\\\tfloat specularIntensityFactor = 1.0;\\\\n\\\\t\\\\tvec3 specularTintFactor = vec3( 1.0 );\\\\n\\\\t\\\\tmaterial.specularF90 = 1.0;\\\\n\\\\t#endif\\\\n\\\\tmaterial.specularColor = mix( min( pow2( ( ior - 1.0 ) / ( ior + 1.0 ) ) * specularTintFactor, vec3( 1.0 ) ) * specularIntensityFactor, diffuseColor.rgb, metalnessFactor );\\\\n#else\\\\n\\\\tmaterial.specularColor = mix( vec3( 0.04 ), diffuseColor.rgb, metalnessFactor );\\\\n\\\\tmaterial.specularF90 = 1.0;\\\\n#endif\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\tmaterial.clearcoat = clearcoat;\\\\n\\\\tmaterial.clearcoatRoughness = clearcoatRoughness;\\\\n\\\\tmaterial.clearcoatF0 = vec3( 0.04 );\\\\n\\\\tmaterial.clearcoatF90 = 1.0;\\\\n\\\\t#ifdef USE_CLEARCOATMAP\\\\n\\\\t\\\\tmaterial.clearcoat *= texture2D( clearcoatMap, vUv ).x;\\\\n\\\\t#endif\\\\n\\\\t#ifdef USE_CLEARCOAT_ROUGHNESSMAP\\\\n\\\\t\\\\tmaterial.clearcoatRoughness *= texture2D( clearcoatRoughnessMap, vUv ).y;\\\\n\\\\t#endif\\\\n\\\\tmaterial.clearcoat = saturate( material.clearcoat );\\\\tmaterial.clearcoatRoughness = max( material.clearcoatRoughness, 0.0525 );\\\\n\\\\tmaterial.clearcoatRoughness += geometryRoughness;\\\\n\\\\tmaterial.clearcoatRoughness = min( material.clearcoatRoughness, 1.0 );\\\\n#endif\\\\n#ifdef USE_SHEEN\\\\n\\\\tmaterial.sheenTint = sheenTint;\\\\n\\\\tmaterial.sheenRoughness = clamp( sheenRoughness, 0.07, 1.0 );\\\\n#endif\\\\\\\",lights_physical_pars_fragment:\\\\\\\"struct PhysicalMaterial {\\\\n\\\\tvec3 diffuseColor;\\\\n\\\\tfloat roughness;\\\\n\\\\tvec3 specularColor;\\\\n\\\\tfloat specularF90;\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\t\\\\tfloat clearcoat;\\\\n\\\\t\\\\tfloat clearcoatRoughness;\\\\n\\\\t\\\\tvec3 clearcoatF0;\\\\n\\\\t\\\\tfloat clearcoatF90;\\\\n\\\\t#endif\\\\n\\\\t#ifdef USE_SHEEN\\\\n\\\\t\\\\tvec3 sheenTint;\\\\n\\\\t\\\\tfloat sheenRoughness;\\\\n\\\\t#endif\\\\n};\\\\nvec3 clearcoatSpecular = vec3( 0.0 );\\\\nvec2 DFGApprox( const in vec3 normal, const in vec3 viewDir, const in float roughness ) {\\\\n\\\\tfloat dotNV = saturate( dot( normal, viewDir ) );\\\\n\\\\tconst vec4 c0 = vec4( - 1, - 0.0275, - 0.572, 0.022 );\\\\n\\\\tconst vec4 c1 = vec4( 1, 0.0425, 1.04, - 0.04 );\\\\n\\\\tvec4 r = roughness * c0 + c1;\\\\n\\\\tfloat a004 = min( r.x * r.x, exp2( - 9.28 * dotNV ) ) * r.x + r.y;\\\\n\\\\tvec2 fab = vec2( - 1.04, 1.04 ) * a004 + r.zw;\\\\n\\\\treturn fab;\\\\n}\\\\nvec3 EnvironmentBRDF( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness ) {\\\\n\\\\tvec2 fab = DFGApprox( normal, viewDir, roughness );\\\\n\\\\treturn specularColor * fab.x + specularF90 * fab.y;\\\\n}\\\\nvoid computeMultiscattering( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness, inout vec3 singleScatter, inout vec3 multiScatter ) {\\\\n\\\\tvec2 fab = DFGApprox( normal, viewDir, roughness );\\\\n\\\\tvec3 FssEss = specularColor * fab.x + specularF90 * fab.y;\\\\n\\\\tfloat Ess = fab.x + fab.y;\\\\n\\\\tfloat Ems = 1.0 - Ess;\\\\n\\\\tvec3 Favg = specularColor + ( 1.0 - specularColor ) * 0.047619;\\\\tvec3 Fms = FssEss * Favg / ( 1.0 - Ems * Favg );\\\\n\\\\tsingleScatter += FssEss;\\\\n\\\\tmultiScatter += Fms * Ems;\\\\n}\\\\n#if NUM_RECT_AREA_LIGHTS > 0\\\\n\\\\tvoid RE_Direct_RectArea_Physical( const in RectAreaLight rectAreaLight, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\t\\\\tvec3 normal = geometry.normal;\\\\n\\\\t\\\\tvec3 viewDir = geometry.viewDir;\\\\n\\\\t\\\\tvec3 position = geometry.position;\\\\n\\\\t\\\\tvec3 lightPos = rectAreaLight.position;\\\\n\\\\t\\\\tvec3 halfWidth = rectAreaLight.halfWidth;\\\\n\\\\t\\\\tvec3 halfHeight = rectAreaLight.halfHeight;\\\\n\\\\t\\\\tvec3 lightColor = rectAreaLight.color;\\\\n\\\\t\\\\tfloat roughness = material.roughness;\\\\n\\\\t\\\\tvec3 rectCoords[ 4 ];\\\\n\\\\t\\\\trectCoords[ 0 ] = lightPos + halfWidth - halfHeight;\\\\t\\\\trectCoords[ 1 ] = lightPos - halfWidth - halfHeight;\\\\n\\\\t\\\\trectCoords[ 2 ] = lightPos - halfWidth + halfHeight;\\\\n\\\\t\\\\trectCoords[ 3 ] = lightPos + halfWidth + halfHeight;\\\\n\\\\t\\\\tvec2 uv = LTC_Uv( normal, viewDir, roughness );\\\\n\\\\t\\\\tvec4 t1 = texture2D( ltc_1, uv );\\\\n\\\\t\\\\tvec4 t2 = texture2D( ltc_2, uv );\\\\n\\\\t\\\\tmat3 mInv = mat3(\\\\n\\\\t\\\\t\\\\tvec3( t1.x, 0, t1.y ),\\\\n\\\\t\\\\t\\\\tvec3( 0, 1, 0 ),\\\\n\\\\t\\\\t\\\\tvec3( t1.z, 0, t1.w )\\\\n\\\\t\\\\t);\\\\n\\\\t\\\\tvec3 fresnel = ( material.specularColor * t2.x + ( vec3( 1.0 ) - material.specularColor ) * t2.y );\\\\n\\\\t\\\\treflectedLight.directSpecular += lightColor * fresnel * LTC_Evaluate( normal, viewDir, position, mInv, rectCoords );\\\\n\\\\t\\\\treflectedLight.directDiffuse += lightColor * material.diffuseColor * LTC_Evaluate( normal, viewDir, position, mat3( 1.0 ), rectCoords );\\\\n\\\\t}\\\\n#endif\\\\nvoid RE_Direct_Physical( const in IncidentLight directLight, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\tfloat dotNL = saturate( dot( geometry.normal, directLight.direction ) );\\\\n\\\\tvec3 irradiance = dotNL * directLight.color;\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\t\\\\tfloat dotNLcc = saturate( dot( geometry.clearcoatNormal, directLight.direction ) );\\\\n\\\\t\\\\tvec3 ccIrradiance = dotNLcc * directLight.color;\\\\n\\\\t\\\\tclearcoatSpecular += ccIrradiance * BRDF_GGX( directLight.direction, geometry.viewDir, geometry.clearcoatNormal, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );\\\\n\\\\t#endif\\\\n\\\\t#ifdef USE_SHEEN\\\\n\\\\t\\\\treflectedLight.directSpecular += irradiance * BRDF_Sheen( directLight.direction, geometry.viewDir, geometry.normal, material.sheenTint, material.sheenRoughness );\\\\n\\\\t#endif\\\\n\\\\treflectedLight.directSpecular += irradiance * BRDF_GGX( directLight.direction, geometry.viewDir, geometry.normal, material.specularColor, material.specularF90, material.roughness );\\\\n\\\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n}\\\\nvoid RE_IndirectDiffuse_Physical( const in vec3 irradiance, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\\\n\\\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\\\n}\\\\nvoid RE_IndirectSpecular_Physical( const in vec3 radiance, const in vec3 irradiance, const in vec3 clearcoatRadiance, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight) {\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\t\\\\tclearcoatSpecular += clearcoatRadiance * EnvironmentBRDF( geometry.clearcoatNormal, geometry.viewDir, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );\\\\n\\\\t#endif\\\\n\\\\tvec3 singleScattering = vec3( 0.0 );\\\\n\\\\tvec3 multiScattering = vec3( 0.0 );\\\\n\\\\tvec3 cosineWeightedIrradiance = irradiance * RECIPROCAL_PI;\\\\n\\\\tcomputeMultiscattering( geometry.normal, geometry.viewDir, material.specularColor, material.specularF90, material.roughness, singleScattering, multiScattering );\\\\n\\\\tvec3 diffuse = material.diffuseColor * ( 1.0 - ( singleScattering + multiScattering ) );\\\\n\\\\treflectedLight.indirectSpecular += radiance * singleScattering;\\\\n\\\\treflectedLight.indirectSpecular += multiScattering * cosineWeightedIrradiance;\\\\n\\\\treflectedLight.indirectDiffuse += diffuse * cosineWeightedIrradiance;\\\\n}\\\\n#define RE_Direct\\\\t\\\\t\\\\t\\\\tRE_Direct_Physical\\\\n#define RE_Direct_RectArea\\\\t\\\\tRE_Direct_RectArea_Physical\\\\n#define RE_IndirectDiffuse\\\\t\\\\tRE_IndirectDiffuse_Physical\\\\n#define RE_IndirectSpecular\\\\t\\\\tRE_IndirectSpecular_Physical\\\\nfloat computeSpecularOcclusion( const in float dotNV, const in float ambientOcclusion, const in float roughness ) {\\\\n\\\\treturn saturate( pow( dotNV + ambientOcclusion, exp2( - 16.0 * roughness - 1.0 ) ) - 1.0 + ambientOcclusion );\\\\n}\\\\\\\",lights_fragment_begin:\\\\\\\"\\\\nGeometricContext geometry;\\\\ngeometry.position = - vViewPosition;\\\\ngeometry.normal = normal;\\\\ngeometry.viewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( vViewPosition );\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\tgeometry.clearcoatNormal = clearcoatNormal;\\\\n#endif\\\\nIncidentLight directLight;\\\\n#if ( NUM_POINT_LIGHTS > 0 ) && defined( RE_Direct )\\\\n\\\\tPointLight pointLight;\\\\n\\\\t#if defined( USE_SHADOWMAP ) && NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\tPointLightShadow pointLightShadow;\\\\n\\\\t#endif\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\\\\n\\\\t\\\\tpointLight = pointLights[ i ];\\\\n\\\\t\\\\tgetPointLightInfo( pointLight, geometry, directLight );\\\\n\\\\t\\\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_POINT_LIGHT_SHADOWS )\\\\n\\\\t\\\\tpointLightShadow = pointLightShadows[ i ];\\\\n\\\\t\\\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getPointShadow( pointShadowMap[ i ], pointLightShadow.shadowMapSize, pointLightShadow.shadowBias, pointLightShadow.shadowRadius, vPointShadowCoord[ i ], pointLightShadow.shadowCameraNear, pointLightShadow.shadowCameraFar ) : 1.0;\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\tRE_Direct( directLight, geometry, material, reflectedLight );\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n#endif\\\\n#if ( NUM_SPOT_LIGHTS > 0 ) && defined( RE_Direct )\\\\n\\\\tSpotLight spotLight;\\\\n\\\\t#if defined( USE_SHADOWMAP ) && NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\tSpotLightShadow spotLightShadow;\\\\n\\\\t#endif\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\\\\n\\\\t\\\\tspotLight = spotLights[ i ];\\\\n\\\\t\\\\tgetSpotLightInfo( spotLight, geometry, directLight );\\\\n\\\\t\\\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\\\\n\\\\t\\\\tspotLightShadow = spotLightShadows[ i ];\\\\n\\\\t\\\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getShadow( spotShadowMap[ i ], spotLightShadow.shadowMapSize, spotLightShadow.shadowBias, spotLightShadow.shadowRadius, vSpotShadowCoord[ i ] ) : 1.0;\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\tRE_Direct( directLight, geometry, material, reflectedLight );\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n#endif\\\\n#if ( NUM_DIR_LIGHTS > 0 ) && defined( RE_Direct )\\\\n\\\\tDirectionalLight directionalLight;\\\\n\\\\t#if defined( USE_SHADOWMAP ) && NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\tDirectionalLightShadow directionalLightShadow;\\\\n\\\\t#endif\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\\\\n\\\\t\\\\tdirectionalLight = directionalLights[ i ];\\\\n\\\\t\\\\tgetDirectionalLightInfo( directionalLight, geometry, directLight );\\\\n\\\\t\\\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_DIR_LIGHT_SHADOWS )\\\\n\\\\t\\\\tdirectionalLightShadow = directionalLightShadows[ i ];\\\\n\\\\t\\\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getShadow( directionalShadowMap[ i ], directionalLightShadow.shadowMapSize, directionalLightShadow.shadowBias, directionalLightShadow.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\tRE_Direct( directLight, geometry, material, reflectedLight );\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n#endif\\\\n#if ( NUM_RECT_AREA_LIGHTS > 0 ) && defined( RE_Direct_RectArea )\\\\n\\\\tRectAreaLight rectAreaLight;\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_RECT_AREA_LIGHTS; i ++ ) {\\\\n\\\\t\\\\trectAreaLight = rectAreaLights[ i ];\\\\n\\\\t\\\\tRE_Direct_RectArea( rectAreaLight, geometry, material, reflectedLight );\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n#endif\\\\n#if defined( RE_IndirectDiffuse )\\\\n\\\\tvec3 iblIrradiance = vec3( 0.0 );\\\\n\\\\tvec3 irradiance = getAmbientLightIrradiance( ambientLightColor );\\\\n\\\\tirradiance += getLightProbeIrradiance( lightProbe, geometry.normal );\\\\n\\\\t#if ( NUM_HEMI_LIGHTS > 0 )\\\\n\\\\t\\\\t#pragma unroll_loop_start\\\\n\\\\t\\\\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\\\\n\\\\t\\\\t\\\\tirradiance += getHemisphereLightIrradiance( hemisphereLights[ i ], geometry.normal );\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\t#pragma unroll_loop_end\\\\n\\\\t#endif\\\\n#endif\\\\n#if defined( RE_IndirectSpecular )\\\\n\\\\tvec3 radiance = vec3( 0.0 );\\\\n\\\\tvec3 clearcoatRadiance = vec3( 0.0 );\\\\n#endif\\\\\\\",lights_fragment_maps:\\\\\\\"#if defined( RE_IndirectDiffuse )\\\\n\\\\t#ifdef USE_LIGHTMAP\\\\n\\\\t\\\\tvec4 lightMapTexel = texture2D( lightMap, vUv2 );\\\\n\\\\t\\\\tvec3 lightMapIrradiance = lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\\\n\\\\t\\\\t#ifndef PHYSICALLY_CORRECT_LIGHTS\\\\n\\\\t\\\\t\\\\tlightMapIrradiance *= PI;\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\tirradiance += lightMapIrradiance;\\\\n\\\\t#endif\\\\n\\\\t#if defined( USE_ENVMAP ) && defined( STANDARD ) && defined( ENVMAP_TYPE_CUBE_UV )\\\\n\\\\t\\\\tiblIrradiance += getIBLIrradiance( geometry.normal );\\\\n\\\\t#endif\\\\n#endif\\\\n#if defined( USE_ENVMAP ) && defined( RE_IndirectSpecular )\\\\n\\\\tradiance += getIBLRadiance( geometry.viewDir, geometry.normal, material.roughness );\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\t\\\\tclearcoatRadiance += getIBLRadiance( geometry.viewDir, geometry.clearcoatNormal, material.clearcoatRoughness );\\\\n\\\\t#endif\\\\n#endif\\\\\\\",lights_fragment_end:\\\\\\\"#if defined( RE_IndirectDiffuse )\\\\n\\\\tRE_IndirectDiffuse( irradiance, geometry, material, reflectedLight );\\\\n#endif\\\\n#if defined( RE_IndirectSpecular )\\\\n\\\\tRE_IndirectSpecular( radiance, iblIrradiance, clearcoatRadiance, geometry, material, reflectedLight );\\\\n#endif\\\\\\\",logdepthbuf_fragment:\\\\\\\"#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )\\\\n\\\\tgl_FragDepthEXT = vIsPerspective == 0.0 ? gl_FragCoord.z : log2( vFragDepth ) * logDepthBufFC * 0.5;\\\\n#endif\\\\\\\",logdepthbuf_pars_fragment:\\\\\\\"#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )\\\\n\\\\tuniform float logDepthBufFC;\\\\n\\\\tvarying float vFragDepth;\\\\n\\\\tvarying float vIsPerspective;\\\\n#endif\\\\\\\",logdepthbuf_pars_vertex:\\\\\\\"#ifdef USE_LOGDEPTHBUF\\\\n\\\\t#ifdef USE_LOGDEPTHBUF_EXT\\\\n\\\\t\\\\tvarying float vFragDepth;\\\\n\\\\t\\\\tvarying float vIsPerspective;\\\\n\\\\t#else\\\\n\\\\t\\\\tuniform float logDepthBufFC;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",logdepthbuf_vertex:\\\\\\\"#ifdef USE_LOGDEPTHBUF\\\\n\\\\t#ifdef USE_LOGDEPTHBUF_EXT\\\\n\\\\t\\\\tvFragDepth = 1.0 + gl_Position.w;\\\\n\\\\t\\\\tvIsPerspective = float( isPerspectiveMatrix( projectionMatrix ) );\\\\n\\\\t#else\\\\n\\\\t\\\\tif ( isPerspectiveMatrix( projectionMatrix ) ) {\\\\n\\\\t\\\\t\\\\tgl_Position.z = log2( max( EPSILON, gl_Position.w + 1.0 ) ) * logDepthBufFC - 1.0;\\\\n\\\\t\\\\t\\\\tgl_Position.z *= gl_Position.w;\\\\n\\\\t\\\\t}\\\\n\\\\t#endif\\\\n#endif\\\\\\\",map_fragment:\\\\\\\"#ifdef USE_MAP\\\\n\\\\tvec4 texelColor = texture2D( map, vUv );\\\\n\\\\ttexelColor = mapTexelToLinear( texelColor );\\\\n\\\\tdiffuseColor *= texelColor;\\\\n#endif\\\\\\\",map_pars_fragment:\\\\\\\"#ifdef USE_MAP\\\\n\\\\tuniform sampler2D map;\\\\n#endif\\\\\\\",map_particle_fragment:\\\\\\\"#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\\\\n\\\\tvec2 uv = ( uvTransform * vec3( gl_PointCoord.x, 1.0 - gl_PointCoord.y, 1 ) ).xy;\\\\n#endif\\\\n#ifdef USE_MAP\\\\n\\\\tvec4 mapTexel = texture2D( map, uv );\\\\n\\\\tdiffuseColor *= mapTexelToLinear( mapTexel );\\\\n#endif\\\\n#ifdef USE_ALPHAMAP\\\\n\\\\tdiffuseColor.a *= texture2D( alphaMap, uv ).g;\\\\n#endif\\\\\\\",map_particle_pars_fragment:\\\\\\\"#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\\\\n\\\\tuniform mat3 uvTransform;\\\\n#endif\\\\n#ifdef USE_MAP\\\\n\\\\tuniform sampler2D map;\\\\n#endif\\\\n#ifdef USE_ALPHAMAP\\\\n\\\\tuniform sampler2D alphaMap;\\\\n#endif\\\\\\\",metalnessmap_fragment:\\\\\\\"float metalnessFactor = metalness;\\\\n#ifdef USE_METALNESSMAP\\\\n\\\\tvec4 texelMetalness = texture2D( metalnessMap, vUv );\\\\n\\\\tmetalnessFactor *= texelMetalness.b;\\\\n#endif\\\\\\\",metalnessmap_pars_fragment:\\\\\\\"#ifdef USE_METALNESSMAP\\\\n\\\\tuniform sampler2D metalnessMap;\\\\n#endif\\\\\\\",morphnormal_vertex:\\\\\\\"#ifdef USE_MORPHNORMALS\\\\n\\\\tobjectNormal *= morphTargetBaseInfluence;\\\\n\\\\t#ifdef MORPHTARGETS_TEXTURE\\\\n\\\\t\\\\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\\\\n\\\\t\\\\t\\\\tif ( morphTargetInfluences[ i ] > 0.0 ) objectNormal += getMorph( gl_VertexID, i, 1, 2 ) * morphTargetInfluences[ i ];\\\\n\\\\t\\\\t}\\\\n\\\\t#else\\\\n\\\\t\\\\tobjectNormal += morphNormal0 * morphTargetInfluences[ 0 ];\\\\n\\\\t\\\\tobjectNormal += morphNormal1 * morphTargetInfluences[ 1 ];\\\\n\\\\t\\\\tobjectNormal += morphNormal2 * morphTargetInfluences[ 2 ];\\\\n\\\\t\\\\tobjectNormal += morphNormal3 * morphTargetInfluences[ 3 ];\\\\n\\\\t#endif\\\\n#endif\\\\\\\",morphtarget_pars_vertex:\\\\\\\"#ifdef USE_MORPHTARGETS\\\\n\\\\tuniform float morphTargetBaseInfluence;\\\\n\\\\t#ifdef MORPHTARGETS_TEXTURE\\\\n\\\\t\\\\tuniform float morphTargetInfluences[ MORPHTARGETS_COUNT ];\\\\n\\\\t\\\\tuniform sampler2DArray morphTargetsTexture;\\\\n\\\\t\\\\tuniform vec2 morphTargetsTextureSize;\\\\n\\\\t\\\\tvec3 getMorph( const in int vertexIndex, const in int morphTargetIndex, const in int offset, const in int stride ) {\\\\n\\\\t\\\\t\\\\tfloat texelIndex = float( vertexIndex * stride + offset );\\\\n\\\\t\\\\t\\\\tfloat y = floor( texelIndex / morphTargetsTextureSize.x );\\\\n\\\\t\\\\t\\\\tfloat x = texelIndex - y * morphTargetsTextureSize.x;\\\\n\\\\t\\\\t\\\\tvec3 morphUV = vec3( ( x + 0.5 ) / morphTargetsTextureSize.x, y / morphTargetsTextureSize.y, morphTargetIndex );\\\\n\\\\t\\\\t\\\\treturn texture( morphTargetsTexture, morphUV ).xyz;\\\\n\\\\t\\\\t}\\\\n\\\\t#else\\\\n\\\\t\\\\t#ifndef USE_MORPHNORMALS\\\\n\\\\t\\\\t\\\\tuniform float morphTargetInfluences[ 8 ];\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\tuniform float morphTargetInfluences[ 4 ];\\\\n\\\\t\\\\t#endif\\\\n\\\\t#endif\\\\n#endif\\\\\\\",morphtarget_vertex:\\\\\\\"#ifdef USE_MORPHTARGETS\\\\n\\\\ttransformed *= morphTargetBaseInfluence;\\\\n\\\\t#ifdef MORPHTARGETS_TEXTURE\\\\n\\\\t\\\\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\\\\n\\\\t\\\\t\\\\t#ifndef USE_MORPHNORMALS\\\\n\\\\t\\\\t\\\\t\\\\tif ( morphTargetInfluences[ i ] > 0.0 ) transformed += getMorph( gl_VertexID, i, 0, 1 ) * morphTargetInfluences[ i ];\\\\n\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\tif ( morphTargetInfluences[ i ] > 0.0 ) transformed += getMorph( gl_VertexID, i, 0, 2 ) * morphTargetInfluences[ i ];\\\\n\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t}\\\\n\\\\t#else\\\\n\\\\t\\\\ttransformed += morphTarget0 * morphTargetInfluences[ 0 ];\\\\n\\\\t\\\\ttransformed += morphTarget1 * morphTargetInfluences[ 1 ];\\\\n\\\\t\\\\ttransformed += morphTarget2 * morphTargetInfluences[ 2 ];\\\\n\\\\t\\\\ttransformed += morphTarget3 * morphTargetInfluences[ 3 ];\\\\n\\\\t\\\\t#ifndef USE_MORPHNORMALS\\\\n\\\\t\\\\t\\\\ttransformed += morphTarget4 * morphTargetInfluences[ 4 ];\\\\n\\\\t\\\\t\\\\ttransformed += morphTarget5 * morphTargetInfluences[ 5 ];\\\\n\\\\t\\\\t\\\\ttransformed += morphTarget6 * morphTargetInfluences[ 6 ];\\\\n\\\\t\\\\t\\\\ttransformed += morphTarget7 * morphTargetInfluences[ 7 ];\\\\n\\\\t\\\\t#endif\\\\n\\\\t#endif\\\\n#endif\\\\\\\",normal_fragment_begin:\\\\\\\"float faceDirection = gl_FrontFacing ? 1.0 : - 1.0;\\\\n#ifdef FLAT_SHADED\\\\n\\\\tvec3 fdx = vec3( dFdx( vViewPosition.x ), dFdx( vViewPosition.y ), dFdx( vViewPosition.z ) );\\\\n\\\\tvec3 fdy = vec3( dFdy( vViewPosition.x ), dFdy( vViewPosition.y ), dFdy( vViewPosition.z ) );\\\\n\\\\tvec3 normal = normalize( cross( fdx, fdy ) );\\\\n#else\\\\n\\\\tvec3 normal = normalize( vNormal );\\\\n\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\tnormal = normal * faceDirection;\\\\n\\\\t#endif\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\t\\\\tvec3 tangent = normalize( vTangent );\\\\n\\\\t\\\\tvec3 bitangent = normalize( vBitangent );\\\\n\\\\t\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\t\\\\ttangent = tangent * faceDirection;\\\\n\\\\t\\\\t\\\\tbitangent = bitangent * faceDirection;\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t#if defined( TANGENTSPACE_NORMALMAP ) || defined( USE_CLEARCOAT_NORMALMAP )\\\\n\\\\t\\\\t\\\\tmat3 vTBN = mat3( tangent, bitangent, normal );\\\\n\\\\t\\\\t#endif\\\\n\\\\t#endif\\\\n#endif\\\\nvec3 geometryNormal = normal;\\\\\\\",normal_fragment_maps:\\\\\\\"#ifdef OBJECTSPACE_NORMALMAP\\\\n\\\\tnormal = texture2D( normalMap, vUv ).xyz * 2.0 - 1.0;\\\\n\\\\t#ifdef FLIP_SIDED\\\\n\\\\t\\\\tnormal = - normal;\\\\n\\\\t#endif\\\\n\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\tnormal = normal * faceDirection;\\\\n\\\\t#endif\\\\n\\\\tnormal = normalize( normalMatrix * normal );\\\\n#elif defined( TANGENTSPACE_NORMALMAP )\\\\n\\\\tvec3 mapN = texture2D( normalMap, vUv ).xyz * 2.0 - 1.0;\\\\n\\\\tmapN.xy *= normalScale;\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\t\\\\tnormal = normalize( vTBN * mapN );\\\\n\\\\t#else\\\\n\\\\t\\\\tnormal = perturbNormal2Arb( - vViewPosition, normal, mapN, faceDirection );\\\\n\\\\t#endif\\\\n#elif defined( USE_BUMPMAP )\\\\n\\\\tnormal = perturbNormalArb( - vViewPosition, normal, dHdxy_fwd(), faceDirection );\\\\n#endif\\\\\\\",normal_pars_fragment:\\\\\\\"#ifndef FLAT_SHADED\\\\n\\\\tvarying vec3 vNormal;\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\t\\\\tvarying vec3 vTangent;\\\\n\\\\t\\\\tvarying vec3 vBitangent;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",normal_pars_vertex:\\\\\\\"#ifndef FLAT_SHADED\\\\n\\\\tvarying vec3 vNormal;\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\t\\\\tvarying vec3 vTangent;\\\\n\\\\t\\\\tvarying vec3 vBitangent;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",normal_vertex:\\\\\\\"#ifndef FLAT_SHADED\\\\n\\\\tvNormal = normalize( transformedNormal );\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\t\\\\tvTangent = normalize( transformedTangent );\\\\n\\\\t\\\\tvBitangent = normalize( cross( vNormal, vTangent ) * tangent.w );\\\\n\\\\t#endif\\\\n#endif\\\\\\\",normalmap_pars_fragment:\\\\\\\"#ifdef USE_NORMALMAP\\\\n\\\\tuniform sampler2D normalMap;\\\\n\\\\tuniform vec2 normalScale;\\\\n#endif\\\\n#ifdef OBJECTSPACE_NORMALMAP\\\\n\\\\tuniform mat3 normalMatrix;\\\\n#endif\\\\n#if ! defined ( USE_TANGENT ) && ( defined ( TANGENTSPACE_NORMALMAP ) || defined ( USE_CLEARCOAT_NORMALMAP ) )\\\\n\\\\tvec3 perturbNormal2Arb( vec3 eye_pos, vec3 surf_norm, vec3 mapN, float faceDirection ) {\\\\n\\\\t\\\\tvec3 q0 = vec3( dFdx( eye_pos.x ), dFdx( eye_pos.y ), dFdx( eye_pos.z ) );\\\\n\\\\t\\\\tvec3 q1 = vec3( dFdy( eye_pos.x ), dFdy( eye_pos.y ), dFdy( eye_pos.z ) );\\\\n\\\\t\\\\tvec2 st0 = dFdx( vUv.st );\\\\n\\\\t\\\\tvec2 st1 = dFdy( vUv.st );\\\\n\\\\t\\\\tvec3 N = surf_norm;\\\\n\\\\t\\\\tvec3 q1perp = cross( q1, N );\\\\n\\\\t\\\\tvec3 q0perp = cross( N, q0 );\\\\n\\\\t\\\\tvec3 T = q1perp * st0.x + q0perp * st1.x;\\\\n\\\\t\\\\tvec3 B = q1perp * st0.y + q0perp * st1.y;\\\\n\\\\t\\\\tfloat det = max( dot( T, T ), dot( B, B ) );\\\\n\\\\t\\\\tfloat scale = ( det == 0.0 ) ? 0.0 : faceDirection * inversesqrt( det );\\\\n\\\\t\\\\treturn normalize( T * ( mapN.x * scale ) + B * ( mapN.y * scale ) + N * mapN.z );\\\\n\\\\t}\\\\n#endif\\\\\\\",clearcoat_normal_fragment_begin:\\\\\\\"#ifdef USE_CLEARCOAT\\\\n\\\\tvec3 clearcoatNormal = geometryNormal;\\\\n#endif\\\\\\\",clearcoat_normal_fragment_maps:\\\\\\\"#ifdef USE_CLEARCOAT_NORMALMAP\\\\n\\\\tvec3 clearcoatMapN = texture2D( clearcoatNormalMap, vUv ).xyz * 2.0 - 1.0;\\\\n\\\\tclearcoatMapN.xy *= clearcoatNormalScale;\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\t\\\\tclearcoatNormal = normalize( vTBN * clearcoatMapN );\\\\n\\\\t#else\\\\n\\\\t\\\\tclearcoatNormal = perturbNormal2Arb( - vViewPosition, clearcoatNormal, clearcoatMapN, faceDirection );\\\\n\\\\t#endif\\\\n#endif\\\\\\\",clearcoat_pars_fragment:\\\\\\\"#ifdef USE_CLEARCOATMAP\\\\n\\\\tuniform sampler2D clearcoatMap;\\\\n#endif\\\\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\\\\n\\\\tuniform sampler2D clearcoatRoughnessMap;\\\\n#endif\\\\n#ifdef USE_CLEARCOAT_NORMALMAP\\\\n\\\\tuniform sampler2D clearcoatNormalMap;\\\\n\\\\tuniform vec2 clearcoatNormalScale;\\\\n#endif\\\\\\\",output_fragment:\\\\\\\"#ifdef OPAQUE\\\\ndiffuseColor.a = 1.0;\\\\n#endif\\\\n#ifdef USE_TRANSMISSION\\\\ndiffuseColor.a *= transmissionAlpha + 0.1;\\\\n#endif\\\\ngl_FragColor = vec4( outgoingLight, diffuseColor.a );\\\\\\\",packing:\\\\\\\"vec3 packNormalToRGB( const in vec3 normal ) {\\\\n\\\\treturn normalize( normal ) * 0.5 + 0.5;\\\\n}\\\\nvec3 unpackRGBToNormal( const in vec3 rgb ) {\\\\n\\\\treturn 2.0 * rgb.xyz - 1.0;\\\\n}\\\\nconst float PackUpscale = 256. / 255.;const float UnpackDownscale = 255. / 256.;\\\\nconst vec3 PackFactors = vec3( 256. * 256. * 256., 256. * 256., 256. );\\\\nconst vec4 UnpackFactors = UnpackDownscale / vec4( PackFactors, 1. );\\\\nconst float ShiftRight8 = 1. / 256.;\\\\nvec4 packDepthToRGBA( const in float v ) {\\\\n\\\\tvec4 r = vec4( fract( v * PackFactors ), v );\\\\n\\\\tr.yzw -= r.xyz * ShiftRight8;\\\\treturn r * PackUpscale;\\\\n}\\\\nfloat unpackRGBAToDepth( const in vec4 v ) {\\\\n\\\\treturn dot( v, UnpackFactors );\\\\n}\\\\nvec4 pack2HalfToRGBA( vec2 v ) {\\\\n\\\\tvec4 r = vec4( v.x, fract( v.x * 255.0 ), v.y, fract( v.y * 255.0 ) );\\\\n\\\\treturn vec4( r.x - r.y / 255.0, r.y, r.z - r.w / 255.0, r.w );\\\\n}\\\\nvec2 unpackRGBATo2Half( vec4 v ) {\\\\n\\\\treturn vec2( v.x + ( v.y / 255.0 ), v.z + ( v.w / 255.0 ) );\\\\n}\\\\nfloat viewZToOrthographicDepth( const in float viewZ, const in float near, const in float far ) {\\\\n\\\\treturn ( viewZ + near ) / ( near - far );\\\\n}\\\\nfloat orthographicDepthToViewZ( const in float linearClipZ, const in float near, const in float far ) {\\\\n\\\\treturn linearClipZ * ( near - far ) - near;\\\\n}\\\\nfloat viewZToPerspectiveDepth( const in float viewZ, const in float near, const in float far ) {\\\\n\\\\treturn ( ( near + viewZ ) * far ) / ( ( far - near ) * viewZ );\\\\n}\\\\nfloat perspectiveDepthToViewZ( const in float invClipZ, const in float near, const in float far ) {\\\\n\\\\treturn ( near * far ) / ( ( far - near ) * invClipZ - far );\\\\n}\\\\\\\",premultiplied_alpha_fragment:\\\\\\\"#ifdef PREMULTIPLIED_ALPHA\\\\n\\\\tgl_FragColor.rgb *= gl_FragColor.a;\\\\n#endif\\\\\\\",project_vertex:\\\\\\\"vec4 mvPosition = vec4( transformed, 1.0 );\\\\n#ifdef USE_INSTANCING\\\\n\\\\tmvPosition = instanceMatrix * mvPosition;\\\\n#endif\\\\nmvPosition = modelViewMatrix * mvPosition;\\\\ngl_Position = projectionMatrix * mvPosition;\\\\\\\",dithering_fragment:\\\\\\\"#ifdef DITHERING\\\\n\\\\tgl_FragColor.rgb = dithering( gl_FragColor.rgb );\\\\n#endif\\\\\\\",dithering_pars_fragment:\\\\\\\"#ifdef DITHERING\\\\n\\\\tvec3 dithering( vec3 color ) {\\\\n\\\\t\\\\tfloat grid_position = rand( gl_FragCoord.xy );\\\\n\\\\t\\\\tvec3 dither_shift_RGB = vec3( 0.25 / 255.0, -0.25 / 255.0, 0.25 / 255.0 );\\\\n\\\\t\\\\tdither_shift_RGB = mix( 2.0 * dither_shift_RGB, -2.0 * dither_shift_RGB, grid_position );\\\\n\\\\t\\\\treturn color + dither_shift_RGB;\\\\n\\\\t}\\\\n#endif\\\\\\\",roughnessmap_fragment:\\\\\\\"float roughnessFactor = roughness;\\\\n#ifdef USE_ROUGHNESSMAP\\\\n\\\\tvec4 texelRoughness = texture2D( roughnessMap, vUv );\\\\n\\\\troughnessFactor *= texelRoughness.g;\\\\n#endif\\\\\\\",roughnessmap_pars_fragment:\\\\\\\"#ifdef USE_ROUGHNESSMAP\\\\n\\\\tuniform sampler2D roughnessMap;\\\\n#endif\\\\\\\",shadowmap_pars_fragment:\\\\\\\"#ifdef USE_SHADOWMAP\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\t\\\\tuniform sampler2D directionalShadowMap[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tstruct DirectionalLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t};\\\\n\\\\t\\\\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\t#endif\\\\n\\\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\t\\\\tuniform sampler2D spotShadowMap[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vSpotShadowCoord[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tstruct SpotLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t};\\\\n\\\\t\\\\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\t#endif\\\\n\\\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\t\\\\tuniform sampler2D pointShadowMap[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tstruct PointLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t\\\\tfloat shadowCameraNear;\\\\n\\\\t\\\\t\\\\tfloat shadowCameraFar;\\\\n\\\\t\\\\t};\\\\n\\\\t\\\\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\t#endif\\\\n\\\\tfloat texture2DCompare( sampler2D depths, vec2 uv, float compare ) {\\\\n\\\\t\\\\treturn step( compare, unpackRGBAToDepth( texture2D( depths, uv ) ) );\\\\n\\\\t}\\\\n\\\\tvec2 texture2DDistribution( sampler2D shadow, vec2 uv ) {\\\\n\\\\t\\\\treturn unpackRGBATo2Half( texture2D( shadow, uv ) );\\\\n\\\\t}\\\\n\\\\tfloat VSMShadow (sampler2D shadow, vec2 uv, float compare ){\\\\n\\\\t\\\\tfloat occlusion = 1.0;\\\\n\\\\t\\\\tvec2 distribution = texture2DDistribution( shadow, uv );\\\\n\\\\t\\\\tfloat hard_shadow = step( compare , distribution.x );\\\\n\\\\t\\\\tif (hard_shadow != 1.0 ) {\\\\n\\\\t\\\\t\\\\tfloat distance = compare - distribution.x ;\\\\n\\\\t\\\\t\\\\tfloat variance = max( 0.00000, distribution.y * distribution.y );\\\\n\\\\t\\\\t\\\\tfloat softness_probability = variance / (variance + distance * distance );\\\\t\\\\t\\\\tsoftness_probability = clamp( ( softness_probability - 0.3 ) / ( 0.95 - 0.3 ), 0.0, 1.0 );\\\\t\\\\t\\\\tocclusion = clamp( max( hard_shadow, softness_probability ), 0.0, 1.0 );\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\treturn occlusion;\\\\n\\\\t}\\\\n\\\\tfloat getShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord ) {\\\\n\\\\t\\\\tfloat shadow = 1.0;\\\\n\\\\t\\\\tshadowCoord.xyz /= shadowCoord.w;\\\\n\\\\t\\\\tshadowCoord.z += shadowBias;\\\\n\\\\t\\\\tbvec4 inFrustumVec = bvec4 ( shadowCoord.x >= 0.0, shadowCoord.x <= 1.0, shadowCoord.y >= 0.0, shadowCoord.y <= 1.0 );\\\\n\\\\t\\\\tbool inFrustum = all( inFrustumVec );\\\\n\\\\t\\\\tbvec2 frustumTestVec = bvec2( inFrustum, shadowCoord.z <= 1.0 );\\\\n\\\\t\\\\tbool frustumTest = all( frustumTestVec );\\\\n\\\\t\\\\tif ( frustumTest ) {\\\\n\\\\t\\\\t#if defined( SHADOWMAP_TYPE_PCF )\\\\n\\\\t\\\\t\\\\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\\\\n\\\\t\\\\t\\\\tfloat dx0 = - texelSize.x * shadowRadius;\\\\n\\\\t\\\\t\\\\tfloat dy0 = - texelSize.y * shadowRadius;\\\\n\\\\t\\\\t\\\\tfloat dx1 = + texelSize.x * shadowRadius;\\\\n\\\\t\\\\t\\\\tfloat dy1 = + texelSize.y * shadowRadius;\\\\n\\\\t\\\\t\\\\tfloat dx2 = dx0 / 2.0;\\\\n\\\\t\\\\t\\\\tfloat dy2 = dy0 / 2.0;\\\\n\\\\t\\\\t\\\\tfloat dx3 = dx1 / 2.0;\\\\n\\\\t\\\\t\\\\tfloat dy3 = dy1 / 2.0;\\\\n\\\\t\\\\t\\\\tshadow = (\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy2 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy2 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy2 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy3 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy3 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy3 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy1 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy1 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy1 ), shadowCoord.z )\\\\n\\\\t\\\\t\\\\t) * ( 1.0 / 17.0 );\\\\n\\\\t\\\\t#elif defined( SHADOWMAP_TYPE_PCF_SOFT )\\\\n\\\\t\\\\t\\\\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\\\\n\\\\t\\\\t\\\\tfloat dx = texelSize.x;\\\\n\\\\t\\\\t\\\\tfloat dy = texelSize.y;\\\\n\\\\t\\\\t\\\\tvec2 uv = shadowCoord.xy;\\\\n\\\\t\\\\t\\\\tvec2 f = fract( uv * shadowMapSize + 0.5 );\\\\n\\\\t\\\\t\\\\tuv -= f * texelSize;\\\\n\\\\t\\\\t\\\\tshadow = (\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, uv, shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, uv + vec2( dx, 0.0 ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, uv + vec2( 0.0, dy ), shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, uv + texelSize, shadowCoord.z ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, 0.0 ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 0.0 ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.x ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.x ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( texture2DCompare( shadowMap, uv + vec2( 0.0, -dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 0.0, 2.0 * dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.y ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( texture2DCompare( shadowMap, uv + vec2( dx, -dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( dx, 2.0 * dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.y ) +\\\\n\\\\t\\\\t\\\\t\\\\tmix( mix( texture2DCompare( shadowMap, uv + vec2( -dx, -dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, -dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t f.x ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t mix( texture2DCompare( shadowMap, uv + vec2( -dx, 2.0 * dy ), shadowCoord.z ), \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 2.0 * dy ), shadowCoord.z ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t f.x ),\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t f.y )\\\\n\\\\t\\\\t\\\\t) * ( 1.0 / 9.0 );\\\\n\\\\t\\\\t#elif defined( SHADOWMAP_TYPE_VSM )\\\\n\\\\t\\\\t\\\\tshadow = VSMShadow( shadowMap, shadowCoord.xy, shadowCoord.z );\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\tshadow = texture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z );\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\treturn shadow;\\\\n\\\\t}\\\\n\\\\tvec2 cubeToUV( vec3 v, float texelSizeY ) {\\\\n\\\\t\\\\tvec3 absV = abs( v );\\\\n\\\\t\\\\tfloat scaleToCube = 1.0 / max( absV.x, max( absV.y, absV.z ) );\\\\n\\\\t\\\\tabsV *= scaleToCube;\\\\n\\\\t\\\\tv *= scaleToCube * ( 1.0 - 2.0 * texelSizeY );\\\\n\\\\t\\\\tvec2 planar = v.xy;\\\\n\\\\t\\\\tfloat almostATexel = 1.5 * texelSizeY;\\\\n\\\\t\\\\tfloat almostOne = 1.0 - almostATexel;\\\\n\\\\t\\\\tif ( absV.z >= almostOne ) {\\\\n\\\\t\\\\t\\\\tif ( v.z > 0.0 )\\\\n\\\\t\\\\t\\\\t\\\\tplanar.x = 4.0 - v.x;\\\\n\\\\t\\\\t} else if ( absV.x >= almostOne ) {\\\\n\\\\t\\\\t\\\\tfloat signX = sign( v.x );\\\\n\\\\t\\\\t\\\\tplanar.x = v.z * signX + 2.0 * signX;\\\\n\\\\t\\\\t} else if ( absV.y >= almostOne ) {\\\\n\\\\t\\\\t\\\\tfloat signY = sign( v.y );\\\\n\\\\t\\\\t\\\\tplanar.x = v.x + 2.0 * signY + 2.0;\\\\n\\\\t\\\\t\\\\tplanar.y = v.z * signY - 2.0;\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\treturn vec2( 0.125, 0.25 ) * planar + vec2( 0.375, 0.75 );\\\\n\\\\t}\\\\n\\\\tfloat getPointShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord, float shadowCameraNear, float shadowCameraFar ) {\\\\n\\\\t\\\\tvec2 texelSize = vec2( 1.0 ) / ( shadowMapSize * vec2( 4.0, 2.0 ) );\\\\n\\\\t\\\\tvec3 lightToPosition = shadowCoord.xyz;\\\\n\\\\t\\\\tfloat dp = ( length( lightToPosition ) - shadowCameraNear ) / ( shadowCameraFar - shadowCameraNear );\\\\t\\\\tdp += shadowBias;\\\\n\\\\t\\\\tvec3 bd3D = normalize( lightToPosition );\\\\n\\\\t\\\\t#if defined( SHADOWMAP_TYPE_PCF ) || defined( SHADOWMAP_TYPE_PCF_SOFT ) || defined( SHADOWMAP_TYPE_VSM )\\\\n\\\\t\\\\t\\\\tvec2 offset = vec2( - 1, 1 ) * shadowRadius * texelSize.y;\\\\n\\\\t\\\\t\\\\treturn (\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyy, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyy, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyx, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyx, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxy, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxy, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxx, texelSize.y ), dp ) +\\\\n\\\\t\\\\t\\\\t\\\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxx, texelSize.y ), dp )\\\\n\\\\t\\\\t\\\\t) * ( 1.0 / 9.0 );\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\treturn texture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp );\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n#endif\\\\\\\",shadowmap_pars_vertex:\\\\\\\"#ifdef USE_SHADOWMAP\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\t\\\\tuniform mat4 directionalShadowMatrix[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tstruct DirectionalLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t};\\\\n\\\\t\\\\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\\\\n\\\\t#endif\\\\n\\\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\t\\\\tuniform mat4 spotShadowMatrix[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vSpotShadowCoord[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tstruct SpotLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t};\\\\n\\\\t\\\\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\\\\n\\\\t#endif\\\\n\\\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\t\\\\tuniform mat4 pointShadowMatrix[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\t\\\\tstruct PointLightShadow {\\\\n\\\\t\\\\t\\\\tfloat shadowBias;\\\\n\\\\t\\\\t\\\\tfloat shadowNormalBias;\\\\n\\\\t\\\\t\\\\tfloat shadowRadius;\\\\n\\\\t\\\\t\\\\tvec2 shadowMapSize;\\\\n\\\\t\\\\t\\\\tfloat shadowCameraNear;\\\\n\\\\t\\\\t\\\\tfloat shadowCameraFar;\\\\n\\\\t\\\\t};\\\\n\\\\t\\\\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\\\\n\\\\t#endif\\\\n#endif\\\\\\\",shadowmap_vertex:\\\\\\\"#ifdef USE_SHADOWMAP\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0 || NUM_SPOT_LIGHT_SHADOWS > 0 || NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\t\\\\tvec3 shadowWorldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\\\\n\\\\t\\\\tvec4 shadowWorldPosition;\\\\n\\\\t#endif\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\t\\\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * directionalLightShadows[ i ].shadowNormalBias, 0 );\\\\n\\\\t\\\\tvDirectionalShadowCoord[ i ] = directionalShadowMatrix[ i ] * shadowWorldPosition;\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\t#endif\\\\n\\\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\t\\\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * spotLightShadows[ i ].shadowNormalBias, 0 );\\\\n\\\\t\\\\tvSpotShadowCoord[ i ] = spotShadowMatrix[ i ] * shadowWorldPosition;\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\t#endif\\\\n\\\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\t\\\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * pointLightShadows[ i ].shadowNormalBias, 0 );\\\\n\\\\t\\\\tvPointShadowCoord[ i ] = pointShadowMatrix[ i ] * shadowWorldPosition;\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\t#endif\\\\n#endif\\\\\\\",shadowmask_pars_fragment:\\\\\\\"float getShadowMask() {\\\\n\\\\tfloat shadow = 1.0;\\\\n\\\\t#ifdef USE_SHADOWMAP\\\\n\\\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\\\n\\\\tDirectionalLightShadow directionalLight;\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\t\\\\tdirectionalLight = directionalLightShadows[ i ];\\\\n\\\\t\\\\tshadow *= receiveShadow ? getShadow( directionalShadowMap[ i ], directionalLight.shadowMapSize, directionalLight.shadowBias, directionalLight.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\t#endif\\\\n\\\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\\\n\\\\tSpotLightShadow spotLight;\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\t\\\\tspotLight = spotLightShadows[ i ];\\\\n\\\\t\\\\tshadow *= receiveShadow ? getShadow( spotShadowMap[ i ], spotLight.shadowMapSize, spotLight.shadowBias, spotLight.shadowRadius, vSpotShadowCoord[ i ] ) : 1.0;\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\t#endif\\\\n\\\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\\\n\\\\tPointLightShadow pointLight;\\\\n\\\\t#pragma unroll_loop_start\\\\n\\\\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\\\\n\\\\t\\\\tpointLight = pointLightShadows[ i ];\\\\n\\\\t\\\\tshadow *= receiveShadow ? getPointShadow( pointShadowMap[ i ], pointLight.shadowMapSize, pointLight.shadowBias, pointLight.shadowRadius, vPointShadowCoord[ i ], pointLight.shadowCameraNear, pointLight.shadowCameraFar ) : 1.0;\\\\n\\\\t}\\\\n\\\\t#pragma unroll_loop_end\\\\n\\\\t#endif\\\\n\\\\t#endif\\\\n\\\\treturn shadow;\\\\n}\\\\\\\",skinbase_vertex:\\\\\\\"#ifdef USE_SKINNING\\\\n\\\\tmat4 boneMatX = getBoneMatrix( skinIndex.x );\\\\n\\\\tmat4 boneMatY = getBoneMatrix( skinIndex.y );\\\\n\\\\tmat4 boneMatZ = getBoneMatrix( skinIndex.z );\\\\n\\\\tmat4 boneMatW = getBoneMatrix( skinIndex.w );\\\\n#endif\\\\\\\",skinning_pars_vertex:\\\\\\\"#ifdef USE_SKINNING\\\\n\\\\tuniform mat4 bindMatrix;\\\\n\\\\tuniform mat4 bindMatrixInverse;\\\\n\\\\t#ifdef BONE_TEXTURE\\\\n\\\\t\\\\tuniform highp sampler2D boneTexture;\\\\n\\\\t\\\\tuniform int boneTextureSize;\\\\n\\\\t\\\\tmat4 getBoneMatrix( const in float i ) {\\\\n\\\\t\\\\t\\\\tfloat j = i * 4.0;\\\\n\\\\t\\\\t\\\\tfloat x = mod( j, float( boneTextureSize ) );\\\\n\\\\t\\\\t\\\\tfloat y = floor( j / float( boneTextureSize ) );\\\\n\\\\t\\\\t\\\\tfloat dx = 1.0 / float( boneTextureSize );\\\\n\\\\t\\\\t\\\\tfloat dy = 1.0 / float( boneTextureSize );\\\\n\\\\t\\\\t\\\\ty = dy * ( y + 0.5 );\\\\n\\\\t\\\\t\\\\tvec4 v1 = texture2D( boneTexture, vec2( dx * ( x + 0.5 ), y ) );\\\\n\\\\t\\\\t\\\\tvec4 v2 = texture2D( boneTexture, vec2( dx * ( x + 1.5 ), y ) );\\\\n\\\\t\\\\t\\\\tvec4 v3 = texture2D( boneTexture, vec2( dx * ( x + 2.5 ), y ) );\\\\n\\\\t\\\\t\\\\tvec4 v4 = texture2D( boneTexture, vec2( dx * ( x + 3.5 ), y ) );\\\\n\\\\t\\\\t\\\\tmat4 bone = mat4( v1, v2, v3, v4 );\\\\n\\\\t\\\\t\\\\treturn bone;\\\\n\\\\t\\\\t}\\\\n\\\\t#else\\\\n\\\\t\\\\tuniform mat4 boneMatrices[ MAX_BONES ];\\\\n\\\\t\\\\tmat4 getBoneMatrix( const in float i ) {\\\\n\\\\t\\\\t\\\\tmat4 bone = boneMatrices[ int(i) ];\\\\n\\\\t\\\\t\\\\treturn bone;\\\\n\\\\t\\\\t}\\\\n\\\\t#endif\\\\n#endif\\\\\\\",skinning_vertex:\\\\\\\"#ifdef USE_SKINNING\\\\n\\\\tvec4 skinVertex = bindMatrix * vec4( transformed, 1.0 );\\\\n\\\\tvec4 skinned = vec4( 0.0 );\\\\n\\\\tskinned += boneMatX * skinVertex * skinWeight.x;\\\\n\\\\tskinned += boneMatY * skinVertex * skinWeight.y;\\\\n\\\\tskinned += boneMatZ * skinVertex * skinWeight.z;\\\\n\\\\tskinned += boneMatW * skinVertex * skinWeight.w;\\\\n\\\\ttransformed = ( bindMatrixInverse * skinned ).xyz;\\\\n#endif\\\\\\\",skinnormal_vertex:\\\\\\\"#ifdef USE_SKINNING\\\\n\\\\tmat4 skinMatrix = mat4( 0.0 );\\\\n\\\\tskinMatrix += skinWeight.x * boneMatX;\\\\n\\\\tskinMatrix += skinWeight.y * boneMatY;\\\\n\\\\tskinMatrix += skinWeight.z * boneMatZ;\\\\n\\\\tskinMatrix += skinWeight.w * boneMatW;\\\\n\\\\tskinMatrix = bindMatrixInverse * skinMatrix * bindMatrix;\\\\n\\\\tobjectNormal = vec4( skinMatrix * vec4( objectNormal, 0.0 ) ).xyz;\\\\n\\\\t#ifdef USE_TANGENT\\\\n\\\\t\\\\tobjectTangent = vec4( skinMatrix * vec4( objectTangent, 0.0 ) ).xyz;\\\\n\\\\t#endif\\\\n#endif\\\\\\\",specularmap_fragment:\\\\\\\"float specularStrength;\\\\n#ifdef USE_SPECULARMAP\\\\n\\\\tvec4 texelSpecular = texture2D( specularMap, vUv );\\\\n\\\\tspecularStrength = texelSpecular.r;\\\\n#else\\\\n\\\\tspecularStrength = 1.0;\\\\n#endif\\\\\\\",specularmap_pars_fragment:\\\\\\\"#ifdef USE_SPECULARMAP\\\\n\\\\tuniform sampler2D specularMap;\\\\n#endif\\\\\\\",tonemapping_fragment:\\\\\\\"#if defined( TONE_MAPPING )\\\\n\\\\tgl_FragColor.rgb = toneMapping( gl_FragColor.rgb );\\\\n#endif\\\\\\\",tonemapping_pars_fragment:\\\\\\\"#ifndef saturate\\\\n#define saturate( a ) clamp( a, 0.0, 1.0 )\\\\n#endif\\\\nuniform float toneMappingExposure;\\\\nvec3 LinearToneMapping( vec3 color ) {\\\\n\\\\treturn toneMappingExposure * color;\\\\n}\\\\nvec3 ReinhardToneMapping( vec3 color ) {\\\\n\\\\tcolor *= toneMappingExposure;\\\\n\\\\treturn saturate( color / ( vec3( 1.0 ) + color ) );\\\\n}\\\\nvec3 OptimizedCineonToneMapping( vec3 color ) {\\\\n\\\\tcolor *= toneMappingExposure;\\\\n\\\\tcolor = max( vec3( 0.0 ), color - 0.004 );\\\\n\\\\treturn pow( ( color * ( 6.2 * color + 0.5 ) ) / ( color * ( 6.2 * color + 1.7 ) + 0.06 ), vec3( 2.2 ) );\\\\n}\\\\nvec3 RRTAndODTFit( vec3 v ) {\\\\n\\\\tvec3 a = v * ( v + 0.0245786 ) - 0.000090537;\\\\n\\\\tvec3 b = v * ( 0.983729 * v + 0.4329510 ) + 0.238081;\\\\n\\\\treturn a / b;\\\\n}\\\\nvec3 ACESFilmicToneMapping( vec3 color ) {\\\\n\\\\tconst mat3 ACESInputMat = mat3(\\\\n\\\\t\\\\tvec3( 0.59719, 0.07600, 0.02840 ),\\\\t\\\\tvec3( 0.35458, 0.90834, 0.13383 ),\\\\n\\\\t\\\\tvec3( 0.04823, 0.01566, 0.83777 )\\\\n\\\\t);\\\\n\\\\tconst mat3 ACESOutputMat = mat3(\\\\n\\\\t\\\\tvec3( 1.60475, -0.10208, -0.00327 ),\\\\t\\\\tvec3( -0.53108, 1.10813, -0.07276 ),\\\\n\\\\t\\\\tvec3( -0.07367, -0.00605, 1.07602 )\\\\n\\\\t);\\\\n\\\\tcolor *= toneMappingExposure / 0.6;\\\\n\\\\tcolor = ACESInputMat * color;\\\\n\\\\tcolor = RRTAndODTFit( color );\\\\n\\\\tcolor = ACESOutputMat * color;\\\\n\\\\treturn saturate( color );\\\\n}\\\\nvec3 CustomToneMapping( vec3 color ) { return color; }\\\\\\\",transmission_fragment:\\\\\\\"#ifdef USE_TRANSMISSION\\\\n\\\\tfloat transmissionAlpha = 1.0;\\\\n\\\\tfloat transmissionFactor = transmission;\\\\n\\\\tfloat thicknessFactor = thickness;\\\\n\\\\t#ifdef USE_TRANSMISSIONMAP\\\\n\\\\t\\\\ttransmissionFactor *= texture2D( transmissionMap, vUv ).r;\\\\n\\\\t#endif\\\\n\\\\t#ifdef USE_THICKNESSMAP\\\\n\\\\t\\\\tthicknessFactor *= texture2D( thicknessMap, vUv ).g;\\\\n\\\\t#endif\\\\n\\\\tvec3 pos = vWorldPosition;\\\\n\\\\tvec3 v = normalize( cameraPosition - pos );\\\\n\\\\tvec3 n = inverseTransformDirection( normal, viewMatrix );\\\\n\\\\tvec4 transmission = getIBLVolumeRefraction(\\\\n\\\\t\\\\tn, v, roughnessFactor, material.diffuseColor, material.specularColor, material.specularF90,\\\\n\\\\t\\\\tpos, modelMatrix, viewMatrix, projectionMatrix, ior, thicknessFactor,\\\\n\\\\t\\\\tattenuationTint, attenuationDistance );\\\\n\\\\ttotalDiffuse = mix( totalDiffuse, transmission.rgb, transmissionFactor );\\\\n\\\\ttransmissionAlpha = mix( transmissionAlpha, transmission.a, transmissionFactor );\\\\n#endif\\\\\\\",transmission_pars_fragment:\\\\\\\"#ifdef USE_TRANSMISSION\\\\n\\\\tuniform float transmission;\\\\n\\\\tuniform float thickness;\\\\n\\\\tuniform float attenuationDistance;\\\\n\\\\tuniform vec3 attenuationTint;\\\\n\\\\t#ifdef USE_TRANSMISSIONMAP\\\\n\\\\t\\\\tuniform sampler2D transmissionMap;\\\\n\\\\t#endif\\\\n\\\\t#ifdef USE_THICKNESSMAP\\\\n\\\\t\\\\tuniform sampler2D thicknessMap;\\\\n\\\\t#endif\\\\n\\\\tuniform vec2 transmissionSamplerSize;\\\\n\\\\tuniform sampler2D transmissionSamplerMap;\\\\n\\\\tuniform mat4 modelMatrix;\\\\n\\\\tuniform mat4 projectionMatrix;\\\\n\\\\tvarying vec3 vWorldPosition;\\\\n\\\\tvec3 getVolumeTransmissionRay( vec3 n, vec3 v, float thickness, float ior, mat4 modelMatrix ) {\\\\n\\\\t\\\\tvec3 refractionVector = refract( - v, normalize( n ), 1.0 / ior );\\\\n\\\\t\\\\tvec3 modelScale;\\\\n\\\\t\\\\tmodelScale.x = length( vec3( modelMatrix[ 0 ].xyz ) );\\\\n\\\\t\\\\tmodelScale.y = length( vec3( modelMatrix[ 1 ].xyz ) );\\\\n\\\\t\\\\tmodelScale.z = length( vec3( modelMatrix[ 2 ].xyz ) );\\\\n\\\\t\\\\treturn normalize( refractionVector ) * thickness * modelScale;\\\\n\\\\t}\\\\n\\\\tfloat applyIorToRoughness( float roughness, float ior ) {\\\\n\\\\t\\\\treturn roughness * clamp( ior * 2.0 - 2.0, 0.0, 1.0 );\\\\n\\\\t}\\\\n\\\\tvec4 getTransmissionSample( vec2 fragCoord, float roughness, float ior ) {\\\\n\\\\t\\\\tfloat framebufferLod = log2( transmissionSamplerSize.x ) * applyIorToRoughness( roughness, ior );\\\\n\\\\t\\\\t#ifdef TEXTURE_LOD_EXT\\\\n\\\\t\\\\t\\\\treturn texture2DLodEXT( transmissionSamplerMap, fragCoord.xy, framebufferLod );\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\treturn texture2D( transmissionSamplerMap, fragCoord.xy, framebufferLod );\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n\\\\tvec3 applyVolumeAttenuation( vec3 radiance, float transmissionDistance, vec3 attenuationColor, float attenuationDistance ) {\\\\n\\\\t\\\\tif ( attenuationDistance == 0.0 ) {\\\\n\\\\t\\\\t\\\\treturn radiance;\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tvec3 attenuationCoefficient = -log( attenuationColor ) / attenuationDistance;\\\\n\\\\t\\\\t\\\\tvec3 transmittance = exp( - attenuationCoefficient * transmissionDistance );\\\\t\\\\t\\\\treturn transmittance * radiance;\\\\n\\\\t\\\\t}\\\\n\\\\t}\\\\n\\\\tvec4 getIBLVolumeRefraction( vec3 n, vec3 v, float roughness, vec3 diffuseColor, vec3 specularColor, float specularF90,\\\\n\\\\t\\\\tvec3 position, mat4 modelMatrix, mat4 viewMatrix, mat4 projMatrix, float ior, float thickness,\\\\n\\\\t\\\\tvec3 attenuationColor, float attenuationDistance ) {\\\\n\\\\t\\\\tvec3 transmissionRay = getVolumeTransmissionRay( n, v, thickness, ior, modelMatrix );\\\\n\\\\t\\\\tvec3 refractedRayExit = position + transmissionRay;\\\\n\\\\t\\\\tvec4 ndcPos = projMatrix * viewMatrix * vec4( refractedRayExit, 1.0 );\\\\n\\\\t\\\\tvec2 refractionCoords = ndcPos.xy / ndcPos.w;\\\\n\\\\t\\\\trefractionCoords += 1.0;\\\\n\\\\t\\\\trefractionCoords /= 2.0;\\\\n\\\\t\\\\tvec4 transmittedLight = getTransmissionSample( refractionCoords, roughness, ior );\\\\n\\\\t\\\\tvec3 attenuatedColor = applyVolumeAttenuation( transmittedLight.rgb, length( transmissionRay ), attenuationColor, attenuationDistance );\\\\n\\\\t\\\\tvec3 F = EnvironmentBRDF( n, v, specularColor, specularF90, roughness );\\\\n\\\\t\\\\treturn vec4( ( 1.0 - F ) * attenuatedColor * diffuseColor, transmittedLight.a );\\\\n\\\\t}\\\\n#endif\\\\\\\",uv_pars_fragment:\\\\\\\"#if ( defined( USE_UV ) && ! defined( UVS_VERTEX_ONLY ) )\\\\n\\\\tvarying vec2 vUv;\\\\n#endif\\\\\\\",uv_pars_vertex:\\\\\\\"#ifdef USE_UV\\\\n\\\\t#ifdef UVS_VERTEX_ONLY\\\\n\\\\t\\\\tvec2 vUv;\\\\n\\\\t#else\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\t#endif\\\\n\\\\tuniform mat3 uvTransform;\\\\n#endif\\\\\\\",uv_vertex:\\\\\\\"#ifdef USE_UV\\\\n\\\\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\\\\n#endif\\\\\\\",uv2_pars_fragment:\\\\\\\"#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\\\n\\\\tvarying vec2 vUv2;\\\\n#endif\\\\\\\",uv2_pars_vertex:\\\\\\\"#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\\\n\\\\tattribute vec2 uv2;\\\\n\\\\tvarying vec2 vUv2;\\\\n\\\\tuniform mat3 uv2Transform;\\\\n#endif\\\\\\\",uv2_vertex:\\\\\\\"#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\\\n\\\\tvUv2 = ( uv2Transform * vec3( uv2, 1 ) ).xy;\\\\n#endif\\\\\\\",worldpos_vertex:\\\\\\\"#if defined( USE_ENVMAP ) || defined( DISTANCE ) || defined ( USE_SHADOWMAP ) || defined ( USE_TRANSMISSION )\\\\n\\\\tvec4 worldPosition = vec4( transformed, 1.0 );\\\\n\\\\t#ifdef USE_INSTANCING\\\\n\\\\t\\\\tworldPosition = instanceMatrix * worldPosition;\\\\n\\\\t#endif\\\\n\\\\tworldPosition = modelMatrix * worldPosition;\\\\n#endif\\\\\\\",background_vert:\\\\\\\"varying vec2 vUv;\\\\nuniform mat3 uvTransform;\\\\nvoid main() {\\\\n\\\\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\\\\n\\\\tgl_Position = vec4( position.xy, 1.0, 1.0 );\\\\n}\\\\\\\",background_frag:\\\\\\\"uniform sampler2D t2D;\\\\nvarying vec2 vUv;\\\\nvoid main() {\\\\n\\\\tvec4 texColor = texture2D( t2D, vUv );\\\\n\\\\tgl_FragColor = mapTexelToLinear( texColor );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",cube_vert:\\\\\\\"varying vec3 vWorldDirection;\\\\n#include \\\\nvoid main() {\\\\n\\\\tvWorldDirection = transformDirection( position, modelMatrix );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tgl_Position.z = gl_Position.w;\\\\n}\\\\\\\",cube_frag:\\\\\\\"#include \\\\nuniform float opacity;\\\\nvarying vec3 vWorldDirection;\\\\n#include \\\\nvoid main() {\\\\n\\\\tvec3 vReflect = vWorldDirection;\\\\n\\\\t#include \\\\n\\\\tgl_FragColor = envColor;\\\\n\\\\tgl_FragColor.a *= opacity;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",depth_vert:\\\\\\\"#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvarying vec2 vHighPrecisionZW;\\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#ifdef USE_DISPLACEMENTMAP\\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t#endif\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvHighPrecisionZW = gl_Position.zw;\\\\n}\\\\\\\",depth_frag:\\\\\\\"#if DEPTH_PACKING == 3200\\\\n\\\\tuniform float opacity;\\\\n#endif\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvarying vec2 vHighPrecisionZW;\\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec4 diffuseColor = vec4( 1.0 );\\\\n\\\\t#if DEPTH_PACKING == 3200\\\\n\\\\t\\\\tdiffuseColor.a = opacity;\\\\n\\\\t#endif\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tfloat fragCoordZ = 0.5 * vHighPrecisionZW[0] / vHighPrecisionZW[1] + 0.5;\\\\n\\\\t#if DEPTH_PACKING == 3200\\\\n\\\\t\\\\tgl_FragColor = vec4( vec3( 1.0 - fragCoordZ ), opacity );\\\\n\\\\t#elif DEPTH_PACKING == 3201\\\\n\\\\t\\\\tgl_FragColor = packDepthToRGBA( fragCoordZ );\\\\n\\\\t#endif\\\\n}\\\\\\\",distanceRGBA_vert:\\\\\\\"#define DISTANCE\\\\nvarying vec3 vWorldPosition;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#ifdef USE_DISPLACEMENTMAP\\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t#endif\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvWorldPosition = worldPosition.xyz;\\\\n}\\\\\\\",distanceRGBA_frag:\\\\\\\"#define DISTANCE\\\\nuniform vec3 referencePosition;\\\\nuniform float nearDistance;\\\\nuniform float farDistance;\\\\nvarying vec3 vWorldPosition;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main () {\\\\n\\\\t#include \\\\n\\\\tvec4 diffuseColor = vec4( 1.0 );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tfloat dist = length( vWorldPosition - referencePosition );\\\\n\\\\tdist = ( dist - nearDistance ) / ( farDistance - nearDistance );\\\\n\\\\tdist = saturate( dist );\\\\n\\\\tgl_FragColor = packDepthToRGBA( dist );\\\\n}\\\\\\\",equirect_vert:\\\\\\\"varying vec3 vWorldDirection;\\\\n#include \\\\nvoid main() {\\\\n\\\\tvWorldDirection = transformDirection( position, modelMatrix );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",equirect_frag:\\\\\\\"uniform sampler2D tEquirect;\\\\nvarying vec3 vWorldDirection;\\\\n#include \\\\nvoid main() {\\\\n\\\\tvec3 direction = normalize( vWorldDirection );\\\\n\\\\tvec2 sampleUV = equirectUv( direction );\\\\n\\\\tvec4 texColor = texture2D( tEquirect, sampleUV );\\\\n\\\\tgl_FragColor = mapTexelToLinear( texColor );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",linedashed_vert:\\\\\\\"uniform float scale;\\\\nattribute float lineDistance;\\\\nvarying float vLineDistance;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\tvLineDistance = scale * lineDistance;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",linedashed_frag:\\\\\\\"uniform vec3 diffuse;\\\\nuniform float opacity;\\\\nuniform float dashSize;\\\\nuniform float totalSize;\\\\nvarying float vLineDistance;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tif ( mod( vLineDistance, totalSize ) > dashSize ) {\\\\n\\\\t\\\\tdiscard;\\\\n\\\\t}\\\\n\\\\tvec3 outgoingLight = vec3( 0.0 );\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\toutgoingLight = diffuseColor.rgb;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshbasic_vert:\\\\\\\"#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#if defined ( USE_ENVMAP ) || defined ( USE_SKINNING )\\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t\\\\t#include \\\\n\\\\t#endif\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshbasic_frag:\\\\\\\"uniform vec3 diffuse;\\\\nuniform float opacity;\\\\n#ifndef FLAT_SHADED\\\\n\\\\tvarying vec3 vNormal;\\\\n#endif\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\t#ifdef USE_LIGHTMAP\\\\n\\\\t\\\\tvec4 lightMapTexel= texture2D( lightMap, vUv2 );\\\\n\\\\t\\\\treflectedLight.indirectDiffuse += lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\\\n\\\\t#else\\\\n\\\\t\\\\treflectedLight.indirectDiffuse += vec3( 1.0 );\\\\n\\\\t#endif\\\\n\\\\t#include \\\\n\\\\treflectedLight.indirectDiffuse *= diffuseColor.rgb;\\\\n\\\\tvec3 outgoingLight = reflectedLight.indirectDiffuse;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshlambert_vert:\\\\\\\"#define LAMBERT\\\\nvarying vec3 vLightFront;\\\\nvarying vec3 vIndirectFront;\\\\n#ifdef DOUBLE_SIDED\\\\n\\\\tvarying vec3 vLightBack;\\\\n\\\\tvarying vec3 vIndirectBack;\\\\n#endif\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshlambert_frag:\\\\\\\"uniform vec3 diffuse;\\\\nuniform vec3 emissive;\\\\nuniform float opacity;\\\\nvarying vec3 vLightFront;\\\\nvarying vec3 vIndirectFront;\\\\n#ifdef DOUBLE_SIDED\\\\n\\\\tvarying vec3 vLightBack;\\\\n\\\\tvarying vec3 vIndirectBack;\\\\n#endif\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\tvec3 totalEmissiveRadiance = emissive;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\treflectedLight.indirectDiffuse += ( gl_FrontFacing ) ? vIndirectFront : vIndirectBack;\\\\n\\\\t#else\\\\n\\\\t\\\\treflectedLight.indirectDiffuse += vIndirectFront;\\\\n\\\\t#endif\\\\n\\\\t#include \\\\n\\\\treflectedLight.indirectDiffuse *= BRDF_Lambert( diffuseColor.rgb );\\\\n\\\\t#ifdef DOUBLE_SIDED\\\\n\\\\t\\\\treflectedLight.directDiffuse = ( gl_FrontFacing ) ? vLightFront : vLightBack;\\\\n\\\\t#else\\\\n\\\\t\\\\treflectedLight.directDiffuse = vLightFront;\\\\n\\\\t#endif\\\\n\\\\treflectedLight.directDiffuse *= BRDF_Lambert( diffuseColor.rgb ) * getShadowMask();\\\\n\\\\t#include \\\\n\\\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshmatcap_vert:\\\\\\\"#define MATCAP\\\\nvarying vec3 vViewPosition;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n}\\\\\\\",meshmatcap_frag:\\\\\\\"#define MATCAP\\\\nuniform vec3 diffuse;\\\\nuniform float opacity;\\\\nuniform sampler2D matcap;\\\\nvarying vec3 vViewPosition;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvec3 viewDir = normalize( vViewPosition );\\\\n\\\\tvec3 x = normalize( vec3( viewDir.z, 0.0, - viewDir.x ) );\\\\n\\\\tvec3 y = cross( viewDir, x );\\\\n\\\\tvec2 uv = vec2( dot( x, normal ), dot( y, normal ) ) * 0.495 + 0.5;\\\\n\\\\t#ifdef USE_MATCAP\\\\n\\\\t\\\\tvec4 matcapColor = texture2D( matcap, uv );\\\\n\\\\t\\\\tmatcapColor = matcapTexelToLinear( matcapColor );\\\\n\\\\t#else\\\\n\\\\t\\\\tvec4 matcapColor = vec4( 1.0 );\\\\n\\\\t#endif\\\\n\\\\tvec3 outgoingLight = diffuseColor.rgb * matcapColor.rgb;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshnormal_vert:\\\\\\\"#define NORMAL\\\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\\\n\\\\tvarying vec3 vViewPosition;\\\\n#endif\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n#endif\\\\n}\\\\\\\",meshnormal_frag:\\\\\\\"#define NORMAL\\\\nuniform float opacity;\\\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\\\n\\\\tvarying vec3 vViewPosition;\\\\n#endif\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tgl_FragColor = vec4( packNormalToRGB( normal ), opacity );\\\\n}\\\\\\\",meshphong_vert:\\\\\\\"#define PHONG\\\\nvarying vec3 vViewPosition;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshphong_frag:\\\\\\\"#define PHONG\\\\nuniform vec3 diffuse;\\\\nuniform vec3 emissive;\\\\nuniform vec3 specular;\\\\nuniform float shininess;\\\\nuniform float opacity;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\tvec3 totalEmissiveRadiance = emissive;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + reflectedLight.directSpecular + reflectedLight.indirectSpecular + totalEmissiveRadiance;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshphysical_vert:\\\\\\\"#define STANDARD\\\\nvarying vec3 vViewPosition;\\\\n#ifdef USE_TRANSMISSION\\\\n\\\\tvarying vec3 vWorldPosition;\\\\n#endif\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n#ifdef USE_TRANSMISSION\\\\n\\\\tvWorldPosition = worldPosition.xyz;\\\\n#endif\\\\n}\\\\\\\",meshphysical_frag:\\\\\\\"#define STANDARD\\\\n#ifdef PHYSICAL\\\\n\\\\t#define IOR\\\\n\\\\t#define SPECULAR\\\\n#endif\\\\nuniform vec3 diffuse;\\\\nuniform vec3 emissive;\\\\nuniform float roughness;\\\\nuniform float metalness;\\\\nuniform float opacity;\\\\n#ifdef IOR\\\\n\\\\tuniform float ior;\\\\n#endif\\\\n#ifdef SPECULAR\\\\n\\\\tuniform float specularIntensity;\\\\n\\\\tuniform vec3 specularTint;\\\\n\\\\t#ifdef USE_SPECULARINTENSITYMAP\\\\n\\\\t\\\\tuniform sampler2D specularIntensityMap;\\\\n\\\\t#endif\\\\n\\\\t#ifdef USE_SPECULARTINTMAP\\\\n\\\\t\\\\tuniform sampler2D specularTintMap;\\\\n\\\\t#endif\\\\n#endif\\\\n#ifdef USE_CLEARCOAT\\\\n\\\\tuniform float clearcoat;\\\\n\\\\tuniform float clearcoatRoughness;\\\\n#endif\\\\n#ifdef USE_SHEEN\\\\n\\\\tuniform vec3 sheenTint;\\\\n\\\\tuniform float sheenRoughness;\\\\n#endif\\\\nvarying vec3 vViewPosition;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\tvec3 totalEmissiveRadiance = emissive;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvec3 totalDiffuse = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse;\\\\n\\\\tvec3 totalSpecular = reflectedLight.directSpecular + reflectedLight.indirectSpecular;\\\\n\\\\t#include \\\\n\\\\tvec3 outgoingLight = totalDiffuse + totalSpecular + totalEmissiveRadiance;\\\\n\\\\t#ifdef USE_CLEARCOAT\\\\n\\\\t\\\\tfloat dotNVcc = saturate( dot( geometry.clearcoatNormal, geometry.viewDir ) );\\\\n\\\\t\\\\tvec3 Fcc = F_Schlick( material.clearcoatF0, material.clearcoatF90, dotNVcc );\\\\n\\\\t\\\\toutgoingLight = outgoingLight * ( 1.0 - clearcoat * Fcc ) + clearcoatSpecular * clearcoat;\\\\n\\\\t#endif\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshtoon_vert:\\\\\\\"#define TOON\\\\nvarying vec3 vViewPosition;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvViewPosition = - mvPosition.xyz;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",meshtoon_frag:\\\\\\\"#define TOON\\\\nuniform vec3 diffuse;\\\\nuniform vec3 emissive;\\\\nuniform float opacity;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\\\n\\\\tvec3 totalEmissiveRadiance = emissive;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",points_vert:\\\\\\\"uniform float size;\\\\nuniform float scale;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\tgl_PointSize = size;\\\\n\\\\t#ifdef USE_SIZEATTENUATION\\\\n\\\\t\\\\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\\\\n\\\\t\\\\tif ( isPerspective ) gl_PointSize *= ( scale / - mvPosition.z );\\\\n\\\\t#endif\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",points_frag:\\\\\\\"uniform vec3 diffuse;\\\\nuniform float opacity;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec3 outgoingLight = vec3( 0.0 );\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\toutgoingLight = diffuseColor.rgb;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",shadow_vert:\\\\\\\"#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",shadow_frag:\\\\\\\"uniform vec3 color;\\\\nuniform float opacity;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\tgl_FragColor = vec4( color, opacity * ( 1.0 - getShadowMask() ) );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",sprite_vert:\\\\\\\"uniform float rotation;\\\\nuniform vec2 center;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec4 mvPosition = modelViewMatrix * vec4( 0.0, 0.0, 0.0, 1.0 );\\\\n\\\\tvec2 scale;\\\\n\\\\tscale.x = length( vec3( modelMatrix[ 0 ].x, modelMatrix[ 0 ].y, modelMatrix[ 0 ].z ) );\\\\n\\\\tscale.y = length( vec3( modelMatrix[ 1 ].x, modelMatrix[ 1 ].y, modelMatrix[ 1 ].z ) );\\\\n\\\\t#ifndef USE_SIZEATTENUATION\\\\n\\\\t\\\\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\\\\n\\\\t\\\\tif ( isPerspective ) scale *= - mvPosition.z;\\\\n\\\\t#endif\\\\n\\\\tvec2 alignedPosition = ( position.xy - ( center - vec2( 0.5 ) ) ) * scale;\\\\n\\\\tvec2 rotatedPosition;\\\\n\\\\trotatedPosition.x = cos( rotation ) * alignedPosition.x - sin( rotation ) * alignedPosition.y;\\\\n\\\\trotatedPosition.y = sin( rotation ) * alignedPosition.x + cos( rotation ) * alignedPosition.y;\\\\n\\\\tmvPosition.xy += rotatedPosition;\\\\n\\\\tgl_Position = projectionMatrix * mvPosition;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\",sprite_frag:\\\\\\\"uniform vec3 diffuse;\\\\nuniform float opacity;\\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\n#include \\\\nvoid main() {\\\\n\\\\t#include \\\\n\\\\tvec3 outgoingLight = vec3( 0.0 );\\\\n\\\\tvec4 diffuseColor = vec4( diffuse, opacity );\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\toutgoingLight = diffuseColor.rgb;\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n}\\\\\\\"},$T={common:{diffuse:{value:new qw(16777215)},opacity:{value:1},map:{value:null},uvTransform:{value:new db},uv2Transform:{value:new db},alphaMap:{value:null},alphaTest:{value:0}},specularmap:{specularMap:{value:null}},envmap:{envMap:{value:null},flipEnvMap:{value:-1},reflectivity:{value:1},ior:{value:1.5},refractionRatio:{value:.98},maxMipLevel:{value:0}},aomap:{aoMap:{value:null},aoMapIntensity:{value:1}},lightmap:{lightMap:{value:null},lightMapIntensity:{value:1}},emissivemap:{emissiveMap:{value:null}},bumpmap:{bumpMap:{value:null},bumpScale:{value:1}},normalmap:{normalMap:{value:null},normalScale:{value:new ub(1,1)}},displacementmap:{displacementMap:{value:null},displacementScale:{value:1},displacementBias:{value:0}},roughnessmap:{roughnessMap:{value:null}},metalnessmap:{metalnessMap:{value:null}},gradientmap:{gradientMap:{value:null}},fog:{fogDensity:{value:25e-5},fogNear:{value:1},fogFar:{value:2e3},fogColor:{value:new qw(16777215)}},lights:{ambientLightColor:{value:[]},lightProbe:{value:[]},directionalLights:{value:[],properties:{direction:{},color:{}}},directionalLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{}}},directionalShadowMap:{value:[]},directionalShadowMatrix:{value:[]},spotLights:{value:[],properties:{color:{},position:{},direction:{},distance:{},coneCos:{},penumbraCos:{},decay:{}}},spotLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{}}},spotShadowMap:{value:[]},spotShadowMatrix:{value:[]},pointLights:{value:[],properties:{color:{},position:{},decay:{},distance:{}}},pointLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{},shadowCameraNear:{},shadowCameraFar:{}}},pointShadowMap:{value:[]},pointShadowMatrix:{value:[]},hemisphereLights:{value:[],properties:{direction:{},skyColor:{},groundColor:{}}},rectAreaLights:{value:[],properties:{color:{},position:{},width:{},height:{}}},ltc_1:{value:null},ltc_2:{value:null}},points:{diffuse:{value:new qw(16777215)},opacity:{value:1},size:{value:1},scale:{value:1},map:{value:null},alphaMap:{value:null},alphaTest:{value:0},uvTransform:{value:new db}},sprite:{diffuse:{value:new qw(16777215)},opacity:{value:1},center:{value:new ub(.5,.5)},rotation:{value:0},map:{value:null},alphaMap:{value:null},alphaTest:{value:0},uvTransform:{value:new db}}},JT={basic:{uniforms:NT([$T.common,$T.specularmap,$T.envmap,$T.aomap,$T.lightmap,$T.fog]),vertexShader:YT.meshbasic_vert,fragmentShader:YT.meshbasic_frag},lambert:{uniforms:NT([$T.common,$T.specularmap,$T.envmap,$T.aomap,$T.lightmap,$T.emissivemap,$T.fog,$T.lights,{emissive:{value:new qw(0)}}]),vertexShader:YT.meshlambert_vert,fragmentShader:YT.meshlambert_frag},phong:{uniforms:NT([$T.common,$T.specularmap,$T.envmap,$T.aomap,$T.lightmap,$T.emissivemap,$T.bumpmap,$T.normalmap,$T.displacementmap,$T.fog,$T.lights,{emissive:{value:new qw(0)},specular:{value:new qw(1118481)},shininess:{value:30}}]),vertexShader:YT.meshphong_vert,fragmentShader:YT.meshphong_frag},standard:{uniforms:NT([$T.common,$T.envmap,$T.aomap,$T.lightmap,$T.emissivemap,$T.bumpmap,$T.normalmap,$T.displacementmap,$T.roughnessmap,$T.metalnessmap,$T.fog,$T.lights,{emissive:{value:new qw(0)},roughness:{value:1},metalness:{value:0},envMapIntensity:{value:1}}]),vertexShader:YT.meshphysical_vert,fragmentShader:YT.meshphysical_frag},toon:{uniforms:NT([$T.common,$T.aomap,$T.lightmap,$T.emissivemap,$T.bumpmap,$T.normalmap,$T.displacementmap,$T.gradientmap,$T.fog,$T.lights,{emissive:{value:new qw(0)}}]),vertexShader:YT.meshtoon_vert,fragmentShader:YT.meshtoon_frag},matcap:{uniforms:NT([$T.common,$T.bumpmap,$T.normalmap,$T.displacementmap,$T.fog,{matcap:{value:null}}]),vertexShader:YT.meshmatcap_vert,fragmentShader:YT.meshmatcap_frag},points:{uniforms:NT([$T.points,$T.fog]),vertexShader:YT.points_vert,fragmentShader:YT.points_frag},dashed:{uniforms:NT([$T.common,$T.fog,{scale:{value:1},dashSize:{value:1},totalSize:{value:2}}]),vertexShader:YT.linedashed_vert,fragmentShader:YT.linedashed_frag},depth:{uniforms:NT([$T.common,$T.displacementmap]),vertexShader:YT.depth_vert,fragmentShader:YT.depth_frag},normal:{uniforms:NT([$T.common,$T.bumpmap,$T.normalmap,$T.displacementmap,{opacity:{value:1}}]),vertexShader:YT.meshnormal_vert,fragmentShader:YT.meshnormal_frag},sprite:{uniforms:NT([$T.sprite,$T.fog]),vertexShader:YT.sprite_vert,fragmentShader:YT.sprite_frag},background:{uniforms:{uvTransform:{value:new db},t2D:{value:null}},vertexShader:YT.background_vert,fragmentShader:YT.background_frag},cube:{uniforms:NT([$T.envmap,{opacity:{value:1}}]),vertexShader:YT.cube_vert,fragmentShader:YT.cube_frag},equirect:{uniforms:{tEquirect:{value:null}},vertexShader:YT.equirect_vert,fragmentShader:YT.equirect_frag},distanceRGBA:{uniforms:NT([$T.common,$T.displacementmap,{referencePosition:{value:new Ab},nearDistance:{value:1},farDistance:{value:1e3}}]),vertexShader:YT.distanceRGBA_vert,fragmentShader:YT.distanceRGBA_frag},shadow:{uniforms:NT([$T.lights,$T.fog,{color:{value:new qw(0)},opacity:{value:1}}]),vertexShader:YT.shadow_vert,fragmentShader:YT.shadow_frag}};function ZT(t,e,n,i,s){const r=new qw(0);let o,a,l=0,c=null,h=0,u=null;function d(t,e){n.buffers.color.setClear(t.r,t.g,t.b,e,s)}return{getClearColor:function(){return r},setClearColor:function(t,e=1){r.set(t),l=e,d(r,l)},getClearAlpha:function(){return l},setClearAlpha:function(t){l=t,d(r,l)},render:function(n,s){let p=!1,_=!0===s.isScene?s.background:null;_&&_.isTexture&&(_=e.get(_));const m=t.xr,f=m.getSession&&m.getSession();f&&\\\\\\\"additive\\\\\\\"===f.environmentBlendMode&&(_=null),null===_?d(r,l):_&&_.isColor&&(d(_,1),p=!0),(t.autoClear||p)&&t.clear(t.autoClearColor,t.autoClearDepth,t.autoClearStencil),_&&(_.isCubeTexture||_.mapping===mx)?(void 0===a&&(a=new MT(new ST(1,1,1),new OT({name:\\\\\\\"BackgroundCubeMaterial\\\\\\\",uniforms:CT(JT.cube.uniforms),vertexShader:JT.cube.vertexShader,fragmentShader:JT.cube.fragmentShader,side:1,depthTest:!1,depthWrite:!1,fog:!1})),a.geometry.deleteAttribute(\\\\\\\"normal\\\\\\\"),a.geometry.deleteAttribute(\\\\\\\"uv\\\\\\\"),a.onBeforeRender=function(t,e,n){this.matrixWorld.copyPosition(n.matrixWorld)},Object.defineProperty(a.material,\\\\\\\"envMap\\\\\\\",{get:function(){return this.uniforms.envMap.value}}),i.update(a)),a.material.uniforms.envMap.value=_,a.material.uniforms.flipEnvMap.value=_.isCubeTexture&&!1===_.isRenderTargetTexture?-1:1,c===_&&h===_.version&&u===t.toneMapping||(a.material.needsUpdate=!0,c=_,h=_.version,u=t.toneMapping),n.unshift(a,a.geometry,a.material,0,0,null)):_&&_.isTexture&&(void 0===o&&(o=new MT(new XT(2,2),new OT({name:\\\\\\\"BackgroundMaterial\\\\\\\",uniforms:CT(JT.background.uniforms),vertexShader:JT.background.vertexShader,fragmentShader:JT.background.fragmentShader,side:0,depthTest:!1,depthWrite:!1,fog:!1})),o.geometry.deleteAttribute(\\\\\\\"normal\\\\\\\"),Object.defineProperty(o.material,\\\\\\\"map\\\\\\\",{get:function(){return this.uniforms.t2D.value}}),i.update(o)),o.material.uniforms.t2D.value=_,!0===_.matrixAutoUpdate&&_.updateMatrix(),o.material.uniforms.uvTransform.value.copy(_.matrix),c===_&&h===_.version&&u===t.toneMapping||(o.material.needsUpdate=!0,c=_,h=_.version,u=t.toneMapping),n.unshift(o,o.geometry,o.material,0,0,null))}}}function QT(t,e,n,i){const s=t.getParameter(34921),r=i.isWebGL2?null:e.get(\\\\\\\"OES_vertex_array_object\\\\\\\"),o=i.isWebGL2||null!==r,a={},l=d(null);let c=l;function h(e){return i.isWebGL2?t.bindVertexArray(e):r.bindVertexArrayOES(e)}function u(e){return i.isWebGL2?t.deleteVertexArray(e):r.deleteVertexArrayOES(e)}function d(t){const e=[],n=[],i=[];for(let t=0;t=0){let r=l[e];if(void 0===r&&(\\\\\\\"instanceMatrix\\\\\\\"===e&&s.instanceMatrix&&(r=s.instanceMatrix),\\\\\\\"instanceColor\\\\\\\"===e&&s.instanceColor&&(r=s.instanceColor)),void 0!==r){const e=r.normalized,o=r.itemSize,l=n.get(r);if(void 0===l)continue;const c=l.buffer,h=l.type,u=l.bytesPerElement;if(r.isInterleavedBufferAttribute){const n=r.data,l=n.stride,d=r.offset;if(n&&n.isInstancedInterleavedBuffer){for(let t=0;t0&&t.getShaderPrecisionFormat(35632,36338).precision>0)return\\\\\\\"highp\\\\\\\";e=\\\\\\\"mediump\\\\\\\"}return\\\\\\\"mediump\\\\\\\"===e&&t.getShaderPrecisionFormat(35633,36337).precision>0&&t.getShaderPrecisionFormat(35632,36337).precision>0?\\\\\\\"mediump\\\\\\\":\\\\\\\"lowp\\\\\\\"}const r=\\\\\\\"undefined\\\\\\\"!=typeof WebGL2RenderingContext&&t instanceof WebGL2RenderingContext||\\\\\\\"undefined\\\\\\\"!=typeof WebGL2ComputeRenderingContext&&t instanceof WebGL2ComputeRenderingContext;let o=void 0!==n.precision?n.precision:\\\\\\\"highp\\\\\\\";const a=s(o);a!==o&&(console.warn(\\\\\\\"THREE.WebGLRenderer:\\\\\\\",o,\\\\\\\"not supported, using\\\\\\\",a,\\\\\\\"instead.\\\\\\\"),o=a);const l=r||e.has(\\\\\\\"WEBGL_draw_buffers\\\\\\\"),c=!0===n.logarithmicDepthBuffer,h=t.getParameter(34930),u=t.getParameter(35660),d=t.getParameter(3379),p=t.getParameter(34076),_=t.getParameter(34921),m=t.getParameter(36347),f=t.getParameter(36348),g=t.getParameter(36349),v=u>0,y=r||e.has(\\\\\\\"OES_texture_float\\\\\\\");return{isWebGL2:r,drawBuffers:l,getMaxAnisotropy:function(){if(void 0!==i)return i;if(!0===e.has(\\\\\\\"EXT_texture_filter_anisotropic\\\\\\\")){const n=e.get(\\\\\\\"EXT_texture_filter_anisotropic\\\\\\\");i=t.getParameter(n.MAX_TEXTURE_MAX_ANISOTROPY_EXT)}else i=0;return i},getMaxPrecision:s,precision:o,logarithmicDepthBuffer:c,maxTextures:h,maxVertexTextures:u,maxTextureSize:d,maxCubemapSize:p,maxAttributes:_,maxVertexUniforms:m,maxVaryings:f,maxFragmentUniforms:g,vertexTextures:v,floatFragmentTextures:y,floatVertexTextures:v&&y,maxSamples:r?t.getParameter(36183):0}}function eA(t){const e=this;let n=null,i=0,s=!1,r=!1;const o=new GT,a=new db,l={value:null,needsUpdate:!1};function c(){l.value!==n&&(l.value=n,l.needsUpdate=i>0),e.numPlanes=i,e.numIntersection=0}function h(t,n,i,s){const r=null!==t?t.length:0;let c=null;if(0!==r){if(c=l.value,!0!==s||null===c){const e=i+4*r,s=n.matrixWorldInverse;a.getNormalMatrix(s),(null===c||c.length0){const o=t.getRenderTarget(),a=new BT(r.height/2);return a.fromEquirectangularTexture(t,s),e.set(s,a),t.setRenderTarget(o),s.addEventListener(\\\\\\\"dispose\\\\\\\",i),n(a.texture,s.mapping)}return null}}}return s},dispose:function(){e=new WeakMap}}}JT.physical={uniforms:NT([JT.standard.uniforms,{clearcoat:{value:0},clearcoatMap:{value:null},clearcoatRoughness:{value:0},clearcoatRoughnessMap:{value:null},clearcoatNormalScale:{value:new ub(1,1)},clearcoatNormalMap:{value:null},sheen:{value:0},sheenTint:{value:new qw(0)},sheenRoughness:{value:0},transmission:{value:0},transmissionMap:{value:null},transmissionSamplerSize:{value:new ub},transmissionSamplerMap:{value:null},thickness:{value:0},thicknessMap:{value:null},attenuationDistance:{value:0},attenuationTint:{value:new qw(0)},specularIntensity:{value:0},specularIntensityMap:{value:null},specularTint:{value:new qw(1,1,1)},specularTintMap:{value:null}}]),vertexShader:YT.meshphysical_vert,fragmentShader:YT.meshphysical_frag};class iA extends PT{constructor(t=-1,e=1,n=1,i=-1,s=.1,r=2e3){super(),this.type=\\\\\\\"OrthographicCamera\\\\\\\",this.zoom=1,this.view=null,this.left=t,this.right=e,this.top=n,this.bottom=i,this.near=s,this.far=r,this.updateProjectionMatrix()}copy(t,e){return super.copy(t,e),this.left=t.left,this.right=t.right,this.top=t.top,this.bottom=t.bottom,this.near=t.near,this.far=t.far,this.zoom=t.zoom,this.view=null===t.view?null:Object.assign({},t.view),this}setViewOffset(t,e,n,i,s,r){null===this.view&&(this.view={enabled:!0,fullWidth:1,fullHeight:1,offsetX:0,offsetY:0,width:1,height:1}),this.view.enabled=!0,this.view.fullWidth=t,this.view.fullHeight=e,this.view.offsetX=n,this.view.offsetY=i,this.view.width=s,this.view.height=r,this.updateProjectionMatrix()}clearViewOffset(){null!==this.view&&(this.view.enabled=!1),this.updateProjectionMatrix()}updateProjectionMatrix(){const t=(this.right-this.left)/(2*this.zoom),e=(this.top-this.bottom)/(2*this.zoom),n=(this.right+this.left)/2,i=(this.top+this.bottom)/2;let s=n-t,r=n+t,o=i+e,a=i-e;if(null!==this.view&&this.view.enabled){const t=(this.right-this.left)/this.view.fullWidth/this.zoom,e=(this.top-this.bottom)/this.view.fullHeight/this.zoom;s+=t*this.view.offsetX,r=s+t*this.view.width,o-=e*this.view.offsetY,a=o-e*this.view.height}this.projectionMatrix.makeOrthographic(s,r,o,a,this.near,this.far),this.projectionMatrixInverse.copy(this.projectionMatrix).invert()}toJSON(t){const e=super.toJSON(t);return e.object.zoom=this.zoom,e.object.left=this.left,e.object.right=this.right,e.object.top=this.top,e.object.bottom=this.bottom,e.object.near=this.near,e.object.far=this.far,null!==this.view&&(e.object.view=Object.assign({},this.view)),e}}iA.prototype.isOrthographicCamera=!0;class sA extends OT{constructor(t){super(t),this.type=\\\\\\\"RawShaderMaterial\\\\\\\"}}sA.prototype.isRawShaderMaterial=!0;const rA=Math.pow(2,8),oA=[.125,.215,.35,.446,.526,.582],aA=5+oA.length,lA=20,cA={[Hx]:0,[jx]:1,[qx]:2,3004:3,3005:4,3006:5,[Wx]:6},hA=new iA,{_lodPlanes:uA,_sizeLods:dA,_sigmas:pA}=bA(),_A=new qw;let mA=null;const fA=(1+Math.sqrt(5))/2,gA=1/fA,vA=[new Ab(1,1,1),new Ab(-1,1,1),new Ab(1,1,-1),new Ab(-1,1,-1),new Ab(0,fA,gA),new Ab(0,fA,-gA),new Ab(gA,0,fA),new Ab(-gA,0,fA),new Ab(fA,gA,0),new Ab(-fA,gA,0)];class yA{constructor(t){this._renderer=t,this._pingPongRenderTarget=null,this._blurMaterial=function(t){const e=new Float32Array(t),n=new Ab(0,1,0);return new sA({name:\\\\\\\"SphericalGaussianBlur\\\\\\\",defines:{n:t},uniforms:{envMap:{value:null},samples:{value:1},weights:{value:e},latitudinal:{value:!1},dTheta:{value:0},mipInt:{value:0},poleAxis:{value:n},inputEncoding:{value:cA[3e3]},outputEncoding:{value:cA[3e3]}},vertexShader:EA(),fragmentShader:`\\\\n\\\\n\\\\t\\\\t\\\\tprecision mediump float;\\\\n\\\\t\\\\t\\\\tprecision mediump int;\\\\n\\\\n\\\\t\\\\t\\\\tvarying vec3 vOutputDirection;\\\\n\\\\n\\\\t\\\\t\\\\tuniform sampler2D envMap;\\\\n\\\\t\\\\t\\\\tuniform int samples;\\\\n\\\\t\\\\t\\\\tuniform float weights[ n ];\\\\n\\\\t\\\\t\\\\tuniform bool latitudinal;\\\\n\\\\t\\\\t\\\\tuniform float dTheta;\\\\n\\\\t\\\\t\\\\tuniform float mipInt;\\\\n\\\\t\\\\t\\\\tuniform vec3 poleAxis;\\\\n\\\\n\\\\t\\\\t\\\\t${SA()}\\\\n\\\\n\\\\t\\\\t\\\\t#define ENVMAP_TYPE_CUBE_UV\\\\n\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t\\\\tvec3 getSample( float theta, vec3 axis ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tfloat cosTheta = cos( theta );\\\\n\\\\t\\\\t\\\\t\\\\t// Rodrigues' axis-angle rotation\\\\n\\\\t\\\\t\\\\t\\\\tvec3 sampleDirection = vOutputDirection * cosTheta\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t+ cross( axis, vOutputDirection ) * sin( theta )\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t+ axis * dot( axis, vOutputDirection ) * ( 1.0 - cosTheta );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn bilinearCubeUV( envMap, sampleDirection, mipInt );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvec3 axis = latitudinal ? poleAxis : cross( poleAxis, vOutputDirection );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tif ( all( equal( axis, vec3( 0.0 ) ) ) ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\taxis = vec3( vOutputDirection.z, 0.0, - vOutputDirection.x );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t\\\\taxis = normalize( axis );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb += weights[ 0 ] * getSample( 0.0, axis );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tfor ( int i = 1; i < n; i++ ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tif ( i >= samples ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tbreak;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat theta = dTheta * float( i );\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb += weights[ i ] * getSample( -1.0 * theta, axis );\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb += weights[ i ] * getSample( theta, axis );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = linearToOutputTexel( gl_FragColor );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t`,blending:0,depthTest:!1,depthWrite:!1})}(lA),this._equirectShader=null,this._cubemapShader=null,this._compileMaterial(this._blurMaterial)}fromScene(t,e=0,n=.1,i=100){mA=this._renderer.getRenderTarget();const s=this._allocateTargets();return this._sceneToCubeUV(t,n,i,s),e>0&&this._blur(s,0,0,e),this._applyPMREM(s),this._cleanup(s),s}fromEquirectangular(t){return this._fromTexture(t)}fromCubemap(t){return this._fromTexture(t)}compileCubemapShader(){null===this._cubemapShader&&(this._cubemapShader=MA(),this._compileMaterial(this._cubemapShader))}compileEquirectangularShader(){null===this._equirectShader&&(this._equirectShader=AA(),this._compileMaterial(this._equirectShader))}dispose(){this._blurMaterial.dispose(),null!==this._cubemapShader&&this._cubemapShader.dispose(),null!==this._equirectShader&&this._equirectShader.dispose();for(let t=0;t2?rA:0,rA,rA),a.setRenderTarget(i),p&&a.render(d,s),a.render(t,s)}d.geometry.dispose(),d.material.dispose(),a.toneMapping=h,a.outputEncoding=c,a.autoClear=l,t.background=_}_setEncoding(t,e){!0===this._renderer.capabilities.isWebGL2&&e.format===Rx&&e.type===Ex&&e.encoding===jx?t.value=cA[3e3]:t.value=cA[e.encoding]}_textureToCubeUV(t,e){const n=this._renderer;t.isCubeTexture?null==this._cubemapShader&&(this._cubemapShader=MA()):null==this._equirectShader&&(this._equirectShader=AA());const i=t.isCubeTexture?this._cubemapShader:this._equirectShader,s=new MT(uA[0],i),r=i.uniforms;r.envMap.value=t,t.isCubeTexture||r.texelSize.value.set(1/t.image.width,1/t.image.height),this._setEncoding(r.inputEncoding,t),this._setEncoding(r.outputEncoding,e.texture),TA(e,0,0,3*rA,2*rA),n.setRenderTarget(e),n.render(s,hA)}_applyPMREM(t){const e=this._renderer,n=e.autoClear;e.autoClear=!1;for(let e=1;elA&&console.warn(`sigmaRadians, ${s}, is too large and will clip, as it requested ${_} samples when the maximum is set to 20`);const m=[];let f=0;for(let t=0;t4?i-8+4:0),3*g,2*g),a.setRenderTarget(e),a.render(c,hA)}}function xA(t){return void 0!==t&&t.type===Ex&&(t.encoding===Hx||t.encoding===jx||t.encoding===Wx)}function bA(){const t=[],e=[],n=[];let i=8;for(let s=0;s4?o=oA[s-8+4-1]:0==s&&(o=0),n.push(o);const a=1/(r-1),l=-a/2,c=1+a/2,h=[l,l,c,l,c,c,l,l,c,c,l,c],u=6,d=6,p=3,_=2,m=1,f=new Float32Array(p*d*u),g=new Float32Array(_*d*u),v=new Float32Array(m*d*u);for(let t=0;t2?0:-1,i=[e,n,0,e+2/3,n,0,e+2/3,n+1,0,e,n,0,e+2/3,n+1,0,e,n+1,0];f.set(i,p*d*t),g.set(h,_*d*t);const s=[t,t,t,t,t,t];v.set(s,m*d*t)}const y=new aT;y.setAttribute(\\\\\\\"position\\\\\\\",new Jw(f,p)),y.setAttribute(\\\\\\\"uv\\\\\\\",new Jw(g,_)),y.setAttribute(\\\\\\\"faceIndex\\\\\\\",new Jw(v,m)),t.push(y),i>4&&i--}return{_lodPlanes:t,_sizeLods:e,_sigmas:n}}function wA(t){const e=new bb(3*rA,3*rA,t);return e.texture.mapping=mx,e.texture.name=\\\\\\\"PMREM.cubeUv\\\\\\\",e.scissorTest=!0,e}function TA(t,e,n,i,s){t.viewport.set(e,n,i,s),t.scissor.set(e,n,i,s)}function AA(){const t=new ub(1,1);return new sA({name:\\\\\\\"EquirectangularToCubeUV\\\\\\\",uniforms:{envMap:{value:null},texelSize:{value:t},inputEncoding:{value:cA[3e3]},outputEncoding:{value:cA[3e3]}},vertexShader:EA(),fragmentShader:`\\\\n\\\\n\\\\t\\\\t\\\\tprecision mediump float;\\\\n\\\\t\\\\t\\\\tprecision mediump int;\\\\n\\\\n\\\\t\\\\t\\\\tvarying vec3 vOutputDirection;\\\\n\\\\n\\\\t\\\\t\\\\tuniform sampler2D envMap;\\\\n\\\\t\\\\t\\\\tuniform vec2 texelSize;\\\\n\\\\n\\\\t\\\\t\\\\t${SA()}\\\\n\\\\n\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvec3 outputDirection = normalize( vOutputDirection );\\\\n\\\\t\\\\t\\\\t\\\\tvec2 uv = equirectUv( outputDirection );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvec2 f = fract( uv / texelSize - 0.5 );\\\\n\\\\t\\\\t\\\\t\\\\tuv -= f * texelSize;\\\\n\\\\t\\\\t\\\\t\\\\tvec3 tl = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tuv.x += texelSize.x;\\\\n\\\\t\\\\t\\\\t\\\\tvec3 tr = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tuv.y += texelSize.y;\\\\n\\\\t\\\\t\\\\t\\\\tvec3 br = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tuv.x -= texelSize.x;\\\\n\\\\t\\\\t\\\\t\\\\tvec3 bl = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvec3 tm = mix( tl, tr, f.x );\\\\n\\\\t\\\\t\\\\t\\\\tvec3 bm = mix( bl, br, f.x );\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb = mix( tm, bm, f.y );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = linearToOutputTexel( gl_FragColor );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t`,blending:0,depthTest:!1,depthWrite:!1})}function MA(){return new sA({name:\\\\\\\"CubemapToCubeUV\\\\\\\",uniforms:{envMap:{value:null},inputEncoding:{value:cA[3e3]},outputEncoding:{value:cA[3e3]}},vertexShader:EA(),fragmentShader:`\\\\n\\\\n\\\\t\\\\t\\\\tprecision mediump float;\\\\n\\\\t\\\\t\\\\tprecision mediump int;\\\\n\\\\n\\\\t\\\\t\\\\tvarying vec3 vOutputDirection;\\\\n\\\\n\\\\t\\\\t\\\\tuniform samplerCube envMap;\\\\n\\\\n\\\\t\\\\t\\\\t${SA()}\\\\n\\\\n\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb = envMapTexelToLinear( textureCube( envMap, vec3( - vOutputDirection.x, vOutputDirection.yz ) ) ).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor = linearToOutputTexel( gl_FragColor );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t`,blending:0,depthTest:!1,depthWrite:!1})}function EA(){return\\\\\\\"\\\\n\\\\n\\\\t\\\\tprecision mediump float;\\\\n\\\\t\\\\tprecision mediump int;\\\\n\\\\n\\\\t\\\\tattribute vec3 position;\\\\n\\\\t\\\\tattribute vec2 uv;\\\\n\\\\t\\\\tattribute float faceIndex;\\\\n\\\\n\\\\t\\\\tvarying vec3 vOutputDirection;\\\\n\\\\n\\\\t\\\\t// RH coordinate system; PMREM face-indexing convention\\\\n\\\\t\\\\tvec3 getDirection( vec2 uv, float face ) {\\\\n\\\\n\\\\t\\\\t\\\\tuv = 2.0 * uv - 1.0;\\\\n\\\\n\\\\t\\\\t\\\\tvec3 direction = vec3( uv, 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\tif ( face == 0.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection = direction.zyx; // ( 1, v, u ) pos x\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 1.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection = direction.xzy;\\\\n\\\\t\\\\t\\\\t\\\\tdirection.xz *= -1.0; // ( -u, 1, -v ) pos y\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 2.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection.x *= -1.0; // ( -u, v, 1 ) pos z\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 3.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection = direction.zyx;\\\\n\\\\t\\\\t\\\\t\\\\tdirection.xz *= -1.0; // ( -1, v, -u ) neg x\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 4.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection = direction.xzy;\\\\n\\\\t\\\\t\\\\t\\\\tdirection.xy *= -1.0; // ( -u, -1, v ) neg y\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( face == 5.0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tdirection.z *= -1.0; // ( u, v, -1 ) neg z\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\treturn direction;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvOutputDirection = getDirection( uv, faceIndex );\\\\n\\\\t\\\\t\\\\tgl_Position = vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\\\\"}function SA(){return\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform int inputEncoding;\\\\n\\\\t\\\\tuniform int outputEncoding;\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\tvec4 inputTexelToLinear( vec4 value ) {\\\\n\\\\n\\\\t\\\\t\\\\tif ( inputEncoding == 0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn value;\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 1 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn sRGBToLinear( value );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 2 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn RGBEToLinear( value );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 3 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn RGBMToLinear( value, 7.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 4 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn RGBMToLinear( value, 16.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( inputEncoding == 5 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn RGBDToLinear( value, 256.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn GammaToLinear( value, 2.2 );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvec4 linearToOutputTexel( vec4 value ) {\\\\n\\\\n\\\\t\\\\t\\\\tif ( outputEncoding == 0 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn value;\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 1 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearTosRGB( value );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 2 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToRGBE( value );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 3 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToRGBM( value, 7.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 4 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToRGBM( value, 16.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else if ( outputEncoding == 5 ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToRGBD( value, 256.0 );\\\\n\\\\n\\\\t\\\\t\\\\t} else {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\treturn LinearToGamma( value, 2.2 );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvec4 envMapTexelToLinear( vec4 color ) {\\\\n\\\\n\\\\t\\\\t\\\\treturn inputTexelToLinear( color );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\\\\"}function CA(t){let e=new WeakMap,n=null;function i(t){const n=t.target;n.removeEventListener(\\\\\\\"dispose\\\\\\\",i);const s=e.get(n);void 0!==s&&(e.delete(n),s.dispose())}return{get:function(s){if(s&&s.isTexture&&!1===s.isRenderTargetTexture){const r=s.mapping,o=r===px||r===_x,a=r===ux||r===dx;if(o||a){if(e.has(s))return e.get(s).texture;{const r=s.image;if(o&&r&&r.height>0||a&&r&&function(t){let e=0;const n=6;for(let i=0;i65535?Qw:Zw)(n,1);a.version=o;const l=r.get(t);l&&e.remove(l),r.set(t,a)}return{get:function(t,e){return!0===s[e.id]||(e.addEventListener(\\\\\\\"dispose\\\\\\\",o),s[e.id]=!0,n.memory.geometries++),e},update:function(t){const n=t.attributes;for(const t in n)e.update(n[t],34962);const i=t.morphAttributes;for(const t in i){const n=i[t];for(let t=0,i=n.length;te.maxTextureSize&&(u=Math.ceil(h/e.maxTextureSize),h=e.maxTextureSize);const d=new Float32Array(h*u*4*i),p=new RA(d,h,u,i);p.format=Rx,p.type=Nx;const _=4*l;for(let e=0;e0)return t;const s=e*n;let r=jA[s];if(void 0===r&&(r=new Float32Array(s),jA[s]=r),0!==e){i.toArray(r,0);for(let i=1,s=0;i!==e;++i)s+=n,t[i].toArray(r,s)}return r}function JA(t,e){if(t.length!==e.length)return!1;for(let n=0,i=t.length;n/gm;function KM(t){return t.replace(QM,tE)}function tE(t,e){const n=YT[e];if(void 0===n)throw new Error(\\\\\\\"Can not resolve #include <\\\\\\\"+e+\\\\\\\">\\\\\\\");return KM(n)}const eE=/#pragma unroll_loop[\\\\s]+?for \\\\( int i \\\\= (\\\\d+)\\\\; i < (\\\\d+)\\\\; i \\\\+\\\\+ \\\\) \\\\{([\\\\s\\\\S]+?)(?=\\\\})\\\\}/g,nE=/#pragma unroll_loop_start\\\\s+for\\\\s*\\\\(\\\\s*int\\\\s+i\\\\s*=\\\\s*(\\\\d+)\\\\s*;\\\\s*i\\\\s*<\\\\s*(\\\\d+)\\\\s*;\\\\s*i\\\\s*\\\\+\\\\+\\\\s*\\\\)\\\\s*{([\\\\s\\\\S]+?)}\\\\s+#pragma unroll_loop_end/g;function iE(t){return t.replace(nE,rE).replace(eE,sE)}function sE(t,e,n,i){return console.warn(\\\\\\\"WebGLProgram: #pragma unroll_loop shader syntax is deprecated. 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i=t[n];!1!==i&&e.push(\\\\\\\"#define \\\\\\\"+n+\\\\\\\" \\\\\\\"+i)}return e.join(\\\\\\\"\\\\n\\\\\\\")}(r),m=s.createProgram();let f,g,v=n.glslVersion?\\\\\\\"#version \\\\\\\"+n.glslVersion+\\\\\\\"\\\\n\\\\\\\":\\\\\\\"\\\\\\\";n.isRawShaderMaterial?(f=[_].filter($M).join(\\\\\\\"\\\\n\\\\\\\"),f.length>0&&(f+=\\\\\\\"\\\\n\\\\\\\"),g=[p,_].filter($M).join(\\\\\\\"\\\\n\\\\\\\"),g.length>0&&(g+=\\\\\\\"\\\\n\\\\\\\")):(f=[oE(n),\\\\\\\"#define SHADER_NAME \\\\\\\"+n.shaderName,_,n.instancing?\\\\\\\"#define USE_INSTANCING\\\\\\\":\\\\\\\"\\\\\\\",n.instancingColor?\\\\\\\"#define USE_INSTANCING_COLOR\\\\\\\":\\\\\\\"\\\\\\\",n.supportsVertexTextures?\\\\\\\"#define VERTEX_TEXTURES\\\\\\\":\\\\\\\"\\\\\\\",\\\\\\\"#define GAMMA_FACTOR \\\\\\\"+d,\\\\\\\"#define MAX_BONES \\\\\\\"+n.maxBones,n.useFog&&n.fog?\\\\\\\"#define USE_FOG\\\\\\\":\\\\\\\"\\\\\\\",n.useFog&&n.fogExp2?\\\\\\\"#define FOG_EXP2\\\\\\\":\\\\\\\"\\\\\\\",n.map?\\\\\\\"#define 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y=v+g+a,x=VM(s,35633,v+f+o),b=VM(s,35632,y);if(s.attachShader(m,x),s.attachShader(m,b),void 0!==n.index0AttributeName?s.bindAttribLocation(m,0,n.index0AttributeName):!0===n.morphTargets&&s.bindAttribLocation(m,0,\\\\\\\"position\\\\\\\"),s.linkProgram(m),t.debug.checkShaderErrors){const t=s.getProgramInfoLog(m).trim(),e=s.getShaderInfoLog(x).trim(),n=s.getShaderInfoLog(b).trim();let i=!0,r=!0;if(!1===s.getProgramParameter(m,35714)){i=!1;const e=WM(s,x,\\\\\\\"vertex\\\\\\\"),n=WM(s,b,\\\\\\\"fragment\\\\\\\");console.error(\\\\\\\"THREE.WebGLProgram: Shader Error \\\\\\\"+s.getError()+\\\\\\\" - VALIDATE_STATUS \\\\\\\"+s.getProgramParameter(m,35715)+\\\\\\\"\\\\n\\\\nProgram Info Log: \\\\\\\"+t+\\\\\\\"\\\\n\\\\\\\"+e+\\\\\\\"\\\\n\\\\\\\"+n)}else\\\\\\\"\\\\\\\"!==t?console.warn(\\\\\\\"THREE.WebGLProgram: Program Info Log:\\\\\\\",t):\\\\\\\"\\\\\\\"!==e&&\\\\\\\"\\\\\\\"!==n||(r=!1);r&&(this.diagnostics={runnable:i,programLog:t,vertexShader:{log:e,prefix:f},fragmentShader:{log:n,prefix:g}})}let w,T;return s.deleteShader(x),s.deleteShader(b),this.getUniforms=function(){return void 0===w&&(w=new GM(s,m)),w},this.getAttributes=function(){return void 0===T&&(T=function(t,e){const n={},i=t.getProgramParameter(e,35721);for(let s=0;s0,C=r.clearcoat>0;return{isWebGL2:l,shaderID:w,shaderName:r.type,vertexShader:A,fragmentShader:M,defines:r.defines,isRawShaderMaterial:!0===r.isRawShaderMaterial,glslVersion:r.glslVersion,precision:p,instancing:!0===v.isInstancedMesh,instancingColor:!0===v.isInstancedMesh&&null!==v.instanceColor,supportsVertexTextures:d,outputEncoding:null!==E?f(E.texture):t.outputEncoding,map:!!r.map,mapEncoding:f(r.map),matcap:!!r.matcap,matcapEncoding:f(r.matcap),envMap:!!b,envMapMode:b&&b.mapping,envMapEncoding:f(b),envMapCubeUV:!!b&&(b.mapping===mx||b.mapping===fx),lightMap:!!r.lightMap,lightMapEncoding:f(r.lightMap),aoMap:!!r.aoMap,emissiveMap:!!r.emissiveMap,emissiveMapEncoding:f(r.emissiveMap),bumpMap:!!r.bumpMap,normalMap:!!r.normalMap,objectSpaceNormalMap:1===r.normalMapType,tangentSpaceNormalMap:0===r.normalMapType,clearcoat:C,clearcoatMap:C&&!!r.clearcoatMap,clearcoatRoughnessMap:C&&!!r.clearcoatRoughnessMap,clearcoatNormalMap:C&&!!r.clearcoatNormalMap,displacementMap:!!r.displacementMap,roughnessMap:!!r.roughnessMap,metalnessMap:!!r.metalnessMap,specularMap:!!r.specularMap,specularIntensityMap:!!r.specularIntensityMap,specularTintMap:!!r.specularTintMap,specularTintMapEncoding:f(r.specularTintMap),alphaMap:!!r.alphaMap,alphaTest:S,gradientMap:!!r.gradientMap,sheen:r.sheen>0,transmission:r.transmission>0,transmissionMap:!!r.transmissionMap,thicknessMap:!!r.thicknessMap,combine:r.combine,vertexTangents:!!r.normalMap&&!!v.geometry&&!!v.geometry.attributes.tangent,vertexColors:r.vertexColors,vertexAlphas:!0===r.vertexColors&&!!v.geometry&&!!v.geometry.attributes.color&&4===v.geometry.attributes.color.itemSize,vertexUvs:!!(r.map||r.bumpMap||r.normalMap||r.specularMap||r.alphaMap||r.emissiveMap||r.roughnessMap||r.metalnessMap||r.clearcoatMap||r.clearcoatRoughnessMap||r.clearcoatNormalMap||r.displacementMap||r.transmissionMap||r.thicknessMap||r.specularIntensityMap||r.specularTintMap),uvsVertexOnly:!(r.map||r.bumpMap||r.normalMap||r.specularMap||r.alphaMap||r.emissiveMap||r.roughnessMap||r.metalnessMap||r.clearcoatNormalMap||r.transmission>0||r.transmissionMap||r.thicknessMap||r.specularIntensityMap||r.specularTintMap||!r.displacementMap),fog:!!y,useFog:r.fog,fogExp2:y&&y.isFogExp2,flatShading:!!r.flatShading,sizeAttenuation:r.sizeAttenuation,logarithmicDepthBuffer:c,skinning:!0===v.isSkinnedMesh&&T>0,maxBones:T,useVertexTexture:h,morphTargets:!!v.geometry&&!!v.geometry.morphAttributes.position,morphNormals:!!v.geometry&&!!v.geometry.morphAttributes.normal,morphTargetsCount:v.geometry&&v.geometry.morphAttributes.position?v.geometry.morphAttributes.position.length:0,numDirLights:a.directional.length,numPointLights:a.point.length,numSpotLights:a.spot.length,numRectAreaLights:a.rectArea.length,numHemiLights:a.hemi.length,numDirLightShadows:a.directionalShadowMap.length,numPointLightShadows:a.pointShadowMap.length,numSpotLightShadows:a.spotShadowMap.length,numClippingPlanes:o.numPlanes,numClipIntersection:o.numIntersection,format:r.format,dithering:r.dithering,shadowMapEnabled:t.shadowMap.enabled&&m.length>0,shadowMapType:t.shadowMap.type,toneMapping:r.toneMapped?t.toneMapping:0,physicallyCorrectLights:t.physicallyCorrectLights,premultipliedAlpha:r.premultipliedAlpha,doubleSided:2===r.side,flipSided:1===r.side,depthPacking:void 0!==r.depthPacking&&r.depthPacking,index0AttributeName:r.index0AttributeName,extensionDerivatives:r.extensions&&r.extensions.derivatives,extensionFragDepth:r.extensions&&r.extensions.fragDepth,extensionDrawBuffers:r.extensions&&r.extensions.drawBuffers,extensionShaderTextureLOD:r.extensions&&r.extensions.shaderTextureLOD,rendererExtensionFragDepth:l||i.has(\\\\\\\"EXT_frag_depth\\\\\\\"),rendererExtensionDrawBuffers:l||i.has(\\\\\\\"WEBGL_draw_buffers\\\\\\\"),rendererExtensionShaderTextureLod:l||i.has(\\\\\\\"EXT_shader_texture_lod\\\\\\\"),customProgramCacheKey:r.customProgramCacheKey()}},getProgramCacheKey:function(e){const n=[];if(e.shaderID?n.push(e.shaderID):(n.push(e.fragmentShader),n.push(e.vertexShader)),void 0!==e.defines)for(const t in e.defines)n.push(t),n.push(e.defines[t]);if(!1===e.isRawShaderMaterial){for(let t=0;t0?s.push(h):!0===n.transparent?r.push(h):i.push(h)},unshift:function(t,e,n,o,l,c){const 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Ab,halfHeight:new Ab}}return t[e.id]=n,n}}}let mE=0;function fE(t,e){return(e.castShadow?1:0)-(t.castShadow?1:0)}function gE(t,e){const n=new _E,i=function(){const t={};return{get:function(e){if(void 0!==t[e.id])return t[e.id];let n;switch(e.type){case\\\\\\\"DirectionalLight\\\\\\\":case\\\\\\\"SpotLight\\\\\\\":n={shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new ub};break;case\\\\\\\"PointLight\\\\\\\":n={shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new ub,shadowCameraNear:1,shadowCameraFar:1e3}}return t[e.id]=n,n}}}(),s={version:0,hash:{directionalLength:-1,pointLength:-1,spotLength:-1,rectAreaLength:-1,hemiLength:-1,numDirectionalShadows:-1,numPointShadows:-1,numSpotShadows:-1},ambient:[0,0,0],probe:[],directional:[],directionalShadow:[],directionalShadowMap:[],directionalShadowMatrix:[],spot:[],spotShadow:[],spotShadowMap:[],spotShadowMatrix:[],rectArea:[],rectAreaLTC1:null,rectAreaLTC2:null,point:[],pointShadow:[],pointShadowMap:[],pointShadowMatrix:[],hemi:[]};for(let t=0;t<9;t++)s.probe.push(new Ab);const r=new Ab,o=new ew,a=new ew;return{setup:function(r,o){let a=0,l=0,c=0;for(let t=0;t<9;t++)s.probe[t].set(0,0,0);let h=0,u=0,d=0,p=0,_=0,m=0,f=0,g=0;r.sort(fE);const v=!0!==o?Math.PI:1;for(let t=0,e=r.length;t0&&(e.isWebGL2||!0===t.has(\\\\\\\"OES_texture_float_linear\\\\\\\")?(s.rectAreaLTC1=$T.LTC_FLOAT_1,s.rectAreaLTC2=$T.LTC_FLOAT_2):!0===t.has(\\\\\\\"OES_texture_half_float_linear\\\\\\\")?(s.rectAreaLTC1=$T.LTC_HALF_1,s.rectAreaLTC2=$T.LTC_HALF_2):console.error(\\\\\\\"THREE.WebGLRenderer: Unable to use RectAreaLight. Missing WebGL extensions.\\\\\\\")),s.ambient[0]=a,s.ambient[1]=l,s.ambient[2]=c;const y=s.hash;y.directionalLength===h&&y.pointLength===u&&y.spotLength===d&&y.rectAreaLength===p&&y.hemiLength===_&&y.numDirectionalShadows===m&&y.numPointShadows===f&&y.numSpotShadows===g||(s.directional.length=h,s.spot.length=d,s.rectArea.length=p,s.point.length=u,s.hemi.length=_,s.directionalShadow.length=m,s.directionalShadowMap.length=m,s.pointShadow.length=f,s.pointShadowMap.length=f,s.spotShadow.length=g,s.spotShadowMap.length=g,s.directionalShadowMatrix.length=m,s.pointShadowMatrix.length=f,s.spotShadowMatrix.length=g,y.directionalLength=h,y.pointLength=u,y.spotLength=d,y.rectAreaLength=p,y.hemiLength=_,y.numDirectionalShadows=m,y.numPointShadows=f,y.numSpotShadows=g,s.version=mE++)},setupView:function(t,e){let n=0,i=0,l=0,c=0,h=0;const u=e.matrixWorldInverse;for(let e=0,d=t.length;e=n.get(i).length?(r=new vE(t,e),n.get(i).push(r)):r=n.get(i)[s],r},dispose:function(){n=new WeakMap}}}class xE extends kw{constructor(t){super(),this.type=\\\\\\\"MeshDepthMaterial\\\\\\\",this.depthPacking=3200,this.map=null,this.alphaMap=null,this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.wireframe=!1,this.wireframeLinewidth=1,this.fog=!1,this.setValues(t)}copy(t){return super.copy(t),this.depthPacking=t.depthPacking,this.map=t.map,this.alphaMap=t.alphaMap,this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this.wireframe=t.wireframe,this.wireframeLinewidth=t.wireframeLinewidth,this}}xE.prototype.isMeshDepthMaterial=!0;class bE extends kw{constructor(t){super(),this.type=\\\\\\\"MeshDistanceMaterial\\\\\\\",this.referencePosition=new Ab,this.nearDistance=1,this.farDistance=1e3,this.map=null,this.alphaMap=null,this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.fog=!1,this.setValues(t)}copy(t){return super.copy(t),this.referencePosition.copy(t.referencePosition),this.nearDistance=t.nearDistance,this.farDistance=t.farDistance,this.map=t.map,this.alphaMap=t.alphaMap,this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this}}bE.prototype.isMeshDistanceMaterial=!0;function wE(t,e,n){let i=new jT;const s=new ub,r=new ub,o=new xb,a=new xE({depthPacking:3201}),l=new bE,c={},h=n.maxTextureSize,u={0:1,1:0,2:2},d=new OT({uniforms:{shadow_pass:{value:null},resolution:{value:new ub},radius:{value:4},samples:{value:8}},vertexShader:\\\\\\\"void main() {\\\\n\\\\tgl_Position = vec4( position, 1.0 );\\\\n}\\\\\\\",fragmentShader:\\\\\\\"uniform sampler2D shadow_pass;\\\\nuniform vec2 resolution;\\\\nuniform float radius;\\\\nuniform float samples;\\\\n#include \\\\nvoid main() {\\\\n\\\\tfloat mean = 0.0;\\\\n\\\\tfloat squared_mean = 0.0;\\\\n\\\\tfloat uvStride = samples <= 1.0 ? 0.0 : 2.0 / ( samples - 1.0 );\\\\n\\\\tfloat uvStart = samples <= 1.0 ? 0.0 : - 1.0;\\\\n\\\\tfor ( float i = 0.0; i < samples; i ++ ) {\\\\n\\\\t\\\\tfloat uvOffset = uvStart + i * uvStride;\\\\n\\\\t\\\\t#ifdef HORIZONTAL_PASS\\\\n\\\\t\\\\t\\\\tvec2 distribution = unpackRGBATo2Half( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( uvOffset, 0.0 ) * radius ) / resolution ) );\\\\n\\\\t\\\\t\\\\tmean += distribution.x;\\\\n\\\\t\\\\t\\\\tsquared_mean += distribution.y * distribution.y + distribution.x * distribution.x;\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\tfloat depth = unpackRGBAToDepth( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( 0.0, uvOffset ) * radius ) / resolution ) );\\\\n\\\\t\\\\t\\\\tmean += depth;\\\\n\\\\t\\\\t\\\\tsquared_mean += depth * depth;\\\\n\\\\t\\\\t#endif\\\\n\\\\t}\\\\n\\\\tmean = mean / samples;\\\\n\\\\tsquared_mean = squared_mean / samples;\\\\n\\\\tfloat std_dev = sqrt( squared_mean - mean * mean );\\\\n\\\\tgl_FragColor = pack2HalfToRGBA( vec2( mean, std_dev ) );\\\\n}\\\\\\\"}),p=d.clone();p.defines.HORIZONTAL_PASS=1;const _=new aT;_.setAttribute(\\\\\\\"position\\\\\\\",new Jw(new Float32Array([-1,-1,.5,3,-1,.5,-1,3,.5]),3));const m=new MT(_,d),f=this;function g(n,i){const s=e.update(m);d.uniforms.shadow_pass.value=n.map.texture,d.uniforms.resolution.value=n.mapSize,d.uniforms.radius.value=n.radius,d.uniforms.samples.value=n.blurSamples,t.setRenderTarget(n.mapPass),t.clear(),t.renderBufferDirect(i,null,s,d,m,null),p.uniforms.shadow_pass.value=n.mapPass.texture,p.uniforms.resolution.value=n.mapSize,p.uniforms.radius.value=n.radius,p.uniforms.samples.value=n.blurSamples,t.setRenderTarget(n.map),t.clear(),t.renderBufferDirect(i,null,s,p,m,null)}function v(e,n,i,s,r,o,h){let d=null;const p=!0===s.isPointLight?e.customDistanceMaterial:e.customDepthMaterial;if(d=void 0!==p?p:!0===s.isPointLight?l:a,t.localClippingEnabled&&!0===i.clipShadows&&0!==i.clippingPlanes.length||i.displacementMap&&0!==i.displacementScale||i.alphaMap&&i.alphaTest>0){const t=d.uuid,e=i.uuid;let n=c[t];void 0===n&&(n={},c[t]=n);let s=n[e];void 0===s&&(s=d.clone(),n[e]=s),d=s}return d.visible=i.visible,d.wireframe=i.wireframe,d.side=3===h?null!==i.shadowSide?i.shadowSide:i.side:null!==i.shadowSide?i.shadowSide:u[i.side],d.alphaMap=i.alphaMap,d.alphaTest=i.alphaTest,d.clipShadows=i.clipShadows,d.clippingPlanes=i.clippingPlanes,d.clipIntersection=i.clipIntersection,d.displacementMap=i.displacementMap,d.displacementScale=i.displacementScale,d.displacementBias=i.displacementBias,d.wireframeLinewidth=i.wireframeLinewidth,d.linewidth=i.linewidth,!0===s.isPointLight&&!0===d.isMeshDistanceMaterial&&(d.referencePosition.setFromMatrixPosition(s.matrixWorld),d.nearDistance=r,d.farDistance=o),d}function y(n,s,r,o,a){if(!1===n.visible)return;if(n.layers.test(s.layers)&&(n.isMesh||n.isLine||n.isPoints)&&(n.castShadow||n.receiveShadow&&3===a)&&(!n.frustumCulled||i.intersectsObject(n))){n.modelViewMatrix.multiplyMatrices(r.matrixWorldInverse,n.matrixWorld);const i=e.update(n),s=n.material;if(Array.isArray(s)){const e=i.groups;for(let l=0,c=e.length;lh||s.y>h)&&(s.x>h&&(r.x=Math.floor(h/p.x),s.x=r.x*p.x,u.mapSize.x=r.x),s.y>h&&(r.y=Math.floor(h/p.y),s.y=r.y*p.y,u.mapSize.y=r.y)),null===u.map&&!u.isPointLightShadow&&3===this.type){const t={minFilter:Tx,magFilter:Tx,format:Rx};u.map=new bb(s.x,s.y,t),u.map.texture.name=c.name+\\\\\\\".shadowMap\\\\\\\",u.mapPass=new bb(s.x,s.y,t),u.camera.updateProjectionMatrix()}if(null===u.map){const t={minFilter:xx,magFilter:xx,format:Rx};u.map=new bb(s.x,s.y,t),u.map.texture.name=c.name+\\\\\\\".shadowMap\\\\\\\",u.camera.updateProjectionMatrix()}t.setRenderTarget(u.map),t.clear();const _=u.getViewportCount();for(let t=0;t<_;t++){const e=u.getViewport(t);o.set(r.x*e.x,r.y*e.y,r.x*e.z,r.y*e.w),d.viewport(o),u.updateMatrices(c,t),i=u.getFrustum(),y(n,a,u.camera,c,this.type)}u.isPointLightShadow||3!==this.type||g(u,a),u.needsUpdate=!1}f.needsUpdate=!1,t.setRenderTarget(l,c,u)}}function TE(t,e,n){const i=n.isWebGL2;const s=new function(){let e=!1;const n=new xb;let i=null;const s=new xb(0,0,0,0);return{setMask:function(n){i===n||e||(t.colorMask(n,n,n,n),i=n)},setLocked:function(t){e=t},setClear:function(e,i,r,o,a){!0===a&&(e*=o,i*=o,r*=o),n.set(e,i,r,o),!1===s.equals(n)&&(t.clearColor(e,i,r,o),s.copy(n))},reset:function(){e=!1,i=null,s.set(-1,0,0,0)}}},r=new function(){let e=!1,n=null,i=null,s=null;return{setTest:function(t){t?B(2929):z(2929)},setMask:function(i){n===i||e||(t.depthMask(i),n=i)},setFunc:function(e){if(i!==e){if(e)switch(e){case 0:t.depthFunc(512);break;case 1:t.depthFunc(519);break;case 2:t.depthFunc(513);break;case 3:t.depthFunc(515);break;case 4:t.depthFunc(514);break;case 5:t.depthFunc(518);break;case 6:t.depthFunc(516);break;case 7:t.depthFunc(517);break;default:t.depthFunc(515)}else t.depthFunc(515);i=e}},setLocked:function(t){e=t},setClear:function(e){s!==e&&(t.clearDepth(e),s=e)},reset:function(){e=!1,n=null,i=null,s=null}}},o=new function(){let e=!1,n=null,i=null,s=null,r=null,o=null,a=null,l=null,c=null;return{setTest:function(t){e||(t?B(2960):z(2960))},setMask:function(i){n===i||e||(t.stencilMask(i),n=i)},setFunc:function(e,n,o){i===e&&s===n&&r===o||(t.stencilFunc(e,n,o),i=e,s=n,r=o)},setOp:function(e,n,i){o===e&&a===n&&l===i||(t.stencilOp(e,n,i),o=e,a=n,l=i)},setLocked:function(t){e=t},setClear:function(e){c!==e&&(t.clearStencil(e),c=e)},reset:function(){e=!1,n=null,i=null,s=null,r=null,o=null,a=null,l=null,c=null}}};let a={},l=null,c={},h=null,u=!1,d=null,p=null,_=null,m=null,f=null,g=null,v=null,y=!1,x=null,b=null,w=null,T=null,A=null;const M=t.getParameter(35661);let E=!1,S=0;const C=t.getParameter(7938);-1!==C.indexOf(\\\\\\\"WebGL\\\\\\\")?(S=parseFloat(/^WebGL (\\\\d)/.exec(C)[1]),E=S>=1):-1!==C.indexOf(\\\\\\\"OpenGL ES\\\\\\\")&&(S=parseFloat(/^OpenGL ES (\\\\d)/.exec(C)[1]),E=S>=2);let N=null,L={};const O=t.getParameter(3088),P=t.getParameter(2978),R=(new xb).fromArray(O),I=(new xb).fromArray(P);function F(e,n,i){const s=new Uint8Array(4),r=t.createTexture();t.bindTexture(e,r),t.texParameteri(e,10241,9728),t.texParameteri(e,10240,9728);for(let e=0;ei||t.height>i)&&(s=i/Math.max(t.width,t.height)),s<1||!0===e){if(\\\\\\\"undefined\\\\\\\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\\\\\\\"undefined\\\\\\\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\\\\\\\"undefined\\\\\\\"!=typeof ImageBitmap&&t instanceof ImageBitmap){const i=e?cb:Math.floor,r=i(s*t.width),o=i(s*t.height);void 0===p&&(p=m(r,o));const a=n?m(r,o):p;a.width=r,a.height=o;return a.getContext(\\\\\\\"2d\\\\\\\").drawImage(t,0,0,r,o),console.warn(\\\\\\\"THREE.WebGLRenderer: Texture has been resized from (\\\\\\\"+t.width+\\\\\\\"x\\\\\\\"+t.height+\\\\\\\") to (\\\\\\\"+r+\\\\\\\"x\\\\\\\"+o+\\\\\\\").\\\\\\\"),a}return\\\\\\\"data\\\\\\\"in t&&console.warn(\\\\\\\"THREE.WebGLRenderer: Image in DataTexture is too big (\\\\\\\"+t.width+\\\\\\\"x\\\\\\\"+t.height+\\\\\\\").\\\\\\\"),t}return t}function g(t){return ab(t.width)&&ab(t.height)}function v(t,e){return t.generateMipmaps&&e&&t.minFilter!==xx&&t.minFilter!==Tx}function y(e,n,s,r,o=1){t.generateMipmap(e);i.get(n).__maxMipLevel=Math.log2(Math.max(s,r,o))}function x(n,i,s,r){if(!1===a)return i;if(null!==n){if(void 0!==t[n])return t[n];console.warn(\\\\\\\"THREE.WebGLRenderer: Attempt to use non-existing WebGL internal format '\\\\\\\"+n+\\\\\\\"'\\\\\\\")}let o=i;return 6403===i&&(5126===s&&(o=33326),5131===s&&(o=33325),5121===s&&(o=33321)),6407===i&&(5126===s&&(o=34837),5131===s&&(o=34843),5121===s&&(o=32849)),6408===i&&(5126===s&&(o=34836),5131===s&&(o=34842),5121===s&&(o=r===jx?35907:32856)),33325!==o&&33326!==o&&34842!==o&&34836!==o||e.get(\\\\\\\"EXT_color_buffer_float\\\\\\\"),o}function b(t){return t===xx||t===bx||t===wx?9728:9729}function w(e){const n=e.target;n.removeEventListener(\\\\\\\"dispose\\\\\\\",w),function(e){const n=i.get(e);if(void 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e=0,s=n.length;e0&&s.__version!==t.version){const n=t.image;if(void 0===n)console.warn(\\\\\\\"THREE.WebGLRenderer: Texture marked for update but image is undefined\\\\\\\");else{if(!1!==n.complete)return void O(s,t,e);console.warn(\\\\\\\"THREE.WebGLRenderer: Texture marked for update but image is incomplete\\\\\\\")}}n.activeTexture(33984+e),n.bindTexture(3553,s.__webglTexture)}function E(e,s){const o=i.get(e);e.version>0&&o.__version!==e.version?function(e,i,s){if(6!==i.image.length)return;L(e,i),n.activeTexture(33984+s),n.bindTexture(34067,e.__webglTexture),t.pixelStorei(37440,i.flipY),t.pixelStorei(37441,i.premultiplyAlpha),t.pixelStorei(3317,i.unpackAlignment),t.pixelStorei(37443,0);const o=i&&(i.isCompressedTexture||i.image[0].isCompressedTexture),l=i.image[0]&&i.image[0].isDataTexture,h=[];for(let t=0;t<6;t++)h[t]=o||l?l?i.image[t].image:i.image[t]:f(i.image[t],!1,!0,c);const u=h[0],d=g(u)||a,p=r.convert(i.format),_=r.convert(i.type),m=x(i.internalFormat,p,_,i.encoding);let b;if(N(34067,i,d),o){for(let t=0;t<6;t++){b=h[t].mipmaps;for(let e=0;e1||i.get(r).__currentAnisotropy)&&(t.texParameterf(n,o.TEXTURE_MAX_ANISOTROPY_EXT,Math.min(r.anisotropy,s.getMaxAnisotropy())),i.get(r).__currentAnisotropy=r.anisotropy)}}function L(e,n){void 0===e.__webglInit&&(e.__webglInit=!0,n.addEventListener(\\\\\\\"dispose\\\\\\\",w),e.__webglTexture=t.createTexture(),o.memory.textures++)}function O(e,i,s){let o=3553;i.isDataTexture2DArray&&(o=35866),i.isDataTexture3D&&(o=32879),L(e,i),n.activeTexture(33984+s),n.bindTexture(o,e.__webglTexture),t.pixelStorei(37440,i.flipY),t.pixelStorei(37441,i.premultiplyAlpha),t.pixelStorei(3317,i.unpackAlignment),t.pixelStorei(37443,0);const l=function(t){return!a&&(t.wrapS!==vx||t.wrapT!==vx||t.minFilter!==xx&&t.minFilter!==Tx)}(i)&&!1===g(i.image),c=f(i.image,l,!1,h),u=g(c)||a,d=r.convert(i.format);let p,_=r.convert(i.type),m=x(i.internalFormat,d,_,i.encoding);N(o,i,u);const 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s=i.get(t);t.version>0&&s.__version!==t.version?O(s,t,e):(n.activeTexture(33984+e),n.bindTexture(35866,s.__webglTexture))},this.setTexture3D=function(t,e){const s=i.get(t);t.version>0&&s.__version!==t.version?O(s,t,e):(n.activeTexture(33984+e),n.bindTexture(32879,s.__webglTexture))},this.setTextureCube=E,this.setupRenderTarget=function(e){const l=e.texture,c=i.get(e),h=i.get(l);e.addEventListener(\\\\\\\"dispose\\\\\\\",T),!0!==e.isWebGLMultipleRenderTargets&&(h.__webglTexture=t.createTexture(),h.__version=l.version,o.memory.textures++);const u=!0===e.isWebGLCubeRenderTarget,d=!0===e.isWebGLMultipleRenderTargets,p=!0===e.isWebGLMultisampleRenderTarget,_=l.isDataTexture3D||l.isDataTexture2DArray,m=g(e)||a;if(!a||l.format!==Px||l.type!==Nx&&l.type!==Lx||(l.format=Rx,console.warn(\\\\\\\"THREE.WebGLRenderer: Rendering to textures with RGB format is not supported. Using RGBA format instead.\\\\\\\")),u){c.__webglFramebuffer=[];for(let e=0;e<6;e++)c.__webglFramebuffer[e]=t.createFramebuffer()}else if(c.__webglFramebuffer=t.createFramebuffer(),d)if(s.drawBuffers){const n=e.texture;for(let e=0,s=n.length;ea+c?(l.inputState.pinching=!1,this.dispatchEvent({type:\\\\\\\"pinchend\\\\\\\",handedness:t.handedness,target:this})):!l.inputState.pinching&&o<=a-c&&(l.inputState.pinching=!0,this.dispatchEvent({type:\\\\\\\"pinchstart\\\\\\\",handedness:t.handedness,target:this}))}else null!==a&&t.gripSpace&&(s=e.getPose(t.gripSpace,n),null!==s&&(a.matrix.fromArray(s.transform.matrix),a.matrix.decompose(a.position,a.rotation,a.scale),s.linearVelocity?(a.hasLinearVelocity=!0,a.linearVelocity.copy(s.linearVelocity)):a.hasLinearVelocity=!1,s.angularVelocity?(a.hasAngularVelocity=!0,a.angularVelocity.copy(s.angularVelocity)):a.hasAngularVelocity=!1));return null!==o&&(o.visible=null!==i),null!==a&&(a.visible=null!==s),null!==l&&(l.visible=null!==r),this}}class LE extends Zx{constructor(t,e){super();const n=this,i=t.state;let s=null,r=1,o=null,a=\\\\\\\"local-floor\\\\\\\",l=null,c=null,h=null,u=null,d=null,p=!1,_=null,m=null,f=null,g=null,v=null,y=null;const x=[],b=new Map,w=new RT;w.layers.enable(1),w.viewport=new xb;const T=new RT;T.layers.enable(2),T.viewport=new xb;const A=[w,T],M=new EE;M.layers.enable(1),M.layers.enable(2);let E=null,S=null;function C(t){const e=b.get(t.inputSource);e&&e.dispatchEvent({type:t.type,data:t.inputSource})}function N(){b.forEach((function(t,e){t.disconnect(e)})),b.clear(),E=null,S=null,i.bindXRFramebuffer(null),t.setRenderTarget(t.getRenderTarget()),h&&e.deleteFramebuffer(h),_&&e.deleteFramebuffer(_),m&&e.deleteRenderbuffer(m),f&&e.deleteRenderbuffer(f),h=null,_=null,m=null,f=null,d=null,u=null,c=null,s=null,F.stop(),n.isPresenting=!1,n.dispatchEvent({type:\\\\\\\"sessionend\\\\\\\"})}function L(t){const e=s.inputSources;for(let t=0;t0&&(e.alphaTest.value=n.alphaTest);const i=t.get(n).envMap;if(i){e.envMap.value=i,e.flipEnvMap.value=i.isCubeTexture&&!1===i.isRenderTargetTexture?-1:1,e.reflectivity.value=n.reflectivity,e.ior.value=n.ior,e.refractionRatio.value=n.refractionRatio;const s=t.get(i).__maxMipLevel;void 0!==s&&(e.maxMipLevel.value=s)}let s,r;n.lightMap&&(e.lightMap.value=n.lightMap,e.lightMapIntensity.value=n.lightMapIntensity),n.aoMap&&(e.aoMap.value=n.aoMap,e.aoMapIntensity.value=n.aoMapIntensity),n.map?s=n.map:n.specularMap?s=n.specularMap:n.displacementMap?s=n.displacementMap:n.normalMap?s=n.normalMap:n.bumpMap?s=n.bumpMap:n.roughnessMap?s=n.roughnessMap:n.metalnessMap?s=n.metalnessMap:n.alphaMap?s=n.alphaMap:n.emissiveMap?s=n.emissiveMap:n.clearcoatMap?s=n.clearcoatMap:n.clearcoatNormalMap?s=n.clearcoatNormalMap:n.clearcoatRoughnessMap?s=n.clearcoatRoughnessMap:n.specularIntensityMap?s=n.specularIntensityMap:n.specularTintMap?s=n.specularTintMap:n.transmissionMap?s=n.transmissionMap:n.thicknessMap&&(s=n.thicknessMap),void 0!==s&&(s.isWebGLRenderTarget&&(s=s.texture),!0===s.matrixAutoUpdate&&s.updateMatrix(),e.uvTransform.value.copy(s.matrix)),n.aoMap?r=n.aoMap:n.lightMap&&(r=n.lightMap),void 0!==r&&(r.isWebGLRenderTarget&&(r=r.texture),!0===r.matrixAutoUpdate&&r.updateMatrix(),e.uv2Transform.value.copy(r.matrix))}function n(e,n){e.roughness.value=n.roughness,e.metalness.value=n.metalness,n.roughnessMap&&(e.roughnessMap.value=n.roughnessMap),n.metalnessMap&&(e.metalnessMap.value=n.metalnessMap),n.emissiveMap&&(e.emissiveMap.value=n.emissiveMap),n.bumpMap&&(e.bumpMap.value=n.bumpMap,e.bumpScale.value=n.bumpScale,1===n.side&&(e.bumpScale.value*=-1)),n.normalMap&&(e.normalMap.value=n.normalMap,e.normalScale.value.copy(n.normalScale),1===n.side&&e.normalScale.value.negate()),n.displacementMap&&(e.displacementMap.value=n.displacementMap,e.displacementScale.value=n.displacementScale,e.displacementBias.value=n.displacementBias);t.get(n).envMap&&(e.envMapIntensity.value=n.envMapIntensity)}return{refreshFogUniforms:function(t,e){t.fogColor.value.copy(e.color),e.isFog?(t.fogNear.value=e.near,t.fogFar.value=e.far):e.isFogExp2&&(t.fogDensity.value=e.density)},refreshMaterialUniforms:function(t,i,s,r,o){i.isMeshBasicMaterial?e(t,i):i.isMeshLambertMaterial?(e(t,i),function(t,e){e.emissiveMap&&(t.emissiveMap.value=e.emissiveMap)}(t,i)):i.isMeshToonMaterial?(e(t,i),function(t,e){e.gradientMap&&(t.gradientMap.value=e.gradientMap);e.emissiveMap&&(t.emissiveMap.value=e.emissiveMap);e.bumpMap&&(t.bumpMap.value=e.bumpMap,t.bumpScale.value=e.bumpScale,1===e.side&&(t.bumpScale.value*=-1));e.normalMap&&(t.normalMap.value=e.normalMap,t.normalScale.value.copy(e.normalScale),1===e.side&&t.normalScale.value.negate());e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isMeshPhongMaterial?(e(t,i),function(t,e){t.specular.value.copy(e.specular),t.shininess.value=Math.max(e.shininess,1e-4),e.emissiveMap&&(t.emissiveMap.value=e.emissiveMap);e.bumpMap&&(t.bumpMap.value=e.bumpMap,t.bumpScale.value=e.bumpScale,1===e.side&&(t.bumpScale.value*=-1));e.normalMap&&(t.normalMap.value=e.normalMap,t.normalScale.value.copy(e.normalScale),1===e.side&&t.normalScale.value.negate());e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isMeshStandardMaterial?(e(t,i),i.isMeshPhysicalMaterial?function(t,e,i){n(t,e),t.ior.value=e.ior,e.sheen>0&&(t.sheenTint.value.copy(e.sheenTint).multiplyScalar(e.sheen),t.sheenRoughness.value=e.sheenRoughness);e.clearcoat>0&&(t.clearcoat.value=e.clearcoat,t.clearcoatRoughness.value=e.clearcoatRoughness,e.clearcoatMap&&(t.clearcoatMap.value=e.clearcoatMap),e.clearcoatRoughnessMap&&(t.clearcoatRoughnessMap.value=e.clearcoatRoughnessMap),e.clearcoatNormalMap&&(t.clearcoatNormalScale.value.copy(e.clearcoatNormalScale),t.clearcoatNormalMap.value=e.clearcoatNormalMap,1===e.side&&t.clearcoatNormalScale.value.negate()));e.transmission>0&&(t.transmission.value=e.transmission,t.transmissionSamplerMap.value=i.texture,t.transmissionSamplerSize.value.set(i.width,i.height),e.transmissionMap&&(t.transmissionMap.value=e.transmissionMap),t.thickness.value=e.thickness,e.thicknessMap&&(t.thicknessMap.value=e.thicknessMap),t.attenuationDistance.value=e.attenuationDistance,t.attenuationTint.value.copy(e.attenuationTint));t.specularIntensity.value=e.specularIntensity,t.specularTint.value.copy(e.specularTint),e.specularIntensityMap&&(t.specularIntensityMap.value=e.specularIntensityMap);e.specularTintMap&&(t.specularTintMap.value=e.specularTintMap)}(t,i,o):n(t,i)):i.isMeshMatcapMaterial?(e(t,i),function(t,e){e.matcap&&(t.matcap.value=e.matcap);e.bumpMap&&(t.bumpMap.value=e.bumpMap,t.bumpScale.value=e.bumpScale,1===e.side&&(t.bumpScale.value*=-1));e.normalMap&&(t.normalMap.value=e.normalMap,t.normalScale.value.copy(e.normalScale),1===e.side&&t.normalScale.value.negate());e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isMeshDepthMaterial?(e(t,i),function(t,e){e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isMeshDistanceMaterial?(e(t,i),function(t,e){e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias);t.referencePosition.value.copy(e.referencePosition),t.nearDistance.value=e.nearDistance,t.farDistance.value=e.farDistance}(t,i)):i.isMeshNormalMaterial?(e(t,i),function(t,e){e.bumpMap&&(t.bumpMap.value=e.bumpMap,t.bumpScale.value=e.bumpScale,1===e.side&&(t.bumpScale.value*=-1));e.normalMap&&(t.normalMap.value=e.normalMap,t.normalScale.value.copy(e.normalScale),1===e.side&&t.normalScale.value.negate());e.displacementMap&&(t.displacementMap.value=e.displacementMap,t.displacementScale.value=e.displacementScale,t.displacementBias.value=e.displacementBias)}(t,i)):i.isLineBasicMaterial?(function(t,e){t.diffuse.value.copy(e.color),t.opacity.value=e.opacity}(t,i),i.isLineDashedMaterial&&function(t,e){t.dashSize.value=e.dashSize,t.totalSize.value=e.dashSize+e.gapSize,t.scale.value=e.scale}(t,i)):i.isPointsMaterial?function(t,e,n,i){t.diffuse.value.copy(e.color),t.opacity.value=e.opacity,t.size.value=e.size*n,t.scale.value=.5*i,e.map&&(t.map.value=e.map);e.alphaMap&&(t.alphaMap.value=e.alphaMap);e.alphaTest>0&&(t.alphaTest.value=e.alphaTest);let s;e.map?s=e.map:e.alphaMap&&(s=e.alphaMap);void 0!==s&&(!0===s.matrixAutoUpdate&&s.updateMatrix(),t.uvTransform.value.copy(s.matrix))}(t,i,s,r):i.isSpriteMaterial?function(t,e){t.diffuse.value.copy(e.color),t.opacity.value=e.opacity,t.rotation.value=e.rotation,e.map&&(t.map.value=e.map);e.alphaMap&&(t.alphaMap.value=e.alphaMap);e.alphaTest>0&&(t.alphaTest.value=e.alphaTest);let n;e.map?n=e.map:e.alphaMap&&(n=e.alphaMap);void 0!==n&&(!0===n.matrixAutoUpdate&&n.updateMatrix(),t.uvTransform.value.copy(n.matrix))}(t,i):i.isShadowMaterial?(t.color.value.copy(i.color),t.opacity.value=i.opacity):i.isShaderMaterial&&(i.uniformsNeedUpdate=!1)}}}function PE(t={}){const e=void 0!==t.canvas?t.canvas:function(){const t=_b(\\\\\\\"canvas\\\\\\\");return t.style.display=\\\\\\\"block\\\\\\\",t}(),n=void 0!==t.context?t.context:null,i=void 0!==t.alpha&&t.alpha,s=void 0===t.depth||t.depth,r=void 0===t.stencil||t.stencil,o=void 0!==t.antialias&&t.antialias,a=void 0===t.premultipliedAlpha||t.premultipliedAlpha,l=void 0!==t.preserveDrawingBuffer&&t.preserveDrawingBuffer,c=void 0!==t.powerPreference?t.powerPreference:\\\\\\\"default\\\\\\\",h=void 0!==t.failIfMajorPerformanceCaveat&&t.failIfMajorPerformanceCaveat;let u=null,d=null;const p=[],_=[];this.domElement=e,this.debug={checkShaderErrors:!0},this.autoClear=!0,this.autoClearColor=!0,this.autoClearDepth=!0,this.autoClearStencil=!0,this.sortObjects=!0,this.clippingPlanes=[],this.localClippingEnabled=!1,this.gammaFactor=2,this.outputEncoding=Hx,this.physicallyCorrectLights=!1,this.toneMapping=0,this.toneMappingExposure=1;const m=this;let f=!1,g=0,v=0,y=null,x=-1,b=null;const w=new xb,T=new xb;let A=null,M=e.width,E=e.height,S=1,C=null,N=null;const L=new xb(0,0,M,E),O=new xb(0,0,M,E);let P=!1;const R=[],I=new jT;let F=!1,D=!1,B=null;const z=new ew,k=new Ab,U={background:null,fog:null,environment:null,overrideMaterial:null,isScene:!0};function G(){return null===y?S:1}let V,H,j,W,q,X,Y,$,J,Z,Q,K,tt,et,nt,it,st,rt,ot,at,lt,ct,ht,ut=n;function dt(t,n){for(let i=0;i0&&function(t,e,n){if(null===B){const t=!0===o&&!0===H.isWebGL2;B=new(t?wb:bb)(1024,1024,{generateMipmaps:!0,type:null!==ct.convert(Lx)?Lx:Ex,minFilter:Mx,magFilter:xx,wrapS:vx,wrapT:vx})}const i=m.getRenderTarget();m.setRenderTarget(B),m.clear();const s=m.toneMapping;m.toneMapping=0,At(t,e,n),m.toneMapping=s,X.updateMultisampleRenderTarget(B),X.updateRenderTargetMipmap(B),m.setRenderTarget(i)}(s,e,n),i&&j.viewport(w.copy(i)),s.length>0&&At(s,e,n),r.length>0&&At(r,e,n),a.length>0&&At(a,e,n)}function At(t,e,n){const i=!0===e.isScene?e.overrideMaterial:null;for(let s=0,r=t.length;s0?_[_.length-1]:null,p.pop(),u=p.length>0?p[p.length-1]:null},this.getActiveCubeFace=function(){return g},this.getActiveMipmapLevel=function(){return v},this.getRenderTarget=function(){return y},this.setRenderTarget=function(t,e=0,n=0){y=t,g=e,v=n,t&&void 0===q.get(t).__webglFramebuffer&&X.setupRenderTarget(t);let i=null,s=!1,r=!1;if(t){const n=t.texture;(n.isDataTexture3D||n.isDataTexture2DArray)&&(r=!0);const o=q.get(t).__webglFramebuffer;t.isWebGLCubeRenderTarget?(i=o[e],s=!0):i=t.isWebGLMultisampleRenderTarget?q.get(t).__webglMultisampledFramebuffer:o,w.copy(t.viewport),T.copy(t.scissor),A=t.scissorTest}else w.copy(L).multiplyScalar(S).floor(),T.copy(O).multiplyScalar(S).floor(),A=P;if(j.bindFramebuffer(36160,i)&&H.drawBuffers){let e=!1;if(t)if(t.isWebGLMultipleRenderTargets){const n=t.texture;if(R.length!==n.length||36064!==R[0]){for(let t=0,e=n.length;t=0&&e<=t.width-i&&n>=0&&n<=t.height-s&&ut.readPixels(e,n,i,s,ct.convert(a),ct.convert(l),r):console.error(\\\\\\\"THREE.WebGLRenderer.readRenderTargetPixels: readPixels from renderTarget failed. Framebuffer not complete.\\\\\\\")}finally{const t=null!==y?q.get(y).__webglFramebuffer:null;j.bindFramebuffer(36160,t)}}},this.copyFramebufferToTexture=function(t,e,n=0){const i=Math.pow(2,-n),s=Math.floor(e.image.width*i),r=Math.floor(e.image.height*i);let o=ct.convert(e.format);H.isWebGL2&&(6407===o&&(o=32849),6408===o&&(o=32856)),X.setTexture2D(e,0),ut.copyTexImage2D(3553,n,o,t.x,t.y,s,r,0),j.unbindTexture()},this.copyTextureToTexture=function(t,e,n,i=0){const s=e.image.width,r=e.image.height,o=ct.convert(n.format),a=ct.convert(n.type);X.setTexture2D(n,0),ut.pixelStorei(37440,n.flipY),ut.pixelStorei(37441,n.premultiplyAlpha),ut.pixelStorei(3317,n.unpackAlignment),e.isDataTexture?ut.texSubImage2D(3553,i,t.x,t.y,s,r,o,a,e.image.data):e.isCompressedTexture?ut.compressedTexSubImage2D(3553,i,t.x,t.y,e.mipmaps[0].width,e.mipmaps[0].height,o,e.mipmaps[0].data):ut.texSubImage2D(3553,i,t.x,t.y,o,a,e.image),0===i&&n.generateMipmaps&&ut.generateMipmap(3553),j.unbindTexture()},this.copyTextureToTexture3D=function(t,e,n,i,s=0){if(m.isWebGL1Renderer)return void console.warn(\\\\\\\"THREE.WebGLRenderer.copyTextureToTexture3D: can only be used with WebGL2.\\\\\\\");const r=t.max.x-t.min.x+1,o=t.max.y-t.min.y+1,a=t.max.z-t.min.z+1,l=ct.convert(i.format),c=ct.convert(i.type);let h;if(i.isDataTexture3D)X.setTexture3D(i,0),h=32879;else{if(!i.isDataTexture2DArray)return void console.warn(\\\\\\\"THREE.WebGLRenderer.copyTextureToTexture3D: only supports 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srcTexture.\\\\\\\"),ut.compressedTexSubImage3D(h,s,e.x,e.y,e.z,r,o,a,l,g.data)):ut.texSubImage3D(h,s,e.x,e.y,e.z,r,o,a,l,c,g),ut.pixelStorei(3314,u),ut.pixelStorei(32878,d),ut.pixelStorei(3316,p),ut.pixelStorei(3315,_),ut.pixelStorei(32877,f),0===s&&i.generateMipmaps&&ut.generateMipmap(h),j.unbindTexture()},this.initTexture=function(t){X.setTexture2D(t,0),j.unbindTexture()},this.resetState=function(){g=0,v=0,y=null,j.reset(),ht.reset()},\\\\\\\"undefined\\\\\\\"!=typeof __THREE_DEVTOOLS__&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent(\\\\\\\"observe\\\\\\\",{detail:this}))}(class extends PE{}).prototype.isWebGL1Renderer=!0;class RE{constructor(t,e=25e-5){this.name=\\\\\\\"\\\\\\\",this.color=new qw(t),this.density=e}clone(){return new RE(this.color,this.density)}toJSON(){return{type:\\\\\\\"FogExp2\\\\\\\",color:this.color.getHex(),density:this.density}}}RE.prototype.isFogExp2=!0;class IE{constructor(t,e=1,n=1e3){this.name=\\\\\\\"\\\\\\\",this.color=new qw(t),this.near=e,this.far=n}clone(){return new IE(this.color,this.near,this.far)}toJSON(){return{type:\\\\\\\"Fog\\\\\\\",color:this.color.getHex(),near:this.near,far:this.far}}}IE.prototype.isFog=!0;class FE extends Ew{constructor(){super(),this.type=\\\\\\\"Scene\\\\\\\",this.background=null,this.environment=null,this.fog=null,this.overrideMaterial=null,this.autoUpdate=!0,\\\\\\\"undefined\\\\\\\"!=typeof __THREE_DEVTOOLS__&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent(\\\\\\\"observe\\\\\\\",{detail:this}))}copy(t,e){return super.copy(t,e),null!==t.background&&(this.background=t.background.clone()),null!==t.environment&&(this.environment=t.environment.clone()),null!==t.fog&&(this.fog=t.fog.clone()),null!==t.overrideMaterial&&(this.overrideMaterial=t.overrideMaterial.clone()),this.autoUpdate=t.autoUpdate,this.matrixAutoUpdate=t.matrixAutoUpdate,this}toJSON(t){const e=super.toJSON(t);return null!==this.fog&&(e.object.fog=this.fog.toJSON()),e}}FE.prototype.isScene=!0;class DE{constructor(t,e){this.array=t,this.stride=e,this.count=void 0!==t?t.length/e:0,this.usage=Yx,this.updateRange={offset:0,count:-1},this.version=0,this.uuid=ib()}onUploadCallback(){}set needsUpdate(t){!0===t&&this.version++}setUsage(t){return this.usage=t,this}copy(t){return this.array=new t.array.constructor(t.array),this.count=t.count,this.stride=t.stride,this.usage=t.usage,this}copyAt(t,e,n){t*=this.stride,n*=e.stride;for(let i=0,s=this.stride;it.far||e.push({distance:a,point:GE.clone(),uv:Bw.getUV(GE,XE,YE,$E,JE,ZE,QE,new ub),face:null,object:this})}copy(t){return super.copy(t),void 0!==t.center&&this.center.copy(t.center),this.material=t.material,this}}function tS(t,e,n,i,s,r){jE.subVectors(t,n).addScalar(.5).multiply(i),void 0!==s?(WE.x=r*jE.x-s*jE.y,WE.y=s*jE.x+r*jE.y):WE.copy(jE),t.copy(e),t.x+=WE.x,t.y+=WE.y,t.applyMatrix4(qE)}KE.prototype.isSprite=!0;const eS=new Ab,nS=new xb,iS=new xb,sS=new Ab,rS=new ew;class oS extends MT{constructor(t,e){super(t,e),this.type=\\\\\\\"SkinnedMesh\\\\\\\",this.bindMode=\\\\\\\"attached\\\\\\\",this.bindMatrix=new ew,this.bindMatrixInverse=new ew}copy(t){return super.copy(t),this.bindMode=t.bindMode,this.bindMatrix.copy(t.bindMatrix),this.bindMatrixInverse.copy(t.bindMatrixInverse),this.skeleton=t.skeleton,this}bind(t,e){this.skeleton=t,void 0===e&&(this.updateMatrixWorld(!0),this.skeleton.calculateInverses(),e=this.matrixWorld),this.bindMatrix.copy(e),this.bindMatrixInverse.copy(e).invert()}pose(){this.skeleton.pose()}normalizeSkinWeights(){const t=new xb,e=this.geometry.attributes.skinWeight;for(let n=0,i=e.count;na)continue;u.applyMatrix4(this.matrixWorld);const d=t.ray.origin.distanceTo(u);dt.far||e.push({distance:d,point:h.clone().applyMatrix4(this.matrixWorld),index:n,face:null,faceIndex:null,object:this})}}else{for(let n=Math.max(0,r.start),i=Math.min(s.count,r.start+r.count)-1;na)continue;u.applyMatrix4(this.matrixWorld);const i=t.ray.origin.distanceTo(u);it.far||e.push({distance:i,point:h.clone().applyMatrix4(this.matrixWorld),index:n,face:null,faceIndex:null,object:this})}}}else n.isGeometry&&console.error(\\\\\\\"THREE.Line.raycast() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}updateMorphTargets(){const t=this.geometry;if(t.isBufferGeometry){const e=t.morphAttributes,n=Object.keys(e);if(n.length>0){const t=e[n[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,n=t.length;e0&&console.error(\\\\\\\"THREE.Line.updateMorphTargets() does not support THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}}}bS.prototype.isLine=!0;const wS=new Ab,TS=new Ab;class AS extends bS{constructor(t,e){super(t,e),this.type=\\\\\\\"LineSegments\\\\\\\"}computeLineDistances(){const t=this.geometry;if(t.isBufferGeometry)if(null===t.index){const e=t.attributes.position,n=[];for(let t=0,i=e.count;t0){const t=e[n[0]];if(void 0!==t){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,n=t.length;e0&&console.error(\\\\\\\"THREE.Points.updateMorphTargets() does not support THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\")}}}function PS(t,e,n,i,s,r,o){const a=CS.distanceSqToPoint(t);if(as.far)return;r.push({distance:l,distanceToRay:Math.sqrt(a),point:n,index:e,face:null,object:o})}}OS.prototype.isPoints=!0;(class extends vb{constructor(t,e,n,i,s,r,o,a,l){super(t,e,n,i,s,r,o,a,l),this.format=void 0!==o?o:Px,this.minFilter=void 0!==r?r:Tx,this.magFilter=void 0!==s?s:Tx,this.generateMipmaps=!1;const c=this;\\\\\\\"requestVideoFrameCallback\\\\\\\"in t&&t.requestVideoFrameCallback((function e(){c.needsUpdate=!0,t.requestVideoFrameCallback(e)}))}clone(){return new this.constructor(this.image).copy(this)}update(){const t=this.image;!1===\\\\\\\"requestVideoFrameCallback\\\\\\\"in t&&t.readyState>=t.HAVE_CURRENT_DATA&&(this.needsUpdate=!0)}}).prototype.isVideoTexture=!0;class RS extends vb{constructor(t,e,n,i,s,r,o,a,l,c,h,u){super(null,r,o,a,l,c,i,s,h,u),this.image={width:e,height:n},this.mipmaps=t,this.flipY=!1,this.generateMipmaps=!1}}RS.prototype.isCompressedTexture=!0;(class extends vb{constructor(t,e,n,i,s,r,o,a,l){super(t,e,n,i,s,r,o,a,l),this.needsUpdate=!0}}).prototype.isCanvasTexture=!0;(class extends vb{constructor(t,e,n,i,s,r,o,a,l,c){if((c=void 0!==c?c:Ix)!==Ix&&c!==Fx)throw new Error(\\\\\\\"DepthTexture format must be either THREE.DepthFormat or THREE.DepthStencilFormat\\\\\\\");void 0===n&&c===Ix&&(n=Sx),void 0===n&&c===Fx&&(n=Ox),super(null,i,s,r,o,a,c,n,l),this.image={width:t,height:e},this.magFilter=void 0!==o?o:xx,this.minFilter=void 0!==a?a:xx,this.flipY=!1,this.generateMipmaps=!1}}).prototype.isDepthTexture=!0;new Ab,new Ab,new Ab,new Bw;class IS{constructor(){this.type=\\\\\\\"Curve\\\\\\\",this.arcLengthDivisions=200}getPoint(){return console.warn(\\\\\\\"THREE.Curve: .getPoint() not implemented.\\\\\\\"),null}getPointAt(t,e){const n=this.getUtoTmapping(t);return this.getPoint(n,e)}getPoints(t=5){const e=[];for(let n=0;n<=t;n++)e.push(this.getPoint(n/t));return e}getSpacedPoints(t=5){const e=[];for(let n=0;n<=t;n++)e.push(this.getPointAt(n/t));return e}getLength(){const t=this.getLengths();return t[t.length-1]}getLengths(t=this.arcLengthDivisions){if(this.cacheArcLengths&&this.cacheArcLengths.length===t+1&&!this.needsUpdate)return this.cacheArcLengths;this.needsUpdate=!1;const e=[];let n,i=this.getPoint(0),s=0;e.push(0);for(let r=1;r<=t;r++)n=this.getPoint(r/t),s+=n.distanceTo(i),e.push(s),i=n;return this.cacheArcLengths=e,e}updateArcLengths(){this.needsUpdate=!0,this.getLengths()}getUtoTmapping(t,e){const n=this.getLengths();let i=0;const s=n.length;let r;r=e||t*n[s-1];let o,a=0,l=s-1;for(;a<=l;)if(i=Math.floor(a+(l-a)/2),o=n[i]-r,o<0)a=i+1;else{if(!(o>0)){l=i;break}l=i-1}if(i=l,n[i]===r)return i/(s-1);const c=n[i];return(i+(r-c)/(n[i+1]-c))/(s-1)}getTangent(t,e){const n=1e-4;let i=t-n,s=t+n;i<0&&(i=0),s>1&&(s=1);const r=this.getPoint(i),o=this.getPoint(s),a=e||(r.isVector2?new ub:new Ab);return a.copy(o).sub(r).normalize(),a}getTangentAt(t,e){const n=this.getUtoTmapping(t);return this.getTangent(n,e)}computeFrenetFrames(t,e){const n=new Ab,i=[],s=[],r=[],o=new Ab,a=new ew;for(let e=0;e<=t;e++){const n=e/t;i[e]=this.getTangentAt(n,new Ab)}s[0]=new Ab,r[0]=new Ab;let l=Number.MAX_VALUE;const c=Math.abs(i[0].x),h=Math.abs(i[0].y),u=Math.abs(i[0].z);c<=l&&(l=c,n.set(1,0,0)),h<=l&&(l=h,n.set(0,1,0)),u<=l&&n.set(0,0,1),o.crossVectors(i[0],n).normalize(),s[0].crossVectors(i[0],o),r[0].crossVectors(i[0],s[0]);for(let e=1;e<=t;e++){if(s[e]=s[e-1].clone(),r[e]=r[e-1].clone(),o.crossVectors(i[e-1],i[e]),o.length()>Number.EPSILON){o.normalize();const t=Math.acos(sb(i[e-1].dot(i[e]),-1,1));s[e].applyMatrix4(a.makeRotationAxis(o,t))}r[e].crossVectors(i[e],s[e])}if(!0===e){let e=Math.acos(sb(s[0].dot(s[t]),-1,1));e/=t,i[0].dot(o.crossVectors(s[0],s[t]))>0&&(e=-e);for(let n=1;n<=t;n++)s[n].applyMatrix4(a.makeRotationAxis(i[n],e*n)),r[n].crossVectors(i[n],s[n])}return{tangents:i,normals:s,binormals:r}}clone(){return(new this.constructor).copy(this)}copy(t){return this.arcLengthDivisions=t.arcLengthDivisions,this}toJSON(){const t={metadata:{version:4.5,type:\\\\\\\"Curve\\\\\\\",generator:\\\\\\\"Curve.toJSON\\\\\\\"}};return t.arcLengthDivisions=this.arcLengthDivisions,t.type=this.type,t}fromJSON(t){return this.arcLengthDivisions=t.arcLengthDivisions,this}}class FS extends IS{constructor(t=0,e=0,n=1,i=1,s=0,r=2*Math.PI,o=!1,a=0){super(),this.type=\\\\\\\"EllipseCurve\\\\\\\",this.aX=t,this.aY=e,this.xRadius=n,this.yRadius=i,this.aStartAngle=s,this.aEndAngle=r,this.aClockwise=o,this.aRotation=a}getPoint(t,e){const n=e||new ub,i=2*Math.PI;let s=this.aEndAngle-this.aStartAngle;const r=Math.abs(s)i;)s-=i;s0?0:(Math.floor(Math.abs(l)/s)+1)*s:0===c&&l===s-1&&(l=s-2,c=1),this.closed||l>0?o=i[(l-1)%s]:(zS.subVectors(i[0],i[1]).add(i[0]),o=zS);const h=i[l%s],u=i[(l+1)%s];if(this.closed||l+2i.length-2?i.length-1:r+1],h=i[r>i.length-3?i.length-1:r+2];return n.set(HS(o,a.x,l.x,c.x,h.x),HS(o,a.y,l.y,c.y,h.y)),n}copy(t){super.copy(t),this.points=[];for(let e=0,n=t.points.length;e=n){const t=i[s]-n,r=this.curves[s],o=r.getLength(),a=0===o?0:1-t/o;return r.getPointAt(a,e)}s++}return null}getLength(){const t=this.getCurveLengths();return t[t.length-1]}updateArcLengths(){this.needsUpdate=!0,this.cacheLengths=null,this.getCurveLengths()}getCurveLengths(){if(this.cacheLengths&&this.cacheLengths.length===this.curves.length)return this.cacheLengths;const t=[];let e=0;for(let n=0,i=this.curves.length;n1&&!e[e.length-1].equals(e[0])&&e.push(e[0]),e}copy(t){super.copy(t),this.curves=[];for(let e=0,n=t.curves.length;e0){const t=l.getPoint(0);t.equals(this.currentPoint)||this.lineTo(t.x,t.y)}this.curves.push(l);const c=l.getPoint(1);return this.currentPoint.copy(c),this}copy(t){return super.copy(t),this.currentPoint.copy(t.currentPoint),this}toJSON(){const t=super.toJSON();return t.currentPoint=this.currentPoint.toArray(),t}fromJSON(t){return super.fromJSON(t),this.currentPoint.fromArray(t.currentPoint),this}}class eC extends tC{constructor(t){super(t),this.uuid=ib(),this.type=\\\\\\\"Shape\\\\\\\",this.holes=[]}getPointsHoles(t){const e=[];for(let n=0,i=this.holes.length;n80*n){a=c=t[0],l=h=t[1];for(let e=n;ec&&(c=u),d>h&&(h=d);p=Math.max(c-a,h-l),p=0!==p?1/p:0}return rC(r,o,n,a,l,p),o};function iC(t,e,n,i,s){let r,o;if(s===function(t,e,n,i){let s=0;for(let r=e,o=n-i;r0)for(r=e;r=e;r-=i)o=AC(r,t[r],t[r+1],o);return o&&vC(o,o.next)&&(MC(o),o=o.next),o}function sC(t,e){if(!t)return t;e||(e=t);let n,i=t;do{if(n=!1,i.steiner||!vC(i,i.next)&&0!==gC(i.prev,i,i.next))i=i.next;else{if(MC(i),i=e=i.prev,i===i.next)break;n=!0}}while(n||i!==e);return e}function rC(t,e,n,i,s,r,o){if(!t)return;!o&&r&&function(t,e,n,i){let 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gC(t.prev,t,t.next)<0?gC(t,e,t.next)>=0&&gC(t,t.prev,e)>=0:gC(t,e,t.prev)<0||gC(t,t.next,e)<0}function TC(t,e){const n=new EC(t.i,t.x,t.y),i=new EC(e.i,e.x,e.y),s=t.next,r=e.prev;return t.next=e,e.prev=t,n.next=s,s.prev=n,i.next=n,n.prev=i,r.next=i,i.prev=r,i}function AC(t,e,n,i){const s=new EC(t,e,n);return i?(s.next=i.next,s.prev=i,i.next.prev=s,i.next=s):(s.prev=s,s.next=s),s}function MC(t){t.next.prev=t.prev,t.prev.next=t.next,t.prevZ&&(t.prevZ.nextZ=t.nextZ),t.nextZ&&(t.nextZ.prevZ=t.prevZ)}function EC(t,e,n){this.i=t,this.x=e,this.y=n,this.prev=null,this.next=null,this.z=null,this.prevZ=null,this.nextZ=null,this.steiner=!1}class SC{static area(t){const e=t.length;let n=0;for(let i=e-1,s=0;s2&&t[e-1].equals(t[0])&&t.pop()}function NC(t,e){for(let n=0;nNumber.EPSILON){const u=Math.sqrt(h),d=Math.sqrt(l*l+c*c),p=e.x-a/u,_=e.y+o/u,m=((n.x-c/d-p)*c-(n.y+l/d-_)*l)/(o*c-a*l);i=p+o*m-t.x,s=_+a*m-t.y;const f=i*i+s*s;if(f<=2)return new ub(i,s);r=Math.sqrt(f/2)}else{let t=!1;o>Number.EPSILON?l>Number.EPSILON&&(t=!0):o<-Number.EPSILON?l<-Number.EPSILON&&(t=!0):Math.sign(a)===Math.sign(c)&&(t=!0),t?(i=-a,s=o,r=Math.sqrt(h)):(i=o,s=a,r=Math.sqrt(h/2))}return new ub(i/r,s/r)}const O=[];for(let t=0,e=E.length,n=e-1,i=t+1;t=0;t--){const e=t/p,n=h*Math.cos(e*Math.PI/2),i=u*Math.sin(e*Math.PI/2)+d;for(let t=0,e=E.length;t=0;){const i=n;let s=n-1;s<0&&(s=t.length-1);for(let t=0,n=a+2*p;t0!=t>0&&this.version++,this._sheen=t}get clearcoat(){return this._clearcoat}set clearcoat(t){this._clearcoat>0!=t>0&&this.version++,this._clearcoat=t}get transmission(){return this._transmission}set transmission(t){this._transmission>0!=t>0&&this.version++,this._transmission=t}copy(t){return super.copy(t),this.defines={STANDARD:\\\\\\\"\\\\\\\",PHYSICAL:\\\\\\\"\\\\\\\"},this.clearcoat=t.clearcoat,this.clearcoatMap=t.clearcoatMap,this.clearcoatRoughness=t.clearcoatRoughness,this.clearcoatRoughnessMap=t.clearcoatRoughnessMap,this.clearcoatNormalMap=t.clearcoatNormalMap,this.clearcoatNormalScale.copy(t.clearcoatNormalScale),this.ior=t.ior,this.sheen=t.sheen,this.sheenTint.copy(t.sheenTint),this.sheenRoughness=t.sheenRoughness,this.transmission=t.transmission,this.transmissionMap=t.transmissionMap,this.thickness=t.thickness,this.thicknessMap=t.thicknessMap,this.attenuationDistance=t.attenuationDistance,this.attenuationTint.copy(t.attenuationTint),this.specularIntensity=t.specularIntensity,this.specularIntensityMap=t.specularIntensityMap,this.specularTint.copy(t.specularTint),this.specularTintMap=t.specularTintMap,this}}FC.prototype.isMeshPhysicalMaterial=!0;class DC extends kw{constructor(t){super(),this.type=\\\\\\\"MeshPhongMaterial\\\\\\\",this.color=new qw(16777215),this.specular=new qw(1118481),this.shininess=30,this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new qw(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new ub(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.specularMap=null,this.alphaMap=null,this.envMap=null,this.combine=0,this.reflectivity=1,this.refractionRatio=.98,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap=\\\\\\\"round\\\\\\\",this.wireframeLinejoin=\\\\\\\"round\\\\\\\",this.flatShading=!1,this.setValues(t)}copy(t){return super.copy(t),this.color.copy(t.color),this.specular.copy(t.specular),this.shininess=t.shininess,this.map=t.map,this.lightMap=t.lightMap,this.lightMapIntensity=t.lightMapIntensity,this.aoMap=t.aoMap,this.aoMapIntensity=t.aoMapIntensity,this.emissive.copy(t.emissive),this.emissiveMap=t.emissiveMap,this.emissiveIntensity=t.emissiveIntensity,this.bumpMap=t.bumpMap,this.bumpScale=t.bumpScale,this.normalMap=t.normalMap,this.normalMapType=t.normalMapType,this.normalScale.copy(t.normalScale),this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this.specularMap=t.specularMap,this.alphaMap=t.alphaMap,this.envMap=t.envMap,this.combine=t.combine,this.reflectivity=t.reflectivity,this.refractionRatio=t.refractionRatio,this.wireframe=t.wireframe,this.wireframeLinewidth=t.wireframeLinewidth,this.wireframeLinecap=t.wireframeLinecap,this.wireframeLinejoin=t.wireframeLinejoin,this.flatShading=t.flatShading,this}}DC.prototype.isMeshPhongMaterial=!0;class BC extends kw{constructor(t){super(),this.defines={TOON:\\\\\\\"\\\\\\\"},this.type=\\\\\\\"MeshToonMaterial\\\\\\\",this.color=new qw(16777215),this.map=null,this.gradientMap=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new qw(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new ub(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.alphaMap=null,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap=\\\\\\\"round\\\\\\\",this.wireframeLinejoin=\\\\\\\"round\\\\\\\",this.setValues(t)}copy(t){return super.copy(t),this.color.copy(t.color),this.map=t.map,this.gradientMap=t.gradientMap,this.lightMap=t.lightMap,this.lightMapIntensity=t.lightMapIntensity,this.aoMap=t.aoMap,this.aoMapIntensity=t.aoMapIntensity,this.emissive.copy(t.emissive),this.emissiveMap=t.emissiveMap,this.emissiveIntensity=t.emissiveIntensity,this.bumpMap=t.bumpMap,this.bumpScale=t.bumpScale,this.normalMap=t.normalMap,this.normalMapType=t.normalMapType,this.normalScale.copy(t.normalScale),this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this.alphaMap=t.alphaMap,this.wireframe=t.wireframe,this.wireframeLinewidth=t.wireframeLinewidth,this.wireframeLinecap=t.wireframeLinecap,this.wireframeLinejoin=t.wireframeLinejoin,this}}BC.prototype.isMeshToonMaterial=!0;class zC extends kw{constructor(t){super(),this.type=\\\\\\\"MeshNormalMaterial\\\\\\\",this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new ub(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.wireframe=!1,this.wireframeLinewidth=1,this.fog=!1,this.flatShading=!1,this.setValues(t)}copy(t){return super.copy(t),this.bumpMap=t.bumpMap,this.bumpScale=t.bumpScale,this.normalMap=t.normalMap,this.normalMapType=t.normalMapType,this.normalScale.copy(t.normalScale),this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this.wireframe=t.wireframe,this.wireframeLinewidth=t.wireframeLinewidth,this.flatShading=t.flatShading,this}}zC.prototype.isMeshNormalMaterial=!0;class kC extends kw{constructor(t){super(),this.type=\\\\\\\"MeshLambertMaterial\\\\\\\",this.color=new qw(16777215),this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new qw(0),this.emissiveIntensity=1,this.emissiveMap=null,this.specularMap=null,this.alphaMap=null,this.envMap=null,this.combine=0,this.reflectivity=1,this.refractionRatio=.98,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap=\\\\\\\"round\\\\\\\",this.wireframeLinejoin=\\\\\\\"round\\\\\\\",this.setValues(t)}copy(t){return super.copy(t),this.color.copy(t.color),this.map=t.map,this.lightMap=t.lightMap,this.lightMapIntensity=t.lightMapIntensity,this.aoMap=t.aoMap,this.aoMapIntensity=t.aoMapIntensity,this.emissive.copy(t.emissive),this.emissiveMap=t.emissiveMap,this.emissiveIntensity=t.emissiveIntensity,this.specularMap=t.specularMap,this.alphaMap=t.alphaMap,this.envMap=t.envMap,this.combine=t.combine,this.reflectivity=t.reflectivity,this.refractionRatio=t.refractionRatio,this.wireframe=t.wireframe,this.wireframeLinewidth=t.wireframeLinewidth,this.wireframeLinecap=t.wireframeLinecap,this.wireframeLinejoin=t.wireframeLinejoin,this}}kC.prototype.isMeshLambertMaterial=!0;class UC extends kw{constructor(t){super(),this.defines={MATCAP:\\\\\\\"\\\\\\\"},this.type=\\\\\\\"MeshMatcapMaterial\\\\\\\",this.color=new qw(16777215),this.matcap=null,this.map=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new ub(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.alphaMap=null,this.flatShading=!1,this.setValues(t)}copy(t){return super.copy(t),this.defines={MATCAP:\\\\\\\"\\\\\\\"},this.color.copy(t.color),this.matcap=t.matcap,this.map=t.map,this.bumpMap=t.bumpMap,this.bumpScale=t.bumpScale,this.normalMap=t.normalMap,this.normalMapType=t.normalMapType,this.normalScale.copy(t.normalScale),this.displacementMap=t.displacementMap,this.displacementScale=t.displacementScale,this.displacementBias=t.displacementBias,this.alphaMap=t.alphaMap,this.flatShading=t.flatShading,this}}UC.prototype.isMeshMatcapMaterial=!0;class GC extends mS{constructor(t){super(),this.type=\\\\\\\"LineDashedMaterial\\\\\\\",this.scale=1,this.dashSize=3,this.gapSize=1,this.setValues(t)}copy(t){return super.copy(t),this.scale=t.scale,this.dashSize=t.dashSize,this.gapSize=t.gapSize,this}}GC.prototype.isLineDashedMaterial=!0;const VC={arraySlice:function(t,e,n){return VC.isTypedArray(t)?new t.constructor(t.subarray(e,void 0!==n?n:t.length)):t.slice(e,n)},convertArray:function(t,e,n){return!t||!n&&t.constructor===e?t:\\\\\\\"number\\\\\\\"==typeof e.BYTES_PER_ELEMENT?new e(t):Array.prototype.slice.call(t)},isTypedArray:function(t){return ArrayBuffer.isView(t)&&!(t instanceof DataView)},getKeyframeOrder:function(t){const e=t.length,n=new Array(e);for(let t=0;t!==e;++t)n[t]=t;return n.sort((function(e,n){return t[e]-t[n]})),n},sortedArray:function(t,e,n){const i=t.length,s=new t.constructor(i);for(let r=0,o=0;o!==i;++r){const i=n[r]*e;for(let n=0;n!==e;++n)s[o++]=t[i+n]}return s},flattenJSON:function(t,e,n,i){let s=1,r=t[0];for(;void 0!==r&&void 0===r[i];)r=t[s++];if(void 0===r)return;let o=r[i];if(void 0!==o)if(Array.isArray(o))do{o=r[i],void 0!==o&&(e.push(r.time),n.push.apply(n,o)),r=t[s++]}while(void 0!==r);else if(void 0!==o.toArray)do{o=r[i],void 0!==o&&(e.push(r.time),o.toArray(n,n.length)),r=t[s++]}while(void 0!==r);else do{o=r[i],void 0!==o&&(e.push(r.time),n.push(o)),r=t[s++]}while(void 0!==r)},subclip:function(t,e,n,i,s=30){const r=t.clone();r.name=e;const o=[];for(let t=0;t=i)){l.push(e.times[t]);for(let n=0;nr.tracks[t].times[0]&&(a=r.tracks[t].times[0]);for(let t=0;t=i.times[u]){const t=u*l+a,e=t+l-a;d=VC.arraySlice(i.values,t,e)}else{const t=i.createInterpolant(),e=a,n=l-a;t.evaluate(r),d=VC.arraySlice(t.resultBuffer,e,n)}if(\\\\\\\"quaternion\\\\\\\"===s){(new Tb).fromArray(d).normalize().conjugate().toArray(d)}const p=o.times.length;for(let t=0;t=s)break t;{const o=e[1];t=s)break e}r=n,n=0}}for(;n>>1;te;)--r;if(++r,0!==s||r!==i){s>=r&&(r=Math.max(r,1),s=r-1);const t=this.getValueSize();this.times=VC.arraySlice(n,s,r),this.values=VC.arraySlice(this.values,s*t,r*t)}return this}validate(){let t=!0;const e=this.getValueSize();e-Math.floor(e)!=0&&(console.error(\\\\\\\"THREE.KeyframeTrack: Invalid value size in track.\\\\\\\",this),t=!1);const n=this.times,i=this.values,s=n.length;0===s&&(console.error(\\\\\\\"THREE.KeyframeTrack: Track is empty.\\\\\\\",this),t=!1);let r=null;for(let e=0;e!==s;e++){const i=n[e];if(\\\\\\\"number\\\\\\\"==typeof i&&isNaN(i)){console.error(\\\\\\\"THREE.KeyframeTrack: Time is not a valid number.\\\\\\\",this,e,i),t=!1;break}if(null!==r&&r>i){console.error(\\\\\\\"THREE.KeyframeTrack: Out of order keys.\\\\\\\",this,e,i,r),t=!1;break}r=i}if(void 0!==i&&VC.isTypedArray(i))for(let e=0,n=i.length;e!==n;++e){const n=i[e];if(isNaN(n)){console.error(\\\\\\\"THREE.KeyframeTrack: Value is not a valid number.\\\\\\\",this,e,n),t=!1;break}}return t}optimize(){const t=VC.arraySlice(this.times),e=VC.arraySlice(this.values),n=this.getValueSize(),i=this.getInterpolation()===zx,s=t.length-1;let r=1;for(let o=1;o0){t[r]=t[s];for(let t=s*n,i=r*n,o=0;o!==n;++o)e[i+o]=e[t+o];++r}return r!==t.length?(this.times=VC.arraySlice(t,0,r),this.values=VC.arraySlice(e,0,r*n)):(this.times=t,this.values=e),this}clone(){const t=VC.arraySlice(this.times,0),e=VC.arraySlice(this.values,0),n=new(0,this.constructor)(this.name,t,e);return n.createInterpolant=this.createInterpolant,n}}XC.prototype.TimeBufferType=Float32Array,XC.prototype.ValueBufferType=Float32Array,XC.prototype.DefaultInterpolation=Bx;class YC extends XC{}YC.prototype.ValueTypeName=\\\\\\\"bool\\\\\\\",YC.prototype.ValueBufferType=Array,YC.prototype.DefaultInterpolation=Dx,YC.prototype.InterpolantFactoryMethodLinear=void 0,YC.prototype.InterpolantFactoryMethodSmooth=void 0;class $C extends XC{}$C.prototype.ValueTypeName=\\\\\\\"color\\\\\\\";class JC extends XC{}JC.prototype.ValueTypeName=\\\\\\\"number\\\\\\\";class ZC extends HC{constructor(t,e,n,i){super(t,e,n,i)}interpolate_(t,e,n,i){const s=this.resultBuffer,r=this.sampleValues,o=this.valueSize,a=(n-e)/(i-e);let l=t*o;for(let t=l+o;l!==t;l+=4)Tb.slerpFlat(s,0,r,l-o,r,l,a);return s}}class QC extends XC{InterpolantFactoryMethodLinear(t){return new ZC(this.times,this.values,this.getValueSize(),t)}}QC.prototype.ValueTypeName=\\\\\\\"quaternion\\\\\\\",QC.prototype.DefaultInterpolation=Bx,QC.prototype.InterpolantFactoryMethodSmooth=void 0;class KC extends XC{}KC.prototype.ValueTypeName=\\\\\\\"string\\\\\\\",KC.prototype.ValueBufferType=Array,KC.prototype.DefaultInterpolation=Dx,KC.prototype.InterpolantFactoryMethodLinear=void 0,KC.prototype.InterpolantFactoryMethodSmooth=void 0;class tN extends XC{}tN.prototype.ValueTypeName=\\\\\\\"vector\\\\\\\";class eN{constructor(t,e=-1,n,i=2500){this.name=t,this.tracks=n,this.duration=e,this.blendMode=i,this.uuid=ib(),this.duration<0&&this.resetDuration()}static parse(t){const e=[],n=t.tracks,i=1/(t.fps||1);for(let t=0,s=n.length;t!==s;++t)e.push(nN(n[t]).scale(i));const s=new this(t.name,t.duration,e,t.blendMode);return s.uuid=t.uuid,s}static toJSON(t){const e=[],n=t.tracks,i={name:t.name,duration:t.duration,tracks:e,uuid:t.uuid,blendMode:t.blendMode};for(let t=0,i=n.length;t!==i;++t)e.push(XC.toJSON(n[t]));return i}static CreateFromMorphTargetSequence(t,e,n,i){const s=e.length,r=[];for(let t=0;t1){const t=r[1];let e=i[t];e||(i[t]=e=[]),e.push(n)}}const r=[];for(const t in i)r.push(this.CreateFromMorphTargetSequence(t,i[t],e,n));return r}static parseAnimation(t,e){if(!t)return console.error(\\\\\\\"THREE.AnimationClip: No animation in JSONLoader data.\\\\\\\"),null;const n=function(t,e,n,i,s){if(0!==n.length){const r=[],o=[];VC.flattenJSON(n,r,o,i),0!==r.length&&s.push(new t(e,r,o))}},i=[],s=t.name||\\\\\\\"default\\\\\\\",r=t.fps||30,o=t.blendMode;let a=t.length||-1;const l=t.hierarchy||[];for(let t=0;t0){this.source.connect(this.filters[0]);for(let t=1,e=this.filters.length;t0){this.source.disconnect(this.filters[0]);for(let t=1,e=this.filters.length;t0&&this._mixBufferRegionAdditive(n,i,this._addIndex*e,1,e);for(let t=e,s=e+e;t!==s;++t)if(n[t]!==n[t+e]){o.setValue(n,i);break}}saveOriginalState(){const t=this.binding,e=this.buffer,n=this.valueSize,i=n*this._origIndex;t.getValue(e,i);for(let t=n,s=i;t!==s;++t)e[t]=e[i+t%n];this._setIdentity(),this.cumulativeWeight=0,this.cumulativeWeightAdditive=0}restoreOriginalState(){const t=3*this.valueSize;this.binding.setValue(this.buffer,t)}_setAdditiveIdentityNumeric(){const t=this._addIndex*this.valueSize,e=t+this.valueSize;for(let n=t;n=.5)for(let i=0;i!==s;++i)t[e+i]=t[n+i]}_slerp(t,e,n,i){Tb.slerpFlat(t,e,t,e,t,n,i)}_slerpAdditive(t,e,n,i,s){const r=this._workIndex*s;Tb.multiplyQuaternionsFlat(t,r,t,e,t,n),Tb.slerpFlat(t,e,t,e,t,r,i)}_lerp(t,e,n,i,s){const r=1-i;for(let o=0;o!==s;++o){const s=e+o;t[s]=t[s]*r+t[n+o]*i}}_lerpAdditive(t,e,n,i,s){for(let r=0;r!==s;++r){const s=e+r;t[s]=t[s]+t[n+r]*i}}}const zN=\\\\\\\"\\\\\\\\[\\\\\\\\]\\\\\\\\.:\\\\\\\\/\\\\\\\",kN=new RegExp(\\\\\\\"[\\\\\\\\[\\\\\\\\]\\\\\\\\.:\\\\\\\\/]\\\\\\\",\\\\\\\"g\\\\\\\"),UN=\\\\\\\"[^\\\\\\\\[\\\\\\\\]\\\\\\\\.:\\\\\\\\/]\\\\\\\",GN=\\\\\\\"[^\\\\\\\"+zN.replace(\\\\\\\"\\\\\\\\.\\\\\\\",\\\\\\\"\\\\\\\")+\\\\\\\"]\\\\\\\",VN=/((?:WC+[\\\\/:])*)/.source.replace(\\\\\\\"WC\\\\\\\",UN),HN=/(WCOD+)?/.source.replace(\\\\\\\"WCOD\\\\\\\",GN),jN=/(?:\\\\.(WC+)(?:\\\\[(.+)\\\\])?)?/.source.replace(\\\\\\\"WC\\\\\\\",UN),WN=/\\\\.(WC+)(?:\\\\[(.+)\\\\])?/.source.replace(\\\\\\\"WC\\\\\\\",UN),qN=new RegExp(\\\\\\\"^\\\\\\\"+VN+HN+jN+WN+\\\\\\\"$\\\\\\\"),XN=[\\\\\\\"material\\\\\\\",\\\\\\\"materials\\\\\\\",\\\\\\\"bones\\\\\\\"];class YN{constructor(t,e,n){this.path=e,this.parsedPath=n||YN.parseTrackName(e),this.node=YN.findNode(t,this.parsedPath.nodeName)||t,this.rootNode=t,this.getValue=this._getValue_unbound,this.setValue=this._setValue_unbound}static create(t,e,n){return t&&t.isAnimationObjectGroup?new YN.Composite(t,e,n):new YN(t,e,n)}static sanitizeNodeName(t){return t.replace(/\\\\s/g,\\\\\\\"_\\\\\\\").replace(kN,\\\\\\\"\\\\\\\")}static parseTrackName(t){const e=qN.exec(t);if(!e)throw new Error(\\\\\\\"PropertyBinding: Cannot parse trackName: \\\\\\\"+t);const n={nodeName:e[2],objectName:e[3],objectIndex:e[4],propertyName:e[5],propertyIndex:e[6]},i=n.nodeName&&n.nodeName.lastIndexOf(\\\\\\\".\\\\\\\");if(void 0!==i&&-1!==i){const t=n.nodeName.substring(i+1);-1!==XN.indexOf(t)&&(n.nodeName=n.nodeName.substring(0,i),n.objectName=t)}if(null===n.propertyName||0===n.propertyName.length)throw new Error(\\\\\\\"PropertyBinding: can not parse propertyName from trackName: \\\\\\\"+t);return n}static findNode(t,e){if(!e||\\\\\\\"\\\\\\\"===e||\\\\\\\".\\\\\\\"===e||-1===e||e===t.name||e===t.uuid)return t;if(t.skeleton){const n=t.skeleton.getBoneByName(e);if(void 0!==n)return n}if(t.children){const n=function(t){for(let i=0;i0){const t=this._interpolants,e=this._propertyBindings;switch(this.blendMode){case 2501:for(let n=0,i=t.length;n!==i;++n)t[n].evaluate(r),e[n].accumulateAdditive(o);break;case Vx:default:for(let n=0,s=t.length;n!==s;++n)t[n].evaluate(r),e[n].accumulate(i,o)}}}_updateWeight(t){let e=0;if(this.enabled){e=this.weight;const n=this._weightInterpolant;if(null!==n){const i=n.evaluate(t)[0];e*=i,t>n.parameterPositions[1]&&(this.stopFading(),0===i&&(this.enabled=!1))}}return this._effectiveWeight=e,e}_updateTimeScale(t){let e=0;if(!this.paused){e=this.timeScale;const n=this._timeScaleInterpolant;if(null!==n){e*=n.evaluate(t)[0],t>n.parameterPositions[1]&&(this.stopWarping(),0===e?this.paused=!0:this.timeScale=e)}}return this._effectiveTimeScale=e,e}_updateTime(t){const e=this._clip.duration,n=this.loop;let i=this.time+t,s=this._loopCount;const r=2202===n;if(0===t)return-1===s?i:r&&1==(1&s)?e-i:i;if(2200===n){-1===s&&(this._loopCount=0,this._setEndings(!0,!0,!1));t:{if(i>=e)i=e;else{if(!(i<0)){this.time=i;break t}i=0}this.clampWhenFinished?this.paused=!0:this.enabled=!1,this.time=i,this._mixer.dispatchEvent({type:\\\\\\\"finished\\\\\\\",action:this,direction:t<0?-1:1})}}else{if(-1===s&&(t>=0?(s=0,this._setEndings(!0,0===this.repetitions,r)):this._setEndings(0===this.repetitions,!0,r)),i>=e||i<0){const n=Math.floor(i/e);i-=e*n,s+=Math.abs(n);const o=this.repetitions-s;if(o<=0)this.clampWhenFinished?this.paused=!0:this.enabled=!1,i=t>0?e:0,this.time=i,this._mixer.dispatchEvent({type:\\\\\\\"finished\\\\\\\",action:this,direction:t>0?1:-1});else{if(1===o){const e=t<0;this._setEndings(e,!e,r)}else this._setEndings(!1,!1,r);this._loopCount=s,this.time=i,this._mixer.dispatchEvent({type:\\\\\\\"loop\\\\\\\",action:this,loopDelta:n})}}else this.time=i;if(r&&1==(1&s))return e-i}return i}_setEndings(t,e,n){const i=this._interpolantSettings;n?(i.endingStart=Ux,i.endingEnd=Ux):(i.endingStart=t?this.zeroSlopeAtStart?Ux:kx:Gx,i.endingEnd=e?this.zeroSlopeAtEnd?Ux:kx:Gx)}_scheduleFading(t,e,n){const i=this._mixer,s=i.time;let r=this._weightInterpolant;null===r&&(r=i._lendControlInterpolant(),this._weightInterpolant=r);const o=r.parameterPositions,a=r.sampleValues;return o[0]=s,a[0]=e,o[1]=s+t,a[1]=n,this}}(class extends Zx{constructor(t){super(),this._root=t,this._initMemoryManager(),this._accuIndex=0,this.time=0,this.timeScale=1}_bindAction(t,e){const n=t._localRoot||this._root,i=t._clip.tracks,s=i.length,r=t._propertyBindings,o=t._interpolants,a=n.uuid,l=this._bindingsByRootAndName;let c=l[a];void 0===c&&(c={},l[a]=c);for(let t=0;t!==s;++t){const s=i[t],l=s.name;let h=c[l];if(void 0!==h)r[t]=h;else{if(h=r[t],void 0!==h){null===h._cacheIndex&&(++h.referenceCount,this._addInactiveBinding(h,a,l));continue}const i=e&&e._propertyBindings[t].binding.parsedPath;h=new BN(YN.create(n,l,i),s.ValueTypeName,s.getValueSize()),++h.referenceCount,this._addInactiveBinding(h,a,l),r[t]=h}o[t].resultBuffer=h.buffer}}_activateAction(t){if(!this._isActiveAction(t)){if(null===t._cacheIndex){const e=(t._localRoot||this._root).uuid,n=t._clip.uuid,i=this._actionsByClip[n];this._bindAction(t,i&&i.knownActions[0]),this._addInactiveAction(t,n,e)}const e=t._propertyBindings;for(let t=0,n=e.length;t!==n;++t){const n=e[t];0==n.useCount++&&(this._lendBinding(n),n.saveOriginalState())}this._lendAction(t)}}_deactivateAction(t){if(this._isActiveAction(t)){const e=t._propertyBindings;for(let t=0,n=e.length;t!==n;++t){const n=e[t];0==--n.useCount&&(n.restoreOriginalState(),this._takeBackBinding(n))}this._takeBackAction(t)}}_initMemoryManager(){this._actions=[],this._nActiveActions=0,this._actionsByClip={},this._bindings=[],this._nActiveBindings=0,this._bindingsByRootAndName={},this._controlInterpolants=[],this._nActiveControlInterpolants=0;const t=this;this.stats={actions:{get total(){return t._actions.length},get inUse(){return t._nActiveActions}},bindings:{get total(){return t._bindings.length},get inUse(){return t._nActiveBindings}},controlInterpolants:{get total(){return t._controlInterpolants.length},get inUse(){return t._nActiveControlInterpolants}}}}_isActiveAction(t){const e=t._cacheIndex;return null!==e&&e=0;--e)t[e].stop();return this}update(t){t*=this.timeScale;const e=this._actions,n=this._nActiveActions,i=this.time+=t,s=Math.sign(t),r=this._accuIndex^=1;for(let o=0;o!==n;++o){e[o]._update(i,t,s,r)}const o=this._bindings,a=this._nActiveBindings;for(let t=0;t!==a;++t)o[t].apply(r);return this}setTime(t){this.time=0;for(let t=0;tthis.max.x||t.ythis.max.y)}containsBox(t){return this.min.x<=t.min.x&&t.max.x<=this.max.x&&this.min.y<=t.min.y&&t.max.y<=this.max.y}getParameter(t,e){return e.set((t.x-this.min.x)/(this.max.x-this.min.x),(t.y-this.min.y)/(this.max.y-this.min.y))}intersectsBox(t){return!(t.max.xthis.max.x||t.max.ythis.max.y)}clampPoint(t,e){return e.copy(t).clamp(this.min,this.max)}distanceToPoint(t){return ZN.copy(t).clamp(this.min,this.max).sub(t).length()}intersect(t){return this.min.max(t.min),this.max.min(t.max),this}union(t){return this.min.min(t.min),this.max.max(t.max),this}translate(t){return this.min.add(t),this.max.add(t),this}equals(t){return t.min.equals(this.min)&&t.max.equals(this.max)}}QN.prototype.isBox2=!0;const KN=new Ab,tL=new Ab;class eL{constructor(t=new Ab,e=new Ab){this.start=t,this.end=e}set(t,e){return this.start.copy(t),this.end.copy(e),this}copy(t){return this.start.copy(t.start),this.end.copy(t.end),this}getCenter(t){return t.addVectors(this.start,this.end).multiplyScalar(.5)}delta(t){return t.subVectors(this.end,this.start)}distanceSq(){return this.start.distanceToSquared(this.end)}distance(){return this.start.distanceTo(this.end)}at(t,e){return this.delta(e).multiplyScalar(t).add(this.start)}closestPointToPointParameter(t,e){KN.subVectors(t,this.start),tL.subVectors(this.end,this.start);const n=tL.dot(tL);let i=tL.dot(KN)/n;return e&&(i=sb(i,0,1)),i}closestPointToPoint(t,e,n){const i=this.closestPointToPointParameter(t,e);return this.delta(n).multiplyScalar(i).add(this.start)}applyMatrix4(t){return this.start.applyMatrix4(t),this.end.applyMatrix4(t),this}equals(t){return t.start.equals(this.start)&&t.end.equals(this.end)}clone(){return(new this.constructor).copy(this)}}(class extends Ew{constructor(t){super(),this.material=t,this.render=function(){},this.hasPositions=!1,this.hasNormals=!1,this.hasColors=!1,this.hasUvs=!1,this.positionArray=null,this.normalArray=null,this.colorArray=null,this.uvArray=null,this.count=0}}).prototype.isImmediateRenderObject=!0;const nL=new Ab,iL=new ew,sL=new ew;function rL(t){const e=[];t&&t.isBone&&e.push(t);for(let n=0;n8&&t<16&&e[n].split(t+1),0!==i&&this.subTrees.push(e[n])}return this}build(){return this.calcBox(),this.split(0),this}getRayTriangles(t,e){for(let n=0;n0)for(let t=0;t0&&i>0||n<-t.radius&&i<-t.radius)return!1;const s=Math.abs(n/(Math.abs(n)+Math.abs(i))),r=uL.copy(t.start).lerp(t.end,s);if(e.containsPoint(r))return{normal:pL.normal.clone(),point:r.clone(),depth:Math.abs(Math.min(n,i))};const o=t.radius*t.radius,a=_L.set(t.start,t.end),l=[[e.a,e.b],[e.b,e.c],[e.c,e.a]];for(let e=0;e0)for(let t=0;t0)for(let t=0;ta&&(i=o.clone().add(t.origin),s=a,n=e[r])}}return s<1e100&&{distance:s,triangle:n,position:i}}fromGraphNode(t){return t.updateWorldMatrix(!0,!0),t.traverse((t=>{if(!0===t.isMesh){let e,n=!1;null!==t.geometry.index?(n=!0,e=t.geometry.toNonIndexed()):e=t.geometry;const i=e.getAttribute(\\\\\\\"position\\\\\\\");for(let e=0;e{if(!e){const n=t;n.geometry&&(e=n)}})),e?this._playerCollisionController=new yL(e):console.error(\\\\\\\"no geo found in\\\\\\\",t)}else this._playerCollisionController=void 0}setCollisionCapsule(t){var e;null===(e=this._playerCollisionController)||void 0===e||e.setCapsule(t)}setJumpParams(t){}setGravity(t){}setPlayerMass(t){}}const bL={rotateSpeed:1,rotationRange:{min:.25*-Math.PI,max:.25*Math.PI}},wL={type:\\\\\\\"change\\\\\\\"},TL=new p.a,AL=new oy;class ML extends xL{constructor(t,e,n){super(),this._camera=t,this.domElement=e,this.player=n,this.translationData={direction:new p.a},this.rotationData={direction:{x:0,y:0}},this._boundMethods={onRotateStart:this._onRotateStart.bind(this),onRotateMove:this._onRotateMove.bind(this),onRotateEnd:this._onRotateEnd.bind(this),onTranslateStart:this._onTranslateStart.bind(this),onTranslateMove:this._onTranslateMove.bind(this),onTranslateEnd:this._onTranslateEnd.bind(this),onJump:this._onJump.bind(this),onRunToggle:this._onRunToggle.bind(this)},this._startCameraRotation=new Zv.a,this._rotationSpeed=bL.rotateSpeed,this._rotationRange={min:bL.rotationRange.min,max:bL.rotationRange.max},this._azimuthalAngle=0,this.vLeft=new p.a,this.vRight=new p.a,this.vTop=new p.a,this.vBottom=new p.a,this.angleY=0,this.angleX=0,this._rotationStartPosition=new d.a,this._rotationMovePosition=new d.a,this._rotationDelta=new d.a,this._startCameraPosition=new p.a,this._translationStartPosition=new d.a,this._translationMovePosition=new d.a,this._translationDelta=new d.a,this._camera.rotation.order=\\\\\\\"ZYX\\\\\\\",this._translateDomElement=this._createTranslateDomElement(),this._translateDomElementRect=this._translateDomElement.getBoundingClientRect(),this._runDomElement=this._createRunDomElement(),this._jumpDomElement=this._createJumpDomElement(),this._addElements(),this._addEvents()}dispose(){this._removeEvents(),this._removeElements(),this.updateElements()}_createTranslateDomElement(){const t=this.domElement.getBoundingClientRect(),e=Math.min(t.width,t.height),n=Math.round(.4*e),i=Math.round(.1*e),s=document.createElement(\\\\\\\"div\\\\\\\");return s.id=\\\\\\\"MobileJoystickControls-translate\\\\\\\",s.style.width=`${n}px`,s.style.height=s.style.width,s.style.border=\\\\\\\"1px solid black\\\\\\\",s.style.borderRadius=`${n}px`,s.style.position=\\\\\\\"absolute\\\\\\\",s.style.bottom=`${i}px`,s.style.left=`${i}px`,s}_jumpDomElementSize(){const t=this.domElement.getBoundingClientRect(),e=Math.min(t.width,t.height);return{size:Math.round(.2*e),margin:Math.round(.05*e)}}_createJumpDomElement(){const{size:t,margin:e}=this._jumpDomElementSize(),n=document.createElement(\\\\\\\"div\\\\\\\");n.id=\\\\\\\"MobileJoystickControls-jump\\\\\\\",n.style.width=`${t}px`;const i=Math.floor(t);return n.style.height=`${i}px`,n.style.border=\\\\\\\"1px solid black\\\\\\\",n.style.position=\\\\\\\"absolute\\\\\\\",n.style.bottom=`${2*e+parseInt(this._runDomElement.style.height)}px`,n.style.right=`${e}px`,n.style.borderRadius=`${i}px`,n}_createRunDomElement(){const t=document.createElement(\\\\\\\"div\\\\\\\"),e=this.domElement.getBoundingClientRect(),n=Math.min(e.width,e.height),i=Math.round(.2*n),s=Math.round(.05*n);return t.id=\\\\\\\"MobileJoystickControls-run\\\\\\\",t.style.width=`${i}px`,t.style.height=`${Math.floor(i)}px`,t.style.border=\\\\\\\"1px solid black\\\\\\\",t.style.position=\\\\\\\"absolute\\\\\\\",t.style.bottom=`${s}px`,t.style.right=`${s}px`,t.style.translate=\\\\\\\"-50%\\\\\\\",t}_addElements(){var t,e,n;null===(t=this.domElement.parentElement)||void 0===t||t.append(this._translateDomElement),null===(e=this.domElement.parentElement)||void 0===e||e.append(this._jumpDomElement),null===(n=this.domElement.parentElement)||void 0===n||n.append(this._runDomElement)}_removeElements(){var t;const e=[this._translateDomElement,this._jumpDomElement,this._runDomElement];for(let n of e)null===(t=n.parentElement)||void 0===t||t.removeChild(n)}updateElements(){this.player&&(this._jumpDomElement.style.display=this.player.jumpAllowed?\\\\\\\"block\\\\\\\":\\\\\\\"none\\\\\\\",this._runDomElement.style.display=this.player.runAllowed?\\\\\\\"block\\\\\\\":\\\\\\\"none\\\\\\\")}_addEvents(){cx.disableContextMenu(),this.domElement.addEventListener(\\\\\\\"touchstart\\\\\\\",this._boundMethods.onRotateStart),this.domElement.addEventListener(\\\\\\\"touchmove\\\\\\\",this._boundMethods.onRotateMove),this.domElement.addEventListener(\\\\\\\"touchend\\\\\\\",this._boundMethods.onRotateEnd),this._translateDomElement.addEventListener(\\\\\\\"touchstart\\\\\\\",this._boundMethods.onTranslateStart),this._translateDomElement.addEventListener(\\\\\\\"touchmove\\\\\\\",this._boundMethods.onTranslateMove),this._translateDomElement.addEventListener(\\\\\\\"touchend\\\\\\\",this._boundMethods.onTranslateEnd),this._jumpDomElement.addEventListener(\\\\\\\"pointerdown\\\\\\\",this._boundMethods.onJump),this._runDomElement.addEventListener(\\\\\\\"pointerdown\\\\\\\",this._boundMethods.onRunToggle)}_removeEvents(){cx.reEstablishContextMenu(),this.domElement.removeEventListener(\\\\\\\"touchstart\\\\\\\",this._boundMethods.onRotateStart),this.domElement.removeEventListener(\\\\\\\"touchmove\\\\\\\",this._boundMethods.onRotateMove),this.domElement.removeEventListener(\\\\\\\"touchend\\\\\\\",this._boundMethods.onRotateEnd),this._translateDomElement.removeEventListener(\\\\\\\"touchstart\\\\\\\",this._boundMethods.onTranslateStart),this._translateDomElement.removeEventListener(\\\\\\\"touchmove\\\\\\\",this._boundMethods.onTranslateMove),this._translateDomElement.removeEventListener(\\\\\\\"touchend\\\\\\\",this._boundMethods.onTranslateEnd),this._jumpDomElement.removeEventListener(\\\\\\\"pointerdown\\\\\\\",this._boundMethods.onJump),this._runDomElement.removeEventListener(\\\\\\\"pointerdown\\\\\\\",this._boundMethods.onRunToggle)}setRotationSpeed(t){this._rotationSpeed=t}setRotationRange(t){this._rotationRange.min=t.min,this._rotationRange.max=t.max}_onRotateStart(t){this._startCameraRotation.copy(this._camera.rotation);const e=this._getTouch(t,this.domElement);e&&(this._rotationStartPosition.set(e.clientX,e.clientY),this.vLeft.set(-1,0,.5),this.vRight.set(1,0,.5),[this.vLeft,this.vRight].forEach((t=>{t.unproject(this._camera),this._camera.worldToLocal(t)})),this.angleY=this.vLeft.angleTo(this.vRight),this.vTop.set(0,1,.5),this.vBottom.set(0,-1,.5),[this.vTop,this.vBottom].forEach((t=>{t.unproject(this._camera),this._camera.worldToLocal(t)})),this.angleX=this.vTop.angleTo(this.vBottom))}_onRotateMove(t){const e=this._getTouch(t,this.domElement);e&&(this._rotationMovePosition.set(e.clientX,e.clientY),this._rotationDelta.copy(this._rotationMovePosition).sub(this._rotationStartPosition),this.rotationData.direction.x=this._rotationDelta.x/this.domElement.clientWidth,this.rotationData.direction.y=this._rotationDelta.y/this.domElement.clientHeight,this._rotateCamera(this.rotationData))}_onRotateEnd(){this.rotationData.direction.x=0,this.rotationData.direction.y=0}_rotateCamera(t){let e=this.angleY*t.direction.x*this._rotationSpeed;this._camera.rotation.y=this._startCameraRotation.y+-e;let n=this.angleX*t.direction.y*this._rotationSpeed;this._camera.rotation.x=or.clamp(this._startCameraRotation.x+-n,this._rotationRange.min,this._rotationRange.max),this._computeAzimuthalAngle(),this.dispatchEvent(wL)}_computeAzimuthalAngle(){this._camera.updateMatrixWorld(),TL.set(0,0,1),this._camera.localToWorld(TL),TL.sub(this._camera.position),AL.setFromVector3(TL),this._azimuthalAngle=AL.theta}_onTranslateStart(t){this._startCameraPosition.copy(this._camera.position);if(!this._getTouch(t,this._translateDomElement))return;this._translateDomElementRect=this._translateDomElement.getBoundingClientRect();const e=this._translateDomElementRect.left+.5*this._translateDomElementRect.width,n=this._translateDomElementRect.top+.5*this._translateDomElementRect.height;this._translationStartPosition.set(e,n)}_onTranslateMove(t){const e=this._getTouch(t,this._translateDomElement);e&&(this._translationMovePosition.set(e.clientX,e.clientY),this._translationDelta.copy(this._translationMovePosition).sub(this._translationStartPosition),this.translationData.direction.x=this._translationDelta.x/this._translateDomElementRect.width*.5,this.translationData.direction.z=-this._translationDelta.y/this._translateDomElementRect.height*.5,this._updatePlayerTranslate(),this.dispatchEvent(wL))}_onTranslateEnd(){this.translationData.direction.x=0,this.translationData.direction.z=0,this._updatePlayerTranslate()}_updatePlayerTranslate(){if(!this.player)return;const t=this.translationData.direction;this.player.setForward(!1),this.player.setBackward(!1),this.player.setLeft(!1),this.player.setRight(!1);const e=Math.abs(t.x),n=Math.abs(t.z),i=n-e;function s(e){t.z>0&&e.setForward(!0),t.z<0&&e.setBackward(!0)}function r(e){t.x>0&&e.setRight(!0),t.x<0&&e.setLeft(!0)}i>0?(s(this.player),i<.5*n&&r(this.player)):(r(this.player),i<.5*e&&s(this.player))}_onJump(){var t;null===(t=this.player)||void 0===t||t.jump()}_onRunToggle(){if(!this.player)return;const t=this.player.running();this.player.setRun(!t);const e=this.player.running()?3:1;this._runDomElement.style.border=`${e}px solid black`}update(t){this.player&&(this.player.setAzimuthalAngle(this._azimuthalAngle),this.player.update(t))}_getTouch(t,e){for(let n=0;n{OL.PARAM_CALLBACK_updatePlayerParams(t)}}}const LL=new class extends ua{constructor(){super(...arguments),this.main=ha.FOLDER(),this.colliderObject=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.SOP},dependentOnFoundNode:!1,callback:t=>{OL.PARAM_CALLBACK_updateCollider(t)}}),this.capsuleRadius=ha.FLOAT(.5,{range:[0,1],rangeLocked:[!0,!1],...NL()}),this.capsuleHeight=ha.FLOAT(1,{range:[0,2],rangeLocked:[!0,!1],...NL()}),this.physics=ha.FOLDER(),this.physicsSteps=ha.INTEGER(5,{range:[1,10],rangeLocked:[!0,!1],...NL()}),this.gravity=ha.VECTOR3([0,-30,0],{...NL()}),this.translateSpeed=ha.FLOAT(1),this.rotateSpeed=ha.FLOAT(bL.rotateSpeed),this.jumpAllowed=ha.BOOLEAN(!0,{...NL()}),this.jumpStrength=ha.FLOAT(10,{range:[0,100],rangeLocked:[!0,!1],...NL()}),this.runAllowed=ha.BOOLEAN(!0,{...NL()}),this.runSpeedMult=ha.FLOAT(2,{range:[0,10],rangeLocked:[!0,!1],...NL()}),this.updateCollider=ha.BUTTON(null,{callback:t=>{OL.PARAM_CALLBACK_updateCollider(t)}}),this.init=ha.FOLDER(),this.startPosition=ha.VECTOR3([0,2,0],{...NL()}),this.startRotation=ha.VECTOR3([0,0,0],{...NL()}),this.reset=ha.BUTTON(null,{callback:t=>{OL.PARAM_CALLBACK_resetPlayer(t)}}),this.minPolarAngle=ha.FLOAT(\\\\\\\"-$PI*0.5\\\\\\\",{range:[-Math.PI,Math.PI],rangeLocked:[!0,!0]}),this.maxPolarAngle=ha.FLOAT(\\\\\\\"$PI*0.5\\\\\\\",{range:[-Math.PI,Math.PI],rangeLocked:[!0,!0]})}};class OL extends Jv{constructor(){super(...arguments),this.paramsConfig=LL,this._controls_by_element_id=new Map}static type(){return _s.MOBILE_JOYSTICK}endEventName(){return\\\\\\\"end\\\\\\\"}collisionController(){return this._collisionController=this._collisionController||new $y(this)}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(OL.INPUT_UPDATE_COLLIDER,Ko.BASE,this._updateCollider.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(EL,Ko.BASE),new ta(SL,Ko.BASE),new ta(CL,Ko.BASE)])}async createControlsInstance(t,e){await this._initPlayer(t);const n=new ML(t,e,this._player);return this._controls_by_element_id.set(e.id,n),this._bind_listeners_to_controls_instance(n),n}async _initPlayer(t){this._player=this._player||await this._createPlayer(t),this._player&&(this._updatePlayerParams(),this._player.reset())}player(){return this._player}async _updatePlayerParams(){this._player&&(this._player.startPosition.copy(this.pv.startPosition),this._player.physicsSteps=this.pv.physicsSteps,this._player.jumpAllowed=this.pv.jumpAllowed,this._player.jumpStrength=this.pv.jumpStrength,this._player.runAllowed=this.pv.runAllowed,this._player.runSpeedMult=this.pv.runSpeedMult,this._player.gravity.copy(this.pv.gravity),this._player.speed=this.pv.translateSpeed,this._player.setCapsule({radius:this.pv.capsuleRadius,height:this.pv.capsuleHeight}),this._controls_by_element_id.forEach((t=>t.updateElements())))}async _createPlayer(t){const e=t,n=await this.collisionController().getCollider();if(!n)return void this.states.error.set(\\\\\\\"invalid collider\\\\\\\");return new jy({object:e,collider:n})}_resetPlayer(){var t;null===(t=this._player)||void 0===t||t.reset()}async _updateCollider(){await this.collisionController().updateCollider()}_bind_listeners_to_controls_instance(t){t.addEventListener(EL,(()=>{this.dispatchEventToOutput(EL,{})})),t.addEventListener(SL,(()=>{this.dispatchEventToOutput(SL,{})})),t.addEventListener(CL,(()=>{this.dispatchEventToOutput(CL,{})}))}updateRequired(){return!0}setupControls(t){t.setRotationSpeed(this.pv.rotateSpeed),t.setRotationRange({min:this.pv.minPolarAngle,max:this.pv.maxPolarAngle}),t.updateElements()}disposeControlsForHtmlElementId(t){this._controls_by_element_id.get(t)&&this._controls_by_element_id.delete(t)}static PARAM_CALLBACK_updateCollider(t){t._updateCollider()}static PARAM_CALLBACK_updatePlayerParams(t){t._updatePlayerParams()}static PARAM_CALLBACK_resetPlayer(t){t._resetPlayer()}}var PL;OL.INPUT_UPDATE_COLLIDER=\\\\\\\"updateCollider\\\\\\\",function(t){t.ALL_TOGETHER=\\\\\\\"all together\\\\\\\",t.BATCH=\\\\\\\"batch\\\\\\\"}(PL||(PL={}));const RL=[PL.ALL_TOGETHER,PL.BATCH];const IL=new class extends ua{constructor(){super(...arguments),this.mask=ha.STRING(\\\\\\\"/geo*\\\\\\\",{callback:t=>{FL.PARAM_CALLBACK_updateResolvedNodes(t)}}),this.force=ha.BOOLEAN(0),this.cookMode=ha.INTEGER(RL.indexOf(PL.ALL_TOGETHER),{menu:{entries:RL.map(((t,e)=>({name:t,value:e})))}}),this.batchSize=ha.INTEGER(1,{visibleIf:{cookMode:RL.indexOf(PL.BATCH)},separatorAfter:!0}),this.registerOnlyFirstCooks=ha.BOOLEAN(!0),this.updateResolve=ha.BUTTON(null,{callback:(t,e)=>{FL.PARAM_CALLBACK_updateResolve(t)}}),this.printResolve=ha.BUTTON(null,{callback:(t,e)=>{FL.PARAM_CALLBACK_printResolve(t)}})}};class FL extends Va{constructor(){super(...arguments),this.paramsConfig=IL,this._resolvedNodes=[],this._dispatchedFirstNodeCooked=!1,this._dispatchedAllNodesCooked=!1,this._cookStateByNodeId=new Map}static type(){return\\\\\\\"nodeCook\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(FL.INPUT_TRIGGER,Ko.BASE,this.processEventTrigger.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(FL.OUTPUT_FIRST_NODE,Ko.BASE),new ta(FL.OUTPUT_EACH_NODE,Ko.BASE),new ta(FL.OUTPUT_ALL_NODES,Ko.BASE)])}trigger(){this.processEventTrigger({})}cook(){this._updateResolvedNodes(),this.cookController.endCook()}dispose(){super.dispose(),this._reset()}resolvedNodes(){return this._resolvedNodes}processEventTrigger(t){this._cook_nodes_with_mode()}_cook_nodes_with_mode(){this._updateResolvedNodes();const t=RL[this.pv.cookMode];switch(t){case PL.ALL_TOGETHER:return this._cookNodesAllTogether();case PL.BATCH:return this._cookNodesInBatch()}os.unreachable(t)}_cookNodesAllTogether(){this._cookNodes(this._resolvedNodes)}async _cookNodesInBatch(){const t=this.pv.batchSize,e=Math.ceil(this._resolvedNodes.length/t);for(let n=0;n{this._onNodeCookComplete(t)})),this._cookStateByNodeId.set(t.graphNodeId(),!1)}_callbackNameForNode(t){return`owner-${this.graphNodeId()}-target-${t.graphNodeId()}`}_reset(){this._dispatchedFirstNodeCooked=!1,this._cookStateByNodeId.clear();for(let t of this._resolvedNodes)t.cookController.deregisterOnCookEnd(this._callbackNameForNode(t));this._resolvedNodes=[]}_allNodesHaveCooked(){for(let t of this._resolvedNodes){if(!this._cookStateByNodeId.get(t.graphNodeId()))return!1}return!0}_onNodeCookComplete(t){const e={value:{node:t}};this._dispatchedFirstNodeCooked||(this._dispatchedFirstNodeCooked=!0,this.dispatchEventToOutput(FL.OUTPUT_FIRST_NODE,e));this._cookStateByNodeId.get(t.graphNodeId())&&this.pv.registerOnlyFirstCooks||this.dispatchEventToOutput(FL.OUTPUT_EACH_NODE,e),this._cookStateByNodeId.set(t.graphNodeId(),!0),this._dispatchedAllNodesCooked||this._allNodesHaveCooked()&&(this._dispatchedAllNodesCooked=!0,this.dispatchEventToOutput(FL.OUTPUT_ALL_NODES,{}))}static PARAM_CALLBACK_updateResolve(t){t._allNodesHaveCooked()}static PARAM_CALLBACK_printResolve(t){t.printResolve()}printResolve(){console.log(this._resolvedNodes)}}var DL,BL;FL.INPUT_TRIGGER=\\\\\\\"trigger\\\\\\\",FL.OUTPUT_FIRST_NODE=\\\\\\\"first\\\\\\\",FL.OUTPUT_EACH_NODE=\\\\\\\"each\\\\\\\",FL.OUTPUT_ALL_NODES=\\\\\\\"all\\\\\\\",function(t){t.TRIGGER=\\\\\\\"trigger\\\\\\\"}(DL||(DL={})),function(t){t.OUT=\\\\\\\"out\\\\\\\"}(BL||(BL={}));const zL=new class extends ua{};class kL extends Va{constructor(){super(...arguments),this.paramsConfig=zL}static type(){return\\\\\\\"null\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(DL.TRIGGER,Ko.BASE,this.processEventTrigger.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(BL.OUT,Ko.BASE)])}processEvent(t){}processEventTrigger(t){this.dispatchEventToOutput(BL.OUT,t)}}const UL=\\\\\\\"init\\\\\\\",GL=\\\\\\\"dispose\\\\\\\",VL=\\\\\\\"reset\\\\\\\";function HL(){return{callback:t=>{YL.PARAM_CALLBACK_updatePlayerParams(t)}}}const jL=new p.a,WL=new p.a,qL=new oy;const XL=new class extends ua{constructor(){super(...arguments),this.main=ha.FOLDER(),this.playerObject=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.OBJ}}),this.colliderObject=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.SOP},dependentOnFoundNode:!1,callback:t=>{YL.PARAM_CALLBACK_updateCollider(t)}}),this.camera=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{types:[is.PERSPECTIVE,is.ORTHOGRAPHIC],context:ts.OBJ}}),this.initPlayer=ha.BUTTON(null,{callback:t=>{YL.PARAM_CALLBACK_initPlayer(t)}}),this.capsuleRadius=ha.FLOAT(.5,{range:[0,1],rangeLocked:[!0,!1],...HL()}),this.capsuleHeight=ha.FLOAT(1,{range:[0,2],rangeLocked:[!0,!1],...HL()}),this.physics=ha.FOLDER(),this.physicsSteps=ha.INTEGER(5,{range:[1,10],rangeLocked:[!0,!1],...HL()}),this.gravity=ha.VECTOR3([0,-30,0],{...HL()}),this.speed=ha.FLOAT(1,{range:[0,10],rangeLocked:[!0,!1],...HL()}),this.jumpAllowed=ha.BOOLEAN(!0,{...HL()}),this.jumpStrength=ha.FLOAT(10,{range:[0,100],rangeLocked:[!0,!1],...HL()}),this.runAllowed=ha.BOOLEAN(!0,{...HL()}),this.runSpeedMult=ha.FLOAT(2,{range:[0,10],rangeLocked:[!0,!1],...HL()}),this.updateCollider=ha.BUTTON(null,{callback:t=>{YL.PARAM_CALLBACK_updateCollider(t)}}),this.mesh=ha.FOLDER(),this.useMesh=ha.BOOLEAN(!0,{callback:t=>{YL.PARAM_CALLBACK_updatePlayerMesh(t)}}),this.material=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.MAT},callback:t=>{YL.PARAM_CALLBACK_updatePlayerMaterial(t)}}),this.init=ha.FOLDER(),this.startPosition=ha.VECTOR3([0,5,0],{...HL()}),this.reset=ha.BUTTON(null,{callback:t=>{YL.PARAM_CALLBACK_resetPlayer(t)}})}};class YL extends Va{constructor(){super(...arguments),this.paramsConfig=XL}static type(){return _s.PLAYER}collisionController(){return this._collisionController=this._collisionController||new $y(this)}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(UL,Ko.BASE,this._initPlayer.bind(this)),new ta(GL,Ko.BASE,this._disposePlayer.bind(this)),new ta(VL,Ko.BASE,this._resetPlayer.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(UL,Ko.BASE),new ta(GL,Ko.BASE),new ta(VL,Ko.BASE)])}async _initPlayer(){if(this._player=this._player||await this._createPlayer(),!this._player)return void this.states.error.set(\\\\\\\"could not create player\\\\\\\");this._updatePlayerMesh(),this._updatePlayerMaterial(),this._updatePlayerParams(),this._corePlayerKeyEvents=new qy(this._player),this._corePlayerKeyEvents.addEvents(),this._player.reset();const t=this._player;this.scene().registerOnBeforeTick(this._callbackName(),(e=>{t.setAzimuthalAngle(this._getAzimuthalAngle()),t.update(e)})),this.dispatchEventToOutput(UL,{})}player(){return this._player}_callbackName(){return`event/PlayerControls-${this.graphNodeId()}`}_disposePlayer(){var t;this._player&&(null===(t=this._corePlayerKeyEvents)||void 0===t||t.removeEvents(),this.scene().unRegisterOnBeforeTick(this._callbackName())),this.dispatchEventToOutput(GL,{})}_resetPlayer(){this._player&&this._player.reset(),this.dispatchEventToOutput(VL,{})}async _updatePlayerParams(){this._player&&(this._player.startPosition.copy(this.pv.startPosition),this._player.physicsSteps=this.pv.physicsSteps,this._player.jumpAllowed=this.pv.jumpAllowed,this._player.jumpStrength=this.pv.jumpStrength,this._player.runAllowed=this.pv.runAllowed,this._player.runSpeedMult=this.pv.runSpeedMult,this._player.gravity.copy(this.pv.gravity),this._player.speed=this.pv.speed,this._player.setCapsule({radius:this.pv.capsuleRadius,height:this.pv.capsuleHeight}))}_updatePlayerMesh(){this._player&&this._player.setUsePlayerMesh(this.pv.useMesh)}async _updatePlayerMaterial(){if(!this._player)return;const t=this.pv.material.nodeWithContext(ts.MAT);if(!t)return void this.states.error.set(\\\\\\\"material node not found\\\\\\\");const e=(await t.compute()).material();this._player.setMaterial(e)}async _createPlayer(){const t=this.pv.playerObject.nodeWithContext(ts.OBJ);if(!t)return void this.states.error.set(\\\\\\\"player node not found\\\\\\\");const e=this.pv.camera.nodeWithContext(ts.OBJ);if(!e)return void this.states.error.set(\\\\\\\"invalid camera node\\\\\\\");this._cameraObject=e.object;const n=t.object,i=await this.collisionController().getCollider();if(!i)return void this.states.error.set(\\\\\\\"invalid collider\\\\\\\");return new jy({object:n,collider:i,meshName:this.path()})}async _updateCollider(){await this.collisionController().updateCollider()}_getAzimuthalAngle(){if(!this._cameraObject||!this._player)return 0;const t=this._cameraObject.position,e=this._player.object.position;return jL.copy(t),WL.copy(e),jL.sub(WL),qL.setFromVector3(jL),qL.theta}static PARAM_CALLBACK_initPlayer(t){t._initPlayer()}static PARAM_CALLBACK_updatePlayerParams(t){t._updatePlayerParams()}static PARAM_CALLBACK_updatePlayerMaterial(t){t._updatePlayerMaterial()}static PARAM_CALLBACK_updatePlayerMesh(t){t._updatePlayerMesh()}static PARAM_CALLBACK_updateCollider(t){t._updateCollider()}static PARAM_CALLBACK_resetPlayer(t){t._resetPlayer()}}var $L,JL=n(39),ZL=n(36);class QL{constructor(t,e,n=0,i=1/0){this.ray=new JL.a(t,e),this.near=n,this.far=i,this.camera=null,this.layers=new ZL.a,this.params={Mesh:{},Line:{threshold:1},LOD:{},Points:{threshold:1},Sprite:{}}}set(t,e){this.ray.set(t,e)}setFromCamera(t,e){e&&e.isPerspectiveCamera?(this.ray.origin.setFromMatrixPosition(e.matrixWorld),this.ray.direction.set(t.x,t.y,.5).unproject(e).sub(this.ray.origin).normalize(),this.camera=e):e&&e.isOrthographicCamera?(this.ray.origin.set(t.x,t.y,(e.near+e.far)/(e.near-e.far)).unproject(e),this.ray.direction.set(0,0,-1).transformDirection(e.matrixWorld),this.camera=e):console.error(\\\\\\\"THREE.Raycaster: Unsupported camera type: \\\\\\\"+e.type)}intersectObject(t,e=!0,n=[]){return tO(t,this,n,e),n.sort(KL),n}intersectObjects(t,e=!0,n=[]){for(let i=0,s=t.length;i{this._mouse.x=t.offsetX/n.offsetWidth*2-1,this._mouse.y=-t.offsetY/n.offsetHeight*2+1,this._mouse.toArray(this._mouse_array),this._node.p.mouse.set(this._mouse_array)})(this._offset),this._raycaster.setFromCamera(this._mouse,i.object)}processEvent(t){this._prepareRaycaster(t);const e=iO[this._node.pv.intersectWith];switch(e){case nO.GEOMETRY:return this._intersect_with_geometry(t);case nO.PLANE:return this._intersect_with_plane(t)}os.unreachable(e)}_intersect_with_plane(t){this._plane.normal.copy(this._node.pv.planeDirection),this._plane.constant=this._node.pv.planeOffset,this._raycaster.ray.intersectPlane(this._plane,this._plane_intersect_target),this._set_position_param(this._plane_intersect_target),this._node.trigger_hit(t)}_intersect_with_geometry(t){if(this._resolved_targets||this.update_target(),this._resolved_targets){this._intersections.length=0;const e=this._raycaster.intersectObjects(this._resolved_targets,this._node.pv.traverseChildren,this._intersections)[0];e?(this._set_position_param(e.point),this._node.pv.geoAttribute&&this._resolve_geometry_attribute(e),t.value={intersect:e},this._node.trigger_hit(t)):this._node.trigger_miss(t)}}_resolve_geometry_attribute(t){const e=ks[this._node.pv.geoAttributeType],n=rO.resolve_geometry_attribute(t,this._node.pv.geoAttributeName,e);if(null!=n){switch(e){case zs.NUMERIC:return void this._node.p.geoAttributeValue1.set(n);case zs.STRING:return void(m.isString(n)&&this._node.p.geoAttributeValues.set(n))}os.unreachable(e)}}static resolve_geometry_attribute(t,e,n){switch(Os(t.object.constructor)){case Ns.MESH:return this.resolve_geometry_attribute_for_mesh(t,e,n);case Ns.POINTS:return this.resolve_geometry_attribute_for_point(t,e,n)}}static resolve_geometry_attribute_for_mesh(t,e,n){const i=t.object.geometry;if(i){const s=i.getAttribute(e);if(s){switch(n){case zs.NUMERIC:{const e=i.getAttribute(\\\\\\\"position\\\\\\\");return t.face?(this._vA.fromBufferAttribute(e,t.face.a),this._vB.fromBufferAttribute(e,t.face.b),this._vC.fromBufferAttribute(e,t.face.c),this._uvA.fromBufferAttribute(s,t.face.a),this._uvB.fromBufferAttribute(s,t.face.b),this._uvC.fromBufferAttribute(s,t.face.c),t.uv=tr.a.getUV(t.point,this._vA,this._vB,this._vC,this._uvA,this._uvB,this._uvC,this._hitUV),this._hitUV.x):void 0}case zs.STRING:{const t=new fr(i).points()[0];return t?t.stringAttribValue(e):void 0}}os.unreachable(n)}}}static resolve_geometry_attribute_for_point(t,e,n){const i=t.object.geometry;if(i&&null!=t.index){switch(n){case zs.NUMERIC:{const n=i.getAttribute(e);return n?n.array[t.index]:void 0}case zs.STRING:{const n=new fr(i).points()[t.index];return n?n.stringAttribValue(e):void 0}}os.unreachable(n)}}_set_position_param(t){if(t.toArray(this._hit_position_array),this._node.pv.tpositionTarget){if(li.playerMode())this._found_position_target_param=this._found_position_target_param||this._node.pv.positionTarget.paramWithType(Cr.VECTOR3);else{const t=this._node.pv.positionTarget;this._found_position_target_param=t.paramWithType(Cr.VECTOR3)}this._found_position_target_param&&this._found_position_target_param.set(this._hit_position_array)}else this._node.p.position.set(this._hit_position_array);this.velocity_controller.process(t)}_prepareRaycaster(t){const e=this._raycaster.params.Points;e&&(e.threshold=this._node.pv.pointsThreshold);let n=t.cameraNode;if(this._node.pv.overrideCamera)if(this._node.pv.overrideRay)this._raycaster.ray.origin.copy(this._node.pv.rayOrigin),this._raycaster.ray.direction.copy(this._node.pv.rayDirection);else{const t=this._node.p.camera.found_node_with_context(ts.OBJ);t&&(n=t)}n&&!this._node.pv.overrideRay&&n.prepareRaycaster(this._mouse,this._raycaster)}update_target(){const t=mO[this._node.pv.targetType];switch(t){case _O.NODE:return this._update_target_from_node();case _O.SCENE_GRAPH:return this._update_target_from_scene_graph()}os.unreachable(t)}_update_target_from_node(){const t=this._node.p.targetNode.value.nodeWithContext(ts.OBJ);if(t){const e=this._node.pv.traverseChildren?t.object:t.childrenDisplayController.sopGroup();this._resolved_targets=e?[e]:void 0}else this._node.states.error.set(\\\\\\\"node is not an object\\\\\\\")}_update_target_from_scene_graph(){const t=this._node.scene().objectsByMask(this._node.pv.objectMask);t.length>0?this._resolved_targets=t:this._resolved_targets=void 0}async update_position_target(){this._node.p.positionTarget.isDirty()&&await this._node.p.positionTarget.compute()}static PARAM_CALLBACK_update_target(t){t.cpuController.update_target()}static PARAM_CALLBACK_print_resolve(t){t.cpuController.print_resolve()}print_resolve(){this.update_target(),console.log(this._resolved_targets)}}rO._vA=new p.a,rO._vB=new p.a,rO._vC=new p.a,rO._uvA=new d.a,rO._uvB=new d.a,rO._uvC=new d.a,rO._hitUV=new d.a;class oO{constructor(t){this._node=t,this._resolved_material=null,this._restore_context={scene:{overrideMaterial:null},renderer:{toneMapping:-1,outputEncoding:-1}},this._mouse=new d.a,this._mouse_array=[0,0],this._read=new Float32Array(4),this._param_read=[0,0,0,0]}updateMouse(t){var e;const n=null===(e=t.viewer)||void 0===e?void 0:e.canvas();n&&t.event&&(t.event instanceof MouseEvent||t.event instanceof DragEvent||t.event instanceof PointerEvent?(this._mouse.x=t.event.offsetX/n.offsetWidth,this._mouse.y=1-t.event.offsetY/n.offsetHeight,this._mouse.toArray(this._mouse_array),this._node.p.mouse.set(this._mouse_array)):console.warn(\\\\\\\"event type not implemented\\\\\\\"))}processEvent(t){var e;const n=null===(e=t.viewer)||void 0===e?void 0:e.canvas();if(!n||!t.cameraNode)return;const i=t.cameraNode,s=i.renderController;if(s){if(this._render_target=this._render_target||new Q(n.offsetWidth,n.offsetHeight,{minFilter:w.V,magFilter:w.ob,format:w.Ib,type:w.G}),!this._resolved_material)return this.update_material(),void console.warn(\\\\\\\"no material found\\\\\\\");const e=i,r=s.resolved_scene||i.scene().threejsScene(),o=s.renderer(n);this._modify_scene_and_renderer(r,o),o.setRenderTarget(this._render_target),o.clear(),o.render(r,e.object),o.setRenderTarget(null),this._restore_scene_and_renderer(r,o),o.readRenderTargetPixels(this._render_target,Math.round(this._mouse.x*n.offsetWidth),Math.round(this._mouse.y*n.offsetHeight),1,1,this._read),this._param_read[0]=this._read[0],this._param_read[1]=this._read[1],this._param_read[2]=this._read[2],this._param_read[3]=this._read[3],this._node.p.pixelValue.set(this._param_read),this._node.pv.pixelValue.x>this._node.pv.hitThreshold?this._node.trigger_hit(t):this._node.trigger_miss(t)}}_modify_scene_and_renderer(t,e){this._restore_context.scene.overrideMaterial=t.overrideMaterial,this._restore_context.renderer.outputEncoding=e.outputEncoding,this._restore_context.renderer.toneMapping=e.toneMapping,t.overrideMaterial=this._resolved_material,e.toneMapping=w.vb,e.outputEncoding=w.U}_restore_scene_and_renderer(t,e){t.overrideMaterial=this._restore_context.scene.overrideMaterial,e.outputEncoding=this._restore_context.renderer.outputEncoding,e.toneMapping=this._restore_context.renderer.toneMapping}update_material(){const t=this._node.p.material.found_node();t?t.context()==ts.MAT?this._resolved_material=t.material:this._node.states.error.set(\\\\\\\"target is not an obj\\\\\\\"):this._node.states.error.set(\\\\\\\"no target found\\\\\\\")}static PARAM_CALLBACK_update_material(t){t.gpuController.update_material()}}const aO=1e3/60;var lO;!function(t){t.CPU=\\\\\\\"cpu\\\\\\\",t.GPU=\\\\\\\"gpu\\\\\\\"}(lO||(lO={}));const cO=[lO.CPU,lO.GPU];function hO(t={}){return t.mode=cO.indexOf(lO.CPU),{visibleIf:t}}function uO(t={}){return t.mode=cO.indexOf(lO.CPU),t.intersectWith=iO.indexOf(nO.GEOMETRY),{visibleIf:t}}function dO(t={}){return t.mode=cO.indexOf(lO.CPU),t.intersectWith=iO.indexOf(nO.PLANE),{visibleIf:t}}function pO(t={}){return t.mode=cO.indexOf(lO.GPU),{visibleIf:t}}var _O;!function(t){t.SCENE_GRAPH=\\\\\\\"scene graph\\\\\\\",t.NODE=\\\\\\\"node\\\\\\\"}(_O||(_O={}));const mO=[_O.SCENE_GRAPH,_O.NODE];const fO=new class extends ua{constructor(){super(...arguments),this.mode=ha.INTEGER(cO.indexOf(lO.CPU),{menu:{entries:cO.map(((t,e)=>({name:t,value:e})))}}),this.mouse=ha.VECTOR2([0,0],{cook:!1}),this.overrideCamera=ha.BOOLEAN(0),this.overrideRay=ha.BOOLEAN(0,{visibleIf:{mode:cO.indexOf(lO.CPU),overrideCamera:1}}),this.camera=ha.OPERATOR_PATH(\\\\\\\"/perspective_camera1\\\\\\\",{nodeSelection:{context:ts.OBJ},dependentOnFoundNode:!1,visibleIf:{overrideCamera:1,overrideRay:0}}),this.rayOrigin=ha.VECTOR3([0,0,0],{visibleIf:{overrideCamera:1,overrideRay:1}}),this.rayDirection=ha.VECTOR3([0,0,1],{visibleIf:{overrideCamera:1,overrideRay:1}}),this.material=ha.OPERATOR_PATH(\\\\\\\"/MAT/mesh_basic_builder1\\\\\\\",{nodeSelection:{context:ts.MAT},dependentOnFoundNode:!1,callback:(t,e)=>{oO.PARAM_CALLBACK_update_material(t)},...pO()}),this.pixelValue=ha.VECTOR4([0,0,0,0],{cook:!1,...pO()}),this.hitThreshold=ha.FLOAT(.5,{cook:!1,...pO()}),this.intersectWith=ha.INTEGER(iO.indexOf(nO.GEOMETRY),{menu:{entries:iO.map(((t,e)=>({name:t,value:e})))},...hO()}),this.pointsThreshold=ha.FLOAT(1,{range:[0,100],rangeLocked:[!0,!1],...hO()}),this.planeDirection=ha.VECTOR3([0,1,0],{...dO()}),this.planeOffset=ha.FLOAT(0,{...dO()}),this.targetType=ha.INTEGER(0,{menu:{entries:mO.map(((t,e)=>({name:t,value:e})))},...uO()}),this.targetNode=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.OBJ},dependentOnFoundNode:!1,callback:(t,e)=>{rO.PARAM_CALLBACK_update_target(t)},...uO({targetType:mO.indexOf(_O.NODE)})}),this.objectMask=ha.STRING(\\\\\\\"*geo1*\\\\\\\",{callback:(t,e)=>{rO.PARAM_CALLBACK_update_target(t)},...uO({targetType:mO.indexOf(_O.SCENE_GRAPH)})}),this.printFoundObjectsFromMask=ha.BUTTON(null,{callback:(t,e)=>{rO.PARAM_CALLBACK_print_resolve(t)},...uO({targetType:mO.indexOf(_O.SCENE_GRAPH)})}),this.traverseChildren=ha.BOOLEAN(!0,{callback:(t,e)=>{rO.PARAM_CALLBACK_update_target(t)},...uO(),separatorAfter:!0}),this.tpositionTarget=ha.BOOLEAN(0,{cook:!1,...hO()}),this.position=ha.VECTOR3([0,0,0],{cook:!1,...hO({tpositionTarget:0})}),this.positionTarget=ha.PARAM_PATH(\\\\\\\"\\\\\\\",{cook:!1,...hO({tpositionTarget:1}),paramSelection:Cr.VECTOR3,computeOnDirty:!0}),this.tvelocity=ha.BOOLEAN(0,{cook:!1}),this.tvelocityTarget=ha.BOOLEAN(0,{cook:!1,...hO({tvelocity:1})}),this.velocity=ha.VECTOR3([0,0,0],{cook:!1,...hO({tvelocity:1,tvelocityTarget:0})}),this.velocityTarget=ha.PARAM_PATH(\\\\\\\"\\\\\\\",{cook:!1,...hO({tvelocity:1,tvelocityTarget:1}),paramSelection:Cr.VECTOR3,computeOnDirty:!0}),this.geoAttribute=ha.BOOLEAN(0,uO()),this.geoAttributeName=ha.STRING(\\\\\\\"id\\\\\\\",{cook:!1,...uO({geoAttribute:1})}),this.geoAttributeType=ha.INTEGER(ks.indexOf(zs.NUMERIC),{menu:{entries:Us},...uO({geoAttribute:1})}),this.geoAttributeValue1=ha.FLOAT(0,{cook:!1,...uO({geoAttribute:1,geoAttributeType:ks.indexOf(zs.NUMERIC)})}),this.geoAttributeValues=ha.STRING(\\\\\\\"\\\\\\\",{...uO({geoAttribute:1,geoAttributeType:ks.indexOf(zs.STRING)})})}};class gO extends Va{constructor(){super(...arguments),this.paramsConfig=fO,this.cpuController=new rO(this),this.gpuController=new oO(this),this._last_event_processed_at=-1}static type(){return\\\\\\\"raycast\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(gO.INPUT_TRIGGER,Ko.BASE,this._process_trigger_event_throttled.bind(this)),new ta(gO.INPUT_MOUSE,Ko.MOUSE,this._process_mouse_event.bind(this)),new ta(gO.INPUT_UPDATE_OBJECTS,Ko.BASE,this._process_trigger_update_objects.bind(this)),new ta(gO.INPUT_TRIGGER_VEL_RESET,Ko.BASE,this._process_trigger_vel_reset.bind(this))]),this.io.outputs.setNamedOutputConnectionPoints([new ta(gO.OUTPUT_HIT,Ko.BASE),new ta(gO.OUTPUT_MISS,Ko.BASE)])}trigger_hit(t){this.dispatchEventToOutput(gO.OUTPUT_HIT,t)}trigger_miss(t){this.dispatchEventToOutput(gO.OUTPUT_MISS,t)}_process_mouse_event(t){this.pv.mode==cO.indexOf(lO.CPU)?this.cpuController.updateMouse(t):this.gpuController.updateMouse(t)}_process_trigger_event_throttled(t){const e=this._last_event_processed_at,n=li.performance.performanceManager().now();this._last_event_processed_at=n;const i=n-e;i{this._process_trigger_event(t)}),aO-i):this._process_trigger_event(t)}_process_trigger_event(t){this.pv.mode==cO.indexOf(lO.CPU)?this.cpuController.processEvent(t):this.gpuController.processEvent(t)}_process_trigger_update_objects(t){this.pv.mode==cO.indexOf(lO.CPU)&&this.cpuController.update_target()}_process_trigger_vel_reset(t){this.pv.mode==cO.indexOf(lO.CPU)&&this.cpuController.velocity_controller.reset()}}var vO;gO.INPUT_TRIGGER=\\\\\\\"trigger\\\\\\\",gO.INPUT_MOUSE=\\\\\\\"mouse\\\\\\\",gO.INPUT_UPDATE_OBJECTS=\\\\\\\"updateObjects\\\\\\\",gO.INPUT_TRIGGER_VEL_RESET=\\\\\\\"triggerVelReset\\\\\\\",gO.OUTPUT_HIT=\\\\\\\"hit\\\\\\\",gO.OUTPUT_MISS=\\\\\\\"miss\\\\\\\",function(t){t.SET=\\\\\\\"set\\\\\\\",t.TOGGLE=\\\\\\\"toggle\\\\\\\"}(vO||(vO={}));const yO=[vO.SET,vO.TOGGLE];const xO=new class extends ua{constructor(){super(...arguments),this.mask=ha.STRING(\\\\\\\"/geo*\\\\\\\",{separatorAfter:!0}),this.tdisplay=ha.BOOLEAN(0),this.displayMode=ha.INTEGER(yO.indexOf(vO.SET),{visibleIf:{tdisplay:1},menu:{entries:yO.map(((t,e)=>({name:t,value:e})))}}),this.display=ha.BOOLEAN(0,{visibleIf:{tdisplay:1,displayMode:yO.indexOf(vO.SET)},separatorAfter:!0}),this.tbypass=ha.BOOLEAN(0),this.bypassMode=ha.INTEGER(yO.indexOf(vO.SET),{visibleIf:{tbypass:1},menu:{entries:yO.map(((t,e)=>({name:t,value:e})))}}),this.bypass=ha.BOOLEAN(0,{visibleIf:{tbypass:1,displayMode:yO.indexOf(vO.SET)}}),this.execute=ha.BUTTON(null,{callback:t=>{bO.PARAM_CALLBACK_execute(t)}})}};class bO extends Va{constructor(){super(...arguments),this.paramsConfig=xO}static type(){return\\\\\\\"setFlag\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(\\\\\\\"trigger\\\\\\\",Ko.BASE)])}async processEvent(t){let e=this.pv.mask;if(t.value){const n=t.value.node;if(n){const t=n.parent();t&&(e=`${t.path()}/${e}`)}}const n=this.scene().nodesController.nodesFromMask(e);for(let t of n)this._update_node_flags(t)}_update_node_flags(t){this._update_node_display_flag(t),this._update_node_bypass_flag(t)}_update_node_display_flag(t){var e;if(!this.pv.tdisplay)return;if(!(null===(e=t.flags)||void 0===e?void 0:e.hasDisplay()))return;const n=t.flags.display;if(!n)return;const i=yO[this.pv.displayMode];switch(i){case vO.SET:return void n.set(this.pv.display);case vO.TOGGLE:return void n.set(!n.active())}os.unreachable(i)}_update_node_bypass_flag(t){var e;if(!this.pv.tbypass)return;if(!(null===(e=t.flags)||void 0===e?void 0:e.hasBypass()))return;const n=t.flags.bypass;if(!n)return;const i=yO[this.pv.bypassMode];switch(i){case vO.SET:return void n.set(this.pv.bypass);case vO.TOGGLE:return void n.set(!n.active())}os.unreachable(i)}static PARAM_CALLBACK_execute(t){t.processEvent({})}}var wO;!function(t){t.BOOLEAN=\\\\\\\"boolean\\\\\\\",t.BUTTON=\\\\\\\"button\\\\\\\",t.NUMBER=\\\\\\\"number\\\\\\\",t.VECTOR2=\\\\\\\"vector2\\\\\\\",t.VECTOR3=\\\\\\\"vector3\\\\\\\",t.VECTOR4=\\\\\\\"vector4\\\\\\\",t.STRING=\\\\\\\"string\\\\\\\"}(wO||(wO={}));const TO=[wO.BOOLEAN,wO.BUTTON,wO.NUMBER,wO.VECTOR2,wO.VECTOR3,wO.VECTOR4,wO.STRING],AO=TO.indexOf(wO.BOOLEAN),MO=TO.indexOf(wO.NUMBER),EO=TO.indexOf(wO.VECTOR2),SO=TO.indexOf(wO.VECTOR3),CO=TO.indexOf(wO.VECTOR4),NO=TO.indexOf(wO.STRING),LO=\\\\\\\"output\\\\\\\";const OO=new class extends ua{constructor(){super(...arguments),this.param=ha.PARAM_PATH(\\\\\\\"\\\\\\\",{paramSelection:!0,computeOnDirty:!0}),this.type=ha.INTEGER(MO,{menu:{entries:TO.map(((t,e)=>({name:t,value:e})))}}),this.toggle=ha.BOOLEAN(0,{visibleIf:{type:AO}}),this.boolean=ha.BOOLEAN(0,{visibleIf:{type:AO,toggle:0}}),this.number=ha.FLOAT(0,{visibleIf:{type:MO}}),this.vector2=ha.VECTOR2([0,0],{visibleIf:{type:EO}}),this.vector3=ha.VECTOR3([0,0,0],{visibleIf:{type:SO}}),this.vector4=ha.VECTOR4([0,0,0,0],{visibleIf:{type:CO}}),this.increment=ha.BOOLEAN(0,{visibleIf:[{type:MO},{type:EO},{type:SO},{type:CO}]}),this.string=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{type:NO}}),this.execute=ha.BUTTON(null,{callback:t=>{PO.PARAM_CALLBACK_execute(t)}})}};class PO extends Va{constructor(){super(...arguments),this.paramsConfig=OO,this._tmp_vector2=new d.a,this._tmp_vector3=new p.a,this._tmp_vector4=new _.a,this._tmp_array2=[0,0],this._tmp_array3=[0,0,0],this._tmp_array4=[0,0,0,0]}static type(){return\\\\\\\"setParam\\\\\\\"}initializeNode(){this.io.inputs.setNamedInputConnectionPoints([new ta(\\\\\\\"trigger\\\\\\\",Ko.BASE)]),this.io.outputs.setNamedOutputConnectionPoints([new ta(LO,Ko.BASE)]),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.param])}))}))}async processEvent(t){this.p.param.isDirty()&&await this.p.param.compute();const e=this.p.param.value.param();if(e){const t=await this._new_param_value(e);null!=t&&e.set(t)}else this.states.error.set(\\\\\\\"target param not found\\\\\\\");this.dispatchEventToOutput(LO,t)}async _new_param_value(t){const e=TO[this.pv.type];switch(e){case wO.BOOLEAN:return await this._compute_params_if_dirty([this.p.toggle]),this.pv.toggle?t.value?0:1:this.pv.boolean?1:0;case wO.BUTTON:return t.options.executeCallback();case wO.NUMBER:return await this._compute_params_if_dirty([this.p.increment,this.p.number]),this.pv.increment?t.type()==Cr.FLOAT?t.value+this.pv.number:t.value:this.pv.number;case wO.VECTOR2:return await this._compute_params_if_dirty([this.p.increment,this.p.vector2]),this.pv.increment?t.type()==Cr.VECTOR2?(this._tmp_vector2.copy(t.value),this._tmp_vector2.add(this.pv.vector2),this._tmp_vector2.toArray(this._tmp_array2)):t.value.toArray(this._tmp_array2):this.pv.vector2.toArray(this._tmp_array2),this._tmp_array2;case wO.VECTOR3:return await this._compute_params_if_dirty([this.p.increment,this.p.vector3]),this.pv.increment?t.type()==Cr.VECTOR3?(this._tmp_vector3.copy(t.value),this._tmp_vector3.add(this.pv.vector3),this._tmp_vector3.toArray(this._tmp_array3)):t.value.toArray(this._tmp_array3):this.pv.vector3.toArray(this._tmp_array3),this._tmp_array3;case wO.VECTOR4:return await this._compute_params_if_dirty([this.p.increment,this.p.vector4]),this.pv.increment?t.type()==Cr.VECTOR4?(this._tmp_vector4.copy(t.value),this._tmp_vector4.add(this.pv.vector4),this._tmp_vector4.toArray(this._tmp_array4)):t.value.toArray(this._tmp_array4):this.pv.vector4.toArray(this._tmp_array4),this._tmp_array4;case wO.STRING:return await this._compute_params_if_dirty([this.p.string]),this.pv.string}os.unreachable(e)}static PARAM_CALLBACK_execute(t){t.processEvent({})}async _compute_params_if_dirty(t){const e=[];for(let n of t)n.isDirty()&&e.push(n);const n=[];for(let t of e)n.push(t.compute());return await Promise.all(n)}}const RO=new class extends ua{constructor(){super(...arguments),this.outputsCount=ha.INTEGER(5,{range:[1,10],rangeLocked:[!0,!1]})}};class IO extends Va{constructor(){super(...arguments),this.paramsConfig=RO}static type(){return\\\\\\\"sequence\\\\\\\"}initializeNode(){this.io.connection_points.set_input_name_function((()=>\\\\\\\"trigger\\\\\\\")),this.io.connection_points.set_expected_input_types_function((()=>[Ko.BASE])),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this)),this.io.connection_points.set_output_name_function(this._output_name.bind(this))}_expected_output_types(){const t=new Array(this.pv.outputsCount);return t.fill(Ko.BASE),t}_output_name(t){return`out${t}`}processEvent(t){const e=this.pv.outputsCount;for(let n=0;n{this._timer_active&&(this.pv.count<=0||this._current_count{var e;null===(e=t.controlsController)||void 0===e||e.create_controls()}))}_process_trigger_disposeControls(t){this.scene().viewersRegister.traverseViewers((t=>{var e;null===(e=t.controlsController)||void 0===e||e.dispose_controls()}))}}class UO extends aa{static context(){return ts.EVENT}cook(){this.cookController.endCook()}}class GO extends UO{}class VO extends GO{constructor(){super(...arguments),this._children_controller_context=ts.ANIM}static type(){return es.ANIM}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class HO extends GO{constructor(){super(...arguments),this._children_controller_context=ts.COP}static type(){return es.COP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class jO extends GO{constructor(){super(...arguments),this._children_controller_context=ts.EVENT}static type(){return es.EVENT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class WO extends GO{constructor(){super(...arguments),this._children_controller_context=ts.MAT}static type(){return es.MAT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class qO extends UO{constructor(){super(...arguments),this.paramsConfig=new ef,this.effectsComposerController=new nf(this),this.displayNodeController=new Fm(this,this.effectsComposerController.displayNodeControllerCallbacks()),this._children_controller_context=ts.POST}static type(){return es.POST}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class XO extends GO{constructor(){super(...arguments),this._children_controller_context=ts.ROP}static type(){return es.ROP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}const YO=\\\\\\\"int\\\\\\\";const $O=new class extends ua{constructor(){super(...arguments),this.float=ha.FLOAT(0)}};class JO extends gf{constructor(){super(...arguments),this.paramsConfig=$O}static type(){return\\\\\\\"floatToInt\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(YO,Uo.INT)])}setLines(t){const e=this.variableForInputParam(this.p.float),n=`int ${this.glVarName(YO)} = int(${mf.float(e)})`;t.addBodyLines(this,[n])}}const ZO=\\\\\\\"float\\\\\\\";const QO=new class extends ua{constructor(){super(...arguments),this.int=ha.INTEGER(0)}};class KO extends gf{constructor(){super(...arguments),this.paramsConfig=QO}static type(){return\\\\\\\"intToFloat\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(ZO,Uo.FLOAT)])}setLines(t){const e=this.variableForInputParam(this.p.int),n=`float ${this.glVarName(ZO)} = float(${mf.integer(e)})`;t.addBodyLines(this,[n])}}const tP=\\\\\\\"bool\\\\\\\";const eP=new class extends ua{constructor(){super(...arguments),this.int=ha.INTEGER(0)}};class nP extends gf{constructor(){super(...arguments),this.paramsConfig=eP}static type(){return\\\\\\\"intToBool\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(tP,Uo.BOOL)])}setLines(t){const e=this.variableForInputParam(this.p.int),n=`bool ${this.glVarName(tP)} = bool(${mf.integer(e)})`;t.addBodyLines(this,[n])}}const iP=new class extends ua{constructor(){super(...arguments),this.bool=ha.BOOLEAN(0)}};class sP extends gf{constructor(){super(...arguments),this.paramsConfig=iP}static type(){return\\\\\\\"boolToInt\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(YO,Uo.INT)])}setLines(t){const e=this.variableForInputParam(this.p.bool),n=`int ${this.glVarName(YO)} = int(${mf.bool(e)})`;t.addBodyLines(this,[n])}}const rP=new class extends ua{constructor(){super(...arguments),this.x=ha.FLOAT(0),this.y=ha.FLOAT(0)}};class oP extends gf{constructor(){super(...arguments),this.paramsConfig=rP}static type(){return\\\\\\\"floatToVec2\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(oP.OUTPUT_NAME,Uo.VEC2)])}setLines(t){const e=this.variableForInputParam(this.p.x),n=this.variableForInputParam(this.p.y),i=`vec2 ${this.glVarName(oP.OUTPUT_NAME)} = ${mf.float2(e,n)}`;t.addBodyLines(this,[i])}}oP.OUTPUT_NAME=\\\\\\\"vec2\\\\\\\";const aP=new class extends ua{constructor(){super(...arguments),this.x=ha.FLOAT(0),this.y=ha.FLOAT(0),this.z=ha.FLOAT(0)}};class lP extends gf{constructor(){super(...arguments),this.paramsConfig=aP}static type(){return\\\\\\\"floatToVec3\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(lP.OUTPUT_NAME,Uo.VEC3)])}setLines(t){const e=this.variableForInputParam(this.p.x),n=this.variableForInputParam(this.p.y),i=this.variableForInputParam(this.p.z),s=`vec3 ${this.glVarName(lP.OUTPUT_NAME)} = ${mf.float3(e,n,i)}`;t.addBodyLines(this,[s])}}lP.OUTPUT_NAME=\\\\\\\"vec3\\\\\\\";const cP=new class extends ua{constructor(){super(...arguments),this.x=ha.FLOAT(0),this.y=ha.FLOAT(0),this.z=ha.FLOAT(0),this.w=ha.FLOAT(0)}};class hP extends gf{constructor(){super(...arguments),this.paramsConfig=cP}static type(){return\\\\\\\"floatToVec4\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(hP.OUTPUT_NAME,Uo.VEC4)])}setLines(t){const e=this.variableForInputParam(this.p.x),n=this.variableForInputParam(this.p.y),i=this.variableForInputParam(this.p.z),s=this.variableForInputParam(this.p.w),r=`vec4 ${this.glVarName(hP.OUTPUT_NAME)} = ${mf.float4(e,n,i,s)}`;t.addBodyLines(this,[r])}}hP.OUTPUT_NAME=\\\\\\\"vec4\\\\\\\";const uP=new class extends ua{};class dP extends gf{constructor(){super(...arguments),this.paramsConfig=uP}}function pP(t,e){const n=e.components,i=e.param_type;return class extends dP{static type(){return t}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints(n.map((t=>new qo(t,Uo.FLOAT))))}createParams(){this.addParam(i,\\\\\\\"vec\\\\\\\",n.map((t=>0)))}setLines(t){const e=[],n=this.variableForInput(\\\\\\\"vec\\\\\\\");this.io.outputs.used_output_names().forEach((t=>{const i=this.glVarName(t);e.push(`float ${i} = ${n}.${t}`)})),t.addBodyLines(this,e)}}}const _P=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\"],mP=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\"],fP=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\",\\\\\\\"w\\\\\\\"];class gP extends(pP(\\\\\\\"vec2ToFloat\\\\\\\",{components:[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\"],param_type:Cr.VECTOR2})){}class vP extends(pP(\\\\\\\"vec3ToFloat\\\\\\\",{components:[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\"],param_type:Cr.VECTOR3})){}class yP extends(pP(\\\\\\\"vec4ToFloat\\\\\\\",{components:fP,param_type:Cr.VECTOR4})){}class xP extends dP{static type(){return\\\\\\\"vec4ToVec3\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(xP.OUTPUT_NAME_VEC3,Uo.VEC3),new qo(xP.OUTPUT_NAME_W,Uo.FLOAT)])}createParams(){this.addParam(Cr.VECTOR4,xP.INPUT_NAME_VEC4,fP.map((t=>0)))}setLines(t){const e=[],n=xP.INPUT_NAME_VEC4,i=xP.OUTPUT_NAME_VEC3,s=xP.OUTPUT_NAME_W,r=this.variableForInput(n),o=this.io.outputs.used_output_names();if(o.indexOf(i)>=0){const t=this.glVarName(i);e.push(`vec3 ${t} = ${r}.xyz`)}if(o.indexOf(s)>=0){const t=this.glVarName(s);e.push(`float ${t} = ${r}.w`)}t.addBodyLines(this,e)}}xP.INPUT_NAME_VEC4=\\\\\\\"vec4\\\\\\\",xP.OUTPUT_NAME_VEC3=\\\\\\\"vec3\\\\\\\",xP.OUTPUT_NAME_W=\\\\\\\"w\\\\\\\";class bP extends dP{static type(){return\\\\\\\"vec3ToVec2\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(bP.OUTPUT_NAME_VEC2,Uo.VEC2),new qo(bP.OUTPUT_NAME_Z,Uo.FLOAT)])}createParams(){this.addParam(Cr.VECTOR3,bP.INPUT_NAME_VEC3,mP.map((t=>0)))}setLines(t){const e=[],n=bP.INPUT_NAME_VEC3,i=bP.OUTPUT_NAME_VEC2,s=bP.OUTPUT_NAME_Z,r=this.variableForInput(n),o=this.io.outputs.used_output_names();if(o.indexOf(i)>=0){const t=this.glVarName(i);e.push(`vec2 ${t} = ${r}.xy`)}if(o.indexOf(s)>=0){const t=this.glVarName(s);e.push(`float ${t} = ${r}.z`)}t.addBodyLines(this,e)}}bP.INPUT_NAME_VEC3=\\\\\\\"vec3\\\\\\\",bP.OUTPUT_NAME_VEC2=\\\\\\\"vec2\\\\\\\",bP.OUTPUT_NAME_Z=\\\\\\\"z\\\\\\\";class wP extends dP{static type(){return\\\\\\\"vec2ToVec3\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(wP.OUTPUT_NAME_VEC3,Uo.VEC3)])}createParams(){this.addParam(Cr.VECTOR2,wP.INPUT_NAME_VEC2,_P.map((t=>0))),this.addParam(Cr.FLOAT,wP.INPUT_NAME_Z,0)}setLines(t){const e=[],n=wP.INPUT_NAME_VEC2,i=wP.INPUT_NAME_Z,s=wP.OUTPUT_NAME_VEC3,r=this.variableForInput(n),o=this.variableForInput(i),a=this.glVarName(s);e.push(`vec3 ${a} = vec3(${r}.xy, ${o})`),t.addBodyLines(this,e)}}wP.INPUT_NAME_VEC2=\\\\\\\"vec3\\\\\\\",wP.INPUT_NAME_Z=\\\\\\\"z\\\\\\\",wP.OUTPUT_NAME_VEC3=\\\\\\\"vec3\\\\\\\";class TP extends dP{static type(){return\\\\\\\"vec3ToVec4\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(TP.OUTPUT_NAME_VEC4,Uo.VEC4)])}createParams(){this.addParam(Cr.VECTOR3,TP.INPUT_NAME_VEC3,mP.map((t=>0))),this.addParam(Cr.FLOAT,TP.INPUT_NAME_W,0)}setLines(t){const e=[],n=TP.INPUT_NAME_VEC3,i=TP.INPUT_NAME_W,s=TP.OUTPUT_NAME_VEC4,r=this.variableForInput(n),o=this.variableForInput(i),a=this.glVarName(s);e.push(`vec4 ${a} = vec4(${r}.xyz, ${o})`),t.addBodyLines(this,e)}}TP.INPUT_NAME_VEC3=\\\\\\\"vec3\\\\\\\",TP.INPUT_NAME_W=\\\\\\\"w\\\\\\\",TP.OUTPUT_NAME_VEC4=\\\\\\\"vec4\\\\\\\";const AP=new class extends ua{};class MP extends gf{constructor(){super(...arguments),this.paramsConfig=AP}gl_method_name(){return\\\\\\\"\\\\\\\"}gl_function_definitions(){return[]}initializeNode(){super.initializeNode(),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this)),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this))}_expected_input_types(){const t=this.io.connection_points.first_input_connection_type()||Uo.FLOAT;if(this.io.connections.firstInputConnection()){const e=this.io.connections.inputConnections();if(e){let n=Math.max(f.compact(e).length+1,2);return f.range(n).map((e=>t))}return[]}return f.range(2).map((e=>t))}_expected_output_types(){return[this._expected_input_types()[0]]}_gl_input_name(t){return\\\\\\\"in\\\\\\\"}setLines(t){const e=this.io.outputs.namedOutputConnectionPoints()[0].type(),n=this.io.inputs.namedInputConnectionPoints().map(((t,e)=>{const n=t.name();return mf.any(this.variableForInput(n))})).join(\\\\\\\", \\\\\\\"),i=`${e} ${this.glVarName(this.io.connection_points.output_name(0))} = ${this.gl_method_name()}(${n})`;t.addBodyLines(this,[i]),t.addDefinitions(this,this.gl_function_definitions())}}class EP extends MP{_gl_input_name(t){return\\\\\\\"in\\\\\\\"}_expected_input_types(){return[this.io.connection_points.first_input_connection_type()||Uo.FLOAT]}}class SP extends MP{_expected_input_types(){const t=this.io.connection_points.first_input_connection_type()||Uo.FLOAT;return[t,t]}}class CP extends MP{_expected_input_types(){const t=this.io.connection_points.first_input_connection_type()||Uo.FLOAT;return[t,t,t]}}class NP extends MP{_expected_input_types(){const t=this.io.connection_points.first_input_connection_type()||Uo.FLOAT;return[t,t,t,t]}}class LP extends MP{_expected_input_types(){const t=this.io.connection_points.first_input_connection_type()||Uo.FLOAT;return[t,t,t,t,t]}}function OP(t,e={}){const n=e.method||t,i=e.out||\\\\\\\"val\\\\\\\",s=e.in||\\\\\\\"in\\\\\\\";return class extends EP{static type(){return t}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function(this._gl_output_name.bind(this))}_gl_input_name(t){return s}_gl_output_name(t){return i}gl_method_name(){return n}}}class PP extends(OP(\\\\\\\"abs\\\\\\\")){}class RP extends(OP(\\\\\\\"acos\\\\\\\",{out:\\\\\\\"radians\\\\\\\"})){}class IP extends(OP(\\\\\\\"asin\\\\\\\",{out:\\\\\\\"radians\\\\\\\"})){}class FP extends(OP(\\\\\\\"atan\\\\\\\",{out:\\\\\\\"radians\\\\\\\"})){}class DP extends(OP(\\\\\\\"ceil\\\\\\\")){}class BP extends(OP(\\\\\\\"cos\\\\\\\",{in:\\\\\\\"radians\\\\\\\"})){}class zP extends(OP(\\\\\\\"degrees\\\\\\\",{in:\\\\\\\"radians\\\\\\\",out:\\\\\\\"degrees\\\\\\\"})){}class kP extends(OP(\\\\\\\"exp\\\\\\\")){}class UP extends(OP(\\\\\\\"exp2\\\\\\\")){}class GP extends(OP(\\\\\\\"floor\\\\\\\")){}class VP extends(OP(\\\\\\\"fract\\\\\\\")){}class HP extends(OP(\\\\\\\"inverseSqrt\\\\\\\",{method:\\\\\\\"inversesqrt\\\\\\\"})){}class jP extends(OP(\\\\\\\"log\\\\\\\")){}class WP extends(OP(\\\\\\\"log2\\\\\\\")){}class qP extends(OP(\\\\\\\"normalize\\\\\\\",{out:\\\\\\\"normalized\\\\\\\"})){}class XP extends(OP(\\\\\\\"radians\\\\\\\",{in:\\\\\\\"degrees\\\\\\\",out:\\\\\\\"radians\\\\\\\"})){}class YP extends(OP(\\\\\\\"sign\\\\\\\")){}class $P extends(OP(\\\\\\\"sin\\\\\\\",{in:\\\\\\\"radians\\\\\\\"})){}class JP extends(OP(\\\\\\\"sqrt\\\\\\\")){}class ZP extends(OP(\\\\\\\"tan\\\\\\\")){}function QP(t,e={}){const n=e.method||t,i=e.out||\\\\\\\"val\\\\\\\",s=e.in||[\\\\\\\"in0\\\\\\\",\\\\\\\"in1\\\\\\\"],r=e.default_in_type,o=e.allowed_in_types,a=e.out_type,l=e.functions||[];return class extends SP{static type(){return t}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function(this._gl_output_name.bind(this)),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),a&&this.io.connection_points.set_expected_output_types_function((()=>[a]))}_gl_input_name(t){return s[t]}_gl_output_name(t){return i}gl_method_name(){return n}gl_function_definitions(){return l?l.map((t=>new Cf(this,t))):[]}_expected_input_types(){let t=this.io.connection_points.first_input_connection_type();if(t&&o&&!o.includes(t)){const e=this.io.inputs.namedInputConnectionPoints()[0];t=e?e.type():r}const e=t||r||Uo.FLOAT;return[e,e]}}}class KP extends(QP(\\\\\\\"distance\\\\\\\",{in:[\\\\\\\"p0\\\\\\\",\\\\\\\"p1\\\\\\\"],default_in_type:Uo.VEC3,allowed_in_types:[Uo.VEC2,Uo.VEC3,Uo.VEC4],out_type:Uo.FLOAT})){}class tR extends(QP(\\\\\\\"dot\\\\\\\",{in:[\\\\\\\"vec0\\\\\\\",\\\\\\\"vec1\\\\\\\"],default_in_type:Uo.VEC3,allowed_in_types:[Uo.VEC2,Uo.VEC3,Uo.VEC4],out_type:Uo.FLOAT})){}class eR extends(QP(\\\\\\\"max\\\\\\\")){}class nR extends(QP(\\\\\\\"min\\\\\\\")){}class iR extends(QP(\\\\\\\"mod\\\\\\\")){paramDefaultValue(t){return{in1:1}[t]}_expected_input_types(){const t=Uo.FLOAT;return[t,t]}}class sR extends(QP(\\\\\\\"pow\\\\\\\",{in:[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\"]})){}class rR extends(QP(\\\\\\\"reflect\\\\\\\",{in:[\\\\\\\"I\\\\\\\",\\\\\\\"N\\\\\\\"],default_in_type:Uo.VEC3})){}class oR extends(QP(\\\\\\\"step\\\\\\\",{in:[\\\\\\\"edge\\\\\\\",\\\\\\\"x\\\\\\\"]})){}function aR(t,e={}){const n=e.method||t,i=e.out||\\\\\\\"val\\\\\\\",s=e.in||[\\\\\\\"in0\\\\\\\",\\\\\\\"in1\\\\\\\",\\\\\\\"in2\\\\\\\"],r=e.default||{},o=e.out_type||Uo.FLOAT,a=e.functions||[];return class extends CP{static type(){return t}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function(this._gl_output_name.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this))}_gl_input_name(t){return s[t]}_gl_output_name(t){return i}gl_method_name(){return n}_expected_output_types(){return[o]}paramDefaultValue(t){return r[t]}gl_function_definitions(){return a.map((t=>new Cf(this,t)))}}}class lR extends(aR(\\\\\\\"clamp\\\\\\\",{in:[\\\\\\\"value\\\\\\\",\\\\\\\"min\\\\\\\",\\\\\\\"max\\\\\\\"],default:{max:1}})){_expected_output_types(){return[this._expected_input_types()[0]]}}class cR extends(aR(\\\\\\\"faceForward\\\\\\\",{in:[\\\\\\\"N\\\\\\\",\\\\\\\"I\\\\\\\",\\\\\\\"Nref\\\\\\\"]})){}class hR extends(aR(\\\\\\\"smoothstep\\\\\\\",{in:[\\\\\\\"edge0\\\\\\\",\\\\\\\"edge1\\\\\\\",\\\\\\\"x\\\\\\\"],default:{edge1:1}})){_expected_output_types(){return[this._expected_input_types()[0]]}}function uR(t,e){const n=e.in_prefix||t,i=e.out||\\\\\\\"val\\\\\\\",s=e.operation,r=e.allowed_in_types;return class extends SP{static type(){return t}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function(this._gl_output_name.bind(this)),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this))}setLines(t){const e=this.io.outputs.namedOutputConnectionPoints()[0].type(),n=this.io.inputs.namedInputConnectionPoints().map(((t,e)=>{const n=t.name(),i=this.variableForInput(n);if(i)return mf.any(i)})).join(` ${this.gl_operation()} `),i=`${e} ${this.glVarName(this.io.connection_points.output_name(0))} = ${this.gl_method_name()}(${n})`;t.addBodyLines(this,[i])}_gl_input_name(t){return`${n}${t}`}_gl_output_name(t){return i}gl_operation(){return s}_expected_input_types(){let t=this.io.connection_points.first_input_connection_type();if(t&&r&&!r.includes(t)){const e=this.io.inputs.namedInputConnectionPoints()[0];e&&(t=e.type())}const e=t||Uo.FLOAT,n=this.io.connections.existingInputConnections(),i=n?Math.max(n.length+1,2):2,s=[];for(let t=0;t{const n=t.name();return mf.any(this.variableForInput(n))})).join(` ${this.boolean_operation()} `),n=`bool ${this.glVarName(this.io.connection_points.output_name(0))} = ${e}`;t.addBodyLines(this,[n])}}function gR(t,e){return class extends fR{static type(){return t}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function(this._gl_output_name.bind(this))}boolean_operation(){return e.op}_gl_output_name(e){return t}_gl_input_name(e=0){return`${t}${e}`}}}class vR extends(gR(\\\\\\\"and\\\\\\\",{op:\\\\\\\"&&\\\\\\\"})){}class yR extends(gR(\\\\\\\"or\\\\\\\",{op:\\\\\\\"||\\\\\\\"})){}var xR;!function(t){t.TIME=\\\\\\\"time\\\\\\\",t.DELTA_TIME=\\\\\\\"delta_time\\\\\\\"}(xR||(xR={}));var bR,wR;!function(t){t.POSITION=\\\\\\\"position\\\\\\\",t.VELOCITY=\\\\\\\"velocity\\\\\\\",t.MASS=\\\\\\\"mass\\\\\\\",t.FORCE=\\\\\\\"force\\\\\\\"}(bR||(bR={})),function(t){t.POSITION=\\\\\\\"position\\\\\\\",t.VELOCITY=\\\\\\\"velocity\\\\\\\"}(wR||(wR={}));const TR=[bR.POSITION,bR.VELOCITY,bR.MASS,bR.FORCE],AR=[wR.POSITION,wR.VELOCITY],MR={[bR.POSITION]:[0,0,0],[bR.VELOCITY]:[0,0,0],[bR.MASS]:1,[bR.FORCE]:[0,-9.8,0]};const ER=new class extends ua{};class SR extends gf{constructor(){super(...arguments),this.paramsConfig=ER}static type(){return\\\\\\\"acceleration\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo(wR.POSITION,Uo.VEC3),new qo(wR.VELOCITY,Uo.VEC3)]),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this)),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function(this._gl_output_name.bind(this))}_expected_input_types(){const t=this.io.connection_points.first_input_connection_type()||Uo.VEC3;return[t,t,Uo.FLOAT,t]}_expected_output_types(){const t=this._expected_input_types()[0];return[t,t]}_gl_input_name(t){return TR[t]}_gl_output_name(t){return AR[t]}paramDefaultValue(t){return MR[t]}setLines(t){const e=this.io.outputs.namedOutputConnectionPoints()[0].type(),n=new Nf(this,Uo.FLOAT,xR.DELTA_TIME),i=new Cf(this,\\\\\\\"float compute_velocity_from_acceleration(float vel, float force, float mass, float time_delta){\\\\n\\\\tfloat impulse = (force * mass) * time_delta;\\\\n\\\\treturn vel + impulse;\\\\n}\\\\nvec2 compute_velocity_from_acceleration(vec2 vel, vec2 force, float mass, float time_delta){\\\\n\\\\tvec2 impulse = (force * mass) * time_delta;\\\\n\\\\treturn vel + impulse;\\\\n}\\\\nvec3 compute_velocity_from_acceleration(vec3 vel, vec3 force, float mass, float time_delta){\\\\n\\\\tvec3 impulse = (force * mass) * time_delta;\\\\n\\\\treturn vel + impulse;\\\\n}\\\\nvec4 compute_velocity_from_acceleration(vec4 vel, vec4 force, float mass, float time_delta){\\\\n\\\\tvec4 impulse = (force * mass) * time_delta;\\\\n\\\\treturn vel + impulse;\\\\n}\\\\nfloat compute_position_from_velocity(float position, float velocity, float time_delta){\\\\n\\\\treturn position + (velocity * time_delta);\\\\n}\\\\nvec2 compute_position_from_velocity(vec2 position, vec2 velocity, float time_delta){\\\\n\\\\treturn position + (velocity * time_delta);\\\\n}\\\\nvec3 compute_position_from_velocity(vec3 position, vec3 velocity, float time_delta){\\\\n\\\\treturn position + (velocity * time_delta);\\\\n}\\\\nvec4 compute_position_from_velocity(vec4 position, vec4 velocity, float time_delta){\\\\n\\\\treturn position + (velocity * time_delta);\\\\n}\\\\\\\");t.addDefinitions(this,[n,i]);const s=mf.any(this.variableForInput(bR.POSITION)),r=mf.any(this.variableForInput(bR.VELOCITY)),o=mf.float(this.variableForInput(bR.MASS)),a=mf.any(this.variableForInput(bR.FORCE)),l=this.glVarName(wR.POSITION),c=this.glVarName(wR.VELOCITY),h=`${e} ${c} = compute_velocity_from_acceleration(${[r,a,o,xR.DELTA_TIME].join(\\\\\\\", \\\\\\\")})`,u=`${e} ${l} = compute_position_from_velocity(${[s,c,xR.DELTA_TIME].join(\\\\\\\", \\\\\\\")})`;t.addBodyLines(this,[h,u])}}var CR,NR=\\\\\\\"\\\\n\\\\n// https://github.com/mattatz/ShibuyaCrowd/blob/master/source/shaders/common/quaternion.glsl\\\\nvec4 quatMult(vec4 q1, vec4 q2)\\\\n{\\\\n\\\\treturn vec4(\\\\n\\\\tq1.w * q2.x + q1.x * q2.w + q1.z * q2.y - q1.y * q2.z,\\\\n\\\\tq1.w * q2.y + q1.y * q2.w + q1.x * q2.z - q1.z * q2.x,\\\\n\\\\tq1.w * q2.z + q1.z * q2.w + q1.y * q2.x - q1.x * q2.y,\\\\n\\\\tq1.w * q2.w - q1.x * q2.x - q1.y * q2.y - q1.z * q2.z\\\\n\\\\t);\\\\n}\\\\n// http://glmatrix.net/docs/quat.js.html#line97\\\\n// let ax = a[0], ay = a[1], az = a[2], aw = a[3];\\\\n\\\\n// let bx = b[0], by = b[1], bz = b[2], bw = b[3];\\\\n\\\\n// out[0] = ax * bw + aw * bx + ay * bz - az * by;\\\\n\\\\n// out[1] = ay * bw + aw * by + az * bx - ax * bz;\\\\n\\\\n// out[2] = az * bw + aw * bz + ax * by - ay * bx;\\\\n\\\\n// out[3] = aw * bw - ax * bx - ay * by - az * bz;\\\\n\\\\n// return out\\\\n\\\\n\\\\n\\\\n// http://www.neilmendoza.com/glsl-rotation-about-an-arbitrary-axis/\\\\nmat4 rotationMatrix(vec3 axis, float angle)\\\\n{\\\\n\\\\taxis = normalize(axis);\\\\n\\\\tfloat s = sin(angle);\\\\n\\\\tfloat c = cos(angle);\\\\n\\\\tfloat oc = 1.0 - c;\\\\n\\\\n \\\\treturn mat4(oc * axis.x * axis.x + c, oc * axis.x * axis.y - axis.z * s, oc * axis.z * axis.x + axis.y * s, 0.0, oc * axis.x * axis.y + axis.z * s, oc * axis.y * axis.y + c, oc * axis.y * axis.z - axis.x * s, 0.0, oc * axis.z * axis.x - axis.y * s, oc * axis.y * axis.z + axis.x * s, oc * axis.z * axis.z + c, 0.0, 0.0, 0.0, 0.0, 1.0);\\\\n}\\\\n\\\\n// https://www.geeks3d.com/20141201/how-to-rotate-a-vertex-by-a-quaternion-in-glsl/\\\\nvec4 quatFromAxisAngle(vec3 axis, float angle)\\\\n{\\\\n\\\\tvec4 qr;\\\\n\\\\tfloat half_angle = (angle * 0.5); // * 3.14159 / 180.0;\\\\n\\\\tfloat sin_half_angle = sin(half_angle);\\\\n\\\\tqr.x = axis.x * sin_half_angle;\\\\n\\\\tqr.y = axis.y * sin_half_angle;\\\\n\\\\tqr.z = axis.z * sin_half_angle;\\\\n\\\\tqr.w = cos(half_angle);\\\\n\\\\treturn qr;\\\\n}\\\\nvec3 rotateWithAxisAngle(vec3 position, vec3 axis, float angle)\\\\n{\\\\n\\\\tvec4 q = quatFromAxisAngle(axis, angle);\\\\n\\\\tvec3 v = position.xyz;\\\\n\\\\treturn v + 2.0 * cross(q.xyz, cross(q.xyz, v) + q.w * v);\\\\n}\\\\n// vec3 applyQuaternionToVector( vec4 q, vec3 v ){\\\\n// \\\\treturn v + 2.0 * cross( q.xyz, cross( q.xyz, v ) + q.w * v );\\\\n// }\\\\nvec3 rotateWithQuat( vec3 v, vec4 q )\\\\n{\\\\n\\\\t// vec4 qv = multQuat( quat, vec4(vec, 0.0) );\\\\n\\\\t// return multQuat( qv, vec4(-quat.x, -quat.y, -quat.z, quat.w) ).xyz;\\\\n\\\\treturn v + 2.0 * cross( q.xyz, cross( q.xyz, v ) + q.w * v );\\\\n}\\\\n// https://github.com/glslify/glsl-look-at/blob/gh-pages/index.glsl\\\\n// mat3 rotation_matrix(vec3 origin, vec3 target, float roll) {\\\\n// \\\\tvec3 rr = vec3(sin(roll), cos(roll), 0.0);\\\\n// \\\\tvec3 ww = normalize(target - origin);\\\\n// \\\\tvec3 uu = normalize(cross(ww, rr));\\\\n// \\\\tvec3 vv = normalize(cross(uu, ww));\\\\n\\\\n// \\\\treturn mat3(uu, vv, ww);\\\\n// }\\\\n// mat3 rotation_matrix(vec3 target, float roll) {\\\\n// \\\\tvec3 rr = vec3(sin(roll), cos(roll), 0.0);\\\\n// \\\\tvec3 ww = normalize(target);\\\\n// \\\\tvec3 uu = normalize(cross(ww, rr));\\\\n// \\\\tvec3 vv = normalize(cross(uu, ww));\\\\n\\\\n// \\\\treturn mat3(uu, vv, ww);\\\\n// }\\\\n\\\\nfloat vectorAngle(vec3 start, vec3 dest){\\\\n\\\\tstart = normalize(start);\\\\n\\\\tdest = normalize(dest);\\\\n\\\\n\\\\tfloat cosTheta = dot(start, dest);\\\\n\\\\tvec3 c1 = cross(start, dest);\\\\n\\\\t// We use the dot product of the cross with the Y axis.\\\\n\\\\t// This is a little arbitrary, but can still give a good sense of direction\\\\n\\\\tvec3 y_axis = vec3(0.0, 1.0, 0.0);\\\\n\\\\tfloat d1 = dot(c1, y_axis);\\\\n\\\\tfloat angle = acos(cosTheta) * sign(d1);\\\\n\\\\treturn angle;\\\\n}\\\\n\\\\n// http://www.opengl-tutorial.org/intermediate-tutorials/tutorial-17-quaternions/#i-need-an-equivalent-of-glulookat-how-do-i-orient-an-object-towards-a-point-\\\\nvec4 vectorAlign(vec3 start, vec3 dest){\\\\n\\\\tstart = normalize(start);\\\\n\\\\tdest = normalize(dest);\\\\n\\\\n\\\\tfloat cosTheta = dot(start, dest);\\\\n\\\\tvec3 axis;\\\\n\\\\n\\\\t// if (cosTheta < -1 + 0.001f){\\\\n\\\\t// \\\\t// special case when vectors in opposite directions:\\\\n\\\\t// \\\\t// there is no ideal rotation axis\\\\n\\\\t// \\\\t// So guess one; any will do as long as it's perpendicular to start\\\\n\\\\t// \\\\taxis = cross(vec3(0.0f, 0.0f, 1.0f), start);\\\\n\\\\t// \\\\tif (length2(axis) < 0.01 ) // bad luck, they were parallel, try again!\\\\n\\\\t// \\\\t\\\\taxis = cross(vec3(1.0f, 0.0f, 0.0f), start);\\\\n\\\\n\\\\t// \\\\taxis = normalize(axis);\\\\n\\\\t// \\\\treturn gtx::quaternion::angleAxis(glm::radians(180.0f), axis);\\\\n\\\\t// }\\\\n\\\\tif(cosTheta > (1.0 - 0.0001) || cosTheta < (-1.0 + 0.0001) ){\\\\n\\\\t\\\\taxis = normalize(cross(start, vec3(0.0, 1.0, 0.0)));\\\\n\\\\t\\\\tif (length(axis) < 0.001 ){ // bad luck, they were parallel, try again!\\\\n\\\\t\\\\t\\\\taxis = normalize(cross(start, vec3(1.0, 0.0, 0.0)));\\\\n\\\\t\\\\t}\\\\n\\\\t} else {\\\\n\\\\t\\\\taxis = normalize(cross(start, dest));\\\\n\\\\t}\\\\n\\\\n\\\\tfloat angle = acos(cosTheta);\\\\n\\\\n\\\\treturn quatFromAxisAngle(axis, angle);\\\\n}\\\\nvec4 vectorAlignWithUp(vec3 start, vec3 dest, vec3 up){\\\\n\\\\tvec4 rot1 = vectorAlign(start, dest);\\\\n\\\\tup = normalize(up);\\\\n\\\\n\\\\t// Recompute desiredUp so that it's perpendicular to the direction\\\\n\\\\t// You can skip that part if you really want to force desiredUp\\\\n\\\\t// vec3 right = normalize(cross(dest, up));\\\\n\\\\t// up = normalize(cross(right, dest));\\\\n\\\\n\\\\t// Because of the 1rst rotation, the up is probably completely screwed up.\\\\n\\\\t// Find the rotation between the up of the rotated object, and the desired up\\\\n\\\\tvec3 newUp = rotateWithQuat(vec3(0.0, 1.0, 0.0), rot1);//rot1 * vec3(0.0, 1.0, 0.0);\\\\n\\\\tvec4 rot2 = vectorAlign(up, newUp);\\\\n\\\\n\\\\t// return rot1;\\\\n\\\\treturn rot2;\\\\n\\\\t// return multQuat(rot1, rot2);\\\\n\\\\t// return rot2 * rot1;\\\\n\\\\n}\\\\n\\\\n// https://www.euclideanspace.com/maths/geometry/rotations/conversions/quaternionToAngle/index.htm\\\\nfloat quatToAngle(vec4 q){\\\\n\\\\treturn 2.0 * acos(q.w);\\\\n}\\\\nvec3 quatToAxis(vec4 q){\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\tq.x / sqrt(1.0-q.w*q.w),\\\\n\\\\t\\\\tq.y / sqrt(1.0-q.w*q.w),\\\\n\\\\t\\\\tq.z / sqrt(1.0-q.w*q.w)\\\\n\\\\t);\\\\n}\\\\n\\\\nvec4 align(vec3 dir, vec3 up){\\\\n\\\\tvec3 start_dir = vec3(0.0, 0.0, 1.0);\\\\n\\\\tvec3 start_up = vec3(0.0, 1.0, 0.0);\\\\n\\\\tvec4 rot1 = vectorAlign(start_dir, dir);\\\\n\\\\tup = normalize(up);\\\\n\\\\n\\\\t// Recompute desiredUp so that it's perpendicular to the direction\\\\n\\\\t// You can skip that part if you really want to force desiredUp\\\\n\\\\tvec3 right = normalize(cross(dir, up));\\\\n\\\\tif(length(right)<0.001){\\\\n\\\\t\\\\tright = vec3(1.0, 0.0, 0.0);\\\\n\\\\t}\\\\n\\\\tup = normalize(cross(right, dir));\\\\n\\\\n\\\\t// Because of the 1rst rotation, the up is probably completely screwed up.\\\\n\\\\t// Find the rotation between the up of the rotated object, and the desired up\\\\n\\\\tvec3 newUp = rotateWithQuat(start_up, rot1);//rot1 * vec3(0.0, 1.0, 0.0);\\\\n\\\\tvec4 rot2 = vectorAlign(normalize(newUp), up);\\\\n\\\\n\\\\t// return rot1;\\\\n\\\\treturn quatMult(rot1, rot2);\\\\n\\\\t// return rot2 * rot1;\\\\n\\\\n}\\\\\\\";!function(t){t.DIR=\\\\\\\"dir\\\\\\\",t.UP=\\\\\\\"up\\\\\\\"}(CR||(CR={}));const LR=[CR.DIR,CR.UP],OR={[CR.DIR]:[0,0,1],[CR.UP]:[0,1,0]};class PR extends SP{static type(){return\\\\\\\"align\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function((t=>LR[t])),this.io.connection_points.set_expected_input_types_function((()=>[Uo.VEC3,Uo.VEC3])),this.io.connection_points.set_expected_output_types_function((()=>[Uo.VEC4]))}paramDefaultValue(t){return OR[t]}gl_method_name(){return\\\\\\\"align\\\\\\\"}gl_function_definitions(){return[new Cf(this,NR)]}}var RR;!function(t){t.LINEAR=\\\\\\\"Linear\\\\\\\",t.GAMMA=\\\\\\\"Gamma\\\\\\\",t.SRGB=\\\\\\\"sRGB\\\\\\\",t.RGBE=\\\\\\\"RGBE\\\\\\\",t.RGBM=\\\\\\\"RGBM\\\\\\\",t.RGBD=\\\\\\\"RGBD\\\\\\\",t.LogLuv=\\\\\\\"LogLuv\\\\\\\"}(RR||(RR={}));const IR=[RR.LINEAR,RR.GAMMA,RR.SRGB,RR.RGBE,RR.RGBM,RR.RGBD,RR.LogLuv];const FR=new class extends ua{constructor(){super(...arguments),this.color=ha.VECTOR4([1,1,1,1]),this.from=ha.INTEGER(IR.indexOf(RR.LINEAR),{menu:{entries:IR.map(((t,e)=>({name:t,value:e})))}}),this.to=ha.INTEGER(IR.indexOf(RR.GAMMA),{menu:{entries:IR.map(((t,e)=>({name:t,value:e})))}}),this.gammaFactor=ha.FLOAT(2.2)}};class DR extends gf{constructor(){super(...arguments),this.paramsConfig=FR}static type(){return\\\\\\\"colorCorrect\\\\\\\"}initializeNode(){this.io.connection_points.spare_params.set_inputless_param_names([\\\\\\\"to\\\\\\\",\\\\\\\"from\\\\\\\"]),this.io.outputs.setNamedOutputConnectionPoints([new qo(DR.OUTPUT_NAME,Uo.VEC4)])}setLines(t){const e=IR[this.pv.from],n=IR[this.pv.to],i=this.glVarName(DR.OUTPUT_NAME),s=mf.any(this.variableForInput(DR.INPUT_NAME)),r=[];if(e!=n){const t=`${e}To${n}`,o=[];if(o.push(s),e==RR.GAMMA||n==RR.GAMMA){const t=mf.any(this.variableForInputParam(this.p.gammaFactor));o.push(t)}r.push(`vec4 ${i} = ${t}(${o.join(\\\\\\\", \\\\\\\")})`)}else r.push(`vec4 ${i} = ${s}`);t.addBodyLines(this,r)}}var BR,zR;DR.INPUT_NAME=\\\\\\\"color\\\\\\\",DR.INPUT_GAMMA_FACTOR=\\\\\\\"gammaFactor\\\\\\\",DR.OUTPUT_NAME=\\\\\\\"out\\\\\\\",function(t){t.EQUAL=\\\\\\\"Equal\\\\\\\",t.LESS_THAN=\\\\\\\"Less Than\\\\\\\",t.GREATER_THAN=\\\\\\\"Greater Than\\\\\\\",t.LESS_THAN_OR_EQUAL=\\\\\\\"Less Than Or Equal\\\\\\\",t.GREATER_THAN_OR_EQUAL=\\\\\\\"Greater Than Or Equal\\\\\\\",t.NOT_EQUAL=\\\\\\\"Not Equal\\\\\\\"}(BR||(BR={})),function(t){t.EQUAL=\\\\\\\"==\\\\\\\",t.LESS_THAN=\\\\\\\"<\\\\\\\",t.GREATER_THAN=\\\\\\\">\\\\\\\",t.LESS_THAN_OR_EQUAL=\\\\\\\"<=\\\\\\\",t.GREATER_THAN_OR_EQUAL=\\\\\\\">=\\\\\\\",t.NOT_EQUAL=\\\\\\\"!=\\\\\\\"}(zR||(zR={}));const kR=[BR.EQUAL,BR.LESS_THAN,BR.GREATER_THAN,BR.LESS_THAN_OR_EQUAL,BR.GREATER_THAN_OR_EQUAL,BR.NOT_EQUAL],UR=[zR.EQUAL,zR.LESS_THAN,zR.GREATER_THAN,zR.LESS_THAN_OR_EQUAL,zR.GREATER_THAN_OR_EQUAL,zR.NOT_EQUAL],GR=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\",\\\\\\\"w\\\\\\\"];const VR=new class extends ua{constructor(){super(...arguments),this.test=ha.INTEGER(0,{menu:{entries:kR.map(((t,e)=>({name:`${UR[e].padEnd(2,\\\\\\\" \\\\\\\")} (${t})`,value:e})))}})}};class HR extends gf{constructor(){super(...arguments),this.paramsConfig=VR}static type(){return\\\\\\\"compare\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.spare_params.set_inputless_param_names([\\\\\\\"test\\\\\\\"]),this.io.connection_points.initializeNode(),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function((t=>\\\\\\\"val\\\\\\\")),this.io.connection_points.set_expected_input_types_function(this._expected_input_type.bind(this)),this.io.connection_points.set_expected_output_types_function((()=>[Uo.BOOL]))}set_test_name(t){this.p.test.set(kR.indexOf(t))}_gl_input_name(t){return[\\\\\\\"value0\\\\\\\",\\\\\\\"value1\\\\\\\"][t]}_expected_input_type(){const t=this.io.connection_points.first_input_connection_type()||Uo.FLOAT;return[t,t]}setLines(t){const e=[],n=this.glVarName(\\\\\\\"val\\\\\\\"),i=UR[this.pv.test],s=mf.any(this.variableForInput(this._gl_input_name(0))),r=mf.any(this.variableForInput(this._gl_input_name(1))),o=this.io.inputs.namedInputConnectionPoints()[0];let a=1;if(o&&(a=Wo[o.type()]||1),a>1){let t=[];for(let n=0;n({name:t,value:e})))}}),this.bool=ha.BOOLEAN(0,WR(Uo.BOOL)),this.int=ha.INTEGER(0,WR(Uo.INT)),this.float=ha.FLOAT(0,WR(Uo.FLOAT)),this.vec2=ha.VECTOR2([0,0],WR(Uo.VEC2)),this.vec3=ha.VECTOR3([0,0,0],WR(Uo.VEC3)),this.vec4=ha.VECTOR4([0,0,0,0],WR(Uo.VEC4))}};class XR extends gf{constructor(){super(...arguments),this.paramsConfig=qR,this._allow_inputs_created_from_params=!1}static type(){return\\\\\\\"constant\\\\\\\"}initializeNode(){this.io.connection_points.set_output_name_function((t=>XR.OUTPUT_NAME)),this.io.connection_points.set_expected_input_types_function((()=>[])),this.io.connection_points.set_expected_output_types_function((()=>[this._current_connection_type]))}setLines(t){const e=this._current_param;if(e){const n=this._current_connection_type;let i=mf.any(e.value);e.name()==this.p.int.name()&&m.isNumber(e.value)&&(i=mf.integer(e.value));const s=`${n} ${this._current_var_name} = ${i}`;t.addBodyLines(this,[s])}else console.warn(`no param found for constant node for type '${this.pv.type}'`)}get _current_connection_type(){null==this.pv.type&&console.warn(\\\\\\\"constant gl node type if not valid\\\\\\\");const t=Go[this.pv.type];return null==t&&console.warn(\\\\\\\"constant gl node type if not valid\\\\\\\"),t}get _current_param(){this._params_by_type=this._params_by_type||new Map([[Uo.BOOL,this.p.bool],[Uo.INT,this.p.int],[Uo.FLOAT,this.p.float],[Uo.VEC2,this.p.vec2],[Uo.VEC3,this.p.vec3],[Uo.VEC4,this.p.vec4]]);const t=Go[this.pv.type];return this._params_by_type.get(t)}get _current_var_name(){return this.glVarName(XR.OUTPUT_NAME)}set_gl_type(t){this.p.type.set(Go.indexOf(t))}}XR.OUTPUT_NAME=\\\\\\\"val\\\\\\\";const YR=\\\\\\\"cross\\\\\\\";const $R=new class extends ua{constructor(){super(...arguments),this.x=ha.VECTOR3([0,0,1]),this.y=ha.VECTOR3([0,1,0])}};class JR extends gf{constructor(){super(...arguments),this.paramsConfig=$R}static type(){return\\\\\\\"cross\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo(YR,Uo.VEC3)])}setLines(t){const e=mf.float(this.variableForInputParam(this.p.x)),n=mf.float(this.variableForInputParam(this.p.y)),i=`vec3 ${this.glVarName(YR)} = cross(${e}, ${n})`;t.addBodyLines(this,[i])}}class ZR extends(aR(\\\\\\\"cycle\\\\\\\",{in:[\\\\\\\"in\\\\\\\",\\\\\\\"min\\\\\\\",\\\\\\\"max\\\\\\\"],default:{max:1},functions:[\\\\\\\"float cycle(float val, float val_min, float val_max){\\\\n\\\\tif(val >= val_min && val < val_max){\\\\n\\\\t\\\\treturn val;\\\\n\\\\t} else {\\\\n\\\\t\\\\tfloat range = val_max - val_min;\\\\n\\\\t\\\\tif(val >= val_max){\\\\n\\\\t\\\\t\\\\tfloat delta = (val - val_max);\\\\n\\\\t\\\\t\\\\treturn val_min + mod(delta, range);\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tfloat delta = (val_min - val);\\\\n\\\\t\\\\t\\\\treturn val_max - mod(delta, range);\\\\n\\\\t\\\\t}\\\\n\\\\t}\\\\n}\\\\\\\"]})){}var QR=\\\\\\\"float disk_feather(float dist, float radius, float feather){\\\\n\\\\tif(feather <= 0.0){\\\\n\\\\t\\\\tif(dist < radius){return 1.0;}else{return 0.0;}\\\\n\\\\t} else {\\\\n\\\\t\\\\tfloat half_feather = feather * 0.5;\\\\n\\\\t\\\\tif(dist < (radius - half_feather)){\\\\n\\\\t\\\\t\\\\treturn 1.0;\\\\n\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\tif(dist > (radius + half_feather)){\\\\n\\\\t\\\\t\\\\t\\\\treturn 0.0;\\\\n\\\\t\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\t\\\\tfloat feather_start = (radius - half_feather);\\\\n\\\\t\\\\t\\\\t\\\\tfloat blend = 1.0 - (dist - feather_start) / feather;\\\\n\\\\t\\\\t\\\\t\\\\treturn blend;\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t}\\\\n\\\\t}\\\\n}\\\\n\\\\nfloat disk2d(vec2 pos, vec2 center, float radius, float feather){\\\\n\\\\tfloat dist = distance(pos, center);\\\\n\\\\treturn disk_feather(dist, radius, feather);\\\\n}\\\\n\\\\n// function could be called sphere, but is an overload of disk, and is the same\\\\nfloat disk3d(vec3 pos, vec3 center, float radius, float feather){\\\\n\\\\tfloat dist = distance(pos, center);\\\\n\\\\treturn disk_feather(dist, radius, feather);\\\\n}\\\\\\\";const KR=new class extends ua{constructor(){super(...arguments),this.position=ha.VECTOR2([0,0]),this.center=ha.VECTOR2([0,0]),this.radius=ha.FLOAT(1),this.feather=ha.FLOAT(.1)}};class tI extends gf{constructor(){super(...arguments),this.paramsConfig=KR}static type(){return\\\\\\\"disk\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"float\\\\\\\",Uo.FLOAT)])}setLines(t){const e=mf.vector2(this.variableForInputParam(this.p.position)),n=mf.vector2(this.variableForInputParam(this.p.center)),i=mf.float(this.variableForInputParam(this.p.radius)),s=mf.float(this.variableForInputParam(this.p.feather)),r=`float ${this.glVarName(\\\\\\\"float\\\\\\\")} = disk2d(${e}, ${n}, ${i}, ${s})`;t.addBodyLines(this,[r]),t.addDefinitions(this,[new Cf(this,QR)])}}var eI=\\\\\\\"\\\\nfloat bounceOut(float t) {\\\\n const float a = 4.0 / 11.0;\\\\n const float b = 8.0 / 11.0;\\\\n const float c = 9.0 / 10.0;\\\\n\\\\n const float ca = 4356.0 / 361.0;\\\\n const float cb = 35442.0 / 1805.0;\\\\n const float cc = 16061.0 / 1805.0;\\\\n\\\\n float t2 = t * t;\\\\n\\\\n return t < a\\\\n ? 7.5625 * t2\\\\n : t < b\\\\n ? 9.075 * t2 - 9.9 * t + 3.4\\\\n : t < c\\\\n ? ca * t2 - cb * t + cc\\\\n : 10.8 * t * t - 20.52 * t + 10.72;\\\\n}\\\\n\\\\n\\\\\\\";const nI=[\\\\\\\"back-in-out\\\\\\\",\\\\\\\"back-in\\\\\\\",\\\\\\\"back-out\\\\\\\",\\\\\\\"bounce-in-out\\\\\\\",\\\\\\\"bounce-in\\\\\\\",\\\\\\\"bounce-out\\\\\\\",\\\\\\\"circular-in-out\\\\\\\",\\\\\\\"circular-in\\\\\\\",\\\\\\\"circular-out\\\\\\\",\\\\\\\"cubic-in-out\\\\\\\",\\\\\\\"cubic-in\\\\\\\",\\\\\\\"cubic-out\\\\\\\",\\\\\\\"elastic-in-out\\\\\\\",\\\\\\\"elastic-in\\\\\\\",\\\\\\\"elastic-out\\\\\\\",\\\\\\\"exponential-in-out\\\\\\\",\\\\\\\"exponential-in\\\\\\\",\\\\\\\"exponential-out\\\\\\\",\\\\\\\"linear\\\\\\\",\\\\\\\"quadratic-in-out\\\\\\\",\\\\\\\"quadratic-in\\\\\\\",\\\\\\\"quadratic-out\\\\\\\",\\\\\\\"sine-in-out\\\\\\\",\\\\\\\"sine-in\\\\\\\",\\\\\\\"sine-out\\\\\\\"],iI={\\\\\\\"circular-in-out\\\\\\\":\\\\\\\"float circularInOut(float t) {\\\\n return t < 0.5\\\\n ? 0.5 * (1.0 - sqrt(1.0 - 4.0 * t * t))\\\\n : 0.5 * (sqrt((3.0 - 2.0 * t) * (2.0 * t - 1.0)) + 1.0);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"exponential-in-out\\\\\\\":\\\\\\\"float exponentialInOut(float t) {\\\\n return t == 0.0 || t == 1.0\\\\n ? t\\\\n : t < 0.5\\\\n ? +0.5 * pow(2.0, (20.0 * t) - 10.0)\\\\n : -0.5 * pow(2.0, 10.0 - (t * 20.0)) + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"circular-in\\\\\\\":\\\\\\\"float circularIn(float t) {\\\\n return 1.0 - sqrt(1.0 - t * t);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"elastic-out\\\\\\\":\\\\\\\"#ifndef HALF_PI\\\\n#define HALF_PI 1.5707963267948966\\\\n#endif\\\\n\\\\nfloat elasticOut(float t) {\\\\n return sin(-13.0 * (t + 1.0) * HALF_PI) * pow(2.0, -10.0 * t) + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"cubic-in\\\\\\\":\\\\\\\"float cubicIn(float t) {\\\\n return t * t * t;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"exponential-out\\\\\\\":\\\\\\\"float exponentialOut(float t) {\\\\n return t == 1.0 ? t : 1.0 - pow(2.0, -10.0 * t);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"quintic-out\\\\\\\":\\\\\\\"float quinticOut(float t) {\\\\n return 1.0 - (pow(t - 1.0, 5.0));\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"elastic-in-out\\\\\\\":\\\\\\\"#ifndef HALF_PI\\\\n#define HALF_PI 1.5707963267948966\\\\n#endif\\\\n\\\\nfloat elasticInOut(float t) {\\\\n return t < 0.5\\\\n ? 0.5 * sin(+13.0 * HALF_PI * 2.0 * t) * pow(2.0, 10.0 * (2.0 * t - 1.0))\\\\n : 0.5 * sin(-13.0 * HALF_PI * ((2.0 * t - 1.0) + 1.0)) * pow(2.0, -10.0 * (2.0 * t - 1.0)) + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",linear:\\\\\\\"float linear(float t) {\\\\n return t;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"circular-out\\\\\\\":\\\\\\\"float circularOut(float t) {\\\\n return sqrt((2.0 - t) * t);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"back-in-out\\\\\\\":\\\\\\\"\\\\nfloat backInOut(float t) {\\\\n float f = t < 0.5\\\\n ? 2.0 * t\\\\n : 1.0 - (2.0 * t - 1.0);\\\\n\\\\n float g = pow(f, 3.0) - f * sin(f * PI);\\\\n\\\\n return t < 0.5\\\\n ? 0.5 * g\\\\n : 0.5 * (1.0 - g) + 0.5;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"back-in\\\\\\\":\\\\\\\"\\\\nfloat backIn(float t) {\\\\n return pow(t, 3.0) - t * sin(t * PI);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"sine-in\\\\\\\":\\\\\\\"#ifndef HALF_PI\\\\n#define HALF_PI 1.5707963267948966\\\\n#endif\\\\n\\\\nfloat sineIn(float t) {\\\\n return sin((t - 1.0) * HALF_PI) + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"back-out\\\\\\\":\\\\\\\"\\\\nfloat backOut(float t) {\\\\n float f = 1.0 - t;\\\\n return 1.0 - (pow(f, 3.0) - f * sin(f * PI));\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"quartic-in-out\\\\\\\":\\\\\\\"float quarticInOut(float t) {\\\\n return t < 0.5\\\\n ? +8.0 * pow(t, 4.0)\\\\n : -8.0 * pow(t - 1.0, 4.0) + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"quadratic-in\\\\\\\":\\\\\\\"float quadraticIn(float t) {\\\\n return t * t;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"cubic-in-out\\\\\\\":\\\\\\\"float cubicInOut(float t) {\\\\n return t < 0.5\\\\n ? 4.0 * t * t * t\\\\n : 0.5 * pow(2.0 * t - 2.0, 3.0) + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"elastic-in\\\\\\\":\\\\\\\"#ifndef HALF_PI\\\\n#define HALF_PI 1.5707963267948966\\\\n#endif\\\\n\\\\nfloat elasticIn(float t) {\\\\n return sin(13.0 * t * HALF_PI) * pow(2.0, 10.0 * (t - 1.0));\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"bounce-out\\\\\\\":eI,\\\\\\\"quadratic-in-out\\\\\\\":\\\\\\\"float quadraticInOut(float t) {\\\\n float p = 2.0 * t * t;\\\\n return t < 0.5 ? p : -p + (4.0 * t) - 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"exponential-in\\\\\\\":\\\\\\\"float exponentialIn(float t) {\\\\n return t == 0.0 ? t : pow(2.0, 10.0 * (t - 1.0));\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"quintic-in-out\\\\\\\":\\\\\\\"float quinticInOut(float t) {\\\\n return t < 0.5\\\\n ? +16.0 * pow(t, 5.0)\\\\n : -0.5 * pow(2.0 * t - 2.0, 5.0) + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"sine-in-out\\\\\\\":\\\\\\\"\\\\nfloat sineInOut(float t) {\\\\n return -0.5 * (cos(PI * t) - 1.0);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"cubic-out\\\\\\\":\\\\\\\"float cubicOut(float t) {\\\\n float f = t - 1.0;\\\\n return f * f * f + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"quadratic-out\\\\\\\":\\\\\\\"float quadraticOut(float t) {\\\\n return -t * (t - 2.0);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"bounce-in-out\\\\\\\":\\\\\\\"\\\\nfloat bounceInOut(float t) {\\\\n return t < 0.5\\\\n ? 0.5 * (1.0 - bounceOut(1.0 - t * 2.0))\\\\n : 0.5 * bounceOut(t * 2.0 - 1.0) + 0.5;\\\\n}\\\\n\\\\n\\\\n\\\\n\\\\\\\",\\\\\\\"quintic-in\\\\\\\":\\\\\\\"float quinticIn(float t) {\\\\n return pow(t, 5.0);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"quartic-in\\\\\\\":\\\\\\\"float quarticIn(float t) {\\\\n return pow(t, 4.0);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"quartic-out\\\\\\\":\\\\\\\"float quarticOut(float t) {\\\\n return pow(t - 1.0, 3.0) * (1.0 - t) + 1.0;\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"bounce-in\\\\\\\":\\\\\\\"\\\\nfloat bounceIn(float t) {\\\\n return 1.0 - bounceOut(1.0 - t);\\\\n}\\\\n\\\\n\\\\\\\",\\\\\\\"sine-out\\\\\\\":\\\\\\\"#ifndef HALF_PI\\\\n#define HALF_PI 1.5707963267948966\\\\n#endif\\\\n\\\\nfloat sineOut(float t) {\\\\n return sin(t * HALF_PI);\\\\n}\\\\n\\\\n\\\\\\\"},sI={\\\\\\\"bounce-in\\\\\\\":[eI],\\\\\\\"bounce-in-out\\\\\\\":[eI]},rI={\\\\\\\"circular-in-out\\\\\\\":\\\\\\\"circularInOut\\\\\\\",\\\\\\\"exponential-in-out\\\\\\\":\\\\\\\"exponentialInOut\\\\\\\",\\\\\\\"circular-in\\\\\\\":\\\\\\\"circularIn\\\\\\\",\\\\\\\"elastic-out\\\\\\\":\\\\\\\"elasticOut\\\\\\\",\\\\\\\"cubic-in\\\\\\\":\\\\\\\"cubicIn\\\\\\\",\\\\\\\"exponential-out\\\\\\\":\\\\\\\"exponentialOut\\\\\\\",\\\\\\\"quintic-out\\\\\\\":\\\\\\\"quinticOut\\\\\\\",\\\\\\\"elastic-in-out\\\\\\\":\\\\\\\"elasticInOut\\\\\\\",linear:\\\\\\\"linear\\\\\\\",\\\\\\\"circular-out\\\\\\\":\\\\\\\"circularOut\\\\\\\",\\\\\\\"back-in-out\\\\\\\":\\\\\\\"backInOut\\\\\\\",\\\\\\\"back-in\\\\\\\":\\\\\\\"backIn\\\\\\\",\\\\\\\"sine-in\\\\\\\":\\\\\\\"sineIn\\\\\\\",\\\\\\\"back-out\\\\\\\":\\\\\\\"backOut\\\\\\\",\\\\\\\"quartic-in-out\\\\\\\":\\\\\\\"quarticInOut\\\\\\\",\\\\\\\"quadratic-in\\\\\\\":\\\\\\\"quadraticIn\\\\\\\",\\\\\\\"cubic-in-out\\\\\\\":\\\\\\\"cubicInOut\\\\\\\",\\\\\\\"elastic-in\\\\\\\":\\\\\\\"elasticIn\\\\\\\",\\\\\\\"bounce-out\\\\\\\":\\\\\\\"bounceOut\\\\\\\",\\\\\\\"quadratic-in-out\\\\\\\":\\\\\\\"quadraticInOut\\\\\\\",\\\\\\\"exponential-in\\\\\\\":\\\\\\\"exponentialIn\\\\\\\",\\\\\\\"quintic-in-out\\\\\\\":\\\\\\\"quinticInOut\\\\\\\",\\\\\\\"sine-in-out\\\\\\\":\\\\\\\"sineInOut\\\\\\\",\\\\\\\"cubic-out\\\\\\\":\\\\\\\"cubicOut\\\\\\\",\\\\\\\"quadratic-out\\\\\\\":\\\\\\\"quadraticOut\\\\\\\",\\\\\\\"bounce-in-out\\\\\\\":\\\\\\\"bounceInOut\\\\\\\",\\\\\\\"quintic-in\\\\\\\":\\\\\\\"quinticIn\\\\\\\",\\\\\\\"quartic-in\\\\\\\":\\\\\\\"quarticIn\\\\\\\",\\\\\\\"quartic-out\\\\\\\":\\\\\\\"quarticOut\\\\\\\",\\\\\\\"bounce-in\\\\\\\":\\\\\\\"bounceIn\\\\\\\",\\\\\\\"sine-out\\\\\\\":\\\\\\\"sineOut\\\\\\\"},oI=nI.indexOf(\\\\\\\"sine-in-out\\\\\\\");const aI=new class extends ua{constructor(){super(...arguments),this.type=ha.INTEGER(oI,{menu:{entries:nI.map(((t,e)=>({name:t,value:e})))}}),this.input=ha.FLOAT(0)}};class lI extends gf{constructor(){super(...arguments),this.paramsConfig=aI}static type(){return\\\\\\\"easing\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.spare_params.set_inputless_param_names([\\\\\\\"type\\\\\\\"]),this.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"out\\\\\\\",Uo.FLOAT)])}setLines(t){const e=nI[this.pv.type],n=rI[e];let i=[new Cf(this,iI[e])];const s=(sI[e]||[]).map((t=>new Cf(this,t)));s&&(i=s.concat(i));const r=mf.float(this.variableForInputParam(this.p.input)),o=`float ${this.glVarName(\\\\\\\"out\\\\\\\")} = ${n}(${r})`;t.addDefinitions(this,i),t.addBodyLines(this,[o])}}var cI=\\\\\\\"//\\\\n//\\\\n// FIT\\\\n//\\\\n//\\\\nfloat fit(float val, float srcMin, float srcMax, float destMin, float destMax){\\\\n\\\\tfloat src_range = srcMax - srcMin;\\\\n\\\\tfloat dest_range = destMax - destMin;\\\\n\\\\n\\\\tfloat r = (val - srcMin) / src_range;\\\\n\\\\treturn (r * dest_range) + destMin;\\\\n}\\\\nvec2 fit(vec2 val, vec2 srcMin, vec2 srcMax, vec2 destMin, vec2 destMax){\\\\n\\\\treturn vec2(\\\\n\\\\t\\\\tfit(val.x, srcMin.x, srcMax.x, destMin.x, destMax.x),\\\\n\\\\t\\\\tfit(val.y, srcMin.y, srcMax.y, destMin.y, destMax.y)\\\\n\\\\t);\\\\n}\\\\nvec3 fit(vec3 val, vec3 srcMin, vec3 srcMax, vec3 destMin, vec3 destMax){\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\tfit(val.x, srcMin.x, srcMax.x, destMin.x, destMax.x),\\\\n\\\\t\\\\tfit(val.y, srcMin.y, srcMax.y, destMin.y, destMax.y),\\\\n\\\\t\\\\tfit(val.z, srcMin.z, srcMax.z, destMin.z, destMax.z)\\\\n\\\\t);\\\\n}\\\\nvec4 fit(vec4 val, vec4 srcMin, vec4 srcMax, vec4 destMin, vec4 destMax){\\\\n\\\\treturn vec4(\\\\n\\\\t\\\\tfit(val.x, srcMin.x, srcMax.x, destMin.x, destMax.x),\\\\n\\\\t\\\\tfit(val.y, srcMin.y, srcMax.y, destMin.y, destMax.y),\\\\n\\\\t\\\\tfit(val.z, srcMin.z, srcMax.z, destMin.z, destMax.z),\\\\n\\\\t\\\\tfit(val.w, srcMin.w, srcMax.w, destMin.w, destMax.w)\\\\n\\\\t);\\\\n}\\\\n\\\\n//\\\\n//\\\\n// FIT TO 01\\\\n// fits the range [srcMin, srcMax] to [0, 1]\\\\n//\\\\nfloat fitTo01(float val, float srcMin, float srcMax){\\\\n\\\\tfloat size = srcMax - srcMin;\\\\n\\\\treturn (val - srcMin) / size;\\\\n}\\\\nvec2 fitTo01(vec2 val, vec2 srcMin, vec2 srcMax){\\\\n\\\\treturn vec2(\\\\n\\\\t\\\\tfitTo01(val.x, srcMin.x, srcMax.x),\\\\n\\\\t\\\\tfitTo01(val.y, srcMin.y, srcMax.y)\\\\n\\\\t);\\\\n}\\\\nvec3 fitTo01(vec3 val, vec3 srcMin, vec3 srcMax){\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\tfitTo01(val.x, srcMin.x, srcMax.x),\\\\n\\\\t\\\\tfitTo01(val.y, srcMin.y, srcMax.y),\\\\n\\\\t\\\\tfitTo01(val.z, srcMin.z, srcMax.z)\\\\n\\\\t);\\\\n}\\\\nvec4 fitTo01(vec4 val, vec4 srcMin, vec4 srcMax){\\\\n\\\\treturn vec4(\\\\n\\\\t\\\\tfitTo01(val.x, srcMin.x, srcMax.x),\\\\n\\\\t\\\\tfitTo01(val.y, srcMin.y, srcMax.y),\\\\n\\\\t\\\\tfitTo01(val.z, srcMin.z, srcMax.z),\\\\n\\\\t\\\\tfitTo01(val.w, srcMin.w, srcMax.w)\\\\n\\\\t);\\\\n}\\\\n\\\\n//\\\\n//\\\\n// FIT FROM 01\\\\n// fits the range [0, 1] to [destMin, destMax]\\\\n//\\\\nfloat fitFrom01(float val, float destMin, float destMax){\\\\n\\\\treturn fit(val, 0.0, 1.0, destMin, destMax);\\\\n}\\\\nvec2 fitFrom01(vec2 val, vec2 srcMin, vec2 srcMax){\\\\n\\\\treturn vec2(\\\\n\\\\t\\\\tfitFrom01(val.x, srcMin.x, srcMax.x),\\\\n\\\\t\\\\tfitFrom01(val.y, srcMin.y, srcMax.y)\\\\n\\\\t);\\\\n}\\\\nvec3 fitFrom01(vec3 val, vec3 srcMin, vec3 srcMax){\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\tfitFrom01(val.x, srcMin.x, srcMax.x),\\\\n\\\\t\\\\tfitFrom01(val.y, srcMin.y, srcMax.y),\\\\n\\\\t\\\\tfitFrom01(val.z, srcMin.z, srcMax.z)\\\\n\\\\t);\\\\n}\\\\nvec4 fitFrom01(vec4 val, vec4 srcMin, vec4 srcMax){\\\\n\\\\treturn vec4(\\\\n\\\\t\\\\tfitFrom01(val.x, srcMin.x, srcMax.x),\\\\n\\\\t\\\\tfitFrom01(val.y, srcMin.y, srcMax.y),\\\\n\\\\t\\\\tfitFrom01(val.z, srcMin.z, srcMax.z),\\\\n\\\\t\\\\tfitFrom01(val.w, srcMin.w, srcMax.w)\\\\n\\\\t);\\\\n}\\\\n\\\\n//\\\\n//\\\\n// FIT FROM 01 TO VARIANCE\\\\n// fits the range [0, 1] to [center - variance, center + variance]\\\\n//\\\\nfloat fitFrom01ToVariance(float val, float center, float variance){\\\\n\\\\treturn fitFrom01(val, center - variance, center + variance);\\\\n}\\\\nvec2 fitFrom01ToVariance(vec2 val, vec2 center, vec2 variance){\\\\n\\\\treturn vec2(\\\\n\\\\t\\\\tfitFrom01ToVariance(val.x, center.x, variance.x),\\\\n\\\\t\\\\tfitFrom01ToVariance(val.y, center.y, variance.y)\\\\n\\\\t);\\\\n}\\\\nvec3 fitFrom01ToVariance(vec3 val, vec3 center, vec3 variance){\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\tfitFrom01ToVariance(val.x, center.x, variance.x),\\\\n\\\\t\\\\tfitFrom01ToVariance(val.y, center.y, variance.y),\\\\n\\\\t\\\\tfitFrom01ToVariance(val.z, center.z, variance.z)\\\\n\\\\t);\\\\n}\\\\nvec4 fitFrom01ToVariance(vec4 val, vec4 center, vec4 variance){\\\\n\\\\treturn vec4(\\\\n\\\\t\\\\tfitFrom01ToVariance(val.x, center.x, variance.x),\\\\n\\\\t\\\\tfitFrom01ToVariance(val.y, center.y, variance.y),\\\\n\\\\t\\\\tfitFrom01ToVariance(val.z, center.z, variance.z),\\\\n\\\\t\\\\tfitFrom01ToVariance(val.w, center.w, variance.w)\\\\n\\\\t);\\\\n}\\\\\\\";const hI={srcMin:0,srcMax:1,destMin:0,destMax:1};class uI extends LP{static type(){return\\\\\\\"fit\\\\\\\"}_gl_input_name(t){return[\\\\\\\"val\\\\\\\",\\\\\\\"srcMin\\\\\\\",\\\\\\\"srcMax\\\\\\\",\\\\\\\"destMin\\\\\\\",\\\\\\\"destMax\\\\\\\"][t]}paramDefaultValue(t){return hI[t]}gl_method_name(){return\\\\\\\"fit\\\\\\\"}gl_function_definitions(){return[new Cf(this,cI)]}}const dI={srcMin:0,srcMax:1};class pI extends CP{static type(){return\\\\\\\"fitTo01\\\\\\\"}_gl_input_name(t){return[\\\\\\\"val\\\\\\\",\\\\\\\"srcMin\\\\\\\",\\\\\\\"srcMax\\\\\\\"][t]}paramDefaultValue(t){return dI[t]}gl_method_name(){return\\\\\\\"fitTo01\\\\\\\"}gl_function_definitions(){return[new Cf(this,cI)]}}const _I={destMin:0,destMax:1};class mI extends CP{static type(){return\\\\\\\"fitFrom01\\\\\\\"}_gl_input_name(t){return[\\\\\\\"val\\\\\\\",\\\\\\\"destMin\\\\\\\",\\\\\\\"destMax\\\\\\\"][t]}paramDefaultValue(t){return _I[t]}gl_method_name(){return\\\\\\\"fitFrom01\\\\\\\"}gl_function_definitions(){return[new Cf(this,cI)]}}const fI={center:.5,variance:.5};class gI extends CP{static type(){return\\\\\\\"fitFrom01ToVariance\\\\\\\"}_gl_input_name(t){return[\\\\\\\"val\\\\\\\",\\\\\\\"center\\\\\\\",\\\\\\\"variance\\\\\\\"][t]}paramDefaultValue(t){return fI[t]}gl_method_name(){return\\\\\\\"fitFrom01ToVariance\\\\\\\"}gl_function_definitions(){return[new Cf(this,cI)]}}const vI=\\\\\\\"color\\\\\\\";const yI=new class extends ua{constructor(){super(...arguments),this.mvPosition=ha.VECTOR4([0,0,0,0]),this.baseColor=ha.COLOR([0,0,0]),this.fogColor=ha.COLOR([1,1,1]),this.near=ha.FLOAT(0),this.far=ha.FLOAT(0)}};class xI extends gf{constructor(){super(...arguments),this.paramsConfig=yI}static type(){return\\\\\\\"fog\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo(vI,Uo.VEC3)])}setLines(t){if(t.current_shader_name==Mf.FRAGMENT){const e=this.glVarName(this.name()),n=new Lf(this,Uo.VEC4,e),i=`${e} = modelViewMatrix * vec4(position, 1.0)`;t.addDefinitions(this,[n],Mf.VERTEX),t.addBodyLines(this,[i],Mf.VERTEX);const s=new Cf(this,\\\\\\\"vec3 compute_fog(vec4 mvPosition, vec3 base_color, vec3 fog_color, float near, float far) {\\\\n\\\\tfloat blend = (-mvPosition.z - near) / (far - near);\\\\n\\\\tblend = clamp(blend, 0.0, 1.0);\\\\n\\\\treturn blend * fog_color + (1.0 - blend) * base_color;\\\\n}\\\\\\\"),r=mf.vector4(this.variableForInputParam(this.p.mvPosition)),o=mf.vector3(this.variableForInputParam(this.p.baseColor)),a=mf.vector3(this.variableForInputParam(this.p.fogColor)),l=mf.vector3(this.variableForInputParam(this.p.near)),c=mf.vector3(this.variableForInputParam(this.p.far)),h=`vec3 ${this.glVarName(vI)} = compute_fog(${[r,o,a,l,c].join(\\\\\\\", \\\\\\\")})`;t.addDefinitions(this,[n,s]),t.addBodyLines(this,[h])}}}const bI=new class extends ua{};class wI extends gf{constructor(){super(...arguments),this.paramsConfig=bI}static type(){return ns.OUTPUT}initializeNode(){this.io.connection_points.set_input_name_function(this._expected_input_name.bind(this)),this.io.connection_points.set_expected_output_types_function((()=>[])),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_create_spare_params_from_inputs(!1),this.addPostDirtyHook(\\\\\\\"setParentDirty\\\\\\\",(()=>{var t;null===(t=this.parent())||void 0===t||t.setDirty(this)}))}parent(){return super.parent()}_expected_input_name(t){const e=this.parent();return(null==e?void 0:e.child_expected_output_connection_point_name(t))||`in${t}`}_expected_input_types(){const t=this.parent();return(null==t?void 0:t.child_expected_output_connection_point_types())||[]}setLines(t){const e=this.parent();if(!e)return;const n=[],i=this.io.connections.inputConnections();if(i)for(let t of i)if(t){const i=t.dest_connection_point(),s=mf.any(this.variableForInput(i.name())),r=`\\\\t${e.glVarName(i.name())} = ${s}`;n.push(r)}t.addBodyLines(this,n),e.set_lines_block_end(t,this)}}class TI extends gf{constructor(){super(...arguments),this._children_controller_context=ts.GL}initializeNode(){var t;null===(t=this.childrenController)||void 0===t||t.set_output_node_find_method((()=>this.nodesByType(wI.type())[0])),this.io.connection_points.set_input_name_function(this._expected_input_name.bind(this)),this.io.connection_points.set_output_name_function(this._expected_output_name.bind(this)),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this))}_expected_inputs_count(){const t=this.io.connections.inputConnections();return t?t.length+1:1}_expected_input_types(){const t=[],e=Uo.FLOAT,n=this.io.connections.inputConnections(),i=this._expected_inputs_count();for(let s=0;s=0){const e=t.dest_connection_point(),i=mf.any(this.variableForInput(e.name())),s=`${e.type()} ${this.glVarName(e.name())} = ${i}`;n.push(s)}const r=this.pv.start,o=this.pv.max,a=this.pv.step,l=mf.float(r),c=mf.float(o),h=mf.float(a),u=this.glVarName(\\\\\\\"i\\\\\\\"),d=`for(float ${u} = ${l}; ${u} < ${c}; ${u}+= ${h}){`;n.push(d);const p=`\\\\tfloat ${e.glVarName(EI.START_INDEX)} = ${u}`;if(n.push(p),s)for(let t of s)if(t&&t.input_index>=0){const i=t.dest_connection_point(),s=this.glVarName(i.name()),r=`\\\\t${i.type()} ${e.glVarName(i.name())} = ${s}`;n.push(r)}t.addBodyLines(e,n)}setLines(t){}}const LI=new class extends ua{};class OI extends gf{constructor(){super(...arguments),this.paramsConfig=LI}static type(){return\\\\\\\"globals\\\\\\\"}initializeNode(){super.initializeNode(),this.lifecycle.add_on_add_hook((()=>{var t,e;null===(e=null===(t=this.material_node)||void 0===t?void 0:t.assemblerController)||void 0===e||e.add_globals_outputs(this)}))}setLines(t){t.assembler().set_node_lines_globals(this,t)}}const PI=new class extends ua{constructor(){super(...arguments),this.hsluv=ha.VECTOR3([1,1,1])}};class RI extends gf{constructor(){super(...arguments),this.paramsConfig=PI}static type(){return\\\\\\\"hsluvToRgb\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"rgb\\\\\\\",Uo.VEC3)])}setLines(t){const e=[],n=[];e.push(new Cf(this,\\\\\\\"// from https://github.com/williammalo/hsluv-glsl\\\\n/*\\\\nHSLUV-GLSL v4.2\\\\nHSLUV is a human-friendly alternative to HSL. ( http://www.hsluv.org )\\\\nGLSL port by William Malo ( https://github.com/williammalo )\\\\nPut this code in your fragment shader.\\\\n*/\\\\n\\\\nvec3 hsluv_intersectLineLine(vec3 line1x, vec3 line1y, vec3 line2x, vec3 line2y) {\\\\n\\\\treturn (line1y - line2y) / (line2x - line1x);\\\\n}\\\\n\\\\nvec3 hsluv_distanceFromPole(vec3 pointx,vec3 pointy) {\\\\n\\\\treturn sqrt(pointx*pointx + pointy*pointy);\\\\n}\\\\n\\\\nvec3 hsluv_lengthOfRayUntilIntersect(float theta, vec3 x, vec3 y) {\\\\n\\\\tvec3 len = y / (sin(theta) - x * cos(theta));\\\\n\\\\tif (len.r < 0.0) {len.r=1000.0;}\\\\n\\\\tif (len.g < 0.0) {len.g=1000.0;}\\\\n\\\\tif (len.b < 0.0) {len.b=1000.0;}\\\\n\\\\treturn len;\\\\n}\\\\n\\\\nfloat hsluv_maxSafeChromaForL(float L){\\\\n\\\\tmat3 m2 = mat3(\\\\n\\\\t\\\\t 3.2409699419045214 ,-0.96924363628087983 , 0.055630079696993609,\\\\n\\\\t\\\\t-1.5373831775700935 , 1.8759675015077207 ,-0.20397695888897657 ,\\\\n\\\\t\\\\t-0.49861076029300328 , 0.041555057407175613, 1.0569715142428786 \\\\n\\\\t);\\\\n\\\\tfloat sub0 = L + 16.0;\\\\n\\\\tfloat sub1 = sub0 * sub0 * sub0 * .000000641;\\\\n\\\\tfloat sub2 = sub1 > 0.0088564516790356308 ? sub1 : L / 903.2962962962963;\\\\n\\\\n\\\\tvec3 top1 = (284517.0 * m2[0] - 94839.0 * m2[2]) * sub2;\\\\n\\\\tvec3 bottom = (632260.0 * m2[2] - 126452.0 * m2[1]) * sub2;\\\\n\\\\tvec3 top2 = (838422.0 * m2[2] + 769860.0 * m2[1] + 731718.0 * m2[0]) * L * sub2;\\\\n\\\\n\\\\tvec3 bounds0x = top1 / bottom;\\\\n\\\\tvec3 bounds0y = top2 / bottom;\\\\n\\\\n\\\\tvec3 bounds1x = top1 / (bottom+126452.0);\\\\n\\\\tvec3 bounds1y = (top2-769860.0*L) / (bottom+126452.0);\\\\n\\\\n\\\\tvec3 xs0 = hsluv_intersectLineLine(bounds0x, bounds0y, -1.0/bounds0x, vec3(0.0) );\\\\n\\\\tvec3 xs1 = hsluv_intersectLineLine(bounds1x, bounds1y, -1.0/bounds1x, vec3(0.0) );\\\\n\\\\n\\\\tvec3 lengths0 = hsluv_distanceFromPole( xs0, bounds0y + xs0 * bounds0x );\\\\n\\\\tvec3 lengths1 = hsluv_distanceFromPole( xs1, bounds1y + xs1 * bounds1x );\\\\n\\\\n\\\\treturn min(lengths0.r,\\\\n\\\\t\\\\t\\\\tmin(lengths1.r,\\\\n\\\\t\\\\t\\\\tmin(lengths0.g,\\\\n\\\\t\\\\t\\\\tmin(lengths1.g,\\\\n\\\\t\\\\t\\\\tmin(lengths0.b,\\\\n\\\\t\\\\t\\\\t\\\\tlengths1.b)))));\\\\n}\\\\n\\\\nfloat hsluv_maxChromaForLH(float L, float H) {\\\\n\\\\n\\\\tfloat hrad = radians(H);\\\\n\\\\n\\\\tmat3 m2 = mat3(\\\\n\\\\t\\\\t 3.2409699419045214 ,-0.96924363628087983 , 0.055630079696993609,\\\\n\\\\t\\\\t-1.5373831775700935 , 1.8759675015077207 ,-0.20397695888897657 ,\\\\n\\\\t\\\\t-0.49861076029300328 , 0.041555057407175613, 1.0569715142428786 \\\\n\\\\t);\\\\n\\\\tfloat sub1 = pow(L + 16.0, 3.0) / 1560896.0;\\\\n\\\\tfloat sub2 = sub1 > 0.0088564516790356308 ? sub1 : L / 903.2962962962963;\\\\n\\\\n\\\\tvec3 top1 = (284517.0 * m2[0] - 94839.0 * m2[2]) * sub2;\\\\n\\\\tvec3 bottom = (632260.0 * m2[2] - 126452.0 * m2[1]) * sub2;\\\\n\\\\tvec3 top2 = (838422.0 * m2[2] + 769860.0 * m2[1] + 731718.0 * m2[0]) * L * sub2;\\\\n\\\\n\\\\tvec3 bound0x = top1 / bottom;\\\\n\\\\tvec3 bound0y = top2 / bottom;\\\\n\\\\n\\\\tvec3 bound1x = top1 / (bottom+126452.0);\\\\n\\\\tvec3 bound1y = (top2-769860.0*L) / (bottom+126452.0);\\\\n\\\\n\\\\tvec3 lengths0 = hsluv_lengthOfRayUntilIntersect(hrad, bound0x, bound0y );\\\\n\\\\tvec3 lengths1 = hsluv_lengthOfRayUntilIntersect(hrad, bound1x, bound1y );\\\\n\\\\n\\\\treturn min(lengths0.r,\\\\n\\\\t\\\\t\\\\tmin(lengths1.r,\\\\n\\\\t\\\\t\\\\tmin(lengths0.g,\\\\n\\\\t\\\\t\\\\tmin(lengths1.g,\\\\n\\\\t\\\\t\\\\tmin(lengths0.b,\\\\n\\\\t\\\\t\\\\t\\\\tlengths1.b)))));\\\\n}\\\\n\\\\nfloat hsluv_fromLinear(float c) {\\\\n\\\\treturn c <= 0.0031308 ? 12.92 * c : 1.055 * pow(c, 1.0 / 2.4) - 0.055;\\\\n}\\\\nvec3 hsluv_fromLinear(vec3 c) {\\\\n\\\\treturn vec3( hsluv_fromLinear(c.r), hsluv_fromLinear(c.g), hsluv_fromLinear(c.b) );\\\\n}\\\\n\\\\nfloat hsluv_toLinear(float c) {\\\\n\\\\treturn c > 0.04045 ? pow((c + 0.055) / (1.0 + 0.055), 2.4) : c / 12.92;\\\\n}\\\\n\\\\nvec3 hsluv_toLinear(vec3 c) {\\\\n\\\\treturn vec3( hsluv_toLinear(c.r), hsluv_toLinear(c.g), hsluv_toLinear(c.b) );\\\\n}\\\\n\\\\nfloat hsluv_yToL(float Y){\\\\n\\\\treturn Y <= 0.0088564516790356308 ? Y * 903.2962962962963 : 116.0 * pow(Y, 1.0 / 3.0) - 16.0;\\\\n}\\\\n\\\\nfloat hsluv_lToY(float L) {\\\\n\\\\treturn L <= 8.0 ? L / 903.2962962962963 : pow((L + 16.0) / 116.0, 3.0);\\\\n}\\\\n\\\\nvec3 xyzToRgb(vec3 tuple) {\\\\n\\\\tconst mat3 m = mat3( \\\\n\\\\t\\\\t3.2409699419045214 ,-1.5373831775700935 ,-0.49861076029300328 ,\\\\n\\\\t\\\\t-0.96924363628087983 , 1.8759675015077207 , 0.041555057407175613,\\\\n\\\\t\\\\t0.055630079696993609,-0.20397695888897657, 1.0569715142428786 );\\\\n\\\\t\\\\n\\\\treturn hsluv_fromLinear(tuple*m);\\\\n}\\\\n\\\\nvec3 rgbToXyz(vec3 tuple) {\\\\n\\\\tconst mat3 m = mat3(\\\\n\\\\t\\\\t0.41239079926595948 , 0.35758433938387796, 0.18048078840183429 ,\\\\n\\\\t\\\\t0.21263900587151036 , 0.71516867876775593, 0.072192315360733715,\\\\n\\\\t\\\\t0.019330818715591851, 0.11919477979462599, 0.95053215224966058 \\\\n\\\\t);\\\\n\\\\treturn hsluv_toLinear(tuple) * m;\\\\n}\\\\n\\\\nvec3 xyzToLuv(vec3 tuple){\\\\n\\\\tfloat X = tuple.x;\\\\n\\\\tfloat Y = tuple.y;\\\\n\\\\tfloat Z = tuple.z;\\\\n\\\\n\\\\tfloat L = hsluv_yToL(Y);\\\\n\\\\t\\\\n\\\\tfloat div = 1./dot(tuple,vec3(1,15,3)); \\\\n\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\t1.,\\\\n\\\\t\\\\t(52. * (X*div) - 2.57179),\\\\n\\\\t\\\\t(117.* (Y*div) - 6.08816)\\\\n\\\\t) * L;\\\\n}\\\\n\\\\n\\\\nvec3 luvToXyz(vec3 tuple) {\\\\n\\\\tfloat L = tuple.x;\\\\n\\\\n\\\\tfloat U = tuple.y / (13.0 * L) + 0.19783000664283681;\\\\n\\\\tfloat V = tuple.z / (13.0 * L) + 0.468319994938791;\\\\n\\\\n\\\\tfloat Y = hsluv_lToY(L);\\\\n\\\\tfloat X = 2.25 * U * Y / V;\\\\n\\\\tfloat Z = (3./V - 5.)*Y - (X/3.);\\\\n\\\\n\\\\treturn vec3(X, Y, Z);\\\\n}\\\\n\\\\nvec3 luvToLch(vec3 tuple) {\\\\n\\\\tfloat L = tuple.x;\\\\n\\\\tfloat U = tuple.y;\\\\n\\\\tfloat V = tuple.z;\\\\n\\\\n\\\\tfloat C = length(tuple.yz);\\\\n\\\\tfloat H = degrees(atan(V,U));\\\\n\\\\tif (H < 0.0) {\\\\n\\\\t\\\\tH = 360.0 + H;\\\\n\\\\t}\\\\n\\\\t\\\\n\\\\treturn vec3(L, C, H);\\\\n}\\\\n\\\\nvec3 lchToLuv(vec3 tuple) {\\\\n\\\\tfloat hrad = radians(tuple.b);\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\ttuple.r,\\\\n\\\\t\\\\tcos(hrad) * tuple.g,\\\\n\\\\t\\\\tsin(hrad) * tuple.g\\\\n\\\\t);\\\\n}\\\\n\\\\nvec3 hsluvToLch(vec3 tuple) {\\\\n\\\\ttuple.g *= hsluv_maxChromaForLH(tuple.b, tuple.r) * .01;\\\\n\\\\treturn tuple.bgr;\\\\n}\\\\n\\\\nvec3 lchToHsluv(vec3 tuple) {\\\\n\\\\ttuple.g /= hsluv_maxChromaForLH(tuple.r, tuple.b) * .01;\\\\n\\\\treturn tuple.bgr;\\\\n}\\\\n\\\\nvec3 hpluvToLch(vec3 tuple) {\\\\n\\\\ttuple.g *= hsluv_maxSafeChromaForL(tuple.b) * .01;\\\\n\\\\treturn tuple.bgr;\\\\n}\\\\n\\\\nvec3 lchToHpluv(vec3 tuple) {\\\\n\\\\ttuple.g /= hsluv_maxSafeChromaForL(tuple.r) * .01;\\\\n\\\\treturn tuple.bgr;\\\\n}\\\\n\\\\nvec3 lchToRgb(vec3 tuple) {\\\\n\\\\treturn xyzToRgb(luvToXyz(lchToLuv(tuple)));\\\\n}\\\\n\\\\nvec3 rgbToLch(vec3 tuple) {\\\\n\\\\treturn luvToLch(xyzToLuv(rgbToXyz(tuple)));\\\\n}\\\\n\\\\nvec3 hsluvToRgb(vec3 tuple) {\\\\n\\\\treturn lchToRgb(hsluvToLch(tuple));\\\\n}\\\\n\\\\nvec3 rgbToHsluv(vec3 tuple) {\\\\n\\\\treturn lchToHsluv(rgbToLch(tuple));\\\\n}\\\\n\\\\nvec3 hpluvToRgb(vec3 tuple) {\\\\n\\\\treturn lchToRgb(hpluvToLch(tuple));\\\\n}\\\\n\\\\nvec3 rgbToHpluv(vec3 tuple) {\\\\n\\\\treturn lchToHpluv(rgbToLch(tuple));\\\\n}\\\\n\\\\nvec3 luvToRgb(vec3 tuple){\\\\n\\\\treturn xyzToRgb(luvToXyz(tuple));\\\\n}\\\\n\\\\n// allow vec4's\\\\nvec4 xyzToRgb(vec4 c) {return vec4( xyzToRgb( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 rgbToXyz(vec4 c) {return vec4( rgbToXyz( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 xyzToLuv(vec4 c) {return vec4( xyzToLuv( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 luvToXyz(vec4 c) {return vec4( luvToXyz( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 luvToLch(vec4 c) {return vec4( luvToLch( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 lchToLuv(vec4 c) {return vec4( lchToLuv( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 hsluvToLch(vec4 c) {return vec4( hsluvToLch( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 lchToHsluv(vec4 c) {return vec4( lchToHsluv( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 hpluvToLch(vec4 c) {return vec4( hpluvToLch( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 lchToHpluv(vec4 c) {return vec4( lchToHpluv( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 lchToRgb(vec4 c) {return vec4( lchToRgb( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 rgbToLch(vec4 c) {return vec4( rgbToLch( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 hsluvToRgb(vec4 c) {return vec4( hsluvToRgb( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 rgbToHsluv(vec4 c) {return vec4( rgbToHsluv( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 hpluvToRgb(vec4 c) {return vec4( hpluvToRgb( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 rgbToHpluv(vec4 c) {return vec4( rgbToHpluv( vec3(c.x,c.y,c.z) ), c.a);}\\\\nvec4 luvToRgb(vec4 c) {return vec4( luvToRgb( vec3(c.x,c.y,c.z) ), c.a);}\\\\n// allow 3 floats\\\\nvec3 xyzToRgb(float x, float y, float z) {return xyzToRgb( vec3(x,y,z) );}\\\\nvec3 rgbToXyz(float x, float y, float z) {return rgbToXyz( vec3(x,y,z) );}\\\\nvec3 xyzToLuv(float x, float y, float z) {return xyzToLuv( vec3(x,y,z) );}\\\\nvec3 luvToXyz(float x, float y, float z) {return luvToXyz( vec3(x,y,z) );}\\\\nvec3 luvToLch(float x, float y, float z) {return luvToLch( vec3(x,y,z) );}\\\\nvec3 lchToLuv(float x, float y, float z) {return lchToLuv( vec3(x,y,z) );}\\\\nvec3 hsluvToLch(float x, float y, float z) {return hsluvToLch( vec3(x,y,z) );}\\\\nvec3 lchToHsluv(float x, float y, float z) {return lchToHsluv( vec3(x,y,z) );}\\\\nvec3 hpluvToLch(float x, float y, float z) {return hpluvToLch( vec3(x,y,z) );}\\\\nvec3 lchToHpluv(float x, float y, float z) {return lchToHpluv( vec3(x,y,z) );}\\\\nvec3 lchToRgb(float x, float y, float z) {return lchToRgb( vec3(x,y,z) );}\\\\nvec3 rgbToLch(float x, float y, float z) {return rgbToLch( vec3(x,y,z) );}\\\\nvec3 hsluvToRgb(float x, float y, float z) {return hsluvToRgb( vec3(x,y,z) );}\\\\nvec3 rgbToHsluv(float x, float y, float z) {return rgbToHsluv( vec3(x,y,z) );}\\\\nvec3 hpluvToRgb(float x, float y, float z) {return hpluvToRgb( vec3(x,y,z) );}\\\\nvec3 rgbToHpluv(float x, float y, float z) {return rgbToHpluv( vec3(x,y,z) );}\\\\nvec3 luvToRgb(float x, float y, float z) {return luvToRgb( vec3(x,y,z) );}\\\\n// allow 4 floats\\\\nvec4 xyzToRgb(float x, float y, float z, float a) {return xyzToRgb( vec4(x,y,z,a) );}\\\\nvec4 rgbToXyz(float x, float y, float z, float a) {return rgbToXyz( vec4(x,y,z,a) );}\\\\nvec4 xyzToLuv(float x, float y, float z, float a) {return xyzToLuv( vec4(x,y,z,a) );}\\\\nvec4 luvToXyz(float x, float y, float z, float a) {return luvToXyz( vec4(x,y,z,a) );}\\\\nvec4 luvToLch(float x, float y, float z, float a) {return luvToLch( vec4(x,y,z,a) );}\\\\nvec4 lchToLuv(float x, float y, float z, float a) {return lchToLuv( vec4(x,y,z,a) );}\\\\nvec4 hsluvToLch(float x, float y, float z, float a) {return hsluvToLch( vec4(x,y,z,a) );}\\\\nvec4 lchToHsluv(float x, float y, float z, float a) {return lchToHsluv( vec4(x,y,z,a) );}\\\\nvec4 hpluvToLch(float x, float y, float z, float a) {return hpluvToLch( vec4(x,y,z,a) );}\\\\nvec4 lchToHpluv(float x, float y, float z, float a) {return lchToHpluv( vec4(x,y,z,a) );}\\\\nvec4 lchToRgb(float x, float y, float z, float a) {return lchToRgb( vec4(x,y,z,a) );}\\\\nvec4 rgbToLch(float x, float y, float z, float a) {return rgbToLch( vec4(x,y,z,a) );}\\\\nvec4 hsluvToRgb(float x, float y, float z, float a) {return hsluvToRgb( vec4(x,y,z,a) );}\\\\nvec4 rgbToHslul(float x, float y, float z, float a) {return rgbToHsluv( vec4(x,y,z,a) );}\\\\nvec4 hpluvToRgb(float x, float y, float z, float a) {return hpluvToRgb( vec4(x,y,z,a) );}\\\\nvec4 rgbToHpluv(float x, float y, float z, float a) {return rgbToHpluv( vec4(x,y,z,a) );}\\\\nvec4 luvToRgb(float x, float y, float z, float a) {return luvToRgb( vec4(x,y,z,a) );}\\\\n\\\\n/*\\\\nEND HSLUV-GLSL\\\\n*/\\\\n\\\\n\\\\n// from https://gist.github.com/mattatz/44f081cac87e2f7c8980\\\\n// converted to glsl by gui@polygonjs.com\\\\n// and made function names consistent with the ones above\\\\n/*\\\\n * Conversion between RGB and LAB colorspace.\\\\n * Import from flowabs glsl program : https://code.google.com/p/flowabs/source/browse/glsl/?r=f36cbdcf7790a28d90f09e2cf89ec9a64911f138\\\\n */\\\\n\\\\n\\\\n\\\\nvec3 xyzToLab( vec3 c ) {\\\\n\\\\tvec3 n = c / vec3(95.047, 100, 108.883);\\\\n\\\\tvec3 v;\\\\n\\\\tv.x = ( n.x > 0.008856 ) ? pow( n.x, 1.0 / 3.0 ) : ( 7.787 * n.x ) + ( 16.0 / 116.0 );\\\\n\\\\tv.y = ( n.y > 0.008856 ) ? pow( n.y, 1.0 / 3.0 ) : ( 7.787 * n.y ) + ( 16.0 / 116.0 );\\\\n\\\\tv.z = ( n.z > 0.008856 ) ? pow( n.z, 1.0 / 3.0 ) : ( 7.787 * n.z ) + ( 16.0 / 116.0 );\\\\n\\\\treturn vec3(( 116.0 * v.y ) - 16.0, 500.0 * ( v.x - v.y ), 200.0 * ( v.y - v.z ));\\\\n}\\\\n\\\\nvec3 rgbToLab( vec3 c ) {\\\\n\\\\tvec3 lab = xyzToLab( rgbToXyz( c ) );\\\\n\\\\treturn vec3( lab.x / 100.0, 0.5 + 0.5 * ( lab.y / 127.0 ), 0.5 + 0.5 * ( lab.z / 127.0 ));\\\\n}\\\\n\\\\nvec3 labToXyz( vec3 c ) {\\\\n\\\\tfloat fy = ( c.x + 16.0 ) / 116.0;\\\\n\\\\tfloat fx = c.y / 500.0 + fy;\\\\n\\\\tfloat fz = fy - c.z / 200.0;\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\t 95.047 * (( fx > 0.206897 ) ? fx * fx * fx : ( fx - 16.0 / 116.0 ) / 7.787),\\\\n\\\\t\\\\t100.000 * (( fy > 0.206897 ) ? fy * fy * fy : ( fy - 16.0 / 116.0 ) / 7.787),\\\\n\\\\t\\\\t108.883 * (( fz > 0.206897 ) ? fz * fz * fz : ( fz - 16.0 / 116.0 ) / 7.787)\\\\n\\\\t);\\\\n}\\\\n\\\\n\\\\n\\\\nvec3 labToRgb( vec3 c ) {\\\\n\\\\treturn xyzToRgb( labToXyz( vec3(100.0 * c.x, 2.0 * 127.0 * (c.y - 0.5), 2.0 * 127.0 * (c.z - 0.5)) ) );\\\\n}\\\\\\\"));const i=mf.vector3(this.variableForInputParam(this.p.hsluv)),s=this.glVarName(\\\\\\\"rgb\\\\\\\");n.push(`vec3 ${s} = hsluvToRgb(${i}.x * 360.0, ${i}.y * 100.0, ${i}.z * 100.0)`),t.addDefinitions(this,e),t.addBodyLines(this,n)}}const II=new class extends ua{constructor(){super(...arguments),this.hsv=ha.VECTOR3([1,1,1])}};class FI extends gf{constructor(){super(...arguments),this.paramsConfig=II}static type(){return\\\\\\\"hsvToRgb\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"rgb\\\\\\\",Uo.VEC3)])}setLines(t){const e=[],n=[];e.push(new Cf(this,\\\\\\\"// https://github.com/hughsk/glsl-hsv2rgb\\\\n// https://stackoverflow.com/questions/15095909/from-rgb-to-hsv-in-opengl-glsl\\\\nvec3 hsv2rgb(vec3 c) {\\\\n\\\\tvec4 K = vec4(1.0, 2.0 / 3.0, 1.0 / 3.0, 3.0);\\\\n\\\\tvec3 p = abs(fract(c.xxx + K.xyz) * 6.0 - K.www);\\\\n\\\\treturn c.z * mix(K.xxx, clamp(p - K.xxx, 0.0, 1.0), c.y);\\\\n}\\\\\\\"));const i=mf.vector3(this.variableForInputParam(this.p.hsv)),s=this.glVarName(\\\\\\\"rgb\\\\\\\");n.push(`vec3 ${s} = hsv2rgb(${i})`),t.addDefinitions(this,e),t.addBodyLines(this,n)}}const DI=\\\\\\\"condition\\\\\\\";const BI=new class extends ua{};class zI extends MI{constructor(){super(...arguments),this.paramsConfig=BI}static type(){return\\\\\\\"ifThen\\\\\\\"}_expected_inputs_count(){const t=this.io.connections.inputConnections();return t?Math.max(t.length+1,2):2}_expected_input_types(){const t=[Uo.BOOL],e=Uo.FLOAT,n=this.io.connections.inputConnections(),i=this._expected_inputs_count();for(let s=1;s[\\\\\\\"value0\\\\\\\",\\\\\\\"value1\\\\\\\",\\\\\\\"blend\\\\\\\"][t])),this.io.connection_points.set_output_name_function(this._gl_output_name.bind(this)),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this))}_gl_output_name(){return\\\\\\\"mix\\\\\\\"}_expected_input_types(){const t=this.io.connection_points.first_input_connection_type()||Uo.FLOAT;return[t,t,Uo.FLOAT]}_expected_output_types(){return[this._expected_input_types()[0]]}}const eF=\\\\\\\"mvMult\\\\\\\";const nF=new class extends ua{constructor(){super(...arguments),this.vector=ha.VECTOR3([0,0,0])}};class iF extends gf{constructor(){super(...arguments),this.paramsConfig=nF}static type(){return\\\\\\\"modelViewMatrixMult\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo(eF,Uo.VEC4)])}setLines(t){if(t.current_shader_name==Mf.VERTEX){const e=mf.vector3(this.variableForInputParam(this.p.vector)),n=`vec4 ${this.glVarName(eF)} = modelViewMatrix * vec4(${e}, 1.0)`;t.addBodyLines(this,[n],Mf.VERTEX)}}}const sF={mult:1};var rF;!function(t){t.VALUE=\\\\\\\"value\\\\\\\",t.PRE_ADD=\\\\\\\"preAdd\\\\\\\",t.MULT=\\\\\\\"mult\\\\\\\",t.POST_ADD=\\\\\\\"postAdd\\\\\\\"}(rF||(rF={}));class oF extends NP{static type(){return\\\\\\\"multAdd\\\\\\\"}_gl_input_name(t){return[rF.VALUE,rF.PRE_ADD,rF.MULT,rF.POST_ADD][t]}paramDefaultValue(t){return sF[t]}setLines(t){const e=mf.any(this.variableForInput(rF.VALUE)),n=mf.any(this.variableForInput(rF.PRE_ADD)),i=mf.any(this.variableForInput(rF.MULT)),s=mf.any(this.variableForInput(rF.POST_ADD)),r=this._expected_output_types()[0],o=this.io.outputs.namedOutputConnectionPoints()[0].name(),a=`${r} ${this.glVarName(o)} = (${i}*(${e} + ${n})) + ${s}`;t.addBodyLines(this,[a])}}class aF extends EP{static type(){return\\\\\\\"negate\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function((t=>[\\\\\\\"in\\\\\\\"][t]))}_gl_input_name(t){return[\\\\\\\"in\\\\\\\"][t]}setLines(t){const e=mf.any(this.variableForInput(this._gl_input_name(0))),n=`${this.io.inputs.namedInputConnectionPoints()[0].type()} ${this.glVarName(this.io.connection_points.output_name(0))} = -1.0 * ${e}`;t.addBodyLines(this,[n])}}var lF;!function(t){t.CLASSIC_PERLIN_2D=\\\\\\\"Classic Perlin 2D\\\\\\\",t.CLASSIC_PERLIN_3D=\\\\\\\"Classic Perlin 3D\\\\\\\",t.CLASSIC_PERLIN_4D=\\\\\\\"Classic Perlin 4D\\\\\\\",t.NOISE_2D=\\\\\\\"noise2D\\\\\\\",t.NOISE_3D=\\\\\\\"noise3D\\\\\\\",t.NOISE_4D=\\\\\\\"noise4D\\\\\\\"}(lF||(lF={}));const cF=[lF.CLASSIC_PERLIN_2D,lF.CLASSIC_PERLIN_3D,lF.CLASSIC_PERLIN_4D,lF.NOISE_2D,lF.NOISE_3D,lF.NOISE_4D],hF={[lF.CLASSIC_PERLIN_2D]:'//\\\\n// GLSL textureless classic 2D noise \\\\\\\"cnoise\\\\\\\",\\\\n// with an RSL-style periodic variant \\\\\\\"pnoise\\\\\\\".\\\\n// Author: Stefan Gustavson (stefan.gustavson@liu.se)\\\\n// Version: 2011-08-22\\\\n//\\\\n// Many thanks to Ian McEwan of Ashima Arts for the\\\\n// ideas for permutation and gradient selection.\\\\n//\\\\n// Copyright (c) 2011 Stefan Gustavson. All rights reserved.\\\\n// Distributed under the MIT license. See LICENSE file.\\\\n// https://github.com/stegu/webgl-noise\\\\n//\\\\n\\\\n\\\\n// Classic Perlin noise\\\\nfloat cnoise(vec2 P)\\\\n{\\\\n vec4 Pi = floor(P.xyxy) + vec4(0.0, 0.0, 1.0, 1.0);\\\\n vec4 Pf = fract(P.xyxy) - vec4(0.0, 0.0, 1.0, 1.0);\\\\n Pi = mod289(Pi); // To avoid truncation effects in permutation\\\\n vec4 ix = Pi.xzxz;\\\\n vec4 iy = Pi.yyww;\\\\n vec4 fx = Pf.xzxz;\\\\n vec4 fy = Pf.yyww;\\\\n\\\\n vec4 i = permute(permute(ix) + iy);\\\\n\\\\n vec4 gx = fract(i * (1.0 / 41.0)) * 2.0 - 1.0 ;\\\\n vec4 gy = abs(gx) - 0.5 ;\\\\n vec4 tx = floor(gx + 0.5);\\\\n gx = gx - tx;\\\\n\\\\n vec2 g00 = vec2(gx.x,gy.x);\\\\n vec2 g10 = vec2(gx.y,gy.y);\\\\n vec2 g01 = vec2(gx.z,gy.z);\\\\n vec2 g11 = vec2(gx.w,gy.w);\\\\n\\\\n vec4 norm = taylorInvSqrt(vec4(dot(g00, g00), dot(g01, g01), dot(g10, g10), dot(g11, g11)));\\\\n g00 *= norm.x; \\\\n g01 *= norm.y; \\\\n g10 *= norm.z; \\\\n g11 *= norm.w; \\\\n\\\\n float n00 = dot(g00, vec2(fx.x, fy.x));\\\\n float n10 = dot(g10, vec2(fx.y, fy.y));\\\\n float n01 = dot(g01, vec2(fx.z, fy.z));\\\\n float n11 = dot(g11, vec2(fx.w, fy.w));\\\\n\\\\n vec2 fade_xy = fade(Pf.xy);\\\\n vec2 n_x = mix(vec2(n00, n01), vec2(n10, n11), fade_xy.x);\\\\n float n_xy = mix(n_x.x, n_x.y, fade_xy.y);\\\\n return 2.3 * n_xy;\\\\n}\\\\n\\\\n// Classic Perlin noise, periodic variant\\\\nfloat pnoise(vec2 P, vec2 rep)\\\\n{\\\\n vec4 Pi = floor(P.xyxy) + vec4(0.0, 0.0, 1.0, 1.0);\\\\n vec4 Pf = fract(P.xyxy) - vec4(0.0, 0.0, 1.0, 1.0);\\\\n Pi = mod(Pi, rep.xyxy); // To create noise with explicit period\\\\n Pi = mod289(Pi); // To avoid truncation effects in permutation\\\\n vec4 ix = Pi.xzxz;\\\\n vec4 iy = Pi.yyww;\\\\n vec4 fx = Pf.xzxz;\\\\n vec4 fy = Pf.yyww;\\\\n\\\\n vec4 i = permute(permute(ix) + iy);\\\\n\\\\n vec4 gx = fract(i * (1.0 / 41.0)) * 2.0 - 1.0 ;\\\\n vec4 gy = abs(gx) - 0.5 ;\\\\n vec4 tx = floor(gx + 0.5);\\\\n gx = gx - tx;\\\\n\\\\n vec2 g00 = vec2(gx.x,gy.x);\\\\n vec2 g10 = vec2(gx.y,gy.y);\\\\n vec2 g01 = vec2(gx.z,gy.z);\\\\n vec2 g11 = vec2(gx.w,gy.w);\\\\n\\\\n vec4 norm = taylorInvSqrt(vec4(dot(g00, g00), dot(g01, g01), dot(g10, g10), dot(g11, g11)));\\\\n g00 *= norm.x; \\\\n g01 *= norm.y; \\\\n g10 *= norm.z; \\\\n g11 *= norm.w; \\\\n\\\\n float n00 = dot(g00, vec2(fx.x, fy.x));\\\\n float n10 = dot(g10, vec2(fx.y, fy.y));\\\\n float n01 = dot(g01, vec2(fx.z, fy.z));\\\\n float n11 = dot(g11, vec2(fx.w, fy.w));\\\\n\\\\n vec2 fade_xy = fade(Pf.xy);\\\\n vec2 n_x = mix(vec2(n00, n01), vec2(n10, n11), fade_xy.x);\\\\n float n_xy = mix(n_x.x, n_x.y, fade_xy.y);\\\\n return 2.3 * n_xy;\\\\n}\\\\n',[lF.CLASSIC_PERLIN_3D]:'//\\\\n// GLSL textureless classic 3D noise \\\\\\\"cnoise\\\\\\\",\\\\n// with an RSL-style periodic variant \\\\\\\"pnoise\\\\\\\".\\\\n// Author: Stefan Gustavson (stefan.gustavson@liu.se)\\\\n// Version: 2011-10-11\\\\n//\\\\n// Many thanks to Ian McEwan of Ashima Arts for the\\\\n// ideas for permutation and gradient selection.\\\\n//\\\\n// Copyright (c) 2011 Stefan Gustavson. All rights reserved.\\\\n// Distributed under the MIT license. See LICENSE file.\\\\n// https://github.com/stegu/webgl-noise\\\\n//\\\\n\\\\n// Classic Perlin noise\\\\nfloat cnoise(vec3 P)\\\\n{\\\\n vec3 Pi0 = floor(P); // Integer part for indexing\\\\n vec3 Pi1 = Pi0 + vec3(1.0); // Integer part + 1\\\\n Pi0 = mod289(Pi0);\\\\n Pi1 = mod289(Pi1);\\\\n vec3 Pf0 = fract(P); // Fractional part for interpolation\\\\n vec3 Pf1 = Pf0 - vec3(1.0); // Fractional part - 1.0\\\\n vec4 ix = vec4(Pi0.x, Pi1.x, Pi0.x, Pi1.x);\\\\n vec4 iy = vec4(Pi0.yy, Pi1.yy);\\\\n vec4 iz0 = Pi0.zzzz;\\\\n vec4 iz1 = Pi1.zzzz;\\\\n\\\\n vec4 ixy = permute(permute(ix) + iy);\\\\n vec4 ixy0 = permute(ixy + iz0);\\\\n vec4 ixy1 = permute(ixy + iz1);\\\\n\\\\n vec4 gx0 = ixy0 * (1.0 / 7.0);\\\\n vec4 gy0 = fract(floor(gx0) * (1.0 / 7.0)) - 0.5;\\\\n gx0 = fract(gx0);\\\\n vec4 gz0 = vec4(0.5) - abs(gx0) - abs(gy0);\\\\n vec4 sz0 = step(gz0, vec4(0.0));\\\\n gx0 -= sz0 * (step(0.0, gx0) - 0.5);\\\\n gy0 -= sz0 * (step(0.0, gy0) - 0.5);\\\\n\\\\n vec4 gx1 = ixy1 * (1.0 / 7.0);\\\\n vec4 gy1 = fract(floor(gx1) * (1.0 / 7.0)) - 0.5;\\\\n gx1 = fract(gx1);\\\\n vec4 gz1 = vec4(0.5) - abs(gx1) - abs(gy1);\\\\n vec4 sz1 = step(gz1, vec4(0.0));\\\\n gx1 -= sz1 * (step(0.0, gx1) - 0.5);\\\\n gy1 -= sz1 * (step(0.0, gy1) - 0.5);\\\\n\\\\n vec3 g000 = vec3(gx0.x,gy0.x,gz0.x);\\\\n vec3 g100 = vec3(gx0.y,gy0.y,gz0.y);\\\\n vec3 g010 = vec3(gx0.z,gy0.z,gz0.z);\\\\n vec3 g110 = vec3(gx0.w,gy0.w,gz0.w);\\\\n vec3 g001 = vec3(gx1.x,gy1.x,gz1.x);\\\\n vec3 g101 = vec3(gx1.y,gy1.y,gz1.y);\\\\n vec3 g011 = vec3(gx1.z,gy1.z,gz1.z);\\\\n vec3 g111 = vec3(gx1.w,gy1.w,gz1.w);\\\\n\\\\n vec4 norm0 = taylorInvSqrt(vec4(dot(g000, g000), dot(g010, g010), dot(g100, g100), dot(g110, g110)));\\\\n g000 *= norm0.x;\\\\n g010 *= norm0.y;\\\\n g100 *= norm0.z;\\\\n g110 *= norm0.w;\\\\n vec4 norm1 = taylorInvSqrt(vec4(dot(g001, g001), dot(g011, g011), dot(g101, g101), dot(g111, g111)));\\\\n g001 *= norm1.x;\\\\n g011 *= norm1.y;\\\\n g101 *= norm1.z;\\\\n g111 *= norm1.w;\\\\n\\\\n float n000 = dot(g000, Pf0);\\\\n float n100 = dot(g100, vec3(Pf1.x, Pf0.yz));\\\\n float n010 = dot(g010, vec3(Pf0.x, Pf1.y, Pf0.z));\\\\n float n110 = dot(g110, vec3(Pf1.xy, Pf0.z));\\\\n float n001 = dot(g001, vec3(Pf0.xy, Pf1.z));\\\\n float n101 = dot(g101, vec3(Pf1.x, Pf0.y, Pf1.z));\\\\n float n011 = dot(g011, vec3(Pf0.x, Pf1.yz));\\\\n float n111 = dot(g111, Pf1);\\\\n\\\\n vec3 fade_xyz = fade(Pf0);\\\\n vec4 n_z = mix(vec4(n000, n100, n010, n110), vec4(n001, n101, n011, n111), fade_xyz.z);\\\\n vec2 n_yz = mix(n_z.xy, n_z.zw, fade_xyz.y);\\\\n float n_xyz = mix(n_yz.x, n_yz.y, fade_xyz.x); \\\\n return 2.2 * n_xyz;\\\\n}\\\\n\\\\n// Classic Perlin noise, periodic variant\\\\nfloat pnoise(vec3 P, vec3 rep)\\\\n{\\\\n vec3 Pi0 = mod(floor(P), rep); // Integer part, modulo period\\\\n vec3 Pi1 = mod(Pi0 + vec3(1.0), rep); // Integer part + 1, mod period\\\\n Pi0 = mod289(Pi0);\\\\n Pi1 = mod289(Pi1);\\\\n vec3 Pf0 = fract(P); // Fractional part for interpolation\\\\n vec3 Pf1 = Pf0 - vec3(1.0); // Fractional part - 1.0\\\\n vec4 ix = vec4(Pi0.x, Pi1.x, Pi0.x, Pi1.x);\\\\n vec4 iy = vec4(Pi0.yy, Pi1.yy);\\\\n vec4 iz0 = Pi0.zzzz;\\\\n vec4 iz1 = Pi1.zzzz;\\\\n\\\\n vec4 ixy = permute(permute(ix) + iy);\\\\n vec4 ixy0 = permute(ixy + iz0);\\\\n vec4 ixy1 = permute(ixy + iz1);\\\\n\\\\n vec4 gx0 = ixy0 * (1.0 / 7.0);\\\\n vec4 gy0 = fract(floor(gx0) * (1.0 / 7.0)) - 0.5;\\\\n gx0 = fract(gx0);\\\\n vec4 gz0 = vec4(0.5) - abs(gx0) - abs(gy0);\\\\n vec4 sz0 = step(gz0, vec4(0.0));\\\\n gx0 -= sz0 * (step(0.0, gx0) - 0.5);\\\\n gy0 -= sz0 * (step(0.0, gy0) - 0.5);\\\\n\\\\n vec4 gx1 = ixy1 * (1.0 / 7.0);\\\\n vec4 gy1 = fract(floor(gx1) * (1.0 / 7.0)) - 0.5;\\\\n gx1 = fract(gx1);\\\\n vec4 gz1 = vec4(0.5) - abs(gx1) - abs(gy1);\\\\n vec4 sz1 = step(gz1, vec4(0.0));\\\\n gx1 -= sz1 * (step(0.0, gx1) - 0.5);\\\\n gy1 -= sz1 * (step(0.0, gy1) - 0.5);\\\\n\\\\n vec3 g000 = vec3(gx0.x,gy0.x,gz0.x);\\\\n vec3 g100 = vec3(gx0.y,gy0.y,gz0.y);\\\\n vec3 g010 = vec3(gx0.z,gy0.z,gz0.z);\\\\n vec3 g110 = vec3(gx0.w,gy0.w,gz0.w);\\\\n vec3 g001 = vec3(gx1.x,gy1.x,gz1.x);\\\\n vec3 g101 = vec3(gx1.y,gy1.y,gz1.y);\\\\n vec3 g011 = vec3(gx1.z,gy1.z,gz1.z);\\\\n vec3 g111 = vec3(gx1.w,gy1.w,gz1.w);\\\\n\\\\n vec4 norm0 = taylorInvSqrt(vec4(dot(g000, g000), dot(g010, g010), dot(g100, g100), dot(g110, g110)));\\\\n g000 *= norm0.x;\\\\n g010 *= norm0.y;\\\\n g100 *= norm0.z;\\\\n g110 *= norm0.w;\\\\n vec4 norm1 = taylorInvSqrt(vec4(dot(g001, g001), dot(g011, g011), dot(g101, g101), dot(g111, g111)));\\\\n g001 *= norm1.x;\\\\n g011 *= norm1.y;\\\\n g101 *= norm1.z;\\\\n g111 *= norm1.w;\\\\n\\\\n float n000 = dot(g000, Pf0);\\\\n float n100 = dot(g100, vec3(Pf1.x, Pf0.yz));\\\\n float n010 = dot(g010, vec3(Pf0.x, Pf1.y, Pf0.z));\\\\n float n110 = dot(g110, vec3(Pf1.xy, Pf0.z));\\\\n float n001 = dot(g001, vec3(Pf0.xy, Pf1.z));\\\\n float n101 = dot(g101, vec3(Pf1.x, Pf0.y, Pf1.z));\\\\n float n011 = dot(g011, vec3(Pf0.x, Pf1.yz));\\\\n float n111 = dot(g111, Pf1);\\\\n\\\\n vec3 fade_xyz = fade(Pf0);\\\\n vec4 n_z = mix(vec4(n000, n100, n010, n110), vec4(n001, n101, n011, n111), fade_xyz.z);\\\\n vec2 n_yz = mix(n_z.xy, n_z.zw, fade_xyz.y);\\\\n float n_xyz = mix(n_yz.x, n_yz.y, fade_xyz.x); \\\\n return 2.2 * n_xyz;\\\\n}\\\\n',[lF.CLASSIC_PERLIN_4D]:'//\\\\n// GLSL textureless classic 4D noise \\\\\\\"cnoise\\\\\\\",\\\\n// with an RSL-style periodic variant \\\\\\\"pnoise\\\\\\\".\\\\n// Author: Stefan Gustavson (stefan.gustavson@liu.se)\\\\n// Version: 2011-08-22\\\\n//\\\\n// Many thanks to Ian McEwan of Ashima Arts for the\\\\n// ideas for permutation and gradient selection.\\\\n//\\\\n// Copyright (c) 2011 Stefan Gustavson. All rights reserved.\\\\n// Distributed under the MIT license. See LICENSE file.\\\\n// https://github.com/stegu/webgl-noise\\\\n//\\\\n\\\\n\\\\n\\\\n// Classic Perlin noise\\\\nfloat cnoise(vec4 P)\\\\n{\\\\n vec4 Pi0 = floor(P); // Integer part for indexing\\\\n vec4 Pi1 = Pi0 + 1.0; // Integer part + 1\\\\n Pi0 = mod289(Pi0);\\\\n Pi1 = mod289(Pi1);\\\\n vec4 Pf0 = fract(P); // Fractional part for interpolation\\\\n vec4 Pf1 = Pf0 - 1.0; // Fractional part - 1.0\\\\n vec4 ix = vec4(Pi0.x, Pi1.x, Pi0.x, Pi1.x);\\\\n vec4 iy = vec4(Pi0.yy, Pi1.yy);\\\\n vec4 iz0 = vec4(Pi0.zzzz);\\\\n vec4 iz1 = vec4(Pi1.zzzz);\\\\n vec4 iw0 = vec4(Pi0.wwww);\\\\n vec4 iw1 = vec4(Pi1.wwww);\\\\n\\\\n vec4 ixy = permute(permute(ix) + iy);\\\\n vec4 ixy0 = permute(ixy + iz0);\\\\n vec4 ixy1 = permute(ixy + iz1);\\\\n vec4 ixy00 = permute(ixy0 + iw0);\\\\n vec4 ixy01 = permute(ixy0 + iw1);\\\\n vec4 ixy10 = permute(ixy1 + iw0);\\\\n vec4 ixy11 = permute(ixy1 + iw1);\\\\n\\\\n vec4 gx00 = ixy00 * (1.0 / 7.0);\\\\n vec4 gy00 = floor(gx00) * (1.0 / 7.0);\\\\n vec4 gz00 = floor(gy00) * (1.0 / 6.0);\\\\n gx00 = fract(gx00) - 0.5;\\\\n gy00 = fract(gy00) - 0.5;\\\\n gz00 = fract(gz00) - 0.5;\\\\n vec4 gw00 = vec4(0.75) - abs(gx00) - abs(gy00) - abs(gz00);\\\\n vec4 sw00 = step(gw00, vec4(0.0));\\\\n gx00 -= sw00 * (step(0.0, gx00) - 0.5);\\\\n gy00 -= sw00 * (step(0.0, gy00) - 0.5);\\\\n\\\\n vec4 gx01 = ixy01 * (1.0 / 7.0);\\\\n vec4 gy01 = floor(gx01) * (1.0 / 7.0);\\\\n vec4 gz01 = floor(gy01) * (1.0 / 6.0);\\\\n gx01 = fract(gx01) - 0.5;\\\\n gy01 = fract(gy01) - 0.5;\\\\n gz01 = fract(gz01) - 0.5;\\\\n vec4 gw01 = vec4(0.75) - abs(gx01) - abs(gy01) - abs(gz01);\\\\n vec4 sw01 = step(gw01, vec4(0.0));\\\\n gx01 -= sw01 * (step(0.0, gx01) - 0.5);\\\\n gy01 -= sw01 * (step(0.0, gy01) - 0.5);\\\\n\\\\n vec4 gx10 = ixy10 * (1.0 / 7.0);\\\\n vec4 gy10 = floor(gx10) * (1.0 / 7.0);\\\\n vec4 gz10 = floor(gy10) * (1.0 / 6.0);\\\\n gx10 = fract(gx10) - 0.5;\\\\n gy10 = fract(gy10) - 0.5;\\\\n gz10 = fract(gz10) - 0.5;\\\\n vec4 gw10 = vec4(0.75) - abs(gx10) - abs(gy10) - abs(gz10);\\\\n vec4 sw10 = step(gw10, vec4(0.0));\\\\n gx10 -= sw10 * (step(0.0, gx10) - 0.5);\\\\n gy10 -= sw10 * (step(0.0, gy10) - 0.5);\\\\n\\\\n vec4 gx11 = ixy11 * (1.0 / 7.0);\\\\n vec4 gy11 = floor(gx11) * (1.0 / 7.0);\\\\n vec4 gz11 = floor(gy11) * (1.0 / 6.0);\\\\n gx11 = fract(gx11) - 0.5;\\\\n gy11 = fract(gy11) - 0.5;\\\\n gz11 = fract(gz11) - 0.5;\\\\n vec4 gw11 = vec4(0.75) - abs(gx11) - abs(gy11) - abs(gz11);\\\\n vec4 sw11 = step(gw11, vec4(0.0));\\\\n gx11 -= sw11 * (step(0.0, gx11) - 0.5);\\\\n gy11 -= sw11 * (step(0.0, gy11) - 0.5);\\\\n\\\\n vec4 g0000 = vec4(gx00.x,gy00.x,gz00.x,gw00.x);\\\\n vec4 g1000 = vec4(gx00.y,gy00.y,gz00.y,gw00.y);\\\\n vec4 g0100 = vec4(gx00.z,gy00.z,gz00.z,gw00.z);\\\\n vec4 g1100 = vec4(gx00.w,gy00.w,gz00.w,gw00.w);\\\\n vec4 g0010 = vec4(gx10.x,gy10.x,gz10.x,gw10.x);\\\\n vec4 g1010 = vec4(gx10.y,gy10.y,gz10.y,gw10.y);\\\\n vec4 g0110 = vec4(gx10.z,gy10.z,gz10.z,gw10.z);\\\\n vec4 g1110 = vec4(gx10.w,gy10.w,gz10.w,gw10.w);\\\\n vec4 g0001 = vec4(gx01.x,gy01.x,gz01.x,gw01.x);\\\\n vec4 g1001 = vec4(gx01.y,gy01.y,gz01.y,gw01.y);\\\\n vec4 g0101 = vec4(gx01.z,gy01.z,gz01.z,gw01.z);\\\\n vec4 g1101 = vec4(gx01.w,gy01.w,gz01.w,gw01.w);\\\\n vec4 g0011 = vec4(gx11.x,gy11.x,gz11.x,gw11.x);\\\\n vec4 g1011 = vec4(gx11.y,gy11.y,gz11.y,gw11.y);\\\\n vec4 g0111 = vec4(gx11.z,gy11.z,gz11.z,gw11.z);\\\\n vec4 g1111 = vec4(gx11.w,gy11.w,gz11.w,gw11.w);\\\\n\\\\n vec4 norm00 = taylorInvSqrt(vec4(dot(g0000, g0000), dot(g0100, g0100), dot(g1000, g1000), dot(g1100, g1100)));\\\\n g0000 *= norm00.x;\\\\n g0100 *= norm00.y;\\\\n g1000 *= norm00.z;\\\\n g1100 *= norm00.w;\\\\n\\\\n vec4 norm01 = taylorInvSqrt(vec4(dot(g0001, g0001), dot(g0101, g0101), dot(g1001, g1001), dot(g1101, g1101)));\\\\n g0001 *= norm01.x;\\\\n g0101 *= norm01.y;\\\\n g1001 *= norm01.z;\\\\n g1101 *= norm01.w;\\\\n\\\\n vec4 norm10 = taylorInvSqrt(vec4(dot(g0010, g0010), dot(g0110, g0110), dot(g1010, g1010), dot(g1110, g1110)));\\\\n g0010 *= norm10.x;\\\\n g0110 *= norm10.y;\\\\n g1010 *= norm10.z;\\\\n g1110 *= norm10.w;\\\\n\\\\n vec4 norm11 = taylorInvSqrt(vec4(dot(g0011, g0011), dot(g0111, g0111), dot(g1011, g1011), dot(g1111, g1111)));\\\\n g0011 *= norm11.x;\\\\n g0111 *= norm11.y;\\\\n g1011 *= norm11.z;\\\\n g1111 *= norm11.w;\\\\n\\\\n float n0000 = dot(g0000, Pf0);\\\\n float n1000 = dot(g1000, vec4(Pf1.x, Pf0.yzw));\\\\n float n0100 = dot(g0100, vec4(Pf0.x, Pf1.y, Pf0.zw));\\\\n float n1100 = dot(g1100, vec4(Pf1.xy, Pf0.zw));\\\\n float n0010 = dot(g0010, vec4(Pf0.xy, Pf1.z, Pf0.w));\\\\n float n1010 = dot(g1010, vec4(Pf1.x, Pf0.y, Pf1.z, Pf0.w));\\\\n float n0110 = dot(g0110, vec4(Pf0.x, Pf1.yz, Pf0.w));\\\\n float n1110 = dot(g1110, vec4(Pf1.xyz, Pf0.w));\\\\n float n0001 = dot(g0001, vec4(Pf0.xyz, Pf1.w));\\\\n float n1001 = dot(g1001, vec4(Pf1.x, Pf0.yz, Pf1.w));\\\\n float n0101 = dot(g0101, vec4(Pf0.x, Pf1.y, Pf0.z, Pf1.w));\\\\n float n1101 = dot(g1101, vec4(Pf1.xy, Pf0.z, Pf1.w));\\\\n float n0011 = dot(g0011, vec4(Pf0.xy, Pf1.zw));\\\\n float n1011 = dot(g1011, vec4(Pf1.x, Pf0.y, Pf1.zw));\\\\n float n0111 = dot(g0111, vec4(Pf0.x, Pf1.yzw));\\\\n float n1111 = dot(g1111, Pf1);\\\\n\\\\n vec4 fade_xyzw = fade(Pf0);\\\\n vec4 n_0w = mix(vec4(n0000, n1000, n0100, n1100), vec4(n0001, n1001, n0101, n1101), fade_xyzw.w);\\\\n vec4 n_1w = mix(vec4(n0010, n1010, n0110, n1110), vec4(n0011, n1011, n0111, n1111), fade_xyzw.w);\\\\n vec4 n_zw = mix(n_0w, n_1w, fade_xyzw.z);\\\\n vec2 n_yzw = mix(n_zw.xy, n_zw.zw, fade_xyzw.y);\\\\n float n_xyzw = mix(n_yzw.x, n_yzw.y, fade_xyzw.x);\\\\n return 2.2 * n_xyzw;\\\\n}\\\\n\\\\n// Classic Perlin noise, periodic version\\\\nfloat pnoise(vec4 P, vec4 rep)\\\\n{\\\\n vec4 Pi0 = mod(floor(P), rep); // Integer part modulo rep\\\\n vec4 Pi1 = mod(Pi0 + 1.0, rep); // Integer part + 1 mod rep\\\\n Pi0 = mod289(Pi0);\\\\n Pi1 = mod289(Pi1);\\\\n vec4 Pf0 = fract(P); // Fractional part for interpolation\\\\n vec4 Pf1 = Pf0 - 1.0; // Fractional part - 1.0\\\\n vec4 ix = vec4(Pi0.x, Pi1.x, Pi0.x, Pi1.x);\\\\n vec4 iy = vec4(Pi0.yy, Pi1.yy);\\\\n vec4 iz0 = vec4(Pi0.zzzz);\\\\n vec4 iz1 = vec4(Pi1.zzzz);\\\\n vec4 iw0 = vec4(Pi0.wwww);\\\\n vec4 iw1 = vec4(Pi1.wwww);\\\\n\\\\n vec4 ixy = permute(permute(ix) + iy);\\\\n vec4 ixy0 = permute(ixy + iz0);\\\\n vec4 ixy1 = permute(ixy + iz1);\\\\n vec4 ixy00 = permute(ixy0 + iw0);\\\\n vec4 ixy01 = permute(ixy0 + iw1);\\\\n vec4 ixy10 = permute(ixy1 + iw0);\\\\n vec4 ixy11 = permute(ixy1 + iw1);\\\\n\\\\n vec4 gx00 = ixy00 * (1.0 / 7.0);\\\\n vec4 gy00 = floor(gx00) * (1.0 / 7.0);\\\\n vec4 gz00 = floor(gy00) * (1.0 / 6.0);\\\\n gx00 = fract(gx00) - 0.5;\\\\n gy00 = fract(gy00) - 0.5;\\\\n gz00 = fract(gz00) - 0.5;\\\\n vec4 gw00 = vec4(0.75) - abs(gx00) - abs(gy00) - abs(gz00);\\\\n vec4 sw00 = step(gw00, vec4(0.0));\\\\n gx00 -= sw00 * (step(0.0, gx00) - 0.5);\\\\n gy00 -= sw00 * (step(0.0, gy00) - 0.5);\\\\n\\\\n vec4 gx01 = ixy01 * (1.0 / 7.0);\\\\n vec4 gy01 = floor(gx01) * (1.0 / 7.0);\\\\n vec4 gz01 = floor(gy01) * (1.0 / 6.0);\\\\n gx01 = fract(gx01) - 0.5;\\\\n gy01 = fract(gy01) - 0.5;\\\\n gz01 = fract(gz01) - 0.5;\\\\n vec4 gw01 = vec4(0.75) - abs(gx01) - abs(gy01) - abs(gz01);\\\\n vec4 sw01 = step(gw01, vec4(0.0));\\\\n gx01 -= sw01 * (step(0.0, gx01) - 0.5);\\\\n gy01 -= sw01 * (step(0.0, gy01) - 0.5);\\\\n\\\\n vec4 gx10 = ixy10 * (1.0 / 7.0);\\\\n vec4 gy10 = floor(gx10) * (1.0 / 7.0);\\\\n vec4 gz10 = floor(gy10) * (1.0 / 6.0);\\\\n gx10 = fract(gx10) - 0.5;\\\\n gy10 = fract(gy10) - 0.5;\\\\n gz10 = fract(gz10) - 0.5;\\\\n vec4 gw10 = vec4(0.75) - abs(gx10) - abs(gy10) - abs(gz10);\\\\n vec4 sw10 = step(gw10, vec4(0.0));\\\\n gx10 -= sw10 * (step(0.0, gx10) - 0.5);\\\\n gy10 -= sw10 * (step(0.0, gy10) - 0.5);\\\\n\\\\n vec4 gx11 = ixy11 * (1.0 / 7.0);\\\\n vec4 gy11 = floor(gx11) * (1.0 / 7.0);\\\\n vec4 gz11 = floor(gy11) * (1.0 / 6.0);\\\\n gx11 = fract(gx11) - 0.5;\\\\n gy11 = fract(gy11) - 0.5;\\\\n gz11 = fract(gz11) - 0.5;\\\\n vec4 gw11 = vec4(0.75) - abs(gx11) - abs(gy11) - abs(gz11);\\\\n vec4 sw11 = step(gw11, vec4(0.0));\\\\n gx11 -= sw11 * (step(0.0, gx11) - 0.5);\\\\n gy11 -= sw11 * (step(0.0, gy11) - 0.5);\\\\n\\\\n vec4 g0000 = vec4(gx00.x,gy00.x,gz00.x,gw00.x);\\\\n vec4 g1000 = vec4(gx00.y,gy00.y,gz00.y,gw00.y);\\\\n vec4 g0100 = vec4(gx00.z,gy00.z,gz00.z,gw00.z);\\\\n vec4 g1100 = vec4(gx00.w,gy00.w,gz00.w,gw00.w);\\\\n vec4 g0010 = vec4(gx10.x,gy10.x,gz10.x,gw10.x);\\\\n vec4 g1010 = vec4(gx10.y,gy10.y,gz10.y,gw10.y);\\\\n vec4 g0110 = vec4(gx10.z,gy10.z,gz10.z,gw10.z);\\\\n vec4 g1110 = vec4(gx10.w,gy10.w,gz10.w,gw10.w);\\\\n vec4 g0001 = vec4(gx01.x,gy01.x,gz01.x,gw01.x);\\\\n vec4 g1001 = vec4(gx01.y,gy01.y,gz01.y,gw01.y);\\\\n vec4 g0101 = vec4(gx01.z,gy01.z,gz01.z,gw01.z);\\\\n vec4 g1101 = vec4(gx01.w,gy01.w,gz01.w,gw01.w);\\\\n vec4 g0011 = vec4(gx11.x,gy11.x,gz11.x,gw11.x);\\\\n vec4 g1011 = vec4(gx11.y,gy11.y,gz11.y,gw11.y);\\\\n vec4 g0111 = vec4(gx11.z,gy11.z,gz11.z,gw11.z);\\\\n vec4 g1111 = vec4(gx11.w,gy11.w,gz11.w,gw11.w);\\\\n\\\\n vec4 norm00 = taylorInvSqrt(vec4(dot(g0000, g0000), dot(g0100, g0100), dot(g1000, g1000), dot(g1100, g1100)));\\\\n g0000 *= norm00.x;\\\\n g0100 *= norm00.y;\\\\n g1000 *= norm00.z;\\\\n g1100 *= norm00.w;\\\\n\\\\n vec4 norm01 = taylorInvSqrt(vec4(dot(g0001, g0001), dot(g0101, g0101), dot(g1001, g1001), dot(g1101, g1101)));\\\\n g0001 *= norm01.x;\\\\n g0101 *= norm01.y;\\\\n g1001 *= norm01.z;\\\\n g1101 *= norm01.w;\\\\n\\\\n vec4 norm10 = taylorInvSqrt(vec4(dot(g0010, g0010), dot(g0110, g0110), dot(g1010, g1010), dot(g1110, g1110)));\\\\n g0010 *= norm10.x;\\\\n g0110 *= norm10.y;\\\\n g1010 *= norm10.z;\\\\n g1110 *= norm10.w;\\\\n\\\\n vec4 norm11 = taylorInvSqrt(vec4(dot(g0011, g0011), dot(g0111, g0111), dot(g1011, g1011), dot(g1111, g1111)));\\\\n g0011 *= norm11.x;\\\\n g0111 *= norm11.y;\\\\n g1011 *= norm11.z;\\\\n g1111 *= norm11.w;\\\\n\\\\n float n0000 = dot(g0000, Pf0);\\\\n float n1000 = dot(g1000, vec4(Pf1.x, Pf0.yzw));\\\\n float n0100 = dot(g0100, vec4(Pf0.x, Pf1.y, Pf0.zw));\\\\n float n1100 = dot(g1100, vec4(Pf1.xy, Pf0.zw));\\\\n float n0010 = dot(g0010, vec4(Pf0.xy, Pf1.z, Pf0.w));\\\\n float n1010 = dot(g1010, vec4(Pf1.x, Pf0.y, Pf1.z, Pf0.w));\\\\n float n0110 = dot(g0110, vec4(Pf0.x, Pf1.yz, Pf0.w));\\\\n float n1110 = dot(g1110, vec4(Pf1.xyz, Pf0.w));\\\\n float n0001 = dot(g0001, vec4(Pf0.xyz, Pf1.w));\\\\n float n1001 = dot(g1001, vec4(Pf1.x, Pf0.yz, Pf1.w));\\\\n float n0101 = dot(g0101, vec4(Pf0.x, Pf1.y, Pf0.z, Pf1.w));\\\\n float n1101 = dot(g1101, vec4(Pf1.xy, Pf0.z, Pf1.w));\\\\n float n0011 = dot(g0011, vec4(Pf0.xy, Pf1.zw));\\\\n float n1011 = dot(g1011, vec4(Pf1.x, Pf0.y, Pf1.zw));\\\\n float n0111 = dot(g0111, vec4(Pf0.x, Pf1.yzw));\\\\n float n1111 = dot(g1111, Pf1);\\\\n\\\\n vec4 fade_xyzw = fade(Pf0);\\\\n vec4 n_0w = mix(vec4(n0000, n1000, n0100, n1100), vec4(n0001, n1001, n0101, n1101), fade_xyzw.w);\\\\n vec4 n_1w = mix(vec4(n0010, n1010, n0110, n1110), vec4(n0011, n1011, n0111, n1111), fade_xyzw.w);\\\\n vec4 n_zw = mix(n_0w, n_1w, fade_xyzw.z);\\\\n vec2 n_yzw = mix(n_zw.xy, n_zw.zw, fade_xyzw.y);\\\\n float n_xyzw = mix(n_yzw.x, n_yzw.y, fade_xyzw.x);\\\\n return 2.2 * n_xyzw;\\\\n}\\\\n',[lF.NOISE_2D]:\\\\\\\"//\\\\n// Description : Array and textureless GLSL 2D simplex noise function.\\\\n// Author : Ian McEwan, Ashima Arts.\\\\n// Maintainer : stegu\\\\n// Lastmod : 20110822 (ijm)\\\\n// License : Copyright (C) 2011 Ashima Arts. All rights reserved.\\\\n// Distributed under the MIT License. See LICENSE file.\\\\n// https://github.com/ashima/webgl-noise\\\\n// https://github.com/stegu/webgl-noise\\\\n// \\\\n\\\\n\\\\nfloat snoise(vec2 v)\\\\n {\\\\n const vec4 C = vec4(0.211324865405187, // (3.0-sqrt(3.0))/6.0\\\\n 0.366025403784439, // 0.5*(sqrt(3.0)-1.0)\\\\n -0.577350269189626, // -1.0 + 2.0 * C.x\\\\n 0.024390243902439); // 1.0 / 41.0\\\\n// First corner\\\\n vec2 i = floor(v + dot(v, C.yy) );\\\\n vec2 x0 = v - i + dot(i, C.xx);\\\\n\\\\n// Other corners\\\\n vec2 i1;\\\\n //i1.x = step( x0.y, x0.x ); // x0.x > x0.y ? 1.0 : 0.0\\\\n //i1.y = 1.0 - i1.x;\\\\n i1 = (x0.x > x0.y) ? vec2(1.0, 0.0) : vec2(0.0, 1.0);\\\\n // x0 = x0 - 0.0 + 0.0 * C.xx ;\\\\n // x1 = x0 - i1 + 1.0 * C.xx ;\\\\n // x2 = x0 - 1.0 + 2.0 * C.xx ;\\\\n vec4 x12 = x0.xyxy + C.xxzz;\\\\n x12.xy -= i1;\\\\n\\\\n// Permutations\\\\n i = mod289(i); // Avoid truncation effects in permutation\\\\n vec3 p = permute( permute( i.y + vec3(0.0, i1.y, 1.0 ))\\\\n\\\\t\\\\t+ i.x + vec3(0.0, i1.x, 1.0 ));\\\\n\\\\n vec3 m = max(0.5 - vec3(dot(x0,x0), dot(x12.xy,x12.xy), dot(x12.zw,x12.zw)), 0.0);\\\\n m = m*m ;\\\\n m = m*m ;\\\\n\\\\n// Gradients: 41 points uniformly over a line, mapped onto a diamond.\\\\n// The ring size 17*17 = 289 is close to a multiple of 41 (41*7 = 287)\\\\n\\\\n vec3 x = 2.0 * fract(p * C.www) - 1.0;\\\\n vec3 h = abs(x) - 0.5;\\\\n vec3 ox = floor(x + 0.5);\\\\n vec3 a0 = x - ox;\\\\n\\\\n// Normalise gradients implicitly by scaling m\\\\n// Approximation of: m *= inversesqrt( a0*a0 + h*h );\\\\n m *= 1.79284291400159 - 0.85373472095314 * ( a0*a0 + h*h );\\\\n\\\\n// Compute final noise value at P\\\\n vec3 g;\\\\n g.x = a0.x * x0.x + h.x * x0.y;\\\\n g.yz = a0.yz * x12.xz + h.yz * x12.yw;\\\\n return 130.0 * dot(m, g);\\\\n}\\\\n\\\\\\\",[lF.NOISE_3D]:\\\\\\\"//\\\\n// Description : Array and textureless GLSL 2D/3D/4D simplex \\\\n// noise functions.\\\\n// Author : Ian McEwan, Ashima Arts.\\\\n// Maintainer : stegu\\\\n// Lastmod : 20110822 (ijm)\\\\n// License : Copyright (C) 2011 Ashima Arts. All rights reserved.\\\\n// Distributed under the MIT License. See LICENSE file.\\\\n// https://github.com/ashima/webgl-noise\\\\n// https://github.com/stegu/webgl-noise\\\\n// \\\\n\\\\n\\\\n\\\\nfloat snoise(vec3 v)\\\\n { \\\\n const vec2 C = vec2(1.0/6.0, 1.0/3.0) ;\\\\n const vec4 D = vec4(0.0, 0.5, 1.0, 2.0);\\\\n\\\\n// First corner\\\\n vec3 i = floor(v + dot(v, C.yyy) );\\\\n vec3 x0 = v - i + dot(i, C.xxx) ;\\\\n\\\\n// Other corners\\\\n vec3 g = step(x0.yzx, x0.xyz);\\\\n vec3 l = 1.0 - g;\\\\n vec3 i1 = min( g.xyz, l.zxy );\\\\n vec3 i2 = max( g.xyz, l.zxy );\\\\n\\\\n // x0 = x0 - 0.0 + 0.0 * C.xxx;\\\\n // x1 = x0 - i1 + 1.0 * C.xxx;\\\\n // x2 = x0 - i2 + 2.0 * C.xxx;\\\\n // x3 = x0 - 1.0 + 3.0 * C.xxx;\\\\n vec3 x1 = x0 - i1 + C.xxx;\\\\n vec3 x2 = x0 - i2 + C.yyy; // 2.0*C.x = 1/3 = C.y\\\\n vec3 x3 = x0 - D.yyy; // -1.0+3.0*C.x = -0.5 = -D.y\\\\n\\\\n// Permutations\\\\n i = mod289(i); \\\\n vec4 p = permute( permute( permute( \\\\n i.z + vec4(0.0, i1.z, i2.z, 1.0 ))\\\\n + i.y + vec4(0.0, i1.y, i2.y, 1.0 )) \\\\n + i.x + vec4(0.0, i1.x, i2.x, 1.0 ));\\\\n\\\\n// Gradients: 7x7 points over a square, mapped onto an octahedron.\\\\n// The ring size 17*17 = 289 is close to a multiple of 49 (49*6 = 294)\\\\n float n_ = 0.142857142857; // 1.0/7.0\\\\n vec3 ns = n_ * D.wyz - D.xzx;\\\\n\\\\n vec4 j = p - 49.0 * floor(p * ns.z * ns.z); // mod(p,7*7)\\\\n\\\\n vec4 x_ = floor(j * ns.z);\\\\n vec4 y_ = floor(j - 7.0 * x_ ); // mod(j,N)\\\\n\\\\n vec4 x = x_ *ns.x + ns.yyyy;\\\\n vec4 y = y_ *ns.x + ns.yyyy;\\\\n vec4 h = 1.0 - abs(x) - abs(y);\\\\n\\\\n vec4 b0 = vec4( x.xy, y.xy );\\\\n vec4 b1 = vec4( x.zw, y.zw );\\\\n\\\\n //vec4 s0 = vec4(lessThan(b0,0.0))*2.0 - 1.0;\\\\n //vec4 s1 = vec4(lessThan(b1,0.0))*2.0 - 1.0;\\\\n vec4 s0 = floor(b0)*2.0 + 1.0;\\\\n vec4 s1 = floor(b1)*2.0 + 1.0;\\\\n vec4 sh = -step(h, vec4(0.0));\\\\n\\\\n vec4 a0 = b0.xzyw + s0.xzyw*sh.xxyy ;\\\\n vec4 a1 = b1.xzyw + s1.xzyw*sh.zzww ;\\\\n\\\\n vec3 p0 = vec3(a0.xy,h.x);\\\\n vec3 p1 = vec3(a0.zw,h.y);\\\\n vec3 p2 = vec3(a1.xy,h.z);\\\\n vec3 p3 = vec3(a1.zw,h.w);\\\\n\\\\n//Normalise gradients\\\\n vec4 norm = taylorInvSqrt(vec4(dot(p0,p0), dot(p1,p1), dot(p2, p2), dot(p3,p3)));\\\\n p0 *= norm.x;\\\\n p1 *= norm.y;\\\\n p2 *= norm.z;\\\\n p3 *= norm.w;\\\\n\\\\n// Mix final noise value\\\\n vec4 m = max(0.6 - vec4(dot(x0,x0), dot(x1,x1), dot(x2,x2), dot(x3,x3)), 0.0);\\\\n m = m * m;\\\\n return 42.0 * dot( m*m, vec4( dot(p0,x0), dot(p1,x1), \\\\n dot(p2,x2), dot(p3,x3) ) );\\\\n }\\\\n\\\\\\\",[lF.NOISE_4D]:\\\\\\\"//\\\\n// Description : Array and textureless GLSL 2D/3D/4D simplex \\\\n// noise functions.\\\\n// Author : Ian McEwan, Ashima Arts.\\\\n// Maintainer : stegu\\\\n// Lastmod : 20110822 (ijm)\\\\n// License : Copyright (C) 2011 Ashima Arts. All rights reserved.\\\\n// Distributed under the MIT License. See LICENSE file.\\\\n// https://github.com/ashima/webgl-noise\\\\n// https://github.com/stegu/webgl-noise\\\\n// \\\\n\\\\n\\\\n\\\\n\\\\n\\\\n\\\\n\\\\nvec4 grad4(float j, vec4 ip)\\\\n {\\\\n const vec4 ones = vec4(1.0, 1.0, 1.0, -1.0);\\\\n vec4 p,s;\\\\n\\\\n p.xyz = floor( fract (vec3(j) * ip.xyz) * 7.0) * ip.z - 1.0;\\\\n p.w = 1.5 - dot(abs(p.xyz), ones.xyz);\\\\n s = vec4(lessThan(p, vec4(0.0)));\\\\n p.xyz = p.xyz + (s.xyz*2.0 - 1.0) * s.www; \\\\n\\\\n return p;\\\\n }\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\n// (sqrt(5) - 1)/4 = F4, used once below\\\\n#define F4 0.309016994374947451\\\\n\\\\nfloat snoise(vec4 v)\\\\n {\\\\n const vec4 C = vec4( 0.138196601125011, // (5 - sqrt(5))/20 G4\\\\n 0.276393202250021, // 2 * G4\\\\n 0.414589803375032, // 3 * G4\\\\n -0.447213595499958); // -1 + 4 * G4\\\\n\\\\n// First corner\\\\n vec4 i = floor(v + dot(v, vec4(F4)) );\\\\n vec4 x0 = v - i + dot(i, C.xxxx);\\\\n\\\\n// Other corners\\\\n\\\\n// Rank sorting originally contributed by Bill Licea-Kane, AMD (formerly ATI)\\\\n vec4 i0;\\\\n vec3 isX = step( x0.yzw, x0.xxx );\\\\n vec3 isYZ = step( x0.zww, x0.yyz );\\\\n// i0.x = dot( isX, vec3( 1.0 ) );\\\\n i0.x = isX.x + isX.y + isX.z;\\\\n i0.yzw = 1.0 - isX;\\\\n// i0.y += dot( isYZ.xy, vec2( 1.0 ) );\\\\n i0.y += isYZ.x + isYZ.y;\\\\n i0.zw += 1.0 - isYZ.xy;\\\\n i0.z += isYZ.z;\\\\n i0.w += 1.0 - isYZ.z;\\\\n\\\\n // i0 now contains the unique values 0,1,2,3 in each channel\\\\n vec4 i3 = clamp( i0, 0.0, 1.0 );\\\\n vec4 i2 = clamp( i0-1.0, 0.0, 1.0 );\\\\n vec4 i1 = clamp( i0-2.0, 0.0, 1.0 );\\\\n\\\\n // x0 = x0 - 0.0 + 0.0 * C.xxxx\\\\n // x1 = x0 - i1 + 1.0 * C.xxxx\\\\n // x2 = x0 - i2 + 2.0 * C.xxxx\\\\n // x3 = x0 - i3 + 3.0 * C.xxxx\\\\n // x4 = x0 - 1.0 + 4.0 * C.xxxx\\\\n vec4 x1 = x0 - i1 + C.xxxx;\\\\n vec4 x2 = x0 - i2 + C.yyyy;\\\\n vec4 x3 = x0 - i3 + C.zzzz;\\\\n vec4 x4 = x0 + C.wwww;\\\\n\\\\n// Permutations\\\\n i = mod289(i); \\\\n float j0 = permute( permute( permute( permute(i.w) + i.z) + i.y) + i.x);\\\\n vec4 j1 = permute( permute( permute( permute (\\\\n i.w + vec4(i1.w, i2.w, i3.w, 1.0 ))\\\\n + i.z + vec4(i1.z, i2.z, i3.z, 1.0 ))\\\\n + i.y + vec4(i1.y, i2.y, i3.y, 1.0 ))\\\\n + i.x + vec4(i1.x, i2.x, i3.x, 1.0 ));\\\\n\\\\n// Gradients: 7x7x6 points over a cube, mapped onto a 4-cross polytope\\\\n// 7*7*6 = 294, which is close to the ring size 17*17 = 289.\\\\n vec4 ip = vec4(1.0/294.0, 1.0/49.0, 1.0/7.0, 0.0) ;\\\\n\\\\n vec4 p0 = grad4(j0, ip);\\\\n vec4 p1 = grad4(j1.x, ip);\\\\n vec4 p2 = grad4(j1.y, ip);\\\\n vec4 p3 = grad4(j1.z, ip);\\\\n vec4 p4 = grad4(j1.w, ip);\\\\n\\\\n// Normalise gradients\\\\n vec4 norm = taylorInvSqrt(vec4(dot(p0,p0), dot(p1,p1), dot(p2, p2), dot(p3,p3)));\\\\n p0 *= norm.x;\\\\n p1 *= norm.y;\\\\n p2 *= norm.z;\\\\n p3 *= norm.w;\\\\n p4 *= taylorInvSqrt(dot(p4,p4));\\\\n\\\\n// Mix contributions from the five corners\\\\n vec3 m0 = max(0.6 - vec3(dot(x0,x0), dot(x1,x1), dot(x2,x2)), 0.0);\\\\n vec2 m1 = max(0.6 - vec2(dot(x3,x3), dot(x4,x4) ), 0.0);\\\\n m0 = m0 * m0;\\\\n m1 = m1 * m1;\\\\n return 49.0 * ( dot(m0*m0, vec3( dot( p0, x0 ), dot( p1, x1 ), dot( p2, x2 )))\\\\n + dot(m1*m1, vec2( dot( p3, x3 ), dot( p4, x4 ) ) ) ) ;\\\\n\\\\n }\\\\n\\\\\\\"},uF={[lF.CLASSIC_PERLIN_2D]:Uo.VEC2,[lF.CLASSIC_PERLIN_3D]:Uo.VEC3,[lF.CLASSIC_PERLIN_4D]:Uo.VEC4,[lF.NOISE_2D]:Uo.VEC2,[lF.NOISE_3D]:Uo.VEC3,[lF.NOISE_4D]:Uo.VEC4},dF={[lF.CLASSIC_PERLIN_2D]:Uo.FLOAT,[lF.CLASSIC_PERLIN_3D]:Uo.FLOAT,[lF.CLASSIC_PERLIN_4D]:Uo.FLOAT,[lF.NOISE_2D]:Uo.FLOAT,[lF.NOISE_3D]:Uo.FLOAT,[lF.NOISE_4D]:Uo.FLOAT},pF={[lF.CLASSIC_PERLIN_2D]:\\\\\\\"cnoise\\\\\\\",[lF.CLASSIC_PERLIN_3D]:\\\\\\\"cnoise\\\\\\\",[lF.CLASSIC_PERLIN_4D]:\\\\\\\"cnoise\\\\\\\",[lF.NOISE_2D]:\\\\\\\"snoise\\\\\\\",[lF.NOISE_3D]:\\\\\\\"snoise\\\\\\\",[lF.NOISE_4D]:\\\\\\\"snoise\\\\\\\"};var _F;!function(t){t[t.NoChange=0]=\\\\\\\"NoChange\\\\\\\",t[t.Float=1]=\\\\\\\"Float\\\\\\\",t[t.Vec2=2]=\\\\\\\"Vec2\\\\\\\",t[t.Vec3=3]=\\\\\\\"Vec3\\\\\\\",t[t.Vec4=4]=\\\\\\\"Vec4\\\\\\\"}(_F||(_F={}));const mF=[_F.NoChange,_F.Float,_F.Vec2,_F.Vec3,_F.Vec4],fF={[_F.NoChange]:\\\\\\\"Same as noise\\\\\\\",[_F.Float]:\\\\\\\"Float\\\\\\\",[_F.Vec2]:\\\\\\\"Vec2\\\\\\\",[_F.Vec3]:\\\\\\\"Vec3\\\\\\\",[_F.Vec4]:\\\\\\\"Vec4\\\\\\\"},gF={[_F.NoChange]:Uo.FLOAT,[_F.Float]:Uo.FLOAT,[_F.Vec2]:Uo.VEC2,[_F.Vec3]:Uo.VEC3,[_F.Vec4]:Uo.VEC4},vF=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\",\\\\\\\"w\\\\\\\"],yF=\\\\\\\"noise\\\\\\\",xF=cF.indexOf(lF.NOISE_3D),bF=_F.NoChange,wF={amp:1,freq:1};var TF;!function(t){t.AMP=\\\\\\\"amp\\\\\\\",t.POSITION=\\\\\\\"position\\\\\\\",t.FREQ=\\\\\\\"freq\\\\\\\",t.OFFSET=\\\\\\\"offset\\\\\\\"}(TF||(TF={}));const AF=new class extends ua{constructor(){super(...arguments),this.type=ha.INTEGER(xF,{menu:{entries:cF.map(((t,e)=>({name:`${t} (output: ${dF[t]})`,value:e})))}}),this.outputType=ha.INTEGER(bF,{menu:{entries:mF.map((t=>{const e=mF[t];return{name:fF[e],value:e}}))}}),this.octaves=ha.INTEGER(3,{range:[1,10],rangeLocked:[!0,!1]}),this.ampAttenuation=ha.FLOAT(.5,{range:[0,1]}),this.freqIncrease=ha.FLOAT(2,{range:[0,10],separatorAfter:!0})}};class MF extends gf{constructor(){super(...arguments),this.paramsConfig=AF}static type(){return\\\\\\\"noise\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.initializeNode(),this.io.connection_points.spare_params.set_inputless_param_names([\\\\\\\"octaves\\\\\\\",\\\\\\\"ampAttenuation\\\\\\\",\\\\\\\"freqIncrease\\\\\\\"]),this.io.outputs.setNamedOutputConnectionPoints([new qo(yF,Uo.FLOAT)]),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this)),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function((()=>yF))}_gl_input_name(t){return[TF.AMP,TF.POSITION,TF.FREQ,TF.OFFSET][t]}paramDefaultValue(t){return wF[t]}_expected_input_types(){const t=cF[this.pv.type],e=this._expected_output_types()[0],n=uF[t];return[e,n,n,n]}_expected_output_types(){const t=cF[this.pv.type],e=mF[this.pv.outputType];return e==_F.NoChange?[uF[t]]:[gF[e]]}setLines(t){const e=[],n=[],i=cF[this.pv.type],s=hF[i],r=dF[i];e.push(new Cf(this,\\\\\\\"// Modulo 289 without a division (only multiplications)\\\\nfloat mod289(float x) {\\\\n return x - floor(x * (1.0 / 289.0)) * 289.0;\\\\n}\\\\nvec2 mod289(vec2 x) {\\\\n return x - floor(x * (1.0 / 289.0)) * 289.0;\\\\n}\\\\nvec3 mod289(vec3 x) {\\\\n return x - floor(x * (1.0 / 289.0)) * 289.0;\\\\n}\\\\nvec4 mod289(vec4 x) {\\\\n return x - floor(x * (1.0 / 289.0)) * 289.0;\\\\n}\\\\n// Modulo 7 without a division\\\\nvec3 mod7(vec3 x) {\\\\n return x - floor(x * (1.0 / 7.0)) * 7.0;\\\\n}\\\\n\\\\n// Permutation polynomial: (34x^2 + x) mod 289\\\\nfloat permute(float x) {\\\\n return mod289(((x*34.0)+1.0)*x);\\\\n}\\\\nvec3 permute(vec3 x) {\\\\n return mod289((34.0 * x + 1.0) * x);\\\\n}\\\\nvec4 permute(vec4 x) {\\\\n return mod289(((x*34.0)+1.0)*x);\\\\n}\\\\n\\\\nfloat taylorInvSqrt(float r)\\\\n{\\\\n return 1.79284291400159 - 0.85373472095314 * r;\\\\n}\\\\nvec4 taylorInvSqrt(vec4 r)\\\\n{\\\\n return 1.79284291400159 - 0.85373472095314 * r;\\\\n}\\\\n\\\\nvec2 fade(vec2 t) {\\\\n return t*t*t*(t*(t*6.0-15.0)+10.0);\\\\n}\\\\nvec3 fade(vec3 t) {\\\\n return t*t*t*(t*(t*6.0-15.0)+10.0);\\\\n}\\\\nvec4 fade(vec4 t) {\\\\n return t*t*t*(t*(t*6.0-15.0)+10.0);\\\\n}\\\\\\\")),e.push(new Cf(this,s)),e.push(new Cf(this,this.fbm_function()));const o=this._expected_output_types()[0];if(o==r){const t=this.single_noise_line();n.push(t)}else{const t=Wo[o],e=[],s=this.glVarName(\\\\\\\"noise\\\\\\\");for(let r=0;rmf.float(1e3*r))).join(\\\\\\\", \\\\\\\")})`,c=this.single_noise_line(t,t,l);n.push(c)}const r=`vec${t} ${s} = vec${t}(${e.join(\\\\\\\", \\\\\\\")})`;n.push(r)}t.addDefinitions(this,e),t.addBodyLines(this,n)}fbm_method_name(){const t=cF[this.pv.type];return`fbm_${pF[t]}_${this.name()}`}fbm_function(){const t=cF[this.pv.type],e=pF[t],n=uF[t];return`\\\\nfloat ${this.fbm_method_name()} (in ${n} st) {\\\\n\\\\tfloat value = 0.0;\\\\n\\\\tfloat amplitude = 1.0;\\\\n\\\\tfor (int i = 0; i < ${mf.integer(this.pv.octaves)}; i++) {\\\\n\\\\t\\\\tvalue += amplitude * ${e}(st);\\\\n\\\\t\\\\tst *= ${mf.float(this.pv.freqIncrease)};\\\\n\\\\t\\\\tamplitude *= ${mf.float(this.pv.ampAttenuation)};\\\\n\\\\t}\\\\n\\\\treturn value;\\\\n}\\\\n`}single_noise_line(t,e,n){const i=this.fbm_method_name(),s=mf.any(this.variableForInput(TF.AMP)),r=mf.any(this.variableForInput(TF.POSITION)),o=mf.any(this.variableForInput(TF.FREQ));let a=mf.any(this.variableForInput(TF.OFFSET));n&&(a=`(${a}+${n})`);const l=[`(${r}*${o})+${a}`].join(\\\\\\\", \\\\\\\"),c=this.glVarName(yF),h=`${s}*${i}(${l})`;if(e)return`float ${c}${t} = (${h}).${e}`;return`${this.io.outputs.namedOutputConnectionPoints()[0].type()} ${c} = ${h}`}}class EF extends EP{static type(){return\\\\\\\"null\\\\\\\"}setLines(t){const e=mf.any(this.variableForInput(this._gl_input_name(0))),n=this.io.outputs.namedOutputConnectionPoints()[0],i=`${n.type()} ${this.glVarName(n.name())} = ${e}`;t.addBodyLines(this,[i])}}const SF=new class extends ua{};class CF extends gf{constructor(){super(...arguments),this.paramsConfig=SF}static type(){return\\\\\\\"output\\\\\\\"}initializeNode(){super.initializeNode(),this.addPostDirtyHook(\\\\\\\"_set_mat_to_recompile\\\\\\\",this._set_mat_to_recompile.bind(this)),this.lifecycle.add_on_add_hook((()=>{var t,e;null===(e=null===(t=this.material_node)||void 0===t?void 0:t.assemblerController)||void 0===e||e.add_output_inputs(this)}))}setLines(t){t.assembler().set_node_lines_output(this,t)}}class NF{constructor(){this._param_configs=[]}reset(){this._param_configs=[]}push(t){this._param_configs.push(t)}list(){return this._param_configs}}const LF=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(\\\\\\\"\\\\\\\"),this.type=ha.INTEGER(Go.indexOf(Uo.FLOAT),{menu:{entries:Go.map(((t,e)=>({name:t,value:e})))}}),this.asColor=ha.BOOLEAN(0,{visibleIf:{type:Go.indexOf(Uo.VEC3)}})}};class OF extends gf{constructor(){super(...arguments),this.paramsConfig=LF,this._allow_inputs_created_from_params=!1,this._on_create_set_name_if_none_bound=this._on_create_set_name_if_none.bind(this)}static type(){return\\\\\\\"param\\\\\\\"}initializeNode(){this.addPostDirtyHook(\\\\\\\"_set_mat_to_recompile\\\\\\\",this._set_mat_to_recompile.bind(this)),this.lifecycle.add_on_create_hook(this._on_create_set_name_if_none_bound),this.io.connection_points.initializeNode(),this.io.connection_points.set_expected_input_types_function((()=>[])),this.io.connection_points.set_expected_output_types_function((()=>[Go[this.pv.type]])),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name])}))}))}setLines(t){const e=[],n=Go[this.pv.type],i=this.uniform_name();e.push(new Nf(this,n,i)),t.addDefinitions(this,e)}paramsGenerating(){return!0}setParamConfigs(){const t=Go[this.pv.type],e=jo[t];let n=Vo[t];if(this._param_configs_controller=this._param_configs_controller||new NF,this._param_configs_controller.reset(),n==Cr.VECTOR3&&this.p.asColor.value&&m.isArray(e)&&3==e.length){const t=new tg(Cr.COLOR,this.pv.name,e,this.uniform_name());this._param_configs_controller.push(t)}else{const t=new tg(n,this.pv.name,e,this.uniform_name());this._param_configs_controller.push(t)}}uniform_name(){const t=this.io.outputs.namedOutputConnectionPoints()[0];return this.glVarName(t.name())}set_gl_type(t){const e=Go.indexOf(t);this.p.type.set(e)}_on_create_set_name_if_none(){\\\\\\\"\\\\\\\"==this.pv.name&&this.p.name.set(this.name())}}class PF extends MP{static type(){return\\\\\\\"refract\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function((t=>[\\\\\\\"I\\\\\\\",\\\\\\\"N\\\\\\\",\\\\\\\"eta\\\\\\\"][t])),this.io.connection_points.set_output_name_function((t=>\\\\\\\"refract\\\\\\\")),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this))}gl_method_name(){return\\\\\\\"refract\\\\\\\"}_expected_input_types(){const t=this.io.connection_points.first_input_connection_type()||Uo.VEC3;return[t,t,Uo.FLOAT]}_expected_output_types(){return[this._expected_input_types()[0]]}}const RF=\\\\\\\"SSSModel\\\\\\\";const IF=new class extends ua{constructor(){super(...arguments),this.color=ha.COLOR([1,1,1]),this.thickness=ha.FLOAT(.1),this.power=ha.FLOAT(2),this.scale=ha.FLOAT(16),this.distortion=ha.FLOAT(.1),this.ambient=ha.FLOAT(.4),this.attenuation=ha.FLOAT(.8)}};class FF extends gf{constructor(){super(...arguments),this.paramsConfig=IF}static type(){return\\\\\\\"SSSModel\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(RF,Uo.SSS_MODEL)])}setLines(t){const e=[],n=this.glVarName(RF);e.push(`SSSModel ${n}`),e.push(`${n}.isActive = true;`),e.push(this._paramLineFloat(n,this.p.color)),e.push(this._paramLineFloat(n,this.p.thickness)),e.push(this._paramLineFloat(n,this.p.power)),e.push(this._paramLineFloat(n,this.p.scale)),e.push(this._paramLineFloat(n,this.p.distortion)),e.push(this._paramLineFloat(n,this.p.ambient)),e.push(this._paramLineFloat(n,this.p.attenuation)),t.addBodyLines(this,e)}_paramLineFloat(t,e){return`${t}.${e.name()} = ${mf.vector3(this.variableForInputParam(e))};`}}class DF extends EP{static type(){return\\\\\\\"quatMult\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function((t=>[\\\\\\\"quat0\\\\\\\",\\\\\\\"quat1\\\\\\\"][t])),this.io.connection_points.set_expected_input_types_function((()=>[Uo.VEC4,Uo.VEC4])),this.io.connection_points.set_expected_output_types_function((()=>[Uo.VEC4]))}gl_method_name(){return\\\\\\\"quatMult\\\\\\\"}gl_function_definitions(){return[new Cf(this,NR)]}}var BF;!function(t){t.AXIS=\\\\\\\"axis\\\\\\\",t.ANGLE=\\\\\\\"angle\\\\\\\"}(BF||(BF={}));const zF=[BF.AXIS,BF.ANGLE],kF={[BF.AXIS]:[0,0,1],[BF.ANGLE]:0};class UF extends SP{static type(){return\\\\\\\"quatFromAxisAngle\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function((t=>zF[t])),this.io.connection_points.set_expected_input_types_function((()=>[Uo.VEC3,Uo.FLOAT])),this.io.connection_points.set_expected_output_types_function((()=>[Uo.VEC4]))}paramDefaultValue(t){return kF[t]}gl_method_name(){return\\\\\\\"quatFromAxisAngle\\\\\\\"}gl_function_definitions(){return[new Cf(this,NR)]}}class GF extends EP{static type(){return\\\\\\\"quatToAngle\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function((t=>[\\\\\\\"quat\\\\\\\"][t])),this.io.connection_points.set_expected_input_types_function((()=>[Uo.VEC4])),this.io.connection_points.set_expected_output_types_function((()=>[Uo.FLOAT]))}gl_method_name(){return\\\\\\\"quatToAngle\\\\\\\"}gl_function_definitions(){return[new Cf(this,NR)]}}class VF extends EP{static type(){return\\\\\\\"quatToAxis\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.set_input_name_function((t=>[\\\\\\\"quat\\\\\\\"][t])),this.io.connection_points.set_expected_input_types_function((()=>[Uo.VEC4])),this.io.connection_points.set_expected_output_types_function((()=>[Uo.VEC3]))}gl_method_name(){return\\\\\\\"quatToAxis\\\\\\\"}gl_function_definitions(){return[new Cf(this,NR)]}}const HF=\\\\\\\"val\\\\\\\";const jF=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(\\\\\\\"ramp\\\\\\\"),this.input=ha.FLOAT(0)}};class WF extends gf{constructor(){super(...arguments),this.paramsConfig=jF}static type(){return\\\\\\\"ramp\\\\\\\"}initializeNode(){super.initializeNode(),this.addPostDirtyHook(\\\\\\\"_set_mat_to_recompile\\\\\\\",this._set_mat_to_recompile.bind(this)),this.io.outputs.setNamedOutputConnectionPoints([new qo(HF,Uo.FLOAT)]),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name])}))}))}setLines(t){const e=Uo.VEC3,n=this.glVarName(\\\\\\\"tmpTexureVarName\\\\\\\"),i=Uo.FLOAT,s=this._uniform_name(),r=this.glVarName(HF),o=new Nf(this,Uo.SAMPLER_2D,s);t.addDefinitions(this,[o]);const a=this.variableForInputParam(this.p.input),l=[`${e} ${n} = texture2D(${this._uniform_name()}, vec2(${a}, 0.0)).xyz`,`${i} ${r} = -1.0 + ${n}.x + ${n}.y + ${n}.z`];t.addBodyLines(this,l)}paramsGenerating(){return!0}setParamConfigs(){this._param_configs_controller=this._param_configs_controller||new NF,this._param_configs_controller.reset();const t=new tg(Cr.RAMP,this.pv.name,Ao.DEFAULT_VALUE,this._uniform_name());this._param_configs_controller.push(t)}_uniform_name(){return\\\\\\\"ramp_texture_\\\\\\\"+this.glVarName(HF)}}const qF=\\\\\\\"rand\\\\\\\";const XF=new class extends ua{constructor(){super(...arguments),this.seed=ha.VECTOR2([1,1])}};class YF extends gf{constructor(){super(...arguments),this.paramsConfig=XF}static type(){return\\\\\\\"random\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo(qF,Uo.FLOAT)])}setLines(t){const e=this.io.inputs.namedInputConnectionPoints()[0].name(),n=mf.vector2(this.variableForInput(e)),i=`float ${this.glVarName(qF)} = rand(${n})`;t.addBodyLines(this,[i])}}const $F=new class extends ua{constructor(){super(...arguments),this.rgb=ha.VECTOR3([1,1,1])}};class JF extends gf{constructor(){super(...arguments),this.paramsConfig=$F}static type(){return\\\\\\\"rgbToHsv\\\\\\\"}initializeNode(){this.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"hsv\\\\\\\",Uo.VEC3)])}setLines(t){const e=[],n=[];e.push(new Cf(this,\\\\\\\"// https://stackoverflow.com/questions/15095909/from-rgb-to-hsv-in-opengl-glsl\\\\nvec3 rgb2hsv(vec3 c)\\\\n{\\\\n\\\\tvec4 K = vec4(0.0, -1.0 / 3.0, 2.0 / 3.0, -1.0);\\\\n\\\\tvec4 p = mix(vec4(c.bg, K.wz), vec4(c.gb, K.xy), step(c.b, c.g));\\\\n\\\\tvec4 q = mix(vec4(p.xyw, c.r), vec4(c.r, p.yzx), step(p.x, c.r));\\\\n\\\\n\\\\tfloat d = q.x - min(q.w, q.y);\\\\n\\\\tfloat e = 1.0e-10;\\\\n\\\\treturn vec3(abs(q.z + (q.w - q.y) / (6.0 * d + e)), d / (q.x + e), q.x);\\\\n}\\\\\\\"));const i=mf.vector3(this.variableForInputParam(this.p.rgb)),s=this.glVarName(\\\\\\\"hsv\\\\\\\");n.push(`vec3 ${s} = rgb2hsv(${i})`),t.addDefinitions(this,e),t.addBodyLines(this,n)}}var ZF;!function(t){t[t.AXIS=0]=\\\\\\\"AXIS\\\\\\\",t[t.QUAT=1]=\\\\\\\"QUAT\\\\\\\"}(ZF||(ZF={}));const QF=[ZF.AXIS,ZF.QUAT],KF={[ZF.AXIS]:\\\\\\\"from axis + angle\\\\\\\",[ZF.QUAT]:\\\\\\\"from quaternion\\\\\\\"},tD={[ZF.AXIS]:[\\\\\\\"vector\\\\\\\",\\\\\\\"axis\\\\\\\",\\\\\\\"angle\\\\\\\"],[ZF.QUAT]:[\\\\\\\"vector\\\\\\\",\\\\\\\"quat\\\\\\\"]},eD={[ZF.AXIS]:\\\\\\\"rotateWithAxisAngle\\\\\\\",[ZF.QUAT]:\\\\\\\"rotateWithQuat\\\\\\\"},nD={[ZF.AXIS]:[Uo.VEC3,Uo.VEC3,Uo.FLOAT],[ZF.QUAT]:[Uo.VEC3,Uo.VEC4]},iD={vector:[0,0,1],axis:[0,1,0]};const sD=new class extends ua{constructor(){super(...arguments),this.signature=ha.INTEGER(ZF.AXIS,{menu:{entries:QF.map(((t,e)=>({name:KF[t],value:e})))}})}};class rD extends gf{constructor(){super(...arguments),this.paramsConfig=sD}static type(){return\\\\\\\"rotate\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this)),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this))}set_signature(t){const e=QF.indexOf(t);this.p.signature.set(e)}_gl_input_name(t){const e=QF[this.pv.signature];return tD[e][t]}paramDefaultValue(t){return iD[t]}gl_method_name(){const t=QF[this.pv.signature];return eD[t]}_expected_input_types(){const t=QF[this.pv.signature];return nD[t]}_expected_output_types(){return[Uo.VEC3]}gl_function_definitions(){return[new Cf(this,NR)]}setLines(t){const e=this.io.outputs.namedOutputConnectionPoints()[0].type(),n=this.io.inputs.namedInputConnectionPoints().map(((t,e)=>{const n=t.name();return mf.any(this.variableForInput(n))})).join(\\\\\\\", \\\\\\\"),i=`${e} ${this.glVarName(this.io.connection_points.output_name(0))} = ${this.gl_method_name()}(${n})`;t.addBodyLines(this,[i]),t.addDefinitions(this,this.gl_function_definitions())}}const oD=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\",\\\\\\\"w\\\\\\\"];class aD extends EP{static type(){return\\\\\\\"round\\\\\\\"}setLines(t){const e=this.io.inputs.namedInputConnectionPoints()[0],n=mf.vector2(this.variableForInput(e.name())),i=this.io.outputs.namedOutputConnectionPoints()[0],s=this.glVarName(i.name()),r=[];if(1==Wo[i.type()])r.push(`${i.type()} ${s} = ${this._simple_line(n)}`);else{const t=oD.map((t=>this._simple_line(`${n}.${t}`)));r.push(`${i.type()} ${s} = ${i.type()}(${t.join(\\\\\\\",\\\\\\\")})`)}t.addBodyLines(this,r)}_simple_line(t){return`sign(${t})*floor(abs(${t})+0.5)`}}const lD=new class extends ua{constructor(){super(...arguments),this.position=ha.VECTOR3([0,0,0]),this.center=ha.VECTOR3([0,0,0]),this.radius=ha.FLOAT(1),this.feather=ha.FLOAT(.1)}};class cD extends gf{constructor(){super(...arguments),this.paramsConfig=lD}static type(){return\\\\\\\"sphere\\\\\\\"}initializeNode(){super.initializeNode(),this.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"float\\\\\\\",Uo.FLOAT)])}setLines(t){const e=mf.vector2(this.variableForInputParam(this.p.position)),n=mf.vector2(this.variableForInputParam(this.p.center)),i=mf.float(this.variableForInputParam(this.p.radius)),s=mf.float(this.variableForInputParam(this.p.feather)),r=`float ${this.glVarName(\\\\\\\"float\\\\\\\")} = disk3d(${e}, ${n}, ${i}, ${s})`;t.addBodyLines(this,[r]),t.addDefinitions(this,[new Cf(this,QR)])}}const hD=new class extends ua{};class uD extends gf{constructor(){super(...arguments),this.paramsConfig=hD}static type(){return ns.INPUT}initializeNode(){this.io.connection_points.set_output_name_function(this._expected_output_names.bind(this)),this.io.connection_points.set_expected_input_types_function((()=>[])),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this))}parent(){return super.parent()}_expected_output_names(t){const e=this.parent();return(null==e?void 0:e.child_expected_input_connection_point_name(t))||`out${t}`}_expected_output_types(){const t=this.parent();return(null==t?void 0:t.child_expected_input_connection_point_types())||[]}setLines(t){const e=this.parent();e&&e.set_lines_block_start(t,this)}}const dD=new class extends ua{};class pD extends gf{constructor(){super(...arguments),this.paramsConfig=dD}static type(){return\\\\\\\"switch\\\\\\\"}initializeNode(){this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this))}_gl_input_name(t){return 0==t?pD.INPUT_INDEX:\\\\\\\"in\\\\\\\"+(t-1)}_expected_input_types(){const t=this.io.connection_points.input_connection_type(1)||Uo.FLOAT,e=this.io.connections.inputConnections(),n=e?or.clamp(e.length,2,16):2,i=[Uo.INT];for(let e=0;e{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.paramName])}))}))}setLines(t){const e=mf.vector2(this.variableForInputParam(this.p.uv)),n=this.glVarName(mD.OUTPUT_NAME),i=this._uniform_name(),s=new Nf(this,Uo.SAMPLER_2D,i),r=`vec4 ${n} = texture2D(${i}, ${e})`;t.addDefinitions(this,[s]),t.addBodyLines(this,[r])}paramsGenerating(){return!0}setParamConfigs(){this._param_configs_controller=this._param_configs_controller||new NF,this._param_configs_controller.reset();const t=new tg(Cr.OPERATOR_PATH,this.pv.paramName,this.pv.defaultValue,this._uniform_name());this._param_configs_controller.push(t)}_uniform_name(){return this.glVarName(this.pv.paramName)}}var fD;mD.OUTPUT_NAME=\\\\\\\"rgba\\\\\\\",function(t){t.POSITION=\\\\\\\"position\\\\\\\",t.DIR_VEC=\\\\\\\"direction vector\\\\\\\"}(fD||(fD={}));const gD=[fD.POSITION,fD.DIR_VEC];const vD=new class extends ua{constructor(){super(...arguments),this.vec=ha.VECTOR3([0,0,0]),this.interpretation=ha.INTEGER(0,{menu:{entries:gD.map(((t,e)=>({name:t,value:e})))}})}};class yD extends gf{constructor(){super(...arguments),this.paramsConfig=vD}static type(){return\\\\\\\"toWorldSpace\\\\\\\"}initializeNode(){this.io.connection_points.spare_params.set_inputless_param_names([\\\\\\\"interpretation\\\\\\\"]),this.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"out\\\\\\\",Uo.VEC3)])}setLines(t){const e=[],n=mf.vector3(this.variableForInputParam(this.p.vec)),i=this.glVarName(\\\\\\\"out\\\\\\\");switch(gD[this.pv.interpretation]){case fD.POSITION:e.push(`vec3 ${i} = (modelMatrix * vec4( ${n}, 1.0 )).xyz`);break;case fD.DIR_VEC:e.push(`vec3 ${i} = normalize( mat3( modelMatrix[0].xyz, modelMatrix[1].xyz, modelMatrix[2].xyz ) * ${n} )`)}t.addBodyLines(this,e)}}var xD;!function(t){t.CONDITION=\\\\\\\"condition\\\\\\\",t.IF_TRUE=\\\\\\\"ifTrue\\\\\\\",t.IF_FALSE=\\\\\\\"ifFalse\\\\\\\"}(xD||(xD={}));const bD=[xD.CONDITION,xD.IF_TRUE,xD.IF_FALSE];class wD extends yf{static type(){return\\\\\\\"twoWaySwitch\\\\\\\"}initializeNode(){super.initializeNode(),this.io.connection_points.initializeNode(),this.io.connection_points.set_expected_input_types_function(this._expected_input_types.bind(this)),this.io.connection_points.set_expected_output_types_function(this._expected_output_types.bind(this)),this.io.connection_points.set_input_name_function(this._gl_input_name.bind(this)),this.io.connection_points.set_output_name_function(this._gl_output_name.bind(this))}_gl_input_name(t){return bD[t]}_gl_output_name(){return\\\\\\\"val\\\\\\\"}_expected_input_types(){const t=this.io.connections.inputConnection(1)||this.io.connections.inputConnection(2),e=t?t.src_connection_point().type():Uo.FLOAT;return[Uo.BOOL,e,e]}_expected_output_types(){return[this._expected_input_types()[1]]}setLines(t){const e=[],n=this.glVarName(\\\\\\\"val\\\\\\\"),i=mf.bool(this.variableForInput(xD.CONDITION)),s=mf.any(this.variableForInput(xD.IF_TRUE)),r=mf.any(this.variableForInput(xD.IF_FALSE)),o=this._expected_output_types()[0];e.push(`${o} ${n}`),e.push(`if(${i}){`),e.push(`${n} = ${s}`),e.push(\\\\\\\"} else {\\\\\\\"),e.push(`${n} = ${r}`),e.push(\\\\\\\"}\\\\\\\"),t.addBodyLines(this,e)}}const TD=[Uo.FLOAT,Uo.VEC2,Uo.VEC3,Uo.VEC4];const AD=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(\\\\\\\"\\\\\\\"),this.type=ha.INTEGER(0,{menu:{entries:TD.map(((t,e)=>({name:t,value:e})))}})}};class MD extends gf{constructor(){super(...arguments),this.paramsConfig=AD,this._on_create_set_name_if_none_bound=this._on_create_set_name_if_none.bind(this)}static type(){return\\\\\\\"varyingRead\\\\\\\"}initializeNode(){this.addPostDirtyHook(\\\\\\\"_set_mat_to_recompile\\\\\\\",this._set_mat_to_recompile.bind(this)),this.lifecycle.add_on_create_hook(this._on_create_set_name_if_none_bound),this.io.connection_points.initializeNode(),this.io.connection_points.set_output_name_function((()=>this.output_name)),this.io.connection_points.set_expected_input_types_function((()=>[])),this.io.connection_points.set_expected_output_types_function((()=>[TD[this.pv.type]])),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name])}))}))}get output_name(){return MD.OUTPUT_NAME}setLines(t){if(t.current_shader_name==Mf.FRAGMENT){const e=this.pv.name,n=new Lf(this,this.gl_type(),e),i=this.glVarName(MD.OUTPUT_NAME),s=`${this.gl_type()} ${i} = ${e}`;t.addDefinitions(this,[n]),t.addBodyLines(this,[s])}}get attribute_name(){return this.pv.name.trim()}gl_type(){return this.io.outputs.namedOutputConnectionPoints()[0].type()}set_gl_type(t){this.p.type.set(TD.indexOf(t))}_on_create_set_name_if_none(){\\\\\\\"\\\\\\\"==this.pv.name&&this.p.name.set(this.name())}}MD.OUTPUT_NAME=\\\\\\\"fragment\\\\\\\";const ED={start:[0,0,1],end:[1,0,0],up:[0,1,0]};class SD extends(aR(\\\\\\\"vectorAlign\\\\\\\",{in:[\\\\\\\"start\\\\\\\",\\\\\\\"end\\\\\\\",\\\\\\\"up\\\\\\\"],method:\\\\\\\"vectorAlignWithUp\\\\\\\",functions:[NR]})){_expected_input_types(){const t=Uo.VEC3;return[t,t,t]}_expected_output_types(){return[Uo.VEC4]}paramDefaultValue(t){return ED[t]}}const CD={start:[0,0,1],end:[1,0,0]};class ND extends(QP(\\\\\\\"vectorAngle\\\\\\\",{in:[\\\\\\\"start\\\\\\\",\\\\\\\"end\\\\\\\"],method:\\\\\\\"vectorAngle\\\\\\\",functions:[NR]})){_expected_input_types(){const t=Uo.VEC3;return[t,t]}_expected_output_types(){return[Uo.FLOAT]}paramDefaultValue(t){return CD[t]}}const LD={only:[`${zI.context()}/${zI.type()}`,`${MI.context()}/${MI.type()}`,`${NI.context()}/${NI.type()}`]};class OD extends aa{static context(){return ts.JS}initializeBaseNode(){this.uiData.setLayoutHorizontal(),this.io.connection_points.initializeNode()}cook(){console.warn(\\\\\\\"js nodes should never cook\\\\\\\")}_set_function_node_to_recompile(){var t;null===(t=this.function_node)||void 0===t||t.assembler_controller.set_compilation_required_and_dirty(this)}get function_node(){var t;const e=this.parent();if(e)return e.type()==this.type()?null===(t=e)||void 0===t?void 0:t.function_node:e}js_var_name(t){return`v_POLY_${this.name()}_${t}`}variableForInput(t){const e=this.io.inputs.get_input_index(t),n=this.io.connections.inputConnection(e);if(n){const e=n.node_src,i=e.io.outputs.namedOutputConnectionPoints()[n.output_index];if(i){const t=i.name();return e.js_var_name(t)}throw console.warn(`no output called '${t}' for gl node ${e.path()}`),\\\\\\\"variable_for_input ERROR\\\\\\\"}return\\\\\\\"to debug...\\\\\\\"}setLines(t){}reset_code(){var t;null===(t=this._param_configs_controller)||void 0===t||t.reset()}setParamConfigs(){}param_configs(){var t;return null===(t=this._param_configs_controller)||void 0===t?void 0:t.list()}js_input_default_value(t){return null}}new class extends ua{};const PD=[Xo.FLOAT,Xo.VEC2,Xo.VEC3,Xo.VEC4];const RD=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(\\\\\\\"\\\\\\\"),this.type=ha.INTEGER(0,{menu:{entries:PD.map(((t,e)=>({name:t,value:e})))}})}};class ID extends OD{constructor(){super(...arguments),this.paramsConfig=RD,this._on_create_set_name_if_none_bound=this._on_create_set_name_if_none.bind(this)}static type(){return\\\\\\\"attribute\\\\\\\"}initializeNode(){this.lifecycle.add_on_create_hook(this._on_create_set_name_if_none_bound),this.io.connection_points.initializeNode(),this.io.connection_points.set_expected_input_types_function((()=>[])),this.io.connection_points.set_expected_output_types_function((()=>[PD[this.pv.type]]))}get input_name(){return ID.INPUT_NAME}get output_name(){return ID.OUTPUT_NAME}setLines(t){var e;null===(e=this.function_node)||void 0===e||e.assembler_controller.assembler.set_node_lines_attribute(this,t)}get attribute_name(){return this.pv.name.trim()}gl_type(){return this.io.outputs.namedOutputConnectionPoints()[0].type()}set_gl_type(t){this.p.type.set(PD.indexOf(t))}connected_input_node(){return this.io.inputs.named_input(ID.INPUT_NAME)}connected_input_connection_point(){return this.io.inputs.named_input_connection_point(ID.INPUT_NAME)}output_connection_point(){return this.io.outputs.namedOutputConnectionPointsByName(this.input_name)}get is_importing(){return this.io.outputs.used_output_names().length>0}_on_create_set_name_if_none(){\\\\\\\"\\\\\\\"==this.pv.name&&this.p.name.set(this.name())}}ID.INPUT_NAME=\\\\\\\"export\\\\\\\",ID.OUTPUT_NAME=\\\\\\\"val\\\\\\\";const FD=new class extends ua{};class DD extends OD{constructor(){super(...arguments),this.paramsConfig=FD}static type(){return\\\\\\\"globals\\\\\\\"}createParams(){var t;null===(t=this.function_node)||void 0===t||t.assembler_controller.add_globals_outputs(this)}setLines(t){var e,n;null===(n=null===(e=this.function_node)||void 0===e?void 0:e.assembler_controller)||void 0===n||n.assembler.set_node_lines_globals(this,t)}}const BD=new class extends ua{};class zD extends OD{constructor(){super(...arguments),this.paramsConfig=BD}static type(){return\\\\\\\"output\\\\\\\"}initializeNode(){super.initializeNode(),this.addPostDirtyHook(\\\\\\\"_set_mat_to_recompile\\\\\\\",this._set_function_node_to_recompile.bind(this))}createParams(){var t;null===(t=this.function_node)||void 0===t||t.assembler_controller.add_output_inputs(this)}setLines(t){var e;null===(e=this.function_node)||void 0===e||e.assembler_controller.assembler.set_node_lines_output(this,t)}}class kD{constructor(t=[]){this._definitions=t,this._errored=!1}get errored(){return this._errored}get error_message(){return this._error_message}uniq(){const t=new Map,e=[];for(let n of this._definitions)if(!this._errored){const i=n.name(),s=t.get(i);s?s.data_type!=n.data_type&&(this._errored=!0,this._error_message=`attempt to create '${n.name()}' with types '${n.data_type}' by node '${n.node.path()}', when there is already an existing with type ${s.data_type} from node '${s.node.path()}'`,console.warn(\\\\\\\"emitting error message:\\\\\\\",this._error_message)):(t.set(i,n),e.push(i))}const n=[];for(let i of e){const e=t.get(i);e&&n.push(e)}return n}}var UD;!function(t){t.ATTRIBUTE=\\\\\\\"attribute\\\\\\\",t.FUNCTION=\\\\\\\"function\\\\\\\",t.UNIFORM=\\\\\\\"uniform\\\\\\\"}(UD||(UD={}));class GD{constructor(t,e,n,i){this._definition_type=t,this._data_type=e,this._node=n,this._name=i}get definition_type(){return this._definition_type}get data_type(){return this._data_type}get node(){return this._node}name(){return this._name}collection_instance(){return new kD}}class VD extends GD{constructor(t,e,n){super(UD.UNIFORM,e,t,n),this._node=t,this._data_type=e,this._name=n}get line(){return`uniform ${this.data_type} ${this.name()}`}}class HD extends Kf{constructor(t,e,n,i){super(t,e,n),this._uniform_name=i}get uniform_name(){return this._uniform_name}static uniform_by_type(t){switch(t){case Cr.BOOLEAN:case Cr.BUTTON:return{value:0};case Cr.COLOR:return{value:new D.a(0,0,0)};case Cr.FLOAT:case Cr.FOLDER:case Cr.INTEGER:case Cr.OPERATOR_PATH:case Cr.NODE_PATH:case Cr.PARAM_PATH:return{value:0};case Cr.RAMP:case Cr.STRING:return{value:null};case Cr.VECTOR2:return{value:new d.a(0,0)};case Cr.VECTOR3:return{value:new p.a(0,0,0)};case Cr.VECTOR4:return{value:new _.a(0,0,0,0)}}os.unreachable(t)}}const jD=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(\\\\\\\"\\\\\\\"),this.type=ha.INTEGER(Yo.indexOf(Xo.FLOAT),{menu:{entries:Yo.map(((t,e)=>({name:t,value:e})))}}),this.asColor=ha.BOOLEAN(0,{visibleIf:{type:Yo.indexOf(Xo.VEC3)}})}};class WD extends OD{constructor(){super(...arguments),this.paramsConfig=jD,this._allow_inputs_created_from_params=!1,this._on_create_set_name_if_none_bound=this._on_create_set_name_if_none.bind(this)}static type(){return\\\\\\\"param\\\\\\\"}initializeNode(){this.addPostDirtyHook(\\\\\\\"_set_mat_to_recompile\\\\\\\",this._set_function_node_to_recompile.bind(this)),this.lifecycle.add_on_create_hook(this._on_create_set_name_if_none_bound),this.io.connection_points.initializeNode(),this.io.connection_points.set_expected_input_types_function((()=>[])),this.io.connection_points.set_expected_output_types_function((()=>[Yo[this.pv.type]]))}setLines(t){const e=[],n=Yo[this.pv.type],i=this.uniform_name();e.push(new VD(this,n,i)),t.addDefinitions(this,e)}setParamConfigs(){const t=Yo[this.pv.type],e=Zo[t];let n=$o[t];if(this._param_configs_controller=this._param_configs_controller||new NF,this._param_configs_controller.reset(),n==Cr.VECTOR3&&this.p.asColor.value&&m.isArray(e)&&3==e.length){const t=new HD(Cr.COLOR,this.pv.name,e,this.uniform_name());this._param_configs_controller.push(t)}else{const t=new HD(n,this.pv.name,e,this.uniform_name());this._param_configs_controller.push(t)}}uniform_name(){const t=this.io.outputs.namedOutputConnectionPoints()[0];return this.js_var_name(t.name())}set_gl_type(t){const e=Yo.indexOf(t);this.p.type.set(e)}_on_create_set_name_if_none(){\\\\\\\"\\\\\\\"==this.pv.name&&this.p.name.set(this.name())}}class qD extends aa{constructor(){super(...arguments),this._cook_main_without_inputs_when_dirty_bound=this._cook_main_without_inputs_when_dirty.bind(this)}static context(){return ts.MAT}initializeBaseNode(){super.initializeBaseNode(),this.nameController.add_post_set_fullPath_hook(this.set_material_name.bind(this)),this.addPostDirtyHook(\\\\\\\"_cook_main_without_inputs_when_dirty\\\\\\\",(()=>{setTimeout(this._cook_main_without_inputs_when_dirty_bound,0)}))}async _cook_main_without_inputs_when_dirty(){await this.cookController.cookMainWithoutInputs()}set_material_name(){this._material&&(this._material.name=this.path())}get material(){return this._material=this._material||this.createMaterial()}setMaterial(t){this._setContainer(t)}}class XD{constructor(t){this.node=t}add_params(){}update(){}get material(){return this.node.material}}const YD={NoBlending:w.ub,NormalBlending:w.xb,AdditiveBlending:w.e,SubtractiveBlending:w.Sc,MultiplyBlending:w.mb},$D=Object.keys(YD);function JD(t){return class extends t{constructor(){super(...arguments),this.doubleSided=ha.BOOLEAN(0),this.front=ha.BOOLEAN(1,{visibleIf:{doubleSided:!1}}),this.overrideShadowSide=ha.BOOLEAN(0),this.shadowDoubleSided=ha.BOOLEAN(0,{visibleIf:{overrideShadowSide:!0}}),this.shadowFront=ha.BOOLEAN(1,{visibleIf:{overrideShadowSide:!0,shadowDoubleSided:!1}}),this.colorWrite=ha.BOOLEAN(1,{separatorBefore:!0,cook:!1,callback:(t,e)=>{ZD.update(t)}}),this.depthWrite=ha.BOOLEAN(1,{cook:!1,callback:(t,e)=>{ZD.update(t)}}),this.depthTest=ha.BOOLEAN(1,{cook:!1,callback:(t,e)=>{ZD.update(t)}}),this.premultipliedAlpha=ha.BOOLEAN(!1,{separatorAfter:!0}),this.blending=ha.INTEGER(w.xb,{menu:{entries:$D.map((t=>({name:t,value:YD[t]})))}}),this.dithering=ha.BOOLEAN(0),this.polygonOffset=ha.BOOLEAN(!1,{separatorBefore:!0}),this.polygonOffsetFactor=ha.INTEGER(0,{range:[0,1e3],visibleIf:{polygonOffset:1}}),this.polygonOffsetUnits=ha.INTEGER(0,{range:[0,1e3],visibleIf:{polygonOffset:1}})}}}JD(ua);class ZD extends XD{constructor(t){super(t),this.node=t}initializeNode(){}async update(){const t=this.node.material,e=this.node.pv;this._updateSides(t,e),t.colorWrite=e.colorWrite,t.depthWrite=e.depthWrite,t.depthTest=e.depthTest,t.blending=e.blending,t.premultipliedAlpha=e.premultipliedAlpha,t.dithering=e.dithering,t.polygonOffset=e.polygonOffset,t.polygonOffset&&(t.polygonOffsetFactor=e.polygonOffsetFactor,t.polygonOffsetUnits=e.polygonOffsetUnits,t.needsUpdate=!0)}_updateSides(t,e){const n=e.front?w.H:w.i,i=e.doubleSided?w.z:n;if(i!=t.side&&(t.side=i,t.needsUpdate=!0),e.overrideShadowSide){const t=e.shadowFront?w.H:w.i,n=e.shadowDoubleSided?w.z:t,i=this.node.material;n!=i.shadowSide&&(i.shadowSide=n,i.needsUpdate=!0)}else t.shadowSide=null;const s=t.customMaterials;if(s){const t=Object.keys(s);for(let n of t){const t=s[n];t&&this._updateSides(t,e)}}}static async update(t){t.controllers.advancedCommon.update()}}class QD extends(JD(ua)){constructor(){super(...arguments),this.color=ha.COLOR([1,1,1]),this.lineWidth=ha.FLOAT(1,{range:[1,10],rangeLocked:[!0,!1]})}}const KD=new QD;class tB extends qD{constructor(){super(...arguments),this.paramsConfig=KD,this.controllers={advancedCommon:new ZD(this)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"lineBasic\\\\\\\"}createMaterial(){return new As.a({color:16777215,linewidth:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();this.material.color.copy(this.pv.color),this.material.linewidth=this.pv.lineWidth,this.setMaterial(this.material)}}function eB(t){return class extends t{constructor(){super(...arguments),this.transparent=ha.BOOLEAN(0),this.opacity=ha.FLOAT(1),this.alphaTest=ha.FLOAT(0)}}}eB(ua);class nB extends XD{constructor(t){super(t),this.node=t}static update(t){const e=t.material,n=t.pv;this._updateTransparency(e,n)}static _updateTransparency(t,e){t.transparent=e.transparent,this._updateCommon(t,e)}static _updateCommon(t,e){t.uniforms.opacity&&(t.uniforms.opacity.value=e.opacity),t.opacity=e.opacity,t.alphaTest=e.alphaTest;const n=t.customMaterials;if(n){const t=Object.keys(n);for(let i of t){const t=n[i];t&&this._updateCommon(t,e)}}}}class iB extends Qf{constructor(t){super(t),this.node=t}toJSON(){const t=this.node.assemblerController;if(!t)return;const e={},n=this.node.material.customMaterials;if(n){const t=Object.keys(n);for(let i of t){const t=n[i];if(t){const n=this._materialToJson(t,{node:this.node,suffix:i});n&&(e[i]=n)}}}const i=[],s=t.assembler.param_configs();for(let t of s)i.push([t.name(),t.uniform_name]);const r=this._materialToJson(this.node.material,{node:this.node,suffix:\\\\\\\"main\\\\\\\"});r||console.warn(\\\\\\\"failed to save material from node\\\\\\\",this.node.path());return{material:r||{},uniforms_time_dependent:t.assembler.uniformsTimeDependent(),uniforms_resolution_dependent:t.assembler.uniforms_resolution_dependent(),param_uniform_pairs:i,customMaterials:e}}load(t){if(this._material=this._loadMaterial(t.material),this._material){if(this._material.customMaterials=this._material.customMaterials||{},t.customMaterials){const e=Object.keys(t.customMaterials);for(let n of e){const e=t.customMaterials[n],i=this._loadMaterial(e);i&&(this._material.customMaterials[n]=i)}}if(t.uniforms_time_dependent&&this.node.scene().uniformsController.addTimeDependentUniformOwner(this._material.uuid,this._material.uniforms),t.uniforms_resolution_dependent&&this.node.scene().uniformsController.addResolutionDependentUniformOwner(this._material.uuid,this._material.uniforms),t.param_uniform_pairs)for(let e of t.param_uniform_pairs){const t=e[0],n=e[1],i=this.node.params.get(t),s=this._material.uniforms[n],r=Object.keys(this._material.customMaterials);let o;for(let t of r){const e=this._material.customMaterials[t],i=null==e?void 0:e.uniforms[n];i&&(o=o||[],o.push(i))}i&&(s||o)&&i.options.setOption(\\\\\\\"callback\\\\\\\",(()=>{if(s&&tg.callback(i,s),o)for(let t of o)tg.callback(i,t)}))}}}material(){if(li.playerMode())return this._material}}function sB(t){return class extends t{constructor(){super(...arguments),this.setBuilderNode=ha.BOOLEAN(0,{callback:t=>{rB.PARAM_CALLBACK_setCompileRequired(t)}}),this.builderNode=ha.NODE_PATH(\\\\\\\"\\\\\\\",{visibleIf:{setBuilderNode:!0},callback:t=>{rB.PARAM_CALLBACK_setCompileRequired(t)}})}}}sB(ua);class rB extends qD{constructor(){super(...arguments),this._children_controller_context=ts.GL,this.persisted_config=new iB(this)}createMaterial(){var t;let e;return this.persisted_config&&(e=this.persisted_config.material()),e||(e=null===(t=this.assemblerController)||void 0===t?void 0:t.assembler.createMaterial()),e}get assemblerController(){return this._assembler_controller=this._assembler_controller||this._create_assembler_controller()}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}childrenAllowed(){return this.assemblerController?super.childrenAllowed():(this.scene().markAsReadOnly(this),!1)}compileIfRequired(){var t;(null===(t=this.assemblerController)||void 0===t?void 0:t.compileRequired())&&this._compile()}_compile(){const t=this.assemblerController;this.material&&t&&(t.assembler.setGlParentNode(this),this._setAssemblerGlParentNode(t),t.assembler.compileMaterial(this.material),t.post_compile())}_setAssemblerGlParentNode(t){if(!this.pv.setBuilderNode)return;const e=this.pv.builderNode.nodeWithContext(ts.MAT);if(!e)return;const n=e;n.assemblerController?n.type()==this.type()?t.assembler.setGlParentNode(n):this.states.error.set(`resolved node '${e.path()}' does not have the same type '${e.type()}' as current node '${this.type()}'`):this.states.error.set(`resolved node '${e.path()}' is not a builder node`)}static PARAM_CALLBACK_setCompileRequired(t){t.PARAM_CALLBACK_setCompileRequired()}PARAM_CALLBACK_setCompileRequired(){var t;null===(t=this.assemblerController)||void 0===t||t.setCompilationRequired(!0)}}function oB(t){return class extends t{constructor(){super(...arguments),this.useFog=ha.BOOLEAN(0)}}}oB(ua);class aB extends XD{constructor(t){super(t),this.node=t}static update(t){const e=t.material,n=t.pv;e.fog=n.useFog}}function lB(t){return class extends t{constructor(){super(...arguments),this.default=ha.FOLDER(null)}}}function cB(t){return class extends t{constructor(){super(...arguments),this.advanced=ha.FOLDER(null)}}}class hB extends(oB(JD(sB(cB(eB(lB(ua))))))){constructor(){super(...arguments),this.linewidth=ha.FLOAT(1,{range:[0,10],rangeLocked:[!0,!1]})}}const uB=new hB;class dB extends rB{constructor(){super(...arguments),this.paramsConfig=uB,this.controllers={advancedCommon:new ZD(this)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"lineBasicBuilder\\\\\\\"}usedAssembler(){return jn.GL_LINE}_create_assembler_controller(){return li.assemblersRegister.assembler(this,this.usedAssembler())}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();nB.update(this),aB.update(this),this.compileIfRequired(),this.material.linewidth=this.pv.linewidth,this.setMaterial(this.material)}}function pB(t){return class extends t{constructor(){super(...arguments),this.color=ha.COLOR([1,1,1],{conversion:lo.SRGB_TO_LINEAR}),this.useVertexColors=ha.BOOLEAN(0,{separatorAfter:!0}),this.transparent=ha.BOOLEAN(0),this.opacity=ha.FLOAT(1),this.alphaTest=ha.FLOAT(0)}}}O.a;pB(ua);class _B extends XD{constructor(t){super(t),this.node=t}static update(t){const e=t.material,n=t.pv;e.color.copy(n.color);const i=n.useVertexColors;i!=e.vertexColors&&(e.vertexColors=i,e.needsUpdate=!0),e.opacity=n.opacity,e.transparent=n.transparent,e.alphaTest=n.alphaTest}}function mB(t){return class extends t{constructor(){super(...arguments),this.useFog=ha.BOOLEAN(0)}}}mB(ua);class fB extends XD{constructor(t){super(t),this.node=t}static update(t){const e=t.material,n=t.pv;e.fog=n.useFog}}function gB(t){return{cook:!1,callback:(e,n)=>{t.update(e)}}}function vB(t,e,n){return{visibleIf:{[e]:1},nodeSelection:{context:ts.COP,types:null==n?void 0:n.types},cook:!1,callback:(e,n)=>{t.update(e)}}}class yB extends XD{constructor(t,e){super(t),this.node=t,this._update_options=e}add_hooks(t,e){t.addPostDirtyHook(\\\\\\\"TextureController\\\\\\\",(()=>{this.update()})),e.addPostDirtyHook(\\\\\\\"TextureController\\\\\\\",(()=>{this.update()}))}static update(t){}async _update(t,e,n,i){if(this._update_options.uniforms){const s=t,r=e;await this._update_texture_on_uniforms(s,r,n,i)}if(this._update_options.directParams){const s=t,r=e;await this._update_texture_on_material(s,r,n,i)}}async _update_texture_on_uniforms(t,e,n,i){this._update_required_attribute(t,t.uniforms,e,n,i,this._apply_texture_on_uniforms.bind(this),this._remove_texture_from_uniforms.bind(this))}_apply_texture_on_uniforms(t,e,n,i){const s=null!=e[n]&&null!=e[n].value;let r=!1;if(s){e[n].value.uuid!=i.uuid&&(r=!0)}if(!s||r){e[n]&&(e[n].value=i),this._apply_texture_on_material(t,t,n,i),t.needsUpdate=!0;const s=t.customMaterials;if(s){const t=Object.keys(s);for(let e of t){const t=s[e];t&&this._apply_texture_on_uniforms(t,t.uniforms,n,i)}}}}_remove_texture_from_uniforms(t,e,n){if(e[n]){if(e[n].value){e[n].value=null,this._remove_texture_from_material(t,t,n),t.needsUpdate=!0;const i=t.customMaterials;if(i){const t=Object.keys(i);for(let e of t){const t=i[e];t&&this._remove_texture_from_uniforms(t,t.uniforms,n)}}}}else li.warn(`'${n}' uniform not found. existing uniforms are:`,Object.keys(e).sort())}async _update_texture_on_material(t,e,n,i){this._update_required_attribute(t,t,e,n,i,this._apply_texture_on_material.bind(this),this._remove_texture_from_material.bind(this))}_apply_texture_on_material(t,e,n,i){const s=null!=e[n];let r=!1;if(s){e[n].uuid!=i.uuid&&(r=!0)}s&&!r||(e[n]=i,t.needsUpdate=!0)}_remove_texture_from_material(t,e,n){e[n]&&(e[n]=null,t.needsUpdate=!0)}async _update_required_attribute(t,e,n,i,s,r,o){i.isDirty()&&await i.compute();if(i.value){s.isDirty()&&await s.compute();const i=s.value.nodeWithContext(ts.COP);if(i){const s=(await i.compute()).texture();if(s)return void r(t,e,n,s)}}o(t,e,n)}}function xB(t){return class extends t{constructor(){super(...arguments),this.useMap=ha.BOOLEAN(0,gB(bB)),this.map=ha.NODE_PATH(vi.EMPTY,vB(bB,\\\\\\\"useMap\\\\\\\"))}}}O.a;xB(ua);class bB extends yB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useMap,this.node.p.map)}async update(){this._update(this.node.material,\\\\\\\"map\\\\\\\",this.node.p.useMap,this.node.p.map)}static async update(t){t.controllers.map.update()}}function wB(t){return class extends t{constructor(){super(...arguments),this.useAlphaMap=ha.BOOLEAN(0,{separatorBefore:!0,...gB(TB)}),this.alphaMap=ha.NODE_PATH(vi.EMPTY,vB(TB,\\\\\\\"useAlphaMap\\\\\\\"))}}}O.a;wB(ua);class TB extends yB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useAlphaMap,this.node.p.alphaMap)}async update(){this._update(this.node.material,\\\\\\\"alphaMap\\\\\\\",this.node.p.useAlphaMap,this.node.p.alphaMap)}static async update(t){t.controllers.alphaMap.update()}}function AB(t){return class extends t{constructor(){super(...arguments),this.useAOMap=ha.BOOLEAN(0,{separatorBefore:!0,...gB(MB)}),this.aoMap=ha.NODE_PATH(vi.EMPTY,vB(MB,\\\\\\\"useAOMap\\\\\\\")),this.aoMapIntensity=ha.FLOAT(1,{range:[0,1],rangeLocked:[!1,!1],visibleIf:{useAOMap:1}})}}}O.a;AB(ua);class MB extends yB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useAOMap,this.node.p.aoMap)}async update(){if(this._update(this.node.material,\\\\\\\"aoMap\\\\\\\",this.node.p.useAOMap,this.node.p.aoMap),this._update_options.uniforms){this.node.material.uniforms.aoMapIntensity.value=this.node.pv.aoMapIntensity}if(this._update_options.directParams){this.node.material.aoMapIntensity=this.node.pv.aoMapIntensity}}static async update(t){t.controllers.aoMap.update()}}var EB;!function(t){t.MULT=\\\\\\\"mult\\\\\\\",t.ADD=\\\\\\\"add\\\\\\\",t.MIX=\\\\\\\"mix\\\\\\\"}(EB||(EB={}));const SB=[EB.MULT,EB.ADD,EB.MIX],CB={[EB.MULT]:w.nb,[EB.ADD]:w.c,[EB.MIX]:w.lb};function NB(t){return class extends t{constructor(){super(...arguments),this.useEnvMap=ha.BOOLEAN(0,gB(LB)),this.envMap=ha.NODE_PATH(vi.EMPTY,vB(LB,\\\\\\\"useEnvMap\\\\\\\",{types:[Fg.CUBE_CAMERA]})),this.combine=ha.INTEGER(0,{visibleIf:{useEnvMap:1},menu:{entries:SB.map(((t,e)=>({name:t,value:e})))}}),this.reflectivity=ha.FLOAT(1,{visibleIf:{useEnvMap:1}}),this.refractionRatio=ha.FLOAT(.98,{range:[-1,1],rangeLocked:[!1,!1],visibleIf:{useEnvMap:1}})}}}NB(ua);class LB extends yB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useEnvMap,this.node.p.envMap)}async update(){this._update(this.node.material,\\\\\\\"envMap\\\\\\\",this.node.p.useEnvMap,this.node.p.envMap);const t=CB[SB[this.node.pv.combine]];if(this._update_options.uniforms){const t=this.node.material;t.uniforms.reflectivity.value=this.node.pv.reflectivity,t.uniforms.refractionRatio.value=this.node.pv.refractionRatio}if(this._update_options.directParams){const e=this.node.material;e.combine=t,e.reflectivity=this.node.pv.reflectivity,e.refractionRatio=this.node.pv.refractionRatio}}static async update(t){t.controllers.envMap.update()}}function OB(t){return class extends t{constructor(){super(...arguments),this.useLightMap=ha.BOOLEAN(0,{separatorBefore:!0,...gB(PB)}),this.lightMap=ha.NODE_PATH(vi.EMPTY,vB(PB,\\\\\\\"useLightMap\\\\\\\")),this.lightMapIntensity=ha.FLOAT(1,{visibleIf:{useLightMap:1}})}}}O.a;OB(ua);class PB extends yB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useLightMap,this.node.p.lightMap)}async update(){if(this._update(this.node.material,\\\\\\\"lightMap\\\\\\\",this.node.p.useLightMap,this.node.p.lightMap),this._update_options.uniforms){this.node.material.uniforms.lightMapIntensity.value=this.node.pv.lightMapIntensity}if(this._update_options.directParams){this.node.material.lightMapIntensity=this.node.pv.lightMapIntensity}}static async update(t){t.controllers.lightMap.update()}}var RB;!function(t){t.ROUND=\\\\\\\"round\\\\\\\",t.BUTT=\\\\\\\"butt\\\\\\\",t.SQUARE=\\\\\\\"square\\\\\\\"}(RB||(RB={}));const IB=[RB.ROUND,RB.BUTT,RB.SQUARE];var FB;!function(t){t.ROUND=\\\\\\\"round\\\\\\\",t.BEVEL=\\\\\\\"bevel\\\\\\\",t.MITER=\\\\\\\"miter\\\\\\\"}(FB||(FB={}));const DB=[FB.ROUND,FB.BEVEL,FB.MITER];function BB(t){return class extends t{constructor(){super(...arguments),this.wireframe=ha.BOOLEAN(0,{separatorBefore:!0}),this.wireframeLinecap=ha.INTEGER(0,{menu:{entries:IB.map(((t,e)=>({name:t,value:e})))},visibleIf:{wireframe:1}}),this.wireframeLinejoin=ha.INTEGER(0,{menu:{entries:DB.map(((t,e)=>({name:t,value:e})))},visibleIf:{wireframe:1}})}}}O.a;BB(ua);class zB extends XD{constructor(t){super(t),this.node=t}static update(t){const e=t.material,n=t.pv;e.wireframe=n.wireframe,e.wireframeLinecap=IB[n.wireframeLinecap],e.wireframeLinejoin=DB[n.wireframeLinejoin],e.needsUpdate=!0}}function kB(t){return class extends t{constructor(){super(...arguments),this.textures=ha.FOLDER(null)}}}const UB={directParams:!0};class GB extends(mB(BB(JD(cB(OB(NB(AB(wB(xB(kB(pB(lB(ua))))))))))))){}const VB=new GB;class HB extends qD{constructor(){super(...arguments),this.paramsConfig=VB,this.controllers={advancedCommon:new ZD(this),alphaMap:new TB(this,UB),aoMap:new MB(this,UB),envMap:new LB(this,UB),lightMap:new PB(this,UB),map:new bB(this,UB)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshBasic\\\\\\\"}createMaterial(){return new lt.a({vertexColors:!1,side:w.H,color:16777215,opacity:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();_B.update(this),fB.update(this),zB.update(this),this.setMaterial(this.material)}}function jB(t){return class extends t{constructor(){super(...arguments),this.wireframe=ha.BOOLEAN(0)}}}jB(ua);class WB extends XD{constructor(t){super(t),this.node=t}static update(t){const e=t.material,n=t.pv;e.wireframe=n.wireframe,e.needsUpdate=!0}}const qB={uniforms:!0};class XB extends(oB(jB(JD(sB(cB(NB(AB(wB(xB(kB(eB(lB(ua))))))))))))){}const YB=new XB;class $B extends rB{constructor(){super(...arguments),this.paramsConfig=YB,this.controllers={advancedCommon:new ZD(this),alphaMap:new TB(this,qB),aoMap:new MB(this,qB),envMap:new LB(this,qB),map:new bB(this,qB)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshBasicBuilder\\\\\\\"}usedAssembler(){return jn.GL_MESH_BASIC}_create_assembler_controller(){return li.assemblersRegister.assembler(this,this.usedAssembler())}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();nB.update(this),aB.update(this),WB.update(this),this.compileIfRequired(),this.setMaterial(this.material)}}function JB(t){return class extends t{constructor(){super(...arguments),this.emissive=ha.COLOR([0,0,0],{separatorBefore:!0}),this.useEmissiveMap=ha.BOOLEAN(0,gB(ZB)),this.emissiveMap=ha.NODE_PATH(vi.EMPTY,vB(ZB,\\\\\\\"useEmissiveMap\\\\\\\")),this.emissiveIntensity=ha.FLOAT(1)}}}O.a;JB(ua);class ZB extends yB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useEmissiveMap,this.node.p.emissiveMap)}async update(){if(this._update(this.node.material,\\\\\\\"emissiveMap\\\\\\\",this.node.p.useEmissiveMap,this.node.p.emissiveMap),this._update_options.uniforms){this.node.material.uniforms.emissive.value.copy(this.node.pv.emissive)}if(this._update_options.directParams){const t=this.node.material;t.emissive.copy(this.node.pv.emissive),t.emissiveIntensity=this.node.pv.emissiveIntensity}}static async update(t){t.controllers.emissiveMap.update()}}const QB={directParams:!0};class KB extends(mB(BB(JD(cB(OB(NB(JB(AB(wB(xB(kB(pB(lB(ua)))))))))))))){}const tz=new KB;class ez extends qD{constructor(){super(...arguments),this.paramsConfig=tz,this.controllers={advancedCommon:new ZD(this),alphaMap:new TB(this,QB),aoMap:new MB(this,QB),emissiveMap:new ZB(this,QB),envMap:new LB(this,QB),lightMap:new PB(this,QB),map:new bB(this,QB)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshLambert\\\\\\\"}createMaterial(){return new Ts.a({vertexColors:!1,side:w.H,color:16777215,opacity:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();_B.update(this),fB.update(this),zB.update(this),this.setMaterial(this.material)}}function nz(t){return class extends t{constructor(){super(...arguments),this.shadowPCSS=ha.BOOLEAN(0,{callback:t=>{iz.PARAM_CALLBACK_setRecompileRequired(t)},separatorBefore:!0}),this.shadowPCSSSamplesCount=ha.INTEGER(16,{visibleIf:{shadowPCSS:1},range:[0,128],rangeLocked:[!0,!1]}),this.shadowPCSSFilterSize=ha.FLOAT(1,{visibleIf:{shadowPCSS:1},range:[0,10],rangeLocked:[!0,!1]})}}}nz(ua);class iz extends XD{constructor(t){super(t),this.node=t}initializeNode(){}static filterFragmentShader(t,e){const n=`\\\\n#define NUM_SAMPLES ${mf.integer(t.pv.shadowPCSSSamplesCount)}\\\\n#define PCSS_FILTER_SIZE ${mf.float(t.pv.shadowPCSSFilterSize)}\\\\n#define LIGHT_WORLD_SIZE 0.005\\\\n// #define LIGHT_FRUSTUM_WIDTH 1.0\\\\n// #define PCSS_FILTER_SIZE 1.0\\\\n#define LIGHT_SIZE_UV (PCSS_FILTER_SIZE * LIGHT_WORLD_SIZE)\\\\n#define NEAR_PLANE 9.5\\\\n\\\\n// #define NUM_SAMPLES 32\\\\n#define NUM_RINGS 11\\\\n#define BLOCKER_SEARCH_NUM_SAMPLES NUM_SAMPLES\\\\n#define PCF_NUM_SAMPLES NUM_SAMPLES\\\\n\\\\nvec2 poissonDisk[NUM_SAMPLES];\\\\n\\\\nvoid initPoissonSamples( const in vec2 randomSeed ) {\\\\n\\\\tfloat ANGLE_STEP = PI2 * float( NUM_RINGS ) / float( NUM_SAMPLES );\\\\n\\\\tfloat INV_NUM_SAMPLES = 1.0 / float( NUM_SAMPLES );\\\\n\\\\n\\\\t// jsfiddle that shows sample pattern: https://jsfiddle.net/a16ff1p7/\\\\n\\\\tfloat angle = rand( randomSeed ) * PI2;\\\\n\\\\tfloat radius = INV_NUM_SAMPLES;\\\\n\\\\tfloat radiusStep = radius;\\\\n\\\\n\\\\tfor( int i = 0; i < NUM_SAMPLES; i ++ ) {\\\\n\\\\t\\\\tpoissonDisk[i] = vec2( cos( angle ), sin( angle ) ) * pow( radius, 0.75 );\\\\n\\\\t\\\\tradius += radiusStep;\\\\n\\\\t\\\\tangle += ANGLE_STEP;\\\\n\\\\t}\\\\n}\\\\n\\\\nfloat penumbraSize( const in float zReceiver, const in float zBlocker ) { // Parallel plane estimation\\\\n\\\\treturn (zReceiver - zBlocker) / zBlocker;\\\\n}\\\\n\\\\nfloat findBlocker( sampler2D shadowMap, const in vec2 uv, const in float zReceiver ) {\\\\n\\\\t// This uses similar triangles to compute what\\\\n\\\\t// area of the shadow map we should search\\\\n\\\\tfloat searchRadius = LIGHT_SIZE_UV * ( zReceiver - NEAR_PLANE ) / zReceiver;\\\\n\\\\tfloat blockerDepthSum = 0.0;\\\\n\\\\tint numBlockers = 0;\\\\n\\\\n\\\\tfor( int i = 0; i < BLOCKER_SEARCH_NUM_SAMPLES; i++ ) {\\\\n\\\\t\\\\tfloat shadowMapDepth = unpackRGBAToDepth(texture2D(shadowMap, uv + poissonDisk[i] * searchRadius));\\\\n\\\\t\\\\tif ( shadowMapDepth < zReceiver ) {\\\\n\\\\t\\\\t\\\\tblockerDepthSum += shadowMapDepth;\\\\n\\\\t\\\\t\\\\tnumBlockers ++;\\\\n\\\\t\\\\t}\\\\n\\\\t}\\\\n\\\\n\\\\tif( numBlockers == 0 ) return -1.0;\\\\n\\\\n\\\\treturn blockerDepthSum / float( numBlockers );\\\\n}\\\\n\\\\nfloat PCF_Filter(sampler2D shadowMap, vec2 uv, float zReceiver, float filterRadius ) {\\\\n\\\\tfloat sum = 0.0;\\\\n\\\\tfor( int i = 0; i < PCF_NUM_SAMPLES; i ++ ) {\\\\n\\\\t\\\\tfloat depth = unpackRGBAToDepth( texture2D( shadowMap, uv + poissonDisk[ i ] * filterRadius ) );\\\\n\\\\t\\\\tif( zReceiver <= depth ) sum += 1.0;\\\\n\\\\t}\\\\n\\\\tfor( int i = 0; i < PCF_NUM_SAMPLES; i ++ ) {\\\\n\\\\t\\\\tfloat depth = unpackRGBAToDepth( texture2D( shadowMap, uv + -poissonDisk[ i ].yx * filterRadius ) );\\\\n\\\\t\\\\tif( zReceiver <= depth ) sum += 1.0;\\\\n\\\\t}\\\\n\\\\treturn sum / ( 2.0 * float( PCF_NUM_SAMPLES ) );\\\\n}\\\\n\\\\nfloat PCSS ( sampler2D shadowMap, vec4 coords ) {\\\\n\\\\tvec2 uv = coords.xy;\\\\n\\\\tfloat zReceiver = coords.z; // Assumed to be eye-space z in this code\\\\n\\\\n\\\\tinitPoissonSamples( uv );\\\\n\\\\t// STEP 1: blocker search\\\\n\\\\tfloat avgBlockerDepth = findBlocker( shadowMap, uv, zReceiver );\\\\n\\\\n\\\\t//There are no occluders so early out (this saves filtering)\\\\n\\\\tif( avgBlockerDepth == -1.0 ) return 1.0;\\\\n\\\\n\\\\t// STEP 2: penumbra size\\\\n\\\\tfloat penumbraRatio = penumbraSize( zReceiver, avgBlockerDepth );\\\\n\\\\tfloat filterRadius = penumbraRatio * LIGHT_SIZE_UV * NEAR_PLANE / zReceiver;\\\\n\\\\n\\\\t// STEP 3: filtering\\\\n\\\\t//return avgBlockerDepth;\\\\n\\\\treturn PCF_Filter( shadowMap, uv, zReceiver, filterRadius );\\\\n}\\\\n`;let i=z;return i=i.replace(\\\\\\\"#ifdef USE_SHADOWMAP\\\\\\\",`#ifdef USE_SHADOWMAP\\\\n${n}\\\\n\\\\t\\\\t\\\\t\\\\t`),i=i.replace(\\\\\\\"#if defined( SHADOWMAP_TYPE_PCF )\\\\\\\",\\\\\\\"\\\\n\\\\t\\\\t\\\\t\\\\treturn PCSS( shadowMap, shadowCoord );\\\\n\\\\t\\\\t\\\\t\\\\t#if defined( SHADOWMAP_TYPE_PCF )\\\\\\\"),e=e.replace(\\\\\\\"#include \\\\\\\",i)}async update(){const t=this.node;if(!t.assemblerController)return;const e=\\\\\\\"PCSS\\\\\\\";this.node.pv.shadowPCSS?t.assemblerController.addFilterFragmentShaderCallback(e,(t=>iz.filterFragmentShader(this.node,t))):t.assemblerController.removeFilterFragmentShaderCallback(e)}static async update(t){t.controllers.PCSS.update()}static PARAM_CALLBACK_setRecompileRequired(t){t.controllers.PCSS.update()}}const sz={uniforms:!0};class rz extends(nz(oB(jB(JD(sB(cB(OB(NB(JB(AB(wB(xB(kB(eB(lB(ua)))))))))))))))){}const oz=new rz;class az extends rB{constructor(){super(...arguments),this.paramsConfig=oz,this.controllers={advancedCommon:new ZD(this),alphaMap:new TB(this,sz),aoMap:new MB(this,sz),emissiveMap:new ZB(this,sz),envMap:new LB(this,sz),lightMap:new PB(this,sz),map:new bB(this,sz),PCSS:new iz(this)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshLambertBuilder\\\\\\\"}usedAssembler(){return jn.GL_MESH_LAMBERT}_create_assembler_controller(){return li.assemblersRegister.assembler(this,this.usedAssembler())}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();nB.update(this),aB.update(this),WB.update(this),this.compileIfRequired(),this.setMaterial(this.material)}}function lz(t){return class extends t{constructor(){super(...arguments),this.useBumpMap=ha.BOOLEAN(0,{separatorBefore:!0,...gB(cz)}),this.bumpMap=ha.NODE_PATH(\\\\\\\"\\\\\\\",vB(cz,\\\\\\\"useBumpMap\\\\\\\")),this.bumpScale=ha.FLOAT(1,{range:[0,1],rangeLocked:[!1,!1],...vB(cz,\\\\\\\"useBumpMap\\\\\\\")}),this.bumpBias=ha.FLOAT(0,{range:[0,1],rangeLocked:[!1,!1],...vB(cz,\\\\\\\"useBumpMap\\\\\\\")})}}}O.a;lz(ua);class cz extends yB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useBumpMap,this.node.p.bumpMap)}async update(){if(this._update(this.node.material,\\\\\\\"bumpMap\\\\\\\",this.node.p.useBumpMap,this.node.p.bumpMap),this._update_options.uniforms){this.node.material.uniforms.bumpScale.value=this.node.pv.bumpScale}if(this._update_options.directParams){this.node.material.bumpScale=this.node.pv.bumpScale}}static async update(t){t.controllers.bumpMap.update()}}var hz;!function(t){t.TANGENT=\\\\\\\"tangent\\\\\\\",t.OBJECT=\\\\\\\"object\\\\\\\"}(hz||(hz={}));const uz=[hz.TANGENT,hz.OBJECT],dz={[hz.TANGENT]:w.Uc,[hz.OBJECT]:w.zb};function pz(t){return class extends t{constructor(){super(...arguments),this.useNormalMap=ha.BOOLEAN(0,{separatorBefore:!0,...gB(_z)}),this.normalMap=ha.NODE_PATH(vi.EMPTY,vB(_z,\\\\\\\"useNormalMap\\\\\\\")),this.normalMapType=ha.INTEGER(0,{visibleIf:{useNormalMap:1},menu:{entries:uz.map(((t,e)=>({name:t,value:e})))}}),this.normalScale=ha.VECTOR2([1,1],{visibleIf:{useNormalMap:1}})}}}O.a;pz(ua);class _z extends yB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useNormalMap,this.node.p.normalMap)}async update(){this._update(this.node.material,\\\\\\\"normalMap\\\\\\\",this.node.p.useNormalMap,this.node.p.normalMap);const t=dz[uz[this.node.pv.normalMapType]];if(this._update_options.uniforms){this.node.material.uniforms.normalScale.value.copy(this.node.pv.normalScale)}const e=this.node.material;e.normalMapType=t,this._update_options.directParams&&e.normalScale.copy(this.node.pv.normalScale)}static async update(t){t.controllers.normalMap.update()}}function mz(t){return class extends t{constructor(){super(...arguments),this.useDisplacementMap=ha.BOOLEAN(0,{separatorBefore:!0,...gB(fz)}),this.displacementMap=ha.NODE_PATH(\\\\\\\"\\\\\\\",vB(fz,\\\\\\\"useDisplacementMap\\\\\\\")),this.displacementScale=ha.FLOAT(1,{range:[0,1],rangeLocked:[!1,!1],...vB(fz,\\\\\\\"useDisplacementMap\\\\\\\")}),this.displacementBias=ha.FLOAT(0,{range:[0,1],rangeLocked:[!1,!1],...vB(fz,\\\\\\\"useDisplacementMap\\\\\\\")})}}}O.a;mz(ua);class fz extends yB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useDisplacementMap,this.node.p.displacementMap)}async update(){if(this._update(this.node.material,\\\\\\\"displacementMap\\\\\\\",this.node.p.useDisplacementMap,this.node.p.displacementMap),this._update_options.uniforms){const t=this.node.material;t.uniforms.displacementScale.value=this.node.pv.displacementScale,t.uniforms.displacementBias.value=this.node.pv.displacementBias}if(this._update_options.directParams){const t=this.node.material;t.displacementScale=this.node.pv.displacementScale,t.displacementBias=this.node.pv.displacementBias}}static async update(t){t.controllers.displacementMap.update()}}function gz(t){return class extends t{constructor(){super(...arguments),this.useMatcapMap=ha.BOOLEAN(0,gB(vz)),this.matcapMap=ha.NODE_PATH(vi.EMPTY,vB(vz,\\\\\\\"useMatcapMap\\\\\\\"))}}}O.a;gz(ua);class vz extends yB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useMatcapMap,this.node.p.matcapMap)}async update(){this._update(this.node.material,\\\\\\\"matcap\\\\\\\",this.node.p.useMatcapMap,this.node.p.matcapMap)}static async update(t){t.controllers.matcap.update()}}const yz={directParams:!0};class xz extends(mB(JD(cB(pz(mz(lz(wB(xB(gz(kB(pB(lB(ua))))))))))))){}const bz=new xz;class wz extends qD{constructor(){super(...arguments),this.paramsConfig=bz,this.controllers={advancedCommon:new ZD(this),alphaMap:new TB(this,yz),bumpMap:new cz(this,yz),displacementMap:new fz(this,yz),map:new bB(this,yz),matcap:new vz(this,yz),normalMap:new _z(this,yz)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshMatcap\\\\\\\"}createMaterial(){return new $f({vertexColors:!1,side:w.H,color:16777215,opacity:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();_B.update(this),fB.update(this),this.setMaterial(this.material)}}const Tz={directParams:!0};class Az extends(mB(JD(pz(mz(lz(kB(lB(ua)))))))){}const Mz=new Az;class Ez extends qD{constructor(){super(...arguments),this.paramsConfig=Mz,this.controllers={advancedCommon:new ZD(this),bumpMap:new cz(this,Tz),displacementMap:new fz(this,Tz),normalMap:new _z(this,Tz)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshNormal\\\\\\\"}createMaterial(){return new Yf({vertexColors:!1,side:w.H,opacity:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();fB.update(this),this.setMaterial(this.material)}}function Sz(t){return class extends t{constructor(){super(...arguments),this.useSpecularMap=ha.BOOLEAN(0,gB(Cz)),this.specularMap=ha.NODE_PATH(vi.EMPTY,vB(Cz,\\\\\\\"useSpecularMap\\\\\\\"))}}}O.a;Sz(ua);class Cz extends yB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useSpecularMap,this.node.p.specularMap)}async update(){this._update(this.node.material,\\\\\\\"specularMap\\\\\\\",this.node.p.useSpecularMap,this.node.p.specularMap)}static async update(t){t.controllers.specularMap.update()}}const Nz={directParams:!0};class Lz extends(mB(BB(JD(cB(Sz(pz(OB(NB(JB(mz(lz(AB(wB(xB(kB(pB(lB(ua)))))))))))))))))){constructor(){super(...arguments),this.flatShading=ha.BOOLEAN(0)}}const Oz=new Lz;class Pz extends qD{constructor(){super(...arguments),this.paramsConfig=Oz,this.controllers={advancedCommon:new ZD(this),alphaMap:new TB(this,Nz),aoMap:new MB(this,Nz),bumpMap:new cz(this,Nz),displacementMap:new fz(this,Nz),emissiveMap:new ZB(this,Nz),envMap:new LB(this,Nz),lightMap:new PB(this,Nz),map:new bB(this,Nz),normalMap:new _z(this,Nz),specularMap:new Cz(this,Nz)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshPhong\\\\\\\"}createMaterial(){return new qf.a({vertexColors:!1,side:w.H,color:16777215,opacity:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();_B.update(this),fB.update(this),zB.update(this),this.material.flatShading!=this.pv.flatShading&&(this.material.flatShading=this.pv.flatShading,this.material.needsUpdate=!0),this.setMaterial(this.material)}}const Rz={uniforms:!0};class Iz extends(nz(oB(jB(JD(sB(cB(Sz(pz(OB(NB(JB(mz(lz(AB(wB(xB(kB(eB(lB(ua)))))))))))))))))))){}const Fz=new Iz;class Dz extends rB{constructor(){super(...arguments),this.paramsConfig=Fz,this.controllers={advancedCommon:new ZD(this),alphaMap:new TB(this,Rz),aoMap:new MB(this,Rz),bumpMap:new cz(this,Rz),displacementMap:new fz(this,Rz),emissiveMap:new ZB(this,Rz),envMap:new LB(this,Rz),lightMap:new PB(this,Rz),map:new bB(this,Rz),normalMap:new _z(this,Rz),specularMap:new Cz(this,Rz),PCSS:new iz(this)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshPhongBuilder\\\\\\\"}usedAssembler(){return jn.GL_MESH_PHONG}_create_assembler_controller(){return li.assemblersRegister.assembler(this,this.usedAssembler())}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();nB.update(this),aB.update(this),WB.update(this),this.compileIfRequired(),this.setMaterial(this.material)}}function Bz(t){return class extends t{constructor(){super(...arguments),this.useEnvMap=ha.BOOLEAN(0,{separatorBefore:!0,...gB(zz)}),this.envMap=ha.NODE_PATH(vi.EMPTY,vB(zz,\\\\\\\"useEnvMap\\\\\\\")),this.envMapIntensity=ha.FLOAT(1,{visibleIf:{useEnvMap:1}}),this.refractionRatio=ha.FLOAT(.98,{range:[-1,1],rangeLocked:[!1,!1],visibleIf:{useEnvMap:1}})}}}Bz(ua);class zz extends yB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useEnvMap,this.node.p.envMap)}async update(){if(this._update(this.node.material,\\\\\\\"envMap\\\\\\\",this.node.p.useEnvMap,this.node.p.envMap),this._update_options.uniforms){const t=this.node.material;t.uniforms.envMapIntensity.value=this.node.pv.envMapIntensity,t.uniforms.refractionRatio.value=this.node.pv.refractionRatio}if(this._update_options.directParams){const t=this.node.material;t.envMapIntensity=this.node.pv.envMapIntensity,t.refractionRatio=this.node.pv.refractionRatio}}static async update(t){t.controllers.envMap.update()}}function kz(t){return class extends t{constructor(){super(...arguments),this.useMetalnessMap=ha.BOOLEAN(0,{separatorBefore:!0,...gB(Uz)}),this.metalnessMap=ha.NODE_PATH(vi.EMPTY,vB(Uz,\\\\\\\"useMetalnessMap\\\\\\\")),this.metalness=ha.FLOAT(1),this.useRoughnessMap=ha.BOOLEAN(0,{separatorBefore:!0,...gB(Uz)}),this.roughnessMap=ha.NODE_PATH(vi.EMPTY,vB(Uz,\\\\\\\"useRoughnessMap\\\\\\\")),this.roughness=ha.FLOAT(.5)}}}O.a;kz(ua);class Uz extends yB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useMetalnessMap,this.node.p.metalnessMap)}async update(){if(this._update(this.node.material,\\\\\\\"metalnessMap\\\\\\\",this.node.p.useMetalnessMap,this.node.p.metalnessMap),this._update_options.uniforms){this.node.material.uniforms.metalness.value=this.node.pv.metalness}if(this._update_options.directParams){this.node.material.metalness=this.node.pv.metalness}if(this._update(this.node.material,\\\\\\\"roughnessMap\\\\\\\",this.node.p.useRoughnessMap,this.node.p.roughnessMap),this._update_options.uniforms){this.node.material.uniforms.roughness.value=this.node.pv.roughness}if(this._update_options.directParams){this.node.material.roughness=this.node.pv.roughness}}static async update(t){t.controllers.metalnessRoughnessMap.update()}}function Gz(t){return class extends t{constructor(){super(...arguments),this.clearcoat=ha.FLOAT(0,{separatorBefore:!0}),this.useClearCoatMap=ha.BOOLEAN(0,gB(Hz)),this.clearcoatMap=ha.NODE_PATH(vi.EMPTY,vB(Hz,\\\\\\\"useClearCoatMap\\\\\\\")),this.useClearCoatNormalMap=ha.BOOLEAN(0,gB(Hz)),this.clearcoatNormalMap=ha.NODE_PATH(vi.EMPTY,vB(Hz,\\\\\\\"useClearCoatNormalMap\\\\\\\")),this.clearcoatNormalScale=ha.VECTOR2([1,1],{visibleIf:{useClearCoatNormalMap:1}}),this.clearcoatRoughness=ha.FLOAT(0),this.useClearCoatRoughnessMap=ha.BOOLEAN(0,gB(Hz)),this.clearcoatRoughnessMap=ha.NODE_PATH(vi.EMPTY,vB(Hz,\\\\\\\"useClearCoatRoughnessMap\\\\\\\")),this.useSheen=ha.BOOLEAN(0),this.sheen=ha.FLOAT(0,{range:[0,1],rangeLocked:[!0,!1],visibleIf:{useSheen:1}}),this.sheenRoughness=ha.FLOAT(1,{range:[0,1],rangeLocked:[!0,!1],visibleIf:{useSheen:1}}),this.sheenColor=ha.COLOR([1,1,1],{visibleIf:{useSheen:1}}),this.transmission=ha.FLOAT(0,{range:[0,1]}),this.useTransmissionMap=ha.BOOLEAN(0),this.transmissionMap=ha.NODE_PATH(vi.EMPTY,{visibleIf:{useTransmissionMap:1}}),this.ior=ha.FLOAT(1.5,{range:[1,2.3333],rangeLocked:[!0,!0]}),this.thickness=ha.FLOAT(.01,{range:[0,10],rangeLocked:[!0,!1]}),this.useThicknessMap=ha.BOOLEAN(0),this.thicknessMap=ha.NODE_PATH(vi.EMPTY,{visibleIf:{useThicknessMap:1}}),this.attenuationDistance=ha.FLOAT(0,{range:[0,10],rangeLocked:[!0,!1]}),this.attenuationColor=ha.COLOR([1,1,1])}}}Gz(ua);const Vz=new Wf.a;class Hz extends yB{constructor(t,e){super(t,e),this.node=t,this._sheenColorClone=new D.a}initializeNode(){this.add_hooks(this.node.p.useClearCoatMap,this.node.p.clearcoatMap),this.add_hooks(this.node.p.useClearCoatNormalMap,this.node.p.clearcoatNormalMap),this.add_hooks(this.node.p.useClearCoatRoughnessMap,this.node.p.clearcoatRoughnessMap),this.add_hooks(this.node.p.useTransmissionMap,this.node.p.transmissionMap),this.add_hooks(this.node.p.useThicknessMap,this.node.p.thicknessMap)}async update(){this._update(this.node.material,\\\\\\\"clearcoatMap\\\\\\\",this.node.p.useClearCoatMap,this.node.p.clearcoatMap),this._update(this.node.material,\\\\\\\"clearcoatNormalMap\\\\\\\",this.node.p.useClearCoatNormalMap,this.node.p.clearcoatNormalMap),this._update(this.node.material,\\\\\\\"clearcoatRoughnessMap\\\\\\\",this.node.p.useClearCoatRoughnessMap,this.node.p.clearcoatRoughnessMap),this._update(this.node.material,\\\\\\\"transmissionMap\\\\\\\",this.node.p.useTransmissionMap,this.node.p.transmissionMap),this._update(this.node.material,\\\\\\\"thicknessMap\\\\\\\",this.node.p.useThicknessMap,this.node.p.thicknessMap);const t=this.node.pv;Vz.ior=t.ior;const e=Vz.reflectivity;if(this._update_options.uniforms){const n=this.node.material;n.uniforms.clearcoat.value=t.clearcoat,n.uniforms.clearcoatNormalScale.value.copy(t.clearcoatNormalScale),n.uniforms.clearcoatRoughness.value=t.clearcoatRoughness,n.uniforms.reflectivity.value=e,n.uniforms.transmission.value=t.transmission,n.uniforms.thickness.value=t.thickness,n.uniforms.attenuationDistance.value=t.attenuationDistance,n.uniforms.attenuationTint.value=t.attenuationColor,t.useSheen?(this._sheenColorClone.copy(t.sheenColor),n.uniforms.sheen.value=t.sheen,n.uniforms.sheenRoughness.value=t.sheenRoughness,n.uniforms.sheenTint.value=this._sheenColorClone):n.uniforms.sheen.value=0,n.uniforms.ior.value=t.ior,n.specularTint=n.uniforms.specularTint.value,n.ior=n.uniforms.ior.value}if(this._update_options.directParams){const n=this.node.material;n.clearcoat=t.clearcoat,null!=n.clearcoatNormalScale&&n.clearcoatNormalScale.copy(t.clearcoatNormalScale),n.clearcoatRoughness=t.clearcoatRoughness,n.reflectivity=e,t.useSheen?(this._sheenColorClone.copy(t.sheenColor),n.sheen=t.sheen,n.sheenRoughness=t.sheenRoughness,n.sheenTint=this._sheenColorClone):n.sheen=0,n.transmission=t.transmission,n.thickness=t.thickness,n.attenuationDistance=t.attenuationDistance,n.attenuationTint=t.attenuationColor}}static async update(t){t.controllers.physical.update()}}const jz={directParams:!0};class Wz extends(mB(BB(JD(cB(Gz(kz(pz(OB(Bz(JB(mz(lz(AB(wB(xB(kB(pB(lB(ua))))))))))))))))))){}const qz=new Wz;class Xz extends qD{constructor(){super(...arguments),this.paramsConfig=qz,this.controllers={advancedCommon:new ZD(this),alphaMap:new TB(this,jz),aoMap:new MB(this,jz),bumpMap:new cz(this,jz),displacementMap:new fz(this,jz),emissiveMap:new ZB(this,jz),envMap:new zz(this,jz),lightMap:new PB(this,jz),map:new bB(this,jz),metalnessRoughnessMap:new Uz(this,jz),normalMap:new _z(this,jz),physical:new Hz(this,jz)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshPhysical\\\\\\\"}createMaterial(){return new Wf.a({vertexColors:!1,side:w.H,color:16777215,opacity:1,metalness:1,roughness:0})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();_B.update(this),fB.update(this),zB.update(this),this.setMaterial(this.material)}}const Yz={uniforms:!0};class $z extends(function(t){return class extends(nz(oB(jB(JD(sB(t)))))){}}(cB(Gz(kz(pz(OB(Bz(JB(mz(lz(AB(wB(xB(kB(eB(lB(ua))))))))))))))))){}const Jz=new $z;class Zz extends rB{constructor(){super(...arguments),this.paramsConfig=Jz,this.controllers={advancedCommon:new ZD(this),alphaMap:new TB(this,Yz),aoMap:new MB(this,Yz),bumpMap:new cz(this,Yz),displacementMap:new fz(this,Yz),emissiveMap:new ZB(this,Yz),envMap:new zz(this,{uniforms:!0,directParams:!0}),lightMap:new PB(this,Yz),map:new bB(this,Yz),metalnessRoughnessMap:new Uz(this,{uniforms:!0,directParams:!0}),normalMap:new _z(this,Yz),physical:new Hz(this,{uniforms:!0,directParams:!0}),PCSS:new iz(this)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshPhysicalBuilder\\\\\\\"}usedAssembler(){return jn.GL_MESH_PHYSICAL}_create_assembler_controller(){return li.assemblersRegister.assembler(this,this.usedAssembler())}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}createMaterial(){const t=super.createMaterial();return t.isMeshStandardMaterial=!0,t.isMeshPhysicalMaterial=!0,t}async cook(){for(let t of this.controllerNames)this.controllers[t].update();nB.update(this),aB.update(this),WB.update(this),this.compileIfRequired(),this.setMaterial(this.material)}}const Qz={directParams:!0};class Kz extends(mB(BB(JD(cB(kz(pz(OB(Bz(JB(mz(lz(AB(wB(xB(kB(pB(lB(ua)))))))))))))))))){}const tk=new Kz;class ek extends qD{constructor(){super(...arguments),this.paramsConfig=tk,this.controllers={advancedCommon:new ZD(this),alphaMap:new TB(this,Qz),aoMap:new MB(this,Qz),bumpMap:new cz(this,Qz),displacementMap:new fz(this,Qz),emissiveMap:new ZB(this,Qz),envMap:new zz(this,Qz),lightMap:new PB(this,Qz),map:new bB(this,Qz),metalnessRoughnessMap:new Uz(this,Qz),normalMap:new _z(this,Qz)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshStandard\\\\\\\"}createMaterial(){return new ws.a({vertexColors:!1,side:w.H,color:16777215,opacity:1,metalness:1,roughness:0})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();_B.update(this),fB.update(this),zB.update(this),this.setMaterial(this.material)}}const nk={uniforms:!0};class ik extends(nz(oB(jB(JD(sB(cB(kz(pz(OB(Bz(JB(mz(lz(AB(wB(xB(kB(eB(lB(ua)))))))))))))))))))){}const sk=new ik;class rk extends rB{constructor(){super(...arguments),this.paramsConfig=sk,this.controllers={advancedCommon:new ZD(this),alphaMap:new TB(this,nk),aoMap:new MB(this,nk),bumpMap:new cz(this,nk),displacementMap:new fz(this,nk),emissiveMap:new ZB(this,nk),envMap:new zz(this,nk),lightMap:new PB(this,nk),map:new bB(this,nk),metalnessRoughnessMap:new Uz(this,nk),normalMap:new _z(this,nk),PCSS:new iz(this)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshStandardBuilder\\\\\\\"}usedAssembler(){return jn.GL_MESH_STANDARD}_create_assembler_controller(){return li.assemblersRegister.assembler(this,this.usedAssembler())}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();nB.update(this),aB.update(this),WB.update(this),this.compileIfRequired(),this.setMaterial(this.material)}}const ok=U.meshphong_frag.slice(0,U.meshphong_frag.indexOf(\\\\\\\"void main() {\\\\\\\")),ak=U.meshphong_frag.slice(U.meshphong_frag.indexOf(\\\\\\\"void main() {\\\\\\\")),lk={uniforms:I.merge([H.phong.uniforms,{thicknessMap:{value:null},thicknessColor:{value:new D.a(16777215)},thicknessDistortion:{value:.1},thicknessAmbient:{value:0},thicknessAttenuation:{value:.1},thicknessPower:{value:2},thicknessScale:{value:10}}]),vertexShader:[\\\\\\\"#define USE_UV\\\\\\\",U.meshphong_vert].join(\\\\\\\"\\\\n\\\\\\\"),fragmentShader:[\\\\\\\"#define USE_UV\\\\\\\",\\\\\\\"#define SUBSURFACE\\\\\\\",ok,\\\\\\\"uniform sampler2D thicknessMap;\\\\\\\",\\\\\\\"uniform float thicknessPower;\\\\\\\",\\\\\\\"uniform float thicknessScale;\\\\\\\",\\\\\\\"uniform float thicknessDistortion;\\\\\\\",\\\\\\\"uniform float thicknessAmbient;\\\\\\\",\\\\\\\"uniform float thicknessAttenuation;\\\\\\\",\\\\\\\"uniform vec3 thicknessColor;\\\\\\\",\\\\\\\"void RE_Direct_Scattering(const in IncidentLight directLight, const in vec2 uv, const in GeometricContext geometry, inout ReflectedLight reflectedLight) {\\\\\\\",\\\\\\\"\\\\tvec3 thickness = thicknessColor * texture2D(thicknessMap, uv).r;\\\\\\\",\\\\\\\"\\\\tvec3 scatteringHalf = normalize(directLight.direction + (geometry.normal * thicknessDistortion));\\\\\\\",\\\\\\\"\\\\tfloat scatteringDot = pow(saturate(dot(geometry.viewDir, -scatteringHalf)), thicknessPower) * thicknessScale;\\\\\\\",\\\\\\\"\\\\tvec3 scatteringIllu = (scatteringDot + thicknessAmbient) * thickness;\\\\\\\",\\\\\\\"\\\\treflectedLight.directDiffuse += scatteringIllu * thicknessAttenuation * directLight.color;\\\\\\\",\\\\\\\"}\\\\\\\",ak.replace(\\\\\\\"#include \\\\\\\",(ck=U.lights_fragment_begin,hk=\\\\\\\"RE_Direct( directLight, geometry, material, reflectedLight );\\\\\\\",uk=[\\\\\\\"RE_Direct( directLight, geometry, material, reflectedLight );\\\\\\\",\\\\\\\"#if defined( SUBSURFACE ) && defined( USE_UV )\\\\\\\",\\\\\\\" RE_Direct_Scattering(directLight, vUv, geometry, reflectedLight);\\\\\\\",\\\\\\\"#endif\\\\\\\"].join(\\\\\\\"\\\\n\\\\\\\"),ck.split(hk).join(uk)))].join(\\\\\\\"\\\\n\\\\\\\")};var ck,hk,uk;function dk(t){return{cook:!1,callback:(e,n)=>{gk.PARAM_CALLBACK_update_uniformColor(e,n,t)}}}function pk(t){return{cook:!1,callback:(e,n)=>{gk.PARAM_CALLBACK_update_uniformN(e,n,t)}}}const _k={uniforms:!0};class mk extends(mB(jB(JD(cB(wB(xB(kB(function(t){return class extends t{constructor(){var t;super(...arguments),this.diffuse=ha.COLOR([1,1,1],{...dk(\\\\\\\"diffuse\\\\\\\")}),this.shininess=ha.FLOAT(1,{range:[0,1e3]}),this.thicknessMap=ha.NODE_PATH(vi.EMPTY,{nodeSelection:{context:ts.COP},...(t=\\\\\\\"thicknessMap\\\\\\\",{cook:!1,callback:(e,n)=>{gk.PARAM_CALLBACK_update_uniformTexture(e,n,t)}})}),this.thicknessColor=ha.COLOR([.5,.3,0],{...dk(\\\\\\\"thicknessColor\\\\\\\")}),this.thicknessDistortion=ha.FLOAT(.1,{...pk(\\\\\\\"thicknessDistortion\\\\\\\")}),this.thicknessAmbient=ha.FLOAT(.4,{...pk(\\\\\\\"thicknessAmbient\\\\\\\")}),this.thicknessAttenuation=ha.FLOAT(.8,{...pk(\\\\\\\"thicknessAttenuation\\\\\\\")}),this.thicknessPower=ha.FLOAT(2,{range:[0,10],...pk(\\\\\\\"thicknessPower\\\\\\\")}),this.thicknessScale=ha.FLOAT(16,{range:[0,100],...pk(\\\\\\\"thicknessScale\\\\\\\")})}}}(lB(ua)))))))))){}const fk=new mk;class gk extends qD{constructor(){super(...arguments),this.paramsConfig=fk,this.controllers={advancedCommon:new ZD(this),alphaMap:new TB(this,_k),map:new bB(this,_k)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshSubsurfaceScattering\\\\\\\"}createMaterial(){const t=I.clone(lk.uniforms),e=new F({uniforms:t,vertexShader:lk.vertexShader,fragmentShader:lk.fragmentShader,lights:!0});return e.extensions.derivatives=!0,e}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();fB.update(this),WB.update(this),this.update_map(this.p.thicknessMap,\\\\\\\"thicknessMap\\\\\\\"),this.material.uniforms.diffuse.value.copy(this.pv.diffuse),this.material.uniforms.shininess.value=this.pv.shininess,this.material.uniforms.thicknessColor.value.copy(this.pv.thicknessColor),this.material.uniforms.thicknessDistortion.value=this.pv.thicknessDistortion,this.material.uniforms.thicknessAmbient.value=this.pv.thicknessAmbient,this.material.uniforms.thicknessAttenuation.value=this.pv.thicknessAttenuation,this.material.uniforms.thicknessPower.value=this.pv.thicknessPower,this.material.uniforms.thicknessScale.value=this.pv.thicknessScale,this.setMaterial(this.material)}static PARAM_CALLBACK_update_uniformN(t,e,n){t.material.uniforms[n].value=e.value}static PARAM_CALLBACK_update_uniformColor(t,e,n){e.parent_param&&t.material.uniforms[n].value.copy(e.parent_param.value)}static PARAM_CALLBACK_update_uniformTexture(t,e,n){t.update_map(e,n)}async update_map(t,e){const n=t.value.nodeWithContext(ts.COP);n||(this.material.uniforms[e].value=null);const i=n,s=await i.compute();this.material.uniforms[e].value=s.texture()}}function vk(t){return class extends t{constructor(){super(...arguments),this.useGradientMap=ha.BOOLEAN(0,gB(yk)),this.gradientMap=ha.NODE_PATH(vi.EMPTY,vB(yk,\\\\\\\"useGradientMap\\\\\\\"))}}}O.a;vk(ua);class yk extends yB{constructor(t,e){super(t,e),this.node=t}initializeNode(){this.add_hooks(this.node.p.useGradientMap,this.node.p.gradientMap)}async update(){this._update(this.node.material,\\\\\\\"gradientMap\\\\\\\",this.node.p.useGradientMap,this.node.p.gradientMap)}static async update(t){t.controllers.gradientMap.update()}}const xk={directParams:!0};class bk extends(mB(BB(JD(cB(pz(OB(vk(JB(mz(lz(AB(wB(xB(kB(pB(lB(ua))))))))))))))))){}const wk=new bk;class Tk extends qD{constructor(){super(...arguments),this.paramsConfig=wk,this.controllers={advancedCommon:new ZD(this),alphaMap:new TB(this,xk),aoMap:new MB(this,xk),bumpMap:new cz(this,xk),displacementMap:new fz(this,xk),emissiveMap:new ZB(this,xk),gradientMap:new yk(this,xk),lightMap:new PB(this,xk),map:new bB(this,xk),normalMap:new _z(this,xk)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"meshToon\\\\\\\"}createMaterial(){return new Xf({vertexColors:!1,side:w.H,color:16777215,opacity:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();_B.update(this),fB.update(this),zB.update(this),this.setMaterial(this.material)}}const Ak={directParams:!0};class Mk extends(oB(JD(cB(wB(xB(kB(pB(function(t){return class extends t{constructor(){super(...arguments),this.size=ha.FLOAT(1),this.sizeAttenuation=ha.BOOLEAN(1)}}}(lB(ua)))))))))){}const Ek=new Mk;class Sk extends qD{constructor(){super(...arguments),this.paramsConfig=Ek,this.controllers={advancedCommon:new ZD(this),alphaMap:new TB(this,Ak),map:new bB(this,Ak)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"points\\\\\\\"}createMaterial(){return new bs.a({vertexColors:!1,side:w.H,color:16777215,opacity:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();_B.update(this),aB.update(this),this.material.size=this.pv.size,this.material.sizeAttenuation=this.pv.sizeAttenuation,this.setMaterial(this.material)}}class Ck extends(oB(JD(sB(cB(eB(lB(ua))))))){}const Nk=new Ck;class Lk extends rB{constructor(){super(...arguments),this.paramsConfig=Nk,this.controllers={advancedCommon:new ZD(this)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"pointsBuilder\\\\\\\"}usedAssembler(){return jn.GL_POINTS}_create_assembler_controller(){return li.assemblersRegister.assembler(this,this.usedAssembler())}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();nB.update(this),aB.update(this),this.compileIfRequired(),this.setMaterial(this.material)}}class Ok extends(JD(pB(ua))){}const Pk=new Ok;class Rk extends qD{constructor(){super(...arguments),this.paramsConfig=Pk,this.controllers={advancedCommon:new ZD(this)},this.controllerNames=Object.keys(this.controllers)}static type(){return\\\\\\\"shadow\\\\\\\"}createMaterial(){return new Hf({vertexColors:!1,side:w.H,color:16777215,opacity:1})}initializeNode(){this.params.onParamsCreated(\\\\\\\"init controllers\\\\\\\",(()=>{for(let t of this.controllerNames)this.controllers[t].initializeNode()}))}async cook(){for(let t of this.controllerNames)this.controllers[t].update();_B.update(this),this.setMaterial(this.material)}}class Ik extends B.a{constructor(){const t=Ik.SkyShader,e=new F({name:\\\\\\\"SkyShader\\\\\\\",fragmentShader:t.fragmentShader,vertexShader:t.vertexShader,uniforms:I.clone(t.uniforms),side:w.i,depthWrite:!1});super(new N(1,1,1),e)}}Ik.prototype.isSky=!0,Ik.SkyShader={uniforms:{turbidity:{value:2},rayleigh:{value:1},mieCoefficient:{value:.005},mieDirectionalG:{value:.8},sunPosition:{value:new p.a},up:{value:new p.a(0,1,0)}},vertexShader:\\\\\\\"\\\\n\\\\t\\\\tuniform vec3 sunPosition;\\\\n\\\\t\\\\tuniform float rayleigh;\\\\n\\\\t\\\\tuniform float turbidity;\\\\n\\\\t\\\\tuniform float mieCoefficient;\\\\n\\\\t\\\\tuniform vec3 up;\\\\n\\\\n\\\\t\\\\tvarying vec3 vWorldPosition;\\\\n\\\\t\\\\tvarying vec3 vSunDirection;\\\\n\\\\t\\\\tvarying float vSunfade;\\\\n\\\\t\\\\tvarying vec3 vBetaR;\\\\n\\\\t\\\\tvarying vec3 vBetaM;\\\\n\\\\t\\\\tvarying float vSunE;\\\\n\\\\n\\\\t\\\\t// constants for atmospheric scattering\\\\n\\\\t\\\\tconst float e = 2.71828182845904523536028747135266249775724709369995957;\\\\n\\\\t\\\\tconst float pi = 3.141592653589793238462643383279502884197169;\\\\n\\\\n\\\\t\\\\t// wavelength of used primaries, according to preetham\\\\n\\\\t\\\\tconst vec3 lambda = vec3( 680E-9, 550E-9, 450E-9 );\\\\n\\\\t\\\\t// this pre-calcuation replaces older TotalRayleigh(vec3 lambda) function:\\\\n\\\\t\\\\t// (8.0 * pow(pi, 3.0) * pow(pow(n, 2.0) - 1.0, 2.0) * (6.0 + 3.0 * pn)) / (3.0 * N * pow(lambda, vec3(4.0)) * (6.0 - 7.0 * pn))\\\\n\\\\t\\\\tconst vec3 totalRayleigh = vec3( 5.804542996261093E-6, 1.3562911419845635E-5, 3.0265902468824876E-5 );\\\\n\\\\n\\\\t\\\\t// mie stuff\\\\n\\\\t\\\\t// K coefficient for the primaries\\\\n\\\\t\\\\tconst float v = 4.0;\\\\n\\\\t\\\\tconst vec3 K = vec3( 0.686, 0.678, 0.666 );\\\\n\\\\t\\\\t// MieConst = pi * pow( ( 2.0 * pi ) / lambda, vec3( v - 2.0 ) ) * K\\\\n\\\\t\\\\tconst vec3 MieConst = vec3( 1.8399918514433978E14, 2.7798023919660528E14, 4.0790479543861094E14 );\\\\n\\\\n\\\\t\\\\t// earth shadow hack\\\\n\\\\t\\\\t// cutoffAngle = pi / 1.95;\\\\n\\\\t\\\\tconst float cutoffAngle = 1.6110731556870734;\\\\n\\\\t\\\\tconst float steepness = 1.5;\\\\n\\\\t\\\\tconst float EE = 1000.0;\\\\n\\\\n\\\\t\\\\tfloat sunIntensity( float zenithAngleCos ) {\\\\n\\\\t\\\\t\\\\tzenithAngleCos = clamp( zenithAngleCos, -1.0, 1.0 );\\\\n\\\\t\\\\t\\\\treturn EE * max( 0.0, 1.0 - pow( e, -( ( cutoffAngle - acos( zenithAngleCos ) ) / steepness ) ) );\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvec3 totalMie( float T ) {\\\\n\\\\t\\\\t\\\\tfloat c = ( 0.2 * T ) * 10E-18;\\\\n\\\\t\\\\t\\\\treturn 0.434 * c * MieConst;\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 worldPosition = modelMatrix * vec4( position, 1.0 );\\\\n\\\\t\\\\t\\\\tvWorldPosition = worldPosition.xyz;\\\\n\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\t\\\\t\\\\tgl_Position.z = gl_Position.w; // set z to camera.far\\\\n\\\\n\\\\t\\\\t\\\\tvSunDirection = normalize( sunPosition );\\\\n\\\\n\\\\t\\\\t\\\\tvSunE = sunIntensity( dot( vSunDirection, up ) );\\\\n\\\\n\\\\t\\\\t\\\\tvSunfade = 1.0 - clamp( 1.0 - exp( ( sunPosition.y / 450000.0 ) ), 0.0, 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\tfloat rayleighCoefficient = rayleigh - ( 1.0 * ( 1.0 - vSunfade ) );\\\\n\\\\n\\\\t\\\\t\\\\t// extinction (absorbtion + out scattering)\\\\n\\\\t\\\\t\\\\t// rayleigh coefficients\\\\n\\\\t\\\\t\\\\tvBetaR = totalRayleigh * rayleighCoefficient;\\\\n\\\\n\\\\t\\\\t\\\\t// mie coefficients\\\\n\\\\t\\\\t\\\\tvBetaM = totalMie( turbidity ) * mieCoefficient;\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\t\\\\tvarying vec3 vWorldPosition;\\\\n\\\\t\\\\tvarying vec3 vSunDirection;\\\\n\\\\t\\\\tvarying float vSunfade;\\\\n\\\\t\\\\tvarying vec3 vBetaR;\\\\n\\\\t\\\\tvarying vec3 vBetaM;\\\\n\\\\t\\\\tvarying float vSunE;\\\\n\\\\n\\\\t\\\\tuniform float mieDirectionalG;\\\\n\\\\t\\\\tuniform vec3 up;\\\\n\\\\n\\\\t\\\\tconst vec3 cameraPos = vec3( 0.0, 0.0, 0.0 );\\\\n\\\\n\\\\t\\\\t// constants for atmospheric scattering\\\\n\\\\t\\\\tconst float pi = 3.141592653589793238462643383279502884197169;\\\\n\\\\n\\\\t\\\\tconst float n = 1.0003; // refractive index of air\\\\n\\\\t\\\\tconst float N = 2.545E25; // number of molecules per unit volume for air at 288.15K and 1013mb (sea level -45 celsius)\\\\n\\\\n\\\\t\\\\t// optical length at zenith for molecules\\\\n\\\\t\\\\tconst float rayleighZenithLength = 8.4E3;\\\\n\\\\t\\\\tconst float mieZenithLength = 1.25E3;\\\\n\\\\t\\\\t// 66 arc seconds -> degrees, and the cosine of that\\\\n\\\\t\\\\tconst float sunAngularDiameterCos = 0.999956676946448443553574619906976478926848692873900859324;\\\\n\\\\n\\\\t\\\\t// 3.0 / ( 16.0 * pi )\\\\n\\\\t\\\\tconst float THREE_OVER_SIXTEENPI = 0.05968310365946075;\\\\n\\\\t\\\\t// 1.0 / ( 4.0 * pi )\\\\n\\\\t\\\\tconst float ONE_OVER_FOURPI = 0.07957747154594767;\\\\n\\\\n\\\\t\\\\tfloat rayleighPhase( float cosTheta ) {\\\\n\\\\t\\\\t\\\\treturn THREE_OVER_SIXTEENPI * ( 1.0 + pow( cosTheta, 2.0 ) );\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tfloat hgPhase( float cosTheta, float g ) {\\\\n\\\\t\\\\t\\\\tfloat g2 = pow( g, 2.0 );\\\\n\\\\t\\\\t\\\\tfloat inverse = 1.0 / pow( 1.0 - 2.0 * g * cosTheta + g2, 1.5 );\\\\n\\\\t\\\\t\\\\treturn ONE_OVER_FOURPI * ( ( 1.0 - g2 ) * inverse );\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec3 direction = normalize( vWorldPosition - cameraPos );\\\\n\\\\n\\\\t\\\\t\\\\t// optical length\\\\n\\\\t\\\\t\\\\t// cutoff angle at 90 to avoid singularity in next formula.\\\\n\\\\t\\\\t\\\\tfloat zenithAngle = acos( max( 0.0, dot( up, direction ) ) );\\\\n\\\\t\\\\t\\\\tfloat inverse = 1.0 / ( cos( zenithAngle ) + 0.15 * pow( 93.885 - ( ( zenithAngle * 180.0 ) / pi ), -1.253 ) );\\\\n\\\\t\\\\t\\\\tfloat sR = rayleighZenithLength * inverse;\\\\n\\\\t\\\\t\\\\tfloat sM = mieZenithLength * inverse;\\\\n\\\\n\\\\t\\\\t\\\\t// combined extinction factor\\\\n\\\\t\\\\t\\\\tvec3 Fex = exp( -( vBetaR * sR + vBetaM * sM ) );\\\\n\\\\n\\\\t\\\\t\\\\t// in scattering\\\\n\\\\t\\\\t\\\\tfloat cosTheta = dot( direction, vSunDirection );\\\\n\\\\n\\\\t\\\\t\\\\tfloat rPhase = rayleighPhase( cosTheta * 0.5 + 0.5 );\\\\n\\\\t\\\\t\\\\tvec3 betaRTheta = vBetaR * rPhase;\\\\n\\\\n\\\\t\\\\t\\\\tfloat mPhase = hgPhase( cosTheta, mieDirectionalG );\\\\n\\\\t\\\\t\\\\tvec3 betaMTheta = vBetaM * mPhase;\\\\n\\\\n\\\\t\\\\t\\\\tvec3 Lin = pow( vSunE * ( ( betaRTheta + betaMTheta ) / ( vBetaR + vBetaM ) ) * ( 1.0 - Fex ), vec3( 1.5 ) );\\\\n\\\\t\\\\t\\\\tLin *= mix( vec3( 1.0 ), pow( vSunE * ( ( betaRTheta + betaMTheta ) / ( vBetaR + vBetaM ) ) * Fex, vec3( 1.0 / 2.0 ) ), clamp( pow( 1.0 - dot( up, vSunDirection ), 5.0 ), 0.0, 1.0 ) );\\\\n\\\\n\\\\t\\\\t\\\\t// nightsky\\\\n\\\\t\\\\t\\\\tfloat theta = acos( direction.y ); // elevation --\\\\x3e y-axis, [-pi/2, pi/2]\\\\n\\\\t\\\\t\\\\tfloat phi = atan( direction.z, direction.x ); // azimuth --\\\\x3e x-axis [-pi/2, pi/2]\\\\n\\\\t\\\\t\\\\tvec2 uv = vec2( phi, theta ) / vec2( 2.0 * pi, pi ) + vec2( 0.5, 0.0 );\\\\n\\\\t\\\\t\\\\tvec3 L0 = vec3( 0.1 ) * Fex;\\\\n\\\\n\\\\t\\\\t\\\\t// composition + solar disc\\\\n\\\\t\\\\t\\\\tfloat sundisk = smoothstep( sunAngularDiameterCos, sunAngularDiameterCos + 0.00002, cosTheta );\\\\n\\\\t\\\\t\\\\tL0 += ( vSunE * 19000.0 * Fex ) * sundisk;\\\\n\\\\n\\\\t\\\\t\\\\tvec3 texColor = ( Lin + L0 ) * 0.04 + vec3( 0.0, 0.0003, 0.00075 );\\\\n\\\\n\\\\t\\\\t\\\\tvec3 retColor = pow( texColor, vec3( 1.0 / ( 1.2 + ( 1.2 * vSunfade ) ) ) );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( retColor, 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\t#include \\\\n\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const Fk=new class extends ua{constructor(){super(...arguments),this.turbidity=ha.FLOAT(2,{range:[0,20]}),this.rayleigh=ha.FLOAT(1,{range:[0,4]}),this.mieCoefficient=ha.FLOAT(.005),this.mieDirectional=ha.FLOAT(.8),this.inclination=ha.FLOAT(.5),this.azimuth=ha.FLOAT(.25),this.up=ha.VECTOR3([0,1,0])}};class Dk extends qD{constructor(){super(...arguments),this.paramsConfig=Fk}static type(){return\\\\\\\"sky\\\\\\\"}createMaterial(){const t=(new Ik).material;return t.depthWrite=!0,t}async cook(){const t=this.material.uniforms;t.turbidity.value=this.pv.turbidity,t.rayleigh.value=this.pv.rayleigh,t.mieCoefficient.value=this.pv.mieCoefficient,t.mieDirectionalG.value=this.pv.mieDirectional,t.up.value.copy(this.pv.up);const e=Math.PI*(this.pv.inclination-.5),n=2*Math.PI*(this.pv.azimuth-.5);t.sunPosition.value.x=Math.cos(n),t.sunPosition.value.y=Math.sin(n)*Math.sin(e),t.sunPosition.value.z=Math.sin(n)*Math.cos(e),this.setMaterial(this.material)}}var Bk=\\\\\\\"precision highp float;\\\\nprecision highp int;\\\\n\\\\nvarying vec3 vPw;\\\\n\\\\n#include \\\\n\\\\nvoid main()\\\\t{\\\\n\\\\n\\\\t// start builder body code\\\\n\\\\n\\\\tvPw = position;\\\\n\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n}\\\\\\\",zk=\\\\\\\"precision highp float;\\\\nprecision highp int;\\\\n\\\\n#include \\\\n\\\\n#define DIR_LIGHTS_COUNT 1\\\\n#define MAX_STEPS_COUNT 4096\\\\n\\\\nuniform vec3 u_Color;\\\\nuniform float u_VolumeDensity;\\\\nuniform float u_ShadowDensity;\\\\nuniform float u_StepSize;\\\\nuniform vec3 u_BoundingBoxMin;\\\\nuniform vec3 u_BoundingBoxMax;\\\\n//const int u_PointsCount = 3;\\\\n//uniform vec3 u_Points[3];\\\\nuniform sampler2D u_Map;\\\\n\\\\n//const int u_DirectionalLightsCount = 1;\\\\nuniform vec3 u_DirectionalLightDirection; //[DIR_LIGHTS_COUNT];\\\\n\\\\nvarying vec3 vPw;\\\\n// varying vec3 vN;\\\\n// varying vec2 vUV;\\\\n//varying vec3 vPCameraSpace;\\\\n// varying vec4 vCd;\\\\n\\\\nvec3 normalize_in_bbox(vec3 point){\\\\n\\\\n\\\\tvec3 min = u_BoundingBoxMin;\\\\n\\\\tvec3 max = u_BoundingBoxMax;\\\\n\\\\n\\\\treturn vec3(\\\\n\\\\t\\\\t(point.x - min.x) / (max.x - min.x),\\\\n\\\\t\\\\t(point.y - min.y) / (max.y - min.y),\\\\n\\\\t\\\\t(point.z - min.z) / (max.z - min.z)\\\\n\\\\t);\\\\n}\\\\n\\\\nbool is_inside_bbox(vec3 Pw){\\\\n\\\\n\\\\tvec3 min = u_BoundingBoxMin;\\\\n\\\\tvec3 max = u_BoundingBoxMax;\\\\n\\\\n\\\\treturn (\\\\n\\\\t\\\\tPw.x > min.x &&\\\\n\\\\t\\\\tPw.y > min.y &&\\\\n\\\\t\\\\tPw.z > min.z &&\\\\n\\\\n\\\\t\\\\tPw.x < max.x &&\\\\n\\\\t\\\\tPw.y < max.y &&\\\\n\\\\t\\\\tPw.z < max.z\\\\n\\\\t\\\\t);\\\\n}\\\\n\\\\nfloat density_to_opacity(float density, float step_size){\\\\n\\\\tfloat curent_density = density;\\\\n\\\\tcurent_density = max(0.0, curent_density);\\\\n\\\\n\\\\tfloat opacity = (1.0-exp(-curent_density * step_size));\\\\n\\\\treturn max(opacity,0.0);\\\\n}\\\\n\\\\nfloat density_function(vec3 position_for_step){\\\\n\\\\tfloat density = 1.0;\\\\n\\\\t// start builder body code\\\\n\\\\n\\\\treturn density;\\\\n}\\\\n\\\\nvec4 raymarch_light(vec3 ray_dir, vec3 start_pos){\\\\n\\\\n\\\\tfloat step_size = u_StepSize;\\\\n\\\\tvec3 step_vector = ray_dir * step_size;\\\\n\\\\n\\\\tvec3 current_pos = start_pos + step_vector*rand(start_pos.x*ray_dir.xy);\\\\n\\\\tfloat opacity = 0.0;\\\\n\\\\tfor(int i=0; i= 0.99){ break; }\\\\n\\\\n\\\\t\\\\tif( is_inside_bbox(current_pos) ){\\\\n\\\\n\\\\t\\\\t\\\\tfloat density = density_function(current_pos) * u_ShadowDensity;\\\\n\\\\t\\\\t\\\\topacity += density_to_opacity(density, step_size);\\\\n\\\\t\\\\t\\\\tcurrent_pos += step_vector;\\\\n\\\\n\\\\t\\\\t}else{\\\\n\\\\t\\\\t\\\\tbreak;\\\\n\\\\t\\\\t}\\\\n\\\\t}\\\\n\\\\n\\\\tvec3 light_color = vec3(1.0, 1.0, 1.0) * u_Color;\\\\n\\\\tlight_color *= (1.0-opacity);\\\\n\\\\treturn vec4(light_color, 1.0-opacity);\\\\n}\\\\n\\\\nvec4 raymarch_bbox(vec3 start_pos, vec3 ray_dir){\\\\n\\\\n\\\\tfloat step_size = u_StepSize;\\\\n\\\\tvec3 step_vector = ray_dir * step_size;\\\\n\\\\n\\\\tvec3 current_pos = start_pos - step_vector*rand(ray_dir.xz);\\\\n\\\\tfloat opacity = 0.0;\\\\n\\\\tvec3 color = vec3(0.0, 0.0, 0.0);\\\\n\\\\tfloat steps_count = 0.0;\\\\n\\\\tbool was_inside_bbox = false;\\\\n\\\\tfor(int i=0; i= 0.99){ break; }\\\\n\\\\n\\\\t\\\\tif( i==0 || is_inside_bbox(current_pos) ){\\\\n\\\\t\\\\t\\\\twas_inside_bbox = true;\\\\n\\\\n\\\\t\\\\t\\\\tfloat density = density_function(current_pos) * u_VolumeDensity;\\\\n\\\\t\\\\t\\\\topacity += density_to_opacity(density, step_size);\\\\n\\\\n\\\\t\\\\t\\\\tvec4 light_color = vec4(0.0,0.0,0.0,1.0); //vec4(1.0,1.0,1.0,1.0);\\\\n\\\\t\\\\t\\\\t// vec3 directional_light_direction;\\\\n\\\\t\\\\t\\\\t// for ( int l = 0; l < DIR_LIGHTS_COUNT; l++ ) {\\\\n\\\\t\\\\t\\\\t// directional_light_direction = u_DirectionalLightsDirection[ l ];\\\\n\\\\t\\\\t\\\\tlight_color += raymarch_light(-u_DirectionalLightDirection, current_pos);\\\\n\\\\t\\\\t\\\\t// }\\\\n\\\\t\\\\t\\\\tfloat blend = 1.0-opacity;\\\\n\\\\t\\\\t\\\\tcolor = mix( color.xyz, light_color.xyz, vec3(blend, blend, blend) );\\\\n\\\\t\\\\t\\\\tsteps_count += 1.0;\\\\n\\\\n\\\\t\\\\t}else{\\\\n\\\\t\\\\t\\\\tif (was_inside_bbox) { break; }\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\tcurrent_pos += step_vector;\\\\n\\\\t}\\\\n\\\\n\\\\treturn vec4(color, opacity);\\\\n\\\\t// steps_count = steps_count / 5.0;\\\\n\\\\t// return vec4(vec3(steps_count, steps_count, steps_count), 1.0);\\\\n}\\\\n\\\\nvoid main()\\\\t{\\\\n\\\\n\\\\tvec3 eye = normalize(vPw - cameraPosition);\\\\n\\\\t// we can start from the bbox, as we are front facing\\\\n\\\\tvec3 start_pos = vPw;\\\\n\\\\n\\\\tvec4 color = raymarch_bbox(start_pos, eye);\\\\n\\\\tgl_FragColor = color;\\\\n\\\\n}\\\\\\\";const kk={u_Color:{value:new D.a(1,1,1)},u_VolumeDensity:{value:5},u_ShadowDensity:{value:2},u_StepSize:{value:.01},u_BoundingBoxMin:{value:new p.a(-1,-1,-1)},u_BoundingBoxMax:{value:new p.a(1,1,1)},u_DirectionalLightDirection:{value:new p.a(-1,-1,-1)}};function Uk(t){return class extends t{constructor(){super(...arguments),this.color=ha.COLOR([1,1,1]),this.stepSize=ha.FLOAT(.01),this.density=ha.FLOAT(1),this.shadowDensity=ha.FLOAT(1),this.lightDir=ha.VECTOR3([-1,-1,-1])}}}Uk(ua);class Gk{constructor(t){this.node=t}static render_hook(t,e,n,i,s,r,o){if(o){this._object_bbox.setFromObject(o);const t=s;t.uniforms.u_BoundingBoxMin.value.copy(this._object_bbox.min),t.uniforms.u_BoundingBoxMax.value.copy(this._object_bbox.max)}}update_uniforms_from_params(){const t=this.node.material.uniforms;t.u_Color.value.copy(this.node.pv.color),t.u_StepSize.value=this.node.pv.stepSize,t.u_VolumeDensity.value=this.node.pv.density,t.u_ShadowDensity.value=this.node.pv.shadowDensity;const e=t.u_DirectionalLightDirection.value,n=this.node.pv.lightDir;e&&(e.x=n.x,e.y=n.y,e.z=n.z)}}Gk._object_bbox=new Cy.a;class Vk extends(Uk(ua)){}const Hk=new Vk;class jk extends qD{constructor(){super(...arguments),this.paramsConfig=Hk,this._volume_controller=new Gk(this)}static type(){return\\\\\\\"volume\\\\\\\"}createMaterial(){const t=new F({vertexShader:Bk,fragmentShader:zk,side:w.H,transparent:!0,depthTest:!0,uniforms:I.clone(kk)});return yr.add_user_data_render_hook(t,Gk.render_hook.bind(Gk)),t}initializeNode(){}async cook(){this._volume_controller.update_uniforms_from_params(),this.setMaterial(this.material)}}class Wk extends(sB(Uk(ua))){}const qk=new Wk;class Xk extends rB{constructor(){super(...arguments),this.paramsConfig=qk,this._volume_controller=new 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Float32Array(t),i=new Float32Array(e);V.LTC_FLOAT_1=new vo.a(n,64,64,w.Ib,w.G,w.Yc,w.n,w.n,w.V,w.ob,1),V.LTC_FLOAT_2=new vo.a(i,64,64,w.Ib,w.G,w.Yc,w.n,w.n,w.V,w.ob,1);const s=new Uint16Array(t.length);t.forEach((function(t,e){s[e]=dU.a.toHalfFloat(t)}));const r=new Uint16Array(e.length);e.forEach((function(t,e){r[e]=dU.a.toHalfFloat(t)})),V.LTC_HALF_1=new vo.a(s,64,64,w.Ib,w.M,w.Yc,w.n,w.n,w.V,w.ob,1),V.LTC_HALF_2=new vo.a(r,64,64,w.Ib,w.M,w.Yc,w.n,w.n,w.V,w.ob,1)}}!function(t){t.OBJECTS=\\\\\\\"objects\\\\\\\",t.GEOMETRIES=\\\\\\\"geometries\\\\\\\"}(uU||(uU={}));const _U=[uU.GEOMETRIES,uU.OBJECTS];var mU;!function(t){t.XYZ=\\\\\\\"XYZ\\\\\\\",t.XZY=\\\\\\\"XZY\\\\\\\",t.YXZ=\\\\\\\"YXZ\\\\\\\",t.YZX=\\\\\\\"YZX\\\\\\\",t.ZYX=\\\\\\\"ZYX\\\\\\\",t.ZXY=\\\\\\\"ZXY\\\\\\\"}(mU||(mU={}));const fU=[mU.XYZ,mU.XZY,mU.YXZ,mU.YZX,mU.ZXY,mU.ZYX],gU=mU.XYZ;class vU{constructor(){this._translation_matrix=new A.a,this._translation_matrix_q=new hh.a,this._translation_matrix_s=new 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set_params_from_object(t,e){t.position.toArray(this.set_params_from_object_position_array),t.rotation.toArray(this.set_params_from_object_rotation_array),this.set_params_from_object_rotation_deg.fromArray(this.set_params_from_object_rotation_array),this.set_params_from_object_rotation_deg.multiplyScalar(180/Math.PI),this.set_params_from_object_rotation_deg.toArray(this.set_params_from_object_rotation_array),e.scene().batchUpdates((()=>{e.params.set_vector3(\\\\\\\"t\\\\\\\",this.set_params_from_object_position_array),e.params.set_vector3(\\\\\\\"r\\\\\\\",this.set_params_from_object_rotation_array)}))}translation_matrix(t){return this._translation_matrix.compose(t,this._translation_matrix_q,this._translation_matrix_s),this._translation_matrix}matrix(t,e,n,i,s){return this._matrix_euler.set(Object(On.e)(e.x),Object(On.e)(e.y),Object(On.e)(e.z),s),this._matrix_q.setFromEuler(this._matrix_euler),this._matrix_s.copy(n).multiplyScalar(i),this._matrix.compose(t,this._matrix_q,this._matrix_s),this._matrix}rotate_geometry(t,e,n){this._rotate_geometry_vec_dest.copy(n),this._rotate_geometry_vec_dest.normalize(),this._rotate_geometry_q.setFromUnitVectors(e,this._rotate_geometry_vec_dest),this._rotate_geometry_m.makeRotationFromQuaternion(this._rotate_geometry_q),t.applyMatrix4(this._rotate_geometry_m)}static decompose_matrix(t){t.matrix.decompose(t.position,t.quaternion,t.scale)}}function yU(t,e){const n=(null==e?void 0:e.matrixAutoUpdate)||!1;return class extends t{constructor(){super(...arguments),this.transform=ha.FOLDER(),this.keepPosWhenParenting=ha.BOOLEAN(0),this.rotationOrder=ha.INTEGER(fU.indexOf(mU.XYZ),{menu:{entries:fU.map(((t,e)=>({name:t,value:e})))}}),this.t=ha.VECTOR3([0,0,0]),this.r=ha.VECTOR3([0,0,0]),this.s=ha.VECTOR3([1,1,1]),this.scale=ha.FLOAT(1),this.matrixAutoUpdate=ha.BOOLEAN(n?1:0),this.updateTransformFromObject=ha.BUTTON(null,{callback:t=>{bU.PARAM_CALLBACK_update_transform_from_object(t)}})}}}vU.set_params_from_matrix_position=new p.a,vU.set_params_from_matrix_quaternion=new hh.a,vU.set_params_from_matrix_scale=new p.a,vU.set_params_from_matrix_euler=new Zv.a,vU.set_params_from_matrix_rotation=new p.a,vU.set_params_from_matrix_t=[0,0,0],vU.set_params_from_matrix_r=[0,0,0],vU.set_params_from_matrix_s=[0,0,0],vU.set_params_from_object_position_array=[0,0,0],vU.set_params_from_object_rotation_deg=new p.a,vU.set_params_from_object_rotation_array=[0,0,0];yU(ua);const xU=\\\\\\\"_cook_main_without_inputs_when_dirty\\\\\\\";class bU{constructor(t){this.node=t,this._cook_main_without_inputs_when_dirty_bound=this._cook_main_without_inputs_when_dirty.bind(this),this._core_transform=new vU,this._keep_pos_when_parenting_m_object=new A.a,this._keep_pos_when_parenting_m_new_parent_inv=new A.a}initializeNode(){this.node.dirtyController.hasHook(xU)||this.node.dirtyController.addPostDirtyHook(xU,this._cook_main_without_inputs_when_dirty_bound)}async _cook_main_without_inputs_when_dirty(){await this.node.cookController.cookMainWithoutInputs()}update(){this.update_transform_with_matrix();this.node.object.matrixAutoUpdate=this.node.pv.matrixAutoUpdate}update_transform_with_matrix(t){const e=this.node.object;null==t||t.equals(e.matrix)?this._update_matrix_from_params_with_core_transform():(e.matrix.copy(t),e.dispatchEvent({type:\\\\\\\"change\\\\\\\"}))}_update_matrix_from_params_with_core_transform(){const t=this.node.object;let e=t.matrixAutoUpdate;e&&(t.matrixAutoUpdate=!1);const n=this._core_transform.matrix(this.node.pv.t,this.node.pv.r,this.node.pv.s,this.node.pv.scale,fU[this.node.pv.rotationOrder]);t.matrix.identity(),t.applyMatrix4(n),this._apply_look_at(),t.updateMatrix(),e&&(t.matrixAutoUpdate=!0),t.dispatchEvent({type:\\\\\\\"change\\\\\\\"})}_apply_look_at(){}set_params_from_matrix(t,e={}){vU.set_params_from_matrix(t,this.node,e)}static update_node_transform_params_if_required(t,e){t.transformController.update_node_transform_params_if_required(e)}update_node_transform_params_if_required(t){if(!this.node.pv.keepPosWhenParenting)return;if(!this.node.scene().loadingController.loaded())return;if(t==this.node.object.parent)return;const e=this.node.object;e.updateMatrixWorld(!0),t.updateMatrixWorld(!0),this._keep_pos_when_parenting_m_object.copy(e.matrixWorld),this._keep_pos_when_parenting_m_new_parent_inv.copy(t.matrixWorld),this._keep_pos_when_parenting_m_new_parent_inv.invert(),this._keep_pos_when_parenting_m_object.premultiply(this._keep_pos_when_parenting_m_new_parent_inv),vU.set_params_from_matrix(this._keep_pos_when_parenting_m_object,this.node,{scale:!0})}update_node_transform_params_from_object(t=!1){const e=this.node.object;t&&e.updateMatrix(),vU.set_params_from_matrix(e.matrix,this.node,{scale:!0})}static PARAM_CALLBACK_update_transform_from_object(t){t.transformController.update_node_transform_params_from_object()}}class wU{constructor(t){this.node=t}initializeNode(){this.node.io.inputs.setCount(0,1),this.node.io.inputs.set_depends_on_inputs(!1),this.node.io.outputs.setHasOneOutput(),this.node.io.inputs.add_on_set_input_hook(\\\\\\\"on_input_updated:update_parent\\\\\\\",(()=>{this.on_input_updated()}))}static on_input_updated(t){const e=t.root().getParentForNode(t);t.transformController&&e&&bU.update_node_transform_params_if_required(t,e),null!=t.io.inputs.input(0)?t.root().addToParentTransform(t):t.root().removeFromParentTransform(t)}on_input_updated(){wU.on_input_updated(this.node)}}yU(ua);class TU extends aU{constructor(){super(...arguments),this.flags=new Di(this),this.hierarchyController=new wU(this),this.transformController=new bU(this)}initializeBaseNode(){super.initializeBaseNode(),this.hierarchyController.initializeNode(),this.transformController.initializeNode()}cook(){this.transformController.update(),this.updateLightParams(),this.updateShadowParams(),this.cookController.endCook()}}class 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t.matrixAutoUpdate=!1,pU.initialized||(pU.init(),pU.initialized=!0),t}updateLightParams(){this.light.color=this.pv.color,this.light.intensity=this.pv.intensity,this.light.width=this.pv.width,this.light.height=this.pv.height,this._helperController.update()}}var PU=n(72);const RU=new p.a,IU=new of.a;class FU extends Ms.a{constructor(t){const e=new S.a,n=new As.a({color:16777215,vertexColors:!0,toneMapped:!1}),i=[],s=[],r={},o=new D.a(16755200),a=new D.a(16711680),l=new D.a(43775),c=new D.a(16777215),h=new D.a(3355443);function u(t,e,n){d(t,n),d(e,n)}function d(t,e){i.push(0,0,0),s.push(e.r,e.g,e.b),void 0===r[t]&&(r[t]=[]),r[t].push(i.length/3-1)}u(\\\\\\\"n1\\\\\\\",\\\\\\\"n2\\\\\\\",o),u(\\\\\\\"n2\\\\\\\",\\\\\\\"n4\\\\\\\",o),u(\\\\\\\"n4\\\\\\\",\\\\\\\"n3\\\\\\\",o),u(\\\\\\\"n3\\\\\\\",\\\\\\\"n1\\\\\\\",o),u(\\\\\\\"f1\\\\\\\",\\\\\\\"f2\\\\\\\",o),u(\\\\\\\"f2\\\\\\\",\\\\\\\"f4\\\\\\\",o),u(\\\\\\\"f4\\\\\\\",\\\\\\\"f3\\\\\\\",o),u(\\\\\\\"f3\\\\\\\",\\\\\\\"f1\\\\\\\",o),u(\\\\\\\"n1\\\\\\\",\\\\\\\"f1\\\\\\\",o),u(\\\\\\\"n2\\\\\\\",\\\\\\\"f2\\\\\\\",o),u(\\\\\\\"n3\\\\\\\",\\\\\\\"f3\\\\\\\",o),u(\\\\\\\"n4\\\\\\\",\\\\\\\"f4\\\\\\\",o),u(\\\\\\\"p\\\\\\\",\\\\\\\"n1\\\\\\\",a),u(\\\\\\\"p\\\\\\\",\\\\\\\"n2\\\\\\\",a),u(\\\\\\\"p\\\\\\\",\\\\\\\"n3\\\\\\\",a),u(\\\\\\\"p\\\\\\\",\\\\\\\"n4\\\\\\\",a),u(\\\\\\\"u1\\\\\\\",\\\\\\\"u2\\\\\\\",l),u(\\\\\\\"u2\\\\\\\",\\\\\\\"u3\\\\\\\",l),u(\\\\\\\"u3\\\\\\\",\\\\\\\"u1\\\\\\\",l),u(\\\\\\\"c\\\\\\\",\\\\\\\"t\\\\\\\",c),u(\\\\\\\"p\\\\\\\",\\\\\\\"c\\\\\\\",h),u(\\\\\\\"cn1\\\\\\\",\\\\\\\"cn2\\\\\\\",h),u(\\\\\\\"cn3\\\\\\\",\\\\\\\"cn4\\\\\\\",h),u(\\\\\\\"cf1\\\\\\\",\\\\\\\"cf2\\\\\\\",h),u(\\\\\\\"cf3\\\\\\\",\\\\\\\"cf4\\\\\\\",h),e.setAttribute(\\\\\\\"position\\\\\\\",new C.c(i,3)),e.setAttribute(\\\\\\\"color\\\\\\\",new C.c(s,3)),super(e,n),this.type=\\\\\\\"CameraHelper\\\\\\\",this.camera=t,this.camera.updateProjectionMatrix&&this.camera.updateProjectionMatrix(),this.matrixAutoUpdate=!1,this.pointMap=r,this.update()}update(){const t=this.geometry,e=this.pointMap;IU.projectionMatrixInverse.copy(this.camera.projectionMatrixInverse),DU(\\\\\\\"c\\\\\\\",e,t,IU,0,0,-1),DU(\\\\\\\"t\\\\\\\",e,t,IU,0,0,1),DU(\\\\\\\"n1\\\\\\\",e,t,IU,-1,-1,-1),DU(\\\\\\\"n2\\\\\\\",e,t,IU,1,-1,-1),DU(\\\\\\\"n3\\\\\\\",e,t,IU,-1,1,-1),DU(\\\\\\\"n4\\\\\\\",e,t,IU,1,1,-1),DU(\\\\\\\"f1\\\\\\\",e,t,IU,-1,-1,1),DU(\\\\\\\"f2\\\\\\\",e,t,IU,1,-1,1),DU(\\\\\\\"f3\\\\\\\",e,t,IU,-1,1,1),DU(\\\\\\\"f4\\\\\\\",e,t,IU,1,1,1),DU(\\\\\\\"u1\\\\\\\",e,t,IU,.7,1.1,-1),DU(\\\\\\\"u2\\\\\\\",e,t,IU,-.7,1.1,-1),DU(\\\\\\\"u3\\\\\\\",e,t,IU,0,2,-1),DU(\\\\\\\"cf1\\\\\\\",e,t,IU,-1,0,1),DU(\\\\\\\"cf2\\\\\\\",e,t,IU,1,0,1),DU(\\\\\\\"cf3\\\\\\\",e,t,IU,0,-1,1),DU(\\\\\\\"cf4\\\\\\\",e,t,IU,0,1,1),DU(\\\\\\\"cn1\\\\\\\",e,t,IU,-1,0,-1),DU(\\\\\\\"cn2\\\\\\\",e,t,IU,1,0,-1),DU(\\\\\\\"cn3\\\\\\\",e,t,IU,0,-1,-1),DU(\\\\\\\"cn4\\\\\\\",e,t,IU,0,1,-1),t.getAttribute(\\\\\\\"position\\\\\\\").needsUpdate=!0}}function DU(t,e,n,i,s,r,o){RU.set(s,r,o).unproject(i);const a=e[t];if(void 0!==a){const t=n.getAttribute(\\\\\\\"position\\\\\\\");for(let e=0,n=a.length;e.9&&o<.1&&(e<.2&&(r[t+0]+=1),n<.2&&(r[t+2]+=1),i<.2&&(r[t+4]+=1))}}()}(),this.setAttribute(\\\\\\\"position\\\\\\\",new C.c(s,3)),this.setAttribute(\\\\\\\"normal\\\\\\\",new C.c(s.slice(),3)),this.setAttribute(\\\\\\\"uv\\\\\\\",new C.c(r,2)),0===i?this.computeVertexNormals():this.normalizeNormals()}static fromJSON(t){return new jU(t.vertices,t.indices,t.radius,t.details)}}class WU extends jU{constructor(t=1,e=0){super([1,0,0,-1,0,0,0,1,0,0,-1,0,0,0,1,0,0,-1],[0,2,4,0,4,3,0,3,5,0,5,2,1,2,5,1,5,3,1,3,4,1,4,2],t,e),this.type=\\\\\\\"OctahedronGeometry\\\\\\\",this.parameters={radius:t,detail:e}}static fromJSON(t){return new WU(t.radius,t.detail)}}class qU extends SU{constructor(){super(...arguments),this._geometry=new WU(1),this._quat=new hh.a,this._default_position=new p.a(0,1,0),this._color1=new D.a,this._color2=new D.a}createObject(){return new B.a}buildHelper(){this._geometry.rotateZ(.5*Math.PI),this._material.vertexColors=!0;const t=this._geometry.getAttribute(\\\\\\\"position\\\\\\\"),e=new Float32Array(3*t.count);this._geometry.setAttribute(\\\\\\\"color\\\\\\\",new C.a(e,3)),this._object.geometry=this._geometry,this._object.material=this._material,this._object.matrixAutoUpdate=!1}update(){if(!this.node.pv.position)return;this._object.position.copy(this.node.pv.position).multiplyScalar(-1),this._quat.setFromUnitVectors(this._default_position,this.node.pv.position),this._object.setRotationFromQuaternion(this._quat),this._object.scale.setScalar(this.node.pv.helperSize),this._object.updateMatrix();const t=this._geometry.getAttribute(\\\\\\\"color\\\\\\\");this._color1.copy(this.node.light.color),this._color2.copy(this.node.light.groundColor);for(let e=0,n=t.count;e0)&&d.push(e,s,l),(t!==n-1||a0&&y(!0),e>0&&y(!1)),this.setIndex(c),this.setAttribute(\\\\\\\"position\\\\\\\",new C.c(h,3)),this.setAttribute(\\\\\\\"normal\\\\\\\",new C.c(u,3)),this.setAttribute(\\\\\\\"uv\\\\\\\",new C.c(_,2))}static fromJSON(t){return new sG(t.radiusTop,t.radiusBottom,t.height,t.radialSegments,t.heightSegments,t.openEnded,t.thetaStart,t.thetaLength)}}class rG extends sG{constructor(t=1,e=1,n=8,i=1,s=!1,r=0,o=2*Math.PI){super(0,t,e,n,i,s,r,o),this.type=\\\\\\\"ConeGeometry\\\\\\\",this.parameters={radius:t,height:e,radialSegments:n,heightSegments:i,openEnded:s,thetaStart:r,thetaLength:o}}static fromJSON(t){return new rG(t.radius,t.height,t.radialSegments,t.heightSegments,t.openEnded,t.thetaStart,t.thetaLength)}}class oG{constructor(t){this.node=t}update(){const t=this.node.pv;if(t.tvolumetric){const e=this.object(),n=this.node.light;iG.updateConeObject(e,{sizeMult:t.helperSize,distance:n.distance,angle:n.angle});const i=e.material.uniforms;i.lightColor.value.copy(n.color),i.attenuation.value=t.volAttenuation,i.anglePower.value=t.volAnglePower,this.node.light.add(e)}else this._mesh&&this.node.light.remove(this._mesh)}object(){return this._mesh=this._mesh||this._createMesh()}_createMesh(){const t=new rG(1,1,256,1);t.applyMatrix4((new A.a).makeTranslation(0,-.5,0)),t.applyMatrix4((new A.a).makeRotationX(-Math.PI/2));const e=this._createMaterial(),n=new B.a(t,e);return n.matrixAutoUpdate=!1,n.name=\\\\\\\"Volumetric\\\\\\\",e.uniforms.lightColor.value.set(\\\\\\\"white\\\\\\\"),n}_createMaterial(){return new F({uniforms:{attenuation:{value:5},anglePower:{value:1.2},lightColor:{value:new D.a(\\\\\\\"cyan\\\\\\\")}},vertexShader:\\\\\\\"varying vec3 vNormal;\\\\nvarying vec3 vWorldPosition;\\\\nvarying vec3 vWorldOrigin;\\\\n\\\\nvoid main(){\\\\n\\\\t// compute intensity\\\\n\\\\tvNormal\\\\t\\\\t= normalize( normalMatrix * normal );\\\\n\\\\n\\\\tvec4 worldPosition\\\\t= modelMatrix * vec4( position, 1.0 );\\\\n\\\\tvWorldPosition\\\\t\\\\t= worldPosition.xyz;\\\\n\\\\n\\\\tvec4 worldOrigin\\\\t= modelMatrix * vec4( 0.0, 0.0, 0.0, 1.0 );\\\\n\\\\tvWorldOrigin\\\\t\\\\t= worldOrigin.xyz;\\\\n\\\\n\\\\t// set gl_Position\\\\n\\\\tgl_Position\\\\t= projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n}\\\\\\\",fragmentShader:\\\\\\\"varying vec3 vNormal;\\\\nvarying vec3 vWorldPosition;\\\\nvarying vec3 vWorldOrigin;\\\\n\\\\nuniform vec3 lightColor;\\\\n\\\\n// uniform vec3 spotPosition;\\\\n\\\\nuniform float attenuation;\\\\nuniform float anglePower;\\\\n\\\\nvoid main(){\\\\n\\\\n\\\\t//////////////////////////////////////////////////////////\\\\n\\\\t// distance attenuation //\\\\n\\\\t//////////////////////////////////////////////////////////\\\\n\\\\tfloat intensity = distance(vWorldPosition, vWorldOrigin) / attenuation;\\\\n\\\\tintensity = 1.0 - clamp(intensity, 0.0, 1.0);\\\\n\\\\n\\\\t//////////////////////////////////////////////////////////\\\\n\\\\t// intensity on angle //\\\\n\\\\t//////////////////////////////////////////////////////////\\\\n\\\\tvec3 normal = vec3(vNormal.x, vNormal.y, abs(vNormal.z));\\\\n\\\\tfloat angleIntensity = pow( dot(normal, vec3(0.0, 0.0, 1.0)), anglePower );\\\\n\\\\tintensity = intensity * angleIntensity;\\\\n\\\\t// 'gl_FragColor = vec4( lightColor, intensity );\\\\n\\\\n\\\\t//////////////////////////////////////////////////////////\\\\n\\\\t// final color //\\\\n\\\\t//////////////////////////////////////////////////////////\\\\n\\\\n\\\\t// set the final color\\\\n\\\\tgl_FragColor = vec4( lightColor, intensity);\\\\n}\\\\\\\",transparent:!0,depthWrite:!1})}}class aG extends(yU(ua)){constructor(){super(...arguments),this.light=ha.FOLDER(),this.color=ha.COLOR([1,1,1],{conversion:lo.SRGB_TO_LINEAR}),this.intensity=ha.FLOAT(1),this.angle=ha.FLOAT(45,{range:[0,180]}),this.penumbra=ha.FLOAT(.1),this.decay=ha.FLOAT(.1,{range:[0,1]}),this.distance=ha.FLOAT(100,{range:[0,100]}),this.showHelper=ha.BOOLEAN(0),this.helperSize=ha.FLOAT(1,{visibleIf:{showHelper:1}}),this.shadow=ha.FOLDER(),this.castShadow=ha.BOOLEAN(1),this.shadowAutoUpdate=ha.BOOLEAN(1,{visibleIf:{castShadow:1}}),this.shadowUpdateOnNextRender=ha.BOOLEAN(0,{visibleIf:{castShadow:1,shadowAutoUpdate:0}}),this.shadowRes=ha.VECTOR2([256,256],{visibleIf:{castShadow:1}}),this.shadowBias=ha.FLOAT(.001,{visibleIf:{castShadow:1},range:[-.01,.01],rangeLocked:[!1,!1]}),this.shadowNear=ha.FLOAT(.1,{visibleIf:{castShadow:1},range:[0,100],rangeLocked:[!0,!1]}),this.shadowFar=ha.FLOAT(100,{visibleIf:{castShadow:1},range:[0,100],rangeLocked:[!0,!1]}),this.shadowRadius=ha.FLOAT(0,{visibleIf:{castShadow:1},range:[0,10],rangeLocked:[!0,!1]}),this.volumetric=ha.FOLDER(),this.tvolumetric=ha.BOOLEAN(0),this.volAttenuation=ha.FLOAT(5,{range:[0,10],rangeLocked:[!0,!1]}),this.volAnglePower=ha.FLOAT(10,{range:[0,20],rangeLocked:[!0,!1]})}}const lG=new aG;class cG extends TU{constructor(){super(...arguments),this.paramsConfig=lG,this._helperController=new AU(this,iG,\\\\\\\"SpotLightHelper\\\\\\\"),this._volumetricController=new oG(this)}static type(){return zU.SPOT}initializeNode(){this._helperController.initializeNode()}createLight(){const t=new nG.a;return t.matrixAutoUpdate=!1,t.castShadow=!0,t.shadow.bias=-.001,t.shadow.mapSize.x=256,t.shadow.mapSize.y=256,t.shadow.camera.near=.1,this._target_target=t.target,this._target_target.name=\\\\\\\"SpotLight Default Target\\\\\\\",this._target_target.matrixAutoUpdate=!1,this.object.add(this._target_target),t}updateLightParams(){this.light.color=this.pv.color,this.light.intensity=this.pv.intensity,this.light.angle=this.pv.angle*(Math.PI/180),this.light.penumbra=this.pv.penumbra,this.light.decay=this.pv.decay,this.light.distance=this.pv.distance,this._helperController.update(),this._volumetricController.update()}updateShadowParams(){this.light.castShadow=this.pv.castShadow,this.light.shadow.autoUpdate=this.pv.shadowAutoUpdate,this.light.shadow.needsUpdate=this.pv.shadowUpdateOnNextRender,this.light.shadow.mapSize.copy(this.pv.shadowRes),this.light.shadow.camera.near=this.pv.shadowNear,this.light.shadow.camera.far=this.pv.shadowFar,this.light.shadow.bias=this.pv.shadowBias,this.light.shadow.radius=this.pv.shadowRadius}}let hG;const uG=function(){return void 0===hG&&(hG=new(window.AudioContext||window.webkitAudioContext)),hG},dG=new p.a,pG=new hh.a,_G=new p.a,mG=new p.a;class fG extends K.a{constructor(){super(),this.type=\\\\\\\"AudioListener\\\\\\\",this.context=uG(),this.gain=this.context.createGain(),this.gain.connect(this.context.destination),this.filter=null,this.timeDelta=0,this._clock=new Dm}getInput(){return this.gain}removeFilter(){return null!==this.filter&&(this.gain.disconnect(this.filter),this.filter.disconnect(this.context.destination),this.gain.connect(this.context.destination),this.filter=null),this}getFilter(){return this.filter}setFilter(t){return null!==this.filter?(this.gain.disconnect(this.filter),this.filter.disconnect(this.context.destination)):this.gain.disconnect(this.context.destination),this.filter=t,this.gain.connect(this.filter),this.filter.connect(this.context.destination),this}getMasterVolume(){return this.gain.gain.value}setMasterVolume(t){return this.gain.gain.setTargetAtTime(t,this.context.currentTime,.01),this}updateMatrixWorld(t){super.updateMatrixWorld(t);const e=this.context.listener,n=this.up;if(this.timeDelta=this._clock.getDelta(),this.matrixWorld.decompose(dG,pG,_G),mG.set(0,0,-1).applyQuaternion(pG),e.positionX){const t=this.context.currentTime+this.timeDelta;e.positionX.linearRampToValueAtTime(dG.x,t),e.positionY.linearRampToValueAtTime(dG.y,t),e.positionZ.linearRampToValueAtTime(dG.z,t),e.forwardX.linearRampToValueAtTime(mG.x,t),e.forwardY.linearRampToValueAtTime(mG.y,t),e.forwardZ.linearRampToValueAtTime(mG.z,t),e.upX.linearRampToValueAtTime(n.x,t),e.upY.linearRampToValueAtTime(n.y,t),e.upZ.linearRampToValueAtTime(n.z,t)}else e.setPosition(dG.x,dG.y,dG.z),e.setOrientation(mG.x,mG.y,mG.z,n.x,n.y,n.z)}}class gG extends(yU(ua)){constructor(){super(...arguments),this.audio=ha.FOLDER(),this.soundOn=ha.BOOLEAN(1),this.masterVolume=ha.FLOAT(1,{range:[0,1],rangeLocked:[!0,!1]})}}const vG=new gG;class yG extends oU{constructor(){super(...arguments),this.paramsConfig=vG,this.hierarchyController=new wU(this),this.transformController=new bU(this),this.flags=new Di(this)}static type(){return Ig.AUDIO_LISTENER}createObject(){const t=new fG;return t.matrixAutoUpdate=!1,t}initializeNode(){this.hierarchyController.initializeNode(),this.transformController.initializeNode(),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.soundOn],(()=>this.pv.soundOn?\\\\\\\"on\\\\\\\":\\\\\\\"off\\\\\\\"))}))}))}cook(){this.transformController.update(),this._updatePositionalAudio(),this.cookController.endCook()}_updatePositionalAudio(){const t=this.pv.soundOn?this.pv.masterVolume:0;this.object.setMasterVolume(t)}}class xG extends Ms.a{constructor(t=1){const e=[0,0,0,t,0,0,0,0,0,0,t,0,0,0,0,0,0,t],n=new S.a;n.setAttribute(\\\\\\\"position\\\\\\\",new C.c(e,3)),n.setAttribute(\\\\\\\"color\\\\\\\",new C.c([1,0,0,1,.6,0,0,1,0,.6,1,0,0,0,1,0,.6,1],3));super(n,new As.a({vertexColors:!0,toneMapped:!1})),this.type=\\\\\\\"AxesHelper\\\\\\\"}setColors(t,e,n){const i=new D.a,s=this.geometry.attributes.color.array;return i.set(t),i.toArray(s,0),i.toArray(s,3),i.set(e),i.toArray(s,6),i.toArray(s,9),i.set(n),i.toArray(s,12),i.toArray(s,15),this.geometry.attributes.color.needsUpdate=!0,this}dispose(){this.geometry.dispose(),this.material.dispose()}}var bG;!function(t){t.TOGETHER=\\\\\\\"translate + rotate together\\\\\\\",t.SEPARATELY=\\\\\\\"translate + rotate separately\\\\\\\"}(bG||(bG={}));const wG=[bG.TOGETHER,bG.SEPARATELY];const TG=new class extends ua{constructor(){super(...arguments),this.object0=ha.OPERATOR_PATH(\\\\\\\"/geo1\\\\\\\",{nodeSelection:{context:ts.OBJ}}),this.object1=ha.OPERATOR_PATH(\\\\\\\"/geo2\\\\\\\",{nodeSelection:{context:ts.OBJ}}),this.mode=ha.INTEGER(wG.indexOf(bG.TOGETHER),{menu:{entries:wG.map(((t,e)=>({name:t,value:e})))}}),this.blend=ha.FLOAT(0,{visibleIf:{mode:wG.indexOf(bG.TOGETHER)},range:[0,1],rangeLocked:[!1,!1]}),this.blendT=ha.FLOAT(0,{visibleIf:{mode:wG.indexOf(bG.SEPARATELY)},range:[0,1],rangeLocked:[!1,!1]}),this.blendR=ha.FLOAT(0,{visibleIf:{mode:wG.indexOf(bG.SEPARATELY)},range:[0,1],rangeLocked:[!1,!1]})}};class AG extends oU{constructor(){super(...arguments),this.paramsConfig=TG,this.hierarchyController=new wU(this),this.flags=new Di(this),this._helper=new xG(1),this._t0=new p.a,this._q0=new hh.a,this._s0=new p.a,this._t1=new p.a,this._q1=new hh.a,this._s1=new p.a}static type(){return\\\\\\\"blend\\\\\\\"}createObject(){const t=new Fn.a;return t.matrixAutoUpdate=!1,t}initializeNode(){this.hierarchyController.initializeNode(),this.io.inputs.setCount(0),this.addPostDirtyHook(\\\\\\\"blend_on_dirty\\\\\\\",(()=>{this.cookController.cookMainWithoutInputs()})),this._updateHelperHierarchy(),this.flags.display.onUpdate((()=>{this._updateHelperHierarchy()}))}_updateHelperHierarchy(){this.flags.display.active()?this.object.add(this._helper):this.object.remove(this._helper)}cook(){const t=this.p.object0.found_node_with_context(ts.OBJ),e=this.p.object1.found_node_with_context(ts.OBJ);t&&e&&this._blend(t.object,e.object),this.cookController.endCook()}_blend(t,e){const n=wG[this.pv.mode];switch(n){case bG.TOGETHER:return this._blend_together(t,e);case bG.SEPARATELY:return this._blend_separately(t,e)}os.unreachable(n)}_blend_together(t,e){this._decompose_matrices(t,e),this._object.position.copy(this._t0).lerp(this._t1,this.pv.blend),this._object.quaternion.copy(this._q0).slerp(this._q1,this.pv.blend),this._object.matrixAutoUpdate||this._object.updateMatrix()}_blend_separately(t,e){this._decompose_matrices(t,e),this._object.position.copy(this._t0).lerp(this._t1,this.pv.blendT),this._object.quaternion.copy(this._q0).slerp(this._q1,this.pv.blendR),this._object.matrixAutoUpdate||this._object.updateMatrix()}_decompose_matrices(t,e){t.matrixWorld.decompose(this._t0,this._q0,this._s0),e.matrixWorld.decompose(this._t1,this._q1,this._s1)}}var MG={uniforms:{tDiffuse:{value:null},h:{value:1/512}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\t\\\\tuniform float h;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 sum = vec4( 0.0 );\\\\n\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x - 4.0 * h, vUv.y ) ) * 0.051;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x - 3.0 * h, vUv.y ) ) * 0.0918;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x - 2.0 * h, vUv.y ) ) * 0.12245;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x - 1.0 * h, vUv.y ) ) * 0.1531;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y ) ) * 0.1633;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x + 1.0 * h, vUv.y ) ) * 0.1531;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x + 2.0 * h, vUv.y ) ) * 0.12245;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x + 3.0 * h, vUv.y ) ) * 0.0918;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x + 4.0 * h, vUv.y ) ) * 0.051;\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = sum;\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const EG={uniforms:{tDiffuse:{value:null},v:{value:1/512}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\t\\\\tuniform float v;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 sum = vec4( 0.0 );\\\\n\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y - 4.0 * v ) ) * 0.051;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y - 3.0 * v ) ) * 0.0918;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y - 2.0 * v ) ) * 0.12245;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y - 1.0 * v ) ) * 0.1531;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y ) ) * 0.1633;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y + 1.0 * v ) ) * 0.1531;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y + 2.0 * v ) ) * 0.12245;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y + 3.0 * v ) ) * 0.0918;\\\\n\\\\t\\\\t\\\\tsum += texture2D( tDiffuse, vec2( vUv.x, vUv.y + 4.0 * v ) ) * 0.051;\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = sum;\\\\n\\\\n\\\\t\\\\t}\\\\\\\"},SG=1/256e3;class CG{constructor(t){this._renderTargetBlur=this._createRenderTarget(t),this._camera=this._createCamera(),this._blurPlane=this._createBlurPlane(),this._horizontalBlurMaterial=new F(MG),this._horizontalBlurMaterial.depthTest=!1,this._verticalBlurMaterial=new F(EG),this._verticalBlurMaterial.depthTest=!1}setSize(t,e){this._renderTargetBlur.setSize(t,e)}_createRenderTarget(t){const e=new Q(t.x,t.y);return e.texture.generateMipmaps=!1,e}_createCamera(){const t=new ot.a(-.5,.5,.5,-.5,0,1);return t.position.z=.5,t}_createBlurPlane(){const t=new L(1,1);return new B.a(t)}applyBlur(t,e,n,i){const s=Math.max(this._renderTargetBlur.width,this._renderTargetBlur.height);this._horizontalBlurMaterial.uniforms.tDiffuse.value=t.texture,this._horizontalBlurMaterial.uniforms.h.value=n*s*SG,this._blurPlane.material=this._horizontalBlurMaterial,e.setRenderTarget(this._renderTargetBlur),e.render(this._blurPlane,this._camera),this._verticalBlurMaterial.uniforms.tDiffuse.value=this._renderTargetBlur.texture,this._verticalBlurMaterial.uniforms.v.value=i*s*SG,this._blurPlane.material=this._verticalBlurMaterial,e.setRenderTarget(t),e.render(this._blurPlane,this._camera)}}var NG;!function(t){t.ON_RENDER=\\\\\\\"On Every Render\\\\\\\",t.MANUAL=\\\\\\\"Manual\\\\\\\"}(NG||(NG={}));const LG=[NG.ON_RENDER,NG.MANUAL];class OG extends(yU(ua)){constructor(){super(...arguments),this.shadow=ha.FOLDER(),this.dist=ha.FLOAT(1,{range:[0,10],rangeLocked:[!0,!1]}),this.planeSize=ha.VECTOR2([1,1]),this.shadowRes=ha.VECTOR2([256,256]),this.blur=ha.FLOAT(1,{range:[0,10],rangeLocked:[!0,!1]}),this.tblur2=ha.BOOLEAN(1),this.blur2=ha.FLOAT(1,{range:[0,10],rangeLocked:[!0,!1],visibleIf:{tblur2:1}}),this.darkness=ha.FLOAT(1),this.opacity=ha.FLOAT(1),this.showHelper=ha.BOOLEAN(0),this.updateMode=ha.INTEGER(LG.indexOf(NG.ON_RENDER),{callback:t=>{IG.PARAM_CALLBACK_update_updateMode(t)},menu:{entries:LG.map(((t,e)=>({name:t,value:e})))}}),this.update=ha.BUTTON(null,{callback:t=>{IG.PARAM_CALLBACK_updateManual(t)},visibleIf:{updateMode:LG.indexOf(NG.MANUAL)}}),this.scene=ha.FOLDER(),this.include=ha.STRING(\\\\\\\"\\\\\\\"),this.exclude=ha.STRING(\\\\\\\"\\\\\\\"),this.updateObjectsList=ha.BUTTON(null,{callback:t=>{IG.PARAM_CALLBACK_updateObjectsList(t)}}),this.printResolveObjectsList=ha.BUTTON(null,{callback:t=>{IG.PARAM_CALLBACK_printResolveObjectsList(t)}})}}const PG=new OG,RG=new d.a(256,256);class IG extends oU{constructor(){super(...arguments),this.paramsConfig=PG,this.hierarchyController=new wU(this),this.flags=new Di(this),this._renderTarget=this._createRenderTarget(RG),this._coreRenderBlur=this._createCoreRenderBlur(RG),this._includedObjects=[],this._includedAncestors=[],this._excludedObjects=[],this.transformController=new bU(this),this._darknessUniform={value:1},this._emptyOnBeforeRender=()=>{},this._emptyRenderHook=()=>{},this._on_object_before_render_bound=this._update.bind(this),this._initialVisibilityState=new WeakMap}static type(){return\\\\\\\"contactShadow\\\\\\\"}_createRenderTarget(t){const e=new Q(t.x,t.y);return e.texture.generateMipmaps=!1,e}_createCoreRenderBlur(t){return new CG(t)}createObject(){const t=new Fn.a;this._shadowGroup=new Fn.a,t.add(this._shadowGroup),this._shadowGroup.name=\\\\\\\"shadowGroup\\\\\\\";const e=new L(1,1).rotateX(-Math.PI/2),n=e.getAttribute(\\\\\\\"uv\\\\\\\").array;for(let t of[1,3,5,7])n[t]=1-n[t];return this._planeMaterial=new lt.a({map:this._renderTarget.texture,opacity:1,transparent:!0,depthWrite:!1}),this._plane=new B.a(e,this._planeMaterial),this._plane.renderOrder=1,this._plane.matrixAutoUpdate=!1,this._shadowGroup.add(this._plane),this._createDepthCamera(this._shadowGroup),this._createMaterials(),t}initializeNode(){this.hierarchyController.initializeNode(),this.transformController.initializeNode(),this._updateShadowGroupVisibility(),this._updateHelperVisibility(),this.flags.display.onUpdate((()=>{this._updateShadowGroupVisibility(),this._updateHelperVisibility()}))}async cook(){this.transformController.update(),this._updateRenderHook(),this._updateHelperVisibility(),this._updateObjectsList(),this._planeMaterial&&(this._planeMaterial.opacity=this.pv.opacity),this._darknessUniform.value=this.pv.darkness,this._plane&&this._shadowCamera&&this._helper&&(this._plane.scale.x=this.pv.planeSize.x,this._plane.scale.z=this.pv.planeSize.y,this._plane.updateMatrix(),this._shadowCamera.left=-this.pv.planeSize.x/2,this._shadowCamera.right=this.pv.planeSize.x/2,this._shadowCamera.bottom=-this.pv.planeSize.y/2,this._shadowCamera.top=this.pv.planeSize.y/2,this._shadowCamera.far=this.pv.dist,this._shadowCamera.updateProjectionMatrix(),this._helper.update()),this._renderTarget.width==this.pv.shadowRes.x&&this._renderTarget.height==this.pv.shadowRes.y||this._planeMaterial&&(this._renderTarget=this._createRenderTarget(this.pv.shadowRes),this._coreRenderBlur=this._createCoreRenderBlur(this.pv.shadowRes),this._planeMaterial.map=this._renderTarget.texture),this.cookController.endCook()}_createDepthCamera(t){this._shadowCamera=new ot.a(-.5,.5,.5,-.5,0,1),this._shadowCamera.rotation.x=Math.PI/2,t.add(this._shadowCamera),this._helper=new FU(this._shadowCamera),this._helper.visible=!1,this._shadowCamera.add(this._helper)}_createMaterials(){this._depthMaterial=new Sn,this._depthMaterial.onBeforeCompile=t=>{t.uniforms.darkness=this._darknessUniform,t.fragmentShader=`\\\\n\\\\t\\\\t\\\\tuniform float darkness;\\\\n\\\\t\\\\t\\\\t${t.fragmentShader.replace(\\\\\\\"gl_FragColor = vec4( vec3( 1.0 - fragCoordZ ), opacity );\\\\\\\",\\\\\\\"gl_FragColor = vec4( vec3( 0.0 ), ( 1.0 - fragCoordZ ) * darkness );\\\\\\\")}\\\\n\\\\t\\\\t`},this._depthMaterial.depthTest=!1,this._depthMaterial.depthWrite=!1}_renderShadow(t,e){if(!this._helper)return;if(!this._depthMaterial)return;if(!this._shadowCamera)return;if(!this._helper)return;if(!this._plane)return;const n=this._plane.onBeforeRender,i=e.background,s=this._helper.visible;e.background=null,this._plane.onBeforeRender=this._emptyOnBeforeRender,this._helper.visible=!1,e.overrideMaterial=this._depthMaterial,this._initVisibility(e),t.setRenderTarget(this._renderTarget),t.render(e,this._shadowCamera),this._coreRenderBlur.applyBlur(this._renderTarget,t,this.pv.blur,this.pv.blur),this.pv.tblur2&&this._coreRenderBlur.applyBlur(this._renderTarget,t,this.pv.blur2,this.pv.blur2),this._restoreVisibility(e),e.overrideMaterial=null,this._helper.visible=s,t.setRenderTarget(null),e.background=i,this._plane.onBeforeRender=n}_updateShadowGroupVisibility(){this._shadowGroup&&(this.flags.display.active()?this._shadowGroup.visible=!0:this._shadowGroup.visible=!1)}_updateHelperVisibility(){this._helper&&(this.flags.display.active()&&this.pv.showHelper?this._helper.visible=!0:this._helper.visible=!1)}_updateRenderHook(){const t=LG[this.pv.updateMode];switch(t){case NG.ON_RENDER:return this._addRenderHook();case NG.MANUAL:return this._removeRenderHook()}os.unreachable(t)}_addRenderHook(){this._plane&&this._plane.onBeforeRender!=this._on_object_before_render_bound&&(this._plane.onBeforeRender=this._on_object_before_render_bound)}_removeRenderHook(){this._plane&&this._plane.onBeforeRender!=this._emptyRenderHook&&(this._plane.onBeforeRender=this._emptyRenderHook)}_update(t,e,n,i,s,r){t&&e?this._renderShadow(t,e):console.log(\\\\\\\"no renderer or scene\\\\\\\")}_updateManual(){const t=li.renderersController.firstRenderer();if(!t)return void console.log(\\\\\\\"no renderer found\\\\\\\");const e=this.scene().threejsScene();this._renderShadow(t,e)}static PARAM_CALLBACK_update_updateMode(t){t._updateRenderHook()}static PARAM_CALLBACK_updateManual(t){t._updateManual()}static PARAM_CALLBACK_updateObjectsList(t){t._updateObjectsList()}_updateObjectsList(){\\\\\\\"\\\\\\\"!=this.pv.include?this._includedObjects=this.scene().objectsByMask(this.pv.include):this._includedObjects=[];const t=new Map;for(let e of this._includedObjects)e.traverseAncestors((e=>{t.set(e.uuid,e)}));this._includedAncestors=[],t.forEach(((t,e)=>{this._includedAncestors.push(t)})),\\\\\\\"\\\\\\\"!=this.pv.exclude?this._excludedObjects=this.scene().objectsByMask(this.pv.exclude):this._excludedObjects=[]}static PARAM_CALLBACK_printResolveObjectsList(t){t._printResolveObjectsList()}_printResolveObjectsList(){console.log(\\\\\\\"included objects:\\\\\\\"),console.log(this._includedObjects),console.log(\\\\\\\"included parents:\\\\\\\"),console.log(this._includedAncestors),console.log(\\\\\\\"excluded objects:\\\\\\\"),console.log(this._excludedObjects)}_initVisibility(t){this._includedObjects.length>0?t.traverse((t=>{this._initialVisibilityState.set(t,t.visible),t.visible=!1})):(this._storeObjectsVisibility(this._includedObjects),this._storeObjectsVisibility(this._includedAncestors),this._storeObjectsVisibility(this._excludedObjects)),this._setObjectsVisibility(this._includedObjects,!0),this._setObjectsVisibility(this._includedAncestors,!0),this._setObjectsVisibility(this._excludedObjects,!1)}_storeObjectsVisibility(t){for(let e of t)this._initialVisibilityState.set(e,e.visible)}_setObjectsVisibility(t,e){for(let n of t)n.visible=e}_restoreVisibility(t){this._includedObjects.length>0?t.traverse((t=>{const e=this._initialVisibilityState.get(t);e&&(t.visible=e)})):(this._restoreObjectsVisibility(this._includedObjects),this._restoreObjectsVisibility(this._includedAncestors),this._restoreObjectsVisibility(this._excludedObjects))}_restoreObjectsVisibility(t){for(let e of t){const t=this._initialVisibilityState.get(e);t&&(e.visible=t)}}}const FG=\\\\\\\"display\\\\\\\";class DG{constructor(t){this.node=t,this._children_uuids_dict=new Map,this._children_length=0,this._sop_group=this._create_sop_group()}_create_sop_group(){const t=new Fn.a;return t.matrixAutoUpdate=!1,t}sopGroup(){return this._sop_group}set_sop_group_name(){this._sop_group.name=`${this.node.name()}:sop_group`}displayNodeControllerCallbacks(){return{onDisplayNodeRemove:()=>{this.remove_children()},onDisplayNodeSet:()=>{setTimeout((()=>{this.request_display_node_container()}),0)},onDisplayNodeUpdate:()=>{this.request_display_node_container()}}}initializeNode(){var t;this.node.object.add(this.sopGroup()),this.node.nameController.add_post_set_fullPath_hook(this.set_sop_group_name.bind(this)),this._create_sop_group();const e=null===(t=this.node.flags)||void 0===t?void 0:t.display;e&&e.onUpdate((()=>{this._updateSopGroupHierarchy(),e.active()&&this.request_display_node_container()}))}_updateSopGroupHierarchy(){var t;if(null===(t=this.node.flags)||void 0===t?void 0:t.display){const t=this.sopGroup();this.usedInScene()?(t.visible=!0,this.node.object.add(t),t.updateMatrix()):(t.visible=!1,this.node.object.remove(t))}}usedInScene(){var t,e;const n=this.node.params.has(FG),i=this.node.params.boolean(FG),s=this.node.usedInScene(),r=(null===(e=null===(t=this.node.flags)||void 0===t?void 0:t.display)||void 0===e?void 0:e.active())||!1;return s&&r&&(!n||i)}async request_display_node_container(){this.node.scene().loadingController.loaded()&&this.usedInScene()&&await this._set_content_under_sop_group()}remove_children(){if(0==this._sop_group.children.length)return;let t;for(;t=this._sop_group.children[0];)this._sop_group.remove(t);this._children_uuids_dict.clear(),this._children_length=0}async _set_content_under_sop_group(){var t;const e=this.node.displayNodeController.displayNode();if(e&&(null===(t=e.parent())||void 0===t?void 0:t.graphNodeId())==this.node.graphNodeId()){const t=(await e.compute()).coreContent();if(t){const e=t.objects();let n=e.length!=this._children_length;if(!n)for(let t of e)this._children_uuids_dict.get(t.uuid)||(n=!0);if(n){this.remove_children();for(let t of e)this._sop_group.add(t),t.updateMatrix(),this._children_uuids_dict.set(t.uuid,!0);this._children_length=e.length}return}}this.remove_children()}}class BG extends(yU(ua)){constructor(){super(...arguments),this.display=ha.BOOLEAN(1),this.renderOrder=ha.INTEGER(0,{range:[0,10],rangeLocked:[!0,!1]})}}const zG=new BG;class kG extends oU{constructor(){super(...arguments),this.paramsConfig=zG,this.hierarchyController=new wU(this),this.transformController=new bU(this),this.flags=new Di(this),this.childrenDisplayController=new DG(this),this.displayNodeController=new Fm(this,this.childrenDisplayController.displayNodeControllerCallbacks()),this._children_controller_context=ts.SOP,this._onChildAddBound=this._onChildAdd.bind(this)}static type(){return Ig.GEO}createObject(){const t=new Fn.a;return t.matrixAutoUpdate=!1,t}initializeNode(){this.lifecycle.add_on_child_add_hook(this._onChildAddBound),this.hierarchyController.initializeNode(),this.transformController.initializeNode(),this.childrenDisplayController.initializeNode()}isDisplayNodeCooking(){if(this.flags.display.active()){const t=this.displayNodeController.displayNode();return!!t&&t.isDirty()}return!1}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}_onChildAdd(t){var e,n;this.scene().loadingController.loaded()&&1==this.children().length&&(null===(n=null===(e=t.flags)||void 0===e?void 0:e.display)||void 0===n||n.set(!0))}cook(){this.transformController.update(),this.object.visible=this.pv.display,this.object.renderOrder=this.pv.renderOrder,this.cookController.endCook()}}class UG extends(yU(ua)){}const GG=new UG;class VG extends oU{constructor(){super(...arguments),this.paramsConfig=GG,this.hierarchyController=new wU(this),this.transformController=new bU(this),this.flags=new Di(this),this._helper=new xG(1)}static type(){return\\\\\\\"null\\\\\\\"}createObject(){const t=new Fn.a;return t.matrixAutoUpdate=!1,t}initializeNode(){this.hierarchyController.initializeNode(),this.transformController.initializeNode(),this._updateHelperHierarchy(),this._helper.matrixAutoUpdate=!1,this.flags.display.onUpdate((()=>{this._updateHelperHierarchy()}))}_updateHelperHierarchy(){this.flags.display.active()?(this.object.add(this._helper),this._helper.updateMatrix()):this.object.remove(this._helper)}cook(){this.transformController.update(),this.cookController.endCook()}}const HG=new class extends ua{constructor(){super(...arguments),this.center=ha.VECTOR3([0,0,0]),this.longitude=ha.FLOAT(0,{range:[0,360]}),this.latitude=ha.FLOAT(0,{range:[-180,180]}),this.depth=ha.FLOAT(1,{range:[0,10]})}},jG=\\\\\\\"_cook_main_without_inputs_when_dirty\\\\\\\",WG=new p.a(0,1,0),qG=new p.a(-1,0,0);class XG extends oU{constructor(){super(...arguments),this.paramsConfig=HG,this.hierarchyController=new wU(this),this.flags=new Di(this),this._helper=new xG(1),this._cook_main_without_inputs_when_dirty_bound=this._cook_main_without_inputs_when_dirty.bind(this),this._centerMatrix=new A.a,this._longitudeMatrix=new A.a,this._latitudeMatrix=new A.a,this._depthMatrix=new A.a,this._fullMatrix=new A.a,this._decomposed={t:new p.a,q:new hh.a,s:new p.a}}static type(){return\\\\\\\"polarTransform\\\\\\\"}createObject(){const t=new Fn.a;return t.matrixAutoUpdate=!1,t}initializeNode(){this.hierarchyController.initializeNode(),this.dirtyController.hasHook(jG)||this.dirtyController.addPostDirtyHook(jG,this._cook_main_without_inputs_when_dirty_bound),this._updateHelperHierarchy(),this._helper.matrixAutoUpdate=!1,this.flags.display.onUpdate((()=>{this._updateHelperHierarchy()}))}_updateHelperHierarchy(){this.flags.display.active()?(this.object.add(this._helper),this._helper.updateMatrix()):this.object.remove(this._helper)}async _cook_main_without_inputs_when_dirty(){await this.cookController.cookMainWithoutInputs()}cook(){const t=this.object;this._centerMatrix.identity(),this._longitudeMatrix.identity(),this._latitudeMatrix.identity(),this._depthMatrix.identity(),this._centerMatrix.makeTranslation(this.pv.center.x,this.pv.center.y,this.pv.center.z),this._longitudeMatrix.makeRotationAxis(WG,Object(On.e)(this.pv.longitude)),this._latitudeMatrix.makeRotationAxis(qG,Object(On.e)(this.pv.latitude)),this._depthMatrix.makeTranslation(0,0,this.pv.depth),this._fullMatrix.copy(this._centerMatrix).multiply(this._longitudeMatrix).multiply(this._latitudeMatrix).multiply(this._depthMatrix),this._fullMatrix.decompose(this._decomposed.t,this._decomposed.q,this._decomposed.s),t.position.copy(this._decomposed.t),t.quaternion.copy(this._decomposed.q),t.scale.copy(this._decomposed.s),t.updateMatrix(),this.cookController.endCook()}}class YG{constructor(t){this._scene=t,this._data={}}data(t){this._scene.nodesController.reset_node_context_signatures();const e=nV.dispatch_node(this._scene.root()),n=e.data(),i=e.ui_data();return this._data={properties:{frame:this._scene.frame()||Nl.START_FRAME,maxFrame:this._scene.maxFrame(),maxFrameLocked:this._scene.timeController.maxFrameLocked(),realtimeState:this._scene.timeController.realtimeState(),mainCameraNodePath:this._scene.camerasController.mainCameraNodePath(),versions:t},root:n,ui:i},this._data}static sanitize_string(t){return t=t.replace(/'/g,\\\\\\\"'\\\\\\\"),t=ss.escapeLineBreaks(t)}}class $G{constructor(t){this._node=t}data(t={}){var e,n,i,s,r,o,a;this.is_root()||this._node.scene().nodesController.register_node_context_signature(this._node),this._data={type:this._node.type()};const l=this.nodes_data(t);Object.keys(l).length>0&&(this._data.nodes=l);const c=this.params_data();if(Object.keys(c).length>0&&(this._data.params=c),!this.is_root()){this._node.io.inputs.maxInputsCountOverriden()&&(this._data.maxInputsCount=this._node.io.inputs.maxInputsCount());const t=this.inputs_data();t.length>0&&(this._data.inputs=t);const e=this.connection_points_data();e&&(this._data.connection_points=e)}if(this._node.flags){const t={};(this._node.flags.hasBypass()||this._node.flags.hasDisplay()||this._node.flags.hasOptimize())&&(this._node.flags.hasBypass()&&(null===(e=this._node.flags.bypass)||void 0===e?void 0:e.active())&&(t.bypass=this._node.flags.bypass.active()),this._node.flags.hasDisplay()&&(!(null===(n=this._node.flags.display)||void 0===n?void 0:n.active())&&(null===(i=this._node.parent())||void 0===i?void 0:i.displayNodeController)||(t.display=null===(s=this._node.flags.display)||void 0===s?void 0:s.active())),this._node.flags.hasOptimize()&&(null===(r=this._node.flags.optimize)||void 0===r?void 0:r.active())&&(t.optimize=null===(o=this._node.flags.optimize)||void 0===o?void 0:o.active())),Object.keys(t).length>0&&(this._data.flags=t)}if(this._node.childrenAllowed()){const t=null===(a=this._node.childrenController)||void 0===a?void 0:a.selection;if(t&&this._node.children().length>0){const e=[],n={};for(let e of t.nodes())n[e.graphNodeId()]=!0;for(let t of this._node.children())t.graphNodeId()in n&&e.push(t);const i=e.map((t=>t.name()));i.length>0&&(this._data.selection=i)}}if(this._node.io.inputs.overrideClonedStateAllowed()){const t=this._node.io.inputs.clonedStateOverriden();t&&(this._data.cloned_state_overriden=t)}if(this._node.persisted_config){const t=this._node.persisted_config.toJSON();t&&(this._data.persisted_config=t)}return this.add_custom(),this._data}ui_data(t={}){const e=this.ui_data_without_children(),n=this._node.children();return n.length>0&&(e.nodes={},n.forEach((n=>{const i=nV.dispatch_node(n);e.nodes[n.name()]=i.ui_data(t)}))),e}ui_data_without_children(){const t={};if(!this.is_root()){const e=this._node.uiData;t.pos=e.position().toArray();const n=e.comment();n&&(t.comment=YG.sanitize_string(n))}return t}is_root(){return null===this._node.parent()&&this._node.graphNodeId()==this._node.root().graphNodeId()}inputs_data(){const t=[];return this._node.io.inputs.inputs().forEach(((e,n)=>{var i;if(e){const s=this._node.io.connections.inputConnection(n);if(this._node.io.inputs.hasNamedInputs()){const r=s.output_index,o=null===(i=e.io.outputs.namedOutputConnectionPoints()[r])||void 0===i?void 0:i.name();o&&(t[n]={index:n,node:e.name(),output:o})}else t[n]=e.name()}})),t}connection_points_data(){if(this._node.io.has_connection_points_controller&&this._node.io.connection_points.initialized()&&(this._node.io.inputs.hasNamedInputs()||this._node.io.outputs.hasNamedOutputs())){const t={};if(this._node.io.inputs.hasNamedInputs()){t.in=[];for(let e of this._node.io.inputs.namedInputConnectionPoints())e&&t.in.push(e.toJSON())}if(this._node.io.outputs.hasNamedOutputs()){t.out=[];for(let e of this._node.io.outputs.namedOutputConnectionPoints())e&&t.out.push(e.toJSON())}return t}}params_data(){const t={};for(let e of this._node.params.names){const n=this._node.params.get(e);if(n&&!n.parent_param){const e=nV.dispatch_param(n);if(e.required()){const i=e.data();t[n.name()]=i}}}return t}nodes_data(t={}){const e={};for(let n of this._node.children()){const i=nV.dispatch_node(n);e[n.name()]=i.data(t)}return e}add_custom(){}}class JG{constructor(t){this._param=t,this._complex_data={}}required(){const t=this._param.options.isSpare()&&!this._param.parent_param,e=!this._param.isDefault();return t||e||this._param.options.hasOptionsOverridden()}data(){if(this._param.parent_param)throw console.warn(\\\\\\\"no component should be saved\\\\\\\"),\\\\\\\"no component should be saved\\\\\\\";return this._require_data_complex()?this._data_complex():this._data_simple()}_data_simple(){return this._param.rawInputSerialized()}_data_complex(){if(this._complex_data={},this._param.options.isSpare()&&!this._param.parent_param&&(this._complex_data.type=this._param.type(),this._complex_data.default_value=this._param.defaultValueSerialized(),this._complex_data.options=this._param.options.current()),this._param.isDefault()||(this._complex_data.raw_input=this._param.rawInputSerialized()),this._param.options.hasOptionsOverridden()){const t={},e=this._param.options.overriddenOptions();for(let n of Object.keys(e)){const i=e[n];m.isString(i)||m.isNumber(i)?t[n]=i:t[n]=JSON.stringify(i)}this._complex_data.overriden_options=t}return this._complex_data}_require_data_complex(){return!!this._param.options.isSpare()||!!this._param.options.hasOptionsOverridden()}add_main(){}}class ZG extends JG{add_main(){if(!this._require_data_complex())return this._param.rawInputSerialized();this._complex_data.raw_input=this._param.rawInputSerialized()}}class QG extends JG{add_main(){let t=this._param.rawInput();if(t=YG.sanitize_string(t),!this._require_data_complex())return t;this._complex_data.raw_input=t}}class KG extends JG{add_main(){let t=this._param.rawInput();if(t=YG.sanitize_string(t),!this._require_data_complex())return t;this._complex_data.raw_input=t}}class tV extends JG{add_main(){if(!this._require_data_complex())return this._param.rawInputSerialized();this._complex_data.raw_input=this._param.rawInputSerialized()}}class eV extends $G{nodes_data(t={}){return t.showPolyNodesData?super.nodes_data(t):{}}ui_data(t={}){return t.showPolyNodesData?super.ui_data(t):this.ui_data_without_children()}}class nV{static dispatch_node(t){return t.polyNodeController?new eV(t):new $G(t)}static dispatch_param(t){return t instanceof ro?new ZG(t):t instanceof fo?new QG(t):t instanceof Mo?new KG(t):t instanceof Ao?new tV(t):new JG(t)}}class iV{constructor(){this._objects=[],this._objects_with_geo=[],this.touch()}timestamp(){return this._timestamp}touch(){const t=li.performance.performanceManager();this._timestamp=t.now(),this.reset()}reset(){this._bounding_box=void 0,this._core_geometries=void 0,this._core_objects=void 0}clone(){const t=new iV;if(this._objects){const e=[];for(let t of this._objects)e.push(br.clone(t));t.setObjects(e)}return t}setObjects(t){this._objects=t,this._objects_with_geo=t.filter((t=>null!=t.geometry)),this.touch()}objects(){return this._objects}objectsWithGeo(){return this._objects_with_geo}coreObjects(){return this._core_objects=this._core_objects||this._create_core_objects()}_create_core_objects(){return this._objects?this._objects.map(((t,e)=>new br(t,e))):[]}objectsData(){return this._objects?this._objects.map((t=>this._objectData(t))):[]}_objectData(t){let e=0;return t.geometry&&(e=fr.pointsCount(t.geometry)),{type:Os(t.constructor),name:t.name,children_count:t.children.length,points_count:e}}geometries(){const t=[];for(let e of this.coreObjects()){const n=e.object().geometry;n&&t.push(n)}return t}coreGeometries(){return this._core_geometries=this._core_geometries||this._createCoreGeometries()}_createCoreGeometries(){const t=[];for(let e of this.geometries())t.push(new fr(e));return t}static geometryFromObject(t){return t.isMesh||t.isLine||t.isPoints?t.geometry:null}faces(){const t=[];for(let e of this.objectsWithGeo())if(e.geometry){const n=new fr(e.geometry).faces();for(let i of n)i.applyMatrix4(e.matrix),t.push(i)}return t}points(){return this.coreGeometries().map((t=>t.points())).flat()}pointsCount(){return f.sum(this.coreGeometries().map((t=>t.pointsCount())))}totalPointsCount(){if(this._objects){let t=0;for(let e of this._objects)e.traverse((e=>{const n=e.geometry;n&&(t+=fr.pointsCount(n))}));return t}return 0}pointsFromGroup(t){if(t){const e=ss.indices(t),n=this.points();return f.compact(e.map((t=>n[t])))}return this.points()}static _fromObjects(t){const e=new iV;return e.setObjects(t),e}objectsFromGroup(t){return this.coreObjectsFromGroup(t).map((t=>t.object()))}coreObjectsFromGroup(t){if(\\\\\\\"\\\\\\\"!==(t=t.trim())){const e=parseInt(t);return m.isNaN(e)?this.coreObjects().filter((e=>ss.matchMask(t,e.name()))):f.compact([this.coreObjects()[e]])}return this.coreObjects()}boundingBox(t=!1){return this._bounding_box=t?this._computeBoundingBox():this._bounding_box||this._computeBoundingBox()}center(){const t=new p.a;return this.boundingBox().getCenter(t),t}size(){const t=new p.a;return this.boundingBox().getSize(t),t}_computeBoundingBox(){let t;if(this._objects)for(let e of this._objects){const n=e.geometry;n&&(n.computeBoundingBox(),t?t.expandByObject(e):n.boundingBox&&(t=n.boundingBox.clone()))}return t=t||new Cy.a(new p.a(-1,-1,-1),new p.a(1,1,1)),t}computeVertexNormals(){for(let t of this.coreObjects())t.computeVertexNormals()}hasAttrib(t){let e;return null!=(e=this.coreGeometries()[0])&&e.hasAttrib(t)}attribType(t){const e=this.coreGeometries()[0];return null!=e?e.attribType(t):null}objectAttribType(t){const e=this.coreObjects()[0];return null!=e?e.attribType(t):null}renameAttrib(t,e,n){switch(n){case js.ATTRIB_CLASS.VERTEX:if(this.hasAttrib(t)&&this._objects)for(let n of this._objects)n.traverse((n=>{const i=iV.geometryFromObject(n);if(i){new fr(i).renameAttrib(t,e)}}));break;case js.ATTRIB_CLASS.OBJECT:if(this.hasAttrib(t)&&this._objects)for(let n of this._objects)n.traverse((n=>{new br(n,0).renameAttrib(t,e)}))}}attribNames(){let t;return null!=(t=this.coreGeometries()[0])?t.attribNames():[]}objectAttribNames(){let t;return null!=(t=this.coreObjects()[0])?t.attribNames():[]}attribNamesMatchingMask(t){const e=ss.attribNames(t),n=[];for(let t of this.attribNames())for(let i of e)if(ss.matchMask(t,i))n.push(t);else{t==Xs.remapName(i)&&n.push(t)}return f.uniq(n)}attribSizes(){let t;return null!=(t=this.coreGeometries()[0])?t.attribSizes():{}}objectAttribSizes(){let t;return null!=(t=this.coreObjects()[0])?t.attribSizes():{}}attribSize(t){let e;return null!=(e=this.coreGeometries()[0])?e.attribSize(t):0}addNumericVertexAttrib(t,e,n){null==n&&(n=Xs.default_value(e));for(let i of this.coreGeometries())i.addNumericAttrib(t,e,n)}static clone(t){const e=new Fn.a;return t.children.forEach((t=>{const n=br.clone(t);e.add(n)})),e}}class sV extends zl{static context(){return ts.SOP}cook(t,e){}createCoreGroupFromObjects(t){const e=new iV;return e.setObjects(t),e}createCoreGroupFromGeometry(t,e=Ns.MESH){const n=sV.createObject(t,e);return this.createCoreGroupFromObjects([n])}createObject(t,e,n){return sV.createObject(t,e,n)}static createObject(t,e,n){this.createIndexIfNone(t);const i=new(0,Ls[e])(t,n=n||js.MATERIALS[e].clone());return i.castShadow=!0,i.receiveShadow=!0,i.frustumCulled=!1,i.matrixAutoUpdate=!1,i}createIndexIfNone(t){sV.createIndexIfNone(t)}static createIndexIfNone(t){pr.createIndexIfNone(t)}}var rV;!function(t){t.FROM_SET_CORE_GROUP=\\\\\\\"from set_core_group\\\\\\\",t.FROM_SET_GROUP=\\\\\\\"from set_group\\\\\\\",t.FROM_SET_OBJECTS=\\\\\\\"from set_objects\\\\\\\",t.FROM_SET_OBJECT=\\\\\\\"from set_object\\\\\\\",t.FROM_SET_GEOMETRIES=\\\\\\\"from set_geometries\\\\\\\",t.FROM_SET_GEOMETRY=\\\\\\\"from set_geometry\\\\\\\"}(rV||(rV={}));const oV=\\\\\\\"input geometry\\\\\\\",aV=[oV,oV,oV,oV];class lV extends aa{constructor(){super(...arguments),this.flags=new Ui(this)}static context(){return ts.SOP}static displayedInputNames(){return aV}initializeBaseNode(){this.flags.display.set(!1),this.flags.display.onUpdate((()=>{if(this.flags.display.active()){const t=this.parent();t&&t.displayNodeController&&t.displayNodeController.setDisplayNode(this)}})),this.io.outputs.setHasOneOutput()}setCoreGroup(t){this._setContainer(t,rV.FROM_SET_CORE_GROUP)}setObject(t){this._setContainerObjects([t],rV.FROM_SET_OBJECT)}setObjects(t){this._setContainerObjects(t,rV.FROM_SET_OBJECTS)}setGeometry(t,e=Ns.MESH){const n=this.createObject(t,e);this._setContainerObjects([n],rV.FROM_SET_GEOMETRY)}setGeometries(t,e=Ns.MESH){const n=[];let i;for(let s of t)i=this.createObject(s,e),n.push(i);this._setContainerObjects(n,rV.FROM_SET_GEOMETRIES)}_setContainerObjects(t,e){const n=this.containerController.container().coreContent()||new iV;n.setObjects(t),n.touch(),this._setContainer(n)}static createObject(t,e,n){return sV.createObject(t,e,n)}createObject(t,e,n){return lV.createObject(t,e,n)}static createIndexIfNone(t){sV.createIndexIfNone(t)}_createIndexIfNone(t){lV.createIndexIfNone(t)}}const cV=new class extends ua{};class hV extends lV{constructor(){super(...arguments),this.paramsConfig=cV}static type(){return ns.OUTPUT}initializeNode(){this.io.inputs.setCount(1),this.io.outputs.setHasNoOutput(),this.io.inputs.initInputsClonedState(Ki.NEVER)}cook(t){this.setCoreGroup(t[0])}}class uV extends lV{constructor(){super(...arguments),this.childrenDisplayController=new pV(this),this.displayNodeController=new Fm(this,this.childrenDisplayController.displayNodeControllerCallbacks()),this._children_controller_context=ts.SOP}initializeBaseNode(){super.initializeBaseNode(),this.childrenDisplayController.initializeNode(),this.cookController.disallowInputsEvaluation()}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}async cook(t){const e=this.childrenDisplayController.output_node();if(e){const t=(await e.compute()).coreContent();t?this.setCoreGroup(t):e.states.error.active()?this.states.error.set(e.states.error.message()):this.setObjects([])}else this.states.error.set(\\\\\\\"no output node found inside subnet\\\\\\\")}}const dV={dependsOnDisplayNode:!0};class pV{constructor(t,e=dV){this.node=t,this.options=e,this._output_node_needs_update=!0}dispose(){var t;null===(t=this._graph_node)||void 0===t||t.dispose()}displayNodeControllerCallbacks(){return{onDisplayNodeRemove:()=>{this.node.setDirty()},onDisplayNodeSet:()=>{this.node.setDirty()},onDisplayNodeUpdate:()=>{this.node.setDirty()}}}output_node(){return this._output_node_needs_update&&this._update_output_node(),this._output_node}initializeNode(){var t;const e=null===(t=this.node.flags)||void 0===t?void 0:t.display;e&&e.onUpdate((()=>{e.active()&&this.node.setDirty()})),this.node.lifecycle.add_on_child_add_hook((()=>{this._output_node_needs_update=!0,this.node.setDirty()})),this.node.lifecycle.add_on_child_remove_hook((()=>{this._output_node_needs_update=!0,this.node.setDirty()}))}_update_output_node(){const t=this.node.nodesByType(hV.type())[0];null!=this._output_node&&null!=t&&this._output_node.graphNodeId()==t.graphNodeId()||(this._graph_node&&this._output_node&&this._graph_node.removeGraphInput(this._output_node),this._output_node=t,this._output_node&&this.options.dependsOnDisplayNode&&(this._graph_node=this._graph_node||this._create_graph_node(),this._graph_node.addGraphInput(this._output_node)))}_create_graph_node(){const t=new Mi(this.node.scene(),\\\\\\\"subnetChildrenDisplayController\\\\\\\");return t.addPostDirtyHook(\\\\\\\"subnetChildrenDisplayController\\\\\\\",(()=>{this.node.setDirty()})),t}}function _V(t,e){const n=new class extends ua{constructor(){super(...arguments),this.template=ha.OPERATOR_PATH(\\\\\\\"../template\\\\\\\"),this.debug=ha.BUTTON(null,{callback:t=>{i.PARAM_CALLBACK_debug(t)}})}};class i extends uV{constructor(){super(...arguments),this.paramsConfig=n,this.polyNodeController=new gV(this,e)}static type(){return t}static PARAM_CALLBACK_debug(t){t._debug()}_debug(){this.polyNodeController.debug(this.p.template)}}return i}const mV=_V(\\\\\\\"poly\\\\\\\",{nodeContext:ts.SOP,inputs:[0,4]});class fV extends mV{}class gV{constructor(t,e){this.node=t,this._definition=e}initializeNode(){this.init_inputs(),this.node.params.onParamsCreated(\\\\\\\"poly_node_init\\\\\\\",(()=>{this.create_params_from_definition()})),this.node.lifecycle.add_on_create_hook((()=>{this.create_params_from_definition(),this.createChildNodesFromDefinition()}))}init_inputs(){const t=this._definition.inputs;t&&this.node.io.inputs.setCount(t[0],t[1])}create_params_from_definition(){const t=this._definition.params;if(t){for(let e of t)e.options=e.options||{},e.options.spare=!0;this.node.params.updateParams({toAdd:t})}}createChildNodesFromDefinition(){const t=this._definition.nodes;if(!t)return;const e=this.node.scene().loadingController.loaded();e&&this.node.scene().loadingController.markAsLoading();const n=new Jl({}),i=new Vl(this.node);i.create_nodes(n,t);const s=this._definition.ui;s&&i.process_nodes_ui_data(n,s),e&&this.node.scene().loadingController.markAsLoaded()}debug(t){const e=t.found_node();if(e){const t=nV.dispatch_node(e),n=t.data({showPolyNodesData:!0}),i=t.ui_data({showPolyNodesData:!0}),s={nodeContext:e.context(),inputs:[0,0],params:[],nodes:n.nodes,ui:i.nodes};console.log(JSON.stringify(s))}}static createNodeClass(t,e,n){switch(e){case ts.SOP:return _V(t,n);case ts.OBJ:return vV(t,n)}}}function vV(t,e){const n=new class extends ua{constructor(){super(...arguments),this.display=ha.BOOLEAN(1),this.template=ha.OPERATOR_PATH(\\\\\\\"../template\\\\\\\"),this.debug=ha.BUTTON(null,{callback:t=>{i.PARAM_CALLBACK_debug(t)}})}};class i extends oU{constructor(){super(...arguments),this.paramsConfig=n,this.hierarchyController=new wU(this),this.flags=new Di(this),this.childrenDisplayController=new DG(this),this.displayNodeController=new Fm(this,this.childrenDisplayController.displayNodeControllerCallbacks()),this._children_controller_context=ts.SOP,this.polyNodeController=new gV(this,e)}static type(){return t}createObject(){const t=new Fn.a;return t.matrixAutoUpdate=!1,t}initializeNode(){this.hierarchyController.initializeNode(),this.childrenDisplayController.initializeNode()}isDisplayNodeCooking(){if(this.flags.display.active()){const t=this.displayNodeController.displayNode();return!!t&&t.isDirty()}return!1}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}cook(){this.object.visible=this.pv.display,this.cookController.endCook()}static PARAM_CALLBACK_debug(t){t._debug()}_debug(){this.polyNodeController.debug(this.p.template)}}return i}const yV=vV(\\\\\\\"poly\\\\\\\",{nodeContext:ts.OBJ});class xV extends yV{}class bV extends K.a{constructor(t){super(),this.type=\\\\\\\"Audio\\\\\\\",this.listener=t,this.context=t.context,this.gain=this.context.createGain(),this.gain.connect(t.getInput()),this.autoplay=!1,this.buffer=null,this.detune=0,this.loop=!1,this.loopStart=0,this.loopEnd=0,this.offset=0,this.duration=void 0,this.playbackRate=1,this.isPlaying=!1,this.hasPlaybackControl=!0,this.source=null,this.sourceType=\\\\\\\"empty\\\\\\\",this._startedAt=0,this._progress=0,this._connected=!1,this.filters=[]}getOutput(){return this.gain}setNodeSource(t){return this.hasPlaybackControl=!1,this.sourceType=\\\\\\\"audioNode\\\\\\\",this.source=t,this.connect(),this}setMediaElementSource(t){return this.hasPlaybackControl=!1,this.sourceType=\\\\\\\"mediaNode\\\\\\\",this.source=this.context.createMediaElementSource(t),this.connect(),this}setMediaStreamSource(t){return this.hasPlaybackControl=!1,this.sourceType=\\\\\\\"mediaStreamNode\\\\\\\",this.source=this.context.createMediaStreamSource(t),this.connect(),this}setBuffer(t){return this.buffer=t,this.sourceType=\\\\\\\"buffer\\\\\\\",this.autoplay&&this.play(),this}play(t=0){if(!0===this.isPlaying)return void console.warn(\\\\\\\"THREE.Audio: Audio is already playing.\\\\\\\");if(!1===this.hasPlaybackControl)return void console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\");this._startedAt=this.context.currentTime+t;const e=this.context.createBufferSource();return e.buffer=this.buffer,e.loop=this.loop,e.loopStart=this.loopStart,e.loopEnd=this.loopEnd,e.onended=this.onEnded.bind(this),e.start(this._startedAt,this._progress+this.offset,this.duration),this.isPlaying=!0,this.source=e,this.setDetune(this.detune),this.setPlaybackRate(this.playbackRate),this.connect()}pause(){if(!1!==this.hasPlaybackControl)return!0===this.isPlaying&&(this._progress+=Math.max(this.context.currentTime-this._startedAt,0)*this.playbackRate,!0===this.loop&&(this._progress=this._progress%(this.duration||this.buffer.duration)),this.source.stop(),this.source.onended=null,this.isPlaying=!1),this;console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\")}stop(){if(!1!==this.hasPlaybackControl)return this._progress=0,this.source.stop(),this.source.onended=null,this.isPlaying=!1,this;console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\")}connect(){if(this.filters.length>0){this.source.connect(this.filters[0]);for(let t=1,e=this.filters.length;t0){this.source.disconnect(this.filters[0]);for(let t=1,e=this.filters.length;t{t.load(e,(function(t){n(t)}))}))}}var OV;!function(t){t.LINEAR=\\\\\\\"linear\\\\\\\",t.INVERSE=\\\\\\\"inverse\\\\\\\",t.EXPONENTIAL=\\\\\\\"exponential\\\\\\\"}(OV||(OV={}));const PV=[OV.LINEAR,OV.INVERSE,OV.EXPONENTIAL];class RV extends(yU(ua)){constructor(){super(...arguments),this.audio=ha.FOLDER(),this.listener=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.OBJ,types:[Ig.AUDIO_LISTENER]}}),this.url=ha.STRING(\\\\\\\"\\\\\\\",{fileBrowse:{type:[Rr.AUDIO]}}),this.volume=ha.FLOAT(1),this.loop=ha.BOOLEAN(1,{separatorBefore:!0}),this.loopStart=ha.FLOAT(0,{visibleIf:{loop:1}}),this.loopEnd=ha.FLOAT(0,{visibleIf:{loop:1},separatorAfter:!0}),this.refDistance=ha.FLOAT(10,{range:[0,10],rangeLocked:[!0,!1]}),this.rolloffFactor=ha.FLOAT(10,{range:[0,10],rangeLocked:[!0,!1]}),this.maxDistance=ha.FLOAT(100,{range:[.001,100],rangeLocked:[!0,!1]}),this.distanceModel=ha.INTEGER(PV.indexOf(OV.LINEAR),{menu:{entries:PV.map(((t,e)=>({name:t,value:e})))}}),this.coneInnerAngle=ha.FLOAT(180,{range:[0,360],rangeLocked:[!0,!0]}),this.coneOuterAngle=ha.FLOAT(230,{range:[0,360],rangeLocked:[!0,!0]}),this.coneOuterGain=ha.FLOAT(.1,{range:[0,1],rangeLocked:[!0,!0]}),this.autoplay=ha.BOOLEAN(1),this.showHelper=ha.BOOLEAN(0),this.helperSize=ha.FLOAT(1,{range:[0,10],rangeLocked:[!0,!1],visibleIf:{showHelper:!0}}),this.play=ha.BUTTON(null,{callback:t=>{FV.PARAM_CALLBACK_play(t)}}),this.pause=ha.BUTTON(null,{callback:t=>{FV.PARAM_CALLBACK_pause(t)}})}}const IV=new RV;class FV extends oU{constructor(){super(...arguments),this.paramsConfig=IV,this.hierarchyController=new wU(this),this.transformController=new bU(this),this.flags=new Di(this)}static type(){return Ig.POSITIONAL_AUDIO}createObject(){const t=new Fn.a;return t.matrixAutoUpdate=!1,t}initializeNode(){this.hierarchyController.initializeNode(),this.transformController.initializeNode(),this._updateHelperHierarchy(),this.flags.display.onUpdate((()=>{this._updateHelperHierarchy()})),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.url],(()=>{const t=this.p.url.rawInput();if(t){const e=t.split(\\\\\\\"/\\\\\\\");return e[e.length-1]}return\\\\\\\"\\\\\\\"}))}))}))}_updateHelperHierarchy(){this._helper&&(this.flags.display.active()?this.object.add(this._helper):this.object.remove(this._helper))}cook(){this.transformController.update(),this._updatePositionalAudio(),this.cookController.endCook()}async _updatePositionalAudio(){this.p.listener.isDirty()&&await this.p.listener.compute();const t=this.pv.url;if(this._loadedUrl!=t)try{await this._createPositionalAudio()}catch(t){this.states.error.set(`error when creating audio: ${t}`)}this._positionalAudio&&(this._positionalAudio.setVolume(this.pv.volume),this._positionalAudio.setLoop(this.pv.loop),this._positionalAudio.setLoopStart(this.pv.loopStart),this._positionalAudio.setLoopEnd(this.pv.loopEnd),this._positionalAudio.setRefDistance(this.pv.refDistance),this._positionalAudio.setRolloffFactor(this.pv.rolloffFactor),this._positionalAudio.setMaxDistance(this.pv.maxDistance),this._positionalAudio.setDistanceModel(PV[this.pv.distanceModel]),this._positionalAudio.setDirectionalCone(this.pv.coneInnerAngle,this.pv.coneOuterAngle,this.pv.coneOuterGain),this.pv.showHelper&&(this._helper=this._helper||this._createHelper(this._positionalAudio),this.object.add(this._helper)),this._helper&&(this._helper.visible=this.pv.showHelper,this._helper.range=this.pv.helperSize,this._helper.update()))}_createHelper(t){const e=new SV(t);return e.matrixAutoUpdate=!1,e}async _createPositionalAudio(){const t=this.pv.listener.nodeWithContext(ts.OBJ);if(!t)return;const e=t.object;this._positionalAudio&&(this._positionalAudio.source&&(this._positionalAudio.stop(),this._positionalAudio.disconnect()),this.object.remove(this._positionalAudio),this._positionalAudio=void 0),this._helper&&(this._helper.dispose(),this._helper=void 0),this._positionalAudio=new EV(e),this._positionalAudio.matrixAutoUpdate=!1;const n=new LV(this.pv.url,this.scene(),this),i=await n.load();this._loadedUrl=this.pv.url,this._positionalAudio.autoplay=this.pv.autoplay,this._positionalAudio.setBuffer(i),this.object.add(this._positionalAudio)}isPlaying(){return!!this._positionalAudio&&this._positionalAudio.isPlaying}static PARAM_CALLBACK_play(t){t.PARAM_CALLBACK_play()}static PARAM_CALLBACK_pause(t){t.PARAM_CALLBACK_pause()}PARAM_CALLBACK_play(){this._positionalAudio&&(this.isPlaying()||this._positionalAudio.play())}PARAM_CALLBACK_pause(){this._positionalAudio&&this.isPlaying()&&this._positionalAudio.pause()}}var DV;!function(t){t.ON_RENDER=\\\\\\\"On Every Render\\\\\\\",t.MANUAL=\\\\\\\"Manual\\\\\\\"}(DV||(DV={}));const BV=[DV.ON_RENDER,DV.MANUAL];const zV=new class extends ua{constructor(){super(...arguments),this.object=ha.OPERATOR_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.OBJ},dependentOnFoundNode:!1,computeOnDirty:!0,callback:t=>{kV.PARAM_CALLBACK_update_resolved_object(t)}}),this.pointIndex=ha.INTEGER(0,{range:[0,100]}),this.updateMode=ha.INTEGER(BV.indexOf(DV.ON_RENDER),{callback:t=>{kV.PARAM_CALLBACK_update_updateMode(t)},menu:{entries:BV.map(((t,e)=>({name:t,value:e})))}}),this.update=ha.BUTTON(null,{callback:t=>{kV.PARAM_CALLBACK_update(t)},visibleIf:{updateMode:BV.indexOf(DV.MANUAL)}})}};class kV extends oU{constructor(){super(...arguments),this.paramsConfig=zV,this.hierarchyController=new wU(this),this.flags=new Di(this),this._helper=new xG(1),this._found_point_post=new p.a,this._on_object_before_render_bound=this._update.bind(this)}static type(){return\\\\\\\"rivet\\\\\\\"}createObject(){const t=new B.a;return t.matrixAutoUpdate=!1,t}initializeNode(){this.hierarchyController.initializeNode(),this.addPostDirtyHook(\\\\\\\"rivet_on_dirty\\\\\\\",(()=>{this.cookController.cookMainWithoutInputs()})),this._updateHelperHierarchy(),this.flags.display.onUpdate((()=>{this._updateHelperHierarchy()}))}_updateHelperHierarchy(){this.flags.display.active()?this.object.add(this._helper):this.object.remove(this._helper)}async cook(){await this._update_resolved_object(),this._update_render_hook(),this.cookController.endCook()}_update_render_hook(){const t=BV[this.pv.updateMode];switch(t){case DV.ON_RENDER:return this._add_render_hook();case DV.MANUAL:return this._remove_render_hook()}os.unreachable(t)}_add_render_hook(){this.object.onBeforeRender=this._on_object_before_render_bound,this.object.frustumCulled=!1}_remove_render_hook(){this.object.onBeforeRender=()=>{}}_update(t,e,n,i,s,r){const o=this._resolved_object();if(o){const t=o.geometry;if(t){const e=t.attributes.position;if(e){const t=e.array;this._found_point_post.fromArray(t,3*this.pv.pointIndex),o.updateWorldMatrix(!0,!1),o.localToWorld(this._found_point_post),this.object.matrix.makeTranslation(this._found_point_post.x,this._found_point_post.y,this._found_point_post.z)}}}}static PARAM_CALLBACK_update_resolved_object(t){t._update_resolved_object()}async _update_resolved_object(){this.p.object.isDirty()&&await this.p.object.compute();const t=this.p.object.found_node();if(t)if(t.context()==ts.OBJ&&t.type()==kG.type()){const e=t;this._resolved_sop_group=e.childrenDisplayController.sopGroup()}else this.states.error.set(\\\\\\\"found node is not a geo node\\\\\\\")}_resolved_object(){if(!this._resolved_sop_group)return;const t=this._resolved_sop_group.children[0];return t||void 0}static PARAM_CALLBACK_update_updateMode(t){t._update_render_hook()}static PARAM_CALLBACK_update(t){t._update()}}class UV extends(Pa(Na(wa(ya(_a(ua)))))){}const GV=new UV;class VV extends oU{constructor(){super(...arguments),this.paramsConfig=GV,this.hierarchyController=new wU(this),this.SceneAutoUpdateController=new ma(this),this.sceneBackgroundController=new xa(this),this.SceneEnvController=new Ta(this),this.sceneFogController=new La(this),this.sceneMaterialOverrideController=new Ra(this)}static type(){return\\\\\\\"scene\\\\\\\"}createObject(){const t=new vs;return t.matrixAutoUpdate=!1,t}initializeNode(){this.hierarchyController.initializeNode()}cook(){this.SceneAutoUpdateController.update(),this.sceneBackgroundController.update(),this.SceneEnvController.update(),this.sceneFogController.update(),this.sceneMaterialOverrideController.update(),this.cookController.endCook()}}class HV{constructor(t,e,n){this._camera_node_id=t,this._controls_node=e,this._controls=n,this._updateRequired=this._controls_node.updateRequired()}updateRequired(){return this._updateRequired}get camera_node_id(){return this._camera_node_id}get controls(){return this._controls}get controls_node(){return this._controls_node}is_equal(t){return t.camera_node_id==this._camera_node_id&&t.controls_node.graphNodeId()==this._controls_node.graphNodeId()}}const jV=\\\\\\\"controls\\\\\\\";class WV{constructor(t){this.node=t,this._applied_controls_by_element_id=new Map,this._controls_node=null}controls_param(){return this.node.params.has(jV)?this.node.params.get(jV):null}async controls_node(){const t=this.node.p.controls,e=t.rawInput();if(e&&\\\\\\\"\\\\\\\"!=e){t.isDirty()&&await t.compute();const e=t.value.node();if(e){if(ms.includes(e.type()))return e;this.node.states.error.set(\\\\\\\"found node is not of a camera control type\\\\\\\")}else this.node.states.error.set(\\\\\\\"no node has been found\\\\\\\")}return null}async update_controls(){const t=await this.controls_node();t&&this._controls_node!=t&&this._dispose_control_refs(),this._controls_node=t}async apply_controls(t){const e=t.canvas();if(!e)return;const n=await this.controls_node();if(n){this._controlsEndEventName=n.endEventName();const i=n.controls_id();let s=!1,r=this._applied_controls_by_element_id.get(e.id);if(r&&r.get(i)&&(s=!0),!s){r=new Map,this._applied_controls_by_element_id.set(e.id,r),r.set(i,n);const s=await n.apply_controls(this.node.object,t);if(!s)return;const o=new HV(this.node.graphNodeId(),n,s);return this.set_controls_events(s),o}}}_dispose_control_refs(){this._applied_controls_by_element_id.forEach(((t,e)=>{this._dispose_controls_for_element_id(e)})),this._applied_controls_by_element_id.clear(),this._controlsEndEventName=void 0}_dispose_controls_for_element_id(t){const e=this._applied_controls_by_element_id.get(t);e&&e.forEach(((e,n)=>{e.disposeControlsForHtmlElementId(t)})),this._applied_controls_by_element_id.delete(t)}async dispose_controls(t){this._dispose_controls_for_element_id(t.id)}set_controls_events(t){const e=BH[this.node.pv.updateFromControlsMode];switch(e){case DH.ON_END:return this._set_controls_events_to_update_on_end(t);case DH.ALWAYS:return this._set_controls_events_to_update_always(t);case DH.NEVER:return this._reset(t)}os.unreachable(e)}_reset(t){this.controls_change_listener&&(t.removeEventListener(\\\\\\\"change\\\\\\\",this.controls_change_listener),this.controls_change_listener=void 0),this.controls_end_listener&&this._controlsEndEventName&&(t.removeEventListener(this._controlsEndEventName,this.controls_end_listener),this.controls_end_listener=void 0)}_set_controls_events_to_update_on_end(t){this._reset(t),this._controlsEndEventName&&(this.controls_end_listener=()=>{this.node.update_transform_params_from_object()},t.addEventListener(this._controlsEndEventName,this.controls_end_listener))}_set_controls_events_to_update_always(t){this._reset(t),this.controls_change_listener=()=>{this.node.update_transform_params_from_object()},t.addEventListener(\\\\\\\"change\\\\\\\",this.controls_change_listener)}}function qV(t){return class extends t{constructor(){super(...arguments),this.layer=ha.INTEGER(0,{range:[0,31],rangeLocked:[!0,!0]})}}}class XV{constructor(t){this.node=t}update(){const t=this.node.object;t.layers.set(0),t.layers.enable(this.node.params.integer(\\\\\\\"layer\\\\\\\"))}}const YV={callback:t=>{qH.PARAM_CALLBACK_reset_effects_composer(t)}};function $V(t){return class extends t{constructor(){super(...arguments),this.doPostProcess=ha.BOOLEAN(0),this.postProcessNode=ha.NODE_PATH(\\\\\\\"\\\\\\\",{visibleIf:{doPostProcess:1},nodeSelection:{types:[es.POST]},...YV})}}}class JV{constructor(t){this.node=t,this._composers_by_canvas_id={},this.node.p.postProcessNode?this._add_param_dirty_hook():this.node.params.onParamsCreated(\\\\\\\"post process add param dirty hook\\\\\\\",(()=>{this._add_param_dirty_hook()}))}_add_param_dirty_hook(){this.node.p.postProcessNode.addPostDirtyHook(\\\\\\\"on_post_node_dirty\\\\\\\",(()=>{this.reset()}))}render(t,e){const n=this.composer(t);n&&(e&&n.setSize(e.x,e.y),n.render())}reset(){const t=Object.keys(this._composers_by_canvas_id);for(let e of t)delete this._composers_by_canvas_id[e]}composer(t){return this._composers_by_canvas_id[t.id]=this._composers_by_canvas_id[t.id]||this._create_composer(t)}_create_composer(t){const e=this.node.renderController.renderer(t);if(e){const n=this.node.renderController.resolved_scene||this.node.scene().threejsScene(),i=this.node.object,s=this.node.p.postProcessNode.value.node();if(s){if(s.type()==es.POST){const r=s,o=this.node.renderController.canvas_resolution(t);return r.effectsComposerController.createEffectsComposer({renderer:e,scene:n,camera:i,resolution:o,requester:this.node,camera_node:this.node})}this.node.states.error.set(\\\\\\\"found node is not a post process node\\\\\\\")}else this.node.states.error.set(\\\\\\\"no post node found\\\\\\\")}}}class ZV extends aa{constructor(){super(...arguments),this.flags=new Pi(this)}static context(){return ts.ROP}initializeBaseNode(){this.dirtyController.addPostDirtyHook(\\\\\\\"cook_immediately\\\\\\\",(()=>{this.cookController.cookMainWithoutInputs()}))}cook(){this.cookController.endCook()}}var QV,KV,tH,eH;!function(t){t.CSS2D=\\\\\\\"CSS2DRenderer\\\\\\\",t.CSS3D=\\\\\\\"CSS3DRenderer\\\\\\\",t.WEBGL=\\\\\\\"WebGLRenderer\\\\\\\"}(QV||(QV={})),function(t){t.Linear=\\\\\\\"Linear\\\\\\\",t.sRGB=\\\\\\\"sRGB\\\\\\\",t.Gamma=\\\\\\\"Gamma\\\\\\\",t.RGBE=\\\\\\\"RGBE\\\\\\\",t.LogLuv=\\\\\\\"LogLuv\\\\\\\",t.RGBM7=\\\\\\\"RGBM7\\\\\\\",t.RGBM16=\\\\\\\"RGBM16\\\\\\\",t.RGBD=\\\\\\\"RGBD\\\\\\\"}(KV||(KV={})),(eH=tH||(tH={}))[eH.Linear=w.U]=\\\\\\\"Linear\\\\\\\",eH[eH.sRGB=w.ld]=\\\\\\\"sRGB\\\\\\\",eH[eH.Gamma=w.J]=\\\\\\\"Gamma\\\\\\\",eH[eH.RGBE=w.gc]=\\\\\\\"RGBE\\\\\\\",eH[eH.LogLuv=w.bb]=\\\\\\\"LogLuv\\\\\\\",eH[eH.RGBM7=w.lc]=\\\\\\\"RGBM7\\\\\\\",eH[eH.RGBM16=w.kc]=\\\\\\\"RGBM16\\\\\\\",eH[eH.RGBD=w.fc]=\\\\\\\"RGBD\\\\\\\";const nH=[KV.Linear,KV.sRGB,KV.Gamma,KV.RGBE,KV.LogLuv,KV.RGBM7,KV.RGBM16,KV.RGBD],iH=[tH.Linear,tH.sRGB,tH.Gamma,tH.RGBE,tH.LogLuv,tH.RGBM7,tH.RGBM16,tH.RGBD],sH=tH.sRGB;var rH,oH,aH;!function(t){t.No=\\\\\\\"No\\\\\\\",t.Linear=\\\\\\\"Linear\\\\\\\",t.Reinhard=\\\\\\\"Reinhard\\\\\\\",t.Cineon=\\\\\\\"Cineon\\\\\\\",t.ACESFilmic=\\\\\\\"ACESFilmic\\\\\\\"}(rH||(rH={})),(aH=oH||(oH={}))[aH.No=w.vb]=\\\\\\\"No\\\\\\\",aH[aH.Linear=w.ab]=\\\\\\\"Linear\\\\\\\",aH[aH.Reinhard=w.vc]=\\\\\\\"Reinhard\\\\\\\",aH[aH.Cineon=w.m]=\\\\\\\"Cineon\\\\\\\",aH[aH.ACESFilmic=w.a]=\\\\\\\"ACESFilmic\\\\\\\";const lH=[rH.No,rH.Linear,rH.Reinhard,rH.Cineon,rH.ACESFilmic],cH=[oH.No,oH.Linear,oH.Reinhard,oH.Cineon,oH.ACESFilmic],hH=oH.ACESFilmic,uH=lH.map(((t,e)=>({name:t,value:cH[e]})));var dH;!function(t){t.HIGH=\\\\\\\"highp\\\\\\\",t.MEDIUM=\\\\\\\"mediump\\\\\\\",t.LOW=\\\\\\\"lowp\\\\\\\"}(dH||(dH={}));const pH=[dH.HIGH,dH.MEDIUM,dH.LOW];var _H;!function(t){t.HIGH=\\\\\\\"high-performance\\\\\\\",t.LOW=\\\\\\\"low-power\\\\\\\",t.DEFAULT=\\\\\\\"default\\\\\\\"}(_H||(_H={}));const mH=[_H.HIGH,_H.LOW,_H.DEFAULT];var fH,gH,vH;!function(t){t.Basic=\\\\\\\"Basic\\\\\\\",t.PCF=\\\\\\\"PCF\\\\\\\",t.PCFSoft=\\\\\\\"PCFSoft\\\\\\\",t.VSM=\\\\\\\"VSM\\\\\\\"}(fH||(fH={})),(vH=gH||(gH={}))[vH.Basic=w.k]=\\\\\\\"Basic\\\\\\\",vH[vH.PCF=w.Fb]=\\\\\\\"PCF\\\\\\\",vH[vH.PCFSoft=w.Gb]=\\\\\\\"PCFSoft\\\\\\\",vH[vH.VSM=w.gd]=\\\\\\\"VSM\\\\\\\";const yH=[fH.Basic,fH.PCF,fH.PCFSoft,fH.VSM],xH=[gH.Basic,gH.PCF,gH.PCFSoft,gH.VSM],bH=(w.k,w.Fb,w.Gb,w.gd,gH.PCFSoft),wH={alpha:!1,precision:dH.HIGH,premultipliedAlpha:!0,antialias:!1,stencil:!0,preserveDrawingBuffer:!1,powerPreference:_H.DEFAULT,depth:!0,logarithmicDepthBuffer:!1};const TH=new class extends ua{constructor(){super(...arguments),this.tprecision=ha.BOOLEAN(0),this.precision=ha.INTEGER(pH.indexOf(dH.HIGH),{visibleIf:{tprecision:1},menu:{entries:pH.map(((t,e)=>({value:e,name:t})))}}),this.tpowerPreference=ha.BOOLEAN(0),this.powerPreference=ha.INTEGER(mH.indexOf(_H.DEFAULT),{visibleIf:{tpowerPreference:1},menu:{entries:mH.map(((t,e)=>({value:e,name:t})))}}),this.alpha=ha.BOOLEAN(1),this.premultipliedAlpha=ha.BOOLEAN(1),this.antialias=ha.BOOLEAN(1),this.stencil=ha.BOOLEAN(1),this.depth=ha.BOOLEAN(1),this.logarithmicDepthBuffer=ha.BOOLEAN(0),this.toneMapping=ha.INTEGER(hH,{menu:{entries:uH}}),this.toneMappingExposure=ha.FLOAT(1,{range:[0,2]}),this.outputEncoding=ha.INTEGER(sH,{menu:{entries:nH.map(((t,e)=>({name:t,value:iH[e]})))}}),this.physicallyCorrectLights=ha.BOOLEAN(1),this.sortObjects=ha.BOOLEAN(1),this.tpixelRatio=ha.BOOLEAN(0),this.pixelRatio=ha.INTEGER(2,{visibleIf:{tpixelRatio:!0},range:[1,4],rangeLocked:[!0,!1]}),this.tshadowMap=ha.BOOLEAN(1),this.shadowMapAutoUpdate=ha.BOOLEAN(1,{visibleIf:{tshadowMap:1}}),this.shadowMapNeedsUpdate=ha.BOOLEAN(0,{visibleIf:{tshadowMap:1}}),this.shadowMapType=ha.INTEGER(bH,{visibleIf:{tshadowMap:1},menu:{entries:yH.map(((t,e)=>({name:t,value:xH[e]})))}})}};class AH extends ZV{constructor(){super(...arguments),this.paramsConfig=TH,this._renderers_by_canvas_id={}}static type(){return QV.WEBGL}createRenderer(t,e){const n={},i=Object.keys(wH);let s;for(s of i)n[s]=wH[s];if(this.pv.tprecision){const t=pH[this.pv.precision];n.precision=t}if(this.pv.tpowerPreference){const t=mH[this.pv.powerPreference];n.powerPreference=t}n.antialias=this.pv.antialias,n.antialias=this.pv.antialias,n.alpha=this.pv.alpha,n.premultipliedAlpha=this.pv.premultipliedAlpha,n.depth=this.pv.depth,n.stencil=this.pv.stencil,n.logarithmicDepthBuffer=this.pv.logarithmicDepthBuffer,n.canvas=t,n.context=e;const r=li.renderersController.createWebGLRenderer(n);return li.renderersController.printDebug()&&(li.renderersController.printDebugMessage(`create renderer from node '${this.path()}'`),li.renderersController.printDebugMessage({params:n})),this._update_renderer(r),this._renderers_by_canvas_id[t.id]=r,r}cook(){const t=Object.keys(this._renderers_by_canvas_id);for(let e of t){const t=this._renderers_by_canvas_id[e];this._update_renderer(t)}this._traverse_scene_and_update_materials(),this.cookController.endCook()}_update_renderer(t){t.physicallyCorrectLights=this.pv.physicallyCorrectLights,t.outputEncoding=this.pv.outputEncoding,t.toneMapping=this.pv.toneMapping,t.toneMappingExposure=this.pv.toneMappingExposure,t.shadowMap.enabled=this.pv.tshadowMap,t.shadowMap.autoUpdate=this.pv.shadowMapAutoUpdate,t.shadowMap.needsUpdate=this.pv.shadowMapNeedsUpdate,t.shadowMap.type=this.pv.shadowMapType,t.sortObjects=this.pv.sortObjects;const e=this.pv.tpixelRatio?this.pv.pixelRatio:EH.defaultPixelRatio();li.renderersController.printDebug()&&(li.renderersController.printDebugMessage(`set renderer pixelRatio from '${this.path()}'`),li.renderersController.printDebugMessage({pixelRatio:e})),t.setPixelRatio(e)}_traverse_scene_and_update_materials(){this.scene().threejsScene().traverse((t=>{const e=t.material;if(e)if(m.isArray(e))for(let t of e)t.needsUpdate=!0;else e.needsUpdate=!0}))}}function MH(t){return class extends t{constructor(){super(...arguments),this.render=ha.FOLDER(),this.setScene=ha.BOOLEAN(0),this.scene=ha.OPERATOR_PATH(\\\\\\\"\\\\\\\",{visibleIf:{setScene:1},nodeSelection:{context:ts.OBJ,types:[VV.type()]}}),this.setRenderer=ha.BOOLEAN(0),this.renderer=ha.OPERATOR_PATH(\\\\\\\"\\\\\\\",{visibleIf:{setRenderer:1},nodeSelection:{context:ts.ROP,types:[AH.type()]}}),this.setCSSRenderer=ha.BOOLEAN(0),this.CSSRenderer=ha.OPERATOR_PATH(\\\\\\\"\\\\\\\",{visibleIf:{setCSSRenderer:1},nodeSelection:{context:ts.ROP,types:[QV.CSS2D,QV.CSS3D]}})}}}class EH{constructor(t){this.node=t,this._renderers_by_canvas_id={},this._resolution_by_canvas_id={},this._super_sampling_size=new d.a}render(t,e,n,i){if(this.node.pv.doPostProcess?this.node.postProcessController.render(t,e):this.renderWithRenderer(t,i),this._resolved_cssRenderer_rop&&this._resolved_scene&&this.node.pv.setCSSRenderer){const e=this.cssRenderer(t);e&&e.render(this._resolved_scene,this.node.object)}}renderWithRenderer(t,e){const n=this.renderer(t);if(n){const t=this._resolved_scene;t&&n.render(t,this.node.object)}}async update(){this.update_scene(),this.update_renderer(),this.update_cssRenderer()}get resolved_scene(){return this._resolved_scene}update_scene(){if(this.node.pv.setScene){const t=this.node.p.scene;t.isDirty()&&t.find_target();const e=t.found_node_with_context_and_type(ts.OBJ,VV.type());e&&(e.isDirty()&&e.cookController.cookMainWithoutInputs(),this._resolved_scene=e.object)}else this._resolved_scene=this.node.scene().threejsScene()}update_renderer(){if(this.node.pv.setRenderer){const t=this.node.p.renderer;t.isDirty()&&t.find_target(),this._resolved_renderer_rop=t.found_node_with_context_and_type(ts.ROP,QV.WEBGL)}else this._resolved_renderer_rop=void 0}update_cssRenderer(){if(this.node.pv.setCSSRenderer){const t=this.node.p.CSSRenderer;t.isDirty()&&t.find_target(),this._resolved_cssRenderer_rop=t.found_node_with_context_and_type(ts.ROP,[QV.CSS2D,QV.CSS3D])}else this._resolved_cssRenderer_rop,this._resolved_cssRenderer_rop=void 0}renderer(t){return this._renderers_by_canvas_id[t.id]}cssRenderer(t){if(this._resolved_cssRenderer_rop&&this.node.pv.setCSSRenderer)return this._resolved_cssRenderer_rop.renderer(t)}createRenderer(t,e){const n=li.renderersController.createRenderingContext(t);if(!n)return void console.error(\\\\\\\"failed to create webgl context\\\\\\\");let i;return this.node.pv.setRenderer&&(this.update_renderer(),this._resolved_renderer_rop&&(i=this._resolved_renderer_rop.createRenderer(t,n))),i||(i=EH._createDefaultRenderer(t,n)),li.renderersController.registerRenderer(i),this._renderers_by_canvas_id[t.id]=i,this._super_sampling_size.copy(e),this.set_renderer_size(t,this._super_sampling_size),i}static defaultPixelRatio(){return ng.isMobile()?1:Math.max(2,window.devicePixelRatio)}static _createDefaultRenderer(t,e){const n={canvas:t,antialias:!1,alpha:!1,context:e},i=li.renderersController.createWebGLRenderer(n),s=this.defaultPixelRatio();return i.setPixelRatio(s),i.shadowMap.enabled=!0,i.shadowMap.type=bH,i.physicallyCorrectLights=!0,i.toneMapping=hH,i.toneMappingExposure=1,i.outputEncoding=sH,li.renderersController.printDebug()&&(li.renderersController.printDebugMessage(\\\\\\\"create default renderer\\\\\\\"),li.renderersController.printDebugMessage({params:n,pixelRatio:s})),i}deleteRenderer(t){const e=this.renderer(t);e&&li.renderersController.deregisterRenderer(e)}canvas_resolution(t){return this._resolution_by_canvas_id[t.id]}set_renderer_size(t,e){this._resolution_by_canvas_id[t.id]=this._resolution_by_canvas_id[t.id]||new d.a,this._resolution_by_canvas_id[t.id].copy(e);const n=this.renderer(t);if(n){const t=!1;n.setSize(e.x,e.y,t)}if(this._resolved_cssRenderer_rop){const n=this.cssRenderer(t);n&&n.setSize(e.x,e.y)}}}class SH{constructor(t){this.viewer=t,this._active=!1,this._controls=null,this._bound_on_controls_start=this._on_controls_start.bind(this),this._bound_on_controls_end=this._on_controls_end.bind(this),this._update_graph_node()}controls(){return this._controls}async create_controls(){var t;this.dispose_controls();this.viewer.canvas()&&(this._config=await(null===(t=this.viewer.cameraControlsController)||void 0===t?void 0:t.apply_controls(this.viewer)),this._config&&(this._controls=this._config.controls,this._controls&&(this.viewer.active()?(this._controls.addEventListener(\\\\\\\"start\\\\\\\",this._bound_on_controls_start),this._controls.addEventListener(\\\\\\\"end\\\\\\\",this._bound_on_controls_end)):this.dispose_controls())))}update(t){this._config&&this._controls&&this._config.updateRequired()&&this._controls.update(t)}dispose(){var t;null===(t=this._graph_node)||void 0===t||t.graphDisconnectPredecessors(),this.dispose_controls()}dispose_controls(){var t;if(this._controls){const e=this.viewer.canvas();e&&(null===(t=this.viewer)||void 0===t||t.cameraControlsController.dispose_controls(e)),this._bound_on_controls_start&&this._controls.removeEventListener(\\\\\\\"start\\\\\\\",this._bound_on_controls_start),this._bound_on_controls_end&&this._controls.removeEventListener(\\\\\\\"end\\\\\\\",this._bound_on_controls_end),this._controls.dispose(),this._controls=null}}_on_controls_start(){this._active=!0}_on_controls_end(){this._active=!1}_update_graph_node(){const t=this.viewer.cameraNode().p.controls;this._graph_node=this._graph_node||this._create_graph_node(),this._graph_node&&(this._graph_node.graphDisconnectPredecessors(),this._graph_node.addGraphInput(t))}_create_graph_node(){const t=new Mi(this.viewer.cameraNode().scene(),\\\\\\\"viewer-controls\\\\\\\");return t.addPostDirtyHook(\\\\\\\"this.viewer.controls_controller\\\\\\\",(async()=>{await this.create_controls()})),t}}class CH{constructor(t){this._viewer=t,this._size=new d.a(100,100),this._aspect=1}cameraNode(){return this._viewer.cameraNode()}get size(){return this._size}get aspect(){return this._aspect}computeSizeAndAspect(){this._updateSize(),this.cameraNode().scene().uniformsController.updateResolutionDependentUniformOwners(this._size),this._aspect=this._getAspect()}_updateSize(){this._size.x=this._viewer.domElement().offsetWidth,this._size.y=this._viewer.domElement().offsetHeight}_getAspect(){return this._size.x/this._size.y}updateCameraAspect(){this.cameraNode().setupForAspectRatio(this._aspect)}async prepareCurrentCamera(){await this.cameraNode().compute(),await this._updateFromCameraContainer()}async _updateFromCameraContainer(){var t;this.updateCameraAspect(),await(null===(t=this._viewer.controlsController)||void 0===t?void 0:t.create_controls())}}class NH{constructor(t){this.viewer=t}init(){const t=this.viewer.canvas();t&&(t.onwebglcontextlost=this._on_webglcontextlost.bind(this),t.onwebglcontextrestored=this._on_webglcontextrestored.bind(this))}_on_webglcontextlost(){console.warn(\\\\\\\"context lost at frame\\\\\\\",this.viewer.scene().frame()),this.request_animation_frame_id?cancelAnimationFrame(this.request_animation_frame_id):console.warn(\\\\\\\"request_animation_frame_id not initialized\\\\\\\"),console.warn(\\\\\\\"not canceled\\\\\\\",this.request_animation_frame_id)}_on_webglcontextrestored(){console.log(\\\\\\\"context restored\\\\\\\")}}const LH=\\\\\\\"hovered\\\\\\\";class OH{constructor(t,e,n){this._container=t,this._scene=e,this._camera_node=n,this._active=!1,this._id=OH._next_viewer_id++,this._scene.viewersRegister.registerViewer(this)}setRenderObjectOverride(t){console.log(\\\\\\\"setRenderObjectOverride\\\\\\\",t),this._renderObjectOverride=t||void 0}active(){return this._active}activate(){this._active=!0}deactivate(){this._active=!1}get camerasController(){return this._cameras_controller=this._cameras_controller||new CH(this)}get controlsController(){return this._controls_controller}get eventsController(){return this._events_controller=this._events_controller||new Wa(this)}get webglController(){return this._webgl_controller=this._webgl_controller||new NH(this)}domElement(){return this._container}scene(){return this._scene}canvas(){return this._canvas}cameraNode(){return this._camera_node}get cameraControlsController(){}id(){return this._id}dispose(){let t;for(this._scene.viewersRegister.unregisterViewer(this),this.eventsController.dispose();t=this._container.children[0];)this._container.removeChild(t)}resetContainerClass(){this.domElement().classList.remove(LH)}setContainerClassHovered(){this.domElement().classList.add(LH)}registerOnBeforeTick(t,e){this._registerCallback(t,e,this.registeredBeforeTickCallbacks())}unRegisterOnBeforeTick(t){this._unregisterCallback(t,this._onBeforeTickCallbacks)}registeredBeforeTickCallbacks(){return this._onBeforeTickCallbacks=this._onBeforeTickCallbacks||new Map}registerOnAfterTick(t,e){this._registerCallback(t,e,this.registeredAfterTickCallbacks())}unRegisterOnAfterTick(t){this._unregisterCallback(t,this._onAfterTickCallbacks)}registeredAfterTickCallbacks(){return this._onAfterTickCallbacks=this._onAfterTickCallbacks||new Map}registerOnBeforeRender(t,e){this._registerCallback(t,e,this.registeredBeforeRenderCallbacks())}unRegisterOnBeforeRender(t){this._unregisterCallback(t,this._onBeforeRenderCallbacks)}registeredBeforeRenderCallbacks(){return this._onBeforeRenderCallbacks=this._onBeforeRenderCallbacks||new Map}registerOnAfterRender(t,e){this._registerCallback(t,e,this.registeredAfterRenderCallbacks())}unRegisterOnAfterRender(t){this._unregisterCallback(t,this._onAfterRenderCallbacks)}registeredAfterRenderCallbacks(){return this._onAfterRenderCallbacks=this._onAfterRenderCallbacks||new Map}_registerCallback(t,e,n){n.has(t)?console.warn(`callback ${t} already registered`):n.set(t,e)}_unregisterCallback(t,e){e&&e.delete(t)}}OH._next_viewer_id=0;class PH extends OH{constructor(t,e,n,i){super(t,e,n),this._scene=e,this._camera_node=n,this._properties=i,this._do_render=!0,this._clock=new Dm,this._delta=0,this._animate_method=this.animate.bind(this),this._onResizeBound=this.onResize.bind(this),this._do_render=null==this._properties||this._properties.autoRender,this._canvas=document.createElement(\\\\\\\"canvas\\\\\\\"),this._canvas.id=`canvas_id_${Math.random()}`.replace(\\\\\\\".\\\\\\\",\\\\\\\"_\\\\\\\"),this._canvas.style.display=\\\\\\\"block\\\\\\\",this._canvas.style.outline=\\\\\\\"none\\\\\\\",this._container.appendChild(this._canvas),this._container.classList.add(\\\\\\\"CoreThreejsViewer\\\\\\\"),this._build(),this._setEvents()}get controlsController(){return this._controls_controller=this._controls_controller||new SH(this)}_build(){this._init_display(),this.activate()}dispose(){this._cancel_animate(),this.controlsController.dispose(),this._disposeEvents(),super.dispose()}get cameraControlsController(){return this._camera_node.controls_controller}_setEvents(){this.eventsController.init(),this.webglController.init(),window.addEventListener(\\\\\\\"resize\\\\\\\",this._onResizeBound.bind(this),!1)}_disposeEvents(){window.removeEventListener(\\\\\\\"resize\\\\\\\",this._onResizeBound.bind(this),!1)}onResize(){const t=this.canvas();t&&(this.camerasController.computeSizeAndAspect(),this._camera_node.renderController.set_renderer_size(t,this.camerasController.size),this.camerasController.updateCameraAspect())}_init_display(){if(!this._canvas)return void console.warn(\\\\\\\"no canvas found for viewer\\\\\\\");this.camerasController.computeSizeAndAspect();const t=this.camerasController.size;this._camera_node.renderController.createRenderer(this._canvas,t),this.camerasController.prepareCurrentCamera(),this.animate()}setAutoRender(t=!0){this._do_render=t,this._do_render&&this.animate()}animate(){var t,e,n;this._do_render&&(this._delta=this._clock.getDelta(),this._request_animation_frame_id=requestAnimationFrame(this._animate_method),null===(t=this._onBeforeTickCallbacks)||void 0===t||t.forEach((t=>t(this._delta))),this._scene.timeController.incrementTimeIfPlaying(this._delta),null===(e=this._onAfterTickCallbacks)||void 0===e||e.forEach((t=>t(this._delta))),this.render(this._delta),null===(n=this._controls_controller)||void 0===n||n.update(this._delta))}_cancel_animate(){this._do_render=!1,this._request_animation_frame_id&&cancelAnimationFrame(this._request_animation_frame_id),this._canvas&&this._camera_node.renderController.deleteRenderer(this._canvas)}render(t){var e,n;if(this.camerasController.cameraNode()&&this._canvas){null===(e=this._onBeforeRenderCallbacks)||void 0===e||e.forEach((e=>e(t)));const i=this.camerasController.size,s=this.camerasController.aspect;this._camera_node.renderController.render(this._canvas,i,s,this._renderObjectOverride),null===(n=this._onAfterRenderCallbacks)||void 0===n||n.forEach((e=>e(t)))}else console.warn(\\\\\\\"no camera to render with\\\\\\\")}renderer(){if(this._canvas)return this._camera_node.renderController.renderer(this._canvas)}}const RH={type:\\\\\\\"change\\\\\\\"},IH=1,FH=100;var DH;!function(t){t.ON_END=\\\\\\\"on move end\\\\\\\",t.ALWAYS=\\\\\\\"always\\\\\\\",t.NEVER=\\\\\\\"never\\\\\\\"}(DH||(DH={}));const BH=[DH.ON_END,DH.ALWAYS,DH.NEVER];function zH(t){return class extends t{constructor(){super(...arguments),this.setMainCamera=ha.BUTTON(null,{callback:(t,e)=>{WH.PARAM_CALLBACK_setMasterCamera(t)}})}}}function kH(t){return class extends t{constructor(){super(...arguments),this.camera=ha.FOLDER(),this.controls=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.EVENT}}),this.updateFromControlsMode=ha.INTEGER(BH.indexOf(DH.ON_END),{menu:{entries:BH.map(((t,e)=>({name:t,value:e})))}}),this.near=ha.FLOAT(IH,{range:[0,100],cook:!1,computeOnDirty:!0,callback:(t,e)=>{qH.PARAM_CALLBACK_update_near_far_from_param(t,e)}}),this.far=ha.FLOAT(FH,{range:[0,100],cook:!1,computeOnDirty:!0,callback:(t,e)=>{qH.PARAM_CALLBACK_update_near_far_from_param(t,e)}}),this.display=ha.BOOLEAN(1),this.showHelper=ha.BOOLEAN(0)}}}var UH;!function(t){t.DEFAULT=\\\\\\\"default\\\\\\\",t.COVER=\\\\\\\"cover\\\\\\\",t.CONTAIN=\\\\\\\"contain\\\\\\\"}(UH||(UH={}));const GH=[UH.DEFAULT,UH.COVER,UH.CONTAIN];function VH(t){return class extends t{constructor(){super(...arguments),this.fovAdjustMode=ha.INTEGER(GH.indexOf(UH.DEFAULT),{menu:{entries:GH.map(((t,e)=>({name:t,value:e})))}}),this.expectedAspectRatio=ha.FLOAT(\\\\\\\"16/9\\\\\\\",{visibleIf:[{fovAdjustMode:GH.indexOf(UH.COVER)},{fovAdjustMode:GH.indexOf(UH.CONTAIN)}],range:[0,2],rangeLocked:[!0,!1]})}}}zH(ua);$V(MH(yU(qV(kH(zH(ua))))));class HH extends oU{constructor(){super(...arguments),this.renderOrder=rU.CAMERA,this._aspect=-1}get object(){return this._object}async cook(){this.updateCamera(),this._object.dispatchEvent(RH),this.cookController.endCook()}on_create(){}on_delete(){}prepareRaycaster(t,e){}camera(){return this._object}updateCamera(){}static PARAM_CALLBACK_setMasterCamera(t){t.set_as_master_camera()}set_as_master_camera(){this.scene().camerasController.setMainCameraNodePath(this.path())}setupForAspectRatio(t){}_updateForAspectRatio(){}update_transform_params_from_object(){vU.set_params_from_object(this._object,this)}static PARAM_CALLBACK_update_from_param(t,e){t.object[e.name()]=t.pv[e.name()]}}class jH extends HH{constructor(){super(...arguments),this.flags=new Di(this),this.hierarchyController=new wU(this),this.transformController=new bU(this),this.childrenDisplayController=new DG(this),this.displayNodeController=new Fm(this,this.childrenDisplayController.displayNodeControllerCallbacks()),this._children_controller_context=ts.SOP}get controls_controller(){return this._controls_controller=this._controls_controller||new WV(this)}get layers_controller(){return this._layers_controller=this._layers_controller||new XV(this)}get renderController(){return this._render_controller=this._render_controller||new EH(this)}get postProcessController(){return this._post_process_controller=this._post_process_controller||new JV(this)}initializeBaseNode(){super.initializeBaseNode(),this.io.outputs.setHasOneOutput(),this.hierarchyController.initializeNode(),this.transformController.initializeNode(),this.childrenDisplayController.initializeNode(),this.initHelperHook()}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}prepareRaycaster(t,e){e.setFromCamera(t,this._object)}async cook(){this.transformController.update(),this.layers_controller.update(),this.updateNearFar(),this.renderController.update(),this.updateCamera(),this._updateHelper(),this.controls_controller.update_controls(),this._object.dispatchEvent(RH),this.cookController.endCook()}static PARAM_CALLBACK_update_near_far_from_param(t,e){t.updateNearFar()}updateNearFar(){this._object.near==this.pv.near&&this._object.far==this.pv.far||(this._object.near=this.pv.near,this._object.far=this.pv.far,this._object.updateProjectionMatrix(),this._updateHelper())}setupForAspectRatio(t){m.isNaN(t)||t&&this._aspect!=t&&(this._aspect=t,this._updateForAspectRatio())}createViewer(t,e){return new PH(t,this.scene(),this,e)}static PARAM_CALLBACK_reset_effects_composer(t){t.postProcessController.reset()}initHelperHook(){this.flags.display.onUpdate((()=>{this._updateHelper()}))}helperVisible(){return this.flags.display.active()&&this.pv.showHelper}_createHelper(){const t=new FU(this.object);return t.update(),t}_updateHelper(){this.helperVisible()?(this._helper||(this._helper=this._createHelper()),this._helper&&(this.object.add(this._helper),this._helper.update())):this._helper&&this.object.remove(this._helper)}}class WH extends HH{}class qH extends jH{PARAM_CALLBACK_update_effects_composer(t){}}const XH=-.5,YH=.5,$H=.5,JH=-.5;class ZH extends($V(MH(qV(zH(VH(function(t){return class extends t{constructor(){super(...arguments),this.size=ha.FLOAT(1)}}}(kH(yU(ua,{matrixAutoUpdate:!0}))))))))){}const QH=new ZH;class KH extends jH{constructor(){super(...arguments),this.paramsConfig=QH}static type(){return is.ORTHOGRAPHIC}createObject(){return new ot.a(2*XH,2*YH,2*$H,2*JH,IH,FH)}updateCamera(){this._updateForAspectRatio()}_updateForAspectRatio(){this._aspect&&(this._adjustFOVFromMode(),this._object.updateProjectionMatrix())}_adjustFOVFromMode(){const t=GH[this.pv.fovAdjustMode];switch(t){case UH.DEFAULT:return this._adjustFOVFromModeDefault();case UH.COVER:return this._adjustFOVFromModeCover();case UH.CONTAIN:return this._adjustFOVFromModeContain()}os.unreachable(t)}_adjustFOVFromModeDefault(){this._adjustFOVFromSize(this.pv.size||1)}_adjustFOVFromModeCover(){const t=this.pv.size||1;this._aspect>this.pv.expectedAspectRatio?this._adjustFOVFromSize(this.pv.expectedAspectRatio*t/this._aspect):this._adjustFOVFromSize(t)}_adjustFOVFromModeContain(){const t=this.pv.size||1;this._aspect>this.pv.expectedAspectRatio?this._adjustFOVFromSize(t):this._adjustFOVFromSize(this.pv.expectedAspectRatio*t/this._aspect)}_adjustFOVFromSize(t){const e=t*this._aspect;this._object.left=XH*e*1,this._object.right=YH*e*1,this._object.top=$H*t*1,this._object.bottom=JH*t*1}}const tj=50;class ej extends($V(MH(qV(zH(VH(function(t){return class extends t{constructor(){super(...arguments),this.fov=ha.FLOAT(tj,{range:[0,100]})}}}(kH(yU(ua,{matrixAutoUpdate:!0}))))))))){}const nj=new ej;class ij extends jH{constructor(){super(...arguments),this.paramsConfig=nj}static type(){return is.PERSPECTIVE}createObject(){return new tt.a(tj,1,IH,FH)}updateCamera(){this._object.fov!=this.pv.fov&&(this._object.fov=this.pv.fov,this._object.updateProjectionMatrix()),this._updateForAspectRatio()}_updateForAspectRatio(){this._aspect&&(this._object.aspect=this._aspect,this._adjustFOVFromMode(),this._object.updateProjectionMatrix())}_adjustFOVFromMode(){const t=GH[this.pv.fovAdjustMode];switch(t){case UH.DEFAULT:return this._adjustFOVFromModeDefault();case UH.COVER:return this._adjustFOVFromModeCover();case UH.CONTAIN:return this._adjustFOVFromModeContain()}os.unreachable(t)}_adjustFOVFromModeDefault(){this._object.fov=this.pv.fov}_adjustFOVFromModeCover(){if(this._object.aspect>this.pv.expectedAspectRatio){const t=Math.tan(Object(On.e)(this.pv.fov/2))/(this._object.aspect/this.pv.expectedAspectRatio);this._object.fov=2*Object(On.k)(Math.atan(t))}else this._object.fov=this.pv.fov}_adjustFOVFromModeContain(){if(this._object.aspect>this.pv.expectedAspectRatio)this._object.fov=this.pv.fov;else{const t=Math.tan(Object(On.e)(this.pv.fov/2))/(this._object.aspect/this.pv.expectedAspectRatio);this._object.fov=2*Object(On.k)(Math.atan(t))}}}class sj extends(function(t){return class extends t{constructor(){super(...arguments),this.main=ha.FOLDER(),this.resolution=ha.INTEGER(256),this.excludedObjects=ha.STRING(\\\\\\\"*`$OS`\\\\\\\"),this.printResolve=ha.BUTTON(null,{callback:t=>{oj.PARAM_CALLBACK_printResolve(t)}}),this.near=ha.FLOAT(1),this.far=ha.FLOAT(100),this.render=ha.BUTTON(null,{callback:t=>{oj.PARAM_CALLBACK_render(t)}}),this.renderTarget=ha.FOLDER(),this.tencoding=ha.BOOLEAN(0),this.encoding=ha.INTEGER(w.ld,{visibleIf:{tencoding:1},menu:{entries:og.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))}}),this.tminFilter=ha.BOOLEAN(0),this.minFilter=ha.INTEGER(Qm,{visibleIf:{tminFilter:1},menu:{entries:tf}}),this.tmagFilter=ha.BOOLEAN(0),this.magFilter=ha.INTEGER(Zm,{visibleIf:{tmagFilter:1},menu:{entries:Km}})}}}(yU(ua))){}const rj=new sj;class oj extends oU{constructor(){super(...arguments),this.paramsConfig=rj,this.hierarchyController=new wU(this),this.transformController=new bU(this),this.flags=new Di(this),this._excludedObjects=[],this._previousVisibleStateByUuid=new Map,this._helper=new xG(1)}static type(){return Ig.CUBE_CAMERA}initializeNode(){this.hierarchyController.initializeNode(),this.transformController.initializeNode(),this._updateHelperHierarchy(),this._helper.matrixAutoUpdate=!1,this.flags.display.onUpdate((()=>{this._updateHelperHierarchy()})),this.io.inputs.setCount(0,1)}createObject(){const t=new Fn.a;return t.matrixAutoUpdate=!0,t}cook(){this.transformController.update(),this._resolveObjects();const t=this._setupCubeCamera();this._cubeCamera&&!t||this._createCubeCamera(),this.cookController.endCook()}_updateHelperHierarchy(){this.flags.display.active()?this.object.add(this._helper):this.object.remove(this._helper)}_setupCubeCamera(){let t=!1;if(this._cubeCamera){const e=this._cubeCamera.children[0],n=e.near,i=e.far,s=this._cubeCamera.renderTarget.width;n==this.pv.near&&i==this.pv.far&&s==this.pv.resolution||(t=!0),t&&this.object.remove(this._cubeCamera)}return t}_createCubeCamera(){const t=new st(this.pv.resolution,{encoding:this.pv.tencoding?this.pv.encoding:w.ld,minFilter:this.pv.tminFilter?this.pv.minFilter:void 0,magFilter:this.pv.tmagFilter?this.pv.magFilter:void 0});this._cubeCamera=new nt(this.pv.near,this.pv.far,t),this._cubeCamera.matrixAutoUpdate=!0,this.object.add(this._cubeCamera)}renderTarget(){if(this._cubeCamera)return this._cubeCamera.renderTarget}render(){const t=li.renderersController.firstRenderer();if(t)if(this._cubeCamera){for(let t of this._excludedObjects)this._previousVisibleStateByUuid.set(t.uuid,t.visible),t.visible=!1;this._cubeCamera.update(t,this.scene().threejsScene());for(let t of this._excludedObjects){const e=this._previousVisibleStateByUuid.get(t.uuid);e&&(t.visible=e)}this._previousVisibleStateByUuid.clear()}else console.warn(`no cubeCamera for ${this.path()}`);else console.warn(`no renderer found for ${this.path()}`)}_resolveObjects(){const t=this.scene().objectsByMask(this.pv.excludedObjects),e=new Map;for(let n of t)e.set(n.uuid,n);this._excludedObjects=[];for(let n of t){const t=n.parent;t&&(e.get(t.uuid)||this._excludedObjects.push(n))}}static PARAM_CALLBACK_printResolve(t){t.param_callback_printResolve()}param_callback_printResolve(){this._resolveObjects(),console.log(this._excludedObjects)}static PARAM_CALLBACK_render(t){t.param_callback_render()}param_callback_render(){this.render()}}class aj extends oU{constructor(){super(...arguments),this._attachableToHierarchy=!1}createObject(){const t=new Fn.a;return t.matrixAutoUpdate=!1,t}cook(){this.cookController.endCook()}}class lj extends aj{}class cj extends lj{constructor(){super(...arguments),this._children_controller_context=ts.ANIM}static type(){return es.ANIM}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class hj extends cj{constructor(){super(...arguments),this.renderOrder=rU.MANAGER}}class uj extends lj{constructor(){super(...arguments),this._children_controller_context=ts.COP}static type(){return es.COP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class dj extends lj{constructor(){super(...arguments),this.renderOrder=rU.MANAGER,this._children_controller_context=ts.EVENT}static type(){return es.EVENT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class pj extends lj{constructor(){super(...arguments),this.renderOrder=rU.MANAGER,this._children_controller_context=ts.MAT}static type(){return es.MAT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class _j extends aj{constructor(){super(...arguments),this.paramsConfig=new ef,this.effectsComposerController=new nf(this),this.displayNodeController=new Fm(this,this.effectsComposerController.displayNodeControllerCallbacks()),this._children_controller_context=ts.POST}static type(){return es.POST}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class mj extends lj{constructor(){super(...arguments),this.renderOrder=rU.MANAGER,this._children_controller_context=ts.ROP}static type(){return es.ROP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}const fj=[\\\\\\\"input pass\\\\\\\"];const gj={cook:!1,callback:function(t,e){vj.PARAM_CALLBACK_updatePasses(t)},computeOnDirty:!0};class vj extends aa{constructor(){super(...arguments),this.flags=new zi(this),this._passes_by_requester_id=new Map,this._update_pass_bound=this.updatePass.bind(this)}static context(){return ts.POST}static displayedInputNames(){return fj}initializeNode(){this.flags.display.set(!1),this.flags.display.onUpdate((()=>{if(this.flags.display.active()){const t=this.parent();t&&t.displayNodeController&&t.displayNodeController.setDisplayNode(this)}})),this.io.inputs.setCount(0,1),this.io.outputs.setHasOneOutput()}cook(){this.cookController.endCook()}setupComposer(t){if(this._addPassFromInput(0,t),!this.flags.bypass.active()){let e=this._passes_by_requester_id.get(t.requester.graphNodeId());e||(e=this._createPass(t),e&&this._passes_by_requester_id.set(t.requester.graphNodeId(),e)),e&&t.composer.addPass(e)}}_addPassFromInput(t,e){const n=this.io.inputs.input(t);n&&n.setupComposer(e)}_createPass(t){}static PARAM_CALLBACK_updatePasses(t){t._updatePasses()}_updatePasses(){this._passes_by_requester_id.forEach(this._update_pass_bound)}updatePass(t){}}const yj={uniforms:{tDiffuse:{value:null}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 texel = texture2D( tDiffuse, vUv );\\\\n\\\\n\\\\t\\\\t\\\\tfloat l = linearToRelativeLuminance( texel.rgb );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( l, l, l, texel.w );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};var xj={uniforms:{tDiffuse:{value:null},averageLuminance:{value:1},luminanceMap:{value:null},maxLuminance:{value:16},minLuminance:{value:.01},middleGrey:{value:.6}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tuniform float middleGrey;\\\\n\\\\t\\\\tuniform float minLuminance;\\\\n\\\\t\\\\tuniform float maxLuminance;\\\\n\\\\t\\\\t#ifdef ADAPTED_LUMINANCE\\\\n\\\\t\\\\t\\\\tuniform sampler2D luminanceMap;\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\tuniform float averageLuminance;\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\tvec3 ToneMap( vec3 vColor ) {\\\\n\\\\t\\\\t\\\\t#ifdef ADAPTED_LUMINANCE\\\\n\\\\t\\\\t\\\\t\\\\t// Get the calculated average luminance\\\\n\\\\t\\\\t\\\\t\\\\tfloat fLumAvg = texture2D(luminanceMap, vec2(0.5, 0.5)).r;\\\\n\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\tfloat fLumAvg = averageLuminance;\\\\n\\\\t\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\t\\\\t// Calculate the luminance of the current pixel\\\\n\\\\t\\\\t\\\\tfloat fLumPixel = linearToRelativeLuminance( vColor );\\\\n\\\\n\\\\t\\\\t\\\\t// Apply the modified operator (Eq. 4)\\\\n\\\\t\\\\t\\\\tfloat fLumScaled = (fLumPixel * middleGrey) / max( minLuminance, fLumAvg );\\\\n\\\\n\\\\t\\\\t\\\\tfloat fLumCompressed = (fLumScaled * (1.0 + (fLumScaled / (maxLuminance * maxLuminance)))) / (1.0 + fLumScaled);\\\\n\\\\t\\\\t\\\\treturn fLumCompressed * vColor;\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 texel = texture2D( tDiffuse, vUv );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( ToneMap( texel.xyz ), texel.w );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};class bj extends km{constructor(t,e){super(),this.resolution=void 0!==e?e:256,this.needsInit=!0,this.adaptive=void 0===t||!!t,this.luminanceRT=null,this.previousLuminanceRT=null,this.currentLuminanceRT=null,void 0===zm&&console.error(\\\\\\\"THREE.AdaptiveToneMappingPass relies on CopyShader\\\\\\\");const n=zm;this.copyUniforms=I.clone(n.uniforms),this.materialCopy=new F({uniforms:this.copyUniforms,vertexShader:n.vertexShader,fragmentShader:n.fragmentShader,blending:w.ub,depthTest:!1}),void 0===yj&&console.error(\\\\\\\"THREE.AdaptiveToneMappingPass relies on LuminosityShader\\\\\\\"),this.materialLuminance=new F({uniforms:I.clone(yj.uniforms),vertexShader:yj.vertexShader,fragmentShader:yj.fragmentShader,blending:w.ub}),this.adaptLuminanceShader={defines:{MIP_LEVEL_1X1:(Math.log(this.resolution)/Math.log(2)).toFixed(1)},uniforms:{lastLum:{value:null},currentLum:{value:null},minLuminance:{value:.01},delta:{value:.016},tau:{value:1}},vertexShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D lastLum;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D currentLum;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float minLuminance;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float delta;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float tau;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 lastLum = texture2D( lastLum, vUv, MIP_LEVEL_1X1 );\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 currentLum = texture2D( currentLum, vUv, MIP_LEVEL_1X1 );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat fLastLum = max( minLuminance, lastLum.r );\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat fCurrentLum = max( minLuminance, currentLum.r );\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t//The adaption seems to work better in extreme lighting differences\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t//if the input luminance is squared.\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfCurrentLum *= fCurrentLum;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t// Adapt the luminance using Pattanaik's technique\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat fAdaptedLum = fLastLum + (fCurrentLum - fLastLum) * (1.0 - exp(-delta * tau));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t// \\\\\\\\\\\"fAdaptedLum = sqrt(fAdaptedLum);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor.r = fAdaptedLum;\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\"},this.materialAdaptiveLum=new F({uniforms:I.clone(this.adaptLuminanceShader.uniforms),vertexShader:this.adaptLuminanceShader.vertexShader,fragmentShader:this.adaptLuminanceShader.fragmentShader,defines:Object.assign({},this.adaptLuminanceShader.defines),blending:w.ub}),void 0===xj&&console.error(\\\\\\\"THREE.AdaptiveToneMappingPass relies on ToneMapShader\\\\\\\"),this.materialToneMap=new F({uniforms:I.clone(xj.uniforms),vertexShader:xj.vertexShader,fragmentShader:xj.fragmentShader,blending:w.ub}),this.fsQuad=new Vm(null)}render(t,e,n,i){this.needsInit&&(this.reset(t),this.luminanceRT.texture.type=n.texture.type,this.previousLuminanceRT.texture.type=n.texture.type,this.currentLuminanceRT.texture.type=n.texture.type,this.needsInit=!1),this.adaptive&&(this.fsQuad.material=this.materialLuminance,this.materialLuminance.uniforms.tDiffuse.value=n.texture,t.setRenderTarget(this.currentLuminanceRT),this.fsQuad.render(t),this.fsQuad.material=this.materialAdaptiveLum,this.materialAdaptiveLum.uniforms.delta.value=i,this.materialAdaptiveLum.uniforms.lastLum.value=this.previousLuminanceRT.texture,this.materialAdaptiveLum.uniforms.currentLum.value=this.currentLuminanceRT.texture,t.setRenderTarget(this.luminanceRT),this.fsQuad.render(t),this.fsQuad.material=this.materialCopy,this.copyUniforms.tDiffuse.value=this.luminanceRT.texture,t.setRenderTarget(this.previousLuminanceRT),this.fsQuad.render(t)),this.fsQuad.material=this.materialToneMap,this.materialToneMap.uniforms.tDiffuse.value=n.texture,this.renderToScreen?(t.setRenderTarget(null),this.fsQuad.render(t)):(t.setRenderTarget(e),this.clear&&t.clear(),this.fsQuad.render(t))}reset(){this.luminanceRT&&this.luminanceRT.dispose(),this.currentLuminanceRT&&this.currentLuminanceRT.dispose(),this.previousLuminanceRT&&this.previousLuminanceRT.dispose();const t={minFilter:w.V,magFilter:w.V,format:w.Ib};this.luminanceRT=new Q(this.resolution,this.resolution,t),this.luminanceRT.texture.name=\\\\\\\"AdaptiveToneMappingPass.l\\\\\\\",this.luminanceRT.texture.generateMipmaps=!1,this.previousLuminanceRT=new Q(this.resolution,this.resolution,t),this.previousLuminanceRT.texture.name=\\\\\\\"AdaptiveToneMappingPass.pl\\\\\\\",this.previousLuminanceRT.texture.generateMipmaps=!1,t.minFilter=w.Y,t.generateMipmaps=!0,this.currentLuminanceRT=new Q(this.resolution,this.resolution,t),this.currentLuminanceRT.texture.name=\\\\\\\"AdaptiveToneMappingPass.cl\\\\\\\",this.adaptive&&(this.materialToneMap.defines.ADAPTED_LUMINANCE=\\\\\\\"\\\\\\\",this.materialToneMap.uniforms.luminanceMap.value=this.luminanceRT.texture),this.fsQuad.material=new lt.a({color:7829367}),this.materialLuminance.needsUpdate=!0,this.materialAdaptiveLum.needsUpdate=!0,this.materialToneMap.needsUpdate=!0}setAdaptive(t){t?(this.adaptive=!0,this.materialToneMap.defines.ADAPTED_LUMINANCE=\\\\\\\"\\\\\\\",this.materialToneMap.uniforms.luminanceMap.value=this.luminanceRT.texture):(this.adaptive=!1,delete this.materialToneMap.defines.ADAPTED_LUMINANCE,this.materialToneMap.uniforms.luminanceMap.value=null),this.materialToneMap.needsUpdate=!0}setAdaptionRate(t){t&&(this.materialAdaptiveLum.uniforms.tau.value=Math.abs(t))}setMinLuminance(t){t&&(this.materialToneMap.uniforms.minLuminance.value=t,this.materialAdaptiveLum.uniforms.minLuminance.value=t)}setMaxLuminance(t){t&&(this.materialToneMap.uniforms.maxLuminance.value=t)}setAverageLuminance(t){t&&(this.materialToneMap.uniforms.averageLuminance.value=t)}setMiddleGrey(t){t&&(this.materialToneMap.uniforms.middleGrey.value=t)}dispose(){this.luminanceRT&&this.luminanceRT.dispose(),this.previousLuminanceRT&&this.previousLuminanceRT.dispose(),this.currentLuminanceRT&&this.currentLuminanceRT.dispose(),this.materialLuminance&&this.materialLuminance.dispose(),this.materialAdaptiveLum&&this.materialAdaptiveLum.dispose(),this.materialCopy&&this.materialCopy.dispose(),this.materialToneMap&&this.materialToneMap.dispose()}}const wj=new class extends ua{constructor(){super(...arguments),this.adaptive=ha.BOOLEAN(1,{...gj}),this.averageLuminance=ha.FLOAT(.7,{...gj}),this.midGrey=ha.FLOAT(.04,{...gj}),this.maxLuminance=ha.FLOAT(16,{range:[0,20],...gj}),this.adaptiveRange=ha.FLOAT(2,{range:[0,10],...gj})}};class Tj extends vj{constructor(){super(...arguments),this.paramsConfig=wj}static type(){return\\\\\\\"adaptiveToneMapping\\\\\\\"}_createPass(t){const e=new bj(this.pv.adaptive,t.resolution.x);return this.updatePass(e),e}updatePass(t){t.setMaxLuminance(this.pv.maxLuminance),t.setMiddleGrey(this.pv.midGrey),t.setAverageLuminance(this.pv.averageLuminance)}}const Aj={uniforms:{damp:{value:.96},tOld:{value:null},tNew:{value:null}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform float damp;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tOld;\\\\n\\\\t\\\\tuniform sampler2D tNew;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvec4 when_gt( vec4 x, float y ) {\\\\n\\\\n\\\\t\\\\t\\\\treturn max( sign( x - y ), 0.0 );\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 texelOld = texture2D( tOld, vUv );\\\\n\\\\t\\\\t\\\\tvec4 texelNew = texture2D( tNew, vUv );\\\\n\\\\n\\\\t\\\\t\\\\ttexelOld *= damp * when_gt( texelOld, 0.1 );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = max(texelNew, texelOld);\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};class Mj extends km{constructor(t=.96){super(),void 0===Aj&&console.error(\\\\\\\"THREE.AfterimagePass relies on AfterimageShader\\\\\\\"),this.shader=Aj,this.uniforms=I.clone(this.shader.uniforms),this.uniforms.damp.value=t,this.textureComp=new Q(window.innerWidth,window.innerHeight,{minFilter:w.V,magFilter:w.ob,format:w.Ib}),this.textureOld=new Q(window.innerWidth,window.innerHeight,{minFilter:w.V,magFilter:w.ob,format:w.Ib}),this.shaderMaterial=new F({uniforms:this.uniforms,vertexShader:this.shader.vertexShader,fragmentShader:this.shader.fragmentShader}),this.compFsQuad=new Vm(this.shaderMaterial);const e=new lt.a;this.copyFsQuad=new Vm(e)}render(t,e,n){this.uniforms.tOld.value=this.textureOld.texture,this.uniforms.tNew.value=n.texture,t.setRenderTarget(this.textureComp),this.compFsQuad.render(t),this.copyFsQuad.material.map=this.textureComp.texture,this.renderToScreen?(t.setRenderTarget(null),this.copyFsQuad.render(t)):(t.setRenderTarget(e),this.clear&&t.clear(),this.copyFsQuad.render(t));const i=this.textureOld;this.textureOld=this.textureComp,this.textureComp=i}setSize(t,e){this.textureComp.setSize(t,e),this.textureOld.setSize(t,e)}}const Ej=new class extends ua{constructor(){super(...arguments),this.damp=ha.FLOAT(.96,{range:[0,1],rangeLocked:[!0,!0],...gj})}};class Sj extends vj{constructor(){super(...arguments),this.paramsConfig=Ej}static type(){return\\\\\\\"afterImage\\\\\\\"}_createPass(t){const e=new Mj;return this.updatePass(e),e}updatePass(t){t.uniforms.damp.value=this.pv.damp}}const Cj={uniforms:{tDiffuse:{value:null},opacity:{value:1}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform float opacity;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 base = texture2D( tDiffuse, vUv );\\\\n\\\\n\\\\t\\\\t\\\\tvec3 lumCoeff = vec3( 0.25, 0.65, 0.1 );\\\\n\\\\t\\\\t\\\\tfloat lum = dot( lumCoeff, base.rgb );\\\\n\\\\t\\\\t\\\\tvec3 blend = vec3( lum );\\\\n\\\\n\\\\t\\\\t\\\\tfloat L = min( 1.0, max( 0.0, 10.0 * ( lum - 0.45 ) ) );\\\\n\\\\n\\\\t\\\\t\\\\tvec3 result1 = 2.0 * base.rgb * blend;\\\\n\\\\t\\\\t\\\\tvec3 result2 = 1.0 - 2.0 * ( 1.0 - blend ) * ( 1.0 - base.rgb );\\\\n\\\\n\\\\t\\\\t\\\\tvec3 newColor = mix( result1, result2, L );\\\\n\\\\n\\\\t\\\\t\\\\tfloat A2 = opacity * base.a;\\\\n\\\\t\\\\t\\\\tvec3 mixRGB = A2 * newColor.rgb;\\\\n\\\\t\\\\t\\\\tmixRGB += ( ( 1.0 - A2 ) * base.rgb );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( mixRGB, base.a );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const Nj=new class extends ua{constructor(){super(...arguments),this.opacity=ha.FLOAT(.95,{range:[-5,5],rangeLocked:[!0,!0],...gj})}};class Lj extends vj{constructor(){super(...arguments),this.paramsConfig=Nj}static type(){return\\\\\\\"bleach\\\\\\\"}_createPass(t){const e=new Hm(Cj);return this.updatePass(e),e}updatePass(t){t.uniforms.opacity.value=this.pv.opacity}}const Oj={uniforms:{tDiffuse:{value:null},brightness:{value:0},contrast:{value:0}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\t\\\\tuniform float brightness;\\\\n\\\\t\\\\tuniform float contrast;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = texture2D( tDiffuse, vUv );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor.rgb += brightness;\\\\n\\\\n\\\\t\\\\t\\\\tif (contrast > 0.0) {\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb = (gl_FragColor.rgb - 0.5) / (1.0 - contrast) + 0.5;\\\\n\\\\t\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\t\\\\tgl_FragColor.rgb = (gl_FragColor.rgb - 0.5) * (1.0 + contrast) + 0.5;\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const Pj=new class extends ua{constructor(){super(...arguments),this.brightness=ha.FLOAT(0,{range:[-1,1],rangeLocked:[!1,!1],...gj}),this.contrast=ha.FLOAT(0,{range:[-1,1],rangeLocked:[!1,!1],...gj}),this.transparent=ha.BOOLEAN(1,gj)}};class Rj extends vj{constructor(){super(...arguments),this.paramsConfig=Pj}static type(){return\\\\\\\"brightnessContrast\\\\\\\"}_createPass(t){const e=new Hm(Oj);return e.fsQuad.material.transparent=!0,this.updatePass(e),e}updatePass(t){t.uniforms.brightness.value=this.pv.brightness,t.uniforms.contrast.value=this.pv.contrast,t.material.transparent=this.pv.transparent}}class Ij extends km{constructor(t,e){super(),this.needsSwap=!1,this.clearColor=void 0!==t?t:0,this.clearAlpha=void 0!==e?e:0,this._oldClearColor=new D.a}render(t,e,n){let i;this.clearColor&&(t.getClearColor(this._oldClearColor),i=t.getClearAlpha(),t.setClearColor(this.clearColor,this.clearAlpha)),t.setRenderTarget(this.renderToScreen?null:n),t.clear(),this.clearColor&&t.setClearColor(this._oldClearColor,i)}}const Fj=new class extends ua{};class Dj extends vj{constructor(){super(...arguments),this.paramsConfig=Fj}static type(){return\\\\\\\"clear\\\\\\\"}_createPass(t){const e=new Ij;return this.updatePass(e),e}updatePass(t){}}const Bj=new class extends ua{};class zj extends vj{constructor(){super(...arguments),this.paramsConfig=Bj}static type(){return\\\\\\\"clearMask\\\\\\\"}_createPass(t){const e=new Wm;return this.updatePass(e),e}updatePass(t){}}const kj={uniforms:{tDiffuse:{value:null},powRGB:{value:new p.a(2,2,2)},mulRGB:{value:new p.a(1,1,1)},addRGB:{value:new p.a(0,0,0)}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\t\\\\tuniform vec3 powRGB;\\\\n\\\\t\\\\tuniform vec3 mulRGB;\\\\n\\\\t\\\\tuniform vec3 addRGB;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = texture2D( tDiffuse, vUv );\\\\n\\\\t\\\\t\\\\tgl_FragColor.rgb = mulRGB * pow( ( gl_FragColor.rgb + addRGB ), powRGB );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const Uj=new class extends ua{constructor(){super(...arguments),this.pow=ha.VECTOR3([2,2,2],{...gj}),this.mult=ha.COLOR([1,1,1],{...gj}),this.add=ha.COLOR([0,0,0],{...gj})}};class Gj extends vj{constructor(){super(...arguments),this.paramsConfig=Uj}static type(){return\\\\\\\"colorCorrection\\\\\\\"}_createPass(t){const e=new Hm(kj);return this.updatePass(e),e}updatePass(t){t.uniforms.powRGB.value.copy(this.pv.pow),t.uniforms.mulRGB.value.set(this.pv.mult.r,this.pv.mult.g,this.pv.mult.b),t.uniforms.addRGB.value.set(this.pv.add.r,this.pv.add.g,this.pv.add.b)}}const Vj=new class extends ua{constructor(){super(...arguments),this.opacity=ha.FLOAT(1,{range:[0,1],rangeLocked:[!0,!0],...gj}),this.transparent=ha.BOOLEAN(1,gj)}};class Hj extends vj{constructor(){super(...arguments),this.paramsConfig=Vj}static type(){return\\\\\\\"copy\\\\\\\"}_createPass(t){const e=new Hm(zm);return this.updatePass(e),e}updatePass(t){t.uniforms.opacity.value=this.pv.opacity,t.material.transparent=this.pv.transparent}}const jj={uniforms:{textureWidth:{value:1},textureHeight:{value:1},focalDepth:{value:1},focalLength:{value:24},fstop:{value:.9},tColor:{value:null},tDepth:{value:null},maxblur:{value:1},showFocus:{value:0},manualdof:{value:0},vignetting:{value:0},depthblur:{value:0},threshold:{value:.5},gain:{value:2},bias:{value:.5},fringe:{value:.7},znear:{value:.1},zfar:{value:100},noise:{value:1},dithering:{value:1e-4},pentagon:{value:0},shaderFocus:{value:1},focusCoords:{value:new d.a}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tColor;\\\\n\\\\t\\\\tuniform sampler2D tDepth;\\\\n\\\\t\\\\tuniform float textureWidth;\\\\n\\\\t\\\\tuniform float textureHeight;\\\\n\\\\n\\\\t\\\\tuniform float focalDepth; //focal distance value in meters, but you may use autofocus option below\\\\n\\\\t\\\\tuniform float focalLength; //focal length in mm\\\\n\\\\t\\\\tuniform float fstop; //f-stop value\\\\n\\\\t\\\\tuniform bool showFocus; //show debug focus point and focal range (red = focal point, green = focal range)\\\\n\\\\n\\\\t\\\\t/*\\\\n\\\\t\\\\tmake sure that these two values are the same for your camera, otherwise distances will be wrong.\\\\n\\\\t\\\\t*/\\\\n\\\\n\\\\t\\\\tuniform float znear; // camera clipping start\\\\n\\\\t\\\\tuniform float zfar; // camera clipping end\\\\n\\\\n\\\\t\\\\t//------------------------------------------\\\\n\\\\t\\\\t//user variables\\\\n\\\\n\\\\t\\\\tconst int samples = SAMPLES; //samples on the first ring\\\\n\\\\t\\\\tconst int rings = RINGS; //ring count\\\\n\\\\n\\\\t\\\\tconst int maxringsamples = rings * samples;\\\\n\\\\n\\\\t\\\\tuniform bool manualdof; // manual dof calculation\\\\n\\\\t\\\\tfloat ndofstart = 1.0; // near dof blur start\\\\n\\\\t\\\\tfloat ndofdist = 2.0; // near dof blur falloff distance\\\\n\\\\t\\\\tfloat fdofstart = 1.0; // far dof blur start\\\\n\\\\t\\\\tfloat fdofdist = 3.0; // far dof blur falloff distance\\\\n\\\\n\\\\t\\\\tfloat CoC = 0.03; //circle of confusion size in mm (35mm film = 0.03mm)\\\\n\\\\n\\\\t\\\\tuniform bool vignetting; // use optical lens vignetting\\\\n\\\\n\\\\t\\\\tfloat vignout = 1.3; // vignetting outer border\\\\n\\\\t\\\\tfloat vignin = 0.0; // vignetting inner border\\\\n\\\\t\\\\tfloat vignfade = 22.0; // f-stops till vignete fades\\\\n\\\\n\\\\t\\\\tuniform bool shaderFocus;\\\\n\\\\t\\\\t// disable if you use external focalDepth value\\\\n\\\\n\\\\t\\\\tuniform vec2 focusCoords;\\\\n\\\\t\\\\t// autofocus point on screen (0.0,0.0 - left lower corner, 1.0,1.0 - upper right)\\\\n\\\\t\\\\t// if center of screen use vec2(0.5, 0.5);\\\\n\\\\n\\\\t\\\\tuniform float maxblur;\\\\n\\\\t\\\\t//clamp value of max blur (0.0 = no blur, 1.0 default)\\\\n\\\\n\\\\t\\\\tuniform float threshold; // highlight threshold;\\\\n\\\\t\\\\tuniform float gain; // highlight gain;\\\\n\\\\n\\\\t\\\\tuniform float bias; // bokeh edge bias\\\\n\\\\t\\\\tuniform float fringe; // bokeh chromatic aberration / fringing\\\\n\\\\n\\\\t\\\\tuniform bool noise; //use noise instead of pattern for sample dithering\\\\n\\\\n\\\\t\\\\tuniform float dithering;\\\\n\\\\n\\\\t\\\\tuniform bool depthblur; // blur the depth buffer\\\\n\\\\t\\\\tfloat dbsize = 1.25; // depth blur size\\\\n\\\\n\\\\t\\\\t/*\\\\n\\\\t\\\\tnext part is experimental\\\\n\\\\t\\\\tnot looking good with small sample and ring count\\\\n\\\\t\\\\tlooks okay starting from samples = 4, rings = 4\\\\n\\\\t\\\\t*/\\\\n\\\\n\\\\t\\\\tuniform bool pentagon; //use pentagon as bokeh shape?\\\\n\\\\t\\\\tfloat feather = 0.4; //pentagon shape feather\\\\n\\\\n\\\\t\\\\t//------------------------------------------\\\\n\\\\n\\\\t\\\\tfloat penta(vec2 coords) {\\\\n\\\\t\\\\t\\\\t//pentagonal shape\\\\n\\\\t\\\\t\\\\tfloat scale = float(rings) - 1.3;\\\\n\\\\t\\\\t\\\\tvec4 HS0 = vec4( 1.0, 0.0, 0.0, 1.0);\\\\n\\\\t\\\\t\\\\tvec4 HS1 = vec4( 0.309016994, 0.951056516, 0.0, 1.0);\\\\n\\\\t\\\\t\\\\tvec4 HS2 = vec4(-0.809016994, 0.587785252, 0.0, 1.0);\\\\n\\\\t\\\\t\\\\tvec4 HS3 = vec4(-0.809016994,-0.587785252, 0.0, 1.0);\\\\n\\\\t\\\\t\\\\tvec4 HS4 = vec4( 0.309016994,-0.951056516, 0.0, 1.0);\\\\n\\\\t\\\\t\\\\tvec4 HS5 = vec4( 0.0 ,0.0 , 1.0, 1.0);\\\\n\\\\n\\\\t\\\\t\\\\tvec4 one = vec4( 1.0 );\\\\n\\\\n\\\\t\\\\t\\\\tvec4 P = vec4((coords),vec2(scale, scale));\\\\n\\\\n\\\\t\\\\t\\\\tvec4 dist = vec4(0.0);\\\\n\\\\t\\\\t\\\\tfloat inorout = -4.0;\\\\n\\\\n\\\\t\\\\t\\\\tdist.x = dot( P, HS0 );\\\\n\\\\t\\\\t\\\\tdist.y = dot( P, HS1 );\\\\n\\\\t\\\\t\\\\tdist.z = dot( P, HS2 );\\\\n\\\\t\\\\t\\\\tdist.w = dot( P, HS3 );\\\\n\\\\n\\\\t\\\\t\\\\tdist = smoothstep( -feather, feather, dist );\\\\n\\\\n\\\\t\\\\t\\\\tinorout += dot( dist, one );\\\\n\\\\n\\\\t\\\\t\\\\tdist.x = dot( P, HS4 );\\\\n\\\\t\\\\t\\\\tdist.y = HS5.w - abs( P.z );\\\\n\\\\n\\\\t\\\\t\\\\tdist = smoothstep( -feather, feather, dist );\\\\n\\\\t\\\\t\\\\tinorout += dist.x;\\\\n\\\\n\\\\t\\\\t\\\\treturn clamp( inorout, 0.0, 1.0 );\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tfloat bdepth(vec2 coords) {\\\\n\\\\t\\\\t\\\\t// Depth buffer blur\\\\n\\\\t\\\\t\\\\tfloat d = 0.0;\\\\n\\\\t\\\\t\\\\tfloat kernel[9];\\\\n\\\\t\\\\t\\\\tvec2 offset[9];\\\\n\\\\n\\\\t\\\\t\\\\tvec2 wh = vec2(1.0/textureWidth,1.0/textureHeight) * dbsize;\\\\n\\\\n\\\\t\\\\t\\\\toffset[0] = vec2(-wh.x,-wh.y);\\\\n\\\\t\\\\t\\\\toffset[1] = vec2( 0.0, -wh.y);\\\\n\\\\t\\\\t\\\\toffset[2] = vec2( wh.x -wh.y);\\\\n\\\\n\\\\t\\\\t\\\\toffset[3] = vec2(-wh.x, 0.0);\\\\n\\\\t\\\\t\\\\toffset[4] = vec2( 0.0, 0.0);\\\\n\\\\t\\\\t\\\\toffset[5] = vec2( wh.x, 0.0);\\\\n\\\\n\\\\t\\\\t\\\\toffset[6] = vec2(-wh.x, wh.y);\\\\n\\\\t\\\\t\\\\toffset[7] = vec2( 0.0, wh.y);\\\\n\\\\t\\\\t\\\\toffset[8] = vec2( wh.x, wh.y);\\\\n\\\\n\\\\t\\\\t\\\\tkernel[0] = 1.0/16.0; kernel[1] = 2.0/16.0; kernel[2] = 1.0/16.0;\\\\n\\\\t\\\\t\\\\tkernel[3] = 2.0/16.0; kernel[4] = 4.0/16.0; kernel[5] = 2.0/16.0;\\\\n\\\\t\\\\t\\\\tkernel[6] = 1.0/16.0; kernel[7] = 2.0/16.0; kernel[8] = 1.0/16.0;\\\\n\\\\n\\\\n\\\\t\\\\t\\\\tfor( int i=0; i<9; i++ ) {\\\\n\\\\t\\\\t\\\\t\\\\tfloat tmp = texture2D(tDepth, coords + offset[i]).r;\\\\n\\\\t\\\\t\\\\t\\\\td += tmp * kernel[i];\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\treturn d;\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\n\\\\t\\\\tvec3 color(vec2 coords,float blur) {\\\\n\\\\t\\\\t\\\\t//processing the sample\\\\n\\\\n\\\\t\\\\t\\\\tvec3 col = vec3(0.0);\\\\n\\\\t\\\\t\\\\tvec2 texel = vec2(1.0/textureWidth,1.0/textureHeight);\\\\n\\\\n\\\\t\\\\t\\\\tcol.r = texture2D(tColor,coords + vec2(0.0,1.0)*texel*fringe*blur).r;\\\\n\\\\t\\\\t\\\\tcol.g = texture2D(tColor,coords + vec2(-0.866,-0.5)*texel*fringe*blur).g;\\\\n\\\\t\\\\t\\\\tcol.b = texture2D(tColor,coords + vec2(0.866,-0.5)*texel*fringe*blur).b;\\\\n\\\\n\\\\t\\\\t\\\\tvec3 lumcoeff = vec3(0.299,0.587,0.114);\\\\n\\\\t\\\\t\\\\tfloat lum = dot(col.rgb, lumcoeff);\\\\n\\\\t\\\\t\\\\tfloat thresh = max((lum-threshold)*gain, 0.0);\\\\n\\\\t\\\\t\\\\treturn col+mix(vec3(0.0),col,thresh*blur);\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvec3 debugFocus(vec3 col, float blur, float depth) {\\\\n\\\\t\\\\t\\\\tfloat edge = 0.002*depth; //distance based edge smoothing\\\\n\\\\t\\\\t\\\\tfloat m = clamp(smoothstep(0.0,edge,blur),0.0,1.0);\\\\n\\\\t\\\\t\\\\tfloat e = clamp(smoothstep(1.0-edge,1.0,blur),0.0,1.0);\\\\n\\\\n\\\\t\\\\t\\\\tcol = mix(col,vec3(1.0,0.5,0.0),(1.0-m)*0.6);\\\\n\\\\t\\\\t\\\\tcol = mix(col,vec3(0.0,0.5,1.0),((1.0-e)-(1.0-m))*0.2);\\\\n\\\\n\\\\t\\\\t\\\\treturn col;\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tfloat linearize(float depth) {\\\\n\\\\t\\\\t\\\\treturn -zfar * znear / (depth * (zfar - znear) - zfar);\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tfloat vignette() {\\\\n\\\\t\\\\t\\\\tfloat dist = distance(vUv.xy, vec2(0.5,0.5));\\\\n\\\\t\\\\t\\\\tdist = smoothstep(vignout+(fstop/vignfade), vignin+(fstop/vignfade), dist);\\\\n\\\\t\\\\t\\\\treturn clamp(dist,0.0,1.0);\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tfloat gather(float i, float j, int ringsamples, inout vec3 col, float w, float h, float blur) {\\\\n\\\\t\\\\t\\\\tfloat rings2 = float(rings);\\\\n\\\\t\\\\t\\\\tfloat step = PI*2.0 / float(ringsamples);\\\\n\\\\t\\\\t\\\\tfloat pw = cos(j*step)*i;\\\\n\\\\t\\\\t\\\\tfloat ph = sin(j*step)*i;\\\\n\\\\t\\\\t\\\\tfloat p = 1.0;\\\\n\\\\t\\\\t\\\\tif (pentagon) {\\\\n\\\\t\\\\t\\\\t\\\\tp = penta(vec2(pw,ph));\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\tcol += color(vUv.xy + vec2(pw*w,ph*h), blur) * mix(1.0, i/rings2, bias) * p;\\\\n\\\\t\\\\t\\\\treturn 1.0 * mix(1.0, i /rings2, bias) * p;\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t//scene depth calculation\\\\n\\\\n\\\\t\\\\t\\\\tfloat depth = linearize(texture2D(tDepth,vUv.xy).x);\\\\n\\\\n\\\\t\\\\t\\\\t// Blur depth?\\\\n\\\\t\\\\t\\\\tif ( depthblur ) {\\\\n\\\\t\\\\t\\\\t\\\\tdepth = linearize(bdepth(vUv.xy));\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t//focal plane calculation\\\\n\\\\n\\\\t\\\\t\\\\tfloat fDepth = focalDepth;\\\\n\\\\n\\\\t\\\\t\\\\tif (shaderFocus) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tfDepth = linearize(texture2D(tDepth,focusCoords).x);\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t// dof blur factor calculation\\\\n\\\\n\\\\t\\\\t\\\\tfloat blur = 0.0;\\\\n\\\\n\\\\t\\\\t\\\\tif (manualdof) {\\\\n\\\\t\\\\t\\\\t\\\\tfloat a = depth-fDepth; // Focal plane\\\\n\\\\t\\\\t\\\\t\\\\tfloat b = (a-fdofstart)/fdofdist; // Far DoF\\\\n\\\\t\\\\t\\\\t\\\\tfloat c = (-a-ndofstart)/ndofdist; // Near Dof\\\\n\\\\t\\\\t\\\\t\\\\tblur = (a>0.0) ? b : c;\\\\n\\\\t\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\t\\\\tfloat f = focalLength; // focal length in mm\\\\n\\\\t\\\\t\\\\t\\\\tfloat d = fDepth*1000.0; // focal plane in mm\\\\n\\\\t\\\\t\\\\t\\\\tfloat o = depth*1000.0; // depth in mm\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tfloat a = (o*f)/(o-f);\\\\n\\\\t\\\\t\\\\t\\\\tfloat b = (d*f)/(d-f);\\\\n\\\\t\\\\t\\\\t\\\\tfloat c = (d-f)/(d*fstop*CoC);\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tblur = abs(a-b)*c;\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\tblur = clamp(blur,0.0,1.0);\\\\n\\\\n\\\\t\\\\t\\\\t// calculation of pattern for dithering\\\\n\\\\n\\\\t\\\\t\\\\tvec2 noise = vec2(rand(vUv.xy), rand( vUv.xy + vec2( 0.4, 0.6 ) ) )*dithering*blur;\\\\n\\\\n\\\\t\\\\t\\\\t// getting blur x and y step factor\\\\n\\\\n\\\\t\\\\t\\\\tfloat w = (1.0/textureWidth)*blur*maxblur+noise.x;\\\\n\\\\t\\\\t\\\\tfloat h = (1.0/textureHeight)*blur*maxblur+noise.y;\\\\n\\\\n\\\\t\\\\t\\\\t// calculation of final color\\\\n\\\\n\\\\t\\\\t\\\\tvec3 col = vec3(0.0);\\\\n\\\\n\\\\t\\\\t\\\\tif(blur < 0.05) {\\\\n\\\\t\\\\t\\\\t\\\\t//some optimization thingy\\\\n\\\\t\\\\t\\\\t\\\\tcol = texture2D(tColor, vUv.xy).rgb;\\\\n\\\\t\\\\t\\\\t} else {\\\\n\\\\t\\\\t\\\\t\\\\tcol = texture2D(tColor, vUv.xy).rgb;\\\\n\\\\t\\\\t\\\\t\\\\tfloat s = 1.0;\\\\n\\\\t\\\\t\\\\t\\\\tint ringsamples;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tfor (int i = 1; i <= rings; i++) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t/*unboxstart*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tringsamples = i * samples;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfor (int j = 0 ; j < maxringsamples ; j++) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif (j >= ringsamples) break;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\ts += gather(float(i), float(j), ringsamples, col, w, h, blur);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t/*unboxend*/\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tcol /= s; //divide by sample count\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\tif (showFocus) {\\\\n\\\\t\\\\t\\\\t\\\\tcol = debugFocus(col, blur, depth);\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\tif (vignetting) {\\\\n\\\\t\\\\t\\\\t\\\\tcol *= vignette();\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor.rgb = col;\\\\n\\\\t\\\\t\\\\tgl_FragColor.a = 1.0;\\\\n\\\\t\\\\t}\\\\\\\"},Wj={uniforms:{mNear:{value:1},mFar:{value:1e3}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying float vViewZDepth;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t#include \\\\n\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t\\\\tvViewZDepth = - mvPosition.z;\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform float mNear;\\\\n\\\\t\\\\tuniform float mFar;\\\\n\\\\n\\\\t\\\\tvarying float vViewZDepth;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tfloat color = 1.0 - smoothstep( mNear, mFar, vViewZDepth );\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( vec3( color ), 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};class qj{constructor(t){this._scene=t}scene(){return this._scene}with_overriden_material(t,e,n,i){const s={};let r;this._scene.traverse((i=>{const o=i;if(o.material){const i=o.geometry;if(i){const a=o.customDepthDOFMaterial;if(a){if(r=a,r.uniforms)for(let t of Object.keys(n))r.uniforms[t].value=n[t].value}else r=fr.markedAsInstance(i)?e:t;r&&(s[o.uuid]=o.material,o.material=r)}}})),i(),this._scene.traverse((t=>{const e=t;if(e.material){e.geometry&&(e.material=s[e.uuid])}}));for(let t of Object.keys(s))delete s[t]}}class Xj{constructor(t,e,n,i){this._depth_of_field_node=t,this._scene=e,this._camera=n,this._resolution=i,this._camera_uniforms={mNear:{value:0},mFar:{value:0}},this.enabled=!0,this.needsSwap=!0,this.clear=!0,this.renderToScreen=!0,this._processing_scene=new vs,this.clear_color=new D.a(1,1,1),this._prev_clear_color=new D.a,this._core_scene=new qj(this._scene);const s=3,r=4;this._processing_camera=new ot.a(this._resolution.x/-2,this._resolution.x/2,this._resolution.y/2,this._resolution.y/-2,-1e4,1e4),this._processing_camera.position.z=100,this._processing_scene.add(this._processing_camera);var o={minFilter:w.V,magFilter:w.V,format:w.ic};this._rtTextureDepth=new Q(this._resolution.x,this._resolution.y,o),this._rtTextureColor=new Q(this._resolution.x,this._resolution.y,o);var a=jj;a||console.error(\\\\\\\"BokehPass relies on BokehShader\\\\\\\"),this.bokeh_uniforms=I.clone(a.uniforms),this.bokeh_uniforms.tColor.value=this._rtTextureColor.texture,this.bokeh_uniforms.tDepth.value=this._rtTextureDepth.texture,this.bokeh_uniforms.textureWidth.value=this._resolution.x,this.bokeh_uniforms.textureHeight.value=this._resolution.y,this.bokeh_material=new F({uniforms:this.bokeh_uniforms,vertexShader:a.vertexShader,fragmentShader:a.fragmentShader,defines:{RINGS:s,SAMPLES:r}}),this._quad=new B.a(new L(this._resolution.x,this._resolution.y),this.bokeh_material),this._quad.position.z=-500,this._processing_scene.add(this._quad);var l=Wj;l||console.error(\\\\\\\"BokehPass relies on BokehDepthShader\\\\\\\"),this.materialDepth=new F({uniforms:l.uniforms,vertexShader:l.vertexShader,fragmentShader:l.fragmentShader}),this.materialDepthInstance=new F({uniforms:l.uniforms,vertexShader:\\\\\\\"#include \\\\n\\\\nvec3 rotate_with_quat( vec3 v, vec4 q )\\\\n{\\\\n\\\\treturn v + 2.0 * cross( q.xyz, cross( q.xyz, v ) + q.w * v );\\\\n}\\\\n\\\\n\\\\nattribute vec4 instanceOrientation;\\\\nattribute vec3 instancePosition;\\\\nattribute vec3 instanceScale;\\\\nvarying float vViewZDepth;\\\\n\\\\n\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec3 v_POLYGON_instance_transform1_position = vec3(position);\\\\n\\\\tv_POLYGON_instance_transform1_position *= instanceScale;\\\\n\\\\tv_POLYGON_instance_transform1_position = rotate_with_quat( v_POLYGON_instance_transform1_position, instanceOrientation );\\\\n\\\\tv_POLYGON_instance_transform1_position += instancePosition;\\\\n\\\\t\\\\n\\\\t// replaces #include \\\\n\\\\tvec3 transformed = v_POLYGON_instance_transform1_position;\\\\n\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvViewZDepth = - mvPosition.z;\\\\n}\\\\\\\",fragmentShader:l.fragmentShader}),this.update_camera_uniforms_with_node(this._depth_of_field_node,this._camera)}setSize(t,e){this._rtTextureDepth.setSize(t,e),this._rtTextureColor.setSize(t,e),this.bokeh_uniforms.textureWidth.value=t,this.bokeh_uniforms.textureHeight.value=e}dispose(){this._rtTextureDepth.dispose(),this._rtTextureColor.dispose()}render(t,e,n){t.getClearColor(this._prev_clear_color),t.setClearColor(this.clear_color),t.clear(),t.setRenderTarget(this._rtTextureColor),t.clear(),t.render(this._scene,this._camera),t.setClearColor(0),this._core_scene.with_overriden_material(this.materialDepth,this.materialDepthInstance,this._camera_uniforms,(()=>{t.setRenderTarget(this._rtTextureDepth),t.clear(),t.render(this._scene,this._camera)})),t.setRenderTarget(null),t.clear(),t.render(this._processing_scene,this._processing_camera),t.setClearColor(this._prev_clear_color)}update_camera_uniforms_with_node(t,e){this.bokeh_uniforms.focalLength.value=e.getFocalLength(),this.bokeh_uniforms.znear.value=e.near,this.bokeh_uniforms.zfar.value=e.far;var n=$j.smoothstep(e.near,e.far,t.pv.focalDepth),i=$j.linearize(1-n,e.near,e.far);this.bokeh_uniforms.focalDepth.value=i,this._camera_uniforms={mNear:{value:e.near},mFar:{value:e.far}};for(let t of[this.materialDepth,this.materialDepthInstance])t.uniforms.mNear.value=this._camera_uniforms.mNear.value,t.uniforms.mFar.value=this._camera_uniforms.mFar.value}}const Yj=new class extends ua{constructor(){super(...arguments),this.focalDepth=ha.FLOAT(10,{range:[0,50],rangeLocked:[!0,!1],step:.001,...gj}),this.fStep=ha.FLOAT(10,{range:[.1,22],rangeLocked:[!0,!0],...gj}),this.maxBlur=ha.FLOAT(2,{range:[0,10],rangeLocked:[!0,!1],...gj}),this.vignetting=ha.BOOLEAN(0,{...gj}),this.depthBlur=ha.BOOLEAN(0,{...gj}),this.threshold=ha.FLOAT(.5,{range:[0,1],rangeLocked:[!0,!0],step:.001,...gj}),this.gain=ha.FLOAT(1,{range:[0,100],rangeLocked:[!0,!0],step:.001,...gj}),this.bias=ha.FLOAT(1,{range:[0,3],rangeLocked:[!0,!0],step:.001,...gj}),this.fringe=ha.FLOAT(.7,{range:[0,5],rangeLocked:[!0,!1],step:.001,...gj}),this.noise=ha.BOOLEAN(0,{...gj}),this.dithering=ha.FLOAT(0,{range:[0,.001],rangeLocked:[!0,!0],step:1e-4,...gj}),this.pentagon=ha.BOOLEAN(0,{...gj}),this.rings=ha.INTEGER(3,{range:[1,8],rangeLocked:[!0,!0],...gj}),this.samples=ha.INTEGER(4,{range:[1,13],rangeLocked:[!0,!0],...gj}),this.clearColor=ha.COLOR([1,1,1],{...gj})}};class $j extends vj{constructor(){super(...arguments),this.paramsConfig=Yj}static type(){return\\\\\\\"depthOfField\\\\\\\"}static saturate(t){return Math.max(0,Math.min(1,t))}static linearize(t,e,n){return-n*e/(t*(n-e)-n)}static smoothstep(t,e,n){var i=this.saturate((n-t)/(e-t));return i*i*(3-2*i)}_createPass(t){if(t.camera.isPerspectiveCamera){const e=t.camera_node;if(e){const n=new Xj(this,t.scene,e.object,t.resolution);this.updatePass(n);const i=new Mi(this.scene(),\\\\\\\"DOF\\\\\\\");return i.addGraphInput(e.p.near),i.addGraphInput(e.p.far),i.addGraphInput(e.p.fov),i.addGraphInput(this.p.focalDepth),i.addPostDirtyHook(\\\\\\\"post/DOF\\\\\\\",(()=>{this.update_pass_from_camera_node(n,e)})),n}}}update_pass_from_camera_node(t,e){t.update_camera_uniforms_with_node(this,e.object)}updatePass(t){t.bokeh_uniforms.fstop.value=this.pv.fStep,t.bokeh_uniforms.maxblur.value=this.pv.maxBlur,t.bokeh_uniforms.threshold.value=this.pv.threshold,t.bokeh_uniforms.gain.value=this.pv.gain,t.bokeh_uniforms.bias.value=this.pv.bias,t.bokeh_uniforms.fringe.value=this.pv.fringe,t.bokeh_uniforms.dithering.value=this.pv.dithering,t.bokeh_uniforms.noise.value=this.pv.noise?1:0,t.bokeh_uniforms.pentagon.value=this.pv.pentagon?1:0,t.bokeh_uniforms.vignetting.value=this.pv.vignetting?1:0,t.bokeh_uniforms.depthblur.value=this.pv.depthBlur?1:0,t.bokeh_uniforms.shaderFocus.value=0,t.bokeh_uniforms.showFocus.value=0,t.bokeh_uniforms.manualdof.value=0,t.bokeh_uniforms.focusCoords.value.set(.5,.5),t.bokeh_material.defines.RINGS=this.pv.rings,t.bokeh_material.defines.SAMPLES=this.pv.samples,t.bokeh_material.needsUpdate=!0,t.clear_color.copy(this.pv.clearColor)}}const Jj={uniforms:{tDiffuse:{value:null},tSize:{value:new d.a(256,256)},center:{value:new d.a(.5,.5)},angle:{value:1.57},scale:{value:1}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform vec2 center;\\\\n\\\\t\\\\tuniform float angle;\\\\n\\\\t\\\\tuniform float scale;\\\\n\\\\t\\\\tuniform vec2 tSize;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tfloat pattern() {\\\\n\\\\n\\\\t\\\\t\\\\tfloat s = sin( angle ), c = cos( angle );\\\\n\\\\n\\\\t\\\\t\\\\tvec2 tex = vUv * tSize - center;\\\\n\\\\t\\\\t\\\\tvec2 point = vec2( c * tex.x - s * tex.y, s * tex.x + c * tex.y ) * scale;\\\\n\\\\n\\\\t\\\\t\\\\treturn ( sin( point.x ) * sin( point.y ) ) * 4.0;\\\\n\\\\n\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 color = texture2D( tDiffuse, vUv );\\\\n\\\\n\\\\t\\\\t\\\\tfloat average = ( color.r + color.g + color.b ) / 3.0;\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( vec3( average * 10.0 - 5.0 + pattern() ), color.a );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const Zj=new class extends ua{constructor(){super(...arguments),this.center=ha.VECTOR2([.5,.5],{...gj}),this.angle=ha.FLOAT(\\\\\\\"$PI*0.5\\\\\\\",{range:[0,10],rangeLocked:[!1,!1],...gj}),this.scale=ha.FLOAT(1,{range:[0,1],rangeLocked:[!1,!1],...gj})}};class Qj extends vj{constructor(){super(...arguments),this.paramsConfig=Zj}static type(){return\\\\\\\"dotScreen\\\\\\\"}_createPass(t){const e=new Hm(Jj);return this.updatePass(e),e}updatePass(t){t.uniforms.center.value=this.pv.center,t.uniforms.angle.value=this.pv.angle,t.uniforms.scale.value=this.pv.scale}}const Kj={uniforms:{tDiffuse:{value:null},time:{value:0},nIntensity:{value:.5},sIntensity:{value:.05},sCount:{value:4096},grayscale:{value:1}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t// control parameter\\\\n\\\\t\\\\tuniform float time;\\\\n\\\\n\\\\t\\\\tuniform bool grayscale;\\\\n\\\\n\\\\t\\\\t// noise effect intensity value (0 = no effect, 1 = full effect)\\\\n\\\\t\\\\tuniform float nIntensity;\\\\n\\\\n\\\\t\\\\t// scanlines effect intensity value (0 = no effect, 1 = full effect)\\\\n\\\\t\\\\tuniform float sIntensity;\\\\n\\\\n\\\\t\\\\t// scanlines effect count value (0 = no effect, 4096 = full effect)\\\\n\\\\t\\\\tuniform float sCount;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t// sample the source\\\\n\\\\t\\\\t\\\\tvec4 cTextureScreen = texture2D( tDiffuse, vUv );\\\\n\\\\n\\\\t\\\\t// make some noise\\\\n\\\\t\\\\t\\\\tfloat dx = rand( vUv + time );\\\\n\\\\n\\\\t\\\\t// add noise\\\\n\\\\t\\\\t\\\\tvec3 cResult = cTextureScreen.rgb + cTextureScreen.rgb * clamp( 0.1 + dx, 0.0, 1.0 );\\\\n\\\\n\\\\t\\\\t// get us a sine and cosine\\\\n\\\\t\\\\t\\\\tvec2 sc = vec2( sin( vUv.y * sCount ), cos( vUv.y * sCount ) );\\\\n\\\\n\\\\t\\\\t// add scanlines\\\\n\\\\t\\\\t\\\\tcResult += cTextureScreen.rgb * vec3( sc.x, sc.y, sc.x ) * sIntensity;\\\\n\\\\n\\\\t\\\\t// interpolate between source and result by intensity\\\\n\\\\t\\\\t\\\\tcResult = cTextureScreen.rgb + clamp( nIntensity, 0.0,1.0 ) * ( cResult - cTextureScreen.rgb );\\\\n\\\\n\\\\t\\\\t// convert to grayscale if desired\\\\n\\\\t\\\\t\\\\tif( grayscale ) {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tcResult = vec3( cResult.r * 0.3 + cResult.g * 0.59 + cResult.b * 0.11 );\\\\n\\\\n\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( cResult, cTextureScreen.a );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};class tW extends km{constructor(t,e,n,i){super(),void 0===Kj&&console.error(\\\\\\\"THREE.FilmPass relies on FilmShader\\\\\\\");const s=Kj;this.uniforms=I.clone(s.uniforms),this.material=new F({uniforms:this.uniforms,vertexShader:s.vertexShader,fragmentShader:s.fragmentShader}),void 0!==i&&(this.uniforms.grayscale.value=i),void 0!==t&&(this.uniforms.nIntensity.value=t),void 0!==e&&(this.uniforms.sIntensity.value=e),void 0!==n&&(this.uniforms.sCount.value=n),this.fsQuad=new Vm(this.material)}render(t,e,n,i){this.uniforms.tDiffuse.value=n.texture,this.uniforms.time.value+=i,this.renderToScreen?(t.setRenderTarget(null),this.fsQuad.render(t)):(t.setRenderTarget(e),this.clear&&t.clear(),this.fsQuad.render(t))}}const eW=new class extends ua{constructor(){super(...arguments),this.noiseIntensity=ha.FLOAT(.5,{range:[0,1],rangeLocked:[!1,!1],...gj}),this.scanlinesIntensity=ha.FLOAT(.05,{range:[0,1],rangeLocked:[!0,!1],...gj}),this.scanlinesCount=ha.FLOAT(4096,{range:[0,4096],rangeLocked:[!0,!1],...gj}),this.grayscale=ha.BOOLEAN(1,{...gj})}};class nW extends vj{constructor(){super(...arguments),this.paramsConfig=eW}static type(){return\\\\\\\"film\\\\\\\"}_createPass(t){const e=new tW(this.pv.noiseIntensity,this.pv.scanlinesIntensity,this.pv.scanlinesCount,this.pv.grayscale?1:0);return this.updatePass(e),e}updatePass(t){t.uniforms.nIntensity.value=this.pv.noiseIntensity,t.uniforms.sIntensity.value=this.pv.scanlinesIntensity,t.uniforms.sCount.value=this.pv.scanlinesCount,t.uniforms.grayscale.value=this.pv.grayscale?1:0}}const iW={uniforms:{tDiffuse:{value:null},resolution:{value:new d.a(1/1024,1/512)}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:'\\\\n\\\\n\\\\t\\\\tprecision highp float;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tuniform vec2 resolution;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\t#define FXAA_PC 1\\\\n\\\\t\\\\t#define FXAA_GLSL_100 1\\\\n\\\\t\\\\t#define FXAA_QUALITY_PRESET 12\\\\n\\\\n\\\\t\\\\t#define FXAA_GREEN_AS_LUMA 1\\\\n\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_PC_CONSOLE\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// The console algorithm for PC is included\\\\n\\\\t\\\\t\\\\t\\\\t// for developers targeting really low spec machines.\\\\n\\\\t\\\\t\\\\t\\\\t// Likely better to just run FXAA_PC, and use a really low preset.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_PC_CONSOLE 0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_GLSL_120\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_GLSL_120 0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_GLSL_130\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_GLSL_130 0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_HLSL_3\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_HLSL_3 0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_HLSL_4\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_HLSL_4 0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_HLSL_5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_HLSL_5 0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*==========================================================================*/\\\\n\\\\t\\\\t#ifndef FXAA_GREEN_AS_LUMA\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// For those using non-linear color,\\\\n\\\\t\\\\t\\\\t\\\\t// and either not able to get luma in alpha, or not wanting to,\\\\n\\\\t\\\\t\\\\t\\\\t// this enables FXAA to run using green as a proxy for luma.\\\\n\\\\t\\\\t\\\\t\\\\t// So with this enabled, no need to pack luma in alpha.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// This will turn off AA on anything which lacks some amount of green.\\\\n\\\\t\\\\t\\\\t\\\\t// Pure red and blue or combination of only R and B, will get no AA.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Might want to lower the settings for both,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t\\\\tfxaaConsoleEdgeThresholdMin\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t\\\\tfxaaQualityEdgeThresholdMin\\\\n\\\\t\\\\t\\\\t\\\\t// In order to insure AA does not get turned off on colors\\\\n\\\\t\\\\t\\\\t\\\\t// which contain a minor amount of green.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// 1 = On.\\\\n\\\\t\\\\t\\\\t\\\\t// 0 = Off.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_GREEN_AS_LUMA 0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_EARLY_EXIT\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Controls algorithm\\\\'s early exit path.\\\\n\\\\t\\\\t\\\\t\\\\t// On PS3 turning this ON adds 2 cycles to the shader.\\\\n\\\\t\\\\t\\\\t\\\\t// On 360 turning this OFF adds 10ths of a millisecond to the shader.\\\\n\\\\t\\\\t\\\\t\\\\t// Turning this off on console will result in a more blurry image.\\\\n\\\\t\\\\t\\\\t\\\\t// So this defaults to on.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// 1 = On.\\\\n\\\\t\\\\t\\\\t\\\\t// 0 = Off.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_EARLY_EXIT 1\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_DISCARD\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only valid for PC OpenGL currently.\\\\n\\\\t\\\\t\\\\t\\\\t// Probably will not work when FXAA_GREEN_AS_LUMA = 1.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// 1 = Use discard on pixels which don\\\\'t need AA.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t\\\\t For APIs which enable concurrent TEX+ROP from same surface.\\\\n\\\\t\\\\t\\\\t\\\\t// 0 = Return unchanged color on pixels which don\\\\'t need AA.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_DISCARD 0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_FAST_PIXEL_OFFSET\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Used for GLSL 120 only.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// 1 = GL API supports fast pixel offsets\\\\n\\\\t\\\\t\\\\t\\\\t// 0 = do not use fast pixel offsets\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t#ifdef GL_EXT_gpu_shader4\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FXAA_FAST_PIXEL_OFFSET 1\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#ifdef GL_NV_gpu_shader5\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FXAA_FAST_PIXEL_OFFSET 1\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#ifdef GL_ARB_gpu_shader5\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FXAA_FAST_PIXEL_OFFSET 1\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#ifndef FXAA_FAST_PIXEL_OFFSET\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FXAA_FAST_PIXEL_OFFSET 0\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#ifndef FXAA_GATHER4_ALPHA\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// 1 = API supports gather4 on alpha channel.\\\\n\\\\t\\\\t\\\\t\\\\t// 0 = API does not support gather4 on alpha channel.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t#if (FXAA_HLSL_5 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FXAA_GATHER4_ALPHA 1\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#ifdef GL_ARB_gpu_shader5\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FXAA_GATHER4_ALPHA 1\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#ifdef GL_NV_gpu_shader5\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FXAA_GATHER4_ALPHA 1\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#ifndef FXAA_GATHER4_ALPHA\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FXAA_GATHER4_ALPHA 0\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\n\\\\t\\\\t/*============================================================================\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFXAA QUALITY - TUNING KNOBS\\\\n\\\\t\\\\t------------------------------------------------------------------------------\\\\n\\\\t\\\\tNOTE the other tuning knobs are now in the shader function inputs!\\\\n\\\\t\\\\t============================================================================*/\\\\n\\\\t\\\\t#ifndef FXAA_QUALITY_PRESET\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Choose the quality preset.\\\\n\\\\t\\\\t\\\\t\\\\t// This needs to be compiled into the shader as it effects code.\\\\n\\\\t\\\\t\\\\t\\\\t// Best option to include multiple presets is to\\\\n\\\\t\\\\t\\\\t\\\\t// in each shader define the preset, then include this file.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// OPTIONS\\\\n\\\\t\\\\t\\\\t\\\\t// -----------------------------------------------------------------------\\\\n\\\\t\\\\t\\\\t\\\\t// 10 to 15 - default medium dither (10=fastest, 15=highest quality)\\\\n\\\\t\\\\t\\\\t\\\\t// 20 to 29 - less dither, more expensive (20=fastest, 29=highest quality)\\\\n\\\\t\\\\t\\\\t\\\\t// 39\\\\t\\\\t\\\\t - no dither, very expensive\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// NOTES\\\\n\\\\t\\\\t\\\\t\\\\t// -----------------------------------------------------------------------\\\\n\\\\t\\\\t\\\\t\\\\t// 12 = slightly faster then FXAA 3.9 and higher edge quality (default)\\\\n\\\\t\\\\t\\\\t\\\\t// 13 = about same speed as FXAA 3.9 and better than 12\\\\n\\\\t\\\\t\\\\t\\\\t// 23 = closest to FXAA 3.9 visually and performance wise\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t_ = the lowest digit is directly related to performance\\\\n\\\\t\\\\t\\\\t\\\\t// _\\\\t= the highest digit is directly related to style\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PRESET 12\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\n\\\\t\\\\t/*============================================================================\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t FXAA QUALITY - PRESETS\\\\n\\\\n\\\\t\\\\t============================================================================*/\\\\n\\\\n\\\\t\\\\t/*============================================================================\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t FXAA QUALITY - MEDIUM DITHER PRESETS\\\\n\\\\t\\\\t============================================================================*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 10)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 3\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 3.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 12.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 11)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 4\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 3.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 12.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 12)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 12.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 13)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 6\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 12.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 14)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 7\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 12.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 15)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 8\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P7 12.0\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\t/*============================================================================\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t FXAA QUALITY - LOW DITHER PRESETS\\\\n\\\\t\\\\t============================================================================*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 20)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 3\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 21)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 4\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 22)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 23)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 6\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 24)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 7\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 3.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 25)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 8\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P7 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 26)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 9\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P7 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P8 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 27)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 10\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P7 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P8 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P9 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 28)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 11\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P7 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P8 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P9 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P10 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 29)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 12\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P7 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P8 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P9 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P10 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P11 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\t/*============================================================================\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t FXAA QUALITY - EXTREME QUALITY\\\\n\\\\t\\\\t============================================================================*/\\\\n\\\\t\\\\t#if (FXAA_QUALITY_PRESET == 39)\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_PS 12\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P0 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P1 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P2 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P3 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P4 1.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P5 1.5\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P6 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P7 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P8 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P9 2.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P10 4.0\\\\n\\\\t\\\\t\\\\t\\\\t#define FXAA_QUALITY_P11 8.0\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\n\\\\n\\\\t\\\\t/*============================================================================\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tAPI PORTING\\\\n\\\\n\\\\t\\\\t============================================================================*/\\\\n\\\\t\\\\t#if (FXAA_GLSL_100 == 1) || (FXAA_GLSL_120 == 1) || (FXAA_GLSL_130 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaBool bool\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaDiscard discard\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaFloat float\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaFloat2 vec2\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaFloat3 vec3\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaFloat4 vec4\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaHalf float\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaHalf2 vec2\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaHalf3 vec3\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaHalf4 vec4\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaInt2 ivec2\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaSat(x) clamp(x, 0.0, 1.0)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTex sampler2D\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaBool bool\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaDiscard clip(-1)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaFloat float\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaFloat2 float2\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaFloat3 float3\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaFloat4 float4\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaHalf half\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaHalf2 half2\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaHalf3 half3\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaHalf4 half4\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaSat(x) saturate(x)\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_GLSL_100 == 1)\\\\n\\\\t\\\\t\\\\t#define FxaaTexTop(t, p) texture2D(t, p, 0.0)\\\\n\\\\t\\\\t\\\\t#define FxaaTexOff(t, p, o, r) texture2D(t, p + (o * r), 0.0)\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_GLSL_120 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t// Requires,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t#version 120\\\\n\\\\t\\\\t\\\\t\\\\t// And at least,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t#extension GL_EXT_gpu_shader4 : enable\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t(or set FXAA_FAST_PIXEL_OFFSET 1 to work like DX9)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexTop(t, p) texture2DLod(t, p, 0.0)\\\\n\\\\t\\\\t\\\\t\\\\t#if (FXAA_FAST_PIXEL_OFFSET == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexOff(t, p, o, r) texture2DLodOffset(t, p, 0.0, o)\\\\n\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexOff(t, p, o, r) texture2DLod(t, p + (o * r), 0.0)\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#if (FXAA_GATHER4_ALPHA == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t// use #extension GL_ARB_gpu_shader5 : enable\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexAlpha4(t, p) textureGather(t, p, 3)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexOffAlpha4(t, p, o) textureGatherOffset(t, p, o, 3)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexGreen4(t, p) textureGather(t, p, 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexOffGreen4(t, p, o) textureGatherOffset(t, p, o, 1)\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_GLSL_130 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t// Requires \\\\\\\"#version 130\\\\\\\" or better\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexTop(t, p) textureLod(t, p, 0.0)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexOff(t, p, o, r) textureLodOffset(t, p, 0.0, o)\\\\n\\\\t\\\\t\\\\t\\\\t#if (FXAA_GATHER4_ALPHA == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t// use #extension GL_ARB_gpu_shader5 : enable\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexAlpha4(t, p) textureGather(t, p, 3)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexOffAlpha4(t, p, o) textureGatherOffset(t, p, o, 3)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexGreen4(t, p) textureGather(t, p, 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define FxaaTexOffGreen4(t, p, o) textureGatherOffset(t, p, o, 1)\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_HLSL_3 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaInt2 float2\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTex sampler2D\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexTop(t, p) tex2Dlod(t, float4(p, 0.0, 0.0))\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexOff(t, p, o, r) tex2Dlod(t, float4(p + (o * r), 0, 0))\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_HLSL_4 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaInt2 int2\\\\n\\\\t\\\\t\\\\t\\\\tstruct FxaaTex { SamplerState smpl; Texture2D tex; };\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexTop(t, p) t.tex.SampleLevel(t.smpl, p, 0.0)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexOff(t, p, o, r) t.tex.SampleLevel(t.smpl, p, 0.0, o)\\\\n\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t#if (FXAA_HLSL_5 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaInt2 int2\\\\n\\\\t\\\\t\\\\t\\\\tstruct FxaaTex { SamplerState smpl; Texture2D tex; };\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexTop(t, p) t.tex.SampleLevel(t.smpl, p, 0.0)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexOff(t, p, o, r) t.tex.SampleLevel(t.smpl, p, 0.0, o)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexAlpha4(t, p) t.tex.GatherAlpha(t.smpl, p)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexOffAlpha4(t, p, o) t.tex.GatherAlpha(t.smpl, p, o)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexGreen4(t, p) t.tex.GatherGreen(t.smpl, p)\\\\n\\\\t\\\\t\\\\t\\\\t#define FxaaTexOffGreen4(t, p, o) t.tex.GatherGreen(t.smpl, p, o)\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\n\\\\t\\\\t/*============================================================================\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t GREEN AS LUMA OPTION SUPPORT FUNCTION\\\\n\\\\t\\\\t============================================================================*/\\\\n\\\\t\\\\t#if (FXAA_GREEN_AS_LUMA == 0)\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat FxaaLuma(FxaaFloat4 rgba) { return rgba.w; }\\\\n\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat FxaaLuma(FxaaFloat4 rgba) { return rgba.y; }\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\n\\\\n\\\\n\\\\t\\\\t/*============================================================================\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t FXAA3 QUALITY - PC\\\\n\\\\n\\\\t\\\\t============================================================================*/\\\\n\\\\t\\\\t#if (FXAA_PC == 1)\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\tFxaaFloat4 FxaaPixelShader(\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Use noperspective interpolation here (turn off perspective interpolation).\\\\n\\\\t\\\\t\\\\t\\\\t// {xy} = center of pixel\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat2 pos,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Used only for FXAA Console, and not used on the 360 version.\\\\n\\\\t\\\\t\\\\t\\\\t// Use noperspective interpolation here (turn off perspective interpolation).\\\\n\\\\t\\\\t\\\\t\\\\t// {xy_} = upper left of pixel\\\\n\\\\t\\\\t\\\\t\\\\t// {_zw} = lower right of pixel\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat4 fxaaConsolePosPos,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Input color texture.\\\\n\\\\t\\\\t\\\\t\\\\t// {rgb_} = color in linear or perceptual color space\\\\n\\\\t\\\\t\\\\t\\\\t// if (FXAA_GREEN_AS_LUMA == 0)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t\\\\t {__a} = luma in perceptual color space (not linear)\\\\n\\\\t\\\\t\\\\t\\\\tFxaaTex tex,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on the optimized 360 version of FXAA Console.\\\\n\\\\t\\\\t\\\\t\\\\t// For everything but 360, just use the same input here as for \\\\\\\"tex\\\\\\\".\\\\n\\\\t\\\\t\\\\t\\\\t// For 360, same texture, just alias with a 2nd sampler.\\\\n\\\\t\\\\t\\\\t\\\\t// This sampler needs to have an exponent bias of -1.\\\\n\\\\t\\\\t\\\\t\\\\tFxaaTex fxaaConsole360TexExpBiasNegOne,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on the optimized 360 version of FXAA Console.\\\\n\\\\t\\\\t\\\\t\\\\t// For everything but 360, just use the same input here as for \\\\\\\"tex\\\\\\\".\\\\n\\\\t\\\\t\\\\t\\\\t// For 360, same texture, just alias with a 3nd sampler.\\\\n\\\\t\\\\t\\\\t\\\\t// This sampler needs to have an exponent bias of -2.\\\\n\\\\t\\\\t\\\\t\\\\tFxaaTex fxaaConsole360TexExpBiasNegTwo,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Quality.\\\\n\\\\t\\\\t\\\\t\\\\t// This must be from a constant/uniform.\\\\n\\\\t\\\\t\\\\t\\\\t// {x_} = 1.0/screenWidthInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {_y} = 1.0/screenHeightInPixels\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat2 fxaaQualityRcpFrame,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Console.\\\\n\\\\t\\\\t\\\\t\\\\t// This must be from a constant/uniform.\\\\n\\\\t\\\\t\\\\t\\\\t// This effects sub-pixel AA quality and inversely sharpness.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Where N ranges between,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t\\\\t N = 0.50 (default)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t\\\\t N = 0.33 (sharper)\\\\n\\\\t\\\\t\\\\t\\\\t// {x__} = -N/screenWidthInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {_y_} = -N/screenHeightInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {_z_} =\\\\tN/screenWidthInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {__w} =\\\\tN/screenHeightInPixels\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat4 fxaaConsoleRcpFrameOpt,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Console.\\\\n\\\\t\\\\t\\\\t\\\\t// Not used on 360, but used on PS3 and PC.\\\\n\\\\t\\\\t\\\\t\\\\t// This must be from a constant/uniform.\\\\n\\\\t\\\\t\\\\t\\\\t// {x__} = -2.0/screenWidthInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {_y_} = -2.0/screenHeightInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {_z_} =\\\\t2.0/screenWidthInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {__w} =\\\\t2.0/screenHeightInPixels\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat4 fxaaConsoleRcpFrameOpt2,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Console.\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on 360 in place of fxaaConsoleRcpFrameOpt2.\\\\n\\\\t\\\\t\\\\t\\\\t// This must be from a constant/uniform.\\\\n\\\\t\\\\t\\\\t\\\\t// {x__} =\\\\t8.0/screenWidthInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {_y_} =\\\\t8.0/screenHeightInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {_z_} = -4.0/screenWidthInPixels\\\\n\\\\t\\\\t\\\\t\\\\t// {__w} = -4.0/screenHeightInPixels\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat4 fxaaConsole360RcpFrameOpt2,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Quality.\\\\n\\\\t\\\\t\\\\t\\\\t// This used to be the FXAA_QUALITY_SUBPIX define.\\\\n\\\\t\\\\t\\\\t\\\\t// It is here now to allow easier tuning.\\\\n\\\\t\\\\t\\\\t\\\\t// Choose the amount of sub-pixel aliasing removal.\\\\n\\\\t\\\\t\\\\t\\\\t// This can effect sharpness.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 1.00 - upper limit (softer)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.75 - default amount of filtering\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.50 - lower limit (sharper, less sub-pixel aliasing removal)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.25 - almost off\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.00 - completely off\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat fxaaQualitySubpix,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Quality.\\\\n\\\\t\\\\t\\\\t\\\\t// This used to be the FXAA_QUALITY_EDGE_THRESHOLD define.\\\\n\\\\t\\\\t\\\\t\\\\t// It is here now to allow easier tuning.\\\\n\\\\t\\\\t\\\\t\\\\t// The minimum amount of local contrast required to apply algorithm.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.333 - too little (faster)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.250 - low quality\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.166 - default\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.125 - high quality\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.063 - overkill (slower)\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat fxaaQualityEdgeThreshold,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Quality.\\\\n\\\\t\\\\t\\\\t\\\\t// This used to be the FXAA_QUALITY_EDGE_THRESHOLD_MIN define.\\\\n\\\\t\\\\t\\\\t\\\\t// It is here now to allow easier tuning.\\\\n\\\\t\\\\t\\\\t\\\\t// Trims the algorithm from processing darks.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.0833 - upper limit (default, the start of visible unfiltered edges)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.0625 - high quality (faster)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.0312 - visible limit (slower)\\\\n\\\\t\\\\t\\\\t\\\\t// Special notes when using FXAA_GREEN_AS_LUMA,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Likely want to set this to zero.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t As colors that are mostly not-green\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t will appear very dark in the green channel!\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Tune by looking at mostly non-green content,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t then start at zero and increase until aliasing is a problem.\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat fxaaQualityEdgeThresholdMin,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Console.\\\\n\\\\t\\\\t\\\\t\\\\t// This used to be the FXAA_CONSOLE_EDGE_SHARPNESS define.\\\\n\\\\t\\\\t\\\\t\\\\t// It is here now to allow easier tuning.\\\\n\\\\t\\\\t\\\\t\\\\t// This does not effect PS3, as this needs to be compiled in.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Use FXAA_CONSOLE_PS3_EDGE_SHARPNESS for PS3.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Due to the PS3 being ALU bound,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t there are only three safe values here: 2 and 4 and 8.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t These options use the shaders ability to a free *|/ by 2|4|8.\\\\n\\\\t\\\\t\\\\t\\\\t// For all other platforms can be a non-power of two.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 8.0 is sharper (default!!!)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 4.0 is softer\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 2.0 is really soft (good only for vector graphics inputs)\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat fxaaConsoleEdgeSharpness,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Console.\\\\n\\\\t\\\\t\\\\t\\\\t// This used to be the FXAA_CONSOLE_EDGE_THRESHOLD define.\\\\n\\\\t\\\\t\\\\t\\\\t// It is here now to allow easier tuning.\\\\n\\\\t\\\\t\\\\t\\\\t// This does not effect PS3, as this needs to be compiled in.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Use FXAA_CONSOLE_PS3_EDGE_THRESHOLD for PS3.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Due to the PS3 being ALU bound,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t there are only two safe values here: 1/4 and 1/8.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t These options use the shaders ability to a free *|/ by 2|4|8.\\\\n\\\\t\\\\t\\\\t\\\\t// The console setting has a different mapping than the quality setting.\\\\n\\\\t\\\\t\\\\t\\\\t// Other platforms can use other values.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.125 leaves less aliasing, but is softer (default!!!)\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.25 leaves more aliasing, and is sharper\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat fxaaConsoleEdgeThreshold,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Only used on FXAA Console.\\\\n\\\\t\\\\t\\\\t\\\\t// This used to be the FXAA_CONSOLE_EDGE_THRESHOLD_MIN define.\\\\n\\\\t\\\\t\\\\t\\\\t// It is here now to allow easier tuning.\\\\n\\\\t\\\\t\\\\t\\\\t// Trims the algorithm from processing darks.\\\\n\\\\t\\\\t\\\\t\\\\t// The console setting has a different mapping than the quality setting.\\\\n\\\\t\\\\t\\\\t\\\\t// This only applies when FXAA_EARLY_EXIT is 1.\\\\n\\\\t\\\\t\\\\t\\\\t// This does not apply to PS3,\\\\n\\\\t\\\\t\\\\t\\\\t// PS3 was simplified to avoid more shader instructions.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.06 - faster but more aliasing in darks\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.05 - default\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t 0.04 - slower and less aliasing in darks\\\\n\\\\t\\\\t\\\\t\\\\t// Special notes when using FXAA_GREEN_AS_LUMA,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Likely want to set this to zero.\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t As colors that are mostly not-green\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t will appear very dark in the green channel!\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t Tune by looking at mostly non-green content,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\t then start at zero and increase until aliasing is a problem.\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat fxaaConsoleEdgeThresholdMin,\\\\n\\\\t\\\\t\\\\t\\\\t//\\\\n\\\\t\\\\t\\\\t\\\\t// Extra constants for 360 FXAA Console only.\\\\n\\\\t\\\\t\\\\t\\\\t// Use zeros or anything else for other platforms.\\\\n\\\\t\\\\t\\\\t\\\\t// These must be in physical constant registers and NOT immediates.\\\\n\\\\t\\\\t\\\\t\\\\t// Immediates will result in compiler un-optimizing.\\\\n\\\\t\\\\t\\\\t\\\\t// {xyzw} = float4(1.0, -1.0, 0.25, -0.25)\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat4 fxaaConsole360ConstDir\\\\n\\\\t\\\\t) {\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat2 posM;\\\\n\\\\t\\\\t\\\\t\\\\tposM.x = pos.x;\\\\n\\\\t\\\\t\\\\t\\\\tposM.y = pos.y;\\\\n\\\\t\\\\t\\\\t\\\\t#if (FXAA_GATHER4_ALPHA == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_DISCARD == 0)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat4 rgbyM = FxaaTexTop(tex, posM);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_GREEN_AS_LUMA == 0)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaM rgbyM.w\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaM rgbyM.y\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_GREEN_AS_LUMA == 0)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat4 luma4A = FxaaTexAlpha4(tex, posM);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat4 luma4B = FxaaTexOffAlpha4(tex, posM, FxaaInt2(-1, -1));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat4 luma4A = FxaaTexGreen4(tex, posM);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat4 luma4B = FxaaTexOffGreen4(tex, posM, FxaaInt2(-1, -1));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_DISCARD == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaM luma4A.w\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaE luma4A.z\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaS luma4A.x\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaSE luma4A.y\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaNW luma4B.w\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaN luma4B.z\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaW luma4B.x\\\\n\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat4 rgbyM = FxaaTexTop(tex, posM);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_GREEN_AS_LUMA == 0)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaM rgbyM.w\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#define lumaM rgbyM.y\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_GLSL_100 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaS = FxaaLuma(FxaaTexOff(tex, posM, FxaaFloat2( 0.0, 1.0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaE = FxaaLuma(FxaaTexOff(tex, posM, FxaaFloat2( 1.0, 0.0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaN = FxaaLuma(FxaaTexOff(tex, posM, FxaaFloat2( 0.0,-1.0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaW = FxaaLuma(FxaaTexOff(tex, posM, FxaaFloat2(-1.0, 0.0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaS = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2( 0, 1), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaE = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2( 1, 0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaN = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2( 0,-1), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaW = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2(-1, 0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat maxSM = max(lumaS, lumaM);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat minSM = min(lumaS, lumaM);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat maxESM = max(lumaE, maxSM);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat minESM = min(lumaE, minSM);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat maxWN = max(lumaN, lumaW);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat minWN = min(lumaN, lumaW);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat rangeMax = max(maxWN, maxESM);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat rangeMin = min(minWN, minESM);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat rangeMaxScaled = rangeMax * fxaaQualityEdgeThreshold;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat range = rangeMax - rangeMin;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat rangeMaxClamped = max(fxaaQualityEdgeThresholdMin, rangeMaxScaled);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool earlyExit = range < rangeMaxClamped;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tif(earlyExit)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_DISCARD == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaDiscard;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\treturn rgbyM;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t#if (FXAA_GATHER4_ALPHA == 0)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_GLSL_100 == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNW = FxaaLuma(FxaaTexOff(tex, posM, FxaaFloat2(-1.0,-1.0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaSE = FxaaLuma(FxaaTexOff(tex, posM, FxaaFloat2( 1.0, 1.0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNE = FxaaLuma(FxaaTexOff(tex, posM, FxaaFloat2( 1.0,-1.0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaSW = FxaaLuma(FxaaTexOff(tex, posM, FxaaFloat2(-1.0, 1.0), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNW = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2(-1,-1), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaSE = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2( 1, 1), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNE = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2( 1,-1), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaSW = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2(-1, 1), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNE = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2(1, -1), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaSW = FxaaLuma(FxaaTexOff(tex, posM, FxaaInt2(-1, 1), fxaaQualityRcpFrame.xy));\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNS = lumaN + lumaS;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaWE = lumaW + lumaE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixRcpRange = 1.0/range;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixNSWE = lumaNS + lumaWE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeHorz1 = (-2.0 * lumaM) + lumaNS;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeVert1 = (-2.0 * lumaM) + lumaWE;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNESE = lumaNE + lumaSE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNWNE = lumaNW + lumaNE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeHorz2 = (-2.0 * lumaE) + lumaNESE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeVert2 = (-2.0 * lumaN) + lumaNWNE;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNWSW = lumaNW + lumaSW;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaSWSE = lumaSW + lumaSE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeHorz4 = (abs(edgeHorz1) * 2.0) + abs(edgeHorz2);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeVert4 = (abs(edgeVert1) * 2.0) + abs(edgeVert2);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeHorz3 = (-2.0 * lumaW) + lumaNWSW;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeVert3 = (-2.0 * lumaS) + lumaSWSE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeHorz = abs(edgeHorz3) + edgeHorz4;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat edgeVert = abs(edgeVert3) + edgeVert4;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixNWSWNESE = lumaNWSW + lumaNESE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lengthSign = fxaaQualityRcpFrame.x;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool horzSpan = edgeHorz >= edgeVert;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixA = subpixNSWE * 2.0 + subpixNWSWNESE;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tif(!horzSpan) lumaN = lumaW;\\\\n\\\\t\\\\t\\\\t\\\\tif(!horzSpan) lumaS = lumaE;\\\\n\\\\t\\\\t\\\\t\\\\tif(horzSpan) lengthSign = fxaaQualityRcpFrame.y;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixB = (subpixA * (1.0/12.0)) - lumaM;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat gradientN = lumaN - lumaM;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat gradientS = lumaS - lumaM;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaNN = lumaN + lumaM;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaSS = lumaS + lumaM;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool pairN = abs(gradientN) >= abs(gradientS);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat gradient = max(abs(gradientN), abs(gradientS));\\\\n\\\\t\\\\t\\\\t\\\\tif(pairN) lengthSign = -lengthSign;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixC = FxaaSat(abs(subpixB) * subpixRcpRange);\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat2 posB;\\\\n\\\\t\\\\t\\\\t\\\\tposB.x = posM.x;\\\\n\\\\t\\\\t\\\\t\\\\tposB.y = posM.y;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat2 offNP;\\\\n\\\\t\\\\t\\\\t\\\\toffNP.x = (!horzSpan) ? 0.0 : fxaaQualityRcpFrame.x;\\\\n\\\\t\\\\t\\\\t\\\\toffNP.y = ( horzSpan) ? 0.0 : fxaaQualityRcpFrame.y;\\\\n\\\\t\\\\t\\\\t\\\\tif(!horzSpan) posB.x += lengthSign * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\tif( horzSpan) posB.y += lengthSign * 0.5;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat2 posN;\\\\n\\\\t\\\\t\\\\t\\\\tposN.x = posB.x - offNP.x * FXAA_QUALITY_P0;\\\\n\\\\t\\\\t\\\\t\\\\tposN.y = posB.y - offNP.y * FXAA_QUALITY_P0;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat2 posP;\\\\n\\\\t\\\\t\\\\t\\\\tposP.x = posB.x + offNP.x * FXAA_QUALITY_P0;\\\\n\\\\t\\\\t\\\\t\\\\tposP.y = posB.y + offNP.y * FXAA_QUALITY_P0;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixD = ((-2.0)*subpixC) + 3.0;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaEndN = FxaaLuma(FxaaTexTop(tex, posN));\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixE = subpixC * subpixC;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaEndP = FxaaLuma(FxaaTexTop(tex, posP));\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tif(!pairN) lumaNN = lumaSS;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat gradientScaled = gradient * 1.0/4.0;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat lumaMM = lumaM - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixF = subpixD * subpixE;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool lumaMLTZero = lumaMM < 0.0;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tlumaEndN -= lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\tlumaEndP -= lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool doneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool doneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P1;\\\\n\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P1;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool doneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P1;\\\\n\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P1;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P2;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P2;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P2;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P2;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 3)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P3;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P3;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P3;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P3;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 4)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P4;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P4;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P4;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P4;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 5)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P5;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 6)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P6;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P6;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P6;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P6;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 7)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P7;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P7;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P7;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P7;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 8)\\\\n\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P8;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P8;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P8;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P8;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 9)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P9;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P9;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P9;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P9;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 10)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P10;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P10;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P10;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P10;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 11)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P11;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P11;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P11;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P11;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#if (FXAA_QUALITY_PS > 12)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(doneNP) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = FxaaLuma(FxaaTexTop(tex, posN.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = FxaaLuma(FxaaTexTop(tex, posP.xy));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) lumaEndN = lumaEndN - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) lumaEndP = lumaEndP - lumaNN * 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneN = abs(lumaEndN) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneP = abs(lumaEndP) >= gradientScaled;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.x -= offNP.x * FXAA_QUALITY_P12;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneN) posN.y -= offNP.y * FXAA_QUALITY_P12;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdoneNP = (!doneN) || (!doneP);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.x += offNP.x * FXAA_QUALITY_P12;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tif(!doneP) posP.y += offNP.y * FXAA_QUALITY_P12;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat dstN = posM.x - posN.x;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat dstP = posP.x - posM.x;\\\\n\\\\t\\\\t\\\\t\\\\tif(!horzSpan) dstN = posM.y - posN.y;\\\\n\\\\t\\\\t\\\\t\\\\tif(!horzSpan) dstP = posP.y - posM.y;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool goodSpanN = (lumaEndN < 0.0) != lumaMLTZero;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat spanLength = (dstP + dstN);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool goodSpanP = (lumaEndP < 0.0) != lumaMLTZero;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat spanLengthRcp = 1.0/spanLength;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool directionN = dstN < dstP;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat dst = min(dstN, dstP);\\\\n\\\\t\\\\t\\\\t\\\\tFxaaBool goodSpan = directionN ? goodSpanN : goodSpanP;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixG = subpixF * subpixF;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat pixelOffset = (dst * (-spanLengthRcp)) + 0.5;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat subpixH = subpixG * fxaaQualitySubpix;\\\\n\\\\t\\\\t/*--------------------------------------------------------------------------*/\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat pixelOffsetGood = goodSpan ? pixelOffset : 0.0;\\\\n\\\\t\\\\t\\\\t\\\\tFxaaFloat pixelOffsetSubpix = max(pixelOffsetGood, subpixH);\\\\n\\\\t\\\\t\\\\t\\\\tif(!horzSpan) posM.x += pixelOffsetSubpix * lengthSign;\\\\n\\\\t\\\\t\\\\t\\\\tif( horzSpan) posM.y += pixelOffsetSubpix * lengthSign;\\\\n\\\\t\\\\t\\\\t\\\\t#if (FXAA_DISCARD == 1)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\treturn FxaaTexTop(tex, posM);\\\\n\\\\t\\\\t\\\\t\\\\t#else\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\treturn FxaaFloat4(FxaaTexTop(tex, posM).xyz, lumaM);\\\\n\\\\t\\\\t\\\\t\\\\t#endif\\\\n\\\\t\\\\t}\\\\n\\\\t\\\\t/*==========================================================================*/\\\\n\\\\t\\\\t#endif\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\tgl_FragColor = FxaaPixelShader(\\\\n\\\\t\\\\t\\\\t\\\\tvUv,\\\\n\\\\t\\\\t\\\\t\\\\tvec4(0.0),\\\\n\\\\t\\\\t\\\\t\\\\ttDiffuse,\\\\n\\\\t\\\\t\\\\t\\\\ttDiffuse,\\\\n\\\\t\\\\t\\\\t\\\\ttDiffuse,\\\\n\\\\t\\\\t\\\\t\\\\tresolution,\\\\n\\\\t\\\\t\\\\t\\\\tvec4(0.0),\\\\n\\\\t\\\\t\\\\t\\\\tvec4(0.0),\\\\n\\\\t\\\\t\\\\t\\\\tvec4(0.0),\\\\n\\\\t\\\\t\\\\t\\\\t0.75,\\\\n\\\\t\\\\t\\\\t\\\\t0.166,\\\\n\\\\t\\\\t\\\\t\\\\t0.0833,\\\\n\\\\t\\\\t\\\\t\\\\t0.0,\\\\n\\\\t\\\\t\\\\t\\\\t0.0,\\\\n\\\\t\\\\t\\\\t\\\\t0.0,\\\\n\\\\t\\\\t\\\\t\\\\tvec4(0.0)\\\\n\\\\t\\\\t\\\\t);\\\\n\\\\n\\\\t\\\\t\\\\t// TODO avoid querying texture twice for same texel\\\\n\\\\t\\\\t\\\\tgl_FragColor.a = texture2D(tDiffuse, vUv).a;\\\\n\\\\t\\\\t}'};const sW=new class extends ua{constructor(){super(...arguments),this.transparent=ha.BOOLEAN(1,gj)}};class rW extends vj{constructor(){super(...arguments),this.paramsConfig=sW}static type(){return\\\\\\\"FXAA\\\\\\\"}_createPass(t){const e=new Hm(iW);return e.uniforms.resolution.value.set(1/t.resolution.x,1/t.resolution.y),e.material.transparent=!0,this.updatePass(e),e}updatePass(t){t.material.transparent=this.pv.transparent}}const oW={uniforms:{tDiffuse:{value:null}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 tex = texture2D( tDiffuse, vUv );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = LinearTosRGB( tex ); // optional: LinearToGamma( tex, float( GAMMA_FACTOR ) );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const aW=new class extends ua{};class lW extends vj{constructor(){super(...arguments),this.paramsConfig=aW}static type(){return\\\\\\\"gammaCorrection\\\\\\\"}_createPass(t){const e=new Hm(oW);return this.updatePass(e),e}updatePass(t){}}const cW=new class extends ua{constructor(){super(...arguments),this.amount=ha.FLOAT(2,{range:[0,10],rangeLocked:[!0,!1],step:.01,...gj}),this.transparent=ha.BOOLEAN(1,gj)}};class hW extends vj{constructor(){super(...arguments),this.paramsConfig=cW}static type(){return\\\\\\\"horizontalBlur\\\\\\\"}_createPass(t){const e=new Hm(MG);return e.resolution_x=t.resolution.x,this.updatePass(e),e}updatePass(t){t.uniforms.h.value=this.pv.amount/(t.resolution_x*window.devicePixelRatio),t.material.transparent=this.pv.transparent}}const uW=new class extends ua{constructor(){super(...arguments),this.map=ha.OPERATOR_PATH(vi.UV,{nodeSelection:{context:ts.COP},...gj}),this.darkness=ha.FLOAT(0,{range:[0,2],rangeLocked:[!0,!1],...gj}),this.offset=ha.FLOAT(0,{range:[0,2],rangeLocked:[!0,!1],...gj})}};class dW extends vj{constructor(){super(...arguments),this.paramsConfig=uW}static type(){return\\\\\\\"image\\\\\\\"}static _create_shader(){return{uniforms:{tDiffuse:{value:null},map:{value:null},offset:{value:1},darkness:{value:1}},vertexShader:\\\\\\\"varying vec2 vUv;\\\\nvoid main() {\\\\n\\\\tvUv = uv;\\\\n\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n}\\\\\\\",fragmentShader:\\\\\\\"uniform float offset;\\\\nuniform float darkness;\\\\nuniform sampler2D tDiffuse;\\\\nuniform sampler2D map;\\\\nvarying vec2 vUv;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec4 texel = texture2D( tDiffuse, vUv );\\\\n\\\\tvec4 map_val = texture2D( map, vUv );\\\\n\\\\tvec2 uv = ( vUv - vec2( 0.5 ) ) * vec2( offset );\\\\n\\\\t// gl_FragColor = vec4( mix( texel.rgb, vec3( 1.0 - darkness ), dot( uv, uv ) ), texel.a );\\\\n\\\\tgl_FragColor = vec4( mix( texel.rgb, map_val.rgb, map_val.a ), texel.a );\\\\n\\\\n}\\\\n\\\\\\\"}}_createPass(t){const e=new Hm(dW._create_shader());return this.updatePass(e),e}updatePass(t){t.uniforms.darkness.value=this.pv.darkness,t.uniforms.offset.value=this.pv.offset,this._update_map(t)}async _update_map(t){this.p.map.isDirty()&&await this.p.map.compute();const e=this.p.map.found_node();if(e)if(e.context()==ts.COP){const n=e,i=(await n.compute()).coreContent();t.uniforms.map.value=i}else this.states.error.set(\\\\\\\"node is not COP\\\\\\\");else this.states.error.set(\\\\\\\"no map found\\\\\\\")}}const pW={tDiffuse:{value:null},texture1:{value:null},texture2:{value:null},h:{value:1/512}},_W=\\\\\\\"varying vec2 vUv;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvUv = uv;\\\\n\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n}\\\\\\\",mW=\\\\\\\"uniform sampler2D texture1;\\\\nuniform sampler2D texture2;\\\\nvarying vec2 vUv;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec4 t1 = texture2D( texture1, vUv);\\\\n\\\\tvec4 t2 = texture2D( texture2, vUv);\\\\n\\\\n\\\\tvec3 c1 = t1.rgb * t1.a * (1.0-t2.a);\\\\n\\\\tvec3 c2 = t2.rgb * t2.a;\\\\n\\\\tfloat a = t2.a + t1.a;\\\\n\\\\tvec3 c = max(c1,c2);\\\\n\\\\n\\\\tgl_FragColor = vec4(c,a);\\\\n\\\\n}\\\\\\\";class fW extends km{constructor(t,e){super(),this._composer1=t,this._composer2=e,this.uniforms=I.clone(pW),this.material=new F({uniforms:this.uniforms,vertexShader:_W,fragmentShader:mW,transparent:!0}),this.fsQuad=new Vm(this.material)}render(t,e){this._composer1.render(),this._composer2.render(),this.uniforms.texture1.value=this._composer1.readBuffer.texture,this.uniforms.texture2.value=this._composer2.readBuffer.texture,this.renderToScreen?(t.setRenderTarget(null),this.fsQuad.render(t)):(t.setRenderTarget(e),this.clear&&t.clear(t.autoClearColor,t.autoClearDepth,t.autoClearStencil),this.fsQuad.render(t))}}const gW=new class extends ua{};class vW extends vj{constructor(){super(...arguments),this.paramsConfig=gW}static type(){return\\\\\\\"layer\\\\\\\"}initializeNode(){super.initializeNode(),this.io.inputs.setCount(2)}setupComposer(t){const e=t.composer.renderer,n={minFilter:w.V,magFilter:w.V,format:w.Ib,stencilBuffer:!0},i=li.renderersController.renderTarget(e.domElement.offsetWidth,e.domElement.offsetHeight,n),s=li.renderersController.renderTarget(e.domElement.offsetWidth,e.domElement.offsetHeight,n),r=new qm(e,i),o=new qm(e,s);r.renderToScreen=!1,o.renderToScreen=!1;const a={...t},l={...t};a.composer=r,l.composer=o,this._addPassFromInput(0,a),this._addPassFromInput(1,l);const c=new fW(r,o);this.updatePass(c),t.composer.addPass(c)}updatePass(t){}}const yW=new class extends ua{constructor(){super(...arguments),this.overrideScene=ha.BOOLEAN(0,gj),this.scene=ha.OPERATOR_PATH(\\\\\\\"/scene1\\\\\\\",{visibleIf:{overrideScene:1},nodeSelection:{context:ts.OBJ,types:[VV.type()]},...gj}),this.overrideCamera=ha.BOOLEAN(0,gj),this.camera=ha.OPERATOR_PATH(\\\\\\\"/perspective_camera1\\\\\\\",{visibleIf:{overrideCamera:1},nodeSelection:{context:ts.OBJ},...gj}),this.inverse=ha.BOOLEAN(0,gj)}};class xW extends vj{constructor(){super(...arguments),this.paramsConfig=yW}static type(){return\\\\\\\"mask\\\\\\\"}_createPass(t){const e=new jm(t.scene,t.camera);return e.context={scene:t.scene,camera:t.camera},this.updatePass(e),e}updatePass(t){t.inverse=this.pv.inverse,this._update_scene(t),this._updateCamera(t)}async _update_scene(t){if(this.pv.overrideScene){this.p.scene.isDirty()&&await this.p.scene.compute();const e=this.p.scene.found_node_with_expected_type();if(e)return void(t.scene=e.object)}t.scene=t.context.scene}async _updateCamera(t){if(this.pv.overrideCamera){this.p.camera.isDirty()&&await this.p.camera.compute();const e=this.p.camera.found_node_with_expected_type();if(e)return void(t.camera=e.object)}t.camera=t.context.camera}}const bW=new class extends ua{};class wW extends vj{constructor(){super(...arguments),this.paramsConfig=bW}static type(){return\\\\\\\"null\\\\\\\"}}class TW extends km{constructor(t,e,n,i){super(),this.renderScene=e,this.renderCamera=n,this.selectedObjects=void 0!==i?i:[],this.visibleEdgeColor=new D.a(1,1,1),this.hiddenEdgeColor=new D.a(.1,.04,.02),this.edgeGlow=0,this.usePatternTexture=!1,this.edgeThickness=1,this.edgeStrength=3,this.downSampleRatio=2,this.pulsePeriod=0,this._visibilityCache=new Map,this.resolution=void 0!==t?new d.a(t.x,t.y):new d.a(256,256);const s={minFilter:w.V,magFilter:w.V,format:w.Ib},r=Math.round(this.resolution.x/this.downSampleRatio),o=Math.round(this.resolution.y/this.downSampleRatio);this.maskBufferMaterial=new lt.a({color:16777215}),this.maskBufferMaterial.side=w.z,this.renderTargetMaskBuffer=new Q(this.resolution.x,this.resolution.y,s),this.renderTargetMaskBuffer.texture.name=\\\\\\\"OutlinePass.mask\\\\\\\",this.renderTargetMaskBuffer.texture.generateMipmaps=!1,this.depthMaterial=new Sn,this.depthMaterial.side=w.z,this.depthMaterial.depthPacking=w.Hb,this.depthMaterial.blending=w.ub,this.prepareMaskMaterial=this.getPrepareMaskMaterial(),this.prepareMaskMaterial.side=w.z,this.prepareMaskMaterial.fragmentShader=function(t,e){var n=e.isPerspectiveCamera?\\\\\\\"perspective\\\\\\\":\\\\\\\"orthographic\\\\\\\";return t.replace(/DEPTH_TO_VIEW_Z/g,n+\\\\\\\"DepthToViewZ\\\\\\\")}(this.prepareMaskMaterial.fragmentShader,this.renderCamera),this.renderTargetDepthBuffer=new Q(this.resolution.x,this.resolution.y,s),this.renderTargetDepthBuffer.texture.name=\\\\\\\"OutlinePass.depth\\\\\\\",this.renderTargetDepthBuffer.texture.generateMipmaps=!1,this.renderTargetMaskDownSampleBuffer=new Q(r,o,s),this.renderTargetMaskDownSampleBuffer.texture.name=\\\\\\\"OutlinePass.depthDownSample\\\\\\\",this.renderTargetMaskDownSampleBuffer.texture.generateMipmaps=!1,this.renderTargetBlurBuffer1=new Q(r,o,s),this.renderTargetBlurBuffer1.texture.name=\\\\\\\"OutlinePass.blur1\\\\\\\",this.renderTargetBlurBuffer1.texture.generateMipmaps=!1,this.renderTargetBlurBuffer2=new Q(Math.round(r/2),Math.round(o/2),s),this.renderTargetBlurBuffer2.texture.name=\\\\\\\"OutlinePass.blur2\\\\\\\",this.renderTargetBlurBuffer2.texture.generateMipmaps=!1,this.edgeDetectionMaterial=this.getEdgeDetectionMaterial(),this.renderTargetEdgeBuffer1=new Q(r,o,s),this.renderTargetEdgeBuffer1.texture.name=\\\\\\\"OutlinePass.edge1\\\\\\\",this.renderTargetEdgeBuffer1.texture.generateMipmaps=!1,this.renderTargetEdgeBuffer2=new Q(Math.round(r/2),Math.round(o/2),s),this.renderTargetEdgeBuffer2.texture.name=\\\\\\\"OutlinePass.edge2\\\\\\\",this.renderTargetEdgeBuffer2.texture.generateMipmaps=!1;this.separableBlurMaterial1=this.getSeperableBlurMaterial(4),this.separableBlurMaterial1.uniforms.texSize.value.set(r,o),this.separableBlurMaterial1.uniforms.kernelRadius.value=1,this.separableBlurMaterial2=this.getSeperableBlurMaterial(4),this.separableBlurMaterial2.uniforms.texSize.value.set(Math.round(r/2),Math.round(o/2)),this.separableBlurMaterial2.uniforms.kernelRadius.value=4,this.overlayMaterial=this.getOverlayMaterial(),void 0===zm&&console.error(\\\\\\\"THREE.OutlinePass relies on CopyShader\\\\\\\");const a=zm;this.copyUniforms=I.clone(a.uniforms),this.copyUniforms.opacity.value=1,this.materialCopy=new F({uniforms:this.copyUniforms,vertexShader:a.vertexShader,fragmentShader:a.fragmentShader,blending:w.ub,depthTest:!1,depthWrite:!1,transparent:!0}),this.enabled=!0,this.needsSwap=!1,this._oldClearColor=new D.a,this.oldClearAlpha=1,this.fsQuad=new Vm(null),this.tempPulseColor1=new D.a,this.tempPulseColor2=new D.a,this.textureMatrix=new A.a}dispose(){this.renderTargetMaskBuffer.dispose(),this.renderTargetDepthBuffer.dispose(),this.renderTargetMaskDownSampleBuffer.dispose(),this.renderTargetBlurBuffer1.dispose(),this.renderTargetBlurBuffer2.dispose(),this.renderTargetEdgeBuffer1.dispose(),this.renderTargetEdgeBuffer2.dispose()}setSize(t,e){this.renderTargetMaskBuffer.setSize(t,e),this.renderTargetDepthBuffer.setSize(t,e);let n=Math.round(t/this.downSampleRatio),i=Math.round(e/this.downSampleRatio);this.renderTargetMaskDownSampleBuffer.setSize(n,i),this.renderTargetBlurBuffer1.setSize(n,i),this.renderTargetEdgeBuffer1.setSize(n,i),this.separableBlurMaterial1.uniforms.texSize.value.set(n,i),n=Math.round(n/2),i=Math.round(i/2),this.renderTargetBlurBuffer2.setSize(n,i),this.renderTargetEdgeBuffer2.setSize(n,i),this.separableBlurMaterial2.uniforms.texSize.value.set(n,i)}changeVisibilityOfSelectedObjects(t){const e=this._visibilityCache;function n(n){n.isMesh&&(!0===t?n.visible=e.get(n):(e.set(n,n.visible),n.visible=t))}for(let t=0;t0){t.getClearColor(this._oldClearColor),this.oldClearAlpha=t.getClearAlpha();const e=t.autoClear;t.autoClear=!1,s&&t.state.buffers.stencil.setTest(!1),t.setClearColor(16777215,1),this.changeVisibilityOfSelectedObjects(!1);const i=this.renderScene.background;if(this.renderScene.background=null,this.renderScene.overrideMaterial=this.depthMaterial,t.setRenderTarget(this.renderTargetDepthBuffer),t.clear(),t.render(this.renderScene,this.renderCamera),this.changeVisibilityOfSelectedObjects(!0),this._visibilityCache.clear(),this.updateTextureMatrix(),this.changeVisibilityOfNonSelectedObjects(!1),this.renderScene.overrideMaterial=this.prepareMaskMaterial,this.prepareMaskMaterial.uniforms.cameraNearFar.value.set(this.renderCamera.near,this.renderCamera.far),this.prepareMaskMaterial.uniforms.depthTexture.value=this.renderTargetDepthBuffer.texture,this.prepareMaskMaterial.uniforms.textureMatrix.value=this.textureMatrix,t.setRenderTarget(this.renderTargetMaskBuffer),t.clear(),t.render(this.renderScene,this.renderCamera),this.renderScene.overrideMaterial=null,this.changeVisibilityOfNonSelectedObjects(!0),this._visibilityCache.clear(),this.renderScene.background=i,this.fsQuad.material=this.materialCopy,this.copyUniforms.tDiffuse.value=this.renderTargetMaskBuffer.texture,t.setRenderTarget(this.renderTargetMaskDownSampleBuffer),t.clear(),this.fsQuad.render(t),this.tempPulseColor1.copy(this.visibleEdgeColor),this.tempPulseColor2.copy(this.hiddenEdgeColor),this.pulsePeriod>0){const t=.625+.75*Math.cos(.01*performance.now()/this.pulsePeriod)/2;this.tempPulseColor1.multiplyScalar(t),this.tempPulseColor2.multiplyScalar(t)}this.fsQuad.material=this.edgeDetectionMaterial,this.edgeDetectionMaterial.uniforms.maskTexture.value=this.renderTargetMaskDownSampleBuffer.texture,this.edgeDetectionMaterial.uniforms.texSize.value.set(this.renderTargetMaskDownSampleBuffer.width,this.renderTargetMaskDownSampleBuffer.height),this.edgeDetectionMaterial.uniforms.visibleEdgeColor.value=this.tempPulseColor1,this.edgeDetectionMaterial.uniforms.hiddenEdgeColor.value=this.tempPulseColor2,t.setRenderTarget(this.renderTargetEdgeBuffer1),t.clear(),this.fsQuad.render(t),this.fsQuad.material=this.separableBlurMaterial1,this.separableBlurMaterial1.uniforms.colorTexture.value=this.renderTargetEdgeBuffer1.texture,this.separableBlurMaterial1.uniforms.direction.value=TW.BlurDirectionX,this.separableBlurMaterial1.uniforms.kernelRadius.value=this.edgeThickness,t.setRenderTarget(this.renderTargetBlurBuffer1),t.clear(),this.fsQuad.render(t),this.separableBlurMaterial1.uniforms.colorTexture.value=this.renderTargetBlurBuffer1.texture,this.separableBlurMaterial1.uniforms.direction.value=TW.BlurDirectionY,t.setRenderTarget(this.renderTargetEdgeBuffer1),t.clear(),this.fsQuad.render(t),this.fsQuad.material=this.separableBlurMaterial2,this.separableBlurMaterial2.uniforms.colorTexture.value=this.renderTargetEdgeBuffer1.texture,this.separableBlurMaterial2.uniforms.direction.value=TW.BlurDirectionX,t.setRenderTarget(this.renderTargetBlurBuffer2),t.clear(),this.fsQuad.render(t),this.separableBlurMaterial2.uniforms.colorTexture.value=this.renderTargetBlurBuffer2.texture,this.separableBlurMaterial2.uniforms.direction.value=TW.BlurDirectionY,t.setRenderTarget(this.renderTargetEdgeBuffer2),t.clear(),this.fsQuad.render(t),this.fsQuad.material=this.overlayMaterial,this.overlayMaterial.uniforms.maskTexture.value=this.renderTargetMaskBuffer.texture,this.overlayMaterial.uniforms.edgeTexture1.value=this.renderTargetEdgeBuffer1.texture,this.overlayMaterial.uniforms.edgeTexture2.value=this.renderTargetEdgeBuffer2.texture,this.overlayMaterial.uniforms.patternTexture.value=this.patternTexture,this.overlayMaterial.uniforms.edgeStrength.value=this.edgeStrength,this.overlayMaterial.uniforms.edgeGlow.value=this.edgeGlow,this.overlayMaterial.uniforms.usePatternTexture.value=this.usePatternTexture,s&&t.state.buffers.stencil.setTest(!0),t.setRenderTarget(n),this.fsQuad.render(t),t.setClearColor(this._oldClearColor,this.oldClearAlpha),t.autoClear=e}this.renderToScreen&&(this.fsQuad.material=this.materialCopy,this.copyUniforms.tDiffuse.value=n.texture,t.setRenderTarget(null),this.fsQuad.render(t))}getPrepareMaskMaterial(){return new F({uniforms:{depthTexture:{value:null},cameraNearFar:{value:new d.a(.5,.5)},textureMatrix:{value:null}},vertexShader:\\\\\\\"#include \\\\n\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvarying vec4 projTexCoord;\\\\n\\\\t\\\\t\\\\t\\\\tvarying vec4 vPosition;\\\\n\\\\t\\\\t\\\\t\\\\tuniform mat4 textureMatrix;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\t\\\\t\\\\t\\\\t\\\\t#include \\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvPosition = mvPosition;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 worldPosition = modelMatrix * vec4( transformed, 1.0 );\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tprojTexCoord = textureMatrix * worldPosition;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"#include \\\\n\\\\t\\\\t\\\\t\\\\tvarying vec4 vPosition;\\\\n\\\\t\\\\t\\\\t\\\\tvarying vec4 projTexCoord;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D depthTexture;\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec2 cameraNearFar;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat depth = unpackRGBAToDepth(texture2DProj( depthTexture, projTexCoord ));\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat viewZ = - DEPTH_TO_VIEW_Z( depth, cameraNearFar.x, cameraNearFar.y );\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat depthTest = (-vPosition.z > viewZ) ? 1.0 : 0.0;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor = vec4(0.0, depthTest, 1.0, 1.0);\\\\n\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\"})}getEdgeDetectionMaterial(){return new F({uniforms:{maskTexture:{value:null},texSize:{value:new d.a(.5,.5)},visibleEdgeColor:{value:new p.a(1,1,1)},hiddenEdgeColor:{value:new p.a(1,1,1)}},vertexShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D maskTexture;\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec2 texSize;\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec3 visibleEdgeColor;\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec3 hiddenEdgeColor;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec2 invSize = 1.0 / texSize;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 uvOffset = vec4(1.0, 0.0, 0.0, 1.0) * vec4(invSize, invSize);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 c1 = texture2D( maskTexture, vUv + uvOffset.xy);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 c2 = texture2D( maskTexture, vUv - uvOffset.xy);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 c3 = texture2D( maskTexture, vUv + uvOffset.yw);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 c4 = texture2D( maskTexture, vUv - uvOffset.yw);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat diff1 = (c1.r - c2.r)*0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat diff2 = (c3.r - c4.r)*0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat d = length( vec2(diff1, diff2) );\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat a1 = min(c1.g, c2.g);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat a2 = min(c3.g, c4.g);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat visibilityFactor = min(a1, a2);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec3 edgeColor = 1.0 - visibilityFactor > 0.001 ? visibleEdgeColor : hiddenEdgeColor;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor = vec4(edgeColor, 1.0) * vec4(d);\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\"})}getSeperableBlurMaterial(t){return new F({defines:{MAX_RADIUS:t},uniforms:{colorTexture:{value:null},texSize:{value:new d.a(.5,.5)},direction:{value:new d.a(.5,.5)},kernelRadius:{value:1}},vertexShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"#include \\\\n\\\\t\\\\t\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D colorTexture;\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec2 texSize;\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec2 direction;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float kernelRadius;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tfloat gaussianPdf(in float x, in float sigma) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\treturn 0.39894 * exp( -0.5 * x * x/( sigma * sigma))/sigma;\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec2 invSize = 1.0 / texSize;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat weightSum = gaussianPdf(0.0, kernelRadius);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 diffuseSum = texture2D( colorTexture, vUv) * weightSum;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec2 delta = direction * invSize * kernelRadius/float(MAX_RADIUS);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec2 uvOffset = delta;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfor( int i = 1; i <= MAX_RADIUS; i ++ ) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tfloat w = gaussianPdf(uvOffset.x, kernelRadius);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tvec4 sample1 = texture2D( colorTexture, vUv + uvOffset);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tvec4 sample2 = texture2D( colorTexture, vUv - uvOffset);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdiffuseSum += ((sample1 + sample2) * w);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tweightSum += (2.0 * w);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tuvOffset += delta;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor = diffuseSum/weightSum;\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\"})}getOverlayMaterial(){return new F({uniforms:{maskTexture:{value:null},edgeTexture1:{value:null},edgeTexture2:{value:null},patternTexture:{value:null},edgeStrength:{value:1},edgeGlow:{value:1},usePatternTexture:{value:0}},vertexShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D maskTexture;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D edgeTexture1;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D edgeTexture2;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D patternTexture;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float edgeStrength;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float edgeGlow;\\\\n\\\\t\\\\t\\\\t\\\\tuniform bool usePatternTexture;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 edgeValue1 = texture2D(edgeTexture1, vUv);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 edgeValue2 = texture2D(edgeTexture2, vUv);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 maskColor = texture2D(maskTexture, vUv);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 patternColor = texture2D(patternTexture, 6.0 * vUv);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat visibilityFactor = 1.0 - maskColor.g > 0.0 ? 1.0 : 0.5;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 edgeValue = edgeValue1 + edgeValue2 * edgeGlow;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec4 finalColor = edgeStrength * maskColor.r * edgeValue;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tif(usePatternTexture)\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tfinalColor += + visibilityFactor * (1.0 - maskColor.r) * (1.0 - patternColor.r);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor = finalColor;\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\",blending:w.e,depthTest:!1,depthWrite:!1,transparent:!0})}}TW.BlurDirectionX=new d.a(1,0),TW.BlurDirectionY=new d.a(0,1);const AW=new class extends ua{constructor(){super(...arguments),this.objectsMask=ha.STRING(\\\\\\\"*outlined*\\\\\\\",{...gj}),this.refreshObjects=ha.BUTTON(null,{...gj}),this.printObjects=ha.BUTTON(null,{cook:!1,callback:t=>{MW.PARAM_CALLBACK_printResolve(t)}}),this.edgeStrength=ha.FLOAT(3,{range:[0,10],rangeLocked:[!0,!1],...gj}),this.edgeThickness=ha.FLOAT(1,{range:[0,4],rangeLocked:[!0,!1],...gj}),this.edgeGlow=ha.FLOAT(0,{range:[0,1],rangeLocked:[!0,!1],...gj}),this.pulsePeriod=ha.FLOAT(0,{range:[0,5],rangeLocked:[!0,!1],...gj}),this.visibleEdgeColor=ha.COLOR([1,1,1],{...gj}),this.hiddenEdgeColor=ha.COLOR([.2,.1,.4],{...gj})}};class MW extends vj{constructor(){super(...arguments),this.paramsConfig=AW,this._resolvedObjects=[],this._map=new Map}static type(){return\\\\\\\"outline\\\\\\\"}_createPass(t){const e=new TW(new d.a(t.resolution.x,t.resolution.y),t.scene,t.camera,t.scene.children);return this.updatePass(e),e}updatePass(t){t.edgeStrength=this.pv.edgeStrength,t.edgeThickness=this.pv.edgeThickness,t.edgeGlow=this.pv.edgeGlow,t.pulsePeriod=this.pv.pulsePeriod,t.visibleEdgeColor=this.pv.visibleEdgeColor,t.hiddenEdgeColor=this.pv.hiddenEdgeColor,this._setSelectedObjects(t)}_setSelectedObjects(t){const e=this.scene().objectsByMask(this.pv.objectsMask);this._map.clear();for(let t of e)this._map.set(t.uuid,t);this._resolvedObjects=e.filter((t=>{let e=!1;return t.traverseAncestors((t=>{this._map.has(t.uuid)&&(e=!0)})),!e})),t.selectedObjects=this._resolvedObjects}static PARAM_CALLBACK_printResolve(t){t.printResolve()}printResolve(){console.log(this._resolvedObjects)}}const EW={uniforms:{tDiffuse:{value:null},resolution:{value:null},pixelSize:{value:1}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying highp vec2 vUv;\\\\n\\\\n\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\t\\\\tuniform float pixelSize;\\\\n\\\\t\\\\tuniform vec2 resolution;\\\\n\\\\n\\\\t\\\\tvarying highp vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main(){\\\\n\\\\n\\\\t\\\\t\\\\tvec2 dxy = pixelSize / resolution;\\\\n\\\\t\\\\t\\\\tvec2 coord = dxy * floor( vUv / dxy );\\\\n\\\\t\\\\t\\\\tgl_FragColor = texture2D(tDiffuse, coord);\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const SW=new class extends ua{constructor(){super(...arguments),this.pixelSize=ha.INTEGER(16,{range:[1,50],rangeLocked:[!0,!1],...gj})}};class CW extends vj{constructor(){super(...arguments),this.paramsConfig=SW}static type(){return\\\\\\\"pixel\\\\\\\"}_createPass(t){const e=new Hm(EW);return e.uniforms.resolution.value=t.resolution,e.uniforms.resolution.value.multiplyScalar(window.devicePixelRatio),this.updatePass(e),e}updatePass(t){t.uniforms.pixelSize.value=this.pv.pixelSize}}const NW=new class extends ua{constructor(){super(...arguments),this.overrideScene=ha.BOOLEAN(0,gj),this.scene=ha.OPERATOR_PATH(\\\\\\\"/scene1\\\\\\\",{visibleIf:{overrideScene:1},nodeSelection:{context:ts.OBJ,types:[VV.type()]},...gj}),this.overrideCamera=ha.BOOLEAN(0,gj),this.camera=ha.OPERATOR_PATH(\\\\\\\"/perspective_camera1\\\\\\\",{visibleIf:{overrideCamera:1},nodeSelection:{context:ts.OBJ},...gj})}};class LW extends vj{constructor(){super(...arguments),this.paramsConfig=NW}static type(){return\\\\\\\"render\\\\\\\"}_createPass(t){const e=new Ym(t.scene,t.camera);return e.context={camera:t.camera,scene:t.scene},this.updatePass(e),e}updatePass(t){this._updateCamera(t),this._update_scene(t)}async _updateCamera(t){if(this.pv.overrideCamera){this.p.camera.isDirty()&&await this.p.camera.compute();const e=this.p.camera.found_node_with_context(ts.OBJ);if(e&&(e.type()==is.PERSPECTIVE||e.type()==is.ORTHOGRAPHIC)){const n=e.object;t.camera=n}}else t.camera=t.context.camera}async _update_scene(t){if(this.pv.overrideScene){this.p.camera.isDirty()&&await this.p.scene.compute();const e=this.p.scene.found_node_with_context(ts.OBJ);if(e&&e.type()==VV.type()){const n=e.object;t.scene=n}}else t.scene=t.context.scene}}const OW={uniforms:{tDiffuse:{value:null},amount:{value:.005},angle:{value:0}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\t\\\\tuniform float amount;\\\\n\\\\t\\\\tuniform float angle;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec2 offset = amount * vec2( cos(angle), sin(angle));\\\\n\\\\t\\\\t\\\\tvec4 cr = texture2D(tDiffuse, vUv + offset);\\\\n\\\\t\\\\t\\\\tvec4 cga = texture2D(tDiffuse, vUv);\\\\n\\\\t\\\\t\\\\tvec4 cb = texture2D(tDiffuse, vUv - offset);\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4(cr.r, cga.g, cb.b, cga.a);\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const PW=new class extends ua{constructor(){super(...arguments),this.amount=ha.FLOAT(.005,{range:[0,1],rangeLocked:[!0,!1],...gj}),this.angle=ha.FLOAT(0,{range:[0,10],rangeLocked:[!0,!1],...gj})}};class RW extends vj{constructor(){super(...arguments),this.paramsConfig=PW}static type(){return\\\\\\\"RGBShift\\\\\\\"}_createPass(t){const e=new Hm(OW);return this.updatePass(e),e}updatePass(t){t.uniforms.amount.value=this.pv.amount,t.uniforms.angle.value=this.pv.angle}}const IW={uniforms:{tDiffuse:{value:null},amount:{value:1}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform float amount;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 color = texture2D( tDiffuse, vUv );\\\\n\\\\t\\\\t\\\\tvec3 c = color.rgb;\\\\n\\\\n\\\\t\\\\t\\\\tcolor.r = dot( c, vec3( 1.0 - 0.607 * amount, 0.769 * amount, 0.189 * amount ) );\\\\n\\\\t\\\\t\\\\tcolor.g = dot( c, vec3( 0.349 * amount, 1.0 - 0.314 * amount, 0.168 * amount ) );\\\\n\\\\t\\\\t\\\\tcolor.b = dot( c, vec3( 0.272 * amount, 0.534 * amount, 1.0 - 0.869 * amount ) );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( min( vec3( 1.0 ), color.rgb ), color.a );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const FW=new class extends ua{constructor(){super(...arguments),this.amount=ha.FLOAT(.5,{range:[0,2],rangeLocked:[!1,!1],...gj})}};class DW extends vj{constructor(){super(...arguments),this.paramsConfig=FW}static type(){return\\\\\\\"sepia\\\\\\\"}_createPass(t){const e=new Hm(IW);return this.updatePass(e),e}updatePass(t){t.uniforms.amount.value=this.pv.amount}}const BW=new class extends ua{};class zW extends vj{constructor(){super(...arguments),this.paramsConfig=BW}static type(){return\\\\\\\"sequence\\\\\\\"}initializeNode(){super.initializeNode(),this.io.inputs.setCount(0,4)}setupComposer(t){this._addPassFromInput(0,t),this._addPassFromInput(1,t),this._addPassFromInput(2,t),this._addPassFromInput(3,t)}}const kW=I.clone(MG.uniforms);kW.delta={value:new d.a};const UW={uniforms:kW,vertexShader:MG.vertexShader,fragmentShader:\\\\\\\"\\\\n#include \\\\n#define ITERATIONS 10.0\\\\nuniform sampler2D tDiffuse;\\\\nuniform vec2 delta;\\\\nvarying vec2 vUv;\\\\nvoid main() {\\\\n\\\\tvec4 color = vec4( 0.0 );\\\\n\\\\tfloat total = 0.0;\\\\n\\\\tfloat offset = rand( vUv );\\\\n\\\\tfor ( float t = -ITERATIONS; t <= ITERATIONS; t ++ ) {\\\\n\\\\t\\\\tfloat percent = ( t + offset - 0.5 ) / ITERATIONS;\\\\n\\\\t\\\\tfloat weight = 1.0 - abs( percent );\\\\n\\\\t\\\\tcolor += texture2D( tDiffuse, vUv + delta * percent ) * weight;\\\\n\\\\t\\\\ttotal += weight;\\\\n\\\\t}\\\\n\\\\tgl_FragColor = color / total;\\\\n}\\\\\\\"};const GW=new class extends ua{constructor(){super(...arguments),this.delta=ha.VECTOR2([2,2],{...gj})}};class VW extends vj{constructor(){super(...arguments),this.paramsConfig=GW}static type(){return\\\\\\\"triangleBlur\\\\\\\"}_createPass(t){const e=new Hm(UW);return e.resolution=t.resolution.clone(),this.updatePass(e),e}updatePass(t){t.uniforms.delta.value.copy(this.pv.delta).divide(t.resolution).multiplyScalar(window.devicePixelRatio)}}const HW={shaderID:\\\\\\\"luminosityHighPass\\\\\\\",uniforms:{tDiffuse:{value:null},luminosityThreshold:{value:1},smoothWidth:{value:1},defaultColor:{value:new D.a(0)},defaultOpacity:{value:0}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\t\\\\tuniform vec3 defaultColor;\\\\n\\\\t\\\\tuniform float defaultOpacity;\\\\n\\\\t\\\\tuniform float luminosityThreshold;\\\\n\\\\t\\\\tuniform float smoothWidth;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvec4 texel = texture2D( tDiffuse, vUv );\\\\n\\\\n\\\\t\\\\t\\\\tvec3 luma = vec3( 0.299, 0.587, 0.114 );\\\\n\\\\n\\\\t\\\\t\\\\tfloat v = dot( texel.xyz, luma );\\\\n\\\\n\\\\t\\\\t\\\\tvec4 outputColor = vec4( defaultColor.rgb, defaultOpacity );\\\\n\\\\n\\\\t\\\\t\\\\tfloat alpha = smoothstep( luminosityThreshold, luminosityThreshold + smoothWidth, v );\\\\n\\\\n\\\\t\\\\t\\\\tgl_FragColor = mix( outputColor, texel, alpha );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};class jW extends km{constructor(t,e,n,i){super(),this.strength=void 0!==e?e:1,this.radius=n,this.threshold=i,this.resolution=void 0!==t?new d.a(t.x,t.y):new d.a(256,256),this.clearColor=new D.a(0,0,0);const s={minFilter:w.V,magFilter:w.V,format:w.Ib};this.renderTargetsHorizontal=[],this.renderTargetsVertical=[],this.nMips=5;let r=Math.round(this.resolution.x/2),o=Math.round(this.resolution.y/2);this.renderTargetBright=new Q(r,o,s),this.renderTargetBright.texture.name=\\\\\\\"UnrealBloomPass.bright\\\\\\\",this.renderTargetBright.texture.generateMipmaps=!1;for(let t=0;t\\\\n\\\\t\\\\t\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D colorTexture;\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec2 texSize;\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec2 direction;\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tfloat gaussianPdf(in float x, in float sigma) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\treturn 0.39894 * exp( -0.5 * x * x/( sigma * sigma))/sigma;\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec2 invSize = 1.0 / texSize;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat fSigma = float(SIGMA);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat weightSum = gaussianPdf(0.0, fSigma);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvec3 diffuseSum = texture2D( colorTexture, vUv).rgb * weightSum;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfor( int i = 1; i < KERNEL_RADIUS; i ++ ) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tfloat x = float(i);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tfloat w = gaussianPdf(x, fSigma);\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tvec2 uvOffset = direction * invSize * x;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tvec3 sample1 = texture2D( colorTexture, vUv + uvOffset).rgb;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tvec3 sample2 = texture2D( colorTexture, vUv - uvOffset).rgb;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tdiffuseSum += (sample1 + sample2) * w;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tweightSum += 2.0 * w;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor = vec4(diffuseSum/weightSum, 1.0);\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\"})}getCompositeMaterial(t){return new F({defines:{NUM_MIPS:t},uniforms:{blurTexture1:{value:null},blurTexture2:{value:null},blurTexture3:{value:null},blurTexture4:{value:null},blurTexture5:{value:null},dirtTexture:{value:null},bloomStrength:{value:1},bloomFactors:{value:null},bloomTintColors:{value:null},bloomRadius:{value:0}},vertexShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"varying vec2 vUv;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D blurTexture1;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D blurTexture2;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D blurTexture3;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D blurTexture4;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D blurTexture5;\\\\n\\\\t\\\\t\\\\t\\\\tuniform sampler2D dirtTexture;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float bloomStrength;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float bloomRadius;\\\\n\\\\t\\\\t\\\\t\\\\tuniform float bloomFactors[NUM_MIPS];\\\\n\\\\t\\\\t\\\\t\\\\tuniform vec3 bloomTintColors[NUM_MIPS];\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tfloat lerpBloomFactor(const in float factor) {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tfloat mirrorFactor = 1.2 - factor;\\\\n\\\\t\\\\t\\\\t\\\\t\\\\treturn mix(factor, mirrorFactor, bloomRadius);\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\n\\\\n\\\\t\\\\t\\\\t\\\\tvoid main() {\\\\n\\\\t\\\\t\\\\t\\\\t\\\\tgl_FragColor = bloomStrength * ( lerpBloomFactor(bloomFactors[0]) * vec4(bloomTintColors[0], 1.0) * texture2D(blurTexture1, vUv) +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tlerpBloomFactor(bloomFactors[1]) * vec4(bloomTintColors[1], 1.0) * texture2D(blurTexture2, vUv) +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tlerpBloomFactor(bloomFactors[2]) * vec4(bloomTintColors[2], 1.0) * texture2D(blurTexture3, vUv) +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tlerpBloomFactor(bloomFactors[3]) * vec4(bloomTintColors[3], 1.0) * texture2D(blurTexture4, vUv) +\\\\n\\\\t\\\\t\\\\t\\\\t\\\\t\\\\tlerpBloomFactor(bloomFactors[4]) * vec4(bloomTintColors[4], 1.0) * texture2D(blurTexture5, vUv) );\\\\n\\\\t\\\\t\\\\t\\\\t}\\\\\\\"})}}jW.BlurDirectionX=new d.a(1,0),jW.BlurDirectionY=new d.a(0,1);const WW=new class extends ua{constructor(){super(...arguments),this.strength=ha.FLOAT(1.5,{range:[0,3],rangeLocked:[!0,!1],...gj}),this.radius=ha.FLOAT(1,{...gj}),this.threshold=ha.FLOAT(0,{...gj})}};class qW extends vj{constructor(){super(...arguments),this.paramsConfig=WW}static type(){return\\\\\\\"unrealBloom\\\\\\\"}_createPass(t){return new jW(new d.a(t.resolution.x,t.resolution.y),this.pv.strength,this.pv.radius,this.pv.threshold)}updatePass(t){t.strength=this.pv.strength,t.radius=this.pv.radius,t.threshold=this.pv.threshold}}const XW=new class extends ua{constructor(){super(...arguments),this.amount=ha.FLOAT(2,{range:[0,10],rangeLocked:[!0,!1],step:.01,...gj}),this.transparent=ha.BOOLEAN(1,gj)}};class YW extends vj{constructor(){super(...arguments),this.paramsConfig=XW}static type(){return\\\\\\\"verticalBlur\\\\\\\"}_createPass(t){const e=new Hm(EG);return e.resolution_y=t.resolution.y,this.updatePass(e),e}updatePass(t){t.uniforms.v.value=this.pv.amount/(t.resolution_y*window.devicePixelRatio),t.material.transparent=this.pv.transparent}}const $W={uniforms:{tDiffuse:{value:null},offset:{value:1},darkness:{value:1}},vertexShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\tvUv = uv;\\\\n\\\\t\\\\t\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n\\\\t\\\\t}\\\\\\\",fragmentShader:\\\\\\\"\\\\n\\\\n\\\\t\\\\tuniform float offset;\\\\n\\\\t\\\\tuniform float darkness;\\\\n\\\\n\\\\t\\\\tuniform sampler2D tDiffuse;\\\\n\\\\n\\\\t\\\\tvarying vec2 vUv;\\\\n\\\\n\\\\t\\\\tvoid main() {\\\\n\\\\n\\\\t\\\\t\\\\t// Eskil's vignette\\\\n\\\\n\\\\t\\\\t\\\\tvec4 texel = texture2D( tDiffuse, vUv );\\\\n\\\\t\\\\t\\\\tvec2 uv = ( vUv - vec2( 0.5 ) ) * vec2( offset );\\\\n\\\\t\\\\t\\\\tgl_FragColor = vec4( mix( texel.rgb, vec3( 1.0 - darkness ), dot( uv, uv ) ), texel.a );\\\\n\\\\n\\\\t\\\\t}\\\\\\\"};const JW=new class extends ua{constructor(){super(...arguments),this.offset=ha.FLOAT(1,{range:[0,1],rangeLocked:[!1,!1],...gj}),this.darkness=ha.FLOAT(1,{range:[0,2],rangeLocked:[!0,!1],...gj})}};class ZW extends vj{constructor(){super(...arguments),this.paramsConfig=JW}static type(){return\\\\\\\"vignette\\\\\\\"}_createPass(t){const e=new Hm($W);return this.updatePass(e),e}updatePass(t){t.uniforms.offset.value=this.pv.offset,t.uniforms.darkness.value=this.pv.darkness}}class QW extends aa{static context(){return ts.POST}cook(){this.cookController.endCook()}}class KW extends QW{}class tq extends KW{constructor(){super(...arguments),this._children_controller_context=ts.ANIM}static type(){return es.ANIM}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class eq extends KW{constructor(){super(...arguments),this._children_controller_context=ts.COP}static type(){return es.COP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class nq extends KW{constructor(){super(...arguments),this._children_controller_context=ts.EVENT}static type(){return es.EVENT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class iq extends KW{constructor(){super(...arguments),this._children_controller_context=ts.MAT}static type(){return es.MAT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class sq extends QW{constructor(){super(...arguments),this.paramsConfig=new ef,this.effectsComposerController=new nf(this),this.displayNodeController=new Fm(this,this.effectsComposerController.displayNodeControllerCallbacks()),this._children_controller_context=ts.POST}static type(){return es.POST}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class rq extends KW{constructor(){super(...arguments),this._children_controller_context=ts.ROP}static type(){return es.ROP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class oq extends aa{static context(){return ts.ROP}cook(){this.cookController.endCook()}}class aq extends oq{}class lq extends aq{constructor(){super(...arguments),this._children_controller_context=ts.COP}static type(){return es.COP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class cq extends K.a{constructor(t){super(),this._element=t,this._element.style.position=\\\\\\\"absolute\\\\\\\",this.addEventListener(\\\\\\\"removed\\\\\\\",this._on_removed.bind(this))}_on_removed(){this.traverse((function(t){t instanceof cq&&t.element instanceof Element&&null!==t.element.parentNode&&t.element.parentNode.removeChild(t.element)}))}get element(){return this._element}clone(t){const e=this._element.cloneNode(!0);return new cq(e).copy(this,t)}copy(t,e){return K.a.prototype.copy.call(this,t,e),this._element=t.element.cloneNode(!0),this.matrixAutoUpdate=t.matrixAutoUpdate,this}}class hq{constructor(){this._width=0,this._height=0,this._widthHalf=0,this._heightHalf=0,this.vector=new p.a,this.viewMatrix=new A.a,this.viewProjectionMatrix=new A.a,this.cache_distanceToCameraSquared=new WeakMap,this.domElement=document.createElement(\\\\\\\"div\\\\\\\"),this._sort_objects=!1,this._use_fog=!1,this._fog_near=1,this._fog_far=100,this.a=new p.a,this.b=new p.a,this.domElement.classList.add(\\\\\\\"polygonjs-CSS2DRenderer\\\\\\\")}getSize(){return{width:this._width,height:this._height}}setSize(t,e){this._width=t,this._height=e,this._widthHalf=this._width/2,this._heightHalf=this._height/2,this.domElement.style.width=t+\\\\\\\"px\\\\\\\",this.domElement.style.height=e+\\\\\\\"px\\\\\\\"}renderObject(t,e,n){if(t instanceof cq){this.vector.setFromMatrixPosition(t.matrixWorld),this.vector.applyMatrix4(this.viewProjectionMatrix);var i=t.element,s=\\\\\\\"translate(-50%,-50%) translate(\\\\\\\"+(this.vector.x*this._widthHalf+this._widthHalf)+\\\\\\\"px,\\\\\\\"+(-this.vector.y*this._heightHalf+this._heightHalf)+\\\\\\\"px)\\\\\\\";if(i.style.webkitTransform=s,i.style.transform=s,i.style.display=t.visible&&this.vector.z>=-1&&this.vector.z<=1?\\\\\\\"\\\\\\\":\\\\\\\"none\\\\\\\",this._sort_objects||this._use_fog){const e=this.getDistanceToSquared(n,t);if(this._use_fog){const t=Math.sqrt(e),n=or.fit(t,this._fog_near,this._fog_far,0,1),s=or.clamp(1-n,0,1);i.style.opacity=`${s}`,0==s&&(i.style.display=\\\\\\\"none\\\\\\\")}this.cache_distanceToCameraSquared.set(t,e)}i.parentNode!==this.domElement&&this.domElement.appendChild(i)}for(var r=0,o=t.children.length;r{const n=this.cache_distanceToCameraSquared.get(t),i=this.cache_distanceToCameraSquared.get(e);return null!=n&&null!=i?n-i:0})),n=e.length;for(let t=0,i=e.length;t{this._update_renderer(t)})),this.cookController.endCook()}_update_renderer(t){t.set_sorting(this.pv.sortObjects),t.set_use_fog(this.pv.useFog),t.set_fog_range(this.pv.fogNear,this.pv.fogFar)}_update_css(){this.css_element().innerHTML=this.pv.css}css_element(){return this._css_element=this._css_element||this._find_element()||this._create_element()}_find_element(){return document.getElementById(this._css_element_id())}_create_element(){const t=document.createElement(\\\\\\\"style\\\\\\\");return t.appendChild(document.createTextNode(\\\\\\\"\\\\\\\")),document.head.appendChild(t),t.id=this._css_element_id(),t}_css_element_id(){return`css_2d_renderer-${this.graphNodeId()}`}}class pq extends aq{constructor(){super(...arguments),this._children_controller_context=ts.ANIM}static type(){return es.ANIM}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class _q extends aq{constructor(){super(...arguments),this._children_controller_context=ts.EVENT}static type(){return es.EVENT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class mq extends aq{constructor(){super(...arguments),this._children_controller_context=ts.MAT}static type(){return es.MAT}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class fq extends oq{constructor(){super(...arguments),this.paramsConfig=new ef,this.effectsComposerController=new nf(this),this.displayNodeController=new Fm(this,this.effectsComposerController.displayNodeControllerCallbacks()),this._children_controller_context=ts.POST}static type(){return es.POST}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class gq extends aq{constructor(){super(...arguments),this._children_controller_context=ts.ROP}static type(){return es.ROP}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}}class vq extends sV{static type(){return\\\\\\\"add\\\\\\\"}cook(t,e){const n=[];return this._create_point(n,e),this._create_polygon(t[0],n,e),this.createCoreGroupFromObjects(n)}_create_point(t,e){if(!e.createPoint)return;const n=new S.a,i=[];for(let t=0;t0&&this._create_polygon_open(t,e,n)}_create_polygon_open(t,e,n){const i=t.points();let s=[];const r=[];let o;for(let t=0;t0&&(r.push(t-1),r.push(t));if(i.length>2&&n.connectToLastPoint){i[0].position().toArray(s,s.length);const t=r[r.length-1];r.push(t),r.push(0)}const a=new S.a;a.setAttribute(\\\\\\\"position\\\\\\\",new C.c(s,3)),a.setIndex(r);const l=this.createObject(a,Ns.LINE_SEGMENTS);e.push(l)}}vq.DEFAULT_PARAMS={createPoint:!0,pointsCount:1,position:new p.a(0,0,0),connectInputPoints:!1,connectToLastPoint:!1};const yq=vq.DEFAULT_PARAMS;const xq=new class extends ua{constructor(){super(...arguments),this.createPoint=ha.BOOLEAN(yq.createPoint),this.pointsCount=ha.INTEGER(yq.pointsCount,{range:[1,100],rangeLocked:[!0,!1],visibleIf:{createPoint:!0}}),this.position=ha.VECTOR3(yq.position,{visibleIf:{createPoint:!0}}),this.connectInputPoints=ha.BOOLEAN(yq.connectInputPoints),this.connectToLastPoint=ha.BOOLEAN(yq.connectToLastPoint)}};class bq extends lV{constructor(){super(...arguments),this.paramsConfig=xq}static type(){return\\\\\\\"add\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to create polygons from (optional)\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1)}cook(t){this._operation=this._operation||new vq(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const wq=new class extends ua{};class Tq extends lV{constructor(){super(...arguments),this.paramsConfig=wq}static type(){return\\\\\\\"animationCopy\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to copy animation to\\\\\\\",\\\\\\\"geometry to copy animation from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(2),this.io.inputs.initInputsClonedState([Ki.FROM_NODE,Ki.NEVER])}cook(t){const e=t[0],n=t[1].objects()[0],i=e.objects()[0],s=n.animations;s?(i.animations=s.map((t=>t.clone())),this.setCoreGroup(e)):this.states.error.set(\\\\\\\"no animation found\\\\\\\")}}class Aq{constructor(t,e,n=null,i=e.blendMode){this._mixer=t,this._clip=e,this._localRoot=n,this.blendMode=i;const s=e.tracks,r=s.length,o=new Array(r),a={endingStart:w.id,endingEnd:w.id};for(let t=0;t!==r;++t){const e=s[t].createInterpolant(null);o[t]=e,e.settings=a}this._interpolantSettings=a,this._interpolants=o,this._propertyBindings=new Array(r),this._cacheIndex=null,this._byClipCacheIndex=null,this._timeScaleInterpolant=null,this._weightInterpolant=null,this.loop=w.eb,this._loopCount=-1,this._startTime=null,this.time=0,this.timeScale=1,this._effectiveTimeScale=1,this.weight=1,this._effectiveWeight=1,this.repetitions=1/0,this.paused=!1,this.enabled=!0,this.clampWhenFinished=!1,this.zeroSlopeAtStart=!0,this.zeroSlopeAtEnd=!0}play(){return this._mixer._activateAction(this),this}stop(){return this._mixer._deactivateAction(this),this.reset()}reset(){return this.paused=!1,this.enabled=!0,this.time=0,this._loopCount=-1,this._startTime=null,this.stopFading().stopWarping()}isRunning(){return this.enabled&&!this.paused&&0!==this.timeScale&&null===this._startTime&&this._mixer._isActiveAction(this)}isScheduled(){return this._mixer._isActiveAction(this)}startAt(t){return this._startTime=t,this}setLoop(t,e){return this.loop=t,this.repetitions=e,this}setEffectiveWeight(t){return this.weight=t,this._effectiveWeight=this.enabled?t:0,this.stopFading()}getEffectiveWeight(){return this._effectiveWeight}fadeIn(t){return this._scheduleFading(t,0,1)}fadeOut(t){return this._scheduleFading(t,1,0)}crossFadeFrom(t,e,n){if(t.fadeOut(e),this.fadeIn(e),n){const n=this._clip.duration,i=t._clip.duration,s=i/n,r=n/i;t.warp(1,s,e),this.warp(r,1,e)}return this}crossFadeTo(t,e,n){return t.crossFadeFrom(this,e,n)}stopFading(){const t=this._weightInterpolant;return null!==t&&(this._weightInterpolant=null,this._mixer._takeBackControlInterpolant(t)),this}setEffectiveTimeScale(t){return this.timeScale=t,this._effectiveTimeScale=this.paused?0:t,this.stopWarping()}getEffectiveTimeScale(){return this._effectiveTimeScale}setDuration(t){return this.timeScale=this._clip.duration/t,this.stopWarping()}syncWith(t){return this.time=t.time,this.timeScale=t.timeScale,this.stopWarping()}halt(t){return this.warp(this._effectiveTimeScale,0,t)}warp(t,e,n){const i=this._mixer,s=i.time,r=this.timeScale;let o=this._timeScaleInterpolant;null===o&&(o=i._lendControlInterpolant(),this._timeScaleInterpolant=o);const a=o.parameterPositions,l=o.sampleValues;return a[0]=s,a[1]=s+n,l[0]=t/r,l[1]=e/r,this}stopWarping(){const t=this._timeScaleInterpolant;return null!==t&&(this._timeScaleInterpolant=null,this._mixer._takeBackControlInterpolant(t)),this}getMixer(){return this._mixer}getClip(){return this._clip}getRoot(){return this._localRoot||this._mixer._root}_update(t,e,n,i){if(!this.enabled)return void this._updateWeight(t);const s=this._startTime;if(null!==s){const i=(t-s)*n;if(i<0||0===n)return;this._startTime=null,e=n*i}e*=this._updateTimeScale(t);const r=this._updateTime(e),o=this._updateWeight(t);if(o>0){const t=this._interpolants,e=this._propertyBindings;switch(this.blendMode){case w.d:for(let n=0,i=t.length;n!==i;++n)t[n].evaluate(r),e[n].accumulateAdditive(o);break;case w.wb:default:for(let n=0,s=t.length;n!==s;++n)t[n].evaluate(r),e[n].accumulate(i,o)}}}_updateWeight(t){let e=0;if(this.enabled){e=this.weight;const n=this._weightInterpolant;if(null!==n){const i=n.evaluate(t)[0];e*=i,t>n.parameterPositions[1]&&(this.stopFading(),0===i&&(this.enabled=!1))}}return this._effectiveWeight=e,e}_updateTimeScale(t){let e=0;if(!this.paused){e=this.timeScale;const n=this._timeScaleInterpolant;if(null!==n){e*=n.evaluate(t)[0],t>n.parameterPositions[1]&&(this.stopWarping(),0===e?this.paused=!0:this.timeScale=e)}}return this._effectiveTimeScale=e,e}_updateTime(t){const e=this._clip.duration,n=this.loop;let i=this.time+t,s=this._loopCount;const r=n===w.db;if(0===t)return-1===s?i:r&&1==(1&s)?e-i:i;if(n===w.cb){-1===s&&(this._loopCount=0,this._setEndings(!0,!0,!1));t:{if(i>=e)i=e;else{if(!(i<0)){this.time=i;break t}i=0}this.clampWhenFinished?this.paused=!0:this.enabled=!1,this.time=i,this._mixer.dispatchEvent({type:\\\\\\\"finished\\\\\\\",action:this,direction:t<0?-1:1})}}else{if(-1===s&&(t>=0?(s=0,this._setEndings(!0,0===this.repetitions,r)):this._setEndings(0===this.repetitions,!0,r)),i>=e||i<0){const n=Math.floor(i/e);i-=e*n,s+=Math.abs(n);const o=this.repetitions-s;if(o<=0)this.clampWhenFinished?this.paused=!0:this.enabled=!1,i=t>0?e:0,this.time=i,this._mixer.dispatchEvent({type:\\\\\\\"finished\\\\\\\",action:this,direction:t>0?1:-1});else{if(1===o){const e=t<0;this._setEndings(e,!e,r)}else this._setEndings(!1,!1,r);this._loopCount=s,this.time=i,this._mixer.dispatchEvent({type:\\\\\\\"loop\\\\\\\",action:this,loopDelta:n})}}else this.time=i;if(r&&1==(1&s))return e-i}return i}_setEndings(t,e,n){const i=this._interpolantSettings;n?(i.endingStart=w.kd,i.endingEnd=w.kd):(i.endingStart=t?this.zeroSlopeAtStart?w.kd:w.id:w.hd,i.endingEnd=e?this.zeroSlopeAtEnd?w.kd:w.id:w.hd)}_scheduleFading(t,e,n){const i=this._mixer,s=i.time;let r=this._weightInterpolant;null===r&&(r=i._lendControlInterpolant(),this._weightInterpolant=r);const o=r.parameterPositions,a=r.sampleValues;return o[0]=s,a[0]=e,o[1]=s+t,a[1]=n,this}}var Mq=n(71),Eq=n(66);class Sq{constructor(t,e,n){let i,s,r;switch(this.binding=t,this.valueSize=n,e){case\\\\\\\"quaternion\\\\\\\":i=this._slerp,s=this._slerpAdditive,r=this._setAdditiveIdentityQuaternion,this.buffer=new Float64Array(6*n),this._workIndex=5;break;case\\\\\\\"string\\\\\\\":case\\\\\\\"bool\\\\\\\":i=this._select,s=this._select,r=this._setAdditiveIdentityOther,this.buffer=new Array(5*n);break;default:i=this._lerp,s=this._lerpAdditive,r=this._setAdditiveIdentityNumeric,this.buffer=new Float64Array(5*n)}this._mixBufferRegion=i,this._mixBufferRegionAdditive=s,this._setIdentity=r,this._origIndex=3,this._addIndex=4,this.cumulativeWeight=0,this.cumulativeWeightAdditive=0,this.useCount=0,this.referenceCount=0}accumulate(t,e){const n=this.buffer,i=this.valueSize,s=t*i+i;let r=this.cumulativeWeight;if(0===r){for(let t=0;t!==i;++t)n[s+t]=n[t];r=e}else{r+=e;const t=e/r;this._mixBufferRegion(n,s,0,t,i)}this.cumulativeWeight=r}accumulateAdditive(t){const e=this.buffer,n=this.valueSize,i=n*this._addIndex;0===this.cumulativeWeightAdditive&&this._setIdentity(),this._mixBufferRegionAdditive(e,i,0,t,n),this.cumulativeWeightAdditive+=t}apply(t){const e=this.valueSize,n=this.buffer,i=t*e+e,s=this.cumulativeWeight,r=this.cumulativeWeightAdditive,o=this.binding;if(this.cumulativeWeight=0,this.cumulativeWeightAdditive=0,s<1){const t=e*this._origIndex;this._mixBufferRegion(n,i,t,1-s,e)}r>0&&this._mixBufferRegionAdditive(n,i,this._addIndex*e,1,e);for(let t=e,s=e+e;t!==s;++t)if(n[t]!==n[t+e]){o.setValue(n,i);break}}saveOriginalState(){const t=this.binding,e=this.buffer,n=this.valueSize,i=n*this._origIndex;t.getValue(e,i);for(let t=n,s=i;t!==s;++t)e[t]=e[i+t%n];this._setIdentity(),this.cumulativeWeight=0,this.cumulativeWeightAdditive=0}restoreOriginalState(){const t=3*this.valueSize;this.binding.setValue(this.buffer,t)}_setAdditiveIdentityNumeric(){const t=this._addIndex*this.valueSize,e=t+this.valueSize;for(let n=t;n=.5)for(let i=0;i!==s;++i)t[e+i]=t[n+i]}_slerp(t,e,n,i){hh.a.slerpFlat(t,e,t,e,t,n,i)}_slerpAdditive(t,e,n,i,s){const r=this._workIndex*s;hh.a.multiplyQuaternionsFlat(t,r,t,e,t,n),hh.a.slerpFlat(t,e,t,e,t,r,i)}_lerp(t,e,n,i,s){const r=1-i;for(let o=0;o!==s;++o){const s=e+o;t[s]=t[s]*r+t[n+o]*i}}_lerpAdditive(t,e,n,i,s){for(let r=0;r!==s;++r){const s=e+r;t[s]=t[s]+t[n+r]*i}}}var Cq=n(64);class Nq extends J.a{constructor(t){super(),this._root=t,this._initMemoryManager(),this._accuIndex=0,this.time=0,this.timeScale=1}_bindAction(t,e){const n=t._localRoot||this._root,i=t._clip.tracks,s=i.length,r=t._propertyBindings,o=t._interpolants,a=n.uuid,l=this._bindingsByRootAndName;let c=l[a];void 0===c&&(c={},l[a]=c);for(let t=0;t!==s;++t){const s=i[t],l=s.name;let h=c[l];if(void 0!==h)r[t]=h;else{if(h=r[t],void 0!==h){null===h._cacheIndex&&(++h.referenceCount,this._addInactiveBinding(h,a,l));continue}const i=e&&e._propertyBindings[t].binding.parsedPath;h=new Sq(Eq.a.create(n,l,i),s.ValueTypeName,s.getValueSize()),++h.referenceCount,this._addInactiveBinding(h,a,l),r[t]=h}o[t].resultBuffer=h.buffer}}_activateAction(t){if(!this._isActiveAction(t)){if(null===t._cacheIndex){const e=(t._localRoot||this._root).uuid,n=t._clip.uuid,i=this._actionsByClip[n];this._bindAction(t,i&&i.knownActions[0]),this._addInactiveAction(t,n,e)}const e=t._propertyBindings;for(let t=0,n=e.length;t!==n;++t){const n=e[t];0==n.useCount++&&(this._lendBinding(n),n.saveOriginalState())}this._lendAction(t)}}_deactivateAction(t){if(this._isActiveAction(t)){const e=t._propertyBindings;for(let t=0,n=e.length;t!==n;++t){const n=e[t];0==--n.useCount&&(n.restoreOriginalState(),this._takeBackBinding(n))}this._takeBackAction(t)}}_initMemoryManager(){this._actions=[],this._nActiveActions=0,this._actionsByClip={},this._bindings=[],this._nActiveBindings=0,this._bindingsByRootAndName={},this._controlInterpolants=[],this._nActiveControlInterpolants=0;const t=this;this.stats={actions:{get total(){return t._actions.length},get inUse(){return t._nActiveActions}},bindings:{get total(){return t._bindings.length},get inUse(){return t._nActiveBindings}},controlInterpolants:{get total(){return t._controlInterpolants.length},get inUse(){return t._nActiveControlInterpolants}}}}_isActiveAction(t){const e=t._cacheIndex;return null!==e&&e=0;--e)t[e].stop();return this}update(t){t*=this.timeScale;const e=this._actions,n=this._nActiveActions,i=this.time+=t,s=Math.sign(t),r=this._accuIndex^=1;for(let o=0;o!==n;++o){e[o]._update(i,t,s,r)}const o=this._bindings,a=this._nActiveBindings;for(let t=0;t!==a;++t)o[t].apply(r);return this}setTime(t){this.time=0;for(let t=0;t{Oq.PARAM_CALLBACK_reset(t,e)}})}};class Oq extends lV{constructor(){super(...arguments),this.paramsConfig=Lq}static type(){return\\\\\\\"animationMixer\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to be animated\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Ki.NEVER)}async cook(t){const e=t[0].objects()[0];e&&(await this.create_mixer_if_required(e),this._update_mixer()),this.setObjects([e])}async create_mixer_if_required(t){if(!this._mixer){const e=await this._create_mixer(t);e&&(this._mixer=e)}}async _create_mixer(t){this.p.clip.isDirty()&&await this.p.clip.compute();if(this.p.clip.found_node_with_context(ts.ANIM)){return new Nq(t)}}_update_mixer(){this._set_mixer_time()}_set_mixer_time(){this.pv.time!=this._previous_time&&(this._mixer&&this._mixer.setTime(this.pv.time),this._previous_time=this.pv.time)}static PARAM_CALLBACK_reset(t,e){e.setDirty(),t.reset_animation_mixer()}async reset_animation_mixer(){this._mixer=void 0,this._previous_time=void 0,this.setDirty()}}class Pq extends sV{static type(){return\\\\\\\"attribAddMult\\\\\\\"}cook(t,e){const n=t[0],i=n.attribNamesMatchingMask(e.name);for(let t of i){const i=n.geometries();for(let n of i)this._update_attrib(t,n,e)}return n}_update_attrib(t,e,n){const i=e.getAttribute(t);if(i){const t=i.array,e=n.preAdd,s=n.mult,r=n.postAdd;for(let n=0;n({name:t,value:e})))}})}};class Hq extends lV{constructor(){super(...arguments),this.paramsConfig=Vq}static type(){return\\\\\\\"attribCast\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Uq.INPUT_CLONED_STATE),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.type],(()=>Bq[this.pv.type]))}))}))}cook(t){this._operation=this._operation||new Uq(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class jq extends sV{static type(){return\\\\\\\"attribCopy\\\\\\\"}cook(t,e){const n=t[0],i=t[1]||n,s=i.attribNamesMatchingMask(e.name);for(let t of s)this.copy_vertex_attribute_between_core_groups(n,i,t,e);return n}copy_vertex_attribute_between_core_groups(t,e,n,i){var s;const r=e.objectsWithGeo(),o=t.objectsWithGeo();if(o.length>r.length)null===(s=this.states)||void 0===s||s.error.set(\\\\\\\"second input does not have enough objects to copy attributes from\\\\\\\");else for(let t=0;ta&&(null===(s=this.states)||void 0===s||s.error.set(\\\\\\\"not enough points in second input\\\\\\\"));const c=i.tnewName?i.newName:n;let h=t.getAttribute(c);if(h)this._fill_dest_array(h,o,i),h.needsUpdate=!0;else{const e=o.array.slice(0,l*r);t.setAttribute(c,new C.c(e,r))}}else null===(r=this.states)||void 0===r||r.error.set(`attribute '${n}' does not exist on second input`)}_fill_dest_array(t,e,n){const i=t.array,s=e.array,r=i.length,o=t.itemSize,a=e.itemSize,l=n.srcOffset,c=n.destOffset;if(t.itemSize==e.itemSize){t.copyArray(e.array);for(let t=0;t{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name,this.p.tnewName,this.p.newName],(()=>this.pv.tnewName?`${this.pv.name} -> ${this.pv.newName}`:this.pv.name))}))}))}cook(t){this._operation=this._operation||new jq(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class Yq extends sV{static type(){return\\\\\\\"attribCreate\\\\\\\"}cook(t,e){var n;const i=t[0];return e.name&&\\\\\\\"\\\\\\\"!=e.name.trim()?this._add_attribute(Ds[e.class],i,e):null===(n=this.states)||void 0===n||n.error.set(\\\\\\\"attribute name is not valid\\\\\\\"),i}async _add_attribute(t,e,n){const i=ks[n.type];switch(t){case Fs.VERTEX:return void await this.add_point_attribute(i,e,n);case Fs.OBJECT:return void await this.add_object_attribute(i,e,n)}os.unreachable(t)}async add_point_attribute(t,e,n){const i=e.coreObjects();switch(t){case zs.NUMERIC:for(let t=0;t{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name])}))}))}cook(t){if(this._is_using_expression())this.pv.name&&\\\\\\\"\\\\\\\"!=this.pv.name.trim()?this._addAttribute(Ds[this.pv.class],t[0]):this.states.error.set(\\\\\\\"attribute name is not valid\\\\\\\");else{this._operation=this._operation||new Yq(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}async _addAttribute(t,e){const n=ks[this.pv.type];switch(t){case Fs.VERTEX:return await this._addPointAttribute(n,e),this.setCoreGroup(e);case Fs.OBJECT:return await this._addObjectAttribute(n,e),this.setCoreGroup(e)}os.unreachable(t)}async _addPointAttribute(t,e){const n=e.coreObjects();switch(t){case zs.NUMERIC:for(let t=0;t{s[t.index()*this.pv.size+0]=e}));else{let e=[this.p.value2,this.p.value3,this.p.value4][this.pv.size-2].components;const i=new Array(e.length);let r;const o=[this._x_arrays_by_geometry_uuid,this._y_arrays_by_geometry_uuid,this._z_arrays_by_geometry_uuid,this._w_arrays_by_geometry_uuid];for(let a=0;a{i[a][t.index()]=e}));else{const t=r.value;for(let e of n)s[e.index()*this.pv.size+a]=t}for(let t=0;t{t.setAttribValue(this.pv.name,e)}));else{let e=[this.p.value2,this.p.value3,this.p.value4][this.pv.size-2].components,n={};const i=this._vector_by_attrib_size(this.pv.size);if(i){for(let e of t)n[e.index()]=i;for(let i=0;i{n[t.index()][r]=e}));else for(let e of t){n[e.index()][r]=s.value}}for(let e=0;e{i[t.index()]=e}));const s=Xs.arrayToIndexedArrays(i),r=t.coreGeometry();r&&r.setIndexedAttribute(this.pv.name,s.values,s.indices)}async add_string_attribute_to_object(t){const e=this.p.string;e.hasExpression()&&e.expressionController&&await e.expressionController.computeExpressionForObjects(t,((t,e)=>{t.setAttribValue(this.pv.name,e)}))}_init_array_if_required(t,e,n){const i=t.uuid,s=e[i];return s?s.length{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name])}))}))}cook(t){const e=t[0],n=e.attribNamesMatchingMask(this.pv.name);for(let t of n)switch(this.pv.class){case Fs.VERTEX:this.delete_vertex_attribute(e,t);case Fs.OBJECT:this.delete_object_attribute(e,t)}this.setCoreGroup(e)}delete_vertex_attribute(t,e){for(let n of t.objects())n.traverse((t=>{const n=t;if(n.geometry){new fr(n.geometry).deleteAttribute(e)}}))}delete_object_attribute(t,e){for(let n of t.objects()){let t=0;n.traverse((n=>{new br(n,t).deleteAttribute(e),t++}))}}}class eX{set_attrib(t){const e=t.geometry,n=t.targetAttribSize;if(n<1||n>4)return;const i=t.add,s=t.mult,r=this._data_from_texture(t.texture);if(!r)return;const{data:o,resx:a,resy:l}=r,c=o.length/(a*l),h=e.getAttribute(t.uvAttribName).array,u=h.length/2,d=new Array(u*n);let p,_,m,f,g,v,y,x,b;const w=or.clamp;for(v=0;v{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.attrib])}))}))}async cook(t){this._operation=this._operation||new nX(this.scene(),this.states);const e=await this._operation.cook(t,this.pv);this.setCoreGroup(e)}}var oX;!function(t){t.MIN_MAX_TO_01=\\\\\\\"min/max to 0/1\\\\\\\",t.VECTOR_TO_LENGTH_1=\\\\\\\"vectors to length 1\\\\\\\"}(oX||(oX={}));const aX=[oX.MIN_MAX_TO_01,oX.VECTOR_TO_LENGTH_1];class lX extends sV{constructor(){super(...arguments),this.min3=new p.a,this.max3=new p.a,this._vec=new p.a}static type(){return\\\\\\\"attribNormalize\\\\\\\"}cook(t,e){const n=t[0],i=t[0].objectsWithGeo(),s=ss.attribNames(e.name);for(let t of i){const n=t.geometry;for(let t of s){const i=n.getAttribute(t);if(i){let t=i;e.changeName&&\\\\\\\"\\\\\\\"!=e.newName&&(t=n.getAttribute(e.newName),t&&(t.needsUpdate=!0),t=t||i.clone()),this._normalize_attribute(i,t,e)}}}return n}_normalize_attribute(t,e,n){switch(aX[n.mode]){case oX.MIN_MAX_TO_01:return this._normalize_from_min_max_to_01(t,e);case oX.VECTOR_TO_LENGTH_1:return this._normalize_vectors(t,e)}}_normalize_from_min_max_to_01(t,e){const n=t.itemSize,i=t.array,s=e.array;switch(n){case 1:{const t=Math.min(...i),e=Math.max(...i);for(let n=0;n({name:t,value:e})))}}),this.name=ha.STRING(cX.name),this.changeName=ha.BOOLEAN(cX.changeName),this.newName=ha.STRING(cX.newName,{visibleIf:{changeName:1}})}};class uX extends lV{constructor(){super(...arguments),this.paramsConfig=hX}static type(){return\\\\\\\"attribNormalize\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(lX.INPUT_CLONED_STATE),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name])}))}))}set_mode(t){this.p.mode.set(aX.indexOf(t))}cook(t){this._operation=this._operation||new lX(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}var dX;!function(t){t[t.MIN=0]=\\\\\\\"MIN\\\\\\\",t[t.MAX=1]=\\\\\\\"MAX\\\\\\\",t[t.FIRST_FOUND=2]=\\\\\\\"FIRST_FOUND\\\\\\\"}(dX||(dX={}));class pX extends sV{constructor(){super(...arguments),this._values_per_attrib_name={},this._filtered_values_per_attrib_name={}}static type(){return\\\\\\\"attribPromote\\\\\\\"}cook(t,e){this._core_group=t[0],this._values_per_attrib_name={},this._filtered_values_per_attrib_name={};for(let t of this._core_group.coreObjects())this._core_object=t,this.find_values(e),this.filter_values(e),this.set_values(e);return this._core_group}find_values(t){const e=ss.attribNames(t.name);for(let n of e)this._find_values_for_attrib_name(n,t)}_find_values_for_attrib_name(t,e){switch(e.classFrom){case Fs.VERTEX:return this.find_values_from_points(t,e);case Fs.OBJECT:return this.find_values_from_object(t,e)}}find_values_from_points(t,e){if(this._core_object){const e=this._core_object.points(),n=e[0];if(n&&!n.isAttribIndexed(t)){const n=new Array(e.length);let i;for(let s=0;s{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.name,this.p.classFrom,this.p.classTo],(()=>{if(\\\\\\\"\\\\\\\"!=this.pv.name){const t=Bs.filter((t=>t.value==this.pv.classFrom))[0].name,e=Bs.filter((t=>t.value==this.pv.classTo))[0].name;return`${this.pv.name} (${t} -> ${e})`}return\\\\\\\"\\\\\\\"}))}))}))}cook(t){this._operation=this._operation||new pX(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const vX=new class extends ua{constructor(){super(...arguments),this.name=ha.STRING(),this.ramp=ha.RAMP(),this.changeName=ha.BOOLEAN(0),this.newName=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{changeName:1}})}};class yX extends lV{constructor(){super(...arguments),this.paramsConfig=vX}static type(){return\\\\\\\"attribRemap\\\\\\\"}initializeNode(){this.io.inputs.setCount(1)}cook(t){const e=t[0];this._remap_attribute(e),this.setCoreGroup(e)}_remap_attribute(t){const e=t.points();if(0===e.length)return;if(\\\\\\\"\\\\\\\"===this.pv.name)return;const n=e[0].attribSize(this.pv.name),i=e.map((t=>t.attribValue(this.pv.name)));let s=new Array(e.length);this._get_remaped_values(n,i,s);let r=this.pv.name;this.pv.changeName&&(r=this.pv.newName,t.hasAttrib(r)||t.addNumericVertexAttrib(r,n,0));let o=0;for(let t of s){e[o].setAttribValue(r,t),o++}}_get_remaped_values(t,e,n){switch(t){case Gs.FLOAT:return this._get_normalized_float(e,n);case Gs.VECTOR2:return this._get_normalized_vector2(e,n);case Gs.VECTOR3:return this._get_normalized_vector3(e,n);case Gs.VECTOR4:return this._get_normalized_vector4(e,n)}os.unreachable(t)}_get_normalized_float(t,e){const n=t,i=this.p.ramp;for(let t=0;t{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.oldName,this.p.newName],(()=>\\\\\\\"\\\\\\\"!=this.pv.oldName&&\\\\\\\"\\\\\\\"!=this.pv.newName?`${this.pv.oldName} -> ${this.pv.newName}`:\\\\\\\"\\\\\\\"))}))}))}cook(t){const e=t[0];e.renameAttrib(this.pv.oldName,this.pv.newName,this.pv.class),this.setCoreGroup(e)}}var wX=n(18);class TX{constructor(t,e=0){this._bbox=t,this._level=e,this._leaves_by_octant={},this._points_by_octant_id={},this._leaves=[],this._bounding_boxes_by_octant={},this._bounding_boxes_by_octant_prepared=!1,this._center=this._bbox.max.clone().add(this._bbox.min).multiplyScalar(.5)}level(){return this._level}traverse(t){t(this);Object.values(this._leaves_by_octant).forEach((e=>{e.traverse(t)}))}intersects_sphere(t){return!!this._bbox&&this._bbox.intersectsSphere(t)}points_in_sphere(t,e){if(0==this._leaves.length){Object.values(this._points_by_octant_id).flat().filter((e=>t.containsPoint(e.position()))).forEach((t=>{e.push(t)}))}else{this._leaves.filter((e=>e.intersects_sphere(t))).forEach((n=>n.points_in_sphere(t,e)))}}bounding_box(){return this._bbox}set_points(t){this._points_by_octant_id={};for(let e of t)this.add_point(e);const e=Object.keys(this._points_by_octant_id);e.length>1&&e.forEach((t=>{this.create_leaf(t)}))}create_leaf(t){const e=this._leaf_bbox(t),n=new TX(e,this._level+1);this._leaves_by_octant[t]=n,this._leaves.push(n),n.set_points(this._points_by_octant_id[t])}add_point(t){const e=this._octant_id(t.position());null==this._points_by_octant_id[e]&&(this._points_by_octant_id[e]=[]),this._points_by_octant_id[e].push(t)}_octant_id(t){return`${t.x>this._center.x?1:0}${t.y>this._center.y?1:0}${t.z>this._center.z?1:0}`}_leaf_bbox(t){return this._bounding_boxes_by_octant_prepared||(this._prepare_leaves_bboxes(),this._bounding_boxes_by_octant_prepared=!0),this._bounding_boxes_by_octant[t]}_bbox_center(t,e,n){const i=this._bbox.min.clone();return t&&(i.x=this._bbox.max.x),e&&(i.y=this._bbox.max.y),n&&(i.z=this._bbox.max.z),i.clone().add(this._center).multiplyScalar(.5)}_prepare_leaves_bboxes(){const t=[];t.push(this._bbox_center(0,0,0)),t.push(this._bbox_center(0,0,1)),t.push(this._bbox_center(0,1,0)),t.push(this._bbox_center(0,1,1)),t.push(this._bbox_center(1,0,0)),t.push(this._bbox_center(1,0,1)),t.push(this._bbox_center(1,1,0)),t.push(this._bbox_center(1,1,1));const e=this._bbox.max.clone().sub(this._bbox.min).multiplyScalar(.25);for(let n of t){const t=this._octant_id(n),i=new Cy.a(n.clone().sub(e),n.clone().add(e));this._bounding_boxes_by_octant[t]=i}}}class AX{constructor(t){this._root=new TX(t)}set_points(t){this._root.set_points(t)}traverse(t){this._root.traverse(t)}find_points(t,e,n){const i=new wX.a(t,e);let s=[];return this._root.intersects_sphere(i)&&this._root.points_in_sphere(i,s),null==n||s.length>n&&(s=f.sortBy(s,(e=>e.position().distanceTo(t))),s=s.slice(0,n)),s}}class MX{constructor(t={}){this._array_index=0,this._count=0,this._current_count_index=0,this._resolve=null,this._max_time_per_chunk=t.max_time_per_chunk||10,this._check_every_interations=t.check_every_interations||100}async startWithCount(t,e){if(this._count=t,this._current_count_index=0,this._iteratee_method_count=e,this._bound_next_with_count=this.nextWithCount.bind(this),this._resolve)throw\\\\\\\"an iterator cannot be started twice\\\\\\\";return new Promise(((t,e)=>{this._resolve=t,this.nextWithCount()}))}nextWithCount(){const t=li.performance.performanceManager(),e=t.now();if(this._iteratee_method_count&&this._bound_next_with_count)for(;this._current_count_indexthis._max_time_per_chunk){setTimeout(this._bound_next_with_count,1);break}this._current_count_index>=this._count&&this._resolve&&this._resolve()}async startWithArray(t,e){if(this._array=t,this._array_index=0,this._iteratee_method_array=e,this._bound_next_with_array=this.nextWithArray.bind(this),this._resolve)throw\\\\\\\"an iterator cannot be started twice\\\\\\\";return new Promise(((t,e)=>{this._resolve=t,this.nextWithArray()}))}nextWithArray(){const t=li.performance.performanceManager(),e=t.now();if(this._iteratee_method_array&&this._bound_next_with_array&&this._array)for(;this._current_array_element=this._array[this._array_index];)if(this._iteratee_method_array(this._current_array_element,this._array_index),this._array_index++,this._array_index%this._check_every_interations==0&&t.now()-e>this._max_time_per_chunk){setTimeout(this._bound_next_with_array,1);break}void 0===this._current_array_element&&this._resolve&&this._resolve()}}const EX=new class extends ua{constructor(){super(...arguments),this.srcGroup=ha.STRING(),this.destGroup=ha.STRING(),this.name=ha.STRING(),this.maxSamplesCount=ha.INTEGER(1,{range:[1,10],rangeLocked:[!0,!1]}),this.distanceThreshold=ha.FLOAT(1),this.blendWidth=ha.FLOAT(0)}};class SX extends lV{constructor(){super(...arguments),this.paramsConfig=EX}static type(){return\\\\\\\"attribTransfer\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to transfer attributes to\\\\\\\",\\\\\\\"geometry to transfer attributes from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(2),this.io.inputs.initInputsClonedState([Ki.FROM_NODE,Ki.NEVER])}async cook(t){this._core_group_dest=t[0];const e=this._core_group_dest.pointsFromGroup(this.pv.destGroup);this._core_group_src=t[1],this._attrib_names=this._core_group_src.attribNamesMatchingMask(this.pv.name),this._error_if_attribute_not_found_on_second_input(),this._build_octree_if_required(this._core_group_src),this._add_attribute_if_required(),await this._transfer_attributes(e),this.setCoreGroup(this._core_group_dest)}_error_if_attribute_not_found_on_second_input(){for(let t of this._attrib_names)this._core_group_src.hasAttrib(t)||this.states.error.set(`attribute '${t}' not found on second input`)}_build_octree_if_required(t){const e=null==this._octree_timestamp||this._octree_timestamp!==t.timestamp();if(this._prev_param_srcGroup!==this.pv.srcGroup||e){this._octree_timestamp=t.timestamp(),this._prev_param_srcGroup=this.pv.srcGroup;const e=this._core_group_src.pointsFromGroup(this.pv.srcGroup);this._octree=new AX(this._core_group_src.boundingBox()),this._octree.set_points(e)}}_add_attribute_if_required(){for(let t of this._attrib_names)if(!this._core_group_dest.hasAttrib(t)){const e=this._core_group_src.attribSize(t);this._core_group_dest.addNumericVertexAttrib(t,e,0)}}async _transfer_attributes(t){const e=new MX;await e.startWithArray(t,this._transfer_attributes_for_point.bind(this))}_transfer_attributes_for_point(t){var e;const n=this.pv.distanceThreshold+this.pv.blendWidth,i=(null===(e=this._octree)||void 0===e?void 0:e.find_points(t.position(),n,this.pv.maxSamplesCount))||[];for(let e of this._attrib_names)this._interpolate_points(t,i,e)}_interpolate_points(t,e,n){let i;i=class{static perform(t,e,n,i,s){switch(e.length){case 0:return t.attribValue(n);case 1:return this._interpolate_with_1_point(t,e[0],n,i,s);default:return this._interpolate_with_multiple_points(t,e,n,i,s)}}static _interpolate_with_1_point(t,e,n,i,s){const r=t.position(),o=e.position(),a=r.distanceTo(o),l=e.attribValue(n);return m.isNumber(l)?this._weighted_value_from_distance(t,l,n,a,i,s):(console.warn(\\\\\\\"value is not a number\\\\\\\",l),0)}static _weight_from_distance(t,e,n){return(t-e)/n}static _weighted_value_from_distance(t,e,n,i,s,r){if(i<=s)return e;{const o=t.attribValue(n);if(m.isNumber(o)){const t=this._weight_from_distance(i,s,r);return t*o+(1-t)*e}return console.warn(\\\\\\\"value is not a number\\\\\\\",o),0}}static _interpolate_with_multiple_points(t,e,n,i,s){const r=e.map((e=>this._interpolate_with_1_point(t,e,n,i,s)));return f.max(r)||0}static weights(t,e){switch(e.length){case 1:return 1;case 2:return this._weights_from_2(t,e);default:return e=e.slice(0,3),this._weights_from_3(t,e)}}static _weights_from_2(t,e){const n=e.map((e=>t.distanceTo(e))),i=f.sum(n);return[n[1]/i,n[0]/i]}static _weights_from_3(t,e){const n=e.map((e=>t.distanceTo(e))),i=f.sum([n[0]*n[1],n[0]*n[2],n[1]*n[2]]);return[n[1]*n[2]/i,n[0]*n[2]/i,n[0]*n[1]/i]}}.perform(t,e,n,this.pv.distanceThreshold,this.pv.blendWidth),null!=i&&t.setAttribValue(n,i)}}const CX=new class extends ua{constructor(){super(...arguments),this.stepSize=ha.FLOAT(.1)}};class NX extends lV{constructor(){super(...arguments),this.paramsConfig=CX}static type(){return\\\\\\\"bboxScatter\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to create points from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1)}cook(t){const e=t[0],n=this.pv.stepSize,i=e.boundingBox(),s=i.min,r=i.max,o=[];for(let t=s.x;t<=r.x;t+=n)for(let e=s.y;e<=r.y;e+=n)for(let i=s.z;i<=r.z;i+=n)o.push(t),o.push(e),o.push(i);const a=new S.a;a.setAttribute(\\\\\\\"position\\\\\\\",new C.a(new Float32Array(o),3)),this.setGeometry(a,Ns.POINTS)}}const LX=new class extends ua{constructor(){super(...arguments),this.attribName=ha.STRING(\\\\\\\"position\\\\\\\"),this.blend=ha.FLOAT(.5,{range:[0,1],rangeLocked:[!0,!0]})}};class OX extends lV{constructor(){super(...arguments),this.paramsConfig=LX}static type(){return\\\\\\\"blend\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to blend from\\\\\\\",\\\\\\\"geometry to blend to\\\\\\\"]}initializeNode(){this.io.inputs.setCount(2),this.io.inputs.initInputsClonedState([Ki.FROM_NODE,Ki.NEVER])}cook(t){const e=t[0],n=t[1],i=e.objects(),s=n.objects();let r,o;for(let t=0;tt.flip())),t}}PX.fromPolygons=function(t){let e=new PX;return e.polygons=t,e};class RX{constructor(t=0,e=0,n=0){this.x=t,this.y=e,this.z=n}copy(t){return this.x=t.x,this.y=t.y,this.z=t.z,this}clone(){return new RX(this.x,this.y,this.z)}negate(){return this.x*=-1,this.y*=-1,this.z*=-1,this}add(t){return this.x+=t.x,this.y+=t.y,this.z+=t.z,this}sub(t){return this.x-=t.x,this.y-=t.y,this.z-=t.z,this}times(t){return this.x*=t,this.y*=t,this.z*=t,this}dividedBy(t){return this.x/=t,this.y/=t,this.z/=t,this}lerp(t,e){return this.add(IX.copy(t).sub(this).times(e))}unit(){return this.dividedBy(this.length())}length(){return Math.sqrt(this.x**2+this.y**2+this.z**2)}normalize(){return this.unit()}cross(t){let e=this;const n=e.x,i=e.y,s=e.z,r=t.x,o=t.y,a=t.z;return this.x=i*a-s*o,this.y=s*r-n*a,this.z=n*o-i*r,this}dot(t){return this.x*t.x+this.y*t.y+this.z*t.z}}let IX=new RX,FX=new RX;class DX{constructor(t,e,n,i){this.pos=(new RX).copy(t),this.normal=(new RX).copy(e),this.uv=(new RX).copy(n),this.uv.z=0,i&&(this.color=(new RX).copy(i))}clone(){return new DX(this.pos,this.normal,this.uv,this.color)}flip(){this.normal.negate()}interpolate(t,e){return new DX(this.pos.clone().lerp(t.pos,e),this.normal.clone().lerp(t.normal,e),this.uv.clone().lerp(t.uv,e),this.color&&t.color&&this.color.clone().lerp(t.color,e))}}class BX{constructor(t,e){this.normal=t,this.w=e}clone(){return new BX(this.normal.clone(),this.w)}flip(){this.normal.negate(),this.w=-this.w}splitPolygon(t,e,n,i,s){let r=0,o=[];for(let e=0;eBX.EPSILON?1:0;r|=i,o.push(i)}switch(r){case 0:(this.normal.dot(t.plane.normal)>0?e:n).push(t);break;case 1:i.push(t);break;case 2:s.push(t);break;case 3:let r=[],a=[];for(let e=0;e=3&&i.push(new zX(r,t.shared)),a.length>=3&&s.push(new zX(a,t.shared))}}}BX.EPSILON=1e-5,BX.fromPoints=function(t,e,n){let i=IX.copy(e).sub(t).cross(FX.copy(n).sub(t)).normalize();return new BX(i.clone(),i.dot(t))};class zX{constructor(t,e){this.vertices=t,this.shared=e,this.plane=BX.fromPoints(t[0].pos,t[1].pos,t[2].pos)}clone(){return new zX(this.vertices.map((t=>t.clone())),this.shared)}flip(){this.vertices.reverse().map((t=>t.flip())),this.plane.flip()}}class kX{constructor(t){this.plane=null,this.front=null,this.back=null,this.polygons=[],t&&this.build(t)}clone(){let t=new kX;return t.plane=this.plane&&this.plane.clone(),t.front=this.front&&this.front.clone(),t.back=this.back&&this.back.clone(),t.polygons=this.polygons.map((t=>t.clone())),t}invert(){for(let t=0;tnew zX(t.vertices.map((t=>new DX(t.pos,t.normal,t.uv))),t.shared))))},PX.fromGeometry=function(t,e){let n=[];if(t.isGeometry){let i=t.faces,s=t.vertices,r=[\\\\\\\"a\\\\\\\",\\\\\\\"b\\\\\\\",\\\\\\\"c\\\\\\\"];for(let o=0;o({top:0,array:new Float32Array(t),write:function(t){this.array[this.top++]=t.x,this.array[this.top++]=t.y,this.array[this.top++]=t.z}}),HX=t=>({top:0,array:new Float32Array(t),write:function(t){this.array[this.top++]=t.x,this.array[this.top++]=t.y}});var jX;PX.toMesh=function(t,e,n){let i,s,r=t.polygons;{let t=0;r.forEach((e=>t+=e.vertices.length-2)),i=new S.a;let e,n=VX(3*t*3),o=VX(3*t*3),a=HX(2*t*3),l=[];if(r.forEach((i=>{let s=i.vertices,r=s.length;void 0!==i.shared&&(l[i.shared]||(l[i.shared]=[])),r&&void 0!==s[0].color&&(e||(e=VX(3*t*3)));for(let t=3;t<=r;t++)void 0!==i.shared&&l[i.shared].push(n.top/3,n.top/3+1,n.top/3+2),n.write(s[0].pos),n.write(s[t-2].pos),n.write(s[t-1].pos),o.write(s[0].normal),o.write(s[t-2].normal),o.write(s[t-1].normal),a.write(s[0].uv),a.write(s[t-2].uv),a.write(s[t-1].uv),e&&(e.write(s[0].color)||e.write(s[t-2].color)||e.write(s[t-1].color))})),i.setAttribute(\\\\\\\"position\\\\\\\",new C.a(n.array,3)),i.setAttribute(\\\\\\\"normal\\\\\\\",new C.a(o.array,3)),i.setAttribute(\\\\\\\"uv\\\\\\\",new C.a(a.array,2)),e&&i.setAttribute(\\\\\\\"color\\\\\\\",new C.a(e.array,3)),l.length){let t=[],e=0;for(let n=0;n({name:t,value:e})))}}),this.useBothMaterials=ha.BOOLEAN(XX.useBothMaterials)}};class $X extends lV{constructor(){super(...arguments),this.paramsConfig=YX}static type(){return\\\\\\\"boolean\\\\\\\"}initializeNode(){super.initializeNode(),this.io.inputs.setCount(2),this.io.inputs.initInputsClonedState(qX.INPUT_CLONED_STATE),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.operation],(()=>WX[this.pv.operation]))}))}))}setOperation(t){this.p.operation.set(WX.indexOf(t))}async cook(t){this._operation=this._operation||new qX(this.scene(),this.states,this);const e=await this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class JX extends sV{constructor(){super(...arguments),this._core_transform=new vU}static type(){return\\\\\\\"box\\\\\\\"}cook(t,e){const n=t[0],i=n?this._cook_with_input(n,e):this._cook_without_input(e);return this.createCoreGroupFromGeometry(i)}_cook_without_input(t){const e=t.divisions,n=t.size,i=new N(n,n,n,e,e,e);return i.translate(t.center.x,t.center.y,t.center.z),i.computeVertexNormals(),i}_cook_with_input(t,e){const n=e.divisions,i=t.boundingBox(),s=i.max.clone().sub(i.min),r=i.max.clone().add(i.min).multiplyScalar(.5),o=new N(s.x,s.y,s.z,n,n,n),a=this._core_transform.translation_matrix(r);return o.applyMatrix4(a),o}}JX.DEFAULT_PARAMS={size:1,divisions:1,center:new p.a(0,0,0)},JX.INPUT_CLONED_STATE=Ki.NEVER;const ZX=JX.DEFAULT_PARAMS;const QX=new class extends ua{constructor(){super(...arguments),this.size=ha.FLOAT(ZX.size),this.divisions=ha.INTEGER(ZX.divisions,{range:[1,10],rangeLocked:[!0,!1]}),this.center=ha.VECTOR3(ZX.center)}};class KX extends lV{constructor(){super(...arguments),this.paramsConfig=QX}static type(){return\\\\\\\"box\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to create bounding box from (optional)\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(JX.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new JX(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class tY{constructor(){}}function eY(t,e,n){return n.min.x=e[t],n.min.y=e[t+1],n.min.z=e[t+2],n.max.x=e[t+3],n.max.y=e[t+4],n.max.z=e[t+5],n}function nY(t){let e=-1,n=-1/0;for(let i=0;i<3;i++){const s=t[i+3]-t[i];s>n&&(n=s,e=i)}return e}function iY(t,e){e.set(t)}function sY(t,e,n){let i,s;for(let r=0;r<3;r++){const o=r+3;i=t[r],s=e[r],n[r]=is?i:s}}function rY(t){const e=t[3]-t[0],n=t[4]-t[1],i=t[5]-t[2];return 2*(e*n+n*i+i*e)}const oY=Math.pow(2,-24);function aY(t,e,n,i,s=null){let r=1/0,o=1/0,a=1/0,l=-1/0,c=-1/0,h=-1/0,u=1/0,d=1/0,p=1/0,_=-1/0,m=-1/0,f=-1/0;const g=null!==s;for(let i=6*e,s=6*(e+n);il&&(l=v),g&&e_&&(_=e);const y=t[i+2],x=t[i+3],b=y-x,w=y+x;bc&&(c=w),g&&ym&&(m=y);const T=t[i+4],A=t[i+5],M=T-A,E=T+A;Mh&&(h=E),g&&Tf&&(f=T)}i[0]=r,i[1]=o,i[2]=a,i[3]=l,i[4]=c,i[5]=h,g&&(s[0]=u,s[1]=d,s[2]=p,s[3]=_,s[4]=m,s[5]=f)}const lY=32,cY=new Array(lY).fill().map((()=>({count:0,bounds:new Float32Array(6),rightCacheBounds:new Float32Array(6),candidate:0}))),hY=new Float32Array(6);function uY(t,e){function n(e,i,d,p=null,_=0){if(!u&&_>=a&&(u=!0,l&&(console.warn(`MeshBVH: Max depth of ${a} reached when generating BVH. Consider increasing maxDepth.`),console.warn(t))),d<=c||_>=a)return e.offset=i,e.count=d,e;const m=function(t,e,n,i,s,r){let o=-1,a=0;if(0===r)o=nY(e),-1!==o&&(a=(e[o]+e[o+3])/2);else if(1===r)o=nY(t),-1!==o&&(a=function(t,e,n,i){let s=0;for(let r=e,o=e+n;r=lY&&(s=31);const r=cY[s];r.count++;const o=r.bounds;for(let t=0;t<3;t++){const i=n[e+2*t],s=n[e+2*t+1],r=i-s,a=i+s;ro[t+3]&&(o[t+3]=a)}}const d=cY[31];iY(d.bounds,d.rightCacheBounds);for(let t=30;t>=0;t--){const e=cY[t],n=cY[t+1];sY(e.bounds,n.rightCacheBounds,e.rightCacheBounds)}let p=0;for(let e=0;e<31;e++){const n=cY[e],i=n.count,c=n.bounds,h=cY[e+1].rightCacheBounds;0!==i&&(0===p?iY(c,hY):sY(c,hY,hY)),p+=i;let u=0,d=0;0!==p&&(u=rY(hY)/r);const _=s-p;0!==_&&(d=rY(h)/r);const m=1+1.25*(u*p+d*_);m=a;)o--;if(!(r65535?new Uint32Array(new i(4*n)):new Uint16Array(new i(2*n)),t.setIndex(new Jw(s,1));for(let t=0;td&&(d=s),a>d&&(d=a);const p=(d-l)/2,_=2*t;o[r+_+0]=l+p,o[r+_+1]=p+(Math.abs(l)+p)*oY,le[t+3]&&(e[t+3]=d)}}return o}(t,i),o=t.index.array,a=e.maxDepth,l=e.verbose,c=e.maxLeafTris,h=e.strategy;let u=!1;const d=[],p=function(t){if(!t.groups||!t.groups.length)return[{offset:0,count:t.index.count/3}];const e=[],n=new Set;for(const e of t.groups)n.add(e.start),n.add(e.start+e.count);const i=Array.from(n.values()).sort(((t,e)=>t-e));for(let t=0;ta&&(a=e);const n=t[i+2];nl&&(l=n);const h=t[i+4];hc&&(c=h)}i[0]=s,i[1]=r,i[2]=o,i[3]=a,i[4]=l,i[5]=c}(r,t.offset,t.count,s),n(e,t.offset,t.count,s),d.push(e)}else for(let t of p){const e=new tY;e.boundingData=new Float32Array(6),aY(r,t.offset,t.count,e.boundingData,s),n(e,t.offset,t.count,s),d.push(e)}return d}const dY=65535;class pY{constructor(){this.min=1/0,this.max=-1/0}setFromPointsField(t,e){let n=1/0,i=-1/0;for(let s=0,r=t.length;si?r:i}this.min=n,this.max=i}setFromPoints(t,e){let n=1/0,i=-1/0;for(let s=0,r=e.length;si?o:i}this.min=n,this.max=i}isSeparated(t){return this.min>t.max||t.min>this.max}}pY.prototype.setFromBox=function(){const t=new Ab;return function(e,n){const i=n.min,s=n.max;let r=1/0,o=-1/0;for(let n=0;n<=1;n++)for(let a=0;a<=1;a++)for(let l=0;l<=1;l++){t.x=i.x*n+s.x*(1-n),t.y=i.y*a+s.y*(1-a),t.z=i.z*l+s.z*(1-l);const c=e.dot(t);r=Math.min(c,r),o=Math.max(c,o)}this.min=r,this.max=o}}();!function(){const t=new pY}();const _Y=function(){const t=new Ab,e=new Ab,n=new Ab;return function(i,s,r){const o=i.start,a=t,l=s.start,c=e;n.subVectors(o,l),t.subVectors(i.end,s.start),e.subVectors(s.end,s.start);const h=n.dot(c),u=c.dot(a),d=c.dot(c),p=n.dot(a),_=a.dot(a)*d-u*u;let m,f;m=0!==_?(h*u-p*d)/_:0,f=(h+m*u)/d,r.x=m,r.y=f}}(),mY=function(){const t=new ub,e=new Ab,n=new Ab;return function(i,s,r,o){_Y(i,s,t);let a=t.x,l=t.y;if(a>=0&&a<=1&&l>=0&&l<=1)return i.at(a,r),void s.at(l,o);if(a>=0&&a<=1)return l<0?s.at(0,o):s.at(1,o),void i.closestPointToPoint(o,!0,r);if(l>=0&&l<=1)return a<0?i.at(0,r):i.at(1,r),void s.closestPointToPoint(r,!0,o);{let t,c;t=a<0?i.start:i.end,c=l<0?s.start:s.end;const h=e,u=n;return i.closestPointToPoint(c,!0,e),s.closestPointToPoint(t,!0,n),h.distanceToSquared(c)<=u.distanceToSquared(t)?(r.copy(h),void o.copy(c)):(r.copy(t),void o.copy(u))}}}(),fY=function(){const t=new Ab,e=new Ab,n=new GT,i=new eL;return function(s,r){const{radius:o,center:a}=s,{a:l,b:c,c:h}=r;i.start=l,i.end=c;if(i.closestPointToPoint(a,!0,t).distanceTo(a)<=o)return!0;i.start=l,i.end=h;if(i.closestPointToPoint(a,!0,t).distanceTo(a)<=o)return!0;i.start=c,i.end=h;if(i.closestPointToPoint(a,!0,t).distanceTo(a)<=o)return!0;const u=r.getPlane(n);if(Math.abs(u.distanceToPoint(a))<=o){const t=u.projectPoint(a,e);if(r.containsPoint(t))return!0}return!1}}();class gY extends Bw{constructor(...t){super(...t),this.isSeparatingAxisTriangle=!0,this.satAxes=new Array(4).fill().map((()=>new Ab)),this.satBounds=new Array(4).fill().map((()=>new pY)),this.points=[this.a,this.b,this.c],this.sphere=new qb,this.plane=new GT,this.needsUpdate=!1}intersectsSphere(t){return fY(t,this)}update(){const t=this.a,e=this.b,n=this.c,i=this.points,s=this.satAxes,r=this.satBounds,o=s[0],a=r[0];this.getNormal(o),a.setFromPoints(o,i);const l=s[1],c=r[1];l.subVectors(t,e),c.setFromPoints(l,i);const h=s[2],u=r[2];h.subVectors(e,n),u.setFromPoints(h,i);const d=s[3],p=r[3];d.subVectors(n,t),p.setFromPoints(d,i),this.sphere.setFromPoints(this.points),this.plane.setFromNormalAndCoplanarPoint(o,t),this.needsUpdate=!1}}gY.prototype.closestPointToSegment=function(){const t=new Ab,e=new Ab,n=new eL;return function(i,s=null,r=null){const{start:o,end:a}=i,l=this.points;let c,h=1/0;for(let o=0;o<3;o++){const a=(o+1)%3;n.start.copy(l[o]),n.end.copy(l[a]),mY(n,i,t,e),c=t.distanceToSquared(e),c1-1e-10)console.warn(\\\\\\\"SeparatingAxisTriangle.intersectsTriangle: Triangles are coplanar which does not support an output edge. Setting edge to 0, 0, 0.\\\\\\\"),p.start.set(0,0,0),p.end.set(0,0,0);else{const n=this.points;let i=!1;for(let t=0;t<3;t++){const s=n[t],r=n[(t+1)%3];if(c.start.copy(s),c.end.copy(r),e.intersectLine(c,i?h.start:h.end)){if(i)break;i=!0}}const s=d.points;let r=!1;for(let e=0;e<3;e++){const n=s[e],i=s[(e+1)%3];if(c.start.copy(n),c.end.copy(i),t.intersectLine(c,r?u.start:u.end)){if(r)break;r=!0}}if(h.delta(o),u.delta(a),o.dot(a)<0){let t=u.start;u.start=u.end,u.end=t}l.subVectors(h.start,u.start),l.dot(o)>0?p.start.copy(h.start):p.start.copy(u.start),l.subVectors(h.end,u.end),l.dot(o)<0?p.end.copy(h.end):p.end.copy(u.end)}}return!0}}(),gY.prototype.distanceToPoint=function(){const t=new Ab;return function(e){return this.closestPointToPoint(e,t),e.distanceTo(t)}}(),gY.prototype.distanceToTriangle=function(){const t=new Ab,e=new Ab,n=[\\\\\\\"a\\\\\\\",\\\\\\\"b\\\\\\\",\\\\\\\"c\\\\\\\"],i=new eL,s=new eL;return function(r,o=null,a=null){const l=o||a?i:null;if(this.intersectsTriangle(r,l))return(o||a)&&(o&&l.getCenter(o),a&&l.getCenter(a)),0;let c=1/0;for(let e=0;e<3;e++){let i;const s=n[e],l=r[s];this.closestPointToPoint(l,t),i=l.distanceToSquared(t),inew Ab)),this.satAxes=new Array(3).fill().map((()=>new Ab)),this.satBounds=new Array(3).fill().map((()=>new pY)),this.alignedSatBounds=new Array(3).fill().map((()=>new pY)),this.needsUpdate=!1}set(t,e,n){super.set(t,e),this.matrix=n,this.needsUpdate=!0}copy(t){super.copy(t),this.matrix.copy(t.matrix),this.needsUpdate=!0}}vY.prototype.update=function(){const t=this.matrix,e=this.min,n=this.max,i=this.points;for(let s=0;s<=1;s++)for(let r=0;r<=1;r++)for(let o=0;o<=1;o++){const a=i[1*s|2*r|4*o];a.x=s?n.x:e.x,a.y=r?n.y:e.y,a.z=o?n.z:e.z,a.applyMatrix4(t)}const s=this.satBounds,r=this.satAxes,o=i[0];for(let t=0;t<3;t++){const e=r[t],n=s[t],a=i[1<new eL)),n=new Array(12).fill().map((()=>new eL)),i=new Ab,s=new Ab;return function(r,o=0,a=null,l=null){if(this.needsUpdate&&this.update(),this.intersectsBox(r))return(a||l)&&(r.getCenter(s),this.closestPointToPoint(s,i),r.closestPointToPoint(i,s),a&&a.copy(i),l&&l.copy(s)),0;const c=o*o,h=r.min,u=r.max,d=this.points;let p=1/0;for(let t=0;t<8;t++){const e=d[t];s.copy(e).clamp(h,u);const n=e.distanceToSquared(s);if(nn.far?null:t)}function CY(t,e,n,i){const s=t.a,r=t.b,o=t.c;let a=e,l=e+1,c=e+2;n&&(a=n.getX(e),l=n.getX(e+1),c=n.getX(e+2)),s.x=i.getX(a),s.y=i.getY(a),s.z=i.getZ(a),r.x=i.getX(l),r.y=i.getY(l),r.z=i.getZ(l),o.x=i.getX(c),o.y=i.getY(c),o.z=i.getZ(c)}function NY(t,e,n,i,s,r,o){const a=n.index,l=n.attributes.position;for(let n=t,c=e+t;n=0;let c,h;l?(c=IY(t),h=FY(t,a)):(c=FY(t,a),h=IY(t));const u=HY(c,r,i,BY)?UY(c,e,n,i):null;if(u){const t=u.point[o];if(l?t<=r[h+s]:t>=r[h+s+3])return u}const d=HY(h,r,i,BY)?UY(h,e,n,i):null;return u&&d?u.distance<=d.distance?u:d:u||d||null}}const GY=function(){let t,e;const n=[],i=new LY((()=>new Sb));return function(...r){t=i.getPrimitive(),e=i.getPrimitive(),n.push(t,e);const o=s(...r);i.releasePrimitive(t),i.releasePrimitive(e),n.pop(),n.pop();const a=n.length;return a>0&&(e=n[a-1],t=n[a-2]),o};function s(n,i,r,o,a=null,l=0,c=0){function h(t){let e=2*t,n=XY,i=YY;for(;!OY(e,n);)e=2*(t=IY(t));return PY(t,i)}function u(t){let e=2*t,n=XY,i=YY;for(;!OY(e,n);)e=2*(t=FY(t,i));return PY(t,i)+RY(e,n)}let d=2*n,p=qY,_=XY,m=YY;if(OY(d,_)){const e=PY(n,m),i=RY(d,_);return eY(n,p,t),o(e,i,!1,c,l+n,t)}{const d=IY(n),f=FY(n,m);let g,v,y,x,b=d,w=f;if(a&&(y=t,x=e,eY(b,p,y),eY(w,p,x),g=a(y),v=a(x),vs.intersectsBox(t),intersectsTriangle:t=>{t.a.applyMatrix4(c),t.b.applyMatrix4(c),t.c.applyMatrix4(c),t.needsUpdate=!0;for(let n=3*g,i=3*(v+g);nnew gY));class h${static serialize(t,e={}){if(e.isBufferGeometry)return console.warn(\\\\\\\"MeshBVH.serialize: The arguments for the function have changed. See documentation for new signature.\\\\\\\"),h$.serialize(arguments[0],{cloneBuffers:void 0===arguments[2]||arguments[2]});e={cloneBuffers:!0,...e};const n=t.geometry,i=t._roots,s=n.getIndex();let r;return r=e.cloneBuffers?{roots:i.map((t=>t.slice())),index:s.array.slice()}:{roots:i,index:s.array},r}static deserialize(t,e,n={}){if(\\\\\\\"boolean\\\\\\\"==typeof n)return console.warn(\\\\\\\"MeshBVH.deserialize: The arguments for the function have changed. See documentation for new signature.\\\\\\\"),h$.deserialize(arguments[0],arguments[1],{setIndex:void 0===arguments[2]||arguments[2]});n={setIndex:!0,...n};const{index:i,roots:s}=t,r=new h$(e,{...n,[ZY]:!0});if(r._roots=s,n.setIndex){const n=e.getIndex();if(null===n){const n=new Jw(t.index,1,!1);e.setIndex(n)}else n.array!==i&&(n.array.set(i),n.needsUpdate=!0)}return r}constructor(t,e={}){if(!t.isBufferGeometry)throw new Error(\\\\\\\"MeshBVH: Only BufferGeometries are supported.\\\\\\\");if(t.index&&t.index.isInterleavedBufferAttribute)throw new Error(\\\\\\\"MeshBVH: InterleavedBufferAttribute is not supported for the index attribute.\\\\\\\");if((e=Object.assign({strategy:0,maxDepth:40,maxLeafTris:10,verbose:!0,useSharedArrayBuffer:!1,setBoundingBox:!0,[ZY]:!1},e)).useSharedArrayBuffer&&\\\\\\\"undefined\\\\\\\"==typeof SharedArrayBuffer)throw new Error(\\\\\\\"MeshBVH: SharedArrayBuffer is not available.\\\\\\\");this._roots=null,e[ZY]||(this._roots=function(t,e){const n=uY(t,e);let i,s,r;const o=[],a=e.useSharedArrayBuffer?SharedArrayBuffer:ArrayBuffer;for(let t=0;tMath.pow(2,32))throw new Error(\\\\\\\"MeshBVH: Cannot store child pointer greater than 32 bits.\\\\\\\");return s[n+6]=a/4,a=c(a,r),s[n+7]=o,a}}}(t,e),!t.boundingBox&&e.setBoundingBox&&(t.boundingBox=this.getBoundingBox(new Sb))),this.geometry=t}refit(t=null){t&&Array.isArray(t)&&(t=new Set(t));const e=this.geometry,n=e.index.array,i=e.attributes.position,s=i.array,r=i.offset||0;let o,a,l,c,h=3;i.isInterleavedBufferAttribute&&(h=i.data.stride);let u=0;const d=this._roots;for(let t=0,e=d.length;tp&&(p=a),l_&&(_=l),cm&&(m=c)}return(c[e+0]!==i||c[e+1]!==o||c[e+2]!==d||c[e+3]!==p||c[e+4]!==_||c[e+5]!==m)&&(c[e+0]=i,c[e+1]=o,c[e+2]=d,c[e+3]=p,c[e+4]=_,c[e+5]=m,!0)}{const n=e+8,s=a[e+6],r=n+i,l=s+i;let h=o,u=!1,d=!1;t?h||(u=t.has(r),d=t.has(l),h=!u&&!d):(u=!0,d=!0);const _=h||d;let m=!1;(h||u)&&(m=p(n,i,h));let f=!1;_&&(f=p(s,i,h));const g=m||f;if(g)for(let t=0;t<3;t++){const i=n+t,r=s+t,o=c[i],a=c[i+3],l=c[r],h=c[r+3];c[e+t]=oh?a:h}return g}}}traverse(t,e=0){const n=this._roots[e],i=new Uint32Array(n),s=new Uint16Array(n);!function e(r,o=0){const a=2*r,l=s[a+15]===dY;if(l){const e=i[r+6],c=s[a+14];t(o,l,new Float32Array(n,4*r,6),e,c)}else{const s=r+8,a=i[r+6],c=i[r+7];t(o,l,new Float32Array(n,4*r,6),c)||(e(s,o+1),e(a,o+1))}}(0)}raycast(t,e=0){const n=this._roots,i=this.geometry,s=[],r=e.isMaterial,o=Array.isArray(e),a=i.groups,l=r?e.side:e;for(let r=0,c=n.length;r{const r=3*n;return t(e,r,r+1,r+2,i,s)}}t={boundsTraverseOrder:n,intersectsBounds:t,intersectsTriangle:e,intersectsRange:null},console.warn(\\\\\\\"MeshBVH: Shapecast function signature has changed and now takes an object of callbacks as a second argument. See docs for new signature.\\\\\\\")}const s=c$.getPrimitive();let{boundsTraverseOrder:r,intersectsBounds:o,intersectsRange:a,intersectsTriangle:l}=t;if(a&&l){const t=a;a=(e,n,r,o,a)=>!!t(e,n,r,o,a)||NY(e,n,i,l,r,o,s)}else a||(a=l?(t,e,n,r)=>NY(t,e,i,l,n,r,s):(t,e,n)=>n);let c=!1,h=0;for(const t of this._roots){if($Y(t),c=GY(0,i,o,a,r,h),JY(),c)break;h+=t.byteLength}return c$.releasePrimitive(s),c}bvhcast(t,e,n){let{intersectsRanges:i,intersectsTriangles:s}=n;const r=t.geometry,o=r.index,a=r.attributes.position;t$.copy(e).invert();const l=c$.getPrimitive(),c=c$.getPrimitive();if(s){function h(t,n,i,r,h,u,d,p){for(let _=i,m=i+r;_KY.intersectsBox(t),intersectsRange:(e,n,s,r,o,a)=>(QY.copy(a),QY.applyMatrix4(t$),t.shapecast({intersectsBounds:t=>QY.intersectsBox(t),intersectsRange:(t,s,a,l,c)=>i(e,n,t,s,r,o,l,c)}))});return c$.releasePrimitive(l),c$.releasePrimitive(c),u}intersectsBox(t,e){return e$.set(t.min,t.max,e),e$.needsUpdate=!0,this.shapecast({intersectsBounds:t=>e$.intersectsBox(t),intersectsTriangle:t=>e$.intersectsTriangle(t)})}intersectsSphere(t){return this.shapecast({intersectsBounds:e=>t.intersectsBox(e),intersectsTriangle:e=>e.intersectsSphere(t)})}closestPointToGeometry(t,e,n={},i={},s=0,r=1/0){t.boundingBox||t.computeBoundingBox(),e$.set(t.boundingBox.min,t.boundingBox.max,e),e$.needsUpdate=!0;const o=this.geometry,a=o.attributes.position,l=o.index,c=t.attributes.position,h=t.index,u=c$.getPrimitive(),d=c$.getPrimitive();let p=s$,_=r$,m=null,f=null;i&&(m=o$,f=a$);let g=1/0,v=null,y=null;return t$.copy(e).invert(),n$.matrix.copy(t$),this.shapecast({boundsTraverseOrder:t=>e$.distanceToBox(t,Math.min(g,r)),intersectsBounds:(t,e,n)=>n{if(t.boundsTree)return t.boundsTree.shapecast({boundsTraverseOrder:t=>n$.distanceToBox(t,Math.min(g,r)),intersectsBounds:(t,e,n)=>n{for(let o=3*t,x=3*(t+r);o(i$.copy(t).clamp(e.min,e.max),i$.distanceToSquared(t)),intersectsBounds:(t,e,n)=>n{e.closestPointToPoint(t,i$);const i=t.distanceToSquared(i$);return i{eY(0,new Float32Array(e),l$),t.union(l$)})),t}}const u$=h$.prototype.raycast;h$.prototype.raycast=function(...t){if(t[0].isMesh){console.warn('MeshBVH: The function signature and results frame for \\\\\\\"raycast\\\\\\\" has changed. See docs for new signature.');const[e,n,i,s]=t;return u$.call(this,i,e.material).forEach((t=>{(t=SY(t,e,n))&&s.push(t)})),s}return u$.apply(this,t)};const d$=h$.prototype.raycastFirst;h$.prototype.raycastFirst=function(...t){if(t[0].isMesh){console.warn('MeshBVH: The function signature and results frame for \\\\\\\"raycastFirst\\\\\\\" has changed. See docs for new signature.');const[e,n,i]=t;return SY(d$.call(this,i,e.material),e,n)}return d$.apply(this,t)};const p$=h$.prototype.closestPointToPoint;h$.prototype.closestPointToPoint=function(...t){if(t[0].isMesh){console.warn('MeshBVH: The function signature and results frame for \\\\\\\"closestPointToPoint\\\\\\\" has changed. See docs for new signature.'),t.unshift();const e=t[1],n={};return t[1]=n,p$.apply(this,t),e&&e.copy(n.point),n.distance}return p$.apply(this,t)};const _$=h$.prototype.closestPointToGeometry;h$.prototype.closestPointToGeometry=function(...t){const e=t[2],n=t[3];if(e&&e.isVector3||n&&n.isVector3){console.warn('MeshBVH: The function signature and results frame for \\\\\\\"closestPointToGeometry\\\\\\\" has changed. See docs for new signature.');const i={},s={},r=t[1];return t[2]=i,t[3]=s,_$.apply(this,t),e&&e.copy(i.point),n&&n.copy(s.point).applyMatrix4(r),i.distance}return _$.apply(this,t)};const m$=h$.prototype.refit;h$.prototype.refit=function(...t){const e=t[0],n=t[1];if(n&&(n instanceof Set||Array.isArray(n))){console.warn('MeshBVH: The function signature for \\\\\\\"refit\\\\\\\" has changed. See docs for new signature.');const t=new Set;n.forEach((e=>t.add(e))),e&&e.forEach((e=>t.add(e))),m$.call(this,t)}else m$.apply(this,t)},[\\\\\\\"intersectsGeometry\\\\\\\",\\\\\\\"shapecast\\\\\\\",\\\\\\\"intersectsBox\\\\\\\",\\\\\\\"intersectsSphere\\\\\\\"].forEach((t=>{const e=h$.prototype[t];h$.prototype[t]=function(...n){return(null===n[0]||n[0].isMesh)&&(n.shift(),console.warn(`MeshBVH: The function signature for \\\\\\\"${t}\\\\\\\" has changed and no longer takes Mesh. See docs for new signature.`)),e.apply(this,n)}}));const f$=new tw,g$=new ew,v$=MT.prototype.raycast;function y$(t,e){if(this.geometry.boundsTree){if(void 0===this.material)return;g$.copy(this.matrixWorld).invert(),f$.copy(t.ray).applyMatrix4(g$);const n=this.geometry.boundsTree;if(!0===t.firstHitOnly){const i=SY(n.raycastFirst(f$,this.material),this,t);i&&e.push(i)}else{const i=n.raycast(f$,this.material);for(let n=0,s=i.length;n{if(t===i||e)return r++,!0;s&&r++}),n);let o=0;const a=new Float32Array(24*r);let l,c;e.traverse(((t,e,n)=>{const r=t===i||e;if(r||s){eY(0,n,x$);const{min:t,max:e}=x$;for(let n=-1;n<=1;n+=2){const i=n<0?t.x:e.x;for(let n=-1;n<=1;n+=2){const s=n<0?t.y:e.y;for(let n=-1;n<=1;n+=2){const r=n<0?t.z:e.z;a[o+0]=i,a[o+1]=s,a[o+2]=r,o+=3}}}return r}}),n),c=this.displayEdges?new Uint8Array([0,4,1,5,2,6,3,7,0,2,1,3,4,6,5,7,0,1,2,3,4,5,6,7]):new Uint8Array([0,1,2,2,1,3,4,6,5,6,7,5,1,4,5,0,4,1,2,3,6,3,7,6,0,2,4,2,6,4,1,5,3,3,5,7]),l=a.length>65535?new Uint32Array(c.length*r):new Uint16Array(c.length*r);const h=c.length;for(let t=0;te;)this._roots.pop();for(let t=0;t=this._roots.length){const e=new b$(this.mesh,this.edgeMaterial,this.depth,t);this.add(e),this._roots.push(e)}const e=this._roots[t];e.depth=this.depth,e.mesh=this.mesh,e.displayParents=this.displayParents,e.displayEdges=this.displayEdges,e.material=this.displayEdges?this.edgeMaterial:this.meshMaterial,e.update()}}updateMatrixWorld(...t){this.position.copy(this.mesh.position),this.rotation.copy(this.mesh.rotation),this.scale.copy(this.mesh.scale),super.updateMatrixWorld(...t)}copy(t){this.depth=t.depth,this.mesh=t.mesh}clone(){return new w$(this.mesh,this.depth)}dispose(){this.edgeMaterial.dispose(),this.meshMaterial.dispose();const t=this.children;for(let e=0,n=t.length;e{const i=t;if(i.isMesh){if(e.keepOnlyPosition){const t=i.geometry;for(const e in t.attributes)\\\\\\\"position\\\\\\\"!==e&&t.deleteAttribute(e)}n.push(i)}}))}const i=this._makeCompact(n);if(i){i.matrixAutoUpdate=!1,i.raycast=y$;const t=new h$(i.geometry,{verbose:!1});return i.geometry.boundsTree=t,this.createCoreGroupFromObjects([i])}return this.createCoreGroupFromObjects([])}_makeCompact(t){var e,n;const i=[];let s;for(let e of t){s=s||e.material;const t=e.geometry;t.applyMatrix4(e.matrix),i.push(t)}try{const t=fr.mergeGeometries(i);if(t){return this.createObject(t,Ns.MESH,s)}null===(e=this.states)||void 0===e||e.error.set(\\\\\\\"merge failed, check that input geometries have the same attributes\\\\\\\")}catch(t){null===(n=this.states)||void 0===n||n.error.set(t.message)}}}T$.DEFAULT_PARAMS={keepOnlyPosition:!1},T$.INPUT_CLONED_STATE=Ki.ALWAYS;const A$=T$.DEFAULT_PARAMS;const M$=new class extends ua{constructor(){super(...arguments),this.keepOnlyPosition=ha.BOOLEAN(A$.keepOnlyPosition)}};class E$ extends lV{constructor(){super(...arguments),this.paramsConfig=M$}static type(){return\\\\\\\"BVH\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to create BVH from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(T$.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new T$(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class S$ extends sV{static type(){return\\\\\\\"BVHVisualizer\\\\\\\"}cook(t,e){const n=t[0].objects()[0],i=new w$(n,e.depth);return i.opacity=1,i.update(),this.createCoreGroupFromObjects([i])}}S$.DEFAULT_PARAMS={depth:0},S$.INPUT_CLONED_STATE=Ki.NEVER;const C$=S$.DEFAULT_PARAMS;const N$=new class extends ua{constructor(){super(...arguments),this.depth=ha.INTEGER(C$.depth,{range:[0,20],rangeLocked:[!0,!1]})}};class L$ extends lV{constructor(){super(...arguments),this.paramsConfig=N$}static type(){return\\\\\\\"BVHVisualizer\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry with bvh\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(S$.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new S$(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class O$ extends C.a{constructor(t,e,n,i=1){\\\\\\\"number\\\\\\\"==typeof n&&(i=n,n=!1,console.error(\\\\\\\"THREE.InstancedBufferAttribute: The constructor now expects normalized as the third argument.\\\\\\\")),super(t,e,n),this.meshPerAttribute=i}copy(t){return super.copy(t),this.meshPerAttribute=t.meshPerAttribute,this}toJSON(){const t=super.toJSON();return t.meshPerAttribute=this.meshPerAttribute,t.isInstancedBufferAttribute=!0,t}}O$.prototype.isInstancedBufferAttribute=!0;const P$=new A.a,R$=new A.a,I$=[],F$=new B.a;class D$ extends B.a{constructor(t,e,n){super(t,e),this.instanceMatrix=new O$(new Float32Array(16*n),16),this.instanceColor=null,this.count=n,this.frustumCulled=!1}copy(t){return super.copy(t),this.instanceMatrix.copy(t.instanceMatrix),null!==t.instanceColor&&(this.instanceColor=t.instanceColor.clone()),this.count=t.count,this}getColorAt(t,e){e.fromArray(this.instanceColor.array,3*t)}getMatrixAt(t,e){e.fromArray(this.instanceMatrix.array,16*t)}raycast(t,e){const n=this.matrixWorld,i=this.count;if(F$.geometry=this.geometry,F$.material=this.material,void 0!==F$.material)for(let s=0;st.far||e.push({distance:a,point:z$.clone(),uv:tr.a.getUV(z$,j$,W$,q$,X$,Y$,$$,new d.a),face:null,object:this})}copy(t){return super.copy(t),void 0!==t.center&&this.center.copy(t.center),this.material=t.material,this}}function Z$(t,e,n,i,s,r){G$.subVectors(t,n).addScalar(.5).multiply(i),void 0!==s?(V$.x=r*G$.x-s*G$.y,V$.y=s*G$.x+r*G$.y):V$.copy(G$),t.copy(e),t.x+=V$.x,t.y+=V$.y,t.applyMatrix4(H$)}J$.prototype.isSprite=!0;var Q$=n(92),K$=n(81),tJ=n(46);class eJ{constructor(){this.coefficients=[];for(let t=0;t<9;t++)this.coefficients.push(new p.a)}set(t){for(let e=0;e<9;e++)this.coefficients[e].copy(t[e]);return this}zero(){for(let t=0;t<9;t++)this.coefficients[t].set(0,0,0);return this}getAt(t,e){const n=t.x,i=t.y,s=t.z,r=this.coefficients;return e.copy(r[0]).multiplyScalar(.282095),e.addScaledVector(r[1],.488603*i),e.addScaledVector(r[2],.488603*s),e.addScaledVector(r[3],.488603*n),e.addScaledVector(r[4],n*i*1.092548),e.addScaledVector(r[5],i*s*1.092548),e.addScaledVector(r[6],.315392*(3*s*s-1)),e.addScaledVector(r[7],n*s*1.092548),e.addScaledVector(r[8],.546274*(n*n-i*i)),e}getIrradianceAt(t,e){const n=t.x,i=t.y,s=t.z,r=this.coefficients;return e.copy(r[0]).multiplyScalar(.886227),e.addScaledVector(r[1],1.023328*i),e.addScaledVector(r[2],1.023328*s),e.addScaledVector(r[3],1.023328*n),e.addScaledVector(r[4],.858086*n*i),e.addScaledVector(r[5],.858086*i*s),e.addScaledVector(r[6],.743125*s*s-.247708),e.addScaledVector(r[7],.858086*n*s),e.addScaledVector(r[8],.429043*(n*n-i*i)),e}add(t){for(let e=0;e<9;e++)this.coefficients[e].add(t.coefficients[e]);return this}addScaledSH(t,e){for(let n=0;n<9;n++)this.coefficients[n].addScaledVector(t.coefficients[n],e);return this}scale(t){for(let e=0;e<9;e++)this.coefficients[e].multiplyScalar(t);return this}lerp(t,e){for(let n=0;n<9;n++)this.coefficients[n].lerp(t.coefficients[n],e);return this}equals(t){for(let e=0;e<9;e++)if(!this.coefficients[e].equals(t.coefficients[e]))return!1;return!0}copy(t){return this.set(t.coefficients)}clone(){return(new this.constructor).copy(this)}fromArray(t,e=0){const n=this.coefficients;for(let i=0;i<9;i++)n[i].fromArray(t,e+3*i);return this}toArray(t=[],e=0){const n=this.coefficients;for(let i=0;i<9;i++)n[i].toArray(t,e+3*i);return t}static getBasisAt(t,e){const n=t.x,i=t.y,s=t.z;e[0]=.282095,e[1]=.488603*i,e[2]=.488603*s,e[3]=.488603*n,e[4]=1.092548*n*i,e[5]=1.092548*i*s,e[6]=.315392*(3*s*s-1),e[7]=1.092548*n*s,e[8]=.546274*(n*n-i*i)}}eJ.prototype.isSphericalHarmonics3=!0;class nJ extends cv.a{constructor(t=new eJ,e=1){super(void 0,e),this.sh=t}copy(t){return super.copy(t),this.sh.copy(t.sh),this}fromJSON(t){return this.intensity=t.intensity,this.sh.fromArray(t.sh),this}toJSON(t){const e=super.toJSON(t);return e.object.sh=this.sh.toArray(),e}}nJ.prototype.isLightProbe=!0;var iJ=n(63),sJ=n(43);class rJ extends S.a{constructor(){super(),this.type=\\\\\\\"InstancedBufferGeometry\\\\\\\",this.instanceCount=1/0}copy(t){return super.copy(t),this.instanceCount=t.instanceCount,this}clone(){return(new this.constructor).copy(this)}toJSON(){const t=super.toJSON(this);return t.instanceCount=this.instanceCount,t.isInstancedBufferGeometry=!0,t}}rJ.prototype.isInstancedBufferGeometry=!0;class oJ extends Vf.a{constructor(t){super(t)}load(t,e,n,i){const s=this,r=new Gf.a(s.manager);r.setPath(s.path),r.setRequestHeader(s.requestHeader),r.setWithCredentials(s.withCredentials),r.load(t,(function(n){try{e(s.parse(JSON.parse(n)))}catch(e){i?i(e):console.error(e),s.manager.itemError(t)}}),n,i)}parse(t){const e={},n={};function i(t,i){if(void 0!==e[i])return e[i];const s=t.interleavedBuffers[i],r=function(t,e){if(void 0!==n[e])return n[e];const i=t.arrayBuffers[e],s=new Uint32Array(i).buffer;return n[e]=s,s}(t,s.buffer),o=Object(It.c)(s.type,r),a=new cr.a(o,s.stride);return a.uuid=s.uuid,e[i]=a,a}const s=t.isInstancedBufferGeometry?new rJ:new S.a,r=t.data.index;if(void 0!==r){const t=Object(It.c)(r.type,r.array);s.setIndex(new C.a(t,1))}const o=t.data.attributes;for(const e in o){const n=o[e];let r;if(n.isInterleavedBufferAttribute){const e=i(t.data,n.data);r=new hr.a(e,n.itemSize,n.offset,n.normalized)}else{const t=Object(It.c)(n.type,n.array);r=new(n.isInstancedBufferAttribute?O$:C.a)(t,n.itemSize,n.normalized)}void 0!==n.name&&(r.name=n.name),void 0!==n.usage&&r.setUsage(n.usage),void 0!==n.updateRange&&(r.updateRange.offset=n.updateRange.offset,r.updateRange.count=n.updateRange.count),s.setAttribute(e,r)}const a=t.data.morphAttributes;if(a)for(const e in a){const n=a[e],r=[];for(let e=0,s=n.length;eNumber.EPSILON){const u=Math.sqrt(h),p=Math.sqrt(l*l+c*c),_=e.x-a/u,m=e.y+o/u,f=((n.x-c/p-_)*c-(n.y+l/p-m)*l)/(o*c-a*l);i=_+o*f-t.x,s=m+a*f-t.y;const g=i*i+s*s;if(g<=2)return new d.a(i,s);r=Math.sqrt(g/2)}else{let t=!1;o>Number.EPSILON?l>Number.EPSILON&&(t=!0):o<-Number.EPSILON?l<-Number.EPSILON&&(t=!0):Math.sign(a)===Math.sign(c)&&(t=!0),t?(i=-a,s=o,r=Math.sqrt(h)):(i=o,s=a,r=Math.sqrt(h/2))}return new d.a(i/r,s/r)}const R=[];for(let t=0,e=C.length,n=e-1,i=t+1;t=0;t--){const e=t/m,n=h*Math.cos(e*Math.PI/2),i=u*Math.sin(e*Math.PI/2)+_;for(let t=0,e=C.length;t=0;){const i=n;let s=n-1;s<0&&(s=t.length-1);for(let t=0,n=a+2*m;t0){const n=new Xg.b(e);s=new iJ.a(n),s.setCrossOrigin(this.crossOrigin);for(let e=0,n=t.length;e0){i=new iJ.a(this.manager),i.setCrossOrigin(this.crossOrigin);for(let e=0,i=t.length;e{IJ.PARAM_CALLBACK_reset(t,e)}})}};class IJ extends lV{constructor(){super(...arguments),this.paramsConfig=RJ}static type(){return\\\\\\\"cache\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to cache\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1)}cook(t){const e=\\\\\\\"\\\\\\\"==this.pv.cache||null==this.pv.cache,n=t[0];if(e&&n){const t=[];for(let e of n.objects())t.push(e.toJSON());this.setCoreGroup(n),this.p.cache.set(JSON.stringify(t))}else if(this.pv.cache){const t=new NJ,e=JSON.parse(this.pv.cache),n=[];for(let i of e){const e=t.parse(i);n.push(e)}this.setObjects(n)}else this.setObjects([])}static PARAM_CALLBACK_reset(t,e){t.param_callback_PARAM_CALLBACK_reset()}async param_callback_PARAM_CALLBACK_reset(){this.p.cache.set(\\\\\\\"\\\\\\\"),this.compute()}}const FJ={direction:new p.a(0,1,0)},DJ=[new d.a(-1,-1),new d.a(-1,1),new d.a(1,1),new d.a(1,-1)],BJ=new p.a(0,0,1);const zJ=new class extends ua{constructor(){super(...arguments),this.camera=ha.NODE_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.OBJ,types:ds}}),this.direction=ha.VECTOR3(FJ.direction),this.offset=ha.FLOAT(0,{range:[-10,10],rangeLocked:[!1,!1]}),this.useSegmentsCount=ha.BOOLEAN(!0),this.stepSize=ha.FLOAT(1,{range:[.001,1],rangeLocked:[!1,!1],visibleIf:{useSegmentsCount:0}}),this.segments=ha.VECTOR2([10,10],{visibleIf:{useSegmentsCount:1}}),this.sizeMult=ha.FLOAT(1,{range:[0,2],rangeLocked:[!0,!1]}),this.updateOnWindowResize=ha.BOOLEAN(1),this.update=ha.BUTTON(null,{callback:t=>{kJ.PARAM_CALLBACK_update(t)}})}};class kJ extends lV{constructor(){super(...arguments),this.paramsConfig=zJ,this._plane=new Y.a,this._raycaster=new QL,this._planeCorners=[new p.a,new p.a,new p.a,new p.a],this._planeCenter=new p.a,this._core_transform=new vU,this.segments_count=new d.a(1,1),this.planeSize=new d.a}static type(){return\\\\\\\"cameraPlane\\\\\\\"}cook(){this._updateWindowControllerDependency();const t=this.pv.camera.nodeWithContext(ts.OBJ);if(!t)return this.states.error.set(\\\\\\\"no camera found\\\\\\\"),void this.cookController.endCook();if(!ds.includes(t.type()))return this.states.error.set(\\\\\\\"node found is not a camera\\\\\\\"),void this.cookController.endCook();const e=t.object;this._computePlaneParams(e)}_updateWindowControllerDependency(){this.pv.updateOnWindowResize?this.addGraphInput(this.scene().windowController.graphNode()):this.removeGraphInput(this.scene().windowController.graphNode())}_computePlaneParams(t){this._plane.normal.copy(this.pv.direction),this._plane.constant=this.pv.offset;let e=0;this._planeCenter.set(0,0,0);for(let n of DJ){this._raycaster.setFromCamera(n,t);const i=this._planeCorners[e];this._raycaster.ray.intersectPlane(this._plane,i),this._planeCenter.add(i),e++}this._planeCenter.multiplyScalar(.25);const n=this._planeCorners[1].distanceTo(this._planeCorners[2]),i=this._planeCorners[0].distanceTo(this._planeCorners[3]),s=this._planeCorners[0].distanceTo(this._planeCorners[1]),r=this._planeCorners[2].distanceTo(this._planeCorners[3]),o=Math.max(n,i)*this.pv.sizeMult,a=Math.max(s,r)*this.pv.sizeMult;this.planeSize.set(o,a);const l=this._createPlane(this.planeSize);this._core_transform.rotate_geometry(l,BJ,this.pv.direction);const c=this._core_transform.translation_matrix(this._planeCenter);l.applyMatrix4(c),this.setGeometry(l)}_createPlane(t){return t=t.clone(),this.pv.useSegmentsCount?(this.segments_count.x=Math.floor(this.pv.segments.x),this.segments_count.y=Math.floor(this.pv.segments.y)):this.pv.stepSize>0&&(this.segments_count.x=Math.floor(t.x/this.pv.stepSize),this.segments_count.y=Math.floor(t.y/this.pv.stepSize),t.x=this.segments_count.x*this.pv.stepSize,t.y=this.segments_count.y*this.pv.stepSize),new L(t.x,t.y,this.segments_count.x,this.segments_count.y)}static PARAM_CALLBACK_update(t){t._paramCallbackUpdate()}_paramCallbackUpdate(){this.setDirty()}}class UJ extends sV{constructor(){super(...arguments),this._pointPosition=new p.a}static type(){return\\\\\\\"cameraProject\\\\\\\"}cook(t,e){var n,i;const s=t[0],r=e.camera.nodeWithContext(ts.OBJ,null===(n=this.states)||void 0===n?void 0:n.error);if(r){const t=r.object;for(let n of s.points())n.getPosition(this._pointPosition),e.unproject?this._pointPosition.unproject(t):this._pointPosition.project(t),n.setPosition(this._pointPosition)}else null===(i=this.states)||void 0===i||i.error.set(\\\\\\\"cameraNode invalid.\\\\\\\");return s}}UJ.DEFAULT_PARAMS={camera:new yi(\\\\\\\"\\\\\\\"),unproject:!1},UJ.INPUT_CLONED_STATE=Ki.FROM_NODE;const GJ=UJ.DEFAULT_PARAMS;const VJ=new class extends ua{constructor(){super(...arguments),this.camera=ha.NODE_PATH(GJ.camera.path(),{nodeSelection:{context:ts.OBJ,types:ds}}),this.unproject=ha.BOOLEAN(GJ.unproject)}};class HJ extends lV{constructor(){super(...arguments),this.paramsConfig=VJ}static type(){return\\\\\\\"cameraProject\\\\\\\"}static displayedInputNames(){return[\\\\\\\"points to project/unproject\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(UJ.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new UJ(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class jJ extends sV{constructor(){super(...arguments),this._geo_center=new p.a}static type(){return\\\\\\\"center\\\\\\\"}cook(t,e){var n;const i=t[0].objectsWithGeo(),s=new Array(3*i.length);s.fill(0);for(let t=0;t0&&(r.push(t-1),r.push(t));r.push(e-1),r.push(0);const a=new S.a;return a.setAttribute(\\\\\\\"position\\\\\\\",new C.c(s,3)),a.setIndex(r),a}}const YJ=new p.a(0,0,1);class $J extends sV{constructor(){super(...arguments),this._core_transform=new vU}static type(){return\\\\\\\"circle\\\\\\\"}cook(t,e){return e.open?this._create_circle(e):this._create_disk(e)}_create_circle(t){const e=XJ.create(t.radius,t.segments,t.arcAngle);return this._core_transform.rotate_geometry(e,YJ,t.direction),this.createCoreGroupFromGeometry(e,Ns.LINE_SEGMENTS)}_create_disk(t){const e=new aJ(t.radius,t.segments);return this._core_transform.rotate_geometry(e,YJ,t.direction),this.createCoreGroupFromGeometry(e)}}$J.DEFAULT_PARAMS={radius:1,segments:12,open:!0,arcAngle:360,direction:new p.a(0,1,0)};const JJ=$J.DEFAULT_PARAMS;const ZJ=new class extends ua{constructor(){super(...arguments),this.radius=ha.FLOAT(JJ.radius),this.segments=ha.INTEGER(JJ.segments,{range:[1,50],rangeLocked:[!0,!1]}),this.open=ha.BOOLEAN(JJ.open),this.arcAngle=ha.FLOAT(JJ.arcAngle,{range:[0,360],rangeLocked:[!1,!1],visibleIf:{open:1}}),this.direction=ha.VECTOR3(JJ.direction)}};class QJ extends lV{constructor(){super(...arguments),this.paramsConfig=ZJ}static type(){return\\\\\\\"circle\\\\\\\"}initializeNode(){}cook(){this._operation=this._operation||new $J(this._scene,this.states);const t=this._operation.cook([],this.pv);this.setCoreGroup(t)}}var KJ;!function(t){t.SEGMENTS_COUNT=\\\\\\\"segments count\\\\\\\",t.SEGMENTS_LENGTH=\\\\\\\"segments length\\\\\\\"}(KJ||(KJ={}));const tZ=[KJ.SEGMENTS_COUNT,KJ.SEGMENTS_LENGTH];var eZ;!function(t){t.ABC=\\\\\\\"abc\\\\\\\",t.ACB=\\\\\\\"acb\\\\\\\",t.AB=\\\\\\\"ab\\\\\\\",t.BC=\\\\\\\"bc\\\\\\\",t.AC=\\\\\\\"ac\\\\\\\"}(eZ||(eZ={}));const nZ=[eZ.ABC,eZ.ACB,eZ.AB,eZ.AC,eZ.BC];class iZ{constructor(t){this.params=t,this.a=new p.a,this.b=new p.a,this.c=new p.a,this.an=new p.a,this.bn=new p.a,this.cn=new p.a,this.ac=new p.a,this.ab=new p.a,this.ab_x_ac=new p.a,this.part0=new p.a,this.part1=new p.a,this.divider=1,this.a_center=new p.a,this.center=new p.a,this.normal=new p.a,this.radius=1,this.x=new p.a,this.y=new p.a,this.z=new p.a,this.angle_ab=1,this.angle_ac=1,this.angle_bc=1,this.angle=2*Math.PI,this.x_rotated=new p.a,this._created_geometries={}}created_geometries(){return this._created_geometries}create(t,e,n){this.a.copy(t),this.b.copy(e),this.c.copy(n),this._compute_axis(),this._create_arc(),this._create_center()}_create_arc(){this._compute_angle();const t=this._points_count(),e=new Array(3*t),n=new Array(t),i=this.angle/(t-1);this.x_rotated.copy(this.x).multiplyScalar(this.radius);let s=0;for(s=0;s0&&(n[2*(s-1)]=s-1,n[2*(s-1)+1]=s);this.params.full&&(n.push(s-1),n.push(0));const r=new S.a;if(r.setAttribute(\\\\\\\"position\\\\\\\",new C.a(new Float32Array(e),3)),r.setIndex(n),this.params.addIdAttribute||this.params.addIdnAttribute){const e=new Array(t);for(let t=0;te/(t-1)));this.params.addIdnAttribute&&r.setAttribute(\\\\\\\"idn\\\\\\\",new C.a(new Float32Array(n),1))}this._created_geometries.arc=r}_create_center(){if(!this.params.center)return;const t=new S.a,e=[this.center.x,this.center.y,this.center.z];t.setAttribute(\\\\\\\"position\\\\\\\",new C.a(new Float32Array(e),3)),this._created_geometries.center=t}_compute_axis(){this.ac.copy(this.c).sub(this.a),this.ab.copy(this.b).sub(this.a),this.ab_x_ac.copy(this.ab).cross(this.ac),this.divider=2*this.ab_x_ac.lengthSq(),this.part0.copy(this.ab_x_ac).cross(this.ab).multiplyScalar(this.ac.lengthSq()),this.part1.copy(this.ac).cross(this.ab_x_ac).multiplyScalar(this.ab.lengthSq()),this.a_center.copy(this.part0).add(this.part1).divideScalar(this.divider),this.radius=this.a_center.length(),this.normal.copy(this.ab_x_ac).normalize(),this.center.copy(this.a).add(this.a_center)}_compute_angle(){this.params.arc&&(this.params.full?(this.x.copy(this.a).sub(this.center).normalize(),this.angle=2*Math.PI):(this.an.copy(this.a).sub(this.center).normalize(),this.bn.copy(this.b).sub(this.center).normalize(),this.cn.copy(this.c).sub(this.center).normalize(),this._set_x_from_joinMode(),this.y.copy(this.normal),this.z.copy(this.x).cross(this.y).normalize(),this.angle_ab=this.an.angleTo(this.bn),this.angle_ac=this.an.angleTo(this.cn),this.angle_bc=this.bn.angleTo(this.cn),this._set_angle_from_joinMode()))}_points_count(){const t=this.params.pointsCountMode;switch(t){case KJ.SEGMENTS_COUNT:return this.params.segmentsCount+1;case KJ.SEGMENTS_LENGTH:{let t=Math.PI*this.radius*this.radius;return this.params.full||(t*=Math.abs(this.angle)/(2*Math.PI)),Math.ceil(t/this.params.segmentsLength)}}os.unreachable(t)}_set_x_from_joinMode(){const t=this.params.joinMode;switch(this.x.copy(this.a).sub(this.center).normalize(),t){case eZ.ABC:case eZ.ACB:case eZ.AB:case eZ.AC:return this.x.copy(this.an);case eZ.BC:return this.x.copy(this.bn)}os.unreachable(t)}_set_angle_from_joinMode(){const t=this.params.joinMode;switch(t){case eZ.ABC:return void(this.angle=this.angle_ab+this.angle_bc);case eZ.ACB:return this.angle=this.angle_ac+this.angle_bc,void(this.angle*=-1);case eZ.AB:return void(this.angle=this.angle_ab);case eZ.AC:return this.angle=this.angle_ac,void(this.angle*=-1);case eZ.BC:return void(this.angle=this.angle_bc)}os.unreachable(t)}}const sZ=new class extends ua{constructor(){super(...arguments),this.arc=ha.BOOLEAN(1),this.pointsCountMode=ha.INTEGER(tZ.indexOf(KJ.SEGMENTS_COUNT),{visibleIf:{arc:1},menu:{entries:tZ.map(((t,e)=>({value:e,name:t})))}}),this.segmentsLength=ha.FLOAT(.1,{visibleIf:{arc:1,pointsCountMode:tZ.indexOf(KJ.SEGMENTS_LENGTH)},range:[0,1],rangeLocked:[!0,!1]}),this.segmentsCount=ha.INTEGER(100,{visibleIf:{arc:1,pointsCountMode:tZ.indexOf(KJ.SEGMENTS_COUNT)},range:[1,100],rangeLocked:[!0,!1]}),this.full=ha.BOOLEAN(1,{visibleIf:{arc:1}}),this.joinMode=ha.INTEGER(nZ.indexOf(eZ.ABC),{visibleIf:{arc:1,full:0},menu:{entries:nZ.map(((t,e)=>({value:e,name:t})))}}),this.addIdAttribute=ha.BOOLEAN(1),this.addIdnAttribute=ha.BOOLEAN(1),this.center=ha.BOOLEAN(0)}};class rZ extends lV{constructor(){super(...arguments),this.paramsConfig=sZ,this.a=new p.a,this.b=new p.a,this.c=new p.a}static type(){return\\\\\\\"circle3Points\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState([Ki.NEVER])}cook(t){const e=t[0].points();e.length<3?this.states.error.set(`only ${e.length} points found, when 3 are required`):this._create_circle(e)}_create_circle(t){const e=new iZ({arc:this.pv.arc,center:this.pv.center,pointsCountMode:tZ[this.pv.pointsCountMode],segmentsLength:this.pv.segmentsLength,segmentsCount:this.pv.segmentsCount,full:this.pv.full,joinMode:nZ[this.pv.joinMode],addIdAttribute:this.pv.addIdAttribute,addIdnAttribute:this.pv.addIdnAttribute});t[0].getPosition(this.a),t[1].getPosition(this.b),t[2].getPosition(this.c),e.create(this.a,this.b,this.c);const n=[],i=e.created_geometries();i.arc&&n.push(this.createObject(i.arc,Ns.LINE_SEGMENTS)),i.center&&n.push(this.createObject(i.center,Ns.POINTS)),this.setObjects(n)}}const oZ=new p.a,aZ=new Oy;class lZ extends sV{constructor(){super(...arguments),this._plane=new Y.a}static type(){return\\\\\\\"clip\\\\\\\"}cook(t,e){const n=t[0].objectsWithGeo()[0];this._plane.set(e.direction,e.distance),this._plane.translate(e.origin);const i=this._createClipGeo(n);return i?this.createCoreGroupFromObjects([i]):this.createCoreGroupFromObjects([])}_createClipGeo(t){var e;const n=t;if(!n.geometry.boundsTree)return void(null===(e=this.states)||void 0===e||e.error.set(\\\\\\\"no BVH found on input geo, make sure to use a BVH SOP node\\\\\\\"));const i=n.geometry.boundsTree,s=t=>{let e=0;return i.shapecast({intersectsBounds:t=>this._plane.intersectsBox(t),intersectsTriangle:n=>{let i=0;aZ.start.copy(n.a),aZ.end.copy(n.b),this._plane.intersectLine(aZ,oZ)&&(null==t||t.setXYZ(e,oZ.x,oZ.y,oZ.z),e++,i++),aZ.start.copy(n.b),aZ.end.copy(n.c),this._plane.intersectLine(aZ,oZ)&&(null==t||t.setXYZ(e,oZ.x,oZ.y,oZ.z),i++,e++),aZ.start.copy(n.c),aZ.end.copy(n.a),this._plane.intersectLine(aZ,oZ)&&(null==t||t.setXYZ(e,oZ.x,oZ.y,oZ.z),i++,e++),2!==i&&(e-=i)}}),{index:e}},{index:r}=s(),o=new S.a,a=new C.a(new Float32Array(3*r),3,!1);o.setAttribute(\\\\\\\"position\\\\\\\",a);const l=new Ms.a(o,js.MATERIALS[Ns.LINE_SEGMENTS]);l.frustumCulled=!1;return s(l.geometry.attributes.position),l}}lZ.DEFAULT_PARAMS={origin:new p.a(0,0,0),distance:0,direction:new p.a(0,1,0)},lZ.INPUT_CLONED_STATE=Ki.NEVER;const cZ=lZ.DEFAULT_PARAMS;const hZ=new class extends ua{constructor(){super(...arguments),this.origin=ha.VECTOR3(cZ.origin),this.distance=ha.FLOAT(cZ.distance,{range:[-10,10],rangeLocked:[!1,!1]}),this.direction=ha.VECTOR3(cZ.direction)}};class uZ extends lV{constructor(){super(...arguments),this.paramsConfig=hZ}static type(){return\\\\\\\"clip\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(lZ.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new lZ(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class dZ extends sV{static type(){return\\\\\\\"color\\\\\\\"}cook(t,e){}}dZ.DEFAULT_PARAMS={fromAttribute:!1,attribName:\\\\\\\"\\\\\\\",color:new D.a(1,1,1),asHsv:!1};const pZ=new D.a(1,1,1),_Z=\\\\\\\"color\\\\\\\",mZ=dZ.DEFAULT_PARAMS;const fZ=new class extends ua{constructor(){super(...arguments),this.fromAttribute=ha.BOOLEAN(mZ.fromAttribute),this.attribName=ha.STRING(mZ.attribName,{visibleIf:{fromAttribute:1}}),this.color=ha.COLOR(mZ.color,{visibleIf:{fromAttribute:0},expression:{forEntities:!0}}),this.asHsv=ha.BOOLEAN(mZ.asHsv,{visibleIf:{fromAttribute:0}})}};class gZ extends lV{constructor(){super(...arguments),this.paramsConfig=fZ,this._r_arrays_by_geometry_uuid={},this._g_arrays_by_geometry_uuid={},this._b_arrays_by_geometry_uuid={}}static type(){return\\\\\\\"color\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to update color of\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Ki.FROM_NODE)}async cook(t){const e=t[0],n=e.coreObjects();for(let t of n)if(this.pv.fromAttribute)this._set_fromAttribute(t);else{this.p.color.hasExpression()?await this._eval_expressions(t):this._eval_simple_values(t)}if(!this.io.inputs.cloneRequired(0)){const t=e.geometries();for(let e of t)e.getAttribute(_Z).needsUpdate=!0}this.setCoreGroup(e)}_set_fromAttribute(t){const e=t.coreGeometry();if(!e)return;this._create_init_color(e,pZ);const n=e.points(),i=e.attribSize(this.pv.attribName),s=e.geometry(),r=s.getAttribute(this.pv.attribName).array,o=s.getAttribute(_Z).array;switch(i){case 1:for(let t=0;t{a[t.index()]=e}));else for(let t of n)e[3*t.index()+i]=r;return a}_init_array_if_required(t,e,n){const i=t.uuid,s=e[i];return s?s.length{const e=new A.a;return this._matrix_from_point(t,e),e}))}_matrix_from_point(t,e){const n=t.position();this._is_scale_present?t.attribValue(\\\\\\\"scale\\\\\\\",this._point_scale):this._point_scale.copy(bZ.SCALE);const i=this._is_pscale_present?t.attribValue(\\\\\\\"pscale\\\\\\\"):bZ.PSCALE;this._point_scale.multiplyScalar(i);const s=this._matrices.scale;s.makeScale(this._point_scale.x,this._point_scale.y,this._point_scale.z);const r=this._matrices.translate;if(r.makeTranslation(n.x,n.y,n.z),e.multiply(r),this._do_rotate_matrices){const n=this._matrices.rotate,i=bZ.EYE;t.attribValue(\\\\\\\"normal\\\\\\\",this._point_normal),this._point_normal.multiplyScalar(-1),this._is_up_present?t.attribValue(\\\\\\\"up\\\\\\\",this._point_up):this._point_up.copy(bZ.UP),this._point_up.normalize(),n.lookAt(i,this._point_normal,this._point_up),e.multiply(n)}e.multiply(s)}static create_instance_buffer_geo(t,e,n){const i=e.points(),s=new rJ;s.copy(t),s.instanceCount=1/0;const r=i.length,o=new Float32Array(3*r),a=new Float32Array(3*r),l=new Float32Array(3*r),c=new Float32Array(4*r),h=e.hasAttrib(AZ),u=new p.a(0,0,0),d=new hh.a,_=new p.a(1,1,1),f=new SZ(e).matrices();i.forEach(((t,e)=>{const n=3*e,i=4*e;f[e].decompose(u,d,_),u.toArray(o,n),d.toArray(c,i),_.toArray(l,n);(h?t.attribValue(AZ,this._point_color):wZ).toArray(a,n)}));const g=e.hasAttrib(\\\\\\\"uv\\\\\\\");if(g){const t=new Float32Array(2*r);i.forEach(((e,n)=>{const i=2*n;(g?e.attribValue(\\\\\\\"uv\\\\\\\",this._point_uv):TZ).toArray(t,i)})),s.setAttribute(MZ.UV,new O$(t,2))}s.setAttribute(MZ.POSITION,new O$(o,3)),s.setAttribute(MZ.SCALE,new O$(l,3)),s.setAttribute(MZ.ORIENTATION,new O$(c,4)),s.setAttribute(MZ.COLOR,new O$(a,3));e.attribNamesMatchingMask(n).forEach((t=>{const n=e.attribSize(t),o=new Float32Array(r*n);i.forEach(((e,i)=>{const s=e.attribValue(t);m.isNumber(s)?o[i]=s:s.toArray(o,i*n)})),s.setAttribute(t,new O$(o,n))}));return new fr(s).markAsInstance(),s}}SZ._point_color=new p.a,SZ._point_uv=new d.a;class CZ extends ah{set_point(t){this._point=t,this.setDirty(),this.removeDirtyState()}value(t){return this._point?t?this._point.attribValue(t):this._point.index():this._global_index}}!function(t){t[t.OBJECT=0]=\\\\\\\"OBJECT\\\\\\\",t[t.GEOMETRY=1]=\\\\\\\"GEOMETRY\\\\\\\"}(EZ||(EZ={}));const NZ=[EZ.OBJECT,EZ.GEOMETRY],LZ=[{name:\\\\\\\"object\\\\\\\",value:EZ.OBJECT},{name:\\\\\\\"geometry\\\\\\\",value:EZ.GEOMETRY}];const OZ=new class extends ua{constructor(){super(...arguments),this.count=ha.INTEGER(1,{range:[1,20],rangeLocked:[!0,!1]}),this.transformOnly=ha.BOOLEAN(0),this.transformMode=ha.INTEGER(0,{menu:{entries:LZ}}),this.copyAttributes=ha.BOOLEAN(0),this.attributesToCopy=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{copyAttributes:!0}}),this.useCopyExpr=ha.BOOLEAN(0)}};class PZ extends lV{constructor(){super(...arguments),this.paramsConfig=OZ,this._attribute_names_to_copy=[],this._objects=[],this._object_position=new p.a}static type(){return\\\\\\\"copy\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to be copied\\\\\\\",\\\\\\\"points to copy to\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1,2),this.io.inputs.initInputsClonedState([Ki.ALWAYS,Ki.NEVER])}async cook(t){const e=t[0];if(!this.io.inputs.has_input(1))return void await this.cook_without_template(e);const n=t[1];n?await this.cook_with_template(e,n):this.states.error.set(\\\\\\\"second input invalid\\\\\\\")}async cook_with_template(t,e){this._objects=[];const n=e.points(),i=new SZ(e).matrices();this._attribute_names_to_copy=ss.attribNames(this.pv.attributesToCopy).filter((t=>e.hasAttrib(t))),await this._copy_moved_objects_on_template_points(t,i,n),this.setObjects(this._objects)}async _copy_moved_objects_on_template_points(t,e,n){for(let i=0;i{const e=br.clone(t);this._objects.push(e)}))}async cook_without_template(t){this._objects=[],await this._copy_moved_objects_for_each_instance(t),this.setObjects(this._objects)}_copyAttributes_from_template(t,e){this._attribute_names_to_copy.forEach(((n,i)=>{const s=e.attribValue(n);new br(t,i).addAttribute(n,s)}))}stamp_value(t){return this.stamp_node.value(t)}get stamp_node(){return this._stamp_node=this._stamp_node||this.create_stamp_node()}create_stamp_node(){const t=new CZ(this.scene());return this.dirtyController.setForbiddenTriggerNodes([t]),t}dispose(){super.dispose(),this._stamp_node&&this._stamp_node.dispose()}}const RZ=\\\\\\\"id\\\\\\\",IZ=\\\\\\\"class\\\\\\\",FZ=\\\\\\\"html\\\\\\\";class DZ extends sV{static type(){return\\\\\\\"CSS2DObject\\\\\\\"}cook(t,e){const n=t[0];if(n){const t=this._create_objects_from_input_points(n,e);return this.createCoreGroupFromObjects(t)}{const t=this._create_object_from_scratch(e);return this.createCoreGroupFromObjects([t])}}_create_objects_from_input_points(t,e){const n=t.points(),i=[];for(let t of n){const n=e.useIdAttrib?t.attribValue(RZ):e.id,s=e.useClassAttrib?t.attribValue(IZ):e.className,r=e.useHTMLAttrib?t.attribValue(FZ):e.html,o=DZ.create_css_object({id:n,className:s,html:r}),a=o.element;if(e.copyAttributes){const n=ss.attribNames(e.attributesToCopy);for(let e of n){const n=t.attribValue(e);m.isString(n)?a.setAttribute(e,n):m.isNumber(n)&&a.setAttribute(e,`${n}`)}}o.position.copy(t.position()),o.updateMatrix(),i.push(o)}return i}_create_object_from_scratch(t){return DZ.create_css_object({id:t.id,className:t.className,html:t.html})}static create_css_object(t){const e=document.createElement(\\\\\\\"div\\\\\\\");e.id=t.id,e.className=t.className,e.innerHTML=t.html;const n=new cq(e);return n.matrixAutoUpdate=!1,n}}DZ.DEFAULT_PARAMS={useIdAttrib:!1,id:\\\\\\\"myCSSObject\\\\\\\",useClassAttrib:!1,className:\\\\\\\"CSS2DObject\\\\\\\",useHTMLAttrib:!1,html:\\\\\\\"
default html
\\\\\\\",copyAttributes:!1,attributesToCopy:\\\\\\\"\\\\\\\"},DZ.INPUT_CLONED_STATE=Ki.NEVER;const BZ=DZ.DEFAULT_PARAMS;const zZ=new class extends ua{constructor(){super(...arguments),this.useIdAttrib=ha.BOOLEAN(BZ.useIdAttrib),this.id=ha.STRING(BZ.id,{visibleIf:{useIdAttrib:0}}),this.useClassAttrib=ha.BOOLEAN(BZ.useClassAttrib),this.className=ha.STRING(BZ.className,{visibleIf:{useClassAttrib:0}}),this.useHTMLAttrib=ha.BOOLEAN(BZ.useHTMLAttrib),this.html=ha.STRING(BZ.html,{visibleIf:{useHTMLAttrib:0},multiline:!0}),this.copyAttributes=ha.BOOLEAN(BZ.copyAttributes),this.attributesToCopy=ha.STRING(BZ.attributesToCopy,{visibleIf:{copyAttributes:!0}})}};class kZ extends lV{constructor(){super(...arguments),this.paramsConfig=zZ}static type(){return\\\\\\\"CSS2DObject\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(DZ.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new DZ(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class UZ{constructor(t,e){this._size=t,this._type=e}size(){return this._size}type(){return this._type}static from_value(t){const e=m.isString(t)?zs.STRING:zs.NUMERIC;return new this(m.isArray(t)?t.length:1,e)}}class GZ{constructor(t={}){this._attribute_datas_by_name={},this._options={},this._options.dataKeysPrefix=t.dataKeysPrefix,this._options.skipEntries=t.skipEntries,this._options.doConvert=t.doConvert||!1,this._options.convertToNumeric=t.convertToNumeric}dataKeysPrefix(){return this._options.dataKeysPrefix}get_prefixed_json(t,e){if(0==e.length)return t;{const n=e.shift();if(n)return this.get_prefixed_json(t[n],e)}return[]}setJSON(t){return this._json=t}createObject(){const t=new S.a,e=new fr(t);if(null!=this._json){const n=this._json.length;e.initPositionAttribute(n),this._find_attributes();const i=ss.attribNames(this._options.convertToNumeric||\\\\\\\"\\\\\\\");for(let n of Object.keys(this._attribute_datas_by_name)){const s=Xs.remapName(n);let r=this._attribute_values_for_name(n).flat();const o=this._attribute_datas_by_name[n],a=o.size();if(o.type()===zs.STRING)if(this._options.doConvert&&ss.matchesOneMask(n,i)){const e=r.map((t=>m.isString(t)?parseFloat(t)||0:t));t.setAttribute(s,new C.c(e,a))}else{const t=Xs.arrayToIndexedArrays(r);e.setIndexedAttribute(s,t.values,t.indices)}else{const e=r;t.setAttribute(s,new C.c(e,a))}}}return t}_find_attributes(){let t;const e=ss.attribNames(this._options.skipEntries||\\\\\\\"\\\\\\\");if(this._json&&null!=(t=this._json[0]))for(let n of Object.keys(t)){const i=t[n];if(this._value_has_subentries(i))for(let t of Object.keys(i)){const s=[n,t].join(\\\\\\\":\\\\\\\"),r=i[n];ss.matchesOneMask(s,e)||(this._attribute_datas_by_name[s]=UZ.from_value(r))}else ss.matchesOneMask(n,e)||(this._attribute_datas_by_name[n]=UZ.from_value(i))}}_attribute_values_for_name(t){return this._json?this._json.map((e=>{const n=t.split(\\\\\\\":\\\\\\\")[0],i=e[n];if(this._value_has_subentries(i)){return i[t.substring(n.length+1)]||0}return i||0})):[]}_value_has_subentries(t){return m.isObject(t)&&!m.isArray(t)}}const VZ=JSON.stringify([{value:-40},{value:-30},{value:-20},{value:-10},{value:0},{value:10},{value:20},{value:30},{value:40},{value:50},{value:60},{value:70},{value:80}]);const HZ=new class extends ua{constructor(){super(...arguments),this.data=ha.STRING(VZ)}};class jZ extends lV{constructor(){super(...arguments),this.paramsConfig=HZ}static type(){return\\\\\\\"data\\\\\\\"}cook(){let t=null;try{t=JSON.parse(this.pv.data)}catch(t){this.states.error.set(\\\\\\\"could not parse json\\\\\\\")}if(t)try{const e=new GZ;e.setJSON(t);const n=e.createObject();this.setGeometry(n,Ns.POINTS)}catch(t){this.states.error.set(\\\\\\\"could not build geometry from json\\\\\\\")}else this.cookController.endCook()}}class WZ extends $g{constructor(t,e,n={},i){super(t,e,i),this._node=i,this._parser=new GZ(n)}async load(t,e,n){const i=await this._urlToLoad();fetch(i).then((async e=>{let n=await e.json();const i=this._parser.dataKeysPrefix();null!=i&&\\\\\\\"\\\\\\\"!=i&&(n=this._parser.get_prefixed_json(n,i.split(\\\\\\\".\\\\\\\"))),this._parser.setJSON(n);const s=this._parser.createObject();t(s)})).catch((t=>{li.error(\\\\\\\"error\\\\\\\",t),n(t)}))}}const qZ=\\\\\\\"position\\\\\\\";class XZ extends $g{constructor(t,e,n,i){super(t,e,i),this.attribute_names=n,this._node=i,this.attribute_names_from_first_line=!1,this.lines=[],this.points_count=0,this.attribute_values_by_name={},this.attribute_data_by_name={},this._loading=!1,this.attribute_names||(this.attribute_names_from_first_line=!0)}async load(){if(this._loading)return void console.warn(\\\\\\\"is already loading\\\\\\\");this._loading=!0,this.points_count=0,await this.loadData(),this.infer_types(),this.read_values();return this.create_points()}async loadData(){const t=await this._urlToLoad(),e=await fetch(t),n=await e.text();this.lines=n.split(\\\\\\\"\\\\n\\\\\\\"),this.attribute_names||(this.attribute_names=this.lines[0].split(XZ.SEPARATOR)),this.attribute_names=this.attribute_names.map((t=>Xs.remapName(t)));for(let t of this.attribute_names)this.attribute_values_by_name[t]=[]}infer_types(){const t=this.attribute_names_from_first_line?1:0;let e=this.lines[t].split(XZ.SEPARATOR);for(let t=0;tparseFloat(t)))}return t}return t}read_values(){if(!this.attribute_names)return;let t;for(let e=this.attribute_names_from_first_line?1:0;e=this.attribute_names.length){for(let t=0;t({name:t,value:e})))}}),this.url=ha.STRING(JZ,{fileBrowse:{type:[Rr.JSON]}}),this.jsonDataKeysPrefix=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{dataType:$Z.indexOf(YZ.JSON)}}),this.skipEntries=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{dataType:$Z.indexOf(YZ.JSON)}}),this.convert=ha.BOOLEAN(0,{visibleIf:{dataType:$Z.indexOf(YZ.JSON)}}),this.convertToNumeric=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{dataType:$Z.indexOf(YZ.JSON),convert:1}}),this.readAttribNamesFromFile=ha.BOOLEAN(1,{visibleIf:{dataType:$Z.indexOf(YZ.CSV)}}),this.attribNames=ha.STRING(\\\\\\\"height scale\\\\\\\",{visibleIf:{dataType:$Z.indexOf(YZ.CSV),readAttribNamesFromFile:0}}),this.reload=ha.BUTTON(null,{callback:(t,e)=>{QZ.PARAM_CALLBACK_reload(t,e)}})}};class QZ extends lV{constructor(){super(...arguments),this.paramsConfig=ZZ}static type(){return\\\\\\\"dataUrl\\\\\\\"}initializeNode(){this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.url],(()=>{const t=this.p.url.rawInput();if(t){const e=t.split(\\\\\\\"/\\\\\\\");return e[e.length-1]}return\\\\\\\"\\\\\\\"}))}))}))}async cook(){this._load()}_load(){switch($Z[this.pv.dataType]){case YZ.JSON:return this._loadJSON();case YZ.CSV:return this._loadCSV()}}_clearLoadedBlob(){switch($Z[this.pv.dataType]){case YZ.JSON:return this._resetJSON();case YZ.CSV:return this._resetCSV()}}_url(){const t=this.scene().assets.root();return t?`${t}${this.pv.url}`:this.pv.url}_loadJSON(){new WZ(this._url(),this.scene(),{dataKeysPrefix:this.pv.jsonDataKeysPrefix,skipEntries:this.pv.skipEntries,doConvert:this.pv.convert,convertToNumeric:this.pv.convertToNumeric},this).load(this._onLoad.bind(this),void 0,this._onError.bind(this))}_resetJSON(){new WZ(this._url(),this.scene()).deregisterUrl()}_onLoad(t){this.setGeometry(t,Ns.POINTS)}_onError(t){this.states.error.set(`could not load geometry from ${this._url()} (${t})`),this.cookController.endCook()}async _loadCSV(){const t=this.pv.readAttribNamesFromFile?void 0:this.pv.attribNames.split(\\\\\\\" \\\\\\\"),e=new XZ(this._url(),this.scene(),t,this),n=await e.load();n?this.setGeometry(n,Ns.POINTS):this.states.error.set(\\\\\\\"could not generate points\\\\\\\")}_resetCSV(){new XZ(this._url(),this.scene(),[],this).deregisterUrl()}static PARAM_CALLBACK_reload(t,e){t.param_callback_reload()}param_callback_reload(){this._clearLoadedBlob(),this.p.url.setDirty()}}class KZ extends S.a{constructor(t,e,n,i){super();const s=[],r=[],o=[],a=new p.a,l=new A.a;l.makeRotationFromEuler(n),l.setPosition(e);const c=new A.a;function h(e,n,i){n.applyMatrix4(t.matrixWorld),n.applyMatrix4(c),i.transformDirection(t.matrixWorld),e.push(new tQ(n.clone(),i.clone()))}function u(t,e){const n=[],s=.5*Math.abs(i.dot(e));for(let i=0;i0,u=t[i+1].position.dot(e)-s>0,p=t[i+2].position.dot(e)-s>0;switch(c=(h?1:0)+(u?1:0)+(p?1:0),c){case 0:n.push(t[i]),n.push(t[i+1]),n.push(t[i+2]);break;case 1:if(h&&(r=t[i+1],o=t[i+2],a=d(t[i],r,e,s),l=d(t[i],o,e,s)),u){r=t[i],o=t[i+2],a=d(t[i+1],r,e,s),l=d(t[i+1],o,e,s),n.push(a),n.push(o.clone()),n.push(r.clone()),n.push(o.clone()),n.push(a.clone()),n.push(l);break}p&&(r=t[i],o=t[i+1],a=d(t[i+2],r,e,s),l=d(t[i+2],o,e,s)),n.push(r.clone()),n.push(o.clone()),n.push(a),n.push(l),n.push(a.clone()),n.push(o.clone());break;case 2:h||(r=t[i].clone(),o=d(r,t[i+1],e,s),a=d(r,t[i+2],e,s),n.push(r),n.push(o),n.push(a)),u||(r=t[i+1].clone(),o=d(r,t[i+2],e,s),a=d(r,t[i],e,s),n.push(r),n.push(o),n.push(a)),p||(r=t[i+2].clone(),o=d(r,t[i],e,s),a=d(r,t[i+1],e,s),n.push(r),n.push(o),n.push(a))}}return n}function d(t,e,n,i){const s=t.position.dot(n)-i,r=s/(s-(e.position.dot(n)-i));return new tQ(new p.a(t.position.x+r*(e.position.x-t.position.x),t.position.y+r*(e.position.y-t.position.y),t.position.z+r*(e.position.z-t.position.z)),new p.a(t.normal.x+r*(e.normal.x-t.normal.x),t.normal.y+r*(e.normal.y-t.normal.y),t.normal.z+r*(e.normal.z-t.normal.z)))}c.copy(l).invert(),function(){let e=[];const n=new p.a,c=new p.a;if(!0===t.geometry.isGeometry)return void console.error(\\\\\\\"THREE.DecalGeometry no longer supports THREE.Geometry. Use BufferGeometry instead.\\\\\\\");const d=t.geometry,_=d.attributes.position,m=d.attributes.normal;if(null!==d.index){const t=d.index;for(let i=0;i{this.setCoreGroup(e)}),Math.max(this.pv.duration,0))}}class aQ{constructor(t){this.node=t,this.selected_state=new Map,this._entities_count=0,this._selected_entities_count=0}init(t){this.selected_state.clear();for(let e of t)this.selected_state.set(e,!1);this._entities_count=t.length,this._selected_entities_count=0}select(t){const e=this.selected_state.get(t);null!=e&&0==e&&(this.selected_state.set(t,!0),this._selected_entities_count++)}entities_to_keep(){return this._entities_for_state(this.node.pv.invert)}entities_to_delete(){return this._entities_for_state(!this.node.pv.invert)}_entities_for_state(t){const e=!!t,n=t?this._selected_entities_count:this._entities_count-this._selected_entities_count;if(0==n)return[];{const t=new Array(n);let i=0;return this.selected_state.forEach(((n,s)=>{n==e&&(t[i]=s,i++)})),t}}}var lQ;!function(t){t.EQUAL=\\\\\\\"==\\\\\\\",t.LESS_THAN=\\\\\\\"<\\\\\\\",t.EQUAL_OR_LESS_THAN=\\\\\\\"<=\\\\\\\",t.EQUAL_OR_GREATER_THAN=\\\\\\\">=\\\\\\\",t.GREATER_THAN=\\\\\\\">\\\\\\\",t.DIFFERENT=\\\\\\\"!=\\\\\\\"}(lQ||(lQ={}));const cQ=[lQ.EQUAL,lQ.LESS_THAN,lQ.EQUAL_OR_LESS_THAN,lQ.EQUAL_OR_GREATER_THAN,lQ.GREATER_THAN,lQ.DIFFERENT],hQ={[lQ.EQUAL]:(t,e)=>t==e,[lQ.LESS_THAN]:(t,e)=>tt<=e,[lQ.EQUAL_OR_GREATER_THAN]:(t,e)=>t>=e,[lQ.GREATER_THAN]:(t,e)=>t>e,[lQ.DIFFERENT]:(t,e)=>t!=e},uQ=cQ.map(((t,e)=>({name:t,value:e})));class dQ{constructor(t){this.node=t}evalForEntities(t){const e=ks[this.node.pv.attribType];switch(e){case zs.NUMERIC:return void this._eval_for_numeric(t);case zs.STRING:return void this._eval_for_string(t)}os.unreachable(e)}_eval_for_string(t){let e;for(let n of t)e=n.stringAttribValue(this.node.pv.attribName),e==this.node.pv.attribString&&this.node.entitySelectionHelper.select(n)}_eval_for_numeric(t){const e=Vs[this.node.pv.attribSize-1];switch(e){case Gs.FLOAT:return this._eval_for_points_numeric_float(t);case Gs.VECTOR2:return this._eval_for_points_numeric_vector2(t);case Gs.VECTOR3:return this._eval_for_points_numeric_vector3(t);case Gs.VECTOR4:return this._eval_for_points_numeric_vector4(t)}os.unreachable(e)}_eval_for_points_numeric_float(t){let e=this.node.pv.attribName;const n=this.node.pv.attribValue1;let i;const s=cQ[this.node.pv.attribComparisonOperator],r=hQ[s];for(let s of t)i=s.attribValue(e),r(i,n)&&this.node.entitySelectionHelper.select(s)}_eval_for_points_numeric_vector2(t){let e=this.node.pv.attribName;const n=this.node.pv.attribValue2;let i=new d.a;for(let s of t){const t=s.attribValue(e,i);n.equals(t)&&this.node.entitySelectionHelper.select(s)}}_eval_for_points_numeric_vector3(t){let e=this.node.pv.attribName;const n=this.node.pv.attribValue3;let i=new p.a;for(let s of t){const t=s.attribValue(e,i);n.equals(t)&&this.node.entitySelectionHelper.select(s)}}_eval_for_points_numeric_vector4(t){let e=this.node.pv.attribName;const n=this.node.pv.attribValue4;let i=new _.a;for(let s of t){const t=s.attribValue(e,i);n.equals(t)&&this.node.entitySelectionHelper.select(s)}}}class pQ{constructor(t){this.node=t}async evalForEntities(t){const e=this.node.p.expression;this.node.p.expression.hasExpression()&&e.expressionController?await this.eval_expressions_for_points_with_expression(t):this.eval_expressions_without_expression(t)}async eval_expressions_for_points_with_expression(t){const e=this.node.p.expression;e.expressionController&&await e.expressionController.computeExpressionForEntities(t,((t,e)=>{e&&this.node.entitySelectionHelper.select(t)}))}eval_expressions_without_expression(t){if(this.node.pv.expression)for(let e of t)this.node.entitySelectionHelper.select(e)}}class _Q{constructor(t){this.node=t,this._point_position=new p.a}evalForPoints(t){const e=this._createBbox();for(let n of t){e.containsPoint(n.getPosition(this._point_position))&&this.node.entitySelectionHelper.select(n)}}_createBbox(){return new Cy.a(this.node.pv.bboxCenter.clone().sub(this.node.pv.bboxSize.clone().multiplyScalar(.5)),this.node.pv.bboxCenter.clone().add(this.node.pv.bboxSize.clone().multiplyScalar(.5)))}}class mQ{constructor(t){this.node=t}eval_for_objects(t){const e=Ps[this.node.pv.objectType];for(let n of t){Os(n.object().constructor)==e&&this.node.entitySelectionHelper.select(n)}}}class fQ{constructor(){this._sidePropertyByMaterial=new WeakMap,this._bound_setMat=this._setObjectMaterialDoubleSided.bind(this),this._bound_restoreMat=this._restoreObjectMaterialSide.bind(this)}setCoreGroupMaterialDoubleSided(t){const e=t.objects();for(let t of e)t.traverse(this._bound_setMat)}restoreMaterialSideProperty(t){const e=t.objects();for(let t of e)t.traverse(this._bound_restoreMat)}_setObjectMaterialDoubleSided(t){const e=t.material;if(e)if(m.isArray(e))for(let t of e)this._setMaterialDoubleSided(t);else this._setMaterialDoubleSided(e)}_restoreObjectMaterialSide(t){const e=t.material;if(e)if(m.isArray(e))for(let t of e)this._restoreMaterialDoubleSided(t);else this._restoreMaterialDoubleSided(e)}_setMaterialDoubleSided(t){this._sidePropertyByMaterial.set(t,t.side),t.side=w.z}_restoreMaterialDoubleSided(t){t.side=this._sidePropertyByMaterial.get(t)||w.z}}const gQ=new p.a(0,1,0),vQ=new p.a(0,-1,0);class yQ{constructor(t){this.node=t,this._matDoubleSideTmpSetter=new fQ,this._point_position=new p.a,this._raycaster=new QL,this._intersections=[]}evalForPoints(t,e){if(!e)return;const n=null==e?void 0:e.objectsWithGeo()[0];if(!n)return;const i=n;if(!i.isMesh)return;this._matDoubleSideTmpSetter.setCoreGroupMaterialDoubleSided(e);const s=n.geometry;s.computeBoundingBox();const r=s.boundingBox;for(let e of t)e.getPosition(this._point_position),r.containsPoint(this._point_position)?this._isPositionInObject(this._point_position,i,gQ)&&this._isPositionInObject(this._point_position,i,vQ)&&this.node.entitySelectionHelper.select(e):this.node.entitySelectionHelper.select(e);this._matDoubleSideTmpSetter.restoreMaterialSideProperty(e)}_isPositionInObject(t,e,n){var i;this._raycaster.ray.direction.copy(n),this._raycaster.ray.origin.copy(t),this._intersections.length=0;const s=this._raycaster.intersectObject(e,!1,this._intersections);if(!s)return!1;if(0==s.length)return!1;const r=null===(i=s[0].face)||void 0===i?void 0:i.normal;if(!r)return!1;return this._raycaster.ray.direction.dot(r)>=0}}const xQ=new class extends ua{constructor(){super(...arguments),this.class=ha.INTEGER(Ds.indexOf(Fs.VERTEX),{menu:{entries:Bs}}),this.invert=ha.BOOLEAN(0),this.byObjectType=ha.BOOLEAN(0,{visibleIf:{class:Ds.indexOf(Fs.OBJECT)}}),this.objectType=ha.INTEGER(Ps.indexOf(Ns.MESH),{menu:{entries:Rs},visibleIf:{class:Ds.indexOf(Fs.OBJECT),byObjectType:!0},separatorAfter:!0}),this.byExpression=ha.BOOLEAN(0),this.expression=ha.BOOLEAN(\\\\\\\"@ptnum==0\\\\\\\",{visibleIf:{byExpression:!0},expression:{forEntities:!0},separatorAfter:!0}),this.byAttrib=ha.BOOLEAN(0),this.attribType=ha.INTEGER(ks.indexOf(zs.NUMERIC),{menu:{entries:Us},visibleIf:{byAttrib:1}}),this.attribName=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{byAttrib:1}}),this.attribSize=ha.INTEGER(1,{range:Hs,rangeLocked:[!0,!0],visibleIf:{byAttrib:1,attribType:ks.indexOf(zs.NUMERIC)}}),this.attribComparisonOperator=ha.INTEGER(cQ.indexOf(lQ.EQUAL),{menu:{entries:uQ},visibleIf:{byAttrib:!0,attribType:ks.indexOf(zs.NUMERIC),attribSize:Gs.FLOAT}}),this.attribValue1=ha.FLOAT(0,{visibleIf:{byAttrib:1,attribType:ks.indexOf(zs.NUMERIC),attribSize:1}}),this.attribValue2=ha.VECTOR2([0,0],{visibleIf:{byAttrib:1,attribType:ks.indexOf(zs.NUMERIC),attribSize:2}}),this.attribValue3=ha.VECTOR3([0,0,0],{visibleIf:{byAttrib:1,attribType:ks.indexOf(zs.NUMERIC),attribSize:3}}),this.attribValue4=ha.VECTOR4([0,0,0,0],{visibleIf:{byAttrib:1,attribType:ks.indexOf(zs.NUMERIC),attribSize:4}}),this.attribString=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{byAttrib:1,attribType:ks.indexOf(zs.STRING)},separatorAfter:!0}),this.byBbox=ha.BOOLEAN(0,{visibleIf:{class:Ds.indexOf(Fs.VERTEX)}}),this.bboxSize=ha.VECTOR3([1,1,1],{visibleIf:{class:Ds.indexOf(Fs.VERTEX),byBbox:!0}}),this.bboxCenter=ha.VECTOR3([0,0,0],{visibleIf:{class:Ds.indexOf(Fs.VERTEX),byBbox:!0},separatorAfter:!0}),this.byBoundingObject=ha.BOOLEAN(0,{visibleIf:{class:Ds.indexOf(Fs.VERTEX)}}),this.keepPoints=ha.BOOLEAN(0,{visibleIf:{class:Ds.indexOf(Fs.OBJECT)}})}};class bQ extends lV{constructor(){super(...arguments),this.paramsConfig=xQ,this._marked_for_deletion_per_object_index=new Map,this.entitySelectionHelper=new aQ(this),this.byExpressionHelper=new pQ(this),this.byAttributeHelper=new dQ(this),this.byObjectTypeHelper=new mQ(this),this.byBboxHelper=new _Q(this),this.byBoundingObjectHelper=new yQ(this)}static type(){return\\\\\\\"delete\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to delete from\\\\\\\",\\\\\\\"points inside this geometry will be deleted (optional)\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1,2),this.io.inputs.initInputsClonedState(Ki.FROM_NODE)}async cook(t){const e=t[0],n=t[1];switch(this.pv.class){case Fs.VERTEX:await this._eval_for_points(e,n);break;case Fs.OBJECT:await this._eval_for_objects(e)}}set_class(t){this.p.class.set(t)}async _eval_for_objects(t){const e=t.coreObjects();this.entitySelectionHelper.init(e),this._marked_for_deletion_per_object_index=new Map;for(let t of e)this._marked_for_deletion_per_object_index.set(t.index(),!1);this.pv.byExpression&&await this.byExpressionHelper.evalForEntities(e),this.pv.byObjectType&&this.byObjectTypeHelper.eval_for_objects(e),this.pv.byAttrib&&\\\\\\\"\\\\\\\"!=this.pv.attribName&&this.byAttributeHelper.evalForEntities(e);const n=this.entitySelectionHelper.entities_to_keep().map((t=>t.object()));if(this.pv.keepPoints){const t=this.entitySelectionHelper.entities_to_delete();for(let e of t){const t=this._point_object(e);t&&n.push(t)}}this.setObjects(n)}async _eval_for_points(t,e){const n=t.coreObjects();let i,s=[];for(let t=0;t0){const e=fr.geometryFromPoints(a,Os(t.constructor));e&&(t.geometry=e,s.push(t))}}}this.setObjects(s)}_point_object(t){const e=t.points(),n=fr.geometryFromPoints(e,Ns.POINTS);if(n)return this.createObject(n,Ns.POINTS)}}const wQ=new class extends ua{constructor(){super(...arguments),this.start=ha.INTEGER(0,{range:[0,100],rangeLocked:[!0,!1]}),this.useCount=ha.BOOLEAN(0),this.count=ha.INTEGER(0,{range:[0,100],rangeLocked:[!0,!1],visibleIf:{useCount:1}})}};class TQ extends lV{constructor(){super(...arguments),this.paramsConfig=wQ}static type(){return\\\\\\\"drawRange\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(Ki.FROM_NODE)}cook(t){const e=t[0],n=e.objects();for(let t of n){const e=t.geometry;if(e){const t=e.drawRange;t.start=this.pv.start,this.pv.useCount?t.count=this.pv.count:t.count=1/0}}this.setCoreGroup(e)}}class AQ{constructor(){this.pluginCallbacks=[],this.register((function(t){return new QQ(t)})),this.register((function(t){return new KQ(t)})),this.register((function(t){return new tK(t)})),this.register((function(t){return new eK(t)})),this.register((function(t){return new nK(t)}))}register(t){return-1===this.pluginCallbacks.indexOf(t)&&this.pluginCallbacks.push(t),this}unregister(t){return-1!==this.pluginCallbacks.indexOf(t)&&this.pluginCallbacks.splice(this.pluginCallbacks.indexOf(t),1),this}parse(t,e,n){const i=new ZQ,s=[];for(let t=0,e=this.pluginCallbacks.length;t0&&(this.options.trs=!0),this.processInput(t);const i=this;Promise.all(this.pending).then((function(){const t=i.buffers,n=i.json,s=i.options,r=i.extensionsUsed,o=new Blob(t,{type:\\\\\\\"application/octet-stream\\\\\\\"}),a=Object.keys(r);if(a.length>0&&(n.extensionsUsed=a),n.buffers&&n.buffers.length>0&&(n.buffers[0].byteLength=o.size),!0===s.binary){const t=new window.FileReader;t.readAsArrayBuffer(o),t.onloadend=function(){const i=$Q(t.result),s=new DataView(new ArrayBuffer(8));s.setUint32(0,i.byteLength,!0),s.setUint32(4,5130562,!0);const r=$Q(function(t){if(void 0!==window.TextEncoder)return(new TextEncoder).encode(t).buffer;const e=new Uint8Array(new ArrayBuffer(t.length));for(let n=0,i=t.length;n255?32:i}return e.buffer}(JSON.stringify(n)),32),o=new DataView(new ArrayBuffer(8));o.setUint32(0,r.byteLength,!0),o.setUint32(4,1313821514,!0);const a=new ArrayBuffer(12),l=new DataView(a);l.setUint32(0,1179937895,!0),l.setUint32(4,2,!0);const c=12+o.byteLength+r.byteLength+s.byteLength+i.byteLength;l.setUint32(8,c,!0);const h=new Blob([a,o,r,s,i],{type:\\\\\\\"application/octet-stream\\\\\\\"}),u=new window.FileReader;u.readAsArrayBuffer(h),u.onloadend=function(){e(u.result)}}}else if(n.buffers&&n.buffers.length>0){const t=new window.FileReader;t.readAsDataURL(o),t.onloadend=function(){const i=t.result;n.buffers[0].uri=i,e(n)}}else e(n)}))}serializeUserData(t,e){if(0===Object.keys(t.userData).length)return;const n=this.options,i=this.extensionsUsed;try{const s=JSON.parse(JSON.stringify(t.userData));if(n.includeCustomExtensions&&s.gltfExtensions){void 0===e.extensions&&(e.extensions={});for(const t in s.gltfExtensions)e.extensions[t]=s.gltfExtensions[t],i[t]=!0;delete s.gltfExtensions}Object.keys(s).length>0&&(e.extras=s)}catch(e){console.warn(\\\\\\\"THREE.GLTFExporter: userData of '\\\\\\\"+t.name+\\\\\\\"' won't be serialized because of JSON.stringify error - \\\\\\\"+e.message)}}getUID(t){return this.uids.has(t)||this.uids.set(t,this.uid++),this.uids.get(t)}isNormalizedNormalAttribute(t){if(this.cache.attributesNormalized.has(t))return!1;const e=new Ab;for(let n=0,i=t.count;n5e-4)return!1;return!0}createNormalizedNormalAttribute(t){const e=this.cache;if(e.attributesNormalized.has(t))return e.attributesNormalized.get(t);const n=t.clone(),i=new Ab;for(let t=0,e=n.count;t4?i=t.array[s*t.itemSize+n]:0===n?i=t.getX(s):1===n?i=t.getY(s):2===n?i=t.getZ(s):3===n&&(i=t.getW(s)),e===PQ?l.setFloat32(c,i,!0):e===RQ?l.setUint32(c,i,!0):e===OQ?l.setUint16(c,i,!0):e===LQ&&l.setUint8(c,i),c+=o}const h={buffer:this.processBuffer(l.buffer),byteOffset:this.byteOffset,byteLength:a};void 0!==s&&(h.target=s),s===IQ&&(h.byteStride=t.itemSize*o),this.byteOffset+=a,r.bufferViews.push(h);return{id:r.bufferViews.length-1,byteLength:0}}processBufferViewImage(t){const e=this,n=e.json;return n.bufferViews||(n.bufferViews=[]),new Promise((function(i){const s=new window.FileReader;s.readAsArrayBuffer(t),s.onloadend=function(){const t=$Q(s.result),r={buffer:e.processBuffer(t),byteOffset:e.byteOffset,byteLength:t.byteLength};e.byteOffset+=t.byteLength,i(n.bufferViews.push(r)-1)}}))}processAccessor(t,e,n,i){const s=this.options,r=this.json;let o;if(t.array.constructor===Float32Array)o=PQ;else if(t.array.constructor===Uint32Array)o=RQ;else if(t.array.constructor===Uint16Array)o=OQ;else{if(t.array.constructor!==Uint8Array)throw new Error(\\\\\\\"THREE.GLTFExporter: Unsupported bufferAttribute component type.\\\\\\\");o=LQ}if(void 0===n&&(n=0),void 0===i&&(i=t.count),s.truncateDrawRange&&void 0!==e&&null===e.index){const s=n+i,r=e.drawRange.count===1/0?t.count:e.drawRange.start+e.drawRange.count;n=Math.max(n,e.drawRange.start),(i=Math.min(s,r)-n)<0&&(i=0)}if(0===i)return null;const a=function(t,e,n){const i={min:new Array(t.itemSize).fill(Number.POSITIVE_INFINITY),max:new Array(t.itemSize).fill(Number.NEGATIVE_INFINITY)};for(let s=e;s4?n=t.array[s*t.itemSize+e]:0===e?n=t.getX(s):1===e?n=t.getY(s):2===e?n=t.getZ(s):3===e&&(n=t.getW(s)),i.min[e]=Math.min(i.min[e],n),i.max[e]=Math.max(i.max[e],n)}return i}(t,n,i);let l;void 0!==e&&(l=t===e.index?FQ:IQ);const c=this.processBufferView(t,o,n,i,l),h={bufferView:c.id,byteOffset:c.byteOffset,componentType:o,count:i,max:a.max,min:a.min,type:{1:\\\\\\\"SCALAR\\\\\\\",2:\\\\\\\"VEC2\\\\\\\",3:\\\\\\\"VEC3\\\\\\\",4:\\\\\\\"VEC4\\\\\\\",16:\\\\\\\"MAT4\\\\\\\"}[t.itemSize]};return!0===t.normalized&&(h.normalized=!0),r.accessors||(r.accessors=[]),r.accessors.push(h)-1}processImage(t,e,n){const i=this,s=i.cache,r=i.json,o=i.options,a=i.pending;s.images.has(t)||s.images.set(t,{});const l=s.images.get(t),c=e===Rx?\\\\\\\"image/png\\\\\\\":\\\\\\\"image/jpeg\\\\\\\",h=c+\\\\\\\":flipY/\\\\\\\"+n.toString();if(void 0!==l[h])return l[h];r.images||(r.images=[]);const u={mimeType:c};if(o.embedImages){const s=JQ=JQ||document.createElement(\\\\\\\"canvas\\\\\\\");s.width=Math.min(t.width,o.maxTextureSize),s.height=Math.min(t.height,o.maxTextureSize);const r=s.getContext(\\\\\\\"2d\\\\\\\");if(!0===n&&(r.translate(0,s.height),r.scale(1,-1)),\\\\\\\"undefined\\\\\\\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\\\\\\\"undefined\\\\\\\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\\\\\\\"undefined\\\\\\\"!=typeof OffscreenCanvas&&t instanceof OffscreenCanvas||\\\\\\\"undefined\\\\\\\"!=typeof ImageBitmap&&t instanceof ImageBitmap)r.drawImage(t,0,0,s.width,s.height);else{e!==Rx&&e!==Px&&console.error(\\\\\\\"GLTFExporter: Only RGB and RGBA formats are supported.\\\\\\\"),(t.width>o.maxTextureSize||t.height>o.maxTextureSize)&&console.warn(\\\\\\\"GLTFExporter: Image size is bigger than maxTextureSize\\\\\\\",t);const n=new Uint8ClampedArray(t.height*t.width*4);if(e===Rx)for(let e=0;e1&&(e.multiplyScalar(1/n),console.warn(\\\\\\\"THREE.GLTFExporter: Some emissive components exceed 1; emissive has been limited\\\\\\\")),n>0&&(i.emissiveFactor=e.toArray()),t.emissiveMap){const e={index:this.processTexture(t.emissiveMap)};this.applyTextureTransform(e,t.emissiveMap),i.emissiveTexture=e}}if(t.normalMap){const e={index:this.processTexture(t.normalMap)};t.normalScale&&1!==t.normalScale.x&&(e.scale=t.normalScale.x),this.applyTextureTransform(e,t.normalMap),i.normalTexture=e}if(t.aoMap){const e={index:this.processTexture(t.aoMap),texCoord:1};1!==t.aoMapIntensity&&(e.strength=t.aoMapIntensity),this.applyTextureTransform(e,t.aoMap),i.occlusionTexture=e}t.transparent?i.alphaMode=\\\\\\\"BLEND\\\\\\\":t.alphaTest>0&&(i.alphaMode=\\\\\\\"MASK\\\\\\\",i.alphaCutoff=t.alphaTest),2===t.side&&(i.doubleSided=!0),\\\\\\\"\\\\\\\"!==t.name&&(i.name=t.name),this.serializeUserData(t,i),this._invokeAll((function(e){e.writeMaterial&&e.writeMaterial(t,i)}));const r=n.materials.push(i)-1;return e.materials.set(t,r),r}processMesh(t){const e=this.cache,n=this.json,i=[t.geometry.uuid];if(Array.isArray(t.material))for(let e=0,n=t.material.length;e0){const n=[],i=[],s={};if(void 0!==t.morphTargetDictionary)for(const e in t.morphTargetDictionary)s[t.morphTargetDictionary[e]]=e;for(let o=0;o0&&(a.extras={},a.extras.targetNames=i)}const _=Array.isArray(t.material);if(_&&0===r.groups.length)return null;const m=_?t.material:[t.material],f=_?r.groups:[{materialIndex:0,start:void 0,count:void 0}];for(let t=0,n=f.length;t0&&(n.targets=h),null!==r.index){let i=this.getUID(r.index);void 0===f[t].start&&void 0===f[t].count||(i+=\\\\\\\":\\\\\\\"+f[t].start+\\\\\\\":\\\\\\\"+f[t].count),e.attributes.has(i)?n.indices=e.attributes.get(i):(n.indices=this.processAccessor(r.index,r,f[t].start,f[t].count),e.attributes.set(i,n.indices)),null===n.indices&&delete n.indices}const i=this.processMaterial(m[f[t].materialIndex]);null!==i&&(n.material=i),c.push(n)}a.primitives=c,n.meshes||(n.meshes=[]),this._invokeAll((function(e){e.writeMesh&&e.writeMesh(t,a)}));const g=n.meshes.push(a)-1;return e.meshes.set(s,g),g}processCamera(t){const e=this.json;e.cameras||(e.cameras=[]);const n=t.isOrthographicCamera,i={type:n?\\\\\\\"orthographic\\\\\\\":\\\\\\\"perspective\\\\\\\"};return n?i.orthographic={xmag:2*t.right,ymag:2*t.top,zfar:t.far<=0?.001:t.far,znear:t.near<0?0:t.near}:i.perspective={aspectRatio:t.aspect,yfov:hb.degToRad(t.fov),zfar:t.far<=0?.001:t.far,znear:t.near<0?0:t.near},\\\\\\\"\\\\\\\"!==t.name&&(i.name=t.type),e.cameras.push(i)-1}processAnimation(t,e){const n=this.json,i=this.nodeMap;n.animations||(n.animations=[]);const s=(t=AQ.Utils.mergeMorphTargetTracks(t.clone(),e)).tracks,r=[],o=[];for(let t=0;t0){const e=[];for(let i=0,s=t.children.length;i0&&(s.children=e)}this._invokeAll((function(e){e.writeNode&&e.writeNode(t,s)}));const r=e.nodes.push(s)-1;return i.set(t,r),r}processScene(t){const e=this.json,n=this.options;e.scenes||(e.scenes=[],e.scene=0);const i={};\\\\\\\"\\\\\\\"!==t.name&&(i.name=t.name),e.scenes.push(i);const s=[];for(let e=0,i=t.children.length;e0&&(i.nodes=s),this.serializeUserData(t,i)}processObjects(t){const e=new FE;e.name=\\\\\\\"AuxScene\\\\\\\";for(let n=0;n0&&this.processObjects(n);for(let t=0;t0&&(r.range=t.distance)):t.isSpotLight&&(r.type=\\\\\\\"spot\\\\\\\",t.distance>0&&(r.range=t.distance),r.spot={},r.spot.innerConeAngle=(t.penumbra-1)*t.angle*-1,r.spot.outerConeAngle=t.angle),void 0!==t.decay&&2!==t.decay&&console.warn(\\\\\\\"THREE.GLTFExporter: Light decay may be lost. glTF is physically-based, and expects light.decay=2.\\\\\\\"),!t.target||t.target.parent===t&&0===t.target.position.x&&0===t.target.position.y&&-1===t.target.position.z||console.warn(\\\\\\\"THREE.GLTFExporter: Light direction may be lost. For best results, make light.target a child of the light with position 0,0,-1.\\\\\\\"),s[this.name]||(i.extensions=i.extensions||{},i.extensions[this.name]={lights:[]},s[this.name]=!0);const o=i.extensions[this.name].lights;o.push(r),e.extensions=e.extensions||{},e.extensions[this.name]={light:o.length-1}}}class KQ{constructor(t){this.writer=t,this.name=\\\\\\\"KHR_materials_unlit\\\\\\\"}writeMaterial(t,e){if(!t.isMeshBasicMaterial)return;const n=this.writer.extensionsUsed;e.extensions=e.extensions||{},e.extensions[this.name]={},n[this.name]=!0,e.pbrMetallicRoughness.metallicFactor=0,e.pbrMetallicRoughness.roughnessFactor=.9}}class tK{constructor(t){this.writer=t,this.name=\\\\\\\"KHR_materials_pbrSpecularGlossiness\\\\\\\"}writeMaterial(t,e){if(!t.isGLTFSpecularGlossinessMaterial)return;const n=this.writer,i=n.extensionsUsed,s={};e.pbrMetallicRoughness.baseColorFactor&&(s.diffuseFactor=e.pbrMetallicRoughness.baseColorFactor);const r=[1,1,1];if(t.specular.toArray(r,0),s.specularFactor=r,s.glossinessFactor=t.glossiness,e.pbrMetallicRoughness.baseColorTexture&&(s.diffuseTexture=e.pbrMetallicRoughness.baseColorTexture),t.specularMap){const e={index:n.processTexture(t.specularMap)};n.applyTextureTransform(e,t.specularMap),s.specularGlossinessTexture=e}e.extensions=e.extensions||{},e.extensions[this.name]=s,i[this.name]=!0}}class eK{constructor(t){this.writer=t,this.name=\\\\\\\"KHR_materials_transmission\\\\\\\"}writeMaterial(t,e){if(!t.isMeshPhysicalMaterial||0===t.transmission)return;const n=this.writer,i=n.extensionsUsed,s={};if(s.transmissionFactor=t.transmission,t.transmissionMap){const e={index:n.processTexture(t.transmissionMap)};n.applyTextureTransform(e,t.transmissionMap),s.transmissionTexture=e}e.extensions=e.extensions||{},e.extensions[this.name]=s,i[this.name]=!0}}class nK{constructor(t){this.writer=t,this.name=\\\\\\\"KHR_materials_volume\\\\\\\"}writeMaterial(t,e){if(!t.isMeshPhysicalMaterial||0===t.thickness)return;const n=this.writer,i=n.extensionsUsed,s={};if(s.thicknessFactor=t.thickness,t.thicknessMap){const e={index:n.processTexture(t.thicknessMap)};n.applyTextureTransform(e,t.thicknessMap),s.thicknessTexture=e}s.attenuationDistance=t.attenuationDistance,s.attenuationColor=t.attenuationTint.toArray(),e.extensions=e.extensions||{},e.extensions[this.name]=s,i[this.name]=!0}}function iK(t,e){const n=document.createElement(\\\\\\\"a\\\\\\\");n.style.display=\\\\\\\"none\\\\\\\",document.body.appendChild(n),n.href=URL.createObjectURL(t),n.download=e,n.click(),setTimeout((()=>{document.body.removeChild(n)}),10)}AQ.Utils={insertKeyframe:function(t,e){const n=.001,i=t.getValueSize(),s=new t.TimeBufferType(t.times.length+1),r=new t.ValueBufferType(t.values.length+i),o=t.createInterpolant(new t.ValueBufferType(i));let a;if(0===t.times.length){s[0]=e;for(let t=0;tt.times[t.times.length-1]){if(Math.abs(t.times[t.times.length-1]-e)e){s.set(t.times.slice(0,l+1),0),s[l+1]=e,s.set(t.times.slice(l+1),l+2),r.set(t.values.slice(0,(l+1)*i),0),r.set(o.evaluate(e),(l+1)*i),r.set(t.values.slice((l+1)*i),(l+2)*i),a=l+1;break}}return t.times=s,t.values=r,a},mergeMorphTargetTracks:function(t,e){const n=[],i={},s=t.tracks;for(let t=0;t{rK.PARAM_CALLBACK_export(t)}})}};class rK extends lV{constructor(){super(...arguments),this.paramsConfig=sK}static type(){return\\\\\\\"exporter\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Ki.NEVER)}async cook(t){this.setCoreGroup(t[0])}static PARAM_CALLBACK_export(t){t._paramCallbackExport()}async _paramCallbackExport(){const t=(await this.compute()).coreContent();if(!t)return void console.error(\\\\\\\"input invalid\\\\\\\");const e=new WeakMap,n=t.objects();for(let t of n)e.set(t,t.parent);const i=new vs;for(let t of n)i.add(t);(new AQ).parse(i,(t=>{if(t instanceof ArrayBuffer)i=\\\\\\\"scene.glb\\\\\\\",iK(new Blob([t],{type:\\\\\\\"application/octet-stream\\\\\\\"}),i);else{!function(t,e){iK(new Blob([t],{type:\\\\\\\"text/plain\\\\\\\"}),e)}(JSON.stringify(t,null,2),\\\\\\\"scene.gltf\\\\\\\")}var i;for(let t of n){const n=e.get(t);n&&n.add(t)}}),{embedImages:!0})}}const oK=new class extends ua{constructor(){super(...arguments),this.makeFacesUnique=ha.BOOLEAN(0),this.addFaceCenterAttribute=ha.BOOLEAN(0,{visibleIf:{makeFacesUnique:1}}),this.addFaceId=ha.BOOLEAN(0,{visibleIf:{makeFacesUnique:1}}),this.transform=ha.BOOLEAN(0,{visibleIf:{makeFacesUnique:1}}),this.scale=ha.FLOAT(1,{visibleIf:{makeFacesUnique:1,transform:1}})}};class aK extends lV{constructor(){super(...arguments),this.paramsConfig=oK}static type(){return\\\\\\\"face\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Ki.FROM_NODE)}cook(t){const e=t[0];this.pv.makeFacesUnique&&(this._makeFacesUnique(e),this.pv.addFaceCenterAttribute&&this._addFaceCenterAttribute(e),this.pv.addFaceId&&this._addFaceId(e),this.pv.transform&&this._transform_faces(e)),this.setCoreGroup(e)}_makeFacesUnique(t){var e;for(let n of t.objects())if(n.isMesh){const t=n.geometry,i=f.chunk((null===(e=t.index)||void 0===e?void 0:e.array)||[],3),s=3*i.length;for(let e of Object.keys(t.attributes)){const n=t.attributes[e],r=n.itemSize,o=new Float32Array(s*r);let a=0;i.forEach((t=>{t.forEach((t=>{for(let e=0;e{const a=t.object(),l=t.coreGeometry();if(a.isMesh&&l){i=l.faces(),l.hasAttrib(e)||l.addNumericAttrib(e,3,-1);for(let t=0;t{const n=t.object(),i=t.coreGeometry();if(n.isMesh&&i){const t=i.faces();i.hasAttrib(e)||i.addNumericAttrib(e,1,-1);for(let n=0;n{const c=t.object(),h=t.coreGeometry();if(c.isMesh&&h){r=h.faces(),h.hasAttrib(e)||h.addNumericAttrib(e,3,-1);for(let t=0;t{t(e)})).catch((t=>{e(t)}))}_load(){return new Promise((async(t,e)=>{const n=await this._urlToLoad(),i=this.extension();if(i==lK.JSON&&this._options.format==lK.AUTO)uK.increment_in_progress_loads_count(),await uK.wait_for_max_concurrent_loads_queue_freed(),fetch(n).then((async e=>{const n=await e.json();new NJ(this.loadingManager).parse(n,(e=>{uK.decrement_in_progress_loads_count(),t(this.on_load_success(e.children[0]))}))})).catch((t=>{uK.decrement_in_progress_loads_count(),e(t)}));else{const s=await this._loaderForFormat();if(s)uK.increment_in_progress_loads_count(),await uK.wait_for_max_concurrent_loads_queue_freed(),s.load(n,(e=>{this.on_load_success(e).then((e=>{uK.decrement_in_progress_loads_count(),t(e)}))}),void 0,(t=>{li.warn(\\\\\\\"error loading\\\\\\\",n,t),uK.decrement_in_progress_loads_count(),e(t)}));else{e(`format not supported (${i})`)}}}))}async on_load_success(t){const e=this.extension();if(e==lK.JSON)return[t];const n=t;if(n.isObject3D)switch(e){case hK.PDB:return this.on_load_succes_pdb(t);case hK.OBJ:default:return[n]}const i=t;if(i.isBufferGeometry)switch(e){case hK.DRC:return this.on_load_succes_drc(i);default:return[new B.a(i)]}const s=t;if(null!=s.scene)switch(e){case hK.GLTF:case hK.GLB:return this.on_load_succes_gltf(s);default:return[n]}const r=t;if(r.geometryAtoms||r.geometryBonds)switch(e){case hK.PDB:return this.on_load_succes_pdb(r);default:return[]}return[]}on_load_succes_drc(t){return[new B.a(t,uK._default_mat_mesh)]}on_load_succes_gltf(t){const e=t.scene;return e.animations=t.animations,[e]}on_load_succes_pdb(t){return[new ys.a(t.geometryAtoms,uK._default_mat_point),new Ms.a(t.geometryBonds,uK._default_mat_line)]}static moduleNamesFromFormat(t,e){switch(t){case lK.AUTO:return this.moduleNamesFromExt(e);case lK.DRC:return[Hn.DRACOLoader];case lK.FBX:return[Hn.FBXLoader];case lK.JSON:return[];case lK.GLTF:return[Hn.GLTFLoader];case lK.GLTF_WITH_DRACO:return[Hn.GLTFLoader,Hn.DRACOLoader];case lK.OBJ:return[Hn.OBJLoader];case lK.PDB:return[Hn.PDBLoader];case lK.PLY:return[Hn.PLYLoader];case lK.STL:return[Hn.STLLoader]}os.unreachable(t)}static moduleNamesFromExt(t){switch(t){case hK.DRC:return[Hn.DRACOLoader];case hK.FBX:return[Hn.FBXLoader];case hK.GLTF:return[Hn.GLTFLoader];case hK.GLB:return[Hn.GLTFLoader,Hn.DRACOLoader];case hK.OBJ:return[Hn.OBJLoader];case hK.PDB:return[Hn.PDBLoader];case hK.PLY:return[Hn.PLYLoader];case hK.STL:return[Hn.STLLoader]}}async _loaderForFormat(){const t=this._options.format;switch(t){case lK.AUTO:return this._loaderForExt();case lK.DRC:return this.loader_for_drc(this._node);case lK.FBX:return this.loader_for_fbx();case lK.JSON:return;case lK.GLTF:return this.loader_for_gltf();case lK.GLTF_WITH_DRACO:return this.loader_for_glb(this._node);case lK.OBJ:return this.loader_for_obj();case lK.PDB:return this.loader_for_pdb();case lK.PLY:return this.loader_for_ply();case lK.STL:return this.loader_for_stl()}os.unreachable(t)}async _loaderForExt(){switch(this.extension().toLowerCase()){case hK.DRC:return this.loader_for_drc(this._node);case hK.FBX:return this.loader_for_fbx();case hK.GLTF:return this.loader_for_gltf();case hK.GLB:return this.loader_for_glb(this._node);case hK.OBJ:return this.loader_for_obj();case hK.PDB:return this.loader_for_pdb();case hK.PLY:return this.loader_for_ply();case hK.STL:return this.loader_for_stl()}}loader_for_fbx(){const t=li.modulesRegister.module(Hn.FBXLoader);if(t)return new t(this.loadingManager)}loader_for_gltf(){const t=li.modulesRegister.module(Hn.GLTFLoader);if(t)return new t(this.loadingManager)}static async loader_for_drc(t){const e=li.modulesRegister.module(Hn.DRACOLoader);if(e){const n=new e(this.loadingManager),i=li.libs.root(),s=li.libs.DRACOPath();if(i||s){const e=`${i||\\\\\\\"\\\\\\\"}${s||\\\\\\\"\\\\\\\"}/`;if(t){const n=[\\\\\\\"draco_decoder.js\\\\\\\",\\\\\\\"draco_decoder.wasm\\\\\\\",\\\\\\\"draco_wasm_wrapper.js\\\\\\\"];await this._loadMultipleBlobGlobal({files:n.map((t=>({storedUrl:`${s}/${t}`,fullUrl:`${e}${t}`}))),node:t,error:\\\\\\\"failed to load draco libraries. Make sure to install them to load .glb files\\\\\\\"})}n.setDecoderPath(e)}else n.setDecoderPath(void 0);return n.setDecoderConfig({type:\\\\\\\"js\\\\\\\"}),n}}loader_for_drc(t){return uK.loader_for_drc(t)}static async loader_for_glb(t){const e=li.modulesRegister.module(Hn.GLTFLoader),n=li.modulesRegister.module(Hn.DRACOLoader);if(e&&n){this.gltf_loader=this.gltf_loader||new e(this.loadingManager),this.draco_loader=this.draco_loader||new n(this.loadingManager);const i=li.libs.root(),s=li.libs.DRACOGLTFPath();if(i||s){const e=`${i||\\\\\\\"\\\\\\\"}${s||\\\\\\\"\\\\\\\"}/`;if(t){const n=[\\\\\\\"draco_decoder.js\\\\\\\",\\\\\\\"draco_decoder.wasm\\\\\\\",\\\\\\\"draco_wasm_wrapper.js\\\\\\\"];await this._loadMultipleBlobGlobal({files:n.map((t=>({storedUrl:`${s}/${t}`,fullUrl:`${e}${t}`}))),node:t,error:\\\\\\\"failed to load draco libraries. Make sure to install them to load .glb files\\\\\\\"})}this.draco_loader.setDecoderPath(e)}else this.draco_loader.setDecoderPath(void 0);return this.gltf_loader.setDRACOLoader(this.draco_loader),this.gltf_loader}}loader_for_glb(t){return uK.loader_for_glb(t)}loader_for_obj(){const t=li.modulesRegister.module(Hn.OBJLoader);if(t)return new t(this.loadingManager)}loader_for_pdb(){const t=li.modulesRegister.module(Hn.PDBLoader);if(t)return new t(this.loadingManager)}loader_for_ply(){const t=li.modulesRegister.module(Hn.PLYLoader);if(t)return new t(this.loadingManager)}loader_for_stl(){const t=li.modulesRegister.module(Hn.STLLoader);if(t)return new t(this.loadingManager)}static setMaxConcurrentLoadsCount(t){this._maxConcurrentLoadsCountMethod=t}static _init_max_concurrent_loads_count(){return this._maxConcurrentLoadsCountMethod?this._maxConcurrentLoadsCountMethod():ng.isChrome()?4:1}static _init_concurrent_loads_delay(){return ng.isChrome()?1:10}static increment_in_progress_loads_count(){this.in_progress_loads_count++}static decrement_in_progress_loads_count(){this.in_progress_loads_count--;const t=this._queue.pop();if(t){const e=this.CONCURRENT_LOADS_DELAY;setTimeout((()=>{t()}),e)}}static async wait_for_max_concurrent_loads_queue_freed(){return this.in_progress_loads_count<=this.MAX_CONCURRENT_LOADS_COUNT?void 0:new Promise((t=>{this._queue.push(t)}))}}uK._default_mat_mesh=new Ts.a,uK._default_mat_point=new bs.a,uK._default_mat_line=new As.a,uK.MAX_CONCURRENT_LOADS_COUNT=uK._init_max_concurrent_loads_count(),uK.CONCURRENT_LOADS_DELAY=uK._init_concurrent_loads_delay(),uK.in_progress_loads_count=0,uK._queue=[];class dK extends sV{static type(){return\\\\\\\"file\\\\\\\"}static loader(t,e,n){return new uK({url:t.url,format:t.format},e,n)}cook(t,e){const n=dK.loader(e,this.scene(),this._node);return new Promise((t=>{n.load((e=>{const n=this._onLoad(e);t(this.createCoreGroupFromObjects(n))}),(t=>{this._onError(t,e)}))}))}clearLoadedBlob(t){dK.loader(t,this.scene(),this._node).deregisterUrl()}_onLoad(t){t=t.flat();for(let e of t)e.traverse((t=>{this._ensureGeometryHasIndex(t),t.matrixAutoUpdate=!1}));return t}_onError(t,e){var n;null===(n=this.states)||void 0===n||n.error.set(`could not load geometry from ${e.url} (${t})`)}_ensureGeometryHasIndex(t){const e=t.geometry;e&&this.createIndexIfNone(e)}}dK.DEFAULT_PARAMS={url:`${qg}/models/wolf.obj`,format:lK.AUTO};const pK=dK.DEFAULT_PARAMS;const _K=new class extends ua{constructor(){super(...arguments),this.url=ha.STRING(pK.url,{fileBrowse:{type:[Rr.GEOMETRY]}}),this.format=ha.STRING(pK.format,{menuString:{entries:cK.map((t=>({name:t,value:t})))}}),this.reload=ha.BUTTON(null,{callback:t=>{mK.PARAM_CALLBACK_reload(t)}})}};class mK extends lV{constructor(){super(...arguments),this.paramsConfig=_K}static type(){return\\\\\\\"file\\\\\\\"}async requiredModules(){for(let t of[this.p.url,this.p.format])t.isDirty()&&await t.compute();const t=$g.extension(this.pv.url||\\\\\\\"\\\\\\\"),e=this.pv.format;return uK.moduleNamesFromFormat(e,t)}initializeNode(){this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.url],(()=>{const t=this.p.url.rawInput();if(t){const e=t.split(\\\\\\\"/\\\\\\\");return e[e.length-1]}return\\\\\\\"\\\\\\\"}))}))}))}operation(){return this._operation=this._operation||new dK(this.scene(),this.states,this)}async cook(t){const e=await this.operation().cook(t,this.pv);this.setCoreGroup(e)}static PARAM_CALLBACK_reload(t){t._paramCallbackReload()}_paramCallbackReload(){this.operation().clearLoadedBlob(this.pv),this.p.url.setDirty()}}const fK=new class extends ua{constructor(){super(...arguments),this.url=ha.STRING(`${qg}/models/\\\\`@name\\\\`.obj`,{fileBrowse:{type:[Rr.GEOMETRY]},expression:{forEntities:!0}}),this.format=ha.STRING(lK.AUTO,{menuString:{entries:cK.map((t=>({name:t,value:t})))}}),this.reload=ha.BUTTON(null,{callback:t=>{gK.PARAM_CALLBACK_reload(t)}})}};class gK extends lV{constructor(){super(...arguments),this.paramsConfig=fK}static type(){return\\\\\\\"fileMulti\\\\\\\"}async requiredModules(){const t=$g.extension(this.p.url.rawInput()||\\\\\\\"\\\\\\\"),e=this.pv.format;return uK.moduleNamesFromFormat(e,t)}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Ki.NEVER),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.url],(()=>this.p.url.rawInput()))}))}))}async cook(t){const e=t[0],n=new SZ(e).matrices(),i=e.points(),s=[],r=new Map,o=new Map,a=new Map,l=this.p.url;if(l.hasExpression()&&l.expressionController){const t=new Set;await l.expressionController.computeExpressionForPoints(i,((e,n)=>{const i=e.index();r.has(i)?this.states.error.set(\\\\\\\"input points have duplicate indices. Make sure to merge inputs together.\\\\\\\"):(r.set(i,n),t.add(n),gK._incrementUrlUsageCount(n,a))})),t.forEach((t=>{s.push(t)}))}else{const t=this.pv.url;s.push(t),gK._incrementUrlUsageCount(t,a)}const c=[],h=s.map((t=>this._loadFromUrlPromises(t,o)));await Promise.all(h);for(let t of i){const e=t.index(),i=r.get(e)||this.pv.url,s=n[e],l=a.get(i)||1;let h=o.get(i);h&&(l>1&&(h=h.clone()),h.applyMatrix4(s),c.push(h))}this.setObjects(c)}static _incrementUrlUsageCount(t,e){const n=e.get(t);null!=n?e.set(t,n+1):e.set(t,1)}async _loadFromUrlPromises(t,e){const n=await this._loadObject(t),i=new Fn.a;i.matrixAutoUpdate=!1,i.name=t;for(let t of n)i.add(t);e.set(t,i)}_loadObject(t){const e=new uK({url:t,format:this.pv.format},this.scene(),this);return new Promise((n=>{e.load((t=>{const e=this._onLoad(t);n(e)}),(e=>{this._onError(e,t)}))}))}_onLoad(t){t=t.flat();for(let e of t)e.traverse((t=>{this._ensureGeometryHasIndex(t),t.matrixAutoUpdate=!1}));return t}_onError(t,e){var n;null===(n=this.states)||void 0===n||n.error.set(`could not load geometry from ${e} (${t})`)}_ensureGeometryHasIndex(t){const e=t.geometry;e&&pr.createIndexIfNone(e)}static PARAM_CALLBACK_reload(t){t._paramCallbackReload()}_paramCallbackReload(){this.p.url.setDirty()}}const vK=new class extends ua{constructor(){super(...arguments),this.dist=ha.FLOAT(.1,{range:[0,1],rangeLocked:[!0,!1]})}};class yK extends lV{constructor(){super(...arguments),this.paramsConfig=vK}static type(){return\\\\\\\"fuse\\\\\\\"}static displayedInputNames(){return[\\\\\\\"points to fuse together\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Ki.FROM_NODE)}cook(t){const e=t[0],n=[];let i;for(let t of e.coreObjects())i=this._fuse_core_object(t),i&&n.push(i);this.setObjects(n)}_fuse_core_object(t){const e=t.object();if(!e)return;const n=t.points(),i=this.pv.dist,s={};for(let t of n){const e=t.position(),n=new p.a(Math.round(e.x/i),Math.round(e.y/i),Math.round(e.z/i)).toArray().join(\\\\\\\"-\\\\\\\");s[n]=s[n]||[],s[n].push(t)}const r=[];if(Object.keys(s).forEach((t=>{r.push(s[t][0])})),e.geometry.dispose(),r.length>0){const t=fr.geometryFromPoints(r,Os(e.constructor));return t&&(e.geometry=t),e}}}class xK{constructor(t,e,n){this._param_size=t,this._param_hexagon_radius=e,this._param_points_only=n}process(){const t=this._param_hexagon_radius,e=.5*t,n=t,i=Math.cos(Math.PI/6)*this._param_hexagon_radius,s=Math.floor(this._param_size.x/n),r=Math.floor(this._param_size.y/i);let o=[],a=[];for(let t=0;t=1&&(0==r||r==s-1?0==r?a.push([r+1+(t-1)*s,r+(t-1)*s,r+t*s]):a.push([r+t*s,r+(t-1)*s,r-1+t*s]):(a.push([r+t*s,r+(t-1)*s,r-1+t*s]),a.push([r+t*s,r+1+(t-1)*s,r+(t-1)*s])));const l=new S.a;return l.setAttribute(\\\\\\\"position\\\\\\\",new C.a(new Float32Array(o.flat()),3)),this._param_points_only||(l.setIndex(a.flat()),l.computeVertexNormals()),l}}const bK=new p.a(0,1,0);const wK=new class extends ua{constructor(){super(...arguments),this.size=ha.VECTOR2([1,1]),this.hexagonRadius=ha.FLOAT(.1,{range:[.001,1],rangeLocked:[!1,!1]}),this.direction=ha.VECTOR3([0,1,0]),this.pointsOnly=ha.BOOLEAN(0)}};class TK extends lV{constructor(){super(...arguments),this.paramsConfig=wK,this._core_transform=new vU}static type(){return\\\\\\\"hexagons\\\\\\\"}initializeNode(){}cook(){if(this.pv.hexagonRadius>0){const t=new xK(this.pv.size,this.pv.hexagonRadius,this.pv.pointsOnly).process();this._core_transform.rotate_geometry(t,bK,this.pv.direction),this.pv.pointsOnly?this.setGeometry(t,Ns.POINTS):this.setGeometry(t)}else this.setObjects([])}}var AK;!function(t){t.ADD_PARENT=\\\\\\\"add_parent\\\\\\\",t.REMOVE_PARENT=\\\\\\\"remove_parent\\\\\\\",t.ADD_CHILD=\\\\\\\"add_child\\\\\\\"}(AK||(AK={}));const MK=[AK.ADD_PARENT,AK.REMOVE_PARENT,AK.ADD_CHILD];class EK extends sV{static type(){return\\\\\\\"hierarchy\\\\\\\"}cook(t,e){const n=t[0],i=MK[e.mode];switch(i){case AK.ADD_PARENT:{const t=this._add_parent_to_core_group(n,e);return this.createCoreGroupFromObjects(t)}case AK.REMOVE_PARENT:{const t=this._remove_parent_from_core_group(n,e);return this.createCoreGroupFromObjects(t)}case AK.ADD_CHILD:{const i=this._add_child_to_core_group(n,t[1],e);return this.createCoreGroupFromObjects(i)}}os.unreachable(i)}_add_parent_to_core_group(t,e){if(0==e.levels)return t.objects();return[this._add_parent_to_object(t.objects(),e)]}_add_parent_to_object(t,e){let n=new Fn.a;if(n.matrixAutoUpdate=!1,n.add(...t),e.levels>0)for(let t=0;t({name:t,value:e})))}}),this.levels=ha.INTEGER(CK.levels,{range:[0,5],visibleIf:[{mode:MK.indexOf(AK.ADD_PARENT)},{mode:MK.indexOf(AK.REMOVE_PARENT)}]}),this.objectMask=ha.STRING(\\\\\\\"\\\\\\\",{visibleIf:{mode:MK.indexOf(AK.ADD_CHILD)}}),this.debugObjectMask=ha.BOOLEAN(0,{visibleIf:{mode:MK.indexOf(AK.ADD_CHILD)}})}};class LK extends lV{constructor(){super(...arguments),this.paramsConfig=NK}static type(){return\\\\\\\"hierarchy\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to add or remove parents to/from\\\\\\\",\\\\\\\"objects to use as parent or children (optional)\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1,2),this.io.inputs.initInputsClonedState(EK.INPUT_CLONED_STATE),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.mode,this.p.levels,this.p.objectMask],(()=>{const t=MK[this.pv.mode];return SK.includes(t)?`${t} ${this.pv.levels}`:`${t} (with mask: ${this.pv.objectMask})`}))}))}))}cook(t){this._operation=this._operation||new EK(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const OK=new class extends ua{constructor(){super(...arguments),this.texture=ha.OPERATOR_PATH(vi.UV,{nodeSelection:{context:ts.COP}}),this.mult=ha.FLOAT(1)}};class PK extends lV{constructor(){super(...arguments),this.paramsConfig=OK}static type(){return\\\\\\\"heightMap\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Ki.FROM_NODE)}async cook(t){const e=t[0],n=this.p.texture.found_node();if(n){if(n.context()==ts.COP){const t=n,i=(await t.compute()).texture();for(let t of e.coreObjects())this._set_position_from_data_texture(t,i)}else this.states.error.set(\\\\\\\"found node is not a texture\\\\\\\")}e.computeVertexNormals(),this.setCoreGroup(e)}_set_position_from_data_texture(t,e){var n;const i=this._data_from_texture(e);if(!i)return;const{data:s,resx:r,resy:o}=i,a=s.length/(r*o),l=null===(n=t.coreGeometry())||void 0===n?void 0:n.geometry();if(!l)return;const c=l.getAttribute(\\\\\\\"position\\\\\\\").array,h=l.getAttribute(\\\\\\\"uv\\\\\\\"),u=l.getAttribute(\\\\\\\"normal\\\\\\\");if(null==h)return void this.states.error.set(\\\\\\\"uvs are required\\\\\\\");if(null==u)return void this.states.error.set(\\\\\\\"normals are required\\\\\\\");const d=h.array,p=u.array,_=c.length/3;let m,f,g,v,y,x,b,w=0;for(let t=0;t<_;t++)m=2*t,f=d[m],g=d[m+1],v=Math.floor((r-1)*f),y=Math.floor((o-1)*(1-g)),x=y*r+v,b=s[a*x],w=3*t,c[w+0]+=p[w+0]*b*this.pv.mult,c[w+1]+=p[w+1]*b*this.pv.mult,c[w+2]+=p[w+2]*b*this.pv.mult}_data_from_texture(t){if(t.image)return t.image.data?this._data_from_data_texture(t):this._data_from_default_texture(t)}_data_from_default_texture(t){const e=t.image.width,n=t.image.height;return{data:Bf.data_from_image(t.image).data,resx:e,resy:n}}_data_from_data_texture(t){return{data:t.image.data,resx:t.image.width,resy:t.image.height}}}function RK(t){return Math.atan2(-t.y,Math.sqrt(t.x*t.x+t.z*t.z))}class IK extends S.a{constructor(t,e,n,i,s){super(),this.type=\\\\\\\"PolyhedronBufferGeometry\\\\\\\",this.parameters={vertices:t,indices:e,radius:n,detail:i},n=n||1,i=i||0;const r=[],o=[],a=new Map;function l(t,e,n,i){const s=i+1,r=[];for(let i=0;i<=s;i++){r[i]=[];const o=t.clone().lerp(n,i/s),a=e.clone().lerp(n,i/s),l=s-i;for(let t=0;t<=l;t++)r[i][t]=0===t&&i===s?o:o.clone().lerp(a,t/l)}for(let t=0;t{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.layer])}))}))}cook(t){const e=t[0];for(let t of e.objects())t.layers.set(this.pv.layer);this.setCoreGroup(e)}}const QK=new class extends ua{constructor(){super(...arguments),this.length=ha.FLOAT(1,{range:[0,10]}),this.pointsCount=ha.INTEGER(1,{range:[2,100],rangeLocked:[!0,!1]}),this.origin=ha.VECTOR3([0,0,0]),this.direction=ha.VECTOR3([0,1,0])}};class KK extends lV{constructor(){super(...arguments),this.paramsConfig=QK}static type(){return\\\\\\\"line\\\\\\\"}initializeNode(){}cook(){const t=Math.max(2,this.pv.pointsCount),e=new Array(3*t),n=new Array(t),i=this.pv.direction.clone().normalize().multiplyScalar(this.pv.length);for(let s=0;s0&&(n[2*(s-1)]=s-1,n[2*(s-1)+1]=s)}const s=new S.a;s.setAttribute(\\\\\\\"position\\\\\\\",new C.c(e,3)),s.setIndex(n),this.setGeometry(s,Ns.LINE_SEGMENTS)}}const t0=new class extends ua{constructor(){super(...arguments),this.distance0=ha.FLOAT(1),this.distance1=ha.FLOAT(2),this.autoUpdate=ha.BOOLEAN(1),this.update=ha.BUTTON(null,{callback:t=>{e0.PARAM_CALLBACK_update(t)}}),this.camera=ha.OPERATOR_PATH(\\\\\\\"/perspective_camera1\\\\\\\",{visibleIf:{autoUpdate:0},dependentOnFoundNode:!1})}};class e0 extends lV{constructor(){super(...arguments),this.paramsConfig=t0,this._lod=this._create_LOD()}static type(){return\\\\\\\"lod\\\\\\\"}static displayedInputNames(){return[\\\\\\\"high res\\\\\\\",\\\\\\\"mid res\\\\\\\",\\\\\\\"low res\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1,3),this.io.inputs.initInputsClonedState(Ki.FROM_NODE)}_create_LOD(){const t=new Cs;return t.matrixAutoUpdate=!1,t}cook(t){this._clear_lod(),this._add_level(t[0],0),this._add_level(t[1],this.pv.distance0),this._add_level(t[2],this.pv.distance1),this._lod.autoUpdate=this.pv.autoUpdate,this.setObject(this._lod)}_add_level(t,e){if(t){const n=t.objects();let i;for(let t=0;t{this._apply_material(t,n,e)}));else for(let i of t.objectsFromGroup(e.group))this._apply_material(i,n,e);return t}null===(i=this.states)||void 0===i||i.error.set(`material invalid. (error: '${r.states.error.message()}')`)}else null===(s=this.states)||void 0===s||s.error.set(\\\\\\\"no material node found\\\\\\\")}_swap_textures(t,e){if(e.swapCurrentTex){this._materials_by_uuid.clear();for(let n of t.objectsFromGroup(e.group))if(e.applyToChildren)n.traverse((t=>{const e=n.material;this._materials_by_uuid.set(e.uuid,e)}));else{const t=n.material;this._materials_by_uuid.set(t.uuid,t)}this._materials_by_uuid.forEach(((t,n)=>{this._swap_texture(t,e)}))}}_apply_material(t,e,n){if(n.group&&!br.isInGroup(n.group,t))return;const i=n.cloneMat?yr.clone(e):e;if(e instanceof F&&i instanceof F)for(let t in e.uniforms)i.uniforms[t]=e.uniforms[t];const s=t;this._old_mat_by_old_new_id.set(i.uuid,s.material),s.material=i,yr.apply_render_hook(t,i),yr.applyCustomMaterials(t,i)}_swap_texture(t,e){if(\\\\\\\"\\\\\\\"==e.texSrc0||\\\\\\\"\\\\\\\"==e.texDest0)return;let n=this._old_mat_by_old_new_id.get(t.uuid);n=n||t;const i=n[e.texSrc0];if(i){t[e.texDest0]=i;const n=t.uniforms;if(n){n[e.texDest0]&&(n[e.texDest0]={value:i})}}}}n0.DEFAULT_PARAMS={group:\\\\\\\"\\\\\\\",assignMat:!0,material:new yi(\\\\\\\"\\\\\\\"),applyToChildren:!0,cloneMat:!1,shareUniforms:!0,swapCurrentTex:!1,texSrc0:\\\\\\\"emissiveMap\\\\\\\",texDest0:\\\\\\\"map\\\\\\\"},n0.INPUT_CLONED_STATE=Ki.FROM_NODE;const i0=n0.DEFAULT_PARAMS;const s0=new class extends ua{constructor(){super(...arguments),this.group=ha.STRING(i0.group),this.assignMat=ha.BOOLEAN(i0.assignMat),this.material=ha.NODE_PATH(i0.material.path(),{nodeSelection:{context:ts.MAT},dependentOnFoundNode:!1,visibleIf:{assignMat:1}}),this.applyToChildren=ha.BOOLEAN(i0.applyToChildren,{visibleIf:{assignMat:1}}),this.cloneMat=ha.BOOLEAN(i0.cloneMat,{visibleIf:{assignMat:1}}),this.shareUniforms=ha.BOOLEAN(i0.shareUniforms,{visibleIf:{assignMat:1,cloneMat:1}}),this.swapCurrentTex=ha.BOOLEAN(i0.swapCurrentTex),this.texSrc0=ha.STRING(i0.texSrc0,{visibleIf:{swapCurrentTex:1}}),this.texDest0=ha.STRING(i0.texDest0,{visibleIf:{swapCurrentTex:1}})}};class r0 extends lV{constructor(){super(...arguments),this.paramsConfig=s0}static type(){return\\\\\\\"material\\\\\\\"}static displayedInputNames(){return[\\\\\\\"objects to assign material to\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(n0.INPUT_CLONED_STATE),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.material],(()=>this.p.material.rawInput()))}))}))}async cook(t){this._operation=this._operation||new n0(this._scene,this.states);const e=await this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class o0 extends sV{static type(){return\\\\\\\"merge\\\\\\\"}cook(t,e){let n=[];for(let i of t)if(i){const t=i.objects();if(e.compact)for(let e of t)e.traverse((t=>{n.push(t)}));else for(let t of i.objects())n.push(t)}e.compact&&(n=this._makeCompact(n));for(let t of n)t.traverse((t=>{t.matrixAutoUpdate=!1}));return this.createCoreGroupFromObjects(n)}_makeCompact(t){const e=new Map,n=new Map,i=[];for(let s of t)s.traverse((t=>{if(t instanceof Fn.a)return;const s=t;if(s.geometry){const t=Os(s.constructor);if(i.includes(t)||i.push(t),t){e.get(t)||e.set(t,s.material),h.pushOnArrayAtEntry(n,t,s)}}}));const s=[];return i.forEach((t=>{var i,r;const o=n.get(t);if(o){const n=[];for(let t of o){const e=t.geometry;e.applyMatrix4(t.matrix),n.push(e)}try{const r=fr.mergeGeometries(n);if(r){const n=e.get(t),i=this.createObject(r,t,n);s.push(i)}else null===(i=this.states)||void 0===i||i.error.set(\\\\\\\"merge failed, check that input geometries have the same attributes\\\\\\\")}catch(t){null===(r=this.states)||void 0===r||r.error.set(t.message)}}})),s}}o0.DEFAULT_PARAMS={compact:!1},o0.INPUT_CLONED_STATE=Ki.FROM_NODE;const a0=\\\\\\\"geometry to merge\\\\\\\",l0=o0.DEFAULT_PARAMS;const c0=new class extends ua{constructor(){super(...arguments),this.compact=ha.BOOLEAN(l0.compact),this.inputsCount=ha.INTEGER(4,{range:[1,32],rangeLocked:[!0,!1],callback:t=>{h0.PARAM_CALLBACK_setInputsCount(t)}})}};class h0 extends lV{constructor(){super(...arguments),this.paramsConfig=c0}static type(){return\\\\\\\"merge\\\\\\\"}static displayedInputNames(){return[a0,a0,a0,a0]}setCompactMode(t){this.p.compact.set(t)}initializeNode(){this.io.inputs.setCount(1,4),this.io.inputs.initInputsClonedState(o0.INPUT_CLONED_STATE),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.compact],(()=>this.pv.compact?\\\\\\\"compact\\\\\\\":\\\\\\\"separate objects\\\\\\\"))})),this.params.addOnSceneLoadHook(\\\\\\\"update inputs\\\\\\\",(()=>{this._callbackUpdateInputsCount()}))}))}cook(t){this._operation=this._operation||new o0(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}_callbackUpdateInputsCount(){this.io.inputs.setCount(1,this.pv.inputsCount),this.emit(Ei.INPUTS_UPDATED)}static PARAM_CALLBACK_setInputsCount(t){t._callbackUpdateInputsCount()}}const u0=new Float32Array(36),d0=new Float32Array(36),p0=new Float32Array(36);function _0(t,e,n){return t+(e-t)*n}class m0 extends S.a{constructor(t,e,n){super(),this.resolution=t,this.isMarchingCubes=!0,this.isolation=80,this.size=-1,this.size2=-1,this.size3=-1,this.halfsize=-1,this.delta=-1,this.yd=-1,this.zd=-1,this.count=-1,this.maxCount=-1,this.enableUvs=void 0!==e&&e,this.enableColors=void 0!==n&&n,this.size=this.resolution,this.size2=this.size*this.size,this.size3=this.size2*this.size,this.halfsize=this.size/2,this.delta=2/this.size,this.yd=this.size,this.zd=this.size2,this.field=new Float32Array(this.size3),this.normal_cache=new Float32Array(3*this.size3),this.palette=new Float32Array(3*this.size3),this.maxCount=this.size3,this.count=0,this.positionArray=new Float32Array(3*this.maxCount),this.setAttribute(\\\\\\\"position\\\\\\\",new C.a(this.positionArray,3)),this.normalArray=new Float32Array(3*this.maxCount),this.setAttribute(\\\\\\\"normal\\\\\\\",new C.a(this.normalArray,3)),this.enableUvs&&(this.uvArray=new Float32Array(2*this.maxCount),this.setAttribute(\\\\\\\"uv\\\\\\\",new C.a(this.uvArray,2))),this.enableColors&&(this.colorArray=new Float32Array(3*this.maxCount),this.setAttribute(\\\\\\\"color\\\\\\\",new C.a(this.colorArray,3)));const i=(t,e,n,i,c)=>{const h=i+1,u=i+this.yd,d=i+this.zd,p=h+this.yd,_=h+this.zd,m=i+this.yd+this.zd,f=h+this.yd+this.zd;let g=0;const v=this.field[i],y=this.field[h],x=this.field[u],b=this.field[p],w=this.field[d],T=this.field[_],A=this.field[m],M=this.field[f];v{const t=this.size-2;for(let e=1;e{const h=(n-o)/(a-o),u=this.normal_cache;u0[e+0]=i+h*this.delta,u0[e+1]=s,u0[e+2]=r,d0[e+0]=_0(u[t+0],u[t+3],h),d0[e+1]=_0(u[t+1],u[t+4],h),d0[e+2]=_0(u[t+2],u[t+5],h),p0[e+0]=_0(this.palette[3*l+0],this.palette[3*c+0],h),p0[e+1]=_0(this.palette[3*l+1],this.palette[3*c+1],h),p0[e+2]=_0(this.palette[3*l+2],this.palette[3*c+2],h)},r=(t,e,n,i,s,r,o,a,l,c)=>{const h=(n-o)/(a-o),u=this.normal_cache;u0[e+0]=i,u0[e+1]=s+h*this.delta,u0[e+2]=r;const d=t+3*this.yd;d0[e+0]=_0(u[t+0],u[d+0],h),d0[e+1]=_0(u[t+1],u[d+1],h),d0[e+2]=_0(u[t+2],u[d+2],h),p0[e+0]=_0(this.palette[3*l+0],this.palette[3*c+0],h),p0[e+1]=_0(this.palette[3*l+1],this.palette[3*c+1],h),p0[e+2]=_0(this.palette[3*l+2],this.palette[3*c+2],h)},o=(t,e,n,i,s,r,o,a,l,c)=>{const h=(n-o)/(a-o),u=this.normal_cache;u0[e+0]=i,u0[e+1]=s,u0[e+2]=r+h*this.delta;const d=t+3*this.zd;d0[e+0]=_0(u[t+0],u[d+0],h),d0[e+1]=_0(u[t+1],u[d+1],h),d0[e+2]=_0(u[t+2],u[d+2],h),p0[e+0]=_0(this.palette[3*l+0],this.palette[3*c+0],h),p0[e+1]=_0(this.palette[3*l+1],this.palette[3*c+1],h),p0[e+2]=_0(this.palette[3*l+2],this.palette[3*c+2],h)},a=t=>{const e=3*t;0===this.normal_cache[e]&&(this.normal_cache[e+0]=this.field[t-1]-this.field[t+1],this.normal_cache[e+1]=this.field[t-this.yd]-this.field[t+this.yd],this.normal_cache[e+2]=this.field[t-this.zd]-this.field[t+this.zd])},l=(t,e,n,i,s,r)=>{const o=3*this.count;if(this.positionArray&&this.normalArray){if(this.positionArray[o+0]=t[i],this.positionArray[o+1]=t[i+1],this.positionArray[o+2]=t[i+2],this.positionArray[o+3]=t[s],this.positionArray[o+4]=t[s+1],this.positionArray[o+5]=t[s+2],this.positionArray[o+6]=t[r],this.positionArray[o+7]=t[r+1],this.positionArray[o+8]=t[r+2],this.normalArray[o+0]=e[i+0],this.normalArray[o+1]=e[i+1],this.normalArray[o+2]=e[i+2],this.normalArray[o+3]=e[s+0],this.normalArray[o+4]=e[s+1],this.normalArray[o+5]=e[s+2],this.normalArray[o+6]=e[r+0],this.normalArray[o+7]=e[r+1],this.normalArray[o+8]=e[r+2],this.enableUvs&&this.uvArray){const e=2*this.count;this.uvArray[e+0]=t[i+0],this.uvArray[e+1]=t[i+2],this.uvArray[e+2]=t[s+0],this.uvArray[e+3]=t[s+2],this.uvArray[e+4]=t[r+0],this.uvArray[e+5]=t[r+2]}this.enableColors&&this.colorArray&&(this.colorArray[o+0]=n[i+0],this.colorArray[o+1]=n[i+1],this.colorArray[o+2]=n[i+2],this.colorArray[o+3]=n[s+0],this.colorArray[o+4]=n[s+1],this.colorArray[o+5]=n[s+2],this.colorArray[o+6]=n[r+0],this.colorArray[o+7]=n[r+1],this.colorArray[o+8]=n[r+2]),this.count+=3}}}createPolygons(){this._createPolygons()}addBall(t,e,n,i,s,r){const o=Math.sign(i);i=Math.abs(i);const a=!(null==r);let l=new D.a(t,e,n);if(a)try{r&&(l=r)}catch(i){l=new D.a(t,e,n)}const c=this.size*Math.sqrt(i/s),h=n*this.size,u=e*this.size,d=t*this.size;let p=Math.floor(h-c);p<1&&(p=1);let _=Math.floor(h+c);_>this.size-1&&(_=this.size-1);let m=Math.floor(u-c);m<1&&(m=1);let f=Math.floor(u+c);f>this.size-1&&(f=this.size-1);let g=Math.floor(d-c);g<1&&(g=1);let v,y,x,b,w,T,A,M,E,S,C,N=Math.floor(d+c);for(N>this.size-1&&(N=this.size-1),x=p;x<_;x++)for(w=this.size2*x,M=x/this.size-n,E=M*M,y=m;y0){this.field[b+v]+=C*o;const t=Math.sqrt((v-d)*(v-d)+(y-u)*(y-u)+(x-h)*(x-h))/c,e=1-t*t*t*(t*(6*t-15)+10);this.palette[3*(b+v)+0]+=l.r*e,this.palette[3*(b+v)+1]+=l.g*e,this.palette[3*(b+v)+2]+=l.b*e}}}const f0=new 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-1,-1,-1,-1,1,10,2,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,1,3,8,9,1,8,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,0,9,1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,0,3,8,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1]),v0=new p.a;class y0 extends sV{static type(){return\\\\\\\"metaball\\\\\\\"}cook(t,e){const n=t[0],i=new m0(e.resolution,e.enableUVs,e.enableColors);i.isolation=e.isolation;const s=n.points();for(let t of s){t.getPosition(v0);let n=e.metaStrength;if(e.useMetaStrengthAttrib){let e=t.attribValue(\\\\\\\"metaStrength\\\\\\\");m.isNumber(e)&&(n*=e)}let s=e.metaSubstract;if(e.useMetaSubstractAttrib){let e=t.attribValue(\\\\\\\"metaSubstract\\\\\\\");m.isNumber(e)&&(s*=e)}i.addBall(v0.x,v0.y,v0.z,n,s,void 0)}return i.createPolygons(),this.createCoreGroupFromGeometry(i)}}y0.DEFAULT_PARAMS={resolution:10,isolation:1,useMetaStrengthAttrib:!1,metaStrength:1,useMetaSubstractAttrib:!1,metaSubstract:1,enableUVs:!1,enableColors:!1},y0.INPUT_CLONED_STATE=Ki.NEVER;const x0=y0.DEFAULT_PARAMS;const b0=new class extends ua{constructor(){super(...arguments),this.resolution=ha.FLOAT(x0.resolution,{range:[0,100],rangeLocked:[!0,!1]}),this.isolation=ha.FLOAT(x0.isolation,{range:[0,10],rangeLocked:[!0,!1]}),this.useMetaStrengthAttrib=ha.BOOLEAN(x0.useMetaStrengthAttrib),this.metaStrength=ha.FLOAT(x0.metaStrength,{range:[0,10],rangeLocked:[!0,!1]}),this.useMetaSubstractAttrib=ha.BOOLEAN(x0.useMetaSubstractAttrib),this.metaSubstract=ha.FLOAT(x0.metaSubstract,{range:[0,10],rangeLocked:[!0,!1]}),this.enableUVs=ha.BOOLEAN(x0.enableUVs),this.enableColors=ha.BOOLEAN(x0.enableColors)}};class w0 extends lV{constructor(){super(...arguments),this.paramsConfig=b0}static type(){return\\\\\\\"metaball\\\\\\\"}static displayedInputNames(){return[\\\\\\\"points to create metaballs from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(y0.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new y0(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class T0{constructor(t=Math){this.grad3=[[1,1,0],[-1,1,0],[1,-1,0],[-1,-1,0],[1,0,1],[-1,0,1],[1,0,-1],[-1,0,-1],[0,1,1],[0,-1,1],[0,1,-1],[0,-1,-1]],this.grad4=[[0,1,1,1],[0,1,1,-1],[0,1,-1,1],[0,1,-1,-1],[0,-1,1,1],[0,-1,1,-1],[0,-1,-1,1],[0,-1,-1,-1],[1,0,1,1],[1,0,1,-1],[1,0,-1,1],[1,0,-1,-1],[-1,0,1,1],[-1,0,1,-1],[-1,0,-1,1],[-1,0,-1,-1],[1,1,0,1],[1,1,0,-1],[1,-1,0,1],[1,-1,0,-1],[-1,1,0,1],[-1,1,0,-1],[-1,-1,0,1],[-1,-1,0,-1],[1,1,1,0],[1,1,-1,0],[1,-1,1,0],[1,-1,-1,0],[-1,1,1,0],[-1,1,-1,0],[-1,-1,1,0],[-1,-1,-1,0]],this.p=[];for(let e=0;e<256;e++)this.p[e]=Math.floor(256*t.random());this.perm=[];for(let t=0;t<512;t++)this.perm[t]=this.p[255&t];this.simplex=[[0,1,2,3],[0,1,3,2],[0,0,0,0],[0,2,3,1],[0,0,0,0],[0,0,0,0],[0,0,0,0],[1,2,3,0],[0,2,1,3],[0,0,0,0],[0,3,1,2],[0,3,2,1],[0,0,0,0],[0,0,0,0],[0,0,0,0],[1,3,2,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[1,2,0,3],[0,0,0,0],[1,3,0,2],[0,0,0,0],[0,0,0,0],[0,0,0,0],[2,3,0,1],[2,3,1,0],[1,0,2,3],[1,0,3,2],[0,0,0,0],[0,0,0,0],[0,0,0,0],[2,0,3,1],[0,0,0,0],[2,1,3,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0],[2,0,1,3],[0,0,0,0],[0,0,0,0],[0,0,0,0],[3,0,1,2],[3,0,2,1],[0,0,0,0],[3,1,2,0],[2,1,0,3],[0,0,0,0],[0,0,0,0],[0,0,0,0],[3,1,0,2],[0,0,0,0],[3,2,0,1],[3,2,1,0]]}dot(t,e,n){return t[0]*e+t[1]*n}dot3(t,e,n,i){return t[0]*e+t[1]*n+t[2]*i}dot4(t,e,n,i,s){return t[0]*e+t[1]*n+t[2]*i+t[3]*s}noise(t,e){let n,i,s;const r=(t+e)*(.5*(Math.sqrt(3)-1)),o=Math.floor(t+r),a=Math.floor(e+r),l=(3-Math.sqrt(3))/6,c=(o+a)*l,h=t-(o-c),u=e-(a-c);let d,p;h>u?(d=1,p=0):(d=0,p=1);const _=h-d+l,m=u-p+l,f=h-1+2*l,g=u-1+2*l,v=255&o,y=255&a,x=this.perm[v+this.perm[y]]%12,b=this.perm[v+d+this.perm[y+p]]%12,w=this.perm[v+1+this.perm[y+1]]%12;let T=.5-h*h-u*u;T<0?n=0:(T*=T,n=T*T*this.dot(this.grad3[x],h,u));let A=.5-_*_-m*m;A<0?i=0:(A*=A,i=A*A*this.dot(this.grad3[b],_,m));let M=.5-f*f-g*g;return M<0?s=0:(M*=M,s=M*M*this.dot(this.grad3[w],f,g)),70*(n+i+s)}noise3d(t,e,n){let i,s,r,o;const a=(t+e+n)*(1/3),l=Math.floor(t+a),c=Math.floor(e+a),h=Math.floor(n+a),u=1/6,d=(l+c+h)*u,p=t-(l-d),_=e-(c-d),m=n-(h-d);let f,g,v,y,x,b;p>=_?_>=m?(f=1,g=0,v=0,y=1,x=1,b=0):p>=m?(f=1,g=0,v=0,y=1,x=0,b=1):(f=0,g=0,v=1,y=1,x=0,b=1):_b?32:0)+(x>w?16:0)+(b>w?8:0)+(x>T?4:0)+(b>T?2:0)+(w>T?1:0),M=r[A][0]>=3?1:0,E=r[A][1]>=3?1:0,S=r[A][2]>=3?1:0,C=r[A][3]>=3?1:0,N=r[A][0]>=2?1:0,L=r[A][1]>=2?1:0,O=r[A][2]>=2?1:0,P=r[A][3]>=2?1:0,R=r[A][0]>=1?1:0,I=r[A][1]>=1?1:0,F=r[A][2]>=1?1:0,D=r[A][3]>=1?1:0,B=x-M+l,z=b-E+l,k=w-S+l,U=T-C+l,G=x-N+2*l,V=b-L+2*l,H=w-O+2*l,j=T-P+2*l,W=x-R+3*l,q=b-I+3*l,X=w-F+3*l,Y=T-D+3*l,$=x-1+4*l,J=b-1+4*l,Z=w-1+4*l,Q=T-1+4*l,K=255&m,tt=255&f,et=255&g,nt=255&v,it=o[K+o[tt+o[et+o[nt]]]]%32,st=o[K+M+o[tt+E+o[et+S+o[nt+C]]]]%32,rt=o[K+N+o[tt+L+o[et+O+o[nt+P]]]]%32,ot=o[K+R+o[tt+I+o[et+F+o[nt+D]]]]%32,at=o[K+1+o[tt+1+o[et+1+o[nt+1]]]]%32;let lt=.6-x*x-b*b-w*w-T*T;lt<0?c=0:(lt*=lt,c=lt*lt*this.dot4(s[it],x,b,w,T));let ct=.6-B*B-z*z-k*k-U*U;ct<0?h=0:(ct*=ct,h=ct*ct*this.dot4(s[st],B,z,k,U));let ht=.6-G*G-V*V-H*H-j*j;ht<0?u=0:(ht*=ht,u=ht*ht*this.dot4(s[rt],G,V,H,j));let ut=.6-W*W-q*q-X*X-Y*Y;ut<0?d=0:(ut*=ut,d=ut*ut*this.dot4(s[ot],W,q,X,Y));let dt=.6-$*$-J*J-Z*Z-Q*Q;return dt<0?p=0:(dt*=dt,p=dt*dt*this.dot4(s[at],$,J,Z,Q)),27*(c+h+u+d+p)}}var A0;!function(t){t.ADD=\\\\\\\"add\\\\\\\",t.SET=\\\\\\\"set\\\\\\\",t.MULT=\\\\\\\"mult\\\\\\\",t.SUBSTRACT=\\\\\\\"substract\\\\\\\",t.DIVIDE=\\\\\\\"divide\\\\\\\"}(A0||(A0={}));const M0=[A0.ADD,A0.SET,A0.MULT,A0.SUBSTRACT,A0.DIVIDE];const E0=new class extends ua{constructor(){super(...arguments),this.amplitude=ha.FLOAT(1),this.tamplitudeAttrib=ha.BOOLEAN(0),this.amplitudeAttrib=ha.STRING(\\\\\\\"amp\\\\\\\",{visibleIf:{tamplitudeAttrib:!0}}),this.freq=ha.VECTOR3([1,1,1]),this.offset=ha.VECTOR3([0,0,0]),this.octaves=ha.INTEGER(3,{range:[1,8],rangeLocked:[!0,!1]}),this.ampAttenuation=ha.FLOAT(.5,{range:[0,1]}),this.freqIncrease=ha.FLOAT(2,{range:[0,10]}),this.seed=ha.INTEGER(0,{range:[0,100],separatorAfter:!0}),this.useNormals=ha.BOOLEAN(0),this.attribName=ha.STRING(\\\\\\\"position\\\\\\\"),this.useRestAttributes=ha.BOOLEAN(0),this.restP=ha.STRING(\\\\\\\"restP\\\\\\\",{visibleIf:{useRestAttributes:!0}}),this.restN=ha.STRING(\\\\\\\"restN\\\\\\\",{visibleIf:{useRestAttributes:!0}}),this.operation=ha.INTEGER(M0.indexOf(A0.ADD),{menu:{entries:M0.map((t=>({name:t,value:M0.indexOf(t)})))}}),this.computeNormals=ha.BOOLEAN(1)}},S0=new p.a,C0=new p.a;class N0 extends lV{constructor(){super(...arguments),this.paramsConfig=E0,this._simplexBySeed=new Map,this._restPos=new p.a,this._restValue2=new d.a,this._restValue4=new _.a,this._noiseValueV=new p.a,this._currentAttribValueF=0,this._currentAttribValueV2=new d.a,this._currentAttribValueV3=new p.a,this._currentAttribValueV4=new _.a}static type(){return\\\\\\\"noise\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to add noise to\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState([Ki.FROM_NODE])}setOperation(t){this.p.operation.set(M0.indexOf(t))}async cook(t){const e=t[0],n=e.points(),i=this.pv.attribName;if(!e.hasAttrib(i))return this.states.error.set(`attribute ${i} not found`),void this.cookController.endCook();if(e.attribType(i)!=zs.NUMERIC)return this.states.error.set(`attribute ${i} is not a numeric attribute`),void this.cookController.endCook();const s=e.attribSize(this.pv.attribName),r=n[0];if(!r)return void this.setCoreGroup(e);const o=r.attribValue(i);if(m.isString(o))return void this.states.error.set(\\\\\\\"cannot add noise to a string attribute\\\\\\\");const a={octaves:this.pv.octaves,ampAttenuation:this.pv.ampAttenuation,freqIncrease:this.pv.freqIncrease};switch(s){case 1:this._cookForFloat(n,a);break;case 2:this._cookForV2(n,a);break;case 3:this._cookForV3(n,a);break;case 4:this._cookForV4(n,a)}if(!this.io.inputs.cloneRequired(0))for(let t of e.geometries())t.getAttribute(i).needsUpdate=!0;this.pv.computeNormals&&e.computeVertexNormals(),this.setCoreGroup(e)}_cookForFloat(t,e){const n=this._getSimplex(),i=this.pv.useRestAttributes,s=this.pv.useNormals,r=this.pv.tamplitudeAttrib,o=this.pv.amplitude,a=M0[this.pv.operation],l=this.pv.attribName;for(let c of t){i?(c.attribValue(this.pv.restP,S0),s&&c.attribValue(this.pv.restN,C0),this._currentAttribValueF=S0.x):(c.getPosition(S0),s&&c.attribValue(Ws.NORMAL,C0),this._currentAttribValueF=c.attribValue(l));const t=r?this._amplitudeFromAttrib(c,o):o,h=this._noiseValue(s,n,t,e,S0,C0).x,u=N0._newAttribValueFromFloat(a,this._currentAttribValueF,h);c.setAttribValue(l,u)}}_cookForV2(t,e){const n=this._getSimplex(),i=this.pv.useRestAttributes,s=this.pv.useNormals,r=this.pv.tamplitudeAttrib,o=this.pv.amplitude,a=M0[this.pv.operation],l=this.pv.attribName;for(let c of t){i?(c.attribValue(this.pv.restP,S0),s&&c.attribValue(this.pv.restN,C0),this._currentAttribValueV2.set(S0.x,S0.y)):(c.getPosition(S0),s&&c.attribValue(Ws.NORMAL,C0),c.attribValue(l,this._currentAttribValueV2));const t=r?this._amplitudeFromAttrib(c,o):o,h=this._noiseValue(s,n,t,e,S0,C0);this._restValue2.set(h.x,h.y);const u=this._restValue2,d=N0._newAttribValueFromVector2(a,this._currentAttribValueV2,u);c.setAttribValue(l,d)}}_cookForV3(t,e){const n=this._getSimplex(),i=this.pv.useRestAttributes,s=this.pv.useNormals,r=this.pv.tamplitudeAttrib,o=this.pv.amplitude,a=M0[this.pv.operation],l=this.pv.attribName;for(let c of t){i?(c.attribValue(this.pv.restP,S0),s&&c.attribValue(this.pv.restN,C0),this._currentAttribValueV3.copy(S0)):(c.getPosition(S0),s&&c.attribValue(Ws.NORMAL,C0),c.attribValue(l,this._currentAttribValueV3));const t=r?this._amplitudeFromAttrib(c,o):o,h=this._noiseValue(s,n,t,e,S0,C0),u=N0._newAttribValueFromVector3(a,this._currentAttribValueV3,h);c.setAttribValue(l,u)}}_cookForV4(t,e){const n=this._getSimplex(),i=this.pv.useRestAttributes,s=this.pv.useNormals,r=this.pv.tamplitudeAttrib,o=this.pv.amplitude,a=M0[this.pv.operation],l=this.pv.attribName;for(let c of t){i?(c.attribValue(this.pv.restP,S0),s&&c.attribValue(this.pv.restN,C0),this._currentAttribValueV4.set(S0.x,S0.y,S0.z,0)):(c.getPosition(S0),s&&c.attribValue(Ws.NORMAL,C0),c.attribValue(l,this._currentAttribValueV4));const t=r?this._amplitudeFromAttrib(c,o):o,h=this._noiseValue(s,n,t,e,S0,C0);this._restValue4.set(h.x,h.y,h.z,0);const u=this._restValue4,d=N0._newAttribValueFromVector4(a,this._currentAttribValueV4,u);c.setAttribValue(l,d)}}_noiseValue(t,e,n,i,s,r){if(this._restPos.copy(s).add(this.pv.offset).multiply(this.pv.freq),t&&r){const t=n*this._fbm(e,i,this._restPos.x,this._restPos.y,this._restPos.z);return this._noiseValueV.copy(r),this._noiseValueV.multiplyScalar(t)}return this._noiseValueV.set(n*this._fbm(e,i,this._restPos.x+545,this._restPos.y+125454,this._restPos.z+2142),n*this._fbm(e,i,this._restPos.x-425,this._restPos.y-25746,this._restPos.z+95242),n*this._fbm(e,i,this._restPos.x+765132,this._restPos.y+21,this._restPos.z-9245)),this._noiseValueV}static _newAttribValueFromFloat(t,e,n){switch(t){case A0.ADD:return e+n;case A0.SET:return n;case A0.MULT:return e*n;case A0.DIVIDE:return e/n;case A0.SUBSTRACT:return e-n}os.unreachable(t)}static _newAttribValueFromVector2(t,e,n){switch(t){case A0.ADD:return e.add(n);case A0.SET:return n;case A0.MULT:return e.multiply(n);case A0.DIVIDE:return e.divide(n);case A0.SUBSTRACT:return e.sub(n)}os.unreachable(t)}static _newAttribValueFromVector3(t,e,n){switch(t){case A0.ADD:return e.add(n);case A0.SET:return n;case A0.MULT:return e.multiply(n);case A0.DIVIDE:return e.divide(n);case A0.SUBSTRACT:return e.sub(n)}os.unreachable(t)}static _newAttribValueFromVector4(t,e,n){switch(t){case A0.ADD:return e.add(n);case A0.SET:return n;case A0.MULT:return e.multiplyScalar(n.x);case A0.DIVIDE:return e.divideScalar(n.x);case A0.SUBSTRACT:return e.sub(n)}os.unreachable(t)}_amplitudeFromAttrib(t,e){const n=t.attribValue(this.pv.amplitudeAttrib);return m.isNumber(n)?n*e:n instanceof d.a||n instanceof p.a||n instanceof _.a?n.x*e:1}_fbm(t,e,n,i,s){let r=0,o=1;for(let a=0;a{s[3*t.index()+0]=e}));else{let t;for(let e=0;e{s[3*t.index()+1]=e}));else{let t;for(let e=0;e{s[3*t.index()+2]=e}));else{let t;for(let e=0;e{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.geometry],(()=>this.p.geometry.rawInput()))}))}))}async cook(t){const e=this.p.geometry.found_node();if(e)if(e.context()==ts.SOP){const t=await e.compute();this.import_input(e,t)}else this.states.error.set(\\\\\\\"found node is not a geometry\\\\\\\");else this.states.error.set(`node not found at path '${this.pv.geometry}'`)}import_input(t,e){let n;null!=(n=e.coreContentCloned())?this.setCoreGroup(n):this.states.error.set(\\\\\\\"invalid target\\\\\\\")}}class B0 extends sV{static type(){return\\\\\\\"objectProperties\\\\\\\"}cook(t,e){const n=t[0];for(let t of n.objects())e.applyToChildren?t.traverse((t=>{this._update_object(t,e)})):this._update_object(t,e);return n}_update_object(t,e){e.tname&&(t.name=e.name),e.trenderOrder&&(t.renderOrder=e.renderOrder),e.tfrustumCulled&&(t.frustumCulled=e.frustumCulled),e.tmatrixAutoUpdate&&(t.matrixAutoUpdate=e.matrixAutoUpdate),e.tvisible&&(t.visible=e.visible),e.tcastShadow&&(t.castShadow=e.castShadow),e.treceiveShadow&&(t.receiveShadow=e.receiveShadow)}}B0.DEFAULT_PARAMS={applyToChildren:!0,tname:!1,name:\\\\\\\"\\\\\\\",trenderOrder:!1,renderOrder:0,tfrustumCulled:!1,frustumCulled:!0,tmatrixAutoUpdate:!1,matrixAutoUpdate:!1,tvisible:!1,visible:!0,tcastShadow:!1,castShadow:!0,treceiveShadow:!1,receiveShadow:!0},B0.INPUT_CLONED_STATE=Ki.FROM_NODE;const z0=B0.DEFAULT_PARAMS;const k0=new class extends ua{constructor(){super(...arguments),this.applyToChildren=ha.BOOLEAN(z0.applyToChildren,{separatorAfter:!0}),this.tname=ha.BOOLEAN(z0.tname),this.name=ha.STRING(z0.name,{visibleIf:{tname:!0},separatorAfter:!0}),this.trenderOrder=ha.BOOLEAN(z0.trenderOrder),this.renderOrder=ha.INTEGER(z0.renderOrder,{visibleIf:{trenderOrder:!0},range:[0,10],rangeLocked:[!1,!1],separatorAfter:!0}),this.tfrustumCulled=ha.BOOLEAN(z0.tfrustumCulled),this.frustumCulled=ha.BOOLEAN(z0.frustumCulled,{visibleIf:{tfrustumCulled:!0},separatorAfter:!0}),this.tmatrixAutoUpdate=ha.BOOLEAN(z0.tmatrixAutoUpdate),this.matrixAutoUpdate=ha.BOOLEAN(z0.matrixAutoUpdate,{visibleIf:{tmatrixAutoUpdate:!0},separatorAfter:!0}),this.tvisible=ha.BOOLEAN(z0.tvisible),this.visible=ha.BOOLEAN(z0.visible,{visibleIf:{tvisible:!0},separatorAfter:!0}),this.tcastShadow=ha.BOOLEAN(z0.tcastShadow),this.castShadow=ha.BOOLEAN(z0.castShadow,{visibleIf:{tcastShadow:!0},separatorAfter:!0}),this.treceiveShadow=ha.BOOLEAN(z0.treceiveShadow),this.receiveShadow=ha.BOOLEAN(z0.receiveShadow,{visibleIf:{treceiveShadow:!0}})}};class U0 extends lV{constructor(){super(...arguments),this.paramsConfig=k0}static type(){return\\\\\\\"objectProperties\\\\\\\"}static displayedInputNames(){return[\\\\\\\"objects to change properties of\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(B0.INPUT_CLONED_STATE)}async cook(t){this._operation=this._operation||new B0(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const G0=new class extends ua{};class V0 extends lV{constructor(){super(...arguments),this.paramsConfig=G0,this._input_configs_by_operation_container=new WeakMap}static type(){return Bl}initializeNode(){this.io.inputs.initInputsClonedState(Ki.FROM_NODE)}set_output_operation_container(t){this._output_operation_container=t}output_operation_container(){return this._output_operation_container}add_input_config(t,e){let n=this._input_configs_by_operation_container.get(t);n||(n=new Map,this._input_configs_by_operation_container.set(t,n)),n.set(e.operation_input_index,e.node_input_index)}add_operation_container_with_path_param_resolve_required(t){this._operation_containers_requiring_resolve||(this._operation_containers_requiring_resolve=[]),this._operation_containers_requiring_resolve.push(t)}resolve_operation_containers_path_params(){if(this._operation_containers_requiring_resolve)for(let t of this._operation_containers_requiring_resolve)t.resolve_path_params(this)}async cook(t){if(this._output_operation_container){this._output_operation_container.setDirty();const e=await this._output_operation_container.compute(t,this._input_configs_by_operation_container);e&&this.setCoreGroup(e)}}}class H0 extends _f{constructor(t){super(),this._uv_name=t}set_texture_allocations_controller(t){this._texture_allocations_controller=t}handle_globals_node(t,e,n){if(!this._texture_allocations_controller)return;const i=t.io.outputs.namedOutputConnectionPointsByName(e),s=t.glVarName(e);if(this._texture_allocations_controller.variable(e)&&i){const r=i.type(),o=`${r} ${s} = ${this.read_attribute(t,r,e,n)}`;n.addBodyLines(t,[o])}else this.globals_geometry_handler=this.globals_geometry_handler||new Pf,this.globals_geometry_handler.handle_globals_node(t,e,n)}read_attribute(t,e,n,i){if(!this._texture_allocations_controller)return;const s=this._texture_allocations_controller.variable(n);if(!s)return Pf.read_attribute(t,e,n,i);{this.add_particles_sim_uv_attribute(t,i);const e=s.component(),n=s.allocation();if(n){const s=n.textureName(),r=new Nf(t,Uo.SAMPLER_2D,s);i.addDefinitions(t,[r]);return`texture2D( ${s}, ${this._uv_name} ).${e}`}}}add_particles_sim_uv_attribute(t,e){const n=new Sf(t,Uo.VEC2,H0.UV_ATTRIB),i=new Lf(t,Uo.VEC2,H0.UV_VARYING);e.addDefinitions(t,[n,i],Mf.VERTEX),e.addDefinitions(t,[i],Mf.FRAGMENT),e.addBodyLines(t,[`${H0.UV_VARYING} = ${H0.UV_ATTRIB}`],Mf.VERTEX)}}H0.UV_ATTRIB=\\\\\\\"particles_sim_uv_attrib\\\\\\\",H0.UV_VARYING=\\\\\\\"particles_sim_uv_varying\\\\\\\",H0.PARTICLE_SIM_UV=\\\\\\\"particleUV\\\\\\\";class j0{constructor(t){this.node=t,this._particles_group_objects=[],this._all_shader_names=[],this._all_uniform_names=[],this.globals_handler=new H0(H0.UV_VARYING)}setShadersByName(t){this._shaders_by_name=t,this._all_shader_names=[],this._all_uniform_names=[],this._shaders_by_name.forEach(((t,e)=>{this._all_shader_names.push(e),this._all_uniform_names.push(`texture_${e}`)})),this.reset_render_material()}assign_render_material(){if(this._render_material){for(let t of this._particles_group_objects){const e=t;e.geometry&&(e.material=this._render_material,yr.applyCustomMaterials(e,this._render_material),e.matrixAutoUpdate=!1,e.updateMatrix())}this._render_material.needsUpdate=!0,this.update_render_material_uniforms()}}update_render_material_uniforms(){var t;if(!this._render_material)return;let e,n;for(let i=0;i=e&&(null==this._lastSimulatedFrame&&(this._lastSimulatedFrame=e-1),null==this._lastSimulatedTime&&(this._lastSimulatedTime=this.node.scene().time()),t>this._lastSimulatedFrame&&this._computeSimulation(t-this._lastSimulatedFrame))}_computeSimulation(t=1){if(!this._gpuCompute||null==this._lastSimulatedTime)return;this._updateSimulationMaterialUniforms();for(let e=0;et)return void this.node.states.error.set(`max particles is set to (${this.node.pv.texturesSize.x}x${this.node.pv.texturesSize.y}=) ${t}`);this._usedTexturesSize.copy(this.node.pv.texturesSize)}this._forceTimeDependent(),this._initParticlesUVs(),this.node.renderController.reset_render_material();const n=await li.renderersController.waitForRenderer();if(n?this._renderer=n:this.node.states.error.set(\\\\\\\"no renderer found\\\\\\\"),!this._renderer)return;const i=new q0(this._usedTexturesSize.x,this._usedTexturesSize.y,this._renderer);if(i.setDataType(this._dataType()),this._gpuCompute=i,this._gpuCompute){this._lastSimulatedFrame=void 0,this._variablesByName.forEach(((t,e)=>{t.renderTargets[0].dispose(),t.renderTargets[1].dispose(),this._variablesByName.delete(e)})),this._allVariables=[],null===(t=this._shadersByName)||void 0===t||t.forEach(((t,e)=>{if(this._gpuCompute){const n=this._gpuCompute.addVariable(this._textureNameForShaderName(e),t,this._createdTexturesByName.get(e));this._variablesByName.set(e,n),this._allVariables.push(n)}})),null===(e=this._variablesByName)||void 0===e||e.forEach(((t,e)=>{this._gpuCompute&&this._gpuCompute.setVariableDependencies(t,this._allVariables)})),this._createTextureRenderTargets(),this._fillTextures(),this._createSimulationMaterialUniforms();var s=this._gpuCompute.init();null!==s&&(console.error(s),this.node.states.error.set(s))}else this.node.states.error.set(\\\\\\\"failed to create the GPUComputationRenderer\\\\\\\")}_forceTimeDependent(){this._graph_node||(this._graph_node=new Mi(this.node.scene(),\\\\\\\"gpu_compute\\\\\\\"),this._graph_node.addGraphInput(this.node.scene().timeController.graphNode),this._graph_node.addPostDirtyHook(\\\\\\\"on_time_change\\\\\\\",this._onGraphNodeDirty.bind(this)))}_onGraphNodeDirty(){this.node.isOnStartFrame()?this.node.setDirty():this.computeSimilationIfRequired()}materials(){const t=[];return this._variablesByName.forEach(((e,n)=>{t.push(e.material)})),t}_createSimulationMaterialUniforms(){const t=this.node.assemblerController,e=null==t?void 0:t.assembler;if(!e&&!this._persistedTextureAllocationsController)return;const n=[];this._variablesByName.forEach(((t,e)=>{n.push(t.material)}));const i=this._readonlyAllocations();for(let t of n)t.uniforms[xR.TIME]={value:this.node.scene().time()},t.uniforms[xR.DELTA_TIME]={value:this.node.scene().time()},i&&this._assignReadonlyTextures(t,i);if(e)for(let t of n)for(let n of e.param_configs())t.uniforms[n.uniform_name]=n.uniform;else{const t=this.node.persisted_config.loaded_data();if(t){const e=this.node.persisted_config.uniforms();if(e){const s=t.param_uniform_pairs;for(let t of s){const s=t[0],r=t[1],o=this.node.params.get(s),a=e[r];for(let t of n)t.uniforms[r]=a,i&&this._assignReadonlyTextures(t,i);o&&a&&o.options.setOption(\\\\\\\"callback\\\\\\\",(()=>{for(let t of n)tg.callback(o,t.uniforms[r])}))}}}}}_assignReadonlyTextures(t,e){for(let n of e){const e=n.shaderName(),i=this._createdTexturesByName.get(e);if(i){const n=this._textureNameForShaderName(e);t.uniforms[n]={value:i}}}}_updateSimulationMaterialUniforms(){for(let t of this._allVariables)t.material.uniforms[xR.TIME].value=this.node.scene().time(),t.material.uniforms[xR.DELTA_TIME].value=this._deltaTime}_initParticlesUVs(){var t=new Float32Array(2*this._points.length);let e=0;for(var n=0,i=0;i=t.length));s++);const r=H0.UV_ATTRIB;if(this._particlesCoreGroup)for(let e of this._particlesCoreGroup.coreGeometries()){const n=e.geometry(),i=e.markedAsInstance()?O$:C.a;n.setAttribute(r,new i(t,2))}}createdTexturesByName(){return this._createdTexturesByName}_fillTextures(){const t=this._textureAllocationsController();t&&this._createdTexturesByName.forEach(((e,n)=>{const i=t.allocationForShaderName(n);if(!i)return void console.warn(`no allocation found for shader ${n}`);const s=i.variables();if(!s)return void console.warn(\\\\\\\"allocation has no variables\\\\\\\");const r=e.image.data;for(let t of s){const e=t.position();let n=t.name();const i=this._points[0];if(i){if(i.hasAttrib(n)){const t=i.attribSize(n);let s=e;for(let e of this._points){if(1==t){const t=e.attribValue(n);r[s]=t}else e.attribValue(n).toArray(r,s);s+=4}}}}}))}resetGpuCompute(){this._gpuCompute=void 0,this._simulationRestartRequired=!0}setRestartNotRequired(){this._simulationRestartRequired=!1}resetGpuComputeAndSetDirty(){this.resetGpuCompute(),this.node.setDirty()}resetParticleGroups(){this._particlesCoreGroup=void 0}initialized(){return null!=this._particlesCoreGroup&&null!=this._gpuCompute}_createTextureRenderTargets(){this._createdTexturesByName.forEach(((t,e)=>{t.dispose()})),this._createdTexturesByName.clear(),this._variablesByName.forEach(((t,e)=>{this._gpuCompute&&this._createdTexturesByName.set(e,this._gpuCompute.createTexture())}));const t=this._readonlyAllocations();if(t&&this._gpuCompute)for(let e of t)this._createdTexturesByName.set(e.shaderName(),this._gpuCompute.createTexture())}_textureAllocationsController(){var t;return(null===(t=this.node.assemblerController)||void 0===t?void 0:t.assembler.textureAllocationsController())||this._persistedTextureAllocationsController}_readonlyAllocations(){var t;return null===(t=this._textureAllocationsController())||void 0===t?void 0:t.readonlyAllocations()}restartSimulationIfRequired(){this._simulationRestartRequired&&this._restartSimulation()}_restartSimulation(){this._lastSimulatedTime=void 0,this._createTextureRenderTargets();this._getPoints()&&(this._fillTextures(),this._variablesByName.forEach(((t,e)=>{const n=this._createdTexturesByName.get(e);this._gpuCompute&&n&&(this._gpuCompute.renderTexture(n,t.renderTargets[0]),this._gpuCompute.renderTexture(n,t.renderTargets[1]))})))}_getPoints(){if(!this._particlesCoreGroup)return;let t=this._particlesCoreGroup.coreGeometries();const e=t[0];if(e){const n=e.markedAsInstance(),i=[];for(let e of t)e.markedAsInstance()==n&&i.push(e);const s=[];for(let t of i)for(let e of t.points())s.push(e);return s}return[]}}class J0{constructor(t,e){if(this._name=t,this._size=e,this._position=-1,this._readonly=!1,!t)throw\\\\\\\"TextureVariable requires a name\\\\\\\"}merge(t){var e;t.readonly()||this.setReadonly(!1),null===(e=t.graphNodeIds())||void 0===e||e.forEach(((t,e)=>{this.addGraphNodeId(e)}))}setReadonly(t){this._readonly=t}readonly(){return this._readonly}setAllocation(t){this._allocation=t}allocation(){return this._allocation}graphNodeIds(){return this._graph_node_ids}addGraphNodeId(t){this._graph_node_ids=this._graph_node_ids||new Map,this._graph_node_ids.set(t,!0)}name(){return this._name}size(){return this._size}setPosition(t){this._position=t}position(){return this._position}component(){return\\\\\\\"xyzw\\\\\\\".split(\\\\\\\"\\\\\\\").splice(this._position,this._size).join(\\\\\\\"\\\\\\\")}static fromJSON(t){return new J0(t.name,t.size)}toJSON(t){const e=[];return this._graph_node_ids&&this._graph_node_ids.forEach(((n,i)=>{const s=t.graph.nodeFromId(i);if(s){const t=s.path();t&&e.push(t)}})),{name:this.name(),size:this.size(),nodes:e}}}class Z0{constructor(){this._size=0}addVariable(t){this._variables=this._variables||[],this._variables.push(t),t.setPosition(this._size),t.setAllocation(this),this._size+=t.size()}hasSpaceForVariable(t){return this._size+t.size()<=4}shaderName(){var t;return((null===(t=this.variables())||void 0===t?void 0:t.map((t=>t.name())))||[\\\\\\\"no_variables_allocated\\\\\\\"]).join(\\\\\\\"_SEPARATOR_\\\\\\\")}textureName(){return`texture_${this.shaderName()}`}variables(){return this._variables}variablesForInputNode(t){var e;return null===(e=this._variables)||void 0===e?void 0:e.filter((e=>{var n;return(null===(n=e.graphNodeIds())||void 0===n?void 0:n.has(t.graphNodeId()))||!1}))}inputNamesForNode(t){const e=this.variablesForInputNode(t);if(e)return t.type()==ps.ATTRIBUTE?[wf.INPUT_NAME]:e.map((t=>t.name()))}variable(t){if(this._variables)for(let e of this._variables)if(e.name()==t)return e}static fromJSON(t){const e=new Z0;for(let n of t){const t=J0.fromJSON(n);e.addVariable(t)}return e}toJSON(t){return this._variables?this._variables.map((e=>e.toJSON(t))):[]}}const Q0=[\\\\\\\"position\\\\\\\",\\\\\\\"normal\\\\\\\",\\\\\\\"color\\\\\\\",\\\\\\\"uv\\\\\\\"];class K0{constructor(){this._writableAllocations=[],this._readonlyAllocations=[]}static _sortNodes(t){const e=t.filter((t=>t.type()==CF.type())),n=t.filter((t=>t.type()!=CF.type())),i=n.map((t=>t.name())).sort(),s=new Map;for(let t of n)s.set(t.name(),t);for(let t of i){const n=s.get(t);n&&e.push(n)}return e}allocateConnectionsFromRootNodes(t,e){const n=[];t=K0._sortNodes(t),e=K0._sortNodes(e);for(let e of t){const t=e.graphNodeId();switch(e.type()){case CF.type():for(let i of e.io.inputs.namedInputConnectionPoints()){if(e.io.inputs.named_input(i.name())){const e=new J0(i.name(),Wo[i.type()]);e.addGraphNodeId(t),n.push(e)}}break;case wf.type():{const i=e,s=i.connected_input_node(),r=i.connected_input_connection_point();if(s&&r){const e=new J0(i.attribute_name,Wo[r.type()]);e.addGraphNodeId(t),n.push(e)}break}}}for(let t of e){const e=t.graphNodeId();switch(t.type()){case OI.type():{const i=t;for(let t of i.io.outputs.used_output_names()){if(Q0.includes(t)){const s=i.io.outputs.namedOutputConnectionPointsByName(t);if(s){const i=s.type(),r=new J0(t,Wo[i]);r.addGraphNodeId(e),n.push(r)}}}break}case wf.type():{const i=t,s=i.output_connection_point();if(s){const t=new J0(i.attribute_name,Wo[s.type()]);i.isExporting()||t.setReadonly(!0),t.addGraphNodeId(e),n.push(t)}break}}}this._allocateVariables(n)}_allocateVariables(t){const e=f.sortBy(t,(t=>-t.size())),n=this._ensureVariablesAreUnique(e);for(let t of n)t.readonly()?this._allocateVariable(t,this._readonlyAllocations):this._allocateVariable(t,this._writableAllocations)}_ensureVariablesAreUnique(t){const e=new Map;for(let n of t)h.pushOnArrayAtEntry(e,n.name(),n);const n=[];return e.forEach(((t,e)=>{const i=t[0];n.push(i);for(let e=1;et.shaderName()));return f.uniq(t)}createShaderConfigs(){return[]}allocationForShaderName(t){const e=this._writableAllocations.filter((e=>e.shaderName()==t))[0];return e||this._readonlyAllocations.filter((e=>e.shaderName()==t))[0]}inputNamesForShaderName(t,e){const n=this.allocationForShaderName(e);if(n)return n.inputNamesForNode(t)}variable(t){for(let e of this._writableAllocations){const n=e.variable(t);if(n)return n}for(let e of this._readonlyAllocations){const n=e.variable(t);if(n)return n}}variables(){const t=this._writableAllocations.map((t=>t.variables()||[])).flat(),e=this._writableAllocations.map((t=>t.variables()||[])).flat();return t.concat(e)}hasVariable(t){return this.variables().map((t=>t.name())).includes(t)}static fromJSON(t){const e=new K0;for(let n of t.writable){const t=n[Object.keys(n)[0]],i=Z0.fromJSON(t);e._addWritableAllocation(i)}for(let n of t.readonly){const t=n[Object.keys(n)[0]],i=Z0.fromJSON(t);e._addReadonlyAllocation(i)}return e}toJSON(t){return{writable:this._writableAllocations.map((e=>({[e.shaderName()]:e.toJSON(t)}))),readonly:this._readonlyAllocations.map((e=>({[e.shaderName()]:e.toJSON(t)})))}}print(t){console.warn(JSON.stringify(this.toJSON(t),[\\\\\\\"\\\\\\\"],2))}}class t1 extends Qf{constructor(t){super(t),this.node=t}toJSON(){const t=this.node.assemblerController;if(!t)return;const e={};this.node.shaders_by_name().forEach(((t,n)=>{e[n]=t}));const n=t.assembler.textureAllocationsController().toJSON(this.node.scene()),i=[],s=new F,r=t.assembler.param_configs();for(let t of r)i.push([t.name(),t.uniform_name]),s.uniforms[t.uniform_name]=t.uniform;const o=this._materialToJson(s,{node:this.node,suffix:\\\\\\\"main\\\\\\\"});return{shaders_by_name:e,texture_allocations:n,param_uniform_pairs:i,uniforms_owner:o||{}}}load(t){li.playerMode()&&(this._loaded_data=t,this.node.init_with_persisted_config())}loaded_data(){return this._loaded_data}shaders_by_name(){if(this._loaded_data){const t=new Map,e=Object.keys(this._loaded_data.shaders_by_name);for(let n of e)t.set(n,this._loaded_data.shaders_by_name[n]);return t}}texture_allocations_controller(){if(this._loaded_data)return K0.fromJSON(this._loaded_data.texture_allocations)}uniforms(){if(this._loaded_data){const t=this._loadMaterial(this._loaded_data.uniforms_owner);return(null==t?void 0:t.uniforms)||{}}}}const e1=new class extends ua{constructor(){super(...arguments),this.startFrame=ha.FLOAT(Nl.START_FRAME,{range:[0,1e3],rangeLocked:[!0,!1]}),this.autoTexturesSize=ha.BOOLEAN(1),this.maxTexturesSize=ha.VECTOR2([1024,1024],{visibleIf:{autoTexturesSize:1}}),this.texturesSize=ha.VECTOR2([64,64],{visibleIf:{autoTexturesSize:0}}),this.dataType=ha.INTEGER(0,{menu:{entries:X0.map(((t,e)=>({value:e,name:t})))}}),this.reset=ha.BUTTON(null,{callback:(t,e)=>{n1.PARAM_CALLBACK_reset(t)}}),this.material=ha.OPERATOR_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.MAT},dependentOnFoundNode:!1})}};class n1 extends lV{constructor(){super(...arguments),this.paramsConfig=e1,this._assembler_controller=this._create_assembler_controller(),this.persisted_config=new t1(this),this.globals_handler=new H0(H0.PARTICLE_SIM_UV),this._shaders_by_name=new Map,this.gpuController=new $0(this),this.renderController=new j0(this),this._reset_material_if_dirty_bound=this._reset_material_if_dirty.bind(this),this._children_controller_context=ts.GL}static type(){return\\\\\\\"particlesSystemGpu\\\\\\\"}dispose(){super.dispose(),this.gpuController.dispose()}get assemblerController(){return this._assembler_controller}usedAssembler(){return jn.GL_PARTICLES}_create_assembler_controller(){return li.assemblersRegister.assembler(this,this.usedAssembler())}shaders_by_name(){return this._shaders_by_name}static require_webgl2(){return!0}static PARAM_CALLBACK_reset(t){t.PARAM_CALLBACK_reset()}PARAM_CALLBACK_reset(){this.gpuController.resetGpuComputeAndSetDirty()}static displayedInputNames(){return[\\\\\\\"points to emit particles from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Ki.NEVER),this.addPostDirtyHook(\\\\\\\"_reset_material_if_dirty\\\\\\\",this._reset_material_if_dirty_bound)}createNode(t,e){return super.createNode(t,e)}children(){return super.children()}nodesByType(t){return super.nodesByType(t)}childrenAllowed(){return this.assemblerController?super.childrenAllowed():(this.scene().markAsReadOnly(this),!1)}async _reset_material_if_dirty(){this.p.material.isDirty()&&(this.renderController.reset_render_material(),this.isOnStartFrame()||await this.renderController.init_render_material())}isOnStartFrame(){return this.scene().frame()==this.pv.startFrame}async cook(t){this.gpuController.setRestartNotRequired();const e=t[0];this.compileIfRequired();const n=this.isOnStartFrame();n&&this.gpuController.resetParticleGroups(),this.gpuController.initialized()||await this.gpuController.init(e),this.renderController.initialized()||(this.renderController.init_core_group(e),await this.renderController.init_render_material()),this.gpuController.restartSimulationIfRequired(),this.gpuController.computeSimilationIfRequired(),n?this.setCoreGroup(e):this.cookController.endCook()}async compileIfRequired(){var t;(null===(t=this.assemblerController)||void 0===t?void 0:t.compileRequired())&&await this.run_assembler()}async run_assembler(){const t=this.assemblerController;if(!t)return;const e=this._find_export_nodes();if(e.length>0){const n=e;t.set_assembler_globals_handler(this.globals_handler),t.assembler.set_root_nodes(n),t.assembler.compile(),t.post_compile()}const n=t.assembler.shaders_by_name();this._setShaderNames(n)}_setShaderNames(t){this._shaders_by_name=t,this.gpuController.setShadersByName(this._shaders_by_name),this.renderController.setShadersByName(this._shaders_by_name),this.gpuController.resetGpuCompute(),this.gpuController.resetParticleGroups()}init_with_persisted_config(){const t=this.persisted_config.shaders_by_name(),e=this.persisted_config.texture_allocations_controller();t&&e&&(this._setShaderNames(t),this.gpuController.setPersistedTextureAllocationController(e))}_find_export_nodes(){const t=Df.findAttributeExportNodes(this),e=Df.findOutputNodes(this);if(e.length>1)return this.states.error.set(\\\\\\\"only one output node is allowed\\\\\\\"),[];const n=e[0];return n&&t.push(n),t}}class i1 extends sV{static type(){return\\\\\\\"peak\\\\\\\"}cook(t,e){const n=t[0];let i,s;for(let t of n.objects())t.traverse((t=>{let n;if(null!=(n=t.geometry)){for(s of(i=new fr(n),i.points())){const t=s.normal(),n=s.position().clone().add(t.multiplyScalar(e.amount));s.setPosition(n)}i.geometry().getAttribute(\\\\\\\"position\\\\\\\").needsUpdate=!0}}));return t[0]}}i1.DEFAULT_PARAMS={amount:0};const s1=i1.DEFAULT_PARAMS;const r1=new class extends ua{constructor(){super(...arguments),this.amount=ha.FLOAT(s1.amount,{range:[-1,1]})}};class o1 extends lV{constructor(){super(...arguments),this.paramsConfig=r1}static type(){return\\\\\\\"peak\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Ki.FROM_NODE)}cook(t){this._operation=this._operation||new i1(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const a1=new p.a(0,0,1),l1=new p.a(0,0,1),c1=new p.a(0,1,0);class h1 extends sV{constructor(){super(...arguments),this._core_transform=new vU,this._size=new p.a,this._center=new p.a,this._segmentsCount=new d.a(1,1)}static type(){return\\\\\\\"plane\\\\\\\"}cook(t,e){const n=t[0];return n?this._cook_with_input(n,e):this._cook_without_input(e)}_cook_without_input(t){const e=this._create_plane(t.size,t);this._core_transform.rotate_geometry(e,a1,t.direction);const n=this._core_transform.translation_matrix(t.center);return e.applyMatrix4(n),this.createCoreGroupFromGeometry(e)}_cook_with_input(t,e){const n=t.boundingBox();n.getSize(this._size),n.getCenter(this._center);const i=new d.a(this._size.x,this._size.z),s=this._create_plane(i,e);this._core_transform.rotate_geometry(s,l1,c1);const r=this._core_transform.translation_matrix(this._center);return s.applyMatrix4(r),this.createCoreGroupFromGeometry(s)}_create_plane(t,e){return t=t.clone(),e.useSegmentsCount?(this._segmentsCount.x=Math.floor(e.segments.x),this._segmentsCount.y=Math.floor(e.segments.y)):e.stepSize>0&&(this._segmentsCount.x=Math.floor(t.x/e.stepSize),this._segmentsCount.y=Math.floor(t.y/e.stepSize),t.x=this._segmentsCount.x*e.stepSize,t.y=this._segmentsCount.y*e.stepSize),new L(t.x,t.y,this._segmentsCount.x,this._segmentsCount.y)}}h1.DEFAULT_PARAMS={size:new d.a(1,1),useSegmentsCount:!1,stepSize:1,segments:new d.a(1,1),direction:new p.a(0,1,0),center:new p.a(0,0,0)},h1.INPUT_CLONED_STATE=Ki.NEVER;const u1=h1.DEFAULT_PARAMS;const d1=new class extends ua{constructor(){super(...arguments),this.size=ha.VECTOR2(u1.size),this.useSegmentsCount=ha.BOOLEAN(u1.useSegmentsCount),this.stepSize=ha.FLOAT(u1.stepSize,{range:[.001,1],rangeLocked:[!1,!1],visibleIf:{useSegmentsCount:0}}),this.segments=ha.VECTOR2(u1.segments,{visibleIf:{useSegmentsCount:1}}),this.direction=ha.VECTOR3(u1.direction),this.center=ha.VECTOR3(u1.center)}};class p1 extends lV{constructor(){super(...arguments),this.paramsConfig=d1}static type(){return\\\\\\\"plane\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to create plane from (optional)\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(h1.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new h1(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class _1 extends sV{static type(){return\\\\\\\"playerCapsule\\\\\\\"}cook(t,e){return this.createCoreGroupFromGeometry(Fy(e))}}_1.DEFAULT_PARAMS={radius:.5,height:1};const m1=_1.DEFAULT_PARAMS;const f1=new class extends ua{constructor(){super(...arguments),this.radius=ha.FLOAT(m1.radius,{range:[0,1],rangeLocked:[!0,!1]}),this.height=ha.FLOAT(m1.height,{range:[0,1],rangeLocked:[!0,!1]})}};class g1 extends lV{constructor(){super(...arguments),this.paramsConfig=f1}static type(){return\\\\\\\"playerCapsule\\\\\\\"}initializeNode(){this.io.inputs.setCount(0)}cook(t){this._operation=this._operation||new _1(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const v1=\\\\\\\"position\\\\\\\";const y1=new class extends ua{constructor(){super(...arguments),this.updateX=ha.BOOLEAN(0),this.x=ha.FLOAT(\\\\\\\"@P.x\\\\\\\",{visibleIf:{updateX:1},expression:{forEntities:!0}}),this.updateY=ha.BOOLEAN(0),this.y=ha.FLOAT(\\\\\\\"@P.y\\\\\\\",{visibleIf:{updateY:1},expression:{forEntities:!0}}),this.updateZ=ha.BOOLEAN(0),this.z=ha.FLOAT(\\\\\\\"@P.z\\\\\\\",{visibleIf:{updateZ:1},expression:{forEntities:!0}}),this.updateNormals=ha.BOOLEAN(1)}};class x1 extends lV{constructor(){super(...arguments),this.paramsConfig=y1,this._x_arrays_by_geometry_uuid=new Map,this._y_arrays_by_geometry_uuid=new Map,this._z_arrays_by_geometry_uuid=new Map}static type(){return\\\\\\\"point\\\\\\\"}static displayedInputNames(){return[\\\\\\\"points to move\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Ki.FROM_NODE)}async cook(t){const e=t[0];await this._eval_expressions_for_core_group(e)}async _eval_expressions_for_core_group(t){const e=t.coreObjects();for(let t=0;t{h[t.index()]=e}));else{let t;for(let e=0;e({name:t,value:e})))}}),this.center=ha.VECTOR3(C1.center.toArray()),this.longitude=ha.FLOAT(C1.longitude,{range:[0,360]}),this.latitude=ha.FLOAT(C1.latitude,{range:[-180,180]}),this.depth=ha.FLOAT(C1.depth,{range:[0,10]})}};class L1 extends lV{constructor(){super(...arguments),this.paramsConfig=N1}static type(){return\\\\\\\"polarTransform\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometries or objects to transform\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(S1.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new S1(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class O1{static accumulated_curve_point_indices(t){let e=[];const n=[];let i,s=null;for(let r=0;r{r[t]=[]})),e.forEach(((e,o)=>{const a=t[e];n.forEach((t=>{const e=a.attribValue(t);let n;n=i[t]>1?e.toArray():[e],n.forEach((e=>{r[t].push(e)}))})),o>0&&(s.push(o-1),s.push(o))}));const o=new S.a;return n.forEach((t=>{const e=i[t],n=r[t];o.setAttribute(t,new C.c(n,e))})),o.setIndex(s),o}static line_segment_to_geometries(t){var e;const n=[],i=new fr(t),s=i.attribNames(),r=i.points(),o=(null===(e=t.getIndex())||void 0===e?void 0:e.array)||[],a=this.accumulated_curve_point_indices(o);if(a.length>0){const e=i.attribSizes();a.forEach(((i,o)=>{t=this.create_line_segment_geometry(r,i,s,e),n.push(t)}))}return n}}class P1{constructor(t,e,n){this.geometry=t,this.geometry1=e,this.geometry0=n}process(){const t=new fr(this.geometry0),e=new fr(this.geometry1),n=t.segments(),i=e.segments();if(0===n.length||0===i.length)return;const s=n.length{const n=l[e];p.push(t[0]),p.push(t[1]),p.push(n[0]+u),p.push(t[1]),p.push(n[1]+u),p.push(n[0]+u)}));f.intersection(r.attribNames(),o.attribNames()).forEach((t=>{const e=r.attribSize(t);let n,i=d.map((e=>e.attribValue(t)));n=1==e?i:i.map((t=>t.toArray())).flat(),this.geometry.setAttribute(t,new C.c(n,e))})),this.geometry.setIndex(p),this.geometry.computeVertexNormals()}}const R1=new p.a(0,0,0),I1=new p.a(1,1,1);const F1=new class extends ua{constructor(){super(...arguments),this.radius=ha.FLOAT(1),this.segmentsRadial=ha.INTEGER(8,{range:[3,20],rangeLocked:[!0,!1]}),this.closed=ha.BOOLEAN(0)}};class D1 extends lV{constructor(){super(...arguments),this.paramsConfig=F1,this._core_transform=new vU,this._geometries=[]}static type(){return\\\\\\\"polywire\\\\\\\"}static displayedInputNames(){return[\\\\\\\"lines to create tubes from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Ki.NEVER)}cook(t){const e=t[0];this._geometries=[];for(let t of e.objects())t instanceof Ms.a&&this._create_tube(t);const n=fr.mergeGeometries(this._geometries);for(let t of this._geometries)t.dispose();if(n){const t=this.createObject(n,Ns.MESH);this.setObject(t)}else this.setObjects([])}_create_tube(t){var e;const n=t.geometry,i=new fr(n).points(),s=null===(e=n.getIndex())||void 0===e?void 0:e.array,r=O1.accumulated_curve_point_indices(s);for(let t of r){const e=t.map((t=>i[t]));this._create_tube_from_points(e)}}_create_tube_from_points(t){if(t.length<=1)return;const e=t.map((t=>t.attribValue(\\\\\\\"position\\\\\\\"))),n=XJ.create(this.pv.radius,this.pv.segmentsRadial),i=[];for(let t of e){const e=t,s=this._core_transform.matrix(e,R1,I1,1,gU),r=n.clone();r.applyMatrix4(s),i.push(r)}for(let t=0;t0){const e=i[t],n=i[t-1],s=this._skin(n,e);this._geometries.push(s)}}_skin(t,e){const n=new S.a;return new P1(n,t,e).process(),n}}const B1=\\\\\\\"dist\\\\\\\";class z1 extends sV{constructor(){super(...arguments),this._matDoubleSideTmpSetter=new fQ,this._raycaster=function(){const t=new QL;return t.firstHitOnly=!0,t}(),this._pointPos=new p.a,this._pointNormal=new p.a}static type(){return\\\\\\\"ray\\\\\\\"}cook(t,e){const n=t[0],i=t[1];return this._ray(n,i,e)}_ray(t,e,n){let i,s;this._matDoubleSideTmpSetter.setCoreGroupMaterialDoubleSided(e),n.addDistAttribute&&(t.hasAttrib(B1)||t.addNumericVertexAttrib(B1,1,-1));const r=t.points();for(let t of r)if(t.getPosition(this._pointPos),i=n.direction,n.useNormals&&(t.getNormal(this._pointNormal),i=this._pointNormal),this._raycaster.set(this._pointPos,i),s=this._raycaster.intersectObjects(e.objects(),!0)[0],s){if(n.transformPoints&&t.setPosition(s.point),n.addDistAttribute){const e=this._pointPos.distanceTo(s.point);console.log(e),t.setAttribValue(B1,e)}n.transferFaceNormals&&s.face&&t.setNormal(s.face.normal)}return this._matDoubleSideTmpSetter.restoreMaterialSideProperty(e),t}}z1.DEFAULT_PARAMS={useNormals:!0,direction:new p.a(0,-1,0),transformPoints:!0,transferFaceNormals:!0,addDistAttribute:!1},z1.INPUT_CLONED_STATE=[Ki.FROM_NODE,Ki.NEVER];const k1=z1.DEFAULT_PARAMS;const U1=new class extends ua{constructor(){super(...arguments),this.useNormals=ha.BOOLEAN(k1.useNormals),this.direction=ha.VECTOR3(k1.direction.toArray(),{visibleIf:{useNormals:0}}),this.transformPoints=ha.BOOLEAN(k1.transformPoints),this.transferFaceNormals=ha.BOOLEAN(k1.transferFaceNormals),this.addDistAttribute=ha.BOOLEAN(k1.addDistAttribute)}};class G1 extends lV{constructor(){super(...arguments),this.paramsConfig=U1}static type(){return\\\\\\\"ray\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to move\\\\\\\",\\\\\\\"geometry to ray onto\\\\\\\"]}initializeNode(){this.io.inputs.setCount(2),this.io.inputs.initInputsClonedState(z1.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new z1(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const V1={color:{value:null},tDiffuse:{value:null},textureMatrix:{value:null},opacity:{value:.5}},H1=\\\\\\\"uniform mat4 textureMatrix;\\\\nvarying vec4 vUv;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvUv = textureMatrix * vec4( position, 1.0 );\\\\n\\\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\\\n\\\\n}\\\\\\\",j1=\\\\\\\"uniform vec3 color;\\\\nuniform sampler2D tDiffuse;\\\\nvarying vec4 vUv;\\\\nuniform float opacity;\\\\n\\\\nfloat blendOverlay( float base, float blend ) {\\\\n\\\\n\\\\treturn( base < 0.5 ? ( 2.0 * base * blend ) : ( 1.0 - 2.0 * ( 1.0 - base ) * ( 1.0 - blend ) ) );\\\\n\\\\n}\\\\n\\\\nvec3 blendOverlay( vec3 base, vec3 blend ) {\\\\n\\\\n\\\\treturn vec3( blendOverlay( base.r, blend.r ), blendOverlay( base.g, blend.g ), blendOverlay( base.b, blend.b ) );\\\\n\\\\n}\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec4 base = texture2DProj( tDiffuse, vUv );\\\\n\\\\tgl_FragColor = vec4( blendOverlay( base.rgb, color ), opacity );\\\\n\\\\n}\\\\\\\",W1={minFilter:w.V,magFilter:w.V,format:w.ic};class q1 extends B.a{constructor(t,e){super(),this.geometry=t,this._options=e,this.type=\\\\\\\"Reflector\\\\\\\",this.reflectorPlane=new Y.a,this.normal=new p.a,this.reflectorWorldPosition=new p.a,this.cameraWorldPosition=new p.a,this.rotationMatrix=new A.a,this.lookAtPosition=new p.a(0,0,-1),this.clipPlane=new _.a,this.view=new p.a,this.target=new p.a,this.q=new _.a,this.textureMatrix=new A.a,this.virtualCamera=new tt.a,this.onBeforeRender=this._onBeforeRender.bind(this),this._onWindowResizeBound=this._onWindowResize.bind(this);const{width:n,height:i}=this._getRendererSize(this._options.renderer);this.renderTarget=new Q(n,i,W1),Object(On.i)(n)&&Object(On.i)(i)||(this.renderTarget.texture.generateMipmaps=!1),this._coreRenderBlur=new CG(new d.a(n,i)),this.material=new F({uniforms:I.clone(V1),fragmentShader:j1,vertexShader:H1}),this.material.uniforms.tDiffuse.value=this.renderTarget.texture,this.material.uniforms.color.value=this._options.color,this.material.uniforms.textureMatrix.value=this.textureMatrix,this.material.uniforms.opacity.value=this._options.opacity,this.material.transparent=this._options.opacity<1,this._addWindowResizeEvent()}_addWindowResizeEvent(){window.addEventListener(\\\\\\\"resize\\\\\\\",this._onWindowResizeBound.bind(this),!1)}_removeWindowResizeEvent(){window.removeEventListener(\\\\\\\"resize\\\\\\\",this._onWindowResizeBound.bind(this),!1)}_onWindowResize(){this.traverseAncestors((t=>{t.parent||t.uuid!=this._options.scene.uuid&&this._removeWindowResizeEvent()}));const{width:t,height:e}=this._getRendererSize(this._options.renderer);this.renderTarget.setSize(t,e),this._coreRenderBlur.setSize(t,e)}_getRendererSize(t){const e=t.domElement;return{width:e.width*this._options.pixelRatio,height:e.height*this._options.pixelRatio}}_onBeforeRender(t,e,n,i,s,r){if(!this._options.active)return;const o=n;if(this.reflectorWorldPosition.setFromMatrixPosition(this.matrixWorld),this.cameraWorldPosition.setFromMatrixPosition(o.matrixWorld),this.rotationMatrix.extractRotation(this.matrixWorld),this.normal.set(0,0,1),this.normal.applyMatrix4(this.rotationMatrix),this.view.subVectors(this.reflectorWorldPosition,this.cameraWorldPosition),!(this.view.dot(this.normal)>0)){this.view.reflect(this.normal).negate(),this.view.add(this.reflectorWorldPosition),this.rotationMatrix.extractRotation(o.matrixWorld),this.lookAtPosition.set(0,0,-1),this.lookAtPosition.applyMatrix4(this.rotationMatrix),this.lookAtPosition.add(this.cameraWorldPosition),this.target.subVectors(this.reflectorWorldPosition,this.lookAtPosition),this.target.reflect(this.normal).negate(),this.target.add(this.reflectorWorldPosition),this.virtualCamera.position.copy(this.view),this.virtualCamera.up.set(0,1,0),this.virtualCamera.up.applyMatrix4(this.rotationMatrix),this.virtualCamera.up.reflect(this.normal),this.virtualCamera.lookAt(this.target),this.virtualCamera.far=o.far,this.virtualCamera.updateMatrixWorld(),this.virtualCamera.projectionMatrix.copy(o.projectionMatrix),this.textureMatrix.set(.5,0,0,.5,0,.5,0,.5,0,0,.5,.5,0,0,0,1),this.textureMatrix.multiply(this.virtualCamera.projectionMatrix),this.textureMatrix.multiply(this.virtualCamera.matrixWorldInverse),this.textureMatrix.multiply(this.matrixWorld),this.reflectorPlane.setFromNormalAndCoplanarPoint(this.normal,this.reflectorWorldPosition),this.reflectorPlane.applyMatrix4(this.virtualCamera.matrixWorldInverse),this.clipPlane.set(this.reflectorPlane.normal.x,this.reflectorPlane.normal.y,this.reflectorPlane.normal.z,this.reflectorPlane.constant);var a=this.virtualCamera.projectionMatrix;this.q.x=(Math.sign(this.clipPlane.x)+a.elements[8])/a.elements[0],this.q.y=(Math.sign(this.clipPlane.y)+a.elements[9])/a.elements[5],this.q.z=-1,this.q.w=(1+a.elements[10])/a.elements[14],this.clipPlane.multiplyScalar(2/this.clipPlane.dot(this.q)),a.elements[2]=this.clipPlane.x,a.elements[6]=this.clipPlane.y,a.elements[10]=this.clipPlane.z+1-this._options.clipBias,a.elements[14]=this.clipPlane.w,this.renderTarget.texture.encoding=t.outputEncoding,this.visible=!1;var l=t.getRenderTarget(),c=t.xr.enabled,h=t.shadowMap.autoUpdate;if(t.xr.enabled=!1,t.shadowMap.autoUpdate=!1,t.setRenderTarget(this.renderTarget),t.state.buffers.depth.setMask(!0),!1===t.autoClear&&t.clear(),t.render(e,this.virtualCamera),this._options.tblur){const e=this._options.blur*this._options.pixelRatio,n=e*this._options.verticalBlurMult;if(this._coreRenderBlur.applyBlur(this.renderTarget,t,e,n),this._options.tblur2){const e=this._options.blur2*this._options.pixelRatio,n=e*this._options.verticalBlur2Mult;this._coreRenderBlur.applyBlur(this.renderTarget,t,e,n)}}t.xr.enabled=c,t.shadowMap.autoUpdate=h,t.setRenderTarget(l);var u=o.viewport;void 0!==u&&t.state.viewport(u),this.visible=!0}}}class X1 extends sV{static type(){return\\\\\\\"reflector\\\\\\\"}async cook(t,e){const n=t[0],i=[],s=await li.renderersController.firstRenderer();if(!s)return this.createCoreGroupFromObjects(i);const r=n.objectsWithGeo();for(let t of r){const n=new q1(t.geometry,{clipBias:e.clipBias,renderer:s,scene:this.scene().threejsScene(),pixelRatio:e.pixelRatio,color:e.color,opacity:e.opacity,active:e.active,tblur:e.tblur,blur:e.blur,verticalBlurMult:e.verticalBlurMult,tblur2:e.tblur2,blur2:e.blur2,verticalBlur2Mult:e.verticalBlur2Mult});n.position.copy(t.position),n.rotation.copy(t.rotation),n.scale.copy(t.scale),n.updateMatrix(),i.push(n)}return this.createCoreGroupFromObjects(i)}}X1.DEFAULT_PARAMS={active:!0,clipBias:.003,color:new D.a(1,1,1),opacity:1,pixelRatio:1,tblur:!1,blur:1,verticalBlurMult:1,tblur2:!1,blur2:1,verticalBlur2Mult:1},X1.INPUT_CLONED_STATE=Ki.NEVER;const Y1=X1.DEFAULT_PARAMS;const $1=new class extends ua{constructor(){super(...arguments),this.active=ha.BOOLEAN(Y1.active),this.clipBias=ha.FLOAT(Y1.clipBias),this.color=ha.COLOR(Y1.color.toArray()),this.opacity=ha.FLOAT(Y1.opacity),this.pixelRatio=ha.INTEGER(Y1.pixelRatio,{range:[1,4],rangeLocked:[!0,!1]}),this.tblur=ha.BOOLEAN(Y1.tblur),this.blur=ha.FLOAT(Y1.blur,{visibleIf:{tblur:1}}),this.verticalBlurMult=ha.FLOAT(Y1.verticalBlurMult,{visibleIf:{tblur:1}}),this.tblur2=ha.BOOLEAN(Y1.tblur2,{visibleIf:{tblur:1}}),this.blur2=ha.FLOAT(Y1.blur2,{visibleIf:{tblur:1,tblur2:1}}),this.verticalBlur2Mult=ha.FLOAT(Y1.verticalBlur2Mult,{visibleIf:{tblur:1,tblur2:1}})}};class J1 extends lV{constructor(){super(...arguments),this.paramsConfig=$1}static type(){return\\\\\\\"reflector\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to create a reflector from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(X1.INPUT_CLONED_STATE)}async cook(t){this._operation=this._operation||new X1(this._scene,this.states);const e=await this._operation.cook(t,this.pv);this.setCoreGroup(e)}}var Z1=n(85);var Q1;!function(t){t.POINTS_COUNT=\\\\\\\"pointsCount\\\\\\\",t.SEGMENT_LENGTH=\\\\\\\"segmentLength\\\\\\\"}(Q1||(Q1={}));const K1=[Q1.POINTS_COUNT,Q1.SEGMENT_LENGTH];var t2;!function(t){t.CENTRIPETAL=\\\\\\\"centripetal\\\\\\\",t.CHORDAL=\\\\\\\"chordal\\\\\\\",t.CATMULLROM=\\\\\\\"catmullrom\\\\\\\"}(t2||(t2={}));const e2=[t2.CENTRIPETAL,t2.CHORDAL,t2.CATMULLROM];const n2=new class extends ua{constructor(){super(...arguments),this.method=ha.INTEGER(K1.indexOf(Q1.POINTS_COUNT),{menu:{entries:K1.map(((t,e)=>({name:t,value:e})))}}),this.curveType=ha.INTEGER(e2.indexOf(t2.CATMULLROM),{range:[0,2],rangeLocked:[!0,!0],menu:{entries:e2.map(((t,e)=>({name:t,value:e})))}}),this.tension=ha.FLOAT(.01,{range:[0,1],rangeLocked:[!0,!0]}),this.pointsCount=ha.INTEGER(100,{visibleIf:{method:K1.indexOf(Q1.POINTS_COUNT)},range:[1,1e3],rangeLocked:[!0,!1]}),this.segmentLength=ha.FLOAT(1,{visibleIf:{method:K1.indexOf(Q1.SEGMENT_LENGTH)}})}};class i2 extends lV{constructor(){super(...arguments),this.paramsConfig=n2}static type(){return\\\\\\\"resample\\\\\\\"}initializeNode(){this.io.inputs.setCount(1)}cook(t){const e=t[0],n=[];if(this.pv.pointsCount>=2){const t=e.coreObjects();for(let e=0;ei[t])),n=this._create_curve_from_points(e);n&&o.push(n)}const a=ur(o);return this.createObject(a,Ns.LINE_SEGMENTS)}_create_curve_from_points(t){if(t.length<=1)return;const e=t.map((t=>t.attribValue(\\\\\\\"position\\\\\\\"))),n=e2[this.pv.curveType],i=this.pv.tension,s=new Z1.a(e,!1,n,i),r=this._get_points_from_curve(s);let o=[];const a=[];for(let t=0;t0&&(a.push(t-1),a.push(t))}const l=new S.a;return l.setAttribute(\\\\\\\"position\\\\\\\",new C.c(o.flat(),3)),l.setIndex(a),l}_get_points_from_curve(t){const e=K1[this.pv.method];switch(e){case Q1.POINTS_COUNT:return t.getSpacedPoints(Math.max(2,this.pv.pointsCount));case Q1.SEGMENT_LENGTH:var n=t.getLength(),i=0!==this.pv.segmentLength?1+n/this.pv.segmentLength:2;return i=Math.max(2,i),t.getSpacedPoints(i)}os.unreachable(e)}}class s2 extends sV{static type(){return\\\\\\\"restAttributes\\\\\\\"}cook(t,e){const n=t[0].objectsWithGeo();return e.tposition&&this._create_rest_attribute(n,e.position,e.restP),e.tnormal&&this._create_rest_attribute(n,e.normal,e.restN),this.createCoreGroupFromObjects(n)}_create_rest_attribute(t,e,n){for(let i of t){const t=i.geometry;if(t){const i=t.getAttribute(e);i&&t.setAttribute(n,i.clone())}}}}s2.DEFAULT_PARAMS={tposition:!0,position:\\\\\\\"position\\\\\\\",restP:\\\\\\\"restP\\\\\\\",tnormal:!0,normal:\\\\\\\"normal\\\\\\\",restN:\\\\\\\"restN\\\\\\\"};const r2=s2.DEFAULT_PARAMS;const o2=new class extends ua{constructor(){super(...arguments),this.tposition=ha.BOOLEAN(r2.tposition),this.position=ha.STRING(r2.position,{visibleIf:{tposition:!0}}),this.restP=ha.STRING(r2.restP,{visibleIf:{tposition:!0}}),this.tnormal=ha.BOOLEAN(r2.tnormal),this.normal=ha.STRING(r2.normal,{visibleIf:{tnormal:!0}}),this.restN=ha.STRING(r2.restN,{visibleIf:{tnormal:!0}})}};class a2 extends lV{constructor(){super(...arguments),this.paramsConfig=o2}static type(){return\\\\\\\"restAttributes\\\\\\\"}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState([Ki.FROM_NODE])}cook(t){this._operation=this._operation||new s2(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class l2 extends sV{constructor(){super(...arguments),this._core_transform=new vU}static type(){return\\\\\\\"roundedBox\\\\\\\"}cook(t,e){const n=t[0],i=n?this._cook_with_input(n,e):this._cook_without_input(e);return this.createCoreGroupFromGeometry(i)}_cook_without_input(t){const e=t.size,n=new Iy(e.x,e.y,e.z,t.divisions,t.bevel);return n.translate(t.center.x,t.center.y,t.center.z),n.computeVertexNormals(),n}_cook_with_input(t,e){const n=e.divisions,i=t.boundingBox(),s=i.max.clone().sub(i.min),r=i.max.clone().add(i.min).multiplyScalar(.5),o=new Iy(s.x,s.y,s.z,n,e.bevel),a=this._core_transform.translation_matrix(r);return o.applyMatrix4(a),o}}l2.DEFAULT_PARAMS={size:new p.a(1,1,1),divisions:2,bevel:.1,center:new p.a(0,0,0)},l2.INPUT_CLONED_STATE=Ki.NEVER;const c2=l2.DEFAULT_PARAMS;const h2=new class extends ua{constructor(){super(...arguments),this.size=ha.VECTOR3(c2.size),this.divisions=ha.INTEGER(c2.divisions,{range:[1,10],rangeLocked:[!0,!1]}),this.bevel=ha.FLOAT(c2.bevel,{range:[0,1],rangeLocked:[!0,!1]}),this.center=ha.VECTOR3(c2.center)}};class u2 extends lV{constructor(){super(...arguments),this.paramsConfig=h2}static type(){return\\\\\\\"roundedBox\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to create bounding box from (optional)\\\\\\\"]}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(l2.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new l2(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class d2 extends sV{static type(){return\\\\\\\"scatter\\\\\\\"}async cook(t,e){const n=t[0];let i=n.faces();const s=[];let r=0;const o=new Map;for(let t of i){const e=t.area();o.set(t.index(),e)}const a=f.sortBy(i,(t=>o.get(t.index())||-1));let l=0;for(let t of a)r+=o.get(t.index()),s[l]=r,l++;const c=[];let h=[];e.transferAttributes&&(h=n.attribNamesMatchingMask(e.attributesToTransfer));const u=new Map,d=new Map;for(let t of h)u.set(t,[]),d.set(t,n.attribSize(t));const p=new MX,_=2454*e.seed%Number.MAX_SAFE_INTEGER;await p.startWithCount(e.pointsCount,(t=>{const e=or.randFloat(_+t)*r;for(let t=0;te/(t-1)));e.addIdnAttribute&&g.setAttribute(\\\\\\\"idn\\\\\\\",new C.a(new Float32Array(i),1))}const v=this.createObject(g,Ns.POINTS);return this.createCoreGroupFromObjects([v])}}d2.DEFAULT_PARAMS={pointsCount:100,seed:0,transferAttributes:!0,attributesToTransfer:\\\\\\\"normal\\\\\\\",addIdAttribute:!0,addIdnAttribute:!0},d2.INPUT_CLONED_STATE=Ki.FROM_NODE;const p2=d2.DEFAULT_PARAMS;const _2=new class extends ua{constructor(){super(...arguments),this.pointsCount=ha.INTEGER(p2.pointsCount,{range:[0,100],rangeLocked:[!0,!1]}),this.seed=ha.INTEGER(p2.seed,{range:[0,100],rangeLocked:[!1,!1]}),this.transferAttributes=ha.BOOLEAN(p2.transferAttributes),this.attributesToTransfer=ha.STRING(p2.attributesToTransfer,{visibleIf:{transferAttributes:1}}),this.addIdAttribute=ha.BOOLEAN(p2.addIdAttribute),this.addIdnAttribute=ha.BOOLEAN(p2.addIdnAttribute)}};class m2 extends lV{constructor(){super(...arguments),this.paramsConfig=_2}static type(){return\\\\\\\"scatter\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to scatter points onto\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(Ki.NEVER)}async cook(t){this._operation=this._operation||new d2(this.scene(),this.states);const e=await this._operation.cook(t,this.pv);this.setCoreGroup(e)}}var f2;!function(t){t.MATRIX=\\\\\\\"matrix\\\\\\\",t.AXIS=\\\\\\\"axis\\\\\\\"}(f2||(f2={}));const g2=[f2.MATRIX,f2.AXIS];var v2;!function(t){t.BBOX_CENTER=\\\\\\\"bbox center\\\\\\\",t.BBOX_CENTER_OFFSET=\\\\\\\"bbox center offset\\\\\\\",t.CUSTOM=\\\\\\\"custom\\\\\\\"}(v2||(v2={}));const y2=[v2.BBOX_CENTER,v2.BBOX_CENTER_OFFSET,v2.CUSTOM];class x2 extends sV{constructor(){super(...arguments),this._m4=new A.a,this._axisNormalized=new p.a,this._center=new p.a,this._pointPos=new p.a,this._axisPlane=new Y.a,this._pointOnPlane=new p.a,this._delta=new p.a,this._deltaNormalized=new p.a,this._offset=new p.a}static type(){return\\\\\\\"shear\\\\\\\"}cook(t,e){const n=t[0].objects();return this._applyShear(n,e),t[0]}_applyShear(t,e){const n=g2[e.mode];switch(n){case f2.MATRIX:return this._applyMatrixShear(t,e);case f2.AXIS:return this._applyAxisShear(t,e)}os.unreachable(n)}_applyMatrixShear(t,e){this._m4.makeShear(e.xy,e.xz,e.yx,e.yz,e.zx,e.zy);for(let e of t){const t=e.geometry;t&&t.applyMatrix4(this._m4)}}_applyAxisShear(t,e){this._axisNormalized.copy(e.axis),this._axisNormalized.normalize();for(let n of t){const t=n.geometry;if(t){this._getAxisModeCenter(t,e),this._axisPlane.setFromNormalAndCoplanarPoint(e.planeAxis,this._center);const n=new fr(t).points();for(let t of n){t.getPosition(this._pointPos),this._axisPlane.projectPoint(this._pointPos,this._pointOnPlane),this._delta.copy(this._pointOnPlane).sub(this._pointPos);const n=this._delta.length();this._deltaNormalized.copy(this._delta).normalize(),this._offset.copy(this._axisNormalized).multiplyScalar(e.axisAmount*n),this._delta.dot(e.planeAxis)>0&&this._offset.multiplyScalar(-1),this._pointPos.add(this._offset),t.setPosition(this._pointPos)}}}}_getAxisModeCenter(t,e){const n=y2[e.centerMode];switch(n){case v2.BBOX_CENTER:return this._getAxisModeCenterBbox(t,e);case v2.BBOX_CENTER_OFFSET:return this._getAxisModeCenterBboxOffset(t,e);case v2.CUSTOM:return this._getAxisModeCenterCustom(e)}os.unreachable(n)}_getAxisModeCenterBbox(t,e){t.computeBoundingBox();const n=t.boundingBox;n?n.getCenter(this._center):this._center.set(0,0,0)}_getAxisModeCenterBboxOffset(t,e){this._getAxisModeCenterBbox(t,e),this._center.add(e.centerOffset)}_getAxisModeCenterCustom(t){return this._center.copy(t.center)}}var b2;x2.DEFAULT_PARAMS={mode:g2.indexOf(f2.AXIS),xy:0,xz:0,yx:0,yz:0,zx:0,zy:0,centerMode:y2.indexOf(v2.BBOX_CENTER),centerOffset:new p.a(0,0,0),center:new p.a(0,0,0),planeAxis:new p.a(0,0,1),axis:new p.a(0,1,0),axisAmount:0},x2.INPUT_CLONED_STATE=Ki.FROM_NODE,function(t){t.SHEAR=\\\\\\\"shear\\\\\\\",t.TRANSFORM=\\\\\\\"transform\\\\\\\",t.UV_LAYOUT=\\\\\\\"uvLayout\\\\\\\",t.UV_TRANSFORM=\\\\\\\"uvTransform\\\\\\\",t.UV_UNWRAP=\\\\\\\"uvUnwrap\\\\\\\"}(b2||(b2={}));const w2=x2.DEFAULT_PARAMS;const T2=new class extends ua{constructor(){super(...arguments),this.mode=ha.INTEGER(w2.mode,{menu:{entries:g2.map(((t,e)=>({name:t,value:e})))}}),this.xy=ha.FLOAT(w2.xy,{visibleIf:{mode:g2.indexOf(f2.MATRIX)}}),this.xz=ha.FLOAT(w2.xz,{visibleIf:{mode:g2.indexOf(f2.MATRIX)}}),this.yx=ha.FLOAT(w2.yx,{visibleIf:{mode:g2.indexOf(f2.MATRIX)}}),this.yz=ha.FLOAT(w2.yz,{visibleIf:{mode:g2.indexOf(f2.MATRIX)}}),this.zx=ha.FLOAT(w2.zx,{visibleIf:{mode:g2.indexOf(f2.MATRIX)}}),this.zy=ha.FLOAT(w2.zy,{visibleIf:{mode:g2.indexOf(f2.MATRIX)}}),this.centerMode=ha.INTEGER(w2.centerMode,{visibleIf:{mode:g2.indexOf(f2.AXIS)},menu:{entries:y2.map(((t,e)=>({name:t,value:e})))}}),this.centerOffset=ha.VECTOR3(w2.centerOffset.toArray(),{visibleIf:{mode:g2.indexOf(f2.AXIS),centerMode:y2.indexOf(v2.BBOX_CENTER_OFFSET)}}),this.center=ha.VECTOR3(w2.center.toArray(),{visibleIf:{mode:g2.indexOf(f2.AXIS),centerMode:y2.indexOf(v2.CUSTOM)}}),this.planeAxis=ha.VECTOR3(w2.planeAxis.toArray(),{visibleIf:{mode:g2.indexOf(f2.AXIS)}}),this.axis=ha.VECTOR3(w2.axis.toArray(),{visibleIf:{mode:g2.indexOf(f2.AXIS)}}),this.axisAmount=ha.FLOAT(w2.axisAmount,{range:[-1,1],visibleIf:{mode:g2.indexOf(f2.AXIS)}})}};class A2 extends lV{constructor(){super(...arguments),this.paramsConfig=T2}static type(){return b2.SHEAR}static displayedInputNames(){return[\\\\\\\"geometries or objects to transform\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(x2.INPUT_CLONED_STATE)}setMode(t){this.p.mode.set(g2.indexOf(t))}cook(t){this._operation=this._operation||new x2(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const M2=new class extends ua{};class E2 extends lV{constructor(){super(...arguments),this.paramsConfig=M2}static type(){return\\\\\\\"skin\\\\\\\"}static displayedInputNames(){return[\\\\\\\"lines to create polygons from\\\\\\\",\\\\\\\"if used, lines from both inputs will be used\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1,2)}cook(t){switch(f.compact(this.io.inputs.inputs()).length){case 1:return this.process_one_input(t);case 2:return this.process_two_inputs(t);default:return this.states.error.set(\\\\\\\"inputs count not valid\\\\\\\")}}process_one_input(t){const e=t[0],n=this._get_line_segments(e),i=[];if(n){const t=n[0];if(t){const e=O1.line_segment_to_geometries(t.geometry);e.forEach(((t,n)=>{if(n>0){const s=e[n-1],r=this._skin(s,t);i.push(r)}}))}}this.setGeometries(i)}process_two_inputs(t){const e=t[0],n=t[1],i=this._get_line_segments(e),s=this._get_line_segments(n),r=f.sortBy([i,s],(t=>-t.length)),o=r[0],a=r[1],l=[];o.forEach(((t,e)=>{const n=a[e];if(null!=t&&null!=n){const e=t.geometry,i=n.geometry,s=this._skin(e,i);l.push(s)}})),this.setGeometries(l)}_get_line_segments(t){return t.objects().filter((t=>t.isLineSegments))}_skin(t,e){const n=new S.a;return new P1(n,t,e).process(),n}}var S2;!function(t){t.X=\\\\\\\"x\\\\\\\",t.Y=\\\\\\\"y\\\\\\\",t.Z=\\\\\\\"z\\\\\\\"}(S2||(S2={}));const C2=[S2.X,S2.Y,S2.Z];class N2 extends sV{constructor(){super(...arguments),this._pointPos=new p.a,this._positions=[],this._indicesByPos=new Map,this._indexDest=new Map,this._debugActive=!1}static type(){return\\\\\\\"sort\\\\\\\"}cook(t,e){const n=t[0],i=n.objectsWithGeo();for(let t of i)this._sortObject(t,e);return n}_debug(t){this._debugActive}_sortObject(t,e){const n=new br(t,0).points(),i=t.geometry.getIndex();if(!i)return void console.warn(\\\\\\\"geometry cannot be sorted since it has no index\\\\\\\");const s=i.array;this._positions=new Array(n.length),this._indicesByPos.clear(),this._indexDest.clear();const r=C2[e.axis];let o=0,a=0;for(let t of n){switch(t.getPosition(this._pointPos),r){case S2.X:o=this._pointPos.x;break;case S2.Y:o=this._pointPos.y;break;case S2.Z:o=this._pointPos.z}this._positions[a]=o,h.pushOnArrayAtEntry(this._indicesByPos,o,t.index()),a++}let l=this._positions.sort(((t,e)=>t-e));e.invert&&l.reverse();const c=new Array(n.length);a=0;const u=f.uniq(l);for(let t of u){const e=this._indicesByPos.get(t);if(e)for(let t of e)c[a]=t,this._indexDest.set(t,a),a++}const d=new Array(s.length);for(let t=0;t ${e}`),null!=e)for(let n=0;n({name:t,value:e})))}}),this.invert=ha.BOOLEAN(L2.invert)}};class P2 extends lV{constructor(){super(...arguments),this.paramsConfig=O2}static type(){return\\\\\\\"sort\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to sort\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState([Ki.FROM_NODE])}cook(t){this._operation=this._operation||new N2(this._scene,this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const R2=new class extends ua{constructor(){super(...arguments),this.startFrame=ha.INTEGER(Nl.START_FRAME)}};class I2 extends uV{constructor(){super(...arguments),this.paramsConfig=R2,this._last_simulated_frame=null,this.childrenDisplayController=new pV(this,{dependsOnDisplayNode:!1}),this.displayNodeController=new Fm(this,{onDisplayNodeRemove:()=>{},onDisplayNodeSet:()=>{},onDisplayNodeUpdate:()=>{}},{dependsOnDisplayNode:!1})}static type(){return\\\\\\\"solver\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,4),this.io.inputs.initInputsClonedState(Ki.NEVER),this.addGraphInput(this.scene().timeController.graphNode)}previousFrameCoreGroup(){return this._previousFrameCoreGroup}async cook(t){this.pv.startFrame==this.scene().frame()&&this._reset(),this.computeSolverIfRequired()}_reset(){this._previousFrameCoreGroup=void 0,this._last_simulated_frame=null}computeSolverIfRequired(){const t=this.scene().frame(),e=this.pv.startFrame;t>=e&&(null==this._last_simulated_frame&&(this._last_simulated_frame=e-1),t>this._last_simulated_frame&&this._computeSolverMultipleTimes(t-this._last_simulated_frame))}_computeSolverMultipleTimes(t=1){for(let e=0;e({name:t,value:z2[t]})))}}),this.radius=ha.FLOAT(G2.radius,{visibleIf:{type:z2.default}}),this.resolution=ha.VECTOR2(G2.resolution,{visibleIf:{type:z2.default}}),this.open=ha.BOOLEAN(G2.open,{visibleIf:{type:z2.default}}),this.phiStart=ha.FLOAT(G2.phiStart,{range:[0,2*Math.PI],visibleIf:{type:z2.default,open:!0}}),this.phiLength=ha.FLOAT(\\\\\\\"$PI*2\\\\\\\",{range:[0,2*Math.PI],visibleIf:{type:z2.default,open:!0}}),this.thetaStart=ha.FLOAT(G2.thetaStart,{range:[0,Math.PI],visibleIf:{type:z2.default,open:!0}}),this.thetaLength=ha.FLOAT(\\\\\\\"$PI\\\\\\\",{range:[0,Math.PI],visibleIf:{type:z2.default,open:!0}}),this.detail=ha.INTEGER(G2.detail,{range:[0,5],rangeLocked:[!0,!1],visibleIf:{type:z2.isocahedron}}),this.center=ha.VECTOR3(G2.center)}};class H2 extends lV{constructor(){super(...arguments),this.paramsConfig=V2}static type(){return\\\\\\\"sphere\\\\\\\"}initializeNode(){this.io.inputs.setCount(0,1),this.io.inputs.initInputsClonedState(U2.INPUT_CLONED_STATE)}cook(t){this._operation=this._operation||new U2(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const j2=new class extends ua{constructor(){super(...arguments),this.attribType=ha.INTEGER(ks.indexOf(zs.NUMERIC),{menu:{entries:Us}}),this.attribName=ha.STRING(\\\\\\\"\\\\\\\")}};class W2 extends lV{constructor(){super(...arguments),this.paramsConfig=j2,this._new_objects=[]}static type(){return\\\\\\\"split\\\\\\\"}static displayedInputNames(){return[\\\\\\\"geometry to split in multiple objects\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1)}async cook(t){const e=t[0];this._new_objects=[],\\\\\\\"\\\\\\\"!=this.pv.attribName&&this._split_core_group(e),this.setObjects(this._new_objects)}async _split_core_group(t){const e=t.coreObjects();for(let t of e)this._split_core_object(t)}_split_core_object(t){let e=t.coreGeometry(),n=this.pv.attribName,i=new Map;if(e){const s=t.object(),r=e.pointsFromGeometry(),o=r[0];if(o){if(o.attribSize(n)!=Gs.FLOAT&&!o.isAttribIndexed(n))return void this.states.error.set(`attrib '${n}' must be a float or a string`);let t;if(o.isAttribIndexed(n))for(let e of r)t=e.indexedAttribValue(n),h.pushOnArrayAtEntry(i,t,e);else for(let e of r)t=e.attribValue(n),h.pushOnArrayAtEntry(i,t,e)}const a=Os(s.constructor);i.forEach(((t,e)=>{const i=fr.geometryFromPoints(t,a);if(i){const t=this.createObject(i,a);br.addAttribute(t,n,e),this._new_objects.push(t)}}))}}}const q2=new A.a,X2=new K.a,Y2=new p.a;class $2 extends J.a{constructor(){super(),this.uuid=On.h(),this.name=\\\\\\\"\\\\\\\",this.type=\\\\\\\"Geometry\\\\\\\",this.vertices=[],this.colors=[],this.faces=[],this.faceVertexUvs=[[]],this.morphTargets=[],this.morphNormals=[],this.skinWeights=[],this.skinIndices=[],this.lineDistances=[],this.boundingBox=null,this.boundingSphere=null,this.elementsNeedUpdate=!1,this.verticesNeedUpdate=!1,this.uvsNeedUpdate=!1,this.normalsNeedUpdate=!1,this.colorsNeedUpdate=!1,this.lineDistancesNeedUpdate=!1,this.groupsNeedUpdate=!1}applyMatrix4(t){const e=(new G.a).getNormalMatrix(t);for(let e=0,n=this.vertices.length;e0)for(let t=0;t0&&(this.normalsNeedUpdate=!0)}computeFlatVertexNormals(){this.computeFaceNormals();for(let t=0,e=this.faces.length;t0&&(this.normalsNeedUpdate=!0)}computeMorphNormals(){for(let t=0,e=this.faces.length;t=0;t--){const e=r[t];this.faces.splice(e,1);for(let t=0,n=this.faceVertexUvs.length;t0,a=e.vertexNormals.length>0,l=1!==e.color.r||1!==e.color.g||1!==e.color.b,p=e.vertexColors.length>0;let _=0;if(_=c(_,0,0),_=c(_,1,i),_=c(_,2,s),_=c(_,3,r),_=c(_,4,o),_=c(_,5,a),_=c(_,6,l),_=c(_,7,p),n.push(_),n.push(e.a,e.b,e.c),n.push(e.materialIndex),r){const e=this.faceVertexUvs[0][t];n.push(d(e[0]),d(e[1]),d(e[2]))}if(o&&n.push(h(e.normal)),a){const t=e.vertexNormals;n.push(h(t[0]),h(t[1]),h(t[2]))}if(l&&n.push(u(e.color)),p){const t=e.vertexColors;n.push(u(t[0]),u(t[1]),u(t[2]))}}function c(t,e,n){return n?t|1<0&&(t.data.colors=r),a.length>0&&(t.data.uvs=[a]),t.data.faces=n,t}clone(){return(new $2).copy(this)}copy(t){this.vertices=[],this.colors=[],this.faces=[],this.faceVertexUvs=[[]],this.morphTargets=[],this.morphNormals=[],this.skinWeights=[],this.skinIndices=[],this.lineDistances=[],this.boundingBox=null,this.boundingSphere=null,this.name=t.name;const e=t.vertices;for(let t=0,n=e.length;t0){const n=new Float32Array(3*t.normals.length);e.setAttribute(\\\\\\\"normal\\\\\\\",new C.a(n,3).copyVector3sArray(t.normals))}if(t.colors.length>0){const n=new Float32Array(3*t.colors.length);e.setAttribute(\\\\\\\"color\\\\\\\",new C.a(n,3).copyColorsArray(t.colors))}if(t.uvs.length>0){const n=new Float32Array(2*t.uvs.length);e.setAttribute(\\\\\\\"uv\\\\\\\",new C.a(n,2).copyVector2sArray(t.uvs))}if(t.uvs2.length>0){const n=new Float32Array(2*t.uvs2.length);e.setAttribute(\\\\\\\"uv2\\\\\\\",new C.a(n,2).copyVector2sArray(t.uvs2))}e.groups=t.groups;for(const n in t.morphTargets){const i=[],s=t.morphTargets[n];for(let t=0,e=s.length;t0){const n=new C.c(4*t.skinIndices.length,4);e.setAttribute(\\\\\\\"skinIndex\\\\\\\",n.copyVector4sArray(t.skinIndices))}if(t.skinWeights.length>0){const n=new C.c(4*t.skinWeights.length,4);e.setAttribute(\\\\\\\"skinWeight\\\\\\\",n.copyVector4sArray(t.skinWeights))}return null!==t.boundingSphere&&(e.boundingSphere=t.boundingSphere.clone()),null!==t.boundingBox&&(e.boundingBox=t.boundingBox.clone()),e}computeTangents(){console.error(\\\\\\\"THREE.Geometry: .computeTangents() has been removed.\\\\\\\")}computeLineDistances(){console.error(\\\\\\\"THREE.Geometry: .computeLineDistances() has been removed. Use THREE.Line.computeLineDistances() instead.\\\\\\\")}applyMatrix(t){return console.warn(\\\\\\\"THREE.Geometry: .applyMatrix() has been renamed to .applyMatrix4().\\\\\\\"),this.applyMatrix4(t)}dispose(){this.dispatchEvent({type:\\\\\\\"dispose\\\\\\\"})}static createBufferGeometryFromObject(t){let e=new S.a;const n=t.geometry;if(t.isPoints||t.isLine){const t=new C.c(3*n.vertices.length,3),i=new C.c(3*n.colors.length,3);if(e.setAttribute(\\\\\\\"position\\\\\\\",t.copyVector3sArray(n.vertices)),e.setAttribute(\\\\\\\"color\\\\\\\",i.copyColorsArray(n.colors)),n.lineDistances&&n.lineDistances.length===n.vertices.length){const t=new C.c(n.lineDistances.length,1);e.setAttribute(\\\\\\\"lineDistance\\\\\\\",t.copyArray(n.lineDistances))}null!==n.boundingSphere&&(e.boundingSphere=n.boundingSphere.clone()),null!==n.boundingBox&&(e.boundingBox=n.boundingBox.clone())}else t.isMesh&&(e=n.toBufferGeometry());return e}}$2.prototype.isGeometry=!0;class J2{constructor(){this.vertices=[],this.normals=[],this.colors=[],this.uvs=[],this.uvs2=[],this.groups=[],this.morphTargets={},this.skinWeights=[],this.skinIndices=[],this.boundingBox=null,this.boundingSphere=null,this.verticesNeedUpdate=!1,this.normalsNeedUpdate=!1,this.colorsNeedUpdate=!1,this.uvsNeedUpdate=!1,this.groupsNeedUpdate=!1}computeGroups(t){const e=[];let n,i,s;const r=t.faces;for(i=0;i0,r=i[1]&&i[1].length>0,o=t.morphTargets,a=o.length;let l;if(a>0){l=[];for(let t=0;t0){u=[];for(let t=0;t0&&0===e.length&&console.error(\\\\\\\"THREE.DirectGeometry: Faceless geometries are not supported.\\\\\\\");for(let t=0;t0;)this.smooth(t);return t.computeFaceNormals(),t.computeVertexNormals(),e?t.toBufferGeometry():t},function(){var t=[\\\\\\\"a\\\\\\\",\\\\\\\"b\\\\\\\",\\\\\\\"c\\\\\\\"];function e(t,e,n){return n[Math.min(t,e)+\\\\\\\"_\\\\\\\"+Math.max(t,e)]}function n(t,e,n,i,s,r){var o,a=Math.min(t,e),l=Math.max(t,e),c=a+\\\\\\\"_\\\\\\\"+l;c in i?o=i[c]:(o={a:n[a],b:n[l],newEdge:null,faces:[]},i[c]=o);o.faces.push(s),r[t].edges.push(o),r[e].edges.push(o)}function i(t,e,n,i,s){t.push(new Z2(e,n,i,void 0,void 0,s))}function s(t,e){return Math.abs(e-t)/2+Math.min(t,e)}function r(t,e,n,i){t.push([e.clone(),n.clone(),i.clone()])}Q2.prototype.smooth=function(o){var a,l,c,h,u,_,m,f,g,v,y,x,b,w=new p.a,T=[];a=o.vertices,l=o.faces;var A,M,E,S,C,N,L,O,P,R,I,F,D,B,z=void 0!==(c=o.faceVertexUvs)[0]&&c[0].length>0;if(z)for(var k=0;k3&&(O=3/(8*_)),P=1-_*O,R=O,_<=2&&2==_&&(P=3/4,R=1/8),B=D.clone().multiplyScalar(P),w.set(0,0,0),k=0;k<_;k++)A=(I=F[k]).a!==D?I.a:I.b,w.add(A);w.multiplyScalar(R),B.add(w),b.push(B)}h=b.concat(x);var U,G,V,H,j,W,q,X=b.length;u=[];var Y=new d.a,$=new d.a,J=new d.a;for(m=0,f=l.length;m{o9.PARAM_CALLBACK_reset(t)}})}};class o9 extends lV{constructor(){super(...arguments),this.paramsConfig=r9}static type(){return ns.INPUT}initializeNode(){this.io.inputs.setCount(0),this.lifecycle.add_on_add_hook((()=>{this.set_parent_input_dependency()}))}async cook(){const t=this.pv.input,e=this.parent();if(e){if(e.io.inputs.has_input(t)){const n=await e.containerController.requestInputContainer(t);if(n){const t=n.coreContent();if(t)return void this.setCoreGroup(t)}}else this.states.error.set(`parent has no input ${t}`);this.cookController.endCook()}else this.states.error.set(\\\\\\\"subnet input has no parent\\\\\\\")}static PARAM_CALLBACK_reset(t){t.set_parent_input_dependency()}set_parent_input_dependency(){this._current_parent_input_graph_node&&this.removeGraphInput(this._current_parent_input_graph_node);const t=this.parent();t&&(this._current_parent_input_graph_node=t.io.inputs.inputGraphNode(this.pv.input),this.addGraphInput(this._current_parent_input_graph_node))}}var a9=n(82);class l9 extends $g{constructor(t,e,n){super(t,e,n)}load(t){return new Promise((async(e,n)=>{const i=new a9.a(this.loadingManager),s=await this._urlToLoad();i.load(s,(i=>{try{const n=this._onLoaded(i,t);e(n)}catch(t){n([])}}))}))}parse(t,e){const n=new a9.a(this.loadingManager).parse(t);return this._onLoaded(n,e)}_onLoaded(t,e){const n=t.paths,i=new Fn.a;for(let t=0;t{const i=await n.load(e);for(let t of i.children)this._ensure_geometry_has_index(t);t(this.createCoreGroupFromObjects(i.children))}))}_ensure_geometry_has_index(t){const e=t.geometry;e&&this.createIndexIfNone(e)}}h9.DEFAULT_PARAMS={url:c9,drawFillShapes:!0,fillShapesWireframe:!1,drawStrokes:!0,strokesWireframe:!1};const u9=h9.DEFAULT_PARAMS;const d9=new class extends ua{constructor(){super(...arguments),this.url=ha.STRING(u9.url,{fileBrowse:{type:[Rr.SVG]}}),this.reload=ha.BUTTON(null,{callback:(t,e)=>{p9.PARAM_CALLBACK_reload(t)}}),this.drawFillShapes=ha.BOOLEAN(u9.drawFillShapes),this.fillShapesWireframe=ha.BOOLEAN(u9.fillShapesWireframe),this.drawStrokes=ha.BOOLEAN(u9.drawStrokes),this.strokesWireframe=ha.BOOLEAN(u9.strokesWireframe)}};class p9 extends lV{constructor(){super(...arguments),this.paramsConfig=d9}static type(){return\\\\\\\"svg\\\\\\\"}async requiredModules(){return[Hn.SVGLoader]}initializeNode(){this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.url],(()=>{const t=this.pv.url;if(t){const e=t.split(\\\\\\\"/\\\\\\\");return e[e.length-1]}return\\\\\\\"\\\\\\\"}))}))}))}async cook(t){this._operation=this._operation||new h9(this.scene(),this.states,this);const e=await this._operation.cook(t,this.pv);this.setCoreGroup(e)}static PARAM_CALLBACK_reload(t){t.param_callback_reload()}param_callback_reload(){this.p.url.setDirty()}}const _9=\\\\\\\"geometry to switch to\\\\\\\";const m9=new class extends ua{constructor(){super(...arguments),this.input=ha.INTEGER(0,{range:[0,3],rangeLocked:[!0,!0]})}};class f9 extends lV{constructor(){super(...arguments),this.paramsConfig=m9}static type(){return\\\\\\\"switch\\\\\\\"}static displayedInputNames(){return[_9,_9,_9,_9]}initializeNode(){this.io.inputs.setCount(0,4),this.io.inputs.initInputsClonedState(Ki.NEVER),this.cookController.disallowInputsEvaluation()}async cook(){const t=this.pv.input;if(this.io.inputs.has_input(t)){const e=await this.containerController.requestInputContainer(t);if(e){const t=e.coreContent();if(t)return void this.setCoreGroup(t)}}else this.states.error.set(`no input ${t}`);this.cookController.endCook()}}class g9 extends IK{constructor(t,e,n){super([1,1,1,-1,-1,1,-1,1,-1,1,-1,-1],[2,1,0,0,3,2,1,3,0,2,3,1],t,e,n),this.type=\\\\\\\"TetrahedronBufferGeometry\\\\\\\",this.parameters={radius:t,detail:e}}}const v9=new class extends ua{constructor(){super(...arguments),this.radius=ha.FLOAT(1),this.detail=ha.INTEGER(0,{range:[0,10],rangeLocked:[!0,!1]}),this.pointsOnly=ha.BOOLEAN(0),this.center=ha.VECTOR3([0,0,0])}};class y9 extends lV{constructor(){super(...arguments),this.paramsConfig=v9}static type(){return\\\\\\\"tetrahedron\\\\\\\"}cook(){const t=this.pv.pointsOnly,e=new g9(this.pv.radius,this.pv.detail,t);if(e.translate(this.pv.center.x,this.pv.center.y,this.pv.center.z),t){const t=this.createObject(e,Ns.POINTS);this.setObject(t)}else e.computeVertexNormals(),this.setGeometry(e)}}class x9 extends fJ{constructor(t,e={}){const n=e.font;if(!n||!n.isFont)return new S.a;const i=n.generateShapes(t,e.size);e.depth=void 0!==e.height?e.height:50,void 0===e.bevelThickness&&(e.bevelThickness=10),void 0===e.bevelSize&&(e.bevelSize=8),void 0===e.bevelEnabled&&(e.bevelEnabled=!1),super(i,e),this.type=\\\\\\\"TextGeometry\\\\\\\"}}var b9=n(48);class w9 extends Vf.a{constructor(t){super(t)}load(t,e,n,i){const s=this,r=new Gf.a(this.manager);r.setPath(this.path),r.setRequestHeader(this.requestHeader),r.setWithCredentials(s.withCredentials),r.load(t,(function(t){let n;try{n=JSON.parse(t)}catch(e){console.warn(\\\\\\\"THREE.FontLoader: typeface.js support is being deprecated. Use typeface.json instead.\\\\\\\"),n=JSON.parse(t.substring(65,t.length-2))}const i=s.parse(n);e&&e(i)}),n,i)}parse(t){return new T9(t)}}class T9{constructor(t){this.type=\\\\\\\"Font\\\\\\\",this.data=t}generateShapes(t,e=100){const n=[],i=function(t,e,n){const i=Array.from(t),s=e/n.resolution,r=(n.boundingBox.yMax-n.boundingBox.yMin+n.underlineThickness)*s,o=[];let a=0,l=0;for(let t=0;t{const i=await this._loadTTFLoader();i&&i.load(t,(t=>{const n=this._font_loader.parse(t);e(n)}),void 0,(()=>{n()}))}))}_loadJSON(t){return new Promise(((e,n)=>{this._font_loader.load(t,(t=>{e(t)}),void 0,(()=>{n()}))}))}async _loadTTFLoader(){const t=await li.modulesRegister.module(Hn.TTFLoader);if(t)return new t(this.loadingManager)}static async loadSVGLoader(){const t=await li.modulesRegister.module(Hn.SVGLoader);if(t)return t}}var E9;!function(t){t.MESH=\\\\\\\"mesh\\\\\\\",t.FLAT=\\\\\\\"flat\\\\\\\",t.LINE=\\\\\\\"line\\\\\\\",t.STROKE=\\\\\\\"stroke\\\\\\\"}(E9||(E9={}));const S9=[E9.MESH,E9.FLAT,E9.LINE,E9.STROKE],C9=\\\\\\\"failed to generate geometry. Try to remove some characters\\\\\\\";const N9=new class extends ua{constructor(){super(...arguments),this.font=ha.STRING(\\\\\\\"https://raw.githubusercontent.com/polygonjs/polygonjs-assets/master/fonts/droid_sans_regular.typeface.json\\\\\\\",{fileBrowse:{type:[Rr.FONT]}}),this.text=ha.STRING(\\\\\\\"polygonjs\\\\\\\",{multiline:!0}),this.type=ha.INTEGER(0,{menu:{entries:S9.map(((t,e)=>({name:t,value:e})))}}),this.size=ha.FLOAT(1,{range:[0,1],rangeLocked:[!0,!1]}),this.extrude=ha.FLOAT(.1,{visibleIf:{type:S9.indexOf(E9.MESH)}}),this.segments=ha.INTEGER(1,{range:[1,20],rangeLocked:[!0,!1],visibleIf:{type:S9.indexOf(E9.MESH)}}),this.strokeWidth=ha.FLOAT(.02,{visibleIf:{type:S9.indexOf(E9.STROKE)}})}};class L9 extends lV{constructor(){super(...arguments),this.paramsConfig=N9,this._loaded_fonts={}}static type(){return\\\\\\\"text\\\\\\\"}initializeNode(){this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.text],(()=>this.p.text.rawInput()))}))}))}async cook(){try{this._loaded_fonts[this.pv.font]=this._loaded_fonts[this.pv.font]||await this._loadFont()}catch(t){return void this.states.error.set(`count not load font (${this.pv.font})`)}const t=this._loaded_fonts[this.pv.font];if(t)switch(S9[this.pv.type]){case E9.MESH:return this._create_geometry_from_type_mesh(t);case E9.FLAT:return this._create_geometry_from_type_flat(t);case E9.LINE:return this._create_geometry_from_type_line(t);case E9.STROKE:return this._create_geometry_from_type_stroke(t);default:console.warn(\\\\\\\"type is not valid\\\\\\\")}}_create_geometry_from_type_mesh(t){const e=this.displayed_text(),n={font:t,size:this.pv.size,height:this.pv.extrude,curveSegments:this.pv.segments};try{const t=new x9(e,n);if(!t.index){const e=t.getAttribute(\\\\\\\"position\\\\\\\").array;t.setIndex(f.range(e.length/3))}this.setGeometry(t)}catch(t){this.states.error.set(C9)}}_create_geometry_from_type_flat(t){const e=this._get_shapes(t);if(e){var n=new bJ(e);this.setGeometry(n)}}_create_geometry_from_type_line(t){const e=this.shapes_from_font(t);if(e){const t=[],n=[];let i=0;for(let s=0;s0&&e0)for(let e=0;e{const n=t.material;n&&(m.isArray(n)||s||(s=n[e.textureName]))}));if(s)for(let t of n.objects())t.traverse((t=>{const n=t.material;if(n&&!m.isArray(n)){n[e.textureName]=s;const t=n.uniforms;if(t){const n=t[e.textureName];n&&(n.value=s)}n.needsUpdate=!0}}));return n}}O9.DEFAULT_PARAMS={textureName:\\\\\\\"map\\\\\\\"},O9.INPUT_CLONED_STATE=[Ki.FROM_NODE,Ki.NEVER];const P9=O9.DEFAULT_PARAMS;const R9=new class extends ua{constructor(){super(...arguments),this.textureName=ha.STRING(P9.textureName)}};class I9 extends lV{constructor(){super(...arguments),this.paramsConfig=R9}static type(){return\\\\\\\"TextureCopy\\\\\\\"}static displayedInputNames(){return[\\\\\\\"objects to copy textures to\\\\\\\",\\\\\\\"objects to copy textures from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(2),this.io.inputs.initInputsClonedState(O9.INPUT_CLONED_STATE)}async cook(t){this._operation=this._operation||new O9(this.scene(),this.states);const e=await this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class F9 extends sV{static type(){return\\\\\\\"textureProperties\\\\\\\"}async cook(t,e){const n=t[0],i=[];for(let t of n.objects())e.applyToChildren?t.traverse((t=>{i.push(t)})):i.push(t);const s=i.map((t=>this._update_object(t,e)));return await Promise.all(s),n}async _update_object(t,e){const n=t.material;n&&await this._update_material(n,e)}async _update_material(t,e){let n=t.map;n&&await this._update_texture(n,e)}async _update_texture(t,e){this._updateEncoding(t,e),this._updateMapping(t,e),this._updateWrap(t,e),await this._updateAnisotropy(t,e),this._updateFilter(t,e)}_updateEncoding(t,e){e.tencoding&&(t.encoding=e.encoding,t.needsUpdate=!0)}_updateMapping(t,e){e.tmapping&&(t.mapping=e.mapping)}_updateWrap(t,e){e.twrap&&(t.wrapS=e.wrapS,t.wrapT=e.wrapT)}async _updateAnisotropy(t,e){if(e.tanisotropy)if(e.useRendererMaxAnisotropy){const e=await li.renderersController.firstRenderer();e&&(t.anisotropy=e.capabilities.getMaxAnisotropy())}else t.anisotropy=e.anisotropy}_updateFilter(t,e){e.tminFilter&&(t.minFilter=e.minFilter),e.tmagFilter&&(t.magFilter=e.magFilter)}}F9.DEFAULT_PARAMS={applyToChildren:!1,tencoding:!1,encoding:w.U,tmapping:!1,mapping:w.Yc,twrap:!1,wrapS:w.wc,wrapT:w.wc,tanisotropy:!1,useRendererMaxAnisotropy:!1,anisotropy:2,tminFilter:!1,minFilter:Qm,tmagFilter:!1,magFilter:Zm},F9.INPUT_CLONED_STATE=Ki.FROM_NODE;const D9=F9.DEFAULT_PARAMS;const B9=new class extends ua{constructor(){super(...arguments),this.applyToChildren=ha.BOOLEAN(D9.applyToChildren,{separatorAfter:!0}),this.tencoding=ha.BOOLEAN(D9.tencoding),this.encoding=ha.INTEGER(D9.encoding,{visibleIf:{tencoding:1},menu:{entries:og.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))}}),this.tmapping=ha.BOOLEAN(D9.tmapping),this.mapping=ha.INTEGER(D9.mapping,{visibleIf:{tmapping:1},menu:{entries:lg.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))}}),this.twrap=ha.BOOLEAN(D9.twrap),this.wrapS=ha.INTEGER(D9.wrapS,{visibleIf:{twrap:1},menu:{entries:ag.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))}}),this.wrapT=ha.INTEGER(D9.wrapT,{visibleIf:{twrap:1},menu:{entries:ag.map((t=>({name:Object.keys(t)[0],value:Object.values(t)[0]})))},separatorAfter:!0}),this.tanisotropy=ha.BOOLEAN(D9.tanisotropy),this.useRendererMaxAnisotropy=ha.BOOLEAN(D9.useRendererMaxAnisotropy,{visibleIf:{tanisotropy:1}}),this.anisotropy=ha.INTEGER(D9.anisotropy,{visibleIf:{tanisotropy:1,useRendererMaxAnisotropy:0},range:[0,32],rangeLocked:[!0,!1]}),this.tminFilter=ha.BOOLEAN(0),this.minFilter=ha.INTEGER(D9.minFilter,{visibleIf:{tminFilter:1},menu:{entries:tf}}),this.tmagFilter=ha.BOOLEAN(0),this.magFilter=ha.INTEGER(D9.magFilter,{visibleIf:{tmagFilter:1},menu:{entries:Km}})}};class z9 extends lV{constructor(){super(...arguments),this.paramsConfig=B9}static type(){return\\\\\\\"textureProperties\\\\\\\"}static displayedInputNames(){return[\\\\\\\"objects with textures to change properties of\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(F9.INPUT_CLONED_STATE)}async cook(t){this._operation=this._operation||new F9(this.scene(),this.states);const e=await this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const k9=new p.a(0,0,1);class U9 extends sV{constructor(){super(...arguments),this._core_transform=new vU}static type(){return\\\\\\\"torus\\\\\\\"}cook(t,e){const n=e.radius,i=e.radiusTube,s=e.segmentsRadial,r=e.segmentsTube,o=new TJ(n,i,s,r);return o.translate(e.center.x,e.center.y,e.center.z),this._core_transform.rotate_geometry(o,k9,e.direction),this.createCoreGroupFromGeometry(o)}}U9.DEFAULT_PARAMS={radius:1,radiusTube:1,segmentsRadial:20,segmentsTube:12,direction:new p.a(0,1,0),center:new p.a(0,0,0)},U9.INPUT_CLONED_STATE=Ki.FROM_NODE;const G9=U9.DEFAULT_PARAMS;const V9=new class extends ua{constructor(){super(...arguments),this.radius=ha.FLOAT(G9.radius,{range:[0,1]}),this.radiusTube=ha.FLOAT(G9.radiusTube,{range:[0,1]}),this.segmentsRadial=ha.INTEGER(G9.segmentsRadial,{range:[1,50],rangeLocked:[!0,!1]}),this.segmentsTube=ha.INTEGER(G9.segmentsTube,{range:[1,50],rangeLocked:[!0,!1]}),this.direction=ha.VECTOR3(G9.direction),this.center=ha.VECTOR3(G9.center)}};class H9 extends lV{constructor(){super(...arguments),this.paramsConfig=V9}static type(){return\\\\\\\"torus\\\\\\\"}cook(t){this._operation=this._operation||new U9(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}class j9 extends sV{static type(){return\\\\\\\"torusKnot\\\\\\\"}cook(t,e){const n=e.radius,i=e.radiusTube,s=e.segmentsRadial,r=e.segmentsTube,o=e.p,a=e.q,l=new AJ(n,i,s,r,o,a);return l.translate(e.center.x,e.center.y,e.center.z),this.createCoreGroupFromGeometry(l)}}j9.DEFAULT_PARAMS={radius:1,radiusTube:1,segmentsRadial:64,segmentsTube:8,p:2,q:3,center:new p.a(0,0,0)},j9.INPUT_CLONED_STATE=Ki.FROM_NODE;const W9=j9.DEFAULT_PARAMS;const q9=new class extends ua{constructor(){super(...arguments),this.radius=ha.FLOAT(W9.radius),this.radiusTube=ha.FLOAT(W9.radiusTube),this.segmentsRadial=ha.INTEGER(W9.segmentsRadial,{range:[1,128]}),this.segmentsTube=ha.INTEGER(W9.segmentsTube,{range:[1,32]}),this.p=ha.INTEGER(W9.p,{range:[1,10]}),this.q=ha.INTEGER(W9.q,{range:[1,10]}),this.center=ha.VECTOR3(W9.center)}};class X9 extends lV{constructor(){super(...arguments),this.paramsConfig=q9}static type(){return\\\\\\\"torusKnot\\\\\\\"}initializeNode(){}cook(t){this._operation=this._operation||new j9(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}var Y9;!function(t){t.SET_PARAMS=\\\\\\\"set params\\\\\\\",t.UPDATE_MATRIX=\\\\\\\"update matrix\\\\\\\"}(Y9||(Y9={}));const $9=[Y9.SET_PARAMS,Y9.UPDATE_MATRIX];class J9 extends sV{constructor(){super(...arguments),this._core_transform=new vU,this._point_pos=new p.a,this._object_scale=new p.a,this._r=new p.a,this._object_position=new p.a}static type(){return\\\\\\\"transform\\\\\\\"}cook(t,e){const n=t[0].objects();return this._apply_transform(n,e),t[0]}_apply_transform(t,e){const n=_U[e.applyOn];switch(n){case uU.GEOMETRIES:return this._update_geometries(t,e);case uU.OBJECTS:return this._update_objects(t,e)}os.unreachable(n)}_update_geometries(t,e){const n=this._matrix(e);if(\\\\\\\"\\\\\\\"===e.group.trim())for(let i of t){const t=i.geometry;t&&(t.translate(-e.pivot.x,-e.pivot.y,-e.pivot.z),t.applyMatrix4(n),t.translate(e.pivot.x,e.pivot.y,e.pivot.z))}else{const i=iV._fromObjects(t).pointsFromGroup(e.group);for(let t of i){const i=t.getPosition(this._point_pos).sub(e.pivot);i.applyMatrix4(n),t.setPosition(i.add(e.pivot))}}}_update_objects(t,e){const n=$9[e.objectMode];switch(n){case Y9.SET_PARAMS:return this._update_objects_params(t,e);case Y9.UPDATE_MATRIX:return this._update_objects_matrix(t,e)}os.unreachable(n)}_update_objects_params(t,e){for(let n of t){n.position.copy(e.t);const t=fU[e.rotationOrder];this._r.copy(e.r).multiplyScalar(On.a),n.rotation.set(this._r.x,this._r.y,this._r.z,t),this._object_scale.copy(e.s).multiplyScalar(e.scale),n.scale.copy(this._object_scale),n.updateMatrix()}}_update_objects_matrix(t,e){const n=this._matrix(e);for(let e of t)this._object_position.copy(e.position),e.position.multiplyScalar(0),e.updateMatrix(),e.applyMatrix4(n),e.position.add(this._object_position),e.updateMatrix()}_matrix(t){return this._core_transform.matrix(t.t,t.r,t.s,t.scale,fU[t.rotationOrder])}}J9.DEFAULT_PARAMS={applyOn:_U.indexOf(uU.GEOMETRIES),objectMode:$9.indexOf(Y9.SET_PARAMS),group:\\\\\\\"\\\\\\\",rotationOrder:fU.indexOf(mU.XYZ),t:new p.a(0,0,0),r:new p.a(0,0,0),s:new p.a(1,1,1),scale:1,pivot:new p.a(0,0,0)},J9.INPUT_CLONED_STATE=Ki.FROM_NODE;const Z9=J9.DEFAULT_PARAMS;const Q9=new class extends ua{constructor(){super(...arguments),this.applyOn=ha.INTEGER(Z9.applyOn,{menu:{entries:_U.map(((t,e)=>({name:t,value:e})))}}),this.objectMode=ha.INTEGER(Z9.objectMode,{visibleIf:{applyOn:_U.indexOf(uU.OBJECTS)},menu:{entries:$9.map(((t,e)=>({name:t,value:e})))}}),this.group=ha.STRING(Z9.group,{visibleIf:{applyOn:_U.indexOf(uU.GEOMETRIES)}}),this.rotationOrder=ha.INTEGER(Z9.rotationOrder,{menu:{entries:fU.map(((t,e)=>({name:t,value:e})))}}),this.t=ha.VECTOR3(Z9.t),this.r=ha.VECTOR3(Z9.r),this.s=ha.VECTOR3(Z9.s),this.scale=ha.FLOAT(Z9.scale,{range:[0,10]}),this.pivot=ha.VECTOR3(Z9.pivot,{visibleIf:{applyOn:_U.indexOf(uU.GEOMETRIES)}})}};class K9 extends lV{constructor(){super(...arguments),this.paramsConfig=Q9}static type(){return b2.TRANSFORM}static displayedInputNames(){return[\\\\\\\"geometries or objects to transform\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1),this.io.inputs.initInputsClonedState(J9.INPUT_CLONED_STATE),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.applyOn],(()=>_U[this.pv.applyOn]))}))}))}setApplyOn(t){this.p.applyOn.set(_U.indexOf(t))}setObjectMode(t){this.p.objectMode.set($9.indexOf(t))}cook(t){this._operation=this._operation||new J9(this.scene(),this.states);const e=this._operation.cook(t,this.pv);this.setCoreGroup(e)}}const t3=new class extends ua{constructor(){super(...arguments),this.useSecondInput=ha.BOOLEAN(1),this.reference=ha.OPERATOR_PATH(\\\\\\\"\\\\\\\",{nodeSelection:{context:ts.SOP},visibleIf:{useSecondInput:0}})}};class e3 extends lV{constructor(){super(...arguments),this.paramsConfig=t3}static type(){return\\\\\\\"transformCopy\\\\\\\"}static displayedInputNames(){return[\\\\\\\"objects to transform\\\\\\\",\\\\\\\"objects to copy transform from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1,2),this.io.inputs.initInputsClonedState([Ki.FROM_NODE,Ki.NEVER])}cook(t){this.pv.useSecondInput&&t[1]?this._copy_from_src_objects(t[0].objects(),t[1].objects()):this._copy_from_found_node(t[0].objects())}_copy_from_src_objects(t,e){let n,i;for(let s=0;s({name:t,value:e})))}};function s3(t){const e=[];for(let n=t+1;n<=6;n++)e.push({count:n});return{visibleIf:e}}const r3=new class extends ua{constructor(){super(...arguments),this.applyOn=ha.INTEGER(_U.indexOf(uU.GEOMETRIES),{menu:{entries:_U.map(((t,e)=>({name:t,value:e})))}}),this.count=ha.INTEGER(2,{range:[0,6],rangeLocked:[!0,!0]}),this.rotationOrder0=ha.INTEGER(n3,{separatorBefore:!0,...i3,...s3(0)}),this.r0=ha.VECTOR3([0,0,0],{...s3(0)}),this.rotationOrder1=ha.INTEGER(n3,{separatorBefore:!0,...i3,...s3(1)}),this.r1=ha.VECTOR3([0,0,0],{...s3(1)}),this.rotationOrder2=ha.INTEGER(n3,{separatorBefore:!0,...i3,...s3(2)}),this.r2=ha.VECTOR3([0,0,0],{...s3(2)}),this.rotationOrder3=ha.INTEGER(n3,{separatorBefore:!0,...i3,...s3(3)}),this.r3=ha.VECTOR3([0,0,0],{...s3(3)}),this.rotationOrder4=ha.INTEGER(n3,{separatorBefore:!0,...i3,...s3(4)}),this.r4=ha.VECTOR3([0,0,0],{...s3(4)}),this.rotationOrder5=ha.INTEGER(n3,{separatorBefore:!0,...i3,...s3(5)}),this.r5=ha.VECTOR3([0,0,0],{...s3(5)})}};class o3 extends lV{constructor(){super(...arguments),this.paramsConfig=r3,this._core_transform=new vU,this._t=new p.a(0,0,0),this._s=new p.a(1,1,1),this._scale=1}static type(){return\\\\\\\"transformMulti\\\\\\\"}static displayedInputNames(){return[\\\\\\\"objects to transform\\\\\\\",\\\\\\\"objects to copy initial transform from\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1,2),this.io.inputs.initInputsClonedState([Ki.FROM_NODE,Ki.NEVER]),this.scene().dispatchController.onAddListener((()=>{this.params.onParamsCreated(\\\\\\\"params_label\\\\\\\",(()=>{this.params.label.init([this.p.applyOn],(()=>_U[this.pv.applyOn]))}))})),this.params.onParamsCreated(\\\\\\\"cache param pairs\\\\\\\",(()=>{this._rot_and_index_pairs=[[this.p.r0,this.p.rotationOrder0],[this.p.r1,this.p.rotationOrder1],[this.p.r2,this.p.rotationOrder2],[this.p.r3,this.p.rotationOrder3],[this.p.r4,this.p.rotationOrder4],[this.p.r5,this.p.rotationOrder5]]}))}cook(t){const e=t[0].objectsWithGeo(),n=t[1]?t[1].objectsWithGeo()[0]:void 0;this._apply_transforms(e,n),this.setObjects(e)}_apply_transforms(t,e){const n=_U[this.pv.applyOn];switch(n){case uU.GEOMETRIES:return this._apply_matrix_to_geometries(t,e);case uU.OBJECTS:return this._apply_matrix_to_objects(t,e)}os.unreachable(n)}_apply_matrix_to_geometries(t,e){if(!this._rot_and_index_pairs)return;if(e){const n=e.geometry;if(n){const e=[Ws.POSITION,Ws.NORMAL,Ws.TANGENT];for(let i of e){const e=n.attributes[i];for(let n of t){const t=n.geometry.attributes[i];e&&t&&Xs.copy(e,t)}}}}let n;for(let e=0;e({name:t,value:e})))}})}};class h3 extends lV{constructor(){super(...arguments),this.paramsConfig=c3,this._bbox_center=new p.a,this._translate_matrix=new A.a}static type(){return\\\\\\\"transformReset\\\\\\\"}static displayedInputNames(){return[\\\\\\\"objects to reset transform\\\\\\\",\\\\\\\"optional reference for center\\\\\\\"]}initializeNode(){this.io.inputs.setCount(1,2),this.io.inputs.initInputsClonedState(Ki.FROM_NODE)}setMode(t){this.p.mode.set(l3.indexOf(t))}cook(t){const e=l3[this.pv.mode];this._select_mode(e,t)}_select_mode(t,e){switch(t){case a3.RESET_OBJECT:return this._reset_objects(e);case a3.CENTER_GEO:return this._center_geos(e,!1);case a3.PROMOTE_GEO_TO_OBJECT:return this._center_geos(e,!0)}os.unreachable(t)}_reset_objects(t){const e=t[0],n=e.objects();for(let t of n)t.matrix.identity(),vU.decompose_matrix(t);this.setCoreGroup(e)}_center_geos(t,e){const n=t[0],i=n.objectsWithGeo();let s=i;const r=t[1];r&&(s=r.objectsWithGeo());for(let t=0;te.h-t.h));const i=[{x:0,y:0,w:Math.max(Math.ceil(Math.sqrt(e/.95)),n),h:1/0}];let s=0,r=0;for(const e of t)for(let t=i.length-1;t>=0;t--){const n=i[t];if(!(e.w>n.w||e.h>n.h)){if(e.x=n.x,e.y=n.y,r=Math.max(r,e.y+e.h),s=Math.max(s,e.x+e.w),e.w===n.w&&e.h===n.h){const e=i.pop();t=this.minAllowedArgumentsCount()&&t<=this.maxAllowedArgumentsCount()}processArguments(t){throw\\\\\\\"Expression.Method._Base.process_arguments virtual method call. Please override\\\\\\\"}async getReferencedNodeContainer(t){const e=this.getReferencedNode(t);if(e){let t;if(t=e.isDirty()?await e.compute():e.containerController.container(),t){if(t.coreContent())return t}throw`referenced node invalid: ${e.path()}`}throw`invalid input (${t})`}getReferencedParam(t,e){const n=this.node();return n?bi.findParam(n,t,e):null}findReferencedGraphNode(t,e){if(!m.isNumber(t)){const n=t;return this.getReferencedNode(n,e)}{const e=t,n=this.node();if(n){return n.io.inputs.inputGraphNode(e)}}return null}getReferencedNode(t,e){let n=null;const i=this.node();if(m.isString(t)){if(i){const s=t;n=bi.findNode(i,s,e)}}else if(i){const e=t;n=i.io.inputs.input(e)}return n||null}findDependency(t){return null}createDependencyFromIndexOrPath(t){const e=new po,n=this.findReferencedGraphNode(t,e);return n?this.createDependency(n,t,e):(li.warn(\\\\\\\"node not found for path\\\\\\\",t),null)}createDependency(t,e,n){return Ur.create(this.param,e,t,n)}}class z3 extends B3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"arguments list\\\\\\\"],[\\\\\\\"number\\\\\\\",\\\\\\\"index\\\\\\\"]]}processArguments(t){return new Promise(((e,n)=>{if(2==t.length){const n=t[0],i=t[1];e(n.split(\\\\\\\" \\\\\\\")[i])}else e(0)}))}}class k3 extends B3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"arguments list\\\\\\\"]]}processArguments(t){return new Promise(((e,n)=>{if(1==t.length){e(t[0].split(\\\\\\\" \\\\\\\").length)}else e(0)}))}}const U3=[\\\\\\\"min\\\\\\\",\\\\\\\"max\\\\\\\",\\\\\\\"size\\\\\\\",\\\\\\\"center\\\\\\\"],G3=[\\\\\\\"x\\\\\\\",\\\\\\\"y\\\\\\\",\\\\\\\"z\\\\\\\"];class V3 extends B3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"],[\\\\\\\"string\\\\\\\",\\\\\\\"vector name, min, max, size or center\\\\\\\"],[\\\\\\\"string\\\\\\\",\\\\\\\"component_name, x,y or z\\\\\\\"]]}findDependency(t){return this.createDependencyFromIndexOrPath(t)}processArguments(t){let e=0;return new Promise((async(n,i)=>{if(t.length>=1){const s=t[0],r=t[1],o=t[2];let a=null;try{a=await this.getReferencedNodeContainer(s)}catch(t){i(t)}a&&(e=this._get_value_from_container(a,r,o),n(e))}else n(0)}))}_get_value_from_container(t,e,n){const i=t.boundingBox();if(!e)return i;if(U3.indexOf(e)>=0){let t=new p.a;switch(e){case\\\\\\\"size\\\\\\\":i.getSize(t);break;case\\\\\\\"center\\\\\\\":i.getCenter(t);break;default:t=i[e]}return n?G3.indexOf(n)>=0?t[n]:-1:t}return-1}}class H3 extends B3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"],[\\\\\\\"string\\\\\\\",\\\\\\\"component_name, x,y or z\\\\\\\"]]}findDependency(t){return this.createDependencyFromIndexOrPath(t)}processArguments(t){return new Promise((async(e,n)=>{if(t.length>=1){const i=t[0],s=t[1];let r=null;try{r=await this.getReferencedNodeContainer(i)}catch(t){n(t)}if(r){const t=r.boundingBox(),n=t.min.clone().add(t.max).multiplyScalar(.5);if(s){const t=n[s];e(null!=t?t:0)}else e(n)}}else e(0)}))}}class j3 extends B3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to param\\\\\\\"]]}findDependency(t){const e=new po,n=this.getReferencedParam(t,e);return n?this.createDependency(n,t,e):null}async processArguments(t){return new Promise((async(e,n)=>{let i=0;if(1==t.length){const s=t[0],r=this.getReferencedParam(s);if(r){r.isDirty()&&await r.compute();const t=r.value;null!=t&&(i=t,e(i))}else n(0)}}))}}class W3 extends B3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to copy\\\\\\\"],[\\\\\\\"integer\\\\\\\",\\\\\\\"default value\\\\\\\"]]}static optionalArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"attribute name (optional)\\\\\\\"]]}findDependency(t){const e=this.findReferencedGraphNode(t);if(e&&\\\\\\\"copy\\\\\\\"==e.type()){const n=e.stamp_node;return this.createDependency(n,t)}return null}processArguments(t){return new Promise(((e,n)=>{if(2==t.length||3==t.length){const n=t[0],i=t[1],s=t[2],r=this.node(),o=r?bi.findNode(r,n):null;let a;o&&o.type()==PZ.type()&&(a=o.stamp_value(s)),null==a&&(a=i),e(a)}else e(0)}))}}class q3 extends B3{constructor(){super(...arguments),this._require_dependency=!0,this._resolution=new d.a}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"],[\\\\\\\"string\\\\\\\",\\\\\\\"component_name: x or y\\\\\\\"]]}findDependency(t){return this.createDependencyFromIndexOrPath(t)}async processArguments(t){if(1==t.length||2==t.length){const e=t[0],n=t[1],i=await this.getReferencedNodeContainer(e);if(i){const t=i.resolution();if(!n)return this._resolution.set(t[0],t[1]),this._resolution;if([0,\\\\\\\"0\\\\\\\",\\\\\\\"x\\\\\\\"].includes(n))return t[0];if([1,\\\\\\\"1\\\\\\\",\\\\\\\"y\\\\\\\"].includes(n))return t[1]}}return-1}}class X3 extends B3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[]}async processArguments(t){return new Promise((async(t,e)=>{t(ng.isMobile())}))}}class Y3 extends B3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[]}async processArguments(t){return new Promise((async(t,e)=>{t(ng.isTouchDevice())}))}}class $3 extends B3{static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"javascript expression\\\\\\\"]]}async processArguments(t){let e=0;if(1==t.length){const n=t[0];if(this._function=this._function||this._create_function(n),this._function)try{e=this._function(this.param.scene(),this.param.node,this.param)}catch(t){console.warn(\\\\\\\"expression error\\\\\\\"),console.warn(t)}}return e}_create_function(t){return new Function(\\\\\\\"scene\\\\\\\",\\\\\\\"node\\\\\\\",\\\\\\\"param\\\\\\\",`return ${t}`)}}class J3 extends B3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"],[\\\\\\\"string\\\\\\\",\\\\\\\"attribute name\\\\\\\"],[\\\\\\\"index\\\\\\\",\\\\\\\"object index\\\\\\\"]]}findDependency(t){return this.createDependencyFromIndexOrPath(t)}processArguments(t){return new Promise((async(e,n)=>{if(3==t.length){const i=t[0],s=t[1],r=t[2];let o=null;try{o=await this.getReferencedNodeContainer(i)}catch(t){n(t)}if(o){e(this._get_value_from_container(o,s,r))}}else console.warn(`${t.length} given when expected 3`),e(0)}))}_get_value_from_container(t,e,n){const i=t.coreContent();if(i){const t=i.coreObjects()[n];return t?t.attribValue(e):0}return null}}class Z3 extends B3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"]]}findDependency(t){return this.createDependencyFromIndexOrPath(t)}processArguments(t){return new Promise((async(e,n)=>{if(1==t.length){const i=t[0];let s;try{s=await this.getReferencedNodeContainer(i)}catch(t){return void n(t)}if(s){e(s.objectsCount())}}else e(0)}))}}class Q3 extends B3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"]]}findDependency(t){const e=this.findReferencedGraphNode(t);if(e){const n=e;if(n.nameController){const e=n.nameController.graph_node;return this.createDependency(e,t)}}return null}processArguments(t){return new Promise(((e,n)=>{if(1==t.length){const n=t[0],i=this.getReferencedNode(n);if(i){const t=i.name();e(ss.tailDigits(t))}else e(0)}else e(0)}))}}class K3 extends B3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"]]}findDependency(t){const e=this.findReferencedGraphNode(t);if(e){const n=e;if(n.nameController){const e=n.nameController.graph_node;return this.createDependency(e,t)}}return null}processArguments(t){return new Promise(((e,n)=>{if(1==t.length){const n=t[0],i=this.getReferencedNode(n);if(i){e(i.name())}else e(0)}else e(0)}))}}class t4 extends B3{static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"number\\\\\\\"]]}processArguments(t){return new Promise((e=>{const n=t[0]||2;e(`${t[1]||0}`.padStart(n,\\\\\\\"0\\\\\\\"))}))}}class e4 extends B3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"],[\\\\\\\"string\\\\\\\",\\\\\\\"attribute name\\\\\\\"],[\\\\\\\"index\\\\\\\",\\\\\\\"point index\\\\\\\"]]}findDependency(t){return this.createDependencyFromIndexOrPath(t)}processArguments(t){return new Promise((async(e,n)=>{if(3==t.length){const i=t[0],s=t[1],r=t[2];let o=null;try{o=await this.getReferencedNodeContainer(i)}catch(t){n(t)}if(o){e(this._get_value_from_container(o,s,r))}}else console.warn(`${t.length} given when expected 3`),e(0)}))}_get_value_from_container(t,e,n){const i=t.coreContent();if(i){const t=i.points()[n];return t?t.attribValue(e):0}return null}}class n4 extends B3{constructor(){super(...arguments),this._require_dependency=!0}static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"path to node\\\\\\\"]]}findDependency(t){return this.createDependencyFromIndexOrPath(t)}processArguments(t){return new Promise((async(e,n)=>{if(1==t.length){const i=t[0];let s;try{s=await this.getReferencedNodeContainer(i)}catch(t){return void n(t)}if(s){e(s.pointsCount())}}else e(0)}))}}class i4 extends B3{static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"string to count characters of\\\\\\\"]]}async processArguments(t){let e=0;if(1==t.length){e=t[0].length}return e}}class s4 extends B3{static requiredArguments(){return[]}async processArguments(t){let e=\\\\\\\"\\\\\\\";for(let n of t)null==n&&(n=\\\\\\\"\\\\\\\"),e+=`${n}`;return e}}class r4 extends B3{static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"string to get index from\\\\\\\"],[\\\\\\\"string\\\\\\\",\\\\\\\"char to find index of\\\\\\\"]]}async processArguments(t){let e=-1;if(2==t.length){const n=t[0],i=t[1];e=n.indexOf(i)}return e}}class o4 extends B3{static requiredArguments(){return[[\\\\\\\"string\\\\\\\",\\\\\\\"string to get range from\\\\\\\"],[\\\\\\\"integer\\\\\\\",\\\\\\\"range start\\\\\\\"],[\\\\\\\"integer\\\\\\\",\\\\\\\"range size\\\\\\\"]]}async processArguments(t){let e=\\\\\\\"\\\\\\\";const n=t[0],i=t[1]||0;let s=t[2]||1;return n&&(e=n.substr(i,s)),e}}class a4 extends B3{constructor(){super(...arguments),this._require_dependency=!0,this._windowSize=new d.a}static requiredArguments(){return[[]]}findDependency(t){return this.param.addGraphInput(this.param.scene().windowController.graphNode()),null}processArguments(t){return new Promise((t=>{this._windowSize.set(window.innerWidth,window.innerHeight),t(this._windowSize)}))}}class l4{constructor(t,e){this._controller=t,this._node=e,this._deleted_params_data=new Map,this._created_spare_param_names=[],this._raw_input_serialized_by_param_name=new Map,this._init_value_serialized_by_param_name=new Map}get assembler(){return this._controller.assembler}createSpareParameters(){var t;const e={},n=this.assembler.param_configs(),i=n.map((t=>t.name())),s=b.clone(i);if(0==this._validateNames(s))return;b.clone(this._created_spare_param_names).concat(s).forEach((t=>{const n=this._node.params.get(t);if(n){this._raw_input_serialized_by_param_name.set(n.name(),n.rawInputSerialized()),this._init_value_serialized_by_param_name.set(n.name(),n.defaultValueSerialized());const t=nV.dispatch_param(n);if(t.required()){const e=t.data();this._deleted_params_data.set(n.name(),e)}}e.namesToDelete=e.namesToDelete||[],e.namesToDelete.push(t)}));for(let t of n)if(s.indexOf(t.name())>=0){const n=b.clone(t.param_options),i={spare:!0,computeOnDirty:!0,cook:!1},s=b.merge(n,i);let r=this._init_value_serialized_by_param_name.get(t.name());null==r&&(r=t.default_value);let o=this._raw_input_serialized_by_param_name.get(t.name());null==o&&(o=t.default_value),e.toAdd=e.toAdd||[],e.toAdd.push({name:t.name(),type:t.type(),init_value:r,raw_input:o,options:s})}this._node.params.updateParams(e),this._created_spare_param_names=(null===(t=e.toAdd)||void 0===t?void 0:t.map((t=>t.name)))||[];for(let t of n){const e=this._node.params.get(t.name());e&&(t.execute_callback(this._node,e),e.type()==Cr.OPERATOR_PATH&&setTimeout((async()=>{e.isDirty()&&await e.compute(),e.options.executeCallback()}),200))}}_validateNames(t){const e=b.clone(this._node.params.non_spare_names),n=f.intersection(t,e);if(n.length>0){const t=`${this._node.path()} attempts to create spare params called '${n.join(\\\\\\\", \\\\\\\")}' with same name as params`;return this._node.states.error.set(t),!1}return!0}}class c4{constructor(t,e){this.node=t,this._globals_handler=new Pf,this._compile_required=!0,this._assembler=new e(this.node),this._spare_params_controller=new l4(this,this.node)}set_assembler_globals_handler(t){(this._globals_handler?this._globals_handler.id():null)!=(t?t.id():null)&&(this._globals_handler=t,this.set_compilation_required_and_dirty(),this._assembler.reset_configs())}get assembler(){return this._assembler}get globals_handler(){return this._globals_handler}add_output_inputs(t){this._assembler.add_output_inputs(t)}add_globals_outputs(t){this._assembler.add_globals_outputs(t)}allow_attribute_exports(){return this._assembler.allow_attribute_exports()}setCompilationRequired(t=!0){this._compile_required=t}set_compilation_required_and_dirty(t){this.setCompilationRequired(),this.node.setDirty(t)}compileRequired(){return this._compile_required}post_compile(){this.createSpareParameters(),this.setCompilationRequired(!1)}createSpareParameters(){this._spare_params_controller.createSpareParameters()}addFilterFragmentShaderCallback(t,e){this.assembler._addFilterFragmentShaderCallback(t,e),this.setCompilationRequired()}removeFilterFragmentShaderCallback(t){this.assembler._removeFilterFragmentShaderCallback(t),this.setCompilationRequired()}}var h4;!function(t){t.FUNCTION_DECLARATION=\\\\\\\"function_declaration\\\\\\\",t.DEFINE=\\\\\\\"define\\\\\\\",t.BODY=\\\\\\\"body\\\\\\\"}(h4||(h4={}));class u4{constructor(t,e,n){this._name=t,this._input_names=e,this._dependencies=n}name(){return this._name}input_names(){return this._input_names}dependencies(){return this._dependencies}}class d4{constructor(t,e={}){this._name=t,this._options=e}name(){return this._name}default_from_attribute(){return this._options.default_from_attribute||!1}default(){return this._options.default}if_condition(){return this._options.if}prefix(){return this._options.prefix||\\\\\\\"\\\\\\\"}suffix(){return this._options.suffix||\\\\\\\"\\\\\\\"}postLines(){return this._options.postLines}}class p4{constructor(t){this._shader_name=t,this._definitions_by_node_id=new Map,this._body_lines_by_node_id=new Map}get shader_name(){return this._shader_name}addDefinitions(t,e){for(let n of e)h.pushOnArrayAtEntry(this._definitions_by_node_id,t.graphNodeId(),n)}definitions(t){return this._definitions_by_node_id.get(t.graphNodeId())}addBodyLines(t,e){for(let n of e)h.pushOnArrayAtEntry(this._body_lines_by_node_id,t.graphNodeId(),n)}body_lines(t){return this._body_lines_by_node_id.get(t.graphNodeId())}}class _4{constructor(t,e,n){this._shader_names=t,this._current_shader_name=e,this._assembler=n,this._lines_controller_by_shader_name=new Map;for(let t of this._shader_names)this._lines_controller_by_shader_name.set(t,new p4(t))}assembler(){return this._assembler}shaderNames(){return this._shader_names}set_current_shader_name(t){this._current_shader_name=t}get current_shader_name(){return this._current_shader_name}addDefinitions(t,e,n){if(0==e.length)return;n=n||this._current_shader_name;const i=this._lines_controller_by_shader_name.get(n);i&&i.addDefinitions(t,e)}definitions(t,e){const n=this._lines_controller_by_shader_name.get(t);if(n)return n.definitions(e)}addBodyLines(t,e,n){if(0==e.length)return;n=n||this._current_shader_name;const i=this._lines_controller_by_shader_name.get(n);i&&i.addBodyLines(t,e)}body_lines(t,e){const n=this._lines_controller_by_shader_name.get(t);if(n)return n.body_lines(e)}}const m4={[h4.FUNCTION_DECLARATION]:\\\\\\\"\\\\\\\",[h4.DEFINE]:\\\\\\\";\\\\\\\",[h4.BODY]:\\\\\\\";\\\\\\\"},f4={[h4.FUNCTION_DECLARATION]:\\\\\\\"\\\\\\\",[h4.DEFINE]:\\\\\\\"\\\\\\\",[h4.BODY]:\\\\\\\"\\\\t\\\\\\\"};class g4{static node_comment(t,e){let n=`// ${t.path()}`,i=f4[e];if(e==h4.BODY){let e=this.node_distance_to_material(t);t.type()==ns.OUTPUT&&(e+=1),i=i.repeat(e)}return e==h4.BODY&&(n=`${i}${n}`),n}static line_wrap(t,e,n){let i=!0;0!=e.indexOf(\\\\\\\"#if\\\\\\\")&&0!=e.indexOf(\\\\\\\"#endif\\\\\\\")||(i=!1);let s=f4[n];if(n==h4.BODY&&(s=s.repeat(this.node_distance_to_material(t))),e=`${s}${e}`,i){const t=e[e.length-1],i=m4[n];t!=i&&\\\\\\\"{\\\\\\\"!=t&&\\\\\\\"}\\\\\\\"!=t&&(e+=i)}return e}static post_line_separator(t){return t==h4.BODY?\\\\\\\"\\\\t\\\\\\\":\\\\\\\"\\\\\\\"}static node_distance_to_material(t){const e=t.parent();if(!e)return 0;if(e.context()!=t.context())return 1;{let n=1;return t.type()!=ns.INPUT&&t.type()!=ns.OUTPUT||(n=0),n+this.node_distance_to_material(e)}}}class v4{constructor(t,e,n){this._node_traverser=t,this._root_nodes_for_shader_method=e,this._assembler=n,this._param_configs_controller=new NF,this._param_configs_set_allowed=!0,this._lines=new Map}shaderNames(){return this._node_traverser.shaderNames()}buildFromNodes(t,e){this._node_traverser.traverse(t);const n=new Map;for(let t of this.shaderNames()){const e=this._node_traverser.nodes_for_shader_name(t);n.set(t,e)}const i=this._node_traverser.sorted_nodes();for(let t of this.shaderNames()){const e=this._root_nodes_for_shader_method(t);for(let i of e)h.pushOnArrayAtEntry(n,t,i)}const s=new Map;for(let t of i)s.set(t.graphNodeId(),!0);for(let e of t)s.get(e.graphNodeId())||(i.push(e),s.set(e.graphNodeId(),!0));for(let t of i)t.reset_code();for(let t of e)t.reset_code();this._shaders_collection_controller=new _4(this.shaderNames(),this.shaderNames()[0],this._assembler),this.reset();for(let t of this.shaderNames()){let e=n.get(t)||[];if(e=f.uniq(e),this._shaders_collection_controller.set_current_shader_name(t),e)for(let t of e)t.setLines(this._shaders_collection_controller)}if(this._param_configs_set_allowed){for(let t of e)t.setParamConfigs();this.setParamConfigs(e)}this.set_code_lines(i)}shaders_collection_controller(){return this._shaders_collection_controller}disallow_new_param_configs(){this._param_configs_set_allowed=!1}allow_new_param_configs(){this._param_configs_set_allowed=!0}reset(){for(let t of this.shaderNames()){const e=new Map;this._lines.set(t,e)}}param_configs(){return this._param_configs_controller.list()||[]}lines(t,e){var n;return(null===(n=this._lines.get(t))||void 0===n?void 0:n.get(e))||[]}all_lines(){return this._lines}setParamConfigs(t){this._param_configs_controller.reset();for(let e of t){const t=e.param_configs();if(t)for(let e of t)this._param_configs_controller.push(e)}}set_code_lines(t){for(let e of this.shaderNames())this.add_code_lines(t,e)}add_code_lines(t,e){this.addDefinitions(t,e,Af.FUNCTION,h4.FUNCTION_DECLARATION),this.addDefinitions(t,e,Af.UNIFORM,h4.DEFINE),this.addDefinitions(t,e,Af.VARYING,h4.DEFINE),this.addDefinitions(t,e,Af.ATTRIBUTE,h4.DEFINE),this.add_code_line_for_nodes_and_line_type(t,e,h4.BODY)}addDefinitions(t,e,n,i){if(!this._shaders_collection_controller)return;const s=[];for(let i of t){let t=this._shaders_collection_controller.definitions(e,i);if(t){t=t.filter((t=>t.definition_type==n));for(let e of t)s.push(e)}}if(s.length>0){const t=new Tf(s),n=t.uniq();if(t.errored)throw`code builder error: ${t.error_message}`;const r=new Map,o=new Map;for(let t of n){const e=t.node.graphNodeId();o.has(e)||o.set(e,!0),h.pushOnArrayAtEntry(r,e,t)}const a=this._lines.get(e);o.forEach(((t,e)=>{const n=r.get(e);if(n){const t=n[0];if(t){const e=g4.node_comment(t.node,i);h.pushOnArrayAtEntry(a,i,e);for(let e of n){const n=g4.line_wrap(t.node,e.line,i);h.pushOnArrayAtEntry(a,i,n)}const s=g4.post_line_separator(i);h.pushOnArrayAtEntry(a,i,s)}}}))}}add_code_line_for_nodes_and_line_type(t,e,n){var i=(t=t.filter((t=>{if(this._shaders_collection_controller){const n=this._shaders_collection_controller.body_lines(e,t);return n&&n.length>0}}))).length;for(let s=0;s0){const r=this._lines.get(e),o=g4.node_comment(t,n);if(h.pushOnArrayAtEntry(r,n,o),f.uniq(s).forEach((e=>{e=g4.line_wrap(t,e,n),h.pushOnArrayAtEntry(r,n,e)})),n!=h4.BODY||!i){const t=g4.post_line_separator(n);h.pushOnArrayAtEntry(r,n,t)}}}}class y4{constructor(t,e,n){this._parent_node=t,this._shader_names=e,this._input_names_for_shader_name_method=n,this._leaves_graph_id=new Map,this._graph_ids_by_shader_name=new Map,this._outputs_by_graph_id=new Map,this._depth_by_graph_id=new Map,this._graph_id_by_depth=new Map,this._graph=this._parent_node.scene().graph}reset(){this._leaves_graph_id.clear(),this._graph_ids_by_shader_name.clear(),this._outputs_by_graph_id.clear(),this._depth_by_graph_id.clear(),this._graph_id_by_depth.clear(),this._shader_names.forEach((t=>{this._graph_ids_by_shader_name.set(t,new Map)}))}shaderNames(){return this._shader_names}input_names_for_shader_name(t,e){return this._input_names_for_shader_name_method(t,e)}traverse(t){this.reset();for(let t of this.shaderNames())this._leaves_graph_id.set(t,new Map);for(let e of this.shaderNames()){this._shader_name=e;for(let e of t)this.find_leaves_from_root_node(e),this.set_nodes_depth()}this._depth_by_graph_id.forEach(((t,e)=>{null!=t&&h.pushOnArrayAtEntry(this._graph_id_by_depth,t,e)}))}leaves_from_nodes(t){var e;this._shader_name=Mf.LEAVES_FROM_NODES_SHADER,this._graph_ids_by_shader_name.set(this._shader_name,new Map),this._leaves_graph_id.set(this._shader_name,new Map);for(let e of t)this.find_leaves(e);const n=[];return null===(e=this._leaves_graph_id.get(this._shader_name))||void 0===e||e.forEach(((t,e)=>{n.push(e)})),this._graph.nodesFromIds(n)}nodes_for_shader_name(t){const e=[];this._graph_id_by_depth.forEach(((t,n)=>{e.push(n)})),e.sort(((t,e)=>t-e));const n=[],i=new Map;return e.forEach((e=>{const s=this._graph_id_by_depth.get(e);s&&s.forEach((e=>{var s;if(null===(s=this._graph_ids_by_shader_name.get(t))||void 0===s?void 0:s.get(e)){const s=this._graph.nodeFromId(e);this.add_nodes_with_children(s,i,n,t)}}))})),n}sorted_nodes(){const t=[];this._graph_id_by_depth.forEach(((e,n)=>{t.push(n)})),t.sort(((t,e)=>t-e));const e=[],n=new Map;return t.forEach((t=>{const i=this._graph_id_by_depth.get(t);if(i)for(let t of i){const i=this._graph.nodeFromId(t);i&&this.add_nodes_with_children(i,n,e)}})),e}add_nodes_with_children(t,e,n,i){if(e.get(t.graphNodeId())||(n.push(t),e.set(t.graphNodeId(),!0)),t.type()==ns.INPUT){const s=t.parent();if(s){const r=this.sorted_nodes_for_shader_name_for_parent(s,i);for(let s of r)s.graphNodeId()!=t.graphNodeId()&&this.add_nodes_with_children(s,e,n,i)}}}sorted_nodes_for_shader_name_for_parent(t,e){const n=[];this._graph_id_by_depth.forEach(((t,e)=>{n.push(e)})),n.sort(((t,e)=>t-e));const i=[];n.forEach((n=>{const s=this._graph_id_by_depth.get(n);s&&s.forEach((n=>{var s;if(!e||(null===(s=this._graph_ids_by_shader_name.get(e))||void 0===s?void 0:s.get(n))){const e=this._graph.nodeFromId(n);e.parent()==t&&i.push(e)}}))}));const s=i[0];return t.context()==s.context()&&i.push(t),i}find_leaves_from_root_node(t){var e;null===(e=this._graph_ids_by_shader_name.get(this._shader_name))||void 0===e||e.set(t.graphNodeId(),!0);const n=this.input_names_for_shader_name(t,this._shader_name);if(n)for(let e of n){const n=t.io.inputs.named_input(e);n&&(h.pushOnArrayAtEntry(this._outputs_by_graph_id,n.graphNodeId(),t.graphNodeId()),this.find_leaves(n))}this._outputs_by_graph_id.forEach(((t,e)=>{this._outputs_by_graph_id.set(e,f.uniq(t))}))}find_leaves(t){var e;null===(e=this._graph_ids_by_shader_name.get(this._shader_name))||void 0===e||e.set(t.graphNodeId(),!0);const n=this._find_inputs_or_children(t),i=f.compact(n),s=f.uniq(i.map((t=>t.graphNodeId()))).map((t=>this._graph.nodeFromId(t)));if(s.length>0)for(let e of s)h.pushOnArrayAtEntry(this._outputs_by_graph_id,e.graphNodeId(),t.graphNodeId()),this.find_leaves(e);else this._leaves_graph_id.get(this._shader_name).set(t.graphNodeId(),!0)}_find_inputs_or_children(t){var e,n;if(t.type()==ns.INPUT)return(null===(e=t.parent())||void 0===e?void 0:e.io.inputs.inputs())||[];if(t.childrenAllowed()){return[null===(n=t.childrenController)||void 0===n?void 0:n.output_node()]}return t.io.inputs.inputs()}set_nodes_depth(){this._leaves_graph_id.forEach(((t,e)=>{t.forEach(((t,e)=>{this.set_node_depth(e)}))}))}set_node_depth(t,e=0){const n=this._depth_by_graph_id.get(t);null!=n?this._depth_by_graph_id.set(t,Math.max(n,e)):this._depth_by_graph_id.set(t,e);const i=this._outputs_by_graph_id.get(t);i&&i.forEach((t=>{this.set_node_depth(t,e+1)}))}}const x4=new Map([[Mf.VERTEX,\\\\\\\"#include \\\\\\\"],[Mf.FRAGMENT,\\\\\\\"#include \\\\\\\"]]),b4=new Map([[Mf.VERTEX,\\\\\\\"#include \\\\\\\"],[Mf.FRAGMENT,\\\\\\\"vec4 diffuseColor = vec4( diffuse, opacity );\\\\\\\"]]),w4=new Map([[Mf.VERTEX,[\\\\\\\"#include \\\\\\\",\\\\\\\"#include \\\\\\\"]],[Mf.FRAGMENT,[]]]);class T4 extends class{}{constructor(t){super(),this._gl_parent_node=t,this._shaders_by_name=new Map,this._lines=new Map,this._root_nodes=[],this._leaf_nodes=[],this._uniforms_time_dependent=!1,this._uniforms_resolution_dependent=!1}setGlParentNode(t){this._overriden_gl_parent_node=t}currentGlParentNode(){return this._overriden_gl_parent_node||this._gl_parent_node}compile(){}_template_shader_for_shader_name(t){var e,n;switch(t){case Mf.VERTEX:return null===(e=this.templateShader())||void 0===e?void 0:e.vertexShader;case Mf.FRAGMENT:return null===(n=this.templateShader())||void 0===n?void 0:n.fragmentShader}}get globals_handler(){var t;return null===(t=this.currentGlParentNode().assemblerController)||void 0===t?void 0:t.globals_handler}compileAllowed(){var t;return null!=(null===(t=this.currentGlParentNode().assemblerController)||void 0===t?void 0:t.globals_handler)}shaders_by_name(){return this._shaders_by_name}_build_lines(){for(let t of this.shaderNames()){const e=this._template_shader_for_shader_name(t);e&&this._replace_template(e,t)}}set_root_nodes(t){this._root_nodes=t}templateShader(){}addUniforms(t){for(let e of this.param_configs())t[e.uniform_name]=e.uniform;this.uniformsTimeDependent()&&(t.time={value:this.currentGlParentNode().scene().time()}),this.uniforms_resolution_dependent()&&(t.resolution={value:new d.a(1e3,1e3)})}root_nodes_by_shader_name(t){const e=[];for(let t of this._root_nodes)switch(t.type()){case CF.type():case OF.type():e.push(t);break;case wf.type():case Ff.type():e.push(t)}return e}leaf_nodes_by_shader_name(t){const e=[];for(let t of this._leaf_nodes)switch(t.type()){case OI.type():e.push(t);break;case wf.type():}return e}set_node_lines_globals(t,e){}set_node_lines_output(t,e){}set_node_lines_attribute(t,e){}codeBuilder(){return this._code_builder=this._code_builder||this._create_code_builder()}_resetCodeBuilder(){this._code_builder=void 0}_create_code_builder(){const t=new y4(this.currentGlParentNode(),this.shaderNames(),((t,e)=>this.input_names_for_shader_name(t,e)));return new v4(t,(t=>this.root_nodes_by_shader_name(t)),this)}build_code_from_nodes(t){const e=Df.findParamGeneratingNodes(this.currentGlParentNode());this.codeBuilder().buildFromNodes(t,e)}allow_new_param_configs(){this.codeBuilder().allow_new_param_configs()}disallow_new_param_configs(){this.codeBuilder().disallow_new_param_configs()}builder_param_configs(){return this.codeBuilder().param_configs()}builder_lines(t,e){return this.codeBuilder().lines(t,e)}all_builder_lines(){return this.codeBuilder().all_lines()}param_configs(){return(this._param_config_owner||this.codeBuilder()).param_configs()}set_param_configs_owner(t){this._param_config_owner=t,this._param_config_owner?this.codeBuilder().disallow_new_param_configs():this.codeBuilder().allow_new_param_configs()}static output_input_connection_points(){return[new qo(\\\\\\\"position\\\\\\\",Uo.VEC3),new qo(\\\\\\\"normal\\\\\\\",Uo.VEC3),new qo(\\\\\\\"color\\\\\\\",Uo.VEC3),new qo(\\\\\\\"alpha\\\\\\\",Uo.FLOAT),new qo(\\\\\\\"uv\\\\\\\",Uo.VEC2)]}add_output_inputs(t){t.io.inputs.setNamedInputConnectionPoints(T4.output_input_connection_points())}static create_globals_node_output_connections(){return[new qo(\\\\\\\"position\\\\\\\",Uo.VEC3),new qo(\\\\\\\"normal\\\\\\\",Uo.VEC3),new qo(\\\\\\\"color\\\\\\\",Uo.VEC3),new qo(\\\\\\\"uv\\\\\\\",Uo.VEC2),new qo(\\\\\\\"mvPosition\\\\\\\",Uo.VEC4),new qo(\\\\\\\"worldPosition\\\\\\\",Uo.VEC4),new qo(\\\\\\\"worldNormal\\\\\\\",Uo.VEC3),new qo(\\\\\\\"gl_Position\\\\\\\",Uo.VEC4),new qo(\\\\\\\"gl_FragCoord\\\\\\\",Uo.VEC4),new qo(\\\\\\\"cameraPosition\\\\\\\",Uo.VEC3),new qo(\\\\\\\"resolution\\\\\\\",Uo.VEC2),new qo(\\\\\\\"time\\\\\\\",Uo.FLOAT)]}create_globals_node_output_connections(){return T4.create_globals_node_output_connections()}add_globals_outputs(t){t.io.outputs.setNamedOutputConnectionPoints(this.create_globals_node_output_connections())}allow_attribute_exports(){return!1}reset_configs(){this._reset_shader_configs(),this._reset_variable_configs(),this._resetUniformsTimeDependency(),this._reset_uniforms_resolution_dependency()}shaderConfigs(){return this._shader_configs=this._shader_configs||this.create_shader_configs()}set_shader_configs(t){this._shader_configs=t}shaderNames(){var t;return(null===(t=this.shaderConfigs())||void 0===t?void 0:t.map((t=>t.name())))||[]}_reset_shader_configs(){this._shader_configs=void 0}create_shader_configs(){return[new u4(Mf.VERTEX,[\\\\\\\"position\\\\\\\",\\\\\\\"normal\\\\\\\",\\\\\\\"uv\\\\\\\",Ff.INPUT_NAME],[]),new u4(Mf.FRAGMENT,[\\\\\\\"color\\\\\\\",\\\\\\\"alpha\\\\\\\"],[Mf.VERTEX])]}shader_config(t){var e;return null===(e=this.shaderConfigs())||void 0===e?void 0:e.filter((e=>e.name()==t))[0]}variable_configs(){return this._variable_configs=this._variable_configs||this.create_variable_configs()}set_variable_configs(t){this._variable_configs=t}variable_config(t){return this.variable_configs().filter((e=>e.name()==t))[0]}static create_variable_configs(){return[new d4(\\\\\\\"position\\\\\\\",{default_from_attribute:!0,prefix:\\\\\\\"vec3 transformed = \\\\\\\"}),new d4(\\\\\\\"normal\\\\\\\",{default_from_attribute:!0,prefix:\\\\\\\"vec3 objectNormal = \\\\\\\",postLines:[\\\\\\\"#ifdef USE_TANGENT\\\\\\\",\\\\\\\"\\\\tvec3 objectTangent = vec3( tangent.xyz );\\\\\\\",\\\\\\\"#endif\\\\\\\"]}),new d4(\\\\\\\"color\\\\\\\",{prefix:\\\\\\\"diffuseColor.xyz = \\\\\\\"}),new d4(\\\\\\\"alpha\\\\\\\",{prefix:\\\\\\\"diffuseColor.a = \\\\\\\"}),new d4(\\\\\\\"uv\\\\\\\",{prefix:\\\\\\\"vUv = \\\\\\\",if:Pf.IF_RULE.uv})]}create_variable_configs(){return T4.create_variable_configs()}_reset_variable_configs(){this._variable_configs=void 0,this.variable_configs()}input_names_for_shader_name(t,e){var n;return(null===(n=this.shader_config(e))||void 0===n?void 0:n.input_names())||[]}_resetUniformsTimeDependency(){this._uniforms_time_dependent=!1}setUniformsTimeDependent(){this._uniforms_time_dependent=!0}uniformsTimeDependent(){return this._uniforms_time_dependent}_reset_uniforms_resolution_dependency(){this._uniforms_resolution_dependent=!1}set_uniforms_resolution_dependent(){this._uniforms_resolution_dependent=!0}uniforms_resolution_dependent(){return this._uniforms_resolution_dependent}insert_define_after(t){return x4.get(t)}insert_body_after(t){return b4.get(t)}lines_to_remove(t){return w4.get(t)}_replace_template(t,e){const n=this.builder_lines(e,h4.FUNCTION_DECLARATION),i=this.builder_lines(e,h4.DEFINE),s=this.builder_lines(e,h4.BODY);let r=t.split(\\\\\\\"\\\\n\\\\\\\");const o=[],a=this.insert_define_after(e),l=this.insert_body_after(e),c=this.lines_to_remove(e);let h=!1,u=!1;for(let t of r){1==h&&(n&&this._insert_lines(o,n),i&&this._insert_lines(o,i),h=!1),1==u&&(s&&this._insert_lines(o,s),u=!1);let e=!1;if(c)for(let n of c)t.indexOf(n)>=0&&(e=!0);e?(o.push(\\\\\\\"// removed:\\\\\\\"),o.push(`//${t}`)):o.push(t),a&&t.indexOf(a)>=0&&(h=!0),l&&t.indexOf(l)>=0&&(u=!0)}this._lines.set(e,o)}_insert_lines(t,e){if(e.length>0){for(let e=0;e<3;e++)t.push(\\\\\\\"\\\\\\\");for(let n of e)t.push(n);for(let e=0;e<3;e++)t.push(\\\\\\\"\\\\\\\")}}_addFilterFragmentShaderCallback(t,e){}_removeFilterFragmentShaderCallback(t){}getCustomMaterials(){return new Map}static expandShader(t){return function t(e){return e.replace(/^[ \\\\t]*#include +<([\\\\w\\\\d./]+)>/gm,(function(e,n){var i=U[n];if(void 0===i)throw new Error(\\\\\\\"Can not resolve #include <\\\\\\\"+n+\\\\\\\">\\\\\\\");return t(i)}))}(t)}}var A4,M4;!function(t){t.DISTANCE=\\\\\\\"customDistanceMaterial\\\\\\\",t.DEPTH=\\\\\\\"customDepthMaterial\\\\\\\",t.DEPTH_DOF=\\\\\\\"customDepthDOFMaterial\\\\\\\"}(A4||(A4={})),function(t){t.TIME=\\\\\\\"time\\\\\\\",t.RESOLUTION=\\\\\\\"resolution\\\\\\\",t.MV_POSITION=\\\\\\\"mvPosition\\\\\\\",t.GL_POSITION=\\\\\\\"gl_Position\\\\\\\",t.GL_FRAGCOORD=\\\\\\\"gl_FragCoord\\\\\\\",t.GL_POINTCOORD=\\\\\\\"gl_PointCoord\\\\\\\"}(M4||(M4={}));const E4=[M4.GL_FRAGCOORD,M4.GL_POINTCOORD];class S4 extends T4{constructor(){super(...arguments),this._assemblers_by_custom_name=new Map,this._filterFragmentShaderCallbacks=new Map}createMaterial(){return new F}custom_assembler_class_by_custom_name(){}_addCustomMaterials(t){const e=this.custom_assembler_class_by_custom_name();e&&e.forEach(((e,n)=>{this._add_custom_material(t,n,e)}))}_add_custom_material(t,e,n){let i=this._assemblers_by_custom_name.get(e);i||(i=new n(this.currentGlParentNode()),this._assemblers_by_custom_name.set(e,i)),t.customMaterials=t.customMaterials||{};const s=i.createMaterial();s.name=e,t.customMaterials[e]=s}compileCustomMaterials(t){const e=this.custom_assembler_class_by_custom_name();e&&e.forEach(((e,n)=>{if(this._code_builder){let i=this._assemblers_by_custom_name.get(n);i||(i=new e(this.currentGlParentNode()),this._assemblers_by_custom_name.set(n,i)),i.set_root_nodes(this._root_nodes),i.set_param_configs_owner(this._code_builder),i.set_shader_configs(this.shaderConfigs()),i.set_variable_configs(this.variable_configs());const s=t.customMaterials[n];s&&(i.setFilterFragmentShaderMethodOwner(this),i.compileMaterial(s),i.setFilterFragmentShaderMethodOwner(void 0))}}))}_resetFilterFragmentShaderCallbacks(){this._filterFragmentShaderCallbacks.clear()}_addFilterFragmentShaderCallback(t,e){this._filterFragmentShaderCallbacks.set(t,e)}_removeFilterFragmentShaderCallback(t){this._filterFragmentShaderCallbacks.delete(t)}setFilterFragmentShaderMethodOwner(t){this._filterFragmentShaderMethodOwner=t}filterFragmentShader(t){return this._filterFragmentShaderCallbacks.forEach(((e,n)=>{t=e(t)})),t}processFilterFragmentShader(t){return this._filterFragmentShaderMethodOwner?this._filterFragmentShaderMethodOwner.filterFragmentShader(t):this.filterFragmentShader(t)}compileMaterial(t){if(!this.compileAllowed())return;const e=Df.findOutputNodes(this.currentGlParentNode());e.length>1&&this.currentGlParentNode().states.error.set(\\\\\\\"only one output node allowed\\\\\\\");const n=Df.findVaryingNodes(this.currentGlParentNode()),i=e.concat(n);this.set_root_nodes(i),this._update_shaders();const s=this._shaders_by_name.get(Mf.VERTEX),r=this._shaders_by_name.get(Mf.FRAGMENT);s&&r&&(t.vertexShader=s,t.fragmentShader=this.processFilterFragmentShader(r),this.addUniforms(t.uniforms),t.needsUpdate=!0);const o=this.currentGlParentNode().scene();this.uniformsTimeDependent()?o.uniformsController.addTimeDependentUniformOwner(t.uuid,t.uniforms):o.uniformsController.removeTimeDependentUniformOwner(t.uuid),this.uniforms_resolution_dependent()?o.uniformsController.addResolutionDependentUniformOwner(t.uuid,t.uniforms):o.uniformsController.removeResolutionDependentUniformOwner(t.uuid),t.customMaterials&&this.compileCustomMaterials(t)}_update_shaders(){this._shaders_by_name=new Map,this._lines=new Map;for(let t of this.shaderNames()){const e=this._template_shader_for_shader_name(t);e&&this._lines.set(t,e.split(\\\\\\\"\\\\n\\\\\\\"))}this._root_nodes.length>0&&(this.build_code_from_nodes(this._root_nodes),this._build_lines());for(let t of this.shaderNames()){const e=this._lines.get(t);e&&this._shaders_by_name.set(t,e.join(\\\\\\\"\\\\n\\\\\\\"))}}shadow_assembler_class_by_custom_name(){return{}}add_output_body_line(t,e,n){var i;const s=t.io.inputs.named_input(n),r=t.variableForInput(n),o=this.variable_config(n);let a=null;if(s)a=mf.vector3(r);else if(o.default_from_attribute()){const s=t.io.inputs.namedInputConnectionPointsByName(n);if(s){const r=s.type(),o=null===(i=this.globals_handler)||void 0===i?void 0:i.read_attribute(t,r,n,e);o&&(a=o)}}else{const t=o.default();t&&(a=t)}if(a){const n=o.prefix(),i=o.suffix(),s=o.if_condition();s&&e.addBodyLines(t,[`#if ${s}`]),e.addBodyLines(t,[`${n}${a}${i}`]);const r=o.postLines();r&&e.addBodyLines(t,r),s&&e.addBodyLines(t,[\\\\\\\"#endif\\\\\\\"])}}set_node_lines_output(t,e){var n;const i=e.current_shader_name,s=null===(n=this.shader_config(i))||void 0===n?void 0:n.input_names();if(s)for(let n of s)t.io.inputs.has_named_input(n)&&this.add_output_body_line(t,e,n)}set_node_lines_attribute(t,e){var n;const i=t.gl_type(),s=null===(n=this.globals_handler)||void 0===n?void 0:n.read_attribute(t,i,t.attribute_name,e),r=t.glVarName(t.output_name);e.addBodyLines(t,[`${i} ${r} = ${s}`])}handle_globals_output_name(t){var e;switch(t.output_name){case M4.TIME:return void this.handleTime(t);case M4.RESOLUTION:return void this.handle_resolution(t);case M4.MV_POSITION:return void this.handle_mvPosition(t);case M4.GL_POSITION:return void this.handle_gl_Position(t);case M4.GL_FRAGCOORD:return void this.handle_gl_FragCoord(t);case M4.GL_POINTCOORD:return void this.handle_gl_PointCoord(t);default:null===(e=this.globals_handler)||void 0===e||e.handle_globals_node(t.globals_node,t.output_name,t.shaders_collection_controller)}}handleTime(t){const e=new Nf(t.globals_node,Uo.FLOAT,t.output_name);t.globals_shader_name&&h.pushOnArrayAtEntry(t.definitions_by_shader_name,t.globals_shader_name,e);const n=`float ${t.var_name} = ${t.output_name}`;for(let i of t.dependencies)h.pushOnArrayAtEntry(t.definitions_by_shader_name,i,e),h.pushOnArrayAtEntry(t.body_lines_by_shader_name,i,n);t.body_lines.push(n),this.setUniformsTimeDependent()}handle_resolution(t){t.body_lines.push(`vec2 ${t.var_name} = resolution`);const e=new Nf(t.globals_node,Uo.VEC2,t.output_name);t.globals_shader_name&&h.pushOnArrayAtEntry(t.definitions_by_shader_name,t.globals_shader_name,e);for(let n of t.dependencies)h.pushOnArrayAtEntry(t.definitions_by_shader_name,n,e);this.set_uniforms_resolution_dependent()}handle_mvPosition(t){if(t.shader_name==Mf.FRAGMENT){const e=t.globals_node,n=t.shaders_collection_controller,i=new Lf(e,Uo.VEC4,t.var_name),s=`${t.var_name} = modelViewMatrix * vec4(position, 1.0)`;n.addDefinitions(e,[i],Mf.VERTEX),n.addBodyLines(e,[s],Mf.VERTEX),n.addDefinitions(e,[i])}}handle_gl_Position(t){if(t.shader_name==Mf.FRAGMENT){const e=t.globals_node,n=t.shaders_collection_controller,i=new Lf(e,Uo.VEC4,t.var_name),s=`${t.var_name} = projectionMatrix * modelViewMatrix * vec4(position, 1.0)`;n.addDefinitions(e,[i],Mf.VERTEX),n.addBodyLines(e,[s],Mf.VERTEX),n.addDefinitions(e,[i])}}handle_gl_FragCoord(t){t.shader_name==Mf.FRAGMENT&&t.body_lines.push(`vec4 ${t.var_name} = gl_FragCoord`)}handle_gl_PointCoord(t){t.shader_name==Mf.FRAGMENT?t.body_lines.push(`vec2 ${t.var_name} = gl_PointCoord`):t.body_lines.push(`vec2 ${t.var_name} = vec2(0.0, 0.0)`)}set_node_lines_globals(t,e){const n=[],i=e.current_shader_name,s=this.shader_config(i);if(!s)return;const r=s.dependencies(),o=new Map,a=new Map,l=this.used_output_names_for_shader(t,i);for(let s of l){const l=t.glVarName(s),c=e.current_shader_name,h={globals_node:t,shaders_collection_controller:e,output_name:s,globals_shader_name:c,definitions_by_shader_name:o,body_lines:n,var_name:l,shader_name:i,dependencies:r,body_lines_by_shader_name:a};this.handle_globals_output_name(h)}o.forEach(((n,i)=>{e.addDefinitions(t,n,i)})),a.forEach(((n,i)=>{e.addBodyLines(t,n,i)})),e.addBodyLines(t,n)}used_output_names_for_shader(t,e){const n=t.io.outputs.used_output_names(),i=[];for(let t of n)e==Mf.VERTEX&&E4.includes(t)||i.push(t);return i}}const C4=new Map([[Mf.VERTEX,\\\\\\\"#include \\\\\\\"],[Mf.FRAGMENT,\\\\\\\"vec4 diffuseColor = vec4( 1.0 );\\\\\\\"]]);const N4=new Map([[Mf.VERTEX,\\\\\\\"#include \\\\\\\"],[Mf.FRAGMENT,\\\\\\\"vec4 diffuseColor = vec4( 1.0 );\\\\\\\"]]);var L4=\\\\\\\"uniform float mNear;\\\\nuniform float mFar;\\\\n\\\\nvarying float vViewZDepth;\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tfloat color = 1.0 - smoothstep( mNear, mFar, vViewZDepth );\\\\n\\\\tgl_FragColor = vec4( vec3( color ), 1.0 );\\\\n\\\\n}\\\\n\\\\\\\";const O4=new Map([[Mf.VERTEX,\\\\\\\"// INSERT DEFINES\\\\\\\"]]),P4=new Map([[Mf.VERTEX,\\\\\\\"// INSERT BODY\\\\\\\"]]);const R4=new Map([]);R4.set(A4.DISTANCE,class extends S4{templateShader(){const t=H.distanceRGBA;return{vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,uniforms:t.uniforms}}insert_body_after(t){return C4.get(t)}createMaterial(){const t=this.templateShader();return new F({defines:{DEPTH_PACKING:[w.Hb,w.j][0]},uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader})}}),R4.set(A4.DEPTH,class extends S4{templateShader(){const t=H.depth;return{vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,uniforms:t.uniforms}}insert_body_after(t){return N4.get(t)}createMaterial(){const t=this.templateShader();return new F({defines:{DEPTH_PACKING:[w.Hb,w.j][0]},uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader})}}),R4.set(A4.DEPTH_DOF,class extends S4{templateShader(){return{vertexShader:\\\\\\\"#include \\\\n\\\\nvarying float vViewZDepth;\\\\n\\\\n// INSERT DEFINES\\\\n\\\\n\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t// INSERT BODY\\\\n\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvViewZDepth = - mvPosition.z;\\\\n}\\\\\\\",fragmentShader:L4,uniforms:{mNear:{value:0},mFar:{value:10}}}}insert_define_after(t){return O4.get(t)}insert_body_after(t){return P4.get(t)}createMaterial(){const t=this.templateShader();return new F({uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader})}});class I4 extends S4{custom_assembler_class_by_custom_name(){return R4}}class F4 extends I4{templateShader(){const t=H.basic;return{vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,uniforms:t.uniforms}}createMaterial(){const t=this.templateShader(),e=new F({lights:!1,uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader});return this._addCustomMaterials(e),e}}class D4 extends I4{templateShader(){const t=H.lambert;return{vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,uniforms:t.uniforms}}createMaterial(){const t=this.templateShader(),e=new F({lights:!0,uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader});return this._addCustomMaterials(e),e}}class B4 extends I4{templateShader(){const t=H.phong;return{vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,uniforms:t.uniforms}}createMaterial(){const t=this.templateShader(),e=new F({lights:!0,uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader});return this._addCustomMaterials(e),e}}var z4=\\\\\\\"SSSModel(/*isActive*/false,/*color*/vec3(1.0, 1.0, 1.0), /*thickness*/0.1, /*power*/2.0, /*scale*/16.0, /*distortion*/0.1,/*ambient*/0.4,/*attenuation*/0.8 )\\\\\\\";class k4 extends I4{constructor(t){super(t),this._gl_parent_node=t,this._addFilterFragmentShaderCallback(\\\\\\\"MeshStandardBuilderMatNode\\\\\\\",k4.filterFragmentShader)}isPhysical(){return!1}templateShader(){const t=this.isPhysical()?H.physical:H.standard;return{vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,uniforms:t.uniforms}}static filterFragmentShader(t){return t=(t=(t=t.replace(\\\\\\\"#include \\\\\\\",\\\\\\\"float metalnessFactor = metalness * POLY_metalness;\\\\n\\\\n#ifdef USE_METALNESSMAP\\\\n\\\\n\\\\tvec4 texelMetalness = texture2D( metalnessMap, vUv );\\\\n\\\\n\\\\t// reads channel B, compatible with a combined OcclusionRoughnessMetallic (RGB) texture\\\\n\\\\tmetalnessFactor *= texelMetalness.b;\\\\n\\\\n#endif\\\\n\\\\\\\")).replace(\\\\\\\"#include \\\\\\\",\\\\\\\"float roughnessFactor = roughness * POLY_roughness;\\\\n\\\\n#ifdef USE_ROUGHNESSMAP\\\\n\\\\n\\\\tvec4 texelRoughness = texture2D( roughnessMap, vUv );\\\\n\\\\n\\\\t// reads channel G, compatible with a combined OcclusionRoughnessMetallic (RGB) texture\\\\n\\\\troughnessFactor *= texelRoughness.g;\\\\n\\\\n#endif\\\\n\\\\\\\")).replace(\\\\\\\"vec3 totalEmissiveRadiance = emissive;\\\\\\\",\\\\\\\"vec3 totalEmissiveRadiance = emissive * POLY_emissive;\\\\\\\"),k4.USE_SSS&&(t=(t=t.replace(/void main\\\\s?\\\\(\\\\) {/,\\\\\\\"struct SSSModel {\\\\n\\\\tbool isActive;\\\\n\\\\tvec3 color;\\\\n\\\\tfloat thickness;\\\\n\\\\tfloat power;\\\\n\\\\tfloat scale;\\\\n\\\\tfloat distortion;\\\\n\\\\tfloat ambient;\\\\n\\\\tfloat attenuation;\\\\n};\\\\n\\\\nvoid RE_Direct_Scattering(\\\\n\\\\tconst in IncidentLight directLight,\\\\n\\\\tconst in GeometricContext geometry,\\\\n\\\\tconst in SSSModel sssModel,\\\\n\\\\tinout ReflectedLight reflectedLight\\\\n\\\\t){\\\\n\\\\tvec3 scatteringHalf = normalize(directLight.direction + (geometry.normal * sssModel.distortion));\\\\n\\\\tfloat scatteringDot = pow(saturate(dot(geometry.viewDir, -scatteringHalf)), sssModel.power) * sssModel.scale;\\\\n\\\\tvec3 scatteringIllu = (scatteringDot + sssModel.ambient) * (sssModel.color * (1.0-sssModel.thickness));\\\\n\\\\treflectedLight.directDiffuse += scatteringIllu * sssModel.attenuation * directLight.color;\\\\n}\\\\n\\\\nvoid main() {\\\\\\\")).replace(\\\\\\\"#include \\\\\\\",\\\\\\\"#include \\\\nif(POLY_SSSModel.isActive){\\\\n\\\\tRE_Direct_Scattering(directLight, geometry, POLY_SSSModel, reflectedLight);\\\\n}\\\\n\\\\n\\\\\\\")),t}createMaterial(){const t=this.templateShader(),e={lights:!0,extensions:{derivatives:!0},uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader},n=new F(e);return this.isPhysical()&&(n.defines.PHYSICAL=!0),this._addCustomMaterials(n),n}add_output_inputs(t){const e=T4.output_input_connection_points();e.push(new qo(\\\\\\\"metalness\\\\\\\",Uo.FLOAT,1)),e.push(new qo(\\\\\\\"roughness\\\\\\\",Uo.FLOAT,1)),e.push(new qo(\\\\\\\"emissive\\\\\\\",Uo.VEC3,[1,1,1])),k4.USE_SSS&&e.push(new qo(\\\\\\\"SSSModel\\\\\\\",Uo.SSS_MODEL,z4)),this.isPhysical()&&(e.push(new qo(\\\\\\\"transmission\\\\\\\",Uo.FLOAT,1)),e.push(new qo(\\\\\\\"thickness\\\\\\\",Uo.FLOAT,1))),t.io.inputs.setNamedInputConnectionPoints(e)}create_shader_configs(){const t=[\\\\\\\"color\\\\\\\",\\\\\\\"alpha\\\\\\\",\\\\\\\"metalness\\\\\\\",\\\\\\\"roughness\\\\\\\",\\\\\\\"emissive\\\\\\\",\\\\\\\"SSSModel\\\\\\\"];return this.isPhysical()&&(t.push(\\\\\\\"transmission\\\\\\\"),t.push(\\\\\\\"thickness\\\\\\\")),[new u4(Mf.VERTEX,[\\\\\\\"position\\\\\\\",\\\\\\\"normal\\\\\\\",\\\\\\\"uv\\\\\\\"],[]),new u4(Mf.FRAGMENT,t,[Mf.VERTEX])]}create_variable_configs(){const t=T4.create_variable_configs();return t.push(new d4(\\\\\\\"metalness\\\\\\\",{default:\\\\\\\"1.0\\\\\\\",prefix:\\\\\\\"float POLY_metalness = \\\\\\\"})),t.push(new d4(\\\\\\\"roughness\\\\\\\",{default:\\\\\\\"1.0\\\\\\\",prefix:\\\\\\\"float POLY_roughness = \\\\\\\"})),t.push(new d4(\\\\\\\"emissive\\\\\\\",{default:\\\\\\\"vec3(1.0, 1.0, 1.0)\\\\\\\",prefix:\\\\\\\"vec3 POLY_emissive = \\\\\\\"})),k4.USE_SSS&&t.push(new d4(\\\\\\\"SSSModel\\\\\\\",{default:z4,prefix:\\\\\\\"SSSModel POLY_SSSModel = \\\\\\\"})),this.isPhysical()&&(t.push(new d4(\\\\\\\"transmission\\\\\\\",{default:\\\\\\\"1.0\\\\\\\",prefix:\\\\\\\"float POLY_transmission = \\\\\\\"})),t.push(new d4(\\\\\\\"thickness\\\\\\\",{default:\\\\\\\"1.0\\\\\\\",prefix:\\\\\\\"float POLY_thickness = \\\\\\\"}))),t}}k4.USE_SSS=!0;class U4 extends k4{constructor(t){super(t),this._gl_parent_node=t,this._addFilterFragmentShaderCallback(\\\\\\\"MeshPhysicalBuilderMatNode\\\\\\\",U4.filterFragmentShader)}isPhysical(){return!0}static filterFragmentShader(t){return t=t.replace(\\\\\\\"#include \\\\\\\",function(t){const e=t.split(\\\\\\\"\\\\n\\\\\\\");let n=0;for(let t of e)t.includes(\\\\\\\"float transmissionFactor = transmission;\\\\\\\")&&(t=\\\\\\\"float transmissionFactor = transmission * POLY_transmission;\\\\\\\",e[n]=t),t.includes(\\\\\\\"float thicknessFactor = thickness;\\\\\\\")&&(t=\\\\\\\"float thicknessFactor = thickness * POLY_thickness;\\\\\\\",e[n]=t),n++;return e.join(\\\\\\\"\\\\n\\\\\\\")}(k))}}const G4=new Map([[Mf.VERTEX,\\\\\\\"// INSERT DEFINES\\\\\\\"]]),V4=new Map([[Mf.VERTEX,\\\\\\\"// INSERT BODY\\\\\\\"]]);const H4=new Map([[Mf.VERTEX,\\\\\\\"// INSERT DEFINES\\\\\\\"]]),j4=new Map([[Mf.VERTEX,\\\\\\\"// INSERT BODY\\\\\\\"]]);const W4=new Map([[Mf.VERTEX,[\\\\\\\"#include \\\\\\\",\\\\\\\"gl_PointSize = size;\\\\\\\"]],[Mf.FRAGMENT,[]]]),q4=new Map;q4.set(A4.DISTANCE,class extends S4{templateShader(){const t=H.distanceRGBA,e=I.clone(t.uniforms);return e.size={value:1},e.scale={value:1},{vertexShader:\\\\\\\"uniform float size;\\\\nuniform float scale;\\\\n#define DISTANCE\\\\nvarying vec3 vWorldPosition;\\\\n#include \\\\n#include \\\\nvarying float vViewZDepth;\\\\n\\\\n// INSERT DEFINES\\\\n\\\\n\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t// INSERT BODY\\\\n\\\\n\\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\t#include \\\\n\\\\n\\\\t#ifdef USE_SIZEATTENUATION\\\\n\\\\t\\\\tbool isPerspective = ( projectionMatrix[ 2 ][ 3 ] == - 1.0 );\\\\n\\\\t\\\\tif ( isPerspective ) gl_PointSize *= ( scale / - mvPosition.z );\\\\n\\\\t#endif\\\\n\\\\tvWorldPosition = worldPosition.xyz;\\\\n}\\\\n\\\\n// #define DISTANCE\\\\n// varying vec3 vWorldPosition;\\\\n// #include \\\\n// #include \\\\n// #include \\\\n// #include \\\\n// #include \\\\n// #include \\\\n// void main() {\\\\n// \\\\t#include \\\\n// \\\\t#include \\\\n// \\\\t#ifdef USE_DISPLACEMENTMAP\\\\n// \\\\t\\\\t#include \\\\n// \\\\t\\\\t#include \\\\n// \\\\t\\\\t#include \\\\n// \\\\t#endif\\\\n// \\\\t#include \\\\n// \\\\t#include \\\\n// \\\\t#include \\\\n// \\\\t#include \\\\n// \\\\t#include \\\\n// \\\\t#include \\\\n// \\\\t#include \\\\n// \\\\tvWorldPosition = worldPosition.xyz;\\\\n// }\\\\n\\\\n\\\\n\\\\\\\",fragmentShader:t.fragmentShader,uniforms:e}}insert_define_after(t){return G4.get(t)}insert_body_after(t){return V4.get(t)}createMaterial(){const t=this.templateShader();return new F({defines:{USE_SIZEATTENUATION:1,DEPTH_PACKING:[w.Hb,w.j][0]},uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader})}}),q4.set(A4.DEPTH_DOF,class extends S4{templateShader(){return{vertexShader:\\\\\\\"uniform float size;\\\\nuniform float scale;\\\\n#include \\\\n\\\\nvarying float vViewZDepth;\\\\n\\\\n// INSERT DEFINES\\\\n\\\\n\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t// INSERT BODY\\\\n\\\\n\\\\n\\\\t#include \\\\n\\\\n\\\\tvViewZDepth = - mvPosition.z;\\\\n\\\\t#ifdef USE_SIZEATTENUATION\\\\n\\\\t\\\\tbool isPerspective = ( projectionMatrix[ 2 ][ 3 ] == - 1.0 );\\\\n\\\\t\\\\tif ( isPerspective ) gl_PointSize *= ( scale / - mvPosition.z );\\\\n\\\\t#endif\\\\n\\\\n}\\\\n\\\\n\\\\\\\",fragmentShader:L4,uniforms:{size:{value:1},scale:{value:1},mNear:{value:0},mFar:{value:10}}}}insert_define_after(t){return H4.get(t)}insert_body_after(t){return j4.get(t)}createMaterial(){const t=this.templateShader();return new F({depthTest:!0,defines:{USE_SIZEATTENUATION:1},uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader})}});class X4 extends S4{custom_assembler_class_by_custom_name(){return q4}templateShader(){const t=H.points;return{vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,uniforms:t.uniforms}}createMaterial(){const t=this.templateShader(),e=new F({transparent:!0,fog:!0,defines:{USE_SIZEATTENUATION:1},uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader});return this._addCustomMaterials(e),e}add_output_inputs(t){const e=T4.output_input_connection_points();e.push(new qo(\\\\\\\"gl_PointSize\\\\\\\",Uo.FLOAT)),t.io.inputs.setNamedInputConnectionPoints(e)}create_globals_node_output_connections(){return T4.create_globals_node_output_connections().concat([new qo(M4.GL_POINTCOORD,Uo.VEC2)])}create_shader_configs(){return[new u4(Mf.VERTEX,[\\\\\\\"position\\\\\\\",\\\\\\\"normal\\\\\\\",\\\\\\\"uv\\\\\\\",\\\\\\\"gl_PointSize\\\\\\\"],[]),new u4(Mf.FRAGMENT,[\\\\\\\"color\\\\\\\",\\\\\\\"alpha\\\\\\\"],[Mf.VERTEX])]}create_variable_configs(){return T4.create_variable_configs().concat([new d4(\\\\\\\"gl_PointSize\\\\\\\",{default:\\\\\\\"1.0\\\\\\\",prefix:\\\\\\\"gl_PointSize = \\\\\\\",suffix:\\\\\\\" * size * 10.0\\\\\\\"})])}lines_to_remove(t){return W4.get(t)}}const Y4=new Map([[Mf.VERTEX,\\\\\\\"// INSERT DEFINES\\\\\\\"]]),$4=new Map([[Mf.VERTEX,\\\\\\\"// INSERT BODY\\\\\\\"]]);const J4=new Map([]);J4.set(A4.DEPTH_DOF,class extends S4{templateShader(){return{vertexShader:\\\\\\\"uniform float scale;\\\\nattribute float lineDistance;\\\\nvarying float vLineDistance;\\\\n#include \\\\n\\\\nvarying float vViewZDepth;\\\\n\\\\n// INSERT DEFINES\\\\n\\\\n\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\t// INSERT BODY\\\\n\\\\n\\\\n\\\\tvLineDistance = scale * lineDistance;\\\\n\\\\tgl_Position = projectionMatrix * mvPosition;\\\\n\\\\n\\\\tvViewZDepth = - mvPosition.z;\\\\n\\\\n\\\\n}\\\\n\\\\n\\\\n\\\\n\\\\\\\",fragmentShader:L4,uniforms:{scale:{value:1},mNear:{value:0},mFar:{value:10}}}}insert_define_after(t){return Y4.get(t)}insert_body_after(t){return $4.get(t)}createMaterial(){const t=this.templateShader();return new F({depthTest:!0,linewidth:100,uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader})}});const Z4=new Map([[Mf.VERTEX,[\\\\\\\"#include \\\\\\\",\\\\\\\"#include \\\\\\\"]],[Mf.FRAGMENT,[]]]);class Q4 extends S4{templateShader(){const t=H.dashed;return{vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,uniforms:t.uniforms}}createMaterial(){const t=this.templateShader(),e=new F({depthTest:!0,alphaTest:.5,linewidth:1,uniforms:I.clone(t.uniforms),vertexShader:t.vertexShader,fragmentShader:t.fragmentShader});return this._addCustomMaterials(e),e}custom_assembler_class_by_custom_name(){return J4}create_shader_configs(){return[new u4(Mf.VERTEX,[\\\\\\\"position\\\\\\\",\\\\\\\"uv\\\\\\\"],[]),new u4(Mf.FRAGMENT,[\\\\\\\"color\\\\\\\",\\\\\\\"alpha\\\\\\\"],[Mf.VERTEX])]}static output_input_connection_points(){return[new qo(\\\\\\\"position\\\\\\\",Uo.VEC3),new qo(\\\\\\\"color\\\\\\\",Uo.VEC3),new qo(\\\\\\\"alpha\\\\\\\",Uo.FLOAT),new qo(\\\\\\\"uv\\\\\\\",Uo.VEC2)]}add_output_inputs(t){t.io.inputs.setNamedInputConnectionPoints(Q4.output_input_connection_points())}static create_globals_node_output_connections(){return[new qo(\\\\\\\"position\\\\\\\",Uo.VEC3),new qo(\\\\\\\"color\\\\\\\",Uo.VEC3),new qo(\\\\\\\"uv\\\\\\\",Uo.VEC2),new qo(\\\\\\\"gl_FragCoord\\\\\\\",Uo.VEC4),new qo(\\\\\\\"resolution\\\\\\\",Uo.VEC2),new qo(\\\\\\\"time\\\\\\\",Uo.FLOAT)]}create_globals_node_output_connections(){return Q4.create_globals_node_output_connections()}create_variable_configs(){return[new d4(\\\\\\\"position\\\\\\\",{default:\\\\\\\"vec3( position )\\\\\\\",prefix:\\\\\\\"vec3 transformed = \\\\\\\",suffix:\\\\\\\";vec4 mvPosition = vec4( transformed, 1.0 ); gl_Position = projectionMatrix * modelViewMatrix * mvPosition;\\\\\\\"}),new d4(\\\\\\\"color\\\\\\\",{prefix:\\\\\\\"diffuseColor.xyz = \\\\\\\"}),new d4(\\\\\\\"alpha\\\\\\\",{prefix:\\\\\\\"diffuseColor.w = \\\\\\\"}),new d4(\\\\\\\"uv\\\\\\\",{prefix:\\\\\\\"vUv = \\\\\\\",if:Pf.IF_RULE.uv})]}lines_to_remove(t){return Z4.get(t)}}class K4 extends T4{templateShader(){}_template_shader_for_shader_name(t){return\\\\\\\"#include \\\\n\\\\n// INSERT DEFINE\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec2 particleUV = (gl_FragCoord.xy / resolution.xy);\\\\n\\\\n\\\\t// INSERT BODY\\\\n\\\\n}\\\\\\\"}compile(){this.setup_shader_names_and_variables(),this.update_shaders()}root_nodes_by_shader_name(t){var e,n;const i=[];for(let s of this._root_nodes)switch(s.type()){case CF.type():i.push(s);break;case wf.type():{const r=s.attribute_name,o=null===(e=this._texture_allocations_controller)||void 0===e?void 0:e.variable(r);if(o&&o.allocation()){(null===(n=o.allocation())||void 0===n?void 0:n.shaderName())==t&&i.push(s)}break}}return i}leaf_nodes_by_shader_name(t){var e,n;const i=[];for(let s of this._leaf_nodes)switch(s.type()){case OI.type():i.push(s);break;case wf.type():{const r=s.attribute_name,o=null===(e=this._texture_allocations_controller)||void 0===e?void 0:e.variable(r);if(o&&o.allocation()){(null===(n=o.allocation())||void 0===n?void 0:n.shaderName())==t&&i.push(s)}break}}return i}setup_shader_names_and_variables(){var t;const e=new y4(this.currentGlParentNode(),this.shaderNames(),((t,e)=>this.input_names_for_shader_name(t,e)));this._leaf_nodes=e.leaves_from_nodes(this._root_nodes),this._texture_allocations_controller=new K0,this._texture_allocations_controller.allocateConnectionsFromRootNodes(this._root_nodes,this._leaf_nodes),this.globals_handler&&(null===(t=this.globals_handler)||void 0===t||t.set_texture_allocations_controller(this._texture_allocations_controller)),this._reset_shader_configs()}update_shaders(){this._shaders_by_name.clear(),this._lines.clear();for(let t of this.shaderNames()){const e=this._template_shader_for_shader_name(t);this._lines.set(t,e.split(\\\\\\\"\\\\n\\\\\\\"))}this._root_nodes.length>0&&(this._resetCodeBuilder(),this.build_code_from_nodes(this._root_nodes),this._build_lines());for(let t of this.shaderNames()){const e=this._lines.get(t);e&&this._shaders_by_name.set(t,e.join(\\\\\\\"\\\\n\\\\\\\"))}}add_output_inputs(t){t.io.inputs.setNamedInputConnectionPoints([new qo(\\\\\\\"position\\\\\\\",Uo.VEC3),new qo(\\\\\\\"velocity\\\\\\\",Uo.VEC3)])}add_globals_outputs(t){t.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"position\\\\\\\",Uo.VEC3),new qo(\\\\\\\"velocity\\\\\\\",Uo.VEC3),new qo(\\\\\\\"time\\\\\\\",Uo.FLOAT)])}allow_attribute_exports(){return!0}textureAllocationsController(){return this._texture_allocations_controller=this._texture_allocations_controller||new K0}create_shader_configs(){var t;return(null===(t=this._texture_allocations_controller)||void 0===t?void 0:t.createShaderConfigs())||[]}create_variable_configs(){return[]}shaderNames(){return this.textureAllocationsController().shaderNames()||[]}input_names_for_shader_name(t,e){return this.textureAllocationsController().inputNamesForShaderName(t,e)||[]}insert_define_after(t){return\\\\\\\"// INSERT DEFINE\\\\\\\"}insert_body_after(t){return\\\\\\\"// INSERT BODY\\\\\\\"}lines_to_remove(t){return[\\\\\\\"// INSERT DEFINE\\\\\\\",\\\\\\\"// INSERT BODY\\\\\\\"]}add_export_body_line(t,e,n,i,s){var r;if(n){const n=t.variableForInput(e),o=mf.vector3(n);if(o){const e=this.textureAllocationsController().variable(i),n=s.current_shader_name;if(e&&(null===(r=e.allocation())||void 0===r?void 0:r.shaderName())==n){const i=`gl_FragColor.${e.component()} = ${o}`;s.addBodyLines(t,[i],n)}}}}set_node_lines_output(t,e){const n=e.current_shader_name,i=this.textureAllocationsController().inputNamesForShaderName(t,n);if(i)for(let n of i){const i=t.io.inputs.named_input(n);if(i){const s=n;this.add_export_body_line(t,n,i,s,e)}}}set_node_lines_attribute(t,e){var n,i;if(t.isImporting()){const s=t.gl_type(),r=t.attribute_name,o=null===(n=this.globals_handler)||void 0===n?void 0:n.read_attribute(t,s,r,e),a=t.glVarName(t.output_name),l=`${s} ${a} = ${o}`;e.addBodyLines(t,[l]);const c=this.textureAllocationsController().variable(r),h=e.current_shader_name;if(c&&(null===(i=c.allocation())||void 0===i?void 0:i.shaderName())==h){const n=this.textureAllocationsController().variable(r);if(n){const i=`gl_FragColor.${n.component()} = ${a}`;e.addBodyLines(t,[i])}}}if(t.isExporting()){const n=t.connected_input_node();if(n){const i=t.attribute_name;this.add_export_body_line(t,t.input_name,n,i,e)}}}set_node_lines_globals(t,e){for(let n of t.io.outputs.used_output_names())switch(n){case\\\\\\\"time\\\\\\\":this._handle_globals_time(t,n,e);break;default:this._handle_globals_default(t,n,e)}}_handle_globals_time(t,e,n){const i=new Nf(t,Uo.FLOAT,e);n.addDefinitions(t,[i]);const s=`float ${t.glVarName(e)} = ${e}`;n.addBodyLines(t,[s]),this.setUniformsTimeDependent()}_handle_globals_default(t,e,n){var i;const s=t.io.outputs.namedOutputConnectionPointsByName(e);if(s){const r=s.type(),o=null===(i=this.globals_handler)||void 0===i?void 0:i.read_attribute(t,r,e,n);if(o){const i=`${r} ${t.glVarName(e)} = ${o}`;n.addBodyLines(t,[i])}}}}class t5 extends T4{templateShader(){return{fragmentShader:\\\\\\\"#include \\\\n\\\\nuniform vec2 resolution;\\\\n\\\\n// INSERT DEFINE\\\\n\\\\nvoid main() {\\\\n\\\\n\\\\tvec4 diffuseColor = vec4(0.0,0.0,0.0,1.0);\\\\n\\\\n\\\\n\\\\t// INSERT BODY\\\\n\\\\n\\\\tgl_FragColor = vec4( diffuseColor );\\\\n}\\\\\\\",vertexShader:void 0,uniforms:void 0}}fragment_shader(){return this._shaders_by_name.get(Mf.FRAGMENT)}uniforms(){return this._uniforms}update_fragment_shader(){this._lines=new Map,this._shaders_by_name=new Map;for(let t of this.shaderNames())if(t==Mf.FRAGMENT){const e=this.templateShader().fragmentShader;this._lines.set(t,e.split(\\\\\\\"\\\\n\\\\\\\"))}this._root_nodes.length>0&&(this.build_code_from_nodes(this._root_nodes),this._build_lines()),this._uniforms=this._uniforms||{},this.addUniforms(this._uniforms);for(let t of this.shaderNames()){const e=this._lines.get(t);e&&this._shaders_by_name.set(t,e.join(\\\\\\\"\\\\n\\\\\\\"))}rg.handleDependencies(this.currentGlParentNode(),this.uniformsTimeDependent(),this._uniforms)}add_output_inputs(t){t.io.inputs.setNamedInputConnectionPoints([new qo(\\\\\\\"color\\\\\\\",Uo.VEC3),new qo(\\\\\\\"alpha\\\\\\\",Uo.FLOAT)])}add_globals_outputs(t){t.io.outputs.setNamedOutputConnectionPoints([new qo(\\\\\\\"gl_FragCoord\\\\\\\",Uo.VEC2),new qo(\\\\\\\"time\\\\\\\",Uo.FLOAT)])}create_shader_configs(){return[new u4(Mf.FRAGMENT,[\\\\\\\"color\\\\\\\",\\\\\\\"alpha\\\\\\\"],[])]}create_variable_configs(){return[new d4(\\\\\\\"color\\\\\\\",{prefix:\\\\\\\"diffuseColor.xyz = \\\\\\\"}),new d4(\\\\\\\"alpha\\\\\\\",{prefix:\\\\\\\"diffuseColor.a = \\\\\\\",default:\\\\\\\"1.0\\\\\\\"})]}insert_define_after(t){return\\\\\\\"// INSERT DEFINE\\\\\\\"}insert_body_after(t){return\\\\\\\"// INSERT BODY\\\\\\\"}lines_to_remove(t){return[\\\\\\\"// INSERT DEFINE\\\\\\\",\\\\\\\"// INSERT BODY\\\\\\\"]}handle_gl_FragCoord(t,e,n){\\\\\\\"fragment\\\\\\\"==e&&t.push(`vec2 ${n} = vec2(gl_FragCoord.x / resolution.x, gl_FragCoord.y / resolution.y)`)}set_node_lines_output(t,e){const n=this.input_names_for_shader_name(t,e.current_shader_name);if(n)for(let i of n){if(t.io.inputs.named_input(i)){const n=t.variableForInput(i);let s;\\\\\\\"color\\\\\\\"==i&&(s=`diffuseColor.xyz = ${mf.any(n)}`),\\\\\\\"alpha\\\\\\\"==i&&(s=`diffuseColor.a = ${mf.any(n)}`),s&&e.addBodyLines(t,[s])}}}set_node_lines_globals(t,e){const n=e.current_shader_name;if(!this.shader_config(n))return;const i=[],s=[];for(let e of t.io.outputs.used_output_names()){const r=t.glVarName(e);switch(e){case\\\\\\\"time\\\\\\\":s.push(new Nf(t,Uo.FLOAT,e)),i.push(`float ${r} = ${e}`),this.setUniformsTimeDependent();break;case\\\\\\\"gl_FragCoord\\\\\\\":this.handle_gl_FragCoord(i,n,r)}}e.addDefinitions(t,s,n),e.addBodyLines(t,i)}}const e5=new Map([]);class n5 extends S4{custom_assembler_class_by_custom_name(){return e5}}const i5=new Map([[Mf.VERTEX,\\\\\\\"// start builder body code\\\\\\\"],[Mf.FRAGMENT,\\\\\\\"// start builder body code\\\\\\\"]]),s5=new Map([[Mf.FRAGMENT,[]]]);class r5 extends n5{templateShader(){return{vertexShader:Bk,fragmentShader:zk,uniforms:I.clone(kk)}}createMaterial(){const t=this.templateShader(),e=new F({vertexShader:t.vertexShader,fragmentShader:t.fragmentShader,side:w.H,transparent:!0,depthTest:!0,uniforms:I.clone(t.uniforms)});return yr.add_user_data_render_hook(e,Gk.render_hook.bind(Gk)),this._addCustomMaterials(e),e}add_output_inputs(t){t.io.inputs.setNamedInputConnectionPoints([new qo(\\\\\\\"density\\\\\\\",Uo.FLOAT,1)])}static create_globals_node_output_connections(){return[new qo(\\\\\\\"position\\\\\\\",Uo.VEC3),new qo(\\\\\\\"pos_normalized\\\\\\\",Uo.VEC3),new qo(\\\\\\\"time\\\\\\\",Uo.FLOAT)]}create_globals_node_output_connections(){return r5.create_globals_node_output_connections()}insert_body_after(t){return i5.get(t)}lines_to_remove(t){return s5.get(t)}create_shader_configs(){return[new u4(Mf.VERTEX,[],[]),new u4(Mf.FRAGMENT,[\\\\\\\"density\\\\\\\"],[Mf.VERTEX])]}static create_variable_configs(){return[new d4(\\\\\\\"position\\\\\\\",{}),new d4(\\\\\\\"density\\\\\\\",{prefix:\\\\\\\"density *= \\\\\\\"})]}create_variable_configs(){return r5.create_variable_configs()}set_node_lines_globals(t,e){const n=[],i=e.current_shader_name,s=this.shader_config(i);if(!s)return;const r=s.dependencies(),o=new Map,a=new Map;let l,c;for(let s of t.io.outputs.used_output_names()){const u=t.glVarName(s),d=e.current_shader_name;switch(s){case\\\\\\\"time\\\\\\\":l=new Nf(t,Uo.FLOAT,s),d&&h.pushOnArrayAtEntry(o,d,l),c=`float ${u} = ${s}`;for(let t of r)h.pushOnArrayAtEntry(o,t,l),h.pushOnArrayAtEntry(a,t,c);n.push(c),this.setUniformsTimeDependent();break;case\\\\\\\"position\\\\\\\":i==Mf.FRAGMENT&&n.push(`vec3 ${u} = position_for_step`);break;case\\\\\\\"pos_normalized\\\\\\\":i==Mf.FRAGMENT&&n.push(`vec3 ${u} = (position_for_step - u_BoundingBoxMax) / (u_BoundingBoxMax - u_BoundingBoxMin)`)}}o.forEach(((n,i)=>{e.addDefinitions(t,n,i)})),a.forEach(((n,i)=>{e.addBodyLines(t,n,i)})),e.addBodyLines(t,n)}}class o5{static async run(){this._started||(this._started=!0,class{static async run(t){(class{static run(t){t.registerNode(k_,ec),t.registerNode(G_,sc),t.registerNode(H_,ec),t.registerNode(W_,ec),t.registerNode(tm,ec),t.registerNode(nm,tc),t.registerNode(sm,ec),t.registerNode(om,sc),t.registerNode(lm,ic),t.registerNode(mm,ic),t.registerNode(gm,ec),t.registerNode(ym,tc),t.registerNode(Sm,ic),t.registerNode(Lm,nc),t.registerNode(Om,nc),t.registerNode(Pm,nc),t.registerNode(Rm,nc),t.registerNode(sf,nc),t.registerNode(rf,nc)}}).run(t),class{static run(t){t.registerNode(rg,rc),t.registerNode(Og,oc),t.registerNode(Rg,oc),t.registerNode(kg,oc),t.registerNode(Hg,oc),t.registerNode(sv,oc),t.registerNode(lv,oc),t.registerNode(pv,ac),t.registerNode(mv,ac),t.registerNode(vv,ac),t.registerNode(xv,ac),t.registerNode(Tv,rc),t.registerNode(Ev,oc),t.registerNode(Nv,rc),t.registerNode(Pv,lc),t.registerNode(Iv,lc),t.registerNode(Rv,lc),t.registerNode(Fv,lc),t.registerNode(Dv,lc),t.registerNode(Bv,lc)}}.run(t),class{static run(t){t.registerNode(Gv,dc),t.registerNode(jv,uc),t.registerNode(qv,uc),t.registerNode($v,uc),t.registerNode(ry,cc),t.registerNode(vy,cc),t.registerNode(gy,cc),t.registerNode(xy,uc),t.registerNode(Tl,hc),t.registerNode(ex,cc),t.registerNode(hl,hc),t.registerNode(rx,uc),t.registerNode(ax,uc),t.registerNode(OL,cc),t.registerNode(Ja,hc),t.registerNode(FL,dc),t.registerNode(kL,uc),t.registerNode(YL,hc),t.registerNode(el,hc),t.registerNode(gO,uc),t.registerNode(rl,dc),t.registerNode(bO,dc),t.registerNode(PO,dc),t.registerNode(IO,uc),t.registerNode(BO,uc),t.registerNode(Ml,hc),t.registerNode(kO,uc),t.registerNode(ml,hc),t.registerNode(VO,pc),t.registerNode(HO,pc),t.registerNode(jO,pc),t.registerNode(WO,pc),t.registerNode(qO,pc),t.registerNode(XO,pc)}}.run(t),class{static run(t){t.registerNode(PP,xc),t.registerNode(SR,bc),t.registerNode(RP,Tc),t.registerNode(dR,xc),t.registerNode(PR,Tc),t.registerNode(vR,yc),t.registerNode(IP,Tc),t.registerNode(FP,Tc),t.registerNode(wf,gc,{except:[`${ts.COP}/builder`]}),t.registerNode(sP,mc),t.registerNode(DP,xc),t.registerNode(lR,xc),t.registerNode(DR,_c),t.registerNode(HR,yc),t.registerNode(jR,xc),t.registerNode(XR,gc),t.registerNode(BP,Tc),t.registerNode(JR,fc),t.registerNode(ZR,xc),t.registerNode(zP,mc),t.registerNode(tI,fc),t.registerNode(KP,fc),t.registerNode(pR,xc),t.registerNode(tR,fc),t.registerNode(lI,xc),t.registerNode(kP,xc),t.registerNode(UP,xc),t.registerNode(cR,fc),t.registerNode(uI,xc),t.registerNode(pI,xc),t.registerNode(mI,xc),t.registerNode(gI,xc),t.registerNode(JO,mc),t.registerNode(oP,mc),t.registerNode(lP,mc),t.registerNode(hP,mc),t.registerNode(GP,xc),t.registerNode(xI,_c),t.registerNode(NI,yc),t.registerNode(VP,xc),t.registerNode(OI,gc),t.registerNode(RI,_c),t.registerNode(FI,_c),t.registerNode(zI,yc),t.registerNode(UI,Ac),t.registerNode(nP,mc),t.registerNode(KO,mc),t.registerNode(HP,xc),t.registerNode(XI,fc),t.registerNode(YI,fc),t.registerNode(JI,_c),t.registerNode(jP,xc),t.registerNode(WP,xc),t.registerNode(eR,xc),t.registerNode(QI,xc),t.registerNode(nR,xc),t.registerNode(iR,xc),t.registerNode(iF,xc),t.registerNode(tF,xc),t.registerNode(mR,xc),t.registerNode(oF,xc),t.registerNode(aF,xc),t.registerNode(EF,Ac),t.registerNode(MF,fc),t.registerNode(qP,xc),t.registerNode(yR,yc),t.registerNode(CF,gc),t.registerNode(OF,gc),t.registerNode(sR,xc),t.registerNode(DF,wc),t.registerNode(UF,wc),t.registerNode(GF,wc),t.registerNode(VF,wc),t.registerNode(WF,gc),t.registerNode(YF,gc),t.registerNode(XP,mc),t.registerNode(rR,fc),t.registerNode(PF,fc),t.registerNode(JF,_c),t.registerNode(rD,fc),t.registerNode(aD,xc),t.registerNode(YP,xc),t.registerNode($P,Tc),t.registerNode(hR,xc),t.registerNode(cD,fc),t.registerNode(JP,xc),t.registerNode(FF,vc),t.registerNode(oR,fc),t.registerNode(MI,yc),t.registerNode(uD,yc,LD),t.registerNode(wI,yc,LD),t.registerNode(_R,xc),t.registerNode(pD,yc),t.registerNode(ZP,Tc),t.registerNode(mD,_c),t.registerNode(yD,gc),t.registerNode(wD,yc),t.registerNode(Ff,gc),t.registerNode(MD,gc),t.registerNode(gP,mc),t.registerNode(wP,mc),t.registerNode(vP,mc),t.registerNode(bP,mc),t.registerNode(TP,mc),t.registerNode(yP,mc),t.registerNode(xP,mc),t.registerNode(SD,fc),t.registerNode(ND,fc)}}.run(t),class{static run(t){t.registerNode(ID,Mc),t.registerNode(DD,Mc),t.registerNode(zD,Mc),t.registerNode(WD,Mc)}}.run(t),class{static run(t){t.registerNode(tB,Sc),t.registerNode(dB,Sc),t.registerNode(HB,Cc),t.registerNode($B,Ec),t.registerNode(ez,Cc),t.registerNode(az,Ec),t.registerNode(wz,Cc),t.registerNode(Ez,Cc),t.registerNode(Pz,Cc),t.registerNode(Dz,Ec),t.registerNode(Xz,Cc),t.registerNode(Zz,Ec),t.registerNode(ek,Cc),t.registerNode(rk,Ec),t.registerNode(gk,Cc),t.registerNode(Tk,Cc),t.registerNode(Sk,Lc),t.registerNode(Lk,Ec),t.registerNode(Rk,Ec),t.registerNode(Dk,Cc),t.registerNode(jk,Oc),t.registerNode(Xk,Oc),t.registerNode(Jk,Nc),t.registerNode(Zk,Nc),t.registerNode(Qk,Nc),t.registerNode(Kk,Nc),t.registerNode(tU,Nc),t.registerNode(eU,Nc)}}.run(t),class{static run(t){t.registerNode(cU,Dc),t.registerNode(OU,Dc),t.registerNode(VU,Dc),t.registerNode($U,Dc),t.registerNode(eG,Dc),t.registerNode(cG,Dc),t.registerNode(yG,Rc),t.registerNode(AG,zc),t.registerNode(IG,Pc),t.registerNode(kG,Fc),t.registerNode(VG,zc),t.registerNode(XG,zc),t.registerNode(xV,Pc),t.registerNode(FV,Rc),t.registerNode(kV,zc),t.registerNode(VV,Pc),t.registerNode(KH,Ic),t.registerNode(ij,Ic),t.registerNode(oj,Ic),t.registerNode(hj,Bc),t.registerNode(uj,Bc),t.registerNode(dj,Bc),t.registerNode(pj,Bc),t.registerNode(_j,Bc),t.registerNode(mj,Bc)}}.run(t),class{static run(t){t.registerNode(Tj,eh),t.registerNode(Sj,eh),t.registerNode(Lj,th),t.registerNode(Rj,th),t.registerNode(Dj,nh),t.registerNode(zj,nh),t.registerNode(Gj,nh),t.registerNode(Hj,nh),t.registerNode(Qj,eh),t.registerNode($j,eh),t.registerNode(nW,eh),t.registerNode(rW,nh),t.registerNode(lW,th),t.registerNode(hW,Kc),t.registerNode(dW,nh),t.registerNode(vW,nh),t.registerNode(xW,nh),t.registerNode(wW,nh),t.registerNode(MW,eh),t.registerNode(CW,eh),t.registerNode(LW,nh),t.registerNode(RW,eh),t.registerNode(DW,th),t.registerNode(zW,nh),t.registerNode(VW,Kc),t.registerNode(qW,eh),t.registerNode(YW,Kc),t.registerNode(ZW,eh),t.registerNode(tq,ih),t.registerNode(eq,ih),t.registerNode(nq,ih),t.registerNode(iq,ih),t.registerNode(sq,ih),t.registerNode(rq,ih)}}.run(t),class{static run(t){t.registerNode(dq,kc),t.registerNode(AH,Gc),t.registerNode(pq,Uc),t.registerNode(lq,Uc),t.registerNode(_q,Uc),t.registerNode(mq,Uc),t.registerNode(fq,Uc),t.registerNode(gq,Uc)}}.run(t),class{static run(t){t.registerOperation(vq),t.registerOperation(Pq),t.registerOperation(Uq),t.registerOperation(jq),t.registerOperation(Yq),t.registerOperation(lX),t.registerOperation(nX),t.registerOperation(pX),t.registerOperation(qX),t.registerOperation(JX),t.registerOperation(T$),t.registerOperation(S$),t.registerOperation(UJ),t.registerOperation(jJ),t.registerOperation($J),t.registerOperation(lZ),t.registerOperation(DZ),t.registerOperation(eQ),t.registerOperation(dK),t.registerOperation(EK),t.registerOperation(DK),t.registerOperation(UK),t.registerOperation(qK),t.registerOperation(o0),t.registerOperation(y0),t.registerOperation(n0),t.registerOperation(P0),t.registerOperation(B0),t.registerOperation(i1),t.registerOperation(h1),t.registerOperation(_1),t.registerOperation(b1),t.registerOperation(S1),t.registerOperation(z1),t.registerOperation(X1),t.registerOperation(s2),t.registerOperation(l2),t.registerOperation(d2),t.registerOperation(x2),t.registerOperation(N2),t.registerOperation(U2),t.registerOperation(K2),t.registerOperation(h9),t.registerOperation(O9),t.registerOperation(F9),t.registerOperation(U9),t.registerOperation(j9),t.registerOperation(J9),t.registerOperation(m3),t.registerOperation(w3),t.registerOperation(E3),t.registerNode(bq,qc),t.registerNode(Tq,Hc),t.registerNode(Oq,Hc),t.registerNode(Fq,jc),t.registerNode(Hq,jc),t.registerNode(Xq,jc),t.registerNode(Qq,jc),t.registerNode(tX,jc),t.registerNode(rX,jc),t.registerNode(uX,jc),t.registerNode(gX,jc),t.registerNode(yX,jc),t.registerNode(bX,jc),t.registerNode(SX,jc),t.registerNode(NX,$c),t.registerNode(OX,$c),t.registerNode($X,$c),t.registerNode(KX,Zc),t.registerNode(E$,Vc),t.registerNode(L$,Vc),t.registerNode(IJ,Yc),t.registerNode(kJ,Zc),t.registerNode(HJ,$c),t.registerNode(qJ,Zc),t.registerNode(QJ,Zc),t.registerNode(rZ,Zc),t.registerNode(uZ,$c),t.registerNode(gZ,$c),t.registerNode(xZ,Zc),t.registerNode(PZ,$c),t.registerNode(kZ,Zc),t.registerNode(jZ,qc),t.registerNode(QZ,qc),t.registerNode(sQ,Yc),t.registerNode(oQ,Yc),t.registerNode(bQ,$c),t.registerNode(TQ,$c),t.registerNode(rK,Vc),t.registerNode(aK,$c),t.registerNode(mK,qc),t.registerNode(gK,qc),t.registerNode(yK,$c),t.registerNode(TK,Zc),t.registerNode(PK,$c),t.registerNode(LK,Yc),t.registerNode(kK,Zc),t.registerNode(HK,Qc),t.registerNode(WK,Qc),t.registerNode($K,$c),t.registerNode(ZK,$c),t.registerNode(KK,Zc),t.registerNode(e0,Vc),t.registerNode(r0,Qc),t.registerNode(h0,Yc),t.registerNode(w0,Zc),t.registerNode(N0,Yc),t.registerNode(O0,$c),t.registerNode(I0,Yc),t.registerNode(D0,qc),t.registerNode(U0,$c),t.registerNode(V0,Vc,{userAllowed:!1}),t.registerNode(n1,Wc),t.registerNode(o1,$c),t.registerNode(p1,Zc),t.registerNode(g1,$c),t.registerNode(L1,$c),t.registerNode(x1,$c),t.registerNode(A1,Xc),t.registerNode(fV,Vc),t.registerNode(D1,$c),t.registerNode(G1,$c),t.registerNode(J1,Qc),t.registerNode(i2,$c),t.registerNode(a2,jc),t.registerNode(u2,qc),t.registerNode(m2,$c),t.registerNode(E2,$c),t.registerNode(A2,$c),t.registerNode(I2,Vc),t.registerNode(D2,Vc),t.registerNode(P2,$c),t.registerNode(H2,Zc),t.registerNode(W2,$c),t.registerNode(n9,$c),t.registerNode(s9,Yc),t.registerNode(o9,Yc),t.registerNode(hV,Yc),t.registerNode(p9,qc),t.registerNode(f9,Yc),t.registerNode(y9,Zc),t.registerNode(L9,Zc),t.registerNode(I9,$c),t.registerNode(z9,$c),t.registerNode(H9,Zc),t.registerNode(X9,Zc),t.registerNode(K9,$c),t.registerNode(e3,$c),t.registerNode(o3,$c),t.registerNode(h3,$c),t.registerNode(p3,Zc),t.registerNode(g3,$c),t.registerNode(b3,$c),t.registerNode(M3,$c),t.registerNode(C3,$c),t.registerNode(O3,Jc),t.registerNode(P3,Jc),t.registerNode(R3,Jc),t.registerNode(I3,Jc),t.registerNode(F3,Jc),t.registerNode(D3,Jc)}}.run(t)}}.run(li),class{static run(t){t.registerCamera(KH),t.registerCamera(ij)}}.run(li),class{static run(t){t.expressionsRegister.register(z3,\\\\\\\"arg\\\\\\\"),t.expressionsRegister.register(k3,\\\\\\\"argc\\\\\\\"),t.expressionsRegister.register(V3,\\\\\\\"bbox\\\\\\\"),t.expressionsRegister.register(H3,\\\\\\\"centroid\\\\\\\"),t.expressionsRegister.register(j3,\\\\\\\"ch\\\\\\\"),t.expressionsRegister.register(W3,\\\\\\\"copy\\\\\\\"),t.expressionsRegister.register(q3,\\\\\\\"copRes\\\\\\\"),t.expressionsRegister.register(X3,\\\\\\\"isDeviceMobile\\\\\\\"),t.expressionsRegister.register(Y3,\\\\\\\"isDeviceTouch\\\\\\\"),t.expressionsRegister.register($3,\\\\\\\"js\\\\\\\"),t.expressionsRegister.register(J3,\\\\\\\"object\\\\\\\"),t.expressionsRegister.register(Z3,\\\\\\\"objectsCount\\\\\\\"),t.expressionsRegister.register(Q3,\\\\\\\"opdigits\\\\\\\"),t.expressionsRegister.register(K3,\\\\\\\"opname\\\\\\\"),t.expressionsRegister.register(t4,\\\\\\\"padzero\\\\\\\"),t.expressionsRegister.register(e4,\\\\\\\"point\\\\\\\"),t.expressionsRegister.register(n4,\\\\\\\"pointsCount\\\\\\\"),t.expressionsRegister.register(i4,\\\\\\\"strCharsCount\\\\\\\"),t.expressionsRegister.register(s4,\\\\\\\"strConcat\\\\\\\"),t.expressionsRegister.register(r4,\\\\\\\"strIndex\\\\\\\"),t.expressionsRegister.register(o4,\\\\\\\"strSub\\\\\\\"),t.expressionsRegister.register(a4,\\\\\\\"windowSize\\\\\\\")}}.run(li),class{static run(t){t.assemblersRegister.register(jn.GL_MESH_BASIC,c4,F4),t.assemblersRegister.register(jn.GL_MESH_LAMBERT,c4,D4),t.assemblersRegister.register(jn.GL_MESH_PHONG,c4,B4),t.assemblersRegister.register(jn.GL_MESH_STANDARD,c4,k4),t.assemblersRegister.register(jn.GL_MESH_PHYSICAL,c4,U4),t.assemblersRegister.register(jn.GL_PARTICLES,c4,K4),t.assemblersRegister.register(jn.GL_POINTS,c4,X4),t.assemblersRegister.register(jn.GL_LINE,c4,Q4),t.assemblersRegister.register(jn.GL_TEXTURE,c4,t5),t.assemblersRegister.register(jn.GL_VOLUME,c4,r5)}}.run(li))}}o5._started=!1,o5.run()}]);void 0===POLY&&console.error(\\\\\\\"esm-webpack-plugin: nothing exported!\\\\\\\");const _POLY$PolyScene=POLY.PolyScene,_POLY$Poly=POLY.Poly,_POLY$SceneJsonImporter=POLY.SceneJsonImporter,_POLY$SceneDataManifestImporter=POLY.SceneDataManifestImporter,_POLY$mountScene=POLY.mountScene;export{_POLY$PolyScene as PolyScene,_POLY$Poly as Poly,_POLY$SceneJsonImporter as SceneJsonImporter,_POLY$SceneDataManifestImporter as 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Safari/537.36"},"fragment":"","postData":null,"protocol":"blob:"},"type":1,"external":false,"timestamp":1724495173422},{"data":{"url":"https://ipfs.arkivo.art/ipfs/QmPqCaV5DCDPXmdwZSBxTcsZhJei1k4aDKjj7UrnqJU78C/flower01.mp3","host":"ipfs.arkivo.art","path":"/ipfs/QmPqCaV5DCDPXmdwZSBxTcsZhJei1k4aDKjj7UrnqJU78C/flower01.mp3","type":"http","query":"","method":"GET","headers":{"referer":"https://ipfs.arkivo.art/ipfs/QmPqCaV5DCDPXmdwZSBxTcsZhJei1k4aDKjj7UrnqJU78C/?creator=tz1djshvCnhi5p5wAebiBb2XQLcvVKBqyH7F&viewer=&objkt=569176","sec-ch-ua":"\"HeadlessChrome\";v=\"119\", \"Chromium\";v=\"119\", \"Not?A_Brand\";v=\"24\"","user-agent":"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) HeadlessChrome/119.0.6045.9 Safari/537.36","sec-ch-ua-mobile":"?0","sec-ch-ua-platform":"\"Linux\""},"fragment":"","postData":null,"protocol":"https:"},"type":1,"external":false,"timestamp":1724495174349},{"data":{"url":"blob:https://ipfs.arkivo.art/d2af42b3-3e24-4540-a2dd-58baa38317a6","host":"","path":"https://ipfs.arkivo.art/d2af42b3-3e24-4540-a2dd-58baa38317a6","type":"http","query":"","method":"GET","headers":{"referer":"","user-agent":"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) HeadlessChrome/119.0.6045.9 Safari/537.36"},"fragment":"","postData":null,"protocol":"blob:"},"type":1,"external":false,"timestamp":1724495174349},{"data":{"url":"blob:https://ipfs.arkivo.art/dff83df7-1054-44bb-a626-53cd7d029443","host":"","path":"https://ipfs.arkivo.art/dff83df7-1054-44bb-a626-53cd7d029443","type":"http","query":"","method":"GET","headers":{"origin":"https://ipfs.arkivo.art","referer":"","user-agent":"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) HeadlessChrome/119.0.6045.9 Safari/537.36"},"fragment":"","postData":null,"protocol":"blob:"},"type":1,"external":false,"timestamp":1724495174350},{"data":{"url":"blob:https://ipfs.arkivo.art/082a176d-680f-46d4-9827-f7be44c34d28","body":"\"var __create = Object.create;\\nvar __defProp = Object.defineProperty;\\nvar __getProtoOf = Object.getPrototypeOf;\\nvar __hasOwnProp = Object.prototype.hasOwnProperty;\\nvar __getOwnPropNames = Object.getOwnPropertyNames;\\nvar __getOwnPropDesc = Object.getOwnPropertyDescriptor;\\nvar __markAsModule = (target) => __defProp(target, \\\\\\\"__esModule\\\\\\\", {value: true});\\nvar __commonJS = (callback, module) => () => {\\n if (!module) {\\n module = {exports: {}};\\n callback(module.exports, module);\\n }\\n return module.exports;\\n};\\nvar __exportStar = (target, module, desc) => {\\n __markAsModule(target);\\n if (module && typeof module === \\\\\\\"object\\\\\\\" || typeof module === \\\\\\\"function\\\\\\\") {\\n for (let key of __getOwnPropNames(module))\\n if (!__hasOwnProp.call(target, key) && key !== \\\\\\\"default\\\\\\\")\\n __defProp(target, key, {get: () => module[key], enumerable: !(desc = __getOwnPropDesc(module, key)) || desc.enumerable});\\n }\\n return target;\\n};\\nvar __toModule = (module) => {\\n if (module && module.__esModule)\\n return module;\\n return __exportStar(__defProp(module != null ? __create(__getProtoOf(module)) : {}, \\\\\\\"default\\\\\\\", {value: module, enumerable: true}), module);\\n};\\n\\n// ../../../node_modules/lodash/_listCacheClear.js\\nvar require_listCacheClear = __commonJS((exports, module) => {\\n function listCacheClear() {\\n this.__data__ = [];\\n this.size = 0;\\n }\\n module.exports = listCacheClear;\\n});\\n\\n// ../../../node_modules/lodash/eq.js\\nvar require_eq = __commonJS((exports, module) => {\\n function eq(value, other) {\\n return value === other || value !== value && other !== other;\\n }\\n module.exports = eq;\\n});\\n\\n// ../../../node_modules/lodash/_assocIndexOf.js\\nvar require_assocIndexOf = __commonJS((exports, module) => {\\n var eq = require_eq();\\n function assocIndexOf(array, key) {\\n var length = array.length;\\n while (length--) {\\n if (eq(array[length][0], key)) {\\n return length;\\n }\\n }\\n return -1;\\n }\\n module.exports = assocIndexOf;\\n});\\n\\n// ../../../node_modules/lodash/_listCacheDelete.js\\nvar require_listCacheDelete = __commonJS((exports, module) => {\\n var assocIndexOf = require_assocIndexOf();\\n var arrayProto = Array.prototype;\\n var splice = arrayProto.splice;\\n function listCacheDelete(key) {\\n var data = this.__data__, index = assocIndexOf(data, key);\\n if (index < 0) {\\n return false;\\n }\\n var lastIndex = data.length - 1;\\n if (index == lastIndex) {\\n data.pop();\\n } else {\\n splice.call(data, index, 1);\\n }\\n --this.size;\\n return true;\\n }\\n module.exports = listCacheDelete;\\n});\\n\\n// ../../../node_modules/lodash/_listCacheGet.js\\nvar require_listCacheGet = __commonJS((exports, module) => {\\n var assocIndexOf = require_assocIndexOf();\\n function listCacheGet(key) {\\n var data = this.__data__, index = assocIndexOf(data, key);\\n return index < 0 ? void 0 : data[index][1];\\n }\\n module.exports = listCacheGet;\\n});\\n\\n// ../../../node_modules/lodash/_listCacheHas.js\\nvar require_listCacheHas = __commonJS((exports, module) => {\\n var assocIndexOf = require_assocIndexOf();\\n function listCacheHas(key) {\\n return assocIndexOf(this.__data__, key) > -1;\\n }\\n module.exports = listCacheHas;\\n});\\n\\n// ../../../node_modules/lodash/_listCacheSet.js\\nvar require_listCacheSet = __commonJS((exports, module) => {\\n var assocIndexOf = require_assocIndexOf();\\n function listCacheSet(key, value) {\\n var data = this.__data__, index = assocIndexOf(data, key);\\n if (index < 0) {\\n ++this.size;\\n data.push([key, value]);\\n } else {\\n data[index][1] = value;\\n }\\n return this;\\n }\\n module.exports = listCacheSet;\\n});\\n\\n// ../../../node_modules/lodash/_ListCache.js\\nvar require_ListCache = __commonJS((exports, module) => {\\n var listCacheClear = require_listCacheClear();\\n var listCacheDelete = require_listCacheDelete();\\n var listCacheGet = require_listCacheGet();\\n var listCacheHas = require_listCacheHas();\\n var listCacheSet = require_listCacheSet();\\n function ListCache(entries) {\\n var index = -1, length = entries == null ? 0 : entries.length;\\n this.clear();\\n while (++index < length) {\\n var entry = entries[index];\\n this.set(entry[0], entry[1]);\\n }\\n }\\n ListCache.prototype.clear = listCacheClear;\\n ListCache.prototype[\\\\\\\"delete\\\\\\\"] = listCacheDelete;\\n ListCache.prototype.get = listCacheGet;\\n ListCache.prototype.has = listCacheHas;\\n ListCache.prototype.set = listCacheSet;\\n module.exports = ListCache;\\n});\\n\\n// ../../../node_modules/lodash/_stackClear.js\\nvar require_stackClear = __commonJS((exports, module) => {\\n var ListCache = require_ListCache();\\n function stackClear() {\\n this.__data__ = new ListCache();\\n this.size = 0;\\n }\\n module.exports = stackClear;\\n});\\n\\n// ../../../node_modules/lodash/_stackDelete.js\\nvar require_stackDelete = __commonJS((exports, module) => {\\n function stackDelete(key) {\\n var data = this.__data__, result = data[\\\\\\\"delete\\\\\\\"](key);\\n this.size = data.size;\\n return result;\\n }\\n module.exports = stackDelete;\\n});\\n\\n// ../../../node_modules/lodash/_stackGet.js\\nvar require_stackGet = __commonJS((exports, module) => {\\n function stackGet(key) {\\n return this.__data__.get(key);\\n }\\n module.exports = stackGet;\\n});\\n\\n// ../../../node_modules/lodash/_stackHas.js\\nvar require_stackHas = __commonJS((exports, module) => {\\n function stackHas(key) {\\n return this.__data__.has(key);\\n }\\n module.exports = stackHas;\\n});\\n\\n// ../../../node_modules/lodash/_freeGlobal.js\\nvar require_freeGlobal = __commonJS((exports, module) => {\\n var freeGlobal = typeof global == \\\\\\\"object\\\\\\\" && global && global.Object === Object && global;\\n module.exports = freeGlobal;\\n});\\n\\n// ../../../node_modules/lodash/_root.js\\nvar require_root = __commonJS((exports, module) => {\\n var freeGlobal = require_freeGlobal();\\n var freeSelf = typeof self == \\\\\\\"object\\\\\\\" && self && self.Object === Object && self;\\n var root = freeGlobal || freeSelf || Function(\\\\\\\"return this\\\\\\\")();\\n module.exports = root;\\n});\\n\\n// ../../../node_modules/lodash/_Symbol.js\\nvar require_Symbol = __commonJS((exports, module) => {\\n var root = require_root();\\n var Symbol2 = root.Symbol;\\n module.exports = Symbol2;\\n});\\n\\n// ../../../node_modules/lodash/_getRawTag.js\\nvar require_getRawTag = __commonJS((exports, module) => {\\n var Symbol2 = require_Symbol();\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n var nativeObjectToString = objectProto.toString;\\n var symToStringTag = Symbol2 ? Symbol2.toStringTag : void 0;\\n function getRawTag(value) {\\n var isOwn = hasOwnProperty.call(value, symToStringTag), tag = value[symToStringTag];\\n try {\\n value[symToStringTag] = void 0;\\n var unmasked = true;\\n } catch (e) {\\n }\\n var result = nativeObjectToString.call(value);\\n if (unmasked) {\\n if (isOwn) {\\n value[symToStringTag] = tag;\\n } else {\\n delete value[symToStringTag];\\n }\\n }\\n return result;\\n }\\n module.exports = getRawTag;\\n});\\n\\n// ../../../node_modules/lodash/_objectToString.js\\nvar require_objectToString = __commonJS((exports, module) => {\\n var objectProto = Object.prototype;\\n var nativeObjectToString = objectProto.toString;\\n function objectToString(value) {\\n return nativeObjectToString.call(value);\\n }\\n module.exports = objectToString;\\n});\\n\\n// ../../../node_modules/lodash/_baseGetTag.js\\nvar require_baseGetTag = __commonJS((exports, module) => {\\n var Symbol2 = require_Symbol();\\n var getRawTag = require_getRawTag();\\n var objectToString = require_objectToString();\\n var nullTag = \\\\\\\"[object Null]\\\\\\\";\\n var undefinedTag = \\\\\\\"[object Undefined]\\\\\\\";\\n var symToStringTag = Symbol2 ? Symbol2.toStringTag : void 0;\\n function baseGetTag(value) {\\n if (value == null) {\\n return value === void 0 ? undefinedTag : nullTag;\\n }\\n return symToStringTag && symToStringTag in Object(value) ? getRawTag(value) : objectToString(value);\\n }\\n module.exports = baseGetTag;\\n});\\n\\n// ../../../node_modules/lodash/isObject.js\\nvar require_isObject = __commonJS((exports, module) => {\\n function isObject(value) {\\n var type = typeof value;\\n return value != null && (type == \\\\\\\"object\\\\\\\" || type == \\\\\\\"function\\\\\\\");\\n }\\n module.exports = isObject;\\n});\\n\\n// ../../../node_modules/lodash/isFunction.js\\nvar require_isFunction = __commonJS((exports, module) => {\\n var baseGetTag = require_baseGetTag();\\n var isObject = require_isObject();\\n var asyncTag = \\\\\\\"[object AsyncFunction]\\\\\\\";\\n var funcTag = \\\\\\\"[object Function]\\\\\\\";\\n var genTag = \\\\\\\"[object GeneratorFunction]\\\\\\\";\\n var proxyTag = \\\\\\\"[object Proxy]\\\\\\\";\\n function isFunction(value) {\\n if (!isObject(value)) {\\n return false;\\n }\\n var tag = baseGetTag(value);\\n return tag == funcTag || tag == genTag || tag == asyncTag || tag == proxyTag;\\n }\\n module.exports = isFunction;\\n});\\n\\n// ../../../node_modules/lodash/_coreJsData.js\\nvar require_coreJsData = __commonJS((exports, module) => {\\n var root = require_root();\\n var coreJsData = root[\\\\\\\"__core-js_shared__\\\\\\\"];\\n module.exports = coreJsData;\\n});\\n\\n// ../../../node_modules/lodash/_isMasked.js\\nvar require_isMasked = __commonJS((exports, module) => {\\n var coreJsData = require_coreJsData();\\n var maskSrcKey = function() {\\n var uid = /[^.]+$/.exec(coreJsData && coreJsData.keys && coreJsData.keys.IE_PROTO || \\\\\\\"\\\\\\\");\\n return uid ? \\\\\\\"Symbol(src)_1.\\\\\\\" + uid : \\\\\\\"\\\\\\\";\\n }();\\n function isMasked(func) {\\n return !!maskSrcKey && maskSrcKey in func;\\n }\\n module.exports = isMasked;\\n});\\n\\n// ../../../node_modules/lodash/_toSource.js\\nvar require_toSource = __commonJS((exports, module) => {\\n var funcProto = Function.prototype;\\n var funcToString = funcProto.toString;\\n function toSource(func) {\\n if (func != null) {\\n try {\\n return funcToString.call(func);\\n } catch (e) {\\n }\\n try {\\n return func + \\\\\\\"\\\\\\\";\\n } catch (e) {\\n }\\n }\\n return \\\\\\\"\\\\\\\";\\n }\\n module.exports = toSource;\\n});\\n\\n// ../../../node_modules/lodash/_baseIsNative.js\\nvar require_baseIsNative = __commonJS((exports, module) => {\\n var isFunction = require_isFunction();\\n var isMasked = require_isMasked();\\n var isObject = require_isObject();\\n var toSource = require_toSource();\\n var reRegExpChar = /[\\\\\\\\^$.*+?()[\\\\]{}|]/g;\\n var reIsHostCtor = /^\\\\[object .+?Constructor\\\\]$/;\\n var funcProto = Function.prototype;\\n var objectProto = Object.prototype;\\n var funcToString = funcProto.toString;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n var reIsNative = RegExp(\\\\\\\"^\\\\\\\" + funcToString.call(hasOwnProperty).replace(reRegExpChar, \\\\\\\"\\\\\\\\$&\\\\\\\").replace(/hasOwnProperty|(function).*?(?=\\\\\\\\\\\\()| for .+?(?=\\\\\\\\\\\\])/g, \\\\\\\"$1.*?\\\\\\\") + \\\\\\\"$\\\\\\\");\\n function baseIsNative(value) {\\n if (!isObject(value) || isMasked(value)) {\\n return false;\\n }\\n var pattern = isFunction(value) ? reIsNative : reIsHostCtor;\\n return pattern.test(toSource(value));\\n }\\n module.exports = baseIsNative;\\n});\\n\\n// ../../../node_modules/lodash/_getValue.js\\nvar require_getValue = __commonJS((exports, module) => {\\n function getValue(object, key) {\\n return object == null ? void 0 : object[key];\\n }\\n module.exports = getValue;\\n});\\n\\n// ../../../node_modules/lodash/_getNative.js\\nvar require_getNative = __commonJS((exports, module) => {\\n var baseIsNative = require_baseIsNative();\\n var getValue = require_getValue();\\n function getNative(object, key) {\\n var value = getValue(object, key);\\n return baseIsNative(value) ? value : void 0;\\n }\\n module.exports = getNative;\\n});\\n\\n// ../../../node_modules/lodash/_Map.js\\nvar require_Map = __commonJS((exports, module) => {\\n var getNative = require_getNative();\\n var root = require_root();\\n var Map2 = getNative(root, \\\\\\\"Map\\\\\\\");\\n module.exports = Map2;\\n});\\n\\n// ../../../node_modules/lodash/_nativeCreate.js\\nvar require_nativeCreate = __commonJS((exports, module) => {\\n var getNative = require_getNative();\\n var nativeCreate = getNative(Object, \\\\\\\"create\\\\\\\");\\n module.exports = nativeCreate;\\n});\\n\\n// ../../../node_modules/lodash/_hashClear.js\\nvar require_hashClear = __commonJS((exports, module) => {\\n var nativeCreate = require_nativeCreate();\\n function hashClear() {\\n this.__data__ = nativeCreate ? nativeCreate(null) : {};\\n this.size = 0;\\n }\\n module.exports = hashClear;\\n});\\n\\n// ../../../node_modules/lodash/_hashDelete.js\\nvar require_hashDelete = __commonJS((exports, module) => {\\n function hashDelete(key) {\\n var result = this.has(key) && delete this.__data__[key];\\n this.size -= result ? 1 : 0;\\n return result;\\n }\\n module.exports = hashDelete;\\n});\\n\\n// ../../../node_modules/lodash/_hashGet.js\\nvar require_hashGet = __commonJS((exports, module) => {\\n var nativeCreate = require_nativeCreate();\\n var HASH_UNDEFINED = \\\\\\\"__lodash_hash_undefined__\\\\\\\";\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n function hashGet(key) {\\n var data = this.__data__;\\n if (nativeCreate) {\\n var result = data[key];\\n return result === HASH_UNDEFINED ? void 0 : result;\\n }\\n return hasOwnProperty.call(data, key) ? data[key] : void 0;\\n }\\n module.exports = hashGet;\\n});\\n\\n// ../../../node_modules/lodash/_hashHas.js\\nvar require_hashHas = __commonJS((exports, module) => {\\n var nativeCreate = require_nativeCreate();\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n function hashHas(key) {\\n var data = this.__data__;\\n return nativeCreate ? data[key] !== void 0 : hasOwnProperty.call(data, key);\\n }\\n module.exports = hashHas;\\n});\\n\\n// ../../../node_modules/lodash/_hashSet.js\\nvar require_hashSet = __commonJS((exports, module) => {\\n var nativeCreate = require_nativeCreate();\\n var HASH_UNDEFINED = \\\\\\\"__lodash_hash_undefined__\\\\\\\";\\n function hashSet(key, value) {\\n var data = this.__data__;\\n this.size += this.has(key) ? 0 : 1;\\n data[key] = nativeCreate && value === void 0 ? HASH_UNDEFINED : value;\\n return this;\\n }\\n module.exports = hashSet;\\n});\\n\\n// ../../../node_modules/lodash/_Hash.js\\nvar require_Hash = __commonJS((exports, module) => {\\n var hashClear = require_hashClear();\\n var hashDelete = require_hashDelete();\\n var hashGet = require_hashGet();\\n var hashHas = require_hashHas();\\n var hashSet = require_hashSet();\\n function Hash(entries) {\\n var index = -1, length = entries == null ? 0 : entries.length;\\n this.clear();\\n while (++index < length) {\\n var entry = entries[index];\\n this.set(entry[0], entry[1]);\\n }\\n }\\n Hash.prototype.clear = hashClear;\\n Hash.prototype[\\\\\\\"delete\\\\\\\"] = hashDelete;\\n Hash.prototype.get = hashGet;\\n Hash.prototype.has = hashHas;\\n Hash.prototype.set = hashSet;\\n module.exports = Hash;\\n});\\n\\n// ../../../node_modules/lodash/_mapCacheClear.js\\nvar require_mapCacheClear = __commonJS((exports, module) => {\\n var Hash = require_Hash();\\n var ListCache = require_ListCache();\\n var Map2 = require_Map();\\n function mapCacheClear() {\\n this.size = 0;\\n this.__data__ = {\\n hash: new Hash(),\\n map: new (Map2 || ListCache)(),\\n string: new Hash()\\n };\\n }\\n module.exports = mapCacheClear;\\n});\\n\\n// ../../../node_modules/lodash/_isKeyable.js\\nvar require_isKeyable = __commonJS((exports, module) => {\\n function isKeyable(value) {\\n var type = typeof value;\\n return type == \\\\\\\"string\\\\\\\" || type == \\\\\\\"number\\\\\\\" || type == \\\\\\\"symbol\\\\\\\" || type == \\\\\\\"boolean\\\\\\\" ? value !== \\\\\\\"__proto__\\\\\\\" : value === null;\\n }\\n module.exports = isKeyable;\\n});\\n\\n// ../../../node_modules/lodash/_getMapData.js\\nvar require_getMapData = __commonJS((exports, module) => {\\n var isKeyable = require_isKeyable();\\n function getMapData(map, key) {\\n var data = map.__data__;\\n return isKeyable(key) ? data[typeof key == \\\\\\\"string\\\\\\\" ? \\\\\\\"string\\\\\\\" : \\\\\\\"hash\\\\\\\"] : data.map;\\n }\\n module.exports = getMapData;\\n});\\n\\n// ../../../node_modules/lodash/_mapCacheDelete.js\\nvar require_mapCacheDelete = __commonJS((exports, module) => {\\n var getMapData = require_getMapData();\\n function mapCacheDelete(key) {\\n var result = getMapData(this, key)[\\\\\\\"delete\\\\\\\"](key);\\n this.size -= result ? 1 : 0;\\n return result;\\n }\\n module.exports = mapCacheDelete;\\n});\\n\\n// ../../../node_modules/lodash/_mapCacheGet.js\\nvar require_mapCacheGet = __commonJS((exports, module) => {\\n var getMapData = require_getMapData();\\n function mapCacheGet(key) {\\n return getMapData(this, key).get(key);\\n }\\n module.exports = mapCacheGet;\\n});\\n\\n// ../../../node_modules/lodash/_mapCacheHas.js\\nvar require_mapCacheHas = __commonJS((exports, module) => {\\n var getMapData = require_getMapData();\\n function mapCacheHas(key) {\\n return getMapData(this, key).has(key);\\n }\\n module.exports = mapCacheHas;\\n});\\n\\n// ../../../node_modules/lodash/_mapCacheSet.js\\nvar require_mapCacheSet = __commonJS((exports, module) => {\\n var getMapData = require_getMapData();\\n function mapCacheSet(key, value) {\\n var data = getMapData(this, key), size = data.size;\\n data.set(key, value);\\n this.size += data.size == size ? 0 : 1;\\n return this;\\n }\\n module.exports = mapCacheSet;\\n});\\n\\n// ../../../node_modules/lodash/_MapCache.js\\nvar require_MapCache = __commonJS((exports, module) => {\\n var mapCacheClear = require_mapCacheClear();\\n var mapCacheDelete = require_mapCacheDelete();\\n var mapCacheGet = require_mapCacheGet();\\n var mapCacheHas = require_mapCacheHas();\\n var mapCacheSet = require_mapCacheSet();\\n function MapCache(entries) {\\n var index = -1, length = entries == null ? 0 : entries.length;\\n this.clear();\\n while (++index < length) {\\n var entry = entries[index];\\n this.set(entry[0], entry[1]);\\n }\\n }\\n MapCache.prototype.clear = mapCacheClear;\\n MapCache.prototype[\\\\\\\"delete\\\\\\\"] = mapCacheDelete;\\n MapCache.prototype.get = mapCacheGet;\\n MapCache.prototype.has = mapCacheHas;\\n MapCache.prototype.set = mapCacheSet;\\n module.exports = MapCache;\\n});\\n\\n// ../../../node_modules/lodash/_stackSet.js\\nvar require_stackSet = __commonJS((exports, module) => {\\n var ListCache = require_ListCache();\\n var Map2 = require_Map();\\n var MapCache = require_MapCache();\\n var LARGE_ARRAY_SIZE = 200;\\n function stackSet(key, value) {\\n var data = this.__data__;\\n if (data instanceof ListCache) {\\n var pairs = data.__data__;\\n if (!Map2 || pairs.length < LARGE_ARRAY_SIZE - 1) {\\n pairs.push([key, value]);\\n this.size = ++data.size;\\n return this;\\n }\\n data = this.__data__ = new MapCache(pairs);\\n }\\n data.set(key, value);\\n this.size = data.size;\\n return this;\\n }\\n module.exports = stackSet;\\n});\\n\\n// ../../../node_modules/lodash/_Stack.js\\nvar require_Stack = __commonJS((exports, module) => {\\n var ListCache = require_ListCache();\\n var stackClear = require_stackClear();\\n var stackDelete = require_stackDelete();\\n var stackGet = require_stackGet();\\n var stackHas = require_stackHas();\\n var stackSet = require_stackSet();\\n function Stack(entries) {\\n var data = this.__data__ = new ListCache(entries);\\n this.size = data.size;\\n }\\n Stack.prototype.clear = stackClear;\\n Stack.prototype[\\\\\\\"delete\\\\\\\"] = stackDelete;\\n Stack.prototype.get = stackGet;\\n Stack.prototype.has = stackHas;\\n Stack.prototype.set = stackSet;\\n module.exports = Stack;\\n});\\n\\n// ../../../node_modules/lodash/_arrayEach.js\\nvar require_arrayEach = __commonJS((exports, module) => {\\n function arrayEach(array, iteratee) {\\n var index = -1, length = array == null ? 0 : array.length;\\n while (++index < length) {\\n if (iteratee(array[index], index, array) === false) {\\n break;\\n }\\n }\\n return array;\\n }\\n module.exports = arrayEach;\\n});\\n\\n// ../../../node_modules/lodash/_defineProperty.js\\nvar require_defineProperty = __commonJS((exports, module) => {\\n var getNative = require_getNative();\\n var defineProperty = function() {\\n try {\\n var func = getNative(Object, \\\\\\\"defineProperty\\\\\\\");\\n func({}, \\\\\\\"\\\\\\\", {});\\n return func;\\n } catch (e) {\\n }\\n }();\\n module.exports = defineProperty;\\n});\\n\\n// ../../../node_modules/lodash/_baseAssignValue.js\\nvar require_baseAssignValue = __commonJS((exports, module) => {\\n var defineProperty = require_defineProperty();\\n function baseAssignValue(object, key, value) {\\n if (key == \\\\\\\"__proto__\\\\\\\" && defineProperty) {\\n defineProperty(object, key, {\\n configurable: true,\\n enumerable: true,\\n value,\\n writable: true\\n });\\n } else {\\n object[key] = value;\\n }\\n }\\n module.exports = baseAssignValue;\\n});\\n\\n// ../../../node_modules/lodash/_assignValue.js\\nvar require_assignValue = __commonJS((exports, module) => {\\n var baseAssignValue = require_baseAssignValue();\\n var eq = require_eq();\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n function assignValue(object, key, value) {\\n var objValue = object[key];\\n if (!(hasOwnProperty.call(object, key) && eq(objValue, value)) || value === void 0 && !(key in object)) {\\n baseAssignValue(object, key, value);\\n }\\n }\\n module.exports = assignValue;\\n});\\n\\n// ../../../node_modules/lodash/_copyObject.js\\nvar require_copyObject = __commonJS((exports, module) => {\\n var assignValue = require_assignValue();\\n var baseAssignValue = require_baseAssignValue();\\n function copyObject(source, props, object, customizer) {\\n var isNew = !object;\\n object || (object = {});\\n var index = -1, length = props.length;\\n while (++index < length) {\\n var key = props[index];\\n var newValue = customizer ? customizer(object[key], source[key], key, object, source) : void 0;\\n if (newValue === void 0) {\\n newValue = source[key];\\n }\\n if (isNew) {\\n baseAssignValue(object, key, newValue);\\n } else {\\n assignValue(object, key, newValue);\\n }\\n }\\n return object;\\n }\\n module.exports = copyObject;\\n});\\n\\n// ../../../node_modules/lodash/_baseTimes.js\\nvar require_baseTimes = __commonJS((exports, module) => {\\n function baseTimes(n, iteratee) {\\n var index = -1, result = Array(n);\\n while (++index < n) {\\n result[index] = iteratee(index);\\n }\\n return result;\\n }\\n module.exports = baseTimes;\\n});\\n\\n// ../../../node_modules/lodash/isObjectLike.js\\nvar require_isObjectLike = __commonJS((exports, module) => {\\n function isObjectLike(value) {\\n return value != null && typeof value == \\\\\\\"object\\\\\\\";\\n }\\n module.exports = isObjectLike;\\n});\\n\\n// ../../../node_modules/lodash/_baseIsArguments.js\\nvar require_baseIsArguments = __commonJS((exports, module) => {\\n var baseGetTag = require_baseGetTag();\\n var isObjectLike = require_isObjectLike();\\n var argsTag = \\\\\\\"[object Arguments]\\\\\\\";\\n function baseIsArguments(value) {\\n return isObjectLike(value) && baseGetTag(value) == argsTag;\\n }\\n module.exports = baseIsArguments;\\n});\\n\\n// ../../../node_modules/lodash/isArguments.js\\nvar require_isArguments = __commonJS((exports, module) => {\\n var baseIsArguments = require_baseIsArguments();\\n var isObjectLike = require_isObjectLike();\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n var propertyIsEnumerable = objectProto.propertyIsEnumerable;\\n var isArguments = baseIsArguments(function() {\\n return arguments;\\n }()) ? baseIsArguments : function(value) {\\n return isObjectLike(value) && hasOwnProperty.call(value, \\\\\\\"callee\\\\\\\") && !propertyIsEnumerable.call(value, \\\\\\\"callee\\\\\\\");\\n };\\n module.exports = isArguments;\\n});\\n\\n// ../../../node_modules/lodash/isArray.js\\nvar require_isArray = __commonJS((exports, module) => {\\n var isArray = Array.isArray;\\n module.exports = isArray;\\n});\\n\\n// ../../../node_modules/lodash/stubFalse.js\\nvar require_stubFalse = __commonJS((exports, module) => {\\n function stubFalse() {\\n return false;\\n }\\n module.exports = stubFalse;\\n});\\n\\n// ../../../node_modules/lodash/isBuffer.js\\nvar require_isBuffer = __commonJS((exports, module) => {\\n var root = require_root();\\n var stubFalse = require_stubFalse();\\n var freeExports = typeof exports == \\\\\\\"object\\\\\\\" && exports && !exports.nodeType && exports;\\n var freeModule = freeExports && typeof module == \\\\\\\"object\\\\\\\" && module && !module.nodeType && module;\\n var moduleExports = freeModule && freeModule.exports === freeExports;\\n var Buffer2 = moduleExports ? root.Buffer : void 0;\\n var nativeIsBuffer = Buffer2 ? Buffer2.isBuffer : void 0;\\n var isBuffer = nativeIsBuffer || stubFalse;\\n module.exports = isBuffer;\\n});\\n\\n// ../../../node_modules/lodash/_isIndex.js\\nvar require_isIndex = __commonJS((exports, module) => {\\n var MAX_SAFE_INTEGER = 9007199254740991;\\n var reIsUint = /^(?:0|[1-9]\\\\d*)$/;\\n function isIndex(value, length) {\\n var type = typeof value;\\n length = length == null ? MAX_SAFE_INTEGER : length;\\n return !!length && (type == \\\\\\\"number\\\\\\\" || type != \\\\\\\"symbol\\\\\\\" && reIsUint.test(value)) && (value > -1 && value % 1 == 0 && value < length);\\n }\\n module.exports = isIndex;\\n});\\n\\n// ../../../node_modules/lodash/isLength.js\\nvar require_isLength = __commonJS((exports, module) => {\\n var MAX_SAFE_INTEGER = 9007199254740991;\\n function isLength(value) {\\n return typeof value == \\\\\\\"number\\\\\\\" && value > -1 && value % 1 == 0 && value <= MAX_SAFE_INTEGER;\\n }\\n module.exports = isLength;\\n});\\n\\n// ../../../node_modules/lodash/_baseIsTypedArray.js\\nvar require_baseIsTypedArray = __commonJS((exports, module) => {\\n var baseGetTag = require_baseGetTag();\\n var isLength = require_isLength();\\n var isObjectLike = require_isObjectLike();\\n var argsTag = \\\\\\\"[object Arguments]\\\\\\\";\\n var arrayTag = \\\\\\\"[object Array]\\\\\\\";\\n var boolTag = \\\\\\\"[object Boolean]\\\\\\\";\\n var dateTag = \\\\\\\"[object Date]\\\\\\\";\\n var errorTag = \\\\\\\"[object Error]\\\\\\\";\\n var funcTag = \\\\\\\"[object Function]\\\\\\\";\\n var mapTag = \\\\\\\"[object Map]\\\\\\\";\\n var numberTag = \\\\\\\"[object Number]\\\\\\\";\\n var objectTag = \\\\\\\"[object Object]\\\\\\\";\\n var regexpTag = \\\\\\\"[object RegExp]\\\\\\\";\\n var setTag = \\\\\\\"[object Set]\\\\\\\";\\n var stringTag = \\\\\\\"[object String]\\\\\\\";\\n var weakMapTag = \\\\\\\"[object WeakMap]\\\\\\\";\\n var arrayBufferTag = \\\\\\\"[object ArrayBuffer]\\\\\\\";\\n var dataViewTag = \\\\\\\"[object DataView]\\\\\\\";\\n var float32Tag = \\\\\\\"[object Float32Array]\\\\\\\";\\n var float64Tag = \\\\\\\"[object Float64Array]\\\\\\\";\\n var int8Tag = \\\\\\\"[object Int8Array]\\\\\\\";\\n var int16Tag = \\\\\\\"[object Int16Array]\\\\\\\";\\n var int32Tag = \\\\\\\"[object Int32Array]\\\\\\\";\\n var uint8Tag = \\\\\\\"[object Uint8Array]\\\\\\\";\\n var uint8ClampedTag = \\\\\\\"[object Uint8ClampedArray]\\\\\\\";\\n var uint16Tag = \\\\\\\"[object Uint16Array]\\\\\\\";\\n var uint32Tag = \\\\\\\"[object Uint32Array]\\\\\\\";\\n var typedArrayTags = {};\\n typedArrayTags[float32Tag] = typedArrayTags[float64Tag] = typedArrayTags[int8Tag] = typedArrayTags[int16Tag] = typedArrayTags[int32Tag] = typedArrayTags[uint8Tag] = typedArrayTags[uint8ClampedTag] = typedArrayTags[uint16Tag] = typedArrayTags[uint32Tag] = true;\\n typedArrayTags[argsTag] = typedArrayTags[arrayTag] = typedArrayTags[arrayBufferTag] = typedArrayTags[boolTag] = typedArrayTags[dataViewTag] = typedArrayTags[dateTag] = typedArrayTags[errorTag] = typedArrayTags[funcTag] = typedArrayTags[mapTag] = typedArrayTags[numberTag] = typedArrayTags[objectTag] = typedArrayTags[regexpTag] = typedArrayTags[setTag] = typedArrayTags[stringTag] = typedArrayTags[weakMapTag] = false;\\n function baseIsTypedArray(value) {\\n return isObjectLike(value) && isLength(value.length) && !!typedArrayTags[baseGetTag(value)];\\n }\\n module.exports = baseIsTypedArray;\\n});\\n\\n// ../../../node_modules/lodash/_baseUnary.js\\nvar require_baseUnary = __commonJS((exports, module) => {\\n function baseUnary(func) {\\n return function(value) {\\n return func(value);\\n };\\n }\\n module.exports = baseUnary;\\n});\\n\\n// ../../../node_modules/lodash/_nodeUtil.js\\nvar require_nodeUtil = __commonJS((exports, module) => {\\n var freeGlobal = require_freeGlobal();\\n var freeExports = typeof exports == \\\\\\\"object\\\\\\\" && exports && !exports.nodeType && exports;\\n var freeModule = freeExports && typeof module == \\\\\\\"object\\\\\\\" && module && !module.nodeType && module;\\n var moduleExports = freeModule && freeModule.exports === freeExports;\\n var freeProcess = moduleExports && freeGlobal.process;\\n var nodeUtil = function() {\\n try {\\n var types = freeModule && freeModule.require && freeModule.require(\\\\\\\"util\\\\\\\").types;\\n if (types) {\\n return types;\\n }\\n return freeProcess && freeProcess.binding && freeProcess.binding(\\\\\\\"util\\\\\\\");\\n } catch (e) {\\n }\\n }();\\n module.exports = nodeUtil;\\n});\\n\\n// ../../../node_modules/lodash/isTypedArray.js\\nvar require_isTypedArray = __commonJS((exports, module) => {\\n var baseIsTypedArray = require_baseIsTypedArray();\\n var baseUnary = require_baseUnary();\\n var nodeUtil = require_nodeUtil();\\n var nodeIsTypedArray = nodeUtil && nodeUtil.isTypedArray;\\n var isTypedArray = nodeIsTypedArray ? baseUnary(nodeIsTypedArray) : baseIsTypedArray;\\n module.exports = isTypedArray;\\n});\\n\\n// ../../../node_modules/lodash/_arrayLikeKeys.js\\nvar require_arrayLikeKeys = __commonJS((exports, module) => {\\n var baseTimes = require_baseTimes();\\n var isArguments = require_isArguments();\\n var isArray = require_isArray();\\n var isBuffer = require_isBuffer();\\n var isIndex = require_isIndex();\\n var isTypedArray = require_isTypedArray();\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n function arrayLikeKeys(value, inherited) {\\n var isArr = isArray(value), isArg = !isArr && isArguments(value), isBuff = !isArr && !isArg && isBuffer(value), isType = !isArr && !isArg && !isBuff && isTypedArray(value), skipIndexes = isArr || isArg || isBuff || isType, result = skipIndexes ? baseTimes(value.length, String) : [], length = result.length;\\n for (var key in value) {\\n if ((inherited || hasOwnProperty.call(value, key)) && !(skipIndexes && (key == \\\\\\\"length\\\\\\\" || isBuff && (key == \\\\\\\"offset\\\\\\\" || key == \\\\\\\"parent\\\\\\\") || isType && (key == \\\\\\\"buffer\\\\\\\" || key == \\\\\\\"byteLength\\\\\\\" || key == \\\\\\\"byteOffset\\\\\\\") || isIndex(key, length)))) {\\n result.push(key);\\n }\\n }\\n return result;\\n }\\n module.exports = arrayLikeKeys;\\n});\\n\\n// ../../../node_modules/lodash/_isPrototype.js\\nvar require_isPrototype = __commonJS((exports, module) => {\\n var objectProto = Object.prototype;\\n function isPrototype(value) {\\n var Ctor = value && value.constructor, proto = typeof Ctor == \\\\\\\"function\\\\\\\" && Ctor.prototype || objectProto;\\n return value === proto;\\n }\\n module.exports = isPrototype;\\n});\\n\\n// ../../../node_modules/lodash/_overArg.js\\nvar require_overArg = __commonJS((exports, module) => {\\n function overArg(func, transform) {\\n return function(arg) {\\n return func(transform(arg));\\n };\\n }\\n module.exports = overArg;\\n});\\n\\n// ../../../node_modules/lodash/_nativeKeys.js\\nvar require_nativeKeys = __commonJS((exports, module) => {\\n var overArg = require_overArg();\\n var nativeKeys = overArg(Object.keys, Object);\\n module.exports = nativeKeys;\\n});\\n\\n// ../../../node_modules/lodash/_baseKeys.js\\nvar require_baseKeys = __commonJS((exports, module) => {\\n var isPrototype = require_isPrototype();\\n var nativeKeys = require_nativeKeys();\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n function baseKeys(object) {\\n if (!isPrototype(object)) {\\n return nativeKeys(object);\\n }\\n var result = [];\\n for (var key in Object(object)) {\\n if (hasOwnProperty.call(object, key) && key != \\\\\\\"constructor\\\\\\\") {\\n result.push(key);\\n }\\n }\\n return result;\\n }\\n module.exports = baseKeys;\\n});\\n\\n// ../../../node_modules/lodash/isArrayLike.js\\nvar require_isArrayLike = __commonJS((exports, module) => {\\n var isFunction = require_isFunction();\\n var isLength = require_isLength();\\n function isArrayLike(value) {\\n return value != null && isLength(value.length) && !isFunction(value);\\n }\\n module.exports = isArrayLike;\\n});\\n\\n// ../../../node_modules/lodash/keys.js\\nvar require_keys = __commonJS((exports, module) => {\\n var arrayLikeKeys = require_arrayLikeKeys();\\n var baseKeys = require_baseKeys();\\n var isArrayLike = require_isArrayLike();\\n function keys(object) {\\n return isArrayLike(object) ? arrayLikeKeys(object) : baseKeys(object);\\n }\\n module.exports = keys;\\n});\\n\\n// ../../../node_modules/lodash/_baseAssign.js\\nvar require_baseAssign = __commonJS((exports, module) => {\\n var copyObject = require_copyObject();\\n var keys = require_keys();\\n function baseAssign(object, source) {\\n return object && copyObject(source, keys(source), object);\\n }\\n module.exports = baseAssign;\\n});\\n\\n// ../../../node_modules/lodash/_nativeKeysIn.js\\nvar require_nativeKeysIn = __commonJS((exports, module) => {\\n function nativeKeysIn(object) {\\n var result = [];\\n if (object != null) {\\n for (var key in Object(object)) {\\n result.push(key);\\n }\\n }\\n return result;\\n }\\n module.exports = nativeKeysIn;\\n});\\n\\n// ../../../node_modules/lodash/_baseKeysIn.js\\nvar require_baseKeysIn = __commonJS((exports, module) => {\\n var isObject = require_isObject();\\n var isPrototype = require_isPrototype();\\n var nativeKeysIn = require_nativeKeysIn();\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n function baseKeysIn(object) {\\n if (!isObject(object)) {\\n return nativeKeysIn(object);\\n }\\n var isProto = isPrototype(object), result = [];\\n for (var key in object) {\\n if (!(key == \\\\\\\"constructor\\\\\\\" && (isProto || !hasOwnProperty.call(object, key)))) {\\n result.push(key);\\n }\\n }\\n return result;\\n }\\n module.exports = baseKeysIn;\\n});\\n\\n// ../../../node_modules/lodash/keysIn.js\\nvar require_keysIn = __commonJS((exports, module) => {\\n var arrayLikeKeys = require_arrayLikeKeys();\\n var baseKeysIn = require_baseKeysIn();\\n var isArrayLike = require_isArrayLike();\\n function keysIn(object) {\\n return isArrayLike(object) ? arrayLikeKeys(object, true) : baseKeysIn(object);\\n }\\n module.exports = keysIn;\\n});\\n\\n// ../../../node_modules/lodash/_baseAssignIn.js\\nvar require_baseAssignIn = __commonJS((exports, module) => {\\n var copyObject = require_copyObject();\\n var keysIn = require_keysIn();\\n function baseAssignIn(object, source) {\\n return object && copyObject(source, keysIn(source), object);\\n }\\n module.exports = baseAssignIn;\\n});\\n\\n// ../../../node_modules/lodash/_cloneBuffer.js\\nvar require_cloneBuffer = __commonJS((exports, module) => {\\n var root = require_root();\\n var freeExports = typeof exports == \\\\\\\"object\\\\\\\" && exports && !exports.nodeType && exports;\\n var freeModule = freeExports && typeof module == \\\\\\\"object\\\\\\\" && module && !module.nodeType && module;\\n var moduleExports = freeModule && freeModule.exports === freeExports;\\n var Buffer2 = moduleExports ? root.Buffer : void 0;\\n var allocUnsafe = Buffer2 ? Buffer2.allocUnsafe : void 0;\\n function cloneBuffer(buffer, isDeep) {\\n if (isDeep) {\\n return buffer.slice();\\n }\\n var length = buffer.length, result = allocUnsafe ? allocUnsafe(length) : new buffer.constructor(length);\\n buffer.copy(result);\\n return result;\\n }\\n module.exports = cloneBuffer;\\n});\\n\\n// ../../../node_modules/lodash/_copyArray.js\\nvar require_copyArray = __commonJS((exports, module) => {\\n function copyArray2(source, array) {\\n var index = -1, length = source.length;\\n array || (array = Array(length));\\n while (++index < length) {\\n array[index] = source[index];\\n }\\n return array;\\n }\\n module.exports = copyArray2;\\n});\\n\\n// ../../../node_modules/lodash/_arrayFilter.js\\nvar require_arrayFilter = __commonJS((exports, module) => {\\n function arrayFilter(array, predicate) {\\n var index = -1, length = array == null ? 0 : array.length, resIndex = 0, result = [];\\n while (++index < length) {\\n var value = array[index];\\n if (predicate(value, index, array)) {\\n result[resIndex++] = value;\\n }\\n }\\n return result;\\n }\\n module.exports = arrayFilter;\\n});\\n\\n// ../../../node_modules/lodash/stubArray.js\\nvar require_stubArray = __commonJS((exports, module) => {\\n function stubArray() {\\n return [];\\n }\\n module.exports = stubArray;\\n});\\n\\n// ../../../node_modules/lodash/_getSymbols.js\\nvar require_getSymbols = __commonJS((exports, module) => {\\n var arrayFilter = require_arrayFilter();\\n var stubArray = require_stubArray();\\n var objectProto = Object.prototype;\\n var propertyIsEnumerable = objectProto.propertyIsEnumerable;\\n var nativeGetSymbols = Object.getOwnPropertySymbols;\\n var getSymbols = !nativeGetSymbols ? stubArray : function(object) {\\n if (object == null) {\\n return [];\\n }\\n object = Object(object);\\n return arrayFilter(nativeGetSymbols(object), function(symbol) {\\n return propertyIsEnumerable.call(object, symbol);\\n });\\n };\\n module.exports = getSymbols;\\n});\\n\\n// ../../../node_modules/lodash/_copySymbols.js\\nvar require_copySymbols = __commonJS((exports, module) => {\\n var copyObject = require_copyObject();\\n var getSymbols = require_getSymbols();\\n function copySymbols(source, object) {\\n return copyObject(source, getSymbols(source), object);\\n }\\n module.exports = copySymbols;\\n});\\n\\n// ../../../node_modules/lodash/_arrayPush.js\\nvar require_arrayPush = __commonJS((exports, module) => {\\n function arrayPush(array, values) {\\n var index = -1, length = values.length, offset = array.length;\\n while (++index < length) {\\n array[offset + index] = values[index];\\n }\\n return array;\\n }\\n module.exports = arrayPush;\\n});\\n\\n// ../../../node_modules/lodash/_getPrototype.js\\nvar require_getPrototype = __commonJS((exports, module) => {\\n var overArg = require_overArg();\\n var getPrototype = overArg(Object.getPrototypeOf, Object);\\n module.exports = getPrototype;\\n});\\n\\n// ../../../node_modules/lodash/_getSymbolsIn.js\\nvar require_getSymbolsIn = __commonJS((exports, module) => {\\n var arrayPush = require_arrayPush();\\n var getPrototype = require_getPrototype();\\n var getSymbols = require_getSymbols();\\n var stubArray = require_stubArray();\\n var nativeGetSymbols = Object.getOwnPropertySymbols;\\n var getSymbolsIn = !nativeGetSymbols ? stubArray : function(object) {\\n var result = [];\\n while (object) {\\n arrayPush(result, getSymbols(object));\\n object = getPrototype(object);\\n }\\n return result;\\n };\\n module.exports = getSymbolsIn;\\n});\\n\\n// ../../../node_modules/lodash/_copySymbolsIn.js\\nvar require_copySymbolsIn = __commonJS((exports, module) => {\\n var copyObject = require_copyObject();\\n var getSymbolsIn = require_getSymbolsIn();\\n function copySymbolsIn(source, object) {\\n return copyObject(source, getSymbolsIn(source), object);\\n }\\n module.exports = copySymbolsIn;\\n});\\n\\n// ../../../node_modules/lodash/_baseGetAllKeys.js\\nvar require_baseGetAllKeys = __commonJS((exports, module) => {\\n var arrayPush = require_arrayPush();\\n var isArray = require_isArray();\\n function baseGetAllKeys(object, keysFunc, symbolsFunc) {\\n var result = keysFunc(object);\\n return isArray(object) ? result : arrayPush(result, symbolsFunc(object));\\n }\\n module.exports = baseGetAllKeys;\\n});\\n\\n// ../../../node_modules/lodash/_getAllKeys.js\\nvar require_getAllKeys = __commonJS((exports, module) => {\\n var baseGetAllKeys = require_baseGetAllKeys();\\n var getSymbols = require_getSymbols();\\n var keys = require_keys();\\n function getAllKeys(object) {\\n return baseGetAllKeys(object, keys, getSymbols);\\n }\\n module.exports = getAllKeys;\\n});\\n\\n// ../../../node_modules/lodash/_getAllKeysIn.js\\nvar require_getAllKeysIn = __commonJS((exports, module) => {\\n var baseGetAllKeys = require_baseGetAllKeys();\\n var getSymbolsIn = require_getSymbolsIn();\\n var keysIn = require_keysIn();\\n function getAllKeysIn(object) {\\n return baseGetAllKeys(object, keysIn, getSymbolsIn);\\n }\\n module.exports = getAllKeysIn;\\n});\\n\\n// ../../../node_modules/lodash/_DataView.js\\nvar require_DataView = __commonJS((exports, module) => {\\n var getNative = require_getNative();\\n var root = require_root();\\n var DataView = getNative(root, \\\\\\\"DataView\\\\\\\");\\n module.exports = DataView;\\n});\\n\\n// ../../../node_modules/lodash/_Promise.js\\nvar require_Promise = __commonJS((exports, module) => {\\n var getNative = require_getNative();\\n var root = require_root();\\n var Promise2 = getNative(root, \\\\\\\"Promise\\\\\\\");\\n module.exports = Promise2;\\n});\\n\\n// ../../../node_modules/lodash/_Set.js\\nvar require_Set = __commonJS((exports, module) => {\\n var getNative = require_getNative();\\n var root = require_root();\\n var Set2 = getNative(root, \\\\\\\"Set\\\\\\\");\\n module.exports = Set2;\\n});\\n\\n// ../../../node_modules/lodash/_WeakMap.js\\nvar require_WeakMap = __commonJS((exports, module) => {\\n var getNative = require_getNative();\\n var root = require_root();\\n var WeakMap2 = getNative(root, \\\\\\\"WeakMap\\\\\\\");\\n module.exports = WeakMap2;\\n});\\n\\n// ../../../node_modules/lodash/_getTag.js\\nvar require_getTag = __commonJS((exports, module) => {\\n var DataView = require_DataView();\\n var Map2 = require_Map();\\n var Promise2 = require_Promise();\\n var Set2 = require_Set();\\n var WeakMap2 = require_WeakMap();\\n var baseGetTag = require_baseGetTag();\\n var toSource = require_toSource();\\n var mapTag = \\\\\\\"[object Map]\\\\\\\";\\n var objectTag = \\\\\\\"[object Object]\\\\\\\";\\n var promiseTag = \\\\\\\"[object Promise]\\\\\\\";\\n var setTag = \\\\\\\"[object Set]\\\\\\\";\\n var weakMapTag = \\\\\\\"[object WeakMap]\\\\\\\";\\n var dataViewTag = \\\\\\\"[object DataView]\\\\\\\";\\n var dataViewCtorString = toSource(DataView);\\n var mapCtorString = toSource(Map2);\\n var promiseCtorString = toSource(Promise2);\\n var setCtorString = toSource(Set2);\\n var weakMapCtorString = toSource(WeakMap2);\\n var getTag = baseGetTag;\\n if (DataView && getTag(new DataView(new ArrayBuffer(1))) != dataViewTag || Map2 && getTag(new Map2()) != mapTag || Promise2 && getTag(Promise2.resolve()) != promiseTag || Set2 && getTag(new Set2()) != setTag || WeakMap2 && getTag(new WeakMap2()) != weakMapTag) {\\n getTag = function(value) {\\n var result = baseGetTag(value), Ctor = result == objectTag ? value.constructor : void 0, ctorString = Ctor ? toSource(Ctor) : \\\\\\\"\\\\\\\";\\n if (ctorString) {\\n switch (ctorString) {\\n case dataViewCtorString:\\n return dataViewTag;\\n case mapCtorString:\\n return mapTag;\\n case promiseCtorString:\\n return promiseTag;\\n case setCtorString:\\n return setTag;\\n case weakMapCtorString:\\n return weakMapTag;\\n }\\n }\\n return result;\\n };\\n }\\n module.exports = getTag;\\n});\\n\\n// ../../../node_modules/lodash/_initCloneArray.js\\nvar require_initCloneArray = __commonJS((exports, module) => {\\n var objectProto = Object.prototype;\\n var hasOwnProperty = objectProto.hasOwnProperty;\\n function initCloneArray(array) {\\n var length = array.length, result = new array.constructor(length);\\n if (length && typeof array[0] == \\\\\\\"string\\\\\\\" && hasOwnProperty.call(array, \\\\\\\"index\\\\\\\")) {\\n result.index = array.index;\\n result.input = array.input;\\n }\\n return result;\\n }\\n module.exports = initCloneArray;\\n});\\n\\n// ../../../node_modules/lodash/_Uint8Array.js\\nvar require_Uint8Array = __commonJS((exports, module) => {\\n var root = require_root();\\n var Uint8Array2 = root.Uint8Array;\\n module.exports = Uint8Array2;\\n});\\n\\n// ../../../node_modules/lodash/_cloneArrayBuffer.js\\nvar require_cloneArrayBuffer = __commonJS((exports, module) => {\\n var Uint8Array2 = require_Uint8Array();\\n function cloneArrayBuffer(arrayBuffer) {\\n var result = new arrayBuffer.constructor(arrayBuffer.byteLength);\\n new Uint8Array2(result).set(new Uint8Array2(arrayBuffer));\\n return result;\\n }\\n module.exports = cloneArrayBuffer;\\n});\\n\\n// ../../../node_modules/lodash/_cloneDataView.js\\nvar require_cloneDataView = __commonJS((exports, module) => {\\n var cloneArrayBuffer = require_cloneArrayBuffer();\\n function cloneDataView(dataView, isDeep) {\\n var buffer = isDeep ? cloneArrayBuffer(dataView.buffer) : dataView.buffer;\\n return new dataView.constructor(buffer, dataView.byteOffset, dataView.byteLength);\\n }\\n module.exports = cloneDataView;\\n});\\n\\n// ../../../node_modules/lodash/_cloneRegExp.js\\nvar require_cloneRegExp = __commonJS((exports, module) => {\\n var reFlags = /\\\\w*$/;\\n function cloneRegExp(regexp) {\\n var result = new regexp.constructor(regexp.source, reFlags.exec(regexp));\\n result.lastIndex = regexp.lastIndex;\\n return result;\\n }\\n module.exports = cloneRegExp;\\n});\\n\\n// ../../../node_modules/lodash/_cloneSymbol.js\\nvar require_cloneSymbol = __commonJS((exports, module) => {\\n var Symbol2 = require_Symbol();\\n var symbolProto = Symbol2 ? Symbol2.prototype : void 0;\\n var symbolValueOf = symbolProto ? symbolProto.valueOf : void 0;\\n function cloneSymbol(symbol) {\\n return symbolValueOf ? Object(symbolValueOf.call(symbol)) : {};\\n }\\n module.exports = cloneSymbol;\\n});\\n\\n// ../../../node_modules/lodash/_cloneTypedArray.js\\nvar require_cloneTypedArray = __commonJS((exports, module) => {\\n var cloneArrayBuffer = require_cloneArrayBuffer();\\n function cloneTypedArray(typedArray, isDeep) {\\n var buffer = isDeep ? cloneArrayBuffer(typedArray.buffer) : typedArray.buffer;\\n return new typedArray.constructor(buffer, typedArray.byteOffset, typedArray.length);\\n }\\n module.exports = cloneTypedArray;\\n});\\n\\n// ../../../node_modules/lodash/_initCloneByTag.js\\nvar require_initCloneByTag = __commonJS((exports, module) => {\\n var cloneArrayBuffer = require_cloneArrayBuffer();\\n var cloneDataView = require_cloneDataView();\\n var cloneRegExp = require_cloneRegExp();\\n var cloneSymbol = require_cloneSymbol();\\n var cloneTypedArray = require_cloneTypedArray();\\n var boolTag = \\\\\\\"[object Boolean]\\\\\\\";\\n var dateTag = \\\\\\\"[object Date]\\\\\\\";\\n var mapTag = \\\\\\\"[object Map]\\\\\\\";\\n var numberTag = \\\\\\\"[object Number]\\\\\\\";\\n var regexpTag = \\\\\\\"[object RegExp]\\\\\\\";\\n var setTag = \\\\\\\"[object Set]\\\\\\\";\\n var stringTag = \\\\\\\"[object String]\\\\\\\";\\n var symbolTag = \\\\\\\"[object Symbol]\\\\\\\";\\n var arrayBufferTag = \\\\\\\"[object ArrayBuffer]\\\\\\\";\\n var dataViewTag = \\\\\\\"[object DataView]\\\\\\\";\\n var float32Tag = \\\\\\\"[object Float32Array]\\\\\\\";\\n var float64Tag = \\\\\\\"[object Float64Array]\\\\\\\";\\n var int8Tag = \\\\\\\"[object Int8Array]\\\\\\\";\\n var int16Tag = \\\\\\\"[object Int16Array]\\\\\\\";\\n var int32Tag = \\\\\\\"[object Int32Array]\\\\\\\";\\n var uint8Tag = \\\\\\\"[object Uint8Array]\\\\\\\";\\n var uint8ClampedTag = \\\\\\\"[object Uint8ClampedArray]\\\\\\\";\\n var uint16Tag = \\\\\\\"[object Uint16Array]\\\\\\\";\\n var uint32Tag = \\\\\\\"[object Uint32Array]\\\\\\\";\\n function initCloneByTag(object, tag, isDeep) {\\n var Ctor = object.constructor;\\n switch (tag) {\\n case arrayBufferTag:\\n return cloneArrayBuffer(object);\\n case boolTag:\\n case dateTag:\\n return new Ctor(+object);\\n case dataViewTag:\\n return cloneDataView(object, isDeep);\\n case float32Tag:\\n case float64Tag:\\n case int8Tag:\\n case int16Tag:\\n case int32Tag:\\n case uint8Tag:\\n case uint8ClampedTag:\\n case uint16Tag:\\n case uint32Tag:\\n return cloneTypedArray(object, isDeep);\\n case mapTag:\\n return new Ctor();\\n case numberTag:\\n case stringTag:\\n return new Ctor(object);\\n case regexpTag:\\n return cloneRegExp(object);\\n case setTag:\\n return new Ctor();\\n case symbolTag:\\n return cloneSymbol(object);\\n }\\n }\\n module.exports = initCloneByTag;\\n});\\n\\n// ../../../node_modules/lodash/_baseCreate.js\\nvar require_baseCreate = __commonJS((exports, module) => {\\n var isObject = require_isObject();\\n var objectCreate = Object.create;\\n var baseCreate = function() {\\n function object() {\\n }\\n return function(proto) {\\n if (!isObject(proto)) {\\n return {};\\n }\\n if (objectCreate) {\\n return objectCreate(proto);\\n }\\n object.prototype = proto;\\n var result = new object();\\n object.prototype = void 0;\\n return result;\\n };\\n }();\\n module.exports = baseCreate;\\n});\\n\\n// ../../../node_modules/lodash/_initCloneObject.js\\nvar require_initCloneObject = __commonJS((exports, module) => {\\n var baseCreate = require_baseCreate();\\n var getPrototype = require_getPrototype();\\n var isPrototype = require_isPrototype();\\n function initCloneObject(object) {\\n return typeof object.constructor == \\\\\\\"function\\\\\\\" && !isPrototype(object) ? baseCreate(getPrototype(object)) : {};\\n }\\n module.exports = initCloneObject;\\n});\\n\\n// ../../../node_modules/lodash/_baseIsMap.js\\nvar require_baseIsMap = __commonJS((exports, module) => {\\n var getTag = require_getTag();\\n var isObjectLike = require_isObjectLike();\\n var mapTag = \\\\\\\"[object Map]\\\\\\\";\\n function baseIsMap(value) {\\n return isObjectLike(value) && getTag(value) == mapTag;\\n }\\n module.exports = baseIsMap;\\n});\\n\\n// ../../../node_modules/lodash/isMap.js\\nvar require_isMap = __commonJS((exports, module) => {\\n var baseIsMap = require_baseIsMap();\\n var baseUnary = require_baseUnary();\\n var nodeUtil = require_nodeUtil();\\n var nodeIsMap = nodeUtil && nodeUtil.isMap;\\n var isMap = nodeIsMap ? baseUnary(nodeIsMap) : baseIsMap;\\n module.exports = isMap;\\n});\\n\\n// ../../../node_modules/lodash/_baseIsSet.js\\nvar require_baseIsSet = __commonJS((exports, module) => {\\n var getTag = require_getTag();\\n var isObjectLike = require_isObjectLike();\\n var setTag = \\\\\\\"[object Set]\\\\\\\";\\n function baseIsSet(value) {\\n return isObjectLike(value) && getTag(value) == setTag;\\n }\\n module.exports = baseIsSet;\\n});\\n\\n// ../../../node_modules/lodash/isSet.js\\nvar require_isSet = __commonJS((exports, module) => {\\n var baseIsSet = require_baseIsSet();\\n var baseUnary = require_baseUnary();\\n var nodeUtil = require_nodeUtil();\\n var nodeIsSet = nodeUtil && nodeUtil.isSet;\\n var isSet = nodeIsSet ? baseUnary(nodeIsSet) : baseIsSet;\\n module.exports = isSet;\\n});\\n\\n// ../../../node_modules/lodash/_baseClone.js\\nvar require_baseClone = __commonJS((exports, module) => {\\n var Stack = require_Stack();\\n var arrayEach = require_arrayEach();\\n var assignValue = require_assignValue();\\n var baseAssign = require_baseAssign();\\n var baseAssignIn = require_baseAssignIn();\\n var cloneBuffer = require_cloneBuffer();\\n var copyArray2 = require_copyArray();\\n var copySymbols = require_copySymbols();\\n var copySymbolsIn = require_copySymbolsIn();\\n var getAllKeys = require_getAllKeys();\\n var getAllKeysIn = require_getAllKeysIn();\\n var getTag = require_getTag();\\n var initCloneArray = require_initCloneArray();\\n var initCloneByTag = require_initCloneByTag();\\n var initCloneObject = require_initCloneObject();\\n var isArray = require_isArray();\\n var isBuffer = require_isBuffer();\\n var isMap = require_isMap();\\n var isObject = require_isObject();\\n var isSet = require_isSet();\\n var keys = require_keys();\\n var keysIn = require_keysIn();\\n var CLONE_DEEP_FLAG = 1;\\n var CLONE_FLAT_FLAG = 2;\\n var CLONE_SYMBOLS_FLAG = 4;\\n var argsTag = \\\\\\\"[object Arguments]\\\\\\\";\\n var arrayTag = \\\\\\\"[object Array]\\\\\\\";\\n var boolTag = \\\\\\\"[object Boolean]\\\\\\\";\\n var dateTag = \\\\\\\"[object Date]\\\\\\\";\\n var errorTag = \\\\\\\"[object Error]\\\\\\\";\\n var funcTag = \\\\\\\"[object Function]\\\\\\\";\\n var genTag = \\\\\\\"[object GeneratorFunction]\\\\\\\";\\n var mapTag = \\\\\\\"[object Map]\\\\\\\";\\n var numberTag = \\\\\\\"[object Number]\\\\\\\";\\n var objectTag = \\\\\\\"[object Object]\\\\\\\";\\n var regexpTag = \\\\\\\"[object RegExp]\\\\\\\";\\n var setTag = \\\\\\\"[object Set]\\\\\\\";\\n var stringTag = \\\\\\\"[object String]\\\\\\\";\\n var symbolTag = \\\\\\\"[object Symbol]\\\\\\\";\\n var weakMapTag = \\\\\\\"[object WeakMap]\\\\\\\";\\n var arrayBufferTag = \\\\\\\"[object ArrayBuffer]\\\\\\\";\\n var dataViewTag = \\\\\\\"[object DataView]\\\\\\\";\\n var float32Tag = \\\\\\\"[object Float32Array]\\\\\\\";\\n var float64Tag = \\\\\\\"[object Float64Array]\\\\\\\";\\n var int8Tag = \\\\\\\"[object Int8Array]\\\\\\\";\\n var int16Tag = \\\\\\\"[object Int16Array]\\\\\\\";\\n var int32Tag = \\\\\\\"[object Int32Array]\\\\\\\";\\n var uint8Tag = \\\\\\\"[object Uint8Array]\\\\\\\";\\n var uint8ClampedTag = \\\\\\\"[object Uint8ClampedArray]\\\\\\\";\\n var uint16Tag = \\\\\\\"[object Uint16Array]\\\\\\\";\\n var uint32Tag = \\\\\\\"[object Uint32Array]\\\\\\\";\\n var cloneableTags = {};\\n cloneableTags[argsTag] = cloneableTags[arrayTag] = cloneableTags[arrayBufferTag] = cloneableTags[dataViewTag] = cloneableTags[boolTag] = cloneableTags[dateTag] = cloneableTags[float32Tag] = cloneableTags[float64Tag] = cloneableTags[int8Tag] = cloneableTags[int16Tag] = cloneableTags[int32Tag] = cloneableTags[mapTag] = cloneableTags[numberTag] = cloneableTags[objectTag] = cloneableTags[regexpTag] = cloneableTags[setTag] = cloneableTags[stringTag] = cloneableTags[symbolTag] = cloneableTags[uint8Tag] = cloneableTags[uint8ClampedTag] = cloneableTags[uint16Tag] = cloneableTags[uint32Tag] = true;\\n cloneableTags[errorTag] = cloneableTags[funcTag] = cloneableTags[weakMapTag] = false;\\n function baseClone(value, bitmask, customizer, key, object, stack) {\\n var result, isDeep = bitmask & CLONE_DEEP_FLAG, isFlat = bitmask & CLONE_FLAT_FLAG, isFull = bitmask & CLONE_SYMBOLS_FLAG;\\n if (customizer) {\\n result = object ? customizer(value, key, object, stack) : customizer(value);\\n }\\n if (result !== void 0) {\\n return result;\\n }\\n if (!isObject(value)) {\\n return value;\\n }\\n var isArr = isArray(value);\\n if (isArr) {\\n result = initCloneArray(value);\\n if (!isDeep) {\\n return copyArray2(value, result);\\n }\\n } else {\\n var tag = getTag(value), isFunc = tag == funcTag || tag == genTag;\\n if (isBuffer(value)) {\\n return cloneBuffer(value, isDeep);\\n }\\n if (tag == objectTag || tag == argsTag || isFunc && !object) {\\n result = isFlat || isFunc ? {} : initCloneObject(value);\\n if (!isDeep) {\\n return isFlat ? copySymbolsIn(value, baseAssignIn(result, value)) : copySymbols(value, baseAssign(result, value));\\n }\\n } else {\\n if (!cloneableTags[tag]) {\\n return object ? value : {};\\n }\\n result = initCloneByTag(value, tag, isDeep);\\n }\\n }\\n stack || (stack = new Stack());\\n var stacked = stack.get(value);\\n if (stacked) {\\n return stacked;\\n }\\n stack.set(value, result);\\n if (isSet(value)) {\\n value.forEach(function(subValue) {\\n result.add(baseClone(subValue, bitmask, customizer, subValue, value, stack));\\n });\\n } else if (isMap(value)) {\\n value.forEach(function(subValue, key2) {\\n result.set(key2, baseClone(subValue, bitmask, customizer, key2, value, stack));\\n });\\n }\\n var keysFunc = isFull ? isFlat ? getAllKeysIn : getAllKeys : isFlat ? keysIn : keys;\\n var props = isArr ? void 0 : keysFunc(value);\\n arrayEach(props || value, function(subValue, key2) {\\n if (props) {\\n key2 = subValue;\\n subValue = value[key2];\\n }\\n assignValue(result, key2, baseClone(subValue, bitmask, customizer, key2, value, stack));\\n });\\n return result;\\n }\\n module.exports = baseClone;\\n});\\n\\n// ../../../node_modules/lodash/cloneDeep.js\\nvar require_cloneDeep = __commonJS((exports, module) => {\\n var baseClone = require_baseClone();\\n var CLONE_DEEP_FLAG = 1;\\n var CLONE_SYMBOLS_FLAG = 4;\\n function cloneDeep(value) {\\n return baseClone(value, CLONE_DEEP_FLAG | CLONE_SYMBOLS_FLAG);\\n }\\n module.exports = cloneDeep;\\n});\\n\\n// ../../../node_modules/lodash/clone.js\\nvar require_clone = __commonJS((exports, module) => {\\n var baseClone = require_baseClone();\\n var CLONE_SYMBOLS_FLAG = 4;\\n function clone(value) {\\n return baseClone(value, CLONE_SYMBOLS_FLAG);\\n }\\n module.exports = clone;\\n});\\n\\n// ../../../node_modules/jsep/build/jsep.js\\nvar require_jsep = __commonJS((exports, module) => {\\n (function(root) {\\n \\\\\\\"use strict\\\\\\\";\\n var COMPOUND = \\\\\\\"Compound\\\\\\\", IDENTIFIER = \\\\\\\"Identifier\\\\\\\", MEMBER_EXP = \\\\\\\"MemberExpression\\\\\\\", LITERAL = \\\\\\\"Literal\\\\\\\", THIS_EXP = \\\\\\\"ThisExpression\\\\\\\", CALL_EXP = \\\\\\\"CallExpression\\\\\\\", UNARY_EXP = \\\\\\\"UnaryExpression\\\\\\\", BINARY_EXP = \\\\\\\"BinaryExpression\\\\\\\", LOGICAL_EXP = \\\\\\\"LogicalExpression\\\\\\\", CONDITIONAL_EXP = \\\\\\\"ConditionalExpression\\\\\\\", ARRAY_EXP = \\\\\\\"ArrayExpression\\\\\\\", PERIOD_CODE = 46, COMMA_CODE = 44, SQUOTE_CODE = 39, DQUOTE_CODE = 34, OPAREN_CODE = 40, CPAREN_CODE = 41, OBRACK_CODE = 91, CBRACK_CODE = 93, QUMARK_CODE = 63, SEMCOL_CODE = 59, COLON_CODE = 58, throwError = function(message, index) {\\n var error = new Error(message + \\\\\\\" at character \\\\\\\" + index);\\n error.index = index;\\n error.description = message;\\n throw error;\\n }, t = true, unary_ops = {\\\\\\\"-\\\\\\\": t, \\\\\\\"!\\\\\\\": t, \\\\\\\"~\\\\\\\": t, \\\\\\\"+\\\\\\\": t}, binary_ops = {\\n \\\\\\\"||\\\\\\\": 1,\\n \\\\\\\"&&\\\\\\\": 2,\\n \\\\\\\"|\\\\\\\": 3,\\n \\\\\\\"^\\\\\\\": 4,\\n \\\\\\\"&\\\\\\\": 5,\\n \\\\\\\"==\\\\\\\": 6,\\n \\\\\\\"!=\\\\\\\": 6,\\n \\\\\\\"===\\\\\\\": 6,\\n \\\\\\\"!==\\\\\\\": 6,\\n \\\\\\\"<\\\\\\\": 7,\\n \\\\\\\">\\\\\\\": 7,\\n \\\\\\\"<=\\\\\\\": 7,\\n \\\\\\\">=\\\\\\\": 7,\\n \\\\\\\"<<\\\\\\\": 8,\\n \\\\\\\">>\\\\\\\": 8,\\n \\\\\\\">>>\\\\\\\": 8,\\n \\\\\\\"+\\\\\\\": 9,\\n \\\\\\\"-\\\\\\\": 9,\\n \\\\\\\"*\\\\\\\": 10,\\n \\\\\\\"/\\\\\\\": 10,\\n \\\\\\\"%\\\\\\\": 10\\n }, getMaxKeyLen = function(obj) {\\n var max_len = 0, len;\\n for (var key in obj) {\\n if ((len = key.length) > max_len && obj.hasOwnProperty(key)) {\\n max_len = len;\\n }\\n }\\n return max_len;\\n }, max_unop_len = getMaxKeyLen(unary_ops), max_binop_len = getMaxKeyLen(binary_ops), literals = {\\n true: true,\\n false: false,\\n null: null\\n }, this_str = \\\\\\\"this\\\\\\\", binaryPrecedence = function(op_val) {\\n return binary_ops[op_val] || 0;\\n }, createBinaryExpression = function(operator, left, right) {\\n var type = operator === \\\\\\\"||\\\\\\\" || operator === \\\\\\\"&&\\\\\\\" ? LOGICAL_EXP : BINARY_EXP;\\n return {\\n type,\\n operator,\\n left,\\n right\\n };\\n }, isDecimalDigit = function(ch) {\\n return ch >= 48 && ch <= 57;\\n }, isIdentifierStart = function(ch) {\\n return ch === 36 || ch === 95 || ch >= 65 && ch <= 90 || ch >= 97 && ch <= 122 || ch >= 128 && !binary_ops[String.fromCharCode(ch)];\\n }, isIdentifierPart = function(ch) {\\n return ch === 36 || ch === 95 || ch >= 65 && ch <= 90 || ch >= 97 && ch <= 122 || ch >= 48 && ch <= 57 || ch >= 128 && !binary_ops[String.fromCharCode(ch)];\\n }, jsep2 = function(expr) {\\n var index = 0, charAtFunc = expr.charAt, charCodeAtFunc = expr.charCodeAt, exprI = function(i) {\\n return charAtFunc.call(expr, i);\\n }, exprICode = function(i) {\\n return charCodeAtFunc.call(expr, i);\\n }, length = expr.length, gobbleSpaces = function() {\\n var ch = exprICode(index);\\n while (ch === 32 || ch === 9 || ch === 10 || ch === 13) {\\n ch = exprICode(++index);\\n }\\n }, gobbleExpression = function() {\\n var test = gobbleBinaryExpression(), consequent, alternate;\\n gobbleSpaces();\\n if (exprICode(index) === QUMARK_CODE) {\\n index++;\\n consequent = gobbleExpression();\\n if (!consequent) {\\n throwError(\\\\\\\"Expected expression\\\\\\\", index);\\n }\\n gobbleSpaces();\\n if (exprICode(index) === COLON_CODE) {\\n index++;\\n alternate = gobbleExpression();\\n if (!alternate) {\\n throwError(\\\\\\\"Expected expression\\\\\\\", index);\\n }\\n return {\\n type: CONDITIONAL_EXP,\\n test,\\n consequent,\\n alternate\\n };\\n } else {\\n throwError(\\\\\\\"Expected :\\\\\\\", index);\\n }\\n } else {\\n return test;\\n }\\n }, gobbleBinaryOp = function() {\\n gobbleSpaces();\\n var biop, to_check = expr.substr(index, max_binop_len), tc_len = to_check.length;\\n while (tc_len > 0) {\\n if (binary_ops.hasOwnProperty(to_check) && (!isIdentifierStart(exprICode(index)) || index + to_check.length < expr.length && !isIdentifierPart(exprICode(index + to_check.length)))) {\\n index += tc_len;\\n return to_check;\\n }\\n to_check = to_check.substr(0, --tc_len);\\n }\\n return false;\\n }, gobbleBinaryExpression = function() {\\n var ch_i2, node2, biop, prec, stack, biop_info, left, right, i, cur_biop;\\n left = gobbleToken();\\n biop = gobbleBinaryOp();\\n if (!biop) {\\n return left;\\n }\\n biop_info = {value: biop, prec: binaryPrecedence(biop)};\\n right = gobbleToken();\\n if (!right) {\\n throwError(\\\\\\\"Expected expression after \\\\\\\" + biop, index);\\n }\\n stack = [left, biop_info, right];\\n while (biop = gobbleBinaryOp()) {\\n prec = binaryPrecedence(biop);\\n if (prec === 0) {\\n break;\\n }\\n biop_info = {value: biop, prec};\\n cur_biop = biop;\\n while (stack.length > 2 && prec <= stack[stack.length - 2].prec) {\\n right = stack.pop();\\n biop = stack.pop().value;\\n left = stack.pop();\\n node2 = createBinaryExpression(biop, left, right);\\n stack.push(node2);\\n }\\n node2 = gobbleToken();\\n if (!node2) {\\n throwError(\\\\\\\"Expected expression after \\\\\\\" + cur_biop, index);\\n }\\n stack.push(biop_info, node2);\\n }\\n i = stack.length - 1;\\n node2 = stack[i];\\n while (i > 1) {\\n node2 = createBinaryExpression(stack[i - 1].value, stack[i - 2], node2);\\n i -= 2;\\n }\\n return node2;\\n }, gobbleToken = function() {\\n var ch, to_check, tc_len;\\n gobbleSpaces();\\n ch = exprICode(index);\\n if (isDecimalDigit(ch) || ch === PERIOD_CODE) {\\n return gobbleNumericLiteral();\\n } else if (ch === SQUOTE_CODE || ch === DQUOTE_CODE) {\\n return gobbleStringLiteral();\\n } else if (ch === OBRACK_CODE) {\\n return gobbleArray();\\n } else {\\n to_check = expr.substr(index, max_unop_len);\\n tc_len = to_check.length;\\n while (tc_len > 0) {\\n if (unary_ops.hasOwnProperty(to_check) && (!isIdentifierStart(exprICode(index)) || index + to_check.length < expr.length && !isIdentifierPart(exprICode(index + to_check.length)))) {\\n index += tc_len;\\n return {\\n type: UNARY_EXP,\\n operator: to_check,\\n argument: gobbleToken(),\\n prefix: true\\n };\\n }\\n to_check = to_check.substr(0, --tc_len);\\n }\\n if (isIdentifierStart(ch) || ch === OPAREN_CODE) {\\n return gobbleVariable();\\n }\\n }\\n return false;\\n }, gobbleNumericLiteral = function() {\\n var number = \\\\\\\"\\\\\\\", ch, chCode;\\n while (isDecimalDigit(exprICode(index))) {\\n number += exprI(index++);\\n }\\n if (exprICode(index) === PERIOD_CODE) {\\n number += exprI(index++);\\n while (isDecimalDigit(exprICode(index))) {\\n number += exprI(index++);\\n }\\n }\\n ch = exprI(index);\\n if (ch === \\\\\\\"e\\\\\\\" || ch === \\\\\\\"E\\\\\\\") {\\n number += exprI(index++);\\n ch = exprI(index);\\n if (ch === \\\\\\\"+\\\\\\\" || ch === \\\\\\\"-\\\\\\\") {\\n number += exprI(index++);\\n }\\n while (isDecimalDigit(exprICode(index))) {\\n number += exprI(index++);\\n }\\n if (!isDecimalDigit(exprICode(index - 1))) {\\n throwError(\\\\\\\"Expected exponent (\\\\\\\" + number + exprI(index) + \\\\\\\")\\\\\\\", index);\\n }\\n }\\n chCode = exprICode(index);\\n if (isIdentifierStart(chCode)) {\\n throwError(\\\\\\\"Variable names cannot start with a number (\\\\\\\" + number + exprI(index) + \\\\\\\")\\\\\\\", index);\\n } else if (chCode === PERIOD_CODE) {\\n throwError(\\\\\\\"Unexpected period\\\\\\\", index);\\n }\\n return {\\n type: LITERAL,\\n value: parseFloat(number),\\n raw: number\\n };\\n }, gobbleStringLiteral = function() {\\n var str = \\\\\\\"\\\\\\\", quote = exprI(index++), closed = false, ch;\\n while (index < length) {\\n ch = exprI(index++);\\n if (ch === quote) {\\n closed = true;\\n break;\\n } else if (ch === \\\\\\\"\\\\\\\\\\\\\\\") {\\n ch = exprI(index++);\\n switch (ch) {\\n case \\\\\\\"n\\\\\\\":\\n str += \\\\\\\"\\\\n\\\\\\\";\\n break;\\n case \\\\\\\"r\\\\\\\":\\n str += \\\\\\\"\\\\r\\\\\\\";\\n break;\\n case \\\\\\\"t\\\\\\\":\\n str += \\\\\\\"\\t\\\\\\\";\\n break;\\n case \\\\\\\"b\\\\\\\":\\n str += \\\\\\\"\\\\b\\\\\\\";\\n break;\\n case \\\\\\\"f\\\\\\\":\\n str += \\\\\\\"\\\\f\\\\\\\";\\n break;\\n case \\\\\\\"v\\\\\\\":\\n str += \\\\\\\"\\\\v\\\\\\\";\\n break;\\n default:\\n str += ch;\\n }\\n } else {\\n str += ch;\\n }\\n }\\n if (!closed) {\\n throwError('Unclosed quote after \\\\\\\"' + str + '\\\\\\\"', index);\\n }\\n return {\\n type: LITERAL,\\n value: str,\\n raw: quote + str + quote\\n };\\n }, gobbleIdentifier = function() {\\n var ch = exprICode(index), start = index, identifier;\\n if (isIdentifierStart(ch)) {\\n index++;\\n } else {\\n throwError(\\\\\\\"Unexpected \\\\\\\" + exprI(index), index);\\n }\\n while (index < length) {\\n ch = exprICode(index);\\n if (isIdentifierPart(ch)) {\\n index++;\\n } else {\\n break;\\n }\\n }\\n identifier = expr.slice(start, index);\\n if (literals.hasOwnProperty(identifier)) {\\n return {\\n type: LITERAL,\\n value: literals[identifier],\\n raw: identifier\\n };\\n } else if (identifier === this_str) {\\n return {type: THIS_EXP};\\n } else {\\n return {\\n type: IDENTIFIER,\\n name: identifier\\n };\\n }\\n }, gobbleArguments = function(termination) {\\n var ch_i2, args = [], node2, closed = false;\\n var separator_count = 0;\\n while (index < length) {\\n gobbleSpaces();\\n ch_i2 = exprICode(index);\\n if (ch_i2 === termination) {\\n closed = true;\\n index++;\\n if (termination === CPAREN_CODE && separator_count && separator_count >= args.length) {\\n throwError(\\\\\\\"Unexpected token \\\\\\\" + String.fromCharCode(termination), index);\\n }\\n break;\\n } else if (ch_i2 === COMMA_CODE) {\\n index++;\\n separator_count++;\\n if (separator_count !== args.length) {\\n if (termination === CPAREN_CODE) {\\n throwError(\\\\\\\"Unexpected token ,\\\\\\\", index);\\n } else if (termination === CBRACK_CODE) {\\n for (var arg = args.length; arg < separator_count; arg++) {\\n args.push(null);\\n }\\n }\\n }\\n } else {\\n node2 = gobbleExpression();\\n if (!node2 || node2.type === COMPOUND) {\\n throwError(\\\\\\\"Expected comma\\\\\\\", index);\\n }\\n args.push(node2);\\n }\\n }\\n if (!closed) {\\n throwError(\\\\\\\"Expected \\\\\\\" + String.fromCharCode(termination), index);\\n }\\n return args;\\n }, gobbleVariable = function() {\\n var ch_i2, node2;\\n ch_i2 = exprICode(index);\\n if (ch_i2 === OPAREN_CODE) {\\n node2 = gobbleGroup();\\n } else {\\n node2 = gobbleIdentifier();\\n }\\n gobbleSpaces();\\n ch_i2 = exprICode(index);\\n while (ch_i2 === PERIOD_CODE || ch_i2 === OBRACK_CODE || ch_i2 === OPAREN_CODE) {\\n index++;\\n if (ch_i2 === PERIOD_CODE) {\\n gobbleSpaces();\\n node2 = {\\n type: MEMBER_EXP,\\n computed: false,\\n object: node2,\\n property: gobbleIdentifier()\\n };\\n } else if (ch_i2 === OBRACK_CODE) {\\n node2 = {\\n type: MEMBER_EXP,\\n computed: true,\\n object: node2,\\n property: gobbleExpression()\\n };\\n gobbleSpaces();\\n ch_i2 = exprICode(index);\\n if (ch_i2 !== CBRACK_CODE) {\\n throwError(\\\\\\\"Unclosed [\\\\\\\", index);\\n }\\n index++;\\n } else if (ch_i2 === OPAREN_CODE) {\\n node2 = {\\n type: CALL_EXP,\\n arguments: gobbleArguments(CPAREN_CODE),\\n callee: node2\\n };\\n }\\n gobbleSpaces();\\n ch_i2 = exprICode(index);\\n }\\n return node2;\\n }, gobbleGroup = function() {\\n index++;\\n var node2 = gobbleExpression();\\n gobbleSpaces();\\n if (exprICode(index) === CPAREN_CODE) {\\n index++;\\n return node2;\\n } else {\\n throwError(\\\\\\\"Unclosed (\\\\\\\", index);\\n }\\n }, gobbleArray = function() {\\n index++;\\n return {\\n type: ARRAY_EXP,\\n elements: gobbleArguments(CBRACK_CODE)\\n };\\n }, nodes = [], ch_i, node;\\n while (index < length) {\\n ch_i = exprICode(index);\\n if (ch_i === SEMCOL_CODE || ch_i === COMMA_CODE) {\\n index++;\\n } else {\\n if (node = gobbleExpression()) {\\n nodes.push(node);\\n } else if (index < length) {\\n throwError('Unexpected \\\\\\\"' + exprI(index) + '\\\\\\\"', index);\\n }\\n }\\n }\\n if (nodes.length === 1) {\\n return nodes[0];\\n } else {\\n return {\\n type: COMPOUND,\\n body: nodes\\n };\\n }\\n };\\n jsep2.version = \\\\\\\"0.3.5\\\\\\\";\\n jsep2.toString = function() {\\n return \\\\\\\"JavaScript Expression Parser (JSEP) v\\\\\\\" + jsep2.version;\\n };\\n jsep2.addUnaryOp = function(op_name) {\\n max_unop_len = Math.max(op_name.length, max_unop_len);\\n unary_ops[op_name] = t;\\n return this;\\n };\\n jsep2.addBinaryOp = function(op_name, precedence2) {\\n max_binop_len = Math.max(op_name.length, max_binop_len);\\n binary_ops[op_name] = precedence2;\\n return this;\\n };\\n jsep2.addLiteral = function(literal_name, literal_value) {\\n literals[literal_name] = literal_value;\\n return this;\\n };\\n jsep2.removeUnaryOp = function(op_name) {\\n delete unary_ops[op_name];\\n if (op_name.length === max_unop_len) {\\n max_unop_len = getMaxKeyLen(unary_ops);\\n }\\n return this;\\n };\\n jsep2.removeAllUnaryOps = function() {\\n unary_ops = {};\\n max_unop_len = 0;\\n return this;\\n };\\n jsep2.removeBinaryOp = function(op_name) {\\n delete binary_ops[op_name];\\n if (op_name.length === max_binop_len) {\\n max_binop_len = getMaxKeyLen(binary_ops);\\n }\\n return this;\\n };\\n jsep2.removeAllBinaryOps = function() {\\n binary_ops = {};\\n max_binop_len = 0;\\n return this;\\n };\\n jsep2.removeLiteral = function(literal_name) {\\n delete literals[literal_name];\\n return this;\\n };\\n jsep2.removeAllLiterals = function() {\\n literals = {};\\n return this;\\n };\\n if (typeof exports === \\\\\\\"undefined\\\\\\\") {\\n var old_jsep = root.jsep;\\n root.jsep = jsep2;\\n jsep2.noConflict = function() {\\n if (root.jsep === jsep2) {\\n root.jsep = old_jsep;\\n }\\n return jsep2;\\n };\\n } else {\\n if (typeof module !== \\\\\\\"undefined\\\\\\\" && module.exports) {\\n exports = module.exports = jsep2;\\n } else {\\n exports.parse = jsep2;\\n }\\n }\\n })(exports);\\n});\\n\\n// ../../../node_modules/three/src/math/MathUtils.js\\nvar DEG2RAD = Math.PI / 180;\\nvar RAD2DEG = 180 / Math.PI;\\nvar _lut = [];\\nfor (let i = 0; i < 256; i++) {\\n _lut[i] = (i < 16 ? \\\\\\\"0\\\\\\\" : \\\\\\\"\\\\\\\") + i.toString(16);\\n}\\nvar hasRandomUUID = typeof crypto !== \\\\\\\"undefined\\\\\\\" && \\\\\\\"randomUUID\\\\\\\" in crypto;\\nfunction generateUUID() {\\n if (hasRandomUUID) {\\n return crypto.randomUUID().toUpperCase();\\n }\\n const d0 = Math.random() * 4294967295 | 0;\\n const d1 = Math.random() * 4294967295 | 0;\\n const d2 = Math.random() * 4294967295 | 0;\\n const d3 = Math.random() * 4294967295 | 0;\\n const uuid = _lut[d0 & 255] + _lut[d0 >> 8 & 255] + _lut[d0 >> 16 & 255] + _lut[d0 >> 24 & 255] + \\\\\\\"-\\\\\\\" + _lut[d1 & 255] + _lut[d1 >> 8 & 255] + \\\\\\\"-\\\\\\\" + _lut[d1 >> 16 & 15 | 64] + _lut[d1 >> 24 & 255] + \\\\\\\"-\\\\\\\" + _lut[d2 & 63 | 128] + _lut[d2 >> 8 & 255] + \\\\\\\"-\\\\\\\" + _lut[d2 >> 16 & 255] + _lut[d2 >> 24 & 255] + _lut[d3 & 255] + _lut[d3 >> 8 & 255] + _lut[d3 >> 16 & 255] + _lut[d3 >> 24 & 255];\\n return uuid.toUpperCase();\\n}\\nfunction clamp(value, min, max) {\\n return Math.max(min, Math.min(max, value));\\n}\\nfunction euclideanModulo(n, m) {\\n return (n % m + m) % m;\\n}\\nfunction lerp(x, y, t) {\\n return (1 - t) * x + t * y;\\n}\\nfunction degToRad(degrees) {\\n return degrees * DEG2RAD;\\n}\\nfunction isPowerOfTwo(value) {\\n return (value & value - 1) === 0 && value !== 0;\\n}\\nfunction floorPowerOfTwo(value) {\\n return Math.pow(2, Math.floor(Math.log(value) / Math.LN2));\\n}\\n\\n// ../../../node_modules/three/src/math/Quaternion.js\\nvar Quaternion = class {\\n constructor(x = 0, y = 0, z = 0, w = 1) {\\n this._x = x;\\n this._y = y;\\n this._z = z;\\n this._w = w;\\n }\\n static slerp(qa, qb, qm, t) {\\n console.warn(\\\\\\\"THREE.Quaternion: Static .slerp() has been deprecated. Use qm.slerpQuaternions( qa, qb, t ) instead.\\\\\\\");\\n return qm.slerpQuaternions(qa, qb, t);\\n }\\n static slerpFlat(dst, dstOffset, src0, srcOffset0, src1, srcOffset1, t) {\\n let x0 = src0[srcOffset0 + 0], y0 = src0[srcOffset0 + 1], z0 = src0[srcOffset0 + 2], w0 = src0[srcOffset0 + 3];\\n const x1 = src1[srcOffset1 + 0], y1 = src1[srcOffset1 + 1], z1 = src1[srcOffset1 + 2], w1 = src1[srcOffset1 + 3];\\n if (t === 0) {\\n dst[dstOffset + 0] = x0;\\n dst[dstOffset + 1] = y0;\\n dst[dstOffset + 2] = z0;\\n dst[dstOffset + 3] = w0;\\n return;\\n }\\n if (t === 1) {\\n dst[dstOffset + 0] = x1;\\n dst[dstOffset + 1] = y1;\\n dst[dstOffset + 2] = z1;\\n dst[dstOffset + 3] = w1;\\n return;\\n }\\n if (w0 !== w1 || x0 !== x1 || y0 !== y1 || z0 !== z1) {\\n let s = 1 - t;\\n const cos = x0 * x1 + y0 * y1 + z0 * z1 + w0 * w1, dir = cos >= 0 ? 1 : -1, sqrSin = 1 - cos * cos;\\n if (sqrSin > Number.EPSILON) {\\n const sin = Math.sqrt(sqrSin), len = Math.atan2(sin, cos * dir);\\n s = Math.sin(s * len) / sin;\\n t = Math.sin(t * len) / sin;\\n }\\n const tDir = t * dir;\\n x0 = x0 * s + x1 * tDir;\\n y0 = y0 * s + y1 * tDir;\\n z0 = z0 * s + z1 * tDir;\\n w0 = w0 * s + w1 * tDir;\\n if (s === 1 - t) {\\n const f = 1 / Math.sqrt(x0 * x0 + y0 * y0 + z0 * z0 + w0 * w0);\\n x0 *= f;\\n y0 *= f;\\n z0 *= f;\\n w0 *= f;\\n }\\n }\\n dst[dstOffset] = x0;\\n dst[dstOffset + 1] = y0;\\n dst[dstOffset + 2] = z0;\\n dst[dstOffset + 3] = w0;\\n }\\n static multiplyQuaternionsFlat(dst, dstOffset, src0, srcOffset0, src1, srcOffset1) {\\n const x0 = src0[srcOffset0];\\n const y0 = src0[srcOffset0 + 1];\\n const z0 = src0[srcOffset0 + 2];\\n const w0 = src0[srcOffset0 + 3];\\n const x1 = src1[srcOffset1];\\n const y1 = src1[srcOffset1 + 1];\\n const z1 = src1[srcOffset1 + 2];\\n const w1 = src1[srcOffset1 + 3];\\n dst[dstOffset] = x0 * w1 + w0 * x1 + y0 * z1 - z0 * y1;\\n dst[dstOffset + 1] = y0 * w1 + w0 * y1 + z0 * x1 - x0 * z1;\\n dst[dstOffset + 2] = z0 * w1 + w0 * z1 + x0 * y1 - y0 * x1;\\n dst[dstOffset + 3] = w0 * w1 - x0 * x1 - y0 * y1 - z0 * z1;\\n return dst;\\n }\\n get x() {\\n return this._x;\\n }\\n set x(value) {\\n this._x = value;\\n this._onChangeCallback();\\n }\\n get y() {\\n return this._y;\\n }\\n set y(value) {\\n this._y = value;\\n this._onChangeCallback();\\n }\\n get z() {\\n return this._z;\\n }\\n set z(value) {\\n this._z = value;\\n this._onChangeCallback();\\n }\\n get w() {\\n return this._w;\\n }\\n set w(value) {\\n this._w = value;\\n this._onChangeCallback();\\n }\\n set(x, y, z, w) {\\n this._x = x;\\n this._y = y;\\n this._z = z;\\n this._w = w;\\n this._onChangeCallback();\\n return this;\\n }\\n clone() {\\n return new this.constructor(this._x, this._y, this._z, this._w);\\n }\\n copy(quaternion) {\\n this._x = quaternion.x;\\n this._y = quaternion.y;\\n this._z = quaternion.z;\\n this._w = quaternion.w;\\n this._onChangeCallback();\\n return this;\\n }\\n setFromEuler(euler, update) {\\n if (!(euler && euler.isEuler)) {\\n throw new Error(\\\\\\\"THREE.Quaternion: .setFromEuler() now expects an Euler rotation rather than a Vector3 and order.\\\\\\\");\\n }\\n const x = euler._x, y = euler._y, z = euler._z, order = euler._order;\\n const cos = Math.cos;\\n const sin = Math.sin;\\n const c1 = cos(x / 2);\\n const c2 = cos(y / 2);\\n const c3 = cos(z / 2);\\n const s1 = sin(x / 2);\\n const s2 = sin(y / 2);\\n const s3 = sin(z / 2);\\n switch (order) {\\n case \\\\\\\"XYZ\\\\\\\":\\n this._x = s1 * c2 * c3 + c1 * s2 * s3;\\n this._y = c1 * s2 * c3 - s1 * c2 * s3;\\n this._z = c1 * c2 * s3 + s1 * s2 * c3;\\n this._w = c1 * c2 * c3 - s1 * s2 * s3;\\n break;\\n case \\\\\\\"YXZ\\\\\\\":\\n this._x = s1 * c2 * c3 + c1 * s2 * s3;\\n this._y = c1 * s2 * c3 - s1 * c2 * s3;\\n this._z = c1 * c2 * s3 - s1 * s2 * c3;\\n this._w = c1 * c2 * c3 + s1 * s2 * s3;\\n break;\\n case \\\\\\\"ZXY\\\\\\\":\\n this._x = s1 * c2 * c3 - c1 * s2 * s3;\\n this._y = c1 * s2 * c3 + s1 * c2 * s3;\\n this._z = c1 * c2 * s3 + s1 * s2 * c3;\\n this._w = c1 * c2 * c3 - s1 * s2 * s3;\\n break;\\n case \\\\\\\"ZYX\\\\\\\":\\n this._x = s1 * c2 * c3 - c1 * s2 * s3;\\n this._y = c1 * s2 * c3 + s1 * c2 * s3;\\n this._z = c1 * c2 * s3 - s1 * s2 * c3;\\n this._w = c1 * c2 * c3 + s1 * s2 * s3;\\n break;\\n case \\\\\\\"YZX\\\\\\\":\\n this._x = s1 * c2 * c3 + c1 * s2 * s3;\\n this._y = c1 * s2 * c3 + s1 * c2 * s3;\\n this._z = c1 * c2 * s3 - s1 * s2 * c3;\\n this._w = c1 * c2 * c3 - s1 * s2 * s3;\\n break;\\n case \\\\\\\"XZY\\\\\\\":\\n this._x = s1 * c2 * c3 - c1 * s2 * s3;\\n this._y = c1 * s2 * c3 - s1 * c2 * s3;\\n this._z = c1 * c2 * s3 + s1 * s2 * c3;\\n this._w = c1 * c2 * c3 + s1 * s2 * s3;\\n break;\\n default:\\n console.warn(\\\\\\\"THREE.Quaternion: .setFromEuler() encountered an unknown order: \\\\\\\" + order);\\n }\\n if (update !== false)\\n this._onChangeCallback();\\n return this;\\n }\\n setFromAxisAngle(axis, angle) {\\n const halfAngle = angle / 2, s = Math.sin(halfAngle);\\n this._x = axis.x * s;\\n this._y = axis.y * s;\\n this._z = axis.z * s;\\n this._w = Math.cos(halfAngle);\\n this._onChangeCallback();\\n return this;\\n }\\n setFromRotationMatrix(m) {\\n const te = m.elements, m11 = te[0], m12 = te[4], m13 = te[8], m21 = te[1], m22 = te[5], m23 = te[9], m31 = te[2], m32 = te[6], m33 = te[10], trace = m11 + m22 + m33;\\n if (trace > 0) {\\n const s = 0.5 / Math.sqrt(trace + 1);\\n this._w = 0.25 / s;\\n this._x = (m32 - m23) * s;\\n this._y = (m13 - m31) * s;\\n this._z = (m21 - m12) * s;\\n } else if (m11 > m22 && m11 > m33) {\\n const s = 2 * Math.sqrt(1 + m11 - m22 - m33);\\n this._w = (m32 - m23) / s;\\n this._x = 0.25 * s;\\n this._y = (m12 + m21) / s;\\n this._z = (m13 + m31) / s;\\n } else if (m22 > m33) {\\n const s = 2 * Math.sqrt(1 + m22 - m11 - m33);\\n this._w = (m13 - m31) / s;\\n this._x = (m12 + m21) / s;\\n this._y = 0.25 * s;\\n this._z = (m23 + m32) / s;\\n } else {\\n const s = 2 * Math.sqrt(1 + m33 - m11 - m22);\\n this._w = (m21 - m12) / s;\\n this._x = (m13 + m31) / s;\\n this._y = (m23 + m32) / s;\\n this._z = 0.25 * s;\\n }\\n this._onChangeCallback();\\n return this;\\n }\\n setFromUnitVectors(vFrom, vTo) {\\n let r = vFrom.dot(vTo) + 1;\\n if (r < Number.EPSILON) {\\n r = 0;\\n if (Math.abs(vFrom.x) > Math.abs(vFrom.z)) {\\n this._x = -vFrom.y;\\n this._y = vFrom.x;\\n this._z = 0;\\n this._w = r;\\n } else {\\n this._x = 0;\\n this._y = -vFrom.z;\\n this._z = vFrom.y;\\n this._w = r;\\n }\\n } else {\\n this._x = vFrom.y * vTo.z - vFrom.z * vTo.y;\\n this._y = vFrom.z * vTo.x - vFrom.x * vTo.z;\\n this._z = vFrom.x * vTo.y - vFrom.y * vTo.x;\\n this._w = r;\\n }\\n return this.normalize();\\n }\\n angleTo(q) {\\n return 2 * Math.acos(Math.abs(clamp(this.dot(q), -1, 1)));\\n }\\n rotateTowards(q, step) {\\n const angle = this.angleTo(q);\\n if (angle === 0)\\n return this;\\n const t = Math.min(1, step / angle);\\n this.slerp(q, t);\\n return this;\\n }\\n identity() {\\n return this.set(0, 0, 0, 1);\\n }\\n invert() {\\n return this.conjugate();\\n }\\n conjugate() {\\n this._x *= -1;\\n this._y *= -1;\\n this._z *= -1;\\n this._onChangeCallback();\\n return this;\\n }\\n dot(v) {\\n return this._x * v._x + this._y * v._y + this._z * v._z + this._w * v._w;\\n }\\n lengthSq() {\\n return this._x * this._x + this._y * this._y + this._z * this._z + this._w * this._w;\\n }\\n length() {\\n return Math.sqrt(this._x * this._x + this._y * this._y + this._z * this._z + this._w * this._w);\\n }\\n normalize() {\\n let l = this.length();\\n if (l === 0) {\\n this._x = 0;\\n this._y = 0;\\n this._z = 0;\\n this._w = 1;\\n } else {\\n l = 1 / l;\\n this._x = this._x * l;\\n this._y = this._y * l;\\n this._z = this._z * l;\\n this._w = this._w * l;\\n }\\n this._onChangeCallback();\\n return this;\\n }\\n multiply(q, p) {\\n if (p !== void 0) {\\n console.warn(\\\\\\\"THREE.Quaternion: .multiply() now only accepts one argument. Use .multiplyQuaternions( a, b ) instead.\\\\\\\");\\n return this.multiplyQuaternions(q, p);\\n }\\n return this.multiplyQuaternions(this, q);\\n }\\n premultiply(q) {\\n return this.multiplyQuaternions(q, this);\\n }\\n multiplyQuaternions(a, b) {\\n const qax = a._x, qay = a._y, qaz = a._z, qaw = a._w;\\n const qbx = b._x, qby = b._y, qbz = b._z, qbw = b._w;\\n this._x = qax * qbw + qaw * qbx + qay * qbz - qaz * qby;\\n this._y = qay * qbw + qaw * qby + qaz * qbx - qax * qbz;\\n this._z = qaz * qbw + qaw * qbz + qax * qby - qay * qbx;\\n this._w = qaw * qbw - qax * qbx - qay * qby - qaz * qbz;\\n this._onChangeCallback();\\n return this;\\n }\\n slerp(qb, t) {\\n if (t === 0)\\n return this;\\n if (t === 1)\\n return this.copy(qb);\\n const x = this._x, y = this._y, z = this._z, w = this._w;\\n let cosHalfTheta = w * qb._w + x * qb._x + y * qb._y + z * qb._z;\\n if (cosHalfTheta < 0) {\\n this._w = -qb._w;\\n this._x = -qb._x;\\n this._y = -qb._y;\\n this._z = -qb._z;\\n cosHalfTheta = -cosHalfTheta;\\n } else {\\n this.copy(qb);\\n }\\n if (cosHalfTheta >= 1) {\\n this._w = w;\\n this._x = x;\\n this._y = y;\\n this._z = z;\\n return this;\\n }\\n const sqrSinHalfTheta = 1 - cosHalfTheta * cosHalfTheta;\\n if (sqrSinHalfTheta <= Number.EPSILON) {\\n const s = 1 - t;\\n this._w = s * w + t * this._w;\\n this._x = s * x + t * this._x;\\n this._y = s * y + t * this._y;\\n this._z = s * z + t * this._z;\\n this.normalize();\\n this._onChangeCallback();\\n return this;\\n }\\n const sinHalfTheta = Math.sqrt(sqrSinHalfTheta);\\n const halfTheta = Math.atan2(sinHalfTheta, cosHalfTheta);\\n const ratioA = Math.sin((1 - t) * halfTheta) / sinHalfTheta, ratioB = Math.sin(t * halfTheta) / sinHalfTheta;\\n this._w = w * ratioA + this._w * ratioB;\\n this._x = x * ratioA + this._x * ratioB;\\n this._y = y * ratioA + this._y * ratioB;\\n this._z = z * ratioA + this._z * ratioB;\\n this._onChangeCallback();\\n return this;\\n }\\n slerpQuaternions(qa, qb, t) {\\n this.copy(qa).slerp(qb, t);\\n }\\n random() {\\n const u1 = Math.random();\\n const sqrt1u1 = Math.sqrt(1 - u1);\\n const sqrtu1 = Math.sqrt(u1);\\n const u2 = 2 * Math.PI * Math.random();\\n const u3 = 2 * Math.PI * Math.random();\\n return this.set(sqrt1u1 * Math.cos(u2), sqrtu1 * Math.sin(u3), sqrtu1 * Math.cos(u3), sqrt1u1 * Math.sin(u2));\\n }\\n equals(quaternion) {\\n return quaternion._x === this._x && quaternion._y === this._y && quaternion._z === this._z && quaternion._w === this._w;\\n }\\n fromArray(array, offset = 0) {\\n this._x = array[offset];\\n this._y = array[offset + 1];\\n this._z = array[offset + 2];\\n this._w = array[offset + 3];\\n this._onChangeCallback();\\n return this;\\n }\\n toArray(array = [], offset = 0) {\\n array[offset] = this._x;\\n array[offset + 1] = this._y;\\n array[offset + 2] = this._z;\\n array[offset + 3] = this._w;\\n return array;\\n }\\n fromBufferAttribute(attribute, index) {\\n this._x = attribute.getX(index);\\n this._y = attribute.getY(index);\\n this._z = attribute.getZ(index);\\n this._w = attribute.getW(index);\\n return this;\\n }\\n _onChange(callback) {\\n this._onChangeCallback = callback;\\n return this;\\n }\\n _onChangeCallback() {\\n }\\n};\\nQuaternion.prototype.isQuaternion = true;\\n\\n// ../../../node_modules/three/src/math/Vector3.js\\nvar Vector3 = class {\\n constructor(x = 0, y = 0, z = 0) {\\n this.x = x;\\n this.y = y;\\n this.z = z;\\n }\\n set(x, y, z) {\\n if (z === void 0)\\n z = this.z;\\n this.x = x;\\n this.y = y;\\n this.z = z;\\n return this;\\n }\\n setScalar(scalar) {\\n this.x = scalar;\\n this.y = scalar;\\n this.z = scalar;\\n return this;\\n }\\n setX(x) {\\n this.x = x;\\n return this;\\n }\\n setY(y) {\\n this.y = y;\\n return this;\\n }\\n setZ(z) {\\n this.z = z;\\n return this;\\n }\\n setComponent(index, value) {\\n switch (index) {\\n case 0:\\n this.x = value;\\n break;\\n case 1:\\n this.y = value;\\n break;\\n case 2:\\n this.z = value;\\n break;\\n default:\\n throw new Error(\\\\\\\"index is out of range: \\\\\\\" + index);\\n }\\n return this;\\n }\\n getComponent(index) {\\n switch (index) {\\n case 0:\\n return this.x;\\n case 1:\\n return this.y;\\n case 2:\\n return this.z;\\n default:\\n throw new Error(\\\\\\\"index is out of range: \\\\\\\" + index);\\n }\\n }\\n clone() {\\n return new this.constructor(this.x, this.y, this.z);\\n }\\n copy(v) {\\n this.x = v.x;\\n this.y = v.y;\\n this.z = v.z;\\n return this;\\n }\\n add(v, w) {\\n if (w !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector3: .add() now only accepts one argument. Use .addVectors( a, b ) instead.\\\\\\\");\\n return this.addVectors(v, w);\\n }\\n this.x += v.x;\\n this.y += v.y;\\n this.z += v.z;\\n return this;\\n }\\n addScalar(s) {\\n this.x += s;\\n this.y += s;\\n this.z += s;\\n return this;\\n }\\n addVectors(a, b) {\\n this.x = a.x + b.x;\\n this.y = a.y + b.y;\\n this.z = a.z + b.z;\\n return this;\\n }\\n addScaledVector(v, s) {\\n this.x += v.x * s;\\n this.y += v.y * s;\\n this.z += v.z * s;\\n return this;\\n }\\n sub(v, w) {\\n if (w !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector3: .sub() now only accepts one argument. Use .subVectors( a, b ) instead.\\\\\\\");\\n return this.subVectors(v, w);\\n }\\n this.x -= v.x;\\n this.y -= v.y;\\n this.z -= v.z;\\n return this;\\n }\\n subScalar(s) {\\n this.x -= s;\\n this.y -= s;\\n this.z -= s;\\n return this;\\n }\\n subVectors(a, b) {\\n this.x = a.x - b.x;\\n this.y = a.y - b.y;\\n this.z = a.z - b.z;\\n return this;\\n }\\n multiply(v, w) {\\n if (w !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector3: .multiply() now only accepts one argument. Use .multiplyVectors( a, b ) instead.\\\\\\\");\\n return this.multiplyVectors(v, w);\\n }\\n this.x *= v.x;\\n this.y *= v.y;\\n this.z *= v.z;\\n return this;\\n }\\n multiplyScalar(scalar) {\\n this.x *= scalar;\\n this.y *= scalar;\\n this.z *= scalar;\\n return this;\\n }\\n multiplyVectors(a, b) {\\n this.x = a.x * b.x;\\n this.y = a.y * b.y;\\n this.z = a.z * b.z;\\n return this;\\n }\\n applyEuler(euler) {\\n if (!(euler && euler.isEuler)) {\\n console.error(\\\\\\\"THREE.Vector3: .applyEuler() now expects an Euler rotation rather than a Vector3 and order.\\\\\\\");\\n }\\n return this.applyQuaternion(_quaternion.setFromEuler(euler));\\n }\\n applyAxisAngle(axis, angle) {\\n return this.applyQuaternion(_quaternion.setFromAxisAngle(axis, angle));\\n }\\n applyMatrix3(m) {\\n const x = this.x, y = this.y, z = this.z;\\n const e = m.elements;\\n this.x = e[0] * x + e[3] * y + e[6] * z;\\n this.y = e[1] * x + e[4] * y + e[7] * z;\\n this.z = e[2] * x + e[5] * y + e[8] * z;\\n return this;\\n }\\n applyNormalMatrix(m) {\\n return this.applyMatrix3(m).normalize();\\n }\\n applyMatrix4(m) {\\n const x = this.x, y = this.y, z = this.z;\\n const e = m.elements;\\n const w = 1 / (e[3] * x + e[7] * y + e[11] * z + e[15]);\\n this.x = (e[0] * x + e[4] * y + e[8] * z + e[12]) * w;\\n this.y = (e[1] * x + e[5] * y + e[9] * z + e[13]) * w;\\n this.z = (e[2] * x + e[6] * y + e[10] * z + e[14]) * w;\\n return this;\\n }\\n applyQuaternion(q) {\\n const x = this.x, y = this.y, z = this.z;\\n const qx = q.x, qy = q.y, qz = q.z, qw = q.w;\\n const ix = qw * x + qy * z - qz * y;\\n const iy = qw * y + qz * x - qx * z;\\n const iz = qw * z + qx * y - qy * x;\\n const iw = -qx * x - qy * y - qz * z;\\n this.x = ix * qw + iw * -qx + iy * -qz - iz * -qy;\\n this.y = iy * qw + iw * -qy + iz * -qx - ix * -qz;\\n this.z = iz * qw + iw * -qz + ix * -qy - iy * -qx;\\n return this;\\n }\\n project(camera) {\\n return this.applyMatrix4(camera.matrixWorldInverse).applyMatrix4(camera.projectionMatrix);\\n }\\n unproject(camera) {\\n return this.applyMatrix4(camera.projectionMatrixInverse).applyMatrix4(camera.matrixWorld);\\n }\\n transformDirection(m) {\\n const x = this.x, y = this.y, z = this.z;\\n const e = m.elements;\\n this.x = e[0] * x + e[4] * y + e[8] * z;\\n this.y = e[1] * x + e[5] * y + e[9] * z;\\n this.z = e[2] * x + e[6] * y + e[10] * z;\\n return this.normalize();\\n }\\n divide(v) {\\n this.x /= v.x;\\n this.y /= v.y;\\n this.z /= v.z;\\n return this;\\n }\\n divideScalar(scalar) {\\n return this.multiplyScalar(1 / scalar);\\n }\\n min(v) {\\n this.x = Math.min(this.x, v.x);\\n this.y = Math.min(this.y, v.y);\\n this.z = Math.min(this.z, v.z);\\n return this;\\n }\\n max(v) {\\n this.x = Math.max(this.x, v.x);\\n this.y = Math.max(this.y, v.y);\\n this.z = Math.max(this.z, v.z);\\n return this;\\n }\\n clamp(min, max) {\\n this.x = Math.max(min.x, Math.min(max.x, this.x));\\n this.y = Math.max(min.y, Math.min(max.y, this.y));\\n this.z = Math.max(min.z, Math.min(max.z, this.z));\\n return this;\\n }\\n clampScalar(minVal, maxVal) {\\n this.x = Math.max(minVal, Math.min(maxVal, this.x));\\n this.y = Math.max(minVal, Math.min(maxVal, this.y));\\n this.z = Math.max(minVal, Math.min(maxVal, this.z));\\n return this;\\n }\\n clampLength(min, max) {\\n const length = this.length();\\n return this.divideScalar(length || 1).multiplyScalar(Math.max(min, Math.min(max, length)));\\n }\\n floor() {\\n this.x = Math.floor(this.x);\\n this.y = Math.floor(this.y);\\n this.z = Math.floor(this.z);\\n return this;\\n }\\n ceil() {\\n this.x = Math.ceil(this.x);\\n this.y = Math.ceil(this.y);\\n this.z = Math.ceil(this.z);\\n return this;\\n }\\n round() {\\n this.x = Math.round(this.x);\\n this.y = Math.round(this.y);\\n this.z = Math.round(this.z);\\n return this;\\n }\\n roundToZero() {\\n this.x = this.x < 0 ? Math.ceil(this.x) : Math.floor(this.x);\\n this.y = this.y < 0 ? Math.ceil(this.y) : Math.floor(this.y);\\n this.z = this.z < 0 ? Math.ceil(this.z) : Math.floor(this.z);\\n return this;\\n }\\n negate() {\\n this.x = -this.x;\\n this.y = -this.y;\\n this.z = -this.z;\\n return this;\\n }\\n dot(v) {\\n return this.x * v.x + this.y * v.y + this.z * v.z;\\n }\\n lengthSq() {\\n return this.x * this.x + this.y * this.y + this.z * this.z;\\n }\\n length() {\\n return Math.sqrt(this.x * this.x + this.y * this.y + this.z * this.z);\\n }\\n manhattanLength() {\\n return Math.abs(this.x) + Math.abs(this.y) + Math.abs(this.z);\\n }\\n normalize() {\\n return this.divideScalar(this.length() || 1);\\n }\\n setLength(length) {\\n return this.normalize().multiplyScalar(length);\\n }\\n lerp(v, alpha) {\\n this.x += (v.x - this.x) * alpha;\\n this.y += (v.y - this.y) * alpha;\\n this.z += (v.z - this.z) * alpha;\\n return this;\\n }\\n lerpVectors(v1, v2, alpha) {\\n this.x = v1.x + (v2.x - v1.x) * alpha;\\n this.y = v1.y + (v2.y - v1.y) * alpha;\\n this.z = v1.z + (v2.z - v1.z) * alpha;\\n return this;\\n }\\n cross(v, w) {\\n if (w !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector3: .cross() now only accepts one argument. Use .crossVectors( a, b ) instead.\\\\\\\");\\n return this.crossVectors(v, w);\\n }\\n return this.crossVectors(this, v);\\n }\\n crossVectors(a, b) {\\n const ax = a.x, ay = a.y, az = a.z;\\n const bx = b.x, by = b.y, bz = b.z;\\n this.x = ay * bz - az * by;\\n this.y = az * bx - ax * bz;\\n this.z = ax * by - ay * bx;\\n return this;\\n }\\n projectOnVector(v) {\\n const denominator = v.lengthSq();\\n if (denominator === 0)\\n return this.set(0, 0, 0);\\n const scalar = v.dot(this) / denominator;\\n return this.copy(v).multiplyScalar(scalar);\\n }\\n projectOnPlane(planeNormal) {\\n _vector.copy(this).projectOnVector(planeNormal);\\n return this.sub(_vector);\\n }\\n reflect(normal) {\\n return this.sub(_vector.copy(normal).multiplyScalar(2 * this.dot(normal)));\\n }\\n angleTo(v) {\\n const denominator = Math.sqrt(this.lengthSq() * v.lengthSq());\\n if (denominator === 0)\\n return Math.PI / 2;\\n const theta = this.dot(v) / denominator;\\n return Math.acos(clamp(theta, -1, 1));\\n }\\n distanceTo(v) {\\n return Math.sqrt(this.distanceToSquared(v));\\n }\\n distanceToSquared(v) {\\n const dx = this.x - v.x, dy = this.y - v.y, dz = this.z - v.z;\\n return dx * dx + dy * dy + dz * dz;\\n }\\n manhattanDistanceTo(v) {\\n return Math.abs(this.x - v.x) + Math.abs(this.y - v.y) + Math.abs(this.z - v.z);\\n }\\n setFromSpherical(s) {\\n return this.setFromSphericalCoords(s.radius, s.phi, s.theta);\\n }\\n setFromSphericalCoords(radius, phi, theta) {\\n const sinPhiRadius = Math.sin(phi) * radius;\\n this.x = sinPhiRadius * Math.sin(theta);\\n this.y = Math.cos(phi) * radius;\\n this.z = sinPhiRadius * Math.cos(theta);\\n return this;\\n }\\n setFromCylindrical(c) {\\n return this.setFromCylindricalCoords(c.radius, c.theta, c.y);\\n }\\n setFromCylindricalCoords(radius, theta, y) {\\n this.x = radius * Math.sin(theta);\\n this.y = y;\\n this.z = radius * Math.cos(theta);\\n return this;\\n }\\n setFromMatrixPosition(m) {\\n const e = m.elements;\\n this.x = e[12];\\n this.y = e[13];\\n this.z = e[14];\\n return this;\\n }\\n setFromMatrixScale(m) {\\n const sx = this.setFromMatrixColumn(m, 0).length();\\n const sy = this.setFromMatrixColumn(m, 1).length();\\n const sz = this.setFromMatrixColumn(m, 2).length();\\n this.x = sx;\\n this.y = sy;\\n this.z = sz;\\n return this;\\n }\\n setFromMatrixColumn(m, index) {\\n return this.fromArray(m.elements, index * 4);\\n }\\n setFromMatrix3Column(m, index) {\\n return this.fromArray(m.elements, index * 3);\\n }\\n equals(v) {\\n return v.x === this.x && v.y === this.y && v.z === this.z;\\n }\\n fromArray(array, offset = 0) {\\n this.x = array[offset];\\n this.y = array[offset + 1];\\n this.z = array[offset + 2];\\n return this;\\n }\\n toArray(array = [], offset = 0) {\\n array[offset] = this.x;\\n array[offset + 1] = this.y;\\n array[offset + 2] = this.z;\\n return array;\\n }\\n fromBufferAttribute(attribute, index, offset) {\\n if (offset !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector3: offset has been removed from .fromBufferAttribute().\\\\\\\");\\n }\\n this.x = attribute.getX(index);\\n this.y = attribute.getY(index);\\n this.z = attribute.getZ(index);\\n return this;\\n }\\n random() {\\n this.x = Math.random();\\n this.y = Math.random();\\n this.z = Math.random();\\n return this;\\n }\\n randomDirection() {\\n const u = (Math.random() - 0.5) * 2;\\n const t = Math.random() * Math.PI * 2;\\n const f = Math.sqrt(1 - u ** 2);\\n this.x = f * Math.cos(t);\\n this.y = f * Math.sin(t);\\n this.z = u;\\n return this;\\n }\\n *[Symbol.iterator]() {\\n yield this.x;\\n yield this.y;\\n yield this.z;\\n }\\n};\\nVector3.prototype.isVector3 = true;\\nvar _vector = /* @__PURE__ */ new Vector3();\\nvar _quaternion = /* @__PURE__ */ new Quaternion();\\n\\n// ../../../node_modules/three/src/math/Matrix4.js\\nvar Matrix4 = class {\\n constructor() {\\n this.elements = [\\n 1,\\n 0,\\n 0,\\n 0,\\n 0,\\n 1,\\n 0,\\n 0,\\n 0,\\n 0,\\n 1,\\n 0,\\n 0,\\n 0,\\n 0,\\n 1\\n ];\\n if (arguments.length > 0) {\\n console.error(\\\\\\\"THREE.Matrix4: the constructor no longer reads arguments. use .set() instead.\\\\\\\");\\n }\\n }\\n set(n11, n12, n13, n14, n21, n22, n23, n24, n31, n32, n33, n34, n41, n42, n43, n44) {\\n const te = this.elements;\\n te[0] = n11;\\n te[4] = n12;\\n te[8] = n13;\\n te[12] = n14;\\n te[1] = n21;\\n te[5] = n22;\\n te[9] = n23;\\n te[13] = n24;\\n te[2] = n31;\\n te[6] = n32;\\n te[10] = n33;\\n te[14] = n34;\\n te[3] = n41;\\n te[7] = n42;\\n te[11] = n43;\\n te[15] = n44;\\n return this;\\n }\\n identity() {\\n this.set(1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1);\\n return this;\\n }\\n clone() {\\n return new Matrix4().fromArray(this.elements);\\n }\\n copy(m) {\\n const te = this.elements;\\n const me = m.elements;\\n te[0] = me[0];\\n te[1] = me[1];\\n te[2] = me[2];\\n te[3] = me[3];\\n te[4] = me[4];\\n te[5] = me[5];\\n te[6] = me[6];\\n te[7] = me[7];\\n te[8] = me[8];\\n te[9] = me[9];\\n te[10] = me[10];\\n te[11] = me[11];\\n te[12] = me[12];\\n te[13] = me[13];\\n te[14] = me[14];\\n te[15] = me[15];\\n return this;\\n }\\n copyPosition(m) {\\n const te = this.elements, me = m.elements;\\n te[12] = me[12];\\n te[13] = me[13];\\n te[14] = me[14];\\n return this;\\n }\\n setFromMatrix3(m) {\\n const me = m.elements;\\n this.set(me[0], me[3], me[6], 0, me[1], me[4], me[7], 0, me[2], me[5], me[8], 0, 0, 0, 0, 1);\\n return this;\\n }\\n extractBasis(xAxis, yAxis, zAxis) {\\n xAxis.setFromMatrixColumn(this, 0);\\n yAxis.setFromMatrixColumn(this, 1);\\n zAxis.setFromMatrixColumn(this, 2);\\n return this;\\n }\\n makeBasis(xAxis, yAxis, zAxis) {\\n this.set(xAxis.x, yAxis.x, zAxis.x, 0, xAxis.y, yAxis.y, zAxis.y, 0, xAxis.z, yAxis.z, zAxis.z, 0, 0, 0, 0, 1);\\n return this;\\n }\\n extractRotation(m) {\\n const te = this.elements;\\n const me = m.elements;\\n const scaleX = 1 / _v1.setFromMatrixColumn(m, 0).length();\\n const scaleY = 1 / _v1.setFromMatrixColumn(m, 1).length();\\n const scaleZ = 1 / _v1.setFromMatrixColumn(m, 2).length();\\n te[0] = me[0] * scaleX;\\n te[1] = me[1] * scaleX;\\n te[2] = me[2] * scaleX;\\n te[3] = 0;\\n te[4] = me[4] * scaleY;\\n te[5] = me[5] * scaleY;\\n te[6] = me[6] * scaleY;\\n te[7] = 0;\\n te[8] = me[8] * scaleZ;\\n te[9] = me[9] * scaleZ;\\n te[10] = me[10] * scaleZ;\\n te[11] = 0;\\n te[12] = 0;\\n te[13] = 0;\\n te[14] = 0;\\n te[15] = 1;\\n return this;\\n }\\n makeRotationFromEuler(euler) {\\n if (!(euler && euler.isEuler)) {\\n console.error(\\\\\\\"THREE.Matrix4: .makeRotationFromEuler() now expects a Euler rotation rather than a Vector3 and order.\\\\\\\");\\n }\\n const te = this.elements;\\n const x = euler.x, y = euler.y, z = euler.z;\\n const a = Math.cos(x), b = Math.sin(x);\\n const c = Math.cos(y), d = Math.sin(y);\\n const e = Math.cos(z), f = Math.sin(z);\\n if (euler.order === \\\\\\\"XYZ\\\\\\\") {\\n const ae = a * e, af = a * f, be = b * e, bf = b * f;\\n te[0] = c * e;\\n te[4] = -c * f;\\n te[8] = d;\\n te[1] = af + be * d;\\n te[5] = ae - bf * d;\\n te[9] = -b * c;\\n te[2] = bf - ae * d;\\n te[6] = be + af * d;\\n te[10] = a * c;\\n } else if (euler.order === \\\\\\\"YXZ\\\\\\\") {\\n const ce = c * e, cf = c * f, de = d * e, df = d * f;\\n te[0] = ce + df * b;\\n te[4] = de * b - cf;\\n te[8] = a * d;\\n te[1] = a * f;\\n te[5] = a * e;\\n te[9] = -b;\\n te[2] = cf * b - de;\\n te[6] = df + ce * b;\\n te[10] = a * c;\\n } else if (euler.order === \\\\\\\"ZXY\\\\\\\") {\\n const ce = c * e, cf = c * f, de = d * e, df = d * f;\\n te[0] = ce - df * b;\\n te[4] = -a * f;\\n te[8] = de + cf * b;\\n te[1] = cf + de * b;\\n te[5] = a * e;\\n te[9] = df - ce * b;\\n te[2] = -a * d;\\n te[6] = b;\\n te[10] = a * c;\\n } else if (euler.order === \\\\\\\"ZYX\\\\\\\") {\\n const ae = a * e, af = a * f, be = b * e, bf = b * f;\\n te[0] = c * e;\\n te[4] = be * d - af;\\n te[8] = ae * d + bf;\\n te[1] = c * f;\\n te[5] = bf * d + ae;\\n te[9] = af * d - be;\\n te[2] = -d;\\n te[6] = b * c;\\n te[10] = a * c;\\n } else if (euler.order === \\\\\\\"YZX\\\\\\\") {\\n const ac = a * c, ad = a * d, bc = b * c, bd = b * d;\\n te[0] = c * e;\\n te[4] = bd - ac * f;\\n te[8] = bc * f + ad;\\n te[1] = f;\\n te[5] = a * e;\\n te[9] = -b * e;\\n te[2] = -d * e;\\n te[6] = ad * f + bc;\\n te[10] = ac - bd * f;\\n } else if (euler.order === \\\\\\\"XZY\\\\\\\") {\\n const ac = a * c, ad = a * d, bc = b * c, bd = b * d;\\n te[0] = c * e;\\n te[4] = -f;\\n te[8] = d * e;\\n te[1] = ac * f + bd;\\n te[5] = a * e;\\n te[9] = ad * f - bc;\\n te[2] = bc * f - ad;\\n te[6] = b * e;\\n te[10] = bd * f + ac;\\n }\\n te[3] = 0;\\n te[7] = 0;\\n te[11] = 0;\\n te[12] = 0;\\n te[13] = 0;\\n te[14] = 0;\\n te[15] = 1;\\n return this;\\n }\\n makeRotationFromQuaternion(q) {\\n return this.compose(_zero, q, _one);\\n }\\n lookAt(eye, target, up) {\\n const te = this.elements;\\n _z.subVectors(eye, target);\\n if (_z.lengthSq() === 0) {\\n _z.z = 1;\\n }\\n _z.normalize();\\n _x.crossVectors(up, _z);\\n if (_x.lengthSq() === 0) {\\n if (Math.abs(up.z) === 1) {\\n _z.x += 1e-4;\\n } else {\\n _z.z += 1e-4;\\n }\\n _z.normalize();\\n _x.crossVectors(up, _z);\\n }\\n _x.normalize();\\n _y.crossVectors(_z, _x);\\n te[0] = _x.x;\\n te[4] = _y.x;\\n te[8] = _z.x;\\n te[1] = _x.y;\\n te[5] = _y.y;\\n te[9] = _z.y;\\n te[2] = _x.z;\\n te[6] = _y.z;\\n te[10] = _z.z;\\n return this;\\n }\\n multiply(m, n) {\\n if (n !== void 0) {\\n console.warn(\\\\\\\"THREE.Matrix4: .multiply() now only accepts one argument. Use .multiplyMatrices( a, b ) instead.\\\\\\\");\\n return this.multiplyMatrices(m, n);\\n }\\n return this.multiplyMatrices(this, m);\\n }\\n premultiply(m) {\\n return this.multiplyMatrices(m, this);\\n }\\n multiplyMatrices(a, b) {\\n const ae = a.elements;\\n const be = b.elements;\\n const te = this.elements;\\n const a11 = ae[0], a12 = ae[4], a13 = ae[8], a14 = ae[12];\\n const a21 = ae[1], a22 = ae[5], a23 = ae[9], a24 = ae[13];\\n const a31 = ae[2], a32 = ae[6], a33 = ae[10], a34 = ae[14];\\n const a41 = ae[3], a42 = ae[7], a43 = ae[11], a44 = ae[15];\\n const b11 = be[0], b12 = be[4], b13 = be[8], b14 = be[12];\\n const b21 = be[1], b22 = be[5], b23 = be[9], b24 = be[13];\\n const b31 = be[2], b32 = be[6], b33 = be[10], b34 = be[14];\\n const b41 = be[3], b42 = be[7], b43 = be[11], b44 = be[15];\\n te[0] = a11 * b11 + a12 * b21 + a13 * b31 + a14 * b41;\\n te[4] = a11 * b12 + a12 * b22 + a13 * b32 + a14 * b42;\\n te[8] = a11 * b13 + a12 * b23 + a13 * b33 + a14 * b43;\\n te[12] = a11 * b14 + a12 * b24 + a13 * b34 + a14 * b44;\\n te[1] = a21 * b11 + a22 * b21 + a23 * b31 + a24 * b41;\\n te[5] = a21 * b12 + a22 * b22 + a23 * b32 + a24 * b42;\\n te[9] = a21 * b13 + a22 * b23 + a23 * b33 + a24 * b43;\\n te[13] = a21 * b14 + a22 * b24 + a23 * b34 + a24 * b44;\\n te[2] = a31 * b11 + a32 * b21 + a33 * b31 + a34 * b41;\\n te[6] = a31 * b12 + a32 * b22 + a33 * b32 + a34 * b42;\\n te[10] = a31 * b13 + a32 * b23 + a33 * b33 + a34 * b43;\\n te[14] = a31 * b14 + a32 * b24 + a33 * b34 + a34 * b44;\\n te[3] = a41 * b11 + a42 * b21 + a43 * b31 + a44 * b41;\\n te[7] = a41 * b12 + a42 * b22 + a43 * b32 + a44 * b42;\\n te[11] = a41 * b13 + a42 * b23 + a43 * b33 + a44 * b43;\\n te[15] = a41 * b14 + a42 * b24 + a43 * b34 + a44 * b44;\\n return this;\\n }\\n multiplyScalar(s) {\\n const te = this.elements;\\n te[0] *= s;\\n te[4] *= s;\\n te[8] *= s;\\n te[12] *= s;\\n te[1] *= s;\\n te[5] *= s;\\n te[9] *= s;\\n te[13] *= s;\\n te[2] *= s;\\n te[6] *= s;\\n te[10] *= s;\\n te[14] *= s;\\n te[3] *= s;\\n te[7] *= s;\\n te[11] *= s;\\n te[15] *= s;\\n return this;\\n }\\n determinant() {\\n const te = this.elements;\\n const n11 = te[0], n12 = te[4], n13 = te[8], n14 = te[12];\\n const n21 = te[1], n22 = te[5], n23 = te[9], n24 = te[13];\\n const n31 = te[2], n32 = te[6], n33 = te[10], n34 = te[14];\\n const n41 = te[3], n42 = te[7], n43 = te[11], n44 = te[15];\\n return n41 * (+n14 * n23 * n32 - n13 * n24 * n32 - n14 * n22 * n33 + n12 * n24 * n33 + n13 * n22 * n34 - n12 * n23 * n34) + n42 * (+n11 * n23 * n34 - n11 * n24 * n33 + n14 * n21 * n33 - n13 * n21 * n34 + n13 * n24 * n31 - n14 * n23 * n31) + n43 * (+n11 * n24 * n32 - n11 * n22 * n34 - n14 * n21 * n32 + n12 * n21 * n34 + n14 * n22 * n31 - n12 * n24 * n31) + n44 * (-n13 * n22 * n31 - n11 * n23 * n32 + n11 * n22 * n33 + n13 * n21 * n32 - n12 * n21 * n33 + n12 * n23 * n31);\\n }\\n transpose() {\\n const te = this.elements;\\n let tmp;\\n tmp = te[1];\\n te[1] = te[4];\\n te[4] = tmp;\\n tmp = te[2];\\n te[2] = te[8];\\n te[8] = tmp;\\n tmp = te[6];\\n te[6] = te[9];\\n te[9] = tmp;\\n tmp = te[3];\\n te[3] = te[12];\\n te[12] = tmp;\\n tmp = te[7];\\n te[7] = te[13];\\n te[13] = tmp;\\n tmp = te[11];\\n te[11] = te[14];\\n te[14] = tmp;\\n return this;\\n }\\n setPosition(x, y, z) {\\n const te = this.elements;\\n if (x.isVector3) {\\n te[12] = x.x;\\n te[13] = x.y;\\n te[14] = x.z;\\n } else {\\n te[12] = x;\\n te[13] = y;\\n te[14] = z;\\n }\\n return this;\\n }\\n invert() {\\n const te = this.elements, n11 = te[0], n21 = te[1], n31 = te[2], n41 = te[3], n12 = te[4], n22 = te[5], n32 = te[6], n42 = te[7], n13 = te[8], n23 = te[9], n33 = te[10], n43 = te[11], n14 = te[12], n24 = te[13], n34 = te[14], n44 = te[15], t11 = n23 * n34 * n42 - n24 * n33 * n42 + n24 * n32 * n43 - n22 * n34 * n43 - n23 * n32 * n44 + n22 * n33 * n44, t12 = n14 * n33 * n42 - n13 * n34 * n42 - n14 * n32 * n43 + n12 * n34 * n43 + n13 * n32 * n44 - n12 * n33 * n44, t13 = n13 * n24 * n42 - n14 * n23 * n42 + n14 * n22 * n43 - n12 * n24 * n43 - n13 * n22 * n44 + n12 * n23 * n44, t14 = n14 * n23 * n32 - n13 * n24 * n32 - n14 * n22 * n33 + n12 * n24 * n33 + n13 * n22 * n34 - n12 * n23 * n34;\\n const det = n11 * t11 + n21 * t12 + n31 * t13 + n41 * t14;\\n if (det === 0)\\n return this.set(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0);\\n const detInv = 1 / det;\\n te[0] = t11 * detInv;\\n te[1] = (n24 * n33 * n41 - n23 * n34 * n41 - n24 * n31 * n43 + n21 * n34 * n43 + n23 * n31 * n44 - n21 * n33 * n44) * detInv;\\n te[2] = (n22 * n34 * n41 - n24 * n32 * n41 + n24 * n31 * n42 - n21 * n34 * n42 - n22 * n31 * n44 + n21 * n32 * n44) * detInv;\\n te[3] = (n23 * n32 * n41 - n22 * n33 * n41 - n23 * n31 * n42 + n21 * n33 * n42 + n22 * n31 * n43 - n21 * n32 * n43) * detInv;\\n te[4] = t12 * detInv;\\n te[5] = (n13 * n34 * n41 - n14 * n33 * n41 + n14 * n31 * n43 - n11 * n34 * n43 - n13 * n31 * n44 + n11 * n33 * n44) * detInv;\\n te[6] = (n14 * n32 * n41 - n12 * n34 * n41 - n14 * n31 * n42 + n11 * n34 * n42 + n12 * n31 * n44 - n11 * n32 * n44) * detInv;\\n te[7] = (n12 * n33 * n41 - n13 * n32 * n41 + n13 * n31 * n42 - n11 * n33 * n42 - n12 * n31 * n43 + n11 * n32 * n43) * detInv;\\n te[8] = t13 * detInv;\\n te[9] = (n14 * n23 * n41 - n13 * n24 * n41 - n14 * n21 * n43 + n11 * n24 * n43 + n13 * n21 * n44 - n11 * n23 * n44) * detInv;\\n te[10] = (n12 * n24 * n41 - n14 * n22 * n41 + n14 * n21 * n42 - n11 * n24 * n42 - n12 * n21 * n44 + n11 * n22 * n44) * detInv;\\n te[11] = (n13 * n22 * n41 - n12 * n23 * n41 - n13 * n21 * n42 + n11 * n23 * n42 + n12 * n21 * n43 - n11 * n22 * n43) * detInv;\\n te[12] = t14 * detInv;\\n te[13] = (n13 * n24 * n31 - n14 * n23 * n31 + n14 * n21 * n33 - n11 * n24 * n33 - n13 * n21 * n34 + n11 * n23 * n34) * detInv;\\n te[14] = (n14 * n22 * n31 - n12 * n24 * n31 - n14 * n21 * n32 + n11 * n24 * n32 + n12 * n21 * n34 - n11 * n22 * n34) * detInv;\\n te[15] = (n12 * n23 * n31 - n13 * n22 * n31 + n13 * n21 * n32 - n11 * n23 * n32 - n12 * n21 * n33 + n11 * n22 * n33) * detInv;\\n return this;\\n }\\n scale(v) {\\n const te = this.elements;\\n const x = v.x, y = v.y, z = v.z;\\n te[0] *= x;\\n te[4] *= y;\\n te[8] *= z;\\n te[1] *= x;\\n te[5] *= y;\\n te[9] *= z;\\n te[2] *= x;\\n te[6] *= y;\\n te[10] *= z;\\n te[3] *= x;\\n te[7] *= y;\\n te[11] *= z;\\n return this;\\n }\\n getMaxScaleOnAxis() {\\n const te = this.elements;\\n const scaleXSq = te[0] * te[0] + te[1] * te[1] + te[2] * te[2];\\n const scaleYSq = te[4] * te[4] + te[5] * te[5] + te[6] * te[6];\\n const scaleZSq = te[8] * te[8] + te[9] * te[9] + te[10] * te[10];\\n return Math.sqrt(Math.max(scaleXSq, scaleYSq, scaleZSq));\\n }\\n makeTranslation(x, y, z) {\\n this.set(1, 0, 0, x, 0, 1, 0, y, 0, 0, 1, z, 0, 0, 0, 1);\\n return this;\\n }\\n makeRotationX(theta) {\\n const c = Math.cos(theta), s = Math.sin(theta);\\n this.set(1, 0, 0, 0, 0, c, -s, 0, 0, s, c, 0, 0, 0, 0, 1);\\n return this;\\n }\\n makeRotationY(theta) {\\n const c = Math.cos(theta), s = Math.sin(theta);\\n this.set(c, 0, s, 0, 0, 1, 0, 0, -s, 0, c, 0, 0, 0, 0, 1);\\n return this;\\n }\\n makeRotationZ(theta) {\\n const c = Math.cos(theta), s = Math.sin(theta);\\n this.set(c, -s, 0, 0, s, c, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1);\\n return this;\\n }\\n makeRotationAxis(axis, angle) {\\n const c = Math.cos(angle);\\n const s = Math.sin(angle);\\n const t = 1 - c;\\n const x = axis.x, y = axis.y, z = axis.z;\\n const tx = t * x, ty = t * y;\\n this.set(tx * x + c, tx * y - s * z, tx * z + s * y, 0, tx * y + s * z, ty * y + c, ty * z - s * x, 0, tx * z - s * y, ty * z + s * x, t * z * z + c, 0, 0, 0, 0, 1);\\n return this;\\n }\\n makeScale(x, y, z) {\\n this.set(x, 0, 0, 0, 0, y, 0, 0, 0, 0, z, 0, 0, 0, 0, 1);\\n return this;\\n }\\n makeShear(xy, xz, yx, yz, zx, zy) {\\n this.set(1, yx, zx, 0, xy, 1, zy, 0, xz, yz, 1, 0, 0, 0, 0, 1);\\n return this;\\n }\\n compose(position, quaternion, scale) {\\n const te = this.elements;\\n const x = quaternion._x, y = quaternion._y, z = quaternion._z, w = quaternion._w;\\n const x2 = x + x, y2 = y + y, z2 = z + z;\\n const xx = x * x2, xy = x * y2, xz = x * z2;\\n const yy = y * y2, yz = y * z2, zz = z * z2;\\n const wx = w * x2, wy = w * y2, wz = w * z2;\\n const sx = scale.x, sy = scale.y, sz = scale.z;\\n te[0] = (1 - (yy + zz)) * sx;\\n te[1] = (xy + wz) * sx;\\n te[2] = (xz - wy) * sx;\\n te[3] = 0;\\n te[4] = (xy - wz) * sy;\\n te[5] = (1 - (xx + zz)) * sy;\\n te[6] = (yz + wx) * sy;\\n te[7] = 0;\\n te[8] = (xz + wy) * sz;\\n te[9] = (yz - wx) * sz;\\n te[10] = (1 - (xx + yy)) * sz;\\n te[11] = 0;\\n te[12] = position.x;\\n te[13] = position.y;\\n te[14] = position.z;\\n te[15] = 1;\\n return this;\\n }\\n decompose(position, quaternion, scale) {\\n const te = this.elements;\\n let sx = _v1.set(te[0], te[1], te[2]).length();\\n const sy = _v1.set(te[4], te[5], te[6]).length();\\n const sz = _v1.set(te[8], te[9], te[10]).length();\\n const det = this.determinant();\\n if (det < 0)\\n sx = -sx;\\n position.x = te[12];\\n position.y = te[13];\\n position.z = te[14];\\n _m1.copy(this);\\n const invSX = 1 / sx;\\n const invSY = 1 / sy;\\n const invSZ = 1 / sz;\\n _m1.elements[0] *= invSX;\\n _m1.elements[1] *= invSX;\\n _m1.elements[2] *= invSX;\\n _m1.elements[4] *= invSY;\\n _m1.elements[5] *= invSY;\\n _m1.elements[6] *= invSY;\\n _m1.elements[8] *= invSZ;\\n _m1.elements[9] *= invSZ;\\n _m1.elements[10] *= invSZ;\\n quaternion.setFromRotationMatrix(_m1);\\n scale.x = sx;\\n scale.y = sy;\\n scale.z = sz;\\n return this;\\n }\\n makePerspective(left, right, top, bottom, near, far) {\\n if (far === void 0) {\\n console.warn(\\\\\\\"THREE.Matrix4: .makePerspective() has been redefined and has a new signature. Please check the docs.\\\\\\\");\\n }\\n const te = this.elements;\\n const x = 2 * near / (right - left);\\n const y = 2 * near / (top - bottom);\\n const a = (right + left) / (right - left);\\n const b = (top + bottom) / (top - bottom);\\n const c = -(far + near) / (far - near);\\n const d = -2 * far * near / (far - near);\\n te[0] = x;\\n te[4] = 0;\\n te[8] = a;\\n te[12] = 0;\\n te[1] = 0;\\n te[5] = y;\\n te[9] = b;\\n te[13] = 0;\\n te[2] = 0;\\n te[6] = 0;\\n te[10] = c;\\n te[14] = d;\\n te[3] = 0;\\n te[7] = 0;\\n te[11] = -1;\\n te[15] = 0;\\n return this;\\n }\\n makeOrthographic(left, right, top, bottom, near, far) {\\n const te = this.elements;\\n const w = 1 / (right - left);\\n const h = 1 / (top - bottom);\\n const p = 1 / (far - near);\\n const x = (right + left) * w;\\n const y = (top + bottom) * h;\\n const z = (far + near) * p;\\n te[0] = 2 * w;\\n te[4] = 0;\\n te[8] = 0;\\n te[12] = -x;\\n te[1] = 0;\\n te[5] = 2 * h;\\n te[9] = 0;\\n te[13] = -y;\\n te[2] = 0;\\n te[6] = 0;\\n te[10] = -2 * p;\\n te[14] = -z;\\n te[3] = 0;\\n te[7] = 0;\\n te[11] = 0;\\n te[15] = 1;\\n return this;\\n }\\n equals(matrix) {\\n const te = this.elements;\\n const me = matrix.elements;\\n for (let i = 0; i < 16; i++) {\\n if (te[i] !== me[i])\\n return false;\\n }\\n return true;\\n }\\n fromArray(array, offset = 0) {\\n for (let i = 0; i < 16; i++) {\\n this.elements[i] = array[i + offset];\\n }\\n return this;\\n }\\n toArray(array = [], offset = 0) {\\n const te = this.elements;\\n array[offset] = te[0];\\n array[offset + 1] = te[1];\\n array[offset + 2] = te[2];\\n array[offset + 3] = te[3];\\n array[offset + 4] = te[4];\\n array[offset + 5] = te[5];\\n array[offset + 6] = te[6];\\n array[offset + 7] = te[7];\\n array[offset + 8] = te[8];\\n array[offset + 9] = te[9];\\n array[offset + 10] = te[10];\\n array[offset + 11] = te[11];\\n array[offset + 12] = te[12];\\n array[offset + 13] = te[13];\\n array[offset + 14] = te[14];\\n array[offset + 15] = te[15];\\n return array;\\n }\\n};\\nMatrix4.prototype.isMatrix4 = true;\\nvar _v1 = /* @__PURE__ */ new Vector3();\\nvar _m1 = /* @__PURE__ */ new Matrix4();\\nvar _zero = /* @__PURE__ */ new Vector3(0, 0, 0);\\nvar _one = /* @__PURE__ */ new Vector3(1, 1, 1);\\nvar _x = /* @__PURE__ */ new Vector3();\\nvar _y = /* @__PURE__ */ new Vector3();\\nvar _z = /* @__PURE__ */ new Vector3();\\n\\n// ../../../node_modules/three/src/core/EventDispatcher.js\\nvar EventDispatcher = class {\\n addEventListener(type, listener) {\\n if (this._listeners === void 0)\\n this._listeners = {};\\n const listeners = this._listeners;\\n if (listeners[type] === void 0) {\\n listeners[type] = [];\\n }\\n if (listeners[type].indexOf(listener) === -1) {\\n listeners[type].push(listener);\\n }\\n }\\n hasEventListener(type, listener) {\\n if (this._listeners === void 0)\\n return false;\\n const listeners = this._listeners;\\n return listeners[type] !== void 0 && listeners[type].indexOf(listener) !== -1;\\n }\\n removeEventListener(type, listener) {\\n if (this._listeners === void 0)\\n return;\\n const listeners = this._listeners;\\n const listenerArray = listeners[type];\\n if (listenerArray !== void 0) {\\n const index = listenerArray.indexOf(listener);\\n if (index !== -1) {\\n listenerArray.splice(index, 1);\\n }\\n }\\n }\\n dispatchEvent(event) {\\n if (this._listeners === void 0)\\n return;\\n const listeners = this._listeners;\\n const listenerArray = listeners[event.type];\\n if (listenerArray !== void 0) {\\n event.target = this;\\n const array = listenerArray.slice(0);\\n for (let i = 0, l = array.length; i < l; i++) {\\n array[i].call(this, event);\\n }\\n event.target = null;\\n }\\n }\\n};\\n\\n// ../../../node_modules/three/src/math/Euler.js\\nvar _matrix = /* @__PURE__ */ new Matrix4();\\nvar _quaternion2 = /* @__PURE__ */ new Quaternion();\\nvar Euler = class {\\n constructor(x = 0, y = 0, z = 0, order = Euler.DefaultOrder) {\\n this._x = x;\\n this._y = y;\\n this._z = z;\\n this._order = order;\\n }\\n get x() {\\n return this._x;\\n }\\n set x(value) {\\n this._x = value;\\n this._onChangeCallback();\\n }\\n get y() {\\n return this._y;\\n }\\n set y(value) {\\n this._y = value;\\n this._onChangeCallback();\\n }\\n get z() {\\n return this._z;\\n }\\n set z(value) {\\n this._z = value;\\n this._onChangeCallback();\\n }\\n get order() {\\n return this._order;\\n }\\n set order(value) {\\n this._order = value;\\n this._onChangeCallback();\\n }\\n set(x, y, z, order = this._order) {\\n this._x = x;\\n this._y = y;\\n this._z = z;\\n this._order = order;\\n this._onChangeCallback();\\n return this;\\n }\\n clone() {\\n return new this.constructor(this._x, this._y, this._z, this._order);\\n }\\n copy(euler) {\\n this._x = euler._x;\\n this._y = euler._y;\\n this._z = euler._z;\\n this._order = euler._order;\\n this._onChangeCallback();\\n return this;\\n }\\n setFromRotationMatrix(m, order = this._order, update = true) {\\n const te = m.elements;\\n const m11 = te[0], m12 = te[4], m13 = te[8];\\n const m21 = te[1], m22 = te[5], m23 = te[9];\\n const m31 = te[2], m32 = te[6], m33 = te[10];\\n switch (order) {\\n case \\\\\\\"XYZ\\\\\\\":\\n this._y = Math.asin(clamp(m13, -1, 1));\\n if (Math.abs(m13) < 0.9999999) {\\n this._x = Math.atan2(-m23, m33);\\n this._z = Math.atan2(-m12, m11);\\n } else {\\n this._x = Math.atan2(m32, m22);\\n this._z = 0;\\n }\\n break;\\n case \\\\\\\"YXZ\\\\\\\":\\n this._x = Math.asin(-clamp(m23, -1, 1));\\n if (Math.abs(m23) < 0.9999999) {\\n this._y = Math.atan2(m13, m33);\\n this._z = Math.atan2(m21, m22);\\n } else {\\n this._y = Math.atan2(-m31, m11);\\n this._z = 0;\\n }\\n break;\\n case \\\\\\\"ZXY\\\\\\\":\\n this._x = Math.asin(clamp(m32, -1, 1));\\n if (Math.abs(m32) < 0.9999999) {\\n this._y = Math.atan2(-m31, m33);\\n this._z = Math.atan2(-m12, m22);\\n } else {\\n this._y = 0;\\n this._z = Math.atan2(m21, m11);\\n }\\n break;\\n case \\\\\\\"ZYX\\\\\\\":\\n this._y = Math.asin(-clamp(m31, -1, 1));\\n if (Math.abs(m31) < 0.9999999) {\\n this._x = Math.atan2(m32, m33);\\n this._z = Math.atan2(m21, m11);\\n } else {\\n this._x = 0;\\n this._z = Math.atan2(-m12, m22);\\n }\\n break;\\n case \\\\\\\"YZX\\\\\\\":\\n this._z = Math.asin(clamp(m21, -1, 1));\\n if (Math.abs(m21) < 0.9999999) {\\n this._x = Math.atan2(-m23, m22);\\n this._y = Math.atan2(-m31, m11);\\n } else {\\n this._x = 0;\\n this._y = Math.atan2(m13, m33);\\n }\\n break;\\n case \\\\\\\"XZY\\\\\\\":\\n this._z = Math.asin(-clamp(m12, -1, 1));\\n if (Math.abs(m12) < 0.9999999) {\\n this._x = Math.atan2(m32, m22);\\n this._y = Math.atan2(m13, m11);\\n } else {\\n this._x = Math.atan2(-m23, m33);\\n this._y = 0;\\n }\\n break;\\n default:\\n console.warn(\\\\\\\"THREE.Euler: .setFromRotationMatrix() encountered an unknown order: \\\\\\\" + order);\\n }\\n this._order = order;\\n if (update === true)\\n this._onChangeCallback();\\n return this;\\n }\\n setFromQuaternion(q, order, update) {\\n _matrix.makeRotationFromQuaternion(q);\\n return this.setFromRotationMatrix(_matrix, order, update);\\n }\\n setFromVector3(v, order = this._order) {\\n return this.set(v.x, v.y, v.z, order);\\n }\\n reorder(newOrder) {\\n _quaternion2.setFromEuler(this);\\n return this.setFromQuaternion(_quaternion2, newOrder);\\n }\\n equals(euler) {\\n return euler._x === this._x && euler._y === this._y && euler._z === this._z && euler._order === this._order;\\n }\\n fromArray(array) {\\n this._x = array[0];\\n this._y = array[1];\\n this._z = array[2];\\n if (array[3] !== void 0)\\n this._order = array[3];\\n this._onChangeCallback();\\n return this;\\n }\\n toArray(array = [], offset = 0) {\\n array[offset] = this._x;\\n array[offset + 1] = this._y;\\n array[offset + 2] = this._z;\\n array[offset + 3] = this._order;\\n return array;\\n }\\n toVector3(optionalResult) {\\n if (optionalResult) {\\n return optionalResult.set(this._x, this._y, this._z);\\n } else {\\n return new Vector3(this._x, this._y, this._z);\\n }\\n }\\n _onChange(callback) {\\n this._onChangeCallback = callback;\\n return this;\\n }\\n _onChangeCallback() {\\n }\\n};\\nEuler.prototype.isEuler = true;\\nEuler.DefaultOrder = \\\\\\\"XYZ\\\\\\\";\\nEuler.RotationOrders = [\\\\\\\"XYZ\\\\\\\", \\\\\\\"YZX\\\\\\\", \\\\\\\"ZXY\\\\\\\", \\\\\\\"XZY\\\\\\\", \\\\\\\"YXZ\\\\\\\", \\\\\\\"ZYX\\\\\\\"];\\n\\n// ../../../node_modules/three/src/core/Layers.js\\nvar Layers = class {\\n constructor() {\\n this.mask = 1 | 0;\\n }\\n set(channel) {\\n this.mask = 1 << channel | 0;\\n }\\n enable(channel) {\\n this.mask |= 1 << channel | 0;\\n }\\n enableAll() {\\n this.mask = 4294967295 | 0;\\n }\\n toggle(channel) {\\n this.mask ^= 1 << channel | 0;\\n }\\n disable(channel) {\\n this.mask &= ~(1 << channel | 0);\\n }\\n disableAll() {\\n this.mask = 0;\\n }\\n test(layers) {\\n return (this.mask & layers.mask) !== 0;\\n }\\n};\\n\\n// ../../../node_modules/three/src/math/Matrix3.js\\nvar Matrix3 = class {\\n constructor() {\\n this.elements = [\\n 1,\\n 0,\\n 0,\\n 0,\\n 1,\\n 0,\\n 0,\\n 0,\\n 1\\n ];\\n if (arguments.length > 0) {\\n console.error(\\\\\\\"THREE.Matrix3: the constructor no longer reads arguments. use .set() instead.\\\\\\\");\\n }\\n }\\n set(n11, n12, n13, n21, n22, n23, n31, n32, n33) {\\n const te = this.elements;\\n te[0] = n11;\\n te[1] = n21;\\n te[2] = n31;\\n te[3] = n12;\\n te[4] = n22;\\n te[5] = n32;\\n te[6] = n13;\\n te[7] = n23;\\n te[8] = n33;\\n return this;\\n }\\n identity() {\\n this.set(1, 0, 0, 0, 1, 0, 0, 0, 1);\\n return this;\\n }\\n copy(m) {\\n const te = this.elements;\\n const me = m.elements;\\n te[0] = me[0];\\n te[1] = me[1];\\n te[2] = me[2];\\n te[3] = me[3];\\n te[4] = me[4];\\n te[5] = me[5];\\n te[6] = me[6];\\n te[7] = me[7];\\n te[8] = me[8];\\n return this;\\n }\\n extractBasis(xAxis, yAxis, zAxis) {\\n xAxis.setFromMatrix3Column(this, 0);\\n yAxis.setFromMatrix3Column(this, 1);\\n zAxis.setFromMatrix3Column(this, 2);\\n return this;\\n }\\n setFromMatrix4(m) {\\n const me = m.elements;\\n this.set(me[0], me[4], me[8], me[1], me[5], me[9], me[2], me[6], me[10]);\\n return this;\\n }\\n multiply(m) {\\n return this.multiplyMatrices(this, m);\\n }\\n premultiply(m) {\\n return this.multiplyMatrices(m, this);\\n }\\n multiplyMatrices(a, b) {\\n const ae = a.elements;\\n const be = b.elements;\\n const te = this.elements;\\n const a11 = ae[0], a12 = ae[3], a13 = ae[6];\\n const a21 = ae[1], a22 = ae[4], a23 = ae[7];\\n const a31 = ae[2], a32 = ae[5], a33 = ae[8];\\n const b11 = be[0], b12 = be[3], b13 = be[6];\\n const b21 = be[1], b22 = be[4], b23 = be[7];\\n const b31 = be[2], b32 = be[5], b33 = be[8];\\n te[0] = a11 * b11 + a12 * b21 + a13 * b31;\\n te[3] = a11 * b12 + a12 * b22 + a13 * b32;\\n te[6] = a11 * b13 + a12 * b23 + a13 * b33;\\n te[1] = a21 * b11 + a22 * b21 + a23 * b31;\\n te[4] = a21 * b12 + a22 * b22 + a23 * b32;\\n te[7] = a21 * b13 + a22 * b23 + a23 * b33;\\n te[2] = a31 * b11 + a32 * b21 + a33 * b31;\\n te[5] = a31 * b12 + a32 * b22 + a33 * b32;\\n te[8] = a31 * b13 + a32 * b23 + a33 * b33;\\n return this;\\n }\\n multiplyScalar(s) {\\n const te = this.elements;\\n te[0] *= s;\\n te[3] *= s;\\n te[6] *= s;\\n te[1] *= s;\\n te[4] *= s;\\n te[7] *= s;\\n te[2] *= s;\\n te[5] *= s;\\n te[8] *= s;\\n return this;\\n }\\n determinant() {\\n const te = this.elements;\\n const a = te[0], b = te[1], c = te[2], d = te[3], e = te[4], f = te[5], g = te[6], h = te[7], i = te[8];\\n return a * e * i - a * f * h - b * d * i + b * f * g + c * d * h - c * e * g;\\n }\\n invert() {\\n const te = this.elements, n11 = te[0], n21 = te[1], n31 = te[2], n12 = te[3], n22 = te[4], n32 = te[5], n13 = te[6], n23 = te[7], n33 = te[8], t11 = n33 * n22 - n32 * n23, t12 = n32 * n13 - n33 * n12, t13 = n23 * n12 - n22 * n13, det = n11 * t11 + n21 * t12 + n31 * t13;\\n if (det === 0)\\n return this.set(0, 0, 0, 0, 0, 0, 0, 0, 0);\\n const detInv = 1 / det;\\n te[0] = t11 * detInv;\\n te[1] = (n31 * n23 - n33 * n21) * detInv;\\n te[2] = (n32 * n21 - n31 * n22) * detInv;\\n te[3] = t12 * detInv;\\n te[4] = (n33 * n11 - n31 * n13) * detInv;\\n te[5] = (n31 * n12 - n32 * n11) * detInv;\\n te[6] = t13 * detInv;\\n te[7] = (n21 * n13 - n23 * n11) * detInv;\\n te[8] = (n22 * n11 - n21 * n12) * detInv;\\n return this;\\n }\\n transpose() {\\n let tmp;\\n const m = this.elements;\\n tmp = m[1];\\n m[1] = m[3];\\n m[3] = tmp;\\n tmp = m[2];\\n m[2] = m[6];\\n m[6] = tmp;\\n tmp = m[5];\\n m[5] = m[7];\\n m[7] = tmp;\\n return this;\\n }\\n getNormalMatrix(matrix4) {\\n return this.setFromMatrix4(matrix4).invert().transpose();\\n }\\n transposeIntoArray(r) {\\n const m = this.elements;\\n r[0] = m[0];\\n r[1] = m[3];\\n r[2] = m[6];\\n r[3] = m[1];\\n r[4] = m[4];\\n r[5] = m[7];\\n r[6] = m[2];\\n r[7] = m[5];\\n r[8] = m[8];\\n return this;\\n }\\n setUvTransform(tx, ty, sx, sy, rotation, cx, cy) {\\n const c = Math.cos(rotation);\\n const s = Math.sin(rotation);\\n this.set(sx * c, sx * s, -sx * (c * cx + s * cy) + cx + tx, -sy * s, sy * c, -sy * (-s * cx + c * cy) + cy + ty, 0, 0, 1);\\n return this;\\n }\\n scale(sx, sy) {\\n const te = this.elements;\\n te[0] *= sx;\\n te[3] *= sx;\\n te[6] *= sx;\\n te[1] *= sy;\\n te[4] *= sy;\\n te[7] *= sy;\\n return this;\\n }\\n rotate(theta) {\\n const c = Math.cos(theta);\\n const s = Math.sin(theta);\\n const te = this.elements;\\n const a11 = te[0], a12 = te[3], a13 = te[6];\\n const a21 = te[1], a22 = te[4], a23 = te[7];\\n te[0] = c * a11 + s * a21;\\n te[3] = c * a12 + s * a22;\\n te[6] = c * a13 + s * a23;\\n te[1] = -s * a11 + c * a21;\\n te[4] = -s * a12 + c * a22;\\n te[7] = -s * a13 + c * a23;\\n return this;\\n }\\n translate(tx, ty) {\\n const te = this.elements;\\n te[0] += tx * te[2];\\n te[3] += tx * te[5];\\n te[6] += tx * te[8];\\n te[1] += ty * te[2];\\n te[4] += ty * te[5];\\n te[7] += ty * te[8];\\n return this;\\n }\\n equals(matrix) {\\n const te = this.elements;\\n const me = matrix.elements;\\n for (let i = 0; i < 9; i++) {\\n if (te[i] !== me[i])\\n return false;\\n }\\n return true;\\n }\\n fromArray(array, offset = 0) {\\n for (let i = 0; i < 9; i++) {\\n this.elements[i] = array[i + offset];\\n }\\n return this;\\n }\\n toArray(array = [], offset = 0) {\\n const te = this.elements;\\n array[offset] = te[0];\\n array[offset + 1] = te[1];\\n array[offset + 2] = te[2];\\n array[offset + 3] = te[3];\\n array[offset + 4] = te[4];\\n array[offset + 5] = te[5];\\n array[offset + 6] = te[6];\\n array[offset + 7] = te[7];\\n array[offset + 8] = te[8];\\n return array;\\n }\\n clone() {\\n return new this.constructor().fromArray(this.elements);\\n }\\n};\\nMatrix3.prototype.isMatrix3 = true;\\n\\n// ../../../node_modules/three/src/core/Object3D.js\\nvar _object3DId = 0;\\nvar _v12 = /* @__PURE__ */ new Vector3();\\nvar _q1 = /* @__PURE__ */ new Quaternion();\\nvar _m12 = /* @__PURE__ */ new Matrix4();\\nvar _target = /* @__PURE__ */ new Vector3();\\nvar _position = /* @__PURE__ */ new Vector3();\\nvar _scale = /* @__PURE__ */ new Vector3();\\nvar _quaternion3 = /* @__PURE__ */ new Quaternion();\\nvar _xAxis = /* @__PURE__ */ new Vector3(1, 0, 0);\\nvar _yAxis = /* @__PURE__ */ new Vector3(0, 1, 0);\\nvar _zAxis = /* @__PURE__ */ new Vector3(0, 0, 1);\\nvar _addedEvent = {type: \\\\\\\"added\\\\\\\"};\\nvar _removedEvent = {type: \\\\\\\"removed\\\\\\\"};\\nvar Object3D = class extends EventDispatcher {\\n constructor() {\\n super();\\n Object.defineProperty(this, \\\\\\\"id\\\\\\\", {value: _object3DId++});\\n this.uuid = generateUUID();\\n this.name = \\\\\\\"\\\\\\\";\\n this.type = \\\\\\\"Object3D\\\\\\\";\\n this.parent = null;\\n this.children = [];\\n this.up = Object3D.DefaultUp.clone();\\n const position = new Vector3();\\n const rotation = new Euler();\\n const quaternion = new Quaternion();\\n const scale = new Vector3(1, 1, 1);\\n function onRotationChange() {\\n quaternion.setFromEuler(rotation, false);\\n }\\n function onQuaternionChange() {\\n rotation.setFromQuaternion(quaternion, void 0, false);\\n }\\n rotation._onChange(onRotationChange);\\n quaternion._onChange(onQuaternionChange);\\n Object.defineProperties(this, {\\n position: {\\n configurable: true,\\n enumerable: true,\\n value: position\\n },\\n rotation: {\\n configurable: true,\\n enumerable: true,\\n value: rotation\\n },\\n quaternion: {\\n configurable: true,\\n enumerable: true,\\n value: quaternion\\n },\\n scale: {\\n configurable: true,\\n enumerable: true,\\n value: scale\\n },\\n modelViewMatrix: {\\n value: new Matrix4()\\n },\\n normalMatrix: {\\n value: new Matrix3()\\n }\\n });\\n this.matrix = new Matrix4();\\n this.matrixWorld = new Matrix4();\\n this.matrixAutoUpdate = Object3D.DefaultMatrixAutoUpdate;\\n this.matrixWorldNeedsUpdate = false;\\n this.layers = new Layers();\\n this.visible = true;\\n this.castShadow = false;\\n this.receiveShadow = false;\\n this.frustumCulled = true;\\n this.renderOrder = 0;\\n this.animations = [];\\n this.userData = {};\\n }\\n onBeforeRender() {\\n }\\n onAfterRender() {\\n }\\n applyMatrix4(matrix) {\\n if (this.matrixAutoUpdate)\\n this.updateMatrix();\\n this.matrix.premultiply(matrix);\\n this.matrix.decompose(this.position, this.quaternion, this.scale);\\n }\\n applyQuaternion(q) {\\n this.quaternion.premultiply(q);\\n return this;\\n }\\n setRotationFromAxisAngle(axis, angle) {\\n this.quaternion.setFromAxisAngle(axis, angle);\\n }\\n setRotationFromEuler(euler) {\\n this.quaternion.setFromEuler(euler, true);\\n }\\n setRotationFromMatrix(m) {\\n this.quaternion.setFromRotationMatrix(m);\\n }\\n setRotationFromQuaternion(q) {\\n this.quaternion.copy(q);\\n }\\n rotateOnAxis(axis, angle) {\\n _q1.setFromAxisAngle(axis, angle);\\n this.quaternion.multiply(_q1);\\n return this;\\n }\\n rotateOnWorldAxis(axis, angle) {\\n _q1.setFromAxisAngle(axis, angle);\\n this.quaternion.premultiply(_q1);\\n return this;\\n }\\n rotateX(angle) {\\n return this.rotateOnAxis(_xAxis, angle);\\n }\\n rotateY(angle) {\\n return this.rotateOnAxis(_yAxis, angle);\\n }\\n rotateZ(angle) {\\n return this.rotateOnAxis(_zAxis, angle);\\n }\\n translateOnAxis(axis, distance) {\\n _v12.copy(axis).applyQuaternion(this.quaternion);\\n this.position.add(_v12.multiplyScalar(distance));\\n return this;\\n }\\n translateX(distance) {\\n return this.translateOnAxis(_xAxis, distance);\\n }\\n translateY(distance) {\\n return this.translateOnAxis(_yAxis, distance);\\n }\\n translateZ(distance) {\\n return this.translateOnAxis(_zAxis, distance);\\n }\\n localToWorld(vector) {\\n return vector.applyMatrix4(this.matrixWorld);\\n }\\n worldToLocal(vector) {\\n return vector.applyMatrix4(_m12.copy(this.matrixWorld).invert());\\n }\\n lookAt(x, y, z) {\\n if (x.isVector3) {\\n _target.copy(x);\\n } else {\\n _target.set(x, y, z);\\n }\\n const parent = this.parent;\\n this.updateWorldMatrix(true, false);\\n _position.setFromMatrixPosition(this.matrixWorld);\\n if (this.isCamera || this.isLight) {\\n _m12.lookAt(_position, _target, this.up);\\n } else {\\n _m12.lookAt(_target, _position, this.up);\\n }\\n this.quaternion.setFromRotationMatrix(_m12);\\n if (parent) {\\n _m12.extractRotation(parent.matrixWorld);\\n _q1.setFromRotationMatrix(_m12);\\n this.quaternion.premultiply(_q1.invert());\\n }\\n }\\n add(object) {\\n if (arguments.length > 1) {\\n for (let i = 0; i < arguments.length; i++) {\\n this.add(arguments[i]);\\n }\\n return this;\\n }\\n if (object === this) {\\n console.error(\\\\\\\"THREE.Object3D.add: object can't be added as a child of itself.\\\\\\\", object);\\n return this;\\n }\\n if (object && object.isObject3D) {\\n if (object.parent !== null) {\\n object.parent.remove(object);\\n }\\n object.parent = this;\\n this.children.push(object);\\n object.dispatchEvent(_addedEvent);\\n } else {\\n console.error(\\\\\\\"THREE.Object3D.add: object not an instance of THREE.Object3D.\\\\\\\", object);\\n }\\n return this;\\n }\\n remove(object) {\\n if (arguments.length > 1) {\\n for (let i = 0; i < arguments.length; i++) {\\n this.remove(arguments[i]);\\n }\\n return this;\\n }\\n const index = this.children.indexOf(object);\\n if (index !== -1) {\\n object.parent = null;\\n this.children.splice(index, 1);\\n object.dispatchEvent(_removedEvent);\\n }\\n return this;\\n }\\n removeFromParent() {\\n const parent = this.parent;\\n if (parent !== null) {\\n parent.remove(this);\\n }\\n return this;\\n }\\n clear() {\\n for (let i = 0; i < this.children.length; i++) {\\n const object = this.children[i];\\n object.parent = null;\\n object.dispatchEvent(_removedEvent);\\n }\\n this.children.length = 0;\\n return this;\\n }\\n attach(object) {\\n this.updateWorldMatrix(true, false);\\n _m12.copy(this.matrixWorld).invert();\\n if (object.parent !== null) {\\n object.parent.updateWorldMatrix(true, false);\\n _m12.multiply(object.parent.matrixWorld);\\n }\\n object.applyMatrix4(_m12);\\n this.add(object);\\n object.updateWorldMatrix(false, true);\\n return this;\\n }\\n getObjectById(id) {\\n return this.getObjectByProperty(\\\\\\\"id\\\\\\\", id);\\n }\\n getObjectByName(name) {\\n return this.getObjectByProperty(\\\\\\\"name\\\\\\\", name);\\n }\\n getObjectByProperty(name, value) {\\n if (this[name] === value)\\n return this;\\n for (let i = 0, l = this.children.length; i < l; i++) {\\n const child = this.children[i];\\n const object = child.getObjectByProperty(name, value);\\n if (object !== void 0) {\\n return object;\\n }\\n }\\n return void 0;\\n }\\n getWorldPosition(target) {\\n this.updateWorldMatrix(true, false);\\n return target.setFromMatrixPosition(this.matrixWorld);\\n }\\n getWorldQuaternion(target) {\\n this.updateWorldMatrix(true, false);\\n this.matrixWorld.decompose(_position, target, _scale);\\n return target;\\n }\\n getWorldScale(target) {\\n this.updateWorldMatrix(true, false);\\n this.matrixWorld.decompose(_position, _quaternion3, target);\\n return target;\\n }\\n getWorldDirection(target) {\\n this.updateWorldMatrix(true, false);\\n const e = this.matrixWorld.elements;\\n return target.set(e[8], e[9], e[10]).normalize();\\n }\\n raycast() {\\n }\\n traverse(callback) {\\n callback(this);\\n const children = this.children;\\n for (let i = 0, l = children.length; i < l; i++) {\\n children[i].traverse(callback);\\n }\\n }\\n traverseVisible(callback) {\\n if (this.visible === false)\\n return;\\n callback(this);\\n const children = this.children;\\n for (let i = 0, l = children.length; i < l; i++) {\\n children[i].traverseVisible(callback);\\n }\\n }\\n traverseAncestors(callback) {\\n const parent = this.parent;\\n if (parent !== null) {\\n callback(parent);\\n parent.traverseAncestors(callback);\\n }\\n }\\n updateMatrix() {\\n this.matrix.compose(this.position, this.quaternion, this.scale);\\n this.matrixWorldNeedsUpdate = true;\\n }\\n updateMatrixWorld(force) {\\n if (this.matrixAutoUpdate)\\n this.updateMatrix();\\n if (this.matrixWorldNeedsUpdate || force) {\\n if (this.parent === null) {\\n this.matrixWorld.copy(this.matrix);\\n } else {\\n this.matrixWorld.multiplyMatrices(this.parent.matrixWorld, this.matrix);\\n }\\n this.matrixWorldNeedsUpdate = false;\\n force = true;\\n }\\n const children = this.children;\\n for (let i = 0, l = children.length; i < l; i++) {\\n children[i].updateMatrixWorld(force);\\n }\\n }\\n updateWorldMatrix(updateParents, updateChildren) {\\n const parent = this.parent;\\n if (updateParents === true && parent !== null) {\\n parent.updateWorldMatrix(true, false);\\n }\\n if (this.matrixAutoUpdate)\\n this.updateMatrix();\\n if (this.parent === null) {\\n this.matrixWorld.copy(this.matrix);\\n } else {\\n this.matrixWorld.multiplyMatrices(this.parent.matrixWorld, this.matrix);\\n }\\n if (updateChildren === true) {\\n const children = this.children;\\n for (let i = 0, l = children.length; i < l; i++) {\\n children[i].updateWorldMatrix(false, true);\\n }\\n }\\n }\\n toJSON(meta) {\\n const isRootObject = meta === void 0 || typeof meta === \\\\\\\"string\\\\\\\";\\n const output = {};\\n if (isRootObject) {\\n meta = {\\n geometries: {},\\n materials: {},\\n textures: {},\\n images: {},\\n shapes: {},\\n skeletons: {},\\n animations: {}\\n };\\n output.metadata = {\\n version: 4.5,\\n type: \\\\\\\"Object\\\\\\\",\\n generator: \\\\\\\"Object3D.toJSON\\\\\\\"\\n };\\n }\\n const object = {};\\n object.uuid = this.uuid;\\n object.type = this.type;\\n if (this.name !== \\\\\\\"\\\\\\\")\\n object.name = this.name;\\n if (this.castShadow === true)\\n object.castShadow = true;\\n if (this.receiveShadow === true)\\n object.receiveShadow = true;\\n if (this.visible === false)\\n object.visible = false;\\n if (this.frustumCulled === false)\\n object.frustumCulled = false;\\n if (this.renderOrder !== 0)\\n object.renderOrder = this.renderOrder;\\n if (JSON.stringify(this.userData) !== \\\\\\\"{}\\\\\\\")\\n object.userData = this.userData;\\n object.layers = this.layers.mask;\\n object.matrix = this.matrix.toArray();\\n if (this.matrixAutoUpdate === false)\\n object.matrixAutoUpdate = false;\\n if (this.isInstancedMesh) {\\n object.type = \\\\\\\"InstancedMesh\\\\\\\";\\n object.count = this.count;\\n object.instanceMatrix = this.instanceMatrix.toJSON();\\n if (this.instanceColor !== null)\\n object.instanceColor = this.instanceColor.toJSON();\\n }\\n function serialize(library, element) {\\n if (library[element.uuid] === void 0) {\\n library[element.uuid] = element.toJSON(meta);\\n }\\n return element.uuid;\\n }\\n if (this.isScene) {\\n if (this.background) {\\n if (this.background.isColor) {\\n object.background = this.background.toJSON();\\n } else if (this.background.isTexture) {\\n object.background = this.background.toJSON(meta).uuid;\\n }\\n }\\n if (this.environment && this.environment.isTexture) {\\n object.environment = this.environment.toJSON(meta).uuid;\\n }\\n } else if (this.isMesh || this.isLine || this.isPoints) {\\n object.geometry = serialize(meta.geometries, this.geometry);\\n const parameters = this.geometry.parameters;\\n if (parameters !== void 0 && parameters.shapes !== void 0) {\\n const shapes = parameters.shapes;\\n if (Array.isArray(shapes)) {\\n for (let i = 0, l = shapes.length; i < l; i++) {\\n const shape = shapes[i];\\n serialize(meta.shapes, shape);\\n }\\n } else {\\n serialize(meta.shapes, shapes);\\n }\\n }\\n }\\n if (this.isSkinnedMesh) {\\n object.bindMode = this.bindMode;\\n object.bindMatrix = this.bindMatrix.toArray();\\n if (this.skeleton !== void 0) {\\n serialize(meta.skeletons, this.skeleton);\\n object.skeleton = this.skeleton.uuid;\\n }\\n }\\n if (this.material !== void 0) {\\n if (Array.isArray(this.material)) {\\n const uuids = [];\\n for (let i = 0, l = this.material.length; i < l; i++) {\\n uuids.push(serialize(meta.materials, this.material[i]));\\n }\\n object.material = uuids;\\n } else {\\n object.material = serialize(meta.materials, this.material);\\n }\\n }\\n if (this.children.length > 0) {\\n object.children = [];\\n for (let i = 0; i < this.children.length; i++) {\\n object.children.push(this.children[i].toJSON(meta).object);\\n }\\n }\\n if (this.animations.length > 0) {\\n object.animations = [];\\n for (let i = 0; i < this.animations.length; i++) {\\n const animation = this.animations[i];\\n object.animations.push(serialize(meta.animations, animation));\\n }\\n }\\n if (isRootObject) {\\n const geometries = extractFromCache(meta.geometries);\\n const materials2 = extractFromCache(meta.materials);\\n const textures = extractFromCache(meta.textures);\\n const images = extractFromCache(meta.images);\\n const shapes = extractFromCache(meta.shapes);\\n const skeletons = extractFromCache(meta.skeletons);\\n const animations = extractFromCache(meta.animations);\\n if (geometries.length > 0)\\n output.geometries = geometries;\\n if (materials2.length > 0)\\n output.materials = materials2;\\n if (textures.length > 0)\\n output.textures = textures;\\n if (images.length > 0)\\n output.images = images;\\n if (shapes.length > 0)\\n output.shapes = shapes;\\n if (skeletons.length > 0)\\n output.skeletons = skeletons;\\n if (animations.length > 0)\\n output.animations = animations;\\n }\\n output.object = object;\\n return output;\\n function extractFromCache(cache) {\\n const values = [];\\n for (const key in cache) {\\n const data = cache[key];\\n delete data.metadata;\\n values.push(data);\\n }\\n return values;\\n }\\n }\\n clone(recursive) {\\n return new this.constructor().copy(this, recursive);\\n }\\n copy(source, recursive = true) {\\n this.name = source.name;\\n this.up.copy(source.up);\\n this.position.copy(source.position);\\n this.rotation.order = source.rotation.order;\\n this.quaternion.copy(source.quaternion);\\n this.scale.copy(source.scale);\\n this.matrix.copy(source.matrix);\\n this.matrixWorld.copy(source.matrixWorld);\\n this.matrixAutoUpdate = source.matrixAutoUpdate;\\n this.matrixWorldNeedsUpdate = source.matrixWorldNeedsUpdate;\\n this.layers.mask = source.layers.mask;\\n this.visible = source.visible;\\n this.castShadow = source.castShadow;\\n this.receiveShadow = source.receiveShadow;\\n this.frustumCulled = source.frustumCulled;\\n this.renderOrder = source.renderOrder;\\n this.userData = JSON.parse(JSON.stringify(source.userData));\\n if (recursive === true) {\\n for (let i = 0; i < source.children.length; i++) {\\n const child = source.children[i];\\n this.add(child.clone());\\n }\\n }\\n return this;\\n }\\n};\\nObject3D.DefaultUp = new Vector3(0, 1, 0);\\nObject3D.DefaultMatrixAutoUpdate = true;\\nObject3D.prototype.isObject3D = true;\\n\\n// ../../../node_modules/three/src/constants.js\\nvar CullFaceNone = 0;\\nvar CullFaceBack = 1;\\nvar CullFaceFront = 2;\\nvar PCFShadowMap = 1;\\nvar PCFSoftShadowMap = 2;\\nvar VSMShadowMap = 3;\\nvar FrontSide = 0;\\nvar BackSide = 1;\\nvar DoubleSide = 2;\\nvar FlatShading = 1;\\nvar NoBlending = 0;\\nvar NormalBlending = 1;\\nvar AdditiveBlending = 2;\\nvar SubtractiveBlending = 3;\\nvar MultiplyBlending = 4;\\nvar CustomBlending = 5;\\nvar AddEquation = 100;\\nvar SubtractEquation = 101;\\nvar ReverseSubtractEquation = 102;\\nvar MinEquation = 103;\\nvar MaxEquation = 104;\\nvar ZeroFactor = 200;\\nvar OneFactor = 201;\\nvar SrcColorFactor = 202;\\nvar OneMinusSrcColorFactor = 203;\\nvar SrcAlphaFactor = 204;\\nvar OneMinusSrcAlphaFactor = 205;\\nvar DstAlphaFactor = 206;\\nvar OneMinusDstAlphaFactor = 207;\\nvar DstColorFactor = 208;\\nvar OneMinusDstColorFactor = 209;\\nvar SrcAlphaSaturateFactor = 210;\\nvar NeverDepth = 0;\\nvar AlwaysDepth = 1;\\nvar LessDepth = 2;\\nvar LessEqualDepth = 3;\\nvar EqualDepth = 4;\\nvar GreaterEqualDepth = 5;\\nvar GreaterDepth = 6;\\nvar NotEqualDepth = 7;\\nvar MultiplyOperation = 0;\\nvar MixOperation = 1;\\nvar AddOperation = 2;\\nvar NoToneMapping = 0;\\nvar LinearToneMapping = 1;\\nvar ReinhardToneMapping = 2;\\nvar CineonToneMapping = 3;\\nvar ACESFilmicToneMapping = 4;\\nvar CustomToneMapping = 5;\\nvar UVMapping = 300;\\nvar CubeReflectionMapping = 301;\\nvar CubeRefractionMapping = 302;\\nvar EquirectangularReflectionMapping = 303;\\nvar EquirectangularRefractionMapping = 304;\\nvar CubeUVReflectionMapping = 306;\\nvar CubeUVRefractionMapping = 307;\\nvar RepeatWrapping = 1e3;\\nvar ClampToEdgeWrapping = 1001;\\nvar MirroredRepeatWrapping = 1002;\\nvar NearestFilter = 1003;\\nvar NearestMipmapNearestFilter = 1004;\\nvar NearestMipmapLinearFilter = 1005;\\nvar LinearFilter = 1006;\\nvar LinearMipmapNearestFilter = 1007;\\nvar LinearMipmapLinearFilter = 1008;\\nvar UnsignedByteType = 1009;\\nvar ByteType = 1010;\\nvar ShortType = 1011;\\nvar UnsignedShortType = 1012;\\nvar IntType = 1013;\\nvar UnsignedIntType = 1014;\\nvar FloatType = 1015;\\nvar HalfFloatType = 1016;\\nvar UnsignedShort4444Type = 1017;\\nvar UnsignedShort5551Type = 1018;\\nvar UnsignedShort565Type = 1019;\\nvar UnsignedInt248Type = 1020;\\nvar AlphaFormat = 1021;\\nvar RGBFormat = 1022;\\nvar RGBAFormat = 1023;\\nvar LuminanceFormat = 1024;\\nvar LuminanceAlphaFormat = 1025;\\nvar RGBEFormat = RGBAFormat;\\nvar DepthFormat = 1026;\\nvar DepthStencilFormat = 1027;\\nvar RedFormat = 1028;\\nvar RedIntegerFormat = 1029;\\nvar RGFormat = 1030;\\nvar RGIntegerFormat = 1031;\\nvar RGBIntegerFormat = 1032;\\nvar RGBAIntegerFormat = 1033;\\nvar RGB_S3TC_DXT1_Format = 33776;\\nvar RGBA_S3TC_DXT1_Format = 33777;\\nvar RGBA_S3TC_DXT3_Format = 33778;\\nvar RGBA_S3TC_DXT5_Format = 33779;\\nvar RGB_PVRTC_4BPPV1_Format = 35840;\\nvar RGB_PVRTC_2BPPV1_Format = 35841;\\nvar RGBA_PVRTC_4BPPV1_Format = 35842;\\nvar RGBA_PVRTC_2BPPV1_Format = 35843;\\nvar RGB_ETC1_Format = 36196;\\nvar RGB_ETC2_Format = 37492;\\nvar RGBA_ETC2_EAC_Format = 37496;\\nvar RGBA_ASTC_4x4_Format = 37808;\\nvar RGBA_ASTC_5x4_Format = 37809;\\nvar RGBA_ASTC_5x5_Format = 37810;\\nvar RGBA_ASTC_6x5_Format = 37811;\\nvar RGBA_ASTC_6x6_Format = 37812;\\nvar RGBA_ASTC_8x5_Format = 37813;\\nvar RGBA_ASTC_8x6_Format = 37814;\\nvar RGBA_ASTC_8x8_Format = 37815;\\nvar RGBA_ASTC_10x5_Format = 37816;\\nvar RGBA_ASTC_10x6_Format = 37817;\\nvar RGBA_ASTC_10x8_Format = 37818;\\nvar RGBA_ASTC_10x10_Format = 37819;\\nvar RGBA_ASTC_12x10_Format = 37820;\\nvar RGBA_ASTC_12x12_Format = 37821;\\nvar RGBA_BPTC_Format = 36492;\\nvar SRGB8_ALPHA8_ASTC_4x4_Format = 37840;\\nvar SRGB8_ALPHA8_ASTC_5x4_Format = 37841;\\nvar SRGB8_ALPHA8_ASTC_5x5_Format = 37842;\\nvar SRGB8_ALPHA8_ASTC_6x5_Format = 37843;\\nvar SRGB8_ALPHA8_ASTC_6x6_Format = 37844;\\nvar SRGB8_ALPHA8_ASTC_8x5_Format = 37845;\\nvar SRGB8_ALPHA8_ASTC_8x6_Format = 37846;\\nvar SRGB8_ALPHA8_ASTC_8x8_Format = 37847;\\nvar SRGB8_ALPHA8_ASTC_10x5_Format = 37848;\\nvar SRGB8_ALPHA8_ASTC_10x6_Format = 37849;\\nvar SRGB8_ALPHA8_ASTC_10x8_Format = 37850;\\nvar SRGB8_ALPHA8_ASTC_10x10_Format = 37851;\\nvar SRGB8_ALPHA8_ASTC_12x10_Format = 37852;\\nvar SRGB8_ALPHA8_ASTC_12x12_Format = 37853;\\nvar ZeroCurvatureEnding = 2400;\\nvar ZeroSlopeEnding = 2401;\\nvar WrapAroundEnding = 2402;\\nvar LinearEncoding = 3e3;\\nvar sRGBEncoding = 3001;\\nvar GammaEncoding = 3007;\\nvar RGBEEncoding = 3002;\\nvar LogLuvEncoding = 3003;\\nvar RGBM7Encoding = 3004;\\nvar RGBM16Encoding = 3005;\\nvar RGBDEncoding = 3006;\\nvar BasicDepthPacking = 3200;\\nvar RGBADepthPacking = 3201;\\nvar TangentSpaceNormalMap = 0;\\nvar ObjectSpaceNormalMap = 1;\\nvar KeepStencilOp = 7680;\\nvar AlwaysStencilFunc = 519;\\nvar StaticDrawUsage = 35044;\\nvar GLSL3 = \\\\\\\"300 es\\\\\\\";\\n\\n// ../../../node_modules/three/src/math/Box3.js\\nvar Box3 = class {\\n constructor(min = new Vector3(Infinity, Infinity, Infinity), max = new Vector3(-Infinity, -Infinity, -Infinity)) {\\n this.min = min;\\n this.max = max;\\n }\\n set(min, max) {\\n this.min.copy(min);\\n this.max.copy(max);\\n return this;\\n }\\n setFromArray(array) {\\n let minX = Infinity;\\n let minY = Infinity;\\n let minZ = Infinity;\\n let maxX = -Infinity;\\n let maxY = -Infinity;\\n let maxZ = -Infinity;\\n for (let i = 0, l = array.length; i < l; i += 3) {\\n const x = array[i];\\n const y = array[i + 1];\\n const z = array[i + 2];\\n if (x < minX)\\n minX = x;\\n if (y < minY)\\n minY = y;\\n if (z < minZ)\\n minZ = z;\\n if (x > maxX)\\n maxX = x;\\n if (y > maxY)\\n maxY = y;\\n if (z > maxZ)\\n maxZ = z;\\n }\\n this.min.set(minX, minY, minZ);\\n this.max.set(maxX, maxY, maxZ);\\n return this;\\n }\\n setFromBufferAttribute(attribute) {\\n let minX = Infinity;\\n let minY = Infinity;\\n let minZ = Infinity;\\n let maxX = -Infinity;\\n let maxY = -Infinity;\\n let maxZ = -Infinity;\\n for (let i = 0, l = attribute.count; i < l; i++) {\\n const x = attribute.getX(i);\\n const y = attribute.getY(i);\\n const z = attribute.getZ(i);\\n if (x < minX)\\n minX = x;\\n if (y < minY)\\n minY = y;\\n if (z < minZ)\\n minZ = z;\\n if (x > maxX)\\n maxX = x;\\n if (y > maxY)\\n maxY = y;\\n if (z > maxZ)\\n maxZ = z;\\n }\\n this.min.set(minX, minY, minZ);\\n this.max.set(maxX, maxY, maxZ);\\n return this;\\n }\\n setFromPoints(points2) {\\n this.makeEmpty();\\n for (let i = 0, il = points2.length; i < il; i++) {\\n this.expandByPoint(points2[i]);\\n }\\n return this;\\n }\\n setFromCenterAndSize(center, size) {\\n const halfSize = _vector2.copy(size).multiplyScalar(0.5);\\n this.min.copy(center).sub(halfSize);\\n this.max.copy(center).add(halfSize);\\n return this;\\n }\\n setFromObject(object) {\\n this.makeEmpty();\\n return this.expandByObject(object);\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n copy(box) {\\n this.min.copy(box.min);\\n this.max.copy(box.max);\\n return this;\\n }\\n makeEmpty() {\\n this.min.x = this.min.y = this.min.z = Infinity;\\n this.max.x = this.max.y = this.max.z = -Infinity;\\n return this;\\n }\\n isEmpty() {\\n return this.max.x < this.min.x || this.max.y < this.min.y || this.max.z < this.min.z;\\n }\\n getCenter(target) {\\n return this.isEmpty() ? target.set(0, 0, 0) : target.addVectors(this.min, this.max).multiplyScalar(0.5);\\n }\\n getSize(target) {\\n return this.isEmpty() ? target.set(0, 0, 0) : target.subVectors(this.max, this.min);\\n }\\n expandByPoint(point) {\\n this.min.min(point);\\n this.max.max(point);\\n return this;\\n }\\n expandByVector(vector) {\\n this.min.sub(vector);\\n this.max.add(vector);\\n return this;\\n }\\n expandByScalar(scalar) {\\n this.min.addScalar(-scalar);\\n this.max.addScalar(scalar);\\n return this;\\n }\\n expandByObject(object) {\\n object.updateWorldMatrix(false, false);\\n const geometry = object.geometry;\\n if (geometry !== void 0) {\\n if (geometry.boundingBox === null) {\\n geometry.computeBoundingBox();\\n }\\n _box.copy(geometry.boundingBox);\\n _box.applyMatrix4(object.matrixWorld);\\n this.union(_box);\\n }\\n const children = object.children;\\n for (let i = 0, l = children.length; i < l; i++) {\\n this.expandByObject(children[i]);\\n }\\n return this;\\n }\\n containsPoint(point) {\\n return point.x < this.min.x || point.x > this.max.x || point.y < this.min.y || point.y > this.max.y || point.z < this.min.z || point.z > this.max.z ? false : true;\\n }\\n containsBox(box) {\\n return this.min.x <= box.min.x && box.max.x <= this.max.x && this.min.y <= box.min.y && box.max.y <= this.max.y && this.min.z <= box.min.z && box.max.z <= this.max.z;\\n }\\n getParameter(point, target) {\\n return target.set((point.x - this.min.x) / (this.max.x - this.min.x), (point.y - this.min.y) / (this.max.y - this.min.y), (point.z - this.min.z) / (this.max.z - this.min.z));\\n }\\n intersectsBox(box) {\\n return box.max.x < this.min.x || box.min.x > this.max.x || box.max.y < this.min.y || box.min.y > this.max.y || box.max.z < this.min.z || box.min.z > this.max.z ? false : true;\\n }\\n intersectsSphere(sphere) {\\n this.clampPoint(sphere.center, _vector2);\\n return _vector2.distanceToSquared(sphere.center) <= sphere.radius * sphere.radius;\\n }\\n intersectsPlane(plane) {\\n let min, max;\\n if (plane.normal.x > 0) {\\n min = plane.normal.x * this.min.x;\\n max = plane.normal.x * this.max.x;\\n } else {\\n min = plane.normal.x * this.max.x;\\n max = plane.normal.x * this.min.x;\\n }\\n if (plane.normal.y > 0) {\\n min += plane.normal.y * this.min.y;\\n max += plane.normal.y * this.max.y;\\n } else {\\n min += plane.normal.y * this.max.y;\\n max += plane.normal.y * this.min.y;\\n }\\n if (plane.normal.z > 0) {\\n min += plane.normal.z * this.min.z;\\n max += plane.normal.z * this.max.z;\\n } else {\\n min += plane.normal.z * this.max.z;\\n max += plane.normal.z * this.min.z;\\n }\\n return min <= -plane.constant && max >= -plane.constant;\\n }\\n intersectsTriangle(triangle) {\\n if (this.isEmpty()) {\\n return false;\\n }\\n this.getCenter(_center);\\n _extents.subVectors(this.max, _center);\\n _v0.subVectors(triangle.a, _center);\\n _v13.subVectors(triangle.b, _center);\\n _v2.subVectors(triangle.c, _center);\\n _f0.subVectors(_v13, _v0);\\n _f1.subVectors(_v2, _v13);\\n _f2.subVectors(_v0, _v2);\\n let axes = [\\n 0,\\n -_f0.z,\\n _f0.y,\\n 0,\\n -_f1.z,\\n _f1.y,\\n 0,\\n -_f2.z,\\n _f2.y,\\n _f0.z,\\n 0,\\n -_f0.x,\\n _f1.z,\\n 0,\\n -_f1.x,\\n _f2.z,\\n 0,\\n -_f2.x,\\n -_f0.y,\\n _f0.x,\\n 0,\\n -_f1.y,\\n _f1.x,\\n 0,\\n -_f2.y,\\n _f2.x,\\n 0\\n ];\\n if (!satForAxes(axes, _v0, _v13, _v2, _extents)) {\\n return false;\\n }\\n axes = [1, 0, 0, 0, 1, 0, 0, 0, 1];\\n if (!satForAxes(axes, _v0, _v13, _v2, _extents)) {\\n return false;\\n }\\n _triangleNormal.crossVectors(_f0, _f1);\\n axes = [_triangleNormal.x, _triangleNormal.y, _triangleNormal.z];\\n return satForAxes(axes, _v0, _v13, _v2, _extents);\\n }\\n clampPoint(point, target) {\\n return target.copy(point).clamp(this.min, this.max);\\n }\\n distanceToPoint(point) {\\n const clampedPoint = _vector2.copy(point).clamp(this.min, this.max);\\n return clampedPoint.sub(point).length();\\n }\\n getBoundingSphere(target) {\\n this.getCenter(target.center);\\n target.radius = this.getSize(_vector2).length() * 0.5;\\n return target;\\n }\\n intersect(box) {\\n this.min.max(box.min);\\n this.max.min(box.max);\\n if (this.isEmpty())\\n this.makeEmpty();\\n return this;\\n }\\n union(box) {\\n this.min.min(box.min);\\n this.max.max(box.max);\\n return this;\\n }\\n applyMatrix4(matrix) {\\n if (this.isEmpty())\\n return this;\\n _points[0].set(this.min.x, this.min.y, this.min.z).applyMatrix4(matrix);\\n _points[1].set(this.min.x, this.min.y, this.max.z).applyMatrix4(matrix);\\n _points[2].set(this.min.x, this.max.y, this.min.z).applyMatrix4(matrix);\\n _points[3].set(this.min.x, this.max.y, this.max.z).applyMatrix4(matrix);\\n _points[4].set(this.max.x, this.min.y, this.min.z).applyMatrix4(matrix);\\n _points[5].set(this.max.x, this.min.y, this.max.z).applyMatrix4(matrix);\\n _points[6].set(this.max.x, this.max.y, this.min.z).applyMatrix4(matrix);\\n _points[7].set(this.max.x, this.max.y, this.max.z).applyMatrix4(matrix);\\n this.setFromPoints(_points);\\n return this;\\n }\\n translate(offset) {\\n this.min.add(offset);\\n this.max.add(offset);\\n return this;\\n }\\n equals(box) {\\n return box.min.equals(this.min) && box.max.equals(this.max);\\n }\\n};\\nBox3.prototype.isBox3 = true;\\nvar _points = [\\n /* @__PURE__ */ new Vector3(),\\n /* @__PURE__ */ new Vector3(),\\n /* @__PURE__ */ new Vector3(),\\n /* @__PURE__ */ new Vector3(),\\n /* @__PURE__ */ new Vector3(),\\n /* @__PURE__ */ new Vector3(),\\n /* @__PURE__ */ new Vector3(),\\n /* @__PURE__ */ new Vector3()\\n];\\nvar _vector2 = /* @__PURE__ */ new Vector3();\\nvar _box = /* @__PURE__ */ new Box3();\\nvar _v0 = /* @__PURE__ */ new Vector3();\\nvar _v13 = /* @__PURE__ */ new Vector3();\\nvar _v2 = /* @__PURE__ */ new Vector3();\\nvar _f0 = /* @__PURE__ */ new Vector3();\\nvar _f1 = /* @__PURE__ */ new Vector3();\\nvar _f2 = /* @__PURE__ */ new Vector3();\\nvar _center = /* @__PURE__ */ new Vector3();\\nvar _extents = /* @__PURE__ */ new Vector3();\\nvar _triangleNormal = /* @__PURE__ */ new Vector3();\\nvar _testAxis = /* @__PURE__ */ new Vector3();\\nfunction satForAxes(axes, v0, v1, v2, extents) {\\n for (let i = 0, j = axes.length - 3; i <= j; i += 3) {\\n _testAxis.fromArray(axes, i);\\n const r = extents.x * Math.abs(_testAxis.x) + extents.y * Math.abs(_testAxis.y) + extents.z * Math.abs(_testAxis.z);\\n const p0 = v0.dot(_testAxis);\\n const p1 = v1.dot(_testAxis);\\n const p2 = v2.dot(_testAxis);\\n if (Math.max(-Math.max(p0, p1, p2), Math.min(p0, p1, p2)) > r) {\\n return false;\\n }\\n }\\n return true;\\n}\\n\\n// ../../../node_modules/three/src/math/Sphere.js\\nvar _box2 = /* @__PURE__ */ new Box3();\\nvar _v14 = /* @__PURE__ */ new Vector3();\\nvar _toFarthestPoint = /* @__PURE__ */ new Vector3();\\nvar _toPoint = /* @__PURE__ */ new Vector3();\\nvar Sphere = class {\\n constructor(center = new Vector3(), radius = -1) {\\n this.center = center;\\n this.radius = radius;\\n }\\n set(center, radius) {\\n this.center.copy(center);\\n this.radius = radius;\\n return this;\\n }\\n setFromPoints(points2, optionalCenter) {\\n const center = this.center;\\n if (optionalCenter !== void 0) {\\n center.copy(optionalCenter);\\n } else {\\n _box2.setFromPoints(points2).getCenter(center);\\n }\\n let maxRadiusSq = 0;\\n for (let i = 0, il = points2.length; i < il; i++) {\\n maxRadiusSq = Math.max(maxRadiusSq, center.distanceToSquared(points2[i]));\\n }\\n this.radius = Math.sqrt(maxRadiusSq);\\n return this;\\n }\\n copy(sphere) {\\n this.center.copy(sphere.center);\\n this.radius = sphere.radius;\\n return this;\\n }\\n isEmpty() {\\n return this.radius < 0;\\n }\\n makeEmpty() {\\n this.center.set(0, 0, 0);\\n this.radius = -1;\\n return this;\\n }\\n containsPoint(point) {\\n return point.distanceToSquared(this.center) <= this.radius * this.radius;\\n }\\n distanceToPoint(point) {\\n return point.distanceTo(this.center) - this.radius;\\n }\\n intersectsSphere(sphere) {\\n const radiusSum = this.radius + sphere.radius;\\n return sphere.center.distanceToSquared(this.center) <= radiusSum * radiusSum;\\n }\\n intersectsBox(box) {\\n return box.intersectsSphere(this);\\n }\\n intersectsPlane(plane) {\\n return Math.abs(plane.distanceToPoint(this.center)) <= this.radius;\\n }\\n clampPoint(point, target) {\\n const deltaLengthSq = this.center.distanceToSquared(point);\\n target.copy(point);\\n if (deltaLengthSq > this.radius * this.radius) {\\n target.sub(this.center).normalize();\\n target.multiplyScalar(this.radius).add(this.center);\\n }\\n return target;\\n }\\n getBoundingBox(target) {\\n if (this.isEmpty()) {\\n target.makeEmpty();\\n return target;\\n }\\n target.set(this.center, this.center);\\n target.expandByScalar(this.radius);\\n return target;\\n }\\n applyMatrix4(matrix) {\\n this.center.applyMatrix4(matrix);\\n this.radius = this.radius * matrix.getMaxScaleOnAxis();\\n return this;\\n }\\n translate(offset) {\\n this.center.add(offset);\\n return this;\\n }\\n expandByPoint(point) {\\n _toPoint.subVectors(point, this.center);\\n const lengthSq = _toPoint.lengthSq();\\n if (lengthSq > this.radius * this.radius) {\\n const length = Math.sqrt(lengthSq);\\n const missingRadiusHalf = (length - this.radius) * 0.5;\\n this.center.add(_toPoint.multiplyScalar(missingRadiusHalf / length));\\n this.radius += missingRadiusHalf;\\n }\\n return this;\\n }\\n union(sphere) {\\n _toFarthestPoint.subVectors(sphere.center, this.center).normalize().multiplyScalar(sphere.radius);\\n this.expandByPoint(_v14.copy(sphere.center).add(_toFarthestPoint));\\n this.expandByPoint(_v14.copy(sphere.center).sub(_toFarthestPoint));\\n return this;\\n }\\n equals(sphere) {\\n return sphere.center.equals(this.center) && sphere.radius === this.radius;\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n};\\n\\n// ../../../node_modules/three/src/math/Plane.js\\nvar _vector1 = /* @__PURE__ */ new Vector3();\\nvar _vector22 = /* @__PURE__ */ new Vector3();\\nvar _normalMatrix = /* @__PURE__ */ new Matrix3();\\nvar Plane = class {\\n constructor(normal = new Vector3(1, 0, 0), constant = 0) {\\n this.normal = normal;\\n this.constant = constant;\\n }\\n set(normal, constant) {\\n this.normal.copy(normal);\\n this.constant = constant;\\n return this;\\n }\\n setComponents(x, y, z, w) {\\n this.normal.set(x, y, z);\\n this.constant = w;\\n return this;\\n }\\n setFromNormalAndCoplanarPoint(normal, point) {\\n this.normal.copy(normal);\\n this.constant = -point.dot(this.normal);\\n return this;\\n }\\n setFromCoplanarPoints(a, b, c) {\\n const normal = _vector1.subVectors(c, b).cross(_vector22.subVectors(a, b)).normalize();\\n this.setFromNormalAndCoplanarPoint(normal, a);\\n return this;\\n }\\n copy(plane) {\\n this.normal.copy(plane.normal);\\n this.constant = plane.constant;\\n return this;\\n }\\n normalize() {\\n const inverseNormalLength = 1 / this.normal.length();\\n this.normal.multiplyScalar(inverseNormalLength);\\n this.constant *= inverseNormalLength;\\n return this;\\n }\\n negate() {\\n this.constant *= -1;\\n this.normal.negate();\\n return this;\\n }\\n distanceToPoint(point) {\\n return this.normal.dot(point) + this.constant;\\n }\\n distanceToSphere(sphere) {\\n return this.distanceToPoint(sphere.center) - sphere.radius;\\n }\\n projectPoint(point, target) {\\n return target.copy(this.normal).multiplyScalar(-this.distanceToPoint(point)).add(point);\\n }\\n intersectLine(line, target) {\\n const direction = line.delta(_vector1);\\n const denominator = this.normal.dot(direction);\\n if (denominator === 0) {\\n if (this.distanceToPoint(line.start) === 0) {\\n return target.copy(line.start);\\n }\\n return null;\\n }\\n const t = -(line.start.dot(this.normal) + this.constant) / denominator;\\n if (t < 0 || t > 1) {\\n return null;\\n }\\n return target.copy(direction).multiplyScalar(t).add(line.start);\\n }\\n intersectsLine(line) {\\n const startSign = this.distanceToPoint(line.start);\\n const endSign = this.distanceToPoint(line.end);\\n return startSign < 0 && endSign > 0 || endSign < 0 && startSign > 0;\\n }\\n intersectsBox(box) {\\n return box.intersectsPlane(this);\\n }\\n intersectsSphere(sphere) {\\n return sphere.intersectsPlane(this);\\n }\\n coplanarPoint(target) {\\n return target.copy(this.normal).multiplyScalar(-this.constant);\\n }\\n applyMatrix4(matrix, optionalNormalMatrix) {\\n const normalMatrix = optionalNormalMatrix || _normalMatrix.getNormalMatrix(matrix);\\n const referencePoint = this.coplanarPoint(_vector1).applyMatrix4(matrix);\\n const normal = this.normal.applyMatrix3(normalMatrix).normalize();\\n this.constant = -referencePoint.dot(normal);\\n return this;\\n }\\n translate(offset) {\\n this.constant -= offset.dot(this.normal);\\n return this;\\n }\\n equals(plane) {\\n return plane.normal.equals(this.normal) && plane.constant === this.constant;\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n};\\nPlane.prototype.isPlane = true;\\n\\n// ../../../node_modules/three/src/math/Frustum.js\\nvar _sphere = /* @__PURE__ */ new Sphere();\\nvar _vector3 = /* @__PURE__ */ new Vector3();\\nvar Frustum = class {\\n constructor(p0 = new Plane(), p1 = new Plane(), p2 = new Plane(), p3 = new Plane(), p4 = new Plane(), p5 = new Plane()) {\\n this.planes = [p0, p1, p2, p3, p4, p5];\\n }\\n set(p0, p1, p2, p3, p4, p5) {\\n const planes = this.planes;\\n planes[0].copy(p0);\\n planes[1].copy(p1);\\n planes[2].copy(p2);\\n planes[3].copy(p3);\\n planes[4].copy(p4);\\n planes[5].copy(p5);\\n return this;\\n }\\n copy(frustum) {\\n const planes = this.planes;\\n for (let i = 0; i < 6; i++) {\\n planes[i].copy(frustum.planes[i]);\\n }\\n return this;\\n }\\n setFromProjectionMatrix(m) {\\n const planes = this.planes;\\n const me = m.elements;\\n const me0 = me[0], me1 = me[1], me2 = me[2], me3 = me[3];\\n const me4 = me[4], me5 = me[5], me6 = me[6], me7 = me[7];\\n const me8 = me[8], me9 = me[9], me10 = me[10], me11 = me[11];\\n const me12 = me[12], me13 = me[13], me14 = me[14], me15 = me[15];\\n planes[0].setComponents(me3 - me0, me7 - me4, me11 - me8, me15 - me12).normalize();\\n planes[1].setComponents(me3 + me0, me7 + me4, me11 + me8, me15 + me12).normalize();\\n planes[2].setComponents(me3 + me1, me7 + me5, me11 + me9, me15 + me13).normalize();\\n planes[3].setComponents(me3 - me1, me7 - me5, me11 - me9, me15 - me13).normalize();\\n planes[4].setComponents(me3 - me2, me7 - me6, me11 - me10, me15 - me14).normalize();\\n planes[5].setComponents(me3 + me2, me7 + me6, me11 + me10, me15 + me14).normalize();\\n return this;\\n }\\n intersectsObject(object) {\\n const geometry = object.geometry;\\n if (geometry.boundingSphere === null)\\n geometry.computeBoundingSphere();\\n _sphere.copy(geometry.boundingSphere).applyMatrix4(object.matrixWorld);\\n return this.intersectsSphere(_sphere);\\n }\\n intersectsSprite(sprite2) {\\n _sphere.center.set(0, 0, 0);\\n _sphere.radius = 0.7071067811865476;\\n _sphere.applyMatrix4(sprite2.matrixWorld);\\n return this.intersectsSphere(_sphere);\\n }\\n intersectsSphere(sphere) {\\n const planes = this.planes;\\n const center = sphere.center;\\n const negRadius = -sphere.radius;\\n for (let i = 0; i < 6; i++) {\\n const distance = planes[i].distanceToPoint(center);\\n if (distance < negRadius) {\\n return false;\\n }\\n }\\n return true;\\n }\\n intersectsBox(box) {\\n const planes = this.planes;\\n for (let i = 0; i < 6; i++) {\\n const plane = planes[i];\\n _vector3.x = plane.normal.x > 0 ? box.max.x : box.min.x;\\n _vector3.y = plane.normal.y > 0 ? box.max.y : box.min.y;\\n _vector3.z = plane.normal.z > 0 ? box.max.z : box.min.z;\\n if (plane.distanceToPoint(_vector3) < 0) {\\n return false;\\n }\\n }\\n return true;\\n }\\n containsPoint(point) {\\n const planes = this.planes;\\n for (let i = 0; i < 6; i++) {\\n if (planes[i].distanceToPoint(point) < 0) {\\n return false;\\n }\\n }\\n return true;\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n};\\n\\n// ../../../node_modules/three/src/math/Vector4.js\\nvar Vector4 = class {\\n constructor(x = 0, y = 0, z = 0, w = 1) {\\n this.x = x;\\n this.y = y;\\n this.z = z;\\n this.w = w;\\n }\\n get width() {\\n return this.z;\\n }\\n set width(value) {\\n this.z = value;\\n }\\n get height() {\\n return this.w;\\n }\\n set height(value) {\\n this.w = value;\\n }\\n set(x, y, z, w) {\\n this.x = x;\\n this.y = y;\\n this.z = z;\\n this.w = w;\\n return this;\\n }\\n setScalar(scalar) {\\n this.x = scalar;\\n this.y = scalar;\\n this.z = scalar;\\n this.w = scalar;\\n return this;\\n }\\n setX(x) {\\n this.x = x;\\n return this;\\n }\\n setY(y) {\\n this.y = y;\\n return this;\\n }\\n setZ(z) {\\n this.z = z;\\n return this;\\n }\\n setW(w) {\\n this.w = w;\\n return this;\\n }\\n setComponent(index, value) {\\n switch (index) {\\n case 0:\\n this.x = value;\\n break;\\n case 1:\\n this.y = value;\\n break;\\n case 2:\\n this.z = value;\\n break;\\n case 3:\\n this.w = value;\\n break;\\n default:\\n throw new Error(\\\\\\\"index is out of range: \\\\\\\" + index);\\n }\\n return this;\\n }\\n getComponent(index) {\\n switch (index) {\\n case 0:\\n return this.x;\\n case 1:\\n return this.y;\\n case 2:\\n return this.z;\\n case 3:\\n return this.w;\\n default:\\n throw new Error(\\\\\\\"index is out of range: \\\\\\\" + index);\\n }\\n }\\n clone() {\\n return new this.constructor(this.x, this.y, this.z, this.w);\\n }\\n copy(v) {\\n this.x = v.x;\\n this.y = v.y;\\n this.z = v.z;\\n this.w = v.w !== void 0 ? v.w : 1;\\n return this;\\n }\\n add(v, w) {\\n if (w !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector4: .add() now only accepts one argument. Use .addVectors( a, b ) instead.\\\\\\\");\\n return this.addVectors(v, w);\\n }\\n this.x += v.x;\\n this.y += v.y;\\n this.z += v.z;\\n this.w += v.w;\\n return this;\\n }\\n addScalar(s) {\\n this.x += s;\\n this.y += s;\\n this.z += s;\\n this.w += s;\\n return this;\\n }\\n addVectors(a, b) {\\n this.x = a.x + b.x;\\n this.y = a.y + b.y;\\n this.z = a.z + b.z;\\n this.w = a.w + b.w;\\n return this;\\n }\\n addScaledVector(v, s) {\\n this.x += v.x * s;\\n this.y += v.y * s;\\n this.z += v.z * s;\\n this.w += v.w * s;\\n return this;\\n }\\n sub(v, w) {\\n if (w !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector4: .sub() now only accepts one argument. Use .subVectors( a, b ) instead.\\\\\\\");\\n return this.subVectors(v, w);\\n }\\n this.x -= v.x;\\n this.y -= v.y;\\n this.z -= v.z;\\n this.w -= v.w;\\n return this;\\n }\\n subScalar(s) {\\n this.x -= s;\\n this.y -= s;\\n this.z -= s;\\n this.w -= s;\\n return this;\\n }\\n subVectors(a, b) {\\n this.x = a.x - b.x;\\n this.y = a.y - b.y;\\n this.z = a.z - b.z;\\n this.w = a.w - b.w;\\n return this;\\n }\\n multiply(v) {\\n this.x *= v.x;\\n this.y *= v.y;\\n this.z *= v.z;\\n this.w *= v.w;\\n return this;\\n }\\n multiplyScalar(scalar) {\\n this.x *= scalar;\\n this.y *= scalar;\\n this.z *= scalar;\\n this.w *= scalar;\\n return this;\\n }\\n applyMatrix4(m) {\\n const x = this.x, y = this.y, z = this.z, w = this.w;\\n const e = m.elements;\\n this.x = e[0] * x + e[4] * y + e[8] * z + e[12] * w;\\n this.y = e[1] * x + e[5] * y + e[9] * z + e[13] * w;\\n this.z = e[2] * x + e[6] * y + e[10] * z + e[14] * w;\\n this.w = e[3] * x + e[7] * y + e[11] * z + e[15] * w;\\n return this;\\n }\\n divideScalar(scalar) {\\n return this.multiplyScalar(1 / scalar);\\n }\\n setAxisAngleFromQuaternion(q) {\\n this.w = 2 * Math.acos(q.w);\\n const s = Math.sqrt(1 - q.w * q.w);\\n if (s < 1e-4) {\\n this.x = 1;\\n this.y = 0;\\n this.z = 0;\\n } else {\\n this.x = q.x / s;\\n this.y = q.y / s;\\n this.z = q.z / s;\\n }\\n return this;\\n }\\n setAxisAngleFromRotationMatrix(m) {\\n let angle, x, y, z;\\n const epsilon = 0.01, epsilon2 = 0.1, te = m.elements, m11 = te[0], m12 = te[4], m13 = te[8], m21 = te[1], m22 = te[5], m23 = te[9], m31 = te[2], m32 = te[6], m33 = te[10];\\n if (Math.abs(m12 - m21) < epsilon && Math.abs(m13 - m31) < epsilon && Math.abs(m23 - m32) < epsilon) {\\n if (Math.abs(m12 + m21) < epsilon2 && Math.abs(m13 + m31) < epsilon2 && Math.abs(m23 + m32) < epsilon2 && Math.abs(m11 + m22 + m33 - 3) < epsilon2) {\\n this.set(1, 0, 0, 0);\\n return this;\\n }\\n angle = Math.PI;\\n const xx = (m11 + 1) / 2;\\n const yy = (m22 + 1) / 2;\\n const zz = (m33 + 1) / 2;\\n const xy = (m12 + m21) / 4;\\n const xz = (m13 + m31) / 4;\\n const yz = (m23 + m32) / 4;\\n if (xx > yy && xx > zz) {\\n if (xx < epsilon) {\\n x = 0;\\n y = 0.707106781;\\n z = 0.707106781;\\n } else {\\n x = Math.sqrt(xx);\\n y = xy / x;\\n z = xz / x;\\n }\\n } else if (yy > zz) {\\n if (yy < epsilon) {\\n x = 0.707106781;\\n y = 0;\\n z = 0.707106781;\\n } else {\\n y = Math.sqrt(yy);\\n x = xy / y;\\n z = yz / y;\\n }\\n } else {\\n if (zz < epsilon) {\\n x = 0.707106781;\\n y = 0.707106781;\\n z = 0;\\n } else {\\n z = Math.sqrt(zz);\\n x = xz / z;\\n y = yz / z;\\n }\\n }\\n this.set(x, y, z, angle);\\n return this;\\n }\\n let s = Math.sqrt((m32 - m23) * (m32 - m23) + (m13 - m31) * (m13 - m31) + (m21 - m12) * (m21 - m12));\\n if (Math.abs(s) < 1e-3)\\n s = 1;\\n this.x = (m32 - m23) / s;\\n this.y = (m13 - m31) / s;\\n this.z = (m21 - m12) / s;\\n this.w = Math.acos((m11 + m22 + m33 - 1) / 2);\\n return this;\\n }\\n min(v) {\\n this.x = Math.min(this.x, v.x);\\n this.y = Math.min(this.y, v.y);\\n this.z = Math.min(this.z, v.z);\\n this.w = Math.min(this.w, v.w);\\n return this;\\n }\\n max(v) {\\n this.x = Math.max(this.x, v.x);\\n this.y = Math.max(this.y, v.y);\\n this.z = Math.max(this.z, v.z);\\n this.w = Math.max(this.w, v.w);\\n return this;\\n }\\n clamp(min, max) {\\n this.x = Math.max(min.x, Math.min(max.x, this.x));\\n this.y = Math.max(min.y, Math.min(max.y, this.y));\\n this.z = Math.max(min.z, Math.min(max.z, this.z));\\n this.w = Math.max(min.w, Math.min(max.w, this.w));\\n return this;\\n }\\n clampScalar(minVal, maxVal) {\\n this.x = Math.max(minVal, Math.min(maxVal, this.x));\\n this.y = Math.max(minVal, Math.min(maxVal, this.y));\\n this.z = Math.max(minVal, Math.min(maxVal, this.z));\\n this.w = Math.max(minVal, Math.min(maxVal, this.w));\\n return this;\\n }\\n clampLength(min, max) {\\n const length = this.length();\\n return this.divideScalar(length || 1).multiplyScalar(Math.max(min, Math.min(max, length)));\\n }\\n floor() {\\n this.x = Math.floor(this.x);\\n this.y = Math.floor(this.y);\\n this.z = Math.floor(this.z);\\n this.w = Math.floor(this.w);\\n return this;\\n }\\n ceil() {\\n this.x = Math.ceil(this.x);\\n this.y = Math.ceil(this.y);\\n this.z = Math.ceil(this.z);\\n this.w = Math.ceil(this.w);\\n return this;\\n }\\n round() {\\n this.x = Math.round(this.x);\\n this.y = Math.round(this.y);\\n this.z = Math.round(this.z);\\n this.w = Math.round(this.w);\\n return this;\\n }\\n roundToZero() {\\n this.x = this.x < 0 ? Math.ceil(this.x) : Math.floor(this.x);\\n this.y = this.y < 0 ? Math.ceil(this.y) : Math.floor(this.y);\\n this.z = this.z < 0 ? Math.ceil(this.z) : Math.floor(this.z);\\n this.w = this.w < 0 ? Math.ceil(this.w) : Math.floor(this.w);\\n return this;\\n }\\n negate() {\\n this.x = -this.x;\\n this.y = -this.y;\\n this.z = -this.z;\\n this.w = -this.w;\\n return this;\\n }\\n dot(v) {\\n return this.x * v.x + this.y * v.y + this.z * v.z + this.w * v.w;\\n }\\n lengthSq() {\\n return this.x * this.x + this.y * this.y + this.z * this.z + this.w * this.w;\\n }\\n length() {\\n return Math.sqrt(this.x * this.x + this.y * this.y + this.z * this.z + this.w * this.w);\\n }\\n manhattanLength() {\\n return Math.abs(this.x) + Math.abs(this.y) + Math.abs(this.z) + Math.abs(this.w);\\n }\\n normalize() {\\n return this.divideScalar(this.length() || 1);\\n }\\n setLength(length) {\\n return this.normalize().multiplyScalar(length);\\n }\\n lerp(v, alpha) {\\n this.x += (v.x - this.x) * alpha;\\n this.y += (v.y - this.y) * alpha;\\n this.z += (v.z - this.z) * alpha;\\n this.w += (v.w - this.w) * alpha;\\n return this;\\n }\\n lerpVectors(v1, v2, alpha) {\\n this.x = v1.x + (v2.x - v1.x) * alpha;\\n this.y = v1.y + (v2.y - v1.y) * alpha;\\n this.z = v1.z + (v2.z - v1.z) * alpha;\\n this.w = v1.w + (v2.w - v1.w) * alpha;\\n return this;\\n }\\n equals(v) {\\n return v.x === this.x && v.y === this.y && v.z === this.z && v.w === this.w;\\n }\\n fromArray(array, offset = 0) {\\n this.x = array[offset];\\n this.y = array[offset + 1];\\n this.z = array[offset + 2];\\n this.w = array[offset + 3];\\n return this;\\n }\\n toArray(array = [], offset = 0) {\\n array[offset] = this.x;\\n array[offset + 1] = this.y;\\n array[offset + 2] = this.z;\\n array[offset + 3] = this.w;\\n return array;\\n }\\n fromBufferAttribute(attribute, index, offset) {\\n if (offset !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector4: offset has been removed from .fromBufferAttribute().\\\\\\\");\\n }\\n this.x = attribute.getX(index);\\n this.y = attribute.getY(index);\\n this.z = attribute.getZ(index);\\n this.w = attribute.getW(index);\\n return this;\\n }\\n random() {\\n this.x = Math.random();\\n this.y = Math.random();\\n this.z = Math.random();\\n this.w = Math.random();\\n return this;\\n }\\n *[Symbol.iterator]() {\\n yield this.x;\\n yield this.y;\\n yield this.z;\\n yield this.w;\\n }\\n};\\nVector4.prototype.isVector4 = true;\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLAnimation.js\\nfunction WebGLAnimation() {\\n let context = null;\\n let isAnimating = false;\\n let animationLoop = null;\\n let requestId = null;\\n function onAnimationFrame(time, frame) {\\n animationLoop(time, frame);\\n requestId = context.requestAnimationFrame(onAnimationFrame);\\n }\\n return {\\n start: function() {\\n if (isAnimating === true)\\n return;\\n if (animationLoop === null)\\n return;\\n requestId = context.requestAnimationFrame(onAnimationFrame);\\n isAnimating = true;\\n },\\n stop: function() {\\n context.cancelAnimationFrame(requestId);\\n isAnimating = false;\\n },\\n setAnimationLoop: function(callback) {\\n animationLoop = callback;\\n },\\n setContext: function(value) {\\n context = value;\\n }\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLAttributes.js\\nfunction WebGLAttributes(gl, capabilities) {\\n const isWebGL2 = capabilities.isWebGL2;\\n const buffers = new WeakMap();\\n function createBuffer(attribute, bufferType) {\\n const array = attribute.array;\\n const usage = attribute.usage;\\n const buffer = gl.createBuffer();\\n gl.bindBuffer(bufferType, buffer);\\n gl.bufferData(bufferType, array, usage);\\n attribute.onUploadCallback();\\n let type = gl.FLOAT;\\n if (array instanceof Float32Array) {\\n type = gl.FLOAT;\\n } else if (array instanceof Float64Array) {\\n console.warn(\\\\\\\"THREE.WebGLAttributes: Unsupported data buffer format: Float64Array.\\\\\\\");\\n } else if (array instanceof Uint16Array) {\\n if (attribute.isFloat16BufferAttribute) {\\n if (isWebGL2) {\\n type = gl.HALF_FLOAT;\\n } else {\\n console.warn(\\\\\\\"THREE.WebGLAttributes: Usage of Float16BufferAttribute requires WebGL2.\\\\\\\");\\n }\\n } else {\\n type = gl.UNSIGNED_SHORT;\\n }\\n } else if (array instanceof Int16Array) {\\n type = gl.SHORT;\\n } else if (array instanceof Uint32Array) {\\n type = gl.UNSIGNED_INT;\\n } else if (array instanceof Int32Array) {\\n type = gl.INT;\\n } else if (array instanceof Int8Array) {\\n type = gl.BYTE;\\n } else if (array instanceof Uint8Array) {\\n type = gl.UNSIGNED_BYTE;\\n } else if (array instanceof Uint8ClampedArray) {\\n type = gl.UNSIGNED_BYTE;\\n }\\n return {\\n buffer,\\n type,\\n bytesPerElement: array.BYTES_PER_ELEMENT,\\n version: attribute.version\\n };\\n }\\n function updateBuffer(buffer, attribute, bufferType) {\\n const array = attribute.array;\\n const updateRange = attribute.updateRange;\\n gl.bindBuffer(bufferType, buffer);\\n if (updateRange.count === -1) {\\n gl.bufferSubData(bufferType, 0, array);\\n } else {\\n if (isWebGL2) {\\n gl.bufferSubData(bufferType, updateRange.offset * array.BYTES_PER_ELEMENT, array, updateRange.offset, updateRange.count);\\n } else {\\n gl.bufferSubData(bufferType, updateRange.offset * array.BYTES_PER_ELEMENT, array.subarray(updateRange.offset, updateRange.offset + updateRange.count));\\n }\\n updateRange.count = -1;\\n }\\n }\\n function get(attribute) {\\n if (attribute.isInterleavedBufferAttribute)\\n attribute = attribute.data;\\n return buffers.get(attribute);\\n }\\n function remove(attribute) {\\n if (attribute.isInterleavedBufferAttribute)\\n attribute = attribute.data;\\n const data = buffers.get(attribute);\\n if (data) {\\n gl.deleteBuffer(data.buffer);\\n buffers.delete(attribute);\\n }\\n }\\n function update(attribute, bufferType) {\\n if (attribute.isGLBufferAttribute) {\\n const cached = buffers.get(attribute);\\n if (!cached || cached.version < attribute.version) {\\n buffers.set(attribute, {\\n buffer: attribute.buffer,\\n type: attribute.type,\\n bytesPerElement: attribute.elementSize,\\n version: attribute.version\\n });\\n }\\n return;\\n }\\n if (attribute.isInterleavedBufferAttribute)\\n attribute = attribute.data;\\n const data = buffers.get(attribute);\\n if (data === void 0) {\\n buffers.set(attribute, createBuffer(attribute, bufferType));\\n } else if (data.version < attribute.version) {\\n updateBuffer(data.buffer, attribute, bufferType);\\n data.version = attribute.version;\\n }\\n }\\n return {\\n get,\\n remove,\\n update\\n };\\n}\\n\\n// ../../../node_modules/three/src/math/Vector2.js\\nvar Vector2 = class {\\n constructor(x = 0, y = 0) {\\n this.x = x;\\n this.y = y;\\n }\\n get width() {\\n return this.x;\\n }\\n set width(value) {\\n this.x = value;\\n }\\n get height() {\\n return this.y;\\n }\\n set height(value) {\\n this.y = value;\\n }\\n set(x, y) {\\n this.x = x;\\n this.y = y;\\n return this;\\n }\\n setScalar(scalar) {\\n this.x = scalar;\\n this.y = scalar;\\n return this;\\n }\\n setX(x) {\\n this.x = x;\\n return this;\\n }\\n setY(y) {\\n this.y = y;\\n return this;\\n }\\n setComponent(index, value) {\\n switch (index) {\\n case 0:\\n this.x = value;\\n break;\\n case 1:\\n this.y = value;\\n break;\\n default:\\n throw new Error(\\\\\\\"index is out of range: \\\\\\\" + index);\\n }\\n return this;\\n }\\n getComponent(index) {\\n switch (index) {\\n case 0:\\n return this.x;\\n case 1:\\n return this.y;\\n default:\\n throw new Error(\\\\\\\"index is out of range: \\\\\\\" + index);\\n }\\n }\\n clone() {\\n return new this.constructor(this.x, this.y);\\n }\\n copy(v) {\\n this.x = v.x;\\n this.y = v.y;\\n return this;\\n }\\n add(v, w) {\\n if (w !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector2: .add() now only accepts one argument. Use .addVectors( a, b ) instead.\\\\\\\");\\n return this.addVectors(v, w);\\n }\\n this.x += v.x;\\n this.y += v.y;\\n return this;\\n }\\n addScalar(s) {\\n this.x += s;\\n this.y += s;\\n return this;\\n }\\n addVectors(a, b) {\\n this.x = a.x + b.x;\\n this.y = a.y + b.y;\\n return this;\\n }\\n addScaledVector(v, s) {\\n this.x += v.x * s;\\n this.y += v.y * s;\\n return this;\\n }\\n sub(v, w) {\\n if (w !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector2: .sub() now only accepts one argument. Use .subVectors( a, b ) instead.\\\\\\\");\\n return this.subVectors(v, w);\\n }\\n this.x -= v.x;\\n this.y -= v.y;\\n return this;\\n }\\n subScalar(s) {\\n this.x -= s;\\n this.y -= s;\\n return this;\\n }\\n subVectors(a, b) {\\n this.x = a.x - b.x;\\n this.y = a.y - b.y;\\n return this;\\n }\\n multiply(v) {\\n this.x *= v.x;\\n this.y *= v.y;\\n return this;\\n }\\n multiplyScalar(scalar) {\\n this.x *= scalar;\\n this.y *= scalar;\\n return this;\\n }\\n divide(v) {\\n this.x /= v.x;\\n this.y /= v.y;\\n return this;\\n }\\n divideScalar(scalar) {\\n return this.multiplyScalar(1 / scalar);\\n }\\n applyMatrix3(m) {\\n const x = this.x, y = this.y;\\n const e = m.elements;\\n this.x = e[0] * x + e[3] * y + e[6];\\n this.y = e[1] * x + e[4] * y + e[7];\\n return this;\\n }\\n min(v) {\\n this.x = Math.min(this.x, v.x);\\n this.y = Math.min(this.y, v.y);\\n return this;\\n }\\n max(v) {\\n this.x = Math.max(this.x, v.x);\\n this.y = Math.max(this.y, v.y);\\n return this;\\n }\\n clamp(min, max) {\\n this.x = Math.max(min.x, Math.min(max.x, this.x));\\n this.y = Math.max(min.y, Math.min(max.y, this.y));\\n return this;\\n }\\n clampScalar(minVal, maxVal) {\\n this.x = Math.max(minVal, Math.min(maxVal, this.x));\\n this.y = Math.max(minVal, Math.min(maxVal, this.y));\\n return this;\\n }\\n clampLength(min, max) {\\n const length = this.length();\\n return this.divideScalar(length || 1).multiplyScalar(Math.max(min, Math.min(max, length)));\\n }\\n floor() {\\n this.x = Math.floor(this.x);\\n this.y = Math.floor(this.y);\\n return this;\\n }\\n ceil() {\\n this.x = Math.ceil(this.x);\\n this.y = Math.ceil(this.y);\\n return this;\\n }\\n round() {\\n this.x = Math.round(this.x);\\n this.y = Math.round(this.y);\\n return this;\\n }\\n roundToZero() {\\n this.x = this.x < 0 ? Math.ceil(this.x) : Math.floor(this.x);\\n this.y = this.y < 0 ? Math.ceil(this.y) : Math.floor(this.y);\\n return this;\\n }\\n negate() {\\n this.x = -this.x;\\n this.y = -this.y;\\n return this;\\n }\\n dot(v) {\\n return this.x * v.x + this.y * v.y;\\n }\\n cross(v) {\\n return this.x * v.y - this.y * v.x;\\n }\\n lengthSq() {\\n return this.x * this.x + this.y * this.y;\\n }\\n length() {\\n return Math.sqrt(this.x * this.x + this.y * this.y);\\n }\\n manhattanLength() {\\n return Math.abs(this.x) + Math.abs(this.y);\\n }\\n normalize() {\\n return this.divideScalar(this.length() || 1);\\n }\\n angle() {\\n const angle = Math.atan2(-this.y, -this.x) + Math.PI;\\n return angle;\\n }\\n distanceTo(v) {\\n return Math.sqrt(this.distanceToSquared(v));\\n }\\n distanceToSquared(v) {\\n const dx = this.x - v.x, dy = this.y - v.y;\\n return dx * dx + dy * dy;\\n }\\n manhattanDistanceTo(v) {\\n return Math.abs(this.x - v.x) + Math.abs(this.y - v.y);\\n }\\n setLength(length) {\\n return this.normalize().multiplyScalar(length);\\n }\\n lerp(v, alpha) {\\n this.x += (v.x - this.x) * alpha;\\n this.y += (v.y - this.y) * alpha;\\n return this;\\n }\\n lerpVectors(v1, v2, alpha) {\\n this.x = v1.x + (v2.x - v1.x) * alpha;\\n this.y = v1.y + (v2.y - v1.y) * alpha;\\n return this;\\n }\\n equals(v) {\\n return v.x === this.x && v.y === this.y;\\n }\\n fromArray(array, offset = 0) {\\n this.x = array[offset];\\n this.y = array[offset + 1];\\n return this;\\n }\\n toArray(array = [], offset = 0) {\\n array[offset] = this.x;\\n array[offset + 1] = this.y;\\n return array;\\n }\\n fromBufferAttribute(attribute, index, offset) {\\n if (offset !== void 0) {\\n console.warn(\\\\\\\"THREE.Vector2: offset has been removed from .fromBufferAttribute().\\\\\\\");\\n }\\n this.x = attribute.getX(index);\\n this.y = attribute.getY(index);\\n return this;\\n }\\n rotateAround(center, angle) {\\n const c = Math.cos(angle), s = Math.sin(angle);\\n const x = this.x - center.x;\\n const y = this.y - center.y;\\n this.x = x * c - y * s + center.x;\\n this.y = x * s + y * c + center.y;\\n return this;\\n }\\n random() {\\n this.x = Math.random();\\n this.y = Math.random();\\n return this;\\n }\\n *[Symbol.iterator]() {\\n yield this.x;\\n yield this.y;\\n }\\n};\\nVector2.prototype.isVector2 = true;\\n\\n// ../../../node_modules/three/src/math/Color.js\\nvar _colorKeywords = {\\n aliceblue: 15792383,\\n antiquewhite: 16444375,\\n aqua: 65535,\\n aquamarine: 8388564,\\n azure: 15794175,\\n beige: 16119260,\\n bisque: 16770244,\\n black: 0,\\n blanchedalmond: 16772045,\\n blue: 255,\\n blueviolet: 9055202,\\n brown: 10824234,\\n burlywood: 14596231,\\n cadetblue: 6266528,\\n chartreuse: 8388352,\\n chocolate: 13789470,\\n coral: 16744272,\\n cornflowerblue: 6591981,\\n cornsilk: 16775388,\\n crimson: 14423100,\\n cyan: 65535,\\n darkblue: 139,\\n darkcyan: 35723,\\n darkgoldenrod: 12092939,\\n darkgray: 11119017,\\n darkgreen: 25600,\\n darkgrey: 11119017,\\n darkkhaki: 12433259,\\n darkmagenta: 9109643,\\n darkolivegreen: 5597999,\\n darkorange: 16747520,\\n darkorchid: 10040012,\\n darkred: 9109504,\\n darksalmon: 15308410,\\n darkseagreen: 9419919,\\n darkslateblue: 4734347,\\n darkslategray: 3100495,\\n darkslategrey: 3100495,\\n darkturquoise: 52945,\\n darkviolet: 9699539,\\n deeppink: 16716947,\\n deepskyblue: 49151,\\n dimgray: 6908265,\\n dimgrey: 6908265,\\n dodgerblue: 2003199,\\n firebrick: 11674146,\\n floralwhite: 16775920,\\n forestgreen: 2263842,\\n fuchsia: 16711935,\\n gainsboro: 14474460,\\n ghostwhite: 16316671,\\n gold: 16766720,\\n goldenrod: 14329120,\\n gray: 8421504,\\n green: 32768,\\n greenyellow: 11403055,\\n grey: 8421504,\\n honeydew: 15794160,\\n hotpink: 16738740,\\n indianred: 13458524,\\n indigo: 4915330,\\n ivory: 16777200,\\n khaki: 15787660,\\n lavender: 15132410,\\n lavenderblush: 16773365,\\n lawngreen: 8190976,\\n lemonchiffon: 16775885,\\n lightblue: 11393254,\\n lightcoral: 15761536,\\n lightcyan: 14745599,\\n lightgoldenrodyellow: 16448210,\\n lightgray: 13882323,\\n lightgreen: 9498256,\\n lightgrey: 13882323,\\n lightpink: 16758465,\\n lightsalmon: 16752762,\\n lightseagreen: 2142890,\\n lightskyblue: 8900346,\\n lightslategray: 7833753,\\n lightslategrey: 7833753,\\n lightsteelblue: 11584734,\\n lightyellow: 16777184,\\n lime: 65280,\\n limegreen: 3329330,\\n linen: 16445670,\\n magenta: 16711935,\\n maroon: 8388608,\\n mediumaquamarine: 6737322,\\n mediumblue: 205,\\n mediumorchid: 12211667,\\n mediumpurple: 9662683,\\n mediumseagreen: 3978097,\\n mediumslateblue: 8087790,\\n mediumspringgreen: 64154,\\n mediumturquoise: 4772300,\\n mediumvioletred: 13047173,\\n midnightblue: 1644912,\\n mintcream: 16121850,\\n mistyrose: 16770273,\\n moccasin: 16770229,\\n navajowhite: 16768685,\\n navy: 128,\\n oldlace: 16643558,\\n olive: 8421376,\\n olivedrab: 7048739,\\n orange: 16753920,\\n orangered: 16729344,\\n orchid: 14315734,\\n palegoldenrod: 15657130,\\n palegreen: 10025880,\\n paleturquoise: 11529966,\\n palevioletred: 14381203,\\n papayawhip: 16773077,\\n peachpuff: 16767673,\\n peru: 13468991,\\n pink: 16761035,\\n plum: 14524637,\\n powderblue: 11591910,\\n purple: 8388736,\\n rebeccapurple: 6697881,\\n red: 16711680,\\n rosybrown: 12357519,\\n royalblue: 4286945,\\n saddlebrown: 9127187,\\n salmon: 16416882,\\n sandybrown: 16032864,\\n seagreen: 3050327,\\n seashell: 16774638,\\n sienna: 10506797,\\n silver: 12632256,\\n skyblue: 8900331,\\n slateblue: 6970061,\\n slategray: 7372944,\\n slategrey: 7372944,\\n snow: 16775930,\\n springgreen: 65407,\\n steelblue: 4620980,\\n tan: 13808780,\\n teal: 32896,\\n thistle: 14204888,\\n tomato: 16737095,\\n turquoise: 4251856,\\n violet: 15631086,\\n wheat: 16113331,\\n white: 16777215,\\n whitesmoke: 16119285,\\n yellow: 16776960,\\n yellowgreen: 10145074\\n};\\nvar _hslA = {h: 0, s: 0, l: 0};\\nvar _hslB = {h: 0, s: 0, l: 0};\\nfunction hue2rgb(p, q, t) {\\n if (t < 0)\\n t += 1;\\n if (t > 1)\\n t -= 1;\\n if (t < 1 / 6)\\n return p + (q - p) * 6 * t;\\n if (t < 1 / 2)\\n return q;\\n if (t < 2 / 3)\\n return p + (q - p) * 6 * (2 / 3 - t);\\n return p;\\n}\\nfunction SRGBToLinear(c) {\\n return c < 0.04045 ? c * 0.0773993808 : Math.pow(c * 0.9478672986 + 0.0521327014, 2.4);\\n}\\nfunction LinearToSRGB(c) {\\n return c < 31308e-7 ? c * 12.92 : 1.055 * Math.pow(c, 0.41666) - 0.055;\\n}\\nvar Color = class {\\n constructor(r, g, b) {\\n if (g === void 0 && b === void 0) {\\n return this.set(r);\\n }\\n return this.setRGB(r, g, b);\\n }\\n set(value) {\\n if (value && value.isColor) {\\n this.copy(value);\\n } else if (typeof value === \\\\\\\"number\\\\\\\") {\\n this.setHex(value);\\n } else if (typeof value === \\\\\\\"string\\\\\\\") {\\n this.setStyle(value);\\n }\\n return this;\\n }\\n setScalar(scalar) {\\n this.r = scalar;\\n this.g = scalar;\\n this.b = scalar;\\n return this;\\n }\\n setHex(hex) {\\n hex = Math.floor(hex);\\n this.r = (hex >> 16 & 255) / 255;\\n this.g = (hex >> 8 & 255) / 255;\\n this.b = (hex & 255) / 255;\\n return this;\\n }\\n setRGB(r, g, b) {\\n this.r = r;\\n this.g = g;\\n this.b = b;\\n return this;\\n }\\n setHSL(h, s, l) {\\n h = euclideanModulo(h, 1);\\n s = clamp(s, 0, 1);\\n l = clamp(l, 0, 1);\\n if (s === 0) {\\n this.r = this.g = this.b = l;\\n } else {\\n const p = l <= 0.5 ? l * (1 + s) : l + s - l * s;\\n const q = 2 * l - p;\\n this.r = hue2rgb(q, p, h + 1 / 3);\\n this.g = hue2rgb(q, p, h);\\n this.b = hue2rgb(q, p, h - 1 / 3);\\n }\\n return this;\\n }\\n setStyle(style) {\\n function handleAlpha(string) {\\n if (string === void 0)\\n return;\\n if (parseFloat(string) < 1) {\\n console.warn(\\\\\\\"THREE.Color: Alpha component of \\\\\\\" + style + \\\\\\\" will be ignored.\\\\\\\");\\n }\\n }\\n let m;\\n if (m = /^((?:rgb|hsl)a?)\\\\(([^\\\\)]*)\\\\)/.exec(style)) {\\n let color;\\n const name = m[1];\\n const components = m[2];\\n switch (name) {\\n case \\\\\\\"rgb\\\\\\\":\\n case \\\\\\\"rgba\\\\\\\":\\n if (color = /^\\\\s*(\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(components)) {\\n this.r = Math.min(255, parseInt(color[1], 10)) / 255;\\n this.g = Math.min(255, parseInt(color[2], 10)) / 255;\\n this.b = Math.min(255, parseInt(color[3], 10)) / 255;\\n handleAlpha(color[4]);\\n return this;\\n }\\n if (color = /^\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(components)) {\\n this.r = Math.min(100, parseInt(color[1], 10)) / 100;\\n this.g = Math.min(100, parseInt(color[2], 10)) / 100;\\n this.b = Math.min(100, parseInt(color[3], 10)) / 100;\\n handleAlpha(color[4]);\\n return this;\\n }\\n break;\\n case \\\\\\\"hsl\\\\\\\":\\n case \\\\\\\"hsla\\\\\\\":\\n if (color = /^\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*,\\\\s*(\\\\d+)\\\\%\\\\s*(?:,\\\\s*(\\\\d*\\\\.?\\\\d+)\\\\s*)?$/.exec(components)) {\\n const h = parseFloat(color[1]) / 360;\\n const s = parseInt(color[2], 10) / 100;\\n const l = parseInt(color[3], 10) / 100;\\n handleAlpha(color[4]);\\n return this.setHSL(h, s, l);\\n }\\n break;\\n }\\n } else if (m = /^\\\\#([A-Fa-f\\\\d]+)$/.exec(style)) {\\n const hex = m[1];\\n const size = hex.length;\\n if (size === 3) {\\n this.r = parseInt(hex.charAt(0) + hex.charAt(0), 16) / 255;\\n this.g = parseInt(hex.charAt(1) + hex.charAt(1), 16) / 255;\\n this.b = parseInt(hex.charAt(2) + hex.charAt(2), 16) / 255;\\n return this;\\n } else if (size === 6) {\\n this.r = parseInt(hex.charAt(0) + hex.charAt(1), 16) / 255;\\n this.g = parseInt(hex.charAt(2) + hex.charAt(3), 16) / 255;\\n this.b = parseInt(hex.charAt(4) + hex.charAt(5), 16) / 255;\\n return this;\\n }\\n }\\n if (style && style.length > 0) {\\n return this.setColorName(style);\\n }\\n return this;\\n }\\n setColorName(style) {\\n const hex = _colorKeywords[style.toLowerCase()];\\n if (hex !== void 0) {\\n this.setHex(hex);\\n } else {\\n console.warn(\\\\\\\"THREE.Color: Unknown color \\\\\\\" + style);\\n }\\n return this;\\n }\\n clone() {\\n return new this.constructor(this.r, this.g, this.b);\\n }\\n copy(color) {\\n this.r = color.r;\\n this.g = color.g;\\n this.b = color.b;\\n return this;\\n }\\n copyGammaToLinear(color, gammaFactor = 2) {\\n this.r = Math.pow(color.r, gammaFactor);\\n this.g = Math.pow(color.g, gammaFactor);\\n this.b = Math.pow(color.b, gammaFactor);\\n return this;\\n }\\n copyLinearToGamma(color, gammaFactor = 2) {\\n const safeInverse = gammaFactor > 0 ? 1 / gammaFactor : 1;\\n this.r = Math.pow(color.r, safeInverse);\\n this.g = Math.pow(color.g, safeInverse);\\n this.b = Math.pow(color.b, safeInverse);\\n return this;\\n }\\n convertGammaToLinear(gammaFactor) {\\n this.copyGammaToLinear(this, gammaFactor);\\n return this;\\n }\\n convertLinearToGamma(gammaFactor) {\\n this.copyLinearToGamma(this, gammaFactor);\\n return this;\\n }\\n copySRGBToLinear(color) {\\n this.r = SRGBToLinear(color.r);\\n this.g = SRGBToLinear(color.g);\\n this.b = SRGBToLinear(color.b);\\n return this;\\n }\\n copyLinearToSRGB(color) {\\n this.r = LinearToSRGB(color.r);\\n this.g = LinearToSRGB(color.g);\\n this.b = LinearToSRGB(color.b);\\n return this;\\n }\\n convertSRGBToLinear() {\\n this.copySRGBToLinear(this);\\n return this;\\n }\\n convertLinearToSRGB() {\\n this.copyLinearToSRGB(this);\\n return this;\\n }\\n getHex() {\\n return this.r * 255 << 16 ^ this.g * 255 << 8 ^ this.b * 255 << 0;\\n }\\n getHexString() {\\n return (\\\\\\\"000000\\\\\\\" + this.getHex().toString(16)).slice(-6);\\n }\\n getHSL(target) {\\n const r = this.r, g = this.g, b = this.b;\\n const max = Math.max(r, g, b);\\n const min = Math.min(r, g, b);\\n let hue, saturation;\\n const lightness = (min + max) / 2;\\n if (min === max) {\\n hue = 0;\\n saturation = 0;\\n } else {\\n const delta = max - min;\\n saturation = lightness <= 0.5 ? delta / (max + min) : delta / (2 - max - min);\\n switch (max) {\\n case r:\\n hue = (g - b) / delta + (g < b ? 6 : 0);\\n break;\\n case g:\\n hue = (b - r) / delta + 2;\\n break;\\n case b:\\n hue = (r - g) / delta + 4;\\n break;\\n }\\n hue /= 6;\\n }\\n target.h = hue;\\n target.s = saturation;\\n target.l = lightness;\\n return target;\\n }\\n getStyle() {\\n return \\\\\\\"rgb(\\\\\\\" + (this.r * 255 | 0) + \\\\\\\",\\\\\\\" + (this.g * 255 | 0) + \\\\\\\",\\\\\\\" + (this.b * 255 | 0) + \\\\\\\")\\\\\\\";\\n }\\n offsetHSL(h, s, l) {\\n this.getHSL(_hslA);\\n _hslA.h += h;\\n _hslA.s += s;\\n _hslA.l += l;\\n this.setHSL(_hslA.h, _hslA.s, _hslA.l);\\n return this;\\n }\\n add(color) {\\n this.r += color.r;\\n this.g += color.g;\\n this.b += color.b;\\n return this;\\n }\\n addColors(color1, color2) {\\n this.r = color1.r + color2.r;\\n this.g = color1.g + color2.g;\\n this.b = color1.b + color2.b;\\n return this;\\n }\\n addScalar(s) {\\n this.r += s;\\n this.g += s;\\n this.b += s;\\n return this;\\n }\\n sub(color) {\\n this.r = Math.max(0, this.r - color.r);\\n this.g = Math.max(0, this.g - color.g);\\n this.b = Math.max(0, this.b - color.b);\\n return this;\\n }\\n multiply(color) {\\n this.r *= color.r;\\n this.g *= color.g;\\n this.b *= color.b;\\n return this;\\n }\\n multiplyScalar(s) {\\n this.r *= s;\\n this.g *= s;\\n this.b *= s;\\n return this;\\n }\\n lerp(color, alpha) {\\n this.r += (color.r - this.r) * alpha;\\n this.g += (color.g - this.g) * alpha;\\n this.b += (color.b - this.b) * alpha;\\n return this;\\n }\\n lerpColors(color1, color2, alpha) {\\n this.r = color1.r + (color2.r - color1.r) * alpha;\\n this.g = color1.g + (color2.g - color1.g) * alpha;\\n this.b = color1.b + (color2.b - color1.b) * alpha;\\n return this;\\n }\\n lerpHSL(color, alpha) {\\n this.getHSL(_hslA);\\n color.getHSL(_hslB);\\n const h = lerp(_hslA.h, _hslB.h, alpha);\\n const s = lerp(_hslA.s, _hslB.s, alpha);\\n const l = lerp(_hslA.l, _hslB.l, alpha);\\n this.setHSL(h, s, l);\\n return this;\\n }\\n equals(c) {\\n return c.r === this.r && c.g === this.g && c.b === this.b;\\n }\\n fromArray(array, offset = 0) {\\n this.r = array[offset];\\n this.g = array[offset + 1];\\n this.b = array[offset + 2];\\n return this;\\n }\\n toArray(array = [], offset = 0) {\\n array[offset] = this.r;\\n array[offset + 1] = this.g;\\n array[offset + 2] = this.b;\\n return array;\\n }\\n fromBufferAttribute(attribute, index) {\\n this.r = attribute.getX(index);\\n this.g = attribute.getY(index);\\n this.b = attribute.getZ(index);\\n if (attribute.normalized === true) {\\n this.r /= 255;\\n this.g /= 255;\\n this.b /= 255;\\n }\\n return this;\\n }\\n toJSON() {\\n return this.getHex();\\n }\\n};\\nColor.NAMES = _colorKeywords;\\nColor.prototype.isColor = true;\\nColor.prototype.r = 1;\\nColor.prototype.g = 1;\\nColor.prototype.b = 1;\\n\\n// ../../../node_modules/three/src/core/BufferAttribute.js\\nvar _vector4 = /* @__PURE__ */ new Vector3();\\nvar _vector23 = /* @__PURE__ */ new Vector2();\\nvar BufferAttribute = class {\\n constructor(array, itemSize, normalized) {\\n if (Array.isArray(array)) {\\n throw new TypeError(\\\\\\\"THREE.BufferAttribute: array should be a Typed Array.\\\\\\\");\\n }\\n this.name = \\\\\\\"\\\\\\\";\\n this.array = array;\\n this.itemSize = itemSize;\\n this.count = array !== void 0 ? array.length / itemSize : 0;\\n this.normalized = normalized === true;\\n this.usage = StaticDrawUsage;\\n this.updateRange = {offset: 0, count: -1};\\n this.version = 0;\\n }\\n onUploadCallback() {\\n }\\n set needsUpdate(value) {\\n if (value === true)\\n this.version++;\\n }\\n setUsage(value) {\\n this.usage = value;\\n return this;\\n }\\n copy(source) {\\n this.name = source.name;\\n this.array = new source.array.constructor(source.array);\\n this.itemSize = source.itemSize;\\n this.count = source.count;\\n this.normalized = source.normalized;\\n this.usage = source.usage;\\n return this;\\n }\\n copyAt(index1, attribute, index2) {\\n index1 *= this.itemSize;\\n index2 *= attribute.itemSize;\\n for (let i = 0, l = this.itemSize; i < l; i++) {\\n this.array[index1 + i] = attribute.array[index2 + i];\\n }\\n return this;\\n }\\n copyArray(array) {\\n this.array.set(array);\\n return this;\\n }\\n copyColorsArray(colors) {\\n const array = this.array;\\n let offset = 0;\\n for (let i = 0, l = colors.length; i < l; i++) {\\n let color = colors[i];\\n if (color === void 0) {\\n console.warn(\\\\\\\"THREE.BufferAttribute.copyColorsArray(): color is undefined\\\\\\\", i);\\n color = new Color();\\n }\\n array[offset++] = color.r;\\n array[offset++] = color.g;\\n array[offset++] = color.b;\\n }\\n return this;\\n }\\n copyVector2sArray(vectors) {\\n const array = this.array;\\n let offset = 0;\\n for (let i = 0, l = vectors.length; i < l; i++) {\\n let vector = vectors[i];\\n if (vector === void 0) {\\n console.warn(\\\\\\\"THREE.BufferAttribute.copyVector2sArray(): vector is undefined\\\\\\\", i);\\n vector = new Vector2();\\n }\\n array[offset++] = vector.x;\\n array[offset++] = vector.y;\\n }\\n return this;\\n }\\n copyVector3sArray(vectors) {\\n const array = this.array;\\n let offset = 0;\\n for (let i = 0, l = vectors.length; i < l; i++) {\\n let vector = vectors[i];\\n if (vector === void 0) {\\n console.warn(\\\\\\\"THREE.BufferAttribute.copyVector3sArray(): vector is undefined\\\\\\\", i);\\n vector = new Vector3();\\n }\\n array[offset++] = vector.x;\\n array[offset++] = vector.y;\\n array[offset++] = vector.z;\\n }\\n return this;\\n }\\n copyVector4sArray(vectors) {\\n const array = this.array;\\n let offset = 0;\\n for (let i = 0, l = vectors.length; i < l; i++) {\\n let vector = vectors[i];\\n if (vector === void 0) {\\n console.warn(\\\\\\\"THREE.BufferAttribute.copyVector4sArray(): vector is undefined\\\\\\\", i);\\n vector = new Vector4();\\n }\\n array[offset++] = vector.x;\\n array[offset++] = vector.y;\\n array[offset++] = vector.z;\\n array[offset++] = vector.w;\\n }\\n return this;\\n }\\n applyMatrix3(m) {\\n if (this.itemSize === 2) {\\n for (let i = 0, l = this.count; i < l; i++) {\\n _vector23.fromBufferAttribute(this, i);\\n _vector23.applyMatrix3(m);\\n this.setXY(i, _vector23.x, _vector23.y);\\n }\\n } else if (this.itemSize === 3) {\\n for (let i = 0, l = this.count; i < l; i++) {\\n _vector4.fromBufferAttribute(this, i);\\n _vector4.applyMatrix3(m);\\n this.setXYZ(i, _vector4.x, _vector4.y, _vector4.z);\\n }\\n }\\n return this;\\n }\\n applyMatrix4(m) {\\n for (let i = 0, l = this.count; i < l; i++) {\\n _vector4.x = this.getX(i);\\n _vector4.y = this.getY(i);\\n _vector4.z = this.getZ(i);\\n _vector4.applyMatrix4(m);\\n this.setXYZ(i, _vector4.x, _vector4.y, _vector4.z);\\n }\\n return this;\\n }\\n applyNormalMatrix(m) {\\n for (let i = 0, l = this.count; i < l; i++) {\\n _vector4.x = this.getX(i);\\n _vector4.y = this.getY(i);\\n _vector4.z = this.getZ(i);\\n _vector4.applyNormalMatrix(m);\\n this.setXYZ(i, _vector4.x, _vector4.y, _vector4.z);\\n }\\n return this;\\n }\\n transformDirection(m) {\\n for (let i = 0, l = this.count; i < l; i++) {\\n _vector4.x = this.getX(i);\\n _vector4.y = this.getY(i);\\n _vector4.z = this.getZ(i);\\n _vector4.transformDirection(m);\\n this.setXYZ(i, _vector4.x, _vector4.y, _vector4.z);\\n }\\n return this;\\n }\\n set(value, offset = 0) {\\n this.array.set(value, offset);\\n return this;\\n }\\n getX(index) {\\n return this.array[index * this.itemSize];\\n }\\n setX(index, x) {\\n this.array[index * this.itemSize] = x;\\n return this;\\n }\\n getY(index) {\\n return this.array[index * this.itemSize + 1];\\n }\\n setY(index, y) {\\n this.array[index * this.itemSize + 1] = y;\\n return this;\\n }\\n getZ(index) {\\n return this.array[index * this.itemSize + 2];\\n }\\n setZ(index, z) {\\n this.array[index * this.itemSize + 2] = z;\\n return this;\\n }\\n getW(index) {\\n return this.array[index * this.itemSize + 3];\\n }\\n setW(index, w) {\\n this.array[index * this.itemSize + 3] = w;\\n return this;\\n }\\n setXY(index, x, y) {\\n index *= this.itemSize;\\n this.array[index + 0] = x;\\n this.array[index + 1] = y;\\n return this;\\n }\\n setXYZ(index, x, y, z) {\\n index *= this.itemSize;\\n this.array[index + 0] = x;\\n this.array[index + 1] = y;\\n this.array[index + 2] = z;\\n return this;\\n }\\n setXYZW(index, x, y, z, w) {\\n index *= this.itemSize;\\n this.array[index + 0] = x;\\n this.array[index + 1] = y;\\n this.array[index + 2] = z;\\n this.array[index + 3] = w;\\n return this;\\n }\\n onUpload(callback) {\\n this.onUploadCallback = callback;\\n return this;\\n }\\n clone() {\\n return new this.constructor(this.array, this.itemSize).copy(this);\\n }\\n toJSON() {\\n const data = {\\n itemSize: this.itemSize,\\n type: this.array.constructor.name,\\n array: Array.prototype.slice.call(this.array),\\n normalized: this.normalized\\n };\\n if (this.name !== \\\\\\\"\\\\\\\")\\n data.name = this.name;\\n if (this.usage !== StaticDrawUsage)\\n data.usage = this.usage;\\n if (this.updateRange.offset !== 0 || this.updateRange.count !== -1)\\n data.updateRange = this.updateRange;\\n return data;\\n }\\n};\\nBufferAttribute.prototype.isBufferAttribute = true;\\nvar Uint16BufferAttribute = class extends BufferAttribute {\\n constructor(array, itemSize, normalized) {\\n super(new Uint16Array(array), itemSize, normalized);\\n }\\n};\\nvar Int32BufferAttribute = class extends BufferAttribute {\\n constructor(array, itemSize, normalized) {\\n super(new Int32Array(array), itemSize, normalized);\\n }\\n};\\nvar Uint32BufferAttribute = class extends BufferAttribute {\\n constructor(array, itemSize, normalized) {\\n super(new Uint32Array(array), itemSize, normalized);\\n }\\n};\\nvar Float16BufferAttribute = class extends BufferAttribute {\\n constructor(array, itemSize, normalized) {\\n super(new Uint16Array(array), itemSize, normalized);\\n }\\n};\\nFloat16BufferAttribute.prototype.isFloat16BufferAttribute = true;\\nvar Float32BufferAttribute = class extends BufferAttribute {\\n constructor(array, itemSize, normalized) {\\n super(new Float32Array(array), itemSize, normalized);\\n }\\n};\\n\\n// ../../../node_modules/three/src/utils.js\\nfunction arrayMax(array) {\\n if (array.length === 0)\\n return -Infinity;\\n let max = array[0];\\n for (let i = 1, l = array.length; i < l; ++i) {\\n if (array[i] > max)\\n max = array[i];\\n }\\n return max;\\n}\\nvar TYPED_ARRAYS = {\\n Int8Array,\\n Uint8Array,\\n Uint8ClampedArray,\\n Int16Array,\\n Uint16Array,\\n Int32Array,\\n Uint32Array,\\n Float32Array,\\n Float64Array\\n};\\nfunction createElementNS(name) {\\n return document.createElementNS(\\\\\\\"http://www.w3.org/1999/xhtml\\\\\\\", name);\\n}\\n\\n// ../../../node_modules/three/src/core/BufferGeometry.js\\nvar _id = 0;\\nvar _m13 = /* @__PURE__ */ new Matrix4();\\nvar _obj = /* @__PURE__ */ new Object3D();\\nvar _offset = /* @__PURE__ */ new Vector3();\\nvar _box3 = /* @__PURE__ */ new Box3();\\nvar _boxMorphTargets = /* @__PURE__ */ new Box3();\\nvar _vector5 = /* @__PURE__ */ new Vector3();\\nvar BufferGeometry = class extends EventDispatcher {\\n constructor() {\\n super();\\n Object.defineProperty(this, \\\\\\\"id\\\\\\\", {value: _id++});\\n this.uuid = generateUUID();\\n this.name = \\\\\\\"\\\\\\\";\\n this.type = \\\\\\\"BufferGeometry\\\\\\\";\\n this.index = null;\\n this.attributes = {};\\n this.morphAttributes = {};\\n this.morphTargetsRelative = false;\\n this.groups = [];\\n this.boundingBox = null;\\n this.boundingSphere = null;\\n this.drawRange = {start: 0, count: Infinity};\\n this.userData = {};\\n }\\n getIndex() {\\n return this.index;\\n }\\n setIndex(index) {\\n if (Array.isArray(index)) {\\n this.index = new (arrayMax(index) > 65535 ? Uint32BufferAttribute : Uint16BufferAttribute)(index, 1);\\n } else {\\n this.index = index;\\n }\\n return this;\\n }\\n getAttribute(name) {\\n return this.attributes[name];\\n }\\n setAttribute(name, attribute) {\\n this.attributes[name] = attribute;\\n return this;\\n }\\n deleteAttribute(name) {\\n delete this.attributes[name];\\n return this;\\n }\\n hasAttribute(name) {\\n return this.attributes[name] !== void 0;\\n }\\n addGroup(start, count, materialIndex = 0) {\\n this.groups.push({\\n start,\\n count,\\n materialIndex\\n });\\n }\\n clearGroups() {\\n this.groups = [];\\n }\\n setDrawRange(start, count) {\\n this.drawRange.start = start;\\n this.drawRange.count = count;\\n }\\n applyMatrix4(matrix) {\\n const position = this.attributes.position;\\n if (position !== void 0) {\\n position.applyMatrix4(matrix);\\n position.needsUpdate = true;\\n }\\n const normal = this.attributes.normal;\\n if (normal !== void 0) {\\n const normalMatrix = new Matrix3().getNormalMatrix(matrix);\\n normal.applyNormalMatrix(normalMatrix);\\n normal.needsUpdate = true;\\n }\\n const tangent = this.attributes.tangent;\\n if (tangent !== void 0) {\\n tangent.transformDirection(matrix);\\n tangent.needsUpdate = true;\\n }\\n if (this.boundingBox !== null) {\\n this.computeBoundingBox();\\n }\\n if (this.boundingSphere !== null) {\\n this.computeBoundingSphere();\\n }\\n return this;\\n }\\n applyQuaternion(q) {\\n _m13.makeRotationFromQuaternion(q);\\n this.applyMatrix4(_m13);\\n return this;\\n }\\n rotateX(angle) {\\n _m13.makeRotationX(angle);\\n this.applyMatrix4(_m13);\\n return this;\\n }\\n rotateY(angle) {\\n _m13.makeRotationY(angle);\\n this.applyMatrix4(_m13);\\n return this;\\n }\\n rotateZ(angle) {\\n _m13.makeRotationZ(angle);\\n this.applyMatrix4(_m13);\\n return this;\\n }\\n translate(x, y, z) {\\n _m13.makeTranslation(x, y, z);\\n this.applyMatrix4(_m13);\\n return this;\\n }\\n scale(x, y, z) {\\n _m13.makeScale(x, y, z);\\n this.applyMatrix4(_m13);\\n return this;\\n }\\n lookAt(vector) {\\n _obj.lookAt(vector);\\n _obj.updateMatrix();\\n this.applyMatrix4(_obj.matrix);\\n return this;\\n }\\n center() {\\n this.computeBoundingBox();\\n this.boundingBox.getCenter(_offset).negate();\\n this.translate(_offset.x, _offset.y, _offset.z);\\n return this;\\n }\\n setFromPoints(points2) {\\n const position = [];\\n for (let i = 0, l = points2.length; i < l; i++) {\\n const point = points2[i];\\n position.push(point.x, point.y, point.z || 0);\\n }\\n this.setAttribute(\\\\\\\"position\\\\\\\", new Float32BufferAttribute(position, 3));\\n return this;\\n }\\n computeBoundingBox() {\\n if (this.boundingBox === null) {\\n this.boundingBox = new Box3();\\n }\\n const position = this.attributes.position;\\n const morphAttributesPosition = this.morphAttributes.position;\\n if (position && position.isGLBufferAttribute) {\\n console.error('THREE.BufferGeometry.computeBoundingBox(): GLBufferAttribute requires a manual bounding box. Alternatively set \\\\\\\"mesh.frustumCulled\\\\\\\" to \\\\\\\"false\\\\\\\".', this);\\n this.boundingBox.set(new Vector3(-Infinity, -Infinity, -Infinity), new Vector3(Infinity, Infinity, Infinity));\\n return;\\n }\\n if (position !== void 0) {\\n this.boundingBox.setFromBufferAttribute(position);\\n if (morphAttributesPosition) {\\n for (let i = 0, il = morphAttributesPosition.length; i < il; i++) {\\n const morphAttribute = morphAttributesPosition[i];\\n _box3.setFromBufferAttribute(morphAttribute);\\n if (this.morphTargetsRelative) {\\n _vector5.addVectors(this.boundingBox.min, _box3.min);\\n this.boundingBox.expandByPoint(_vector5);\\n _vector5.addVectors(this.boundingBox.max, _box3.max);\\n this.boundingBox.expandByPoint(_vector5);\\n } else {\\n this.boundingBox.expandByPoint(_box3.min);\\n this.boundingBox.expandByPoint(_box3.max);\\n }\\n }\\n }\\n } else {\\n this.boundingBox.makeEmpty();\\n }\\n if (isNaN(this.boundingBox.min.x) || isNaN(this.boundingBox.min.y) || isNaN(this.boundingBox.min.z)) {\\n console.error('THREE.BufferGeometry.computeBoundingBox(): Computed min/max have NaN values. The \\\\\\\"position\\\\\\\" attribute is likely to have NaN values.', this);\\n }\\n }\\n computeBoundingSphere() {\\n if (this.boundingSphere === null) {\\n this.boundingSphere = new Sphere();\\n }\\n const position = this.attributes.position;\\n const morphAttributesPosition = this.morphAttributes.position;\\n if (position && position.isGLBufferAttribute) {\\n console.error('THREE.BufferGeometry.computeBoundingSphere(): GLBufferAttribute requires a manual bounding sphere. Alternatively set \\\\\\\"mesh.frustumCulled\\\\\\\" to \\\\\\\"false\\\\\\\".', this);\\n this.boundingSphere.set(new Vector3(), Infinity);\\n return;\\n }\\n if (position) {\\n const center = this.boundingSphere.center;\\n _box3.setFromBufferAttribute(position);\\n if (morphAttributesPosition) {\\n for (let i = 0, il = morphAttributesPosition.length; i < il; i++) {\\n const morphAttribute = morphAttributesPosition[i];\\n _boxMorphTargets.setFromBufferAttribute(morphAttribute);\\n if (this.morphTargetsRelative) {\\n _vector5.addVectors(_box3.min, _boxMorphTargets.min);\\n _box3.expandByPoint(_vector5);\\n _vector5.addVectors(_box3.max, _boxMorphTargets.max);\\n _box3.expandByPoint(_vector5);\\n } else {\\n _box3.expandByPoint(_boxMorphTargets.min);\\n _box3.expandByPoint(_boxMorphTargets.max);\\n }\\n }\\n }\\n _box3.getCenter(center);\\n let maxRadiusSq = 0;\\n for (let i = 0, il = position.count; i < il; i++) {\\n _vector5.fromBufferAttribute(position, i);\\n maxRadiusSq = Math.max(maxRadiusSq, center.distanceToSquared(_vector5));\\n }\\n if (morphAttributesPosition) {\\n for (let i = 0, il = morphAttributesPosition.length; i < il; i++) {\\n const morphAttribute = morphAttributesPosition[i];\\n const morphTargetsRelative = this.morphTargetsRelative;\\n for (let j = 0, jl = morphAttribute.count; j < jl; j++) {\\n _vector5.fromBufferAttribute(morphAttribute, j);\\n if (morphTargetsRelative) {\\n _offset.fromBufferAttribute(position, j);\\n _vector5.add(_offset);\\n }\\n maxRadiusSq = Math.max(maxRadiusSq, center.distanceToSquared(_vector5));\\n }\\n }\\n }\\n this.boundingSphere.radius = Math.sqrt(maxRadiusSq);\\n if (isNaN(this.boundingSphere.radius)) {\\n console.error('THREE.BufferGeometry.computeBoundingSphere(): Computed radius is NaN. The \\\\\\\"position\\\\\\\" attribute is likely to have NaN values.', this);\\n }\\n }\\n }\\n computeTangents() {\\n const index = this.index;\\n const attributes = this.attributes;\\n if (index === null || attributes.position === void 0 || attributes.normal === void 0 || attributes.uv === void 0) {\\n console.error(\\\\\\\"THREE.BufferGeometry: .computeTangents() failed. Missing required attributes (index, position, normal or uv)\\\\\\\");\\n return;\\n }\\n const indices = index.array;\\n const positions = attributes.position.array;\\n const normals = attributes.normal.array;\\n const uvs = attributes.uv.array;\\n const nVertices = positions.length / 3;\\n if (attributes.tangent === void 0) {\\n this.setAttribute(\\\\\\\"tangent\\\\\\\", new BufferAttribute(new Float32Array(4 * nVertices), 4));\\n }\\n const tangents = attributes.tangent.array;\\n const tan1 = [], tan2 = [];\\n for (let i = 0; i < nVertices; i++) {\\n tan1[i] = new Vector3();\\n tan2[i] = new Vector3();\\n }\\n const vA = new Vector3(), vB = new Vector3(), vC = new Vector3(), uvA = new Vector2(), uvB = new Vector2(), uvC = new Vector2(), sdir = new Vector3(), tdir = new Vector3();\\n function handleTriangle(a, b, c) {\\n vA.fromArray(positions, a * 3);\\n vB.fromArray(positions, b * 3);\\n vC.fromArray(positions, c * 3);\\n uvA.fromArray(uvs, a * 2);\\n uvB.fromArray(uvs, b * 2);\\n uvC.fromArray(uvs, c * 2);\\n vB.sub(vA);\\n vC.sub(vA);\\n uvB.sub(uvA);\\n uvC.sub(uvA);\\n const r = 1 / (uvB.x * uvC.y - uvC.x * uvB.y);\\n if (!isFinite(r))\\n return;\\n sdir.copy(vB).multiplyScalar(uvC.y).addScaledVector(vC, -uvB.y).multiplyScalar(r);\\n tdir.copy(vC).multiplyScalar(uvB.x).addScaledVector(vB, -uvC.x).multiplyScalar(r);\\n tan1[a].add(sdir);\\n tan1[b].add(sdir);\\n tan1[c].add(sdir);\\n tan2[a].add(tdir);\\n tan2[b].add(tdir);\\n tan2[c].add(tdir);\\n }\\n let groups = this.groups;\\n if (groups.length === 0) {\\n groups = [{\\n start: 0,\\n count: indices.length\\n }];\\n }\\n for (let i = 0, il = groups.length; i < il; ++i) {\\n const group = groups[i];\\n const start = group.start;\\n const count = group.count;\\n for (let j = start, jl = start + count; j < jl; j += 3) {\\n handleTriangle(indices[j + 0], indices[j + 1], indices[j + 2]);\\n }\\n }\\n const tmp = new Vector3(), tmp2 = new Vector3();\\n const n = new Vector3(), n2 = new Vector3();\\n function handleVertex(v) {\\n n.fromArray(normals, v * 3);\\n n2.copy(n);\\n const t = tan1[v];\\n tmp.copy(t);\\n tmp.sub(n.multiplyScalar(n.dot(t))).normalize();\\n tmp2.crossVectors(n2, t);\\n const test = tmp2.dot(tan2[v]);\\n const w = test < 0 ? -1 : 1;\\n tangents[v * 4] = tmp.x;\\n tangents[v * 4 + 1] = tmp.y;\\n tangents[v * 4 + 2] = tmp.z;\\n tangents[v * 4 + 3] = w;\\n }\\n for (let i = 0, il = groups.length; i < il; ++i) {\\n const group = groups[i];\\n const start = group.start;\\n const count = group.count;\\n for (let j = start, jl = start + count; j < jl; j += 3) {\\n handleVertex(indices[j + 0]);\\n handleVertex(indices[j + 1]);\\n handleVertex(indices[j + 2]);\\n }\\n }\\n }\\n computeVertexNormals() {\\n const index = this.index;\\n const positionAttribute = this.getAttribute(\\\\\\\"position\\\\\\\");\\n if (positionAttribute !== void 0) {\\n let normalAttribute = this.getAttribute(\\\\\\\"normal\\\\\\\");\\n if (normalAttribute === void 0) {\\n normalAttribute = new BufferAttribute(new Float32Array(positionAttribute.count * 3), 3);\\n this.setAttribute(\\\\\\\"normal\\\\\\\", normalAttribute);\\n } else {\\n for (let i = 0, il = normalAttribute.count; i < il; i++) {\\n normalAttribute.setXYZ(i, 0, 0, 0);\\n }\\n }\\n const pA = new Vector3(), pB = new Vector3(), pC = new Vector3();\\n const nA = new Vector3(), nB = new Vector3(), nC = new Vector3();\\n const cb = new Vector3(), ab = new Vector3();\\n if (index) {\\n for (let i = 0, il = index.count; i < il; i += 3) {\\n const vA = index.getX(i + 0);\\n const vB = index.getX(i + 1);\\n const vC = index.getX(i + 2);\\n pA.fromBufferAttribute(positionAttribute, vA);\\n pB.fromBufferAttribute(positionAttribute, vB);\\n pC.fromBufferAttribute(positionAttribute, vC);\\n cb.subVectors(pC, pB);\\n ab.subVectors(pA, pB);\\n cb.cross(ab);\\n nA.fromBufferAttribute(normalAttribute, vA);\\n nB.fromBufferAttribute(normalAttribute, vB);\\n nC.fromBufferAttribute(normalAttribute, vC);\\n nA.add(cb);\\n nB.add(cb);\\n nC.add(cb);\\n normalAttribute.setXYZ(vA, nA.x, nA.y, nA.z);\\n normalAttribute.setXYZ(vB, nB.x, nB.y, nB.z);\\n normalAttribute.setXYZ(vC, nC.x, nC.y, nC.z);\\n }\\n } else {\\n for (let i = 0, il = positionAttribute.count; i < il; i += 3) {\\n pA.fromBufferAttribute(positionAttribute, i + 0);\\n pB.fromBufferAttribute(positionAttribute, i + 1);\\n pC.fromBufferAttribute(positionAttribute, i + 2);\\n cb.subVectors(pC, pB);\\n ab.subVectors(pA, pB);\\n cb.cross(ab);\\n normalAttribute.setXYZ(i + 0, cb.x, cb.y, cb.z);\\n normalAttribute.setXYZ(i + 1, cb.x, cb.y, cb.z);\\n normalAttribute.setXYZ(i + 2, cb.x, cb.y, cb.z);\\n }\\n }\\n this.normalizeNormals();\\n normalAttribute.needsUpdate = true;\\n }\\n }\\n merge(geometry, offset) {\\n if (!(geometry && geometry.isBufferGeometry)) {\\n console.error(\\\\\\\"THREE.BufferGeometry.merge(): geometry not an instance of THREE.BufferGeometry.\\\\\\\", geometry);\\n return;\\n }\\n if (offset === void 0) {\\n offset = 0;\\n console.warn(\\\\\\\"THREE.BufferGeometry.merge(): Overwriting original geometry, starting at offset=0. Use BufferGeometryUtils.mergeBufferGeometries() for lossless merge.\\\\\\\");\\n }\\n const attributes = this.attributes;\\n for (const key in attributes) {\\n if (geometry.attributes[key] === void 0)\\n continue;\\n const attribute1 = attributes[key];\\n const attributeArray1 = attribute1.array;\\n const attribute2 = geometry.attributes[key];\\n const attributeArray2 = attribute2.array;\\n const attributeOffset = attribute2.itemSize * offset;\\n const length = Math.min(attributeArray2.length, attributeArray1.length - attributeOffset);\\n for (let i = 0, j = attributeOffset; i < length; i++, j++) {\\n attributeArray1[j] = attributeArray2[i];\\n }\\n }\\n return this;\\n }\\n normalizeNormals() {\\n const normals = this.attributes.normal;\\n for (let i = 0, il = normals.count; i < il; i++) {\\n _vector5.fromBufferAttribute(normals, i);\\n _vector5.normalize();\\n normals.setXYZ(i, _vector5.x, _vector5.y, _vector5.z);\\n }\\n }\\n toNonIndexed() {\\n function convertBufferAttribute(attribute, indices2) {\\n const array = attribute.array;\\n const itemSize = attribute.itemSize;\\n const normalized = attribute.normalized;\\n const array2 = new array.constructor(indices2.length * itemSize);\\n let index = 0, index2 = 0;\\n for (let i = 0, l = indices2.length; i < l; i++) {\\n if (attribute.isInterleavedBufferAttribute) {\\n index = indices2[i] * attribute.data.stride + attribute.offset;\\n } else {\\n index = indices2[i] * itemSize;\\n }\\n for (let j = 0; j < itemSize; j++) {\\n array2[index2++] = array[index++];\\n }\\n }\\n return new BufferAttribute(array2, itemSize, normalized);\\n }\\n if (this.index === null) {\\n console.warn(\\\\\\\"THREE.BufferGeometry.toNonIndexed(): BufferGeometry is already non-indexed.\\\\\\\");\\n return this;\\n }\\n const geometry2 = new BufferGeometry();\\n const indices = this.index.array;\\n const attributes = this.attributes;\\n for (const name in attributes) {\\n const attribute = attributes[name];\\n const newAttribute = convertBufferAttribute(attribute, indices);\\n geometry2.setAttribute(name, newAttribute);\\n }\\n const morphAttributes = this.morphAttributes;\\n for (const name in morphAttributes) {\\n const morphArray = [];\\n const morphAttribute = morphAttributes[name];\\n for (let i = 0, il = morphAttribute.length; i < il; i++) {\\n const attribute = morphAttribute[i];\\n const newAttribute = convertBufferAttribute(attribute, indices);\\n morphArray.push(newAttribute);\\n }\\n geometry2.morphAttributes[name] = morphArray;\\n }\\n geometry2.morphTargetsRelative = this.morphTargetsRelative;\\n const groups = this.groups;\\n for (let i = 0, l = groups.length; i < l; i++) {\\n const group = groups[i];\\n geometry2.addGroup(group.start, group.count, group.materialIndex);\\n }\\n return geometry2;\\n }\\n toJSON() {\\n const data = {\\n metadata: {\\n version: 4.5,\\n type: \\\\\\\"BufferGeometry\\\\\\\",\\n generator: \\\\\\\"BufferGeometry.toJSON\\\\\\\"\\n }\\n };\\n data.uuid = this.uuid;\\n data.type = this.type;\\n if (this.name !== \\\\\\\"\\\\\\\")\\n data.name = this.name;\\n if (Object.keys(this.userData).length > 0)\\n data.userData = this.userData;\\n if (this.parameters !== void 0) {\\n const parameters = this.parameters;\\n for (const key in parameters) {\\n if (parameters[key] !== void 0)\\n data[key] = parameters[key];\\n }\\n return data;\\n }\\n data.data = {attributes: {}};\\n const index = this.index;\\n if (index !== null) {\\n data.data.index = {\\n type: index.array.constructor.name,\\n array: Array.prototype.slice.call(index.array)\\n };\\n }\\n const attributes = this.attributes;\\n for (const key in attributes) {\\n const attribute = attributes[key];\\n data.data.attributes[key] = attribute.toJSON(data.data);\\n }\\n const morphAttributes = {};\\n let hasMorphAttributes = false;\\n for (const key in this.morphAttributes) {\\n const attributeArray = this.morphAttributes[key];\\n const array = [];\\n for (let i = 0, il = attributeArray.length; i < il; i++) {\\n const attribute = attributeArray[i];\\n array.push(attribute.toJSON(data.data));\\n }\\n if (array.length > 0) {\\n morphAttributes[key] = array;\\n hasMorphAttributes = true;\\n }\\n }\\n if (hasMorphAttributes) {\\n data.data.morphAttributes = morphAttributes;\\n data.data.morphTargetsRelative = this.morphTargetsRelative;\\n }\\n const groups = this.groups;\\n if (groups.length > 0) {\\n data.data.groups = JSON.parse(JSON.stringify(groups));\\n }\\n const boundingSphere = this.boundingSphere;\\n if (boundingSphere !== null) {\\n data.data.boundingSphere = {\\n center: boundingSphere.center.toArray(),\\n radius: boundingSphere.radius\\n };\\n }\\n return data;\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n copy(source) {\\n this.index = null;\\n this.attributes = {};\\n this.morphAttributes = {};\\n this.groups = [];\\n this.boundingBox = null;\\n this.boundingSphere = null;\\n const data = {};\\n this.name = source.name;\\n const index = source.index;\\n if (index !== null) {\\n this.setIndex(index.clone(data));\\n }\\n const attributes = source.attributes;\\n for (const name in attributes) {\\n const attribute = attributes[name];\\n this.setAttribute(name, attribute.clone(data));\\n }\\n const morphAttributes = source.morphAttributes;\\n for (const name in morphAttributes) {\\n const array = [];\\n const morphAttribute = morphAttributes[name];\\n for (let i = 0, l = morphAttribute.length; i < l; i++) {\\n array.push(morphAttribute[i].clone(data));\\n }\\n this.morphAttributes[name] = array;\\n }\\n this.morphTargetsRelative = source.morphTargetsRelative;\\n const groups = source.groups;\\n for (let i = 0, l = groups.length; i < l; i++) {\\n const group = groups[i];\\n this.addGroup(group.start, group.count, group.materialIndex);\\n }\\n const boundingBox = source.boundingBox;\\n if (boundingBox !== null) {\\n this.boundingBox = boundingBox.clone();\\n }\\n const boundingSphere = source.boundingSphere;\\n if (boundingSphere !== null) {\\n this.boundingSphere = boundingSphere.clone();\\n }\\n this.drawRange.start = source.drawRange.start;\\n this.drawRange.count = source.drawRange.count;\\n this.userData = source.userData;\\n if (source.parameters !== void 0)\\n this.parameters = Object.assign({}, source.parameters);\\n return this;\\n }\\n dispose() {\\n this.dispatchEvent({type: \\\\\\\"dispose\\\\\\\"});\\n }\\n};\\nBufferGeometry.prototype.isBufferGeometry = true;\\n\\n// ../../../node_modules/three/src/geometries/BoxGeometry.js\\nvar BoxGeometry = class extends BufferGeometry {\\n constructor(width = 1, height = 1, depth2 = 1, widthSegments = 1, heightSegments = 1, depthSegments = 1) {\\n super();\\n this.type = \\\\\\\"BoxGeometry\\\\\\\";\\n this.parameters = {\\n width,\\n height,\\n depth: depth2,\\n widthSegments,\\n heightSegments,\\n depthSegments\\n };\\n const scope = this;\\n widthSegments = Math.floor(widthSegments);\\n heightSegments = Math.floor(heightSegments);\\n depthSegments = Math.floor(depthSegments);\\n const indices = [];\\n const vertices = [];\\n const normals = [];\\n const uvs = [];\\n let numberOfVertices = 0;\\n let groupStart = 0;\\n buildPlane(\\\\\\\"z\\\\\\\", \\\\\\\"y\\\\\\\", \\\\\\\"x\\\\\\\", -1, -1, depth2, height, width, depthSegments, heightSegments, 0);\\n buildPlane(\\\\\\\"z\\\\\\\", \\\\\\\"y\\\\\\\", \\\\\\\"x\\\\\\\", 1, -1, depth2, height, -width, depthSegments, heightSegments, 1);\\n buildPlane(\\\\\\\"x\\\\\\\", \\\\\\\"z\\\\\\\", \\\\\\\"y\\\\\\\", 1, 1, width, depth2, height, widthSegments, depthSegments, 2);\\n buildPlane(\\\\\\\"x\\\\\\\", \\\\\\\"z\\\\\\\", \\\\\\\"y\\\\\\\", 1, -1, width, depth2, -height, widthSegments, depthSegments, 3);\\n buildPlane(\\\\\\\"x\\\\\\\", \\\\\\\"y\\\\\\\", \\\\\\\"z\\\\\\\", 1, -1, width, height, depth2, widthSegments, heightSegments, 4);\\n buildPlane(\\\\\\\"x\\\\\\\", \\\\\\\"y\\\\\\\", \\\\\\\"z\\\\\\\", -1, -1, width, height, -depth2, widthSegments, heightSegments, 5);\\n this.setIndex(indices);\\n this.setAttribute(\\\\\\\"position\\\\\\\", new Float32BufferAttribute(vertices, 3));\\n this.setAttribute(\\\\\\\"normal\\\\\\\", new Float32BufferAttribute(normals, 3));\\n this.setAttribute(\\\\\\\"uv\\\\\\\", new Float32BufferAttribute(uvs, 2));\\n function buildPlane(u, v, w, udir, vdir, width2, height2, depth3, gridX, gridY, materialIndex) {\\n const segmentWidth = width2 / gridX;\\n const segmentHeight = height2 / gridY;\\n const widthHalf = width2 / 2;\\n const heightHalf = height2 / 2;\\n const depthHalf = depth3 / 2;\\n const gridX1 = gridX + 1;\\n const gridY1 = gridY + 1;\\n let vertexCounter = 0;\\n let groupCount = 0;\\n const vector = new Vector3();\\n for (let iy = 0; iy < gridY1; iy++) {\\n const y = iy * segmentHeight - heightHalf;\\n for (let ix = 0; ix < gridX1; ix++) {\\n const x = ix * segmentWidth - widthHalf;\\n vector[u] = x * udir;\\n vector[v] = y * vdir;\\n vector[w] = depthHalf;\\n vertices.push(vector.x, vector.y, vector.z);\\n vector[u] = 0;\\n vector[v] = 0;\\n vector[w] = depth3 > 0 ? 1 : -1;\\n normals.push(vector.x, vector.y, vector.z);\\n uvs.push(ix / gridX);\\n uvs.push(1 - iy / gridY);\\n vertexCounter += 1;\\n }\\n }\\n for (let iy = 0; iy < gridY; iy++) {\\n for (let ix = 0; ix < gridX; ix++) {\\n const a = numberOfVertices + ix + gridX1 * iy;\\n const b = numberOfVertices + ix + gridX1 * (iy + 1);\\n const c = numberOfVertices + (ix + 1) + gridX1 * (iy + 1);\\n const d = numberOfVertices + (ix + 1) + gridX1 * iy;\\n indices.push(a, b, d);\\n indices.push(b, c, d);\\n groupCount += 6;\\n }\\n }\\n scope.addGroup(groupStart, groupCount, materialIndex);\\n groupStart += groupCount;\\n numberOfVertices += vertexCounter;\\n }\\n }\\n static fromJSON(data) {\\n return new BoxGeometry(data.width, data.height, data.depth, data.widthSegments, data.heightSegments, data.depthSegments);\\n }\\n};\\n\\n// ../../../node_modules/three/src/geometries/PlaneGeometry.js\\nvar PlaneGeometry = class extends BufferGeometry {\\n constructor(width = 1, height = 1, widthSegments = 1, heightSegments = 1) {\\n super();\\n this.type = \\\\\\\"PlaneGeometry\\\\\\\";\\n this.parameters = {\\n width,\\n height,\\n widthSegments,\\n heightSegments\\n };\\n const width_half = width / 2;\\n const height_half = height / 2;\\n const gridX = Math.floor(widthSegments);\\n const gridY = Math.floor(heightSegments);\\n const gridX1 = gridX + 1;\\n const gridY1 = gridY + 1;\\n const segment_width = width / gridX;\\n const segment_height = height / gridY;\\n const indices = [];\\n const vertices = [];\\n const normals = [];\\n const uvs = [];\\n for (let iy = 0; iy < gridY1; iy++) {\\n const y = iy * segment_height - height_half;\\n for (let ix = 0; ix < gridX1; ix++) {\\n const x = ix * segment_width - width_half;\\n vertices.push(x, -y, 0);\\n normals.push(0, 0, 1);\\n uvs.push(ix / gridX);\\n uvs.push(1 - iy / gridY);\\n }\\n }\\n for (let iy = 0; iy < gridY; iy++) {\\n for (let ix = 0; ix < gridX; ix++) {\\n const a = ix + gridX1 * iy;\\n const b = ix + gridX1 * (iy + 1);\\n const c = ix + 1 + gridX1 * (iy + 1);\\n const d = ix + 1 + gridX1 * iy;\\n indices.push(a, b, d);\\n indices.push(b, c, d);\\n }\\n }\\n this.setIndex(indices);\\n this.setAttribute(\\\\\\\"position\\\\\\\", new Float32BufferAttribute(vertices, 3));\\n this.setAttribute(\\\\\\\"normal\\\\\\\", new Float32BufferAttribute(normals, 3));\\n this.setAttribute(\\\\\\\"uv\\\\\\\", new Float32BufferAttribute(uvs, 2));\\n }\\n static fromJSON(data) {\\n return new PlaneGeometry(data.width, data.height, data.widthSegments, data.heightSegments);\\n }\\n};\\n\\n// ../../../node_modules/three/src/materials/Material.js\\nvar materialId = 0;\\nvar Material = class extends EventDispatcher {\\n constructor() {\\n super();\\n Object.defineProperty(this, \\\\\\\"id\\\\\\\", {value: materialId++});\\n this.uuid = generateUUID();\\n this.name = \\\\\\\"\\\\\\\";\\n this.type = \\\\\\\"Material\\\\\\\";\\n this.fog = true;\\n this.blending = NormalBlending;\\n this.side = FrontSide;\\n this.vertexColors = false;\\n this.opacity = 1;\\n this.format = RGBAFormat;\\n this.transparent = false;\\n this.blendSrc = SrcAlphaFactor;\\n this.blendDst = OneMinusSrcAlphaFactor;\\n this.blendEquation = AddEquation;\\n this.blendSrcAlpha = null;\\n this.blendDstAlpha = null;\\n this.blendEquationAlpha = null;\\n this.depthFunc = LessEqualDepth;\\n this.depthTest = true;\\n this.depthWrite = true;\\n this.stencilWriteMask = 255;\\n this.stencilFunc = AlwaysStencilFunc;\\n this.stencilRef = 0;\\n this.stencilFuncMask = 255;\\n this.stencilFail = KeepStencilOp;\\n this.stencilZFail = KeepStencilOp;\\n this.stencilZPass = KeepStencilOp;\\n this.stencilWrite = false;\\n this.clippingPlanes = null;\\n this.clipIntersection = false;\\n this.clipShadows = false;\\n this.shadowSide = null;\\n this.colorWrite = true;\\n this.precision = null;\\n this.polygonOffset = false;\\n this.polygonOffsetFactor = 0;\\n this.polygonOffsetUnits = 0;\\n this.dithering = false;\\n this.alphaToCoverage = false;\\n this.premultipliedAlpha = false;\\n this.visible = true;\\n this.toneMapped = true;\\n this.userData = {};\\n this.version = 0;\\n this._alphaTest = 0;\\n }\\n get alphaTest() {\\n return this._alphaTest;\\n }\\n set alphaTest(value) {\\n if (this._alphaTest > 0 !== value > 0) {\\n this.version++;\\n }\\n this._alphaTest = value;\\n }\\n onBuild() {\\n }\\n onBeforeRender() {\\n }\\n onBeforeCompile() {\\n }\\n customProgramCacheKey() {\\n return this.onBeforeCompile.toString();\\n }\\n setValues(values) {\\n if (values === void 0)\\n return;\\n for (const key in values) {\\n const newValue = values[key];\\n if (newValue === void 0) {\\n console.warn(\\\\\\\"THREE.Material: '\\\\\\\" + key + \\\\\\\"' parameter is undefined.\\\\\\\");\\n continue;\\n }\\n if (key === \\\\\\\"shading\\\\\\\") {\\n console.warn(\\\\\\\"THREE.\\\\\\\" + this.type + \\\\\\\": .shading has been removed. Use the boolean .flatShading instead.\\\\\\\");\\n this.flatShading = newValue === FlatShading ? true : false;\\n continue;\\n }\\n const currentValue = this[key];\\n if (currentValue === void 0) {\\n console.warn(\\\\\\\"THREE.\\\\\\\" + this.type + \\\\\\\": '\\\\\\\" + key + \\\\\\\"' is not a property of this material.\\\\\\\");\\n continue;\\n }\\n if (currentValue && currentValue.isColor) {\\n currentValue.set(newValue);\\n } else if (currentValue && currentValue.isVector3 && (newValue && newValue.isVector3)) {\\n currentValue.copy(newValue);\\n } else {\\n this[key] = newValue;\\n }\\n }\\n }\\n toJSON(meta) {\\n const isRoot = meta === void 0 || typeof meta === \\\\\\\"string\\\\\\\";\\n if (isRoot) {\\n meta = {\\n textures: {},\\n images: {}\\n };\\n }\\n const data = {\\n metadata: {\\n version: 4.5,\\n type: \\\\\\\"Material\\\\\\\",\\n generator: \\\\\\\"Material.toJSON\\\\\\\"\\n }\\n };\\n data.uuid = this.uuid;\\n data.type = this.type;\\n if (this.name !== \\\\\\\"\\\\\\\")\\n data.name = this.name;\\n if (this.color && this.color.isColor)\\n data.color = this.color.getHex();\\n if (this.roughness !== void 0)\\n data.roughness = this.roughness;\\n if (this.metalness !== void 0)\\n data.metalness = this.metalness;\\n if (this.sheen !== void 0)\\n data.sheen = this.sheen;\\n if (this.sheenTint && this.sheenTint.isColor)\\n data.sheenTint = this.sheenTint.getHex();\\n if (this.sheenRoughness !== void 0)\\n data.sheenRoughness = this.sheenRoughness;\\n if (this.emissive && this.emissive.isColor)\\n data.emissive = this.emissive.getHex();\\n if (this.emissiveIntensity && this.emissiveIntensity !== 1)\\n data.emissiveIntensity = this.emissiveIntensity;\\n if (this.specular && this.specular.isColor)\\n data.specular = this.specular.getHex();\\n if (this.specularIntensity !== void 0)\\n data.specularIntensity = this.specularIntensity;\\n if (this.specularTint && this.specularTint.isColor)\\n data.specularTint = this.specularTint.getHex();\\n if (this.shininess !== void 0)\\n data.shininess = this.shininess;\\n if (this.clearcoat !== void 0)\\n data.clearcoat = this.clearcoat;\\n if (this.clearcoatRoughness !== void 0)\\n data.clearcoatRoughness = this.clearcoatRoughness;\\n if (this.clearcoatMap && this.clearcoatMap.isTexture) {\\n data.clearcoatMap = this.clearcoatMap.toJSON(meta).uuid;\\n }\\n if (this.clearcoatRoughnessMap && this.clearcoatRoughnessMap.isTexture) {\\n data.clearcoatRoughnessMap = this.clearcoatRoughnessMap.toJSON(meta).uuid;\\n }\\n if (this.clearcoatNormalMap && this.clearcoatNormalMap.isTexture) {\\n data.clearcoatNormalMap = this.clearcoatNormalMap.toJSON(meta).uuid;\\n data.clearcoatNormalScale = this.clearcoatNormalScale.toArray();\\n }\\n if (this.map && this.map.isTexture)\\n data.map = this.map.toJSON(meta).uuid;\\n if (this.matcap && this.matcap.isTexture)\\n data.matcap = this.matcap.toJSON(meta).uuid;\\n if (this.alphaMap && this.alphaMap.isTexture)\\n data.alphaMap = this.alphaMap.toJSON(meta).uuid;\\n if (this.lightMap && this.lightMap.isTexture) {\\n data.lightMap = this.lightMap.toJSON(meta).uuid;\\n data.lightMapIntensity = this.lightMapIntensity;\\n }\\n if (this.aoMap && this.aoMap.isTexture) {\\n data.aoMap = this.aoMap.toJSON(meta).uuid;\\n data.aoMapIntensity = this.aoMapIntensity;\\n }\\n if (this.bumpMap && this.bumpMap.isTexture) {\\n data.bumpMap = this.bumpMap.toJSON(meta).uuid;\\n data.bumpScale = this.bumpScale;\\n }\\n if (this.normalMap && this.normalMap.isTexture) {\\n data.normalMap = this.normalMap.toJSON(meta).uuid;\\n data.normalMapType = this.normalMapType;\\n data.normalScale = this.normalScale.toArray();\\n }\\n if (this.displacementMap && this.displacementMap.isTexture) {\\n data.displacementMap = this.displacementMap.toJSON(meta).uuid;\\n data.displacementScale = this.displacementScale;\\n data.displacementBias = this.displacementBias;\\n }\\n if (this.roughnessMap && this.roughnessMap.isTexture)\\n data.roughnessMap = this.roughnessMap.toJSON(meta).uuid;\\n if (this.metalnessMap && this.metalnessMap.isTexture)\\n data.metalnessMap = this.metalnessMap.toJSON(meta).uuid;\\n if (this.emissiveMap && this.emissiveMap.isTexture)\\n data.emissiveMap = this.emissiveMap.toJSON(meta).uuid;\\n if (this.specularMap && this.specularMap.isTexture)\\n data.specularMap = this.specularMap.toJSON(meta).uuid;\\n if (this.specularIntensityMap && this.specularIntensityMap.isTexture)\\n data.specularIntensityMap = this.specularIntensityMap.toJSON(meta).uuid;\\n if (this.specularTintMap && this.specularTintMap.isTexture)\\n data.specularTintMap = this.specularTintMap.toJSON(meta).uuid;\\n if (this.envMap && this.envMap.isTexture) {\\n data.envMap = this.envMap.toJSON(meta).uuid;\\n if (this.combine !== void 0)\\n data.combine = this.combine;\\n }\\n if (this.envMapIntensity !== void 0)\\n data.envMapIntensity = this.envMapIntensity;\\n if (this.reflectivity !== void 0)\\n data.reflectivity = this.reflectivity;\\n if (this.refractionRatio !== void 0)\\n data.refractionRatio = this.refractionRatio;\\n if (this.gradientMap && this.gradientMap.isTexture) {\\n data.gradientMap = this.gradientMap.toJSON(meta).uuid;\\n }\\n if (this.transmission !== void 0)\\n data.transmission = this.transmission;\\n if (this.transmissionMap && this.transmissionMap.isTexture)\\n data.transmissionMap = this.transmissionMap.toJSON(meta).uuid;\\n if (this.thickness !== void 0)\\n data.thickness = this.thickness;\\n if (this.thicknessMap && this.thicknessMap.isTexture)\\n data.thicknessMap = this.thicknessMap.toJSON(meta).uuid;\\n if (this.attenuationDistance !== void 0)\\n data.attenuationDistance = this.attenuationDistance;\\n if (this.attenuationTint !== void 0)\\n data.attenuationTint = this.attenuationTint.getHex();\\n if (this.size !== void 0)\\n data.size = this.size;\\n if (this.shadowSide !== null)\\n data.shadowSide = this.shadowSide;\\n if (this.sizeAttenuation !== void 0)\\n data.sizeAttenuation = this.sizeAttenuation;\\n if (this.blending !== NormalBlending)\\n data.blending = this.blending;\\n if (this.side !== FrontSide)\\n data.side = this.side;\\n if (this.vertexColors)\\n data.vertexColors = true;\\n if (this.opacity < 1)\\n data.opacity = this.opacity;\\n if (this.format !== RGBAFormat)\\n data.format = this.format;\\n if (this.transparent === true)\\n data.transparent = this.transparent;\\n data.depthFunc = this.depthFunc;\\n data.depthTest = this.depthTest;\\n data.depthWrite = this.depthWrite;\\n data.colorWrite = this.colorWrite;\\n data.stencilWrite = this.stencilWrite;\\n data.stencilWriteMask = this.stencilWriteMask;\\n data.stencilFunc = this.stencilFunc;\\n data.stencilRef = this.stencilRef;\\n data.stencilFuncMask = this.stencilFuncMask;\\n data.stencilFail = this.stencilFail;\\n data.stencilZFail = this.stencilZFail;\\n data.stencilZPass = this.stencilZPass;\\n if (this.rotation && this.rotation !== 0)\\n data.rotation = this.rotation;\\n if (this.polygonOffset === true)\\n data.polygonOffset = true;\\n if (this.polygonOffsetFactor !== 0)\\n data.polygonOffsetFactor = this.polygonOffsetFactor;\\n if (this.polygonOffsetUnits !== 0)\\n data.polygonOffsetUnits = this.polygonOffsetUnits;\\n if (this.linewidth && this.linewidth !== 1)\\n data.linewidth = this.linewidth;\\n if (this.dashSize !== void 0)\\n data.dashSize = this.dashSize;\\n if (this.gapSize !== void 0)\\n data.gapSize = this.gapSize;\\n if (this.scale !== void 0)\\n data.scale = this.scale;\\n if (this.dithering === true)\\n data.dithering = true;\\n if (this.alphaTest > 0)\\n data.alphaTest = this.alphaTest;\\n if (this.alphaToCoverage === true)\\n data.alphaToCoverage = this.alphaToCoverage;\\n if (this.premultipliedAlpha === true)\\n data.premultipliedAlpha = this.premultipliedAlpha;\\n if (this.wireframe === true)\\n data.wireframe = this.wireframe;\\n if (this.wireframeLinewidth > 1)\\n data.wireframeLinewidth = this.wireframeLinewidth;\\n if (this.wireframeLinecap !== \\\\\\\"round\\\\\\\")\\n data.wireframeLinecap = this.wireframeLinecap;\\n if (this.wireframeLinejoin !== \\\\\\\"round\\\\\\\")\\n data.wireframeLinejoin = this.wireframeLinejoin;\\n if (this.flatShading === true)\\n data.flatShading = this.flatShading;\\n if (this.visible === false)\\n data.visible = false;\\n if (this.toneMapped === false)\\n data.toneMapped = false;\\n if (JSON.stringify(this.userData) !== \\\\\\\"{}\\\\\\\")\\n data.userData = this.userData;\\n function extractFromCache(cache) {\\n const values = [];\\n for (const key in cache) {\\n const data2 = cache[key];\\n delete data2.metadata;\\n values.push(data2);\\n }\\n return values;\\n }\\n if (isRoot) {\\n const textures = extractFromCache(meta.textures);\\n const images = extractFromCache(meta.images);\\n if (textures.length > 0)\\n data.textures = textures;\\n if (images.length > 0)\\n data.images = images;\\n }\\n return data;\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n copy(source) {\\n this.name = source.name;\\n this.fog = source.fog;\\n this.blending = source.blending;\\n this.side = source.side;\\n this.vertexColors = source.vertexColors;\\n this.opacity = source.opacity;\\n this.format = source.format;\\n this.transparent = source.transparent;\\n this.blendSrc = source.blendSrc;\\n this.blendDst = source.blendDst;\\n this.blendEquation = source.blendEquation;\\n this.blendSrcAlpha = source.blendSrcAlpha;\\n this.blendDstAlpha = source.blendDstAlpha;\\n this.blendEquationAlpha = source.blendEquationAlpha;\\n this.depthFunc = source.depthFunc;\\n this.depthTest = source.depthTest;\\n this.depthWrite = source.depthWrite;\\n this.stencilWriteMask = source.stencilWriteMask;\\n this.stencilFunc = source.stencilFunc;\\n this.stencilRef = source.stencilRef;\\n this.stencilFuncMask = source.stencilFuncMask;\\n this.stencilFail = source.stencilFail;\\n this.stencilZFail = source.stencilZFail;\\n this.stencilZPass = source.stencilZPass;\\n this.stencilWrite = source.stencilWrite;\\n const srcPlanes = source.clippingPlanes;\\n let dstPlanes = null;\\n if (srcPlanes !== null) {\\n const n = srcPlanes.length;\\n dstPlanes = new Array(n);\\n for (let i = 0; i !== n; ++i) {\\n dstPlanes[i] = srcPlanes[i].clone();\\n }\\n }\\n this.clippingPlanes = dstPlanes;\\n this.clipIntersection = source.clipIntersection;\\n this.clipShadows = source.clipShadows;\\n this.shadowSide = source.shadowSide;\\n this.colorWrite = source.colorWrite;\\n this.precision = source.precision;\\n this.polygonOffset = source.polygonOffset;\\n this.polygonOffsetFactor = source.polygonOffsetFactor;\\n this.polygonOffsetUnits = source.polygonOffsetUnits;\\n this.dithering = source.dithering;\\n this.alphaTest = source.alphaTest;\\n this.alphaToCoverage = source.alphaToCoverage;\\n this.premultipliedAlpha = source.premultipliedAlpha;\\n this.visible = source.visible;\\n this.toneMapped = source.toneMapped;\\n this.userData = JSON.parse(JSON.stringify(source.userData));\\n return this;\\n }\\n dispose() {\\n this.dispatchEvent({type: \\\\\\\"dispose\\\\\\\"});\\n }\\n set needsUpdate(value) {\\n if (value === true)\\n this.version++;\\n }\\n};\\nMaterial.prototype.isMaterial = true;\\n\\n// ../../../node_modules/three/src/renderers/shaders/UniformsUtils.js\\nfunction cloneUniforms(src) {\\n const dst = {};\\n for (const u in src) {\\n dst[u] = {};\\n for (const p in src[u]) {\\n const property = src[u][p];\\n if (property && (property.isColor || property.isMatrix3 || property.isMatrix4 || property.isVector2 || property.isVector3 || property.isVector4 || property.isTexture || property.isQuaternion)) {\\n dst[u][p] = property.clone();\\n } else if (Array.isArray(property)) {\\n dst[u][p] = property.slice();\\n } else {\\n dst[u][p] = property;\\n }\\n }\\n }\\n return dst;\\n}\\nfunction mergeUniforms(uniforms) {\\n const merged = {};\\n for (let u = 0; u < uniforms.length; u++) {\\n const tmp = cloneUniforms(uniforms[u]);\\n for (const p in tmp) {\\n merged[p] = tmp[p];\\n }\\n }\\n return merged;\\n}\\nvar UniformsUtils = {clone: cloneUniforms, merge: mergeUniforms};\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/default_vertex.glsl.js\\nvar default_vertex_glsl_default = `\\nvoid main() {\\n\\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/default_fragment.glsl.js\\nvar default_fragment_glsl_default = `\\nvoid main() {\\n\\tgl_FragColor = vec4( 1.0, 0.0, 0.0, 1.0 );\\n}\\n`;\\n\\n// ../../../node_modules/three/src/materials/ShaderMaterial.js\\nvar ShaderMaterial = class extends Material {\\n constructor(parameters) {\\n super();\\n this.type = \\\\\\\"ShaderMaterial\\\\\\\";\\n this.defines = {};\\n this.uniforms = {};\\n this.vertexShader = default_vertex_glsl_default;\\n this.fragmentShader = default_fragment_glsl_default;\\n this.linewidth = 1;\\n this.wireframe = false;\\n this.wireframeLinewidth = 1;\\n this.fog = false;\\n this.lights = false;\\n this.clipping = false;\\n this.extensions = {\\n derivatives: false,\\n fragDepth: false,\\n drawBuffers: false,\\n shaderTextureLOD: false\\n };\\n this.defaultAttributeValues = {\\n color: [1, 1, 1],\\n uv: [0, 0],\\n uv2: [0, 0]\\n };\\n this.index0AttributeName = void 0;\\n this.uniformsNeedUpdate = false;\\n this.glslVersion = null;\\n if (parameters !== void 0) {\\n if (parameters.attributes !== void 0) {\\n console.error(\\\\\\\"THREE.ShaderMaterial: attributes should now be defined in THREE.BufferGeometry instead.\\\\\\\");\\n }\\n this.setValues(parameters);\\n }\\n }\\n copy(source) {\\n super.copy(source);\\n this.fragmentShader = source.fragmentShader;\\n this.vertexShader = source.vertexShader;\\n this.uniforms = cloneUniforms(source.uniforms);\\n this.defines = Object.assign({}, source.defines);\\n this.wireframe = source.wireframe;\\n this.wireframeLinewidth = source.wireframeLinewidth;\\n this.lights = source.lights;\\n this.clipping = source.clipping;\\n this.extensions = Object.assign({}, source.extensions);\\n this.glslVersion = source.glslVersion;\\n return this;\\n }\\n toJSON(meta) {\\n const data = super.toJSON(meta);\\n data.glslVersion = this.glslVersion;\\n data.uniforms = {};\\n for (const name in this.uniforms) {\\n const uniform = this.uniforms[name];\\n const value = uniform.value;\\n if (value && value.isTexture) {\\n data.uniforms[name] = {\\n type: \\\\\\\"t\\\\\\\",\\n value: value.toJSON(meta).uuid\\n };\\n } else if (value && value.isColor) {\\n data.uniforms[name] = {\\n type: \\\\\\\"c\\\\\\\",\\n value: value.getHex()\\n };\\n } else if (value && value.isVector2) {\\n data.uniforms[name] = {\\n type: \\\\\\\"v2\\\\\\\",\\n value: value.toArray()\\n };\\n } else if (value && value.isVector3) {\\n data.uniforms[name] = {\\n type: \\\\\\\"v3\\\\\\\",\\n value: value.toArray()\\n };\\n } else if (value && value.isVector4) {\\n data.uniforms[name] = {\\n type: \\\\\\\"v4\\\\\\\",\\n value: value.toArray()\\n };\\n } else if (value && value.isMatrix3) {\\n data.uniforms[name] = {\\n type: \\\\\\\"m3\\\\\\\",\\n value: value.toArray()\\n };\\n } else if (value && value.isMatrix4) {\\n data.uniforms[name] = {\\n type: \\\\\\\"m4\\\\\\\",\\n value: value.toArray()\\n };\\n } else {\\n data.uniforms[name] = {\\n value\\n };\\n }\\n }\\n if (Object.keys(this.defines).length > 0)\\n data.defines = this.defines;\\n data.vertexShader = this.vertexShader;\\n data.fragmentShader = this.fragmentShader;\\n const extensions = {};\\n for (const key in this.extensions) {\\n if (this.extensions[key] === true)\\n extensions[key] = true;\\n }\\n if (Object.keys(extensions).length > 0)\\n data.extensions = extensions;\\n return data;\\n }\\n};\\nShaderMaterial.prototype.isShaderMaterial = true;\\n\\n// ../../../node_modules/three/src/math/Ray.js\\nvar _vector6 = /* @__PURE__ */ new Vector3();\\nvar _segCenter = /* @__PURE__ */ new Vector3();\\nvar _segDir = /* @__PURE__ */ new Vector3();\\nvar _diff = /* @__PURE__ */ new Vector3();\\nvar _edge1 = /* @__PURE__ */ new Vector3();\\nvar _edge2 = /* @__PURE__ */ new Vector3();\\nvar _normal = /* @__PURE__ */ new Vector3();\\nvar Ray = class {\\n constructor(origin = new Vector3(), direction = new Vector3(0, 0, -1)) {\\n this.origin = origin;\\n this.direction = direction;\\n }\\n set(origin, direction) {\\n this.origin.copy(origin);\\n this.direction.copy(direction);\\n return this;\\n }\\n copy(ray) {\\n this.origin.copy(ray.origin);\\n this.direction.copy(ray.direction);\\n return this;\\n }\\n at(t, target) {\\n return target.copy(this.direction).multiplyScalar(t).add(this.origin);\\n }\\n lookAt(v) {\\n this.direction.copy(v).sub(this.origin).normalize();\\n return this;\\n }\\n recast(t) {\\n this.origin.copy(this.at(t, _vector6));\\n return this;\\n }\\n closestPointToPoint(point, target) {\\n target.subVectors(point, this.origin);\\n const directionDistance = target.dot(this.direction);\\n if (directionDistance < 0) {\\n return target.copy(this.origin);\\n }\\n return target.copy(this.direction).multiplyScalar(directionDistance).add(this.origin);\\n }\\n distanceToPoint(point) {\\n return Math.sqrt(this.distanceSqToPoint(point));\\n }\\n distanceSqToPoint(point) {\\n const directionDistance = _vector6.subVectors(point, this.origin).dot(this.direction);\\n if (directionDistance < 0) {\\n return this.origin.distanceToSquared(point);\\n }\\n _vector6.copy(this.direction).multiplyScalar(directionDistance).add(this.origin);\\n return _vector6.distanceToSquared(point);\\n }\\n distanceSqToSegment(v0, v1, optionalPointOnRay, optionalPointOnSegment) {\\n _segCenter.copy(v0).add(v1).multiplyScalar(0.5);\\n _segDir.copy(v1).sub(v0).normalize();\\n _diff.copy(this.origin).sub(_segCenter);\\n const segExtent = v0.distanceTo(v1) * 0.5;\\n const a01 = -this.direction.dot(_segDir);\\n const b0 = _diff.dot(this.direction);\\n const b1 = -_diff.dot(_segDir);\\n const c = _diff.lengthSq();\\n const det = Math.abs(1 - a01 * a01);\\n let s0, s1, sqrDist, extDet;\\n if (det > 0) {\\n s0 = a01 * b1 - b0;\\n s1 = a01 * b0 - b1;\\n extDet = segExtent * det;\\n if (s0 >= 0) {\\n if (s1 >= -extDet) {\\n if (s1 <= extDet) {\\n const invDet = 1 / det;\\n s0 *= invDet;\\n s1 *= invDet;\\n sqrDist = s0 * (s0 + a01 * s1 + 2 * b0) + s1 * (a01 * s0 + s1 + 2 * b1) + c;\\n } else {\\n s1 = segExtent;\\n s0 = Math.max(0, -(a01 * s1 + b0));\\n sqrDist = -s0 * s0 + s1 * (s1 + 2 * b1) + c;\\n }\\n } else {\\n s1 = -segExtent;\\n s0 = Math.max(0, -(a01 * s1 + b0));\\n sqrDist = -s0 * s0 + s1 * (s1 + 2 * b1) + c;\\n }\\n } else {\\n if (s1 <= -extDet) {\\n s0 = Math.max(0, -(-a01 * segExtent + b0));\\n s1 = s0 > 0 ? -segExtent : Math.min(Math.max(-segExtent, -b1), segExtent);\\n sqrDist = -s0 * s0 + s1 * (s1 + 2 * b1) + c;\\n } else if (s1 <= extDet) {\\n s0 = 0;\\n s1 = Math.min(Math.max(-segExtent, -b1), segExtent);\\n sqrDist = s1 * (s1 + 2 * b1) + c;\\n } else {\\n s0 = Math.max(0, -(a01 * segExtent + b0));\\n s1 = s0 > 0 ? segExtent : Math.min(Math.max(-segExtent, -b1), segExtent);\\n sqrDist = -s0 * s0 + s1 * (s1 + 2 * b1) + c;\\n }\\n }\\n } else {\\n s1 = a01 > 0 ? -segExtent : segExtent;\\n s0 = Math.max(0, -(a01 * s1 + b0));\\n sqrDist = -s0 * s0 + s1 * (s1 + 2 * b1) + c;\\n }\\n if (optionalPointOnRay) {\\n optionalPointOnRay.copy(this.direction).multiplyScalar(s0).add(this.origin);\\n }\\n if (optionalPointOnSegment) {\\n optionalPointOnSegment.copy(_segDir).multiplyScalar(s1).add(_segCenter);\\n }\\n return sqrDist;\\n }\\n intersectSphere(sphere, target) {\\n _vector6.subVectors(sphere.center, this.origin);\\n const tca = _vector6.dot(this.direction);\\n const d2 = _vector6.dot(_vector6) - tca * tca;\\n const radius2 = sphere.radius * sphere.radius;\\n if (d2 > radius2)\\n return null;\\n const thc = Math.sqrt(radius2 - d2);\\n const t0 = tca - thc;\\n const t1 = tca + thc;\\n if (t0 < 0 && t1 < 0)\\n return null;\\n if (t0 < 0)\\n return this.at(t1, target);\\n return this.at(t0, target);\\n }\\n intersectsSphere(sphere) {\\n return this.distanceSqToPoint(sphere.center) <= sphere.radius * sphere.radius;\\n }\\n distanceToPlane(plane) {\\n const denominator = plane.normal.dot(this.direction);\\n if (denominator === 0) {\\n if (plane.distanceToPoint(this.origin) === 0) {\\n return 0;\\n }\\n return null;\\n }\\n const t = -(this.origin.dot(plane.normal) + plane.constant) / denominator;\\n return t >= 0 ? t : null;\\n }\\n intersectPlane(plane, target) {\\n const t = this.distanceToPlane(plane);\\n if (t === null) {\\n return null;\\n }\\n return this.at(t, target);\\n }\\n intersectsPlane(plane) {\\n const distToPoint = plane.distanceToPoint(this.origin);\\n if (distToPoint === 0) {\\n return true;\\n }\\n const denominator = plane.normal.dot(this.direction);\\n if (denominator * distToPoint < 0) {\\n return true;\\n }\\n return false;\\n }\\n intersectBox(box, target) {\\n let tmin, tmax, tymin, tymax, tzmin, tzmax;\\n const invdirx = 1 / this.direction.x, invdiry = 1 / this.direction.y, invdirz = 1 / this.direction.z;\\n const origin = this.origin;\\n if (invdirx >= 0) {\\n tmin = (box.min.x - origin.x) * invdirx;\\n tmax = (box.max.x - origin.x) * invdirx;\\n } else {\\n tmin = (box.max.x - origin.x) * invdirx;\\n tmax = (box.min.x - origin.x) * invdirx;\\n }\\n if (invdiry >= 0) {\\n tymin = (box.min.y - origin.y) * invdiry;\\n tymax = (box.max.y - origin.y) * invdiry;\\n } else {\\n tymin = (box.max.y - origin.y) * invdiry;\\n tymax = (box.min.y - origin.y) * invdiry;\\n }\\n if (tmin > tymax || tymin > tmax)\\n return null;\\n if (tymin > tmin || tmin !== tmin)\\n tmin = tymin;\\n if (tymax < tmax || tmax !== tmax)\\n tmax = tymax;\\n if (invdirz >= 0) {\\n tzmin = (box.min.z - origin.z) * invdirz;\\n tzmax = (box.max.z - origin.z) * invdirz;\\n } else {\\n tzmin = (box.max.z - origin.z) * invdirz;\\n tzmax = (box.min.z - origin.z) * invdirz;\\n }\\n if (tmin > tzmax || tzmin > tmax)\\n return null;\\n if (tzmin > tmin || tmin !== tmin)\\n tmin = tzmin;\\n if (tzmax < tmax || tmax !== tmax)\\n tmax = tzmax;\\n if (tmax < 0)\\n return null;\\n return this.at(tmin >= 0 ? tmin : tmax, target);\\n }\\n intersectsBox(box) {\\n return this.intersectBox(box, _vector6) !== null;\\n }\\n intersectTriangle(a, b, c, backfaceCulling, target) {\\n _edge1.subVectors(b, a);\\n _edge2.subVectors(c, a);\\n _normal.crossVectors(_edge1, _edge2);\\n let DdN = this.direction.dot(_normal);\\n let sign;\\n if (DdN > 0) {\\n if (backfaceCulling)\\n return null;\\n sign = 1;\\n } else if (DdN < 0) {\\n sign = -1;\\n DdN = -DdN;\\n } else {\\n return null;\\n }\\n _diff.subVectors(this.origin, a);\\n const DdQxE2 = sign * this.direction.dot(_edge2.crossVectors(_diff, _edge2));\\n if (DdQxE2 < 0) {\\n return null;\\n }\\n const DdE1xQ = sign * this.direction.dot(_edge1.cross(_diff));\\n if (DdE1xQ < 0) {\\n return null;\\n }\\n if (DdQxE2 + DdE1xQ > DdN) {\\n return null;\\n }\\n const QdN = -sign * _diff.dot(_normal);\\n if (QdN < 0) {\\n return null;\\n }\\n return this.at(QdN / DdN, target);\\n }\\n applyMatrix4(matrix4) {\\n this.origin.applyMatrix4(matrix4);\\n this.direction.transformDirection(matrix4);\\n return this;\\n }\\n equals(ray) {\\n return ray.origin.equals(this.origin) && ray.direction.equals(this.direction);\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n};\\n\\n// ../../../node_modules/three/src/math/Triangle.js\\nvar _v02 = /* @__PURE__ */ new Vector3();\\nvar _v15 = /* @__PURE__ */ new Vector3();\\nvar _v22 = /* @__PURE__ */ new Vector3();\\nvar _v3 = /* @__PURE__ */ new Vector3();\\nvar _vab = /* @__PURE__ */ new Vector3();\\nvar _vac = /* @__PURE__ */ new Vector3();\\nvar _vbc = /* @__PURE__ */ new Vector3();\\nvar _vap = /* @__PURE__ */ new Vector3();\\nvar _vbp = /* @__PURE__ */ new Vector3();\\nvar _vcp = /* @__PURE__ */ new Vector3();\\nvar Triangle = class {\\n constructor(a = new Vector3(), b = new Vector3(), c = new Vector3()) {\\n this.a = a;\\n this.b = b;\\n this.c = c;\\n }\\n static getNormal(a, b, c, target) {\\n target.subVectors(c, b);\\n _v02.subVectors(a, b);\\n target.cross(_v02);\\n const targetLengthSq = target.lengthSq();\\n if (targetLengthSq > 0) {\\n return target.multiplyScalar(1 / Math.sqrt(targetLengthSq));\\n }\\n return target.set(0, 0, 0);\\n }\\n static getBarycoord(point, a, b, c, target) {\\n _v02.subVectors(c, a);\\n _v15.subVectors(b, a);\\n _v22.subVectors(point, a);\\n const dot00 = _v02.dot(_v02);\\n const dot01 = _v02.dot(_v15);\\n const dot02 = _v02.dot(_v22);\\n const dot11 = _v15.dot(_v15);\\n const dot12 = _v15.dot(_v22);\\n const denom = dot00 * dot11 - dot01 * dot01;\\n if (denom === 0) {\\n return target.set(-2, -1, -1);\\n }\\n const invDenom = 1 / denom;\\n const u = (dot11 * dot02 - dot01 * dot12) * invDenom;\\n const v = (dot00 * dot12 - dot01 * dot02) * invDenom;\\n return target.set(1 - u - v, v, u);\\n }\\n static containsPoint(point, a, b, c) {\\n this.getBarycoord(point, a, b, c, _v3);\\n return _v3.x >= 0 && _v3.y >= 0 && _v3.x + _v3.y <= 1;\\n }\\n static getUV(point, p1, p2, p3, uv1, uv2, uv3, target) {\\n this.getBarycoord(point, p1, p2, p3, _v3);\\n target.set(0, 0);\\n target.addScaledVector(uv1, _v3.x);\\n target.addScaledVector(uv2, _v3.y);\\n target.addScaledVector(uv3, _v3.z);\\n return target;\\n }\\n static isFrontFacing(a, b, c, direction) {\\n _v02.subVectors(c, b);\\n _v15.subVectors(a, b);\\n return _v02.cross(_v15).dot(direction) < 0 ? true : false;\\n }\\n set(a, b, c) {\\n this.a.copy(a);\\n this.b.copy(b);\\n this.c.copy(c);\\n return this;\\n }\\n setFromPointsAndIndices(points2, i0, i1, i2) {\\n this.a.copy(points2[i0]);\\n this.b.copy(points2[i1]);\\n this.c.copy(points2[i2]);\\n return this;\\n }\\n setFromAttributeAndIndices(attribute, i0, i1, i2) {\\n this.a.fromBufferAttribute(attribute, i0);\\n this.b.fromBufferAttribute(attribute, i1);\\n this.c.fromBufferAttribute(attribute, i2);\\n return this;\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n copy(triangle) {\\n this.a.copy(triangle.a);\\n this.b.copy(triangle.b);\\n this.c.copy(triangle.c);\\n return this;\\n }\\n getArea() {\\n _v02.subVectors(this.c, this.b);\\n _v15.subVectors(this.a, this.b);\\n return _v02.cross(_v15).length() * 0.5;\\n }\\n getMidpoint(target) {\\n return target.addVectors(this.a, this.b).add(this.c).multiplyScalar(1 / 3);\\n }\\n getNormal(target) {\\n return Triangle.getNormal(this.a, this.b, this.c, target);\\n }\\n getPlane(target) {\\n return target.setFromCoplanarPoints(this.a, this.b, this.c);\\n }\\n getBarycoord(point, target) {\\n return Triangle.getBarycoord(point, this.a, this.b, this.c, target);\\n }\\n getUV(point, uv1, uv2, uv3, target) {\\n return Triangle.getUV(point, this.a, this.b, this.c, uv1, uv2, uv3, target);\\n }\\n containsPoint(point) {\\n return Triangle.containsPoint(point, this.a, this.b, this.c);\\n }\\n isFrontFacing(direction) {\\n return Triangle.isFrontFacing(this.a, this.b, this.c, direction);\\n }\\n intersectsBox(box) {\\n return box.intersectsTriangle(this);\\n }\\n closestPointToPoint(p, target) {\\n const a = this.a, b = this.b, c = this.c;\\n let v, w;\\n _vab.subVectors(b, a);\\n _vac.subVectors(c, a);\\n _vap.subVectors(p, a);\\n const d1 = _vab.dot(_vap);\\n const d2 = _vac.dot(_vap);\\n if (d1 <= 0 && d2 <= 0) {\\n return target.copy(a);\\n }\\n _vbp.subVectors(p, b);\\n const d3 = _vab.dot(_vbp);\\n const d4 = _vac.dot(_vbp);\\n if (d3 >= 0 && d4 <= d3) {\\n return target.copy(b);\\n }\\n const vc = d1 * d4 - d3 * d2;\\n if (vc <= 0 && d1 >= 0 && d3 <= 0) {\\n v = d1 / (d1 - d3);\\n return target.copy(a).addScaledVector(_vab, v);\\n }\\n _vcp.subVectors(p, c);\\n const d5 = _vab.dot(_vcp);\\n const d6 = _vac.dot(_vcp);\\n if (d6 >= 0 && d5 <= d6) {\\n return target.copy(c);\\n }\\n const vb = d5 * d2 - d1 * d6;\\n if (vb <= 0 && d2 >= 0 && d6 <= 0) {\\n w = d2 / (d2 - d6);\\n return target.copy(a).addScaledVector(_vac, w);\\n }\\n const va = d3 * d6 - d5 * d4;\\n if (va <= 0 && d4 - d3 >= 0 && d5 - d6 >= 0) {\\n _vbc.subVectors(c, b);\\n w = (d4 - d3) / (d4 - d3 + (d5 - d6));\\n return target.copy(b).addScaledVector(_vbc, w);\\n }\\n const denom = 1 / (va + vb + vc);\\n v = vb * denom;\\n w = vc * denom;\\n return target.copy(a).addScaledVector(_vab, v).addScaledVector(_vac, w);\\n }\\n equals(triangle) {\\n return triangle.a.equals(this.a) && triangle.b.equals(this.b) && triangle.c.equals(this.c);\\n }\\n};\\n\\n// ../../../node_modules/three/src/materials/MeshBasicMaterial.js\\nvar MeshBasicMaterial = class extends Material {\\n constructor(parameters) {\\n super();\\n this.type = \\\\\\\"MeshBasicMaterial\\\\\\\";\\n this.color = new Color(16777215);\\n this.map = null;\\n this.lightMap = null;\\n this.lightMapIntensity = 1;\\n this.aoMap = null;\\n this.aoMapIntensity = 1;\\n this.specularMap = null;\\n this.alphaMap = null;\\n this.envMap = null;\\n this.combine = MultiplyOperation;\\n this.reflectivity = 1;\\n this.refractionRatio = 0.98;\\n this.wireframe = false;\\n this.wireframeLinewidth = 1;\\n this.wireframeLinecap = \\\\\\\"round\\\\\\\";\\n this.wireframeLinejoin = \\\\\\\"round\\\\\\\";\\n this.setValues(parameters);\\n }\\n copy(source) {\\n super.copy(source);\\n this.color.copy(source.color);\\n this.map = source.map;\\n this.lightMap = source.lightMap;\\n this.lightMapIntensity = source.lightMapIntensity;\\n this.aoMap = source.aoMap;\\n this.aoMapIntensity = source.aoMapIntensity;\\n this.specularMap = source.specularMap;\\n this.alphaMap = source.alphaMap;\\n this.envMap = source.envMap;\\n this.combine = source.combine;\\n this.reflectivity = source.reflectivity;\\n this.refractionRatio = source.refractionRatio;\\n this.wireframe = source.wireframe;\\n this.wireframeLinewidth = source.wireframeLinewidth;\\n this.wireframeLinecap = source.wireframeLinecap;\\n this.wireframeLinejoin = source.wireframeLinejoin;\\n return this;\\n }\\n};\\nMeshBasicMaterial.prototype.isMeshBasicMaterial = true;\\n\\n// ../../../node_modules/three/src/objects/Mesh.js\\nvar _inverseMatrix = /* @__PURE__ */ new Matrix4();\\nvar _ray = /* @__PURE__ */ new Ray();\\nvar _sphere2 = /* @__PURE__ */ new Sphere();\\nvar _vA = /* @__PURE__ */ new Vector3();\\nvar _vB = /* @__PURE__ */ new Vector3();\\nvar _vC = /* @__PURE__ */ new Vector3();\\nvar _tempA = /* @__PURE__ */ new Vector3();\\nvar _tempB = /* @__PURE__ */ new Vector3();\\nvar _tempC = /* @__PURE__ */ new Vector3();\\nvar _morphA = /* @__PURE__ */ new Vector3();\\nvar _morphB = /* @__PURE__ */ new Vector3();\\nvar _morphC = /* @__PURE__ */ new Vector3();\\nvar _uvA = /* @__PURE__ */ new Vector2();\\nvar _uvB = /* @__PURE__ */ new Vector2();\\nvar _uvC = /* @__PURE__ */ new Vector2();\\nvar _intersectionPoint = /* @__PURE__ */ new Vector3();\\nvar _intersectionPointWorld = /* @__PURE__ */ new Vector3();\\nvar Mesh = class extends Object3D {\\n constructor(geometry = new BufferGeometry(), material = new MeshBasicMaterial()) {\\n super();\\n this.type = \\\\\\\"Mesh\\\\\\\";\\n this.geometry = geometry;\\n this.material = material;\\n this.updateMorphTargets();\\n }\\n copy(source) {\\n super.copy(source);\\n if (source.morphTargetInfluences !== void 0) {\\n this.morphTargetInfluences = source.morphTargetInfluences.slice();\\n }\\n if (source.morphTargetDictionary !== void 0) {\\n this.morphTargetDictionary = Object.assign({}, source.morphTargetDictionary);\\n }\\n this.material = source.material;\\n this.geometry = source.geometry;\\n return this;\\n }\\n updateMorphTargets() {\\n const geometry = this.geometry;\\n if (geometry.isBufferGeometry) {\\n const morphAttributes = geometry.morphAttributes;\\n const keys = Object.keys(morphAttributes);\\n if (keys.length > 0) {\\n const morphAttribute = morphAttributes[keys[0]];\\n if (morphAttribute !== void 0) {\\n this.morphTargetInfluences = [];\\n this.morphTargetDictionary = {};\\n for (let m = 0, ml = morphAttribute.length; m < ml; m++) {\\n const name = morphAttribute[m].name || String(m);\\n this.morphTargetInfluences.push(0);\\n this.morphTargetDictionary[name] = m;\\n }\\n }\\n }\\n } else {\\n const morphTargets = geometry.morphTargets;\\n if (morphTargets !== void 0 && morphTargets.length > 0) {\\n console.error(\\\\\\\"THREE.Mesh.updateMorphTargets() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\");\\n }\\n }\\n }\\n raycast(raycaster, intersects) {\\n const geometry = this.geometry;\\n const material = this.material;\\n const matrixWorld = this.matrixWorld;\\n if (material === void 0)\\n return;\\n if (geometry.boundingSphere === null)\\n geometry.computeBoundingSphere();\\n _sphere2.copy(geometry.boundingSphere);\\n _sphere2.applyMatrix4(matrixWorld);\\n if (raycaster.ray.intersectsSphere(_sphere2) === false)\\n return;\\n _inverseMatrix.copy(matrixWorld).invert();\\n _ray.copy(raycaster.ray).applyMatrix4(_inverseMatrix);\\n if (geometry.boundingBox !== null) {\\n if (_ray.intersectsBox(geometry.boundingBox) === false)\\n return;\\n }\\n let intersection;\\n if (geometry.isBufferGeometry) {\\n const index = geometry.index;\\n const position = geometry.attributes.position;\\n const morphPosition = geometry.morphAttributes.position;\\n const morphTargetsRelative = geometry.morphTargetsRelative;\\n const uv = geometry.attributes.uv;\\n const uv2 = geometry.attributes.uv2;\\n const groups = geometry.groups;\\n const drawRange = geometry.drawRange;\\n if (index !== null) {\\n if (Array.isArray(material)) {\\n for (let i = 0, il = groups.length; i < il; i++) {\\n const group = groups[i];\\n const groupMaterial = material[group.materialIndex];\\n const start = Math.max(group.start, drawRange.start);\\n const end = Math.min(index.count, Math.min(group.start + group.count, drawRange.start + drawRange.count));\\n for (let j = start, jl = end; j < jl; j += 3) {\\n const a = index.getX(j);\\n const b = index.getX(j + 1);\\n const c = index.getX(j + 2);\\n intersection = checkBufferGeometryIntersection(this, groupMaterial, raycaster, _ray, position, morphPosition, morphTargetsRelative, uv, uv2, a, b, c);\\n if (intersection) {\\n intersection.faceIndex = Math.floor(j / 3);\\n intersection.face.materialIndex = group.materialIndex;\\n intersects.push(intersection);\\n }\\n }\\n }\\n } else {\\n const start = Math.max(0, drawRange.start);\\n const end = Math.min(index.count, drawRange.start + drawRange.count);\\n for (let i = start, il = end; i < il; i += 3) {\\n const a = index.getX(i);\\n const b = index.getX(i + 1);\\n const c = index.getX(i + 2);\\n intersection = checkBufferGeometryIntersection(this, material, raycaster, _ray, position, morphPosition, morphTargetsRelative, uv, uv2, a, b, c);\\n if (intersection) {\\n intersection.faceIndex = Math.floor(i / 3);\\n intersects.push(intersection);\\n }\\n }\\n }\\n } else if (position !== void 0) {\\n if (Array.isArray(material)) {\\n for (let i = 0, il = groups.length; i < il; i++) {\\n const group = groups[i];\\n const groupMaterial = material[group.materialIndex];\\n const start = Math.max(group.start, drawRange.start);\\n const end = Math.min(position.count, Math.min(group.start + group.count, drawRange.start + drawRange.count));\\n for (let j = start, jl = end; j < jl; j += 3) {\\n const a = j;\\n const b = j + 1;\\n const c = j + 2;\\n intersection = checkBufferGeometryIntersection(this, groupMaterial, raycaster, _ray, position, morphPosition, morphTargetsRelative, uv, uv2, a, b, c);\\n if (intersection) {\\n intersection.faceIndex = Math.floor(j / 3);\\n intersection.face.materialIndex = group.materialIndex;\\n intersects.push(intersection);\\n }\\n }\\n }\\n } else {\\n const start = Math.max(0, drawRange.start);\\n const end = Math.min(position.count, drawRange.start + drawRange.count);\\n for (let i = start, il = end; i < il; i += 3) {\\n const a = i;\\n const b = i + 1;\\n const c = i + 2;\\n intersection = checkBufferGeometryIntersection(this, material, raycaster, _ray, position, morphPosition, morphTargetsRelative, uv, uv2, a, b, c);\\n if (intersection) {\\n intersection.faceIndex = Math.floor(i / 3);\\n intersects.push(intersection);\\n }\\n }\\n }\\n }\\n } else if (geometry.isGeometry) {\\n console.error(\\\\\\\"THREE.Mesh.raycast() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\");\\n }\\n }\\n};\\nMesh.prototype.isMesh = true;\\nfunction checkIntersection(object, material, raycaster, ray, pA, pB, pC, point) {\\n let intersect;\\n if (material.side === BackSide) {\\n intersect = ray.intersectTriangle(pC, pB, pA, true, point);\\n } else {\\n intersect = ray.intersectTriangle(pA, pB, pC, material.side !== DoubleSide, point);\\n }\\n if (intersect === null)\\n return null;\\n _intersectionPointWorld.copy(point);\\n _intersectionPointWorld.applyMatrix4(object.matrixWorld);\\n const distance = raycaster.ray.origin.distanceTo(_intersectionPointWorld);\\n if (distance < raycaster.near || distance > raycaster.far)\\n return null;\\n return {\\n distance,\\n point: _intersectionPointWorld.clone(),\\n object\\n };\\n}\\nfunction checkBufferGeometryIntersection(object, material, raycaster, ray, position, morphPosition, morphTargetsRelative, uv, uv2, a, b, c) {\\n _vA.fromBufferAttribute(position, a);\\n _vB.fromBufferAttribute(position, b);\\n _vC.fromBufferAttribute(position, c);\\n const morphInfluences = object.morphTargetInfluences;\\n if (morphPosition && morphInfluences) {\\n _morphA.set(0, 0, 0);\\n _morphB.set(0, 0, 0);\\n _morphC.set(0, 0, 0);\\n for (let i = 0, il = morphPosition.length; i < il; i++) {\\n const influence = morphInfluences[i];\\n const morphAttribute = morphPosition[i];\\n if (influence === 0)\\n continue;\\n _tempA.fromBufferAttribute(morphAttribute, a);\\n _tempB.fromBufferAttribute(morphAttribute, b);\\n _tempC.fromBufferAttribute(morphAttribute, c);\\n if (morphTargetsRelative) {\\n _morphA.addScaledVector(_tempA, influence);\\n _morphB.addScaledVector(_tempB, influence);\\n _morphC.addScaledVector(_tempC, influence);\\n } else {\\n _morphA.addScaledVector(_tempA.sub(_vA), influence);\\n _morphB.addScaledVector(_tempB.sub(_vB), influence);\\n _morphC.addScaledVector(_tempC.sub(_vC), influence);\\n }\\n }\\n _vA.add(_morphA);\\n _vB.add(_morphB);\\n _vC.add(_morphC);\\n }\\n if (object.isSkinnedMesh) {\\n object.boneTransform(a, _vA);\\n object.boneTransform(b, _vB);\\n object.boneTransform(c, _vC);\\n }\\n const intersection = checkIntersection(object, material, raycaster, ray, _vA, _vB, _vC, _intersectionPoint);\\n if (intersection) {\\n if (uv) {\\n _uvA.fromBufferAttribute(uv, a);\\n _uvB.fromBufferAttribute(uv, b);\\n _uvC.fromBufferAttribute(uv, c);\\n intersection.uv = Triangle.getUV(_intersectionPoint, _vA, _vB, _vC, _uvA, _uvB, _uvC, new Vector2());\\n }\\n if (uv2) {\\n _uvA.fromBufferAttribute(uv2, a);\\n _uvB.fromBufferAttribute(uv2, b);\\n _uvC.fromBufferAttribute(uv2, c);\\n intersection.uv2 = Triangle.getUV(_intersectionPoint, _vA, _vB, _vC, _uvA, _uvB, _uvC, new Vector2());\\n }\\n const face = {\\n a,\\n b,\\n c,\\n normal: new Vector3(),\\n materialIndex: 0\\n };\\n Triangle.getNormal(_vA, _vB, _vC, face.normal);\\n intersection.face = face;\\n }\\n return intersection;\\n}\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/alphamap_fragment.glsl.js\\nvar alphamap_fragment_glsl_default = `\\n#ifdef USE_ALPHAMAP\\n\\n\\tdiffuseColor.a *= texture2D( alphaMap, vUv ).g;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/alphamap_pars_fragment.glsl.js\\nvar alphamap_pars_fragment_glsl_default = `\\n#ifdef USE_ALPHAMAP\\n\\n\\tuniform sampler2D alphaMap;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/alphatest_fragment.glsl.js\\nvar alphatest_fragment_glsl_default = `\\n#ifdef USE_ALPHATEST\\n\\n\\tif ( diffuseColor.a < alphaTest ) discard;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/alphatest_pars_fragment.glsl.js\\nvar alphatest_pars_fragment_glsl_default = `\\n#ifdef USE_ALPHATEST\\n\\tuniform float alphaTest;\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/aomap_fragment.glsl.js\\nvar aomap_fragment_glsl_default = `\\n#ifdef USE_AOMAP\\n\\n\\t// reads channel R, compatible with a combined OcclusionRoughnessMetallic (RGB) texture\\n\\tfloat ambientOcclusion = ( texture2D( aoMap, vUv2 ).r - 1.0 ) * aoMapIntensity + 1.0;\\n\\n\\treflectedLight.indirectDiffuse *= ambientOcclusion;\\n\\n\\t#if defined( USE_ENVMAP ) && defined( STANDARD )\\n\\n\\t\\tfloat dotNV = saturate( dot( geometry.normal, geometry.viewDir ) );\\n\\n\\t\\treflectedLight.indirectSpecular *= computeSpecularOcclusion( dotNV, ambientOcclusion, material.roughness );\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/aomap_pars_fragment.glsl.js\\nvar aomap_pars_fragment_glsl_default = `\\n#ifdef USE_AOMAP\\n\\n\\tuniform sampler2D aoMap;\\n\\tuniform float aoMapIntensity;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/begin_vertex.glsl.js\\nvar begin_vertex_glsl_default = `\\nvec3 transformed = vec3( position );\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/beginnormal_vertex.glsl.js\\nvar beginnormal_vertex_glsl_default = `\\nvec3 objectNormal = vec3( normal );\\n\\n#ifdef USE_TANGENT\\n\\n\\tvec3 objectTangent = vec3( tangent.xyz );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/bsdfs.glsl.js\\nvar bsdfs_glsl_default = `\\n\\nvec3 BRDF_Lambert( const in vec3 diffuseColor ) {\\n\\n\\treturn RECIPROCAL_PI * diffuseColor;\\n\\n} // validated\\n\\nvec3 F_Schlick( const in vec3 f0, const in float f90, const in float dotVH ) {\\n\\n\\t// Original approximation by Christophe Schlick '94\\n\\t// float fresnel = pow( 1.0 - dotVH, 5.0 );\\n\\n\\t// Optimized variant (presented by Epic at SIGGRAPH '13)\\n\\t// https://cdn2.unrealengine.com/Resources/files/2013SiggraphPresentationsNotes-26915738.pdf\\n\\tfloat fresnel = exp2( ( - 5.55473 * dotVH - 6.98316 ) * dotVH );\\n\\n\\treturn f0 * ( 1.0 - fresnel ) + ( f90 * fresnel );\\n\\n} // validated\\n\\n// Moving Frostbite to Physically Based Rendering 3.0 - page 12, listing 2\\n// https://seblagarde.files.wordpress.com/2015/07/course_notes_moving_frostbite_to_pbr_v32.pdf\\nfloat V_GGX_SmithCorrelated( const in float alpha, const in float dotNL, const in float dotNV ) {\\n\\n\\tfloat a2 = pow2( alpha );\\n\\n\\tfloat gv = dotNL * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNV ) );\\n\\tfloat gl = dotNV * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNL ) );\\n\\n\\treturn 0.5 / max( gv + gl, EPSILON );\\n\\n}\\n\\n// Microfacet Models for Refraction through Rough Surfaces - equation (33)\\n// http://graphicrants.blogspot.com/2013/08/specular-brdf-reference.html\\n// alpha is \\\\\\\"roughness squared\\\\\\\" in Disney\\\\u2019s reparameterization\\nfloat D_GGX( const in float alpha, const in float dotNH ) {\\n\\n\\tfloat a2 = pow2( alpha );\\n\\n\\tfloat denom = pow2( dotNH ) * ( a2 - 1.0 ) + 1.0; // avoid alpha = 0 with dotNH = 1\\n\\n\\treturn RECIPROCAL_PI * a2 / pow2( denom );\\n\\n}\\n\\n// GGX Distribution, Schlick Fresnel, GGX_SmithCorrelated Visibility\\nvec3 BRDF_GGX( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in vec3 f0, const in float f90, const in float roughness ) {\\n\\n\\tfloat alpha = pow2( roughness ); // UE4's roughness\\n\\n\\tvec3 halfDir = normalize( lightDir + viewDir );\\n\\n\\tfloat dotNL = saturate( dot( normal, lightDir ) );\\n\\tfloat dotNV = saturate( dot( normal, viewDir ) );\\n\\tfloat dotNH = saturate( dot( normal, halfDir ) );\\n\\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\\n\\n\\tvec3 F = F_Schlick( f0, f90, dotVH );\\n\\n\\tfloat V = V_GGX_SmithCorrelated( alpha, dotNL, dotNV );\\n\\n\\tfloat D = D_GGX( alpha, dotNH );\\n\\n\\treturn F * ( V * D );\\n\\n}\\n\\n// Rect Area Light\\n\\n// Real-Time Polygonal-Light Shading with Linearly Transformed Cosines\\n// by Eric Heitz, Jonathan Dupuy, Stephen Hill and David Neubelt\\n// code: https://github.com/selfshadow/ltc_code/\\n\\nvec2 LTC_Uv( const in vec3 N, const in vec3 V, const in float roughness ) {\\n\\n\\tconst float LUT_SIZE = 64.0;\\n\\tconst float LUT_SCALE = ( LUT_SIZE - 1.0 ) / LUT_SIZE;\\n\\tconst float LUT_BIAS = 0.5 / LUT_SIZE;\\n\\n\\tfloat dotNV = saturate( dot( N, V ) );\\n\\n\\t// texture parameterized by sqrt( GGX alpha ) and sqrt( 1 - cos( theta ) )\\n\\tvec2 uv = vec2( roughness, sqrt( 1.0 - dotNV ) );\\n\\n\\tuv = uv * LUT_SCALE + LUT_BIAS;\\n\\n\\treturn uv;\\n\\n}\\n\\nfloat LTC_ClippedSphereFormFactor( const in vec3 f ) {\\n\\n\\t// Real-Time Area Lighting: a Journey from Research to Production (p.102)\\n\\t// An approximation of the form factor of a horizon-clipped rectangle.\\n\\n\\tfloat l = length( f );\\n\\n\\treturn max( ( l * l + f.z ) / ( l + 1.0 ), 0.0 );\\n\\n}\\n\\nvec3 LTC_EdgeVectorFormFactor( const in vec3 v1, const in vec3 v2 ) {\\n\\n\\tfloat x = dot( v1, v2 );\\n\\n\\tfloat y = abs( x );\\n\\n\\t// rational polynomial approximation to theta / sin( theta ) / 2PI\\n\\tfloat a = 0.8543985 + ( 0.4965155 + 0.0145206 * y ) * y;\\n\\tfloat b = 3.4175940 + ( 4.1616724 + y ) * y;\\n\\tfloat v = a / b;\\n\\n\\tfloat theta_sintheta = ( x > 0.0 ) ? v : 0.5 * inversesqrt( max( 1.0 - x * x, 1e-7 ) ) - v;\\n\\n\\treturn cross( v1, v2 ) * theta_sintheta;\\n\\n}\\n\\nvec3 LTC_Evaluate( const in vec3 N, const in vec3 V, const in vec3 P, const in mat3 mInv, const in vec3 rectCoords[ 4 ] ) {\\n\\n\\t// bail if point is on back side of plane of light\\n\\t// assumes ccw winding order of light vertices\\n\\tvec3 v1 = rectCoords[ 1 ] - rectCoords[ 0 ];\\n\\tvec3 v2 = rectCoords[ 3 ] - rectCoords[ 0 ];\\n\\tvec3 lightNormal = cross( v1, v2 );\\n\\n\\tif( dot( lightNormal, P - rectCoords[ 0 ] ) < 0.0 ) return vec3( 0.0 );\\n\\n\\t// construct orthonormal basis around N\\n\\tvec3 T1, T2;\\n\\tT1 = normalize( V - N * dot( V, N ) );\\n\\tT2 = - cross( N, T1 ); // negated from paper; possibly due to a different handedness of world coordinate system\\n\\n\\t// compute transform\\n\\tmat3 mat = mInv * transposeMat3( mat3( T1, T2, N ) );\\n\\n\\t// transform rect\\n\\tvec3 coords[ 4 ];\\n\\tcoords[ 0 ] = mat * ( rectCoords[ 0 ] - P );\\n\\tcoords[ 1 ] = mat * ( rectCoords[ 1 ] - P );\\n\\tcoords[ 2 ] = mat * ( rectCoords[ 2 ] - P );\\n\\tcoords[ 3 ] = mat * ( rectCoords[ 3 ] - P );\\n\\n\\t// project rect onto sphere\\n\\tcoords[ 0 ] = normalize( coords[ 0 ] );\\n\\tcoords[ 1 ] = normalize( coords[ 1 ] );\\n\\tcoords[ 2 ] = normalize( coords[ 2 ] );\\n\\tcoords[ 3 ] = normalize( coords[ 3 ] );\\n\\n\\t// calculate vector form factor\\n\\tvec3 vectorFormFactor = vec3( 0.0 );\\n\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 0 ], coords[ 1 ] );\\n\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 1 ], coords[ 2 ] );\\n\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 2 ], coords[ 3 ] );\\n\\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 3 ], coords[ 0 ] );\\n\\n\\t// adjust for horizon clipping\\n\\tfloat result = LTC_ClippedSphereFormFactor( vectorFormFactor );\\n\\n/*\\n\\t// alternate method of adjusting for horizon clipping (see referece)\\n\\t// refactoring required\\n\\tfloat len = length( vectorFormFactor );\\n\\tfloat z = vectorFormFactor.z / len;\\n\\n\\tconst float LUT_SIZE = 64.0;\\n\\tconst float LUT_SCALE = ( LUT_SIZE - 1.0 ) / LUT_SIZE;\\n\\tconst float LUT_BIAS = 0.5 / LUT_SIZE;\\n\\n\\t// tabulated horizon-clipped sphere, apparently...\\n\\tvec2 uv = vec2( z * 0.5 + 0.5, len );\\n\\tuv = uv * LUT_SCALE + LUT_BIAS;\\n\\n\\tfloat scale = texture2D( ltc_2, uv ).w;\\n\\n\\tfloat result = len * scale;\\n*/\\n\\n\\treturn vec3( result );\\n\\n}\\n\\n// End Rect Area Light\\n\\n\\nfloat G_BlinnPhong_Implicit( /* const in float dotNL, const in float dotNV */ ) {\\n\\n\\t// geometry term is (n dot l)(n dot v) / 4(n dot l)(n dot v)\\n\\treturn 0.25;\\n\\n}\\n\\nfloat D_BlinnPhong( const in float shininess, const in float dotNH ) {\\n\\n\\treturn RECIPROCAL_PI * ( shininess * 0.5 + 1.0 ) * pow( dotNH, shininess );\\n\\n}\\n\\nvec3 BRDF_BlinnPhong( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in vec3 specularColor, const in float shininess ) {\\n\\n\\tvec3 halfDir = normalize( lightDir + viewDir );\\n\\n\\tfloat dotNH = saturate( dot( normal, halfDir ) );\\n\\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\\n\\n\\tvec3 F = F_Schlick( specularColor, 1.0, dotVH );\\n\\n\\tfloat G = G_BlinnPhong_Implicit( /* dotNL, dotNV */ );\\n\\n\\tfloat D = D_BlinnPhong( shininess, dotNH );\\n\\n\\treturn F * ( G * D );\\n\\n} // validated\\n\\n#if defined( USE_SHEEN )\\n\\n// https://github.com/google/filament/blob/master/shaders/src/brdf.fs\\nfloat D_Charlie( float roughness, float dotNH ) {\\n\\n\\tfloat alpha = pow2( roughness );\\n\\n\\t// Estevez and Kulla 2017, \\\\\\\"Production Friendly Microfacet Sheen BRDF\\\\\\\"\\n\\tfloat invAlpha = 1.0 / alpha;\\n\\tfloat cos2h = dotNH * dotNH;\\n\\tfloat sin2h = max( 1.0 - cos2h, 0.0078125 ); // 2^(-14/2), so sin2h^2 > 0 in fp16\\n\\n\\treturn ( 2.0 + invAlpha ) * pow( sin2h, invAlpha * 0.5 ) / ( 2.0 * PI );\\n\\n}\\n\\n// https://github.com/google/filament/blob/master/shaders/src/brdf.fs\\nfloat V_Neubelt( float dotNV, float dotNL ) {\\n\\n\\t// Neubelt and Pettineo 2013, \\\\\\\"Crafting a Next-gen Material Pipeline for The Order: 1886\\\\\\\"\\n\\treturn saturate( 1.0 / ( 4.0 * ( dotNL + dotNV - dotNL * dotNV ) ) );\\n\\n}\\n\\nvec3 BRDF_Sheen( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, vec3 sheenTint, const in float sheenRoughness ) {\\n\\n\\tvec3 halfDir = normalize( lightDir + viewDir );\\n\\n\\tfloat dotNL = saturate( dot( normal, lightDir ) );\\n\\tfloat dotNV = saturate( dot( normal, viewDir ) );\\n\\tfloat dotNH = saturate( dot( normal, halfDir ) );\\n\\n\\tfloat D = D_Charlie( sheenRoughness, dotNH );\\n\\tfloat V = V_Neubelt( dotNV, dotNL );\\n\\n\\treturn sheenTint * ( D * V );\\n\\n}\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/bumpmap_pars_fragment.glsl.js\\nvar bumpmap_pars_fragment_glsl_default = `\\n#ifdef USE_BUMPMAP\\n\\n\\tuniform sampler2D bumpMap;\\n\\tuniform float bumpScale;\\n\\n\\t// Bump Mapping Unparametrized Surfaces on the GPU by Morten S. Mikkelsen\\n\\t// http://api.unrealengine.com/attachments/Engine/Rendering/LightingAndShadows/BumpMappingWithoutTangentSpace/mm_sfgrad_bump.pdf\\n\\n\\t// Evaluate the derivative of the height w.r.t. screen-space using forward differencing (listing 2)\\n\\n\\tvec2 dHdxy_fwd() {\\n\\n\\t\\tvec2 dSTdx = dFdx( vUv );\\n\\t\\tvec2 dSTdy = dFdy( vUv );\\n\\n\\t\\tfloat Hll = bumpScale * texture2D( bumpMap, vUv ).x;\\n\\t\\tfloat dBx = bumpScale * texture2D( bumpMap, vUv + dSTdx ).x - Hll;\\n\\t\\tfloat dBy = bumpScale * texture2D( bumpMap, vUv + dSTdy ).x - Hll;\\n\\n\\t\\treturn vec2( dBx, dBy );\\n\\n\\t}\\n\\n\\tvec3 perturbNormalArb( vec3 surf_pos, vec3 surf_norm, vec2 dHdxy, float faceDirection ) {\\n\\n\\t\\t// Workaround for Adreno 3XX dFd*( vec3 ) bug. See #9988\\n\\n\\t\\tvec3 vSigmaX = vec3( dFdx( surf_pos.x ), dFdx( surf_pos.y ), dFdx( surf_pos.z ) );\\n\\t\\tvec3 vSigmaY = vec3( dFdy( surf_pos.x ), dFdy( surf_pos.y ), dFdy( surf_pos.z ) );\\n\\t\\tvec3 vN = surf_norm;\\t\\t// normalized\\n\\n\\t\\tvec3 R1 = cross( vSigmaY, vN );\\n\\t\\tvec3 R2 = cross( vN, vSigmaX );\\n\\n\\t\\tfloat fDet = dot( vSigmaX, R1 ) * faceDirection;\\n\\n\\t\\tvec3 vGrad = sign( fDet ) * ( dHdxy.x * R1 + dHdxy.y * R2 );\\n\\t\\treturn normalize( abs( fDet ) * surf_norm - vGrad );\\n\\n\\t}\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/clipping_planes_fragment.glsl.js\\nvar clipping_planes_fragment_glsl_default = `\\n#if NUM_CLIPPING_PLANES > 0\\n\\n\\tvec4 plane;\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < UNION_CLIPPING_PLANES; i ++ ) {\\n\\n\\t\\tplane = clippingPlanes[ i ];\\n\\t\\tif ( dot( vClipPosition, plane.xyz ) > plane.w ) discard;\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n\\t#if UNION_CLIPPING_PLANES < NUM_CLIPPING_PLANES\\n\\n\\t\\tbool clipped = true;\\n\\n\\t\\t#pragma unroll_loop_start\\n\\t\\tfor ( int i = UNION_CLIPPING_PLANES; i < NUM_CLIPPING_PLANES; i ++ ) {\\n\\n\\t\\t\\tplane = clippingPlanes[ i ];\\n\\t\\t\\tclipped = ( dot( vClipPosition, plane.xyz ) > plane.w ) && clipped;\\n\\n\\t\\t}\\n\\t\\t#pragma unroll_loop_end\\n\\n\\t\\tif ( clipped ) discard;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/clipping_planes_pars_fragment.glsl.js\\nvar clipping_planes_pars_fragment_glsl_default = `\\n#if NUM_CLIPPING_PLANES > 0\\n\\n\\tvarying vec3 vClipPosition;\\n\\n\\tuniform vec4 clippingPlanes[ NUM_CLIPPING_PLANES ];\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/clipping_planes_pars_vertex.glsl.js\\nvar clipping_planes_pars_vertex_glsl_default = `\\n#if NUM_CLIPPING_PLANES > 0\\n\\n\\tvarying vec3 vClipPosition;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/clipping_planes_vertex.glsl.js\\nvar clipping_planes_vertex_glsl_default = `\\n#if NUM_CLIPPING_PLANES > 0\\n\\n\\tvClipPosition = - mvPosition.xyz;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/color_fragment.glsl.js\\nvar color_fragment_glsl_default = `\\n#if defined( USE_COLOR_ALPHA )\\n\\n\\tdiffuseColor *= vColor;\\n\\n#elif defined( USE_COLOR )\\n\\n\\tdiffuseColor.rgb *= vColor;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/color_pars_fragment.glsl.js\\nvar color_pars_fragment_glsl_default = `\\n#if defined( USE_COLOR_ALPHA )\\n\\n\\tvarying vec4 vColor;\\n\\n#elif defined( USE_COLOR )\\n\\n\\tvarying vec3 vColor;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/color_pars_vertex.glsl.js\\nvar color_pars_vertex_glsl_default = `\\n#if defined( USE_COLOR_ALPHA )\\n\\n\\tvarying vec4 vColor;\\n\\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )\\n\\n\\tvarying vec3 vColor;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/color_vertex.glsl.js\\nvar color_vertex_glsl_default = `\\n#if defined( USE_COLOR_ALPHA )\\n\\n\\tvColor = vec4( 1.0 );\\n\\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )\\n\\n\\tvColor = vec3( 1.0 );\\n\\n#endif\\n\\n#ifdef USE_COLOR\\n\\n\\tvColor *= color;\\n\\n#endif\\n\\n#ifdef USE_INSTANCING_COLOR\\n\\n\\tvColor.xyz *= instanceColor.xyz;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/common.glsl.js\\nvar common_glsl_default = `\\n#define PI 3.141592653589793\\n#define PI2 6.283185307179586\\n#define PI_HALF 1.5707963267948966\\n#define RECIPROCAL_PI 0.3183098861837907\\n#define RECIPROCAL_PI2 0.15915494309189535\\n#define EPSILON 1e-6\\n\\n#ifndef saturate\\n// may have defined saturate() already\\n#define saturate( a ) clamp( a, 0.0, 1.0 )\\n#endif\\n#define whiteComplement( a ) ( 1.0 - saturate( a ) )\\n\\nfloat pow2( const in float x ) { return x*x; }\\nfloat pow3( const in float x ) { return x*x*x; }\\nfloat pow4( const in float x ) { float x2 = x*x; return x2*x2; }\\nfloat max3( const in vec3 v ) { return max( max( v.x, v.y ), v.z ); }\\nfloat average( const in vec3 color ) { return dot( color, vec3( 0.3333 ) ); }\\n\\n// expects values in the range of [0,1]x[0,1], returns values in the [0,1] range.\\n// do not collapse into a single function per: http://byteblacksmith.com/improvements-to-the-canonical-one-liner-glsl-rand-for-opengl-es-2-0/\\nhighp float rand( const in vec2 uv ) {\\n\\n\\tconst highp float a = 12.9898, b = 78.233, c = 43758.5453;\\n\\thighp float dt = dot( uv.xy, vec2( a,b ) ), sn = mod( dt, PI );\\n\\n\\treturn fract( sin( sn ) * c );\\n\\n}\\n\\n#ifdef HIGH_PRECISION\\n\\tfloat precisionSafeLength( vec3 v ) { return length( v ); }\\n#else\\n\\tfloat precisionSafeLength( vec3 v ) {\\n\\t\\tfloat maxComponent = max3( abs( v ) );\\n\\t\\treturn length( v / maxComponent ) * maxComponent;\\n\\t}\\n#endif\\n\\nstruct IncidentLight {\\n\\tvec3 color;\\n\\tvec3 direction;\\n\\tbool visible;\\n};\\n\\nstruct ReflectedLight {\\n\\tvec3 directDiffuse;\\n\\tvec3 directSpecular;\\n\\tvec3 indirectDiffuse;\\n\\tvec3 indirectSpecular;\\n};\\n\\nstruct GeometricContext {\\n\\tvec3 position;\\n\\tvec3 normal;\\n\\tvec3 viewDir;\\n#ifdef USE_CLEARCOAT\\n\\tvec3 clearcoatNormal;\\n#endif\\n};\\n\\nvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\\n\\n\\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\\n\\n}\\n\\nvec3 inverseTransformDirection( in vec3 dir, in mat4 matrix ) {\\n\\n\\t// dir can be either a direction vector or a normal vector\\n\\t// upper-left 3x3 of matrix is assumed to be orthogonal\\n\\n\\treturn normalize( ( vec4( dir, 0.0 ) * matrix ).xyz );\\n\\n}\\n\\nmat3 transposeMat3( const in mat3 m ) {\\n\\n\\tmat3 tmp;\\n\\n\\ttmp[ 0 ] = vec3( m[ 0 ].x, m[ 1 ].x, m[ 2 ].x );\\n\\ttmp[ 1 ] = vec3( m[ 0 ].y, m[ 1 ].y, m[ 2 ].y );\\n\\ttmp[ 2 ] = vec3( m[ 0 ].z, m[ 1 ].z, m[ 2 ].z );\\n\\n\\treturn tmp;\\n\\n}\\n\\n// https://en.wikipedia.org/wiki/Relative_luminance\\nfloat linearToRelativeLuminance( const in vec3 color ) {\\n\\n\\tvec3 weights = vec3( 0.2126, 0.7152, 0.0722 );\\n\\n\\treturn dot( weights, color.rgb );\\n\\n}\\n\\nbool isPerspectiveMatrix( mat4 m ) {\\n\\n\\treturn m[ 2 ][ 3 ] == - 1.0;\\n\\n}\\n\\nvec2 equirectUv( in vec3 dir ) {\\n\\n\\t// dir is assumed to be unit length\\n\\n\\tfloat u = atan( dir.z, dir.x ) * RECIPROCAL_PI2 + 0.5;\\n\\n\\tfloat v = asin( clamp( dir.y, - 1.0, 1.0 ) ) * RECIPROCAL_PI + 0.5;\\n\\n\\treturn vec2( u, v );\\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/cube_uv_reflection_fragment.glsl.js\\nvar cube_uv_reflection_fragment_glsl_default = `\\n#ifdef ENVMAP_TYPE_CUBE_UV\\n\\n\\t#define cubeUV_maxMipLevel 8.0\\n\\t#define cubeUV_minMipLevel 4.0\\n\\t#define cubeUV_maxTileSize 256.0\\n\\t#define cubeUV_minTileSize 16.0\\n\\n\\t// These shader functions convert between the UV coordinates of a single face of\\n\\t// a cubemap, the 0-5 integer index of a cube face, and the direction vector for\\n\\t// sampling a textureCube (not generally normalized ).\\n\\n\\tfloat getFace( vec3 direction ) {\\n\\n\\t\\tvec3 absDirection = abs( direction );\\n\\n\\t\\tfloat face = - 1.0;\\n\\n\\t\\tif ( absDirection.x > absDirection.z ) {\\n\\n\\t\\t\\tif ( absDirection.x > absDirection.y )\\n\\n\\t\\t\\t\\tface = direction.x > 0.0 ? 0.0 : 3.0;\\n\\n\\t\\t\\telse\\n\\n\\t\\t\\t\\tface = direction.y > 0.0 ? 1.0 : 4.0;\\n\\n\\t\\t} else {\\n\\n\\t\\t\\tif ( absDirection.z > absDirection.y )\\n\\n\\t\\t\\t\\tface = direction.z > 0.0 ? 2.0 : 5.0;\\n\\n\\t\\t\\telse\\n\\n\\t\\t\\t\\tface = direction.y > 0.0 ? 1.0 : 4.0;\\n\\n\\t\\t}\\n\\n\\t\\treturn face;\\n\\n\\t}\\n\\n\\t// RH coordinate system; PMREM face-indexing convention\\n\\tvec2 getUV( vec3 direction, float face ) {\\n\\n\\t\\tvec2 uv;\\n\\n\\t\\tif ( face == 0.0 ) {\\n\\n\\t\\t\\tuv = vec2( direction.z, direction.y ) / abs( direction.x ); // pos x\\n\\n\\t\\t} else if ( face == 1.0 ) {\\n\\n\\t\\t\\tuv = vec2( - direction.x, - direction.z ) / abs( direction.y ); // pos y\\n\\n\\t\\t} else if ( face == 2.0 ) {\\n\\n\\t\\t\\tuv = vec2( - direction.x, direction.y ) / abs( direction.z ); // pos z\\n\\n\\t\\t} else if ( face == 3.0 ) {\\n\\n\\t\\t\\tuv = vec2( - direction.z, direction.y ) / abs( direction.x ); // neg x\\n\\n\\t\\t} else if ( face == 4.0 ) {\\n\\n\\t\\t\\tuv = vec2( - direction.x, direction.z ) / abs( direction.y ); // neg y\\n\\n\\t\\t} else {\\n\\n\\t\\t\\tuv = vec2( direction.x, direction.y ) / abs( direction.z ); // neg z\\n\\n\\t\\t}\\n\\n\\t\\treturn 0.5 * ( uv + 1.0 );\\n\\n\\t}\\n\\n\\tvec3 bilinearCubeUV( sampler2D envMap, vec3 direction, float mipInt ) {\\n\\n\\t\\tfloat face = getFace( direction );\\n\\n\\t\\tfloat filterInt = max( cubeUV_minMipLevel - mipInt, 0.0 );\\n\\n\\t\\tmipInt = max( mipInt, cubeUV_minMipLevel );\\n\\n\\t\\tfloat faceSize = exp2( mipInt );\\n\\n\\t\\tfloat texelSize = 1.0 / ( 3.0 * cubeUV_maxTileSize );\\n\\n\\t\\tvec2 uv = getUV( direction, face ) * ( faceSize - 1.0 );\\n\\n\\t\\tvec2 f = fract( uv );\\n\\n\\t\\tuv += 0.5 - f;\\n\\n\\t\\tif ( face > 2.0 ) {\\n\\n\\t\\t\\tuv.y += faceSize;\\n\\n\\t\\t\\tface -= 3.0;\\n\\n\\t\\t}\\n\\n\\t\\tuv.x += face * faceSize;\\n\\n\\t\\tif ( mipInt < cubeUV_maxMipLevel ) {\\n\\n\\t\\t\\tuv.y += 2.0 * cubeUV_maxTileSize;\\n\\n\\t\\t}\\n\\n\\t\\tuv.y += filterInt * 2.0 * cubeUV_minTileSize;\\n\\n\\t\\tuv.x += 3.0 * max( 0.0, cubeUV_maxTileSize - 2.0 * faceSize );\\n\\n\\t\\tuv *= texelSize;\\n\\n\\t\\tvec3 tl = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\n\\n\\t\\tuv.x += texelSize;\\n\\n\\t\\tvec3 tr = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\n\\n\\t\\tuv.y += texelSize;\\n\\n\\t\\tvec3 br = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\n\\n\\t\\tuv.x -= texelSize;\\n\\n\\t\\tvec3 bl = envMapTexelToLinear( texture2D( envMap, uv ) ).rgb;\\n\\n\\t\\tvec3 tm = mix( tl, tr, f.x );\\n\\n\\t\\tvec3 bm = mix( bl, br, f.x );\\n\\n\\t\\treturn mix( tm, bm, f.y );\\n\\n\\t}\\n\\n\\t// These defines must match with PMREMGenerator\\n\\n\\t#define r0 1.0\\n\\t#define v0 0.339\\n\\t#define m0 - 2.0\\n\\t#define r1 0.8\\n\\t#define v1 0.276\\n\\t#define m1 - 1.0\\n\\t#define r4 0.4\\n\\t#define v4 0.046\\n\\t#define m4 2.0\\n\\t#define r5 0.305\\n\\t#define v5 0.016\\n\\t#define m5 3.0\\n\\t#define r6 0.21\\n\\t#define v6 0.0038\\n\\t#define m6 4.0\\n\\n\\tfloat roughnessToMip( float roughness ) {\\n\\n\\t\\tfloat mip = 0.0;\\n\\n\\t\\tif ( roughness >= r1 ) {\\n\\n\\t\\t\\tmip = ( r0 - roughness ) * ( m1 - m0 ) / ( r0 - r1 ) + m0;\\n\\n\\t\\t} else if ( roughness >= r4 ) {\\n\\n\\t\\t\\tmip = ( r1 - roughness ) * ( m4 - m1 ) / ( r1 - r4 ) + m1;\\n\\n\\t\\t} else if ( roughness >= r5 ) {\\n\\n\\t\\t\\tmip = ( r4 - roughness ) * ( m5 - m4 ) / ( r4 - r5 ) + m4;\\n\\n\\t\\t} else if ( roughness >= r6 ) {\\n\\n\\t\\t\\tmip = ( r5 - roughness ) * ( m6 - m5 ) / ( r5 - r6 ) + m5;\\n\\n\\t\\t} else {\\n\\n\\t\\t\\tmip = - 2.0 * log2( 1.16 * roughness ); // 1.16 = 1.79^0.25\\n\\t\\t}\\n\\n\\t\\treturn mip;\\n\\n\\t}\\n\\n\\tvec4 textureCubeUV( sampler2D envMap, vec3 sampleDir, float roughness ) {\\n\\n\\t\\tfloat mip = clamp( roughnessToMip( roughness ), m0, cubeUV_maxMipLevel );\\n\\n\\t\\tfloat mipF = fract( mip );\\n\\n\\t\\tfloat mipInt = floor( mip );\\n\\n\\t\\tvec3 color0 = bilinearCubeUV( envMap, sampleDir, mipInt );\\n\\n\\t\\tif ( mipF == 0.0 ) {\\n\\n\\t\\t\\treturn vec4( color0, 1.0 );\\n\\n\\t\\t} else {\\n\\n\\t\\t\\tvec3 color1 = bilinearCubeUV( envMap, sampleDir, mipInt + 1.0 );\\n\\n\\t\\t\\treturn vec4( mix( color0, color1, mipF ), 1.0 );\\n\\n\\t\\t}\\n\\n\\t}\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/defaultnormal_vertex.glsl.js\\nvar defaultnormal_vertex_glsl_default = `\\nvec3 transformedNormal = objectNormal;\\n\\n#ifdef USE_INSTANCING\\n\\n\\t// this is in lieu of a per-instance normal-matrix\\n\\t// shear transforms in the instance matrix are not supported\\n\\n\\tmat3 m = mat3( instanceMatrix );\\n\\n\\ttransformedNormal /= vec3( dot( m[ 0 ], m[ 0 ] ), dot( m[ 1 ], m[ 1 ] ), dot( m[ 2 ], m[ 2 ] ) );\\n\\n\\ttransformedNormal = m * transformedNormal;\\n\\n#endif\\n\\ntransformedNormal = normalMatrix * transformedNormal;\\n\\n#ifdef FLIP_SIDED\\n\\n\\ttransformedNormal = - transformedNormal;\\n\\n#endif\\n\\n#ifdef USE_TANGENT\\n\\n\\tvec3 transformedTangent = ( modelViewMatrix * vec4( objectTangent, 0.0 ) ).xyz;\\n\\n\\t#ifdef FLIP_SIDED\\n\\n\\t\\ttransformedTangent = - transformedTangent;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/displacementmap_pars_vertex.glsl.js\\nvar displacementmap_pars_vertex_glsl_default = `\\n#ifdef USE_DISPLACEMENTMAP\\n\\n\\tuniform sampler2D displacementMap;\\n\\tuniform float displacementScale;\\n\\tuniform float displacementBias;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/displacementmap_vertex.glsl.js\\nvar displacementmap_vertex_glsl_default = `\\n#ifdef USE_DISPLACEMENTMAP\\n\\n\\ttransformed += normalize( objectNormal ) * ( texture2D( displacementMap, vUv ).x * displacementScale + displacementBias );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/emissivemap_fragment.glsl.js\\nvar emissivemap_fragment_glsl_default = `\\n#ifdef USE_EMISSIVEMAP\\n\\n\\tvec4 emissiveColor = texture2D( emissiveMap, vUv );\\n\\n\\temissiveColor.rgb = emissiveMapTexelToLinear( emissiveColor ).rgb;\\n\\n\\ttotalEmissiveRadiance *= emissiveColor.rgb;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/emissivemap_pars_fragment.glsl.js\\nvar emissivemap_pars_fragment_glsl_default = `\\n#ifdef USE_EMISSIVEMAP\\n\\n\\tuniform sampler2D emissiveMap;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/encodings_fragment.glsl.js\\nvar encodings_fragment_glsl_default = `\\ngl_FragColor = linearToOutputTexel( gl_FragColor );\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/encodings_pars_fragment.glsl.js\\nvar encodings_pars_fragment_glsl_default = `\\n// For a discussion of what this is, please read this: http://lousodrome.net/blog/light/2013/05/26/gamma-correct-and-hdr-rendering-in-a-32-bits-buffer/\\n\\nvec4 LinearToLinear( in vec4 value ) {\\n\\treturn value;\\n}\\n\\nvec4 GammaToLinear( in vec4 value, in float gammaFactor ) {\\n\\treturn vec4( pow( value.rgb, vec3( gammaFactor ) ), value.a );\\n}\\n\\nvec4 LinearToGamma( in vec4 value, in float gammaFactor ) {\\n\\treturn vec4( pow( value.rgb, vec3( 1.0 / gammaFactor ) ), value.a );\\n}\\n\\nvec4 sRGBToLinear( in vec4 value ) {\\n\\treturn vec4( mix( pow( value.rgb * 0.9478672986 + vec3( 0.0521327014 ), vec3( 2.4 ) ), value.rgb * 0.0773993808, vec3( lessThanEqual( value.rgb, vec3( 0.04045 ) ) ) ), value.a );\\n}\\n\\nvec4 LinearTosRGB( in vec4 value ) {\\n\\treturn vec4( mix( pow( value.rgb, vec3( 0.41666 ) ) * 1.055 - vec3( 0.055 ), value.rgb * 12.92, vec3( lessThanEqual( value.rgb, vec3( 0.0031308 ) ) ) ), value.a );\\n}\\n\\nvec4 RGBEToLinear( in vec4 value ) {\\n\\treturn vec4( value.rgb * exp2( value.a * 255.0 - 128.0 ), 1.0 );\\n}\\n\\nvec4 LinearToRGBE( in vec4 value ) {\\n\\tfloat maxComponent = max( max( value.r, value.g ), value.b );\\n\\tfloat fExp = clamp( ceil( log2( maxComponent ) ), -128.0, 127.0 );\\n\\treturn vec4( value.rgb / exp2( fExp ), ( fExp + 128.0 ) / 255.0 );\\n\\t// return vec4( value.brg, ( 3.0 + 128.0 ) / 256.0 );\\n}\\n\\n// reference: http://iwasbeingirony.blogspot.ca/2010/06/difference-between-rgbm-and-rgbd.html\\nvec4 RGBMToLinear( in vec4 value, in float maxRange ) {\\n\\treturn vec4( value.rgb * value.a * maxRange, 1.0 );\\n}\\n\\nvec4 LinearToRGBM( in vec4 value, in float maxRange ) {\\n\\tfloat maxRGB = max( value.r, max( value.g, value.b ) );\\n\\tfloat M = clamp( maxRGB / maxRange, 0.0, 1.0 );\\n\\tM = ceil( M * 255.0 ) / 255.0;\\n\\treturn vec4( value.rgb / ( M * maxRange ), M );\\n}\\n\\n// reference: http://iwasbeingirony.blogspot.ca/2010/06/difference-between-rgbm-and-rgbd.html\\nvec4 RGBDToLinear( in vec4 value, in float maxRange ) {\\n\\treturn vec4( value.rgb * ( ( maxRange / 255.0 ) / value.a ), 1.0 );\\n}\\n\\nvec4 LinearToRGBD( in vec4 value, in float maxRange ) {\\n\\tfloat maxRGB = max( value.r, max( value.g, value.b ) );\\n\\tfloat D = max( maxRange / maxRGB, 1.0 );\\n\\t// NOTE: The implementation with min causes the shader to not compile on\\n\\t// a common Alcatel A502DL in Chrome 78/Android 8.1. Some research suggests \\n\\t// that the chipset is Mediatek MT6739 w/ IMG PowerVR GE8100 GPU.\\n\\t// D = min( floor( D ) / 255.0, 1.0 );\\n\\tD = clamp( floor( D ) / 255.0, 0.0, 1.0 );\\n\\treturn vec4( value.rgb * ( D * ( 255.0 / maxRange ) ), D );\\n}\\n\\n// LogLuv reference: http://graphicrants.blogspot.ca/2009/04/rgbm-color-encoding.html\\n\\n// M matrix, for encoding\\nconst mat3 cLogLuvM = mat3( 0.2209, 0.3390, 0.4184, 0.1138, 0.6780, 0.7319, 0.0102, 0.1130, 0.2969 );\\nvec4 LinearToLogLuv( in vec4 value ) {\\n\\tvec3 Xp_Y_XYZp = cLogLuvM * value.rgb;\\n\\tXp_Y_XYZp = max( Xp_Y_XYZp, vec3( 1e-6, 1e-6, 1e-6 ) );\\n\\tvec4 vResult;\\n\\tvResult.xy = Xp_Y_XYZp.xy / Xp_Y_XYZp.z;\\n\\tfloat Le = 2.0 * log2(Xp_Y_XYZp.y) + 127.0;\\n\\tvResult.w = fract( Le );\\n\\tvResult.z = ( Le - ( floor( vResult.w * 255.0 ) ) / 255.0 ) / 255.0;\\n\\treturn vResult;\\n}\\n\\n// Inverse M matrix, for decoding\\nconst mat3 cLogLuvInverseM = mat3( 6.0014, -2.7008, -1.7996, -1.3320, 3.1029, -5.7721, 0.3008, -1.0882, 5.6268 );\\nvec4 LogLuvToLinear( in vec4 value ) {\\n\\tfloat Le = value.z * 255.0 + value.w;\\n\\tvec3 Xp_Y_XYZp;\\n\\tXp_Y_XYZp.y = exp2( ( Le - 127.0 ) / 2.0 );\\n\\tXp_Y_XYZp.z = Xp_Y_XYZp.y / value.y;\\n\\tXp_Y_XYZp.x = value.x * Xp_Y_XYZp.z;\\n\\tvec3 vRGB = cLogLuvInverseM * Xp_Y_XYZp.rgb;\\n\\treturn vec4( max( vRGB, 0.0 ), 1.0 );\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/envmap_fragment.glsl.js\\nvar envmap_fragment_glsl_default = `\\n#ifdef USE_ENVMAP\\n\\n\\t#ifdef ENV_WORLDPOS\\n\\n\\t\\tvec3 cameraToFrag;\\n\\n\\t\\tif ( isOrthographic ) {\\n\\n\\t\\t\\tcameraToFrag = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\\n\\n\\t\\t} else {\\n\\n\\t\\t\\tcameraToFrag = normalize( vWorldPosition - cameraPosition );\\n\\n\\t\\t}\\n\\n\\t\\t// Transforming Normal Vectors with the Inverse Transformation\\n\\t\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\n\\n\\t\\t#ifdef ENVMAP_MODE_REFLECTION\\n\\n\\t\\t\\tvec3 reflectVec = reflect( cameraToFrag, worldNormal );\\n\\n\\t\\t#else\\n\\n\\t\\t\\tvec3 reflectVec = refract( cameraToFrag, worldNormal, refractionRatio );\\n\\n\\t\\t#endif\\n\\n\\t#else\\n\\n\\t\\tvec3 reflectVec = vReflect;\\n\\n\\t#endif\\n\\n\\t#ifdef ENVMAP_TYPE_CUBE\\n\\n\\t\\tvec4 envColor = textureCube( envMap, vec3( flipEnvMap * reflectVec.x, reflectVec.yz ) );\\n\\n\\t\\tenvColor = envMapTexelToLinear( envColor );\\n\\n\\t#elif defined( ENVMAP_TYPE_CUBE_UV )\\n\\n\\t\\tvec4 envColor = textureCubeUV( envMap, reflectVec, 0.0 );\\n\\n\\t#else\\n\\n\\t\\tvec4 envColor = vec4( 0.0 );\\n\\n\\t#endif\\n\\n\\t#ifdef ENVMAP_BLENDING_MULTIPLY\\n\\n\\t\\toutgoingLight = mix( outgoingLight, outgoingLight * envColor.xyz, specularStrength * reflectivity );\\n\\n\\t#elif defined( ENVMAP_BLENDING_MIX )\\n\\n\\t\\toutgoingLight = mix( outgoingLight, envColor.xyz, specularStrength * reflectivity );\\n\\n\\t#elif defined( ENVMAP_BLENDING_ADD )\\n\\n\\t\\toutgoingLight += envColor.xyz * specularStrength * reflectivity;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/envmap_common_pars_fragment.glsl.js\\nvar envmap_common_pars_fragment_glsl_default = `\\n#ifdef USE_ENVMAP\\n\\n\\tuniform float envMapIntensity;\\n\\tuniform float flipEnvMap;\\n\\tuniform int maxMipLevel;\\n\\n\\t#ifdef ENVMAP_TYPE_CUBE\\n\\t\\tuniform samplerCube envMap;\\n\\t#else\\n\\t\\tuniform sampler2D envMap;\\n\\t#endif\\n\\t\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/envmap_pars_fragment.glsl.js\\nvar envmap_pars_fragment_glsl_default = `\\n#ifdef USE_ENVMAP\\n\\n\\tuniform float reflectivity;\\n\\n\\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG )\\n\\n\\t\\t#define ENV_WORLDPOS\\n\\n\\t#endif\\n\\n\\t#ifdef ENV_WORLDPOS\\n\\n\\t\\tvarying vec3 vWorldPosition;\\n\\t\\tuniform float refractionRatio;\\n\\t#else\\n\\t\\tvarying vec3 vReflect;\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/envmap_pars_vertex.glsl.js\\nvar envmap_pars_vertex_glsl_default = `\\n#ifdef USE_ENVMAP\\n\\n\\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) ||defined( PHONG )\\n\\n\\t\\t#define ENV_WORLDPOS\\n\\n\\t#endif\\n\\n\\t#ifdef ENV_WORLDPOS\\n\\t\\t\\n\\t\\tvarying vec3 vWorldPosition;\\n\\n\\t#else\\n\\n\\t\\tvarying vec3 vReflect;\\n\\t\\tuniform float refractionRatio;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/envmap_vertex.glsl.js\\nvar envmap_vertex_glsl_default = `\\n#ifdef USE_ENVMAP\\n\\n\\t#ifdef ENV_WORLDPOS\\n\\n\\t\\tvWorldPosition = worldPosition.xyz;\\n\\n\\t#else\\n\\n\\t\\tvec3 cameraToVertex;\\n\\n\\t\\tif ( isOrthographic ) {\\n\\n\\t\\t\\tcameraToVertex = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\\n\\n\\t\\t} else {\\n\\n\\t\\t\\tcameraToVertex = normalize( worldPosition.xyz - cameraPosition );\\n\\n\\t\\t}\\n\\n\\t\\tvec3 worldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\\n\\n\\t\\t#ifdef ENVMAP_MODE_REFLECTION\\n\\n\\t\\t\\tvReflect = reflect( cameraToVertex, worldNormal );\\n\\n\\t\\t#else\\n\\n\\t\\t\\tvReflect = refract( cameraToVertex, worldNormal, refractionRatio );\\n\\n\\t\\t#endif\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/fog_vertex.glsl.js\\nvar fog_vertex_glsl_default = `\\n#ifdef USE_FOG\\n\\n\\tvFogDepth = - mvPosition.z;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/fog_pars_vertex.glsl.js\\nvar fog_pars_vertex_glsl_default = `\\n#ifdef USE_FOG\\n\\n\\tvarying float vFogDepth;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/fog_fragment.glsl.js\\nvar fog_fragment_glsl_default = `\\n#ifdef USE_FOG\\n\\n\\t#ifdef FOG_EXP2\\n\\n\\t\\tfloat fogFactor = 1.0 - exp( - fogDensity * fogDensity * vFogDepth * vFogDepth );\\n\\n\\t#else\\n\\n\\t\\tfloat fogFactor = smoothstep( fogNear, fogFar, vFogDepth );\\n\\n\\t#endif\\n\\n\\tgl_FragColor.rgb = mix( gl_FragColor.rgb, fogColor, fogFactor );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/fog_pars_fragment.glsl.js\\nvar fog_pars_fragment_glsl_default = `\\n#ifdef USE_FOG\\n\\n\\tuniform vec3 fogColor;\\n\\tvarying float vFogDepth;\\n\\n\\t#ifdef FOG_EXP2\\n\\n\\t\\tuniform float fogDensity;\\n\\n\\t#else\\n\\n\\t\\tuniform float fogNear;\\n\\t\\tuniform float fogFar;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/gradientmap_pars_fragment.glsl.js\\nvar gradientmap_pars_fragment_glsl_default = `\\n\\n#ifdef USE_GRADIENTMAP\\n\\n\\tuniform sampler2D gradientMap;\\n\\n#endif\\n\\nvec3 getGradientIrradiance( vec3 normal, vec3 lightDirection ) {\\n\\n\\t// dotNL will be from -1.0 to 1.0\\n\\tfloat dotNL = dot( normal, lightDirection );\\n\\tvec2 coord = vec2( dotNL * 0.5 + 0.5, 0.0 );\\n\\n\\t#ifdef USE_GRADIENTMAP\\n\\n\\t\\treturn texture2D( gradientMap, coord ).rgb;\\n\\n\\t#else\\n\\n\\t\\treturn ( coord.x < 0.7 ) ? vec3( 0.7 ) : vec3( 1.0 );\\n\\n\\t#endif\\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lightmap_fragment.glsl.js\\nvar lightmap_fragment_glsl_default = `\\n#ifdef USE_LIGHTMAP\\n\\n\\tvec4 lightMapTexel = texture2D( lightMap, vUv2 );\\n\\tvec3 lightMapIrradiance = lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\n\\n\\t#ifndef PHYSICALLY_CORRECT_LIGHTS\\n\\n\\t\\tlightMapIrradiance *= PI;\\n\\n\\t#endif\\n\\n\\treflectedLight.indirectDiffuse += lightMapIrradiance;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lightmap_pars_fragment.glsl.js\\nvar lightmap_pars_fragment_glsl_default = `\\n#ifdef USE_LIGHTMAP\\n\\n\\tuniform sampler2D lightMap;\\n\\tuniform float lightMapIntensity;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_lambert_vertex.glsl.js\\nvar lights_lambert_vertex_glsl_default = `\\nvec3 diffuse = vec3( 1.0 );\\n\\nGeometricContext geometry;\\ngeometry.position = mvPosition.xyz;\\ngeometry.normal = normalize( transformedNormal );\\ngeometry.viewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( -mvPosition.xyz );\\n\\nGeometricContext backGeometry;\\nbackGeometry.position = geometry.position;\\nbackGeometry.normal = -geometry.normal;\\nbackGeometry.viewDir = geometry.viewDir;\\n\\nvLightFront = vec3( 0.0 );\\nvIndirectFront = vec3( 0.0 );\\n#ifdef DOUBLE_SIDED\\n\\tvLightBack = vec3( 0.0 );\\n\\tvIndirectBack = vec3( 0.0 );\\n#endif\\n\\nIncidentLight directLight;\\nfloat dotNL;\\nvec3 directLightColor_Diffuse;\\n\\nvIndirectFront += getAmbientLightIrradiance( ambientLightColor );\\n\\nvIndirectFront += getLightProbeIrradiance( lightProbe, geometry.normal );\\n\\n#ifdef DOUBLE_SIDED\\n\\n\\tvIndirectBack += getAmbientLightIrradiance( ambientLightColor );\\n\\n\\tvIndirectBack += getLightProbeIrradiance( lightProbe, backGeometry.normal );\\n\\n#endif\\n\\n#if NUM_POINT_LIGHTS > 0\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\\n\\n\\t\\tgetPointLightInfo( pointLights[ i ], geometry, directLight );\\n\\n\\t\\tdotNL = dot( geometry.normal, directLight.direction );\\n\\t\\tdirectLightColor_Diffuse = directLight.color;\\n\\n\\t\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\n\\n\\t\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\t\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\n\\n\\t\\t#endif\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n#endif\\n\\n#if NUM_SPOT_LIGHTS > 0\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\\n\\n\\t\\tgetSpotLightInfo( spotLights[ i ], geometry, directLight );\\n\\n\\t\\tdotNL = dot( geometry.normal, directLight.direction );\\n\\t\\tdirectLightColor_Diffuse = directLight.color;\\n\\n\\t\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\n\\n\\t\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\t\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\n\\n\\t\\t#endif\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n#endif\\n\\n#if NUM_DIR_LIGHTS > 0\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\\n\\n\\t\\tgetDirectionalLightInfo( directionalLights[ i ], geometry, directLight );\\n\\n\\t\\tdotNL = dot( geometry.normal, directLight.direction );\\n\\t\\tdirectLightColor_Diffuse = directLight.color;\\n\\n\\t\\tvLightFront += saturate( dotNL ) * directLightColor_Diffuse;\\n\\n\\t\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\t\\tvLightBack += saturate( - dotNL ) * directLightColor_Diffuse;\\n\\n\\t\\t#endif\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n#endif\\n\\n#if NUM_HEMI_LIGHTS > 0\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\\n\\n\\t\\tvIndirectFront += getHemisphereLightIrradiance( hemisphereLights[ i ], geometry.normal );\\n\\n\\t\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\t\\tvIndirectBack += getHemisphereLightIrradiance( hemisphereLights[ i ], backGeometry.normal );\\n\\n\\t\\t#endif\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_pars_begin.glsl.js\\nvar lights_pars_begin_glsl_default = `\\nuniform bool receiveShadow;\\nuniform vec3 ambientLightColor;\\nuniform vec3 lightProbe[ 9 ];\\n\\n// get the irradiance (radiance convolved with cosine lobe) at the point 'normal' on the unit sphere\\n// source: https://graphics.stanford.edu/papers/envmap/envmap.pdf\\nvec3 shGetIrradianceAt( in vec3 normal, in vec3 shCoefficients[ 9 ] ) {\\n\\n\\t// normal is assumed to have unit length\\n\\n\\tfloat x = normal.x, y = normal.y, z = normal.z;\\n\\n\\t// band 0\\n\\tvec3 result = shCoefficients[ 0 ] * 0.886227;\\n\\n\\t// band 1\\n\\tresult += shCoefficients[ 1 ] * 2.0 * 0.511664 * y;\\n\\tresult += shCoefficients[ 2 ] * 2.0 * 0.511664 * z;\\n\\tresult += shCoefficients[ 3 ] * 2.0 * 0.511664 * x;\\n\\n\\t// band 2\\n\\tresult += shCoefficients[ 4 ] * 2.0 * 0.429043 * x * y;\\n\\tresult += shCoefficients[ 5 ] * 2.0 * 0.429043 * y * z;\\n\\tresult += shCoefficients[ 6 ] * ( 0.743125 * z * z - 0.247708 );\\n\\tresult += shCoefficients[ 7 ] * 2.0 * 0.429043 * x * z;\\n\\tresult += shCoefficients[ 8 ] * 0.429043 * ( x * x - y * y );\\n\\n\\treturn result;\\n\\n}\\n\\nvec3 getLightProbeIrradiance( const in vec3 lightProbe[ 9 ], const in vec3 normal ) {\\n\\n\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\n\\n\\tvec3 irradiance = shGetIrradianceAt( worldNormal, lightProbe );\\n\\n\\treturn irradiance;\\n\\n}\\n\\nvec3 getAmbientLightIrradiance( const in vec3 ambientLightColor ) {\\n\\n\\tvec3 irradiance = ambientLightColor;\\n\\n\\treturn irradiance;\\n\\n}\\n\\nfloat getDistanceAttenuation( const in float lightDistance, const in float cutoffDistance, const in float decayExponent ) {\\n\\n\\t#if defined ( PHYSICALLY_CORRECT_LIGHTS )\\n\\n\\t\\t// based upon Frostbite 3 Moving to Physically-based Rendering\\n\\t\\t// page 32, equation 26: E[window1]\\n\\t\\t// https://seblagarde.files.wordpress.com/2015/07/course_notes_moving_frostbite_to_pbr_v32.pdf\\n\\t\\tfloat distanceFalloff = 1.0 / max( pow( lightDistance, decayExponent ), 0.01 );\\n\\n\\t\\tif ( cutoffDistance > 0.0 ) {\\n\\n\\t\\t\\tdistanceFalloff *= pow2( saturate( 1.0 - pow4( lightDistance / cutoffDistance ) ) );\\n\\n\\t\\t}\\n\\n\\t\\treturn distanceFalloff;\\n\\n\\t#else\\n\\n\\t\\tif ( cutoffDistance > 0.0 && decayExponent > 0.0 ) {\\n\\n\\t\\t\\treturn pow( saturate( - lightDistance / cutoffDistance + 1.0 ), decayExponent );\\n\\n\\t\\t}\\n\\n\\t\\treturn 1.0;\\n\\n\\t#endif\\n\\n}\\n\\nfloat getSpotAttenuation( const in float coneCosine, const in float penumbraCosine, const in float angleCosine ) {\\n\\n\\treturn smoothstep( coneCosine, penumbraCosine, angleCosine );\\n\\n}\\n\\n#if NUM_DIR_LIGHTS > 0\\n\\n\\tstruct DirectionalLight {\\n\\t\\tvec3 direction;\\n\\t\\tvec3 color;\\n\\t};\\n\\n\\tuniform DirectionalLight directionalLights[ NUM_DIR_LIGHTS ];\\n\\n\\tvoid getDirectionalLightInfo( const in DirectionalLight directionalLight, const in GeometricContext geometry, out IncidentLight light ) {\\n\\n\\t\\tlight.color = directionalLight.color;\\n\\t\\tlight.direction = directionalLight.direction;\\n\\t\\tlight.visible = true;\\n\\n\\t}\\n\\n#endif\\n\\n\\n#if NUM_POINT_LIGHTS > 0\\n\\n\\tstruct PointLight {\\n\\t\\tvec3 position;\\n\\t\\tvec3 color;\\n\\t\\tfloat distance;\\n\\t\\tfloat decay;\\n\\t};\\n\\n\\tuniform PointLight pointLights[ NUM_POINT_LIGHTS ];\\n\\n\\t// light is an out parameter as having it as a return value caused compiler errors on some devices\\n\\tvoid getPointLightInfo( const in PointLight pointLight, const in GeometricContext geometry, out IncidentLight light ) {\\n\\n\\t\\tvec3 lVector = pointLight.position - geometry.position;\\n\\n\\t\\tlight.direction = normalize( lVector );\\n\\n\\t\\tfloat lightDistance = length( lVector );\\n\\n\\t\\tlight.color = pointLight.color;\\n\\t\\tlight.color *= getDistanceAttenuation( lightDistance, pointLight.distance, pointLight.decay );\\n\\t\\tlight.visible = ( light.color != vec3( 0.0 ) );\\n\\n\\t}\\n\\n#endif\\n\\n\\n#if NUM_SPOT_LIGHTS > 0\\n\\n\\tstruct SpotLight {\\n\\t\\tvec3 position;\\n\\t\\tvec3 direction;\\n\\t\\tvec3 color;\\n\\t\\tfloat distance;\\n\\t\\tfloat decay;\\n\\t\\tfloat coneCos;\\n\\t\\tfloat penumbraCos;\\n\\t};\\n\\n\\tuniform SpotLight spotLights[ NUM_SPOT_LIGHTS ];\\n\\n\\t// light is an out parameter as having it as a return value caused compiler errors on some devices\\n\\tvoid getSpotLightInfo( const in SpotLight spotLight, const in GeometricContext geometry, out IncidentLight light ) {\\n\\n\\t\\tvec3 lVector = spotLight.position - geometry.position;\\n\\n\\t\\tlight.direction = normalize( lVector );\\n\\n\\t\\tfloat angleCos = dot( light.direction, spotLight.direction );\\n\\n\\t\\tfloat spotAttenuation = getSpotAttenuation( spotLight.coneCos, spotLight.penumbraCos, angleCos );\\n\\n\\t\\tif ( spotAttenuation > 0.0 ) {\\n\\n\\t\\t\\tfloat lightDistance = length( lVector );\\n\\n\\t\\t\\tlight.color = spotLight.color * spotAttenuation;\\n\\t\\t\\tlight.color *= getDistanceAttenuation( lightDistance, spotLight.distance, spotLight.decay );\\n\\t\\t\\tlight.visible = ( light.color != vec3( 0.0 ) );\\n\\n\\t\\t} else {\\n\\n\\t\\t\\tlight.color = vec3( 0.0 );\\n\\t\\t\\tlight.visible = false;\\n\\n\\t\\t}\\n\\n\\t}\\n\\n#endif\\n\\n\\n#if NUM_RECT_AREA_LIGHTS > 0\\n\\n\\tstruct RectAreaLight {\\n\\t\\tvec3 color;\\n\\t\\tvec3 position;\\n\\t\\tvec3 halfWidth;\\n\\t\\tvec3 halfHeight;\\n\\t};\\n\\n\\t// Pre-computed values of LinearTransformedCosine approximation of BRDF\\n\\t// BRDF approximation Texture is 64x64\\n\\tuniform sampler2D ltc_1; // RGBA Float\\n\\tuniform sampler2D ltc_2; // RGBA Float\\n\\n\\tuniform RectAreaLight rectAreaLights[ NUM_RECT_AREA_LIGHTS ];\\n\\n#endif\\n\\n\\n#if NUM_HEMI_LIGHTS > 0\\n\\n\\tstruct HemisphereLight {\\n\\t\\tvec3 direction;\\n\\t\\tvec3 skyColor;\\n\\t\\tvec3 groundColor;\\n\\t};\\n\\n\\tuniform HemisphereLight hemisphereLights[ NUM_HEMI_LIGHTS ];\\n\\n\\tvec3 getHemisphereLightIrradiance( const in HemisphereLight hemiLight, const in vec3 normal ) {\\n\\n\\t\\tfloat dotNL = dot( normal, hemiLight.direction );\\n\\t\\tfloat hemiDiffuseWeight = 0.5 * dotNL + 0.5;\\n\\n\\t\\tvec3 irradiance = mix( hemiLight.groundColor, hemiLight.skyColor, hemiDiffuseWeight );\\n\\n\\t\\treturn irradiance;\\n\\n\\t}\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/envmap_physical_pars_fragment.glsl.js\\nvar envmap_physical_pars_fragment_glsl_default = `\\n#if defined( USE_ENVMAP )\\n\\n\\t#ifdef ENVMAP_MODE_REFRACTION\\n\\n\\t\\tuniform float refractionRatio;\\n\\n\\t#endif\\n\\n\\tvec3 getIBLIrradiance( const in vec3 normal ) {\\n\\n\\t\\t#if defined( ENVMAP_TYPE_CUBE_UV )\\n\\n\\t\\t\\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\\n\\n\\t\\t\\tvec4 envMapColor = textureCubeUV( envMap, worldNormal, 1.0 );\\n\\n\\t\\t\\treturn PI * envMapColor.rgb * envMapIntensity;\\n\\n\\t\\t#else\\n\\n\\t\\t\\treturn vec3( 0.0 );\\n\\n\\t\\t#endif\\n\\n\\t}\\n\\n\\tvec3 getIBLRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness ) {\\n\\n\\t\\t#if defined( ENVMAP_TYPE_CUBE_UV )\\n\\n\\t\\t\\tvec3 reflectVec;\\n\\n\\t\\t\\t#ifdef ENVMAP_MODE_REFLECTION\\n\\n\\t\\t\\t\\treflectVec = reflect( - viewDir, normal );\\n\\n\\t\\t\\t\\t// Mixing the reflection with the normal is more accurate and keeps rough objects from gathering light from behind their tangent plane.\\n\\t\\t\\t\\treflectVec = normalize( mix( reflectVec, normal, roughness * roughness) );\\n\\n\\t\\t\\t#else\\n\\n\\t\\t\\t\\treflectVec = refract( - viewDir, normal, refractionRatio );\\n\\n\\t\\t\\t#endif\\n\\n\\t\\t\\treflectVec = inverseTransformDirection( reflectVec, viewMatrix );\\n\\n\\t\\t\\tvec4 envMapColor = textureCubeUV( envMap, reflectVec, roughness );\\n\\n\\t\\t\\treturn envMapColor.rgb * envMapIntensity;\\n\\n\\t\\t#else\\n\\n\\t\\t\\treturn vec3( 0.0 );\\n\\n\\t\\t#endif\\n\\n\\t}\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_toon_fragment.glsl.js\\nvar lights_toon_fragment_glsl_default = `\\nToonMaterial material;\\nmaterial.diffuseColor = diffuseColor.rgb;\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_toon_pars_fragment.glsl.js\\nvar lights_toon_pars_fragment_glsl_default = `\\nvarying vec3 vViewPosition;\\n\\nstruct ToonMaterial {\\n\\n\\tvec3 diffuseColor;\\n\\n};\\n\\nvoid RE_Direct_Toon( const in IncidentLight directLight, const in GeometricContext geometry, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\\n\\n\\tvec3 irradiance = getGradientIrradiance( geometry.normal, directLight.direction ) * directLight.color;\\n\\n\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\n\\n}\\n\\nvoid RE_IndirectDiffuse_Toon( const in vec3 irradiance, const in GeometricContext geometry, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\\n\\n\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\n\\n}\\n\\n#define RE_Direct\\t\\t\\t\\tRE_Direct_Toon\\n#define RE_IndirectDiffuse\\t\\tRE_IndirectDiffuse_Toon\\n\\n#define Material_LightProbeLOD( material )\\t(0)\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_phong_fragment.glsl.js\\nvar lights_phong_fragment_glsl_default = `\\nBlinnPhongMaterial material;\\nmaterial.diffuseColor = diffuseColor.rgb;\\nmaterial.specularColor = specular;\\nmaterial.specularShininess = shininess;\\nmaterial.specularStrength = specularStrength;\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_phong_pars_fragment.glsl.js\\nvar lights_phong_pars_fragment_glsl_default = `\\nvarying vec3 vViewPosition;\\n\\nstruct BlinnPhongMaterial {\\n\\n\\tvec3 diffuseColor;\\n\\tvec3 specularColor;\\n\\tfloat specularShininess;\\n\\tfloat specularStrength;\\n\\n};\\n\\nvoid RE_Direct_BlinnPhong( const in IncidentLight directLight, const in GeometricContext geometry, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\\n\\n\\tfloat dotNL = saturate( dot( geometry.normal, directLight.direction ) );\\n\\tvec3 irradiance = dotNL * directLight.color;\\n\\n\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\n\\n\\treflectedLight.directSpecular += irradiance * BRDF_BlinnPhong( directLight.direction, geometry.viewDir, geometry.normal, material.specularColor, material.specularShininess ) * material.specularStrength;\\n\\n}\\n\\nvoid RE_IndirectDiffuse_BlinnPhong( const in vec3 irradiance, const in GeometricContext geometry, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\\n\\n\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\n\\n}\\n\\n#define RE_Direct\\t\\t\\t\\tRE_Direct_BlinnPhong\\n#define RE_IndirectDiffuse\\t\\tRE_IndirectDiffuse_BlinnPhong\\n\\n#define Material_LightProbeLOD( material )\\t(0)\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_physical_fragment.glsl.js\\nvar lights_physical_fragment_glsl_default = `\\nPhysicalMaterial material;\\nmaterial.diffuseColor = diffuseColor.rgb * ( 1.0 - metalnessFactor );\\n\\nvec3 dxy = max( abs( dFdx( geometryNormal ) ), abs( dFdy( geometryNormal ) ) );\\nfloat geometryRoughness = max( max( dxy.x, dxy.y ), dxy.z );\\n\\nmaterial.roughness = max( roughnessFactor, 0.0525 );// 0.0525 corresponds to the base mip of a 256 cubemap.\\nmaterial.roughness += geometryRoughness;\\nmaterial.roughness = min( material.roughness, 1.0 );\\n\\n#ifdef IOR\\n\\n\\t#ifdef SPECULAR\\n\\n\\t\\tfloat specularIntensityFactor = specularIntensity;\\n\\t\\tvec3 specularTintFactor = specularTint;\\n\\n\\t\\t#ifdef USE_SPECULARINTENSITYMAP\\n\\n\\t\\t\\tspecularIntensityFactor *= texture2D( specularIntensityMap, vUv ).a;\\n\\n\\t\\t#endif\\n\\n\\t\\t#ifdef USE_SPECULARTINTMAP\\n\\n\\t\\t\\tspecularTintFactor *= specularTintMapTexelToLinear( texture2D( specularTintMap, vUv ) ).rgb;\\n\\n\\t\\t#endif\\n\\n\\t\\tmaterial.specularF90 = mix( specularIntensityFactor, 1.0, metalnessFactor );\\n\\n\\t#else\\n\\n\\t\\tfloat specularIntensityFactor = 1.0;\\n\\t\\tvec3 specularTintFactor = vec3( 1.0 );\\n\\t\\tmaterial.specularF90 = 1.0;\\n\\n\\t#endif\\n\\n\\tmaterial.specularColor = mix( min( pow2( ( ior - 1.0 ) / ( ior + 1.0 ) ) * specularTintFactor, vec3( 1.0 ) ) * specularIntensityFactor, diffuseColor.rgb, metalnessFactor );\\n\\n#else\\n\\n\\tmaterial.specularColor = mix( vec3( 0.04 ), diffuseColor.rgb, metalnessFactor );\\n\\tmaterial.specularF90 = 1.0;\\n\\n#endif\\n\\n#ifdef USE_CLEARCOAT\\n\\n\\tmaterial.clearcoat = clearcoat;\\n\\tmaterial.clearcoatRoughness = clearcoatRoughness;\\n\\tmaterial.clearcoatF0 = vec3( 0.04 );\\n\\tmaterial.clearcoatF90 = 1.0;\\n\\n\\t#ifdef USE_CLEARCOATMAP\\n\\n\\t\\tmaterial.clearcoat *= texture2D( clearcoatMap, vUv ).x;\\n\\n\\t#endif\\n\\n\\t#ifdef USE_CLEARCOAT_ROUGHNESSMAP\\n\\n\\t\\tmaterial.clearcoatRoughness *= texture2D( clearcoatRoughnessMap, vUv ).y;\\n\\n\\t#endif\\n\\n\\tmaterial.clearcoat = saturate( material.clearcoat ); // Burley clearcoat model\\n\\tmaterial.clearcoatRoughness = max( material.clearcoatRoughness, 0.0525 );\\n\\tmaterial.clearcoatRoughness += geometryRoughness;\\n\\tmaterial.clearcoatRoughness = min( material.clearcoatRoughness, 1.0 );\\n\\n#endif\\n\\n#ifdef USE_SHEEN\\n\\n\\tmaterial.sheenTint = sheenTint;\\n\\tmaterial.sheenRoughness = clamp( sheenRoughness, 0.07, 1.0 );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_physical_pars_fragment.glsl.js\\nvar lights_physical_pars_fragment_glsl_default = `\\nstruct PhysicalMaterial {\\n\\n\\tvec3 diffuseColor;\\n\\tfloat roughness;\\n\\tvec3 specularColor;\\n\\tfloat specularF90;\\n\\n\\t#ifdef USE_CLEARCOAT\\n\\t\\tfloat clearcoat;\\n\\t\\tfloat clearcoatRoughness;\\n\\t\\tvec3 clearcoatF0;\\n\\t\\tfloat clearcoatF90;\\n\\t#endif\\n\\n\\t#ifdef USE_SHEEN\\n\\t\\tvec3 sheenTint;\\n\\t\\tfloat sheenRoughness;\\n\\t#endif\\n\\n};\\n\\n// temporary\\nvec3 clearcoatSpecular = vec3( 0.0 );\\n\\n// Analytical approximation of the DFG LUT, one half of the\\n// split-sum approximation used in indirect specular lighting.\\n// via 'environmentBRDF' from \\\\\\\"Physically Based Shading on Mobile\\\\\\\"\\n// https://www.unrealengine.com/blog/physically-based-shading-on-mobile\\nvec2 DFGApprox( const in vec3 normal, const in vec3 viewDir, const in float roughness ) {\\n\\n\\tfloat dotNV = saturate( dot( normal, viewDir ) );\\n\\n\\tconst vec4 c0 = vec4( - 1, - 0.0275, - 0.572, 0.022 );\\n\\n\\tconst vec4 c1 = vec4( 1, 0.0425, 1.04, - 0.04 );\\n\\n\\tvec4 r = roughness * c0 + c1;\\n\\n\\tfloat a004 = min( r.x * r.x, exp2( - 9.28 * dotNV ) ) * r.x + r.y;\\n\\n\\tvec2 fab = vec2( - 1.04, 1.04 ) * a004 + r.zw;\\n\\n\\treturn fab;\\n\\n}\\n\\nvec3 EnvironmentBRDF( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness ) {\\n\\n\\tvec2 fab = DFGApprox( normal, viewDir, roughness );\\n\\n\\treturn specularColor * fab.x + specularF90 * fab.y;\\n\\n}\\n\\n// Fdez-Ag\\\\xFCera's \\\\\\\"Multiple-Scattering Microfacet Model for Real-Time Image Based Lighting\\\\\\\"\\n// Approximates multiscattering in order to preserve energy.\\n// http://www.jcgt.org/published/0008/01/03/\\nvoid computeMultiscattering( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness, inout vec3 singleScatter, inout vec3 multiScatter ) {\\n\\n\\tvec2 fab = DFGApprox( normal, viewDir, roughness );\\n\\n\\tvec3 FssEss = specularColor * fab.x + specularF90 * fab.y;\\n\\n\\tfloat Ess = fab.x + fab.y;\\n\\tfloat Ems = 1.0 - Ess;\\n\\n\\tvec3 Favg = specularColor + ( 1.0 - specularColor ) * 0.047619; // 1/21\\n\\tvec3 Fms = FssEss * Favg / ( 1.0 - Ems * Favg );\\n\\n\\tsingleScatter += FssEss;\\n\\tmultiScatter += Fms * Ems;\\n\\n}\\n\\n#if NUM_RECT_AREA_LIGHTS > 0\\n\\n\\tvoid RE_Direct_RectArea_Physical( const in RectAreaLight rectAreaLight, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\n\\n\\t\\tvec3 normal = geometry.normal;\\n\\t\\tvec3 viewDir = geometry.viewDir;\\n\\t\\tvec3 position = geometry.position;\\n\\t\\tvec3 lightPos = rectAreaLight.position;\\n\\t\\tvec3 halfWidth = rectAreaLight.halfWidth;\\n\\t\\tvec3 halfHeight = rectAreaLight.halfHeight;\\n\\t\\tvec3 lightColor = rectAreaLight.color;\\n\\t\\tfloat roughness = material.roughness;\\n\\n\\t\\tvec3 rectCoords[ 4 ];\\n\\t\\trectCoords[ 0 ] = lightPos + halfWidth - halfHeight; // counterclockwise; light shines in local neg z direction\\n\\t\\trectCoords[ 1 ] = lightPos - halfWidth - halfHeight;\\n\\t\\trectCoords[ 2 ] = lightPos - halfWidth + halfHeight;\\n\\t\\trectCoords[ 3 ] = lightPos + halfWidth + halfHeight;\\n\\n\\t\\tvec2 uv = LTC_Uv( normal, viewDir, roughness );\\n\\n\\t\\tvec4 t1 = texture2D( ltc_1, uv );\\n\\t\\tvec4 t2 = texture2D( ltc_2, uv );\\n\\n\\t\\tmat3 mInv = mat3(\\n\\t\\t\\tvec3( t1.x, 0, t1.y ),\\n\\t\\t\\tvec3( 0, 1, 0 ),\\n\\t\\t\\tvec3( t1.z, 0, t1.w )\\n\\t\\t);\\n\\n\\t\\t// LTC Fresnel Approximation by Stephen Hill\\n\\t\\t// http://blog.selfshadow.com/publications/s2016-advances/s2016_ltc_fresnel.pdf\\n\\t\\tvec3 fresnel = ( material.specularColor * t2.x + ( vec3( 1.0 ) - material.specularColor ) * t2.y );\\n\\n\\t\\treflectedLight.directSpecular += lightColor * fresnel * LTC_Evaluate( normal, viewDir, position, mInv, rectCoords );\\n\\n\\t\\treflectedLight.directDiffuse += lightColor * material.diffuseColor * LTC_Evaluate( normal, viewDir, position, mat3( 1.0 ), rectCoords );\\n\\n\\t}\\n\\n#endif\\n\\nvoid RE_Direct_Physical( const in IncidentLight directLight, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\n\\n\\tfloat dotNL = saturate( dot( geometry.normal, directLight.direction ) );\\n\\n\\tvec3 irradiance = dotNL * directLight.color;\\n\\n\\t#ifdef USE_CLEARCOAT\\n\\n\\t\\tfloat dotNLcc = saturate( dot( geometry.clearcoatNormal, directLight.direction ) );\\n\\n\\t\\tvec3 ccIrradiance = dotNLcc * directLight.color;\\n\\n\\t\\tclearcoatSpecular += ccIrradiance * BRDF_GGX( directLight.direction, geometry.viewDir, geometry.clearcoatNormal, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );\\n\\n\\t#endif\\n\\n\\t#ifdef USE_SHEEN\\n\\n\\t\\treflectedLight.directSpecular += irradiance * BRDF_Sheen( directLight.direction, geometry.viewDir, geometry.normal, material.sheenTint, material.sheenRoughness );\\n\\n\\t#endif\\n\\n\\treflectedLight.directSpecular += irradiance * BRDF_GGX( directLight.direction, geometry.viewDir, geometry.normal, material.specularColor, material.specularF90, material.roughness );\\n\\n\\n\\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\n}\\n\\nvoid RE_IndirectDiffuse_Physical( const in vec3 irradiance, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\\n\\n\\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\\n\\n}\\n\\nvoid RE_IndirectSpecular_Physical( const in vec3 radiance, const in vec3 irradiance, const in vec3 clearcoatRadiance, const in GeometricContext geometry, const in PhysicalMaterial material, inout ReflectedLight reflectedLight) {\\n\\n\\t#ifdef USE_CLEARCOAT\\n\\n\\t\\tclearcoatSpecular += clearcoatRadiance * EnvironmentBRDF( geometry.clearcoatNormal, geometry.viewDir, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );\\n\\n\\t#endif\\n\\n\\t// Both indirect specular and indirect diffuse light accumulate here\\n\\n\\tvec3 singleScattering = vec3( 0.0 );\\n\\tvec3 multiScattering = vec3( 0.0 );\\n\\tvec3 cosineWeightedIrradiance = irradiance * RECIPROCAL_PI;\\n\\n\\tcomputeMultiscattering( geometry.normal, geometry.viewDir, material.specularColor, material.specularF90, material.roughness, singleScattering, multiScattering );\\n\\n\\tvec3 diffuse = material.diffuseColor * ( 1.0 - ( singleScattering + multiScattering ) );\\n\\n\\treflectedLight.indirectSpecular += radiance * singleScattering;\\n\\treflectedLight.indirectSpecular += multiScattering * cosineWeightedIrradiance;\\n\\n\\treflectedLight.indirectDiffuse += diffuse * cosineWeightedIrradiance;\\n\\n}\\n\\n#define RE_Direct\\t\\t\\t\\tRE_Direct_Physical\\n#define RE_Direct_RectArea\\t\\tRE_Direct_RectArea_Physical\\n#define RE_IndirectDiffuse\\t\\tRE_IndirectDiffuse_Physical\\n#define RE_IndirectSpecular\\t\\tRE_IndirectSpecular_Physical\\n\\n// ref: https://seblagarde.files.wordpress.com/2015/07/course_notes_moving_frostbite_to_pbr_v32.pdf\\nfloat computeSpecularOcclusion( const in float dotNV, const in float ambientOcclusion, const in float roughness ) {\\n\\n\\treturn saturate( pow( dotNV + ambientOcclusion, exp2( - 16.0 * roughness - 1.0 ) ) - 1.0 + ambientOcclusion );\\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_fragment_begin.glsl.js\\nvar lights_fragment_begin_glsl_default = `\\n/**\\n * This is a template that can be used to light a material, it uses pluggable\\n * RenderEquations (RE)for specific lighting scenarios.\\n *\\n * Instructions for use:\\n * - Ensure that both RE_Direct, RE_IndirectDiffuse and RE_IndirectSpecular are defined\\n * - If you have defined an RE_IndirectSpecular, you need to also provide a Material_LightProbeLOD. <---- ???\\n * - Create a material parameter that is to be passed as the third parameter to your lighting functions.\\n *\\n * TODO:\\n * - Add area light support.\\n * - Add sphere light support.\\n * - Add diffuse light probe (irradiance cubemap) support.\\n */\\n\\nGeometricContext geometry;\\n\\ngeometry.position = - vViewPosition;\\ngeometry.normal = normal;\\ngeometry.viewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( vViewPosition );\\n\\n#ifdef USE_CLEARCOAT\\n\\n\\tgeometry.clearcoatNormal = clearcoatNormal;\\n\\n#endif\\n\\nIncidentLight directLight;\\n\\n#if ( NUM_POINT_LIGHTS > 0 ) && defined( RE_Direct )\\n\\n\\tPointLight pointLight;\\n\\t#if defined( USE_SHADOWMAP ) && NUM_POINT_LIGHT_SHADOWS > 0\\n\\tPointLightShadow pointLightShadow;\\n\\t#endif\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\\n\\n\\t\\tpointLight = pointLights[ i ];\\n\\n\\t\\tgetPointLightInfo( pointLight, geometry, directLight );\\n\\n\\t\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_POINT_LIGHT_SHADOWS )\\n\\t\\tpointLightShadow = pointLightShadows[ i ];\\n\\t\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getPointShadow( pointShadowMap[ i ], pointLightShadow.shadowMapSize, pointLightShadow.shadowBias, pointLightShadow.shadowRadius, vPointShadowCoord[ i ], pointLightShadow.shadowCameraNear, pointLightShadow.shadowCameraFar ) : 1.0;\\n\\t\\t#endif\\n\\n\\t\\tRE_Direct( directLight, geometry, material, reflectedLight );\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n#endif\\n\\n#if ( NUM_SPOT_LIGHTS > 0 ) && defined( RE_Direct )\\n\\n\\tSpotLight spotLight;\\n\\t#if defined( USE_SHADOWMAP ) && NUM_SPOT_LIGHT_SHADOWS > 0\\n\\tSpotLightShadow spotLightShadow;\\n\\t#endif\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\\n\\n\\t\\tspotLight = spotLights[ i ];\\n\\n\\t\\tgetSpotLightInfo( spotLight, geometry, directLight );\\n\\n\\t\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\\n\\t\\tspotLightShadow = spotLightShadows[ i ];\\n\\t\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getShadow( spotShadowMap[ i ], spotLightShadow.shadowMapSize, spotLightShadow.shadowBias, spotLightShadow.shadowRadius, vSpotShadowCoord[ i ] ) : 1.0;\\n\\t\\t#endif\\n\\n\\t\\tRE_Direct( directLight, geometry, material, reflectedLight );\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n#endif\\n\\n#if ( NUM_DIR_LIGHTS > 0 ) && defined( RE_Direct )\\n\\n\\tDirectionalLight directionalLight;\\n\\t#if defined( USE_SHADOWMAP ) && NUM_DIR_LIGHT_SHADOWS > 0\\n\\tDirectionalLightShadow directionalLightShadow;\\n\\t#endif\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\\n\\n\\t\\tdirectionalLight = directionalLights[ i ];\\n\\n\\t\\tgetDirectionalLightInfo( directionalLight, geometry, directLight );\\n\\n\\t\\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_DIR_LIGHT_SHADOWS )\\n\\t\\tdirectionalLightShadow = directionalLightShadows[ i ];\\n\\t\\tdirectLight.color *= all( bvec2( directLight.visible, receiveShadow ) ) ? getShadow( directionalShadowMap[ i ], directionalLightShadow.shadowMapSize, directionalLightShadow.shadowBias, directionalLightShadow.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\\n\\t\\t#endif\\n\\n\\t\\tRE_Direct( directLight, geometry, material, reflectedLight );\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n#endif\\n\\n#if ( NUM_RECT_AREA_LIGHTS > 0 ) && defined( RE_Direct_RectArea )\\n\\n\\tRectAreaLight rectAreaLight;\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_RECT_AREA_LIGHTS; i ++ ) {\\n\\n\\t\\trectAreaLight = rectAreaLights[ i ];\\n\\t\\tRE_Direct_RectArea( rectAreaLight, geometry, material, reflectedLight );\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n#endif\\n\\n#if defined( RE_IndirectDiffuse )\\n\\n\\tvec3 iblIrradiance = vec3( 0.0 );\\n\\n\\tvec3 irradiance = getAmbientLightIrradiance( ambientLightColor );\\n\\n\\tirradiance += getLightProbeIrradiance( lightProbe, geometry.normal );\\n\\n\\t#if ( NUM_HEMI_LIGHTS > 0 )\\n\\n\\t\\t#pragma unroll_loop_start\\n\\t\\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\\n\\n\\t\\t\\tirradiance += getHemisphereLightIrradiance( hemisphereLights[ i ], geometry.normal );\\n\\n\\t\\t}\\n\\t\\t#pragma unroll_loop_end\\n\\n\\t#endif\\n\\n#endif\\n\\n#if defined( RE_IndirectSpecular )\\n\\n\\tvec3 radiance = vec3( 0.0 );\\n\\tvec3 clearcoatRadiance = vec3( 0.0 );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_fragment_maps.glsl.js\\nvar lights_fragment_maps_glsl_default = `\\n#if defined( RE_IndirectDiffuse )\\n\\n\\t#ifdef USE_LIGHTMAP\\n\\n\\t\\tvec4 lightMapTexel = texture2D( lightMap, vUv2 );\\n\\t\\tvec3 lightMapIrradiance = lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\n\\n\\t\\t#ifndef PHYSICALLY_CORRECT_LIGHTS\\n\\n\\t\\t\\tlightMapIrradiance *= PI;\\n\\n\\t\\t#endif\\n\\n\\t\\tirradiance += lightMapIrradiance;\\n\\n\\t#endif\\n\\n\\t#if defined( USE_ENVMAP ) && defined( STANDARD ) && defined( ENVMAP_TYPE_CUBE_UV )\\n\\n\\t\\tiblIrradiance += getIBLIrradiance( geometry.normal );\\n\\n\\t#endif\\n\\n#endif\\n\\n#if defined( USE_ENVMAP ) && defined( RE_IndirectSpecular )\\n\\n\\tradiance += getIBLRadiance( geometry.viewDir, geometry.normal, material.roughness );\\n\\n\\t#ifdef USE_CLEARCOAT\\n\\n\\t\\tclearcoatRadiance += getIBLRadiance( geometry.viewDir, geometry.clearcoatNormal, material.clearcoatRoughness );\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/lights_fragment_end.glsl.js\\nvar lights_fragment_end_glsl_default = `\\n#if defined( RE_IndirectDiffuse )\\n\\n\\tRE_IndirectDiffuse( irradiance, geometry, material, reflectedLight );\\n\\n#endif\\n\\n#if defined( RE_IndirectSpecular )\\n\\n\\tRE_IndirectSpecular( radiance, iblIrradiance, clearcoatRadiance, geometry, material, reflectedLight );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/logdepthbuf_fragment.glsl.js\\nvar logdepthbuf_fragment_glsl_default = `\\n#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )\\n\\n\\t// Doing a strict comparison with == 1.0 can cause noise artifacts\\n\\t// on some platforms. See issue #17623.\\n\\tgl_FragDepthEXT = vIsPerspective == 0.0 ? gl_FragCoord.z : log2( vFragDepth ) * logDepthBufFC * 0.5;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/logdepthbuf_pars_fragment.glsl.js\\nvar logdepthbuf_pars_fragment_glsl_default = `\\n#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )\\n\\n\\tuniform float logDepthBufFC;\\n\\tvarying float vFragDepth;\\n\\tvarying float vIsPerspective;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/logdepthbuf_pars_vertex.glsl.js\\nvar logdepthbuf_pars_vertex_glsl_default = `\\n#ifdef USE_LOGDEPTHBUF\\n\\n\\t#ifdef USE_LOGDEPTHBUF_EXT\\n\\n\\t\\tvarying float vFragDepth;\\n\\t\\tvarying float vIsPerspective;\\n\\n\\t#else\\n\\n\\t\\tuniform float logDepthBufFC;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/logdepthbuf_vertex.glsl.js\\nvar logdepthbuf_vertex_glsl_default = `\\n#ifdef USE_LOGDEPTHBUF\\n\\n\\t#ifdef USE_LOGDEPTHBUF_EXT\\n\\n\\t\\tvFragDepth = 1.0 + gl_Position.w;\\n\\t\\tvIsPerspective = float( isPerspectiveMatrix( projectionMatrix ) );\\n\\n\\t#else\\n\\n\\t\\tif ( isPerspectiveMatrix( projectionMatrix ) ) {\\n\\n\\t\\t\\tgl_Position.z = log2( max( EPSILON, gl_Position.w + 1.0 ) ) * logDepthBufFC - 1.0;\\n\\n\\t\\t\\tgl_Position.z *= gl_Position.w;\\n\\n\\t\\t}\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/map_fragment.glsl.js\\nvar map_fragment_glsl_default = `\\n#ifdef USE_MAP\\n\\n\\tvec4 texelColor = texture2D( map, vUv );\\n\\n\\ttexelColor = mapTexelToLinear( texelColor );\\n\\tdiffuseColor *= texelColor;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/map_pars_fragment.glsl.js\\nvar map_pars_fragment_glsl_default = `\\n#ifdef USE_MAP\\n\\n\\tuniform sampler2D map;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/map_particle_fragment.glsl.js\\nvar map_particle_fragment_glsl_default = `\\n#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\\n\\n\\tvec2 uv = ( uvTransform * vec3( gl_PointCoord.x, 1.0 - gl_PointCoord.y, 1 ) ).xy;\\n\\n#endif\\n\\n#ifdef USE_MAP\\n\\n\\tvec4 mapTexel = texture2D( map, uv );\\n\\tdiffuseColor *= mapTexelToLinear( mapTexel );\\n\\n#endif\\n\\n#ifdef USE_ALPHAMAP\\n\\n\\tdiffuseColor.a *= texture2D( alphaMap, uv ).g;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/map_particle_pars_fragment.glsl.js\\nvar map_particle_pars_fragment_glsl_default = `\\n#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\\n\\n\\tuniform mat3 uvTransform;\\n\\n#endif\\n\\n#ifdef USE_MAP\\n\\n\\tuniform sampler2D map;\\n\\n#endif\\n\\n#ifdef USE_ALPHAMAP\\n\\n\\tuniform sampler2D alphaMap;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/metalnessmap_fragment.glsl.js\\nvar metalnessmap_fragment_glsl_default = `\\nfloat metalnessFactor = metalness;\\n\\n#ifdef USE_METALNESSMAP\\n\\n\\tvec4 texelMetalness = texture2D( metalnessMap, vUv );\\n\\n\\t// reads channel B, compatible with a combined OcclusionRoughnessMetallic (RGB) texture\\n\\tmetalnessFactor *= texelMetalness.b;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/metalnessmap_pars_fragment.glsl.js\\nvar metalnessmap_pars_fragment_glsl_default = `\\n#ifdef USE_METALNESSMAP\\n\\n\\tuniform sampler2D metalnessMap;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/morphnormal_vertex.glsl.js\\nvar morphnormal_vertex_glsl_default = `\\n#ifdef USE_MORPHNORMALS\\n\\n\\t// morphTargetBaseInfluence is set based on BufferGeometry.morphTargetsRelative value:\\n\\t// When morphTargetsRelative is false, this is set to 1 - sum(influences); this results in normal = sum((target - base) * influence)\\n\\t// When morphTargetsRelative is true, this is set to 1; as a result, all morph targets are simply added to the base after weighting\\n\\tobjectNormal *= morphTargetBaseInfluence;\\n\\n\\t#ifdef MORPHTARGETS_TEXTURE\\n\\n\\t\\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\\n\\n\\t\\t\\tif ( morphTargetInfluences[ i ] > 0.0 ) objectNormal += getMorph( gl_VertexID, i, 1, 2 ) * morphTargetInfluences[ i ];\\n\\n\\t\\t}\\n\\n\\t#else\\n\\n\\t\\tobjectNormal += morphNormal0 * morphTargetInfluences[ 0 ];\\n\\t\\tobjectNormal += morphNormal1 * morphTargetInfluences[ 1 ];\\n\\t\\tobjectNormal += morphNormal2 * morphTargetInfluences[ 2 ];\\n\\t\\tobjectNormal += morphNormal3 * morphTargetInfluences[ 3 ];\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/morphtarget_pars_vertex.glsl.js\\nvar morphtarget_pars_vertex_glsl_default = `\\n#ifdef USE_MORPHTARGETS\\n\\n\\tuniform float morphTargetBaseInfluence;\\n\\n\\t#ifdef MORPHTARGETS_TEXTURE\\n\\n\\t\\tuniform float morphTargetInfluences[ MORPHTARGETS_COUNT ];\\n\\t\\tuniform sampler2DArray morphTargetsTexture;\\n\\t\\tuniform vec2 morphTargetsTextureSize;\\n\\n\\t\\tvec3 getMorph( const in int vertexIndex, const in int morphTargetIndex, const in int offset, const in int stride ) {\\n\\n\\t\\t\\tfloat texelIndex = float( vertexIndex * stride + offset );\\n\\t\\t\\tfloat y = floor( texelIndex / morphTargetsTextureSize.x );\\n\\t\\t\\tfloat x = texelIndex - y * morphTargetsTextureSize.x;\\n\\n\\t\\t\\tvec3 morphUV = vec3( ( x + 0.5 ) / morphTargetsTextureSize.x, y / morphTargetsTextureSize.y, morphTargetIndex );\\n\\t\\t\\treturn texture( morphTargetsTexture, morphUV ).xyz;\\n\\n\\t\\t}\\n\\n\\t#else\\n\\n\\t\\t#ifndef USE_MORPHNORMALS\\n\\n\\t\\t\\tuniform float morphTargetInfluences[ 8 ];\\n\\n\\t\\t#else\\n\\n\\t\\t\\tuniform float morphTargetInfluences[ 4 ];\\n\\n\\t\\t#endif\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/morphtarget_vertex.glsl.js\\nvar morphtarget_vertex_glsl_default = `\\n#ifdef USE_MORPHTARGETS\\n\\n\\t// morphTargetBaseInfluence is set based on BufferGeometry.morphTargetsRelative value:\\n\\t// When morphTargetsRelative is false, this is set to 1 - sum(influences); this results in position = sum((target - base) * influence)\\n\\t// When morphTargetsRelative is true, this is set to 1; as a result, all morph targets are simply added to the base after weighting\\n\\ttransformed *= morphTargetBaseInfluence;\\n\\n\\t#ifdef MORPHTARGETS_TEXTURE\\n\\n\\t\\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\\n\\n\\t\\t\\t#ifndef USE_MORPHNORMALS\\n\\n\\t\\t\\t\\tif ( morphTargetInfluences[ i ] > 0.0 ) transformed += getMorph( gl_VertexID, i, 0, 1 ) * morphTargetInfluences[ i ];\\n\\n\\t\\t\\t#else\\n\\n\\t\\t\\t\\tif ( morphTargetInfluences[ i ] > 0.0 ) transformed += getMorph( gl_VertexID, i, 0, 2 ) * morphTargetInfluences[ i ];\\n\\n\\t\\t\\t#endif\\n\\n\\t\\t}\\n\\n\\t#else\\n\\n\\t\\ttransformed += morphTarget0 * morphTargetInfluences[ 0 ];\\n\\t\\ttransformed += morphTarget1 * morphTargetInfluences[ 1 ];\\n\\t\\ttransformed += morphTarget2 * morphTargetInfluences[ 2 ];\\n\\t\\ttransformed += morphTarget3 * morphTargetInfluences[ 3 ];\\n\\n\\t\\t#ifndef USE_MORPHNORMALS\\n\\n\\t\\t\\ttransformed += morphTarget4 * morphTargetInfluences[ 4 ];\\n\\t\\t\\ttransformed += morphTarget5 * morphTargetInfluences[ 5 ];\\n\\t\\t\\ttransformed += morphTarget6 * morphTargetInfluences[ 6 ];\\n\\t\\t\\ttransformed += morphTarget7 * morphTargetInfluences[ 7 ];\\n\\n\\t\\t#endif\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/normal_fragment_begin.glsl.js\\nvar normal_fragment_begin_glsl_default = `\\nfloat faceDirection = gl_FrontFacing ? 1.0 : - 1.0;\\n\\n#ifdef FLAT_SHADED\\n\\n\\t// Workaround for Adreno GPUs not able to do dFdx( vViewPosition )\\n\\n\\tvec3 fdx = vec3( dFdx( vViewPosition.x ), dFdx( vViewPosition.y ), dFdx( vViewPosition.z ) );\\n\\tvec3 fdy = vec3( dFdy( vViewPosition.x ), dFdy( vViewPosition.y ), dFdy( vViewPosition.z ) );\\n\\tvec3 normal = normalize( cross( fdx, fdy ) );\\n\\n#else\\n\\n\\tvec3 normal = normalize( vNormal );\\n\\n\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\tnormal = normal * faceDirection;\\n\\n\\t#endif\\n\\n\\t#ifdef USE_TANGENT\\n\\n\\t\\tvec3 tangent = normalize( vTangent );\\n\\t\\tvec3 bitangent = normalize( vBitangent );\\n\\n\\t\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\t\\ttangent = tangent * faceDirection;\\n\\t\\t\\tbitangent = bitangent * faceDirection;\\n\\n\\t\\t#endif\\n\\n\\t\\t#if defined( TANGENTSPACE_NORMALMAP ) || defined( USE_CLEARCOAT_NORMALMAP )\\n\\n\\t\\t\\tmat3 vTBN = mat3( tangent, bitangent, normal );\\n\\n\\t\\t#endif\\n\\n\\t#endif\\n\\n#endif\\n\\n// non perturbed normal for clearcoat among others\\n\\nvec3 geometryNormal = normal;\\n\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/normal_fragment_maps.glsl.js\\nvar normal_fragment_maps_glsl_default = `\\n\\n#ifdef OBJECTSPACE_NORMALMAP\\n\\n\\tnormal = texture2D( normalMap, vUv ).xyz * 2.0 - 1.0; // overrides both flatShading and attribute normals\\n\\n\\t#ifdef FLIP_SIDED\\n\\n\\t\\tnormal = - normal;\\n\\n\\t#endif\\n\\n\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\tnormal = normal * faceDirection;\\n\\n\\t#endif\\n\\n\\tnormal = normalize( normalMatrix * normal );\\n\\n#elif defined( TANGENTSPACE_NORMALMAP )\\n\\n\\tvec3 mapN = texture2D( normalMap, vUv ).xyz * 2.0 - 1.0;\\n\\tmapN.xy *= normalScale;\\n\\n\\t#ifdef USE_TANGENT\\n\\n\\t\\tnormal = normalize( vTBN * mapN );\\n\\n\\t#else\\n\\n\\t\\tnormal = perturbNormal2Arb( - vViewPosition, normal, mapN, faceDirection );\\n\\n\\t#endif\\n\\n#elif defined( USE_BUMPMAP )\\n\\n\\tnormal = perturbNormalArb( - vViewPosition, normal, dHdxy_fwd(), faceDirection );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/normal_pars_fragment.glsl.js\\nvar normal_pars_fragment_glsl_default = `\\n#ifndef FLAT_SHADED\\n\\n\\tvarying vec3 vNormal;\\n\\n\\t#ifdef USE_TANGENT\\n\\n\\t\\tvarying vec3 vTangent;\\n\\t\\tvarying vec3 vBitangent;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/normal_pars_vertex.glsl.js\\nvar normal_pars_vertex_glsl_default = `\\n#ifndef FLAT_SHADED\\n\\n\\tvarying vec3 vNormal;\\n\\n\\t#ifdef USE_TANGENT\\n\\n\\t\\tvarying vec3 vTangent;\\n\\t\\tvarying vec3 vBitangent;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/normal_vertex.glsl.js\\nvar normal_vertex_glsl_default = `\\n#ifndef FLAT_SHADED // normal is computed with derivatives when FLAT_SHADED\\n\\n\\tvNormal = normalize( transformedNormal );\\n\\n\\t#ifdef USE_TANGENT\\n\\n\\t\\tvTangent = normalize( transformedTangent );\\n\\t\\tvBitangent = normalize( cross( vNormal, vTangent ) * tangent.w );\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/normalmap_pars_fragment.glsl.js\\nvar normalmap_pars_fragment_glsl_default = `\\n#ifdef USE_NORMALMAP\\n\\n\\tuniform sampler2D normalMap;\\n\\tuniform vec2 normalScale;\\n\\n#endif\\n\\n#ifdef OBJECTSPACE_NORMALMAP\\n\\n\\tuniform mat3 normalMatrix;\\n\\n#endif\\n\\n#if ! defined ( USE_TANGENT ) && ( defined ( TANGENTSPACE_NORMALMAP ) || defined ( USE_CLEARCOAT_NORMALMAP ) )\\n\\n\\t// Normal Mapping Without Precomputed Tangents\\n\\t// http://www.thetenthplanet.de/archives/1180\\n\\n\\tvec3 perturbNormal2Arb( vec3 eye_pos, vec3 surf_norm, vec3 mapN, float faceDirection ) {\\n\\n\\t\\t// Workaround for Adreno 3XX dFd*( vec3 ) bug. See #9988\\n\\n\\t\\tvec3 q0 = vec3( dFdx( eye_pos.x ), dFdx( eye_pos.y ), dFdx( eye_pos.z ) );\\n\\t\\tvec3 q1 = vec3( dFdy( eye_pos.x ), dFdy( eye_pos.y ), dFdy( eye_pos.z ) );\\n\\t\\tvec2 st0 = dFdx( vUv.st );\\n\\t\\tvec2 st1 = dFdy( vUv.st );\\n\\n\\t\\tvec3 N = surf_norm; // normalized\\n\\n\\t\\tvec3 q1perp = cross( q1, N );\\n\\t\\tvec3 q0perp = cross( N, q0 );\\n\\n\\t\\tvec3 T = q1perp * st0.x + q0perp * st1.x;\\n\\t\\tvec3 B = q1perp * st0.y + q0perp * st1.y;\\n\\n\\t\\tfloat det = max( dot( T, T ), dot( B, B ) );\\n\\t\\tfloat scale = ( det == 0.0 ) ? 0.0 : faceDirection * inversesqrt( det );\\n\\n\\t\\treturn normalize( T * ( mapN.x * scale ) + B * ( mapN.y * scale ) + N * mapN.z );\\n\\n\\t}\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/clearcoat_normal_fragment_begin.glsl.js\\nvar clearcoat_normal_fragment_begin_glsl_default = `\\n#ifdef USE_CLEARCOAT\\n\\n\\tvec3 clearcoatNormal = geometryNormal;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/clearcoat_normal_fragment_maps.glsl.js\\nvar clearcoat_normal_fragment_maps_glsl_default = `\\n#ifdef USE_CLEARCOAT_NORMALMAP\\n\\n\\tvec3 clearcoatMapN = texture2D( clearcoatNormalMap, vUv ).xyz * 2.0 - 1.0;\\n\\tclearcoatMapN.xy *= clearcoatNormalScale;\\n\\n\\t#ifdef USE_TANGENT\\n\\n\\t\\tclearcoatNormal = normalize( vTBN * clearcoatMapN );\\n\\n\\t#else\\n\\n\\t\\tclearcoatNormal = perturbNormal2Arb( - vViewPosition, clearcoatNormal, clearcoatMapN, faceDirection );\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/clearcoat_pars_fragment.glsl.js\\nvar clearcoat_pars_fragment_glsl_default = `\\n\\n#ifdef USE_CLEARCOATMAP\\n\\n\\tuniform sampler2D clearcoatMap;\\n\\n#endif\\n\\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\\n\\n\\tuniform sampler2D clearcoatRoughnessMap;\\n\\n#endif\\n\\n#ifdef USE_CLEARCOAT_NORMALMAP\\n\\n\\tuniform sampler2D clearcoatNormalMap;\\n\\tuniform vec2 clearcoatNormalScale;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/output_fragment.glsl.js\\nvar output_fragment_glsl_default = `\\n#ifdef OPAQUE\\ndiffuseColor.a = 1.0;\\n#endif\\n\\n// https://github.com/mrdoob/three.js/pull/22425\\n#ifdef USE_TRANSMISSION\\ndiffuseColor.a *= transmissionAlpha + 0.1;\\n#endif\\n\\ngl_FragColor = vec4( outgoingLight, diffuseColor.a );\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/packing.glsl.js\\nvar packing_glsl_default = `\\nvec3 packNormalToRGB( const in vec3 normal ) {\\n\\treturn normalize( normal ) * 0.5 + 0.5;\\n}\\n\\nvec3 unpackRGBToNormal( const in vec3 rgb ) {\\n\\treturn 2.0 * rgb.xyz - 1.0;\\n}\\n\\nconst float PackUpscale = 256. / 255.; // fraction -> 0..1 (including 1)\\nconst float UnpackDownscale = 255. / 256.; // 0..1 -> fraction (excluding 1)\\n\\nconst vec3 PackFactors = vec3( 256. * 256. * 256., 256. * 256., 256. );\\nconst vec4 UnpackFactors = UnpackDownscale / vec4( PackFactors, 1. );\\n\\nconst float ShiftRight8 = 1. / 256.;\\n\\nvec4 packDepthToRGBA( const in float v ) {\\n\\tvec4 r = vec4( fract( v * PackFactors ), v );\\n\\tr.yzw -= r.xyz * ShiftRight8; // tidy overflow\\n\\treturn r * PackUpscale;\\n}\\n\\nfloat unpackRGBAToDepth( const in vec4 v ) {\\n\\treturn dot( v, UnpackFactors );\\n}\\n\\nvec4 pack2HalfToRGBA( vec2 v ) {\\n\\tvec4 r = vec4( v.x, fract( v.x * 255.0 ), v.y, fract( v.y * 255.0 ) );\\n\\treturn vec4( r.x - r.y / 255.0, r.y, r.z - r.w / 255.0, r.w );\\n}\\n\\nvec2 unpackRGBATo2Half( vec4 v ) {\\n\\treturn vec2( v.x + ( v.y / 255.0 ), v.z + ( v.w / 255.0 ) );\\n}\\n\\n// NOTE: viewZ/eyeZ is < 0 when in front of the camera per OpenGL conventions\\n\\nfloat viewZToOrthographicDepth( const in float viewZ, const in float near, const in float far ) {\\n\\treturn ( viewZ + near ) / ( near - far );\\n}\\nfloat orthographicDepthToViewZ( const in float linearClipZ, const in float near, const in float far ) {\\n\\treturn linearClipZ * ( near - far ) - near;\\n}\\n\\n// NOTE: https://twitter.com/gonnavis/status/1377183786949959682\\n\\nfloat viewZToPerspectiveDepth( const in float viewZ, const in float near, const in float far ) {\\n\\treturn ( ( near + viewZ ) * far ) / ( ( far - near ) * viewZ );\\n}\\nfloat perspectiveDepthToViewZ( const in float invClipZ, const in float near, const in float far ) {\\n\\treturn ( near * far ) / ( ( far - near ) * invClipZ - far );\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/premultiplied_alpha_fragment.glsl.js\\nvar premultiplied_alpha_fragment_glsl_default = `\\n#ifdef PREMULTIPLIED_ALPHA\\n\\n\\t// Get get normal blending with premultipled, use with CustomBlending, OneFactor, OneMinusSrcAlphaFactor, AddEquation.\\n\\tgl_FragColor.rgb *= gl_FragColor.a;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/project_vertex.glsl.js\\nvar project_vertex_glsl_default = `\\nvec4 mvPosition = vec4( transformed, 1.0 );\\n\\n#ifdef USE_INSTANCING\\n\\n\\tmvPosition = instanceMatrix * mvPosition;\\n\\n#endif\\n\\nmvPosition = modelViewMatrix * mvPosition;\\n\\ngl_Position = projectionMatrix * mvPosition;\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/dithering_fragment.glsl.js\\nvar dithering_fragment_glsl_default = `\\n#ifdef DITHERING\\n\\n\\tgl_FragColor.rgb = dithering( gl_FragColor.rgb );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/dithering_pars_fragment.glsl.js\\nvar dithering_pars_fragment_glsl_default = `\\n#ifdef DITHERING\\n\\n\\t// based on https://www.shadertoy.com/view/MslGR8\\n\\tvec3 dithering( vec3 color ) {\\n\\t\\t//Calculate grid position\\n\\t\\tfloat grid_position = rand( gl_FragCoord.xy );\\n\\n\\t\\t//Shift the individual colors differently, thus making it even harder to see the dithering pattern\\n\\t\\tvec3 dither_shift_RGB = vec3( 0.25 / 255.0, -0.25 / 255.0, 0.25 / 255.0 );\\n\\n\\t\\t//modify shift acording to grid position.\\n\\t\\tdither_shift_RGB = mix( 2.0 * dither_shift_RGB, -2.0 * dither_shift_RGB, grid_position );\\n\\n\\t\\t//shift the color by dither_shift\\n\\t\\treturn color + dither_shift_RGB;\\n\\t}\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/roughnessmap_fragment.glsl.js\\nvar roughnessmap_fragment_glsl_default = `\\nfloat roughnessFactor = roughness;\\n\\n#ifdef USE_ROUGHNESSMAP\\n\\n\\tvec4 texelRoughness = texture2D( roughnessMap, vUv );\\n\\n\\t// reads channel G, compatible with a combined OcclusionRoughnessMetallic (RGB) texture\\n\\troughnessFactor *= texelRoughness.g;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/roughnessmap_pars_fragment.glsl.js\\nvar roughnessmap_pars_fragment_glsl_default = `\\n#ifdef USE_ROUGHNESSMAP\\n\\n\\tuniform sampler2D roughnessMap;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/shadowmap_pars_fragment.glsl.js\\nvar shadowmap_pars_fragment_glsl_default = `\\n#ifdef USE_SHADOWMAP\\n\\n\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\n\\n\\t\\tuniform sampler2D directionalShadowMap[ NUM_DIR_LIGHT_SHADOWS ];\\n\\t\\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\\n\\n\\t\\tstruct DirectionalLightShadow {\\n\\t\\t\\tfloat shadowBias;\\n\\t\\t\\tfloat shadowNormalBias;\\n\\t\\t\\tfloat shadowRadius;\\n\\t\\t\\tvec2 shadowMapSize;\\n\\t\\t};\\n\\n\\t\\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\\n\\n\\t#endif\\n\\n\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\n\\n\\t\\tuniform sampler2D spotShadowMap[ NUM_SPOT_LIGHT_SHADOWS ];\\n\\t\\tvarying vec4 vSpotShadowCoord[ NUM_SPOT_LIGHT_SHADOWS ];\\n\\n\\t\\tstruct SpotLightShadow {\\n\\t\\t\\tfloat shadowBias;\\n\\t\\t\\tfloat shadowNormalBias;\\n\\t\\t\\tfloat shadowRadius;\\n\\t\\t\\tvec2 shadowMapSize;\\n\\t\\t};\\n\\n\\t\\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\\n\\n\\t#endif\\n\\n\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\n\\n\\t\\tuniform sampler2D pointShadowMap[ NUM_POINT_LIGHT_SHADOWS ];\\n\\t\\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\\n\\n\\t\\tstruct PointLightShadow {\\n\\t\\t\\tfloat shadowBias;\\n\\t\\t\\tfloat shadowNormalBias;\\n\\t\\t\\tfloat shadowRadius;\\n\\t\\t\\tvec2 shadowMapSize;\\n\\t\\t\\tfloat shadowCameraNear;\\n\\t\\t\\tfloat shadowCameraFar;\\n\\t\\t};\\n\\n\\t\\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\\n\\n\\t#endif\\n\\n\\t/*\\n\\t#if NUM_RECT_AREA_LIGHTS > 0\\n\\n\\t\\t// TODO (abelnation): create uniforms for area light shadows\\n\\n\\t#endif\\n\\t*/\\n\\n\\tfloat texture2DCompare( sampler2D depths, vec2 uv, float compare ) {\\n\\n\\t\\treturn step( compare, unpackRGBAToDepth( texture2D( depths, uv ) ) );\\n\\n\\t}\\n\\n\\tvec2 texture2DDistribution( sampler2D shadow, vec2 uv ) {\\n\\n\\t\\treturn unpackRGBATo2Half( texture2D( shadow, uv ) );\\n\\n\\t}\\n\\n\\tfloat VSMShadow (sampler2D shadow, vec2 uv, float compare ){\\n\\n\\t\\tfloat occlusion = 1.0;\\n\\n\\t\\tvec2 distribution = texture2DDistribution( shadow, uv );\\n\\n\\t\\tfloat hard_shadow = step( compare , distribution.x ); // Hard Shadow\\n\\n\\t\\tif (hard_shadow != 1.0 ) {\\n\\n\\t\\t\\tfloat distance = compare - distribution.x ;\\n\\t\\t\\tfloat variance = max( 0.00000, distribution.y * distribution.y );\\n\\t\\t\\tfloat softness_probability = variance / (variance + distance * distance ); // Chebeyshevs inequality\\n\\t\\t\\tsoftness_probability = clamp( ( softness_probability - 0.3 ) / ( 0.95 - 0.3 ), 0.0, 1.0 ); // 0.3 reduces light bleed\\n\\t\\t\\tocclusion = clamp( max( hard_shadow, softness_probability ), 0.0, 1.0 );\\n\\n\\t\\t}\\n\\t\\treturn occlusion;\\n\\n\\t}\\n\\n\\tfloat getShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord ) {\\n\\n\\t\\tfloat shadow = 1.0;\\n\\n\\t\\tshadowCoord.xyz /= shadowCoord.w;\\n\\t\\tshadowCoord.z += shadowBias;\\n\\n\\t\\t// if ( something && something ) breaks ATI OpenGL shader compiler\\n\\t\\t// if ( all( something, something ) ) using this instead\\n\\n\\t\\tbvec4 inFrustumVec = bvec4 ( shadowCoord.x >= 0.0, shadowCoord.x <= 1.0, shadowCoord.y >= 0.0, shadowCoord.y <= 1.0 );\\n\\t\\tbool inFrustum = all( inFrustumVec );\\n\\n\\t\\tbvec2 frustumTestVec = bvec2( inFrustum, shadowCoord.z <= 1.0 );\\n\\n\\t\\tbool frustumTest = all( frustumTestVec );\\n\\n\\t\\tif ( frustumTest ) {\\n\\n\\t\\t#if defined( SHADOWMAP_TYPE_PCF )\\n\\n\\t\\t\\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\\n\\n\\t\\t\\tfloat dx0 = - texelSize.x * shadowRadius;\\n\\t\\t\\tfloat dy0 = - texelSize.y * shadowRadius;\\n\\t\\t\\tfloat dx1 = + texelSize.x * shadowRadius;\\n\\t\\t\\tfloat dy1 = + texelSize.y * shadowRadius;\\n\\t\\t\\tfloat dx2 = dx0 / 2.0;\\n\\t\\t\\tfloat dy2 = dy0 / 2.0;\\n\\t\\t\\tfloat dx3 = dx1 / 2.0;\\n\\t\\t\\tfloat dy3 = dy1 / 2.0;\\n\\n\\t\\t\\tshadow = (\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy0 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy0 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy0 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy2 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy2 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy2 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, 0.0 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, 0.0 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, 0.0 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, 0.0 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy3 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy3 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy3 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy1 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy1 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy1 ), shadowCoord.z )\\n\\t\\t\\t) * ( 1.0 / 17.0 );\\n\\n\\t\\t#elif defined( SHADOWMAP_TYPE_PCF_SOFT )\\n\\n\\t\\t\\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\\n\\t\\t\\tfloat dx = texelSize.x;\\n\\t\\t\\tfloat dy = texelSize.y;\\n\\n\\t\\t\\tvec2 uv = shadowCoord.xy;\\n\\t\\t\\tvec2 f = fract( uv * shadowMapSize + 0.5 );\\n\\t\\t\\tuv -= f * texelSize;\\n\\n\\t\\t\\tshadow = (\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, uv, shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, uv + vec2( dx, 0.0 ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, uv + vec2( 0.0, dy ), shadowCoord.z ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, uv + texelSize, shadowCoord.z ) +\\n\\t\\t\\t\\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, 0.0 ), shadowCoord.z ), \\n\\t\\t\\t\\t\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 0.0 ), shadowCoord.z ),\\n\\t\\t\\t\\t\\t f.x ) +\\n\\t\\t\\t\\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, dy ), shadowCoord.z ), \\n\\t\\t\\t\\t\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, dy ), shadowCoord.z ),\\n\\t\\t\\t\\t\\t f.x ) +\\n\\t\\t\\t\\tmix( texture2DCompare( shadowMap, uv + vec2( 0.0, -dy ), shadowCoord.z ), \\n\\t\\t\\t\\t\\t texture2DCompare( shadowMap, uv + vec2( 0.0, 2.0 * dy ), shadowCoord.z ),\\n\\t\\t\\t\\t\\t f.y ) +\\n\\t\\t\\t\\tmix( texture2DCompare( shadowMap, uv + vec2( dx, -dy ), shadowCoord.z ), \\n\\t\\t\\t\\t\\t texture2DCompare( shadowMap, uv + vec2( dx, 2.0 * dy ), shadowCoord.z ),\\n\\t\\t\\t\\t\\t f.y ) +\\n\\t\\t\\t\\tmix( mix( texture2DCompare( shadowMap, uv + vec2( -dx, -dy ), shadowCoord.z ), \\n\\t\\t\\t\\t\\t\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, -dy ), shadowCoord.z ),\\n\\t\\t\\t\\t\\t\\t f.x ),\\n\\t\\t\\t\\t\\t mix( texture2DCompare( shadowMap, uv + vec2( -dx, 2.0 * dy ), shadowCoord.z ), \\n\\t\\t\\t\\t\\t\\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 2.0 * dy ), shadowCoord.z ),\\n\\t\\t\\t\\t\\t\\t f.x ),\\n\\t\\t\\t\\t\\t f.y )\\n\\t\\t\\t) * ( 1.0 / 9.0 );\\n\\n\\t\\t#elif defined( SHADOWMAP_TYPE_VSM )\\n\\n\\t\\t\\tshadow = VSMShadow( shadowMap, shadowCoord.xy, shadowCoord.z );\\n\\n\\t\\t#else // no percentage-closer filtering:\\n\\n\\t\\t\\tshadow = texture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z );\\n\\n\\t\\t#endif\\n\\n\\t\\t}\\n\\n\\t\\treturn shadow;\\n\\n\\t}\\n\\n\\t// cubeToUV() maps a 3D direction vector suitable for cube texture mapping to a 2D\\n\\t// vector suitable for 2D texture mapping. This code uses the following layout for the\\n\\t// 2D texture:\\n\\t//\\n\\t// xzXZ\\n\\t// y Y\\n\\t//\\n\\t// Y - Positive y direction\\n\\t// y - Negative y direction\\n\\t// X - Positive x direction\\n\\t// x - Negative x direction\\n\\t// Z - Positive z direction\\n\\t// z - Negative z direction\\n\\t//\\n\\t// Source and test bed:\\n\\t// https://gist.github.com/tschw/da10c43c467ce8afd0c4\\n\\n\\tvec2 cubeToUV( vec3 v, float texelSizeY ) {\\n\\n\\t\\t// Number of texels to avoid at the edge of each square\\n\\n\\t\\tvec3 absV = abs( v );\\n\\n\\t\\t// Intersect unit cube\\n\\n\\t\\tfloat scaleToCube = 1.0 / max( absV.x, max( absV.y, absV.z ) );\\n\\t\\tabsV *= scaleToCube;\\n\\n\\t\\t// Apply scale to avoid seams\\n\\n\\t\\t// two texels less per square (one texel will do for NEAREST)\\n\\t\\tv *= scaleToCube * ( 1.0 - 2.0 * texelSizeY );\\n\\n\\t\\t// Unwrap\\n\\n\\t\\t// space: -1 ... 1 range for each square\\n\\t\\t//\\n\\t\\t// #X##\\t\\tdim := ( 4 , 2 )\\n\\t\\t// # #\\t\\tcenter := ( 1 , 1 )\\n\\n\\t\\tvec2 planar = v.xy;\\n\\n\\t\\tfloat almostATexel = 1.5 * texelSizeY;\\n\\t\\tfloat almostOne = 1.0 - almostATexel;\\n\\n\\t\\tif ( absV.z >= almostOne ) {\\n\\n\\t\\t\\tif ( v.z > 0.0 )\\n\\t\\t\\t\\tplanar.x = 4.0 - v.x;\\n\\n\\t\\t} else if ( absV.x >= almostOne ) {\\n\\n\\t\\t\\tfloat signX = sign( v.x );\\n\\t\\t\\tplanar.x = v.z * signX + 2.0 * signX;\\n\\n\\t\\t} else if ( absV.y >= almostOne ) {\\n\\n\\t\\t\\tfloat signY = sign( v.y );\\n\\t\\t\\tplanar.x = v.x + 2.0 * signY + 2.0;\\n\\t\\t\\tplanar.y = v.z * signY - 2.0;\\n\\n\\t\\t}\\n\\n\\t\\t// Transform to UV space\\n\\n\\t\\t// scale := 0.5 / dim\\n\\t\\t// translate := ( center + 0.5 ) / dim\\n\\t\\treturn vec2( 0.125, 0.25 ) * planar + vec2( 0.375, 0.75 );\\n\\n\\t}\\n\\n\\tfloat getPointShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord, float shadowCameraNear, float shadowCameraFar ) {\\n\\n\\t\\tvec2 texelSize = vec2( 1.0 ) / ( shadowMapSize * vec2( 4.0, 2.0 ) );\\n\\n\\t\\t// for point lights, the uniform @vShadowCoord is re-purposed to hold\\n\\t\\t// the vector from the light to the world-space position of the fragment.\\n\\t\\tvec3 lightToPosition = shadowCoord.xyz;\\n\\n\\t\\t// dp = normalized distance from light to fragment position\\n\\t\\tfloat dp = ( length( lightToPosition ) - shadowCameraNear ) / ( shadowCameraFar - shadowCameraNear ); // need to clamp?\\n\\t\\tdp += shadowBias;\\n\\n\\t\\t// bd3D = base direction 3D\\n\\t\\tvec3 bd3D = normalize( lightToPosition );\\n\\n\\t\\t#if defined( SHADOWMAP_TYPE_PCF ) || defined( SHADOWMAP_TYPE_PCF_SOFT ) || defined( SHADOWMAP_TYPE_VSM )\\n\\n\\t\\t\\tvec2 offset = vec2( - 1, 1 ) * shadowRadius * texelSize.y;\\n\\n\\t\\t\\treturn (\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyy, texelSize.y ), dp ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyy, texelSize.y ), dp ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyx, texelSize.y ), dp ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyx, texelSize.y ), dp ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxy, texelSize.y ), dp ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxy, texelSize.y ), dp ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxx, texelSize.y ), dp ) +\\n\\t\\t\\t\\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxx, texelSize.y ), dp )\\n\\t\\t\\t) * ( 1.0 / 9.0 );\\n\\n\\t\\t#else // no percentage-closer filtering\\n\\n\\t\\t\\treturn texture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp );\\n\\n\\t\\t#endif\\n\\n\\t}\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/shadowmap_pars_vertex.glsl.js\\nvar shadowmap_pars_vertex_glsl_default = `\\n#ifdef USE_SHADOWMAP\\n\\n\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\n\\n\\t\\tuniform mat4 directionalShadowMatrix[ NUM_DIR_LIGHT_SHADOWS ];\\n\\t\\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\\n\\n\\t\\tstruct DirectionalLightShadow {\\n\\t\\t\\tfloat shadowBias;\\n\\t\\t\\tfloat shadowNormalBias;\\n\\t\\t\\tfloat shadowRadius;\\n\\t\\t\\tvec2 shadowMapSize;\\n\\t\\t};\\n\\n\\t\\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\\n\\n\\t#endif\\n\\n\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\n\\n\\t\\tuniform mat4 spotShadowMatrix[ NUM_SPOT_LIGHT_SHADOWS ];\\n\\t\\tvarying vec4 vSpotShadowCoord[ NUM_SPOT_LIGHT_SHADOWS ];\\n\\n\\t\\tstruct SpotLightShadow {\\n\\t\\t\\tfloat shadowBias;\\n\\t\\t\\tfloat shadowNormalBias;\\n\\t\\t\\tfloat shadowRadius;\\n\\t\\t\\tvec2 shadowMapSize;\\n\\t\\t};\\n\\n\\t\\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\\n\\n\\t#endif\\n\\n\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\n\\n\\t\\tuniform mat4 pointShadowMatrix[ NUM_POINT_LIGHT_SHADOWS ];\\n\\t\\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\\n\\n\\t\\tstruct PointLightShadow {\\n\\t\\t\\tfloat shadowBias;\\n\\t\\t\\tfloat shadowNormalBias;\\n\\t\\t\\tfloat shadowRadius;\\n\\t\\t\\tvec2 shadowMapSize;\\n\\t\\t\\tfloat shadowCameraNear;\\n\\t\\t\\tfloat shadowCameraFar;\\n\\t\\t};\\n\\n\\t\\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\\n\\n\\t#endif\\n\\n\\t/*\\n\\t#if NUM_RECT_AREA_LIGHTS > 0\\n\\n\\t\\t// TODO (abelnation): uniforms for area light shadows\\n\\n\\t#endif\\n\\t*/\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/shadowmap_vertex.glsl.js\\nvar shadowmap_vertex_glsl_default = `\\n#ifdef USE_SHADOWMAP\\n\\n\\t#if NUM_DIR_LIGHT_SHADOWS > 0 || NUM_SPOT_LIGHT_SHADOWS > 0 || NUM_POINT_LIGHT_SHADOWS > 0\\n\\n\\t\\t// Offsetting the position used for querying occlusion along the world normal can be used to reduce shadow acne.\\n\\t\\tvec3 shadowWorldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\\n\\t\\tvec4 shadowWorldPosition;\\n\\n\\t#endif\\n\\n\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\\n\\n\\t\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * directionalLightShadows[ i ].shadowNormalBias, 0 );\\n\\t\\tvDirectionalShadowCoord[ i ] = directionalShadowMatrix[ i ] * shadowWorldPosition;\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n\\t#endif\\n\\n\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\\n\\n\\t\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * spotLightShadows[ i ].shadowNormalBias, 0 );\\n\\t\\tvSpotShadowCoord[ i ] = spotShadowMatrix[ i ] * shadowWorldPosition;\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n\\t#endif\\n\\n\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\\n\\n\\t\\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * pointLightShadows[ i ].shadowNormalBias, 0 );\\n\\t\\tvPointShadowCoord[ i ] = pointShadowMatrix[ i ] * shadowWorldPosition;\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n\\t#endif\\n\\n\\t/*\\n\\t#if NUM_RECT_AREA_LIGHTS > 0\\n\\n\\t\\t// TODO (abelnation): update vAreaShadowCoord with area light info\\n\\n\\t#endif\\n\\t*/\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/shadowmask_pars_fragment.glsl.js\\nvar shadowmask_pars_fragment_glsl_default = `\\nfloat getShadowMask() {\\n\\n\\tfloat shadow = 1.0;\\n\\n\\t#ifdef USE_SHADOWMAP\\n\\n\\t#if NUM_DIR_LIGHT_SHADOWS > 0\\n\\n\\tDirectionalLightShadow directionalLight;\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\\n\\n\\t\\tdirectionalLight = directionalLightShadows[ i ];\\n\\t\\tshadow *= receiveShadow ? getShadow( directionalShadowMap[ i ], directionalLight.shadowMapSize, directionalLight.shadowBias, directionalLight.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n\\t#endif\\n\\n\\t#if NUM_SPOT_LIGHT_SHADOWS > 0\\n\\n\\tSpotLightShadow spotLight;\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\\n\\n\\t\\tspotLight = spotLightShadows[ i ];\\n\\t\\tshadow *= receiveShadow ? getShadow( spotShadowMap[ i ], spotLight.shadowMapSize, spotLight.shadowBias, spotLight.shadowRadius, vSpotShadowCoord[ i ] ) : 1.0;\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n\\t#endif\\n\\n\\t#if NUM_POINT_LIGHT_SHADOWS > 0\\n\\n\\tPointLightShadow pointLight;\\n\\n\\t#pragma unroll_loop_start\\n\\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\\n\\n\\t\\tpointLight = pointLightShadows[ i ];\\n\\t\\tshadow *= receiveShadow ? getPointShadow( pointShadowMap[ i ], pointLight.shadowMapSize, pointLight.shadowBias, pointLight.shadowRadius, vPointShadowCoord[ i ], pointLight.shadowCameraNear, pointLight.shadowCameraFar ) : 1.0;\\n\\n\\t}\\n\\t#pragma unroll_loop_end\\n\\n\\t#endif\\n\\n\\t/*\\n\\t#if NUM_RECT_AREA_LIGHTS > 0\\n\\n\\t\\t// TODO (abelnation): update shadow for Area light\\n\\n\\t#endif\\n\\t*/\\n\\n\\t#endif\\n\\n\\treturn shadow;\\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/skinbase_vertex.glsl.js\\nvar skinbase_vertex_glsl_default = `\\n#ifdef USE_SKINNING\\n\\n\\tmat4 boneMatX = getBoneMatrix( skinIndex.x );\\n\\tmat4 boneMatY = getBoneMatrix( skinIndex.y );\\n\\tmat4 boneMatZ = getBoneMatrix( skinIndex.z );\\n\\tmat4 boneMatW = getBoneMatrix( skinIndex.w );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/skinning_pars_vertex.glsl.js\\nvar skinning_pars_vertex_glsl_default = `\\n#ifdef USE_SKINNING\\n\\n\\tuniform mat4 bindMatrix;\\n\\tuniform mat4 bindMatrixInverse;\\n\\n\\t#ifdef BONE_TEXTURE\\n\\n\\t\\tuniform highp sampler2D boneTexture;\\n\\t\\tuniform int boneTextureSize;\\n\\n\\t\\tmat4 getBoneMatrix( const in float i ) {\\n\\n\\t\\t\\tfloat j = i * 4.0;\\n\\t\\t\\tfloat x = mod( j, float( boneTextureSize ) );\\n\\t\\t\\tfloat y = floor( j / float( boneTextureSize ) );\\n\\n\\t\\t\\tfloat dx = 1.0 / float( boneTextureSize );\\n\\t\\t\\tfloat dy = 1.0 / float( boneTextureSize );\\n\\n\\t\\t\\ty = dy * ( y + 0.5 );\\n\\n\\t\\t\\tvec4 v1 = texture2D( boneTexture, vec2( dx * ( x + 0.5 ), y ) );\\n\\t\\t\\tvec4 v2 = texture2D( boneTexture, vec2( dx * ( x + 1.5 ), y ) );\\n\\t\\t\\tvec4 v3 = texture2D( boneTexture, vec2( dx * ( x + 2.5 ), y ) );\\n\\t\\t\\tvec4 v4 = texture2D( boneTexture, vec2( dx * ( x + 3.5 ), y ) );\\n\\n\\t\\t\\tmat4 bone = mat4( v1, v2, v3, v4 );\\n\\n\\t\\t\\treturn bone;\\n\\n\\t\\t}\\n\\n\\t#else\\n\\n\\t\\tuniform mat4 boneMatrices[ MAX_BONES ];\\n\\n\\t\\tmat4 getBoneMatrix( const in float i ) {\\n\\n\\t\\t\\tmat4 bone = boneMatrices[ int(i) ];\\n\\t\\t\\treturn bone;\\n\\n\\t\\t}\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/skinning_vertex.glsl.js\\nvar skinning_vertex_glsl_default = `\\n#ifdef USE_SKINNING\\n\\n\\tvec4 skinVertex = bindMatrix * vec4( transformed, 1.0 );\\n\\n\\tvec4 skinned = vec4( 0.0 );\\n\\tskinned += boneMatX * skinVertex * skinWeight.x;\\n\\tskinned += boneMatY * skinVertex * skinWeight.y;\\n\\tskinned += boneMatZ * skinVertex * skinWeight.z;\\n\\tskinned += boneMatW * skinVertex * skinWeight.w;\\n\\n\\ttransformed = ( bindMatrixInverse * skinned ).xyz;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/skinnormal_vertex.glsl.js\\nvar skinnormal_vertex_glsl_default = `\\n#ifdef USE_SKINNING\\n\\n\\tmat4 skinMatrix = mat4( 0.0 );\\n\\tskinMatrix += skinWeight.x * boneMatX;\\n\\tskinMatrix += skinWeight.y * boneMatY;\\n\\tskinMatrix += skinWeight.z * boneMatZ;\\n\\tskinMatrix += skinWeight.w * boneMatW;\\n\\tskinMatrix = bindMatrixInverse * skinMatrix * bindMatrix;\\n\\n\\tobjectNormal = vec4( skinMatrix * vec4( objectNormal, 0.0 ) ).xyz;\\n\\n\\t#ifdef USE_TANGENT\\n\\n\\t\\tobjectTangent = vec4( skinMatrix * vec4( objectTangent, 0.0 ) ).xyz;\\n\\n\\t#endif\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/specularmap_fragment.glsl.js\\nvar specularmap_fragment_glsl_default = `\\nfloat specularStrength;\\n\\n#ifdef USE_SPECULARMAP\\n\\n\\tvec4 texelSpecular = texture2D( specularMap, vUv );\\n\\tspecularStrength = texelSpecular.r;\\n\\n#else\\n\\n\\tspecularStrength = 1.0;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/specularmap_pars_fragment.glsl.js\\nvar specularmap_pars_fragment_glsl_default = `\\n#ifdef USE_SPECULARMAP\\n\\n\\tuniform sampler2D specularMap;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/tonemapping_fragment.glsl.js\\nvar tonemapping_fragment_glsl_default = `\\n#if defined( TONE_MAPPING )\\n\\n\\tgl_FragColor.rgb = toneMapping( gl_FragColor.rgb );\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/tonemapping_pars_fragment.glsl.js\\nvar tonemapping_pars_fragment_glsl_default = `\\n#ifndef saturate\\n// may have defined saturate() already\\n#define saturate( a ) clamp( a, 0.0, 1.0 )\\n#endif\\n\\nuniform float toneMappingExposure;\\n\\n// exposure only\\nvec3 LinearToneMapping( vec3 color ) {\\n\\n\\treturn toneMappingExposure * color;\\n\\n}\\n\\n// source: https://www.cs.utah.edu/~reinhard/cdrom/\\nvec3 ReinhardToneMapping( vec3 color ) {\\n\\n\\tcolor *= toneMappingExposure;\\n\\treturn saturate( color / ( vec3( 1.0 ) + color ) );\\n\\n}\\n\\n// source: http://filmicworlds.com/blog/filmic-tonemapping-operators/\\nvec3 OptimizedCineonToneMapping( vec3 color ) {\\n\\n\\t// optimized filmic operator by Jim Hejl and Richard Burgess-Dawson\\n\\tcolor *= toneMappingExposure;\\n\\tcolor = max( vec3( 0.0 ), color - 0.004 );\\n\\treturn pow( ( color * ( 6.2 * color + 0.5 ) ) / ( color * ( 6.2 * color + 1.7 ) + 0.06 ), vec3( 2.2 ) );\\n\\n}\\n\\n// source: https://github.com/selfshadow/ltc_code/blob/master/webgl/shaders/ltc/ltc_blit.fs\\nvec3 RRTAndODTFit( vec3 v ) {\\n\\n\\tvec3 a = v * ( v + 0.0245786 ) - 0.000090537;\\n\\tvec3 b = v * ( 0.983729 * v + 0.4329510 ) + 0.238081;\\n\\treturn a / b;\\n\\n}\\n\\n// this implementation of ACES is modified to accommodate a brighter viewing environment.\\n// the scale factor of 1/0.6 is subjective. see discussion in #19621.\\n\\nvec3 ACESFilmicToneMapping( vec3 color ) {\\n\\n\\t// sRGB => XYZ => D65_2_D60 => AP1 => RRT_SAT\\n\\tconst mat3 ACESInputMat = mat3(\\n\\t\\tvec3( 0.59719, 0.07600, 0.02840 ), // transposed from source\\n\\t\\tvec3( 0.35458, 0.90834, 0.13383 ),\\n\\t\\tvec3( 0.04823, 0.01566, 0.83777 )\\n\\t);\\n\\n\\t// ODT_SAT => XYZ => D60_2_D65 => sRGB\\n\\tconst mat3 ACESOutputMat = mat3(\\n\\t\\tvec3( 1.60475, -0.10208, -0.00327 ), // transposed from source\\n\\t\\tvec3( -0.53108, 1.10813, -0.07276 ),\\n\\t\\tvec3( -0.07367, -0.00605, 1.07602 )\\n\\t);\\n\\n\\tcolor *= toneMappingExposure / 0.6;\\n\\n\\tcolor = ACESInputMat * color;\\n\\n\\t// Apply RRT and ODT\\n\\tcolor = RRTAndODTFit( color );\\n\\n\\tcolor = ACESOutputMat * color;\\n\\n\\t// Clamp to [0, 1]\\n\\treturn saturate( color );\\n\\n}\\n\\nvec3 CustomToneMapping( vec3 color ) { return color; }\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/transmission_fragment.glsl.js\\nvar transmission_fragment_glsl_default = `\\n#ifdef USE_TRANSMISSION\\n\\n\\tfloat transmissionAlpha = 1.0;\\n\\tfloat transmissionFactor = transmission;\\n\\tfloat thicknessFactor = thickness;\\n\\n\\t#ifdef USE_TRANSMISSIONMAP\\n\\n\\t\\ttransmissionFactor *= texture2D( transmissionMap, vUv ).r;\\n\\n\\t#endif\\n\\n\\t#ifdef USE_THICKNESSMAP\\n\\n\\t\\tthicknessFactor *= texture2D( thicknessMap, vUv ).g;\\n\\n\\t#endif\\n\\n\\tvec3 pos = vWorldPosition;\\n\\tvec3 v = normalize( cameraPosition - pos );\\n\\tvec3 n = inverseTransformDirection( normal, viewMatrix );\\n\\n\\tvec4 transmission = getIBLVolumeRefraction(\\n\\t\\tn, v, roughnessFactor, material.diffuseColor, material.specularColor, material.specularF90,\\n\\t\\tpos, modelMatrix, viewMatrix, projectionMatrix, ior, thicknessFactor,\\n\\t\\tattenuationTint, attenuationDistance );\\n\\n\\ttotalDiffuse = mix( totalDiffuse, transmission.rgb, transmissionFactor );\\n\\ttransmissionAlpha = mix( transmissionAlpha, transmission.a, transmissionFactor );\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/transmission_pars_fragment.glsl.js\\nvar transmission_pars_fragment_glsl_default = `\\n#ifdef USE_TRANSMISSION\\n\\n\\t// Transmission code is based on glTF-Sampler-Viewer\\n\\t// https://github.com/KhronosGroup/glTF-Sample-Viewer\\n\\n\\tuniform float transmission;\\n\\tuniform float thickness;\\n\\tuniform float attenuationDistance;\\n\\tuniform vec3 attenuationTint;\\n\\n\\t#ifdef USE_TRANSMISSIONMAP\\n\\n\\t\\tuniform sampler2D transmissionMap;\\n\\n\\t#endif\\n\\n\\t#ifdef USE_THICKNESSMAP\\n\\n\\t\\tuniform sampler2D thicknessMap;\\n\\n\\t#endif\\n\\n\\tuniform vec2 transmissionSamplerSize;\\n\\tuniform sampler2D transmissionSamplerMap;\\n\\n\\tuniform mat4 modelMatrix;\\n\\tuniform mat4 projectionMatrix;\\n\\n\\tvarying vec3 vWorldPosition;\\n\\n\\tvec3 getVolumeTransmissionRay( vec3 n, vec3 v, float thickness, float ior, mat4 modelMatrix ) {\\n\\n\\t\\t// Direction of refracted light.\\n\\t\\tvec3 refractionVector = refract( - v, normalize( n ), 1.0 / ior );\\n\\n\\t\\t// Compute rotation-independant scaling of the model matrix.\\n\\t\\tvec3 modelScale;\\n\\t\\tmodelScale.x = length( vec3( modelMatrix[ 0 ].xyz ) );\\n\\t\\tmodelScale.y = length( vec3( modelMatrix[ 1 ].xyz ) );\\n\\t\\tmodelScale.z = length( vec3( modelMatrix[ 2 ].xyz ) );\\n\\n\\t\\t// The thickness is specified in local space.\\n\\t\\treturn normalize( refractionVector ) * thickness * modelScale;\\n\\n\\t}\\n\\n\\tfloat applyIorToRoughness( float roughness, float ior ) {\\n\\n\\t\\t// Scale roughness with IOR so that an IOR of 1.0 results in no microfacet refraction and\\n\\t\\t// an IOR of 1.5 results in the default amount of microfacet refraction.\\n\\t\\treturn roughness * clamp( ior * 2.0 - 2.0, 0.0, 1.0 );\\n\\n\\t}\\n\\n\\tvec4 getTransmissionSample( vec2 fragCoord, float roughness, float ior ) {\\n\\n\\t\\tfloat framebufferLod = log2( transmissionSamplerSize.x ) * applyIorToRoughness( roughness, ior );\\n\\n\\t\\t#ifdef TEXTURE_LOD_EXT\\n\\n\\t\\t\\treturn texture2DLodEXT( transmissionSamplerMap, fragCoord.xy, framebufferLod );\\n\\n\\t\\t#else\\n\\n\\t\\t\\treturn texture2D( transmissionSamplerMap, fragCoord.xy, framebufferLod );\\n\\n\\t\\t#endif\\n\\n\\t}\\n\\n\\tvec3 applyVolumeAttenuation( vec3 radiance, float transmissionDistance, vec3 attenuationColor, float attenuationDistance ) {\\n\\n\\t\\tif ( attenuationDistance == 0.0 ) {\\n\\n\\t\\t\\t// Attenuation distance is +\\\\u221E (which we indicate by zero), i.e. the transmitted color is not attenuated at all.\\n\\t\\t\\treturn radiance;\\n\\n\\t\\t} else {\\n\\n\\t\\t\\t// Compute light attenuation using Beer's law.\\n\\t\\t\\tvec3 attenuationCoefficient = -log( attenuationColor ) / attenuationDistance;\\n\\t\\t\\tvec3 transmittance = exp( - attenuationCoefficient * transmissionDistance ); // Beer's law\\n\\t\\t\\treturn transmittance * radiance;\\n\\n\\t\\t}\\n\\n\\t}\\n\\n\\tvec4 getIBLVolumeRefraction( vec3 n, vec3 v, float roughness, vec3 diffuseColor, vec3 specularColor, float specularF90,\\n\\t\\tvec3 position, mat4 modelMatrix, mat4 viewMatrix, mat4 projMatrix, float ior, float thickness,\\n\\t\\tvec3 attenuationColor, float attenuationDistance ) {\\n\\n\\t\\tvec3 transmissionRay = getVolumeTransmissionRay( n, v, thickness, ior, modelMatrix );\\n\\t\\tvec3 refractedRayExit = position + transmissionRay;\\n\\n\\t\\t// Project refracted vector on the framebuffer, while mapping to normalized device coordinates.\\n\\t\\tvec4 ndcPos = projMatrix * viewMatrix * vec4( refractedRayExit, 1.0 );\\n\\t\\tvec2 refractionCoords = ndcPos.xy / ndcPos.w;\\n\\t\\trefractionCoords += 1.0;\\n\\t\\trefractionCoords /= 2.0;\\n\\n\\t\\t// Sample framebuffer to get pixel the refracted ray hits.\\n\\t\\tvec4 transmittedLight = getTransmissionSample( refractionCoords, roughness, ior );\\n\\n\\t\\tvec3 attenuatedColor = applyVolumeAttenuation( transmittedLight.rgb, length( transmissionRay ), attenuationColor, attenuationDistance );\\n\\n\\t\\t// Get the specular component.\\n\\t\\tvec3 F = EnvironmentBRDF( n, v, specularColor, specularF90, roughness );\\n\\n\\t\\treturn vec4( ( 1.0 - F ) * attenuatedColor * diffuseColor, transmittedLight.a );\\n\\n\\t}\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/uv_pars_fragment.glsl.js\\nvar uv_pars_fragment_glsl_default = `\\n#if ( defined( USE_UV ) && ! defined( UVS_VERTEX_ONLY ) )\\n\\n\\tvarying vec2 vUv;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/uv_pars_vertex.glsl.js\\nvar uv_pars_vertex_glsl_default = `\\n#ifdef USE_UV\\n\\n\\t#ifdef UVS_VERTEX_ONLY\\n\\n\\t\\tvec2 vUv;\\n\\n\\t#else\\n\\n\\t\\tvarying vec2 vUv;\\n\\n\\t#endif\\n\\n\\tuniform mat3 uvTransform;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/uv_vertex.glsl.js\\nvar uv_vertex_glsl_default = `\\n#ifdef USE_UV\\n\\n\\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/uv2_pars_fragment.glsl.js\\nvar uv2_pars_fragment_glsl_default = `\\n#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\n\\n\\tvarying vec2 vUv2;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/uv2_pars_vertex.glsl.js\\nvar uv2_pars_vertex_glsl_default = `\\n#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\n\\n\\tattribute vec2 uv2;\\n\\tvarying vec2 vUv2;\\n\\n\\tuniform mat3 uv2Transform;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/uv2_vertex.glsl.js\\nvar uv2_vertex_glsl_default = `\\n#if defined( USE_LIGHTMAP ) || defined( USE_AOMAP )\\n\\n\\tvUv2 = ( uv2Transform * vec3( uv2, 1 ) ).xy;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk/worldpos_vertex.glsl.js\\nvar worldpos_vertex_glsl_default = `\\n#if defined( USE_ENVMAP ) || defined( DISTANCE ) || defined ( USE_SHADOWMAP ) || defined ( USE_TRANSMISSION )\\n\\n\\tvec4 worldPosition = vec4( transformed, 1.0 );\\n\\n\\t#ifdef USE_INSTANCING\\n\\n\\t\\tworldPosition = instanceMatrix * worldPosition;\\n\\n\\t#endif\\n\\n\\tworldPosition = modelMatrix * worldPosition;\\n\\n#endif\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/background.glsl.js\\nvar vertex = `\\nvarying vec2 vUv;\\nuniform mat3 uvTransform;\\n\\nvoid main() {\\n\\n\\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\\n\\n\\tgl_Position = vec4( position.xy, 1.0, 1.0 );\\n\\n}\\n`;\\nvar fragment = `\\nuniform sampler2D t2D;\\n\\nvarying vec2 vUv;\\n\\nvoid main() {\\n\\n\\tvec4 texColor = texture2D( t2D, vUv );\\n\\n\\tgl_FragColor = mapTexelToLinear( texColor );\\n\\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/cube.glsl.js\\nvar vertex2 = `\\nvarying vec3 vWorldDirection;\\n\\n#include \\n\\nvoid main() {\\n\\n\\tvWorldDirection = transformDirection( position, modelMatrix );\\n\\n\\t#include \\n\\t#include \\n\\n\\tgl_Position.z = gl_Position.w; // set z to camera.far\\n\\n}\\n`;\\nvar fragment2 = `\\n#include \\nuniform float opacity;\\n\\nvarying vec3 vWorldDirection;\\n\\n#include \\n\\nvoid main() {\\n\\n\\tvec3 vReflect = vWorldDirection;\\n\\t#include \\n\\n\\tgl_FragColor = envColor;\\n\\tgl_FragColor.a *= opacity;\\n\\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/depth.glsl.js\\nvar vertex3 = `\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\n// This is used for computing an equivalent of gl_FragCoord.z that is as high precision as possible.\\n// Some platforms compute gl_FragCoord at a lower precision which makes the manually computed value better for\\n// depth-based postprocessing effects. Reproduced on iPad with A10 processor / iPadOS 13.3.1.\\nvarying vec2 vHighPrecisionZW;\\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\t#include \\n\\n\\t#ifdef USE_DISPLACEMENTMAP\\n\\n\\t\\t#include \\n\\t\\t#include \\n\\t\\t#include \\n\\n\\t#endif\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tvHighPrecisionZW = gl_Position.zw;\\n\\n}\\n`;\\nvar fragment3 = `\\n#if DEPTH_PACKING == 3200\\n\\n\\tuniform float opacity;\\n\\n#endif\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvarying vec2 vHighPrecisionZW;\\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec4 diffuseColor = vec4( 1.0 );\\n\\n\\t#if DEPTH_PACKING == 3200\\n\\n\\t\\tdiffuseColor.a = opacity;\\n\\n\\t#endif\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\n\\t// Higher precision equivalent of gl_FragCoord.z. This assumes depthRange has been left to its default values.\\n\\tfloat fragCoordZ = 0.5 * vHighPrecisionZW[0] / vHighPrecisionZW[1] + 0.5;\\n\\n\\t#if DEPTH_PACKING == 3200\\n\\n\\t\\tgl_FragColor = vec4( vec3( 1.0 - fragCoordZ ), opacity );\\n\\n\\t#elif DEPTH_PACKING == 3201\\n\\n\\t\\tgl_FragColor = packDepthToRGBA( fragCoordZ );\\n\\n\\t#endif\\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/distanceRGBA.glsl.js\\nvar vertex4 = `\\n#define DISTANCE\\n\\nvarying vec3 vWorldPosition;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\t#include \\n\\n\\t#ifdef USE_DISPLACEMENTMAP\\n\\n\\t\\t#include \\n\\t\\t#include \\n\\t\\t#include \\n\\n\\t#endif\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tvWorldPosition = worldPosition.xyz;\\n\\n}\\n`;\\nvar fragment4 = `\\n#define DISTANCE\\n\\nuniform vec3 referencePosition;\\nuniform float nearDistance;\\nuniform float farDistance;\\nvarying vec3 vWorldPosition;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main () {\\n\\n\\t#include \\n\\n\\tvec4 diffuseColor = vec4( 1.0 );\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tfloat dist = length( vWorldPosition - referencePosition );\\n\\tdist = ( dist - nearDistance ) / ( farDistance - nearDistance );\\n\\tdist = saturate( dist ); // clamp to [ 0, 1 ]\\n\\n\\tgl_FragColor = packDepthToRGBA( dist );\\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/equirect.glsl.js\\nvar vertex5 = `\\nvarying vec3 vWorldDirection;\\n\\n#include \\n\\nvoid main() {\\n\\n\\tvWorldDirection = transformDirection( position, modelMatrix );\\n\\n\\t#include \\n\\t#include \\n\\n}\\n`;\\nvar fragment5 = `\\nuniform sampler2D tEquirect;\\n\\nvarying vec3 vWorldDirection;\\n\\n#include \\n\\nvoid main() {\\n\\n\\tvec3 direction = normalize( vWorldDirection );\\n\\n\\tvec2 sampleUV = equirectUv( direction );\\n\\n\\tvec4 texColor = texture2D( tEquirect, sampleUV );\\n\\n\\tgl_FragColor = mapTexelToLinear( texColor );\\n\\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/linedashed.glsl.js\\nvar vertex6 = `\\nuniform float scale;\\nattribute float lineDistance;\\n\\nvarying float vLineDistance;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\tvLineDistance = scale * lineDistance;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\nvar fragment6 = `\\nuniform vec3 diffuse;\\nuniform float opacity;\\n\\nuniform float dashSize;\\nuniform float totalSize;\\n\\nvarying float vLineDistance;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tif ( mod( vLineDistance, totalSize ) > dashSize ) {\\n\\n\\t\\tdiscard;\\n\\n\\t}\\n\\n\\tvec3 outgoingLight = vec3( 0.0 );\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\n\\t#include \\n\\t#include \\n\\n\\toutgoingLight = diffuseColor.rgb; // simple shader\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/meshbasic.glsl.js\\nvar vertex7 = `\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#if defined ( USE_ENVMAP ) || defined ( USE_SKINNING )\\n\\n\\t\\t#include \\n\\t\\t#include \\n\\t\\t#include \\n\\t\\t#include \\n\\t\\t#include \\n\\n\\t#endif\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\nvar fragment7 = `\\nuniform vec3 diffuse;\\nuniform float opacity;\\n\\n#ifndef FLAT_SHADED\\n\\n\\tvarying vec3 vNormal;\\n\\n#endif\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\n\\n\\t// accumulation (baked indirect lighting only)\\n\\t#ifdef USE_LIGHTMAP\\n\\n\\t\\tvec4 lightMapTexel= texture2D( lightMap, vUv2 );\\n\\t\\treflectedLight.indirectDiffuse += lightMapTexelToLinear( lightMapTexel ).rgb * lightMapIntensity;\\n\\n\\t#else\\n\\n\\t\\treflectedLight.indirectDiffuse += vec3( 1.0 );\\n\\n\\t#endif\\n\\n\\t// modulation\\n\\t#include \\n\\n\\treflectedLight.indirectDiffuse *= diffuseColor.rgb;\\n\\n\\tvec3 outgoingLight = reflectedLight.indirectDiffuse;\\n\\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/meshlambert.glsl.js\\nvar vertex8 = `\\n#define LAMBERT\\n\\nvarying vec3 vLightFront;\\nvarying vec3 vIndirectFront;\\n\\n#ifdef DOUBLE_SIDED\\n\\tvarying vec3 vLightBack;\\n\\tvarying vec3 vIndirectBack;\\n#endif\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n}\\n`;\\nvar fragment8 = `\\nuniform vec3 diffuse;\\nuniform vec3 emissive;\\nuniform float opacity;\\n\\nvarying vec3 vLightFront;\\nvarying vec3 vIndirectFront;\\n\\n#ifdef DOUBLE_SIDED\\n\\tvarying vec3 vLightBack;\\n\\tvarying vec3 vIndirectBack;\\n#endif\\n\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\n\\tvec3 totalEmissiveRadiance = emissive;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t// accumulation\\n\\n\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\treflectedLight.indirectDiffuse += ( gl_FrontFacing ) ? vIndirectFront : vIndirectBack;\\n\\n\\t#else\\n\\n\\t\\treflectedLight.indirectDiffuse += vIndirectFront;\\n\\n\\t#endif\\n\\n\\t#include \\n\\n\\treflectedLight.indirectDiffuse *= BRDF_Lambert( diffuseColor.rgb );\\n\\n\\t#ifdef DOUBLE_SIDED\\n\\n\\t\\treflectedLight.directDiffuse = ( gl_FrontFacing ) ? vLightFront : vLightBack;\\n\\n\\t#else\\n\\n\\t\\treflectedLight.directDiffuse = vLightFront;\\n\\n\\t#endif\\n\\n\\treflectedLight.directDiffuse *= BRDF_Lambert( diffuseColor.rgb ) * getShadowMask();\\n\\n\\t// modulation\\n\\n\\t#include \\n\\n\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\\n\\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/meshmatcap.glsl.js\\nvar vertex9 = `\\n#define MATCAP\\n\\nvarying vec3 vViewPosition;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tvViewPosition = - mvPosition.xyz;\\n\\n}\\n`;\\nvar fragment9 = `\\n#define MATCAP\\n\\nuniform vec3 diffuse;\\nuniform float opacity;\\nuniform sampler2D matcap;\\n\\nvarying vec3 vViewPosition;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tvec3 viewDir = normalize( vViewPosition );\\n\\tvec3 x = normalize( vec3( viewDir.z, 0.0, - viewDir.x ) );\\n\\tvec3 y = cross( viewDir, x );\\n\\tvec2 uv = vec2( dot( x, normal ), dot( y, normal ) ) * 0.495 + 0.5; // 0.495 to remove artifacts caused by undersized matcap disks\\n\\n\\t#ifdef USE_MATCAP\\n\\n\\t\\tvec4 matcapColor = texture2D( matcap, uv );\\n\\t\\tmatcapColor = matcapTexelToLinear( matcapColor );\\n\\n\\t#else\\n\\n\\t\\tvec4 matcapColor = vec4( 1.0 );\\n\\n\\t#endif\\n\\n\\tvec3 outgoingLight = diffuseColor.rgb * matcapColor.rgb;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/meshnormal.glsl.js\\nvar vertex10 = `\\n#define NORMAL\\n\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\n\\n\\tvarying vec3 vViewPosition;\\n\\n#endif\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\n\\n\\tvViewPosition = - mvPosition.xyz;\\n\\n#endif\\n\\n}\\n`;\\nvar fragment10 = `\\n#define NORMAL\\n\\nuniform float opacity;\\n\\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( TANGENTSPACE_NORMALMAP )\\n\\n\\tvarying vec3 vViewPosition;\\n\\n#endif\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tgl_FragColor = vec4( packNormalToRGB( normal ), opacity );\\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/meshphong.glsl.js\\nvar vertex11 = `\\n#define PHONG\\n\\nvarying vec3 vViewPosition;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tvViewPosition = - mvPosition.xyz;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\nvar fragment11 = `\\n#define PHONG\\n\\nuniform vec3 diffuse;\\nuniform vec3 emissive;\\nuniform vec3 specular;\\nuniform float shininess;\\nuniform float opacity;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\n\\tvec3 totalEmissiveRadiance = emissive;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t// accumulation\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t// modulation\\n\\t#include \\n\\n\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + reflectedLight.directSpecular + reflectedLight.indirectSpecular + totalEmissiveRadiance;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/meshphysical.glsl.js\\nvar vertex12 = `\\n#define STANDARD\\n\\nvarying vec3 vViewPosition;\\n\\n#ifdef USE_TRANSMISSION\\n\\n\\tvarying vec3 vWorldPosition;\\n\\n#endif\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tvViewPosition = - mvPosition.xyz;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n#ifdef USE_TRANSMISSION\\n\\n\\tvWorldPosition = worldPosition.xyz;\\n\\n#endif\\n}\\n`;\\nvar fragment12 = `\\n#define STANDARD\\n\\n#ifdef PHYSICAL\\n\\t#define IOR\\n\\t#define SPECULAR\\n#endif\\n\\nuniform vec3 diffuse;\\nuniform vec3 emissive;\\nuniform float roughness;\\nuniform float metalness;\\nuniform float opacity;\\n\\n#ifdef IOR\\n\\tuniform float ior;\\n#endif\\n\\n#ifdef SPECULAR\\n\\tuniform float specularIntensity;\\n\\tuniform vec3 specularTint;\\n\\n\\t#ifdef USE_SPECULARINTENSITYMAP\\n\\t\\tuniform sampler2D specularIntensityMap;\\n\\t#endif\\n\\n\\t#ifdef USE_SPECULARTINTMAP\\n\\t\\tuniform sampler2D specularTintMap;\\n\\t#endif\\n#endif\\n\\n#ifdef USE_CLEARCOAT\\n\\tuniform float clearcoat;\\n\\tuniform float clearcoatRoughness;\\n#endif\\n\\n#ifdef USE_SHEEN\\n\\tuniform vec3 sheenTint;\\n\\tuniform float sheenRoughness;\\n#endif\\n\\nvarying vec3 vViewPosition;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\n\\tvec3 totalEmissiveRadiance = emissive;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t// accumulation\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t// modulation\\n\\t#include \\n\\n\\tvec3 totalDiffuse = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse;\\n\\tvec3 totalSpecular = reflectedLight.directSpecular + reflectedLight.indirectSpecular;\\n\\n\\t#include \\n\\n\\tvec3 outgoingLight = totalDiffuse + totalSpecular + totalEmissiveRadiance;\\n\\n\\t#ifdef USE_CLEARCOAT\\n\\n\\t\\tfloat dotNVcc = saturate( dot( geometry.clearcoatNormal, geometry.viewDir ) );\\n\\n\\t\\tvec3 Fcc = F_Schlick( material.clearcoatF0, material.clearcoatF90, dotNVcc );\\n\\n\\t\\toutgoingLight = outgoingLight * ( 1.0 - clearcoat * Fcc ) + clearcoatSpecular * clearcoat;\\n\\n\\t#endif\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/meshtoon.glsl.js\\nvar vertex13 = `\\n#define TOON\\n\\nvarying vec3 vViewPosition;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tvViewPosition = - mvPosition.xyz;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\nvar fragment13 = `\\n#define TOON\\n\\nuniform vec3 diffuse;\\nuniform vec3 emissive;\\nuniform float opacity;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\\n\\tvec3 totalEmissiveRadiance = emissive;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t// accumulation\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t// modulation\\n\\t#include \\n\\n\\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/points.glsl.js\\nvar vertex14 = `\\nuniform float size;\\nuniform float scale;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\tgl_PointSize = size;\\n\\n\\t#ifdef USE_SIZEATTENUATION\\n\\n\\t\\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\\n\\n\\t\\tif ( isPerspective ) gl_PointSize *= ( scale / - mvPosition.z );\\n\\n\\t#endif\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\nvar fragment14 = `\\nuniform vec3 diffuse;\\nuniform float opacity;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec3 outgoingLight = vec3( 0.0 );\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\toutgoingLight = diffuseColor.rgb;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/shadow.glsl.js\\nvar vertex15 = `\\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\nvar fragment15 = `\\nuniform vec3 color;\\nuniform float opacity;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\tgl_FragColor = vec4( color, opacity * ( 1.0 - getShadowMask() ) );\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/sprite.glsl.js\\nvar vertex16 = `\\nuniform float rotation;\\nuniform vec2 center;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec4 mvPosition = modelViewMatrix * vec4( 0.0, 0.0, 0.0, 1.0 );\\n\\n\\tvec2 scale;\\n\\tscale.x = length( vec3( modelMatrix[ 0 ].x, modelMatrix[ 0 ].y, modelMatrix[ 0 ].z ) );\\n\\tscale.y = length( vec3( modelMatrix[ 1 ].x, modelMatrix[ 1 ].y, modelMatrix[ 1 ].z ) );\\n\\n\\t#ifndef USE_SIZEATTENUATION\\n\\n\\t\\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\\n\\n\\t\\tif ( isPerspective ) scale *= - mvPosition.z;\\n\\n\\t#endif\\n\\n\\tvec2 alignedPosition = ( position.xy - ( center - vec2( 0.5 ) ) ) * scale;\\n\\n\\tvec2 rotatedPosition;\\n\\trotatedPosition.x = cos( rotation ) * alignedPosition.x - sin( rotation ) * alignedPosition.y;\\n\\trotatedPosition.y = sin( rotation ) * alignedPosition.x + cos( rotation ) * alignedPosition.y;\\n\\n\\tmvPosition.xy += rotatedPosition;\\n\\n\\tgl_Position = projectionMatrix * mvPosition;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\nvar fragment16 = `\\nuniform vec3 diffuse;\\nuniform float opacity;\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\nvoid main() {\\n\\n\\t#include \\n\\n\\tvec3 outgoingLight = vec3( 0.0 );\\n\\tvec4 diffuseColor = vec4( diffuse, opacity );\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n\\toutgoingLight = diffuseColor.rgb;\\n\\n\\t#include \\n\\t#include \\n\\t#include \\n\\t#include \\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderChunk.js\\nvar ShaderChunk = {\\n alphamap_fragment: alphamap_fragment_glsl_default,\\n alphamap_pars_fragment: alphamap_pars_fragment_glsl_default,\\n alphatest_fragment: alphatest_fragment_glsl_default,\\n alphatest_pars_fragment: alphatest_pars_fragment_glsl_default,\\n aomap_fragment: aomap_fragment_glsl_default,\\n aomap_pars_fragment: aomap_pars_fragment_glsl_default,\\n begin_vertex: begin_vertex_glsl_default,\\n beginnormal_vertex: beginnormal_vertex_glsl_default,\\n bsdfs: bsdfs_glsl_default,\\n bumpmap_pars_fragment: bumpmap_pars_fragment_glsl_default,\\n clipping_planes_fragment: clipping_planes_fragment_glsl_default,\\n clipping_planes_pars_fragment: clipping_planes_pars_fragment_glsl_default,\\n clipping_planes_pars_vertex: clipping_planes_pars_vertex_glsl_default,\\n clipping_planes_vertex: clipping_planes_vertex_glsl_default,\\n color_fragment: color_fragment_glsl_default,\\n color_pars_fragment: color_pars_fragment_glsl_default,\\n color_pars_vertex: color_pars_vertex_glsl_default,\\n color_vertex: color_vertex_glsl_default,\\n common: common_glsl_default,\\n cube_uv_reflection_fragment: cube_uv_reflection_fragment_glsl_default,\\n defaultnormal_vertex: defaultnormal_vertex_glsl_default,\\n displacementmap_pars_vertex: displacementmap_pars_vertex_glsl_default,\\n displacementmap_vertex: displacementmap_vertex_glsl_default,\\n emissivemap_fragment: emissivemap_fragment_glsl_default,\\n emissivemap_pars_fragment: emissivemap_pars_fragment_glsl_default,\\n encodings_fragment: encodings_fragment_glsl_default,\\n encodings_pars_fragment: encodings_pars_fragment_glsl_default,\\n envmap_fragment: envmap_fragment_glsl_default,\\n envmap_common_pars_fragment: envmap_common_pars_fragment_glsl_default,\\n envmap_pars_fragment: envmap_pars_fragment_glsl_default,\\n envmap_pars_vertex: envmap_pars_vertex_glsl_default,\\n envmap_physical_pars_fragment: envmap_physical_pars_fragment_glsl_default,\\n envmap_vertex: envmap_vertex_glsl_default,\\n fog_vertex: fog_vertex_glsl_default,\\n fog_pars_vertex: fog_pars_vertex_glsl_default,\\n fog_fragment: fog_fragment_glsl_default,\\n fog_pars_fragment: fog_pars_fragment_glsl_default,\\n gradientmap_pars_fragment: gradientmap_pars_fragment_glsl_default,\\n lightmap_fragment: lightmap_fragment_glsl_default,\\n lightmap_pars_fragment: lightmap_pars_fragment_glsl_default,\\n lights_lambert_vertex: lights_lambert_vertex_glsl_default,\\n lights_pars_begin: lights_pars_begin_glsl_default,\\n lights_toon_fragment: lights_toon_fragment_glsl_default,\\n lights_toon_pars_fragment: lights_toon_pars_fragment_glsl_default,\\n lights_phong_fragment: lights_phong_fragment_glsl_default,\\n lights_phong_pars_fragment: lights_phong_pars_fragment_glsl_default,\\n lights_physical_fragment: lights_physical_fragment_glsl_default,\\n lights_physical_pars_fragment: lights_physical_pars_fragment_glsl_default,\\n lights_fragment_begin: lights_fragment_begin_glsl_default,\\n lights_fragment_maps: lights_fragment_maps_glsl_default,\\n lights_fragment_end: lights_fragment_end_glsl_default,\\n logdepthbuf_fragment: logdepthbuf_fragment_glsl_default,\\n logdepthbuf_pars_fragment: logdepthbuf_pars_fragment_glsl_default,\\n logdepthbuf_pars_vertex: logdepthbuf_pars_vertex_glsl_default,\\n logdepthbuf_vertex: logdepthbuf_vertex_glsl_default,\\n map_fragment: map_fragment_glsl_default,\\n map_pars_fragment: map_pars_fragment_glsl_default,\\n map_particle_fragment: map_particle_fragment_glsl_default,\\n map_particle_pars_fragment: map_particle_pars_fragment_glsl_default,\\n metalnessmap_fragment: metalnessmap_fragment_glsl_default,\\n metalnessmap_pars_fragment: metalnessmap_pars_fragment_glsl_default,\\n morphnormal_vertex: morphnormal_vertex_glsl_default,\\n morphtarget_pars_vertex: morphtarget_pars_vertex_glsl_default,\\n morphtarget_vertex: morphtarget_vertex_glsl_default,\\n normal_fragment_begin: normal_fragment_begin_glsl_default,\\n normal_fragment_maps: normal_fragment_maps_glsl_default,\\n normal_pars_fragment: normal_pars_fragment_glsl_default,\\n normal_pars_vertex: normal_pars_vertex_glsl_default,\\n normal_vertex: normal_vertex_glsl_default,\\n normalmap_pars_fragment: normalmap_pars_fragment_glsl_default,\\n clearcoat_normal_fragment_begin: clearcoat_normal_fragment_begin_glsl_default,\\n clearcoat_normal_fragment_maps: clearcoat_normal_fragment_maps_glsl_default,\\n clearcoat_pars_fragment: clearcoat_pars_fragment_glsl_default,\\n output_fragment: output_fragment_glsl_default,\\n packing: packing_glsl_default,\\n premultiplied_alpha_fragment: premultiplied_alpha_fragment_glsl_default,\\n project_vertex: project_vertex_glsl_default,\\n dithering_fragment: dithering_fragment_glsl_default,\\n dithering_pars_fragment: dithering_pars_fragment_glsl_default,\\n roughnessmap_fragment: roughnessmap_fragment_glsl_default,\\n roughnessmap_pars_fragment: roughnessmap_pars_fragment_glsl_default,\\n shadowmap_pars_fragment: shadowmap_pars_fragment_glsl_default,\\n shadowmap_pars_vertex: shadowmap_pars_vertex_glsl_default,\\n shadowmap_vertex: shadowmap_vertex_glsl_default,\\n shadowmask_pars_fragment: shadowmask_pars_fragment_glsl_default,\\n skinbase_vertex: skinbase_vertex_glsl_default,\\n skinning_pars_vertex: skinning_pars_vertex_glsl_default,\\n skinning_vertex: skinning_vertex_glsl_default,\\n skinnormal_vertex: skinnormal_vertex_glsl_default,\\n specularmap_fragment: specularmap_fragment_glsl_default,\\n specularmap_pars_fragment: specularmap_pars_fragment_glsl_default,\\n tonemapping_fragment: tonemapping_fragment_glsl_default,\\n tonemapping_pars_fragment: tonemapping_pars_fragment_glsl_default,\\n transmission_fragment: transmission_fragment_glsl_default,\\n transmission_pars_fragment: transmission_pars_fragment_glsl_default,\\n uv_pars_fragment: uv_pars_fragment_glsl_default,\\n uv_pars_vertex: uv_pars_vertex_glsl_default,\\n uv_vertex: uv_vertex_glsl_default,\\n uv2_pars_fragment: uv2_pars_fragment_glsl_default,\\n uv2_pars_vertex: uv2_pars_vertex_glsl_default,\\n uv2_vertex: uv2_vertex_glsl_default,\\n worldpos_vertex: worldpos_vertex_glsl_default,\\n background_vert: vertex,\\n background_frag: fragment,\\n cube_vert: vertex2,\\n cube_frag: fragment2,\\n depth_vert: vertex3,\\n depth_frag: fragment3,\\n distanceRGBA_vert: vertex4,\\n distanceRGBA_frag: fragment4,\\n equirect_vert: vertex5,\\n equirect_frag: fragment5,\\n linedashed_vert: vertex6,\\n linedashed_frag: fragment6,\\n meshbasic_vert: vertex7,\\n meshbasic_frag: fragment7,\\n meshlambert_vert: vertex8,\\n meshlambert_frag: fragment8,\\n meshmatcap_vert: vertex9,\\n meshmatcap_frag: fragment9,\\n meshnormal_vert: vertex10,\\n meshnormal_frag: fragment10,\\n meshphong_vert: vertex11,\\n meshphong_frag: fragment11,\\n meshphysical_vert: vertex12,\\n meshphysical_frag: fragment12,\\n meshtoon_vert: vertex13,\\n meshtoon_frag: fragment13,\\n points_vert: vertex14,\\n points_frag: fragment14,\\n shadow_vert: vertex15,\\n shadow_frag: fragment15,\\n sprite_vert: vertex16,\\n sprite_frag: fragment16\\n};\\n\\n// ../../../node_modules/three/src/renderers/shaders/UniformsLib.js\\nvar UniformsLib = {\\n common: {\\n diffuse: {value: new Color(16777215)},\\n opacity: {value: 1},\\n map: {value: null},\\n uvTransform: {value: new Matrix3()},\\n uv2Transform: {value: new Matrix3()},\\n alphaMap: {value: null},\\n alphaTest: {value: 0}\\n },\\n specularmap: {\\n specularMap: {value: null}\\n },\\n envmap: {\\n envMap: {value: null},\\n flipEnvMap: {value: -1},\\n reflectivity: {value: 1},\\n ior: {value: 1.5},\\n refractionRatio: {value: 0.98},\\n maxMipLevel: {value: 0}\\n },\\n aomap: {\\n aoMap: {value: null},\\n aoMapIntensity: {value: 1}\\n },\\n lightmap: {\\n lightMap: {value: null},\\n lightMapIntensity: {value: 1}\\n },\\n emissivemap: {\\n emissiveMap: {value: null}\\n },\\n bumpmap: {\\n bumpMap: {value: null},\\n bumpScale: {value: 1}\\n },\\n normalmap: {\\n normalMap: {value: null},\\n normalScale: {value: new Vector2(1, 1)}\\n },\\n displacementmap: {\\n displacementMap: {value: null},\\n displacementScale: {value: 1},\\n displacementBias: {value: 0}\\n },\\n roughnessmap: {\\n roughnessMap: {value: null}\\n },\\n metalnessmap: {\\n metalnessMap: {value: null}\\n },\\n gradientmap: {\\n gradientMap: {value: null}\\n },\\n fog: {\\n fogDensity: {value: 25e-5},\\n fogNear: {value: 1},\\n fogFar: {value: 2e3},\\n fogColor: {value: new Color(16777215)}\\n },\\n lights: {\\n ambientLightColor: {value: []},\\n lightProbe: {value: []},\\n directionalLights: {value: [], properties: {\\n direction: {},\\n color: {}\\n }},\\n directionalLightShadows: {value: [], properties: {\\n shadowBias: {},\\n shadowNormalBias: {},\\n shadowRadius: {},\\n shadowMapSize: {}\\n }},\\n directionalShadowMap: {value: []},\\n directionalShadowMatrix: {value: []},\\n spotLights: {value: [], properties: {\\n color: {},\\n position: {},\\n direction: {},\\n distance: {},\\n coneCos: {},\\n penumbraCos: {},\\n decay: {}\\n }},\\n spotLightShadows: {value: [], properties: {\\n shadowBias: {},\\n shadowNormalBias: {},\\n shadowRadius: {},\\n shadowMapSize: {}\\n }},\\n spotShadowMap: {value: []},\\n spotShadowMatrix: {value: []},\\n pointLights: {value: [], properties: {\\n color: {},\\n position: {},\\n decay: {},\\n distance: {}\\n }},\\n pointLightShadows: {value: [], properties: {\\n shadowBias: {},\\n shadowNormalBias: {},\\n shadowRadius: {},\\n shadowMapSize: {},\\n shadowCameraNear: {},\\n shadowCameraFar: {}\\n }},\\n pointShadowMap: {value: []},\\n pointShadowMatrix: {value: []},\\n hemisphereLights: {value: [], properties: {\\n direction: {},\\n skyColor: {},\\n groundColor: {}\\n }},\\n rectAreaLights: {value: [], properties: {\\n color: {},\\n position: {},\\n width: {},\\n height: {}\\n }},\\n ltc_1: {value: null},\\n ltc_2: {value: null}\\n },\\n points: {\\n diffuse: {value: new Color(16777215)},\\n opacity: {value: 1},\\n size: {value: 1},\\n scale: {value: 1},\\n map: {value: null},\\n alphaMap: {value: null},\\n alphaTest: {value: 0},\\n uvTransform: {value: new Matrix3()}\\n },\\n sprite: {\\n diffuse: {value: new Color(16777215)},\\n opacity: {value: 1},\\n center: {value: new Vector2(0.5, 0.5)},\\n rotation: {value: 0},\\n map: {value: null},\\n alphaMap: {value: null},\\n alphaTest: {value: 0},\\n uvTransform: {value: new Matrix3()}\\n }\\n};\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib.js\\nvar ShaderLib = {\\n basic: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.specularmap,\\n UniformsLib.envmap,\\n UniformsLib.aomap,\\n UniformsLib.lightmap,\\n UniformsLib.fog\\n ]),\\n vertexShader: ShaderChunk.meshbasic_vert,\\n fragmentShader: ShaderChunk.meshbasic_frag\\n },\\n lambert: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.specularmap,\\n UniformsLib.envmap,\\n UniformsLib.aomap,\\n UniformsLib.lightmap,\\n UniformsLib.emissivemap,\\n UniformsLib.fog,\\n UniformsLib.lights,\\n {\\n emissive: {value: new Color(0)}\\n }\\n ]),\\n vertexShader: ShaderChunk.meshlambert_vert,\\n fragmentShader: ShaderChunk.meshlambert_frag\\n },\\n phong: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.specularmap,\\n UniformsLib.envmap,\\n UniformsLib.aomap,\\n UniformsLib.lightmap,\\n UniformsLib.emissivemap,\\n UniformsLib.bumpmap,\\n UniformsLib.normalmap,\\n UniformsLib.displacementmap,\\n UniformsLib.fog,\\n UniformsLib.lights,\\n {\\n emissive: {value: new Color(0)},\\n specular: {value: new Color(1118481)},\\n shininess: {value: 30}\\n }\\n ]),\\n vertexShader: ShaderChunk.meshphong_vert,\\n fragmentShader: ShaderChunk.meshphong_frag\\n },\\n standard: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.envmap,\\n UniformsLib.aomap,\\n UniformsLib.lightmap,\\n UniformsLib.emissivemap,\\n UniformsLib.bumpmap,\\n UniformsLib.normalmap,\\n UniformsLib.displacementmap,\\n UniformsLib.roughnessmap,\\n UniformsLib.metalnessmap,\\n UniformsLib.fog,\\n UniformsLib.lights,\\n {\\n emissive: {value: new Color(0)},\\n roughness: {value: 1},\\n metalness: {value: 0},\\n envMapIntensity: {value: 1}\\n }\\n ]),\\n vertexShader: ShaderChunk.meshphysical_vert,\\n fragmentShader: ShaderChunk.meshphysical_frag\\n },\\n toon: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.aomap,\\n UniformsLib.lightmap,\\n UniformsLib.emissivemap,\\n UniformsLib.bumpmap,\\n UniformsLib.normalmap,\\n UniformsLib.displacementmap,\\n UniformsLib.gradientmap,\\n UniformsLib.fog,\\n UniformsLib.lights,\\n {\\n emissive: {value: new Color(0)}\\n }\\n ]),\\n vertexShader: ShaderChunk.meshtoon_vert,\\n fragmentShader: ShaderChunk.meshtoon_frag\\n },\\n matcap: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.bumpmap,\\n UniformsLib.normalmap,\\n UniformsLib.displacementmap,\\n UniformsLib.fog,\\n {\\n matcap: {value: null}\\n }\\n ]),\\n vertexShader: ShaderChunk.meshmatcap_vert,\\n fragmentShader: ShaderChunk.meshmatcap_frag\\n },\\n points: {\\n uniforms: mergeUniforms([\\n UniformsLib.points,\\n UniformsLib.fog\\n ]),\\n vertexShader: ShaderChunk.points_vert,\\n fragmentShader: ShaderChunk.points_frag\\n },\\n dashed: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.fog,\\n {\\n scale: {value: 1},\\n dashSize: {value: 1},\\n totalSize: {value: 2}\\n }\\n ]),\\n vertexShader: ShaderChunk.linedashed_vert,\\n fragmentShader: ShaderChunk.linedashed_frag\\n },\\n depth: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.displacementmap\\n ]),\\n vertexShader: ShaderChunk.depth_vert,\\n fragmentShader: ShaderChunk.depth_frag\\n },\\n normal: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.bumpmap,\\n UniformsLib.normalmap,\\n UniformsLib.displacementmap,\\n {\\n opacity: {value: 1}\\n }\\n ]),\\n vertexShader: ShaderChunk.meshnormal_vert,\\n fragmentShader: ShaderChunk.meshnormal_frag\\n },\\n sprite: {\\n uniforms: mergeUniforms([\\n UniformsLib.sprite,\\n UniformsLib.fog\\n ]),\\n vertexShader: ShaderChunk.sprite_vert,\\n fragmentShader: ShaderChunk.sprite_frag\\n },\\n background: {\\n uniforms: {\\n uvTransform: {value: new Matrix3()},\\n t2D: {value: null}\\n },\\n vertexShader: ShaderChunk.background_vert,\\n fragmentShader: ShaderChunk.background_frag\\n },\\n cube: {\\n uniforms: mergeUniforms([\\n UniformsLib.envmap,\\n {\\n opacity: {value: 1}\\n }\\n ]),\\n vertexShader: ShaderChunk.cube_vert,\\n fragmentShader: ShaderChunk.cube_frag\\n },\\n equirect: {\\n uniforms: {\\n tEquirect: {value: null}\\n },\\n vertexShader: ShaderChunk.equirect_vert,\\n fragmentShader: ShaderChunk.equirect_frag\\n },\\n distanceRGBA: {\\n uniforms: mergeUniforms([\\n UniformsLib.common,\\n UniformsLib.displacementmap,\\n {\\n referencePosition: {value: new Vector3()},\\n nearDistance: {value: 1},\\n farDistance: {value: 1e3}\\n }\\n ]),\\n vertexShader: ShaderChunk.distanceRGBA_vert,\\n fragmentShader: ShaderChunk.distanceRGBA_frag\\n },\\n shadow: {\\n uniforms: mergeUniforms([\\n UniformsLib.lights,\\n UniformsLib.fog,\\n {\\n color: {value: new Color(0)},\\n opacity: {value: 1}\\n }\\n ]),\\n vertexShader: ShaderChunk.shadow_vert,\\n fragmentShader: ShaderChunk.shadow_frag\\n }\\n};\\nShaderLib.physical = {\\n uniforms: mergeUniforms([\\n ShaderLib.standard.uniforms,\\n {\\n clearcoat: {value: 0},\\n clearcoatMap: {value: null},\\n clearcoatRoughness: {value: 0},\\n clearcoatRoughnessMap: {value: null},\\n clearcoatNormalScale: {value: new Vector2(1, 1)},\\n clearcoatNormalMap: {value: null},\\n sheen: {value: 0},\\n sheenTint: {value: new Color(0)},\\n sheenRoughness: {value: 0},\\n transmission: {value: 0},\\n transmissionMap: {value: null},\\n transmissionSamplerSize: {value: new Vector2()},\\n transmissionSamplerMap: {value: null},\\n thickness: {value: 0},\\n thicknessMap: {value: null},\\n attenuationDistance: {value: 0},\\n attenuationTint: {value: new Color(0)},\\n specularIntensity: {value: 0},\\n specularIntensityMap: {value: null},\\n specularTint: {value: new Color(1, 1, 1)},\\n specularTintMap: {value: null}\\n }\\n ]),\\n vertexShader: ShaderChunk.meshphysical_vert,\\n fragmentShader: ShaderChunk.meshphysical_frag\\n};\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLBackground.js\\nfunction WebGLBackground(renderer, cubemaps, state, objects, premultipliedAlpha) {\\n const clearColor = new Color(0);\\n let clearAlpha = 0;\\n let planeMesh;\\n let boxMesh;\\n let currentBackground = null;\\n let currentBackgroundVersion = 0;\\n let currentTonemapping = null;\\n function render(renderList, scene) {\\n let forceClear = false;\\n let background2 = scene.isScene === true ? scene.background : null;\\n if (background2 && background2.isTexture) {\\n background2 = cubemaps.get(background2);\\n }\\n const xr = renderer.xr;\\n const session = xr.getSession && xr.getSession();\\n if (session && session.environmentBlendMode === \\\\\\\"additive\\\\\\\") {\\n background2 = null;\\n }\\n if (background2 === null) {\\n setClear(clearColor, clearAlpha);\\n } else if (background2 && background2.isColor) {\\n setClear(background2, 1);\\n forceClear = true;\\n }\\n if (renderer.autoClear || forceClear) {\\n renderer.clear(renderer.autoClearColor, renderer.autoClearDepth, renderer.autoClearStencil);\\n }\\n if (background2 && (background2.isCubeTexture || background2.mapping === CubeUVReflectionMapping)) {\\n if (boxMesh === void 0) {\\n boxMesh = new Mesh(new BoxGeometry(1, 1, 1), new ShaderMaterial({\\n name: \\\\\\\"BackgroundCubeMaterial\\\\\\\",\\n uniforms: cloneUniforms(ShaderLib.cube.uniforms),\\n vertexShader: ShaderLib.cube.vertexShader,\\n fragmentShader: ShaderLib.cube.fragmentShader,\\n side: BackSide,\\n depthTest: false,\\n depthWrite: false,\\n fog: false\\n }));\\n boxMesh.geometry.deleteAttribute(\\\\\\\"normal\\\\\\\");\\n boxMesh.geometry.deleteAttribute(\\\\\\\"uv\\\\\\\");\\n boxMesh.onBeforeRender = function(renderer2, scene2, camera) {\\n this.matrixWorld.copyPosition(camera.matrixWorld);\\n };\\n Object.defineProperty(boxMesh.material, \\\\\\\"envMap\\\\\\\", {\\n get: function() {\\n return this.uniforms.envMap.value;\\n }\\n });\\n objects.update(boxMesh);\\n }\\n boxMesh.material.uniforms.envMap.value = background2;\\n boxMesh.material.uniforms.flipEnvMap.value = background2.isCubeTexture && background2.isRenderTargetTexture === false ? -1 : 1;\\n if (currentBackground !== background2 || currentBackgroundVersion !== background2.version || currentTonemapping !== renderer.toneMapping) {\\n boxMesh.material.needsUpdate = true;\\n currentBackground = background2;\\n currentBackgroundVersion = background2.version;\\n currentTonemapping = renderer.toneMapping;\\n }\\n renderList.unshift(boxMesh, boxMesh.geometry, boxMesh.material, 0, 0, null);\\n } else if (background2 && background2.isTexture) {\\n if (planeMesh === void 0) {\\n planeMesh = new Mesh(new PlaneGeometry(2, 2), new ShaderMaterial({\\n name: \\\\\\\"BackgroundMaterial\\\\\\\",\\n uniforms: cloneUniforms(ShaderLib.background.uniforms),\\n vertexShader: ShaderLib.background.vertexShader,\\n fragmentShader: ShaderLib.background.fragmentShader,\\n side: FrontSide,\\n depthTest: false,\\n depthWrite: false,\\n fog: false\\n }));\\n planeMesh.geometry.deleteAttribute(\\\\\\\"normal\\\\\\\");\\n Object.defineProperty(planeMesh.material, \\\\\\\"map\\\\\\\", {\\n get: function() {\\n return this.uniforms.t2D.value;\\n }\\n });\\n objects.update(planeMesh);\\n }\\n planeMesh.material.uniforms.t2D.value = background2;\\n if (background2.matrixAutoUpdate === true) {\\n background2.updateMatrix();\\n }\\n planeMesh.material.uniforms.uvTransform.value.copy(background2.matrix);\\n if (currentBackground !== background2 || currentBackgroundVersion !== background2.version || currentTonemapping !== renderer.toneMapping) {\\n planeMesh.material.needsUpdate = true;\\n currentBackground = background2;\\n currentBackgroundVersion = background2.version;\\n currentTonemapping = renderer.toneMapping;\\n }\\n renderList.unshift(planeMesh, planeMesh.geometry, planeMesh.material, 0, 0, null);\\n }\\n }\\n function setClear(color, alpha) {\\n state.buffers.color.setClear(color.r, color.g, color.b, alpha, premultipliedAlpha);\\n }\\n return {\\n getClearColor: function() {\\n return clearColor;\\n },\\n setClearColor: function(color, alpha = 1) {\\n clearColor.set(color);\\n clearAlpha = alpha;\\n setClear(clearColor, clearAlpha);\\n },\\n getClearAlpha: function() {\\n return clearAlpha;\\n },\\n setClearAlpha: function(alpha) {\\n clearAlpha = alpha;\\n setClear(clearColor, clearAlpha);\\n },\\n render\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLBindingStates.js\\nfunction WebGLBindingStates(gl, extensions, attributes, capabilities) {\\n const maxVertexAttributes = gl.getParameter(gl.MAX_VERTEX_ATTRIBS);\\n const extension = capabilities.isWebGL2 ? null : extensions.get(\\\\\\\"OES_vertex_array_object\\\\\\\");\\n const vaoAvailable = capabilities.isWebGL2 || extension !== null;\\n const bindingStates = {};\\n const defaultState = createBindingState(null);\\n let currentState = defaultState;\\n function setup(object, material, program, geometry, index) {\\n let updateBuffers = false;\\n if (vaoAvailable) {\\n const state = getBindingState(geometry, program, material);\\n if (currentState !== state) {\\n currentState = state;\\n bindVertexArrayObject(currentState.object);\\n }\\n updateBuffers = needsUpdate(geometry, index);\\n if (updateBuffers)\\n saveCache(geometry, index);\\n } else {\\n const wireframe = material.wireframe === true;\\n if (currentState.geometry !== geometry.id || currentState.program !== program.id || currentState.wireframe !== wireframe) {\\n currentState.geometry = geometry.id;\\n currentState.program = program.id;\\n currentState.wireframe = wireframe;\\n updateBuffers = true;\\n }\\n }\\n if (object.isInstancedMesh === true) {\\n updateBuffers = true;\\n }\\n if (index !== null) {\\n attributes.update(index, gl.ELEMENT_ARRAY_BUFFER);\\n }\\n if (updateBuffers) {\\n setupVertexAttributes(object, material, program, geometry);\\n if (index !== null) {\\n gl.bindBuffer(gl.ELEMENT_ARRAY_BUFFER, attributes.get(index).buffer);\\n }\\n }\\n }\\n function createVertexArrayObject() {\\n if (capabilities.isWebGL2)\\n return gl.createVertexArray();\\n return extension.createVertexArrayOES();\\n }\\n function bindVertexArrayObject(vao) {\\n if (capabilities.isWebGL2)\\n return gl.bindVertexArray(vao);\\n return extension.bindVertexArrayOES(vao);\\n }\\n function deleteVertexArrayObject(vao) {\\n if (capabilities.isWebGL2)\\n return gl.deleteVertexArray(vao);\\n return extension.deleteVertexArrayOES(vao);\\n }\\n function getBindingState(geometry, program, material) {\\n const wireframe = material.wireframe === true;\\n let programMap = bindingStates[geometry.id];\\n if (programMap === void 0) {\\n programMap = {};\\n bindingStates[geometry.id] = programMap;\\n }\\n let stateMap = programMap[program.id];\\n if (stateMap === void 0) {\\n stateMap = {};\\n programMap[program.id] = stateMap;\\n }\\n let state = stateMap[wireframe];\\n if (state === void 0) {\\n state = createBindingState(createVertexArrayObject());\\n stateMap[wireframe] = state;\\n }\\n return state;\\n }\\n function createBindingState(vao) {\\n const newAttributes = [];\\n const enabledAttributes = [];\\n const attributeDivisors = [];\\n for (let i = 0; i < maxVertexAttributes; i++) {\\n newAttributes[i] = 0;\\n enabledAttributes[i] = 0;\\n attributeDivisors[i] = 0;\\n }\\n return {\\n geometry: null,\\n program: null,\\n wireframe: false,\\n newAttributes,\\n enabledAttributes,\\n attributeDivisors,\\n object: vao,\\n attributes: {},\\n index: null\\n };\\n }\\n function needsUpdate(geometry, index) {\\n const cachedAttributes = currentState.attributes;\\n const geometryAttributes = geometry.attributes;\\n let attributesNum = 0;\\n for (const key in geometryAttributes) {\\n const cachedAttribute = cachedAttributes[key];\\n const geometryAttribute = geometryAttributes[key];\\n if (cachedAttribute === void 0)\\n return true;\\n if (cachedAttribute.attribute !== geometryAttribute)\\n return true;\\n if (cachedAttribute.data !== geometryAttribute.data)\\n return true;\\n attributesNum++;\\n }\\n if (currentState.attributesNum !== attributesNum)\\n return true;\\n if (currentState.index !== index)\\n return true;\\n return false;\\n }\\n function saveCache(geometry, index) {\\n const cache = {};\\n const attributes2 = geometry.attributes;\\n let attributesNum = 0;\\n for (const key in attributes2) {\\n const attribute = attributes2[key];\\n const data = {};\\n data.attribute = attribute;\\n if (attribute.data) {\\n data.data = attribute.data;\\n }\\n cache[key] = data;\\n attributesNum++;\\n }\\n currentState.attributes = cache;\\n currentState.attributesNum = attributesNum;\\n currentState.index = index;\\n }\\n function initAttributes() {\\n const newAttributes = currentState.newAttributes;\\n for (let i = 0, il = newAttributes.length; i < il; i++) {\\n newAttributes[i] = 0;\\n }\\n }\\n function enableAttribute(attribute) {\\n enableAttributeAndDivisor(attribute, 0);\\n }\\n function enableAttributeAndDivisor(attribute, meshPerAttribute) {\\n const newAttributes = currentState.newAttributes;\\n const enabledAttributes = currentState.enabledAttributes;\\n const attributeDivisors = currentState.attributeDivisors;\\n newAttributes[attribute] = 1;\\n if (enabledAttributes[attribute] === 0) {\\n gl.enableVertexAttribArray(attribute);\\n enabledAttributes[attribute] = 1;\\n }\\n if (attributeDivisors[attribute] !== meshPerAttribute) {\\n const extension2 = capabilities.isWebGL2 ? gl : extensions.get(\\\\\\\"ANGLE_instanced_arrays\\\\\\\");\\n extension2[capabilities.isWebGL2 ? \\\\\\\"vertexAttribDivisor\\\\\\\" : \\\\\\\"vertexAttribDivisorANGLE\\\\\\\"](attribute, meshPerAttribute);\\n attributeDivisors[attribute] = meshPerAttribute;\\n }\\n }\\n function disableUnusedAttributes() {\\n const newAttributes = currentState.newAttributes;\\n const enabledAttributes = currentState.enabledAttributes;\\n for (let i = 0, il = enabledAttributes.length; i < il; i++) {\\n if (enabledAttributes[i] !== newAttributes[i]) {\\n gl.disableVertexAttribArray(i);\\n enabledAttributes[i] = 0;\\n }\\n }\\n }\\n function vertexAttribPointer(index, size, type, normalized, stride, offset) {\\n if (capabilities.isWebGL2 === true && (type === gl.INT || type === gl.UNSIGNED_INT)) {\\n gl.vertexAttribIPointer(index, size, type, stride, offset);\\n } else {\\n gl.vertexAttribPointer(index, size, type, normalized, stride, offset);\\n }\\n }\\n function setupVertexAttributes(object, material, program, geometry) {\\n if (capabilities.isWebGL2 === false && (object.isInstancedMesh || geometry.isInstancedBufferGeometry)) {\\n if (extensions.get(\\\\\\\"ANGLE_instanced_arrays\\\\\\\") === null)\\n return;\\n }\\n initAttributes();\\n const geometryAttributes = geometry.attributes;\\n const programAttributes = program.getAttributes();\\n const materialDefaultAttributeValues = material.defaultAttributeValues;\\n for (const name in programAttributes) {\\n const programAttribute = programAttributes[name];\\n if (programAttribute.location >= 0) {\\n let geometryAttribute = geometryAttributes[name];\\n if (geometryAttribute === void 0) {\\n if (name === \\\\\\\"instanceMatrix\\\\\\\" && object.instanceMatrix)\\n geometryAttribute = object.instanceMatrix;\\n if (name === \\\\\\\"instanceColor\\\\\\\" && object.instanceColor)\\n geometryAttribute = object.instanceColor;\\n }\\n if (geometryAttribute !== void 0) {\\n const normalized = geometryAttribute.normalized;\\n const size = geometryAttribute.itemSize;\\n const attribute = attributes.get(geometryAttribute);\\n if (attribute === void 0)\\n continue;\\n const buffer = attribute.buffer;\\n const type = attribute.type;\\n const bytesPerElement = attribute.bytesPerElement;\\n if (geometryAttribute.isInterleavedBufferAttribute) {\\n const data = geometryAttribute.data;\\n const stride = data.stride;\\n const offset = geometryAttribute.offset;\\n if (data && data.isInstancedInterleavedBuffer) {\\n for (let i = 0; i < programAttribute.locationSize; i++) {\\n enableAttributeAndDivisor(programAttribute.location + i, data.meshPerAttribute);\\n }\\n if (object.isInstancedMesh !== true && geometry._maxInstanceCount === void 0) {\\n geometry._maxInstanceCount = data.meshPerAttribute * data.count;\\n }\\n } else {\\n for (let i = 0; i < programAttribute.locationSize; i++) {\\n enableAttribute(programAttribute.location + i);\\n }\\n }\\n gl.bindBuffer(gl.ARRAY_BUFFER, buffer);\\n for (let i = 0; i < programAttribute.locationSize; i++) {\\n vertexAttribPointer(programAttribute.location + i, size / programAttribute.locationSize, type, normalized, stride * bytesPerElement, (offset + size / programAttribute.locationSize * i) * bytesPerElement);\\n }\\n } else {\\n if (geometryAttribute.isInstancedBufferAttribute) {\\n for (let i = 0; i < programAttribute.locationSize; i++) {\\n enableAttributeAndDivisor(programAttribute.location + i, geometryAttribute.meshPerAttribute);\\n }\\n if (object.isInstancedMesh !== true && geometry._maxInstanceCount === void 0) {\\n geometry._maxInstanceCount = geometryAttribute.meshPerAttribute * geometryAttribute.count;\\n }\\n } else {\\n for (let i = 0; i < programAttribute.locationSize; i++) {\\n enableAttribute(programAttribute.location + i);\\n }\\n }\\n gl.bindBuffer(gl.ARRAY_BUFFER, buffer);\\n for (let i = 0; i < programAttribute.locationSize; i++) {\\n vertexAttribPointer(programAttribute.location + i, size / programAttribute.locationSize, type, normalized, size * bytesPerElement, size / programAttribute.locationSize * i * bytesPerElement);\\n }\\n }\\n } else if (materialDefaultAttributeValues !== void 0) {\\n const value = materialDefaultAttributeValues[name];\\n if (value !== void 0) {\\n switch (value.length) {\\n case 2:\\n gl.vertexAttrib2fv(programAttribute.location, value);\\n break;\\n case 3:\\n gl.vertexAttrib3fv(programAttribute.location, value);\\n break;\\n case 4:\\n gl.vertexAttrib4fv(programAttribute.location, value);\\n break;\\n default:\\n gl.vertexAttrib1fv(programAttribute.location, value);\\n }\\n }\\n }\\n }\\n }\\n disableUnusedAttributes();\\n }\\n function dispose() {\\n reset();\\n for (const geometryId in bindingStates) {\\n const programMap = bindingStates[geometryId];\\n for (const programId in programMap) {\\n const stateMap = programMap[programId];\\n for (const wireframe in stateMap) {\\n deleteVertexArrayObject(stateMap[wireframe].object);\\n delete stateMap[wireframe];\\n }\\n delete programMap[programId];\\n }\\n delete bindingStates[geometryId];\\n }\\n }\\n function releaseStatesOfGeometry(geometry) {\\n if (bindingStates[geometry.id] === void 0)\\n return;\\n const programMap = bindingStates[geometry.id];\\n for (const programId in programMap) {\\n const stateMap = programMap[programId];\\n for (const wireframe in stateMap) {\\n deleteVertexArrayObject(stateMap[wireframe].object);\\n delete stateMap[wireframe];\\n }\\n delete programMap[programId];\\n }\\n delete bindingStates[geometry.id];\\n }\\n function releaseStatesOfProgram(program) {\\n for (const geometryId in bindingStates) {\\n const programMap = bindingStates[geometryId];\\n if (programMap[program.id] === void 0)\\n continue;\\n const stateMap = programMap[program.id];\\n for (const wireframe in stateMap) {\\n deleteVertexArrayObject(stateMap[wireframe].object);\\n delete stateMap[wireframe];\\n }\\n delete programMap[program.id];\\n }\\n }\\n function reset() {\\n resetDefaultState();\\n if (currentState === defaultState)\\n return;\\n currentState = defaultState;\\n bindVertexArrayObject(currentState.object);\\n }\\n function resetDefaultState() {\\n defaultState.geometry = null;\\n defaultState.program = null;\\n defaultState.wireframe = false;\\n }\\n return {\\n setup,\\n reset,\\n resetDefaultState,\\n dispose,\\n releaseStatesOfGeometry,\\n releaseStatesOfProgram,\\n initAttributes,\\n enableAttribute,\\n disableUnusedAttributes\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLBufferRenderer.js\\nfunction WebGLBufferRenderer(gl, extensions, info, capabilities) {\\n const isWebGL2 = capabilities.isWebGL2;\\n let mode;\\n function setMode(value) {\\n mode = value;\\n }\\n function render(start, count) {\\n gl.drawArrays(mode, start, count);\\n info.update(count, mode, 1);\\n }\\n function renderInstances(start, count, primcount) {\\n if (primcount === 0)\\n return;\\n let extension, methodName;\\n if (isWebGL2) {\\n extension = gl;\\n methodName = \\\\\\\"drawArraysInstanced\\\\\\\";\\n } else {\\n extension = extensions.get(\\\\\\\"ANGLE_instanced_arrays\\\\\\\");\\n methodName = \\\\\\\"drawArraysInstancedANGLE\\\\\\\";\\n if (extension === null) {\\n console.error(\\\\\\\"THREE.WebGLBufferRenderer: using THREE.InstancedBufferGeometry but hardware does not support extension ANGLE_instanced_arrays.\\\\\\\");\\n return;\\n }\\n }\\n extension[methodName](mode, start, count, primcount);\\n info.update(count, mode, primcount);\\n }\\n this.setMode = setMode;\\n this.render = render;\\n this.renderInstances = renderInstances;\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLCapabilities.js\\nfunction WebGLCapabilities(gl, extensions, parameters) {\\n let maxAnisotropy;\\n function getMaxAnisotropy() {\\n if (maxAnisotropy !== void 0)\\n return maxAnisotropy;\\n if (extensions.has(\\\\\\\"EXT_texture_filter_anisotropic\\\\\\\") === true) {\\n const extension = extensions.get(\\\\\\\"EXT_texture_filter_anisotropic\\\\\\\");\\n maxAnisotropy = gl.getParameter(extension.MAX_TEXTURE_MAX_ANISOTROPY_EXT);\\n } else {\\n maxAnisotropy = 0;\\n }\\n return maxAnisotropy;\\n }\\n function getMaxPrecision(precision2) {\\n if (precision2 === \\\\\\\"highp\\\\\\\") {\\n if (gl.getShaderPrecisionFormat(gl.VERTEX_SHADER, gl.HIGH_FLOAT).precision > 0 && gl.getShaderPrecisionFormat(gl.FRAGMENT_SHADER, gl.HIGH_FLOAT).precision > 0) {\\n return \\\\\\\"highp\\\\\\\";\\n }\\n precision2 = \\\\\\\"mediump\\\\\\\";\\n }\\n if (precision2 === \\\\\\\"mediump\\\\\\\") {\\n if (gl.getShaderPrecisionFormat(gl.VERTEX_SHADER, gl.MEDIUM_FLOAT).precision > 0 && gl.getShaderPrecisionFormat(gl.FRAGMENT_SHADER, gl.MEDIUM_FLOAT).precision > 0) {\\n return \\\\\\\"mediump\\\\\\\";\\n }\\n }\\n return \\\\\\\"lowp\\\\\\\";\\n }\\n const isWebGL2 = typeof WebGL2RenderingContext !== \\\\\\\"undefined\\\\\\\" && gl instanceof WebGL2RenderingContext || typeof WebGL2ComputeRenderingContext !== \\\\\\\"undefined\\\\\\\" && gl instanceof WebGL2ComputeRenderingContext;\\n let precision = parameters.precision !== void 0 ? parameters.precision : \\\\\\\"highp\\\\\\\";\\n const maxPrecision = getMaxPrecision(precision);\\n if (maxPrecision !== precision) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer:\\\\\\\", precision, \\\\\\\"not supported, using\\\\\\\", maxPrecision, \\\\\\\"instead.\\\\\\\");\\n precision = maxPrecision;\\n }\\n const drawBuffers = isWebGL2 || extensions.has(\\\\\\\"WEBGL_draw_buffers\\\\\\\");\\n const logarithmicDepthBuffer = parameters.logarithmicDepthBuffer === true;\\n const maxTextures = gl.getParameter(gl.MAX_TEXTURE_IMAGE_UNITS);\\n const maxVertexTextures = gl.getParameter(gl.MAX_VERTEX_TEXTURE_IMAGE_UNITS);\\n const maxTextureSize = gl.getParameter(gl.MAX_TEXTURE_SIZE);\\n const maxCubemapSize = gl.getParameter(gl.MAX_CUBE_MAP_TEXTURE_SIZE);\\n const maxAttributes = gl.getParameter(gl.MAX_VERTEX_ATTRIBS);\\n const maxVertexUniforms = gl.getParameter(gl.MAX_VERTEX_UNIFORM_VECTORS);\\n const maxVaryings = gl.getParameter(gl.MAX_VARYING_VECTORS);\\n const maxFragmentUniforms = gl.getParameter(gl.MAX_FRAGMENT_UNIFORM_VECTORS);\\n const vertexTextures = maxVertexTextures > 0;\\n const floatFragmentTextures = isWebGL2 || extensions.has(\\\\\\\"OES_texture_float\\\\\\\");\\n const floatVertexTextures = vertexTextures && floatFragmentTextures;\\n const maxSamples = isWebGL2 ? gl.getParameter(gl.MAX_SAMPLES) : 0;\\n return {\\n isWebGL2,\\n drawBuffers,\\n getMaxAnisotropy,\\n getMaxPrecision,\\n precision,\\n logarithmicDepthBuffer,\\n maxTextures,\\n maxVertexTextures,\\n maxTextureSize,\\n maxCubemapSize,\\n maxAttributes,\\n maxVertexUniforms,\\n maxVaryings,\\n maxFragmentUniforms,\\n vertexTextures,\\n floatFragmentTextures,\\n floatVertexTextures,\\n maxSamples\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLClipping.js\\nfunction WebGLClipping(properties) {\\n const scope = this;\\n let globalState = null, numGlobalPlanes = 0, localClippingEnabled = false, renderingShadows = false;\\n const plane = new Plane(), viewNormalMatrix = new Matrix3(), uniform = {value: null, needsUpdate: false};\\n this.uniform = uniform;\\n this.numPlanes = 0;\\n this.numIntersection = 0;\\n this.init = function(planes, enableLocalClipping, camera) {\\n const enabled = planes.length !== 0 || enableLocalClipping || numGlobalPlanes !== 0 || localClippingEnabled;\\n localClippingEnabled = enableLocalClipping;\\n globalState = projectPlanes(planes, camera, 0);\\n numGlobalPlanes = planes.length;\\n return enabled;\\n };\\n this.beginShadows = function() {\\n renderingShadows = true;\\n projectPlanes(null);\\n };\\n this.endShadows = function() {\\n renderingShadows = false;\\n resetGlobalState();\\n };\\n this.setState = function(material, camera, useCache) {\\n const planes = material.clippingPlanes, clipIntersection = material.clipIntersection, clipShadows = material.clipShadows;\\n const materialProperties = properties.get(material);\\n if (!localClippingEnabled || planes === null || planes.length === 0 || renderingShadows && !clipShadows) {\\n if (renderingShadows) {\\n projectPlanes(null);\\n } else {\\n resetGlobalState();\\n }\\n } else {\\n const nGlobal = renderingShadows ? 0 : numGlobalPlanes, lGlobal = nGlobal * 4;\\n let dstArray = materialProperties.clippingState || null;\\n uniform.value = dstArray;\\n dstArray = projectPlanes(planes, camera, lGlobal, useCache);\\n for (let i = 0; i !== lGlobal; ++i) {\\n dstArray[i] = globalState[i];\\n }\\n materialProperties.clippingState = dstArray;\\n this.numIntersection = clipIntersection ? this.numPlanes : 0;\\n this.numPlanes += nGlobal;\\n }\\n };\\n function resetGlobalState() {\\n if (uniform.value !== globalState) {\\n uniform.value = globalState;\\n uniform.needsUpdate = numGlobalPlanes > 0;\\n }\\n scope.numPlanes = numGlobalPlanes;\\n scope.numIntersection = 0;\\n }\\n function projectPlanes(planes, camera, dstOffset, skipTransform) {\\n const nPlanes = planes !== null ? planes.length : 0;\\n let dstArray = null;\\n if (nPlanes !== 0) {\\n dstArray = uniform.value;\\n if (skipTransform !== true || dstArray === null) {\\n const flatSize = dstOffset + nPlanes * 4, viewMatrix = camera.matrixWorldInverse;\\n viewNormalMatrix.getNormalMatrix(viewMatrix);\\n if (dstArray === null || dstArray.length < flatSize) {\\n dstArray = new Float32Array(flatSize);\\n }\\n for (let i = 0, i4 = dstOffset; i !== nPlanes; ++i, i4 += 4) {\\n plane.copy(planes[i]).applyMatrix4(viewMatrix, viewNormalMatrix);\\n plane.normal.toArray(dstArray, i4);\\n dstArray[i4 + 3] = plane.constant;\\n }\\n }\\n uniform.value = dstArray;\\n uniform.needsUpdate = true;\\n }\\n scope.numPlanes = nPlanes;\\n scope.numIntersection = 0;\\n return dstArray;\\n }\\n}\\n\\n// ../../../node_modules/three/src/extras/ImageUtils.js\\nvar _canvas;\\nvar ImageUtils = class {\\n static getDataURL(image) {\\n if (/^data:/i.test(image.src)) {\\n return image.src;\\n }\\n if (typeof HTMLCanvasElement == \\\\\\\"undefined\\\\\\\") {\\n return image.src;\\n }\\n let canvas;\\n if (image instanceof HTMLCanvasElement) {\\n canvas = image;\\n } else {\\n if (_canvas === void 0)\\n _canvas = createElementNS(\\\\\\\"canvas\\\\\\\");\\n _canvas.width = image.width;\\n _canvas.height = image.height;\\n const context = _canvas.getContext(\\\\\\\"2d\\\\\\\");\\n if (image instanceof ImageData) {\\n context.putImageData(image, 0, 0);\\n } else {\\n context.drawImage(image, 0, 0, image.width, image.height);\\n }\\n canvas = _canvas;\\n }\\n if (canvas.width > 2048 || canvas.height > 2048) {\\n console.warn(\\\\\\\"THREE.ImageUtils.getDataURL: Image converted to jpg for performance reasons\\\\\\\", image);\\n return canvas.toDataURL(\\\\\\\"image/jpeg\\\\\\\", 0.6);\\n } else {\\n return canvas.toDataURL(\\\\\\\"image/png\\\\\\\");\\n }\\n }\\n};\\n\\n// ../../../node_modules/three/src/textures/Texture.js\\nvar textureId = 0;\\nvar Texture = class extends EventDispatcher {\\n constructor(image = Texture.DEFAULT_IMAGE, mapping = Texture.DEFAULT_MAPPING, wrapS = ClampToEdgeWrapping, wrapT = ClampToEdgeWrapping, magFilter = LinearFilter, minFilter = LinearMipmapLinearFilter, format = RGBAFormat, type = UnsignedByteType, anisotropy = 1, encoding = LinearEncoding) {\\n super();\\n Object.defineProperty(this, \\\\\\\"id\\\\\\\", {value: textureId++});\\n this.uuid = generateUUID();\\n this.name = \\\\\\\"\\\\\\\";\\n this.image = image;\\n this.mipmaps = [];\\n this.mapping = mapping;\\n this.wrapS = wrapS;\\n this.wrapT = wrapT;\\n this.magFilter = magFilter;\\n this.minFilter = minFilter;\\n this.anisotropy = anisotropy;\\n this.format = format;\\n this.internalFormat = null;\\n this.type = type;\\n this.offset = new Vector2(0, 0);\\n this.repeat = new Vector2(1, 1);\\n this.center = new Vector2(0, 0);\\n this.rotation = 0;\\n this.matrixAutoUpdate = true;\\n this.matrix = new Matrix3();\\n this.generateMipmaps = true;\\n this.premultiplyAlpha = false;\\n this.flipY = true;\\n this.unpackAlignment = 4;\\n this.encoding = encoding;\\n this.version = 0;\\n this.onUpdate = null;\\n this.isRenderTargetTexture = false;\\n }\\n updateMatrix() {\\n this.matrix.setUvTransform(this.offset.x, this.offset.y, this.repeat.x, this.repeat.y, this.rotation, this.center.x, this.center.y);\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n copy(source) {\\n this.name = source.name;\\n this.image = source.image;\\n this.mipmaps = source.mipmaps.slice(0);\\n this.mapping = source.mapping;\\n this.wrapS = source.wrapS;\\n this.wrapT = source.wrapT;\\n this.magFilter = source.magFilter;\\n this.minFilter = source.minFilter;\\n this.anisotropy = source.anisotropy;\\n this.format = source.format;\\n this.internalFormat = source.internalFormat;\\n this.type = source.type;\\n this.offset.copy(source.offset);\\n this.repeat.copy(source.repeat);\\n this.center.copy(source.center);\\n this.rotation = source.rotation;\\n this.matrixAutoUpdate = source.matrixAutoUpdate;\\n this.matrix.copy(source.matrix);\\n this.generateMipmaps = source.generateMipmaps;\\n this.premultiplyAlpha = source.premultiplyAlpha;\\n this.flipY = source.flipY;\\n this.unpackAlignment = source.unpackAlignment;\\n this.encoding = source.encoding;\\n return this;\\n }\\n toJSON(meta) {\\n const isRootObject = meta === void 0 || typeof meta === \\\\\\\"string\\\\\\\";\\n if (!isRootObject && meta.textures[this.uuid] !== void 0) {\\n return meta.textures[this.uuid];\\n }\\n const output = {\\n metadata: {\\n version: 4.5,\\n type: \\\\\\\"Texture\\\\\\\",\\n generator: \\\\\\\"Texture.toJSON\\\\\\\"\\n },\\n uuid: this.uuid,\\n name: this.name,\\n mapping: this.mapping,\\n repeat: [this.repeat.x, this.repeat.y],\\n offset: [this.offset.x, this.offset.y],\\n center: [this.center.x, this.center.y],\\n rotation: this.rotation,\\n wrap: [this.wrapS, this.wrapT],\\n format: this.format,\\n type: this.type,\\n encoding: this.encoding,\\n minFilter: this.minFilter,\\n magFilter: this.magFilter,\\n anisotropy: this.anisotropy,\\n flipY: this.flipY,\\n premultiplyAlpha: this.premultiplyAlpha,\\n unpackAlignment: this.unpackAlignment\\n };\\n if (this.image !== void 0) {\\n const image = this.image;\\n if (image.uuid === void 0) {\\n image.uuid = generateUUID();\\n }\\n if (!isRootObject && meta.images[image.uuid] === void 0) {\\n let url;\\n if (Array.isArray(image)) {\\n url = [];\\n for (let i = 0, l = image.length; i < l; i++) {\\n if (image[i].isDataTexture) {\\n url.push(serializeImage(image[i].image));\\n } else {\\n url.push(serializeImage(image[i]));\\n }\\n }\\n } else {\\n url = serializeImage(image);\\n }\\n meta.images[image.uuid] = {\\n uuid: image.uuid,\\n url\\n };\\n }\\n output.image = image.uuid;\\n }\\n if (!isRootObject) {\\n meta.textures[this.uuid] = output;\\n }\\n return output;\\n }\\n dispose() {\\n this.dispatchEvent({type: \\\\\\\"dispose\\\\\\\"});\\n }\\n transformUv(uv) {\\n if (this.mapping !== UVMapping)\\n return uv;\\n uv.applyMatrix3(this.matrix);\\n if (uv.x < 0 || uv.x > 1) {\\n switch (this.wrapS) {\\n case RepeatWrapping:\\n uv.x = uv.x - Math.floor(uv.x);\\n break;\\n case ClampToEdgeWrapping:\\n uv.x = uv.x < 0 ? 0 : 1;\\n break;\\n case MirroredRepeatWrapping:\\n if (Math.abs(Math.floor(uv.x) % 2) === 1) {\\n uv.x = Math.ceil(uv.x) - uv.x;\\n } else {\\n uv.x = uv.x - Math.floor(uv.x);\\n }\\n break;\\n }\\n }\\n if (uv.y < 0 || uv.y > 1) {\\n switch (this.wrapT) {\\n case RepeatWrapping:\\n uv.y = uv.y - Math.floor(uv.y);\\n break;\\n case ClampToEdgeWrapping:\\n uv.y = uv.y < 0 ? 0 : 1;\\n break;\\n case MirroredRepeatWrapping:\\n if (Math.abs(Math.floor(uv.y) % 2) === 1) {\\n uv.y = Math.ceil(uv.y) - uv.y;\\n } else {\\n uv.y = uv.y - Math.floor(uv.y);\\n }\\n break;\\n }\\n }\\n if (this.flipY) {\\n uv.y = 1 - uv.y;\\n }\\n return uv;\\n }\\n set needsUpdate(value) {\\n if (value === true)\\n this.version++;\\n }\\n};\\nTexture.DEFAULT_IMAGE = void 0;\\nTexture.DEFAULT_MAPPING = UVMapping;\\nTexture.prototype.isTexture = true;\\nfunction serializeImage(image) {\\n if (typeof HTMLImageElement !== \\\\\\\"undefined\\\\\\\" && image instanceof HTMLImageElement || typeof HTMLCanvasElement !== \\\\\\\"undefined\\\\\\\" && image instanceof HTMLCanvasElement || typeof ImageBitmap !== \\\\\\\"undefined\\\\\\\" && image instanceof ImageBitmap) {\\n return ImageUtils.getDataURL(image);\\n } else {\\n if (image.data) {\\n return {\\n data: Array.prototype.slice.call(image.data),\\n width: image.width,\\n height: image.height,\\n type: image.data.constructor.name\\n };\\n } else {\\n console.warn(\\\\\\\"THREE.Texture: Unable to serialize Texture.\\\\\\\");\\n return {};\\n }\\n }\\n}\\n\\n// ../../../node_modules/three/src/renderers/WebGLRenderTarget.js\\nvar WebGLRenderTarget = class extends EventDispatcher {\\n constructor(width, height, options = {}) {\\n super();\\n this.width = width;\\n this.height = height;\\n this.depth = 1;\\n this.scissor = new Vector4(0, 0, width, height);\\n this.scissorTest = false;\\n this.viewport = new Vector4(0, 0, width, height);\\n this.texture = new Texture(void 0, options.mapping, options.wrapS, options.wrapT, options.magFilter, options.minFilter, options.format, options.type, options.anisotropy, options.encoding);\\n this.texture.isRenderTargetTexture = true;\\n this.texture.image = {width, height, depth: 1};\\n this.texture.generateMipmaps = options.generateMipmaps !== void 0 ? options.generateMipmaps : false;\\n this.texture.internalFormat = options.internalFormat !== void 0 ? options.internalFormat : null;\\n this.texture.minFilter = options.minFilter !== void 0 ? options.minFilter : LinearFilter;\\n this.depthBuffer = options.depthBuffer !== void 0 ? options.depthBuffer : true;\\n this.stencilBuffer = options.stencilBuffer !== void 0 ? options.stencilBuffer : false;\\n this.depthTexture = options.depthTexture !== void 0 ? options.depthTexture : null;\\n }\\n setTexture(texture) {\\n texture.image = {\\n width: this.width,\\n height: this.height,\\n depth: this.depth\\n };\\n this.texture = texture;\\n }\\n setSize(width, height, depth2 = 1) {\\n if (this.width !== width || this.height !== height || this.depth !== depth2) {\\n this.width = width;\\n this.height = height;\\n this.depth = depth2;\\n this.texture.image.width = width;\\n this.texture.image.height = height;\\n this.texture.image.depth = depth2;\\n this.dispose();\\n }\\n this.viewport.set(0, 0, width, height);\\n this.scissor.set(0, 0, width, height);\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n copy(source) {\\n this.width = source.width;\\n this.height = source.height;\\n this.depth = source.depth;\\n this.viewport.copy(source.viewport);\\n this.texture = source.texture.clone();\\n this.texture.image = {...this.texture.image};\\n this.depthBuffer = source.depthBuffer;\\n this.stencilBuffer = source.stencilBuffer;\\n this.depthTexture = source.depthTexture;\\n return this;\\n }\\n dispose() {\\n this.dispatchEvent({type: \\\\\\\"dispose\\\\\\\"});\\n }\\n};\\nWebGLRenderTarget.prototype.isWebGLRenderTarget = true;\\n\\n// ../../../node_modules/three/src/cameras/Camera.js\\nvar Camera = class extends Object3D {\\n constructor() {\\n super();\\n this.type = \\\\\\\"Camera\\\\\\\";\\n this.matrixWorldInverse = new Matrix4();\\n this.projectionMatrix = new Matrix4();\\n this.projectionMatrixInverse = new Matrix4();\\n }\\n copy(source, recursive) {\\n super.copy(source, recursive);\\n this.matrixWorldInverse.copy(source.matrixWorldInverse);\\n this.projectionMatrix.copy(source.projectionMatrix);\\n this.projectionMatrixInverse.copy(source.projectionMatrixInverse);\\n return this;\\n }\\n getWorldDirection(target) {\\n this.updateWorldMatrix(true, false);\\n const e = this.matrixWorld.elements;\\n return target.set(-e[8], -e[9], -e[10]).normalize();\\n }\\n updateMatrixWorld(force) {\\n super.updateMatrixWorld(force);\\n this.matrixWorldInverse.copy(this.matrixWorld).invert();\\n }\\n updateWorldMatrix(updateParents, updateChildren) {\\n super.updateWorldMatrix(updateParents, updateChildren);\\n this.matrixWorldInverse.copy(this.matrixWorld).invert();\\n }\\n clone() {\\n return new this.constructor().copy(this);\\n }\\n};\\nCamera.prototype.isCamera = true;\\n\\n// ../../../node_modules/three/src/cameras/PerspectiveCamera.js\\nvar PerspectiveCamera = class extends Camera {\\n constructor(fov2 = 50, aspect2 = 1, near = 0.1, far = 2e3) {\\n super();\\n this.type = \\\\\\\"PerspectiveCamera\\\\\\\";\\n this.fov = fov2;\\n this.zoom = 1;\\n this.near = near;\\n this.far = far;\\n this.focus = 10;\\n this.aspect = aspect2;\\n this.view = null;\\n this.filmGauge = 35;\\n this.filmOffset = 0;\\n this.updateProjectionMatrix();\\n }\\n copy(source, recursive) {\\n super.copy(source, recursive);\\n this.fov = source.fov;\\n this.zoom = source.zoom;\\n this.near = source.near;\\n this.far = source.far;\\n this.focus = source.focus;\\n this.aspect = source.aspect;\\n this.view = source.view === null ? null : Object.assign({}, source.view);\\n this.filmGauge = source.filmGauge;\\n this.filmOffset = source.filmOffset;\\n return this;\\n }\\n setFocalLength(focalLength) {\\n const vExtentSlope = 0.5 * this.getFilmHeight() / focalLength;\\n this.fov = RAD2DEG * 2 * Math.atan(vExtentSlope);\\n this.updateProjectionMatrix();\\n }\\n getFocalLength() {\\n const vExtentSlope = Math.tan(DEG2RAD * 0.5 * this.fov);\\n return 0.5 * this.getFilmHeight() / vExtentSlope;\\n }\\n getEffectiveFOV() {\\n return RAD2DEG * 2 * Math.atan(Math.tan(DEG2RAD * 0.5 * this.fov) / this.zoom);\\n }\\n getFilmWidth() {\\n return this.filmGauge * Math.min(this.aspect, 1);\\n }\\n getFilmHeight() {\\n return this.filmGauge / Math.max(this.aspect, 1);\\n }\\n setViewOffset(fullWidth, fullHeight, x, y, width, height) {\\n this.aspect = fullWidth / fullHeight;\\n if (this.view === null) {\\n this.view = {\\n enabled: true,\\n fullWidth: 1,\\n fullHeight: 1,\\n offsetX: 0,\\n offsetY: 0,\\n width: 1,\\n height: 1\\n };\\n }\\n this.view.enabled = true;\\n this.view.fullWidth = fullWidth;\\n this.view.fullHeight = fullHeight;\\n this.view.offsetX = x;\\n this.view.offsetY = y;\\n this.view.width = width;\\n this.view.height = height;\\n this.updateProjectionMatrix();\\n }\\n clearViewOffset() {\\n if (this.view !== null) {\\n this.view.enabled = false;\\n }\\n this.updateProjectionMatrix();\\n }\\n updateProjectionMatrix() {\\n const near = this.near;\\n let top = near * Math.tan(DEG2RAD * 0.5 * this.fov) / this.zoom;\\n let height = 2 * top;\\n let width = this.aspect * height;\\n let left = -0.5 * width;\\n const view = this.view;\\n if (this.view !== null && this.view.enabled) {\\n const fullWidth = view.fullWidth, fullHeight = view.fullHeight;\\n left += view.offsetX * width / fullWidth;\\n top -= view.offsetY * height / fullHeight;\\n width *= view.width / fullWidth;\\n height *= view.height / fullHeight;\\n }\\n const skew = this.filmOffset;\\n if (skew !== 0)\\n left += near * skew / this.getFilmWidth();\\n this.projectionMatrix.makePerspective(left, left + width, top, top - height, near, this.far);\\n this.projectionMatrixInverse.copy(this.projectionMatrix).invert();\\n }\\n toJSON(meta) {\\n const data = super.toJSON(meta);\\n data.object.fov = this.fov;\\n data.object.zoom = this.zoom;\\n data.object.near = this.near;\\n data.object.far = this.far;\\n data.object.focus = this.focus;\\n data.object.aspect = this.aspect;\\n if (this.view !== null)\\n data.object.view = Object.assign({}, this.view);\\n data.object.filmGauge = this.filmGauge;\\n data.object.filmOffset = this.filmOffset;\\n return data;\\n }\\n};\\nPerspectiveCamera.prototype.isPerspectiveCamera = true;\\n\\n// ../../../node_modules/three/src/cameras/CubeCamera.js\\nvar fov = 90;\\nvar aspect = 1;\\nvar CubeCamera = class extends Object3D {\\n constructor(near, far, renderTarget) {\\n super();\\n this.type = \\\\\\\"CubeCamera\\\\\\\";\\n if (renderTarget.isWebGLCubeRenderTarget !== true) {\\n console.error(\\\\\\\"THREE.CubeCamera: The constructor now expects an instance of WebGLCubeRenderTarget as third parameter.\\\\\\\");\\n return;\\n }\\n this.renderTarget = renderTarget;\\n const cameraPX = new PerspectiveCamera(fov, aspect, near, far);\\n cameraPX.layers = this.layers;\\n cameraPX.up.set(0, -1, 0);\\n cameraPX.lookAt(new Vector3(1, 0, 0));\\n this.add(cameraPX);\\n const cameraNX = new PerspectiveCamera(fov, aspect, near, far);\\n cameraNX.layers = this.layers;\\n cameraNX.up.set(0, -1, 0);\\n cameraNX.lookAt(new Vector3(-1, 0, 0));\\n this.add(cameraNX);\\n const cameraPY = new PerspectiveCamera(fov, aspect, near, far);\\n cameraPY.layers = this.layers;\\n cameraPY.up.set(0, 0, 1);\\n cameraPY.lookAt(new Vector3(0, 1, 0));\\n this.add(cameraPY);\\n const cameraNY = new PerspectiveCamera(fov, aspect, near, far);\\n cameraNY.layers = this.layers;\\n cameraNY.up.set(0, 0, -1);\\n cameraNY.lookAt(new Vector3(0, -1, 0));\\n this.add(cameraNY);\\n const cameraPZ = new PerspectiveCamera(fov, aspect, near, far);\\n cameraPZ.layers = this.layers;\\n cameraPZ.up.set(0, -1, 0);\\n cameraPZ.lookAt(new Vector3(0, 0, 1));\\n this.add(cameraPZ);\\n const cameraNZ = new PerspectiveCamera(fov, aspect, near, far);\\n cameraNZ.layers = this.layers;\\n cameraNZ.up.set(0, -1, 0);\\n cameraNZ.lookAt(new Vector3(0, 0, -1));\\n this.add(cameraNZ);\\n }\\n update(renderer, scene) {\\n if (this.parent === null)\\n this.updateMatrixWorld();\\n const renderTarget = this.renderTarget;\\n const [cameraPX, cameraNX, cameraPY, cameraNY, cameraPZ, cameraNZ] = this.children;\\n const currentXrEnabled = renderer.xr.enabled;\\n const currentRenderTarget = renderer.getRenderTarget();\\n renderer.xr.enabled = false;\\n const generateMipmaps = renderTarget.texture.generateMipmaps;\\n renderTarget.texture.generateMipmaps = false;\\n renderer.setRenderTarget(renderTarget, 0);\\n renderer.render(scene, cameraPX);\\n renderer.setRenderTarget(renderTarget, 1);\\n renderer.render(scene, cameraNX);\\n renderer.setRenderTarget(renderTarget, 2);\\n renderer.render(scene, cameraPY);\\n renderer.setRenderTarget(renderTarget, 3);\\n renderer.render(scene, cameraNY);\\n renderer.setRenderTarget(renderTarget, 4);\\n renderer.render(scene, cameraPZ);\\n renderTarget.texture.generateMipmaps = generateMipmaps;\\n renderer.setRenderTarget(renderTarget, 5);\\n renderer.render(scene, cameraNZ);\\n renderer.setRenderTarget(currentRenderTarget);\\n renderer.xr.enabled = currentXrEnabled;\\n }\\n};\\n\\n// ../../../node_modules/three/src/textures/CubeTexture.js\\nvar CubeTexture = class extends Texture {\\n constructor(images, mapping, wrapS, wrapT, magFilter, minFilter, format, type, anisotropy, encoding) {\\n images = images !== void 0 ? images : [];\\n mapping = mapping !== void 0 ? mapping : CubeReflectionMapping;\\n super(images, mapping, wrapS, wrapT, magFilter, minFilter, format, type, anisotropy, encoding);\\n this.flipY = false;\\n }\\n get images() {\\n return this.image;\\n }\\n set images(value) {\\n this.image = value;\\n }\\n};\\nCubeTexture.prototype.isCubeTexture = true;\\n\\n// ../../../node_modules/three/src/renderers/WebGLCubeRenderTarget.js\\nvar WebGLCubeRenderTarget = class extends WebGLRenderTarget {\\n constructor(size, options, dummy) {\\n if (Number.isInteger(options)) {\\n console.warn(\\\\\\\"THREE.WebGLCubeRenderTarget: constructor signature is now WebGLCubeRenderTarget( size, options )\\\\\\\");\\n options = dummy;\\n }\\n super(size, size, options);\\n options = options || {};\\n this.texture = new CubeTexture(void 0, options.mapping, options.wrapS, options.wrapT, options.magFilter, options.minFilter, options.format, options.type, options.anisotropy, options.encoding);\\n this.texture.isRenderTargetTexture = true;\\n this.texture.generateMipmaps = options.generateMipmaps !== void 0 ? options.generateMipmaps : false;\\n this.texture.minFilter = options.minFilter !== void 0 ? options.minFilter : LinearFilter;\\n this.texture._needsFlipEnvMap = false;\\n }\\n fromEquirectangularTexture(renderer, texture) {\\n this.texture.type = texture.type;\\n this.texture.format = RGBAFormat;\\n this.texture.encoding = texture.encoding;\\n this.texture.generateMipmaps = texture.generateMipmaps;\\n this.texture.minFilter = texture.minFilter;\\n this.texture.magFilter = texture.magFilter;\\n const shader = {\\n uniforms: {\\n tEquirect: {value: null}\\n },\\n vertexShader: `\\n\\n\\t\\t\\t\\tvarying vec3 vWorldDirection;\\n\\n\\t\\t\\t\\tvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\\n\\n\\t\\t\\t\\t\\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\\n\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\tvoid main() {\\n\\n\\t\\t\\t\\t\\tvWorldDirection = transformDirection( position, modelMatrix );\\n\\n\\t\\t\\t\\t\\t#include \\n\\t\\t\\t\\t\\t#include \\n\\n\\t\\t\\t\\t}\\n\\t\\t\\t`,\\n fragmentShader: `\\n\\n\\t\\t\\t\\tuniform sampler2D tEquirect;\\n\\n\\t\\t\\t\\tvarying vec3 vWorldDirection;\\n\\n\\t\\t\\t\\t#include \\n\\n\\t\\t\\t\\tvoid main() {\\n\\n\\t\\t\\t\\t\\tvec3 direction = normalize( vWorldDirection );\\n\\n\\t\\t\\t\\t\\tvec2 sampleUV = equirectUv( direction );\\n\\n\\t\\t\\t\\t\\tgl_FragColor = texture2D( tEquirect, sampleUV );\\n\\n\\t\\t\\t\\t}\\n\\t\\t\\t`\\n };\\n const geometry = new BoxGeometry(5, 5, 5);\\n const material = new ShaderMaterial({\\n name: \\\\\\\"CubemapFromEquirect\\\\\\\",\\n uniforms: cloneUniforms(shader.uniforms),\\n vertexShader: shader.vertexShader,\\n fragmentShader: shader.fragmentShader,\\n side: BackSide,\\n blending: NoBlending\\n });\\n material.uniforms.tEquirect.value = texture;\\n const mesh = new Mesh(geometry, material);\\n const currentMinFilter = texture.minFilter;\\n if (texture.minFilter === LinearMipmapLinearFilter)\\n texture.minFilter = LinearFilter;\\n const camera = new CubeCamera(1, 10, this);\\n camera.update(renderer, mesh);\\n texture.minFilter = currentMinFilter;\\n mesh.geometry.dispose();\\n mesh.material.dispose();\\n return this;\\n }\\n clear(renderer, color, depth2, stencil) {\\n const currentRenderTarget = renderer.getRenderTarget();\\n for (let i = 0; i < 6; i++) {\\n renderer.setRenderTarget(this, i);\\n renderer.clear(color, depth2, stencil);\\n }\\n renderer.setRenderTarget(currentRenderTarget);\\n }\\n};\\nWebGLCubeRenderTarget.prototype.isWebGLCubeRenderTarget = true;\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLCubeMaps.js\\nfunction WebGLCubeMaps(renderer) {\\n let cubemaps = new WeakMap();\\n function mapTextureMapping(texture, mapping) {\\n if (mapping === EquirectangularReflectionMapping) {\\n texture.mapping = CubeReflectionMapping;\\n } else if (mapping === EquirectangularRefractionMapping) {\\n texture.mapping = CubeRefractionMapping;\\n }\\n return texture;\\n }\\n function get(texture) {\\n if (texture && texture.isTexture && texture.isRenderTargetTexture === false) {\\n const mapping = texture.mapping;\\n if (mapping === EquirectangularReflectionMapping || mapping === EquirectangularRefractionMapping) {\\n if (cubemaps.has(texture)) {\\n const cubemap = cubemaps.get(texture).texture;\\n return mapTextureMapping(cubemap, texture.mapping);\\n } else {\\n const image = texture.image;\\n if (image && image.height > 0) {\\n const currentRenderTarget = renderer.getRenderTarget();\\n const renderTarget = new WebGLCubeRenderTarget(image.height / 2);\\n renderTarget.fromEquirectangularTexture(renderer, texture);\\n cubemaps.set(texture, renderTarget);\\n renderer.setRenderTarget(currentRenderTarget);\\n texture.addEventListener(\\\\\\\"dispose\\\\\\\", onTextureDispose);\\n return mapTextureMapping(renderTarget.texture, texture.mapping);\\n } else {\\n return null;\\n }\\n }\\n }\\n }\\n return texture;\\n }\\n function onTextureDispose(event) {\\n const texture = event.target;\\n texture.removeEventListener(\\\\\\\"dispose\\\\\\\", onTextureDispose);\\n const cubemap = cubemaps.get(texture);\\n if (cubemap !== void 0) {\\n cubemaps.delete(texture);\\n cubemap.dispose();\\n }\\n }\\n function dispose() {\\n cubemaps = new WeakMap();\\n }\\n return {\\n get,\\n dispose\\n };\\n}\\n\\n// ../../../node_modules/three/src/cameras/OrthographicCamera.js\\nvar OrthographicCamera = class extends Camera {\\n constructor(left = -1, right = 1, top = 1, bottom = -1, near = 0.1, far = 2e3) {\\n super();\\n this.type = \\\\\\\"OrthographicCamera\\\\\\\";\\n this.zoom = 1;\\n this.view = null;\\n this.left = left;\\n this.right = right;\\n this.top = top;\\n this.bottom = bottom;\\n this.near = near;\\n this.far = far;\\n this.updateProjectionMatrix();\\n }\\n copy(source, recursive) {\\n super.copy(source, recursive);\\n this.left = source.left;\\n this.right = source.right;\\n this.top = source.top;\\n this.bottom = source.bottom;\\n this.near = source.near;\\n this.far = source.far;\\n this.zoom = source.zoom;\\n this.view = source.view === null ? null : Object.assign({}, source.view);\\n return this;\\n }\\n setViewOffset(fullWidth, fullHeight, x, y, width, height) {\\n if (this.view === null) {\\n this.view = {\\n enabled: true,\\n fullWidth: 1,\\n fullHeight: 1,\\n offsetX: 0,\\n offsetY: 0,\\n width: 1,\\n height: 1\\n };\\n }\\n this.view.enabled = true;\\n this.view.fullWidth = fullWidth;\\n this.view.fullHeight = fullHeight;\\n this.view.offsetX = x;\\n this.view.offsetY = y;\\n this.view.width = width;\\n this.view.height = height;\\n this.updateProjectionMatrix();\\n }\\n clearViewOffset() {\\n if (this.view !== null) {\\n this.view.enabled = false;\\n }\\n this.updateProjectionMatrix();\\n }\\n updateProjectionMatrix() {\\n const dx = (this.right - this.left) / (2 * this.zoom);\\n const dy = (this.top - this.bottom) / (2 * this.zoom);\\n const cx = (this.right + this.left) / 2;\\n const cy = (this.top + this.bottom) / 2;\\n let left = cx - dx;\\n let right = cx + dx;\\n let top = cy + dy;\\n let bottom = cy - dy;\\n if (this.view !== null && this.view.enabled) {\\n const scaleW = (this.right - this.left) / this.view.fullWidth / this.zoom;\\n const scaleH = (this.top - this.bottom) / this.view.fullHeight / this.zoom;\\n left += scaleW * this.view.offsetX;\\n right = left + scaleW * this.view.width;\\n top -= scaleH * this.view.offsetY;\\n bottom = top - scaleH * this.view.height;\\n }\\n this.projectionMatrix.makeOrthographic(left, right, top, bottom, this.near, this.far);\\n this.projectionMatrixInverse.copy(this.projectionMatrix).invert();\\n }\\n toJSON(meta) {\\n const data = super.toJSON(meta);\\n data.object.zoom = this.zoom;\\n data.object.left = this.left;\\n data.object.right = this.right;\\n data.object.top = this.top;\\n data.object.bottom = this.bottom;\\n data.object.near = this.near;\\n data.object.far = this.far;\\n if (this.view !== null)\\n data.object.view = Object.assign({}, this.view);\\n return data;\\n }\\n};\\nOrthographicCamera.prototype.isOrthographicCamera = true;\\n\\n// ../../../node_modules/three/src/materials/RawShaderMaterial.js\\nvar RawShaderMaterial = class extends ShaderMaterial {\\n constructor(parameters) {\\n super(parameters);\\n this.type = \\\\\\\"RawShaderMaterial\\\\\\\";\\n }\\n};\\nRawShaderMaterial.prototype.isRawShaderMaterial = true;\\n\\n// ../../../node_modules/three/src/extras/PMREMGenerator.js\\nvar LOD_MIN = 4;\\nvar LOD_MAX = 8;\\nvar SIZE_MAX = Math.pow(2, LOD_MAX);\\nvar EXTRA_LOD_SIGMA = [0.125, 0.215, 0.35, 0.446, 0.526, 0.582];\\nvar TOTAL_LODS = LOD_MAX - LOD_MIN + 1 + EXTRA_LOD_SIGMA.length;\\nvar MAX_SAMPLES = 20;\\nvar ENCODINGS = {\\n [LinearEncoding]: 0,\\n [sRGBEncoding]: 1,\\n [RGBEEncoding]: 2,\\n [RGBM7Encoding]: 3,\\n [RGBM16Encoding]: 4,\\n [RGBDEncoding]: 5,\\n [GammaEncoding]: 6\\n};\\nvar _flatCamera = /* @__PURE__ */ new OrthographicCamera();\\nvar {_lodPlanes, _sizeLods, _sigmas} = /* @__PURE__ */ _createPlanes();\\nvar _clearColor = /* @__PURE__ */ new Color();\\nvar _oldTarget = null;\\nvar PHI = (1 + Math.sqrt(5)) / 2;\\nvar INV_PHI = 1 / PHI;\\nvar _axisDirections = [\\n /* @__PURE__ */ new Vector3(1, 1, 1),\\n /* @__PURE__ */ new Vector3(-1, 1, 1),\\n /* @__PURE__ */ new Vector3(1, 1, -1),\\n /* @__PURE__ */ new Vector3(-1, 1, -1),\\n /* @__PURE__ */ new Vector3(0, PHI, INV_PHI),\\n /* @__PURE__ */ new Vector3(0, PHI, -INV_PHI),\\n /* @__PURE__ */ new Vector3(INV_PHI, 0, PHI),\\n /* @__PURE__ */ new Vector3(-INV_PHI, 0, PHI),\\n /* @__PURE__ */ new Vector3(PHI, INV_PHI, 0),\\n /* @__PURE__ */ new Vector3(-PHI, INV_PHI, 0)\\n];\\nvar PMREMGenerator = class {\\n constructor(renderer) {\\n this._renderer = renderer;\\n this._pingPongRenderTarget = null;\\n this._blurMaterial = _getBlurShader(MAX_SAMPLES);\\n this._equirectShader = null;\\n this._cubemapShader = null;\\n this._compileMaterial(this._blurMaterial);\\n }\\n fromScene(scene, sigma = 0, near = 0.1, far = 100) {\\n _oldTarget = this._renderer.getRenderTarget();\\n const cubeUVRenderTarget = this._allocateTargets();\\n this._sceneToCubeUV(scene, near, far, cubeUVRenderTarget);\\n if (sigma > 0) {\\n this._blur(cubeUVRenderTarget, 0, 0, sigma);\\n }\\n this._applyPMREM(cubeUVRenderTarget);\\n this._cleanup(cubeUVRenderTarget);\\n return cubeUVRenderTarget;\\n }\\n fromEquirectangular(equirectangular) {\\n return this._fromTexture(equirectangular);\\n }\\n fromCubemap(cubemap) {\\n return this._fromTexture(cubemap);\\n }\\n compileCubemapShader() {\\n if (this._cubemapShader === null) {\\n this._cubemapShader = _getCubemapShader();\\n this._compileMaterial(this._cubemapShader);\\n }\\n }\\n compileEquirectangularShader() {\\n if (this._equirectShader === null) {\\n this._equirectShader = _getEquirectShader();\\n this._compileMaterial(this._equirectShader);\\n }\\n }\\n dispose() {\\n this._blurMaterial.dispose();\\n if (this._cubemapShader !== null)\\n this._cubemapShader.dispose();\\n if (this._equirectShader !== null)\\n this._equirectShader.dispose();\\n for (let i = 0; i < _lodPlanes.length; i++) {\\n _lodPlanes[i].dispose();\\n }\\n }\\n _cleanup(outputTarget) {\\n this._pingPongRenderTarget.dispose();\\n this._renderer.setRenderTarget(_oldTarget);\\n outputTarget.scissorTest = false;\\n _setViewport(outputTarget, 0, 0, outputTarget.width, outputTarget.height);\\n }\\n _fromTexture(texture) {\\n _oldTarget = this._renderer.getRenderTarget();\\n const cubeUVRenderTarget = this._allocateTargets(texture);\\n this._textureToCubeUV(texture, cubeUVRenderTarget);\\n this._applyPMREM(cubeUVRenderTarget);\\n this._cleanup(cubeUVRenderTarget);\\n return cubeUVRenderTarget;\\n }\\n _allocateTargets(texture) {\\n const params = {\\n magFilter: NearestFilter,\\n minFilter: NearestFilter,\\n generateMipmaps: false,\\n type: UnsignedByteType,\\n format: RGBEFormat,\\n encoding: _isLDR(texture) ? texture.encoding : RGBEEncoding,\\n depthBuffer: false\\n };\\n const cubeUVRenderTarget = _createRenderTarget(params);\\n cubeUVRenderTarget.depthBuffer = texture ? false : true;\\n this._pingPongRenderTarget = _createRenderTarget(params);\\n return cubeUVRenderTarget;\\n }\\n _compileMaterial(material) {\\n const tmpMesh = new Mesh(_lodPlanes[0], material);\\n this._renderer.compile(tmpMesh, _flatCamera);\\n }\\n _sceneToCubeUV(scene, near, far, cubeUVRenderTarget) {\\n const fov2 = 90;\\n const aspect2 = 1;\\n const cubeCamera = new PerspectiveCamera(fov2, aspect2, near, far);\\n const upSign = [1, -1, 1, 1, 1, 1];\\n const forwardSign = [1, 1, 1, -1, -1, -1];\\n const renderer = this._renderer;\\n const originalAutoClear = renderer.autoClear;\\n const outputEncoding = renderer.outputEncoding;\\n const toneMapping = renderer.toneMapping;\\n renderer.getClearColor(_clearColor);\\n renderer.toneMapping = NoToneMapping;\\n renderer.outputEncoding = LinearEncoding;\\n renderer.autoClear = false;\\n const backgroundMaterial = new MeshBasicMaterial({\\n name: \\\\\\\"PMREM.Background\\\\\\\",\\n side: BackSide,\\n depthWrite: false,\\n depthTest: false\\n });\\n const backgroundBox = new Mesh(new BoxGeometry(), backgroundMaterial);\\n let useSolidColor = false;\\n const background2 = scene.background;\\n if (background2) {\\n if (background2.isColor) {\\n backgroundMaterial.color.copy(background2);\\n scene.background = null;\\n useSolidColor = true;\\n }\\n } else {\\n backgroundMaterial.color.copy(_clearColor);\\n useSolidColor = true;\\n }\\n for (let i = 0; i < 6; i++) {\\n const col = i % 3;\\n if (col == 0) {\\n cubeCamera.up.set(0, upSign[i], 0);\\n cubeCamera.lookAt(forwardSign[i], 0, 0);\\n } else if (col == 1) {\\n cubeCamera.up.set(0, 0, upSign[i]);\\n cubeCamera.lookAt(0, forwardSign[i], 0);\\n } else {\\n cubeCamera.up.set(0, upSign[i], 0);\\n cubeCamera.lookAt(0, 0, forwardSign[i]);\\n }\\n _setViewport(cubeUVRenderTarget, col * SIZE_MAX, i > 2 ? SIZE_MAX : 0, SIZE_MAX, SIZE_MAX);\\n renderer.setRenderTarget(cubeUVRenderTarget);\\n if (useSolidColor) {\\n renderer.render(backgroundBox, cubeCamera);\\n }\\n renderer.render(scene, cubeCamera);\\n }\\n backgroundBox.geometry.dispose();\\n backgroundBox.material.dispose();\\n renderer.toneMapping = toneMapping;\\n renderer.outputEncoding = outputEncoding;\\n renderer.autoClear = originalAutoClear;\\n scene.background = background2;\\n }\\n _setEncoding(uniform, texture) {\\n if (this._renderer.capabilities.isWebGL2 === true && texture.format === RGBAFormat && texture.type === UnsignedByteType && texture.encoding === sRGBEncoding) {\\n uniform.value = ENCODINGS[LinearEncoding];\\n } else {\\n uniform.value = ENCODINGS[texture.encoding];\\n }\\n }\\n _textureToCubeUV(texture, cubeUVRenderTarget) {\\n const renderer = this._renderer;\\n if (texture.isCubeTexture) {\\n if (this._cubemapShader == null) {\\n this._cubemapShader = _getCubemapShader();\\n }\\n } else {\\n if (this._equirectShader == null) {\\n this._equirectShader = _getEquirectShader();\\n }\\n }\\n const material = texture.isCubeTexture ? this._cubemapShader : this._equirectShader;\\n const mesh = new Mesh(_lodPlanes[0], material);\\n const uniforms = material.uniforms;\\n uniforms[\\\\\\\"envMap\\\\\\\"].value = texture;\\n if (!texture.isCubeTexture) {\\n uniforms[\\\\\\\"texelSize\\\\\\\"].value.set(1 / texture.image.width, 1 / texture.image.height);\\n }\\n this._setEncoding(uniforms[\\\\\\\"inputEncoding\\\\\\\"], texture);\\n this._setEncoding(uniforms[\\\\\\\"outputEncoding\\\\\\\"], cubeUVRenderTarget.texture);\\n _setViewport(cubeUVRenderTarget, 0, 0, 3 * SIZE_MAX, 2 * SIZE_MAX);\\n renderer.setRenderTarget(cubeUVRenderTarget);\\n renderer.render(mesh, _flatCamera);\\n }\\n _applyPMREM(cubeUVRenderTarget) {\\n const renderer = this._renderer;\\n const autoClear = renderer.autoClear;\\n renderer.autoClear = false;\\n for (let i = 1; i < TOTAL_LODS; i++) {\\n const sigma = Math.sqrt(_sigmas[i] * _sigmas[i] - _sigmas[i - 1] * _sigmas[i - 1]);\\n const poleAxis = _axisDirections[(i - 1) % _axisDirections.length];\\n this._blur(cubeUVRenderTarget, i - 1, i, sigma, poleAxis);\\n }\\n renderer.autoClear = autoClear;\\n }\\n _blur(cubeUVRenderTarget, lodIn, lodOut, sigma, poleAxis) {\\n const pingPongRenderTarget = this._pingPongRenderTarget;\\n this._halfBlur(cubeUVRenderTarget, pingPongRenderTarget, lodIn, lodOut, sigma, \\\\\\\"latitudinal\\\\\\\", poleAxis);\\n this._halfBlur(pingPongRenderTarget, cubeUVRenderTarget, lodOut, lodOut, sigma, \\\\\\\"longitudinal\\\\\\\", poleAxis);\\n }\\n _halfBlur(targetIn, targetOut, lodIn, lodOut, sigmaRadians, direction, poleAxis) {\\n const renderer = this._renderer;\\n const blurMaterial = this._blurMaterial;\\n if (direction !== \\\\\\\"latitudinal\\\\\\\" && direction !== \\\\\\\"longitudinal\\\\\\\") {\\n console.error(\\\\\\\"blur direction must be either latitudinal or longitudinal!\\\\\\\");\\n }\\n const STANDARD_DEVIATIONS = 3;\\n const blurMesh = new Mesh(_lodPlanes[lodOut], blurMaterial);\\n const blurUniforms = blurMaterial.uniforms;\\n const pixels = _sizeLods[lodIn] - 1;\\n const radiansPerPixel = isFinite(sigmaRadians) ? Math.PI / (2 * pixels) : 2 * Math.PI / (2 * MAX_SAMPLES - 1);\\n const sigmaPixels = sigmaRadians / radiansPerPixel;\\n const samples = isFinite(sigmaRadians) ? 1 + Math.floor(STANDARD_DEVIATIONS * sigmaPixels) : MAX_SAMPLES;\\n if (samples > MAX_SAMPLES) {\\n console.warn(`sigmaRadians, ${sigmaRadians}, is too large and will clip, as it requested ${samples} samples when the maximum is set to ${MAX_SAMPLES}`);\\n }\\n const weights = [];\\n let sum = 0;\\n for (let i = 0; i < MAX_SAMPLES; ++i) {\\n const x2 = i / sigmaPixels;\\n const weight = Math.exp(-x2 * x2 / 2);\\n weights.push(weight);\\n if (i == 0) {\\n sum += weight;\\n } else if (i < samples) {\\n sum += 2 * weight;\\n }\\n }\\n for (let i = 0; i < weights.length; i++) {\\n weights[i] = weights[i] / sum;\\n }\\n blurUniforms[\\\\\\\"envMap\\\\\\\"].value = targetIn.texture;\\n blurUniforms[\\\\\\\"samples\\\\\\\"].value = samples;\\n blurUniforms[\\\\\\\"weights\\\\\\\"].value = weights;\\n blurUniforms[\\\\\\\"latitudinal\\\\\\\"].value = direction === \\\\\\\"latitudinal\\\\\\\";\\n if (poleAxis) {\\n blurUniforms[\\\\\\\"poleAxis\\\\\\\"].value = poleAxis;\\n }\\n blurUniforms[\\\\\\\"dTheta\\\\\\\"].value = radiansPerPixel;\\n blurUniforms[\\\\\\\"mipInt\\\\\\\"].value = LOD_MAX - lodIn;\\n this._setEncoding(blurUniforms[\\\\\\\"inputEncoding\\\\\\\"], targetIn.texture);\\n this._setEncoding(blurUniforms[\\\\\\\"outputEncoding\\\\\\\"], targetIn.texture);\\n const outputSize = _sizeLods[lodOut];\\n const x = 3 * Math.max(0, SIZE_MAX - 2 * outputSize);\\n const y = (lodOut === 0 ? 0 : 2 * SIZE_MAX) + 2 * outputSize * (lodOut > LOD_MAX - LOD_MIN ? lodOut - LOD_MAX + LOD_MIN : 0);\\n _setViewport(targetOut, x, y, 3 * outputSize, 2 * outputSize);\\n renderer.setRenderTarget(targetOut);\\n renderer.render(blurMesh, _flatCamera);\\n }\\n};\\nfunction _isLDR(texture) {\\n if (texture === void 0 || texture.type !== UnsignedByteType)\\n return false;\\n return texture.encoding === LinearEncoding || texture.encoding === sRGBEncoding || texture.encoding === GammaEncoding;\\n}\\nfunction _createPlanes() {\\n const _lodPlanes2 = [];\\n const _sizeLods2 = [];\\n const _sigmas2 = [];\\n let lod = LOD_MAX;\\n for (let i = 0; i < TOTAL_LODS; i++) {\\n const sizeLod = Math.pow(2, lod);\\n _sizeLods2.push(sizeLod);\\n let sigma = 1 / sizeLod;\\n if (i > LOD_MAX - LOD_MIN) {\\n sigma = EXTRA_LOD_SIGMA[i - LOD_MAX + LOD_MIN - 1];\\n } else if (i == 0) {\\n sigma = 0;\\n }\\n _sigmas2.push(sigma);\\n const texelSize = 1 / (sizeLod - 1);\\n const min = -texelSize / 2;\\n const max = 1 + texelSize / 2;\\n const uv1 = [min, min, max, min, max, max, min, min, max, max, min, max];\\n const cubeFaces = 6;\\n const vertices = 6;\\n const positionSize = 3;\\n const uvSize = 2;\\n const faceIndexSize = 1;\\n const position = new Float32Array(positionSize * vertices * cubeFaces);\\n const uv = new Float32Array(uvSize * vertices * cubeFaces);\\n const faceIndex = new Float32Array(faceIndexSize * vertices * cubeFaces);\\n for (let face = 0; face < cubeFaces; face++) {\\n const x = face % 3 * 2 / 3 - 1;\\n const y = face > 2 ? 0 : -1;\\n const coordinates = [\\n x,\\n y,\\n 0,\\n x + 2 / 3,\\n y,\\n 0,\\n x + 2 / 3,\\n y + 1,\\n 0,\\n x,\\n y,\\n 0,\\n x + 2 / 3,\\n y + 1,\\n 0,\\n x,\\n y + 1,\\n 0\\n ];\\n position.set(coordinates, positionSize * vertices * face);\\n uv.set(uv1, uvSize * vertices * face);\\n const fill = [face, face, face, face, face, face];\\n faceIndex.set(fill, faceIndexSize * vertices * face);\\n }\\n const planes = new BufferGeometry();\\n planes.setAttribute(\\\\\\\"position\\\\\\\", new BufferAttribute(position, positionSize));\\n planes.setAttribute(\\\\\\\"uv\\\\\\\", new BufferAttribute(uv, uvSize));\\n planes.setAttribute(\\\\\\\"faceIndex\\\\\\\", new BufferAttribute(faceIndex, faceIndexSize));\\n _lodPlanes2.push(planes);\\n if (lod > LOD_MIN) {\\n lod--;\\n }\\n }\\n return {_lodPlanes: _lodPlanes2, _sizeLods: _sizeLods2, _sigmas: _sigmas2};\\n}\\nfunction _createRenderTarget(params) {\\n const cubeUVRenderTarget = new WebGLRenderTarget(3 * SIZE_MAX, 3 * SIZE_MAX, params);\\n cubeUVRenderTarget.texture.mapping = CubeUVReflectionMapping;\\n cubeUVRenderTarget.texture.name = \\\\\\\"PMREM.cubeUv\\\\\\\";\\n cubeUVRenderTarget.scissorTest = true;\\n return cubeUVRenderTarget;\\n}\\nfunction _setViewport(target, x, y, width, height) {\\n target.viewport.set(x, y, width, height);\\n target.scissor.set(x, y, width, height);\\n}\\nfunction _getBlurShader(maxSamples) {\\n const weights = new Float32Array(maxSamples);\\n const poleAxis = new Vector3(0, 1, 0);\\n const shaderMaterial = new RawShaderMaterial({\\n name: \\\\\\\"SphericalGaussianBlur\\\\\\\",\\n defines: {n: maxSamples},\\n uniforms: {\\n envMap: {value: null},\\n samples: {value: 1},\\n weights: {value: weights},\\n latitudinal: {value: false},\\n dTheta: {value: 0},\\n mipInt: {value: 0},\\n poleAxis: {value: poleAxis},\\n inputEncoding: {value: ENCODINGS[LinearEncoding]},\\n outputEncoding: {value: ENCODINGS[LinearEncoding]}\\n },\\n vertexShader: _getCommonVertexShader(),\\n fragmentShader: `\\n\\n\\t\\t\\tprecision mediump float;\\n\\t\\t\\tprecision mediump int;\\n\\n\\t\\t\\tvarying vec3 vOutputDirection;\\n\\n\\t\\t\\tuniform sampler2D envMap;\\n\\t\\t\\tuniform int samples;\\n\\t\\t\\tuniform float weights[ n ];\\n\\t\\t\\tuniform bool latitudinal;\\n\\t\\t\\tuniform float dTheta;\\n\\t\\t\\tuniform float mipInt;\\n\\t\\t\\tuniform vec3 poleAxis;\\n\\n\\t\\t\\t${_getEncodings()}\\n\\n\\t\\t\\t#define ENVMAP_TYPE_CUBE_UV\\n\\t\\t\\t#include \\n\\n\\t\\t\\tvec3 getSample( float theta, vec3 axis ) {\\n\\n\\t\\t\\t\\tfloat cosTheta = cos( theta );\\n\\t\\t\\t\\t// Rodrigues' axis-angle rotation\\n\\t\\t\\t\\tvec3 sampleDirection = vOutputDirection * cosTheta\\n\\t\\t\\t\\t\\t+ cross( axis, vOutputDirection ) * sin( theta )\\n\\t\\t\\t\\t\\t+ axis * dot( axis, vOutputDirection ) * ( 1.0 - cosTheta );\\n\\n\\t\\t\\t\\treturn bilinearCubeUV( envMap, sampleDirection, mipInt );\\n\\n\\t\\t\\t}\\n\\n\\t\\t\\tvoid main() {\\n\\n\\t\\t\\t\\tvec3 axis = latitudinal ? poleAxis : cross( poleAxis, vOutputDirection );\\n\\n\\t\\t\\t\\tif ( all( equal( axis, vec3( 0.0 ) ) ) ) {\\n\\n\\t\\t\\t\\t\\taxis = vec3( vOutputDirection.z, 0.0, - vOutputDirection.x );\\n\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\taxis = normalize( axis );\\n\\n\\t\\t\\t\\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\\n\\t\\t\\t\\tgl_FragColor.rgb += weights[ 0 ] * getSample( 0.0, axis );\\n\\n\\t\\t\\t\\tfor ( int i = 1; i < n; i++ ) {\\n\\n\\t\\t\\t\\t\\tif ( i >= samples ) {\\n\\n\\t\\t\\t\\t\\t\\tbreak;\\n\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\tfloat theta = dTheta * float( i );\\n\\t\\t\\t\\t\\tgl_FragColor.rgb += weights[ i ] * getSample( -1.0 * theta, axis );\\n\\t\\t\\t\\t\\tgl_FragColor.rgb += weights[ i ] * getSample( theta, axis );\\n\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\tgl_FragColor = linearToOutputTexel( gl_FragColor );\\n\\n\\t\\t\\t}\\n\\t\\t`,\\n blending: NoBlending,\\n depthTest: false,\\n depthWrite: false\\n });\\n return shaderMaterial;\\n}\\nfunction _getEquirectShader() {\\n const texelSize = new Vector2(1, 1);\\n const shaderMaterial = new RawShaderMaterial({\\n name: \\\\\\\"EquirectangularToCubeUV\\\\\\\",\\n uniforms: {\\n envMap: {value: null},\\n texelSize: {value: texelSize},\\n inputEncoding: {value: ENCODINGS[LinearEncoding]},\\n outputEncoding: {value: ENCODINGS[LinearEncoding]}\\n },\\n vertexShader: _getCommonVertexShader(),\\n fragmentShader: `\\n\\n\\t\\t\\tprecision mediump float;\\n\\t\\t\\tprecision mediump int;\\n\\n\\t\\t\\tvarying vec3 vOutputDirection;\\n\\n\\t\\t\\tuniform sampler2D envMap;\\n\\t\\t\\tuniform vec2 texelSize;\\n\\n\\t\\t\\t${_getEncodings()}\\n\\n\\t\\t\\t#include \\n\\n\\t\\t\\tvoid main() {\\n\\n\\t\\t\\t\\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\\n\\n\\t\\t\\t\\tvec3 outputDirection = normalize( vOutputDirection );\\n\\t\\t\\t\\tvec2 uv = equirectUv( outputDirection );\\n\\n\\t\\t\\t\\tvec2 f = fract( uv / texelSize - 0.5 );\\n\\t\\t\\t\\tuv -= f * texelSize;\\n\\t\\t\\t\\tvec3 tl = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\n\\t\\t\\t\\tuv.x += texelSize.x;\\n\\t\\t\\t\\tvec3 tr = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\n\\t\\t\\t\\tuv.y += texelSize.y;\\n\\t\\t\\t\\tvec3 br = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\n\\t\\t\\t\\tuv.x -= texelSize.x;\\n\\t\\t\\t\\tvec3 bl = envMapTexelToLinear( texture2D ( envMap, uv ) ).rgb;\\n\\n\\t\\t\\t\\tvec3 tm = mix( tl, tr, f.x );\\n\\t\\t\\t\\tvec3 bm = mix( bl, br, f.x );\\n\\t\\t\\t\\tgl_FragColor.rgb = mix( tm, bm, f.y );\\n\\n\\t\\t\\t\\tgl_FragColor = linearToOutputTexel( gl_FragColor );\\n\\n\\t\\t\\t}\\n\\t\\t`,\\n blending: NoBlending,\\n depthTest: false,\\n depthWrite: false\\n });\\n return shaderMaterial;\\n}\\nfunction _getCubemapShader() {\\n const shaderMaterial = new RawShaderMaterial({\\n name: \\\\\\\"CubemapToCubeUV\\\\\\\",\\n uniforms: {\\n envMap: {value: null},\\n inputEncoding: {value: ENCODINGS[LinearEncoding]},\\n outputEncoding: {value: ENCODINGS[LinearEncoding]}\\n },\\n vertexShader: _getCommonVertexShader(),\\n fragmentShader: `\\n\\n\\t\\t\\tprecision mediump float;\\n\\t\\t\\tprecision mediump int;\\n\\n\\t\\t\\tvarying vec3 vOutputDirection;\\n\\n\\t\\t\\tuniform samplerCube envMap;\\n\\n\\t\\t\\t${_getEncodings()}\\n\\n\\t\\t\\tvoid main() {\\n\\n\\t\\t\\t\\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\\n\\t\\t\\t\\tgl_FragColor.rgb = envMapTexelToLinear( textureCube( envMap, vec3( - vOutputDirection.x, vOutputDirection.yz ) ) ).rgb;\\n\\t\\t\\t\\tgl_FragColor = linearToOutputTexel( gl_FragColor );\\n\\n\\t\\t\\t}\\n\\t\\t`,\\n blending: NoBlending,\\n depthTest: false,\\n depthWrite: false\\n });\\n return shaderMaterial;\\n}\\nfunction _getCommonVertexShader() {\\n return `\\n\\n\\t\\tprecision mediump float;\\n\\t\\tprecision mediump int;\\n\\n\\t\\tattribute vec3 position;\\n\\t\\tattribute vec2 uv;\\n\\t\\tattribute float faceIndex;\\n\\n\\t\\tvarying vec3 vOutputDirection;\\n\\n\\t\\t// RH coordinate system; PMREM face-indexing convention\\n\\t\\tvec3 getDirection( vec2 uv, float face ) {\\n\\n\\t\\t\\tuv = 2.0 * uv - 1.0;\\n\\n\\t\\t\\tvec3 direction = vec3( uv, 1.0 );\\n\\n\\t\\t\\tif ( face == 0.0 ) {\\n\\n\\t\\t\\t\\tdirection = direction.zyx; // ( 1, v, u ) pos x\\n\\n\\t\\t\\t} else if ( face == 1.0 ) {\\n\\n\\t\\t\\t\\tdirection = direction.xzy;\\n\\t\\t\\t\\tdirection.xz *= -1.0; // ( -u, 1, -v ) pos y\\n\\n\\t\\t\\t} else if ( face == 2.0 ) {\\n\\n\\t\\t\\t\\tdirection.x *= -1.0; // ( -u, v, 1 ) pos z\\n\\n\\t\\t\\t} else if ( face == 3.0 ) {\\n\\n\\t\\t\\t\\tdirection = direction.zyx;\\n\\t\\t\\t\\tdirection.xz *= -1.0; // ( -1, v, -u ) neg x\\n\\n\\t\\t\\t} else if ( face == 4.0 ) {\\n\\n\\t\\t\\t\\tdirection = direction.xzy;\\n\\t\\t\\t\\tdirection.xy *= -1.0; // ( -u, -1, v ) neg y\\n\\n\\t\\t\\t} else if ( face == 5.0 ) {\\n\\n\\t\\t\\t\\tdirection.z *= -1.0; // ( u, v, -1 ) neg z\\n\\n\\t\\t\\t}\\n\\n\\t\\t\\treturn direction;\\n\\n\\t\\t}\\n\\n\\t\\tvoid main() {\\n\\n\\t\\t\\tvOutputDirection = getDirection( uv, faceIndex );\\n\\t\\t\\tgl_Position = vec4( position, 1.0 );\\n\\n\\t\\t}\\n\\t`;\\n}\\nfunction _getEncodings() {\\n return `\\n\\n\\t\\tuniform int inputEncoding;\\n\\t\\tuniform int outputEncoding;\\n\\n\\t\\t#include \\n\\n\\t\\tvec4 inputTexelToLinear( vec4 value ) {\\n\\n\\t\\t\\tif ( inputEncoding == 0 ) {\\n\\n\\t\\t\\t\\treturn value;\\n\\n\\t\\t\\t} else if ( inputEncoding == 1 ) {\\n\\n\\t\\t\\t\\treturn sRGBToLinear( value );\\n\\n\\t\\t\\t} else if ( inputEncoding == 2 ) {\\n\\n\\t\\t\\t\\treturn RGBEToLinear( value );\\n\\n\\t\\t\\t} else if ( inputEncoding == 3 ) {\\n\\n\\t\\t\\t\\treturn RGBMToLinear( value, 7.0 );\\n\\n\\t\\t\\t} else if ( inputEncoding == 4 ) {\\n\\n\\t\\t\\t\\treturn RGBMToLinear( value, 16.0 );\\n\\n\\t\\t\\t} else if ( inputEncoding == 5 ) {\\n\\n\\t\\t\\t\\treturn RGBDToLinear( value, 256.0 );\\n\\n\\t\\t\\t} else {\\n\\n\\t\\t\\t\\treturn GammaToLinear( value, 2.2 );\\n\\n\\t\\t\\t}\\n\\n\\t\\t}\\n\\n\\t\\tvec4 linearToOutputTexel( vec4 value ) {\\n\\n\\t\\t\\tif ( outputEncoding == 0 ) {\\n\\n\\t\\t\\t\\treturn value;\\n\\n\\t\\t\\t} else if ( outputEncoding == 1 ) {\\n\\n\\t\\t\\t\\treturn LinearTosRGB( value );\\n\\n\\t\\t\\t} else if ( outputEncoding == 2 ) {\\n\\n\\t\\t\\t\\treturn LinearToRGBE( value );\\n\\n\\t\\t\\t} else if ( outputEncoding == 3 ) {\\n\\n\\t\\t\\t\\treturn LinearToRGBM( value, 7.0 );\\n\\n\\t\\t\\t} else if ( outputEncoding == 4 ) {\\n\\n\\t\\t\\t\\treturn LinearToRGBM( value, 16.0 );\\n\\n\\t\\t\\t} else if ( outputEncoding == 5 ) {\\n\\n\\t\\t\\t\\treturn LinearToRGBD( value, 256.0 );\\n\\n\\t\\t\\t} else {\\n\\n\\t\\t\\t\\treturn LinearToGamma( value, 2.2 );\\n\\n\\t\\t\\t}\\n\\n\\t\\t}\\n\\n\\t\\tvec4 envMapTexelToLinear( vec4 color ) {\\n\\n\\t\\t\\treturn inputTexelToLinear( color );\\n\\n\\t\\t}\\n\\t`;\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLCubeUVMaps.js\\nfunction WebGLCubeUVMaps(renderer) {\\n let cubeUVmaps = new WeakMap();\\n let pmremGenerator = null;\\n function get(texture) {\\n if (texture && texture.isTexture && texture.isRenderTargetTexture === false) {\\n const mapping = texture.mapping;\\n const isEquirectMap = mapping === EquirectangularReflectionMapping || mapping === EquirectangularRefractionMapping;\\n const isCubeMap = mapping === CubeReflectionMapping || mapping === CubeRefractionMapping;\\n if (isEquirectMap || isCubeMap) {\\n if (cubeUVmaps.has(texture)) {\\n return cubeUVmaps.get(texture).texture;\\n } else {\\n const image = texture.image;\\n if (isEquirectMap && image && image.height > 0 || isCubeMap && image && isCubeTextureComplete(image)) {\\n const currentRenderTarget = renderer.getRenderTarget();\\n if (pmremGenerator === null)\\n pmremGenerator = new PMREMGenerator(renderer);\\n const renderTarget = isEquirectMap ? pmremGenerator.fromEquirectangular(texture) : pmremGenerator.fromCubemap(texture);\\n cubeUVmaps.set(texture, renderTarget);\\n renderer.setRenderTarget(currentRenderTarget);\\n texture.addEventListener(\\\\\\\"dispose\\\\\\\", onTextureDispose);\\n return renderTarget.texture;\\n } else {\\n return null;\\n }\\n }\\n }\\n }\\n return texture;\\n }\\n function isCubeTextureComplete(image) {\\n let count = 0;\\n const length = 6;\\n for (let i = 0; i < length; i++) {\\n if (image[i] !== void 0)\\n count++;\\n }\\n return count === length;\\n }\\n function onTextureDispose(event) {\\n const texture = event.target;\\n texture.removeEventListener(\\\\\\\"dispose\\\\\\\", onTextureDispose);\\n const cubemapUV = cubeUVmaps.get(texture);\\n if (cubemapUV !== void 0) {\\n cubeUVmaps.delete(texture);\\n cubemapUV.dispose();\\n }\\n }\\n function dispose() {\\n cubeUVmaps = new WeakMap();\\n if (pmremGenerator !== null) {\\n pmremGenerator.dispose();\\n pmremGenerator = null;\\n }\\n }\\n return {\\n get,\\n dispose\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLExtensions.js\\nfunction WebGLExtensions(gl) {\\n const extensions = {};\\n function getExtension(name) {\\n if (extensions[name] !== void 0) {\\n return extensions[name];\\n }\\n let extension;\\n switch (name) {\\n case \\\\\\\"WEBGL_depth_texture\\\\\\\":\\n extension = gl.getExtension(\\\\\\\"WEBGL_depth_texture\\\\\\\") || gl.getExtension(\\\\\\\"MOZ_WEBGL_depth_texture\\\\\\\") || gl.getExtension(\\\\\\\"WEBKIT_WEBGL_depth_texture\\\\\\\");\\n break;\\n case \\\\\\\"EXT_texture_filter_anisotropic\\\\\\\":\\n extension = gl.getExtension(\\\\\\\"EXT_texture_filter_anisotropic\\\\\\\") || gl.getExtension(\\\\\\\"MOZ_EXT_texture_filter_anisotropic\\\\\\\") || gl.getExtension(\\\\\\\"WEBKIT_EXT_texture_filter_anisotropic\\\\\\\");\\n break;\\n case \\\\\\\"WEBGL_compressed_texture_s3tc\\\\\\\":\\n extension = gl.getExtension(\\\\\\\"WEBGL_compressed_texture_s3tc\\\\\\\") || gl.getExtension(\\\\\\\"MOZ_WEBGL_compressed_texture_s3tc\\\\\\\") || gl.getExtension(\\\\\\\"WEBKIT_WEBGL_compressed_texture_s3tc\\\\\\\");\\n break;\\n case \\\\\\\"WEBGL_compressed_texture_pvrtc\\\\\\\":\\n extension = gl.getExtension(\\\\\\\"WEBGL_compressed_texture_pvrtc\\\\\\\") || gl.getExtension(\\\\\\\"WEBKIT_WEBGL_compressed_texture_pvrtc\\\\\\\");\\n break;\\n default:\\n extension = gl.getExtension(name);\\n }\\n extensions[name] = extension;\\n return extension;\\n }\\n return {\\n has: function(name) {\\n return getExtension(name) !== null;\\n },\\n init: function(capabilities) {\\n if (capabilities.isWebGL2) {\\n getExtension(\\\\\\\"EXT_color_buffer_float\\\\\\\");\\n } else {\\n getExtension(\\\\\\\"WEBGL_depth_texture\\\\\\\");\\n getExtension(\\\\\\\"OES_texture_float\\\\\\\");\\n getExtension(\\\\\\\"OES_texture_half_float\\\\\\\");\\n getExtension(\\\\\\\"OES_texture_half_float_linear\\\\\\\");\\n getExtension(\\\\\\\"OES_standard_derivatives\\\\\\\");\\n getExtension(\\\\\\\"OES_element_index_uint\\\\\\\");\\n getExtension(\\\\\\\"OES_vertex_array_object\\\\\\\");\\n getExtension(\\\\\\\"ANGLE_instanced_arrays\\\\\\\");\\n }\\n getExtension(\\\\\\\"OES_texture_float_linear\\\\\\\");\\n getExtension(\\\\\\\"EXT_color_buffer_half_float\\\\\\\");\\n },\\n get: function(name) {\\n const extension = getExtension(name);\\n if (extension === null) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: \\\\\\\" + name + \\\\\\\" extension not supported.\\\\\\\");\\n }\\n return extension;\\n }\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLGeometries.js\\nfunction WebGLGeometries(gl, attributes, info, bindingStates) {\\n const geometries = {};\\n const wireframeAttributes = new WeakMap();\\n function onGeometryDispose(event) {\\n const geometry = event.target;\\n if (geometry.index !== null) {\\n attributes.remove(geometry.index);\\n }\\n for (const name in geometry.attributes) {\\n attributes.remove(geometry.attributes[name]);\\n }\\n geometry.removeEventListener(\\\\\\\"dispose\\\\\\\", onGeometryDispose);\\n delete geometries[geometry.id];\\n const attribute = wireframeAttributes.get(geometry);\\n if (attribute) {\\n attributes.remove(attribute);\\n wireframeAttributes.delete(geometry);\\n }\\n bindingStates.releaseStatesOfGeometry(geometry);\\n if (geometry.isInstancedBufferGeometry === true) {\\n delete geometry._maxInstanceCount;\\n }\\n info.memory.geometries--;\\n }\\n function get(object, geometry) {\\n if (geometries[geometry.id] === true)\\n return geometry;\\n geometry.addEventListener(\\\\\\\"dispose\\\\\\\", onGeometryDispose);\\n geometries[geometry.id] = true;\\n info.memory.geometries++;\\n return geometry;\\n }\\n function update(geometry) {\\n const geometryAttributes = geometry.attributes;\\n for (const name in geometryAttributes) {\\n attributes.update(geometryAttributes[name], gl.ARRAY_BUFFER);\\n }\\n const morphAttributes = geometry.morphAttributes;\\n for (const name in morphAttributes) {\\n const array = morphAttributes[name];\\n for (let i = 0, l = array.length; i < l; i++) {\\n attributes.update(array[i], gl.ARRAY_BUFFER);\\n }\\n }\\n }\\n function updateWireframeAttribute(geometry) {\\n const indices = [];\\n const geometryIndex = geometry.index;\\n const geometryPosition = geometry.attributes.position;\\n let version = 0;\\n if (geometryIndex !== null) {\\n const array = geometryIndex.array;\\n version = geometryIndex.version;\\n for (let i = 0, l = array.length; i < l; i += 3) {\\n const a = array[i + 0];\\n const b = array[i + 1];\\n const c = array[i + 2];\\n indices.push(a, b, b, c, c, a);\\n }\\n } else {\\n const array = geometryPosition.array;\\n version = geometryPosition.version;\\n for (let i = 0, l = array.length / 3 - 1; i < l; i += 3) {\\n const a = i + 0;\\n const b = i + 1;\\n const c = i + 2;\\n indices.push(a, b, b, c, c, a);\\n }\\n }\\n const attribute = new (arrayMax(indices) > 65535 ? Uint32BufferAttribute : Uint16BufferAttribute)(indices, 1);\\n attribute.version = version;\\n const previousAttribute = wireframeAttributes.get(geometry);\\n if (previousAttribute)\\n attributes.remove(previousAttribute);\\n wireframeAttributes.set(geometry, attribute);\\n }\\n function getWireframeAttribute(geometry) {\\n const currentAttribute = wireframeAttributes.get(geometry);\\n if (currentAttribute) {\\n const geometryIndex = geometry.index;\\n if (geometryIndex !== null) {\\n if (currentAttribute.version < geometryIndex.version) {\\n updateWireframeAttribute(geometry);\\n }\\n }\\n } else {\\n updateWireframeAttribute(geometry);\\n }\\n return wireframeAttributes.get(geometry);\\n }\\n return {\\n get,\\n update,\\n getWireframeAttribute\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLIndexedBufferRenderer.js\\nfunction WebGLIndexedBufferRenderer(gl, extensions, info, capabilities) {\\n const isWebGL2 = capabilities.isWebGL2;\\n let mode;\\n function setMode(value) {\\n mode = value;\\n }\\n let type, bytesPerElement;\\n function setIndex(value) {\\n type = value.type;\\n bytesPerElement = value.bytesPerElement;\\n }\\n function render(start, count) {\\n gl.drawElements(mode, count, type, start * bytesPerElement);\\n info.update(count, mode, 1);\\n }\\n function renderInstances(start, count, primcount) {\\n if (primcount === 0)\\n return;\\n let extension, methodName;\\n if (isWebGL2) {\\n extension = gl;\\n methodName = \\\\\\\"drawElementsInstanced\\\\\\\";\\n } else {\\n extension = extensions.get(\\\\\\\"ANGLE_instanced_arrays\\\\\\\");\\n methodName = \\\\\\\"drawElementsInstancedANGLE\\\\\\\";\\n if (extension === null) {\\n console.error(\\\\\\\"THREE.WebGLIndexedBufferRenderer: using THREE.InstancedBufferGeometry but hardware does not support extension ANGLE_instanced_arrays.\\\\\\\");\\n return;\\n }\\n }\\n extension[methodName](mode, count, type, start * bytesPerElement, primcount);\\n info.update(count, mode, primcount);\\n }\\n this.setMode = setMode;\\n this.setIndex = setIndex;\\n this.render = render;\\n this.renderInstances = renderInstances;\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLInfo.js\\nfunction WebGLInfo(gl) {\\n const memory = {\\n geometries: 0,\\n textures: 0\\n };\\n const render = {\\n frame: 0,\\n calls: 0,\\n triangles: 0,\\n points: 0,\\n lines: 0\\n };\\n function update(count, mode, instanceCount) {\\n render.calls++;\\n switch (mode) {\\n case gl.TRIANGLES:\\n render.triangles += instanceCount * (count / 3);\\n break;\\n case gl.LINES:\\n render.lines += instanceCount * (count / 2);\\n break;\\n case gl.LINE_STRIP:\\n render.lines += instanceCount * (count - 1);\\n break;\\n case gl.LINE_LOOP:\\n render.lines += instanceCount * count;\\n break;\\n case gl.POINTS:\\n render.points += instanceCount * count;\\n break;\\n default:\\n console.error(\\\\\\\"THREE.WebGLInfo: Unknown draw mode:\\\\\\\", mode);\\n break;\\n }\\n }\\n function reset() {\\n render.frame++;\\n render.calls = 0;\\n render.triangles = 0;\\n render.points = 0;\\n render.lines = 0;\\n }\\n return {\\n memory,\\n render,\\n programs: null,\\n autoReset: true,\\n reset,\\n update\\n };\\n}\\n\\n// ../../../node_modules/three/src/textures/DataTexture2DArray.js\\nvar DataTexture2DArray = class extends Texture {\\n constructor(data = null, width = 1, height = 1, depth2 = 1) {\\n super(null);\\n this.image = {data, width, height, depth: depth2};\\n this.magFilter = NearestFilter;\\n this.minFilter = NearestFilter;\\n this.wrapR = ClampToEdgeWrapping;\\n this.generateMipmaps = false;\\n this.flipY = false;\\n this.unpackAlignment = 1;\\n this.needsUpdate = true;\\n }\\n};\\nDataTexture2DArray.prototype.isDataTexture2DArray = true;\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLMorphtargets.js\\nfunction numericalSort(a, b) {\\n return a[0] - b[0];\\n}\\nfunction absNumericalSort(a, b) {\\n return Math.abs(b[1]) - Math.abs(a[1]);\\n}\\nfunction denormalize(morph, attribute) {\\n let denominator = 1;\\n const array = attribute.isInterleavedBufferAttribute ? attribute.data.array : attribute.array;\\n if (array instanceof Int8Array)\\n denominator = 127;\\n else if (array instanceof Int16Array)\\n denominator = 32767;\\n else if (array instanceof Int32Array)\\n denominator = 2147483647;\\n else\\n console.error(\\\\\\\"THREE.WebGLMorphtargets: Unsupported morph attribute data type: \\\\\\\", array);\\n morph.divideScalar(denominator);\\n}\\nfunction WebGLMorphtargets(gl, capabilities, textures) {\\n const influencesList = {};\\n const morphInfluences = new Float32Array(8);\\n const morphTextures = new WeakMap();\\n const morph = new Vector3();\\n const workInfluences = [];\\n for (let i = 0; i < 8; i++) {\\n workInfluences[i] = [i, 0];\\n }\\n function update(object, geometry, material, program) {\\n const objectInfluences = object.morphTargetInfluences;\\n if (capabilities.isWebGL2 === true) {\\n const numberOfMorphTargets = geometry.morphAttributes.position.length;\\n let entry = morphTextures.get(geometry);\\n if (entry === void 0 || entry.count !== numberOfMorphTargets) {\\n if (entry !== void 0)\\n entry.texture.dispose();\\n const hasMorphNormals = geometry.morphAttributes.normal !== void 0;\\n const morphTargets = geometry.morphAttributes.position;\\n const morphNormals = geometry.morphAttributes.normal || [];\\n const numberOfVertices = geometry.attributes.position.count;\\n const numberOfVertexData = hasMorphNormals === true ? 2 : 1;\\n let width = numberOfVertices * numberOfVertexData;\\n let height = 1;\\n if (width > capabilities.maxTextureSize) {\\n height = Math.ceil(width / capabilities.maxTextureSize);\\n width = capabilities.maxTextureSize;\\n }\\n const buffer = new Float32Array(width * height * 4 * numberOfMorphTargets);\\n const texture = new DataTexture2DArray(buffer, width, height, numberOfMorphTargets);\\n texture.format = RGBAFormat;\\n texture.type = FloatType;\\n const vertexDataStride = numberOfVertexData * 4;\\n for (let i = 0; i < numberOfMorphTargets; i++) {\\n const morphTarget = morphTargets[i];\\n const morphNormal = morphNormals[i];\\n const offset = width * height * 4 * i;\\n for (let j = 0; j < morphTarget.count; j++) {\\n morph.fromBufferAttribute(morphTarget, j);\\n if (morphTarget.normalized === true)\\n denormalize(morph, morphTarget);\\n const stride = j * vertexDataStride;\\n buffer[offset + stride + 0] = morph.x;\\n buffer[offset + stride + 1] = morph.y;\\n buffer[offset + stride + 2] = morph.z;\\n buffer[offset + stride + 3] = 0;\\n if (hasMorphNormals === true) {\\n morph.fromBufferAttribute(morphNormal, j);\\n if (morphNormal.normalized === true)\\n denormalize(morph, morphNormal);\\n buffer[offset + stride + 4] = morph.x;\\n buffer[offset + stride + 5] = morph.y;\\n buffer[offset + stride + 6] = morph.z;\\n buffer[offset + stride + 7] = 0;\\n }\\n }\\n }\\n entry = {\\n count: numberOfMorphTargets,\\n texture,\\n size: new Vector2(width, height)\\n };\\n morphTextures.set(geometry, entry);\\n }\\n let morphInfluencesSum = 0;\\n for (let i = 0; i < objectInfluences.length; i++) {\\n morphInfluencesSum += objectInfluences[i];\\n }\\n const morphBaseInfluence = geometry.morphTargetsRelative ? 1 : 1 - morphInfluencesSum;\\n program.getUniforms().setValue(gl, \\\\\\\"morphTargetBaseInfluence\\\\\\\", morphBaseInfluence);\\n program.getUniforms().setValue(gl, \\\\\\\"morphTargetInfluences\\\\\\\", objectInfluences);\\n program.getUniforms().setValue(gl, \\\\\\\"morphTargetsTexture\\\\\\\", entry.texture, textures);\\n program.getUniforms().setValue(gl, \\\\\\\"morphTargetsTextureSize\\\\\\\", entry.size);\\n } else {\\n const length = objectInfluences === void 0 ? 0 : objectInfluences.length;\\n let influences = influencesList[geometry.id];\\n if (influences === void 0 || influences.length !== length) {\\n influences = [];\\n for (let i = 0; i < length; i++) {\\n influences[i] = [i, 0];\\n }\\n influencesList[geometry.id] = influences;\\n }\\n for (let i = 0; i < length; i++) {\\n const influence = influences[i];\\n influence[0] = i;\\n influence[1] = objectInfluences[i];\\n }\\n influences.sort(absNumericalSort);\\n for (let i = 0; i < 8; i++) {\\n if (i < length && influences[i][1]) {\\n workInfluences[i][0] = influences[i][0];\\n workInfluences[i][1] = influences[i][1];\\n } else {\\n workInfluences[i][0] = Number.MAX_SAFE_INTEGER;\\n workInfluences[i][1] = 0;\\n }\\n }\\n workInfluences.sort(numericalSort);\\n const morphTargets = geometry.morphAttributes.position;\\n const morphNormals = geometry.morphAttributes.normal;\\n let morphInfluencesSum = 0;\\n for (let i = 0; i < 8; i++) {\\n const influence = workInfluences[i];\\n const index = influence[0];\\n const value = influence[1];\\n if (index !== Number.MAX_SAFE_INTEGER && value) {\\n if (morphTargets && geometry.getAttribute(\\\\\\\"morphTarget\\\\\\\" + i) !== morphTargets[index]) {\\n geometry.setAttribute(\\\\\\\"morphTarget\\\\\\\" + i, morphTargets[index]);\\n }\\n if (morphNormals && geometry.getAttribute(\\\\\\\"morphNormal\\\\\\\" + i) !== morphNormals[index]) {\\n geometry.setAttribute(\\\\\\\"morphNormal\\\\\\\" + i, morphNormals[index]);\\n }\\n morphInfluences[i] = value;\\n morphInfluencesSum += value;\\n } else {\\n if (morphTargets && geometry.hasAttribute(\\\\\\\"morphTarget\\\\\\\" + i) === true) {\\n geometry.deleteAttribute(\\\\\\\"morphTarget\\\\\\\" + i);\\n }\\n if (morphNormals && geometry.hasAttribute(\\\\\\\"morphNormal\\\\\\\" + i) === true) {\\n geometry.deleteAttribute(\\\\\\\"morphNormal\\\\\\\" + i);\\n }\\n morphInfluences[i] = 0;\\n }\\n }\\n const morphBaseInfluence = geometry.morphTargetsRelative ? 1 : 1 - morphInfluencesSum;\\n program.getUniforms().setValue(gl, \\\\\\\"morphTargetBaseInfluence\\\\\\\", morphBaseInfluence);\\n program.getUniforms().setValue(gl, \\\\\\\"morphTargetInfluences\\\\\\\", morphInfluences);\\n }\\n }\\n return {\\n update\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/WebGLMultisampleRenderTarget.js\\nvar WebGLMultisampleRenderTarget = class extends WebGLRenderTarget {\\n constructor(width, height, options) {\\n super(width, height, options);\\n this.samples = 4;\\n }\\n copy(source) {\\n super.copy.call(this, source);\\n this.samples = source.samples;\\n return this;\\n }\\n};\\nWebGLMultisampleRenderTarget.prototype.isWebGLMultisampleRenderTarget = true;\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLObjects.js\\nfunction WebGLObjects(gl, geometries, attributes, info) {\\n let updateMap = new WeakMap();\\n function update(object) {\\n const frame = info.render.frame;\\n const geometry = object.geometry;\\n const buffergeometry = geometries.get(object, geometry);\\n if (updateMap.get(buffergeometry) !== frame) {\\n geometries.update(buffergeometry);\\n updateMap.set(buffergeometry, frame);\\n }\\n if (object.isInstancedMesh) {\\n if (object.hasEventListener(\\\\\\\"dispose\\\\\\\", onInstancedMeshDispose) === false) {\\n object.addEventListener(\\\\\\\"dispose\\\\\\\", onInstancedMeshDispose);\\n }\\n attributes.update(object.instanceMatrix, gl.ARRAY_BUFFER);\\n if (object.instanceColor !== null) {\\n attributes.update(object.instanceColor, gl.ARRAY_BUFFER);\\n }\\n }\\n return buffergeometry;\\n }\\n function dispose() {\\n updateMap = new WeakMap();\\n }\\n function onInstancedMeshDispose(event) {\\n const instancedMesh = event.target;\\n instancedMesh.removeEventListener(\\\\\\\"dispose\\\\\\\", onInstancedMeshDispose);\\n attributes.remove(instancedMesh.instanceMatrix);\\n if (instancedMesh.instanceColor !== null)\\n attributes.remove(instancedMesh.instanceColor);\\n }\\n return {\\n update,\\n dispose\\n };\\n}\\n\\n// ../../../node_modules/three/src/textures/DataTexture3D.js\\nvar DataTexture3D = class extends Texture {\\n constructor(data = null, width = 1, height = 1, depth2 = 1) {\\n super(null);\\n this.image = {data, width, height, depth: depth2};\\n this.magFilter = NearestFilter;\\n this.minFilter = NearestFilter;\\n this.wrapR = ClampToEdgeWrapping;\\n this.generateMipmaps = false;\\n this.flipY = false;\\n this.unpackAlignment = 1;\\n this.needsUpdate = true;\\n }\\n};\\nDataTexture3D.prototype.isDataTexture3D = true;\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLUniforms.js\\nvar emptyTexture = new Texture();\\nvar emptyTexture2dArray = new DataTexture2DArray();\\nvar emptyTexture3d = new DataTexture3D();\\nvar emptyCubeTexture = new CubeTexture();\\nvar arrayCacheF32 = [];\\nvar arrayCacheI32 = [];\\nvar mat4array = new Float32Array(16);\\nvar mat3array = new Float32Array(9);\\nvar mat2array = new Float32Array(4);\\nfunction flatten(array, nBlocks, blockSize) {\\n const firstElem = array[0];\\n if (firstElem <= 0 || firstElem > 0)\\n return array;\\n const n = nBlocks * blockSize;\\n let r = arrayCacheF32[n];\\n if (r === void 0) {\\n r = new Float32Array(n);\\n arrayCacheF32[n] = r;\\n }\\n if (nBlocks !== 0) {\\n firstElem.toArray(r, 0);\\n for (let i = 1, offset = 0; i !== nBlocks; ++i) {\\n offset += blockSize;\\n array[i].toArray(r, offset);\\n }\\n }\\n return r;\\n}\\nfunction arraysEqual(a, b) {\\n if (a.length !== b.length)\\n return false;\\n for (let i = 0, l = a.length; i < l; i++) {\\n if (a[i] !== b[i])\\n return false;\\n }\\n return true;\\n}\\nfunction copyArray(a, b) {\\n for (let i = 0, l = b.length; i < l; i++) {\\n a[i] = b[i];\\n }\\n}\\nfunction allocTexUnits(textures, n) {\\n let r = arrayCacheI32[n];\\n if (r === void 0) {\\n r = new Int32Array(n);\\n arrayCacheI32[n] = r;\\n }\\n for (let i = 0; i !== n; ++i) {\\n r[i] = textures.allocateTextureUnit();\\n }\\n return r;\\n}\\nfunction setValueV1f(gl, v) {\\n const cache = this.cache;\\n if (cache[0] === v)\\n return;\\n gl.uniform1f(this.addr, v);\\n cache[0] = v;\\n}\\nfunction setValueV2f(gl, v) {\\n const cache = this.cache;\\n if (v.x !== void 0) {\\n if (cache[0] !== v.x || cache[1] !== v.y) {\\n gl.uniform2f(this.addr, v.x, v.y);\\n cache[0] = v.x;\\n cache[1] = v.y;\\n }\\n } else {\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform2fv(this.addr, v);\\n copyArray(cache, v);\\n }\\n}\\nfunction setValueV3f(gl, v) {\\n const cache = this.cache;\\n if (v.x !== void 0) {\\n if (cache[0] !== v.x || cache[1] !== v.y || cache[2] !== v.z) {\\n gl.uniform3f(this.addr, v.x, v.y, v.z);\\n cache[0] = v.x;\\n cache[1] = v.y;\\n cache[2] = v.z;\\n }\\n } else if (v.r !== void 0) {\\n if (cache[0] !== v.r || cache[1] !== v.g || cache[2] !== v.b) {\\n gl.uniform3f(this.addr, v.r, v.g, v.b);\\n cache[0] = v.r;\\n cache[1] = v.g;\\n cache[2] = v.b;\\n }\\n } else {\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform3fv(this.addr, v);\\n copyArray(cache, v);\\n }\\n}\\nfunction setValueV4f(gl, v) {\\n const cache = this.cache;\\n if (v.x !== void 0) {\\n if (cache[0] !== v.x || cache[1] !== v.y || cache[2] !== v.z || cache[3] !== v.w) {\\n gl.uniform4f(this.addr, v.x, v.y, v.z, v.w);\\n cache[0] = v.x;\\n cache[1] = v.y;\\n cache[2] = v.z;\\n cache[3] = v.w;\\n }\\n } else {\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform4fv(this.addr, v);\\n copyArray(cache, v);\\n }\\n}\\nfunction setValueM2(gl, v) {\\n const cache = this.cache;\\n const elements = v.elements;\\n if (elements === void 0) {\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniformMatrix2fv(this.addr, false, v);\\n copyArray(cache, v);\\n } else {\\n if (arraysEqual(cache, elements))\\n return;\\n mat2array.set(elements);\\n gl.uniformMatrix2fv(this.addr, false, mat2array);\\n copyArray(cache, elements);\\n }\\n}\\nfunction setValueM3(gl, v) {\\n const cache = this.cache;\\n const elements = v.elements;\\n if (elements === void 0) {\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniformMatrix3fv(this.addr, false, v);\\n copyArray(cache, v);\\n } else {\\n if (arraysEqual(cache, elements))\\n return;\\n mat3array.set(elements);\\n gl.uniformMatrix3fv(this.addr, false, mat3array);\\n copyArray(cache, elements);\\n }\\n}\\nfunction setValueM4(gl, v) {\\n const cache = this.cache;\\n const elements = v.elements;\\n if (elements === void 0) {\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniformMatrix4fv(this.addr, false, v);\\n copyArray(cache, v);\\n } else {\\n if (arraysEqual(cache, elements))\\n return;\\n mat4array.set(elements);\\n gl.uniformMatrix4fv(this.addr, false, mat4array);\\n copyArray(cache, elements);\\n }\\n}\\nfunction setValueV1i(gl, v) {\\n const cache = this.cache;\\n if (cache[0] === v)\\n return;\\n gl.uniform1i(this.addr, v);\\n cache[0] = v;\\n}\\nfunction setValueV2i(gl, v) {\\n const cache = this.cache;\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform2iv(this.addr, v);\\n copyArray(cache, v);\\n}\\nfunction setValueV3i(gl, v) {\\n const cache = this.cache;\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform3iv(this.addr, v);\\n copyArray(cache, v);\\n}\\nfunction setValueV4i(gl, v) {\\n const cache = this.cache;\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform4iv(this.addr, v);\\n copyArray(cache, v);\\n}\\nfunction setValueV1ui(gl, v) {\\n const cache = this.cache;\\n if (cache[0] === v)\\n return;\\n gl.uniform1ui(this.addr, v);\\n cache[0] = v;\\n}\\nfunction setValueV2ui(gl, v) {\\n const cache = this.cache;\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform2uiv(this.addr, v);\\n copyArray(cache, v);\\n}\\nfunction setValueV3ui(gl, v) {\\n const cache = this.cache;\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform3uiv(this.addr, v);\\n copyArray(cache, v);\\n}\\nfunction setValueV4ui(gl, v) {\\n const cache = this.cache;\\n if (arraysEqual(cache, v))\\n return;\\n gl.uniform4uiv(this.addr, v);\\n copyArray(cache, v);\\n}\\nfunction setValueT1(gl, v, textures) {\\n const cache = this.cache;\\n const unit = textures.allocateTextureUnit();\\n if (cache[0] !== unit) {\\n gl.uniform1i(this.addr, unit);\\n cache[0] = unit;\\n }\\n textures.safeSetTexture2D(v || emptyTexture, unit);\\n}\\nfunction setValueT3D1(gl, v, textures) {\\n const cache = this.cache;\\n const unit = textures.allocateTextureUnit();\\n if (cache[0] !== unit) {\\n gl.uniform1i(this.addr, unit);\\n cache[0] = unit;\\n }\\n textures.setTexture3D(v || emptyTexture3d, unit);\\n}\\nfunction setValueT6(gl, v, textures) {\\n const cache = this.cache;\\n const unit = textures.allocateTextureUnit();\\n if (cache[0] !== unit) {\\n gl.uniform1i(this.addr, unit);\\n cache[0] = unit;\\n }\\n textures.safeSetTextureCube(v || emptyCubeTexture, unit);\\n}\\nfunction setValueT2DArray1(gl, v, textures) {\\n const cache = this.cache;\\n const unit = textures.allocateTextureUnit();\\n if (cache[0] !== unit) {\\n gl.uniform1i(this.addr, unit);\\n cache[0] = unit;\\n }\\n textures.setTexture2DArray(v || emptyTexture2dArray, unit);\\n}\\nfunction getSingularSetter(type) {\\n switch (type) {\\n case 5126:\\n return setValueV1f;\\n case 35664:\\n return setValueV2f;\\n case 35665:\\n return setValueV3f;\\n case 35666:\\n return setValueV4f;\\n case 35674:\\n return setValueM2;\\n case 35675:\\n return setValueM3;\\n case 35676:\\n return setValueM4;\\n case 5124:\\n case 35670:\\n return setValueV1i;\\n case 35667:\\n case 35671:\\n return setValueV2i;\\n case 35668:\\n case 35672:\\n return setValueV3i;\\n case 35669:\\n case 35673:\\n return setValueV4i;\\n case 5125:\\n return setValueV1ui;\\n case 36294:\\n return setValueV2ui;\\n case 36295:\\n return setValueV3ui;\\n case 36296:\\n return setValueV4ui;\\n case 35678:\\n case 36198:\\n case 36298:\\n case 36306:\\n case 35682:\\n return setValueT1;\\n case 35679:\\n case 36299:\\n case 36307:\\n return setValueT3D1;\\n case 35680:\\n case 36300:\\n case 36308:\\n case 36293:\\n return setValueT6;\\n case 36289:\\n case 36303:\\n case 36311:\\n case 36292:\\n return setValueT2DArray1;\\n }\\n}\\nfunction setValueV1fArray(gl, v) {\\n gl.uniform1fv(this.addr, v);\\n}\\nfunction setValueV2fArray(gl, v) {\\n const data = flatten(v, this.size, 2);\\n gl.uniform2fv(this.addr, data);\\n}\\nfunction setValueV3fArray(gl, v) {\\n const data = flatten(v, this.size, 3);\\n gl.uniform3fv(this.addr, data);\\n}\\nfunction setValueV4fArray(gl, v) {\\n const data = flatten(v, this.size, 4);\\n gl.uniform4fv(this.addr, data);\\n}\\nfunction setValueM2Array(gl, v) {\\n const data = flatten(v, this.size, 4);\\n gl.uniformMatrix2fv(this.addr, false, data);\\n}\\nfunction setValueM3Array(gl, v) {\\n const data = flatten(v, this.size, 9);\\n gl.uniformMatrix3fv(this.addr, false, data);\\n}\\nfunction setValueM4Array(gl, v) {\\n const data = flatten(v, this.size, 16);\\n gl.uniformMatrix4fv(this.addr, false, data);\\n}\\nfunction setValueV1iArray(gl, v) {\\n gl.uniform1iv(this.addr, v);\\n}\\nfunction setValueV2iArray(gl, v) {\\n gl.uniform2iv(this.addr, v);\\n}\\nfunction setValueV3iArray(gl, v) {\\n gl.uniform3iv(this.addr, v);\\n}\\nfunction setValueV4iArray(gl, v) {\\n gl.uniform4iv(this.addr, v);\\n}\\nfunction setValueV1uiArray(gl, v) {\\n gl.uniform1uiv(this.addr, v);\\n}\\nfunction setValueV2uiArray(gl, v) {\\n gl.uniform2uiv(this.addr, v);\\n}\\nfunction setValueV3uiArray(gl, v) {\\n gl.uniform3uiv(this.addr, v);\\n}\\nfunction setValueV4uiArray(gl, v) {\\n gl.uniform4uiv(this.addr, v);\\n}\\nfunction setValueT1Array(gl, v, textures) {\\n const n = v.length;\\n const units = allocTexUnits(textures, n);\\n gl.uniform1iv(this.addr, units);\\n for (let i = 0; i !== n; ++i) {\\n textures.safeSetTexture2D(v[i] || emptyTexture, units[i]);\\n }\\n}\\nfunction setValueT6Array(gl, v, textures) {\\n const n = v.length;\\n const units = allocTexUnits(textures, n);\\n gl.uniform1iv(this.addr, units);\\n for (let i = 0; i !== n; ++i) {\\n textures.safeSetTextureCube(v[i] || emptyCubeTexture, units[i]);\\n }\\n}\\nfunction getPureArraySetter(type) {\\n switch (type) {\\n case 5126:\\n return setValueV1fArray;\\n case 35664:\\n return setValueV2fArray;\\n case 35665:\\n return setValueV3fArray;\\n case 35666:\\n return setValueV4fArray;\\n case 35674:\\n return setValueM2Array;\\n case 35675:\\n return setValueM3Array;\\n case 35676:\\n return setValueM4Array;\\n case 5124:\\n case 35670:\\n return setValueV1iArray;\\n case 35667:\\n case 35671:\\n return setValueV2iArray;\\n case 35668:\\n case 35672:\\n return setValueV3iArray;\\n case 35669:\\n case 35673:\\n return setValueV4iArray;\\n case 5125:\\n return setValueV1uiArray;\\n case 36294:\\n return setValueV2uiArray;\\n case 36295:\\n return setValueV3uiArray;\\n case 36296:\\n return setValueV4uiArray;\\n case 35678:\\n case 36198:\\n case 36298:\\n case 36306:\\n case 35682:\\n return setValueT1Array;\\n case 35680:\\n case 36300:\\n case 36308:\\n case 36293:\\n return setValueT6Array;\\n }\\n}\\nfunction SingleUniform(id, activeInfo, addr) {\\n this.id = id;\\n this.addr = addr;\\n this.cache = [];\\n this.setValue = getSingularSetter(activeInfo.type);\\n}\\nfunction PureArrayUniform(id, activeInfo, addr) {\\n this.id = id;\\n this.addr = addr;\\n this.cache = [];\\n this.size = activeInfo.size;\\n this.setValue = getPureArraySetter(activeInfo.type);\\n}\\nPureArrayUniform.prototype.updateCache = function(data) {\\n const cache = this.cache;\\n if (data instanceof Float32Array && cache.length !== data.length) {\\n this.cache = new Float32Array(data.length);\\n }\\n copyArray(cache, data);\\n};\\nfunction StructuredUniform(id) {\\n this.id = id;\\n this.seq = [];\\n this.map = {};\\n}\\nStructuredUniform.prototype.setValue = function(gl, value, textures) {\\n const seq = this.seq;\\n for (let i = 0, n = seq.length; i !== n; ++i) {\\n const u = seq[i];\\n u.setValue(gl, value[u.id], textures);\\n }\\n};\\nvar RePathPart = /(\\\\w+)(\\\\])?(\\\\[|\\\\.)?/g;\\nfunction addUniform(container, uniformObject) {\\n container.seq.push(uniformObject);\\n container.map[uniformObject.id] = uniformObject;\\n}\\nfunction parseUniform(activeInfo, addr, container) {\\n const path = activeInfo.name, pathLength = path.length;\\n RePathPart.lastIndex = 0;\\n while (true) {\\n const match = RePathPart.exec(path), matchEnd = RePathPart.lastIndex;\\n let id = match[1];\\n const idIsIndex = match[2] === \\\\\\\"]\\\\\\\", subscript = match[3];\\n if (idIsIndex)\\n id = id | 0;\\n if (subscript === void 0 || subscript === \\\\\\\"[\\\\\\\" && matchEnd + 2 === pathLength) {\\n addUniform(container, subscript === void 0 ? new SingleUniform(id, activeInfo, addr) : new PureArrayUniform(id, activeInfo, addr));\\n break;\\n } else {\\n const map = container.map;\\n let next = map[id];\\n if (next === void 0) {\\n next = new StructuredUniform(id);\\n addUniform(container, next);\\n }\\n container = next;\\n }\\n }\\n}\\nfunction WebGLUniforms(gl, program) {\\n this.seq = [];\\n this.map = {};\\n const n = gl.getProgramParameter(program, gl.ACTIVE_UNIFORMS);\\n for (let i = 0; i < n; ++i) {\\n const info = gl.getActiveUniform(program, i), addr = gl.getUniformLocation(program, info.name);\\n parseUniform(info, addr, this);\\n }\\n}\\nWebGLUniforms.prototype.setValue = function(gl, name, value, textures) {\\n const u = this.map[name];\\n if (u !== void 0)\\n u.setValue(gl, value, textures);\\n};\\nWebGLUniforms.prototype.setOptional = function(gl, object, name) {\\n const v = object[name];\\n if (v !== void 0)\\n this.setValue(gl, name, v);\\n};\\nWebGLUniforms.upload = function(gl, seq, values, textures) {\\n for (let i = 0, n = seq.length; i !== n; ++i) {\\n const u = seq[i], v = values[u.id];\\n if (v.needsUpdate !== false) {\\n u.setValue(gl, v.value, textures);\\n }\\n }\\n};\\nWebGLUniforms.seqWithValue = function(seq, values) {\\n const r = [];\\n for (let i = 0, n = seq.length; i !== n; ++i) {\\n const u = seq[i];\\n if (u.id in values)\\n r.push(u);\\n }\\n return r;\\n};\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLShader.js\\nfunction WebGLShader(gl, type, string) {\\n const shader = gl.createShader(type);\\n gl.shaderSource(shader, string);\\n gl.compileShader(shader);\\n return shader;\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLProgram.js\\nvar programIdCount = 0;\\nfunction addLineNumbers(string) {\\n const lines = string.split(\\\\\\\"\\\\n\\\\\\\");\\n for (let i = 0; i < lines.length; i++) {\\n lines[i] = i + 1 + \\\\\\\": \\\\\\\" + lines[i];\\n }\\n return lines.join(\\\\\\\"\\\\n\\\\\\\");\\n}\\nfunction getEncodingComponents(encoding) {\\n switch (encoding) {\\n case LinearEncoding:\\n return [\\\\\\\"Linear\\\\\\\", \\\\\\\"( value )\\\\\\\"];\\n case sRGBEncoding:\\n return [\\\\\\\"sRGB\\\\\\\", \\\\\\\"( value )\\\\\\\"];\\n case RGBEEncoding:\\n return [\\\\\\\"RGBE\\\\\\\", \\\\\\\"( value )\\\\\\\"];\\n case RGBM7Encoding:\\n return [\\\\\\\"RGBM\\\\\\\", \\\\\\\"( value, 7.0 )\\\\\\\"];\\n case RGBM16Encoding:\\n return [\\\\\\\"RGBM\\\\\\\", \\\\\\\"( value, 16.0 )\\\\\\\"];\\n case RGBDEncoding:\\n return [\\\\\\\"RGBD\\\\\\\", \\\\\\\"( value, 256.0 )\\\\\\\"];\\n case GammaEncoding:\\n return [\\\\\\\"Gamma\\\\\\\", \\\\\\\"( value, float( GAMMA_FACTOR ) )\\\\\\\"];\\n case LogLuvEncoding:\\n return [\\\\\\\"LogLuv\\\\\\\", \\\\\\\"( value )\\\\\\\"];\\n default:\\n console.warn(\\\\\\\"THREE.WebGLProgram: Unsupported encoding:\\\\\\\", encoding);\\n return [\\\\\\\"Linear\\\\\\\", \\\\\\\"( value )\\\\\\\"];\\n }\\n}\\nfunction getShaderErrors(gl, shader, type) {\\n const status = gl.getShaderParameter(shader, gl.COMPILE_STATUS);\\n const errors = gl.getShaderInfoLog(shader).trim();\\n if (status && errors === \\\\\\\"\\\\\\\")\\n return \\\\\\\"\\\\\\\";\\n return type.toUpperCase() + \\\\\\\"\\\\n\\\\n\\\\\\\" + errors + \\\\\\\"\\\\n\\\\n\\\\\\\" + addLineNumbers(gl.getShaderSource(shader));\\n}\\nfunction getTexelDecodingFunction(functionName, encoding) {\\n const components = getEncodingComponents(encoding);\\n return \\\\\\\"vec4 \\\\\\\" + functionName + \\\\\\\"( vec4 value ) { return \\\\\\\" + components[0] + \\\\\\\"ToLinear\\\\\\\" + components[1] + \\\\\\\"; }\\\\\\\";\\n}\\nfunction getTexelEncodingFunction(functionName, encoding) {\\n const components = getEncodingComponents(encoding);\\n return \\\\\\\"vec4 \\\\\\\" + functionName + \\\\\\\"( vec4 value ) { return LinearTo\\\\\\\" + components[0] + components[1] + \\\\\\\"; }\\\\\\\";\\n}\\nfunction getToneMappingFunction(functionName, toneMapping) {\\n let toneMappingName;\\n switch (toneMapping) {\\n case LinearToneMapping:\\n toneMappingName = \\\\\\\"Linear\\\\\\\";\\n break;\\n case ReinhardToneMapping:\\n toneMappingName = \\\\\\\"Reinhard\\\\\\\";\\n break;\\n case CineonToneMapping:\\n toneMappingName = \\\\\\\"OptimizedCineon\\\\\\\";\\n break;\\n case ACESFilmicToneMapping:\\n toneMappingName = \\\\\\\"ACESFilmic\\\\\\\";\\n break;\\n case CustomToneMapping:\\n toneMappingName = \\\\\\\"Custom\\\\\\\";\\n break;\\n default:\\n console.warn(\\\\\\\"THREE.WebGLProgram: Unsupported toneMapping:\\\\\\\", toneMapping);\\n toneMappingName = \\\\\\\"Linear\\\\\\\";\\n }\\n return \\\\\\\"vec3 \\\\\\\" + functionName + \\\\\\\"( vec3 color ) { return \\\\\\\" + toneMappingName + \\\\\\\"ToneMapping( color ); }\\\\\\\";\\n}\\nfunction generateExtensions(parameters) {\\n const chunks = [\\n parameters.extensionDerivatives || parameters.envMapCubeUV || parameters.bumpMap || parameters.tangentSpaceNormalMap || parameters.clearcoatNormalMap || parameters.flatShading || parameters.shaderID === \\\\\\\"physical\\\\\\\" ? \\\\\\\"#extension GL_OES_standard_derivatives : enable\\\\\\\" : \\\\\\\"\\\\\\\",\\n (parameters.extensionFragDepth || parameters.logarithmicDepthBuffer) && parameters.rendererExtensionFragDepth ? \\\\\\\"#extension GL_EXT_frag_depth : enable\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.extensionDrawBuffers && parameters.rendererExtensionDrawBuffers ? \\\\\\\"#extension GL_EXT_draw_buffers : require\\\\\\\" : \\\\\\\"\\\\\\\",\\n (parameters.extensionShaderTextureLOD || parameters.envMap || parameters.transmission) && parameters.rendererExtensionShaderTextureLod ? \\\\\\\"#extension GL_EXT_shader_texture_lod : enable\\\\\\\" : \\\\\\\"\\\\\\\"\\n ];\\n return chunks.filter(filterEmptyLine).join(\\\\\\\"\\\\n\\\\\\\");\\n}\\nfunction generateDefines(defines) {\\n const chunks = [];\\n for (const name in defines) {\\n const value = defines[name];\\n if (value === false)\\n continue;\\n chunks.push(\\\\\\\"#define \\\\\\\" + name + \\\\\\\" \\\\\\\" + value);\\n }\\n return chunks.join(\\\\\\\"\\\\n\\\\\\\");\\n}\\nfunction fetchAttributeLocations(gl, program) {\\n const attributes = {};\\n const n = gl.getProgramParameter(program, gl.ACTIVE_ATTRIBUTES);\\n for (let i = 0; i < n; i++) {\\n const info = gl.getActiveAttrib(program, i);\\n const name = info.name;\\n let locationSize = 1;\\n if (info.type === gl.FLOAT_MAT2)\\n locationSize = 2;\\n if (info.type === gl.FLOAT_MAT3)\\n locationSize = 3;\\n if (info.type === gl.FLOAT_MAT4)\\n locationSize = 4;\\n attributes[name] = {\\n type: info.type,\\n location: gl.getAttribLocation(program, name),\\n locationSize\\n };\\n }\\n return attributes;\\n}\\nfunction filterEmptyLine(string) {\\n return string !== \\\\\\\"\\\\\\\";\\n}\\nfunction replaceLightNums(string, parameters) {\\n return string.replace(/NUM_DIR_LIGHTS/g, parameters.numDirLights).replace(/NUM_SPOT_LIGHTS/g, parameters.numSpotLights).replace(/NUM_RECT_AREA_LIGHTS/g, parameters.numRectAreaLights).replace(/NUM_POINT_LIGHTS/g, parameters.numPointLights).replace(/NUM_HEMI_LIGHTS/g, parameters.numHemiLights).replace(/NUM_DIR_LIGHT_SHADOWS/g, parameters.numDirLightShadows).replace(/NUM_SPOT_LIGHT_SHADOWS/g, parameters.numSpotLightShadows).replace(/NUM_POINT_LIGHT_SHADOWS/g, parameters.numPointLightShadows);\\n}\\nfunction replaceClippingPlaneNums(string, parameters) {\\n return string.replace(/NUM_CLIPPING_PLANES/g, parameters.numClippingPlanes).replace(/UNION_CLIPPING_PLANES/g, parameters.numClippingPlanes - parameters.numClipIntersection);\\n}\\nvar includePattern = /^[ \\\\t]*#include +<([\\\\w\\\\d./]+)>/gm;\\nfunction resolveIncludes(string) {\\n return string.replace(includePattern, includeReplacer);\\n}\\nfunction includeReplacer(match, include) {\\n const string = ShaderChunk[include];\\n if (string === void 0) {\\n throw new Error(\\\\\\\"Can not resolve #include <\\\\\\\" + include + \\\\\\\">\\\\\\\");\\n }\\n return resolveIncludes(string);\\n}\\nvar deprecatedUnrollLoopPattern = /#pragma unroll_loop[\\\\s]+?for \\\\( int i \\\\= (\\\\d+)\\\\; i < (\\\\d+)\\\\; i \\\\+\\\\+ \\\\) \\\\{([\\\\s\\\\S]+?)(?=\\\\})\\\\}/g;\\nvar unrollLoopPattern = /#pragma unroll_loop_start\\\\s+for\\\\s*\\\\(\\\\s*int\\\\s+i\\\\s*=\\\\s*(\\\\d+)\\\\s*;\\\\s*i\\\\s*<\\\\s*(\\\\d+)\\\\s*;\\\\s*i\\\\s*\\\\+\\\\+\\\\s*\\\\)\\\\s*{([\\\\s\\\\S]+?)}\\\\s+#pragma unroll_loop_end/g;\\nfunction unrollLoops(string) {\\n return string.replace(unrollLoopPattern, loopReplacer).replace(deprecatedUnrollLoopPattern, deprecatedLoopReplacer);\\n}\\nfunction deprecatedLoopReplacer(match, start, end, snippet) {\\n console.warn(\\\\\\\"WebGLProgram: #pragma unroll_loop shader syntax is deprecated. Please use #pragma unroll_loop_start syntax instead.\\\\\\\");\\n return loopReplacer(match, start, end, snippet);\\n}\\nfunction loopReplacer(match, start, end, snippet) {\\n let string = \\\\\\\"\\\\\\\";\\n for (let i = parseInt(start); i < parseInt(end); i++) {\\n string += snippet.replace(/\\\\[\\\\s*i\\\\s*\\\\]/g, \\\\\\\"[ \\\\\\\" + i + \\\\\\\" ]\\\\\\\").replace(/UNROLLED_LOOP_INDEX/g, i);\\n }\\n return string;\\n}\\nfunction generatePrecision(parameters) {\\n let precisionstring = \\\\\\\"precision \\\\\\\" + parameters.precision + \\\\\\\" float;\\\\nprecision \\\\\\\" + parameters.precision + \\\\\\\" int;\\\\\\\";\\n if (parameters.precision === \\\\\\\"highp\\\\\\\") {\\n precisionstring += \\\\\\\"\\\\n#define HIGH_PRECISION\\\\\\\";\\n } else if (parameters.precision === \\\\\\\"mediump\\\\\\\") {\\n precisionstring += \\\\\\\"\\\\n#define MEDIUM_PRECISION\\\\\\\";\\n } else if (parameters.precision === \\\\\\\"lowp\\\\\\\") {\\n precisionstring += \\\\\\\"\\\\n#define LOW_PRECISION\\\\\\\";\\n }\\n return precisionstring;\\n}\\nfunction generateShadowMapTypeDefine(parameters) {\\n let shadowMapTypeDefine = \\\\\\\"SHADOWMAP_TYPE_BASIC\\\\\\\";\\n if (parameters.shadowMapType === PCFShadowMap) {\\n shadowMapTypeDefine = \\\\\\\"SHADOWMAP_TYPE_PCF\\\\\\\";\\n } else if (parameters.shadowMapType === PCFSoftShadowMap) {\\n shadowMapTypeDefine = \\\\\\\"SHADOWMAP_TYPE_PCF_SOFT\\\\\\\";\\n } else if (parameters.shadowMapType === VSMShadowMap) {\\n shadowMapTypeDefine = \\\\\\\"SHADOWMAP_TYPE_VSM\\\\\\\";\\n }\\n return shadowMapTypeDefine;\\n}\\nfunction generateEnvMapTypeDefine(parameters) {\\n let envMapTypeDefine = \\\\\\\"ENVMAP_TYPE_CUBE\\\\\\\";\\n if (parameters.envMap) {\\n switch (parameters.envMapMode) {\\n case CubeReflectionMapping:\\n case CubeRefractionMapping:\\n envMapTypeDefine = \\\\\\\"ENVMAP_TYPE_CUBE\\\\\\\";\\n break;\\n case CubeUVReflectionMapping:\\n case CubeUVRefractionMapping:\\n envMapTypeDefine = \\\\\\\"ENVMAP_TYPE_CUBE_UV\\\\\\\";\\n break;\\n }\\n }\\n return envMapTypeDefine;\\n}\\nfunction generateEnvMapModeDefine(parameters) {\\n let envMapModeDefine = \\\\\\\"ENVMAP_MODE_REFLECTION\\\\\\\";\\n if (parameters.envMap) {\\n switch (parameters.envMapMode) {\\n case CubeRefractionMapping:\\n case CubeUVRefractionMapping:\\n envMapModeDefine = \\\\\\\"ENVMAP_MODE_REFRACTION\\\\\\\";\\n break;\\n }\\n }\\n return envMapModeDefine;\\n}\\nfunction generateEnvMapBlendingDefine(parameters) {\\n let envMapBlendingDefine = \\\\\\\"ENVMAP_BLENDING_NONE\\\\\\\";\\n if (parameters.envMap) {\\n switch (parameters.combine) {\\n case MultiplyOperation:\\n envMapBlendingDefine = \\\\\\\"ENVMAP_BLENDING_MULTIPLY\\\\\\\";\\n break;\\n case MixOperation:\\n envMapBlendingDefine = \\\\\\\"ENVMAP_BLENDING_MIX\\\\\\\";\\n break;\\n case AddOperation:\\n envMapBlendingDefine = \\\\\\\"ENVMAP_BLENDING_ADD\\\\\\\";\\n break;\\n }\\n }\\n return envMapBlendingDefine;\\n}\\nfunction WebGLProgram(renderer, cacheKey, parameters, bindingStates) {\\n const gl = renderer.getContext();\\n const defines = parameters.defines;\\n let vertexShader = parameters.vertexShader;\\n let fragmentShader = parameters.fragmentShader;\\n const shadowMapTypeDefine = generateShadowMapTypeDefine(parameters);\\n const envMapTypeDefine = generateEnvMapTypeDefine(parameters);\\n const envMapModeDefine = generateEnvMapModeDefine(parameters);\\n const envMapBlendingDefine = generateEnvMapBlendingDefine(parameters);\\n const gammaFactorDefine = renderer.gammaFactor > 0 ? renderer.gammaFactor : 1;\\n const customExtensions = parameters.isWebGL2 ? \\\\\\\"\\\\\\\" : generateExtensions(parameters);\\n const customDefines = generateDefines(defines);\\n const program = gl.createProgram();\\n let prefixVertex, prefixFragment;\\n let versionString = parameters.glslVersion ? \\\\\\\"#version \\\\\\\" + parameters.glslVersion + \\\\\\\"\\\\n\\\\\\\" : \\\\\\\"\\\\\\\";\\n if (parameters.isRawShaderMaterial) {\\n prefixVertex = [\\n customDefines\\n ].filter(filterEmptyLine).join(\\\\\\\"\\\\n\\\\\\\");\\n if (prefixVertex.length > 0) {\\n prefixVertex += \\\\\\\"\\\\n\\\\\\\";\\n }\\n prefixFragment = [\\n customExtensions,\\n customDefines\\n ].filter(filterEmptyLine).join(\\\\\\\"\\\\n\\\\\\\");\\n if (prefixFragment.length > 0) {\\n prefixFragment += \\\\\\\"\\\\n\\\\\\\";\\n }\\n } else {\\n prefixVertex = [\\n generatePrecision(parameters),\\n \\\\\\\"#define SHADER_NAME \\\\\\\" + parameters.shaderName,\\n customDefines,\\n parameters.instancing ? \\\\\\\"#define USE_INSTANCING\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.instancingColor ? \\\\\\\"#define USE_INSTANCING_COLOR\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.supportsVertexTextures ? \\\\\\\"#define VERTEX_TEXTURES\\\\\\\" : \\\\\\\"\\\\\\\",\\n \\\\\\\"#define GAMMA_FACTOR \\\\\\\" + gammaFactorDefine,\\n \\\\\\\"#define MAX_BONES \\\\\\\" + parameters.maxBones,\\n parameters.useFog && parameters.fog ? \\\\\\\"#define USE_FOG\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.useFog && parameters.fogExp2 ? \\\\\\\"#define FOG_EXP2\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.map ? \\\\\\\"#define USE_MAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.envMap ? \\\\\\\"#define USE_ENVMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.envMap ? \\\\\\\"#define \\\\\\\" + envMapModeDefine : \\\\\\\"\\\\\\\",\\n parameters.lightMap ? \\\\\\\"#define USE_LIGHTMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.aoMap ? \\\\\\\"#define USE_AOMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.emissiveMap ? \\\\\\\"#define USE_EMISSIVEMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.bumpMap ? \\\\\\\"#define USE_BUMPMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.normalMap ? \\\\\\\"#define USE_NORMALMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.normalMap && parameters.objectSpaceNormalMap ? \\\\\\\"#define OBJECTSPACE_NORMALMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.normalMap && parameters.tangentSpaceNormalMap ? \\\\\\\"#define TANGENTSPACE_NORMALMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.clearcoatMap ? \\\\\\\"#define USE_CLEARCOATMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.clearcoatRoughnessMap ? \\\\\\\"#define USE_CLEARCOAT_ROUGHNESSMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.clearcoatNormalMap ? \\\\\\\"#define USE_CLEARCOAT_NORMALMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.displacementMap && parameters.supportsVertexTextures ? \\\\\\\"#define USE_DISPLACEMENTMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.specularMap ? \\\\\\\"#define USE_SPECULARMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.specularIntensityMap ? \\\\\\\"#define USE_SPECULARINTENSITYMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.specularTintMap ? \\\\\\\"#define USE_SPECULARTINTMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.roughnessMap ? \\\\\\\"#define USE_ROUGHNESSMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.metalnessMap ? \\\\\\\"#define USE_METALNESSMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.alphaMap ? \\\\\\\"#define USE_ALPHAMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.transmission ? \\\\\\\"#define USE_TRANSMISSION\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.transmissionMap ? \\\\\\\"#define USE_TRANSMISSIONMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.thicknessMap ? \\\\\\\"#define USE_THICKNESSMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.vertexTangents ? \\\\\\\"#define USE_TANGENT\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.vertexColors ? \\\\\\\"#define USE_COLOR\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.vertexAlphas ? \\\\\\\"#define USE_COLOR_ALPHA\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.vertexUvs ? \\\\\\\"#define USE_UV\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.uvsVertexOnly ? \\\\\\\"#define UVS_VERTEX_ONLY\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.flatShading ? \\\\\\\"#define FLAT_SHADED\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.skinning ? \\\\\\\"#define USE_SKINNING\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.useVertexTexture ? \\\\\\\"#define BONE_TEXTURE\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.morphTargets ? \\\\\\\"#define USE_MORPHTARGETS\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.morphNormals && parameters.flatShading === false ? \\\\\\\"#define USE_MORPHNORMALS\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.morphTargets && parameters.isWebGL2 ? \\\\\\\"#define MORPHTARGETS_TEXTURE\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.morphTargets && parameters.isWebGL2 ? \\\\\\\"#define MORPHTARGETS_COUNT \\\\\\\" + parameters.morphTargetsCount : \\\\\\\"\\\\\\\",\\n parameters.doubleSided ? \\\\\\\"#define DOUBLE_SIDED\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.flipSided ? \\\\\\\"#define FLIP_SIDED\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.shadowMapEnabled ? \\\\\\\"#define USE_SHADOWMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.shadowMapEnabled ? \\\\\\\"#define \\\\\\\" + shadowMapTypeDefine : \\\\\\\"\\\\\\\",\\n parameters.sizeAttenuation ? \\\\\\\"#define USE_SIZEATTENUATION\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.logarithmicDepthBuffer ? \\\\\\\"#define USE_LOGDEPTHBUF\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.logarithmicDepthBuffer && parameters.rendererExtensionFragDepth ? \\\\\\\"#define USE_LOGDEPTHBUF_EXT\\\\\\\" : \\\\\\\"\\\\\\\",\\n \\\\\\\"uniform mat4 modelMatrix;\\\\\\\",\\n \\\\\\\"uniform mat4 modelViewMatrix;\\\\\\\",\\n \\\\\\\"uniform mat4 projectionMatrix;\\\\\\\",\\n \\\\\\\"uniform mat4 viewMatrix;\\\\\\\",\\n \\\\\\\"uniform mat3 normalMatrix;\\\\\\\",\\n \\\\\\\"uniform vec3 cameraPosition;\\\\\\\",\\n \\\\\\\"uniform bool isOrthographic;\\\\\\\",\\n \\\\\\\"#ifdef USE_INSTANCING\\\\\\\",\\n \\\\\\\"\\tattribute mat4 instanceMatrix;\\\\\\\",\\n \\\\\\\"#endif\\\\\\\",\\n \\\\\\\"#ifdef USE_INSTANCING_COLOR\\\\\\\",\\n \\\\\\\"\\tattribute vec3 instanceColor;\\\\\\\",\\n \\\\\\\"#endif\\\\\\\",\\n \\\\\\\"attribute vec3 position;\\\\\\\",\\n \\\\\\\"attribute vec3 normal;\\\\\\\",\\n \\\\\\\"attribute vec2 uv;\\\\\\\",\\n \\\\\\\"#ifdef USE_TANGENT\\\\\\\",\\n \\\\\\\"\\tattribute vec4 tangent;\\\\\\\",\\n \\\\\\\"#endif\\\\\\\",\\n \\\\\\\"#if defined( USE_COLOR_ALPHA )\\\\\\\",\\n \\\\\\\"\\tattribute vec4 color;\\\\\\\",\\n \\\\\\\"#elif defined( USE_COLOR )\\\\\\\",\\n \\\\\\\"\\tattribute vec3 color;\\\\\\\",\\n \\\\\\\"#endif\\\\\\\",\\n \\\\\\\"#if ( defined( USE_MORPHTARGETS ) && ! defined( MORPHTARGETS_TEXTURE ) )\\\\\\\",\\n \\\\\\\"\\tattribute vec3 morphTarget0;\\\\\\\",\\n \\\\\\\"\\tattribute vec3 morphTarget1;\\\\\\\",\\n \\\\\\\"\\tattribute vec3 morphTarget2;\\\\\\\",\\n \\\\\\\"\\tattribute vec3 morphTarget3;\\\\\\\",\\n \\\\\\\"\\t#ifdef USE_MORPHNORMALS\\\\\\\",\\n \\\\\\\"\\t\\tattribute vec3 morphNormal0;\\\\\\\",\\n \\\\\\\"\\t\\tattribute vec3 morphNormal1;\\\\\\\",\\n \\\\\\\"\\t\\tattribute vec3 morphNormal2;\\\\\\\",\\n \\\\\\\"\\t\\tattribute vec3 morphNormal3;\\\\\\\",\\n \\\\\\\"\\t#else\\\\\\\",\\n \\\\\\\"\\t\\tattribute vec3 morphTarget4;\\\\\\\",\\n \\\\\\\"\\t\\tattribute vec3 morphTarget5;\\\\\\\",\\n \\\\\\\"\\t\\tattribute vec3 morphTarget6;\\\\\\\",\\n \\\\\\\"\\t\\tattribute vec3 morphTarget7;\\\\\\\",\\n \\\\\\\"\\t#endif\\\\\\\",\\n \\\\\\\"#endif\\\\\\\",\\n \\\\\\\"#ifdef USE_SKINNING\\\\\\\",\\n \\\\\\\"\\tattribute vec4 skinIndex;\\\\\\\",\\n \\\\\\\"\\tattribute vec4 skinWeight;\\\\\\\",\\n \\\\\\\"#endif\\\\\\\",\\n \\\\\\\"\\\\n\\\\\\\"\\n ].filter(filterEmptyLine).join(\\\\\\\"\\\\n\\\\\\\");\\n prefixFragment = [\\n customExtensions,\\n generatePrecision(parameters),\\n \\\\\\\"#define SHADER_NAME \\\\\\\" + parameters.shaderName,\\n customDefines,\\n \\\\\\\"#define GAMMA_FACTOR \\\\\\\" + gammaFactorDefine,\\n parameters.useFog && parameters.fog ? \\\\\\\"#define USE_FOG\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.useFog && parameters.fogExp2 ? \\\\\\\"#define FOG_EXP2\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.map ? \\\\\\\"#define USE_MAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.matcap ? \\\\\\\"#define USE_MATCAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.envMap ? \\\\\\\"#define USE_ENVMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.envMap ? \\\\\\\"#define \\\\\\\" + envMapTypeDefine : \\\\\\\"\\\\\\\",\\n parameters.envMap ? \\\\\\\"#define \\\\\\\" + envMapModeDefine : \\\\\\\"\\\\\\\",\\n parameters.envMap ? \\\\\\\"#define \\\\\\\" + envMapBlendingDefine : \\\\\\\"\\\\\\\",\\n parameters.lightMap ? \\\\\\\"#define USE_LIGHTMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.aoMap ? \\\\\\\"#define USE_AOMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.emissiveMap ? \\\\\\\"#define USE_EMISSIVEMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.bumpMap ? \\\\\\\"#define USE_BUMPMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.normalMap ? \\\\\\\"#define USE_NORMALMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.normalMap && parameters.objectSpaceNormalMap ? \\\\\\\"#define OBJECTSPACE_NORMALMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.normalMap && parameters.tangentSpaceNormalMap ? \\\\\\\"#define TANGENTSPACE_NORMALMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.clearcoat ? \\\\\\\"#define USE_CLEARCOAT\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.clearcoatMap ? \\\\\\\"#define USE_CLEARCOATMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.clearcoatRoughnessMap ? \\\\\\\"#define USE_CLEARCOAT_ROUGHNESSMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.clearcoatNormalMap ? \\\\\\\"#define USE_CLEARCOAT_NORMALMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.specularMap ? \\\\\\\"#define USE_SPECULARMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.specularIntensityMap ? \\\\\\\"#define USE_SPECULARINTENSITYMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.specularTintMap ? \\\\\\\"#define USE_SPECULARTINTMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.roughnessMap ? \\\\\\\"#define USE_ROUGHNESSMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.metalnessMap ? \\\\\\\"#define USE_METALNESSMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.alphaMap ? \\\\\\\"#define USE_ALPHAMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.alphaTest ? \\\\\\\"#define USE_ALPHATEST\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.sheen ? \\\\\\\"#define USE_SHEEN\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.transmission ? \\\\\\\"#define USE_TRANSMISSION\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.transmissionMap ? \\\\\\\"#define USE_TRANSMISSIONMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.thicknessMap ? \\\\\\\"#define USE_THICKNESSMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.vertexTangents ? \\\\\\\"#define USE_TANGENT\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.vertexColors || parameters.instancingColor ? \\\\\\\"#define USE_COLOR\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.vertexAlphas ? \\\\\\\"#define USE_COLOR_ALPHA\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.vertexUvs ? \\\\\\\"#define USE_UV\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.uvsVertexOnly ? \\\\\\\"#define UVS_VERTEX_ONLY\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.gradientMap ? \\\\\\\"#define USE_GRADIENTMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.flatShading ? \\\\\\\"#define FLAT_SHADED\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.doubleSided ? \\\\\\\"#define DOUBLE_SIDED\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.flipSided ? \\\\\\\"#define FLIP_SIDED\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.shadowMapEnabled ? \\\\\\\"#define USE_SHADOWMAP\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.shadowMapEnabled ? \\\\\\\"#define \\\\\\\" + shadowMapTypeDefine : \\\\\\\"\\\\\\\",\\n parameters.premultipliedAlpha ? \\\\\\\"#define PREMULTIPLIED_ALPHA\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.physicallyCorrectLights ? \\\\\\\"#define PHYSICALLY_CORRECT_LIGHTS\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.logarithmicDepthBuffer ? \\\\\\\"#define USE_LOGDEPTHBUF\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.logarithmicDepthBuffer && parameters.rendererExtensionFragDepth ? \\\\\\\"#define USE_LOGDEPTHBUF_EXT\\\\\\\" : \\\\\\\"\\\\\\\",\\n (parameters.extensionShaderTextureLOD || parameters.envMap) && parameters.rendererExtensionShaderTextureLod ? \\\\\\\"#define TEXTURE_LOD_EXT\\\\\\\" : \\\\\\\"\\\\\\\",\\n \\\\\\\"uniform mat4 viewMatrix;\\\\\\\",\\n \\\\\\\"uniform vec3 cameraPosition;\\\\\\\",\\n \\\\\\\"uniform bool isOrthographic;\\\\\\\",\\n parameters.toneMapping !== NoToneMapping ? \\\\\\\"#define TONE_MAPPING\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.toneMapping !== NoToneMapping ? ShaderChunk[\\\\\\\"tonemapping_pars_fragment\\\\\\\"] : \\\\\\\"\\\\\\\",\\n parameters.toneMapping !== NoToneMapping ? getToneMappingFunction(\\\\\\\"toneMapping\\\\\\\", parameters.toneMapping) : \\\\\\\"\\\\\\\",\\n parameters.dithering ? \\\\\\\"#define DITHERING\\\\\\\" : \\\\\\\"\\\\\\\",\\n parameters.format === RGBFormat ? \\\\\\\"#define OPAQUE\\\\\\\" : \\\\\\\"\\\\\\\",\\n ShaderChunk[\\\\\\\"encodings_pars_fragment\\\\\\\"],\\n parameters.map ? getTexelDecodingFunction(\\\\\\\"mapTexelToLinear\\\\\\\", parameters.mapEncoding) : \\\\\\\"\\\\\\\",\\n parameters.matcap ? getTexelDecodingFunction(\\\\\\\"matcapTexelToLinear\\\\\\\", parameters.matcapEncoding) : \\\\\\\"\\\\\\\",\\n parameters.envMap ? getTexelDecodingFunction(\\\\\\\"envMapTexelToLinear\\\\\\\", parameters.envMapEncoding) : \\\\\\\"\\\\\\\",\\n parameters.emissiveMap ? getTexelDecodingFunction(\\\\\\\"emissiveMapTexelToLinear\\\\\\\", parameters.emissiveMapEncoding) : \\\\\\\"\\\\\\\",\\n parameters.specularTintMap ? getTexelDecodingFunction(\\\\\\\"specularTintMapTexelToLinear\\\\\\\", parameters.specularTintMapEncoding) : \\\\\\\"\\\\\\\",\\n parameters.lightMap ? getTexelDecodingFunction(\\\\\\\"lightMapTexelToLinear\\\\\\\", parameters.lightMapEncoding) : \\\\\\\"\\\\\\\",\\n getTexelEncodingFunction(\\\\\\\"linearToOutputTexel\\\\\\\", parameters.outputEncoding),\\n parameters.depthPacking ? \\\\\\\"#define DEPTH_PACKING \\\\\\\" + parameters.depthPacking : \\\\\\\"\\\\\\\",\\n \\\\\\\"\\\\n\\\\\\\"\\n ].filter(filterEmptyLine).join(\\\\\\\"\\\\n\\\\\\\");\\n }\\n vertexShader = resolveIncludes(vertexShader);\\n vertexShader = replaceLightNums(vertexShader, parameters);\\n vertexShader = replaceClippingPlaneNums(vertexShader, parameters);\\n fragmentShader = resolveIncludes(fragmentShader);\\n fragmentShader = replaceLightNums(fragmentShader, parameters);\\n fragmentShader = replaceClippingPlaneNums(fragmentShader, parameters);\\n vertexShader = unrollLoops(vertexShader);\\n fragmentShader = unrollLoops(fragmentShader);\\n if (parameters.isWebGL2 && parameters.isRawShaderMaterial !== true) {\\n versionString = \\\\\\\"#version 300 es\\\\n\\\\\\\";\\n prefixVertex = [\\n \\\\\\\"precision mediump sampler2DArray;\\\\\\\",\\n \\\\\\\"#define attribute in\\\\\\\",\\n \\\\\\\"#define varying out\\\\\\\",\\n \\\\\\\"#define texture2D texture\\\\\\\"\\n ].join(\\\\\\\"\\\\n\\\\\\\") + \\\\\\\"\\\\n\\\\\\\" + prefixVertex;\\n prefixFragment = [\\n \\\\\\\"#define varying in\\\\\\\",\\n parameters.glslVersion === GLSL3 ? \\\\\\\"\\\\\\\" : \\\\\\\"out highp vec4 pc_fragColor;\\\\\\\",\\n parameters.glslVersion === GLSL3 ? \\\\\\\"\\\\\\\" : \\\\\\\"#define gl_FragColor pc_fragColor\\\\\\\",\\n \\\\\\\"#define gl_FragDepthEXT gl_FragDepth\\\\\\\",\\n \\\\\\\"#define texture2D texture\\\\\\\",\\n \\\\\\\"#define textureCube texture\\\\\\\",\\n \\\\\\\"#define texture2DProj textureProj\\\\\\\",\\n \\\\\\\"#define texture2DLodEXT textureLod\\\\\\\",\\n \\\\\\\"#define texture2DProjLodEXT textureProjLod\\\\\\\",\\n \\\\\\\"#define textureCubeLodEXT textureLod\\\\\\\",\\n \\\\\\\"#define texture2DGradEXT textureGrad\\\\\\\",\\n \\\\\\\"#define texture2DProjGradEXT textureProjGrad\\\\\\\",\\n \\\\\\\"#define textureCubeGradEXT textureGrad\\\\\\\"\\n ].join(\\\\\\\"\\\\n\\\\\\\") + \\\\\\\"\\\\n\\\\\\\" + prefixFragment;\\n }\\n const vertexGlsl = versionString + prefixVertex + vertexShader;\\n const fragmentGlsl = versionString + prefixFragment + fragmentShader;\\n const glVertexShader = WebGLShader(gl, gl.VERTEX_SHADER, vertexGlsl);\\n const glFragmentShader = WebGLShader(gl, gl.FRAGMENT_SHADER, fragmentGlsl);\\n gl.attachShader(program, glVertexShader);\\n gl.attachShader(program, glFragmentShader);\\n if (parameters.index0AttributeName !== void 0) {\\n gl.bindAttribLocation(program, 0, parameters.index0AttributeName);\\n } else if (parameters.morphTargets === true) {\\n gl.bindAttribLocation(program, 0, \\\\\\\"position\\\\\\\");\\n }\\n gl.linkProgram(program);\\n if (renderer.debug.checkShaderErrors) {\\n const programLog = gl.getProgramInfoLog(program).trim();\\n const vertexLog = gl.getShaderInfoLog(glVertexShader).trim();\\n const fragmentLog = gl.getShaderInfoLog(glFragmentShader).trim();\\n let runnable = true;\\n let haveDiagnostics = true;\\n if (gl.getProgramParameter(program, gl.LINK_STATUS) === false) {\\n runnable = false;\\n const vertexErrors = getShaderErrors(gl, glVertexShader, \\\\\\\"vertex\\\\\\\");\\n const fragmentErrors = getShaderErrors(gl, glFragmentShader, \\\\\\\"fragment\\\\\\\");\\n console.error(\\\\\\\"THREE.WebGLProgram: Shader Error \\\\\\\" + gl.getError() + \\\\\\\" - VALIDATE_STATUS \\\\\\\" + gl.getProgramParameter(program, gl.VALIDATE_STATUS) + \\\\\\\"\\\\n\\\\nProgram Info Log: \\\\\\\" + programLog + \\\\\\\"\\\\n\\\\\\\" + vertexErrors + \\\\\\\"\\\\n\\\\\\\" + fragmentErrors);\\n } else if (programLog !== \\\\\\\"\\\\\\\") {\\n console.warn(\\\\\\\"THREE.WebGLProgram: Program Info Log:\\\\\\\", programLog);\\n } else if (vertexLog === \\\\\\\"\\\\\\\" || fragmentLog === \\\\\\\"\\\\\\\") {\\n haveDiagnostics = false;\\n }\\n if (haveDiagnostics) {\\n this.diagnostics = {\\n runnable,\\n programLog,\\n vertexShader: {\\n log: vertexLog,\\n prefix: prefixVertex\\n },\\n fragmentShader: {\\n log: fragmentLog,\\n prefix: prefixFragment\\n }\\n };\\n }\\n }\\n gl.deleteShader(glVertexShader);\\n gl.deleteShader(glFragmentShader);\\n let cachedUniforms;\\n this.getUniforms = function() {\\n if (cachedUniforms === void 0) {\\n cachedUniforms = new WebGLUniforms(gl, program);\\n }\\n return cachedUniforms;\\n };\\n let cachedAttributes;\\n this.getAttributes = function() {\\n if (cachedAttributes === void 0) {\\n cachedAttributes = fetchAttributeLocations(gl, program);\\n }\\n return cachedAttributes;\\n };\\n this.destroy = function() {\\n bindingStates.releaseStatesOfProgram(this);\\n gl.deleteProgram(program);\\n this.program = void 0;\\n };\\n this.name = parameters.shaderName;\\n this.id = programIdCount++;\\n this.cacheKey = cacheKey;\\n this.usedTimes = 1;\\n this.program = program;\\n this.vertexShader = glVertexShader;\\n this.fragmentShader = glFragmentShader;\\n return this;\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLPrograms.js\\nfunction WebGLPrograms(renderer, cubemaps, cubeuvmaps, extensions, capabilities, bindingStates, clipping) {\\n const programs = [];\\n const isWebGL2 = capabilities.isWebGL2;\\n const logarithmicDepthBuffer = capabilities.logarithmicDepthBuffer;\\n const floatVertexTextures = capabilities.floatVertexTextures;\\n const maxVertexUniforms = capabilities.maxVertexUniforms;\\n const vertexTextures = capabilities.vertexTextures;\\n let precision = capabilities.precision;\\n const shaderIDs = {\\n MeshDepthMaterial: \\\\\\\"depth\\\\\\\",\\n MeshDistanceMaterial: \\\\\\\"distanceRGBA\\\\\\\",\\n MeshNormalMaterial: \\\\\\\"normal\\\\\\\",\\n MeshBasicMaterial: \\\\\\\"basic\\\\\\\",\\n MeshLambertMaterial: \\\\\\\"lambert\\\\\\\",\\n MeshPhongMaterial: \\\\\\\"phong\\\\\\\",\\n MeshToonMaterial: \\\\\\\"toon\\\\\\\",\\n MeshStandardMaterial: \\\\\\\"physical\\\\\\\",\\n MeshPhysicalMaterial: \\\\\\\"physical\\\\\\\",\\n MeshMatcapMaterial: \\\\\\\"matcap\\\\\\\",\\n LineBasicMaterial: \\\\\\\"basic\\\\\\\",\\n LineDashedMaterial: \\\\\\\"dashed\\\\\\\",\\n PointsMaterial: \\\\\\\"points\\\\\\\",\\n ShadowMaterial: \\\\\\\"shadow\\\\\\\",\\n SpriteMaterial: \\\\\\\"sprite\\\\\\\"\\n };\\n const parameterNames = [\\n \\\\\\\"precision\\\\\\\",\\n \\\\\\\"isWebGL2\\\\\\\",\\n \\\\\\\"supportsVertexTextures\\\\\\\",\\n \\\\\\\"outputEncoding\\\\\\\",\\n \\\\\\\"instancing\\\\\\\",\\n \\\\\\\"instancingColor\\\\\\\",\\n \\\\\\\"map\\\\\\\",\\n \\\\\\\"mapEncoding\\\\\\\",\\n \\\\\\\"matcap\\\\\\\",\\n \\\\\\\"matcapEncoding\\\\\\\",\\n \\\\\\\"envMap\\\\\\\",\\n \\\\\\\"envMapMode\\\\\\\",\\n \\\\\\\"envMapEncoding\\\\\\\",\\n \\\\\\\"envMapCubeUV\\\\\\\",\\n \\\\\\\"lightMap\\\\\\\",\\n \\\\\\\"lightMapEncoding\\\\\\\",\\n \\\\\\\"aoMap\\\\\\\",\\n \\\\\\\"emissiveMap\\\\\\\",\\n \\\\\\\"emissiveMapEncoding\\\\\\\",\\n \\\\\\\"bumpMap\\\\\\\",\\n \\\\\\\"normalMap\\\\\\\",\\n \\\\\\\"objectSpaceNormalMap\\\\\\\",\\n \\\\\\\"tangentSpaceNormalMap\\\\\\\",\\n \\\\\\\"clearcoat\\\\\\\",\\n \\\\\\\"clearcoatMap\\\\\\\",\\n \\\\\\\"clearcoatRoughnessMap\\\\\\\",\\n \\\\\\\"clearcoatNormalMap\\\\\\\",\\n \\\\\\\"displacementMap\\\\\\\",\\n \\\\\\\"specularMap\\\\\\\",\\n \\\\\\\"specularIntensityMap\\\\\\\",\\n \\\\\\\"specularTintMap\\\\\\\",\\n \\\\\\\"specularTintMapEncoding\\\\\\\",\\n \\\\\\\"roughnessMap\\\\\\\",\\n \\\\\\\"metalnessMap\\\\\\\",\\n \\\\\\\"gradientMap\\\\\\\",\\n \\\\\\\"alphaMap\\\\\\\",\\n \\\\\\\"alphaTest\\\\\\\",\\n \\\\\\\"combine\\\\\\\",\\n \\\\\\\"vertexColors\\\\\\\",\\n \\\\\\\"vertexAlphas\\\\\\\",\\n \\\\\\\"vertexTangents\\\\\\\",\\n \\\\\\\"vertexUvs\\\\\\\",\\n \\\\\\\"uvsVertexOnly\\\\\\\",\\n \\\\\\\"fog\\\\\\\",\\n \\\\\\\"useFog\\\\\\\",\\n \\\\\\\"fogExp2\\\\\\\",\\n \\\\\\\"flatShading\\\\\\\",\\n \\\\\\\"sizeAttenuation\\\\\\\",\\n \\\\\\\"logarithmicDepthBuffer\\\\\\\",\\n \\\\\\\"skinning\\\\\\\",\\n \\\\\\\"maxBones\\\\\\\",\\n \\\\\\\"useVertexTexture\\\\\\\",\\n \\\\\\\"morphTargets\\\\\\\",\\n \\\\\\\"morphNormals\\\\\\\",\\n \\\\\\\"morphTargetsCount\\\\\\\",\\n \\\\\\\"premultipliedAlpha\\\\\\\",\\n \\\\\\\"numDirLights\\\\\\\",\\n \\\\\\\"numPointLights\\\\\\\",\\n \\\\\\\"numSpotLights\\\\\\\",\\n \\\\\\\"numHemiLights\\\\\\\",\\n \\\\\\\"numRectAreaLights\\\\\\\",\\n \\\\\\\"numDirLightShadows\\\\\\\",\\n \\\\\\\"numPointLightShadows\\\\\\\",\\n \\\\\\\"numSpotLightShadows\\\\\\\",\\n \\\\\\\"shadowMapEnabled\\\\\\\",\\n \\\\\\\"shadowMapType\\\\\\\",\\n \\\\\\\"toneMapping\\\\\\\",\\n \\\\\\\"physicallyCorrectLights\\\\\\\",\\n \\\\\\\"doubleSided\\\\\\\",\\n \\\\\\\"flipSided\\\\\\\",\\n \\\\\\\"numClippingPlanes\\\\\\\",\\n \\\\\\\"numClipIntersection\\\\\\\",\\n \\\\\\\"depthPacking\\\\\\\",\\n \\\\\\\"dithering\\\\\\\",\\n \\\\\\\"format\\\\\\\",\\n \\\\\\\"sheen\\\\\\\",\\n \\\\\\\"transmission\\\\\\\",\\n \\\\\\\"transmissionMap\\\\\\\",\\n \\\\\\\"thicknessMap\\\\\\\"\\n ];\\n function getMaxBones(object) {\\n const skeleton = object.skeleton;\\n const bones = skeleton.bones;\\n if (floatVertexTextures) {\\n return 1024;\\n } else {\\n const nVertexUniforms = maxVertexUniforms;\\n const nVertexMatrices = Math.floor((nVertexUniforms - 20) / 4);\\n const maxBones = Math.min(nVertexMatrices, bones.length);\\n if (maxBones < bones.length) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Skeleton has \\\\\\\" + bones.length + \\\\\\\" bones. This GPU supports \\\\\\\" + maxBones + \\\\\\\".\\\\\\\");\\n return 0;\\n }\\n return maxBones;\\n }\\n }\\n function getTextureEncodingFromMap(map) {\\n let encoding;\\n if (map && map.isTexture) {\\n encoding = map.encoding;\\n } else if (map && map.isWebGLRenderTarget) {\\n console.warn(\\\\\\\"THREE.WebGLPrograms.getTextureEncodingFromMap: don't use render targets as textures. Use their .texture property instead.\\\\\\\");\\n encoding = map.texture.encoding;\\n } else {\\n encoding = LinearEncoding;\\n }\\n if (isWebGL2 && map && map.isTexture && map.format === RGBAFormat && map.type === UnsignedByteType && map.encoding === sRGBEncoding) {\\n encoding = LinearEncoding;\\n }\\n return encoding;\\n }\\n function getParameters(material, lights, shadows, scene, object) {\\n const fog = scene.fog;\\n const environment = material.isMeshStandardMaterial ? scene.environment : null;\\n const envMap = (material.isMeshStandardMaterial ? cubeuvmaps : cubemaps).get(material.envMap || environment);\\n const shaderID = shaderIDs[material.type];\\n const maxBones = object.isSkinnedMesh ? getMaxBones(object) : 0;\\n if (material.precision !== null) {\\n precision = capabilities.getMaxPrecision(material.precision);\\n if (precision !== material.precision) {\\n console.warn(\\\\\\\"THREE.WebGLProgram.getParameters:\\\\\\\", material.precision, \\\\\\\"not supported, using\\\\\\\", precision, \\\\\\\"instead.\\\\\\\");\\n }\\n }\\n let vertexShader, fragmentShader;\\n if (shaderID) {\\n const shader = ShaderLib[shaderID];\\n vertexShader = shader.vertexShader;\\n fragmentShader = shader.fragmentShader;\\n } else {\\n vertexShader = material.vertexShader;\\n fragmentShader = material.fragmentShader;\\n }\\n const currentRenderTarget = renderer.getRenderTarget();\\n const useAlphaTest = material.alphaTest > 0;\\n const useClearcoat = material.clearcoat > 0;\\n const parameters = {\\n isWebGL2,\\n shaderID,\\n shaderName: material.type,\\n vertexShader,\\n fragmentShader,\\n defines: material.defines,\\n isRawShaderMaterial: material.isRawShaderMaterial === true,\\n glslVersion: material.glslVersion,\\n precision,\\n instancing: object.isInstancedMesh === true,\\n instancingColor: object.isInstancedMesh === true && object.instanceColor !== null,\\n supportsVertexTextures: vertexTextures,\\n outputEncoding: currentRenderTarget !== null ? getTextureEncodingFromMap(currentRenderTarget.texture) : renderer.outputEncoding,\\n map: !!material.map,\\n mapEncoding: getTextureEncodingFromMap(material.map),\\n matcap: !!material.matcap,\\n matcapEncoding: getTextureEncodingFromMap(material.matcap),\\n envMap: !!envMap,\\n envMapMode: envMap && envMap.mapping,\\n envMapEncoding: getTextureEncodingFromMap(envMap),\\n envMapCubeUV: !!envMap && (envMap.mapping === CubeUVReflectionMapping || envMap.mapping === CubeUVRefractionMapping),\\n lightMap: !!material.lightMap,\\n lightMapEncoding: getTextureEncodingFromMap(material.lightMap),\\n aoMap: !!material.aoMap,\\n emissiveMap: !!material.emissiveMap,\\n emissiveMapEncoding: getTextureEncodingFromMap(material.emissiveMap),\\n bumpMap: !!material.bumpMap,\\n normalMap: !!material.normalMap,\\n objectSpaceNormalMap: material.normalMapType === ObjectSpaceNormalMap,\\n tangentSpaceNormalMap: material.normalMapType === TangentSpaceNormalMap,\\n clearcoat: useClearcoat,\\n clearcoatMap: useClearcoat && !!material.clearcoatMap,\\n clearcoatRoughnessMap: useClearcoat && !!material.clearcoatRoughnessMap,\\n clearcoatNormalMap: useClearcoat && !!material.clearcoatNormalMap,\\n displacementMap: !!material.displacementMap,\\n roughnessMap: !!material.roughnessMap,\\n metalnessMap: !!material.metalnessMap,\\n specularMap: !!material.specularMap,\\n specularIntensityMap: !!material.specularIntensityMap,\\n specularTintMap: !!material.specularTintMap,\\n specularTintMapEncoding: getTextureEncodingFromMap(material.specularTintMap),\\n alphaMap: !!material.alphaMap,\\n alphaTest: useAlphaTest,\\n gradientMap: !!material.gradientMap,\\n sheen: material.sheen > 0,\\n transmission: material.transmission > 0,\\n transmissionMap: !!material.transmissionMap,\\n thicknessMap: !!material.thicknessMap,\\n combine: material.combine,\\n vertexTangents: !!material.normalMap && !!object.geometry && !!object.geometry.attributes.tangent,\\n vertexColors: material.vertexColors,\\n vertexAlphas: material.vertexColors === true && !!object.geometry && !!object.geometry.attributes.color && object.geometry.attributes.color.itemSize === 4,\\n vertexUvs: !!material.map || !!material.bumpMap || !!material.normalMap || !!material.specularMap || !!material.alphaMap || !!material.emissiveMap || !!material.roughnessMap || !!material.metalnessMap || !!material.clearcoatMap || !!material.clearcoatRoughnessMap || !!material.clearcoatNormalMap || !!material.displacementMap || !!material.transmissionMap || !!material.thicknessMap || !!material.specularIntensityMap || !!material.specularTintMap,\\n uvsVertexOnly: !(!!material.map || !!material.bumpMap || !!material.normalMap || !!material.specularMap || !!material.alphaMap || !!material.emissiveMap || !!material.roughnessMap || !!material.metalnessMap || !!material.clearcoatNormalMap || material.transmission > 0 || !!material.transmissionMap || !!material.thicknessMap || !!material.specularIntensityMap || !!material.specularTintMap) && !!material.displacementMap,\\n fog: !!fog,\\n useFog: material.fog,\\n fogExp2: fog && fog.isFogExp2,\\n flatShading: !!material.flatShading,\\n sizeAttenuation: material.sizeAttenuation,\\n logarithmicDepthBuffer,\\n skinning: object.isSkinnedMesh === true && maxBones > 0,\\n maxBones,\\n useVertexTexture: floatVertexTextures,\\n morphTargets: !!object.geometry && !!object.geometry.morphAttributes.position,\\n morphNormals: !!object.geometry && !!object.geometry.morphAttributes.normal,\\n morphTargetsCount: !!object.geometry && !!object.geometry.morphAttributes.position ? object.geometry.morphAttributes.position.length : 0,\\n numDirLights: lights.directional.length,\\n numPointLights: lights.point.length,\\n numSpotLights: lights.spot.length,\\n numRectAreaLights: lights.rectArea.length,\\n numHemiLights: lights.hemi.length,\\n numDirLightShadows: lights.directionalShadowMap.length,\\n numPointLightShadows: lights.pointShadowMap.length,\\n numSpotLightShadows: lights.spotShadowMap.length,\\n numClippingPlanes: clipping.numPlanes,\\n numClipIntersection: clipping.numIntersection,\\n format: material.format,\\n dithering: material.dithering,\\n shadowMapEnabled: renderer.shadowMap.enabled && shadows.length > 0,\\n shadowMapType: renderer.shadowMap.type,\\n toneMapping: material.toneMapped ? renderer.toneMapping : NoToneMapping,\\n physicallyCorrectLights: renderer.physicallyCorrectLights,\\n premultipliedAlpha: material.premultipliedAlpha,\\n doubleSided: material.side === DoubleSide,\\n flipSided: material.side === BackSide,\\n depthPacking: material.depthPacking !== void 0 ? material.depthPacking : false,\\n index0AttributeName: material.index0AttributeName,\\n extensionDerivatives: material.extensions && material.extensions.derivatives,\\n extensionFragDepth: material.extensions && material.extensions.fragDepth,\\n extensionDrawBuffers: material.extensions && material.extensions.drawBuffers,\\n extensionShaderTextureLOD: material.extensions && material.extensions.shaderTextureLOD,\\n rendererExtensionFragDepth: isWebGL2 || extensions.has(\\\\\\\"EXT_frag_depth\\\\\\\"),\\n rendererExtensionDrawBuffers: isWebGL2 || extensions.has(\\\\\\\"WEBGL_draw_buffers\\\\\\\"),\\n rendererExtensionShaderTextureLod: isWebGL2 || extensions.has(\\\\\\\"EXT_shader_texture_lod\\\\\\\"),\\n customProgramCacheKey: material.customProgramCacheKey()\\n };\\n return parameters;\\n }\\n function getProgramCacheKey(parameters) {\\n const array = [];\\n if (parameters.shaderID) {\\n array.push(parameters.shaderID);\\n } else {\\n array.push(parameters.fragmentShader);\\n array.push(parameters.vertexShader);\\n }\\n if (parameters.defines !== void 0) {\\n for (const name in parameters.defines) {\\n array.push(name);\\n array.push(parameters.defines[name]);\\n }\\n }\\n if (parameters.isRawShaderMaterial === false) {\\n for (let i = 0; i < parameterNames.length; i++) {\\n array.push(parameters[parameterNames[i]]);\\n }\\n array.push(renderer.outputEncoding);\\n array.push(renderer.gammaFactor);\\n }\\n array.push(parameters.customProgramCacheKey);\\n return array.join();\\n }\\n function getUniforms(material) {\\n const shaderID = shaderIDs[material.type];\\n let uniforms;\\n if (shaderID) {\\n const shader = ShaderLib[shaderID];\\n uniforms = UniformsUtils.clone(shader.uniforms);\\n } else {\\n uniforms = material.uniforms;\\n }\\n return uniforms;\\n }\\n function acquireProgram(parameters, cacheKey) {\\n let program;\\n for (let p = 0, pl = programs.length; p < pl; p++) {\\n const preexistingProgram = programs[p];\\n if (preexistingProgram.cacheKey === cacheKey) {\\n program = preexistingProgram;\\n ++program.usedTimes;\\n break;\\n }\\n }\\n if (program === void 0) {\\n program = new WebGLProgram(renderer, cacheKey, parameters, bindingStates);\\n programs.push(program);\\n }\\n return program;\\n }\\n function releaseProgram(program) {\\n if (--program.usedTimes === 0) {\\n const i = programs.indexOf(program);\\n programs[i] = programs[programs.length - 1];\\n programs.pop();\\n program.destroy();\\n }\\n }\\n return {\\n getParameters,\\n getProgramCacheKey,\\n getUniforms,\\n acquireProgram,\\n releaseProgram,\\n programs\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLProperties.js\\nfunction WebGLProperties() {\\n let properties = new WeakMap();\\n function get(object) {\\n let map = properties.get(object);\\n if (map === void 0) {\\n map = {};\\n properties.set(object, map);\\n }\\n return map;\\n }\\n function remove(object) {\\n properties.delete(object);\\n }\\n function update(object, key, value) {\\n properties.get(object)[key] = value;\\n }\\n function dispose() {\\n properties = new WeakMap();\\n }\\n return {\\n get,\\n remove,\\n update,\\n dispose\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLRenderLists.js\\nfunction painterSortStable(a, b) {\\n if (a.groupOrder !== b.groupOrder) {\\n return a.groupOrder - b.groupOrder;\\n } else if (a.renderOrder !== b.renderOrder) {\\n return a.renderOrder - b.renderOrder;\\n } else if (a.program !== b.program) {\\n return a.program.id - b.program.id;\\n } else if (a.material.id !== b.material.id) {\\n return a.material.id - b.material.id;\\n } else if (a.z !== b.z) {\\n return a.z - b.z;\\n } else {\\n return a.id - b.id;\\n }\\n}\\nfunction reversePainterSortStable(a, b) {\\n if (a.groupOrder !== b.groupOrder) {\\n return a.groupOrder - b.groupOrder;\\n } else if (a.renderOrder !== b.renderOrder) {\\n return a.renderOrder - b.renderOrder;\\n } else if (a.z !== b.z) {\\n return b.z - a.z;\\n } else {\\n return a.id - b.id;\\n }\\n}\\nfunction WebGLRenderList(properties) {\\n const renderItems = [];\\n let renderItemsIndex = 0;\\n const opaque = [];\\n const transmissive = [];\\n const transparent = [];\\n const defaultProgram = {id: -1};\\n function init() {\\n renderItemsIndex = 0;\\n opaque.length = 0;\\n transmissive.length = 0;\\n transparent.length = 0;\\n }\\n function getNextRenderItem(object, geometry, material, groupOrder, z, group) {\\n let renderItem = renderItems[renderItemsIndex];\\n const materialProperties = properties.get(material);\\n if (renderItem === void 0) {\\n renderItem = {\\n id: object.id,\\n object,\\n geometry,\\n material,\\n program: materialProperties.program || defaultProgram,\\n groupOrder,\\n renderOrder: object.renderOrder,\\n z,\\n group\\n };\\n renderItems[renderItemsIndex] = renderItem;\\n } else {\\n renderItem.id = object.id;\\n renderItem.object = object;\\n renderItem.geometry = geometry;\\n renderItem.material = material;\\n renderItem.program = materialProperties.program || defaultProgram;\\n renderItem.groupOrder = groupOrder;\\n renderItem.renderOrder = object.renderOrder;\\n renderItem.z = z;\\n renderItem.group = group;\\n }\\n renderItemsIndex++;\\n return renderItem;\\n }\\n function push(object, geometry, material, groupOrder, z, group) {\\n const renderItem = getNextRenderItem(object, geometry, material, groupOrder, z, group);\\n if (material.transmission > 0) {\\n transmissive.push(renderItem);\\n } else if (material.transparent === true) {\\n transparent.push(renderItem);\\n } else {\\n opaque.push(renderItem);\\n }\\n }\\n function unshift(object, geometry, material, groupOrder, z, group) {\\n const renderItem = getNextRenderItem(object, geometry, material, groupOrder, z, group);\\n if (material.transmission > 0) {\\n transmissive.unshift(renderItem);\\n } else if (material.transparent === true) {\\n transparent.unshift(renderItem);\\n } else {\\n opaque.unshift(renderItem);\\n }\\n }\\n function sort(customOpaqueSort, customTransparentSort) {\\n if (opaque.length > 1)\\n opaque.sort(customOpaqueSort || painterSortStable);\\n if (transmissive.length > 1)\\n transmissive.sort(customTransparentSort || reversePainterSortStable);\\n if (transparent.length > 1)\\n transparent.sort(customTransparentSort || reversePainterSortStable);\\n }\\n function finish() {\\n for (let i = renderItemsIndex, il = renderItems.length; i < il; i++) {\\n const renderItem = renderItems[i];\\n if (renderItem.id === null)\\n break;\\n renderItem.id = null;\\n renderItem.object = null;\\n renderItem.geometry = null;\\n renderItem.material = null;\\n renderItem.program = null;\\n renderItem.group = null;\\n }\\n }\\n return {\\n opaque,\\n transmissive,\\n transparent,\\n init,\\n push,\\n unshift,\\n finish,\\n sort\\n };\\n}\\nfunction WebGLRenderLists(properties) {\\n let lists = new WeakMap();\\n function get(scene, renderCallDepth) {\\n let list;\\n if (lists.has(scene) === false) {\\n list = new WebGLRenderList(properties);\\n lists.set(scene, [list]);\\n } else {\\n if (renderCallDepth >= lists.get(scene).length) {\\n list = new WebGLRenderList(properties);\\n lists.get(scene).push(list);\\n } else {\\n list = lists.get(scene)[renderCallDepth];\\n }\\n }\\n return list;\\n }\\n function dispose() {\\n lists = new WeakMap();\\n }\\n return {\\n get,\\n dispose\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLLights.js\\nfunction UniformsCache() {\\n const lights = {};\\n return {\\n get: function(light) {\\n if (lights[light.id] !== void 0) {\\n return lights[light.id];\\n }\\n let uniforms;\\n switch (light.type) {\\n case \\\\\\\"DirectionalLight\\\\\\\":\\n uniforms = {\\n direction: new Vector3(),\\n color: new Color()\\n };\\n break;\\n case \\\\\\\"SpotLight\\\\\\\":\\n uniforms = {\\n position: new Vector3(),\\n direction: new Vector3(),\\n color: new Color(),\\n distance: 0,\\n coneCos: 0,\\n penumbraCos: 0,\\n decay: 0\\n };\\n break;\\n case \\\\\\\"PointLight\\\\\\\":\\n uniforms = {\\n position: new Vector3(),\\n color: new Color(),\\n distance: 0,\\n decay: 0\\n };\\n break;\\n case \\\\\\\"HemisphereLight\\\\\\\":\\n uniforms = {\\n direction: new Vector3(),\\n skyColor: new Color(),\\n groundColor: new Color()\\n };\\n break;\\n case \\\\\\\"RectAreaLight\\\\\\\":\\n uniforms = {\\n color: new Color(),\\n position: new Vector3(),\\n halfWidth: new Vector3(),\\n halfHeight: new Vector3()\\n };\\n break;\\n }\\n lights[light.id] = uniforms;\\n return uniforms;\\n }\\n };\\n}\\nfunction ShadowUniformsCache() {\\n const lights = {};\\n return {\\n get: function(light) {\\n if (lights[light.id] !== void 0) {\\n return lights[light.id];\\n }\\n let uniforms;\\n switch (light.type) {\\n case \\\\\\\"DirectionalLight\\\\\\\":\\n uniforms = {\\n shadowBias: 0,\\n shadowNormalBias: 0,\\n shadowRadius: 1,\\n shadowMapSize: new Vector2()\\n };\\n break;\\n case \\\\\\\"SpotLight\\\\\\\":\\n uniforms = {\\n shadowBias: 0,\\n shadowNormalBias: 0,\\n shadowRadius: 1,\\n shadowMapSize: new Vector2()\\n };\\n break;\\n case \\\\\\\"PointLight\\\\\\\":\\n uniforms = {\\n shadowBias: 0,\\n shadowNormalBias: 0,\\n shadowRadius: 1,\\n shadowMapSize: new Vector2(),\\n shadowCameraNear: 1,\\n shadowCameraFar: 1e3\\n };\\n break;\\n }\\n lights[light.id] = uniforms;\\n return uniforms;\\n }\\n };\\n}\\nvar nextVersion = 0;\\nfunction shadowCastingLightsFirst(lightA, lightB) {\\n return (lightB.castShadow ? 1 : 0) - (lightA.castShadow ? 1 : 0);\\n}\\nfunction WebGLLights(extensions, capabilities) {\\n const cache = new UniformsCache();\\n const shadowCache = ShadowUniformsCache();\\n const state = {\\n version: 0,\\n hash: {\\n directionalLength: -1,\\n pointLength: -1,\\n spotLength: -1,\\n rectAreaLength: -1,\\n hemiLength: -1,\\n numDirectionalShadows: -1,\\n numPointShadows: -1,\\n numSpotShadows: -1\\n },\\n ambient: [0, 0, 0],\\n probe: [],\\n directional: [],\\n directionalShadow: [],\\n directionalShadowMap: [],\\n directionalShadowMatrix: [],\\n spot: [],\\n spotShadow: [],\\n spotShadowMap: [],\\n spotShadowMatrix: [],\\n rectArea: [],\\n rectAreaLTC1: null,\\n rectAreaLTC2: null,\\n point: [],\\n pointShadow: [],\\n pointShadowMap: [],\\n pointShadowMatrix: [],\\n hemi: []\\n };\\n for (let i = 0; i < 9; i++)\\n state.probe.push(new Vector3());\\n const vector3 = new Vector3();\\n const matrix4 = new Matrix4();\\n const matrix42 = new Matrix4();\\n function setup(lights, physicallyCorrectLights) {\\n let r = 0, g = 0, b = 0;\\n for (let i = 0; i < 9; i++)\\n state.probe[i].set(0, 0, 0);\\n let directionalLength = 0;\\n let pointLength = 0;\\n let spotLength = 0;\\n let rectAreaLength = 0;\\n let hemiLength = 0;\\n let numDirectionalShadows = 0;\\n let numPointShadows = 0;\\n let numSpotShadows = 0;\\n lights.sort(shadowCastingLightsFirst);\\n const scaleFactor = physicallyCorrectLights !== true ? Math.PI : 1;\\n for (let i = 0, l = lights.length; i < l; i++) {\\n const light = lights[i];\\n const color = light.color;\\n const intensity = light.intensity;\\n const distance = light.distance;\\n const shadowMap = light.shadow && light.shadow.map ? light.shadow.map.texture : null;\\n if (light.isAmbientLight) {\\n r += color.r * intensity * scaleFactor;\\n g += color.g * intensity * scaleFactor;\\n b += color.b * intensity * scaleFactor;\\n } else if (light.isLightProbe) {\\n for (let j = 0; j < 9; j++) {\\n state.probe[j].addScaledVector(light.sh.coefficients[j], intensity);\\n }\\n } else if (light.isDirectionalLight) {\\n const uniforms = cache.get(light);\\n uniforms.color.copy(light.color).multiplyScalar(light.intensity * scaleFactor);\\n if (light.castShadow) {\\n const shadow2 = light.shadow;\\n const shadowUniforms = shadowCache.get(light);\\n shadowUniforms.shadowBias = shadow2.bias;\\n shadowUniforms.shadowNormalBias = shadow2.normalBias;\\n shadowUniforms.shadowRadius = shadow2.radius;\\n shadowUniforms.shadowMapSize = shadow2.mapSize;\\n state.directionalShadow[directionalLength] = shadowUniforms;\\n state.directionalShadowMap[directionalLength] = shadowMap;\\n state.directionalShadowMatrix[directionalLength] = light.shadow.matrix;\\n numDirectionalShadows++;\\n }\\n state.directional[directionalLength] = uniforms;\\n directionalLength++;\\n } else if (light.isSpotLight) {\\n const uniforms = cache.get(light);\\n uniforms.position.setFromMatrixPosition(light.matrixWorld);\\n uniforms.color.copy(color).multiplyScalar(intensity * scaleFactor);\\n uniforms.distance = distance;\\n uniforms.coneCos = Math.cos(light.angle);\\n uniforms.penumbraCos = Math.cos(light.angle * (1 - light.penumbra));\\n uniforms.decay = light.decay;\\n if (light.castShadow) {\\n const shadow2 = light.shadow;\\n const shadowUniforms = shadowCache.get(light);\\n shadowUniforms.shadowBias = shadow2.bias;\\n shadowUniforms.shadowNormalBias = shadow2.normalBias;\\n shadowUniforms.shadowRadius = shadow2.radius;\\n shadowUniforms.shadowMapSize = shadow2.mapSize;\\n state.spotShadow[spotLength] = shadowUniforms;\\n state.spotShadowMap[spotLength] = shadowMap;\\n state.spotShadowMatrix[spotLength] = light.shadow.matrix;\\n numSpotShadows++;\\n }\\n state.spot[spotLength] = uniforms;\\n spotLength++;\\n } else if (light.isRectAreaLight) {\\n const uniforms = cache.get(light);\\n uniforms.color.copy(color).multiplyScalar(intensity);\\n uniforms.halfWidth.set(light.width * 0.5, 0, 0);\\n uniforms.halfHeight.set(0, light.height * 0.5, 0);\\n state.rectArea[rectAreaLength] = uniforms;\\n rectAreaLength++;\\n } else if (light.isPointLight) {\\n const uniforms = cache.get(light);\\n uniforms.color.copy(light.color).multiplyScalar(light.intensity * scaleFactor);\\n uniforms.distance = light.distance;\\n uniforms.decay = light.decay;\\n if (light.castShadow) {\\n const shadow2 = light.shadow;\\n const shadowUniforms = shadowCache.get(light);\\n shadowUniforms.shadowBias = shadow2.bias;\\n shadowUniforms.shadowNormalBias = shadow2.normalBias;\\n shadowUniforms.shadowRadius = shadow2.radius;\\n shadowUniforms.shadowMapSize = shadow2.mapSize;\\n shadowUniforms.shadowCameraNear = shadow2.camera.near;\\n shadowUniforms.shadowCameraFar = shadow2.camera.far;\\n state.pointShadow[pointLength] = shadowUniforms;\\n state.pointShadowMap[pointLength] = shadowMap;\\n state.pointShadowMatrix[pointLength] = light.shadow.matrix;\\n numPointShadows++;\\n }\\n state.point[pointLength] = uniforms;\\n pointLength++;\\n } else if (light.isHemisphereLight) {\\n const uniforms = cache.get(light);\\n uniforms.skyColor.copy(light.color).multiplyScalar(intensity * scaleFactor);\\n uniforms.groundColor.copy(light.groundColor).multiplyScalar(intensity * scaleFactor);\\n state.hemi[hemiLength] = uniforms;\\n hemiLength++;\\n }\\n }\\n if (rectAreaLength > 0) {\\n if (capabilities.isWebGL2) {\\n state.rectAreaLTC1 = UniformsLib.LTC_FLOAT_1;\\n state.rectAreaLTC2 = UniformsLib.LTC_FLOAT_2;\\n } else {\\n if (extensions.has(\\\\\\\"OES_texture_float_linear\\\\\\\") === true) {\\n state.rectAreaLTC1 = UniformsLib.LTC_FLOAT_1;\\n state.rectAreaLTC2 = UniformsLib.LTC_FLOAT_2;\\n } else if (extensions.has(\\\\\\\"OES_texture_half_float_linear\\\\\\\") === true) {\\n state.rectAreaLTC1 = UniformsLib.LTC_HALF_1;\\n state.rectAreaLTC2 = UniformsLib.LTC_HALF_2;\\n } else {\\n console.error(\\\\\\\"THREE.WebGLRenderer: Unable to use RectAreaLight. Missing WebGL extensions.\\\\\\\");\\n }\\n }\\n }\\n state.ambient[0] = r;\\n state.ambient[1] = g;\\n state.ambient[2] = b;\\n const hash = state.hash;\\n if (hash.directionalLength !== directionalLength || hash.pointLength !== pointLength || hash.spotLength !== spotLength || hash.rectAreaLength !== rectAreaLength || hash.hemiLength !== hemiLength || hash.numDirectionalShadows !== numDirectionalShadows || hash.numPointShadows !== numPointShadows || hash.numSpotShadows !== numSpotShadows) {\\n state.directional.length = directionalLength;\\n state.spot.length = spotLength;\\n state.rectArea.length = rectAreaLength;\\n state.point.length = pointLength;\\n state.hemi.length = hemiLength;\\n state.directionalShadow.length = numDirectionalShadows;\\n state.directionalShadowMap.length = numDirectionalShadows;\\n state.pointShadow.length = numPointShadows;\\n state.pointShadowMap.length = numPointShadows;\\n state.spotShadow.length = numSpotShadows;\\n state.spotShadowMap.length = numSpotShadows;\\n state.directionalShadowMatrix.length = numDirectionalShadows;\\n state.pointShadowMatrix.length = numPointShadows;\\n state.spotShadowMatrix.length = numSpotShadows;\\n hash.directionalLength = directionalLength;\\n hash.pointLength = pointLength;\\n hash.spotLength = spotLength;\\n hash.rectAreaLength = rectAreaLength;\\n hash.hemiLength = hemiLength;\\n hash.numDirectionalShadows = numDirectionalShadows;\\n hash.numPointShadows = numPointShadows;\\n hash.numSpotShadows = numSpotShadows;\\n state.version = nextVersion++;\\n }\\n }\\n function setupView(lights, camera) {\\n let directionalLength = 0;\\n let pointLength = 0;\\n let spotLength = 0;\\n let rectAreaLength = 0;\\n let hemiLength = 0;\\n const viewMatrix = camera.matrixWorldInverse;\\n for (let i = 0, l = lights.length; i < l; i++) {\\n const light = lights[i];\\n if (light.isDirectionalLight) {\\n const uniforms = state.directional[directionalLength];\\n uniforms.direction.setFromMatrixPosition(light.matrixWorld);\\n vector3.setFromMatrixPosition(light.target.matrixWorld);\\n uniforms.direction.sub(vector3);\\n uniforms.direction.transformDirection(viewMatrix);\\n directionalLength++;\\n } else if (light.isSpotLight) {\\n const uniforms = state.spot[spotLength];\\n uniforms.position.setFromMatrixPosition(light.matrixWorld);\\n uniforms.position.applyMatrix4(viewMatrix);\\n uniforms.direction.setFromMatrixPosition(light.matrixWorld);\\n vector3.setFromMatrixPosition(light.target.matrixWorld);\\n uniforms.direction.sub(vector3);\\n uniforms.direction.transformDirection(viewMatrix);\\n spotLength++;\\n } else if (light.isRectAreaLight) {\\n const uniforms = state.rectArea[rectAreaLength];\\n uniforms.position.setFromMatrixPosition(light.matrixWorld);\\n uniforms.position.applyMatrix4(viewMatrix);\\n matrix42.identity();\\n matrix4.copy(light.matrixWorld);\\n matrix4.premultiply(viewMatrix);\\n matrix42.extractRotation(matrix4);\\n uniforms.halfWidth.set(light.width * 0.5, 0, 0);\\n uniforms.halfHeight.set(0, light.height * 0.5, 0);\\n uniforms.halfWidth.applyMatrix4(matrix42);\\n uniforms.halfHeight.applyMatrix4(matrix42);\\n rectAreaLength++;\\n } else if (light.isPointLight) {\\n const uniforms = state.point[pointLength];\\n uniforms.position.setFromMatrixPosition(light.matrixWorld);\\n uniforms.position.applyMatrix4(viewMatrix);\\n pointLength++;\\n } else if (light.isHemisphereLight) {\\n const uniforms = state.hemi[hemiLength];\\n uniforms.direction.setFromMatrixPosition(light.matrixWorld);\\n uniforms.direction.transformDirection(viewMatrix);\\n uniforms.direction.normalize();\\n hemiLength++;\\n }\\n }\\n }\\n return {\\n setup,\\n setupView,\\n state\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLRenderStates.js\\nfunction WebGLRenderState(extensions, capabilities) {\\n const lights = new WebGLLights(extensions, capabilities);\\n const lightsArray = [];\\n const shadowsArray = [];\\n function init() {\\n lightsArray.length = 0;\\n shadowsArray.length = 0;\\n }\\n function pushLight(light) {\\n lightsArray.push(light);\\n }\\n function pushShadow(shadowLight) {\\n shadowsArray.push(shadowLight);\\n }\\n function setupLights(physicallyCorrectLights) {\\n lights.setup(lightsArray, physicallyCorrectLights);\\n }\\n function setupLightsView(camera) {\\n lights.setupView(lightsArray, camera);\\n }\\n const state = {\\n lightsArray,\\n shadowsArray,\\n lights\\n };\\n return {\\n init,\\n state,\\n setupLights,\\n setupLightsView,\\n pushLight,\\n pushShadow\\n };\\n}\\nfunction WebGLRenderStates(extensions, capabilities) {\\n let renderStates = new WeakMap();\\n function get(scene, renderCallDepth = 0) {\\n let renderState;\\n if (renderStates.has(scene) === false) {\\n renderState = new WebGLRenderState(extensions, capabilities);\\n renderStates.set(scene, [renderState]);\\n } else {\\n if (renderCallDepth >= renderStates.get(scene).length) {\\n renderState = new WebGLRenderState(extensions, capabilities);\\n renderStates.get(scene).push(renderState);\\n } else {\\n renderState = renderStates.get(scene)[renderCallDepth];\\n }\\n }\\n return renderState;\\n }\\n function dispose() {\\n renderStates = new WeakMap();\\n }\\n return {\\n get,\\n dispose\\n };\\n}\\n\\n// ../../../node_modules/three/src/materials/MeshDepthMaterial.js\\nvar MeshDepthMaterial = class extends Material {\\n constructor(parameters) {\\n super();\\n this.type = \\\\\\\"MeshDepthMaterial\\\\\\\";\\n this.depthPacking = BasicDepthPacking;\\n this.map = null;\\n this.alphaMap = null;\\n this.displacementMap = null;\\n this.displacementScale = 1;\\n this.displacementBias = 0;\\n this.wireframe = false;\\n this.wireframeLinewidth = 1;\\n this.fog = false;\\n this.setValues(parameters);\\n }\\n copy(source) {\\n super.copy(source);\\n this.depthPacking = source.depthPacking;\\n this.map = source.map;\\n this.alphaMap = source.alphaMap;\\n this.displacementMap = source.displacementMap;\\n this.displacementScale = source.displacementScale;\\n this.displacementBias = source.displacementBias;\\n this.wireframe = source.wireframe;\\n this.wireframeLinewidth = source.wireframeLinewidth;\\n return this;\\n }\\n};\\nMeshDepthMaterial.prototype.isMeshDepthMaterial = true;\\n\\n// ../../../node_modules/three/src/materials/MeshDistanceMaterial.js\\nvar MeshDistanceMaterial = class extends Material {\\n constructor(parameters) {\\n super();\\n this.type = \\\\\\\"MeshDistanceMaterial\\\\\\\";\\n this.referencePosition = new Vector3();\\n this.nearDistance = 1;\\n this.farDistance = 1e3;\\n this.map = null;\\n this.alphaMap = null;\\n this.displacementMap = null;\\n this.displacementScale = 1;\\n this.displacementBias = 0;\\n this.fog = false;\\n this.setValues(parameters);\\n }\\n copy(source) {\\n super.copy(source);\\n this.referencePosition.copy(source.referencePosition);\\n this.nearDistance = source.nearDistance;\\n this.farDistance = source.farDistance;\\n this.map = source.map;\\n this.alphaMap = source.alphaMap;\\n this.displacementMap = source.displacementMap;\\n this.displacementScale = source.displacementScale;\\n this.displacementBias = source.displacementBias;\\n return this;\\n }\\n};\\nMeshDistanceMaterial.prototype.isMeshDistanceMaterial = true;\\n\\n// ../../../node_modules/three/src/renderers/shaders/ShaderLib/vsm.glsl.js\\nvar vertex17 = `\\nvoid main() {\\n\\n\\tgl_Position = vec4( position, 1.0 );\\n\\n}\\n`;\\nvar fragment17 = `\\nuniform sampler2D shadow_pass;\\nuniform vec2 resolution;\\nuniform float radius;\\nuniform float samples;\\n\\n#include \\n\\nvoid main() {\\n\\n\\tfloat mean = 0.0;\\n\\tfloat squared_mean = 0.0;\\n\\n\\t// This seems totally useless but it's a crazy work around for a Adreno compiler bug\\n\\t// float depth = unpackRGBAToDepth( texture2D( shadow_pass, ( gl_FragCoord.xy ) / resolution ) );\\n\\n\\tfloat uvStride = samples <= 1.0 ? 0.0 : 2.0 / ( samples - 1.0 );\\n\\tfloat uvStart = samples <= 1.0 ? 0.0 : - 1.0;\\n\\tfor ( float i = 0.0; i < samples; i ++ ) {\\n\\n\\t\\tfloat uvOffset = uvStart + i * uvStride;\\n\\n\\t\\t#ifdef HORIZONTAL_PASS\\n\\n\\t\\t\\tvec2 distribution = unpackRGBATo2Half( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( uvOffset, 0.0 ) * radius ) / resolution ) );\\n\\t\\t\\tmean += distribution.x;\\n\\t\\t\\tsquared_mean += distribution.y * distribution.y + distribution.x * distribution.x;\\n\\n\\t\\t#else\\n\\n\\t\\t\\tfloat depth = unpackRGBAToDepth( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( 0.0, uvOffset ) * radius ) / resolution ) );\\n\\t\\t\\tmean += depth;\\n\\t\\t\\tsquared_mean += depth * depth;\\n\\n\\t\\t#endif\\n\\n\\t}\\n\\n\\tmean = mean / samples;\\n\\tsquared_mean = squared_mean / samples;\\n\\n\\tfloat std_dev = sqrt( squared_mean - mean * mean );\\n\\n\\tgl_FragColor = pack2HalfToRGBA( vec2( mean, std_dev ) );\\n\\n}\\n`;\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLShadowMap.js\\nfunction WebGLShadowMap(_renderer, _objects, _capabilities) {\\n let _frustum = new Frustum();\\n const _shadowMapSize = new Vector2(), _viewportSize = new Vector2(), _viewport = new Vector4(), _depthMaterial = new MeshDepthMaterial({depthPacking: RGBADepthPacking}), _distanceMaterial = new MeshDistanceMaterial(), _materialCache = {}, _maxTextureSize = _capabilities.maxTextureSize;\\n const shadowSide = {0: BackSide, 1: FrontSide, 2: DoubleSide};\\n const shadowMaterialVertical = new ShaderMaterial({\\n uniforms: {\\n shadow_pass: {value: null},\\n resolution: {value: new Vector2()},\\n radius: {value: 4},\\n samples: {value: 8}\\n },\\n vertexShader: vertex17,\\n fragmentShader: fragment17\\n });\\n const shadowMaterialHorizontal = shadowMaterialVertical.clone();\\n shadowMaterialHorizontal.defines.HORIZONTAL_PASS = 1;\\n const fullScreenTri = new BufferGeometry();\\n fullScreenTri.setAttribute(\\\\\\\"position\\\\\\\", new BufferAttribute(new Float32Array([-1, -1, 0.5, 3, -1, 0.5, -1, 3, 0.5]), 3));\\n const fullScreenMesh = new Mesh(fullScreenTri, shadowMaterialVertical);\\n const scope = this;\\n this.enabled = false;\\n this.autoUpdate = true;\\n this.needsUpdate = false;\\n this.type = PCFShadowMap;\\n this.render = function(lights, scene, camera) {\\n if (scope.enabled === false)\\n return;\\n if (scope.autoUpdate === false && scope.needsUpdate === false)\\n return;\\n if (lights.length === 0)\\n return;\\n const currentRenderTarget = _renderer.getRenderTarget();\\n const activeCubeFace = _renderer.getActiveCubeFace();\\n const activeMipmapLevel = _renderer.getActiveMipmapLevel();\\n const _state = _renderer.state;\\n _state.setBlending(NoBlending);\\n _state.buffers.color.setClear(1, 1, 1, 1);\\n _state.buffers.depth.setTest(true);\\n _state.setScissorTest(false);\\n for (let i = 0, il = lights.length; i < il; i++) {\\n const light = lights[i];\\n const shadow2 = light.shadow;\\n if (shadow2 === void 0) {\\n console.warn(\\\\\\\"THREE.WebGLShadowMap:\\\\\\\", light, \\\\\\\"has no shadow.\\\\\\\");\\n continue;\\n }\\n if (shadow2.autoUpdate === false && shadow2.needsUpdate === false)\\n continue;\\n _shadowMapSize.copy(shadow2.mapSize);\\n const shadowFrameExtents = shadow2.getFrameExtents();\\n _shadowMapSize.multiply(shadowFrameExtents);\\n _viewportSize.copy(shadow2.mapSize);\\n if (_shadowMapSize.x > _maxTextureSize || _shadowMapSize.y > _maxTextureSize) {\\n if (_shadowMapSize.x > _maxTextureSize) {\\n _viewportSize.x = Math.floor(_maxTextureSize / shadowFrameExtents.x);\\n _shadowMapSize.x = _viewportSize.x * shadowFrameExtents.x;\\n shadow2.mapSize.x = _viewportSize.x;\\n }\\n if (_shadowMapSize.y > _maxTextureSize) {\\n _viewportSize.y = Math.floor(_maxTextureSize / shadowFrameExtents.y);\\n _shadowMapSize.y = _viewportSize.y * shadowFrameExtents.y;\\n shadow2.mapSize.y = _viewportSize.y;\\n }\\n }\\n if (shadow2.map === null && !shadow2.isPointLightShadow && this.type === VSMShadowMap) {\\n const pars = {minFilter: LinearFilter, magFilter: LinearFilter, format: RGBAFormat};\\n shadow2.map = new WebGLRenderTarget(_shadowMapSize.x, _shadowMapSize.y, pars);\\n shadow2.map.texture.name = light.name + \\\\\\\".shadowMap\\\\\\\";\\n shadow2.mapPass = new WebGLRenderTarget(_shadowMapSize.x, _shadowMapSize.y, pars);\\n shadow2.camera.updateProjectionMatrix();\\n }\\n if (shadow2.map === null) {\\n const pars = {minFilter: NearestFilter, magFilter: NearestFilter, format: RGBAFormat};\\n shadow2.map = new WebGLRenderTarget(_shadowMapSize.x, _shadowMapSize.y, pars);\\n shadow2.map.texture.name = light.name + \\\\\\\".shadowMap\\\\\\\";\\n shadow2.camera.updateProjectionMatrix();\\n }\\n _renderer.setRenderTarget(shadow2.map);\\n _renderer.clear();\\n const viewportCount = shadow2.getViewportCount();\\n for (let vp = 0; vp < viewportCount; vp++) {\\n const viewport = shadow2.getViewport(vp);\\n _viewport.set(_viewportSize.x * viewport.x, _viewportSize.y * viewport.y, _viewportSize.x * viewport.z, _viewportSize.y * viewport.w);\\n _state.viewport(_viewport);\\n shadow2.updateMatrices(light, vp);\\n _frustum = shadow2.getFrustum();\\n renderObject(scene, camera, shadow2.camera, light, this.type);\\n }\\n if (!shadow2.isPointLightShadow && this.type === VSMShadowMap) {\\n VSMPass(shadow2, camera);\\n }\\n shadow2.needsUpdate = false;\\n }\\n scope.needsUpdate = false;\\n _renderer.setRenderTarget(currentRenderTarget, activeCubeFace, activeMipmapLevel);\\n };\\n function VSMPass(shadow2, camera) {\\n const geometry = _objects.update(fullScreenMesh);\\n shadowMaterialVertical.uniforms.shadow_pass.value = shadow2.map.texture;\\n shadowMaterialVertical.uniforms.resolution.value = shadow2.mapSize;\\n shadowMaterialVertical.uniforms.radius.value = shadow2.radius;\\n shadowMaterialVertical.uniforms.samples.value = shadow2.blurSamples;\\n _renderer.setRenderTarget(shadow2.mapPass);\\n _renderer.clear();\\n _renderer.renderBufferDirect(camera, null, geometry, shadowMaterialVertical, fullScreenMesh, null);\\n shadowMaterialHorizontal.uniforms.shadow_pass.value = shadow2.mapPass.texture;\\n shadowMaterialHorizontal.uniforms.resolution.value = shadow2.mapSize;\\n shadowMaterialHorizontal.uniforms.radius.value = shadow2.radius;\\n shadowMaterialHorizontal.uniforms.samples.value = shadow2.blurSamples;\\n _renderer.setRenderTarget(shadow2.map);\\n _renderer.clear();\\n _renderer.renderBufferDirect(camera, null, geometry, shadowMaterialHorizontal, fullScreenMesh, null);\\n }\\n function getDepthMaterial(object, geometry, material, light, shadowCameraNear, shadowCameraFar, type) {\\n let result = null;\\n const customMaterial = light.isPointLight === true ? object.customDistanceMaterial : object.customDepthMaterial;\\n if (customMaterial !== void 0) {\\n result = customMaterial;\\n } else {\\n result = light.isPointLight === true ? _distanceMaterial : _depthMaterial;\\n }\\n if (_renderer.localClippingEnabled && material.clipShadows === true && material.clippingPlanes.length !== 0 || material.displacementMap && material.displacementScale !== 0 || material.alphaMap && material.alphaTest > 0) {\\n const keyA = result.uuid, keyB = material.uuid;\\n let materialsForVariant = _materialCache[keyA];\\n if (materialsForVariant === void 0) {\\n materialsForVariant = {};\\n _materialCache[keyA] = materialsForVariant;\\n }\\n let cachedMaterial = materialsForVariant[keyB];\\n if (cachedMaterial === void 0) {\\n cachedMaterial = result.clone();\\n materialsForVariant[keyB] = cachedMaterial;\\n }\\n result = cachedMaterial;\\n }\\n result.visible = material.visible;\\n result.wireframe = material.wireframe;\\n if (type === VSMShadowMap) {\\n result.side = material.shadowSide !== null ? material.shadowSide : material.side;\\n } else {\\n result.side = material.shadowSide !== null ? material.shadowSide : shadowSide[material.side];\\n }\\n result.alphaMap = material.alphaMap;\\n result.alphaTest = material.alphaTest;\\n result.clipShadows = material.clipShadows;\\n result.clippingPlanes = material.clippingPlanes;\\n result.clipIntersection = material.clipIntersection;\\n result.displacementMap = material.displacementMap;\\n result.displacementScale = material.displacementScale;\\n result.displacementBias = material.displacementBias;\\n result.wireframeLinewidth = material.wireframeLinewidth;\\n result.linewidth = material.linewidth;\\n if (light.isPointLight === true && result.isMeshDistanceMaterial === true) {\\n result.referencePosition.setFromMatrixPosition(light.matrixWorld);\\n result.nearDistance = shadowCameraNear;\\n result.farDistance = shadowCameraFar;\\n }\\n return result;\\n }\\n function renderObject(object, camera, shadowCamera, light, type) {\\n if (object.visible === false)\\n return;\\n const visible = object.layers.test(camera.layers);\\n if (visible && (object.isMesh || object.isLine || object.isPoints)) {\\n if ((object.castShadow || object.receiveShadow && type === VSMShadowMap) && (!object.frustumCulled || _frustum.intersectsObject(object))) {\\n object.modelViewMatrix.multiplyMatrices(shadowCamera.matrixWorldInverse, object.matrixWorld);\\n const geometry = _objects.update(object);\\n const material = object.material;\\n if (Array.isArray(material)) {\\n const groups = geometry.groups;\\n for (let k = 0, kl = groups.length; k < kl; k++) {\\n const group = groups[k];\\n const groupMaterial = material[group.materialIndex];\\n if (groupMaterial && groupMaterial.visible) {\\n const depthMaterial = getDepthMaterial(object, geometry, groupMaterial, light, shadowCamera.near, shadowCamera.far, type);\\n _renderer.renderBufferDirect(shadowCamera, null, geometry, depthMaterial, object, group);\\n }\\n }\\n } else if (material.visible) {\\n const depthMaterial = getDepthMaterial(object, geometry, material, light, shadowCamera.near, shadowCamera.far, type);\\n _renderer.renderBufferDirect(shadowCamera, null, geometry, depthMaterial, object, null);\\n }\\n }\\n }\\n const children = object.children;\\n for (let i = 0, l = children.length; i < l; i++) {\\n renderObject(children[i], camera, shadowCamera, light, type);\\n }\\n }\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLState.js\\nfunction WebGLState(gl, extensions, capabilities) {\\n const isWebGL2 = capabilities.isWebGL2;\\n function ColorBuffer() {\\n let locked = false;\\n const color = new Vector4();\\n let currentColorMask = null;\\n const currentColorClear = new Vector4(0, 0, 0, 0);\\n return {\\n setMask: function(colorMask) {\\n if (currentColorMask !== colorMask && !locked) {\\n gl.colorMask(colorMask, colorMask, colorMask, colorMask);\\n currentColorMask = colorMask;\\n }\\n },\\n setLocked: function(lock) {\\n locked = lock;\\n },\\n setClear: function(r, g, b, a, premultipliedAlpha) {\\n if (premultipliedAlpha === true) {\\n r *= a;\\n g *= a;\\n b *= a;\\n }\\n color.set(r, g, b, a);\\n if (currentColorClear.equals(color) === false) {\\n gl.clearColor(r, g, b, a);\\n currentColorClear.copy(color);\\n }\\n },\\n reset: function() {\\n locked = false;\\n currentColorMask = null;\\n currentColorClear.set(-1, 0, 0, 0);\\n }\\n };\\n }\\n function DepthBuffer() {\\n let locked = false;\\n let currentDepthMask = null;\\n let currentDepthFunc = null;\\n let currentDepthClear = null;\\n return {\\n setTest: function(depthTest) {\\n if (depthTest) {\\n enable(gl.DEPTH_TEST);\\n } else {\\n disable(gl.DEPTH_TEST);\\n }\\n },\\n setMask: function(depthMask) {\\n if (currentDepthMask !== depthMask && !locked) {\\n gl.depthMask(depthMask);\\n currentDepthMask = depthMask;\\n }\\n },\\n setFunc: function(depthFunc) {\\n if (currentDepthFunc !== depthFunc) {\\n if (depthFunc) {\\n switch (depthFunc) {\\n case NeverDepth:\\n gl.depthFunc(gl.NEVER);\\n break;\\n case AlwaysDepth:\\n gl.depthFunc(gl.ALWAYS);\\n break;\\n case LessDepth:\\n gl.depthFunc(gl.LESS);\\n break;\\n case LessEqualDepth:\\n gl.depthFunc(gl.LEQUAL);\\n break;\\n case EqualDepth:\\n gl.depthFunc(gl.EQUAL);\\n break;\\n case GreaterEqualDepth:\\n gl.depthFunc(gl.GEQUAL);\\n break;\\n case GreaterDepth:\\n gl.depthFunc(gl.GREATER);\\n break;\\n case NotEqualDepth:\\n gl.depthFunc(gl.NOTEQUAL);\\n break;\\n default:\\n gl.depthFunc(gl.LEQUAL);\\n }\\n } else {\\n gl.depthFunc(gl.LEQUAL);\\n }\\n currentDepthFunc = depthFunc;\\n }\\n },\\n setLocked: function(lock) {\\n locked = lock;\\n },\\n setClear: function(depth2) {\\n if (currentDepthClear !== depth2) {\\n gl.clearDepth(depth2);\\n currentDepthClear = depth2;\\n }\\n },\\n reset: function() {\\n locked = false;\\n currentDepthMask = null;\\n currentDepthFunc = null;\\n currentDepthClear = null;\\n }\\n };\\n }\\n function StencilBuffer() {\\n let locked = false;\\n let currentStencilMask = null;\\n let currentStencilFunc = null;\\n let currentStencilRef = null;\\n let currentStencilFuncMask = null;\\n let currentStencilFail = null;\\n let currentStencilZFail = null;\\n let currentStencilZPass = null;\\n let currentStencilClear = null;\\n return {\\n setTest: function(stencilTest) {\\n if (!locked) {\\n if (stencilTest) {\\n enable(gl.STENCIL_TEST);\\n } else {\\n disable(gl.STENCIL_TEST);\\n }\\n }\\n },\\n setMask: function(stencilMask) {\\n if (currentStencilMask !== stencilMask && !locked) {\\n gl.stencilMask(stencilMask);\\n currentStencilMask = stencilMask;\\n }\\n },\\n setFunc: function(stencilFunc, stencilRef, stencilMask) {\\n if (currentStencilFunc !== stencilFunc || currentStencilRef !== stencilRef || currentStencilFuncMask !== stencilMask) {\\n gl.stencilFunc(stencilFunc, stencilRef, stencilMask);\\n currentStencilFunc = stencilFunc;\\n currentStencilRef = stencilRef;\\n currentStencilFuncMask = stencilMask;\\n }\\n },\\n setOp: function(stencilFail, stencilZFail, stencilZPass) {\\n if (currentStencilFail !== stencilFail || currentStencilZFail !== stencilZFail || currentStencilZPass !== stencilZPass) {\\n gl.stencilOp(stencilFail, stencilZFail, stencilZPass);\\n currentStencilFail = stencilFail;\\n currentStencilZFail = stencilZFail;\\n currentStencilZPass = stencilZPass;\\n }\\n },\\n setLocked: function(lock) {\\n locked = lock;\\n },\\n setClear: function(stencil) {\\n if (currentStencilClear !== stencil) {\\n gl.clearStencil(stencil);\\n currentStencilClear = stencil;\\n }\\n },\\n reset: function() {\\n locked = false;\\n currentStencilMask = null;\\n currentStencilFunc = null;\\n currentStencilRef = null;\\n currentStencilFuncMask = null;\\n currentStencilFail = null;\\n currentStencilZFail = null;\\n currentStencilZPass = null;\\n currentStencilClear = null;\\n }\\n };\\n }\\n const colorBuffer = new ColorBuffer();\\n const depthBuffer = new DepthBuffer();\\n const stencilBuffer = new StencilBuffer();\\n let enabledCapabilities = {};\\n let xrFramebuffer = null;\\n let currentBoundFramebuffers = {};\\n let currentProgram = null;\\n let currentBlendingEnabled = false;\\n let currentBlending = null;\\n let currentBlendEquation = null;\\n let currentBlendSrc = null;\\n let currentBlendDst = null;\\n let currentBlendEquationAlpha = null;\\n let currentBlendSrcAlpha = null;\\n let currentBlendDstAlpha = null;\\n let currentPremultipledAlpha = false;\\n let currentFlipSided = null;\\n let currentCullFace = null;\\n let currentLineWidth = null;\\n let currentPolygonOffsetFactor = null;\\n let currentPolygonOffsetUnits = null;\\n const maxTextures = gl.getParameter(gl.MAX_COMBINED_TEXTURE_IMAGE_UNITS);\\n let lineWidthAvailable = false;\\n let version = 0;\\n const glVersion = gl.getParameter(gl.VERSION);\\n if (glVersion.indexOf(\\\\\\\"WebGL\\\\\\\") !== -1) {\\n version = parseFloat(/^WebGL (\\\\d)/.exec(glVersion)[1]);\\n lineWidthAvailable = version >= 1;\\n } else if (glVersion.indexOf(\\\\\\\"OpenGL ES\\\\\\\") !== -1) {\\n version = parseFloat(/^OpenGL ES (\\\\d)/.exec(glVersion)[1]);\\n lineWidthAvailable = version >= 2;\\n }\\n let currentTextureSlot = null;\\n let currentBoundTextures = {};\\n const scissorParam = gl.getParameter(gl.SCISSOR_BOX);\\n const viewportParam = gl.getParameter(gl.VIEWPORT);\\n const currentScissor = new Vector4().fromArray(scissorParam);\\n const currentViewport = new Vector4().fromArray(viewportParam);\\n function createTexture(type, target, count) {\\n const data = new Uint8Array(4);\\n const texture = gl.createTexture();\\n gl.bindTexture(type, texture);\\n gl.texParameteri(type, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\\n gl.texParameteri(type, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\\n for (let i = 0; i < count; i++) {\\n gl.texImage2D(target + i, 0, gl.RGBA, 1, 1, 0, gl.RGBA, gl.UNSIGNED_BYTE, data);\\n }\\n return texture;\\n }\\n const emptyTextures = {};\\n emptyTextures[gl.TEXTURE_2D] = createTexture(gl.TEXTURE_2D, gl.TEXTURE_2D, 1);\\n emptyTextures[gl.TEXTURE_CUBE_MAP] = createTexture(gl.TEXTURE_CUBE_MAP, gl.TEXTURE_CUBE_MAP_POSITIVE_X, 6);\\n colorBuffer.setClear(0, 0, 0, 1);\\n depthBuffer.setClear(1);\\n stencilBuffer.setClear(0);\\n enable(gl.DEPTH_TEST);\\n depthBuffer.setFunc(LessEqualDepth);\\n setFlipSided(false);\\n setCullFace(CullFaceBack);\\n enable(gl.CULL_FACE);\\n setBlending(NoBlending);\\n function enable(id) {\\n if (enabledCapabilities[id] !== true) {\\n gl.enable(id);\\n enabledCapabilities[id] = true;\\n }\\n }\\n function disable(id) {\\n if (enabledCapabilities[id] !== false) {\\n gl.disable(id);\\n enabledCapabilities[id] = false;\\n }\\n }\\n function bindXRFramebuffer(framebuffer) {\\n if (framebuffer !== xrFramebuffer) {\\n gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffer);\\n xrFramebuffer = framebuffer;\\n }\\n }\\n function bindFramebuffer(target, framebuffer) {\\n if (framebuffer === null && xrFramebuffer !== null)\\n framebuffer = xrFramebuffer;\\n if (currentBoundFramebuffers[target] !== framebuffer) {\\n gl.bindFramebuffer(target, framebuffer);\\n currentBoundFramebuffers[target] = framebuffer;\\n if (isWebGL2) {\\n if (target === gl.DRAW_FRAMEBUFFER) {\\n currentBoundFramebuffers[gl.FRAMEBUFFER] = framebuffer;\\n }\\n if (target === gl.FRAMEBUFFER) {\\n currentBoundFramebuffers[gl.DRAW_FRAMEBUFFER] = framebuffer;\\n }\\n }\\n return true;\\n }\\n return false;\\n }\\n function useProgram(program) {\\n if (currentProgram !== program) {\\n gl.useProgram(program);\\n currentProgram = program;\\n return true;\\n }\\n return false;\\n }\\n const equationToGL = {\\n [AddEquation]: gl.FUNC_ADD,\\n [SubtractEquation]: gl.FUNC_SUBTRACT,\\n [ReverseSubtractEquation]: gl.FUNC_REVERSE_SUBTRACT\\n };\\n if (isWebGL2) {\\n equationToGL[MinEquation] = gl.MIN;\\n equationToGL[MaxEquation] = gl.MAX;\\n } else {\\n const extension = extensions.get(\\\\\\\"EXT_blend_minmax\\\\\\\");\\n if (extension !== null) {\\n equationToGL[MinEquation] = extension.MIN_EXT;\\n equationToGL[MaxEquation] = extension.MAX_EXT;\\n }\\n }\\n const factorToGL = {\\n [ZeroFactor]: gl.ZERO,\\n [OneFactor]: gl.ONE,\\n [SrcColorFactor]: gl.SRC_COLOR,\\n [SrcAlphaFactor]: gl.SRC_ALPHA,\\n [SrcAlphaSaturateFactor]: gl.SRC_ALPHA_SATURATE,\\n [DstColorFactor]: gl.DST_COLOR,\\n [DstAlphaFactor]: gl.DST_ALPHA,\\n [OneMinusSrcColorFactor]: gl.ONE_MINUS_SRC_COLOR,\\n [OneMinusSrcAlphaFactor]: gl.ONE_MINUS_SRC_ALPHA,\\n [OneMinusDstColorFactor]: gl.ONE_MINUS_DST_COLOR,\\n [OneMinusDstAlphaFactor]: gl.ONE_MINUS_DST_ALPHA\\n };\\n function setBlending(blending, blendEquation, blendSrc, blendDst, blendEquationAlpha, blendSrcAlpha, blendDstAlpha, premultipliedAlpha) {\\n if (blending === NoBlending) {\\n if (currentBlendingEnabled === true) {\\n disable(gl.BLEND);\\n currentBlendingEnabled = false;\\n }\\n return;\\n }\\n if (currentBlendingEnabled === false) {\\n enable(gl.BLEND);\\n currentBlendingEnabled = true;\\n }\\n if (blending !== CustomBlending) {\\n if (blending !== currentBlending || premultipliedAlpha !== currentPremultipledAlpha) {\\n if (currentBlendEquation !== AddEquation || currentBlendEquationAlpha !== AddEquation) {\\n gl.blendEquation(gl.FUNC_ADD);\\n currentBlendEquation = AddEquation;\\n currentBlendEquationAlpha = AddEquation;\\n }\\n if (premultipliedAlpha) {\\n switch (blending) {\\n case NormalBlending:\\n gl.blendFuncSeparate(gl.ONE, gl.ONE_MINUS_SRC_ALPHA, gl.ONE, gl.ONE_MINUS_SRC_ALPHA);\\n break;\\n case AdditiveBlending:\\n gl.blendFunc(gl.ONE, gl.ONE);\\n break;\\n case SubtractiveBlending:\\n gl.blendFuncSeparate(gl.ZERO, gl.ZERO, gl.ONE_MINUS_SRC_COLOR, gl.ONE_MINUS_SRC_ALPHA);\\n break;\\n case MultiplyBlending:\\n gl.blendFuncSeparate(gl.ZERO, gl.SRC_COLOR, gl.ZERO, gl.SRC_ALPHA);\\n break;\\n default:\\n console.error(\\\\\\\"THREE.WebGLState: Invalid blending: \\\\\\\", blending);\\n break;\\n }\\n } else {\\n switch (blending) {\\n case NormalBlending:\\n gl.blendFuncSeparate(gl.SRC_ALPHA, gl.ONE_MINUS_SRC_ALPHA, gl.ONE, gl.ONE_MINUS_SRC_ALPHA);\\n break;\\n case AdditiveBlending:\\n gl.blendFunc(gl.SRC_ALPHA, gl.ONE);\\n break;\\n case SubtractiveBlending:\\n gl.blendFunc(gl.ZERO, gl.ONE_MINUS_SRC_COLOR);\\n break;\\n case MultiplyBlending:\\n gl.blendFunc(gl.ZERO, gl.SRC_COLOR);\\n break;\\n default:\\n console.error(\\\\\\\"THREE.WebGLState: Invalid blending: \\\\\\\", blending);\\n break;\\n }\\n }\\n currentBlendSrc = null;\\n currentBlendDst = null;\\n currentBlendSrcAlpha = null;\\n currentBlendDstAlpha = null;\\n currentBlending = blending;\\n currentPremultipledAlpha = premultipliedAlpha;\\n }\\n return;\\n }\\n blendEquationAlpha = blendEquationAlpha || blendEquation;\\n blendSrcAlpha = blendSrcAlpha || blendSrc;\\n blendDstAlpha = blendDstAlpha || blendDst;\\n if (blendEquation !== currentBlendEquation || blendEquationAlpha !== currentBlendEquationAlpha) {\\n gl.blendEquationSeparate(equationToGL[blendEquation], equationToGL[blendEquationAlpha]);\\n currentBlendEquation = blendEquation;\\n currentBlendEquationAlpha = blendEquationAlpha;\\n }\\n if (blendSrc !== currentBlendSrc || blendDst !== currentBlendDst || blendSrcAlpha !== currentBlendSrcAlpha || blendDstAlpha !== currentBlendDstAlpha) {\\n gl.blendFuncSeparate(factorToGL[blendSrc], factorToGL[blendDst], factorToGL[blendSrcAlpha], factorToGL[blendDstAlpha]);\\n currentBlendSrc = blendSrc;\\n currentBlendDst = blendDst;\\n currentBlendSrcAlpha = blendSrcAlpha;\\n currentBlendDstAlpha = blendDstAlpha;\\n }\\n currentBlending = blending;\\n currentPremultipledAlpha = null;\\n }\\n function setMaterial(material, frontFaceCW) {\\n material.side === DoubleSide ? disable(gl.CULL_FACE) : enable(gl.CULL_FACE);\\n let flipSided = material.side === BackSide;\\n if (frontFaceCW)\\n flipSided = !flipSided;\\n setFlipSided(flipSided);\\n material.blending === NormalBlending && material.transparent === false ? setBlending(NoBlending) : setBlending(material.blending, material.blendEquation, material.blendSrc, material.blendDst, material.blendEquationAlpha, material.blendSrcAlpha, material.blendDstAlpha, material.premultipliedAlpha);\\n depthBuffer.setFunc(material.depthFunc);\\n depthBuffer.setTest(material.depthTest);\\n depthBuffer.setMask(material.depthWrite);\\n colorBuffer.setMask(material.colorWrite);\\n const stencilWrite = material.stencilWrite;\\n stencilBuffer.setTest(stencilWrite);\\n if (stencilWrite) {\\n stencilBuffer.setMask(material.stencilWriteMask);\\n stencilBuffer.setFunc(material.stencilFunc, material.stencilRef, material.stencilFuncMask);\\n stencilBuffer.setOp(material.stencilFail, material.stencilZFail, material.stencilZPass);\\n }\\n setPolygonOffset(material.polygonOffset, material.polygonOffsetFactor, material.polygonOffsetUnits);\\n material.alphaToCoverage === true ? enable(gl.SAMPLE_ALPHA_TO_COVERAGE) : disable(gl.SAMPLE_ALPHA_TO_COVERAGE);\\n }\\n function setFlipSided(flipSided) {\\n if (currentFlipSided !== flipSided) {\\n if (flipSided) {\\n gl.frontFace(gl.CW);\\n } else {\\n gl.frontFace(gl.CCW);\\n }\\n currentFlipSided = flipSided;\\n }\\n }\\n function setCullFace(cullFace) {\\n if (cullFace !== CullFaceNone) {\\n enable(gl.CULL_FACE);\\n if (cullFace !== currentCullFace) {\\n if (cullFace === CullFaceBack) {\\n gl.cullFace(gl.BACK);\\n } else if (cullFace === CullFaceFront) {\\n gl.cullFace(gl.FRONT);\\n } else {\\n gl.cullFace(gl.FRONT_AND_BACK);\\n }\\n }\\n } else {\\n disable(gl.CULL_FACE);\\n }\\n currentCullFace = cullFace;\\n }\\n function setLineWidth(width) {\\n if (width !== currentLineWidth) {\\n if (lineWidthAvailable)\\n gl.lineWidth(width);\\n currentLineWidth = width;\\n }\\n }\\n function setPolygonOffset(polygonOffset, factor, units) {\\n if (polygonOffset) {\\n enable(gl.POLYGON_OFFSET_FILL);\\n if (currentPolygonOffsetFactor !== factor || currentPolygonOffsetUnits !== units) {\\n gl.polygonOffset(factor, units);\\n currentPolygonOffsetFactor = factor;\\n currentPolygonOffsetUnits = units;\\n }\\n } else {\\n disable(gl.POLYGON_OFFSET_FILL);\\n }\\n }\\n function setScissorTest(scissorTest) {\\n if (scissorTest) {\\n enable(gl.SCISSOR_TEST);\\n } else {\\n disable(gl.SCISSOR_TEST);\\n }\\n }\\n function activeTexture(webglSlot) {\\n if (webglSlot === void 0)\\n webglSlot = gl.TEXTURE0 + maxTextures - 1;\\n if (currentTextureSlot !== webglSlot) {\\n gl.activeTexture(webglSlot);\\n currentTextureSlot = webglSlot;\\n }\\n }\\n function bindTexture(webglType, webglTexture) {\\n if (currentTextureSlot === null) {\\n activeTexture();\\n }\\n let boundTexture = currentBoundTextures[currentTextureSlot];\\n if (boundTexture === void 0) {\\n boundTexture = {type: void 0, texture: void 0};\\n currentBoundTextures[currentTextureSlot] = boundTexture;\\n }\\n if (boundTexture.type !== webglType || boundTexture.texture !== webglTexture) {\\n gl.bindTexture(webglType, webglTexture || emptyTextures[webglType]);\\n boundTexture.type = webglType;\\n boundTexture.texture = webglTexture;\\n }\\n }\\n function unbindTexture() {\\n const boundTexture = currentBoundTextures[currentTextureSlot];\\n if (boundTexture !== void 0 && boundTexture.type !== void 0) {\\n gl.bindTexture(boundTexture.type, null);\\n boundTexture.type = void 0;\\n boundTexture.texture = void 0;\\n }\\n }\\n function compressedTexImage2D() {\\n try {\\n gl.compressedTexImage2D.apply(gl, arguments);\\n } catch (error) {\\n console.error(\\\\\\\"THREE.WebGLState:\\\\\\\", error);\\n }\\n }\\n function texImage2D() {\\n try {\\n gl.texImage2D.apply(gl, arguments);\\n } catch (error) {\\n console.error(\\\\\\\"THREE.WebGLState:\\\\\\\", error);\\n }\\n }\\n function texImage3D() {\\n try {\\n gl.texImage3D.apply(gl, arguments);\\n } catch (error) {\\n console.error(\\\\\\\"THREE.WebGLState:\\\\\\\", error);\\n }\\n }\\n function scissor(scissor2) {\\n if (currentScissor.equals(scissor2) === false) {\\n gl.scissor(scissor2.x, scissor2.y, scissor2.z, scissor2.w);\\n currentScissor.copy(scissor2);\\n }\\n }\\n function viewport(viewport2) {\\n if (currentViewport.equals(viewport2) === false) {\\n gl.viewport(viewport2.x, viewport2.y, viewport2.z, viewport2.w);\\n currentViewport.copy(viewport2);\\n }\\n }\\n function reset() {\\n gl.disable(gl.BLEND);\\n gl.disable(gl.CULL_FACE);\\n gl.disable(gl.DEPTH_TEST);\\n gl.disable(gl.POLYGON_OFFSET_FILL);\\n gl.disable(gl.SCISSOR_TEST);\\n gl.disable(gl.STENCIL_TEST);\\n gl.disable(gl.SAMPLE_ALPHA_TO_COVERAGE);\\n gl.blendEquation(gl.FUNC_ADD);\\n gl.blendFunc(gl.ONE, gl.ZERO);\\n gl.blendFuncSeparate(gl.ONE, gl.ZERO, gl.ONE, gl.ZERO);\\n gl.colorMask(true, true, true, true);\\n gl.clearColor(0, 0, 0, 0);\\n gl.depthMask(true);\\n gl.depthFunc(gl.LESS);\\n gl.clearDepth(1);\\n gl.stencilMask(4294967295);\\n gl.stencilFunc(gl.ALWAYS, 0, 4294967295);\\n gl.stencilOp(gl.KEEP, gl.KEEP, gl.KEEP);\\n gl.clearStencil(0);\\n gl.cullFace(gl.BACK);\\n gl.frontFace(gl.CCW);\\n gl.polygonOffset(0, 0);\\n gl.activeTexture(gl.TEXTURE0);\\n gl.bindFramebuffer(gl.FRAMEBUFFER, null);\\n if (isWebGL2 === true) {\\n gl.bindFramebuffer(gl.DRAW_FRAMEBUFFER, null);\\n gl.bindFramebuffer(gl.READ_FRAMEBUFFER, null);\\n }\\n gl.useProgram(null);\\n gl.lineWidth(1);\\n gl.scissor(0, 0, gl.canvas.width, gl.canvas.height);\\n gl.viewport(0, 0, gl.canvas.width, gl.canvas.height);\\n enabledCapabilities = {};\\n currentTextureSlot = null;\\n currentBoundTextures = {};\\n xrFramebuffer = null;\\n currentBoundFramebuffers = {};\\n currentProgram = null;\\n currentBlendingEnabled = false;\\n currentBlending = null;\\n currentBlendEquation = null;\\n currentBlendSrc = null;\\n currentBlendDst = null;\\n currentBlendEquationAlpha = null;\\n currentBlendSrcAlpha = null;\\n currentBlendDstAlpha = null;\\n currentPremultipledAlpha = false;\\n currentFlipSided = null;\\n currentCullFace = null;\\n currentLineWidth = null;\\n currentPolygonOffsetFactor = null;\\n currentPolygonOffsetUnits = null;\\n currentScissor.set(0, 0, gl.canvas.width, gl.canvas.height);\\n currentViewport.set(0, 0, gl.canvas.width, gl.canvas.height);\\n colorBuffer.reset();\\n depthBuffer.reset();\\n stencilBuffer.reset();\\n }\\n return {\\n buffers: {\\n color: colorBuffer,\\n depth: depthBuffer,\\n stencil: stencilBuffer\\n },\\n enable,\\n disable,\\n bindFramebuffer,\\n bindXRFramebuffer,\\n useProgram,\\n setBlending,\\n setMaterial,\\n setFlipSided,\\n setCullFace,\\n setLineWidth,\\n setPolygonOffset,\\n setScissorTest,\\n activeTexture,\\n bindTexture,\\n unbindTexture,\\n compressedTexImage2D,\\n texImage2D,\\n texImage3D,\\n scissor,\\n viewport,\\n reset\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLTextures.js\\nfunction WebGLTextures(_gl, extensions, state, properties, capabilities, utils, info) {\\n const isWebGL2 = capabilities.isWebGL2;\\n const maxTextures = capabilities.maxTextures;\\n const maxCubemapSize = capabilities.maxCubemapSize;\\n const maxTextureSize = capabilities.maxTextureSize;\\n const maxSamples = capabilities.maxSamples;\\n const _videoTextures = new WeakMap();\\n let _canvas2;\\n let useOffscreenCanvas = false;\\n try {\\n useOffscreenCanvas = typeof OffscreenCanvas !== \\\\\\\"undefined\\\\\\\" && new OffscreenCanvas(1, 1).getContext(\\\\\\\"2d\\\\\\\") !== null;\\n } catch (err) {\\n }\\n function createCanvas(width, height) {\\n return useOffscreenCanvas ? new OffscreenCanvas(width, height) : createElementNS(\\\\\\\"canvas\\\\\\\");\\n }\\n function resizeImage(image, needsPowerOfTwo, needsNewCanvas, maxSize) {\\n let scale = 1;\\n if (image.width > maxSize || image.height > maxSize) {\\n scale = maxSize / Math.max(image.width, image.height);\\n }\\n if (scale < 1 || needsPowerOfTwo === true) {\\n if (typeof HTMLImageElement !== \\\\\\\"undefined\\\\\\\" && image instanceof HTMLImageElement || typeof HTMLCanvasElement !== \\\\\\\"undefined\\\\\\\" && image instanceof HTMLCanvasElement || typeof ImageBitmap !== \\\\\\\"undefined\\\\\\\" && image instanceof ImageBitmap) {\\n const floor = needsPowerOfTwo ? floorPowerOfTwo : Math.floor;\\n const width = floor(scale * image.width);\\n const height = floor(scale * image.height);\\n if (_canvas2 === void 0)\\n _canvas2 = createCanvas(width, height);\\n const canvas = needsNewCanvas ? createCanvas(width, height) : _canvas2;\\n canvas.width = width;\\n canvas.height = height;\\n const context = canvas.getContext(\\\\\\\"2d\\\\\\\");\\n context.drawImage(image, 0, 0, width, height);\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Texture has been resized from (\\\\\\\" + image.width + \\\\\\\"x\\\\\\\" + image.height + \\\\\\\") to (\\\\\\\" + width + \\\\\\\"x\\\\\\\" + height + \\\\\\\").\\\\\\\");\\n return canvas;\\n } else {\\n if (\\\\\\\"data\\\\\\\" in image) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Image in DataTexture is too big (\\\\\\\" + image.width + \\\\\\\"x\\\\\\\" + image.height + \\\\\\\").\\\\\\\");\\n }\\n return image;\\n }\\n }\\n return image;\\n }\\n function isPowerOfTwo2(image) {\\n return isPowerOfTwo(image.width) && isPowerOfTwo(image.height);\\n }\\n function textureNeedsPowerOfTwo(texture) {\\n if (isWebGL2)\\n return false;\\n return texture.wrapS !== ClampToEdgeWrapping || texture.wrapT !== ClampToEdgeWrapping || texture.minFilter !== NearestFilter && texture.minFilter !== LinearFilter;\\n }\\n function textureNeedsGenerateMipmaps(texture, supportsMips) {\\n return texture.generateMipmaps && supportsMips && texture.minFilter !== NearestFilter && texture.minFilter !== LinearFilter;\\n }\\n function generateMipmap(target, texture, width, height, depth2 = 1) {\\n _gl.generateMipmap(target);\\n const textureProperties = properties.get(texture);\\n textureProperties.__maxMipLevel = Math.log2(Math.max(width, height, depth2));\\n }\\n function getInternalFormat(internalFormatName, glFormat, glType, encoding) {\\n if (isWebGL2 === false)\\n return glFormat;\\n if (internalFormatName !== null) {\\n if (_gl[internalFormatName] !== void 0)\\n return _gl[internalFormatName];\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Attempt to use non-existing WebGL internal format '\\\\\\\" + internalFormatName + \\\\\\\"'\\\\\\\");\\n }\\n let internalFormat = glFormat;\\n if (glFormat === _gl.RED) {\\n if (glType === _gl.FLOAT)\\n internalFormat = _gl.R32F;\\n if (glType === _gl.HALF_FLOAT)\\n internalFormat = _gl.R16F;\\n if (glType === _gl.UNSIGNED_BYTE)\\n internalFormat = _gl.R8;\\n }\\n if (glFormat === _gl.RGB) {\\n if (glType === _gl.FLOAT)\\n internalFormat = _gl.RGB32F;\\n if (glType === _gl.HALF_FLOAT)\\n internalFormat = _gl.RGB16F;\\n if (glType === _gl.UNSIGNED_BYTE)\\n internalFormat = _gl.RGB8;\\n }\\n if (glFormat === _gl.RGBA) {\\n if (glType === _gl.FLOAT)\\n internalFormat = _gl.RGBA32F;\\n if (glType === _gl.HALF_FLOAT)\\n internalFormat = _gl.RGBA16F;\\n if (glType === _gl.UNSIGNED_BYTE)\\n internalFormat = encoding === sRGBEncoding ? _gl.SRGB8_ALPHA8 : _gl.RGBA8;\\n }\\n if (internalFormat === _gl.R16F || internalFormat === _gl.R32F || internalFormat === _gl.RGBA16F || internalFormat === _gl.RGBA32F) {\\n extensions.get(\\\\\\\"EXT_color_buffer_float\\\\\\\");\\n }\\n return internalFormat;\\n }\\n function filterFallback(f) {\\n if (f === NearestFilter || f === NearestMipmapNearestFilter || f === NearestMipmapLinearFilter) {\\n return _gl.NEAREST;\\n }\\n return _gl.LINEAR;\\n }\\n function onTextureDispose(event) {\\n const texture = event.target;\\n texture.removeEventListener(\\\\\\\"dispose\\\\\\\", onTextureDispose);\\n deallocateTexture(texture);\\n if (texture.isVideoTexture) {\\n _videoTextures.delete(texture);\\n }\\n info.memory.textures--;\\n }\\n function onRenderTargetDispose(event) {\\n const renderTarget = event.target;\\n renderTarget.removeEventListener(\\\\\\\"dispose\\\\\\\", onRenderTargetDispose);\\n deallocateRenderTarget(renderTarget);\\n }\\n function deallocateTexture(texture) {\\n const textureProperties = properties.get(texture);\\n if (textureProperties.__webglInit === void 0)\\n return;\\n _gl.deleteTexture(textureProperties.__webglTexture);\\n properties.remove(texture);\\n }\\n function deallocateRenderTarget(renderTarget) {\\n const texture = renderTarget.texture;\\n const renderTargetProperties = properties.get(renderTarget);\\n const textureProperties = properties.get(texture);\\n if (!renderTarget)\\n return;\\n if (textureProperties.__webglTexture !== void 0) {\\n _gl.deleteTexture(textureProperties.__webglTexture);\\n info.memory.textures--;\\n }\\n if (renderTarget.depthTexture) {\\n renderTarget.depthTexture.dispose();\\n }\\n if (renderTarget.isWebGLCubeRenderTarget) {\\n for (let i = 0; i < 6; i++) {\\n _gl.deleteFramebuffer(renderTargetProperties.__webglFramebuffer[i]);\\n if (renderTargetProperties.__webglDepthbuffer)\\n _gl.deleteRenderbuffer(renderTargetProperties.__webglDepthbuffer[i]);\\n }\\n } else {\\n _gl.deleteFramebuffer(renderTargetProperties.__webglFramebuffer);\\n if (renderTargetProperties.__webglDepthbuffer)\\n _gl.deleteRenderbuffer(renderTargetProperties.__webglDepthbuffer);\\n if (renderTargetProperties.__webglMultisampledFramebuffer)\\n _gl.deleteFramebuffer(renderTargetProperties.__webglMultisampledFramebuffer);\\n if (renderTargetProperties.__webglColorRenderbuffer)\\n _gl.deleteRenderbuffer(renderTargetProperties.__webglColorRenderbuffer);\\n if (renderTargetProperties.__webglDepthRenderbuffer)\\n _gl.deleteRenderbuffer(renderTargetProperties.__webglDepthRenderbuffer);\\n }\\n if (renderTarget.isWebGLMultipleRenderTargets) {\\n for (let i = 0, il = texture.length; i < il; i++) {\\n const attachmentProperties = properties.get(texture[i]);\\n if (attachmentProperties.__webglTexture) {\\n _gl.deleteTexture(attachmentProperties.__webglTexture);\\n info.memory.textures--;\\n }\\n properties.remove(texture[i]);\\n }\\n }\\n properties.remove(texture);\\n properties.remove(renderTarget);\\n }\\n let textureUnits = 0;\\n function resetTextureUnits() {\\n textureUnits = 0;\\n }\\n function allocateTextureUnit() {\\n const textureUnit = textureUnits;\\n if (textureUnit >= maxTextures) {\\n console.warn(\\\\\\\"THREE.WebGLTextures: Trying to use \\\\\\\" + textureUnit + \\\\\\\" texture units while this GPU supports only \\\\\\\" + maxTextures);\\n }\\n textureUnits += 1;\\n return textureUnit;\\n }\\n function setTexture2D(texture, slot) {\\n const textureProperties = properties.get(texture);\\n if (texture.isVideoTexture)\\n updateVideoTexture(texture);\\n if (texture.version > 0 && textureProperties.__version !== texture.version) {\\n const image = texture.image;\\n if (image === void 0) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Texture marked for update but image is undefined\\\\\\\");\\n } else if (image.complete === false) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Texture marked for update but image is incomplete\\\\\\\");\\n } else {\\n uploadTexture(textureProperties, texture, slot);\\n return;\\n }\\n }\\n state.activeTexture(_gl.TEXTURE0 + slot);\\n state.bindTexture(_gl.TEXTURE_2D, textureProperties.__webglTexture);\\n }\\n function setTexture2DArray(texture, slot) {\\n const textureProperties = properties.get(texture);\\n if (texture.version > 0 && textureProperties.__version !== texture.version) {\\n uploadTexture(textureProperties, texture, slot);\\n return;\\n }\\n state.activeTexture(_gl.TEXTURE0 + slot);\\n state.bindTexture(_gl.TEXTURE_2D_ARRAY, textureProperties.__webglTexture);\\n }\\n function setTexture3D(texture, slot) {\\n const textureProperties = properties.get(texture);\\n if (texture.version > 0 && textureProperties.__version !== texture.version) {\\n uploadTexture(textureProperties, texture, slot);\\n return;\\n }\\n state.activeTexture(_gl.TEXTURE0 + slot);\\n state.bindTexture(_gl.TEXTURE_3D, textureProperties.__webglTexture);\\n }\\n function setTextureCube(texture, slot) {\\n const textureProperties = properties.get(texture);\\n if (texture.version > 0 && textureProperties.__version !== texture.version) {\\n uploadCubeTexture(textureProperties, texture, slot);\\n return;\\n }\\n state.activeTexture(_gl.TEXTURE0 + slot);\\n state.bindTexture(_gl.TEXTURE_CUBE_MAP, textureProperties.__webglTexture);\\n }\\n const wrappingToGL = {\\n [RepeatWrapping]: _gl.REPEAT,\\n [ClampToEdgeWrapping]: _gl.CLAMP_TO_EDGE,\\n [MirroredRepeatWrapping]: _gl.MIRRORED_REPEAT\\n };\\n const filterToGL = {\\n [NearestFilter]: _gl.NEAREST,\\n [NearestMipmapNearestFilter]: _gl.NEAREST_MIPMAP_NEAREST,\\n [NearestMipmapLinearFilter]: _gl.NEAREST_MIPMAP_LINEAR,\\n [LinearFilter]: _gl.LINEAR,\\n [LinearMipmapNearestFilter]: _gl.LINEAR_MIPMAP_NEAREST,\\n [LinearMipmapLinearFilter]: _gl.LINEAR_MIPMAP_LINEAR\\n };\\n function setTextureParameters(textureType, texture, supportsMips) {\\n if (supportsMips) {\\n _gl.texParameteri(textureType, _gl.TEXTURE_WRAP_S, wrappingToGL[texture.wrapS]);\\n _gl.texParameteri(textureType, _gl.TEXTURE_WRAP_T, wrappingToGL[texture.wrapT]);\\n if (textureType === _gl.TEXTURE_3D || textureType === _gl.TEXTURE_2D_ARRAY) {\\n _gl.texParameteri(textureType, _gl.TEXTURE_WRAP_R, wrappingToGL[texture.wrapR]);\\n }\\n _gl.texParameteri(textureType, _gl.TEXTURE_MAG_FILTER, filterToGL[texture.magFilter]);\\n _gl.texParameteri(textureType, _gl.TEXTURE_MIN_FILTER, filterToGL[texture.minFilter]);\\n } else {\\n _gl.texParameteri(textureType, _gl.TEXTURE_WRAP_S, _gl.CLAMP_TO_EDGE);\\n _gl.texParameteri(textureType, _gl.TEXTURE_WRAP_T, _gl.CLAMP_TO_EDGE);\\n if (textureType === _gl.TEXTURE_3D || textureType === _gl.TEXTURE_2D_ARRAY) {\\n _gl.texParameteri(textureType, _gl.TEXTURE_WRAP_R, _gl.CLAMP_TO_EDGE);\\n }\\n if (texture.wrapS !== ClampToEdgeWrapping || texture.wrapT !== ClampToEdgeWrapping) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Texture is not power of two. Texture.wrapS and Texture.wrapT should be set to THREE.ClampToEdgeWrapping.\\\\\\\");\\n }\\n _gl.texParameteri(textureType, _gl.TEXTURE_MAG_FILTER, filterFallback(texture.magFilter));\\n _gl.texParameteri(textureType, _gl.TEXTURE_MIN_FILTER, filterFallback(texture.minFilter));\\n if (texture.minFilter !== NearestFilter && texture.minFilter !== LinearFilter) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Texture is not power of two. Texture.minFilter should be set to THREE.NearestFilter or THREE.LinearFilter.\\\\\\\");\\n }\\n }\\n if (extensions.has(\\\\\\\"EXT_texture_filter_anisotropic\\\\\\\") === true) {\\n const extension = extensions.get(\\\\\\\"EXT_texture_filter_anisotropic\\\\\\\");\\n if (texture.type === FloatType && extensions.has(\\\\\\\"OES_texture_float_linear\\\\\\\") === false)\\n return;\\n if (isWebGL2 === false && (texture.type === HalfFloatType && extensions.has(\\\\\\\"OES_texture_half_float_linear\\\\\\\") === false))\\n return;\\n if (texture.anisotropy > 1 || properties.get(texture).__currentAnisotropy) {\\n _gl.texParameterf(textureType, extension.TEXTURE_MAX_ANISOTROPY_EXT, Math.min(texture.anisotropy, capabilities.getMaxAnisotropy()));\\n properties.get(texture).__currentAnisotropy = texture.anisotropy;\\n }\\n }\\n }\\n function initTexture(textureProperties, texture) {\\n if (textureProperties.__webglInit === void 0) {\\n textureProperties.__webglInit = true;\\n texture.addEventListener(\\\\\\\"dispose\\\\\\\", onTextureDispose);\\n textureProperties.__webglTexture = _gl.createTexture();\\n info.memory.textures++;\\n }\\n }\\n function uploadTexture(textureProperties, texture, slot) {\\n let textureType = _gl.TEXTURE_2D;\\n if (texture.isDataTexture2DArray)\\n textureType = _gl.TEXTURE_2D_ARRAY;\\n if (texture.isDataTexture3D)\\n textureType = _gl.TEXTURE_3D;\\n initTexture(textureProperties, texture);\\n state.activeTexture(_gl.TEXTURE0 + slot);\\n state.bindTexture(textureType, textureProperties.__webglTexture);\\n _gl.pixelStorei(_gl.UNPACK_FLIP_Y_WEBGL, texture.flipY);\\n _gl.pixelStorei(_gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, texture.premultiplyAlpha);\\n _gl.pixelStorei(_gl.UNPACK_ALIGNMENT, texture.unpackAlignment);\\n _gl.pixelStorei(_gl.UNPACK_COLORSPACE_CONVERSION_WEBGL, _gl.NONE);\\n const needsPowerOfTwo = textureNeedsPowerOfTwo(texture) && isPowerOfTwo2(texture.image) === false;\\n const image = resizeImage(texture.image, needsPowerOfTwo, false, maxTextureSize);\\n const supportsMips = isPowerOfTwo2(image) || isWebGL2, glFormat = utils.convert(texture.format);\\n let glType = utils.convert(texture.type), glInternalFormat = getInternalFormat(texture.internalFormat, glFormat, glType, texture.encoding);\\n setTextureParameters(textureType, texture, supportsMips);\\n let mipmap;\\n const mipmaps = texture.mipmaps;\\n if (texture.isDepthTexture) {\\n glInternalFormat = _gl.DEPTH_COMPONENT;\\n if (isWebGL2) {\\n if (texture.type === FloatType) {\\n glInternalFormat = _gl.DEPTH_COMPONENT32F;\\n } else if (texture.type === UnsignedIntType) {\\n glInternalFormat = _gl.DEPTH_COMPONENT24;\\n } else if (texture.type === UnsignedInt248Type) {\\n glInternalFormat = _gl.DEPTH24_STENCIL8;\\n } else {\\n glInternalFormat = _gl.DEPTH_COMPONENT16;\\n }\\n } else {\\n if (texture.type === FloatType) {\\n console.error(\\\\\\\"WebGLRenderer: Floating point depth texture requires WebGL2.\\\\\\\");\\n }\\n }\\n if (texture.format === DepthFormat && glInternalFormat === _gl.DEPTH_COMPONENT) {\\n if (texture.type !== UnsignedShortType && texture.type !== UnsignedIntType) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Use UnsignedShortType or UnsignedIntType for DepthFormat DepthTexture.\\\\\\\");\\n texture.type = UnsignedShortType;\\n glType = utils.convert(texture.type);\\n }\\n }\\n if (texture.format === DepthStencilFormat && glInternalFormat === _gl.DEPTH_COMPONENT) {\\n glInternalFormat = _gl.DEPTH_STENCIL;\\n if (texture.type !== UnsignedInt248Type) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Use UnsignedInt248Type for DepthStencilFormat DepthTexture.\\\\\\\");\\n texture.type = UnsignedInt248Type;\\n glType = utils.convert(texture.type);\\n }\\n }\\n state.texImage2D(_gl.TEXTURE_2D, 0, glInternalFormat, image.width, image.height, 0, glFormat, glType, null);\\n } else if (texture.isDataTexture) {\\n if (mipmaps.length > 0 && supportsMips) {\\n for (let i = 0, il = mipmaps.length; i < il; i++) {\\n mipmap = mipmaps[i];\\n state.texImage2D(_gl.TEXTURE_2D, i, glInternalFormat, mipmap.width, mipmap.height, 0, glFormat, glType, mipmap.data);\\n }\\n texture.generateMipmaps = false;\\n textureProperties.__maxMipLevel = mipmaps.length - 1;\\n } else {\\n state.texImage2D(_gl.TEXTURE_2D, 0, glInternalFormat, image.width, image.height, 0, glFormat, glType, image.data);\\n textureProperties.__maxMipLevel = 0;\\n }\\n } else if (texture.isCompressedTexture) {\\n for (let i = 0, il = mipmaps.length; i < il; i++) {\\n mipmap = mipmaps[i];\\n if (texture.format !== RGBAFormat && texture.format !== RGBFormat) {\\n if (glFormat !== null) {\\n state.compressedTexImage2D(_gl.TEXTURE_2D, i, glInternalFormat, mipmap.width, mipmap.height, 0, mipmap.data);\\n } else {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Attempt to load unsupported compressed texture format in .uploadTexture()\\\\\\\");\\n }\\n } else {\\n state.texImage2D(_gl.TEXTURE_2D, i, glInternalFormat, mipmap.width, mipmap.height, 0, glFormat, glType, mipmap.data);\\n }\\n }\\n textureProperties.__maxMipLevel = mipmaps.length - 1;\\n } else if (texture.isDataTexture2DArray) {\\n state.texImage3D(_gl.TEXTURE_2D_ARRAY, 0, glInternalFormat, image.width, image.height, image.depth, 0, glFormat, glType, image.data);\\n textureProperties.__maxMipLevel = 0;\\n } else if (texture.isDataTexture3D) {\\n state.texImage3D(_gl.TEXTURE_3D, 0, glInternalFormat, image.width, image.height, image.depth, 0, glFormat, glType, image.data);\\n textureProperties.__maxMipLevel = 0;\\n } else {\\n if (mipmaps.length > 0 && supportsMips) {\\n for (let i = 0, il = mipmaps.length; i < il; i++) {\\n mipmap = mipmaps[i];\\n state.texImage2D(_gl.TEXTURE_2D, i, glInternalFormat, glFormat, glType, mipmap);\\n }\\n texture.generateMipmaps = false;\\n textureProperties.__maxMipLevel = mipmaps.length - 1;\\n } else {\\n state.texImage2D(_gl.TEXTURE_2D, 0, glInternalFormat, glFormat, glType, image);\\n textureProperties.__maxMipLevel = 0;\\n }\\n }\\n if (textureNeedsGenerateMipmaps(texture, supportsMips)) {\\n generateMipmap(textureType, texture, image.width, image.height);\\n }\\n textureProperties.__version = texture.version;\\n if (texture.onUpdate)\\n texture.onUpdate(texture);\\n }\\n function uploadCubeTexture(textureProperties, texture, slot) {\\n if (texture.image.length !== 6)\\n return;\\n initTexture(textureProperties, texture);\\n state.activeTexture(_gl.TEXTURE0 + slot);\\n state.bindTexture(_gl.TEXTURE_CUBE_MAP, textureProperties.__webglTexture);\\n _gl.pixelStorei(_gl.UNPACK_FLIP_Y_WEBGL, texture.flipY);\\n _gl.pixelStorei(_gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, texture.premultiplyAlpha);\\n _gl.pixelStorei(_gl.UNPACK_ALIGNMENT, texture.unpackAlignment);\\n _gl.pixelStorei(_gl.UNPACK_COLORSPACE_CONVERSION_WEBGL, _gl.NONE);\\n const isCompressed = texture && (texture.isCompressedTexture || texture.image[0].isCompressedTexture);\\n const isDataTexture = texture.image[0] && texture.image[0].isDataTexture;\\n const cubeImage = [];\\n for (let i = 0; i < 6; i++) {\\n if (!isCompressed && !isDataTexture) {\\n cubeImage[i] = resizeImage(texture.image[i], false, true, maxCubemapSize);\\n } else {\\n cubeImage[i] = isDataTexture ? texture.image[i].image : texture.image[i];\\n }\\n }\\n const image = cubeImage[0], supportsMips = isPowerOfTwo2(image) || isWebGL2, glFormat = utils.convert(texture.format), glType = utils.convert(texture.type), glInternalFormat = getInternalFormat(texture.internalFormat, glFormat, glType, texture.encoding);\\n setTextureParameters(_gl.TEXTURE_CUBE_MAP, texture, supportsMips);\\n let mipmaps;\\n if (isCompressed) {\\n for (let i = 0; i < 6; i++) {\\n mipmaps = cubeImage[i].mipmaps;\\n for (let j = 0; j < mipmaps.length; j++) {\\n const mipmap = mipmaps[j];\\n if (texture.format !== RGBAFormat && texture.format !== RGBFormat) {\\n if (glFormat !== null) {\\n state.compressedTexImage2D(_gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, j, glInternalFormat, mipmap.width, mipmap.height, 0, mipmap.data);\\n } else {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Attempt to load unsupported compressed texture format in .setTextureCube()\\\\\\\");\\n }\\n } else {\\n state.texImage2D(_gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, j, glInternalFormat, mipmap.width, mipmap.height, 0, glFormat, glType, mipmap.data);\\n }\\n }\\n }\\n textureProperties.__maxMipLevel = mipmaps.length - 1;\\n } else {\\n mipmaps = texture.mipmaps;\\n for (let i = 0; i < 6; i++) {\\n if (isDataTexture) {\\n state.texImage2D(_gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, 0, glInternalFormat, cubeImage[i].width, cubeImage[i].height, 0, glFormat, glType, cubeImage[i].data);\\n for (let j = 0; j < mipmaps.length; j++) {\\n const mipmap = mipmaps[j];\\n const mipmapImage = mipmap.image[i].image;\\n state.texImage2D(_gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, j + 1, glInternalFormat, mipmapImage.width, mipmapImage.height, 0, glFormat, glType, mipmapImage.data);\\n }\\n } else {\\n state.texImage2D(_gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, 0, glInternalFormat, glFormat, glType, cubeImage[i]);\\n for (let j = 0; j < mipmaps.length; j++) {\\n const mipmap = mipmaps[j];\\n state.texImage2D(_gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, j + 1, glInternalFormat, glFormat, glType, mipmap.image[i]);\\n }\\n }\\n }\\n textureProperties.__maxMipLevel = mipmaps.length;\\n }\\n if (textureNeedsGenerateMipmaps(texture, supportsMips)) {\\n generateMipmap(_gl.TEXTURE_CUBE_MAP, texture, image.width, image.height);\\n }\\n textureProperties.__version = texture.version;\\n if (texture.onUpdate)\\n texture.onUpdate(texture);\\n }\\n function setupFrameBufferTexture(framebuffer, renderTarget, texture, attachment, textureTarget) {\\n const glFormat = utils.convert(texture.format);\\n const glType = utils.convert(texture.type);\\n const glInternalFormat = getInternalFormat(texture.internalFormat, glFormat, glType, texture.encoding);\\n if (textureTarget === _gl.TEXTURE_3D || textureTarget === _gl.TEXTURE_2D_ARRAY) {\\n state.texImage3D(textureTarget, 0, glInternalFormat, renderTarget.width, renderTarget.height, renderTarget.depth, 0, glFormat, glType, null);\\n } else {\\n state.texImage2D(textureTarget, 0, glInternalFormat, renderTarget.width, renderTarget.height, 0, glFormat, glType, null);\\n }\\n state.bindFramebuffer(_gl.FRAMEBUFFER, framebuffer);\\n _gl.framebufferTexture2D(_gl.FRAMEBUFFER, attachment, textureTarget, properties.get(texture).__webglTexture, 0);\\n state.bindFramebuffer(_gl.FRAMEBUFFER, null);\\n }\\n function setupRenderBufferStorage(renderbuffer, renderTarget, isMultisample) {\\n _gl.bindRenderbuffer(_gl.RENDERBUFFER, renderbuffer);\\n if (renderTarget.depthBuffer && !renderTarget.stencilBuffer) {\\n let glInternalFormat = _gl.DEPTH_COMPONENT16;\\n if (isMultisample) {\\n const depthTexture = renderTarget.depthTexture;\\n if (depthTexture && depthTexture.isDepthTexture) {\\n if (depthTexture.type === FloatType) {\\n glInternalFormat = _gl.DEPTH_COMPONENT32F;\\n } else if (depthTexture.type === UnsignedIntType) {\\n glInternalFormat = _gl.DEPTH_COMPONENT24;\\n }\\n }\\n const samples = getRenderTargetSamples(renderTarget);\\n _gl.renderbufferStorageMultisample(_gl.RENDERBUFFER, samples, glInternalFormat, renderTarget.width, renderTarget.height);\\n } else {\\n _gl.renderbufferStorage(_gl.RENDERBUFFER, glInternalFormat, renderTarget.width, renderTarget.height);\\n }\\n _gl.framebufferRenderbuffer(_gl.FRAMEBUFFER, _gl.DEPTH_ATTACHMENT, _gl.RENDERBUFFER, renderbuffer);\\n } else if (renderTarget.depthBuffer && renderTarget.stencilBuffer) {\\n if (isMultisample) {\\n const samples = getRenderTargetSamples(renderTarget);\\n _gl.renderbufferStorageMultisample(_gl.RENDERBUFFER, samples, _gl.DEPTH24_STENCIL8, renderTarget.width, renderTarget.height);\\n } else {\\n _gl.renderbufferStorage(_gl.RENDERBUFFER, _gl.DEPTH_STENCIL, renderTarget.width, renderTarget.height);\\n }\\n _gl.framebufferRenderbuffer(_gl.FRAMEBUFFER, _gl.DEPTH_STENCIL_ATTACHMENT, _gl.RENDERBUFFER, renderbuffer);\\n } else {\\n const texture = renderTarget.isWebGLMultipleRenderTargets === true ? renderTarget.texture[0] : renderTarget.texture;\\n const glFormat = utils.convert(texture.format);\\n const glType = utils.convert(texture.type);\\n const glInternalFormat = getInternalFormat(texture.internalFormat, glFormat, glType, texture.encoding);\\n if (isMultisample) {\\n const samples = getRenderTargetSamples(renderTarget);\\n _gl.renderbufferStorageMultisample(_gl.RENDERBUFFER, samples, glInternalFormat, renderTarget.width, renderTarget.height);\\n } else {\\n _gl.renderbufferStorage(_gl.RENDERBUFFER, glInternalFormat, renderTarget.width, renderTarget.height);\\n }\\n }\\n _gl.bindRenderbuffer(_gl.RENDERBUFFER, null);\\n }\\n function setupDepthTexture(framebuffer, renderTarget) {\\n const isCube = renderTarget && renderTarget.isWebGLCubeRenderTarget;\\n if (isCube)\\n throw new Error(\\\\\\\"Depth Texture with cube render targets is not supported\\\\\\\");\\n state.bindFramebuffer(_gl.FRAMEBUFFER, framebuffer);\\n if (!(renderTarget.depthTexture && renderTarget.depthTexture.isDepthTexture)) {\\n throw new Error(\\\\\\\"renderTarget.depthTexture must be an instance of THREE.DepthTexture\\\\\\\");\\n }\\n if (!properties.get(renderTarget.depthTexture).__webglTexture || renderTarget.depthTexture.image.width !== renderTarget.width || renderTarget.depthTexture.image.height !== renderTarget.height) {\\n renderTarget.depthTexture.image.width = renderTarget.width;\\n renderTarget.depthTexture.image.height = renderTarget.height;\\n renderTarget.depthTexture.needsUpdate = true;\\n }\\n setTexture2D(renderTarget.depthTexture, 0);\\n const webglDepthTexture = properties.get(renderTarget.depthTexture).__webglTexture;\\n if (renderTarget.depthTexture.format === DepthFormat) {\\n _gl.framebufferTexture2D(_gl.FRAMEBUFFER, _gl.DEPTH_ATTACHMENT, _gl.TEXTURE_2D, webglDepthTexture, 0);\\n } else if (renderTarget.depthTexture.format === DepthStencilFormat) {\\n _gl.framebufferTexture2D(_gl.FRAMEBUFFER, _gl.DEPTH_STENCIL_ATTACHMENT, _gl.TEXTURE_2D, webglDepthTexture, 0);\\n } else {\\n throw new Error(\\\\\\\"Unknown depthTexture format\\\\\\\");\\n }\\n }\\n function setupDepthRenderbuffer(renderTarget) {\\n const renderTargetProperties = properties.get(renderTarget);\\n const isCube = renderTarget.isWebGLCubeRenderTarget === true;\\n if (renderTarget.depthTexture) {\\n if (isCube)\\n throw new Error(\\\\\\\"target.depthTexture not supported in Cube render targets\\\\\\\");\\n setupDepthTexture(renderTargetProperties.__webglFramebuffer, renderTarget);\\n } else {\\n if (isCube) {\\n renderTargetProperties.__webglDepthbuffer = [];\\n for (let i = 0; i < 6; i++) {\\n state.bindFramebuffer(_gl.FRAMEBUFFER, renderTargetProperties.__webglFramebuffer[i]);\\n renderTargetProperties.__webglDepthbuffer[i] = _gl.createRenderbuffer();\\n setupRenderBufferStorage(renderTargetProperties.__webglDepthbuffer[i], renderTarget, false);\\n }\\n } else {\\n state.bindFramebuffer(_gl.FRAMEBUFFER, renderTargetProperties.__webglFramebuffer);\\n renderTargetProperties.__webglDepthbuffer = _gl.createRenderbuffer();\\n setupRenderBufferStorage(renderTargetProperties.__webglDepthbuffer, renderTarget, false);\\n }\\n }\\n state.bindFramebuffer(_gl.FRAMEBUFFER, null);\\n }\\n function setupRenderTarget(renderTarget) {\\n const texture = renderTarget.texture;\\n const renderTargetProperties = properties.get(renderTarget);\\n const textureProperties = properties.get(texture);\\n renderTarget.addEventListener(\\\\\\\"dispose\\\\\\\", onRenderTargetDispose);\\n if (renderTarget.isWebGLMultipleRenderTargets !== true) {\\n textureProperties.__webglTexture = _gl.createTexture();\\n textureProperties.__version = texture.version;\\n info.memory.textures++;\\n }\\n const isCube = renderTarget.isWebGLCubeRenderTarget === true;\\n const isMultipleRenderTargets = renderTarget.isWebGLMultipleRenderTargets === true;\\n const isMultisample = renderTarget.isWebGLMultisampleRenderTarget === true;\\n const isRenderTarget3D = texture.isDataTexture3D || texture.isDataTexture2DArray;\\n const supportsMips = isPowerOfTwo2(renderTarget) || isWebGL2;\\n if (isWebGL2 && texture.format === RGBFormat && (texture.type === FloatType || texture.type === HalfFloatType)) {\\n texture.format = RGBAFormat;\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Rendering to textures with RGB format is not supported. Using RGBA format instead.\\\\\\\");\\n }\\n if (isCube) {\\n renderTargetProperties.__webglFramebuffer = [];\\n for (let i = 0; i < 6; i++) {\\n renderTargetProperties.__webglFramebuffer[i] = _gl.createFramebuffer();\\n }\\n } else {\\n renderTargetProperties.__webglFramebuffer = _gl.createFramebuffer();\\n if (isMultipleRenderTargets) {\\n if (capabilities.drawBuffers) {\\n const textures = renderTarget.texture;\\n for (let i = 0, il = textures.length; i < il; i++) {\\n const attachmentProperties = properties.get(textures[i]);\\n if (attachmentProperties.__webglTexture === void 0) {\\n attachmentProperties.__webglTexture = _gl.createTexture();\\n info.memory.textures++;\\n }\\n }\\n } else {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: WebGLMultipleRenderTargets can only be used with WebGL2 or WEBGL_draw_buffers extension.\\\\\\\");\\n }\\n } else if (isMultisample) {\\n if (isWebGL2) {\\n renderTargetProperties.__webglMultisampledFramebuffer = _gl.createFramebuffer();\\n renderTargetProperties.__webglColorRenderbuffer = _gl.createRenderbuffer();\\n _gl.bindRenderbuffer(_gl.RENDERBUFFER, renderTargetProperties.__webglColorRenderbuffer);\\n const glFormat = utils.convert(texture.format);\\n const glType = utils.convert(texture.type);\\n const glInternalFormat = getInternalFormat(texture.internalFormat, glFormat, glType, texture.encoding);\\n const samples = getRenderTargetSamples(renderTarget);\\n _gl.renderbufferStorageMultisample(_gl.RENDERBUFFER, samples, glInternalFormat, renderTarget.width, renderTarget.height);\\n state.bindFramebuffer(_gl.FRAMEBUFFER, renderTargetProperties.__webglMultisampledFramebuffer);\\n _gl.framebufferRenderbuffer(_gl.FRAMEBUFFER, _gl.COLOR_ATTACHMENT0, _gl.RENDERBUFFER, renderTargetProperties.__webglColorRenderbuffer);\\n _gl.bindRenderbuffer(_gl.RENDERBUFFER, null);\\n if (renderTarget.depthBuffer) {\\n renderTargetProperties.__webglDepthRenderbuffer = _gl.createRenderbuffer();\\n setupRenderBufferStorage(renderTargetProperties.__webglDepthRenderbuffer, renderTarget, true);\\n }\\n state.bindFramebuffer(_gl.FRAMEBUFFER, null);\\n } else {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: WebGLMultisampleRenderTarget can only be used with WebGL2.\\\\\\\");\\n }\\n }\\n }\\n if (isCube) {\\n state.bindTexture(_gl.TEXTURE_CUBE_MAP, textureProperties.__webglTexture);\\n setTextureParameters(_gl.TEXTURE_CUBE_MAP, texture, supportsMips);\\n for (let i = 0; i < 6; i++) {\\n setupFrameBufferTexture(renderTargetProperties.__webglFramebuffer[i], renderTarget, texture, _gl.COLOR_ATTACHMENT0, _gl.TEXTURE_CUBE_MAP_POSITIVE_X + i);\\n }\\n if (textureNeedsGenerateMipmaps(texture, supportsMips)) {\\n generateMipmap(_gl.TEXTURE_CUBE_MAP, texture, renderTarget.width, renderTarget.height);\\n }\\n state.unbindTexture();\\n } else if (isMultipleRenderTargets) {\\n const textures = renderTarget.texture;\\n for (let i = 0, il = textures.length; i < il; i++) {\\n const attachment = textures[i];\\n const attachmentProperties = properties.get(attachment);\\n state.bindTexture(_gl.TEXTURE_2D, attachmentProperties.__webglTexture);\\n setTextureParameters(_gl.TEXTURE_2D, attachment, supportsMips);\\n setupFrameBufferTexture(renderTargetProperties.__webglFramebuffer, renderTarget, attachment, _gl.COLOR_ATTACHMENT0 + i, _gl.TEXTURE_2D);\\n if (textureNeedsGenerateMipmaps(attachment, supportsMips)) {\\n generateMipmap(_gl.TEXTURE_2D, attachment, renderTarget.width, renderTarget.height);\\n }\\n }\\n state.unbindTexture();\\n } else {\\n let glTextureType = _gl.TEXTURE_2D;\\n if (isRenderTarget3D) {\\n if (isWebGL2) {\\n const isTexture3D = texture.isDataTexture3D;\\n glTextureType = isTexture3D ? _gl.TEXTURE_3D : _gl.TEXTURE_2D_ARRAY;\\n } else {\\n console.warn(\\\\\\\"THREE.DataTexture3D and THREE.DataTexture2DArray only supported with WebGL2.\\\\\\\");\\n }\\n }\\n state.bindTexture(glTextureType, textureProperties.__webglTexture);\\n setTextureParameters(glTextureType, texture, supportsMips);\\n setupFrameBufferTexture(renderTargetProperties.__webglFramebuffer, renderTarget, texture, _gl.COLOR_ATTACHMENT0, glTextureType);\\n if (textureNeedsGenerateMipmaps(texture, supportsMips)) {\\n generateMipmap(glTextureType, texture, renderTarget.width, renderTarget.height, renderTarget.depth);\\n }\\n state.unbindTexture();\\n }\\n if (renderTarget.depthBuffer) {\\n setupDepthRenderbuffer(renderTarget);\\n }\\n }\\n function updateRenderTargetMipmap(renderTarget) {\\n const supportsMips = isPowerOfTwo2(renderTarget) || isWebGL2;\\n const textures = renderTarget.isWebGLMultipleRenderTargets === true ? renderTarget.texture : [renderTarget.texture];\\n for (let i = 0, il = textures.length; i < il; i++) {\\n const texture = textures[i];\\n if (textureNeedsGenerateMipmaps(texture, supportsMips)) {\\n const target = renderTarget.isWebGLCubeRenderTarget ? _gl.TEXTURE_CUBE_MAP : _gl.TEXTURE_2D;\\n const webglTexture = properties.get(texture).__webglTexture;\\n state.bindTexture(target, webglTexture);\\n generateMipmap(target, texture, renderTarget.width, renderTarget.height);\\n state.unbindTexture();\\n }\\n }\\n }\\n function updateMultisampleRenderTarget(renderTarget) {\\n if (renderTarget.isWebGLMultisampleRenderTarget) {\\n if (isWebGL2) {\\n const width = renderTarget.width;\\n const height = renderTarget.height;\\n let mask = _gl.COLOR_BUFFER_BIT;\\n if (renderTarget.depthBuffer)\\n mask |= _gl.DEPTH_BUFFER_BIT;\\n if (renderTarget.stencilBuffer)\\n mask |= _gl.STENCIL_BUFFER_BIT;\\n const renderTargetProperties = properties.get(renderTarget);\\n state.bindFramebuffer(_gl.READ_FRAMEBUFFER, renderTargetProperties.__webglMultisampledFramebuffer);\\n state.bindFramebuffer(_gl.DRAW_FRAMEBUFFER, renderTargetProperties.__webglFramebuffer);\\n _gl.blitFramebuffer(0, 0, width, height, 0, 0, width, height, mask, _gl.NEAREST);\\n state.bindFramebuffer(_gl.READ_FRAMEBUFFER, null);\\n state.bindFramebuffer(_gl.DRAW_FRAMEBUFFER, renderTargetProperties.__webglMultisampledFramebuffer);\\n } else {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: WebGLMultisampleRenderTarget can only be used with WebGL2.\\\\\\\");\\n }\\n }\\n }\\n function getRenderTargetSamples(renderTarget) {\\n return isWebGL2 && renderTarget.isWebGLMultisampleRenderTarget ? Math.min(maxSamples, renderTarget.samples) : 0;\\n }\\n function updateVideoTexture(texture) {\\n const frame = info.render.frame;\\n if (_videoTextures.get(texture) !== frame) {\\n _videoTextures.set(texture, frame);\\n texture.update();\\n }\\n }\\n let warnedTexture2D = false;\\n let warnedTextureCube = false;\\n function safeSetTexture2D(texture, slot) {\\n if (texture && texture.isWebGLRenderTarget) {\\n if (warnedTexture2D === false) {\\n console.warn(\\\\\\\"THREE.WebGLTextures.safeSetTexture2D: don't use render targets as textures. Use their .texture property instead.\\\\\\\");\\n warnedTexture2D = true;\\n }\\n texture = texture.texture;\\n }\\n setTexture2D(texture, slot);\\n }\\n function safeSetTextureCube(texture, slot) {\\n if (texture && texture.isWebGLCubeRenderTarget) {\\n if (warnedTextureCube === false) {\\n console.warn(\\\\\\\"THREE.WebGLTextures.safeSetTextureCube: don't use cube render targets as textures. Use their .texture property instead.\\\\\\\");\\n warnedTextureCube = true;\\n }\\n texture = texture.texture;\\n }\\n setTextureCube(texture, slot);\\n }\\n this.allocateTextureUnit = allocateTextureUnit;\\n this.resetTextureUnits = resetTextureUnits;\\n this.setTexture2D = setTexture2D;\\n this.setTexture2DArray = setTexture2DArray;\\n this.setTexture3D = setTexture3D;\\n this.setTextureCube = setTextureCube;\\n this.setupRenderTarget = setupRenderTarget;\\n this.updateRenderTargetMipmap = updateRenderTargetMipmap;\\n this.updateMultisampleRenderTarget = updateMultisampleRenderTarget;\\n this.safeSetTexture2D = safeSetTexture2D;\\n this.safeSetTextureCube = safeSetTextureCube;\\n}\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLUtils.js\\nfunction WebGLUtils(gl, extensions, capabilities) {\\n const isWebGL2 = capabilities.isWebGL2;\\n function convert(p) {\\n let extension;\\n if (p === UnsignedByteType)\\n return gl.UNSIGNED_BYTE;\\n if (p === UnsignedShort4444Type)\\n return gl.UNSIGNED_SHORT_4_4_4_4;\\n if (p === UnsignedShort5551Type)\\n return gl.UNSIGNED_SHORT_5_5_5_1;\\n if (p === UnsignedShort565Type)\\n return gl.UNSIGNED_SHORT_5_6_5;\\n if (p === ByteType)\\n return gl.BYTE;\\n if (p === ShortType)\\n return gl.SHORT;\\n if (p === UnsignedShortType)\\n return gl.UNSIGNED_SHORT;\\n if (p === IntType)\\n return gl.INT;\\n if (p === UnsignedIntType)\\n return gl.UNSIGNED_INT;\\n if (p === FloatType)\\n return gl.FLOAT;\\n if (p === HalfFloatType) {\\n if (isWebGL2)\\n return gl.HALF_FLOAT;\\n extension = extensions.get(\\\\\\\"OES_texture_half_float\\\\\\\");\\n if (extension !== null) {\\n return extension.HALF_FLOAT_OES;\\n } else {\\n return null;\\n }\\n }\\n if (p === AlphaFormat)\\n return gl.ALPHA;\\n if (p === RGBFormat)\\n return gl.RGB;\\n if (p === RGBAFormat)\\n return gl.RGBA;\\n if (p === LuminanceFormat)\\n return gl.LUMINANCE;\\n if (p === LuminanceAlphaFormat)\\n return gl.LUMINANCE_ALPHA;\\n if (p === DepthFormat)\\n return gl.DEPTH_COMPONENT;\\n if (p === DepthStencilFormat)\\n return gl.DEPTH_STENCIL;\\n if (p === RedFormat)\\n return gl.RED;\\n if (p === RedIntegerFormat)\\n return gl.RED_INTEGER;\\n if (p === RGFormat)\\n return gl.RG;\\n if (p === RGIntegerFormat)\\n return gl.RG_INTEGER;\\n if (p === RGBIntegerFormat)\\n return gl.RGB_INTEGER;\\n if (p === RGBAIntegerFormat)\\n return gl.RGBA_INTEGER;\\n if (p === RGB_S3TC_DXT1_Format || p === RGBA_S3TC_DXT1_Format || p === RGBA_S3TC_DXT3_Format || p === RGBA_S3TC_DXT5_Format) {\\n extension = extensions.get(\\\\\\\"WEBGL_compressed_texture_s3tc\\\\\\\");\\n if (extension !== null) {\\n if (p === RGB_S3TC_DXT1_Format)\\n return extension.COMPRESSED_RGB_S3TC_DXT1_EXT;\\n if (p === RGBA_S3TC_DXT1_Format)\\n return extension.COMPRESSED_RGBA_S3TC_DXT1_EXT;\\n if (p === RGBA_S3TC_DXT3_Format)\\n return extension.COMPRESSED_RGBA_S3TC_DXT3_EXT;\\n if (p === RGBA_S3TC_DXT5_Format)\\n return extension.COMPRESSED_RGBA_S3TC_DXT5_EXT;\\n } else {\\n return null;\\n }\\n }\\n if (p === RGB_PVRTC_4BPPV1_Format || p === RGB_PVRTC_2BPPV1_Format || p === RGBA_PVRTC_4BPPV1_Format || p === RGBA_PVRTC_2BPPV1_Format) {\\n extension = extensions.get(\\\\\\\"WEBGL_compressed_texture_pvrtc\\\\\\\");\\n if (extension !== null) {\\n if (p === RGB_PVRTC_4BPPV1_Format)\\n return extension.COMPRESSED_RGB_PVRTC_4BPPV1_IMG;\\n if (p === RGB_PVRTC_2BPPV1_Format)\\n return extension.COMPRESSED_RGB_PVRTC_2BPPV1_IMG;\\n if (p === RGBA_PVRTC_4BPPV1_Format)\\n return extension.COMPRESSED_RGBA_PVRTC_4BPPV1_IMG;\\n if (p === RGBA_PVRTC_2BPPV1_Format)\\n return extension.COMPRESSED_RGBA_PVRTC_2BPPV1_IMG;\\n } else {\\n return null;\\n }\\n }\\n if (p === RGB_ETC1_Format) {\\n extension = extensions.get(\\\\\\\"WEBGL_compressed_texture_etc1\\\\\\\");\\n if (extension !== null) {\\n return extension.COMPRESSED_RGB_ETC1_WEBGL;\\n } else {\\n return null;\\n }\\n }\\n if (p === RGB_ETC2_Format || p === RGBA_ETC2_EAC_Format) {\\n extension = extensions.get(\\\\\\\"WEBGL_compressed_texture_etc\\\\\\\");\\n if (extension !== null) {\\n if (p === RGB_ETC2_Format)\\n return extension.COMPRESSED_RGB8_ETC2;\\n if (p === RGBA_ETC2_EAC_Format)\\n return extension.COMPRESSED_RGBA8_ETC2_EAC;\\n }\\n }\\n if (p === RGBA_ASTC_4x4_Format || p === RGBA_ASTC_5x4_Format || p === RGBA_ASTC_5x5_Format || p === RGBA_ASTC_6x5_Format || p === RGBA_ASTC_6x6_Format || p === RGBA_ASTC_8x5_Format || p === RGBA_ASTC_8x6_Format || p === RGBA_ASTC_8x8_Format || p === RGBA_ASTC_10x5_Format || p === RGBA_ASTC_10x6_Format || p === RGBA_ASTC_10x8_Format || p === RGBA_ASTC_10x10_Format || p === RGBA_ASTC_12x10_Format || p === RGBA_ASTC_12x12_Format || p === SRGB8_ALPHA8_ASTC_4x4_Format || p === SRGB8_ALPHA8_ASTC_5x4_Format || p === SRGB8_ALPHA8_ASTC_5x5_Format || p === SRGB8_ALPHA8_ASTC_6x5_Format || p === SRGB8_ALPHA8_ASTC_6x6_Format || p === SRGB8_ALPHA8_ASTC_8x5_Format || p === SRGB8_ALPHA8_ASTC_8x6_Format || p === SRGB8_ALPHA8_ASTC_8x8_Format || p === SRGB8_ALPHA8_ASTC_10x5_Format || p === SRGB8_ALPHA8_ASTC_10x6_Format || p === SRGB8_ALPHA8_ASTC_10x8_Format || p === SRGB8_ALPHA8_ASTC_10x10_Format || p === SRGB8_ALPHA8_ASTC_12x10_Format || p === SRGB8_ALPHA8_ASTC_12x12_Format) {\\n extension = extensions.get(\\\\\\\"WEBGL_compressed_texture_astc\\\\\\\");\\n if (extension !== null) {\\n return p;\\n } else {\\n return null;\\n }\\n }\\n if (p === RGBA_BPTC_Format) {\\n extension = extensions.get(\\\\\\\"EXT_texture_compression_bptc\\\\\\\");\\n if (extension !== null) {\\n return p;\\n } else {\\n return null;\\n }\\n }\\n if (p === UnsignedInt248Type) {\\n if (isWebGL2)\\n return gl.UNSIGNED_INT_24_8;\\n extension = extensions.get(\\\\\\\"WEBGL_depth_texture\\\\\\\");\\n if (extension !== null) {\\n return extension.UNSIGNED_INT_24_8_WEBGL;\\n } else {\\n return null;\\n }\\n }\\n }\\n return {convert};\\n}\\n\\n// ../../../node_modules/three/src/cameras/ArrayCamera.js\\nvar ArrayCamera = class extends PerspectiveCamera {\\n constructor(array = []) {\\n super();\\n this.cameras = array;\\n }\\n};\\nArrayCamera.prototype.isArrayCamera = true;\\n\\n// ../../../node_modules/three/src/objects/Group.js\\nvar Group = class extends Object3D {\\n constructor() {\\n super();\\n this.type = \\\\\\\"Group\\\\\\\";\\n }\\n};\\nGroup.prototype.isGroup = true;\\n\\n// ../../../node_modules/three/src/renderers/webxr/WebXRController.js\\nvar _moveEvent = {type: \\\\\\\"move\\\\\\\"};\\nvar WebXRController = class {\\n constructor() {\\n this._targetRay = null;\\n this._grip = null;\\n this._hand = null;\\n }\\n getHandSpace() {\\n if (this._hand === null) {\\n this._hand = new Group();\\n this._hand.matrixAutoUpdate = false;\\n this._hand.visible = false;\\n this._hand.joints = {};\\n this._hand.inputState = {pinching: false};\\n }\\n return this._hand;\\n }\\n getTargetRaySpace() {\\n if (this._targetRay === null) {\\n this._targetRay = new Group();\\n this._targetRay.matrixAutoUpdate = false;\\n this._targetRay.visible = false;\\n this._targetRay.hasLinearVelocity = false;\\n this._targetRay.linearVelocity = new Vector3();\\n this._targetRay.hasAngularVelocity = false;\\n this._targetRay.angularVelocity = new Vector3();\\n }\\n return this._targetRay;\\n }\\n getGripSpace() {\\n if (this._grip === null) {\\n this._grip = new Group();\\n this._grip.matrixAutoUpdate = false;\\n this._grip.visible = false;\\n this._grip.hasLinearVelocity = false;\\n this._grip.linearVelocity = new Vector3();\\n this._grip.hasAngularVelocity = false;\\n this._grip.angularVelocity = new Vector3();\\n }\\n return this._grip;\\n }\\n dispatchEvent(event) {\\n if (this._targetRay !== null) {\\n this._targetRay.dispatchEvent(event);\\n }\\n if (this._grip !== null) {\\n this._grip.dispatchEvent(event);\\n }\\n if (this._hand !== null) {\\n this._hand.dispatchEvent(event);\\n }\\n return this;\\n }\\n disconnect(inputSource) {\\n this.dispatchEvent({type: \\\\\\\"disconnected\\\\\\\", data: inputSource});\\n if (this._targetRay !== null) {\\n this._targetRay.visible = false;\\n }\\n if (this._grip !== null) {\\n this._grip.visible = false;\\n }\\n if (this._hand !== null) {\\n this._hand.visible = false;\\n }\\n return this;\\n }\\n update(inputSource, frame, referenceSpace) {\\n let inputPose = null;\\n let gripPose = null;\\n let handPose = null;\\n const targetRay = this._targetRay;\\n const grip = this._grip;\\n const hand = this._hand;\\n if (inputSource && frame.session.visibilityState !== \\\\\\\"visible-blurred\\\\\\\") {\\n if (targetRay !== null) {\\n inputPose = frame.getPose(inputSource.targetRaySpace, referenceSpace);\\n if (inputPose !== null) {\\n targetRay.matrix.fromArray(inputPose.transform.matrix);\\n targetRay.matrix.decompose(targetRay.position, targetRay.rotation, targetRay.scale);\\n if (inputPose.linearVelocity) {\\n targetRay.hasLinearVelocity = true;\\n targetRay.linearVelocity.copy(inputPose.linearVelocity);\\n } else {\\n targetRay.hasLinearVelocity = false;\\n }\\n if (inputPose.angularVelocity) {\\n targetRay.hasAngularVelocity = true;\\n targetRay.angularVelocity.copy(inputPose.angularVelocity);\\n } else {\\n targetRay.hasAngularVelocity = false;\\n }\\n this.dispatchEvent(_moveEvent);\\n }\\n }\\n if (hand && inputSource.hand) {\\n handPose = true;\\n for (const inputjoint of inputSource.hand.values()) {\\n const jointPose = frame.getJointPose(inputjoint, referenceSpace);\\n if (hand.joints[inputjoint.jointName] === void 0) {\\n const joint2 = new Group();\\n joint2.matrixAutoUpdate = false;\\n joint2.visible = false;\\n hand.joints[inputjoint.jointName] = joint2;\\n hand.add(joint2);\\n }\\n const joint = hand.joints[inputjoint.jointName];\\n if (jointPose !== null) {\\n joint.matrix.fromArray(jointPose.transform.matrix);\\n joint.matrix.decompose(joint.position, joint.rotation, joint.scale);\\n joint.jointRadius = jointPose.radius;\\n }\\n joint.visible = jointPose !== null;\\n }\\n const indexTip = hand.joints[\\\\\\\"index-finger-tip\\\\\\\"];\\n const thumbTip = hand.joints[\\\\\\\"thumb-tip\\\\\\\"];\\n const distance = indexTip.position.distanceTo(thumbTip.position);\\n const distanceToPinch = 0.02;\\n const threshold = 5e-3;\\n if (hand.inputState.pinching && distance > distanceToPinch + threshold) {\\n hand.inputState.pinching = false;\\n this.dispatchEvent({\\n type: \\\\\\\"pinchend\\\\\\\",\\n handedness: inputSource.handedness,\\n target: this\\n });\\n } else if (!hand.inputState.pinching && distance <= distanceToPinch - threshold) {\\n hand.inputState.pinching = true;\\n this.dispatchEvent({\\n type: \\\\\\\"pinchstart\\\\\\\",\\n handedness: inputSource.handedness,\\n target: this\\n });\\n }\\n } else {\\n if (grip !== null && inputSource.gripSpace) {\\n gripPose = frame.getPose(inputSource.gripSpace, referenceSpace);\\n if (gripPose !== null) {\\n grip.matrix.fromArray(gripPose.transform.matrix);\\n grip.matrix.decompose(grip.position, grip.rotation, grip.scale);\\n if (gripPose.linearVelocity) {\\n grip.hasLinearVelocity = true;\\n grip.linearVelocity.copy(gripPose.linearVelocity);\\n } else {\\n grip.hasLinearVelocity = false;\\n }\\n if (gripPose.angularVelocity) {\\n grip.hasAngularVelocity = true;\\n grip.angularVelocity.copy(gripPose.angularVelocity);\\n } else {\\n grip.hasAngularVelocity = false;\\n }\\n }\\n }\\n }\\n }\\n if (targetRay !== null) {\\n targetRay.visible = inputPose !== null;\\n }\\n if (grip !== null) {\\n grip.visible = gripPose !== null;\\n }\\n if (hand !== null) {\\n hand.visible = handPose !== null;\\n }\\n return this;\\n }\\n};\\n\\n// ../../../node_modules/three/src/renderers/webxr/WebXRManager.js\\nvar WebXRManager = class extends EventDispatcher {\\n constructor(renderer, gl) {\\n super();\\n const scope = this;\\n const state = renderer.state;\\n let session = null;\\n let framebufferScaleFactor = 1;\\n let referenceSpace = null;\\n let referenceSpaceType = \\\\\\\"local-floor\\\\\\\";\\n let pose = null;\\n let glBinding = null;\\n let glFramebuffer = null;\\n let glProjLayer = null;\\n let glBaseLayer = null;\\n let isMultisample = false;\\n let glMultisampledFramebuffer = null;\\n let glColorRenderbuffer = null;\\n let glDepthRenderbuffer = null;\\n let xrFrame = null;\\n let depthStyle = null;\\n let clearStyle = null;\\n const controllers = [];\\n const inputSourcesMap = new Map();\\n const cameraL = new PerspectiveCamera();\\n cameraL.layers.enable(1);\\n cameraL.viewport = new Vector4();\\n const cameraR = new PerspectiveCamera();\\n cameraR.layers.enable(2);\\n cameraR.viewport = new Vector4();\\n const cameras = [cameraL, cameraR];\\n const cameraVR = new ArrayCamera();\\n cameraVR.layers.enable(1);\\n cameraVR.layers.enable(2);\\n let _currentDepthNear = null;\\n let _currentDepthFar = null;\\n this.cameraAutoUpdate = true;\\n this.enabled = false;\\n this.isPresenting = false;\\n this.getController = function(index) {\\n let controller = controllers[index];\\n if (controller === void 0) {\\n controller = new WebXRController();\\n controllers[index] = controller;\\n }\\n return controller.getTargetRaySpace();\\n };\\n this.getControllerGrip = function(index) {\\n let controller = controllers[index];\\n if (controller === void 0) {\\n controller = new WebXRController();\\n controllers[index] = controller;\\n }\\n return controller.getGripSpace();\\n };\\n this.getHand = function(index) {\\n let controller = controllers[index];\\n if (controller === void 0) {\\n controller = new WebXRController();\\n controllers[index] = controller;\\n }\\n return controller.getHandSpace();\\n };\\n function onSessionEvent(event) {\\n const controller = inputSourcesMap.get(event.inputSource);\\n if (controller) {\\n controller.dispatchEvent({type: event.type, data: event.inputSource});\\n }\\n }\\n function onSessionEnd() {\\n inputSourcesMap.forEach(function(controller, inputSource) {\\n controller.disconnect(inputSource);\\n });\\n inputSourcesMap.clear();\\n _currentDepthNear = null;\\n _currentDepthFar = null;\\n state.bindXRFramebuffer(null);\\n renderer.setRenderTarget(renderer.getRenderTarget());\\n if (glFramebuffer)\\n gl.deleteFramebuffer(glFramebuffer);\\n if (glMultisampledFramebuffer)\\n gl.deleteFramebuffer(glMultisampledFramebuffer);\\n if (glColorRenderbuffer)\\n gl.deleteRenderbuffer(glColorRenderbuffer);\\n if (glDepthRenderbuffer)\\n gl.deleteRenderbuffer(glDepthRenderbuffer);\\n glFramebuffer = null;\\n glMultisampledFramebuffer = null;\\n glColorRenderbuffer = null;\\n glDepthRenderbuffer = null;\\n glBaseLayer = null;\\n glProjLayer = null;\\n glBinding = null;\\n session = null;\\n animation.stop();\\n scope.isPresenting = false;\\n scope.dispatchEvent({type: \\\\\\\"sessionend\\\\\\\"});\\n }\\n this.setFramebufferScaleFactor = function(value) {\\n framebufferScaleFactor = value;\\n if (scope.isPresenting === true) {\\n console.warn(\\\\\\\"THREE.WebXRManager: Cannot change framebuffer scale while presenting.\\\\\\\");\\n }\\n };\\n this.setReferenceSpaceType = function(value) {\\n referenceSpaceType = value;\\n if (scope.isPresenting === true) {\\n console.warn(\\\\\\\"THREE.WebXRManager: Cannot change reference space type while presenting.\\\\\\\");\\n }\\n };\\n this.getReferenceSpace = function() {\\n return referenceSpace;\\n };\\n this.getBaseLayer = function() {\\n return glProjLayer !== null ? glProjLayer : glBaseLayer;\\n };\\n this.getBinding = function() {\\n return glBinding;\\n };\\n this.getFrame = function() {\\n return xrFrame;\\n };\\n this.getSession = function() {\\n return session;\\n };\\n this.setSession = async function(value) {\\n session = value;\\n if (session !== null) {\\n session.addEventListener(\\\\\\\"select\\\\\\\", onSessionEvent);\\n session.addEventListener(\\\\\\\"selectstart\\\\\\\", onSessionEvent);\\n session.addEventListener(\\\\\\\"selectend\\\\\\\", onSessionEvent);\\n session.addEventListener(\\\\\\\"squeeze\\\\\\\", onSessionEvent);\\n session.addEventListener(\\\\\\\"squeezestart\\\\\\\", onSessionEvent);\\n session.addEventListener(\\\\\\\"squeezeend\\\\\\\", onSessionEvent);\\n session.addEventListener(\\\\\\\"end\\\\\\\", onSessionEnd);\\n session.addEventListener(\\\\\\\"inputsourceschange\\\\\\\", onInputSourcesChange);\\n const attributes = gl.getContextAttributes();\\n if (attributes.xrCompatible !== true) {\\n await gl.makeXRCompatible();\\n }\\n if (session.renderState.layers === void 0) {\\n const layerInit = {\\n antialias: attributes.antialias,\\n alpha: attributes.alpha,\\n depth: attributes.depth,\\n stencil: attributes.stencil,\\n framebufferScaleFactor\\n };\\n glBaseLayer = new XRWebGLLayer(session, gl, layerInit);\\n session.updateRenderState({baseLayer: glBaseLayer});\\n } else if (gl instanceof WebGLRenderingContext) {\\n const layerInit = {\\n antialias: true,\\n alpha: attributes.alpha,\\n depth: attributes.depth,\\n stencil: attributes.stencil,\\n framebufferScaleFactor\\n };\\n glBaseLayer = new XRWebGLLayer(session, gl, layerInit);\\n session.updateRenderState({layers: [glBaseLayer]});\\n } else {\\n isMultisample = attributes.antialias;\\n let depthFormat = null;\\n if (attributes.depth) {\\n clearStyle = gl.DEPTH_BUFFER_BIT;\\n if (attributes.stencil)\\n clearStyle |= gl.STENCIL_BUFFER_BIT;\\n depthStyle = attributes.stencil ? gl.DEPTH_STENCIL_ATTACHMENT : gl.DEPTH_ATTACHMENT;\\n depthFormat = attributes.stencil ? gl.DEPTH24_STENCIL8 : gl.DEPTH_COMPONENT24;\\n }\\n const projectionlayerInit = {\\n colorFormat: attributes.alpha ? gl.RGBA8 : gl.RGB8,\\n depthFormat,\\n scaleFactor: framebufferScaleFactor\\n };\\n glBinding = new XRWebGLBinding(session, gl);\\n glProjLayer = glBinding.createProjectionLayer(projectionlayerInit);\\n glFramebuffer = gl.createFramebuffer();\\n session.updateRenderState({layers: [glProjLayer]});\\n if (isMultisample) {\\n glMultisampledFramebuffer = gl.createFramebuffer();\\n glColorRenderbuffer = gl.createRenderbuffer();\\n gl.bindRenderbuffer(gl.RENDERBUFFER, glColorRenderbuffer);\\n gl.renderbufferStorageMultisample(gl.RENDERBUFFER, 4, gl.RGBA8, glProjLayer.textureWidth, glProjLayer.textureHeight);\\n state.bindFramebuffer(gl.FRAMEBUFFER, glMultisampledFramebuffer);\\n gl.framebufferRenderbuffer(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.RENDERBUFFER, glColorRenderbuffer);\\n gl.bindRenderbuffer(gl.RENDERBUFFER, null);\\n if (depthFormat !== null) {\\n glDepthRenderbuffer = gl.createRenderbuffer();\\n gl.bindRenderbuffer(gl.RENDERBUFFER, glDepthRenderbuffer);\\n gl.renderbufferStorageMultisample(gl.RENDERBUFFER, 4, depthFormat, glProjLayer.textureWidth, glProjLayer.textureHeight);\\n gl.framebufferRenderbuffer(gl.FRAMEBUFFER, depthStyle, gl.RENDERBUFFER, glDepthRenderbuffer);\\n gl.bindRenderbuffer(gl.RENDERBUFFER, null);\\n }\\n state.bindFramebuffer(gl.FRAMEBUFFER, null);\\n }\\n }\\n referenceSpace = await session.requestReferenceSpace(referenceSpaceType);\\n animation.setContext(session);\\n animation.start();\\n scope.isPresenting = true;\\n scope.dispatchEvent({type: \\\\\\\"sessionstart\\\\\\\"});\\n }\\n };\\n function onInputSourcesChange(event) {\\n const inputSources = session.inputSources;\\n for (let i = 0; i < controllers.length; i++) {\\n inputSourcesMap.set(inputSources[i], controllers[i]);\\n }\\n for (let i = 0; i < event.removed.length; i++) {\\n const inputSource = event.removed[i];\\n const controller = inputSourcesMap.get(inputSource);\\n if (controller) {\\n controller.dispatchEvent({type: \\\\\\\"disconnected\\\\\\\", data: inputSource});\\n inputSourcesMap.delete(inputSource);\\n }\\n }\\n for (let i = 0; i < event.added.length; i++) {\\n const inputSource = event.added[i];\\n const controller = inputSourcesMap.get(inputSource);\\n if (controller) {\\n controller.dispatchEvent({type: \\\\\\\"connected\\\\\\\", data: inputSource});\\n }\\n }\\n }\\n const cameraLPos = new Vector3();\\n const cameraRPos = new Vector3();\\n function setProjectionFromUnion(camera, cameraL2, cameraR2) {\\n cameraLPos.setFromMatrixPosition(cameraL2.matrixWorld);\\n cameraRPos.setFromMatrixPosition(cameraR2.matrixWorld);\\n const ipd = cameraLPos.distanceTo(cameraRPos);\\n const projL = cameraL2.projectionMatrix.elements;\\n const projR = cameraR2.projectionMatrix.elements;\\n const near = projL[14] / (projL[10] - 1);\\n const far = projL[14] / (projL[10] + 1);\\n const topFov = (projL[9] + 1) / projL[5];\\n const bottomFov = (projL[9] - 1) / projL[5];\\n const leftFov = (projL[8] - 1) / projL[0];\\n const rightFov = (projR[8] + 1) / projR[0];\\n const left = near * leftFov;\\n const right = near * rightFov;\\n const zOffset = ipd / (-leftFov + rightFov);\\n const xOffset = zOffset * -leftFov;\\n cameraL2.matrixWorld.decompose(camera.position, camera.quaternion, camera.scale);\\n camera.translateX(xOffset);\\n camera.translateZ(zOffset);\\n camera.matrixWorld.compose(camera.position, camera.quaternion, camera.scale);\\n camera.matrixWorldInverse.copy(camera.matrixWorld).invert();\\n const near2 = near + zOffset;\\n const far2 = far + zOffset;\\n const left2 = left - xOffset;\\n const right2 = right + (ipd - xOffset);\\n const top2 = topFov * far / far2 * near2;\\n const bottom2 = bottomFov * far / far2 * near2;\\n camera.projectionMatrix.makePerspective(left2, right2, top2, bottom2, near2, far2);\\n }\\n function updateCamera(camera, parent) {\\n if (parent === null) {\\n camera.matrixWorld.copy(camera.matrix);\\n } else {\\n camera.matrixWorld.multiplyMatrices(parent.matrixWorld, camera.matrix);\\n }\\n camera.matrixWorldInverse.copy(camera.matrixWorld).invert();\\n }\\n this.updateCamera = function(camera) {\\n if (session === null)\\n return;\\n cameraVR.near = cameraR.near = cameraL.near = camera.near;\\n cameraVR.far = cameraR.far = cameraL.far = camera.far;\\n if (_currentDepthNear !== cameraVR.near || _currentDepthFar !== cameraVR.far) {\\n session.updateRenderState({\\n depthNear: cameraVR.near,\\n depthFar: cameraVR.far\\n });\\n _currentDepthNear = cameraVR.near;\\n _currentDepthFar = cameraVR.far;\\n }\\n const parent = camera.parent;\\n const cameras2 = cameraVR.cameras;\\n updateCamera(cameraVR, parent);\\n for (let i = 0; i < cameras2.length; i++) {\\n updateCamera(cameras2[i], parent);\\n }\\n cameraVR.matrixWorld.decompose(cameraVR.position, cameraVR.quaternion, cameraVR.scale);\\n camera.position.copy(cameraVR.position);\\n camera.quaternion.copy(cameraVR.quaternion);\\n camera.scale.copy(cameraVR.scale);\\n camera.matrix.copy(cameraVR.matrix);\\n camera.matrixWorld.copy(cameraVR.matrixWorld);\\n const children = camera.children;\\n for (let i = 0, l = children.length; i < l; i++) {\\n children[i].updateMatrixWorld(true);\\n }\\n if (cameras2.length === 2) {\\n setProjectionFromUnion(cameraVR, cameraL, cameraR);\\n } else {\\n cameraVR.projectionMatrix.copy(cameraL.projectionMatrix);\\n }\\n };\\n this.getCamera = function() {\\n return cameraVR;\\n };\\n this.getFoveation = function() {\\n if (glProjLayer !== null) {\\n return glProjLayer.fixedFoveation;\\n }\\n if (glBaseLayer !== null) {\\n return glBaseLayer.fixedFoveation;\\n }\\n return void 0;\\n };\\n this.setFoveation = function(foveation) {\\n if (glProjLayer !== null) {\\n glProjLayer.fixedFoveation = foveation;\\n }\\n if (glBaseLayer !== null && glBaseLayer.fixedFoveation !== void 0) {\\n glBaseLayer.fixedFoveation = foveation;\\n }\\n };\\n let onAnimationFrameCallback = null;\\n function onAnimationFrame(time, frame) {\\n pose = frame.getViewerPose(referenceSpace);\\n xrFrame = frame;\\n if (pose !== null) {\\n const views = pose.views;\\n if (glBaseLayer !== null) {\\n state.bindXRFramebuffer(glBaseLayer.framebuffer);\\n }\\n let cameraVRNeedsUpdate = false;\\n if (views.length !== cameraVR.cameras.length) {\\n cameraVR.cameras.length = 0;\\n cameraVRNeedsUpdate = true;\\n }\\n for (let i = 0; i < views.length; i++) {\\n const view = views[i];\\n let viewport = null;\\n if (glBaseLayer !== null) {\\n viewport = glBaseLayer.getViewport(view);\\n } else {\\n const glSubImage = glBinding.getViewSubImage(glProjLayer, view);\\n state.bindXRFramebuffer(glFramebuffer);\\n if (glSubImage.depthStencilTexture !== void 0) {\\n gl.framebufferTexture2D(gl.FRAMEBUFFER, depthStyle, gl.TEXTURE_2D, glSubImage.depthStencilTexture, 0);\\n }\\n gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, glSubImage.colorTexture, 0);\\n viewport = glSubImage.viewport;\\n }\\n const camera = cameras[i];\\n camera.matrix.fromArray(view.transform.matrix);\\n camera.projectionMatrix.fromArray(view.projectionMatrix);\\n camera.viewport.set(viewport.x, viewport.y, viewport.width, viewport.height);\\n if (i === 0) {\\n cameraVR.matrix.copy(camera.matrix);\\n }\\n if (cameraVRNeedsUpdate === true) {\\n cameraVR.cameras.push(camera);\\n }\\n }\\n if (isMultisample) {\\n state.bindXRFramebuffer(glMultisampledFramebuffer);\\n if (clearStyle !== null)\\n gl.clear(clearStyle);\\n }\\n }\\n const inputSources = session.inputSources;\\n for (let i = 0; i < controllers.length; i++) {\\n const controller = controllers[i];\\n const inputSource = inputSources[i];\\n controller.update(inputSource, frame, referenceSpace);\\n }\\n if (onAnimationFrameCallback)\\n onAnimationFrameCallback(time, frame);\\n if (isMultisample) {\\n const width = glProjLayer.textureWidth;\\n const height = glProjLayer.textureHeight;\\n state.bindFramebuffer(gl.READ_FRAMEBUFFER, glMultisampledFramebuffer);\\n state.bindFramebuffer(gl.DRAW_FRAMEBUFFER, glFramebuffer);\\n gl.invalidateFramebuffer(gl.READ_FRAMEBUFFER, [depthStyle]);\\n gl.invalidateFramebuffer(gl.DRAW_FRAMEBUFFER, [depthStyle]);\\n gl.blitFramebuffer(0, 0, width, height, 0, 0, width, height, gl.COLOR_BUFFER_BIT, gl.NEAREST);\\n gl.invalidateFramebuffer(gl.READ_FRAMEBUFFER, [gl.COLOR_ATTACHMENT0]);\\n state.bindFramebuffer(gl.READ_FRAMEBUFFER, null);\\n state.bindFramebuffer(gl.DRAW_FRAMEBUFFER, null);\\n state.bindFramebuffer(gl.FRAMEBUFFER, glMultisampledFramebuffer);\\n }\\n xrFrame = null;\\n }\\n const animation = new WebGLAnimation();\\n animation.setAnimationLoop(onAnimationFrame);\\n this.setAnimationLoop = function(callback) {\\n onAnimationFrameCallback = callback;\\n };\\n this.dispose = function() {\\n };\\n }\\n};\\n\\n// ../../../node_modules/three/src/renderers/webgl/WebGLMaterials.js\\nfunction WebGLMaterials(properties) {\\n function refreshFogUniforms(uniforms, fog) {\\n uniforms.fogColor.value.copy(fog.color);\\n if (fog.isFog) {\\n uniforms.fogNear.value = fog.near;\\n uniforms.fogFar.value = fog.far;\\n } else if (fog.isFogExp2) {\\n uniforms.fogDensity.value = fog.density;\\n }\\n }\\n function refreshMaterialUniforms(uniforms, material, pixelRatio, height, transmissionRenderTarget) {\\n if (material.isMeshBasicMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n } else if (material.isMeshLambertMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n refreshUniformsLambert(uniforms, material);\\n } else if (material.isMeshToonMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n refreshUniformsToon(uniforms, material);\\n } else if (material.isMeshPhongMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n refreshUniformsPhong(uniforms, material);\\n } else if (material.isMeshStandardMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n if (material.isMeshPhysicalMaterial) {\\n refreshUniformsPhysical(uniforms, material, transmissionRenderTarget);\\n } else {\\n refreshUniformsStandard(uniforms, material);\\n }\\n } else if (material.isMeshMatcapMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n refreshUniformsMatcap(uniforms, material);\\n } else if (material.isMeshDepthMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n refreshUniformsDepth(uniforms, material);\\n } else if (material.isMeshDistanceMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n refreshUniformsDistance(uniforms, material);\\n } else if (material.isMeshNormalMaterial) {\\n refreshUniformsCommon(uniforms, material);\\n refreshUniformsNormal(uniforms, material);\\n } else if (material.isLineBasicMaterial) {\\n refreshUniformsLine(uniforms, material);\\n if (material.isLineDashedMaterial) {\\n refreshUniformsDash(uniforms, material);\\n }\\n } else if (material.isPointsMaterial) {\\n refreshUniformsPoints(uniforms, material, pixelRatio, height);\\n } else if (material.isSpriteMaterial) {\\n refreshUniformsSprites(uniforms, material);\\n } else if (material.isShadowMaterial) {\\n uniforms.color.value.copy(material.color);\\n uniforms.opacity.value = material.opacity;\\n } else if (material.isShaderMaterial) {\\n material.uniformsNeedUpdate = false;\\n }\\n }\\n function refreshUniformsCommon(uniforms, material) {\\n uniforms.opacity.value = material.opacity;\\n if (material.color) {\\n uniforms.diffuse.value.copy(material.color);\\n }\\n if (material.emissive) {\\n uniforms.emissive.value.copy(material.emissive).multiplyScalar(material.emissiveIntensity);\\n }\\n if (material.map) {\\n uniforms.map.value = material.map;\\n }\\n if (material.alphaMap) {\\n uniforms.alphaMap.value = material.alphaMap;\\n }\\n if (material.specularMap) {\\n uniforms.specularMap.value = material.specularMap;\\n }\\n if (material.alphaTest > 0) {\\n uniforms.alphaTest.value = material.alphaTest;\\n }\\n const envMap = properties.get(material).envMap;\\n if (envMap) {\\n uniforms.envMap.value = envMap;\\n uniforms.flipEnvMap.value = envMap.isCubeTexture && envMap.isRenderTargetTexture === false ? -1 : 1;\\n uniforms.reflectivity.value = material.reflectivity;\\n uniforms.ior.value = material.ior;\\n uniforms.refractionRatio.value = material.refractionRatio;\\n const maxMipLevel = properties.get(envMap).__maxMipLevel;\\n if (maxMipLevel !== void 0) {\\n uniforms.maxMipLevel.value = maxMipLevel;\\n }\\n }\\n if (material.lightMap) {\\n uniforms.lightMap.value = material.lightMap;\\n uniforms.lightMapIntensity.value = material.lightMapIntensity;\\n }\\n if (material.aoMap) {\\n uniforms.aoMap.value = material.aoMap;\\n uniforms.aoMapIntensity.value = material.aoMapIntensity;\\n }\\n let uvScaleMap;\\n if (material.map) {\\n uvScaleMap = material.map;\\n } else if (material.specularMap) {\\n uvScaleMap = material.specularMap;\\n } else if (material.displacementMap) {\\n uvScaleMap = material.displacementMap;\\n } else if (material.normalMap) {\\n uvScaleMap = material.normalMap;\\n } else if (material.bumpMap) {\\n uvScaleMap = material.bumpMap;\\n } else if (material.roughnessMap) {\\n uvScaleMap = material.roughnessMap;\\n } else if (material.metalnessMap) {\\n uvScaleMap = material.metalnessMap;\\n } else if (material.alphaMap) {\\n uvScaleMap = material.alphaMap;\\n } else if (material.emissiveMap) {\\n uvScaleMap = material.emissiveMap;\\n } else if (material.clearcoatMap) {\\n uvScaleMap = material.clearcoatMap;\\n } else if (material.clearcoatNormalMap) {\\n uvScaleMap = material.clearcoatNormalMap;\\n } else if (material.clearcoatRoughnessMap) {\\n uvScaleMap = material.clearcoatRoughnessMap;\\n } else if (material.specularIntensityMap) {\\n uvScaleMap = material.specularIntensityMap;\\n } else if (material.specularTintMap) {\\n uvScaleMap = material.specularTintMap;\\n } else if (material.transmissionMap) {\\n uvScaleMap = material.transmissionMap;\\n } else if (material.thicknessMap) {\\n uvScaleMap = material.thicknessMap;\\n }\\n if (uvScaleMap !== void 0) {\\n if (uvScaleMap.isWebGLRenderTarget) {\\n uvScaleMap = uvScaleMap.texture;\\n }\\n if (uvScaleMap.matrixAutoUpdate === true) {\\n uvScaleMap.updateMatrix();\\n }\\n uniforms.uvTransform.value.copy(uvScaleMap.matrix);\\n }\\n let uv2ScaleMap;\\n if (material.aoMap) {\\n uv2ScaleMap = material.aoMap;\\n } else if (material.lightMap) {\\n uv2ScaleMap = material.lightMap;\\n }\\n if (uv2ScaleMap !== void 0) {\\n if (uv2ScaleMap.isWebGLRenderTarget) {\\n uv2ScaleMap = uv2ScaleMap.texture;\\n }\\n if (uv2ScaleMap.matrixAutoUpdate === true) {\\n uv2ScaleMap.updateMatrix();\\n }\\n uniforms.uv2Transform.value.copy(uv2ScaleMap.matrix);\\n }\\n }\\n function refreshUniformsLine(uniforms, material) {\\n uniforms.diffuse.value.copy(material.color);\\n uniforms.opacity.value = material.opacity;\\n }\\n function refreshUniformsDash(uniforms, material) {\\n uniforms.dashSize.value = material.dashSize;\\n uniforms.totalSize.value = material.dashSize + material.gapSize;\\n uniforms.scale.value = material.scale;\\n }\\n function refreshUniformsPoints(uniforms, material, pixelRatio, height) {\\n uniforms.diffuse.value.copy(material.color);\\n uniforms.opacity.value = material.opacity;\\n uniforms.size.value = material.size * pixelRatio;\\n uniforms.scale.value = height * 0.5;\\n if (material.map) {\\n uniforms.map.value = material.map;\\n }\\n if (material.alphaMap) {\\n uniforms.alphaMap.value = material.alphaMap;\\n }\\n if (material.alphaTest > 0) {\\n uniforms.alphaTest.value = material.alphaTest;\\n }\\n let uvScaleMap;\\n if (material.map) {\\n uvScaleMap = material.map;\\n } else if (material.alphaMap) {\\n uvScaleMap = material.alphaMap;\\n }\\n if (uvScaleMap !== void 0) {\\n if (uvScaleMap.matrixAutoUpdate === true) {\\n uvScaleMap.updateMatrix();\\n }\\n uniforms.uvTransform.value.copy(uvScaleMap.matrix);\\n }\\n }\\n function refreshUniformsSprites(uniforms, material) {\\n uniforms.diffuse.value.copy(material.color);\\n uniforms.opacity.value = material.opacity;\\n uniforms.rotation.value = material.rotation;\\n if (material.map) {\\n uniforms.map.value = material.map;\\n }\\n if (material.alphaMap) {\\n uniforms.alphaMap.value = material.alphaMap;\\n }\\n if (material.alphaTest > 0) {\\n uniforms.alphaTest.value = material.alphaTest;\\n }\\n let uvScaleMap;\\n if (material.map) {\\n uvScaleMap = material.map;\\n } else if (material.alphaMap) {\\n uvScaleMap = material.alphaMap;\\n }\\n if (uvScaleMap !== void 0) {\\n if (uvScaleMap.matrixAutoUpdate === true) {\\n uvScaleMap.updateMatrix();\\n }\\n uniforms.uvTransform.value.copy(uvScaleMap.matrix);\\n }\\n }\\n function refreshUniformsLambert(uniforms, material) {\\n if (material.emissiveMap) {\\n uniforms.emissiveMap.value = material.emissiveMap;\\n }\\n }\\n function refreshUniformsPhong(uniforms, material) {\\n uniforms.specular.value.copy(material.specular);\\n uniforms.shininess.value = Math.max(material.shininess, 1e-4);\\n if (material.emissiveMap) {\\n uniforms.emissiveMap.value = material.emissiveMap;\\n }\\n if (material.bumpMap) {\\n uniforms.bumpMap.value = material.bumpMap;\\n uniforms.bumpScale.value = material.bumpScale;\\n if (material.side === BackSide)\\n uniforms.bumpScale.value *= -1;\\n }\\n if (material.normalMap) {\\n uniforms.normalMap.value = material.normalMap;\\n uniforms.normalScale.value.copy(material.normalScale);\\n if (material.side === BackSide)\\n uniforms.normalScale.value.negate();\\n }\\n if (material.displacementMap) {\\n uniforms.displacementMap.value = material.displacementMap;\\n uniforms.displacementScale.value = material.displacementScale;\\n uniforms.displacementBias.value = material.displacementBias;\\n }\\n }\\n function refreshUniformsToon(uniforms, material) {\\n if (material.gradientMap) {\\n uniforms.gradientMap.value = material.gradientMap;\\n }\\n if (material.emissiveMap) {\\n uniforms.emissiveMap.value = material.emissiveMap;\\n }\\n if (material.bumpMap) {\\n uniforms.bumpMap.value = material.bumpMap;\\n uniforms.bumpScale.value = material.bumpScale;\\n if (material.side === BackSide)\\n uniforms.bumpScale.value *= -1;\\n }\\n if (material.normalMap) {\\n uniforms.normalMap.value = material.normalMap;\\n uniforms.normalScale.value.copy(material.normalScale);\\n if (material.side === BackSide)\\n uniforms.normalScale.value.negate();\\n }\\n if (material.displacementMap) {\\n uniforms.displacementMap.value = material.displacementMap;\\n uniforms.displacementScale.value = material.displacementScale;\\n uniforms.displacementBias.value = material.displacementBias;\\n }\\n }\\n function refreshUniformsStandard(uniforms, material) {\\n uniforms.roughness.value = material.roughness;\\n uniforms.metalness.value = material.metalness;\\n if (material.roughnessMap) {\\n uniforms.roughnessMap.value = material.roughnessMap;\\n }\\n if (material.metalnessMap) {\\n uniforms.metalnessMap.value = material.metalnessMap;\\n }\\n if (material.emissiveMap) {\\n uniforms.emissiveMap.value = material.emissiveMap;\\n }\\n if (material.bumpMap) {\\n uniforms.bumpMap.value = material.bumpMap;\\n uniforms.bumpScale.value = material.bumpScale;\\n if (material.side === BackSide)\\n uniforms.bumpScale.value *= -1;\\n }\\n if (material.normalMap) {\\n uniforms.normalMap.value = material.normalMap;\\n uniforms.normalScale.value.copy(material.normalScale);\\n if (material.side === BackSide)\\n uniforms.normalScale.value.negate();\\n }\\n if (material.displacementMap) {\\n uniforms.displacementMap.value = material.displacementMap;\\n uniforms.displacementScale.value = material.displacementScale;\\n uniforms.displacementBias.value = material.displacementBias;\\n }\\n const envMap = properties.get(material).envMap;\\n if (envMap) {\\n uniforms.envMapIntensity.value = material.envMapIntensity;\\n }\\n }\\n function refreshUniformsPhysical(uniforms, material, transmissionRenderTarget) {\\n refreshUniformsStandard(uniforms, material);\\n uniforms.ior.value = material.ior;\\n if (material.sheen > 0) {\\n uniforms.sheenTint.value.copy(material.sheenTint).multiplyScalar(material.sheen);\\n uniforms.sheenRoughness.value = material.sheenRoughness;\\n }\\n if (material.clearcoat > 0) {\\n uniforms.clearcoat.value = material.clearcoat;\\n uniforms.clearcoatRoughness.value = material.clearcoatRoughness;\\n if (material.clearcoatMap) {\\n uniforms.clearcoatMap.value = material.clearcoatMap;\\n }\\n if (material.clearcoatRoughnessMap) {\\n uniforms.clearcoatRoughnessMap.value = material.clearcoatRoughnessMap;\\n }\\n if (material.clearcoatNormalMap) {\\n uniforms.clearcoatNormalScale.value.copy(material.clearcoatNormalScale);\\n uniforms.clearcoatNormalMap.value = material.clearcoatNormalMap;\\n if (material.side === BackSide) {\\n uniforms.clearcoatNormalScale.value.negate();\\n }\\n }\\n }\\n if (material.transmission > 0) {\\n uniforms.transmission.value = material.transmission;\\n uniforms.transmissionSamplerMap.value = transmissionRenderTarget.texture;\\n uniforms.transmissionSamplerSize.value.set(transmissionRenderTarget.width, transmissionRenderTarget.height);\\n if (material.transmissionMap) {\\n uniforms.transmissionMap.value = material.transmissionMap;\\n }\\n uniforms.thickness.value = material.thickness;\\n if (material.thicknessMap) {\\n uniforms.thicknessMap.value = material.thicknessMap;\\n }\\n uniforms.attenuationDistance.value = material.attenuationDistance;\\n uniforms.attenuationTint.value.copy(material.attenuationTint);\\n }\\n uniforms.specularIntensity.value = material.specularIntensity;\\n uniforms.specularTint.value.copy(material.specularTint);\\n if (material.specularIntensityMap) {\\n uniforms.specularIntensityMap.value = material.specularIntensityMap;\\n }\\n if (material.specularTintMap) {\\n uniforms.specularTintMap.value = material.specularTintMap;\\n }\\n }\\n function refreshUniformsMatcap(uniforms, material) {\\n if (material.matcap) {\\n uniforms.matcap.value = material.matcap;\\n }\\n if (material.bumpMap) {\\n uniforms.bumpMap.value = material.bumpMap;\\n uniforms.bumpScale.value = material.bumpScale;\\n if (material.side === BackSide)\\n uniforms.bumpScale.value *= -1;\\n }\\n if (material.normalMap) {\\n uniforms.normalMap.value = material.normalMap;\\n uniforms.normalScale.value.copy(material.normalScale);\\n if (material.side === BackSide)\\n uniforms.normalScale.value.negate();\\n }\\n if (material.displacementMap) {\\n uniforms.displacementMap.value = material.displacementMap;\\n uniforms.displacementScale.value = material.displacementScale;\\n uniforms.displacementBias.value = material.displacementBias;\\n }\\n }\\n function refreshUniformsDepth(uniforms, material) {\\n if (material.displacementMap) {\\n uniforms.displacementMap.value = material.displacementMap;\\n uniforms.displacementScale.value = material.displacementScale;\\n uniforms.displacementBias.value = material.displacementBias;\\n }\\n }\\n function refreshUniformsDistance(uniforms, material) {\\n if (material.displacementMap) {\\n uniforms.displacementMap.value = material.displacementMap;\\n uniforms.displacementScale.value = material.displacementScale;\\n uniforms.displacementBias.value = material.displacementBias;\\n }\\n uniforms.referencePosition.value.copy(material.referencePosition);\\n uniforms.nearDistance.value = material.nearDistance;\\n uniforms.farDistance.value = material.farDistance;\\n }\\n function refreshUniformsNormal(uniforms, material) {\\n if (material.bumpMap) {\\n uniforms.bumpMap.value = material.bumpMap;\\n uniforms.bumpScale.value = material.bumpScale;\\n if (material.side === BackSide)\\n uniforms.bumpScale.value *= -1;\\n }\\n if (material.normalMap) {\\n uniforms.normalMap.value = material.normalMap;\\n uniforms.normalScale.value.copy(material.normalScale);\\n if (material.side === BackSide)\\n uniforms.normalScale.value.negate();\\n }\\n if (material.displacementMap) {\\n uniforms.displacementMap.value = material.displacementMap;\\n uniforms.displacementScale.value = material.displacementScale;\\n uniforms.displacementBias.value = material.displacementBias;\\n }\\n }\\n return {\\n refreshFogUniforms,\\n refreshMaterialUniforms\\n };\\n}\\n\\n// ../../../node_modules/three/src/renderers/WebGLRenderer.js\\nfunction createCanvasElement() {\\n const canvas = createElementNS(\\\\\\\"canvas\\\\\\\");\\n canvas.style.display = \\\\\\\"block\\\\\\\";\\n return canvas;\\n}\\nfunction WebGLRenderer(parameters = {}) {\\n const _canvas2 = parameters.canvas !== void 0 ? parameters.canvas : createCanvasElement(), _context2 = parameters.context !== void 0 ? parameters.context : null, _alpha = parameters.alpha !== void 0 ? parameters.alpha : false, _depth = parameters.depth !== void 0 ? parameters.depth : true, _stencil = parameters.stencil !== void 0 ? parameters.stencil : true, _antialias = parameters.antialias !== void 0 ? parameters.antialias : false, _premultipliedAlpha = parameters.premultipliedAlpha !== void 0 ? parameters.premultipliedAlpha : true, _preserveDrawingBuffer = parameters.preserveDrawingBuffer !== void 0 ? parameters.preserveDrawingBuffer : false, _powerPreference = parameters.powerPreference !== void 0 ? parameters.powerPreference : \\\\\\\"default\\\\\\\", _failIfMajorPerformanceCaveat = parameters.failIfMajorPerformanceCaveat !== void 0 ? parameters.failIfMajorPerformanceCaveat : false;\\n let currentRenderList = null;\\n let currentRenderState = null;\\n const renderListStack = [];\\n const renderStateStack = [];\\n this.domElement = _canvas2;\\n this.debug = {\\n checkShaderErrors: true\\n };\\n this.autoClear = true;\\n this.autoClearColor = true;\\n this.autoClearDepth = true;\\n this.autoClearStencil = true;\\n this.sortObjects = true;\\n this.clippingPlanes = [];\\n this.localClippingEnabled = false;\\n this.gammaFactor = 2;\\n this.outputEncoding = LinearEncoding;\\n this.physicallyCorrectLights = false;\\n this.toneMapping = NoToneMapping;\\n this.toneMappingExposure = 1;\\n const _this = this;\\n let _isContextLost = false;\\n let _currentActiveCubeFace = 0;\\n let _currentActiveMipmapLevel = 0;\\n let _currentRenderTarget = null;\\n let _currentMaterialId = -1;\\n let _currentCamera = null;\\n const _currentViewport = new Vector4();\\n const _currentScissor = new Vector4();\\n let _currentScissorTest = null;\\n let _width = _canvas2.width;\\n let _height = _canvas2.height;\\n let _pixelRatio = 1;\\n let _opaqueSort = null;\\n let _transparentSort = null;\\n const _viewport = new Vector4(0, 0, _width, _height);\\n const _scissor = new Vector4(0, 0, _width, _height);\\n let _scissorTest = false;\\n const _currentDrawBuffers = [];\\n const _frustum = new Frustum();\\n let _clippingEnabled = false;\\n let _localClippingEnabled = false;\\n let _transmissionRenderTarget = null;\\n const _projScreenMatrix = new Matrix4();\\n const _vector32 = new Vector3();\\n const _emptyScene = {background: null, fog: null, environment: null, overrideMaterial: null, isScene: true};\\n function getTargetPixelRatio() {\\n return _currentRenderTarget === null ? _pixelRatio : 1;\\n }\\n let _gl = _context2;\\n function getContext(contextNames, contextAttributes) {\\n for (let i = 0; i < contextNames.length; i++) {\\n const contextName = contextNames[i];\\n const context = _canvas2.getContext(contextName, contextAttributes);\\n if (context !== null)\\n return context;\\n }\\n return null;\\n }\\n try {\\n const contextAttributes = {\\n alpha: _alpha,\\n depth: _depth,\\n stencil: _stencil,\\n antialias: _antialias,\\n premultipliedAlpha: _premultipliedAlpha,\\n preserveDrawingBuffer: _preserveDrawingBuffer,\\n powerPreference: _powerPreference,\\n failIfMajorPerformanceCaveat: _failIfMajorPerformanceCaveat\\n };\\n _canvas2.addEventListener(\\\\\\\"webglcontextlost\\\\\\\", onContextLost, false);\\n _canvas2.addEventListener(\\\\\\\"webglcontextrestored\\\\\\\", onContextRestore, false);\\n if (_gl === null) {\\n const contextNames = [\\\\\\\"webgl2\\\\\\\", \\\\\\\"webgl\\\\\\\", \\\\\\\"experimental-webgl\\\\\\\"];\\n if (_this.isWebGL1Renderer === true) {\\n contextNames.shift();\\n }\\n _gl = getContext(contextNames, contextAttributes);\\n if (_gl === null) {\\n if (getContext(contextNames)) {\\n throw new Error(\\\\\\\"Error creating WebGL context with your selected attributes.\\\\\\\");\\n } else {\\n throw new Error(\\\\\\\"Error creating WebGL context.\\\\\\\");\\n }\\n }\\n }\\n if (_gl.getShaderPrecisionFormat === void 0) {\\n _gl.getShaderPrecisionFormat = function() {\\n return {rangeMin: 1, rangeMax: 1, precision: 1};\\n };\\n }\\n } catch (error) {\\n console.error(\\\\\\\"THREE.WebGLRenderer: \\\\\\\" + error.message);\\n throw error;\\n }\\n let extensions, capabilities, state, info;\\n let properties, textures, cubemaps, cubeuvmaps, attributes, geometries, objects;\\n let programCache, materials2, renderLists, renderStates, clipping, shadowMap;\\n let background2, morphtargets, bufferRenderer, indexedBufferRenderer;\\n let utils, bindingStates;\\n function initGLContext() {\\n extensions = new WebGLExtensions(_gl);\\n capabilities = new WebGLCapabilities(_gl, extensions, parameters);\\n extensions.init(capabilities);\\n utils = new WebGLUtils(_gl, extensions, capabilities);\\n state = new WebGLState(_gl, extensions, capabilities);\\n _currentDrawBuffers[0] = _gl.BACK;\\n info = new WebGLInfo(_gl);\\n properties = new WebGLProperties();\\n textures = new WebGLTextures(_gl, extensions, state, properties, capabilities, utils, info);\\n cubemaps = new WebGLCubeMaps(_this);\\n cubeuvmaps = new WebGLCubeUVMaps(_this);\\n attributes = new WebGLAttributes(_gl, capabilities);\\n bindingStates = new WebGLBindingStates(_gl, extensions, attributes, capabilities);\\n geometries = new WebGLGeometries(_gl, attributes, info, bindingStates);\\n objects = new WebGLObjects(_gl, geometries, attributes, info);\\n morphtargets = new WebGLMorphtargets(_gl, capabilities, textures);\\n clipping = new WebGLClipping(properties);\\n programCache = new WebGLPrograms(_this, cubemaps, cubeuvmaps, extensions, capabilities, bindingStates, clipping);\\n materials2 = new WebGLMaterials(properties);\\n renderLists = new WebGLRenderLists(properties);\\n renderStates = new WebGLRenderStates(extensions, capabilities);\\n background2 = new WebGLBackground(_this, cubemaps, state, objects, _premultipliedAlpha);\\n shadowMap = new WebGLShadowMap(_this, objects, capabilities);\\n bufferRenderer = new WebGLBufferRenderer(_gl, extensions, info, capabilities);\\n indexedBufferRenderer = new WebGLIndexedBufferRenderer(_gl, extensions, info, capabilities);\\n info.programs = programCache.programs;\\n _this.capabilities = capabilities;\\n _this.extensions = extensions;\\n _this.properties = properties;\\n _this.renderLists = renderLists;\\n _this.shadowMap = shadowMap;\\n _this.state = state;\\n _this.info = info;\\n }\\n initGLContext();\\n const xr = new WebXRManager(_this, _gl);\\n this.xr = xr;\\n this.getContext = function() {\\n return _gl;\\n };\\n this.getContextAttributes = function() {\\n return _gl.getContextAttributes();\\n };\\n this.forceContextLoss = function() {\\n const extension = extensions.get(\\\\\\\"WEBGL_lose_context\\\\\\\");\\n if (extension)\\n extension.loseContext();\\n };\\n this.forceContextRestore = function() {\\n const extension = extensions.get(\\\\\\\"WEBGL_lose_context\\\\\\\");\\n if (extension)\\n extension.restoreContext();\\n };\\n this.getPixelRatio = function() {\\n return _pixelRatio;\\n };\\n this.setPixelRatio = function(value) {\\n if (value === void 0)\\n return;\\n _pixelRatio = value;\\n this.setSize(_width, _height, false);\\n };\\n this.getSize = function(target) {\\n return target.set(_width, _height);\\n };\\n this.setSize = function(width, height, updateStyle) {\\n if (xr.isPresenting) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer: Can't change size while VR device is presenting.\\\\\\\");\\n return;\\n }\\n _width = width;\\n _height = height;\\n _canvas2.width = Math.floor(width * _pixelRatio);\\n _canvas2.height = Math.floor(height * _pixelRatio);\\n if (updateStyle !== false) {\\n _canvas2.style.width = width + \\\\\\\"px\\\\\\\";\\n _canvas2.style.height = height + \\\\\\\"px\\\\\\\";\\n }\\n this.setViewport(0, 0, width, height);\\n };\\n this.getDrawingBufferSize = function(target) {\\n return target.set(_width * _pixelRatio, _height * _pixelRatio).floor();\\n };\\n this.setDrawingBufferSize = function(width, height, pixelRatio) {\\n _width = width;\\n _height = height;\\n _pixelRatio = pixelRatio;\\n _canvas2.width = Math.floor(width * pixelRatio);\\n _canvas2.height = Math.floor(height * pixelRatio);\\n this.setViewport(0, 0, width, height);\\n };\\n this.getCurrentViewport = function(target) {\\n return target.copy(_currentViewport);\\n };\\n this.getViewport = function(target) {\\n return target.copy(_viewport);\\n };\\n this.setViewport = function(x, y, width, height) {\\n if (x.isVector4) {\\n _viewport.set(x.x, x.y, x.z, x.w);\\n } else {\\n _viewport.set(x, y, width, height);\\n }\\n state.viewport(_currentViewport.copy(_viewport).multiplyScalar(_pixelRatio).floor());\\n };\\n this.getScissor = function(target) {\\n return target.copy(_scissor);\\n };\\n this.setScissor = function(x, y, width, height) {\\n if (x.isVector4) {\\n _scissor.set(x.x, x.y, x.z, x.w);\\n } else {\\n _scissor.set(x, y, width, height);\\n }\\n state.scissor(_currentScissor.copy(_scissor).multiplyScalar(_pixelRatio).floor());\\n };\\n this.getScissorTest = function() {\\n return _scissorTest;\\n };\\n this.setScissorTest = function(boolean) {\\n state.setScissorTest(_scissorTest = boolean);\\n };\\n this.setOpaqueSort = function(method) {\\n _opaqueSort = method;\\n };\\n this.setTransparentSort = function(method) {\\n _transparentSort = method;\\n };\\n this.getClearColor = function(target) {\\n return target.copy(background2.getClearColor());\\n };\\n this.setClearColor = function() {\\n background2.setClearColor.apply(background2, arguments);\\n };\\n this.getClearAlpha = function() {\\n return background2.getClearAlpha();\\n };\\n this.setClearAlpha = function() {\\n background2.setClearAlpha.apply(background2, arguments);\\n };\\n this.clear = function(color, depth2, stencil) {\\n let bits = 0;\\n if (color === void 0 || color)\\n bits |= _gl.COLOR_BUFFER_BIT;\\n if (depth2 === void 0 || depth2)\\n bits |= _gl.DEPTH_BUFFER_BIT;\\n if (stencil === void 0 || stencil)\\n bits |= _gl.STENCIL_BUFFER_BIT;\\n _gl.clear(bits);\\n };\\n this.clearColor = function() {\\n this.clear(true, false, false);\\n };\\n this.clearDepth = function() {\\n this.clear(false, true, false);\\n };\\n this.clearStencil = function() {\\n this.clear(false, false, true);\\n };\\n this.dispose = function() {\\n _canvas2.removeEventListener(\\\\\\\"webglcontextlost\\\\\\\", onContextLost, false);\\n _canvas2.removeEventListener(\\\\\\\"webglcontextrestored\\\\\\\", onContextRestore, false);\\n renderLists.dispose();\\n renderStates.dispose();\\n properties.dispose();\\n cubemaps.dispose();\\n cubeuvmaps.dispose();\\n objects.dispose();\\n bindingStates.dispose();\\n xr.dispose();\\n xr.removeEventListener(\\\\\\\"sessionstart\\\\\\\", onXRSessionStart);\\n xr.removeEventListener(\\\\\\\"sessionend\\\\\\\", onXRSessionEnd);\\n if (_transmissionRenderTarget) {\\n _transmissionRenderTarget.dispose();\\n _transmissionRenderTarget = null;\\n }\\n animation.stop();\\n };\\n function onContextLost(event) {\\n event.preventDefault();\\n console.log(\\\\\\\"THREE.WebGLRenderer: Context Lost.\\\\\\\");\\n _isContextLost = true;\\n }\\n function onContextRestore() {\\n console.log(\\\\\\\"THREE.WebGLRenderer: Context Restored.\\\\\\\");\\n _isContextLost = false;\\n const infoAutoReset = info.autoReset;\\n const shadowMapEnabled = shadowMap.enabled;\\n const shadowMapAutoUpdate = shadowMap.autoUpdate;\\n const shadowMapNeedsUpdate = shadowMap.needsUpdate;\\n const shadowMapType = shadowMap.type;\\n initGLContext();\\n info.autoReset = infoAutoReset;\\n shadowMap.enabled = shadowMapEnabled;\\n shadowMap.autoUpdate = shadowMapAutoUpdate;\\n shadowMap.needsUpdate = shadowMapNeedsUpdate;\\n shadowMap.type = shadowMapType;\\n }\\n function onMaterialDispose(event) {\\n const material = event.target;\\n material.removeEventListener(\\\\\\\"dispose\\\\\\\", onMaterialDispose);\\n deallocateMaterial(material);\\n }\\n function deallocateMaterial(material) {\\n releaseMaterialProgramReferences(material);\\n properties.remove(material);\\n }\\n function releaseMaterialProgramReferences(material) {\\n const programs = properties.get(material).programs;\\n if (programs !== void 0) {\\n programs.forEach(function(program) {\\n programCache.releaseProgram(program);\\n });\\n }\\n }\\n function renderObjectImmediate(object, program) {\\n object.render(function(object2) {\\n _this.renderBufferImmediate(object2, program);\\n });\\n }\\n this.renderBufferImmediate = function(object, program) {\\n bindingStates.initAttributes();\\n const buffers = properties.get(object);\\n if (object.hasPositions && !buffers.position)\\n buffers.position = _gl.createBuffer();\\n if (object.hasNormals && !buffers.normal)\\n buffers.normal = _gl.createBuffer();\\n if (object.hasUvs && !buffers.uv)\\n buffers.uv = _gl.createBuffer();\\n if (object.hasColors && !buffers.color)\\n buffers.color = _gl.createBuffer();\\n const programAttributes = program.getAttributes();\\n if (object.hasPositions) {\\n _gl.bindBuffer(_gl.ARRAY_BUFFER, buffers.position);\\n _gl.bufferData(_gl.ARRAY_BUFFER, object.positionArray, _gl.DYNAMIC_DRAW);\\n bindingStates.enableAttribute(programAttributes.position.location);\\n _gl.vertexAttribPointer(programAttributes.position.location, 3, _gl.FLOAT, false, 0, 0);\\n }\\n if (object.hasNormals) {\\n _gl.bindBuffer(_gl.ARRAY_BUFFER, buffers.normal);\\n _gl.bufferData(_gl.ARRAY_BUFFER, object.normalArray, _gl.DYNAMIC_DRAW);\\n bindingStates.enableAttribute(programAttributes.normal.location);\\n _gl.vertexAttribPointer(programAttributes.normal.location, 3, _gl.FLOAT, false, 0, 0);\\n }\\n if (object.hasUvs) {\\n _gl.bindBuffer(_gl.ARRAY_BUFFER, buffers.uv);\\n _gl.bufferData(_gl.ARRAY_BUFFER, object.uvArray, _gl.DYNAMIC_DRAW);\\n bindingStates.enableAttribute(programAttributes.uv.location);\\n _gl.vertexAttribPointer(programAttributes.uv.location, 2, _gl.FLOAT, false, 0, 0);\\n }\\n if (object.hasColors) {\\n _gl.bindBuffer(_gl.ARRAY_BUFFER, buffers.color);\\n _gl.bufferData(_gl.ARRAY_BUFFER, object.colorArray, _gl.DYNAMIC_DRAW);\\n bindingStates.enableAttribute(programAttributes.color.location);\\n _gl.vertexAttribPointer(programAttributes.color.location, 3, _gl.FLOAT, false, 0, 0);\\n }\\n bindingStates.disableUnusedAttributes();\\n _gl.drawArrays(_gl.TRIANGLES, 0, object.count);\\n object.count = 0;\\n };\\n this.renderBufferDirect = function(camera, scene, geometry, material, object, group) {\\n if (scene === null)\\n scene = _emptyScene;\\n const frontFaceCW = object.isMesh && object.matrixWorld.determinant() < 0;\\n const program = setProgram(camera, scene, geometry, material, object);\\n state.setMaterial(material, frontFaceCW);\\n let index = geometry.index;\\n const position = geometry.attributes.position;\\n if (index === null) {\\n if (position === void 0 || position.count === 0)\\n return;\\n } else if (index.count === 0) {\\n return;\\n }\\n let rangeFactor = 1;\\n if (material.wireframe === true) {\\n index = geometries.getWireframeAttribute(geometry);\\n rangeFactor = 2;\\n }\\n bindingStates.setup(object, material, program, geometry, index);\\n let attribute;\\n let renderer = bufferRenderer;\\n if (index !== null) {\\n attribute = attributes.get(index);\\n renderer = indexedBufferRenderer;\\n renderer.setIndex(attribute);\\n }\\n const dataCount = index !== null ? index.count : position.count;\\n const rangeStart = geometry.drawRange.start * rangeFactor;\\n const rangeCount = geometry.drawRange.count * rangeFactor;\\n const groupStart = group !== null ? group.start * rangeFactor : 0;\\n const groupCount = group !== null ? group.count * rangeFactor : Infinity;\\n const drawStart = Math.max(rangeStart, groupStart);\\n const drawEnd = Math.min(dataCount, rangeStart + rangeCount, groupStart + groupCount) - 1;\\n const drawCount = Math.max(0, drawEnd - drawStart + 1);\\n if (drawCount === 0)\\n return;\\n if (object.isMesh) {\\n if (material.wireframe === true) {\\n state.setLineWidth(material.wireframeLinewidth * getTargetPixelRatio());\\n renderer.setMode(_gl.LINES);\\n } else {\\n renderer.setMode(_gl.TRIANGLES);\\n }\\n } else if (object.isLine) {\\n let lineWidth = material.linewidth;\\n if (lineWidth === void 0)\\n lineWidth = 1;\\n state.setLineWidth(lineWidth * getTargetPixelRatio());\\n if (object.isLineSegments) {\\n renderer.setMode(_gl.LINES);\\n } else if (object.isLineLoop) {\\n renderer.setMode(_gl.LINE_LOOP);\\n } else {\\n renderer.setMode(_gl.LINE_STRIP);\\n }\\n } else if (object.isPoints) {\\n renderer.setMode(_gl.POINTS);\\n } else if (object.isSprite) {\\n renderer.setMode(_gl.TRIANGLES);\\n }\\n if (object.isInstancedMesh) {\\n renderer.renderInstances(drawStart, drawCount, object.count);\\n } else if (geometry.isInstancedBufferGeometry) {\\n const instanceCount = Math.min(geometry.instanceCount, geometry._maxInstanceCount);\\n renderer.renderInstances(drawStart, drawCount, instanceCount);\\n } else {\\n renderer.render(drawStart, drawCount);\\n }\\n };\\n this.compile = function(scene, camera) {\\n currentRenderState = renderStates.get(scene);\\n currentRenderState.init();\\n renderStateStack.push(currentRenderState);\\n scene.traverseVisible(function(object) {\\n if (object.isLight && object.layers.test(camera.layers)) {\\n currentRenderState.pushLight(object);\\n if (object.castShadow) {\\n currentRenderState.pushShadow(object);\\n }\\n }\\n });\\n currentRenderState.setupLights(_this.physicallyCorrectLights);\\n scene.traverse(function(object) {\\n const material = object.material;\\n if (material) {\\n if (Array.isArray(material)) {\\n for (let i = 0; i < material.length; i++) {\\n const material2 = material[i];\\n getProgram(material2, scene, object);\\n }\\n } else {\\n getProgram(material, scene, object);\\n }\\n }\\n });\\n renderStateStack.pop();\\n currentRenderState = null;\\n };\\n let onAnimationFrameCallback = null;\\n function onAnimationFrame(time) {\\n if (onAnimationFrameCallback)\\n onAnimationFrameCallback(time);\\n }\\n function onXRSessionStart() {\\n animation.stop();\\n }\\n function onXRSessionEnd() {\\n animation.start();\\n }\\n const animation = new WebGLAnimation();\\n animation.setAnimationLoop(onAnimationFrame);\\n if (typeof window !== \\\\\\\"undefined\\\\\\\")\\n animation.setContext(window);\\n this.setAnimationLoop = function(callback) {\\n onAnimationFrameCallback = callback;\\n xr.setAnimationLoop(callback);\\n callback === null ? animation.stop() : animation.start();\\n };\\n xr.addEventListener(\\\\\\\"sessionstart\\\\\\\", onXRSessionStart);\\n xr.addEventListener(\\\\\\\"sessionend\\\\\\\", onXRSessionEnd);\\n this.render = function(scene, camera) {\\n if (camera !== void 0 && camera.isCamera !== true) {\\n console.error(\\\\\\\"THREE.WebGLRenderer.render: camera is not an instance of THREE.Camera.\\\\\\\");\\n return;\\n }\\n if (_isContextLost === true)\\n return;\\n if (scene.autoUpdate === true)\\n scene.updateMatrixWorld();\\n if (camera.parent === null)\\n camera.updateMatrixWorld();\\n if (xr.enabled === true && xr.isPresenting === true) {\\n if (xr.cameraAutoUpdate === true)\\n xr.updateCamera(camera);\\n camera = xr.getCamera();\\n }\\n if (scene.isScene === true)\\n scene.onBeforeRender(_this, scene, camera, _currentRenderTarget);\\n currentRenderState = renderStates.get(scene, renderStateStack.length);\\n currentRenderState.init();\\n renderStateStack.push(currentRenderState);\\n _projScreenMatrix.multiplyMatrices(camera.projectionMatrix, camera.matrixWorldInverse);\\n _frustum.setFromProjectionMatrix(_projScreenMatrix);\\n _localClippingEnabled = this.localClippingEnabled;\\n _clippingEnabled = clipping.init(this.clippingPlanes, _localClippingEnabled, camera);\\n currentRenderList = renderLists.get(scene, renderListStack.length);\\n currentRenderList.init();\\n renderListStack.push(currentRenderList);\\n projectObject(scene, camera, 0, _this.sortObjects);\\n currentRenderList.finish();\\n if (_this.sortObjects === true) {\\n currentRenderList.sort(_opaqueSort, _transparentSort);\\n }\\n if (_clippingEnabled === true)\\n clipping.beginShadows();\\n const shadowsArray = currentRenderState.state.shadowsArray;\\n shadowMap.render(shadowsArray, scene, camera);\\n if (_clippingEnabled === true)\\n clipping.endShadows();\\n if (this.info.autoReset === true)\\n this.info.reset();\\n background2.render(currentRenderList, scene);\\n currentRenderState.setupLights(_this.physicallyCorrectLights);\\n if (camera.isArrayCamera) {\\n const cameras = camera.cameras;\\n for (let i = 0, l = cameras.length; i < l; i++) {\\n const camera2 = cameras[i];\\n renderScene(currentRenderList, scene, camera2, camera2.viewport);\\n }\\n } else {\\n renderScene(currentRenderList, scene, camera);\\n }\\n if (_currentRenderTarget !== null) {\\n textures.updateMultisampleRenderTarget(_currentRenderTarget);\\n textures.updateRenderTargetMipmap(_currentRenderTarget);\\n }\\n if (scene.isScene === true)\\n scene.onAfterRender(_this, scene, camera);\\n state.buffers.depth.setTest(true);\\n state.buffers.depth.setMask(true);\\n state.buffers.color.setMask(true);\\n state.setPolygonOffset(false);\\n bindingStates.resetDefaultState();\\n _currentMaterialId = -1;\\n _currentCamera = null;\\n renderStateStack.pop();\\n if (renderStateStack.length > 0) {\\n currentRenderState = renderStateStack[renderStateStack.length - 1];\\n } else {\\n currentRenderState = null;\\n }\\n renderListStack.pop();\\n if (renderListStack.length > 0) {\\n currentRenderList = renderListStack[renderListStack.length - 1];\\n } else {\\n currentRenderList = null;\\n }\\n };\\n function projectObject(object, camera, groupOrder, sortObjects) {\\n if (object.visible === false)\\n return;\\n const visible = object.layers.test(camera.layers);\\n if (visible) {\\n if (object.isGroup) {\\n groupOrder = object.renderOrder;\\n } else if (object.isLOD) {\\n if (object.autoUpdate === true)\\n object.update(camera);\\n } else if (object.isLight) {\\n currentRenderState.pushLight(object);\\n if (object.castShadow) {\\n currentRenderState.pushShadow(object);\\n }\\n } else if (object.isSprite) {\\n if (!object.frustumCulled || _frustum.intersectsSprite(object)) {\\n if (sortObjects) {\\n _vector32.setFromMatrixPosition(object.matrixWorld).applyMatrix4(_projScreenMatrix);\\n }\\n const geometry = objects.update(object);\\n const material = object.material;\\n if (material.visible) {\\n currentRenderList.push(object, geometry, material, groupOrder, _vector32.z, null);\\n }\\n }\\n } else if (object.isImmediateRenderObject) {\\n if (sortObjects) {\\n _vector32.setFromMatrixPosition(object.matrixWorld).applyMatrix4(_projScreenMatrix);\\n }\\n currentRenderList.push(object, null, object.material, groupOrder, _vector32.z, null);\\n } else if (object.isMesh || object.isLine || object.isPoints) {\\n if (object.isSkinnedMesh) {\\n if (object.skeleton.frame !== info.render.frame) {\\n object.skeleton.update();\\n object.skeleton.frame = info.render.frame;\\n }\\n }\\n if (!object.frustumCulled || _frustum.intersectsObject(object)) {\\n if (sortObjects) {\\n _vector32.setFromMatrixPosition(object.matrixWorld).applyMatrix4(_projScreenMatrix);\\n }\\n const geometry = objects.update(object);\\n const material = object.material;\\n if (Array.isArray(material)) {\\n const groups = geometry.groups;\\n for (let i = 0, l = groups.length; i < l; i++) {\\n const group = groups[i];\\n const groupMaterial = material[group.materialIndex];\\n if (groupMaterial && groupMaterial.visible) {\\n currentRenderList.push(object, geometry, groupMaterial, groupOrder, _vector32.z, group);\\n }\\n }\\n } else if (material.visible) {\\n currentRenderList.push(object, geometry, material, groupOrder, _vector32.z, null);\\n }\\n }\\n }\\n }\\n const children = object.children;\\n for (let i = 0, l = children.length; i < l; i++) {\\n projectObject(children[i], camera, groupOrder, sortObjects);\\n }\\n }\\n function renderScene(currentRenderList2, scene, camera, viewport) {\\n const opaqueObjects = currentRenderList2.opaque;\\n const transmissiveObjects = currentRenderList2.transmissive;\\n const transparentObjects = currentRenderList2.transparent;\\n currentRenderState.setupLightsView(camera);\\n if (transmissiveObjects.length > 0)\\n renderTransmissionPass(opaqueObjects, scene, camera);\\n if (viewport)\\n state.viewport(_currentViewport.copy(viewport));\\n if (opaqueObjects.length > 0)\\n renderObjects(opaqueObjects, scene, camera);\\n if (transmissiveObjects.length > 0)\\n renderObjects(transmissiveObjects, scene, camera);\\n if (transparentObjects.length > 0)\\n renderObjects(transparentObjects, scene, camera);\\n }\\n function renderTransmissionPass(opaqueObjects, scene, camera) {\\n if (_transmissionRenderTarget === null) {\\n const needsAntialias = _antialias === true && capabilities.isWebGL2 === true;\\n const renderTargetType = needsAntialias ? WebGLMultisampleRenderTarget : WebGLRenderTarget;\\n _transmissionRenderTarget = new renderTargetType(1024, 1024, {\\n generateMipmaps: true,\\n type: utils.convert(HalfFloatType) !== null ? HalfFloatType : UnsignedByteType,\\n minFilter: LinearMipmapLinearFilter,\\n magFilter: NearestFilter,\\n wrapS: ClampToEdgeWrapping,\\n wrapT: ClampToEdgeWrapping\\n });\\n }\\n const currentRenderTarget = _this.getRenderTarget();\\n _this.setRenderTarget(_transmissionRenderTarget);\\n _this.clear();\\n const currentToneMapping = _this.toneMapping;\\n _this.toneMapping = NoToneMapping;\\n renderObjects(opaqueObjects, scene, camera);\\n _this.toneMapping = currentToneMapping;\\n textures.updateMultisampleRenderTarget(_transmissionRenderTarget);\\n textures.updateRenderTargetMipmap(_transmissionRenderTarget);\\n _this.setRenderTarget(currentRenderTarget);\\n }\\n function renderObjects(renderList, scene, camera) {\\n const overrideMaterial = scene.isScene === true ? scene.overrideMaterial : null;\\n for (let i = 0, l = renderList.length; i < l; i++) {\\n const renderItem = renderList[i];\\n const object = renderItem.object;\\n const geometry = renderItem.geometry;\\n const material = overrideMaterial === null ? renderItem.material : overrideMaterial;\\n const group = renderItem.group;\\n if (object.layers.test(camera.layers)) {\\n renderObject(object, scene, camera, geometry, material, group);\\n }\\n }\\n }\\n function renderObject(object, scene, camera, geometry, material, group) {\\n object.onBeforeRender(_this, scene, camera, geometry, material, group);\\n object.modelViewMatrix.multiplyMatrices(camera.matrixWorldInverse, object.matrixWorld);\\n object.normalMatrix.getNormalMatrix(object.modelViewMatrix);\\n material.onBeforeRender(_this, scene, camera, geometry, object, group);\\n if (object.isImmediateRenderObject) {\\n const program = setProgram(camera, scene, geometry, material, object);\\n state.setMaterial(material);\\n bindingStates.reset();\\n renderObjectImmediate(object, program);\\n } else {\\n if (material.transparent === true && material.side === DoubleSide) {\\n material.side = BackSide;\\n material.needsUpdate = true;\\n _this.renderBufferDirect(camera, scene, geometry, material, object, group);\\n material.side = FrontSide;\\n material.needsUpdate = true;\\n _this.renderBufferDirect(camera, scene, geometry, material, object, group);\\n material.side = DoubleSide;\\n } else {\\n _this.renderBufferDirect(camera, scene, geometry, material, object, group);\\n }\\n }\\n object.onAfterRender(_this, scene, camera, geometry, material, group);\\n }\\n function getProgram(material, scene, object) {\\n if (scene.isScene !== true)\\n scene = _emptyScene;\\n const materialProperties = properties.get(material);\\n const lights = currentRenderState.state.lights;\\n const shadowsArray = currentRenderState.state.shadowsArray;\\n const lightsStateVersion = lights.state.version;\\n const parameters2 = programCache.getParameters(material, lights.state, shadowsArray, scene, object);\\n const programCacheKey = programCache.getProgramCacheKey(parameters2);\\n let programs = materialProperties.programs;\\n materialProperties.environment = material.isMeshStandardMaterial ? scene.environment : null;\\n materialProperties.fog = scene.fog;\\n materialProperties.envMap = (material.isMeshStandardMaterial ? cubeuvmaps : cubemaps).get(material.envMap || materialProperties.environment);\\n if (programs === void 0) {\\n material.addEventListener(\\\\\\\"dispose\\\\\\\", onMaterialDispose);\\n programs = new Map();\\n materialProperties.programs = programs;\\n }\\n let program = programs.get(programCacheKey);\\n if (program !== void 0) {\\n if (materialProperties.currentProgram === program && materialProperties.lightsStateVersion === lightsStateVersion) {\\n updateCommonMaterialProperties(material, parameters2);\\n return program;\\n }\\n } else {\\n parameters2.uniforms = programCache.getUniforms(material);\\n material.onBuild(parameters2, _this);\\n material.onBeforeCompile(parameters2, _this);\\n program = programCache.acquireProgram(parameters2, programCacheKey);\\n programs.set(programCacheKey, program);\\n materialProperties.uniforms = parameters2.uniforms;\\n }\\n const uniforms = materialProperties.uniforms;\\n if (!material.isShaderMaterial && !material.isRawShaderMaterial || material.clipping === true) {\\n uniforms.clippingPlanes = clipping.uniform;\\n }\\n updateCommonMaterialProperties(material, parameters2);\\n materialProperties.needsLights = materialNeedsLights(material);\\n materialProperties.lightsStateVersion = lightsStateVersion;\\n if (materialProperties.needsLights) {\\n uniforms.ambientLightColor.value = lights.state.ambient;\\n uniforms.lightProbe.value = lights.state.probe;\\n uniforms.directionalLights.value = lights.state.directional;\\n uniforms.directionalLightShadows.value = lights.state.directionalShadow;\\n uniforms.spotLights.value = lights.state.spot;\\n uniforms.spotLightShadows.value = lights.state.spotShadow;\\n uniforms.rectAreaLights.value = lights.state.rectArea;\\n uniforms.ltc_1.value = lights.state.rectAreaLTC1;\\n uniforms.ltc_2.value = lights.state.rectAreaLTC2;\\n uniforms.pointLights.value = lights.state.point;\\n uniforms.pointLightShadows.value = lights.state.pointShadow;\\n uniforms.hemisphereLights.value = lights.state.hemi;\\n uniforms.directionalShadowMap.value = lights.state.directionalShadowMap;\\n uniforms.directionalShadowMatrix.value = lights.state.directionalShadowMatrix;\\n uniforms.spotShadowMap.value = lights.state.spotShadowMap;\\n uniforms.spotShadowMatrix.value = lights.state.spotShadowMatrix;\\n uniforms.pointShadowMap.value = lights.state.pointShadowMap;\\n uniforms.pointShadowMatrix.value = lights.state.pointShadowMatrix;\\n }\\n const progUniforms = program.getUniforms();\\n const uniformsList = WebGLUniforms.seqWithValue(progUniforms.seq, uniforms);\\n materialProperties.currentProgram = program;\\n materialProperties.uniformsList = uniformsList;\\n return program;\\n }\\n function updateCommonMaterialProperties(material, parameters2) {\\n const materialProperties = properties.get(material);\\n materialProperties.outputEncoding = parameters2.outputEncoding;\\n materialProperties.instancing = parameters2.instancing;\\n materialProperties.skinning = parameters2.skinning;\\n materialProperties.morphTargets = parameters2.morphTargets;\\n materialProperties.morphNormals = parameters2.morphNormals;\\n materialProperties.morphTargetsCount = parameters2.morphTargetsCount;\\n materialProperties.numClippingPlanes = parameters2.numClippingPlanes;\\n materialProperties.numIntersection = parameters2.numClipIntersection;\\n materialProperties.vertexAlphas = parameters2.vertexAlphas;\\n materialProperties.vertexTangents = parameters2.vertexTangents;\\n }\\n function setProgram(camera, scene, geometry, material, object) {\\n if (scene.isScene !== true)\\n scene = _emptyScene;\\n textures.resetTextureUnits();\\n const fog = scene.fog;\\n const environment = material.isMeshStandardMaterial ? scene.environment : null;\\n const encoding = _currentRenderTarget === null ? _this.outputEncoding : _currentRenderTarget.texture.encoding;\\n const envMap = (material.isMeshStandardMaterial ? cubeuvmaps : cubemaps).get(material.envMap || environment);\\n const vertexAlphas = material.vertexColors === true && !!geometry && !!geometry.attributes.color && geometry.attributes.color.itemSize === 4;\\n const vertexTangents = !!material.normalMap && !!geometry && !!geometry.attributes.tangent;\\n const morphTargets = !!geometry && !!geometry.morphAttributes.position;\\n const morphNormals = !!geometry && !!geometry.morphAttributes.normal;\\n const morphTargetsCount = !!geometry && !!geometry.morphAttributes.position ? geometry.morphAttributes.position.length : 0;\\n const materialProperties = properties.get(material);\\n const lights = currentRenderState.state.lights;\\n if (_clippingEnabled === true) {\\n if (_localClippingEnabled === true || camera !== _currentCamera) {\\n const useCache = camera === _currentCamera && material.id === _currentMaterialId;\\n clipping.setState(material, camera, useCache);\\n }\\n }\\n let needsProgramChange = false;\\n if (material.version === materialProperties.__version) {\\n if (materialProperties.needsLights && materialProperties.lightsStateVersion !== lights.state.version) {\\n needsProgramChange = true;\\n } else if (materialProperties.outputEncoding !== encoding) {\\n needsProgramChange = true;\\n } else if (object.isInstancedMesh && materialProperties.instancing === false) {\\n needsProgramChange = true;\\n } else if (!object.isInstancedMesh && materialProperties.instancing === true) {\\n needsProgramChange = true;\\n } else if (object.isSkinnedMesh && materialProperties.skinning === false) {\\n needsProgramChange = true;\\n } else if (!object.isSkinnedMesh && materialProperties.skinning === true) {\\n needsProgramChange = true;\\n } else if (materialProperties.envMap !== envMap) {\\n needsProgramChange = true;\\n } else if (material.fog && materialProperties.fog !== fog) {\\n needsProgramChange = true;\\n } else if (materialProperties.numClippingPlanes !== void 0 && (materialProperties.numClippingPlanes !== clipping.numPlanes || materialProperties.numIntersection !== clipping.numIntersection)) {\\n needsProgramChange = true;\\n } else if (materialProperties.vertexAlphas !== vertexAlphas) {\\n needsProgramChange = true;\\n } else if (materialProperties.vertexTangents !== vertexTangents) {\\n needsProgramChange = true;\\n } else if (materialProperties.morphTargets !== morphTargets) {\\n needsProgramChange = true;\\n } else if (materialProperties.morphNormals !== morphNormals) {\\n needsProgramChange = true;\\n } else if (capabilities.isWebGL2 === true && materialProperties.morphTargetsCount !== morphTargetsCount) {\\n needsProgramChange = true;\\n }\\n } else {\\n needsProgramChange = true;\\n materialProperties.__version = material.version;\\n }\\n let program = materialProperties.currentProgram;\\n if (needsProgramChange === true) {\\n program = getProgram(material, scene, object);\\n }\\n let refreshProgram = false;\\n let refreshMaterial = false;\\n let refreshLights = false;\\n const p_uniforms = program.getUniforms(), m_uniforms = materialProperties.uniforms;\\n if (state.useProgram(program.program)) {\\n refreshProgram = true;\\n refreshMaterial = true;\\n refreshLights = true;\\n }\\n if (material.id !== _currentMaterialId) {\\n _currentMaterialId = material.id;\\n refreshMaterial = true;\\n }\\n if (refreshProgram || _currentCamera !== camera) {\\n p_uniforms.setValue(_gl, \\\\\\\"projectionMatrix\\\\\\\", camera.projectionMatrix);\\n if (capabilities.logarithmicDepthBuffer) {\\n p_uniforms.setValue(_gl, \\\\\\\"logDepthBufFC\\\\\\\", 2 / (Math.log(camera.far + 1) / Math.LN2));\\n }\\n if (_currentCamera !== camera) {\\n _currentCamera = camera;\\n refreshMaterial = true;\\n refreshLights = true;\\n }\\n if (material.isShaderMaterial || material.isMeshPhongMaterial || material.isMeshToonMaterial || material.isMeshStandardMaterial || material.envMap) {\\n const uCamPos = p_uniforms.map.cameraPosition;\\n if (uCamPos !== void 0) {\\n uCamPos.setValue(_gl, _vector32.setFromMatrixPosition(camera.matrixWorld));\\n }\\n }\\n if (material.isMeshPhongMaterial || material.isMeshToonMaterial || material.isMeshLambertMaterial || material.isMeshBasicMaterial || material.isMeshStandardMaterial || material.isShaderMaterial) {\\n p_uniforms.setValue(_gl, \\\\\\\"isOrthographic\\\\\\\", camera.isOrthographicCamera === true);\\n }\\n if (material.isMeshPhongMaterial || material.isMeshToonMaterial || material.isMeshLambertMaterial || material.isMeshBasicMaterial || material.isMeshStandardMaterial || material.isShaderMaterial || material.isShadowMaterial || object.isSkinnedMesh) {\\n p_uniforms.setValue(_gl, \\\\\\\"viewMatrix\\\\\\\", camera.matrixWorldInverse);\\n }\\n }\\n if (object.isSkinnedMesh) {\\n p_uniforms.setOptional(_gl, object, \\\\\\\"bindMatrix\\\\\\\");\\n p_uniforms.setOptional(_gl, object, \\\\\\\"bindMatrixInverse\\\\\\\");\\n const skeleton = object.skeleton;\\n if (skeleton) {\\n if (capabilities.floatVertexTextures) {\\n if (skeleton.boneTexture === null)\\n skeleton.computeBoneTexture();\\n p_uniforms.setValue(_gl, \\\\\\\"boneTexture\\\\\\\", skeleton.boneTexture, textures);\\n p_uniforms.setValue(_gl, \\\\\\\"boneTextureSize\\\\\\\", skeleton.boneTextureSize);\\n } else {\\n p_uniforms.setOptional(_gl, skeleton, \\\\\\\"boneMatrices\\\\\\\");\\n }\\n }\\n }\\n if (!!geometry && (geometry.morphAttributes.position !== void 0 || geometry.morphAttributes.normal !== void 0)) {\\n morphtargets.update(object, geometry, material, program);\\n }\\n if (refreshMaterial || materialProperties.receiveShadow !== object.receiveShadow) {\\n materialProperties.receiveShadow = object.receiveShadow;\\n p_uniforms.setValue(_gl, \\\\\\\"receiveShadow\\\\\\\", object.receiveShadow);\\n }\\n if (refreshMaterial) {\\n p_uniforms.setValue(_gl, \\\\\\\"toneMappingExposure\\\\\\\", _this.toneMappingExposure);\\n if (materialProperties.needsLights) {\\n markUniformsLightsNeedsUpdate(m_uniforms, refreshLights);\\n }\\n if (fog && material.fog) {\\n materials2.refreshFogUniforms(m_uniforms, fog);\\n }\\n materials2.refreshMaterialUniforms(m_uniforms, material, _pixelRatio, _height, _transmissionRenderTarget);\\n WebGLUniforms.upload(_gl, materialProperties.uniformsList, m_uniforms, textures);\\n }\\n if (material.isShaderMaterial && material.uniformsNeedUpdate === true) {\\n WebGLUniforms.upload(_gl, materialProperties.uniformsList, m_uniforms, textures);\\n material.uniformsNeedUpdate = false;\\n }\\n if (material.isSpriteMaterial) {\\n p_uniforms.setValue(_gl, \\\\\\\"center\\\\\\\", object.center);\\n }\\n p_uniforms.setValue(_gl, \\\\\\\"modelViewMatrix\\\\\\\", object.modelViewMatrix);\\n p_uniforms.setValue(_gl, \\\\\\\"normalMatrix\\\\\\\", object.normalMatrix);\\n p_uniforms.setValue(_gl, \\\\\\\"modelMatrix\\\\\\\", object.matrixWorld);\\n return program;\\n }\\n function markUniformsLightsNeedsUpdate(uniforms, value) {\\n uniforms.ambientLightColor.needsUpdate = value;\\n uniforms.lightProbe.needsUpdate = value;\\n uniforms.directionalLights.needsUpdate = value;\\n uniforms.directionalLightShadows.needsUpdate = value;\\n uniforms.pointLights.needsUpdate = value;\\n uniforms.pointLightShadows.needsUpdate = value;\\n uniforms.spotLights.needsUpdate = value;\\n uniforms.spotLightShadows.needsUpdate = value;\\n uniforms.rectAreaLights.needsUpdate = value;\\n uniforms.hemisphereLights.needsUpdate = value;\\n }\\n function materialNeedsLights(material) {\\n return material.isMeshLambertMaterial || material.isMeshToonMaterial || material.isMeshPhongMaterial || material.isMeshStandardMaterial || material.isShadowMaterial || material.isShaderMaterial && material.lights === true;\\n }\\n this.getActiveCubeFace = function() {\\n return _currentActiveCubeFace;\\n };\\n this.getActiveMipmapLevel = function() {\\n return _currentActiveMipmapLevel;\\n };\\n this.getRenderTarget = function() {\\n return _currentRenderTarget;\\n };\\n this.setRenderTarget = function(renderTarget, activeCubeFace = 0, activeMipmapLevel = 0) {\\n _currentRenderTarget = renderTarget;\\n _currentActiveCubeFace = activeCubeFace;\\n _currentActiveMipmapLevel = activeMipmapLevel;\\n if (renderTarget && properties.get(renderTarget).__webglFramebuffer === void 0) {\\n textures.setupRenderTarget(renderTarget);\\n }\\n let framebuffer = null;\\n let isCube = false;\\n let isRenderTarget3D = false;\\n if (renderTarget) {\\n const texture = renderTarget.texture;\\n if (texture.isDataTexture3D || texture.isDataTexture2DArray) {\\n isRenderTarget3D = true;\\n }\\n const __webglFramebuffer = properties.get(renderTarget).__webglFramebuffer;\\n if (renderTarget.isWebGLCubeRenderTarget) {\\n framebuffer = __webglFramebuffer[activeCubeFace];\\n isCube = true;\\n } else if (renderTarget.isWebGLMultisampleRenderTarget) {\\n framebuffer = properties.get(renderTarget).__webglMultisampledFramebuffer;\\n } else {\\n framebuffer = __webglFramebuffer;\\n }\\n _currentViewport.copy(renderTarget.viewport);\\n _currentScissor.copy(renderTarget.scissor);\\n _currentScissorTest = renderTarget.scissorTest;\\n } else {\\n _currentViewport.copy(_viewport).multiplyScalar(_pixelRatio).floor();\\n _currentScissor.copy(_scissor).multiplyScalar(_pixelRatio).floor();\\n _currentScissorTest = _scissorTest;\\n }\\n const framebufferBound = state.bindFramebuffer(_gl.FRAMEBUFFER, framebuffer);\\n if (framebufferBound && capabilities.drawBuffers) {\\n let needsUpdate = false;\\n if (renderTarget) {\\n if (renderTarget.isWebGLMultipleRenderTargets) {\\n const textures2 = renderTarget.texture;\\n if (_currentDrawBuffers.length !== textures2.length || _currentDrawBuffers[0] !== _gl.COLOR_ATTACHMENT0) {\\n for (let i = 0, il = textures2.length; i < il; i++) {\\n _currentDrawBuffers[i] = _gl.COLOR_ATTACHMENT0 + i;\\n }\\n _currentDrawBuffers.length = textures2.length;\\n needsUpdate = true;\\n }\\n } else {\\n if (_currentDrawBuffers.length !== 1 || _currentDrawBuffers[0] !== _gl.COLOR_ATTACHMENT0) {\\n _currentDrawBuffers[0] = _gl.COLOR_ATTACHMENT0;\\n _currentDrawBuffers.length = 1;\\n needsUpdate = true;\\n }\\n }\\n } else {\\n if (_currentDrawBuffers.length !== 1 || _currentDrawBuffers[0] !== _gl.BACK) {\\n _currentDrawBuffers[0] = _gl.BACK;\\n _currentDrawBuffers.length = 1;\\n needsUpdate = true;\\n }\\n }\\n if (needsUpdate) {\\n if (capabilities.isWebGL2) {\\n _gl.drawBuffers(_currentDrawBuffers);\\n } else {\\n extensions.get(\\\\\\\"WEBGL_draw_buffers\\\\\\\").drawBuffersWEBGL(_currentDrawBuffers);\\n }\\n }\\n }\\n state.viewport(_currentViewport);\\n state.scissor(_currentScissor);\\n state.setScissorTest(_currentScissorTest);\\n if (isCube) {\\n const textureProperties = properties.get(renderTarget.texture);\\n _gl.framebufferTexture2D(_gl.FRAMEBUFFER, _gl.COLOR_ATTACHMENT0, _gl.TEXTURE_CUBE_MAP_POSITIVE_X + activeCubeFace, textureProperties.__webglTexture, activeMipmapLevel);\\n } else if (isRenderTarget3D) {\\n const textureProperties = properties.get(renderTarget.texture);\\n const layer = activeCubeFace || 0;\\n _gl.framebufferTextureLayer(_gl.FRAMEBUFFER, _gl.COLOR_ATTACHMENT0, textureProperties.__webglTexture, activeMipmapLevel || 0, layer);\\n }\\n _currentMaterialId = -1;\\n };\\n this.readRenderTargetPixels = function(renderTarget, x, y, width, height, buffer, activeCubeFaceIndex) {\\n if (!(renderTarget && renderTarget.isWebGLRenderTarget)) {\\n console.error(\\\\\\\"THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not THREE.WebGLRenderTarget.\\\\\\\");\\n return;\\n }\\n let framebuffer = properties.get(renderTarget).__webglFramebuffer;\\n if (renderTarget.isWebGLCubeRenderTarget && activeCubeFaceIndex !== void 0) {\\n framebuffer = framebuffer[activeCubeFaceIndex];\\n }\\n if (framebuffer) {\\n state.bindFramebuffer(_gl.FRAMEBUFFER, framebuffer);\\n try {\\n const texture = renderTarget.texture;\\n const textureFormat = texture.format;\\n const textureType = texture.type;\\n if (textureFormat !== RGBAFormat && utils.convert(textureFormat) !== _gl.getParameter(_gl.IMPLEMENTATION_COLOR_READ_FORMAT)) {\\n console.error(\\\\\\\"THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not in RGBA or implementation defined format.\\\\\\\");\\n return;\\n }\\n const halfFloatSupportedByExt = textureType === HalfFloatType && (extensions.has(\\\\\\\"EXT_color_buffer_half_float\\\\\\\") || capabilities.isWebGL2 && extensions.has(\\\\\\\"EXT_color_buffer_float\\\\\\\"));\\n if (textureType !== UnsignedByteType && utils.convert(textureType) !== _gl.getParameter(_gl.IMPLEMENTATION_COLOR_READ_TYPE) && !(textureType === FloatType && (capabilities.isWebGL2 || extensions.has(\\\\\\\"OES_texture_float\\\\\\\") || extensions.has(\\\\\\\"WEBGL_color_buffer_float\\\\\\\"))) && !halfFloatSupportedByExt) {\\n console.error(\\\\\\\"THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not in UnsignedByteType or implementation defined type.\\\\\\\");\\n return;\\n }\\n if (_gl.checkFramebufferStatus(_gl.FRAMEBUFFER) === _gl.FRAMEBUFFER_COMPLETE) {\\n if (x >= 0 && x <= renderTarget.width - width && (y >= 0 && y <= renderTarget.height - height)) {\\n _gl.readPixels(x, y, width, height, utils.convert(textureFormat), utils.convert(textureType), buffer);\\n }\\n } else {\\n console.error(\\\\\\\"THREE.WebGLRenderer.readRenderTargetPixels: readPixels from renderTarget failed. Framebuffer not complete.\\\\\\\");\\n }\\n } finally {\\n const framebuffer2 = _currentRenderTarget !== null ? properties.get(_currentRenderTarget).__webglFramebuffer : null;\\n state.bindFramebuffer(_gl.FRAMEBUFFER, framebuffer2);\\n }\\n }\\n };\\n this.copyFramebufferToTexture = function(position, texture, level = 0) {\\n const levelScale = Math.pow(2, -level);\\n const width = Math.floor(texture.image.width * levelScale);\\n const height = Math.floor(texture.image.height * levelScale);\\n let glFormat = utils.convert(texture.format);\\n if (capabilities.isWebGL2) {\\n if (glFormat === _gl.RGB)\\n glFormat = _gl.RGB8;\\n if (glFormat === _gl.RGBA)\\n glFormat = _gl.RGBA8;\\n }\\n textures.setTexture2D(texture, 0);\\n _gl.copyTexImage2D(_gl.TEXTURE_2D, level, glFormat, position.x, position.y, width, height, 0);\\n state.unbindTexture();\\n };\\n this.copyTextureToTexture = function(position, srcTexture, dstTexture, level = 0) {\\n const width = srcTexture.image.width;\\n const height = srcTexture.image.height;\\n const glFormat = utils.convert(dstTexture.format);\\n const glType = utils.convert(dstTexture.type);\\n textures.setTexture2D(dstTexture, 0);\\n _gl.pixelStorei(_gl.UNPACK_FLIP_Y_WEBGL, dstTexture.flipY);\\n _gl.pixelStorei(_gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, dstTexture.premultiplyAlpha);\\n _gl.pixelStorei(_gl.UNPACK_ALIGNMENT, dstTexture.unpackAlignment);\\n if (srcTexture.isDataTexture) {\\n _gl.texSubImage2D(_gl.TEXTURE_2D, level, position.x, position.y, width, height, glFormat, glType, srcTexture.image.data);\\n } else {\\n if (srcTexture.isCompressedTexture) {\\n _gl.compressedTexSubImage2D(_gl.TEXTURE_2D, level, position.x, position.y, srcTexture.mipmaps[0].width, srcTexture.mipmaps[0].height, glFormat, srcTexture.mipmaps[0].data);\\n } else {\\n _gl.texSubImage2D(_gl.TEXTURE_2D, level, position.x, position.y, glFormat, glType, srcTexture.image);\\n }\\n }\\n if (level === 0 && dstTexture.generateMipmaps)\\n _gl.generateMipmap(_gl.TEXTURE_2D);\\n state.unbindTexture();\\n };\\n this.copyTextureToTexture3D = function(sourceBox, position, srcTexture, dstTexture, level = 0) {\\n if (_this.isWebGL1Renderer) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer.copyTextureToTexture3D: can only be used with WebGL2.\\\\\\\");\\n return;\\n }\\n const width = sourceBox.max.x - sourceBox.min.x + 1;\\n const height = sourceBox.max.y - sourceBox.min.y + 1;\\n const depth2 = sourceBox.max.z - sourceBox.min.z + 1;\\n const glFormat = utils.convert(dstTexture.format);\\n const glType = utils.convert(dstTexture.type);\\n let glTarget;\\n if (dstTexture.isDataTexture3D) {\\n textures.setTexture3D(dstTexture, 0);\\n glTarget = _gl.TEXTURE_3D;\\n } else if (dstTexture.isDataTexture2DArray) {\\n textures.setTexture2DArray(dstTexture, 0);\\n glTarget = _gl.TEXTURE_2D_ARRAY;\\n } else {\\n console.warn(\\\\\\\"THREE.WebGLRenderer.copyTextureToTexture3D: only supports THREE.DataTexture3D and THREE.DataTexture2DArray.\\\\\\\");\\n return;\\n }\\n _gl.pixelStorei(_gl.UNPACK_FLIP_Y_WEBGL, dstTexture.flipY);\\n _gl.pixelStorei(_gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, dstTexture.premultiplyAlpha);\\n _gl.pixelStorei(_gl.UNPACK_ALIGNMENT, dstTexture.unpackAlignment);\\n const unpackRowLen = _gl.getParameter(_gl.UNPACK_ROW_LENGTH);\\n const unpackImageHeight = _gl.getParameter(_gl.UNPACK_IMAGE_HEIGHT);\\n const unpackSkipPixels = _gl.getParameter(_gl.UNPACK_SKIP_PIXELS);\\n const unpackSkipRows = _gl.getParameter(_gl.UNPACK_SKIP_ROWS);\\n const unpackSkipImages = _gl.getParameter(_gl.UNPACK_SKIP_IMAGES);\\n const image = srcTexture.isCompressedTexture ? srcTexture.mipmaps[0] : srcTexture.image;\\n _gl.pixelStorei(_gl.UNPACK_ROW_LENGTH, image.width);\\n _gl.pixelStorei(_gl.UNPACK_IMAGE_HEIGHT, image.height);\\n _gl.pixelStorei(_gl.UNPACK_SKIP_PIXELS, sourceBox.min.x);\\n _gl.pixelStorei(_gl.UNPACK_SKIP_ROWS, sourceBox.min.y);\\n _gl.pixelStorei(_gl.UNPACK_SKIP_IMAGES, sourceBox.min.z);\\n if (srcTexture.isDataTexture || srcTexture.isDataTexture3D) {\\n _gl.texSubImage3D(glTarget, level, position.x, position.y, position.z, width, height, depth2, glFormat, glType, image.data);\\n } else {\\n if (srcTexture.isCompressedTexture) {\\n console.warn(\\\\\\\"THREE.WebGLRenderer.copyTextureToTexture3D: untested support for compressed srcTexture.\\\\\\\");\\n _gl.compressedTexSubImage3D(glTarget, level, position.x, position.y, position.z, width, height, depth2, glFormat, image.data);\\n } else {\\n _gl.texSubImage3D(glTarget, level, position.x, position.y, position.z, width, height, depth2, glFormat, glType, image);\\n }\\n }\\n _gl.pixelStorei(_gl.UNPACK_ROW_LENGTH, unpackRowLen);\\n _gl.pixelStorei(_gl.UNPACK_IMAGE_HEIGHT, unpackImageHeight);\\n _gl.pixelStorei(_gl.UNPACK_SKIP_PIXELS, unpackSkipPixels);\\n _gl.pixelStorei(_gl.UNPACK_SKIP_ROWS, unpackSkipRows);\\n _gl.pixelStorei(_gl.UNPACK_SKIP_IMAGES, unpackSkipImages);\\n if (level === 0 && dstTexture.generateMipmaps)\\n _gl.generateMipmap(glTarget);\\n state.unbindTexture();\\n };\\n this.initTexture = function(texture) {\\n textures.setTexture2D(texture, 0);\\n state.unbindTexture();\\n };\\n this.resetState = function() {\\n _currentActiveCubeFace = 0;\\n _currentActiveMipmapLevel = 0;\\n _currentRenderTarget = null;\\n state.reset();\\n bindingStates.reset();\\n };\\n if (typeof __THREE_DEVTOOLS__ !== \\\\\\\"undefined\\\\\\\") {\\n __THREE_DEVTOOLS__.dispatchEvent(new CustomEvent(\\\\\\\"observe\\\\\\\", {detail: this}));\\n }\\n}\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/RenderersController.ts\\nvar CONTEXT_OPTIONS = {};\\nvar WebGLContext;\\n(function(WebGLContext2) {\\n WebGLContext2[\\\\\\\"WEBGL\\\\\\\"] = \\\\\\\"webgl\\\\\\\";\\n WebGLContext2[\\\\\\\"WEBGL2\\\\\\\"] = \\\\\\\"webgl2\\\\\\\";\\n WebGLContext2[\\\\\\\"EXPERIMENTAL_WEBGL\\\\\\\"] = \\\\\\\"experimental-webgl\\\\\\\";\\n WebGLContext2[\\\\\\\"EXPERIMENTAL_WEBGL2\\\\\\\"] = \\\\\\\"experimental-webgl2\\\\\\\";\\n})(WebGLContext || (WebGLContext = {}));\\nvar RenderersController = class {\\n constructor() {\\n this._next_renderer_id = 0;\\n this._renderers = {};\\n this._printDebug = false;\\n this._require_webgl2 = false;\\n this._resolves = [];\\n }\\n setPrintDebug(state = true) {\\n this._printDebug = state;\\n }\\n printDebug() {\\n return this._printDebug;\\n }\\n printDebugMessage(message) {\\n if (!this._printDebug) {\\n return;\\n }\\n console.warn(\\\\\\\"[Poly debug]\\\\\\\", message);\\n }\\n setRequireWebGL2() {\\n if (!this._require_webgl2) {\\n this._require_webgl2 = true;\\n }\\n }\\n webgl2Available() {\\n if (this._webgl2_available === void 0) {\\n this._webgl2_available = this._set_webgl2_available();\\n }\\n return this._webgl2_available;\\n }\\n _set_webgl2_available() {\\n const canvas = document.createElement(\\\\\\\"canvas\\\\\\\");\\n return (window.WebGL2RenderingContext && canvas.getContext(WebGLContext.WEBGL2)) != null;\\n }\\n createWebGLRenderer(params) {\\n const renderer = new WebGLRenderer(params);\\n this.printDebugMessage([`create renderer:`, params]);\\n return renderer;\\n }\\n createRenderingContext(canvas) {\\n let gl = null;\\n if (this._require_webgl2) {\\n gl = this._getRenderingContextWebgl(canvas, true);\\n if (!gl) {\\n console.warn(\\\\\\\"failed to create webgl2 context\\\\\\\");\\n }\\n }\\n if (!gl) {\\n gl = this._getRenderingContextWebgl(canvas, false);\\n }\\n return gl;\\n }\\n _getRenderingContextWebgl(canvas, webgl2) {\\n let context_name;\\n if (this.webgl2Available()) {\\n context_name = WebGLContext.WEBGL2;\\n } else {\\n context_name = webgl2 ? WebGLContext.WEBGL2 : WebGLContext.WEBGL;\\n }\\n let gl = canvas.getContext(context_name, CONTEXT_OPTIONS);\\n if (gl) {\\n this.printDebugMessage(`create gl context: ${context_name}.`);\\n } else {\\n context_name = webgl2 ? WebGLContext.EXPERIMENTAL_WEBGL2 : WebGLContext.EXPERIMENTAL_WEBGL;\\n this.printDebugMessage(`create gl context: ${context_name}.`);\\n gl = canvas.getContext(context_name, CONTEXT_OPTIONS);\\n }\\n return gl;\\n }\\n registerRenderer(renderer) {\\n if (renderer._polygon_id) {\\n throw new Error(\\\\\\\"render already registered\\\\\\\");\\n }\\n renderer._polygon_id = this._next_renderer_id += 1;\\n this._renderers[renderer._polygon_id] = renderer;\\n if (Object.keys(this._renderers).length == 1) {\\n this.flush_callbacks_with_renderer(renderer);\\n }\\n }\\n deregisterRenderer(renderer) {\\n delete this._renderers[renderer._polygon_id];\\n renderer.dispose();\\n }\\n firstRenderer() {\\n const first_id = Object.keys(this._renderers)[0];\\n if (first_id) {\\n return this._renderers[first_id];\\n }\\n return null;\\n }\\n renderers() {\\n return Object.values(this._renderers);\\n }\\n flush_callbacks_with_renderer(renderer) {\\n let callback;\\n while (callback = this._resolves.pop()) {\\n callback(renderer);\\n }\\n }\\n async waitForRenderer() {\\n const renderer = this.firstRenderer();\\n if (renderer) {\\n return renderer;\\n } else {\\n return new Promise((resolve, reject) => {\\n this._resolves.push(resolve);\\n });\\n }\\n }\\n renderTarget(width, height, parameters) {\\n if (this.webgl2Available()) {\\n return new WebGLMultisampleRenderTarget(width, height, parameters);\\n } else {\\n return new WebGLRenderTarget(width, height, parameters);\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/PolyLibsController.ts\\nvar PolyLibsController = class {\\n constructor() {\\n this._root = \\\\\\\"/three/js/libs\\\\\\\";\\n this._BASISPath = \\\\\\\"/basis\\\\\\\";\\n this._DRACOPath = \\\\\\\"/draco\\\\\\\";\\n this._DRACOGLTFPath = \\\\\\\"/draco/gltf\\\\\\\";\\n }\\n root() {\\n return this._root;\\n }\\n setRoot(url) {\\n this._root = url;\\n }\\n BASISPath() {\\n return this._BASISPath;\\n }\\n DRACOPath() {\\n return this._DRACOPath;\\n }\\n DRACOGLTFPath() {\\n return this._DRACOGLTFPath;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/nodes/NodesRegister.ts\\nvar NodesRegister = class {\\n constructor(poly) {\\n this.poly = poly;\\n this._node_register = new Map();\\n this._node_register_categories = new Map();\\n this._node_register_options = new Map();\\n }\\n static type(node) {\\n return this.filterType(node.type());\\n }\\n static filterType(nodeType) {\\n return nodeType.toLowerCase();\\n }\\n register(node, tab_menu_category, options) {\\n const context = node.context();\\n const nodeType = NodesRegister.type(node);\\n let current_nodes_for_context = this._node_register.get(context);\\n if (!current_nodes_for_context) {\\n current_nodes_for_context = new Map();\\n this._node_register.set(context, current_nodes_for_context);\\n }\\n const already_registered_node = current_nodes_for_context.get(nodeType);\\n if (already_registered_node) {\\n console.error(`node ${context}/${nodeType} already registered`);\\n return;\\n }\\n current_nodes_for_context.set(nodeType, node);\\n if (tab_menu_category) {\\n let current_categories = this._node_register_categories.get(context);\\n if (!current_categories) {\\n current_categories = new Map();\\n this._node_register_categories.set(context, current_categories);\\n }\\n current_categories.set(nodeType, tab_menu_category);\\n }\\n if (options) {\\n let current_options = this._node_register_options.get(context);\\n if (!current_options) {\\n current_options = new Map();\\n this._node_register_options.set(context, current_options);\\n }\\n current_options.set(nodeType, options);\\n }\\n this.poly.pluginsRegister.registerNode(node);\\n }\\n deregister(context, nodeType) {\\n nodeType = NodesRegister.filterType(nodeType);\\n this._node_register.get(context)?.delete(nodeType);\\n this._node_register_categories.get(context)?.delete(nodeType);\\n this._node_register_options.get(context)?.delete(nodeType);\\n }\\n isRegistered(context, nodeType) {\\n const nodes_for_context = this._node_register.get(context);\\n if (!nodes_for_context) {\\n return false;\\n }\\n nodeType = NodesRegister.filterType(nodeType);\\n return nodes_for_context.get(nodeType) != null;\\n }\\n nodeOptions(context, nodeType) {\\n nodeType = NodesRegister.filterType(nodeType);\\n return this._node_register_options.get(context)?.get(nodeType);\\n }\\n registeredNodesForContextAndParentType(context, parent_node_type) {\\n const map = this._node_register.get(context);\\n if (map) {\\n const nodes_for_context = [];\\n this._node_register.get(context)?.forEach((node, type) => {\\n nodes_for_context.push(node);\\n });\\n return nodes_for_context.filter((node) => {\\n const nodeType = NodesRegister.type(node);\\n const options = this._node_register_options.get(context)?.get(nodeType);\\n if (!options) {\\n return true;\\n } else {\\n const option_only = options[\\\\\\\"only\\\\\\\"];\\n const option_except = options[\\\\\\\"except\\\\\\\"];\\n const context_and_type = `${context}/${parent_node_type}`;\\n if (option_only) {\\n return option_only.includes(context_and_type);\\n }\\n if (option_except) {\\n return !option_except.includes(context_and_type);\\n }\\n return true;\\n }\\n });\\n } else {\\n return [];\\n }\\n }\\n registeredNodes(context, parentNodeType) {\\n const nodesByType = {};\\n const nodes = this.registeredNodesForContextAndParentType(context, parentNodeType);\\n for (let node of nodes) {\\n const nodeType = NodesRegister.type(node);\\n nodesByType[nodeType] = node;\\n }\\n return nodesByType;\\n }\\n registeredCategory(context, nodeType) {\\n nodeType = NodesRegister.filterType(nodeType);\\n return this._node_register_categories.get(context)?.get(nodeType);\\n }\\n map() {\\n return this._node_register;\\n }\\n};\\nvar OperationsRegister = class {\\n constructor(poly) {\\n this.poly = poly;\\n this._operation_register = new Map();\\n }\\n static type(node) {\\n return this.filterType(node.type());\\n }\\n static filterType(nodeType) {\\n return nodeType.toLowerCase();\\n }\\n register(operation) {\\n const context = operation.context();\\n let current_operations_for_context = this._operation_register.get(context);\\n if (!current_operations_for_context) {\\n current_operations_for_context = new Map();\\n this._operation_register.set(context, current_operations_for_context);\\n }\\n const operationType = OperationsRegister.type(operation);\\n const already_registered_operation = current_operations_for_context.get(operationType);\\n if (already_registered_operation) {\\n const message = `operation ${context}/${operationType} already registered`;\\n console.error(message);\\n return;\\n }\\n current_operations_for_context.set(operationType, operation);\\n this.poly.pluginsRegister.registerOperation(operation);\\n }\\n registeredOperationsForContextAndParentType(context, parentNodeType) {\\n const map = this._operation_register.get(context);\\n if (map) {\\n const nodes_for_context = [];\\n this._operation_register.get(context)?.forEach((operation, type) => {\\n nodes_for_context.push(operation);\\n });\\n return nodes_for_context;\\n } else {\\n return [];\\n }\\n }\\n registeredOperation(context, operationType) {\\n const current_operations_for_context = this._operation_register.get(context);\\n if (current_operations_for_context) {\\n operationType = OperationsRegister.filterType(operationType);\\n return current_operations_for_context.get(operationType);\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/expressions/_BaseRegister.ts\\nvar BaseExpressionRegister = class {\\n constructor() {\\n this._methods_names = [];\\n this._methods_by_name = new Map();\\n }\\n register(expression, name) {\\n this._methods_names.push(name);\\n this._methods_by_name.set(name, expression);\\n }\\n getMethod(name) {\\n return this._methods_by_name.get(name);\\n }\\n availableMethods() {\\n return this._methods_names;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/expressions/ExpressionRegister.ts\\nvar ExpressionRegister = class extends BaseExpressionRegister {\\n getMethod(name) {\\n return super.getMethod(name);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/modules/_BaseRegister.ts\\nvar BaseModulesRegister = class {\\n constructor() {\\n this._module_by_name = new Map();\\n }\\n register(name, module) {\\n this._module_by_name.set(name, module);\\n }\\n moduleNames() {\\n const list = [];\\n this._module_by_name.forEach((module, moduleName) => {\\n list.push(moduleName);\\n });\\n return list;\\n }\\n module(moduleName) {\\n return this._module_by_name.get(moduleName);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/modules/DynamicModulesRegister.ts\\nvar DynamicModulesRegister = class extends BaseModulesRegister {\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/assemblers/_BaseRegister.ts\\nvar AssemblerName;\\n(function(AssemblerName3) {\\n AssemblerName3[\\\\\\\"GL_MESH_BASIC\\\\\\\"] = \\\\\\\"GL_MESH_BASIC\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_MESH_LAMBERT\\\\\\\"] = \\\\\\\"GL_MESH_LAMBERT\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_MESH_STANDARD\\\\\\\"] = \\\\\\\"GL_MESH_STANDARD\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_MESH_PHONG\\\\\\\"] = \\\\\\\"GL_MESH_PHONG\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_MESH_PHYSICAL\\\\\\\"] = \\\\\\\"GL_MESH_PHYSICAL\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_PARTICLES\\\\\\\"] = \\\\\\\"GL_PARTICLES\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_POINTS\\\\\\\"] = \\\\\\\"GL_POINTS\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_LINE\\\\\\\"] = \\\\\\\"GL_LINE\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_TEXTURE\\\\\\\"] = \\\\\\\"GL_TEXTURE\\\\\\\";\\n AssemblerName3[\\\\\\\"GL_VOLUME\\\\\\\"] = \\\\\\\"GL_VOLUME\\\\\\\";\\n})(AssemblerName || (AssemblerName = {}));\\nvar BaseAssemblersRegister = class {\\n constructor() {\\n this._controller_assembler_by_name = new Map();\\n }\\n register(name, controller, assembler) {\\n this._controller_assembler_by_name.set(name, {\\n controller,\\n assembler\\n });\\n }\\n unregister(name) {\\n this._controller_assembler_by_name.delete(name);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/assemblers/AssemblersRegistry.ts\\nvar AssemblersRegister = class extends BaseAssemblersRegister {\\n assembler(node, name) {\\n const pair = this._controller_assembler_by_name.get(name);\\n if (pair) {\\n const controller = pair.controller;\\n const assembler = pair.assembler;\\n return new controller(node, assembler);\\n }\\n return pair;\\n }\\n unregister(name) {\\n const pair = this._controller_assembler_by_name.get(name);\\n super.unregister(name);\\n return pair;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/plugins/PluginsRegister.ts\\nvar PluginsRegister = class {\\n constructor(poly) {\\n this.poly = poly;\\n this._plugins_by_name = new Map();\\n this._plugin_name_by_node_context_by_type = new Map();\\n this._plugin_name_by_operation_context_by_type = new Map();\\n }\\n register(plugin) {\\n this._current_plugin = plugin;\\n this._plugins_by_name.set(plugin.name(), plugin);\\n plugin.init(this.poly);\\n this._current_plugin = void 0;\\n }\\n pluginByName(pluginName) {\\n return this._plugins_by_name.get(pluginName);\\n }\\n registerNode(node) {\\n if (!this._current_plugin) {\\n return;\\n }\\n const context = node.context();\\n const type = node.type();\\n let map_for_context = this._plugin_name_by_node_context_by_type.get(context);\\n if (!map_for_context) {\\n map_for_context = new Map();\\n this._plugin_name_by_node_context_by_type.set(context, map_for_context);\\n }\\n map_for_context.set(type, this._current_plugin.name());\\n }\\n registerOperation(operation) {\\n if (!this._current_plugin) {\\n return;\\n }\\n const context = operation.context();\\n const type = operation.type();\\n let map_for_context = this._plugin_name_by_operation_context_by_type.get(context);\\n if (!map_for_context) {\\n map_for_context = new Map();\\n this._plugin_name_by_operation_context_by_type.set(context, map_for_context);\\n }\\n map_for_context.set(type, this._current_plugin.name());\\n }\\n toJson() {\\n const data = {\\n plugins: {},\\n nodes: {},\\n operations: {}\\n };\\n this._plugins_by_name.forEach((plugin, name) => {\\n data.plugins[name] = plugin.toJSON();\\n });\\n this._plugin_name_by_node_context_by_type.forEach((map_for_context, context) => {\\n data.nodes[context] = {};\\n map_for_context.forEach((plugin_name, type) => {\\n data.nodes[context][type] = plugin_name;\\n });\\n });\\n this._plugin_name_by_operation_context_by_type.forEach((map_for_context, context) => {\\n data.operations[context] = {};\\n map_for_context.forEach((plugin_name, type) => {\\n data.operations[context][type] = plugin_name;\\n });\\n });\\n return data;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/cameras/CamerasRegister.ts\\nvar CamerasRegister = class {\\n constructor(poly) {\\n this._camera_types = [];\\n }\\n register(node) {\\n const node_type = node.type();\\n if (!this._camera_types.includes(node_type)) {\\n this._camera_types.push(node_type);\\n }\\n }\\n registeredTypes() {\\n return this._camera_types;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/BlobUtils.ts\\nfunction createObjectURL(fileOrBlob) {\\n const urlCreator = window.URL || window.webkitURL;\\n return urlCreator.createObjectURL(fileOrBlob);\\n}\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/BlobsController.ts\\nvar BlobsController = class {\\n constructor() {\\n this._blobUrlsByStoredUrl = new Map();\\n this._blobsByStoredUrl = new Map();\\n this._blobDataByNodeId = new Map();\\n this._globalBlobsByStoredUrl = new Map();\\n }\\n registerBlobUrl(data) {\\n if (!Poly.playerMode()) {\\n return;\\n }\\n this._blobUrlsByStoredUrl.set(data.storedUrl, data.blobUrl);\\n }\\n deregisterUrl(url) {\\n this._blobUrlsByStoredUrl.delete(url);\\n }\\n blobUrl(storedUrl) {\\n return this._blobUrlsByStoredUrl.get(storedUrl);\\n }\\n clear() {\\n this._blobUrlsByStoredUrl.clear();\\n this._blobsByStoredUrl.clear();\\n this._blobDataByNodeId.clear();\\n }\\n _clearBlobForNode(node) {\\n const blobData = this._blobDataByNodeId.get(node.graphNodeId());\\n if (blobData) {\\n this._blobsByStoredUrl.delete(blobData.storedUrl);\\n this._blobUrlsByStoredUrl.delete(blobData.storedUrl);\\n }\\n this._blobDataByNodeId.delete(node.graphNodeId());\\n }\\n _assignBlobToNode(node, blobData) {\\n this._clearBlobForNode(node);\\n this._blobDataByNodeId.set(node.graphNodeId(), {\\n storedUrl: blobData.storedUrl,\\n fullUrl: blobData.fullUrl\\n });\\n }\\n async fetchBlobGlobal(options) {\\n if (Poly.playerMode()) {\\n return {};\\n }\\n try {\\n const existingBlob = this._blobUrlsByStoredUrl.get(options.storedUrl);\\n if (existingBlob) {\\n return {};\\n }\\n const remapedUrl = Poly.assetUrls.remapedUrl(options.fullUrl);\\n const response = await fetch(remapedUrl || options.fullUrl);\\n if (response.ok) {\\n const blob = await response.blob();\\n this._blobsByStoredUrl.set(options.storedUrl, blob);\\n this._blobUrlsByStoredUrl.set(options.storedUrl, this.createBlobUrl(blob));\\n this._globalBlobsByStoredUrl.set(options.storedUrl, blob);\\n return {\\n blobData: {\\n storedUrl: options.storedUrl,\\n fullUrl: options.fullUrl\\n }\\n };\\n } else {\\n return {error: `failed to fetch ${options.fullUrl}`};\\n }\\n } catch (err) {\\n return {error: `failed to fetch ${options.fullUrl}`};\\n }\\n }\\n async fetchBlobForNode(options) {\\n if (Poly.playerMode()) {\\n return {};\\n }\\n try {\\n const existingBlob = this._blobUrlsByStoredUrl.get(options.storedUrl);\\n if (existingBlob) {\\n return {};\\n }\\n const remapedUrl = Poly.assetUrls.remapedUrl(options.fullUrl);\\n const response = await fetch(remapedUrl || options.fullUrl);\\n if (response.ok) {\\n const blob = await response.blob();\\n this._blobsByStoredUrl.set(options.storedUrl, blob);\\n this._blobUrlsByStoredUrl.set(options.storedUrl, this.createBlobUrl(blob));\\n this._scene = options.node.scene();\\n this._assignBlobToNode(options.node, {\\n storedUrl: options.storedUrl,\\n fullUrl: options.fullUrl\\n });\\n return {\\n blobData: {\\n storedUrl: options.storedUrl,\\n fullUrl: options.fullUrl\\n }\\n };\\n } else {\\n return {error: `failed to fetch ${options.fullUrl}`};\\n }\\n } catch (err) {\\n return {error: `failed to fetch ${options.fullUrl}`};\\n }\\n }\\n forEachBlob(callback) {\\n this._blobDataByNodeId.forEach((blobData, nodeGraphNodeId) => {\\n if (this._scene) {\\n const node = this._scene.graph.nodeFromId(nodeGraphNodeId);\\n if (node) {\\n const {storedUrl} = blobData;\\n const blob = this._blobsByStoredUrl.get(storedUrl);\\n if (blob) {\\n callback(blob, storedUrl);\\n }\\n }\\n }\\n });\\n let storedUrls = [];\\n const blobsByStoreUrl = new Map();\\n this._globalBlobsByStoredUrl.forEach((blob, storedUrl) => {\\n storedUrls.push(storedUrl);\\n blobsByStoreUrl.set(storedUrl, blob);\\n });\\n storedUrls = storedUrls.sort();\\n storedUrls.forEach((storedUrl) => {\\n const blob = this._globalBlobsByStoredUrl.get(storedUrl);\\n if (blob) {\\n callback(blob, storedUrl);\\n }\\n });\\n }\\n createBlobUrl(blob) {\\n return createObjectURL(blob);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/AssetUrlsController.ts\\nvar AssetUrlsController = class {\\n setMap(map) {\\n this._map = map;\\n }\\n remapedUrl(url) {\\n if (!this._map) {\\n return;\\n }\\n const elements = url.split(\\\\\\\"?\\\\\\\");\\n const preQuery = elements[0];\\n const query = elements[1];\\n const remapedUrl = this._map[preQuery];\\n if (remapedUrl) {\\n if (query) {\\n return `${remapedUrl}?${query}`;\\n } else {\\n return remapedUrl;\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/DomEffects.ts\\nvar DomEffects = class {\\n static fadeOut(element) {\\n return new Promise((resolve) => {\\n const fadeEffect = setInterval(() => {\\n if (!element.style.opacity) {\\n element.style.opacity = \\\\\\\"1\\\\\\\";\\n }\\n const opacity = parseFloat(element.style.opacity);\\n if (opacity > 0) {\\n element.style.opacity = `${opacity - 0.05}`;\\n } else {\\n resolve();\\n clearInterval(fadeEffect);\\n }\\n }, 20);\\n });\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/io/self_contained/Common.ts\\nvar SelfContainedFileName;\\n(function(SelfContainedFileName2) {\\n SelfContainedFileName2[\\\\\\\"CODE\\\\\\\"] = \\\\\\\"code.json\\\\\\\";\\n SelfContainedFileName2[\\\\\\\"EDITOR\\\\\\\"] = \\\\\\\"editor.json\\\\\\\";\\n SelfContainedFileName2[\\\\\\\"ASSETS\\\\\\\"] = \\\\\\\"assets.json\\\\\\\";\\n SelfContainedFileName2[\\\\\\\"POLYGONJS\\\\\\\"] = \\\\\\\"js/all.js\\\\\\\";\\n SelfContainedFileName2[\\\\\\\"POLY_CONFIG\\\\\\\"] = \\\\\\\"js/polyConfig.js\\\\\\\";\\n SelfContainedFileName2[\\\\\\\"JS_FILES\\\\\\\"] = \\\\\\\"js_files.json\\\\\\\";\\n SelfContainedFileName2[\\\\\\\"POSTER\\\\\\\"] = \\\\\\\"poster.png\\\\\\\";\\n})(SelfContainedFileName || (SelfContainedFileName = {}));\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/SelfContainedSceneLoader.ts\\nvar SelfContainedScenesLoader = class {\\n markAsLoaded(callback, sceneJsonImporterContructor) {\\n this._sceneJsonImporterContructor = sceneJsonImporterContructor;\\n callback();\\n }\\n load(map) {\\n if (!this._sceneJsonImporterContructor) {\\n return;\\n }\\n const elements = [];\\n map.forEach((data, element) => {\\n elements.push(element);\\n });\\n for (let element of elements) {\\n const data = map.get(element);\\n if (data) {\\n this._loadElement(element, data, this._sceneJsonImporterContructor);\\n map.delete(element);\\n }\\n }\\n }\\n async _loadElement(element, viewerData, sceneJsonImporterContructor) {\\n const {sceneData, assetsManifest, unzippedData} = viewerData;\\n const storedUrls = Object.keys(assetsManifest);\\n for (let storedUrl of storedUrls) {\\n const assetUrl = assetsManifest[storedUrl];\\n const assetUintArray = unzippedData[`assets/${assetUrl}`];\\n if (!assetUintArray) {\\n console.error(storedUrl, assetUintArray);\\n return;\\n }\\n const assetBlob = new Blob([assetUintArray]);\\n const blobUrl = Poly.blobs.createBlobUrl(assetBlob);\\n const blobUrlData = {\\n storedUrl,\\n blobUrl\\n };\\n Poly.blobs.registerBlobUrl(blobUrlData);\\n }\\n Poly.setPlayerMode(true);\\n Poly.libs.setRoot(null);\\n const polyConfigId = `${Math.random()}`.replace(\\\\\\\".\\\\\\\", \\\\\\\"_\\\\\\\");\\n const ids = {\\n Poly: `___POLY_polyConfig_configurePolygonjs_${polyConfigId}`,\\n scriptElementId: `___POLY_polyConfig_scriptElement_${polyConfigId}`,\\n loadSceneArgs: `___POLY_polyConfig_loadSceneArgs_${polyConfigId}`\\n };\\n window[ids.Poly] = Poly;\\n const method = this._loadScene.bind(this);\\n const loadSceneArgs = {\\n method,\\n element,\\n sceneData,\\n sceneJsonImporterContructor\\n };\\n window[ids.loadSceneArgs] = loadSceneArgs;\\n const polyConfigLoaded = this._loadPolyConfig(ids, unzippedData);\\n if (polyConfigLoaded) {\\n return;\\n }\\n this._loadScene(element, sceneData, sceneJsonImporterContructor);\\n }\\n _loadPolyConfig(ids, unzippedData) {\\n const polyConfigArray = unzippedData[SelfContainedFileName.POLY_CONFIG];\\n if (!polyConfigArray) {\\n return false;\\n }\\n const polyConfigUrl = this._createJsBlob(polyConfigArray, \\\\\\\"polyConfig\\\\\\\");\\n let script = document.getElementById(ids.scriptElementId);\\n const lines = [];\\n lines.push(`import {configurePolygonjs, configureScene} from '${polyConfigUrl}';`);\\n lines.push(`configurePolygonjs(window.${ids.Poly});`);\\n lines.push(`window.${ids.loadSceneArgs}.method(window.${ids.loadSceneArgs}.element, window.${ids.loadSceneArgs}.sceneData, window.${ids.loadSceneArgs}.sceneJsonImporterContructor, configureScene);`);\\n lines.push(`delete window.${ids.loadSceneArgs};`);\\n if (!script) {\\n script = document.createElement(\\\\\\\"script\\\\\\\");\\n script.setAttribute(\\\\\\\"type\\\\\\\", \\\\\\\"module\\\\\\\");\\n script.text = lines.join(\\\\\\\"\\\\n\\\\\\\");\\n document.body.append(script);\\n }\\n return true;\\n }\\n async _loadScene(element, sceneData, sceneJsonImporterContructor, configureScene2) {\\n this._fadeOutPoster(element);\\n const importer = new sceneJsonImporterContructor(sceneData);\\n const scene = await importer.scene();\\n if (configureScene2) {\\n configureScene2(scene);\\n }\\n const cameraNode = scene.mainCameraNode();\\n if (!cameraNode) {\\n console.warn(\\\\\\\"no master camera found\\\\\\\");\\n return;\\n }\\n const viewer = cameraNode.createViewer(element);\\n scene.play();\\n element.scene = scene;\\n element.viewer = viewer;\\n }\\n _fadeOutPoster(element) {\\n const posterElement = element.firstElementChild;\\n if (posterElement) {\\n posterElement.style.pointerEvents = \\\\\\\"none\\\\\\\";\\n DomEffects.fadeOut(posterElement).then(() => {\\n posterElement.parentElement?.removeChild(posterElement);\\n });\\n }\\n }\\n _createJsBlob(array, filename) {\\n const blob = new Blob([array]);\\n const file = new File([blob], `${filename}.js`, {type: \\\\\\\"application/javascript\\\\\\\"});\\n return createObjectURL(file);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/PerformanceController.ts\\nvar PolyPerformanceformanceController = class {\\n setPerformanceManager(p) {\\n this._performanceManager = p;\\n }\\n performanceManager() {\\n return this._performanceManager || window.performance;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/Poly.ts\\nvar PolyEngine = class {\\n constructor() {\\n this.renderersController = new RenderersController();\\n this.nodesRegister = new NodesRegister(this);\\n this.operationsRegister = new OperationsRegister(this);\\n this.expressionsRegister = new ExpressionRegister();\\n this.modulesRegister = new DynamicModulesRegister();\\n this.assemblersRegister = new AssemblersRegister();\\n this.pluginsRegister = new PluginsRegister(this);\\n this.camerasRegister = new CamerasRegister(this);\\n this.blobs = new BlobsController();\\n this.assetUrls = new AssetUrlsController();\\n this.selfContainedScenesLoader = new SelfContainedScenesLoader();\\n this.performance = new PolyPerformanceformanceController();\\n this.scenesByUuid = {};\\n this._player_mode = true;\\n this._logger = null;\\n }\\n static _instance_() {\\n if (window.__POLYGONJS_POLY_INSTANCE__) {\\n return window.__POLYGONJS_POLY_INSTANCE__;\\n } else {\\n const instance = new PolyEngine();\\n window.__POLYGONJS_POLY_INSTANCE__ = instance;\\n return window.__POLYGONJS_POLY_INSTANCE__;\\n }\\n }\\n setPlayerMode(mode) {\\n this._player_mode = mode;\\n }\\n playerMode() {\\n return this._player_mode;\\n }\\n registerNode(node, tab_menu_category, options) {\\n this.nodesRegister.register(node, tab_menu_category, options);\\n }\\n registerOperation(operation) {\\n this.operationsRegister.register(operation);\\n }\\n registerCamera(node) {\\n this.camerasRegister.register(node);\\n }\\n registerPlugin(plugin) {\\n this.pluginsRegister.register(plugin);\\n }\\n registeredNodes(parent_context, type) {\\n return this.nodesRegister.registeredNodes(parent_context, type);\\n }\\n registeredOperation(parent_context, operation_type) {\\n return this.operationsRegister.registeredOperation(parent_context, operation_type);\\n }\\n registeredCameraTypes() {\\n return this.camerasRegister.registeredTypes();\\n }\\n inWorkerThread() {\\n return false;\\n }\\n desktopController() {\\n }\\n get libs() {\\n return this._libs_controller = this._libs_controller || new PolyLibsController();\\n }\\n setEnv(env) {\\n this._env = env;\\n }\\n env() {\\n return this._env;\\n }\\n setLogger(logger) {\\n this._logger = logger;\\n }\\n log(message, ...optionalParams) {\\n this._logger?.log(...[message, ...optionalParams]);\\n }\\n warn(message, ...optionalParams) {\\n this._logger?.warn(...[message, ...optionalParams]);\\n }\\n error(message, ...optionalParams) {\\n this._logger?.error(...[message, ...optionalParams]);\\n }\\n};\\nvar Poly = PolyEngine._instance_();\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/graph/DirtyController.ts\\nvar DirtyController = class {\\n constructor(node) {\\n this.node = node;\\n this._dirty_count = 0;\\n this._dirty = true;\\n }\\n dispose() {\\n this._cached_successors = void 0;\\n this._post_dirty_hooks = void 0;\\n this._post_dirty_hook_names = void 0;\\n }\\n isDirty() {\\n return this._dirty === true;\\n }\\n dirtyTimestamp() {\\n return this._dirty_timestamp;\\n }\\n dirtyCount() {\\n return this._dirty_count;\\n }\\n addPostDirtyHook(name, method) {\\n this._post_dirty_hook_names = this._post_dirty_hook_names || [];\\n this._post_dirty_hooks = this._post_dirty_hooks || [];\\n if (!this._post_dirty_hook_names.includes(name)) {\\n this._post_dirty_hook_names.push(name);\\n this._post_dirty_hooks.push(method);\\n } else {\\n console.warn(`hook with name ${name} already exists`, this.node);\\n }\\n }\\n removePostDirtyHook(name) {\\n if (this._post_dirty_hook_names && this._post_dirty_hooks) {\\n const index = this._post_dirty_hook_names.indexOf(name);\\n if (index >= 0) {\\n this._post_dirty_hook_names.splice(index, 1);\\n this._post_dirty_hooks.splice(index, 1);\\n }\\n }\\n }\\n hasHook(name) {\\n if (this._post_dirty_hook_names) {\\n return this._post_dirty_hook_names.includes(name);\\n }\\n return false;\\n }\\n removeDirtyState() {\\n this._dirty = false;\\n }\\n setForbiddenTriggerNodes(nodes) {\\n this._forbidden_trigger_nodes = nodes.map((n) => n.graphNodeId());\\n }\\n setDirty(original_trigger_graph_node, propagate) {\\n if (propagate == null) {\\n propagate = true;\\n }\\n if (original_trigger_graph_node && this._forbidden_trigger_nodes && this._forbidden_trigger_nodes.includes(original_trigger_graph_node.graphNodeId())) {\\n return;\\n }\\n if (original_trigger_graph_node == null) {\\n original_trigger_graph_node = this.node;\\n }\\n this._dirty = true;\\n const performance2 = Poly.performance.performanceManager();\\n this._dirty_timestamp = performance2.now();\\n this._dirty_count += 1;\\n this.runPostDirtyHooks(original_trigger_graph_node);\\n if (propagate === true) {\\n this.setSuccessorsDirty(original_trigger_graph_node);\\n }\\n }\\n runPostDirtyHooks(original_trigger_graph_node) {\\n if (this._post_dirty_hooks) {\\n const cooker = this.node.scene().cooker;\\n if (cooker.blocked) {\\n cooker.enqueue(this.node, original_trigger_graph_node);\\n } else {\\n for (let hook of this._post_dirty_hooks) {\\n hook(original_trigger_graph_node);\\n }\\n }\\n }\\n }\\n setSuccessorsDirty(original_trigger_graph_node) {\\n const propagate = false;\\n this._cached_successors = this._cached_successors || this.node.graphAllSuccessors();\\n for (let successor of this._cached_successors) {\\n successor.dirtyController.setDirty(original_trigger_graph_node, propagate);\\n }\\n }\\n clearSuccessorsCache() {\\n this._cached_successors = void 0;\\n }\\n clearSuccessorsCacheWithPredecessors() {\\n this.clearSuccessorsCache();\\n for (let predecessor of this.node.graphAllPredecessors()) {\\n predecessor.dirtyController.clearSuccessorsCache();\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/graph/CoreGraphNode.ts\\nvar CoreGraphNode = class {\\n constructor(_scene, _name) {\\n this._scene = _scene;\\n this._name = _name;\\n this._dirty_controller = new DirtyController(this);\\n this._graph_node_id = _scene.graph.nextId();\\n _scene.graph.addNode(this);\\n this._graph = _scene.graph;\\n }\\n dispose() {\\n this._dirty_controller.dispose();\\n this.graphRemove();\\n }\\n name() {\\n return this._name;\\n }\\n setName(name) {\\n this._name = name;\\n }\\n scene() {\\n return this._scene;\\n }\\n graphNodeId() {\\n return this._graph_node_id;\\n }\\n get dirtyController() {\\n return this._dirty_controller;\\n }\\n setDirty(trigger) {\\n trigger = trigger || this;\\n this._dirty_controller.setDirty(trigger);\\n }\\n setSuccessorsDirty(trigger) {\\n this._dirty_controller.setSuccessorsDirty(trigger);\\n }\\n removeDirtyState() {\\n this._dirty_controller.removeDirtyState();\\n }\\n isDirty() {\\n return this._dirty_controller.isDirty();\\n }\\n addPostDirtyHook(name, callback) {\\n this._dirty_controller.addPostDirtyHook(name, callback);\\n }\\n graphRemove() {\\n this._graph.removeNode(this);\\n }\\n addGraphInput(src, check_if_graph_has_cycle = true) {\\n return this._graph.connect(src, this, check_if_graph_has_cycle);\\n }\\n removeGraphInput(src) {\\n this._graph.disconnect(src, this);\\n }\\n graphDisconnectPredecessors() {\\n this._graph.disconnectPredecessors(this);\\n }\\n graphDisconnectSuccessors() {\\n this._graph.disconnectSuccessors(this);\\n }\\n graphPredecessorIds() {\\n return this._graph.predecessorIds(this._graph_node_id) || [];\\n }\\n graphPredecessors() {\\n return this._graph.predecessors(this);\\n }\\n graphSuccessors() {\\n return this._graph.successors(this);\\n }\\n graphAllPredecessors() {\\n return this._graph.allPredecessors(this);\\n }\\n graphAllSuccessors() {\\n return this._graph.allSuccessors(this);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/NodeEvent.ts\\nvar NodeEvent;\\n(function(NodeEvent2) {\\n NodeEvent2[\\\\\\\"CREATED\\\\\\\"] = \\\\\\\"node_created\\\\\\\";\\n NodeEvent2[\\\\\\\"DELETED\\\\\\\"] = \\\\\\\"node_deleted\\\\\\\";\\n NodeEvent2[\\\\\\\"NAME_UPDATED\\\\\\\"] = \\\\\\\"node_name_update\\\\\\\";\\n NodeEvent2[\\\\\\\"OVERRIDE_CLONABLE_STATE_UPDATE\\\\\\\"] = \\\\\\\"node_override_clonable_state_update\\\\\\\";\\n NodeEvent2[\\\\\\\"NAMED_OUTPUTS_UPDATED\\\\\\\"] = \\\\\\\"node_named_outputs_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"NAMED_INPUTS_UPDATED\\\\\\\"] = \\\\\\\"node_named_inputs_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"INPUTS_UPDATED\\\\\\\"] = \\\\\\\"node_inputs_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"PARAMS_UPDATED\\\\\\\"] = \\\\\\\"node_params_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"UI_DATA_POSITION_UPDATED\\\\\\\"] = \\\\\\\"node_ui_data_position_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"UI_DATA_COMMENT_UPDATED\\\\\\\"] = \\\\\\\"node_ui_data_comment_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"ERROR_UPDATED\\\\\\\"] = \\\\\\\"node_error_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"FLAG_BYPASS_UPDATED\\\\\\\"] = \\\\\\\"bypass_flag_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"FLAG_DISPLAY_UPDATED\\\\\\\"] = \\\\\\\"display_flag_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"FLAG_OPTIMIZE_UPDATED\\\\\\\"] = \\\\\\\"optimize_flag_updated\\\\\\\";\\n NodeEvent2[\\\\\\\"SELECTION_UPDATED\\\\\\\"] = \\\\\\\"selection_updated\\\\\\\";\\n})(NodeEvent || (NodeEvent = {}));\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/Type.ts\\nvar CoreType = class {\\n static isNumber(value) {\\n return typeof value == \\\\\\\"number\\\\\\\";\\n }\\n static isVector(value) {\\n return value instanceof Vector2 || value instanceof Vector3 || value instanceof Vector4;\\n }\\n static isString(value) {\\n return typeof value == \\\\\\\"string\\\\\\\";\\n }\\n static isBoolean(value) {\\n return value === true || value === false;\\n }\\n static isNaN(value) {\\n return isNaN(value);\\n }\\n static isArray(value) {\\n return Array.isArray(value);\\n }\\n static isObject(value) {\\n var type = typeof value;\\n return value != null && (type == \\\\\\\"object\\\\\\\" || type == \\\\\\\"function\\\\\\\");\\n }\\n};\\nfunction isBooleanTrue(value) {\\n return value;\\n}\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/UIData.ts\\nvar UIData = class {\\n constructor(node, x = 0, y = 0) {\\n this.node = node;\\n this._position = new Vector2();\\n this._width = 50;\\n this._color = new Color(0.75, 0.75, 0.75);\\n this._layout_vertical = true;\\n this._json = {\\n x: 0,\\n y: 0\\n };\\n this._position.x = x;\\n this._position.y = y;\\n }\\n setComment(comment) {\\n this._comment = comment;\\n this.node.emit(NodeEvent.UI_DATA_COMMENT_UPDATED);\\n }\\n comment() {\\n return this._comment;\\n }\\n setColor(color) {\\n this._color = color;\\n }\\n color() {\\n return this._color;\\n }\\n setLayoutHorizontal() {\\n this._layout_vertical = false;\\n }\\n isLayoutVertical() {\\n return this._layout_vertical;\\n }\\n copy(ui_data) {\\n this._position.copy(ui_data.position());\\n this._color.copy(ui_data.color());\\n }\\n position() {\\n return this._position;\\n }\\n setPosition(new_position, y = 0) {\\n if (CoreType.isNumber(new_position)) {\\n const x = new_position;\\n this._position.set(x, y);\\n } else {\\n this._position.copy(new_position);\\n }\\n this.node.emit(NodeEvent.UI_DATA_POSITION_UPDATED);\\n }\\n translate(offset, snap = false) {\\n this._position.add(offset);\\n if (snap) {\\n this._position.x = Math.round(this._position.x);\\n this._position.y = Math.round(this._position.y);\\n }\\n this.node.emit(NodeEvent.UI_DATA_POSITION_UPDATED);\\n }\\n toJSON() {\\n this._json.x = this._position.x;\\n this._json.y = this._position.y;\\n this._json.comment = this._comment;\\n return this._json;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/flags/Base.ts\\nvar BaseFlag = class {\\n constructor(node) {\\n this.node = node;\\n this._state = true;\\n this._hooks = null;\\n }\\n onUpdate(hook) {\\n this._hooks = this._hooks || [];\\n this._hooks.push(hook);\\n }\\n _on_update() {\\n }\\n set(new_state) {\\n if (this._state != new_state) {\\n this._state = new_state;\\n this._on_update();\\n this.runHooks();\\n }\\n }\\n active() {\\n return this._state;\\n }\\n toggle() {\\n this.set(!this._state);\\n }\\n runHooks() {\\n if (this._hooks) {\\n for (let hook of this._hooks) {\\n hook();\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/flags/Bypass.ts\\nvar BypassFlag = class extends BaseFlag {\\n constructor() {\\n super(...arguments);\\n this._state = false;\\n }\\n _on_update() {\\n this.node.emit(NodeEvent.FLAG_BYPASS_UPDATED);\\n this.node.setDirty();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/flags/Display.ts\\nvar DisplayFlag = class extends BaseFlag {\\n _on_update() {\\n this.node.emit(NodeEvent.FLAG_DISPLAY_UPDATED);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/flags/Optimize.ts\\nvar OptimizeFlag = class extends BaseFlag {\\n constructor() {\\n super(...arguments);\\n this._state = false;\\n }\\n _on_update() {\\n this.node.emit(NodeEvent.FLAG_OPTIMIZE_UPDATED);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/FlagsController.ts\\nvar FlagsController = class {\\n constructor(node) {\\n this.node = node;\\n }\\n hasDisplay() {\\n return false;\\n }\\n hasBypass() {\\n return false;\\n }\\n hasOptimize() {\\n return false;\\n }\\n};\\nfunction Display(Base) {\\n return class Mixin extends Base {\\n constructor() {\\n super(...arguments);\\n this.display = new DisplayFlag(this.node);\\n }\\n hasDisplay() {\\n return true;\\n }\\n };\\n}\\nfunction Bypass(Base) {\\n return class Mixin extends Base {\\n constructor() {\\n super(...arguments);\\n this.bypass = new BypassFlag(this.node);\\n }\\n hasBypass() {\\n return true;\\n }\\n };\\n}\\nfunction Optimize(Base) {\\n return class Mixin extends Base {\\n constructor() {\\n super(...arguments);\\n this.optimize = new OptimizeFlag(this.node);\\n }\\n hasOptimize() {\\n return true;\\n }\\n };\\n}\\nvar FlagsControllerD = class extends Display(FlagsController) {\\n};\\nvar FlagsControllerB = class extends Bypass(FlagsController) {\\n};\\nvar FlagsControllerDB = class extends Bypass(Display(FlagsController)) {\\n};\\nvar FlagsControllerBO = class extends Optimize(Bypass(FlagsController)) {\\n};\\nvar FlagsControllerDBO = class extends Optimize(Bypass(Display(FlagsController))) {\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/states/Base.ts\\nvar BaseState = class {\\n constructor(node) {\\n this.node = node;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/states/TimeDependent.ts\\nvar TimeDependentState = class extends BaseState {\\n active() {\\n return this.paramsTimeDependent() || this.inputsTimeDependent();\\n }\\n paramsTimeDependent() {\\n const param_names = this.node.params.names;\\n for (let param_name of param_names) {\\n const param = this.node.params.get(param_name);\\n if (param && param.states.timeDependent.active()) {\\n return true;\\n }\\n }\\n return false;\\n }\\n inputsTimeDependent() {\\n const inputs = this.node.io.inputs.inputs();\\n for (let input of inputs) {\\n if (input && input.states.timeDependent.active()) {\\n return true;\\n }\\n }\\n return false;\\n }\\n forceTimeDependent() {\\n const predecessor_ids = this.node.graphPredecessors().map((n) => n.graphNodeId());\\n const frame_node = this.node.scene().timeController.graphNode;\\n if (!predecessor_ids.includes(frame_node.graphNodeId())) {\\n this.node.addGraphInput(frame_node, false);\\n }\\n }\\n unforceTimeDependent() {\\n const frame_node = this.node.scene().timeController.graphNode;\\n this.node.removeGraphInput(frame_node);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/states/Error.ts\\nvar NodeErrorState = class extends BaseState {\\n set(message) {\\n if (this._message != message) {\\n if (message) {\\n Poly.error(`[${this.node.path()}] error: '${message}'`);\\n }\\n this._message = message;\\n this.onUpdate();\\n }\\n }\\n message() {\\n return this._message;\\n }\\n clear() {\\n this.set(void 0);\\n }\\n active() {\\n return this._message != null;\\n }\\n onUpdate() {\\n if (this._message != null) {\\n this.node._setContainer(null, `from error '${this._message}'`);\\n }\\n this.node.emit(NodeEvent.ERROR_UPDATED);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/StatesController.ts\\nvar StatesController = class {\\n constructor(node) {\\n this.node = node;\\n this.timeDependent = new TimeDependentState(this.node);\\n this.error = new NodeErrorState(this.node);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/NameController.ts\\nvar NameController = class {\\n constructor(node) {\\n this.node = node;\\n this._graph_node = new CoreGraphNode(node.scene(), \\\\\\\"node_name_controller\\\\\\\");\\n }\\n dispose() {\\n this._graph_node.dispose();\\n this._on_set_name_hooks = void 0;\\n this._on_set_fullPath_hooks = void 0;\\n }\\n get graph_node() {\\n return this._graph_node;\\n }\\n static base_name(node) {\\n let base = node.type();\\n const last_char = base[base.length - 1];\\n if (!CoreType.isNaN(parseInt(last_char))) {\\n base += \\\\\\\"_\\\\\\\";\\n }\\n return `${base}1`;\\n }\\n request_name_to_parent(new_name) {\\n const parent = this.node.parent();\\n if (parent && parent.childrenAllowed() && parent.childrenController) {\\n parent.childrenController.set_child_name(this.node, new_name);\\n } else {\\n console.warn(\\\\\\\"request_name_to_parent failed, no parent found\\\\\\\");\\n }\\n }\\n setName(new_name) {\\n if (new_name != this.node.name()) {\\n this.request_name_to_parent(new_name);\\n }\\n }\\n update_name_from_parent(new_name) {\\n this.node._set_core_name(new_name);\\n this.post_setName();\\n this.run_post_set_fullPath_hooks();\\n if (this.node.childrenAllowed()) {\\n const children = this.node.childrenController?.children();\\n if (children) {\\n for (let child_node of children) {\\n child_node.nameController.run_post_set_fullPath_hooks();\\n }\\n }\\n }\\n if (this.node.lifecycle.creationCompleted()) {\\n this.node.scene().missingExpressionReferencesController.checkForMissingReferences(this.node);\\n this.node.scene().expressionsController.regenerateReferringExpressions(this.node);\\n }\\n this.node.scene().referencesController.notifyNameUpdated(this.node);\\n this.node.emit(NodeEvent.NAME_UPDATED);\\n }\\n add_post_set_name_hook(hook) {\\n this._on_set_name_hooks = this._on_set_name_hooks || [];\\n this._on_set_name_hooks.push(hook);\\n }\\n add_post_set_fullPath_hook(hook) {\\n this._on_set_fullPath_hooks = this._on_set_fullPath_hooks || [];\\n this._on_set_fullPath_hooks.push(hook);\\n }\\n post_setName() {\\n if (this._on_set_name_hooks) {\\n for (let hook of this._on_set_name_hooks) {\\n hook();\\n }\\n }\\n }\\n run_post_set_fullPath_hooks() {\\n if (this._on_set_fullPath_hooks) {\\n for (let hook of this._on_set_fullPath_hooks) {\\n hook();\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/Walker.ts\\nvar TypedNodePathParamValue = class {\\n constructor(_path = \\\\\\\"\\\\\\\") {\\n this._path = _path;\\n this._node = null;\\n }\\n set_path(path) {\\n this._path = path;\\n }\\n set_node(node) {\\n this._node = node;\\n }\\n path() {\\n return this._path;\\n }\\n node() {\\n return this._node;\\n }\\n resolve(node_start) {\\n this._node = CoreWalker.findNode(node_start, this._path);\\n }\\n clone() {\\n const cloned = new TypedNodePathParamValue(this._path);\\n cloned.set_node(this._node);\\n return cloned;\\n }\\n nodeWithContext(context, error_state) {\\n const found_node = this.node();\\n if (!found_node) {\\n error_state?.set(`no node found at ${this.path()}`);\\n return;\\n }\\n const node_context = found_node.context();\\n if (node_context == context) {\\n return found_node;\\n } else {\\n error_state?.set(`expected ${context} node, but got a ${node_context}`);\\n return;\\n }\\n }\\n};\\nvar TypedParamPathParamValue = class {\\n constructor(_path = \\\\\\\"\\\\\\\") {\\n this._path = _path;\\n this._param = null;\\n }\\n set_path(path) {\\n this._path = path;\\n }\\n set_param(param) {\\n this._param = param;\\n }\\n path() {\\n return this._path;\\n }\\n param() {\\n return this._param;\\n }\\n resolve(node_start) {\\n this._param = CoreWalker.findParam(node_start, this._path);\\n }\\n clone() {\\n const cloned = new TypedParamPathParamValue(this._path);\\n cloned.set_param(this._param);\\n return cloned;\\n }\\n paramWithType(paramType, error_state) {\\n const foundParam = this.param();\\n if (!foundParam) {\\n error_state?.set(`no param found at ${this.path()}`);\\n return;\\n }\\n if (foundParam.type() == paramType) {\\n return foundParam;\\n } else {\\n error_state?.set(`expected ${paramType} node, but got a ${foundParam.type()}`);\\n return;\\n }\\n }\\n};\\nvar CoreWalker2 = class {\\n static split_parent_child(path) {\\n const elements = path.split(CoreWalker2.SEPARATOR).filter((e) => e.length > 0);\\n const child_path = elements.pop();\\n const parent_path = elements.join(CoreWalker2.SEPARATOR);\\n return {parent: parent_path, child: child_path};\\n }\\n static findNode(node_src, path, decomposed_path) {\\n if (!node_src) {\\n return null;\\n }\\n const elements = path.split(CoreWalker2.SEPARATOR).filter((e) => e.length > 0);\\n const first_element = elements[0];\\n let next_node = null;\\n if (path[0] === CoreWalker2.SEPARATOR) {\\n const path_from_root = path.substr(1);\\n next_node = this.findNode(node_src.root(), path_from_root, decomposed_path);\\n } else {\\n switch (first_element) {\\n case CoreWalker2.PARENT:\\n decomposed_path?.add_path_element(first_element);\\n next_node = node_src.parent();\\n break;\\n case CoreWalker2.CURRENT:\\n decomposed_path?.add_path_element(first_element);\\n next_node = node_src;\\n break;\\n default:\\n next_node = node_src.node(first_element);\\n if (next_node) {\\n decomposed_path?.add_node(first_element, next_node);\\n }\\n }\\n if (next_node != null && elements.length > 1) {\\n const remainder = elements.slice(1).join(CoreWalker2.SEPARATOR);\\n next_node = this.findNode(next_node, remainder, decomposed_path);\\n }\\n return next_node;\\n }\\n return next_node;\\n }\\n static findParam(node_src, path, decomposed_path) {\\n if (!node_src) {\\n return null;\\n }\\n const elements = path.split(CoreWalker2.SEPARATOR);\\n if (elements.length === 1) {\\n return node_src.params.get(elements[0]);\\n } else {\\n const node_path = elements.slice(0, +(elements.length - 2) + 1 || void 0).join(CoreWalker2.SEPARATOR);\\n const node = this.findNode(node_src, node_path, decomposed_path);\\n if (node != null) {\\n const param_name = elements[elements.length - 1];\\n const param = node.params.get(param_name);\\n if (decomposed_path && param) {\\n decomposed_path.add_node(param_name, param);\\n }\\n return param;\\n } else {\\n return null;\\n }\\n }\\n }\\n static relativePath(src_graph_node, dest_graph_node) {\\n const parent = this.closestCommonParent(src_graph_node, dest_graph_node);\\n if (!parent) {\\n return dest_graph_node.path();\\n } else {\\n const distance = this.distanceToParent(src_graph_node, parent);\\n let up = \\\\\\\"\\\\\\\";\\n if (distance > 0) {\\n let i = 0;\\n const ups = [];\\n while (i++ < distance) {\\n ups.push(CoreWalker2.PARENT);\\n }\\n up = ups.join(CoreWalker2.SEPARATOR) + CoreWalker2.SEPARATOR;\\n }\\n const parent_path_elements = parent.path().split(CoreWalker2.SEPARATOR).filter((e) => e.length > 0);\\n const dest_path_elements = dest_graph_node.path().split(CoreWalker2.SEPARATOR).filter((e) => e.length > 0);\\n const remaining_elements = [];\\n let cmptr = 0;\\n for (let dest_path_element of dest_path_elements) {\\n if (!parent_path_elements[cmptr]) {\\n remaining_elements.push(dest_path_element);\\n }\\n cmptr++;\\n }\\n const down = remaining_elements.join(CoreWalker2.SEPARATOR);\\n return `${up}${down}`;\\n }\\n }\\n static closestCommonParent(graph_node1, graph_node2) {\\n const parents1 = this.parents(graph_node1).reverse().concat([graph_node1]);\\n const parents2 = this.parents(graph_node2).reverse().concat([graph_node2]);\\n const min_depth = Math.min(parents1.length, parents2.length);\\n let found_parent = null;\\n for (let i = 0; i < min_depth; i++) {\\n if (parents1[i].graphNodeId() == parents2[i].graphNodeId()) {\\n found_parent = parents1[i];\\n }\\n }\\n return found_parent;\\n }\\n static parents(graph_node) {\\n const parents = [];\\n let parent = graph_node.parent();\\n while (parent) {\\n parents.push(parent);\\n parent = parent.parent();\\n }\\n return parents;\\n }\\n static distanceToParent(graph_node, dest) {\\n let distance = 0;\\n let current = graph_node;\\n const dest_id = dest.graphNodeId();\\n while (current && current.graphNodeId() != dest_id) {\\n distance += 1;\\n current = current.parent();\\n }\\n if (current && current.graphNodeId() == dest_id) {\\n return distance;\\n } else {\\n return -1;\\n }\\n }\\n static makeAbsolutePath(nodeSrc, path) {\\n if (path[0] == CoreWalker2.SEPARATOR) {\\n return path;\\n }\\n const pathElements = path.split(CoreWalker2.SEPARATOR);\\n const firstElement = pathElements.shift();\\n if (firstElement) {\\n switch (firstElement) {\\n case \\\\\\\"..\\\\\\\": {\\n const parent = nodeSrc.parent();\\n if (parent) {\\n if (parent == nodeSrc.scene().root()) {\\n return CoreWalker2.SEPARATOR + pathElements.join(CoreWalker2.SEPARATOR);\\n } else {\\n return this.makeAbsolutePath(parent, pathElements.join(CoreWalker2.SEPARATOR));\\n }\\n } else {\\n return null;\\n }\\n }\\n case \\\\\\\".\\\\\\\": {\\n return this.makeAbsolutePath(nodeSrc, pathElements.join(CoreWalker2.SEPARATOR));\\n }\\n default: {\\n return [nodeSrc.path(), path].join(CoreWalker2.SEPARATOR);\\n }\\n }\\n } else {\\n return nodeSrc.path();\\n }\\n }\\n};\\nvar CoreWalker = CoreWalker2;\\nCoreWalker.SEPARATOR = \\\\\\\"/\\\\\\\";\\nCoreWalker.DOT = \\\\\\\".\\\\\\\";\\nCoreWalker.CURRENT = CoreWalker2.DOT;\\nCoreWalker.PARENT = \\\\\\\"..\\\\\\\";\\nCoreWalker.CURRENT_WITH_SLASH = `${CoreWalker2.CURRENT}/`;\\nCoreWalker.PARENT_WITH_SLASH = `${CoreWalker2.PARENT}/`;\\nCoreWalker.NON_LETTER_PREFIXES = [CoreWalker2.SEPARATOR, CoreWalker2.DOT];\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/hierarchy/ParentController.ts\\nvar HierarchyParentController = class {\\n constructor(node) {\\n this.node = node;\\n this._parent = null;\\n }\\n parent() {\\n return this._parent;\\n }\\n setParent(parent) {\\n if (parent != this.node.parentController.parent()) {\\n this._parent = parent;\\n if (this._parent) {\\n this.node.nameController.request_name_to_parent(NameController.base_name(this.node));\\n }\\n }\\n }\\n firstAncestorWithContext(context) {\\n if (this._parent) {\\n if (this._parent.context() == context) {\\n return this._parent;\\n } else {\\n return this._parent.parentController.firstAncestorWithContext(context);\\n }\\n }\\n return null;\\n }\\n path(relative_to_parent) {\\n const separator = CoreWalker.SEPARATOR;\\n if (this._parent != null) {\\n if (this._parent == relative_to_parent) {\\n return this.node.name();\\n } else {\\n const parent_fullPath = this._parent.path(relative_to_parent);\\n if (parent_fullPath === separator) {\\n return parent_fullPath + this.node.name();\\n } else {\\n return parent_fullPath + separator + this.node.name();\\n }\\n }\\n } else {\\n return separator;\\n }\\n }\\n onSetParent() {\\n if (this._on_set_parent_hooks) {\\n for (let hook of this._on_set_parent_hooks) {\\n hook();\\n }\\n }\\n }\\n findNode(path) {\\n if (path == null) {\\n return null;\\n }\\n if (path == CoreWalker.CURRENT || path == CoreWalker.CURRENT_WITH_SLASH) {\\n return this.node;\\n }\\n if (path == CoreWalker.PARENT || path == CoreWalker.PARENT_WITH_SLASH) {\\n return this.node.parent();\\n }\\n const separator = CoreWalker.SEPARATOR;\\n if (path === separator) {\\n return this.node.scene().root();\\n }\\n if (path[0] === separator) {\\n path = path.substring(1, path.length);\\n return this.node.scene().root().node(path);\\n }\\n if (path.split) {\\n const elements = path.split(separator);\\n if (elements.length === 1) {\\n const name = elements[0];\\n if (this.node.childrenController) {\\n return this.node.childrenController.child_by_name(name);\\n } else {\\n return null;\\n }\\n } else {\\n return CoreWalker.findNode(this.node, path);\\n }\\n } else {\\n console.error(\\\\\\\"unexpected path given:\\\\\\\", path);\\n return null;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/MapUtils.ts\\nvar MapUtils = class {\\n static pushOnArrayAtEntry(map, key, new_element) {\\n let has_entry = map.has(key);\\n if (has_entry) {\\n map.get(key).push(new_element);\\n } else {\\n map.set(key, [new_element]);\\n }\\n }\\n static popFromArrayAtEntry(map, key, element_to_remove) {\\n let has_entry = map.has(key);\\n if (has_entry) {\\n const array = map.get(key);\\n const index = array.indexOf(element_to_remove);\\n if (index >= 0) {\\n array.splice(index, 1);\\n }\\n }\\n }\\n static unshiftOnArrayAtEntry(map, key, new_element) {\\n let has_entry = map.has(key);\\n if (has_entry) {\\n map.get(key).unshift(new_element);\\n } else {\\n map.set(key, [new_element]);\\n }\\n }\\n static concatOnArrayAtEntry(map, key, new_elements) {\\n let has_entry = map.has(key);\\n if (has_entry) {\\n let array = map.get(key);\\n for (let element of new_elements) {\\n array.push(element);\\n }\\n } else {\\n map.set(key, new_elements);\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/SetUtils.ts\\nvar SetUtils = class {\\n static union(set0, set1) {\\n const newSet = new Set();\\n set0.forEach((val) => newSet.add(val));\\n set1.forEach((val) => newSet.add(val));\\n return newSet;\\n }\\n static intersection(set0, set1) {\\n const newSet = new Set();\\n set0.forEach((val) => {\\n if (set1.has(val)) {\\n newSet.add(val);\\n }\\n });\\n set1.forEach((val) => {\\n if (set0.has(val)) {\\n newSet.add(val);\\n }\\n });\\n return newSet;\\n }\\n static difference(set0, set1) {\\n const newSet = new Set();\\n set0.forEach((val) => {\\n if (!set1.has(val)) {\\n newSet.add(val);\\n }\\n });\\n set1.forEach((val) => {\\n if (!set0.has(val)) {\\n newSet.add(val);\\n }\\n });\\n return newSet;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/ArrayUtils.ts\\nvar ArrayUtils = class {\\n static shallowClone(array) {\\n return [...array];\\n }\\n static min(array) {\\n let min = array[0];\\n for (let element of array) {\\n if (element < min) {\\n min = element;\\n }\\n }\\n return min;\\n }\\n static max(array) {\\n let min = array[0];\\n for (let element of array) {\\n if (element > min) {\\n min = element;\\n }\\n }\\n return min;\\n }\\n static sum(array) {\\n let sum = 0;\\n for (let element of array) {\\n sum += element;\\n }\\n return sum;\\n }\\n static compact(array) {\\n const newArray = [];\\n for (let elem of array) {\\n if (elem != null) {\\n newArray.push(elem);\\n }\\n }\\n return newArray;\\n }\\n static uniq(array) {\\n const tmpSet = new Set();\\n for (let elem of array) {\\n tmpSet.add(elem);\\n }\\n const newArray = new Array(tmpSet.size);\\n let i = 0;\\n tmpSet.forEach((elem) => {\\n newArray[i] = elem;\\n i++;\\n });\\n return newArray;\\n }\\n static chunk(array, chunkSize) {\\n const newArray = [];\\n let newSubArray = [];\\n newArray.push(newSubArray);\\n for (let i = 0; i < array.length; i++) {\\n if (newSubArray.length == chunkSize) {\\n newSubArray = [];\\n newArray.push(newSubArray);\\n }\\n newSubArray.push(array[i]);\\n }\\n return newArray;\\n }\\n static union(array0, array1) {\\n const newArray = [];\\n const unionSet = SetUtils.union(this.toSet(array0), this.toSet(array1));\\n unionSet.forEach((val) => newArray.push(val));\\n return newArray;\\n }\\n static intersection(array0, array1) {\\n const newArray = [];\\n const intersectionSet = SetUtils.intersection(this.toSet(array0), this.toSet(array1));\\n intersectionSet.forEach((val) => newArray.push(val));\\n return newArray;\\n }\\n static difference(array0, array1) {\\n const newArray = [];\\n const differenceSet = SetUtils.difference(this.toSet(array0), this.toSet(array1));\\n differenceSet.forEach((val) => newArray.push(val));\\n return newArray;\\n }\\n static toSet(array) {\\n const set = new Set();\\n for (let elem of array) {\\n set.add(elem);\\n }\\n return set;\\n }\\n static isEqual(array0, array1) {\\n if (array0.length != array1.length) {\\n return false;\\n }\\n const count = array0.length;\\n for (let i = 0; i < count; i++) {\\n if (array0[i] != array1[i]) {\\n return false;\\n }\\n }\\n return true;\\n }\\n static sortBy(array, callback) {\\n if (array.length == 0) {\\n return [];\\n }\\n const elementsByValue = new Map();\\n const valuesSet = new Set();\\n for (let elem of array) {\\n const value = callback(elem);\\n valuesSet.add(value);\\n MapUtils.pushOnArrayAtEntry(elementsByValue, value, elem);\\n }\\n const values = new Array(valuesSet.size);\\n let i = 0;\\n valuesSet.forEach((value) => {\\n values[i] = value;\\n i++;\\n });\\n if (CoreType.isString(values[0])) {\\n values.sort();\\n } else {\\n values.sort((a, b) => a - b);\\n }\\n const sorted_elements = new Array(array.length);\\n i = 0;\\n for (let value of values) {\\n const elements_for_value = elementsByValue.get(value);\\n if (elements_for_value) {\\n for (let element of elements_for_value) {\\n sorted_elements[i] = element;\\n i++;\\n }\\n }\\n }\\n return sorted_elements;\\n }\\n static range(start, end, step = 1) {\\n if (end == null) {\\n end = start;\\n start = 0;\\n }\\n const length = Math.floor((end - start) / step);\\n const array = new Array(length);\\n for (let i = 0; i < array.length; i++) {\\n array[i] = start + i * step;\\n }\\n return array;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/String.ts\\nvar ATTRIB_NAMES_SEPARATOR = /[, ]/;\\nvar TAIL_DIGIT_MATCH_REGEXP = /\\\\d+$/;\\nvar LEADING_ZEROS_MATCH_REGEXP = /^0+/;\\nvar INDICES_LIST_SEPARATOR = /,| /;\\nvar ZERO = \\\\\\\"0\\\\\\\";\\nvar SPACE = \\\\\\\" \\\\\\\";\\nvar NUM_REGEXP = /^-?\\\\d+\\\\.?\\\\d*$/;\\nvar BooleanString;\\n(function(BooleanString2) {\\n BooleanString2[\\\\\\\"TRUE\\\\\\\"] = \\\\\\\"true\\\\\\\";\\n BooleanString2[\\\\\\\"FALSE\\\\\\\"] = \\\\\\\"false\\\\\\\";\\n})(BooleanString || (BooleanString = {}));\\nvar CoreString = class {\\n static isBoolean(word) {\\n return word == BooleanString.TRUE || word == BooleanString.FALSE;\\n }\\n static toBoolean(word) {\\n return word == BooleanString.TRUE;\\n }\\n static isNumber(word) {\\n return NUM_REGEXP.test(word);\\n }\\n static tailDigits(word) {\\n const match = word.match(TAIL_DIGIT_MATCH_REGEXP);\\n if (match) {\\n return parseInt(match[0]);\\n } else {\\n return 0;\\n }\\n }\\n static increment(word) {\\n const match = word.match(TAIL_DIGIT_MATCH_REGEXP);\\n if (match) {\\n let numbers_as_str = match[0];\\n let zeros_prefix = \\\\\\\"\\\\\\\";\\n const leading_zeros_match = numbers_as_str.match(LEADING_ZEROS_MATCH_REGEXP);\\n if (leading_zeros_match) {\\n zeros_prefix = leading_zeros_match[0];\\n }\\n const digits = parseInt(numbers_as_str);\\n if (digits == 0) {\\n if (zeros_prefix.length > 0) {\\n if (zeros_prefix[zeros_prefix.length - 1] == ZERO) {\\n zeros_prefix = zeros_prefix.slice(0, -1);\\n }\\n }\\n }\\n const prefix = word.substring(0, word.length - match[0].length);\\n return `${prefix}${zeros_prefix}${digits + 1}`;\\n } else {\\n return `${word}1`;\\n }\\n }\\n static pluralize(word) {\\n const last_char = word[word.length - 1];\\n if (last_char !== \\\\\\\"s\\\\\\\") {\\n return `${word}s`;\\n } else {\\n return word;\\n }\\n }\\n static camelCase(str) {\\n const elements = str.replace(/_/g, \\\\\\\" \\\\\\\").split(\\\\\\\" \\\\\\\");\\n let newWord = \\\\\\\"\\\\\\\";\\n for (let i = 0; i < elements.length; i++) {\\n let element = elements[i].toLowerCase();\\n if (i > 0) {\\n element = this.upperFirst(element);\\n }\\n newWord += element;\\n }\\n return newWord;\\n }\\n static upperFirst(word) {\\n const newString = word[0].toUpperCase() + word.substr(1);\\n return newString;\\n }\\n static titleize(word) {\\n const elements = word.split(/\\\\s|_/g);\\n const newElements = elements.map((elem) => this.upperFirst(elem));\\n return newElements.join(\\\\\\\" \\\\\\\");\\n }\\n static precision(val, decimals = 2) {\\n decimals = Math.max(decimals, 0);\\n const elements = `${val}`.split(\\\\\\\".\\\\\\\");\\n if (decimals <= 0) {\\n return elements[0];\\n }\\n let frac = elements[1];\\n if (frac !== void 0) {\\n if (frac.length > decimals) {\\n frac = frac.substring(0, decimals);\\n }\\n frac = frac.padEnd(decimals, \\\\\\\"0\\\\\\\");\\n return `${elements[0]}.${frac}`;\\n } else {\\n const string_to_pad = `${val}.`;\\n const pad = string_to_pad.length + decimals;\\n return string_to_pad.padEnd(pad, \\\\\\\"0\\\\\\\");\\n }\\n }\\n static ensureFloat(num) {\\n const num_as_string = `${num}`;\\n const dot_pos = num_as_string.indexOf(\\\\\\\".\\\\\\\");\\n if (dot_pos >= 0) {\\n return num_as_string;\\n } else {\\n return `${num_as_string}.0`;\\n }\\n }\\n static ensureInteger(num) {\\n const num_as_string = `${num}`;\\n const dot_pos = num_as_string.indexOf(\\\\\\\".\\\\\\\");\\n if (dot_pos >= 0) {\\n return num_as_string.split(\\\\\\\".\\\\\\\")[0];\\n } else {\\n return num_as_string;\\n }\\n }\\n static matchMask(word, mask) {\\n if (mask === \\\\\\\"*\\\\\\\") {\\n return true;\\n }\\n if (word == mask) {\\n return true;\\n }\\n const elements = mask.split(SPACE);\\n if (elements.length > 1) {\\n for (let element of elements) {\\n const match = this.matchMask(word, element);\\n if (match) {\\n return true;\\n }\\n }\\n return false;\\n }\\n mask = mask.split(\\\\\\\"*\\\\\\\").join(\\\\\\\".*\\\\\\\");\\n mask = `^${mask}$`;\\n const regex = new RegExp(mask);\\n return regex.test(word);\\n }\\n static matchesOneMask(word, masks) {\\n let matches_one_mask = false;\\n for (let mask of masks) {\\n if (CoreString.matchMask(word, mask)) {\\n matches_one_mask = true;\\n }\\n }\\n return matches_one_mask;\\n }\\n static attribNames(word) {\\n const elements = word.split(ATTRIB_NAMES_SEPARATOR);\\n const names_set = new Set();\\n for (let element of elements) {\\n element = element.trim();\\n if (element.length > 0) {\\n names_set.add(element);\\n }\\n }\\n const names = new Array(names_set.size);\\n let i = 0;\\n names_set.forEach((name) => {\\n names[i] = name;\\n i++;\\n });\\n return names;\\n }\\n static indices(indices_string) {\\n const elements = indices_string.split(INDICES_LIST_SEPARATOR);\\n if (elements.length > 1) {\\n const indices = elements.flatMap((element) => this.indices(element));\\n return ArrayUtils.uniq(indices).sort((a, b) => a - b);\\n } else {\\n const element = elements[0];\\n if (element) {\\n const range_separator = \\\\\\\"-\\\\\\\";\\n if (element.indexOf(range_separator) > 0) {\\n const range_elements = element.split(range_separator);\\n return ArrayUtils.range(parseInt(range_elements[0]), parseInt(range_elements[1]) + 1);\\n } else {\\n const parsed = parseInt(element);\\n if (CoreType.isNumber(parsed)) {\\n return [parsed];\\n } else {\\n return [];\\n }\\n }\\n } else {\\n return [];\\n }\\n }\\n }\\n static escapeLineBreaks(word) {\\n return word.replace(/(\\\\r\\\\n|\\\\n|\\\\r)/gm, \\\\\\\"\\\\\\\\n\\\\\\\");\\n }\\n static sanitizeName(name) {\\n name = name.replace(/[^A-Za-z0-9]/g, \\\\\\\"_\\\\\\\");\\n name = name.replace(/^[0-9]/, \\\\\\\"_\\\\\\\");\\n return name;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/NodeSelection.ts\\nvar CoreNodeSelection = class {\\n constructor(_node) {\\n this._node = _node;\\n this._node_ids = [];\\n this._json = [];\\n }\\n node() {\\n return this._node;\\n }\\n nodes() {\\n return this._node.scene().graph.nodesFromIds(this._node_ids);\\n }\\n contains(node) {\\n return this._node_ids.includes(node.graphNodeId());\\n }\\n equals(nodes) {\\n const node_ids = nodes.map((node) => node.graphNodeId()).sort();\\n return ArrayUtils.isEqual(node_ids, this._node_ids);\\n }\\n clear() {\\n this._node_ids = [];\\n this.send_update_event();\\n }\\n set(nodes) {\\n this._node_ids = [];\\n this.add(nodes);\\n }\\n add(nodes_to_add) {\\n const node_ids_to_add = nodes_to_add.map((node) => node.graphNodeId());\\n this._node_ids = ArrayUtils.union(this._node_ids, node_ids_to_add);\\n this.send_update_event();\\n }\\n remove(nodes_to_remove) {\\n const node_ids_to_remove = nodes_to_remove.map((node) => node.graphNodeId());\\n this._node_ids = ArrayUtils.difference(this._node_ids, node_ids_to_remove);\\n this.send_update_event();\\n }\\n send_update_event() {\\n this._node.emit(NodeEvent.SELECTION_UPDATED);\\n }\\n toJSON() {\\n this._json = this._json || [];\\n this._json = this._node_ids.map((id) => id);\\n return this._json;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/InputCloneMode.ts\\nvar InputCloneMode;\\n(function(InputCloneMode2) {\\n InputCloneMode2[\\\\\\\"ALWAYS\\\\\\\"] = \\\\\\\"always\\\\\\\";\\n InputCloneMode2[\\\\\\\"NEVER\\\\\\\"] = \\\\\\\"never\\\\\\\";\\n InputCloneMode2[\\\\\\\"FROM_NODE\\\\\\\"] = \\\\\\\"from_node\\\\\\\";\\n})(InputCloneMode || (InputCloneMode = {}));\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/Assert.ts\\nvar TypeAssert = class {\\n static unreachable(x) {\\n throw new Error(\\\\\\\"Didn't expect to get here\\\\\\\");\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/operations/container/utils/inputs/ClonedStatesController.ts\\nvar ClonedStatesController = class {\\n constructor(inputs_controller) {\\n this.inputs_controller = inputs_controller;\\n this._clone_required_states = [];\\n this._overridden = false;\\n }\\n init_inputs_cloned_state(states) {\\n if (CoreType.isArray(states)) {\\n this._cloned_states = states;\\n } else {\\n this._cloned_state = states;\\n }\\n this._update_clone_required_state();\\n }\\n override_cloned_state_allowed() {\\n if (this._cloned_states) {\\n for (let state of this._cloned_states) {\\n if (state == InputCloneMode.FROM_NODE) {\\n return true;\\n }\\n }\\n }\\n if (this._cloned_state) {\\n return this._cloned_state == InputCloneMode.FROM_NODE;\\n }\\n return false;\\n }\\n clone_required_state(index) {\\n return this._clone_required_states[index];\\n }\\n clone_required_states() {\\n return this._clone_required_states;\\n }\\n _get_clone_required_state(index) {\\n const states = this._cloned_states;\\n if (states) {\\n const state = states[index];\\n if (state != null) {\\n return this.clone_required_from_state(state);\\n }\\n }\\n if (this._cloned_state) {\\n return this.clone_required_from_state(this._cloned_state);\\n }\\n return true;\\n }\\n clone_required_from_state(state) {\\n switch (state) {\\n case InputCloneMode.ALWAYS:\\n return true;\\n case InputCloneMode.NEVER:\\n return false;\\n case InputCloneMode.FROM_NODE:\\n return !this._overridden;\\n }\\n return TypeAssert.unreachable(state);\\n }\\n override_cloned_state(state) {\\n this._overridden = state;\\n this._update_clone_required_state();\\n }\\n overriden() {\\n return this._overridden;\\n }\\n _update_clone_required_state() {\\n if (this._cloned_states) {\\n const states = [];\\n for (let i = 0; i < this._cloned_states.length; i++) {\\n states[i] = this._get_clone_required_state(i);\\n }\\n this._clone_required_states = states;\\n return;\\n }\\n if (this._cloned_state) {\\n const max_inputs = this.inputs_controller.inputs_count();\\n const states = [];\\n for (let i = 0; i < max_inputs; i++) {\\n states[i] = this._get_clone_required_state(i);\\n }\\n this._clone_required_states = states;\\n return;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/operations/container/utils/InputsController.ts\\nvar InputsController = class {\\n constructor(operation_container) {\\n this.operation_container = operation_container;\\n }\\n inputs_count() {\\n return this.operation_container.inputs_count();\\n }\\n init_inputs_cloned_state(states) {\\n if (!this._cloned_states_controller) {\\n this._cloned_states_controller = new ClonedStatesController(this);\\n this._cloned_states_controller.init_inputs_cloned_state(states);\\n }\\n }\\n clone_required(index) {\\n const state = this._cloned_states_controller?.clone_required_state(index);\\n if (state != null) {\\n return state;\\n }\\n return true;\\n }\\n override_cloned_state(state) {\\n this._cloned_states_controller?.override_cloned_state(state);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/operations/container/_Base.ts\\nvar BaseOperationContainer = class {\\n constructor(operation, name, init_params) {\\n this.operation = operation;\\n this.name = name;\\n this.params = {};\\n this._apply_default_params();\\n this._apply_init_params(init_params);\\n this._init_cloned_states();\\n }\\n path_param_resolve_required() {\\n return this._path_params != null;\\n }\\n resolve_path_params(node_start) {\\n if (!this._path_params) {\\n return;\\n }\\n for (let path_param of this._path_params) {\\n path_param.resolve(node_start);\\n }\\n }\\n _apply_default_params() {\\n const default_params = this.operation.constructor.DEFAULT_PARAMS;\\n const param_names = Object.keys(default_params);\\n for (let param_name of param_names) {\\n const param_data = default_params[param_name];\\n const clone_param_data = this._convert_param_data(param_name, param_data);\\n if (clone_param_data != void 0) {\\n this.params[param_name] = clone_param_data;\\n }\\n }\\n }\\n _apply_init_params(init_params) {\\n const param_names = Object.keys(init_params);\\n for (let param_name of param_names) {\\n const param_data = init_params[param_name];\\n if (param_data.simple_data != null) {\\n const simple_data = param_data.simple_data;\\n const clone_param_data = this._convert_export_param_data(param_name, simple_data);\\n if (clone_param_data != void 0) {\\n this.params[param_name] = clone_param_data;\\n }\\n }\\n }\\n }\\n _convert_param_data(param_name, param_data) {\\n if (CoreType.isNumber(param_data) || CoreType.isBoolean(param_data) || CoreType.isString(param_data)) {\\n return param_data;\\n }\\n if (param_data instanceof TypedNodePathParamValue) {\\n const cloned = param_data.clone();\\n if (!this._path_params) {\\n this._path_params = [];\\n }\\n this._path_params.push(cloned);\\n return cloned;\\n }\\n if (param_data instanceof Color || param_data instanceof Vector2 || param_data instanceof Vector3 || param_data instanceof Vector4) {\\n return param_data.clone();\\n }\\n }\\n _convert_export_param_data(param_name, param_data) {\\n const default_param = this.params[param_name];\\n if (CoreType.isBoolean(param_data)) {\\n return param_data;\\n }\\n if (CoreType.isNumber(param_data)) {\\n if (CoreType.isBoolean(default_param)) {\\n return param_data >= 1 ? true : false;\\n } else {\\n return param_data;\\n }\\n }\\n if (CoreType.isString(param_data)) {\\n if (default_param) {\\n if (default_param instanceof TypedNodePathParamValue) {\\n return default_param.set_path(param_data);\\n }\\n if (default_param instanceof TypedParamPathParamValue) {\\n return default_param.set_path(param_data);\\n }\\n }\\n return param_data;\\n }\\n if (CoreType.isArray(param_data)) {\\n this.params[param_name].fromArray(param_data);\\n }\\n }\\n setInput(index, input) {\\n this._inputs = this._inputs || [];\\n this._inputs[index] = input;\\n }\\n inputs_count() {\\n if (this._inputs) {\\n return this._inputs.length;\\n } else {\\n return 0;\\n }\\n }\\n inputsController() {\\n return this._inputs_controller = this._inputs_controller || new InputsController(this);\\n }\\n _init_cloned_states() {\\n const default_cloned_states = this.operation.constructor.INPUT_CLONED_STATE;\\n this.inputsController().init_inputs_cloned_state(default_cloned_states);\\n }\\n input_clone_required(index) {\\n if (!this._inputs_controller) {\\n return true;\\n }\\n return this._inputs_controller.clone_required(index);\\n }\\n override_input_clone_state(state) {\\n this.inputsController().override_cloned_state(state);\\n }\\n cook(input_contents) {\\n return this.operation.cook(input_contents, this.params);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/operations/container/sop.ts\\nvar SopOperationContainer = class extends BaseOperationContainer {\\n constructor(operation, name, init_params) {\\n super(operation, name, init_params);\\n this.operation = operation;\\n this.name = name;\\n this.init_params = init_params;\\n this._inputs = [];\\n this._current_input_index = 0;\\n this._dirty = true;\\n }\\n add_input(input) {\\n super.setInput(this._current_input_index, input);\\n this.increment_input_index();\\n }\\n increment_input_index() {\\n this._current_input_index++;\\n }\\n current_input_index() {\\n return this._current_input_index;\\n }\\n setDirty() {\\n if (this._dirty) {\\n return;\\n }\\n this._compute_result = void 0;\\n for (let i = 0; i < this._inputs.length; i++) {\\n const input_operation = this._inputs[i];\\n input_operation.setDirty();\\n }\\n }\\n async compute(input_contents, operation_inputs_map) {\\n if (this._compute_result) {\\n return this._compute_result;\\n }\\n const operation_input_contents = [];\\n const node_inputs_map = operation_inputs_map.get(this);\\n if (node_inputs_map) {\\n node_inputs_map.forEach((node_input_index, operation_input_index) => {\\n operation_input_contents[operation_input_index] = input_contents[node_input_index];\\n });\\n }\\n for (let i = 0; i < this._inputs.length; i++) {\\n const input_operation = this._inputs[i];\\n let result2 = await input_operation.compute(input_contents, operation_inputs_map);\\n if (result2) {\\n if (this.input_clone_required(i)) {\\n result2 = result2.clone();\\n }\\n operation_input_contents[i] = result2;\\n }\\n }\\n const result = this.operation.cook(operation_input_contents, this.params);\\n if (result) {\\n if (result instanceof Promise) {\\n this._compute_result = await result;\\n } else {\\n this._compute_result = result;\\n }\\n } else {\\n this._compute_result = void 0;\\n }\\n this._dirty = false;\\n return this._compute_result;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/hierarchy/ChildrenController.ts\\nvar HierarchyChildrenController = class {\\n constructor(node, _context2) {\\n this.node = node;\\n this._context = _context2;\\n this._children = {};\\n this._children_by_type = {};\\n this._children_and_grandchildren_by_context = {};\\n }\\n get selection() {\\n return this._selection = this._selection || new CoreNodeSelection(this.node);\\n }\\n dispose() {\\n const children = this.children();\\n for (let child of children) {\\n this.node.removeNode(child);\\n }\\n this._selection = void 0;\\n }\\n get context() {\\n return this._context;\\n }\\n set_output_node_find_method(method) {\\n this._output_node_find_method = method;\\n }\\n output_node() {\\n if (this._output_node_find_method) {\\n return this._output_node_find_method();\\n }\\n }\\n set_child_name(node, new_name) {\\n let current_child_with_name;\\n new_name = CoreString.sanitizeName(new_name);\\n if ((current_child_with_name = this._children[new_name]) != null) {\\n if (node.name() === new_name && current_child_with_name.graphNodeId() === node.graphNodeId()) {\\n return;\\n }\\n new_name = CoreString.increment(new_name);\\n return this.set_child_name(node, new_name);\\n } else {\\n const current_name = node.name();\\n const current_child = this._children[current_name];\\n if (current_child) {\\n delete this._children[current_name];\\n }\\n this._children[new_name] = node;\\n node.nameController.update_name_from_parent(new_name);\\n this._add_to_nodesByType(node);\\n this.node.scene().nodesController.addToInstanciatedNode(node);\\n }\\n }\\n node_context_signature() {\\n return `${this.node.context()}/${this.node.type()}`;\\n }\\n available_children_classes() {\\n return Poly.registeredNodes(this._context, this.node.type());\\n }\\n is_valid_child_type(node_type) {\\n const node_class = this.available_children_classes()[node_type];\\n return node_class != null;\\n }\\n createNode(node_class_or_string, params_init_value_overrides, node_type = \\\\\\\"\\\\\\\") {\\n if (typeof node_class_or_string == \\\\\\\"string\\\\\\\") {\\n const node_class = this._find_node_class(node_class_or_string);\\n return this._create_and_init_node(node_class, params_init_value_overrides, node_type);\\n } else {\\n return this._create_and_init_node(node_class_or_string, params_init_value_overrides, node_type);\\n }\\n }\\n _create_and_init_node(node_class, params_init_value_overrides, node_type = \\\\\\\"\\\\\\\") {\\n const child_node = new node_class(this.node.scene(), `child_node_${node_type}`, params_init_value_overrides);\\n child_node.initialize_base_and_node();\\n this.add_node(child_node);\\n child_node.lifecycle.setCreationCompleted();\\n return child_node;\\n }\\n _find_node_class(node_type) {\\n const node_class = this.available_children_classes()[node_type.toLowerCase()];\\n if (node_class == null) {\\n const message = `child node type '${node_type}' not found for node '${this.node.path()}'. Available types are: ${Object.keys(this.available_children_classes()).join(\\\\\\\", \\\\\\\")}, ${this._context}, ${this.node.type()}`;\\n console.error(message);\\n throw message;\\n }\\n return node_class;\\n }\\n create_operation_container(operation_type, operation_container_name, params_init_value_overrides) {\\n const operation_class = Poly.registeredOperation(this._context, operation_type);\\n if (operation_class == null) {\\n const message = `no operation found with context ${this._context}/${operation_type}`;\\n console.error(message);\\n throw message;\\n } else {\\n const operation = new operation_class(this.node.scene());\\n const operation_container = new SopOperationContainer(operation, operation_container_name, params_init_value_overrides || {});\\n return operation_container;\\n }\\n }\\n add_node(child_node) {\\n child_node.setParent(this.node);\\n child_node.params.init();\\n child_node.parentController.onSetParent();\\n child_node.nameController.run_post_set_fullPath_hooks();\\n if (child_node.childrenAllowed() && child_node.childrenController) {\\n for (let child of child_node.childrenController.children()) {\\n child.nameController.run_post_set_fullPath_hooks();\\n }\\n }\\n this.node.emit(NodeEvent.CREATED, {child_node_json: child_node.toJSON()});\\n if (this.node.scene().lifecycleController.onCreateHookAllowed()) {\\n child_node.lifecycle.run_on_create_hooks();\\n }\\n child_node.lifecycle.run_on_add_hooks();\\n this.set_child_name(child_node, NameController.base_name(child_node));\\n this.node.lifecycle.run_on_child_add_hooks(child_node);\\n if (child_node.require_webgl2()) {\\n this.node.scene().webgl_controller.set_require_webgl2();\\n }\\n this.node.scene().missingExpressionReferencesController.checkForMissingReferences(child_node);\\n return child_node;\\n }\\n removeNode(child_node) {\\n if (child_node.parent() != this.node) {\\n return console.warn(`node ${child_node.name()} not under parent ${this.node.path()}`);\\n } else {\\n if (this.selection.contains(child_node)) {\\n this.selection.remove([child_node]);\\n }\\n const first_connection = child_node.io.connections.firstInputConnection();\\n const input_connections = child_node.io.connections.inputConnections();\\n const output_connections = child_node.io.connections.outputConnections();\\n if (input_connections) {\\n for (let input_connection of input_connections) {\\n if (input_connection) {\\n input_connection.disconnect({setInput: true});\\n }\\n }\\n }\\n if (output_connections) {\\n for (let output_connection of output_connections) {\\n if (output_connection) {\\n output_connection.disconnect({setInput: true});\\n if (first_connection) {\\n const old_src = first_connection.node_src;\\n const old_output_index = output_connection.output_index;\\n const old_dest = output_connection.node_dest;\\n const old_input_index = output_connection.input_index;\\n old_dest.io.inputs.setInput(old_input_index, old_src, old_output_index);\\n }\\n }\\n }\\n }\\n child_node.setParent(null);\\n delete this._children[child_node.name()];\\n this._remove_from_nodesByType(child_node);\\n this.node.scene().nodesController.removeFromInstanciatedNode(child_node);\\n child_node.setSuccessorsDirty(this.node);\\n child_node.graphDisconnectSuccessors();\\n this.node.lifecycle.run_on_child_remove_hooks(child_node);\\n child_node.lifecycle.run_on_delete_hooks();\\n child_node.dispose();\\n child_node.emit(NodeEvent.DELETED, {parent_id: this.node.graphNodeId()});\\n }\\n }\\n _add_to_nodesByType(node) {\\n const node_id = node.graphNodeId();\\n const type = node.type();\\n this._children_by_type[type] = this._children_by_type[type] || [];\\n if (!this._children_by_type[type].includes(node_id)) {\\n this._children_by_type[type].push(node_id);\\n }\\n this.add_to_children_and_grandchildren_by_context(node);\\n }\\n _remove_from_nodesByType(node) {\\n const node_id = node.graphNodeId();\\n const type = node.type();\\n if (this._children_by_type[type]) {\\n const index = this._children_by_type[type].indexOf(node_id);\\n if (index >= 0) {\\n this._children_by_type[type].splice(index, 1);\\n if (this._children_by_type[type].length == 0) {\\n delete this._children_by_type[type];\\n }\\n }\\n }\\n this.remove_from_children_and_grandchildren_by_context(node);\\n }\\n add_to_children_and_grandchildren_by_context(node) {\\n const node_id = node.graphNodeId();\\n const type = node.context();\\n this._children_and_grandchildren_by_context[type] = this._children_and_grandchildren_by_context[type] || [];\\n if (!this._children_and_grandchildren_by_context[type].includes(node_id)) {\\n this._children_and_grandchildren_by_context[type].push(node_id);\\n }\\n const parent = this.node.parent();\\n if (parent && parent.childrenAllowed()) {\\n parent.childrenController?.add_to_children_and_grandchildren_by_context(node);\\n }\\n }\\n remove_from_children_and_grandchildren_by_context(node) {\\n const node_id = node.graphNodeId();\\n const type = node.context();\\n if (this._children_and_grandchildren_by_context[type]) {\\n const index = this._children_and_grandchildren_by_context[type].indexOf(node_id);\\n if (index >= 0) {\\n this._children_and_grandchildren_by_context[type].splice(index, 1);\\n if (this._children_and_grandchildren_by_context[type].length == 0) {\\n delete this._children_and_grandchildren_by_context[type];\\n }\\n }\\n }\\n const parent = this.node.parent();\\n if (parent && parent.childrenAllowed()) {\\n parent.childrenController?.remove_from_children_and_grandchildren_by_context(node);\\n }\\n }\\n nodesByType(type) {\\n const node_ids = this._children_by_type[type] || [];\\n const graph = this.node.scene().graph;\\n const nodes = [];\\n for (let node_id of node_ids) {\\n const node = graph.nodeFromId(node_id);\\n if (node) {\\n nodes.push(node);\\n }\\n }\\n return nodes;\\n }\\n child_by_name(name) {\\n return this._children[name];\\n }\\n has_children_and_grandchildren_with_context(context) {\\n return this._children_and_grandchildren_by_context[context] != null;\\n }\\n children() {\\n return Object.values(this._children);\\n }\\n children_names() {\\n return Object.keys(this._children).sort();\\n }\\n traverse_children(callback) {\\n for (let child of this.children()) {\\n callback(child);\\n child.childrenController?.traverse_children(callback);\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/LifeCycleController.ts\\nvar LifeCycleController = class {\\n constructor(node) {\\n this.node = node;\\n this._creation_completed = false;\\n }\\n dispose() {\\n this._on_child_add_hooks = void 0;\\n this._on_child_remove_hooks = void 0;\\n this._on_create_hooks = void 0;\\n this._on_add_hooks = void 0;\\n this._on_delete_hooks = void 0;\\n }\\n setCreationCompleted() {\\n if (!this._creation_completed) {\\n this._creation_completed = true;\\n }\\n }\\n creationCompleted() {\\n return this.node.scene().loadingController.loaded() && this._creation_completed;\\n }\\n add_on_child_add_hook(callback) {\\n this._on_child_add_hooks = this._on_child_add_hooks || [];\\n this._on_child_add_hooks.push(callback);\\n }\\n run_on_child_add_hooks(node) {\\n this.execute_hooks_with_child_node(this._on_child_add_hooks, node);\\n }\\n add_on_child_remove_hook(callback) {\\n this._on_child_remove_hooks = this._on_child_remove_hooks || [];\\n this._on_child_remove_hooks.push(callback);\\n }\\n run_on_child_remove_hooks(node) {\\n this.execute_hooks_with_child_node(this._on_child_remove_hooks, node);\\n }\\n add_on_create_hook(callback) {\\n this._on_create_hooks = this._on_create_hooks || [];\\n this._on_create_hooks.push(callback);\\n }\\n run_on_create_hooks() {\\n this.execute_hooks(this._on_create_hooks);\\n }\\n add_on_add_hook(callback) {\\n this._on_add_hooks = this._on_add_hooks || [];\\n this._on_add_hooks.push(callback);\\n }\\n run_on_add_hooks() {\\n this.execute_hooks(this._on_add_hooks);\\n }\\n add_delete_hook(callback) {\\n this._on_delete_hooks = this._on_delete_hooks || [];\\n this._on_delete_hooks.push(callback);\\n }\\n run_on_delete_hooks() {\\n this.execute_hooks(this._on_delete_hooks);\\n }\\n execute_hooks(hooks) {\\n if (hooks) {\\n let hook;\\n for (hook of hooks) {\\n hook();\\n }\\n }\\n }\\n execute_hooks_with_child_node(hooks, child_node) {\\n if (hooks) {\\n let hook;\\n for (hook of hooks) {\\n hook(child_node);\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/NodeContext.ts\\nvar NodeContext;\\n(function(NodeContext3) {\\n NodeContext3[\\\\\\\"ANIM\\\\\\\"] = \\\\\\\"anim\\\\\\\";\\n NodeContext3[\\\\\\\"COP\\\\\\\"] = \\\\\\\"cop\\\\\\\";\\n NodeContext3[\\\\\\\"EVENT\\\\\\\"] = \\\\\\\"event\\\\\\\";\\n NodeContext3[\\\\\\\"GL\\\\\\\"] = \\\\\\\"gl\\\\\\\";\\n NodeContext3[\\\\\\\"JS\\\\\\\"] = \\\\\\\"js\\\\\\\";\\n NodeContext3[\\\\\\\"MANAGER\\\\\\\"] = \\\\\\\"manager\\\\\\\";\\n NodeContext3[\\\\\\\"MAT\\\\\\\"] = \\\\\\\"mat\\\\\\\";\\n NodeContext3[\\\\\\\"OBJ\\\\\\\"] = \\\\\\\"obj\\\\\\\";\\n NodeContext3[\\\\\\\"POST\\\\\\\"] = \\\\\\\"post\\\\\\\";\\n NodeContext3[\\\\\\\"ROP\\\\\\\"] = \\\\\\\"rop\\\\\\\";\\n NodeContext3[\\\\\\\"SOP\\\\\\\"] = \\\\\\\"sop\\\\\\\";\\n})(NodeContext || (NodeContext = {}));\\nvar NetworkNodeType;\\n(function(NetworkNodeType2) {\\n NetworkNodeType2[\\\\\\\"ANIM\\\\\\\"] = \\\\\\\"animationsNetwork\\\\\\\";\\n NetworkNodeType2[\\\\\\\"COP\\\\\\\"] = \\\\\\\"copNetwork\\\\\\\";\\n NetworkNodeType2[\\\\\\\"EVENT\\\\\\\"] = \\\\\\\"eventsNetwork\\\\\\\";\\n NetworkNodeType2[\\\\\\\"MAT\\\\\\\"] = \\\\\\\"materialsNetwork\\\\\\\";\\n NetworkNodeType2[\\\\\\\"POST\\\\\\\"] = \\\\\\\"postProcessNetwork\\\\\\\";\\n NetworkNodeType2[\\\\\\\"ROP\\\\\\\"] = \\\\\\\"renderersNetwork\\\\\\\";\\n})(NetworkNodeType || (NetworkNodeType = {}));\\nvar NetworkChildNodeType;\\n(function(NetworkChildNodeType2) {\\n NetworkChildNodeType2[\\\\\\\"INPUT\\\\\\\"] = \\\\\\\"subnetInput\\\\\\\";\\n NetworkChildNodeType2[\\\\\\\"OUTPUT\\\\\\\"] = \\\\\\\"subnetOutput\\\\\\\";\\n})(NetworkChildNodeType || (NetworkChildNodeType = {}));\\nvar CameraNodeType;\\n(function(CameraNodeType2) {\\n CameraNodeType2[\\\\\\\"PERSPECTIVE\\\\\\\"] = \\\\\\\"perspectiveCamera\\\\\\\";\\n CameraNodeType2[\\\\\\\"ORTHOGRAPHIC\\\\\\\"] = \\\\\\\"orthographicCamera\\\\\\\";\\n})(CameraNodeType || (CameraNodeType = {}));\\nvar CAMERA_TYPES = [CameraNodeType.ORTHOGRAPHIC, CameraNodeType.PERSPECTIVE];\\nvar GlNodeType;\\n(function(GlNodeType2) {\\n GlNodeType2[\\\\\\\"ATTRIBUTE\\\\\\\"] = \\\\\\\"attribute\\\\\\\";\\n})(GlNodeType || (GlNodeType = {}));\\nvar CameraControlsNodeType;\\n(function(CameraControlsNodeType2) {\\n CameraControlsNodeType2[\\\\\\\"DEVICE_ORIENTATION\\\\\\\"] = \\\\\\\"cameraDeviceOrientationControls\\\\\\\";\\n CameraControlsNodeType2[\\\\\\\"MAP\\\\\\\"] = \\\\\\\"cameraMapControls\\\\\\\";\\n CameraControlsNodeType2[\\\\\\\"ORBIT\\\\\\\"] = \\\\\\\"cameraOrbitControls\\\\\\\";\\n CameraControlsNodeType2[\\\\\\\"FIRST_PERSON\\\\\\\"] = \\\\\\\"firstPersonControls\\\\\\\";\\n CameraControlsNodeType2[\\\\\\\"PLAYER\\\\\\\"] = \\\\\\\"playerControls\\\\\\\";\\n CameraControlsNodeType2[\\\\\\\"MOBILE_JOYSTICK\\\\\\\"] = \\\\\\\"mobileJoystickControls\\\\\\\";\\n})(CameraControlsNodeType || (CameraControlsNodeType = {}));\\nvar CAMERA_CONTROLS_NODE_TYPES = [\\n CameraControlsNodeType.DEVICE_ORIENTATION,\\n CameraControlsNodeType.MAP,\\n CameraControlsNodeType.ORBIT,\\n CameraControlsNodeType.FIRST_PERSON,\\n CameraControlsNodeType.MOBILE_JOYSTICK\\n];\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/_Base.ts\\nvar TypedContainer = class {\\n constructor(_node) {\\n this._node = _node;\\n }\\n set_node(node) {\\n this._node = node;\\n }\\n node() {\\n return this._node;\\n }\\n set_content(content) {\\n this._content = content;\\n this._post_set_content();\\n }\\n has_content() {\\n return this._content != null;\\n }\\n content() {\\n return this._content;\\n }\\n _post_set_content() {\\n }\\n coreContent() {\\n return this._content;\\n }\\n coreContentCloned() {\\n return this._content;\\n }\\n infos() {\\n return [];\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Animation.ts\\nvar AnimationContainer = class extends TypedContainer {\\n set_content(content) {\\n super.set_content(content);\\n }\\n setTimelineBuilder(timeline_builder) {\\n return this.set_content(timeline_builder);\\n }\\n timeline_builder() {\\n return this.content();\\n }\\n coreContentCloned() {\\n if (this._content) {\\n return this._content.clone();\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Event.ts\\nvar EventContainer = class extends TypedContainer {\\n set_content(content) {\\n super.set_content(content);\\n }\\n};\\n\\n// ../../../node_modules/three/src/objects/SkinnedMesh.js\\nvar _basePosition = /* @__PURE__ */ new Vector3();\\nvar _skinIndex = /* @__PURE__ */ new Vector4();\\nvar _skinWeight = /* @__PURE__ */ new Vector4();\\nvar _vector7 = /* @__PURE__ */ new Vector3();\\nvar _matrix2 = /* @__PURE__ */ new Matrix4();\\nvar SkinnedMesh = class extends Mesh {\\n constructor(geometry, material) {\\n super(geometry, material);\\n this.type = \\\\\\\"SkinnedMesh\\\\\\\";\\n this.bindMode = \\\\\\\"attached\\\\\\\";\\n this.bindMatrix = new Matrix4();\\n this.bindMatrixInverse = new Matrix4();\\n }\\n copy(source) {\\n super.copy(source);\\n this.bindMode = source.bindMode;\\n this.bindMatrix.copy(source.bindMatrix);\\n this.bindMatrixInverse.copy(source.bindMatrixInverse);\\n this.skeleton = source.skeleton;\\n return this;\\n }\\n bind(skeleton, bindMatrix) {\\n this.skeleton = skeleton;\\n if (bindMatrix === void 0) {\\n this.updateMatrixWorld(true);\\n this.skeleton.calculateInverses();\\n bindMatrix = this.matrixWorld;\\n }\\n this.bindMatrix.copy(bindMatrix);\\n this.bindMatrixInverse.copy(bindMatrix).invert();\\n }\\n pose() {\\n this.skeleton.pose();\\n }\\n normalizeSkinWeights() {\\n const vector = new Vector4();\\n const skinWeight = this.geometry.attributes.skinWeight;\\n for (let i = 0, l = skinWeight.count; i < l; i++) {\\n vector.x = skinWeight.getX(i);\\n vector.y = skinWeight.getY(i);\\n vector.z = skinWeight.getZ(i);\\n vector.w = skinWeight.getW(i);\\n const scale = 1 / vector.manhattanLength();\\n if (scale !== Infinity) {\\n vector.multiplyScalar(scale);\\n } else {\\n vector.set(1, 0, 0, 0);\\n }\\n skinWeight.setXYZW(i, vector.x, vector.y, vector.z, vector.w);\\n }\\n }\\n updateMatrixWorld(force) {\\n super.updateMatrixWorld(force);\\n if (this.bindMode === \\\\\\\"attached\\\\\\\") {\\n this.bindMatrixInverse.copy(this.matrixWorld).invert();\\n } else if (this.bindMode === \\\\\\\"detached\\\\\\\") {\\n this.bindMatrixInverse.copy(this.bindMatrix).invert();\\n } else {\\n console.warn(\\\\\\\"THREE.SkinnedMesh: Unrecognized bindMode: \\\\\\\" + this.bindMode);\\n }\\n }\\n boneTransform(index, target) {\\n const skeleton = this.skeleton;\\n const geometry = this.geometry;\\n _skinIndex.fromBufferAttribute(geometry.attributes.skinIndex, index);\\n _skinWeight.fromBufferAttribute(geometry.attributes.skinWeight, index);\\n _basePosition.copy(target).applyMatrix4(this.bindMatrix);\\n target.set(0, 0, 0);\\n for (let i = 0; i < 4; i++) {\\n const weight = _skinWeight.getComponent(i);\\n if (weight !== 0) {\\n const boneIndex = _skinIndex.getComponent(i);\\n _matrix2.multiplyMatrices(skeleton.bones[boneIndex].matrixWorld, skeleton.boneInverses[boneIndex]);\\n target.addScaledVector(_vector7.copy(_basePosition).applyMatrix4(_matrix2), weight);\\n }\\n }\\n return target.applyMatrix4(this.bindMatrixInverse);\\n }\\n};\\nSkinnedMesh.prototype.isSkinnedMesh = true;\\n\\n// ../../../node_modules/three/src/scenes/Scene.js\\nvar Scene = class extends Object3D {\\n constructor() {\\n super();\\n this.type = \\\\\\\"Scene\\\\\\\";\\n this.background = null;\\n this.environment = null;\\n this.fog = null;\\n this.overrideMaterial = null;\\n this.autoUpdate = true;\\n if (typeof __THREE_DEVTOOLS__ !== \\\\\\\"undefined\\\\\\\") {\\n __THREE_DEVTOOLS__.dispatchEvent(new CustomEvent(\\\\\\\"observe\\\\\\\", {detail: this}));\\n }\\n }\\n copy(source, recursive) {\\n super.copy(source, recursive);\\n if (source.background !== null)\\n this.background = source.background.clone();\\n if (source.environment !== null)\\n this.environment = source.environment.clone();\\n if (source.fog !== null)\\n this.fog = source.fog.clone();\\n if (source.overrideMaterial !== null)\\n this.overrideMaterial = source.overrideMaterial.clone();\\n this.autoUpdate = source.autoUpdate;\\n this.matrixAutoUpdate = source.matrixAutoUpdate;\\n return this;\\n }\\n toJSON(meta) {\\n const data = super.toJSON(meta);\\n if (this.fog !== null)\\n data.object.fog = this.fog.toJSON();\\n return data;\\n }\\n};\\nScene.prototype.isScene = true;\\n\\n// ../../../node_modules/three/src/materials/PointsMaterial.js\\nvar PointsMaterial = class extends Material {\\n constructor(parameters) {\\n super();\\n this.type = \\\\\\\"PointsMaterial\\\\\\\";\\n this.color = new Color(16777215);\\n this.map = null;\\n this.alphaMap = null;\\n this.size = 1;\\n this.sizeAttenuation = true;\\n this.setValues(parameters);\\n }\\n copy(source) {\\n super.copy(source);\\n this.color.copy(source.color);\\n this.map = source.map;\\n this.alphaMap = source.alphaMap;\\n this.size = source.size;\\n this.sizeAttenuation = source.sizeAttenuation;\\n return this;\\n }\\n};\\nPointsMaterial.prototype.isPointsMaterial = true;\\n\\n// ../../../node_modules/three/src/objects/Points.js\\nvar _inverseMatrix2 = /* @__PURE__ */ new Matrix4();\\nvar _ray2 = /* @__PURE__ */ new Ray();\\nvar _sphere3 = /* @__PURE__ */ new Sphere();\\nvar _position2 = /* @__PURE__ */ new Vector3();\\nvar Points = class extends Object3D {\\n constructor(geometry = new BufferGeometry(), material = new PointsMaterial()) {\\n super();\\n this.type = \\\\\\\"Points\\\\\\\";\\n this.geometry = geometry;\\n this.material = material;\\n this.updateMorphTargets();\\n }\\n copy(source) {\\n super.copy(source);\\n this.material = source.material;\\n this.geometry = source.geometry;\\n return this;\\n }\\n raycast(raycaster, intersects) {\\n const geometry = this.geometry;\\n const matrixWorld = this.matrixWorld;\\n const threshold = raycaster.params.Points.threshold;\\n const drawRange = geometry.drawRange;\\n if (geometry.boundingSphere === null)\\n geometry.computeBoundingSphere();\\n _sphere3.copy(geometry.boundingSphere);\\n _sphere3.applyMatrix4(matrixWorld);\\n _sphere3.radius += threshold;\\n if (raycaster.ray.intersectsSphere(_sphere3) === false)\\n return;\\n _inverseMatrix2.copy(matrixWorld).invert();\\n _ray2.copy(raycaster.ray).applyMatrix4(_inverseMatrix2);\\n const localThreshold = threshold / ((this.scale.x + this.scale.y + this.scale.z) / 3);\\n const localThresholdSq = localThreshold * localThreshold;\\n if (geometry.isBufferGeometry) {\\n const index = geometry.index;\\n const attributes = geometry.attributes;\\n const positionAttribute = attributes.position;\\n if (index !== null) {\\n const start = Math.max(0, drawRange.start);\\n const end = Math.min(index.count, drawRange.start + drawRange.count);\\n for (let i = start, il = end; i < il; i++) {\\n const a = index.getX(i);\\n _position2.fromBufferAttribute(positionAttribute, a);\\n testPoint(_position2, a, localThresholdSq, matrixWorld, raycaster, intersects, this);\\n }\\n } else {\\n const start = Math.max(0, drawRange.start);\\n const end = Math.min(positionAttribute.count, drawRange.start + drawRange.count);\\n for (let i = start, l = end; i < l; i++) {\\n _position2.fromBufferAttribute(positionAttribute, i);\\n testPoint(_position2, i, localThresholdSq, matrixWorld, raycaster, intersects, this);\\n }\\n }\\n } else {\\n console.error(\\\\\\\"THREE.Points.raycast() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\");\\n }\\n }\\n updateMorphTargets() {\\n const geometry = this.geometry;\\n if (geometry.isBufferGeometry) {\\n const morphAttributes = geometry.morphAttributes;\\n const keys = Object.keys(morphAttributes);\\n if (keys.length > 0) {\\n const morphAttribute = morphAttributes[keys[0]];\\n if (morphAttribute !== void 0) {\\n this.morphTargetInfluences = [];\\n this.morphTargetDictionary = {};\\n for (let m = 0, ml = morphAttribute.length; m < ml; m++) {\\n const name = morphAttribute[m].name || String(m);\\n this.morphTargetInfluences.push(0);\\n this.morphTargetDictionary[name] = m;\\n }\\n }\\n }\\n } else {\\n const morphTargets = geometry.morphTargets;\\n if (morphTargets !== void 0 && morphTargets.length > 0) {\\n console.error(\\\\\\\"THREE.Points.updateMorphTargets() does not support THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\");\\n }\\n }\\n }\\n};\\nPoints.prototype.isPoints = true;\\nfunction testPoint(point, index, localThresholdSq, matrixWorld, raycaster, intersects, object) {\\n const rayPointDistanceSq = _ray2.distanceSqToPoint(point);\\n if (rayPointDistanceSq < localThresholdSq) {\\n const intersectPoint = new Vector3();\\n _ray2.closestPointToPoint(point, intersectPoint);\\n intersectPoint.applyMatrix4(matrixWorld);\\n const distance = raycaster.ray.origin.distanceTo(intersectPoint);\\n if (distance < raycaster.near || distance > raycaster.far)\\n return;\\n intersects.push({\\n distance,\\n distanceToRay: Math.sqrt(rayPointDistanceSq),\\n point: intersectPoint,\\n index,\\n face: null,\\n object\\n });\\n }\\n}\\n\\n// ../../../node_modules/three/src/objects/Bone.js\\nvar Bone = class extends Object3D {\\n constructor() {\\n super();\\n this.type = \\\\\\\"Bone\\\\\\\";\\n }\\n};\\nBone.prototype.isBone = true;\\n\\n// ../../../node_modules/three/src/materials/MeshStandardMaterial.js\\nvar MeshStandardMaterial = class extends Material {\\n constructor(parameters) {\\n super();\\n this.defines = {STANDARD: \\\\\\\"\\\\\\\"};\\n this.type = \\\\\\\"MeshStandardMaterial\\\\\\\";\\n this.color = new Color(16777215);\\n this.roughness = 1;\\n this.metalness = 0;\\n this.map = null;\\n this.lightMap = null;\\n this.lightMapIntensity = 1;\\n this.aoMap = null;\\n this.aoMapIntensity = 1;\\n this.emissive = new Color(0);\\n this.emissiveIntensity = 1;\\n this.emissiveMap = null;\\n this.bumpMap = null;\\n this.bumpScale = 1;\\n this.normalMap = null;\\n this.normalMapType = TangentSpaceNormalMap;\\n this.normalScale = new Vector2(1, 1);\\n this.displacementMap = null;\\n this.displacementScale = 1;\\n this.displacementBias = 0;\\n this.roughnessMap = null;\\n this.metalnessMap = null;\\n this.alphaMap = null;\\n this.envMap = null;\\n this.envMapIntensity = 1;\\n this.refractionRatio = 0.98;\\n this.wireframe = false;\\n this.wireframeLinewidth = 1;\\n this.wireframeLinecap = \\\\\\\"round\\\\\\\";\\n this.wireframeLinejoin = \\\\\\\"round\\\\\\\";\\n this.flatShading = false;\\n this.setValues(parameters);\\n }\\n copy(source) {\\n super.copy(source);\\n this.defines = {STANDARD: \\\\\\\"\\\\\\\"};\\n this.color.copy(source.color);\\n this.roughness = source.roughness;\\n this.metalness = source.metalness;\\n this.map = source.map;\\n this.lightMap = source.lightMap;\\n this.lightMapIntensity = source.lightMapIntensity;\\n this.aoMap = source.aoMap;\\n this.aoMapIntensity = source.aoMapIntensity;\\n this.emissive.copy(source.emissive);\\n this.emissiveMap = source.emissiveMap;\\n this.emissiveIntensity = source.emissiveIntensity;\\n this.bumpMap = source.bumpMap;\\n this.bumpScale = source.bumpScale;\\n this.normalMap = source.normalMap;\\n this.normalMapType = source.normalMapType;\\n this.normalScale.copy(source.normalScale);\\n this.displacementMap = source.displacementMap;\\n this.displacementScale = source.displacementScale;\\n this.displacementBias = source.displacementBias;\\n this.roughnessMap = source.roughnessMap;\\n this.metalnessMap = source.metalnessMap;\\n this.alphaMap = source.alphaMap;\\n this.envMap = source.envMap;\\n this.envMapIntensity = source.envMapIntensity;\\n this.refractionRatio = source.refractionRatio;\\n this.wireframe = source.wireframe;\\n this.wireframeLinewidth = source.wireframeLinewidth;\\n this.wireframeLinecap = source.wireframeLinecap;\\n this.wireframeLinejoin = source.wireframeLinejoin;\\n this.flatShading = source.flatShading;\\n return this;\\n }\\n};\\nMeshStandardMaterial.prototype.isMeshStandardMaterial = true;\\n\\n// ../../../node_modules/three/src/materials/MeshLambertMaterial.js\\nvar MeshLambertMaterial = class extends Material {\\n constructor(parameters) {\\n super();\\n this.type = \\\\\\\"MeshLambertMaterial\\\\\\\";\\n this.color = new Color(16777215);\\n this.map = null;\\n this.lightMap = null;\\n this.lightMapIntensity = 1;\\n this.aoMap = null;\\n this.aoMapIntensity = 1;\\n this.emissive = new Color(0);\\n this.emissiveIntensity = 1;\\n this.emissiveMap = null;\\n this.specularMap = null;\\n this.alphaMap = null;\\n this.envMap = null;\\n this.combine = MultiplyOperation;\\n this.reflectivity = 1;\\n this.refractionRatio = 0.98;\\n this.wireframe = false;\\n this.wireframeLinewidth = 1;\\n this.wireframeLinecap = \\\\\\\"round\\\\\\\";\\n this.wireframeLinejoin = \\\\\\\"round\\\\\\\";\\n this.setValues(parameters);\\n }\\n copy(source) {\\n super.copy(source);\\n this.color.copy(source.color);\\n this.map = source.map;\\n this.lightMap = source.lightMap;\\n this.lightMapIntensity = source.lightMapIntensity;\\n this.aoMap = source.aoMap;\\n this.aoMapIntensity = source.aoMapIntensity;\\n this.emissive.copy(source.emissive);\\n this.emissiveMap = source.emissiveMap;\\n this.emissiveIntensity = source.emissiveIntensity;\\n this.specularMap = source.specularMap;\\n this.alphaMap = source.alphaMap;\\n this.envMap = source.envMap;\\n this.combine = source.combine;\\n this.reflectivity = source.reflectivity;\\n this.refractionRatio = source.refractionRatio;\\n this.wireframe = source.wireframe;\\n this.wireframeLinewidth = source.wireframeLinewidth;\\n this.wireframeLinecap = source.wireframeLinecap;\\n this.wireframeLinejoin = source.wireframeLinejoin;\\n return this;\\n }\\n};\\nMeshLambertMaterial.prototype.isMeshLambertMaterial = true;\\n\\n// ../../../node_modules/three/src/materials/LineBasicMaterial.js\\nvar LineBasicMaterial = class extends Material {\\n constructor(parameters) {\\n super();\\n this.type = \\\\\\\"LineBasicMaterial\\\\\\\";\\n this.color = new Color(16777215);\\n this.linewidth = 1;\\n this.linecap = \\\\\\\"round\\\\\\\";\\n this.linejoin = \\\\\\\"round\\\\\\\";\\n this.setValues(parameters);\\n }\\n copy(source) {\\n super.copy(source);\\n this.color.copy(source.color);\\n this.linewidth = source.linewidth;\\n this.linecap = source.linecap;\\n this.linejoin = source.linejoin;\\n return this;\\n }\\n};\\nLineBasicMaterial.prototype.isLineBasicMaterial = true;\\n\\n// ../../../node_modules/three/src/objects/Line.js\\nvar _start = /* @__PURE__ */ new Vector3();\\nvar _end = /* @__PURE__ */ new Vector3();\\nvar _inverseMatrix3 = /* @__PURE__ */ new Matrix4();\\nvar _ray3 = /* @__PURE__ */ new Ray();\\nvar _sphere4 = /* @__PURE__ */ new Sphere();\\nvar Line = class extends Object3D {\\n constructor(geometry = new BufferGeometry(), material = new LineBasicMaterial()) {\\n super();\\n this.type = \\\\\\\"Line\\\\\\\";\\n this.geometry = geometry;\\n this.material = material;\\n this.updateMorphTargets();\\n }\\n copy(source) {\\n super.copy(source);\\n this.material = source.material;\\n this.geometry = source.geometry;\\n return this;\\n }\\n computeLineDistances() {\\n const geometry = this.geometry;\\n if (geometry.isBufferGeometry) {\\n if (geometry.index === null) {\\n const positionAttribute = geometry.attributes.position;\\n const lineDistances = [0];\\n for (let i = 1, l = positionAttribute.count; i < l; i++) {\\n _start.fromBufferAttribute(positionAttribute, i - 1);\\n _end.fromBufferAttribute(positionAttribute, i);\\n lineDistances[i] = lineDistances[i - 1];\\n lineDistances[i] += _start.distanceTo(_end);\\n }\\n geometry.setAttribute(\\\\\\\"lineDistance\\\\\\\", new Float32BufferAttribute(lineDistances, 1));\\n } else {\\n console.warn(\\\\\\\"THREE.Line.computeLineDistances(): Computation only possible with non-indexed BufferGeometry.\\\\\\\");\\n }\\n } else if (geometry.isGeometry) {\\n console.error(\\\\\\\"THREE.Line.computeLineDistances() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\");\\n }\\n return this;\\n }\\n raycast(raycaster, intersects) {\\n const geometry = this.geometry;\\n const matrixWorld = this.matrixWorld;\\n const threshold = raycaster.params.Line.threshold;\\n const drawRange = geometry.drawRange;\\n if (geometry.boundingSphere === null)\\n geometry.computeBoundingSphere();\\n _sphere4.copy(geometry.boundingSphere);\\n _sphere4.applyMatrix4(matrixWorld);\\n _sphere4.radius += threshold;\\n if (raycaster.ray.intersectsSphere(_sphere4) === false)\\n return;\\n _inverseMatrix3.copy(matrixWorld).invert();\\n _ray3.copy(raycaster.ray).applyMatrix4(_inverseMatrix3);\\n const localThreshold = threshold / ((this.scale.x + this.scale.y + this.scale.z) / 3);\\n const localThresholdSq = localThreshold * localThreshold;\\n const vStart = new Vector3();\\n const vEnd = new Vector3();\\n const interSegment = new Vector3();\\n const interRay = new Vector3();\\n const step = this.isLineSegments ? 2 : 1;\\n if (geometry.isBufferGeometry) {\\n const index = geometry.index;\\n const attributes = geometry.attributes;\\n const positionAttribute = attributes.position;\\n if (index !== null) {\\n const start = Math.max(0, drawRange.start);\\n const end = Math.min(index.count, drawRange.start + drawRange.count);\\n for (let i = start, l = end - 1; i < l; i += step) {\\n const a = index.getX(i);\\n const b = index.getX(i + 1);\\n vStart.fromBufferAttribute(positionAttribute, a);\\n vEnd.fromBufferAttribute(positionAttribute, b);\\n const distSq = _ray3.distanceSqToSegment(vStart, vEnd, interRay, interSegment);\\n if (distSq > localThresholdSq)\\n continue;\\n interRay.applyMatrix4(this.matrixWorld);\\n const distance = raycaster.ray.origin.distanceTo(interRay);\\n if (distance < raycaster.near || distance > raycaster.far)\\n continue;\\n intersects.push({\\n distance,\\n point: interSegment.clone().applyMatrix4(this.matrixWorld),\\n index: i,\\n face: null,\\n faceIndex: null,\\n object: this\\n });\\n }\\n } else {\\n const start = Math.max(0, drawRange.start);\\n const end = Math.min(positionAttribute.count, drawRange.start + drawRange.count);\\n for (let i = start, l = end - 1; i < l; i += step) {\\n vStart.fromBufferAttribute(positionAttribute, i);\\n vEnd.fromBufferAttribute(positionAttribute, i + 1);\\n const distSq = _ray3.distanceSqToSegment(vStart, vEnd, interRay, interSegment);\\n if (distSq > localThresholdSq)\\n continue;\\n interRay.applyMatrix4(this.matrixWorld);\\n const distance = raycaster.ray.origin.distanceTo(interRay);\\n if (distance < raycaster.near || distance > raycaster.far)\\n continue;\\n intersects.push({\\n distance,\\n point: interSegment.clone().applyMatrix4(this.matrixWorld),\\n index: i,\\n face: null,\\n faceIndex: null,\\n object: this\\n });\\n }\\n }\\n } else if (geometry.isGeometry) {\\n console.error(\\\\\\\"THREE.Line.raycast() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\");\\n }\\n }\\n updateMorphTargets() {\\n const geometry = this.geometry;\\n if (geometry.isBufferGeometry) {\\n const morphAttributes = geometry.morphAttributes;\\n const keys = Object.keys(morphAttributes);\\n if (keys.length > 0) {\\n const morphAttribute = morphAttributes[keys[0]];\\n if (morphAttribute !== void 0) {\\n this.morphTargetInfluences = [];\\n this.morphTargetDictionary = {};\\n for (let m = 0, ml = morphAttribute.length; m < ml; m++) {\\n const name = morphAttribute[m].name || String(m);\\n this.morphTargetInfluences.push(0);\\n this.morphTargetDictionary[name] = m;\\n }\\n }\\n }\\n } else {\\n const morphTargets = geometry.morphTargets;\\n if (morphTargets !== void 0 && morphTargets.length > 0) {\\n console.error(\\\\\\\"THREE.Line.updateMorphTargets() does not support THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\");\\n }\\n }\\n }\\n};\\nLine.prototype.isLine = true;\\n\\n// ../../../node_modules/three/src/objects/LineSegments.js\\nvar _start2 = /* @__PURE__ */ new Vector3();\\nvar _end2 = /* @__PURE__ */ new Vector3();\\nvar LineSegments = class extends Line {\\n constructor(geometry, material) {\\n super(geometry, material);\\n this.type = \\\\\\\"LineSegments\\\\\\\";\\n }\\n computeLineDistances() {\\n const geometry = this.geometry;\\n if (geometry.isBufferGeometry) {\\n if (geometry.index === null) {\\n const positionAttribute = geometry.attributes.position;\\n const lineDistances = [];\\n for (let i = 0, l = positionAttribute.count; i < l; i += 2) {\\n _start2.fromBufferAttribute(positionAttribute, i);\\n _end2.fromBufferAttribute(positionAttribute, i + 1);\\n lineDistances[i] = i === 0 ? 0 : lineDistances[i - 1];\\n lineDistances[i + 1] = lineDistances[i] + _start2.distanceTo(_end2);\\n }\\n geometry.setAttribute(\\\\\\\"lineDistance\\\\\\\", new Float32BufferAttribute(lineDistances, 1));\\n } else {\\n console.warn(\\\\\\\"THREE.LineSegments.computeLineDistances(): Computation only possible with non-indexed BufferGeometry.\\\\\\\");\\n }\\n } else if (geometry.isGeometry) {\\n console.error(\\\\\\\"THREE.LineSegments.computeLineDistances() no longer supports THREE.Geometry. Use THREE.BufferGeometry instead.\\\\\\\");\\n }\\n return this;\\n }\\n};\\nLineSegments.prototype.isLineSegments = true;\\n\\n// ../../../node_modules/three/src/objects/LOD.js\\nvar _v16 = /* @__PURE__ */ new Vector3();\\nvar _v23 = /* @__PURE__ */ new Vector3();\\nvar LOD = class extends Object3D {\\n constructor() {\\n super();\\n this._currentLevel = 0;\\n this.type = \\\\\\\"LOD\\\\\\\";\\n Object.defineProperties(this, {\\n levels: {\\n enumerable: true,\\n value: []\\n },\\n isLOD: {\\n value: true\\n }\\n });\\n this.autoUpdate = true;\\n }\\n copy(source) {\\n super.copy(source, false);\\n const levels = source.levels;\\n for (let i = 0, l = levels.length; i < l; i++) {\\n const level = levels[i];\\n this.addLevel(level.object.clone(), level.distance);\\n }\\n this.autoUpdate = source.autoUpdate;\\n return this;\\n }\\n addLevel(object, distance = 0) {\\n distance = Math.abs(distance);\\n const levels = this.levels;\\n let l;\\n for (l = 0; l < levels.length; l++) {\\n if (distance < levels[l].distance) {\\n break;\\n }\\n }\\n levels.splice(l, 0, {distance, object});\\n this.add(object);\\n return this;\\n }\\n getCurrentLevel() {\\n return this._currentLevel;\\n }\\n getObjectForDistance(distance) {\\n const levels = this.levels;\\n if (levels.length > 0) {\\n let i, l;\\n for (i = 1, l = levels.length; i < l; i++) {\\n if (distance < levels[i].distance) {\\n break;\\n }\\n }\\n return levels[i - 1].object;\\n }\\n return null;\\n }\\n raycast(raycaster, intersects) {\\n const levels = this.levels;\\n if (levels.length > 0) {\\n _v16.setFromMatrixPosition(this.matrixWorld);\\n const distance = raycaster.ray.origin.distanceTo(_v16);\\n this.getObjectForDistance(distance).raycast(raycaster, intersects);\\n }\\n }\\n update(camera) {\\n const levels = this.levels;\\n if (levels.length > 1) {\\n _v16.setFromMatrixPosition(camera.matrixWorld);\\n _v23.setFromMatrixPosition(this.matrixWorld);\\n const distance = _v16.distanceTo(_v23) / camera.zoom;\\n levels[0].object.visible = true;\\n let i, l;\\n for (i = 1, l = levels.length; i < l; i++) {\\n if (distance >= levels[i].distance) {\\n levels[i - 1].object.visible = false;\\n levels[i].object.visible = true;\\n } else {\\n break;\\n }\\n }\\n this._currentLevel = i - 1;\\n for (; i < l; i++) {\\n levels[i].object.visible = false;\\n }\\n }\\n }\\n toJSON(meta) {\\n const data = super.toJSON(meta);\\n if (this.autoUpdate === false)\\n data.object.autoUpdate = false;\\n data.object.levels = [];\\n const levels = this.levels;\\n for (let i = 0, l = levels.length; i < l; i++) {\\n const level = levels[i];\\n data.object.levels.push({\\n object: level.object.uuid,\\n distance: level.distance\\n });\\n }\\n return data;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Constant.ts\\nvar ObjectType;\\n(function(ObjectType2) {\\n ObjectType2[\\\\\\\"OBJECT3D\\\\\\\"] = \\\\\\\"Object3D\\\\\\\";\\n ObjectType2[\\\\\\\"GROUP\\\\\\\"] = \\\\\\\"Group\\\\\\\";\\n ObjectType2[\\\\\\\"MESH\\\\\\\"] = \\\\\\\"Mesh\\\\\\\";\\n ObjectType2[\\\\\\\"POINTS\\\\\\\"] = \\\\\\\"Points\\\\\\\";\\n ObjectType2[\\\\\\\"LINE_SEGMENTS\\\\\\\"] = \\\\\\\"LineSegments\\\\\\\";\\n ObjectType2[\\\\\\\"LOD\\\\\\\"] = \\\\\\\"LOD\\\\\\\";\\n})(ObjectType || (ObjectType = {}));\\nvar OBJECT_CONSTRUCTOR_BY_OBJECT_TYPE = {\\n [ObjectType.MESH]: Mesh,\\n [ObjectType.GROUP]: Group,\\n [ObjectType.POINTS]: Points,\\n [ObjectType.LINE_SEGMENTS]: LineSegments,\\n [ObjectType.OBJECT3D]: Object3D,\\n [ObjectType.LOD]: LOD\\n};\\nfunction objectTypeFromConstructor(constructor) {\\n switch (constructor) {\\n case Object3D:\\n return ObjectType.OBJECT3D;\\n case Group:\\n return ObjectType.GROUP;\\n case Mesh:\\n return ObjectType.MESH;\\n case Points:\\n return ObjectType.POINTS;\\n case LineSegments:\\n return ObjectType.LINE_SEGMENTS;\\n case LOD:\\n return ObjectType.LOD;\\n default:\\n Poly.warn(\\\\\\\"object type not supported\\\\\\\", constructor);\\n return ObjectType.MESH;\\n }\\n}\\nvar ObjectTypes = [ObjectType.MESH, ObjectType.POINTS, ObjectType.LINE_SEGMENTS];\\nvar ObjectTypeMenuEntries = [\\n {name: \\\\\\\"Mesh\\\\\\\", value: ObjectTypes.indexOf(ObjectType.MESH)},\\n {name: \\\\\\\"Points\\\\\\\", value: ObjectTypes.indexOf(ObjectType.POINTS)},\\n {name: \\\\\\\"LineSegments\\\\\\\", value: ObjectTypes.indexOf(ObjectType.LINE_SEGMENTS)}\\n];\\nvar materials = {\\n MeshStandard: new MeshStandardMaterial({\\n color: 16777215,\\n side: FrontSide,\\n metalness: 0.5,\\n roughness: 0.9\\n }),\\n [ObjectType.MESH]: new MeshLambertMaterial({\\n color: new Color(1, 1, 1),\\n side: FrontSide,\\n vertexColors: false,\\n transparent: true,\\n depthTest: true\\n }),\\n [ObjectType.POINTS]: new PointsMaterial({\\n color: 16777215,\\n size: 0.1,\\n depthTest: true\\n }),\\n [ObjectType.LINE_SEGMENTS]: new LineBasicMaterial({\\n color: 16777215,\\n linewidth: 1\\n })\\n};\\nvar AttribClass;\\n(function(AttribClass3) {\\n AttribClass3[AttribClass3[\\\\\\\"VERTEX\\\\\\\"] = 0] = \\\\\\\"VERTEX\\\\\\\";\\n AttribClass3[AttribClass3[\\\\\\\"OBJECT\\\\\\\"] = 1] = \\\\\\\"OBJECT\\\\\\\";\\n})(AttribClass || (AttribClass = {}));\\nvar AttribType;\\n(function(AttribType2) {\\n AttribType2[AttribType2[\\\\\\\"NUMERIC\\\\\\\"] = 0] = \\\\\\\"NUMERIC\\\\\\\";\\n AttribType2[AttribType2[\\\\\\\"STRING\\\\\\\"] = 1] = \\\\\\\"STRING\\\\\\\";\\n})(AttribType || (AttribType = {}));\\nvar AttribSize;\\n(function(AttribSize5) {\\n AttribSize5[AttribSize5[\\\\\\\"FLOAT\\\\\\\"] = 1] = \\\\\\\"FLOAT\\\\\\\";\\n AttribSize5[AttribSize5[\\\\\\\"VECTOR2\\\\\\\"] = 2] = \\\\\\\"VECTOR2\\\\\\\";\\n AttribSize5[AttribSize5[\\\\\\\"VECTOR3\\\\\\\"] = 3] = \\\\\\\"VECTOR3\\\\\\\";\\n AttribSize5[AttribSize5[\\\\\\\"VECTOR4\\\\\\\"] = 4] = \\\\\\\"VECTOR4\\\\\\\";\\n})(AttribSize || (AttribSize = {}));\\nvar CoreConstant = {\\n ATTRIB_CLASS: {\\n VERTEX: 0,\\n OBJECT: 1\\n },\\n OBJECT_TYPES: ObjectTypes,\\n CONSTRUCTOR_NAMES_BY_CONSTRUCTOR_NAME: {\\n [Scene.name]: \\\\\\\"Scene\\\\\\\",\\n [Group.name]: \\\\\\\"Group\\\\\\\",\\n [Object3D.name]: \\\\\\\"Object3D\\\\\\\",\\n [Mesh.name]: \\\\\\\"Mesh\\\\\\\",\\n [Points.name]: \\\\\\\"Points\\\\\\\",\\n [LineSegments.name]: \\\\\\\"LineSegments\\\\\\\",\\n [Bone.name]: \\\\\\\"Bone\\\\\\\",\\n [SkinnedMesh.name]: \\\\\\\"SkinnedMesh\\\\\\\"\\n },\\n CONSTRUCTORS_BY_NAME: {\\n [ObjectType.MESH]: Mesh,\\n [ObjectType.POINTS]: Points,\\n [ObjectType.LINE_SEGMENTS]: LineSegments\\n },\\n MATERIALS: materials\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Attribute.ts\\nvar Attribute;\\n(function(Attribute2) {\\n Attribute2[\\\\\\\"POSITION\\\\\\\"] = \\\\\\\"position\\\\\\\";\\n Attribute2[\\\\\\\"NORMAL\\\\\\\"] = \\\\\\\"normal\\\\\\\";\\n Attribute2[\\\\\\\"TANGENT\\\\\\\"] = \\\\\\\"tangent\\\\\\\";\\n})(Attribute || (Attribute = {}));\\nvar ATTRIB_NAME_MAP = {\\n P: \\\\\\\"position\\\\\\\",\\n N: \\\\\\\"normal\\\\\\\",\\n Cd: \\\\\\\"color\\\\\\\"\\n};\\nvar CoreAttribute = class {\\n static remapName(name) {\\n return ATTRIB_NAME_MAP[name] || name;\\n }\\n static arrayToIndexedArrays(array) {\\n const index_by_value = {};\\n let current_index = 0;\\n const indices = [];\\n const values = [];\\n let i = 0;\\n while (i < array.length) {\\n const value = array[i];\\n const index = index_by_value[value];\\n if (index != null) {\\n indices.push(index);\\n } else {\\n values.push(value);\\n indices.push(current_index);\\n index_by_value[value] = current_index;\\n current_index += 1;\\n }\\n i++;\\n }\\n return {\\n indices,\\n values\\n };\\n }\\n static default_value(size) {\\n switch (size) {\\n case 1:\\n return 0;\\n case 2:\\n return new Vector2(0, 0);\\n case 3:\\n return new Vector3(0, 0, 0);\\n default:\\n throw `size ${size} not yet implemented`;\\n }\\n }\\n static copy(src, dest, mark_as_needs_update = true) {\\n const src_array = src?.array;\\n const dest_array = dest?.array;\\n if (src_array && dest_array) {\\n const min_length = Math.min(src_array.length, dest_array.length);\\n for (let i = 0; i < min_length; i++) {\\n dest_array[i] = src_array[i];\\n }\\n if (mark_as_needs_update) {\\n dest.needsUpdate = true;\\n }\\n }\\n }\\n static attribSizeFromValue(val) {\\n if (CoreType.isString(val) || CoreType.isNumber(val)) {\\n return AttribSize.FLOAT;\\n }\\n if (CoreType.isArray(val)) {\\n return val.length;\\n }\\n switch (val.constructor) {\\n case Vector2:\\n return AttribSize.VECTOR2;\\n case Vector3:\\n return AttribSize.VECTOR3;\\n case Vector4:\\n return AttribSize.VECTOR4;\\n }\\n return 0;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Entity.ts\\nvar CoreEntity = class {\\n constructor(_index) {\\n this._index = _index;\\n }\\n index() {\\n return this._index;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Point.ts\\nvar ATTRIB_NAMES = {\\n POSITION: \\\\\\\"position\\\\\\\",\\n NORMAL: \\\\\\\"normal\\\\\\\"\\n};\\nvar ComponentName;\\n(function(ComponentName2) {\\n ComponentName2[\\\\\\\"x\\\\\\\"] = \\\\\\\"x\\\\\\\";\\n ComponentName2[\\\\\\\"y\\\\\\\"] = \\\\\\\"y\\\\\\\";\\n ComponentName2[\\\\\\\"z\\\\\\\"] = \\\\\\\"z\\\\\\\";\\n ComponentName2[\\\\\\\"w\\\\\\\"] = \\\\\\\"w\\\\\\\";\\n ComponentName2[\\\\\\\"r\\\\\\\"] = \\\\\\\"r\\\\\\\";\\n ComponentName2[\\\\\\\"g\\\\\\\"] = \\\\\\\"g\\\\\\\";\\n ComponentName2[\\\\\\\"b\\\\\\\"] = \\\\\\\"b\\\\\\\";\\n})(ComponentName || (ComponentName = {}));\\nvar COMPONENT_INDICES = {\\n x: 0,\\n y: 1,\\n z: 2,\\n w: 3,\\n r: 0,\\n g: 1,\\n b: 2\\n};\\nvar PTNUM = \\\\\\\"ptnum\\\\\\\";\\nvar DOT = \\\\\\\".\\\\\\\";\\nvar CorePoint = class extends CoreEntity {\\n constructor(_coreGeometry, _index) {\\n super(_index);\\n this._coreGeometry = _coreGeometry;\\n this._geometry = this._coreGeometry.geometry();\\n }\\n applyMatrix4(matrix) {\\n this.position().applyMatrix4(matrix);\\n }\\n coreGeometry() {\\n return this._coreGeometry;\\n }\\n geometry() {\\n return this._geometry = this._geometry || this._coreGeometry.geometry();\\n }\\n attribSize(name) {\\n name = CoreAttribute.remapName(name);\\n return this._geometry.getAttribute(name).itemSize;\\n }\\n hasAttrib(name) {\\n const remapped_name = CoreAttribute.remapName(name);\\n return this._coreGeometry.hasAttrib(remapped_name);\\n }\\n attribValue(name, target) {\\n if (name === PTNUM) {\\n return this.index();\\n } else {\\n let component_name = null;\\n let component_index = null;\\n if (name[name.length - 2] === DOT) {\\n component_name = name[name.length - 1];\\n component_index = COMPONENT_INDICES[component_name];\\n name = name.substring(0, name.length - 2);\\n }\\n const remaped_name = CoreAttribute.remapName(name);\\n const attrib = this._geometry.getAttribute(remaped_name);\\n if (attrib) {\\n const {array} = attrib;\\n if (this._coreGeometry.isAttribIndexed(remaped_name)) {\\n return this.indexedAttribValue(remaped_name);\\n } else {\\n const size = attrib.itemSize;\\n const start_index = this._index * size;\\n if (component_index == null) {\\n switch (size) {\\n case 1:\\n return array[start_index];\\n break;\\n case 2:\\n target = target || new Vector2();\\n target.fromArray(array, start_index);\\n return target;\\n break;\\n case 3:\\n target = target || new Vector3();\\n target.fromArray(array, start_index);\\n return target;\\n break;\\n case 4:\\n target = target || new Vector4();\\n target.fromArray(array, start_index);\\n return target;\\n break;\\n default:\\n throw `size not valid (${size})`;\\n }\\n } else {\\n switch (size) {\\n case 1:\\n return array[start_index];\\n break;\\n default:\\n return array[start_index + component_index];\\n }\\n }\\n }\\n } else {\\n const message = `attrib ${name} not found. availables are: ${Object.keys(this._geometry.attributes || {}).join(\\\\\\\",\\\\\\\")}`;\\n console.warn(message);\\n throw message;\\n }\\n }\\n }\\n indexedAttribValue(name) {\\n const value_index = this.attribValueIndex(name);\\n return this._coreGeometry.userDataAttrib(name)[value_index];\\n }\\n stringAttribValue(name) {\\n return this.indexedAttribValue(name);\\n }\\n attribValueIndex(name) {\\n if (this._coreGeometry.isAttribIndexed(name)) {\\n return this._geometry.getAttribute(name).array[this._index];\\n } else {\\n return -1;\\n }\\n }\\n isAttribIndexed(name) {\\n return this._coreGeometry.isAttribIndexed(name);\\n }\\n position() {\\n return this._position || (this._position = this.getPosition(new Vector3()));\\n }\\n getPosition(target) {\\n const {array} = this._geometry.getAttribute(ATTRIB_NAMES.POSITION);\\n return target.fromArray(array, this._index * 3);\\n }\\n setPosition(new_position) {\\n this.setAttribValueVector3(ATTRIB_NAMES.POSITION, new_position);\\n }\\n normal() {\\n return this._normal = this._normal || this.getNormal(new Vector3());\\n }\\n getNormal(target) {\\n const {array} = this._geometry.getAttribute(ATTRIB_NAMES.NORMAL);\\n return target.fromArray(array, this._index * 3);\\n }\\n setNormal(new_normal) {\\n return this.setAttribValueVector3(ATTRIB_NAMES.NORMAL, new_normal);\\n }\\n setAttribValue(name, value) {\\n if (value == null) {\\n return;\\n }\\n if (name == null) {\\n throw \\\\\\\"Point.set_attrib_value requires a name\\\\\\\";\\n }\\n const attrib = this._geometry.getAttribute(name);\\n const array = attrib.array;\\n const attrib_size = attrib.itemSize;\\n if (CoreType.isArray(value)) {\\n for (let i = 0; i < attrib_size; i++) {\\n array[this._index * attrib_size + i] = value[i];\\n }\\n return;\\n }\\n switch (attrib_size) {\\n case 1:\\n array[this._index] = value;\\n break;\\n case 2:\\n const v2 = value;\\n array[this._index * 2 + 0] = v2.x;\\n array[this._index * 2 + 1] = v2.y;\\n break;\\n case 3:\\n const is_color = value.r != null;\\n if (is_color) {\\n const col = value;\\n array[this._index * 3 + 0] = col.r;\\n array[this._index * 3 + 1] = col.g;\\n array[this._index * 3 + 2] = col.b;\\n } else {\\n const v3 = value;\\n array[this._index * 3 + 0] = v3.x;\\n array[this._index * 3 + 1] = v3.y;\\n array[this._index * 3 + 2] = v3.z;\\n }\\n break;\\n case 4:\\n const v4 = value;\\n array[this._index * 4 + 0] = v4.x;\\n array[this._index * 4 + 1] = v4.y;\\n array[this._index * 4 + 2] = v4.z;\\n array[this._index * 4 + 3] = v4.w;\\n break;\\n default:\\n console.warn(`Point.set_attrib_value does not yet allow attrib size ${attrib_size}`);\\n throw `attrib size ${attrib_size} not implemented`;\\n }\\n }\\n setAttribValueVector3(name, value) {\\n if (value == null) {\\n return;\\n }\\n if (name == null) {\\n throw \\\\\\\"Point.set_attrib_value requires a name\\\\\\\";\\n }\\n const attrib = this._geometry.getAttribute(name);\\n const array = attrib.array;\\n const i = this._index * 3;\\n array[i] = value.x;\\n array[i + 1] = value.y;\\n array[i + 2] = value.z;\\n }\\n setAttribIndex(name, new_value_index) {\\n const array = this._geometry.getAttribute(name).array;\\n return array[this._index] = new_value_index;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/math/Easing.ts\\nvar ease_i = function(power) {\\n return function(t) {\\n return Math.pow(t, power);\\n };\\n};\\nvar ease_o = function(power) {\\n return function(t) {\\n return 1 - Math.abs(Math.pow(t - 1, power));\\n };\\n};\\nvar ease_io = function(power) {\\n return function(t) {\\n return t < 0.5 ? ease_i(power)(t * 2) / 2 : ease_o(power)(t * 2 - 1) / 2 + 0.5;\\n };\\n};\\nvar Easing = {\\n linear: ease_io(1),\\n ease_i: function(t, power) {\\n return ease_i(power)(t);\\n },\\n ease_o: function(t, power) {\\n return ease_o(power)(t);\\n },\\n ease_io: function(t, power) {\\n return ease_io(power)(t);\\n },\\n ease_i2: ease_i(2),\\n ease_o2: ease_o(2),\\n ease_io2: ease_io(2),\\n ease_i3: ease_io(3),\\n ease_o3: ease_io(3),\\n ease_io3: ease_io(3),\\n ease_i4: ease_io(4),\\n ease_o4: ease_io(4),\\n ease_io4: ease_io(4),\\n ease_i_sin: function(t) {\\n return 1 + Math.sin(Math.PI / 2 * t - Math.PI / 2);\\n },\\n ease_o_sin: function(t) {\\n return Math.sin(Math.PI / 2 * t);\\n },\\n ease_io_sin: function(t) {\\n return (1 + Math.sin(Math.PI * t - Math.PI / 2)) / 2;\\n },\\n ease_i_elastic: function(t) {\\n return (0.04 - 0.04 / t) * Math.sin(25 * t) + 1;\\n },\\n ease_o_elastic: function(t) {\\n return 0.04 * t / --t * Math.sin(25 * t);\\n },\\n ease_io_elastic: function(t) {\\n return (t -= 0.5) < 0 ? (0.02 + 0.01 / t) * Math.sin(50 * t) : (0.02 - 0.01 / t) * Math.sin(50 * t) + 1;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/math/_Module.ts\\nvar RAD_DEG_RATIO = Math.PI / 180;\\nvar RAND_A = 12.9898;\\nvar RAND_B = 78.233;\\nvar RAND_C = 43758.5453;\\nvar CoreMath = class {\\n static clamp(val, min, max) {\\n if (val < min) {\\n return min;\\n } else if (val > max) {\\n return max;\\n } else {\\n return val;\\n }\\n }\\n static fit01(val, dest_min, dest_max) {\\n return this.fit(val, 0, 1, dest_min, dest_max);\\n }\\n static fit(val, src_min, src_max, dest_min, dest_max) {\\n const src_range = src_max - src_min;\\n const dest_range = dest_max - dest_min;\\n const r = (val - src_min) / src_range;\\n return r * dest_range + dest_min;\\n }\\n static blend(num0, num1, blend) {\\n return (1 - blend) * num0 + blend * num1;\\n }\\n static degrees_to_radians(degrees) {\\n return degrees * RAD_DEG_RATIO;\\n }\\n static radians_to_degrees(radians) {\\n return radians / RAD_DEG_RATIO;\\n }\\n static deg2rad(deg) {\\n return this.degrees_to_radians(deg);\\n }\\n static rad2deg(rad) {\\n return this.radians_to_degrees(rad);\\n }\\n static rand(number) {\\n if (CoreType.isNumber(number)) {\\n return this.randFloat(number);\\n } else {\\n return this.randVec2(number);\\n }\\n }\\n static round(number, step_size) {\\n const steps_count = number / step_size;\\n const rounded_steps_count = number < 0 ? Math.ceil(steps_count) : Math.floor(steps_count);\\n return rounded_steps_count * step_size;\\n }\\n static highest_even(number) {\\n return 2 * Math.ceil(number * 0.5);\\n }\\n static randFloat(x, y = 136574) {\\n this._vec.x = x;\\n this._vec.y = y;\\n return this.randVec2(this._vec);\\n }\\n static randVec2(uv) {\\n const dt = uv.x * RAND_A + uv.y * RAND_B;\\n const sn = dt % Math.PI;\\n return this.fract(Math.sin(sn) * RAND_C);\\n }\\n static geodesic_distance(lnglat1, lnglat2) {\\n var R = 6371e3;\\n var d1 = this.deg2rad(lnglat1.lat);\\n var d2 = this.deg2rad(lnglat2.lat);\\n var ad1 = this.deg2rad(lnglat2.lat - lnglat1.lat);\\n var ad2 = this.deg2rad(lnglat2.lng - lnglat1.lng);\\n var a = Math.sin(ad1 / 2) * Math.sin(ad1 / 2) + Math.cos(d1) * Math.cos(d2) * Math.sin(ad2 / 2) * Math.sin(ad2 / 2);\\n var c = 2 * Math.atan2(Math.sqrt(a), Math.sqrt(1 - a));\\n var d = R * c;\\n return d;\\n }\\n static expand_triangle(triangle, margin) {\\n triangle.getMidpoint(this._triangle_mid);\\n this._triangle_mid_to_corner.copy(triangle.a).sub(this._triangle_mid);\\n this._triangle_mid_to_corner.normalize().multiplyScalar(margin);\\n triangle.a.add(this._triangle_mid_to_corner);\\n this._triangle_mid_to_corner.copy(triangle.b).sub(this._triangle_mid);\\n this._triangle_mid_to_corner.normalize().multiplyScalar(margin);\\n triangle.b.add(this._triangle_mid_to_corner);\\n this._triangle_mid_to_corner.copy(triangle.c).sub(this._triangle_mid);\\n this._triangle_mid_to_corner.normalize().multiplyScalar(margin);\\n triangle.c.add(this._triangle_mid_to_corner);\\n }\\n static nearestPower2(num) {\\n return Math.pow(2, Math.ceil(Math.log(num) / Math.log(2)));\\n }\\n};\\nCoreMath.Easing = Easing;\\nCoreMath.fract = (number) => number - Math.floor(number);\\nCoreMath._vec = {x: 0, y: 136574};\\nCoreMath._triangle_mid = new Vector3();\\nCoreMath._triangle_mid_to_corner = new Vector3();\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Face.ts\\nvar CoreFace = class {\\n constructor(_coreGeometry, _index) {\\n this._coreGeometry = _coreGeometry;\\n this._index = _index;\\n this._geometry = this._coreGeometry.geometry();\\n }\\n index() {\\n return this._index;\\n }\\n points() {\\n return this._points = this._points || this._get_points();\\n }\\n applyMatrix4(matrix) {\\n for (let point of this.points()) {\\n point.applyMatrix4(matrix);\\n }\\n }\\n _get_points() {\\n const indexArray = this._geometry.index?.array || [];\\n const start = this._index * 3;\\n return [\\n new CorePoint(this._coreGeometry, indexArray[start + 0]),\\n new CorePoint(this._coreGeometry, indexArray[start + 1]),\\n new CorePoint(this._coreGeometry, indexArray[start + 2])\\n ];\\n }\\n positions() {\\n return this._positions = this._positions || this._getPositions();\\n }\\n _getPositions() {\\n const points2 = this.points();\\n return [points2[0].position(), points2[1].position(), points2[2].position()];\\n }\\n triangle() {\\n return this._triangle = this._triangle || this._get_triangle();\\n }\\n _get_triangle() {\\n const positions = this.positions();\\n return new Triangle(positions[0], positions[1], positions[2]);\\n }\\n deltas() {\\n return this._deltas = this._deltas || this._getDeltas();\\n }\\n _getDeltas() {\\n const positions = this.positions();\\n return [positions[1].clone().sub(positions[0]), positions[2].clone().sub(positions[0])];\\n }\\n area() {\\n return this.triangle().getArea();\\n }\\n center(target) {\\n const positions = this.positions();\\n target.x = (positions[0].x + positions[1].x + positions[2].x) / 3;\\n target.y = (positions[0].y + positions[1].y + positions[2].y) / 3;\\n target.z = (positions[0].z + positions[1].z + positions[2].z) / 3;\\n return target;\\n }\\n randomPosition(seed) {\\n let weights = [CoreMath.randFloat(seed), CoreMath.randFloat(seed * 6541)];\\n if (weights[0] + weights[1] > 1) {\\n weights[0] = 1 - weights[0];\\n weights[1] = 1 - weights[1];\\n }\\n return this.positions()[0].clone().add(this.deltas()[0].clone().multiplyScalar(weights[0])).add(this.deltas()[1].clone().multiplyScalar(weights[1]));\\n }\\n attribValueAtPosition(attrib_name, position) {\\n const barycentricCoordinates = new Vector3();\\n this.triangle().getBarycoord(position, barycentricCoordinates);\\n const weights = barycentricCoordinates.toArray();\\n const attrib = this._geometry.attributes[attrib_name];\\n const attribSize = attrib.itemSize;\\n const pointValues = this.points().map((point) => point.attribValue(attrib_name));\\n let newAttribValue;\\n let sum;\\n let index = 0;\\n switch (attribSize) {\\n case 1: {\\n sum = 0;\\n for (let pointValue of pointValues) {\\n sum += pointValue * weights[index];\\n index++;\\n }\\n newAttribValue = sum;\\n break;\\n }\\n default: {\\n for (let pointValue of pointValues) {\\n const weightedValue = pointValue.multiplyScalar(weights[index]);\\n if (sum) {\\n sum.add(weightedValue);\\n } else {\\n sum = weightedValue;\\n }\\n index++;\\n }\\n newAttribValue = sum;\\n }\\n }\\n return newAttribValue;\\n }\\n static interpolatedValue(geometry, face, intersectPoint, attrib) {\\n const pointIndices = [face.a, face.b, face.c];\\n const positionAttrib = geometry.getAttribute(\\\\\\\"position\\\\\\\");\\n const positionAttribArray = positionAttrib.array;\\n const pointPositions = pointIndices.map((point_index) => new Vector3(positionAttribArray[point_index * 3 + 0], positionAttribArray[point_index * 3 + 1], positionAttribArray[point_index * 3 + 2]));\\n const attribSize = attrib.itemSize;\\n const attribArray = attrib.array;\\n let attribValues = [];\\n switch (attribSize) {\\n case 1:\\n attribValues = pointIndices.map((point_index) => attribArray[point_index]);\\n break;\\n case 2:\\n attribValues = pointIndices.map((point_index) => new Vector2(attribArray[point_index * 2 + 0], attribArray[point_index * 2 + 1]));\\n break;\\n case 3:\\n attribValues = pointIndices.map((point_index) => new Vector3(attribArray[point_index * 3 + 0], attribArray[point_index * 3 + 1], attribArray[point_index * 3 + 2]));\\n break;\\n }\\n const distToPoints = pointIndices.map((point_index, i) => intersectPoint.distanceTo(pointPositions[i]));\\n const distanceTotal = ArrayUtils.sum([\\n distToPoints[0] * distToPoints[1],\\n distToPoints[0] * distToPoints[2],\\n distToPoints[1] * distToPoints[2]\\n ]);\\n const weights = [\\n distToPoints[1] * distToPoints[2] / distanceTotal,\\n distToPoints[0] * distToPoints[2] / distanceTotal,\\n distToPoints[0] * distToPoints[1] / distanceTotal\\n ];\\n let newAttribValue;\\n switch (attribSize) {\\n case 1:\\n newAttribValue = ArrayUtils.sum(pointIndices.map((point_indx, i) => weights[i] * attribValues[i]));\\n break;\\n default:\\n var values = pointIndices.map((point_index, i) => attribValues[i].multiplyScalar(weights[i]));\\n newAttribValue = null;\\n for (let value of values) {\\n if (newAttribValue) {\\n newAttribValue.add(value);\\n } else {\\n newAttribValue = value;\\n }\\n }\\n }\\n return newAttribValue;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/builders/_Base.ts\\nvar CoreGeometryBuilderBase = class {\\n from_points(points2) {\\n points2 = this._filter_points(points2);\\n const geometry = new BufferGeometry();\\n const core_geometry = new CoreGeometry(geometry);\\n const first_point = points2[0];\\n if (first_point != null) {\\n const old_geometry = first_point.geometry();\\n const old_core_geometry = first_point.coreGeometry();\\n const new_index_by_old_index = {};\\n for (let i = 0; i < points2.length; i++) {\\n new_index_by_old_index[points2[i].index()] = i;\\n }\\n const indices = this._indices_from_points(new_index_by_old_index, old_geometry);\\n if (indices) {\\n geometry.setIndex(indices);\\n }\\n const {attributes} = old_geometry;\\n for (let attribute_name of Object.keys(attributes)) {\\n const attrib_values = old_core_geometry.userDataAttribs()[attribute_name];\\n const is_attrib_indexed = attrib_values != null;\\n if (is_attrib_indexed) {\\n const new_values = ArrayUtils.uniq(points2.map((point) => point.indexedAttribValue(attribute_name)));\\n const new_index_by_value = {};\\n new_values.forEach((new_value, i) => new_index_by_value[new_value] = i);\\n core_geometry.userDataAttribs()[attribute_name] = new_values;\\n const new_attrib_indices = [];\\n for (let point of points2) {\\n const new_index = new_index_by_value[point.indexedAttribValue(attribute_name)];\\n new_attrib_indices.push(new_index);\\n }\\n geometry.setAttribute(attribute_name, new Float32BufferAttribute(new_attrib_indices, 1));\\n } else {\\n const attrib_size = attributes[attribute_name].itemSize;\\n const values = new Array(points2.length * attrib_size);\\n switch (attrib_size) {\\n case 1:\\n for (let i = 0; i < points2.length; i++) {\\n values[i] = points2[i].attribValue(attribute_name);\\n }\\n break;\\n default:\\n let value;\\n for (let i = 0; i < points2.length; i++) {\\n value = points2[i].attribValue(attribute_name);\\n value.toArray(values, i * attrib_size);\\n }\\n break;\\n }\\n geometry.setAttribute(attribute_name, new Float32BufferAttribute(values, attrib_size));\\n }\\n }\\n }\\n return geometry;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/builders/Points.ts\\nvar CoreGeometryBuilderPoints = class extends CoreGeometryBuilderBase {\\n _filter_points(points2) {\\n return points2;\\n }\\n _indices_from_points(new_index_by_old_index, old_geometry) {\\n const index_attrib = old_geometry.index;\\n if (index_attrib != null) {\\n const old_indices = index_attrib.array;\\n const new_indices = [];\\n let old_index;\\n let new_index;\\n for (let i = 0; i < old_indices.length; i++) {\\n old_index = old_indices[i];\\n new_index = new_index_by_old_index[old_index];\\n if (new_index != null) {\\n new_indices.push(new_index);\\n }\\n }\\n return new_indices;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/modules/three/examples/jsm/utils/BufferGeometryUtils.js\\nfunction mergeBufferGeometries(geometries, useGroups = false) {\\n const isIndexed = geometries[0].index !== null;\\n const attributesUsed = new Set(Object.keys(geometries[0].attributes));\\n const morphAttributesUsed = new Set(Object.keys(geometries[0].morphAttributes));\\n const attributes = {};\\n const morphAttributes = {};\\n const morphTargetsRelative = geometries[0].morphTargetsRelative;\\n const mergedGeometry = new BufferGeometry();\\n let offset = 0;\\n for (let i = 0; i < geometries.length; ++i) {\\n const geometry = geometries[i];\\n let attributesCount = 0;\\n if (isIndexed !== (geometry.index !== null)) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferGeometries() failed with geometry at index \\\\\\\" + i + \\\\\\\". All geometries must have compatible attributes; make sure index attribute exists among all geometries, or in none of them.\\\\\\\");\\n return null;\\n }\\n for (const name in geometry.attributes) {\\n if (!attributesUsed.has(name)) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferGeometries() failed with geometry at index \\\\\\\" + i + '. All geometries must have compatible attributes; make sure \\\\\\\"' + name + '\\\\\\\" attribute exists among all geometries, or in none of them.');\\n return null;\\n }\\n if (attributes[name] === void 0)\\n attributes[name] = [];\\n attributes[name].push(geometry.attributes[name]);\\n attributesCount++;\\n }\\n if (attributesCount !== attributesUsed.size) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferGeometries() failed with geometry at index \\\\\\\" + i + \\\\\\\". Make sure all geometries have the same number of attributes.\\\\\\\");\\n return null;\\n }\\n if (morphTargetsRelative !== geometry.morphTargetsRelative) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferGeometries() failed with geometry at index \\\\\\\" + i + \\\\\\\". .morphTargetsRelative must be consistent throughout all geometries.\\\\\\\");\\n return null;\\n }\\n for (const name in geometry.morphAttributes) {\\n if (!morphAttributesUsed.has(name)) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferGeometries() failed with geometry at index \\\\\\\" + i + \\\\\\\". .morphAttributes must be consistent throughout all geometries.\\\\\\\");\\n return null;\\n }\\n if (morphAttributes[name] === void 0)\\n morphAttributes[name] = [];\\n morphAttributes[name].push(geometry.morphAttributes[name]);\\n }\\n mergedGeometry.userData.mergedUserData = mergedGeometry.userData.mergedUserData || [];\\n mergedGeometry.userData.mergedUserData.push(geometry.userData);\\n if (useGroups) {\\n let count;\\n if (isIndexed) {\\n count = geometry.index.count;\\n } else if (geometry.attributes.position !== void 0) {\\n count = geometry.attributes.position.count;\\n } else {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferGeometries() failed with geometry at index \\\\\\\" + i + \\\\\\\". The geometry must have either an index or a position attribute\\\\\\\");\\n return null;\\n }\\n mergedGeometry.addGroup(offset, count, i);\\n offset += count;\\n }\\n }\\n if (isIndexed) {\\n let indexOffset = 0;\\n const mergedIndex = [];\\n for (let i = 0; i < geometries.length; ++i) {\\n const index = geometries[i].index;\\n for (let j = 0; j < index.count; ++j) {\\n mergedIndex.push(index.getX(j) + indexOffset);\\n }\\n indexOffset += geometries[i].attributes.position.count;\\n }\\n mergedGeometry.setIndex(mergedIndex);\\n }\\n for (const name in attributes) {\\n const mergedAttribute = mergeBufferAttributes(attributes[name]);\\n if (!mergedAttribute) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferGeometries() failed while trying to merge the \\\\\\\" + name + \\\\\\\" attribute.\\\\\\\");\\n return null;\\n }\\n mergedGeometry.setAttribute(name, mergedAttribute);\\n }\\n for (const name in morphAttributes) {\\n const numMorphTargets = morphAttributes[name][0].length;\\n if (numMorphTargets === 0)\\n break;\\n mergedGeometry.morphAttributes = mergedGeometry.morphAttributes || {};\\n mergedGeometry.morphAttributes[name] = [];\\n for (let i = 0; i < numMorphTargets; ++i) {\\n const morphAttributesToMerge = [];\\n for (let j = 0; j < morphAttributes[name].length; ++j) {\\n morphAttributesToMerge.push(morphAttributes[name][j][i]);\\n }\\n const mergedMorphAttribute = mergeBufferAttributes(morphAttributesToMerge);\\n if (!mergedMorphAttribute) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferGeometries() failed while trying to merge the \\\\\\\" + name + \\\\\\\" morphAttribute.\\\\\\\");\\n return null;\\n }\\n mergedGeometry.morphAttributes[name].push(mergedMorphAttribute);\\n }\\n }\\n return mergedGeometry;\\n}\\nfunction mergeBufferAttributes(attributes) {\\n let TypedArray;\\n let itemSize;\\n let normalized;\\n let arrayLength = 0;\\n for (let i = 0; i < attributes.length; ++i) {\\n const attribute = attributes[i];\\n if (attribute.isInterleavedBufferAttribute) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferAttributes() failed. InterleavedBufferAttributes are not supported.\\\\\\\");\\n return null;\\n }\\n if (TypedArray === void 0)\\n TypedArray = attribute.array.constructor;\\n if (TypedArray !== attribute.array.constructor) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferAttributes() failed. BufferAttribute.array must be of consistent array types across matching attributes.\\\\\\\");\\n return null;\\n }\\n if (itemSize === void 0)\\n itemSize = attribute.itemSize;\\n if (itemSize !== attribute.itemSize) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferAttributes() failed. BufferAttribute.itemSize must be consistent across matching attributes.\\\\\\\");\\n return null;\\n }\\n if (normalized === void 0)\\n normalized = attribute.normalized;\\n if (normalized !== attribute.normalized) {\\n console.error(\\\\\\\"THREE.BufferGeometryUtils: .mergeBufferAttributes() failed. BufferAttribute.normalized must be consistent across matching attributes.\\\\\\\");\\n return null;\\n }\\n arrayLength += attribute.array.length;\\n }\\n const array = new TypedArray(arrayLength);\\n let offset = 0;\\n for (let i = 0; i < attributes.length; ++i) {\\n array.set(attributes[i].array, offset);\\n offset += attributes[i].array.length;\\n }\\n return new BufferAttribute(array, itemSize, normalized);\\n}\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/util/IndexBuilder.ts\\nvar POSITION = \\\\\\\"position\\\\\\\";\\nvar CoreGeometryIndexBuilder = class {\\n static createIndexIfNone(geometry) {\\n if (!geometry.index) {\\n const position = geometry.getAttribute(POSITION);\\n if (position) {\\n const position_array = position.array;\\n geometry.setIndex(ArrayUtils.range(position_array.length / 3));\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/builders/Merge.ts\\nvar CoreGeometryBuilderMerge = class {\\n static merge(geometries) {\\n if (geometries.length === 0) {\\n return;\\n }\\n for (let geometry of geometries) {\\n CoreGeometryIndexBuilder.createIndexIfNone(geometry);\\n }\\n const core_geometries = geometries.map((geometry) => new CoreGeometry(geometry));\\n const indexed_attribute_names = core_geometries[0].indexedAttributeNames();\\n const new_values_by_attribute_name = {};\\n for (let indexed_attribute_name of indexed_attribute_names) {\\n const index_by_values = {};\\n const all_geometries_points = [];\\n for (let core_geometry of core_geometries) {\\n const geometry_points = core_geometry.points();\\n for (let point of geometry_points) {\\n all_geometries_points.push(point);\\n const value = point.indexedAttribValue(indexed_attribute_name);\\n index_by_values[value] != null ? index_by_values[value] : index_by_values[value] = Object.keys(index_by_values).length;\\n }\\n }\\n const values = Object.keys(index_by_values);\\n for (let point of all_geometries_points) {\\n const value = point.indexedAttribValue(indexed_attribute_name);\\n const new_index = index_by_values[value];\\n point.setAttribIndex(indexed_attribute_name, new_index);\\n }\\n new_values_by_attribute_name[indexed_attribute_name] = values;\\n }\\n const merged_geometry = mergeBufferGeometries(geometries);\\n const merged_core_geometry = new CoreGeometry(merged_geometry);\\n Object.keys(new_values_by_attribute_name).forEach((indexed_attribute_name) => {\\n const values = new_values_by_attribute_name[indexed_attribute_name];\\n merged_core_geometry.setIndexedAttributeValues(indexed_attribute_name, values);\\n });\\n if (merged_geometry) {\\n delete merged_geometry.userData.mergedUserData;\\n }\\n return merged_geometry;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/builders/Mesh.ts\\nvar CoreGeometryBuilderMesh = class extends CoreGeometryBuilderBase {\\n _filter_points(points2) {\\n const first_point = points2[0];\\n if (first_point) {\\n const geometry = first_point.geometry();\\n const indices = geometry.getIndex()?.array;\\n if (indices) {\\n const points_by_index = {};\\n for (let point of points2) {\\n points_by_index[point.index()] = point;\\n }\\n const filtered_points = [];\\n const index_length = indices.length;\\n let pt0;\\n let pt1;\\n let pt2;\\n for (let i = 0; i < index_length; i += 3) {\\n pt0 = points_by_index[indices[i + 0]];\\n pt1 = points_by_index[indices[i + 1]];\\n pt2 = points_by_index[indices[i + 2]];\\n if (pt0 && pt1 && pt2) {\\n filtered_points.push(pt0);\\n filtered_points.push(pt1);\\n filtered_points.push(pt2);\\n }\\n }\\n return filtered_points;\\n }\\n }\\n return [];\\n }\\n _indices_from_points(new_index_by_old_index, old_geometry) {\\n const index_attrib = old_geometry.index;\\n if (index_attrib != null) {\\n const old_indices = index_attrib.array;\\n const new_indices = [];\\n let old_index0;\\n let old_index1;\\n let old_index2;\\n let new_index0;\\n let new_index1;\\n let new_index2;\\n for (let i = 0; i < old_indices.length; i += 3) {\\n old_index0 = old_indices[i + 0];\\n old_index1 = old_indices[i + 1];\\n old_index2 = old_indices[i + 2];\\n new_index0 = new_index_by_old_index[old_index0];\\n new_index1 = new_index_by_old_index[old_index1];\\n new_index2 = new_index_by_old_index[old_index2];\\n if (new_index0 != null && new_index1 != null && new_index2 != null) {\\n new_indices.push(new_index0);\\n new_indices.push(new_index1);\\n new_indices.push(new_index2);\\n }\\n }\\n return new_indices;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/builders/LineSegments.ts\\nvar CoreGeometryBuilderLineSegments = class extends CoreGeometryBuilderBase {\\n _filter_points(points2) {\\n const first_point = points2[0];\\n if (first_point) {\\n const geometry = first_point.geometry();\\n const indices = geometry.getIndex()?.array;\\n if (indices) {\\n const points_by_index = {};\\n for (let point of points2) {\\n points_by_index[point.index()] = point;\\n }\\n const filtered_points = [];\\n const index_length = indices.length;\\n let pt0;\\n let pt1;\\n for (let i = 0; i < index_length; i += 2) {\\n pt0 = points_by_index[indices[i + 0]];\\n pt1 = points_by_index[indices[i + 1]];\\n if (pt0 && pt1) {\\n filtered_points.push(pt0);\\n filtered_points.push(pt1);\\n }\\n }\\n return filtered_points;\\n }\\n }\\n return [];\\n }\\n _indices_from_points(new_index_by_old_index, old_geometry) {\\n const index_attrib = old_geometry.index;\\n if (index_attrib != null) {\\n const old_indices = index_attrib.array;\\n const new_indices = [];\\n let old_index0;\\n let old_index1;\\n let new_index0;\\n let new_index1;\\n for (let i = 0; i < old_indices.length; i += 2) {\\n old_index0 = old_indices[i];\\n old_index1 = old_indices[i + 1];\\n new_index0 = new_index_by_old_index[old_index0];\\n new_index1 = new_index_by_old_index[old_index1];\\n if (new_index0 != null && new_index1 != null) {\\n new_indices.push(new_index0);\\n new_indices.push(new_index1);\\n }\\n }\\n return new_indices;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/ObjectUtils.ts\\nvar import_cloneDeep = __toModule(require_cloneDeep());\\nvar import_clone = __toModule(require_clone());\\nvar ObjectUtils = class {\\n static isEqual(object0, object1) {\\n if (CoreType.isObject(object0) && CoreType.isObject(object1)) {\\n const keys0 = Object.keys(object0);\\n const keys1 = Object.keys(object1);\\n if (!ArrayUtils.isEqual(keys0, keys1)) {\\n return false;\\n }\\n return JSON.stringify(object0) == JSON.stringify(object1);\\n }\\n return false;\\n }\\n static merge(object0, object1) {\\n return Object.assign(object0, object1);\\n }\\n static clone(value) {\\n return import_clone.default(value);\\n }\\n static cloneDeep(value) {\\n return import_cloneDeep.default(value);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Geometry.ts\\nvar IS_INSTANCE_KEY = \\\\\\\"isInstance\\\\\\\";\\nvar INDEX_ATTRIB_VALUES = \\\\\\\"indexed_attrib_values\\\\\\\";\\nvar CoreGeometry2 = class {\\n constructor(_geometry) {\\n this._geometry = _geometry;\\n }\\n geometry() {\\n return this._geometry;\\n }\\n uuid() {\\n return this._geometry.uuid;\\n }\\n boundingBox() {\\n return this._bounding_box = this._bounding_box || this._create_bounding_box();\\n }\\n _create_bounding_box() {\\n this._geometry.computeBoundingBox();\\n if (this._geometry.boundingBox) {\\n return this._geometry.boundingBox;\\n }\\n }\\n markAsInstance() {\\n this._geometry.userData[IS_INSTANCE_KEY] = true;\\n }\\n static markedAsInstance(geometry) {\\n return geometry.userData[IS_INSTANCE_KEY] === true;\\n }\\n markedAsInstance() {\\n return CoreGeometry2.markedAsInstance(this._geometry);\\n }\\n positionAttribName() {\\n let name = \\\\\\\"position\\\\\\\";\\n if (this.markedAsInstance()) {\\n name = \\\\\\\"instancePosition\\\\\\\";\\n }\\n return name;\\n }\\n computeVertexNormals() {\\n this._geometry.computeVertexNormals();\\n }\\n userDataAttribs() {\\n return this._geometry.userData[INDEX_ATTRIB_VALUES] = this._geometry.userData[INDEX_ATTRIB_VALUES] || {};\\n }\\n indexedAttributeNames() {\\n return Object.keys(this.userDataAttribs() || {});\\n }\\n userDataAttrib(name) {\\n name = CoreAttribute.remapName(name);\\n return this.userDataAttribs()[name];\\n }\\n isAttribIndexed(name) {\\n name = CoreAttribute.remapName(name);\\n return this.userDataAttrib(name) != null;\\n }\\n hasAttrib(name) {\\n if (name === \\\\\\\"ptnum\\\\\\\") {\\n return true;\\n }\\n name = CoreAttribute.remapName(name);\\n return this._geometry.attributes[name] != null;\\n }\\n attribType(name) {\\n if (this.isAttribIndexed(name)) {\\n return AttribType.STRING;\\n } else {\\n return AttribType.NUMERIC;\\n }\\n }\\n static attribNames(geometry) {\\n return Object.keys(geometry.attributes);\\n }\\n attribNames() {\\n return CoreGeometry2.attribNames(this._geometry);\\n }\\n static attribNamesMatchingMask(geometry, masks_string) {\\n const masks = CoreString.attribNames(masks_string);\\n const matching_attrib_names = [];\\n for (let attrib_name of this.attribNames(geometry)) {\\n for (let mask of masks) {\\n if (CoreString.matchMask(attrib_name, mask)) {\\n matching_attrib_names.push(attrib_name);\\n }\\n }\\n }\\n return ArrayUtils.uniq(matching_attrib_names);\\n }\\n attribSizes() {\\n const h = {};\\n for (let attrib_name of this.attribNames()) {\\n h[attrib_name] = this._geometry.attributes[attrib_name].itemSize;\\n }\\n return h;\\n }\\n attribSize(name) {\\n let attrib;\\n name = CoreAttribute.remapName(name);\\n if ((attrib = this._geometry.attributes[name]) != null) {\\n return attrib.itemSize;\\n } else {\\n if (name === \\\\\\\"ptnum\\\\\\\") {\\n return 1;\\n } else {\\n return 0;\\n }\\n }\\n }\\n setIndexedAttributeValues(name, values) {\\n this.userDataAttribs()[name] = values;\\n }\\n setIndexedAttribute(name, values, indices) {\\n this.setIndexedAttributeValues(name, values);\\n this._geometry.setAttribute(name, new Int32BufferAttribute(indices, 1));\\n }\\n addNumericAttrib(name, size = 1, default_value = 0) {\\n const values = [];\\n let attribute_added = false;\\n if (CoreType.isNumber(default_value)) {\\n for (let i = 0; i < this.pointsCount(); i++) {\\n for (let j = 0; j < size; j++) {\\n values.push(default_value);\\n }\\n }\\n attribute_added = true;\\n } else {\\n if (size > 1) {\\n if (CoreType.isArray(default_value)) {\\n for (let i = 0; i < this.pointsCount(); i++) {\\n for (let j = 0; j < size; j++) {\\n values.push(default_value[j]);\\n }\\n }\\n attribute_added = true;\\n } else {\\n const vec2 = default_value;\\n if (size == 2 && vec2.x != null && vec2.y != null) {\\n for (let i = 0; i < this.pointsCount(); i++) {\\n values.push(vec2.x);\\n values.push(vec2.y);\\n }\\n attribute_added = true;\\n }\\n const vec3 = default_value;\\n if (size == 3 && vec3.x != null && vec3.y != null && vec3.z != null) {\\n for (let i = 0; i < this.pointsCount(); i++) {\\n values.push(vec3.x);\\n values.push(vec3.y);\\n values.push(vec3.z);\\n }\\n attribute_added = true;\\n }\\n const col = default_value;\\n if (size == 3 && col.r != null && col.g != null && col.b != null) {\\n for (let i = 0; i < this.pointsCount(); i++) {\\n values.push(col.r);\\n values.push(col.g);\\n values.push(col.b);\\n }\\n attribute_added = true;\\n }\\n const vec4 = default_value;\\n if (size == 4 && vec4.x != null && vec4.y != null && vec4.z != null && vec4.w != null) {\\n for (let i = 0; i < this.pointsCount(); i++) {\\n values.push(vec4.x);\\n values.push(vec4.y);\\n values.push(vec4.z);\\n values.push(vec4.w);\\n }\\n attribute_added = true;\\n }\\n }\\n }\\n }\\n if (attribute_added) {\\n this._geometry.setAttribute(name.trim(), new Float32BufferAttribute(values, size));\\n } else {\\n console.warn(default_value);\\n throw `CoreGeometry.add_numeric_attrib error: no other default value allowed for now in add_numeric_attrib (default given: ${default_value})`;\\n }\\n }\\n initPositionAttribute(points_count, default_value) {\\n const values = [];\\n if (default_value == null) {\\n default_value = new Vector3();\\n }\\n for (let i = 0; i < points_count; i++) {\\n values.push(default_value.x);\\n values.push(default_value.y);\\n values.push(default_value.z);\\n }\\n return this._geometry.setAttribute(\\\\\\\"position\\\\\\\", new Float32BufferAttribute(values, 3));\\n }\\n addAttribute(name, attrib_data) {\\n switch (attrib_data.type()) {\\n case AttribType.STRING:\\n return console.log(\\\\\\\"TODO: to implement\\\\\\\");\\n case AttribType.NUMERIC:\\n return this.addNumericAttrib(name, attrib_data.size());\\n }\\n }\\n renameAttrib(old_name, new_name) {\\n if (this.isAttribIndexed(old_name)) {\\n this.userDataAttribs()[new_name] = ObjectUtils.clone(this.userDataAttribs()[old_name]);\\n delete this.userDataAttribs()[old_name];\\n }\\n const old_attrib = this._geometry.getAttribute(old_name);\\n this._geometry.setAttribute(new_name.trim(), new Float32BufferAttribute(old_attrib.array, old_attrib.itemSize));\\n return this._geometry.deleteAttribute(old_name);\\n }\\n deleteAttribute(name) {\\n if (this.isAttribIndexed(name)) {\\n delete this.userDataAttribs()[name];\\n }\\n return this._geometry.deleteAttribute(name);\\n }\\n clone() {\\n return CoreGeometry2.clone(this._geometry);\\n }\\n static clone(src_geometry) {\\n let src_userData;\\n const new_geometry = src_geometry.clone();\\n if ((src_userData = src_geometry.userData) != null) {\\n new_geometry.userData = ObjectUtils.cloneDeep(src_userData);\\n }\\n return new_geometry;\\n }\\n pointsCount() {\\n return CoreGeometry2.pointsCount(this._geometry);\\n }\\n static pointsCount(geometry) {\\n let position;\\n let count = 0;\\n const core_geometry = new this(geometry);\\n let position_attrib_name = \\\\\\\"position\\\\\\\";\\n if (core_geometry.markedAsInstance()) {\\n position_attrib_name = \\\\\\\"instancePosition\\\\\\\";\\n }\\n if ((position = geometry.getAttribute(position_attrib_name)) != null) {\\n let array;\\n if ((array = position.array) != null) {\\n count = array.length / 3;\\n }\\n }\\n return count;\\n }\\n points() {\\n return this.pointsFromGeometry();\\n }\\n pointsFromGeometry() {\\n const points2 = [];\\n const positionAttrib = this._geometry.getAttribute(this.positionAttribName());\\n if (positionAttrib != null) {\\n const count = positionAttrib.array.length / 3;\\n for (let i = 0; i < count; i++) {\\n const point = new CorePoint(this, i);\\n points2.push(point);\\n }\\n }\\n return points2;\\n }\\n static geometryFromPoints(points2, object_type) {\\n switch (object_type) {\\n case ObjectType.MESH:\\n return this._mesh_builder.from_points(points2);\\n case ObjectType.POINTS:\\n return this._points_builder.from_points(points2);\\n case ObjectType.LINE_SEGMENTS:\\n return this._lines_segment_builder.from_points(points2);\\n case ObjectType.OBJECT3D:\\n return null;\\n case ObjectType.GROUP:\\n return null;\\n case ObjectType.LOD:\\n return null;\\n }\\n TypeAssert.unreachable(object_type);\\n }\\n static mergeGeometries(geometries) {\\n return CoreGeometryBuilderMerge.merge(geometries);\\n }\\n static merge_geometries(geometries) {\\n return CoreGeometryBuilderMerge.merge(geometries);\\n }\\n segments() {\\n const index = this.geometry().index?.array || [];\\n return ArrayUtils.chunk(index, 2);\\n }\\n faces() {\\n return this.facesFromGeometry();\\n }\\n facesFromGeometry() {\\n const index_array = this.geometry().index?.array || [];\\n const faces_count = index_array.length / 3;\\n return ArrayUtils.range(faces_count).map((i) => new CoreFace(this, i));\\n }\\n};\\nvar CoreGeometry = CoreGeometry2;\\nCoreGeometry._mesh_builder = new CoreGeometryBuilderMesh();\\nCoreGeometry._points_builder = new CoreGeometryBuilderPoints();\\nCoreGeometry._lines_segment_builder = new CoreGeometryBuilderLineSegments();\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Material.ts\\nvar CustomMaterialName;\\n(function(CustomMaterialName2) {\\n CustomMaterialName2[\\\\\\\"customDistanceMaterial\\\\\\\"] = \\\\\\\"customDistanceMaterial\\\\\\\";\\n CustomMaterialName2[\\\\\\\"customDepthMaterial\\\\\\\"] = \\\\\\\"customDepthMaterial\\\\\\\";\\n CustomMaterialName2[\\\\\\\"customDepthDOFMaterial\\\\\\\"] = \\\\\\\"customDepthDOFMaterial\\\\\\\";\\n})(CustomMaterialName || (CustomMaterialName = {}));\\nvar RENDER_HOOK_USER_DATA_KEY = \\\\\\\"POLY_render_hook\\\\\\\";\\nvar EMPTY_RENDER_HOOK = (renderer, scene, camera, geometry, material, group) => {\\n};\\nvar CoreMaterial = class {\\n static node(scene, material) {\\n return scene.node(material.name);\\n }\\n static clone(src_material) {\\n const cloned_material = src_material.clone();\\n const src_uniforms = src_material.uniforms;\\n if (src_uniforms) {\\n cloned_material.uniforms = UniformsUtils.clone(src_uniforms);\\n }\\n return cloned_material;\\n }\\n static add_user_data_render_hook(material, render_hook) {\\n material.userData[RENDER_HOOK_USER_DATA_KEY] = render_hook;\\n }\\n static apply_render_hook(object, material) {\\n if (material.userData) {\\n const render_hook = material.userData[RENDER_HOOK_USER_DATA_KEY];\\n if (render_hook) {\\n object.onBeforeRender = (renderer, scene, camera, geometry, material2, group) => {\\n render_hook(renderer, scene, camera, geometry, material2, group, object);\\n };\\n return;\\n }\\n }\\n object.onBeforeRender = EMPTY_RENDER_HOOK;\\n }\\n static applyCustomMaterials(object, material) {\\n const material_with_custom = material;\\n if (material_with_custom.customMaterials) {\\n for (let name of Object.keys(material_with_custom.customMaterials)) {\\n const mat_name = name;\\n const custom_material = material_with_custom.customMaterials[mat_name];\\n if (custom_material) {\\n object[mat_name] = custom_material;\\n custom_material.needsUpdate = true;\\n }\\n }\\n }\\n }\\n static assign_custom_uniforms(mat, uniform_name, uniform_value) {\\n const material = mat;\\n if (material.customMaterials) {\\n for (let name of Object.keys(material.customMaterials)) {\\n const mat_name = name;\\n const custom_material = material.customMaterials[mat_name];\\n if (custom_material) {\\n custom_material.uniforms[uniform_name].value = uniform_value;\\n }\\n }\\n }\\n }\\n static init_custom_material_uniforms(mat, uniform_name, uniform_value) {\\n const material = mat;\\n if (material.customMaterials) {\\n for (let name of Object.keys(material.customMaterials)) {\\n const mat_name = name;\\n const custom_material = material.customMaterials[mat_name];\\n if (custom_material) {\\n custom_material.uniforms[uniform_name] = custom_material.uniforms[uniform_name] || uniform_value;\\n }\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Object.ts\\nvar PTNUM2 = \\\\\\\"ptnum\\\\\\\";\\nvar NAME_ATTR = \\\\\\\"name\\\\\\\";\\nvar ATTRIBUTES = \\\\\\\"attributes\\\\\\\";\\nvar CoreObject = class extends CoreEntity {\\n constructor(_object, index) {\\n super(index);\\n this._object = _object;\\n if (this._object.userData[ATTRIBUTES] == null) {\\n this._object.userData[ATTRIBUTES] = {};\\n }\\n }\\n object() {\\n return this._object;\\n }\\n geometry() {\\n return this._object.geometry;\\n }\\n coreGeometry() {\\n const geo = this.geometry();\\n if (geo) {\\n return new CoreGeometry(geo);\\n } else {\\n return null;\\n }\\n }\\n points() {\\n return this.coreGeometry()?.points() || [];\\n }\\n pointsFromGroup(group) {\\n if (group) {\\n const indices = CoreString.indices(group);\\n if (indices) {\\n const points2 = this.points();\\n return indices.map((i) => points2[i]);\\n } else {\\n return [];\\n }\\n } else {\\n return this.points();\\n }\\n }\\n static isInGroup(groupString, object) {\\n const group = groupString.trim();\\n if (group.length == 0) {\\n return true;\\n }\\n const elements = group.split(\\\\\\\"=\\\\\\\");\\n const attribNameWithPrefix = elements[0];\\n if (attribNameWithPrefix[0] == \\\\\\\"@\\\\\\\") {\\n const attribName = attribNameWithPrefix.substr(1);\\n const expectedAttribValue = elements[1];\\n const currentAttribValue = this.attribValue(object, attribName);\\n return expectedAttribValue == currentAttribValue;\\n }\\n return false;\\n }\\n computeVertexNormals() {\\n this.coreGeometry()?.computeVertexNormals();\\n }\\n static _convert_array_to_vector(value) {\\n switch (value.length) {\\n case 1:\\n return value[0];\\n case 2:\\n return new Vector2(value[0], value[1]);\\n case 3:\\n return new Vector3(value[0], value[1], value[2]);\\n case 4:\\n return new Vector4(value[0], value[1], value[2], value[3]);\\n }\\n }\\n static addAttribute(object, attrib_name, value) {\\n if (CoreType.isArray(value)) {\\n const converted_value = this._convert_array_to_vector(value);\\n if (!converted_value) {\\n const message = `attribute_value invalid`;\\n console.error(message, value);\\n throw new Error(message);\\n }\\n }\\n const data = value;\\n const user_data = object.userData;\\n user_data[ATTRIBUTES] = user_data[ATTRIBUTES] || {};\\n user_data[ATTRIBUTES][attrib_name] = data;\\n }\\n addAttribute(name, value) {\\n CoreObject.addAttribute(this._object, name, value);\\n }\\n addNumericAttrib(name, value) {\\n this.addAttribute(name, value);\\n }\\n setAttribValue(name, value) {\\n this.addAttribute(name, value);\\n }\\n addNumericVertexAttrib(name, size, default_value) {\\n if (default_value == null) {\\n default_value = CoreAttribute.default_value(size);\\n }\\n this.coreGeometry()?.addNumericAttrib(name, size, default_value);\\n }\\n attributeNames() {\\n return Object.keys(this._object.userData[ATTRIBUTES]);\\n }\\n attribNames() {\\n return this.attributeNames();\\n }\\n hasAttrib(name) {\\n return this.attributeNames().includes(name);\\n }\\n renameAttrib(old_name, new_name) {\\n const current_value = this.attribValue(old_name);\\n if (current_value != null) {\\n this.addAttribute(new_name, current_value);\\n this.deleteAttribute(old_name);\\n } else {\\n console.warn(`attribute ${old_name} not found`);\\n }\\n }\\n deleteAttribute(name) {\\n delete this._object.userData[ATTRIBUTES][name];\\n }\\n static attribValue(object, name, index = 0, target) {\\n if (name === PTNUM2) {\\n return index;\\n }\\n if (object.userData && object.userData[ATTRIBUTES]) {\\n const val = object.userData[ATTRIBUTES][name];\\n if (val == null) {\\n if (name == NAME_ATTR) {\\n return object.name;\\n }\\n } else {\\n if (CoreType.isArray(val) && target) {\\n target.fromArray(val);\\n return target;\\n }\\n }\\n return val;\\n }\\n if (name == NAME_ATTR) {\\n return object.name;\\n }\\n }\\n static stringAttribValue(object, name, index = 0) {\\n const str = this.attribValue(object, name, index);\\n if (str != null) {\\n if (CoreType.isString(str)) {\\n return str;\\n } else {\\n return `${str}`;\\n }\\n }\\n }\\n attribValue(name, target) {\\n return CoreObject.attribValue(this._object, name, this._index, target);\\n }\\n stringAttribValue(name) {\\n return CoreObject.stringAttribValue(this._object, name, this._index);\\n }\\n name() {\\n return this.attribValue(NAME_ATTR);\\n }\\n humanType() {\\n return CoreConstant.CONSTRUCTOR_NAMES_BY_CONSTRUCTOR_NAME[this._object.constructor.name];\\n }\\n attribTypes() {\\n const h = {};\\n for (let attrib_name of this.attribNames()) {\\n const type = this.attribType(attrib_name);\\n if (type != null) {\\n h[attrib_name] = type;\\n }\\n }\\n return h;\\n }\\n attribType(name) {\\n const val = this.attribValue(name);\\n if (CoreType.isString(val)) {\\n return AttribType.STRING;\\n } else {\\n return AttribType.NUMERIC;\\n }\\n }\\n attribSizes() {\\n const h = {};\\n for (let attrib_name of this.attribNames()) {\\n const size = this.attribSize(attrib_name);\\n if (size != null) {\\n h[attrib_name] = size;\\n }\\n }\\n return h;\\n }\\n attribSize(name) {\\n const val = this.attribValue(name);\\n if (val == null) {\\n return null;\\n }\\n return CoreAttribute.attribSizeFromValue(val);\\n }\\n clone() {\\n return CoreObject.clone(this._object);\\n }\\n static clone(src_object) {\\n const new_object = src_object.clone();\\n var sourceLookup = new Map();\\n var cloneLookup = new Map();\\n CoreObject.parallelTraverse(src_object, new_object, function(sourceNode, clonedNode) {\\n sourceLookup.set(clonedNode, sourceNode);\\n cloneLookup.set(sourceNode, clonedNode);\\n });\\n new_object.traverse(function(node) {\\n const src_node = sourceLookup.get(node);\\n const mesh_node = node;\\n if (mesh_node.geometry) {\\n const src_node_geometry = src_node.geometry;\\n mesh_node.geometry = CoreGeometry.clone(src_node_geometry);\\n const mesh_node_geometry = mesh_node.geometry;\\n if (mesh_node_geometry.userData) {\\n mesh_node_geometry.userData = ObjectUtils.cloneDeep(src_node_geometry.userData);\\n }\\n }\\n if (mesh_node.material) {\\n mesh_node.material = src_node.material;\\n CoreMaterial.applyCustomMaterials(node, mesh_node.material);\\n const material_with_color = mesh_node.material;\\n if (material_with_color.color == null) {\\n material_with_color.color = new Color(1, 1, 1);\\n }\\n }\\n if (src_object.userData) {\\n node.userData = ObjectUtils.cloneDeep(src_node.userData);\\n }\\n const src_node_with_animations = src_node;\\n if (src_node_with_animations.animations) {\\n node.animations = src_node_with_animations.animations.map((animation) => animation.clone());\\n }\\n const skinned_node = node;\\n if (skinned_node.isSkinnedMesh) {\\n var clonedMesh = skinned_node;\\n var sourceMesh = src_node;\\n var sourceBones = sourceMesh.skeleton.bones;\\n clonedMesh.skeleton = sourceMesh.skeleton.clone();\\n clonedMesh.bindMatrix.copy(sourceMesh.bindMatrix);\\n const new_bones = sourceBones.map(function(bone) {\\n return cloneLookup.get(bone);\\n });\\n clonedMesh.skeleton.bones = new_bones;\\n clonedMesh.bind(clonedMesh.skeleton, clonedMesh.bindMatrix);\\n }\\n });\\n return new_object;\\n }\\n static parallelTraverse(a, b, callback) {\\n callback(a, b);\\n for (var i = 0; i < a.children.length; i++) {\\n this.parallelTraverse(a.children[i], b.children[i], callback);\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Geometry.ts\\nvar GeometryContainer = class extends TypedContainer {\\n coreContentCloned() {\\n if (this._content) {\\n return this._content.clone();\\n }\\n }\\n set_content(content) {\\n super.set_content(content);\\n }\\n firstObject() {\\n if (this._content) {\\n return this._content.objects()[0];\\n }\\n }\\n firstCoreObject() {\\n const object = this.firstObject();\\n if (object) {\\n return new CoreObject(object, 0);\\n }\\n }\\n firstGeometry() {\\n const object = this.firstObject();\\n if (object) {\\n return object.geometry;\\n } else {\\n return null;\\n }\\n }\\n objectsCount() {\\n if (this._content) {\\n return this._content.objects().length;\\n } else {\\n return 0;\\n }\\n }\\n objectsVisibleCount() {\\n let count = 0;\\n if (this._content) {\\n const objects = this._content.objects();\\n for (let object of objects) {\\n if (object.visible) {\\n count++;\\n }\\n }\\n }\\n return count;\\n }\\n objectsCountByType() {\\n const count_by_type = {};\\n const core_group = this._content;\\n if (this._content && core_group) {\\n for (let core_object of core_group.coreObjects()) {\\n const human_type = core_object.humanType();\\n if (count_by_type[human_type] == null) {\\n count_by_type[human_type] = 0;\\n }\\n count_by_type[human_type] += 1;\\n }\\n }\\n return count_by_type;\\n }\\n objectsNamesByType() {\\n const names_by_type = {};\\n const core_group = this._content;\\n if (this._content && core_group) {\\n for (let core_object of core_group.coreObjects()) {\\n const human_type = core_object.humanType();\\n names_by_type[human_type] = names_by_type[human_type] || [];\\n names_by_type[human_type].push(core_object.name());\\n }\\n }\\n return names_by_type;\\n }\\n pointAttributeNames() {\\n let names = [];\\n const geometry = this.firstGeometry();\\n if (geometry) {\\n names = Object.keys(geometry.attributes);\\n }\\n return names;\\n }\\n pointAttributeSizesByName() {\\n let sizes_by_name = {};\\n const geometry = this.firstGeometry();\\n if (geometry) {\\n Object.keys(geometry.attributes).forEach((attrib_name) => {\\n const attrib = geometry.attributes[attrib_name];\\n sizes_by_name[attrib_name] = attrib.itemSize;\\n });\\n }\\n return sizes_by_name;\\n }\\n objectAttributeSizesByName() {\\n let sizes_by_name = {};\\n const core_object = this.firstCoreObject();\\n if (core_object) {\\n const attribNames = core_object.attribNames();\\n for (let name of attribNames) {\\n const size = core_object.attribSize(name);\\n if (size != null) {\\n sizes_by_name[name] = size;\\n }\\n }\\n }\\n return sizes_by_name;\\n }\\n pointAttributeTypesByName() {\\n let types_by_name = {};\\n const geometry = this.firstGeometry();\\n if (geometry) {\\n const core_geo = new CoreGeometry(geometry);\\n Object.keys(geometry.attributes).forEach((attrib_name) => {\\n types_by_name[attrib_name] = core_geo.attribType(attrib_name);\\n });\\n }\\n return types_by_name;\\n }\\n objectAttributeTypesByName() {\\n let types_by_name = {};\\n const core_object = this.firstCoreObject();\\n if (core_object) {\\n for (let name of core_object.attribNames()) {\\n types_by_name[name] = core_object.attribType(name);\\n }\\n }\\n return types_by_name;\\n }\\n objectAttributeNames() {\\n let names = [];\\n const object = this.firstObject();\\n if (object) {\\n names = Object.keys(object.userData[\\\\\\\"attributes\\\\\\\"] || {});\\n }\\n return names;\\n }\\n pointsCount() {\\n if (this._content) {\\n return this._content.pointsCount();\\n } else {\\n return 0;\\n }\\n }\\n totalPointsCount() {\\n if (this._content) {\\n return this._content.totalPointsCount();\\n } else {\\n return 0;\\n }\\n }\\n objectsData() {\\n if (this._content) {\\n return this._content.objectsData();\\n } else {\\n return [];\\n }\\n }\\n boundingBox(forceUpdate = false) {\\n return this._content.boundingBox(forceUpdate);\\n }\\n center() {\\n return this._content.center();\\n }\\n size() {\\n return this._content.size();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Gl.ts\\nvar GlContainer = class extends TypedContainer {\\n object() {\\n return this._content;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Js.ts\\nvar JsContainer = class extends TypedContainer {\\n object() {\\n return this._content;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Manager.ts\\nvar ManagerContainer = class extends TypedContainer {\\n set_content(content) {\\n super.set_content(content);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Material.ts\\nvar MaterialContainer = class extends TypedContainer {\\n set_content(content) {\\n super.set_content(content);\\n }\\n set_material(material) {\\n if (this._content != null) {\\n this._content.dispose();\\n }\\n this.set_content(material);\\n }\\n has_material() {\\n return this.has_content();\\n }\\n material() {\\n return this.content();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Object.ts\\nvar ObjectContainer = class extends TypedContainer {\\n set_content(content) {\\n super.set_content(content);\\n }\\n set_object(object) {\\n return this.set_content(object);\\n }\\n has_object() {\\n return this.has_content();\\n }\\n object() {\\n return this.content();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Texture.ts\\nvar TextureContainer = class extends TypedContainer {\\n set_content(content) {\\n super.set_content(content);\\n }\\n texture() {\\n return this._content;\\n }\\n coreContent() {\\n return this._content;\\n }\\n coreContentCloned() {\\n const texture = this._content?.clone();\\n if (texture) {\\n texture.needsUpdate = true;\\n }\\n return texture;\\n }\\n object() {\\n return this.texture();\\n }\\n infos() {\\n if (this._content != null) {\\n return [this._content];\\n }\\n }\\n resolution() {\\n if (this._content) {\\n const image = this._content.image;\\n if (image) {\\n if (image instanceof HTMLImageElement || image instanceof Image || image instanceof ImageData || image instanceof HTMLCanvasElement) {\\n return [image.width, image.height];\\n }\\n if (image.data && image.width != null && image.height != null) {\\n return [image.width, image.height];\\n }\\n const video = image;\\n return [video.videoWidth, video.videoHeight];\\n }\\n }\\n return [-1, -1];\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/PostProcess.ts\\nvar PostProcessContainer = class extends TypedContainer {\\n set_content(content) {\\n super.set_content(content);\\n }\\n render_pass() {\\n return this._content;\\n }\\n object(options = {}) {\\n return this.render_pass();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/Rop.ts\\nvar RopContainer = class extends TypedContainer {\\n set_content(content) {\\n super.set_content(content);\\n }\\n renderer() {\\n return this._content;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/containers/utils/ContainerMap.ts\\nvar ContainerClassMap = {\\n [NodeContext.ANIM]: AnimationContainer,\\n [NodeContext.COP]: TextureContainer,\\n [NodeContext.EVENT]: EventContainer,\\n [NodeContext.GL]: GlContainer,\\n [NodeContext.JS]: JsContainer,\\n [NodeContext.MANAGER]: ManagerContainer,\\n [NodeContext.MAT]: MaterialContainer,\\n [NodeContext.OBJ]: ObjectContainer,\\n [NodeContext.POST]: PostProcessContainer,\\n [NodeContext.ROP]: RopContainer,\\n [NodeContext.SOP]: GeometryContainer\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/ContainerController.ts\\nvar TypedContainerController = class {\\n constructor(node) {\\n this.node = node;\\n this._callbacks = [];\\n this._callbacks_tmp = [];\\n const container_class = ContainerClassMap[node.context()];\\n this._container = new container_class(this.node);\\n }\\n container() {\\n return this._container;\\n }\\n async compute() {\\n if (this.node.flags?.bypass?.active()) {\\n const container = await this.requestInputContainer(0) || this._container;\\n this.node.cookController.endCook();\\n return container;\\n }\\n if (this.node.isDirty()) {\\n return new Promise((resolve, reject) => {\\n this._callbacks.push(resolve);\\n this.node.cookController.cookMain();\\n });\\n }\\n return this._container;\\n }\\n async requestInputContainer(input_index) {\\n const inputNode = this.node.io.inputs.input(input_index);\\n if (inputNode) {\\n return await inputNode.compute();\\n } else {\\n this.node.states.error.set(`input ${input_index} required`);\\n this.notifyRequesters();\\n return null;\\n }\\n }\\n notifyRequesters(container) {\\n this._callbacks_tmp = this._callbacks.slice();\\n this._callbacks.splice(0, this._callbacks.length);\\n if (!container) {\\n container = this.node.containerController.container();\\n }\\n let callback;\\n while (callback = this._callbacks_tmp.pop()) {\\n callback(container);\\n }\\n this.node.scene().cookController.removeNode(this.node);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/cook/PerformanceController.ts\\nvar performance = Poly.performance.performanceManager();\\nvar NodeCookPerformanceformanceController = class {\\n constructor(cookController) {\\n this.cookController = cookController;\\n this._inputs_start = 0;\\n this._params_start = 0;\\n this._cook_start = 0;\\n this._cooksCount = 0;\\n this._data = {\\n inputsTime: 0,\\n paramsTime: 0,\\n cookTime: 0\\n };\\n }\\n cooksCount() {\\n return this._cooksCount;\\n }\\n data2() {\\n return this._data;\\n }\\n active() {\\n return this.cookController.performanceRecordStarted();\\n }\\n recordInputsStart() {\\n if (this.active()) {\\n this._inputs_start = performance.now();\\n }\\n }\\n recordInputsEnd() {\\n if (this.active()) {\\n this._data.inputsTime = performance.now() - this._inputs_start;\\n }\\n }\\n recordParamsStart() {\\n if (this.active()) {\\n this._params_start = performance.now();\\n }\\n }\\n recordParamsEnd() {\\n if (this.active()) {\\n this._data.paramsTime = performance.now() - this._params_start;\\n }\\n }\\n recordCookStart() {\\n if (this.active()) {\\n this._cook_start = performance.now();\\n }\\n }\\n recordCookEnd() {\\n if (this.active()) {\\n this._data.cookTime = performance.now() - this._cook_start;\\n this._cooksCount += 1;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/CookController.ts\\nvar NodeCookController = class {\\n constructor(node) {\\n this.node = node;\\n this._cooking = false;\\n this._performanceController = new NodeCookPerformanceformanceController(this);\\n this._inputs_evaluation_required = true;\\n this._core_performance = this.node.scene().performance;\\n }\\n performanceRecordStarted() {\\n return this._core_performance.started();\\n }\\n disallowInputsEvaluation() {\\n this._inputs_evaluation_required = false;\\n }\\n isCooking() {\\n return this._cooking === true;\\n }\\n _start_cook_if_no_errors(input_contents) {\\n if (this.node.states.error.active()) {\\n this.endCook();\\n } else {\\n try {\\n this._performanceController.recordCookStart();\\n this.node.cook(input_contents);\\n } catch (e) {\\n this.node.states.error.set(`node internal error: '${e}'.`);\\n Poly.warn(e);\\n this.endCook();\\n }\\n }\\n }\\n async cookMain() {\\n if (this.isCooking()) {\\n return;\\n }\\n this._initCookingState();\\n this.node.states.error.clear();\\n this.node.scene().cookController.addNode(this.node);\\n let input_contents;\\n if (this._inputs_evaluation_required) {\\n input_contents = await this._evaluateInputs();\\n } else {\\n input_contents = [];\\n }\\n if (this.node.params.paramsEvalRequired()) {\\n await this._evaluateParams();\\n }\\n this._start_cook_if_no_errors(input_contents);\\n }\\n async cookMainWithoutInputs() {\\n this.node.scene().cookController.addNode(this.node);\\n if (this.isCooking()) {\\n Poly.warn(\\\\\\\"cook_main_without_inputs already cooking\\\\\\\", this.node.path());\\n return;\\n }\\n this._initCookingState();\\n this.node.states.error.clear();\\n if (this.node.params.paramsEvalRequired()) {\\n await this._evaluateParams();\\n }\\n this._start_cook_if_no_errors([]);\\n }\\n endCook(message) {\\n this._finalizeCookPerformance();\\n const dirty_timestamp = this.node.dirtyController.dirtyTimestamp();\\n if (dirty_timestamp == null || dirty_timestamp === this._cooking_dirty_timestamp) {\\n this.node.removeDirtyState();\\n this._terminateCookProcess();\\n } else {\\n Poly.log(\\\\\\\"COOK AGAIN\\\\\\\", dirty_timestamp, this._cooking_dirty_timestamp, this.node.path());\\n this._cooking = false;\\n this.cookMain();\\n }\\n }\\n _initCookingState() {\\n this._cooking = true;\\n this._cooking_dirty_timestamp = this.node.dirtyController.dirtyTimestamp();\\n }\\n _terminateCookProcess() {\\n if (this.isCooking()) {\\n this._cooking = false;\\n this.node.containerController.notifyRequesters();\\n this._run_on_cook_complete_hooks();\\n }\\n }\\n async _evaluateInputs() {\\n this._performanceController.recordInputsStart();\\n let input_containers = [];\\n const io_inputs = this.node.io.inputs;\\n if (this._inputs_evaluation_required) {\\n if (io_inputs.is_any_input_dirty()) {\\n input_containers = await io_inputs.eval_required_inputs();\\n } else {\\n input_containers = await io_inputs.containers_without_evaluation();\\n }\\n }\\n const inputs = io_inputs.inputs();\\n const input_contents = [];\\n let input_container;\\n for (let i = 0; i < inputs.length; i++) {\\n input_container = input_containers[i];\\n if (input_container) {\\n if (io_inputs.cloneRequired(i)) {\\n input_contents[i] = input_container.coreContentCloned();\\n } else {\\n input_contents[i] = input_container.coreContent();\\n }\\n }\\n }\\n this._performanceController.recordInputsEnd();\\n return input_contents;\\n }\\n async _evaluateParams() {\\n this._performanceController.recordParamsStart();\\n await this.node.params.evalAll();\\n this._performanceController.recordParamsEnd();\\n }\\n cooksCount() {\\n return this._performanceController.cooksCount();\\n }\\n cookTime() {\\n return this._performanceController.data2().cookTime;\\n }\\n _finalizeCookPerformance() {\\n if (!this._core_performance.started()) {\\n return;\\n }\\n this._performanceController.recordCookEnd();\\n this._core_performance.record_node_cook_data(this.node, this._performanceController.data2());\\n }\\n registerOnCookEnd(callbackName, callback) {\\n this._on_cook_complete_hook_names = this._on_cook_complete_hook_names || [];\\n this._on_cook_complete_hooks = this._on_cook_complete_hooks || [];\\n this._on_cook_complete_hook_names.push(callbackName);\\n this._on_cook_complete_hooks.push(callback);\\n }\\n deregisterOnCookEnd(callbackName) {\\n if (!this._on_cook_complete_hook_names || !this._on_cook_complete_hooks) {\\n return;\\n }\\n const index = this._on_cook_complete_hook_names?.indexOf(callbackName);\\n this._on_cook_complete_hook_names.splice(index, 1);\\n this._on_cook_complete_hooks.splice(index, 1);\\n }\\n _run_on_cook_complete_hooks() {\\n if (this._on_cook_complete_hooks) {\\n for (let hook of this._on_cook_complete_hooks) {\\n hook();\\n }\\n }\\n }\\n onCookEndCallbackNames() {\\n return this._on_cook_complete_hook_names;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/Serializer.ts\\nvar NodeSerializer = class {\\n constructor(node) {\\n this.node = node;\\n }\\n toJSON(include_param_components = false) {\\n const data = {\\n name: this.node.name(),\\n type: this.node.type(),\\n graph_node_id: this.node.graphNodeId(),\\n is_dirty: this.node.isDirty(),\\n ui_data_json: this.node.uiData.toJSON(),\\n error_message: this.node.states.error.message(),\\n children: this.childrenIds(),\\n maxInputsCount: this.maxInputsCount(),\\n inputs: this.inputIds(),\\n input_connection_output_indices: this.inputConnectionOutputIndices(),\\n named_input_connection_points: this.namedInputConnectionPoints(),\\n named_output_connection_points: this.namedOutputConnectionPoints(),\\n param_ids: this.to_json_params(include_param_components),\\n override_cloned_state_allowed: this.node.io.inputs.overrideClonedStateAllowed(),\\n inputs_clone_required_states: this.node.io.inputs.cloneRequiredStates(),\\n flags: {\\n display: this.node.flags?.display?.active(),\\n bypass: this.node.flags?.bypass?.active(),\\n optimize: this.node.flags?.optimize?.active()\\n },\\n selection: void 0\\n };\\n if (this.node.childrenAllowed() && this.node.childrenController) {\\n data[\\\\\\\"selection\\\\\\\"] = this.node.childrenController.selection.toJSON();\\n }\\n return data;\\n }\\n childrenIds() {\\n return this.node.children().map((node) => node.graphNodeId());\\n }\\n maxInputsCount() {\\n return this.node.io.inputs.maxInputsCount();\\n }\\n inputIds() {\\n return this.node.io.inputs.inputs().map((node) => node != null ? node.graphNodeId() : void 0);\\n }\\n inputConnectionOutputIndices() {\\n return this.node.io.connections.inputConnections()?.map((connection) => connection != null ? connection.output_index : void 0);\\n }\\n namedInputConnectionPoints() {\\n return this.node.io.inputs.namedInputConnectionPoints().map((i) => i.toJSON());\\n }\\n namedOutputConnectionPoints() {\\n return this.node.io.outputs.namedOutputConnectionPoints().map((o) => o.toJSON());\\n }\\n to_json_params_from_names(param_names, include_components = false) {\\n return param_names.map((param_name) => {\\n return this.node.params.get(param_name).graphNodeId();\\n });\\n }\\n to_json_params(include_components = false) {\\n return this.to_json_params_from_names(this.node.params.names, include_components);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/ParamType.ts\\nvar ParamType;\\n(function(ParamType2) {\\n ParamType2[\\\\\\\"BOOLEAN\\\\\\\"] = \\\\\\\"boolean\\\\\\\";\\n ParamType2[\\\\\\\"BUTTON\\\\\\\"] = \\\\\\\"button\\\\\\\";\\n ParamType2[\\\\\\\"COLOR\\\\\\\"] = \\\\\\\"color\\\\\\\";\\n ParamType2[\\\\\\\"FLOAT\\\\\\\"] = \\\\\\\"float\\\\\\\";\\n ParamType2[\\\\\\\"FOLDER\\\\\\\"] = \\\\\\\"folder\\\\\\\";\\n ParamType2[\\\\\\\"INTEGER\\\\\\\"] = \\\\\\\"integer\\\\\\\";\\n ParamType2[\\\\\\\"OPERATOR_PATH\\\\\\\"] = \\\\\\\"operator_path\\\\\\\";\\n ParamType2[\\\\\\\"PARAM_PATH\\\\\\\"] = \\\\\\\"param_path\\\\\\\";\\n ParamType2[\\\\\\\"NODE_PATH\\\\\\\"] = \\\\\\\"node_path\\\\\\\";\\n ParamType2[\\\\\\\"RAMP\\\\\\\"] = \\\\\\\"ramp\\\\\\\";\\n ParamType2[\\\\\\\"STRING\\\\\\\"] = \\\\\\\"string\\\\\\\";\\n ParamType2[\\\\\\\"VECTOR2\\\\\\\"] = \\\\\\\"vector2\\\\\\\";\\n ParamType2[\\\\\\\"VECTOR3\\\\\\\"] = \\\\\\\"vector3\\\\\\\";\\n ParamType2[\\\\\\\"VECTOR4\\\\\\\"] = \\\\\\\"vector4\\\\\\\";\\n})(ParamType || (ParamType = {}));\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/ParamEvent.ts\\nvar ParamEvent;\\n(function(ParamEvent2) {\\n ParamEvent2[\\\\\\\"VISIBLE_UPDATED\\\\\\\"] = \\\\\\\"param_visible_updated\\\\\\\";\\n ParamEvent2[\\\\\\\"RAW_INPUT_UPDATED\\\\\\\"] = \\\\\\\"raw_input_updated\\\\\\\";\\n ParamEvent2[\\\\\\\"VALUE_UPDATED\\\\\\\"] = \\\\\\\"param_value_updated\\\\\\\";\\n ParamEvent2[\\\\\\\"EXPRESSION_UPDATED\\\\\\\"] = \\\\\\\"param_expression_update\\\\\\\";\\n ParamEvent2[\\\\\\\"ERROR_UPDATED\\\\\\\"] = \\\\\\\"param_error_updated\\\\\\\";\\n ParamEvent2[\\\\\\\"DELETED\\\\\\\"] = \\\\\\\"param_deleted\\\\\\\";\\n})(ParamEvent || (ParamEvent = {}));\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/utils/OptionsController.ts\\nvar CALLBACK_OPTION = \\\\\\\"callback\\\\\\\";\\nvar CALLBACK_STRING_OPTION = \\\\\\\"callbackString\\\\\\\";\\nvar COMPUTE_ON_DIRTY = \\\\\\\"computeOnDirty\\\\\\\";\\nvar COOK_OPTION = \\\\\\\"cook\\\\\\\";\\nvar FILE_BROWSE_OPTION = \\\\\\\"fileBrowse\\\\\\\";\\nvar FILE_TYPE_OPTION = \\\\\\\"type\\\\\\\";\\nvar EXPRESSION = \\\\\\\"expression\\\\\\\";\\nvar FOR_ENTITIES = \\\\\\\"forEntities\\\\\\\";\\nvar LABEL = \\\\\\\"label\\\\\\\";\\nvar LEVEL = \\\\\\\"level\\\\\\\";\\nvar MENU = \\\\\\\"menu\\\\\\\";\\nvar MENU_STRING = \\\\\\\"menuString\\\\\\\";\\nvar ENTRIES = \\\\\\\"entries\\\\\\\";\\nvar MULTILINE_OPTION = \\\\\\\"multiline\\\\\\\";\\nvar LANGUAGE_OPTION = \\\\\\\"language\\\\\\\";\\nvar NODE_SELECTION = \\\\\\\"nodeSelection\\\\\\\";\\nvar NODE_SELECTION_CONTEXT = \\\\\\\"context\\\\\\\";\\nvar NODE_SELECTION_TYPES = \\\\\\\"types\\\\\\\";\\nvar PARAM_SELECTION = \\\\\\\"paramSelection\\\\\\\";\\nvar DEPENDENT_ON_FOUND_NODE = \\\\\\\"dependentOnFoundNode\\\\\\\";\\nvar RANGE_OPTION = \\\\\\\"range\\\\\\\";\\nvar RANGE_LOCKED_OPTION = \\\\\\\"rangeLocked\\\\\\\";\\nvar STEP_OPTION = \\\\\\\"step\\\\\\\";\\nvar SPARE_OPTION = \\\\\\\"spare\\\\\\\";\\nvar TEXTURE_OPTION = \\\\\\\"texture\\\\\\\";\\nvar ENV_OPTION = \\\\\\\"env\\\\\\\";\\nvar HIDDEN_OPTION = \\\\\\\"hidden\\\\\\\";\\nvar FIELD_OPTION = \\\\\\\"field\\\\\\\";\\nvar VISIBLE_IF_OPTION = \\\\\\\"visibleIf\\\\\\\";\\nvar COLOR_CONVERSION = \\\\\\\"conversion\\\\\\\";\\nvar SEPARATOR_BEFORE_OPTION = \\\\\\\"separatorBefore\\\\\\\";\\nvar SEPARATOR_AFTER_OPTION = \\\\\\\"separatorAfter\\\\\\\";\\nvar StringParamLanguage;\\n(function(StringParamLanguage2) {\\n StringParamLanguage2[\\\\\\\"TYPESCRIPT\\\\\\\"] = \\\\\\\"typescript\\\\\\\";\\n})(StringParamLanguage || (StringParamLanguage = {}));\\nvar FileType;\\n(function(FileType2) {\\n FileType2[\\\\\\\"AUDIO\\\\\\\"] = \\\\\\\"audio\\\\\\\";\\n FileType2[\\\\\\\"TEXTURE_IMAGE\\\\\\\"] = \\\\\\\"texture_image\\\\\\\";\\n FileType2[\\\\\\\"TEXTURE_VIDEO\\\\\\\"] = \\\\\\\"texture_video\\\\\\\";\\n FileType2[\\\\\\\"GEOMETRY\\\\\\\"] = \\\\\\\"geometry\\\\\\\";\\n FileType2[\\\\\\\"FONT\\\\\\\"] = \\\\\\\"font\\\\\\\";\\n FileType2[\\\\\\\"SVG\\\\\\\"] = \\\\\\\"svg\\\\\\\";\\n FileType2[\\\\\\\"JSON\\\\\\\"] = \\\\\\\"json\\\\\\\";\\n})(FileType || (FileType = {}));\\nvar OptionsController = class {\\n constructor(_param) {\\n this._param = _param;\\n this._programatic_visible_state = true;\\n this._callbackAllowed = false;\\n this._updateVisibilityAndRemoveDirtyBound = this.updateVisibilityAndRemoveDirty.bind(this);\\n this._ui_data_dependency_set = false;\\n }\\n dispose() {\\n try {\\n this._options[CALLBACK_OPTION] = void 0;\\n this._options[CALLBACK_STRING_OPTION] = void 0;\\n } catch (err) {\\n }\\n this._visibility_graph_node?.dispose();\\n }\\n set(options) {\\n this._default_options = options;\\n this._options = ObjectUtils.cloneDeep(this._default_options);\\n this.post_set_options();\\n }\\n copy(options_controller) {\\n this._default_options = ObjectUtils.cloneDeep(options_controller.default());\\n this._options = ObjectUtils.cloneDeep(options_controller.current());\\n this.post_set_options();\\n }\\n setOption(name, value) {\\n this._options[name] = value;\\n if (this._param.components) {\\n for (let component of this._param.components) {\\n component.options.setOption(name, value);\\n }\\n }\\n }\\n post_set_options() {\\n this._handleComputeOnDirty();\\n }\\n param() {\\n return this._param;\\n }\\n node() {\\n return this._param.node;\\n }\\n default() {\\n return this._default_options;\\n }\\n current() {\\n return this._options;\\n }\\n hasOptionsOverridden() {\\n return !ObjectUtils.isEqual(this._options, this._default_options);\\n }\\n overriddenOptions() {\\n const overriden = {};\\n const option_names = Object.keys(this._options);\\n for (let option_name of option_names) {\\n if (!ObjectUtils.isEqual(this._options[option_name], this._default_options[option_name])) {\\n const cloned_option = ObjectUtils.cloneDeep(this._options[option_name]);\\n Object.assign(overriden, {[option_name]: cloned_option});\\n }\\n }\\n return overriden;\\n }\\n overriddenOptionNames() {\\n return Object.keys(this.overriddenOptions());\\n }\\n computeOnDirty() {\\n return this._options[COMPUTE_ON_DIRTY] || false;\\n }\\n _handleComputeOnDirty() {\\n if (this.computeOnDirty()) {\\n if (!this._computeOnDirty_callback_added) {\\n this.param().addPostDirtyHook(\\\\\\\"computeOnDirty\\\\\\\", this._computeParam.bind(this));\\n this._computeOnDirty_callback_added = true;\\n }\\n }\\n }\\n async _computeParam() {\\n await this.param().compute();\\n }\\n hasCallback() {\\n return this._options[CALLBACK_OPTION] != null || this._options[CALLBACK_STRING_OPTION] != null;\\n }\\n allowCallback() {\\n this._callbackAllowed = true;\\n }\\n executeCallback() {\\n if (!this._callbackAllowed) {\\n return;\\n }\\n if (!this.node()) {\\n return;\\n }\\n const callback = this.getCallback();\\n if (!callback) {\\n return;\\n }\\n if (!this.node().scene().loadingController.loaded()) {\\n return;\\n }\\n const parent_param = this.param().parent_param;\\n if (parent_param) {\\n parent_param.options.executeCallback();\\n } else {\\n callback(this.node(), this.param());\\n }\\n }\\n getCallback() {\\n if (this.hasCallback()) {\\n return this._options[CALLBACK_OPTION] = this._options[CALLBACK_OPTION] || this.createCallbackFromString();\\n }\\n }\\n createCallbackFromString() {\\n const callbackString = this._options[CALLBACK_STRING_OPTION];\\n if (callbackString) {\\n const callback_function = new Function(\\\\\\\"node\\\\\\\", \\\\\\\"scene\\\\\\\", \\\\\\\"window\\\\\\\", \\\\\\\"location\\\\\\\", callbackString);\\n return () => {\\n callback_function(this.node(), this.node().scene(), null, null);\\n };\\n }\\n }\\n colorConversion() {\\n return this._options[COLOR_CONVERSION];\\n }\\n makesNodeDirtyWhenDirty() {\\n let cook_options;\\n if (this.param().parent_param != null) {\\n return false;\\n }\\n let value = true;\\n if ((cook_options = this._options[COOK_OPTION]) != null) {\\n value = cook_options;\\n }\\n return value;\\n }\\n fileBrowseOption() {\\n return this._options[FILE_BROWSE_OPTION];\\n }\\n fileBrowseAllowed() {\\n return this.fileBrowseOption() != null;\\n }\\n fileBrowseType() {\\n const option = this.fileBrowseOption();\\n if (option) {\\n return option[FILE_TYPE_OPTION];\\n } else {\\n return null;\\n }\\n }\\n separatorBefore() {\\n return this._options[SEPARATOR_BEFORE_OPTION];\\n }\\n separatorAfter() {\\n return this._options[SEPARATOR_AFTER_OPTION];\\n }\\n isExpressionForEntities() {\\n const expr_option = this._options[EXPRESSION];\\n if (expr_option) {\\n return expr_option[FOR_ENTITIES] || false;\\n }\\n return false;\\n }\\n level() {\\n return this._options[LEVEL] || 0;\\n }\\n hasMenu() {\\n return this.menuOptions() != null || this.menuStringOptions() != null;\\n }\\n menuOptions() {\\n return this._options[MENU];\\n }\\n menuStringOptions() {\\n return this._options[MENU_STRING];\\n }\\n menuEntries() {\\n const options = this.menuOptions() || this.menuStringOptions();\\n if (options) {\\n return options[ENTRIES];\\n } else {\\n return [];\\n }\\n }\\n isMultiline() {\\n return this._options[MULTILINE_OPTION] === true;\\n }\\n language() {\\n return this._options[LANGUAGE_OPTION];\\n }\\n isCode() {\\n return this.language() != null;\\n }\\n nodeSelectionOptions() {\\n return this._options[NODE_SELECTION];\\n }\\n nodeSelectionContext() {\\n const options = this.nodeSelectionOptions();\\n if (options) {\\n return options[NODE_SELECTION_CONTEXT];\\n }\\n }\\n nodeSelectionTypes() {\\n const options = this.nodeSelectionOptions();\\n if (options) {\\n return options[NODE_SELECTION_TYPES];\\n }\\n }\\n dependentOnFoundNode() {\\n if (DEPENDENT_ON_FOUND_NODE in this._options) {\\n return this._options[DEPENDENT_ON_FOUND_NODE];\\n } else {\\n return true;\\n }\\n }\\n isSelectingParam() {\\n return this.paramSelectionOptions() != null;\\n }\\n paramSelectionOptions() {\\n return this._options[PARAM_SELECTION];\\n }\\n paramSelectionType() {\\n const options = this.paramSelectionOptions();\\n if (options) {\\n const type_or_boolean = options;\\n if (!CoreType.isBoolean(type_or_boolean)) {\\n return type_or_boolean;\\n }\\n }\\n }\\n range() {\\n return this._options[RANGE_OPTION] || [0, 1];\\n }\\n step() {\\n return this._options[STEP_OPTION];\\n }\\n rangeLocked() {\\n return this._options[RANGE_LOCKED_OPTION] || [false, false];\\n }\\n ensureInRange(value) {\\n const range = this.range();\\n if (value >= range[0] && value <= range[1]) {\\n return value;\\n } else {\\n if (value < range[0]) {\\n return this.rangeLocked()[0] === true ? range[0] : value;\\n } else {\\n return this.rangeLocked()[1] === true ? range[1] : value;\\n }\\n }\\n }\\n isSpare() {\\n return this._options[SPARE_OPTION] || false;\\n }\\n textureOptions() {\\n return this._options[TEXTURE_OPTION];\\n }\\n textureAsEnv() {\\n const texture_options = this.textureOptions();\\n if (texture_options != null) {\\n return texture_options[ENV_OPTION] === true;\\n }\\n return false;\\n }\\n isHidden() {\\n return this._options[HIDDEN_OPTION] === true || this._programatic_visible_state === false;\\n }\\n isVisible() {\\n return !this.isHidden();\\n }\\n setVisibleState(state) {\\n this._options[HIDDEN_OPTION] = !state;\\n this.param().emit(ParamEvent.VISIBLE_UPDATED);\\n }\\n label() {\\n return this._options[LABEL];\\n }\\n isLabelHidden() {\\n const type = this.param().type();\\n return type === ParamType.BUTTON || type === ParamType.BOOLEAN && this.isFieldHidden();\\n }\\n isFieldHidden() {\\n return this._options[FIELD_OPTION] === false;\\n }\\n uiDataDependsOnOtherParams() {\\n return VISIBLE_IF_OPTION in this._options;\\n }\\n visibilityPredecessors() {\\n const visibility_options = this._options[VISIBLE_IF_OPTION];\\n if (!visibility_options) {\\n return [];\\n }\\n let predecessor_names = [];\\n if (CoreType.isArray(visibility_options)) {\\n predecessor_names = ArrayUtils.uniq(visibility_options.map((options) => Object.keys(options)).flat());\\n } else {\\n predecessor_names = Object.keys(visibility_options);\\n }\\n const node = this.param().node;\\n return ArrayUtils.compact(predecessor_names.map((name) => {\\n const param = node.params.get(name);\\n if (param) {\\n return param;\\n } else {\\n console.error(`param ${name} not found as visibility condition for ${this.param().name()} in node ${this.param().node.type()}`);\\n }\\n }));\\n }\\n setUiDataDependency() {\\n if (this._ui_data_dependency_set) {\\n return;\\n }\\n this._ui_data_dependency_set = true;\\n const predecessors = this.visibilityPredecessors();\\n if (predecessors.length > 0) {\\n this._visibility_graph_node = new CoreGraphNode(this.param().scene(), \\\\\\\"param_visibility\\\\\\\");\\n for (let predecessor of predecessors) {\\n this._visibility_graph_node.addGraphInput(predecessor);\\n }\\n this._visibility_graph_node.addPostDirtyHook(\\\\\\\"_update_visibility_and_remove_dirty\\\\\\\", this._updateVisibilityAndRemoveDirtyBound);\\n }\\n }\\n updateVisibilityAndRemoveDirty() {\\n this.updateVisibility();\\n this.param().removeDirtyState();\\n }\\n async updateVisibility() {\\n const options = this._options[VISIBLE_IF_OPTION];\\n if (options) {\\n const params = this.visibilityPredecessors();\\n const promises = params.map((p) => {\\n if (p.isDirty()) {\\n return p.compute();\\n }\\n });\\n this._programatic_visible_state = false;\\n await Promise.all(promises);\\n if (CoreType.isArray(options)) {\\n for (let options_set of options) {\\n const satisfied_values = params.filter((param) => param.value == options_set[param.name()]);\\n if (satisfied_values.length == params.length) {\\n this._programatic_visible_state = true;\\n }\\n }\\n } else {\\n const satisfied_values = params.filter((param) => param.value == options[param.name()]);\\n this._programatic_visible_state = satisfied_values.length == params.length;\\n }\\n this.param().emit(ParamEvent.VISIBLE_UPDATED);\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/utils/EmitController.ts\\nvar EmitController = class {\\n constructor(param) {\\n this.param = param;\\n this._blocked_emit = false;\\n this._blocked_parent_emit = false;\\n this._count_by_event_name = {};\\n }\\n emitAllowed() {\\n if (this._blocked_emit === true) {\\n return false;\\n }\\n if (this.param.scene().loadingController.isLoading()) {\\n return false;\\n }\\n return this.param.scene().dispatchController.emitAllowed();\\n }\\n blockEmit() {\\n this._blocked_emit = true;\\n if (this.param.isMultiple() && this.param.components) {\\n for (let component of this.param.components) {\\n component.emitController.blockEmit();\\n }\\n }\\n return true;\\n }\\n unblockEmit() {\\n this._blocked_emit = false;\\n if (this.param.isMultiple() && this.param.components) {\\n for (let component of this.param.components) {\\n component.emitController.unblockEmit();\\n }\\n }\\n return true;\\n }\\n blockParentEmit() {\\n this._blocked_parent_emit = true;\\n return true;\\n }\\n unblockParentEmit() {\\n this._blocked_parent_emit = false;\\n return true;\\n }\\n incrementCount(event_name) {\\n this._count_by_event_name[event_name] = this._count_by_event_name[event_name] || 0;\\n this._count_by_event_name[event_name] += 1;\\n }\\n eventsCount(event_name) {\\n return this._count_by_event_name[event_name] || 0;\\n }\\n emit(event) {\\n if (this.emitAllowed()) {\\n this.param.emit(event);\\n if (this.param.parent_param != null && this._blocked_parent_emit !== true) {\\n this.param.parent_param.emit(event);\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/utils/Serializer.ts\\nvar ParamSerializer = class {\\n constructor(param) {\\n this.param = param;\\n }\\n toJSON() {\\n const data = {\\n name: this.param.name(),\\n type: this.param.type(),\\n raw_input: this.rawInput(),\\n value: this.value(),\\n value_pre_conversion: this.value_pre_conversion(),\\n expression: this.expression(),\\n graph_node_id: this.param.graphNodeId(),\\n error_message: this.error_message(),\\n is_visible: this.is_visible(),\\n components: void 0\\n };\\n if (this.param.isMultiple() && this.param.components) {\\n data[\\\\\\\"components\\\\\\\"] = this.param.components.map((component) => component.graphNodeId());\\n }\\n return data;\\n }\\n rawInput() {\\n return this.param.rawInputSerialized();\\n }\\n value() {\\n return this.param.valueSerialized();\\n }\\n value_pre_conversion() {\\n return this.param.valuePreConversionSerialized();\\n }\\n expression() {\\n return this.param.hasExpression() ? this.param.expressionController?.expression() : void 0;\\n }\\n error_message() {\\n return this.param.states.error.message();\\n }\\n is_visible() {\\n return this.param.options.isVisible();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/utils/states/TimeDependent.ts\\nvar TimeDependentState2 = class {\\n constructor(param) {\\n this.param = param;\\n }\\n active() {\\n const frame_graph_node_id = this.param.scene().timeController.graphNode.graphNodeId();\\n return this.param.graphPredecessorIds().includes(frame_graph_node_id);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/utils/states/Error.ts\\nvar ParamErrorState = class {\\n constructor(param) {\\n this.param = param;\\n }\\n set(message) {\\n if (this._message != message) {\\n this._message = message;\\n if (this._message) {\\n Poly.warn(this.param.path(), this._message);\\n }\\n this.param.emitController.emit(ParamEvent.ERROR_UPDATED);\\n }\\n }\\n message() {\\n return this._message;\\n }\\n clear() {\\n this.set(void 0);\\n }\\n active() {\\n return this._message != null;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/utils/StatesController.ts\\nvar StatesController2 = class {\\n constructor(param) {\\n this.param = param;\\n this.timeDependent = new TimeDependentState2(this.param);\\n this.error = new ParamErrorState(this.param);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/MethodDependency.ts\\nvar MethodDependency = class extends CoreGraphNode {\\n constructor(param, path_argument, decomposed_path) {\\n super(param.scene(), \\\\\\\"MethodDependency\\\\\\\");\\n this.param = param;\\n this.path_argument = path_argument;\\n this.decomposed_path = decomposed_path;\\n this._update_from_name_change_bound = this._update_from_name_change.bind(this);\\n param.expressionController?.registerMethodDependency(this);\\n this.addPostDirtyHook(\\\\\\\"_update_from_name_change\\\\\\\", this._update_from_name_change_bound);\\n }\\n _update_from_name_change(trigger) {\\n if (trigger && this.decomposed_path) {\\n const node = trigger;\\n this.decomposed_path.update_from_name_change(node);\\n const new_path = this.decomposed_path.to_path();\\n const literal = this.jsep_node;\\n if (literal) {\\n literal.value = `${literal.value}`.replace(`${this.path_argument}`, new_path);\\n literal.raw = literal.raw.replace(`${this.path_argument}`, new_path);\\n }\\n if (this.param.expressionController) {\\n this.param.expressionController.updateFromMethodDependencyNameChange();\\n }\\n }\\n }\\n reset() {\\n this.graphDisconnectPredecessors();\\n }\\n listen_for_name_changes() {\\n if (this.jsep_node && this.decomposed_path) {\\n for (let node_in_path of this.decomposed_path.named_nodes()) {\\n if (node_in_path) {\\n const node = node_in_path;\\n if (node.nameController) {\\n this.addGraphInput(node.nameController.graph_node);\\n }\\n }\\n }\\n }\\n }\\n set_jsep_node(jsep_node) {\\n this.jsep_node = jsep_node;\\n }\\n set_resolved_graph_node(node) {\\n this.resolved_graph_node = node;\\n }\\n set_unresolved_path(path) {\\n this.unresolved_path = path;\\n }\\n static create(param, index_or_path, node, decomposed_path) {\\n const is_index = CoreType.isNumber(index_or_path);\\n const instance = new MethodDependency(param, index_or_path, decomposed_path);\\n if (node) {\\n instance.set_resolved_graph_node(node);\\n } else {\\n if (!is_index) {\\n const path = index_or_path;\\n instance.set_unresolved_path(path);\\n }\\n }\\n return instance;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/_Base.ts\\nvar TYPED_PARAM_DEFAULT_COMPONENT_NAMES = [];\\nvar TypedParam = class extends CoreGraphNode {\\n constructor(scene, node) {\\n super(scene, \\\\\\\"BaseParam\\\\\\\");\\n this._options = new OptionsController(this);\\n this._emit_controller = new EmitController(this);\\n this._is_computing = false;\\n this._node = node;\\n this.initialize_param();\\n }\\n get options() {\\n return this._options = this._options || new OptionsController(this);\\n }\\n get emitController() {\\n return this._emit_controller = this._emit_controller || new EmitController(this);\\n }\\n get expressionController() {\\n return this._expression_controller;\\n }\\n get serializer() {\\n return this._serializer = this._serializer || new ParamSerializer(this);\\n }\\n get states() {\\n return this._states = this._states || new StatesController2(this);\\n }\\n dispose() {\\n const predecessors = this.graphPredecessors();\\n for (let predecessor of predecessors) {\\n if (predecessor instanceof MethodDependency) {\\n predecessor.dispose();\\n }\\n }\\n this.scene().missingExpressionReferencesController.deregisterParam(this);\\n this._expression_controller?.dispose();\\n super.dispose();\\n this._options?.dispose();\\n }\\n initialize_param() {\\n }\\n static type() {\\n return ParamType.FLOAT;\\n }\\n type() {\\n return this.constructor.type();\\n }\\n isNumeric() {\\n return false;\\n }\\n setName(name) {\\n super.setName(name);\\n }\\n get value() {\\n return this._value;\\n }\\n copy_value(param) {\\n if (param.type() == this.type()) {\\n this._copy_value(param);\\n } else {\\n console.warn(`cannot copy value from ${param.type()} to ${this.type()}`);\\n }\\n }\\n _copy_value(param) {\\n throw \\\\\\\"abstract method param._copy_value\\\\\\\";\\n }\\n valuePreConversionSerialized() {\\n return void 0;\\n }\\n convert(raw_val) {\\n return null;\\n }\\n static are_raw_input_equal(val1, val2) {\\n return false;\\n }\\n is_raw_input_equal(other_raw_input) {\\n return this.constructor.are_raw_input_equal(this._raw_input, other_raw_input);\\n }\\n static are_values_equal(val1, val2) {\\n return false;\\n }\\n is_value_equal(other_val) {\\n return this.constructor.are_values_equal(this.value, other_val);\\n }\\n _clone_raw_input(raw_input) {\\n return raw_input;\\n }\\n set(raw_input) {\\n this._raw_input = this._clone_raw_input(this._prefilter_invalid_raw_input(raw_input));\\n this.emitController.emit(ParamEvent.RAW_INPUT_UPDATED);\\n this.processRawInput();\\n }\\n _prefilter_invalid_raw_input(raw_input) {\\n return raw_input;\\n }\\n defaultValue() {\\n return this._default_value;\\n }\\n isDefault() {\\n return this._raw_input == this._default_value;\\n }\\n rawInput() {\\n return this._raw_input;\\n }\\n processRawInput() {\\n }\\n async compute() {\\n if (this.scene().loadingController.isLoading()) {\\n console.warn(`param attempt to compute ${this.path()}`);\\n }\\n if (this.isDirty()) {\\n if (!this._is_computing) {\\n this._is_computing = true;\\n await this.processComputation();\\n this._is_computing = false;\\n if (this._compute_resolves) {\\n let callback;\\n while (callback = this._compute_resolves.pop()) {\\n callback();\\n }\\n }\\n } else {\\n return new Promise((resolve, reject) => {\\n this._compute_resolves = this._compute_resolves || [];\\n this._compute_resolves.push(resolve);\\n });\\n }\\n }\\n }\\n async processComputation() {\\n }\\n setInitValue(init_value) {\\n this._default_value = this._clone_raw_input(this._prefilter_invalid_raw_input(init_value));\\n }\\n _setupNodeDependencies(node) {\\n if (!node) {\\n if (this._node) {\\n this._node.params.params_node?.removeGraphInput(this);\\n }\\n } else {\\n this.options.allowCallback();\\n if (!this.parent_param) {\\n if (this.options.makesNodeDirtyWhenDirty()) {\\n node.params.params_node?.addGraphInput(this, false);\\n } else {\\n this.dirtyController.addPostDirtyHook(\\\\\\\"run callback\\\\\\\", async () => {\\n await this.compute();\\n this.options.executeCallback();\\n });\\n }\\n }\\n }\\n if (this.components) {\\n for (let c of this.components) {\\n c._setupNodeDependencies(node);\\n }\\n }\\n }\\n get node() {\\n return this._node;\\n }\\n parent() {\\n return this.node;\\n }\\n set_parent_param(param) {\\n param.addGraphInput(this, false);\\n this._parent_param = param;\\n }\\n get parent_param() {\\n return this._parent_param;\\n }\\n has_parent_param() {\\n return this._parent_param != null;\\n }\\n path() {\\n return this.node?.path() + \\\\\\\"/\\\\\\\" + this.name();\\n }\\n pathRelativeTo(node) {\\n const nodeRelativePath = CoreWalker.relativePath(node, this.node);\\n if (nodeRelativePath.length > 0) {\\n return `${nodeRelativePath}${CoreWalker.SEPARATOR}${this.name()}`;\\n } else {\\n return this.name();\\n }\\n }\\n emit(event_name) {\\n if (this.emitController.emitAllowed()) {\\n this.emitController.incrementCount(event_name);\\n this.scene().dispatchController.dispatch(this, event_name);\\n }\\n }\\n get components() {\\n return this._components;\\n }\\n componentNames() {\\n return TYPED_PARAM_DEFAULT_COMPONENT_NAMES;\\n }\\n isMultiple() {\\n return this.componentNames().length > 0;\\n }\\n initComponents() {\\n }\\n hasExpression() {\\n return this.expressionController != null && this.expressionController.active();\\n }\\n toJSON() {\\n return this.serializer.toJSON();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/traversers/ParsedTree.ts\\nvar import_jsep = __toModule(require_jsep());\\nimport_jsep.default.addUnaryOp(\\\\\\\"@\\\\\\\");\\nvar precedence = 10;\\nimport_jsep.default.addBinaryOp(\\\\\\\"**\\\\\\\", precedence);\\nvar JSEP_IDENTIFIER = \\\\\\\"Identifier\\\\\\\";\\nvar JSEP_LITERAL = \\\\\\\"Literal\\\\\\\";\\nvar JSEP_CALL_EXPRESSION = \\\\\\\"CallExpression\\\\\\\";\\nvar STRING_EXPRESSION_SEPARATOR = \\\\\\\"`\\\\\\\";\\nvar ParsedTree = class {\\n constructor() {\\n }\\n parse_expression(string) {\\n try {\\n this.reset();\\n this.node = import_jsep.default(string);\\n } catch (e) {\\n const message = `could not parse the expression '${string}' (error: ${e})`;\\n this.error_message = message;\\n }\\n }\\n parse_expression_for_string_param(string) {\\n try {\\n this.reset();\\n const elements = ParsedTree.string_value_elements(string);\\n const nodes = [];\\n for (let i = 0; i < elements.length; i++) {\\n const element = elements[i];\\n let node;\\n if (i % 2 == 1) {\\n node = import_jsep.default(element);\\n } else {\\n const sanitizedElement = element.replace(/\\\\'/g, \\\\\\\"\\\\\\\\'\\\\\\\");\\n node = {\\n type: JSEP_LITERAL,\\n value: `'${sanitizedElement}'`,\\n raw: `'${sanitizedElement}'`\\n };\\n }\\n nodes.push(node);\\n }\\n this.node = {\\n type: JSEP_CALL_EXPRESSION,\\n arguments: nodes,\\n callee: {\\n type: JSEP_IDENTIFIER,\\n name: \\\\\\\"strConcat\\\\\\\"\\n }\\n };\\n } catch (e) {\\n const message = `could not parse the expression '${string}' (error: ${e})`;\\n this.error_message = message;\\n }\\n }\\n static string_value_elements(v) {\\n if (v != null) {\\n if (CoreType.isString(v)) {\\n return v.split(STRING_EXPRESSION_SEPARATOR);\\n } else {\\n return [];\\n }\\n } else {\\n return [];\\n }\\n }\\n reset() {\\n this.node = void 0;\\n this.error_message = void 0;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/LiteralConstructsController.ts\\nvar LiteralConstructsController = class {\\n static if(args) {\\n const condition = args[0];\\n const val_true = args[1];\\n const val_false = args[2];\\n return `(${condition}) ? (${val_true}) : (${val_false})`;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/traversers/_Base.ts\\nvar VARIABLE_PREFIX = \\\\\\\"$\\\\\\\";\\nvar BaseTraverser = class {\\n constructor(param) {\\n this.param = param;\\n this._set_error_from_error_bound = this._set_error_from_error.bind(this);\\n }\\n clear_error() {\\n this._error_message = void 0;\\n }\\n set_error(message) {\\n this._error_message = this._error_message || message;\\n }\\n _set_error_from_error(error) {\\n if (CoreType.isString(error)) {\\n this._error_message = error;\\n } else {\\n this._error_message = error.message;\\n }\\n }\\n is_errored() {\\n return this._error_message != null;\\n }\\n error_message() {\\n return this._error_message;\\n }\\n reset() {\\n this._error_message = void 0;\\n }\\n traverse_node(node) {\\n const method_name = `traverse_${node.type}`;\\n const method = this[method_name];\\n if (method) {\\n return this[method_name](node);\\n } else {\\n this.set_error(`expression unknown node type: ${node.type}`);\\n }\\n }\\n traverse_BinaryExpression(node) {\\n return `${this.traverse_node(node.left)} ${node.operator} ${this.traverse_node(node.right)}`;\\n }\\n traverse_LogicalExpression(node) {\\n return `${this.traverse_node(node.left)} ${node.operator} ${this.traverse_node(node.right)}`;\\n }\\n traverse_MemberExpression(node) {\\n return `${this.traverse_node(node.object)}.${this.traverse_node(node.property)}`;\\n }\\n traverse_ConditionalExpression(node) {\\n return `(${this.traverse_node(node.test)}) ? (${this.traverse_node(node.consequent)}) : (${this.traverse_node(node.alternate)})`;\\n }\\n traverse_Compound(node) {\\n const args = node.body;\\n let traversed_args = [];\\n for (let i = 0; i < args.length; i++) {\\n const arg_node = args[i];\\n if (arg_node.type == \\\\\\\"Identifier\\\\\\\") {\\n if (arg_node.name[0] == VARIABLE_PREFIX) {\\n traversed_args.push(\\\\\\\"`${\\\\\\\" + this.traverse_node(arg_node) + \\\\\\\"}`\\\\\\\");\\n } else {\\n traversed_args.push(`'${arg_node.name}'`);\\n }\\n } else {\\n traversed_args.push(\\\\\\\"`${\\\\\\\" + this.traverse_node(arg_node) + \\\\\\\"}`\\\\\\\");\\n }\\n }\\n return traversed_args.join(\\\\\\\" + \\\\\\\");\\n }\\n traverse_Literal(node) {\\n return `${node.raw}`;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/AttributeRequirementsController.ts\\nvar VAR_CORE_GEOMETRY = `coreGeometry`;\\nvar AttributeRequirementsController = class {\\n constructor() {\\n }\\n reset() {\\n if (this._attributeNames) {\\n this._attributeNames.clear();\\n }\\n }\\n assignAttributesLines() {\\n if (this._attributeNames) {\\n const lines = [];\\n for (let attribName of this._attributeNames) {\\n lines.push(AttributeRequirementsController.assignAttributeLine(attribName));\\n }\\n return lines.join(\\\\\\\";\\\\n\\\\\\\");\\n } else {\\n return \\\\\\\"\\\\\\\";\\n }\\n }\\n assignArraysLines() {\\n if (this._attributeNames) {\\n const lines = [];\\n if (this._attributeNames.size > 0) {\\n const coreGeoLine = `const ${VAR_CORE_GEOMETRY} = entities[0].coreGeometry();`;\\n lines.push(coreGeoLine);\\n }\\n for (let attribName of this._attributeNames) {\\n lines.push(AttributeRequirementsController.assignItemSizeLine(attribName));\\n lines.push(AttributeRequirementsController.assignArrayLine(attribName));\\n }\\n return lines.join(\\\\\\\";\\\\n\\\\\\\");\\n } else {\\n return \\\\\\\"\\\\\\\";\\n }\\n }\\n attributePresenceCheckLine() {\\n if (this._attributeNames) {\\n const varNames = [];\\n for (let attribName of this._attributeNames) {\\n const varName = AttributeRequirementsController._varAttribute(attribName);\\n varNames.push(varName);\\n }\\n if (varNames.length > 0) {\\n return varNames.join(\\\\\\\" && \\\\\\\");\\n }\\n }\\n return \\\\\\\"true\\\\\\\";\\n }\\n add(attribName) {\\n this._attributeNames = this._attributeNames || new Set();\\n this._attributeNames.add(attribName);\\n }\\n static assignAttributeLine(attribName) {\\n const varAttribute = this._varAttribute(attribName);\\n return `const ${varAttribute} = entities[0].geometry().attributes['${attribName}']`;\\n }\\n static assignItemSizeLine(attribName) {\\n const varAttribute = this._varAttribute(attribName);\\n const varAttributeSize = this._varAttribSize(attribName);\\n return `const ${varAttributeSize} = ${varAttribute}.itemSize`;\\n }\\n static assignArrayLine(attribName) {\\n const varAttribute = this._varAttribute(attribName);\\n const varArray = this._varArray(attribName);\\n const isIndexedCondition = `${VAR_CORE_GEOMETRY}.isAttribIndexed('${attribName}')`;\\n const indexedArray = `entities.map(e=>e.indexedAttribValue('${attribName}'))`;\\n const nonIndexedArray = `${varAttribute}.array`;\\n return `const ${varArray} = ${isIndexedCondition} ? ${indexedArray} : ${nonIndexedArray}`;\\n }\\n static _varAttribute(attribName) {\\n return `attrib_${attribName}`;\\n }\\n static _varAttribSize(attribName) {\\n return `attrib_size_${attribName}`;\\n }\\n static _varArray(attribName) {\\n return `array_${attribName}`;\\n }\\n varAttributeSize(attribName) {\\n return AttributeRequirementsController._varAttribSize(attribName);\\n }\\n varArray(attribName) {\\n return AttributeRequirementsController._varArray(attribName);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/traversers/FunctionGenerator.ts\\nvar NATIVE_MATH_METHODS = [\\n \\\\\\\"abs\\\\\\\",\\n \\\\\\\"acos\\\\\\\",\\n \\\\\\\"acosh\\\\\\\",\\n \\\\\\\"asin\\\\\\\",\\n \\\\\\\"asinh\\\\\\\",\\n \\\\\\\"atan\\\\\\\",\\n \\\\\\\"atan2\\\\\\\",\\n \\\\\\\"atanh\\\\\\\",\\n \\\\\\\"ceil\\\\\\\",\\n \\\\\\\"cos\\\\\\\",\\n \\\\\\\"cosh\\\\\\\",\\n \\\\\\\"exp\\\\\\\",\\n \\\\\\\"expm1\\\\\\\",\\n \\\\\\\"floor\\\\\\\",\\n \\\\\\\"log\\\\\\\",\\n \\\\\\\"log1p\\\\\\\",\\n \\\\\\\"log2\\\\\\\",\\n \\\\\\\"log10\\\\\\\",\\n \\\\\\\"max\\\\\\\",\\n \\\\\\\"min\\\\\\\",\\n \\\\\\\"pow\\\\\\\",\\n \\\\\\\"round\\\\\\\",\\n \\\\\\\"sign\\\\\\\",\\n \\\\\\\"sin\\\\\\\",\\n \\\\\\\"sinh\\\\\\\",\\n \\\\\\\"sqrt\\\\\\\",\\n \\\\\\\"tan\\\\\\\",\\n \\\\\\\"tanh\\\\\\\"\\n];\\nvar NATIVE_ES6_MATH_METHODS = [\\\\\\\"cbrt\\\\\\\", \\\\\\\"hypot\\\\\\\", \\\\\\\"log10\\\\\\\", \\\\\\\"trunc\\\\\\\"];\\nvar NATIVE_MATH_METHODS_RENAMED = {\\n math_random: \\\\\\\"random\\\\\\\"\\n};\\nvar CORE_MATH_METHODS = [\\\\\\\"fit\\\\\\\", \\\\\\\"fit01\\\\\\\", \\\\\\\"fract\\\\\\\", \\\\\\\"deg2rad\\\\\\\", \\\\\\\"rad2deg\\\\\\\", \\\\\\\"rand\\\\\\\", \\\\\\\"clamp\\\\\\\"];\\nvar EASING_METHODS = Object.keys(Easing);\\nvar CORE_STRING_METHODS = [\\\\\\\"precision\\\\\\\"];\\nvar NATIVE_MATH_CONSTANTS = [\\\\\\\"E\\\\\\\", \\\\\\\"LN2\\\\\\\", \\\\\\\"LN10\\\\\\\", \\\\\\\"LOG10E\\\\\\\", \\\\\\\"LOG2E\\\\\\\", \\\\\\\"PI\\\\\\\", \\\\\\\"SQRT1_2\\\\\\\", \\\\\\\"SQRT2\\\\\\\"];\\nvar DIRECT_EXPRESSION_FUNCTIONS = {};\\nNATIVE_MATH_METHODS.forEach((name) => {\\n DIRECT_EXPRESSION_FUNCTIONS[name] = `Math.${name}`;\\n});\\nNATIVE_ES6_MATH_METHODS.forEach((name) => {\\n DIRECT_EXPRESSION_FUNCTIONS[name] = `Math.${name}`;\\n});\\nObject.keys(NATIVE_MATH_METHODS_RENAMED).forEach((name) => {\\n const remaped = NATIVE_MATH_METHODS_RENAMED[name];\\n DIRECT_EXPRESSION_FUNCTIONS[name] = `Math.${remaped}`;\\n});\\nCORE_MATH_METHODS.forEach((name) => {\\n DIRECT_EXPRESSION_FUNCTIONS[name] = `Core.Math.${name}`;\\n});\\nEASING_METHODS.forEach((name) => {\\n DIRECT_EXPRESSION_FUNCTIONS[name] = `Core.Math.Easing.${name}`;\\n});\\nCORE_STRING_METHODS.forEach((name) => {\\n DIRECT_EXPRESSION_FUNCTIONS[name] = `Core.String.${name}`;\\n});\\nvar LITERAL_CONSTRUCT = {\\n if: LiteralConstructsController.if\\n};\\nvar GLOBAL_CONSTANTS = {};\\nNATIVE_MATH_CONSTANTS.forEach((name) => {\\n GLOBAL_CONSTANTS[name] = `Math.${name}`;\\n});\\nvar QUOTE = \\\\\\\"'\\\\\\\";\\nvar ARGUMENTS_SEPARATOR = \\\\\\\", \\\\\\\";\\nvar ATTRIBUTE_PREFIX = \\\\\\\"@\\\\\\\";\\nvar PROPERTY_OFFSETS = {\\n x: 0,\\n y: 1,\\n z: 2,\\n w: 3,\\n r: 0,\\n g: 1,\\n b: 2\\n};\\nvar FunctionGenerator = class extends BaseTraverser {\\n constructor(param) {\\n super(param);\\n this.param = param;\\n this._attribute_requirements_controller = new AttributeRequirementsController();\\n this.methods = [];\\n this.method_index = -1;\\n this.method_dependencies = [];\\n this.immutable_dependencies = [];\\n }\\n parse_tree(parsed_tree) {\\n this.reset();\\n if (parsed_tree.error_message == null) {\\n try {\\n this._attribute_requirements_controller = new AttributeRequirementsController();\\n if (parsed_tree.node) {\\n const function_main_string = this.traverse_node(parsed_tree.node);\\n if (function_main_string && !this.is_errored()) {\\n this.function_main_string = function_main_string;\\n }\\n } else {\\n console.warn(\\\\\\\"no parsed_tree.node\\\\\\\");\\n }\\n } catch (e) {\\n console.warn(`error in expression for param ${this.param.path()}`);\\n console.warn(e);\\n }\\n if (this.function_main_string) {\\n try {\\n const body = this._functionBody();\\n this.function = new Function(\\\\\\\"Core\\\\\\\", \\\\\\\"param\\\\\\\", \\\\\\\"methods\\\\\\\", \\\\\\\"_set_error_from_error\\\\\\\", `\\n\\t\\t\\t\\t\\ttry {\\n\\t\\t\\t\\t\\t\\t${body}\\n\\t\\t\\t\\t\\t} catch(e) {\\n\\t\\t\\t\\t\\t\\t_set_error_from_error(e)\\n\\t\\t\\t\\t\\t\\treturn null;\\n\\t\\t\\t\\t\\t}`);\\n } catch (e) {\\n console.warn(e);\\n this.set_error(\\\\\\\"cannot generate function\\\\\\\");\\n }\\n } else {\\n this.set_error(\\\\\\\"cannot generate function body\\\\\\\");\\n }\\n } else {\\n this.set_error(\\\\\\\"cannot parse expression\\\\\\\");\\n }\\n }\\n reset() {\\n super.reset();\\n this.function_main_string = void 0;\\n this.methods = [];\\n this.method_index = -1;\\n this.function = void 0;\\n this.method_dependencies = [];\\n this.immutable_dependencies = [];\\n }\\n _functionBody() {\\n if (this.param.options.isExpressionForEntities()) {\\n return `\\n\\t\\t\\tconst entities = param.expressionController.entities();\\n\\t\\t\\tif(entities){\\n\\t\\t\\t\\treturn new Promise( async (resolve, reject)=>{\\n\\t\\t\\t\\t\\tlet entity;\\n\\t\\t\\t\\t\\tconst entity_callback = param.expressionController.entity_callback();\\n\\t\\t\\t\\t\\t// assign_attributes_lines\\n\\t\\t\\t\\t\\t${this._attribute_requirements_controller.assignAttributesLines()}\\n\\t\\t\\t\\t\\t// check if attributes are present\\n\\t\\t\\t\\t\\tif( ${this._attribute_requirements_controller.attributePresenceCheckLine()} ){\\n\\t\\t\\t\\t\\t\\t// assign_arrays_lines\\n\\t\\t\\t\\t\\t\\t${this._attribute_requirements_controller.assignArraysLines()}\\n\\t\\t\\t\\t\\t\\tfor(let index=0; index < entities.length; index++){\\n\\t\\t\\t\\t\\t\\t\\tentity = entities[index];\\n\\t\\t\\t\\t\\t\\t\\tresult = ${this.function_main_string};\\n\\t\\t\\t\\t\\t\\t\\tentity_callback(entity, result);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\tresolve()\\n\\t\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\t\\tconst error = new Error('attribute not found')\\n\\t\\t\\t\\t\\t\\t_set_error_from_error(error)\\n\\t\\t\\t\\t\\t\\treject(error)\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t})\\n\\t\\t\\t}\\n\\t\\t\\treturn []`;\\n } else {\\n return `\\n\\t\\t\\treturn new Promise( async (resolve, reject)=>{\\n\\t\\t\\t\\ttry {\\n\\t\\t\\t\\t\\tconst value = ${this.function_main_string}\\n\\t\\t\\t\\t\\tresolve(value)\\n\\t\\t\\t\\t} catch(e) {\\n\\t\\t\\t\\t\\t_set_error_from_error(e)\\n\\t\\t\\t\\t\\treject()\\n\\t\\t\\t\\t}\\n\\t\\t\\t})\\n\\t\\t\\t`;\\n }\\n }\\n evalAllowed() {\\n return this.function != null;\\n }\\n evalFunction() {\\n if (this.function) {\\n this.clear_error();\\n const Core = {\\n Math: CoreMath,\\n String: CoreString\\n };\\n const result = this.function(Core, this.param, this.methods, this._set_error_from_error_bound);\\n return result;\\n }\\n }\\n traverse_CallExpression(node) {\\n const method_arguments = node.arguments.map((arg) => {\\n return this.traverse_node(arg);\\n });\\n const callee = node.callee;\\n const method_name = callee.name;\\n if (method_name) {\\n const literal_contruct = LITERAL_CONSTRUCT[method_name];\\n if (literal_contruct) {\\n return literal_contruct(method_arguments);\\n }\\n const arguments_joined = `${method_arguments.join(ARGUMENTS_SEPARATOR)}`;\\n const direct_function_name = DIRECT_EXPRESSION_FUNCTIONS[method_name];\\n if (direct_function_name) {\\n return `${direct_function_name}(${arguments_joined})`;\\n }\\n const expressionRegister = Poly.expressionsRegister;\\n const indirect_method = expressionRegister.getMethod(method_name);\\n if (indirect_method) {\\n const path_node = node.arguments[0];\\n const function_string = `return ${method_arguments[0]}`;\\n let path_argument_function;\\n let path_argument = [];\\n try {\\n path_argument_function = new Function(function_string);\\n path_argument = path_argument_function();\\n } catch {\\n }\\n this._create_method_and_dependencies(method_name, path_argument, path_node);\\n return `(await methods[${this.method_index}].processArguments([${arguments_joined}]))`;\\n } else {\\n const available_methods = expressionRegister.availableMethods().join(\\\\\\\", \\\\\\\");\\n const message = `method not found (${method_name}), available methods are: ${available_methods}`;\\n Poly.warn(message);\\n }\\n }\\n this.set_error(`unknown method: ${method_name}`);\\n }\\n traverse_BinaryExpression(node) {\\n return `(${this.traverse_node(node.left)} ${node.operator} ${this.traverse_node(node.right)})`;\\n }\\n traverse_LogicalExpression(node) {\\n return `(${this.traverse_node(node.left)} ${node.operator} ${this.traverse_node(node.right)})`;\\n }\\n traverse_MemberExpression(node) {\\n return `${this.traverse_node(node.object)}.${this.traverse_node(node.property)}`;\\n }\\n traverse_UnaryExpression(node) {\\n if (node.operator === ATTRIBUTE_PREFIX) {\\n let argument = node.argument;\\n let attribute_name;\\n let property;\\n switch (argument.type) {\\n case \\\\\\\"Identifier\\\\\\\": {\\n const argument_identifier = argument;\\n attribute_name = argument_identifier.name;\\n break;\\n }\\n case \\\\\\\"MemberExpression\\\\\\\": {\\n const argument_member_expression = argument;\\n const attrib_node = argument_member_expression.object;\\n const property_node = argument_member_expression.property;\\n attribute_name = attrib_node.name;\\n property = property_node.name;\\n break;\\n }\\n }\\n if (attribute_name) {\\n attribute_name = CoreAttribute.remapName(attribute_name);\\n if (attribute_name == \\\\\\\"ptnum\\\\\\\") {\\n return \\\\\\\"((entity != null) ? entity.index() : 0)\\\\\\\";\\n } else {\\n const var_attribute_size = this._attribute_requirements_controller.varAttributeSize(attribute_name);\\n const var_array = this._attribute_requirements_controller.varArray(attribute_name);\\n this._attribute_requirements_controller.add(attribute_name);\\n if (property) {\\n const property_offset = PROPERTY_OFFSETS[property];\\n return `${var_array}[entity.index()*${var_attribute_size}+${property_offset}]`;\\n } else {\\n return `${var_array}[entity.index()*${var_attribute_size}]`;\\n }\\n }\\n } else {\\n console.warn(\\\\\\\"attribute not found\\\\\\\");\\n return \\\\\\\"\\\\\\\";\\n }\\n } else {\\n return `${node.operator}${this.traverse_node(node.argument)}`;\\n }\\n }\\n traverse_Literal(node) {\\n return `${node.raw}`;\\n }\\n traverse_Identifier(node) {\\n const identifier_first_char = node.name[0];\\n if (identifier_first_char == VARIABLE_PREFIX) {\\n const identifier_name_without_dollar_sign = node.name.substr(1);\\n const direct_constant_name = GLOBAL_CONSTANTS[identifier_name_without_dollar_sign];\\n if (direct_constant_name) {\\n return direct_constant_name;\\n }\\n const method_name = `traverse_Identifier_${identifier_name_without_dollar_sign}`;\\n const method = this[method_name];\\n if (method) {\\n return this[method_name]();\\n } else {\\n this.set_error(`identifier unknown: ${node.name}`);\\n }\\n } else {\\n return node.name;\\n }\\n }\\n traverse_Identifier_F() {\\n this.immutable_dependencies.push(this.param.scene().timeController.graphNode);\\n return `param.scene().timeController.frame()`;\\n }\\n traverse_Identifier_T() {\\n this.immutable_dependencies.push(this.param.scene().timeController.graphNode);\\n return `param.scene().timeController.time()`;\\n }\\n traverse_Identifier_OS() {\\n return `${QUOTE}${this.param.node.name()}${QUOTE}`;\\n }\\n traverse_Identifier_CH() {\\n return `${QUOTE}${this.param.name()}${QUOTE}`;\\n }\\n traverse_Identifier_CEX() {\\n return this._method_centroid(\\\\\\\"x\\\\\\\");\\n }\\n traverse_Identifier_CEY() {\\n return this._method_centroid(\\\\\\\"y\\\\\\\");\\n }\\n traverse_Identifier_CEZ() {\\n return this._method_centroid(\\\\\\\"z\\\\\\\");\\n }\\n _method_centroid(component) {\\n const method_arguments = [0, `${QUOTE}${component}${QUOTE}`];\\n const arguments_joined = method_arguments.join(ARGUMENTS_SEPARATOR);\\n this._create_method_and_dependencies(\\\\\\\"centroid\\\\\\\", 0);\\n return `(await methods[${this.method_index}].processArguments([${arguments_joined}]))`;\\n }\\n _create_method_and_dependencies(method_name, path_argument, path_node) {\\n const expressionRegister = Poly.expressionsRegister;\\n const method_constructor = expressionRegister.getMethod(method_name);\\n if (!method_constructor) {\\n const available_methods = expressionRegister.availableMethods();\\n const message = `method not found (${method_name}), available methods are: ${available_methods.join(\\\\\\\", \\\\\\\")}`;\\n this.set_error(message);\\n Poly.warn(message);\\n return;\\n }\\n const method = new method_constructor(this.param);\\n this.method_index += 1;\\n this.methods[this.method_index] = method;\\n if (method.require_dependency()) {\\n const method_dependency = method.findDependency(path_argument);\\n if (method_dependency) {\\n if (path_node) {\\n method_dependency.set_jsep_node(path_node);\\n }\\n this.method_dependencies.push(method_dependency);\\n } else {\\n if (path_node && CoreType.isString(path_argument)) {\\n this.param.scene().missingExpressionReferencesController.register(this.param, path_argument);\\n }\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/traversers/ExpressionStringGenerator.ts\\nvar ARGUMENTS_SEPARATOR2 = \\\\\\\", \\\\\\\";\\nvar ExpressionStringGenerator = class extends BaseTraverser {\\n constructor(param) {\\n super(param);\\n this.param = param;\\n }\\n parse_tree(parsed_tree) {\\n if (parsed_tree.error_message == null && parsed_tree.node) {\\n try {\\n return this.traverse_node(parsed_tree.node);\\n } catch (e) {\\n this.set_error(\\\\\\\"could not traverse tree\\\\\\\");\\n }\\n } else {\\n this.set_error(\\\\\\\"cannot parse tree\\\\\\\");\\n }\\n }\\n traverse_CallExpression(node) {\\n const method_arguments = node.arguments.map((arg) => {\\n return this.traverse_node(arg);\\n });\\n const arguments_joined = `${method_arguments.join(ARGUMENTS_SEPARATOR2)}`;\\n const method_name = node.callee.name;\\n return `${method_name}(${arguments_joined})`;\\n }\\n traverse_UnaryExpression(node) {\\n return `${node.operator}${this.traverse_node(node.argument)}`;\\n }\\n traverse_Identifier(node) {\\n return `${node.name}`;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/DependenciesController.ts\\nvar DependenciesController = class {\\n constructor(param) {\\n this.param = param;\\n this.cyclic_graph_detected = false;\\n this.method_dependencies = [];\\n }\\n set_error(message) {\\n this.error_message = this.error_message || message;\\n }\\n reset() {\\n this.param.graphDisconnectPredecessors();\\n this.method_dependencies.forEach((method_dependency) => {\\n method_dependency.reset();\\n });\\n this.method_dependencies = [];\\n }\\n update(function_generator) {\\n this.cyclic_graph_detected = false;\\n this.connect_immutable_dependencies(function_generator);\\n this.method_dependencies = function_generator.method_dependencies;\\n this.handle_method_dependencies();\\n this.listen_for_name_changes();\\n }\\n connect_immutable_dependencies(function_generator) {\\n function_generator.immutable_dependencies.forEach((dependency) => {\\n if (this.cyclic_graph_detected == false) {\\n if (this.param.addGraphInput(dependency) == false) {\\n this.cyclic_graph_detected = true;\\n this.set_error(\\\\\\\"cannot create expression, infinite graph detected\\\\\\\");\\n this.reset();\\n return;\\n }\\n }\\n });\\n }\\n handle_method_dependencies() {\\n this.method_dependencies.forEach((method_dependency) => {\\n if (this.cyclic_graph_detected == false) {\\n this.handle_method_dependency(method_dependency);\\n }\\n });\\n }\\n handle_method_dependency(method_dependency) {\\n const node_simple = method_dependency.resolved_graph_node;\\n if (node_simple) {\\n if (!this.param.addGraphInput(node_simple)) {\\n this.cyclic_graph_detected = true;\\n this.set_error(\\\\\\\"cannot create expression, infinite graph detected\\\\\\\");\\n this.reset();\\n return;\\n }\\n }\\n }\\n listen_for_name_changes() {\\n this.method_dependencies.forEach((method_dependency) => {\\n method_dependency.listen_for_name_changes();\\n });\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/expressions/ExpressionManager.ts\\nvar ExpressionManager = class {\\n constructor(param) {\\n this.param = param;\\n this.parse_completed = false;\\n this.parse_started = false;\\n this.parsed_tree = new ParsedTree();\\n this._functionGenerator = new FunctionGenerator(this.param);\\n this.dependencies_controller = new DependenciesController(this.param);\\n }\\n parseExpression(expression) {\\n if (this.parse_started) {\\n throw new Error(`parse in progress for param ${this.param.path()}`);\\n }\\n this.parse_started = true;\\n this.parse_completed = false;\\n this.parsed_tree = this.parsed_tree || new ParsedTree();\\n this.reset();\\n if (this.param.type() == ParamType.STRING) {\\n this.parsed_tree.parse_expression_for_string_param(expression);\\n } else {\\n this.parsed_tree.parse_expression(expression);\\n }\\n this._functionGenerator.parse_tree(this.parsed_tree);\\n if (this._functionGenerator.error_message() == null) {\\n this.dependencies_controller.update(this._functionGenerator);\\n if (this.dependencies_controller.error_message) {\\n this.param.states.error.set(this.dependencies_controller.error_message);\\n } else {\\n this.parse_completed = true;\\n this.parse_started = false;\\n }\\n }\\n }\\n async computeFunction() {\\n if (this._computeAllowed()) {\\n try {\\n const new_value = await this._functionGenerator.evalFunction();\\n return new_value;\\n } catch (e) {\\n return;\\n }\\n } else {\\n return new Promise((resolve, reject) => {\\n resolve(null);\\n });\\n }\\n }\\n reset() {\\n this.parse_completed = false;\\n this.parse_started = false;\\n this.dependencies_controller.reset();\\n this._functionGenerator.reset();\\n }\\n is_errored() {\\n return this._functionGenerator.is_errored();\\n }\\n error_message() {\\n return this._functionGenerator.error_message();\\n }\\n _computeAllowed() {\\n return this._functionGenerator.evalAllowed();\\n }\\n updateFromMethodDependencyNameChange() {\\n this.expression_string_generator = this.expression_string_generator || new ExpressionStringGenerator(this.param);\\n const new_expression_string = this.expression_string_generator.parse_tree(this.parsed_tree);\\n if (new_expression_string) {\\n this.param.set(new_expression_string);\\n } else {\\n console.warn(\\\\\\\"failed to regenerate expression\\\\\\\");\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/utils/ExpressionController.ts\\nvar ExpressionController = class {\\n constructor(param) {\\n this.param = param;\\n }\\n dispose() {\\n this.param.scene().expressionsController.deregisterParam(this.param);\\n this._resetMethodDependencies();\\n }\\n _resetMethodDependencies() {\\n this._method_dependencies_by_graph_node_id?.forEach((method_dependency) => {\\n method_dependency.dispose();\\n });\\n this._method_dependencies_by_graph_node_id?.clear();\\n }\\n registerMethodDependency(method_dependency) {\\n this._method_dependencies_by_graph_node_id = this._method_dependencies_by_graph_node_id || new Map();\\n this._method_dependencies_by_graph_node_id.set(method_dependency.graphNodeId(), method_dependency);\\n }\\n active() {\\n return this._expression != null;\\n }\\n expression() {\\n return this._expression;\\n }\\n is_errored() {\\n if (this._manager) {\\n return this._manager.is_errored();\\n }\\n return false;\\n }\\n error_message() {\\n if (this._manager) {\\n return this._manager.error_message();\\n }\\n return null;\\n }\\n requires_entities() {\\n return this.param.options.isExpressionForEntities();\\n }\\n set_expression(expression, set_dirty = true) {\\n this.param.scene().missingExpressionReferencesController.deregisterParam(this.param);\\n this.param.scene().expressionsController.deregisterParam(this.param);\\n if (this._expression != expression) {\\n this._resetMethodDependencies();\\n this._expression = expression;\\n if (this._expression) {\\n this._manager = this._manager || new ExpressionManager(this.param);\\n this._manager.parseExpression(this._expression);\\n } else {\\n this._manager?.reset();\\n }\\n if (set_dirty) {\\n this.param.setDirty();\\n }\\n }\\n }\\n updateFromMethodDependencyNameChange() {\\n if (this._manager && this.active()) {\\n this._manager.updateFromMethodDependencyNameChange();\\n }\\n }\\n async computeExpression() {\\n if (this._manager && this.active()) {\\n const result = await this._manager.computeFunction();\\n return result;\\n }\\n }\\n async computeExpressionForEntities(entities, callback) {\\n this.set_entities(entities, callback);\\n await this.computeExpression();\\n if (this._manager?.error_message()) {\\n this.param.node.states.error.set(`expression evalution error: ${this._manager?.error_message()}`);\\n }\\n this.reset_entities();\\n }\\n computeExpressionForPoints(entities, callback) {\\n return this.computeExpressionForEntities(entities, callback);\\n }\\n computeExpressionForObjects(entities, callback) {\\n return this.computeExpressionForEntities(entities, callback);\\n }\\n entities() {\\n return this._entities;\\n }\\n entity_callback() {\\n return this._entity_callback;\\n }\\n set_entities(entities, callback) {\\n this._entities = entities;\\n this._entity_callback = callback;\\n }\\n reset_entities() {\\n this._entities = void 0;\\n this._entity_callback = void 0;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/_Numeric.ts\\nvar TypedNumericParam = class extends TypedParam {\\n isNumeric() {\\n return true;\\n }\\n isDefault() {\\n return this._raw_input == this._default_value;\\n }\\n _prefilter_invalid_raw_input(raw_input) {\\n if (CoreType.isArray(raw_input)) {\\n return raw_input[0];\\n } else {\\n return raw_input;\\n }\\n }\\n processRawInput() {\\n this.states.error.clear();\\n const converted = this.convert(this._raw_input);\\n if (converted != null) {\\n if (this._expression_controller) {\\n this._expression_controller.set_expression(void 0, false);\\n this.emitController.emit(ParamEvent.EXPRESSION_UPDATED);\\n }\\n if (converted != this._value) {\\n this._update_value(converted);\\n this.setSuccessorsDirty(this);\\n }\\n } else {\\n if (CoreType.isString(this._raw_input)) {\\n this._expression_controller = this._expression_controller || new ExpressionController(this);\\n if (this._raw_input != this._expression_controller.expression()) {\\n this._expression_controller.set_expression(this._raw_input);\\n this.emitController.emit(ParamEvent.EXPRESSION_UPDATED);\\n }\\n } else {\\n this.states.error.set(`param input is invalid (${this.path()})`);\\n }\\n }\\n }\\n async processComputation() {\\n if (this.expressionController?.active() && !this.expressionController.requires_entities()) {\\n const expression_result = await this.expressionController.computeExpression();\\n if (this.expressionController.is_errored()) {\\n this.states.error.set(`expression error: \\\\\\\"${this.expressionController.expression()}\\\\\\\" (${this.expressionController.error_message()})`);\\n } else {\\n const converted = this.convert(expression_result);\\n if (converted != null) {\\n if (this.states.error.active()) {\\n this.states.error.clear();\\n }\\n this._update_value(converted);\\n } else {\\n this.states.error.set(`expression returns an invalid type (${expression_result}) (${this.expressionController.expression()})`);\\n }\\n }\\n }\\n }\\n _update_value(new_value) {\\n this._value = new_value;\\n if (this.parent_param) {\\n this.parent_param.set_value_from_components();\\n }\\n this.options.executeCallback();\\n this.emitController.emit(ParamEvent.VALUE_UPDATED);\\n this.removeDirtyState();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Boolean.ts\\nvar BooleanParam = class extends TypedNumericParam {\\n static type() {\\n return ParamType.BOOLEAN;\\n }\\n defaultValueSerialized() {\\n if (CoreType.isString(this._default_value)) {\\n return this._default_value;\\n } else {\\n return this.convert(this._default_value) || false;\\n }\\n }\\n rawInputSerialized() {\\n return this._raw_input;\\n }\\n valueSerialized() {\\n return this.value;\\n }\\n _copy_value(param) {\\n this.set(param.value);\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return raw_input1 == raw_input2;\\n }\\n static are_values_equal(val1, val2) {\\n return val1 == val2;\\n }\\n convert(raw_val) {\\n if (CoreType.isBoolean(raw_val)) {\\n return raw_val;\\n } else {\\n if (CoreType.isNumber(raw_val)) {\\n return raw_val >= 1;\\n } else {\\n if (CoreType.isString(raw_val)) {\\n if (CoreString.isBoolean(raw_val)) {\\n return CoreString.toBoolean(raw_val);\\n } else {\\n if (CoreString.isNumber(raw_val)) {\\n const parsed = parseFloat(raw_val);\\n return parsed >= 1;\\n }\\n }\\n }\\n }\\n }\\n return null;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Button.ts\\nvar ButtonParam = class extends TypedParam {\\n static type() {\\n return ParamType.BUTTON;\\n }\\n defaultValueSerialized() {\\n return this._default_value;\\n }\\n rawInputSerialized() {\\n return this._raw_input;\\n }\\n valueSerialized() {\\n return this.value;\\n }\\n _copy_value(param) {\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return true;\\n }\\n static are_values_equal(val1, val2) {\\n return true;\\n }\\n async pressButton() {\\n if (this.node.isDirty() || this.node.cookController.isCooking()) {\\n await this.node.compute();\\n }\\n this.options.executeCallback();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Float.ts\\nvar FloatParam = class extends TypedNumericParam {\\n static type() {\\n return ParamType.FLOAT;\\n }\\n defaultValueSerialized() {\\n return this._default_value;\\n }\\n rawInputSerialized() {\\n return this._raw_input;\\n }\\n valueSerialized() {\\n return this.value;\\n }\\n _copy_value(param) {\\n this.set(param.valueSerialized());\\n }\\n _prefilter_invalid_raw_input(raw_input) {\\n if (CoreType.isArray(raw_input)) {\\n return raw_input[0];\\n }\\n if (CoreType.isString(raw_input) && CoreString.isNumber(raw_input)) {\\n return parseFloat(raw_input);\\n }\\n return raw_input;\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return raw_input1 == raw_input2;\\n }\\n static are_values_equal(val1, val2) {\\n return val1 == val2;\\n }\\n static convert(raw_val) {\\n if (CoreType.isNumber(raw_val)) {\\n return raw_val;\\n } else {\\n if (CoreType.isBoolean(raw_val)) {\\n return raw_val ? 1 : 0;\\n } else {\\n if (CoreString.isNumber(raw_val)) {\\n const parsed = parseFloat(raw_val);\\n if (CoreType.isNumber(parsed)) {\\n return parsed;\\n }\\n }\\n }\\n return null;\\n }\\n }\\n convert(raw_val) {\\n const result = FloatParam.convert(raw_val);\\n if (result) {\\n return this.options.ensureInRange(result);\\n } else {\\n return result;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/_Multiple.ts\\nvar TypedMultipleParam = class extends TypedParam {\\n constructor() {\\n super(...arguments);\\n this._components_contructor = FloatParam;\\n }\\n get components() {\\n return this._components;\\n }\\n isNumeric() {\\n return true;\\n }\\n isDefault() {\\n for (let c of this.components) {\\n if (!c.isDefault()) {\\n return false;\\n }\\n }\\n return true;\\n }\\n rawInput() {\\n return this._components.map((c) => c.rawInput());\\n }\\n rawInputSerialized() {\\n return this._components.map((c) => c.rawInputSerialized());\\n }\\n _copy_value(param) {\\n for (let i = 0; i < this.components.length; i++) {\\n const component = this.components[i];\\n const src_component = param.components[i];\\n component.copy_value(src_component);\\n }\\n }\\n initComponents() {\\n if (this._components != null) {\\n return;\\n }\\n let index = 0;\\n this._components = new Array(this.componentNames().length);\\n for (let component_name of this.componentNames()) {\\n const component = new this._components_contructor(this.scene(), this._node);\\n let default_val;\\n if (CoreType.isArray(this._default_value)) {\\n default_val = this._default_value[index];\\n } else {\\n default_val = this._default_value[component_name];\\n }\\n component.options.copy(this.options);\\n component.setInitValue(default_val);\\n component.setName(`${this.name()}${component_name}`);\\n component.set_parent_param(this);\\n this._components[index] = component;\\n index++;\\n }\\n }\\n async processComputation() {\\n await this.compute_components();\\n this.set_value_from_components();\\n }\\n set_value_from_components() {\\n }\\n hasExpression() {\\n for (let c of this.components) {\\n if (c.expressionController?.active()) {\\n return true;\\n }\\n }\\n return false;\\n }\\n async compute_components() {\\n const components = this.components;\\n const promises = [];\\n for (let c of components) {\\n if (c.isDirty()) {\\n promises.push(c.compute());\\n }\\n }\\n await Promise.all(promises);\\n this.removeDirtyState();\\n }\\n _prefilter_invalid_raw_input(raw_input) {\\n if (!CoreType.isArray(raw_input)) {\\n const number_or_string = raw_input;\\n const raw_input_wrapped_in_array = this.componentNames().map(() => number_or_string);\\n return raw_input_wrapped_in_array;\\n } else {\\n return raw_input;\\n }\\n }\\n processRawInput() {\\n const cooker = this.scene().cooker;\\n cooker.block();\\n const components = this.components;\\n for (let c of components) {\\n c.emitController.blockParentEmit();\\n }\\n const value = this._raw_input;\\n let prev_value = 0;\\n if (CoreType.isArray(value)) {\\n for (let i = 0; i < components.length; i++) {\\n let component_value = value[i];\\n if (component_value == null) {\\n component_value = prev_value;\\n }\\n components[i].set(component_value);\\n prev_value = component_value;\\n }\\n } else {\\n for (let i = 0; i < components.length; i++) {\\n const component_name = this.componentNames()[i];\\n let component_value = value[component_name];\\n if (component_value == null) {\\n component_value = prev_value;\\n }\\n components[i].set(component_value);\\n prev_value = component_value;\\n }\\n }\\n cooker.unblock();\\n for (let i = 0; i < components.length; i++) {\\n components[i].emitController.unblockParentEmit();\\n }\\n this.emitController.emit(ParamEvent.VALUE_UPDATED);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/Color.ts\\nvar ColorConversion;\\n(function(ColorConversion2) {\\n ColorConversion2[\\\\\\\"NONE\\\\\\\"] = \\\\\\\"no conversion\\\\\\\";\\n ColorConversion2[\\\\\\\"GAMMA_TO_LINEAR\\\\\\\"] = \\\\\\\"gamma -> linear\\\\\\\";\\n ColorConversion2[\\\\\\\"LINEAR_TO_GAMMA\\\\\\\"] = \\\\\\\"linear -> gamma\\\\\\\";\\n ColorConversion2[\\\\\\\"SRGB_TO_LINEAR\\\\\\\"] = \\\\\\\"sRGB -> linear\\\\\\\";\\n ColorConversion2[\\\\\\\"LINEAR_TO_SRGB\\\\\\\"] = \\\\\\\"linear -> sRGB\\\\\\\";\\n})(ColorConversion || (ColorConversion = {}));\\nvar COLOR_CONVERSIONS = [\\n ColorConversion.NONE,\\n ColorConversion.GAMMA_TO_LINEAR,\\n ColorConversion.LINEAR_TO_GAMMA,\\n ColorConversion.SRGB_TO_LINEAR,\\n ColorConversion.LINEAR_TO_SRGB\\n];\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Color.ts\\nvar COMPONENT_NAMES_COLOR = [\\\\\\\"r\\\\\\\", \\\\\\\"g\\\\\\\", \\\\\\\"b\\\\\\\"];\\nvar ColorParam = class extends TypedMultipleParam {\\n constructor() {\\n super(...arguments);\\n this._value = new Color();\\n this._value_pre_conversion = new Color();\\n this._value_serialized_dirty = false;\\n this._value_serialized = [0, 0, 0];\\n this._value_pre_conversion_serialized = [0, 0, 0];\\n this._copied_value = [0, 0, 0];\\n }\\n static type() {\\n return ParamType.COLOR;\\n }\\n componentNames() {\\n return COMPONENT_NAMES_COLOR;\\n }\\n defaultValueSerialized() {\\n if (CoreType.isArray(this._default_value)) {\\n return this._default_value;\\n } else {\\n return this._default_value.toArray();\\n }\\n }\\n valueSerialized() {\\n this._update_value_serialized_if_required();\\n return this._value_serialized;\\n }\\n valuePreConversionSerialized() {\\n this._update_value_serialized_if_required();\\n return this._value_pre_conversion_serialized;\\n }\\n _copy_value(param) {\\n param.value.toArray(this._copied_value);\\n this.set(this._copied_value);\\n }\\n _clone_raw_input(raw_input) {\\n if (raw_input instanceof Color) {\\n return raw_input.clone();\\n } else {\\n const new_array = [raw_input[0], raw_input[1], raw_input[2]];\\n if (new_array[0] == null) {\\n new_array[0] = new_array[0] || 0;\\n }\\n if (new_array[1] == null) {\\n new_array[1] = new_array[1] || new_array[0];\\n }\\n if (new_array[2] == null) {\\n new_array[2] = new_array[2] || new_array[1];\\n }\\n return new_array;\\n }\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n if (raw_input1 instanceof Color) {\\n if (raw_input2 instanceof Color) {\\n return raw_input1.equals(raw_input2);\\n } else {\\n return raw_input1.r == raw_input2[0] && raw_input1.g == raw_input2[1] && raw_input1.b == raw_input2[2];\\n }\\n } else {\\n if (raw_input2 instanceof Color) {\\n return raw_input1[0] == raw_input2.r && raw_input1[1] == raw_input2.g && raw_input1[2] == raw_input2.b;\\n } else {\\n return raw_input1[0] == raw_input2[0] && raw_input1[1] == raw_input2[1] && raw_input1[2] == raw_input2[2];\\n }\\n }\\n }\\n static are_values_equal(val1, val2) {\\n return val1.equals(val2);\\n }\\n initComponents() {\\n super.initComponents();\\n this.r = this.components[0];\\n this.g = this.components[1];\\n this.b = this.components[2];\\n this._value_serialized_dirty = true;\\n }\\n _update_value_serialized_if_required() {\\n if (!this._value_serialized_dirty) {\\n return;\\n }\\n this._value_serialized[0] = this._value.r;\\n this._value_serialized[1] = this._value.g;\\n this._value_serialized[2] = this._value.b;\\n this._value_pre_conversion_serialized[0] = this._value_pre_conversion.r;\\n this._value_pre_conversion_serialized[1] = this._value_pre_conversion.g;\\n this._value_pre_conversion_serialized[2] = this._value_pre_conversion.b;\\n }\\n valuePreConversion() {\\n return this._value_pre_conversion;\\n }\\n set_value_from_components() {\\n this._value_pre_conversion.r = this.r.value;\\n this._value_pre_conversion.g = this.g.value;\\n this._value_pre_conversion.b = this.b.value;\\n this._value.copy(this._value_pre_conversion);\\n const conversion = this.options.colorConversion();\\n if (conversion != null && conversion != ColorConversion.NONE) {\\n switch (conversion) {\\n case ColorConversion.GAMMA_TO_LINEAR: {\\n this._value.convertGammaToLinear();\\n return;\\n }\\n case ColorConversion.LINEAR_TO_GAMMA: {\\n this._value.convertLinearToGamma();\\n return;\\n }\\n case ColorConversion.SRGB_TO_LINEAR: {\\n this._value.convertSRGBToLinear();\\n return;\\n }\\n case ColorConversion.LINEAR_TO_SRGB: {\\n this._value.convertLinearToSRGB();\\n return;\\n }\\n }\\n TypeAssert.unreachable(conversion);\\n }\\n this._value_serialized_dirty = true;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Folder.ts\\nvar FolderParam = class extends TypedParam {\\n static type() {\\n return ParamType.FOLDER;\\n }\\n defaultValueSerialized() {\\n return this._default_value;\\n }\\n rawInputSerialized() {\\n return this._raw_input;\\n }\\n valueSerialized() {\\n return this.value;\\n }\\n _copy_value(param) {\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return true;\\n }\\n static are_values_equal(val1, val2) {\\n return true;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Integer.ts\\nvar IntegerParam = class extends TypedNumericParam {\\n static type() {\\n return ParamType.INTEGER;\\n }\\n defaultValueSerialized() {\\n return this._default_value;\\n }\\n rawInputSerialized() {\\n return this._raw_input;\\n }\\n valueSerialized() {\\n return this.value;\\n }\\n _copy_value(param) {\\n this.set(param.valueSerialized());\\n }\\n _prefilter_invalid_raw_input(raw_input) {\\n if (CoreType.isArray(raw_input)) {\\n return raw_input[0];\\n }\\n if (CoreType.isString(raw_input) && CoreString.isNumber(raw_input)) {\\n return parseInt(raw_input);\\n }\\n return raw_input;\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return raw_input1 == raw_input2;\\n }\\n static are_values_equal(val1, val2) {\\n return val1 == val2;\\n }\\n static convert(raw_val) {\\n if (CoreType.isNumber(raw_val)) {\\n return Math.round(raw_val);\\n } else {\\n if (CoreType.isBoolean(raw_val)) {\\n return raw_val ? 1 : 0;\\n } else {\\n if (CoreString.isNumber(raw_val)) {\\n const parsed = parseInt(raw_val);\\n if (CoreType.isNumber(parsed)) {\\n return parsed;\\n }\\n }\\n }\\n return null;\\n }\\n }\\n convert(raw_val) {\\n const result = IntegerParam.convert(raw_val);\\n if (result) {\\n return this.options.ensureInRange(result);\\n } else {\\n return result;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/DecomposedPath.ts\\nvar DecomposedPath = class {\\n constructor() {\\n this._index = -1;\\n this._path_elements = [];\\n this._named_nodes = [];\\n this._graph_node_ids = [];\\n this._node_element_by_graph_node_id = new Map();\\n }\\n reset() {\\n this._index = -1;\\n this._path_elements = [];\\n this._named_nodes = [];\\n this._graph_node_ids = [];\\n this._node_element_by_graph_node_id.clear();\\n }\\n add_node(name, node) {\\n this._index += 1;\\n if (name == node.name()) {\\n this._named_nodes[this._index] = node;\\n }\\n this._graph_node_ids[this._index] = node.graphNodeId();\\n this._node_element_by_graph_node_id.set(node.graphNodeId(), name);\\n }\\n add_path_element(path_element) {\\n this._index += 1;\\n this._path_elements[this._index] = path_element;\\n }\\n named_graph_nodes() {\\n return this._named_nodes;\\n }\\n named_nodes() {\\n const nodes = [];\\n for (let graph_node of this._named_nodes) {\\n if (graph_node) {\\n const node = graph_node;\\n if (node.nameController) {\\n nodes.push(node);\\n }\\n }\\n }\\n return nodes;\\n }\\n update_from_name_change(node) {\\n const named_graph_node_ids = this._named_nodes.map((n) => n?.graphNodeId());\\n if (named_graph_node_ids.includes(node.graphNodeId())) {\\n this._node_element_by_graph_node_id.set(node.graphNodeId(), node.name());\\n }\\n }\\n to_path() {\\n const elements = new Array(this._index);\\n for (let i = 0; i <= this._index; i++) {\\n const node = this._named_nodes[i];\\n if (node) {\\n const node_name = this._node_element_by_graph_node_id.get(node.graphNodeId());\\n if (node_name) {\\n elements[i] = node_name;\\n }\\n } else {\\n const path_element = this._path_elements[i];\\n if (path_element) {\\n elements[i] = path_element;\\n }\\n }\\n }\\n let joined_path = elements.join(CoreWalker.SEPARATOR);\\n const first_char = joined_path[0];\\n if (first_char) {\\n if (!CoreWalker.NON_LETTER_PREFIXES.includes(first_char)) {\\n joined_path = `${CoreWalker.SEPARATOR}${joined_path}`;\\n }\\n }\\n return joined_path;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/_BasePath.ts\\nvar TypedPathParam = class extends TypedParam {\\n constructor() {\\n super(...arguments);\\n this.decomposed_path = new DecomposedPath();\\n }\\n _handleReferences(node, path) {\\n this.scene().referencesController.setNamedNodesFromParam(this);\\n if (node) {\\n this.scene().referencesController.setReferenceFromParam(this, node);\\n } else {\\n this.scene().missingExpressionReferencesController.register(this, path);\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/OperatorPath.ts\\nvar OperatorPathMode;\\n(function(OperatorPathMode2) {\\n OperatorPathMode2[\\\\\\\"NODE\\\\\\\"] = \\\\\\\"NODE\\\\\\\";\\n OperatorPathMode2[\\\\\\\"PARAM\\\\\\\"] = \\\\\\\"PARAM\\\\\\\";\\n})(OperatorPathMode || (OperatorPathMode = {}));\\nvar OperatorPathParam = class extends TypedPathParam {\\n constructor() {\\n super(...arguments);\\n this._found_node = null;\\n this._found_node_with_expected_type = null;\\n this._found_param = null;\\n this._found_param_with_expected_type = null;\\n }\\n static type() {\\n return ParamType.OPERATOR_PATH;\\n }\\n defaultValueSerialized() {\\n return this._default_value;\\n }\\n rawInputSerialized() {\\n return `${this._raw_input}`;\\n }\\n valueSerialized() {\\n return `${this.value}`;\\n }\\n _copy_value(param) {\\n this.set(param.valueSerialized());\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return raw_input1 == raw_input2;\\n }\\n static are_values_equal(val1, val2) {\\n return val1 == val2;\\n }\\n isDefault() {\\n return this._value == this._default_value;\\n }\\n setNode(node) {\\n this.set(node.path());\\n }\\n processRawInput() {\\n if (this._value != this._raw_input) {\\n this._value = this._raw_input;\\n this.setDirty();\\n this.emitController.emit(ParamEvent.VALUE_UPDATED);\\n }\\n }\\n async processComputation() {\\n this.find_target();\\n }\\n find_target() {\\n if (!this.node) {\\n return;\\n }\\n const path = this._value;\\n let node = null;\\n let param = null;\\n const path_non_empty = path != null && path !== \\\\\\\"\\\\\\\";\\n const mode = this.options.paramSelectionOptions() ? OperatorPathMode.PARAM : OperatorPathMode.NODE;\\n this.scene().referencesController.resetReferenceFromParam(this);\\n this.decomposed_path.reset();\\n if (path_non_empty) {\\n if (mode == OperatorPathMode.PARAM) {\\n param = CoreWalker.findParam(this.node, path, this.decomposed_path);\\n } else {\\n node = CoreWalker.findNode(this.node, path, this.decomposed_path);\\n }\\n }\\n const current_found_entity = mode == OperatorPathMode.PARAM ? this._found_param : this._found_node;\\n const newly_found_entity = mode == OperatorPathMode.PARAM ? param : node;\\n this._handleReferences(node, path);\\n if (current_found_entity?.graphNodeId() !== newly_found_entity?.graphNodeId()) {\\n const dependent_on_found_node = this.options.dependentOnFoundNode();\\n if (this._found_node) {\\n if (dependent_on_found_node) {\\n this.removeGraphInput(this._found_node);\\n } else {\\n }\\n }\\n if (mode == OperatorPathMode.PARAM) {\\n this._found_param = param;\\n this._found_node = null;\\n } else {\\n this._found_node = node;\\n this._found_param = null;\\n }\\n if (node) {\\n this._assign_found_node(node);\\n }\\n if (param) {\\n this._assign_found_param(param);\\n }\\n this.options.executeCallback();\\n }\\n this.removeDirtyState();\\n }\\n _assign_found_node(node) {\\n const dependent_on_found_node = this.options.dependentOnFoundNode();\\n if (this._is_node_expected_context(node)) {\\n if (this._is_node_expected_type(node)) {\\n this._found_node_with_expected_type = node;\\n if (dependent_on_found_node) {\\n this.addGraphInput(node);\\n }\\n } else {\\n this.states.error.set(`node type is ${node.type()} but the params expects one of ${(this._expected_node_types() || []).join(\\\\\\\", \\\\\\\")}`);\\n }\\n } else {\\n this.states.error.set(`node context is ${node.context()} but the params expects a ${this._expected_context()}`);\\n }\\n }\\n _assign_found_param(param) {\\n if (this._is_param_expected_type(param)) {\\n this._found_param_with_expected_type = param;\\n } else {\\n this.states.error.set(`param type is ${param.type()} but the params expects a ${this._expected_param_type()}`);\\n }\\n }\\n found_node() {\\n return this._found_node;\\n }\\n found_param() {\\n return this._found_param;\\n }\\n found_node_with_context(context) {\\n return this._found_node_with_expected_type;\\n }\\n found_node_with_context_and_type(context, type_or_types) {\\n const node = this.found_node_with_context(context);\\n if (node) {\\n if (CoreType.isArray(type_or_types)) {\\n for (let type of type_or_types) {\\n if (node.type() == type) {\\n return node;\\n }\\n }\\n this.states.error.set(`expected node type to be ${type_or_types.join(\\\\\\\", \\\\\\\")}, but was instead ${node.type()}`);\\n } else {\\n const type = type_or_types;\\n if (node.type() == type) {\\n return node;\\n } else {\\n this.states.error.set(`expected node type to be ${type}, but was instead ${node.type()}`);\\n }\\n }\\n }\\n }\\n found_param_with_type(type) {\\n if (this._found_param_with_expected_type) {\\n return this._found_param_with_expected_type;\\n }\\n }\\n found_node_with_expected_type() {\\n return this._found_node_with_expected_type;\\n }\\n _expected_context() {\\n return this.options.nodeSelectionContext();\\n }\\n _is_node_expected_context(node) {\\n const expected_context = this._expected_context();\\n if (expected_context == null) {\\n return true;\\n }\\n const node_context = node.parent()?.childrenController?.context;\\n return expected_context == node_context;\\n }\\n _expected_node_types() {\\n return this.options.nodeSelectionTypes();\\n }\\n _expected_param_type() {\\n return this.options.paramSelectionType();\\n }\\n _is_node_expected_type(node) {\\n const expected_types = this._expected_node_types();\\n if (expected_types == null) {\\n return true;\\n }\\n return expected_types?.includes(node.type());\\n }\\n _is_param_expected_type(param) {\\n const expected_types = this._expected_node_types();\\n if (expected_types == null) {\\n return true;\\n }\\n return expected_types.includes(param.type());\\n }\\n notifyPathRebuildRequired(node) {\\n this.decomposed_path.update_from_name_change(node);\\n const new_path = this.decomposed_path.to_path();\\n this.set(new_path);\\n }\\n notifyTargetParamOwnerParamsUpdated(node) {\\n this.setDirty();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/ParamPath.ts\\nvar ParamPathParam = class extends TypedPathParam {\\n static type() {\\n return ParamType.PARAM_PATH;\\n }\\n initialize_param() {\\n this._value = new TypedParamPathParamValue();\\n }\\n defaultValueSerialized() {\\n return this._default_value;\\n }\\n rawInputSerialized() {\\n return `${this._raw_input}`;\\n }\\n valueSerialized() {\\n return `${this.value}`;\\n }\\n _copy_value(param) {\\n this.set(param.valueSerialized());\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return raw_input1 == raw_input2;\\n }\\n static are_values_equal(val1, val2) {\\n return val1 == val2;\\n }\\n isDefault() {\\n return this._raw_input == this._default_value;\\n }\\n setParam(param) {\\n this.set(param.path());\\n }\\n processRawInput() {\\n if (this._value.path() != this._raw_input) {\\n this._value.set_path(this._raw_input);\\n this.find_target();\\n this.setDirty();\\n this.emitController.emit(ParamEvent.VALUE_UPDATED);\\n }\\n }\\n async processComputation() {\\n this.find_target();\\n }\\n find_target() {\\n if (!this.node) {\\n return;\\n }\\n const path = this._raw_input;\\n let param = null;\\n const path_non_empty = path != null && path !== \\\\\\\"\\\\\\\";\\n this.scene().referencesController.resetReferenceFromParam(this);\\n this.decomposed_path.reset();\\n if (path_non_empty) {\\n param = CoreWalker.findParam(this.node, path, this.decomposed_path);\\n }\\n const current_found_entity = this._value.param();\\n const newly_found_entity = param;\\n this._handleReferences(param, path);\\n if (current_found_entity?.graphNodeId() !== newly_found_entity?.graphNodeId()) {\\n const dependent_on_found_node = this.options.dependentOnFoundNode();\\n const previously_found_node = this._value.param();\\n if (previously_found_node) {\\n if (dependent_on_found_node) {\\n this.removeGraphInput(previously_found_node);\\n } else {\\n }\\n }\\n if (param) {\\n this._assign_found_node(param);\\n } else {\\n this._value.set_param(null);\\n }\\n this.options.executeCallback();\\n }\\n this.removeDirtyState();\\n }\\n _assign_found_node(param) {\\n const dependent_on_found_node = this.options.dependentOnFoundNode();\\n this._value.set_param(param);\\n if (dependent_on_found_node) {\\n this.addGraphInput(param);\\n }\\n }\\n notifyPathRebuildRequired(param) {\\n this.decomposed_path.update_from_name_change(param);\\n const new_path = this.decomposed_path.to_path();\\n this.set(new_path);\\n }\\n notifyTargetParamOwnerParamsUpdated(node) {\\n this.setDirty();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/NodePath.ts\\nvar NodePathParam = class extends TypedPathParam {\\n static type() {\\n return ParamType.NODE_PATH;\\n }\\n initialize_param() {\\n this._value = new TypedNodePathParamValue();\\n }\\n defaultValueSerialized() {\\n return this._default_value;\\n }\\n rawInputSerialized() {\\n return `${this._raw_input}`;\\n }\\n valueSerialized() {\\n return `${this.value}`;\\n }\\n _copy_value(param) {\\n this.set(param.valueSerialized());\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return raw_input1 == raw_input2;\\n }\\n static are_values_equal(val1, val2) {\\n return val1 == val2;\\n }\\n isDefault() {\\n return this._raw_input == this._default_value;\\n }\\n setNode(node) {\\n this.set(node.path());\\n }\\n processRawInput() {\\n if (this._value.path() != this._raw_input) {\\n this._value.set_path(this._raw_input);\\n this._findTarget();\\n this.setDirty();\\n this.emitController.emit(ParamEvent.VALUE_UPDATED);\\n }\\n }\\n async processComputation() {\\n this._findTarget();\\n }\\n _findTarget() {\\n if (!this.node) {\\n return;\\n }\\n const path = this._raw_input;\\n let node = null;\\n const path_non_empty = path != null && path !== \\\\\\\"\\\\\\\";\\n this.scene().referencesController.resetReferenceFromParam(this);\\n this.decomposed_path.reset();\\n if (path_non_empty) {\\n node = CoreWalker.findNode(this.node, path, this.decomposed_path);\\n }\\n const current_found_entity = this._value.node();\\n const newly_found_entity = node;\\n this._handleReferences(node, path);\\n if (current_found_entity?.graphNodeId() !== newly_found_entity?.graphNodeId()) {\\n const dependent_on_found_node = this.options.dependentOnFoundNode();\\n const previously_found_node = this._value.node();\\n if (previously_found_node) {\\n if (dependent_on_found_node) {\\n this.removeGraphInput(previously_found_node);\\n } else {\\n }\\n }\\n if (node) {\\n this._assign_found_node(node);\\n } else {\\n this._value.set_node(null);\\n }\\n this.options.executeCallback();\\n }\\n if (path_non_empty && !node && this.scene().loadingController.loaded()) {\\n if (path_non_empty) {\\n this.states.error.set(`no node found at path '${path}'`);\\n }\\n }\\n this.removeDirtyState();\\n }\\n _assign_found_node(node) {\\n const dependent_on_found_node = this.options.dependentOnFoundNode();\\n if (this._isNodeExpectedContext(node)) {\\n if (this._is_node_expected_type(node)) {\\n this.states.error.clear();\\n this._value.set_node(node);\\n if (dependent_on_found_node) {\\n this.addGraphInput(node);\\n }\\n } else {\\n this.states.error.set(`node type is ${node.type()} but the params expects one of ${(this._expected_node_types() || []).join(\\\\\\\", \\\\\\\")}`);\\n }\\n } else {\\n this.states.error.set(`node context is ${node.context()} but the params expects a ${this._expectedContext()}`);\\n }\\n }\\n _expectedContext() {\\n return this.options.nodeSelectionContext();\\n }\\n _isNodeExpectedContext(node) {\\n const expected_context = this._expectedContext();\\n if (expected_context == null) {\\n return true;\\n }\\n const node_context = node.parent()?.childrenController?.context;\\n return expected_context == node_context;\\n }\\n _expected_node_types() {\\n return this.options.nodeSelectionTypes();\\n }\\n _is_node_expected_type(node) {\\n const expected_types = this._expected_node_types();\\n if (expected_types == null) {\\n return true;\\n }\\n return expected_types?.includes(node.type());\\n }\\n notifyPathRebuildRequired(node) {\\n this.decomposed_path.update_from_name_change(node);\\n const newPath = this.decomposed_path.to_path();\\n this.set(newPath);\\n }\\n notifyTargetParamOwnerParamsUpdated(node) {\\n this.setDirty();\\n }\\n};\\n\\n// ../../../node_modules/three/src/textures/DataTexture.js\\nvar DataTexture = class extends Texture {\\n constructor(data = null, width = 1, height = 1, format, type, mapping, wrapS, wrapT, magFilter = NearestFilter, minFilter = NearestFilter, anisotropy, encoding) {\\n super(null, mapping, wrapS, wrapT, magFilter, minFilter, format, type, anisotropy, encoding);\\n this.image = {data, width, height};\\n this.magFilter = magFilter;\\n this.minFilter = minFilter;\\n this.generateMipmaps = false;\\n this.flipY = false;\\n this.unpackAlignment = 1;\\n this.needsUpdate = true;\\n }\\n};\\nDataTexture.prototype.isDataTexture = true;\\n\\n// ../../../node_modules/three/src/math/Interpolant.js\\nvar Interpolant = class {\\n constructor(parameterPositions, sampleValues, sampleSize, resultBuffer) {\\n this.parameterPositions = parameterPositions;\\n this._cachedIndex = 0;\\n this.resultBuffer = resultBuffer !== void 0 ? resultBuffer : new sampleValues.constructor(sampleSize);\\n this.sampleValues = sampleValues;\\n this.valueSize = sampleSize;\\n this.settings = null;\\n this.DefaultSettings_ = {};\\n }\\n evaluate(t) {\\n const pp = this.parameterPositions;\\n let i1 = this._cachedIndex, t1 = pp[i1], t0 = pp[i1 - 1];\\n validate_interval: {\\n seek: {\\n let right;\\n linear_scan: {\\n forward_scan:\\n if (!(t < t1)) {\\n for (let giveUpAt = i1 + 2; ; ) {\\n if (t1 === void 0) {\\n if (t < t0)\\n break forward_scan;\\n i1 = pp.length;\\n this._cachedIndex = i1;\\n return this.afterEnd_(i1 - 1, t, t0);\\n }\\n if (i1 === giveUpAt)\\n break;\\n t0 = t1;\\n t1 = pp[++i1];\\n if (t < t1) {\\n break seek;\\n }\\n }\\n right = pp.length;\\n break linear_scan;\\n }\\n if (!(t >= t0)) {\\n const t1global = pp[1];\\n if (t < t1global) {\\n i1 = 2;\\n t0 = t1global;\\n }\\n for (let giveUpAt = i1 - 2; ; ) {\\n if (t0 === void 0) {\\n this._cachedIndex = 0;\\n return this.beforeStart_(0, t, t1);\\n }\\n if (i1 === giveUpAt)\\n break;\\n t1 = t0;\\n t0 = pp[--i1 - 1];\\n if (t >= t0) {\\n break seek;\\n }\\n }\\n right = i1;\\n i1 = 0;\\n break linear_scan;\\n }\\n break validate_interval;\\n }\\n while (i1 < right) {\\n const mid = i1 + right >>> 1;\\n if (t < pp[mid]) {\\n right = mid;\\n } else {\\n i1 = mid + 1;\\n }\\n }\\n t1 = pp[i1];\\n t0 = pp[i1 - 1];\\n if (t0 === void 0) {\\n this._cachedIndex = 0;\\n return this.beforeStart_(0, t, t1);\\n }\\n if (t1 === void 0) {\\n i1 = pp.length;\\n this._cachedIndex = i1;\\n return this.afterEnd_(i1 - 1, t0, t);\\n }\\n }\\n this._cachedIndex = i1;\\n this.intervalChanged_(i1, t0, t1);\\n }\\n return this.interpolate_(i1, t0, t, t1);\\n }\\n getSettings_() {\\n return this.settings || this.DefaultSettings_;\\n }\\n copySampleValue_(index) {\\n const result = this.resultBuffer, values = this.sampleValues, stride = this.valueSize, offset = index * stride;\\n for (let i = 0; i !== stride; ++i) {\\n result[i] = values[offset + i];\\n }\\n return result;\\n }\\n interpolate_() {\\n throw new Error(\\\\\\\"call to abstract method\\\\\\\");\\n }\\n intervalChanged_() {\\n }\\n};\\nInterpolant.prototype.beforeStart_ = Interpolant.prototype.copySampleValue_;\\nInterpolant.prototype.afterEnd_ = Interpolant.prototype.copySampleValue_;\\n\\n// ../../../node_modules/three/src/math/interpolants/CubicInterpolant.js\\nvar CubicInterpolant = class extends Interpolant {\\n constructor(parameterPositions, sampleValues, sampleSize, resultBuffer) {\\n super(parameterPositions, sampleValues, sampleSize, resultBuffer);\\n this._weightPrev = -0;\\n this._offsetPrev = -0;\\n this._weightNext = -0;\\n this._offsetNext = -0;\\n this.DefaultSettings_ = {\\n endingStart: ZeroCurvatureEnding,\\n endingEnd: ZeroCurvatureEnding\\n };\\n }\\n intervalChanged_(i1, t0, t1) {\\n const pp = this.parameterPositions;\\n let iPrev = i1 - 2, iNext = i1 + 1, tPrev = pp[iPrev], tNext = pp[iNext];\\n if (tPrev === void 0) {\\n switch (this.getSettings_().endingStart) {\\n case ZeroSlopeEnding:\\n iPrev = i1;\\n tPrev = 2 * t0 - t1;\\n break;\\n case WrapAroundEnding:\\n iPrev = pp.length - 2;\\n tPrev = t0 + pp[iPrev] - pp[iPrev + 1];\\n break;\\n default:\\n iPrev = i1;\\n tPrev = t1;\\n }\\n }\\n if (tNext === void 0) {\\n switch (this.getSettings_().endingEnd) {\\n case ZeroSlopeEnding:\\n iNext = i1;\\n tNext = 2 * t1 - t0;\\n break;\\n case WrapAroundEnding:\\n iNext = 1;\\n tNext = t1 + pp[1] - pp[0];\\n break;\\n default:\\n iNext = i1 - 1;\\n tNext = t0;\\n }\\n }\\n const halfDt = (t1 - t0) * 0.5, stride = this.valueSize;\\n this._weightPrev = halfDt / (t0 - tPrev);\\n this._weightNext = halfDt / (tNext - t1);\\n this._offsetPrev = iPrev * stride;\\n this._offsetNext = iNext * stride;\\n }\\n interpolate_(i1, t0, t, t1) {\\n const result = this.resultBuffer, values = this.sampleValues, stride = this.valueSize, o1 = i1 * stride, o0 = o1 - stride, oP = this._offsetPrev, oN = this._offsetNext, wP = this._weightPrev, wN = this._weightNext, p = (t - t0) / (t1 - t0), pp = p * p, ppp = pp * p;\\n const sP = -wP * ppp + 2 * wP * pp - wP * p;\\n const s0 = (1 + wP) * ppp + (-1.5 - 2 * wP) * pp + (-0.5 + wP) * p + 1;\\n const s1 = (-1 - wN) * ppp + (1.5 + wN) * pp + 0.5 * p;\\n const sN = wN * ppp - wN * pp;\\n for (let i = 0; i !== stride; ++i) {\\n result[i] = sP * values[oP + i] + s0 * values[o0 + i] + s1 * values[o1 + i] + sN * values[oN + i];\\n }\\n return result;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/ramp/RampValue.ts\\nvar RampPoint = class {\\n constructor(_position3 = 0, _value = 0) {\\n this._position = _position3;\\n this._value = _value;\\n }\\n toJSON() {\\n return {\\n position: this._position,\\n value: this._value\\n };\\n }\\n position() {\\n return this._position;\\n }\\n value() {\\n return this._value;\\n }\\n copy(point) {\\n this._position = point.position();\\n this._value = point.value();\\n }\\n clone() {\\n const point = new RampPoint();\\n point.copy(this);\\n return point;\\n }\\n isEqual(other_point) {\\n return this._position == other_point.position() && this._value == other_point.value();\\n }\\n isEqualJSON(json) {\\n return this._position == json.position && this._value == json.value;\\n }\\n fromJSON(json) {\\n this._position = json.position;\\n this._value = json.value;\\n }\\n static areEqualJSON(json1, json2) {\\n return json1.position == json2.position && json1.value == json2.value;\\n }\\n static fromJSON(json) {\\n return new RampPoint(json.position, json.value);\\n }\\n};\\nvar RampInterpolation;\\n(function(RampInterpolation2) {\\n RampInterpolation2[\\\\\\\"LINEAR\\\\\\\"] = \\\\\\\"linear\\\\\\\";\\n})(RampInterpolation || (RampInterpolation = {}));\\nvar RampValue = class {\\n constructor(_interpolation = RampInterpolation.LINEAR, _points2 = []) {\\n this._interpolation = _interpolation;\\n this._points = _points2;\\n this._uuid = generateUUID();\\n }\\n uuid() {\\n return this._uuid;\\n }\\n interpolation() {\\n return this._interpolation;\\n }\\n points() {\\n return this._points;\\n }\\n static fromJSON(json) {\\n const points2 = [];\\n for (let jsonPoint of json.points) {\\n points2.push(RampPoint.fromJSON(jsonPoint));\\n }\\n return new RampValue(json.interpolation, points2);\\n }\\n toJSON() {\\n return {\\n interpolation: this._interpolation,\\n points: this._points.map((p) => p.toJSON())\\n };\\n }\\n clone() {\\n const ramp = new RampValue();\\n ramp.copy(this);\\n return ramp;\\n }\\n copy(ramp) {\\n this._interpolation = ramp.interpolation();\\n let index = 0;\\n for (let point of ramp.points()) {\\n const current_point = this._points[index];\\n if (current_point) {\\n current_point.copy(point);\\n } else {\\n this._points.push(point.clone());\\n }\\n index += 1;\\n }\\n }\\n is_equal(other_ramp_value) {\\n if (this._interpolation != other_ramp_value.interpolation()) {\\n return false;\\n }\\n const other_points = other_ramp_value.points();\\n if (this._points.length != other_points.length) {\\n return false;\\n }\\n let index = 0;\\n for (let point of this._points) {\\n const other_point = other_points[index];\\n if (!point.isEqual(other_point)) {\\n return false;\\n }\\n index += 1;\\n }\\n return true;\\n }\\n is_equal_json(json) {\\n if (this._interpolation != json.interpolation) {\\n return false;\\n }\\n if (this._points.length != json.points.length) {\\n return false;\\n }\\n let index = 0;\\n for (let point of this._points) {\\n const other_point = json.points[index];\\n if (!point.isEqualJSON(other_point)) {\\n return false;\\n }\\n index += 1;\\n }\\n return true;\\n }\\n static are_json_equal(json1, json2) {\\n if (json1.interpolation != json2.interpolation) {\\n return false;\\n }\\n if (json1.points.length != json2.points.length) {\\n return false;\\n }\\n let index = 0;\\n for (let point1 of json1.points) {\\n const point2 = json2.points[index];\\n if (!RampPoint.areEqualJSON(point1, point2)) {\\n return false;\\n }\\n index += 1;\\n }\\n return true;\\n }\\n from_json(json) {\\n this._interpolation = json.interpolation;\\n let index = 0;\\n for (let json_point of json.points) {\\n const current_point = this._points[index];\\n if (current_point) {\\n current_point.fromJSON(json_point);\\n } else {\\n this._points.push(RampPoint.fromJSON(json_point));\\n }\\n index += 1;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Ramp.ts\\nvar TEXTURE_WIDTH = 1024;\\nvar TEXTURE_HEIGHT = 1;\\nvar TEXTURE_SIZE = TEXTURE_WIDTH * TEXTURE_HEIGHT;\\nvar TEXTURE_BYTES_MULT = 255;\\nvar RampParam2 = class extends TypedParam {\\n constructor() {\\n super(...arguments);\\n this._texture_data = new Uint8Array(3 * TEXTURE_SIZE);\\n this._ramp_texture = new DataTexture(this._texture_data, TEXTURE_WIDTH, TEXTURE_HEIGHT, RGBFormat);\\n }\\n static type() {\\n return ParamType.RAMP;\\n }\\n defaultValueSerialized() {\\n if (this._default_value instanceof RampValue) {\\n return this._default_value.toJSON();\\n } else {\\n return this._default_value;\\n }\\n }\\n _clone_raw_input(raw_input) {\\n if (raw_input instanceof RampValue) {\\n return raw_input.clone();\\n } else {\\n return RampValue.fromJSON(raw_input).toJSON();\\n }\\n }\\n rawInputSerialized() {\\n if (this._raw_input instanceof RampValue) {\\n return this._raw_input.toJSON();\\n } else {\\n return RampValue.fromJSON(this._raw_input).toJSON();\\n }\\n }\\n valueSerialized() {\\n return this.value.toJSON();\\n }\\n _copy_value(param) {\\n this.set(param.valueSerialized());\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n if (raw_input1 instanceof RampValue) {\\n if (raw_input2 instanceof RampValue) {\\n return raw_input1.is_equal(raw_input2);\\n } else {\\n return raw_input1.is_equal_json(raw_input2);\\n }\\n } else {\\n if (raw_input2 instanceof RampValue) {\\n return raw_input2.is_equal_json(raw_input1);\\n } else {\\n return RampValue.are_json_equal(raw_input1, raw_input2);\\n }\\n }\\n }\\n static are_values_equal(val1, val2) {\\n return val1.is_equal(val2);\\n }\\n isDefault() {\\n if (this._default_value instanceof RampValue) {\\n return this.value.is_equal(this._default_value);\\n } else {\\n return this.value.is_equal_json(this._default_value);\\n }\\n }\\n processRawInput() {\\n if (this._raw_input instanceof RampValue) {\\n if (!this._value) {\\n this._value = this._raw_input;\\n } else {\\n this._value.copy(this._raw_input);\\n }\\n } else {\\n if (!this._value) {\\n this._value = RampValue.fromJSON(this._raw_input);\\n } else {\\n this._value.from_json(this._raw_input);\\n }\\n }\\n this._resetRampInterpolant();\\n this._updateRampTexture();\\n this.options.executeCallback();\\n this.emitController.emit(ParamEvent.VALUE_UPDATED);\\n this.setSuccessorsDirty(this);\\n }\\n hasExpression() {\\n return false;\\n }\\n _resetRampInterpolant() {\\n this._ramp_interpolant = void 0;\\n }\\n rampTexture() {\\n return this._ramp_texture;\\n }\\n _updateRampTexture() {\\n this._updateRampTextureData();\\n this.rampTexture().needsUpdate = true;\\n }\\n _updateRampTextureData() {\\n let stride = 0;\\n let position = 0;\\n let value = 0;\\n for (var i = 0; i < TEXTURE_SIZE; i++) {\\n stride = i * 3;\\n position = i / TEXTURE_WIDTH;\\n value = this.valueAtPosition(position);\\n if (value <= 0) {\\n this._texture_data[stride + 0] = (clamp(value, -1, 0) + 1) * TEXTURE_BYTES_MULT;\\n this._texture_data[stride + 1] = 0;\\n this._texture_data[stride + 2] = 0;\\n } else {\\n if (value <= 1) {\\n this._texture_data[stride + 0] = TEXTURE_BYTES_MULT;\\n this._texture_data[stride + 1] = clamp(value, 0, 1) * TEXTURE_BYTES_MULT;\\n this._texture_data[stride + 2] = 0;\\n } else {\\n this._texture_data[stride + 0] = TEXTURE_BYTES_MULT;\\n this._texture_data[stride + 1] = TEXTURE_BYTES_MULT;\\n this._texture_data[stride + 2] = (clamp(value, 1, 2) - 1) * TEXTURE_BYTES_MULT;\\n }\\n }\\n }\\n }\\n static createInterpolant(positions, values) {\\n const valuesCount = 1;\\n const interpolatedValues = new Float32Array(valuesCount);\\n return new CubicInterpolant(positions, values, valuesCount, interpolatedValues);\\n }\\n interpolant() {\\n return this._ramp_interpolant = this._ramp_interpolant || this._createInterpolant();\\n }\\n _createInterpolant() {\\n const points2 = this.value.points();\\n const sortedPoints = ArrayUtils.sortBy(points2, (point) => point.position());\\n const positions = new Float32Array(sortedPoints.length);\\n const values = new Float32Array(sortedPoints.length);\\n let i = 0;\\n for (let sortedPoint of sortedPoints) {\\n positions[i] = sortedPoint.position();\\n values[i] = sortedPoint.value();\\n i++;\\n }\\n return RampParam2.createInterpolant(positions, values);\\n }\\n valueAtPosition(position) {\\n return this.interpolant().evaluate(position)[0];\\n }\\n};\\nvar RampParam = RampParam2;\\nRampParam.DEFAULT_VALUE = new RampValue(RampInterpolation.LINEAR, [new RampPoint(0, 0), new RampPoint(1, 1)]);\\nRampParam.DEFAULT_VALUE_JSON = RampParam2.DEFAULT_VALUE.toJSON();\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/String.ts\\nvar StringParam = class extends TypedParam {\\n static type() {\\n return ParamType.STRING;\\n }\\n defaultValueSerialized() {\\n return this._default_value;\\n }\\n _clone_raw_input(raw_input) {\\n return `${raw_input}`;\\n }\\n rawInputSerialized() {\\n return `${this._raw_input}`;\\n }\\n valueSerialized() {\\n return `${this.value}`;\\n }\\n _copy_value(param) {\\n this.set(param.value);\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n return raw_input1 == raw_input2;\\n }\\n static are_values_equal(val1, val2) {\\n return val1 == val2;\\n }\\n isDefault() {\\n return this._raw_input == this._default_value;\\n }\\n convert(raw_val) {\\n if (CoreType.isString(raw_val)) {\\n return raw_val;\\n }\\n return `${raw_val}`;\\n }\\n rawInput() {\\n return this._raw_input;\\n }\\n processRawInput() {\\n this.states.error.clear();\\n if (this._value_elements(this._raw_input).length >= 3) {\\n this._expression_controller = this._expression_controller || new ExpressionController(this);\\n if (this._raw_input != this._expression_controller.expression()) {\\n this._expression_controller.set_expression(this._raw_input);\\n this.setDirty();\\n this.emitController.emit(ParamEvent.EXPRESSION_UPDATED);\\n }\\n } else {\\n if (this._raw_input != this._value) {\\n this._value = this._raw_input;\\n this.removeDirtyState();\\n this.setSuccessorsDirty(this);\\n this.emitController.emit(ParamEvent.VALUE_UPDATED);\\n this.options.executeCallback();\\n if (this._expression_controller) {\\n this._expression_controller.set_expression(void 0, false);\\n this.emitController.emit(ParamEvent.EXPRESSION_UPDATED);\\n }\\n }\\n }\\n }\\n async processComputation() {\\n if (this.expressionController?.active() && !this.expressionController.requires_entities()) {\\n const expression_result = await this.expressionController.computeExpression();\\n if (this.expressionController.is_errored()) {\\n this.states.error.set(`expression error: ${this.expressionController.error_message()}`);\\n } else {\\n const converted = this.convert(expression_result);\\n if (converted != null) {\\n this._value = converted;\\n this.emitController.emit(ParamEvent.VALUE_UPDATED);\\n this.options.executeCallback();\\n } else {\\n this.states.error.set(`expression returns an invalid type (${expression_result})`);\\n }\\n this.removeDirtyState();\\n }\\n }\\n }\\n _value_elements(v) {\\n return ParsedTree.string_value_elements(v);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Vector2.ts\\nvar COMPONENT_NAMES_VECTOR2 = [\\\\\\\"x\\\\\\\", \\\\\\\"y\\\\\\\"];\\nvar Vector2Param = class extends TypedMultipleParam {\\n constructor() {\\n super(...arguments);\\n this._value = new Vector2();\\n this._copied_value = [0, 0];\\n }\\n static type() {\\n return ParamType.VECTOR2;\\n }\\n componentNames() {\\n return COMPONENT_NAMES_VECTOR2;\\n }\\n defaultValueSerialized() {\\n if (CoreType.isArray(this._default_value)) {\\n return this._default_value;\\n } else {\\n return this._default_value.toArray();\\n }\\n }\\n valueSerialized() {\\n return this.value.toArray();\\n }\\n _copy_value(param) {\\n param.value.toArray(this._copied_value);\\n this.set(this._copied_value);\\n }\\n _clone_raw_input(raw_input) {\\n if (raw_input instanceof Vector2) {\\n return raw_input.clone();\\n } else {\\n const new_array = [raw_input[0], raw_input[1]];\\n if (new_array[0] == null) {\\n new_array[0] = new_array[0] || 0;\\n }\\n if (new_array[1] == null) {\\n new_array[1] = new_array[1] || new_array[0];\\n }\\n return new_array;\\n }\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n if (raw_input1 instanceof Vector2) {\\n if (raw_input2 instanceof Vector2) {\\n return raw_input1.equals(raw_input2);\\n } else {\\n return raw_input1.x == raw_input2[0] && raw_input1.y == raw_input2[1];\\n }\\n } else {\\n if (raw_input2 instanceof Vector2) {\\n return raw_input1[0] == raw_input2.x && raw_input1[1] == raw_input2.y;\\n } else {\\n return raw_input1[0] == raw_input2[0] && raw_input1[1] == raw_input2[1];\\n }\\n }\\n }\\n static are_values_equal(val1, val2) {\\n return val1.equals(val2);\\n }\\n initComponents() {\\n super.initComponents();\\n this.x = this.components[0];\\n this.y = this.components[1];\\n }\\n set_value_from_components() {\\n this._value.x = this.x.value;\\n this._value.y = this.y.value;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Vector3.ts\\nvar COMPONENT_NAMES_VECTOR3 = [\\\\\\\"x\\\\\\\", \\\\\\\"y\\\\\\\", \\\\\\\"z\\\\\\\"];\\nvar Vector3Param = class extends TypedMultipleParam {\\n constructor() {\\n super(...arguments);\\n this._value = new Vector3();\\n this._copied_value = [0, 0, 0];\\n }\\n static type() {\\n return ParamType.VECTOR3;\\n }\\n componentNames() {\\n return COMPONENT_NAMES_VECTOR3;\\n }\\n defaultValueSerialized() {\\n if (CoreType.isArray(this._default_value)) {\\n return this._default_value;\\n } else {\\n return this._default_value.toArray();\\n }\\n }\\n valueSerialized() {\\n return this.value.toArray();\\n }\\n _copy_value(param) {\\n param.value.toArray(this._copied_value);\\n this.set(this._copied_value);\\n }\\n _clone_raw_input(raw_input) {\\n if (raw_input instanceof Vector3) {\\n return raw_input.clone();\\n } else {\\n const new_array = [raw_input[0], raw_input[1], raw_input[2]];\\n if (new_array[0] == null) {\\n new_array[0] = new_array[0] || 0;\\n }\\n if (new_array[1] == null) {\\n new_array[1] = new_array[1] || new_array[0];\\n }\\n if (new_array[2] == null) {\\n new_array[2] = new_array[2] || new_array[1];\\n }\\n return new_array;\\n }\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n if (raw_input1 instanceof Vector3) {\\n if (raw_input2 instanceof Vector3) {\\n return raw_input1.equals(raw_input2);\\n } else {\\n return raw_input1.x == raw_input2[0] && raw_input1.y == raw_input2[1] && raw_input1.z == raw_input2[2];\\n }\\n } else {\\n if (raw_input2 instanceof Vector3) {\\n return raw_input1[0] == raw_input2.x && raw_input1[1] == raw_input2.y && raw_input1[2] == raw_input2.z;\\n } else {\\n return raw_input1[0] == raw_input2[0] && raw_input1[1] == raw_input2[1] && raw_input1[2] == raw_input2[2];\\n }\\n }\\n }\\n static are_values_equal(val1, val2) {\\n return val1.equals(val2);\\n }\\n initComponents() {\\n super.initComponents();\\n this.x = this.components[0];\\n this.y = this.components[1];\\n this.z = this.components[2];\\n }\\n set_value_from_components() {\\n this._value.x = this.x.value;\\n this._value.y = this.y.value;\\n this._value.z = this.z.value;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/Vector4.ts\\nvar COMPONENT_NAMES_VECTOR4 = [\\\\\\\"x\\\\\\\", \\\\\\\"y\\\\\\\", \\\\\\\"z\\\\\\\", \\\\\\\"w\\\\\\\"];\\nvar Vector4Param = class extends TypedMultipleParam {\\n constructor() {\\n super(...arguments);\\n this._value = new Vector4();\\n this._copied_value = [0, 0, 0, 0];\\n }\\n static type() {\\n return ParamType.VECTOR4;\\n }\\n componentNames() {\\n return COMPONENT_NAMES_VECTOR4;\\n }\\n defaultValueSerialized() {\\n if (CoreType.isArray(this._default_value)) {\\n return this._default_value;\\n } else {\\n return this._default_value.toArray();\\n }\\n }\\n valueSerialized() {\\n return this.value.toArray();\\n }\\n _copy_value(param) {\\n param.value.toArray(this._copied_value);\\n this.set(this._copied_value);\\n }\\n _clone_raw_input(raw_input) {\\n if (raw_input instanceof Vector4) {\\n return raw_input.clone();\\n } else {\\n const new_array = [raw_input[0], raw_input[1], raw_input[2], raw_input[3]];\\n if (new_array[0] == null) {\\n new_array[0] = new_array[0] || 0;\\n }\\n if (new_array[1] == null) {\\n new_array[1] = new_array[1] || new_array[0];\\n }\\n if (new_array[2] == null) {\\n new_array[2] = new_array[2] || new_array[1];\\n }\\n if (new_array[3] == null) {\\n new_array[3] = new_array[3] || new_array[2];\\n }\\n return new_array;\\n }\\n }\\n static are_raw_input_equal(raw_input1, raw_input2) {\\n if (raw_input1 instanceof Vector4) {\\n if (raw_input2 instanceof Vector4) {\\n return raw_input1.equals(raw_input2);\\n } else {\\n return raw_input1.x == raw_input2[0] && raw_input1.y == raw_input2[1] && raw_input1.z == raw_input2[2] && raw_input1.w == raw_input2[3];\\n }\\n } else {\\n if (raw_input2 instanceof Vector4) {\\n return raw_input1[0] == raw_input2.x && raw_input1[1] == raw_input2.y && raw_input1[2] == raw_input2.z && raw_input1[3] == raw_input2.w;\\n } else {\\n return raw_input1[0] == raw_input2[0] && raw_input1[1] == raw_input2[1] && raw_input1[2] == raw_input2[2] && raw_input1[3] == raw_input2[3];\\n }\\n }\\n }\\n static are_values_equal(val1, val2) {\\n return val1.equals(val2);\\n }\\n initComponents() {\\n super.initComponents();\\n this.x = this.components[0];\\n this.y = this.components[1];\\n this.z = this.components[2];\\n this.w = this.components[3];\\n }\\n set_value_from_components() {\\n this._value.x = this.x.value;\\n this._value.y = this.y.value;\\n this._value.z = this.z.value;\\n this._value.w = this.w.value;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/params/types/ParamConstructorByType.ts\\nvar ParamConstructorByType = {\\n [ParamType.BOOLEAN]: BooleanParam,\\n [ParamType.BUTTON]: ButtonParam,\\n [ParamType.COLOR]: ColorParam,\\n [ParamType.FLOAT]: FloatParam,\\n [ParamType.FOLDER]: FolderParam,\\n [ParamType.INTEGER]: IntegerParam,\\n [ParamType.OPERATOR_PATH]: OperatorPathParam,\\n [ParamType.PARAM_PATH]: ParamPathParam,\\n [ParamType.NODE_PATH]: NodePathParam,\\n [ParamType.RAMP]: RampParam,\\n [ParamType.STRING]: StringParam,\\n [ParamType.VECTOR2]: Vector2Param,\\n [ParamType.VECTOR3]: Vector3Param,\\n [ParamType.VECTOR4]: Vector4Param\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/params/ParamsLabelController.ts\\nvar ParamsLabelController = class {\\n dispose() {\\n this._callback = void 0;\\n }\\n params() {\\n return this._params;\\n }\\n callback() {\\n return this._callback;\\n }\\n init(params, callback) {\\n this._params = params;\\n if (callback) {\\n this._callback = callback;\\n } else {\\n const param = this._params[0];\\n switch (param.type()) {\\n case ParamType.STRING:\\n return this._handle_string_param(param);\\n case ParamType.OPERATOR_PATH:\\n return this._handle_operator_path_param(param);\\n case ParamType.NODE_PATH:\\n return this._handle_node_path_param(param);\\n case ParamType.PARAM_PATH:\\n return this._handle_param_path_param(param);\\n case ParamType.FLOAT:\\n return this._handle_number_param(param);\\n case ParamType.INTEGER:\\n return this._handle_number_param(param);\\n }\\n }\\n }\\n _handle_string_param(param) {\\n this._callback = () => {\\n return param.value;\\n };\\n }\\n _handle_operator_path_param(param) {\\n this._callback = () => {\\n return param.value;\\n };\\n }\\n _handle_node_path_param(param) {\\n this._callback = () => {\\n return param.value.path();\\n };\\n }\\n _handle_param_path_param(param) {\\n this._callback = () => {\\n return param.value.path();\\n };\\n }\\n _handle_number_param(param) {\\n this._callback = () => {\\n return `${param.value}`;\\n };\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/params/ParamsController.ts\\nvar NODE_SIMPLE_NAME = \\\\\\\"params\\\\\\\";\\nvar ParamsController = class {\\n constructor(node) {\\n this.node = node;\\n this._param_create_mode = false;\\n this._params_created = false;\\n this._params_by_name = {};\\n this._params_list = [];\\n this._param_names = [];\\n this._non_spare_params = [];\\n this._spare_params = [];\\n this._non_spare_param_names = [];\\n this._spare_param_names = [];\\n this._params_added_since_last_params_eval = false;\\n }\\n get label() {\\n return this._label_controller = this._label_controller || new ParamsLabelController();\\n }\\n hasLabelController() {\\n return this._label_controller != null;\\n }\\n dispose() {\\n if (this._params_node) {\\n this._params_node.dispose();\\n }\\n for (let param of this.all) {\\n param.dispose();\\n }\\n this._post_create_params_hook_names = void 0;\\n this._post_create_params_hooks = void 0;\\n this._on_scene_load_hooks = void 0;\\n this._on_scene_load_hook_names = void 0;\\n this._label_controller?.dispose();\\n }\\n initDependencyNode() {\\n if (!this._params_node) {\\n this._params_node = new CoreGraphNode(this.node.scene(), NODE_SIMPLE_NAME);\\n this.node.addGraphInput(this._params_node, false);\\n }\\n }\\n init() {\\n this.initDependencyNode();\\n this._param_create_mode = true;\\n this._initFromParamsConfig();\\n this.node.createParams();\\n this._postCreateParams();\\n }\\n _postCreateParams() {\\n this._updateCaches();\\n this._initParamAccessors();\\n this._param_create_mode = false;\\n this._params_created = true;\\n this._runPostCreateParamsHooks();\\n }\\n postCreateSpareParams() {\\n this._updateCaches();\\n this._initParamAccessors();\\n this.node.scene().referencesController.notifyParamsUpdated(this.node);\\n this.node.emit(NodeEvent.PARAMS_UPDATED);\\n }\\n updateParams(options) {\\n let has_created_a_param = false;\\n let has_deleted_a_param = false;\\n if (options.namesToDelete) {\\n for (let param_name of options.namesToDelete) {\\n if (this.has(param_name)) {\\n this._deleteParam(param_name);\\n has_deleted_a_param = true;\\n }\\n }\\n }\\n if (options.toAdd) {\\n for (let param_data of options.toAdd) {\\n const param = this.addParam(param_data.type, param_data.name, param_data.init_value, param_data.options);\\n if (param) {\\n if (param_data.raw_input != null) {\\n param.set(param_data.raw_input);\\n }\\n has_created_a_param = true;\\n }\\n }\\n }\\n if (has_deleted_a_param || has_created_a_param) {\\n this.postCreateSpareParams();\\n }\\n }\\n _initFromParamsConfig() {\\n const paramsConfig = this.node.paramsConfig;\\n let init_values_used = false;\\n if (paramsConfig) {\\n for (let name of Object.keys(paramsConfig)) {\\n const config = paramsConfig[name];\\n let init_value;\\n if (this.node.params_init_value_overrides) {\\n init_value = this.node.params_init_value_overrides[name];\\n init_values_used = true;\\n }\\n this.addParam(config.type, name, config.init_value, config.options, init_value);\\n }\\n }\\n if (init_values_used) {\\n this.node.setDirty();\\n }\\n this.node.params_init_value_overrides = void 0;\\n }\\n _initParamAccessors() {\\n let current_names_in_accessor = Object.getOwnPropertyNames(this.node.pv);\\n this._removeUnneededAccessors(current_names_in_accessor);\\n current_names_in_accessor = Object.getOwnPropertyNames(this.node.pv);\\n for (let param of this.all) {\\n const is_spare = param.options.isSpare();\\n const param_not_yet_in_accessors = !current_names_in_accessor.includes(param.name());\\n if (param_not_yet_in_accessors || is_spare) {\\n Object.defineProperty(this.node.pv, param.name(), {\\n get: () => {\\n return param.value;\\n },\\n configurable: is_spare\\n });\\n Object.defineProperty(this.node.p, param.name(), {\\n get: () => {\\n return param;\\n },\\n configurable: is_spare\\n });\\n }\\n }\\n }\\n _removeUnneededAccessors(current_names_in_accessor) {\\n const current_param_names = this._param_names;\\n const names_to_remove = [];\\n for (let current_name_in_accessor of current_names_in_accessor) {\\n if (!current_param_names.includes(current_name_in_accessor)) {\\n names_to_remove.push(current_name_in_accessor);\\n }\\n }\\n for (let name_to_remove of names_to_remove) {\\n Object.defineProperty(this.node.pv, name_to_remove, {\\n get: () => {\\n return void 0;\\n },\\n configurable: true\\n });\\n Object.defineProperty(this.node.p, name_to_remove, {\\n get: () => {\\n return void 0;\\n },\\n configurable: true\\n });\\n }\\n }\\n get params_node() {\\n return this._params_node;\\n }\\n get all() {\\n return this._params_list;\\n }\\n get non_spare() {\\n return this._non_spare_params;\\n }\\n get spare() {\\n return this._spare_params;\\n }\\n get names() {\\n return this._param_names;\\n }\\n get non_spare_names() {\\n return this._non_spare_param_names;\\n }\\n get spare_names() {\\n return this._spare_param_names;\\n }\\n set_with_type(param_name, value, type) {\\n const param = this.param_with_type(param_name, type);\\n if (param) {\\n param.set(value);\\n } else {\\n Poly.warn(`param ${param_name} not found with type ${type}`);\\n }\\n }\\n set_float(param_name, value) {\\n this.set_with_type(param_name, value, ParamType.FLOAT);\\n }\\n set_vector3(param_name, value) {\\n this.set_with_type(param_name, value, ParamType.VECTOR3);\\n }\\n has_param(param_name) {\\n return this._params_by_name[param_name] != null;\\n }\\n has(param_name) {\\n return this.has_param(param_name);\\n }\\n get(param_name) {\\n return this.param(param_name);\\n }\\n param_with_type(param_name, type) {\\n const param = this.param(param_name);\\n if (param && param.type() == type) {\\n return param;\\n }\\n }\\n get_float(param_name) {\\n return this.param_with_type(param_name, ParamType.FLOAT);\\n }\\n get_operator_path(param_name) {\\n return this.param_with_type(param_name, ParamType.OPERATOR_PATH);\\n }\\n value(param_name) {\\n return this.param(param_name)?.value;\\n }\\n value_with_type(param_name, type) {\\n return this.param_with_type(param_name, type)?.value;\\n }\\n boolean(param_name) {\\n return this.value_with_type(param_name, ParamType.BOOLEAN);\\n }\\n float(param_name) {\\n return this.value_with_type(param_name, ParamType.FLOAT);\\n }\\n integer(param_name) {\\n return this.value_with_type(param_name, ParamType.INTEGER);\\n }\\n string(param_name) {\\n return this.value_with_type(param_name, ParamType.STRING);\\n }\\n vector2(param_name) {\\n return this.value_with_type(param_name, ParamType.VECTOR2);\\n }\\n vector3(param_name) {\\n return this.value_with_type(param_name, ParamType.VECTOR3);\\n }\\n color(param_name) {\\n return this.value_with_type(param_name, ParamType.COLOR);\\n }\\n param(param_name) {\\n const p = this._params_by_name[param_name];\\n if (p != null) {\\n return p;\\n } else {\\n Poly.warn(`tried to access param '${param_name}' in node ${this.node.path()}, but existing params are: ${this.names} on node ${this.node.path()}`);\\n return null;\\n }\\n }\\n _deleteParam(param_name) {\\n const param = this._params_by_name[param_name];\\n if (param) {\\n if (this._params_node) {\\n this._params_node.removeGraphInput(this._params_by_name[param_name]);\\n }\\n param._setupNodeDependencies(null);\\n delete this._params_by_name[param_name];\\n if (param.isMultiple() && param.components) {\\n for (let component of param.components) {\\n const child_name = component.name();\\n delete this._params_by_name[child_name];\\n }\\n }\\n } else {\\n throw new Error(`param '${param_name}' does not exist on node ${this.node.path()}`);\\n }\\n }\\n addParam(type, param_name, default_value, options = {}, init_data) {\\n const is_spare = options[\\\\\\\"spare\\\\\\\"] || false;\\n if (this._param_create_mode === false && !is_spare) {\\n Poly.warn(`node ${this.node.path()} (${this.node.type()}) param '${param_name}' cannot be created outside of create_params`);\\n }\\n if (this.node.scene() == null) {\\n Poly.warn(`node ${this.node.path()} (${this.node.type()}) has no scene assigned`);\\n }\\n const constructor = ParamConstructorByType[type];\\n if (constructor != null) {\\n const existing_param = this._params_by_name[param_name];\\n if (existing_param) {\\n if (is_spare) {\\n if (existing_param.type() != type) {\\n this._deleteParam(existing_param.name());\\n }\\n } else {\\n Poly.warn(`a param named ${param_name} already exists`, this.node);\\n }\\n }\\n const param = new constructor(this.node.scene(), this.node);\\n param.options.set(options);\\n param.setName(param_name);\\n param.setInitValue(default_value);\\n param.initComponents();\\n if (init_data == null) {\\n param.set(default_value);\\n } else {\\n if (param.options.isExpressionForEntities()) {\\n param.set(default_value);\\n }\\n if (init_data.raw_input != null) {\\n param.set(init_data.raw_input);\\n } else {\\n if (init_data.simple_data != null) {\\n param.set(init_data.simple_data);\\n } else {\\n if (init_data.complex_data != null) {\\n const raw_input = init_data.complex_data.raw_input;\\n if (raw_input) {\\n param.set(raw_input);\\n } else {\\n param.set(default_value);\\n }\\n const overriden_options = init_data.complex_data.overriden_options;\\n if (overriden_options != null) {\\n const keys = Object.keys(overriden_options);\\n for (let key of keys) {\\n param.options.setOption(key, overriden_options[key]);\\n }\\n }\\n }\\n }\\n }\\n }\\n param._setupNodeDependencies(this.node);\\n this._params_by_name[param.name()] = param;\\n if (param.isMultiple() && param.components) {\\n for (let component of param.components) {\\n this._params_by_name[component.name()] = component;\\n }\\n }\\n this._params_added_since_last_params_eval = true;\\n return param;\\n }\\n }\\n _updateCaches() {\\n this._params_list = Object.values(this._params_by_name);\\n this._param_names = Object.keys(this._params_by_name);\\n this._non_spare_params = Object.values(this._params_by_name).filter((p) => !p.options.isSpare());\\n this._spare_params = Object.values(this._params_by_name).filter((p) => p.options.isSpare());\\n this._non_spare_param_names = Object.values(this._params_by_name).filter((p) => !p.options.isSpare()).map((p) => p.name());\\n this._spare_param_names = Object.values(this._params_by_name).filter((p) => p.options.isSpare()).map((p) => p.name());\\n }\\n async _evalParam(param) {\\n if (param.isDirty()) {\\n await param.compute();\\n if (param.states.error.active()) {\\n this.node.states.error.set(`param '${param.name()}' error: ${param.states.error.message()}`);\\n }\\n } else {\\n }\\n }\\n async evalParams(params) {\\n const promises = [];\\n for (let param of params) {\\n if (param.isDirty()) {\\n promises.push(this._evalParam(param));\\n }\\n }\\n await Promise.all(promises);\\n if (this.node.states.error.active()) {\\n this.node._setContainer(null);\\n }\\n }\\n paramsEvalRequired() {\\n return this._params_node != null && (this._params_node.isDirty() || this._params_added_since_last_params_eval);\\n }\\n async evalAll() {\\n if (this.paramsEvalRequired()) {\\n await this.evalParams(this._params_list);\\n this._params_node?.removeDirtyState();\\n this._params_added_since_last_params_eval = false;\\n }\\n }\\n onParamsCreated(hook_name, hook) {\\n if (this._params_created) {\\n hook();\\n } else {\\n if (this._post_create_params_hook_names && this._post_create_params_hook_names.includes(hook_name)) {\\n Poly.error(`hook name ${hook_name} already exists`);\\n return;\\n }\\n this._post_create_params_hook_names = this._post_create_params_hook_names || [];\\n this._post_create_params_hook_names.push(hook_name);\\n this._post_create_params_hooks = this._post_create_params_hooks || [];\\n this._post_create_params_hooks.push(hook);\\n }\\n }\\n addOnSceneLoadHook(param_name, method) {\\n this._on_scene_load_hook_names = this._on_scene_load_hook_names || [];\\n this._on_scene_load_hooks = this._on_scene_load_hooks || [];\\n if (!this._on_scene_load_hook_names.includes(param_name)) {\\n this._on_scene_load_hook_names.push(param_name);\\n this._on_scene_load_hooks.push(method);\\n } else {\\n Poly.warn(`hook with name ${param_name} already exists`, this.node);\\n }\\n }\\n _runPostCreateParamsHooks() {\\n if (this._post_create_params_hooks) {\\n for (let hook of this._post_create_params_hooks) {\\n hook();\\n }\\n }\\n }\\n runOnSceneLoadHooks() {\\n if (this._on_scene_load_hooks) {\\n for (let hook of this._on_scene_load_hooks) {\\n hook();\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/params/ParamsValueAccessor.ts\\nvar ParamsValueAccessor = class {\\n constructor() {\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/NodeConnection.ts\\nvar TypedNodeConnection2 = class {\\n constructor(_node_src, _node_dest, _output_index = 0, _input_index = 0) {\\n this._node_src = _node_src;\\n this._node_dest = _node_dest;\\n this._output_index = _output_index;\\n this._input_index = _input_index;\\n if (this._output_index == null) {\\n throw \\\\\\\"bad output index\\\\\\\";\\n }\\n if (this._input_index == null) {\\n throw \\\\\\\"bad input index\\\\\\\";\\n }\\n this._id = TypedNodeConnection2._next_id++;\\n if (this._node_src.io.connections && this._node_dest.io.connections) {\\n this._node_src.io.connections.addOutputConnection(this);\\n this._node_dest.io.connections.addInputConnection(this);\\n }\\n }\\n get id() {\\n return this._id;\\n }\\n get node_src() {\\n return this._node_src;\\n }\\n get node_dest() {\\n return this._node_dest;\\n }\\n get output_index() {\\n return this._output_index;\\n }\\n get input_index() {\\n return this._input_index;\\n }\\n src_connection_point() {\\n const node_src = this._node_src;\\n const output_index = this._output_index;\\n return node_src.io.outputs.namedOutputConnectionPoints()[output_index];\\n }\\n dest_connection_point() {\\n const node_dest = this._node_dest;\\n const input_index = this._input_index;\\n return node_dest.io.inputs.namedInputConnectionPoints()[input_index];\\n }\\n disconnect(options = {}) {\\n if (this._node_src.io.connections && this._node_dest.io.connections) {\\n this._node_src.io.connections.removeOutputConnection(this);\\n this._node_dest.io.connections.removeInputConnection(this);\\n }\\n if (options.setInput === true) {\\n this._node_dest.io.inputs.setInput(this._input_index, null);\\n }\\n }\\n};\\nvar TypedNodeConnection = TypedNodeConnection2;\\nTypedNodeConnection._next_id = 0;\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/utils/ClonedStatesController.ts\\nvar ClonedStatesController2 = class {\\n constructor(inputs_controller) {\\n this.inputs_controller = inputs_controller;\\n this._clone_required_states = [];\\n this._overridden = false;\\n this.node = inputs_controller.node;\\n }\\n initInputsClonedState(states) {\\n if (CoreType.isArray(states)) {\\n this._cloned_states = states;\\n } else {\\n this._cloned_state = states;\\n }\\n this._update_clone_required_state();\\n }\\n overrideClonedStateAllowed() {\\n if (this._cloned_states) {\\n for (let state of this._cloned_states) {\\n if (state == InputCloneMode.FROM_NODE) {\\n return true;\\n }\\n }\\n }\\n if (this._cloned_state) {\\n return this._cloned_state == InputCloneMode.FROM_NODE;\\n }\\n return false;\\n }\\n cloneRequiredState(index) {\\n return this._clone_required_states[index];\\n }\\n cloneRequiredStates() {\\n return this._clone_required_states;\\n }\\n _get_clone_required_state(index) {\\n const states = this._cloned_states;\\n if (states) {\\n const state = states[index];\\n if (state != null) {\\n return this.clone_required_from_state(state);\\n }\\n }\\n if (this._cloned_state) {\\n return this.clone_required_from_state(this._cloned_state);\\n }\\n return true;\\n }\\n clone_required_from_state(state) {\\n switch (state) {\\n case InputCloneMode.ALWAYS:\\n return true;\\n case InputCloneMode.NEVER:\\n return false;\\n case InputCloneMode.FROM_NODE:\\n return !this._overridden;\\n }\\n return TypeAssert.unreachable(state);\\n }\\n overrideClonedState(state) {\\n this._overridden = state;\\n this._update_clone_required_state();\\n this.node.emit(NodeEvent.OVERRIDE_CLONABLE_STATE_UPDATE);\\n this.node.setDirty();\\n }\\n overriden() {\\n return this._overridden;\\n }\\n _update_clone_required_state() {\\n if (this._cloned_states) {\\n const states = [];\\n for (let i = 0; i < this._cloned_states.length; i++) {\\n states[i] = this._get_clone_required_state(i);\\n }\\n this._clone_required_states = states;\\n return;\\n }\\n if (this._cloned_state) {\\n const max_inputs = this.inputs_controller.maxInputsCount();\\n const states = [];\\n for (let i = 0; i < max_inputs; i++) {\\n states[i] = this._get_clone_required_state(i);\\n }\\n this._clone_required_states = states;\\n return;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/InputsController.ts\\nvar MAX_INPUTS_COUNT_UNSET = 0;\\nvar InputsController2 = class {\\n constructor(node) {\\n this.node = node;\\n this._graph_node_inputs = [];\\n this._inputs = [];\\n this._has_named_inputs = false;\\n this._minInputsCount = 0;\\n this._maxInputsCount = MAX_INPUTS_COUNT_UNSET;\\n this._maxInputsCountOnInput = MAX_INPUTS_COUNT_UNSET;\\n this._depends_on_inputs = true;\\n }\\n dispose() {\\n if (this._graph_node) {\\n this._graph_node.dispose();\\n }\\n for (let graph_node of this._graph_node_inputs) {\\n if (graph_node) {\\n graph_node.dispose();\\n }\\n }\\n this._on_update_hooks = void 0;\\n this._on_update_hook_names = void 0;\\n }\\n set_depends_on_inputs(depends_on_inputs) {\\n this._depends_on_inputs = depends_on_inputs;\\n }\\n setMinCount(minInputsCount) {\\n this._minInputsCount = minInputsCount;\\n }\\n minCount() {\\n return this._minInputsCount;\\n }\\n setMaxCount(maxInputsCount) {\\n if (this._maxInputsCount == MAX_INPUTS_COUNT_UNSET) {\\n this._maxInputsCountOnInput = maxInputsCount;\\n }\\n this._maxInputsCount = maxInputsCount;\\n this._initGraphNodeInputs();\\n }\\n namedInputConnectionPointsByName(name) {\\n if (this._named_input_connection_points) {\\n for (let connection_point of this._named_input_connection_points) {\\n if (connection_point && connection_point.name() == name) {\\n return connection_point;\\n }\\n }\\n }\\n }\\n setNamedInputConnectionPoints(connection_points) {\\n this._has_named_inputs = true;\\n const connections = this.node.io.connections.inputConnections();\\n if (connections) {\\n for (let connection of connections) {\\n if (connection) {\\n if (connection.input_index >= connection_points.length) {\\n connection.disconnect({setInput: true});\\n }\\n }\\n }\\n }\\n this._named_input_connection_points = connection_points;\\n this.setMinCount(0);\\n this.setMaxCount(connection_points.length);\\n this._initGraphNodeInputs();\\n this.node.emit(NodeEvent.NAMED_INPUTS_UPDATED);\\n }\\n hasNamedInputs() {\\n return this._has_named_inputs;\\n }\\n namedInputConnectionPoints() {\\n return this._named_input_connection_points || [];\\n }\\n _initGraphNodeInputs() {\\n for (let i = 0; i < this._maxInputsCount; i++) {\\n this._graph_node_inputs[i] = this._graph_node_inputs[i] || this._createGraphNodeInput(i);\\n }\\n }\\n _createGraphNodeInput(index) {\\n const graph_input_node = new CoreGraphNode(this.node.scene(), `input_${index}`);\\n if (!this._graph_node) {\\n this._graph_node = new CoreGraphNode(this.node.scene(), \\\\\\\"inputs\\\\\\\");\\n this.node.addGraphInput(this._graph_node, false);\\n }\\n this._graph_node.addGraphInput(graph_input_node, false);\\n return graph_input_node;\\n }\\n maxInputsCount() {\\n return this._maxInputsCount || 0;\\n }\\n maxInputsCountOverriden() {\\n return this._maxInputsCount != this._maxInputsCountOnInput;\\n }\\n inputGraphNode(input_index) {\\n return this._graph_node_inputs[input_index];\\n }\\n setCount(min, max) {\\n if (max == null) {\\n max = min;\\n }\\n this.setMinCount(min);\\n this.setMaxCount(max);\\n this._initConnectionControllerInputs();\\n }\\n _initConnectionControllerInputs() {\\n this.node.io.connections.initInputs();\\n }\\n is_any_input_dirty() {\\n return this._graph_node?.isDirty() || false;\\n }\\n async containers_without_evaluation() {\\n const containers = [];\\n for (let i = 0; i < this._inputs.length; i++) {\\n const input_node = this._inputs[i];\\n let container = void 0;\\n if (input_node) {\\n container = await input_node.compute();\\n }\\n containers.push(container);\\n }\\n return containers;\\n }\\n existing_input_indices() {\\n const existing_input_indices = [];\\n if (this._maxInputsCount > 0) {\\n for (let i = 0; i < this._inputs.length; i++) {\\n if (this._inputs[i]) {\\n existing_input_indices.push(i);\\n }\\n }\\n }\\n return existing_input_indices;\\n }\\n async eval_required_inputs() {\\n let containers = [];\\n if (this._maxInputsCount > 0) {\\n const existing_input_indices = this.existing_input_indices();\\n if (existing_input_indices.length < this._minInputsCount) {\\n this.node.states.error.set(\\\\\\\"inputs are missing\\\\\\\");\\n } else {\\n if (existing_input_indices.length > 0) {\\n const promises = [];\\n let input;\\n for (let i = 0; i < this._inputs.length; i++) {\\n input = this._inputs[i];\\n if (input) {\\n promises.push(this.eval_required_input(i));\\n }\\n }\\n containers = await Promise.all(promises);\\n this._graph_node?.removeDirtyState();\\n }\\n }\\n }\\n return containers;\\n }\\n async eval_required_input(input_index) {\\n let container = void 0;\\n const input_node = this.input(input_index);\\n if (input_node) {\\n container = await input_node.compute();\\n this._graph_node_inputs[input_index].removeDirtyState();\\n }\\n if (container && container.coreContent()) {\\n } else {\\n const input_node2 = this.input(input_index);\\n if (input_node2) {\\n const input_error_message = input_node2.states.error.message();\\n if (input_error_message) {\\n this.node.states.error.set(`input ${input_index} is invalid (error: ${input_error_message})`);\\n }\\n }\\n }\\n return container;\\n }\\n get_named_input_index(name) {\\n if (this._named_input_connection_points) {\\n for (let i = 0; i < this._named_input_connection_points.length; i++) {\\n if (this._named_input_connection_points[i]?.name() == name) {\\n return i;\\n }\\n }\\n }\\n return -1;\\n }\\n get_input_index(input_index_or_name) {\\n if (CoreType.isString(input_index_or_name)) {\\n if (this.hasNamedInputs()) {\\n return this.get_named_input_index(input_index_or_name);\\n } else {\\n throw new Error(`node ${this.node.path()} has no named inputs`);\\n }\\n } else {\\n return input_index_or_name;\\n }\\n }\\n setInput(input_index_or_name, node, output_index_or_name = 0) {\\n const input_index = this.get_input_index(input_index_or_name) || 0;\\n if (input_index < 0) {\\n const message = `invalid input (${input_index_or_name}) for node ${this.node.path()}`;\\n console.warn(message);\\n throw new Error(message);\\n }\\n let output_index = 0;\\n if (node) {\\n if (node.io.outputs.hasNamedOutputs()) {\\n output_index = node.io.outputs.getOutputIndex(output_index_or_name);\\n if (output_index == null || output_index < 0) {\\n const connection_points = node.io.outputs.namedOutputConnectionPoints();\\n const names = connection_points.map((cp) => cp.name());\\n console.warn(`node ${node.path()} does not have an output named ${output_index_or_name}. inputs are: ${names.join(\\\\\\\", \\\\\\\")}`);\\n return;\\n }\\n }\\n }\\n const graph_input_node = this._graph_node_inputs[input_index];\\n if (graph_input_node == null) {\\n const message = `graph_input_node not found at index ${input_index}`;\\n console.warn(message);\\n throw new Error(message);\\n }\\n if (node && this.node.parent() != node.parent()) {\\n return;\\n }\\n const old_input_node = this._inputs[input_index];\\n let old_output_index = null;\\n let old_connection = void 0;\\n if (this.node.io.connections) {\\n old_connection = this.node.io.connections.inputConnection(input_index);\\n }\\n if (old_connection) {\\n old_output_index = old_connection.output_index;\\n }\\n if (node !== old_input_node || output_index != old_output_index) {\\n if (old_input_node != null) {\\n if (this._depends_on_inputs) {\\n graph_input_node.removeGraphInput(old_input_node);\\n }\\n }\\n if (node != null) {\\n if (graph_input_node.addGraphInput(node)) {\\n if (!this._depends_on_inputs) {\\n graph_input_node.removeGraphInput(node);\\n }\\n if (old_connection) {\\n old_connection.disconnect({setInput: false});\\n }\\n this._inputs[input_index] = node;\\n new TypedNodeConnection(node, this.node, output_index, input_index);\\n } else {\\n console.warn(`cannot connect ${node.path()} to ${this.node.path()}`);\\n }\\n } else {\\n this._inputs[input_index] = null;\\n if (old_connection) {\\n old_connection.disconnect({setInput: false});\\n }\\n }\\n this._run_on_set_input_hooks();\\n graph_input_node.setSuccessorsDirty();\\n this.node.emit(NodeEvent.INPUTS_UPDATED);\\n }\\n }\\n remove_input(node) {\\n const inputs = this.inputs();\\n let input;\\n for (let i = 0; i < inputs.length; i++) {\\n input = inputs[i];\\n if (input != null && node != null) {\\n if (input.graphNodeId() === node.graphNodeId()) {\\n this.setInput(i, null);\\n }\\n }\\n }\\n }\\n input(input_index) {\\n return this._inputs[input_index];\\n }\\n named_input(input_name) {\\n if (this.hasNamedInputs()) {\\n const input_index = this.get_input_index(input_name);\\n return this._inputs[input_index];\\n } else {\\n return null;\\n }\\n }\\n named_input_connection_point(input_name) {\\n if (this.hasNamedInputs() && this._named_input_connection_points) {\\n const input_index = this.get_input_index(input_name);\\n return this._named_input_connection_points[input_index];\\n }\\n }\\n has_named_input(name) {\\n return this.get_named_input_index(name) >= 0;\\n }\\n has_input(input_index) {\\n return this._inputs[input_index] != null;\\n }\\n inputs() {\\n return this._inputs;\\n }\\n initInputsClonedState(states) {\\n if (!this._cloned_states_controller) {\\n this._cloned_states_controller = new ClonedStatesController2(this);\\n this._cloned_states_controller.initInputsClonedState(states);\\n }\\n }\\n overrideClonedStateAllowed() {\\n return this._cloned_states_controller?.overrideClonedStateAllowed() || false;\\n }\\n overrideClonedState(state) {\\n this._cloned_states_controller?.overrideClonedState(state);\\n }\\n clonedStateOverriden() {\\n return this._cloned_states_controller?.overriden() || false;\\n }\\n cloneRequired(index) {\\n const state = this._cloned_states_controller?.cloneRequiredState(index);\\n if (state != null) {\\n return state;\\n }\\n return true;\\n }\\n cloneRequiredStates() {\\n const states = this._cloned_states_controller?.cloneRequiredStates();\\n if (states != null) {\\n return states;\\n }\\n return true;\\n }\\n add_on_set_input_hook(name, hook) {\\n this._on_update_hooks = this._on_update_hooks || [];\\n this._on_update_hook_names = this._on_update_hook_names || [];\\n if (!this._on_update_hook_names.includes(name)) {\\n this._on_update_hooks.push(hook);\\n this._on_update_hook_names.push(name);\\n } else {\\n console.warn(`hook with name ${name} already exists`, this.node);\\n }\\n }\\n _run_on_set_input_hooks() {\\n if (this._on_update_hooks) {\\n for (let hook of this._on_update_hooks) {\\n hook();\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/OutputsController.ts\\nvar OutputsController = class {\\n constructor(node) {\\n this.node = node;\\n this._has_outputs = false;\\n this._has_named_outputs = false;\\n }\\n setHasOneOutput() {\\n this._has_outputs = true;\\n }\\n setHasNoOutput() {\\n this._has_outputs = false;\\n }\\n hasOutputs() {\\n return this._has_outputs;\\n }\\n hasNamedOutputs() {\\n return this._has_named_outputs;\\n }\\n hasNamedOutput(name) {\\n return this.getNamedOutputIndex(name) >= 0;\\n }\\n namedOutputConnectionPoints() {\\n return this._named_output_connection_points || [];\\n }\\n namedOutputConnection(index) {\\n if (this._named_output_connection_points) {\\n return this._named_output_connection_points[index];\\n }\\n }\\n getNamedOutputIndex(name) {\\n if (this._named_output_connection_points) {\\n for (let i = 0; i < this._named_output_connection_points.length; i++) {\\n if (this._named_output_connection_points[i]?.name() == name) {\\n return i;\\n }\\n }\\n }\\n return -1;\\n }\\n getOutputIndex(output_index_or_name) {\\n if (output_index_or_name != null) {\\n if (CoreType.isString(output_index_or_name)) {\\n if (this.hasNamedOutputs()) {\\n return this.getNamedOutputIndex(output_index_or_name);\\n } else {\\n console.warn(`node ${this.node.path()} has no named outputs`);\\n return -1;\\n }\\n } else {\\n return output_index_or_name;\\n }\\n }\\n return -1;\\n }\\n namedOutputConnectionPointsByName(name) {\\n if (this._named_output_connection_points) {\\n for (let connection_point of this._named_output_connection_points) {\\n if (connection_point?.name() == name) {\\n return connection_point;\\n }\\n }\\n }\\n }\\n setNamedOutputConnectionPoints(connection_points, set_dirty = true) {\\n this._has_named_outputs = true;\\n const connections = this.node.io.connections.outputConnections();\\n if (connections) {\\n for (let connection of connections) {\\n if (connection) {\\n if (connection.output_index >= connection_points.length) {\\n connection.disconnect({setInput: true});\\n }\\n }\\n }\\n }\\n this._named_output_connection_points = connection_points;\\n if (set_dirty && this.node.scene()) {\\n this.node.setDirty(this.node);\\n }\\n this.node.emit(NodeEvent.NAMED_OUTPUTS_UPDATED);\\n }\\n used_output_names() {\\n const connections_controller = this.node.io.connections;\\n if (connections_controller) {\\n const output_connections = connections_controller.outputConnections();\\n let output_indices = output_connections.map((connection) => connection ? connection.output_index : null);\\n output_indices = ArrayUtils.uniq(output_indices);\\n const used_output_indices = [];\\n output_indices.forEach((index) => {\\n if (CoreType.isNumber(index)) {\\n used_output_indices.push(index);\\n }\\n });\\n const used_output_names = [];\\n for (let index of used_output_indices) {\\n const name = this.namedOutputConnectionPoints()[index]?.name();\\n if (name) {\\n used_output_names.push(name);\\n }\\n }\\n return used_output_names;\\n } else {\\n return [];\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/ConnectionsController.ts\\nvar ConnectionsController = class {\\n constructor(_node) {\\n this._node = _node;\\n this._output_connections = new Map();\\n }\\n initInputs() {\\n const count = this._node.io.inputs.maxInputsCount();\\n this._input_connections = this._input_connections || new Array(count);\\n while (this._input_connections.length < count) {\\n this._input_connections.push(void 0);\\n }\\n }\\n addInputConnection(connection) {\\n if (this._input_connections) {\\n this._input_connections[connection.input_index] = connection;\\n } else {\\n console.warn(`input connections array not initialized`);\\n }\\n }\\n removeInputConnection(connection) {\\n if (this._input_connections) {\\n if (connection.input_index < this._input_connections.length) {\\n this._input_connections[connection.input_index] = void 0;\\n let all_connections_after_are_undefined = true;\\n for (let i = connection.input_index; i < this._input_connections.length; i++) {\\n if (this._input_connections[i]) {\\n all_connections_after_are_undefined = false;\\n }\\n }\\n if (all_connections_after_are_undefined) {\\n this._input_connections = this._input_connections.slice(0, connection.input_index);\\n }\\n } else {\\n console.warn(`attempt to remove an input connection at index ${connection.input_index}`);\\n }\\n } else {\\n console.warn(`input connections array not initialized`);\\n }\\n }\\n inputConnection(index) {\\n if (this._input_connections) {\\n return this._input_connections[index];\\n }\\n }\\n firstInputConnection() {\\n if (this._input_connections) {\\n return ArrayUtils.compact(this._input_connections)[0];\\n } else {\\n return null;\\n }\\n }\\n inputConnections() {\\n return this._input_connections;\\n }\\n existingInputConnections() {\\n const current_connections = this._input_connections;\\n if (current_connections) {\\n while (current_connections.length > 1 && current_connections[current_connections.length - 1] === void 0) {\\n current_connections.pop();\\n }\\n }\\n return current_connections;\\n }\\n addOutputConnection(connection) {\\n const output_index = connection.output_index;\\n const id = connection.id;\\n let connections_by_id = this._output_connections.get(output_index);\\n if (!connections_by_id) {\\n connections_by_id = new Map();\\n this._output_connections.set(output_index, connections_by_id);\\n }\\n connections_by_id.set(id, connection);\\n }\\n removeOutputConnection(connection) {\\n const output_index = connection.output_index;\\n const id = connection.id;\\n let connections_by_id = this._output_connections.get(output_index);\\n if (connections_by_id) {\\n connections_by_id.delete(id);\\n }\\n }\\n outputConnections() {\\n let list = [];\\n this._output_connections.forEach((connections_by_id, output_index) => {\\n connections_by_id.forEach((connection, id) => {\\n if (connection) {\\n list.push(connection);\\n }\\n });\\n });\\n return list;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/SavedConnectionPointsDataController.ts\\nvar SavedConnectionPointsDataController = class {\\n constructor(_node) {\\n this._node = _node;\\n }\\n set_in(data) {\\n this._in = data;\\n }\\n set_out(data) {\\n this._out = data;\\n }\\n clear() {\\n this._in = void 0;\\n this._out = void 0;\\n }\\n in() {\\n return this._in;\\n }\\n out() {\\n return this._out;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/connections/_Base.ts\\nvar BaseConnectionPoint = class {\\n constructor(_name, _type, _init_value) {\\n this._name = _name;\\n this._type = _type;\\n this._init_value = _init_value;\\n }\\n get init_value() {\\n return this._init_value;\\n }\\n name() {\\n return this._name;\\n }\\n type() {\\n return this._type;\\n }\\n are_types_matched(src_type, dest_type) {\\n return true;\\n }\\n toJSON() {\\n return this._json = this._json || this._create_json();\\n }\\n _create_json() {\\n return {\\n name: this._name,\\n type: this._type\\n };\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/connections/Gl.ts\\nvar GlConnectionPointType;\\n(function(GlConnectionPointType2) {\\n GlConnectionPointType2[\\\\\\\"BOOL\\\\\\\"] = \\\\\\\"bool\\\\\\\";\\n GlConnectionPointType2[\\\\\\\"INT\\\\\\\"] = \\\\\\\"int\\\\\\\";\\n GlConnectionPointType2[\\\\\\\"FLOAT\\\\\\\"] = \\\\\\\"float\\\\\\\";\\n GlConnectionPointType2[\\\\\\\"VEC2\\\\\\\"] = \\\\\\\"vec2\\\\\\\";\\n GlConnectionPointType2[\\\\\\\"VEC3\\\\\\\"] = \\\\\\\"vec3\\\\\\\";\\n GlConnectionPointType2[\\\\\\\"VEC4\\\\\\\"] = \\\\\\\"vec4\\\\\\\";\\n GlConnectionPointType2[\\\\\\\"SAMPLER_2D\\\\\\\"] = \\\\\\\"sampler2D\\\\\\\";\\n GlConnectionPointType2[\\\\\\\"SSS_MODEL\\\\\\\"] = \\\\\\\"SSSModel\\\\\\\";\\n})(GlConnectionPointType || (GlConnectionPointType = {}));\\nvar GL_CONNECTION_POINT_TYPES = [\\n GlConnectionPointType.BOOL,\\n GlConnectionPointType.INT,\\n GlConnectionPointType.FLOAT,\\n GlConnectionPointType.VEC2,\\n GlConnectionPointType.VEC3,\\n GlConnectionPointType.VEC4\\n];\\nvar GlConnectionPointTypeToParamTypeMap = {\\n [GlConnectionPointType.BOOL]: ParamType.BOOLEAN,\\n [GlConnectionPointType.INT]: ParamType.INTEGER,\\n [GlConnectionPointType.FLOAT]: ParamType.FLOAT,\\n [GlConnectionPointType.VEC2]: ParamType.VECTOR2,\\n [GlConnectionPointType.VEC3]: ParamType.VECTOR3,\\n [GlConnectionPointType.VEC4]: ParamType.VECTOR4,\\n [GlConnectionPointType.SAMPLER_2D]: ParamType.RAMP,\\n [GlConnectionPointType.SSS_MODEL]: ParamType.STRING\\n};\\nvar GLParamTypeToConnectionPointTypeMap = {\\n [ParamType.BOOLEAN]: GlConnectionPointType.BOOL,\\n [ParamType.COLOR]: GlConnectionPointType.VEC3,\\n [ParamType.INTEGER]: GlConnectionPointType.INT,\\n [ParamType.FLOAT]: GlConnectionPointType.FLOAT,\\n [ParamType.FOLDER]: void 0,\\n [ParamType.VECTOR2]: GlConnectionPointType.VEC2,\\n [ParamType.VECTOR3]: GlConnectionPointType.VEC3,\\n [ParamType.VECTOR4]: GlConnectionPointType.VEC4,\\n [ParamType.BUTTON]: void 0,\\n [ParamType.OPERATOR_PATH]: void 0,\\n [ParamType.PARAM_PATH]: void 0,\\n [ParamType.NODE_PATH]: void 0,\\n [ParamType.RAMP]: void 0,\\n [ParamType.STRING]: void 0\\n};\\nvar GlConnectionPointInitValueMap = {\\n [GlConnectionPointType.BOOL]: false,\\n [GlConnectionPointType.INT]: 0,\\n [GlConnectionPointType.FLOAT]: 0,\\n [GlConnectionPointType.VEC2]: [0, 0],\\n [GlConnectionPointType.VEC3]: [0, 0, 0],\\n [GlConnectionPointType.VEC4]: [0, 0, 0, 0],\\n [GlConnectionPointType.SAMPLER_2D]: RampParam.DEFAULT_VALUE_JSON,\\n [GlConnectionPointType.SSS_MODEL]: \\\\\\\"SSSModel()\\\\\\\"\\n};\\nvar GlConnectionPointComponentsCountMap = {\\n [GlConnectionPointType.BOOL]: 1,\\n [GlConnectionPointType.INT]: 1,\\n [GlConnectionPointType.FLOAT]: 1,\\n [GlConnectionPointType.VEC2]: 2,\\n [GlConnectionPointType.VEC3]: 3,\\n [GlConnectionPointType.VEC4]: 4,\\n [GlConnectionPointType.SAMPLER_2D]: 1,\\n [GlConnectionPointType.SSS_MODEL]: 1\\n};\\nvar GlConnectionPoint = class extends BaseConnectionPoint {\\n constructor(_name, _type, _init_value) {\\n super(_name, _type);\\n this._name = _name;\\n this._type = _type;\\n this._init_value = _init_value;\\n this._init_value = this._init_value || GlConnectionPointInitValueMap[this._type];\\n }\\n type() {\\n return this._type;\\n }\\n are_types_matched(src_type, dest_type) {\\n return src_type == dest_type;\\n }\\n get param_type() {\\n return GlConnectionPointTypeToParamTypeMap[this._type];\\n }\\n get init_value() {\\n return this._init_value;\\n }\\n toJSON() {\\n return this._json = this._json || this._create_json();\\n }\\n _create_json() {\\n return {\\n name: this._name,\\n type: this._type\\n };\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/connections/Js.ts\\nvar JsConnectionPointType;\\n(function(JsConnectionPointType2) {\\n JsConnectionPointType2[\\\\\\\"BOOL\\\\\\\"] = \\\\\\\"bool\\\\\\\";\\n JsConnectionPointType2[\\\\\\\"INT\\\\\\\"] = \\\\\\\"int\\\\\\\";\\n JsConnectionPointType2[\\\\\\\"FLOAT\\\\\\\"] = \\\\\\\"float\\\\\\\";\\n JsConnectionPointType2[\\\\\\\"VEC2\\\\\\\"] = \\\\\\\"vec2\\\\\\\";\\n JsConnectionPointType2[\\\\\\\"VEC3\\\\\\\"] = \\\\\\\"vec3\\\\\\\";\\n JsConnectionPointType2[\\\\\\\"VEC4\\\\\\\"] = \\\\\\\"vec4\\\\\\\";\\n})(JsConnectionPointType || (JsConnectionPointType = {}));\\nvar JS_CONNECTION_POINT_TYPES = [\\n JsConnectionPointType.BOOL,\\n JsConnectionPointType.INT,\\n JsConnectionPointType.FLOAT,\\n JsConnectionPointType.VEC2,\\n JsConnectionPointType.VEC3,\\n JsConnectionPointType.VEC4\\n];\\nvar JsConnectionPointTypeToParamTypeMap = {\\n [JsConnectionPointType.BOOL]: ParamType.BOOLEAN,\\n [JsConnectionPointType.INT]: ParamType.INTEGER,\\n [JsConnectionPointType.FLOAT]: ParamType.FLOAT,\\n [JsConnectionPointType.VEC2]: ParamType.VECTOR2,\\n [JsConnectionPointType.VEC3]: ParamType.VECTOR3,\\n [JsConnectionPointType.VEC4]: ParamType.VECTOR4\\n};\\nvar JsParamTypeToConnectionPointTypeMap = {\\n [ParamType.BOOLEAN]: JsConnectionPointType.BOOL,\\n [ParamType.COLOR]: JsConnectionPointType.VEC3,\\n [ParamType.INTEGER]: JsConnectionPointType.INT,\\n [ParamType.FLOAT]: JsConnectionPointType.FLOAT,\\n [ParamType.FOLDER]: void 0,\\n [ParamType.VECTOR2]: JsConnectionPointType.VEC2,\\n [ParamType.VECTOR3]: JsConnectionPointType.VEC3,\\n [ParamType.VECTOR4]: JsConnectionPointType.VEC4,\\n [ParamType.BUTTON]: void 0,\\n [ParamType.OPERATOR_PATH]: void 0,\\n [ParamType.PARAM_PATH]: void 0,\\n [ParamType.NODE_PATH]: void 0,\\n [ParamType.RAMP]: void 0,\\n [ParamType.STRING]: void 0\\n};\\nvar JsConnectionPointInitValueMap = {\\n [JsConnectionPointType.BOOL]: false,\\n [JsConnectionPointType.INT]: 0,\\n [JsConnectionPointType.FLOAT]: 0,\\n [JsConnectionPointType.VEC2]: [0, 0],\\n [JsConnectionPointType.VEC3]: [0, 0, 0],\\n [JsConnectionPointType.VEC4]: [0, 0, 0, 0]\\n};\\nvar GlConnectionPointComponentsCountMap2 = {\\n [JsConnectionPointType.BOOL]: 1,\\n [JsConnectionPointType.INT]: 1,\\n [JsConnectionPointType.FLOAT]: 1,\\n [JsConnectionPointType.VEC2]: 2,\\n [JsConnectionPointType.VEC3]: 3,\\n [JsConnectionPointType.VEC4]: 4\\n};\\nvar JsConnectionPoint = class extends BaseConnectionPoint {\\n constructor(_name, _type) {\\n super(_name, _type);\\n this._name = _name;\\n this._type = _type;\\n this._init_value = JsConnectionPointInitValueMap[this._type];\\n }\\n type() {\\n return this._type;\\n }\\n are_types_matched(src_type, dest_type) {\\n return src_type == dest_type;\\n }\\n get param_type() {\\n return JsConnectionPointTypeToParamTypeMap[this._type];\\n }\\n get init_value() {\\n return this._init_value;\\n }\\n toJSON() {\\n return this._json = this._json || this._create_json();\\n }\\n _create_json() {\\n return {\\n name: this._name,\\n type: this._type\\n };\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/connections/Event.ts\\nvar EventConnectionPointType;\\n(function(EventConnectionPointType2) {\\n EventConnectionPointType2[\\\\\\\"BASE\\\\\\\"] = \\\\\\\"base\\\\\\\";\\n EventConnectionPointType2[\\\\\\\"DRAG\\\\\\\"] = \\\\\\\"drag\\\\\\\";\\n EventConnectionPointType2[\\\\\\\"KEYBOARD\\\\\\\"] = \\\\\\\"keyboard\\\\\\\";\\n EventConnectionPointType2[\\\\\\\"MOUSE\\\\\\\"] = \\\\\\\"mouse\\\\\\\";\\n EventConnectionPointType2[\\\\\\\"POINTER\\\\\\\"] = \\\\\\\"pointer\\\\\\\";\\n})(EventConnectionPointType || (EventConnectionPointType = {}));\\nvar EventConnectionPoint = class extends BaseConnectionPoint {\\n constructor(_name, _type, _event_listener) {\\n super(_name, _type);\\n this._name = _name;\\n this._type = _type;\\n this._event_listener = _event_listener;\\n }\\n type() {\\n return this._type;\\n }\\n get param_type() {\\n return ParamType.FLOAT;\\n }\\n are_types_matched(src_type, dest_type) {\\n if (dest_type == EventConnectionPointType.BASE) {\\n return true;\\n } else {\\n return src_type == dest_type;\\n }\\n }\\n get event_listener() {\\n return this._event_listener;\\n }\\n toJSON() {\\n return this._json = this._json || this._create_json();\\n }\\n _create_json() {\\n return {\\n name: this._name,\\n type: this._type\\n };\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/connections/ConnectionMap.ts\\nvar DEFAULT_CONNECTION_POINT_ENUM_MAP = {\\n [NodeContext.ANIM]: void 0,\\n [NodeContext.COP]: void 0,\\n [NodeContext.EVENT]: EventConnectionPointType.BASE,\\n [NodeContext.GL]: GlConnectionPointType.FLOAT,\\n [NodeContext.JS]: JsConnectionPointType.FLOAT,\\n [NodeContext.MANAGER]: void 0,\\n [NodeContext.MAT]: void 0,\\n [NodeContext.OBJ]: void 0,\\n [NodeContext.POST]: void 0,\\n [NodeContext.ROP]: void 0,\\n [NodeContext.SOP]: void 0\\n};\\nfunction create_connection_point(context, name, type) {\\n switch (context) {\\n case NodeContext.EVENT: {\\n return new EventConnectionPoint(name, type);\\n }\\n case NodeContext.GL: {\\n return new GlConnectionPoint(name, type);\\n }\\n case NodeContext.JS: {\\n return new JsConnectionPoint(name, type);\\n }\\n default: {\\n return void 0;\\n }\\n }\\n}\\nfunction param_type_to_connection_point_type_map(context) {\\n switch (context) {\\n case NodeContext.EVENT: {\\n return void 0;\\n }\\n case NodeContext.GL: {\\n return GLParamTypeToConnectionPointTypeMap;\\n }\\n case NodeContext.JS: {\\n return JsParamTypeToConnectionPointTypeMap;\\n }\\n default: {\\n return void 0;\\n }\\n }\\n}\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/ConnectionPointsSpareParamsController.ts\\nvar ConnectionPointsSpareParamsController = class {\\n constructor(node, _context2) {\\n this.node = node;\\n this._context = _context2;\\n this._raw_input_serialized_by_param_name = new Map();\\n this._default_value_serialized_by_param_name = new Map();\\n this._initialized = false;\\n }\\n initializeNode() {\\n if (this._initialized) {\\n console.warn(\\\\\\\"already initialized\\\\\\\", this.node);\\n return;\\n }\\n this._initialized = true;\\n this.node.params.onParamsCreated(\\\\\\\"create_inputs_from_params\\\\\\\", this.create_inputs_from_params.bind(this));\\n }\\n initialized() {\\n return this._initialized;\\n }\\n create_inputs_from_params() {\\n const connection_type_map = param_type_to_connection_point_type_map(this._context);\\n if (!connection_type_map) {\\n return;\\n }\\n const connection_points = [];\\n for (let param_name of this.node.params.names) {\\n let add_input = true;\\n if (this._inputless_param_names && this._inputless_param_names.length > 0 && this._inputless_param_names.includes(param_name)) {\\n add_input = false;\\n }\\n if (add_input) {\\n if (this.node.params.has(param_name)) {\\n const param = this.node.params.get(param_name);\\n if (param && !param.parent_param) {\\n const connection_type = connection_type_map[param.type()];\\n if (connection_type) {\\n const connection_point = create_connection_point(this._context, param.name(), connection_type);\\n if (connection_point) {\\n connection_points.push(connection_point);\\n }\\n }\\n }\\n }\\n }\\n }\\n this.node.io.inputs.setNamedInputConnectionPoints(connection_points);\\n }\\n set_inputless_param_names(names) {\\n return this._inputless_param_names = names;\\n }\\n createSpareParameters() {\\n if (this.node.scene().loadingController.isLoading()) {\\n return;\\n }\\n const current_param_names = this.node.params.spare_names;\\n const params_update_options = {};\\n for (let param_name of current_param_names) {\\n if (this.node.params.has(param_name)) {\\n const param = this.node.params.get(param_name);\\n if (param) {\\n this._raw_input_serialized_by_param_name.set(param_name, param.rawInputSerialized());\\n this._default_value_serialized_by_param_name.set(param_name, param.defaultValueSerialized());\\n params_update_options.namesToDelete = params_update_options.namesToDelete || [];\\n params_update_options.namesToDelete.push(param_name);\\n }\\n }\\n }\\n for (let connection_point of this.node.io.inputs.namedInputConnectionPoints()) {\\n if (connection_point) {\\n const param_name = connection_point.name();\\n const param_type = connection_point.param_type;\\n let init_value = connection_point.init_value;\\n const last_param_init_value = this._default_value_serialized_by_param_name.get(param_name);\\n let default_value_from_name = this.node.paramDefaultValue(param_name);\\n if (default_value_from_name != null) {\\n init_value = default_value_from_name;\\n } else {\\n if (last_param_init_value != null) {\\n init_value = last_param_init_value;\\n } else {\\n init_value = connection_point.init_value;\\n }\\n }\\n if (CoreType.isArray(connection_point.init_value)) {\\n if (CoreType.isNumber(init_value)) {\\n const array = new Array(connection_point.init_value.length);\\n array.fill(init_value);\\n init_value = array;\\n } else if (CoreType.isArray(init_value)) {\\n if (init_value.length == connection_point.init_value.length) {\\n if (last_param_init_value != null) {\\n init_value = connection_point.init_value;\\n }\\n }\\n }\\n }\\n if (init_value != null) {\\n params_update_options.toAdd = params_update_options.toAdd || [];\\n params_update_options.toAdd.push({\\n name: param_name,\\n type: param_type,\\n init_value: ObjectUtils.clone(init_value),\\n raw_input: ObjectUtils.clone(init_value),\\n options: {\\n spare: true\\n }\\n });\\n }\\n }\\n }\\n this.node.params.updateParams(params_update_options);\\n for (let spare_param of this.node.params.spare) {\\n if (!spare_param.parent_param) {\\n const raw_input = this._raw_input_serialized_by_param_name.get(spare_param.name());\\n if (raw_input) {\\n spare_param.set(raw_input);\\n }\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/ConnectionPointsController.ts\\nvar ConnectionPointsController = class {\\n constructor(node, _context2) {\\n this.node = node;\\n this._context = _context2;\\n this._create_spare_params_from_inputs = true;\\n this._functions_overridden = false;\\n this._input_name_function = (index) => {\\n return `in${index}`;\\n };\\n this._output_name_function = (index) => {\\n return index == 0 ? \\\\\\\"val\\\\\\\" : `val${index}`;\\n };\\n this._expected_input_types_function = () => {\\n const type = this.first_input_connection_type() || this.default_connection_type();\\n return [type, type];\\n };\\n this._expected_output_types_function = () => {\\n return [this._expected_input_types_function()[0]];\\n };\\n this._update_signature_if_required_bound = this.update_signature_if_required.bind(this);\\n this._initialized = false;\\n this._spare_params_controller = new ConnectionPointsSpareParamsController(this.node, this._context);\\n }\\n default_connection_type() {\\n return DEFAULT_CONNECTION_POINT_ENUM_MAP[this._context];\\n }\\n create_connection_point(name, type) {\\n return create_connection_point(this._context, name, type);\\n }\\n functions_overridden() {\\n return this._functions_overridden;\\n }\\n initialized() {\\n return this._initialized;\\n }\\n set_create_spare_params_from_inputs(state) {\\n this._create_spare_params_from_inputs = state;\\n }\\n set_input_name_function(func) {\\n this._initialize_if_required();\\n this._input_name_function = func;\\n }\\n set_output_name_function(func) {\\n this._initialize_if_required();\\n this._output_name_function = func;\\n }\\n set_expected_input_types_function(func) {\\n this._initialize_if_required();\\n this._functions_overridden = true;\\n this._expected_input_types_function = func;\\n }\\n set_expected_output_types_function(func) {\\n this._initialize_if_required();\\n this._functions_overridden = true;\\n this._expected_output_types_function = func;\\n }\\n input_name(index) {\\n return this._wrapped_input_name_function(index);\\n }\\n output_name(index) {\\n return this._wrapped_output_name_function(index);\\n }\\n initializeNode() {\\n if (this._initialized) {\\n console.warn(\\\\\\\"already initialized\\\\\\\", this.node);\\n return;\\n }\\n this._initialized = true;\\n this.node.io.inputs.add_on_set_input_hook(\\\\\\\"_update_signature_if_required\\\\\\\", this._update_signature_if_required_bound);\\n this.node.params.addOnSceneLoadHook(\\\\\\\"_update_signature_if_required\\\\\\\", this._update_signature_if_required_bound);\\n this.node.params.onParamsCreated(\\\\\\\"_update_signature_if_required_bound\\\\\\\", this._update_signature_if_required_bound);\\n this.node.addPostDirtyHook(\\\\\\\"_update_signature_if_required\\\\\\\", this._update_signature_if_required_bound);\\n if (!this._spare_params_controller.initialized()) {\\n this._spare_params_controller.initializeNode();\\n }\\n }\\n _initialize_if_required() {\\n if (!this._initialized) {\\n this.initializeNode();\\n }\\n }\\n get spare_params() {\\n return this._spare_params_controller;\\n }\\n update_signature_if_required(dirty_trigger) {\\n if (!this.node.lifecycle.creationCompleted() || !this._connections_match_inputs()) {\\n this.update_connection_types();\\n this.node.removeDirtyState();\\n if (!this.node.scene().loadingController.isLoading()) {\\n this.make_successors_update_signatures();\\n }\\n }\\n }\\n make_successors_update_signatures() {\\n const successors = this.node.graphAllSuccessors();\\n if (this.node.childrenAllowed()) {\\n const subnet_inputs = this.node.nodesByType(NetworkChildNodeType.INPUT);\\n const subnet_outputs = this.node.nodesByType(NetworkChildNodeType.OUTPUT);\\n for (let subnet_input of subnet_inputs) {\\n successors.push(subnet_input);\\n }\\n for (let subnet_output of subnet_outputs) {\\n successors.push(subnet_output);\\n }\\n }\\n for (let graph_node of successors) {\\n const node = graph_node;\\n if (node.io && node.io.has_connection_points_controller && node.io.connection_points.initialized()) {\\n node.io.connection_points.update_signature_if_required(this.node);\\n }\\n }\\n }\\n update_connection_types() {\\n const set_dirty = false;\\n const expected_input_types = this._wrapped_expected_input_types_function();\\n const expected_output_types = this._wrapped_expected_output_types_function();\\n const named_input_connection_points = [];\\n for (let i = 0; i < expected_input_types.length; i++) {\\n const type = expected_input_types[i];\\n const point = this.create_connection_point(this._wrapped_input_name_function(i), type);\\n named_input_connection_points.push(point);\\n }\\n const named_output_connect_points = [];\\n for (let i = 0; i < expected_output_types.length; i++) {\\n const type = expected_output_types[i];\\n const point = this.create_connection_point(this._wrapped_output_name_function(i), type);\\n named_output_connect_points.push(point);\\n }\\n this.node.io.inputs.setNamedInputConnectionPoints(named_input_connection_points);\\n this.node.io.outputs.setNamedOutputConnectionPoints(named_output_connect_points, set_dirty);\\n if (this._create_spare_params_from_inputs) {\\n this._spare_params_controller.createSpareParameters();\\n }\\n }\\n _connections_match_inputs() {\\n const current_input_types = this.node.io.inputs.namedInputConnectionPoints().map((c) => c?.type());\\n const current_output_types = this.node.io.outputs.namedOutputConnectionPoints().map((c) => c?.type());\\n const expected_input_types = this._wrapped_expected_input_types_function();\\n const expected_output_types = this._wrapped_expected_output_types_function();\\n if (expected_input_types.length != current_input_types.length) {\\n return false;\\n }\\n if (expected_output_types.length != current_output_types.length) {\\n return false;\\n }\\n for (let i = 0; i < current_input_types.length; i++) {\\n if (current_input_types[i] != expected_input_types[i]) {\\n return false;\\n }\\n }\\n for (let i = 0; i < current_output_types.length; i++) {\\n if (current_output_types[i] != expected_output_types[i]) {\\n return false;\\n }\\n }\\n return true;\\n }\\n _wrapped_expected_input_types_function() {\\n if (this.node.scene().loadingController.isLoading()) {\\n const in_data = this.node.io.saved_connection_points_data.in();\\n if (in_data) {\\n return in_data.map((d) => d.type);\\n }\\n }\\n return this._expected_input_types_function();\\n }\\n _wrapped_expected_output_types_function() {\\n if (this.node.scene().loadingController.isLoading()) {\\n const out_data = this.node.io.saved_connection_points_data.out();\\n if (out_data) {\\n return out_data.map((d) => d.type);\\n }\\n }\\n return this._expected_output_types_function();\\n }\\n _wrapped_input_name_function(index) {\\n if (this.node.scene().loadingController.isLoading()) {\\n const in_data = this.node.io.saved_connection_points_data.in();\\n if (in_data) {\\n return in_data[index].name;\\n }\\n }\\n return this._input_name_function(index);\\n }\\n _wrapped_output_name_function(index) {\\n if (this.node.scene().loadingController.isLoading()) {\\n const out_data = this.node.io.saved_connection_points_data.out();\\n if (out_data) {\\n return out_data[index].name;\\n }\\n }\\n return this._output_name_function(index);\\n }\\n first_input_connection_type() {\\n return this.input_connection_type(0);\\n }\\n input_connection_type(index) {\\n const connections = this.node.io.connections.inputConnections();\\n if (connections) {\\n const connection = connections[index];\\n if (connection) {\\n return connection.src_connection_point().type();\\n }\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/io/IOController.ts\\nvar IOController = class {\\n constructor(node) {\\n this.node = node;\\n this._connections = new ConnectionsController(this.node);\\n }\\n get connections() {\\n return this._connections;\\n }\\n get inputs() {\\n return this._inputs = this._inputs || new InputsController2(this.node);\\n }\\n has_inputs() {\\n return this._inputs != null;\\n }\\n get outputs() {\\n return this._outputs = this._outputs || new OutputsController(this.node);\\n }\\n has_outputs() {\\n return this._outputs != null;\\n }\\n get connection_points() {\\n return this._connection_points = this._connection_points || new ConnectionPointsController(this.node, this.node.context());\\n }\\n get has_connection_points_controller() {\\n return this._connection_points != null;\\n }\\n get saved_connection_points_data() {\\n return this._saved_connection_points_data = this._saved_connection_points_data || new SavedConnectionPointsDataController(this.node);\\n }\\n clear_saved_connection_points_data() {\\n if (this._saved_connection_points_data) {\\n this._saved_connection_points_data.clear();\\n this._saved_connection_points_data = void 0;\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/params/ParamsAccessor.ts\\nvar ParamsAccessor = class {\\n constructor() {\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/_Base.ts\\nvar TypedNode = class extends CoreGraphNode {\\n constructor(scene, name = \\\\\\\"BaseNode\\\\\\\", params_init_value_overrides) {\\n super(scene, name);\\n this.params_init_value_overrides = params_init_value_overrides;\\n this.containerController = new TypedContainerController(this);\\n this.pv = new ParamsValueAccessor();\\n this.p = new ParamsAccessor();\\n this._initialized = false;\\n }\\n copy_param_values(node) {\\n const non_spare = this.params.non_spare;\\n for (let param of non_spare) {\\n const other_param = node.params.get(param.name());\\n if (other_param) {\\n param.copy_value(other_param);\\n }\\n }\\n }\\n get parentController() {\\n return this._parent_controller = this._parent_controller || new HierarchyParentController(this);\\n }\\n static displayedInputNames() {\\n return [];\\n }\\n get childrenControllerContext() {\\n return this._children_controller_context;\\n }\\n _create_children_controller() {\\n if (this._children_controller_context) {\\n return new HierarchyChildrenController(this, this._children_controller_context);\\n }\\n }\\n get childrenController() {\\n return this._children_controller = this._children_controller || this._create_children_controller();\\n }\\n childrenAllowed() {\\n return this._children_controller_context != null;\\n }\\n get uiData() {\\n return this._ui_data = this._ui_data || new UIData(this);\\n }\\n get states() {\\n return this._states = this._states || new StatesController(this);\\n }\\n get lifecycle() {\\n return this._lifecycle = this._lifecycle || new LifeCycleController(this);\\n }\\n get serializer() {\\n return this._serializer = this._serializer || new NodeSerializer(this);\\n }\\n get cookController() {\\n return this._cook_controller = this._cook_controller || new NodeCookController(this);\\n }\\n get io() {\\n return this._io = this._io || new IOController(this);\\n }\\n get nameController() {\\n return this._name_controller = this._name_controller || new NameController(this);\\n }\\n setName(name) {\\n this.nameController.setName(name);\\n }\\n _set_core_name(name) {\\n this._name = name;\\n }\\n get params() {\\n return this._params_controller = this._params_controller || new ParamsController(this);\\n }\\n initialize_base_and_node() {\\n if (!this._initialized) {\\n this._initialized = true;\\n this.displayNodeController?.initializeNode();\\n this.initializeBaseNode();\\n this.initializeNode();\\n if (this.polyNodeController) {\\n this.polyNodeController.initializeNode();\\n }\\n } else {\\n console.warn(\\\\\\\"node already initialized\\\\\\\");\\n }\\n }\\n initializeBaseNode() {\\n }\\n initializeNode() {\\n }\\n static type() {\\n throw \\\\\\\"type to be overriden\\\\\\\";\\n }\\n type() {\\n const c = this.constructor;\\n return c.type();\\n }\\n static context() {\\n console.error(\\\\\\\"node has no node_context\\\\\\\", this);\\n throw \\\\\\\"context requires override\\\\\\\";\\n }\\n context() {\\n const c = this.constructor;\\n return c.context();\\n }\\n static require_webgl2() {\\n return false;\\n }\\n require_webgl2() {\\n const c = this.constructor;\\n return c.require_webgl2();\\n }\\n setParent(parent) {\\n this.parentController.setParent(parent);\\n }\\n parent() {\\n return this.parentController.parent();\\n }\\n firstAncestorWithContext(context) {\\n return this.parentController.firstAncestorWithContext(context);\\n }\\n root() {\\n return this._scene.root();\\n }\\n path(relative_to_parent) {\\n return this.parentController.path(relative_to_parent);\\n }\\n createParams() {\\n }\\n addParam(type, name, default_value, options) {\\n return this._params_controller?.addParam(type, name, default_value, options);\\n }\\n paramDefaultValue(name) {\\n return null;\\n }\\n cook(input_contents) {\\n return null;\\n }\\n onCookEnd(callbackName, callback) {\\n this.cookController.registerOnCookEnd(callbackName, callback);\\n }\\n async compute() {\\n if (this.isDirty() || this.flags?.bypass?.active()) {\\n return await this.containerController.compute();\\n } else {\\n return this.containerController.container();\\n }\\n }\\n _setContainer(content, message = null) {\\n this.containerController.container().set_content(content);\\n if (content != null) {\\n if (!content.name) {\\n content.name = this.path();\\n }\\n if (!content.node) {\\n content.node = this;\\n }\\n }\\n this.cookController.endCook(message);\\n }\\n createNode(nodeClass, params_init_value_overrides) {\\n return this.childrenController?.createNode(nodeClass, params_init_value_overrides);\\n }\\n create_operation_container(type, operation_container_name, params_init_value_overrides) {\\n return this.childrenController?.create_operation_container(type, operation_container_name, params_init_value_overrides);\\n }\\n removeNode(node) {\\n this.childrenController?.removeNode(node);\\n }\\n dispose() {\\n super.dispose();\\n this.setParent(null);\\n this.io.inputs.dispose();\\n this.lifecycle.dispose();\\n this.displayNodeController?.dispose();\\n this.nameController.dispose();\\n this.childrenController?.dispose();\\n this.params.dispose();\\n }\\n children() {\\n return this.childrenController?.children() || [];\\n }\\n node(path) {\\n return this.parentController?.findNode(path) || null;\\n }\\n nodeSibbling(name) {\\n const parent = this.parent();\\n if (parent) {\\n const node = parent.childrenController?.child_by_name(name);\\n if (node) {\\n return node;\\n }\\n }\\n return null;\\n }\\n nodesByType(type) {\\n return this.childrenController?.nodesByType(type) || [];\\n }\\n setInput(input_index_or_name, node, output_index_or_name = 0) {\\n this.io.inputs.setInput(input_index_or_name, node, output_index_or_name);\\n }\\n emit(event_name, data = null) {\\n this.scene().dispatchController.dispatch(this, event_name, data);\\n }\\n toJSON(include_param_components = false) {\\n return this.serializer.toJSON(include_param_components);\\n }\\n async requiredModules() {\\n }\\n usedAssembler() {\\n }\\n integrationData() {\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/obj/_Base.ts\\nvar INPUT_OBJECT_NAME = \\\\\\\"parent object\\\\\\\";\\nvar DEFAULT_INPUT_NAMES = [INPUT_OBJECT_NAME, INPUT_OBJECT_NAME, INPUT_OBJECT_NAME, INPUT_OBJECT_NAME];\\nvar ObjNodeRenderOrder;\\n(function(ObjNodeRenderOrder2) {\\n ObjNodeRenderOrder2[ObjNodeRenderOrder2[\\\\\\\"MANAGER\\\\\\\"] = 0] = \\\\\\\"MANAGER\\\\\\\";\\n ObjNodeRenderOrder2[ObjNodeRenderOrder2[\\\\\\\"CAMERA\\\\\\\"] = 2] = \\\\\\\"CAMERA\\\\\\\";\\n ObjNodeRenderOrder2[ObjNodeRenderOrder2[\\\\\\\"LIGHT\\\\\\\"] = 3] = \\\\\\\"LIGHT\\\\\\\";\\n})(ObjNodeRenderOrder || (ObjNodeRenderOrder = {}));\\nvar TypedObjNode = class extends TypedNode {\\n constructor() {\\n super(...arguments);\\n this.renderOrder = 0;\\n this._children_group = this._create_children_group();\\n this._attachableToHierarchy = true;\\n this._used_in_scene = true;\\n }\\n static context() {\\n return NodeContext.OBJ;\\n }\\n static displayedInputNames() {\\n return DEFAULT_INPUT_NAMES;\\n }\\n _create_children_group() {\\n const group = new Group();\\n group.matrixAutoUpdate = false;\\n return group;\\n }\\n attachableToHierarchy() {\\n return this._attachableToHierarchy;\\n }\\n usedInScene() {\\n return this._used_in_scene;\\n }\\n addObjectToParent(parent) {\\n if (this.attachableToHierarchy()) {\\n parent.add(this.object);\\n }\\n }\\n removeObjectFromParent() {\\n if (this.attachableToHierarchy()) {\\n const parent = this.object.parent;\\n if (parent) {\\n parent.remove(this.object);\\n }\\n }\\n }\\n initializeBaseNode() {\\n this._object = this._create_object_with_attributes();\\n this.nameController.add_post_set_fullPath_hook(this.set_object_name.bind(this));\\n this.set_object_name();\\n }\\n get children_group() {\\n return this._children_group;\\n }\\n get object() {\\n return this._object;\\n }\\n _create_object_with_attributes() {\\n const object = this.createObject();\\n object.node = this;\\n object.add(this._children_group);\\n return object;\\n }\\n set_object_name() {\\n if (this._object) {\\n this._object.name = this.path();\\n this._children_group.name = `${this.path()}:parented_outputs`;\\n }\\n }\\n createObject() {\\n const object = new Object3D();\\n object.matrixAutoUpdate = false;\\n return object;\\n }\\n isDisplayNodeCooking() {\\n if (this.displayNodeController) {\\n const displayNode = this.displayNodeController.displayNode();\\n if (displayNode) {\\n return displayNode.cookController.isCooking();\\n }\\n }\\n return false;\\n }\\n isDisplayed() {\\n return this.flags?.display?.active() || false;\\n }\\n};\\n\\n// ../../../node_modules/three/src/audio/AudioAnalyser.js\\nvar AudioAnalyser = class {\\n constructor(audio, fftSize = 2048) {\\n this.analyser = audio.context.createAnalyser();\\n this.analyser.fftSize = fftSize;\\n this.data = new Uint8Array(this.analyser.frequencyBinCount);\\n audio.getOutput().connect(this.analyser);\\n }\\n getFrequencyData() {\\n this.analyser.getByteFrequencyData(this.data);\\n return this.data;\\n }\\n getAverageFrequency() {\\n let value = 0;\\n const data = this.getFrequencyData();\\n for (let i = 0; i < data.length; i++) {\\n value += data[i];\\n }\\n return value / data.length;\\n }\\n};\\n\\n// ../../../node_modules/three/src/audio/Audio.js\\nvar Audio2 = class extends Object3D {\\n constructor(listener) {\\n super();\\n this.type = \\\\\\\"Audio\\\\\\\";\\n this.listener = listener;\\n this.context = listener.context;\\n this.gain = this.context.createGain();\\n this.gain.connect(listener.getInput());\\n this.autoplay = false;\\n this.buffer = null;\\n this.detune = 0;\\n this.loop = false;\\n this.loopStart = 0;\\n this.loopEnd = 0;\\n this.offset = 0;\\n this.duration = void 0;\\n this.playbackRate = 1;\\n this.isPlaying = false;\\n this.hasPlaybackControl = true;\\n this.source = null;\\n this.sourceType = \\\\\\\"empty\\\\\\\";\\n this._startedAt = 0;\\n this._progress = 0;\\n this._connected = false;\\n this.filters = [];\\n }\\n getOutput() {\\n return this.gain;\\n }\\n setNodeSource(audioNode) {\\n this.hasPlaybackControl = false;\\n this.sourceType = \\\\\\\"audioNode\\\\\\\";\\n this.source = audioNode;\\n this.connect();\\n return this;\\n }\\n setMediaElementSource(mediaElement) {\\n this.hasPlaybackControl = false;\\n this.sourceType = \\\\\\\"mediaNode\\\\\\\";\\n this.source = this.context.createMediaElementSource(mediaElement);\\n this.connect();\\n return this;\\n }\\n setMediaStreamSource(mediaStream) {\\n this.hasPlaybackControl = false;\\n this.sourceType = \\\\\\\"mediaStreamNode\\\\\\\";\\n this.source = this.context.createMediaStreamSource(mediaStream);\\n this.connect();\\n return this;\\n }\\n setBuffer(audioBuffer) {\\n this.buffer = audioBuffer;\\n this.sourceType = \\\\\\\"buffer\\\\\\\";\\n if (this.autoplay)\\n this.play();\\n return this;\\n }\\n play(delay = 0) {\\n if (this.isPlaying === true) {\\n console.warn(\\\\\\\"THREE.Audio: Audio is already playing.\\\\\\\");\\n return;\\n }\\n if (this.hasPlaybackControl === false) {\\n console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\");\\n return;\\n }\\n this._startedAt = this.context.currentTime + delay;\\n const source = this.context.createBufferSource();\\n source.buffer = this.buffer;\\n source.loop = this.loop;\\n source.loopStart = this.loopStart;\\n source.loopEnd = this.loopEnd;\\n source.onended = this.onEnded.bind(this);\\n source.start(this._startedAt, this._progress + this.offset, this.duration);\\n this.isPlaying = true;\\n this.source = source;\\n this.setDetune(this.detune);\\n this.setPlaybackRate(this.playbackRate);\\n return this.connect();\\n }\\n pause() {\\n if (this.hasPlaybackControl === false) {\\n console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\");\\n return;\\n }\\n if (this.isPlaying === true) {\\n this._progress += Math.max(this.context.currentTime - this._startedAt, 0) * this.playbackRate;\\n if (this.loop === true) {\\n this._progress = this._progress % (this.duration || this.buffer.duration);\\n }\\n this.source.stop();\\n this.source.onended = null;\\n this.isPlaying = false;\\n }\\n return this;\\n }\\n stop() {\\n if (this.hasPlaybackControl === false) {\\n console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\");\\n return;\\n }\\n this._progress = 0;\\n this.source.stop();\\n this.source.onended = null;\\n this.isPlaying = false;\\n return this;\\n }\\n connect() {\\n if (this.filters.length > 0) {\\n this.source.connect(this.filters[0]);\\n for (let i = 1, l = this.filters.length; i < l; i++) {\\n this.filters[i - 1].connect(this.filters[i]);\\n }\\n this.filters[this.filters.length - 1].connect(this.getOutput());\\n } else {\\n this.source.connect(this.getOutput());\\n }\\n this._connected = true;\\n return this;\\n }\\n disconnect() {\\n if (this.filters.length > 0) {\\n this.source.disconnect(this.filters[0]);\\n for (let i = 1, l = this.filters.length; i < l; i++) {\\n this.filters[i - 1].disconnect(this.filters[i]);\\n }\\n this.filters[this.filters.length - 1].disconnect(this.getOutput());\\n } else {\\n this.source.disconnect(this.getOutput());\\n }\\n this._connected = false;\\n return this;\\n }\\n getFilters() {\\n return this.filters;\\n }\\n setFilters(value) {\\n if (!value)\\n value = [];\\n if (this._connected === true) {\\n this.disconnect();\\n this.filters = value.slice();\\n this.connect();\\n } else {\\n this.filters = value.slice();\\n }\\n return this;\\n }\\n setDetune(value) {\\n this.detune = value;\\n if (this.source.detune === void 0)\\n return;\\n if (this.isPlaying === true) {\\n this.source.detune.setTargetAtTime(this.detune, this.context.currentTime, 0.01);\\n }\\n return this;\\n }\\n getDetune() {\\n return this.detune;\\n }\\n getFilter() {\\n return this.getFilters()[0];\\n }\\n setFilter(filter) {\\n return this.setFilters(filter ? [filter] : []);\\n }\\n setPlaybackRate(value) {\\n if (this.hasPlaybackControl === false) {\\n console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\");\\n return;\\n }\\n this.playbackRate = value;\\n if (this.isPlaying === true) {\\n this.source.playbackRate.setTargetAtTime(this.playbackRate, this.context.currentTime, 0.01);\\n }\\n return this;\\n }\\n getPlaybackRate() {\\n return this.playbackRate;\\n }\\n onEnded() {\\n this.isPlaying = false;\\n }\\n getLoop() {\\n if (this.hasPlaybackControl === false) {\\n console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\");\\n return false;\\n }\\n return this.loop;\\n }\\n setLoop(value) {\\n if (this.hasPlaybackControl === false) {\\n console.warn(\\\\\\\"THREE.Audio: this Audio has no playback control.\\\\\\\");\\n return;\\n }\\n this.loop = value;\\n if (this.isPlaying === true) {\\n this.source.loop = this.loop;\\n }\\n return this;\\n }\\n setLoopStart(value) {\\n this.loopStart = value;\\n return this;\\n }\\n setLoopEnd(value) {\\n this.loopEnd = value;\\n return this;\\n }\\n getVolume() {\\n return this.gain.gain.value;\\n }\\n setVolume(value) {\\n this.gain.gain.setTargetAtTime(value, this.context.currentTime, 0.01);\\n return this;\\n }\\n};\\n\\n// ../../../node_modules/three/src/audio/AudioContext.js\\nvar _context;\\nvar AudioContext = {\\n getContext: function() {\\n if (_context === void 0) {\\n _context = new (window.AudioContext || window.webkitAudioContext)();\\n }\\n return _context;\\n },\\n setContext: function(value) {\\n _context = value;\\n }\\n};\\n\\n// ../../../node_modules/three/src/loaders/Cache.js\\nvar Cache = {\\n enabled: false,\\n files: {},\\n add: function(key, file) {\\n if (this.enabled === false)\\n return;\\n this.files[key] = file;\\n },\\n get: function(key) {\\n if (this.enabled === false)\\n return;\\n return this.files[key];\\n },\\n remove: function(key) {\\n delete this.files[key];\\n },\\n clear: function() {\\n this.files = {};\\n }\\n};\\n\\n// ../../../node_modules/three/src/loaders/LoadingManager.js\\nvar LoadingManager = class {\\n constructor(onLoad, onProgress, onError) {\\n const scope = this;\\n let isLoading = false;\\n let itemsLoaded = 0;\\n let itemsTotal = 0;\\n let urlModifier = void 0;\\n const handlers = [];\\n this.onStart = void 0;\\n this.onLoad = onLoad;\\n this.onProgress = onProgress;\\n this.onError = onError;\\n this.itemStart = function(url) {\\n itemsTotal++;\\n if (isLoading === false) {\\n if (scope.onStart !== void 0) {\\n scope.onStart(url, itemsLoaded, itemsTotal);\\n }\\n }\\n isLoading = true;\\n };\\n this.itemEnd = function(url) {\\n itemsLoaded++;\\n if (scope.onProgress !== void 0) {\\n scope.onProgress(url, itemsLoaded, itemsTotal);\\n }\\n if (itemsLoaded === itemsTotal) {\\n isLoading = false;\\n if (scope.onLoad !== void 0) {\\n scope.onLoad();\\n }\\n }\\n };\\n this.itemError = function(url) {\\n if (scope.onError !== void 0) {\\n scope.onError(url);\\n }\\n };\\n this.resolveURL = function(url) {\\n if (urlModifier) {\\n return urlModifier(url);\\n }\\n return url;\\n };\\n this.setURLModifier = function(transform) {\\n urlModifier = transform;\\n return this;\\n };\\n this.addHandler = function(regex, loader) {\\n handlers.push(regex, loader);\\n return this;\\n };\\n this.removeHandler = function(regex) {\\n const index = handlers.indexOf(regex);\\n if (index !== -1) {\\n handlers.splice(index, 2);\\n }\\n return this;\\n };\\n this.getHandler = function(file) {\\n for (let i = 0, l = handlers.length; i < l; i += 2) {\\n const regex = handlers[i];\\n const loader = handlers[i + 1];\\n if (regex.global)\\n regex.lastIndex = 0;\\n if (regex.test(file)) {\\n return loader;\\n }\\n }\\n return null;\\n };\\n }\\n};\\nvar DefaultLoadingManager = new LoadingManager();\\n\\n// ../../../node_modules/three/src/loaders/Loader.js\\nvar Loader = class {\\n constructor(manager) {\\n this.manager = manager !== void 0 ? manager : DefaultLoadingManager;\\n this.crossOrigin = \\\\\\\"anonymous\\\\\\\";\\n this.withCredentials = false;\\n this.path = \\\\\\\"\\\\\\\";\\n this.resourcePath = \\\\\\\"\\\\\\\";\\n this.requestHeader = {};\\n }\\n load() {\\n }\\n loadAsync(url, onProgress) {\\n const scope = this;\\n return new Promise(function(resolve, reject) {\\n scope.load(url, resolve, onProgress, reject);\\n });\\n }\\n parse() {\\n }\\n setCrossOrigin(crossOrigin) {\\n this.crossOrigin = crossOrigin;\\n return this;\\n }\\n setWithCredentials(value) {\\n this.withCredentials = value;\\n return this;\\n }\\n setPath(path) {\\n this.path = path;\\n return this;\\n }\\n setResourcePath(resourcePath) {\\n this.resourcePath = resourcePath;\\n return this;\\n }\\n setRequestHeader(requestHeader) {\\n this.requestHeader = requestHeader;\\n return this;\\n }\\n};\\n\\n// ../../../node_modules/three/src/loaders/FileLoader.js\\nvar loading = {};\\nvar FileLoader = class extends Loader {\\n constructor(manager) {\\n super(manager);\\n }\\n load(url, onLoad, onProgress, onError) {\\n if (url === void 0)\\n url = \\\\\\\"\\\\\\\";\\n if (this.path !== void 0)\\n url = this.path + url;\\n url = this.manager.resolveURL(url);\\n const scope = this;\\n const cached = Cache.get(url);\\n if (cached !== void 0) {\\n scope.manager.itemStart(url);\\n setTimeout(function() {\\n if (onLoad)\\n onLoad(cached);\\n scope.manager.itemEnd(url);\\n }, 0);\\n return cached;\\n }\\n if (loading[url] !== void 0) {\\n loading[url].push({\\n onLoad,\\n onProgress,\\n onError\\n });\\n return;\\n }\\n const dataUriRegex = /^data:(.*?)(;base64)?,(.*)$/;\\n const dataUriRegexResult = url.match(dataUriRegex);\\n let request;\\n if (dataUriRegexResult) {\\n const mimeType = dataUriRegexResult[1];\\n const isBase64 = !!dataUriRegexResult[2];\\n let data = dataUriRegexResult[3];\\n data = decodeURIComponent(data);\\n if (isBase64)\\n data = atob(data);\\n try {\\n let response;\\n const responseType = (this.responseType || \\\\\\\"\\\\\\\").toLowerCase();\\n switch (responseType) {\\n case \\\\\\\"arraybuffer\\\\\\\":\\n case \\\\\\\"blob\\\\\\\":\\n const view = new Uint8Array(data.length);\\n for (let i = 0; i < data.length; i++) {\\n view[i] = data.charCodeAt(i);\\n }\\n if (responseType === \\\\\\\"blob\\\\\\\") {\\n response = new Blob([view.buffer], {type: mimeType});\\n } else {\\n response = view.buffer;\\n }\\n break;\\n case \\\\\\\"document\\\\\\\":\\n const parser = new DOMParser();\\n response = parser.parseFromString(data, mimeType);\\n break;\\n case \\\\\\\"json\\\\\\\":\\n response = JSON.parse(data);\\n break;\\n default:\\n response = data;\\n break;\\n }\\n setTimeout(function() {\\n if (onLoad)\\n onLoad(response);\\n scope.manager.itemEnd(url);\\n }, 0);\\n } catch (error) {\\n setTimeout(function() {\\n if (onError)\\n onError(error);\\n scope.manager.itemError(url);\\n scope.manager.itemEnd(url);\\n }, 0);\\n }\\n } else {\\n loading[url] = [];\\n loading[url].push({\\n onLoad,\\n onProgress,\\n onError\\n });\\n request = new XMLHttpRequest();\\n request.open(\\\\\\\"GET\\\\\\\", url, true);\\n request.addEventListener(\\\\\\\"load\\\\\\\", function(event) {\\n const response = this.response;\\n const callbacks = loading[url];\\n delete loading[url];\\n if (this.status === 200 || this.status === 0) {\\n if (this.status === 0)\\n console.warn(\\\\\\\"THREE.FileLoader: HTTP Status 0 received.\\\\\\\");\\n Cache.add(url, response);\\n for (let i = 0, il = callbacks.length; i < il; i++) {\\n const callback = callbacks[i];\\n if (callback.onLoad)\\n callback.onLoad(response);\\n }\\n scope.manager.itemEnd(url);\\n } else {\\n for (let i = 0, il = callbacks.length; i < il; i++) {\\n const callback = callbacks[i];\\n if (callback.onError)\\n callback.onError(event);\\n }\\n scope.manager.itemError(url);\\n scope.manager.itemEnd(url);\\n }\\n }, false);\\n request.addEventListener(\\\\\\\"progress\\\\\\\", function(event) {\\n const callbacks = loading[url];\\n for (let i = 0, il = callbacks.length; i < il; i++) {\\n const callback = callbacks[i];\\n if (callback.onProgress)\\n callback.onProgress(event);\\n }\\n }, false);\\n request.addEventListener(\\\\\\\"error\\\\\\\", function(event) {\\n const callbacks = loading[url];\\n delete loading[url];\\n for (let i = 0, il = callbacks.length; i < il; i++) {\\n const callback = callbacks[i];\\n if (callback.onError)\\n callback.onError(event);\\n }\\n scope.manager.itemError(url);\\n scope.manager.itemEnd(url);\\n }, false);\\n request.addEventListener(\\\\\\\"abort\\\\\\\", function(event) {\\n const callbacks = loading[url];\\n delete loading[url];\\n for (let i = 0, il = callbacks.length; i < il; i++) {\\n const callback = callbacks[i];\\n if (callback.onError)\\n callback.onError(event);\\n }\\n scope.manager.itemError(url);\\n scope.manager.itemEnd(url);\\n }, false);\\n if (this.responseType !== void 0)\\n request.responseType = this.responseType;\\n if (this.withCredentials !== void 0)\\n request.withCredentials = this.withCredentials;\\n if (request.overrideMimeType)\\n request.overrideMimeType(this.mimeType !== void 0 ? this.mimeType : \\\\\\\"text/plain\\\\\\\");\\n for (const header in this.requestHeader) {\\n request.setRequestHeader(header, this.requestHeader[header]);\\n }\\n request.send(null);\\n }\\n scope.manager.itemStart(url);\\n return request;\\n }\\n setResponseType(value) {\\n this.responseType = value;\\n return this;\\n }\\n setMimeType(value) {\\n this.mimeType = value;\\n return this;\\n }\\n};\\n\\n// ../../../node_modules/three/src/loaders/AudioLoader.js\\nvar AudioLoader = class extends Loader {\\n constructor(manager) {\\n super(manager);\\n }\\n load(url, onLoad, onProgress, onError) {\\n const scope = this;\\n const loader = new FileLoader(this.manager);\\n loader.setResponseType(\\\\\\\"arraybuffer\\\\\\\");\\n loader.setPath(this.path);\\n loader.setRequestHeader(this.requestHeader);\\n loader.setWithCredentials(this.withCredentials);\\n loader.load(url, function(buffer) {\\n try {\\n const bufferCopy = buffer.slice(0);\\n const context = AudioContext.getContext();\\n context.decodeAudioData(bufferCopy, function(audioBuffer) {\\n onLoad(audioBuffer);\\n });\\n } catch (e) {\\n if (onError) {\\n onError(e);\\n } else {\\n console.error(e);\\n }\\n scope.manager.itemError(url);\\n }\\n }, onProgress, onError);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/utils/params/ParamsConfig.ts\\nvar ParamTemplate = class {\\n constructor(type, init_value, options) {\\n this.type = type;\\n this.init_value = init_value;\\n this.options = options;\\n }\\n};\\nvar ParamConfig = class {\\n static BUTTON(init_value, options) {\\n return new ParamTemplate(ParamType.BUTTON, init_value, options);\\n }\\n static BOOLEAN(init_value, options) {\\n return new ParamTemplate(ParamType.BOOLEAN, init_value, options);\\n }\\n static COLOR(init_value, options) {\\n if (init_value instanceof Color) {\\n init_value = init_value.toArray();\\n }\\n return new ParamTemplate(ParamType.COLOR, init_value, options);\\n }\\n static FLOAT(init_value, options) {\\n return new ParamTemplate(ParamType.FLOAT, init_value, options);\\n }\\n static FOLDER(init_value = null, options) {\\n return new ParamTemplate(ParamType.FOLDER, init_value, options);\\n }\\n static INTEGER(init_value, options) {\\n return new ParamTemplate(ParamType.INTEGER, init_value, options);\\n }\\n static RAMP(init_value = RampParam.DEFAULT_VALUE, options) {\\n return new ParamTemplate(ParamType.RAMP, init_value, options);\\n }\\n static STRING(init_value = \\\\\\\"\\\\\\\", options) {\\n return new ParamTemplate(ParamType.STRING, init_value, options);\\n }\\n static VECTOR2(init_value, options) {\\n if (init_value instanceof Vector2) {\\n init_value = init_value.toArray();\\n }\\n return new ParamTemplate(ParamType.VECTOR2, init_value, options);\\n }\\n static VECTOR3(init_value, options) {\\n if (init_value instanceof Vector3) {\\n init_value = init_value.toArray();\\n }\\n return new ParamTemplate(ParamType.VECTOR3, init_value, options);\\n }\\n static VECTOR4(init_value, options) {\\n if (init_value instanceof Vector4) {\\n init_value = init_value.toArray();\\n }\\n return new ParamTemplate(ParamType.VECTOR4, init_value, options);\\n }\\n static OPERATOR_PATH(init_value, options) {\\n return new ParamTemplate(ParamType.OPERATOR_PATH, init_value, options);\\n }\\n static NODE_PATH(init_value, options) {\\n return new ParamTemplate(ParamType.NODE_PATH, init_value, options);\\n }\\n static PARAM_PATH(init_value, options) {\\n return new ParamTemplate(ParamType.PARAM_PATH, init_value, options);\\n }\\n};\\nvar NodeParamsConfig = class {\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/Transform.ts\\nvar TransformTargetType;\\n(function(TransformTargetType2) {\\n TransformTargetType2[\\\\\\\"OBJECTS\\\\\\\"] = \\\\\\\"objects\\\\\\\";\\n TransformTargetType2[\\\\\\\"GEOMETRIES\\\\\\\"] = \\\\\\\"geometries\\\\\\\";\\n})(TransformTargetType || (TransformTargetType = {}));\\nvar TRANSFORM_TARGET_TYPES = [\\n TransformTargetType.GEOMETRIES,\\n TransformTargetType.OBJECTS\\n];\\nvar RotationOrder;\\n(function(RotationOrder2) {\\n RotationOrder2[\\\\\\\"XYZ\\\\\\\"] = \\\\\\\"XYZ\\\\\\\";\\n RotationOrder2[\\\\\\\"XZY\\\\\\\"] = \\\\\\\"XZY\\\\\\\";\\n RotationOrder2[\\\\\\\"YXZ\\\\\\\"] = \\\\\\\"YXZ\\\\\\\";\\n RotationOrder2[\\\\\\\"YZX\\\\\\\"] = \\\\\\\"YZX\\\\\\\";\\n RotationOrder2[\\\\\\\"ZYX\\\\\\\"] = \\\\\\\"ZYX\\\\\\\";\\n RotationOrder2[\\\\\\\"ZXY\\\\\\\"] = \\\\\\\"ZXY\\\\\\\";\\n})(RotationOrder || (RotationOrder = {}));\\nvar ROTATION_ORDERS = [\\n RotationOrder.XYZ,\\n RotationOrder.XZY,\\n RotationOrder.YXZ,\\n RotationOrder.YZX,\\n RotationOrder.ZXY,\\n RotationOrder.ZYX\\n];\\nvar DEFAULT_ROTATION_ORDER = RotationOrder.XYZ;\\nvar CoreTransform = class {\\n constructor() {\\n this._translation_matrix = new Matrix4();\\n this._translation_matrix_q = new Quaternion();\\n this._translation_matrix_s = new Vector3(1, 1, 1);\\n this._matrix = new Matrix4().identity();\\n this._matrix_q = new Quaternion();\\n this._matrix_euler = new Euler();\\n this._matrix_s = new Vector3();\\n this._rotate_geometry_m = new Matrix4();\\n this._rotate_geometry_q = new Quaternion();\\n this._rotate_geometry_vec_dest = new Vector3();\\n }\\n static set_params_from_matrix(matrix, node, options = {}) {\\n let update_scale = options[\\\\\\\"scale\\\\\\\"];\\n if (update_scale == null) {\\n update_scale = true;\\n }\\n matrix.decompose(this.set_params_from_matrix_position, this.set_params_from_matrix_quaternion, this.set_params_from_matrix_scale);\\n this.set_params_from_matrix_euler.setFromQuaternion(this.set_params_from_matrix_quaternion);\\n this.set_params_from_matrix_euler.toVector3(this.set_params_from_matrix_rotation);\\n this.set_params_from_matrix_rotation.divideScalar(Math.PI / 180);\\n this.set_params_from_matrix_position.toArray(this.set_params_from_matrix_t);\\n this.set_params_from_matrix_rotation.toArray(this.set_params_from_matrix_r);\\n this.set_params_from_matrix_scale.toArray(this.set_params_from_matrix_s);\\n node.scene().batchUpdates(() => {\\n node.params.set_vector3(\\\\\\\"t\\\\\\\", this.set_params_from_matrix_t);\\n node.params.set_vector3(\\\\\\\"r\\\\\\\", this.set_params_from_matrix_r);\\n node.params.set_vector3(\\\\\\\"s\\\\\\\", this.set_params_from_matrix_s);\\n if (update_scale) {\\n node.params.set_float(\\\\\\\"scale\\\\\\\", 1);\\n }\\n });\\n }\\n static set_params_from_object(object, node) {\\n object.position.toArray(this.set_params_from_object_position_array);\\n object.rotation.toArray(this.set_params_from_object_rotation_array);\\n this.set_params_from_object_rotation_deg.fromArray(this.set_params_from_object_rotation_array);\\n this.set_params_from_object_rotation_deg.multiplyScalar(180 / Math.PI);\\n this.set_params_from_object_rotation_deg.toArray(this.set_params_from_object_rotation_array);\\n node.scene().batchUpdates(() => {\\n node.params.set_vector3(\\\\\\\"t\\\\\\\", this.set_params_from_object_position_array);\\n node.params.set_vector3(\\\\\\\"r\\\\\\\", this.set_params_from_object_rotation_array);\\n });\\n }\\n translation_matrix(t) {\\n this._translation_matrix.compose(t, this._translation_matrix_q, this._translation_matrix_s);\\n return this._translation_matrix;\\n }\\n matrix(t, r, s, scale, rotation_order) {\\n this._matrix_euler.set(degToRad(r.x), degToRad(r.y), degToRad(r.z), rotation_order);\\n this._matrix_q.setFromEuler(this._matrix_euler);\\n this._matrix_s.copy(s).multiplyScalar(scale);\\n this._matrix.compose(t, this._matrix_q, this._matrix_s);\\n return this._matrix;\\n }\\n rotate_geometry(geometry, vec_origin, vec_dest) {\\n this._rotate_geometry_vec_dest.copy(vec_dest);\\n this._rotate_geometry_vec_dest.normalize();\\n this._rotate_geometry_q.setFromUnitVectors(vec_origin, this._rotate_geometry_vec_dest);\\n this._rotate_geometry_m.makeRotationFromQuaternion(this._rotate_geometry_q);\\n geometry.applyMatrix4(this._rotate_geometry_m);\\n }\\n static decompose_matrix(object) {\\n object.matrix.decompose(object.position, object.quaternion, object.scale);\\n }\\n};\\nCoreTransform.set_params_from_matrix_position = new Vector3();\\nCoreTransform.set_params_from_matrix_quaternion = new Quaternion();\\nCoreTransform.set_params_from_matrix_scale = new Vector3();\\nCoreTransform.set_params_from_matrix_euler = new Euler();\\nCoreTransform.set_params_from_matrix_rotation = new Vector3();\\nCoreTransform.set_params_from_matrix_t = [0, 0, 0];\\nCoreTransform.set_params_from_matrix_r = [0, 0, 0];\\nCoreTransform.set_params_from_matrix_s = [0, 0, 0];\\nCoreTransform.set_params_from_object_position_array = [0, 0, 0];\\nCoreTransform.set_params_from_object_rotation_deg = new Vector3();\\nCoreTransform.set_params_from_object_rotation_array = [0, 0, 0];\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/obj/utils/TransformController.ts\\nfunction TransformedParamConfig(Base, default_params) {\\n const matrixAutoUpdate = default_params?.matrixAutoUpdate || false;\\n return class Mixin extends Base {\\n constructor() {\\n super(...arguments);\\n this.transform = ParamConfig.FOLDER();\\n this.keepPosWhenParenting = ParamConfig.BOOLEAN(0);\\n this.rotationOrder = ParamConfig.INTEGER(ROTATION_ORDERS.indexOf(RotationOrder.XYZ), {\\n menu: {\\n entries: ROTATION_ORDERS.map((order, v) => {\\n return {name: order, value: v};\\n })\\n }\\n });\\n this.t = ParamConfig.VECTOR3([0, 0, 0]);\\n this.r = ParamConfig.VECTOR3([0, 0, 0]);\\n this.s = ParamConfig.VECTOR3([1, 1, 1]);\\n this.scale = ParamConfig.FLOAT(1);\\n this.matrixAutoUpdate = ParamConfig.BOOLEAN(matrixAutoUpdate ? 1 : 0);\\n this.updateTransformFromObject = ParamConfig.BUTTON(null, {\\n callback: (node) => {\\n TransformController.PARAM_CALLBACK_update_transform_from_object(node);\\n }\\n });\\n }\\n };\\n}\\nvar TransformedParamsConfig = class extends TransformedParamConfig(NodeParamsConfig) {\\n};\\nvar HOOK_NAME = \\\\\\\"_cook_main_without_inputs_when_dirty\\\\\\\";\\nvar TransformController = class {\\n constructor(node) {\\n this.node = node;\\n this._cook_main_without_inputs_when_dirty_bound = this._cook_main_without_inputs_when_dirty.bind(this);\\n this._core_transform = new CoreTransform();\\n this._keep_pos_when_parenting_m_object = new Matrix4();\\n this._keep_pos_when_parenting_m_new_parent_inv = new Matrix4();\\n }\\n initializeNode() {\\n if (!this.node.dirtyController.hasHook(HOOK_NAME)) {\\n this.node.dirtyController.addPostDirtyHook(HOOK_NAME, this._cook_main_without_inputs_when_dirty_bound);\\n }\\n }\\n async _cook_main_without_inputs_when_dirty() {\\n await this.node.cookController.cookMainWithoutInputs();\\n }\\n update() {\\n this.update_transform_with_matrix();\\n const object = this.node.object;\\n object.matrixAutoUpdate = isBooleanTrue(this.node.pv.matrixAutoUpdate);\\n }\\n update_transform_with_matrix(matrix) {\\n const object = this.node.object;\\n if (matrix != null && !matrix.equals(object.matrix)) {\\n object.matrix.copy(matrix);\\n object.dispatchEvent({type: \\\\\\\"change\\\\\\\"});\\n } else {\\n this._update_matrix_from_params_with_core_transform();\\n }\\n }\\n _update_matrix_from_params_with_core_transform() {\\n const object = this.node.object;\\n let prev_auto_update = object.matrixAutoUpdate;\\n if (prev_auto_update) {\\n object.matrixAutoUpdate = false;\\n }\\n const matrix = this._core_transform.matrix(this.node.pv.t, this.node.pv.r, this.node.pv.s, this.node.pv.scale, ROTATION_ORDERS[this.node.pv.rotationOrder]);\\n object.matrix.identity();\\n object.applyMatrix4(matrix);\\n this._apply_look_at();\\n object.updateMatrix();\\n if (prev_auto_update) {\\n object.matrixAutoUpdate = true;\\n }\\n object.dispatchEvent({type: \\\\\\\"change\\\\\\\"});\\n }\\n _apply_look_at() {\\n }\\n set_params_from_matrix(matrix, options = {}) {\\n CoreTransform.set_params_from_matrix(matrix, this.node, options);\\n }\\n static update_node_transform_params_if_required(node, new_parent_object) {\\n node.transformController.update_node_transform_params_if_required(new_parent_object);\\n }\\n update_node_transform_params_if_required(new_parent_object) {\\n if (!isBooleanTrue(this.node.pv.keepPosWhenParenting)) {\\n return;\\n }\\n if (!this.node.scene().loadingController.loaded()) {\\n return;\\n }\\n if (new_parent_object == this.node.object.parent) {\\n return;\\n }\\n const object = this.node.object;\\n object.updateMatrixWorld(true);\\n new_parent_object.updateMatrixWorld(true);\\n this._keep_pos_when_parenting_m_object.copy(object.matrixWorld);\\n this._keep_pos_when_parenting_m_new_parent_inv.copy(new_parent_object.matrixWorld);\\n this._keep_pos_when_parenting_m_new_parent_inv.invert();\\n this._keep_pos_when_parenting_m_object.premultiply(this._keep_pos_when_parenting_m_new_parent_inv);\\n CoreTransform.set_params_from_matrix(this._keep_pos_when_parenting_m_object, this.node, {scale: true});\\n }\\n update_node_transform_params_from_object(update_matrix = false) {\\n const object = this.node.object;\\n if (update_matrix) {\\n object.updateMatrix();\\n }\\n CoreTransform.set_params_from_matrix(object.matrix, this.node, {scale: true});\\n }\\n static PARAM_CALLBACK_update_transform_from_object(node) {\\n node.transformController.update_node_transform_params_from_object();\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/obj/utils/HierarchyController.ts\\nvar HierarchyController = class {\\n constructor(node) {\\n this.node = node;\\n }\\n initializeNode() {\\n this.node.io.inputs.setCount(0, 1);\\n this.node.io.inputs.set_depends_on_inputs(false);\\n this.node.io.outputs.setHasOneOutput();\\n this.node.io.inputs.add_on_set_input_hook(\\\\\\\"on_input_updated:update_parent\\\\\\\", () => {\\n this.on_input_updated();\\n });\\n }\\n static on_input_updated(node) {\\n const parent_object = node.root().getParentForNode(node);\\n if (node.transformController && parent_object) {\\n TransformController.update_node_transform_params_if_required(node, parent_object);\\n }\\n if (node.io.inputs.input(0) != null) {\\n node.root().addToParentTransform(node);\\n } else {\\n node.root().removeFromParentTransform(node);\\n }\\n }\\n on_input_updated() {\\n HierarchyController.on_input_updated(this.node);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/loader/_Base.ts\\nvar LOADING_MANAGER = new LoadingManager();\\nLOADING_MANAGER.setURLModifier((url) => {\\n const remapedUrl = Poly.assetUrls.remapedUrl(url);\\n if (remapedUrl) {\\n return remapedUrl;\\n }\\n const blobUrl = Poly.blobs.blobUrl(url);\\n if (blobUrl) {\\n return blobUrl;\\n }\\n return url;\\n});\\nvar CoreBaseLoader2 = class {\\n constructor(_url, _scene, _node) {\\n this._url = _url;\\n this._scene = _scene;\\n this._node = _node;\\n this.loadingManager = LOADING_MANAGER;\\n }\\n static extension(url) {\\n let ext = null;\\n try {\\n const _url = new URL(url);\\n ext = _url.searchParams.get(\\\\\\\"ext\\\\\\\");\\n } catch (e) {\\n }\\n if (!ext) {\\n const url_without_params = url.split(\\\\\\\"?\\\\\\\")[0];\\n const elements = url_without_params.split(\\\\\\\".\\\\\\\");\\n ext = elements[elements.length - 1].toLowerCase();\\n }\\n return ext;\\n }\\n extension() {\\n return CoreBaseLoader2.extension(this._url);\\n }\\n async _urlToLoad() {\\n const {storedUrl, fullUrl} = this._urlData();\\n if (this._node) {\\n await Poly.blobs.fetchBlobForNode({storedUrl, fullUrl, node: this._node});\\n }\\n const blobUrl = Poly.blobs.blobUrl(storedUrl);\\n return blobUrl || fullUrl;\\n }\\n deregisterUrl() {\\n const {storedUrl} = this._urlData();\\n Poly.blobs.deregisterUrl(storedUrl);\\n }\\n _urlData() {\\n let fullUrl = this._url;\\n const storedUrl = this._url.split(\\\\\\\"?\\\\\\\")[0];\\n if (fullUrl[0] != \\\\\\\"h\\\\\\\") {\\n const assets_root = this._scene.assets.root();\\n if (assets_root) {\\n fullUrl = `${assets_root}${fullUrl}`;\\n }\\n }\\n return {fullUrl, storedUrl};\\n }\\n static async _loadMultipleBlobGlobal(options) {\\n const promises = [];\\n for (let file of options.files) {\\n const storedUrl = file.storedUrl;\\n const fullUrl = file.fullUrl;\\n const node = options.node;\\n promises.push(Poly.blobs.fetchBlobGlobal({storedUrl, fullUrl, node}));\\n }\\n const responses = await Promise.all(promises);\\n for (let response of responses) {\\n if (response.error) {\\n options.node.states.error.set(options.error);\\n }\\n }\\n }\\n};\\nvar CoreBaseLoader = CoreBaseLoader2;\\nCoreBaseLoader.loadingManager = LOADING_MANAGER;\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/loader/Audio.ts\\nvar Extension;\\n(function(Extension2) {\\n Extension2[\\\\\\\"MP3\\\\\\\"] = \\\\\\\"mp3\\\\\\\";\\n Extension2[\\\\\\\"WAV\\\\\\\"] = \\\\\\\"wav\\\\\\\";\\n})(Extension || (Extension = {}));\\nvar AUDIO_EXTENSIONS = [Extension.MP3, Extension.WAV];\\nvar CoreLoaderAudio = class extends CoreBaseLoader {\\n async load() {\\n const audioLoader = new AudioLoader(this.loadingManager);\\n const url = await this._urlToLoad();\\n return new Promise((resolve) => {\\n audioLoader.load(url, function(buffer) {\\n resolve(buffer);\\n });\\n });\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/poly/registers/nodes/types/Obj.ts\\nvar ObjType;\\n(function(ObjType2) {\\n ObjType2[\\\\\\\"GEO\\\\\\\"] = \\\\\\\"geo\\\\\\\";\\n ObjType2[\\\\\\\"CUBE_CAMERA\\\\\\\"] = \\\\\\\"cubeCamera\\\\\\\";\\n ObjType2[\\\\\\\"AUDIO_LISTENER\\\\\\\"] = \\\\\\\"audioListener\\\\\\\";\\n ObjType2[\\\\\\\"POSITIONAL_AUDIO\\\\\\\"] = \\\\\\\"positionalAudio\\\\\\\";\\n})(ObjType || (ObjType = {}));\\n\\n// src/engine/nodes/obj/AudioAnalyzer.ts\\nvar AudioAnalyzerParamConfig = class extends NodeParamsConfig {\\n constructor() {\\n super(...arguments);\\n this.url = ParamConfig.STRING(\\\\\\\"\\\\\\\", {\\n fileBrowse: {type: [FileType.AUDIO]}\\n });\\n this.listener = ParamConfig.NODE_PATH(\\\\\\\"\\\\\\\", {\\n nodeSelection: {\\n context: NodeContext.OBJ,\\n types: [ObjType.AUDIO_LISTENER]\\n }\\n });\\n this.fftSize = ParamConfig.INTEGER(128, {\\n range: [1, 1024]\\n });\\n this.output0 = ParamConfig.FLOAT(1);\\n this.output1 = ParamConfig.FLOAT(1);\\n this.play = ParamConfig.BUTTON(null, {\\n callback: (node) => {\\n AudioAnalyzerObjNode.PARAM_CALLBACK_play(node);\\n }\\n });\\n this.pause = ParamConfig.BUTTON(null, {\\n callback: (node) => {\\n AudioAnalyzerObjNode.PARAM_CALLBACK_pause(node);\\n }\\n });\\n }\\n};\\nvar ParamsConfig = new AudioAnalyzerParamConfig();\\nvar AudioAnalyzerObjNode = class extends TypedObjNode {\\n constructor() {\\n super(...arguments);\\n this.paramsConfig = ParamsConfig;\\n this.hierarchyController = new HierarchyController(this);\\n this.flags = new FlagsControllerD(this);\\n }\\n static type() {\\n return \\\\\\\"audioAnalyzer\\\\\\\";\\n }\\n createObject() {\\n const group = new Group();\\n group.matrixAutoUpdate = false;\\n return group;\\n }\\n initializeNode() {\\n this.hierarchyController.initializeNode();\\n }\\n cook() {\\n this.cookController.endCook();\\n }\\n async audioAnalyzer() {\\n return this._audioAnalyzer = this._audioAnalyzer || await this._createAudioAnalyzer();\\n }\\n async _createAudioAnalyzer() {\\n console.log(\\\\\\\"_createAudioAnalyzer\\\\\\\");\\n if (this.p.listener.isDirty()) {\\n await this.p.listener.compute();\\n }\\n const node = this.pv.listener.nodeWithContext(NodeContext.OBJ);\\n if (!node) {\\n return;\\n }\\n console.log(\\\\\\\"_createAudioAnalyzer B\\\\\\\");\\n const listener = node.object;\\n this._audio = new Audio2(listener);\\n if (/(iPad|iPhone|iPod)/g.test(navigator.userAgent)) {\\n const loader2 = new AudioLoader();\\n loader2.load(this.pv.url, (buffer) => {\\n if (this._audio) {\\n this._audio.setBuffer(buffer);\\n this._audio.hasPlaybackControl = true;\\n console.log(\\\\\\\"play A\\\\\\\");\\n }\\n });\\n } else {\\n this._mediaElement = new Audio(this.pv.url);\\n console.log(\\\\\\\"play B\\\\\\\");\\n this._audio.setMediaElementSource(this._mediaElement);\\n this._audio.hasPlaybackControl = true;\\n }\\n const audioAnalyzer = new AudioAnalyser(this._audio, this.pv.fftSize);\\n const loader = new CoreLoaderAudio(this.pv.url, this.scene(), this);\\n this.scene().registerOnBeforeTick(`audioAnalyzer-${this.path()}`, () => {\\n if (this._audioAnalyzer) {\\n this._audioAnalyzer.getFrequencyData();\\n const value = this._audioAnalyzer.data[0];\\n console.log(value, this._audioAnalyzer.data);\\n this.p.output0.set(value);\\n const average = this._audioAnalyzer.getAverageFrequency();\\n this.p.output1.set(average);\\n }\\n });\\n return audioAnalyzer;\\n }\\n isPlaying() {\\n if (this._audio) {\\n return isBooleanTrue(this._audio.isPlaying);\\n }\\n if (this._mediaElement) {\\n return isBooleanTrue(this._mediaElement.isPlaying);\\n }\\n return false;\\n }\\n static PARAM_CALLBACK_play(node) {\\n node.PARAM_CALLBACK_play();\\n }\\n static PARAM_CALLBACK_pause(node) {\\n node.PARAM_CALLBACK_pause();\\n }\\n PARAM_CALLBACK_play() {\\n this.audioAnalyzer();\\n if (!this.isPlaying()) {\\n console.log(\\\\\\\"play !\\\\\\\");\\n this._audio?.play();\\n this._mediaElement?.play();\\n }\\n }\\n PARAM_CALLBACK_pause() {\\n this.audioAnalyzer();\\n if (this.isPlaying()) {\\n console.log(\\\\\\\"-pause-\\\\\\\");\\n this._audio?.pause();\\n this._mediaElement?.pause();\\n }\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/core/geometry/Group.ts\\nvar CoreGroup = class {\\n constructor() {\\n this._objects = [];\\n this._objects_with_geo = [];\\n this.touch();\\n }\\n timestamp() {\\n return this._timestamp;\\n }\\n touch() {\\n const performance2 = Poly.performance.performanceManager();\\n this._timestamp = performance2.now();\\n this.reset();\\n }\\n reset() {\\n this._bounding_box = void 0;\\n this._core_geometries = void 0;\\n this._core_objects = void 0;\\n }\\n clone() {\\n const core_group = new CoreGroup();\\n if (this._objects) {\\n const objects = [];\\n for (let object of this._objects) {\\n objects.push(CoreObject.clone(object));\\n }\\n core_group.setObjects(objects);\\n }\\n return core_group;\\n }\\n setObjects(objects) {\\n this._objects = objects;\\n this._objects_with_geo = objects.filter((obj) => obj.geometry != null);\\n this.touch();\\n }\\n objects() {\\n return this._objects;\\n }\\n objectsWithGeo() {\\n return this._objects_with_geo;\\n }\\n coreObjects() {\\n return this._core_objects = this._core_objects || this._create_core_objects();\\n }\\n _create_core_objects() {\\n if (this._objects) {\\n return this._objects.map((object, i) => new CoreObject(object, i));\\n }\\n return [];\\n }\\n objectsData() {\\n if (this._objects) {\\n return this._objects.map((object) => this._objectData(object));\\n }\\n return [];\\n }\\n _objectData(object) {\\n let points_count = 0;\\n if (object.geometry) {\\n points_count = CoreGeometry.pointsCount(object.geometry);\\n }\\n return {\\n type: objectTypeFromConstructor(object.constructor),\\n name: object.name,\\n children_count: object.children.length,\\n points_count\\n };\\n }\\n geometries() {\\n const list = [];\\n for (let core_object of this.coreObjects()) {\\n const geometry = core_object.object().geometry;\\n if (geometry) {\\n list.push(geometry);\\n }\\n }\\n return list;\\n }\\n coreGeometries() {\\n return this._core_geometries = this._core_geometries || this._createCoreGeometries();\\n }\\n _createCoreGeometries() {\\n const list = [];\\n for (let geometry of this.geometries()) {\\n list.push(new CoreGeometry(geometry));\\n }\\n return list;\\n }\\n static geometryFromObject(object) {\\n if (object.isMesh || object.isLine || object.isPoints) {\\n return object.geometry;\\n }\\n return null;\\n }\\n faces() {\\n const faces = [];\\n for (let object of this.objectsWithGeo()) {\\n if (object.geometry) {\\n const coreGeo = new CoreGeometry(object.geometry);\\n const geoFaces = coreGeo.faces();\\n for (let geoFace of geoFaces) {\\n geoFace.applyMatrix4(object.matrix);\\n faces.push(geoFace);\\n }\\n }\\n }\\n return faces;\\n }\\n points() {\\n return this.coreGeometries().map((g) => g.points()).flat();\\n }\\n pointsCount() {\\n return ArrayUtils.sum(this.coreGeometries().map((g) => g.pointsCount()));\\n }\\n totalPointsCount() {\\n if (this._objects) {\\n let sum = 0;\\n for (let object of this._objects) {\\n object.traverse((object2) => {\\n const geometry = object2.geometry;\\n if (geometry) {\\n sum += CoreGeometry.pointsCount(geometry);\\n }\\n });\\n }\\n return sum;\\n } else {\\n return 0;\\n }\\n }\\n pointsFromGroup(group) {\\n if (group) {\\n const indices = CoreString.indices(group);\\n const points2 = this.points();\\n return ArrayUtils.compact(indices.map((i) => points2[i]));\\n } else {\\n return this.points();\\n }\\n }\\n static _fromObjects(objects) {\\n const core_group = new CoreGroup();\\n core_group.setObjects(objects);\\n return core_group;\\n }\\n objectsFromGroup(group_name) {\\n return this.coreObjectsFromGroup(group_name).map((co) => co.object());\\n }\\n coreObjectsFromGroup(group_name) {\\n group_name = group_name.trim();\\n if (group_name !== \\\\\\\"\\\\\\\") {\\n const index = parseInt(group_name);\\n if (!CoreType.isNaN(index)) {\\n return ArrayUtils.compact([this.coreObjects()[index]]);\\n } else {\\n return this.coreObjects().filter((core_object) => {\\n return CoreString.matchMask(group_name, core_object.name());\\n });\\n }\\n } else {\\n return this.coreObjects();\\n }\\n }\\n boundingBox(forceUpdate = false) {\\n if (forceUpdate) {\\n return this._bounding_box = this._computeBoundingBox();\\n }\\n return this._bounding_box = this._bounding_box || this._computeBoundingBox();\\n }\\n center() {\\n const center = new Vector3();\\n this.boundingBox().getCenter(center);\\n return center;\\n }\\n size() {\\n const size = new Vector3();\\n this.boundingBox().getSize(size);\\n return size;\\n }\\n _computeBoundingBox() {\\n let bbox;\\n if (this._objects) {\\n for (let object of this._objects) {\\n const geometry = object.geometry;\\n if (geometry) {\\n geometry.computeBoundingBox();\\n if (bbox) {\\n bbox.expandByObject(object);\\n } else {\\n if (geometry.boundingBox) {\\n bbox = geometry.boundingBox.clone();\\n }\\n }\\n }\\n }\\n }\\n bbox = bbox || new Box3(new Vector3(-1, -1, -1), new Vector3(1, 1, 1));\\n return bbox;\\n }\\n computeVertexNormals() {\\n for (let object of this.coreObjects()) {\\n object.computeVertexNormals();\\n }\\n }\\n hasAttrib(name) {\\n let first_geometry;\\n if ((first_geometry = this.coreGeometries()[0]) != null) {\\n return first_geometry.hasAttrib(name);\\n } else {\\n return false;\\n }\\n }\\n attribType(name) {\\n const first_core_geometry = this.coreGeometries()[0];\\n if (first_core_geometry != null) {\\n return first_core_geometry.attribType(name);\\n } else {\\n return null;\\n }\\n }\\n objectAttribType(name) {\\n const first_core_object = this.coreObjects()[0];\\n if (first_core_object != null) {\\n return first_core_object.attribType(name);\\n } else {\\n return null;\\n }\\n }\\n renameAttrib(old_name, new_name, attrib_class) {\\n switch (attrib_class) {\\n case CoreConstant.ATTRIB_CLASS.VERTEX:\\n if (this.hasAttrib(old_name)) {\\n if (this._objects) {\\n for (let object of this._objects) {\\n object.traverse((child) => {\\n const geometry = CoreGroup.geometryFromObject(child);\\n if (geometry) {\\n const core_geometry = new CoreGeometry(geometry);\\n core_geometry.renameAttrib(old_name, new_name);\\n }\\n });\\n }\\n }\\n }\\n break;\\n case CoreConstant.ATTRIB_CLASS.OBJECT:\\n if (this.hasAttrib(old_name)) {\\n if (this._objects) {\\n for (let object of this._objects) {\\n object.traverse((child) => {\\n const core_object = new CoreObject(child, 0);\\n core_object.renameAttrib(old_name, new_name);\\n });\\n }\\n }\\n }\\n break;\\n }\\n }\\n attribNames() {\\n let first_geometry;\\n if ((first_geometry = this.coreGeometries()[0]) != null) {\\n return first_geometry.attribNames();\\n } else {\\n return [];\\n }\\n }\\n objectAttribNames() {\\n let first_object;\\n if ((first_object = this.coreObjects()[0]) != null) {\\n return first_object.attribNames();\\n } else {\\n return [];\\n }\\n }\\n attribNamesMatchingMask(masks_string) {\\n const masks = CoreString.attribNames(masks_string);\\n const matching_attrib_names = [];\\n for (let attrib_name of this.attribNames()) {\\n for (let mask of masks) {\\n if (CoreString.matchMask(attrib_name, mask)) {\\n matching_attrib_names.push(attrib_name);\\n } else {\\n const remapped = CoreAttribute.remapName(mask);\\n if (attrib_name == remapped) {\\n matching_attrib_names.push(attrib_name);\\n }\\n }\\n }\\n }\\n return ArrayUtils.uniq(matching_attrib_names);\\n }\\n attribSizes() {\\n let first_geometry;\\n if ((first_geometry = this.coreGeometries()[0]) != null) {\\n return first_geometry.attribSizes();\\n } else {\\n return {};\\n }\\n }\\n objectAttribSizes() {\\n let first_object;\\n if ((first_object = this.coreObjects()[0]) != null) {\\n return first_object.attribSizes();\\n } else {\\n return {};\\n }\\n }\\n attribSize(attrib_name) {\\n let first_geometry;\\n if ((first_geometry = this.coreGeometries()[0]) != null) {\\n return first_geometry.attribSize(attrib_name);\\n } else {\\n return 0;\\n }\\n }\\n addNumericVertexAttrib(name, size, default_value) {\\n if (default_value == null) {\\n default_value = CoreAttribute.default_value(size);\\n }\\n for (let core_geometry of this.coreGeometries()) {\\n core_geometry.addNumericAttrib(name, size, default_value);\\n }\\n }\\n static clone(src_group) {\\n const new_group = new Group();\\n src_group.children.forEach((src_object) => {\\n const new_object = CoreObject.clone(src_object);\\n new_group.add(new_object);\\n });\\n return new_group;\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/operations/_Base.ts\\nvar BaseOperation = class {\\n constructor(_scene, states, _node) {\\n this._scene = _scene;\\n this.states = states;\\n this._node = _node;\\n }\\n static type() {\\n throw \\\\\\\"type to be overriden\\\\\\\";\\n }\\n type() {\\n const c = this.constructor;\\n return c.type();\\n }\\n static context() {\\n console.error(\\\\\\\"operation has no node_context\\\\\\\", this);\\n throw \\\\\\\"context requires override\\\\\\\";\\n }\\n context() {\\n const c = this.constructor;\\n return c.context();\\n }\\n scene() {\\n return this._scene;\\n }\\n cook(input_contents, params) {\\n }\\n};\\nBaseOperation.DEFAULT_PARAMS = {};\\nBaseOperation.INPUT_CLONED_STATE = [];\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/operations/sop/_Base.ts\\nvar BaseSopOperation = class extends BaseOperation {\\n static context() {\\n return NodeContext.SOP;\\n }\\n cook(input_contents, params) {\\n }\\n createCoreGroupFromObjects(objects) {\\n const core_group = new CoreGroup();\\n core_group.setObjects(objects);\\n return core_group;\\n }\\n createCoreGroupFromGeometry(geometry, type = ObjectType.MESH) {\\n const object = BaseSopOperation.createObject(geometry, type);\\n return this.createCoreGroupFromObjects([object]);\\n }\\n createObject(geometry, type, material) {\\n return BaseSopOperation.createObject(geometry, type, material);\\n }\\n static createObject(geometry, type, material) {\\n this.createIndexIfNone(geometry);\\n const object_constructor = OBJECT_CONSTRUCTOR_BY_OBJECT_TYPE[type];\\n material = material || CoreConstant.MATERIALS[type].clone();\\n const object = new object_constructor(geometry, material);\\n object.castShadow = true;\\n object.receiveShadow = true;\\n object.frustumCulled = false;\\n object.matrixAutoUpdate = false;\\n return object;\\n }\\n createIndexIfNone(geometry) {\\n BaseSopOperation.createIndexIfNone(geometry);\\n }\\n static createIndexIfNone(geometry) {\\n CoreGeometryIndexBuilder.createIndexIfNone(geometry);\\n }\\n};\\n\\n// ../../../node_modules/@polygonjs/polygonjs/src/engine/nodes/sop/_Base.ts\\nvar MESSAGE;\\n(function(MESSAGE2) {\\n MESSAGE2[\\\\\\\"FROM_SET_CORE_GROUP\\\\\\\"] = \\\\\\\"from set_core_group\\\\\\\";\\n MESSAGE2[\\\\\\\"FROM_SET_GROUP\\\\\\\"] = \\\\\\\"from set_group\\\\\\\";\\n MESSAGE2[\\\\\\\"FROM_SET_OBJECTS\\\\\\\"] = \\\\\\\"from set_objects\\\\\\\";\\n MESSAGE2[\\\\\\\"FROM_SET_OBJECT\\\\\\\"] = \\\\\\\"from set_object\\\\\\\";\\n MESSAGE2[\\\\\\\"FROM_SET_GEOMETRIES\\\\\\\"] = \\\\\\\"from set_geometries\\\\\\\";\\n MESSAGE2[\\\\\\\"FROM_SET_GEOMETRY\\\\\\\"] = \\\\\\\"from set_geometry\\\\\\\";\\n})(MESSAGE || (MESSAGE = {}));\\nvar INPUT_GEOMETRY_NAME = \\\\\\\"input geometry\\\\\\\";\\nvar DEFAULT_INPUT_NAMES2 = [INPUT_GEOMETRY_NAME, INPUT_GEOMETRY_NAME, INPUT_GEOMETRY_NAME, INPUT_GEOMETRY_NAME];\\nvar TypedSopNode = class extends TypedNode {\\n constructor() {\\n super(...arguments);\\n this.flags = new FlagsControllerDBO(this);\\n }\\n static context() {\\n return NodeContext.SOP;\\n }\\n static displayedInputNames() {\\n return DEFAULT_INPUT_NAMES2;\\n }\\n initializeBaseNode() {\\n this.flags.display.set(false);\\n this.flags.display.onUpdate(() => {\\n if (this.flags.display.active()) {\\n const parent = this.parent();\\n if (parent && parent.displayNodeController) {\\n parent.displayNodeController.setDisplayNode(this);\\n }\\n }\\n });\\n this.io.outputs.setHasOneOutput();\\n }\\n setCoreGroup(core_group) {\\n this._setContainer(core_group, MESSAGE.FROM_SET_CORE_GROUP);\\n }\\n setObject(object) {\\n this._setContainerObjects([object], MESSAGE.FROM_SET_OBJECT);\\n }\\n setObjects(objects) {\\n this._setContainerObjects(objects, MESSAGE.FROM_SET_OBJECTS);\\n }\\n setGeometry(geometry, type = ObjectType.MESH) {\\n const object = this.createObject(geometry, type);\\n this._setContainerObjects([object], MESSAGE.FROM_SET_GEOMETRY);\\n }\\n setGeometries(geometries, type = ObjectType.MESH) {\\n const objects = [];\\n let object;\\n for (let geometry of geometries) {\\n object = this.createObject(geometry, type);\\n objects.push(object);\\n }\\n this._setContainerObjects(objects, MESSAGE.FROM_SET_GEOMETRIES);\\n }\\n _setContainerObjects(objects, message) {\\n const core_group = this.containerController.container().coreContent() || new CoreGroup();\\n core_group.setObjects(objects);\\n core_group.touch();\\n this._setContainer(core_group);\\n }\\n static createObject(geometry, type, material) {\\n return BaseSopOperation.createObject(geometry, type, material);\\n }\\n createObject(geometry, type, material) {\\n return TypedSopNode.createObject(geometry, type, material);\\n }\\n static createIndexIfNone(geometry) {\\n BaseSopOperation.createIndexIfNone(geometry);\\n }\\n _createIndexIfNone(geometry) {\\n TypedSopNode.createIndexIfNone(geometry);\\n }\\n};\\n\\n// src/engine/nodes/sop/AudioAnalyzer.ts\\nvar AudioAnalyzerParamConfig2 = class extends NodeParamsConfig {\\n constructor() {\\n super(...arguments);\\n this.url = ParamConfig.STRING(\\\\\\\"\\\\\\\", {\\n fileBrowse: {type: [FileType.AUDIO]}\\n });\\n this.listener = ParamConfig.NODE_PATH(\\\\\\\"\\\\\\\", {\\n nodeSelection: {\\n context: NodeContext.OBJ,\\n types: [ObjType.AUDIO_LISTENER]\\n }\\n });\\n this.fftSize = ParamConfig.INTEGER(128, {\\n range: [1, 1024]\\n });\\n this.outputMult = ParamConfig.FLOAT(0.1);\\n this.average = ParamConfig.FLOAT(1, {\\n cook: false\\n });\\n this.play = ParamConfig.BUTTON(null, {\\n callback: (node) => {\\n AudioAnalyzerSopNode.PARAM_CALLBACK_play(node);\\n }\\n });\\n this.pause = ParamConfig.BUTTON(null, {\\n callback: (node) => {\\n AudioAnalyzerSopNode.PARAM_CALLBACK_pause(node);\\n }\\n });\\n }\\n};\\nvar ParamsConfig2 = new AudioAnalyzerParamConfig2();\\nvar AudioAnalyzerSopNode = class extends TypedSopNode {\\n constructor() {\\n super(...arguments);\\n this.paramsConfig = ParamsConfig2;\\n }\\n static type() {\\n return \\\\\\\"audioAnalyzer\\\\\\\";\\n }\\n initializeNode() {\\n this.io.inputs.setCount(1);\\n this.addGraphInput(this.scene().timeController.graphNode);\\n this.io.inputs.initInputsClonedState(InputCloneMode.FROM_NODE);\\n }\\n cook(input_contents) {\\n console.log(\\\\\\\"cook\\\\\\\");\\n const core_group = input_contents[0];\\n const objects = core_group.objects();\\n if (this._audioAnalyzer) {\\n const outputMult = this.pv.outputMult;\\n this._audioAnalyzer.getFrequencyData();\\n const data = this._audioAnalyzer.data;\\n const maxCount = Math.min(objects.length, data.length);\\n for (let i = 0; i < maxCount; i++) {\\n const object = objects[i];\\n const dataEntry = data[i] * outputMult;\\n object.position.y = dataEntry;\\n }\\n const average = this._audioAnalyzer.getAverageFrequency();\\n this.p.average.set(average);\\n }\\n this.setCoreGroup(core_group);\\n }\\n async audioAnalyzer() {\\n return this._audioAnalyzer = this._audioAnalyzer || await this._createAudioAnalyzer();\\n }\\n async _createAudioAnalyzer() {\\n console.log(\\\\\\\"_createAudioAnalyzer\\\\\\\");\\n if (this.p.listener.isDirty()) {\\n await this.p.listener.compute();\\n }\\n const node = this.pv.listener.nodeWithContext(NodeContext.OBJ);\\n if (!node) {\\n return;\\n }\\n console.log(\\\\\\\"_createAudioAnalyzer B\\\\\\\");\\n const listener = node.object;\\n this._audio = new Audio2(listener);\\n if (/(iPad|iPhone|iPod)/g.test(navigator.userAgent)) {\\n const loader = new AudioLoader();\\n loader.load(this.pv.url, (buffer) => {\\n if (this._audio) {\\n this._audio.setBuffer(buffer);\\n console.log(\\\\\\\"play A\\\\\\\");\\n }\\n });\\n } else {\\n this._mediaElement = new Audio(this.pv.url);\\n 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dWo+3dLcBPV7Jxhl5tsF3zBLTIaVR91d9s1r9m3QJf+whX1MCR9hcZlGt8xVrLvHYsWbhBCazN5EqvcpxYAdfq1qf7lT7Rafor03gLyFPr3zSt0bsf6ebMJX/gpX703vWO7fEtJ+4U0L/vULw2M3zNdQsge1y5reTvLYAghhBBC9qGATgghhBBCyA7DucNhTv+o4WbWuNrNzqp3RwXtLIo13OwSPOCuptziCmJCxcrdLFyv4UlEmSBgXx2Zhb05Ezl8De6en1ahttiwTtxqIpdmt5g1aVT6oj56cJfm1QKDm2WnrjlKH3+M9FIitdlZ/cvCDVdvMfCt3L5q4pKIXs8kfgZ5YOhDg0KsLcPou7f30nXf3fsaB5knI9rMP7U4qrhj4cOtRbY1Czq2hsPdw9ucd3uq+4EfQ+HEhb+nKkWL1bvc+uj3Et+PUJeD3KSdd2nd67Zrt7d1H/Ladmf1fM26OJ6FTq5lfH+s711yA+7VfdS/uWn5TgghhJA3DAV0QgghhBBCjnDUunOpCcwnviV+C3pI3YY76sAqXbDebQK5lvgEggQTDdSlUKU3t5+v0+RgIvJcbNirjyeyazxrFQ28wGPbLrfPkNZksvdqXBx5IlggKlDRnG51Y+HOqa/uC1p8ptp2z77875oyVCtVVaj2W9dLeO61TJ0f1AaQRcmWt7aiI7rhKltrRqo+dkl8X67PuKXt3N7eeml8Fc/3UAP6iorVIbXf+l7VWqbXv4d8r7TIwW1jRYtdQo3syyaKrebEcmricHPH+2Md3MbdsuLeihWd5876WivjOjOz8HndiHuqzl13ay/jBkSgIrCN6vN3yaOIXFuPUp+pSl40IXL9khCBIKXwwvLV0H3XwUt6EEiy/Li8q0zG9b71lxj6BQRX6OgaxtpFAWfFalf0PhmeuiJ5TvZGiUtu677Xhlu+2gkhhBBC3ggU0AkhhBBCCDlAnQQsWnPUDd3t6feZfh7Fc39mtZQL1Y9GC0EnugxuJ8ipj0fatW5CVIpoEeO0vEf13mVqhgk/F7ztUbVAVeDshGDtJZUsFLtEnPgLAJISDkgl6zzExQaCWk9axJuVu4nn8b7Fa/ezu53jnEOI5GUPLjPHMGEvNDrbVr6rD9VqCVonuyVflxxJXyNLt7WdojbK6TqFaOn3ysbTGs5VwXw/q4Koy1MTKb+DHKBW/62d9GOHtZA46LS8iHcfFs2dW/rn2o9jY4DYsvI1dfej4LnnthIkvAiu/S+9oG8jPujZN7fFOL+KWxWQpOFJqrsprUl7BbiMG0kUmhK6ut01iZb6YeMnsN2k5kpCsWD3BfLxtjyLWemXtpY/BElOyEsv3DgrUvx7Eb3F5Uuyu3bgWndfjNFr1ylt4dM+3kd9Qqb53zCU0BKdXIsfdW8VwO8RwimiE0IIIeQtQwGdEEIIIYSQo0jTJva2vJ1NVB7Fn6XdCzYrpWCWUn9NVJplcpeWdNckuFv4yeVLM6K6dByjakh6sS5z0foCVgk7a1CHczCPZchWvbfnHuWeXpRfhe2e+wvMPvd7FPjMXOEeOse17hu5VZmqufBC8HPhxcYoIq+U2VmnvCf9KNsv0rzDPdbrTF58fu5NWXZGDZlc8/faAhsZPYlb8OQt1WHJlbfF5m5dbBPq4kQVgbtFSAfRreSr7KrhRf76rP37JQ4RmAxvIR8Sb8WyxAU98f6ue82TLZcJj+w7nZBAyHdj+vvv2jhAEZ0QQgghbxMK6IQQQgghhNzIrefGHraIdta9cmTL2eJ36lZnRdudKe4s/3SMoRoUx6zV+5MK0OHLTWTBoVljxoUJOW8C6UQgNF+TCovCyEwoebrJ3j3b0xXDKofp5e+H1r815zcpjIrdbbEv5uBGrMHeSBU8b8z7TZkPjbA528PvhcS4XOTpWFpKXwpwzQqVaQIvJ6/csuBpFMnbmDP0+tmiJP+lbtG+488J5n2k5b3gd4I4IqI701KtZuTuvXBpoCzhddvgreTd26T379zNmlsham3Ziea7ojgO3ttHJt8OeG6vTJ0tOBleqXWRRL1Zwg5hriWMT9dapL/cchXyUty+qPO28LFFUkQnhBBCyFuEAjohhBBCCCFXUAzu6vcnixdwmqMXMV9+qltEDk7QNz/3bjE7aA7LlMx+NgREL2bcajv7KiZ8X0Um3gi3Ct8W3P7dLP7fYa73UgrDyw8xbxzpmt3K2jxSdeoioC89wWuu40h13Y4JfkDU+s/OY5eQXh2HZ24BsJU9G8Rpw3vtKQjwB3LauZ+ye+xU9+WwMl/zMVtoNqSzCkwIIYQQQgh5VVBAJ4QQQggh5ACma0er84vakxMellPm3WS61GDZes1EjVvsJGMyXuAer638Arhw9qrWe7M07tE0/fahg12iGVtWUcZb07t8RFF9yPnC3RSul9EYuwJfJ7g8xTbk11ieDYKzyNUi9K2Wbosc3RhMke7eOeHG8E+gqd3W1xbiLTlEZ4HeXWuOPct+WYjnQ3Oo6rQb26D5HeGuVhE85GM0LHdqubeM3gsYMrjJuRawLvhSuDLPCyblH+oRHfG94SzSXdCJAffNrPrKWO8xAyFfl/rOIr91Id6F4EeIY+1yARt1e0IIIYQQQg5DAZ0QQgghhJAnZm9C/OJcu2qeDO9U46ed9V6L57q4vhe+F8/nccvVwt4o9ozf9zhuNX8xpieI4za0bNksL2Gt+Er2W70lC3KPIKwCeZLlBzfg+/2zpvsCaf6RuNBXVtVbrc93IpkO/53O3azGD/VZE+GlWZ8Dcdv0cXeV2fnl1XK97Mve9RxbeCTte8cGSPIFDIJ5SM8b4Mv0xpXUfI2XI92brCyi8xfjWoN4fSbIP+1iIUIIIYQQQsj3gAI6IYQQQgh5O7yQjliTPqDLSZzg7+IJNnnRks0cql1Z9TtMszdxWafXL4voc/HcX2/cJgwuRZPIoM7n+rv5HOsa744V5aHgN4SbqC0rA9Dvjt/teeXFdiYYg93dXWct6RJVq7unwnT95C5Fu0Fv3/79KSzQMW/366htEHqqp/ZnpH8xdM1vNsa3y4OI3vp66PdapOm4R7p1kirq6vAIe71XqtV3n4cLRVzQb+3uUlHfpAQiYYSw99zWC/nNx2WT/Lv7y4Z5uWX6tWUhiuduQcMs3Epg37t2N4sdY2K7fBG4aoAQQgghhLwRKKATQgghhBBygKea843xhI1X8/+ngvHTCKmDbW0nzNRc7CuiE/E8ayBOCPH7t6tXU67M72R7+8vcYYE8xvTs4d+6vnBvO71FOO+48PiHe+HYgWss/qMl6TrsPEe1a5U+JO68gVoPQbCr62sWVrB76wd0+BYF9P6u7/qXauWSUEguMxNeY5My8Ts/Z+1E9c56O1qk18aTb1S/T7HbRG943gm1gjb+5/vasizb7Yk/RZ5nL2TtvQz3d9zTKr+Qhe/JLW9PQgghhBBCSIYCOiGEEEIIeVM89yTwMAF9w4y36RYWvpfI0G2Pq/5vJ0r4OzcSlJhmbR69za0Bq38vkquJ/r4Q4fsdluBV3JdRirhk4W3a/UtxryG054U2FR+426p/L+7gmJV4T/y2+6LoBDuvk7mlH9NI6zqQoa3N0cXn2ufiqri2Xu+NsWqxUo4x2LUkeRvt462l1FC3I8VSZl8vAwiLflIfu4t5LtjH9N4W2mU8lmFPRFXEBUYtru69EeJr6UjnH8iLOFSkvVdKB7Bd26Wmod39m/DdaGKunS3PpdrW1zJJeW+cS7uQUDbRzr20BL91gBfJjXR4+Y2J6eL7MuqFW4vjNbXxl/w9RQghhBBCyGuHAjohhBBCCCEHuHWiuYqoCzV3PFtWe29mIY77NnK/JJbPLNNzhmQpjvfbtpc4vpNiXc+GP8jT6bwvabdXzkC/QXZ4mvPfb+PwwgFtItlcvp0EOZSDXnC2NI6EVyc/HylDjPee1nLMEHhdQxJEyFXoWcL3tfKdXGsYt2whzEy4LE8rrrnpfL5B4X2lT9cFEyr9+Dtd29GWgnhRufa1HE19n8jKPcnHrQvDhnIFsb9ZuGveWSG+7M6aRWzR+JAnX/uciyV484NX6DZWSDzffBJslp010ULdrVmgSTghhBBCCCGvGwrohBBCCCGE7OC3oj064d2JCBMLwjhBL1WAbn+8gaDkfaWhN064e5G7z4Y2D+VT2836Rcq+vFHkycbn0UY1cr9KYFWvTr2YbZVrSXWayx0aS7OivaMMNyRuolgu97jF/nMwWNHKvBbsWgrGrE1Ydm0b69Zg5Y2t6do2X9PRPqbtcATOfnuuaU7p+vytxxVYRHc86ktpr+/u9+R4bWgfC2HfP7++JYTwQTQeti2vDWoRfup5ntdL168l7lgwjE2LMajWjQm5q1Ue9g6pfVDc+NACtjrsF434fPQ5tNDm/5YambSo+OyG6+VdVitKS+ZM0LYXXzDXvnuhh8uilj/i+l1J2ie5Hn+aNf3w3mlRrX83PJN4Louz0J8xC4QQQgghhLxZKKATQgghhBBylAMierS+rdaCeiF4Va9G8S5fvl0JzlrB1l/wX7RN9kdL9GxAKE4+X2diJhSZQHPrZP1M1Gvyj/Nn4sq1FoUXuCfvt6XXk+v/+4rnJrJMtdfJ4oqu3uunNLeshadLxp2CFvZaY88uvzFO93kx/GS3hkt5qHm9Y+uDO5vqk/G07X0qKw4sn7XM29tuKt02+MdytlogcikO8zEeezHNzhixoA2cs8FTQ75EijW3eZEuuNel5+4ml7dem5YLIC7RBNpVAcdos/Csrez1hjYP6Ld995Vg7rveKU6bD+sfRlYC+NEMuGLVrenDGPecxI0ACCGEEEIIIXMooBNCCCGEkNfPZML3uUTNKNz6a9N5dR2vV/FcJ5PXTa/LZ9d2iZpkLTsqzGXUiYLtWsyGNr8xrAiGrdwXRBnKhKlbn5e4vFksbWPzsK17Xa0QrO6uTXwo5tyi83sRxcAD6zbm8UzE3CRFQnPbp+dttvNz2uAbcPt+Kf1zqLRrn/nQZ5zAdKTlx76pExH1kkbm45BFwhfzIn0fuKYObt1hooaHtys+mv6lZTHFVxkGFut7Rsvd3W+N2kQPCorL8lzYYkDShftxq3nDusDm8qqApOZ7w9zCt8Zdwqzv6mTxSlN4LevWS0WkWU2rVEPttthJXFuYCeptSUlb9nL9QqEW16Lt6rx1Kdrx49rVu7j2UPLUnaHuUr5DBJZafO0syFcs1waszkxwl5cLPnx/ec4VWiHJl/gdddvKKEIIIYQQQp4fCuiEEEIIIeTN8JLzrV6I8O6Zv86t/edFZv5U79HPl+G9tXk7I330mM86DwLpc55HPhE5TETfS0MOiv57vMY5/t26X5xXXy9ZHMG9TOtiDWjw14T5p6i7W+K45Zl3Mm9Zb3Kkf8/uP0W5bcMJE62P9CHB9enrBTHrQnO6m6NlW+Xh4vO4+mGUUd4LnNYW/EoMlxHRrSvI8Az26q0rkLSXTBWOrRzx7PNRpa2W2WHdUP85WqDP9N/VONEtMnFxxe3f6yigOhVPi/bf+y4JC6RUZ34ITfDuc3fzUQla0lStcV9Y39C74/UYeNWX7F638EG7IHv1HrNxrfs1sLeogBBCCCGEkNcGBXRCCCGEEPKm2Lfm+07plS+H0p5NqtuEvV20D7c9dufPKTf50so8U3ednvkEutQ0qlXiAVFC3N/u+jSoTAXw65G5axBYvFXjeFb60aTimcw1sQm6ui23FVvExC1B3rJZ6+4EuQ068W6RwkzTEbM+71S3UlPi3eqesWu3u4wVdns3VWxbH8e9izAuNcEmJIaHX75+VMFZUC2VUwhr8f+iesVqmZBHbTWf207ZZSGFhSC2MER6/TW3mytPshbXSFVb+p0quxDoDor6Xbgrn+NKtI/icPS26pMyva71r7jvPsww3pzdfdtmvTSCQWx3n3KS7rKr+txuurjc4pTl6gUpeYrj42K83EU68d0ffxG062Z8XbaTVxvnS+l8nxAItlacei9BsYW3ieU75WhKHlrv9eUQKMaSzYR8jBUexrVVOxqSMLflbUZoPN1PgVYpqOeOHFyZckkkvxQ2p6/dM91pVRevXENNX67LN3m7HH1HEEIIIYS8ZiigE0IIIYQQcgAJwkE3M29z0m5bbHNXXaQTQC1kEWuKKCfah/PmoSKnceLZa+1QZ1nXeYGIIE2UK5MktDqeZpI8ZDF8OY4FSenC/suTRQsmg3l98CqsPryApC3eUbGLz6yIWgvFcGo9absAiOanIgnVyjOc0dwLTqOQFGMXtYUMvfTozz/Pt7tIomMLAAAgAElEQVTlFM+OKrApan3WR3vhIXY7+S/b+k747rtUIbTtzCA4qWITwSdRfFDBqfbjrKc+APhQMv3lhtqz59zlZhD+In17s+2992XFmGb7rk6sHLTDEKmGbKZobXwp6xOOWrlfrJZrw9lzngToFikAULddvAiQd3NPXcS2c4DVUfIR+PTDIqpm1R3GGslbxUvxq8hxJyQkSU2Y1ctCa1d2J6j6CqjieXCLc2eBLLQSV8HSXixIpU5sDFJoG+fcoo/d5xmeg/VTf1+Dv+797P7Wths/L6TrXu7oYx29xnhrugmAplL3+YHFnSCGnSGsDDW+rtP2DXvy0m3NTLtbXbG7cTNUCIXQPzU37fZQ2zKXSxBCCCHk7UIBnRBCCCGEvElebD7XTU5XMUGzBDCIq17QLt+rzuFn+tVN8o8KAIB+nn86Iak+Xou2iDJVJF2IuauyPgULUe0o15/MO4/l1lBBzpwbDMadBMxvETS7axPBrA+bRRVJQBrsMtc5Ffd9RqcBRW2kKFtJ0LQY8X6P1188I/uq7blLUqI+nrmwmUKe6nH3Nd83PnNtefDxfbYOhlzbn2ZKpeX/QDqTYEHZK+NKUWL9E1Yo3kvCZ90gIvhJgS/S2mZctzET1Jf5cQKd7Nwf/VvetV7uhkHZEXGBuoLj0mOLfa9q2b3qvGQV/WrL/nb+eF+mmlwpXG1v2o8ZqQQ4WV6D0KlAWUBlFaRdvdXx3i10EfcQJPV58WkPbsTxrLgm75PujO6Je6iQPvRwvdd9W3uumvosGktnhSAvDCoe1fIZhHaT6LvzzjWkraiLAmbp1OxMO+6Y3m7+tURUd5bRtf8wnsbKqptdxOcxSVdQ3knqW5lPa90B730LU0J9u9x8VAJKuxGK6IQQQgh5u1BAJ4QQQggh5AakiuJhctldr24frlyTmf/JxL8PE2ex/+hTkk8inR9RD3fCHgk6TDAvBPWruCPfh+MvX6YaT0k/CtO7Ufq2vBCd7t2KfUgzJHdNfnfjXcQzPNonSs/zswK/em1tomt5C/cvQSyP+VrqnI6Y/Wv9bzCxf/Qk2BEnlzFeh1bz7Kfn1l4cNf0EJ/g7D36MGoR8E8FN4K3vnLJQQbMVd67j/pz02YKFoYpm77CFXwnf7xlbgSx+53Zx/SKrWfomns/KXq+HvuRFdW9d78NGokA+LEgKfof3uNrvh/zl6valQy5y/GGLiLjIyBZP6LAaghBCCCGEEDKDAjohhBBCCHk77AjTR8i7I984428T3nAT4XAnBmsRNYq/QVR34cwK2ebBfXw+SLUu86buvjw+hFmqlk9FL+x+Ty32tXN12aOoFBc8oF9AodBmXhoEHbm4+/xECAGgKlDtz9ruA/bhNJbyUqGbEevaKvdysst4V9cOdVtnJlvPRF5kMoqU1sUnOv5hZlaxrS/NVsTAtYU17xX4vMhQ68dZPI+pzYa+WVrOEDp/Ok/L9G+opJh2HYu6vfR7D/vP3j30nSyth+9iYdzvpL5I57KA6C3P/eclElxduBS34E9nDxS5ndv7QGGieXuoUm7GhRxZUHY7nFjaIu14Brum/qT31tJue0fcskeIlBSzJXrOxS2KrvQdp8anXUsyC39VrVvr+zqJY9q15dnL+bS9lt8Aq8Uxt2Dtorjas54dZzFJsx8v3f4A0l/3be/a/NWfOH/mHyOEEEIIIeRNQQGdEEIIIYS8OY5aBg/h7p257XSXIMKsrI6r4Nq2mPXXO1He3fJGYnuWflGs8dexuPecvGQ+eknugH9pMkEUzL0poYTC2LOqwqs2i9shHp85f726nTnkal/pI6wq/JJafiS9qNLdkI2LYbSvv6e2XL+Enddsgtx4PwtyXsC8xEo8f0reb1kdm6W1TP+pRC0JI6wsvq8jOOx9FPHGcXQR8khGnoUsegMqrTPZWN9JobUt9uUW5C3i/S4D4oYPwAI0WVn8+0bGGr+qdqT+uZK9N9YVScd2q17mbUlZvdVPJ6Jfyt6wkCbkfshCy0aXfoughZYtu+/d3To3H2nPtCbYhPA+S32C/Rg3D+NGYtzShzRWFCGEEEIIIW8ACuiEEEIIIeRNIe7freFvQd1fL363r+FeTctMCYuVnb+vkxOenWArflJbers6zyBSe8tzNzv/EvPX1+iy04COmxZNyETwnlrlaa9ODYcr9/noz5pvFnZ1i+X6HDsTvkkGayzdtdrGD2sVUcm9vraqhWBEumbZaSlHkzsqgNc8nGS8PknGZ7eTeO4SpdoD0KL8WE+1tqO228N3EmTdeo1dPmg+X/s//6//GwCQypYH/+d//b/499Em4A6Ovrm/zvrUXiTa+1HNFR7reQhmw2zpYHWb6iTdWDfJYJ/4yTvHtGr3XyyIctuDdB+2k3zXrSfNJKYoZYsFvzjM+pqJ6FqyYxbpJoXbgp0uWy4NUc35Us2W9bb4Y1N0q3/sY1L3+23xPhH9noVtFrY/Y1lcHXZLm1rS9l4QxJYx5nR4f0QPXdLdM9CVx83a8K2W/315xPJV9vm3nQesrfj+tE1STG6rFLPWrwUK3Py0dNrVCCGEEEIIebVQQCeEEEIIIeQIpmjFrbMnwnm9oDvuieX5oJqF7yLjVsAXEVmKUa+dzvLvRp0yifSKRxTK99KePEIvakdLxyGOLt2DGa6q12H1s0/A6x4zdXmhB95N1FtuVGJNfIz5urj+4AmZCWoJ+5boM/a2bD/Kx9JcPy3i+ST5zPQvnz/jp/fvoVD843/9L7zD3/AX/VcdUn67JGY/QUV2z03Ge8ATtrfAddthzzxp+HTOOA6U610se6LqotB+wUez+22DS77ihU2tVsZmUb0q7qw72vNJbqv3Tkk2n5P2fJuw/vrZawmz+7NxqfM/WSgRLdIVAMriBbnlDHSLpDw3axPuibZ/7rF2C4wWMd+9Sw8hhBBCCCF/ICigE0IIIYSQPxW3W6aqE8vdpHdUWOuHtsnyKrz2ifuTaKNleozaLGGvm/xuIr0Xfp+TOn9/ZdrNerL/PBKmUs6il04+Kj7r3tt2Ru68eppmlJU0by+o7vpcyNZmsXwhrzoL3ylkKylnpu5hstCjj8adcjvG7Aw1h+QWuRhNauf+L2Gt/NoFE7GdRa3v0v1aPTGcsziHF9H9db/jgwv7FFu27wrfhV8F+PUf/wX8A8XyVPBB/1Xzo1iL+e9V8dlvK10+b1r/MLHm7eJz98fn42W/Po7OX7l96vqhIiUJTX7VXyYlCtbLHSkHlTJG+Aa/6h9H6sy2Xa9bb6uNcX3oVn8uAefP7qfZAh73vTO4j+J/V5Z+vBKvwCp6RXbIbcjiRb73soqdlLWMcxPBu/8yIQy5e4s2qs4d4lVoOQf9Ngv09rtCuzUQuV3l3RhESuLSRPYcriyScBm3HTXsXHpZjG+EEEIIIYT8maCATgghhBBC/jzcNRmsvaXpzCRR0cSYqm/OxalOl42fg2pkVoFFtDhYBi+ov+gU+J36yExMFWTr8m1y9nxXalWoOPtO7SvYCxheT2lyWy+8VT8+PTVpXXcfo+dIlfQLK+Lii1vYEQpfCTNB/0iYJ6PrnLO05pbor42VxXrke57LLsGxt/hn/+Z+GgLBdilwfa4rIf3C9RL+yMKCC00o+7F1GBbfIGov0olC/U5i07zq3M+hjMYHajEctFh/bb1muWjKfV8tfLKwl8oU0+gX8mg9+uM6FHVRnthio7gSQIpQXh5DceYM2QqAfRHd3Wj+7j2wnRBCCCGEkDcEBXRCCCGEEPLn4tYJ4KisIloFatG5ewG9nunbybpRZB/z1sctbeLbJsYde4L6azEeuzobpttEYalYg5o1sOk6W9nbfqu23IJUAptNZRSUFG2DZNsa39xnUyi0PSR7tsOW3dWC3YvxUvOvLvU0qYm5rK21PF18Nb/ahW3pti2fR6T8z4W0BuIFspjFvYe3uDfIkCG5vV64l5VLXBKkVv2hS2+ioXZnn2N+JvqK99oE7Rj1R2tmyLs6A/eL2n7s+KC5TVv7XgrrQdG9NgvW6rRvXUNEy/FoIQTH1jyrZa19zKVTXB/LxTOAL4ukfTZ/Cs/xiz3flFOX0sDaAqjegvi9Al8n5Vjqj+I81LHN39DOlf1JHUdMBy1HqNfnbP7bc0FXQVZf8ZQJQf8o+lyESPqMYY5baGT5n8f0LHTlmSxa0FDg6XiAvo4u/aQYTvJwD8PGjVjP+25tu+7XjBSH/UaQvOG/jYfi+nfVz7sU0B9HUcfpIqZTOCeEEEIIIX9CKKATQgghhBByhDLrHK1P/bbu/a3e52jV1YJFIX1q4apuxvyoBforEc+vIWY5BeVH3Py+FzHKTstVMOosO6X5rwJE/zRKuPaMUue/CdiXrI/j3ZV7FKZ6d1o8vMk6jquI6S/3ND/IqhxPwa3N98mbfTQjBfBUluhHtmi/BrMiNT5JFtG9cP7eZTtv3/76xLFJlR+65/lYhuSL1vgTlVSnYS4oqYWfNG+ZrgA+m7dFhutZ5lK23K7+dkro/dVnbQtswvsp5Hx42iX/q3Hl0vg1XW2yvIfuhSeTd9lLt0QJ9QHsLw241LSG9RL2Pqv1MFHxL+EX6Un/qWWBnZ2tXt9o5SW4iUClLHRxmcvB5rXvxzmekU4IIYQQQv5MUEAnhBBCCCFvi5tn2PVmI6pefEWnhtj23XlOPJxnOp89b7drpFpvVSvmEm8N0ZmxFQFiIXqOl1/npPeQq65e290EwXY26bt6Ls9EO7eF2sozOQmgmrCJEx0AaHBXiztvgaeoMql2T2MmK0UbwSJkyhbKGsvRY2dBt50L4n3/bSbhzMM1S3MpX716MitSb4n4AYJPvs5WFrW1fmMGFv4n5I0Drj8HvWWhBdyGBQJa+9yc1Omp6sNr20EgWqJbbB/Oit+82bQCvzkPu8cvuCy9Lxrb5/hsDnTlKIT59AHgk+VVi3V8alHfOlL0vbBd889QBaOJdKUX9GJP894V/bqPLEBL5+9nzel9kstl+nFTfHH9phibQ/Az3uFX/Bu5nr7MIrK6K/e+1DhKfko+f4IgaW6PX6W9iyTlKGrXCmmIhKey5Vyav7gQpo0fkSaw+282qq2aZeyvsY3s7byAKpC3AaMfpc0y2gu0fWb2hwCZfB9eumOeMLyKncU1ek1b5mOWDF9Gqq6tzvPwA0EvFbLzHZPVQUwvh4lYd2oesdm1lMLWBIC6hmdiuriB0NytrbzO3xSEEEIIIYQ8JRTQCSGEEELIm0EwTuAfxqsuNwW1ye4w4W3bdw/bevfOqFl6Rb5N5mvd8tvCDDmeaaZvgD2xvPd3uXASPoFWLcM9lW7Xe6cn7LpN+1lJ5iN6yNdl9gWptkRjoVxXoapH+tvoa++KBvUURTzAPWIuULbgRxNWbZHLboIztbaiRUwblzQoFB8V+E0Ev6VFOl6gQxavBVngfT9pZJ9L23uv6MaEpzyz/FNbqQPIjkh8FL+wYnF/uYX/cjw4kmwL+8HpiUeb6tdgsQ9kAV6Q8PHvf8dfRPD47Rv+KoKv//hnsRr/Gb/Ir9P8zvL8tbafXN8/qeBrUHFn4cbzrVc1cvuDa0sPLr/DrF7HhTz7KVy1W4NfSAUM6n5b6rBX5ktC+lpyH6JZJFPF8QtV3y84KJGqtVud5sFr7t3Q1aXl35bek0K1LKIoizXqszMNX8LhCC7e7F/KbvBVYXdHoR9YlRLw7+VneoUQQgghhBByNxTQCSGEEELI0/EdZkZHueo+9i3m9gIiiOdzoczrHVmfKhPkw0GoPpooYVjcg5kh/AXbrtlv2yxhgv2l6FLegCZ72Nnl2YdZCNtnEzW2KvomnU/AR+1ipoHma+2s9JVsMqspEzu6Oq2ah4ZLk/bg1JW1faTdvyCkBCm/OwPZxVPjDcJLs2jfVYlhJpeqTmwB8MkJrbsc1bQW3TBbFNu2w5OFJxewLJ401k//ufkA5dN3uUpy/UqRdy5w+fm45Zr9TaS1v65RCkQEH398j23b8PXbV6gqfithN8nbuPsz7n8qSbwPWQSAn0rGPzn965oRzfcRE8x/guBzGdvOnSVzO1u7b8UO09fKltHd2Nf+tHbn7w9s7rt/fv3xF+qUeLtv6xZsgcF7zduofwzXe9ziCpc3AMjS+C/45b+Kz6BhC37Fex3jHftrX3NSKvQrgPcqSAB+d8+/HkERFxrEw7mHlQpxPJPus/kyG/Q23rbtvPdF5rH714c/hIte+nyUtMXlYrWbymRcdc0KrWWtBPP19aP9Zsz59feajyZIH2bq1Tpm/K2QB+5ut5QipqsUcVwBbDrLYInD/RLRSTu787gP+371T7GX+zlD7oErJgghhBDyhqGATgghhBBCXi1PLZ6P55RfFbjNfburR/TCIG1OfJirbM07iCKyFC/X4vnz0iUdhNJe9F5LxF182n8OaRT3noAxyQpmmxuv8AsapOQlW+f57dz707CrKCBZ1FttzRxzeO8c89DWZm3oMF0jfDJWObCmHUXKVY4WUmKv8VzwP7s/y6yIE+gskAsc22AXFlk831Tx+PiIb+dHnLccMMn6/HMTZb04u9TQ7nhMgiye27nPF88Kv5ajA+UsQBUFFQiLFuYrMUyiVfykwEPp6QLFZydQT5960TVXVRm3+7aFB58lC/R23vnR+vtxEmekDvevRHxaaq13vFIXmr2/uxO43Z9FcSxPT1O5x7uh3zQfxxXkS96GV6oT0Z1SrTZYbRuqBXpdqaHN3UzNDyR+Hd/nzULeGte8z+91E0IIIYTcAwV0QgghhBByNcs573AO7RStf+YTvzvpqWoVoPbm3Weilpbws3gvkcNu0JL2Vialp5PB1bCr2hy2iT1JMClnKpta3YRzY4PJXV8Gf17s7cZhO6gd453T0yBGeaGrE7Pytc0WLZSyNZkr+z3V2rIayYklV4tpqDHvbldmz0Nrnsfp1VlrjeET1IldsvOpeZcBe3aiEEnDo2vlt/T6dtQvNpjJg5nzkNM+fMtZSzyLwVtZRyL1GlSRqjmo1DxlS/TaoHMdS6hpsWvl2WruZ5v2zxEi0zz1mc93TiJIyZtYtzrywqI3yrVFDB815+dXQXji+f4H1XwG+EpHTfmfSEKSydbT5XDh9yn3t88PitMpIX071/x7UVFVcRLBt/M3QHPZpFx/KOL8udRZrv4mZPmartm17jTJlg/eucXp/uXLT8jPXaweS3lFmsDXztO2NuD7jsXo2kLNU6vcWqY4bsTKL2X27crF4LzqvPVsXpjMT3uDP0N+MjKoOzE8Jf/QssypveW78bs0S/HPIviowIP+jP/+twd8+ec/ysKIvqw+9S8oW/Mj29xrOci9PotSFVrrpMWXmo16jTefLuLzKd39yEyYF/SW3Ha77XTh2wSwBX+WTYmHs7uGa2Nx95Iqz2rsZ300MbpcZHVjj47hpJ0Vvw2PUaa70QjWfanLh7aX4nD8xySvLf+5NycINqSQiOt7toNGyGMbjq3BWMq+Hwra0SXanomrI9ms38/emBOXtPxI0u53xxhqUhlWp+mEhyTdmObHyqGwQ/yyPAZi5nuIbmfRQizT6ho5hgRX7fq6bB4Td3uZHg/T3HubYxBCCCGEHIECOiGEEEIIuYqZ6FjviZ+692GCmOBmtUyoa3cdwWJcN60T18tpUJ3nYTYJd83cmqpC9ZwFj2UcOeVwumiZzE+ocoTM67GJg9qLXosZxGZ57qYbFU8qoou2f+Y+FK58pjLBr+GuyTJ9PUSZxmrMt58gFnSVosFvL/khXPEbRnfxFcHNnlgLmeNvIrLdKGKFoBcBMbbTKATFXFvZTQCs+fbPOISYM96voVz+86S2DDFqTcf3QWtvfTqCXmYUlbrYRDCKEFVsm/Ye4JTSIKBbnvqC+Gzl3J4019lfxcrQSprvKx4U+HdtyFqLuCXAtlyHjG22FC4/HwU+J0A3YHvccDrl/7Q+b32r8thikl6SdBP94ZG15+WyOmnuXVuKcUjwXvx/gQLJnb9uOZEmpdoTkZpp33pDX1RXnz4+wJ1ksJI8cpgU3EepsqO29roW62M/z3eSpNJ1S6tX2w1kIu6ixS8i+A0boL8A/yzC+iT78dIn5Lp/APCjCn4v40frKnFs927bhn01HstcKDTrYnQJ+VAXr4Xc1C3+LbVUt9a3sTJf32D13O62cUihEvrNgSaQm5ROLo6RpJqe3YrjfwsRHsH0fao6EXwX8Y0urW1Oh/6yoYniYwx9dIuno3lE7sR2hKoqi2eO/wiy3246L3cb1IO7byAPCThJqiOIlT/3MhsvVr8HLTor1Xwb/lWNqeq8X0ygcP50yOR4k/5XUrsW3TauX/dGmMRBCCGEEHIjFNAJIYQQQsjd1Ikv7T7cxLO7UcTY8cxoc2t3qZ/w1G4ybTrFGfPQXR8n4pbTpLM5YpiF5owiBhRdRoYMNMFyCKbuH7zYGzLk4hSLLM4QPsG8b50DV+TJ+PLMRo2viVBaZkdNdG1ZzdeaEN4K6sVNqb7Fxz7JWZVmJn5aZYyyd5yUl/DZ8tssZss/9WcTi8t4Ka/6HC2ma6ug2+5bKF8zMYZZe+03je9L0eLoy9vrStYRvfgdYpQgb2t7Vr6tSlK3tX2L/mQ11mbBc97NKl/bOecR3bZe3NqbAQ/hfy3a4LYSSsIuGT8Xx79FsvgnTZBtT6aVQ4sU+O1B8ICmYeWFPYJTegBUcd7OVkG1AKkstGhbLM+6fyuQq+YuDx32HCR6Wg0EtrtAdn0uAX/aNqQE/O5NoH0CXXxxJJgNQi0fgn5BRRvAXLxi9T3rBZfdvsRfJS/cGcerxgags4yX1hfba0eLZfqGswmAp1PRoW0nAeCUBA8q0PMZX/tS7fJFgA+at4D/UPL0NfhRG1t85wrjnGIUeafN31+MW3cvx5M4bsZWGpIIo1dsPd17wb0oo6V7zNVyCLAjEcxZPs19tvQS0C2GsIfsCrI3zMy5HGIhcc9+JNVRp/ff37/YrmrxFnkrFunxeawYhM+6gCOErHW5aIjOgl03ddq/i8e8uujW76+QSfI2uLKTPYUA/hRxEEIIIeTPCwV0QgghhBByF3sixVTzKBPXswlRGbYr3Z/26qab3eTrNG0vQE+c08g90iaIp8JfTT8KQvMo53U2n9ZeSJzryfkr6QRcK4f/VORJd5lUyzS2hsktcyF4L55VvLLb5mbisw/Rwu3XnhQd3QtxuX62IKK30MMOtFjrkC14n8tDIsmEoxPE4w4FscbkcB6qECuT5xksEv39uPhh6Ceq2M7n7tpoxe4qcu9+QINo1gTIfHFDFt02W2SAbDUrRUXK25mr6Xb5vko5nkHxeN66ccy2shcRbNtmcvKk1AvcmGN5r9EPIihwuCWExL+UBQQfqnsVcBX/TLifLIhZqRlDu9xLa5Z6L+BZ/j+o4LMAP6ldc21PWz/PW+iHsaVk6OzFeBNsy7qIBMGmwFkAPJyQzuduHL3EF8nt6yOGR7KDjvVa7xyNolX4NePNJb+zN9hMCD0q4B7Jz21xaGsEPk+doH0h/IG8rYLW+vDf6+hgiwj6/jS+WWdvwpW7jWd5e3cJGVlmdWxf3UKMeHMdFyys7SwUHp4fzvKt/rfW7OckeTvc8nt1dTzCxXCTtNheCCGEEHILFNAJIYQQQshx6rynxssdbcpWwg6rNmGr1Zk/tTn95Ozgbdw+tJuoD6J4nDSLW3hG/z7v0zRSEUw6T0WEKIl5y+d+8jta9EpdTNASGcvuk6kSVa8V1bL4ufL6Vdz94hbvRnPbDr9VPDd/JZ+dlfGYve5zZD59adGvwpvUuLKoi1cTmq25wJ7H9ZJ02c27PpfaBk07X0R5SRha3d/cldiG/dVL9e77Sr7eRLKiAZfnaIJxrKeynXI5k7ftIK3uWbS0pPRpEzvsvGxpptkuZlQBxXYkGLfDj7WQL7SjlaU1fhll6HZr/oCisP5b+Uw+3SrgqL8E1HOPS92WxBSKVOrV7M2tWyf7Xs6ZF1f3HxX4zRWnG1mtv9cLTQALpwT4LI0XwoIBAPiLAmnLiwUeRfGpPirFl4kon8XnMBgj9APrGPG5+bOifbzducx58FF17e1KiXW1YOJLqcevkrdM/1I+tdyrudX8ALfSPgX5ZkoCSMLjloXx8/YIADjhhJO1X0W2qoVWXfrhwaZarCUptnIEyYZ2LvWPAB42QMtODj9qLstX6ftvrhupFta1drSv7/qOaA26G19tp5B2J9Tvoh6Hq4ttlXXit7vm2tqG8j4vW1j43Iw7uMyxhSxxO3Y7asXqQ7v1OGrDW0XMZN39Fsldss9A658yLPi7hA+bx5jwW8a9d9u3ve2rr0vfh9PYv8bu3XzH8cZ2J3GLpFo7VLvQ+a/1an1skpheeuaTrd2HvM24/vVPCCGEEEIIAArohBBCCCHkDsZJ9eieqDy6c79OssY0/Bm3Cya3BuEgCOgaPe9FKwCQAClnnA+KAGBbYmd3OBcaTtQrSkHWlrwv7e63wFoLI+HyNLPS+/Ha4HBkbJmANrGuE88tKmd6flkov55YT05uDd+cQNTF0BdKur+yFLsv5mi5DfhcKBpzcvt9dc96L8xKc2jSi4kOfTvtI7aHe0GNkKbHWv68HldTKyLikCfpn3QWw6W/PuiwfSx/heBBc3nszPl6vnIJ9gjg8+qZL1c+CN4r8nnWMHHLiZCmjJYttPPW/XY+uOCs5ywObUPn7XYhsHr5WYFfk2/faKK5e/JOe6r1ZELzZosTivg+L9d46VcBfirfv0irt1UEnTW6E9J7oW8nwWtZda4djvTxr6V+v0heFPBBgU/WTrVPdtMssp7kBMh5iEtV8QjFA8TtVpDPBFf0gqKIIEGQkuCsub7P21aLal++SBbQa1sLFWIi+sW6mLhr2cJuBXb9cHVHgflgHur13G3qWFH7+lI0XUS8eN/P8lFF9M7zhtnim2E8De8AX/8q484qe/g48yu1vNywEycAACAASURBVKOG94wv5Jir206E7n/3yGzxxCpUfD5+LIzb0vgXQPRfvuq2de+Nrk59VidtfZZUbDtH3puEEEIIIYQcgQI6IYQQQgi5zCBoh9vBatwmeDvxusaj48ymRme2TJPunqJu/TkGmedvktQSmQjS8GJhkxna+Z1eQupliJkW2ddTFEjMz+Sqtm2kvbAa82kkP99evkeRrN4ycc7q1VmH+fRHC/ox/SMayCgV9KKABl+rsP3puq2gTzVpntueYHfRhsvXpMoHP1jcu5iPLv5ODnPxD52oi6H1yd6dugy3s+hrfZpgZlaTpVNaV0xmgevSDz2h9CHpyyAA7Dx0n7+yvXBK2SR0K+1eUg7zq5UgiMZNeNYs0ARzzrZxeitjFMs+l2LXOhC45z9v3WqKv1n87zUZV9e/Sn/Zlye2IRFUC1q1ccDKVAXNaIM7Ju2/faoWzu26eEGwfglCb/Pt/GlXB/uMomX3/ZlUry+lkSYFftK8KGNT4FO5n4uj+P3xWzduRwG72J0jluS85Qd2Sqe8c4q1rRL+x3fv6tPeBEjbhp8knxX/RfMxAPl52JNuGbMejP7OLtVXki5U11fDmN8XtL8wvgIX/SNYDWtJROvD1nptltzQHCbvHSC8Tl34ydKHLjd1UKtj2Hx87c+gL5/2G+Xwtu8Wl+3M04/aq7FjbweWWxAFsPln0BPrEtGbtyhvmWz37Ma0SWjdBaHp8LVRt0VCwLwytJ1jH0ewlj1Z3Hm24YUQQgghhPxBoIBOCCGEEPLWeMEZwDbRvhAr/eSyvx/Vw71ZcW3W5l7g7YTdHc1g2AY1ZiKenewDT8TpNg/cTi8Os8mDYNjfcTF15Z5MXE/rSZu47z4tJXGiDASQTVs5XBIzgTsK4p1eWK/nciek5nHCTKA3334620sNNgHeTh/usrOIx57AvDTDVZldvYQXUvZ9LXFJ6k4W9uLIwnMf3VoaiPFKv/vALH7pPy3qIkOXh+ras1hbl34hhxOpzTlszW7Xrb+UBip172SrJ4GkhJOJuaXNp1S2r5YWz6wlmKDt1tp0bUiB0pK1pefc6la+VHFMh2FjFPyiIL7gkgGx3yLf59wMPb1gd9Qiuc/TSsAer2v4dgu+7i9k7I40bovkveZFE18kn0F+Syk3vyV1pbXJh80tbBAAkvAI4HHbYNv6a1lIklTxcDrhPU7Qx0foBnxLFmMTzEcx9fryK9AtGLv5CfsOcUVTEUV3FMp6vL+c/N1NqBssjo/5/SISu4aLgvqwgbo7NqHbccKNTOP78donFiq7bJsfb/vfXDFYC59rvf8tFHp6tEx3Dr/DQtsZRcrY7vwJuns1Hntc0tw1zZq/5rbjEvyRHLFsEq8f+wlwPU8w3hFCCCGEkOeDAjohhBBCCLmfXunurjdReDET2fn3IrN2c6P19s6Epj/uNwoETbqrznE7c4zuau/UWTV5OTOe817uBPEy7Jw7TsxqEDS0nzO2yVyTJevW5MVK2q6bNZeInwVukei2U4GY14lZy6WJ/6j5z2Vt789NkHd3rFrm0/J+Vvsq8eAGhUXcP3X1/jKT3xpcTtwN37Kr1J94307s8ccMSCuXiTpa3XDxeH8ARLve1OQdn5fkxO7SH6oIXLZfL58/I1uW/8///A/8f//4J0SAv0jCJsC/i6iyad72/IzUzuMu+a3bytu1eDBuGUfscm+rrdjig9Vexu4HIcEHVfxWwrwvHfuTE2/2x6iqjnVx27nc9szsyX2SvNW48Vv7WtIJ8cGc/YX3xdtnmd+351Tj3o2t+fD9vwmDvm2sKqMtAqgyWt0KXdHvDzDrxG0sEIxnYK8WFlj9iyR8FuAn1TpWn1BE9UlqK2K9GX9V4Mf/+A+c//EI+Zvg4eEEiOD87REQwddPn4Gy5f8ZuXMoULe3Pj2cWi0p8Hs5Yz0eLRBr5CgSPg0b403cNve5+LbnYq+R7p2gfXsAgJO3KO5i0PLq6sczv99BfGX2+e1F6hhPu+d3rBgjHOINF2Iz8vXW/ewp1/OOHv3+KHuC+kyj3d3F4gloZbhuC3pg8kz8BXtXdqt9mmf/VIcWXLbXMet0e3dMd1aJW8fXwUZrWPMbTgcZf4fJmJfZYkVCCCGEEPLnhAI6IYQQQsgb5WW0vDiZOXd3ormbZR0mqWfh44yus2avAvpk1ld675P6yYKzeFPSyeRpS9fF41SSbNmr8aJL08raT413k7dDGd0/Xx6LtwqRxaq4XvfClrbyaD5ztyudTfTvme8DdXvoLh9oQslCh1gKMr3fKMvN41iFts+r2/4NakQ39y/jtWVSB68fy1FsEFfQrcAoUdgikJUoJKGg7lM6Z3GFiDoZXVz7dEJGS6P5TgD+E8Dv//gFf0PCr0nwqzQr9w+bIEHxSwKStDFmJrCZ/jJXRnrPLXyvlCQTM13ef9oUn4uY/Vmk9ocvFqZ8/oC8DbhZN79XwWe/KkVCJhyf3BiTP1u+EoAEzZbSav69CN0XMbI8E37BTNgbfWDh63blqTUpH36My+RzANh2ZPoxXD+OfBHFByckfr5c8EP8IgD+9U98FODdL8DDf/4Hfv0//0CSj3lbd1GIKk4CvCttPYvHUspkzz03wB9THrt1A75NqlZCc39XBq1TLW3+swH4fdH/PXGx1KorxWujIF3eh3HQyYdhYyvvrbZwatZ23G+ARfqrFmBhxoVh/W+S1bto1YrrAjnrs8vfHe2moq8HjakesERv+b/zF6BL0tpGV0V73dsuS3/Byud/5wyPHb0wXs9/twV/fuGfulDllaNbXGLnMmIvG5UxSix+BmgI3sf4ZL+zn2BIIYQQQgghLwAFdEIIIYQQ8jQ48bxtt95/DhPZg4A+ub48N3wMOtuSVnofzYOMk+od5b5K2TRXBZ3V0zX4mf+VeB6T1/5+krZNuqCfZ25ihQx17ooDAEjDlLAO3vcmjbeFnzatLd2VUY/SZVX4a34BwstMPi8ezB5u1n0qRriYj8ZnIs1agI+1W4LOLHAl+qqec31Ls9b060xqmyt+ffz1M2jE0ry2nRKq8Cyd33+jF+xOZiquwCaKXyW326yPVKUm5y8o6SICkVRb2VYyZ4KXL0MnujkhJ/vLElsWwhVfS96/pK0sMpFWEs1xKYBPUKhqPktbs9v0H59mfJ6/Cco58+V+eRCqit/cc/tYBCHVLOa/Q7YG/lf1AXzUdsa5qxnMWAmHszb6Qb3Ib/7b8w+bj3SMueklz3wOtllY+763ypGzZJ6JaZaZ1EthvYCZ8/3JNdb3W76hzopY9cgChJbfnzQL13/9738HdMO3xzN++8e/8P5v/w3/+PVfeEinYuKdW1FCsX7/6Wc8fv4VSZrEqMjW3+eSd3kQPEDcOF5aazkyIbl2IwB0O0MgOJX6OAF4qIJsDv07FD9C8PvOyNTqzYmT/n75PNnrp1bL+BvAPq0bK7SNFTYSdGOVtF0mavxavGWPaXWUQfG/hZTrWBDamcWyaVnOYGKs3bfsuVetubtyx2yU9pSkvRNFFVsSaHleQwsPadTrQ++5gdnLOQjiIVF3bxKorLxru7PngqoGb3DPcTb4TI5DsBdg14JqeKeSa3v3zLJNCCGEEELItVBAJ4QQQggh17Njea6qziKyzHrOLMvL7cFh/uN3cwLoBLgQwzBhGnWYK2kiOvxc7jziTkDKnqvA5jShOm9drpm4pzbjPNSVVFHHZomlTFB3OlnZBjXfkhhDzG2X7bms3kLvPz6/Ze0olPhv4/U5dwsEd+DlO+Bg04kVvBBULrn76KRZv1/ZflfP2wvIPlK7rsUhTonopDp/lIFvZy6hLAqaVN4Ll01cD/KVc8c2U9Mu8WkRPHOfSb0/SZDk9FMUgQ7o1ByFVnGs33K5r5OvolmsrF7z96Kz1q3pz5BWrsmz2nt83UgiWVAzCTVbdDYfv9mAIsCHrYQVwc9dHMBHl+Inl/iHIAa/d+73ms8DX/Fp514VRIdSrf0f46hPmep6e8FNrxMX0OrCyvP+YPI/eTG1/NvKuP/u3QM+I5+X3guKUt+Xj1D8+vnfeCcJGwSSyh4iuuEBwGkrSwXSCX0tS100AqC2FS0LPk5SD1EvZWpv0CRAUuBdie9dqcN5Nfbjt7WTW16rbat/hW5bEFrjezW721HyfT7QXx4yFQX36uVCxqO2PPVzRT/fQs9QoCyYae9MUc3X3FvUFsq5XxNY/NK5gvb7qpbxSIFjIBsAawTZ3Y7QmP9Os+G03049jPrdggJtv7ssWgHsTI662E76Xz3iI5wPy7u/iwghhBBCCKGATgghhBBCrmNQANuEqjj1S22/9XJtrWOHGXu/7fsgSM9j2M9f+BpE7F1hywdQQE2YW6nQizgk3tci7GmrsyrmuZnsFk6RLB7YmevaLL3suhM0zZIvCgdbcMct22fFEek3m40Csw8RzyJeEavwaLhbUF08nEk+7Fo7b7jEcTDsU1O1ggt+4v0oXRTNGbGdKFDd4oThmrDFIl1L67+J6Sg+rWbJ7aOr27qLvx5qsuZPkIpgncRdd/mvN7QIKTJZwqHZSllNwKxDTLFe1mLRWfqVF6xHMcfS6vtWQq67BDsveshF+NIVt22uoeF5CoKI3sKIAOcqrsU4i8UrBD9r37+8KCxQvC8iakLekr4X1bPnT9LEKsW4xXd/cnstVf2M21BHfVvsf9pfH5C+Rmu8mv/EHfJ1izGVdpe8P3cyt39vIW/Hr8iW6QnA51RH4S5Wk7XtagLw+b/+K6vo6Wf8+Ne/IYngL6eP+IYv+Pr4iJMUS3LJ7fK8bRAofsBH/PjzOzx+PmM7KZIqHlLCu/cJnz79XmtzU8VDsWAGgPc//oR3Pzxg2xTffv0NAHBOeQnJZmLtloXGEwQimq3RyzP+CuBRN6gq/tvHj0gp4dMvv9Qybq76fRvqW3r+9nWhTIr7+14TzqVPfokNKoRItg5A/VUMDWUr/Vh6X85CvbQbLYtTMAk/pI5OKF7+BoBvz8EtoUeIdAs3LL9baXupXJy/F2/bwL3vOeGXwd4LpvPSxiLTyW3bdi0DWf1dEtrIateCI3nYtvjgy7hSzfTdG88dXt6lEerc3x/HT0IIIYQQQiigE0IIIYS8HRaTiy8x0dfEIO3V1KpOFdGq3psLkVUgjnv/mrDl04yT1kFoqeJFmGetE+5q1ryjxLOiijlVo1P74lPo8tgLlz4taRP7Wx9/PbMTrbr8WcBSJoqz6K5ZDKgz1r60bdrY7H+jgHd00rrmRVqcvazYx7SMfz+ZkO8Dng5M9Lc0XVsM6ey5c+m0TvrPJbhe5IzXY5hL7mkFOEVuVT979ZYkdf56K3ATNH0kZkXd0rayJAvYZa3J414cqVbmnQ+75wRI8XGg5Qemi5dMiCCJWdqifObrIqnftleknJNbnrluVVxV1XxetmZFObtSFTDz54bNVUqxVXf5U1ifNMv0hCxmZhE9n9duZenrd03rb76OpY470RK91lYp+28ujY9uDOzPepaytfuYoR/KUP6hacf1s1meT0Qp9PcmI/wyxBVd+SL9zif++ipA+yo7R4PYU/wqgh93Mmz1/1MZ4xPaZ8Jv+P23hB9//hu+4EsWSEsbfof3+XgCVSg+YYPih7894Mvn3/Du4QEn5Pb8iA14fEBKKbdHBR5SaXeSoCLQb4rz6YzfP/+OR5Gs3adUxr9s6Y1tAzbFllJ+/5Q+dRZA1Nq04Ndff8Xv0G4ng1Mos28n/p8AQ12ZoP6j2ngieARwKvH/WGL7enm0nTLe9XJ1/3XivIp+4dqYas1P9x73uXIjihOgAUVSwaZbEYZzndft3cOuHfegk/zPxuHqrr+33NuxtJ/6cyh+9glORXRLt1usiPzTpv2sLH1bBKLd0i9UET1m3P1WkNgEwjC6N0rd2kaW2bn0Q4kQQgghhLwqKKATQgghhLxBXuXc20yp8DOGGmYzy6XOIkjn8fgd4ZfJlz9+Ars/E127s4ttMnVZl1VIshl/aYL1gTl9LzKLMyOTWJaSce1MzXSoBpOATxBn7dvkyTahbVne4NRvSHcPdbf3WpwoMBRrTtPpoygcT2EVrKsj1rH3O5trj3Hd6/aJLHYInigf1810d0KpTO7tuK+nFUiD2+6bRbmR9WjpQkQBoXm0i9KL02iCtxfhfRz1fhRbozAMk6Fb+CysZeE/nWwHhZzvJLatdUJKglMxSU2n1AT1wuPjI3TbSpstkpUAuik23WrL3aRYNta+Ltg2gWx59wFbH9TVT8mwt1TdgGaV6YTcvee8GkKGGlWXvyDIfRLgLwrr6QCyAO7b/6+zzLtUTWz/Vtx+e3dBE89901aMlrq5rjVcWdOe+74QubQIrvH0/8u7CfQpdPl3Fb+n9xlJUo37i+sLPxaL2N9TH9K2Nv+owIf//DtSGUe2bcOXX/+Nnz/+BZ8//QpJeZnFo3zNedg2JEl43M7Qf/+CH374gHfvTng8C759+jfeJcHpx3d4/LphkwSRBN20bN2e5fqvOEM+nyGSkMqCK5RtwUVOuRTv+m1UHnWDqOLxnDcZf9hy5cjDO/wIxRnAz+/fV0FXVaG/KdLPCf/73//Ce22LtfrnkndisDbxXtEv6lJFguIsOQ1bxODXMuSdEKxnlic1vCzaGzBXdD9adWelq+WntZB6lrxf2OPev7X9lY9Um5X4j67cLvnh69BDxH2Wx+LHxS6MWlkASanuenH1+0Trn8Nh+7dL98Oq+bFHJF0T6/zmIy/62pi+r+uPlHLBbz3gt+twoWtPd2OWOB/tqJyX4SXTJoQQQgght0EBnRBCCCHkBZhZysnMNGfCQqO7IRP9l+MTe/2Ecn9Hq4DUb3/ePPuyi4a66MLMkt2VvIdwNmnq8xcnbVflljqV7iKLk7rev5/b1ybctfTFz+3Cpvy9DDq68rfkZKYoVEaBSP0Wqj7vNV+tTsRM5t1j8meuribDBw1j4dZw7YjbP+HBrRfuh7yIC3Nt3o1BBxD3fKT5seveYn1XTrzUgafCp4Rre+5eqDBr5lFwQN9eaoVOakbstiDVshfBXM1V2ubkfHUffRROBbmdJxGkU8IpnWqYkyRISjilhHQ64VQEdklmZV/afLE+/wbB+XyugpkWQUxTFmJsjNpUoedsnatazqzGGRvK2dQwW1GtWykr8phVz2J3Wy5rqfNVe7mItC+Ccdv2VKzu7foHFZxLzj5oFrvjeecfFombP7Oc/qCKT5LjnJ11/v2Fn2z9n+tA/dUrY7nOcz4h4FKo8f5nKN4jLiNq/CaA/p//wl///p/Ytg2//vOfgAgef/knUko4le3Dz1tbqLSVgfmdfMCHv3zEdj7jh5Pi9LefkYpF+YYN6fQOum3YsAEbypbVhnQW9dZmHgA8Wq9zXf2UBNANpyR4sD4ikrd8R95Nob7XSxj5S8Kmir//5a/4WrZ49/3DRpgTrP/l+2d3T+w9qlnzjk3Otojvz6AXfJH4e+W2ltmnVzISfytcGGJFJbiB3c0MhkzYIBp+S5ileT0qYvK60DYm+fHVsjlNbnJ/ds1fX8Up0Ze9BEuG4+8Gif7i77xq4u4fgv+tlb9r8sHLzg0CSHL1tAnamTclI7bffCjI2A4sjKXjf42NNTs+bpl9PMP4SQau6YuEEEIIIQvk7//zf/C3HCGEEEJuxgQPch23CuimLYh3Bx/TWMIksE0Oa7sQJgd1NtfYpV0nNstn3im7WF/6+PzEqDr3TvkG6jWbPV2Ej5Ojwa3OXqvfOnpek3HuXDvLqTCFrH16dtfuJ0lZ7FPLQpERQx7TRHFLUFfyDWahNt38Oioklp8yh9ys+bWb7I+T/9V/zkDLNsZJ4VvcR+Nb6RfH0tLhZjxjeRperP2GNiz9U69CBwBTlKOA3vX1aBLusYRdJz+V7cmrHaRaN9pK/BZJtkH27eGUBCnZemmdtJXWRlrSqbYBhbUP81eswK3c9Yxzy5fWehIRnNIJIsDPms+R7gparGMFkuvNu0XwcEp4SA+QlPCQEh5OD/jhdMLDD+/w8PCQ4z6lpo2ct7z1+rbhvG04f3vE4/ncRLD2lKDS3lmbat7uXTeohd02nLdHnDcbzzZsqjluzdtf67bhjCLAV4vzNoL2J1u46/W71ufZxqP8d3M93QS0vvpai21Cunuyrr3NhPDuOQzocMel5nxMQt44qyC1psrCABnzADRLYKnNtvexbdYn+p5d35UzrVJRjsYQpLJBueYHDzskfcPW95zQniI/aVh4Jb4sxSGS3wVJcNrc+fCb4oy8+0FCwqm0d0kJ37494nzesAlwkgek0wnbdsa2Ia/8kLxo5GTvFctEOfc5PbyDHYmQu28CzmecToJUdhs5dVWa29e59A+cz/jBFo4A2E6n3AecX902QLOVxkmBR5jVObo+YEbij6o465bfyuVaKn3HdkJ47+r7s7QdE37bbdszrAGU3wBb3Zsip2vPILSf7r5/AUluO1t5pmaZrmXFVvLvBtcg7BgZhbMed7+RulZl7ngdY//w13OaLn2Lzn3GQ3IudV8Nn0OY4Udpvyyl5kYsazkXvpZj3NOfgra7R+lH+RVl76O2kEpSaeuWenlZDb874iu5/unHj7ZwqS9V9xzEXQs38m8vV+dXt98/J7P/VjocVvrwt8dECCGEkD8ztEAnhBBCCHnlVGE9KH7Vivhi+N7tNJs6cdtvyan+w11uymOLUpt4ZoHUxTdYFcVIR2ebuhzv98wKNoaNAhCCu8kdY01GcdVvoWplD7XRJE1tE+9ZzMjb6Iqdt2wxCTor9XY2dE7P6qPVy6mlH3La5ulNGmgTvFoUFe/uhLJYfMuDNDvcVf18b3d8QsfzUtU2P69/IO0mFGnf4Fs+pBfJ7HonUoTJW6km/pNJfOkzZpckIe8qoL20UyTHoQx1m3aJW7gr1KzwXEyWG+sHvt5cdlsbLNult63aYbVUxxYBqiD+udZ9qVFJ9ZxlE/LqFu2lMt6dTnhIDzidTng4Jbx7eIcfHt7hhx/e4eGHH/BwOiGlU0lzw/nxjO3xjMfzI7Ztw4aE88nOMrd8KyQl2EIAoFic6zkLk+czztsZ523D4/ZQRPMi8J3P2M5nPG4bNpyxiWSxsMiHm9Vc7TPNStw2jFdViLo2VcViQTPVjH2yc5VraE+sfP9iz0C1G7ePaTT2rC8LDdcIEHHs9H1j9OkXIsxTutYSfTWam7V23PhEsXWW22ZBm1xMingW/cgXAX5EG9Nt23d/JrikhDOycK0AHmqHboJfUgDfHnFOkq3ESxESBOl0qmK16hnWG09oO5jb++dkQrFu9ZWVRJCSQpLgvOV2KJr7g7Xhk+R3xOkhAThhezjhy+MjEgQPqng4/YgTFN/wDeeywEROJ8j5jEdka/PZcxBky/Q4lp8196NPEq3O2zOyzzTextjiFsRXvXYfkxT3L1dLej9yujTMXfuBthF4luOYtfWvk5CP8F39bxWRLi7z5d0x/lUtrvKhwxf3bvM33IIju7q03B+uheMxfKXa7hyQurORjZ/Nol9CRclY+bWyXf7qGK1t4BD7jWVBxV67fT1Iey9cN4IRIL4Dj9P9TrtDhCeEEEIIoYBOCCGEEPIKuHaSyCaGovXyjJkQ3oslxyaXLgkHw73ZlpxvEW3iYTkeFsA4+W3lT03hKh9lG/c8q1uFRzc162iT8Jtq2T63iaVNsPTZ0+D2gqWv/juegxNW7n2az90abpt+3WcpMC7qyPSVIdxO5rLomrdott0d2tPuZY+2ZbqzwBNg07axspdLWvvTuuV/FstN6clnK5/quNTapR1VIGKtshUmj0vqRCOtd6rVa7GqP0kRs5MgIUGS1MUmD6cHvDs95C3bbev2lIDUzjuvoqImpKQ4nxSCB5xxhr5L9T90Ld2UUvlu4bJ17eP5jLM84lzqMCXFCQ9ZON8U5/MjziJ4dLWu53OOr2zpkGrl5G1+tcSvAFLZatm2hN90q2qRdnVkT9YJcb5efcNw95vwdGvv9NLkYRlxkjtrD30LjfHIUL4cbitLDWxb7CjsRQvh1YKoMb1M6wt9PtrZ9ZNMdzHs15Pnq/lzi5R+d0cY4LwhJal7iTxCoMner/mM8q8lnXfnDZAzfvzxHX77/AWClHdBUMW5WKALFKmeJZ5r4pTKBuom2J6zpH0qZf4iwPsffioW04JtO7vjByTHJbn9qgh+/OEdkgh+//YNX7cNX8+/4R2AH/AR3+Q3iAjOEODhBJwVmoqAqYqUz0YoJRJ8A/Dg6rCUGgnAf9O8IOSD25/c3pTvS385A/hJ23nz/fNZUe4X9V1SLmsalNvSLjbtw1ku6pAo4Xdbn77tiNBiLSfAz9X/u9ktvfsNZs9YYfuWHItjNrp0AvxKBL9AO05mDD/LW7KRslj6xwULdh0mevu95Ov7bVIWEbfRjPobbWy59bfsjXVDCCGEEEJeHgrohBBCCCEvwEwwvyiihxnMotd01+rEonc7x1R80MFnFY0H7aBsB7uaah3mF6OIfmH+cSYQeyHpkBa8uNcXRUJaXnL2eREnBtojKJvWmipaYvTz4hK+17Q68UuCu897CrkupyI7b76gzkJcBSomOVwnIK8m07uJ8ivie0rW7eK6cNfiW/sQV3zQu5mQ3m06rhfWAtk41CRZDR1MqohtojLEBJJebGwlmQmY87TNGrw3jHd/NcrnFqj1IoEd85GyUF7OMs9itl0TiCQ8pBbqXdmy3fw9FDH9QRJOyIJ78qmI5n8plqUI9DVNqYLKeduQznl7brGdHs7leaeETTc8bmecHwXfgrUhVLMw7rast22Dz7rVRUqKshCmbFWtRUXZinTlFx3ZVthNiLYSrPZ/8Nwo7Dwp7dz4fV+Z/i3lrOfrQqPoz9zHynp0OcF3G89KxKfTCQmCTdvCkiz8lbbgdwLRfA669aJ3Dwnv3uW2//u3R9iuBYoN6XSCiOBRznmRTYlA5YTT6VTFrkzjoQAAIABJREFUQynPZTvnFvatqI4CweffP+OHdIIWER6CvGhGANFyRAIEDwnYzlvdevsBilNJ8Zv8ijPydu0PpXvhZAsSsvj+eBKcH884Ib/XfkTemWGruW5V9u4//oIfIPj2j1+wSbZkb3s9NL9fJFuqf/5uD3CG1j6c5HKvzJQxU/r2mNDK1Npq/JXSFg+U1K/OscVRf5+o1t0B/PFLG/o+E8um4Vr0Z123vtcGjyV2HeM28bxbEOoyo9jPm0+nswAXNPHctTX76abaajf+Vm6LX+JvZR9vKBvEXZfmr0ug5OPGIftWi2xCCCGEEHIbFNAJIYQQQl6ImybCTCvCQvTq9Gqboesn7KZW5HF2tCW39lKjj1O/oxjffU7SOKpDDr50enXhFmQrsD6/TVAsnyXOFCZ6q1g2CJBtmlXgn09Ck7yBk56chZ97RtrH43ObfZxrnUqXd7sfJoBVwv1Z7Jepgkzn/nMTH9XFOq3Wb8fijhaNWZDcyqKVGHW21pUihvmt1ev2sqsFGXVrWxdfuCBI7Vz3SWZr/ylCeyqfJs6dnLV4SgkPKQt7SRJOp4Qkp2wFWi3PmyT+w+kB71LpL5KtaVPZ+t0sVaUbkEo6kiCSt16HKiShbctddn/I552XxQhbrtu6pXx6ABKQHvIW7o/nM75J7sdZDW/jlaoJgKXey1nuUs5iz0a3CtlMUBdsukG2PAZlwTK3D79II9Z3LzFO8PrOM3fS0Frz/y5k4hzKYjb7omW07HZaGNPa7XOu/V46s93X7LSVm+l2XKV2kfxcT3LKQTfFo57zmeeFVERtVeBRsgX6qdz/8eFdzY1A8rnoRehLp3e1bSXNIrRAsElpQSnHcd6K2G1HNkj7umXbcqCc7f64fcNDEfeTAJryWfBbOYxcRXA+A2nL7fznj+/x9fdHbFCk85bPYT+fgXQqzz+X8Z38jDMe8Vk/5zwlxV/Sz3iUz3jcNhQ9HyfN5TwXC/r//cu/8ZNmMf6dAj/+t78CAD798xc8AvjiFFI7E/0BwL9u+zkVxE13r9Sljb1t6/D8uWl7Rrk2w++D+PtOW7j+re7yogBS3NUjttPr6WV5V2RtsdpuI+r+TcNc4TasBBOpemmB7t1Onq7x2Y4r7aegLVBpO6HE7/ZOrN1CWkiJNazlelfp8ydgYUX6XNq7p5W41AQ1cEIIIYSQN8P/z96brkduK9uCKwAyJdVke9vd3+nz/s927xnssmtSSUkC0T8iAgiAzFRKJdfgjVVfViZJzARAKlYMg0AfGBgYGBgYGPgGeB4rktZCxiy+oOc2rtq5/7Etr7avraHIKdncmDdM/bbMzfFeLbVccun25ZWaiqlYgJ2gPU4eswk5u2tNLGcWQbmdKVaD4EK9V4Fy0/INwWPXgzs2gapcqdZs/qwbitLqrQj5VK2nRuFL8VgS6Z+BnthsQPuE+kbhYMNS63e/B9BGhA+dkNUrrS+yJBYhfygu3Gss8ezXnSPN+9iw2wZuGtKcJPjZquQ1NLa4umWPIQqJHgJiiJimCVOMak0e1Sq8Wsv7Ls8hYIqxXBGCO1SSKed2nHPxcy8W+ykhZxY+kQJCDmAiiV2u+2LW9GBGIIBChHiJDwhzRMo1hi4YEnM6u9WolpymwIAgbuixruAARGZkBnIIStRD743FQu9plR8P/XztnzkePYnXliLfrBbWnkA/na8v//TO/+V4zP4ne/7eI967id4r9WqeHGUqz9pAQRRCIH0MIaIqgmQkZnD2FSpR27kQt3ABRpwqnQgmYCXCpJ4TLNvC6vKdRJHmwLK+1xxxVBf0HAMQJcQCQ6zFA4R4v+ePDbkJAO/zB7yIEQikHhyqu/sIYAbwEwMLgA8E3ADgv97j6pefJIY8Aa8Y+OjGNgM4Qly6A71b99OwPRLMu/fKv1ede12jU9PszHRxW7erg/Tdo9LmXFJuAzt8GTylTf6U1OIU/dpZtO1DQ3qfSSfX9ajbI8rjzJ3etUhvCG6Xxi2k9l5ZfQAT11AowsC34W304ULkvH90Td2+7e31dCcD1y9WN/KP3ZWG5fnAwMDAwMDAwLfBINAHBgYGBgYGBr4RTCD2kMVegxNJPXluVoDFJS7aa7ttMaHmJW7kT5Sx676d9y60xe0Sg18BJqhGYpOnqgBbiLqsomMhvc3haiXSW6K8L3cLsRb0rtZbapybUkuico7d/5fgEfL8C/FjkejfQty8I0IX7Og5NAThDpFNYHXvbpa5esXI+k0M3m2VoZDpPWnuifYTfWGAsyNuqHIYfu4TifWsuWkntTCfYkQMk/yeJszTjHmaMU0W2zyW+st+lTOYgYlIYzjrmiz8BiOnFZylPlNi4JwBFqvWnBPWZUFKSUj3INbxnpiswW7VfXwkUIigqER9CAASmANykE8MEzhycfeeMkNM0ql8ynBmpSp1/yu7L3c78DOYjG92jAuLtPta4/s+rX6fv50v7Y7VEuLbiWcW7JXz6km2/cl62la9ks4Pw6lD1Q15qyHgyrN6r7g9L8oVrv4QwSGoFblvmX5zffaEIN4OUmYs6yoX1lWVTUShJGdRDknKdFuYA7/zWM+9S30G1CcKtEJRQskwMp2QAUzqdt0ERQtn8KplEuHqnjCHgExRQiZwRg6EsK5Y1oREYs0sz1DgzZtfkT8mrNOCJd0W7xAcJX9IGSEzVrA+YRk3eImJP2GBuGi/+/MdbgAc+KWO8idkv54B3NH+BH5IjYJ6lrS/bhpw3X2G7r/M+/NszwOCTSfvSSa7i0St0pMQvnqfn4FArWPRBojp2+nHwyzTc5d2703lXJ2PxaUW6SUJUXcPembfKSLo/rKXnt163OtMeVd29TZEfDld5waT8yPQ9etSMPPZ5/3AwMDAwMDAwMDfg0GgDwwMDAwMDAx8YzxEpPvzZDyaiyfZpO3J844436tDLG64IdG9EHFPaHeyrZs27dS3+f9yIWsRAD+R7LFayzgyuzIreW6p27ZSEcGSO94jaHy+lmwX4Tm5YTpl4dWWdL7DLRlbD56H7n6IgvjnYzO+l0xcI4e7Y1B3N2mnMDWrCwwhdJHRm+NVYnxvpnVNIavGuXonnBbIM5ToquVX1/BUzxGEMFcrc/sOMWCeJsQobtvnacZhPmCeWwLdSOWcMlJOYArIKSFoWRY2gTkreW69z85S0Mh3sSrPnJDWFSllIGRQrgR67hQRhDwHgAkhEihOAIn1rrl5N8LcygghIDBr2QEZ1eqaGUKe51zOZ7NEZ7c3o/UqEAgNcfZ3gnZ+PSdkFp6L1ryl0N0TrtnrLhuSZ+7HA5VeybQols62HYQ+YdngZV4HJdSS7QuOZLfn75oS5jghaOgE8egQEQIhhAkpr6V4IsIUJ6xpRebVtcTKbMeFwGU9+XOWeiFgVgUPny77ckJQopsxcUZKQOaEGAhhnkTNLCVRZtF9gpmBVwETz+D7F1iXj2ACEqtKWZBPSLmszzt8wgSxKl8BHEks1Q/4BGIXD526bfGJuIiY7JOczHN+5vt3CHZ3qT4eqCjdkL+n9GwP9M37ia8f3bFNhYBKBBNaEphRh+PhJu7Hjt/bD/o3D398qr2k68q807cKDFzGlrtKG+t3ULM+TzW0J9OL+pAn4C0JVZ2cM4/qgYGBgYGBgYGB7wyDQB8YGBgYGBgY+I5RiRkVxnGlGAhOdldImc7yHJVUP1fHxST6XjlaXyXP1Y2yWaBruwuolR02csRHCogvkUGSlstZBP9eGOu50KB0QpV7tuT1Hl2+Ffq2QumWEOJiTdan3VJK5/t4Sv7KtBVuDzwfmJ5H7m0014a46Q6NtAWFssZrUjI+25HcXHcHp0BTCnZk+LYf+1QKgdSSPRRir4QnIAJFwhQipjBhmoQYj+aqfYrF+vwwzYVADyEgksR3zjlhVfNCI5lJx4bKfpaRkrqYhrk5rl3kLGkyhEjnLCudMgEhICvT5kmRYASfo7CIRHFgWRYkjWWe1HU7scaIBhr9JWsTZzle04qUEjKqm/hCotsOZESlIwCD42L+zuVb73JPpvpffofZmxf7O5CfVeSyPdSffUJNzt4oWV1a68q9YeCzVvSCzQq7LdW33vd4z9X3ld5cmY66kpwVqT3fAhivuJKhLVSFIIiyRSUcJX/M5rVAWiXe12VFigt1UQ6Z51kUWcQ/O1Ja9Tkuz+NAVNIGmG8TWUen7o5HdMRohPO4QrVfBOAQAsI0gzKX50rOjIUSDhSwqNV0nCKupgn3n+/AKSHiBgTC+49v8eb1r2AQDtcHzId/4f72M1a+QwKwpoQrAJgmUAigZUHKGauOWQAjMornFxBwBSHUW/J822M/P/bQvwOcA4V2btV3Klu0Ot/cuO6d71tT09lxa7sebN5xeTVr8JhXpqekbfK4979AtJ/mG6J59tkGbePnPGIUQruxJLcv2Yj3FVvd85daNaH+3RlWtdVdFuV4ORsYGBgYGBgY+JEwCPSBgYGBgYGBge8QPXHOjfSVVYRPVbi/R553hNtD9TVk3g6JXupXUuhESdXMxktXnUTxIYH1PmHscvEZAr47R67u8zaRlUQL3XnqUnlyoqcarZ6eerc8+xHYe/LKg3fP2pVynrbnC9H3Rai0048m9v2S9p5bNaeUF07lNZk5dzejrjdqvvxNJXIEi7JHxWWwd8luxDjV87L6c9GmsLi2xXX7hthsCYGgDQ9qYR40xjdpLHJz3x6CuGyf44RopLlamMdJiPRJSfUSF506Al9YcHBKYvlNGYhRSeiMpC6rc0qdFa0q7yhh7mNwS1xyICjJWFVZZI/KgFq2JyABCYyJGWtKuF+OxZ18ZgbnpOS+bo1spJbFjc7IyMgMrGvCmlbYus9Q63lwsbBltPuROuxXYv7rrLTtHD+1q57bYR/GQyn72NV27JfDC67tLUSq4oU+DzYW4Kfao5lfQqed1hHZkakk8bz9fh922rW/TxAQgjw/XSLKcn/ZLz52bqRJFEFWJMQQMQXJn1YGs3hlCBRg7rdzlgbnogCHopghShv7vk2izl3bfgJ0vcGUQQAmoXE5TAgxInNWV/F1nhIBmbi4a48xYE0ZIQA5Zax0W4j4j+9/xw29QXgVsd4uSLgr4xiIJAZ7iADn4vHBVM3snthYE4tF+iX4fEG6Swn0Fg+/V516Zts1mVdU5punzev7g7kc70fh6c+33efTA2k8LJiN994TiTaedC558/R1c3ee3cmyLXpi2pexe9AWzP6EEduWTb1DbBRJ+z5po7x79pJ/J59XrqnbOruyLsdw3z4wMDAwMDAw8G0wCPSBgYGBgYGBge8AXhjnSaDNN1TgaxbnctHlK4VUgexjJXW1IY01DYBdd6nb4h+q77QgkFoZ8SbHuZItTU5KVJ3I6x2zC/FixLzFKDcCkkq+U3RST4QZxGaQy28AiOhtPv8eUvqJd/sMTlNFAxdgl3+k3TReSE7ESla3zB01gWF1DlNoY6IbA9Xdtuq+ndr00HXsLQxDACFgIiG/hSiPMGLfXKAHi3k+TRr3XFy4i5VsQCSxNg8MEGcgSeYMcZWe0oq8yietGWtOkjerBTgzUhZSOuu52mYjtbPb/7j2LweJ04x+3SoTnoA1ZRAtJU/OGWtKtZ7i1lrqzmoRD87Fgl7Oy7W0rhKn3Tj2UmfdT+rtdPcbVeHmW6irsKv9qWhjQpeCAQDX3b7bKyK91MHiB2JZA0qWF/Jbx9WUSDR71KuqRoJMbbq9cgFbB0IsUwbmKBbp089vwMT4/Ne77r6KBXcCsBJEQSQEIdyzKHcUltS119h7QgYxgaKqAKwJjIQlREwHWVO1beZhQpRaGAxkPUOk64B0jEIdJNSlTVnZc9LnOzFmJQAZ4gWCQsR8dYWUVkxx0tjc+j6RJJwEg0BTwHpcwCnheJexZAZxxoFuANxrPHTg+tXPYAArJ+Am4Dr8jPXjgiuWGOwcPiOn6p4eIEQwDtrmTMBHAm6Y8MtvPyH98RdIx9zmkVib97PG32H/PiR9p+7aY1D1n0J3XudZbonSojAQ3D5A1V0+IYCZEd30gN5Tazeb6bTrmuW3WOXn35FqbHrDXvpGYaFLxzvnjEy3eWjX9vJciv6tw2KgP7ac+h6sx8ZxnyloGx+9u96T5zuuQzyZbqvW7vl4mxoYGBgYGBgY+HEwCPSBgYGBgYGBgW+EPWK7WpHvkN8qcBchnDhcJSel9GQ6UAzctoJIYEvgta2oKbs2cmd9Xn9ylZhy37e2jL7+ni/Zb5rQLn1/jIwRD5kW2/IUAePtzOtxa2MOJzptr7fjuBnRDf1k5M6pkX6IJtu71tZKJ1K2bXg2/DtJfb+IRex+Uzd/TlieN+Q33Pw08q1MeqcKQpIuBCqEkFmYZyWSQUJqhGCxlONJAr2Qn8wIFBERnAX5hDBFFNfx1r0QMIXgrM+FbLfrhdxniXVORiwBSognpDUhrxkW65xZXKcLwZ6wKpFuBHoNF2FtN4WiGltc9oWEzK6vehOyWrxnhlqat7HJd60P9X+JtZ6lTTmJVXzO4vKdc7FcV/7UcsneRO0xbD7wqV3r70X/bPDoCbRLrvv55GnFK4hnj72ybPfkwo71qgWn0aThWq88B6R31s7YThlMKDoUMk9ZOWVU3ZNCFBKwvHuHdWe0jN4OACaW9ZBKWVfNcme+a9lHU3TbIdUoJyz3DJomEEGUWAqhas9C811gjQ3gJAcNYcdOfSO6OgBMgUHFgTsXAjSljDhN4oUhMRB0f8grEMXd+nFJSuSLK/bEjBlOKU3x6eNfePHqZ213xvH9EfGVzJBwGwC8wpSBY/6r3A/73FLrbj8z8PLXn3H7x1/lPtnYXev33eYubbHZXx8L9hPK31TPgLvkltIRwdzeQV0/OgkhCc21f7lePI/A9ABc3ktApYpTPDIDu+9hmznacvm77ydVkUhVhE4odPrqTpH3/aO1T39KV7SuD9dW7XzzNDYefK/wknG39PKrvt/W51ztAD1I3p/CxkvUwMDAwMDAwMDAV8Eg0AcGBgYGBgYGvgN4wtwT6P6cHoCYVADbupHcFlp/toJHT93u5Of2R09W9SR9ScoNLVTTnmlikV2zO+6u2+VWiErgZOf3ySdyaX3ZLXHdkvIMQtSrlQASiWcl6EtO7Me/bXr3JJwSavuR3yfoC03yRRzw18T32M6HrN0uH9/u7lDnheAE+SFxz9mR5e7Oe9ftSp4TUFwsW5gE5bCLm3UiQoyxfINamqsI+nXNiuW4uGD37tn3ZlyI4pp9ihGT1mEImoOZgZSwAkqSq3t0TsjJxT5XQi7lJCQ6Z7WstQji282irnAZN2aJg94wJKWjcj0zIyetI2W1JBcH2bHrg40pSAi8XMh8Lh8GI2fbHi+f1e3e9XVXw7nd6qGWUPddzvfu+SHeNyaYUkFPkJuqgZDogSoF3re17m77fQC4lM9NLXXe2JnUpfkYZLm9zsDLf/2MOyVok8uZAczi/B0Jn+DJ9lLSsipHrfNxAhh3yIHACEDKhagH1TAslIQ6pkjgzBozPSMvCwhAmrKEUogBYMbNi9d4/8fvwodm4Pr1S+lplHqnGMHMSFpuSqks7zpcGTlA2qUDE+Is6y1nrEnVyVIChQkgQjavGDnJ3kOEnDI4BMyQNi64wyKcOwK/AOgW7z/8iQDg1atfML0RTxaBGXd0BFNCoAROUcYHwATGIsOHa+X9gz5x12XFPYRYN5f/TBIX3d/jdn74fdPOlLeJmsGuP+C5p73Mm98WM/3UOspKZG9fxcxNvnuWq5KNb55Zntsunrv2lr5Zd1xrWvJ8u6p2yWxrz461tR3aemjK07nuFRX2CPHzo/0ANsz+9rAnzJvrm2vul+/3g420Ue3eEEjf29Wr0w/1gjYwMDAwMDAw8G+OQaAPDAwMDAwM/LB4jMDt2WRVXyTl6wpSQZoR1H0MX3/OCCeheBnMKsR2Qte2gSLOpF1JXaVdT3anNMHa5i7wqfGkztzG2tEJHukU7Xv6uDiyZgZYKDmlXGAW423PayltTHNvodgKoD1VyWBEzcnlfy8ehiPPT43GOfvzWr+lrbVv5auVTtqWZ0T6pecvx9eh9h5d7jPoKGzn/bmFrffEW37DCHY/6/bWGgMbctyXW2er/ypndQ/oaYdqUU0IEIIcgcTS3M6r1TkFSUNR3KmHGJX4im3bTAFGAtwiICJSxBwnzNOEOE2IIXaEgq6hECS+eZRvIfUrESWEtlhuczILcnO/bsSQkHjK/ynZl13s8e4eOUUCBiR2shHzIDBVy3Lxxl7dvNfzaj2uBHpKGQGEyDVuOgCN/S4MixH/ObNanTvLdb2Bfmfg5qQdyRVu0rTT5knY8s4XY7cdjy1jhzw363Nfj3/+yI5qkZUZhNcAfShtCXgNAEj4sGkfufIy826IEUtpa7Un7xiyln9SJvxIwPL2L8yoO75fqTLEHwEQVleeWNi/0mfSJ3Ebj084ZvHCEFj7Te04M+rcIgBTIBwOc1HwCKuus3VFAiHFgBAnvP/zD0w311ju78EE3H3+DACYpgNAhBjkSbesS/Wq4MM3AGAybxJyjQGs64I4z+pqXEIahHlCTnp/VHGHzSsEEaZ5QgiENWesSr5bLxf+BPEaLyP++dNfmPkVptczsoZ5uMeKmQGmgMC5EJ5WypUb40CEeZoQGPhXfo1b+iDXGLhyJPo5kPth7woNeXqBmXA7mx4HAhAI6m7fh42BKhI1dulNm+nE8aaORlGgb7e/Yvtom3+7TmRcHnp3PPUkFEWR6iGkp5qf7dUaQP+oaNqxY8XdjuF2RpyvzGWrrgXq7k4+IW3zXYr2EbK59hzvRQMDAwMDAwMDA1sMAn1gYGBgYOAfiD0q9aHjHcrz7PHAF6KwtXziW38XoSM3+di5/G3Eqbs3i5oLlRjqZ4SndHwj/c8dgpCrIBhwMdOLxQ6VpLWtD8+ikiIbQUXgRELCteJu993GNa20SW1vdn0xAh5o3c4acYKmJt6t90twLtZmxu6d+OHxtHHby3Vul/oyVFfbe3X547075M/tURfUdafmrWEF5HSVx/s09r+S51TjjYcQEHR9T1PENM1CoBOBwoQYg5LdQRgTF7+XivKO7DvE4sJ9niZx4z5NYpmtLcqOiA5q5R5DRFQ38TFEABK/3Fyvi4W2fdt+pHuStSl463NUYr80lOoepnnBarEL20K1jszInJChJLlashtBB2YkrkQug5DAMB/cQnQZRUuAxoKW9GIRr+oAlUglApOUY1RTnQnOGt/vyWUmcJ18T0Ddt74e2H335NkVqHgMT25uB7xEQMQd3uNen1GqGoYrfITMHHUNjk+4J4apQl1xu3wCzHm/qYuxnn+j9+U9ZGR7y/agtcAeYwDUDbtLyUmOZ3oJAnAfPpbnCkMs2aPWBzASPiIBuFM2n1jmSkCUVhQS28ZNngFTEAqeAFH4IEKIE9a8AqASFuF+XYC0Aky4//wZIFHomFZ/PwIyZ13Kun70mOJc0jETKDDMwT5B4p8jMTjbvQpAAq5urgEi3N5+xIQJFCPWdcE0TVhTRgiEKUSsSfaSECJSzqC0inqEWmQvYIA/4N1fCS9AmObXONAEDkdQJqQpyrpMGTMYmQlHADMywIT3v/+JDFGgM/IcqPHPryDu+m2OpO46FUWG/XVW9iU9zvWCjOwT3Wg3TxDWPcXez7imsv0ss+0eEhKiV/Tr22HvNXZ+Q2DXGi5qZ+77y+zKsEKpjEv/BNzk93WU11l+wnieuG+bNz1N3b2G2kO1vhkGl0PvS8N9132afbKz7etGg7nxaHPqb6+HSn247oENdgb4KX/znjp+yt/bjz3+krYODAwMDAwMfDkGgT4wMDAwMPAPwZ5M5ZQAbe/4MWn9uW8hy/HCgQe5Bj4lUODNyX2xY3OxGzNPjzzcjm391arczpkFnbmLNOqmCFNUGhgAZ22nLTfXkE1vqDk2oSAhwJzdeu5erNvtzqrAlFtL6urS3ZE9Rgixz+mpFe2fzZq9IWNnLe7HxRVjLSM36q1FVhV+c1d/pWBCNyeMkK/3U67nZiT7/5+G3Zl4Ycr+LO2c79v2PKI02q3ra4Dcpz1jtJk/c3JiWcaSmlqhOiDrsaTY2RxcWiZZi8VdN7kZX/5jsfL25nDk/SVYgwhE1WWvXRdy3FaM71uNdR6oWn3HqJ+gZHaMmKapWIzGECQOurpbNyI6ZXWPnnL1dpFtjal7cmJ1Kw1QAIiEqLe+Elmsc/MbD3FhzASiXHvAQvSUcSYojx9ACIBy6ObeWChOURQQl/NVecaPtWyXOis4I6eklrCMxGJZnlhctJtFPABn3Z6lfbq/rlRnQtC5IcXXUA5FgcD+UZ2BbViI09gTftfOdecegI2H0cRPEaQ/1N6zIPcsAXAtd3RnZ3oJUVRIuCf39NR5eg9GcXPcrxWQkumuUr1+xYAxXwTGyh9k7RCV/V3+yTyf8AYAIeMdgs7J3ns3GenFQMJHrLp+mVAUL6wJ8jwNCHiFhI/N0LB6LAiB9KmSgYwS85oBrKItIhbIlMvaX8R9AqKGamgVJOp7TNK2BzBAooBCFLCkRWpUhnW2kYgyTplNwUZuIJOuCy0vkoiMsiqtXF3dAADWuxUhxjJuzIzjmpDXFYEz5vgSwH0pJwDIuoaOkD1kZSDke4j1u9w7UUCRNqYMzDqnE8lIRX17CQTJD9uPZTgCA1nd8YM1fjoBNwDutbGFRC/vLP0s7d8udK+n0O7n7H/0z8i943Y1UyHJubQp2ziwvbMEWPxr5pbubdC9++12Z2c36d+hT63/zciUja5e8a9tp0MM2a6qN0j3ygiAXYiTTc6yBdQHeU1T39r6vN6LUqs4ytr5+n7QVtHeQztle3stispzg9BOj3b7Yl3z7WVdEjsdbQ+3s8f30V3bJKpz7N8Je2/CdOb693z81Lz/Xnd8YGBgYGDg78Mg0AcGBgYGBv4B6N2mbkWA3bFezgE7AAAgAElEQVRKEi459nKk5vg7wGOE/ZeSEJfkM6F8tcxp21Rl2m3rGqGeujQ+VWcntitSNzJ5Jft0tR3FKhNOomwpyQTF5iBUSXQVCvbCzhpDM5RyASAlF194000tn2v+Qktau3KVW/q5GXQ8KqHft4ddXS2l7+sRoXMVllbqpf7P3blebOvnltmxU5cDTRntCGzrOIdWtHnqN6G3HesltXbuqbP9DMhmzRcV8fgc3N690haubWqvUydYB8rddHGsZXn0o8nOCruLcO8XpUrQRXZuc9LPPieUz0ldk7O2W36LQS3XvduIcrUmJ8i1aJaqxYpU1xIIE8SSfA4T5sMB8zThMKmleBCXyiHEQhATBbES1TSG47JgWYT4WtYVOUk9AQGBIvKakMOKNM+YJsY0BSXqJ4nH3NwHGQnOAKKSzawuz9nuhOxN5ha97AskbryzJjTyXGKiExIIzEEs2VmjoSsxaeUD4lZ9WRaxfGdRg6mu4NVinP1HrSWZywZrceXBEgPbbi0jl3qsx2aBbveRwUjmOcRNH9uXfKxiqkW3e3nz6zI0XM0jYfvdlwje+2ceoZK9Qvq9wtVvV1h/X/EZf6nleY92H7ti0nSMa5Z5sBgFTYQXDLz41y/FEPb+7XtkMD6a0kbxqODaaa748Q6mHPYLv8Hh1wMCCHd/3GOlDyBSkpyElI3CeSMT4Y4YL1hJP9d2BmPBR9xRvR9ZLXfXnEAZsj5V0eQ+LZijrNWUE8BAjFLqMaXSfgawLgke3jMCA0q8Ase0wu9B/XMosZiqT4iyvlit91dLqU71lStec8B8mHB/dydxnJFFkS8AzKRu1QNCBG5CwB0zaGXk9ZPUGoJ4wWDGzEDOcl+CBJZAxDXAwEL36sJd1iETIUbGDMY9AZQJQcfVgqtc6XEC8IKFeJ9gCjXA5wC80F5NDBwg9/TePc9Or7vuSvHWQXVOsXgXkMeLpe9Xz4nVZI8I3dur5Xhbb3bvXtB5vme0HXfOFbL3REv2WtbvAf1raplP7p205KR2vu25Sw8IMJUq71uEUd/96nPajaYvqivWvFf4C+zukVVgSqKb3lgnKKhHFH+VN8+4+pLqEpJL36w9qZikeNMTauaeV9jx/evfUz36Nz5y7zfcpSSY4tpTdvYfH6Jw6MazuV+46G9eu9UXHWO77158fKZtj21rVQodGBgYGBgY+BIMAn1gYGBgYOAfABOj7p3fPabHHZP/4xz7wrtvga2b5R3ygE5c35UqnCMIVYTVjw2MSpECixwOcG7NfX0qUivuzU+1/fz9NEFyTyAWl6CuR13VAFhJHBHsWVNIBc+Bal5SN89mxQoATKvarlc5YqlvI5vkYmXlWKbKO6p0thcQcs2+6XsnY3R5qPnVibudwIq7fF6Eu4dKpbYi9z2x5gPYNvqBup+CVpD8HKi9Bp677Acr5m3t3v1xkUb7dQi7bpncwm2La1JWK+KWfNq0qTk+R0vw5tiaWhQSqPapCu+p7l2OQSDSeOYhYAoBk8Ynv5oOmOcZh3kuLtfNdXtKjOxiEoMBTtVyOq8J67piXVas6yrkt1lWy0ami8kGbhJOYZKB2JLo8r2mDHDGmjKytsEsvm1NEVj3AgYgsZOZGZlXcLIgCqY8gHbDYTgCPesHyJyxajxzgNXNOkrYC0+glxo2ltA2peruXtvdEhEMNO55e6LC8pO2wX/7UfXTxT9HHgPGlvB6CFZ/dktkr4hL2uLzZbTWshkfwFnchx/pRHnu5YKJcN/EcZYZdiU2uSU5xQgi4Pi/f2It+0D7hLZD8xhh+4a190jvccW/AnHChBmB32Ch97Uk0ntci0Jy5vWBXoEgyha5e1+y/pMuciYGqzeFq3nWObsdx6pARqXFbRqZLISg72i9slh7rr7YSUmJRTWEWP2yaPiHJSV5frKSiViwHBmghIBJY6sHhJhhxBSYkVdxNT7ZYrGxyraNmx8NBlEoigXI96V5AVk8UDCUXicsQdIdwEhgpO4ORxZFhpUI129e4fO7D+XaS65x1M3VPvnMDuffv6o6nikhls3Zv+eVvOeOt3WYb4S9XLvrhJul0qTz6bM71xN2F2GTmHYcntdjt9ROg8W7SlkT7PpanuuuP2XedK9LXcX9+HU7r0+87SZ373JufG3dA37MqTyLpAZnba8bRnlm+T6Vd2K4AtkZ8Wtbi5v5tjuWv56w5wqaxE++3/9AmBJHM0TUfG2O+795d+/FuWN8wfEDbbu0rYM6HxgYGBgYeD4MAn1gYGBgYOCfgOfny344PDQEu9edlOkS69qNwINNdCblNOIKEyTyVpBVBWmPhJPPBTLxckvC7WZRgbYJ+JirFWUvY7HYwlJm6OK1Sg1Z7ChPNtP6LXXVRhBEUElZGps5I1ROb0cAXG3YqRzvi0gB5/69pN5ybpdgP3kvLn4o/eXXv3982QbzHFvTqTLOz4gt+OSRI0ZNhg1nH/fUTvjF4BZpnUneuTSa3jCjWKWGILHLCaTW3xFzjJinCfMkxPnhcMBhFkv0OEW18AQSJaQ1idW2ksoWl5zVWns5LljXFWkVq1diJbxIrCslkDXBx0wHCFMh0WONZa7cQkoJOUm9OWVxFa8EueQWF+tC+jJICfbMSQh+VkvXnTtGNkAs6axcVgv2xrW6zpJcSA2xVM2uTFaWpDrYb9Si5H8Sd9c2JqVlZb7YIcOP0sWrp2xWj/X0YPudtMC7TX8MLJ/zLfJoXEFdsLs2zAAWLfPz27eY8Aav+SdkJHzEBzQKCwXU/GIQPru5cKWkKSAKX3f/+xeAV5jwERnADQfcka3q6MrV+QxV+nDbxf3bFYRV87xHYCreWfyzKTDjVQLYFcv4CLH7fomJRchixK1XAmBmCZUAICMpSSxR3Ek9H6QsBLaFZIlRiGxzwb6qS/c5qP27PptzWsGoAUq8/4PiQYbcPLVnr857ibst5Ka4C+eyBxFWpMz46dUN1uMivmtykHkfVkSqg5nXBDAhMeNIjCkzQg6YJ/EL8/rVC9x/yFhwq/Xr1CcZnyA/pBdEEjud5Hq0cDKBwEEsd/9Kq6xwzljff8Q1iZv8+c0rTFPApz/eYQFwa+ujJ6Qegb08YZeRf+i4PgMmR/B57L03AmhIZl/WOYq4edKZ4tADmrCbGOtaUi1L5wkYnjuuRF6bv4TN0JR+dvpW1iPraD3vLdpPKwp1I1MGp6+x7sytdfk2e71G5RG4UR7dfRfZaZr7A6B9NjR/kOjPyo5SZo0g0Pwl4dLzDps6iNR/d5x/Ix4YGBgYGBi4BINAHxgYGBgY+IfgOUiqb1n+14dz54wqRtum2v8NoBPKYSul4BMiTbPCfCyz61uyEd75X0aUo3FVDBV0itVmJcBNKBlCKES5CPPb473adtsmtUuZaA5h0j2hDWiTqxDvm9QevStzbAgrI4LKWLh6trkfhhcMf6kr803Bl+CbScD4my/+lp6oMaj3G3ZC/YEZe+5k93Ltx239AnzJ+Jk8XdfjFCLmKWKKEw5RXLFPccI8z5gmsUafpgkxRlWyEeTMwKokdlKr7JyRUsKyLDiuC9Y1IaW1EBVCYEUlp6PbOyax+p6EcJtiFIoyRjVUF0Iwp4SkoSqyCvfJiDZHpjAzUkrgnIXUz6sQ68zVIr/kNZ7Z7XGaLykBL7HONa476o5oLt894VP4DOq2KNg+4azflRjPfo9in1L+64zkH3hO1H7U8BrSHjIC5fzUKOjDSpwmTnpKrqWujAa6PHeFkedXoOLefEXL6WSo5TIIr/ETMr9HApxL9y352Nd5r8TWgYHP//sOV7/9IrGz+Qq3v79V7zTiFtvPFyOG6/O+7WuGszp3ranPE70WTu0+n8p549cjk/bPk2bs7pHbm3b2nhhkHVOQ2Rzs2QxCFncRpksifdCxyTro5dloZCBZX9uY1ZYeXOdAPxbvPrzDYQqYcYXAIkpKAYiz5FsWIdOJGROoKFQclAA8BEL+xDhQEJJd12QsVsZ6Z4jqnNE9BBTAJGvwqPHdCYQ5WA8nLMigNWMG8On9R9zIrcK19vMzyZj7d48b9XByd7FW4w6B+UhsQ4/sHVX0NV1y3JfnV3uzni5+3DFiiDC30Jk13AYR5hiRc1Ye90SBhRu28Ch+x2sVf3beDKUI1vTMCKF6NOjvSf3fCiWgS9e/xclc838QtO/Z5uVh1/WVK6TpfsdeegU916F6I9w+QJ15PiMUC/TSzDKmgL0bya9uJlF9/n0rnHv/+ir1/83pvyX21/nAwMDAwMDAc2EQ6AMDAwMDAwM/PPZFkZdk2iFCnUDqofIacVwvtSjuHbk7/QziDa5CwyIqLLI3Rw5xdd1crDKVSM+ZG2vRKtwy4pyaD2DkAyB0wGmQslLyzWo5V2kZooTdsa/dK22x4yoo5Ub+GBtCtRUIN+dKjQ/PkvMpfiSx2j8Xj1lFVVatQvMLbyGXmfdtYeR5jFGszSdx0z7HWAl0R5zHaAS6ugVOWUjMnJHSipQyEmekdcWaEtZ1wXFZkXNCyizhIUIQQoMk5nNmRlKSeuLqjt0+szHdSqIzoOR5bmJ+Q8nAwvg5BZ+UpU1CoAOyV6C4opegzAB0H2K1Ps9q1SsxzzNWO2fEYLdDtLa5bpzhFX7cvS/N113X3P1y74XDyHBuyG/zVGIpCuHT+N01Ysb5FenIl55E3pvGlq/M9bNwNJVyRa1vkZ4JOpW7HjNZfGvCpCWYy+3Kz37S3y8BMGb8jNf/cY3b/7pFwgckTbt07eCdpXtPStr/8WcdLk/EN0psOr4k1sp29iWAa/4ZBMLqxiDonVpVmcS8pRQj9ujqgRGz25GLeAXgY+0NiwLLPE0aZkByeEW2lLIQ5wR8Ph6lFgKuphlTjAAIMQYwizP7nDIi5RqeYOcGEWQvSbreeovZGGQSLGrRbUo05lni6jAXwi5jRVruMPELRAQsy7G0nbOuDV1CVyHUe0oA0524XSfxkRGVsM9cwwhwrq7wkRmBGUK3y725jjJGq9M7uI6EiIg4BYSbK8yL+ARYk+Q7AHjJGUvK4JzKffqs7003DNw94vFuyhi2v/UW2yfzXV7F34KiHIXNFnMWAQR2ipdB9xoiQtLzIUTcXB1AEIWMT3efaygdm99cn6y2cnp6G6Vt9T23WJxrHAVylulCKlPjVSRvene6t0+5J42SB1DDk2zYzK5ORmG+2d6/N7s7qtIf296XZb0buY/69wUVP/NU8mojaxO+IXk+MDAwMDAwMPAjYxDoAwMDAwMDAz8svDjsYqrAExI7AmZLuJd+c549t9IR5Y5Mac5XdntDrl8Cix0u8v98xo2ltoLbNhgJHkIlx0MQYkHcRFeSwdL7thfhfN+umqgI61oi3AkGffpdoSahdRTdkuBGg5OIFFEtb2pKX/eW6HmaCLut+yvhe5B5XrrIviYeaEu/Gusvt2hr4NF67TsCESEqKW7W5fM843oSa/MpRCHWQyh9MatyZkaggEDQ+OYLjssRx/ujxgdPWFP9XtNa13cICNkoxAQiQs4ZIQQhznNGilEsvp1LdssfYyykP6s1qkepJ2dx/aztBoQsZwQQsYR7CEpMEYFCJaGL+2ktS6whjUSvpBb7D7V3uCFtColhLonb3atnJCsB6f0hUD3vCXi0c8uXvatQReRi5LbtfQiVN3ncYt2QV/5heGkZ3spb83bO02v5AIBbEMRC/e6/ARAj4jUOiGAwZohl+rHNVHDQeMGmsHGnBPuVPn8+G/vLEnO7bWMohHcobebmmW6k78zA4V8/4e7tuzJWe1siaR4rs5J5jICXuOFP1Q09UTOHbPbZr0nXV7kNLPf2bllwNU0IIQBJCLZ5noApAiRhE+7XtWuVKVVIa/buLRGBQtDxsQpRZjYzI1FS5RGx7E/MSPwJ0woEugHpfpF5QSZCJIlPHiDKEJkZITOmKPvVanUoCUus98OI9KBtJplNE5ES6WKBnorCgbzTTHpnAgC+uwfFiBUZERlMwJGBlYB5nhAyAauQ6JGBW3oced6O797vy3N9a3xpWzJn2e8RcIiTMsIBOS14ffMCt5/VVX9Tn7NDP9GAdk+SqOmmzFF2d7b3P5k3pOE56jN9n0S/xItQuzdTfQR078Cn/gbY61Ftt34Xryr6uxRBbR6GrIdsebhJxn03u1Jqtd/mHedbW58PDAwMDAwMDHwJBoE+MDAwMDAw8I/HnujGzlERWvHJtKiXt8ePJc6/BGzkkVjjEIoxTkNiPQQjuM59fLvbsltiSGSV1c1xJbbEVS+4ugvthYNZE3qyHFwtyk3EmTRjQLWZE2e2W8Houd7TRWLTvXz1O5xL+A/FU0Wf34PIlP2303yg5urpdfstEUBClOvnMM+4mmfM04w5TqoEY5HORbi+cgbzKoQGSZiE43LE8XjEchQSfVlXsfbWGOWJM1KqdtoRAIcINjtcHZOeRPfhIfo9wyzmezQhJULAuq6Nhb2mElITQhQIx0BFSUDIPBYTR5Z+1w+UPK9Wjuy2eLu7Rrq2yjBUxj37Kzt7eY2qjiad424cag0HZtxvVkabIZQc+yvo3LoSvphc7y8DwcU+b9bI5fozJW42gKUjhYsVqivTKzAkvC+Es1msz/gJP/3nC9z+n094h3c46CI+aouOqj51pfv6a36JF//vS3z6n09I+IBXLH26VRL9hm19Ez6TuO4+8GtMiIi/BMQY8P53cQvv9/wM4O7tO2Sbf3rOGmzqAhRqbGWvLMD4VMp64dw/m9KIzFFRXJFjI/nlc4iT/g7NGC4pIVC1GPeeHhgMDagAIq5rB0BOonAyT7MugIBAEcu61HtNATOEcLaTiQFwRlDSO04TCITjsiDwZ/z8r99AkXD/3xMyJWTcgkEILEKnFYyAjKPOjIP2ZIq6QE3JgWTGxHUFWOq1FZ0AcIwINuYAJgYQAo5ZFApXDd1wzAlTjDiEAE4Jc0pgFs8Yt7pQiYFfc8ANAUdwIeUZjLtN2Jr99XSp5bmVYnfxaz9pMlcCV/wSCR7T/j0E2AabcX+8K+cP8wHruhhNjhfXN2BkfL77rF4qtuoHp16zRWnDMnBZlzVv3fNIieJJlUUBUi8kdcd51OjLSzdg/TwxXBuSeMteb3tmCit9mUbUs7vADKbWu0ndm3l3ANsq3dH38HI2MDAwMDAwMPCDYBDoAwMDAwMDAz8uzgizmjRdMnIyq0qTONG+kzOZ1dYeHyHFsEvnKtR8PR/XpHuCBNUT/8GzENiSf5UQF4F4dRFLCCGWa23JtX3eTXL9LZaj5p69qY+VOOci59y0nlxaO1OUAFx39oaGSw5P6bSW7pfIBb9UdvhFEdCfUWpO3fep6z86TgvVH1eKCaOpWCK3FKGzDytk8jel0wkgJZZjjIhqcR5CELKuxDhnJZqyuJ02y1UAnDKW5Yj7u3sclwXL8SjkOefiXp1ziYaM4rrZSOtmL+Ri3b6naGDEulnMW1stry+HWWKk+7KqN4yIKZDE23V3gSEkELGFhfBj1dLgp+7bHoHr8zzLmtGxa63YleCxmBml2X26cuHRrZkBVOtIci7Qz6MhYYBixfnQ/nK6JMG6Q70fsFVCsnH3MZAtV15XvPjPl7hO17j77zskZAR8LLHWAbFufgHg9X+8AohwwAzGL1CH5oj8HjP/ghWrlks4sFybEDH9OuH4x4LwryBkLLZz6NRvO7Y+9HNq79vytIpjkiJDQhlY+ONio85ylaDPV4J6XqirYzG35Mx1ORAqee6I6EL2macINhfUopTALO6wyRF4lDMmCKtPMFfcQmwGFgWC9//937jCG0RMCHiFhE/IhGpZ7jbVKQAzrrHSKietTUquMsmMMCt2e68I6uEgaNqo4xcoiOKGaswEc7EeJogVOyNQJVDtPh1J6iACJl0/TMALrkolxXNAh0db1n6DB0ruFJwAnYt/s1XwmrN4G7B2pAQCcJgOAIBlud+8Q/abjR92b2UtnLZd5LrnuhVILF4NMoBA/dDv9715jW+5awDbcezR7Bu793rnJPtO+dPcbRr67KCax9RThYcnUZZpGtPv7ufa9jfjn/JCOjAwMDAwMPBvh0GgDwwMDAwMDPywuFQesyHP7duR6IaN8KsIt/YlTtyn6y9ssp06/zA8RRTMUjwzQFui3sgoolBimpuLdiKxtgOoI3CknNa6NCNnbs6VEOga5jRDmHMT9MuhCsHZd1V+Bc/OcEtU7g2LowkbPNYd5eMpqe8X/y7kueFL5L0tBVtl0CZ4l1/befitXboToHGQXbgFcscuLYuGi1iJKvKaxH37US3Q1wXLIq7aLVay5LX6qBDzgcwGnFw6+Tai3M7560agMzPmed70ydrJup80+wpEYSAQa1z3udwVzkKHUtKY6jlDLFarHSKZq/eOvLaxtG9/jz2JKU69d58GJ0DNnuLnj7WnJ9GPSsK0YTWCO27VugyHTc3OYhz7BO7B7Zt7+0EhELt6NPw8jDv1dZwl5fnhfWeBEP3WztiVb1apGUDCO9z+D3Dz2684/r7gA96VNr4E4cVvv+L4+1r6F6cJx7s7xF9EQez4uxCzET8DAGZx5o2AAPolYppnibWdVtzjHd79BbwqxLWUuRAw27zn6g0FYFyxxEy/DWUBlfYRezrPZlU7Ov3sopSK+3d/3RuhZgAgU44gHat2HZveS9I45IHC7n62pBWcAHGiX1fINXsvCJ7B5HKPAwiRXkn5gcH0GR/e/Qm6PoCStJFSwITXWPKHElv+CoQjZzAIvBIy3wKJsDAjHmZp57IKMW+cOqFYTDMDpMozWePHJwA0SR8PAI4UkKF7J4C8HIEQkKcIyhkhZ7wiAunWESDx1s0Sm7SfP/32E/784x1uNW7Ol7qh9vP8kvPPBetXoFb10FuhQ58pKecykWJ4pL+dbs9d1wXriqJEdb8cATAOUZ4LN9cvQMRISdbw/fHY7CGEdu5TtydxsTCXupk1DIj2U1VBpLxSLqlyhl/LF3WuPie/ZB5w+W/nD49SgbxPO48rfRIAW7ftbAvGnj21jkqs/9PeDAcGBgYGBgYG/n4MAn1gYGBgYGDgh0NDGni50Al5mAnQ+vz9eUDdI7IRPT4B1/OlIHIuy9vKK3/eNcqnO0HKn0IhSUhJcNUAEIuzLm5vIczbjyfSfTOMzDJBmxHpRp57a1GSmlsBrPvtiX4Twve3pxfjnbIH2huhU4TQ3wmR43+R7fkz1P+0fD88LujEqXlSiSOdNe7rZFlc41rjhOXh1wDDrEJZY5uvWIMjz41ch4VdMPaPS14hMVas64q0pkJEG2FiMC/PxStFIejVDXdnQU5ESEk0abyg39y8M3NxPe/dtpvluY/V7uOoW2M4Whv0huleS0YuWJ+DxG6mnGVPDAzk1hW2nwd+72hJdUdxcvc46TYvI8BbO9ZuThWip5u8mmjW00YoM4TGBJ/eY3z5RnrPXRnY+e4JcJ+HAFzBiClSjpTBVC3CLW2wtCfaZ22y+qweuGN051YI6WlEupDorYtlmbOplHuDN7j5jxegEHD4zyt8+D8f5P6mJPMtyJ2e/yWx1Ne3CSv+krLptcRs/pMQ/yNizSvyW8YBwD0TPhHjDTvX87w/Z+zZt3evjgBAjCtux2pv3p3DyXRmdW3KP9rG+xPlZK8R8ACuWO5FxCswPrkVVOcy4YWuEyVm9ZxuPY2C0orbQnpGNmKzCqEINwi4Qwjigp5QXZxnWBAJN469mwJovPTi9kaIYgIQwWBVOMo6sxBlThBDXfLn0l6vkGLd/tevPyH8/ldp952uE8B4zkc+H3RinXld/TZgxtV8hSUtWNL6t1aVIQpRWFni16sy1vV8wLquyFxDGzy4Rsj0OuxJwWVuVoUoU2PRI1Y37/rQs+cDXH0WkqhFfXnw5P6j7yV3Pzwhb39zdJ5K/PVime7fZXa0MMqfLzZnCd0T62vjH/E2OjAwMDAwMPBviEGgDwwMDAwMDPyw2LPc2Qqb98+T+0g6rum9n9HO+tJL26oraFfdJcS5L++RMHlYjAGRIpBdTGEHI8mDun22uOdGovt2ZHUZy0wN0QUwOCXkNSPnJO5iWVy2UrFqA0wEyaxWQk1rvQj+Mphs0BNBnkz4Uhr7KW5X61yhx+e3Yp54z/08HSLIy2Bxr7ceEIwgRjOY+3fmcuLpbwGL29tkhC1XBR8wA3ESK8EQNESDnDcrb3BGMvJcSWshJ1SYriR6ZkZwwnwiT8jXtnjLaftO6paXs7qE130GzIghIE1TSW9EeXIEOtBujUQECkCeoCRCO/NNicVivEcicfUcIogZKUeEkLGWWOhClPi5YJSocHHk/reajBzXx4FtADtj0exFO/Okfw5Y+tU9l1RfoSgx+HQzhNAExNJ2Qc0HoFj2mlOQU7vtpGmC+/bNLXsuuf2V2jx9qX13D5AxtjauXRqj5eycCSJ455rf5e/f/gUAeKGzdMFHrP/1saQMeAmAcPt/P8NGPICw4C9nla3W2vyhkOgf/+uDW+KEN2LejUTqklzPZxAsmIC3gr0n4N4p2HA2ohktoW1KH8Wgtx+5WsaBq1eD8n7Du1OrLBxLe1PyWOoXYNzCoh14C/WmfFTyeMbLQjSahW5bJsC4reuCASS9V8n2Bv+M1XcQAByEtC57SyAkLMg6EyhngAg5BNnHAmkscyFUxYJaaiYQgroHjzZdtaNR8xJIyoziUWNNSdbufIUMIOeE43LEtVpIR+2dvdu8//M9AEaggAnAAsbLzPhU7iM33Ocv/Fr3jA94d+qZYWvcPZcefCuwOfo3P4c+H+8QiHCYZizrUnx73ByuEELAcTnKGJZ50TbI0tvw2BwwxQjbUdO6IICQOCM7lykMu8/BCsCa08ZyHu436z3gMkC2ak3Zc8ftuj5WQpnZ8gy0db1/X9wi4nZFlHQn7w/XD7vST71bGPPdt5td6BnL220OvGlUPSRb+AMDAwMDAwMDA4/CINAHBgYGBgYG/pCEMdAAACAASURBVBkwOdKONJK6dO3vVpJpxLEQUXKSi9zLCdHI2SNv6uwl1tgefwGZCrC4ng1cyKTGmtSRYL0byJwT2hHhamVuJFjOyGlFSmKdlYvgjuFsc2t7TKB4YZ/8UNY+ddc3ff52KOSWka/49m0CTs9rE9Db97PU9T10+FlQBdfcicCdmPu7AEPWnllqm7IMoc7HSKGQSXa+uEmfJhxmdf5NBFpXUFIywt1QT8ACaBVy+gHpZfpgIeWVgWPdG4XPIIQYa1rmEnc954ScNeYy1z0rkLiRPwIay70lqeoWU/fgqBbvzBFARsriVtqTowxW2o1FUUg7FVyZ3jqPyOgZDTlRjuqwUDd/qr8N195uDbJpGBGV84U8JuCahR40q28rL2Pfffrs8veoVr6VhIf77VUTjDhfy22X3k6oxFgh2dG2+4A6AhmMKz1v7TXr+BPcTkFPjvk6jRrbdyr9CcBLrHiv5LmQuz0JXcv9UFpS66k3KrBYNUd/3/Q7k1kit87+z/VFTpxkyhocHSF/pfMu6/OnEJPum3e+7bfsDC9B+NTUKBbk5I5Dya20MxZ8dGP9mM2/jmNtl00q0vujCivmY1r3YuM/ZahIvepI/GprfQ3nUpVXTEEglQpF0SgaUcoA5yTKNpD3FHsvOkwzjuuq9Un+Kx2RpGN4qwo4N2rBjlVm9o3W+1nbF94Q0ntJ+5pl/pO77gflMc/mUzzrc8OeN3ldMUVVaiDCcV1wiDPmacZhPuDu7vOjn5G+D7YuzdNLb1FdUjEjBmqVMrvHkh8Xv5dXeFUom41+tdc2lT1CeWZRFajvBrUzvHWfTnt1dxWUipof244QTr9wecKcfQY0J3l7SlN+/Re58kz96jUPDAwMDAwMDDwPBoE+MDAwMDAw8MPDyVdPCmn68w3ZznDSr0pUQU+zEurlxMlSXaHnyPOnwgv0mzYbWe5/e1LdrMxbkl3K4UKcr2sCckZKSqJzkt8sDmuN9xFxtxsfI+3OYCMfPHP9fP4vE8P1ygYXoRPsFivYR9ad8QxzoLTizLET0F/S1Uv68U8SfrL/j+o5+Thh/jeHrlslnlmtni06eQwBOU4AJDZ6VKaJslpcZ0Y++BjhDW9bvlNOJU+tWid9yzyidzFOMAWbDE5A1sDCmcXanEK7F8leo9dzLvurxV+Pmp6zWM+DxPK0eNSAxmg3hiDIaMTMoMAo6kEZINIVx5XGyzDSBoW8IdfFMg+UUA6u7967CHVj0gxdT1644zqs3J2XgyNJ7PIDqLg1X1EtwXt4dagJ7bT1hCvBXLYTZryQ678EpD8zPuOTkuovNDgHkPCx/LbyF5j9b2tdbkR5dZKMJt8Kcf0eQVjA6iKc1I55Czs7d+ej1m1evNt5eIuIRgUCKMfVw0CoTy4YeQtUbwUlJ4siA0MI7ATgM7n3ANdOOvFdE7L/Ajb9bnOQruP7bqEduvebnpTsS8qOOG+bU0e+Ut3tffOe0usoClndeFFn4D7UONOAeahx/eTs2ke4YfEakSnKPkayfjNFXXvVWn8GELK0b1XX4hSknGwW/7YVaC1X02w6jkWhB7A9CWDdFwhAzozrq2uAGVnL5xDUvbvMgSvoe8NyBHLGPM1gTlingGVdytvA248fcE3AXffQPfls3ruOndlB3TkllE2x4EsfVZbf7xc5JSAERFVqSnlFxAQKwMubF0X5gYiwrAvWnAD1KJK7d+VA7dxiFq8ORlTbdb3NsBAhsjeTeHag9p0VMCWI+o5bH9uq/EMB3VNN7zvpTlXndbNz6V4caRumqNThFl95FT/5kuT3DUIbd2oPet7Gbe9vCf8AcpX7MejLkPf3r0uhfxevUQMDAwMDAwMDX4hBoA8MDAwMDAz8uOikM7uCoR0JDnEnMu7cKnJzugq/imtkzctUraBORhbshF9PdePdl5HTCs5RyCWCkEohFKstX1dxx15kaoQYI8zdM+dUSPOUGdlIc84lHqUIS63v3xed+hi+08v1H1O+//2tev99jfq3R38bee+3To7sBNwPjqOtlzN1fW1YnGNOCSkE5JCVQFJyIRBAQUiQwEDOmGIEHQ4ltnlQa/UMLrHVJf6sE7IziwtlZBBvZ7uRHs0JReZc98NVrOYDhYZEZ/XswZkLyS7urQMoE8CEEIBjSrhXC8RAhDhFTHHCFAKiBoAWMjSAkAEKYBLyjokR1f07axvNch8gZOSyZ5Rou/4ZYK7tdUxqV6khd/wQ+G29iY3ekSC+DLuvzTBy3c/s+1xE4gk1frinuy2vL8eQcCvff9ZzM94g/hqQMmN5m0B4iaQELGmfCEJ8BwArGOsDbfO4BzCBcaP5wy8E+hO413J69PHTDYTqbtxzVtx9e/hreSddT0pnqMKCEmi39Myr3yZMmRs7DWkgCY56/eA0NALqePQW6m3unWacaWI7X9pzNq+ODxKB+1jBCMW9toSgCACIsxCooPLOAtiaqfU060sRSdWKiBCDOmPnXMlzfbEzJUNZg+oWPidQqD4aiFrbews1kXXzE080E47Jz1Bpz91XeEif5WqfgFPvT7ZPzdNU1v+aMmKQe3I8LiUk0ByiKkQxgt87O/LcvvfaH7RzWRlp0jJMb4VC4bZLGY1TJ2zXsvSt3WtBlTz3ravzuyoABD22kDCSnRoL9MJlW7a+wxdik7wvT9ukf3y0RLx5ftncyNpIgu/E49r2JSj3+xvUPTAwMDAwMDDwHBgE+sDAwMDAwMAPjV4W84BNRyEoTDhX4K1m2Ltv3zsv176dHIiR1L0xk1hzCR++ddluFubFRTuzkOcudnrOSYnzpMRaLtcMxdqH94fta2HvfnsBcE+o9McmRL80fS/s/VYEOnXfz1HWPwmFbuk4Kfnd0S3UyPU36ZvyvgPYWmQiIAAxZ6Sc1ZpaOmLxwAMAVgIjqqIMBSHOrdOJNX/OQr659W6x1oViyEp3VgK1DJuW1e43nliWPSqEIBaGakVuEEv0emcoZVmXgZAZSGtCXlfEGDCFgDnPwAzQNCMSA0HaE4iQicQ6nQNADKYIBiNqzGyrRc5BKXcuz4JCqhblKOm/jaW7ERsC3PJtPD2cskrv8vaIqC6p7/TchH2i+gUIN7++ATPj/u0HkMYCz+qs/vD/zBLT+OYGx8+fkVJC+kPIwOv/7wbH+3vktxmv/iXjdP/HEUf+hHuIxbgQ5q9x+G0CZ2B9u2LBBxAIEWIhf4Utsep7l8GIIKxg3AH4YKn/PL26zC19vxfvEer+utGrXv3F7ihI2goGYreyV5/OlXnb7Rt7d21vn3ho37BQJ5uQJ+VVoz3fK6wZcT3n1gNB0rS056oA7X0619Y9At6v/WoZ32+2p3re3iFxbc7AumJFQgwBxMD14Qqka5RACOsKgigOEAFXiCUuOxDAQcJBXM0zzCm3kN+q2EgBx2XBmlu1iSlEJV8Za1oRcxRvFUpCWrz7+6NEsZc9LCDZHmVKhcybe/MwSPJz3Ssf7RGH9kfa3lnNovsxzy8Le8Aw1/9ybl1XHKYITrnsmcdjktAgxJimWKyap2lCZsa6rmBmTIeIT/ef7W6AAcxxkndXlr3b9zyZR4Gd/paf3oMQt6tvb63qUwkyN+r13N85ZXir4oZ799V7ZjlM/8XHTKdu43vM2Fu7NiGh9DCg3dPAtWeSTn/vKeVsKntEw54BvdLE9/JONTAwMDAwMDDwGAwCfWBgYGBg4DvBo4VoPu8ztuNb4EkutQGTizfn94RvhNZYwwRQhTBSwWBXdCGdiq2KxsIsaVMurn5rW9TSUuthoFhZZldneIor8dJ0UpLLLGuzCnXTxkW576NYfqqV+brKsZ1Xon1PgGjllN+ZCsnTWJY4kPu1JaC9EPT8/O3zAtVVqz/fW989hhA/Vd/mmE2I+W3EgNT9X+abOw84cvjE/Hr0rPseNpii9dDfUTTHXsHF/vfGxSZn3t5Bd0YF+1Yl99ef0nac3+ckTISSQHpOLEsriRfUijyYtwkjrHUvCCFgirFYBeaUsC4rckp6TutSy3OvJEMk5LPEBxZ36ZxbQtG+Zc1zdZHcpYGlIdI9D2pFWCOtm0W9rSjboynJhpCy7GnEhMQZgTOieQZQt8JBLVczM2KOiLPGWM9C4qS0Qrz/yrmcMxKbW/eATOIev7j11j08086acveR3aYn5Em9BwDE5XA/a7wiVneemxMAELC6fdOTpIZrAC9/+wkA8PmPDzj88jPSnxkrVlUQyKXstCyYr6+Bu3vgV8n/6f9+RMInTHiF9DbjiI8Sa1uVMF7gFe7wEQGE9IcQhoECDvgJK943bekJ2WLoCUB9IuAAwgRxA08Qi/QtuFjTn7JAvwS2N6rn59Ieq/O6O+/n9j35WYkm7IFfnZsZwi3Zfqpd545Ppj+xb6wdUT6XBlQCdW+3PLri9va32c29BTWGvR0/5+OAIR5wmIHjco8pTkgpI+YkrsPNmhnApHMoFaJR2pmT34skcnUMEWtKuj+2ddorYCDgME2Fh83gotQQQsA0TVhTQmJG4tQ8D4hknTP3pZ6H7Z2VfCc8noR3ZCr8PGmOTtZv86J102/lqkcLInmWUJA9MhACRSG/Q0BOKyYi3B/v8OLqBmBGWhcsKSHnrJ5ACG9uXuL27jOIGZmFkG9dr18I0vj1qgzBuoD92t3ra19PUdkq+zChH01ToGpLrqUxiyJF7qZWo/eymQ66nwS736dffPtnRqMA+NDfDDtKOVzmRdZnUw97P6nHRNtrp968zjanfKu3G33/2gsntWlVpww88HiQrZsn5B3jPjAwMDAwUDEI9IGBgYGBge8AZFLap+AH/xv3SYoDmiX0MihyRPm5rASACVkFtyJg2ArKCg9Z2HEqSThnJM3M4HIPTdBkebInTLK5TBahlsU6vRiOHGSQkFLgJn7rqXw+1i/zqkK5fRLyXN0MiRvaC16bsXIguPFQBKLNdD85El2TAqiJqXkq/7Mes/9ZxVGPnblfTjxs46+Tm5NNyh3S9iliegCN+9Jvg739kVSAvj+HveB2c/20DLmS3UUCvlfH5fAKLd6C7RTMihBQgoMl9rmUo8R5CBK2QTMUKiCIxfk0TYgxIqklYFiDE9zvtrLOaLXmJpKY5MzbPGVsebuOfZoqcNcxPLu9aC+UXILtk8wAghLwTn1FSXSY1X0MiDp2OWfEQEgpiJU9q3cNIiATcs4A5UqiwyzuqRBrUIv/ZtvvrNHtK2tMECPfcqH82nQ21u35WuakV8W6m3Dsxps0zRWAGS+RMyO9TUgA8p/vcPPbL4gc8Ol/3+KAV1h+V1vf3zJmIuS84vjHEcCt0oyEhE/4DOAaJIS1jud73AIIOO7G0d43cbZn0YEkxYRXSPhY9qsZhABGBkrf2gLsLrTP5H6K9dNo7zo7kryZh6zWp+55ZvUdydnKdhO72R66LVeeiZfvr3vpzu8wl5V8vLQBrlRvvGrVmJKDYfHPv2Zo2go3ceS7/Y77+2kPFv2sKWGFENUrgGMxzdVypqnwjkQEBLEWT5nBkDUPENaUxepcmxPUa0QgUSLK2ayRCdk8QhAQSdy4H5cVgQjTFBEoYk2rhJsoN74SrMw1Fnnp1pnxFi9GxV4e1dYbxbJ97/2m7Hto57O/ZueT7pOxs0T3bwKW3tcU/XsNixeQhFQ0WcyDyDzNmOIkrttlOLAqmxzVA0AMEcu6YFkW3UOptCeGgFdXNwAYKa+4O96LZ6Rg7dL7UsbY3rNtytRjW67NmDsL9b23n/3gLH5uUpeq7kl2VpRz6vPB7fhtsd1BwPaZyX3yLr9/dNi86bp0ErYXyvMMKOrA5f1QUxHpXll333od5R6W348hV937o+0z+2FMtu+sdjzI3MejUaR+Sn5gjPvAwMDAwIBiEOgDAwMDAwMD/wxw9+0v7AmjNsJevbaxENwWaiRXtTzX707ws3HFqlaTvQvgp+CisKzOxM4L+79EJEInfn8NfO369ur/Vm0gfNv6v0f0c7nfAgo3Y0L2Xu78HQ5msy2wkc9ubyGJEQ4KIArFfW7xLpFSEXxm/R0oIIYoccTTBE5akVlowshFJQdyABFD6KmddjXt/ZsGUe9ZMEUJZombviYkkCgixYjGNbwK6olIlAhCFAv4bBboCZOOUc4ZKWVkTsiJwZSVeGJnWcg6dzpBv2vmnq3iqe7UPKdh13pCZgZwgPzxzgBWfAK9FZftDODmt581jjww4YXk+W0GABx/P+KIIwImREyFvJ7wAve4xQx1F6/PtYnoydbfgJDjImT4iIhXEJWCWwBiYR5BuAYXF/VfG2Jl3rrf7h/zhPP36bnxd6yiU3Nud/8jf+J0zz3BeCm+fBylhECVYDUS1XRPS3xnrxkBAESYQsSaUyGG2d177+7clJ1qaJsaAzypIg5nIdJNGaPga0+YB/B3zCdTkDiuC6acEaOs8imKQldiiRfPYKSUMEWx4GdVZmBVUJmChNgIBMQQMYWoigxOCSPn6snCEbD2g/V920htr0BwCbnb0sRN0dVDDdVUp1QR7HQAYA5bnkpWdkXWazvvLpfW0ZTrmm9/g1RvIfrE6yrw6Yo3Dr9PPjDRmns3MDAwMDAwMPCDYhDoAwMDAwMDAz82HFvmXbHXy1wEp3LCEeeFCLf8jvTeuNZtiXUCISpxU4Rb1dSqCHglrf5vQj+T0D1Ru5+8f/iuGO+ytJWFtRY16AXAZ+Ct+DwZ7+tAd+4pbknPgbrvrw1PXn8PbXhsvh8b7BRb+lmN3eMa91qP3SA0gvMTg/OcQt+9tdB7HSFQsWRsYrx2W5qQRepaN6AQ6FDCJ1PGyiyubpmLu1QKJCR61AjQlLQKBuVUSCOxBAQAdeneWYFuerSx1DWq4SES7vRFpbaUv2AQk5DnSaytwYwYI8As5LmSLybhJ5K9mSbZazMDzBk5ZaSckHKWGOthRUqElTJykudH4gwQI+nkkbHi8nzZU0Cq+wJ12liO7KsURZNkjxBZwbsxz69/fYMQCbf/807zfsQK4IDXABgprfj0+58lTjT9DhzwCoSAjIwF78WyV8s74BZwx9aW9Rmszqz9GR+LvTqjhiUAxJI+oY3v7j1sEPr47+T+b8dsBiPotVWvHOFINmfR2phbl4dbvbMP9r7j0R67L5+g4Z4dp/pRbq+b4xf2vHtvaTen6mnDEdpAy8q50xTakagW6luCEgCOy1Gvtx4Qpik2hPk8yd5h1r7MwBRnrElmkpDhQnqSkaSlH+qBAxFLEjWSeZoxxxnmaSitq4SCCLlY99Y5dXoM22cVaQzwmqeQ+TvvsIw6vqyKPqfIy6hzvnoEaBNulLIuRfGawVhyxqLjWZQOALy6eYHbuztkzljWpXhNAYDM8kw6rkcwi8eAeZpwmGcwgGU5gnNGjBFxmgEW1ZtAQdy/yyaNGALu1+POM6afR/vwe69/n7cdvj5+nRoTOYv4rl5bP0Hfyxl02muP33tOaMFu9zfzHqXry8JMXLJN086s5OarqZV0P2zelxpvAPut3Yy1e8GyUcuo7fZW5acUj/825byBgYGBgYGBgUdiEOgDAwMDAwMDPya4lX03JLkmMEvxKu+tkqOGDC0S5E4gXJJvJU5E6tJSJbQbktoLmguZgiK43IvNeSkYO7I3rv08RTH6Eh7LkezVuSUOtlRhT6b3LsgvwVOJ478D35pE9zgnID53/UdFT16eImmf4nLd5NPPPmYbd6SPygxZq9uFV8gUoFhGJqjLdqorLkBclhOURJ+iCMfVXE7i1YbWnaqGWOATo+H3sXqm7xwBFm/8Ef2t5KkQEUHblLPEK1/1d1ZL8hgCgsZ9RwgaHoJAMSqfTv8/e++6HsfNYwsvkNWS7Tjv5DR7f/d/d99M4jixLNvqIrF/ACBBFqsPknxKuB7L3VXF4pkgG4sAEQkABzAFBA6IOSPHiJQi0poQ0oocAtYsZ62nzAALWR9h/Y6VJzNyxpFTpHlX0iSgtSAfn6pLLg6JImt6I+vvCCBGwpqkd6+11nH4LeLj729x1Dg8P/pRXajD3bfzxYdu1J8AOU++ppP0z1zTW90EVGK8Od+dqLjBt3xy9z6AzeaCA6zn1LoBEW65lQSfUKbrAk8xPnI6tqw/dj/cN4/Sf/qONNrJUB40u0jG7w1qfW/uOjWnVUvlKhO9twhZJ/aOu1mPT+BqxU4mb4XuA+pxM2s6Sh8zN+QUSj/cluBcR3iOWeapPfZE812JrK7SiQjvPtw3qz0hoeVOICpeBFJKSEnmtsMi7uBTTgCJ+3ZORyxxQUDAYVmQGYiQY0kOhwMyi/t3ZkYycvuKAehlcu2WtsKgcmWQabFKbqAl6r0kD6g3ss6j7YYHTWe8v2GzzrF7pb24JbhPogvLfjdsOyDagd4t9lnN4O3og+17tgao94tM7IJbPkbE+STNJyYmJiYmJr5FTAJ9YmJiYmJi4qviMWesNSqWnjx3VjJN/I7ZphqsvLtxz8vbdLwuiEJAXGJN0tx+KmlUlGrcnqHs4zx7dvkOzOaDc9ay2HnBVbHX5GEATwZdmqaUh8p1S5dR91nvm3K1z/+2TPtpfzuk8KmzpL9kLi67fsrmg2+FDyrjiKoNcO273ISrd0/T6LvjQj+9EXht714oXIdqzO3GApG4KR++YOnXCArFTNoTmcEs7shhRLMjLKK6y5XrIG53iUA5F2J6TalY6pKmUd3jWtFFovhweqclzjvl/Olx3cuKercSkiqvc8YKIKiS3cjzvCyIaokeY0QmKtbpmlGYm3dCQNC+k1NGjglrTAhrxLquCCkjs9RHZlKZnoucLuezo+11pOR50NynpscUdk/7rJfRLa1nY7W1ugZe6OeapG1f/PojPv7xDi9++xnMjPvf3+KDq/abC1ywj04x35unLkWp7u6+30ywQDYDBIgFeoSUdQXkDHvy0rUSor4+brs0j5C2OWi931hZiHCs7GrZjNG4Lta+mznX8QkUt8nE1TVz6Fkrqn2Bed8iuEcfbLA/psTbfhvPmZ9bTjdLK5cY9Uwfb764F7fh5FiGug4JQQntLv1KZYYmZrufUrulYtF1WdbxZpbdUTfYRD1GZ00Zh8OCdTVvHLaOkngiRYDkbPa2LO3ccrMcEGLEx4dPuiGp9tsRgo6RXLtmV95aPxae3TUxYbshAE03KbIZoweXrb0sf/0Z7zXRfs3MjVzxc7GVhyGbD8xbR0orUk5YQsSLF6+QWY55ABGOKQHMeDhK+8ZlwbIs+PjpIzIDtzcvcP/pI17dvhQyHUCMCz5+/IDEOg+GjlhnT56PSPRaZ4ECbOOUn7Nzln5CIZawvoqaPspKvNPmJ8rF8KSzZvLsoO8fN3H430Je6JVHrF6uHGztReP3XEALriQ6l6mY6+OSl94SfXQ2+sTExMTExMTE18Yk0CcmJiYmJia+Owy8rsK0P3vEeTkzE95Su2r7e8uHhuQqvEdV6MQQcYgLQNDzdYVoocSw84Rzp5CVeJ9YeMsFwym8mic7V+4+X6+csjSNNvPoCWXauV+edYTbqfPc6czzL42vRZ1/bcr+S5E1J6HW0aOuy83flnry30djcExROTx3A+xYpm/k0OCeEOVcrLAJADKQ1VqyEugBmVJDAsQg1uYh2rniGWtUN7s5I4cgLoxDBGVJxzInpDY3im4G1/FJ9azUCyrAbe7wlKmjMiozU4RoTqmQ0awyV87bjYW8WtdVCHMi2eik5HpQF/YgQlwCmCOWmLDGBWlJ4iJeCXSkI1aWTQZ2ZjoRFev3bWkuKLEjC/buJVBxRW53P0J+tH/84x1e/fYf6JHCoBDw6X8+FvIcELJ9m7vLsKXlPg9kBnmNjLtCpi8QorqePy/orc33lBfkyPJD+2DAWLHella7AcAU8Emd39/o/QfwSUvPhigbtO2l2LOK/9egIeGeLmhTVi8cJP4QspKpDCPVpQcyGJ8ejljsKB7LgTaIeZSwHAmRrCsgrtlOnEG5HunzeFcEp2fZs3PwJZPXF19IDNheru68b2NEXBZwZhzXo3hDiREMkeMZMucsIYI549PxAZnFb0UIAT+8fAUGI+sehwDC7c0tjusqGyt22qInz/tctjMSDxcI9VCOuiHJ7O19vyHIhg1yBHSTq1EWfTqW/B5xfq5N3W+g/reI/73k1xn9POBduJd5gqha5ZvnF92gYeuAcyNhWqJPTExMTExMfA+YBPrExMTExMTEdwlRYpryR76zXhSCWUPafWHXqmpILIXI/lVCxxlX7GmnliVgiRFMBKIs2qKUwF4brkQ1q4vLQv5dq2yv5iPFvahX+V5hmPJ4cPs5sjT3KNc75lX+vHi3j2FTAOqj4G2YL4sR7felU/484U/FA3z+aj+V1zqc2ZGsI7qvdZXtldzN2PaWUO66z4M/1/dsJgcgoo0FH7lno7TgxgYFIFBUMsjqIQOckJNYO4MBDoxgpLSzuIS+Z2euy/m+ovBPKSHFiBjcmeo5g0JAICCDwMhijWZijVB3MHWkQjnS2FGxtX3qycV7o8db/xVXsU5O+j6QUwKHoCJdZGzIWS3NS4WKjI7ykzeQPAshgoIRAguWJOei55yR9GzfvBJCSrIpSi3eS7TMrfeQjvTty60paR+s1o+kdxviYmeQmZX2h9//xg8AbvAKn/7nEw6/LHjxRtyxRwAPfX+9Ak+1+LvEMwcB6hqfEfEjhEq7R4CcY/6B5DkgioqDe8/c6aP7vAGwsp79bFa7RnTCmBwueTTL/1s35jMDxNI/jLSvFufagt1OruBOd8/IzoV4TWuEzRnKu/Xez6mXhBql14Y7t1nosty0bfCSgU/U3j8PlWa2XNIvUesxxLb+a/7ZvT14nlm2QlAub7TlEGLdzuY22WrpHtOKEKixEOcMJGaEIGM3g4s8MbIwUkR2rdvnty01ylEb1vxZt7701r+N0bDFQLYxoMob39/aWc/6Y+t3ottj6uqn/fQNz9jvB33w0N3Z9DcGPq0rH88jmAAAIABJREFUsK7+VtkQRHZ2OjIeUgYn8Qhi3mXe3d91CRMe0hGZGTfLIuVlIEPqKmgYS4n0f2mD1hLdy237ncC6/rYZJufuHe0P1FVg9jNCVgt7oJyT7qbNmrqraPdTBuYaw69lGvGxO6gHKyXur8cj1xPtZdOcyVQmFHNzTd+T6Js8DTrQniV6Tf9Lr7QnJiYmJiYmJlpMAn1iYmJiYmLiu4WRJ5V87TWConnckGL6fyW3yCkNRSFExZqzvuU53yVGhBhrfKpFzYC6VVY307kq/ET/7tM6DVPsIVeF6EUk4xdGX56nuji/pF4m/j1gdIpmdx+D+5fG+WhG6gnYWpj37Do1YYO6u/VuTVPKICQgCFnEMYApljNmizUYxC1y2QRAUJfuoveOenY4BdpawbInqrhudGHoJiFPFLJToncRaRnJlXW/eget7OIt9tFux4O5oS/npLuym4t7AoFjKGmHIG7eScuR1XqdMyNxRlgDMgEhJqScxKodYl23MsABQE5azG3v689Ar/Xgv9VjNnzpgXpuuI/Zn7csz3VzA5ZCyDhH00P0BOp+qM83k1g5CPdYAAT8gIjXSLgDQLjVHNj56AeM529CrWMCcCDvWabiBnamfGtdfwvZdGAEfF/iA8Zn0bf4WjPudXhucTYiUD/S86ezn/LT6r26FFciFFnFVpWfOVdRTIUVrHkIRMhG9KnIEwL82rxVS+izITtC9fw7OyGsrXpRe0EsF+XzgjCjl/qNApyTF/XFBfxebWWbp8B4WI+F+F5CBBCxpu2IdrNWTXcYOzffTAY1IXSuAbU91UtUal9Qwr07LuVrYYdA33dQj7om8KX0wwWubCc6xrQ6n5iYmJiYmPiWMQn0iYmJiYmJia+GR7s8hSlo3FnI9rFHnnOrKqMB2WRn2YLqOcCF+CFHfpFYMQY9S9OUqV3pINbuXCyrTBnolYK7UDfNXsHqLdsYGZzbSK6lPq6tf4m/pfx2LdE9EYgLyjtIa+/+11KzXatI/sfgco39Rbg+mvZ05jqaPInenwnbPr86MyOu5pHl3yiGi8ypxLZZiPvwIoNClVMAkMXadWUAgcGBkTkgE2MJBNbwMOvGYOfNKhkfJF0mlHPDiUKTPpgLSd5UQfHL2im7VRZnF5oolDPB971VnGgd6i5I3+RqnU6WV0DlcCiyMoCAGMGs7mTVai9QQKSAJcRi4Qjd7JQ4IzIDgZDAoBSw5tDlV8tpsl2LYG7XSzW5rHPDHlRvJNWkv+3hAYSM1pW7vX0A8PrX/+DDH3/j9pf/6uJ28Td3LgN1eboW17h/P8I2A7zHa7wG4Qcw3iMS4YC6gSCjWrIm9+6iuQwWjk0yyAxhJ8xbP/FnHt9IadE67u5cv0Ms4iW9bp4t8tC1XWM1afdPg5wF+/PgsnhG/eOqdcMgvvME5DYGs/AnALcMPHQZ41w3mTCAGLmEb2PrZX2VY6fST6VHyRaUQOKOHQBCqK/7s7tbQtToXFk3pjU1ddnLu+34cOUhIHLbbzZzmyMlfbyWnz1L942M6bIRNvlra1irpMy8/fNQTM2794rnJQzR+Cgx7nsQthabSrwWlN0Z50R1hVpjZhzzqvkMCBCvJJkz1nRsvENp5E2avu18kNoP+i1wbt2ugiIGavpM5hoWAF6xeN6AeXrpu2/ZGdTOm5vuTYN758B9nxlEwOzqYTB305ZE91bqbPM31zyOyPKRJbrd99cTExMTExMTE18ak0CfmJiYmJiY+P7gNYz6N9QbeUaZ0Kq6yM7HJXef1GoFzgK9J7uoxMdZXEpmlk/RrJn1OVBcrns3xIV88mf8+nLZpoCWcOFtsN1qOYdiHX8luCEpvILYPrcKrl6B6q1pLYD3jEvd9beFttxfMtWpOtyiFwP1/j6V1yvpL6nXUyTA+Xe7Fzdu20+/beS5IXMGJQaI5YzuzIgcZNDEgIUYHPRM86J3p0LSE8gO8y3nhBvhDnNNrq6By0YiG/WnMttUuFILXm7uBz6DVk4ShY3c8f3AZGVYIpZlQYyLfoqregoBIbpyQwkLJsQMAOIGPsSIAEYgIDAjMCPmDA56njxneTHnTdfYuqAdExtEQcN5Io1aAh7VanuBnHH+8Y+/EfEf3L35C6zPF/2sdPEWEaet1BdN//iIuUFeve5oEsv3EXd48fN/8PCWwHgF4L7IPCPIgVoni3vX2jwSyTwMk5fiZru3OSXXGAdU2UEEPOysIzbTdLnxPBPVtt7GROW3ik3/x2bptVnDeNyyuH8fLoeGaZwKeT3EvTchhCieLJQxNrmTs4yorAuTcs61I3JTyoghInF+3MZQHn49jQGX+TS0svpctFUuVwq/h1/JjnAqjc28bmehZBbCtj8bxTLl19vuUdKVwU1YkFZr47HM6vuvL0v7bM9/gF+3k/5jcLb3uQn5MjPutX+FDCCINyu+RgScq2ycHoe70eqE1BwRwFbVtsjQm0wlz0TyHtuugGBHWPnfQdu0JlE+MTExMTEx8a1hEugTExMTExMTXx2PsYRGIagd+dCFIrQElRFhpmBflCgxFCe/LkxD+JqSl0RtxikhMSNzQkpyfq6R6dlct1czplreNkdKxDurGg3lv3sU0uUJitPHKHlNvTqixE5ZnlPz3ILpF+7aaKAE3JBvX4lgL33iSyr42NLdL3QZD3pBo/uPQFEcP5o8fh7UMVBP1q6kaWd5Xty8tpnYNFntfk1eN9SVZ8+fWqDOwrze7ilhN8KU6OWyOUdIUKYkLogJsnknMIAIBD0rWi2yF9vAw9tzRQMRopLtkQIyie0zQGoMF4p72cbgvPH13pSkEAzEzmq+PBm+dLK6vOwoYthZx1s9+VkgECEuCw7LASHGQqCHEMq5w5KLallnm3YIVFzhRwpgEmt8JgIHOUM+ZgLU2j17U9VNTdSeWo27rePZfSquf/3WJPN6kiDzUgTwX7++Rs6MT3/eFXlg5Hpx8W7TjcZyC7GgjgBWMF7os+ze+UE/76xOvqB8IwCfAOS370AAfvg/L/Dpf813AcC4KyT6EdVtu5HnZdOEMjrFPwVL/z0oie6tGVet84PmYCUbL62Ute8H+M0JruvZl8D1aIMrsGcRvEsXnx02Z+RUJ9y4GTXbYGdSedQ9e+JXEZ/EfLVsblIDXhFpGooJ4NTuLDHZHzr5SdSumna3I5TqZ13HPQAADvEABuOYVpEH6sVjTanIZLCRiFS8V5isevXiBe4/foR5qBjxvE2++smnmfG2soTB6q68X1NuIhqCum/5DPHdP7VRUiypy9p1sHBrJo9Bu5yoG/+cNZ3ijYlgg7ycJU7d2rBZB5T3gY8PdniDZPDlzS2W5YB3H943VtDk3vdlK8eglHJ3aw4N+yMD7wh17oZseAv2SyOIN5N7W+RpphkAsnq2UrlmaTVk/aju9qZmlG7blGv3qrPEL8Q2dwFL+Xx+tO5sfQLoosTCUBtnX4TOEl3y/gXX3BMTExMTExMTHSaBPjExMTExMfFV8XhLaKiGzJ0vrsoZx3c3BA6hKmKIhDyP1f9kcfPL3bte42eKu8yMlBNyzsjIyJmR9dpbn9fIOwWQaKmKtXpVJ/dK0b1KOPXwNB7rOt+r1KzWvIIXzT35r6lHWDv0buBbfMuqMiP1gC+dz7Zv+PSbfLB2Nd52ucfgCd3s2WH2pXt5qv260yJfUA+dbneLZ27sPcv0XlFcNgR4OQcGq6VXCgnIEZkYIWcwhAIPISDnhDWt4BzEXbluFiKE4r7cSPS4xErQkOUnwtzK+vwUUoMZTKrSN1e4oM0mmMeQ5+dgruiNpOfi1UPI78OyIC5idR4dcc4wF7sJ5I7AMK8cDIhM179qIV5JIjv2Q663Foi7Vo2Edk6wOI2wIaEexFKckEl4ByPQMwPHt8Dtbz/j3R9/4gFyfvcD2jhrGoxPQCGKX0EIeftjAK8ABLxCxr2e+/34jm7k+6OPZiHCh//9ExE/gmBnSkteCVVxYcS/zUFZ3yW3ecZTQseuzx0AHIkQmMGk9UOET4N8G3l+CtsZ+1uewb4e+rVA/wzAcP4i1PXd+Q12l4vwvV5KQVg/244RguScOZcNRZltg2S/zpSIX9zcOKL2Moymqgunr2fHaD16OuzO/TObB54Dlss+zvPbCCTE4SAS8hAjKC74tB6b3wGjeHpZ7vuA3c4QEj3wTyAw3oY/QZ2E6t/xaWbdfEAsHjaYqGwgagJfgTHn3pHoRuL78vVjblM5XH4fkf1O0htMDOQAivtk+aX3JyYmJiYmJia+BiaBPjExMTExMfH18QhtWiFzvaUIk1O+iobHu14vLtkh5zZGCg2BbvkgJcCHGWQjYTLWdUXKWSxLuCNe3NvtecFyJro/29Wowb4iHslDfBFs7NCpXlO93BKF9rwzaz5FqG/RKh+/LLpyf5nkWkWly0Wpb/+OIyGu84d/mcL8XFafEz0l3o4UR10Vi6luDG3Uw6fTGpaBXD++VmHtB8PmmaddPCnr+5iemepNi1EtcUOGuhXPyJlAlIGMYkFHRMhkLt3l5UgubSKEGLAs9rOQAFI3rBxEAa4Js/2vMjCYVbuRW/DK81IqV+LL+lbpz8WCTS20WcksJbCD5tUsy9VPvVjUL4u6bK/1mplBKSMxwI48tw0ArPXKKYFTFpIsZ/UQsmk8nXuM1XOlbIgVa8Uugs4SvZGfZJsDJD+3AG5//gHHP+9w89tPuPvjTxx1Q8CDxm7pqP+AJqkE4AaMbJsrwAiQ+Ucs0e/B2Lp47+ngs63Hup3gwjFirtjt7HHzAFPPK79H1tFLAKKWbNGc3P7yI0DAwx/viqv2W8j59WaVmri6gb+BbLRgMG6UnGpKS81VyZeNjCPGJLBsGsDgyWnYYQSZGESDPmZ5sS7S37f0+xZS4cCW2b7rlev2vZ40O4kT4YZ11H1a38uQdu3f8+/basra0eqtWsS2FGopVTu0Nnnpi2HhPx1lVL24udW+KCkzLyAC4hKRc0ZaV3AGjutR5I4KwSIToW1zZiHn57hm3VhngGZuss+GTEUrY9p4xqCuvvZyFvr+dSbeEo7Hl9g5M93ClM1ENrWcGFZeRvX1dyqTxChHPry7vwfAuD3cgJnx4yuRK+/u75BTql5YunRD6FokmwyR0PdloL0FuXXIrz//jDdv/yjlM+ntnDLpZ+1HP//4E96++0vmcUAt00tSzXuj+rFc0mbeAVwymzYjf5+268z+q1nj+wjZrze4rsm2Ee5k/uIJaAdf54fCxMTExMTExD8Ik0CfmJiYmJj4TOj1lp/j+t8OI3RafVxVyhT1VkAhz4NzQyiueqOLCY2FpSl7zArR6UWxqnVnyrmQL5ztDGH7QyFCoM8lPyTuDXn/rOZvEeT+MPj0YcCt4rOE7e7vvr+Hytd1bz3X6Oq1dduUvv7Y8zUwzqcPw5sau/y63efwZXsrDz7zIESjcC7/25PeQthIgxPa4F2q6unYd9++A3VbuyHBoLQiSQkzCwlH6io2IGBNK3JmhEAgCsiHRdozULVADwExiJtzc1esrD9SUkU9TA7CKcAZ7OqWbCMTwblD7+vtEZpw7YqVRHdnqxMhxghyn6TnuhOMyCLknGsZ1Brf5oOaMylfhsj2lBM46xEd2RHpg7xTpQ2eDiIA0gaWuwOA9e09iH4EABwpILhRXVOmUg6CEMZ2QImNiVuIdfsKLpbo0LBtHripHbtmd12foT5vmJjTMmbV6wWVeCH8oC6OGRE/AniHUJzMW00zgHsc39zh8MvrkosjAUd1zc5atgeX3oNLv27EMRnZ5hQQwvzgvu+hjgTa3LdcPxWn5p2OR7s4Pl/qDdF2Ve6ux6h31PTb3LVhLXee4Rvl9tR8vhkxzfWBGQ9ka8tQWjEjg1c2JhIhROS0wjbtmNttQGRUpADbXOlz/xzYqzv//FKJtN8O17x5Ter2XsZwNadLdNrriIPon8atSoQP6xGZM25vX4CIcRMXcFzwcHzYvsf92qgfh9u5TzaNMj79+QYmLAmhKWP1k9JK3T//fites+y3C8RDSV3xPL4eSCfu55jD+r0irDcpnNjIOOh0m2a/VsBNTExMTExMTDwjJoE+MTExMTHxGeCJRb7gGqikgz33ar/R+9+CLuFqBd2JF8ZKp3GoRoVKZnUHtTpXdacqVo3AtnNt5VxfUXSGSNWKRJPOhNadL2e9zs5iBEgpYU1JCXM05JJckxIZRsAHl+uWrG88T5/kHJ6J2LtSoUvNd2sDds/EfW4hfdi/w/Au2+unV1qP8zbKQz8exqPl1LXzOLBN/eQ1ga4z6P4MqKVpCYGmNYq/W31in43EGV33n1TGWNkUMugwl8uinszY78FtbtRtLlCOUCCYZaInyD3ByX2tFCFL3g9/yVpLytTaNaKtzZgnvk+VnwAZGwBAQcZGY2pWXZVK21ob+ny5dGyeICr5zGD1miHW50QEpowMsUgPWS3QlTgP5oJcyegQIw68IIaAnBetH0LKgHDPJq8kDfGyweCckDPAOQFsY7/WXNiMNUdacisDMGqScp+K5XkgzX8IiJr3EAKWGMv3QKRu2kX2VPftcOfRGtlsFSr3E7hsjlozFyv0rOUWa3RGzxR4ktRb3PXuzHsDwB6MVsy/hPXw1zjiDndvfO20xK3191cERAYWfecewG///RP+/t+/cO/CWTK3qG7KI1Fjhe7jbXM5+F58//pn4wlNrM/r9avffsan3x8Autf5/CUCRSx4jVRPZ2/iz2Dcv7mDEdgPrlBGfh9g1s4kBLpuSOEy79b52Nps8YsxVPK8l/3l9VTnPY/SJ4Jdt/H6qjk1s9vKYRO/E6dVgrjnvH2nDWVylctGCzDKqQ08yugwnvpyHWlW/poz7itQRbI88zGQCyvXQddVKNb+lgyBSnvpnLWdZjQqHSdlg0jQaylr0P51VNn48HCUOgyyXeXF4RYUgWM6giLh06cH2RRJjJQSbuIiOc1yJjpz1vzX2ffUZgo7yz3v9aOuQFbTzXrYYTvLjtP2T0f9aLTqugw76WXnR4ZsZq/IavHdWEm7dXLxcOKn0T30Re+GoMwJqc6HILy7vytyO4aAm0W20TysdRvNCwZe//wr0psj3tDfNUPk5nArT64rlAzCnRXd9YgfwHjHYqdOOjdqdy/91X5bZAJeMfBBf/iYhTzrvNYIKkbjEQa+Xkdw64IavG5aOyWnxrCW1t9QJXk9ICH01v1+IeAaXOcWW492InozQjbX0x38xMTExMTExBMwCfSJiYmJiYlnglm9lWuniLzkGhirqAitMoC6598zvJ6nUXh0+nnzzutDC/HDSF7Va/9R0bUW8jxGQqRFCRYl1ENAJAlYzrtkIOUVCUBOGTklJE5KpJuOVgialCthULMcAGLV9yi9QdVipCiUUi7Z3fMWP7w+/2D4eNRntv1tqyDzLvBNUW90zV6aVf9lKsJO8Tto90tBmxHQl+L051aJvS3x9topE9GfePwlweWPN/cV2seKbKFCD7lw1Ya4MjPt8+21dtTzGlN5o6ukzdneKCrhrhjeglzDkSiWM6mq3Y2vNnyuMZp3B2JEhGLNVshqUpKG+v5QMoKyK+YJLS4yQwklMktoS9/IIWsrPWZCBZed5+2z1RALECvbwAxGQkiETBlmXR8piBXkYmRxRuKMNWdgXUtdhEC4OdyUeqEQRFkeFoBCQwbnlHBcVxyPRxw/PeB4PCIzY+XUuDoPkbCoVXghrdm8eGwtduu4NPe9Ih8jBYQoZ7THKOeZl/yREOsxRhyWBUtcsCwLQoxI6oa9tqNrSa1bApQcZ3DOWFmIsJQTUkpyTAfrc70Wy3QuVu0l/7YpgQic1kuHyajHaNlDsTBMYMSfCQ9/5kJut1NGJSmkjwcI5fgR94ggEN68eYdXMeIGwH0nw7yVNrM/911aptYeUMfCzvWFQ2VFdeGeALz/409QEKvdQK+d1L3Hom2dWcZ/0v70wMADGAvckSmkhLcb1wwUl/Xi+YXA5pWAZZMcQsCi3heiW088WF1xkZidDDTpStuynyKq3DNZgnhLVCOJWckslCNPGCZDqnz2Y6fG312PnpOb3ajOLvszIjU3S8ufXMC47IziJ4iM4eYG2ty4jVyWUQtt92yhWAOaNBmUxs9voWz+k+FD0jZkm+VIdhGZT3EQUspiee4LBRYvH5mxpoQqrCUOcmW5FqMaJcn5poX9O3trOT+6R8/HqW1TOC3jtnH1PbJ/Uub8srHU91c3ZIJb3FwpaW3F0KaI9sxtlS83hxssy4L7jx8AAEuIspGKGR8JeM2MFX/jt//8BAD4+NdbJAbuqa0Bv96Nrpar5CR8ICrW5X7FzCzFZcuWxvee5FOcrJjs1fnHuXcv8orUwzzvr1+r+GlDPIV8LiM5M9KapGy6xhG5anJIt7NYGey5rU+5tlfXLep3N+T8rEQEkK5FHoN+E9zExMTExMTEvw+TQJ+YmJiYmHgGUPkbKxhH13u/5Wnn+7lnXxV7mdnROzTKjU4JRl7po9ejeisWGsEp+IseSWINqqgJgRApIkaxYIwk7wVQ0w6NUk2tzjOc9aHlmam1PEd5Ra2OTKFeHTLmXn/NW0ujZwNvm6RXqI76Fo2ekCf4MCS/qbRkm4q/bsO2Y+VcX95TBLchTqv+65u9Hc35d77uaPNEC3cq80ptkWsY1rBmuQSYktVdo732amUfC5Vef2VnZTSWTzWnNXYe3Ler3ISTDQHeAl14FPMUwfV+EQL1uljcqqWWWaB7S3Qvk+TL+TJf2iseq7gVEjsgUCilIBMc3NalUWvm9YKYgJDF7avVj72vZDbpJiICJB11fx70zHQKC0KoKv8MUYIfjg94AIFSBqeMRIxMWSzhVfgIYVl7VN3mQEXTXSQDuZGpZrNEQmPa+ezLIm7mQ0OgS76XELAsBw23IMYoGw9CtRbv3dxWu9AATgkJQp6vWf7M6pyNPDdX7ozS56yNngNWTwHmVl3i/wTgP7/+iE9//I3Xv/yEuzdvC+Hdj1a7cw+RB7cgvFSpQahjKoDw82//wYff/0YEEPASf+FevKYA6HsWue/onvXX1/T1pHGb9XvZ5IKMQMDNLxFEr5HfZDDe48WvAe/+kE0EDLMMZ6xKrnhPDgcd2qtZlQO4YSHEoX2nkYQELIEQSUiuBOAjY2PpWL5Vjqqu/xz/1mBzWHUbqeW6blQx3ogAs9qEWaZSiY442BONq+aI3HW7jc3CO0vtQh5zy7sHapvZymePNbO5D4A6vqyeSxndSkAS7VcedYVQRhhLrq3egn9/s9ah/Q167O/W+Y9JPei4lYxd1zgZnz49uFWOrAE9ufbpuJaEqtVuzQXzyIbX57HtODY95cakvtqzU/e+n9GvXVNds87pPVhcin6FUe6XDU5uMxzXdzbjycaebZILvt95bPzHuCvfPlsQEY7rEcf1WMIcDnI4xO3NC6Sc8fvbN/j1Pz/h+NfbUq6XABYG3rmIzcuVhAkItvmqhNGjSVz+TOa+YsL7XEtAgO3RbTwtMAE/ZMZdqOuc0RaHUX1cjm3POtcHik8Klv+YGHZ8VdmUohsH/fEvwxQ6ceQvpM9spLS+Nx53ExMTExMTExOXYhLoExMTExMTz4T58/x69HVWlESsqpqiSLbwqsChqlQrSmf9bi57A4AQIiKpVVswi04JF0ylwlXVZNZoOSclSzLkDMtq6+rs0Go5Cp9VldVWokJwWALfIPZUp/29XjHdvzf6fmm4U3k7dX0NJB+92vlzpPTcONVvvGq1Zzt6xfE+CTZWrFaa/VKMcurj2CsJD74zlENCS6hbzjYW7J7gMRaKlCiiGqRa3o/K1tUEPa0nhECgEDf3q2cHFMtlyzaMaCAWMjsGmEW9WJdxkSdePsqF69/OUo8tDXHJIS7QQyhuz2PQs8QDgUittSjCrLUBEkvMwMhmFR4jYgzgVIn4zFxcpq9ZpKW5sC9HY3DfZ60xuLRbCIRAEWHx1ueSV4rOAp1Eznsr+aSbnUqzOwW6kQsAdFOUWJ/nJHI/5YRcjuYogr35/JwWaRlybnmimv/0R8KCV/j05i/8+NvPePf7WxwdidZ6xRBSFUBDtN/oXaP4/vz9byyaFuMePwC4ezSx8nwgQF3/3wH8Az78eY8DgOXnHxAXwn/+G/jrf94V8txLDh3uAISQiUSIELfJAHAE4xbAR9iZ1XLMQSAuPG4CYQFrvaB6UPCpOFZ9+/wpJXcoRdvOS+0M1rNK1JFQVNZRG9qTK2m1cfPss/WE4nlZPpphK7W4Re8Ke2xNfsF8LsJUY/SyxxOs164HqFvPUSHNq4vqU+/vY69Ee7h2jq7p9L6Bvi3sbkjZhtTPfl65vHQvGfhwrhK1fXPOiFG2lf7x7i1A8j4gY+nlT/+Fw19cXLv7aKt0pmpRbjKrPKsS/QP5dtr3Y8BQq3SgIePLuqJb633N1e3e740GHcHu3+3jKq8Mnn/L/XtiYmJiYmLi+8Ek0CcmJiYmJp4L7e/8i/AtUXSPgxEj7V3aBrnoun2vKqkbM6bCnNuHuc4V8joShHRCwFKsKeU83qgWluUdJauyI3ZSzkjZyBR134uOsCvcSlarPVK9elXI8oZoaRVYzF9bjTVOfaOg4lbhta/Ob+Pwyu+L0rk4r3vWJNcoqL+vkff43F4plK7UPu7GfCZJdwIqvGq3Ic6LlXklThprNOMviu58S3z7YjRZuqhKuOn019ow1fHtyVuXBUeaE7VhqiWteM8IIVRi3VmQG+vl8+XHm8m+6m3DSOeAGAOiuTw3Mp3UctsswlhsyL3b++r+vMZHQT152MalzhVuaVcT3eoZgazsFn8Q0zojxYWgJ1AUgj+GAIpRytSUx+S5yHLKcm55I7ssTMe1ZJZzzlPOWFPGmhIyJzBYDf3Z9dftgDBX9MVNvyunlVUIjZbIqB6h2wwRCJnEoa1Fc4+P+Om3H5F/Jxx/P+IV/oOP+BsMIckrNlG7AAAgAElEQVRHHjlauc04uqemADjq3wKhZgpNM5QZjyAYr7g2jy2yUUb+T3++x41ueEh/vscR1h5iWV5j4PK+5X0lwgrZOGCk0g2AB5KazSCNm/EJ4rp9hWy2OcLIUONvrBZRhU5Hojdl6duWa9uyl8nNRpL62drNjmbcth/aVRjGVvtB7YN7op3aB3peANsZ7tx+lrcsQluTGSGo7vJ7N0ItHSYbb05ONRavC8SjADso1WwbEoocsre38nmbRr3nN+OQo0RrdmjzzvlcuiVut66u8mS7Cutl/6l0+nxs+0G9OpnXEw/9o6eSl94ld/ugvV+OQ+pSprKBDKiuFRiv82u8/OUWH978DsJr3NEd7i/I8Kfjg8iFh08gAC9vbnBMK3548QMSJ9D791jB4L/+AgP4TXf9rSQbl95r16MQXKxu3tA5McMNJ/Yh9I2sFuYEvGbCXeSu3uXKPETI61upce3Gn2c5R5yhA7kIV7dGEFlBKjuLW32zUt9kSKNs1hVtUhMTExMTExMTz4FJoE9MTExMTEw8CRslxRnC/KQKhru/ct8ULV1cRjYRQEEs1yJCIZ0WKIFOhEik7oydIoaM4xH3vHbGbcqMpG7bM1fiXHQ/jJwZnKAush1NMVBIjZQ4+Ru1RO+x31atnf0lb7RvTnxP8L21b71revKYftyGqS5dvw08d59tzhmnes8TgEC1Xg+qcGdmOWe8HH7KPc/fEGUUvDt2KkS5WHQLeX7QM8ODuooPLrbkzjT31uOlfdie2waASvwQAC5nVFTqppLxIpfNbXxxJ6+FiDEIia4bAGIIWIJaxIdQNgRoZJIXIiAl56ocZQNAqEw6rN9lKHnOjDWt8reucmxHIFdeNJ89ehK9tkb9Wkl0R1IZ0Wp1g+rxwUJaWT79vuL21x/l+x/vcAMC4RVegJDwHh82udoSapbU2oWz88jtTPKvMe5WQCzNgZLh4qoclVA6AnggIDDJsShwNa1j6gCUDQNSNi6eB8wSnxl4CAHMjAiGHThwgJ17LqkW/qbktOameLIYVFjbtr4tth5sPgccn/1knFuzlWN3ULmxzVqNYccdD+KUWuk3mVySp+coYxW5/Uj5svgWVkafIw/PXatUqOZTm0FcogQAGS91vryjO9z9+Q6vId/Pvtrf17lmWRbcLAdQAF5wRPhJzkJf3zIYf+GoP1kCgBcM3OI1VtzhjiolnkF69IlPgOqg0rG0t8nkrt/Ngh2/Apyb5wxuBdQ5PAd57rNj472zMGcl2PujMx5D3nuZWzc+PSXXExMTExMTE/9WTAJ9YmJiYmJi4vEoSo7WcqVXHHdG4xdhL2xrcaNElHBPiBTkT8/zjSSWl8X60t5hzbVaH5oFYkorUrJrUTJlOBIpZyQWXZR4Uq4K32Jw6okmqyZfIY58+pZxXkHdP1FirKMa6vfn0Vx5gnDiy2OoVKb6bBRevtRzuLn/3ylL+7EillZKehpRowTyqBdUkrISVdT94cTnqGiPV92iyBhz7WvW2UaeUzl3nAqJDqBad+8k7s97NgRln0O5Flfr5qI9xoio54QfDguWKOeGmzt3yTAA3VAkstDEmtxb17X85ZSkjbIc0mokcSXwS85akhzqol03B/g/e49IbVOdbBdLd9sCVQkU20yQNLNFFGt9BhA4y1zB6v6ec8KaM9accEwJx5xwTCuOaUVGpSGylu+cvG5J9NpupU6KJXoo4aUd3YaRYmUnadsP9QTgEz7g+EdpfY3lAwKAAwgLxP14BiOBG5L8/EzDYjnprOi/NNlwcGkGtQhf8ArhZ5nfH97cIQH44dfXWP+4w6okunjmloyG0t7AC0D6MQBmEuv1pq5l/iYSl+0MwgMJ4d46xlf37m6ur+R5tVT381Kpx8LblM6gpews0c9UdJ3vxi05loPb0MPUjNgustWnoz0hj15sc9S85iYJ2feorqcZxaK05IXcWChx9fS6RXtuDJ5Gn/1sZS6HuLcFLflROXbLBCYuRyNIew52SVyI4qXE6qo8aD4+G87PbW2/q5skpNx7/ctgm7Hq8QCX9eNT5S41fsH6mVM7H3wIKOQsQY+sGETzwhHWH/cqiBl39+8BAD9AvFfcxtfgzMjE+FPng1eaxJGAe7oDAfiRCe/IpLyUXKSNejMIXOYfwMaIqx99EFl6bM7iQv4+aJzBAtfMv2TgHvrjxWQaxnU9muvIMvIE9E63PInepqgCSV/y8+opjDxIUHfnG//ZNTExMTExMfGNYhLoExMTExMTE09Dx5a31lrtdauWvQK9i1T9DGphSQSEAATSM89jVKtzs1R0Ct6Gn2NwhrjvVZftKSUh1SHKd1GeixaMQQBnVbMaUdSqqnvFdVFGOcvN7x09Gdm36IioHIec+B5xaS/m7ju7q/4ZcGpTCRcSprxwQUfac837JWAEd2YGpVzIcnbkKpnVt55J7kl079Y9Z5E47HcbSAytBTugG4bkOhpxHmI5R3yJEYuS6EtcEJelyufMyDmBMyPlhOPKSCmX51nl4/F4xPF4xLquIi/Vewd5tgIQcl49f3gCPao1vLlp9wQ6BSFCc8pC0BO37acyu7fw1Roy2zqQugMPJC7RQ3DnyIPBSWT+mhLWtIrsZ3EBn8Ewv9W2EUrunSfweivztk/4Pl5o/g1BAtR5hCHnlFsZ0yDeiMqZLCBEMA76bkalBXvL85P4gmNmgViMHzRZsxb/hHvgz1q+25+FWI9EWAtxTbVZdOwcAdwwi9cZAB+VKCMlK2tdK3HL1LnCFwtTYk+WS3Dvkp/hXAzvVFjfT8t9PJ8l+oXicAhbFzFt7j65C1xUukHm90fQafRrjlEcp+M+X+KgJPrzQMe/zm1PacdrUzVcsumgX7fzoBafJ9/Xt/y50My2AUJr19bxyLt5NtL85YVZudPWe5/f4Sf6EX/jrmyuvR+Quu/cPYLItux6L3mX5ia7OjHjj2sg6PntOo5HtfiBAMo2h9WnAdANip9/w8YIJ0n08nU8956zSm+esm6Imj9AJiYmJiYmJh6BSaBPTExMTEx87/iWOFnuPp8CpxwhvTRLPrNOCGZtrpaa1fLczjuvVjD+QMkMCBHOjMSVAMopI3NCSmp9rgorUehzOZvQtJ1F5WP6dSPJXT3Y/Wo+2xJgnwOjWJ+fyO5J870YP0fK/w4t2LdWympJptd74Qbv2JNeRFR17pZS96rekTvkBtTl6pnl4rk+J8lvw5zbM0Mq3Ko3Df2uCvPcWz8zt67LQcWqPagle6Aoso+iuGePESEIcR7jATEuCHFRN/JmZc3IaUVakxxjsSqBnnMj28wKXTYaSQuRbVoqGxaEsL65uVHX8Eaii2t2e95boMt9KXs6HrGqvFRKG1XwOq8g2jrc9RlriUTiAp44l3DMjJzkuI51XbEmKbNtnDIxbWGL1xCc61aVoDeaxluiW920Z6JrU7qylGeq7y8GsoBamrcwkjzqnBUhfxmVoAGAG7zCA+4HRPpoo8nj6TxTMIzkhL+3unsvYPw3IeFONsChbhpIAI5vGcx3Qnb79YGS4rbxhJkRiJr4q1wg3JDEe9S7RyMxyY3yTt4Ui/G676GgeNbwRD7cZgkdy1Q7gyPIno4+lp7w7O/79zZtM+jgJT774o9w7hvZJRq4vU+WoMktZ5HvI9nmk7pw7bM92rXP2rXL0xJOj6L42M8tm4xKii9ZCU27zeNyBTdnEICcawi/GeA5l9Vj9Gu5/qmNIG4+98J3I84NjHF720emsVW7zSvjk87PQ0U/mHN7xEAYhSa8ZMYH2pLfZ9Nhxp/8t0ZDSLrxrXqd6cKDBj2ei7csEzZE9Vx0i8jX6EsmfCTGq/waDMJ7vHPvsx2GDu+zx57/yD/iHd6VPDefDsUjzhUyq123nAjoz0S3udzvFiCAQts3/AYksjx3wmyY06/1e/lbW8xPTExMTExMXIVJoE9MTExMTEw8K57NOAfVusKUN0Y0mVWine8bgXJObkOqd6o/sSY0l7wQwiQLSSRn4WYhz/UcXSajQUR5npURrzo4cwdJ6tIdQwt802N5teGX1KeMKGwaPD9HgV+S5z7uS9+b+LbBeyxFH65/p3vW0+RjlXxHnhdKEri4N33mTud1zJXQDl0YqgSsKaCNMB/lT8PZVwYXC2+gKopNkR2IYf7Oq8v3askeo1p8xyjW5mZ9HqNuMFI35UktsY9HrMcVSc8C7y3QTSFuG46gsu8QFyAqmaXk+LIsuL29Ld5AqHgKsSM3qgt3avIv5XzIjBwzOGcQk5D8XGW4/rMJQvLX9BPXUFw5E9sEkHPGmjJSls0AKYv1ubF8psRnb7GnuxrszqgJR/JvE8b6xW4AJZkcceKHX4S5Gm+RtBZWHXgR8mPfrNEZH/ASPyLhDivqOeF7ebiWbbBz1JsoFD1Ryy5fQpK9AtGHMpaMNPdEu5yPPiZ3fLxEhE/987IRgnE01+9NHhvKqtmPU/NuHUnaxh9TLE9Pt2kb1/eDU/15YxyqZCV1A8SuSxvZkHqmHNqoHT+9jGDfe757Pewjghd8wv33Bfj8pLmhHwHXvfk58/dc8ZMKZbefZbDhrdb4hyd2SgZgG91OyXn/RJy32+whcsqeb7LjJwQCPupgugt3eM2vy/3NHFWKyMXq/B29q5HZ0QqfySKd0MmKBnXureOploCZN61VZQxhUNqa6MTExMTExMTEEzEJ9ImJiYmJiX8IvqSewCt2TFl0afjttd51cRQ+CpWUMQKmkumMGAIWiNvfqKSSuW31J82yWlgyZ3BiJWOEPM85ISdWl8F6T9/MXlHFABdHwZAUGACbxYS3uGBja4pSqicQvgTOKoAveKe/T12oy848/7fYjP/D0A3Nvg1Ho74nzSVcVYduCXRHT6ki2FyVc30AwCyvbTA6UnOUaaPbz7j5fAyqoRYpea1nd9vooDawtxhvrLjUZXjIWa3vAihzkXM5s7P09vIQaj0uZ3rbViE7wqJYspM7XzyqxXfUA8aJwLphSMjyFenhiOPDA1JKei8j74h2gnj8QBDL81DcsgdQCDgsC17cvkSMscpsVPndn+9eSVBWbyKE1d7jAFAuFtW2uQBgcL+zQ0m6XDYu1KeZUTyM5CwbE9acROZzrgXjSpQDnewu+dySI0VGkpEhFkH1GjCyRO/HgWSBigW6v2/W5wegs7CueTXbPILwmQ8uTMYdAJRzwrn80dYy/YKhs0CI+hEZyaiW3pbf6MK70QzGh7Lxg5jxfpCWz59t/ghaf5Z+6PJs9X4A8KCbMDJnGXuZ4Wkqnx+ZwlXu6JiztUThm6h18+5lDQ/aXLtVY4n+LcC3xUVwR4V3HqEFrkFKvQFylrr2adL6k5OfdUx1uxrYx+c+3WEeJe8lsXLdW6yO16GnytwT8n3YjWzUG/cWcjQZAqXdy+tONsrjssLcpOvXYaNq30MvR0bhz61Rbd7y+ZJ8jGPqV4bbmbqzwO7XGfql9T/iqdWx74Jhs7DLq8n26jJC/h9apPsc9eU6HVq4XScTsG2HNsb2qljel/5SjyfxYH3pVWZkvNPzzgUvmPGB2zHDOnAbLx6amx/cu7kfh1ei789Wtk1vYa2moTzU43syNzIF0E0AXjb4dRmjbvosMufxh2Y8dh35bUj4iYmJiYmJiadiEugTExMTExMTjwejWGG5W7sKpo0Cs1Ps9NqGQpzDXPt6Ih16xq9aW1JVqBUljSnMcxbCPDninOVeWhmcVnGf6czFs1ER3g1ryZgqhZgAzp2i9J+vMmmU1u4eBvcnef7vwcjivP9sZcWe5fkOI+MstM/hcxDnm/iV8Ns7uxxAOd8ccIpktWxmFm8XZg3m3zej2aQEr988RCAh3QOBWF1WhyCK4uDzFNQi3ZHoeh45WKzLOSU8HI94eHgQt+kPR3Fpnlasq57hPiS/xW17DNW6PUYhz2OMOCwLbg63ki/XHm27uHowkoD1P1YCgQIQMggBgaUOM9SLSHZnmpf8Scw5Z9SoJP6UxW27uW/PmZG4ushnbQMJ3yr+N22PSoJ78EhJb405iGdLwls/shoaw5PJDPejnqgbY/XTv2PhA+yMdcbSE1qDeEZEXICQ9KfOWDdr91X/Fve+nfHuidBb5saK3KMZY1RdJB/c+34cHSGc7wLpz4EDcsoAiYcDBumxLt4dOKs8I21T1yas49FI4LIRwhFFO9anVBPwd3dK+g/GZy/ytqL7dcuIUN/G4fG4tV1PCD9l30Qlra9/r49jdHX67tMxyodtNtqXPpfHuf+sXW00cqxpoHPbCJ4Xe30vqDyxNZPvu81mELf3oDk2wH16uerroBw1YHMWAe+bASJh42eySPc4OSaYkYN4ohG5irKGEa5c1oX+aBTA//Kw33D/Qjk7MTExMTEx8SyYBPrExMTExMTE1fBqCbO+PqGFPI2eNLeoOvK8npFrZ5ujuGwPZmEAEoVSIU3kRNucGJmTnPPrzzvPQqaX832LIsayxk6xUxXqjSaU1Y5mZFbBVdlF7ttjqula7BHc9n30/NQ7p1KgnfugqsKqVrflv0eB3P+Pwz9/g8PnwtA+aNAUvZJ8RKT3oTxxVUWJEplmQgQlNYl3e0CvI30OnanPr3nEaMhzd3Z5CNQkGtUi20jzXAjjulGAc4adexrMOrwkXh27kpLZAXbWud5vLC/Jke2aFbs22ZMzElDOPF+PRyHP1xUpp6LNDoFEvnUEOoBS5hADKBIoEhAIy7IU8t7cpde26En09ozxzHIqLCupbWWjEMt3c+WeTJ4zI3vPIGaZ7NKW/lPJiAx5L7FZn7M2GQ37uJGjUpfUKPuH3YtRvClUpoOaDSB1Y5YSARspSvXxKI0mrAvDQNY07Ie+EdY37h0ju2vryLiKzAhc0x6Vk7u/hHb+WDAm633aCZVET5D5PJVYGJEItyzEPFQOWBsd9J0boqZvH8mNzzIOCYemv+mmFCLkRPKZMyhLvdVNfa5WtY3sbihtqUE25E3d0DGyRIe+fm6XBG++9Z8W3WVCbi+U9YE+G08VnZslkcmiWg01jcGuj9Jsm7Vlt5oxueI8dWy/jM/X9vPTeVy6yG1rjjdf2nj6jRbFELru2Bim4ntpv77bCz/63m8l6N9vn27TKfPKBemfXmdaPJ3s3KRjp4fXFLkN2HzN/c3yrG6ykojb8UW9OwuRLjs9yeNE/2jGfF1ZyF/fvyStoHPaomWxbNom33aNo8JFO9FHP94YuOWAj0FqxAj3Wk7CS/lJg49aqpcMfHD9oplrrsLgN9KJoA20EZk0cwQnTCQAEW8yyGVg0AkL9/P43JsxJyYmJiYmJr59TAJ9YmJiYmJi4nnglKJ7GJ6PvlGSVYW4J8/NNbARR4HEXXsspwdWpVtxtZ6rtXlOWdz3ZgavYn2+poys73JJHCAEkLp5LXYrjXbQKcQZMMu1vXL1CkIL8Lmo3JGC8pSClQZhRuH6J6N3ytM9pdPjNXATXxG9kh64nDzf3tsOek8on3r/MjxzJ3PEZzUWr+R5MK8YRip7wllllrmOppRLHXDOhUwHhPNjI+S91CD3xayTlRz0+TEyqXclX4lvkWY5A8gJ63HFejziqOR5TrnkJYaIEAiMaj2/sUQP1R08mYyWEMg545iPXfrt97opAWVzAQEgzsVtbQihehoJERtr8ixEuO8ncvxGUJfvKt8zFYHFELI+a5tInFI/1a1wC+9XoFi9wZEeRt51ZGlL7BBGSnxvrdzU1SAfI7T8CRUCzojRAE+U13vAluzO4OIm/hyMAO9dySe0eerjO3TXdt45wVy9V5KKgLq2UCFkG0iICCvV9YIcX0DFy0IoRxlQqWNmRsgBOSUkJORMyCAkMMSLP8O7bu9pQclCR7CjbcOG2Dxhid54kD7FuW0IWR7en+jRr3oG7TB463MvT/qc9LTpOYzm4kvTvSadbxUmHb2F9h62m1Dsau+J57hHxDh1465f3Zxumb2ne21TNm/5qyYZIZWpdKru94qPiQgPKi/L750mU1RI9VesEpCAVxCyvRwtoBXUzykX42QHHDy0Ria3eYH0jHmbsVnWIUxcngFo9zlNeTkxMTExMTHxSEwCfWJiYmJi4nvFkKB9nGLtsUnvWSRcnAcjoMuL1HwvlpQwN+1GSIkSPcLIgtb1arH29OR5TkhHIdEzo7jyZWZwsEw7xRKFhuAqx3OqcYelVby+D9DQICNd3GdWZV5OiJ8Oc46Al3vnVIPPhd7i5nI8xXXqKfzT1XJFubtT0F6F3LzrBETPF422kJRxhao3LePMImSUs7+3bt2V/GruPX/Dm0wqlt7mDSMYyS3pm7KZwWohKfIJxQU5F3Ka2Vy3c4nXxyXkaOtGndzBrWqQ29WF1oDJMWZALbztrPOUElKSDUMic4O6hI8iB52bdU/0AiZnM9K6AiECoWr3Tb56IrNshnJ1VzYcSEbluyq+IxFiCFiWiBhj6RMpZ+SUsOYEyuZmG+Wc6ZQZEW5OoCxEMjOIcukzQqZbGDSbvHrLs+aq9MeOSHdlsDbpbjVxt/XZBBinewF2j/IdIFv4Uh/+BPUW/SgyYvza/HlCfUEl1P155UAlSzJakn51adpGOwCNlxr/1xPolNJgk4CNx1p+djVRZBYB2a5YLR+xJWoG2ycGba4PzoinZjMBnp9QD6j5b+O19HayeXLdo2O4i6RZS5zL7jWM8iBCs0ivR6vbOrHW5yiJ89m6rJ43c2G3qaav303971im9+/ZvVO58mXd73atLNvL16k0Tt3fa87++V4/rgd2tG9u1rkawG8gAtr1i705ytOeRXqJtU7HGsyvWlDmZBoIf9//67bfvV9QbYuV+LVAEa0dviuBeBHxyVuUoWY8dMXz9XNP/ZzE+OW/fsbD27fljPQzDjRqaXq518Q6yP1ood7NzXWTE8pvNio/3jQOJ7hJ6+Oxa/Vr3+vXusNBOzExMTExMfHdYBLoExMTExMT3zm+9u9xr1x+DEaKP2+BV0kWs+4UAj2SKEWEaKmpszEiDHEFnOWcYW+BbiS6nZNr1g1G2AvPZcQcVUtzy5SVOXPR0jF6hdM/E+eUqqP7//xa+edjb3z35HkTznUWP4T6d3oioA/n7/XK19ZS+3P1NHMh3WnOgYZIt/POCV6WVOKas1idZ7e5xzb7QIk+K4eR8mZRbkmai/eWwKeTZa/ni5vVO2RDUSHPEzJnteyVs9JjWEBhAYUgcpLr8ReeTC/XOYMpI6nMzDljPa6FQLc/OSs9Np5F2JdjQDouIWCJC5abQ6n7dU1IYQUyAYmKO3ch0CXNDHN/L2RnUGJB2okaEzo2loEuIyMrOWI3KpH6NWFz5vUvKmnMT5nNr4cR414p4cf96q5H/bz3bBBjLJ89gQ605Ez7HZCT0KvleXUUbUS6p93I3dX1Bp62FnoKnmpdeYpgfdS1E+z++ltbC1y4h2H4zvO1tcX0mNxMPAWPacMqgvbb6yWL+/Q+sdLKOwmfyo95ErFPP2Ux9esldxSH3bQw53ZbDEE4xAMOv/43Prz5XeORFM3F/OfstYUQt9xwQ59bFst92d+nz77y77KvNSdMTExMTExMPB8mgT4xMTExMfEs+PpqwaF79EfB2URs4hxZCwAXswYjBs2U0EEsDQnirhchiMW5WZSVT6jrZAISw9wbVrfFcrIhixki0irWlWtOSJyB4h6YwHb2X3DZMmIIaCwujUQDAxlJiJthZWzvj/Q3z9Fcp3od7Xy3O6F7To1tjL+vz5wFSO/EsrnaFLajOZ/MMPE3QVJ9+dSeu9Ct7Y8f72PL8PGRA/7epl6c0nbrbtXJGaBzaexUjrpRptWeuj7nCDT/CfRW6GMIMX76OAVv5G5W33akRDkP3Tba2KYczZudWd4rUZsi7uVTE2YjgJWcJgolH0akj+KxjT+cGeu6iryMqZDoaV3l/GcvY3WTEgVgWSJCXApxnlIq+Uop6cYAs8clkYuan5wzjg/HhkCPMZa4Yqyk+qKkp2yQ8tMEqbeQDKQEHAEEkVxG3HsSnHQuyipxgs4Fm3nHbZaiEEBZ8l0JQKmPUof966ibIxrX3Zq+Pw+7WiXa9DAggBuBZv1pi8rbnO/XWykMRL1fXLZvBKnltSf0ngjefNnALMJDCFqHknwAwIPyFrKaK+FtfbdYopdNGaQEt2z0ANe5Xa6lj0jfq94MtIM336HxSjOFUqJMWcaV5W8wSfHmf1/D/YzNpc8UTxuw2RRN2xHbk5pQacGdurNUmqcm4zRA9IQbUMamtyonx9yZBWsofb8j0z2h5/NJLlyHAQfpp4YxOpNjy+/I8tzOf/az7NACdgAZu/V6M4sUi1tPubsCbN5r74/G8G5egEGfOv0uuXby6I+A2MvHuZXJ6PneGuISSTNynW7l7tMYehnoPD+ca+W953lXnml9MuMetUwmFQKbh6t2oNnaYSt123VDlQAaRhvKuiGX9Ntyv9Qv9/qMiauMc8WwcfJCMomPpD1Ax8j//8f/dOWtA19f2bTFtnbaLybDm3BUfXydislkATWdX9c85ax0ACFDpnhqM7G99JlrMztu6sGli8Xq42v/YJmYmJiYmJh4MiaBPjExMTExofg3WA9fhD3lkCcJ7Cm1yoGzJH6vSDDFDRFiiFhiRAwBIcZG+W2EhZAi4iZZrB7Esry4dTf3yVmI8jVByPOUkPKqiiwhnpiAqArwonBT4jwzg5VoN5KokOla8MCEAD37+FGauMcrVZRGO/n81HUoterj246Bek1FIQSo68c9f94d2GvgT+TpUkgLfk2F1NeUE89f7uasZj+e+3F+Kjc0uGffWYmrjjjy34vStWNzil6UqOvvMuh8f60kchvRRim6aT5uZdiIcFLlNlEoBBrp2dxGkks4ORrCSFRm4HBYEOJS8+asxwMFObNTS2vPm/rJpsQOMKqQoEdZmBU3eUvbbd7NynzFsbpthRv3gFjsKtlvnjfiErEsh0J6WznTurlA+ZwAACAASURBVIIgcjKlVAg+T+bnnHE81jPQg1qyy18C81JIdQIKmZ656OuVoMpY14yUM9ZV8+ZI66RyOnMGcr0umnWubvK5dDRXh2AAsdksRbZBC4D5hB+fY92S5+JdIJf4t+E3twYPdtT4O5skBg0+Vthze7b5JgR7CuYcNTaGLzNv/j8fHZF4mhkzgFbPzpGzsBPyXceBWKBXjzWWsLVPyhkprbJ5ZE2yMSQncJbxTW7zHNRTBHN72m9Zi4SgniOAdV2xcqGwCinG7KXfXrl1FBY+Siky5oYcKi7tOZcxZ/W6JTlPrBD6jTZ2u3tciLpefFL9LkcPUwnfBW/Cj4hSQiXcRxnejoz95+fQx2WeLxowOkYOQ5Lvuhxct2boZ6/9gcNNqC+Lx6RqHka24+EaSSOts+3xI3DzzeTRE/w1UJlW3KaoNvmXjHKW+MXRmnzHdhyVPSodO23PX7LWh/bR96glBVjOLweDM+EWwAdiMDFeZeB+wFV/sHiz+tpgPlGeOqr9poU8mKe2Xlt8KezWeJ5j9vGP50jbeCXilMtvlJwAhGzZqPmxxvQb1micB19FwxzTZvkK+6WSJoE+MTExMTHx3WMS6BMTExMTEx6PJdG/od/Hj1UM7SoIOzengFeIs9PstITZNl+O/LGbQVywGyHek1Gm1PexBSOOQEIuZbGADDGAUgZRQGZCJkIOrGeW5qLIzmAEEKrdWpt/U5xXZZVahnjllbM0L/qYR9T8UxWfZ90MX3kNjAkaazcAlYD6F2446QmGL4pHyJhHZ7Mb5/1nn8iIFPfXG6J8EN5G0zguQlMausy63MdcX+9zYMpSu/LKU70KXDbuFOtvVHnVbEYhc/AsaRV37Bo+UNAdKBGg3MjXYrHeEzsUUCq6aNXNhTqDgrhSJyPZqZKLIEeospDeVthAQl2RuVgHlU0BgQiLusEGhBD3rSDk+SoEY24JPbNA93NK1o0AshlJLNGNQF+dq+2oVmIhMwLEMjkE2WDFSyxW45YOGcGdGSknpCRkOhOJ/lyV6jkJcZ8LwWxzThALNSaQWY+7Ni0bP3Y2WXgSvfYoGn6/DNrvuv4dNa0kiQIAbgAcB2TonlxvygApU9TrBMIBwOpI5/Ok1DgdAKWOWfugPtwavft3XR8qaTXrDyWQnUSxbh6YsaYE8y4gXhRCGXvsSHSz6raNEpEDcgA4Sdm0d8nMT3bmeSkgbPNF7z6+HBvA+ra3gvTrmAFnCxuWjgxnVMpxU08dGtGgbdf6mfH57/rwNtTw/qjpaOf76Lr3egPNh7dYvyQfTQUNYPsdtgRbR72ZXHYZK6QoCOzcW4zHeZ03hGjsiLadOWo8A7XPvfShQbjRODrVXqOc1I0d7VrW3hv0HgBy9rYPd7mE86vtx6LP6/WxEbdt1yN3afi5oAxnqp9NYAAfgw17845VgxB0gy4gHrZQ29ss21+hI+C5vvcyt88IQngzuJQnWpxc24kBJLCQ57YZScP/gID3nReel0z4UF034FUmEP+A9+Gupk2QebakUnMVuNbRuRbqifW9dtmbS4f33cCxuc7mH7J1QSNv6XRHdmubUV63r54RUhMTExMTExPfFSaBPjExMTExMfEkFIUSUFlm3vBC6qaTKqHkiNmGlAIK2S3MR6e0VJIlkPBQxX0pM5gCECUtNmv0UNO3qLLG3biGLZZtHfTmRjk8uDcx8W9C74TgMeT5HqH+xJxdHFJEgHOy21kDE1C9YaibcyPmtvEY4UViRaraWiGJgBwCAjKMPA9cz0i3OEbnrG8tRlkN0zMoUCGjxUpcrL+IAMqM7EkgFlKEujiN/IshYAkRFAiBImKUM9CNVAbQuHNncdcBZBY36xCCXPXTlpLcI1LyvMYXQsC6rpXA13oCAVFl+xL1SI8FYhWuFsaVjgAYZqGekMxaPorgT5zLvXruPEq7cggIWekygpBs1BJmQ3fcfHoTx+jZufmCT4Ty5HmEtjGAA8SzvQ/HkB/5Zlx4hJAqsDgcGWAlO0DI9EBU4jOizFuueyxw7uAH+QVXF/fVut/KOh6jttFiFKbsAxmQ7JlIjinQMWdHvlCoHh/6dykExAzkSEBqx4rUHekCo1KJpMxbPbqhlpeUss7Gydqaw8o86kf2mGr5tkTo1t52Yh9frq7q6tcTodfOYXtUm8XXcamPhifjJy7HpVRoFflGyfKmzkdtOop7aMU+uufiIhfOJ+D7ps19DHHpTuw3JFV8IG48a90TA3SHV0zIAD6a55zyO8rVkjPPN886X5tG9sdOeBRPJvpQ8lo9iIw2zkxMTExMTEz8+zAJ9ImJiYmJie8dJ9x4XoOq+KvxoVEu2E7+qhiqeXDfc6ek1p39Ad79uhHmGqZYcgKcucRfzhRmp4gyC08iLCyWDjnKmb0cAWSxxsze7bqzCjXrD7FerIqeLXHOjeJsS6thl1y/BN7+/TE4lyZ13/v87z7n7sHUHX13SueRgvZp6E5pbY1wNgrmc0Q6znzfape7GLnmyBNjVCxcyRF1VXGsL9RkzILU3/YkNlDcmpsi2KyfR6jnYqOQdpGqtXQh0YmL8Xlv4UzUtl5fR0UmEsHMZikEZGZQiOCQdbcSIROwmkcNQD1vSBnM8rK6fq/nR9e/wvzBrLyRGZyy5D/LPXFzzeCcuo1TrhxOGV3cwSvJaX+AWuURAApYHMHrN2uYZa25ZhdHJCxW8TlJPsFKoLNYnucMzkmtRNlaVHdhETIzArO6f99p192W34bfHIdxyXvlf/nzs2iSaRQHEFb9buT1AWJBHrVWVhKSI+jfLdBcW198cGkzgFVTjOWOv5Z0/JNV4zas8P3VzbvsyuLr1zYouOtT08/edFTkT0pYoVM6CFkJ9OAJdKCuC8q48PUgngsoAMyEwAG5WNDrh8kA7cOAnBcuETESi9ebELJsMtFllCw1rptQ69EXvb3wuA7ke2jDUBvi0r65wzk9Gt/ePEpQF0WCpm3qeM+o/ZS5OgDftuU5qtXWsW1N5EG7+vlym8q4Jk9ZY+/NzYOV/yb+cz127/lzt/dj49tdj7TDerNEsOvknpNv/92ExrUcqE2rzDXtB96X/iChPZnu6+AVA/dKTr9i4NUvP+PhzZ9gZtz+/Ct+f/MG5n2jbWe5Z+W838xtVIaG4SUTPhLjnhgvsvV/4IV62fjkLdjLgqtWJDGLTLVcVFcPpcLLxri9nURdfY6CnO0jXqjpz78y40qjtJG7jtJ7SLHfcOPxOH84TUxMTExM/JMwCfSJiYmJiYl/Ap7pt7rpPUxR1ERrOg3uFSUuALNpGV2k6qadSMnziBiokDgj6yojWYSUyULUmOrRKakoRIACVgKYCCFnBIqtIpGoKG3KmaQMMLGQR97ynLm68e3z5OpHFC5UFC+PwdOUiz0FfjruS/NJpZCKTsFk9yb+neiV+SPF9Ojan3/+PN1nHIuR131v77u1RyHPqSU+vSt371K9cdluspAAb7msAVti3uKCKrCjI2GchW7NVRWjXp5lU0aTHEeBICSxEdDE6rpa5XF2HjxsM0DIjBADAgMMR/CHgGBnoccI0hPCSRPmlJHXjJzEAj2n7GSqylXOxYo4xvanJvfzQkegE5Fx/3JuPMXaQP4Pjjy3uaL8CYlOiAAJeS7nXuumKpJ37aztQNIimc1NfRarYZsHWp15KcdZ63O3OeMalLe4utr2yScS1+02QyUI/1c3pBECqzW5vpMhbQ+0ZLER4lajPjxTdR5uRH1PqB70mVmiCwkxoF0dcdx6rVCXunB9YzMOeHvZWwWadwRmUFplXUEE5IwQCNkIdN9mg/QaQsQmPlSXyDX/8rwpC8lmFIZsxCAOSBkIISNl1I0btNl+eLVQPEWkewy9IDxiY8c/F7aVxq7QfWuflE1OZ9rL99q2B7cO+bvefQW2NLyf466Lcy7oLkXfXudqbjRF1M1bg3h2GvADCYmemXDv5McHqiT6BwL+EyJe/N//D58ePiGV3ymCAJHrPzBwp4Le9g/335s8kOWB8VIXO2Z9/kJJ9W05d2SMcdMi8FsPYNvaaG71Y2qbyhWyrPDzOmqasxfIfgA3g8rmyHZe12M6Tq4wJyYmJiYmJv4JmAT6xMTExMTEPwLcfDw9uqqgbY1yKiVmz5okSZQRgaqaXogRtTwPSp5TKAp94XlMQZkLAV9IGSVjSNMveg0CEjPAWdwlgwHEQqwkiLvexEI0MaDn9bXWtJ48rxsAagCLulGa6rW/d6365DIV+D7OnQF9Km97CqiT8V0RduLr4LO1kSNyPWk0Eje9gnmocD6R0X0RZiOm1fj2lttym9Hza4Vy2NF1evLcW6wSVfKxZl3j17SETCNw1jOXzdSKCJn7s2SpWKgXBxjm7t0R6V62ljOclRRnrY4AOQM8lbNKGSnIedCkLt2FvZPHi8piI++tNr2i3RjNYAUEgROLZ48kltw55ZbX1LpjADmjWq4PMKBXa72ra/xIhOWw4HC4RQyEJQSEJSLEReq2eA0xaW5sgbnZB+x8eMuvWMdzITptQxcpkZ6zuAHPLC7xk+Yrs9wPPWnbgTT9iFA2XTwWhLDpo55ysXPKDyRW58cSRrCgHXsvAdz88hoUAtIfd8huGJjVOIGxaG2Kq3jGy18C7t/k4greW2IajFw2K3V25+62+UfdmKb1GJll8xu4jF977F3TN+Q62RLh9GLH0spJBtmuS32u38Xdu3fX3jHkNg7JLxHqTL7mJOUnBiMDug7KlAAdqyV/J3N/GVovHK2M8huA6hH0tW3c/oBdcfy55pNvZS3hiT25bskw1sPUA2Tsl7PanUePHrZBZ7+M2z5gnkH8XerCyhN2Ibbno2f3vcx33XuX1L3FXPPXP28/94j7ves6s4xxLo+jOeQU+nClXPoldwF60eJHlv9NRF0JT5XfWiBAvYmUyZ9NTIjs4MLROrkniX4M9dgru/2R6lEdv//xB35g4L3KJ/N+k9l+AQVEvMYr/gvv3RRT52vXkp6xVnzwAhMoZ6S/YMLH8UpProyEbsaZhOOBJTrK+qiN58lyyqfDcL1cNyVQzaON4LKJrkurX8tuN9VQM09MTExMTExMfN+YBPrExMTExMQ/BBd4vbswnp2f/GcU1kVhG5xrdpC4UFXiJhqZriSGWRAW4kgVRd6q0ZPYZiLNqv2129ksx3MCISBDLCNXPfuWjXHqlEKNu163OcC0K6UcvbbEsROPre9TFuQXx7EXhWontwriiYnHwVGV3f3xd7tm4OKO1w+zcn+v/27MpjSn3e2iq8aOu03yX81aVa+d5bnE5akOlRNKmOYg7wdwEz67uCUuNJ9QN6gteT6gCXqSHeK626zPEYJsMAoBAQxODF6TyAIl0ig6ilAJZ5cRlbkBOYuVuyWUUi6EtMnm1lU5Cz1AVMLUehqjHN1BVCzQYxBi+3A44Pb2pnouCQExRl8NpZ64lEU8nIBJz2jP5TiPbF5MmGT+gbqsj3IqPFFGyISkHZbziiS7G06UoJZDozYe/+wGp5PxAWjO3XY5sHgPjmywkMHqBkJoZ333AQC9vcfNL6/xiSR/t6jhZJwS1kLbiTV6/hN4/euCD29kQ0HA9jx0I84TtP+SWL8nVxJTOBw1ywvXsXHDYv1vVu4UAqBjppLy1QMNLL9dk4w8OXji3Y+mfmQJKRURKTYbZ1qrdbEbtZxkNNs3wMyIFMQrBOsZ9SQWimZ1PiKFngMlhxvr8paQsnKNwnzJtQE137/iqsStKeWSNU9dsCvajBidlwVPaNdkfSZGdHtLMG/Tt+eDWQJKPw7zNw6/F/Kfv2Ls2+op2NtI0AcgAOahxg9I8pGgtq9Ymds43WbYu3i/tzmoPK25ITDehXeyYYB8iF42UPMhgXi383x06wSDWae3JWlB9rsthMHa8ctQz+W3YcmU5c3nxR0J1GzYdLKhVNn4/sTExMTExMT3jUmgT0xMTExMTADYKglHlucjpUajDKV6VnBQF+2VICEAoZ4DyHJ+Lq+pnFfea8YD6xG1ICAIQWJmAkQoCnNRF2Zw1jN2WUiTlO0viVtaY9IaTVeXbk+q9wzhM5Dnz47n1jVxVeYRf0Pl/ML4XsrdKky/fNqPxZCMPxFh3QjjKAdmgEJ59v/Ye9MuyY0cW/DCjO4RuUhVqlJVd78zM2f+/8960+d1dVcpJaVyiQinAfMBgBnMSHp4LKlcxKujDCdptH0jrgHYEnSeAw3/LzMVNcN77XZNw0hrUdJMUpsLY5jOvHsUYAfyj+vBIUskBXur4VCR6rgqWe8+xZlZSWRmMFKNQ4npjJwnTFPGYTpgmiZM04TDNOnznJFAmNT5MwSEKRFACYWoM7NezcWHFhRpmnzx0IHYwy0SKtZrrV8oYT+XgpRUqxtV+07/EV1OALY1JhEyMgjqX17NsTvtSaaVruHIfL37gS4QQJzBmQEGBAUsCZQYCQnCpbILi4MD1Fo5wUh0Ss1P9kMhgB5xWDPRTEaGqs9tJb1bn2UL6cL/7HUFwgnA/OYdXqCZfb+xlI54BUAw03stUiCq5zfaz5xsT+jHiFMjE4BbAl4L8B7AFQiZnHRvRLpTzt4bxPpwhlTCfwZhAnCqhGans1jTPaCnh25XqcjlmK6UsRHLfpgipwT3H65tDB+4NR9sY5QgKPaX44mdur9pB3H0OItqoTe+JpC16/zSo7Gsg5FeXcfl5OrD4G1WNbifOf6noyfO21xFNh/VRUX/jAT5uB7o8aUab+vrYzi/H4+HUHhvvaZGo/OyCHnf+y2UrNwf4+HFfQr/rqHV37muPdbLvQT0EO6p4DZkz2Kr3bDRn5f2BOy3jD1iSMQqq53Z0fr7aNri0cJAxMd7Ki5RNVbeDsUh1ru1c91yUDUN36VmFhnaAJC6vnjGXgvhPQQ3JHgthHduXcfy8Fpe4R3eWb5sjeTm2kIQ90nny/VoxL0IBUtA4+FIy4taPRtrPaw80TpNrC7p62bHjh07duzY8fViJ9B37NixY8eOHedxRvumF6RHTUIz2U5OolsY6gVvIlI1BWtayo+pUDs5AW/kjZn49Ujc7y2TiSvNBLz7uy0ilTznQCZVEgZK4kcCXYXfMS9OrKPm7UvFc8loKlE1nDfY8QeF8wfo/z5bv4hCx3h96eGNhSb68w1SgZhP7HbdEdwGEjF2kfTQD6Fq02oACgeM+vxW/+FQlxWRpE8UCOZomaPmRuNhtZ2u5Ln99XnONa2dPD8eD5gOB0w5Y8pKoE+UVZPZDiSpn3UA1BPnOWeIqFWPURsuJdX8rsQ5DSTw4pCWVOGz/2Uz6VqEMc8FeUrGTCfNXyAXIFTrOAuByUjzlDAX04E26wAF7qM+qZY7mQa6a+CTqLV7s77PIhAGCjESJRSLu290MssG1rZ+oMvq61HjgwAg1YNL41iLbgYANXdPaObO2ejuOoeHXAiAGwAHo0ySteBEGYcfJ7z/6QMSXkLwHgIyyreZhHetcB8OM4KWOICjAB+JcLT7B1KC3y0EK0FOOIkflBBkEnOHomR+AjCRxucmloXaMKo9qBLV0qUvoS7Wq5dqPTpJTiBkSphS1gMV/hyk5pUDgV5YfZzbkTywmM/zUoZ0GicW75ixAlR3Es+ApWWNkOq456oh1vsnAav3z6d3GbbS+1K3VJ/CWsAS1i88zWeojcfG8CkOUFySly+5DzwVl3DA3Vwxktbhyk21r+GFAB+xXZcPa1My8nw8YtHjpQAfhsjfhcON3YxoY+mdHdLqUU8W2Bq/ZT/hE8DJ/RUSvYLCd189SNcuff+i99sD8euVNt2xY8eOHTt2fF3YCfQdO3bs2LHjm4FEOcTjYxlVJmrsgcgJqJqWgSBy8nyNQHFNURGBFDOxG4TPWVTRQVJSjUFjcCmrnvmo2ecm4NmFH0a+MDOKkehNxG6aGBTz0yqNrMg0asMbcT6acv+cQj8aLs4S+/c93/FZ8TWI1nwMSbvAMBy2xa3VCWYvGO3I8q13PV0J4xOkfsMRSNwgCLWk7LYEEmkpmK5y4loGOzgTxnhHmFcSu49JdUxZTbkbQZ6kzZt+kMjNQo+a8Z6Gmxqv1jKMCF8QiOvVhOonnTRX06Qkec4Zh8MBx+MRx8MRx+MBOWVM06SHlQAlpANRn9KElCcwMw6Hg97nAoKYT3B05trZ/IyXUiBANbm+mtVBK9216JOZKOHCOOUTpsOE43TA1dEPAmTThleynaD+2lkY7tybIEr2TxNghH6t7URIKev/pIe9SIuOnBLAQEqCxAls/uTdB7prSGuDNvKV/DCWE+neznjE2K7y9qZxH0lPfUTN5LmlM0EJCxLCRE6Ma5jbGkZ9pr/++5/x9l9vkQG8oO+R/pLw8ec7pJTw8m+vcPdP1e0WCGb8BgD47i8J796w0caKw1A+BuHanicn4EPd+Xu5jiE2wwqCLLrwryjyqaEBNA3Mye5NeIWrv2UUZvz0029qRj68t0aWgwhXZlVB3c3YngWEjCmca2nh3XR7a6Le5UzdeImP3ZYP/7tm/j6uy09enmmYa8K90Ux7ZxkjRHGpzYTHkefraUbC/ql1QMPfEffFv2r+Xy+6n+7L3veSQk1He9gd113n+e1ZiO9c/sIq3Pa0D0fsm/14affPt/B66jS0wBYhP85rY3623ntubPW75WGTdv2QAw5xxoi9f4w/bC3qEwGWh6jsJNILVq3zWNu32Or/evU9v8Yb+lXnOnc1sdGO7AeaLSLVFF8SwR9qdvsYxCbRDyR4IYSbcI7Q91aRrBbbhBGj2/PATbv79tH71XMfbKmHsJY9TvdBIQ9D0rLZixAsVXwNO/wdO3bs2LFjxznsBPqOHTt27NjxLcAkti50eXp89R90YqBR0tOZJEY1peskUTKBC9m7rIxLJaC4zOBSwMyqbSYqkHBfsgKY6fZctdopSJRmi1eF1hovs5twFyPPpQphBs6qI8I8WgrCcC++C/wq2baomcfhkTqK/nIj4e6XvGr4en0m5+Oj30uaueOLReWKwlganyPcX/Yu2ryM8Z0TZFeT7GjmMp249PuVZY/hA9G5lpVWhhbeSfSaOksTskpLM4IZICmQqn1MlVghIhUqC4IW+loeoERwmGc5peW4dXJ9zD+54F3ADORM1VT7lCccj0dcHY84Xl3heDgg54wpTTq3WSOr+fMCFiXAU1aSXYw8Zz7UMpWi5SulVEK8+ki3PK2Z0I8C8GLzv8dp564wn3TCvro6gI9qmn6aJqScQdm0zrkZBOfidaKTXTMzr/6oOaxVyf9PyTS59R0mAhJU8zxp/CrEN1/WlSR3EoCaBn2gyXrf8PdPnSOJpWmFtTU+p2U/PlAz0aslEvutxLX7SydbkykJciIwCCd6j/zLS1ynAwplHKcDPqSfMeElrn44QH7OYADvfwGmlLvlIJLD/jsDKEY8A9rvSyD5vZ+otQW1lHCC9x1C4lIrJYVDCOTpBFLp8LcJICAh4094iZ/pfW2LWt5EOJi1ASLCbPuJg5Hneh/QwyNUydE1WqTm3fdb3DyhV1IdqL9F2qyp7eP5Cnu11v0W6/JhIFadpj2hD4dQXk9/SWf67z4s0Ii6T42t/c4z02EPgyxn89GthAWLIewvLe6MoDPP1sKew+9ZT/dtKb92yMbvrTDxes1g/lpdRQLdR2Q0179Nva4/I4vjhqDEtGl7n28rTe99eockMOLc9znr79U+25YgXVG678LL8LFqpIeRIL6F0Y8S8jEoFsbnfT88uOIjfShiy3gsR01OVp8votn4LhJJfXt031L+Z1w3hm/kHTt27NixY8dXjZ1A37Fjx44dO74VLPnuZ4gsXsoybhHV4HPyHEYwsTIx0XeiEiuAGEHkZAuxgIr7FSUTvsNIABc3uWl2JyxUn61wMZ/BJsg24pwj0SdNYO2FkSBY6WTY0pexCu4FziB2eIhw9FkRCcHtIIvfWwI7Wgkz/t7xfPhy63U9Z0aFmQD4TJ9fkcg6pfSowyJ0/qzHdh4i8XGfeFn/IQsr1PxxWhaqG4dlXtZZcJ97XFu+iVcte90zv9/S6/LG3NV3l2Il452wpVpmD1d9l5vvbwrvZCQk+wtSQhBJkJD1RAD0HkHNcLsJd46HoDxcJBcNrlXuz9ew8AXPqI62u0MPdigL5DJpUl/z0uJJdlBBWDDlXIlzsUNVtV6ouReJUPOxCYkEKZH5QRckSRASJCQzkR7qPJDlFMsYy7XWdsOzsU7IrK9sdblYbwWqWU5WiEKq+e8m1qtlGADXRJA3N/jhP/6Km3/+ijsABxyQiPARCXf/+gnIGSfcQt7e4Cr/uWqhM4A//fAKtz+/r37Uo9aya5lf0fco9BuYCIUSppXDHiys7cKMyRgVZsGBgxWJUD+zSHAxoPdvfm7mgGkSvCgZLLWDVNI8Wd8vRDgkN91PbfyAtB8FFfFIhkP0DA3DLOawWrnxQ4EFgsKu09lcPLA01zFr8IOCB1A3t/hIvgXjCDWJT2im6fOCuNXyrfmMr2UAoHYyzmON2Luf2G3prsfZk0tb4Htyt2VB5Cnr6RZ5/hDogRdtz7XDVU3DfJuqjauUW7po9a9XCeumrce1I+5pL8p/eG/tegy3FsMWEXtJfLHcq7HfUxDX9PVVL9XwGy9uFOS+fn+uTs8T8uN47OO8tK2EWzvf+M6q8c2AAN/L9zoH0Tu8p5a2AOpaBO5GQvDK9j3vx/kZgtcC81Ru7kx8bUZYf8NBRmPC+wJ20ersqMR/e0ACXAvhu7/9Hf/86Z9WJqnzsv5mPeiW+v5PMqQhIRuXLraXBOoWuiFyT2xzn+mZuiTtHTt27NixY8eXip1A37Fjx44d3wweIvZ67m/ZRXznMjNKS57Kwm6Qu0+LEEu2SFbuGToCR1A1zPQ1qYS5BPPExAwUGLkhNRGqzHdIWtp7YvFXc8FcjLRy87LSV0c0pSuWH+qL05HnQXgfzbaPbRwpwcdU/SjkfgxItmPweZ9rrwAAIABJREFU/I/3GmRxn4bfy3dW8Gz9bseTsCX1vZQFiWEf91jDBDniZvgtST0tg9XpsY5VqYrGTkYvUltjnGk5WlVDuo8/arj77TTEOZp07ohwJ/hcsk0tTjLmvM12C/pmuHRN7r4Io0n6RubGVyOZFjRtYzgCciCSiZIeRiKYq4xmatsJ6qq5nRKYpTePPuQd1Ndlra97tLJElLBvprdTK5/7LI+CbMsXu5Z/AvRYAKn2Gjdy/5wJXo8xJUJiNRMvRUn55nvcNdupplvff8SEviRpqMa9ltPY9s5bAKppPnmMIdKiLyER8IIIGYSrv/+glnJTRibgQAd8xK/InWjATbh/wBHfo0DJ6o9vb3DIqpV+tDTvoHU3WVpMH8E0QYgwgcwnvMVq63cSxskIdIHgIHqQrlAz9y5opHwbC4IJQPTzzvY8UwFxwmz9nKF9VYxAn2p/Cv97cTmWGjUtT5eFq3WbuRh5jkaiC7NppCPsVZzkkjpfrZEpJ0vDTeK7xeADqP5em9LqCKD2zjb06ej6wq1hkO+NwrPl2+fxkEN9jkdtHy5hMc/djutNt2w0UjKGPZvHxR7rPoPtA2i88H3zesC15Z0WYWpP69fQDVya2zHcCnf5YFySv7W0z3WBtWey8fuhmX6s+XBZ+UsbBT+3Zatz/uI9wp/ke6QfCOWXgvf9Mm9rk1tP0a+XD758Wsjv5DtL/y1+W+F8F5Z5pH+6mKSkvwSAm8Bu+72PEHz81/+EOUnj8zma3ewICxJBD8l1H28hDem3B2f7/abGeX9fcrBUNuzh6vEES7RVT6i9caA8Fzb6z7inffKH5oCHFOGZk96xY8eOHTs+G3YCfceOHTt27HgCPvfH4edOH0AlVhQmcK4m+YzwdoEyC8jMITM3QaHKJMQ0b1TTT7XJCYkFQkBB1OxSAh1OrMPT0cgIEiRNQZjgAm0OwiALquZb0bQIheqzpVSuiaYeS4M/qe08z2ciebgp/4fk6P6wD43tPtF7FAZ+Cf3+MXh8viNlMsY1CNZdrXElxV64T6gmMxeSNr1OUt1KX4THyAa7HK4JA9ceSej7a8zSRhz1b6wCQasVl4Vu5jDWevgdZaXUt0wa+q7mWbAcvN4Orf0IMJ/oHqSZfnfyrxKqK5OBHytiYRQuEM7gwuBSUFLChISCEg4/VeoQEEGZCwTFTLc7IUh1DDrZx4Qq2EZKKMwaHbNXcEuDjBSM2tsUCD0rxuEw4TAdcDgecLg64nA8YJomZDOR79ZMalMase+TPYMhlHWNIKlEZ12fVsj02HLuF17QqFrXKK5a/MM73ooPwUg8ufB/tdeFH2vzP1sE9T4BR8slEXAyDf3801t8JACJcE3fISHjJf0Zt3iLAlmUKYHw+m9/w+mfJ9zhLRKAVyCUQNQd8R1m+g0nq5vsBHXSumwMOnAFRhHCBMEdEV7La9zyb+BJAEmVeyBRDXoOWudewQLBlbRyEwQnmlGYcSTCTJouEQHJ+oe3mPe3yGYJ0Ayya6yqdMkAC4qR5/q3jQfuDveFg4NiPcfJc1GCXAgoohYDIpUkdlSA0DSx3arAbNcv8BI3eF+fuxbqS+g4fAmqWuiz9xJCJXyYdFyStHVA4OR7a3Wx+h3vtd/e7tT9XY6n8X4ffox7ed9H3rDGdbFtE7tr/BENHGAfqc+BK5EO+Y1zYDXfHEwnnJsH1peu2sPhBqO5tpH06Qx58KctXEsnXl+KS+uzXUt3/dCdDl9W7ZuIB0kJgbu850TT1uHY8cZ9POS5/raG2u1ka80Y63NoR6+rOH9B8Cv9ipc/q3/0PjGz5mXru9ggWO5LfgMD+P7v/453//wH/v1v/4aP/7wBAPyCXxbjfhyfNX8U9je+nQjl9Ypv2SfLj9655oQbEkjy/PmhMtRwbp0lzjl1D9cV6jMizC+PGYdPSbeS6Dt27NixY8eOZ8FOoO/YsWPHjq8enWDvgo/mToDm9x6RaC88XxfuLQUgLXESza+b8l0PD2x9Bi8J0nOhz+McCbwWa9SIrCK9KijmgTRn42VUmCyMqqkFwDQd+/prWqzSiHUu1WSwmDZY1DUXOPnQWiZqp2rdUxNyd8InBIESVaEPhedLqqX9P4jvhnDb1+da/b7rs9S9nI87Cl1bTrbE08Pv1Q7WixCXuvntmlbC99dR7BuvW1oP0vBaze2XIF27EE0qibX+0MsLqetdjUwP8w41H98+F7ZeEeJvD+4lBMbgWxNstfA5XA/BLkLNKa3NhSs1NdhIVoHyMsNVSFwjB0CpvRh/Uf9uL70Vn9xb3CKLkOHpSnwueI7xEJrpdiCaEI9vk73HLGBSDfJSGCXNKCXhkA6YUbQHJTXwTXFeJEC4QAorscgMmB9wgpl0J/Uv7n7mExEkqZYzs2A27WISgBIBlJHgSuSuWW7rCKXu+ng84Op4hel4wHQ44Hg4YpomkPktd6I3zPZ6kMv7FiXNs9W7QJBM45l1IbFhEedEzVcW76PJqltQKIGoIIX1Rd9rBxnW/cT2bMa4XyGsjAMKZncxzFet46GZjzXNQhJbk1MNUrXACcgEHCnhBDVTTwSc8AETEa5/+DOu6S8obwo+4C18RAsIM27x8aePePHXP6H8rGNhhlg7EK7xHQDBHSW1aGB9QQ9HpNpXIMAkhDtRwviYBUcmFPmACQShhCNNVaPd+7DAyEQbBmxjlwWYIDjiJQre256KIUQ4kvteb33CR3FdWaRvE6E23tjTMZPtzIzCehhFDwEqmZ4sxmSHMwBUn+6NRNf4iyVOpHnP1Pov2/6o9RTfzwjIJuoZ73GA4GTPDyCcqsFvby0lvvWZtATj3NNNjoPFnvqb0Ej09fW6jZ20+rxhYy+BcS3e2mcsZ8v1vZntBTeISeqDtWm6ez/W1Vjutfxcvmr1IWPmaTOatV3ceqrUrf59qH6Oe25stfpI6C9gWxTx+XYIGHeAMc61tMd31vMT/p5ptrU4nwP+xeItFXe5l2CrLmO5GGEeA/Bavsc7eusjo20zAl5BSXd3iHF9d4v/9eO/4+50B5FfQQD+LH/Cz/JG82tTSk07XHtGX4jgo43uFwx8TGv12vdmj/flj3/B9NOMd/KbvpTaeBcyi+r+XZiCNrqvm4uB/kSIzYQ07OGotyzUihJaaq1jd7hv/pC1QVCnKd8/yPg8Rj8cMKlBLpy6tnJ/n7wlylounyV37NixY8eOLxM7gb5jx44dO74ZRKHBWdBSYD1+n4ag56Lpfi+E3EFrqooJorBO2odxM4HeSfPa+2uCwk7i2bRPHo5ReOdf5i0/Lkr3bCP8LvMMKVwFCPG5ZzUxmxvzRqCqIIYhXJZCHZaq+SVJFtqV0gk4G2nRabEEM3sx7+qvkkwwncILWs8U3xJUk8yjqFevEzDcu/Sa6vtRTLgmLl2/Xqa9Fiy0rTSyp5MRVyG5y34GaQwtfjwKbRxQ1bDqxcEyXC//tqI8XjD2VZHnAa0GXHcxlqWNB516gtCta05qh1OC5Ha1RmT46+TkIJzcsmjaTIjbmAvd9aHWEZzkjZmjILVdmkKVLpvEYYKxSbibQlwSWbtgkA4LwEOG/RDC6uiW+LpqrY6HWTRJAo0RyHKuc83uSNR63L7CsM1bTnYJlBydCwOnOzBPmESQU0bmhHkuuMUN8jzhlOZqkj2njCkn9RGdbY4mARWyPsSalrOXIiBhJBuRQkAWJdEh0PtWpoTQhCKmPc5KtCZCnjIO0wF5Ssg5YZom/T9PyJSRQUiiVhHU6kmCpISJEjhPtWI9CS5sfs+1LzKr5v0M6MGArt2o8xMPAIdpgroIMY39UjCXgjLPzQIKa7/OKSHlrGbyUwZzAYsdFEiNXCxm+jss/GEsulsSYMpTFc6LwOougbKbQtcaFwsPmKZ3Ms18d5UCNrPlAHLGlLRtr4nsEJr2zRmE219/xZEIr/7tB9BPk2k96+QhEGQhvDheg+kdEl6bz/S3mIgwEeEOHzAhgYu295HUfD6IkFnswIJo+wG4soa6A6w+BVdTxmGaav+G9bXmG1nvZaurW2aUUnCHt2DW/YK/nQBMon2uWCtPXtVEmOuA1YywnewgqxeUAqCY5QY7QGJlqIcEhVEg1T+7+4WvLJPNw7klU8eAwOYlCG5F8yrQsAnAi7++ws1P783yjtaH/9Zxpxr8k9UVg8EkuIOEucDnJEHc2bjGfpvORx30NjKk5hZ9nPVuXI+HfVqIJ+zChpmz7QeWFHCj793KUI07TukxnWFrHPPBGHK4EnatHOM+bNwHLt62vPHi0Vhz/rtbjOoTr5dGvPZ78e1Dj/1BxXGf0Fqjxb+Vu63rtT05rbwRU/GUYnv4utEVcAAPGZNQgph/D7f4viN7R9afj4mOB/36h7SaR2DZE8Zg43HH++p5bcd7zuoUA+b3vFXnr+ktol2NJEAextmt3X/lB4De/KzzIwgfEuG1CAS/4i/4C+jPwPzzz3gL+JG7ZoHMEhUjz2v/S4QXQkEz3jem6CvN2umnn37uK6QAJe7fSNRdC+l6A7K2YhvhJN02DmiH/PrqXW9LGjaUOveU1iF8n+GH6SgcBaAWwOfWztpJyFZnLArL6mgPpB4yIRkCh+vV5+jLfab7rHbr1XvbQ6BHzM+OHTt27NjxlWMn0Hfs2LFjx7eFc1+HQBOYte/gs1HV5/cITJaCPAB+Oh3AgmXqJIEIH9s9MSOIH8R9HFWkYgLVajb9gYhaezW+8LOZJ415kCr3c6+fmvseZMJ/qRJwqvWfIM7BrEJYVCBWSjNbXBuu1bjXlsggpHWpXBQoAFAtyhbb2MZR2OhCxrWabSZ8BwlQlWrEXiHDM0HzbjqGj3FtXzed8VF47QUZxaGth1H3fCUt6vM6jIazuTyHVsrR5kJMb7weR1cUwf4xEESRi14whux6knd/GV4Zx8QGak3XLtDNTDouVuaOzj9lyP9D+koPGvqrLEflymTdbsVJzUZ16GLdPFvjoP4yPjX2plNqpyCPNZLUNUgXOp4moO2Uluy2RGbIBb8+09QDAz7nLTOn5LlmpKBAZr9OKDyjlAwipRRnUi3ilBNyzjhMAqQJh0SglEFJIKpPDhbzBY7WlgmNjANsTrd8VJ/MRMiJVHM8aspX8+tKMCciTEacH6YJecqYUkZKGSmpyWuyNYjM97pmJLcEQx3Nqaj2sK2NzAUzBNnXSnINYdPeTmQHB5IRV1lXABaUVMCp4EQzZhDKXCoBq+bKMybKyHlCmjLmOYGFtV6T6ygDM80opXr1BqWsByRE271Yrz5OEwioZsJrG00ZMJ/1IgXz3OZLSgk5qf/wMpe6tlbf6ETI2YhSUnXAJFzb8ZASvvv7X3HzrzegnHEFNyeuub2WV+A3dzjkhBnvcQfBAYRMCaCPIEpKlFPR2ksE9iYyjX9hAclLHPABkghFlLgRI9iLCK5BVvOtryTyec3nlYJZoAfsWNu2MCOTHgbwweEm00GERE2LMInGWawNmQCihAOoWc9hoIhgFtU8V030ZtEAIkgQlHBQso5EI87jnEJhDisQTPYes9hYRSX4GcDNm/d1ra5HZbrxLu1/AQoJTn6IkeKByn4f4CS1ky0JtEJyrO8dtojyrfDrC0+/nqurBLdC1Kyj6N+WZ51wUZ9HrO2exudrv5c4t8fZTmFZ2rXy35ez83nYCra2rm61Qq2nDdXRh+6qKm8q6LRwx3iiJnodJ6TZGMnzMWtxK9HikK5MNT8SDy2Etcb+JVCIX8ZgKwVcu0WP38j026KVetrIRtjSX0xersUTsp7Q1y0AfADwUpqA+B0Br1j/vhSAwEiY8I4I34neV2sjvsYxescP+uuGhiM9lemVrs1jv11sbeKcYJmnpLsPhlrv8IONfn60jlzyg4kru+fNtmwP2Cye1Vh97PnBd2nha08X3xNy52KgRe/z7jBrjCz/yuS1Wj9nnq8duqD4/vZW9+Jnq4iDdseOHTt27PjKsRPoO3bs2LHjD4n7BG6PQeBjunvjt+Oq6NE1vreI9gXLLMOVdKblHgIhk7IHaVjT2L4nzk5AHH6LlV0adaTybsaIR7VD1ZBfCoH0XpDGucpt1JCpgUeBivQSPpigJ5DzvXBI/1+WYUvA3F+PgqYHvStbgt1Pfa33ejE4bYQd63fUYXtY2lvi+y8Fv1++HlZvhDTMGCr0I6CzgTC+q72710+75JjOaj2cmXQvqbeHzG6Xjav+ydgje6r4/hw+vu03xeaLcE5UVLOh8VkYWYtSi2oQQ1IlIIoACWrumpjApEQhcVGT21DBeE6AIIEm1drOQhD7n6NKp7vVCP6hczYNZNfuRqqHBFwYTpQw5YyckxLlSUnnKSkhTUk15sAAUwExQYhr6ShpPlX7OyFnrQFmRkFbVglKkHOSqhkfHmps8YCIwJXdNB3KQBKkCShImFKCE7KUPP8ZCQmSBGBRzXlKtgyJEoVkB8fQ/MdSAqp/e0E1g05giKhp+mSm630limfZAFHtO1JCHjkDZYYahim4g2o2F2GAEtj6kFsFOCYT9idgJjXB71YIUspmJnfGQV5iKkec+FfMhZXEF8bsJuSB6qO+uDldFiRhSGFMwpj+nFDeFCQGsgAkL3H88Qrv//Eet6cb/MZN4zrO+BmohzOKHYgos1oGUGsAAjFLCj5fzRAcodraSqLbiCCpJPpdHULaD4ofsDBNdGYGMWNmxmx7iMm04glAJtJDGVZett9x7+S/3BbB0bZcs3W9P+ElAMENPjStXLT5+eVfXgFIeP/T22ZBJGab+jHfzLdvwSJZ2XI+Zi/y+OshV7VP2z6hM8VuriBAoVegPl8r7dYuo6Z3NjcPh+/3Pb20QVSzzV9Nv/98vaSupPG7opkE75+P639PKPYU9OPRpzruz4zYDM/GdqrtY/VUFv61yEhxKy01v9cCLA5+SAiHlef3l2S4K+tPLzURPtbP5bkYUgxWZ9Z2I/fF789fFeBDnStktZ98IOC1AL8R8NcffoAI8OHXN6rZLm8hv+jzd9TmMz8h/RqE99Tqv8uAtLHh/su3uv1//Nt/4L/+8X/qYYGuuqPWOAOu/U1EekCLAEoJvDq3PQ7jd3D4/Kx7MfH6DKcixVyGqUv4jYn7Qiz3p+f/du9JX21PwXPPmTt27NixY8fXgp1A37Fjx44dfyw8VKKx8fq5Z4Thg3vjtwyipKa1OYi2qlbH8iO+hpfHCwuYGSmlPm+eZv278TI5yWDiORfmRx46/H2qRKMzXSkqsmjVMErT0GcCwzVh0BCzfwMjr4JHihLIDRL9IfCUnmZM3MmXT4sNwSJGAv0xsX3qvP8xMU5xsZajycj2XP/jbobZiiVeRwFsb2K29cw+xkvmz4dg652L41ohnxZBhmllw7CDhbXSh8M9C/PyFMMtsqP3h7i7y0Hw6oRa184hH0pbp3qfRVBYQKRa5YmAkgrAQCmzapRZHg6Jusi1rkyDWVXPlPxVFV4AzWQ6AOSczbR4VnPm9SBHs2qSCEgpI5umObm2elJCPbkGvgBSBuKHgCQJSNDw5CS95rmuF2YegFJC9jUtA2Q+rRdkggBgX9dUyzolAcmETAmFGMypHVqgZOXUfLModaRlC2Um0+KXRnu5Fhsl0rLAiAkx4swIgWTxt0bvlqU2H5smv3eRaoJcGCdWslxJdCV/U9LDAJQypjzhBSUUEKYpmxn9DJoSsgDMBXenE2ieUDBjLqbFrwUBESG7KQbAtKzdmDwwA7h784u2gbzUriwCnk+YkPChMKTcefXXPktEmL0PQglrMOPOTOtzKXDLC8JcB50Q4Q6kGogCM0uscRxIkKVpfav5dQKLmmRn1rHCIiiisyOJVAca5APC/vrYjNODpzeF9gGCqXegWlXwd7xNxzq4/fk3829MzUqFaHubXjwOtEGcb0xwSzLzMfuZZ4KbQxZtn3CuxeaTuLrYffy+ub0kvU+Xn6ftnbc+fT41IfbYNqotvvLyfXle+IReDfSITD0VT0xzxe5OeHb+TUBw9de/4AUEP79502VmHE/vCPhOgPlNwa/0aw0TncQg3PX3Gjnfr0y9QwmyA03jbrLP7d///u/473/+YyiHvbRyMqJaBdILm5/TcJDpCb09bgSJVq3/9Jsw228biR7tq9fVf4hzkc7wbOw+564XXa3fNtZ8PAr7p9uOHTt27PgDYifQd+zYsWPHjmfCmqBoS4N78SE/kuZ2bwy/VFAXI9Dl0eS0gKpp0tXk1+KV4acLOz0/iPz1w/NVT/XXtJ2o8DT1vhIVaZHHSiAFIYcK6/syjITimlyAMMg5hmd/RFmCicHq70vCfwug4e+Xj/Wckv+zyrVsuCxw8hRQTS/pI4h1s3h7o8LOCvzufePpeMz43VIc2r4/aIuvTDT1VvdM6hy1lUvXemrlWBpQrdqLrlnLqnVeiKoGmTBBUjX2reaqE6Og6PvCgKhf8cIMdmqPElKaUF2QpwzhAg4TZjLiupo7hR/4EhPqpkqcKxtPRh4Kkph/dwJAsmIKVQlPEtX8JWbTllYT3N2yYJrwEYUAFEDcMooJuiWQmj7LERGmiSCSkFjAMqFafrH2Tck0x73MkU4wFe+kzLg2tRHYlUQ3ApjnUtfkdsCDGlFLhCQCpNyVTU3xqxn5UgrmeUYpRbXNTcv/RcrgrGkmoPoqv0rf4+bde6Tra0wADocJh8OE6XDAMWWchNUHfE443hFmO0Dh5XcT/WSH8YQZky26UyKciHEjan4fzADfgFndCBwPPwC5gIo+usYr3OIdZuuzL+gVCj7gzvpPMQJd3LS6uDn+otr3RurrAY2khxbIqBzTRn/541/w8c0v1ZRxqc/bvkrHj/cvJb67OYMalQQRJLL+aAcl8rCvY+1u1b2BADgB+A0fuhGe7Tnb/+9/+Vj3U7OnK+biRgQHagcv7tc+//Ih6A/KjOvRuA7/XuvxFgm9DOEY9qUL4s9HtnShl+b3x99rz2N89+Wzhe9jvazftDFg857vx7t079Orb+/7G5nDgVio5nnsCS203bHxVzXFw/rQHY595uHQfKS39Pplfb2/Pjkb0veTrRiXvUxnj5/f/HS2TWKvUl/qb7v94CubE3+zNUnP11ns4m+2fIbzRXAivbLc3drc19F//fc/4Pufrn96OAr1vVKgZjlAbN1te6VngYw93L8xw16P2v7D9zrdB2folJtk+o4dO3bs2LHji8FOoO/YsWPHjh1PgfQXHT97geZ544dlaY5wFL7Fj/Fw0z/OH3u6ns5w7+fiNE4DxAAZweLkOV/w/vlM9SZQa34EHRnlplb7MIuK7O9X2ZuLsHuhzzLRpViyp6guJ5K/JXx67fetdD9f2l87qg9tQMdqYLvdt6f7hY7GYYmq6LOT7cVwQBvvkWD6FhDLaJzVqia6329+zPuDBt07QWbq5jVXBe0SXgjVORLzC1OiaOPENc9FTOOaW7sxlORmZg3HDE4JJRWd2zm0qficq95OkTQNognZNKuFcw3j9ZAoDebRTaDs9H9SjXYxQTeDUQoBLAuC2X2ZErVMsaifUWJSn+8gCJeujlJSs/N5pY6VbLfeW/MW6pFQ0wWgZuPFNKvdL3aIT8dJq/t6n1C1yAVm7ty01p0YBxGklHZgxUzapyl39SgpoTA38+5JfaSnlEE5gZmRc67pT9OE62nCYcqgSUUAB8unADjSa/zw45/x/p8/67PDhMPhgMM0gXLCVBinMiNnwm0ilJSQS4ZrnicrizK/rCbeS8EBQLZDDmq7nsFG7ksRkBTc/PwrXv2vv6D810fcnWbMeI8S1uWP+FB/e50Wq//az6yPoxSrazKNfzZjCT2R/uu/3mAiPxCkBxJm6LMJwJ23IwgTXmGm962/2OGDuPPw8UtuYcCtDdS2JyPkNWxBjzj+Z6BquoPIyto02cXiSyAwuBLmBCXQd3xurBOodS96QRNpf+hp2TH2dfp8/Tq+M1KJj/xyeNRbzxF72LZ8Mfi9Rl1dp2INbGgvrxHt5+qt9pG16Ag230RivPVQPcPT14L6B/e9Yd1N1t9b/Tj2Vh8Hnk5Nz4Oyp+0Zc7JaA5Gt5ymb+5pHHDSXje/repAilKBaZPF3bN8BTnbw1OotfsteQKb3LnvuyW+Nq7+++IVLI9yXmh07duzY8QfCTqDv2LFjx44dz4SOALlU8/zMs1Vt8zHuqIH+SFziP30kLJMLKEwTrEgv1Hqyf8VBnbMzw9f9Jix152M86Cqy8lpoRKGTho77ZALuhTYKcXY5wreJr7ddV3JOG+XZkEY7OV6Jc/s/CXWadKsa62OcNAg9H4ynvR1jWft9GXoy415N9HXuYyu6lq8oKcaQiGv7ivoOd/P7Jqf1q26+NqPmKtBl+x8FIgkzjNAzYlGnc0Eh1SZGKWoSO8ZL7a8vAyCAUlZSOTVSc57ViDXXfkS+ZAGgKmwWYRW0G7mPQmBRYnBKGSln85Oeq7l0z4frKJa5gImroLmwOSVwrWhoVQqpWXghApPWmBOd1aILgn/XvnVC48U1ua15zE1nUiAQLuENgBIh02Qa26h5i/FNh4M2fVLz8ZSTmbhf5irlrH7js9aTiGC2NA+HgxLrKeHq+hpXV1e4OhxwPEw4iWqOZtMWBwDczvjhu+80r1PGNKlfdwI0zpnAJMgp4XqaIMzN3P6ketNsPslLUdPxB9PMlpRwJQIUwTyfcHd7hzLPmGc96PDbz7+hHCYwqQb7AWpGXYJ1nFjHCQJh03yHgO0QRDWNjqZtLmQWFuwaKaGAketzQUnJzLkTGFrfSALKAsEtJpnw17+8xu1Pv6HYIRASVNcXlUwiwkEEhJe4pfe9NQb7W8L1EcDtSk8roc84mT7bII3TRqK0mH+vLcSt3f8WtNKBuK+k8O82n/OpeJ7741unrnxeTnELT8t8Lh2gjLHfv0tVLA/3rOVume6Col28N9KfjSBt0NF43yIodT/RNLv1RzJrINUHuv23yfPZGEwO5i7pAAAgAElEQVSyVXfPOwY8vzxkaPRJ/9h+uN3+fWxbn29r4+GSgxNjfF6ed/Vlm4dd03yIO41ENgAI1YMjvqXxeU3s5XagsCeWxb+57PvNSXyJfzVDui+gvhwCVP/o58r9UNQDo4tvdfthWxpJAIjrZsmttrQDfk6SAwtN+a2N5ifCYm4YxtLG58KOHTt27NjxzWMn0Hfs2LFjxx8Dm5KC8PsiycJ96UTJ2PiCdH/i7UW0g+nPer2QlEhNR4Iw4yFYj9dhzJe4QMvfMUEuqzFf16p6MnHeZez+uBZVvBLFwnxjFG7EdLaEUKuy0CVV9fWSrRcilJ8W/57H89bNrn/+GLiYrjZjJA1DhUbXCUouStWerEJzaYPCBedR8KfEJc6OzYfgSxLYRWF4k21Kk+bCBcJLQf/oI90lv9Enus5J6z2cPPLOdGwQuEq718VvhJ8wg7kAokRo8nargm1Brua9E3ie1VQ2zBe5aUj770g8i2kEu0ScwxomIqaVa3Uj7R33/y1MwDxDslkVMbK1TJP50m4+wN3HuUcoLObOwyvfqpBIfYczVMu9q0xq5talVlWox9DHpY0JvdPMhguLkahWx6ICfj2Yhm4tTzmpFnnOyFMOa4vU+DScapsnovpOyrlqpXsduHZ6zhlpUh/m8zyj3Kn2OQAcJjXD/vLlS7x88QLT8YiXxyNOohYHUAqoaI6T1eER3+PqxwPe/fprS68UrcOckA4HcCnIANhMw1fy/nTCPBeUMgMCvASAnICUVZOaBae7W+SccXd7B0p3KOyWZJLVLUMESMTg5IcutA8lUdPlMyVw0ntqBcH6lPlA92FCEO3LxuUlQPs0EW4JmKBEOwFIWQ+bJCIcEiGnrGS3mek5Tgcc/v4D3v/rLUQYwlpncyD1hAgTvcId3mufbcNSzQl3/aj9f266LNZfUQkX7zayeOsEQbZWO4JwsvvfCon+reEif92Pj93+PjNx3MWtv7X/juksC9blKC5T0p6vxXLmC6V73ujIL2ff8OlJx271qnNFexZCDk1yeb7cfcjyRYK2X9Ws7lohBo9fS75zjAH6UMOOsgbzLVfdt6D/W/MVPt58n0Tt4eUHz+8Jt/nd69tgtrXNMk62eRy18L280u0dh9MAj8HGyYHx9n3jZiEiGV/csWPHjh07vmHsBPqOHTt27PhDoRP5LAjBUSQ0vHvp9+tquIElX5C6EoLI8MogCIlRycr1gyHn35MmIHGyrWreWZACWRGZPB4XE/ECrKqgu9m7UWAgy9/n2nwLY1l/b/nBc9b1Y9L+FGG/JHx9+aYzV5fHsC7+dtFeFHuuyc6aCH0UtNF4cwXrI/5hJdkK/Snbs5rsPIORaug0xAMh3oczwte0ZEnVmJQUDELqaqK8UZ1V0zXZLxECsyipXxiSEoiWbZVJhb1EGl/1Uw4BQ02REpH6Dgds6RCAWa1zOwlsBKgXqq2vqZqg7Uy8MyElBqeMxAU5ZfOVLZisTykRTuZ41eoFXLWUWcycuiec1Lc6JEHM5LofDqnktxHcI5JpplMltVt41zZXc/haPyzS/MKLQG28E5iL1jsA14SnKWGaJkyHqfabUgrEfJWL6MEG15SuGtTWWlXrjQiZtJx6OIA63t9N30+HA66urnB9fY3rFy9wfTzi6nDQQwnMmIv6SU/MamodBKFbzO9u8eO//x0Cwe1PM95PbzHxhIkLXmqNoICQMuGQMlJOOBXG7d2tWgMoWh8viNRywDThZD7Lb28OtWNMwvgwz255HUcA80D2TkAlggv6JZ8IWq9cGtHeuicANXNu3udNJ7Zpp5/sMAYJ27hKOCaBYMI0vQB+0L5GAE7/OmHmgutpwm/MmKiAGUim8Q/TgD3RR7C0DF7JC4AIt/QBxWiTLFoWN9cOrG9laiHXyHOyeWA4cHkDwbX1h2+ROB81pNPGDP+p1/FL+aN2gEKMMLc5xTbwS5rwfLw96bbyrQJdI1wzmjp7Gs1FCw/12EbMuB7FfNFKvp+GUWM8iXvtthQl7kRiffo+vt/vxzA9Pg21noboRo10xyXE5Ln72+/HNRGd1YsxX3Ev5hrdm1jnXRf9tbZHPYzcjww/gDncbvHVfqrtzuJH0CytLYbcb3uy1kHqNOnuZ8yziH/qVgKb3H/78/SHrXhYGFSNMVCdt50odw18nRuGA8JrG/NL8Iknv8dma8eOHTt27PhasRPoO3bs2LHj28IZiVZHOq6Qp2evN8K3dMdPSVl/1t3u32mk9BCX399610mAx37NnnmPELTOjT2ISbnGYVoI4p6OS2Qa4pKHlZeXQkAsrlfJq8Z3rIJgAiFpehZfH+H6OPRlfVqb73rknwPUab2qMLEJQ12Y1/mr7t42wZmZEV8IpKvm06cRVH8e+PxrBwkGobLWmZFbEuvB5kdq7+r7QcM/tIWTbx5nl4O4/gxTXvV9XsOEFcSZBBGzkM4ocDJZg6RuRKsJdNd0bmbiZWWudQ1s08Z2H+qBGM/ms7uVi8Ma0jTQCwg5MSipT+9CpZJAaueckAtVP9axV3HNg5LpcBI65448F9OeB1DzDDPz3rvwsHk9SIibf/hApPt/ll6vQQ6QJDCLavx7zIcJU8qYJvUvXrWmRcDGIFeLEAQzVU/1r3caIkJOSsTnaapm2iklCDKOx6MeAkgJV8djM99+dYVpmnCcJiTrCzMnJFIzygzgSGraHgTcvrnD1V+vcJgm/Pjjv0OE8fHNL8ZaE5AATgkM1dhmZhymjLu5KGkA4AUlTHlCyRlHZpRStM3ngsKMD6cZiQWlMK6geajEnijRzNLaNfZ7b69G5rX3fDx6qEj2iOiZA9VqD/VaDykkpCS4/vEAMHB6U5D/mkEHAvg3HL//Addc8O6fvwAAStd/xFwiEAp0jyHWnsX7lZEnTubMW/vRatEiskKo80U3GocN0w0ER6uVaxBuvom5eImvbR/xHNrmkbzaJNnrg7M7YPv3vr3c89dx3DvXlUX65w7B9v1Goi/jxxB29cbX1X0egZ7qrP3iknKHvU7Xa2yrsxUFhXB+x+O4bxYae6dAOiseq9jcOC0DVsIaYc6M8+wjcdZtmwCo7gzEOm1buxC3jvZvK5I9f3CGPILlDCnDj2b5aD2q2m7jOjW+t7bt/zaXnR07duzY8QfETqDv2LFjx45vBn6y/rN9r60lvPVRvUKeN7O747PlOwtz7U8odKfV5PdcymwCbT/JLyGMmly9TJj3UKxV26oP+E3do3XEsnpClYDCuiCuvYxqppDi9QPS3/F58O210frhkHvfWZOCjqFWbldCEQSqpht6E5gUInAt0Cp43VTRflrL/F7tKiYldH/jsTgUAmVK9a4LR1PVDbfZMxxQMLEt2sJFQzM1wfNmxiiGXnqhrQQxA5xUE6oYSZ6AzkutZoFqXJkEKRGKEcZmyRqugSispLKS11wPWbHNqZzUX3mlJsXXupgglIiVhMRK4CdSc+0JhMQFxITTrHRLBiMV19lFTa+Rp3bfNLqJuZLJ/TuRcG++06OZdIAgwlAN/lZG9vXaCfZBA10kwdXV/dxBIqqm2KdJSXSiFi8zI/FSB7nWR861HNl8wk+HAybzfd71KSNwU0rVhPvV8Yhp0k//G2bw6YT5dEKZZ5zmGWRafydSv+s5JyD/Bn7zEYfDBLy9BXLGy5cvtU0Tga1fVx/ezLgibTNRS+q4JsKBEu5SAjHjbi5AKbi7OuIwn5DvJiXVZ8INgJMwEpt7GBH1ZS/ej62K3b89gNCbzsL7r48ZtfTeiPVUBKckoARcAWAQbt58QAJAU0L59YQ//79/x+3NFd7+42eUMmOaJkjxZhcl0qUNYG+Lk3yEoLm64dZb1Sx9uHfRnLayj1nDCb0biQMI8yXx77gIa3yRk359OBub0od3X9+PcX10rp+0YyMb6YaQMbZmiP18fkYrKlv5GWNZrmt2iER8JRzrzeKxH2zrTrIbUXP9EnIWQNXyXc/h84AWvyT8u8TW/Yv3N0ME41eRzyt+MMmLzyuVFvn16tqE+vqt2456MLBvvxbO5x91BE4kRry3CXKNuM02U/ohLJ3t1arN//N//d/4z//zn13h3KJDvSWtR/v1aoXYXiaFQq+2BVH3bfig8SqAsOhBQDu4KF292+5ohcRffK9+Kkgg0dH3Whr+jjh3/2KrfTt27NixY8dXgJ1A37Fjx44dXz3Gjz1gU57YfemNn6Y0PL8v/FrknQC0SnvHYPF+EKANWuQS/pEubIjUuax787aNkeCicCpfuEutJ/q7B/3lg/NAHn+IeuWQwSLQamReJvuIXxFntUhb3D0N1Z41WQ9VQVIf22N1oB4jNl1E8VlQhf+PjuGpbz6lx/9xpTqdOUzXepbW0V0jtmkYaXjnhKI2kMBFf70AtYnig4lMPK3FPifqDB000KOWfiMrvO5q5SmBCpfmBtPSo9Y4jalZjGcqrqZV31wGNg63mrAGA4VYBcamIZuG+asdjCJIYkCaD2ptTKfP1Qd09QEuAnDTzq6ErqvfqrS60jPtLql8HQI24peIMIkAOaMwA7OylAwgc6lkeBTudnO9a6kzg5L6tR7NXzsh6/09AXY4ilbqPGiaO8k9hPGxUMsfAiQMxPc0VR/lgJpbz+ZDXERwNLI75YwpJ+Ss4VNK9f1pmjAdD0gp177HfgAhpbqux/AENRfP84zbmxvc3t5iPs3APEPN9OuBiZQyjocJV8cJh5xwTYR0OIBc4z1TJaFEGJMAswhOwlpO4Wq55hoAE2ECQEVrhk0rvpSCeS6h3WYIAGbBZObv2YaTk+YCUfP8DEzEYJCGIUIh6kzgeh71gAP1TGI4fDIBSFTUV631V0qk815KSEkpnePxCsera9z89A5uWp+TWmpQU/is2vs2NskPi1CnH1+HtpujL6E7rQ35NSKFEEy+bxyGGpEAXIFw+wdeAz81vsSa3dLSXselVHT/xiXPu1gDK2dL5YNyJuHdGF2MfisPn9bv/KfFY0nVug9xorTnvkO4xYsh8fh96++uazi3w8WaqAdP5Kv1amohjrZmR6s6//s//z/Es3DdPin8XfSHmJRvSlHp6z4MreSs+0Ye89pbFlorjbCtN6KHUKXrkHYvWW1KK0jvKf0xWO5n1toLbTns6m6s2hp+iCeIKLr7X+kw27Fjx44dOxbYCfQdO3bs2PFNYu2j7V4zf8MX95qP9HtRPyBl+cEe7o8fnsRDeJcAILy3cr83Y/rIj1VyU71QAsQiiqS9/9oiz9c+qJ+CVW3zqIFfKaa+UUdKeyTPq+jGjtsvyoSVMphgIYp9ImFDa+9cgKeSip9bMPFY+v/3MLn6uevmU+PR5Vt5cU3wZ/xqN1d5fxeTjvYjq5GiJg+sEu5+fAQS82nZ/qQYxzqqu4bQewXIlBHo7nqfxspbwUiAAwjmpBEqaJxhKMxJFK7XEvN51Eh08/vMSYWyehhimEV97gXABZAShKMSyOcubJCc1nyZxlsQBrtGW5N5N9FsE2JrjooQiBnF+pynWUwL2+dxL3WCEscgCofAAGI1SU4h/qjNTKRCfclmrr52/lZ/teaNnAYGAkYCwZ6CNntKyADISHA1ua5EeErqDz6RmmOHm2LPGa9ev8bV1RFTzsjThCkrcZ2dDD9MlRSHKLk8zzPmeQaXAp5LJTeSWUWQwphlxnw64TSfcPPxBh9vPmI+nTDPs+aTgCkRJGXcXB3xCld4OU2qYU6E46S+zilb/YsfqWFkEGYk5MkZDK27LLq/KRDMpKb1D9OE6+triAiuAfxqZTncnjDlO7UOUBipFPUjX5qJ/sQMEjV5X6DkczZz9K/++hpv/+fX1l6hiTKAUptTD024r+A7AKkkXKMgUcINEQ5CQEpGjgCUCL/8538j28EOApCT1i9RwQyBmN93J8XFfs811bbu+325f6rYRDvAdBlu0ebtQ9glPYWe+ZygMIPo9efKx/qdsEVeRRpY3Dr9S399aRtvlX+Mj/wMUD3kpNfNZ3qf/5DDLq37adD15z4OEifVHvZ1xNeFsAap5QjvqTYeIZ32+Rj/pfn6VBjrG3Wk9RjbdezH8Vr3VUMMD+n4vqTZ5kFg3lFCFjjkx9sIQLXuNvLWYwWPmu8+O/kOqflm15mRhp7m83N0gwEIMjIgYvmj4RCbHvoKpzzbXtQtPNgJpUX91f5mzxGuuzpDf8g7xiNOcZ8h0euBypXKqz9139L2NaL7znDQ60HwskWn958Q3/o3144dO3bs2LET6Dt27Nix45vD6oecLJ+N4TqaYiX8atwDidyRKOg43/7+IIiKZMQycr+U/m8MsiYcuBBk2mGACtBIGmHhGqpihYlJuwA9XH06jEQNWn0v24iGv3afBrI7CpS6kDGuPs7Fb5XSbLx9Hs+gf/4ZhRY96fXQd59GotO98qStx5doOf1h4FqRrg3tYs6ozRgGi44dn4M2I0UMsLBR8LmZjmdAJF5de9lH83a/7ucvGutJQt2322fi6gW41fxn/6StK6btziRI+qMKqMdRXLXN7X2pgmt/uMItUz+v+o+uF8hGsbzIHofNyyyMmTX9nLJOs6WoRnk9OOZxmHl0aw+ipqFOg7B7tKKSKAGZQKLkexwXscO2eDSjKbV4k7ipcQY4WTRmhcE1yI08z3mqJHx9P2eASP2TH4/40/ff4frly05b3TXSK4meMyglcCmYT3M1Bz+fTri5vbWyqen3nBLmpPk63Z1wd3eHjzcf8fHDR8zzjDTPKATcWb4POeEFCU5TQinFSAJtyWKkixJbgmT7BCLg2ogA14wWFmRhdQHAXPcp0+Ggmt1EQM6qkX484vb2DofDHZiL+kgvRQ8GFP0tzEqWl7laK0ApYFKC/O6nd0ik6ccarsSIteuMRoRMUCJ7AoMKg5JgIu0PTuSo2X7za06EyWIvSc3Tl5yAeQbjpBrxgGnGR9KowTXPL8V90+VjlrWTvXUE4QBCBuH0iHg+J87t5/+I2CKSnxvPGW8cm8tnbR1aCxc5yZHPXZLVXz7O1esmif6gyNvKV1e3uDwCy4Pm4TnZAl3X/7juy5B/C+ttSOLvOm3udHu0W9TeVbPmSS8k9oCtllxuLrtdVty00DLMWB7/ficAlC2ndb9nr1zQqfpD7pFIDz22Fo1CwqHHP+LDpVYZqDsQ4EWNaDIIu6YhzPD+Ijww/NixY8eOHTu+PewE+o4dO3bs2PFMeIq/r/H7eKGZsKqRHdJ+ZLokKsZoio/2W9gIj21/iOMhgN8Tj6nqnjz3X2ti7F5M1/srjvF9O9KCb6Uk30o5tvE8JVwXVjesji8BRtltE2uOZsCfP3/PHZ/OB0sLEiraTfWJkmHbwtmn454DJVWqvQwzarG7odQqBHahsAlkKWhCNXG0zW/UyPPOT3lLrHseQSb47YT7VRhN6wyImXJ1k+0e1MEsEClATjV8SQnZfLlH7XMSgKWoTpuZQ01G6kbGwH20xwMLkgBKU8hwE7s3+wlS80lugrZzqS5AInAhqHqnxpGSmmnP04TDYQrkeRPIC4zoNqL8+voar7/7Dq9evTLiXUnznJJpwJsWuBO7paCUGXd3d7i5ucGHd+/x29u3VVt+miYcDgeknJBTxt3dHU6nEz7e3OD08SNui/okT2R8BQDOGYcpg48HSCmYRTCLIHEBCkDEVcM6W5Ul0gMIAsEVvsP0g/pmf/eP92C8Vf/gACgRcp5wOB5xOBxwurrCn25vcXt9h7ubO1wf7yphfjI/7a5dT/OMMs+YS8ac9JqIMBdCwYyZEyBcm2Zx4C/kuViAGaiaf8dUQJIwgyBJAFHteibW/sSm7UgEyRlXQjhRQpKElG/DXKJ9sONLPhHU5cDjZ6MMJdMzVCv9ayPRgSfsf+3vp2qfh8a//IboDwotia9GQcbrS+NfaKZXsrOPh8njTyG9ZVrL/KD767vtJObahRig9o2RbD5s5q3b3lssfxzCNwKv5aU/9tTjU5PoowWBhanvIUNje21/a43vbaQ/xBN9jQP6raf7mf6dWv9DjnzfI/W6/45ay+3aMwo7LQJVX/a1GcM62N7VA2GeAxEOB+PsfUuMxe3otLV6DXoAIXxHj+PBiWP79nXrLcQMmHWbbTPt59Hc9ojtyWzntyDk11zzPBKCdgrgHnTrVOTvZfwi/vTjaMeOHTt27PgSsRPoO3bs2LHjm8FZQaV9sG59R9b7GwT15q0ap8C182q4YK6ufZiagCiErffXwrfIuhPfiwz1vMW9IPgHvJEr0r61218OZdLytTqW1fp5LLpqXzsssJL/pbDI/vXT++0I/ookrREorQ174VEUFK09t8QXBNyleKj51f7dHTseip74rONnoW3eQID5FBZTjqHF2JPhZX+n6RX16az5Hl3kamVYPFrz6h48Rti+lZXqsVLEJthmkvPRE2ZH6q7l1NKW4C+zZrCbWKvf2Dr5CzozsyN53sTnzRSrdPdbOPK0pdEoLRf9PLwmjHXhdSfAFzapPQHCABdISkhs4njq68XrOpFq2KeoSiVL4gXQ9U+Yq4a051VYurwBqsGdjMhG0EAvzM3+cdH+77wmQU2056QkuJtpT1nJbSW6SUlyJ9Bfv8aLl6+QclLN+tQOGfi1iKCIgEUwm6a2k+jv378HzDT88eoIZsZ0OECyKAF9mlFOM0opoFIAM4nrLsCnoDndUVOiRIa49iABhSLxof3nTt6C37wGyx0K3iMR4To1n+9zPWCgdQAAlDMSZSWwjUB/kTM+5Aw+nTDnhJIS7sxKgFjZCZY+AVwYwglsfbgM+xZCO/eQ4HsdrccC4E6ADPdP66u+xlHECD7rFEVUyzwp9WMuBAjCThCSWfZA9YXe9hFmKcFcKlBS9wZPOYS5NcPEOd8JHKJWIzcQZBDuoBYFDkhVO91eenymdnwxkK0O8pQ4h337vQQ++jm+Es7eL4de7OuK7yUEOraYgMX+IqSh1+Mqtbx6DKIFk94a1ePHib87fvMsDqo9cSy2Gb3Vzdgm5zZC47dO3GWMO46Wis16Nt/FXtLOzTnx3ecx9pN4qKP2Cz8YaK9QiFR9ibf71R3CPV2g1UdfuniGcS2KLTPu3fVKhcf9t5PqvtZ65uu37ZjRlbwvcxVG1bjVH/MQ7w/tHvfta71wbV+/Y8eOHTt2fEvYCfQdO3bs2PFF4akCgrNv0/J5J7Bc+YY8+7UdzNxCVOBeiWUnIaQR35WCECy0+OLH7WMgTtTcF0cQ0rrweA75ZDlvWHQ9+vVa32rKXltETNPwssKPPs3Xc0hN+BDEOc2UXp/zFMz9bscb7osLkpoxwsdA4/g8UoenpLoqzHnQ+59b0vK50388RgHmQ8ACoKyM7yAnjALt+phUVF11f6hRqKPQ1H/LMBkJnJCMgttAUA7xjHYvLh1nbQzTcB1jGcZtELLGd2KcrnU8ml5fC18hliYtcz/m735o+lUvfhRmBpOfUuc/NOFyzVA/9wJmmtrmx544j3+pLRxETdDbrWFOLkpNij2HUQhMbf7sciYtv5XcNBl4EQaKaq5lVtPfSdnsOibG/jLlrER2VxDpXHnUbioMngtmZhRi9VEeyHcnud13OaUEMgJdRIBS6m+hpqVchfndeIKaar864ng84urqCgfzaU6JcDge8erVKxyurlqBfL8ggkICRtLfhdXU+VyqlvZc9K+IYE4JKSccpwOIoKbcvY4JVn8EpgIRwWRafiVnYJog06Sa8SmhwE2jEzIBlBIkJSWHRcDCyCwoXAABbvCLHjighGwHBcCqMc+nGXenE4QZzAwC9FCBmbYnI//nnHENYBYld8GCAzPAjJITJslIAE5JzaXPRf2jzyJIRcsEZiXSgWqh4Dj0M3gfIkIhbVtv6wQt+8HiYgFOMB/nou4Nqi97ykAqgCQw1HdzgjSNT+sGSRKQVBcT5jJnbf5pxEvbI/k4jc8IUDcHw+HDcVfVpRPmNB8HkxCuIHgJ4ESEj5YjN3MPrK/fT9GSjNqp982In2rlfmi8F2yzV+MdNbTvy8eoCb6V/kKT2dfxSILJSn+gMPeu5MA1z91Xe7RUhSHufm/u5VymRxC17gA9+KLp6wzOCdafJeRP1L0G2jyfjMSuPtvF6cs+xbZTGa8e35NEWMc2nNgPh5s83uz5iu/5XmKMsVkAy/Yt0g7pcH+wWgQppVamgRAdvijDsqfrkpDWabIDjh73qHnuSEKB5PYIyRtcf4ut5TqBek67fAGWpllfSb5PINF9qcflVnJE2yrVKAmMnpjWqKi9a/kSUNsOWZbdaMyItXOGHluswXpQy/c8naZ8fG+dRO8O8nV7T910C7R9fK/ph1U1eEJObYO6LEZbOWi8TW3v0a0ry6roULMe3o8R9DvJrXw9bV3YsWPHjh07vjTsBPqOHTt27Pjy8Ik0Xrpv6MYF2PUDP/TiifL61z78JQgwxT4iRwGoLD8un0ws3lME570I6D7uG3Fyfx20+qPu5prw91JcRJ6PfWJD4HcmkdV+RaCqPXdvjPfV72U5edIbz4XnSPnzE+EPx65Mt9KJhbY7xL1CuyCgDE+i+FRl4y7cjhTCtg2GTyJ2GzTtZVwDFsGamHApQ3yIODK+85iSbY+00b935zfzDPqqkKad1eVV73C426bdIEje0pqL9SswMrvqyPcpifqadoJb4OQJ1cMYDEaSBDYaVwAQM5KF68h8InCBCuwF1US3Z0hIfT7XtcvWYxECwOrBxMhlQtM6d5I3pVQ10IWjaXsGSy+tj77S3az64TDh6uoKL168wPX1NY7HA/KULY1JfZtXjXgA3A4nEIBc9xO+ckuzHiACSgQpqlnPs5poxzyjgIxwn8GFARZMYqS4j1pSrXIi4AglmdW8t/7NFoiIkGEGAoRRCuPO/ZOzYBbW+ksJU844ZGWVyMhwKpqPMs+1u8wf73C6vcXMjIlZyfYy43SacZpn3BU95DCbRvidtU1mQDJAKQEp4cAFTKhwjmgAACAASURBVG1tV9PDRnSRku0TqSDkJISJpR7KoEQgSva/hj/ACEgGZlJCPJLn8HrKWS0QpIJU9IhdCf08jrvmExggkoWFJLH+ErUsF3ulMxqqDzY1LKjm219C2/4jtI7I/s4h+JbW7I5t/NFqamvlqpwnrG/XTUQwXy2CJMMnFtoqSoGIHZ+Nv39PkK9Hi/tL8n5JTrqFCARLET7GenPf9+Ti3kcUiPt44KH7Rl6pxEUpAgktwwTWrfNESOTkv0fMSE6iQ+dQJrLyB+I3rNN+U6QzAgMAtvai8epbG9jwwRqyH/Lah2vVYLtYCduf0F+7JIbDe/e2nbQ0YkOQq76HQ1FuOa0v2/a+b3MsbAyQGt63lCuZly7tM/Hs68OOHTt27PhGsBPoO3bs2LFjhyN8ZT6YZxN0Gh7jCfQabCTPt1icB6AKYzc4nSasRTVt6hrn4nm6R9R07mlC5w72XsS0nvptPcg5dtyDL72eLslfT0/9UfC4EtPw+/LhtiIAtvfX3HGPsrxuKpLmO3MLD50G8hBb0+j2XC6lvo+bYquOGT5dr9tumb4+t+iIe+Zu4Y6UiBVRm9IJ7HpfnzSt8jHO82k+paYiYeL/x1Z1/6lJzBrCQDyiamorWev5IYFpn4uZAU7I0sraZYA8vAvCg0ZyykhZSVYA6h8bgiQJIhlZ1KQ7C6tJciduAaAS6AdcX1/jxYsXePHiBXJWs+7OCJzmGSizarpH7XWosXAnV8jIhuyHDuz+YTpgxgxmRhHBx9MdigimSf2Kn04nlLmAmHEEcP3jd7j7n19wZ/V1LcBLVhPpXp8Zatrd01WNeEZiQWFGYcbJtN/vSgHPc+1vU1Y/7GRm7AuUrJ1Lwc3trZqTn2ecbu9we6Oa6R+Zwaza9aei/zMXgAW3XMDMOBiBXUlq8jamyqJwSqaBSZZ/YDJyvIggW+cgZCA16wbJImwjX0l7J87rwRIxU/J2wKL2XdZDH95x41jyQ5VA66OrYyBomf9emAF8gB6UuILu7T7aswmodf05sE0RPTwePCGu8b2xdbb4uuUdCf9enq810q97fk938fcjQb2Wfh414C/shsv8kcXX3/e/TGarhD20EoSjvZyRHPfDWPFaf69/0VzAYT4I3f6KnOCmutZ4ACfAW7hx/2Lh+oVMtbaFFuN/a8bY7Bc2ibkP9GAbZrFH3EIce2s2dRYJrmxr1j5RYx6itj3QXIMws59Nb/fJwoWMJat/EYYf8iLArCaFavTsyXqby/jDwrP4Gut74cawf7IZOhy+H0HDAcaFhYhxw77RwG38bOUBtcxb0ew0+Y4dO3bs+NaxE+g7duzYseOPga2vu3q/+VFrz+In5SD52YiT7Eu7EwQEIXTUSPc0aiqPlgwGcmTIW4q3VrTOq6DpiV+/29TOILgYnz+DYDgKdZb31u+vXo9EzBo2wvzRCN0/Wnl3KDoSfbwZf17QQbZp40+DTkFb7wBuQhZRi83psog4ozwm1/recp60+yO7r1LflpuV+uze6d5fBo7uK/qmcw1Y9JO0VZTw1hy9XQcutF5fH8e5eT3Xvja1fzU/LOp9W00LM0iSHc5wMrLF4e5IKlmE5hsdSbW4Y6oU6nokRpJpJav/8t6EO7GZv8/tGBmbZD4lQjKtdUqafk4Zx8OxEujX19eNqCcl30+nO7AIpjyBspK6zbQr3P66Ee8TKCsx7RruecpgETAzuMy4E4EUQZlVEz3NM6bC9UBdQsLx73/GgQve/fwOJwB3LJjMFzkzd1rcbjuCjTxnMzWsWtrqZ/3u9k6JdGYcpglXxyOujkccp6P5myfMzLgtBeX2Fre3t7i9PeHu5k7TM/K8lIJb81Gfq9Y3KrHAfo+5azPXeERSqwBVMzQliJFd6hRBrN+Y2X5oPUrSHjpDte9L0Axt5o8tfREQJUyp7apEEljUkoAY0UO+/0NP4JydUVzzcG0cbpnPeCJmKFF+sLxdAbi1Z6Mm+o4dT4KY5vEDX+tJ9P5bjboQ/RtP33fEQzXtQFElz6kR5YATrtvkeURv/tvf6Yf56jRwYc597+aH5cY1eBXhE3jli7gFGSOS4UAAobaT7g96X/I6pY9HJB7TUu3bGoE4jwTwIm/3oB3L8Ly1nZzP42v1cn+869eLqhz2KmupdE/j1jBu2Md9+n0Z8nfshahUfz43O3bs2LFjx7eHnUDfsWPHjh3fFM59Ey8+VmX5rA8zfGYO5LmMQZU57+JZflgGQh2DUPSRWuid8GiLOA/m3xotsZnJSx4BlmoCLfPekfUhH12Q5/vsXpIxTUCExbP7f69C+vji/186tgQ1zxPb49//GuruKXguM/efvp9dHvs4ZppWJcZp6JE5aSmkcG9yx6I1hctToZAxquxulKj25lFpdWboRKYXpx0jpsXtRg/XAJXFlSCYbmkSXDi/lodlj6vkuR8WCFZPqiH9sJ5FMl2UQe/iXy2iZ3lM2/7x7BKhKkRt/R2bRqlyN9ouYDS/0mRmwlMI69XKwpZmJC0ECQkw7fVBIT/UYCRBqJLoVQs9p14DXTL+f/betEtyXMcSvCAlM4/MfPWWqequ7plzZv7/j5r5MGe6u5a35hLuZiIwHwCQICWZmy+RsaRupoeZSRR3ccElgFTnWNNwXwgpZUzzZG2W6vPzSTXQ/Y+5VPPrBYzrdUFhhszAhAlwEt0aiCghp4RECWWeMM0zpilXE/M5ZSykftDLwigokFxQUgZzARfGJIITO2FT8PTnH3GBgFLCjH9ClhNS+R6lqJ/yib8H4YpsdaLm6oEJgouRMqosqUT9cr1iuVywXBdwzqCHBWBBekhItW4BFMbTsuCXp0c8PV7x+PhUifOlqPl5Ye2Hj8YmZSjBO1n/LkZiL9zcEbh5XfViLtUce0oEoYQSNBRJgBkEt22xEAHVhHvzd+4WhCBsfbER6NovTLQiAqEEpoRCqR5YNIoMzV1Ac2Rxa0QZfZuPeA15cw/cpPsMNet+QU+eTyHMr4H3mgPfcy59Kxmr/27HEofE98Te7Lk5fofre/fH5/fyu5um6Bi+58XcfbWjmvX2uauR6MOuJtCc7bqsavqeN2c9/9VcBIsc8TcQxrf4dCDaW3Gknh7wPWl0c+IHpwDVxKYNZ/bS5WujdINJAjICuZW+Edm34P2m5VP/mPo1qq8Fa7JCNk9rqHDUqS0S2pOoh+ekz5nXqbs38UNsHirZIsTn5pZvn+vD5ACYL/t7YLnw7TvcbYveTepHRuuGbvemUPLN36v8hLmjHcqwkHVt59WoCxqS0OdptNe0V7q3YSuNg1g/cODAgQPfEg4C/cCBAwcOfDO4h2Sq92X47c/XI9YSgzVsaHnX61Gr3AWtN37H6Fyz6aWoQiKXCwiqKfle41w/XXDx3hvb5/xhSihzl6EWwevShZa/b0caPmPYtZDopSnvhX9Poex74wbt9e6xHvhtoesFQeJfhahA59/3rrEnDMPv3cvimBuuhuu9Rtv2vHJnrmgUTDcyWwWiMWz7sRrPIouyo3leNb/Rj3GNJA+EQzX92ZN3SqYGcXac1zz/K/Ozbbyl/kaYE9G0/+NniHbzerithLkggVE4IZEgkROSAElIf48hUul6FbI3ze+1f1ktemujSJYQVKNcta6NXBeCiOaLKCFlYJomzNPU6tQJ4JwxTROmaaoah6UUsDCWZalazkgAJVQNdvUpjpr/lBNSzphyRs6TaruTaj37IboENT3OLEpdsLbVYtmZrTyghEzeToKl/AOX6xMerv8Ncj2jLAsm/g5c1Kc5cwHkZywwTXsQJpmAXFBy0uvMkOuiZLgAk6UjOQPmZzznjCllTHnCNRUkSiBiI9YE11JUg14EKREmsTq0eqsa4Uay+5hRYKS+SGjjZt49eX1au7DaKADbfULr6pXIEdjBATUp7Jr3gKj595SQJatmfG7rvkStPznxDpFqEth9qRtt1L3uexgJOn7HA4kjIkk+aqD/miT6zvDwWXFPW70FXzIJNQ7hL4LP7RSG/3Fb4ERzIDol3GvHTzxsH7LN4M85qbqFYb6zObKbD6j/reG2n9/rwePeqSPi7ZGUEpjL7nZpn5T1egRGff1xD7yL0ABjXVZiPfz2tq3XRPpWWLW1/juacQesLrcODd4YEAhqcn1Le5/CgYJ7xpSoAB7Xg5t9KqTZ+uo+7tpPxgNU4TCgf9c5r180B3EDhDcW0qvFWp/hMbiE+42wH6Ia11A7ZTtw4MCBAwe+RhwE+oEDBw4cOOB4AYkbyfDNz3q7EeXN7Ce6a/79lmm/7Uy0L0qc+2a6Jz2UfHiZAOklYffy3U7ph3KPQhT0ZM9bsUeOb2XxSxPEfj3YphR/3Ri+bLxnn35d+p8mzq14o5BQiUxsyeMqWeXhmtA1NWFf1bUZtcl6jaK3YRTCjlLALWyKE29fI6V2E8EoXv1ba48HaeUg1KR6zUjfnZ713NxRSXQ4USHdQYFImI+HodakRpOixj7RxtqWl9ceCvPPjrq3zqWyYAYbgZJCnyFQPaxRNf2iprF9T0jBLLuSvyMB0g5VbBAbN6rbzagDwGREOXM/98cwEMGyLFiuVxQokQ5AtdxTBlVi3AmVphldzcunrER6SgCpht7CbHVISITq21tVPakR6kR4+stPSk5bnyjCkMJIy4JyKZj+kDH/04SH351xmmcwAxMzHv8M9fNNhJQewZTAUlCuE55yxkKq/Y3CKHJBSQnXnHGaZ5zs8ECaJuTzCZkZMwMTC64p4UqEJAISRi6MRRiZ1Py6H3hgNusEon7Q3Wx91Nh2bfUM1ZT037Ut4T7Pmy2DeBildgFbr7ExSGqandtBC9E6ZutDmRKQMmgiFDfz7+tAI/zZSPgi3EzB1zSVIInv7Kqv2edLzV+/Bk6SnzfuuUBp2fn9nvgSSfRPhb1yvjcxNRJ99xB/Y7gXHSTYa0QjNjkEEkAPJ+3kqCeD+zmt11+O9PHbMJLnwPg7hr0Rj7Q90l46XRys+7zq09vDjc+tfuuVFEovG/efw+76T8L3zfj9mo6dKeREAJSu+IKxJxUba72XkQUbzrtXZtdGaRBlANJ8qcu647WecRt9E7V8CPRwGkTXevEIx2sPhvfprterdY0WL6Nd7+3Ta513hwCimnwIOjzVoXu/JZDoBw4cOHDgwG8EB4F+4MCBAwe+Pdza1YV7q61tlVT2YXzTj0goxFPy9rsKPRHI8U7bvP3uyPM3igSb1nlf8CiG+FQbXRVkyIsFBfcK6O7LA3VxVWFQ/7FO7bk8r4ijHZ7rK8aLD20AoV7e0Gdf/eSBz4JbHPMgi6sC1fd5uT8BqNNAioP++D7EX8+/KusATXu5v9/7Lw/E6l5+9yIe49oI26a1gUS/mWZ4uIu9/7bWPm//RrnvKPBeke5j/GK/hsxVkXuI231zuwngmqOUOmI8B2Izmflz9RueTOs5aCjDBde0EmDXA2qs5Cczqx9wDr6x9yZcEdMyL1iWBZfLBaUUXC4XXK6XqoWcp4w0TZjPM6ZpQqKs1A8zRBhLAbgwlrJguVxxvV5wXa5YzOe4iJpidw33FMoNVpI5l4KPRbBA/cGfhDCTkhmMn0DlB5TrE/j7Ky6XJyzle3z86RcspxOe/noB6COIvgPSI4gSQFm17nnCaZ7x3XyGnAp4WdT3OqCm3Z+e1Cz7NIMLAyyYKOE8T5ByQimCTAmZCBdrkyUVTMxVk7yubUjrkwuABFygvxH6n5PlRQQQwpUESdSEekc61MMTwzskYaW2IjPQ2tr6BQFKnmftviklTJLrOtK11jXfelghMWORApKmnd6n7VlsliTiNZL3oAXvwyV8X9CqYEIvWPqUc/znJtG/VeLoreV6jkQfCfq9RG/Fsyb5nUxsZHmc67apwJ2E78B6zUyb19ZY78Zukee3035Z7yfS+mCbm4S6ZcddeM2y362BJPTrkL7M0j+wuYIJabvt+c0o+ued5u73xzr2j1riz62Hat4DQe5nIeMKrq21UAfHt5LN6y7ifT1mMKxVOia8o/Tt6X7929bDwy56qKPuzQnrua76Dxw4cODAgW8UB4F+4MCBAwd+M9jyeR5/k0sWPGzkyGUwwe5CzirnDN+DgGAky0fEU/gvEokYaZ4ieR8EqYw+zb24nxNS7eGmGGdDy3zv+nsLQncJmTfGN8b5tRDAX1o+v7T8vDe+XM3zW/l6Ps/pRijXOPc32z0u6hjUtI2KaQUBLohsn6/Fy8sbzaYHYSO5MHAcM10M3+fy3Vq5Sin3hPz9tdW8dYPwvyfpTcHoszmperodjb5l/WM1fsq6yJW/jMz+3sAb0AnhyQTl8D5nGtc5m2YxkCpxTvZdNdAzmXn0QJ57/C5Ybv6vxTS3iwqsWVBYSWvmAmYjRquZ76ZhWH8XNdN+eXoCoATr5elRTbdDyfMPHx4wn8/I84yck6VVsDAr6SylrjmulwueHh9xebrger2iFCWap5xB04ScEqaUkCgjJQKXAiqM6+UCKhrPSQTZfKWSAJMICn7EFQmXyxUff/oZSRJ+/6ff4y//898wn0+QnJHzT8jImBIgRDgR4Zx+j+/++5/w/eUK/D//gaUwMl1Uy74UfHx8wikv4GlRTVNbOk15wnkGZv4eP6e/hbYC8rKgFNV0j/22cEFiUmsEIjjBtAENV2uz2i+YgZTAYCQGJCel29yqQOwDlSXw/rDudzEvIgKwWDSkPurRovKe5VryzIxCBUUYS2Fzq65m6Nmd7VYrApaWW46wPFQNVXx+RO3zDOBpI8xo/v3A6/DS9fz4XCQN7xvz++fGIfm9KGoKmrNOfr7oefi7oiS6E7cveR53PhO1zUdt9Fu52xpHngU3ErazjvHCTaPaa2E9QPRGUvcuEPysma6xbDjl0PN8bHMXFD0v3h8vb640nEDWQtR2FgDgqnHuEbKYRrr5TC82d9Zwbu1DbhxnJ6pygbavRx3va37tHkOQ4wRg4d6jzlvXCfNAOMjeW7qTJvwYOoweALBSfAmTyIEDBw4cOPAF4yDQDxw4cODAt4MbBHnkSiJGLqVu6n03HjTGnQBumuT9c9FMeb0qGJ4ZiZhgUvAlmgjFHzFNC4KZA2zE1EvxEm3kMeRe2V8az1vgZulWfEvU1nwFxfmtyhVepX0ObPN9B75ZRCJ0S2upajMNAtmBj67Xnus6e/dH4f1LMShq15ioFlBWo0MliKm/8toXoNc8377eE8y9JlB8iIZxbTfNIcy9r29vzny4Psb50rFkT0rdZMBKGGzE62J2MtK0Co1DlEKmgU5mpn3Qwq7frYyugW6FMrX21vOjWXsRJTsFqESoa6GL+8a2a8uyIE+5CtvdXPeyXPH4+IilFKSUUJarEts5IU0JOU+Y5xlpyqCkBxaurCTDUgrKsoCXUjXQnx4f8fjxEZeLarHPp1k17HNCpozs/r6JUK4LChZw0qMFWVh9pCZBQgIngNHI31IuuDzOmKaPeHr8gH/6L/+Mv//7f2j+iDClhFmAydZMGQnnB/WZnuYLPpxOeGIGl6La9tcFTN/jmgSCj0aSKXG8XAsu15+xLFcsy4JrKViWAi5an6u+4PVe/wS0QcR4s4qR0kgJ1cWMrfOUQ6CODFHCoZEUkcBOpMR9ItNo9PjhYyapCXcj1vxdUQK9oBQleqjoYQwumh6Jmq1nZnBKSMx6GCmkPb5vX9J0vEAJrTOa9v+CJnSa8T4+03eJrl8Bv/Ul0Fvn4hGxPscZdq+u1+F6jfNozr3FI5+k7bbeyVthR6wOwkX+d9havXrdDt0j1kMG9562GPAy0t7JcawPMzTGux6tHNuntej2QaG4x9uzwnEru9LVR9i7bsXRHdij+juOQwSfMtSlR1QIT+g47hdhq2Trw34UO0l/b9RM15MYz+fnuRd9nVz32IEDBw4cOPAt4SDQDxw4cODAAUM82a7kOQJR3shz93eGEH7ld9xvB/J8Dy8hdYm7yM1npgleiaoA4r1xe48tKxPyUcviufJ/CmwJBT63dvCXhTfWxWCT8Gut2bfn+/OU/PlU35avFde88Tv5N+OZkqSq1SThepXBSeWEdyHD537+5EaoeC+S5PEoQNNEH8nx/nccNfrv6+MCG6cFsDPu7NRBR5bT8DuG25F67rXVSJ43zdVtQt6RQJ3APMbzFkH+XSAEjS3pqjeS6CMEJsSmBMoZGdF0+0Cio/cnXpEE4KalXuMW97Gtvr8rgS5c/ZwLBKWoxnTOGXRp8YgAUhjXpwsep0ekywUpJTAX1RrHjBmENGXkeUJK9pYZMS+s5Pvl6YLL5QmXR/28Pl1wvVxwvVyRiPDw8AHTlJHzhAxrRxEjmJUsyEQqCBDBh//tB+DvCfOfTsj/UBIcEFyxIEnGfD6Bcsbj40cwF3z/hz+A/wac0wlL+mj+uxmzvfCXXx5R/rzgu/n3oHJGWp4gl1/Ay0fwZUH+ZwIl4Jf/USBEEPwMEsGyMC7Xgms5oZSMy5WxXCewJLD5hmf5uZ5xYCMHzn/8ATOAj//fz6pdiP6gRwaw1MORAjLtczFNzPr2br1AZu63kRSAmElkP2ZQLQmx1Hj8cEa0cFD7UEkoKFi8BzOZ3+eCIgJi0oGoFPWpLqYlP2igx2x+SaTuZee6E+mf0kf6r4WRwP0S8NyIvD6C0j83zr9bZHb8vYfX1wmtfgn2+7b3ey9XJGn1OafN+/j205Xu14hb5Wok+vNHO6IFiZRsnbF1WKySsT52YfP9303HPtfrOXflIpvhX4PdZ30dI3Gva2OhrdX62t9aV/WWODyUa623Nan+atdbPSOET6mv61Hz/Ln3wSLd2P+3GEQ36F3/zLGD3qmNfu/Wee8Qh2Yt1JP/E9hzb5+wpH83fEnz0oEDBw4cOPAWHAT6gQMHDhz4pvB6kb7Y/4EYdx7GyXMeNMm7zXN7thJFVejfhP9xgx6pbvJwe+USi3fQrqom7QhIO5pXz5T6zUSIxHrrrq+v0SCaeCup7UROrVcKfaAzb0r1XpemSF9hAyl8K3fx/iemkt4dBBM2vSbjlQjt6cQXRfErH6g48HZsvQ+3BNt1SPsiXo61gDoqHDcJYhwPafhD+BxFufFel2yIU1bBdhTSuzGMXAIt64d6Ahzb16Uf4+nOOAAAprl8c1wM1dBNY9ILZusz4TdZ/rr7MV9Bu1y/PDNudJHYXE1DGqYRXP2jD+bbCU7ASyU4KGioV//Vbr69MBhStc9jNlnMb3nKlbQnIixlwePjY81PzuqvfJpnEBGY1Uc61foXgBmuLV1YNbMvyxXXq5pGFwFSzjhNM757eEBKqlkvzJCipt9L8JE+EWFJhBMmTNOM6b9MmE8z6MOEkh9RwDgx8PBwxul8ArESAsu14HQifP9/fIeH7x6Q0x/wy398BMmjak7L38F/LiD5AfkPM9L/uGL+04zzDyf8/H//qET//3vBL/I3TPIBIr/YGopRlgdcFoDLBYUZl/JX9RfPbObMP8D1lxlqrj3boQZAcP7j73EWwS9//hs4dOYC1ZBfwqELPxgZO03ruhI+u86jfYSS9e/WH+v60Lui+PokvjO28iO3CKBxpQRk02SHcPciCtBpjjqJ3vX0r2A+XYbPb0UIdRBE74A7KnA9uzYStpse0Wui+5X3aqP+XVP/0Y3Y9ld3a33Q5oVo8p3sQBeF8cWh84qOu+5SxNN6CcYR7tbTMn55Jqlu+7Qqewvgh8lJGvG8pqg9QRn+1nVJIeR7v4N7y9aaG9kL0TDudW3q1kMeBBBLPbzXUe9DgfZS8are6Dartutdf7jPc+raZrVGDFHtrXSfq/NP1T4HDhw4cODA58C3snc5cODAgQMH3oRGeLfNrpPn7rsU7EIAM3mKGFwF3E4i3CPeWIXZ2GGSQO3fhSxpuvGaIAnUbO09hR2T3RDI3hvPc4LbvfvvpQ2+R2/192n3/kieb5JYd+Tha8OKBHvh001I+XViW1T05eJWH1+HfO3dbVQf0kKr9w3ox6WttG7d276+jpEgtce9qsVoLXSuZRkLNBLoEp+I32Xj+xAkRjdGsXWZ+qtNOEo1o1tR7MnTnaTbC9hMsPfPuel09xFKNhduC5V7obb0N9sntTA+1tb630HvM7QnJ288pfkw8ppNA1gPm4W2DZrnrkncH6ogIzZcg9x6p1mhcfK8cDFSPWSqEul6PQPIKSFn9UO+LAWFH+vcO89TsIhAKKXger3WAwxKqnM77yXmS/16RSkLhM3v+TThfD7hw3cfqoWI6+WKa7kY6b5AuCCLkcopg0mw/O0XfP+//zNOpxMEBR9OvwNzwRMX8OMFD//6gF/+8RNOU8Y8E67//oT0gTD994z0kDDThEUERQQLs/39Fdf/fMJSHvH3//kTfv7pJ/z9+ojL8oTz8gFXvuAXftI2YgZKwVJ+wuOiZtkZjKkwPjIjM2OS71RLXWYU/IIzvscC1Ti//M//BCC4sqj1fdPcJwCFCNk18J6ZtCT05lW/rl2H6poixldQIEUQ39LKJ0VWSmCHWlBdCyQhZMoQMl1Fbv1HiCApqb/629m/e905zidb88vtMfp9Zs4Z5i3hzvBf4prjS8zTHvbm5PH31jp6L56tteRr6+R+om27x+yvNSjk9VYKt6nBcSrvym7seU+i30iJADI3G2sSXYny5BZPkls/40qij/kaDw2M+b1Vlj2u/CXtqMZH+icErS6oWksDcqBW/Zvnf33UYVxr9TnryuGa5KZh7nMyexrUwgGAK6LTEH/zvd7XSHOQpnnyOZvrfM/t2cBRk1sqsfkpJ2oH+1CXIt000a2XNt6M9Ts55rWPrDfzTu8zgB84cODAgQO/IRwE+oEDBw4ceDe8VZD01v3clsxiN849AUQU+Jvmue/uq6/MulkOAoOqlX5bCNT5WY3Z2dLWDuT5mO0tIe/nQq2XFUIh32rud79C4cqdFK556j153vLQiWGkv/ac8PBT4FOlcTve16b6tuMPMZRi7wAAIABJREFULhv6/D33FfgMmX5pXb8pi0Fwt4pso9HErwOduXa/99K8NLHqMB7TGNs4Eq5y1cdLHaXVOOkhjIpGB6caJhTfz/Tu4LQ7qKw1yIbDAUHzeivk/hs43KF2xXOZQr46AmDQSicEM/0EIw7RjfXqQ7QJnWMZXtT2GwVV7SwVPXMI9lzETkKIMAoTkpGSlPQQiJtZFw/cqQgHzWC7mJIR6Qh6jNIs0qjZbpv/rQwpERLM9zgBKWXknDHlXE22l0VJeE31DJ7nWqfL5armyZP6cp9S1ngJSCkhp4yUqX2f9PucMx5OZ5zPDxBWn+MiDLlewZcrluuTagBa2acpIYHwT//yB5zOZ5wfzjhP32N+WLBwwYkLloXx/Xff4Tw/gK8fMeWENCfkOYN/ZPBHxnf/9TuIPODv//YfuIKwCLAUxs9LweVyxfXpguVyRb4sKEvBz+UfrR4FKIVRCgMsOBHwlFTD+/f/+i/4frnq/J4IP/+vj5hEAElg/IIMgoj1EREARcNaWyo5K+BIm1U1UO8sdPN9q/0KBCFp74TFUV9x7uOB54kYxKl2NV83BiNGei/pQQ62bkRGePh74GNYtTq0Awl/MS9e5PF3fc4Indt1EO7FdZO88H0PyEDQXG2fUWvYa/VVY8snxle7lvmMGPdqt/rceH8dtt3p+8t6Xor3O7LyVka3XhhpMVMYBKKbh7Gz1mh8z0IEyglI5lIkpc4Sih6YYhvrbAQjNU++tZ26Z62veyXp8vNufdfG3VV8EpdIrQXaLLy3rtvKYd/C8Z4O+dT5Mu9cwGC9rqxrzW7/OGR+qNn4jCVZofONpjLmtCudtbNQ840uCPW32ZixV493qPtcoSso9XOg0DrSvX3ACzcjW6054i17yQMHDhw4cODXxEGgHzhw4MCBbwLbm8oXhBcVWDbLckEoXs25m8DcwkXiWJjNH7nG/tZNIZVeyAGJoobnafPn7o+8TicYfSlEwEOKdPPba3F/DFqe7Vw0AXCj6l6Tt6YT+9LcrUO/rW72hEq3ftPO/T1xOw3/0sbd+39vx/787/H7S/EevfHXFPg8n9Y9YtP2/da4kGrrevs2atS9QPciaTSNnkFw2oTF2Loavo85Gn+7puco5OvFlD2JuzKeaVr0vUZ3JWiIWvmGwzceyb4AcL9GXyaY3mnHcHlPhvkS+X9CPze18b8fIcce0KVXK3fbH/NuAV4Bfzq6Dt0rsJMS/hSzAFSAlABWTWQ1m2oWW5KWhQlKrtdeov3Aza2r+XYYSTuQ6K5xNrChybXWUwaBMKWEecqmgZ5QloLlesVlWUAETFMGF4abar9erqCygLJqrdM0I2fVk89JTb4rIU9IkiGYME8Z52nG+XTG6TSjXE1rnRmP1yseL0/gy5OS+SkDBNCUkSlj+fEJf/yv/wL6m+DhD8DDh39CkQIpBZfrgsd//xsKW17nM3BOmE5XnOaEOX8P/guj8IIz/gmzCJ7kI574EWn5Ccvlih8vF1wvT1iuC9LCWGqbhneMGRmEmX6P3/3rGdM84+mXj0g/ZixcUPiKNCcIXzBLrr5dBcBEhPOffoe//dtf1NQ9kWrYAyhQCh2wvuqk9FZv22HyIk3jln66sUIASWqtaOyf3g8Tkh7gGPqLj0FKngkSmW930sMTaroe1Qd6R4AM+XtuNN0pXrtPeFZL/73mP4JaQUiI45COtF4zY1q9x/n3wuejcN63HPfDR8kyXAPaXNfP9f2cSuHv1uoyrpG1D6suMDVzDu0e+pYd496b/7Z4vvZMy9VqzyNhLlvhRp/YaDSy6+Tvz63Fls9T9XBVAuVGoCckI+LVqBmEQUxgqOltinPQS/J9X1E2Y7unn2odxHWaH0aM6zC9rU5PuMbdr0m8J0g9OHcv6lpkGB/d53mxftAO2TXmfHtsbG9BXBNybAEBclh3+OEo7xM6vjc3A+qlg+v8wSB7HurCg/ruEy3ev6R1KfzbFbCZSGhh7d7W2vK5fcNzuEWeHzhw4MCBA18TDgL9wIEDBw68GR0tQuvN0j2bvip0WNnTvS0widfiFraaRnOiG/YZd73DT3OKaZvVRpQ37XL/8+f7zXokG/bqoBd8bJSz5qOH1L9PsxV9qQ/NztDpSjvUxFVbWvWdRMYlF/t1MopWWhv7s6nXHgBMKtbEgJ6U+62Lgjiq/22JAUexYZ+f8c6+SGu7TCsBx8aT21e6N24j3PO/W1/bSiGKQGN6tAr68pT7co8CUrrx+7MiCLB+zbxspXXPm7oV5u43PJZ1JXV2UXQjf/re2F+PLi6i24l49KQK20N/4pAgQTVv998iufHbMxaEhmKmO90UM1kq9aUYniYEjeR9bAkfYYJaiuMdxdxuiKjD/bF+owWT6kd5yEMlwHomZPUuJSjRG8nizjw1EaYpg3KG+/0Wbp91noTYdSWUlbT1TmSjrOe3Iy+HRq35NgF0ks7wAGF7cdHG8P79JPNdXrWCRaCGwROYtA9IIqScQDm3eoCa1CZB1T5PREggFBEwF0AETEpqQEJrGuEOCISBnAmTxQ0BlusVuALXZVFz6tZAy6I+0fF34PHxEdM8YZonzOcZ8zwjnwVJJiAlZACneQYBmHLCcl2wLAXCBUtZwE+M6/WCsixK0l/UTHpOBJkzAKsT04Q8n8+YTmfMpwse/q9/xsPjB9C5gKDtmM+CMzMgrBpzacKUM/KUwQCu/CMI3wECFFlwXRZcL1csTwXl6YrL5YrlWvC4MGRZIEsBseAJ7EsuFFaK4grCRIKP//5n/O6//Svm0wmcL0D6CRDBLIIsp2rOWH3qCs5//B0AwcM04dEIdO8uGUC2dWA0s+8EdfI1ZyLk5BSP5sdJethnb4WorQ91nekm9oMv9NBfmcxYeT0Maf9ZPpVSMtIokucpVb+5iQiFC0iokvUeR/c+CYyklC4P8VUTO/CpFh5Ix8RhORGHxPp+bQx09x4ZFQCZlLjNnpyg+niPlTauKDUPMmbxnfB+MbYZ6D58mhX9NsbVbXcwCX3e61xM2pfis1tm0F+yhkvYxngoVeDrjfjbI/T5vB0upu5zvS9r7gIGv+n+utLwG+Ed0Fe3s0Dh81qCj6djL+6/tPdU332dT4CMBCAhUQaSzjsZCZLUfQOLmEURxnJdapkZbqSs1YBbyqipCoJp8XbUuX1uTqrtgBBRjV0kHkmQMPc1dHtJC8+wMZIISH44PWQw1Fq3Xw953VpxiuihgnCqr9YCgNbRfI/u1juS5gpi5t1ruQSycUBBzOeGWgFY932xNSLE1gAs1bAN+xtD/fuwW/+1KeN6Wcu00VJWvL7O2uFP6QdtX2R7nyE012/BggqI2rvQPe/r2rCojJaLNg+mYd1JYll3sT133TtS/5rj6oEDBw4c+G3gINAPHDhw4MC7oZLnww7n2Y2M7RApCHXjgyuCYOt56F452SZWr/um2YWgbdMetcj0Y/x0AUELFzXPt0667+0dQxZvX5W2YYy+2gToBCLx8Q1Z5qvxMhK9CX93pCguUbidN4l3aOPfvvWjdmR85o7shi8mXiPvM2MPa0HXOpjrHlhFOruC5SBg2ChJj/3fGroXfzXRVgx77+/PCOo+Vt/v+f2K5N6E2FrvLcC/Jz5v8fvCoRJI8UYz9ahIphO0LtfWsQ+q0uQqbvRDR6vU+9wKpAovo7wzyOXsEJVecHIlumNIMUMShf3D+0XrvCfNbL1X379KGo/5738r0X677sf7PibEcTXMFrfbM5iCZhuyUjD9Gk1Pd/3Sx9NBiN3GU/2eTEs6uwlwcqI4KXEHgBLhdD5jmiYshVFETYJzYbAR5bC5lYVBhVFKAQhg02103+GV7B9+a26bZRfPukBArMLq1QgaqqwJ+fVes6KAVp76vM7f1UupE6g5I01ZyVMi9c/KQGJBpoQ8ZWRr/ySMUgBhQUkFibmmqM2SkLJqmAsYidTPeKYEsGDhBYUZSymqhZbUPzsvCx75Iy5PT5imCQ8f1Jy6lAfQB8GUMhIIOZvP9GnCNGWcH2Zcn664PF3w+PgRj5eP4KL1yGVBWRZIUVo25YQ5z3bYAZgS4ZQTpocTTh8+gC8PWDLjd//n73D9y09I+B4L/YyMhEKpvqtkXYqlmE9XhuAnM0W74Lo84nJ5xNPTR8jlhHxdMC9/x6UwLoXxtLhp+YI2qxEICROAjAkT/R6P//YzhH4GEuGE3EYWUeJJmFHsMMfTP35RQnmaMIuS0BMBS+gj7Z0a3kfrd5QINKnFACfmtW/rS1itD5m1IfY1JUstQST1Wt9uia3WWPYuM1Qrs8R1FUE1UwEjz5WEJ2getN5C/DSM5L42C6jvWSt8JeBWq5GwXPB7cZ6oh1R3xrA4D8Xf0ef5BOVt0jBGUvdEbLPXWQu6D6+PeW+ldQutnJ9hRRbe5X6VPuZdSfY2T1v9S3vq1houwd8D+y2Nsk/dnbHFW0vHFYV40kNZJNxHCM9AmP8IyUZ/dwsybqtWvy0iH/Pq1Gvvl5PnelALqG4WPA/VIoVbu7H8kr7vEAIVgYgS6FM2KzGkh3k8fRZARA9LoTCY45wZS08AJR8ZdMzxw21G5UoYB71cXZm9HOFAgFd5pxHuw4j0bdwF8TWfp0jc5AQidaytY4OYVvoqMqllkkpJ22GB8CKtxlfu+wWFtOtHHA5jPYxZ8Ha3FqbUj2kx/pyTrf2AbPOV3ic7yNdVEorNN955UrUyomsmSdtHTjaqaf0mSf/+AqgHzGomYyEpvGPJD1miv+5jfzhk0UXh12M2xgr192mzZH07hajvxjiuHThw4MCBA2/FQaAfOHDgwIFPgpcIkjx8FCi9KBFPq5Oi1N39xm483AufVYDvYTbI8z6a8NwrQYAJZ9cCtSaC/fKxqcUQSrQtYGyCrXvQQnZ0ykao8c7WdzJhQxAkbMazn5IMn1t4ru36enmerG+h+/rdjvVT/T7wOfFcn4q9ItXP3Ma1V6bY+nt42ylqIq/z+GxqlYTpZPL12loCJ2/qjt0bFchzoqYl7aHIpdeRdOqyTRvX1ti8HoSaLWfbD1FquR7bUDVf26jYjbjUyuum24nUXGgiJZenZCbCKamJcMpmSlbrZ0p6LyWBcNKDXEkATkBC1TRPUNPWifRTKNX5tOsbJjlWja5tAqmS7URrTcBQXVUj3cbvZgraBP8She1oEtxixEdKICbVrmS9l4hQkJBEwGbunRalGghQjcFSsCxLPUwg3LT6nJhpB/RgXUj7kPexKSVwIqSk9Z1yQq6EhabB1wXXfNHDDUIAM3iekKeMlGFm4ifgZG1MMPPwC8p1ARcCp6T5Y39rtVwsACVgzhnzwxnzw4w8T8hzxt/+82/4w7/8EcKC6S/f21M/4/SnH/DLn/8BYS8PI/MDrvKzETyqJfn0dMFyvWJZFlyWRyzlI8CMJMCEH8C4AvQjWFKtowxBAfDDv/wz5tOMX/7XL2D8VJdysd/XtKyui5NWQigkKNKbpu7agvq+JtbfWke0WqprPiPMOXw38lxMA17PebjGoXTLT6CNj55gN1IKUKhpnwtESXRLg1ltJrj2ezU5vDH9jzxIx5OH611djMNpeG53ZRHHpp2wdYUyjumk70hB00LvLGb4c8O6XaO5e1Z5Ad53bbNVD18itsbdz5F+rK+4qgU2u3gNKOPDW5B1/C/G1taRWv5WGRzXL/B3QDWl/cBL69p2WKaONzaf6HAPPVZESBCIkeqSEwoBwgXKN/f7R603qu9fygQSs7wyZnOzgm1dNGgWu5b2inAPn10b+vtc22t80aUjzz0S5Y3H/Xabv9po4KVcYxh2ujuJnttVt9lme9e33/G2yt8Rx3Wv2Q/WJGKktoTtaKh/Wy9KePJFI9cwBo9z6uZirDb2kGLs+LEjxdOw1l9fkK2Wv2efOnDgwIEDBz4PDgL9wIEDBw68L7YElHc842HfnHzYuY6m5Ppd7cZnEG5GDfNInlch5h55/kwhBhmnCbab4MNNjAqe2+S/Dp9yc7otqN0RctRLgqpudQN7ZtDX3zuxw+bvG5l5Me4R5EXxw+1yjL9v1UsU1bxfq65j2o/7SxJ03J+XLynXW/3hPni/2yU5sO79W2Hu/R3THcf3zfG7/th+TzcJl9CVpbvTfGmOEdz9Rm8IhD0cwTR+KPi9Tk3jVpjBpdS89HMcrQTK46gdDYJ6uqswKybhdr/wWaJVGbXvQaOe0PyOEkg1qonUFzclTHlS7WbTxM5ESNn8Y4NAOQOJIKa7l8XUrlIxEp3BDLAkUBL18cxJ/UFzk7WKCMR9j1vH7U25+wEG/42qzYdQlvZdf6X4fLgO6NwKatperp0uiUDMKMwgZjO36plNyGCwQLXNmQBuWq+FVfO+LAvKUsBcAgmgPsfNgHson64XvLUyAZwzCEA28jwR2UEJM2JsadCTlcvWLrOIkf9ZiZGcmiWBnDFNE65PT3jCk5r+zblpT1tuWLR8OQGUM/L5hPk0I88ZaUpAyvjprz+b6QOpftR/+be/VrPpYCXLpXxEYdb8CkMKV//uy0U14JdSwObenYSg+vy/M9JYda4LfkYC8Mt//qcebPCaE0CMTClG4LCVZTFNPjd5LimhFAEH07ert8berf4e1ffGtbGjdieLkdt6ckA14L0epJHdSnLsOIOJ68kub0rAa12o3Ya69hPu1pqQvlxKaoWEYqzOb+yNTTsM0x1DTx0zR/I8lreuTMblifTxM8b3GpWo6/PlJrfff038GqzH+K8b1dL1Dj3X2li/VSLWOgFtqYVv/pL6+7lVf0dGbsS6tfLdapdbPeYl7RZXL9EaR7w/rshFnMhub32zGiF1Dee61cKqpc0MpKr67zObHn4T025mABkFYLNDZeNPjdOsr6hFi2QurNr4w5bprTVoV666ViLbz/Vb6Wh1Y70j6eOOutcS1lL+nB8QYml143HHd3/Ms4R+Na5Ru1y4RQAiNAJekCjVeAioGuPjeOM12N6SdT669rf/curfm5Yvt8hgg7W4SXmYC5mQsmB3/fgculxacp21hWHdHe9RaPBqNcgWdu0AlgUaSPR7MlVDydhbDhw4cODAgS8LB4F+4MCBAwfeF7aH2hbD7IT3sOTCQlrdezYu2zU3baMgsBy1B7c0z+GCDVlfD/FGoWlM5q48epidZxlRxHJPRHh2j3rgwIFvF6Nhx7S68tyIdN8AUqmb0UkoRsIjUkON8HmDkY4e9PJBr5kMB5xId23pRpabRnJyMjNV85LMJZBgKgJ1oqf+iEJVGXO49l5J4V9/pl2iIWCghj1crFCTsRMaSUz1twZQLbaEnAg5ZdU8Txk5qz/rZASsmnRvPrIlmeFUUvKdCU0DnRgC1U6HCfILmrY6JQGCdvbGFy2XtUNKSfPvxIFINcHq5WtrhWC6nuKdPomo/euafsaOo6oCCkMkGXmhIv4U8uraxzDilJnNBLn54Hahcm0aMdP1aSXwdjPfOSlhnvNk9W1FNqZ5WdSveVoumK4TLqcLzuWKB/6gOvVW5CkpmTNVQt79uENNt9cyejWR+hu3PCYC5vMZ59OM0+mENE1IlNS/u2g5S6dxX0wjW7XauRSgLKDCWFjN+AMM+t13wAko/yhYLj/iWhatN/wEQQGIAXoA5BcAZlJZxFwLVAPEdexYAqF9rWuxaKLZP4c13NDbQgeCuwzy6wL0fsU5aJwbYS5FfxfXFBUfB6SuV93PMaERHq1fOhmv/VBHFO1zC7kPdM1x1HJ38h4iq/XjitDyaxLuYT/sr43yfJAvHr9FoicSg18btkjVt26gVi5bnGS8R/PWGNI4dzALOKmLEAhQBHUuJjLNaRvnEzMKsb5MRDZOeb7sWkdO2wqE9cgSIMgSHUKtVyxAXdo0XrSaFkebo8d6wdqH+LP1sfP91rXXYUuisEf3D3kY11zj2iKUux34sWdjqu28QZ+zavY8DOwb80cMey9Whw8q890yIx2rHoQ4Flb8OX+mW5P53kDaDbtc031hI269nV/zGHTgwIEDB75+HAT6gQMHDhz4JLhrkyNxA4amrfJSUtrlp3D/fJ30vH6tBHm415HkJrDsokAfbtRIH/PwPF8lNa0YXEkCqpvae+vP96rPJX9sOj8vNiieLwJfYp5egtdqcP9a2M/dy/J9f2i68evtiII4JbcaUbUV7r0En42MCtLcnXB711NKdZx1n9+RMM/22z+dpGUmgN2vd3I+sgkzXfjodUFtTnFEM+uoZdnKZxPq+nTY+VbWyMJXCU/oZKDeVKleI6i570xKnueUMOVZifOcMTlxPmVkyua/U9MsooShkGqxIYmS5iKqHsVsmmxatzkJnLZnI6TDZNqXwVTjNX9Utd+dUGd2g9Zh/KyEZ1+f65Yf5m2/WgnlRrSqpjobOeD0pZmRN6KzmtM2awQlHKLbasro731ESgmU7cDCpIcYnOLhUlDKguWqn/IE9V0+X1ST24TZasY9Q5tB85ooAXlCpqx6bcUIV88TJZgrdtWaJpV5n+cZmCY1D58nMNTKQIES15dlweVywfV6BZYF16K+z8EFvCipzkawg1kJ+B9/QlkWXK8LLouac3et7Upm0UeoaePYTq2vK6EtWESsnwkW6ds0UiDsD9U0pBujaqTRQkNoH10fBlKcXdtc612s3CWS6hzGue5ADdV+vSIqnEQP9VEgKASApJbb14psBzUk2l/u1s7NvHIti7R14Xg9sjpf9uz59WBv/f02ivbTY53fgRQO83j1XY06uq5IMRkuuGb6/f3s3o3Uy9CPGOpoo7bNC5PSqdHKRSvbOPoubs5PpEdlBHZY3HIWbGpzYSBpSMKkrlGyTZUpIQmQKSFxqVZTqBQUSiAfIHz8JB8qwjolJSRhuEdx8vxuVEIcW70Ck8Vfx1Uz7R7ThcfnZewiavUiAHh4O54nTMf+0X57nPGZ30Hw9+5uC9OlJasvHZrlBWm8OYX07J+Yqy6ncWoAISUyyyocQ4XULMcswUpH02Sv8/rKmsrzaJr38Voo1Cq8f7G+GvtLs88fntdwtDMHvSCjz14+5q8DBw4cOPBr4iDQDxw4cODAr49uM4lhRySrDVeVM2wEr/GY4LR+IpA7q135+r5UgaanMQjgwzNjmJaPZ7ZzKhndvPwqMduXLp07cODAu8ANPQIukBo1zUfsDQzvNGBUKeI63m5crEPy29NVOd0rBj3Xpq6aXFSJ85TzJpnemw83YlqSzU9KgLkJZSEKWqEqXFQT3jZthPt7dAKN/9ZJsNFkscr9agrPE5GR56ZRH2akbGV0DfOUk2p8W920NMUzrdVmRGIk7JKTnKI0hJdNfRuT3U8gYnDKAKQqLmkcZgKXLA/BF3j2uk/JNJ43aqxbCMT52H7bDy1aql0gmdb9NKmp8ynrX7a0qzag5TWlDCI1qUulme+2JlUxtFs0GNszqWn1piev9UpJSWw3tz6fTpimqXEPvGBZFjzKIwCgyAJA1Ow6ex5i2d2MqhH2SMgimPkETErWNKsECZSouolhCDgBOWU15e6m+00zkUVQSsH1esXT4yOeLhdcL5emgS7QA4empV6WxQ4gEsBNc50vV/CymLa6HcgIdQnrE5GQcNPsYv1aqJlX13oyj+HSr9EW5ko4q7a3re0CyVPrKulBEO9vECUsXKPcv9eDE+GvDJrpmnkdF/T9QxtrKPQBGCHOzY+6a6D7gYZI/DeLR6EcWwc4D3xW3JqVvo1luvtp7q82gzSvK+EWYbr1Ge+/JKW98K8lz7fTsIMEth7oDwSFNH3sGWljiTFBDwtJ0nDmzkKthSQ7LKVrkZQKKNm8XkyzPKTLsDFGmtsLn3/HxHVo7SZSXdcAeE512P2jb9zBS3v+c09ICDc+Ee/51YQ/4Z/wF/wYnnq5fvyqany4r2Dqq6mLvx4g8LWSQA+OtZysyu0dqd7bcYXm/W3j+hbaeTGxyUZsXUa1Fv3wg/aJUNCOPK8LVMug/64vQF2rfxvj34EDBw4cOHAQ6AcOHDhw4FPgjt0SYWdfLn2Yl8ZbtcJGYUAQPsZwnXKSoJ4Il3hxI/wuITRcruG4Ca0pbEGrvltqRMk9qMKCZ3anxwntA1v42vvF16N5fl8+X1+aPUr2fdFEZi7Oi1dbDlxMe688/d58E5yIkigFvBvVjLsyqfo9N9/flegKZp07Qja5lFKFi8nILSLXSmo9cotEHzWRx5pzAjG251jKFUnrn5YekZKlbga7ktUw8pjcfHtWLbZg7huAatyav2kiUfPpyuTBNZ6UotXypiCI9rk8gcBEyAA4JRDrjAdqbVD9zQ/a/8n+nNBMRCufoWN9VCJWZGUJwOkKquSDatlP09T+TAu/Hpjw8lpdVS1guGWa1gpOiKRElajx+yk1DfT1G5qQkhHo84zTPCNl88HKC5brAilW8hIOFAZ5tX8XF4SbEDwRATmDprbWSaEeIkldNUpTOzRSExBU8nhZFlyuVzw+PuJ6uYALt3WSKJntZLlwUWsNdo2WYuT5Un2pd1rQliDX14tMQ1vzUew6RXPBYodY3MS6E+nuh93aQckjruSzp6UHQ5oVBaIEkqL5ECfRvW8xmE0LnQXMi32WzrS/c1csAkls/TzZoR20QxbiLgE0Xs8jQyCkZpfjCpQlrF29wt+ML4PSyFj7BP6asTUrff5avg+BDusQTYy/BKNP9DXxGdOI8TciT/aeoP7qbt58rBsCkA2g1cZLl8TzJa3riBE2b8T0xmB1Vq7Epf5FlyHK/JqrhkBeppx03iYCM9e4MgiFWOdjPzhkYxJQwBJIWJsn2r42FLt+31tpxHVgq0GNN5LodSW0qoCx1iiGDXHHHMhm+P6ZEX7tb/hLIIY1hu8B/DSEWx+G78GhN/o6mCgcTKhdSRuVQx2KAFNOoYrtCAULMumhzLUmPoV5z+tbwAy4Of9aAmnpbtVFXEv6Os19mNeHyK1JDLVPGriOAtVaQuwJ7TpJ7Wm6ZqQkoeRdAAAgAElEQVSY3oEDBw4cOPB14yDQDxw4cODAu6GaYL83bPwdHt0iD57zn6X3TZCuXw0uSHBBpwy7TAlSliCwCLd1Y/hcibbz7XFLd79tPOM++BW80IEDB74h3PJpHgXLL9eh+bTYF2X2YVbcWff87d9vHR4JgcStmtgDeY5Iyjr5xs8VbZWODJ/x3vg9Hqiq+Vw9Systvyp8N43zTOrn3An0aMY9QwnhqsVWCWMnIQkwk6JCUslfBqPE+ZPDfCloVlql5TdBicAMQHJuZTRtOSIyTXMjzJOT6akKoV2DvtTaUXQuBERMk5cDMSnVjHDOWl6Pf8o9eZ7N3zfZ4QiPR81ytz8nY11zms3NS5Bi30bV5FOyPaeEnJXMn+cJ54ez+Z9XEqIsC6accbo8YSmL8ikp4fRwwsOHDzg9nDFNs2rIw8liQP2KUzUN7mubOl4w1fwYkxK0o73fox2MCOVdlgXX6xWXyxXMBWCpbVkPLJiWOPOCsjT/6WVZQFxQCistUDmhdrSgAFgsDyRKnCO0fUrABHUZUCydImpOXVhNq19FYE4aqon9SKJ7Yp7nxKyHJ8B2CILgTSuhPzEXFBawlHp4wEnwRraj9hVhrdOUtI7cTL2vMT1utyrgZnolex9v46lrkDaiZLS4UDvZ6sr29a3RaXPl+slRPkuqB16Pvi/F+UlISXPXUpeOkPtyEM3Qf5oEtjdyvtujSki2AWnc+/qnH4YjSuaCRef2bNYyKIc32A+rOXkOATEDnCBUtC3EyVclONlSF9H2Egya5NLmAXjew4G7uF6JpXyP+t0bzd4S1uvq57ufGkvaX91LYyvafukmG99uxThoqosAlNa1LbC1zFYGwney9ZoJSshIdBmqpJ5X9QJsTBVueaHaaw/X7VyfWWhqJPrWjLRf8gMHDhw4cODLwUGgHzhw4MCBNyNuMzdJ9J1dYkce2wXdn9lmcYNF2d1QBZl32/Sj19wZ1c3HT5bq03Iz/pDndia7he82hh7fEIVrJm6deN8q294G+7mN5bHx/DLwpbXDl5afrxXbItK3PH/vc79OC46iQ5Em8hVg5evUha2rIXuD9H0NtuJ+zfPRhDuZVnbUvhUnlEWUmHOiOAzQ1MVrRMFKQ3ST5dqQrTdytROiB43oVG10NsIxPh0J80RKlkcSmqBmujPZoQGyQwMek/kxZ1GilsGVdHYT2LUoro0e51mJ8xdVDb9WINWYSpRB2Yh8M9vu2uGUmql1wLzUkptBb6WWSgrr/Mok1SQ2EZt5cT2YNqVJSXRLS023z4FAV4IdAhQpQAFYipkHTzaHc9OcLnaP2YTLjUCOPnHdAoH7vyZCM+lOaj7fyfx5mnGaT5hPM3LOqtVWihLo1xOWslR3AfPphNPDGadZ/dcrYa26aiqgVu1/mO9zbxv2PmrdSA9HWJ1bHuM6SRKBJBnZLbXsZVmwXNWEOwRAzkjZTAwH7emyMMqiGufqG32pps/9fagWEoK1B4JpJLOYRR7VygbUVYAkgIVQiMw/O2NhRikMsH6fLB9wE+twbUzpxgBiLSeLmEan2lYoZrKWw8EJsbiFC4owmAGpGujc+iS7ewOxgwwJIgxVMmwa6FLJc9M+d635kiBpGOuGccWvN83tbvUdRoY9imK8/nnI828Jt4iebQruy8OdW7bV/UiiOmm+qck6Plf9RQ/rg6qqSqtn4u9xX3VPnu/DLTovhur3f43gNAJzrXpeTW07me6pxT1zeyN9/k7IpGe1COgOoDEDU7KDKCz9fMCMAqilHEoQ8/luMdf6Z8uvj71dXUrfCiI+d+zVWStdvL5Nqese2OtxtETR9at6Jb5p2+2xfT3mq5VwKzb/Pdihq2sxsUrxg02+1ElmYWQxyyyuoa5dgdRiS1XHlhqnujERX1T7dFznLE/Y12t+mKqw1LT1fst4tXgyyjw8VSt463cmmfBGjzVBaP3Z73v3jv3W2XKSnjz3FqjhQpv6I9jHlz5uHjhw4MCB3xYOAv3AgQMHDnwWbG6ctiQl96DuM3tRSjO73kc0Xq++Jl+Bbb9k0pHnLij4VFqja5HTgQMHvmTsa5o/Nwh+CW95nycO5E4n2B5In3dBldy95JG+zqJvYTZNVAn3WARcigkxVU8yp2SksZZSEDRBB0FlFao/m03aGbvjrNJMsY8hyAS3zddyOxBQvW8TVeJctZwzppyqgF61rqGatBAjognEBElGBIbO6ppsKeQEJp7PiGFDjqn5b3Vf5ykP/uY3TL0mMp/hLmmN4m4BOFkbMlcinYnNHi5VP+c9ga6a5zk3cl6gBIRw0XYvjIUXXE0Azov6JV9KqUSw+s9mcBIk8/MemYWUCDlnzPOMaZ4qcZ9zQs5G4OdJLSDkVH2ip0TgnMDLAhAhS9Z+lKDhUwKz4HJ5UsJaUAkQgJAQSBmrKrDAj+0B0DRTRuYJaZ7MrUHTPsziOuhUzerD2kiT0/qv7nJMGl9JJVEtbTd7XsOGAWJcC4kT3V3/TvACxdB9V9F3ubClGbS9EwAKlgPEBPsigpSAwmQEk5m3hz4PmKEFEUAYxUy4d2bXu/9ap43uGxisxDk7m2D9tY4f/t2rRvzMQ183tX1bk37NyFBrA98KvoQZ+XOi65v1RxuARnPufner3p7r23v3V2uP+NsG+ZiNSmLfY1pswKb59pqua/Ta3CnjeGWuHcCNQAyHiRLQ5uuUkIN1Fp2vttOm8KeHeOzPD6YBIG51oOMMGy9KenCcuNZLG9v7RGJZgvGRVf3cs5++9d6sV3nximyE2OtRMaWeLqf6b4vnBzTz7j3aWnZUEvDDa9aj9NpO3fTrRPu3dlbtpDKE858Unhrztb7UzOpXStzWr24WvjtbsFV/Eq9LJdFrPrqOrXlvNS2tNmjdMr/1MfPAgQMHDnydOAj0AwcOHDjw/tjZO0fZytYGqifB9+PZfg5hExri2SDLtz5j2Fu4FYIAoAQyJoTutPj2nt8x/fdcZujeijrwzeJbF0jQxrdfO/3+0M99+Xh9bin8++thLN+YfhWLVbnf9tize3gJ22Pgc2LBFIW3NwTYuwjaP2LSzcLcftu1qHXKzGApzU+4FbwTcI7zyQ55vlZIo+4z3lHirxc+tr9GNlP1YZ5Uw9vI6GRhnDxPREoam//zKacqDEVphKD6VW1pCAsok2kXUSCyPZ9N6KrkqmmLd/WF+mx2rf8czLcrc4CE0OYuvDeNba+/Pn00UlQYXLiZ6zanr/M8Y8pT84FuPs+rFr7Tyk6wFgEXRlkKhBhPENVkLgwuBUsprT9zAeeM5ELp2C5W36fTCaf5hNP5ZET6XLW/c81HeyY5WQJgmXSLPlGu/UBcy21ZlJwWxlK0D3tvStBDFdnqzZx6Q0oje6fZtPDlhFNS37okqT9/SK1/JTt84X3KSfstCKA+w4uZNwcPBxQ1coET1O19iTYsSAiUBJAEyrEPrMfiIKpXX7LifLXgUonwrmupOXmCEkyEanbdTRu72wZhxiJcyyxSIJDq1sDfeiYl613jkZBAIlhcHc/XakZo6GEBrgSHazzKynf0evzsv1i81pfvGVw/5WHOW8hQbdnyq6f866OSVp81F6/H1rwP+LwkGwSnh+u/VW1n6WNNMs582/sjNS3eQgjQE+Gm6upDEg3hOg7Q46easxesJWj43pOxlXAmpw6NQfXxvXtUnap4TgnhIBz0oNmU9LCbW45J1OaKVmPhYJC0cQ+AWlbJNl5TAidGFkGxMVcPLBESEzgxBIwkGXrsZ2N0GJl0y0EkiqMVn0iib1lri3SwANXdTAlhIu0tqyv6KV2YlkI7jupHwcb26zXQHT+O5a7xtLgEwA8C/AOhP3Hp8hjnO4G613ErJFHzPlpg0YoU7yIAYBYFCHDLJBJrDnUdznUN0q5DmmUc2CFR1WLfJ9FrPVXincL18L7UF8tfJ3ufJOr8i2mit/kPQDuA8OtPQQcOHDhw4MCbcBDoBw4cOHDgV0FPPm3cXwn5tuPYhIx/0jZ4YaPX5LM7912ocjeiNJ8R5LQvFlAGg7ovx+5x9wMHDnxOrDXN997yL+/9leG7kz1Vi2lnlHutNY+78BruHIAT5cysBKVrng/az5VMRRNKM8yfqIbAHq21V+xx7tsa6SOdvhITi5twpRomGRHr5tv9uwpfjUCH3nNN7KiB7tkuPicWvdA47yZIrTl2AtM065gSUmKAczXpXwn46lfciYVaweAiSIlRhGs+ewG55iUlAClZnE1TnTp23vx/Jw6axhrbNE3qL7aSEwQIQV2dCwopmVBYSfP4p22uhLmwHi7wuInagQIyTUEyc/Sexw8PH/Dhuw84n884n86YTqqJDiM8WFS4XErB5XLV/BTVQIcIluVqmu6tf5ZSsHDBdbnicr1isd9qMTyY8E+pEuiiTskhhev7qoT+CQ+JMM16wCAK7UEWHyVkM3c/u9n7nM2kO9fuwdADJ6WoBn81ax76UkrJ3qcmYAdQzZgXWz+R95ekbUVJKe16qEPcdC5VrcwpT2AUEBOKaXX7+z4TIKLm+Be0+FHTN7/x1QewE+gWh2i/Kr6utP6mhEVP+kk9ONJIPSCQOIJ+bAndONIUIzHUvxltkdkVJQ7MMfw4KLXBW8P9StOO04W/FXzb/NCa0nwOQut3b33/7Tl7Ft1E/P6tVMnjSEaGtHTq0ONivqLwsTdBD1HlpO5FpimHA19hBGABc4EURmGu1nLUtYjNTaSa7MgJyDoG6VSwoHCbJ5kYIgWFEiAMdqscdV8cLWTYNelrrT9KEIt8nyb6PdhLYwyzysPuM9SNsi89UvQjgD/ij/gr/grjjXfSc9Pr2sHbAUv/pLo+BXQ+9INiNRw58W3X0GYI6WaGoc95vH6QI2q/75DoqzhquCGg8+nOqdsXMnbcXfyM9eHvePSJvod7385vd5w9cODAgQNfGg4C/cCBAwcOvBtuEdybhPiw8xnD3CTMd+/ZBn/QCGzE+ih9bPddeHlXWvW0uG4uOQgcbmGvTJtpP4dASjwX/4FvC2vB+teK2yX4XOXbT/dVb+odaX2ekq770e18VGLJNcMk3mvj7fuT6E4kvi1eAVBM01pIfSm7CdXdJwQonYfQrWD79zp/44bVbzc9vUGvJ5+bCFXDuJprd+Lcvrsgvj6bkgrik2pfu/9tiJGryT+lCXM9F7W6mxA33ksCMJES3SYNdcI3wcyAc4lMovWfApZmEnzUxmqkYjLCgax+qPoR9+te95z007XytOzq/7yrcyt3MT1YEYA5kucLyrJoFtxCgQV0oTMB1SS9m8annJu5cxA+fPiAH374AQ8PDzg/PKgG+jQpCV4WXK5XXN0svDBKWXC9ZmQjs8XI85xyI2RFcL1c8Xh5wuPTI67LFUthy4/5licjYEylX0yDXsriTYDCBYUFaZ4w8xmJBTSNZI+2pfafqf3lrMSNoArW3YR6MX/kwlKve3t6f2hNZvUJ1VaH+QKPbUWiWtwkeggiJWralpbPlFPIth6QIYkuGdw/u1INeThk0WlxAihBS1AA9U/u4d1Xuf3rWn+RVBDUr/XVEUCtNQgqUeP6ir2Z2zAah2VrRFUwFNMCrlXcjxqNGhrRDiCgNc+vMvt8/WuVl+HbKq+WRoKG6z2zsZNoHsd4VKrqAUujM/0ZJRbb6kiw9pVdVx3kcwuGFMaQMHPbTkLSixtK5z8d+8jnuZBKJSc9fDxYA5+3COh0vXVum1LClPVQlmqhJzPh3g4Qgc2VBDPEDi2xWckgsrkpp2aRJiUrN7BcCVSK7VkFnAhSACKBsJamHkCq2uowf+qo+ulxzdrrKrd5eawHHWObj/Ddug1xtlr1+wMhO1xJqyfiaqh/0tPZlE2snui/CaDkud+xrsS1Ltq8oC5DqDtgn0j91Se7wrB1Hmm/ZAtcLe+g/97cnfj7aNehrkv0fTKbQJbBrl2wr4leLerUAkvt7zGg9mmf1+J1Pbzm7n66+GMMe4NHW9Z1c9xWQ733LuPAgQMHDhy4hYNAP3DgwIED74575BFx87RFBu7FsbXpWl9rwlFgzW1smtt9BeHjm9CW6rGdO3Dgt4r7tc0bPreQ/b1GrK9h5Ktj9aAFGgXc0R+pa3P5M/bl5eliu53jvEdj1BSuWUAlzzVvGe5X3DS03cTrYOZVzXln9flt5HlORqAnIx8koQr+PT8Wl2vMujjVDwOIyVOJkwqNTfNI/Zpr3lia5jbCXCuQNmdrxaOS8rUMZiI+tXBkId1cPYxIh5iGqzR6UzWnoiFXGClQqkwXIubTmitxrubaldithuWdOKfmEzz6LZ+mCSmr1qCH+e7Dd/jhhx/w4eEDHj58wDyr7/WnyxMuTxcUZlxNi5y5aNmSk/KE06Qa66rl3tqzMGNZrrhcLrheFyxSqs9cCIA8QcqCcrWysoAXJVlcIu+m8cty1vZB6O+hP1JS7cUplDNPk9aTMVnevqWon/hiZA68DwnBq7GStlX7TmqbKQFf6nMkCZQKfBTVdk7tOSME1FSx5pWZUZarmWNv/Uag5MRssT25wXRpfdKpHdWo1+fYD1xWIil6kveeNbzb1K47Mtzk9bBCpPZF769HiXt1I99+YOnT0Og5fP8a5ogDL0PsMWP73upN7b3ZPvgx/m5cXP/GBe8IFs6I+Hg9cn/viVdY/nKLKyA1Y29UZiNJodZDpuQHsrKOcb5GERuXgmuRshiBDkGmBMkAzGLLlPTQHKXU8is6XiQRsBqQAbEeB2JiJFYS3Q9LCPQAELMATNsm3r18+DTveYx3ncaaIt8+PrEdq69vRosib0c8POBm7cPvkDVhBlPQircPFkEmho+k99Svl2Ksg7je3XzRAom+jjSQ6ERqTcLXyn5/g0SP8cefd/eTY9I4cODAgQNfEA4C/cCBAwcOvB/ktozilsZ5L76T/Y3T1vUqZfFT8+2irO4NRMgd6RAQtBbaqeiOGDjo868XzwjBtoQyowDn1yJCPzfh+n7YEp9+Ptybj7fk93OWeCVMW90ZBNmjdkoNReGSan51YyVREBb2b4mbo9TvLfxWJnXMvadkL8BA3Em4VjWLU1K/yCKdwM+JXydUI9Ya7LQqSxUwUptDaOgRaqa61UkjNF37GlWgnnNGNrLWTbauD2wIEuXqbztT6gT4YnlyjTiKhEAk0MXMw6YE4ZBhD1pzWXNrJGgjDn3+dW3frh7JzaGT1r3VjgQ7oAQnr8nqgDrz5qjtM1aB+nqN2unCNl+LavKJaU6XYtra7B6pufosT8biOoGuxMSEnNcEes4Zp4cTHh4e9O98xjTPyFM2krfU92NZlHj2Kk8EzNOEeZorUZ9SNsJ4qQcGvA5r36mdlSEFKGUxDUVNj5cFzkRP04zZNKtj/4f1P9cGTVbneZowzTPmecY8TeBpaq8AM9g1IksB8xIE9VD/5QPjLMIoSyOxq3l8jgtIVsLc7qkv31GjUaq1A2h3RebUhP1oGqvZ+iGLIDGQhHHhts4Uz0sdFzQrjKaRjnqdqqYh4isT3gIPnxHff02n9wHevf0AujMjWCrFFtbEXk2rpWyo6K018C7elzyfAVzRfJ53WfqNYn/+/bKwR0DSGEBQza5X8+sdXzbMiHdO5v0au/la9z9/l/yMjHgo1ru+D5MulvZ+V9vSNTFZvR/dmmQvn/7eu6ZtXdeM2ud9ycS+qocTsnpp7jcSobplyW5pBTY6+J5ToOUVtfYh6pNEU6A2jsDyl5IeoNP5mzUesxiSSI3EcNJGZElgUjKegwUWAamVGlZ3GuKb4IgwDnZDfgi3t1Py9qEhnMja5sA2xlSHhWa9vFqpdbT5MKRuhhyWPzspD/HJ+rB9XYPWMIyJUqjHdnAvjtBb72a1AhDeM4H2s26pBSj5ndKqDHGtP66l3NLeikRHePmlt8hCPmdVVfLNFuryEefTFfYGpzGOAe+9jThw4MCBA79dHAT6gQMHDhx4N9zaqLxI47yXgHTXq/B9CA5ATa6ybyR7ggTdJt5OnUu3Z3y2DB6PyPbGfutZGu64kGMd8G0k7JcqkPvUqMKl4Te6zxB+qPtbmlsrQVCIqxelfK342vP/eeAUX/t9h8D1k+XmPrQh9f6crKxrVE3tMW5xbm4zjTgOiwncR5BHAHtvqcp/AchdQu3dcqCZbY9ws6iaPtWMiAkICzez7W4+vgkWR7IKXTzJS+LyRSsLmbC8E7L7HxHIhN3VDCvItIdVEzgl9YuaplwJ8ZaHJqEka6gpT8ikGudsZOeCpRKWpZRKIEs0Vz2Uzds9aiojCIC7eS0I8UWUkPY5U0zr20l1rzMiQpIEYakm6glAJjNNbj7cp2y+xkGq6cweX6jHRKja6WQCY1ET9WxEOjOrZ20vL1sfjgUyMnyeJzPN3qCkcjNtTnbf64aXgsvlAkB9l6eckTLhcrnicr3gcnnCsizVb202snyeMs7nE373w+9wPp/URDlp/0VSMjdPE84PZyxsZs+NWOFSIEXAbiaXGAzVqheI9amM0/mE77/7HufzGfM8IxGhlIKcJyWqrT7gJuFzxumkBwKYGVPOuF6uVXP/crmqT16YliJU+1/7cTCjL6ia6kxsYVEPgaSchjFHu0g07d4d8PD6Di92ztoWnfUIMiV4I/onYaAsSEvBIxcloqweO/ojrCE70jyQ4eMaoesjqMr3NfyaUG6x+FvjZ1T0s2kt1kM4NohGkkOMVNtcOt9YHH6qeem35vP8W8J9fcLGTmqknZLp968y2qq9JxtHaJ/uxwUO76bUMJGwbM91c3YYP2K8t9YXq51ZHXva77gDWZtvpzo5RZcRFN55J83dqpmbaCcAyGaO24lUK6iwPjdPk82R6u6DbL6QUup4k2jGlBPOpxNOecLVXIiUsgAJmOw5ETUDXhZ1NcLMKMKVYBWfVCF1KOKhfW4irB38YNCoyB8tBSHEHdthe9xtV1f7ulX7RnnAfox97GM/2Pm+cfmmhRDpfzhhLqIHKrYT2n7P1tlo6/YtqQlRWhH5YzWMVVf7YOvWq/t1GRVeyttvud6r+g8x5BvW/gcOHDhw4MB74iDQDxw4cODAu6Db4m3skbY2WattkQyb2rjxknhhSCBuuF1YPtxfbfAjMeBRBAGqf8SnEoCFe+K8IxA2UDfdg1Alfr4V37qg8nYtNeFVJVA2iHNgo97v0DzfE7vQboivC59LNvG5a+359Nd96D6h8OtT/LSgV7W1C6mDfDgIyIz4IQpjUBOINh/XPYm+9dr0Auh234ngt6KaInchdNDswTAuNJ/HAoDh2tghtjH2Lo83xyC4Nnm8bxrklJDMz3TOGVNSjWYuBQSqBPI0z5Vk98quGrwDAZ5Nm14Fk9J8OpvpcjEN7KoFbBrBWg8dnbgSIDe+fE0wdFeC5jmbtlzTRLfqNRPkal0+deUgEDKR+YfN7SFW/+WAkqPeToS+fsVIVhGxg3VKWlMBQIJ6tCI2q7jQW8ltJ2W9jpRYnyuB7ssH9zu7LAseHx+xXBdcpgsoK6Gsmu5FzcSnhHmetZ3MTPp8yjifznh4OGOeT3YSQ8zELiAPQJ5nnB/OdgjAtM2XguvliuVywQKoZnglc1pdpkSqNT/PyEb8K1FdSwDVbATU9bgR6POM5XyGiGg7TDO46CEBZsFyvdrSS5oCOBFSJkxJxQ0sDOYEt2IRj1+kZG1khytY1Bgzm4aloNcU9cMo+uKk2hdTIiQ4keQSfmu3auZdy3UlFYQsUEKO0TTWqyloy2dc9flS1Mku72czAKe1/erTmg7ofm2tI+LYETXfnbHydzkBKAM3+PxacH1Q871mplqX0IMC3/q69C3oabAvB8/1BQo9FqC1VTEj0/2Q3J7mOYV1O0KMkQQHGjnbdnDtDYtEXSPL49vUP4HwHlM3mGClOT6Wt9+/ree8aC0mlqcn2y1n9v6SxxXr0Q4vCXE9OEcg5CQApdUeOZMesJrMSoivc0QWXMu1hpOcQSJ6mC7bOFjY5sZm3QUg86OtJSlUQGzrOGIIMqjojCmiVkESRBXiQ4Ns9W+fE/yAIkTT2bTeJq3tCG1c9vrce29aFtoI64f1iPpesfd07FfdvfUyp8a3t0zVepJ2+GqAr1N8rcU2ufh1T7YtiVvut/PZzyzF4ov92GZ5S1e8S25iVaQYvWwElOG2oCkz7A56YxvfjHqF1fUvdXA9cODAgQNfPQ4C/cCBAwcOfHLQ8Dl+B2ACySC035Y77uNTbpZMaFmOHdknx5647cCBXxve61zYlDua98CnRFS2/PIVUHoCPkIEgwZ6+Aua1kRkxHnTtE5ZtcwxzSAjj6dpwjzPyLlp9goLpBT1p11YtYGlaZwLu0g5mFHnnkx3c+aRuHZNOAivSPFK8q2EyuuDA2tT/htVKGIm2/2gQyPzOZlp7cC410MIOQOlKIm60SqdeX0/TJDUP3txYbIIkpGrVlEQERRhpJSwlFRNcVP1gZ7VFPppxjzN6hc2COmfLk+4Lov6Sk8ZeVIT7zmrhYFpmjCf5669c87IExkJn8w3OpkQnTBNGUiESRqhJAI1A3+9IKeMKyWAH3HlCworse4m1omkmqxnLvUzEaEdnKD67v3/7L3nluy4rib4gVRkVp17ZnX3rH7/J+w16/ZxtTNDBOYHDEFKiog02wtVuUOGnhQNPhhvv1or5HLBMzMKEa51wXq9Yl3XEBagoppsLpQBYkVTvV+hAHprTQUITGAjxlBHk25r692kBDok8DwGndVdhPEqjEWAJoInACsRXpJmeYbsojRJMNOFDnxsPdkzBvAa5XEY/oEJzNAGh29cO9OFEiL/JAzaZCeJb0AVAE/PFug6eWqe/970Huzq1lEvC6OM9/16fnYUbsjjO+0pRjEZ6d89AWgMLt1KhVtOaUV07SLdDBWzWCLF7VuY+XfYnCA2z7kwEhjCDa2xwuOi1kogDOJ03ra9VgFpfsuCIgXV0mmWZiu6ZrqLFUZBgeclj8+iPN4AACAASURBVHf+pHpO0/3XINm5stwP33w0v7ekl3HpW/veo1XFn++D611QRIZniLVyNLef0+3m2cU25sN+NzbqnthYQtdEj/lhKvxerHMdOemkk0466UejE0A/6aSTTjrpE2k88syAOR0H7SDDDjdlOO45EzMftJ2TLOm5xD9jCWX8xcA03YliQMMmnc2TXN7+7/bJwan4g6fFHx5jephGFtP2etQ4/9a0m+ds8SDCjqyAWbdhz2j/rTr9zH1MO1ffNt/bId5bqkfTfz/9zL3+OAXTEFvwfPCp/knNsVmP3lDOef5xoFFvaAw85Gn/ESkQCwXQSykopObWA0jNf8V8nlc1G35ZFtRlUQBZBGxazXS9dvPsprXrgKkYY9t9qLKHcY3WBKYnxBBra+oahXZmY+rCJV73uU07M/iWkIGaAy4G8JbCYFJz7i4E4BrCOhZMG5xMc68UUOPeGciCFxSAatZAo8YdPDcz6rnUArG9iARwGabmXZjBTLhfLgsaM9bWTf5frytErqBi2n2LCj88Pz3j6ekJT5cFl6dnPBkAXxe3KGDldt/fPtYKodICWhzIp9DOvL5e8QKgNcb1egWDsbYr2rpCmprpZ2HV9nPwXVwooQO0e8C113mpFfL0ZHVfsF4uuL6+gpnx8vLSNelMGKNZuiIMJu0bFeYwzUczTyw+JpyB70IeDh47MOPpWfjsJ3wagiFg4eTCF6oB3xQ8agqiF+mwtY8OEoe9KfZ+f9rblvaCZigfAuDLMIMhbTDHEkZbR9l6qM2OUWxbK0hgGwy0mrCmg/2j2WuY/K6/n9wsPU/PxPI4Nc9/X8q72zIhZJtj1RSRdwbNHpiW7/NfznuOtw/pzTffjoZ9Q8y9qs0NVispJA3N1moqAApDyPYBl4u5OlEA3ecq6mI3NnGoJREAaCujltb9qDcBsbsfKopoMgHFzMoXQqWKIgWoOv+WtoJNCI3JNNVFyxtuWRSuvzkJDJZ+bF9XqB/hI4z4zDy6wvC22wWIp1aWaJ8x/BbY3ln7hqeyKYDs3D8y9w1j1SLNbI++Jmv46sKS9r7aXqvJ1hIDgKTxbvGMsVLdIk0qDdl6AhZQmX21I304o49zSWsc+cadXOM/fXFhTWCkTVtR3/9TjrC/lG7p9zgqnXTSSSed9B3pBNBPOumkk076XEoMwb3ne/eU7zenqvTAGQqQiXko0+9OGrun5/E55dsELDxK++e3I5OZewYM30dHzISfh/aA5H1g80c8Ix+1/YZhd9IPSd5HJX7PXvtW1LV2jSmHNIeHRoyxUYm+00clA3gvlOZw2heEyRTm2UnNpJZS1Od1PNO/pXRN5OJm3GvF0+UJy7KEmW+/LoVMQ1vXqGYmX0UYjRuaaR+3tvalztc100TrIF0yk53WUQUcpZtrtwp5jTlrnN9Qmcpm67NWsMOJBEAaIBXq2xWEBkFh/VNBAEEToIqARY27Oms22MiSRhKRMvipaF+hmEa6gCugin0CKgxSe+6apsBAY9UUr8sSptldoMEtASzLglIrmmlza3u7z/OulY1GWLFiqRWNF+RthQqHODjLIJD5uzc0nRxEsXFTCqgW1T5n9SkOCNq64nq9qp/1l1f1fc4MbqxCEKhb08PoIHkp3W/8/JGRCXEQEKb0i2mfZx/w3WqBaihyg0vB2FhjM8u+GSFxNQD6b9BIjDE4CUvAwXhWs8i9nxh9wBAuIFRR8IEBvIrgKUEGnl4GwV8HMGKfsqb6/LyX3DX7EngOq36aEr1JJBdobIGBHgfOH5tUDW4bGEg///7z29MWwPu56K3Y1h79rvvjLgLchcEJuqYRMRrpWdT/GgtQCoTENM0JKASx9WXQBhbApI1sDmEwA9IYbV0jbwVlSwCnOkeyThikAlq6LjgALRDR/Up1tyJwwSRouZlBKCYIp+vYIPx484ScIN3JzHsPd/TNfJ2RdPP7nLK8Ub076R7Van5Oh2EfmUf6crGThu9nDb32dTSvcyS+7+1m98cGwACij+B53jxOBdppsyzs8jPPkSeddNJJJ/16dALoJ5100kknfT7tgegynTkPAfXpxZ6mOdD9ahkF+D0zXGdQXcbn2TxmlFkQmkdHUtP7z2fmNN28/owjv59Zf+aD5rY1tkx+/aXhHW1Cfj06ymdj5nWKM7NAZlb6r8JApJ2r70l7Ihn7z9+X7o9Ry1+DOnM1fS3BPDXmbmbCvQFUi+TS71v6rq9ZaQEzbqNrk+f04zrxEQsV1ASUl0KoZUlAOqGUisVASjfdXlzbeVnwdFlQSjcBXiix4U3TtxkwuLaGdV3RVjWXva4rQgM9apXXPsA1fzfLr5t/z89dmIAcHLxtqHoAM6mzywUKajoVsw1NtYS2ucAATRGszF3TXKBv2DSbxXSuBCAzdUtM4FJQwAqiF2XwI+cffx2QF5hgRCkJSOggc9mxEHA1hvO6ans/2zsFjU17PbcQYXgWzGpmzbu60XhvfwVOio+RpSp4ser7tTVc1xUvry94fX3B9Xrt/Snqb72W2oUvbDx2E/fu3z11MyT88EYflQKQm5hnTc/GcQdxusZ3dEpu7N6BCVxJ2vARJ429DEKLhAYeQS3Fu6Z1NUGNvN0jEYg0EDcszICZka8+9qjvyTg1wBO6tjWL4FW4+2T2MgJ48pKlZ27GffF9pI3lAp8f9Iv5T7Q0GZBF0Uaex+BSYeijGYp5bGbztoIkgP0N4M+KPg02dG3ic028TT/CHv0GbvWm+E5zOo+mS0DIw+V48zQh03MnPgh7dIp4XAz669Ncxj5tiOGPDC4FxLoiFdK5tBSByGIyQgpUCwQg0xpH2p6kxhEDtMUAbhXoI4AIatS9YWVRFxdAdzVTEJsYN/VeSoGb89a1GSDXdCcCuJnBGkp7AxmtjOzs38Qaw0H33feH90nwcqett2ew+zTPpRL/9fxzMXW7elyOI/LwMzw+p9NMICGEEGPNkeG2p+uP3dWLBmjaY0mGUdfVag+YXNvfBR/Y0qP4wBg+3my8CCD2MQ8gugiStOnthid064MHdblHR2fwk0466aSTTvosOgH0k0466aSTPp2CkX348sZ9xLeDZWLA5ue78Y/A8zn9w+f6z1sPwXt0xMzcM2F70shS2kLMtPv0R6Gj0XILVNL3PwJL9fch74tT0/zHp67x7eCadB+Z37jb9r5jBwBg/ME8lsj/sXUmQE+iQeO8Jo3iSglMj4yVqR38RzFG+NoZ09wY67ri9fqK15dXvF5fcX29orUVa2sBorO3W/9Bnrnm+2BmFoBkrFvUL0DM22IlVAyMjnl8YhM7bpgaumtCWzOYOXc3R+4MevXlrt5XRwZsMpdftd05QF4tAzc2n/GM5hr46AApm/Y2V45+DDC8UPSf9203TcugQliWfsxWU+4Vy+Vi2uVlZGInE/fd0IKgcQtQQwCgqPl/FRiU8Cu+XtUP+vXlVQUmkjBEXQoqCp6envH8/BwWDRQMdwa3qKaiNJiOo2prW8fMIIRrPbo7ArcwQAbMdFVpdCEMdKDH6+p7MdVK7+5yumxHz9nBZ4JZD4hvr3+ji+Xv7efm2ymZj2+N7V5Swlquij7FOECkfs3HtfqPBHl0CKSX9tkqkYG7Yn8O0v8FwUUrqdYEYv/Zyy8yAugZuD8yuX+PHDSv6Rnd26xY+HkNPelxehS8+9pl+CHJGmcGxfdIsG3LW0D6D0cToOhrYgfACW4zRZcy6lsh+42wtp7Ngnw0XcPWSirowlMAmi2axJzMsJsJfik2B3ZXKgRCLTXau0A10BuRWTlRYb4MhB+N+zz/v6cJ78fs+b+d9kbZjdCOJL+bHs/LV5pHBKbm76LnY4A5Rpcc7IJeLjjhwmi2Oet7NL3Imun+ntJ73UhhGoyp3BbM04k60u3WuHXmzml89wn3pJNOOumkX4pOAP2kk0466aTPp4x9HLx3ovnFpBHeT4AHwPmsoX70LJKf08/MyRlQeJyO/VnTJsxeyI1Z+t+G9sGXsPY742Vz48n72CPfhrp/wpkyg+tnpKPR/r2Idq62dx9J99G0fuZe/UY0NVFn0k3vJM0D22hfn3ZRc7tIpqIHEJlomLOIED7O9bcO4LkC6DVMuldLtxpz0oFIYYGghUaw+zB3DfPVzHdfr3rd2qpgc1PT4p5U4PqZQUnDD4DeFYPp9SG4/zt1kIzMzwCxE5O/+8e0KAWh3e3a1bWqxr2WxYFidAYtkfp2D23nsXtAXjYCNVLT+aY5rXxdUZPeprHPllYfdKO2GdD3DjPT37FiNv/f4bed3YoNxUAe2gGAgM3Eu9XUQQiLqwC6lqkuCxa+4GI+7VnUbHtrDasLTLSmJtStHQoRlrrgsiz4449n/PHnn3h6flLz8wHkk9WDbYwYN1u6VriD/IVUcCD2UqEBp0B6KQQhq85gBjaDGeNI6xYUOO3R3Jdvb28HnuvOeFQM3FJPJuNdG76KmkImblhEAP4viDAu/5vwj//v3yjp28gQdgHwRTjqSZbel9T5Vro+GFIdn60YLzaQLrEnUA33HlqwCLBGOyU0EUARwToMSBn2xRUUgMGjZts9HKH7Mb9HXnYXLDhJaez1t5wfMsT145PXb+77o7V5bpe9dxOm1x/JFC5dD0DZwfu9sN+O9ltkPO34fNXnroKCSg5yK1hdiUzj3PcFZCD1mHA+XxYiVBckMqE8Mm3j2LNQQTVv2S6oHmsqqmqW2/zcxIXwDNYn7za7j/WKQwu5A5gU+w0x5oAD7G4txAXCfAHXqbtvAF1gJ4+7jI9ORvGDfBzQFP4eSfrXS0REATDvjcn3UJ8vfN73Vh3HiufhayARqf9z6w8XPPNIBaS4dVrb856vxOARs/ivJajULfR4fm5zwPtUQqs88UvE+ojQz+RmFnAYp0I+2KxrOyjfhbi2Fo3e1Ma+zZzzPumkk0466aQP0gmgn3TSSSed9OlEwBb4dJIx3Pa99DCJQTjGl+kEu2NIe5frItvknMn6SWyWPczFr87D3H3atFE+kJ900hvINRa/lqb5zOQ56TYFcLjTaG9hbn4f6qzOUNr1N0kLjKiPNwfWC7rmM8VzGFPcgXTXUFeGqIPWBPVDvq7qVkRY0JjN5/aKtioA3LihtRW86jthZXizcDB9tfTpYtJam6sr2K5aWVBg4mArEzRAzDl8/15itXXtcBCoql/tpS7hd5yodsa4MFqT8FstMCECVZtO3yKpljb1khM5cK0m2b36Htf9lzfmABxCcCBpVndmtEQ/EDMAF1hQMLu1htcvr6qxZ1YH6rJguZjZ/qWimsYfN4bIqmC+qJ9aB0eYzSy/Me+XywXPfzzj8vyMp/YEEKnp9uuqYL0DHKWXv5SCy+UJfzw/4c8//8Sff/sTz3/8gcvTZdRCB7oQgZnk9Xo6gO2CIDDT9GxldrCfDOgBFZSi7+Hm9DNYBM+va1i3xh0E8B4OjWskYBopTP91ED0DJoJuucAFDCr/F174/wLyTxstf8f/+H//H/zzv/9le9a8ExQFCxzIm/ePYaJev4U/hPAlrwoCvCRoBPPVwYS3hISLAikspnEP1QaV1BzhuiipkNe9RLEF1qs9q+neyduTpmtPJwM8J510RN97Xf+RxBP8XAx08LCvTbpvICpYXJgsrNKU2BsUExwLgZ6ecr93qyBu9YUAJHcd5MCrz6+iz8AuqCdAa0Ah0z4XrLzqNFeXvhbaHqAJq19sEZRC6svdZ1LK9Z0EHyYN9G4UfP/9x1v//aTz9bcaSduyzvOtSAfBhzZD/+ayJrjYC1cG5yncDDZL/JnrHNvHRH5iwhMkIF+bDATvGLm+78WzHBNQHuvWHmJOQ6yTTjrppJNO+u50AugnnXTSSSd9nCZQPDxQvvXUIx3QHpKewPLhd+/5Bi1AN9fZuaGmXTWzFW+ACm+gDDwcmdXMYd4qLb17qMxgxs9KCZxSTTLqh+30/FBA4/OL8xDtDfUOufW3ZTfESe+lW6b93/o9vTXnr0u/4NggZxhvv5eNABSwbYJBhfp9+X8oHu2n4VrFxbVwQcbcJDPbrKO0GIheqGub12q+qY1RnsF5r2VrBrZyU//mrnXeGphNy1w0DAw0D81hHCzDG2EGGtxV9gIIXNetQ8/agyR7mkIzQ9QYuMapj5QICmgD4VN8WVRTui4Lal3Uv3lTTWtDvK1+EuC51xEOCli6G+GA0Lob29bbyTWVo22IUCphKRWlVJTSZxoRMYEFVYlvpYTm/7qqBvi6XsFg7dNCWAz6XJbFQHMtfyOAhAcrAq2tENOKb62BwaBScHm64PX6B56uVzxfn4FCaMJ4efmC19dXrGtLbSIAdEwtS8XlcsHT8xOen//A00U10Muilg8EyYQrC9p1RWs8gOeAAuhLrWoKGIj6Np5BdO9fhV6ldDcEYcQ/afM7cM+NI56b0XcgHejATw1NSO1f98mt9TBT7JZuExUuuTJjFQbjn2ADplcI+P/8y/qog/UC4An/E00Eq/w3BAaUiwSA7R+W2Bfyh/u/nTesIfynz15ipvN28BJ3s+1XKLgVAxQKWguAP20K/BcmGoC5LS3oAgbz85x+fp6TcsDlNN2+T3Ozz3N4X+H6OSSL/X7trfvc75ul9SDeUXly/e6V+fA9TUe7O2V5C23b/3vRtiT+pBh4rus+oZqVFAfOK03guYV1lV2f/7pbEkAinFoKCUDdAW+gz+skqjnOrK5i/EzlS7gImgvhsc651ZdWokBwVWuZwVJQWH2zq9CXJmZYKggSwoV+zA+hNKDP84QA5KPM79rzzZD8x8BYdisslpBYuWJ8y63vSNt/T0Med54oqQhTF8eSof28ZrGF8fWTACFBs/Jm6y0CoBZ94esaWyVKCiMwYFwYYmNJIg8FwRmEImK+0K3fsmq5jC3fe4Y2a5ZH67U6aKIHJ8tfgS1y0kknnXTSj0EngH7SSSeddNLnkUx/DwSnzRPZBsqH56Nrv9/Jd3P4tnAiX98I5SF4Pj//yMkeAO1X/aelQZNR8nO/wA9R4VtD/RHm4kkfJ2f2ODjz0Tb/AYbVL0fZt/O970LcVOT+y+/zUcXEs1N64027CeuKYszrrDGmsWqAvOoTu1IdfKEHTOuArgGLAglz7a/riut6NRPtLcDG3TL7XwaHkatAXTAgP7OqqmZzNxcr6f3gkkR62nMyCVZXkN6BgVJQa1Gt84tqni/LgloWlLrguq6QtppWnGksMwdgGxroqb4KdI+Agbfnfn/6bWfkEiljuS69TKWMabXGuL6+YjWt7OtVfY8zNzNHTpAV4MLqQ960s1W4IYG11r+vr1e8vr7g5csXXK+v4bu+8QqBgArh8vSMp9crnl9f8fT8hFIKmljcL1/w8vKiQhVmxr0UhkARjxBQsHautaLUBaXWxAwv4MZ4ub7i9cs1xl+Ybl8WcGuopQaAfr1e1WVAmMA3ADy3Z27nPiTgDH834R4a3qW3jUBAIuGr1UEVEjFT8dvJQETwIur3nFuDtAa4pQKLxwAWFDQIrrA+MkwJAK74bwB/72M7bzimofSn6JfwH8hQmj5VpTE6bF8TZCiuHeqBDvaN9vtsoV53Q92mPRPve7kpoKJ0sTDtIOxJb6UfZAN7QB8p3Uf2vXt5zkfKW/d7gPyPSL52FiKUmkHzqmvPZLq92Dqd4GbTWAdQulhLMaHjYm42Ij8HPpnVZDep4I5bEfEwRXTuDivccGDd1nYRAz8R4Dygex8ykD006kU12AMER4aAH2ijd2igj+N2tCbykZkrxpp0lkQyTvJAyo/m7zXIv4hzjQzh5mT3v1oZ3oo9S+JUth5SCpgsrUc4SSA92T6rCw0oiO5CbpJ+HUTvtdf9qLsCGHLpw+VTvt/zDH7SSSeddNJn0gmgn3TSSSed9GmkzEYZpbJn2sHHgzk/aI9PzMojzfPM1JQdTJ39eNfjCwvYWINZC6QbGn0fbbRhM5Oets8HX6h3GAW/9CGQppbbCB0kMD2BNwOm9R1INv92UobHlqHxIzP1btHx+Ps6I3Ob6u183gucvzXO13fE8Ot+6f7NDszvjSlSBKN4M9N/QAP9SJDpDQl0oHz70gBxCn/mC9Xwuw1WjfACUq0yY5BfasXi2tclGVB2oM/MqXJjMBjr6v7Or7g6aMmuO+Qa1h0FjnZO8+aIZlK8EwfRkce4oOsyZ5KhfzKfdRB8yMxQ8exMgKAQ6lKwLBcDqS9YloJSFlApMQCam5UVRH2bAaMsecEnaFO7ufUC6k45IZvCIvWn9pOUblI386+zOXiBaqK11nC9XlGqmt5X87WmSVirmVHXVqNCJiDRtQ1diALo4AaBwsR8aw3r9YqVTTe4EkAFVAtQKED1xoz1qkA2m/90KoRlUasGy1JxMQ10b2sqRU3QtwYmHWssguv1iut1xV//+Qt//ecLnDvu5VtqVWsBZjlgXVe8vLwocH+9jsIMPpwCcJAYB4CodQH39z7v28RGnlktaIndf5lm4L//r/+Jf/7ff8yRzfw949oY0hpW5hDE8HZvVraKv4Pln2AQRHzVJhD+ZSC4+5i19gDg/uL/tBH2H5nBIQeN3K98fyoWVv93YKrPgV7PnNoVvlf9GxYAK/4DhuBPK+1qu1c3tOTttVr8FXdomtRcIz2Pe4KaeT99nz9O2y2qP+H0JsN80xniK5Vj9Lm8n1++PgIK98q3F29ezWn6Zd8XSBp3NMfaTWqvkbd7hzvl/Po0FpKAcLHhFmhqrVhMoE5NuHcRtdjfpu+bzP0GkUOjDkqq2xiUNOo8LbG52IF0m/sBqPBZqTEiWQTVfGe70E3fEVgcKmCfz0j6+u4hbF3zB9q346iIO3JAts98MU4mMH1+n78vb43t3QfI2ioL2RGgfsihbefr3N7edX9Hm+f8vQ1Kz3z7/aVzZ9/kxTjpfWjXpecjAIRMaAJjhTyfxuqfvojYOilwsQkCwKsuWMXcuUgMToIL3WUQPYQucjigL/zTHmuP3nXc32/2k0466aSTTnoXnQD6SSeddNJJX4UESBLMx4EGho34gVDGQ88ReH4HSNnTPOcAHL4uPax5ftKE6eyz9H7UZhvZn9t3P2ixf1qatc0R9++jk7fybSgAw8mkhDPYBsaq3GCVfQcN9GBexz+yCWDwp2qR1YqlLOG/1Fmbbs7dmeNLrapplvyTunlVZjUTzsxoUDCwJfPt7re7m7vszEtn5CYW6w7yYRzgWxNrYqj6PNfbYdtGG8AjhYsuVW6zautXM9e+LFiWqpp01H29u7l6B1jDVL2ZQDeL9ZG3+7AGABIOk/jeZ3lbkcEIsTbIPrSZDcRuBQu38CHbzY2vaAZ2U1VQ+pIAdGdUh3n/Wsw0fUWpCqarxryOjKfLxbS8VZhCBf8EZuPdBA5U2KKQAR/N/Le7BmHRvGspoEUCnHl6UpPtS60gKhBmrCKQBsiq4HBjxvV6xevLK/7973/jr//8NQ4dA3sKlTD72pixvr7i5fVVTc+boIjvy7zfXBhEn+lDH+M8m3738TJ9Yozuo9uhxwLg+t+MWkbg0cc/2zdyZdZr3/kR4cnmnYX/BxiMqwutoEDsW4WYhncS5nQAXPGiDihsgZAeL4Nfui8OqKsX2EMSdf+x0Pxd+/sZwAKCgMAgXFM7LDbyGV1L/DPXtmZpX6D9UNLzk07ao3NvtSVfcsn2AcUFq2pFrUuYbq+2V/J5I34pz8c6s1ApgLBBnOavGgIpJZ2BaThvM6tp9pijqAQgDwBNmvpEN432EHx0AfmUVgiCYd5OUJTV5AiHM3k2jPN1KG86PprRGL/vuzpQ/Xma03TwO1/3QtzaEvcz6rQepfe7qYskwYl4GIEYBMQ+q7vpOQTRiUKQ8qSTTjrppJN+RjoB9JNOOumkX4zeeni7e5aZT1cPgOLAAXh+EDfgEj9/3RLGjuf95a522YRsipnB3Qb9XFbjLkBOw88mTPcLuolyOy8kYOIHoKEl5yY9qFtnESTuwwSid63PxFDYRWxu0xGgfUvi/VEQ/CjMrfj7ghwZ4vn2LMj7df26A+6WRlTcy5YJdJzeMe237n6M3XJ8b/oGwyPmmGkgb9h4gu5De2c+JijAN5j5tnlcAkQffVZmz8mbyr6l7o921rx+eGTXGIY3g4FcjkH7nGV/lWoAmbVU9XNOava6WHwH0ktRbTEChRnr1hwsV6C8sWrQNlHN62aA4Mh81kqyA8XifkhNC35vABMNcccmcMZ6b3vvufiNaH2Bm81yRnxjnBaU0LwrxQDhWlUrWmAmZRUcvq7N7rNgga7jbj8m5xVMbRHrlILoNSKAZLsvof4nPXSsL1TITPOXqI+bwW2Nrd8dYFeN72VZtC55BFcFn4VZtbUhWNc1/Kt7m9dS8fT8DGHG9bKEljZqwXK54PL0hLosKFW/mWtbwa2C6xL+z3WcaTsTEf58fsYfz39guSxqbt6FMETHlAsqvLy+4vXlBX/99YLrl1czkd/9oLvmfDH4VGxsqrn5VRES/35NWkFgFn/EzLSbStxgtt3SLoUiz3Hz1n9WElT73gDgC/4Z+ycPww7Qi30nbu5fJIQlXiys0D8g8kcHxQEUEhT8Hf/CPzFB4pGLC1uQ1dhDhRDGbEFpGKQAyaQBaIPQx98a31yB25JgAP/EXwbxA08g6EgiXCIvQsWkcX5nK3G4ltL2tqEzjwoeBNDzlmbO995e/yehvWnlsef6RAYH1L1d2KfWaaM/99feGNVwR4sfDfHuLZGPL6E931vD7gKEAAjg9dtrrc8FPo/oa+7ntqc9XSt8v1AmNy7q/iV5C3fJL0Mffa4k6hroYr7RSVSzvYkKAXEqgy75Op/I5PPL3c/4OgdGzNWebqQTtst9dhJUqIfzZk41xCZTsc2hCv3onsRbQSAqDIZRe5tAEHIf3n4uFG+NnTYdaa/Hi6X8odOVN5lvLdIyxejtOZ5V0+VOhl6r/r10Te85RL6fd2x5r+zFO8pU10i/s/caeQAAIABJREFU1hFS3GKRvSjio0/QbPz5lpFEbIyqD3RR80pJGNZ83SfwPKQlXBIjxl/eRx43mW/r4j31e4oA6GMO0/rySfTW5H6Ic+JJJ5100kmfRieAftJJJ530W9DeceTe/eSzajg67NyHts178sr3U/qS7++E3ZCWpg1a5zdOs8Fm+EjZx9T8bTAp7WbO6b3kQM6Pwn/cY/PlcbRl1tL2fTjg6+HnMG9uwXecZDuD/Pj99t1nH5l/lJ79tlTid8OO2r0/otuzw89L37Tsgu4TkbazXzzwKTthARGGzGcnTHPFIrjBy2C3S7BfB1ahxNP312EAd6dK7AMNfa4p1CNmZnIwFqFAeDXg0jXLay14vjxhWZ7g/kQ9TsmCQmxaYawA+dqamWlvCqgb2CmmOSaJS0jxtbipcwGLgs+1FJQlG2DfW+O87VODeNqhQT/N5oRuztTjT2VR5qjdE9u9mrlXjbui4IFp3Yow1rVr2jMLWnONegToCuS8YWNSehWMhbuQKrVnM9lhajSqbwzcofuV0VuWolqBy6IagSBAVjTSsgEcBakgUNX2qrUO5uVdC15E8GIa2wGehA/4i/km1/v6t/+CmjFvWsbiAPrFTMRXMDOu7QrmBm4cfar+dKs3Gp6WC54uT6ZBTuC14fXLK17WV7xcX3C9NryuV7x8UXPswirA4Brc3AQtaSvGd03pOjXdrHnOYoIR7nKAAUzfsmrqV6jBdhnSGz5Zm4MWUXDoyR6Fppw4QJC13CUY+3ngEoAXEizynzBZnjPOxooJZObu07gD8BcEfwPwBwhf0ox1vC8YdxV5bxjfmY/tyMvnTcRvJQVBCihAKQfMcppy534u3fy7R66NvuB9Jt1D+EjS/U9Ot08Ct2h/F/nz0iN7cm0tdUXQ75XmuJ9xSrof/97+8mDFHO7fkr6bNte9ApnWeQfPYxW1uZRsPiuAzuNQgSwUz71B1A+LrX76XRYgNMYBqPUTFLAwiE08yMpQFnXPIaKWTcgL4EA6AGIDeItM8xPZ1EoIUD+EhWB7g7ftWt+roT6PmHmeEytTuXNuHtLI877NXUzjez+2anX7PE9CDwu6b4P5/vjWl7CNlWeV/biDDZQIw0OIHMf36naXQHGXpyBB9DvDhQLs18K7ENuj34ykcLkOG032tKzeSvczZpOTTjrppJN+XzoB9JNOOumkX4TyoWA8rO0dVcgOGoIk8x3vaBav9vgqEh4HL0nHGwI6OCDz0cx+yeM7M9TNqlpEUd+YXRU9Mec9Lw+a6xZpeOUNlpkZpyk1L7Vrsun96On1MbZKv3Le/BxkZBBaHT2OMf9dAWU++N+6H/PpZvZ6Vl/7qNgPxrc0XXZaKbWJm271MWn9lA7DFOl05rcP8kM9F9q2XTABdtrlqPRHzOH5cD+msh39/S6/22Nr5NSPWYu5Xd7DEshiCI/G+Bp0NG52nyYm1psZlg+U5PNDfi7tj7m30XtnBDJtEp3C/Wvq33FPt49HBd37PG4YarfiHnFdz5OGtDJIzDFX+1ecmHnpfgbf8ufR08sPU5CZ05iBnibGBPZ52/TGCaZBpn9LrbjUC57qk/r4rhWXyzOe6qLgr2kJx9pk7cCsvs7X1nA1n9ZruyqQLGauHDMI6Kxa6gU2c6lFFhCxaZSNoPawnud+M62geOrz8TzgUp9Tzn9OrhcJVGqYFK/VNfTdn3bxTtb8WSCNwzdraJyLQMZW2M5+4jpVDS3UNzHWYaiPpWdmaouZUXDfsGoy/wq2cjZmHQrmA1vjVogQihBKaVhXCszB13jtJ4B5Da16AKiFsFwWPD39gafLBZenRf2Uk68OtpAxtE1aMysHZkqdFjBXqJaf6viB0ZFUUR/pDloLGF++vOLLl1e8vL7g5fqC1+sV19fVTLG/an8IQaSpAIOwatv7Xso/FvLdY4l6sgjYLAfA2ojd/7iP9xh6bKAPrK+75rhIH4ssEm3YilWNdNxVa+PiA5AbSASFGcQMgvlQt/QLMV7EAB777wpBo+7y4AJCw7/TFNX3yfkTsBKjAfhiDweTyf4sRqzPl10vlPI3mL6ZPEwdCCMYcA6YhqmY1Q8dWy0l1V2djGvG3toRc1reE9g/fp19tDs1KIDufSAYNdI3ecnOOzkI+5NSmonjfn/NnUOmN6Lg3K02YfLxtB/qlheU3fAHper385N9Ot5Vjm9eIxNbt8V1b/cLPD/NS3T/Z/Y/3Z8N8aa2zWM/g3sheEXpREyIuXksUJ8/4l0gwDQsvQqcI6ywFKpmnSfvL7xMBBRJ1kUUdF9qRV2qCbgRGhMYDSIFVdSSiWixQvCMWfo8OTa/Ap6CLoxjazUXe9KazYKuoS7w0GLmeWqpkCraFmYtpjHHWPR2luE/a5ooh4W1TgzjLERgtn5Jc2aA9Ll/4attGgvJvrrvFMn2JnsjbtqiQtCFEXI5885qS9KFJO2My7If0lOgVL5eEtuTxCAaBbt6r+XypxbIE3MauOO+eUzDBUabWYOpRR2okElDBGju9XLBCqjVnkLjqkkASi++vrFODjDcTViFKSFgPBlYFbzPprnP2FMHLTuugXnsH9HNnnpgwcpGHn6V9e2kk0466XenE0A/6aSTTvrFSA82W/bASH6f9TudZdDB0GCeG+dAwP29MQb9fJZiDJLBFHqHEunDAQETr1fmqmqJq3m4dHQdTiB+Qsrlyu87K4TttC1hV9jeC9khUEtdQrVS4v3+PfrpLN2Hz9WDFp5PYXrw00PhHjjr1ZoPe0f3nnsxDms0iRhjYz6wyxGL6r10S5o8s6YQofK9j6U8gggIrYU5JsmOybcHnKrJztVHqKcy5h1g0PBM/z1up73U90Puv/l5j+ezyMqRxrnTo234uWN8zP97UjB/3k3via3MsSJm6jGpf8hei+TvNr8OgSl7N02rvXR9tvOwLZjjFNotGj6vFd0Mpj+WJJkUzFeiSEHImNJwU6gqKOB+PyEEaoCwmUMvMJ+Pqm2u2mMLKi24lAWXesHz8oTnp2csl4rLohrDlSraupp5cgavDBbTtg3t8xWrgeevr1dc1ysaqwayqO1sY+aXELzqis42MxBhMVOwoQ0UFljIuyExK6fGz8MjpubOtB1MLsvY/uPYdOYpm0/4qn64lyfVPDdNOKKa0iRb/6mXq6jAmdaVw2c2Q0KAYc7dm2PlFez+y0s3ax7MW+7a7bpv0XYuABoD69rUF/t6RaFqbeptU1BI9yuNBdX+mBteX6+g8Gvv65UzpFezMqB9Vwthua7gFeAnRmuCZWFQUSC5tTX6t9SKy2VRn+bPz1iWBcui+ysG0Jqo9v7rivZ6VYEN6Wx29VFuAhprw/V6xfX6itfriuu6Yl0buDVrTYp8RdxCAOJXkM21h0F9BdtXB8A54uvYoQgHiPnEVWBHy8ZmIt5SdnP+1jelECD67QkpyEPFNDmhmI67PZDWAG6o/Ccu+EfAA//mJL3oZfE9s+0XX2KeSCNZxs/FmfUpmD7jUSRzf63ef1ekm/KF9PbiiEWh8V1DwCJl7n2Qcrl3H6WikqxsjKXNF7E3M3JcxhlKdXq+m5YX9Deg42r2eTMsYmMaY/j++42vRbFkpXuZ39sv7zzT3w5a755qqAPq2eVKvI7f8cr3A/6RxHnYgOJuEcInw74OD3q6Yd0kn4M8LdU2X8wSS0XRuZXF9iD6jqANwFjRRHTPgYKnuuD56TnWmev1Fa+vr6Cida1VwXlfo6/rtbvtYFaz3EiCaWuz9Uh9oVMhLMsCQEDsusR9jnFrOWgMWirKYgJy5pIFpWBdV0hTYaomvOkjTzOEpSlZ+hklrQAAtWiZxSbeAUjPa3+6H3p8D7wW4Fhso5OuSX0/eqRRPqcT+1QzVpOw4Q3leTXt1tA3YoCvBnOJb9egCwvcL/H2eTHhR0D3x1Op49sd1yL/VjTE/nfYF9AOolubpYWVxuwASYIVucTT4UjotgD8cY1v08Nu82js05NOOumkk35+OgH0k0466aRfkiiduWjaxM+7/8xJxHi4QTc56y9du1zioDOFT+n2/3byHbghrhk8MiThjNcINzP7Q+YZxP0QFuA8FFDIZQLldN54v8dNjPaTMcgO5W7IDM2ZDnro7v2oiWiJ51NzMrv2cRpLsX9QNMbRNP5o6MtRm4N6rKlxepvv+rF9hGQn6DT8H6Xi/J0pocwfyXr5nWE91XYukGwubtCOMMGDdD/a12HdHlsqeFuuby/dx+rz9RnZj+fw3rK876vvbMM+hnti98qS37tcVLKGnsLQTozOmBPq+kp5RdHvreAICCYxZqPk0udZZnyWhcec6UiWTiHTBJWi2sZkv+bF3JnbxTSrl7Jgqaphlv2RhpYtd3BbGObvXEHUrrGbOY7Ur8PqR+pVogD3qSjgqD4tXehBYn2VzWqUmZ5pxaSU5wENr3a0gmB9RFTN/3k1H/Bq5j7MmaMBKF1+ThqacIw/hoKsHJroxnB3YCOBiIBAmNAKmUZyARe2PUMfgJnxXsy6jlCBgLE2Nz2uQne19rYlaqqVzoRae18xF/NpnupVeiutrZlmtzZOKxT+7IXVfH2tWicGo/EKsAovllpwWRZc1yue14blsmC5LFonFnBbFUC+NtM6VxjTx1JjhrCC52trWK9XA84dPGc17YsyarBmqZcEbHSA3RvdtOC7VEfUm4Yx7GMLYGHbpvVvmohQBGATZoBbvzCzxSXGOWFF9vlt/cAMtnKt+FesyYK/4Rn/RgNwla1mm/jw7RGiTBksz+GIaONPNuo77shixGXyb83F7gZTwfZbUkgXHBlz6WN+mKOnNOMeW4o911soVW6125p+ozXuLDwPAxI/Ec1V6vqd45zN0zZ3bqoO2O2fL7aAViqDjKM7ywIfTehzflHqD3dSHqHHmrv5uNmve5vJQZxbT6ZpZ/tuuh5/7V/KT2WYC3wf7hbdXGBKhXuKWVk3CyekfsYrGVBt6zWoxDcYQsR+T2KCXZ63hIUOglojkVIgdbH5sZlwkZpj58Ymxk7hAsbnVBcUKO5Oxdc4CJgYrav7AiIopdiS0GcytXFjaxapX3MXNhDIxt967CdMYEjywWw+V7mg5nRm9XHg0bKv9xwmkj38TLJe90SUXZ2PPuWxF34nj4GfAbMAkBaZvB7kMozz9BYuz+92ih0x8jjKFmDunRubCcUV7cxo/+jz0oFzTa8MXSjAYNY+l5ZSnRwsjxahrnNOctyfFE9yve1pKoh/+7vdP25RDsfANieMBbuV9kknnXTSSb8UnQD6SSeddNIvSsMRKxgn866fpjvaMA8xHGLm04Rry0wnkUPqzAcvmJiZT2VS0o207txL5vPOrNF3pPdWZuJ3ot1D37cuw6DlP7/bu9+MqDHMDpt30t9Ib75P7bu0+xFL+qQ9OtI4P+nr0wzmvCfufP1wvJkznulOgRQ4QvBdB0BIulaQf4+9nhJhBqsqaYnZ1mVkYOtKqkBt8bRiPe3aUH3x6XELKMDzTapi/pktXjdzjb4G+vziIDHINF9ds3krQKNBu/YzSEDktk9dY1uCoar8yySUMAAF2/vcYPtzd7oyZDWEAATRCg6Eqs9wbScpBUTcq7sC3LqGGqBAlEAFD1TDnqyJvL69LG6WVq8ZRYr6LU3tG2OE3Je0msZWC+RN9yRVNdgFQCmqBaj7q2ZgOZmfbQTQ7pCuA+m93xtYGNyMLU/F/IIr0FHXq2p7Wb80du/cAqoF12XB06og+XK54LIs+taEMbiZP3R3FZDN6bamGuprU6DdgPPWVPPcgXwQQI4cwIe39yWCES++6YKHy2B6HkP53gOUsJrDjOjLbjCiaU+YFilcGIFUQCGbUdYWUqtGMVoFcV/wd/wH/0DDvyeIu292AxBPxT+arnrNlF4jnXkvMO7OHtkd+6/PL3k+u5fGe3dCj+xgHp3z3aw74bY2+u9L6Xuht+/fHz1pafrblGcjWl8n5z16NN5ei/jaPYJ4Hz37zFauHqaYDwHkNbiUvtaXPl8RIcxa6/qi76tpXI87AwO186Ym1k0NwT5fr6uuLWYK/rKoFYulFV9u0SRxAmI96OUlgroDMc3x6uuoMNYsLNVUQ72UCibd2zjg6fsjm6jTjPUz7O37OpDh7GEuRveIErHeMXbSapOe9HyOx/Ktt4+vMVngcg63/8UZuQmUCcL2uuRVfUjL9skxNOyZbFJK5TDBjn0eDiZ+1E5ZgQ7cE8IyzfBJfYC+N6/lpJNOOumk70sngH7SSSed9EsSbaV//fqRE8DAAO3M5jhD5UPMXnriTFMagyRNpttMyYNjoOS08nMDMiBhQnPLyNwk9Uk0H7n3D6hHJfkIi2G3Lb4T3dcspjfd7z3vjOUO7MgwKG7l/7Uol2+83mNMH5bjG/XhcTt8TgttUznq1/fl+giz/30pf2bsr5PSZ9HbSvTYvHYvj2P2+/0UsxJ2mF4fmIZpLkiZbeaUhDYTjd9qGe77BeXw5Gm4SeqU3ZAnoaPA/mrSIkoMPXGN6mgkjUuloDAgrgXkZQt7l86zdmY9jXW0d2G23MHsJKg2sCkdlMxpT+02k3+P0R7GNO3MdWBJ/s9V63xBLaaBXkv4goVp83sVGcBCUASOGEAFTJNaTYoqFWuruZRs2shUPM3JH+6sluaMW+nmy13AoRoTWZjM/K3lwT42CqitCpS0EhrSpIVPzGvpGucCEDGYC5gF66ra51IItVarQ9P9DQGlFdUSb2qpoF5XLBZOoKC8mGUDYvP+LQJuApaG1hREXw2AaY2xthViZn1doKCgJPC8t5gkAKYD6jK0ZddKT9/nzvjpDHfVsPSRRARUmA95Mb3d9N25hiQMoLLcUKHgUXOBAREA6mt+lX/iGTqe/oKLj2jCwcyXEQTIYjh+n9+DgAuAavG+IGsrDoMq/p12w+ldgpwCdCjDeB1nuz4hzmP6a9Kj+bimZpLB2I2/v3P+MeiorG+leTypRu4IIo3r2bSWTfER4ff7Y35+VO49cP1r7ACP0vSvKoNuW/jysVY/Cr15vhdwr8FuNAQBtib0dVTXHhOsKzb3ZwA9rt1ChGqNk4PrDxwUXGCuC0QJmjCKlaVQQVkKijC4FHV9ISZIBQ3ja7JriwMAzFIN1WwNBuDmADng1m6okLleAVaz7KOuZbrW/W7hHyA5+J3fH8U7Sid/K7e61m3RzLvLo31r3v8FpUAuGOEptYhnY8D2RtknupdxTGrai013XdN8f97wu5L270eu42aStL4sVCGQEJ5YJ1covh3L6ylg4LVYe9DYE+EmRXxnP5b5qLM0/fQyIgZzYDfS/Pitc3rsRU466aSTTvpt6QTQTzrppJN+YdozofUIHR40M3dQMF/ELU2JBDNVgOAcfwYZc7tDASf9qnQ4jD+j2z/xUOwMspxs/31cm+wo7Z+N3urj/B4dMbRO+ro0j92fmcJc9IZpvVdDY4xnTTNf1+K/tM5Sfj8ulzN4EsrrY3bq67wSipgmGU3jXgTkZq1di62UANCDEevMdiKQm1w1pn+kN5myPurjI/7+0W9Upap221IrlsV+E2he3XRs0YoyuTCBRHsRAWS+ud30bBeUQ2j+hQAAMthr4IG1gZO3z1AnoqT52+tAIgApaKFM4FDJgkLXABUVUigFvW6lWhrUTRYH0NwF/ZgZa2uBnpYCLJcLqBYLp8zlUqpqrwuDuaGWBS+VIj1h2w9Jd73Don7cGzcD3hsaKwivQExLgPg+KRPdy+1hBRlQ73XrAgK7fOwEwHcXBakrXcNcqIP3BuKEoEgpMHvIYBsHq5gmuvg2U3q7Wdrdu/uWjiG7UZ/S31/QzZSPo2X/G9oCIj4LuOnmnheZ2eQymc6d0xjSPzB1/AjtCTh8hK6erv25JvqRP9rfjRxHinWgvxmu7oGGt0D091COtwEM/VOUo1x/IxI34d4nOSKg1Gpzf/qzeavY/oHswOqm3MNyChLQm8aGe/9QALtAGkNYrZi0xiiVsQCRHwmjmECUrDZ3uEsLAkrVLzL3dZSzlI58FgPGoZrzVHUWraUCRFoGS1Mdr9v8fGd8jOO9P7sruTCEPQbaj8Lfpnne7l/fHqj96Pflwt2zpYnYYtAj4P78hg6eH1M/k2oJZsGmo0jb1UxFAvhObJ/3N6G84i7AmdYdiUa5385u5v3mieQ8KJ500kknnfQV6ATQTzrppJN+cYrzQz6NSOLz71xvDjKC5As9c/ylB9jmODDqO4jef9/D7MvldUbp7EfsTvSHwr2HbqX5q57jfoR6zVL3b6FHgcH9MLR5s9WsH69mTaLH8vm8958R43bso/p/Rm6P0PtyeH+5foQv4HF6Pwz+Flbk54b8GkTxN43XHXDdwe8hNAHha9xBvdLnA4ZpSrcWcdg0Y8XyKaUo+GqSbkQEap6/mjdnaWjsWrUcSzAzK4geflSVITnMMoQOIA/aw8m8t6Wnbl6sjmF300qeyjyToPPcfWtAprVUasHTcsHl6YKnpydclgsul0toESt4roBpoQoRRmG29lQQtQipr/EiKCKqJYfJ56kBq14Zmd5Ffw9DWIZ9i1h8IVGwIxi6BRIa6QwR02YPY/KaR4H6BaVi/mwLGadaQdA1+mFv1eh7IQYDBaqFjmI5qN9rBoOkojXGtawgelVtbAhI/L31FyMEESBm3l2aPhc2LXrJDTWM7b1+9rHrrcaDNnqvR+tOwa1fUjuLxPhjTgPHMlYtxwUQPgDQzZy+WQugon59LXFchbGy1s/NuIcWHAjP1N1BXDca3vsCbkeAZYMa6h9mBqrx3gU2xt2xt6G5hCCYiwm7BgVa6d+ciJj5596UDojMwPl7wfDPBtGB3lb+W/HzmHOfzwlvB8+Ontl8JOqa4tbJJT+ZNU2P8olzkb11ewXbGLdG/n66QF8nZrsHCQrbKf0xvbVdfxQa7Vh0AbYZPKcEkpPFUdkfRSgFFACro5beIyIOFAIoQGFSoSHUKIO75gBgQlzW88w65zOHFRUCoSwLFiomiIXYB7Bpqhe4pntTayBL1WKZpZNSFy0TAS4ERIV0PvZ1hHwu8/MVwUfwOCP2GXU7U96GlLehP+dk75YZ/Dua88TBF0XWcbVvQ8bSENm0rvsHNgE610SvNv9yCCCMO85uAUWG+yyQ3MP30vvaMpZGtun5+jK1h8dotvesYbzfy+nrj6VLNKTjeynfUupQlNgXyFCsaTbYEXAcyjjFe/cSdjzUhumMcpG+7/HlpJNOOumk70QngH7SSSed9LvRxMCN6yMOhqS/IZxsw2H/EHMInr9HWwbGwLGD2EfA05M+RucZcqRjcPL3aanTx/mvSj95P94yQz692wvKIqM2mIG2VAqo2p/5FDUMM5jbnj631jWnKWl22VJIxCiFFUQsBaUy1kbAqlrDZGCsuFlWKigioAoQU3x8mU1qhVdmuxbKwHhjnrrKLsF8q1symvzQIAHSgQaeo4PCvp77sl5QcHm64PnpCYuB58uyBICulukNeCCAoYz4aFvP3vqogCBU4Mhj7FsCdBBgAI5TXx32vuUhpnQXDyxtMFgIzGaBgLoebfQBAUQ1maSvUUdmB627AIPvuUq0qzPOBSsaSIDK1QAR7nkxgTTEWPjUL94PzMm8OgQwhn1swVI1Qd7FnsKA7O3QnvCj973EewVixjAK6khcR3O7hQci1FIcmklxlYPtgJQApgnHwZnPWu0CFVoo8HGQxrUluw4a3vrQGSMrjmmxdsua1jJc9HbN9c+gzABqeOBhZ57ipXJObyLFH0kD3cnbcMFtjOJ3oRmUy5roR6G3724jOPmtj+me7/vPSkO6c0V+Y/J5i8L6S7cKg1jHZsG7AWGO43XpQXTeEOngui4Y4eLEXTywMFZuqi3OZMJJQGMV4MtCe4UIdVlQ6oLWVnPhodrsPpWqf/YSdaqL+ka/QOcWhu5rfF5lkJlwLxDKI67/eAViv2Ek9vSY9iHsr0lpRo2ybYf78QewtyrmmX0WxKSdiDlfTOFzCfI1DWWS9G478/p4nP2653S3tXMBkLwu97Qllfne9OBCflSoC3EOmd9GszdlpG0LxTf0xkXnbtnvvD/ppJNOOunXphNAP+mkk0761Wk6g77pPJGBczswD4nOEsKePnlwieduzgwzcJ7KJNvzX89WegDXonu0Ct+Sbh10v3XeTo8fkj9ANxKbfcXdYwbM17u/n1n4t34XE2WT7dvy27+h1Yi4f1se2/t9dvt7U3xv7C3j4tvS+3L8eDl/Dzhgy6j7zBS/LQ1+zzcf1JbJ6BODrj+qc6wgroYPoDv+lDGuWrirgtbsADqZP1JNSwD1jeoMcQDgAggrqFwqCnfwXVaBiJli9z9qgNi8UjWRUsrg49S1yzg0fxFg47CmZ06vEFBUi5loYhnGWj7rfO3MCAaGllKw1IJa7M/9gxsgQKZxDhbVtCsFhdWvLJqBsdZ/tRTVTE/AqFjfhFCd1c99unpfdVO5qrEdexKCWRLoJsQ9LTfWLkjgMBw4US36uiy4XC64LAvqsqDWaoIOWkBGAwRojlJAhQGaSk2kUnWrAOt6RZOWFrudVXtA4zpjnPqgTWM5jLAPUWVIR4JJrpr3QADv6HXvG8OcSnIRAIr+JXumfUIgYv2mBg146gA+EagSICXy7mEohe37Su8rL4truKtGupl2t78/qJuwfRKg2Xb0FVq+DPpmED1Ka+nVbGcZvZsyI1/iRd8D+deeZ5sZZCF0rdQAxK0NaTMMxgdfCwx/L9m0BMDaDT+PFjrQm3neg97bft4PZ1CUTgF59D5Ung5j0ea5PqWdMuyDbP3u6KSwB1rJGP5oPP4m+6QsrCQGWqsFjIb80RYCUCoq+vTBtuYzCSrc97iZytabDq4XwlKWAOhFBGtruudorCuWCNamwnuu0UxmHYdKVSspUi1z3RO4YJ+Qrq2luHWYGnOuCLC2K0yPHiSCYpMckQnAgUOLWwsMmNkChD+fFUUPAAAgAElEQVQWa4tYVzejd7O0pacyPNmO2XEkz4Dn8dclkTJN94K+Zrj58nh+Z7617Zauz93UgFmXQVgWYXYhB1shrOtDIz7FJXvPvmYC5mbGbRz4erPTipRrixDI8KDxfFze4io00UvfKWgF/EfD1TK2C1uZhj5vglpL+nbGMmzWsklD3fcW8drmUqQ108NtmiNF3Zv1ct9HXvn5/OKkk0466aTfgk4A/aSTTjrpdyF5+15/Pqr2p8inHQD9cEQ77wYN9GDeH5RJ0qFFehmYJR1s7rGvfl96pI+/5dnvEfCcdt7f+/2Usn1CejmNbRk/lvrPcDY/Nc5P+hloDzx3bbFgtLk2WTAbOwtNNdAJnNiGAXTbn5rv1rArM4jdB3NnfkI8HzP7in6va2MBivoxpaZa7RwaxcbodpOrIqaRnRbNIsr0LrZSsoCNka5MREMMnUE8c5pjwaWUrnMazeKLhctMRTc1m9tzaCOqqKTguft+dXOx4Qu2iGrBUQlT7aLq21HEaKtUbBYBmvlkVXVuQARlKahL0VBJgEkgyphmBSqF1PRqoW6GXyj7+kyAu/VlcfP9teJyURP1bqZ+uVywXq+4rldgteJzZ7+LSiaAoCCx187bUUTwunIoV894gaYhvV2szQsBBBdQMNPupKCG5kZg6mvWYIXA0wRQoWnlcSJp/PgwyQz2gVVfXAuzrw5CDiwVBISavjvX5HchFP30apQra6j3HCkx1a3f+vCGiGtu950sI2t6CqqQAeKCNYWbNdAHprro+1swjsZRrb39fXRPdybX8B3T7GZvfzbyEp9Mpy2g9xHK42qElsYw9+nte7YdaO63okFQxtdCF2xjGYBzF0ITEXNXYm5JbK6qZHMqlWFOZROYYd8zAGrdpJgbETF3GdzQqIFohQsdsag7ELHCFdK9SSlmKUe4+0FJQnmFCIyC4sBtIdSivt3Z1n/GChLGYMzc1hUXOAMQaysAMyU+j5rHRucI5OYn9+3P3c9hBG9zufbOdfP1PPaP5nq3NjHLFmC6J8klofTe9iCU+CJTmts8bNwNZep3sQ/YKW+sdTvvUunurG5HMX1M60UppGWQbS9vIgIDkB5ltH17gOg7UT9z5fzs9E466aSTTvo56DzLnHTSSSf9YtSZxNNzTMccSc+kh0F6Fqa2IkxK3J6LP/dD3XR6yYzXrLXmWmVzGeMwF4xQBQ6K8w6Fd+sWxcKPQT8SU+mIufYhygf/VNlHGcX37t9dmDekK/g44HtcjwwiUTx6q0bO54+j96W4V6/3p/Yz0+9X41+FXeRWU4Htd7inuUn2T9dstkScceuAXgKNFStlyJqhxa4ZTJZXIYKUAgmGdgLmCwFcUCsUCCZSjR8msGk+F4hqNItqijdqoKaMyQaApBiDkruPaK+TQ3vUGfPeOF6+aCUDQ8N3u63HznCP1Kwt3GStA7p93U//ZQ0hK0MpJYBSR0AvywWNBQvM/DzSSKTenk0aWmPw2tBaw8qqkXepi/qmpx5T+5Kh+EHfS1AhSOkgeqVuStzryJm5bWBEKSXG0nZMFYB4HCIGxGsNOeKIGVTtexi3ABCdtiUTMtC0SwetaYYWNBG24cjWJyxdW3IQbCwqQBDbPd+HIZtJR7zMfaom+Yv2f+kAUvd5LqgQmBxItCOZ5n+pFW76nUjst39bHokB80I/wh0OoIubsDfNd/ENL1RzrrtpV9cM1TJYqYMHWQt9QTfZ3nPr43Fvj9VHhQTwkcGLOa187yB6fIsxEE0oIDb6P/Z61AA8oQNrgp9PCx04Bsbu0bxyZksJe+GyKeZbK+7xPtu/laPYeyPVa7ctLab0tqPXQvoWd1LNHO9+ESIDg7P2KzMaTOaMON6N+wqGcMFKBdXAP52SirphkRIax9ryAhbVPmcRVFtfS602f7O6ZzG3GAq4O4qKZAWk2PzXtZU9b51/CWpxxAWVaKybSJ9r3cII3HqOndh9uZDxHO6weaxTkkfY2/eV+1/P3rw70eEAHEf00XdzOM/3JXM6T76tXhcTnmjuG303BUGxD017lKa3tj/bLW/+fvfXH0H3xd6mdPKHTAC46d6pmBn2pXg8DebeWSqNZt89mey+BuxWfaY6D/stX/d8n7ozB8F8u0fFx9nnqO925dIIYxyZ7q0dNproKdysPHDSSSeddNLPTyeAftJJJ530i1Dev9/iuW4OTtPBwJ+RzGGC49jT4C0IHkzw8eGgMTWb7IrQKRoBwailFOcWve/o+jn0SzGI3kAxXn7XBtg9ym+ZZ90Pbwr9E2qTPapx/ksyTn8ReosQB/2CPUk736fe74fOgIbfOTsyg6PKC5RYF9m1p7lz6tzEuoOvtVYQs5lMTczrAhAXlCKopSpTvkA59EXNVJemwCCLoDQDpQzsLMV8TCZf2ITOVA8GO7pGdxb06W3SbxgJTHW/qdYyhBLx3CR7ca36xpDSwKWA2UDjokxInz9KcVOifU58ugAoqkktXpZU7iiXqLnadV3RDERv3FBLNdO1PVkWQZOmQgXs+sFKpZpwQpid7xrQ4n7kzeRtHx0JaPD/nAkeY4PiTzDujzbmaw1kUEa0m/zv7ZrNmJONIzdPr8IC1pdiezFoH7gutFh9WFSwonFT8IVbr1dVM8G54WLP5v2P8Xkmd22goH5nfhcSNNdspKLlmtwg+NjxdnYQfcxFTHvegLu0efX6uaWEzvjWQFcBLs787tHU77z9OoietdBv+USPesc/6b4XeRDgGZ6jm95FLlcqZPZxnn2iB74u3bT9j0avQJis/t3oVp33ZR+2EN4emJbBsc+ht/TOmPt+WT6/hD8KzVZrdK4hgDnNb5uTMQAxyyUFEAWfi6/1RKBqLmKAmPPcLgkBEKoAAcXMXhcmNFlNE12FyEA6P9SqFnHcooeXAFAf5i5Up25RKlwcSafTHl5YwEVA3Of8vW71HZKvV5GOz3lEoMe8rt0lmX6P3t+Lf28Ez9SB4AzsPnaMKzb5H+CtsQJweq+2Y/bL6u9jX5TSKhjzyTXL/URTGEYyKe/hnf8y1WfgIwWTiIY1a8zzmEIgEwAlk+5jGIn10/dJLmXmz2J/5Q190KVbntW495+j5vu909Be2wz8s5NOOumkk34ZOgH0k0466aTfhWR7mBqkZe2Ra50HUD6D5yJD3LeXIx0+JZUnMwtFD+4Dm/nglDofbH5bSic7Qjr4Dsz+/eefmv8OzYfIeRzuvZ/DHYVR9tIOE/9+sex9Zl2/jfbqkdOiqU/msPnT2kvvKM/30dtieugZIPf7o/Y96q/Pp/f32bfI50elR8c6DVdHTOG35fw96fDbmkF0H9+URrgjY8bsdtOkbjI8tGuJzTGlMqhd41aYQ5vYQdBimuS1ds1hB9EdCNV5urd9KRSgLgAwMdhVeWHm2sExsRRRkFKBSSQNZYq8Qmvc65gog6TEAhL1pc7EyaR5b8cQCjDgupSKMUFHNB39lHEhmu6XpaIs3awtobdflJcAbgYgLBlA56FrGQoaEzPAJbQEXbahEKFQBbkP9lpRlxrFco1tMvBB0srThEGtAdcrGrMBGdbfhVCkoNSCiqrgsPuij/b1Sxs7JKhUTNtvIvLmNv/uZnJetcaNoc/qQsCHr5vBd4FEcfP/pr2oggEG1AhhRbP7tIblsvbbfAGPIGCIGLBPOs5UjoQ7uO11IXNlYG3eoQCdd9j2gt48uU0EFEz0+MJ9eNnvsCYrlz3AcBHgAhPSFIrPfKhS2i/1/TAiH0A1rF/29tdwwYVsNn5vFjIfx5O2eQcK8h7H6urCKTup/YhUoRr8F/yce/X3njPm4RSCLBNgI1McxJcwgl17AM5+vvNI3F49Rh2w26bTSxbPfX6azCx/7/X/a1NYqEnCSpkcZOTCYG5YRS2OFJO8U4s0Pi7UNomu4Tr3cAEgjMIqLNYbGroGsPtON2setWK5XAJAZ2FzA2MjytaNIgVNBAUq3BY2Pdgh9aZnfjcNjy7QFC5TbIL0ESE2kfp/QntjQDZt9Lb2vomRPhTPdk1RGi/1eN/jYXijxNYYLtCVNbjh93R8fp1Lt9i+rxsN8vOpPmArc/4i3Rv53Cb52VFb5PoV8ny7IAdIxi3a3B4scS8QlGr1FV3xuKmtkWrjzd0SeL48/RJ31wfbAhOAETAfXu8pb3i6U70/k4Z9wUknnXTSSb80nQD6SSeddNIvRrcOlMM72T6Lg8Bw6urcvDiYOfN7DHGbwrbmQRmdkR1MiH6Ye+sh+ddm1WxpOOSnfpWprTN4/rXa6CjdeZzdZwDevp5/vydl3fKBYT+8H1lIe5L6e+3yGOPlpJMep0dA9AxTTQ9+Wjqq91YTPTGngQR820NyLTExjWYGQYFZVIY01UJ2TS/mNmh8xXeegGwq6vd7MbPjpRRlvjrDsRAKaswlBNUka00Z8mwcXGEGkwBSIMW00ZI2sIPbtVQUA+/JfFVP+N2oqUwNhQmrqBb23F7aRgqeq1CAgsYwrSDJ+4qeQaz1GyAdQF0WXGoZpsni2ueWpwDmc1aBhbY2rK2Bual/WKj52SLeJ4LCK7gxiLTdCNR9mhOBagHVglqXGAPCmgaz9qu3i7dTaw2uod64YVkW1QIkAlVChWoPCqv/WbG9UJhEhyTEtITpeQf+N+SahdOfAxsBVvufm/oV/VWBAHRbq/GZi/mT76Zk30QCMBNKUQEOVbakqC8biA8HWcwigra3mibW9mCFBiw8e/sQMKpy9+/Bzbc63qNZ7qygXlcBRCjKVaxZ3eT4NaEFA5N8Wrev4sVKM4y4aJ5/7clFQ96xxTdnIPpmZ+ObNn/cP1Kdp3o4+YHNuVf8FxYAr/j3r7CUfIh8LI3dNZ+iPhOReQ/U6LSzUf1KOf0sNFgQmSx07IUBepsUBtrawOrfJFyAFFFXJS5c4Wds9vWSASoqINe4dQEqn2NsKlAT74SyVCxPSwjMra1BsNrcaHuRYlZApEDcyQIn0TBuajKcxJBbsumzh9Ezp066QjsjhWxe3mtHb8PHm35Db4k7bD0O05Hd9516baYeRxnm+PQb0/x2B3p074bvXfDKIfMyhBvT6yvN9sx8VJ+sva6gtMWwSPcs/8WSvJMXTeHiX1vPibR+sReKwKJjEyMoHpYeLO5wjyj8mKlsH/eSfJx+9bnupJNOOumkkU4A/aSTTjrpV6U93OMGYEdA1zbaOV265vmeX6f50JRNTGr88cB5dOggAVobC/HIAe6k70vf+xC5GX+4Py5mRsdb88t5fSZ9PmD+WArB4JvC3zPR/rZcPp++Vfv8LvS7tMZj5tsRgF1JTGrniirMxyApqt1VVANdArw0MJPFtMaMfC21cihwqwBiq4xaq2qalwIYKEggUAFUN0jBYzWH3kyjtpmGmZaNwShcFLytNRjp1YDKkoHuMlbezWkCwNrWAFMbGohNi70ggHQ3A19IfWJ62tWEAlS72Hy9T+ADi4BaiznbwejWminJjXsJ9r6jxPw1gLg17mCzAQkCRoWB+EwgYoh6vAaBsFILJm2lApgZdxHB6+tr5JHzins3vQsXhCj93nyBSwVI7F5KB7OTcEKA3Zw8oRvA4q5v3F95zj9Muk/UQXMFoVWQo6n1ABbzk+rwbgexizHsuTF8uB6tk0eaXpLSLlXboFQ3z48QPog0CCis4yl8lhswo4IA9uvccDGtRnSmegAjLkCQ0qAUZgQklK4AqnQT4zViqLZ09nu+W1/7u1heLZ7nUiaAwlIPGEZ6aAQA9YiI06gJ2eu7D9wd0WeAWI/QX/g3FrwVjv329NnttR/O5hQRSHi+6ODkrXQojU+9v3eqOnp3XBNK/4YVksO0pxEr4/MOBT5Szp+cslC5dOSuA936Xn2X9zgNwCIVSf8b/kWTqCC5A4aNBYSGUoFqJt2pkFrQEJtz64JlWbAsl7Ayo+tB0UN2UU1gtIZGBeR+1926iq//BEghBSlLFt2zedqBT0p8AU/LAX2L1Y2Rp+b6vJYf0qLhyQgQz5RNpG/T2Mvn6PvU5655TnMprEHdx/3mc/DHdu/nrrA1MLvoULMpkYBbAnA+jvffCKhvZ19J5RVCCNd7GgVkomyxVKU6I9Ysf+z8G6Km66kVms2iYKW07omEtQId612zXphjfzzwgHxMpe/rPTTHHLKg6X4nwoYt9QtPayeddNJJJ3U6AfSTTjrppF+Y9sDzI1bKEXiew2e/Ths+ib0IhjNG8PsWEE6bfN92tN4cht4U+6SP0IApfccyAJ1RkMfnzCY8Gv/3ws8A/UPl2tFC+cCZ/6STTvoE6hrm8/e583F6GDOD7uQAXzPT7VTYTKYznKXo/zVRn9wOqkNYtYA9i6R9LgtDZIHDeQ7ohd/vAvOPTgFgB8gha9fAFYFQU4Z6qeaTvKAuFbX63xLPe726RrRrCjdqwKppFipg4sQc1zaibIrb/VrXRcH0UsNEfQZ9lZGaTKMbU94BdCkUZuOj7axLhnTivWt2a0DXgI8wBFRSH+wNBQ0rijl2JyJIMV+lFZAmeL2+ajpe9kJRZxVI8P6jIUz35e0CEBIAcbSvAefczCx+YzA1kDGsAYQ5foH5rd3R/ve65XZwTWixZ9wcPO/m/gGxcVdRgNBoLCCs64q18bDWlXnhiq4fnwsL1nUFCKhNrRxUrhHe692FLtRSAjNbe+WvJ31FBuqQcfYllSHKkYUcpO9BMwM8XztYsKIzRHSM+/fdTY7f84FOULC9pGd5PxIgwQ5wGXsWsfoRQpvcQ88CHGMuH6djOPXzyIULfkfm02wi+iMpPfb8Xj63IfH3lvIjcX9WCsGfzdlZ+tpoTzy8hmWgqGAVO2htDagu1XXuUi1dwIWhrsxYgHD1gkIg0Z0C1ara58uCy+US84ZaZClquARQU9lZaMvWDuZmgn8GJIICoAd1gT63mOJawEK9/DF3x4HHKpV5A+n30/tj5y5EmY6R8eFVPu+9aUzfq9S96XvnPlgzeYDEpbZ/QTb7ntKiPLd3oTLaKShNSRe4yXhKuUr8e6+qef+wd47uwPuYZn5PvjdLgLlf3jLZfovuzowJm9+bVXM5T17TSSeddNLvRb/jGeakk0466ZcnZRKSAd4PANciQ7A4YLiUeTJV2sPKbtKtsJ+8jdnXmZnb9CObyMtNiDkT9JYGbDAX4tnHjjMjy/Kt5Ayy70fzgTYOeUN/5RD9OPtext4jsWbQeY6Tc++H+2OwOx+9Pfxc79HUXa/prIE213xbtuP7rpMxl3+HMoPMw8nt9vuaYynXOjP9j76343S+LRFutPHdmL8fbWud9TEphdtvHzXvLdg1PfKGEjjoOZRkJ8l7Fke25cvXZPhgrtc23FtJv9v+4QrU5KoCv02frdLNsU+sWBZ0f+ieTMlfnfribtwgK7Ayo15X1ei2L7IaI76aj1OPV2rBgkUB/Fr6mmvluCwLlotrpPU/LysH8KzRog5m3v2v//yl2vPOqK8EEvOQaWB0AaHU2rXMS1UT9LVguSyoy6L+rQvZewPb0cEFSX+qDa11XJtrlPfODAEB4Q6upn2JwHzKWtrNzKq3tYHXhmtb0cTN3kvXurK+BeVxKGgkYGnm396+FbKZ3/ZZBAfPCStKF5pImxzdSnVBAQXF1ay8AuM6ptgELBo4tKkd/M4M6M04tTKHYEVodFucBDLDyq4CHgJpDKECkaImfmncT7RIx0Bgr1Zaiz3PzvBnUFN/7LPlAe/3tgpWbjoersXaxb8VSX0tkVtm/+s+UDXUmwkiuLCJ5lPcOLG2jY+T2PcKngRoMN/opiEnEDxD24dhfs5h06CkegvCOlOhZGGBgBKCDfb5wIEOSXXo4wwQdzWM3tppHx2xHOAYd3wlNvR9utp6Hx776h5loCRNgUMeMeM9OMkKYDYg7gsmfG1677JwA4c7CD/FKON54Tje7fRz/4zxZLr3cXOwzu+mvFeOPv4I2/xpqtBxO0ka++P9+EX0q2SHYijfmEqKKzmkDOM1LMoA8YH6vOTavJK3PZTSmoS3EM/GOo4WQggg6aAyAbrzVoGp67oCAqx1xWLWTIq1XyWVmpPGBoATwkRIKepfOgS2gLU1fHl5xbUxirlrEWGQaZ6zMBondyTczDJIn83d+kt2mZL7yZtFXWsIRLq9DYLnCbX4wg1r40n4S0fN3tg9IrG9VG5f35v18T2m5sJoEFYhts1pz+dr6Zrb6e0tivfBa0F8EC6U6AJcAigfxY2xhBl9CgEJAKrN7+nABNdM0MGXXbJ1x/eifo4s5EJaaklFCN2izaZOt7938RnBu75vYywdA9VFNvE5fWsxJizjrKFfqM+KbgUpf7MEX68Ftfh+bvzOXIAjj6VwjSFQd0oAhMZyIN2PM7G9mjXf79Ebgp500kknnfTz0gmgn3TSSSf9ckT9WEgYTxMzOfNPEEzkbRiLx+7zU6CKUcY8RDrIkh5Y9vho+VDopexpiDEVO2/h3kFWUnqZuSM4YhHdp/lw9mgsAF0q/7tRZ5RuNSH82T7TzsfLm6S5D6q6lwIdPM/vy9CL25TGg/+jYY+f0cHvvfBzHGfW36sjgE2b7cW5d3/SSZ9Ft7Ti6IDh9CFOUQKXBbZObJhUE2P6KKkjIGBmYr+nnBtyDdj+nTMRiBmtFEhTBjQZ+BymvF37SxjNzVajs45jjYa2amOByIrWDFgSnRdrqahEWEoFF9UiVzPqhCLVGLilA8KWOhEpYH5RbbSnyxMulwuWSz/+qd9wGDihGuauwVZLxcvLazSsArAFVAQFApESjNtqmubqW93DlQE8R9H11dvJQfTUysZ0LyiVTDOO+7hJncmipsCZO7iqzenlJDPdDvXrujLauuLl+hqm3p05G/lL13YmUtP3uxx+1yo00ISYAFILBKqcb8CrCSZ0gN/BcOn+yKd3CqgzVrNYwBPQFEW4NVpzukOxt7ECdAcAadre1tZZrnIQBNiFrOK1xdU6zfNItlqgP4K1tQGQykBL3qM4OB/M+WC2J+a9lb9rkJGN1aQhGYKgPV6FAhmv8G9Uga0CMvPuCrR3k+59/+s7kgt1Rr0L8nShUEtXRIGOBCTo14ekQjjucYb2TW+0fN6c805IejnmNN4opDSfDTZAep/NHiLXRC/oQHo7CPuz0970sQWrPkZ78bcj6LFcPN4cP9/v7YU/i/pM3r/rboviVi1kiCeY4495bEqeQHS9tbmL+muNFSfXgbYuYSjCb7LLB3SbK91CTWkr1lKwmEuX6pZOSMBUUMnStPTVekgFigrbCavFkRduwHrF/8/eey5Lcutagwus3UY6ZyZi3v8hv4jvXplWVxLzgwRhSGZmme1aXFLvSkOftFgE+FKPg7m8XJAuF/B2LdZO8oaNGRvnssFPxh+bVmpJ1FW1GVeYAFQN9lzszENU3NMlgeqms7KBMLc1vi+I20j0IeyGyUbc2jFK7qnlR9+UdLRxC624nYsuSui3JROulB+RzAOgbgYBCmnf0hRlGqz/ZA2vB4CU3zarduOtpI1bMLGt2rberlqCpQBCz27aAxl/3H5DwRE0fS4Y3eyabMBuQ6U9U75sejmsJ+y/e+asdVo22IKqpRdTwSUeu9EPpnzGy5Sn938LCwsLCx8bi0BfWFhY+MXgJvQDws4uBkSbxioX6sJNhIxov5bvcLu161pEFqF74BaOmic9Y+r9zAJbBXr/PpRd6YMFpvu2I9HPM+J+zM9bLEJfK44mC/twoMmdngN7q7Z5H+rrYR7PrSn4mF/n42IkJv98OCIYSQYsJzDriSAx/a1uNPwMxoUZmYpGOuo1OBdhH6uAfCw69mlloGnLMqp1FelgigprORedillVEQBemOo5qVkFpYRKoH/By5evRev8cqkC7pJ3ORN744xtq9rQXM5Pz8wguiJzLoJ3ysWCa9Usz/mlaVelqv1WCPTUzr4mANt2LcRAPRudUy5nTl9SUcJMQkQnJLoAqYm6UTbWVYs2Vusvc7M8Q2LmXDR3W3lVzXPecN2u2LYrrttWNJKqRrqc7W6Fx0J4g1h/B3VISIxiqr1uoqoagESELWeka02vyJQ7snzwDPU+m/tDCi6+1DPTbX3bB7W5mMjsreA71tX96P18rlmGANpkc0ZQeEJfBehX+T71+Sy+Mk+lds56K89B+g034e6tOw7XNmYiVBOzwE8GvrpRdpK/9lvLgQhyrrtsz8nG14j+iGnyV/sWdW7Fa44CGwqBTiim8jPeXyP9NRDrnO/99/1MeJtTs/iR315TN94rWVrqmaWRyLiczS9jfn08Z+rTrHSOS+12l2+GWnxd/8JKO7azpjNjS2UMoFTmEhuX40f4ctHjRC51rBVT7ijHfiQiMZYCpASm8p4J2K4bfl5/Vs3zeryHWErhmOCSUiEzwaga7Ob4EYgJePWWwW7OY/M86l/jOwD4L4D/vb2UDxF7aLstQ+Zctrbv1cVpHKz1Xs4A140Zxc1L1VC/1nEqkTWT3vcZMk1NUOsqAJoll6qgDmnhkuaEMjdksAvU5qmYag+55DqXgszHtP1KaXH0YNJuNw9IvmUa68ZcLvXnJRDXgnaGOquFgMslzNFbYsO8PsqSwny/Zq/Nl13+WOVdqqVu/A3SurCwsLDw62MR6AsLCwu/EOyCoE3yoxYS++fDZQujkev6pjyQOLiG1RYfdm2ys6oQAYEsVNgISTsJ5SBpszDF2S0CpiE+0YrILSPlg8Rn9VfIc0uiW1ErWfd3pOE1Ba1nhW633N8a/tTvyXq/sLDwPoiiPjXvbEY/L1ubhKPhEYDEVUu1EufEjJQzchOGch0rGWoCdkxJqsasoSrI9NFUTaSKFJLImYFPzGLDuQ3KRITLl6KBfrlcQC9VkA4hzzdcczlvfKumXCmnclbqVs6kzrWc0iWBkUDM4JxUyljLs5wBLkS4aoFftw0pC4GekVMCXwDGBZfEAC4oyvTciHTJOzMjMTWtNimLTAzOAKVCYDIADhrVI7AAACAASURBVGOfnOe6bRuu24af9Vz1n3nDNV+x1TPFS9F6Ibdo2W3ytVvQKj4WDTMxnVuym1o6r9u1bVBi+7dFwe7XTqpkXqTk+W0DS/N/k6YxYwNVIbWSC2Padk98Xu9N2fp0SB1l+2O0yU3eWemAUt1imYWyrU5yNe0fd3SOyuOLSRUD+Mpu2uRzT+JOTPaqoH5mvac9j/PwwcxJUptA6HXwY46VKIkx2z5kFP38PPW3h5DokpILfk0SXTAi5CKx+FpfpY1Jp1xGRNJqPG9+dB3g8y+tbT9VPL2KqYpjRH1LswfoxwhpecFtdNf8T8rbPs0o4xio9MFgBglJnRMyyREYRQf3JclRKQli6UUaOyUC5wx7/no7+BzlmJifP3+2zXNwVlzM9yOfTiHEM3M5/mTLZaOdHO9milg3h0m5qKn1s3jdNjD4LjX9QkQP2+EgUU7WIs+MPETqSqsu0a3tlwfptaOEHkVSUp/AWvBh/mo12518xU4RQx7Kay0deya6gs3cFK1M4lEhMlbmLgi/jf+e/iJnxuWiG/7i8TBj8lwyyTq5lhfURnXfrjk4QV8FXrO/XlhYWFj4eFgE+sLCwsKvjJHszS4Kmhv27oPmuf6qG6uBTiYYlgeDNBCAXE28N3NunfaQd3+0OnmmEOcR4U/Zxf3OCIt0+2nt89fCLHz/Tan9lfvUffU9Lao+lr0q8tp5vgVFBLb/fu/+1rjk6hGN82ek5b5wP9KX+3w4X3pk/n1+3JOLkRBOzoduzwhOuxko/U7RtipngRdinqqyOEHMUWY3VnpasoUPY4oTGr6Q3ahnrVOmZnkyZUm3lYoWyWUzIU8ljI0z+FqI/utG7fzT63XDJmZdWc6PhgroTVpKHAS6XLoa08xwityRuZDyVUM3ITUt9O2yFW31y6VoolMx+05yhnQlA1jCyqRSaQCctyLI37aWbjX7LZrqXM3T/8TPLeOf7Yrr9Yq8FY10a07WCp65DppFKzyb6YkdZcREONVzZYvWH4ToIAK2s2LV0WRJCI37RLNcz1C/yU/7u3f2p+ip9ZrplvAtmyJriFFS3uTblQroNj4AnEtrYHCLkZHbNNSn108625aD9kw3JKD+StF+BeFHDeMLPLUopK4tip+2P6iZSqY9b+jH976llxPbY0svyU3tfHQbxxi6DdLyHFazXTYi2JR4/cSTIE/0cLh/dOTYUDYySD4u+Lwm3WO7iG+kvruNIZiQegPMXBx91ZiuWF+O4rPzSYlryK8JpCHk6P8cNH2zEtUc6+bgmN7+ucC1mUA+NjeTjTHO/cTz0G8l78oQYxoRlyNhUs7lPaWywYsICRkb17OwicGZ4C2T8PQ7MDMylbnDFQnIjOvPK35ey1EdQnSX5BCQ6tdluAZuNXy5jon+nGvbZ5X+uBxfUq3D7BDnqqnsv9MfU/etyE49H8GTun1PLENH7OPYuRuXuWiwpzoP2GoZJOMPwa+dS22sVn1iPPb3pewexIaimX2hMifZWnhU56d6dJCQ3qMyEos+1r6Et7xU6m5CKhsbWzh2JLaDhI5Dvpx01GKgbDoEcK3zlZc655RNcNKGZA9INuO4hG+jLFO/cmHrt2R8b5PsyALVGQzb3s2hLCwsLCx8BiwCfWFhYeGXg6xqg5heJB6BsLbux+5YTZKFd2eXGlTD1yC5W0B27k3SblvSkPl7Ox4VBr43ZP0o1xa6lhyLGx4ps0ioRBcUvsvsHoP7cdhGYLMb8z5E2HAfxv5moY3ycet9tzAfSWQWFhbOIQjAm5UO04nKsGcbWxO0NsFyCYeIkLiKB5vaSjbhWXG/xKi0hJrYleQV8huJQBtwJUK1Wg5uRLYR1lMlz+pt0Rgrplqt8DRXrfNCMl/rGcyGdK0C4JeXl6phTU5YSURNSGznBOUyS+S4bkWfNBEVEv2yIW0XXC4bLltCSoVEp+1SCPZqbpYIYDE3X828c/1ecn74dr0i51zIBkl7SxPjei2m27dKml+rNnrOm3M/Jh/Cma1ehbcKY8s3SSkVCwSy+YDIpUm/Dbn7Nva15/KBREgsteNGcazd+Hgjig+r61bqZnbp6Gkt5tA2rGY9zHhPkqyxKWhwNT+PooXNLUT10Wvvm5TIcQattlOdb9Y2XUwb4Ks5UbUQ6RnfamM3Ps01mTD1W1HnwpcMuSvpX5InG1qfYYtjJpYfPe/rMNf6qf2OaNhpqnpyY4IabauvrGTMM0EYaSz+WpjVDnT3M6prjNclbPbn2GOM1xj6tqfV6ki6G54dHW0v1JeWjqdjfVf7lHpSHCgknGymcxuuyDpxc4hoeaPTSK/dKBOXsQyVvGQgoxDmGQAoATljqx0NE4EpIeXSP9r9CXoOtpLquW0U2sAptbHs53bF9fqzzU+kVJs1lVZMuvlGxgTRKLfHfIC5bXQTol0tiNQwRB19gttq+hhn/bdRSYZktitI8tW2jlWjNdlozRufEaMzCnfX+m8Qhjxvow/bOartrOWHnN9sArOtO2TfJai1Olsu9Q81SwO2YUi8MVTt/foNXRKOHXNHZWJaL9l5u0QRCk2aaPPGZozs82plXGZKporpscJRf/u6ffLCwsLCwntgEegLCwsLvyCcrNfKMb1MUy9koafSUP3NsgDGcOUwWnjZC1nsMHTxPfI/zcvB+xjWv33RcpvM3IqK70cUJMS3fhk8WhRT534/bBpc9aLIM7ifPFdtAx/ePO7XEDizu5N0lVw9onHeh/pc7NWX147hV8b5XP9a5XNLbixJfmTGnY10ja1DVMXoEmDptURwbISWJGGYNKr4vycR5BRzebOBAc7IG2FDRuKMa0q4XC5I2xWUynnjtiAIqn2ergnp5z86tNeztXPO4MyqvR06TyHMt5xxSamdnV6IcDLxoJ831MxwJbtljEkg0FY3GVSynNpvqlx57b2IgEvRdi+dqv1OXM4wrxsASjzs0g6gvMuMa66/29aum6CX++/Q7gzR3clL91SZTDot+UI1TFvv4m+jK7JQEnZiNof1zQy/GcKEcGa+VZKidSobbXiZLWRMUsW5ao9pfFaebfMuBEy5riRRlo2WtTFyPWNX4m/keYi2hZO7Z40JkXjA+AHGNwDf6rPf2ttYGpoPHtwwyFjR1dhjOXOoRKlpiFfXJH3FaAZx9P17PfP2jHzeven4k6Z0KRBB8f4BXNBrZ76lCfejbJxo5mN/k3iaxm0dVyzBW76IuLAbq/qaeSui71vXVXadsL9iIPMXeqwIWiPZj4v7esnurz6NV7OSGmn7j3BWE32oqXpCE11bIdyV6zO49q71iJLMxUYXCGDakHIq41qN8pK4pYcSVXPsZUxnrhrJhKJhTihHmRhLM0DCJcl8wWz/4Qzk3Pri1t9Xkj0jFbL/kpz1tVZz65jR+jjW76BloZBaT4PvN4IfLffdtfImNLJ/1D4JWqci4ng2S496qJsjRIMaPt6jXMqGh9TmIL52y2/TVOei6JDI1na/oUvG7VF6bf8EMC7G7didiYNKu9V5ARv3vnWGnSfIvNVyEk30Um8kH1ud112qZrrsqZSjhagUVjm6oA3KAzsr5Jvo8BvWDyR+rRs2F41EX1hYWFj412ER6AsLCwv/BjSpKvxKAOW5CMMI1h2r7Vn2YcTFhz0ryy5cWnhshZnPh11M3ynv+tTg9mcfPWGjJXZvuYlAQc/6PBe3FatReH8uLdZ9H+lt+bk9987HG66mu7b3ttEvLHxaWNldFIIPtcXMPxtGM8PL9RxKMiQIa19GqGOrDTdooisp4UWTNhFF41qEoxmXXEy8pmQIaImzdaw6IKv2rZx9nieb2agJECWMF2Zs6VKCEw17qpuihhJG+DmEeR77eiH55ezzRsxLXJcL6FI00kGaNslDzhl524ymtuZDeEPZLJArMVs0/QrJ2/IMQ2jPxikajTKSTUPutIi5vWvkKFDPuvWbMSRsJS+EwJDNGMc9fFf8N8632P1aUXu5t3XFvnEktQnDpcf8TYimxU3csjFFH9Rpp89L1G63z9k/qK4YYOrS9DcY30F6XqwRnkey4y/JpWyIsO2kmaM3pnBJ+oI4L9W+wUriWylq45uM7QcjfiWu9Jxzk2Zo9bRpOQWXX3gN9AcmILIJcdTX/qpoX7ARNpE2NHXkQ8GOV4+vtUabB9DGZdtriAsbe0wRXEgSfnnO5m7kT907HnyiWW7h+cCxe92EJ1rh0ONJDLEpfUchzcumMCYgUwZz2YAm4x5Aqp1+BSgRiOt7VistYO2PQChjvx1zieomPLWgUvrRhJxgSHRoXSUgMZA5IXGxcENkNwao+KCYerdjIQ7xKmuaEK98f9VEN89656eCjv0hDd516zcO70PGbVmM6m87BUD6kjLJKBtRgqmQM/kq1ZcGbkMqSDW+HTFdJkGtDfdjn31i5snw33x2fILLPxfrTCmldni9jONd/akvShVsHS9C5UZvcsD2O9pvd+KOGOGjnePCwsLCwofEItAXFhYWfkHYhZWTSsXZPqNpnrv5ftQ4D4LwGFcL0kjCiqCOy2Z6Hu1l3sdHEx3N4IU374X7Vm+PaF/fAhpcz2I+EjicjecWPFIKhwKJG94d3fdvi4tnaJzPfX42ScDnSu/bp/Zzlc8RzubGKUc37op17GskEzXhYBOtm+GQjaBYtGMlQD3S1AjsWc5vVDrEjxmByB9kUIfvkpANGZSrkJEJGdmYCffht7xVAjnX87Gbli8qEV7TWEjyKtZnBvKGZISKSR3XHsiPIl5TlfozoWfzCFJjnwwqhRZMuLcz3XM5G5vr+ecxL6KB34ScLN+kj1xFvPU7tG6VlAkY+Bxlw0x/ynuntRjLoabIEO7ao+e2eZEm6d5Fy+/wVZfmnWDqr9ZRq8HGnavyt3ej2GQ+OUpPFXBXWbibgipGGuaGsGr3IR+WTDdp+5vLaevfxGHbzFDy8VdNha+dtoWJIWltCVHbEOjLOd47bXSbbtdrHNeF2Mdotoxp5UAK3INnjSLWZPtbap4f4V7N84j4tbqVUKgofmzoa5C+f7sVh0+i1rARFTaugTiqtoqWwVHvsefJDTw4q8k8wkwT/SHP4Tszc9uIF5bO7htLW2Ua1J2ckZEAykAu/Y9on+c61qO1eQ34QpdCuFcSnVIh0dvGNmaAMyhTsQpiOuGyWQ+oExBkMFLdmEdi5l3+Y9b7Nr7F2Y9C6pD0v2e+39H6O/aYsRcd98ul/txSA63/cdWpGtVVFnIRzfRQV1TjXNNffrkLW8uTcanfRc5EryeVNDI5ts+98rJtes/d6FpTVK7Vhg67t23jSZtXZJd/OXpIx/Pq381DaxpztajAAF1SnbZJBK7Rje9rptttHLwXFhYWFhYqFoG+sLCw8EtCVgRQSSLbd+Z5e2yEkaJ5LsLOFs5oqeQXWonLIk6Cy5yfvhaZhbfWPILxdxrBayQ9AbUy7AmMR+/23kfXlox6FHOBxzm/e/ej50d+DgXtJ9K1sLDQw2uFBTl3eMBmDCuN0FCwZkht9yIgJiGJLUl4acHoMGzS0pFyKMSq3IqmmaSMUYXVReusKGiTCgMNWSikuJg5z3Ieu9OoI0DCEQFseYnrRkhJ89L3lzXljQA3RqIr+d2kk6asohi3G6OIkEuyWjh65no947Waq22fqealaMmjkQLW/LedxVgqiE381AZFL8QfWtGpZdvKxWiUd67Z0vX6zARVRra2YZFrvbqj179xzyKhclZWFQ9qSjamIAcpsz+XXPz496N8OwqJS52O+zXt9/NNlm1Q+q4veJfPweNq0t1v+PgbgRwfHf5tioHAoGqKluQlqx4syQvWdiKfKaFuLtiFLcExvREtAYlGYauXzLDag4/Mme8hmCI2qDDqUu/l+iMR6q8K1nHgUdz7Tc4Qka+xvtLWYWPxZJtNw15I7a9scmN9Z0dQCY3dW0/ytelAIOLasRxh7DrSRLeFp6am0Zbpvl0bt2RKw1hiER8MBiqByDW+zHI0i5hQ12MwEqhYriE2m9Lq6GXZVjZlKuQiqDkjJKS6eU37tVoujHoGexm/bl1fSvSj3u7RPsdZTzFhe3Db2HNrnSfzS+F+9HsUzrn4KNzb67LJ0lqyOSrD8TvfhlqboTquu/nkXgSjr+jTP/Iqz61vG2+NHJRzm4+WPsC/L3OwEoLM86gFaM9Q12QN0+S7hfh4YWFhYeEXxSLQFxYWFv4N4HBhJMhFnsberRWGmvs9iGZZrivqnG+T4H6WhUdc2MZl4Hvloztr7ASa0iKd+sQ7AQ3CbXIjr6PYm8gdv5/lIgogHi3ve7XwrZj8baBxqcZ5ScUTP92pN4/g+aG+5TdY+Ch45lc/OgudK28mmlhR8N7chfS1YdaQqkE25wSBIxPyREC6XIr7sBlOzjW1QnX1yy0fRWuMgQsjMcAZTdCtCaam9MdAvWYkqMARqOa1zfyByGwcoHqOuRG2XrMlIU3hmItRH8yESgIAhZNMyJVEEMEoIxvN3RJaokJVZpR5DYGbmVYmDbxo1pWz3+Use+nTs5C9be7Dda7Um70vRUfu3xGapYP+DVBL+2JZkptqu4ZxMxoZUtJ3PK6YeeL0vdZ0R6gPQldLAb07PeMc+m3gTct3AvOWwjGU4Cj6hj/A+F7fFQJF0/ENwI9BCGTqcl/mRY9diAyuJJM0J6Uzyg+x6D3eQp94GkiTQ9O6qnOzczF17kjn+1T/3Dt/vEyeb5Pnb4WYnXvHm5k/Nt9dIizmsbN7PEvXTJP33rngGX++po18sHm7P4+PGFFqc7pPW21rTjwIg8bP+1QPzjSXMAcZuP9MdNnARTrGthyZVlYv2xnPVDaPXeoAR3Rp1lks+W+H5gwhi+ubOqblWli6DTkj5YRMW9PiLRvUdLwTTfK28UbyFwqVnR89Jmb0bY/Wb6P6TZjvCxv1vZL7CK2luhVbLJ5bixgMWZ/2KY194vS+dozX6v+lbrASq3ztDPNBGvfu9bnMy2r49azwrY5NG9TSgU1fav79KB3jivPV2uq6tFkLJ+pzvp7vWkaTH8l7aQuqwV7Ks9h3aeVG7Mq6TZGJgRTtH+2gzu2Dyr5L76196z1+FhYWFhY+NhaBvrCwsPArQgS/HB/CC+Gj8LG+dwtkp3nuF0f2qqzLZQFzctkwcEY3eB/hjAB7hkfPaT8SCrwFombECM8yT+nDtAJ/jUO+54g4v+Xev3luBm6uM+zX1/OULiwsfATM+vYo/G5ktxOiFYEySAWVgL73wsVRHIYIBDUTz/q2hlKF7lbwWoTnqZIBlcA1NrKLhna9MaRZtkM1AaJlVjTWRSutjPFN47ylhkUqWs9m1TmDJZGVuCj/JRS2u5GPZi7gBMykpta7nQqtvFDF+7kITTkjUSobACCm8+NYW+jKZgR28M2FuCgEgT7k2qmnqqFENa/I2c+TAokugmM7hhwR6UKg9wLWIgxOADglW/3eBHb+Mm0vkaB2mudDH4Nr397cOzlPfCedbSNLnJYCrV7sYdZemaSl9hJ0Ic/jd7UHM7g3pv3GDRMEtM0qZArd14f9WUVvhWdAIRnrCLDzM8M4np6jhDmP8/tg/RRi7L1J848A3Xo0pl/8UzZ/j8L1eOST2fjtieW3zHf7zWdWw9WvpAjSMyotCvMM6LXCmy9C10J10xW353YesKuJDl920h+I/5kmuvhr/waFJWMi1fGaqJpWp1SPgUllLnCR8UXIbFmuW9PpXElasdRS+zVKYGzNak0GIVFWKzbSD7E3v96st+Tc5jPOPLchznPm8s+6Cvk9X1/6ujAL46hOj2YD7hlBj5ixnZv5WG4eY+7tP5/S15EKHJWd6eLLPFHqCnk38aaVqV/OG2dxbhXaYNNEH83Bxn2aC1+nwa0tyUk+mi/tcWZ7ERkA5Twn0WvdlvbbpayGG7/erV/zOMcLCwsLC58Ji0BfWFhY+AXBddGXyg26KfxIpun8dpLp5jAuJIih53mKX+wvHOI7Fyb3bs/iFre34jXD/vywwi2Ea3JaT/WJu/b3vXBtr+wf/S630vFnBBfPgZapUCmpE5rfGtptbz42Pmu6C94+9Z+7vATPyIUlyRuvFIkmdVwFj2IGVdMRNcv3EhdpgTgGtnuTqBacmEEX5lzOTm2CxXrh0j4wnVoF9OIuVeF6ZYvr2dOGKCA0akHSjdqVq6BZ32n6zWwh63ygnbkqwk9Jiplu6K8QfAlIAFPy5mbtxj43XalhA8ayjpGEtrTWFLJSNhkAKCNxMvMgE7LRyJuhaWIFUt24gNU2tJSNO5xEBLg3d/hjjbkzuNXHLRsOrXD9NvHzJG5NhPcRzk6eTGO7tmKvSghWmw74DYQfCKabd6XjwkTBsQFN4xESkbTlqn3ePr/raQah+5l4P4sp7y+Uwnfilviz34/Q57UjXx5kCT4MeT6pchOe5vHg2f1Uso4qAYVhLdARh5BPFvwjn2eUb7OHy41n6rbe3RhxO3JDCDMu5J9rN5a0gy0XQ6zZdmpSpBi3qVs00U/5j2xgaDhU/Tjz7JTquJeQUkKisj0tEYGS77dyHQcb2Z3r5rhqXn3LlcaWca6ei06k1jOSbK6Djk461tvxD8i81XFSx9GMarIdWY9VMTKE0Tgo5SQWbmSWEfuBuDIcaT/vQUZa6Yal3g6mRkNIHs+2fW0DfhOM+Jf2SmbeBOjGzKZZXb/XpZWdDzWmORG555c6L2QUaztbPepmaMKebBtCsIzg3bbndfzQ9NZ0QM49t7MsTb2f8fT9hW6Ok4l5+ZVyS1SvuMZf+fEtaPSDZZ7KrW1xa4uYf3CLZ3X6CwsLCwu/DBaBvrCwsPARYFcnjwqjOlmZSGhCoEOS3Ptn5qEAVwQF5ILntv5vO58HUNGxeca9m737UZhydZoO7eQcjwuijEj/UXninfDLVX2qgh0ryyCzWH8EKn7R8Fs0MUlNjhQ+wMH7kQjmGbA0xrPwSGij4nrfOrWwMBAA31oZjxrFbCyK8d3duHwe5gRnnyQ2AmqJvySNjHQ9dny9FNKL9v34GYmtZqpc/BFQFMq4padRBlXbp8VjSRlmbHkr7xMV8+omjaLZrjkNaWb2WveuHnhRrppNr7EzwNmYeAdAxEj2HGkpV7FeY7XQCYUwIFKTtZWMKPMMamlm1LM+TY+p53Erac3WR82b+E1UTdymXDYGyvc2WY5TtVuhKan5kkperyWFBHgz2TfG0l/vN1hparbOcXDgyAtXyULsVutyoK1/ru8wdasbAIVSixLuWZqou3Jzzqq9+p1rqBTckXw37sOqt99B+MHSvtWd1tBaus5Sj3ZqFMKbLwT6eZHrJgfzJ68Z6K99H7SPWT2MpNYsvFlumDHUyB24xLxcXhfPmiHucjI72fKvfB18qDTMsLVf22b9yAMsk9tYUv5GC1pxzBRX4r/XOi9povYX7sqm2vrwb85vquXQhmMNLe2LWzcmo5uaqNZfIfoIBCQd+5REJyU7ZewSbXMU4hpZyeycjRsZ9TLXiYT2OUR1rEUxFZ9QSFcyDgiEjIxtq+R4Uo1mOV9944ycs55/br9l2EQ9+hrn6nH/TWMNmIVjyfM4Qtrx1gU6CCxOS7vvvZOOvV6MDn5HiO+aHYc6FskGyxhWnOe15+TDtPly81ZpJ9yq98BHuT/fP0nJmLZEaJtoAJ23tznxoAwkVmokvCSSNLHs7U1QfebGZBNwLLfmMmRuEAwGzrpwFxYWFhY+BxaBvrCwsPBmGIlf7cJ+/P6me9aF4FRz6cRqht1fK9AI7lh/rZA9CvUsPvqC4Rnpe2vx3kz8EDUizmhR3Jf/Jv7d8T97c+TvbPz3tp39mM++fbzeaAhV/wTpVVvL27bEZ5bPZ8bnzcWRSHB078VO0fIEOPZdlhaz4i0Vq/UC81vuY7rRTEA2cTKr4M6kFOCswrFhSHpNtf3OOlzCfj1w7xjgnIuQmrmYUG3aZIRMVLVwGGRV5AEQF1OqW9UUopTAiZDkBEziJltkBsROvdU2LVpt/lxeFf6rmxocGJYkLQHLKFSSyeXMcUbVENezM1V7rYSZXi640EsT4Mdy5vqxGolAogFVTzJ15IykNVcmQzTFyz1TMf+ekMAZTVu+RMQtrGTNYrfEhDGMlJxgSu0dkZi6r2G3NBWygegCgn6QXt/uFvSidYntEKzC46GQuAm0WyXRu9aWfDv29/W7h/lJbLmSllLXlYaWTzJMuudtOsvlbY5M3g8R8AOMb1zO5b6aNBAT/ia/qSGG/8Po5No8U81DpF30ecwxhWv/vu83yPmI6DX95rjd2oGm4d5Zr5TKBVb71JbXqD+/P77j1Oy/edb4HcOxZxJ7F/OFnG0P/dtj8OA6xqq11ofYjQXT/uYc5FgThteStSSZvLOziUTSR9WazrKprKafvYaz+Iwm8me5mGHUV8Wa2Xo4ghgWGIRg+guq9yTHtpBuIKMEVOIw5zpmoY6XGdh4a9eFUM9qup1ZSe6cwTm3eYrEK8eOpNp/p5RAqVqMSQCozCV+btcyvueSNvvNMnLRfG/x6jedl6vv16QdbIc1OPSlJ1xfSrKd9QQdZ3yo3XvjzH9j/8zWUxuelLXISaKmvWhO5zC3kLmRWkqaTitr+rS/1/6B8ULlIJ4NYoK/tDhmrm2l+CAZxAFzvrhpP+2b1u0tbL8go5gLQiuBWB6lfgE5mMXv+xsdr62LMr8s8ziqJgUYqqm/VYtHkvaXXAl3kuY1GEHZXAixHj8yfH2Y1ek27a0ewnRkYWFhYeGTYxHoCwsLC6+BbsY8mnr7nbxths/hvkh3MZzRm/BV2Aedxbf0cPiNr0eiFJt2v2wk46wt+EySKK4umNoqRYiTkciGwr2PP6ZH72XRmNrK5QC0I4A94X0mbJqZhzuHx5dZvbArnO0XF9/hwZ4gdg9ktq0PLRUOQrZCsBFmZawhjtpCFCmeuQf8lvEjUHd1q/DNYi4ePU7RPfEtLNyGUVuR+xNtS8AqOpi2wgAAIABJREFUKGY5dJtVONfGvOrXCh6LMCxSbYO4mWoQrGG5RqL9VNO+bI/CGNv8V6GaHbZIxd4ynpFxHmV0TZvZpgPeYcuR0ZRpuROhoJDnoqVN5UR1zgRQbmyCkIii0c2ZkYkrgZ2QU9awpaNx/TZp1oFmXYYlv9XJaAyV8UfI7TIX4Cb4ROZqkt6QwyxEgJxtXu4TpxYJ1W/CovJk/lHLsBnS7LTFlb34K9ekl+19018kX+tKnhnZEuQmmqK5J06NBpMxryqJcyNie1Z+y3Qpa+g3Woi5eybRqr+QTpMAedTKq2eWKz9fdEGE8bZ9A+dW27CY4if2sYnge2+bgZ1li7/eTUFiQkLRXLtAyRybAUsyi9a5yZiGz9VjKys7O/P5D9scY5QmF/M2NyoB+9xaG/Lm9CVf57Vue4zLf/ZVbDxXzIRR/QySMc/r/ZjNMF8HFK4Z4zrpXfTY93cevNcwTFwHTh6MXMKfbbpRFNpPiVsKfRHLiqdZJ/Hfl1uoyfUb5FuLJnGQ1GZpjbwbr2TNppMi6Qo6Il3Gx+aAitY4cUZiKpvnakdU9rddQJRrmmQDXG4bzzJniEWXbMy3Zy5msLe8IWfpgXTNXYagMhtLqWzhTZyQUtXkTYW4v24bMmdQSpB9aplkSC1pLyS6bPRj09dwK0f/hedDXPPb8hodjkci/Qr1y3IZ65P5TrYvj9MECu9dmkLo1uZI7uapehVmPdMwB8Otz5NMoXYCkrmtayjVL5kX5ZXOWyysHMdqtsu7OPa3VlU3dgKMXMcVItngImFVKwgylwXCxk1Is3FIIJWzMJqWeRMx2cJrEwR2c2oh1G3ZiNhNJ3YMcCrpDm1Wy7cvNBusmcH1GWF1ewue3gcvLCwsLNyERaAvLCwsvBJ6famde5mhy1rb3ktoHARvVnjI/rEsBpsQG3CaObJzWOPvp/HNDGddiZU1CNVVfHG/sa4h7MLK/ra8uihiWdgnUaxkF8h0cG9/dxAXzs73sX8Od8VgngnjjlUOy+rybpiFKADAG0AUIl0W0Cro5er6kcWZ9X0cigjJHAnV5cSHPgrhXDrmvzYFPtyRMK0Xro1CvR1VIxFe4/xMeKPaMl7Svx8ej/1ziwzeP/XPTEGo+3WcasIud09GuFX7pipw9R2lCLd6HWNC0UwUU9oi8rNystYG5OxYVkEdWPriYppUzWTX9HVlI08M2d/iT0jEVX9H+y2X4iYlrRd2XHWCPR+ryDe5CeSsFpJoc9WyYqDp61WBsmjbIIvmtURXxLmXy8X371mEeq2A6nuhDPUjkQg8g+S7lYs8cHmSkjETBJjvkrltirCFQ5RwgUhCEwBC3nIL0SatjdMiFHWlKc+pbe6yozQBSFzyy8mWOWmem9DZfkOjSW/i1PipFanWJB+EnuXrw5VnZPy0zRmmLmoud+YKvPc+jmfeH1AFv0LSAK0d6xwjjlP247OZy1T3bE4wZrRy1LarYZU8exKC60YJP+qb+mTjJ7hzgllj7hBqHxhUSXRUAp3xd5hfE2uoZbx2+rJmlkAhbVJrZPNKgv3qjKL9ybX+lGii1uxgnh6eRas1M1pc5vcplt+NKOmM5XDsxw8DRftVtNDJ7WoxX+nBtM5Sw8ivNlAfzeinViakvpGeEm3Ds1YexuHelsZu09fAUT8rtr2h99P6jJ3uxvck43h1xPZ9Qq69eZyB6wa6ebS56GebOYSdTSitrKunwfAd7TsnLcdhVmN30Aqy9pdcrcwQIXNGBmGja5u3yIj69csX/Ja+FxK/mllP6YILLgAzrpW4zjmDaUPeMpi3EmGu2sfJaECzyXG1eoLMoJyLBnqmajK79EAbX4ufLbf8CLEt/xUSvfbZ7TkcIZ3R17mWJOayGa1udGskvLEEMyxgDcGMv9K7p5oeavPR7nPwuP6NkikhbKEOi22Dthmuukw1HNGUjmee58lUUc423+pYcCEdN2ZtvLUIGUvafAa41BS2YzwkHjMHkTSM9pXLhhUOZSX3Mm5d6i6TsqeTiqWfWtdzG8tLzSsGDrj5zSayBDvvRvcxWnq3cvVS+6NrDX/LOt9rPmqZckLrWammV6QmQB2HUvKbR0231jZqQjZLah+0UelnxHGstdaa/MLCwsLC58Ei0BcWFhZeDTS47n9p8LwziycLoHrdYCWQkbU12ubcfuXsUA7hsL+WlZAJMhEV02xtKUNuRWwXyP3mAezcj97Eldu8/Pzvkbiqd+Wv5/7nfswvmYXnjShCgtv9qahH72VxGj+kNe9mfZ9J7uFXG23T9kk7F8OkGvcha776XAwq8CQU/3QmLpn7sHfPXAyfLbYzZvkXFh5GI1ptuzItz7R/kWELhmdL6ltnNtKNiVZY5WK0Z2BrOGWMM2OmPBMNdop9RL0ie++39Yg4UXuUUW/TJGxOI24K9n2zCjz9veRD/diUmzGSrdjTg5Kl+cM8oTm346dI+2IfWgWM3Oe/bJYwQmvS58aRRinzD1dR5PsQ2kYHIzCfjc1xLLPZEE1BmQPF8a/fPBXANv8az2x200qseRuNh3HbAFrKyBSLbHmwX4+868mdKYA70PybKeLpsQi1pYTpJdx805a+Ptd6VX/N3NaWS3Hjy8tUofrNNe9n8mDL7h8UzXJCIaN/Y0OiN7cEMONvk+4+zNmsIG6/UCIkSxtD+apyXIAN88wGzz24PjB+k5NBxxy1VnVD0qzTDYQvoEYyXaUm2S4OVLQBWcag54AHVxY7vcPTcNRSTTE8DXYEusWPwI+Z9dnoujNHVsPaiTj26eP6Vi2ODV2MS9SMNCBDonuN9yw9E2zf2k9bTM0ww4htn90++L3MkBKIXOcxzLrdRpBSIdiJUtWmppYW4krIsmqoIxXSuHyG0m9Zzdi44aBcV+sr2RCDtV/KXMOtOW3WcFq6lexumxTaNMWoAJBsyg/FYcJD02CX8E/UVmd+ph+t+3mjvDmaX5gbdj++Xbjw/NicTCyjXztijMI8AzujaeD+fSxKtelgnsVxXIJjO3XTcVtt90CqEdDmn+T82CNZdPNAGN1qIjP8d5y1SYKaaheFE7cltH2/Wjc2Ku0uTnUFCaBc3re5pEmLm+aytpUM3TARismX4S0f9jUHoIWFhYWF01gE+sLCwsKrYLiMae+i2GF6L4JDI2S09+K6XwwFsC5NxJSZXNcLcdalvC1W2iqHYNXZxYS7F3qM8n4k5Hj0/jZEwdiZ9Ul0M1oE30OePwK7mJyJbB/F7IuOF/n7sce69RjGwrkz6NN7X327Pfaxxvm9mIfwVhVxLkT9N2Km8ffrYSgun4i8779XcoaRqAjbqFPzIue2C00kYDvpbve036vs+jYeR+66FLAK5pz7mACe1avjciRznvX93yF+VWppnBOFe9iP5xbfszGkbWQYfI/9ULl78gyomBntKo6f9h+Q6vhQ5lf+3FZy93b2JvZmsups7aZIEVLDQeg89DOqb1YMbtvpqFX1Y8eojTB6PddGqhshf/zm0p7lXQnOi9+7b8AJP1BI9AuKSeQEzZOQA1Tz2utd276oz2nUG/TtuqRtSFp0vZve9++eB/Mlp+8enfhe0FskuICwzSbcT8NxgHv5P+OviyHYhW5k3k4E7Bw8txBmJE4Xm2tH7ms59x1GG64eBKFYiOgpv3NIoKqJWzbM+B4r1ScWcmL02XWi/WKmrMg/DZ4G4Rhv8ozLmvvCjExoa4mmjZ4rdZdqCJXt5LSBOAkD3gLlEIl+9+pGyPkw5WKjnqxWgU7WCfPuqFbHmWWP+KW8e9+b+pY0D+V+xHYf87k1zW8K9wUX0pGuhONLdeOypeKFPI2rdhNmqOMVSTyiiV7urWUl5yfcN/0Ks9mTR+4JNfxizv2FCEzU8ivtolndqRsf2MiW/IYx2fygzSiOhKjvueYPDEhxbvXFJalGP1DaTwLUBLzJcPt2NUlkjnMCoW7wJJg9LM0fMbfnfW+5sLCwsPBZsQj0hYWFhVeAWj+fLGnYzdMHQgyVClqT6M7kU9RIG+3OZj9xb5rng93cUdOl/E9qsr1qw5zaBT4TErwa4nI1njL5eMh7z6MothfNnoznTimdXbT3JW9FEOPnI0SXx+KLPVevjVG8t6TlsXS/V64XFt4aRyTNs9uCkGRFEMXmDEQ2fV3UwhWpFR+mVwR97pGcF2zcDLwNXx0/H6dnL51eD/l2nPN77OZIvApo2Z3DkVtvvPzRunWP/1v9jOZn8kZHyIO5QTM7r0HNCLlIGLTawurj9ExE5q3sW9ctiGTuXuxzs+T6G2TaEon7HdRCNLprN4B5usoHKP3NNwA/nO+eMvgOKprq0/Z9hH4WdwZO43UyA7wVtl2PvkGfwtvSPILtqV9M7VNT0xLH43FJjB8fZ21ivUbMR7jvG4y+npjuPxuqp9R6vKCYcN4LIWF0XvWIjIzG88W5uSe913PRa3iyaBciWsJufRf1jauGaeO1IyFXE+mlNWSALs0PJSqkHjISEvhSj5vIqKbcSRTUdc3Z1pGRvKzB2rEIPl2xhkb5gF2HP6vl+vB1/ifxaepiGvbmWLePk4fgvtz2VuBatuMoepmD1M4zCSpbQGQjiMxFInF+fpyK7v2XsPW1xNO3IzJ+rLEfnxp2899ROv21aMJXvwxvdIlh5HNo48oFGO8Bkw0OQsjbCkZG6iFrDVKFEp3vIRab6wNuwS1ent3WFhYWFhYWgb6wsLDwaohCqP79+Frg1ufCYc8WeVFY20lbWclvNqbCjQZ6M51WzyMsMgFubrKYhYus7SfDPYuKvazGBTIL4/Pm8Dpt+2LUfUrlNrqFkHbcfTS8/aKyxJhMmd+jeX6G3npbRDLt34l/j8Z5wXvUMivwA0QUqGLRmQhxjwAfPhfe7MjfudeHkHG2C4eiG7p/vH2lDzYiym8jzx/DqDhymB9Zzda9s7A9RiL4e1C+rDVgKt9aTzT2YBNtq/cnNDhVVC3h6EaTUdsYzyKpCbHPltRj6PO1l0edZ7WZViGGho04TIHZCt79e/3anhD6u4j18R9QI9H/dmVMLrwfUOG9fR4xoeOGObYHR0ha9/xFkuER2PIJnMFhOm7FFuKR8Lepj9fDo2UXy2XEjbrrsFaYbSrpa81+P3WmFxt9x1n+48ri1sFxfhTTfWVuTUb79BV8IeAngBfz4grbLxCuONpofbKmh8OMnbW3MCbG/ojBw2MgRn7L84xtKy2DiEDp0txSVbclYjC9gLAhMYGwgQnIGWjm3SHji/Z7NrcMRjIEMNkN9M6PaDGbchpssj/6xmdH3bG7vtWou9gn+n5+lsb70jGH9J3668eJVAO8Vg1zCV810n1MciZ6CUPfiWZ6TFe30aH+praxg1q49nmnaDHIVw0AYP0KKgupsTMm38d8kdYurHSBhuPqbM4vsyuzfxCAnj2/cdkycJF5dUUG2kZdKx4bTmnDC2l/opUfK0eCz7sYb/h3rRwXFhYWfg0sAn1hYWHhFdEWwFF4QOE+TKbtIlX9C3EdFjSNBDfxtkfs3Vh3jlAP4pE6wZczy7KP8lNM/I8Wto++H/opEomTWvrPAw2u4iLUXp8RYsWQxu8/Q01YWFj4zKD2T8dTd+IiB4lV8xioxciaob9neCHaINRh+g7THyRxU50fmRuYc03t/T14NrFNToWnj+OM9vEubpxvCJ0ajZZvYKj4+W3H5BJpqaFiih04P69w58UeuTV/qcbbTK1OaLJhedCQ+/iX49l08Sh8oKcELFGgf+ehvN2M7DVKQ0h0G7bVTP7sCHzOjruZi9tKfU4wHft7S1xOvCeMNcpnm1SsNrtdu3xBIdWlNb2Aaria6zFNx115dt9JSLVIwtX5iWu9lpiWWj8ky9m4qL18Zmy5koCpbMst1nkqeZ7qTClnUEpI4KKLTlzKcpMSsXkWOYElzJVgV5GBJ8/Fj6Z1DHuEjGjOPx9RF12e9mS7p7PfGTRvpzOqeEREPwoO0Vix0pk4RG7Ujlap964dmJBm4fqRbu7iMG1tiirfeeTahFXbb6pNMR7NYklyO9dVbXfrFu27droUNHh2As3LmY/xAar1wsLCwq+KRaAvLCwsfALMzreaLVqtQLVplltSnoNGuonnwgzO1Fa9OSyYPysmFMsu7ifR7/D4BHREU/d+9nz/fv/diF7/OHj7lHlBtmjIPeO88/fFZ0//c7E0z98+/nmvxlMRmWDUl7MEbCMJ4Twy6qnQ62QPS/5S+vL+zPfzeDXy/EQcM23KkzFhlulIRhXN8/EXHsgvnd/9+O3vbZBRwFoeOU+Gz2PfoSmC/3J1gTefupcGP3c5s23heYjtu6d59DkAfEMCA/jRufAbFSI93Z2pWu+/g0JYxefWwooEdfyq8l6+Aw9d9b4lZbrdYRQusNcing9LO1i8Zvyx9D/TimNYTjtMydlz64/6z6NWutf3PFa++wudzgw6iely7+dog8TsfSTeo7sLiubnz5DEL1ysRVxByGC8APg5IV819YO3bpJgRiTSfoKbO+7yHYOCEHSIpeopusyMbdtKaqqfxKmloY0bREiJkDmBEnDJAF8Il2spl62F3o+nLUtUYxYZAes46/bky2avE7uvjo2Fn6uV837V96xjt7KhgcLzt5Fz2L6NuY+Ru2tuGuE5VpDgWTTTLxRrUUyDH6dSY8BR4xn3T6Ipv4VvrXIivWdAreCkWuKkZ5AziqY7G/8+raMjmGSSrlQ7mceyzo7pESsJF0ogMLYcyonKt9hqGKMpbUeea3MfwLTHG2VCn2ncW1hYWPi3YRHoCwsLC68GNSPVJtGdC33fWWEPWuHTM8u71Rf7a1nFRxtaAYR6XhQzcKnOZ3HMMvLB8RQy5KzjN2WcjgnzM0bbZzTP3Oe/jUZcWFh4H1DlI6pgTMyfN0FaETTndmcElbRPyETZthNwjrjrntvS28E7KpJD565pjFLsZ5/foz4t3EEQXvN1QvaZMnF5HTzvIwzznvq7GbH/600/HiuzSAq/JWw1LOf9Cj07okXHJMp74Nap01dDj/zT7n0I/4DxvT7zZtgLvtVa/B2Ev9rbPhVz2z19qdEJNyNX8Y7DSc3H6XkO3qMefDbS/AzcGi88k+vPOIcO9NU0H+ruPghRvrlramaRhQj+MkiD9AQXc80AvtS+Ym99Y+nDZqocgTAb8eJt0W++PJsNEx3jpu6YR4QhYMe4DMbGGdgAuhByzsi0YSMCEhWT7UnMrduCqBMZO+GYfBbVtgW45oNqHmYa5yor+CgteGzWnQd3o37noIieglGcNLh2KQpnbEs4o00C5f6WHIzcKhEtcqp79mRSDSBbqwqs4c32BNCwkVmX81PgbTqpxSNnqvuSsv4zMy5tfs7epa3faqYBYNQNMKxa+KRzL78g6fPZJ37v5bFfScOJoBYWFhYWbsAi0BcWFhZeAW3ienbt0pHnR+7nDtpyR2btHNzLqsU8u4Cw5VyvEy5MzRzqGRL9PQXFR3iLhfBHwljEuyeo/TXx9nksMcrC+1ka58ehPCun94Xzb6hLFv+2LSMfKbdWCN7vB1Oh2CNkoBDmZK6lEEZkCAbPjuiyKADFzvWjoFeSoglhvpduIcndfGhAllMr8HPpzJUE3v++H2NWci9BNkv9+fmMElvljqvm4VjgfPs2hEc3F/j05RpiQt9+CMDXev3D/H4BnIb/b1CBtS2nbyat36qpYwnney2P2Jd8D+FoaPGazBNLgNkU7JktNoTC4O1MY/NRk+1H/t5j3jwq3Y8Od2wEzceAaX5oVJMmDh/Arb5tvzEKiAYuZ2Fw/XNPXxg1y8V/NOke7y/mmfQpuQYg45L4+wbtD2JcN9XDlsHzvmKZsOkPbEjNDTPylsW0CBIRckogzsU8eyIgU3PLZhP9btmzEKRemzzLeobYb6pHuAaBjHn2vgTO9ij9yHS/66MvqGnS6cdtPd89/eSe2/hONcG1ZsjshzBe2zPKWd8AOqsG2iZFvoPKC/u5s5y9LuE4v3d0zqJpLxsxiIuWt1hC1PmO5s/4NqOg5EbzbZtcpuI71Y5V860WMBhcNc9LaZZ5R3Ljd+aq9c+GJw+tlepGk5aaugGmnHGudSpJH39Anss+gbN16gyJvrCwsLDwXCwCfWFhYeEVoBNXPpw0Nz/TN/70qBmh7XaEZ0+ca3LUTTELqybaZL/2kfB/9Lwtbt55wj4T0OwJsm6934tbhKXxu5/G08zt2sWluSbvRoUyE/LjRCxrjbawsPDaEJJVRFzNbDtrL8RE9czP/tTg2RjAk19LbJhHx+mEHxOjXwJ176Mg1J0nbjrZu0eHJ40rLs2DM8/jdTRjXR8OSBjznEfJ9cLSBNox2/5s3Fd2bGYE+uxkTCzCVL7vvMxAdPgUSTHH0uMqdK1vn2z6/14QClFu5xpfzbtkruV9mlwDalJ2hAQh272Y3p+HqlSLf9aTGfadj9X7Hc2j9kpffHyML/Rc9OX9CTD4EF3bqo7mzdkbdd9zdy4xj/WN99StewjyIxTtcdUlHp2FPoJorLfz0Lnek9Kl0l6LG7v5xffdullFTJnXP7YrYMfWFSfkQynvxqvr7utP+l9mRkYGZSAT4ZozsEkOUDTQ25Ev9ai2XLTWM7MhZCv5HghxxmjsKKXTjn3zCQru7q87b4Fx2/L9KU+f3Rv+c0DQajElseV9vY3j38x9j5mvO75w9TIaOXtnMysM96dhNBcnaKuOz9paIGeklEpzTCHWoIrfyHezGUC+10hrX+JxpdzmfebF/kRgjCWUWVhYWHg1LAJ9YWFh4cmwQlB7edOSo1ukyuPBwna0oLXm22Zhop4/Vbcgl4UWtQW0mG77TJPxR5J6i6D7NeJ/FEekTHTtyRC4xO+JgfsYP5YY9+1SU2ISDbjLk2K+TSzwjDg/1vdbWBiBzC+HK0u4yFawSMRYYVW7DsJGtpE8E/NuuBfumTNUxdEjyXn2Geh7YfbaUI+cgT6GCobL+eKMvTPQ54g5eDSVo/BGY/IuGgejG/Bmc8czIuaRD/EnZQeU8iPY81VpUOue+yXjBgMlq1Wz7iukDomAumiZA8CXlv7fAZSjG1LtExIuYPwPEv7TYviJP2q+S7/we4g717h/tCeMr+A2vts+5zvEFLyWUXkGfAuS7/6M9pjrGbVez4od+ua2ceBXwQs8wXKWKH0v6DcrqR5TbbYX0BrkL2Zfv7+KrstbqUM8cfEozo4fY8an9Tp1B9wt2qsXlHm1tm17dMcxNph6VZN14UKiC7GYIRt0ylg1qncxZ2xfOJK892SHSjsHIefUk4aF++bhOCvr/Y25Eecg6RNKfyXnZTetYmZkMHLOJg2VIK4MH4fwTYTVnLtos8/L/5EaOB+Pb6Owx+tUH+54Y2U/s5yrE8zj3XN9PrQe8fucnb/8NBrs1p2c/Z1DeFJ35Ixz0bCWql6eH3+dfr4e08tmvqPzRPkb5022bu32SNWhWAbp1+WyCUZCqmexX5KLWfobcZVz0UgXrXlHntfbpupS74m1n5l9n7bXxaafNN5PJH5bWFhY+FdgEegLCwsLrwYVqhDgNqj3LuFmysz9lHuoeR5n3gwlz/ckFUT1vHMRhpcZv5MFGO/TBcsnmd0/V/B77OIeUfPjpqE7KkavzKu55uBOaJO6axezn6QqLCwsfCJYQZwV5JXxlLBVobEKxVDPRzfnlsKK6ELAE/DAjewpky50l28P42dKfV8rs4NGtFLfI9t394Du9zoOzxL8k7HEqklFIeBumU2e23EmjjcE0UgvT3vRrtDBVEfmsyNVK/m7UDS5bzv9186/uBJO9izLsxhqCkY3Jk5CNVdezfSCqPtu8oXfRusflTz3FCTMs4iM/63+/t8qPP8dGX+AKsHu60uB1c774VzIs0KMC8TUM4ObWfh/6juu7+fwlJm/Htczm6JaGwzZ9mvNuD41YTD8hNw9PiR/hj3l6N2Z52+J5385Oe/c0lwEclrlZ/rnK4qw0244sVYrCMAPEL6AzYY739dZarU9jxrnk4FOubYphVaDiO1az0RnwJl3ZmYkrunN9aCJql2eQJ54b6bYgYxczzdXmcOQ3AvnPHfnnU/qdryKB7y81dhxjFl99c9Ha9tzPvdx5N/G249K87DseNneTZvIyZy0um03Cfn4j+ZyUv1bqDyO3T6bhXvLjGw0gxvNP0v6CCB4iz/1Xh5lZrwk1DYhjhp7rtNekwHiPhwb/kg7XQl5uPPUbbiHGf8oTW1hYWHhF8Mi0BcWFhZeA+GA1j3yvDg4eDbRSI8LnfZjBKhxFzsBINE6JwJnbzCRRYjKxv1O0p8om38q3idd7yci8ELmiTFRR3jMyYzO73BB9hjB8Cy8XSos3aVxXiZlfS60+9PxOB4L5/2//Nvi33b2ueBIgPdImI94lvQkeO0VT5vasy2fI1cq4yeccMy+G/vpa4/tewn9OK3vCLLh7d4UP+3bURSJ91f2biQg7V2Pwuuf7tVDgmoMFbcMav9Zf4TrmDIYhEvD7zbLU/Qp87BbIALSqI34yPhylAJ5n0DlOAQqvu0Z5XbbgYZ7Nm9nRP969x1KUsk55yV9wAvsKaT/qa7+BAN4wX9qWnNr+YTfQSjn+L7g/6nh/g8u+C/+wf+6M86lfoiGO0CNqPsHgG6G9b3IV+j5yYSihS45UkJ91vNw+LVP/BVV2m82t3s23noeO9K0fw+cad8j9F/YtiAT/iRA216l/utzclc2pfeOz2e+7/F4KS60VY6J1d4s81G6N/eeW70niGn2czm+QC1TyBnoCcA3KseAbFxIdgbhCuBrdfcTNv/lqtMWDXkZvggkWTeOk3VePPjyG2inA83ces65bphKoFzSmByBjpb3XK/tXEhclve9Gfs4hmVXL/ts9LrDt+HZ/c7R6NPXVWln45obj6WJPfjeuLuXt4743knnyM8sDN+G9U7ONo/WCkQjXc5Az5wN+T2bNxGshvtevxGJ5Bhu9OvDJ+OhtZCHAAAgAElEQVSD2xsL1RyXub8JuzLRiaUfNuHlXO5S0rJjgJL0OyXcnLk9k9yW+btmvq1NuM8Lhw/melDbbM3HvGfdcu+8cWFhYWFhH4tAX1hYWHglsFmstrXo1HHvmcy1+ek92Rdc7hlcd5qTvjfbYwm6S53JCpmpLJimC6Ux3vvs84ijhersGYfr0+Hds8J5FQQiY/rRemO7duHXueY+rA+R3YWFhV8bZvga6cDarteL8fr7R6AUhklXlEIbd7vjJXwP7EXO/jmjasx1pt1vwzNNuU9NuMfNelVT59aY99xPBbPu2tJO1MZ1Sxw8JzVj9+UszGzq38lQ3nFQnaVTyjCj18eM7kbJFxLZvvsxcGNJaKr3ZJ4pef472KTlBf8BUEw7X2pMkUigZhgeAP7TiPMXKFH3DeTSJWEUEr/4/Vnf/RPyRVBN9J4EuY9EOku23IsjYuY9sEc+fWbcQ37cGsL7fM+4SnoNykZJqgxvYv3MkCYbXO1wvbH2MxfotRxjZii0NuMgCtZsTNbbMttFJOwYNXJtmNy4Pm+5tnOY0QYERjb5yFsGUS4mt8NGNxCa29nGpyOLJaMkt+DfkKmzY8Wz0ZPNQGw9Z+cP0Z0lTrviGgQ4I8cd4XqUAPh6/xo9gaWzj/rv2A6jewru5F0afJV4H39HbiRAdgnw82qKchCjiMLyWzVMCMmdSU+m3bsWKKI6GsjKTFriuqalFepvtgFrYWFhYeFtsAj0hYWFhVeCXZDeaoZzd448C8gs0FvU0T4UKxGRsy7QzToCxL3Jtlvw2eb3I6L8LHkew/kMgr8jcuejY2+h/DoxFchZaunBmN+/7N8/BQufD6O+8a0wE5p1Aqfw/JmEzGu1mlm4b9fP/TrYE64yVHvumXHYN4WECZsIHo7xMcT47ymBIsQmU4ZjPejRdpUf4ZnMP75W/7JB5Du8uf9vNYYf4KaFLiPwhv8LAiHhv7jifysR9p9Gd/3AHy11uYZf3P+/YGzI9Tx0yZeQ6d9QNFtFu1WImp8DEuUfFO1zTZdoyxP+qfH9A1v+fXn5khlTIko4jCnSmzZoGOzVi/eqs4yyoeFNx5inZHZwVIMwICGKEX+ynxxpFWn4Xse4eamdyeKItLd1axT6qKebkXstnXUxPOo/LuZaNrZcTeruEVpaayTS3mzMFwDN8AZKf8GQvkCf/STDi8t6PpDo7ZFd+xPwwsCFzhO/Z7YisOTNqKqKhq2zkhXZ7eS/ZPe9ZMO+pN+4zZBvN6/Hz5xzjUK6lTyft7fYj/q2qvkn9z7WXLF/NCODGb5+PYqjck0km018OmaIZ6BLPremia7t2j6/J22CWX8yq/f+udRtS92XJyXfQm6ra2/BgY1rm+p6HwpONutdpP3X9+lS7VpkBhmz7iNN9JYH1mt538b3+i4ajyBDoi8sLCwsvD8Wgb6wsLAwwBGBPNXAMhcpJbfKJjaGZk3wbZLsEjBZTNhVezXTzsZcPJuwU9NY05l6NMxplzKOdLd54v1FGA2u33O+P1uYnfV35Hb6nurmg5tifRt09ZXkR1aJHKulqcv7dV2Xo6WetXo7kiTshvR+mAkfj4ylvn/KFxYex7D+Dx4ZsezbI0ism8AJpZ0WIaUVjlXBJtXeifTMY9FA5XiYOaJ43b8ejXWSNuoejtLvA3DlydrVjsr5kVLnHM/+pt30usdEYQgYl0Lp8xm21xyf17wznggZcCcr2OUw2NwV0uEcbjm/nBoRa5/diqb91MZivvsM9Idg/PfzonHYbvrIpZzbmeGD9CRbB+u5vDBtWn6/Q88sbmUC4IL/1rZczv294o829yib3X4H4YKM/2kk+hX/t7zn37Hhj0qWlfBSS3uhRLYW5zi/X6wEHIwvEF3R86CWG+23mNRYvHXXrkk+jycS+kOYx4jfwsVS+8pZMNN69ehUl7WcQzff4fZSPoPDSeodOBfWcVfnW2CsHc9K8V7tOXqua0qlhGZkmPUb32/wJHrENdyf6easFRCJ9wrgUvtWQDjl0nEl0vlBkjkEuKy3qzNX/+rDF1QLFWS+DFeCHuUYCVtebG5s+anpaVSt1/q8acJGQlADYxEm9IWgl1zGxVzzBLAh7/bHPJqFPwGbsFsY9hgxGtcDmxaqartEhJyfMLYNUnkGe+2N3F/9sES2ptQvySp9sf5H7U/c6fu+7TsT5Sgm18nUl/L3AoY/qg+IcgGdM9t3NpwW7843GPfPWj8ppLd31YdHzW0/NsY7ar7KpJzahhI7uaBB3mUlYdLDAMk5TcxoKwjt5mrjZtBlNC/ey6vmpLR1tKmvuE1A23yRjRsfzhiPrBcWFhYWFuZYBPrCwsLCK4AoNQK9mXvLjMxZBYzmnHLAC7L8ma7x1GWUyXyuBHo9Ay2bg8tfLhckSk0Y69b7m9XDYt2BbNxMiYKYTwn/A+HNFw6G9OgN7X0OlKrTSTqmedHFpy485Uyx6IfCbxfWieeDdWNw90ipj0SYQohQ0zwHosBB2sx+A/g49eHjpGTh9TEXekcChSbPCxIHt+9YjWZyu0Y6mr5YSPVMqrvHVUCV6nO5b+K16v9oSJv2cTWw7r2RilH4F/Mw3q80Po/7DGSO4INTc5T+cd9bR4H9iRh9mCG8m/xXYf99KB/Yepe+/DoQJjt/NRls73dc228TBdA3plghGyQPU/BAHDvIPKYpfT69mzKNKOn+Csbfg/jE/V9gfEc9o5jImVqWI4zknlFMtJfrP8Ag5HaGeTi2gaSt/AUG8K2elQ4AGX9WEbgK9IUov9QgcqXkxVz715CDK3wN/0qlXm1AOUMeniQYIZInpW/iMvNvfRK1/Fi3gQ7Q78Fcz0OexRTSIA5Z5jFUrSdoB/ZqhPkAFz4f7Mic9f0YHZoB98TH5Z/b9sAjD8aFUDBAWSMC9Yxhk4r62JGa5b1dtSlSlxLUcMe9F3cX2pbDaBAz0sVt26fcW7rLpUfSK7uExoXV2qPga21T/9T8vED7gzOQDTaJgWuN+gVlgwyT1LuSi0za30roDOAf1GPRapK/AIDpH4lLX6f9kJJ1Py1vJ2Ey8Dt+w1/4Cy9c+hQiAqgQ8XGjgPXMXOYv8rARnKY9lx9WDzaolEApwabW9Sd2431MBtV4mF2vG7fntaTEuIn0zO1Qn7v+rLoX+wEFsXYcw+biW83pD/d83Je472We0K7LPiTZmDUaL234ozmlLYscvsgoVoZoiHtrLqXcknMrJLvvnfp5yzaQU/W9ZEy7fOOyCSXv5DuG6++t5YjoJlrk0FL0PaJs5iGzmdaS/KT/UZVjcF1MsGwAKY2OkZFqBy1lcqFUN3fUYx6MDXi22uwmczLX9880nwy/lpE1izsGgLTdDL/FPTsvFxYWFhYOsQj0hYWFhVeDmSGzWTqxChnn/kYhmQVx8O/DUjGG3OlE/Rb9q/17m9RnCnifgb08jhcb/mV0s+tnhrc8GO4Aqr0gQhdZmO2UlNgja0L8XqBbpK/jmkKhTKfF8YRF3r3bFu4VvMYiWFj4rBidr/l5MRD6YtxErRCLw32DISHaeDopqkhjHI2fh8OH+RUT1Gf8RYytC4z67Z203DmWlbnHo3Xr+f5fcGlC3b589svZC3k9XWSrz41FrH4koE8xsPjWFe+0Do9H2r+rq9+gppTjtNiaUebBP4lXaR9qlibkecafRbuVGcDvzk9Js6bcaooCk76DyPlvli1q4r+AOrPvzn8L19YYr2e/V+/ZlKjdAFVIp+pG2L7ReoJHdjbeD3IO9S4pM2lMj2qkjkeMvff3xKCjbGsTfFaTnnfu5AntvD8O/6js5z5nKRlRgh5n+0bbjoFKBd6Q2CsK4Z2V10KGktSpdrgZGG6rIpSjGv4x6bHHN0jbf6lp+onaJombQRXt0xUb/sJv+B0/8Sdear5kOSUkOjPXej/4xoN6z+ZvuZoUlNls/8xR5pameLMliYPAj85G/w7ZeORr+5kU7M0h++c6G9Axqd+YERFbzF7zOB4h9tJ3P/bii+8kP7FNyXPdwlF87/XD82NxRimKNifQn2s+iLWNLwTPTg+IeZsZNkQ1g5G4zCHEfVxbxG/H0MSNYrH9H6POg2xSoWG6Wv0Zpo8LCwsLnxCLQF9YWFh4InSyLAITrnw3N+L8ofArea7m5HrhbwKK2XW3euJ25rk+mbDF/zLIYiQKZdv7N07Pa8EKoYAzIq59nC2XjySoHaOk0J9xrqKP+0J7Ddwa8uuk5ON/z8+JX6Wf+ehow6IIt6Nga9AxUvhd+PiYCZmFNJf3l2qo17Y/EXkXQe/cqkpEF9etjZolnPfvDeymgL33fekUMuqf4Pp7fSckx/fq728Af9XwvsAKhAvRnUDY8D9NA13oSECIrFJaP2p436FC+0JE/YWisV6eX/BXTcnvAP6scXD7zhmFzLKEnYWYmJb3f7mcK6zQXwXcfrPBiPj0tgw8VZBA5ozXnlQ40z/NSJr37tsY9+iXvh06ksKY7Bq3kfh9xqPIJXnNUKklqa1LlJLufc9jPTpmjE34bF7ENSoHj5RtKm+HmEc/W9+utZxfNIGFsA49lJTv3sYVcU1QTXbfZuvaGb8h4y9spM+/1bRb7WWC6vYKIfjV5M+GHetP6R//bILYL+G93Auk37nlHHX5rmQrT93ZFdNz5nv0G/X7seqIKD6Mo3tyNBIVHJXL3+AhyT4nbktOZJvBuVTsh2zL5ig8S5zeg2fPIGTTWL5DhmUp6DjXsm4AWy6y1cGXQDzORf2MS4ohsjDrY+SOa1uh4K7eNxMa5U3TRK9ytXRJheDONZw0jiuI5Uro5N2O5qyAkevF/E3ztLCwsLDwbCwCfWFhYeEOzIjwNvlnXasK4d12hWZD1U6lk8EoKGtYaqqN26KAiEDm+mIWzfGcdAlylG4A3ZnnNHD/UeHOUTx0qxdM/Zud4hqE9PxTGW+FXe4XkDEDWd04jYbiRnx74S5591wXtKRnq1lVp7bIbZUuLAj3qrok/kT+fIr1/v1Lf2Hh82Gs90G77z8nuPUzclTwSIDZzuS0g4MI6UTSZd3XvyLoPEOsNndG8kW2Sx0IyR4RpPbCbC9ujMLHaND4Xcf/h6qfjGGjN0KWeusqNsoEmh73+mrF0RKrJnJfNb5hGjxpdru83BpwjcSRJ4zt5y3nElsBeam5W6XcLihklTW9KpqhX004Eq4nm+EE6E3TH78j859t7pT4fIW7pViUNJlrXc7aqUV2LnTGN0p1PCvdUQJt7ubdA2jm3GW+B+h6p83/bmeTpjijff6RMU63pcpGz3VkGX67p6XuPPbm5+fXQrMQn5kjKb/Bmc7mWghnuwFK8iLGnwv5Le2orGMSfgOhbLhJkE0dVPsUxheUPkf7GTGvLVvmtVVqvL1VC/Eb1zUxreI+Y/YdTL/mnrLzLxcXqjKBG9bKDuzjaPGbgCzJ6sx/U9//TU+JsC94RrvehrObD0zE0FmQjmB+LDuTLvXlN8Sw+/6j61FMZ2J+ZL74zPC8/+OyivHEdjHqV+NIyMGfkN+pPqDgN42SRghKKGEubGQjRcDhbYyQdCDOc5DQNNV4TZTULWpylhZdKAeTP8mzeWmH6YWFhYWF52ER6AsLCwtPhFvgCGkthHlmva4mFN0isTvrsIbJGpaS4QPhajMrSchM5eyptr41C7h4Lhn8RLubdB+seW6dpL+WoOxoUbn7nEXg0AsVRiKwYTjvLgFUM5GyoByZ/VUS3T7rQ/K0wtivr4XULzbrq5mgUOKOC94+Z/77xgXwbXXQ0l7c1rjRTNytuN33ay1vXyfctRif492b/g04azqz13D8NWoAx86kQvtNYMyj9aJT27/6MXSutezccuj32AjtnlXc7L95TLtP3+ArPzMtD+HWRJD71qPx5WIEmqN8P5L1++cDSkq8Z7HLtHOk8bTvUc4vLx6F9JUzxW3TYxTyW0iuUvVlDvZH1QYv5wsLvoIqaVX8fzPhaMvTRF/wG5i5arL/CcZv2PAXCH8B/L2Yjodoxv6OhD9bCD+hRJxoR1uZ+i0a07N2Z89yjvOa+Azde9WcLwJ0CoRVXw87N+JQ0lZJgdk4Ef0/AtkU0UxY34mbzUFXXwX7/tj8nm+PVM6s7UYCMmUty8PsyI9xv/z6aPF0a4NaAkLgkK+Zs7oQXNkYhuTgEYTokv5ESvYnGBcA1/AdpT5dAN3XS1LuhBf+BsLfAH4DQef/pV/SDXdE/gTpJGmuCc+tXErgYnnjK9RhzK/Ns4QrcQjvxtDNQfZM9K81lf+A8FLD+geyfvXlJWtbuOfeesVN9Wv2rQfrvjJ+cHAX1o9x/hXPc9+J89kY9HSu7lod9DjXG0hjuifSS8ez3+31Xo8U680eRu7suLUHcRMPFLlH89ymRcPVknByqeBPNrnMSpRCyPLXnb/Ovq0yoAoiYV6I+k46C+Iyf4z2QcQdZS5dZfIdASVqMg3ODLpQS7GLr7UDO/dRF207jqkY7TIWCvnndsxaWFhYWHguFoG+sLCwcAcO1xLMyDmrFLJISgCwO/+8hUM+UGozYgkPjTiPBLogibSsmdqqHifLrpmA/+z92XdvCR7ccfd87Ed/e0HEMI7+4gMgiq3qMqwJecSZCAVsrhVOcNDOy1SBGTXJrD/djSv702nu8byUjhb2R2JOOvzCHiIokwX6R6m7Cx8bH6mVP4pbNM/vPf/6mdgjk1rrP5lMO9SS6VyY0CxldEE13sOIucKGN73WjWz2/a2lGMk0Gjw/F5D04f03PfOdxXTnW8KNRSwmhu9LxdFcbXfs2Rm3TsR8ny+pm1DR/aM4HYIR1Mb03BxWC/L4uzHEvHoxzVzI7N+Q8WczmfyCQmh3RBaKsFmnY+yO5dn4TyT8hg1/gvh3cDXbnpmR8FchrVhpe4YSWWJGWXRdhWx/pqnxKVGNnbkn+v4BZv5fHko/JZemtJwmOVWisP/47SiDI030mLiTGJET9+L2Xopbx3yGG7o59L1By6fi7jjeCmfJtxF07JqvRc/AbnTN8CdZj45Z2AB8QbEiYjfEyWWu23LK0U0JxdZFRqpHegCEXBcyqdGkZfPOF3DVOpd0KfVFAF6Imma7i9msv0aEIZlfAuqxF4U0t9rTVZKg+WXGz5YKv+615qtLvglJLOLdgT0Nckt8D0lwos49B/f9EQLvN/NmdzWvu5785P4d2TsNs7m+o/+5pzUdraUfcW19RR/eJo3kPMYzD8nOn4/yPHo/9BMKMIZPUOsTs7CYuZpVp6rxnQGuEgaqqwAmMJno7DyWSIdrJ2XRJAJQC1UYfA2Ck7dEedbCwsLCwnOxCPSFhYWFAXoN3f3paLfIq+tTknVqIM+74MJkvlGSljAXv9mbrmsC7sxtgZqRC6EO1RYZpvGXhRci9G/6e27/7bv/qJB02p3jldYeChft84Gop7nqdbrgBLUSAmNi8vYEgbFHMI0EBfbZsSDBL0zvJqJ2Qr8trI8qJh3jc6X2uYiivDP4jFsyRuR5HAPfLV8HcjyGCihvsMDcBS8diZM3h/CiGffe1Hqve960Ou8E4Z4+JoQxiN9tANghz98TtjwfHYd7oa7/jW7exQSmITZ0/D5OxzPmKCLIVy3Ncbijsdg+n5VzhJBe5ZzyQhJlqKb6BX+BQO1Mc0YhlKR0UiWzEv6DDRmMv5Q0kjD4O8op5X/VZ1W7vBI3ou2paf8Tcl66wJ6nznidc7pnBOW47HyNEDKxeKCWt1TbbmYOmugltmZ+tvpjGCs8hjB31ivsc6dJel8NtBr+9+LRPupmgm52rkOFaA+3spIiNTGWv+VJuiH9Q5cz/2x7kImTM3G6ef4gFXGt3KLnEL0QpOO1xlFafnbHQ819EAhfQtjSTqSOix7sRn+B+HsbZ670h9FmJ7ywrA0JmUqdzSBsKNaryjKb2vEvX7hatTIW4WJqR3263MdNJfJc+kepT3IvZDxXx9ZggI9TyUj5vbXldJvL2ebPbKVmHn5X6TeiBQyrVKD+wuybn2f5YoT5uLZfSv341+e8X6v2bfMoZ2fmARYxFbeWnNYXQv819vzFdFireP55dCfxaslQ2+g+n2lQeKrb6c6U2ez7ljPRGRwXFTVau0+NZYyFXmMD+FLTVgZkE2cNgExA7bmGa/PV8sd+nWOtLPHI/SzjCwsLCwt3YRHoCwsLCzfA7Z62U9NoUr2uXjmjnmXE4Mxtsj0OXIiLForMztt1Z3oRxUyVhZyd5HeAn8jcL4TRovHfUgRlEeUXl1ETXd6cWRY3v25BDbPCe1+S5QgiMLu8PR2y8Inxb+kvLD4y+e/6dPLPR9/Ky728mUQ27wvZsUOkmqtgvdbdW+q8E05PKtOs65wJ118D702Svxfeon3fI/An1jH36MO/Vh4Y83b1GhCNUdHwFlJV2pEllbxgvZRVGeOLaXZA58BNeO+m6txIzszcbTjMUNI8iuxfD0pTzCjP/W/hfY3SOzLnjir0d5zwIAH3mUg/xq94/vkpUvqk2+N6t+MiVvwTvvdc3/WdwhLUnxD+fMgmF4CRquZnrhElEFIgnwjfQSza6N9Kf8GyqcFoRxPqcRIeP1GIbNtPEOQ8dIV9v6EvS1nys22jNQBpI9IPtjkMK2F9AfBPIGPZ5cCkgQE+2ARyhFitst34ZdI1qn8c5Bg2QJdeEXsYf58LYyKd3TtfF/a64TP3gueX1PN7aakj2hf4XmF0dSvaPNzN03380b1LH8/LWDPA7Vbc6LUZ1TO38dad0+SY8uLAhzhII4/v7brGfbF/5xR/YWFh4VWwCPSFhYWFO9AWerOFIKOcf9RWspY8P1iIcJ36sgk/mG4n8y9vuZ2/BqMZ0pJm5+dPwj1hvdbyd5aW11xuRxJHHn7kdcpME32U5ri4HPl9Vvl2ZNPTQObvc0O9L8zXrh2Phf+R6+5b4Fn1+VGi4S1J7FOa5wPTvu8CMqReINDjdROSR2KctP2yuUfIogrZTAntqCRHs+32Wu+77JQxYxrm6+AzaJ7/CrhL4H+Dad33bo7Pgj3fNwq3IwVhnxP+g5/4A1+gjf0F/2kuM/4E8Cc2qAZ7FHanGn/sQ0QzPaYpD9J0FrFvweA+gbqznHt3PoQUQ3Ta47b/tproe/RE3z/saaI/iuuxk3dFl8N61kf3XIgLKRv/2DgbjK/mmAyxMEYpGTcAUb2vZS5nEhfFxoRLMnqXhvi5bpH2nXwzCml78Numro7I/KKS6HU4tW3qXMBwWXipg/21Erdxo+yFAcJvNQVUz5z/C8D3Og/4280JCAnt1GKj3S1m3AmFBJckZFILGpI+W452TkI1PQm/g6qpeEZGrhYyRLs0knF2vc/hmWz4+UJyFnpNl6XQTafFwtTfCJsmGjwHxv2B6y+j6XqneCD1OsQ7Me3+2pj10xzexLPC+/ZV3OcdF20eKu94tAY3c8XB+xEciXonxnb5bscoreN5sfSf3K5sCLr9Js4WvP/Ws0zm2Amy1aX2o+FLzvqmFmttiBq2ppMZpaG3N0KW13uSew7rK5/Y2febfXfpQ7KpT8+oAwsLCwsLikWgLywsLNyLoaa3LLxRFjlV6ibEeVwE+kVZNW8GBjHpgssS58b8GZn4JB3y/iNrEr4GvABUhB79smG2kLAC2r3FonUXJAHvXOLjZVbUGp+R6OMwoqYIuzAt6ySCO65s1O7O7ZOpP/Jrlqvum+kZ50pm1dTtxPHvai8LCxaz+u+IVMKR9dpXBYff0bsZSP50ZukxPB9Vw2Vw0Ebrwh6eEf7c/uSMsPRW/Ork+aMC9/crBRG4F+tCVgD62s3P7t00STnn9wnxC9VntS5t3bdi8w1/AIA7t5hA2PAHGFUbldEIdNFK31Dqxtbi4aZxXsLvxfb+0KTb4amTeaFGKkCf3166icYmj4ea6IAX5E+k7q+lif5uaAPDLXmajUDHjWVMIinJU+qarYXVjXmvZ+XWDRJi5NiYDGdi5Kxz/9sNME/GBjzezmUVYdcXI8rx0TFPNTF/ayVGraf4DdKqEn4DGbrZkk9cj0S4SJ9Ipj9B1Qg330bSbudKBE9oXeg3gBMyNmSxmGH8uv6G0LTfladjt4egWa1g4AvsWen1q3eb/PfnMzO0mmE2iByeeW5iKt+Thu+sl+4M9CcT599A+PFKhPAtfo0Up7XlZ+bUzhnee0bnNgcY9L3NSOIwC20eF59wdwa+7xyH11dPaXdobDYneVBDKUelH8RtQ9xLQe8xce1D3vvDLywsLPyCWAT6wsLCwgPodke3VUuZwRJ7N0WL3ARA+mMfZ3BHVshtqsKVvOX6nFVDxO5oPZ2J/hFNnn8EHJOxcwK9d9uT7yM3M/e3pu21oAtNS5nPnuq55n04vTu/eOuXtI08r4LAWIqxbp+l72cYkVz+zSh958I6cnPu+751Lbgvvl9xbf1Bu6yb0B2V8Aq4SfN8Jv16I7j+l/pnAFoa95NI7rxZ15dPilp7T0IeEBFaZvvl+YwvGc9EvAVnz7PX827f99tLKp5xPMgjSW+C0DeAF/pyM+XO5u2rIpDnHZl+NpiT32xMJpb4rM6skEexKlL7V84+b2bXq4Ov/99/sf2fDVf8hVwJc0vGFHPxtdSbpinhilLtXuDzLuaTJW3H89DRvGfuS2ZW47Y5J73sjMyVvawFwlE77bxW058oAUj6EczE7UgTXd7diqeOcLcG1vo63lW2VjJ10hIpttxxei7p0iyFERiidkpJvztJupqlBFJrvx386fHu04PwM/8EA0iJkFJqecw5+36N5LuWQOwm7fLUbx9RInecrO4zkByjoPMaGjm8c3yTdtm0+Ll8kmwCorZqrmVao7ObbLUv+B2MjI3+BqES6m19T/hGwAbCD2jJpOr3J6FpkH+Db1uqkQ8war8E7WcIwAv+CznDuVjQ0GaYjTvU9G41//YLZXtnTKOXakrm2vdRk8/h1z9uU4457VvqjyPHtUyb8R5juaE33sfuxVfUzQDRYe5m0i4AACAASURBVI30W724lQy/lzw/IjGPZnv9+GX7c+2LxN2tm7Zirmw3Pu1Cnoi9qeLZtYyfRUsJ9TKHua/4pEf8jjrUlTfRootVPmhfzfYtvtpqPBlgyiCkuhtSwql/rEn3YW7qfVhH7G1iZvPRnzq2LiwsLCw0LAJ9YWFh4UZEMZYS5OW+CWQqYW5JdNjr6lrPPFcCPBLtfmGgwqvZDnAeasV50N71eM36ifCc5SKH63Goe2KIt8SReNU+jc/HZtrGGutBugoRpYypv6Pl71k3M7ciCJNYO5OmT4p34WPjDSimXwIj8rxzMyLB3kIKt4NHo07VVK7AZmcetgjMspJIpOOvd3leUDiOyf/OcGuf1bsdi3qjyfn9MF4Xz6lmD2rLHleOw/hnBbcfpHzh3ES2b4LK6UkK7h0cz27iPCLfNnPPAzdier2M/z2u/yeDQEhVYzMasp6ZSp9BSbfz5MYtXeYRRaAzMU/kHs7zjzTRayKtBnpzPcnAszTRn1az7+2gHh7TznsuGuKyeZWaZROldm2Qhtg1xLON0Z0oYvJhSVsJcNsYl1S2jAihZgnmZDyIFbTCE/m61uXpphIIWTzxbtQFzSi1RqTXfmyPbGLzn6wcZE1UyidBluAJQDabGsT6ciG8yznosSRaX0F6X35V8z1DTL//Vn3+jSv+t5l3v+A/YDASEjb80bTOZdu8DXfcF/CgLBnM959BP+rbZxtnhuvJGvGMPG9EvPPgIRrkkQj/Bqt9/znQtx/9os+ac73VGvcZ8Wg9lrbYk+j7df523DZTYf9oQIDb/lmsR1piW/xR88xqBcvK/AYbcI8sgJGZw43uFxYWFhYexyLQFxYWFu5BZ2asXdU5Mevk2fKrZkd4vVDxCakTS6AXgQjhUhfxTdMGHFZg3PwjTKIjCP3Cod1zuL8LPLi6x7diJEyNflQsoi73jKPx4E23QeIgbe+1PhnFq5/eioPiUysApYFfuSsujYzVxK2ifQ4+0IU8F3LbeG8RNFvxkeZwX9g3DkuFkrttIoJ3374RRik+5+tXwNOE7++M9zk+IJC/o3OxQ7Ko/nmtsygPS6EmwI97Bz1H68aoEhjkmm6Ua82CyKZMqErPrTivtMTGQLjw4rjavWAlPYZpn3g7X2vGLn0ayf0e+X1tTL/qXZOJ++urI6luxtjOy259q+wMMZ9z/0RUWa4TuMa55JukweA6eS4VRJ5bclzmGX/jT/PtGV9MWLnNIIxGJIANjEsN72eIMoXfSMjP8mDDH/U34xoyJwj8zMzP6SzM0ede49xey7+mja2RSn1wjdH1Wab0JK4bG+gzzj/vrGWc94jRHGpvncEjh/W5aBhfQNioPP3GwI/6fKtnkX99edFjP9qQQe2DufUiiua6m82bTikRYZMz052FAca3r6XGb7kEeL0WHeZLPVv9khKYGRmVRk6ycbuSpJX9lXC3rKc4lzT4WThzP++3xdQ0sE0Yrp8P4+EMcfyzFipkbLfpuNQtChsyLrjUUpRtMFzDUGtbso4k/CbG8cG84Yo/qjY6cGHCN5RNCF+oaKBnEF5Q6vQF3MjzuApLdAFzxhcGvuM/uNIfdX1EdW3/p/n88oxcWcWzmQnmLPRaAD/Dig3gOp5JJx/7Dd/ItX+xH6Z0Hl4rV7z6FSDBn2fO3QXc2Byt+UVT9N9RtP5/TOZ9I/I8rkEfwbiU+vCHcxfyl31abI19bGtS/z3R6tfjoe9jFLJNzdyaxsi9jmx77o7CkdYeoxUrj6nN59sg5gLop+21LclL1hYj4QIMotJ7sMjsat6bxnqdSBB7K392fUVEnfzuaK0yLOLZ2mNhYWFh4WYsAn1hYeGXwon5+dTfLSiTZy6CTrsy5PK80bhmwtyR5zawIANityD1AlVrAs9prJsAyYR5bx4fw+st0vZiU9mTF4we+dt7f1tO3jbfI0STp6PvPstXFLmMnu9jJEJ7DNzdqYhANM+b9gnOCgi8QMot8qc+4LRPBolb+Ncj1qBb798RB8kYCQVf70z055ajmMZMQKeREbPgQqJyJm3T/qqyZ+Lag7S+QAMl8689m5STcxcj7q4WgH6Otzfnu2c++LTyjpXgbFqmUtB/J3hSFk1bfvSu/hIBGwuB4Oc9HO5F432bVADbPC0F5zBIqyXPnon9jVeWzJRcHoneW8D6qCU+MGHEYY1SFzqvtLlqD35GeB+OmpsQlADwhbVc/wnrNqDUHwnvx+B9KT4GpaqLTs2ab10+xhlv1Ro3BDlzMc1OKeH/Z+9NlyTHcTXRD5Q81qxequv2nWNjNu//XNdsbOacU1t3VcbiLhH3BwASpCi53MNjyxS6s8IlUdzEBcBHAEihvGSnIhYrY6II6MHryACR3O9IAJtAFm8dGO2gd6qrxFGf80oiMudUyrIlb9qXp82AAlDCtP+O5UaQOMACu1qLWkd4zR9AB06A+iOAGy3HPAQEJJkh7f8sZTAQAyHoOrODHBYg1wiGXtMziO8APGh+ATv+AbufunRw/vn3P1wf+hXnVuH/r+lgl4D0LiY61+/oTXffqyxOnjUMlCf9KK0D05HCxZ/ZAlcsGdcAnsC4BeHp1OqekP5SdPr2TZOrS9U9syEfSNY4gWor9HWtoGIW8OQZNVJaX7kQJXp/uiKjuuNmHbu5qP8IAKdFPjMupEIUTeaVvveCz+XX4kt99Y0l3WijjTbaAPSNNtroLYmnDOmlr+0eT+5W5NwVFszlDKd5TO6TU93ZdftEl9QAzyf2SUmBkdOmNGxqFJRgOpEw5o2mEleCwYnc73lKaZEY1gqQrTRe78xH0hZ5EZJSx5Qf5WhoOcEsVTOMcuwwarvm6Qic/lpZ4RatkJia47VR9NzcKO8vqw192uOCWEtTkkbtbD9SdV0/96lyLahI3XZAn3Nqz1/fPhOY51uY8nk3n2gvVxJ/JHqpMP4x2tNSRS7PFKrGcu6HY7tc6+ocylp91vqwaOiz8ocW5g25utHyvK2vm9ZOXK6i07qWm/Rc+60t5Wol17ktNCmruKbGWkACTRCTWJqpYsvWgrxk2/6sJU/Mbfy1r1HVsnpiUJmK0U5W5bI8Mqs6+51Snq8fZa82D9M44+KW78XasqjeJepdbs1o9e15kQLTzxPMf6/me++wx/jv/26KUi146uWiza0wpoD3UCcgx4tXHzzll6ZemwPoqmvv46ieX0xTcL3u0zZ/Vqao+aK8fvm0Uw4m8+DVvqGn/zLwXeeUZYycFWv/cXHfrKC9BSq/4DSVWe6eR2nBzddHktc3/Pewb2ceC2RN4Aw8pu9L2HF2wc5AipdNkHjYvdu6oj4fhxGRgKuw07kuoQag7wa1EGeItThRQCDCMI6ShlyeMeL66goMRuQIjhGko3WMJj/KIeuw24Fga6ZaRbKMqEBIB1VGjhAD9OBAdUYInu+OIAqg0OGwPzjum5Bdo+uoLUzq/W5HatBcfRDKQ29pr5tbszPdIKTo5DYzzNK83DUIdvD4ASMBjEfYwjGCEXCHHl8w8FeNce5kSQK6qPXogCcmXAEKirFaYQsEH3Arfc6Enu9AIPQ/dRh+HhFpRMRjyrnHPQICIhiRoj4DiO9A/NVZoVvL5CCGrVWH1FLK7Fpq9nHpr9Xf8l2o4AFbs67UAEx5uDrfxLvx9PtYudeQtt2DMSBzct6V+xLvE+DlezlawQD2zXbM779zq0zreEZaV3QM+H7jOk1RQp673ttADufQqpEvNT8p6zvfukkuLzwMZZbdsRU+xL5xGhr5m7NLUY6Fkgem6m7mCW2F8/uu308peWXxPHcKzWRfsgidkb9D0JEUOcpvnV7mNTLv0BHMIS1k6QCU1iggIIHnsvgD5OTB5H+97D/29Z6ltPqmPli5O67IdT29Gx+JV5RLNtpoo++eNgB9o402enVaw6y/xvUS83a0Tpzvmb5JhFcWhljd4rFaoZvru1SoCdSaSXEe1nGzXufkhR1xdxdEORMZoKAu72jSMHnPxA2kNIVb3gtyslOBzz+5XBmz1CjcFJesii4fJ84rdbI4lcV2rtIWLrpmazS9jigVcXMM/Ou5bC7zzS0s7yWFYPWmr1dLuKfqfllCaQPu+8f3clmTdc/9tbmhyyWJKnBsiNmWsm4bVWlo0vK2I+PXE8jW5vw5RML6O7ynEP1atPQlTm7vkc/q9Sv55rljgdRdbHuktxQt5byPbi3Nc2cKNDoAp3g2gXUm/50+K2eyXFDuGEDjyfo8KNUwV4nBGF1rgkuZFWmgMv6kKUblMFVIzyaxa13PUQGr5FW3nh2mUtMTDKjXRftBc/EvGnR0JZ3fmMq/FyDhf87IkGp1aVmtNb/TPZpfk+aul/JbT+evfASk0wGvxy8sFb5wvTYb992PKeMLd87GS9uzxUJamTUrM73mFlxO7p/LkOFXiRRTveaxGPOhataQ8bBr+M3WtbnvzpQP+HgX7pY2r+vm3tnBNTzlglslazGgctKeRK/HX7W4+PIeQdxt21gIADrW70gQ+QuUl2j3Xk8hHTrLkoNyxNYduuAGQjocQyqfBd0no8s1LcP6oQLnOsJ9sxxTPY/jbBkOAfKdHAs2uTKvp10Q8DxGFuA48RksQL3zblbafurOFWUWFIe+CQCiW7tKjiG3NKD86jn/1hib3vM7RN5Pc9zfZzBuUzpfUoeg89fLhY+wVSiA0neTuOUmjX/ByA/JRX+qifZbGBk78vXIx1JMgmH1dWHz5ennf+EJhJ4lIztIslOwPoDQ4wsI9xjxFREPAN8AeEyuoQnTdecKhL31jOu8es9buzka3zB1w13vwJYguP2f3b/y3Wst5EnTJhfXyGOuQ9nGHfJoOWh4HqMiFnpyC285sqahBKjnVaH0UbB2a1lKP+nrGZrjP8rn5UHQuTq01lJq3p2WIUvMpSQ2mYhWX+PDiGRuEelBm+I6r5n2PM/DukXlIbPM8ZfpiZDGoD9+ZvOi9EVXFAE7pJH71f4neco9AcKzPCVzfoSuv7ql5vnGklmUg1OkG0XKN4S0H5cH1xa+PE3TGNDf+fZaFRpZHOMwJmUt0GuF+dpoo402+gi0AegbbbTR6xG/llJkHS2WXfF3if9scJH+GTMSeI6YgXNy1uf2npzAbTC9jl/31gReGRdI3LtJfWI6xO9tRFKelYAhb4bCAv1of5xIc+yxqUtyqnbKUsWHQqnPM+nSvUZDGFn5mB0a5hxEIIll+klJXoReFiem6qAsitfCSl1db71wMWq4//Jfwdejrh/glS95LPFC+rqwKQA+qc6Lnpd1m36LmH5nQZT0FWIv+kqMysrWCkstrFUPfra9PJ4cTT7dmjqty/l96VsXoVug8eQ6TST9kZSJpTqD5wdBzpmQrRWmu8C6OlvFaebN6TKS1wHS/Q6q2KKchqp3bXZQdTOny/eTO/SlimgKi6OaFVLt92w19y1hzvuoPBph1vceHKC6QWyKS6cE1O9givOUlrISjQpQ3H8vdg3w6jk0J026deEJrfr6yXV9f00+nmpF3UusuIuvbDwTyv2pLvP867daMVesjFT8eZOaJQU6Tfv3VKLqo0/DDLlyk3cmu15Vwsz9Mq/FwTf7zM9H6RV/QG8HW7OEbxqqV1uu4ls1zs/Z3TNe6pg6e/46W9vbCqhzSCdR6Xpdf7PBiFR8gJOU6C8YpJfhFbj6yUlmKlPJnQIsU+CuQz4KKmAyqyyGZLFtLwaVFlitBinIYztYkT27SPoOJPFxFbROa45ZISZ2gWGWh8ScPGsRGBQCAtsI0fBdoxxqk71RARmOCH0vYzR0iByL/SbaXtgFjDyCAqEndSXfdYk/FpBewCxvSS0WmDKWrna95qdjiKN0ksogEqN9+i1IeyXFRuf86Yp1iH16TC4GAjpmBVkJ3EG/F0PiiavL+iju3DnV5UE/551iXPcQt+zlfn390w4MxvDzgN2PHfa/EsBf0yxlglqJA4EZu9REmVchtfTOSodY/fcYeEBEwA66jrihetDvzgBu8Cd2+AGEL3jifxcHIyz2eSAksAwQy+o7PShg16n/W3N1xRKTuBXKj22H9ntGPjxZ8T2FNwJ5W9pJuMc9HvAVVkoA48rtzBJnXo4fXLnjiz+A9ECD3LFjEAakX+upkEfO6+s+cXwC4O8BXIOx13v+UMoSn9Hqppr/MT2E7x/RVbgSWGNyw44d5Fxa8bu9k3Eq7vuR67ma9uKc1jVXX3K/X0K2E8v6EVzexkc7eDp9P39t38LWDatRfVQkt9ByyFz4lFKeOs+9FxX/BpuZuq6r1gLbVYOuOLasUkoruXRMskam5kXdJ2TyyCEqBkWAuhwkggEgdBhjLHmm5PWFivkneetIch/PxlK5mnn5xWVd9xW1vz9Tu0/tpn2l3L91xm9Al2EmNtpoo41maQPQN9poo42AGaarUsiIdiBdEyPFPSuY0pUM3BJfaQq6qfrnHHoPDtb/Oz+Xyb0Zxt6amO0js+LJ16P+RC1XflNgfb5WUyC2FGLfmo4J+z5dLegvXdd5t3J8TUs5UyrUVp+moCi+K+UjCiqXiyISANRCx3/nJQXDHNV1+B7oe2nnMrVmht1ff12AJlQ/r9LqxsIO2ZpaAa2judqvec/0S8WqnqvkUrqH1fo4p4BZX6/1/Vz7FqmpVI/WHTrtYFPmJ2UUQUByV3G7nqo1pyUff7aRUD13Pjt9/ha8Nr2kh+Zipp9FxkMmXlINylwZHUoQ/XBiEe21c+7eKdetg4J1Gr+al+DF56ZsXVr0kAHSQLa2dt/SwEaLLQ1kfr4+WmtJCECHW4x4TOnYJzQiToC7gGac+FMpk5Inhnz4IR+wjJFhzt2hwDbU+1mysjRPDhaOhQVezeVI2QFQADzKO3qorifgoDHVs4W7/O5cw63s6J6PWnZ5mLXcSfPv6Vj3PIAfka1ZUfPfAqLb1zaAq5YNHsuRb7wUSrgtg3Dy7v7nAVH7kH/NrTK+LDBgiBYXb1tfy3WHDiNGRDwh4B7EmUuYhC9wnWZ9GjEioEPHhAMe03hM3jA497f9e4aA0FbFdg/O3cvXXlLixnO7psXnjcZVKQ30tus9pO03yN+pB6MHcACj017oGQk8vLHvzxIzXfqPiv9Zmbfpt4HulK3Xz+aWp+0qRv6RLMtSMw99bEvLI3g9vQ0nslSzZd5Yvh3Ppq37qrUbEsh5pVhb9vS61HAc59tTq9OSYes1kuFMeisCsXOhYpjTvF4ik8nmiADnIWX6sO7Zlv6ouNfsx2mZG4e70UYbfcu0AegbbbTRq9N76WMmTFyt+QCOuzYvJG7lRF2M85SVMakrOUfPPHN1L46sJ8oNOPHiq3uhKqvN0r9d70/V3G0liZFXHuXny8rymabn52ROvZ32AUgxG+X3fB5TRcNxKkAVd/9SPb82nxrYMqGp6VKUG3CRK4h4vo/n6nf5kTYVpmvFWa3+TW4G4esvEqspskRxasqgU/wBZFXba9Cbu+rd6Exap1ij2irAvZ3WopS4uq7TAwm08Yrf01UVNAGxj7XEzyuxtiqf+vlT7GkkKq3S0WK2tk+uOt1Li3Uhtz9UzX5pyOi2io7zZpC2Eypfsm/hw6V8p/P43Fa/fW+dV+LllIJ1+Y2c6/H9VhpJv3Fe6MMcszyfpHlBuZNY5y+kAjzXPAe9v6NcXoe2stu6s1WdsqrzvPLrzQ/HPX1DS1aKz87lhpLv6zUw0fYbgMEQC+BbVutel1Rcqt+Dw4PscURgPBWAZv01CyDXLLK7bJVJBIQAcKQku1BwYbsICHoNdVlNgRDHCAqMvt9hHIeivf1OorgPwwFgiZcOYnRBW6kyQug6/R0RY0TfBbFEB5BBeQIHYBgGdKFDhMREDzHvkb2GGevQJfnCXLrb78iMOLZhIbNEz+xA7kWCOn5z38c/sz4WDj0/FRCKMRCwUw8Bns8gAiKLJXqPLzDXy5LsEYRbOLttMEb06MG4B9TFOkjAWoYcpLAY9Af8OZEYCLJOjHjA7se/IvwqXgJs3BmQ7pdDU9Re/3SNruux/89/w6zqRb671TH3mHgzgoDDrOUdEHHFhH2hRFie9PPrDzf3ozVbVNkfpbT/iK+z5T8DyRk/QVzTB8hc6VxYHSD3pY2HqPfuQHaUJM3RzLfK4eyn9O0FTE8u8BfaVz9P83dBA+Pjmqd1BfUBhGlIuJpvX3qWc5neW6p/Tp9l5Pn36mBw81SXv2bLyUbMNVjua9jKt1osCOg4FDLEXPn2/UKyCS/7oS419V/aV3SB8bEIGCAfb8HkOHufGYiEGMQiXfaVeb7CF740k2u5zH4zSr3VXAZ13mzNKsWizEbU9ycXG2200UafnzYAfaONNvr+aIahm/CQSb/EmeN0ILoIkubGvcq3DpjXKqzSGSZGOhV+Ca3WW3KvdSe8PLf691Lu78Wn19agR778m9LcF5mo8KkSlAjFYZBLjca15C3OjT5Sn7Z+f2b6VtrxrdCrfY8LTqKijqYXSor342vPRDlTraNn1WMhjeXfUr77dE2w68y6bbTRqeQ9XyaF5VuWTZntfYtNtwbYP0v8zAzY5aWhVnZfmpv/VumYpd1bEaV/Apc8BOA22rM7MB4QCQC+OmBlClJRda8GQsxVPjvQmIB0uLMApYJ3OZxL4cjoOuD5acQ4CjTY9QKGiycUUgt0x8yzWrkLclwMSiJC13UYx4iO3HandYxjxK7fIehJAdb6W9kFekLSh5EJXejAHDEyI1BA1J44Oh8mgHmbm5gCf/mtFlTWOlDMBEQe9Vs+pnuMx3SYuMMXWLCoDh0Yt4j8qECYfHGTWCIigsZOj3jQv1/VQ5rk9/zrAVc/9rjFX/D86x4jHnGF7JI9genWrhCADrj+8a+Iv/6ueQLQ+lrbGOUhRwKw0z7YgXA4g5FpsT+nsUSX0Q14aTBCDpKMEGvdTp+O0Pabxa8O/5Bg8jwqoqb/orW7BWGEWO4TJI7888Loq1s4l64emxMn5FrHPOd0DqedI/9dBTxjxfx6YS7y9G336pp3X+Ll1+R1yjsnpW8mzmtw00iDBVVnDelhbUthQi7MF9UHJzbaaKONNlpHG4C+0UYbfdc0UVbWD9kpLgoAvcqnkTe5//qMa+VkUp6MVhluFTEpbJmZf32VHU+uzJ53mZK+YZKHu1cBHTzH7TtFT3ovxdRcFg38SeKkaiFM4nceJVMYsVfArX2xXZ8XkwHiM4BRy5XyxALdD91KoGvR5QQxH4HutPxT6APfFrx0JmRFaXOdeCF9rxar3xrV43NpvL7kWRotZw0bXRvJ2wGVNFWM8uRXAQy5NbhYOunIXKmfc7UGzdZ+/f36GVdl1pbrBfCxsEd9T/TS1WlO8fd6CrxjNT6vxJfW8/j7XM4FuPH4VoOQ4Cypyr+rszii7J2zPP8swLnRiGzteIzHaD1bxSejvT7XNNdzL527p4FkL6NeyzvVBf5LyX+7AcBOpYEb13CGWA3DpTVrVpN5PF/srdaNuuKKwVFcqHOvtqcWaz0qkBvV9lk32b7vMY4aYZ2l3PGZ0an5egidYYYAGONBejIo4k1qIR7HQWq264AIcBwEpCcBfyU5o7P0bC7dpWVPzyOYGddXPUCEq91O1yiV/yjgj4evuO53EuOXgagu5QHGrt8JkDwsW/cmOcw8sBmQPzMgD27xvOL8PTqwhlqT/h312wTNZ1BZaKTH5mEl4xkG/lO/s1iqX//jBuMvO+z532BYjPMcBuxA6tJfD0QYMN7r32d8Rfz1Btf/2OH6p2sA14gxYre7wm//+d/YuX6JAL7+11fc/fMO/a7HCKDHLchZnef23snYUGC9Q2mNvYPEW36uen3NOiMJOdVpPYl+wLwptGhpLFynHPz8k9/PJM+TVTdJfz85TxTXROhA6j0iWzN34NRvphAfnPRJsMMHEh99rn6tluT9kzXsR4Cdtvc8syUueGfTKdhoYsup7Cv73ezSlQxW+ib1QTb9bykplId7Lr03zO037XLyaCj49pm8s2V5u2NqicjSd66Mdj5tkhANnENwpfuZudNzTumvufjiYGu8rnvqeWSi05oRsI7t25MeqDvvWGfq84mMVBW6aTY22mijb5Hm9OAbbbTRRt8VJQWA/xdFecBQRYfGLzJFQU6bMtDMalGvQTXAlzN5Mb0cMHxncmDtUq/4Zzzh4E/rSx8b7WRS+dPAd4knSGgfM34dOmf08Mzvl9ahzmvpuk5vNgL271heS0SYzgWZa9M03xrxif82eht6SV8n14Aur6U53LymI88Xrq3E9xovc2M3Vr/rf62xvvibstJ8mxsbvSUZG8nV9ZuVbyxsUaFT81j30mcDzFvk158AAWG6mXT+9yVbfiyvz7KODfgY9TyQ/65iwRqpmhM8BcgD7hSUu8cVvgCYgoyLvKbGMifKICxgYgSLC3ZXhUAB1Al4brIGMzCOA2JUeRUQV+v2j5zF9mEEOGKMEcMwanoD9hXQDyEB8F2QFocQkhv4KeZHiMy46nfZM5cEaC/kqxp8WuqX47LgVOar00nNxfH5aHlpoQNZyC8Bu2z/T3VjVN6YBVQcf4kIfw/p8ESnUNuIEeyswmUcZWkkg7OMAQ8YfokpvEDoOoS+w4//8U9c4T6B6FbuqIcf/v4f/8T1j1e4wg/ocZfKkX8PDsjPaxNgB1QYz+Bklf4Z6BktWTHTngiPkIMaEezimNv7jJEYIxFGIklH8uX8txEQntBDD1lA1vPaLOBUGde+OLmKF3JprQ9K5wwYderLr+d8Qoavu0KfnjtP3sv9857S/XS+TygZ6Ni13POqQHtTDuLwxLhjqYVrW/5avfR5VpeNNtpoo9Nos0DfaKONvmGqWTieXnoLGJTXxt0mK3VjeJtsvknY5bM55rkQkhKyEYvnk2JWH/nOItslaa1w40uvBd7ZWrkXlspZfMb2r5I+6qKq+0X4zXOAb9fgMkYul3lVsewvJYoWAnUNkLnC5k4ll+fLRE1RJQAAIABJREFU9be1p5LfW7HR63yT3qxRXrvNNcRdvuvz8tVZUqjU96gxJFoA+/Tt1xQDXyf/j6CE/h5orp9T7PPmw/b1+rVV45HW89PVaarUruYJtecWZv7m1qwDz1t1aJWNum5Vm5q77MJ0OWnc0/H0PNeIV6a5dewtlFw0c/996X1r86brKZc/bb99ix6YwlCXbfu3YnnuaWz87tCOXXqMF5rjC+tl6JTeagM5H5cGrIj7+krkLQVzrGjCtcp8Qa2ou2Dw700CSsUV9IPKdfJ0h3swCAd8lb4nc5+u36XrQDEqb64AOQlALWC5WByOg/TG1fW1xDNPQBwlTzLjMGKkEV0X0PU9ui6oxSvAUUeNiiMh+2AHg9H1XZKbRGQRR+DjGKWuKc65wIjXu966Rqzao7QpUEDkiMBiFR8V8BljRFT37YC4SgcIFDrJxMlFrbGdY6OXYFn6y+WudaWyzhMhWaL7sX9l8JpmcBtJReuy9FETmAWqWaqDvyrQegP6LeD6739D/I0xYkRERNRI2naQxnvyIgAHlvG9h1mjRxD1CCQlDfs9QISbf94gDj2GX/+ltXvE4y+PuP/nTyAQbu/v8Nuv/we3/8+POPx3wF5jrkvaqSe43EvyK0BclO8d3NiidTLcW1CpTZnytaTAebmS2nzcu0fXIHTMCTAHxLNBzo9gEdPlWzFudAQ+V307VdNwysH+JlmcFo7pk+PzdPNPqXlR65Ra3eLlj635SV5JMnLZf3Xsb3L9SsgeId76aG1uX2tno6r9Waio28OTdsI9J/c9Ufyt/QHkGmi+6klSQnIAFLQWXj9Fmk+KnUNACGDv5t0eMRAig7tQ6mrcxZLs1KKa5zj12n7UluhLOqCNNtpoo89OG4C+0UYbfX+UJW/9UwmQ/j47BV+VvoyH7v5WNCfAUHqnZsCnwMhbxsH8jMTpX6lkWUOXMhQ3pRYAOWzhMma7fk1l8QIolLyAVfePCdmTWOh0fCx6wem40likSFNS1ULXMaXBHHnAqQbPP7oSeYm2ZeDbpjXft1CeLLw7d7023do6NRUlVCpRjr177J6vx0vngFdoJ8WmL1j/LSlJN3o5HRsbG32b9JkB8znygK+NaVOw8Ey6mpZ65VI9dmo+7/WlXhNEn9tv2m1libUMuBBNNw5MqvO7dTy15BpwA4DB4QCJQR7TuxbmOMXRZmSX6ZOK5xjlgMyjEIJ6vQpgRNcIUhA1AIhJ/ghdB4wW69sAHS26cJWu9VTAyUAgq4elIwAjR4AJnVq4RxZQHqOUG2oBy/JM5XjY8pwx579gyXXsKQPqlj9VgslUJsnQmMQfZoyar9cUMB5BuAcFgsCmEYxHEwQhYyeXucNfMOKAA74CyOvDiK84/Bxw/c8AUMDTfz1hxAM63CMgoMcdDnjA3Y9/w/OvB4zjgNBdgULAj//rf+Lx4QG7n3Y4/AxXu3kgtYccVFm797Z4zfegZwA3MMtwjX9OyF7fUIKiS6FEnolxjXy4Qt4tZWTWkdABuIf4L7Dv6XOdv/Y52agqe71mPc+lWg44RaexPqnUsgZJTymn7ifgUuOqloqo+aR13abLcKZOnECsDSoApw/KAkcK2+FAdK9iDMzgECS/qqYfEbB+ax7/o7V/o402+vZoA9A32mijb5ZmQUGgCYaXLLhz1+59LBWAOjK31hDUChCvVTfV3scYU3w4tN6Jy+0p8izoGDy6TC9hRCeC0lSHcuS6vOPlDC4TukKgZxpU0KsyPSZUnhz7fJpDkoOK+OrshPlXANGtpOgvKmrJbvKgEj0duGRjdBIL3a7dNKiLXgfKTR3nzwnVS9etOebj0duzqbJzjtanPI/I/Xejz0iFEqb6MTe7ufGsVnytLb1WZrfer4GBueenXNdtKFRWVJVJU4UOu5fmrCUm8SHd26ktZ08eata/zjOp4ZcWtQvRt7MONDiQI3vdOmXm+6rE3q707EzW9uX05K0q0dByn1p2zUetsTyvx8nLebH3o2Hmvrl3r1vm+afWu5f+9PUavoZ/e0uS+M4Z6Ls01e1lmIhFEKtPn24KSWQPMw8po7RfwCymCVd/vwIR4elfj5qok76PuUQGo+sIkQ6w/Y1B6BAEBAwBV1eiqts/PUvdQra5FBF1xDiO6HdXSV4dhgFX19cyf2NuQxxHiBUsgTpCHIdkcS5AsKQlIlCUhgUISG/guOVlQL4K1OI2HupanpAA8uEwgDhKF0RWsB8AdQihA4jwvN9niJFrW/PU89r/+UsSgLGyQN9rAgPO7Z+NpU6TR0j8a4nRLvcC53HRueK7xowxOW/4ZYB5Bgq4ExfqbC79H8AE7PAFB/yBHe5xiy94xh8ppvYIIOIP0H/9BSNGkDpc3+MrCECPe1zjC7q+w/3/2ImMGxnPD4+pM5gjAm4R8QjCLUwCJeSDKBZywB/sYUiM7wNqe9o28dmh5uQ9plI2PpWeIO/fI8+3a4h1uc83xTkvQHT7uJLuWRnQK+S+SdbiYASWeWExzHUW44qCWKFrdmzzn/38z9cWDqiW+zxfXkucjFY/HeelrIBapvee4+pcR+2fUB1CMEpAbfV8rPbsjsr7dT7HZPpzKberbGFpaT6tS+73Um7LuchTC38QqxrXeof2apVXdQAg5mSZ7i3+mRQYtwEDBkUAgYqCghZEkfN6TGXr5uqzilqbo7+eK2PuvXeg6Y690UYbbXRZ2gD0jTba6LunbIHuFPSMFPfcJRTFpk80Q9Rk2+2ZvdvQ2F+M1ojDH49UzC6uW7+n75SpWqe9lygpbM9Q3JIKqOaSn0AgcwfJtRD/MakAyd+AQhJOX6JOaRMhx/yz6/q3V6zVad6DPvbo2OhcKtavapBlxdqJeZq2DlRsG16p7stOinbk5Y1nnq+5Ln7RdO4srbyt9GvJ6nBuv03ITX6yAt57IfgOaev2TIpFFXrIt/Q+VLOl53wcrhTu9f259N86eVfSdbdadKa3dF8+B4V9hK9hrtxfC0RvU7nD7Rg4EONA8js/e0DAXeo/sfG27/kI4AdJmPYXBWgUcYvxGUCfeFQBX3sgReeGujxXl++WB4kleFSw1g7jdn2HEIIC8wAFUitrRlSQO7uP9+ASKXjuKwtwjBghLtc9tGRAGusiZfPWA1GE7KLeg5gBYiEfAonLdYa6jJf2dV1AHMeCH18zDo+l8fOtkAlUXrPDGp58pLS6HgZGZp5IvoXEOX/IZRIQ2KKuMwb8mXLc/aPH8MsdoK79rYQRI3Z/79HvdhjHHn/+8nsq4+qnK5WWJPnIY+q7OEaMv4n1uwcGW/1jz7rq/g7ZlftnoEiEjmRsRWrHmTar73x4vZERCfh+xQwmQiBx2T8CICaAJQ8msX7vIX3YgRCJFbjPeaG4dgAutcd0sc+754FK9RIRL6mbynIbdNo2ft44+Nb5uJeq6ObnpILlpkgKtipQsWZN6hEZHclcaKU5tb6XwL6Jp3LuRhtttNG3RhuAvtFGG337NIu8Fmi4/5mE++w7KSs38w9MQXQX38hO4PtqmABMRBrnDonTpQLd4JdxsmWlXjF1RTPM82yes8y2P7fr8mhIoHZ/mt4JsK2ia8HDuSY8iZIGKVtUZ+EdCUQX3GvaEx6oOoXOEXgm3VeDeoBT7LnnNZoGTCzRj1MJZRNOb/Ncri2Q3P+uwfK63Ln35+icOTI3Dj+P2mojT3PKsMWbDQD7LEr5cLYusbUG5bWVJ3OZklKW/VwG1l1X9Sa975U1x/A3du8VTXJltYgBRMr7wulrRwO9d9fkFgjrr21uLtG6L/DZAdK3q72zfm3o+9+sHtWcP9cC/RzL82+ZvCUogGSBukMGYd8j9rfRR/sSIwTo2+HyfVPsURUDa1d7d39PwEFfugYBeExWq+m9EMBEGIPsUF//rRbqYQShB2MAAQj9tYDKDIRrwuFpj77vISHQZWcbxxGRBMTbH0ZQCCDNH2rpzSo/8hiz/Og2Yuo6sXjUFosskt1JhxAAIjCPbo4zQqcBlQwgj1H3amE0xFId6j4+4ObuFuMw4PlRLKITCNh1OOz3YI66JgTpsw4YYwSrpTnHiD50OIxq42nAozIxx2IrdzmkO4Ack/mg96/E+D2DUXoRYr4XZooweYgBcRfOQI8viRfp0GHEiACSr6snkOTLPGjehJEYPd+BAAy/CNyegFrNf48H7H8DbvED+p96fPnH3wEAfb/LhxVilmtv7u5AgaSPb4A//8+gIPojCHdStmuHlJEtruf417n79jeetWa7d46wDWvkWmtPr1LVNbLngZTGjXWifJihLonA2BPhCuYNQGS1kcxrCMFs0U12fAZwwDzfC2R5r9Zh2LUdYoigoo9NnxHIG3QEHS05naVNadx9YL18Xn/fqY6gbIelq0Mz1PdtnJgHi7fb66UnCi+AmB92uV3V+Kn0R5bjXJjAuv+a+isAFHWMketRYkTWMqItWJSEKwLSKa30XfVvFxkxhKPr5BK11DxL1/V7cM+9t4ONNtpoo2+RNgB9o402+qbJM361Yr9+nn4YcM5cHkfnyY8FKtMkwcZZDoYq5ZLC9Jiqeh4AfEtWlqu/5+czJ3zMXV+KznEdageH7X37zjnu2Toya4bXorXj6Txwapm8xfmaOpxCNSA+B5S/Xs+uo7mR8N712uizkipyqkFeWJFW17auJjBctXBrryelNzDpep2x4uvY45P33DpakALZEeXfU/bE1rXfd9klIldm672NLk+vsed8RjLl+Xv3RcHqnliZ2gL9e7c8N2rFSa8tQTdqU8BlAfTm/lPcmx+brX1B9gwD6SKCwEaatndgV6fAByNcd4j7ERwi9sOArhN0JHQE4iCHuMHogoySyBkINBmJAD1sQw68kCf//v13XN/cSNxzGMBOaf8ntbgdxKt70eK+6zAMQ3ovcsxgZMXDx3FE1+WRTHpqmEC4urrC836POEaxkte6daHDGB0IGF1c+GZvL9H0LQAnH/xZIlMDcFXURL6jnCBbq9+i40dEPCDiFhEPYFyjA8CNxXXAn+Cf73H10xUAIPQ9wIxxEAv9cTiA9RADR0YcIuTwtkhXBt4H3GFUEN/u71x7yP2rre6BdT3/GnSlf58azwjioN7rB1pWuufQPv0iXCkfKId47LC3uHKPEOW5HHpiPB/JN+t9gLpXaxm1+W56K3POXN2BSzfHX6+j9lxaQ3k9arz/BoNpun57TcCad+bSLfdkdvs/zdnXh6rvBtiw4PV6p5l+DMyI4eN7Otxoo402+hZoA9A32mijb5ZEODGhP98rLMsBCEKADJ6727NS+Jzlufs5cVerilGLFWfiM7nndf2XrmuaPD9V8Xla8sW3vWBSPKFW6nyvFjOXQPT5mpRiiil9ZuOAT05SnyF6Tj4WgQxEV/drDKgCDJfV7pxRv5aFm79eFMBP1rDYTHwdYKCVLxX3/S9qvHFGzU7qg/eGQzZ6TVryLHDuwZ+16Zpzlpau1fIclGMjOrD82LW3aK9CjzZ7wVune9XcrJpuZqpYX5oCE9Rew+p3jqvQbF2+hPLxNPq8q8Lr1LweD5+3f84lQ7GMO3yfPvC81yW5lE25KzRWvz2I/pYu3DeCA53dNYAlIOlQuUpJce0VBI60F+vx0AHo0PWEGBn9cCWvdIzdFWEYR3DHCMMO3TVhHAYwAeOY3aNTRxiGAwiE0KkdLJmNrFWDNea4XIeuA5hxfXsDABijjKhgoGsAiAnDKAB53/d4enpG13cSS73vMY4jAmWrxoAO5u1mHCK6LiS2eRwGcGfxzEW+JSKMUfLf9T1GiogcESgk1/QgBkcd78zoO4mHTiEALPUdOeJwGAA9TGBWxXA9kKQ9a7/35AaoHFZ9c2mUkKLHAXcACBFfi++d0rNYnYs7dkKPH3Dz/97g8T8lOnaHOzAYIx7QMdDhHgxGQMABEmd9xCOu1BJ9JAVhecpBRnrA4y8P6PEF+EliHd/c3WE8DMAYcPj5AP6H1HP4ZUT3Y0hyr43aqOB5p5BzB2DAo+8adMhg+pXeP+izeTjRj7zL0/7I8yciXEP6bgBjpwcHroEmmF2ME53wXNw3Bja3y6zZb5CNHQhB12ebE/JucPv1PJF4Yih6r60nMZ6dfb3J66yqfm98qJrnrqVdRo5ZPgVxywy5upvGV4qdrtfq+qHTsBAWC91GpRkXnOfBYJ3IPQeiH+P/cz2RDvnnYxNw1/6vkGnzJuuR5VsVLmsJF97CUqgOVqidJI38qwSsiOLUiD0OkcGBiv6l6uOt7nlbO0uWNPfjmvyOCnuvRN+f4LDRRhu9MW0A+kYbbbRRImX4WUWbOaZvSQCoGU1khnnj7OaJq39A2f0v5b8nlhNnWJqvoeyGX9H671xp/JqxzufIqwFaZS7VY5uhG62iBaA3/a7SXCx2d1We108sXRdg+gmgeQtEb63RRqn8Bni+pEuZm3t+XzDw3EIGHuvQYtel4/O7pXT0RWzrw9vRewPq3/fOvdFbkenDbXxvIPrbUnueH5/90fZGvSb3L++PIxA7BYD1GRMOzwzqBEHprjswm39eTpsnBTjA2IEioGpPIoApAykAQIRoyLAmjsmMOleYmTEcBtkbCYUlOUj49pHHFP4FhMKLFLMB9tVeqxcSqoxBgRA4FHu2gNgEGtnlx1l2gpQVyEAlDXt29NNMd+4WiCh/7xXwekCXjkLc6ZsPpVxK2veUgamn/3zCiD/BAAK+wNB4aSYr5Ap0uEPEV7VafkDETQJfvcwLLcc+1QF/Ysd/A4ExHgaEvgMdAvp/BDz9InBxxCPwa+mZx0BxoUcQbhA17ID1RzqMWPXNDhlEP0avhY1doW2BbsB5RwCIsCORLA3E9iB62204J1VMy+MbFf8l7AHcaGgEYpIDJJRd4Acdqgb6e17Ze1OyQ/Tn0Kl9bLx3DXzP51NrWk7jtGYNE+q8XqwCkxasAdLrQuu+eBOq2jtXtgHn6YIZHEn2B1sc6pdn+pLMSwnz0ZBYs3XxxZga64T3GdjcuG+00UbfNG0A+kYbbfTpad6yJZ3v1IQVU5dOtTvBXY9bzmaZTPBqtboKXaqkNyDVwHNCtjy3k9BeoKGJFL3Y5GZLp1VdL2JckryypVZi5Aue3nOnWrMV+RFyQkKZvhaMG+B5bXlOZdys+SIbJbHkx8z5cHAr3rmOs0vEq6pr5bOcCoxTRUEorqvn3ChndZVLVdUckO0zngPipvlNn/u/WfXh25SVcf55rh8V+bRrWM/X+c54F2F9o7elNNiOfOWZx2s9UcyvE06J3XxvmpLtP2rNksBx97xUUel9N41ki+TihexxJc8j2/f8Kk+qDJ9T5M3p1yxt1F2hWOtp8mNeUWWbs2ZK/n6ZsPEykgXNJM8Tae0br3XIy9NpVsGnqS5Pz/9IXkdqcone+shKv9N7/wLlLShP577tsRjoG5U06N+du/dSEH1u7fhs32FE5lPngL1Wm1LM6OqZj/UNyP4XoRbcFpN7kpvuWNWDtG86WYYA3NzcID4zhvEZ1HVqAR4w0AACoe+DpidQYIyDANhj5CLniTO0MSIh0Aywdsz19Q0O+2cYBh8VEI/jiKubG7Fa1gxT7HNtFlFAjOKCnVWGMZL7fapLsooPfmwxuq4Hc8Ru1yOOESNHjD5PpRQbGbFYzNgOF+jzYRjAALogsGgcFZTWmOty2MB/nRYImi2FQaHk3RU27uIPAtD/PQC4Su3qY8D4O6P/8e9gQIHqh5RBJMZIQKQ/EAr+SSyMr3Cf3N7LXZH7e77DiK8QN/+P2LFYhguo/ph71DFCAbcYfhlx/R+34MjYPz5hd73D4/9+gMQ7b4PgcO3tca/l3GPEiIjHZHXs55e9ccwCvKZT9iXzIlDrZTwZSP4FhIP2D0MA9WdX3hfNj+x/DSTX70UJ3HO1pqSn0GvX9wTgRpQ5ed6BU9x1gHEgcfF+rVzzntz3KKaJ1JGLGpQ6ENMj2F3frwKGUvFsTmbOB3fLKN7l6pItwUvL87mcp3ezjsvej2X+qa6k7eKC7z51J2rqXRbq185jQT7Qv2ZRHhLzY1977j0q3kvtI5mdForDPnCWYGiSh41hNstzBlj1huZBRBYdyqdkivU4H8qJC9/S0+S71s/dtKq2z4n4lWXI8jtXU6E6XHLCdT14qibWYcI22mijjV6DNgB9o402+mbJwPEkFjAD0YGXBpgnl+752uQmYWah3Ji+6UzwfDrRz1NiowWniJn5qxQkBeMHgEq9QEFLymFqPD8t9vZlKQmlBdfcUHK5214ZlWGS+Xq2FF35OttIZKy8DZL4+wRqYifzXvyrDwhMrD582kuA57Ok4xOM0vK1aF/+K6f2S6KZ30Ap0CzR+bHOj4lxU3GzFvvrIVdD48Gl8OB6aR0/nU3lrOWifJ//PK3rgY0+C1FSQlt4kFq+N2rN9RDMTam87RXw+Ue5MJZjsFYgl7OnpTwonrMpFf3eKOtGSDuY/Tcr5WTNjVkxrRkTuFgfKhVm+m8AgQNlXWRFVP2t6x5JrH+sYjYTW7NLdKLVihbcukSNNa6RT35G8t0W0pxD9b5U7EdvAKDXNAc8CZ1fn0u3pVW7Zo3doY41W9hUefj9qeGKueM6ZPWBzO+wzy5BpdWoKGisJ9eC6a15NgWR56GAj0h+H+qRDxwUaWbaOG1qXt8oPV+CVfI7NY0QS9jIGdoiAONTBN0Q4hMDcVReYcweaMKVVVJdmedyCgCCIQA3RgAECgSOlj5vhGMcIObqMW/qmv756Ulco8+0j1WWNRnWt5eIMBwOsFPhCUBXyYE0KXt+IRAQhT9iRYLtPYuBXjqxnt+HI8f2IZwT0ZEZrAVB2xF/13r8jdIhu/4fHThGUJBo9hH3gIsnTmBElpjYQQ9eEIlL9Q4/gBFT/kGjnQNAoB8wYMTIXxU0zxyi/ZI8bxEQsPuxw/7XA/qhk7r00or7//EF//6/D8XckH+3GB0YDwD93zsMvw2IYER+xJhKqq3fp9bwp1Ah7s8lSvNtvhTzxhFAuAYlYPIGwN6BhSPETfiOsmv0wLk/J7yUzie7DiTfO3lXipzmg6SRMbKjgNAReBDuNyrPH+DDb5Tgdqtvasmz6BLAfZXcRaIjmdcZ1GECJ3KAW5teQmu0Fqyncev21DubX+Nen6ZSxbHVfvLuuRVlgIP0XKRqXMwYa/i6cWREiqo2ZLCemLKDUt4cQM54mEYngEi8foDb42OpSUl/9AI+jrReaXwSkneGtNUcu4bb+6tPUVy7OWDXLxlbG/+60UYbHaMNQN9oo40+Ha1mcET6yExjNKkkK1cM2JT4bpweJ6ZPWf2iROX2RMGRFbQFQ6v1FLDCFAwO+GDHLM/Ik6co+P3z92H/cqlT8MKl8goRTTyxtPCCZLOEZUFgipVT88H0BPUyzQqxJnAbIFY/wNsy5f4Ufbrn/taCXPG8quYEGFtshuQegAk4v0R1lqagyiqH1vPyNxX382yci1tWQ+a1hLY8Jgw2dXVwQlurjI2+IbJ9gbLy2Nb7VuKj61mtTTJlAvw6V6s5j1ZxoqjK174+Xr2WLWS4qpDVZU71WSh+3G9TKDLMVfHxOTGXf73+F91GxZ/0qzwgNZ2Tp8zQl87myTrWOMS1dP/t6XLlv5dSilRJDpzemvdTpM3V9I3rUwFqpxAzHx2/7z++PxYZSN4j80+ep2gBx+dSAkOLOLgvo9f6mj5OPEH6Z+lAgYHjcdImTs+BDOswZKhnS94WRwrXwGwxbfG77ZHEmX4CnoCAK0QecBhH7LoOwWIDjyOQJAV1Sw4AQfjtYRxxf3+H/fNerK31G42DWMqHjgRE0R1tHNR59wR0IHSdOrcm2+1DavfUHboH8DR9yE7Gk90t63sKZj4/VoDtbodxGBDHMYEbzAI4ZwN6xn4YwSwx0pMczmIhPyKmNorVvB4ecN9sjlIs42r9YscsRGQuPvEnv0t9+x97PVAAIEZc/3SFrt9hGK4BZjz++nsBFA5kgKqUN+APK0bqoT9G9aFDuEOHez2KmEFwBtIhi4hHRGbcXf0T+IkwDAMef/0Xfvxf/xPPT0/Y/9ceo74j8tat9tWDArtfMOJPALc4/Daq5XseGzFxemLZvYPMqwgBqiNOt0TP/f9CqvaFANJ/jD1kXF8ju3iX9nM6CH2jdUj1T9OXkotr+xfIe52w/9rHdSEHWPrnmSnJegcAe2bcEOEJjDvQxII98fFsltjsmpf5kiRFENKcF51U7o9Kw+LWqfLgjbU1rW8zHyRM+MzlLzeXKskTWtDIuT5zu4Lf19aOl7r8uTx8H5SagvykltX9eyGlKUuqZYvSvt/nw/kpQ72bNPQBpcrB5evu6bhhmEcLQGNayNpKlDZIho5tRdizJfqkyClVD2a2zpysrnv1Qou3m9yiqtj6elqtVddp7NH6sVXQBqBvtNFGR+gUHfdGG2200eegpOnn9C/HNWd3O4Pn/j6K10t37l65Pa/oZiByBUZ+L0wZI/ujZ3+3TpVTqJyTfh9J/1F70onf5f2KIZ8DVl8FcM16tYk4icbvc6lLSo5s0V2Xsfaaqn9AtkpotcHfD9U/uV+28FJt/8hjcaPXp9kDNTP/0nPbV8BJkVk+zyoYp4pZVUb9Ly5cA9Pxu5xfu8W2bs+21+ddrfOTfObyd++0Ysu32nAu1etPvVZttNFGG70WrVZ6f0dUAx6XUl6xlz2Udis2jxbw4rA2AIRIg+QfIw7jmFyPd10nlq+RMA7Zh43xqQEBT1+fs4tlGPjAafNMIKDWwGQPs2z01toprJjVkDmDMfD7p22wjQ5g10cTsCQUMnAcI0LXKYCkdaKQZGk74GDkPRDn7xtSXaQLDRZZguXatCw3iov1kbJdNpjBo1ifA0D8NeKw3wuw/2tEwH1ZfxBCzYQ4iiiOzidAXWSlO3T6L+A2hdSxf4e9RPR+/vWAEcB//3//G8NhwB5/LPJLA/4E4VbL/6oAuzwz4N2+bTjpAAAgAElEQVRqvEOO6W228gFlSIm1dAl5aM4Rn92/qe4/IsdzNxlwjpK79zR/7H/23I0tZjxFFkB4ZHQs7uR7ljKe00EdPYjBwDUohT9Lf6t/88oMne8G7ocACuJJYumwWcFfp39c3Vv+MpeWY9fO0lPKrdOu58uX+64lA126R1r6iyWy8eP1N+nZrBA2TSd7RwPMXqhPKruR7ljdN15lo402+h5os0DfaKONPg0tWQTV7rRFUGE4/+vyM0qCBFIUrtstkVFpi2AKiNLq3KV15ZrrLIJYGLSqvuSyfZJ2fVKsZf4vLTSlHBmJA68tzpu8v3kEoOOCXlXSq1I5pFw7ige5zXL690jtiJBPFWcF2UvIC/9JMeKCQZH6xbKT1Vlf1ga6W3m37/l5QEl5UQPcp+TLLq9paeXdFoA+bVFLmG8cVVj4ZMfGWkuw3+jbptKKu1zjfJr6ic34ictZANlbiiqa85W+lcnmSqvcNddzTwglIK36+lId1wK/GaWFgVO4p3ldARWtc2dLc83qAlfH2bl2ZBLOPTYF52S9+lCT+kNV5kPTGkvoD0VuYrfVnvn+2jm90ecis67eIfNzn2EE+/X+0lS7t18SnUhjyBow6y2PDWQGbH9mXAEplrVNv95tNgNZmeW8CtXza81DLMKBcNWDQZqpAHEdReyfRwTVvlEQOYAp4Ob2Gn/++TW7mVYZISIqGKKArrpxN4vVQNk6kWMEFNC22kaz3M7IIMw+kd39yGPijBmcLOaJ1c11skoXWTdGcZ09cvaNICD5kABAuRdT+TGOsCAx17uduEFX19lk4dK0y3Z9j/1wQA42VYbHosn3ta+c2+C/zxUyUAwAI/2RxlSEhIgBAePv9yAuA0Dx7wBr7PabH68Q8Xc8/PybF3WPUE50wJ8KYsfiPkMA2k5vBdxh/+uAZ/xZyM5ff/tXrhdkvYh4RKfvAA/I4Pmj5v1YzM8WL8nIB4+lnrnf2F0vUc2XrqFrfWevZeW82kfKnxr3HgG1wUeSQ5v1c6H2QipBahwKfU+SpPEExi0Ie8uXZG3+KwgDZNxkq3fGNRH2yIdE7O+IRv+QtTSn9DG1bR6PiFl35evoeOqUN1suBdeeWpTnQK4hVTkv0Rz/YRbtdvBnzkL7JZS/yhq53JXvhYdqp6rr6fvKf685DyV1v8l6FdO3zYeZqhrXfB6pvtDVjoDiIFXOx+KkA9Tp06h1CZTmMli8M4AI45JlNTd/luX6Z5O659u+z9bofS5FG9e70UYbvRVtAPpGG2306WkSt9P+mKs5BmDMprG7TeC81OD7+FJenC6YRpeeACDW7G+bJq6y6+etd2Zzaz17P3ayjHNn92pASe8nYQsfggOeAEFYECzdeEv1fydNZwaPK2Gr+hJpVBK5sV0+b+Vd/7Z44l3KP0y+eSu/1nUZddnPnHZnEqazKzRSz1mel+/mXx9g+G30Sag1Vo4BWvacOWalNMo10Cuq63UnvV+tpGvqMk1DxXKVreCA7LTVlIp1/XB0nasVXem3W2BbippWtl4BiOr3JZbbIg+eyfMd1/aNvh8iILn83Oj7Jg8aE3y83fUx0b8l8qCGQhSJDDSfu3YpUe4kdu9lyn5mC1GSKcQeTEDkAxiMGAmEHUIHxIHRUwB2hGEYEUgA6fsv93h8eEiuzCkBI8CIAUS98LquchQIHVvJ5hKeU73qpkvf5NFlssv0gKo+N7Noe5aQa8cbcLlBmne37AtdnocQENU7W35CqT1EqZJgMLpAiCMXX+0l5L94hMwp4vsUv9wSMZlnOuOBqBg1w88jCHdgjYvuqQXT+d6xXrf79WgMuAXjESMexCod7bZ3yNbkDJsPD+jUQl6it3/BiBHR1dPXh5DnUS1DXQF4rtq0hk79VlaXa5T1sjLt4MqxNc/6oCUL+roFeOtzpNRE9t0JzAa0o/hOwU08onzIKep156ThfbWJB8bEW5LVu5ZWmao5Hmkydsv362s9HMPTNOfMI3/gf47eikWeq8W6smttRql5qPM4f83RvGc6pVWOvDFdR2uFVDpsZEX4JFyUrvcIYNaDVi4ByvXHvb74rS/XRxtttNFGn5M2AH2jjTb6tFQD51wAmsK8corzJkJ7Tpsy0VeU2fVKGGZwctUujO0EPyBky3MFzy3eVYxjYQkAe89xrUvgZf3sUkLsazG8hQA4sTxvgOcOmLGrOWCoZvRfk9ZanhfQaxKOaZp2hmpLiZeSV3oBVbxhzkqC2mWdVqLIp/7txztxdtMeirTnis/Wl+ssz+3vHHRf5tV6dzqbXir4XxLQ2+jjk1f0AdM1I69X7r+cZ7oppWvladq7XJ6Fyp+K1LN1O37NxTPvxjXmn9V6nLTcxwd6YwNKSiKu1UTzdS3vL2iiqhepWs8KZWT9Olf3qr2Zq/dPpcutCdvq8tb0Ltbr1eSYA9PnFZnnqzi59fpG70I+Jjojg8ZXuFPQ5uHsOMWvSfVou9Rw8vstIcdstn7K8dw5XbOLOdyyRC/28PJp+n0FxjMB10xlOt3HRgAj5bjSnZNoiAihvwF4QAyQuNdR3LgfnkbgkC1fn3gPAuP65hohdHj8+gCAELqg+6aVTgihQxwEWhxYYVQFtK0f4ig90+2cqi/JqwFdH4AQEOPoQpXZX5FfU5HIElocc9uIqXAH779D6nSS8vLCFkGhQ0CHwIwDhmxcnmQoO4QdYK7ahGWidF3L0NNx15avRpjyU+NE01edX2K9zQqmD4kxkHw6AB3/APxilvpe1jIr9sz77bUf7iIy2OXqmVNqPRNP+JjaFfGYAGHr5RE57vntP67x9ZffKz6StW0WIqiMUV+THcypw/sQynjoV/q3tsA1eokUSygty28g32iExDY/gNFBrMwZAuzfuroBGey/hfTPnbWJ5RlBAHAiF2bM8b0MArqQ9BDk0oxE6Dkf/CjlXqR1IADJ1j8fLpfvT0EPlfgDszyvF/H5h+K5PaglXG7m59/io/fmaSkUmsk3PlWel+0dYG7ern1e05wMnmcYuX/tElt7QF2f9bUppcAkV2hGpp9JYbx0bDH5A0ME0gdJzwiIrpFI0nIAR4A6aSmPQQ+DSMnJYyZLuIzoBc+qca12L/UB1z8KoWkho4022mijT0wbgL7RRht9Skon3IHJX7kAEGOyQk8KCONUUQkq/r4H0WFKRScYuN+ih2FwzO8mt/DvzEEeY4Zfi/yJWBNGW0IiF9desVBeA+/UjrlS58BxNsH7NFpzuntdPnWureeqFODpswmw1LieWp5bnuePdbNAz33QAsTbs6lWqk7fnuY2VU9stNEJZFpldVFSLwel2qRc1+QvT9+pdM4+ffn78ithWU6pbipKc8rkCR2ZRqZAmlNQLe1Vp7bYrwfpn+5J9boyWQd52pRthdjorSgp9T049IaMXB1mYaP3p1qSYAADHjDMpP9WKQHlKGM2L1mmrrNEz3dqq9EdCxB2U+1d9pcARFawL4j7bf+9WHAOBS0IROKynKK5N2eAsmv2ECSG+DiMmkmWLf26EAeumkAAcRm7Vl2tZ2bDXnDyRh1K5ujkpwwupg7QvL03sZTaITMw2TAgxqgu4gXMTAb0CuRH/W0Wv1mifrmkZK7Ie1goLV/XOy3PW5ZnJ8/iUN9c7JefgAAEJgxpDEmNR3W5POtW3OXB7oLrZ/o3ALjGF+x+2uHq5hoH/IAD/kgAe8QDerU8r2VpA/qnIKe9m8Fam1f+kM5VdX0J2kOsz42uXR0M6L6CuEX3gLl5EKjJ2mfPHiCA/B6yHgTK38LioXv9TiJ/j4CRGYFrN/P5O9nvW7AeOBDgH3B6AdUPyRhngDkdxPEHbPWlYuG3EAekCq2pXDG9Nw9fvwadDjG/Td1KD3d2b4nTOaVuy2mPM2+MvJ/5OU/AZBFgwGUnQs0k/MXkZVcbnu6JzRqe8GHmDhtsfORGG230rdIGoG+00UYfnibxYivwfKIgUXftzCwKDMCBHg6oK7nRSVmFooQBKphKFcI4pvyini6W2HAAUVdkf0rM85dQForfiYWthLu6m0urxsvW8RK5TVwnz1ieJ0uXyZtH4OSJj/ipy/vTiYpfaew6y3MPjNVvTSDwFpBUxAVsg9wvrfkc9F3f93XIf+temCqeT63vsfE0AeRW5rvR5yVvfVSC3VPLc0vkx9E84F7eexOaQ4sXUeT2KJ+op7zyj/M1AaU1Bc5rb97XX0a1xTk031q5fOrkvtxasK0q70HvZn0OTAbfmqosK3F95stFX2q4zWWzKVZPIx8TnQCMePhu+9CsPIEMOux0cozMalFse7Ny4zOW6MFiioNTnr2u+3vdXPYEXDHQcbahBgNPQb5HIhH9MLj6jYPY1FIg8WTWiW06ESHygO6qB4HQ3/QYnwYwRowRoH2n9e4AMEYeVZ5UIIgYzBpRmRjMhC4Aw6Dxz9XpNYFAAflwt0KsxlUPg/Alu+trxOGAyALWj3FEhw7Uk/IuAviFQAABXeiSi3lmTjHWi/XD5G+TiJiK9ZRIXM0zgK7rAWI5NJBkqmzZHkJAv9thVIv6/cEg8HIWzIE21t6DbvQ729tDliMigBi/Fjz8DvfylMWy3Eq0sDYdugRae6iq13bu0zOpwUjyBYLxjCQco11nd9sZzvbwp/0KgLhl/zniGc/Y/eMK+19KrO2AP9PviAwqG0CeSyh7co8cz9vSXblnr0VWDkGsxa9drXw7zJLc379Gtj6H+30DAbHvNJ8bAHu3v5rsGChobHQCBZUmHa9qiZkZVzGK239XD+v3ndax1zpFnXFWT/nHQBTPADLfosSmdnosSp4uopMvuKwXmXX9VKpllIqmmqUPq/kaa/3x3capFzCesDn5eXMpGahmoeQ3Vc+nubdioa/pqXocTCU6n2P+Y6EJUviKaq4nT2a1338dUCSZyNiMnNd7spv2p+xhA9FjQ9c5w34ebXtqv1vb5tbj16K3Lm+jjTb6fmkD0DfaaKNPSzV4nl24cxLg7TfQAmu55Lha4Lkyqi40G8Aie1OFhBgD599NAs93yNm1gaE2ZH5O97x5l86YZyTXW4AKNidovU9JtyYr9w/F32kZtRu6Oh9JI786zrm2gOKXtGAVZjeTvm5DLUT5owlz5XyHU3Oji1BWxZRr3fERNQ1xIVSH/GgTXW5DmZt0k8lXqICOUq18YldlAQHK5fSU9eNiqyWjaXFel0EuvemlNvoc9C4g+EYbvRJ5/q4HmlboZnn5rcZJL2Kfo9xr6tjoKd2sJXrO0+yKaxklghCJ0XPmJW8iMCjzaWlbf61uZC7S2QE1Ti6NDmwWF75BwbZcH1KL7eQlgrJ4O8QMtlodYwW6JTk4MckK06g7YAAC9kdgwIAr7JAKIy7EFOtPs37Mbse0xQoOw7W5kI1hzymFPAMEpGeWw+jkTjwMh0O2FF74lmtBlOLbII+bCezFACGgYyBO4GYg4B4RXwvgyTzaX1WMQw3cCe9RfrOSbyp5QaujHJ14TM+GXx7Se75NBpzPjU9frt3fVdeMDJy/JpBe55lB9FyX5yrNEwQUn6NnfdPaRABuIAcW9gBg1ugkYRICBYQQgCBeEeT/uYfGGDFQLCzkLV8jcTuf+360WUkZQOco82aMESMIHEd14kDu0AkngDXdS/WhlGbCSLv+av3e6HyqweX6vv1+dyCXM4A9n0a8e4zHXY6spndvt9bB2r/RRhtt9Fq0AegbbbTRh6WWkGxCews8L+6ZZqEFsKcbXjmuSo0iAc0oYLNbPUBO4JvQz6ZIMPnGlTXN/9K0zL6+FnNrjHMhYHADPC9Ao/ZvVHnN1Tndv2CHHrM8b92vLSklFxW76/G2oMw/puCbpQqEyv+8Ysb918ahCuOTGhXjlFKaUOSEye+aKp3dBNxuPZ/Lmapf5OpldwMwqWFZV6p+5+tVvV5XeLa2G32rVMyWQtNZrmbpl3Npmua2ToI5BdfsWJxMvAuB6NWalOLlHa3EcSqVwaa4n9Y5KX4XmpPXiVy/Zm04d89ShfxaWbzn6lQADitoWwc2ejG5TfKS09zliLlVxgMwr6kIXa7FRnOUXU/n79RyYWxkzxjfJpjugfIAoFOXywy1Rp+xRA+Gy6Z85IbFLo+NGUAgDFSNXQYOBIQg5ffidxycLMUtsfAH/XgFBiNQwAiztiYc/jyAEMBBY6oPEVf3PYZncePexV6s5HUjiqPUJyp21iFgBKPrc617Z+2eLMXHmPpDeBK5HoYDLH46K7DSBbWCB4BQSgoc1ZI9CPgoZ2tJ40sHsFqWc2QwZffUpPUhEqvzw2FUYDGKlSWVPH2n/Rz19F3kCERGFwIGCcSe2ui/aPp6kwVG0o26oKoNP66caxxyG3/kr9L//AMAwv0/73E47AX8/DWi+6lDzx3wC2HEn4Xcqt0GAHiEQJ479WIQKTZlXDvMN4XpXZ4+vUvnI8wH3CE6F/RUpa35Mt9nB+R1xpf/Gq7b58gs0Yu+RAbUfT2ekNtiz5+ra+/S3fr4BuZlQuZS0HnShw4IASFk72b5AAuluQ3IOuz7cdQ677SOPSRMQPpeJHnFIF4KE2AubiIwEmWjDC73Y4A00kN+Lr4mPJmj+AA7reO//cn8qYaTmFqst3fwc/fzOZ3AS8nn48MWtJ6X920doTS3lt7L/avrs1uHWunm8rFxFpjyeCueCN3FgIdknZO/MTNJPBEJdJ7kLaKqh8nWR1nrI6qQYoWiZt2oKeS8VJ8FWewVaOMnN9poo7eiDUDfaKONPg3NAYxNUF0keDSRXHu+QBLnnCaAgsglXHD7hSUdnS2uXIjen420WEzlvQwmFfcnQthxp+5v3sIFy3OgFACl6WZtsVL4uICVnAeEytPxc/HE54DmTAF1rPM5obCEs2qFjb/XEpa92sueB/e8zs+D+Yx2We3arv8mG200T+VaxtX9OmW99jHaa2GT5raTpJk4czVcCZz7tcnWtEmJZ1RhbksuV5J8v6X0rYk4rxtpLSz2ZveMS2AydTM3yjEWYls6PhV9Rutzm9ZFWIEXTPNTC3+rojZ6GRmf54G41mi3Z8dihX92quM690TYtw5rrTioWnKXwKAZL70VIYBF705bWQ6Mcl6NiBVfTogY80EtBsavI7izfYzQIySX5in4uFqFMySOcghdcsNuFtwEShbm0+VQeW4D/sEKHGYJYt1aoK1jy4XFWj4NUEZURNsAyXEcAGhMZ7VcF7FafgcDjzjb1TPyd7Z85pb4U9axBEIq/1AfmBvpDxB/AQDsdlfY758xIiJAXdkjIOAv2OPfxXveG4JxfDHVPbq7ORb7KTtW3cYOt3q/zMW+pnffXoOLwNTC24PmbwWet8qaAyxrqutvVuwe0Avg1Ac3TDiwTKdAAX0I6PsORAHU5UPa4iHC+k5i2vdai859NIbyoATcQrDMHYAHYjCZ638gckyeQ7pODqowRxDnMWB5pXyDjRsFTYkARHXnX8GXNqfSOlfy8KvILPP7TkI0rD7c/5E4CFspXsa6z83Len1vP233x9y+Xes6TJfk6ZEYt+oN5aEYe1zKdVp8OrvtXGKmWjGXe2JLSXMi2Vzb5KWNNtroW6UNQN9oo40+FdVAeRs856mUiOl1wd/RFForFbDGqXL6Y7HOM79pjKgJ/edr3j8y77mqboVg6QGjLBC0rNDXC3i5mLPqt0BzluelFXrxRlFyFpsMGm6IVw0Aa51ib+l57a7cxQYvqkjVO21YWVRpDnXy+bjsWoD1nFDYfp57qk7v2+F/1e2b5tkSaV0u7jHxCeOuasNHnqefneb6lvBypchLyAPn3Fi5mpbn9ctGxaAl/ycnt73JKUBe7KKutd817qd4sl6rU61zq4nXrfJpqbLtnEzZ0wIB1lMaMx6c9M95OqfrNn4U1eBnovcCsi9yMO294qCT29curowsJnNZNJkCdBvpH5Vqt+2tmLzA++2PNb1dfRQwVkiwJ8LgXIHPxUQ3MY1TdGvGFYsUN5CL461QZM8GrEsGYWSxTvdgBnxsdXkwsrj67vkOAKc9NfIDAm7QDzt5lyTGdTdYjHb5L+tpsNApx6yxlAPJiBiGQZ934AiMcQRRBEjtUkNXHCKLsXRaLmC7IIWJy3aHxSXGbgbXd9fXCCHg8etXeWr9rM/HcUyxpaHxnCMiutCJ7EzmAz/KekfS+F7QQgzDgGGM6LqAyACxgHrgiI4Adof+/GpldwcyQIkSIime48qZos7yEUn+sX1pJ78yRTz+11N6s9O6P/36uwLT9+jxBQP+zBWJArreWT05x8UOTOohoVxnGcCg38u6fm7esPsHACMeJ889heod+Splul31TtvyfH7/eAu6rq6XwH0fD71DPkQQtG87ZgyVroiQD2nnDs7hEIjESt8AcSLJ8wrASFLOM8SF/wHALQjPYHFVochioCChGhLPTyC9JkbpglvHcBcUzIeFPegAjiDKB/ZLNj2YEJLv5eYs89LMiGN+L6S6e5rqMACAY5Vxium+TGtHU13ttfnOy5Pt9M53gPRBle7O/f5apPc5M2oD8Hre1pbaEd4Aw2lHkjwkx3ACE+4jgSniqQs5U43IkUN1SN4cISC603dY6IBAhNE/0AqdOtObffnWy8RHYXw22mijb5Y2AH2jjTb69FQD6uDjPNQSoCc3KLm5lowhnG7DlbcIUVkQSjdPoGP1+Ww8oTHOyYWfv4+WsPExaBY8x/JtGwk2Xi6u815BVPyj4l5OQ7PvmNKgdtdOVfrp+/MtnZY/fa6qu6LP2kJtqTCjmfTTNtY9stFGL6NSCdIAonAiCDUBz6kYqqZcrtFfPnM8T+ZhvX9ZGq9xdz/Wtkz11u6ddl8dz2RlgUcoWfY2Cm0pq/31x9yxPj59Rkvw9yQivLsF+lsV+RFpDeC7tCTNvb8MP5xPI7K7awPFgNIbBzAfM/3bIFKX3CUf2c3EeTV3yvIbhczo+xAAdiyu2gGgZ0uR8xxI7o8kvzsFpyxVy+02AHCCSsqxEdC5eNu5fWkHZQPSGIxRLGarwRQ5IqpVKwXbs/PMjrFCDV3lckxzB+4wxLRWyyYQ4jgqkGcycACFgDjsYe6BAQPqlctnO3huB4YJKY6zMgsmRXUUgE6AoMBZYmy5OM/WwiXwSBZOzfingBR+rQaHuPptzwWuekDAXyZz7Panv+Hx533q29p9OlJ+JafmD0CSPoeu+3U89qV14lT+xHtqsDIO88kXn70XeUvzGkyfoz1kjcxKb05AtV0D0v+FDsd0Pi4EgT06ABLuQK93AO7+8Vc8//Iv3Lp7Ud97tgM3LK7gS/A8c59EdsBCqmF8OJODVSnPn8D2Lc0lt2/RrBpjBeX6ROYJgPwt01+Ayp/E8p5/DwHRhdZxTz7VSSIOA48E3Ls9607vWYaTA9Z2P43vcp+Mzp376RX6GLTJahtttNFb0Qagb7TRRq9OawTBVZmUqEUWcFIaE3aM/+PCVesceGd/aoG6eINdwd76HVmYsQPvpFrPXDUuy5rUYXqv5l9P5WfrbroErSm/KMt3n0NRyvpws64vqXOpWDlfFkjjYVYCPbGWtYstVIAVUVLutOoxR5T+Td2tT1y1mxUn56dVisk7SYHWqE85ri8pceW8TN3la1XXewn4Kq4nVWzVufFdue6li6xq3y6dMDXW9+B7O+DXtYrk13Stqu5RtT25v3OKk3pUUWERntePenacSi0PGM1nrjxTHBd1XlO8UwRKf8y/5PPW0Keyezq9TittK6PJOmX6ei7rX64lx6lWj523t1D+nJ4/0fqBaNpNH3ypmXWnS9Px9hGpOSrfq9oVM3rZ7mvPv4srHY/U+SVNOquuK19qBKmYZDCt+9Kz5fvTPE5v3Yipi/YRouQxEGyHHJ93rvyXjIFjY/RY3vkYpb1QXi9lb7vkgGyRn0rVNdaD5j4/A4kPiOhACQAfNa1ZBAMRB/LcZ96UBpfvSPotWOPQE6HDNUY84fZvP+Dx9z8EXONbMEi/m8RGBwTMYGSw02QnjmofH0cAe3AvjqSHGEGUraJHjQ8eQkCMYlcPknyJgRgZbCCei/jOCdg2V/FWrjwPJgNb/Q5q2d73YGYM4wjEEYSA3c01nh4ESCYKAHEBpANA33fo+is8Pz7KHp+sI016ByiIRe4hRonljhwjmNPJhPrIiFBScOrmP46cLoWPI/3ukkOnDwNMvs8ZMIDn8O90HZmBXy2/e3TmnQA99oxkQWx8Rw6zTui1D0ewWrxnYmKxjnYMykH7qwOnls7NBT+6cwTlTHtre9VPvudY0x1fL96fnrF+H3mCtPNLekd6ghHBHHRcs7pTD+AohhmRIzgyKJDO0dy3z2BcQ8bOAYThl38BsDEk4+tRlR43THhiGU1kB0ZyNWS8OLcY9ismAV/yC2kcqAxPyIdUzSW3MbvJ04bOJ5Z1AAC6oz2X17dAoSF9lSt6llmk9dEJP6fuKy2ZqHXd0l+s3cXmWkMg/AHGD+7Jn8jzJlRvHp+Lms7xcl6GqGXBND/NY0rFDHrLdPOWESCA+oNX1tif5MHMbud1MAIgdwgqkK5tNf/ZaFMhB82oUWju2Qo6hxe5BA9by3cbbbTRRjVtAPpGG230aWjC8CZX7Zy5TruG/G7FNK0V6y3+zsDIoAoFhsvbTsNXFug5LxVs+GWMWM2snvLeezOAnJj15fqYoujV6oHMEF9KB70sRk5LyjYV+v4FteHzOdXOzt1dtjrkMQ4gxXU7r9yXtkm+kv9ec3lT4958nufS2tl3yZH1bdHaXjm/9952lSsVnY17jevmfcIEWCeXJyA3SiAbSYGWri9As0B6fR/utttfp6qV9rWpe04lni4GL6KaH3B66uPvztyhxba3n9mb2T03JWX7xTesd6ZsYfX2dDlX5Mvje/rB+Eja976eq+vHo7fnZVslLt1r9eup32SpnNPIcuhncvOg+vzbwMcYj2vzYtucxBI9NcOhFibELe4pEZEEpA2U3RA4O5wAACAASURBVLVbeQMxeqYUF7294+e6iXzDAJ5AYDz+/m94SIQ0XcQTgjoFDgiIiIgQMFo49YARA9jBmQQGK+AhFqsmZwiIFjqB2si8L3PRMQArqO66hkkAd2U3UquKfdNeYM6WtESgcRS+BYT901PKgMSE1fWTWMUzM2IcC77A8xcZDIzoBLeURyGJ4Y6X8jKW7bHGy7j8lROxv/XXOzY7PVmaiK9g3KNHh/A3Av1WZQYZT8YnkHNpzXqAweJf22EJUgtkYk6HQuyAjH3K8qCIllPV3Vcj4tjclzQf0er8peTZqoEYHYBA+gUYIETx6MBApAgoeM4R4CjeHDp0GvTcchR61t83CApm5mfRy/1R2Xh2f+23zTlQcfiCDG11JWZ5QSeDOHXPsa5hY5+zB4YXEeVCV/Ljb8tNtGWVupp+DADtpmTQnBAgwPLvKOcSQw5htEtvlazfQjtwSQ6qZcX5morF+a3W0VL8lYF/Ufttcg2wMRZS3SSNWaIn3epMXvbbrlstRuP+a9J0ZmZaw03UnM+5XM1GG2307dMGoG+00UavSKWboGSHXetK7GcjXiw7F1qsQoIINuLAjqNLkwRU+dsxZWXApG7VeVqe/gwAwCbgarmcT9ZmV18uL1UsNMto0BzTVTPZ6wSSNvt9Kr1Y+CGkuLWFgqJiyFvWmcfoWLr2c1PIVG0zRU36jqZ4KZ+33P3CpWz111R442Ic2SRgV2Y9/stxOxUSfXxFF+3cvUfVu/I3QIAbs1ghrXDtZtC3pZ5DU9mKqpPZk1nv3rS75K6tjPyLiifTnEvyEf58bXMugPuW6ZNX37yilpDYXE9WxnlrlvG22obL0AuWGf9lzm262I2Y48Jz63Ba6aLghOqTxIIr+of2x69xhHS+y2fEDaWuf5F1PxMFsmWcPZ7U0vukJdWa5u+Tf96iiZW7ewRxi5su2D/Jczn/sPmVtXs8V/c5rUXaZssVymacV4rL/ayMzKuirntU7sn1CjlLqT65b5b9XtQrR7WGuQNMxaDRV6gKYljHM7wkvcb682ktzmdT1erX6jqdlrQPaOOeqvdw9Nr4hHmVYOt6oW7Na1/udNIlXhvnrrDn09pDDyfXasWQzGt1uZZ5P0l5vTaGkmB9VvIt8iwDfL4SrYXuPDr2psU1PiBbm3pAzhMBYtkLOIa95JFSSxP/7NPna7KDxiuuLcps0c95cXRtzZup9bo9Iea0rwr0LDXtIcCguUQu4gtDLHvB4r52BKOHgJe9Zj26vVqssCOuOc+dJ0o1g/+VrUJHib1MhIBbRHoCAAz8gOj2+AOLE+CObrWBZnEtH+TqL9fY/xkAjojYg9WFOgAMIFDXAQSEyCCNk05EGGPMvRrlO0WxtxZr8yjx2AXoVt6EFPSVILl6z66B0VxaR2A/juJmvQsSfzfox2MWsJgI6AICAcSEkSMoEogjxmEAEeHq+hr752fJU8HyvusBjhhGuRdVRuEo8dQDBQT0/z97b7YlOY6jCX8gzT0iM9bMrJ6eupz3f6i5+c/f1dVVGWvG4iYRcwGABCnKTDIzdzePEPJEuomiuBPEQgAY1Kn37W3E97u9rg0GUYQtJGZGjLoLR1kA+2TzZfOcV1I1j8/z9Ad9y4Wega2lv5D4V6R3VSJGMCJTtfdH4qz8N2thc8lvOMXTgzfkPf9wtsA3zwVmoX6TeyMY6rv2ob0Yfaul21UM815xi1opb+8zOoDfN1P79vpU6WGlKR1UwcyrQ96S5DPqpheSSudTj+IvOs4vkUDMiAkIY8CdktWRCTEGFLmOXDIZhn32ukAkHh4CBYQYEAJhHwKek0RG3wEYGUBi/MqMr8y44xEvQPiSGQlrXcgjZniVIRd4QEEum0DWklHAJovq8Rf2O1+maGhpO14ttIXJAfoyJ0dJq1DH5F/Byw/8ryw3WWca0TsZl8nBWvrGp2OSXma1nGu2awT1JH0vb97AX1MA7FqElWP745WW81lnsqZjKJfHenZkV/vt+WntMV4l1OfJL5rpLwL+AuMli6cRQsI3IjxngEbCZ8MvVHpNACh6TsnqlDjomacJpkRvz1/rTQ0eG7B+PxfOkstHvdfTvCtYCW4eyi6rsU9+pjofFAdUaXVzDz5PXOdvsMEGPyRsCvQNNtjg4SBTL40oqdWkehfp2W0csuI8sd0OtncNM8tCbAYiRAqZcKzACWF6rwhobs1b7uJqb1qe78cRZvEo9AnXpd88Jh1n/GERhU2Hw54PyUqXEM9d8WPzTX7HXBHRPt1Dnt0OEX2gmgn02Dljo1pl/fww1HulpNaRvT2jW6ejel/9NuGWa0Fvxc+BzxtQmK+2xb0ecNUe/36eReu/FydmNKtAn2mza/yxeWxduraln7fTf1yO69i49NbJ4dHwVkOc/1uKHau2Ea1WHFpNHOR7w3Ht+/w8s5TTRChRLMdqJJn/V8mH2NwyEtyFkFao6Ipo08+wCCYgxzbNOLzZk3XM8/IrW2CtQaruOVml5OrK5VNOJxSvGllopAIiDQc7rWbRcNRBMpYp0HvvIMLZXqVsQp3yntHG67wemBNut+mnWoJfhSI+b7I5AW0/XwnnAywWx7GtK9Zl7TfTofqPtK098LjtU1OWCeh7TbVirmFuLg614Ds723AXdD0y5mpeeILzpnmm7/vPa1pcwM+JxTvfoUzh4J4rJXpDGvrSS/OlJouT2tLP+XLTKc+qeAJUmct1He7KQvfZWhVt27j3Wmqdn0o3wyR36btPI7cfBR+L0v4GpU4AuNM5SOB8yZVceQHPMapFeoUe+BftvzvsobQGEtJnUaERCa1bFDpSbmISy2UwKAGMUfjgQKJgCXIqJk655mzZrorvAFVUs42NmzI9e4kCkFK2PLcWJD275Le/LKGj61zoJ06qAJeJGIe9Kgyl76IAB0ABIY1I0LObCUkJLxnVQWNAi4v4XQwYxkEU7Np4Iq2fbR2k3GZQQGIfGXyKEcf81uiY2o1zCTXzVS+nlIuV0iWji6QdFrM6sMMYLO309dpe0PsELn55H3fUe6OsoUEGSwS+ju+0HtilGkubcxNf75ea+ukpOlsqd0LfNgXPK8qPcAX+Qmcn3btFZ1j/Er6zKsuZwYkQR+nbQEHmg8UbBDSEwzDscbffi1wpEGKMiHGHEPRfDEgh6OUbQkgJRAkYgV8Y+JYY3xQnEBOIA4hY1idJMIWk5z7ZXgj6z8ZQL08k64vtM9TcEFkdzVjVM7BkfAn1avHpXrbm89gas1Xg8OoRkmFCMXNZzcvBWlTGxpFXKJf0ywp91Un3GKGHIer178dWn9jnLFIES/N73+9gv/+YKF+mNEOPL5D1ZG1NSqiRLVotIwXz9OF5Fbn4HfK0kvJGgtdtqyQueLyG6VxIK5rdngDE6frz4zWBlkU69u2BRdF7dYgC7+2TU2CK9zbYYIMfETYF+gYbbPBoUIkqWqWCsyo35j1b5QFFjs5TgoUgPEemEblDUB2gcqRcx8ayMf0zH50oHJ6DVoxzyveenTnGfFxKDJoZBKp/K99XdSo/z1Cc546o//4YcXxu/2u28Xzw89abwx47W9JbpqUwwBbzLKIo2i+nlWkV6AK1rYZvj39u31/yeT30SzjExF9qDH9s6M36spGb5qrERacMP02Z/uXfFcG1Z+Zb68W6vU0ZLqE1KD+KrzWTyD+oEmRnoaGr93JurK3QGWFpTp6IiPzH66vzo7NCaJLXmC2RVuJ1sM5eomHYpTX3nt08TeTJBSf3vAxcCn5IvSeAYwO1fL8vE/Ye/PYicGpZK/t5dn33Cw/dquPT3mtRwXltuuk/linS18Mc/Wnpg3u/c+8Mb9t7O1d8Acxl17R/qXrqtWD5c6vgbs/RyfnZJNrPhDqeM6FSo8y2BGAdG1KDP8ZXVbw+Z1ILRKj7bXZkM2HHomLJVsJOWSOKF1N2AcAXia9ctVnXjlqmj0lji+NXAISRRj3HExjfcv8DPcNIX8FJ3NZjHLUcOUd2IRZcT6JER27HqLSC2hyTfydBzwedYbl4FjGMo1xVjZLGSnuRuq42WiOBM1HDrj1EhDQmsVQHwKP4tCZzGZynQpVFPIIoiKISjHFMeimBsrU2EWMXAvbDKDGrwQgh5jklgsRmZ8Zt/BXMAfv4BUwBN3IjD6//9r8RQsQ//uv/t+rz/BGA7zqGt07mUCnUSEgDSk75ZTwvyrljsYpHAIkYIxIScS7/GRd5RVk74glhRKnQPCkMzSIeqqfpCh9yqqxha79ZoJ/LF68gr7qQvYG1l+9yq08jXKprTXlOCF8BPFeSkgnYIQEYcZuASMAdAkApx6ymGLBLUddyaXNKI4ZBvFOkEBFIrINvubgBvyHgJkS1Pga+IYH0BhMHkS0lCopvSXEJ6VozbCHzZkp2Y33Y8jaj7nmTvBc775OGKAwTwrD/HLL3pEN8fC/9+KrwbWzJ38PksDeOKDmlpf16Lf1lU0dAfeZ51Xe7MglUhVYAgFcQhftHzVE8OLR8U90yzh4uBMT5B4Pyf+Uc+0IS8zyXTABz8WVAAF7qofMpnxda75iQiBCCsTTayiQXq+wCVw6h0Rgo9UaTPFPrzr9VcITfuRdq9R4KnRujDTbY4MeBTYG+wQYbPB505VDFAiQLSSyt+JRsSPea4soMTyagUYyDFrWrYUSOuHm+DziHAGsZpYeEVnnOQFEYtbxUL/2S0FKybT0nDnLLNp4rOOjXUYceoOpNv+5ahd1rZWHFejWe3tZS+vIvLgnTUbo0PNZ+empwbJzatbtE7OKhFaQvqnSupBM0ia0Q3vBb9a4RBLT6a/+NPa9tCoHUwpWyZVkVa9q5cOf2TD0DeiKzItqbln5R3Ogll82LiTDPhuHIBaGjw5476fHnGjggDdLzqeuStDoXWxHi9cGPZ418RJr30HBfR2YPLn3h5kmDKXUAoFH0oUKzE7iSlVOBxVO2tgWI6+c9obpLOVE6O4WR5bh0B7lB4aeswkJTFNfYQOOuvjmve15sCDou+jxQ9qSrfI1zs8xmQcoYqLAdAxU38KbY9yRLcg220d7hF4z46lV+yPGMQUh4rqWL2/KA7JG8tJ2MNhEr9aSMNOe2CT0gntQGdXUuSmYEd/a4xhKpy2eSkfWub80FPZniuzn0k6mCmfO4SeP9JJeybVMFZx0udI5cAk4piRV0koZSINzskC0tPa0j1pUWU57BNJZwbCg+AFJKWcl4CLiZR39KtNuB2IUNAPKlcfs+2rh5rwaurHa9lFVw0tXPXE776xTw/r6kNCnPt+w++OLToXhEkP0rlr3fdcnvDAuwrANiwg0SBg0DQKShi0LpVVGeMwIn+RcSQiAgBAwAngOIJG73d0E8pTGAyAFfOIExgJEwMiEkUivgYiQiisxmHZXedLAW14+Ayr6KstZ14QCV0yCAZoX3KOF+GS0cXwn3IRKa7pnabxZ10ktbDPdyte5txcs74LN+8wr1Ja5C6vd9Vk1GxISVefi9on1m/JpzxoopeENboWeX4EDFJQwkSgjBfEsU7ylyTpAzHurzP+wEeQQgOc8kx2A1d9MbxKox/eTF7TiBtGnb3p3XDTbY4IeBTYG+wQYbPBxwISXlGd2/wjwwwKyMrZKsjBzDTZ77AvueJey6NgrYjf1ZQujKBI1ta44R3ccJ12sUAa6A+QHJUAmeHMNxH9CWTc3f+e+m69mv8zpXAXWQiOgcDq7ZG8fbVcNj7Yap+HMdnNOPJ75DLgrH+FoPh3BTezO/n6cIbh9qEqZtUiFBYz3V+XlQ5NmKqpYAOaFyUCV6UAW6V2Yycw55AiCHQDkVvHCrEjTNjsEFscK8tC8n57HkdeO6VNBzmaW2ZqdcDi6t455Tmj+cMn1ZPSetQNKzknqr/R4hK6aKW+nHOmNI//dQ53rLDlwDTKxjV8BUMD734jLQWhDOjadZopordyJgR7Wl+hI4go7vH5qKI/shLmpxH4l3B2+pK7n3qizIdstUlK/PGOKqXdMTkGNO20HDYV45szc8AnHrTDBlHWHHjJGQrVIZwICvueisak5yWc4sUXcQRfqI7wCegfibRTQHUC4LDPsxpxKQLb+NRkjJ3KhLrqQ8N7nYxpwYKQBgK4sxDKPEf44BIEIIQn/s90O+rMfMCEHec2IwF0teZrWwJxJX/RqShiFxpYGiuLl5/iv238QyP+q7XdwhcRLZgGQGhYhxHHE3jogUcLMT5TsBoBjATBjTHRKzXARgznqqP//xD4AIUdtHLJb4tUU38N1WRZDLFTepLAMGwKHQHjZW1ZXmfIFAnkdYfGIZj726W761Pum3o61HXd9fabkK3dZtSaCz5RZtGJv+xcn5NvpLOD1POxPLVxfKpq3/bCC5ihIADJw09EFAwoibsMMtMxIRBhKX7UE9ObCuv5REiU4jEGICxRExRFAMICJ8JcIvLBdtIknMdLCspcgA0077pnhqHDPmym7akyn/y4UgZgnrgGxY4geR61+NNq+4CJdE4wciFSzS44mpeW6GcXLeRJ23UeV+a6591JJC20PTPmL2vV8vtWW35XrbpNh54c8QQCKeR0yWqctfAmIAwCeIVfsbwFmiTy+d+L7W4EurOWXfvr90fF+4/cQECeUBOWfAhNf6egTjcxC8CgJeJMZfpN5EmDHyKJc/rGZ3O/AYHVTxnDiuQJZzoOru6fDohMgGG2zws8GmQN9ggw0eGBjOj5ZLQ8MM2O8k8XRg71HeNWCu4io14Rpe8coU4peBS9xWX1LLdcGhts+pL+YUJGvGwbM+S+s/9K62N/dtpW5qW1axZG9KzjLAwiT1WnZsbK4FHjw+MF/3eDwUzO2l3rsezOGNw9/K4IvsjVZPxEUUInYUVVKlGYHhhbGjCMDlrynPYwgI0dxLlkYl5iykZq5dvV4K5sazG5blUkAFv5W9SA7fOdxFwGIMtm3qRTAX67xNv3j4gJVwCWV+WT/r615dPWd9QbYcOw3OGfcap67tw2PP+bnQXkDywuO5df0UPTCYNbq3SDd4qjOYlZkuzVxnD5gqRecgl9GQFy0NsANhP6MCaVMHYuzYn0O/gvClUqxMFTgk119Vg1r7mHoGxrdJ3a31YzseRV1UWhlwi6RW7T4fqUKl4g4q3CD0x2Q/uFJI+2Jx2INZqucyLKvkQVbqICvPOVu/lx74NrC6oY56OYABxChm6aKETAASzMzbYgsniIIaQWJhW+kRslamu5rVGl8V3SiUhVNjabrro9IoxS1zubSScYfifmL5Yd5zRs2fl0E7CZMRqaE6vi7l8s0r10CTPtvlgWNKb8OvS9MvBdmDkz4nAH8x4wUnBAyIdANmUXLHANxQwPcdASkgpYRhkK9SGvXCCECJEMaAFBMCR8QQwCEggcAUhU6niATgF/WA8JkA0E7ipmtbAlQpbxcuTACmorODc60L0fqVr8J4PMY2Bg0PUxBPV0Hu37s/dZ5ZOOdEaddsq6JdsqabxqOEzjB8+QFiPW5W3AxRhr8C470r/22nNmuNpX+CxVWXvwzgr06vemVMc0xTPR70b4klfMCLJBep2msLrxKBifElAJ8o4SUT/gLnMyYxQOr6orjqV/xFQe2XjswlHZbHzJ6nK2E6oxtssMEGDwObAn2DDTa4d2hC40wVCqo8Z1OY6+vEDE6oXNCS+21gN+pNdB5QGInVjZw0bHnyQ8OhZljsvV6u44QndYj5BVDkAEfbd69gFR/hqVq+8Vzwgo1e31sVTo8Jq5/7LZt3wW7rXyzOd5UozeW8Fz3SoS+uU7h8bqsWLrOfBk4fh6kwcDHuOKHSs6wKVYAlMQrdSbbA8nxeyHwKqFCMGgv0EPJFMpG5c7E6N2X6mVAJ4xdYnt+LQs0VOY8NFSOrQHG9m/xz4Toww2Nanp+z1w60YGXuqaBx2Yfem8MDUTMEZB+SF7AWPLcpprRZ9d2Jc97O6pWQ2QAuvI4fqKOz1bgXg0uqrbPrbw7tuGuggwLMormklb6wWl1OWxjd79rlrShWi/U6YXQKl/YkJxR37XtzyZ1rZ5ePVbEBjPRFlSHG22r7g333TZW5L8AAbt/cAETYv9/DrNMZtwj4rtGbxZLen/EVvzFKb0y5QYEQ+BnM4w+xWq+nQZoQoirRC1rKvQ1CVzARhv1Q6lKL86xUZ6snZkWg0SUI5PaVeJsLAYghIu52GPaD9JPEtbUpycWrTsoKd3PzzhALdoZ5j0sYxoSbXRT3xIlVKSn0kNQqdFRkcZ+f1H0+EfCcs2gCAHBn86lK6BG1U+bMTzJlbwUyfy5HEIvWpFbkRITnLHGUB5J+3AXl3NUD3s6UvUnmd/VGqxaBru6zNFedc36iqptPt9O46PQXWqJjnvZY1XxXh+GL75AY5l9YlImEQcIEhCAe3IjwAoQUIHkCYRx1LSp9TTDrdEYEAzEiMGMEYU+EPUZAnDKAQPgG9bgQCDeKeChIHRgJPA7gxHrhRPEIF3wBdqQC5kgFmYFWwduDUT06mE+KZIp79UhhFuXzx1dPJezmbOX5ye5f3/qcmpx1y6h6X3690ZxmHQ6IUtxK/IgaPuqX1vv3Wt5r1JeVXmv5n105Vi5DYpJ/Iq5aVtpae0rx/fOtLxdTStpf5HpPABPjU2C8TIJno/KDAaT4j/BiFNz9kYBXpBb6RPgCBqWyaohK+IB8rvi92mmy8J/Fw8cxZfrEEv0YQTH3/poIxg022OCHhk2BvsEGG9wvHCNqlEPNSnJ2AndllP2zGacDfcGwZ46WNmHecnDh9/cES4bulPfHWNBsb3ACr2oGFg9uEawwYZkODdI9TGyfxTyWf/7Zp1RKoSYPVXl8S5qc1P+mZkynbZlTUv204GQCP+s4lLV2GvjVtrYcRnF/eYn6136Zj6G+/tjlurwC2VxL29/glOdBnw1SSkghIKSUFf/nwqQ/M5bmF+93s+A8ZpwKVhWrcY0vaWGT+qLAnxfmLM3b56doiTuF3pm5vl8mKD+p+sZ97Wr82CKnU5qQ53Rt3U9XktlamPvnJZboTxUMte5Q4n57OKZ8eUwQC/OiPO/NiEb5nnzXK8sUn57/Sx3aOH+vr4aZAfLKK6/qMct/fzbp6oJ39Z3UAjkEcSRMGsy8RBN/BouJnlBfCrA+BTzPFuYSy/22KMowgjFgRKFZfCxd64XxhWIVa333PVN8IcFza0Vl1u7ogJG5drf3QsvYfkrjmBXrIhZISvNIMYECOCXEGBBYvgugynI5pSRWwEncYeczCqSEgNEI0t+Er9jhV+whFxtA9WWJ1qLcujNZR2T4s+Q1nRNruv29C8CNulw21/leGbbT5zsAz0xRtpSIcW2vGePTePsuLLRE72EQn7eyOHcKMmZ3/eRStAW5P7YUgCxbEpkTYUTScAuMGzVX34HwjUMOH8As64yZwYmAoDvQvCAw4wsRdgTcUkRkvTRiVr564SOS8DMcCCPJhZ/EjIQBlCiPZEC5gGN96NGqrONFUBo4I5cyG/67Wknt9/T0uaiSa03mfZ6EZfW0bbL6Gb011sKcrOM9RLEOFAW71fKh2xIZhREu5jjK2WHwDsBrN2KvGfhI07GaH7ten8o8dHubz0HHhxHllJH1Ig4Dr0jXhu615wC+BAmXUV2Ctj4SgRKDg+5Z61l2m2TNPRTEoWTt9ZKb93PPrRz4x6DENthgg6cAmwJ9gw02eHioKPeiPJcbtqZI90p1JxlpqX4Fz1sJM0qzivG6LSUPKXM/zn23RljW42zOhHOLW8V+nsCrPpbSfA14gVXv+Vj+3vveF0u+afP02mZlTdvhwxWIKC7mumnSgkN1zTHh50/ndS6I62zVjwPLx7fkXCOgNxngWfjwBPy8Br8di3n+o8J9KpSmOKyIwwrm87jLBNM4ONeXm4/rmtmH0mVfW8zzFtarGx57Hieiwg2uBO7Fo8LccrswwZ9XVVPuarfm/eIfcPdIDaqDyopxbvSCFhN9AFXK8x3qfHapLFFRiJgipLZcrweuxBIuemFRyDX5qeTZu983XJcc3A2AoJpZBjDiCwBgfCc1PvvtFpyA/cc9AELiLyA4xXmg3L4dnkPUz9+g3tGVjvmOcWwUX+3EpVHyW39UgW/u1SkgK7nle3Vlbb6xdaHtdjuxSE8px0X/9uULEGPWWjJTjnEuylTkeLymrEwpORfVapUOaIg3iTPNbn+achIaQ9qszmNUS+FUz+cAgHQsvUqOmbEnwq2mf1dl5neS0bNSnilhavMQK7GFp1UIAwVEAm7tQg5kPewJeAaVXdhFAK3jOxF2mo/B3Ysui4CmU70WmPu74rja7FCZ9+u2vVSEzD9M+W2lGkkscBmEv0jW1q1+9CvkQsOeSigldoWZUh15fRCeAdjzACKWdckBY5QNTkEo1xB3iATsmIuHqwFIPMCu7No1BVGuk1ymYMNSXrFKsFVXj+hUKdrmEMtzzhbnZomezCBdrSRKjOxirWylNZilquXUY61V61NTUk+tXHYd41XznblZ/wTgN9duRb35HPjdlf9O87wG4QPKJaeXIOzAKoOp4aOWb/u4VaITxDodAD5R24+pLKmewbLwqvO3oA+MjGyJbjBCzsHsmczWMggvRgDMuKNyjcvCYuS8hp82EnWDDTb4CWFToG+wwQYPB0ZsNe5dTXkuvLQqz5VJgKWjL7DJxPoxDUzv3cR89ILRatdohHqfn9CQHmvUfz4GVP1Z1YbHlj13YKp4mX/Xe7+8S7X65lCOpXWVEr1KyL+vleXk0qjOWH3flrtkjVzh1F4NXIvq5amBH7elWMpESVnUsOZjX8bZUsTqj0vWdjXnnIdzBIWsor2j+S6s6DnV8rxtxdqee8EmFURWpREoK1Q8/stf0Dze3WA5/NiW5xtsIPCzWqIDwA2Ku+pD8Fg0j4/Z7o9+sxb2iu3e5QD/TXspwKet8daSy6wG5TBhsicZa18nWb1UK3T8GKd3psmyPM8BFwvdN2HAt1yGSZAcWQAAIABJREFU/fMWk5P2K/SDP+m7EIon8KrT1ljKf2UYCOMwaExdAMx4/ssvGPb7KkqF6WSCs37MFumpKNpBABMjMLJiXIrWFcBlbETR6ELA5fEtCsYe1GNDctnB64vI/zCVl/yfg3hDMMPfiYKLSCyalTYZSdZ0dnkPVDHirQSCKb54sXxgsgLzmjlt1xa8Z89WbkmYs0TPZbjV2Oads0S/JMwWq2PzLcj8fCNxtb8D4RvkbyQJFbEjwgsifCfCQIQvVPePEyPRCE5ClY4EDGlACAkUImKM2IGxpyg0aiAEJkTsEHc6xymBoyheR04lhAEIxEn3AOmlkWk/Z3n7puPm1rteK4cEWM3cUj2iCbbG8o5AH9PeP7Brh64w91ae36AozD0klFGwf3+DeauQd7/p3w9gjY3eH7d3qN25v2LGR6MdUPbpKzYl+hQ790bPf2s5/TvvQSO5vSW4pFywyDJWy8PA88T4ZpeaMq9dlOcSWqC2VG+x4SpoOzGzUSerupUPb6zIBhtscM+wKdA32GCDe4Oleo2sPDdXWJ6j9rw592mj9uYya+aDdFRHuZEuYXl+QTi/VmO31n91ijz8cVik64FjQ9YyaEuHuBcxiyBuDAlAyG6Kyf3f5Z6pqFW816zlurZOxT3XB9fZqh8Hlo/vNOdSvGHySHODaWmt4ODY86lwTBTUE3PcVwxwO+fE2oVAKWlsTVevvmd9vi/8PNfH+zwPqMF1Ld6r8y5Lm4ND4sSfFbNcv9K8KE36b+d3Mciscg7P/H0BqUtXU6icByfsQqubHp6muyYacs7i/F4s0SeV3G/xc7DWsnXufL188ynT0IypS/Z2NrwCPKBYaDOKksfeWVpPaV7OF+qe/dT8zfzsjODft/eOCu192yoCUI9tUiX5d/L5GOzwHAPZstpcOMPVAaCEMXGx2pNLzxwjFRrDeEJTcnJCtlq0uvI3Znkeb8AaqzyEgGEYgOyaXc9rtvwSNx1wLrFNwUNB3cKjaoeVcbOTmRX+3Zxct/NESDzqPDOQiqWqzzeUSQTYXP9zbqsot/0oSSKxzCUAsVQntUDvaGmZxIXyqGM2aotvlZ/b63jb5YqgLY3a0lFXoglwj+3XKQ4/fWdO8N6MkGepJXpR3bq0GUv0S1ioty0ymZKsZfHiFkPAPgTsYgAFqhhok6gwJD2EgJgYvwZdV0S4yxtOzvAExtfEiDSCEqvjBcZXJkQwiANAIcc5JxLePsSICOCGABpHKQ8S1jAFwo4JCQkJVMICVGeSzUI9SR4/H+Rl9EWggIAAVuxY8RdNeYCnCy3cw+UkQ35L9fCw1OTpPsIrk5c0Y2AjE923hv8janfsnrfYaerf9PnXv/2O8V9/5u+zsjm3V758T4y3XNJeZyU6Syxyrex1xsPAx0x/kiu5HZMSzIPhtiST4ERdG+YRw87QD1qnjU3StgUGQiJQYPyisdK/BcAuHSVXByGJJxC7WOgnZsVWnUEjG2ywwQZXCZsCfYMNNrgX8EKFWeF6oyw3d0IlFroro/6wrkWZ9szcurinfPB7fWz+Tto5k37fcG69U5ZpGWRCeCWv+pgEcJepeqAGUfWbDknsDyqme+96ludWh70nXfOtII/8A/x7cjIBV24zXofaem3wWGvP45ifCioh7vQ3cGROuMa7y63BGSBvf16fLxMB2YI2LZ2/4+cET9vjz5p8oJ2/WlgH0JTnGEctWhTpBv5MFcH3BaKgr7Q8b601LwFkcUMNP+b1OO95wwvBNlgHay3Pr8kyN9MzbfrsFzVGOHXZmivYVZBphCaG8Mq6zx/20vaTLlNewbxfCuYsznvpjwn3Nea3EMXAIVfvD0EDmZXgOeqY2jW7ALl3h6BXZ0QZF89nlt9z6p758r3KpEdfzdEh+bsGZ7Ttastry+7N4yRNG8dAsSw3nJGEFklJojUPw4gYnSVjQ6+1NLS5ajeb2MRJYp5DZQaJgWDXGaiyqpQfpJbt9d70Ch5y7e/1NxGQWOZ2l8ro+PGdGxzrj1mgJ6oVdAlidZ4UwbfzkEeTC51rPB5y/VN+bw7y91Udp+3WibGCWv8vs0Qvjsjz+QZTZD6QJXrmO1RxnxcAiaKYCDFEUV6HKGlB1pgpGEfoVJBQlTEQKAWwKhd/0XZ/18puGAicdN5FzhUCYc8BIzN+SQF3IYIi5bUSAiHqlR/S+nkcspyLLFxCAoiTrNdJXz2m9FigxSHF+pzhcKzGTS+W5KUkdFLaKxP5yRb1RY+npQXWO7x3doj3Ks7jFyAeWLynkx0Knh/zdzpXFPDm99/w9c93CBBL8xHiut3DGwbeE/CWS2iQV8z41OxN+5sAvGKq3i/pp/36yyGrly7dny+fSBT2fu4BZF4xgIBIeJZEie49SlD+JgHOEn2t7NBn9bPVrrfpvE1HoPvhBhtssMGFYVOgb7DBBvcKE6ImP7MyiEa9yb1e1t+tazjqlqPkFk9eZErRxx6zesvPGcH/JQRRZzAM5wiIShnGqp5QkvnS+wFgTmB0H+UDRbgxl/dYe3yaWR4UJXrQ/9uN6pIPhBybrFdy++aQYK7X1vleXT881XZfOxwd1wMZDGUzeJ0rdY3LZpYNZg3khQNWfvs8bR4dfF/n7UP5flrCxG37kTqWggnRwAATIY0joPE+RWZSCzizZxV/Ye30yidt6Waba/cZ50rGYSaXM2Ejau8eWbAFmuC8y+KC68Qslz6655TnDwdr6yuCvL7yfMFuJ87xTcs3999vImS3v3IZdL0HISnHWwrOiSD7UAnBT6j8EvTrtcGjWqIvhGNtObWV9t3O/V4aN/0yUCtAWsvz2a+KLg8JQGwUFdaX5FIl7i3nPG0rWizQt1inwtf6r92Hvhz7u8/6QtnzN7r5NKS50PmV4rHEbK+wlNNbdaoub9wNdQJw++IlPn3+hNt8SUSz2fcsSrWURMEnl/EIrA3c7XZgZoxafkrFVnHYSwTg5PAZEWU37CDq0i9B465buPJAFnuZEUJUa/U+jiZVcLJ64Alqxp5SqnR6tp5u9Nks+KP2HYGhukQQgOdKN37zN46p/LnTnHtNuG2yDSTKcwap+2tCtvIHcKP7OBEhJsYoobLlG22H96BwLOTCfVmgV/wiTUhDremCluh8Pg0pfIdxEDAiQdoaCIFUeR6jKK5DyPXdqUeHMRBGDtgTYVBLcJtHgu5XAn7tuOgWTw8JnAg7ZnxLjGEkhDgCKYBCkP3Eut9jBHEAgxBZLpMQCJQYyRSXEI8Gsj+nnhRJ+2wzZjgrUwfN3CUi5xkC4j7e4ZDsxtuX78udLIR5ioBm3xyD6VevUNS7UrbhFME5CRLv3HJYuyO48j4SQRgcDWmXpHaovT1YCz7/z7/Ec4HWOep8mHv3d5rzA0mr7Hzx7tUBsTZ/61yX2Hn7Rvf8x4oWXQefgcwAvUrS167iHICdgIF3SIFBg1z4eMbA10Dq+bC0JWmvYKEErpMt2mCDDTa4GGwK9A022OD+YUJPc/1OreTKb33B08hM0+KURNZvyCUzKN80z/U+FHF3JiF5CZncOYLMp04DU+e3XxuXKrv3pvy/K7bqtq33LCXUKdSkk3/T4UbnY55Pv+/161BbN9jg6KJo3lfKGS9aW7i4GCjuCiEXrZjYuR+tUa9/ztuDeqfK8XrblOI2T4Utc0j7HhQsJghEEhd7SAlIKbuiLFVzV+B5kTYstDy/XIUFT5lAP1uqsQnfAcs1xZ+Lqlj0/mfDhUuV6L18j6FgrIX7a2erp26YnudHodmLi6smICvOW+vKpcWcM+ZnLu5rsMa+DzhkiX4NcF/7bA9R0pkSAqgt8nL9uB+86GN2n9vDQyqIQ3G/575Z9L5zaBwbJ25+U/5bVJIJUyVMo4LsppaynoHx/UhLpl8Jm15i5WYNHOm+UE2v3xteYZlgVrSFKsuXlfL+KrMhRcthz0CO2cycEELIsX1Jrxgk3IDAGNO+4oGt3cHGrpmEYnkr42zt9N33tKR/VdR1mMQv9zQoK6FCrh72fbP+kcQYFkv7MvJEwB1DY3OXcm/Qv9TSWwGn0EWlvL7njWOW6P779vdEce4VoJe+zM/KP7D2hbUmIgQihBgQg/2LYn1u7dP5Mhrb/t2RxDh/Dn+ZxejPIE7WyS7AACmJde8IYJAXCCkgpB0oBoSduHQPQUO06YiMaVS3BQyEJDc/KIERkXhEIEbi+SsLs5fhslyszBkTNfjQu+iW935W8wD5xzr1YvyHP2f8mZA9Urh3rczlJUSJ/gpyhs3h/GcoSnRTng8ol3W9e3dz2x71r+UZ0b/sFSCW6G902E2R/ZHqkWz7uRwKbzrpH9uFgOI2PuND1x8hQdncZIASIwTglwR8i5wbWnmOYAYHFxOdplhm0Roon+czA3Bj0F9mF19nG2ywwQZzsCnQN9hgg8cB5gmZz/kfF0YaEObyoGXFlEmbkG6d7+/F8vwMuGTtP6ug38Mx5mOl7m9BbnJW4JM/q0qqn4W1iQ1zGNovfN0n1HOJnBtsAMzhMoejG+Z4Ke4ryvNyVrTC5rlnrlJrJXrLfB97fmzwZxVBrU5Ugtkq0PWHZlaByJUofdZCLRSrLcyDe+97d0wxclorrg+e6JReEE7yt7Oq/MvCQ0/YtWGxDZ4KmBLdVo5XKszBuTyIt6y2s/oCAUhmz3RTIuxAlYLkGBQXx/a3lF+VkdyLuoDqhz3u1ar1htWC3nIpojcFqo9M3NI+AEpMdHvWA3HEXdXK73/9hVu10rYvjEZjMIJooMFB3JtHVSBySmAGxnHMSmr5mopiHaQW6RZORhWDqky2OkyJzpxy3WZJntSKlig4Jbr2m4tlOUjKSlyfBxZbnWBzzHlazF2zuW42ytHSCWJlrEMAAHiTXmKgv/IcfCdIm4zv03xmtWptuZFJxIjiot1bgBpv59dRHUJB5szvvXUY/fRzp3a1/kRPEs5SJpkv6BqjoLHHJf64rbsMJNa3KcmMt5dV8/ZW10hRy056uSNQBBhINGJk4IvuBySxKI8JCCyrL+wICAGBGEBUt+/qH0OV/mYdIl4dgsq9TJnZmxvDL3NvmmFyv6j71TI49N2hd4eolaJcLqtQ9pG8+YD6IgYBeAPZ229RFOFRcb2VEQHs9cuIsg/t/LMab/AGAz7kc6LlM61VOwB/6O9RY9i/146N+t7irb/KHa1PKBuH31hwwLwl+vS7Mk4FPhJyeInPVOq1Pv/6tz/AzPj673cgVg8jal1+mxhfKekFC8Fa4hBELlWANSb6Catlomw3lnZ1SRtssMEG9wubAn2DDTa4CLQCffcGdtM3E3PmTsoYclOmmyV6+dQpIaeM26LbmQfc1t6vAr3REC2Aac7T2mPE/MXEswvHpbrh7BrQjQP8UDBTXW9sqPndPs+DiVjKVzL1TpC0oJypXK1moPptnlee19/1a17TnqcNXP05GWjy40xg54Ly4eE+lG4m38m//Y+KIXaxzLvvMRlmH5oiqXC2CFFrHNQ+52q4WB/NiSAOPftTKAtNzsRrOaauq1EscExAUVpgnlUMx1Rnb8dldfuevJXAAmiV7Wf3da6eQ21w/6xNomAh975Ynrdl5rS28hXr34ROGyyHh7yUeNGaruHw031/DU1ZA0vn/LEvrJ4C3uLyVHjQPTFTl1mRrlGCtTyFKJsxUeQtWa/+UpMpMESpqu1DoagttvBS1+2Tdjekn1d2VC9QW+Kth6liw49vfpsTSv7+PDhewsEITM44r+Ly/ey16tj8tOPjv1fv0k2bXI1J3SWrApxU8UKAxm1mQN8xQyxm1WW06O41j2rCRTejFvdq5QxOqMydiyjB0bN9rqdYuRcqTqtFxHO8BOE7f8m9GgHcKL1l6896O9BfOcZ5ALBj4M4169j42pwHqMKT6rGmiaLMKUDP5mNOPFWc5bnncdtiu2OwBtnk8hw9S1NadD34ay5O0ZhlTzw7f0EV5iFQjovuMdX3XK64+U/a1u8s63jQpgsuk0siSRkSi3e/I0KIBLBZn6tbd0TEFJQnEOvzhFTRt4HkUkgwm/W8TBgTJOChnZfePE0RzpVAjWst7SUou2sHxOI8am4f63yEWWuXTu0ge927uvf/BA98yLgDmmYryg/VgHLxKYJzqIXXLC7dX3FR1CftRDvUPlxDBJq3vYmoJ7M9kxkAMeE1i9t4s0SHtYGBGGPhRfMfwh0BvybgS2AJW8BSlvHh2UNKaPhQLi3OsoF2o1F7XlKF0x0LXMry5XVG4hQ4xWvWVW2JDTbY4N5hU6BvsMEGF4dMADHA6q7KeGJWTtcrzYWRFoYic8JGtHFxo2bEV6tYhDK41V9tiMRpqyE1aYUwuzQJtFCQ2E071ZpqKt64FPSISp/GQEWp++dzFDaroGXo6ybN19nkmyheGsWMpXj1jbLfmaXu1dF+2wokC1MOBNX+xUYtNG2b7wNN0nq//R7rwXSHXTdkJstxMq2yy69UrtKna6btMc2+uQQ8Fut1goth/zX5lV+PbwsW4ZGVm+d8Bsx9cXhUUj4/6jm38mefIc9mzXQKyJdh8ddLx3jqCt2EvNYBFVDYwC8oo/u+cyZ229hJ8y7hj0GvzElc+CNjY25iSX+bVVCOC0u1u/YAqmPAussV4Wzh69LT5OlCbz6CiwN6DM455w/JePvfsvsN9KKFn4zfjn12z54c8qqeLd5h286YS7OmqsD+/PTOvxmcvMCTk9RPR/P8CHBs/hfh4wvCyfuPjn87QNbErf6rrWLXQ4TRtwKeFiAgu9A9F3w3u/ojo0O0/2v7ZHhnji5v686xtjUhQKwg9zMf2qljinOLG27jZPHB1dvupP7W8J2S9tfHvYGjg831LpW6CbfAKFa6z16Icu/u7q5cXgSyhpnByvczbm5vgCSxm0VHqWF3kLAfEyICYtTzZUymfnE0D/D8l1sAwPfve6XnGEnzWntzvRDlRyBCDEJvjkrvxGCKxQgQ4XYY8I0YN1rOnr9iB0aExHE3jg78KygRQJ9F4UZCS4T0AglfsyV7BPCMy6XQOx3Eltu4Y2lr0DkIQH3xE/X8jirXyHj5nnDp0vPXvyd3DtYXNTVvTiLpKzMC25jM05KBgnziaL5zQS7dJiMmxdo8X4hKuBv2GIcBMQQMIWK32+Em7rCLO+w0LvpN3OU+p2TtZ4xj7TVgB+AL9JKv8tpSNQF6WTbudkUhqhdb5TWBEyQkU4wgAnYx4kX8BfthwH4/IKU7gBlpSACPWW4QQ9QLIdLXlCxuOufLL36mq+mxVEGGLh9q0pcJB4+9dkqb57XrLGQus/+Fx7uGNcTCXOift6jdqhtVFCBu2o1/3YGwB+MGJe65pE/b9A7Aa63PW6r7fIZ39/r+BoTnACIbr8L4LEgAbxm4IUZyQgvDhWahbmX+zsgx2z/Wt6sn41d484LTwcBLlrF4wdPz99O//8RnAv4A4fY//sCX//k3wHK5IxHwCYy3TPhIpWwrQNg1MZjK4TVc2QfnnGuZ4WPCSXR9g8OvoBur4Uel0zfY4NKwKdA32GCDk6AvSOvkU0Y6f2PEuTHSEwt0HKSyTJBuT56up0ao6ZXnLXGLA8+Xg2VkVK/+01wVHhm8C0OeN1+rq/6slpwomPZKk/x8KK/73eYl94vy/1GltqKzw32exufyhLoohvQNq/AAJXZar90+MWCFoGGmofNjcFww+NBg9YpC0bFpnpGZUUr6514oiY4qBsaGdhnTJwzrmMUjCoE8LuzSmmdGHvUKL3cE3Z1TJpffChpp5hkurcVTxrA3suSJkMfJjhzGOzxu+Tw6mOs4mJBOkILhOBiaOKm8g3jxTOXXGjxxKIZwe54bDg6kuJco40YRSGXZaH15xi201pphrmdt+lPf43MwF9u8OpfuQUm8dM5N4dL7ptfWQ2WfDU2x/bEq742+XV1HRi1OUN0Uww6R9UI2iOIBk/S2E63nqEOtnfPYNKdAb+OE/0jCuSVr7Fi/H2s8qvUCm/f1bbFSzLWtd1V9aHR8KKJeecfW4algCogp/6e85z1j+UP9ogW5LNV4w9jktFO9RMCtv/PXaVqFj6+70pUBCHhW3jNkrFQ5EtyBai0XF9eyou7u9llBzpwqnhGApgVYDG1P32VFPrROMDgpDaaKauORrM6kHUvgPKWFfhBvTwzONNAtigvnoOkRvyCAMfBXGQ8G6E0APthlB5by8RlEtYWoH2+2WnvERGVRID/9RQdPr1JD5z02LdLbvdn9/izofJJ5vhCDCbEy7ax3KmcIUchpJks6FwIFUCj0I7PIqRIzEggpjADLfAcicDB31WaFLhc/UgrqWh0YmSGab+CroRRdU0hAUvUtwVmwd8YsJXEPHxKQKCAERgiEGHZyGSUkRAoYlBZO5n3O/gSScUqQWOm6KYh4whu7LVeN/QTIbItn3vc+sXp6dSwF43cWFODxYeHRC+/Qxi8nFPfpBrcoinqPLwnFytwU6x/17yt9v0Ppc6uwl8tmjAjKoTf+ALBnAMT4EAhvIWExfB887h6b8hkSR/3DASV6ab1eS9Jsn0iU6H4yrYQdgFeKX/f/M+AjMd6wtP8mEV4EieH+iglf3Fog0stcmhYSA4GyEj3XY/T8XKvbo9jl9z9aXt63o1pzKxHmKfyDI9mrtCcFPxB9vsEG9w2bAn2DDTa4CPTPXscssyMLnVD0IRv0cJbnjwuPzWA/NTgkzJt73wMvlFqyorygyqfYzemAde04kV+YadnTg4fcxfcvbr12WDbaIgQQKYihWXb/cr5GSHhwH5Fee2BkpbtZoWclvNaX41E2z+jkr57ZlWvP9LBrrAfmanKd890CpwgH7nudU/N3Lt2EUiSy2EnMc/8MYCp4WQlPZY9fTl/sR++UE3BdXf1Sy2U1p2Zp8px70jWbfPX7+wMC9AII3ePiW9a/c6qf0jYbrIXHPmvmwNzQ7lDicNuzKRda3ClKhKLMMIVhb53scVnYoVjsHR7T0/DKNHf/+6Cn9oj6om1W6LCOkyL0G81kbobN5012Bc2E5wx8c7XKuJvKiSf1SDsOKWQt1rj32PINhOcY8VXaY1qTQBhBiFFUV2bpHYgAJnBgpMQYx1ToL+X/QYRdDEhjyrHLmczSmpziDPj69bu2rGhOAgX1Wlc8GYWGQGPWMc2XiUgtcwljSrrOKI+TeURI9DW7Mg74BXv6Av6APJoM60st1gBEV2njfGs6cpJ9MVRaHcagH+fY9vrWFHX+YkqPNn4sOOl0pPInWAghkrFv5TIt5EuWZ3ZcLl2GrGTO3pwMWalLatY6U0pIY8JICTEk7Pd7UWAnWbPMEpc8hJiV0eLgya5lFwt71vWfr19nZsitKd3lgc3NOwDW1RACEJE9KYUYcLMTa3hKI5hlPTFDtJis+4GCmDyzXVjoXJVayEqcMvyncSnTeo0mlOe6xFf6119kMfftrzWv4N3SJoIohH1Je0iokPZi0rHT4LNrp9QpyvXXEE8tpkRnmBK95H7521t8e/8eb5mzB5GQy5NV4c9N6ydg5xrjDRPeV0r0jvY5j115a/HPP5JYont5U4DgnU/0AW9YVy0nDES4oYCXWtrbRPhg8TkDIceiYIAjJKRHaLxTdFrn3x3iuw6tpUustQ022GCDJbAp0DfYYINVMLVCcb/nyJeGWajSz6B4SCqtmG0Cik87HGY8r4XYmmvHqe17SMFlS/Bey5geglY1MKe4mReN1f9vy7NIUCVtrsTOTJ24SIs7w5kMTTm9bPPjcO3Qxzy1bKvFCcdEqYXx9Gu8dqv9s8J07Fo3lZbm54DJjTy7r8je92fF8riSqrwWmzor0y3rwudpHZjGTr+i6S4W5OuxLUOU6K2oxVuCF4Gl5rovi941YOe8+6sy8QqHV+7b7TtegMtmMhwS5mywHo5ZnvfyLLUwv6jlOeX/we+zeSv49nO3WA9XMgVH01KTdXrXs27jsRjdU9e6nTIgNMz027rsbE14pM657zd42jBAhEjeUk+Ufn0RuVcU2l+jrWynnOZ56zCw+/eY0OM1fAzdTGfO7nHjOEqG70b7oE9DNbpBAEXRZN/EKrendUvbQlbTl5ysbTHlNGBKQkJCyopES89fks9reETeiYJQsrFltW91sOwSoXnZEMtKc8MvKqeisaTc92zRzAkhEMZRLMnLvBRqlSHKqUEvDcCpHhklVjABCPwrGF9Eec5OUedYsqDlWcfnroe1a7W3bi+CPruFXH6H1OelzlkIyBboTPW8zny7JExIL52oVhlL/fI3UEAOk8IMJsE+niYWN+gjxpEwMMBjjaEsJjoQweOol19Ywhai5jWK5a1c4shezApDJB4ZQjmH5Q2Dg64ZXfe7GMU6PgSMKWAcR/A4YlRLeukXIZJ4ZhrTAL+rK4cbXOpBzkXwvK4fw1C1zgPPPLX9WQ+Gaw7RU7aPx847w3N2OaVth83VB4jiGxAlPOuz5TV37W3ZHswy/YO+e6vf7EBZaW9n3bd37xGJ1BKeK9zcno0G3oo+6Ki8ZbEKLy2qz4xeewneEr3G+VbPK8Vntyjx3G/evAF//IiUGHcBeJEITOJ1IdfgOkGjIPXuHsaUtybXhS4l0fJ4jq9vx26DDTbY4D5gU6BvsMEGF4HW0nxCvHglOquQwDEOc1IOan4bcWWMtQkHsrwScovXw5h6JLVr0yPBfddeHIyvq6kV9HiC+xA8NsE61741YvU2b2FDaMKS+DjmRaU1jW5O8HPRfmviFYmRVSnbW0Zhpr09JmtN3469O9aGa4KaeZoq1nvYyaOdHttZypqqzZ/KuNwv1CK/qXU0V2/tdwIXpbpjgnul9961AhBq8h56bstohTtzz9cAYsUlv9aCyLqdYBL9vlkc0WuBSqjCRcjeWqGj8xczz0uBVRg5VWw8deipdFZ+fsI33c9M2UA1tTKNrep2MZX8pynPZ0S6WSHkd//URe1B5blBd80cFwJrp7QMrt6bkqoWSNYGtRJuAAAgAElEQVTYrX0/yc+WKq6V21K6gstOQlWuTYtz3z5fd68PTwyOaHuPnVtPuOcZfLzwW7Q7SlbSErqc0Vd8rIHeWX09JxhgrTHu1JaP3fc2Gqh9b55XAkuc88CEEbXFJVk5np3OOBVZsZ6VyVqe1ev5CCu3KNaL4kn4ba+sBlIqKFPKafBOjdHzikisaiAekZ1pc3G/braXhksCO/4oH/qUB9CHlGCk7Fo7QeJuS32FO4sxIhKANGh/OI87A+Cg7UwJTAzy1sIqx2ACRvqcx2aAxT6XdgcuCvpnBER+jpFNKS/fm8cFH4s4APgOuZByyzL+Za/1McfMadaBw9zi0nKW1+c/UpfoAIgCUkoIMBf+83Guj5fbq8p4bnM9Lpc9svI8EKKz9wVRnmdz7Z4SIyFhpBEYGaO6bycKpawgM0fMID50KLDbXxJOAODq/JSLqwHMI0bdkMwMDooXiBApIARCCgwKAWEUKjgxgDRiMJfu4Gxpzxww8ggTnFWW8E38KiUNCtmhG9MoszQZ7Cln5dfG3DpZu35s9xVJCk9WMqNYn79BcdFe9la5uOBx3l6/e1W1R/J+1PRPmMJcuof32pZff38L+vM9Rlc/IB5GRm3ji7/9jr/+9ScGFN7GeGazYvd9Ti7PWyaMYHw6euiVkSQUS3Q7f01B713evyPgP/gt9viAr+/e4cUffyAx4+7jR/GMoheWGABJjK1Cx0KW2HgY7SyC9vMfgYbaYIMNnh5sCvQNNtjgJOhannNhBkTQx5KRjRNArWtxhR2iq7qCcG7SvUKhlaA8hhTlTMruXMKwViqsHACLPecbwVOdzVypj03UTmOVH8p7fHS86tz/yt+a4IjrUff5er/LX5q8XzKIbduXzHJ3Ly18nmNepuzzw4LJACqr5Czs6ouv52N093tpdugFU7HioOsS0T4YZGGLCWC4GkeP5v2IV++J5/M3w9pdX83i7M90/3lN3slz55h5aDhHiV4p5KjYdXjLUuhzZYn+yOCVBSrvzJboRDU+zBf0jjSdOtm6JAoed76fMhxSbs9Znk/WYPsNTb9ZU+9hMOJyKgaetkX/tqvDLlyccutCq8vujLsZfPts79ai5NaCz19G8Lr5ku5F0778Rjh+xBK9l6+uu5++wdMGW0FiuSu/I8q1w3Y1eSXAfVieXyvY/urt7Djzrt0hEfV4lrGvz8E81jxNm9JoNfg5Ce65jTUctPZ8qV1xp5AOnn5GxSwUGgYAJRBCPsgJDFLXwVZGSpA4zkrsBddRTlIxZxmEKeFF/jBC20XFyj2RX4uFDq3GwwaOOePMpG3P5JeWM5iIg0o3BxIP2pY10VepX8sgNZZv6zZl1h7ALa0PD3YMDvvsWlpPGbNFfBAV3G8XK/JZfoBea5Mm53qHFuif06agJ4l/TkGV4dr6xOUfK95imelxTLCY7TEGxBgRQkQIhBAAUEQEgxH1Agcjy72AxtmihTC0fMgkh7Q6gTmAOJXLKSzpFAIoBsQQ5BKAKtSl+UnXlHjogtEPFsLA0SpMjpPNN238gLfXXpqL0ccWh3vP3Jq0dKpbDbXyvF19v6GMp73baS88XrOzx5Tgn1As0F8C+Kx9/oS+nGMJhfkWchGGGdj99hbju3fag9I+w6l//etP3IAQwflijd8efVlLmZm4qEVT+KTb8AWX/Ww4J0Jiot/hA24geO6//vw3/v7HH3j+VlzQRwC/JMKXIBdDyLk8keUkF7LH9tKn79CRps+eiQu/32CDDTa4FGwK9A022OBkmFidOwW6ZijX4o1JyFzg6Wxgl4hlBpSRsPdjGh0bUCi1H1VcV+uTPEu7rset59FstcD9klqB0EON7xJ6mfocR/7+UBnyfprDbqfXzFspjZt803JJ3wdxwzabrw9z43s6//CDcB4mzJrDLTPpPWHSnIDT3EIeRl8/yHgehVr8aCKNVjBrwkaflsA5veSrS+3V1MI1j/R9ta0oqy6HaeeEUa1i7BqUXbmdXBSB1fs1TWw2+owM9yrhdAcBZ67MMz9v5V0MTCzPc1WVcpbzh7WFc13OemgF8vXemlOay5fUf3EiqJwf5KwtewprgSKcn+7RPn7oK6xpaunfoWcKHC63tUA/XPd8+tWDuR7+mbS/B6CNXc6AKtIPX5AucJkT01bS7mIlXgbsbMmKCW3ojSl1WHZdtsQP1Z9K4Wvp/tm+K4oFKS85vIk2DwxTFI8z2SBV3VATiYo86Qtb7urxWixhwdix5BM5QFFa5jo5iQxA+fRIEUTAOI6VNkTOAgKIC89pl+wZGDmpQjBmJboY87J1G0AonjVY+wexfgZpH4gQCRhoJ33lUZTjbrgYAAeh979lMYbGSiYruyiEzfo8uVE2TD7qv52OkY3MM5a6Rp3fW52DQfVLI8vcW0z0O3B2R30KzPI29wH1Yena0Mf3x86COeX5wTweWP/HKEr0KMpoMBcF+iijm/cCJyQuNCdRQAjlrBPqZZf7S0QYc6x0cw1f80ZeLtZ0oGovMQOcMA5A3AGsa1hcxwdwYIRAiBqLPYWEpHuwHE66yNTqnRDASM7qn+ZlcvbayftqCUiHiO4N+0xaO1utHKn9tn3+BFF2R4i192stw/DmMx33AcUbRGkxZY8A5qqdtczWUv0lipW61Wvu2j281XYQxPLcLh99U8W5tavXT0KJxb4D4c61oXDSNoeGV7I/Aalfl/BHKrN0SPJRYssL/KXfvWR2VvCSZl4w3jDw9d9/ggC8/vv/xof//ieICC8S4bPRpWQh2uxcEfybHIL1ssaMb7tt7UM7hhtssMEGDwGbAn2DDTZYBJ6p8Te7/TtjnDWXz+wYAXvLVbY5CtsT1+R+2O+gdRxiCNu310Js3Vc7WuHIWnaZUCshWJ9bxnsqhEHFoDwGEIolRE6b6/5MI6cMnR9F93+aprVj1L4vlhiNu/ZLDdrCPvXSjj3PfV9YuscDE2wxu7ZUl3kURzWtbJnXniV6m04eF14NNnl4MKbdxt7S7Ae7dz7OWW8OKsaZpu960NtvPwucvO5YXZH2rEihY9qxFL0WMCE6oeB1O6/s7AGc4PNQOQfeb3C/kK2+UAu85xSv+e8Cgfn5sdB5Us9Ubk/dF5UiGzjJAL0UW1/fq+Tq1cWWmjavLcqne7m1RM/yzLlLDOjjgXnFftuXubrrdN+3DX4smOiIHqDOa6QP/DiYlWhyxFFy72bUU5Oyjikdpm7Uj59/bO07kq9bqE8gBlLBLYGiuPiFXCAmVgU6JE+IEUSENI6iaDGlnx34DIQGqbbowuxdjesya1sGY0zqnlsXRwqFHjI39a13qnIN3xClMMN3LHTtTTIat0SN9nPCxNgxZWv0AUB0t9FDKbLMi6NfAqG6vO49AFwlzFh/W+fyuEwnTo7eY+f35Gzu0w/U7KAEUSwHdnMcAkKI2MUgdSc1AgkS0J5Hc1jejriuFGaQWYJHAgIVpfo4YiTTxbNMJOvc+gnN/Ta6SC+gqeU4kX2XkAZ5n0gs3wly8SWEgF2MADNSYEBjt4sDSKkoEMklGFWig/UKjhesccprWJmBvCemJhnHcMop0ic3IAugxY1vILHH36K4IR9RxxZv27tEgkGolecttK7c30CU6H16qic7q6UMBs8gcdPryzLlQnqmoZu/YjWu7abDvfPlfCbzKFLjG8L0wo6n58yyPJKuNxbVe/bZRwBgF6jUAEHxexsc0bbwsRXQrrci92kybLDBBhtcGDYF+gYbbLAKWp7HW51nxXqVkVVoj6xUKR/be/9cwAvEfZpRfMJ4euGhMDuJ2y+U4HxIwdwCHuBYa05pLTX/LgGeuZ8S/vPP9wVr+rV2HHoMSflNzfOhMvox0+2XWZ9T890hQVmbJzTph9rUvmtZ2+4+W9m2x4KeaKN6bvb9XP6W75oT+s4LZX8ijk0Rcd96fwahT0ST/XLbr3sGfn49PuQavJoZnl+E11jsRWHN+XbtfXlYOHM0LjyYjOPC8mx5PpPNK9cr/HyuEn3yeS1A1kqrNrRtsrasrlq7m8vh6ck0r4guHThmyXc6PXwe5n2yFucKk5a3QauvDB5rpA/twL6M+7KS70qJufrLy7XDQ1siayJjfvm0igu/+yxe90Fg5T3I2y/WZZXIwMDUo7PimeYjU44M4wgCsIvBdG6+d9o/FuU5EVISpV+MAbc3twghIKUxKyJDCAhE2A/Fp4EYB5cGBGh85xDVcl75fE5I5vWOgtYTkVLC97vvYhkMYAdRfvuLSjc3NxiR8P17jlJdrPdVUWljThBFEzNwpwNjCnS/7gBRmicwog5sckeaKaaCWxg2R9n1uyZ45RjcN+0aGHAYbrT8nseIsyGfiZ1kxfsppflL7WcwmbNnvtEQDHBKSBQQslIZ2SU7gUS5nhgICTwmJBrl2axxs3eV0pcYVWEexJ+cuVYnImAkMA9IKQEUdHFwdaSTKhWD/dMY68Ep45kZnBhMoxnH574RaSz3WPq/HwfsIRbwiUeU6AiKB3QtMkSGxpmfs7GyNa3r3KvF/a27zqSdizXLNZSaHzm0DD4DeJspNM5xx22/iiLd9q2k32ldn/NXJhWpFci+P7145/b+NcQi/T1Eof4Kosz/3eUhlP0ZXPqvf/yG4c93GLTWALE+ZwBv/v6f+L//+O+sELfvEkos+wRGbFpuiu/XDHysJsU/MGze23H+rAlvubQ3aV3EGgaDGR//6x8IAN78/e9499//xMsAICV8DuoR1B04IvIV3H1JEtDOHaLF6GKDDTbY4GTYFOgbbLDBQWgtzwElcFVx7q3OJ1bpyix4y/O2zAOy0YMgPGstDvBEKje/HlySfqYm4lLE5UljC6yynJpnpR4XjipZZmTzXqjU/lY5QMnrKPZ6FdpX7a+6gDVy/l5/6Mj7XhmnPPfKvh5GpVHjVjiLezm6at/yy2MQarBMnf6zQj1azsLJCU8Z6Kbb/+19K+ju/e4tvtaR4EPD/YnZVzTg1MqL2ak+FivQvN6PWJY+Cvjj3Amhlxot/cx79hrgWMzz9rckrC+jW87J4DbaTB1zMVdPAXI/ehiu2bqa1sYgN7q8Xvk9a3Cvp69PPutzgx+OWKLP9muBJfoGPxecySYtKv9a7jVw87tVY6ROWvsdcE5/HD98IfClSYzyoq+096TKRmMqdzFit9shig9s3NzsANyIkhGMEHei6E6ivAwxYExjLtAudAeIEr6mxSOYJXCAxKkOGqs6YRgGpDSAQsBo8oM8mGKpnq3TWwkC5erFyze4Ulxz9a/MLgPY67fedbMoLuv0qGmjEjWZ99KC2UJGaJrnzdq5mIcSu326vpavjUNnq72q8pAqJp3XlENnt/dqOIcgjlueA9lFuQ66yKXM6MP5FSO91O6EH3YPQ2KSJ1lvVK6tF/kXS8gVU5pHIGInCnZmhBB0RQRReabkvpOyAjBRnmdFPICRGYkTMAYEJGSn8DtCoKh5GSbWT5BQByNSPtfN1bwpS3P89ZqDQ2sNzTClc1kf9WVCrtaTX5E0SVsHazBWz0o+XzYBYXQl2R2EDwBeobhDB2TsTBlu5fi29Nr0Wb8xC3gPA0r4BUJRvFidt3/8hv2/3yH+/gZ4/x47iFv5F3/7HRQIaUz4P//5n3j/j3/kSy9e+W5lJvdsfwmMBOoo0VtoR699K2MZtT+yvuQ5AerJKOHt//oPvP+ff8p64QRCyASrLDXKSDSEULlztz+T+6JHoFqJXKrYYIMNNrgv2BToG2ywwSKolOS99yiMSY7vxZDbrY0CfSnQIeqZGTnmeWthSiUmr7h1/rEdLfeVnk7hu7r3U8p1CS27hNF4CFjDqrVrrPdt7cLdf+uE58pA9zpcW55T/kuOafBw/2N2RQqxC8CcAGlOID9NnXyJdox6Ak9bOvctBH5KYKxyKyy2VD7wbJm52UZz++Exxpwxfy49yTXg3LlXybi+/th5duh99fcHO/Rp8uPpwjF33wJFeD6nHL8fpXlzohyoo/59bn0m6IbGQK/L9a7W5dmJvL3Vuymmmzp6nkGOWoPToXz9k3fpHDw1S/Sn0tKn0s77gohpfPDTYG69n1eana2mxPEKVHt3zIr4VOi5c/cNNDUKVzjFc3bkEFH9ej/swQCe39yoEoNKuBiCWPICSJzEap0hVuQUAQJ2ux3AjGEvaqLd7ga7mxuMwx4xRQzDAIARdqIWM8tzigHjfnAXcgKePX+Gu+93GMYRGMZs2Z64jo0+gkX56Dr07PYGKTGGccDo+mcQiIBA4GSXjzTGciaaisKoxxP7IneoPYlxs8RCR3SSUKxLAafEcmX6tdZeuDC6qAiAeWKNvgQO7a/e+azLoCage1uKCwfBxFnJNndWHKMlpqFJRFaVklp1q9t2zgGZxZo8sIwVE8CJEMn491rBLxb1si9MiR4DIcWAyAGMCIzm0pqQdO1wSvJNrlWU59G7gc9NZmBM4p49d3BESBEIGg+dspk5RmbEFEWJzikra7X1GhWhrMb68pxMjB+15NSrhb4wwqQd+bLSV+pCJ6V4mOPz7e0H3XEEwmsUV+QRajXdKcvinlP1f3n7CozPnfb0pAWAKeOL8t3SPwL4DWWfBgA3bnSJgBu1QI9E+ALGcxC+/etPCTsAQgTh1z9+w//3p8RR/41LzeIpA/mCQNQ+JAC//PYb8O4dMKtEr2fd4yh7895N899/f4sdgC9/vkfUeiNkeX75r/8GgfD897f4/vEDXiYCkLKFPwUq/CZBleg0xU+dMd5ggw02uCbYFOgbbLDBemisz/sW6UoCJbFA90kVDecYxMzwuHp6YOX9AHLkewNy/04ZqVZZOJf+8Mrfw6Dsb9Ww2d6bfJ6a5+o7939XbNdKjktuu9NcjT/l1mV3anmOjGt4QgLlawEZtkZEcsTyfJreCAUyQ13S6/XeWFj/bKAIfaro1pTJpabavaUtdTb3l/YZTQUV/uwwyHu8I2B8CDh4uevBGnHaZ36vZHeMPYtQreKalFz1uTYdgrn0DR4PDim5j8U/9+lLlegXgYowwEQ5XupuP/OEx1IqtclT5PiOhrAX0+/q7ekUX67YJTHR7f6f5PK7rHyzxBK9fT5ksb5Zom8wx1+cCteO+48pVVuX7dcF/b3p6TpAcVIAyOKXc6HTmQEeB1UIjohxpy60ge/fv2O/v8tl7vd7eacKcAYjhghT8BMR7r7fYUxj5v0SGOnLiLi7yUp6ZkaMO4QQMI57gIGEYglcbjNLQ0MgmNH7hNRTkinrD9sJJHuoMXfLW+7QX6v5IkWzMdyxIPHU3fc9fr1HG7U0nf1/h6lL9znILsVRX9ya9c4CgvopV48Adr2ls5ZYldIscwP1ajD1sFLXkevppOemkSrxlJdjZoxpxDDKGo0UwBTEGtxkVSGAEoDIOewawOotAXn9jBrGgPQcTaxnd4jq+l1amBggDmCMSEROiW6xz/1YsNszcpGAEpAoyb5yyndQAEVRoDMBu5QwpojIEvdd4x1OZGt+TU3ihOdz2HrteGQuz4U7LnNYT+kyjHweS1X7ffDljFVLpTcBwD73x/rPeRxKqfPnSa+9nyAK9FcoFuy+rNIm54o9Mb7++Q47knYFEP5JjDc6/nswRjCGf7/DWzDeE+EdiWt1a3vpia0J+fvt3XvsdAwISyzR6/Za2ApAYqr/15/v8IeTkxEYg/ZlD+CG3uDbu/eIQW3fKQAs4QuqPazrJzAyXm/rbtHqBhtssMG1wKZA32CDDS4CE4U6Ggaw1YqcUgegMc+VVWpvJremOjzDpD1xWCogKuzreWMwx9hUDPlZNSxvx6XLOPxMynDV72qm3bMtgLlpqwXflOOdRy2NlIkDPIM5HcVW6NJr888Kc6O23PJcUueV4FP22a/36Sr4uYDdL25S6jyd2JAqgAMXpXlvFp4S9p5r672sjEsX+oQs0X90mIx3K6g/v8QH/bwq6kTL80PK84vjCLL/1Yrdad3tZ+cPFLlyqSmxtdi2uy9Vsz01NvO+S8uZchzI9Etx9WrAkzb4kn3ONZcapv16WpbpGR45Fvqp3E47Uw96jnXrPi84iymCzDrucgrpOdXkOjDX36ZAYZQlcz8c6+ESfa+8hbpZ/oa8l009JZHBQxMsvWbxA3YxIBEjjdI7iXWeFCntRIE9jBiHESDCs+fPVLmquIh32P0a8e3LF/leyEWMfAeEgJvbWxCRWK4PEJfv4NxeTiNCjKJwZ7F2ZHa+CYYBKdOmKStITed/u7vByAlDGtWTXhkzH94C+k0ggAPUPbyMRBVbvjlPjGtQ3WaZDyrxz+3Zo5So+lCmEte5tGu6OqP7zSgKxejSGMCtewZUIYZ5xXpvF8yfibLSY4y4ubmBX+n5EoMqzxkMSiTxu5FEgU1Tvm4ZLVFaEiggON/3KSWM4yB3JhIjBVWgk7hqD3YCEym/ruch62WOymiEMw3tdITqrSBqwHpRoKeUxE3/MIJDEE8GXI8oJ7UrtjU/jvmiB7kLZ3axhPSfxSyPMSCmHXZggORCgq2VzO+S89TR0Alc/TL783LxoJ5bi53uyyhYpV2Th7jtQzDlu+t3tqteZiWytOLV//oDn//5r4xn92D8gjcgfABBLMfFYr2UBQCftISXIHyu6mXtIVf5OX8nrtwBUaQDxfKc8rPELP8OxvjnOzCAP3Vt/o1FOS5W5eVCzdDU9J5I45NLf2+1RQMcXgE7Tyfy3RsWq+9PuUN9GUf5LSP/mQRPee8o1XkB4I7f4wYAJ0IKEjX9BUSJ/lf0vjakEjlHWLwyYIMNNtjgacCmQN9ggw3WwUQT4n4bJa5/nYdJZTyWiR7mxBSmPM8vG4rLiD2vELsfgcQaWFN7y7qsa7lnVevf5wl8bNTvdRyNp5vTii6Ell1rmbfWrS916poXSFDJT140UH51GTyaltLOCbGt2/m2z6W1bV6SbtDuNT8Ua+b8Wpgf2e++5QUfNOIXeFax59Oinde5+uzv2j1yOYH0qaPv+34oz/Q9Z+VM6Tm7svz7RDUeZn1vR0V+R+4IWTo4DyHVN3j0RV7WrM3cKdCzIu26gG4EkUtrOzolDunMhscAqQEv5Xifp051r90njtzK7+cxQm1XXAsbJ5Zdj7/wzoajrtZrid0kL/k8aJ/rItDkLQUvfW6JEaofJ9U0FIORqGz/Ww6t1WEu7ICVtlfImKW5We21eXqW6JMLqG2bMK1zri3d7xdaohs8SeX5FcH60/zHhHA8SwZeOTCXGkfbjS3PsarsucxtQdxP9i25hEclTgBRAjhk3CGW6KLEZBjO4XJvj4H9fsBut8Pts2e4u7vDOO7BXxq60TqQEob9PruiZqC4iCcxWx7HhJAYuAFCiNJDjbsOABQIgYNaO8u56+OaE5vtreJAL8Bw9RruShVN7N9bo1FkIk7R2joqsezVPMnwSZpaydu6aXkQNOktVm8Vhe2Ra9/NKc89vu6tpeJ+3DpIAMk3MUbc7Ez0XC4vy8UKce9v1t3CB0wlOBNaYo4y7NARIYR8yDIz0pAwhAEpjWCK4BARicAxIlJAdHHIa3annPOjKs/d1Or8BlAgxBAg4Qa1pQNkIQQGp7HGAYxqb/h46ZySrhnxyEAh6KUAAtTte2CAg/Qz7mJe0XseQEkuvpBzmWCX5ObvfNUzvJQG95TyjFRkYY3L6/M8EbvUb//8N1787Q98/te/c+oXfMAt6j0A1BeZyj4+xkFMW2xK+Q/65jWaWOgkyvFnIPxD1+MrLWIPU35nhAICEGiKnZO+tTYqaqigcI0FywcAr5icEr3GFtMZK320ixj+3BrBxTsDA7e//4b3Hz7gJZOcBRoLPZfb7OHAjETFEl1o2apJq6Has2s+2mCDDTY4ApsCfYMNfkpYI1Q0RqkmiatndoQbu39w1FxFxBxi76zk+lYrcdKvKDOXFtspR2dSJjjLHMkRYQ8O65gGD57glWf/dHjOCmFb19/mviS0Uzxvj9rClETP00drRo+cQIGyoKHK0WmM1TfXolClNNZgbPU4AcuE1SJEvbceqpJmdgD7L4//PpS2NscxmJvL+Tleg2PWPZN79vVn1KOD65lon6sVB3gRjeSm6v20R140Gxrm9LHglHFt8UorRus/5/Ey/EoN2tdM3KTb3EzSUMrwLf1RYGl/lq0d7+bxFFHTIwLDXRRCdu86FSA7rKp4PbhzYWFVeXgOymEWb1i/y+uPaeKqe8GznR1V/ZyLLREnfwI4cMARvCJsOo7+9J0rcj3UEZS5eXOojuOU9DIgKvFWLw2n04LHvjxGqRg8IZz1xOCUE6E9z68B75xDS5kSxHbxtZ6S1j8fC52qNwtoOH/QVSV3npOcN1wxPqUsU2/UficoK4VJTYElIu98fnFfzWo1CxAFMJLGIGfwOIoyhdXCVpWtwzBgHEfc3t7i9vYWURWtKd0gjQl337/rN7JIRfEtPr/kSBUFoVe8JIz4zlI3gcCcsNvtsIsRI4uMgffJhRMKiCSWw2NKYpEed0gpgVX3vh/NBjPoWZ3ARM7dscxkUoWnTBHhlu0rRlQldI8HtaRMK09oZgIRwxlTgyHrfoBYkh+i7HuUiX1v563VdYNiqW7r1J7FmvcIeDfuYMQQsgW6D7OVUpILEE6DmUhiiwciWTfH6jrWFBB2IYI5Iek6Glk8JAQCUkiIIWEX1FY3ABRkPch6A4xkIwI4EZgIzIO0L4m7dCL5bhcJxAEhRISonuk4ATFo/xNSUgK48qbIQFIFOrMo9xmgxKDAsn5IYrLvYkCMBOilBSaxLg4UsCMG7aK0fRBrfpM+EGyoGYndhUTzBGCTcHA856ikw5i7fdvWMlfrsfm396FKkysEX//17/x+B+n7v1AsxD8BeOu++6zvbB+8glikW5nSj3pXGWfjMesblH3zgYA3PN2ff7DkeR9kcf3GwDtivOB6f4rMifFW52vQt4aFLQa6KXYSOJ8pNYa2Z8YrBj6Rz1FaxnXrzvEAACAASURBVC6fh8+Kj17ruRAga+49MV5rm7/9+Q6/UcC7wCAmvEkJv+qIfdlR0w7ZAoHKWJ1Oo9ZwDWf/itM8Py84zbvPp9R17vNjj+8GGzwGbAr0DTb4aaAm9rh911qH2A92h6XGpJI0jcuUoMxwccM1pYgbhrzDzhGKxXrN8EnbWAKqVWReHbOJs8UalBlmcLZkbAmA48BVPybfHXNRacxIt4SWpS2kKnGZHf//Je02gtT/9mmnQyZzUU/u1D2dPeWUGepqXj3QW4vTvNX6QBFEeNfo1Vez7ZjWQ9U7Vzv3803b6vaXNszbnFO1qazcsnHm5mzZPNa5jhG3c4xKjzBeysD22zKxuT+Qt23ZVEhnf4tQCc56hFH82/Yt0KfYjmbe+W9qrwOsaTUuOmWWlr/zrTkbyO3TtswKf3Fex37MR3O3mAUHOs6umCL862EI/VdvuLqJnV9zedsuLBMDLa/LLKW8l4slc9W7xLXCw3HTJrPaOm/+u1bmM27cqxbo7aTSp9a1aU+UVv4vbqJdql5Eyn8VsuWXWaAzxKIHZSR6Lc0na345PT16eCBfAKQ+7iPrK9Up1OyNwwuilNw9/yp0WV8g9EqPY5cCl7rPXppvLv7o0jp61ue9ON1tm9zJDj8j5J5pklbvy2JdbdPEqDLMNty3qW1jyZTrcZ4SoHSoGN5RxoEEXWf27I4ze67K9pZvzaqt4pZ36MyeUblsb7P+dONMLkOVOGc75tYlz7l1L3O51qL8ybpwvyAYy9TDRUBZE7Pv3ff27K3T7DmXZQXNEYRPGMyN+6Eu5THQBz9ua8dx8XMHB/GBOf9/7L3pYhy5rib4gcyUvMhLnXNvT7//y03fnlOLZVmWlUFifgAgQQYjM1KLLduBKjljYXAnCOIjwHG+qblrZFkejF5nOdvK0yP5ur/2Yef3JqnXdV+fNnSeD2BOCvTJCz+/pTwhKugIAnjKCBRwGV7h7utXCccAIyOCkEp7dP9aXSYgK/pNIHBKIDGIbJdeGQKiB9K1BLkalm8DWF0qq7xC1Yq3Fns+txUP3y5ca6E+J/PcZFS3dXHpg/37vbsfWRXXObWdP0s+u/hocG/zN0PAwAOozHczUpmSfZ4dcN64b9d5zTY7UCCklJCQpG3cueOlPBY3FmQKG2uZi1xYeiy7IVLGKKvhBSNnRiaGYN7UiA72Cbt6ziBdBwpwmd1Ylm8ziAX8DiEgxp2snlJGpiT9FBls7tozdOOAbDQRQ3OxaI+BsIs7uaYgQH5pY0YgYBcCiCNAhClPoHKWhfY75oHxy4gPEMDtCo4Y5fiDOVkvo0bGeeic0n96KirfpL6d+lIx6jnl7+H1B8AVarvekAHtfarrC+T7SirPlHNonctYIPxJjPfmhIF73lzvYuFPpPzT8ytW042BXIZ2ql8sBw3kP6ppsEstgHAF4DpI3qV/vce/8jX+DoxPgXDlGoRQj6EIrFWQGbtI4tHBZdaXXvppm18/F7N/4Mo7fDKaf5eqg9z7M2jo8bK770dcO0fMZY/F910ax8bMKB+n3i/d/4Ii40YbnaQNQN9oo9+BqLotAzBfeaF750nD2m5YKGgugr0tbGwxlGtcXM8hqgu2fsqvaXvxsJnIy0JcXAMBdjbbwnTtVsTskhqpBnqikl6JoS7CLYxzXdZ8O1g92vdtCjXv1N3bktrZ1Ld5O5L3UTjC+u9mtUntJa/yqVwXxvVsuVl0XYu3YjypaE3s6wSz+jDJWt6F0k6yIFkWVE8RDVJq8+3i4eYHgOz8lhzVfhJcKG7/aT4eAv9n5f+U2Dun2QLJPT+PRiL1mjxZPbX1bks0RnA7ytue4/Noi1//rMbR1L57X2Mdtfpo6TlaZJijyln/OEKeE64JPyfjFcfT8L+jqi98rsmRaYoIVetXewoTkIkxpYzECY0WuUufu/vmethNupZwSrE+eKm7bigN++4aQGbmGrLLWsmE8hjbud9EvZTOseXp8S89hzRrMFH86Tyy6Hr5dC48ANaAl/08p8A5BXFpmdnmN651awq5LgdVBgBMGQj3RroWFQCxKgkIIJkLAlitatQvCLs8duVnKC/tXJHwCSum0t7UPql8gmeB53KAC0A+xDncwVJVrtXJMEvg4jJQ/TAO0+Rmwf32sTxQkwdr5u47ZSt9WxI8S2m2EpT3JdzgeX1UmUPTo7XPuZw3rnbtvj9j3d6OlFV9jQQKcu6uBTRZ8kgk1Hzf8uMCPHDlAwDKZpoWUK/ntHYV4oBteWpyddt2MvZGSnKiqHnIDe9YD3r3NTXvW7tdVU/4cvd07N1TU99sz0VFEaxN76ELk2jqMqfyiMJly1iSMZRdfH4Dh91XOaCm8TB6DJ+ptfp4biVkAEhEI9UMU27eUfvONs7VelMwkGhYj76efXylfvXe7JiJBUTw1nfcfHCqpCPJqL/nkklfF5WzVomqJiv35PLfrkwbKawUmBAEGNcKM6A6QwCiKcl2hszWhXXNGyWtdJjw6tUOLOg6wn4PzmLRnklhbM5ILFaYNjpG5zmXbHECsvL0DFxeXuF+OoAgVuwFyCUghLIKBQdS60gGQoCBozsAeUqYwCDO2OM94scdMjFu/vkLGYQpRDAYu6luMLV5wvoRIMDrqG8WiZy7e9iZymLTOeHLULoIeK3ffW3WRzKtyEbz0MXt0/bxWZ6DbkLIWgesm7ysjxygZ6kz46DPAuucRYxpmnB/OACoc1UxvADU5XkE7URumKYJU5xwuD+opXcLotvc48HzMr9lM/LIBXwPtrHN6kjLY5bupNyCoeMxZwHys9VCXXdJX9MWIYgbdauzoPyBzT29lDEQFECPoLAH7zJymqScmDAdGFNKYs2eUeqJdFPBPgTsdhEXux32u4gYZaNJZsbEDNK/AOhmhB0igOlwwATp5zbfMxOQDcQFsg1I0MwHTzu9zo96mN+Reofow86Z2dp51ep8TTgj4TSs/KfdFPIRKM8zxAodEDCdXNj3oAK0j/Lbc1t7/gnAFbiC9Fq9CTImzGNE1PSvkrz/TMAnEwaJ8IfTvWVWb4YEJBszhSdXjYdoTrKOBXb5JT3RXsqXIVbx182c18mJvoxkI6DW1zs2a/eAD2BQkHc3dC1u6Vl6zA0R3gF4lwAmxteo8dvQJQCZxVOJ8tk6T9VSlGd+I45rEDaG1PVZL977MvlytjXwOOpnYhy5f+7fpfR76uti1te9nNPfP4GXkI02+lloA9A32ui3oE4j0D/32poROamVndKm2bI50kI0O+BH9r3HBGv53uO2BuIeV7VwF6ZN7uQEP1hFnqNYqqJskW41EqsgX2FOXeGsPUXQc3XHFs6rLkZL3rqAGwlvS2VYqpPGgshL0OWD5dpcs9Bp42jVMu2TJlf1iv3iof4uAdFr2q/GcyzEife2QOc27Bqj0eNlfx56KqH3dM0d/9YL65VXLOfOL6iL8wuSf9rFloVsF/O1552Con2Kc2L37niO21h8+g9LVVKj2fMulAEsJcLKa/wZg3Xh7L6mrkTEzruHbJRpWILPxbFirRlEg+AFYOtYkm3Y8lyxsqnzevhi1hY0PUXBvFjojnc/0Jq3pmXtdby3nSp16UEnwPP6Tkepq4cWDFyacfxsRN2/Omc1vLymRVw3UHk+X/SlDixqyyb59FzFK1ns8UhBMGwdLYLnHjb6+r2Jc0uo82aip1ZCPKa/PSZN6u6Xwi1Wh/b10ZxYrwec231g1lU+PErfaCOd3Zty3T+vn8/vqb2XZzTrBse6xQLXk3I6kNrA/iXL797DxOic8bI/qrMUt3z78TMCyb+Xpfhwc+rCho6XYLm+lIeH5K1fNQAtDyr/MmA7kJoVhuNZp+6fgh7Ka/yGkKcmG/8GGJzzXfk9ox77qbBfqc3Sadalp+aKpfv1vzzMUS9L6HiCQeYDr3VHciZ14CuhxpEbWcht31R+BAKmNGGPS6lXlnwwGLuLPdKUBJtPqaaF8ZqzlKoUmRACYZqS+46bOLJ62bbvIqicMS3n/16CEHDxPuD+8wQCYfevC6SUcPhnwg5vdTje4n7Q8H69UNJ0+a3ykKs6X7Yyp4lr/NxPjGzBvs7rgqvmoHoAaCW0JfLvA41B/4vZHFMBO2Igp4TD4VA2KQB1Hilnp4dqhS5nfIeSQTv2x+KvVXL60BvZeoFSP0QE8Yhgs7xUHjOQMiNQFqaRJE9W8SHUbygQwOrOIDMKiORk4yK5smy8CbGCoNIf5Yx0JnPBTshEsmnD1X0gSN2gbu5rxacMhrrCtzHjLMqpUaahrouYivzdcIZSz/bBSALre3MzKw14xvPLogaUA3JcguUhAnj7X//C1//8VeYCvxxw4luJZzfIc18Tw7Xv8M34e8kvIYLxt1cSaXv5IxXMm8q1Zvq9NSF7AwzreFT6Y90EVdvF50Fcuc9zWu3Z+xavv3awh6UeCHinffDG+qfys1tiXCEjshq9NO5YWDbk5Iyom0IeRF1/tTVz3axdg/ZaaZtv+rI2HcVTf8/jx2s+PXnv4l6awc+5n+fPzctL39LyvTThj5e/N9roe9AGoG+00S9PJjnNRILBbS8WUhFGqPyr74rWgIfT7lwh3sc/uvfJV4kl53ahPPt2waVPDTdWGcySPPH+8TQWtWnh/XyJejp8WYDjdHnX0kgx4VN/6nrzeR/3mPlCzp74M5/OT/eY/fmxOKn8F93JpSboLtXPUy4lj4+z70GPSbNtT9+/nT5o9n6pT47ru1MsuxXRsurleJl8WnPV41p6zEhdM/KWl/dL98Ir57VcF9+i8ssQ67YyTTwB/Yie+yPoIThDbROvUnneGhtZd9vvUHSYdYS2f3ewavHeUN6xV2pU8FzIuPvp3rbKYcrKuutTbMvNbSjSa/oRp5j3s+YjpYAHftqnerS1jqbRKpBHwZc+991x9s3CpouZBf8w0IkMNN37se2/PL57PdUYnF03VuY6wHmaY/B8lqvy7jxao26cp/Oj6Jj8AaA9hNUHPDX1dgmUz5ymesaHXBMvyUMvtya/D03dfQ+kj2bSdVLTMlRybOVmae810D0EmI1dXubj8JH3FdFz75cl177/HR/WBAqhCZ/VbbbwA0WkbaMjAxF7CGh3h0AXQBbANOGAaUq4u73Fq6u3emY6kFJCCAHhIiDnAL4X696gIFHiPkf6y/WIpbiLyOo5Q0BaYOq86IiXvQgEc8jdWkMGiti9u8Q03ePy4ytQDGAGDlnA9IxbMIALvMWegbtwI2VWi+L5mHOb8YAZUGJt4VU4BGDCTW1Sh0P1qh7fbFYO0gDJPffzNg/u/TNCtdw1Dw93+mtu5EfreGZGmiZwCAh6xrhZgINQrmeaI5uzg2yqzN1WGGY7Tsptktb4QhBraOmFoYsZTUdnMFIm2dhBLBbvAaBc1487jojqiSmECLCA1owM1k7IrNb9UixJletGAvFiobXK6podhKxea5ADcjCGr9+pI8m6wbWdDQisbtkl3zlzPY6AWVqZGeJ1gVE2teh1YIGbc+FW7WGCY2o7GzdP5oenHZNI5nLI+PeUVPO5uzeLcgJw95+/9Mzu1gr7WsMBlT9/hpxh/lnfXev9pxPp+/xfd88+k1h82/dJecseH3HAPyXcB66+KC8I+AbPJSrg/VnX3u8Z+KTeuT5wLmup2eYb+Pqk5uqKWxDdNllaT/P174/L+6z98Z321QSp15vBQOMMfCHCFTHeZsIXMBB1zDoQPWQGBbcR1L5fqGvfJ8gK6XkjeR4EW6K1v4M62ug8Wrfi2Gijn582AH2jjX43WtAEN4JK44qF6z1375rVHdodro7OVSTXTZhLatNTNJjCz90ZdyT4KaXtqpeD+GnheunZY9Wzq6nXGA40iKPqMmHqVD7XlqPdLVr/7WGWxwIX58KpDwfeHxf2IeGflx6bm3nH6s947LsgmrdzxaZ/t/zmcfluYxhbZhzvHU/A3x5MPNSMjtV8UH1PPbOyGIS8rI747DQa73MraHveKQMHz9alySXlvtf2ABovPB8dQVJcYHordJ/H7jm73zMLUOPidsz0vLucfV7y6EfK+anPRIpB1kbXx1KpCtuu7R8qtpyiF6CZWOW6ve/vZ34jCvQqj1qP933hdHzlamZ97d8fzystprWGHsLZ5+Tmwn6MH3FpPsvLgoW2957RuKtvmPrxjjc6AuJnpXOsxE+FPMcS/VFD++ev9u9KhPOt0Z+D+pNvZnP6987QExBBLWVpvCIqsgYzMk3aFgTCPYj2ADKgVun30wH58w0uLi4QdhGZBUgPISKEiLjL4InV1fWcbD1QLDPV3DrnjNuvX7CP+3pMhvE7ru6q2dBhZ/UcQEjhHpEvMH1l7N8y0uEgQHIgTMh4+/FfuPnnb0z4AkAUrQljscADU0DXH6j+Nmobmn8T8cayj4Rbua6iVt0E4f68HGcbDI7t/en7I6Nu+gDEdfsxVsQQC/ScEna7CEIEERdvy42HFAyOsSvuhcVddDYgePBN2fBFUKt1WaMHollBrGycAVKrc04EDtxYqRcd2U42i8QQ1BI/ApF1KcUuTwoh95tQFRwU9zjynkgs0yMHcI5IlEHJYmAQBR07QcNbn2TZyMB6ZjszUs7IOSPJ2YpStsTVS5t3eXGCyYwk7TGP8jJa/ar6dluZ4BOTT80s0/ujFALsjHMhX+ZPkE0Jn/T+H6yjpVK+4/ZdTYuxB+EjM/4h4BMB/2JpW/rjI15RwO2ff+lYZQG6XVzXcLyD3U0paN9SApa/0+fXyhQ66bAcrwEQnDODRkNjdAPgqrhVB94xlXyWPOg4ugnAG854wwG3ZoSlYQnKj7J4e8i6KWRJt1NXhZV3k2/EbsFMrl5oEKRvH5/qTCLuX4xvn5xeksg3quafUXbZaKNzaAPQN9rolyceY0QLM1x12qP3JqSZEON3aj99TlXukwyPLc+7zD0hNS62W796zcJz8Xt/w6eFiKdRsL48soX4kqg7xxr8v6M68Q580f22MZ5Tn33Y8+2Q61nn9uuH2iZErqN+bC0ttbm7Pq2GPnXvn/+qo/HhNKotv3Ds1ESL4+eXpEesEs2S5Pwkq0a0wuiqqCJq5+cFWnLX3oSZpVsCy48TKR7M44qyZO44rnGBPpJdHk0LEf503feJM/wE0c3ODF8BnlfyfbNTnpuCdvZd12dm1z7MOA/H4jwLFF473TyAmrO+e0HzKLWjdOnMcnOfPBuLaIFGImpca7bxjdI+J69raW2bPK8Edo6cd4wvr85lj26lYaiT9Fyt8lRUFbIL2ukHklnZ/jjwvC1P0suo426CWKV7Q/FVbbO2I5K/8I7LT3x2svplko7m1pqAEIAYoni1VoSbQgDnDEIAUy45KGsnPoj1IYJYZlJA5ozDdAClCa/evAFnxv23bwAECF9TBmtr5oyUIFbsTEhpwqu3V7i7u5Mz6FXfsMcr3OVbUAygXF2K2/nbBMLXL5+xf/0a6SYhvA3ItxOQgEABd//cl7a7I+AVvwbjawHwkeeetQhA4LZ/BLwGgRAYuKfbuuY1FYxrl4CA3b93CjR9wOHvCUkB/H7d1JNF493In1IZcakJGad+1jbr1D1a7w8EINl55LrcIiKx8CY7n5xcGvPc2pyccx6C6H1YNoA6BLU0pTLXSSIGy9VK5Zx1cws1m0stnRhFu2FeDACAMwvo7cI1abgNbKyVbfsySPMaKMrRAZFLzdlZ6IG03wYCqf9320ghwCEjI5fz3nPOSDmVMZZYTwMvG0SkpUgbM3PlB43+zz05zYW7NYmLwyy+1x2VVmOreVjWCxwjqUmx8o4lXipW9kCdDxit9fq7cr+sF3oHzM5HL/xmkFuCgNV/cK0tSf+TWqIDH1msuP/SzpH/+rt8vQdjglicX3fZsvb7RIwrAJ/1eLaP3B2FqeV5x4xrMstxOYGgbXzXb50e2bapWCt7s4bPZGeiS7k+ZOCTKgNl3OmGmUy4DZKH1znglhSot7FpCHhmt6Y4we170dg971/QwvONNtpoozW0AegbbfSLUwU8ePCwVewwuCjHm4WFA8/ZfdO616n0UJnERLUnlWq4nvM7BAaaunh8Wc5Rqv26REUYBjCsjHm92iKt/fVX6J548Hzp6nguN/rZyY9sz7fGIVuAYK0C8Wej1QoH0dwsfj/imVbHv2rdrSVZ49cZy9MYAqwPemvvc4hUEyG9V9WX3TzMPFfQjvI3fNdZji1akh2JfzE9rvemNPScurhsLwCCPldF46PMgTd6FD3EinxNXIvfeOVyIwO08a5zx87DPC2C9S7Ol2JVfe55437jQP/ZcpHagP4M1x95Bvr3pnPLdCp0v15aikFWPi+jv/3qZHsRHrgH4cmoX+0m8uf3Plf+nmPM1sndNtNkURY0m/ABm88r7zAwKxCBmBF5hx0IBz6AOSBxQtzFWbZtbjgu7bgcKnKZk+QtEuH29hYhRJilcGAZpwKYA3YUSwEeySzmCenLhIurPZiA+CrgcDMhvovANYHxBglf8L//1//Gf/7n/y1zmQFLds+QDRRtTSpQiwizQI4sxyURC7AuoOit1BveQlyVR4DE1f3+4w74+wqJbpq06+p4LLdm974Pb8BgcGHt3pN3E7+DuHZv24GH6zTpD6zgcguZCcAcyjMB1biA3BaG3PnkzZFT7ORIGJhX66Hw5vK8/77e56zW3jkjK2hu/T6EUMrnvb6wxqgSe618yzsCQhTb+sgG9U7quSCDQkSIsXhfsLgzGOBcXLYnBc6nnDClrMC65Beu3kc6vNEIWqtD4eYJz982esZ1NFx7PoAsR7aZYzfgGOYlwlN13T5P+SPEGv26i2fN2vsdA38T8C99KeA963jpPNixjH054oNRt/DwwrnlAIhx4/pYXbP7XEp/ljioKD9NB8omP7p2M/4zL2vb+jdgvNP4MwHvmXBtUZHxe9kAk1h0zq9BuHX5Jwtsfads0JzX6JCf8bKc24TvJ2BeHgs+keK5qXu+0UYb/R60AegbbfS70cJE70Eoal+Mw69QMi0J34uCugpNJy3Pz6VZofQxz5X7WLrf6Dxyi1UvkfoF+fKTvrFodn3KWvwoSHTk3bpw1fLc8nFOdzlfRXpOjn8eBexjczpfuJ43aKnpLT9Pva2hk0p9/T1W6hlLNKULVaVUG7598OuCAaaAqNSU1PG+pp5tJ31R8LXfLt1XBSU7MNFUhHWHvp/mDETHAPRaS0sbBOxZkybPA/pR1XBwIi1TC4+ORmEF2Z9iQj6hUflpaN3cRxjXqVGp0RPlX9NnZhsvNP517tyX3H8vywESvnWxfgrkX2O9Lvf1u1U87EjXZPAcYVhB49og1SdWUGFJqSjvTfdYFfk+9qIE9PH56Lq6LeFmfP+hpXpuIftU2z1N+kMFrj1bCcY/KCfWrx5pTv3S2N88P2uklWPft7EYkBLRnwn9fcnzX3L5IdTzpY9q85fYo/W50AY4tunxWB0s175kzsBNA2qIBETMOZf7ZhM+i/V4JJFoQCiAKYiQcA+A8PrNa6QvSYD0TPj65bZYg3/79q3EX3JDwBF2WIwaxeiZsN/t1UpezzqfRIi5p28lXjOWZmKESIBaPxMYE93j8OUe7z58wP3nr1K264yMjMiEAwF//s//wUErbm9TQccwOOgjs0pmAcXv6bMEdmtnXzyzUCcQ4r8CckrSl4iAKGVkvAErNLVz4aWPZUDfGXg44tCW3kF/L/TZQf8uMN8U4GWP16gbByYAX8fNU9dwLlF/tnnQOaiRu0Odw22+LvN5weBOWa5WRZB5eJGf9jz10idYLLxzZuTA9YgA3RgbYwTniuBlBQnnLrZ7eUYs0E0zX9ZbUPfuMYhXBN0kUPo6s7pwz8gKnqeU9D4jMSODdCMLN3Vb69j3r1biXuILre2xH3YjxkTN5oyH0EOlB7MqNzftEyq/9aA5oZ517sO/d2Hsnblyb+utfdZPywZ2f2AB0W3s2JnhMqYYO63NPzTCv2Uhh/csfU05LUjjuiZfF6ydt7biJ0WFzWpdYpdcXmleroXJgcgd10l1nWu3wmMtfWp+fU3egBFI4o8APmbgn+CGtkwCEr9t+LZOxACCcQyJL7Dwyafcr/nS5J6NNtro56ENQN9oo9+FeqVXI4mwc8vaLmAsbHEPqwJ7Iy26+04VuSprooD/DmqMp9TX+fLSXKn44+mxdTlSh69Jw3bsizBeg6qwPYumty9r1f698/a6/Dctd7tYB8/dva/J9UY/lnhwvTSk+rDyd1xJ0i/ynsOCmt2/bdqtMqIPcTzfo/c8fDqLbxl/WnhRa75cDSwHcvHqsVFD5H89f+rOLVdLmqLwBYpid+m+6tsY3h+f6PVUoUFU0+ifHwHRTfE3tAY+AZ6ew0tJ42u8i7C7o3acemWv4/gbvQA61/L8GJA+vq5KQtJJvpFIaP7tsfRnkunAcn0elyqrF2IstMAK+TibfgDV8QywUybScJiau8xK1LwrMtXoWx155ma2OfqBWt4ye/+b05qz6ofPt+r7LWkEDP0cXcF4QHD3VHiLx0PKF1w3/VUn7hVwInieAsS3EYfbCWaF6L1hoIlbUuvl5d7SmADEsMMuRrF41xfFGj5oDIMh6+Ur3z6311/w+o8r3PznM5LaDO/e77D/DN0KAOyzg4M0Ej/T+WsmIOFLPc7OrZ0j3iL+EQFiTH8JRLf7d3D1LhUXQsDu3wE7RNz9aXXst4swgFsQ3iAgALgpbqxndai/+3mVlDz31up9ueys9EAkltQxIoSgZ4Fbtrm0Lfm2hrlRbzPWWJ5rmAIum04qn15PLus3+mAlowJMTwlkZVIX8WUODK5N1Qo86DxdNRnW3y1/BA5B1GkhI0SBSiMBIe4QYkQMUcZb+Yad5bmA5czuLHS9ZlZLZ65jsK2U5XWrWfs3zwY1168iPXEX7inEonPjIFTwPKBu+vCbR3ze7Ne7aH/f3S/l59SaHhBA/aMGzKhjJGlfVOUBHgAAIABJREFUsdH6nhnXCohbOB/XFQM31OZ7NH9cU32vnBo3RHpueduixnoqEK/f9t1mWDbZ8sKQfL1jcSF/xcBnty5mKxcR3jJDT/qQMcTzXkLFnfs49VUbfVe86/lx/85fzCzRN9poo9+CNgB9o41+e6qLRVtMzhEedpKThCdT4C2C5+uIAORkZ0d93zPPH0tlwchwC6NfgY7BFX0bzMMVpTejBdEH31SIxL8Zw+Z2hS78sdwez+m54VrL88fH93xfvmQalWrN4rNf2NZfD5+vq7O+Hz0VHV9Yjha3nUXFIL55Ln3Jn4+8BURf1/mUVceR3P1SluluAU16byqH3kV0AcTd46Ymjt1T+UeeNxGhzo0diO6fd190ecT8fa+QWFJQnNEJW/i8nTcrWO55fZ1PHt5vFlR7P103bMvx2Ow/hfJnycX/OuIjbepUtV7p7IIvA/ddnz5iYX40HAiRVpiPLw0LqkrBx1IBpZq06kjvhnkLMhWwGyVsu6mm9isqAedn2Xs3t0QkVnawcXzanftYRb8u5PPQ06a/wGVO0qNL+0SW6D+avgc77mWtHzMFjGXVXnEf9CIvafOXqLCs9gMPSYxksz566nhLFT+MD4T5HE6EzIxAVTVAHrDT+MjlxoD0umFHUri7lbPOwy5gt99jd3EBzgIQppTk3GmkWmdsclYLsFt+KQQBpoLkm5nFOjcZdKx/ll/SM6cJ5axrAhBiADEBRAi8x9d8gxAC9nGHb3yDwK8w3Yifgwg1pvRNw7qOVHDKlsgBbwC+RSaIxWUV4jTMGxACYgy4+889srpBlnlB8jP9OeErfUZkYIcrLT8h4bb0KW8JHEDIyCC8gXOi3PSDpft990bAP0JAC7q9+1//jfv/e4d7XCMS4U0ISCHgMgRECkge8NZ2MXSzAW878KwA6KDimcCAdIacCV7lZm4HWI0EZH1vcYC5dNTrS8qpbHCICnpHA9JN0GfxkMBZbP0RYpFi7RiAMjJ1DBEHMDE4BITM4t8/R8QQEOMOIQYg6qHxug7LYGcVb0C6gulZ3Luzwa5Oj8e6htDcwW+DWWrzDtJswtTa4+Z+Xu02wqUMD53/zp1v/SaPDDlawLwn2PtLED6C8Q+q5XoPmr/D/Kz0a/29OZIfc7meUK3R/6HWlTtB3nuX7pcg/GEbfBbK3M8da+rEWulmsGm1AdH9W7dmGHuca3sPoz1n/R2zuox3GHlKABPeRtkycAtI/3T8T34IARlZefFZR+1wu4TeaKONNnoMbQD6Rhv96lSkoFaZJk/dQsdvLfSCiVmf27cOTF9SWTaKyCMyDun76oryiclAHuLqpatLpxH3uBf/Hk62MGb/4LvTo1Xs+lsXO22cy41mypBRlDPwx92NFOrtO2ofum822fhl0EPbYdSbRgtF++XmuanKRou6BfKIwqPoqbjGA6lLcliajiUvjWSnRqz3XBfLBqDziJn+bjTSs1GrGCNq50NvgXIyLkfeAqS5MF22A7B6S3QJ142LFolsgFCzAGoyvZTPhWzb/NfKBV4ViVJPxPUpubzZJqyiXDye9EbfgdZYnp9vbT74xv50/NBSuG6TyjjucRmWXLq33z281wnw8uDPAaAd01X0dmVqlf7z98NYm29qWvOnIw6/dBb63FX8z0lPlf81luf+WJRfamPZRqupBz48RwtQ+esHdY2jI4EZ3ADV1p/FulzONEdZ8xWZsgDU+oDqxiDxNqIgYxAUdb/fg0JoMvPq9Wvc3d6CkwKlxdsG1Tgtj/rNLu5U36DhmAWQh+o4spzO24o77sZ5FRa1SkJGQmBCPiRcfrjEt7+/IPNXBLxRi3EFxNg7JNa1Crt5Di7vmkliYId3SPwZwBtE7EAg3P3nG+7pSwHE05+v8erfl2AAEyccCDgQcJFvAJJsT1xdr5tlqwCIX2o/w2nej0GYXjabryEYl//rFe7/7zUoBFyEIGd6qwX6BRG+eV6pc36gIOB+UE9Fet55Y+mNKq96S3WTws3bAUAIhHqOuvYXWzcSalsX9YTJ7tpffJqcGYmS9KEQEAIDMRb5tbGiJQKxjIdAsuUhmHCj4W3TRq03QggE5AjEjLiL2O12urFA8sSWD66geWZndY6sm1O0FXQdZ1bosN/Fdrb6aD07PIQV+SMi/VP/rqZ73spyTdimbZWuAXyAbASx53eQrQYfAHzSvGVUd+6jND+5+Hpw3VLv78yduo/P8/+sT2XrAykfkZoyoH1ZF9L8Y4x5Vq/cXAmTblS/fZldBH2a/guG9W/tY0ADol8xywYCN6ldg3Gl3iYyMQJzWReWMmgmAkub0GwDaL1c7BOzhXEXuFtXLy3Tyye9zLyJcBtt9FvQBqBvtNFvSkWg5X7O70SPIXjeCloPIQKAbHkwcXEps+clRhqZyV/moWheVp/GWUmsz8fzRP1yiapwL+vOrsZVQ0FO0vWL17L0bSrPhV9Shjtopli/z7O2lGVNalll0J95voYeoXp/8Jc/inolylKYxxB3v/31eHXUZ2JNTs/N1WNUC89I3QK9X1zOFsj9r/JMUzDa2/ofHlTkn/6sdJtgvMIW6DSvzu0kWj611uZiWCuDTxsAq7dEt3SX5tABILlklX5UocpYPMakKon9f05p7C2J0PUHeoZRtRDhS++FT5a/B0Q0Aq5p4fna7wHoGaajTq3/EEDO0nEQaNHCfJbWAmDe858C5phi/tz6MpCFH/At7FuZVzwobcPb/gKZ0rPy4xq+3VDj67jyi16B3p2Bjrkyu7dEh4ZfY4G+VBXzr/o5+ntL0I8bafOvx/lnp9Q2a8bR+Pmt1g9PQMfqK7j3YxDge1Jtf4Y7R1rXrtYTIoDk1rPrJe25pLfAbVuATC0ETXw5Kt3O+Icd/jDXKjRswzF0L5KHELHbqZtqpd1+Jy6ok3iom6YJACPEgIsYME1ijY6gAGmjsxB5k9Q6GCznrzNnJ5OJRTGzWpfrU3ODLRbG2lYZCujqvEHALgbc3nzC66t32NNb3PFnZNwiEuEeAOdqqEBSSJhCwnO6HL4oL5AnEW9x8e8diP4FZsb9nwkHfMJEwKQfTQB2uMXdn7cA3oDxtcR33zWVuZO/gJyl/NrSxdyN9ajdM+Z9pw9ndcflHeHT//0TEVJfuxARd7Gc5c1EiBAQ/d74nwLNFAiBFfDOrJbZDOo9bZCb211Fkw6iQAQO2iuL9wGUDikus2vJsovHH2Xk52JmA6QTcgiIkYt1fwhB5mZXQx7gD4RybyTs3ziBztsKzAcExN1OAHSSNDIyzFU7d9bndj57anR16labVd/Gvv+RllvT7cauSl+Om4y5JrkrvxKv/cni6fme3PXN2ve/pful8D35s9AJwEe9N0A6os4PEcAfkHPKLa9zYHxOx0AVszo34Nws0if9rh9HufxJffVzl1GEnIX+iexNpyFRxeeS3kS1sOLBg/q3LoxrVN/WNYZ2HjP9gI03czP/DurOXReMqgbG55zwlglvOOBr5Lpm1c2jxZtlljGUNfKR2Lk0zy1RE76Tf7tHXfnH7zfaaKNfmzYAfaONfgfy1iJQUdpLC0Xm4rEk0IHns/DFIt2tuGlZkPUy2rMKHuyF/YWyubBzagtR8k1V0QEAjX7ycbq3Z6KHZMot7Zck7+ZBG1Z0MLVifA5odjd/W3efdnCLk8oJ5KwcGxUFOp3xKhqBW7EsBzZ6Kjq1GPHhlhbJrRKUZ9fntdhjuBC5ETCO51js5wCqo1gf0M0H6Y9iH2ySYgeaew3JRqoLtvMaq1J4ptcjPN7Ckflk9VPNVEnYn5G5lo6dK2fz4bndwCtaC793v204r5Ld6CXQWpDcnh0F2Rc6cttHRmFsnu/jPp1+o/4jamSW/lt1kDvP4AripR0la74FCQhufJ66t5pvUSxKXnMzrnv+3c4UftNN4+KdMTp+svlm6f7U85+BDBx5rrhH1ya1/HQbyX5C8u6r3Qrnh1Cfdiy/rwC+q67bUS3R8/fI8Jndv2ze8xv4RmT8BSaf1NkfYFAg7Ha74i7dKGfGdDiAmZGmSQCuGMHMuLi8BNEBOXE5/zrruRkCFNaxFqO40D7c36vaQrYdJQ0fY0SM4o47cyrfZs5ADsVynZ0KxMtAnDL2byO+Xcu7BHdmMeu+KqsiEjftVi+5XsovQ9yzkxxxd/f3P0gEfBu0/0RicQ58HTTO/JFPy2rawN8MAdr3Low/c3nk5tvCUXfvs1DOeFbQN6qFadCAkQiXREghKHAsrtA5MyZMyCEDGXoGuLQJu4bIWTZEhBya+T6EABAXoH4XY9FZVV7PYt1b9FhOa2RWF67ArKA1WME/IlBKmORl6Zt2jjUF2YBPgXTDIIl3Bs1mznXlaueVSz6kPzPJufExRgVTZZJmzsjISFnOQbc6KWs0a4XA4NnxHrZm5lqmIms8nsn4Kmu9w9lxDZVymfnalfDS2n/tfc0LzeJltK7bg7v3tIe6yD8Sv9EfLu429UoGmssbub8mAcC9Fwhz457B2GHufn5Udq+J4z4ng8zPHnUuOHu9RG+B3vYSbq4Ei5/lovACAnCVWyt8CcDIDLzhiFu3wahZFWo+guebLkOjdvpu87xvhI022uiXpQ1A32ijX5zm8kkrvJqEs6g0YgXbVVlXJCKnjO/jWwIvW9lCF6ajoM+hwGLMXMqeopGCpQcNyv2LFZgeqiYaLIePNks9z7S2c5Vq29jmy+0WOAnd/QhWofKuyTXN2+RU6e39vNvNRPeNHkCn6s0r1MqDhXCj3/FHo8jqs9bd7EP5Dc0WiKdA9Bk/RtuHl0oxjg2P0gJXy0yN8Ui91/PQuSgAn4rqpoefcYTVvtRyP+izWsf22x8V0tPa8TJqhsa1pf/GwLJZDmvYkVv3Y5kgd72WyiY7910Pnpe6Yt+9teIeQicq9KX3urF68Snjh8a//D50fWGt5fm54etzU+aiWLsvhV2yOK/Xp/K+8BxmgX5mDylyx8N7FqvAmtnmKZdXBajrNhq5D07wzuVe43NM2zj50PW6RiE/yz2jAcm5PqtprafRnHhuiJdNbT0ede0+6DKre5EdjZt9ar8SPY12eiw/fj8Sa1yxPAQEAA0soEkAMNFdAzQAI2DmcdRv3GxkCRovwUeSNACklEEALl/tMR0SMjIyAzs9k9qsdYkAJgUSIf09cUIMApqHIMBiCAEpJbGkTRn3999Kqjmnkvqr16903UAIkeR8aAaYc5VnSazaCRCgXGUvIgXFssBUBt7vL/a4+/pV9BoEBDBevb3Ct5t7IACMpO6xxfKcmfVsdcb09YBX718j7nZgIqTDvVi1Mik4JomzCYBaiYHe6ls5gzyTnU3+Gfd/XwFJnhl47vw/DddAxreXRsnUvbuAKIPNCv0Nat9kVAvZiLcgEDK+FLDPp+/B9b77sMZvs7GBlnYfKAiYHiJe7yIoBEwhIE1J+gmlsrEiAMiJxGW5tqnpsHLIKF6OzMqbABArgL6DgecCOAOCLgsI7TdglzUPoxHaSztqujklIAiw7WViigGgIEA62aaAgBBQ8maeYLLmn21jADSMmKvL5o5dBNn7VL0s5Jnr9m59aPO+bRhgkx+Uw3SW6LU95T6rK/jeC1/lo2POZOIHF2OIKq/471Fy0sq5S3x6iQ/68NS98SKcWZJ/QO2LVXKS/nX5X//G1//8iczV+vsj6iaTkTX634P8kV8oUQXPLR17/onErbuB5QHAxOLVwMYNA4igYpFuaVl64ha+NSdYqq1hnbJrM9fepX20Ytt2Mb1f3aZgc1ctnq9dqYN3LHXzMQP/FI9NUq/vUgYHwhXv8IX8xpYaD0M23RBXS/SSWxqvjZtFePfMO4xoxH1qftr6mgerz1/6ovInoJ91E+5GvwdtAPpGG/2mdM7ktGSVMQPjVxDJh7PF+DZVPiWR+/s9yC9cHxuTLJh+r/r7EbSkDvULNB489+/kz6uU6iLclnRVMThvz8dZy2kOGkT05fWZJYUWgAKeMzA+46x4HvGKDbXeoDaujVABNwe8jVxIP6TPWfOYcu+ceZOqNmu++D8Ffnb3JQ9LH3A7+8yu2T8/BjO+vLG00TPQUNv1PDQEz3n0XHvnIwD0x1LjtrIowQFRCFeVHbOfxyqveSiPESUpLW70+ZktzH8ErTkLHcDG7n5z6ufUXo//1NbnHkQ/N+qeZQsOmQGi2TtfLnL3Ei4IkJkBoggGEKLYPIcQwFG+TCkhqQt32QjIOHw7FKtzgAUM53rGc8oC7Nvx6QwAWeRXs1L3MtX94R5TmsCcsaMLvHn7ChdXr/Htyx1eXV3i8OUAQCyYM+6L/JLcWiOEqAYH3GwALHtjCI21ZKk73Dag0wSxPBVQNswtv50M1cd1LmVUV9UWnQHqBjBOAIIC52YxbMCilwe9vzZ239v7BADMiDkDBEQO2GlkMQRc7MTSOoSITABHRuCAMNXz0Eu+JymtWV4TESgJ6Bx08wZINv8Ry7OoRwNkziAO0mdZ790Z0COd17ENjJyzlm0qdRiIgAjZYEFiWT87rx1ZNlSQrWMtHSqb5aBnxYcQZJy4HVLMKNbnmaultFgAm+troD/fuuR75Tz+GNbT8zUe/LZh2u09PTi55v5UWJ+XT6ju3COAi3/9Ub7w4868KHxy39uZ5/9CBdDPJW+V7vMfMfdMYWMsoS0Lo43Dx3MOFdbEBpvXOHIXIc++quA287zHlL7NUmfvIf20nImu9IWAd5mRKOM1E74WgL3brK5927u27zKGGni5wGXfqa0FXJFmw2OT0TbaaCNsAPpGG230DHqwpShNMMmzhYld/DpKuVNWhs+Ycvf3vCk95N2j0uwj7hYe3svAqTwM4FT3bHT1XPRzS+WPzf2xxe0I+OXuemmcGYguWqs5iPk05DRZL4h9MVAqdFSH/tp2bPNg0Vjrmrt7fFfg62elGXi+ov8dGw+kij2/5h+lN8iI/ObcNPAQODxlHTzYADcLO/glU1Z0vHURQi9jilzY9YOseCP5SenJ834iwoekd4479zMj1gvzRrPcZ5eeexB8GLVOHhTHcwORvFtvSX4qXNt3j+r1yM4knauAj4HoPnYPCDRnqbsY2zPNuwlDx4+fD4Zu3EM3Jnsfo73GfEU/7JXD8xA4GuJlUt+Wo7vnTu1XoJUdaUUsL6VuMkHddguNhk9km/MVOASB2yF/No2OEFq/DG/b4dv9vQK6wjHt7HDvrtokSbO8NR/eBEZKGcwTDPUzN94UCHG3Q04JOSfY+ejittuVRSf8AJK4srrFzlMNAyrgKHN23vUYb6/eggDcf824eHuBsIvglPHqzSscDgekmwS8JlAMiBwxfc3IlEEc8ebfV2Itf3eHSHKcBlMAQ86ijmTpoJxvTwAC3iLjS+H0lfe9QUTAxR8XuP9bTjM3oChzgaJmbWl16dvlFE0Ql+2eXwSIZfoEwOz/X6G1HF9an/XUL42k7qWOJl2vXxBhTxExBCBGpBDxlggHBr5QLhslYoh4DanHf9StO7NunoC48Q85FFA6BLEAl28DQogAuIDnCQBlOWc8E6vepl0ALZWplkfDpAzvJSmGACAKcB81H6ib8gS4C9JetrHDW5CrLC6eGepYIEVPbRzBbRqRWFg/pzJfS9jB4fErZlfrlfWM9JaqpbqFns9vklKV9jtJBX1/Xrpe834sNc3JgPCP+t7ElvzX3yAAf0IA8h2qi/cMAcszqseGj5ANKO/1e7NOX2KjBpizxmPgce/CfefyZeMugbHTtvDl9L+9uLVEfevT4JmRrD1dQm7esH+XuQ2X/mqRX3HLSwBxYw9IGRkA5YwvgfCWA74OIjdveFHnQaa21ZfKP4vK1qW1o8rjsl6dx/WzSqA/Ez3Uo9VGG30P2gD0jTb6xcmsBUW61SXWQLFcFkPZVnlq1ZnreU8+4EjxfUxhQ+XF91EeSeRWKvs7rm2g7t8wVPZjfM/c/NalDLvHbVxl4YW54Nqfx+TPcVpS6BbXZSWML1GlNcJg9plDXd70And7xzV3nTDaJtDW5Nxde++0vaoGUOpxLtmW+nmgIqlPt777PjQaU6Mwx+5/VirCMuCUgqZ1kjdeL+97o7RaGCzD5+OzEcZXVd6YX3lVFavSxUpQ+qoqRWtxaDweTvDE1QvBM8m7Imysy1HZWU1Il/em3ASQKlN/Mirt17htc+zVtfnozLoR9cDYzLLkiCVgcIByr5CStqbyW3uw/TDMoaQHrsjiPZXv/pcAMKnVjAPQXP78OefeiqZpTpc2DZ75OczcvvdxFlf+nRcab13ezz8j4NOP1zpWqyRhYGHN+yyK347mLsrH79eA2E8V5hj146t3He6fVwsTrkrmxXz1ZZ3XSx0igzrTfuat2nx6wcXpeXi/CcTlCDZfMQZ9tYhUysN49rqJi9T1cAGbNFQFgOTerNTbM7bFfawdfurd0dqf8asyp3Hl/V7efAgd7TNW/cbjn3hQrznH/NgmjP4M5nPILFsfSuz6z6n6f/rNgL8X/Si17GwlOlhnerJllH1HMNmLOkHtx5PkUaRhD0B4Mt5Sx6h6M1I9xZRQAcMiewqfjmEHA/3FUl3ORQc7XQeg4HtCylmAcv3GGt3qUax6jRkSUk64eHuB/atLUCDcf73Dbr/HdH9AvIpIXzISJiRkFfEJ7/77vUQ7ZRzuvorFMTNSZgQW/izrgFohmeXc7YwbCYN2zEcw9h8CwGItz8huo+vTtzmjHiFg94Q3COpW3gB2c0Xv3Sr7GZLVCtravbhpJ9kQZl5SMmfkiREo4yZNeB134B3jorRLxgRCmiakaULOGXtmRO1bORDecsSXKHwwp1yOBMycQZl0cwMBeqZ6IPUrR2LRzSFgB2DKSf4myAaOLOfOQ8tKFCT/2c1XKntEL9u7Zsk5Y5p0M0jOyBSQo1jAl6MZSM8xz4yUJj22QOooBAIyIVAGMuEwSZ/LzJjShIkzJiuzjhMCwDlrf5HsGHgvcnqoZ8fn5X7UHtflNuGV977f1BPMPYBe4V2C+SCwXt73dYu3B+jtvroSxyzWJl/ufqYFGKyDjMya2wD1D6hg+T/gch81L7bWv9bw7921S1Gt08mNFc0nKyjOFRx/x9XCPemfnX9uebEyM4Q/3KPVE/q6eSiH4O6aFu+Pp2AeQGDfdPPANRHea5mJAj64MJGkvRjAq8RIkfCKWUB0k9ndujTrWMzkVpOjjOtvu2GUdRz6sFR41nKfmq9deSHc70TWLudKphtIvtHPRhuAvtFGvzox7Ign+wdLIKHsZs3wO1pzzu2BNkWYpjJLLk2WjYBcFO84Ksw+Ly1P7QV4pvZpATq6RUR/PS+MA89ngb0Cc5yzeU6P593/Wmmoe79EJeZGscnNe1+8Np9V4W1LpxrRIMtc87dUBprVex9+qR7q3zEa9X7rz6dTWaZ+QXiaBqqyJaUoj8vWLx5fAlH3y93vEhUF0Sw2LptN5osYCRMIbd8bJtB93XTqwQAdR1L+reXz7rR1JLRIYulfbZJ0vFL42Kifu7g7q8OWuq61ald170xVLJackI5yGtkuPT0dT+F4gY9ZNi8dSTILZ5fOnDlQKMq6AtCV1bnkuvQK1SJ7pVE57xHL3axROpBtfFPFggHMZsniv6OqnM5+vtX5V6xYwrBmhgC3AzpNHigeZPw8XuYzlx8yixt7eqKDcnsxa461gNGaSeAnpPMsr93zpWHwSPD9HPJgqfWpxiVjB3BbX+oz70H1CrjT7Pm4DPo8HAtLTWgiAwG85djSLNyWtc9DBbFt3Ni9UzTCKUJDzVP9VjgJkVduB7fRxOpZ+bROqnWT19zVMSEX2dwD6y004sqH42QW/YXSOJyrGPlZZtenUrSIAAg4Ndq00SbJw+f27KH9fw14f+p70KnNC+fl7aXIiC+JJRMGrl+/E3k5lgCRpdQsOaBamuehPGzgufv+UXmp45z7N92AnInIJQ+9JCr89ZDE8vtityuBmevGpKSb9VkZFBGQbHMeKfBNAbsLATh2O1FZ2rnYQFbxKgAkoKdZlgMqpxXwjgH2a2JgZ3KNnsn+7euEgICwh2xSREC6zqCPWcDSuAO9SzhcHySPk5xV//n/kwgvXl8gUpCNSATkIKBhzmKFfslikW6glwHsZpFe6p+AhC/49ukK+w9ARMA31xdm49nqFlxcd3chrFWwRJOG3sNZuuMWBDkTHWjBOoKphRhR21VsNGRjq2LNEOi/ApCAWOsiZ0TO2j7A172mS8CeWDY2QNo6poScMgIUNCQCI2AXgXdE+GzzS0ILohewrVqiy331bgAAxAFI0sdSzkA2+15fYGmh5nxyL3tAKoG4ysnJ5P+UwTGAsAeTnSetcxXk+IKcU+m/kn+CvCCABGTHISFl2RSSOJe6LQir5oFTNrWJuo0PiEEB6aRpnuAarIvAss5BnRP9ZmuAcAnCNzBeAbgDlza13lpP067bzOFC9DnJsycWz/ibnvs0a2xNdbZWdmTA+bsmD9Wi/FMTmvFvjedfLr0/XIi/NS63CpT4VbaKkPPK7dxzwJ8LXsf4tX74B8s3jNYKfQeGHioB1jg/q95h7bxwak7u+U1ft3DPmrDMykPlIbk1a1B+d6Py7XuQeiejekwJcxkjNE24IUKMwcnMblMpG48hJJL5FM2mWCqLVK5qjJp328BkG2N0/mIXrqxvqSTZ1B73V8c63C9KzVrn3G8x0L908W4g+0YviTYAfaONfnEyJWAP2DbkFO2GnVZF0OMmLVtYoItpmwo3egl0zPJ8o+9HXNT7du+fY7girFylLpGP6r0XXj5cLrclo186PiERZlaKs/e0MukF5ae/X0pq49VzClTVibPq95pNm3zdql08upA3tG4W5yUKUwAyo5lBuSplDHD5ISBJKZveuj+AGvd8cNfUhd/o96RjFuiPiXPuyrwq0gG4c3Plvc+L33NQNvN18Y7SAOYKnlH5+g0p8ov59w1DkDE+UiCRt55KhAt/AAAgAElEQVQZkGyo6ZR6gzAlI2VItwrIpbIdU2r1U/Zape7vRlu9fF96CXOOlxwBlM2jmavVbhDMt7G0fIp+4uNpPX35+P34P09GZifviGIc1ULWrkdn5BoowiwQX5Lzy8tHFs5kfq7AWE7J8VNuz0vnrOzUFYQknohXiCyq0HglMt1+fwEA+PqfW4AIOSXs9nvNX8DuaofAhOlzwISvmPgbAhHubu+LTCObwGH2CA2IU/KQGVMkRL03HNT6RlTgMSG5429c23HtNyjpjoHEtXSAgOjW53pfHCMQzcOl9syXxX9HOWNHIgMzZ9k8QoQdZ0ycQTkj6LnktrKLAF4TAAq42O1BMeCOGfvM4Jyw1/PBc8gN4BtiQIwRMe4Q7Uz0XCvSe6KhEKqr9BAQspS89f5igGg9RsXXi9t5XOZM5t4yVkaZuZsmDuDACBRB6vIf2l8okB5/IOlltVb3/Z5UTiAKCEH6ZyA5JZ1tQLvNcqO/pi46WrNN+pu+v1MQ/WvztrT8DGgdrUGB2n9rv9INyCab6Xopu3v7sGuWB63MLXxyURmYbv3du3T38Vv4a1RA3s5J/0zVTXl04c2lu73v100ZAtb0FvcRrVv9WtNwd4+nc2JaatPainbn+jnXtrXTgLzN1meSc9KJMXTlDrg6Ydlg5ueg/oiiqlNpn9dJTr49Nd+286j/cpPnNtroV6cNQN9oo5+AHrLzyi+kbEfd0bid8NAI116mGEZwJA+2GB5ZrLWZWI7kiWgJID0JnD6g3D8tPaBMVViUqyezS10RxQicWRvenvwYl+0vQYX3ssiUJXYNvWfY4sotSzxbskWzLaYXwJNjKZtrPsCxopkWamlp6JeXNHvbpl7LZ+Okdz08/2bUW7h5SdSGWj/6an5Uz+Lu/dL3+zC7Pp0Xu6mF5KzF0g9ZlZl9OAbs4DixBkVR4hrw7XB12FXteq5BAIC7GnKK5VnaBvI5i8aiRH4kNTEcAdGLV5dBSzbyybLWRcL0mreVxAvXPb2cXta2/xNF96R0DsDdcOJjVrXU9pr6zH/RyrAj63P/zCg4sNxbdC+5eK8u5EmVpG50Ogv0Ed/uLcxnQHux8q7hREEfm+9KcABM1ZMFlToxIP74JtfA5l62KvOZIZ7di0KdipzPIbhJwJcvNyD6bGpcoPLeUJisSsk+npkCU+ns/isfhIW+9qNE9vlmg7bvPfn8uuCB/mS7jRjmEd58NJHjj46nvZIWy3PCiz7BW9l+f7IRG3Xun9y7DODeeJI+6wGVnYuDgLK+LtZ7buW/lIOlumufG5/q3zaih5N17SpU3QER7g9qib7fSX71vOoYQwEGAXZWy7LBkEjOPOdvXKzPA4XiQWN/eYlpOiDfZUxZrNEjBSRMpU5k7FVfA16myiBkfNP6iKAvQHgjbsMZjP2HixJHShO+fLpWl8PigpwCEHAJTt9wmDIu9vvCJwOAyxCRCNiR1AeHJH1uSjLTqQxZa/UNSF2mA0D8ENRN/aEMaUKt9+w7gbssm4lLqddybKGDuyYI2DfqSVarlq7vdQYwJncvWWBwklOOvxk4TYygrsfvUkZAQg4ZuxAQssrPFMBE2O12iLsdEmfsU0bOhPdEuCfC15DrWehQAD1ExChW2GTCOpwcQ3rGeFbgPAZEDkix7cMN+MdVz9Fw9IZ/qicFBa+zrQ9IR1+R+0ksbRkI6nqibLIzuQbm6l03HWRZcDSyChGYzLI+NLnz3mZKntB6ShkdqVP7wMIaw751dfBtED6UVcA8vNy3/XX+HlJevc99Njs+5DurrcvWjACG9FPPjwkCngMyDjJkfBBko0mXHACxTLdyvHdxfIZYnX/oMkEQEB2ovH4H4COjs+Xv88tl/tihWqxzU4vLs8B5XGFOrXSuv7ZxxLVp7la4fVmulTl8yOrTIMh4Mwv2t9afcsZbEL70Ho40rbLph4HEmHk0qtNj7TAqTfslNsjvbugjWBBR1/axjTba6NegDUDfaKNflLwQSpgLpYBT6DCXs86ZURYhZUftEb3WMeHMdgES5ku6Jtw5BTuTxnldVugfK9tcZfoz0ENyPRLXj6cwbsP5Er4uG+s9Nc8r7NKGXlg1lavzetFmef60dEplt5Z6HW6jx6W5XteeA1AQxfJBgFkdjDKlyhRmAoXkDVNgu6PlAZewx3LdKhGdsqX0Tm56cRPbEVBqhiPVNzosTvf7YRT60CuBKi094Vn7/Kw0sqrs3/f3xR05EaK6DWWo28bsaoh77sWlHxIBgaKccUiWjnIhA9Srjrfd4KaAm7k+tedLpWgtSx93pnGJEzVvS++WvlzDG3x3niklN3pRtNal/Oy9gdpcww9dacMrvSysT2MMnntwXM6zJvcNuvBo3pulpFg5qSRC9RfumpwXiuJ62yFLRO4oGrjxzE7F6azAGmDd1YPq8FdupHXcnlrpe3kskYBBmZFtg08bUxvag+kzcHiek2J578rTxzOk88TQF0Eny7QQ5rnXQRtVsrr+0fU9Sp9RFf+R5+t3oJW1bYikB46TNu71vfD0PqoiSbc6B5PRs1rWwjxPOYCtWP2SeLFGRpoSQghISE4mAvKdWOUSB4DEfXTOFXbybuiXxuUBYjmeAdDtJS7fyZwRQkDc73B/d4f7awvDYiUpCg5kfEPUvJLxOFaQj80tuVgEI6OUs0iGbuelr/0i+zAjIhZL17YEPZduVx/sZEn458NaGNWL0AUqWO43c3jrW0ZrIWsz464PV+Y/8TIgjtUJ95lBKSECODAjBgKFWOrK5ttdEGA8JBQXDSaPE0mFm7vxoDJ6TReNHN0eG1O/Eytuc/+PrgOzbNpm67cm97d1LeNYdWo5gCkh8w5JN75J1oPUZ7AjnbRXsK0jatxyTnqqxzJpxQQEIBCCjqRAJGdIazzEqOh9v3j216PxbPJDt+Gt//Qc6r9ZEwf7YxgG35b9ee5+lM4plvVZf81y3ML7+CwtxmBzCFp+PapuT2Z5/r4LYLeG4472w5krdwv7FBvBHiODlO+8bOveUXfHsy/rilm6m4yRXB4QbonlOImFs34IlefJ5tIuj30nsCUIt7mzgLNkOl5axuFGG23029EGoG+00U9C5xppN4slquprkUe8pM8qYGeT1OUrv+DAXP1NC9dNvAxdJpnQ1C3Vjyj/n4r6fa+1HrrymOLUPW8UuBiX8ykWFc9HhHkp1n43v1uKZbg4ofZNH2Nfz3DtMge2R3ejPPYnbC3l+2ktzzcZWuhUPzE6vYgeA7W9tblnYxVIAcz61tzfzbR9BajQ+FJ1hWZAdwUdeKZAcam6xaJdydd1F75xP7H+C+4NGHL+IvkY5/U3V1Z6nrau99nisv26KiLHuhVfT22I6hZtVfIPolOzw8MX+9z89mWo272UJw3A9KDWrLbYJ6rnPpYoi/W5PLBo4i5gF4Ke06b9FCQWSa5pq+VILorHnBmZW3el1ToVbWch54bOAXvHdGanqAfD/IA8oYs7HXffHM/fxXwyP4CPPzLFJYb7DAUZjYFj4RYBcXIuxxfy6S2tVXitfJFRwHeKY/C8AdndWG3z1gLtTRw15XpuKuDmE3d+Khzv7IT0Er57z6jj1rtRLTNIFq9NSRXHIiu7oa0+L+0Zm57fxqbX/JmlGrP7TpT4lmLJdpC0dRIFWN2Uanz+yIm++UagsG9mIkIOejax8QvbYNt1iMeedeg3ZzTPLV/N8qcN+NgjBHwcx9zej1zvP0HSq6hrxmeL/7noJLtTxGGpfDbPFAtawhileGbqQQ9zTRw1fxOpS1p777q1446AfpPH3X5AfY3NvzIp1r9vPSjwzNNDfeugVLcZ5/4wgQBcXOwhfEe+iCHANh95fghAvYYwUp6Q7lKdQwAcDgfZUMgJYFbZei9iFZNaoVd+VqX8eWGZ1fI03yFdf9NzquXT12+vcKB7cd2ssjAxY0eXyLhHYhZvH8rv9yrXMYw/ZxCJq2vihBD2YM7YTRdgEHK41fr9KtyeCDtcuXyr8KjzYAE0g7oZL9VtOhcqfUXO8TU5/2Hy373+Xuqvnbk8Ej8Y0q8TRMFsluik36WccdAMXwbdHIGAlGW2E0t9BmIAZa6b0IjwOgCvQsREhEsicbGt82gA8IoI38q8THM+rCb7OWeRjZ3cTIC6cBc5nJhAyXRW85piZDBTsa6tdSH9OEPn8QCAMyhQOZedIBvVIhgcgliNgxp5gXMWsDzLGQCZBUA3cZtYtx4E+WN1BR9DRAoZyKnwjaLO6zfrHWEWo01yvo2tzKPxb/3kblZnqAAnlP8RirzSj85S1lbKmuW156P9vfeUMCpHT3bmuZX6g5bfjjbwgH2/iQQQHuF5s4U1K/M+LwwB0o3ecwXPO0lYxxEh/usjDn/9jQQdVxCLdQD4p+uuS+O9f/4YecDymYGyaTTpC9vWw349rO9qHhifVE7/f/74A//z1594p4oJtUfH+yRxvM4JlyB82nWTtvK/rDIthXZNvkR21nkjxw9dyvm0tBRj9rDRM9CaY6M22uh70Qagb7TRL0qN8soWYG7iMfC6KvKgLqIYyHUhW6DGc4SEks5Y1P5x8sY45e+luPp5qF8arQ2tahdqd5g21UvUKHjb5edjqV/Kj0JslucvhUZLYm8RXRaaS4pBMjWfB8/F6lAUIXEGYgAt72MWhYqdM11ACFMgdHyzzT+rUi7M+tOSSzxzL7iWjodcN06Lkrh7BtQFJs/+nT//1WjJWtBbm8Mr5Ow9oAt7lMplsCpqqqJTpt3glIByv4s7xBgLaFeUdtaBgaI0kz4qVlZgRqKMlHJVjsGCVw78kAntVAv7GJuFLLm6gOPnTjHZfNvf/5pd65eic8Hzno7roai5XgQwrZ9RO078vblr95blo2cnrdahMrNThJoSv/KGmn4pp1dOQ+YhAzma9zkr25C5RfgI13kpqPt1iHtmsWKEWlNW1+25nK8rtcxaP/0mr1Oj28Bc0sgIuqeWSo0VnrbG8nwp5SXLa3TPn0ShO2iXNXTMle1Tk9+MtGBUtdGAHqOzXgIRXgLxYKgmqoBMCae/s/HFD+tHbdw0uFr+au1KsedIIAKFyrNYN/qY8bjJneUsW6CAwlkB6awufysTZGT+VgE3J7vxoDxNPyoCm9wGUoCMgS9fbsbl5/sSLkEAtqGso3krFtGckBAQEJBwU3JmdUkQYJk/MfYfdgABEVcAbrQeeqtgBahKur60T4fxeODPW+JmCIhnLtvL2qKrhwo4WgsxdvoNGEg5gZgE4E4BHMUSPMYorvmJcTgccEgJh5yQU8JhmkBJzj7/UtKzjW41fXAdR1HPGucsLtsZYs2bF9A2VsC/8dioZQllI7F0TqbaPgyZoxGkbFPOOj51fRm4ei8IJJupvSSd1OOUrlGTDg4B3NX6XOWREAgxBeQQ9Lx3ADmVNuvl7oYIM3lmzZxp8TKAVyB8BeMVSPsG4zVsgznhG4BLHb/3KqJckoLsGonf4M0DXuZ1TPV+zNPJhezD+XwfJwJ1ofx3jNY63Vy/28YRQrsvK3dpetDcrNE9yO7zbL/R9RBLj1GP9ThGy3ygrY21PL2Pu1x3bVdbSx7aJoRjstZ/ffwD93/9JXXMsjksgRFZLMOnPlHH8kvdceU7JiOD/XRBtbN5/q868RLvkVrzJStHDW4A70Yb/fK0AegbbfQT0KPn47Iyayd3706r7E6d7QLvxC5eEieEbBElgoou7Dot+fcTL/yS1ITqNvcmv80t7IfS+29Dfil3bAHuF+0AZlauvu77+I/dj/N03tu50+KnBc7Xx7RpR5fIcSPYpnjrQwy0rIf6Fm3HNkitCEJACFHBkwBzwWtfGCgJFuu6EKieJwgUhf4xEJ2bK1va+8Mq6vmzkvd5mELHuseA78wVgQuKn+6DPlT//eyefdyjEv+c5L0DrAFLqnW3ziFaAVVJ06pkRHdHoBAqSK5WJhQIOz2bkQigIK4mC5inylZmcaks4DkQggHqqOE6wG6WX80MDcKcSwNdRVGD+uf2SyUfLc8dKfJmLeAS+x4A+/fjzk+U0g+YTk6Nk0XLcxrMuF67ad8w3Bnl2muY61hSNkxEQAHFax9rgfIW4Pau1pfAc4nWfWf/6XjzfdrGnwHLvljF/TCzzkOqTlatIoPBIXayttRFVtiDdfNMyAQQO34sSn6ZV0SFL1cKyBcZrOarWHmbbhCMjGq9LgNZ5XS1DWdlboXPB42n1wAv9AGjxlOF1SlRASR6i+x+jvbfnscG2hmyB9PttsT5TDxmtSW6cciSr+8zu/bj8txURxzhe7EmL7EsyfT9+sUANAOlGYPzdJ8qcw+Mt4ADjooFJddlPDAv38N7Tb9ak6u6tjOu0MAkxTPFKD99DP7N/aRnoqsMlJBr4QDHC4Rf2nnmbEI6qWt3BdKJAqBAo3zPxtIUwFIbxtAeqQEHSEr88s1utwcImDSfBqzWOpY8TJxhlsPFXboGCtpozFBLfUIIcra7PAMS3YIRxCU8gIh3IIil8uUfF/h6f48QAzIzLj7s8fbzW2Tc4mvp9/JrngDMdXdZy7jNB1wEV7s5n6w1vRUuo7WW9We1W3jv9r32hHqk1RsAyYw49PlEGcgBuxjx7r8/IsSAuz8/Ix8OyIGQpoSblDClCfucy9nVNsd4WUIjBlledf7loPNvmetsLp4fq5LZz8N1ri8OW0zXZeXUeY5AyJlACJjyhAx1Sx8UXA4EsLyXOqtSNWtds54Pz2Y5D/HiEkz+0Q0BOQQErbMJsqXXZAlf/2z564TrfjOjL38TzrU9A3ilbfwKVLwTBFDVBSLjkrQXEHDB5RKXftxAxlHkXOQPItdttT6+zNarc/Kcx1uJ+/zP++QoFsJnffO+e2P92r4zQGXSCC+4hrE0vAj1rllDyr2dq+7L5tM4gLEHYfrr79IfLU4bh3+w1LsH6EfkxyLjWD2sI7+uzir/AsqXdb3K5biB2s9r+8rF//nrT7zLjAt+j4muwXYSAwuIvssECsBVYtwQhJm6iip1x5W/s+tDx9y7M1Dyas+p6SjkPkAZj76DfR/p7felzRJ9o5dAG4C+0Ua/AxVNmK7omGUxys7i3M5V1V9bMveQYy+TeeEwEiHlXM9w+m7qlNO0pOzpy3bsfm2c27RupGqQWYWs6VGj50vfnKZQevLL6ZMbGbHX9aAoIsgthtxfSwQycNqUCyHIjvwQG8tecW9r1gPqWMxAbnK7zYuWsi6iUJQkR0uBFgbonw34Is1L1dzRaPwshh4rE/i0zqz/jodP23b4PfmcV4WQzpXa/4K8r6A5gfS8cw+gS38UZap0hwxwgKngTIkn4yLLX846NeeSRnF5CbS9qln11zCmiB6BoedyRWqu2P20Fr9V93A+7zULgo1eNh2zPB/KSA24Tc2z5UT6OFD4egXPbSNKTaePvwfPPfBe+i5MArHjFdC8F+WvKc58xhQWIAYTIYSIGKpSvYLlBnhTOVNXNvOYkpgQiZFJHMRmNnffjBhZPUURQoCe96u+L4KB6zUtK4+fX02BmVl4FrG5T60W0WXcFkU2Od3hnI+co8xa8vwxCFjm3LVy9ak8rU77O9K2ZngcebBkRF7/PQozsvx+UCZ6ROaJyGfNAy6j33Ju7BNQK8n2lfSwRKrcyAUsDaAK8KoMYZsbxeuG3yBE6hKdGtY784xBth2oZrXxLAQgUyjpAwrku0iz20TbzCMs6Xlg2NdK1HSsfPWdyn2SYVmLODnp4sMODCB9rjzq2/0BTIx4Dexoh4S3eM03uD3aYU2SrP/Wpw8nOxPdUo4L8XkQ3afLgHpdyQIcy8RawL+EanENDUeQjQyRI+6nCSFnsRZPGd9ywi6JS/gAYKJ67nlgZ/ur8nRgBrNYftvmthCCbMwmmUtzlnPGwUDmDM5qST5YZ9Wzyq1vVGCOtKxZ1weJAaRUNgUGEDICOLksYodA4uadc0ZOCTknJHXnDugmP/VsE8gc5EvfEpfwBM4EUARIRw5nZDKcUeQTYmr6tt84KPnxBVnqEdaybS8g92cgOoGL1yzdF1iNLUj41uTuyW1ssLgyST95w4wvcGvabgKwDSmjbNPC9XFqQwa0oHxCu0nE3k8QkOUChASendXu8+f1HBaXD+f5vj3fo47Jfqz14P76cvLC3flkug8ZIzKmjecZL7d2rj1P6DMBH/kaO+0XPi+ZGDEDOxCuAvClm5ZM/rX7oGmW+izL45YjlvlFZW2bC/zRJeSeuw/lLW1y3EYb/S60AegbbfST0LlWCdRcmUSpggy7awXPzSKz7K6dLf7G8fvflGQvZGu56AvxY8QLET47IZ/mz0f3o7iO3T92kfoS6Jz8194lV25f6Yk4j/Wo/tt+G8e8PXvBv497ZKXy0HZ66MLrV6fHlrYCvZ2ygua+BEqapEotdQFJamUSgrjnE+tei1+sO5DbM8olntYFov5f0pizrnbVzl3/a5dcy+4wK/w5f7+gH5jH4bU2g/ejh6aQbBfxqtrs+bftxrY/6r/8OWmmLOqeA1UhW+/1i1ztP6UPQgA8kLhQDKReEIJz0a5nJyugXTApRtkEAkbZ5AFWyyzrjApumUUTmwLStQ+cshd6X94t0OLYGoSj5k33Zdf/qkpuzBnKUx48W5Gf8wP8KDovY3170Ozi5dBay3MPwC5Sz/wMrDYQO8qLHoDvwXOvELbwRN7C3G9yUTeo/ltUKy9TdhfZ0KWpxazZL2K2XETnwr2MUWIwB5QjkljdujLL+eMKzIjbySgKcOM5LBboIZAoxXMQ63A9j5VznQtFvPc8vLM6Z7FwtznXOKEoEEnPQ7c26efjeQ8lVY4CUEtRiMbe3/vwgcrzuUWJW6/MUl9H1s4lz64unhtEn1u89+Vrw83n0uca6MfL/ALZywlqc7y09rKNWPbOrM/LR60IthT9nObC3Pi7RzZv6sKbpaFZqvcrpsis56E/WiIv8cNdcVNQb82nR9lQaML1lugpy/bV+4PI4RcXscoVygvlTjbHBlI32wokmkeROsw8HyHddAiEHYGwB+MAwg7ApPOJOA7fR+HsUxKIbxfFMjllgfqC8i8KdRMVA0AWcD4Eq/lqsbwLUcun450Zu0hy7M40IacMRAVi9juxiD9MyATc/fOPzkFvwZ+Ai/c75GvGIXwB8xvJEwKAK7ziz7jr+bAOgKD1kLlAQq7tgN4SfclTQKX5OAMqkOfdt5u3BEJ17W7A6R7AgQgcQpFdI4BMhJ3WFalhxwGkmwsm/P0/fyKGiIsQ8HeacMmMKWdQzpjU3H6CbIjgwGWTQ5thnW+ztEvIuXqICQ5AZ1YQXcDzzBlmmU6aZ1L53xRm1XVzraoyberakXIGJ+gxKUDIQI6xWYcx6uYLpIzMSTzOuLNaiHR9q0C6tY5t4xXLdD0PnQWmpxBkKRGk/KQM8bRO5ThZ+Dut7EswbiCu241H2Uje6XolExC1XpLmPUGe3+m3tsaxmjEDYwZw9V9/4PY/fwEA3oBxi8oHSr9UGWfEho+tr4+VEQCu9dcs0S2+HWp/F7mxxpkgVuNAu7HEW417a/F3DFxouD58xEcc8A+g32VN20B0C2vj7R0D10eadD7qW37fnyV/iswThoxblUkhRybU/OnxBm7jkAwJnuXnn8B4y9JfpG/rbyZ8DowPnHH58SPyp2t8JQDOSsDqTJbOKleHMDv6bCY0sMq3g111VMq2cAzfoM9t9Hy0WaJv9CNpA9A32ugXpVZBwFUxz/Wsc1OyeReRRucK02yK/pJoFUDWCKrPQUsl6HW9p7/4vWguOq4Nb1dti9MswuWF29O1gMRUzjPd2vbFEqPble0UD9W9nlLTjLqYIcAsfu3c2aA79EP0lgiMkOUsPbMeKOAnnDCuShJDFnoBfa7w7vv8vK91RsHNl8fqxS/KRjG3IEmzhhzGPdMrdaXhWaiFSH6h4VR2yaP2A1OW2bMOjykchfS9KLUiEIFI7viAGPSdWMZQIFAxvRDuVNyKFn0sgbJaaoQsZxtGsVhKmdWdewDpGYc9FffHboHJzMVy68gEuKq2lvoHlf/a+oHmhYBRB2xi/u5CwkYPpgoAjp+f/Jbr9WyjCqzvuLFRvq1giQfMg/M2YvHWZzaOFRQPYr0VAjVeSooXE/0+kvNdY/NEB6Ib9W5fYwwF7LFNM0XmZvMuEcSKnBkF+IYoFLMq/kyVnLNYoItL16AugYPGqxZbbJXVndu6lkjrnscj3TYYzKzQF86PtTBNPmjh+ROR9zAAoIDY30PR1qezNt1zZe6NHk49kPKzUS9+jbitt8J8ajf1Xl7qe+5avQG7q8x2rEL1BgWwiEflPCcuPFhvG8tAXwvNflKa9BiOJPIWM4gyQohAkvR26koeCvKVNYjyuazQmAFE1frUrVspSDx6KHqplWaHlc1dQd3Nm8z5GoG/Srws8iMY4Gsp86urdwCAw+cJBML+/Q7p01vYmeiWk36V4q+eyhL9AAHCDSwHqsUtuz+/ZvGWt3sQkvFnqmCfd20t86/qqhRUT0jIDLwH44YzvjHjwsAxAPddz2vPV67zshmLMAU9JiULgB6oyMgCoucyT8/jw6DCW19jJaTq19gKqfMyBfUgBf7/2XvPBTlyHU30AxlZVfItnZ49e2ff/9Fmd+acbpVcSWUyiPsDAAEyGGnKyHQnuksZhkFPEIYAajmlFMyqHK+GLVoPkIYny9n/yKx74TI+kLjypwRKwMwEcEGCHpjTwZgxI5XUcH8PVUhZaIHU9YW5dW/6JTy333NQY8ltlE9U5H754xITgN8AbEF4CQ6rwL5rIWENbBW3XG8c2t6DXP91O8P8ubXJKLG4VuLzrV6/5rH01OcTVeU5a60SqCrn43ex/hZb/Ti4LzXSj7L3q+0ZHrYmtnHUy/LtFQEvWTwmWD8mAK8KcEeM+fKDxsuI/WV4tZWHgNULw0p/NGuWEPj0mMeKIOcEJzjB3wpOCvQTnMOL/WkAACAASURBVOBXgXsStcIMimSNGZUgd2ZCmYQm++MIBDshywuyL1b9x4gsqCMG3RCqE9ialVN8/suebHsogbdi370jW2quikkvxpxT/K4KO9oc9hS3UnZ/fewxkMPLeayUfwVoxVdjpnIfcLwwRcBaNzaCEVnQSQVTpqwcWaAXZhSelYEzwYjkR6G8QwQIUYAYmTbDgQsLd6gFYPOtfNZbrw/7ZeVhFaDox4uqU5tHc61CyMi4j9Tp/s6Yd/5LMJJRGNtancc0ES9RfVet2lTJloiQcwaSWKCbFTrqnDTBMIES/L7Zj3xec2IQJ3FvmhmJxYU7SOIuFp03JQj4rPLDUQnCwPusz/idK4V0ri/mwbIGPY4YQhR8/yXgcVoyWNI/HkwI1s23nS7Zu4asKdopnLirCvLwrirMzRILEg801fWVwqGqHBTu9n0KSvRB/HQT5BJhSinQhoonQh0o4Nwe99ohGntpSvAa/7ykao1jVm52oFVIZguHJGs95SLfJwJxkdiqXFCKxOlNBKftkSEqeNuXXIFfOzOx8AbquVjec1UQVcMh7pTCdaO097IXVBRklpvkZQ8VyToufWgJnhfJmuL2gY+lq25GSvSar/YbeH1OHgO9IqJ3A72wRF+I8J8KDqIufmK439i0StGxgoUHz/d2T1edXZ5sDsr3wOZVhVKgX4BWUSmv9+0ce5izbuW1VDct2ru4DzTJqD72fjsXEIlnDYK7lK7yiVAfgoatIAnR1FeVoB6AlLxK5umiEm7h0FWyHJPWY24UOxZjepOmmrdYxGb5vhj/wXU/AgQXM7k05GbL4FkVp0QoZav1ZeWWvwIANuklrukKxPI+IYNAmD/PSCBkzihKeNpYnzNVC2DpU+8PpyvZF0BE3erKu6XyR9DOE7N43WjPbdHOPVN09Xw8Q9wxT6DGEtSs12e4d4W69bBYgSdOuMYMLozrbi+60X5tRDeRL4LOPVWQMyBxlVWRDha356bgK+aNMfKIoTxRrkUmzC1qYXUx/k/7veje7yyr7UUZpYjb+olm4Vd1VhJDQ4xB5nueMOWMKed6UByl6EE71OElSshJPeewnMTlJHOSg+/xGbMjvsjzYLBX7wD79GUNhtDiC62+8wDhxaypE0QB//Y/3mKeZ9y8/6wWxHI8IzHjDK9xg0+40fRnAG4hhyqsWTOAK/gaBvrZ6/Bc31yFNC803RcEei/kQ5D5Hg8FxPcMb2e1mNZf+87en+lzw9exDVPI0yDV2nCjlEcoI7bT7l8yJFb4CvR736H+5RLFOQ7Miqvt0Gkf9sD4ZcexceJFmUnbgC8QWvIlC94w3JopiYt3AM+Z8JVCZSiMX90bvH8XuxG142yHVuRBqKMRylFgdIIfCmsHmU9wgqeEkwL9BCf4BeAwcmb0HdTqvErHgvDOLGCE+O6F6wZ7SYQgeHLrlz6Hn2NDc7bG74HHEZrF/H6O1gLe4vu079hvIruye8zbGvVq7mW5x9feXYid4NeCOouOnLZVoWHus1WRbsJ8wHgeY9J4KMiOAiazQt+Nf40NbBkwLJ6ufc6rJ6KlTq0AZ6eQd1DNJXPcvu3v17L/eXDa48BelN9bmDaKdLgCDyJISDkjZwKljKzeD8TA3BRwLhzIWdLYfbNvsIpVicUVq+3XnJDAAJdghc5IVDSu5HiEaox0zWvdGuNA0KKoipPXcH2Y+7/4QYu/O/SW5rsV3/fL+9A8/HVrfd66ZrfnSb2S5PptdPfexk4PecGV8lPOqy7c+6oym0BReqoq0PW+sKxbsz5H8RjmxRTfaplYVNM9M8N2IOYMoqKxWhNycjfuQIG5nSTyOOmCGo7A3qTrmvvHbdviIbRVCbV/Xft/V1xywySPZS2+S3H9vSzSDy3PlF335fVOILAm1o7erh+XI90lSP8+QnYroR58wQFL8oHlGXW7e77uKr1S2PXOaBU5wCQKlWbtUtBbMOsBKCvKW129iCTB8XM4UgCYa/aIx3RvCKauvfLMiiCQehGChKGo+QE55YrH7OA+g0GleL8RAazfy2UtZcaVxLDHV1XAvcaWZhRcAXil+427sD8fMA7Luc075wKrN677zBSL8RwVh2ZJfofW6jbWK6ZHeJaIMCeAiipiyQ/FCV1sByraueFnI1o833uVkjwg+7EewiipgGeqlW0PbFi+movSDWt43PiCehO2R7b6h/rOzECZkYnrQTpzwU7k7twzPCxZniZkU6ADmIncSp01vroeHuPMojwnOXiXCiOruwBOjMRJQ8p4exZtuweiHMnBSncvNWznDAO4/PclXuJlKxFiRsJr3OFTWCsy9zbwAxyMVpHcS6Ss5BchnVG29v4rgJcQN+2fQc23fZpdO8mI5ya45wb5EyVzDu/jYa52RWr4Lg3iYAdQztAeoPFWet+O9oT9UrqHAod/9So0auHRYfx5c/8F8s0LloMIEwP57RvMHz7WcAbNrkSp2fitOOn3CON6eB0H2MoQ92iCnEi4E5zgLw8nBfoJTvAd4ND99EHM7lohKpVno+KxVJ4vK7Ff8cMAkrltpM6DI0fiiZWIWWe1n0rEQBToJ1pjik10dVgtemZ0jTl9OhqqL6mn3uJzGjzfn/OxYh9jU2OrF2EyGxZmVNt975c93zBZzb9jSva+8+zo7wbE/2PB2vx77PwPhZGwbsQ8jsrpGV3HGDR43s5z/1fZ5qA4sfhwYoHiFoBlETPQz1qPGMxRG9eftSxpVCy2qsYW03B9MwBHr6vve2v25jVVVDx6Xb/13zZlO0a87JQfDLsEg22KHpaC0UPArShUOQexUko5Y0pJYp7nLIIvtVxdYiOZARbXk1yqh6aLm7GXjUzc9iWkxKBUROA7qHztl6CUqwfnho2lwceDDJu1ZzPZWuGVb5ScfV8PSj8UeqHPmiBoWPWV+4fBd1oEXTH75/3jggh9x5bm/f3B7tt33OvDKr50i2Z5ZbHMF27cU6cIJ1Ge5+zCtVZpvluJnknc+yZaUaCjXxHwNcwcLNDVqpwBdxMrcUqTWr5R9AZle8U8AyTWawRRihOSxuQVC/SUJLZqTiJIB0kMc0pAKbOS8x2lxKJkr/8lUzSrBR4IScttPtcNgZt4K7X5i7XuBqhc7xsFRKTNw/xiGYg2Eyzn+yFr2Q/2rn/RNM8s1Q/IO37vKNI33YXiXhPW/H+4pcyvIvE9nodpoJXdL/aLXrmzmim3jyLlOPq+ljkiIFfqeRRovbaGF7lSwytZ7hQS4Jh+9tRLJXr1KNGlXPCVqhQvivOS1rxwwcwFU54cvzIwpYSX/3iHz39ewrxKwA7JRIWMVqfMXK3YFXWDAdzezkrLaYxokvjoS2ql885U/D7FtOojPyVtY9XbKIXEoqTOacIMsbY3q2Eq50i0FQxP6g6dlXbHZ/2ecIPPOKOXSBAa8/nvL/Dt3wkzZlzwV1wT+1zTrjUjSser0hCbjou5MaTzujTd3Z3SxBtNzwzcgbAh4EafT7C9XOpoVsc33M67DRQ32sEEEoWhWH2P525O7lq/GoiE5tjqTGFq1BVre1kKe1rTcPIDFnDPCKSHqtdXDTWXJmZjG1cGErPs7QUAFdguHz1aIWVkgtAcKYn1eRIL9Lo/WviXIMsj3T8JAKeCzMAMlj29SFsyZyCZNwftG7Y1wrWN+4ABnKPO9OadeSe4hcQ3ty5+DmpwFHW/d7iq81bcnCf97xXu8LlRvCsHBYBrPPBXWpMC4BrAcwDfau3aI78MUZaPWvpSR/4rMZ5DLNWtnp8hlu+x3g1+Cxn2ec/aLxtwtdkv8MPN/XaTtXfPf38HIsLmbIOP//X/sPn9H9hME8p//w/u4Gs6h1buskwfju7iIY9vyfG8xTh3GXBxYriWrHS6EEAwHtrwo6Re1ijiL2jaKwKqTOXDB2TKIIir9y96wirypiaMrLIepsaVOxviDHSqEmq+KCwvtjytfj7qi/1t1J2hXX85GHXAD4CTRfoJvgecFOgnOMEvAIfy35Z2AQ0FH5/b6zb3StDuKjgQPUa49YSpva+kC7FTLaSp+iA1CzJvSJ4ecB+fHwArlA+vJBmVvpMwPQrWqJCenBylHaV5mtpE6Ptp1zfH1+4wysyYkXTUivk54JBRW2fYsffNMXDfnov16/NoBFErXy9QU0AqZgXQAwHuyrcyZiIac8vfbv4EgYMJtzyFzSG4AkEZfr/vW9bjrGXL1g7oCP4s4f5wJqy6nm2grQsv6ta6i/Wv+yupdYvlaZHmp+CYvhvoDFHlOSW1CiFVnqv1uYUSkLRo9SSmQHMxnvwV3SeZw3atb+0ePgeb+W0KJ7Pgsm2ePJ8Cn+sPGTZzXW8L0w+H2FORTJi1lqVMD5wnw3WhcoxoxYXBfXz+uNvCrr34r7EuHnuFH6poX6WAdnzn84wqzs4qkBZdOwFrivOkrlOT7R/QUCBi7WVCWxNOg0jiDJuFHKDr1BYfg/Q7m3cW67wQyeEWjb9aCiOpu3Vb+wR1zVpmuWM5DCYKIcAt4Kkqiau7eBQR0tvzBa7f1fG6oomQDG90/U+271RS/h7W3E+4dawf0FBB51ML1HrGAKEPIw4a4KMlfdQneur7Xxf2TafoWtriNq99t6uXbMW7/o9A4W30y1KtZXfk91ggrqWXdX0KiCvqmHZ42uWX1f6cCERZdRXk1qVEuLr8oOs5um+fvT7UjqwpBAGAeRKlD5ldptlPj9GRpNI6gYGaN9X/gBIOypg4IwntxdYq8uaSfS21KnytNJyXf6cXakAsyk8Q2CzRZ4nKPr3OKJ8+44YY5yz5XqtFeZ2fYU5UXL5CH+2iZnYD4Q7iktrWxlZ5NrMOJpucynPd6AGu6O78Tr8+I+P3vL6ZErbsB9G8cnU1Kq0rij2uSjzbrwI1GoZDhsj2snal+jyTlPHQnqVvuT/ysQZqub2HKKeK5U+8Qyl+MgI9Z+QCIEtnkNEiOYEsdAEDzSgpgnPam2r4iqyHNhKxxH+nIod4E9cDIGis0b1fR+PtYOsj9oL0ywzGDKiFtH8zh1zanVkOXZyHdFyff8JUVeZueW73hnEzYhgBUpfsjBcArgSLLOruh+j7w+ysh/9k9b2CHWmJqZeYXea1rvzg/tve68hghligTzCPidHtudfl7N1vACzEhTx785//xO3tFne3W2xAyGBdPzFyPNWWveKCzxRr22O8diZ7v66njT0R79v+iAyn+RWx93Y01J+2pQS6NR6w1H+viPCcGZnci9MFgG8EWwTwXb+tk+U28v5nHpiaY5RBmd5HcLdk1OW3y7Pg3wWOoT77lbLv/V+Hcj3BrwgnBfoJTvCE0CB3Wkf2drh24RIRRmS2W0VPytQN3JRCXSZsnJNI0VvLc+43opaZQ0v718RUiT0XnhW2mF5ag9hmZZg84xGRFqElOP1Zw/os7onDPXHbWQhMut3XY7fORDXDsHK4YFTjUe2dSWvfr9NWtPLWZ8LonVSdAF6eo99VUvztCZVh4pVXHBLtKn35zp+suRemWrtx/jQclfF6OQYO/07rdU9qbm3Eh5Xh3fPu0LFfy+PYJsT0BVFwOE7bs1b+261nBsxkpPJCmorCIRyC4z1CqsIDV6i3kIjApK7riAO+WLKJMLauJnHmr03bWyOMsBrX76MVMAdLv/p96KR947Hsa+fmrAbLPCJebLE/A0Hwp+x4xNkMtwahhzKJ92d/DFXvWw/jb3tkvFyBvYUrmnsSV+0kCrqUMhKZparNOxGikgkNAdRDG0W8IZiCXEIumvKM5QC/vbM9FraFi3tni25cT897r4johINyPu4PAzpE5lzErRTetU+qAt6ecjwcQnX+itWQPrbl3M81teYBobpmbXBolUgs9/F+84ohH0h7bmQVM5qvw/4YwDolsCATuvfa+sWJxGPvvx8sqLEoAF5VUB4HdY3pxp/qGnOcn1RhK3+G11MTt5xSAoKSPNd1mET5bekspEdKC0t0CfuRqwJdykoajsEV8ra+QTv2WjvIonkZUk0pgVkswkop4JRknqq79cK+7lGADAaSKNsl1jkDSY81MUA8A0zIicQQLdLMlECqKDIS123h/RmHZ6UjVEkFx9A0Zj2eEvkZtDVr6+YZah72PPIgpN9VQ22Gn7WNc6vPW61Oy3LxrUBL6cY6N7TCynxe2/Nhda3vyVPE6oMUz9UOafJeo5scD9AT3ZuAuQs+fw/4Kax9dlShwNWmGa2SxqDuYWT0ptPoccztPcB1vjIYSV10G/+bgGa9PYhkAlYZJaMHqtveMC8Pg+PHbrFPjNLonDB33A21zIxSZBQKCImNbmBspklooSx7wFyS4EEUABIyJxGwnWVkchKvPqVwZekdzRCAuVrsMm2QkFHwDQWMMzzHHV1LPZPRMTrqxKIILUXctrNaCxulkaSgmQsKq+ttAsrtrIeglIYrW8GnWedSbTcaRduF1tfomEQ+4DM+Y75klPIc5+/OkctrPKfPtZ5OFxMm07MWCe+R6mz1IwZxkpjiryHcat8N7s3aU2m4u2bvkOQb1pjpkQ7WhXRGQGLCDbWY6Y4SzhRHfgPhAlL3RIJDL0I7mIELiA74G/zAF9d/JFcbMbNW9wPB5OmMlmxQpY6DoexKaAaitfYONXurIXTWd83eWpF9sGVnyBpIDJ4ZnCVu+kxFYmenXA/8KXMhB3iTxHFH5korWR3lUAchJ4ntHorVA7U2y7y+dZy6to0xJdd22521lwFsxxgBRdOf4wW2atv9OpSXAXwE4xlcUXFXTSOK5u3u0H08ZQ6Ii3drhUgrX+nM95oKiF+fojugzmmwqnsZL2trGK8AfIJLP70fSu0LhPc9jRhXktFdd2BkrYWVbX0g9KaM67TZYHt3h+tv3zDlhNs/3tdWZzDO3v2Gm/cftM9tRCS/LYBXzKpEb48JPDf8DOBT3NNCXd0PQ10Itb+hbUlQuUpooXtY82dF6a1McjglkdGA1kHWc37QSEhBPbKk9PUMsTjPYDxjxlQPfwIUagH2Q0427jb3BbVq2wJtZvund5QffLA+pfCGa+4dnRAgYs993h3qvLkPOfVgAuN+xVUcog+j+D1g2+bevo/N7Ku/677fmYb1G/AmJzjBQ+GkQD/BCb4HyO7fPQxEK1X+Ir5uNpjIRHXZQKlhEUJFJTlUKF8o5Mf12nklasraCeyElBA9HdMUqwUAUIbX+LS4iSmh05bZbnIerSZuudylU2KtI9QWVV8pwwSeqNwdqgKircvhIKR6a52/FLhGEsz/BRCuYuqlctytbDWF8XUHkRbL2lSin9ocDm/7qObjVO1FS3Ad9K1Cqn12fJu/Fzw2TduvEvn3uFKO6aXmMExXcuA7unf9GooWbe2bUmeZ4qcgIHdFmDI9QJVQCL9VUGaxUkiTCBQkxrQJ6uXP8Chlt1pP84xtKQshvKTVErRqGc68SQuM2WpZxuWJbBFi9Mydtfuogxcdp9Fgz2aPWZ6mr/1LrcChfY8gdOXl4FbhzXqlI6P4M0KtHwGieEvBohNNAwgQhZumyUSYKONsmqrwxvB2YQBF3eYlqGAx9oJbk2I2UZMozzgMAzf4GzDMr+IHbLdb3M1zFdiKy2OzvYiCA1PkafvcmKaz4kEYUqlz3Iko2o9zUWt56FSi+n3cuwRhEGz5uAAzNenq4Rgrv9sP7GXNvsYvXZ9d/fp8DLC1HWqHil/6tEpMuMI8Wi9ZbiNxwq77Hwd9vMI1ZfqaYn3h4agqtKm5T00fydxISXE2NE3SOURU3bJS+M/cn6ac6ndgqIJcD7tMWZQkSVyhJvUkQTmLO8hMXiZs2lEzH0GdG18M9l9qftQ3L4ttuVqgF2aNaV6QinmnYG081TAMc2GkVDDPBUQF8wwkKmo8RkgJKCXpWCUQzUgpg1nUaaXYPJT8RI9Eej83VbZDUw0lx7qjrCmXO0V6fG4K87X4sdWFZz+vqE2zVvah+4zPtzSew4bWKPwavvTXddc0Gy+G41M7aDFK3+SJih5bXLzQePb47invY03vAw/5tpltg3e7vzym7DgubSxcT0DwF9T9Wgb+3CYMt6SRLuNqARzuY+WfCrtbGxKA+YmIsX7G7J9B/Vs/bCBuoymQqqTvDd8WgCbxjEGl0isJamlbVNENOVCUdJ3HNVdYaXTeApyR8QxknHrYbq2WTaxcFrfwXnVVl6mCXHgMyWfeuktjBqFQ9MJDSDwDlDDDLMaNJuJ6JV3RU9OSfzJ33v+RsH2/AYMxvc3YfLjE10CLyfeptoXBmMHI1i+G6BlAxY/S90t8G/BkU0YcVhlMBsBUcGM+y0lqYAfXAMJGacIMwnUsg8Ua/UzvxY03hdI0/jeb0QYDxDq28g1R6urINa+mt2u73ROZzZd+pkooe1v8SVz1F+tZs0+pBHzQy+vem8Sri7/UY55kdXJlfQFjO8+gecb2DqDzhLPpHEXLNDpoM51hmibZ3wtQeFZPN7IeattIDiHQvAW2hG3ZYuYi39TwMdpTYc9bYkhbT+bGPuJtqq0t2td+BNjhBsAzfVZwhUmV6JYm+JbANzBeww8FGZj1udkXT5C1VHQ1t+7Qo1K37ti15rYPKGbAVtcIw+KTz3VeAQXPIHHQRRUfuQKuZdT6Uqlq/7rMOB45kNpJEIcCpzm50peJJKwFgbHZbJAgh442bxl3l+arSBTJF//4DTd/XuIujA7AmLTVrxjq5tz3/CtivGDgM8n7T2QHBsjRMHw+97IDrq0tfgi8/kXoZbkRl2pNidW7G2r5NpJkC854SyuFgK9gPGdCJsnDD2jaWgz400ZdkQiTHnzRuV09yFGDQsJBXquRzhlSowjby43vC1tZLZmHrQ+t/PWBjvytI6InDI85v8Xh/qQgP8H3hJMC/QQn+A5QNwQKqpZgWcW7dlTYdk/dMycJ6wUbAW9xkaA0C1cCIpK7JijfWfewKUXnaCA5iV2JhkETuP6nRFVlKJxD4UVLnKyM9dTKNG3Hyu/CwnDUrtUX698esz33JKS1caRE93iaTlr0+ilnr0ZjRk2KfbBm6e2kZVvPpybqKFzsKiuw680Td1TVvr9vvQ//7rCUPcH4IOgz4f4F7U52IPTZVsHCKB0zorzb1zo3a5vbrwZ1quIP2DF+4vAs4Kv6XJNyYWBS5itwOTUOtOUByTcRgVPaab3minsvyMqj0Lq+DdWxdYNf7Z66fjxOzVf7uDJrEVP2Od33vjYQS+W5lz/O4zszgfcsrO42lSl2BU0jtDTr0yQn5nMiZHPXHjJidoaOC7vxkiI14mZH871hoDCxOaZ3TX2ZReA1cxAYBi10MOwM3wdhKHFVgKeQpsH2leuPe4oJ9ygGu4MPQFib5HlSaF99HqZrS4+0OS6AgOZj+Br4PkCD67pQwjMT2oTUfSMP/t1di58FdinSF8/1DEUURI2U59KldsAFiFbk8irZNHXrcECtxhNSzp43CCln5CwxZFNKSFm/yuIelXJCThlZLc/rdmH1iXtrmON1r0FLnTV0LAPIrJYvWZXYBSgFiQpmEtVGIbH6ln1L3pvb4aKHY+dZDg+UJDF8eU4gYrFcU0F4SkktMZP2p1mjs+I6oeQ5aG+r0JTcojYKeQmtAry34B4JsKLyXLZe5RvQ7RxB0mg4ra4my7/PO7w7FNxlcKTMucEjphjlehOqyf7Vog01t44P6rdny5sdf/XfdLXu3kacc+x9rEzc0LuKPQms0Sn6dk1htw/6QdlTgxkYHnIYfR+V4dHLQB0R9mdAPGSjMcl5vQwKVW8ePgLUeRhw2OONqi1UpSNIPGn0yrK+vFLT92uZqjI89uvdVgLdYMp1PyBVnSVOKIpH5PAQYy7Atsx68JVBWeiiUlRtqjF3p2nC5uwc8xfGlmecvZA9YfvxKxjAjbZi09CDzoukSXDqfDeru2h5Xy1ikx453LrCiCFKPwaQylz3KwvxwTDX7YSNhqWeSSy0W37dZto3zO9TfUQAyuWMDb3CS74SN8ZsClrpvC0XURZxCQrJMLEj/0WxxG5EFydN7Y78kRO4qIG/9VtbU99AONc+ewaJU90XdQaJoQ2IpTnr/gSYc3VxE15xaddP8b7ByQtiM8rmYpewb/hNm+P3CW5YYp95aVXNXDeZiAQWBHv9fi6m5BVl+ly2wDyBWeJ9Q73jiPcryKHdQiCSQ67VNpzc00ZiICegEMsBPKNi2Od5nAdrfWopzhc97Qr0q0o1+NcMj4Fu9+ltxubyFWZ81m8F3jR0iVmbO3e2CaUWH1Fs4Aps+RNV/qx5WZ9OILCq4OVwICMxMOkXMxFuwdjUmtq8I7yEB15rFeShzrocjNrJtk3VZcJ1PzL8whBreHlbMAEof7wHg3GHDyAknP/+BgBhs3mHzf8ifP3XHwAIt+8vcfbuLV7/n3/i3//1/5CD+3IC2jUPG1/GK/YDB6JEl4MDH8lowHbU/Vq+N89Fudngep8FSvsCTlvXt1LHlKjm2RoGQUdR1kpSpt32E1urX7URF4UFl9QvvT5ed65sLDFAxCYqByWnV60RRhMTDD+yPic9EKFzLvTXiEaMhyY7TBJ6dQmHkAVPRbUdCg1lGeiiUZtoce34lEaJVu69zB/d+hP83eCkQD/BCb4X0ONtcFUMwrqPKwHDLASyGps47f9IBbfKpmWmC96piak0SjnK56HpH6exD83Fye1DYR+JROM01cqxf/9XJCgWYhf9Hb//EfBI8q+fAnav9gAU5zt3FlXLPA4V5q3Rz4vfXniyUyke0gZrgV3lj1PsagEPK1/lJw+AJsZWl9lTzf59GLmHX20NmBKpt4Q0q3RT3OVJrH5ySkhVaBYmn8kKLQ/qxqhqDM22gCqnSfE79qRcF5YXUt1UwqxA7E0UeJmAY3n0bqxv6uZSKHcpPzS8699UV+yL8h4LWjb8+2P6lf23vtt3vxQZHH7/fWFNiNPDSHG5T3nuhwX9+X1dwGsGYqlD7lVELNUl/njKGUQkd3e06gAAIABJREFUinNKYqGu1uZihZ5AlIEsCnYybxPmtcEUudop7SiaIr9/alcqSDUUwexhlkqBKYnFdfGMkjNSKWqVyMiFwSkhcQGXVOOXpsQAkirKJS8OOKPuwd5FSIkwz4etmrreQ3Kx5nS3pWsK82F+eyzQf2YYCkGxG/+MvllNtyCGHoJjHnIPLDX9f30wXHTQtBwgxiEte2T3PVWvFxJ5ACBkxtNaortXuvvmMLpvyB+jiQAI1hSYi3jUICLklERhTn6YkHAGxp3KQwjzVg8ugZAguN6Am7KFeqqHfzRNguTthzBIn6PWTJzMe1sYquSjjm7CWPjPYNwqfXjB7Z5Z8Uv00W+0GgMTXuICV7juxiNBvSDYrGXoHmSd29arU21gOEbOTA3WwoBeiyyXVr9SrTUDVjraHkg5JeQT3hwk9Th6jR3M/HrufduNH27KZh9/OSgXiAobltpI9x9QZsbt7R2micFZ9v5pkkPgGcGDlc5XCVUDoY9IaASaSw2BYx5/koY9YC2Y7SQwGNww8tYCvz/3FaJv5f2YUvbZYblkABkv6xqw9VTC+4J2nAsIE0wZ3nmI6Mpt1f+utDcl+gyfY5ZXtCjPsIOZhnFiGdGMx8sxlXxMF9vvfdSuFoLglRL6gRGDqtihgIJpvkTOb3H9r/fIb73/ZxRs319i/ufvePXuLb69vwQHtbmN0kvuayN/r5jxiYAvgY70mrfP7Dr4Im1ae9xe1s4L8RrS59DWwI9rtWNoKZ4x4SvgBg87NqYl3gqLsE55zcQWcV231pl2IFULJU82bu0JHhP+fpTrCX40nBToJzjBj4K4aw+58BZ2MaemRI9MhVFgsYgHAQdRfHGCB1CGElGwz6gxz0O6RSUGbab4fLArjtqx2raBwGMvPJaA4V47+QFCrtXnD694k8MeovMx4NDsx8zYcb1zv3Lul/KJu+0guM/02yck3m8tM/iKgmu4rpy17KhZuBT+YjmNNM1RReMib5n39yWwu0VEiscfuLBaVnIkvNn/5UFwYDUPQOv3yfYwuO+A+oSRcan8sjPPDAaxKNhyTsg5YzNNInSdbcP1XY6ru0oWt54EdZ082OKpvajyAkJYM55vFRpo9aLAzJj4NrSu48i4kuTCR0DeL1K4oMBEJOwUSLRKj1/V57YmyZ56lhzfd33yM+BNYB/NdOzeSyvXh2QzJoSaqbJi+b0LxzTu2Ltnxy6nnQrzJPg4BAAIluJUZU86TXwNJLlpUKdJkiXzqtxOIGQOQuHkcctTzhrOQ36RM6ackdIkSvSkMc9zAmUCaTrKomg3C69+97Ebm++pWQf9eMusJwZQVGBZxBKQWL2SlCIyt6Iu2dU6nVNCLgUFCUgFM6vyXN0Ui2tPQs5koX3dIwuTn6uEVEMsNWsXNmPVCst78S6H50uiurEyB6pl6ChNzSdYoltXUafAXdAHvQLe5kHwMnM/aPfoOr4df8YxaY/IRtmtEDirdNQqo/TY0NNSu95HOBo7HPF8scqeBEYsYdZny1m7kkGXzy6ujYDGhXiXzZPTpYWArHO3aGGJ/XpXnVahm8Cy9pbYos/Ini/CJY32o3C33W5BAGa1IN9sJv3O46rflYTCt7onap0qfhGl1MyO/Lhwdau+/SQummdEhRVwZ2s80GIAkLQ+bmXXRgjmecZMqHoU2SOk34jbfY1rDhIvnAm4U/fFF4pwbrWgi9LuMIxv2OA18m9qEf++IL1LuHt/h4mf4xldoQC4pViOu4yPfNhy76qjs2demIeVBZUXG1ifc7CK3ehjwiutz2f/gKXem5A1Q/o8rlOi1uV3U+RavR/KM/R5NFNkuXfx6oUhBut9pbGNiGbDS+Jy/foO2JSCMk3YMAAiccWfknYvV36EdCFQSnLAkC2MkBzEEw88Wa2iZ/WiUJT2YLXoLt2BtzDGBNzo/YU+Ldx6N3wGwgzGbUeIfANXK/QZX8CXLxv8G7s5wd21b/ACReOlG87OAO7gs86Uz/ZedJ52vKcFd3IenLrrfNrYmBBh+v0trv68RNIcZpgVOzVzsZv5vj/ow0ItL0TK11m+Fp191t9J67Gt9ZO/b5dAxiUmAPMlcI2C3//zf+PL//0XChhX//MnNm+lfltIfHSAajm2pjNYY8V7vV+zWKE3PIa914vAZYABTOpRxMLbpeCRqbYVCAdN271e3NN76Bv/brxQ53jAHcBcQxAJRX6dlLdwgbQsjYCTQ3OqZXsmHU/uR9JTNyPFqK7b7bALA+AQpmwVrI+4zfnpKaCnh1300GPDeJROcIKnh5MC/QQn+F7ARsw9KIsBMzDY7B97BzngeP6YRD0OIlMKve70TwflYfCjN9K4mT8VEfFXILiOBVff/B1b/1Swe7Uct5ZcNLNEHbz4V6AXR66VuF/kuMvKzWKrh8Sraf/K8PdsdYAF58WtEIoBUktPgrpvzxnTNEnSMleljcc9ZJNBAYlBcwbl0gghTGBSrcWNoa+ojADW3dTy1/8KF4lXuGC2jQV3W5BRE2Nqv+6wqH7UWLOGl0089JAXBeFQrFcrKlmqSU4Y/BhoxQN7XaWvwL61vxbL/ND7xTsTeAUCNu7hBAJpzFWf297WGIM4VYvz5HOOCFljq2ao0Dgo0TdZFOZVgT5NSFNQoCdXoJtr90Sej8/Zrt2geiCgruPFjOaq4EXRVVoIXDKIZ5RCLiE2YVxhIBF4VqFfKaCSxNqc1dVotUIXCyMyxbrSzMRihVb3wn5xdttovy0iJGt26UH88GOty/u0+779FS3XT/B94D4C07347x55/uxgvLWh4DUl+v3z38//H1NcL+uwe1PUiOJkAighn2VMpWBbNmoZflvpJsCU19JmUaqdoeBGKbBnSl19bZTnuyBal/cqIeuBxOKSPbMLWmMbLL2FxavPmj1yd58UAFv6hIzf9L4A731vTUwoC0vOcd5ON9LqsxVqoxn3URrJQdOxuNQ3WVgOKc6YRSmrmWxYLNGrq+augAKEUCPi7t1jqbflQ9NWIvwxoLK5KxkaT0DWQuMXbPzVIwGjehOwnmZA3Ebr3XZmlLmAp1IPrHAiMCckznI4j4vv50YDgYFkNIrSWkk99KQENr/iqYA0HnpKBRKdkUC05OGNNouyLTnzQa7Ah7g6LyuzRuLamxv+L43ivZ/jtmbE79crbPGxdn/jCl6/MeW5GfYQEIx7UL9YU1w6n/YK+W0GFznsYW2Z0GK6JrRlV3dTCnupo/Ahku+s+MLqcqu1SSE/a4u1R48S4Y//+z949e43zO8/yrrKb5Hxvlrq95IW+8v6xPjSGRYHXdKaQn33nvjwHZMXZuIH5KkHUOut/hu54AUO7YppSgnvGpzGUKt485alRy/qaVVZW0wQun3BQ++HEx98ghP8WnBSoJ/gBN8BYky9IVnA3fUa3cDdZZcuWno+mryJw/nNanneZj5z34AW9hEHQVa/TN/TVQfkF9P9aEHIUxJGx+b9sxBpx4zf6Mna9/dt38/SL/eHyKIdlrJfFz3aqfdrC6gRuHNgWTynxqq3ybvFI64sSU1unmcodMQWkVUICzfca8Cm1Hgk+NF4RuD71WLXTHvs9bkKo/3i2O+rsLIVBIrVdRAmEtz9IYCCWU7clyKujYsLmigVMCdQYqj9h+9FZJlZQQSmNhamCd6KWoOwKs4LF7HuNN+kKpB0oZtslimsu5GgtHchCqC1/gySyogvTJgHSqFctJbPg2f1tH346+v0a8IDa/6Az2NM6Gg9Hp+ngQSnxxBryvBDXLFX6KSfFMa71ovFDbg8bw9bZKJab3EV7nNalOXmol3jn6sgOAHVwgqUsEmiIJ9I3LAjT5jyJApz9SCRpwk5T6A8IU2mJFfBmMZGp+zW7OYW3ptXEUZtB7VvwrUKunW9SlzSgjQnUQLNlg9AWzgkADyDicFFBN6iRK85giwGY5I0S1+RVrMowh3tDyIkB1AV7jXWI1l1TEluynOuc2AU1snGeZ8lejM/yBUssY8BNAr6GHe9z/fRYY3v4PYJL1JRn/AvAmt9vMAqT12RtpQju7m3OC8YK0DuXZ8efvA0MLftppxhCLpIPHbpvm80J02wXayP3qHvON+lUmO8lntK3/DJ7Z2oss42QD57Br4Vi9mzizPcXn8DzRdC36c7JJypooXBdAcAmLffkHABphvMfAWGWLH2td45bNze8ODuLKBdu+yVahkvwfgyVPZYMefcO6OO3BJwd3mHQle4I8ard2+x/dO+fQ7iq4rIk1pJFo2rXi05K8btaIFwtb7ye/tex31Lbs1xPLM4mkl4VWnZQty4pb8BcAZq+i6Ha4YcArEzAmcgbAi4wyAGciWZud4fD6PFsrK3RqW/rrsz7YEbMM4A3BCFuMruQtw4BtlpbROUsANG4yMRaLuVEC+piHLdeFpmpCRes1LOSEmiYVtBlbZJGoaKACpq+UwF8yw8DFXkQI0M7sxWeai7jDULraRK9AKh7UadfQ3GhbZtq7PkOXy+nP/Hb/j67w+NcnqLzwCAjNfI7yYgEb7+8Sey2lZ7baX87QpW1yOHivcZV/rlG+1tW5/X+ITNJWGm9qDLppbgsa9nLD0hfALw1vq9ToZAjZGtYz10wFLWuZXFgpeS/l2AcBN4uq32uaW/fv8BGxCmd69x98clzv/xFunPD7iBxDN/w+16nMN8Nt8QVr+XWslCLtHpRzIpzT6zzEs7Wl09GKQRVvEeEGW2HmDVN8YHEFVxc1Nek0vris1lP4bvap7xvSq4yZ87d66eovqWWjobP0agRw3fm+Jc6PU45j0O7GGtl05wghP8vHBSoJ/gBD8hUPdre/lCYBAs3zgS7PVf4xruuTlHK5FVttiqxDvfn+AEDwV3lXoiNh8Cu1bpoavYPb4q/gEqy1/fD/Nfvoi2s48BI+X4SMBu6R6qSP8ZsN7PUIdfFUwh1yhs0DPrPqeZzRpcFNo8y7WticTiIpRyQeIs4jDLm4BMSYQDZGUDwoBTXVPMBYVZhBOzlDPrvbkCjXu9tMPWJbmgsDYgNni/sH99TVAtCzxeV70CtangCe4JQQSz0o27lIiH4IdjlZB9/PK1eOZVCQ6f75Yqukhf0L3huQkR7drKSxAFdzaLK/3L0wTSkAtZFegpZ0ybCXnaIKWMNImb9imRSvNVqGzxz82FezOfffHU4wCkvwDALuhjPfBiQnLBEapkKkWF5Wphl3PNi1hCR4AZRLMcxtHMvY+D8LM5NLZ7T1tYjHfC3YpEehniihV4m4wW79qsj7Q8d13KQelP8PeAh+4iUeU1ymukLDgm719hlzOcNLKeTBDleq8gt4N5Jdz3VuzWb/ftvx5G/ZkATLgQy1sCtjyDaIub6xsAbrGZcYE7XCPTBhMm3LE4exbl3nV1/Xyf8dr1jeUZXRKvpS/4UtPuynPXMaiMjMSvwfwJn99f4gwvkcUXCzKAcwauyWrtuN2swJc1X2/TGqzuD0aTWuksuW3gz2faYsZVdQleKxfSWB9YTgTghuSQgtMSXBt0AWtzKL/uk/dco7356spe1PRDUJpWy3HidiwJqHEeyOLUs7ZTDygor5G4YMszUkmYS5aDeKWgbGfMs3rF4iJha/TAIOUJyAmgtgcTaQz1AsyJkFV5nhKLZ5x6sNHbcw7UmsnYtrt/AaoS3fSI5yC1pm4hKtEjnP3Hb9huRb17C1FUnL17jdv3n8AA8juxW7/7Y4sJr8D4UuOlA67otv7t6ZDW7bqXP8PXofX/Vu9nazPM8btziLk+b9fTMwAfAfUPMQaGW5ZLXqZU93ASHNKdQ1y6W51KSG+HgMr7T5jevsb2zxmbf/yG8uclXq/KY+RfG9MvJDHSGRIL/eWOuu+CiPOEJTW+seer2ZXmsDWyi/9cB+4uPE/HdbWkOjEi18HL7ynWkVENyjTTqExHgoRCTx3hGjtleXmCE5zgF4STAv0EJ/hRMKAPesFh/wyAuzgfEOnVMu1ROFeu1Blz6+6oJqkMyoEFPrbsq8vvZyZK+vFcVW48JP+V/vhZ+uXQegxUMju/v2/7fpZ+eRBULmW3iGNN+HIsLAUuvHxX5Rj9u6XST2AgYjLhDqnMYoEIu99Qm54pjUK9Re134C5euR7dfx8YlfrrKBTWavqj1i+RKfRUcQWNgWaWGQZBYT5vxVR0W4oItWb7tTiCYoGZqICQxG2o5m1zmolBVKqAKoFQiHwZFFGAzSz5l6IKerAo3oNyvBdYt/FW3eKnLkr3Udf1H1cXr+vuawwPmzCko1koppEH0cXiaBGueBg9DH5VBH7Pei888XTK6/56X9eOvjnIIt2ljMO2LCzfzdJNleWmNM90AYoeGkhc7yYiXSOqiCB5lsOsz4lknemvuSzNOQPTBGgs9Cln5GmDnBNomjBNE/JZVgutDGS1MFelOZLkJVZa7nGi7RT7MbyR6tj47CdABd1m1Z3UrGZG8bYBYEwAFYlRPgMJBZiBVEpdZKy4yYS75v5V+tWUAm6B1gowTclvFuSiNqvfUQKIxRKKxTWs1DeyFq6cMIGh7bW9dbilJxLbqnpIIHYhUUAzrPioRSiOT6UiBbst0XtB+ZPBHhwW+/1+mT82YnviHnmsg1F7sll9ndZejHOweWWxwSeSffOO2nQmBx/1XuSHe759RN0ePAJPuKeZQam1K+sCHhXJkPcz+XVPcpuuwJTwc93/W0XEsW2yNT3yoAIAz/AK5+/O8fX9V2w/z5r/JGE8AFy8fYbPH9+jbAVPlmCLaiQISUFHjU3ELwTnMWYwtiBMuuLvNN2Zza9ahu0Obr8K2B7g0pULF72ACbhlxsbwI5bdaSgw44UcvlKL3IyMhDcg3gL0tamF4d9KN8IPhI3a7KXXUqvSrfZKsD5usGCgC8GiPD/DS8z4jDt8wjfbVyqNqv2nn53FfmdqDm3cwsfvAna4Qp5dsLh0b/aFBxzAItDi+4VMrDnM1iTENRjnkLG8BnABxi3IeQIE71E6MLbfR75WWQCUon1LjLnMmMsMnhkF5rGKq2V0oo2GeUFV5AM6D8jMY/RwHvVjLYpz7wfzFMeaVtertYVZ433LYN6uEPkXkAMeW8iY3QE4x0vc/vsDCoCX/98/cHt9g69/fsLN+08VzW/ff9DyXgEgFLB6dnCr/fir3Q/qRot0Bb6sfSvptzBvAb4mogX6rN9C658gSvQE4ApcLdEnzSfyZ6n7tX4DWrw6YJUwazvPQLhTuoohSvV4fwcGX34UpfqfwPnvb3EOIKWEr//6EzeDsSAAn4nxgsVl+xude1ehEqNRjNM8ouvKSyPwECk197HsmL/h56TpS2mPeFE9CGJzuM2L7XS64qKcDM9GmpFE2U1GS8bWKT1aFeTdeja6u9vmuACsg1DnGkFDkQaPYVq9ZtRrJyxDJpzgBCf4+eCkQD/BCX5REAZQrpkRdvFAMi6YmXuUsQ9+8Gb/hPKGB0MvWOmf9c8PacuuNITD8/k1QFqSD5eQnWAHfI+l2pfh2Gh36ZF5MkPcapC7733H5DGLa23VkNbvojlEL5BYqw+vXD817CrnxF89Hph7aJsnwv+KAg/wKVPmgpm2uIMKT+cZZZ4xlwKeZ1Gk6yxPVESpxwUpmyIwuKKkpEo7wdbVTbQib1b/fTMH5flcUFjWUemwvMv9SSzTdXGIG3oTHCJcrGgFgFUBI6lQIPL7yz2Nhs97wUjMc1iFLv1pvkdY9ggtTjLo74Edd1/L85H1+ZpHgurunNqKimW5rLqCMyS6A3CGpKJx6uZUVpyeVMGdUwJRcnelOYsyPYuCfDNNyDmDJrHGmtQiPatLdzGTEmtzEKn79qSHBJbtId10Uq1daBMhuIAkFaTNgk9ss7GDNcQAJ6ihF9JsqmagFAIlETgSMxLJ2pe4765Gt0LNO4Z7VAEaxQX77utK84ElOnuCOstMkB/mWO9SfRQDXe49AupI8V2/WZmntIIIal44bIrHETzhkhMYmJLC3Gr3QJA5eIib80PK+Znmnq2taIE+WidTtzzX+NUcPwJhS8cfHzEl1J0p5Fioptj/CcD026RKwAJRF7cehEDA69/+gas/vwAACr41Cp1jR8L6oKdregpsS+revuJJL22N7/d7U2K6G+lbEmUeIIc7zrp6tHWSr6hSh5Kb/Pu1LcwUOIyhoeQYTAW5m76LM33UyxsAE16EWgXOkAOvhqq5ar7fRat8gyjRrf9I76vCkENp91mMZP06hn2Hsd16W69ZFKy3mjlTwEVMjYcABgV+th6hq7K/wuY6Ww70IpG4fFf+ZFI32RYCyumE2jT5peXcBKQPz0Pr7VM/dCGK4zm00Sykd/WJQYEr6WuYg1Kw2UzVKpsQ53xrG23PIz6Ph2bsPtbf29BakH/VvzdocaOtq3jYReK4c1XePwfhtptcjewitNHmaWzzgkfqfg0muCX6HRjnbwlfLt11vijaA92cMrbbLc7eAeW9H/KJ+b5kUZ5bu15oZb90hTd72RNsbGvZ7S9qnKLOnUp/Uveyx6p2KTho6XgiWKTr585eVwLb6dWQbR3P0aZwYCtPcIIT/Hg4KdBPcIIfAM1Wzc6or2tyOi52LV3k2Pq0R3CzLrgyTrA0WRTb48uOrb6lIdr8D6/Kw+Ee7X8MOKa4tbQ9Ib1GTB/y/mlhrUTe+XY9F2Okx18+tH3fv3++D0SxhUdhRfM7/E5p/sgYtnmuPOsvyGrQM5DLWpj9AtCOR88oj+pjz6OLREeqrQtbAuoJe3kQ+kU1D4/PrjxOjofO01+d3Tq2/o+2fgfWtmyPa9BAmatzmSVmsTwAz1vMptzWOOgFtoZMwZPqajRrToa4mkwEmPYsU5K4bbZfasKZNd/Z53SoVrc+3OKjXWcQ15WVPlgKJWPa9sLLadJZ+RwFb76We5fXzfe86PZV6MmY73WM6sn2h0fKeGE5Tt3znubpx/MIy/O1+2G9sJwPUahsY0hQ63NThlfLlALQhVqfn1e8nk1FQltJTwDZIRRK4o49afzylJFTltjnOYNSror1PCVMk8RJT1PuFOiSF5JcF3KrcpALTxF/Q9/FWZ70mzIzmET8K/pyApcEohnghJRmYEt1Pc0gdRkv9HamAhBDvbkja7zzpFZjBW7Rz93CqgJ3qydL3PRSijrYkBiVZq1j04iZa2xMExEuppXGQq9HglaswqmLhR6noyvBY53bK4uhGS1SzfKdiIBymCX6Gmv11PBYeOThdV9g8AfnOMz2ieDximnbbfjKFD0b1msK3hUgilxg6a7cMMEhFOTPQqMx/ECACf5jXGlLA7R0tt1HoJCmdM8njds9B7faPT0/MTV7uuFBszgm9RWQWRTIttbvPtxhep0x41rH5zkIhO12CwJVxXlb33NAI2NH18cjiHyoWdhLPeSLqtBnxk0kp5hFMaX35rbaFN9mt+tliM3rXHqMJXMtwZWuzfuAkMVRYEFCwtk/JoCAuz+2MEV8QYFEl76qpYqnERmNqGgfrbO1MW+JUOflYkz0mC7Gav6qMd/XhDOmWAa4Kpc3mozBuB0xh3p/rX2WA/Udcq4E9n2sPBsPKz2Pu2J53npZEazyTfN6pk04g4z1NaP1eMFLGl925RgsrSaVecHJiHDxpKU0VimySkspwldY+CnjK4wXHvQLAYuDFjaLv0GOsZyB1PtBDMuzGzPegHEDUTqbC3aGrN0tgKv/uQQz48U/34IZ+PavSwCGa75gevsbyqUdopExyVqvqPiufBfMktznJut9pE1f6Ldzncvy/Arilv2sm6/bmpPER/e2dHIMpdPsQICdWySgfmM5p+77RtahkOs6I2wvgVfv3uDr+4+13UXTXP/xAa//z//C9b/+RAHh2bs3wPsPYqkOUZAzgNcMvGJRopvS/PVg3GxMi3oyyEnjyXeylJyStmH3Dr48eKK92a0pY79T01OWzOlRWaZODzc0Y33va7M9cNrVhLnGVF+tM/l42oFQrgfZJYFnEWnetj5a6+9FVp3gBCd4AJwU6Cc4wQ+Euo1ye4/uObpft9wyRVFgsTjEkOF7bMfsTJDlN0oTq7ULej7ne8OPLv8E9wFj9E+k5HEwjia+a/4bwx7/Dv12X8o19nmkYH+cGOjOcPXWcKtffAd/WSf887iwJuw7Ko/ItDqv7XPFtGDQ+VQYW96Ci6itRADFC0GUxDgUC1ZitRwFUEoQ5KQiuE0FXQWpKkKDbFbyKhLTkLl1g9y7O3YplwtFrUA27h6ocSBXO4WX2dov1f/6zxqRavM1rd4dD39n4YLjsA6vPaBD1vDiLuV5nacD6/PVvMJhphZM9Gl0GnVzjFXoSfrvORLu1GMDAFWiiyt3tzqfpklct9c/jX+eJ+RJ3qcpg7J8R6o4Z20XJ0IOCmoQ1NtJi3lMTi1rkZpnIBPWFqdBWRQmlEg8S+jw5QIwESaaUQqBi8YeLTMYLG7dE0NiodsfIyWJqS7OVlRkHfraXFOOl7zGVw0EclRnEMxVaaen6CzN9z0fqH8Wlud7Y6HvKvO0u57gkaCfSYU87veh3/xo6HWK/bMeRli73/93bTEc0vRKq3V6gBvlOYdvt8TIEL8dZ8EiecOiuBYLV+4a5SWJtfkFxGE2II6i5f5QcDzIKARkpnrI4DCQ+pxpRreq0NkEhVnQp0ho6uJl1wOKaH/XQOKov4qaOhiXNatCclm9nger1G5T6iE01wg/98/OIfz8tj6JtKyDHZ64DXToGQ0OT+6Y1AyIdW6/AAIdfB/ow5TE58tny0rFR9IfOlKmeKyHu9sxIHtX/2SOFHX7TgyNt5LUTTshJaNv5EBhAcDqMauwHAjmovxKUKKPeGc7DLFgN0xhCY3dTVT5C1Fxjg4xLMH4ogkA4SUYjBlXTV+OlIzlcg69tMRBthyaQzohfbwWT0hc1bCiAKfmO0CO4Ewh/9gnDFRX6n0Mc6+n9yd37/q8qPu151uli+/C03MQbt9/bNIXbVMG4f1//Q9QFhmWAAAgAElEQVTOIUeSbt9/wAzxBnEHUZx/JOATEd4w4w0DH7QyBa1legSvl1vwj6CnIfeB8duUD9l5vBQ7GJG6N/GTHrfurqlxJQfUF8Z+myzAC6qhKeB8e3NY354DAJ1cuJ/gBL8CnBToJzjBjwDufgOsbtb1NF5IN9B6RSZISAwOT/bVixf3kSitr6tMdEw0UZ++f7dSmX2Eyppwfx8cS8A9FfT1jUTzMW1ZPPthjdtd66XDr8NyWcv10D46tJy/KvDi3wF0naGsNEZret+9S+B7xBaF5/GamucUGLDKsEcGg0La8L4gMiAtOoytj3IlCm2PJ6YXbVIc16BXYpgVgfeXl//YsDZ2PwMu+1HQCxPs2bF51F+bA0VzVGWgKcuoThiZDPPsboldaR7md1BqVmGGWnaYsErEGhJfGSTiIrGwpaaBnr6RizZSlaU8L7iWs0fGv3N4YNmQfwe4u/m2r8KZeQprjmIKeeDpYh4LZHMQmIV7tH6p/fBD4cdUII71WvxzebDyvMmLhml2Wpp3kqm4jhq6bFGfQVkqRIr1yJRgcdI9b9JifSZmOkeiGWZ9TklcsFNOSNlcuxOmnNRVe0LOhCkRNhobPSezXD8DUgLTFkwkBlyUVJlujUtNW2Ntkl2TP6ckV9tc1FpbVmXiDE4S0zGrO3aihDLPmFBQ1KoapYCoYJ6LCo8TUiGAZt95WBTqEgc1IaWCUpLEUS+iWI8WOUXXXNJ9ddZ8iYsvR1L8x6xhJFr6LSWquEzyNUt0NOmi5Y/h0EbJEHCYHBRYuoCP2TF5I0wAaRY+hHH8dR+r77BfPnFB/Yp8eDFra/xQxPw4pfalfU+sGmkICn+tS3M9VMMj6/OYy88J+2q31TblKFNA61Y4/lb0X+nntpyII81icupiVgPAhgmJn2OmryF2uubEarUONLGTz1gOGt0RcI0rXH1iPKNnIBBmXKHgAqxKclZLc6n3N1VovcAGCTNmFHUe3lM55inD7uscMQtIoxUVr5nl6jkTbhom3OoveV0o0bI4YKAPUnmBhIQtPst7M00NuRFQXa5TabmbCa+R3yZs/xDfIdM7GcG791sUYlz35NfCYjzW2uVGxxx43BmiQ2Em4G5FJsTdvZXcKJphPgSWvG04jyXuxknmNUHcuF9HeVUnRzq8jV5qrXNrxupj27+HuZIXy/PExt+qRx2In4AZVK3uq8t0fX9j7WZG4YK5FI/rXALVX/dCnddg9ZbF1fp8rp6zjJvV3jFehbsRCXyCzZkM8dAww6WM8cBkxksU+owXTLiCeCAYHWP5BlEASyzxL5jevgZdvsSsngq+quV5dMNOAK7xRZ85VTZBuKsCYELCFnXU4TPEZ7y1IwM4e/cbbt9fYguPed7aOot1eoFYo78EqrIcNcd2DhDEQv0GGrELwHOjxbq8re+cHpM5HPcjABrz3a3mbyGK+42mi55E7jR9ApDV8vz5//4P/PHf/6qlfwqeAxnAu//8J55f3+L/Xnq/v2Fpx+dQX98HCgpYPKlB5w4JfWjpDlpvtobIaUaC0KzhdTUaG8VSb+hz44P0fq4rhPwD6yj4nKfUrnW0yXY3Qf+tc8DoXKs/tfit5Sf2l/FzUxwnOMHfB04K9BOc4AfA0cR7UJ5T/7xyDr612t5/1Ga7SLzja96bYgjGBO56v+sZraT5FSEKbdbeH5J2Xz6/Ipwinj8cjie0GUBZfLfvvn3jjOrSytzftM9dGKIGsB13IayIXS7fwwX25LXohUFR+ySMMdcWx/RN3Sjkw56vMdY9O/53g5+l3fcShkH3onogAjDlOatla1Qmm1CpWmNUaxHLkJw5jtYiNQ37gY1SqqJQpmYQuawJ97QuLqZT4FEfEEw02luct66OySU93RqhmKZpY6teXwoDsBBs9Hnugn7fA1wIcQIVtzywLw61PLdnhyjid6UlouGeLmtl8PyVuE/nz9HFrEV5vUACIdMFkGbJuyrERSlu1uf1OSVkOkemDVLaIOcJWV28s63T6u4U6s4dPt/jqRG087yq1qtgzPsg8QTGrEpwUSakwkhEKEkko2Rm6ImAQkjq1QLzjGlWFp0L5q0IUzmx/E3imSIlRs4J84xGiQ4UzDO8zkT10Ku1YbnnBTEeAcH78nBMj/HesnTvrvfluDyOs34/wQkc1rYR2vEOWFOe/1zwkNkfQ7KM8uzdB/e/I4gKgcRtH7IWxljGl6fwb+QVbkkU7xtm3BFjwy1OHpXvb58rZ1OwiAe+43srvZApolCtyGMbCcAZkyr8l3VypZrRmkvPPHf41ORodJuNTVXIcfxOIKvCPL0llEs1emCxPu+V57aXcvNkWev47FDya5cl+i0RzhAPW3kPn6GFW31tMZxjPc40r77+C+BWiXkOVaI/aKF0NLLS87FvTGk2fI7oet3muPxmPRCeoYrzcJCQ4fOgsBzkwMxg8V3lPVkZUo+PPhdGgijM53lGYQnjYn9VYWvzjJeuuA0kDrq1QOurdILxxGaJbsLKCaJwfw3CHYDncN75JpRyA7GUJgB3l5+QNcY5oz3Q01Mv/SEfBlSJHurTvY9AkDoCwPb9By3POfsEURo/07RftQ0vAHzR5xu4Ir23gN8HfftquJ2VtP299ck3JSNfdviBIZbwCcD2/ceKh377/R0+/XEJAqrF+VuTcZSCnBNeM/ApSZ6m7H/JbUx0w9c07Nl7gh5MX/ISo11olEJwrO1bwLjv1hCb8+Neki39feijZmf7BKFRogOOw+28fM/znijZE5zg54eTAv0EJ/iOMFQeBwE4hfvRjt/s9bsERjsEX4d8lEBVWSDWLvBKGpF1RAmRqGjuj/3+wPe/GgGyRhKutfvY598blvWILPAh6dbeP1Z9/t7QW3RWIQ37s/j+yNwRleL9G/ltLT36VM4CVbt0mOAnvh+5+HchFQPc5rBsW0C2HXJ2QZCLPNZQ8wm+IwTmE7j/2o4hSup4suixUnJvCFaYCcsWQrQqLPJYeVWROBLwMkN8dgZho35PIZ9abq1vuGAEy0+3kieTCrAnrFu3ftNK2iwZKaOvisrK7If2W9tC39X7VYV5Ky7dB7tEI2TdfoAQ477wZPvEodK0XVlQiKNH/mwtLYCwVvak25Gmea9J0p604aOmHs1zQh1Q1iiu06uscc0Fb6fXqjb/zDXuuVi1JBTcIiGL4FLXmx96kWeb9AyZNtjQhEwTpjQhUUaC/BJlqUImMJ2pFboIgIlILdt98KgbAMoyx31NxPVKwCTu1wFZW8wa75wZmQsSEWYq0t55Rkoaq1TXW8kJEydx0T5JRzIn/8u5sRYrhUAk1ucsDwb97yI6a1lS5frCdSy58DBmlLLirhj4WN5oshLGf8mM9NWx/Ou80t8mdnqXBxGp4J7VU4X07d9BkX4oKjm+J9Zyflif/ih+pZ3N7bMIMzFmErfiUaG78OTyE4JTp/eHqoTqGmqW6Xck1+E8zs6ZQuG3Kt+55TtmfBPlUfN8yQG3cgbGhOeYGCj4irl8q7GPgW91u5lDTgTg7JUclvp6+V6UTpV2VBqwU6/1so27UPE7EmV5hljeXjBwvbA+b9txUy08TQEv9zNBcdjn+q3VLYYOkDjsL2q+wvtU3yeY3xfkt3KAbMYWt++32NIXfEv9CjB7Wn8e+6nSr4u3bYuMDxvNOx9Kp68t/QTggghXIdRQVJ7fxoxYlMojuNCt5ybwALEu555FfZ/jk/vuEbE+vJIXY/wcqFbW3yCKV5CHBuCQv7kIr2R8+J4gnhgIjDueJQyMHVwIDU7qXcYO9DFziH3uSvS6XyoPUXl0Nc6JHmbOaq30wIamviAZu0+a7pUwT5hxJeuPXmh3fKlrM+KS2HV39f2XqqDYwpXM0j8vUbrQBAnAldb9OUiV2lxdycfY6LJ+EA4fRBmBuJ23cAMZwJuuvl8hXg0IYlFv88uUzGL9LjTsrO9egurRnaJpLbZ2LZ+5etUjqDMi8v4yNOMrX/psAuMlA1ckfwDwIpBnhoNvIWN5999/APA1UUB4zcDzf/yGnDO+/fcfoLcy394w4yO5Yr7fSyPGrAfMyUOSybOeH7EMHC8y84KvaLEPV4t2owu5q1M81N5iOYGs389KF1fL9oj8tC4NvxXy2Is5aqc4f26VIcX3aZCvpUsrh1ca6NDiX5/iPcEJfj44KdBPcILvAPsYeMJiT1x8G4mBfS67Ofx7EESrNKKdViGWd8+0nGA3fG8hzM8s9FmD3LDzJ3gKiFbVdt+8v1+u4e8XA+aB3f1SWf4Lt/CvCQysyNcOBhc8iUBJOFgVDuXcJ26FYlTZ4/qucYudXOQjSij/thexCr/dHvRYWPbWctq8TLlE4TpCI9BmLYfaQwOhJQvUW61p4UrCQ+EYbH7C+AfCD+6o+1ipL9J3v54PqrwpWmDRK3HPTlcyBwlAgrhxt3jo8i2Fwyualz5PqnzPlMXdu7llF3/rWoEJSCLiNbfhZJbpWmM/VOOCTqq1CvdEYE5yViYcUAExqBSgJBTiemAAIDDPogBX3JFzApeErILfVK3s459YCwnMKEXjo5ulOw5XKjuv4dT9coxapdZ9LNH3xctdrdwgCamw3tOcdugTjGGfEHzbMdauYG2//1ngqWe6ua8HRNkbXb1HWmXUPz2OzxCFUEyToRaUqvvreRH5XvDNpomZziA8R3UzTl9B1Ub0G1rc9bxaFJqd5ATG1jYaa2jTkrYVfbXutF+sDzZsinVz297mwN23eTGzBEpAY/WXgYxXABgZGeldwva9x35mAOltwnxZMP2eMb3LuH1/N+Rp+nat4vjuqe3Du9bBqOfiHJkYmOgNJILzx5ruFmaB3pYXywUGZ7UG9bA63IRnpuiscrNDFFRPCJWfJHE33p8xtDk6opFmFtqBEpBnDXVAriCvCklyGsTCUVk5+yzQF8r4Bfgx9ljP57+/wac/PkgZaBXeNtujJwuGKGijFXqBWKHH2OGWf8JLbFVpvvRvJ2mfgfANjK9gvADhXL8vTT6xXi1PzzUNYVYlur3vPShFV/T9eDHEXXiG4bh2pl6THLwZxeq2+lpdubu2POfuHSCu4b9phlcEPONlvVnzPwOweUsol6QW6oyUUs10eynfPoPwth+otW7v62xkGPfa6AMhp7SHBhzwHYgY7PhVXc/C1+r29e7zJQl5tMbrNMw2Om8h4XB6U8xyBuyKJ3+CE5zg54CTAv0EJ3hCqFvjgJ6gA7QxzriQbsCAxSiqv2A/LVrM8jIQwCrlWxUe6AlhI5q5FN++2YkMLVLKO6YTePUGa0RWZKWC4VMlTkaM+uj7H6LwaoimCAMha2ARaZh+/PUo3xHT+VCBzzo9u3vc9vX5Mt1SUPVQ5Vgs51cBWbv3/75VYnheHP9l7oQRXNf2iDH1L9fujYXh5Zh1Hxpr4CwCd0m5pmu0KfJwMbGjwK0KIljiw9lRbgKBZ0ZhzYAZc5kxb2eUMtcWD2sS3HvXviEr2N2WJWNvlWMaKpMeY0L/xHBs67j+c184YK2snmiXeWJ/sqdQfAlTqpt1a7uNBWFVZ5HepAllQS0mqzX3jvnQxPPt8rKKOHPu9Wj3bdaDcBrnsOh6M+EaQpvNcteseKvwTXqt/mq5431J7qx8x+jrAkG7SZq+329M2NB4yLB23mM5rQloDrao3jnh9uexVv7qXFhKV48CSt33R5RdD20APjD1xxXJoyZRWuZpc8CEukkDDTIYmcTyvKileXqTUL2oIwi6QMhEmFKW2Oe0Qcqzumkn/RPFcqbzagljluRTSkjZ45+L2ZAo0CkBnGSuFYLPMdKXAMJy0VvyG4R1Y3cp1zYQQxTjzOCUxNtDsb8tKAFlhsRhLwVICXmaQEwAF8xzgrlhZ8VNpDHgNblC0bjoGhsdDGRJz0W4iAJRsjOzWr2bXViqTRYrHbOMqpPC8fYIgdd+iZbo1OClmK72IeTwUQlBlSN+ag4MRcsmGkxt7f/+kJHh8N6FvOVPfV6V9CB/H2n7qvSnRT+063x98fUHB8SbydIZ6n1hEb5jtY7xbcsv9v3iYxKfhb3wvnU9AAev8Rd1XSwo03bCuUV5pENtvi5tImP6Ybl7axryGvSN0JOjnfG7c61DSF01rIam6M0c8DrEUpTgboVHYTsiLTDXdL5PmYcOoJ17ku4ZZFSu61MGMPGresd4rm6bCxjf6qFsZsbzd+9w/f4aW74CFP+NgEJ9YrtjG6KScBsOe50xcNcdxKgumlkUyRbjPZytanmZ2g9yn9WpdP6HHOqc3oXDnQzMlyKzuftjW1vgnkk44G3JsI/FbteRjrN38VlqvluuCiFvFwgDG+hYUsH52zNc/Bu41bV31iZtwKyfWfvjmiEH2gaJafB9fJcBvCBCIeBrsKo+BpjhXl0A7ELzo/xvNdkzOB0dPxOresaF7TmgOggEYFLaXNYJ44Kpep1iiGW0bcvqxL3S+0g6phb3fMBT1H01PlIaLdbzWlM81zlxC+Duj494qWN6RYxnDJxp9QU3m9W6e4jo8cNN15GvQNWym1V5PgPYqmV7398FwIV+Y/cRu2a8xB2utFxv5/nbd5gvZ3C1oZfnNwAyS+z2GdBjLILnogL9Gq7gnsK1rAddKwycsym43RqdEK27BaGaYn0Ga4x5b6XgVrecN/fsGcDbf/6OV3d/4vN76e0rEqX6UiHP2AI4S78B+IjpLZAugZt/XwLgenjgTlNvQPiN5ZvPBLzWcXa/GQLm+l/kyQVcUt1nG+h5Y/12yhNmddlUWEMZDaDuHx3+zibvgVjVG06YgaYOSXtv5iL9rTjF5NsAgYiFjo4FGj3AvFCiWzrrX2FaUCdCDGvQTE6jtVSrfgwNtYOC+1vDkiI/wQkeH04K9BOc4DvDfTY3qrtzEFQogVEV31UZwA3jV5n0aDEX8mhAlfL1KYefB+1IMWJwrEUL1JFaRIG5hhMpsX27+jMcBfiu0DOisZ69qjuqxWnxZZ/PoofC1/EOeCgJ8TQ9N84zdzX+OxOA9+13UkrcFcmASx8sGAOUuXC1MTeLeyD4Qztqu2p3iB7KDuv0TJWFinBrERESWLu6RdTmmVA1CAzGzCxub1UJOAPADJTCYBYFQ1F3dmtMiInjTNjgvQe3KqwKB7Ni7Hvrrw7UDMtxXwK9YOYpoJ8yJqifS6kMurucC4pBmUCYqxVHzHQ/o7sWq5fs94gDFXVWMevBO/LpFuZoXOtgAIVbxbrup9Je1Lp4v6gSUtsY61l3HlXyaHZDaOXHbP/799R+uysfa6cr0XnxwagvOdJKCPRRXwYRCi/j7Y3i7w2VxasK6HjT1mnft30D7SzRj4Q1q6SR9TAX70+j3+I8a+ZVvG+e+diLMpiQXhPyV4lpPlECpaTKd9br5IdAUnJlPTJSzkjThGmakKapumkHCJwYyEmUyUkFmaW0634xBoovwis7OMDQuZsAYl1vAJIKsaEHXUV5XoBZRJqJGYUTOAGUxCIoTQA4I6UZREDRWKbRQn/Kya22VGlCJBbs4qaVkJK6yi8JhIKURBfAjQCxiv8gLl+XioZdwql7Ca6oxxeodXgI9GtrpDiPac3RaC2XHGf5HO9rpePd47t711PXwAMaP9pR47jKffvcdpiU0vDwy97wDkZNruDYx4K9tVgp2oT68V5qrSr0Pbi18bgwSLzsn3X6oB+LmucD8PsxtMRafY6BkYUk4Ot/13YVrS7TIP0c9nqDcyaIhXlblsH0RvDXzcc7mAIlISHhlYQBMbzMjPO35+BLxgV/xfXeeT1+Wo0Zagpu7iIX3wAztjQWvJrSXPieFifOmJHQKs0t6+3ljKIcHeMKwAv9XW/FrnGK97217i6aLeZZ6R1IbxUSa+MznAEoyJADcuZKe+1wiXFcxqJaTOshvTdsqSh3L6yOBCQKob+OnPqFxf15hF1mDe09qlcARhfaANIHN7LZaEgAwrnOM4LQ5Cnlpp0x8ID1P3fPrPNoNrfXXaPJj7NXCDd+YKrAlaHOT1iZ/fz4RsCZ2nBLmrJQaBPE3X70GBBhhivbCaK4toMrQf9YoY95be7Tqaa/wgRTSC+plRm8OEa1BUDM2MAV2QSZU99Curji3oQ+MTfpdrTlgt1K3Ir3PYFrmwqArfJuKSQ31/AbEDJYrdG5Wrmn/BYbSKgKi1f+nLv1afn/+VHm0KVIXOZAA231eobMW1PSv2ENPYEleI/qoQtuVnCA8cJLBKQ84XZ7p3zsGGwOLtZiOIyWjHbn9p3wFXJduChtp+r2MB5z6fKlvgztzyXS13OjIYwRCR/A5LIvImkwG8KkmNkJ7gO9C/9j4O8Q+ukEjwsnBfoJTvBdgZsfg2opwBj+NkSrQt3fjbvolOc1b/3HRWGVShDrFr1GFBCxf1yzx1g4M2zQEA4Xr7mFj923DM8qnTHM/uffGEkZ5l1MGIX7hRBHiUI/OR9Zqkep4SPl0s3BAZP5OOX8/YDjCncJKfy/fjYEJbo+oSYXS7VrFvU5+pzbRY+uCbf35b98a2U5o+6NMVzowsyF8pwfQji3LGlt0d+ECTJWZSRQPj6fI8BlNzs/dsVve9+XHuOc7yu2ScGtWL3loEcl3QMbDwWLJPTCYJ9fYtUev7Yxzv1wWms967tJf0DLknf7sVeur+wQaqkdubHQ3Yy+7xrZHgD4ORhh6up23yVSp+SOJiXWOIncCifjLwONRdveciMtAVRJet/Xi0MHafCe23tTlBfcINMzPdvpyuz8JqF8KrKXUAExkF9nEKmV+WtCuhYX7BYHltRGz+f0prbc2pJeZwmaahM5AYXUawqRHsKywyW6XxCA3A8eiYI79LC5SdUbVE0Iiejb3raHUIrMd0pgKkDKmAuQUgEVQkkMpAmFZ1Q72QSkNKvCW5SdxAngAmIpiZkwz15XiRuphz+6wyt+2C7iQOUFyOx0WKzzw7pKTGqFKmXbgSLu8jWD8oWldc/uRLqel3isn7bmvWvo8jkcxEDd302s20JiUbqW4FPT9NdeZqh3FJ6yW6XHdb7b/e0ynwjMu9/vg324L+YaY9vG944maNlhg3z8ifTaQ5S5azCqJxDnj9a4ClCtBVTTcbg32JJY96LMw4NA9wfti5UW7C9lN+Jvnj6kv/e0d0vH3Wce0yG2ujzQhECCKb24SVfpCv2d6CUIwC2+DPO//vgp5KLf4BVu8Rn4BDx780bS6/508fYCzGfAhw//P3tvuibHzasJvmBk1qLSYsn26dNn5pn7v655+us5/dmWZC21ZhDzAwABLpFblcqylbBLGcHgvoAgQACYIWbVK2BUY9fOJ3talTqKZmiGCMg517QnQl6yHzbtheMyCzMt/zV7Tps/Nkjq61wicamfaeUmFeVV2rwcV+j22dXRuSW8X0F9r3StLZDB2OBP4P0LGD+LQLgH40zbcA4ReK9LqnpMLyBz7J5oXM+FpXAL0/quW3zw0jkCPfge6/jVfL2/1CxNIOwHWOmfO8uAxR2LOSmwurSiyQvycY5Nu1Y+QBn3TojudVxqJsPn1ItBR2cA57jCHb7ipX43YTfR1yLsFP/gYo79QQsXIXpd6jlEoHun80L6iCthu/mEv9U4cc2KGXczpS5fzOIFAWqlgoxFgOldAr8Xv+fRu/orrfMGwDle4Q6fsQK07lX3lYsaphVu68MuDbkQnXFLnnKj7Zg0TbQQMQF40HiivZ+x8mupYbwJ9w8S8+V//gJkxpd//4EXYUwj7gTEJ7rpiMv319jgTxBcmG41sQsLK8j582MSX/cMEdIDwe86y1WRr+XOz06CSPpBCdez9ZlYCYxSbO+ufr/Xd7vwmQgwSz5xzreWauzCbeYc6PWGHrW0Sg+VskP5VQfrT8nDCFXb2Ko0eoXPbk+Fy+GFdlnAUTUNMAr8sSAKz4+C74BvcIK/F4wsLJ3gBCd4JjCCGkCF+an5RoxKG0v+vj3CL/T8E8HTs1ZO8HcGZ9RXK+EEj4AoPLefaP+Bw99iHnvGG6d8HGpiHmt6NpGGYZXFCbs8UH5zZaVjq/B8SZMqaE5qwA85bZcYZofAo8y97vq+l/A8Cj6ovHcH4+8NWgENN3QCAkuTUDRyixhP2xhZMBEDN7O7YSY/Ho7Ji4ChluqPCTpu7KbvE4/HL6Z4bP9tE563GuXx12Wzy2z5UY2n16Z3VWuoExHSq3jBw4XXCYQkBmML+8+WS/4s+0OuSlG+lTIz3Xy7fkyejy6mgPK7lVKeSCVDpW5kbYiRLFw0wAmkpuZFEz7p76Sa9VMi/Utqpp5ANGm/poovtw81tYx/qXnrxztGWal5+6Fmd3zu9s6FOfGMqNf6KRVTuCf4IaGsecc1S382aVpLGifozwxxT0oqXjKB4Yjnb1qO9t2eM2ZsxGv5FtwmoXbWucXn8pw/Zsx/KuZnsdxn47bClQjCmzrHPNsLZSvbb0Pl92GmxjZzF+oQz2r1JYUw34qABpjxFbc6Nb8CxTx0PQKHzFMO/47rNq75dhDhGlV9RywCZcurNek+GpdRa/ZpKaN3S/CcEGltmy/RLP4FsMjbYwB3nHELLn6+Mxi3+mdhpqVtQt8Z0qfn36Q9XjcCwPiKc1wFs+v+V6/5LyWsFZwb3AVh+a22rdVUv1P60bXYCbcQobnX0QWpVn6GzDl3w+AXwdu58xnud5zxGed4jQS55HGpfxcgXICKRjrDhfNL0+0yfLilGicwRg5FTJtdariBCPEZMr4MP+vljQqitV4GbV1MFGzzZXqXcPb2J2y0/nNIm0k0z8W8O/A2e19dsfxZ7Ua+3feB0n7OmNK0Ne7+ue2OI0uuHYFRzIiBUK3TNkWZb2U9xxy4WhyVW7QTHXqCE/wt4KSBfoITPBdw/UJOLXQM8RKu73YxzYQ+UUhU0lgcDA6nIbBs6lVsyaAoohtDocr+uJ1dcncytj+c1v8OD0Ch6Iop9zcjNkaHPgAHEU0jwnSU79N0zX5k8K5YS/UiDm0AACAASURBVKzVp2Y9nVhZggTMzLH5CbXF7DfWx0e7ZbZJG2ccTgFpHI4vFPEoc7KYVC1IoZnV4fAijBkRCWZkYdIQYKZ/i58t9QOd2cx/cbmZ3NaEB8/V+48+2dhH+piueEz3jfaJ8kzUhPf7jDwlsN6rpxDT9sdKCM9oLo73B2dLO2JSxPCyFdveSqg1Mre8V/kG/4dAjKM7blBfZqKiKUX2LzlDr7CINY8UyqyW3VIDG1ja59rfLj4vhDfvT7G3tQLg0XNf+lK8GH582V0+FZ2m4Sw+24Msx4enEnIuM852mY4v3/fUPLeKdPFsDkXN9HhZhczculCHycLeiOb06iehHMW3+YRpIlASo5zpFYGuSbXQAcIKhHVFG2c2obn+S4xM4uNRqiFCcyIC0yw+ylFWQ2ibP1MjKklIoe22rgCiBM5c3tvJT0xi1lGdgjIxaFZ/5LO0Kq8YmTbKUSUkZvHhvkqY5gl5ngFOYoKyaM4zQLPWCUUjuplFoUKapopjmvIivkpISlNQoS3SRMhzxqaYwRQtuUoTPemerH4t2wVs1UWq3bqMzFy3QKqZRzqG4wtvVl49X0nTzVRTRF2yLeVvhcdk8HTEu02ATlNLPvVhMdm3hH27Z+nc4NDvw6Ov/T7i6zkDmDhhRbtpVj9uj+enL/HtHbi7/eMvz33cXeq/JchNRBMCrRnIuFX6vMc+Jb3+tprqzDfDZdH2s5kx3hAXyyyA+NNNTLh7LyK3xKKTmugKGdeYmDBTLwRvabf2m+VvlCRYhOtiD0s0PIG6/wjQqwCsDFgjLmvsDLiwN4EwvUud8BxEWL1L4PevwfwJX2vsjRh5aa4uQeTXWD/QIP+WPDRYw8fZ0k+4wuqXNc7wK+jf/678QEuuS7Xk4vtZ3BNx14BACg/aotuMPptf6Ptx9MV11uwiVS+Mn0dp66+261noFUQL+r7Y89f+I3T72Mj0uQmkz2A9KgLPxCLszVD/3QsX6Dp3PMY1iEdvbUbmIFwmNXeuFhBSlVbP35recMCNZrokRN8HYlqGaKVbmJEX5sU9kmByuUDize8/qql3wgqidW6my281fgKw/vkngBLy7za3CQ/ajgsQLrWEDOAajFcg8cWt69bWcwZwTVovlnxuCXip42tjZpcgJp3/s1Kf0WbgLUQrfAXC9R9/YgKwfisk4OX//AUpTXj413+XvijnT6C0GRDT9V/ff4BQuIw/SWhYi/ySxZVGDv02sfT3LTE+NajpkoGrLPW+6aw4NaDz42x9pq8Z4Iyz1QpEJCbdIzTaxonq1WXWDuwcy5am0lw3M/PiB93OIJ4/FwtKSd+FnicQBXeDWc7Xtlap0BHNig9TvL6LyhBtebVoBEKTfBm+MZ12ghOcYBlOAvQTnOC5gLnsnJXwfBhVhUeFqSVUgGlnFqKUNVKRfNeH01ERtf9hWqxDTTA/7uhO3W97FPHf+rDZCkP+OTRD3yfj7/Y8avtSv33vUIusTvBUkO2IasuaUBjefgt2wDAdhh4CemC1Mg4cVscvdtXGmUoj1lKLj5Iedkxf0PhR1gdFGx8sPmFz0EhHfQDr/IWOfsNh7IeHI7uBuodDMzAcYtnU73VoX3o08NamrfKM/E3n5/lPYHJZYt+3l97red3yA6upxXXRAMRqctPv9bsJwACQH86rQ3xh3PVtr/aTQbvHZT4NfMsdYWSm9xANwvGyX5hhe+S7bBmhfi9+6dmZeSO6oYQFBlPL3I7VX/IHPXpfNNveaGIuahkvtFXq2NCkEIYUUSrCzoQgcDdB+6sEupavZs6dIQLzxAlZaeWsf5P5iiX16khiPjER6zoRRhoCjWyXFbheFaVOINs/fB1R0cpGWT+Flo3NZACcgMRS3ykjYQWQqvfMKhJS4TTA2GwmpDRhmhLmaUJmxsQM1ptm0jfFKGzT0yMg/zG8FgWtKh6ytdOZY2/CTbDNIcuIeuSyguPAUb4tPbJkXvspzW6bFc2/GkZipL3TykSt6aMB0hrhsb9Ck3phW3k+MAY5ABB1KyZG29o7J1JwK0Qc0O5HWAiLOCAN4kR6PIZlJUqiMH9DX5DwQr7jBkRXABOIE4heIAed7QhLY74hEZTH+rf+4HeDm4aPwv4WVniN9HZZv92EPGu8wg0+DcupSzsEapdeS+tg6fxotIqn/wrOr0EpYU1vAPxZkFG1RzT5MURYfKYvZu3YKrNPu+4BnPPjlmoCFT/mVs+lM8YorE1pqet9kuQSBgG3HPIf+itZLEDNv8uKOw+0idCR3CUTVmJ79o0HHYcMmbMTBX/kOi5xHUSf50tjC2z3g/4YsPKtbyN+X8E19c3PuoXZnL0G8CJmSKm7uLqG+EK/BRdtb3u2fq0pR8n/gkXzvKK7mnjrELYJbYjvDNFEj+c2otdhxM1PupcR6yT0cQ0MEZh/DZX5TMA7lrrXZTPOmPCWGQ8k8QBJe4V6/e8DbkERKqg+bsWKcNxNz/cHNxOCW7kaTP1MzYX+RvXN0hOrEH1QTrjHDj9FULMQfOTbO1InOMEJvk84CdBPcILnhECgdn7P7bkKtxuKata4fOM+3QIoT0WelSDnzDATx2TZxQPh3rv3fhH9iFGTiNW9XYq8xYYJuzP/Y2r1/QA1v234UvwWjFj91u3fl9XWt0dCzCfViHHyLevzI4CjiHpBl0MytqOOXd/72OWY4bG5/r6PxmNhvgdEEM32tv6mai1gLjhSNAqDBm7oD8OhDNFOHPZVeI/BJpwpTHvy+p/guJ44imlP/YswDcK+sWO+eZT60Cohy3WKu1jxIcv+jcN7BV0YoVYz7+O2DMX4nQoHccSKs1dtG4clZRVmT9eZu2/yqZg/C8jgqVbBU+0H22Ck/c36PGSEFk1NZX1UnZFCvD6NC4+316Ofl/5sJUxhnCLzK36zdnj6pPi8Fmi28ayQNOibYXuGbVC3AFx/r/607KS+B1vBOxEBX4D02vs6kZosnwgTTUjThGmakCbxBTu9JvBXZ0NLOd5DooU+IyOrZsoMwiQLIz2I1nliTNMKKRE4rQBikHIVU/J6+0jJgvLxUS14CtpkBIASOLHWK8aU0crEupYBnoCUE0AZyKK5hJX4FxejKjPAwHo1Y95ssEkTpmkGs+Q7QUwTq0vyomUTcY3hSVv/PlR1YKKw14FBEC33RFSYiVm14ZlZGIiqnWO+wePmSWnSQ8asc097IOC66t3WotYnDwT3cY5ZXVHy2UG1UBAOhLAnh6U8dxDox8qyvT8NH5QORauJbkL0aKnk8UL0uEOOvyyl2t4lu/bzfi+sRX8Wapcz6zIzTIA5Lsf3Svm1NWz9LVaPYhu4KX97vt8LLI3BY/flDQGX+QU2dI1M/dUeg6mpgAnjTMBl8HDgzT0RojAyblRg9hVEpoF5iTW/RMYXzAVP+n66Dbxe43nfhnLzYQPz/S0a8oaXyl5NwIY/gz+8RELC9M7pDWYgv8+YVS/1/Oc13v7xEz7iz6aWlptfzVnq/zaVVLXm2cQWjikYgQeYFrT3Z8JrpKRnMcx4CcIDGPdEuGfxhS5lqC9jzStB/H+bNnD0ZV6dVbdM0DVQWWOZBnXeBRzagua5xj7o45Q9saawxSe4j45djkwsJt1vIfvqkAbn/fatO5aLeCYMPleNVxNa25yLe6Kdcey7/C/vSdsza/SptM8FtdLHDCbnPRjONYGuaYs/lfDcNM8vtH9vkHEOYC0UTKl/XBEEFNdv09s3WE8Jn3//gATgtX5fA1j9/Bbz7xswPhVf5oBoioumOYoFCMCF6DbXALkUwVCrJ/C5cYHxnLF18PI/fsbDZoO7939qX8pl0Rkyd74QYw3g1a/vwPOsLoFQLD+dvyVcf4hqCpJOjB/5+HxtLt46bpOUfyQRaL9iwdXqYEkvpxISA58Dbv5CYtr9Ys64JiAVs+xjzGqa5utpAsJRYp0mpbdTpY3e4ld7Tx0G9zcKF+WoXJrVfHIQikNwHxEhcxSiM0okWPzkmu6aLkrC5VF7lOs4VQ2bhrS9tM/790ZTnOAE/1Q4CdBPcIK/AkxDoyGGo/C84kHpN3kX8++tr+MRyBZPIbOaJNpnsz3sqLoLaq23Ekr+vY99ghOcYBcoaugYwy48X17JLRo6pvSY/85VWxa8c9I74YzG2+pnMlxIYmN+6fmmYyyo4Nz8oMcLSZGRPBKeu5ZEy6zn6ucER8CRTPvoN6wIzxtBX2+mtn53+WZTh0PrVA7FPYPR9vk4Y3rG/vb3rqygIdulMSEeldfqskClFhLSDvflhfr8Haf7srb3fuGutblEu3i6XYLm8GWYVzH5qD09kbNcCaw+z8/BSViPE1/CBEOMu44xY4yibeO2S0i+Lby0mfvv8bmf+yMWEJd6Ay54l73A2c8E9RNOqQiwZjDAs20IkiNnvSBqQi3TxZuBlEDqb5xopSbHRSvdrJkkxStxfbT3IqYQJxWzl4RMGcauK8J1HUvmDBHqMKZpQs4ETlkcTQJI2KiAmkAJmGdxQSK+0RNW04Q8J+SUdD9LSFMCZfWD2eFAtRU/gGjSkkgYiY4yqOzP0Ux7wW32HsywLwm6QSKIR0gXZ0E7x4ym2CUcP0R4/j0D1f8cAbLCXJPf1h1HBOZjVhXz9Get5zy99Xuo69zG58V6UUcF7F2W0d2n8+oy3KRrrNjMuQuaazWvLSz6hW5hH+FvC4Ltb8JFCQ1nYMINJrzEOV/hmr7snaf5Jp+MVwOno6zu+2Aii1dc+ZAZnNZ5S0Dm3M2t/MEck3wRQf4fb7AJor26hOPB2lXv3ftxj0xYmFTQuP55Qlb8nzDh8ud3oGnCn//+DbcEFaJHOjTSAnWJhHBGa45jI4L1HqLpbFESRMC/ZMZ9Cfo1vkAzR/qn/Gt7u7xbndo5E66iyzdTmBntDQtDUdKFWXjNpo1udFDWLBruALfvNf+A4Rro1qpZz9wM8xcuf5twNrL2zcBwpj4GlrTY7yCCjthN7VqF1ilNCZvfN0XgvdI409vXgNJqhNdI+FTyyNi+Gma4mXujwKwfzhm404QjTe249s7O1nr1U8yt22gYRZcBzPMGK0p4+O0jzn79qeRz/4GxBlXm7q3edhz8snU519jsEwGv9XnNlo/MqV+yXIr5oA36SiJEf8HqOmBfYJ/uhW7njLPVujfpPk4+HBNzRVSH1UHFIlKTRy707yA+zFKVQFWCxS8Dqg8F56NZXVR+KtQ2aNCId3eiQk5wgm8PJwH6CU7wnBC1Mtqdj+uAWoGUnYgNRLH7G6yZA+PzhGqeG5OM+xv6o1PfvgfB3TA2TtgSslvfBxUZEQtPV+fHATV/Mfwp84/E5tPlvG/oPrlJyumJSbsToViDHA4cN5Rw/bdfE7tWyb4pOPxFvNNiIoSThB9Cok8v0TqkIvhLQ6a6/8lZJJj60ugRv3LEl63wHHryPxJj/MhzcAm/PXcdAGXq6InT5kz5pifbWrbS13hJu8QOucWnc5cXyg10oubdIsQ8dLq19zB2vdtzZLhVLTUhnn3Xq/RR44UrzmOdB1WFhjpuWRq7lMGGcyOiA+6//1WMgKWmLNejobAeocHZCeL132gI0qIk1W1JfCXzmkTDmZEBvgBI2MLCJGNEyosAcMOt21XvVhguY6Zzy4T7XMcdC94bjXQVWLea6tYf8UKBWSNJBP0jgEXYjZcE3ALMGZk3YF5BHIuv1LQ7Y1YNaEIG0QZIUzELT7QWIXqapG8ykNIsc5emsn7qCzdcNFUAEsF5qDepP3UOEp9pNWlKBvEEZiDNGRkZRBOYCTzZeE9gykASQfuEBOYkJtyLBv4KU5IyxGVqRqJJ6j57Pct8ogSiGUwkFwdYzFz6ZVwVoieSPmBlsW+5wMaQtpomuhGi0Rw7Qi0I4qs9CnCTnkdyjMxQqw+e2ubCcwnJR+j3STM2eK7DShCid+G2sTwJ0t0lSh6fA8eh20qpnxzHcYMxPRpVjaz3wcdAuVwZcG2sj2HiEWPfa7N9Inyr+XhwfkdWwITOaxYBHKMXiG/TUD+0YIu96acBANPCfIGZMhI7lbREf4xKn6vtjXCmuCtDNF/NvDKAcsm3LsB2BL+AYXPJwjJdq8b5FRhcTIlPmJDwEowvuMefIIifa9tBokDR5lY0a30MuKBSNMZbWtTG1ERc0a99zozN+4z1r2tc/Y8X4j5lSiX9Gfyiyz1EwD2FPM71d6fQe0vjGK7lPWEseD1mnVHzG8Prb/Wp+A6iGW6mwwkoDgXOESCcWduClrdDP5Mb3IJxDrnUcFmmI6m/75p3UPAYW32o1DG2IQp0CW4WfYb5XJdRvQxpAOn/FyBcPwFGszG0CwkE8Sdv5X2C+CSXb27lQcg9ueZ4+/sHEICLt2+QPzgWmj+Ia4TzX98izxnze6es4mWfK80nI2r3+/y1PrM1OEGEy9ZPk27PSr2CIVrm1/9+L+X//AbzHzNe/dcL/L//32+41C37guXC5PX7TzgHYfXzG6SU8HD/gDyLiD1BNOnvtSYybnYRsrayNMJ87Qh9IuA1Q/GRXxQAgFe/vAP9/h73yU26EwDOciIx2ngbEEHd7QXyRMxXYD2tcD9vFtdclY/Wn+KbScCDoJz18G4XSE3ZIuu3eBlfLG2p9nlS/G2XXKxttQZG6AQpO9IBrPELzfLcB98TnOAEB8NJgH6CEzwTVHtiRy/uJiCL8Nz+ygd25mVVTqSw63oMhecL1Xiqw7rUrS7VGJDU1Lp9H+W17d2Ik7+aDhnVYR+i75D8nyqvE/wTgMPhl5sv9e+jVnYz4eoD/CjfcIAAV0KSLmYRQFARpFcnDba2RRzocVpBumuU2y9g2ujHQM8afi7u9/cHhP6CwzF5HJWOHL8WjVQN7OrUcph4NI5+SPa6NXtonMZNfiV8xOPi8I1QCdFH+YzelxlztpZ8TRVGnQklQ1uYclcOWUJ71wsHsc5d/FC/3QyM8M6hKB6nbfe1b7HC9tc8p8L3qMPH6Uaa14NShnlFk+/GnDMzts5esTH1MTJT7fLrPg0lu/raYtuXlSY5lutex4NfzlgQmI9+i5UI/WPcg+mi5FOliZc/KK5vKh0kpsMBvgY4KRuQ1wBnMDM2zAAeQLxCxgoJs5hzpyRm74mQMBXt6ESi8YcEzDkpgzX5xZymX2PfpBRMtK+h+QGcqRrfZOPBWay1rxKg2ud5TqCcCyeVUxIhu44pUcI0JaymhE2akNIGKRGmKSHnWczNa/9U46NMyGJukmrvpBzMtZDNtYI3bO/0dlTzAlDT+JK3zbCRVrgzIW0+5OobLcb395Ef9hPU0PVbYSPXjOMY58nKfmTaSrb4RHntovVmyMWcXWWa6eGwcuq+DWGDbfOHhUlZFHZB5oHcBPCKewH3c4EIt65BeIFMeccs2Q8MsxomXMOFyQVa8rT9zOgsaIkm+lckXGkWuiciIYMwg4tGcwI6r+42J/VaV1kf7Zobn958NhMIr7QOM76W+ttekXCFCV9L+y3PGQz6MCO9lb2Jc8a0XiFnuah2Dr0MB8HtZ3ABIoX6bhujdhrtGk+r4zn200SvRWLtWUF/l84QbGPWA8FNysed+R7SdrbCB9ajhnVsCfRSjrzfqia6zdNs/RstuiHSvLaP+Nzu6PpQ2kafb5oRm9GPyd3OUToM7uCXSKxeAHCBVNoZ6x7X6gNkvQJAejdh8/4jNojm/glpSpjgfscjX8Xowxug+EMHvN2x7zLk4iBCOvZlVp05TDidmbH6ZQUG8P/813/g/b9+k4sPJJcwNhBacU3Aw2bGlAjMn5FAuIVdeFFz9V5KqOmuXavGEJ8IeAW5EGXt2ICxmT/g8pe3wB8f8RKMzyQ+1T2P/eF8NSEzsMlzwEOM9TRhM48tKkWIOKgqeaCJTtXnwC9q8pMLsJGW9Rwo88CtQnPwj3nrWdvSnOiGE5zg7wEnAfoJTvAcsIVJUW6uAZVf9OhDrWhMcrjp1gjSh4S5BWZG4VwH84tF1uR7+lZm66GsbCr/9umWmHEnM3i74el76Gly7A9VEpIW8j+21NMMcYhMQvsvho/i+jsvfu/jbim9OIBy1mLRpnCJXi9UKXFSqYuZwHUtxTDaevIktAz0AaYaCc6rhyoyFq4UbQcCTHv9qRi/PxI81udqEUQ3eY00z9wM3CN8vYapc0wOMY2Lmvzb0ntVFgGJnQ3UXkaptM4b4Xn8vrWOLdOgCLC62nxTeDrW2nGrM5oe71lvMV4sQ8rZd4510eI4sjHmzOshQHzm7iq0nIxag820ht23JUo7Ru3rmIoWbujd/uxiRarnXpdOf1OL71ucTmZphHSNWlxrq8SVy6NqDLZpBIGQWXRpiDdgZqw03oonpDyB8YCMMzBNap4dIJpAtAKp4JxSAlIqfionrcN0OYHuGHRO4Ntc0TLWrulCfDQmFcQbFywB4gM9XEgpfc1ikhJsGt+kvhgnOQekDJ4IYnpddFfF1Lz8TYkwTRNYLwsU8+0TIc3qHz4l5Cx5kWrOiEsnwswmSI+4Q+c5MygxMAPmBzLut3Hcc8CnUe/XtNLlg585NEDHLlIsAZqAREmF9HUdCl6yYghdXf8WsLRADY5EuYt9UW5THJfvYnlPEPMxVSrH3RDmOOXxYOz6spu0l6bKGbqnq2Vl+NPfCh65nGYSQXluwtLTT8EK/DQyBhd2XyPhBc5ZzUvXw3lQHTfaVkvzADcdvuTreWP7ZRNuJzm//ChC9Akvyz5UBDoqoLnnOMOKaC7Mv9giHrz1EE+Ut2Dc4gsIIvS+1/BLEG4BXOArrn75Gbe/32PGZwDRzDUhJULOM6Zpwtd/fQEzY4Kb9DaKhMFFoBm1fBnAWnFaFHovTtHQuKIkGj6pwZm9zLm7+HFcRBce8IJY7qltHFh7bjT+JUSYfal1uitxTPC2a6RqqCnScMWHWTXRbZbItxfs9CMDMK3YXGrqrc+6fmMnrPglHvBF02hZ5NY078a7/ZPDCMP6HGOchf436gpw0/L04c8qn4L3f3uPBDXp/uETHmACccbZuze4ff8JCa75Hs2ri0WK+twXRzPW2daCmcI36wRgxs3vH3ELYEUJK4g5958ZuNEzXwZw88dHXL59jbPzS/D0M+7f/g76IEL0BL/gsFZ6MEM04b/o+c4E1dEFCsF9xVs9r1iE6G8ArJiwAePyl7e4//0jrukDLkB49fYn8IePYACvMuNTApAln9Rqopfzhsw3ofuA9WrCxAl3m43eq5VzRFJLRmlK2Gw2YZ/v919q2gPtz9L3ZBdboRdB4YpmpL0hESUNqRDdNMeJvKScURyrI1w8ZYAi04J1Ren5oJoUJzjBCb5rOAnQT3CCZwIu/8TAAeckMDzELKKEcRGga3w9DbgJ1cEOXFGSNBYehZTfirTteMTGsGu/NIK1bRcPTjCAU3f9kGDHgHg83X1Qpeppr4PtkLg3w5R9xEUtRWi4/przNItvvm0pufYhEQkTPWVQVi0G+AGnqgGH1rCHIbSzx5Y7TjBLTNhdNqz/qWDjV1heR2fzqHSmiVPq1GiylgtnJjN4DDO9GuqQT9SehAvJ/HBev5sJam7it6b+YkkljK08a6NVIRoAje0c5NZuu00bqWvroEL7wBgt7L9PfQOmwiGa5234iDG3XfN8e8WrSw+jugTazeYR0534a+QLUFKmFtkOcCs81iA8B8Z811ajPIZTwMVL7Wzbu+376H0r2J5hGtWl4/1SCKtANWfT0MqYWdiBxNKGxBtddGtkbABeqXbfBCZCShDB+ZSUISfryrTQ6UIu/9GllkkSj868PSLUJlmTmoebiITsRbr4u3VFokNoaiwpASAGzQRW8/YggJiQiZHIfaCnJKba5TnLfmn1C39i9TKBJmDOGTxbPYHMwtyLfEwGkE1jndS3o5md7Nat+IQsQvTATKS4BxvyK/PABLvqrz3auR/NlaB1HjWn/5bC8m1A3cPwdXvyeH5E1UedJjqiH/THIdkwxH9DUJpwSwNM+zxCaTNbLq1G+uk6uMFfoWW+az7OJJrwbdw1i5b8sRA1Wc+OzGMkrDWz97W5d4uL6sKb0Qye3wIPqkmxq89sK2a49jBBtI0JIkRf/faAy/+4wM2/LfcM4AtWb1PBPZvNAwjATBkZ4k7EYtrN2DMWrfoENR1OqPaVnfimQUpmFt4uTug2fxDsrXkeaUA946YuVd3nI+Gqi3ftEKOhW2hjbge+5KsnDo1g43fOLjKt8ukZlv5vmYtynrE79BOusFEh+iM8oz0KrNi2eHMWIONfX4mVurv7gRX8coX4L3+JDb7I/FST7iu4Jvr9+z/LpRY7y91pGedhkEybPA7f6FxhdeKQ7u7DZ6whvsRnHZ2vmsE5RDBu5vPp/SecX1xgWk2Y5rdIvzAefv9QLKjEM6rVw0uNvyNQ2gGiWZ61PhMIN7+L9jn//hF3xLjkP5Hg2uqvM/Apbac24oWgzIyHzYzLszN5nudCY08piRY6A+vVqtNIr/u4txZDzhQY0pE5M6ZEyFloZMGxrBcaqM6TOfQp1eO6eA4OMannop3gBCf4fuEkQD/BCZ4LOlqUu+9LhFSXRXgYEb4Wx3wScqPFqYov5dbcMuMgknCPASfVItGK8DxksJqmxIElAU9T68dAbOfSmG77vthPO/Ky5/3avx+XYFes9nuref5UvJO/LzNqiYL+VqVtOfjulX43LuqgYcRSOaVROFC4adnCCxBOveA/gtz+pQROJAKBpLOJAMoU8qDFVlUCC40TY/XPRzI7/95c4yeBXXjpuaAIjUAIN7RgQn7m7FyeY8uoygvvYa7FuUfo5yKR4UUTdKPUKVkhkRHazLFyA19jlDjk73ZoL3Vk64vd7Sr1aOCQblssh5t+2xOeaoktC3G5iTfqgT7tKD+iZsAW046LqAT2OoEyGBNRYfwCDE53mEGqkf7glBqN8L+CNiu6OCjz0ujBJikBepEp1K1J76jecH/4TlRprJumh+Fwkjo13AAAIABJREFU0ANAkzCjggDYLqXI/GVwFiFwuRrAjJwJ+auYPCcAU/HCKH00y+1TJLuICgZhEvcgiYQrplrdIgifpGnZLyWIHF/2onQVe8zyc3xj61J8uwOcJhR3IQTVOAfyLAS4XaTJs2qCp6Rl2zsBM5c1b0WlpP2j9ZL6E6ZEYo46SZ+TqdNngFm161MGsgrrc1Lhdy3AVleTRfPMhOMmjC3jhwTm7MJtSxhpdpa6xzlZnyr8aYl2LwKGROqf0mEkRH9qwfo3P1MYuskt1d8UfOQm2/VHpNVMGnIkPMm+vx9aXkzXzqc4XuOs/SwKmHbfcnH9+aZ+LiifQoXgp/MQ1JzXD+u9fxqpab2T2M27AyLUnh8xsSzffbKYC312LXWB+EWfmJFxg4zDhf+URJg1ZanDnaY/Y+B+S153JNrrxpiN+soE6aPoRn31LmF+z1jjNYBPeNhK4XGHx6gJMecDh5wTqfqVlHf4hM2/gRVeYf1uJXvJhzeyHxEhrVZIOYHfZjx8+KR9LnRO3InuI/+H6jGttMbDcooXFu4HG4mZuS97Sqj5PlroERZ7uxWmg7YI6l3Ydq2/F1rZC8iY3CKOVQ3dNtdGa1FNy3Zk81Hu436h8yDix41+t4sh8UKRuRwwiwOA5FkuD/5FYJr0JrCOY7ABYQ2uvjO4CNkZ7q5DSKgvOHv7Cg8fPlem6MX/tzdyBe/qK6UIZ3i/GY6ZIILwBF/vbR1zCDfBuJwBCF+IcMGMCwY2alUpmod/8etb/P6/f8MEYAJjBdE4v3j3Gl/f/1nylHElfKF2qrgmutXC+sJmiqW54sgzItz8/hGXv77D3e9/4P6DlAulpw2v1xwXrn4fVBB+NollpwzGzf09JnXr9zBvsJ6k19arFWaWC6RnE+F+s4wFo8A7gl0QbcHpbI2n/RzXUDTnbjwpAoc8WyxpCfsynTb4CxfNCU5wgr3gJEA/wQ8DT8EAfjIIpg2H4QgUiTI43NS7Bob3vbbcBZN9S/3yNIf1Ir4IIf1hoDXpvAuWzgRLZ4eawTKOu1jII6FltsgvDcIGjJkuLyM7Ry0esR2/JcvFiMJvke8TZf2tqvidQjzc7Mt13TVrlpjZVc5Ur0S/fF8LNMkOI+16J9H6M01zSqqFbgcYi6fa52aqtapN1ASvKr0sPI9hnlsdY7vmZGj3GL0+CkpN9sz4OLbsPhUYQBivo8p85Lok2yPJ51Gpj00rxD4ZsAYXmEq76urMCp+/VZaE4XtcL6aBbh+q2bzw7smpHNr78kL4wvIw4eRS24xte8wQ7ZoH0YLdErTzeOQT9KlgH81zea/rVi6H7VMvGr9WaSmUWeY0ByG6xy8UABGYxMNqBhfhtNXTy4n5DtrKfbs72mOxX1zbefS9ijcItz3LmMwUaVvSVZb0US0wMTP4C6tzSlnXmTfirZynYrmpGGgsFpwmOE2qmm1qwt3+6DKJRjTn0C9q5h1Sp3IxlX0OxD4opusTwFlMUTIYPEdNQda8VExt5l3D5TC7z8Bl8IJmudU3CNFF49wobP2lkhRAwpSAmQEgiwY+A5nd3LrhE9INLWrpFBZfFbf2S76k8dwKcaMm+XYwLWkt337ITPuH54A0D8deo91/HGf3t0PLpi1v+wNTtM4QcJYOX5BFHUxbfP/AW962A8GELWXyVGCaoWyRh0TwGDLGTPseDFftU+M9odT1wEr/TWBi0ktSPezqxtgDaRDWfjsGNiTa7GfsWs9nHIS0A/pzAxGiL9aVXxTaIP/hJ74Jr3COz8gEPAwb73PAfH57SE2I7BKi1z7R+zpuYNqwn8Hvr3D56yX4V70cp649HjYPuP/wMezDgreiQPIM7EgMRifU5zUTehPcF3M7kFWfK7hwlEsdCLxViD6aH0u8rBib0PZT3aY2dpyPM7hLsxWGA8f1X4PmasPqjBuIefdCj8GFzFPI0cfiJZi/lDyKyfMR2jkWvx2Qzlp6B8Z5Kbj+bqbbCaZRXNfPfJTPbJdqgPz+M9ZvX+FWhegTXGvdhN32rKQpMrlQ3cqd0VszaYrvwPJfwU2wMxkdq5drLAcGPv/2AZOOIcPne8zDSo11ifPAKKKWX9nW8SsBLwG5qArC+bvXuP7tPdZEara/5iu1v0sQV/sMxmY2xwDA/bzB2WqNzGbqXawhraYJ896a6B4+AovPrLSVTvp+Snc6586vVxdUZINVSm7npC3KZlMYVnL7fr6rXf9I+CEbfYK/Ek4C9BOc4BtCh8tHPJaFX2oojpjXLp5TdEksjCutTJZMjZmZI0Orqp6RTk95mt9vb1tiso6+LdWuI9bInqiJtbtGx+zHFP7qsMjc3E64jcN3UQlPM149Obat3+JhWmbR4zTPe4bTcj77jeH3BW19d50y9zl1OqPazbmPS2tzOvRQs6seVOwI1rN1JDyvND1LMoIJCloBvPhvlcOMHVoiA6I+KKG7j9TXNsDBUykcwxQ/E/crZ3uhO+LuCRHfPTUs4iLtr3T0+ntkjeM+qVWg8p+/xXLKfNE08ftibQYfHJfHsJrtuO09LdRt93top14UGPV+9E3Ys/Oa9wa9FEELYSedcQzEJbJr5hQmHfn701RpN+tmG7TMEoT6Gdun/ua64xajanuK7MiQVsOYgEyqicz+pTe5qUw1YwLqM7XZQsOHbetfWorFaxe0xKvvcQW2a1L+TSE1VTkT+AuA11DUypgmMVmeeQYyQJgAYr1UICIq0YBSRi9pA9XMuwiBdb0U//HBNGzsw7uMdE7IkAtciVyrOrOkz+a73Paw5gKNadznWWyhc0mfRZiZhCbPedZpRIC2A5nFdH1KyETARDKQPAstn9yPOYrgfC7vgAnUzZw81C07o1hKL4tK8RFJnrZnivBczMVnvYwgPiBNM40qf5jRnKWZ6E0k2ulRKGkXApJanDHT7Um9sJa4WrWWyix3hqulMtrcI0Jb2PyhVNLC9/YstJSDV3gU91CiosVw1H8eBPcRlvJte/SQPHr4ZpT3AUi+uPHpsKEDhbgSUI+XXCjx1CvVfCvWFkBIYOQ5D0fYh8UQpqTqL4dQlW/JgeR3Sfts57BXMdsxXn5vd519ct+vHo+DaFrdys1NoUmJgqTuLR4DD+TCV/m5Lm1lyDfGbk30rhakeWeuBPEr3pIXwwxyFUHuGex8AWRcY8IrMBjpneyXd+/vMWHCCi8BABO+VEKxB/1dh5E7B3BPXKPSUoWWuh3375B+CASemMK+RkpXhZ7knLF6cY7pYg1wxt0fHz0vStpPjI3R6Vr6jFroGWtkWud3zftSnc2U+wxhghvdZs/7a6FT9UxW2YoeUMHbwg3Q2BrDJV/1/YWWcAHV6N5z5fVrekzMt7nFGCb4tDpYnhnSZ0X7PKQRwbCY8r4A4Tbc2GIEOtQC20vvg+btbjWHfwVuwbjUVHf61ftQ2mRpWGnRjLhGvQeNQjUN/PThc/mewWrenTqt9I3+GmnvtJILwK1fjW5tYQ4DafE3EH/nXk/fAzdan3g50epULoy8/1ROI3doL0R4fp67h2yjTj4T8IYlv7v3fyIDuHj3E1YE/OuDrPGbRLgIe23OMovMF/p4f/HTRuYse7Hyh+42D7g4O0Oec+EvTdMkroq4xm19zvEwFGd4/K794Croury5XlKaPuqoGTVCSoATUNwWefFO0ApJHkfBen3//ZzCX2zh43bHfw4sj/C4rw6hjU7w48FJgH6CfzxEBLiPFtMSv2Uv0rURSFeV4Oa7lRMICvN3Dm7qESgXpzkJfi8xlKnpUkhKpJtzRUQbZcZ9UAkfk0tlYwmMriXCanvYfiwBbzKPU/AgLoQA4eapPrJYyHgbpW5bHb9TlXdPxFD5lkKsWH79vM+BwXs9/u6Kf8y7hVk5gzkU3usY7e3pfcvet+6xbgP4y6kfG00zJhZH95B3b3d9XKxJbS5PDktd0JpUbeO2Z92uWRw/2EFDw8oZwTXmXIsshFuiwKi0A2spqmFG2GFRepUrS1jlkKI+cANqxYi9GnOOcePHwgMYTDERTlF5riY/9d3WFtFGKOOwa1mEdO2KHNQSfcN6nL+Uclv6BBOFcbMv7T6GtHhiv7T9kSfOmSKmExMFiB1oNXXBj8fva6b5c7tPtPg89tFIpD5+p4NT1LDdwDjVc28LMSPrpUpcaSsu0Ut786sH87dFG1v3OvKkmcZNeSpfyLt9dNcLu4jEq44OHYsGTUZiLiZMzXdq8mprYXgJjpPsEks7XmmAhIT34/g3aq0vQZyrPofrVbD0PXXx/QKJXyMxw6qmuyOTzxhl5UKVNnC+zrq8TVdN2J9FU5RDD1pAtUIEG6TyLBpwRACdE4pmOJlmHMQNkq0J6biAe6Sh0hatL3ReEvziKkjocGLQLJXLcX/JbvKUVfMdE4RhxwmSSPsi1X/FfUWiUr8yz1iF5ATpV4jmZtGKMc5fWPtSjlyGZELFHHShpcSLGjjScrNGLgmJPY49+T7udpWCuL2Ay/m5CJbipaleRhldUoWPNhmq+E1iMuqqRVyE+qw13tO2f99Gy9bf+l1nV3p7j3RY3zdGg0VNzlH67VCn+mthXN9Dd4LRnGO1dgECZh4LEDxtM880XaTniGR+j/fOKLKMuGqfMY/vMX1DAI+o+3Y5PDNQ87sNWjPvih1FU/QIIXq7wmznGdUxD8IPARPQW50BEaIP/awHdBA1RY2OcFckOvM07vl/nOP233eFvFjDhZxn8L4yMNPnkWYYzZRlqPfUlmIxk9UbMDabB0zTGplkv0s5gxLh4YO4pgEA4kskXJc+mHRvmm2OUr2PJHA5VZtAvLSN5d20ye872kSE+2dwQad9a+dAi8lrbN1SPbEz+vPBGMJ6HYDtqyIAXq5XDN8H6jbFnb1CYUpZUQn1b/UOkvAKGZ9DXuF8VVmeQSGiIu40MqRtgFjI2dYKT38GEQoTXIieIXPgrhs1DnOKSm7RT7rTM6QXM2XBGCePwZhBWOE1gM+iJa25J+1L0+K3tT+9fYX5/efQo7VPdGuLwTUB5+wzKAptkn43E+pmpSpeoI5Xdx+0XoDjBruY8pJFCF717IGb/Eb3zWKtYLUq+Rg/5oaAFwxb6QsgddzkDaY0lfFKyeeW7W2393c4X62QWS6IEhGmlIoQHaX90TpXoDyrTchpWI+ns4MIrHgrq7WoYrnALufualOZgmF/NtoeSueDAz2uK0TjU6BD0PHzI3wf1NlzQEsJdSR/883QT7xA3l7qH6ChnRTYCX48OAnQT/DDgDFfdkI5pAzCI1pd2LyqM2sIrDSBwiFI5NRhc7UM4m8WM48Wh8punaq6lk3BGGOk1cxKRiXZHjizaJ+X/FTEx0Y2uqmcKGaIG0u70SxtPEJAuhG84dYedrjRgS6+u1+g7aPJGicXgsRqZ/eY7T0cBFomeiHAakIsxqLmqRbo+NFDYBq2vxatjL63X7h6jgxJ/7p0HI6jxNV3Wow/Au7ip9KrOcRqj0rb3yVP8/Q0rouPWPsO1Ec7DL7vft8NNRkVxyahFW/5nGvnWy09ab/HEY3pbe7XIvBc9ebutbHPexEWxBaSoxdvn6yxMiaMoOQj78FNFBis5kYpJJcwZMEWmRmUEzhoSTBnZM7IMyPnGcyCxxK4+I3V08XW9lu9R73UE+I6g7nOlSAH+4mBiafq0Fqn11c/81VCMOsUPxyFyz6M+Fbieh0U05S9jRYYtD2WgpbVb1h2GIzY37E7hdAJCZOW2ZYwKrvGO7sFd9vgJ3oNIsINiQ/FO6RyQAJQNooiRwIBNIlGKcL2TUBtIzx8iJtu0b5E1Qd1u3btirEfo2HYFi9g/F5VMe7fdhll0FGDMBOeJmt2akQ2uoa4nRvRKd8CjD7Fg2rcYotAbDm7kmcZnqiGbd+3CM+XTLTvgi5P0/gnx7xlBthPHMqSzv98mnETj7xf9qteXdfRGIesCNZuKScKz7U2JV5En5aHaWoL8kcRxMXrTvXVJ8+AgcIBTRMhYUKaVEMa0s85GwUzY0rAilagLwDekOaheH5ybW82gRRE+9rvy9h+Yf7JJ9XIVsE9EYwlB5a6kTiDBK0AugNwlkVzhNWE5yRrP+uwpbWwCCmjWFEhYqWvCTPPwqickjKAy0KVvmeI33aeQMRgnpEtc+UiJwKwSiBOoq0+MdKGMDGQkLFKkL6YxI87KKkmU8YmC7ONRM0dnHVPxlzGNyGBKZf6xfmSQZhEbV36f9L9eZYeF6YhI1OuGKZOVTMmkjHiSfzbI4svegaDTSOe1ad6lr29aKITV+c1RrPkqaE3Sjwu7ZN1GnBo+dC8l7Ws5dhljTCPRQDqZu45rlcbshC3Rh0U3rdSHKX3KyRQ5o4NBocOoeZ7bIkuVCZQQ5KWtnJYsyGr0u8VA7rH1SPf80dBl87Xy7jkkhDezvps6bRNjefasYk/JmTc5Oy4WrsyXigrAoG4J1XZ6bq3c0zYuv1SSVt8pAXaObHve5t+9N62fuma3m7YrfO/DCZQvk/y3GqY54KgY64SKTFhIvcfPKP2Lb5Pe+LcFZwa98FLADflPWn+S77Zd1rqIxGWnzWS+HUGHlJd57iKpxBekxUM4Cvm91fIYFy8O0OeNzAMOOElGBkTrjFDBGdrIPhI91IKOiTGORPuqOUjWOktbTpopi6IsxCLANz88REgFM35O/W6nfEZop1JILrDGq80xVfZF8HF17bEBygL/0oudwlpcQFzlWBa9raWgDNQ0Shn1OfzjkaCcGiuwHiAm4b3tHYFrE4zEsCAWwG6/C7PFN+D47zz81/vR707G27J2/dKhlFHArnkb5wT7z3gAYyLQtvFOroPcbHYQHiBhAcYP8rqaxSBm1O/C33SWjto93Ro6tb2R90egRUIK7j9CAbc9U5pA+FGbwmfQy5pTrLxw6znkF7KBSiY7pb2z0TiEqAQnISZv+o85jLumcT3eGLGzGI9KgPY/PEJgAirr7gebwC4ePcat+8/lX5+oR+/kgi5mYA3kIsfX5TpsNF2AIJnVlC3N5mQOOPlz2/AzPj6/s+iKR97boVaiN5SErvghW61Zsp9xTIOcxa69iXLN6EZIylGhcekn4UO0YLnzJh5g/VqrZanSPlB0tYpCW15nzNWlHR/Z1ASvsQm6wVbrnc5m8W+O4ZLFdbz5K237yml4D6QkIqpL6cPCIwpGy2p7gHKN4WcAvLR2c1KYyMjQzY36RtS+j6QSRTXfuAYsc33Gj/3+PyfC7TwvDONM9F0buoj1eeP9t0KeewF/hP8/eAkQD/BjwW7MCr75t5Gp7iDRTUtTTcsovA2uAjQy2FZD+VFcGI7oDFIOm6G7rkVtR62Sq1S3Cybi2xG2Yspx1BnF5fXpLYnqo8BpXhrXxWr77dycXDHAFgXlE2pSVKawW0dl2pfv6tujIQoZVXXmUOfcsmGunh9G408t29Rx8nj7+dRrevnYaxR67dB+/Ux70vf+qPQ4WAkbQzp52Q95+r3MIJOp1bx+zkbS49l7fPueWjptD2Wv8fwpsXcXwRYOoj3Pd3PmENH26tHFW0JwLXHLWXUZLPSORD8pQDTGBfcGRmUEkeY6zlnMQFLc8WU5cwqcJn1ElAugnd2EU85iS0fAAcryjQhqv7gLgMOD6aBLmbc+lwj2m01ekuzy0GdtX+8Uxh19/R117kWD2dbZqz0TXxv/NmWQbf+s7nsg0nsN+wTCBPToOxD3/dZbfVkmrASn2c0gSA++2zEzQck6fgVVlZ1KLZ/OXzbUlfy/E3AXHwZd/FHeXnZZsC6/ral7Hq1Ad1hzeiRQTNC/etnnTe6fowOAXxvlCovOw7ZvpuH2jV0SZtw105RvhOKFsK+rMMItXBsP/C2151Lo+G232qbZ1NTwLDHlqZKRwjtB61pdoIyVSgFDY4+jhWRGiJStgC78GHxbZ+r+5RaSZ3O08wMSiS4w8yiF4yT9SLUPRLOS/vpZUJSx5QMgJUZZRPIGOxlj2d2JoYiW/YqwOjQYg2l4G+WC6opiQ9H0wYpKumAEbCkdL+sD+8neSUYQey41AbDKmGCs0BbylaogvTScUBiTKRHdBMaZAatJqS8RlpxYfyS9CKmecZmWoHSBmlKmLKYopcLCEAiDnQvl771S0VOJ4v2fQoWWFTwnaMmeCrjUB02dE6UOwEAMDFYtYKy0gx+mY6RQ69lhlzqCfPe8DXrZVg7L9XXCH0+VEAFPaIQHWWON3tMnCPaJzJGIQzQfdq/h5mgmkTUo2lYmja8bqW/RhwQ9qql91IPH0ddHD42pSY13dDtKEqnVX7rq+9LjTgMv+6TxnEwNeFl9Td4XUy9lnRUj9Ww6jV50V1KcmF5873BBT6PeKAkZgsn4A6uf+t9Yh+6KFSqSr/r3fdld8Nz2Ng9RoBOmv4cF5jp9sCiqWoVQQWlB2ihy3Lo48uqugnPEner2fU9wTQWCe47+SwI0a1egGvcR8F+CnMkqSFqBjC/z0jvjKY0LHhdjY4L0RsIexgRVFgK3BLjggm3nf+XbX3sc0uE//Ls178/616ubSDTh60JJ7ngpoLI0CICY+ZcLgQVNpymPLPtf7GuhDNQ6QOze1MvbSl3FfrKvyffK9FP2UVSbmusPjzWJ25TlxAN63O4aXKbo2MIe2Oh462VFsMdsMSdNNbGcGm8Tm2n7ehbm0FYgcqFh6i5DhDWEBpqo2ltLwcQLizVPcsImr5o93hvfd0H8hYtDAEhV/I5am7hrKYEUqsIpkFOBU9mfc8EnEO0zc19ECCm67nwEYymEVpvdvICM0To3FqFAIAbFZ773iW/L+H4Z6P0zDlEo5vguAJw101mpeHujz9x9vNPlfl4QIXaEMF50v54xcCfZD0d6SBsBcvrCwGvmctlk82Hj6ViRYnC8FRYChy+G5B9yPbG1UDb2EYqkCE0auGrlJTjC+/xe8mhnGl87lb5B1qwBp0zOiYmUBdaGcG9VnakZTPP5j6zGazShSYupCiR0N8F/zT8odIvj9yk/qYQMf4SXi5riutw+RBosurj9nfHFNt3xhP88+AkQD/BCQYwQsIHJR5AxdjsuBVOLAhfpCUUtkP9neMZ3m+xDciH3Qif9oq1X73G7diV+6Cr+l8aEXjhcFFtfqyEDVXxLKTWNpfv8UBj7/GeXx033jy23+Nm09ORQk9LVLW5pWZuLTFW9j1w9v367d+PS9syF+x53zXTzmZ/q7/4m8fcfxU/FbTsutGs2ia2jrF2llVugfu71KHvgXE9RjH3h/pQ1ZcVD9zGuopzt2XwtSNd9MwYegHA6x2Zv32tEGI2mQI4gIdY0vU3lh1r0UJ44hT4wNSU+w1Xqp5eTDvn3f/4TzABm/s7gAif33/EGXnkTZeH1djxPgD8hNcAgI/4tFddapP1R2CSfcapTdoe/JaSDe5ptfLzak7qJB0KfAgiOAScQzO38XZDuw4eA5G/cHjK48uM2KDg5XKQNg0WYKmlrbAvUgc1tmpw+x4d1zEF4jeqtSDbX6sJJccpZg6S1JR6CjRkJTi3iyWBpnJBIyk/SgWyKRWNoBjHhPZJ65qIgK8Ar1RIzjNSmoBJLlBMaRKBear3CC1OLoRocApCbVY8RWxaRdpu659zQppI8oUwSmlC0Gb2epNk7rQ2EXjmGgGHiVr2MxX08+CiLAGFNuUsGqxczDZkcGI1AS8VYYKYlk9q7n6VkGZCSpPETaKpx5SRiDDPVnMC8gxWvb08Z6zOCQ+3LJrgRXBKrgnK5Jow2fXBWLmC5lsebBcdxGIA56xtHs07v+oozGRl5ad6utuSivcjbE0U+j50fUw7QmmdtRHaBzO01MQxV3h2QOGAj8vd+c7Ne2reQ3xq3iMcjlf3hAHXuVgtpT6e97C9d6n3Ki6rZbVOAF/CUfKPMXaXN8LxQJGcU21nJhzNl+s8yLelBvuZd/j7gi24PaE+lbSwfOXOYUPmW/x2z2vlMf/xlnjOwN0Rzar9APvz+HQW4TAMYG12tyYCZzovzKS7aSxGq1bxgi7hGowriD0XYMaM+b2LMhlfq/achZpS+LeeR6J9/oJlziYWO3KXTLjpDhXj8c0UzU0TzrQGmxAzQclHxbkrXGGjwn7hI2QkXOl+8FUFe1Zf2WtmFdCZdrqkaus3wDUg1Sqn0i8WOwHDc5ynrdtL3bfl98dCzM+F54eWV2M5W8H9pSSjZT2EENwlwPvHzrD36FVD6jrKar1p1ouQFr6S412NJQzS7lujvf5FxKIMXBA1PuQlpl2TuSzjTurKoeUO2uhLuPh6J5zjJe7wBSIsb2sh6cwFQes33lo96zfC7mPVCiKgfqnv10oYfVWa8Eov8wN6OVEZwHdg3P0hfshtx4v47TMBP7HX6zUDn8ivHtQnZQfL45pqfLwhYGLG/e8fcEes2uf+/SYRXjCpGXcuFpray80W/2F+ABFhpebcVbRf6uWuniR+ztL3qyQirk1WLNGgsXKxzs4B5cpBLD/OOD8DOOlO5ezSWsHx2RMIVzuclwnG1Xnc1lSl9NZZF2p7KH56cqr0BCc4wQBOAvQTnCBCw1c5GJbSGfOoNXmHSOqPEjtHaCuRzk0ecZ/lEInrKrTMgpisrdMuIn3XIeJRh4pmXNqmGR0z7EJqfreW0RuU8uTtEcoIo/pQZQKwpYPYjwLHtjsO12P67lsfag8r/Zj4vPC9XalPDE/Q6e2hvHw+UPtTUFY4yncSvtrygyZ5XO8HHFPj57pU08mU28aEVJnsq3FTa+IvFjU6GtVeSmPivmWV4hlGrNEF5pdtFY15ATvM1WizXo2ugU0Akd52fx5gVp+OREhvkytT6yHa5oM1KZquLOKaomnpbTLTjmdN70WNnWWcsu+M03jNvD6cAf4EYFXRKdYofuzUODgGjlmb3zNU7TmmYVtoE0YQDi8wfsp7IPsMzKSjrdzI+JTw8xJPxNT3wkjWyzxJ843CclKGnb+7FnrMva6eWx0Z0UVCUCBAAAAgAElEQVREhJxMV0kF7ClqeBijNKuPbLuul5EwLcypgL0ZZb1RI6w2a04UOk+sRal5eNNisexC3xQhXwp4xJ4jI02rUcaMnP0HREOMBNFa1cJUIM/IAItWVzZrVdXOIXWhlDBRwpQmTFOSivEkAmxKmAN7liCMuqzt5ZQw3zMSkQixy7hzcHgUam0XHtg1lL1rA/aNKoJQSxelq4W5ayYxPZ2adbfuImeUtlrRjPBug9hviD1QoCXaDdtzHiTcB7ac47bGGcBjkeXChjXM9i/iuxZ/lFyHPSpP/d0/m2YS7Eq47XDRnFHjPrvrculftTfy4GnfFE9T7rJ59KV09kfN85oXfIsvwIr71d7S5I/VPI8Q64rwa9qhGHxr90wREQaLWwV7ZjCuC36Ps80vki4DsQvWorCv10TfPf4ZomncMpndQYWsho3W13dM9whNzYphqJavfptIYj+wtN/EX+bz/ELTnuvvg+Z6VlH+VQ8MnuJXWky5E54Ap5n2efSHvk+27VbXVsrXUdyFjc6wE1WdPs7N6DfeBO1myeBOZ1R7Ru9r5Hs62GnI0TbdXyjq10rbygvUpuMjpNBmWzsWlkPNbS7ae8ZXnEMsGtQ7SKyffHlA5VCmWmMxZuPApWvnFasGesg71r0Fgvs5/0qi+X6jEV+wCeGBjySC8zUEV7xhdFfJ94WvJLj8HYtZ/UJwh0oRgEtmqUuL8NC/Mxg0kWiXNxEz2M9AYSDcIlbtACAeq8zCHqUocI9XfnqI+45VNIMLDyR+Jy3fr+dwVQF5tJVXjhkln4IZmcpicE3+2DsnAA5Hs49By22f77cznuCfAicB+glO8FdBNDkJCD/pGK51xfneQnWGYNTBMBaqs+WGXKUfDpYYHqNjlDOo++PuXwf71WHfmvZtjkfhOAsfR0p8L723P3DzvF/t/1mra4wzFhkO7Wl8V7cVHMZVES1Dqg3fB0Y1b6tUs1YoPBFgggGu048Ohqzv9r0/bO2u9zFrY1GJJOQZtStHK7rEJdfgfE54izcACBf/8wKbzUMRtoGAi6sXICKsL85BRPj0r/8uTLN1aUUUiDuOWgO4/L/EJObFfAEA+OO//0/5BjSmL2nQn08JtPXVw6PpT6p/H1XgwvdinaW5RG/ArT3CbwytoGR0oH1a2LEztaplzwBlLcZqEAWcQoVRJLU/A6BWM1hNICYG4xwiIL4r+ZYyIGOeFNeZxkelhV4hPIeioQyoULZvw6TC9UQbUJqQScy0mvlWZ5jOyJiQaeo0z11Ar7iKIQJatftuQmCYRncKbCfV4CFyc52ghooxYbB+i33jTy49Y0C1r7UvzXdjSkjIYErgjRr5tIWjzDwwu4sS9R8vfswzkOtFlgjgpP7lpwlTIqynSczRg8FZtcAJSGpWgGkDmpXZzQzwRqygMCMhIc8s2o+6P5k1AjOBndWGu2g5KXtcTYqzXkCYC+OPYWrGzMZMj0YPVaveXmM/NGCa8R6Nimb/0tkpCuBjlktpjvbj/ZQw1EQ/Ij2OQ0VLNNUiVGYZGrzMGC/6WN7BldR9iFL1XqqjFbG148KYXGLE2MyGaer0E5Fbj40xCrPebNNGJ2g17Vn1I7X1rLBGwDXYCt+K9HiqfEs/5l0NEbO0r//zVwDAl//zGRm3wZ/5MkUcR9C0/LPuFCtd1/sIvjckQnQ7v4/GsBXuP6afrE5rlnyZ5Pc6uV/4TKHlSmtGgbh8mzHpBTK7/PmgmuexjuMuWG7BLVDw8bkuTPOLHgVG28D6Tj0QV5drCwXFcH/ICrPWv0V/BQ2ytd/slchKXUP2G/nCxTqV1VrqguLmqT16Pubs+FxAgF55dOH5/idGpwMt/miHde3e+tutvl1o32UAL96+wt0HMclvGtQb1CbCJ5jgup6NIwF4VYeAJ5V0qnAzh1Ruw0becsg/gYqRIAC4BOGm/HoZ5uzgXPM6g4k8ueAWKyuak7dy2zpxVav456dqG7nokxxN3kswaeyXwY8IgfCFGJcs7ZDLpkJfRguR1yQr4ool3IToV4pjHkIdXrEIw20+LM2y2LoY531ivGHJ5zPJtZ/Y9vqiLPyL8XiahTnnjCklcSMU+yMlbOa5cTmEQrOvpxUyZ8xzS1DZrJG93Gjcs9UazMBm3oRYXS3LZWM/GtQVrr1f2EyxC5/LOLT6Mup01o0jdGZcIyc4wQm+PZwE6Cc4wbNB2N4C46YTahcB0R7bIcebnSMSBiUv3pNLsT9J/g+DUYMJlc95oVd6XXRCTRSfAKBTb/wwsDTSZaW0h4Uih9BjZtAaK9rBjfalMM6bS0chSizhIIZs4Zi17NORkMQhhXgU6lvhT2OEtRlQfAxG4tiEXXBNxKZN1GTRbhWjulITp41Xa5237aZSNwsjTdTW5VvCGSKjomaDjRhihBeAarfEb2t4VzxA/fJVuVStLmA380sM6ntqXzjqotwJfmiIWs8GS8Jz/aq+HKM2urKQ2QTWYQaT6G8RnSPjHqZtTYD6LUdJI4yv5EL0wvVrMQjMrZ/jxwYZicl2/YX43aZkjG9GxgPcYywV/bR6Xav+WbACIprgmku2ingdCgbRf2hNuqZJTcCLxrSZ0wX1bTPmruFPjsiYnbVaMIpGEtP2ymxlLkJ+40QKfsjgnDFn0UrPzGKaUoXrsYxEhAmEnIA8rZBTLvZ/mTJyktZmMiYwq0Y7RCCfEnLOpY2JGDOZmMJPFVZ/cctIpQpZGYLFakIWAXzmrExJnx2d9kzgBWqFAc3nGL2aaMrT+nebsLyjN/5BcGiLjt+VXHBwSCXIl+R3CYSxn9rH5bggPHrGfnBhD9VhT12HHfm5T1ggTeY1d/9so9Cp2nNwmJcZM60eIWqCEg7TkN8HHqgWFF9kz39XMQQg4xqMVzBxHavg2ISYBivsp31e5a/r8o4Y50w4Z9J8ZIXf7BrXhTa0grZetOjx7Ldde6Z5njmF8WGsdX/L7PHcX7a9OYVSaBuIAL49J8Tf7wEMF90cnbr3DO/YqO6V2qlhRa0hwy4VU9HSNrP8EV8SXDP9Egm31Ugu7xNFC75cqiO0s2OkzW40XVwPkfqytfZC45wjCvbramTUWvVxfppAfXQphKsUNfR9LjB1Meu4I7D6tDjK/KqLnab+u8EVi2D8NQt+uFLS84vS5m80nxWTxu33rSVo6/wxiQD9JaDugNw1xaGewHKWSzMpiSa6jXPOjIlSqWHmjCmMEDMjUUIm7ujAlNSnOJuWuNKMB61+rvj4rTW3Fnb2ZpCvc/iHufb3Psr3BCc4wfPASYB+ghM8AxhzbXmDa7fEQ4XnWoqdRkqhktcyv57Dv7tC/9kwGps+rBcateR9G++p6vJXQlufJc3zE/Two60iO3KPVwANJ8uIwc0mUAjv2wSPoy/7zsuM/iJSu66peqKi0Wn1R8Tvg4RRCMFVTjFiz4Lu3kt+uvZ2CWMHwvW2enEVx5VNoRw0cQht/b8dmK/C1a8TGIRpPWF9vgYRsJlnMAE5z2IOepbfF7+eAzjH3W9iYO8WX7q6rsNzWqn3OP395f/+LwDAn//rf4MhN/ONYHZvkw0sqQ8ciQSW+nbk43x7RoQoACyawy3w1lf0o17HaBTyng2Wunep/q0GzDLsmN21Y9Kd5Y/ohL1qEaQbbqqQBhYvImMxsov9L7Hraac3IqzmT4K8MkyYqYxRin5B1Rd6IhBNSMkE3aEZLS5SzfRWyF+YVEGjm0CgJGsaxKrZ/CB9mObi51vdcBfLE7UiegZ4UgE4KUkshm1Na4WZkeeMNCmTOJpxrx6kF0Hq9ztytTQesbSPs5RhA27jNSVl6Zr2OHv5wgBUje0pAZyRN3PZ4+as8ThLtzIjzzPmeUaeN+DNRvdIdisASHoJQcziJ5sFmZEmEdCIMrg4GadJGdasrjBYTV0mZU1mqb9oqmuPEEAiwZA2mKY+B8a17XEqPU9JtNZ5juz6uA+65luj8uXfw9wiSkWbfQQV772k2S1E/+5gXzxv+PaRmuftuIyEW6MESwz/Nu3IassoLF6yGJ1FU2CWD0u212Q/EjCbz/Nu79NJ18yDDVt5yrTmuqXMbcvH83uhloUePJQ+WMr/cNghqukK2LPEPI7d0bIa4eN//7vE2FQRx+XZvJwAJL7ATLeaWnHnfrWs4IFEEx0wf9hShoU/pRl3gztSn+jka4WA+izB3h4TtmX3HlyJU/yyk89DMaNOakFpvGpiqLk8EiE6444YZ6zjoj18pfP+mup8AOBehe4myLMThDy9AOG6aN0Ctj97PQjug5qb7wl2qU46aAO5vOUXAYOQOLhpsn4xdyRuJN76zR3DWN9F4eNftTsw3De7mYh+AZ8P7md8n5rGUeIutMYENea1OD7/gPsPn8u1xoSXmPGlMsBkmtpfwLjAssAa0D14UEtA5iBxO6tjq2pnZ3ZZgpCwgZj8b8H69QXENc4d3A96bH2cKwyZb0nLFN/l7vKAUM0+p2fgfRt9yDOANV6B8bm64LJtvzVT7NbKll+g4l9sQHpR3PkxGaKxbqN6xZ7fpHlfMXBNZrpezrsTM65A+LJQpwgMF85H2BBwxjBqHjmRtl/w34w+TZsvYHT0DMIk9H/m0g+xJxIlZB1701oHgFWaMGdxXhRn4kSpohVFmE44m1aYwZjnekdp52oKm7itH9nbY0yqUy5ooTexADDMar3o1pFvEqBmwmzfpJa+fqfU7wlO8F3DSYB+ghMA+3FgjzxA1fw4Do+sG6L6b1GT7uVQzgt5NPkMw484lP9jwalbh+YsQW0YnLGK8CN0S01ol3CKoTj1/wl+HLA1UtCPHiN2aJ5vg6iVXt6BIoSofKNvyW7xU4tfm/f+TGJHIzcDaEyZev1LQDw8m0AhHvSt3tJn2poijHBmYHs+cgbHbugEV3WXeovIWhbCyQVnVXyK/dNrwH5boKov9ukGGvwWywdNWNU3RWP2CqSa7DZ+K67NbFabxB7wVwhsjiRftsI+ZNO3rsM/CaIv80J+KAIQXENDXEdwc4JAP5cFzlDNWBUyTykhv2HwZ9MeymX9G/PWTMKL6faElFLR3DBNYYYyhArjOlawv7LgzCevT0rkjW00liqT8SlecArX+OyiCJObNFQNbrUirjhQMXgRPBum01828/F1G/r6cyXsoCBQs+8m/GZI2eVySebg1lC0zZmNScignME8i9CZIWbYZ42XMzIzKHNh9sl9Ae970epPyAk6qgnEjHkiME963iBMEJOYKSXk7H7iU1LtHp1wRa7NzsqOfdGNL5nv+DAndCNkrWuZpQzxq65sUBrkG2mGqFUefyO0muW7NNF/VNjGsI9xsGe8No6E7VPKNqhn2GN3z0PTP+Y4fUyfPRYe6wHgOcAEW5kO15CeSQRY63xZhD2Aa8JGYbf5ODch0TFa5N9CeG5QC+AEaOG7aZVy+Oaa1tclLKYFtvevWWQy4WjFJmmIDdNItzqcM+FOiRaLG90lWd0RwqyQWSPEtgAmuHaBdhSuS7nBzQob/eCZse03oeqi8er72KSi+PZskzV05OihvD8j6e5944USfC7vBqOMatxZa3BHQW/dHz1uonLejZY50tsJqw9ULhabYJYBXMHcuXBVatj6NWctsbsEanOcmnbU8Z2C8xbaxYMVevrTYIKbbo/QzlubyyZYju3s+gP9vI7nR5T0n7t6jeoZa5cW4lhai2tevKPJ+bZNto4tTgZwyXWaCULHvYSYYR/VMb6bIDy29Zp03bHj0uqsreXusmwByIWZzIzJXDEZbV3OH5anWuVIqdB+/jeBWWhog6QXZS29XNJTIfyW+lS4WqtQ1k67gKie79GUe/RiVNEbSnRXZKshQMNz+v7jUrEnOMHzw0mAfoITBKj2Ou7Dqw3KNjyu43PzPSYom+NA2/KQza+YOlMh/FCIQeh8xQyijKv6D4Jy6AkERmFK79nw0dhQ+FuK89fBt6mNs6r90HICgX/yGjoEqCL/KX44GDo8ueN9mEdVt+VI26pH1cyPgmYTXASBDjVzoTlQlt4ZhCM8J6JywKvPYa1wTHJYwlHb36nyj9au6hTb1aV83vVPADjPgApB5ocNEkG0NhOQ540ISFQrMquv4LNfhd1xTj+DiHDzb9FWuld/i5ElwyGAsxybr369AHCB1W8PABjXehc/+v07VPN8l9bjUr8ua57XM/TwgRlwNdAz3vr2jCmIJbrCrDE+/75Rl+hGtZfGYEcNW5uxTwyEZdpktKZb9xGpGU/J6h7ABRjBpLuoewuuUa2M4ktcBehQHGfC5kRJtdAbKwYMEeZG1G9Cy1KVeo5SSioMJ9VmF1/chBXYnrWsaUqgVcJEE1IiZXj5LxMDnEJdhHHOAHJWAb9qSccLXkQAnZELYrlw5d3axxCR+ho2Jn5a1bZ5qOBv0zbP3m+rhFm1yHkzSx1Fgo6s2ufzZoM8i9nKXFyYZF1DppvnGupScobZlSdlXFp7MhISZ6SJEJHWapUxZ8UiDH3WS0K6QUn/yDxBVmypfcZhnwLXZnQBIJMaezVF34wiRLeWUCY1C29a7VzeO7zU4M9WQ30RqEn7SKKtnRZ/GQ3Y7AuHnSVdOLCLmc9bvrXh9Vl6R40WP49onUBDWeieDTa85/dcGtF+sw0WH+pwr8sAYDqx4ZpMV++Yj13e6Yi9utj+QxEgxbdBu2I5AVoG35IgeDl/D1np5r15xI1JS3mmeMZoSBcIHpb3Hd2qhqika4Xn0PeJ3SzzPoJHEywRHql9/kiE0ApTZrTTiIs2OsCVEK/OZ3tFqEl3pvk/AMXFEUP2UxOiAy50j8Lz+hwjK8Trfa07FsLFQMndtamhabibv1H45GuDwni5oXaGC+Mt70vbjzRtHqwvy+t+a489DyygC9juLT7RGXeOafR329mCqhiV9RfUovoWz1r+8bKFUpAgvALUypebD68vxF3o0+2O+bg/jNtrQma1KYZZny221X+j6WyeeS/6vLV0BA7PdbmseUwQ//StkNtj1+f0DHGNYNYOoiA7tsryW4XwhHosucx94FYLudDyTNCfMb6gGMkHe/6UGK+IkCAWKGYALxn41EyKEY0wQpdfCHhNCSuYSXjgwuhnSN/tFqIrns8z5jzjbC0YJypuFDdCNn8ry0VuRYuRAD3jZzBWdlYi54kYvdBqoo+qWGYCWx4yvsUSB/l5C6G+xKyXR5ehKNhZQIbekIXS5v7bCe33gN1Y4wQnOEELJwH6CX4sGJ3uQxA18YZ8s5id8Xa4jjPi5Yig2zfBNs6QARTDbJNtHKw85mx3bNq/C4zaVzE1mjjb+qMIybpIQaAWbkCe4AQ/HBQG5JhD2Gp6VT7QAywyw3n5W8ujbfFwxYyI4cbIa+KCLFxbE7Q67XhWmXG3BCF9qHZfh/LNTd/GZHKwpcbYmDFm6xyIux6vYWE/i4fw2K743duzHO/ZgLyD24NiVzuqR2vUd3u1QG+5t6ntdwUARzBZt2k9Ln2RqvTz/zlGgoBiMaHzY3xohQ6scLt+fpQtdnEehOfaj7kLh5OpQjSQNE76yX2Ym4ZGAiGrUNqwkWmhG/OJTIg+RR+DUKsgCFodVJZrEStrvlY3VuF5SklkvCa8BwGUwAmY1FR8mhJSUuE5Eogmlemngo/swk/Bd2pinRhippwBuiTQRUI6S0irhDR5Pb2/CETGbrQPPutEo83xtSiSBITUmWfMlcUp2ccyeAaKwJwzKKuv83kWLfNZNdC1/KxheTPrc9biWDTUVbgOsJidJmk3SMOJwNMk/myLCXRhXxLNyEhAlrbMzMKjy6wCEGHRJoivdcpSJ5dFc3eoKRc7FGcU7TDtzqKJHpygO1NetclaYfkOLfJK87wMB1ffv2uz7d8JcPM7+t6jFw5Px1MIkU4alT8SThwLOosX8x/Va3tuW2BL4i2sCbGIET6ksnaw9RK4ryWB1o83d0996Wv2y5KECyS+LYLGeaHwkaBahE9U6sxkgsrj16Fpou+Op1aDICaDHxaGaUOusR7DviVsyF0UtTCabxTCOQjPt/WiaZkToKbcHeI6vg/xCbWLIyu9FaJfMOkY1h0lQjsJj/cNdccK5ubNnPYVbvRSK2Cm5xtcUI0NlTNaYpbLLc0B64HDfgPohazeN3Ss230I71v/vDAaewuzPp0PqpW3urVwFqiZEqudVSbIjdiC9GF6l3D33oXTIlAmqKOZRlArJZwDlVl3rmpCIZybGm/Dxe35rt+HBH/xIEUPref2pb1nA1kvZ3AXX6Pxi/kmuKZ461M9po17scXdeTZgEaRfjo8BAOrxjEsnQfyjZxI8ncFILNdaX7L5Sm8qtxBU4VIAazCumDqT7V9IBOiXDNws1HdrQbAziF8GmbP4PrdvBEZKhMwZKSWsUiqXPQE9B4W8UkowwfVECRnzTtqAUZ+RI2b05wZfhtcy9u2WbIGhIKYxjfXceOoEJ/gR4SRAP8EPA8bf+h7YJhXTSR40fFy7chBmYEzGKZlnTKJFzXMnf5c22Uik/ijQ9kU0dUzN32JYVFcqJna+YaXrGn+TVFQ9+83MQ9IdXqfl1NsOJI+BXcP0rEP5NwVaelsYJGoEP8Ay/pOP8ZG35v3/s/emzXHkOrvgAzKzSpLd67lLxMyNuDH//0/N3A8z8d73nN5sy5IqCcwHACTIzCyVZLvbfVxwyFWVyX0BQaznYJvxG9rlnxL2eLXwdGZi+/daY9R2HilrIF58je1TGQcVK0tF8R0uGtu+qmfnfd/+9c7rrDVX/4+/vjyc/qmsuvn/mHF6elJNcrMiK8sCSoScVLB2vHsDANXFccoZRITD/7wBAHz8MAEieP+v3wEAvCz2qSzZp/9Qu5X8D72AH/+bsjnv/7fOgVu3AvrZWSo9gyxeKsCJlucxb52x8XDyN9Tni99H6+EIe6wl8k2xMnPaYlHtPf0EeDH9dn5tri3Rn1nLL409/wJ4zrAvDftT8VLfoE54jp42IRyrgl8LT6CJCAC+I+B9QiIBUxOaZBAoJeR0REoaTzCbMBtwplWBEIFlHvCnlpNShltEq+dFAlGxWOWtIQQgpyMoCYSyCu8zgXK2vZ2QKKlQnXJY8ipUVyaYMRg91rsQ0g2BbgC6TWZB7y7opePsEiVQ6uMrbym6uOJsldFWDn0YdJFmwUqmCpW1fctpMU8ZGt9QIAALimhsdKl5CTUCLAtQCsAMKQuYGS0OeGBr+/yaIFwSAZKQcnPMyQRMROBCKFTMcweBSUBsONPK50QgZrBAvXoQqwKBJBSwdj1Rc5lvTEgiMhf1doZF4YePkburr8NHaArCUvFe9fJFPZMTHgt95f6rrUHLuMK3Me7qbkisF8KF6P+LwGtP4a227tLZO5V4+lSxxoXtOvOyw3V+mO2m74kitUwDylKQcsJpWeocd33r/aKuizfPDUX8pwv+hoPg2QuEL/Bhndpjpj3832wM4x1EqMXrBjbCTRi4sHySZuWXpWGLGk0CgtLRA600db37BgmEAkamO5AQmBhJPuJkDT8MGqw5fN+iuUlQ3X+vIPpCvhBG5YA9EE975v2zQvNPxBdx7k5xWQ/LwwVcFV0i3EksZcT+UQAONGH5KDSP4II/B0Jz+R4tXj2GurM2HklwYy7co4cJb2+zwt3yr9hUhpt76Q9VkcDXqq/RLbz6RMAx4PcYtuAxnjs1o1gfXo4p/7wbTg97rrdlSKOCaAypImytVztjMe7PXpn7aN+a9bXtIbzB/POkc/RLqXPp+6rFnScs9Y6rK/WNfStAFxt9L9THmvKNfWp5HgAcIUYrt/jkMwgZb/CID+H60kTyrcfe9v7+ktDu4oprubMyJ+uLC84TBAuaIJetJWw9eagW2Dpmk+WdoPNIaHvIexjx9YTeUt3b0PrQWqYW3YI7wWoUXXi/d3vLIihkOErUnXkWwVsMQvRV3vV3QHHGA4DvrT0uRL+TZn3+VvTv+MOP+Ncfv/UFDLT4qejKmmo4KVRlXoLFNg9z67R8ThmFCyZTyC1cTLGyNZoIWGrsc8Uvh2nGwqV6txv7l+I578q7AESG+za5dbyWPSrcditci1K63squoZ9kPSZ/Fa66whW+NbgK0K/wbw/xMAq8rW0Iz9ckP1YnZiRaxnoE4VK8dXmvr2T9RjYaOVie11qvlhSXwXgLGaBeTAOh6YzAcV3o32B9Gosl4Gxg5m8A/hIL1Sv8pUA04CMKz8d0iOzBDfw3QHMTu7GRbVNWXOzM+l3G5PBc6n913+reX+/36vYYLqBZ4++N4ra7JeGssG8Cd0nWUhOo3bG6u1YTdIXR6Pt55llUionv2uzQau7+2itaOwP3+lWFwx0y3mLKAEiERP09dPzU2NJuwSj48b/9DBLg3f/+ZVXmS9x9vsQCfUx6sft3iWdTvKC30+tS18de3lD8q+BKsfTwnPA87lfHF6PlucPWc8cssTS3JgegrtQdwRCDcFBXh1BMl03gnNOMPDGmnOHSTQFDOKFIBhEjEZuAueFLFXirJTmS7SW3Qg/7OZG1y127U0bKALL1KxEmSiCaax4CIVWc7WJ0G6SDqKW81Z2Sxjkka0/KKjBPpBbwlFpbGLTad63Ofl66oe3mMrA0zX2DxjR3i3TWP2YUbkJrKfqbl4JSiuIgFpTCKKWAC0NKGWbUhjTZSjEOr5KiqkhAydy/S0KiAiZC5oQlMYQzJBVVDGJBsjYxACkJhRmUSOeaC1LSeefEABszWgChIOyTxtT0Bnaxz0E1fTvXmkLZ1jUIaOv6knjm0SL9aone4HP0+pIytkUi58tbbaMXlENAVSAXiIVAAFyJoj/Ktmo63z4X7H2uVTP2a6RuBWvr8zHdGLPZBS8uCBU04Q4BSLgFQKpgAxUQTRCIPKobdGiMWcWlR2QACwoK3RuevrOyBIfakJ7HEftUd7sLAwwmnI/P/RJ4TnjudNlsQivIdt2viZF+CRykjy0cn59b2Fuk17hqxyLOCW7CBB4AACAASURBVMw9/db6dUG6j8tpeA677wihWqAfhGq6cR2PCgDxrWAtHPe0o37mKAB7CveyFrrE6fitc9uF/J82uX/2SRHHo3kDa9TcS3qzlTbSXv1T6uYj8roSWhx5I+DsOZmSjT4mNBfoCdKVUfEazrPJIt27naDj6uqjoIypj/XufMJ9FWD7WEYB9binUv2jKoQdV1CMgZ6xXutel4cteAjNduUPF5x7fRPC2Azl+bgCjS4S7WJlD++t0S3c48+97fH3OFfufcy9i2zV0z0zEn8rnXuXeCMqRL8nVSYAmheQx99+e7HCMpuXJwiQM+GQJ5yWooqp0PuFWqUTpuQO/tXLFYuYQnJrcaaEohJ5sFmkTynjibnmPYsTxuVJ/SsH5e8IXLAOn08BKjOLdB3rRBp9zBSUf9d1XOEKV/hycBWgX+GbhK0zZouJ2aUbD0Pp8+2dW+35S8jvPm0V6jrBWG8YveU5nIB4przXtOjfCVr8rWfojWCptTfP8WLQnil8+fF9HbX0souXph4FbZ+vhjWMTJjPPY4vLe9b3SeXA3V75RwhvyU4bPYIPaxcu184Ey+5R7SLdn9pbIyD5nayClXD81jnucZsMYS38q3KdLxDLQWFz+f25TjcUUFoq14CqmXrGrcNv/+EjRHdW6rLyjuACMu/CvLPhHQ4AERImVXolycQUXUx7ZacMKGd2OX35s0tRIDj/9C40Hw6AUQop8e6iAnA6V/KHsz/3Rxbmvlp1FaP4NZFr2EMr86RHQZCZ3ken7tgEqqE0Vuu73y3xRkZWS1281YLKZIbL4KXx0DfOlk/P4dgm5H458PIfIt7MlqgryzM/TPi4A4OxuyJhKu9ElQvDS0mejJX70BCRk4JU06Y8oScM3LOKuSG7q+CAsiiFsXBslct301APamwmjKZu3aLeistZra7aAcJ0pSRUoKGONe2UZos9J+3LTUG7o2VbwgueYxAkFmAJ2NQhbMmCmITtQWdUhX8OkOLiOoZsFKYtHTN4tmKycaaLDruXNSynKDu8EuYQY35DRWiQwBmLMsCLgVFtI3MBcXctws325qUyAQE6pY/5wRhhk0rPJ44pawu3VlQEiFla09ZwCzAlJBZQ0NSWVSIDkASIzGhFAETA0k0fCQxiC3GqMXJBCcIBQajEFJide3PYuEbte2cGsNTz7qe4hstz/fB8WHgKse3bUFuW6J/ZiH658Yjz7XuNfVtHV8rWiTQHNtlXEiPrS7X51tcQ4R0NE8kXNZ0CQDkbF4xLFp5Mnw2Ua5WhcebG9zff9yNFdoxthvvWt/V31a/9DGD2/89e7x97Q/O50ZvLEWgwnSP6e3s/jTkcbu5adwH9sn4CMItBB8hINz+9CMefvkNk7wBUUHGAwhHDXsBoICx0IdqbQ68B9CszsOpUlsRhfpV8Ys0tnW8A2TQvhv2rYDerwBvm7smJ2ljsyls3l2el+MJV6Z0639Cb5XvpRHaXLoF7x6Vs+Xm2f+ei9m91/JDeO8xz2Md/tnSEU62Fd2DAAltuHvv6479cQHc2OZ541ktwwo4hI486mUFRyMgGCpcB3q87sqvtTE4M8VfEfg6iHPn9vzxpPTfj7s33xbmRobdOoriXXhOENwggSFV8PsmYLcT7jH/8hbp54z88wHll4KMVPeTq1cmSBUKu2qc460ZSgfMVud9bU8bAFfido8CkXajLr3+fgJwZ+30et5DcIPmbc17vKDhTwqfTYisIdSaoofjNcf10gmgW0g06fbqfTeLbaw9jQviC3QPLGjKBwwVMANqqU2k9DJTE3TfW7G3Qnhw7SDET8IDCd5IL/T3t++s/Dd2vrlluis8OghJxZ3fhXxeU0+9rcHDO90nwo0oTnGX8B63/QHAm8rHHk/57RqIkoZAgt5NmRkQYJ4mHKYJj6cFT8uCU3FL81zzAaYkH4r0MFcEQc4ZT8ti7/Wi7BbssYVxdiN9gHBG1v0cfrR7hgvRh0GTmMlGIQz2qswrXOEKfwpcBehX+OZg84zZIKrHdFuXmk3rCOwIcIZbpkB6xs1GYdViopofPsN4+EQ+0OdlI319EEdwNZo7cznmcTJuvT76VKubzzcGVwv0bw9GfutzlueXwqWC81VDnsnmzLThzr7GE4Z+IzMwshw2vYiEAjs0H5+jMRVGZrR4vTGP+U/0mLFVkEPnz65Y6Eqg3vWV6rOK54JFfvhv7M1fCMN8PHNMxv6nRGoZKs0qNn46UwUA8qSX7uPxDhAgScK7//wXAEBcEBf+nBHysp7st9Vhz3KyJvW1mlDdVQOoVsDMrAINMYaGWRSZzKsXpGNnhp/bvt8Y6k+2T/kT+r23fzucQz3mJKIaSqBjqlTmYizP1qgJL23qkZIykqKVcBWgi76b0oQpZ0xZhek5ZRUOi4ChVtSZkgpW2Rk6itVU+G7C8EzV6ptohkBdkbtcJpGmQ1bL8Zxz7ZNaj6dq6dSrMEm1MKduDNTiPFHAkeRW7tbPlJFSViE7tfJ85BoOFMO5/V5rcxTGOg68uOBNnFNmQuPmql3MIl3dsgPConHRS0FZFkMq6uJdY6Avtv+b0gORICeCSIYkBotaoTtzDsnrBSSp4JsFQGKkDJQiAGtMSMkCnNS1JYmAUwKVArjLdndNb11NopbqKSn+ECa13EFjEALP3JciAq88cluzAeetBSM475FjJ81Ydp3Sb9Qi/XmonFy8FMGPI/pyNBldDZ/P3Xs46OsUETx8/BgexNa0NR3bvPcb6GPI8ivGZWzgqIADhGfQvZU3qnH8o0KcG5Qq8mptjzOn1o0t0mzOE25++gGnXwoOP84ov2YrSys60ftNWfbToBiRjXhYC8RliIu+NZpfHiKO/pK7fLbCj1v4Tiy2MHoLbUG/s7Z22jiPq/BPz7UrlBetv4G1u/f4Lgq15/DMz8Uxhruvxy3lXgLMo4FBGKM9y3kJnSao2+8nQncO6LmrHhGiEB0u+Aqn9EoB7iuHUXEi4iT/3qyGt/EQDX2PJUSX7XFtNbvxgR7yOn/KKL+4yscHMMj2uaowRTfjOQiiqasjlt63XcL/ccX3rV/DOL8+LtnKKFbXFNrSW/n3LYjhASa0FuXwfEuZqbUnlmp08dCzOKe+T/39rTQBc3UUtVHHw9ZghH5IaPMW/pPhe2u3rpD3pIJzgp5D3wF4t1flM/Bg590MrOOqGxzFlGSeBTFcY+ogRJgmC1ckgiknEE1Yiq7GlAhsdLcTyQJBQq4h4QjAUym4SQm3hxnMgqUwmnKeCu0dunvB0Lb1imqPV7QRyyq2efSoqAQ82XVEKg6O3sb+ouP1Clf4puAqQL/CFf4CuMRlcQV2iomcE9e+R4ZfV8bALEJPOI8Es3Q5vk0GUiTs/XcVOMl+mr8TjXJpW+N6eZnl+eeFL7ESv83V/bmAhs+/H+y1nDa+R4tD3xMjLlU4s6p2bvlRY3iMZ+Z1x/a4MnP1nmFtc0PL59xAj32L3yNrydtcn1H4LuvMf+Z+ynhb65v+a0YiAvOi45JSdd/YC56HszClKsACCCnbBTQljS3sAuefE/iXNdt4eXzEdDzi+N0dpllJ6Pv/9x4CwSN92Kl1DdueGMY0G/nQYvT1T+1STWEOs2rLT1PGfDyqq+hFhZbuMpqTOimsAi+7qVcrQGwJlXy19Cyuzwd/DX7Z5TukrYfKRKKYxMiwzxW9ZWTzdvtVDuawPOx9mztN9wQy1nZjHzvDUsC/M5AB+sEEx6TPzWZcSyHHMbqOcsqY8qTW4aTut8FqCV6FwVAGUDLiiYiQklpFp5xBWYXXat2SUdIJSQQi1pdEyFMyAbrG2BQRJItPbmJxQAJz9wjb+2qB3nliIFOSqVbspG7bk7t1t2cmQI/CbUpb+NK5l0qDU33hSg4hA3ssc/1TK2yu34VZhealoBSGSIEUe14WlOUJy8kiiIqOA5cCG+VOp7Z5D1DX7MncUia4kBi1HDIzpsxQQTsSEjGYBUkELAyGQIoy9MBsfSMUJmDRBadWUgJIUlwC1HuJuvolY1Ia0zWp8NtdqapLeKlrl5Kmd5o73G6GL8M+qUL1gLQ2Mrqy3Gp/joj2KxOir7ozwEv5pc8xz9fPW9RYtF13MbT29y2sZ1V9vDvBfTLy9aO3k1T3uVQaAGjT6DFLs7lthTHS+/A6Q9vqcmptqkoX3Na/74uEdj3vexzD8sDWn77P0qxJIw1YQ4C3rQGgCWbjszgX6pq9F+Is1IcUr8x4qCA3CfDHf/6z4rHTb/rpwq52dsDa3KjfZSA6y44HCGA/5vifCU4nx7H7nG7kgWbZPsZIBtp8+jMXeB3Rz2OkKeLRHgV8vmbOjWsUmHt5saYD3uCED3V9zFAhtgvER2H6hF7IfbC3jyTVG0GkUVxAecJ4DTL6IKQdrxZ7v09EtX3j/cUtdm+kt0bHMO6vhTHvp5wSz+F0oLn8vrVPt0r2nD4uGmd8q4XP1b5uS9zzT/U71fdeH6B4L/+U8fDru5omWQ6PCf4Iwh0cB/X3BbeLP0GF63dhxQuAIoIHqHcdGnIfhTTWPYDbroVruEWLXe7nBYMwW/oZZEL/Nh5+0jGk4uaGB6Xbd3H8OLTSn7+x9A81t1RlA+9XtnZ8gGCCmOt7wqO9i0L08Y57Z93+2A7IzXHwmOO30qzaI0RLd//9JozpW1Gav9ijSYAfRMNe7MVE99b42vHf5O0VxRNvRc+qBwCFNHb71v03lpks/FL0FAUR3B5mkHljWkoBgTBPE+ascc1PZYGrYpBZu6eUgjKltnRKGQTC3fEGAPD+40c8lYKU9I50WmRY0UMbgyA8UfO0tTJioMbb2SopJhf/z2mdIAdQ+p5ejeT2sn1d1PAVrvB1wFWAfoVvCy49CfZOsQ2rr+4A9QPQXbuJM22kt0JBK0v81j1ao3verjy7nnMUwatbHZFYhJVdKTsCwPWgfQl/qLf0uTxX1w4nHHYmID4VGh6E33EMXgtKaA0afqDhM6T1tsexDUIKj49b4+vZfx1D7wrfCHz++V5vh76OuMq2lGT2ytmtLJSrX7QGAbCizZ2RicAMlS5339aGCFbP6zsZ0l4Ebd+ODD9Q27s0ZrHEWwLy+G/7BuPPz7czJt9LMaI7fbrGurT6v13094StW4VT/7PhOPt/xH/deDr+k2Gq/zRUt2r9RuXnG9MY7K0TKlOSdokmIP0j1XV4enjAfHvrGXXN1vPNGfc6dl5OtLRp7rWfaxuF7+tebS2lyrwyiZ+fcVPKOBxmTIdDFfZzmVGWE8ppwVLUHfTC6v6eQ588Xqm4lXqoa1zxn0JWXZ7TWXmRFfPlwdfCOOgp7ItxRV7SOp/nUTbv7tnd/fC4J5McAJBafFu6Wl9Fwa0FvhZc2B5jn4MAeQfI96E9lDD9qJbg8ocgp4Sbf9zgMM+YJrVABxHkPVDY2bZU17+7Q0zfJ+CeME0T5vmAec6gnJGyCsfFlEBLmcDCKFKUmTZlpAlI+YA8ZbXYE277S7wOUZL2xixGqAnDdRNQwE2irjiFq+KSCs/Vkj5P2Uzx2/x1Nu4E89rQc7na3FvazlxUqttyQIXTwha/3ATnzAVS3CW7xjxn0Rjoi8c657be1Vpd92NbHX7AmceMlDFNgsIC4hBJMwi+QAIxl/WJlUksicBFFWmIAZFJ03FRt+ylAIYjU0oWilGAnKrrSWJWt/RCyIY7WFIVonsfHOcKwljSsG+i6TqepwcudcVelUX+RCH52LZLLOdfXMcr851rge+rvp1U7zwvKfGynq5Tde6Xrf6Gd6XSnomkCqYrPvY1Z2upnZ/NTXEstbtV12q9TNlsoSC6/lXaiJ2GiOemLWciGz/p58zj5ALNk4mn8aZsjSHhFmzW5N5C31cEPaeK7a2t2NKFBGnQKHHBeBaqQvEs5s6Y4pi1/x0mISwXzjYBg2X66+C5MmaE/lNTJNg41j8JPL76Hkm8NyojJTteNxyLj+kjLXjAtvvzcf24gI8ALLhXQfOQ5wlYWZVHcEF7TPcUhOixbgmfrR+BP7bRH//NA+lVz25xLITOg5ivp1h//Vb31CUzvr3Xt9b7p8KI3db1RXAVx759ozeBl9Yfc7uL+O17hqcJc/SrCqWLtcZxzWPIwQj7LeAPhuKejgamsZZG28SxcotjVf+jmmOLP+h4bwt3e5l5YyYYrqrY3sR1HMc/ngMYPrWN7Q4TQdes1PruQHiEVFfrRxBO9v1GgMfqbWHszNaM9eA93BKeR4iCdE1PuEVbG8VwKKR9vsV5IfoI43gm9N5VbgXBR0oPyRQxYYqhtXMGzII5Jzw+nVRZXBhTyThME3LWSPNPy6L3GD+j7Q7syrbePnX7rrzz4zxBBKp8bohnvA/HVaRrQu8N7qHGz35NrJtFrxUtnFHTCAijRQ13+TWEnDfHACVVy/AWRD76czyHPe9MV3g5nMPnV/j3gqsA/QpXMDh3maoES3c6+gGKah2i99bwaemEAZibxihMb0IjaQcngMq442ZNI5UZhyas9QZ5MQPqrhr41lLeIC57hL8W2+wJZ56H5larkfvr+senYxO3iN79KtfEaf10IYelq+8EQVOQ1utANr4GZkxstBLwXkLT934OvjS5cmn5TuwDqAz615TzZ1EQX6KalyuLfHnYalHTuTZLQGi8MWXi2T6uSjp9QZcxbjVuqqevfAcXmhte8nhRPhuR37lZT8SNOJPuAqjXa6JVvGiXd0C8TVSfq4UcqlVeStXmsv0f7jAds1NGhNBrrr8UmhC371ciP122gbxdRLXtm+l2XnTGQ0Td73NnoTW6S/ultnvPhNBvvtamw8H6bi7P3AIdUEtGszJjDdYLUp/mevkNfcjzofVioyMaP1kXi7uUFgbKopEcU0r4/v/6ATlnvP+/lRXyAX/U8pNZeQMwF9PUK4xgY6x3Yp9XK1rm4TGFy7Iyl3LOmKYJeZ4wHSa1/iWNFR+ZDqeTMsBcOcblgwwJdE043+gSl6GRCTac76vdv58v5gIEJBKsuBzfnNkjFxAuncLCXr7UlnxEpe2Ub/vg3F7YVI4Ie4+6NE1xsVr8hLwCwUSTVhiC3VYBDd1CICqItylMSMhkLtiT7gcCgPcAfacFTz/kunbm/z5hyjPubo+4OR6RsqZfTgtO3y1YfmXwwhZz0Nb79ypCSClj/nnG4Tjj5uYW+XFGnhLylEAmdC1iguJFmVQLF+QpY54OKkifs61HXzUEYmVDlSLKUXT6lNySXBeyhMkQCLgwltOiHhgKQ6BW8dOscd2RyCym1ZV6pBO7PeDnBymeyVVpxay7rWIBNA65MKQwSilYTieUUsBc1MK86DsujLIUFF4gi37nslhcR/ELRl0k8Yyt7zVYvJ5lecZkAnzFNWw8uEYrVBY0s1qcF0GhAtj3OSekBWBOSAvjRACfGCmr2HIiQkFW6zACChO4kLZD2KgRUXwrGjqiQK2BUKQyEtkvUBhw4paQmVBxZ3XfG/bcKk9FJ3t4ZQe+AAPxEo8j2uxglf9cmZ4P7Xp6SR/3z+yGm9sK0TNQ8zWac51VwGJxQQdF7VbXQClRy7v1vO49UHhm3igQYpWS0UHVi4QykqvlOWULL2Fn/oC02drux2rF5XZ3ZSvP6T1V0mk9Y5s3VWYieyAA5XpX9C6ISA3Bw47fOUbWtbmUJljws8aFxJ5OLSObmCEhQ1VYbiG4r7Gm3TOEAJhYLf3i/JdYKFDXH7cudt/dVTvIXNmGvMueGV0HLcPnsEzfK0PQu1xG+E5oHmROkdA8C+fxSCxG0Cyg3ZV77/GggQvL/LknC+pPeESzRJaNP7ccj/nHFse0ah3e98Otyz0WeYxrviDERkazbn8CNgXnAFUPDRm9NbuLeY6h3tUUUFv38fkhGI/4s0dqY+wKDE+ev2saOfEUxmVNo14KK/z9grzjPPUl9Jjc1WNusZ4zXSMq2jxC45Vv3wa3a1xDT2tGaGhThd7Lr+9A9CZQqprmY5dfTJiucLQ32d6V4TSJvcsw6/VE8Jl6JMHRaMI7ozFaywkQwgLGI6BxzwUgMB6sbl2PmqdAcEQ8ldqqiCdVVCrw2tzbQWyvx0AnqABc48drH7w/nv6RgDsRC0nUwhpkCA5Qy/MnCL7/x0+4IcLpn7/hAaJ0HahzbV4Ddgy8hBaJfTvAyHPr9QM5jcVVqB6t199Ct9NktOX3omfLe5Oqj+X7GDY6QqpV/VtRnHJn556I4rNHCns10AnJ6F0RQZqSnrlGm5+EFXcJUFhnrzDjw+MjjtOEnBJ+/uE7/PL7O8+CurNEjJegmISZcf/wiHme8PR0wk8//oB//fIbWIB5mrW+01PXV6o7UqrSVnTZzyKVtgIAkqYW7vciIqoKgXXsaJhDvWSYch6BiRpt4mH+zijuX8p3eyH1/E1CpXlxGZYd4Ro66u8HVwH6Fb4ZeA6pbb1fPavchQ1kJw0JRktz5Q0Fpo8Rf5EpNxI+lmgbxnTYRtovRcfPCg5fxFQyolja760WjU832xw6t9enddNaBgpp9ELlFwQa8vbC8/gdZ54NTQyt/PsfiKsY1pdk+vt3+xM0MF+b71Pa4AxGv5rop0DgZi8uX6sXmA1rrRcTyURDG7dsUzeaipcTi3u4yfu02pdWfBMKtys+eXl1yEwAbUzZKix3PPEyvsPLIHK1uiLGm1Kbu9omOE7r+3YJkFcRxif+3ixnmLLP5ab6ZUCgn8YZ7y+ZlwxCHEsx5rW6bM5VCEdIKoSPhdqaULfvCSgqsMp5qpdwP/vaudMusBT2zKdemLqYZ2hCxGSxz3POKhycJhWWisVUPp0gbIJVi+sOWrAYd1SINWpMKUEQRT3N8xpi6k+GSy3+Y/rNlLUcqUMQhRqr5FCrvzEeenQtvNfGVmZYM5Y2ybG6sqxPHVd1zBKpAi+3Yheo4kFlFAXhIxFh+nFCSgT8DEx5wnxQ6+8pJczTjGma1Rq8KpNoLEC5E8gikHdi9ZK5PU+af5owzzOOhyPmtxPSQ64x0NVegrGUBSWrC/OEgiknzNOENE1qGe4NFROMFQDCSEcVPKuoNgHuGt7oa3cPLnCGnFTmFJsyK8HyZGXGuaIMEUFKAkiqUL2dqTbugmZ+4/jT2uqW4iqMd5fsBUUYhYvFMS8a5zyEVOCFUcpiAne1Soe489N4vtuUU51Ua7vGoXf8laHCP5bU2kyAmNUpgcBmHc+pqEJFKeDg/r0YB5Ch/dB1BhOWazlL8SEgEBWIqFtNjT/pLrQJLKR1sI3nGZ+VOuVNCRdhDrdw50vw6kUyvs8Ar6Ej3Ur5ovK3Ml9SxyVlE9b46myZJjr4VEYgdR/o9lZI4oqDXVYiwxPaokpvQurPii87wYspDJNU5XRCcNEeUrsC30g9uxt3HpSrHYfHcUneBOxPmVDzcrIPN/b+AYQbcLC1JNxBcN/dRkWasHhV7Qs5v26ZzuQBGV4G6xyfl2hw4a/3s4sjLT3vwS2qP6m+YUCjimNbOwpjXF//GeMw75Xl5bm9oeef0cIA1KPJvm9ZmZ/QC8jH9rhFexwbQmMae5u3LNWNOq5LKrbTLZXjmLjg3+uJ4YPGcl0pIcY6B1yI3qinG5tjF6T3BbXN554nYppzGOxzrtJW1nM4M9BrQxsIwENdERsGIBe2ID6RnRRtL1GY23vMeGvr5AOUDow5Aj4G4TEUfgujYWq9pF5t7LuQiyGtNBIVgjsNNrTVsfKTjcMjgEMYuwm9EpKvzRY+Q1brdeXNqfJXekg2LgXu3l2qYPt+qHPkFybLH70nHKwf7//1O26I6nnHNssXxwe/eDGcOwBCq4M1gY+shhYgww2C7wT4g1qKS+A9qTt4DxPx3HFEiaoiXSPB/axVY7F5zihSIAJkIuREOJWiVuX3gsOUsBS77wZGTxVniyq9FxFMovep33//A4d5wsPp1HWvpxFa2wUAiahwW4k7w8nRi5QT5pojwY3dlKYfqJww+E7gUI0P0u7sWz4Mr/AlIArPXwVX4fnfEq4C9Ctc4WLYPtJdQN5SSfv9SrxIIiAk5xS04ClR0hJvgJ6P1nxu2U667keXYyRN/55wKfmwdVGL9N/o7u1zkSVfmrx5Sf9Ha7fXlHOFfxfYn3FnXp5P9SfDiOBGvIi4f4O4mYzR9NV0pMGW4H6Fp2TN5H623LMlfh1DsdeG+b+q3Yy6XZ6qYojYZ6rWtwQ+qXvp0+MjnMHtiiPz8bhSIkk5Q0pBPtyAT496AhIsL+DWqIC6SZ5TrhQ0pebqfTyi1dI3IQrQP0XI0Ftp+sP2m+winhKpsJIALgsgqMI6jTNslsjHjGme1UJ2WXA6LQAXSCJQAeDeJ4wB0M1NVTLpmaIhwdj6nV79Oatuq5bPfaa/tKy4z7cYMK08qbHJ9X1SoTeMoVn5WvrW94GG97HVKFAhaMrgwhrT/Ae1wK5W52aRnZIK0FNyC2NBJq5u/dU9t7ohJwB4m5ChXkt07akAfJrVCn2eZmBRzwgpZ2UkScGSZizppBagYIASDtOs+yZr/ZkSChhgQBKjZNa43MQWP13Mmp60fUVdLJLFPHaLEBUCG30uDAZXLwsufCe3as3NAwtZXld0rXhHnMFKxowPAt7qbt3inPuzIjV8Aom6m2RW5RbmUn+rxWhwc67m7XVhdGvMJHIa/x1wJYCUEpKoskLzdEKVuUYgkFm500JAFvCS1KV+EXASyAJMKKiOTIviBUICJQabn91SVBxPpH0SYQjb2rM2pUSajvS5Wg3b9abiMkETv0jX11djzY0CqoearxH2DvWdc+Pi8aF1mpEeiIz9c+VsP06ILnrX5xMNL8aEAYcRKoM8epZJUCUd36tevkCF1/rcxIepXz9VGYW9TrE+696aCFVJBDArQxFjyKMq4NQ80gtSXDhjDmdAvLZSBNbrrgznqA8hUy/MmeUGbOIyAGCLqpugMVqT7ZtiTPjXLu9RGSWHBheSFut8AE/nQtI8vG+W4qMVTi0dZwAAIABJREFU8efZiIJewBvHMV4R3EjP23MQzcf2bHlhcybpe+Do7CA91+iBVNA+W3oXAD/Z867taG0mREF1EypG190pfI6zs6ccsPfche1RwD4K0qOAvLWsWeHGdjCABRIEle1dh+1DYTfSYj5vtpHWQvTIufLP2uBY6ReCl6/iPW9MK4wBQD1WxLFv9sUtHcFXCEKKyyCO3VZLpPszWs9x5c8Z+EXfvYWulWh5PswIALesbxba3nJf/3pGa18WqDW5krJOvyjcQy3JvW1uaf4AMc8NWscHsHk9ILNCJ7MMltUS8f3lv6j+T/X5uMYZTWFzey3I8Omx6wULgAPegvChhsBwpRjgLdJPhFsQ/vj1j86a+RJY17p+51Syftu+twkE99Tye0z1N9C+H4UwQ++JbwC8G+41Xnc9p4fl6Uo9SQTv0ZRgquJ6aBYzmzv2UDJpbQlqcT4lws180JjnovHPnUf+tCy4PRwwJcGpFDyeluohbimaNyUTpYtaos/zjFMpmLOebI+nBRDBPM1GM582x3gwCod7zWmIKtIpBIAbTjShe5yVOp6xMoHRJNt0bYvvfoUrXOFzwFWAfoUrAPvUyOq57P90JoF/HamWi9sykrCXtOsKe7AayTC85L/hwofIbLHnw1iP5V1Jkit8C6BW21/Xao/MXgm3hi135PXCTdYXcb5+t+s3yj4Pr0XFe0yKl7Zhu/Vn0o74bBir17Tha4Jokb/5npr1hCN9PQeKMe0JdLgBPz0qI74WFZn8gpwnc9Hc3CTf/Y83KlT8X8o2v6f3ABEyKaPknOD81ZdbaX0hQhMEAhpzedFE3laXtBJBXWS7e/lSkJ6Uenl6EiQSIAPC6gpXNsbhW4XRFWsKyhVEhNFibISqgLSiLahLU8tclzAgjd77R2W3uMX6mDzCe0H6mTCbxXc2wXdO6nBSBaIFWBhCyjg6nU5YiipjsDDSW1cOUVualAh5mlR4Ps84HA6Y5yPoyKCP6sLd2fApFeQMsEwoYKQEZJo1TnomdSWeJ5RSICzgA4N4QSnNfSkXjVHYh8MgNFNjHUFnEBYRFAa4CJgLEqvg3SVfAlI3jiJD2CMxhQSocE4SGFzn0S2qq5CezUqeCwoXlLLYX0FZlPmm79XFOxePiS41PrqebbX6egS7F5WUTFiR3XOGbu6c1QuA6t7yoFhLUP1caooQOSOVgjJl8MJIqYCLIIOwBNYdEYETwEndszMziAlEDKYFpRBSKjgtQEoFIgThVL97rHq36nehf1UAiUT5FT4zrIUY2/Ap43/+fLBZP5OznclN1dEZ6Kbe61FYvJyzkjJp9/HVnZzq++p9x5XhbEEmw+eJgFIEmVTBJIpUtsRdTpclXO6mvDbPUFca3nFz1jvke7DPNwAEGcm8N9xCJESS3RoeIxa2ZlwgGtOc2okW46J7uBCB1BjpWo0L/HpYu0r+fDZyqlrZCxbH83Ocq/g8A2apaB5kcLkgfYsGH5ebfz9dUGZsV7Qqj6VvxXUeOUdbc+pC8SgkP+EyK3x32+57cxTPev1dTGuo8FzH2NeLvnchuGzkia6b92DMc7J9k9Hm+ii9kH2bmmobo8q0sLNd/iIY19IebbjV/j3YyzvW6fAImKC6CeqLAEIfwL/ofMwgLKKuyI9QV+Q9T3PYgeKePhyn9H1rhh2CE5RQiJGn/bb3KIJbX1/Sl+HKMXdWu7twz2j4ObbQBeAJMNpHhrXerIcnqOv1+D56kqi9roT42jLY+5PwoVomd8oxPyVMU8ayLHhj8+Br+zkr9HNsaBmeS/dtXXB/w2jKH97W6efv8fTLH8ggzCLVpfuHoag9KuSe1JV7FuCNqOLTTbd/qVPQq6WIntuRyGVRwfiUM47zXIXgbIJkZqVfj/OM+TDj9sj44/5Bwya5hyx2eptwWhbklPB4Uvr97ngEM+NUNBBLSgmlrEetO3u2tsGwoTXCktFAYl4YghA90sk1W/AUJ9IKHEMiXYXoV7jC54OrAP0K3xS85OjYFsIo6IVcajp3UUROvDnf7oWUN4X/u2/19N2GTZeGWBNI5y4Ejai5lMny94I499XqS162Ji4pG3h+9L40CXNp+f0FZetieYVvHaLV0FeLFQQb+LEJj1zjtxetUiekOte5LQZZfPcpMDIsnmOAvbTuFd4LT+kz4b/PBc8yfCjXM8pdrVbrRbtQcilVSA4IUp4AITAvdS2nlGp81DjoyYXrwsizxlgHAXxSFjgzq2WspfdLOShZbGNGtfYEVJg9XFhrvS8Zh6GMZsXe9mZcxzknUCYVLFp6kAog3DI55UnXf9JLeUoJmGccQHh4fLIB9Yu5HZcWR/7Zhbk2jbm0p58Z9hr6+npdGG0erM1N+prWOseAGgXlI8QyCQDJAe5um0CYSL0v0A+28P/wcnu7sCqAomYp1HldSOpOXd20T/o3TyBKZiEhdb0qM0ljnS/lCWU5qbtxYTAnTFOy+NsZOSXkPONw8L8bHI4HbfOdu1lk8AcTvlrfqsWbWX9M+YApT5imWV29l4JCC3CSyqUswhq/XFBjHKecw1woMe4yscXcqYt4LPKMQmqZksxvtbvCl+rSyQswuRoJhNV9caIMScZgZYDcAl3YXLYvVXi+lEW9PJgg3eOfi7l3lyIQXsCLCrUhUuMRa9PIhNC2vqrWp8a2J+XkAaReOqZpNsv5sPpImY0ugIcxCgsvoIWRWcBTAZ9Y48XbmLi0IqWCUgiSBWSx66lo2zQEOoOLxZXm1LwV2OmbyGL+JmVievHKGPzCFMbIyPWp/YoOQZ3j/XebMGbYSTfaO0q3S1yRYc08f07M6XTWZmx0oLM06+649aP/fcg59LXhLke+lKhb0iDoPukuzE3MWNe60YBs617c01v1oBLPy8aAToYPUs66n4qOl8cFd68PVQAX2kVQgYBaKHbdrNDwTHwWLNqlPbOGbtKKCz4AAG6+fwv+XQBq1urYqKNrzMbUZVHFohxecmqznBtKgdsv+kgChMneF2rWmf46A0jklvI6ny9VNACa4Hy0ygXWYVTGbvr3p5103v61IL1NxBQaE2OWx3znsNosJvhFm98ianHeW7LGkdURi3HKYx2ju/YIW0LyPVfunja6cwfafcgFkJ5udBsvNT9ZeS08AqO3ID9IiBU/tCOht0Y/WIIY+9wFiU+kQjdv32rsqb8HrYMx+P9xvOO7zwlkYxEEXaHOse0PoU0A8J216C1077iqTEM/a1z+qb14RPMsQXD3917mHQjAjHsUAI+Bo9jaNWKt0VJdhfR5larN5/j3xlowQcBC1YL7O6c5DFtPoSWxTfG6IoA5oge+hwrbPY1A6byDccuaG26p/3s7CTovAuA++UyLXas03wMRbhopi0crP8NjomsrU1JlyGVZViN4mSt3r71fP17WNn4aU+2vJI+JTr/+DgB1nBP0jPjeDr5CqBbsRKjKqZGueU/A94lwU1raN0IoInjKXmu/I4kAYa7GED4Tiwu3jaZ/c3sDLkqXMzNOS8FhmvD0eMJ333+HtyJ49/ERroRfrMzk55cw7g4zPjw84r084Ps3d/j48IhTKYAAB7N2x8YdX9DIdbdEX5Fa1aOOGI96e74qKT+eL06LWLkxnwvPr0L0K1zh88BVgH6FbwYuOTJqGhl+r9LZwSborV4E7ZIan10Ksv6ZvKIrvBoiuVW/y7n5NegYBNvpxsvVmuy8whW+flhjGKoEugvg6vfw+XVAZEC0y1u/P6NAPdXbB/XZVyWO+3rvwnnpaKyYp0DH7471PVfmHl56rs5Lyv3a4PI2+ajoCKYpg08hznkQoqsrc8vlfmGlX++xZr+A8sI4yZNaiZpkjrkJzg/mav7ptxSYyn0Zcf+8Zrw9vrW3lUj7lIhq7GmtD42x4GveBJ1kwjYidRqXTaD+lt/g/YcPqonPjGxCHe1eYxl9Oryg55cu9i8I1ZKb2gMfhyj0bowd6vKOODMKiRzSmAcA6Ang41aLgnU5If1A4N/XNAnB17u5dSdz720uC0XM9aSoQFcdLwiE1XV3MkWMZMhyOZ2wLEt1xZgzdW7gU5pwOMyY5wPmw1FduM9TFeSKcHOPTkBOyViSdua4AD2p5c08m8LAgSAnBpUEjcOO2vYIdY5E1zo5khdRq3KPSc6MxAxIQhIxd+aaXgwfJLLY3VYyDfVofHkTtsOZlOrtgS0sAi9FQyScFpyWE5bTgrKc1G17EbU6N2G5SFFBupgYwlyYQhSXUNJBI5u7RKoskyiZYNzGb87I86R7Fww3a/XQUC4kBNTKnkoG5daeggUgU6ykpoAW14xa8rC9U8WlUtSlf2HHuTbXnCDJXfwndf1P7rkAqpRgzM8dD9HfDLyetPr0GORbHnlWAvTdn9t17/aHug9dl7bG1PJWd5jHNq8iAKKqBO0Cf4GA9oIn13YYlvE8IhZn105p6QVqnQWXIRSNQ+tPpIZT36MLvTlRuBhZAwQVMggazVGFQxvj/KxATwTyu6e7RaKPFle2MdC9qmSIsgyX4QR0IQ54Y0NmV+SpygehTYbnk9za849V+KTxcoEkKjpv3luakOc5Qbq7NvYY9THgw0g/X0pHbz3zMmdj8bhA3F22jzvF00x7C2EDTtTKj3WfEAWVHnd6zVQ6F8s8gluPe85zQva9/A5JT5GVG/dxjXdsMds7DmTz7EL0UYnhEAYkAbiVtYLFYWecx7tbq3PcOS0G+t7zl96dXgN7dYxr61xbRmv8lsZzUvfUy7ykbWO6aGGteNTdrhME9yhEmEC4AeMRbonueHqEYexF3a4fSBV3yOg79agR5kXUpX2CoAXqcaE21TFhNDWqvvfj+lyD54stjCPZMJeuGE/XFDfibSD0tCozkSmGCG6lx3+uGMQAln/9BvovP0J+fafnxTB64zrZBDp/Ru3leabUFQgBiwiSNEF6xQ+iPlI+PrOJFgBzspj1pOftlAim1g1KwJRyHX+9A6h3mNYQbfOpMMQc5R+mCTnrXWMphIVPVUj+8f4jppzx/d0NHp40fYHde+38e1oKjvMMEKEUxrIU3N4cwR8fUFhjrc/ThNPTCT0lMezNcLZ2B1fgN/t/NRmLKgoDa124kFe875awKvN/Vfy6K1zh7w9XAfoVrvBZoCcwostFh5GIGoHs0tknGJjto5b6Oav0rhR/tm7FPkH77QANf5GQ6QnmdZ698l7y/HPBa8rfYx58S+TWuOK/pb73EC6Z5DR4fEaB8f51QbT66YXnVONB1uscBUffG7fnyHL4M3u6ZnE8k/4rnIcvCVX4nZO6cyaokDdB4x4nBKFMVtfTAPI8gR+XoSzAY6W6EAcwoZTFVnP35iezAl0elQ2Ubm6xmMtlCECJQr0ETsrazSagZlHm8cmsMVeC1PD9IgHIoHpO1odMCXlKmKdJLcqtD5F+qFYI5mLaOSsEgpBarh5vbzBNGaenE56eTnh4euzrXTfIW/9cwy9MN0Cm0FFcYNn+5aDJvHtL0YZ+tpULNoXnMuxzoh26DWB6RBKP7mjPfxfQD4T0o7Ky+XfNrb9DnX+grgdNgCoIdW8NXJw9vSgHi1AtqYmMaW7FLUtBKSoIr1bnecJ8mDGZEH2aDzjMB8zTjHmekXMGl8UskmGuw6W6PU+2j1UJxLw8JFXoQLa42idVVHH2r1ucSynKYCWzJvU4xjUYsbGiiGoc9MLqPr1wUSt4JnBWwV1VNIExbolASSBMEK+fVKGgV4wQaxeqd4qyFJyWE8qyYFkKTqeTxkA/ndQVdPHwCqxMsuJxz6XR++Suzr0tZPHhU7WuIUpIOZkrS6gyw0HZsCJsVq7eVgJljZnMECQWUGbQksCZIYUshrvbWLUVWeMjV8t4bVvg2WERsfiUAmaytRe+i1iUR4snTVzpDdnkEJ4HRwvP5xjwl7uiDrP3twTq56h+c6Yq9W/2BEzjk8qg3n69yt88o4wJtjNOeUL0tzvZerbCMOcJBKpeMCT0CTWZl53DRU2FKHmg4MR9snpeW5d7TGbFJ60+L22mbEx7tW1cSrM8dzERAeq9Af2ZHnnlW/GqvWscynNLaj/23PJ7zOsY/pHeW/omxplqniZE978J5snH20i2ZnY2RhbqhKU3fAcmRqGHSk+rMOuj9lP0/GAbwywUq+/aH53ibwnSXXgk6C1SY1MjPhAEYfGwDL1bbsVcT0DS8YquwIE2hq3tWiBDqiB8lm2L9i2oAmBq9evdxejN2k+qce2jUNctw90CfB4+Ed6dLP2IJ59z2w701ucI+UfX8qNb+UZx3Bld9KE+K9aXPVLuidq8OOXu9zpXnPC6xvF+JB1bT3+09XgCVrQz4DTbeifuPf+8sKWU5/X34zvShtVDxZC2jU2fo2HzyxboVioBaiCJN+j3MOG+tp+hgu0bEIIfjFVf99ryGNrq8c3VOluqR4zk73/+Dg+/vKv7pq1PDzCx3Y/W7vY9rsf39pYh+A5rfFPCbwk784Pl11XfI1GfJz0r244RAAUJquIoOKG5nj8BkH/+humn75BSwjEniADv/vPX2oZtkOHzPJ20tyrOpY/j+N5ouFv7naRZ73tPJwFuWfCB1AtRrNnrcVfuAPD2O+D+vbnJN+G3H+HxuCbRezYBqtAh5ixNgFMpSER4eHoypdwJOSXcHg7apjyBhfHh4wPubm5we3MAhDCd1GsdC2MparHOLPju9gZLKfjj/iO+v7vFm9sb/P5e/RYImxB9Waso1bOJbEwqKRJOLHVx1dHAdQW5FbmnHhFCvTNIuDpcrc6vcIUvAVcB+hW+PThHD2/d/bcyyfC3mUa2v29Aress8+hvy975a2EctufoCCc8hnx72VZMpGeqv8IVvlro7tZU6Xj9SfXvayPGowGNf698WL+PhL5tMe/2IFoBRaucrn48v8/38ceXHcuuXdSYsgDcAPFsnq9lpuNRe3asV2tTL5Dz8Qa8FAgYy+Mj5pvjytqu/z0+b/WeHh9UwMTmUnuaQCQ4/adqsz/gA4SAI72F4B5Ppjlemb/BNXasqVkIh34PtEBVYhFrF+lnToRpypjmCXmakHJWhsOU1bKVWQUIxrThwi0/XLNdP52xk3JGnhgTawxqD1dTXdCdm4d+CD8T/IWrsePW6AdTc2/bWbkMc9hkQs4u2V9jY1UypN9k9BIAIdAPqOuhlilQX5RJgD/aeolC3+W3BZwY+YeC5URd+xNJ2xfJy9U2pJSQc8I0zzgeZkyHubqDdxfu05SRstYrQhbqQP+Woq7TYRamyZQSaixv6xyzAKzhD8Ss5EthsBQTxAMQUSG3IzhR6yUNuZCsfgFY1CrJ61+aIoEGYAeIrS3m45tIlbCECELczg+zaO3wkqglP1jU6rwUlFOp7tuXZTH39wVgbgoFvjVrgc4lRDt7zZo+ZYsznzWefIJ7FMgmtSCkaQJlwzjSRC+UzKo8ka0sBiUCszKkiVXQlSZGZrYY7+rIVBUWBISMZWFMlKGh3BNSYmQklCJIyQT6qY2MWp5rnaW0LlXGcuMsP3tf+neFtu9fh+cuUb4aU1SyKO652oqhHWd+bgqhK721zkhoeMhFD6ockmrDcsq17CpnJ+9DszQU0S3unWmYbayXaj2t4YQoNiFsKAHUODFtjxNREJijMtq3MLQv7VHg6P2Jz71laeOZoTVwam7dOxCYpWb9UVvTLDjbuKjXh9YHF9R31ueh+CT9TLZ2ufW/dHm664Q9iDSnxv1t/Wq0u1kdolmcjkLUUZFi+IoOlb4CFmqKCl72+tQ2AddnIku8HBccu7B5hrpBP6HtJRcWHizNJbTxE5oQ/TXQ7XfEdS1mlaxP/Lu3JYfvsX3JZnfPDXV00e71j/3bU1ZwAXyct1U/goLLOUv0Lwt7q3TL/j2+bd/OrXMXwfm+396//e+xjjFdBEI/xgJUvNjWQMQ6fe7Yj1hbFIa32OvtjxAFs4IZwEl6EXrEdhXn7fTHlVdGnOXBZ94D+CHkSyBkiCmC9K3ue933ylM5Xe/fHki9LPg9YrJ9lKHHzwKAfnmH9I8fwAtbiJ8+ZEVXZzzihjTP/b4UtsoRqAD8VoB3ycIp2Jn8gYC3rEL0NwA+nlm5C4BMhId3NlLUyvFQS+Lf0ZON7m5fo7roe/0ueDKL9CnnoFSsq+NUGH/c3+PN7S3mnJAOMwQC4YwpMz48PmLK6pVtMiV7F6L/8PYN3n14X93Sz3nCUk7n92W4SwdSOBKC/Z4NSLeSymj7rb4j6UnooNi4UnLEQA9d4QpXuAiuAvQrXMFgK+Z5BzJ8F5gruKbB7hf9FzOARkrVGZbONdi6kdvH5VWtD8mxS68npb5O2JzHP7n+r7EevXw4MU/d828Jzl86v73x2Ae/vXyFwvP454w56t+1G65ZnodLnb++BJzJ97nh1SO64lDuJ6s1hT7sHCt/Olxcr7lKFhf+Aiocru9hS9VdC/tVuu+pQK3JD3d3tQxtiDPYcxUi8+LlAClN1l5WAVtSwdU0ZY0vPpnFOzRWapIEQTJZFdWFWUqzrfJ4eFq9a4sPAomNS68PnK/xlNSFdp4mpGlCnjIoNZsJkSZEF7RY7HUcRQVzRBo7nZkhrO6Ys8VMFmYUM01jn49hXDenbavh5yCd/XlBjPWBQXC+thdDJMlanFVCErMqeEGFkQn0XLr1QKDj6lOUIlUui+0Hm/9kc+lxvlkEYHUxXp6cGUUmr1W3/sktwZkqoyplbfc0ZxwPM443B8wHtTinlDHlCfOcMc1Z14kom11ELbK5FCwnlaRSEvUqUbIqJAQXIswCkMUSLwWFi8VDX8ALG7PILUvdOjyyMKmdCzY6wmxu3BeUQqBMgCRM5lZcCMCkeLLGIhTtOFUEukFPs7m9t/Ld4lyF5urCfVkWrZvN4lwq11QVE6oFik9es3TPmWr4hZSzWp+b6/xE5jnDmGppSqApqct6ABC3Yk8Vp2gX1Mo2FUASQEsBJCPnAqSsrlKTWpS7AB3CamFeGDkbPmACi8U2T2TPbS7suYgK6nPSRjIi43OPPX/msVz0+Az0Ocba/i63obq+fXqsIxKIlR5Px92h36IoY2V5Pta32xDfY7SdLqliSnLPL1aDW5WxeY/IKWkM8HpOWqnhSgxqnlUS9LwXCLpEYd+H/3pvHACSZMDiomrHh3HTOGrgwn2nbHxzUlvIehxROx+9AeMSFzQLRn9fx016oZjPTjacLtLOHUET9C7ucKPiE8s90g6Wd7QY7nggto6yABAKbWnAUIWlh3TfvduikR1jOj5x9BbjlPu6nezoKgTc/fw97n/5HYc4XmiChwiRHLjEstphL4awPz8O/fF6RsH5pZbnq/Qb+QjNwvjeeu0KmOpCnVaULaO3Fo9jMNvvJ6iFaEwz4/nxGr0lSPjtwscWE9pxjHZsMZtcF3i6e2qCuuEGBDfSyozjGOv0ep4IuBPC/TOXsYbftN4jbE4DidSn/zMszkdY06rbWHsNTSFm//Rcd7PHLJ8CrtQyd5gKKPbbFYNu7HOMdT625hy4RfoNfN3oZwZwvDmC/9uM5T9+BdDI5CdIDTewAHgwxPhWWhkplMdo8bzj5dofFTGBNnR9qxC94e13YTgJwH1of8V/oe2xdLul2XdCqWW3fp4A0L9+R/7HD1h+eYcDgF9IcGOI88FJLi+pKkitKSPp/h8RkWz86vsWn8fV5PN5T+35B2rv3yfgO1ZPHSjcWaLHch9IheyAKnbeAzgURrHQU56+3YsFxQ7ZbJjSz3P11ASANIxVEQEKY4aunaenJxARbg9zzVO4hY6ZpgRmwtvjDRYuOBwPgAB3R8bHpxPuHx/xho44zjPun56QkqoMEff39oiPCO0Mc1LcsWeq9ACGvKQeqzLVca641vGnqLJqpfGcp+GjdLVGv8IVPgtcBehX+HYgXg533o3PVwyVrgwZ3m3dGi8gDVd+WC4ka+Wy4q+g8OyYbozllcy4wrcKzRg3uG2nPfz01yIiskuyyjZaG+NlZfz92iavLNB3mPiXwl+CY8JNNTIigzfV3Tx/xUw3VgYAt0ZbHdYqTJIgGPb4qNM8o5xOyPOE0+ODun0HsDw9YTockHKMKucxglMV1Au65Q8+qRNJ/pXBxHigdyAidS1JhDc//6DumX8RCL7DE94BUIJ7sTTRSnh1uY2CD5FVulW/E6nr7HlGzmp97gLSZn2u31kEXKTFb/c9DkA41fEWbnHd3TZRiEAS4rA9N3GvXdxDPlk/+suhZ0LodxWeU0izm7tO8VbMc7HntNp0bosTQGyNCIAknVUvgOrtgAuDTFqh7g7VsgYWs1oEYDVxa+7dASCbU1kRdalOpJ7RKWPKGYfDETc3R9ze3mGeZ0zTDCK1js5Z02g7mrU1RC3I9ZmNE5ubdNHnJG49zeAClCIozFhM2L+YML0qy6Rk7r+1/86QTJTqPKhVShPCIyXIQpCUIOYlQmAMvSVrf0XM8wLDFXhUAaGfNGEAUrRfi1nYLyf9Ky0OujBruImAa6m6ssy2360j5opaFRiUcZinDMoZU05wt+05T4CNubdJLdIJQEISd+bcznL3PgEmjXGcYX4y/U/rczf9xAk5GctZMkTUqTDboGs8drJY8PZnSELL8XRb+yHcn3wtX+GzwR4DfBRf0EbaS6GuJ6DirfURrcJz8vRojGHPn+x7fSYNH7pQwD0/uMIbj0p03gJq9YaXcI8avaV5CE8gLW2TDlA/QASAx344E/x5q9CtOamKD0M1Hd1q4MIVJjt3olDQOu8M9Rhz19909ZN621i5/A90VnTDW/thcxMVVm34N9vc16n19PGU+/EAgPtffg9nZf+u4uuh/D5Yz6dDHNo/AzUJzqyR8DuBqgWu/lYLc08TBeNRQO4u0GXj3R48olm7R4rMy4hCwfas7wHbPa2GIoALBm0fQ2o5DidqLtifwvyXIPbbg7p3RGlvgVrEPqJukerxBsBZS/QvB5+CdZ+HNXcxUtMR5NfaAAAgAElEQVQ9nn5pK0ZqVGx+GwUgVeC8FY4hoivpnvhHuAvZ73ZDMfwHTZLsTgdoeABAKl5QKqj103FO9FLxMaytcdRkqG9t9e3eAiQ88f+rUyAtQ9r5CERVM8EjUadI4gojs33PUAWYO9E46b4HfIw3V9InXpy21oTP2XMr926HlHtnQvRJgLfQvm0pVyj9rrUc7fzqBNIWDgii8c8Tqfv0UhiF21wAqpw3WUg1PbcED6cTWETzmHIxM+PpdMJxPmApBXPOeHw64WlZcHs4YLK7NQtriJkD4cPjI/64v8cPd7c42H1HBfCKoesd/sz4xh25pZ/r6RJpGKkVH6oeUK5WFXDaYIFeswS8d4UrXOFlcBWgX+EKrwFnBA7kwe45tPOCnEg0dzyRtEJkpNVH0jHenoOeMN0HCf9/C7DHlNgapdfQn59Is35RaPGg//xW7jHyRiLyteV+zeP+dcPeyFEQ9hFGuv7rGm+9XCfqn8U+xH1f4UK0t8+EHrH0l4OxDvmLNYk/9cS4pPVuISOACn0BQBiUJhABjx/uMb+5Cy0yV8U7Vtt5ctsbZeksj0+Yb8xGwrQJpDDIhFEqkNfznkuBQCC/qrDokczGQAhZ+niOiQgf+DdEybuYtJCIOis48nf+O5EJG+3Z0Jexbzlp3Ok8zchzbvWZ8JwLa9uZ1RJZmma+jqegFMZyUpfaUaHA6ypSTFCRWvl7k/ZaGDhTNPzaZ9r8ibTLatFur+Jxa0YFiOYpY+xhe96dabucKsM80n5XsjEUyKXg9MuCNCVkykCxXWJrscazDsFFczbn9FU6EtetWhhP0wE3Nze4u3uDu7tbi3U+Qcx1es4ZMAG2ukJkFSIDIBLIQbnZUgC1TlenvsV8mROARYDMgCwFSzlVN+juJUGtbIwxz7qnqxtjW9+StH5mZayVUkDL0tYxKTPyYHsu54ycXXGEKi2uLoalluuCby7q2aEsBWUp4FMBR5ftJ7OeL9pusNPxJlCs5n3xJFFC32Oep5RBmZCmjJymqqBAyUI12NxozHb1SEHJxAbSiqdk54YLurNYvPO2osR8KVMCsiRwggrnJev77LFFBTkLRBKYU7Ug1vrdQTODxc/gtraHm43+7568tpb6FuwQI3seVi4rqOXcO5/+6pvSaHhZmalJmjcVnKO3z9B7G3mfJTNGXLf1PgitKVEVVPmJjSLqrSLkrnjQPJ3U0CWhFr9CW4L2NWXMs7K42EIlMOs9m30/257horazOdv6pgL3QqP5lElPlOCm2S1+rXpUYFGGPjF353Ycj7OMagpoPgj8BU0gHNd1PEuEQjxVsvUg7Z2XKa4MBIBJqht4AgAhlLCwXKcmzuUstyj0sQrDissvIJiD4mq0Ko/u4JOgzqNah/Y21LPnH/przVvBOsrsl4EnUmHPsrsPtnbNa0DzP9ev5l9lVFVpYjynm7esy5+Glm5ZrO9BCp++DmNc+tYaj9venrHlmEIZ0z++w/Kvd/VM2LLi93pGTwAH2bf6d/ftXh+hxZQ/ej1Kjq/Yc3+NJXoDHdvn2xDvs1FA/FyehjtfzjkZV/pjeK5rTTAbPeZpljOUeyxXhm/jm9thnbv3go//378w/Zcfu7YVuIDDXH2HMh9cuRiqUOHC8zuJFuhr8HffVTzcQmBIzd8TJa4Y5pQNhe7Fk7q1yPvs6zBa+psQ/Zc/1BOD7X/fYy58f1h5ZliPexzlMXb8c3O1V86Yw125+4jcSXvuQvQsAFhwCwGn1ATpBBADJIKcCcW8shxYcCpLd4fOKSMRcJxniAhuDgec6IQp3+DpdMJi9142q/KcyfY84VQYLCccD7PegQujELDwE47ThHcPD7iZZxAB7z8+4O3dDcqiJ+Dj6YTF4qszBB+fnnBzOODh8REibEL9pO0dZkPX5HDl9TPczu5xe/p6871VwnsyZXhBdN/e6Opd/tcVrnCFV8FVgH6Fbwpee3icIyVGFy2dJcVr63NXkWfTXFDOq1vwbwxO0O0M78iTG5NdCZArfEtQBejUflf4izVXK/OAqLpqo40UMUa6ShOe38VbPYv3mfr9U3lnhGdxfU0aGJ7jpXWv+m3RQKhbhr6MzPlnG/Vcgs8DldEO6tokAvzx//yK7//nTxCWppVO6tKYC6MsC/I8g5dmm8SlIOcZSAnLwwOmmxvrj613j3FOYQzI4542Oxk/7wsRbuk75JxxOBxUgHR3BxDhUfwCzyjMnQW6d8IF1RKY+/UZgqWy/7Z4yATSuNOHA/I8meAKvdV5UXfSVQWGkrqDBtX64MI06xeLIKUMZsY0T5ATILLAxYpbLlRX8NK1QXs/vw5Kpgp0asOoe9e+r59tpachvYQ8FNNI/c/SuaUUwL8L8k99Pfy7ryELYcDmtjiuKSuzhRCgIKw198hJ3XuTuV7OKWvcbSJMk67zm5sb3N7e4PZWBehEKhaBNAUNlmafll05Y7LxLIqOKUHjeWerPxEyJZU1s4AnAT+ZQEs0BqSHOxjHuHlCF9vHaqVKzChlwemUwAQUERRhTCiY1IQck7WXkUGSkNHXQSBQUQUB13tlLuCFq5C8hFjnyxLczReBBzonMqZ3MiF6t7+Vg+ahHygrIy5ntUBPeVIhf9L48pSzKka6twDAxhEWwTMhSXTcDY2nDvfmQZXYdaUsSloeg5CYNH9SizLHGSovF6iSRAIRI9n6YWYNE2SCU/fOUdd+6C/Q8Khbqn+r4MqKZ9PsPIjk2OUYkzY/L2ehtxp3BcSknhzqzIoLz/2ubLVVyyoTJwh6RTKRrk0UWkloXhrUSl3XHi+LKoC5wo3hQwBGK2jb69oMwnoRVQAhSAjfY/aGlMBSOmUoqvnaSF4yhtUS7IIzlaACaoEe1ytRSdSEQYs/zZAao9qVbKILaBovxQ0ltLLpAS60pZrH62rrJu30Xy3OxSyg96neEQO4pbq/y+ssXxz2hed/PrgVbKT9dU5ccClVKA6o4O2cUJ5Cuj0h+ow4J9t0ja3iOrNkbXVvCQCq14IEU2H957uV+G6ErbZX4flOtkc0gV3QC1RrXSIcRV18971oosQtS/S/Uqi+BXXv2u8bAA/hHTa+P1cesJLb7f52iJbohF4o6Ouy3XJHHO5lbtcWhbvR+pul7YEFAP/nb6syoxA9BTounnCPAed2OM1BCG2kY5/WfSAQ3oi7L99XgHCljdECmEB4CC7Zo1cHAjD9nMC/CB6giikZTanEx33L0v9LwEV8ARuLDpcDeCPq1r3YmerzmI1P89HSMhmuJ0JOehdohYcVUt1YNe9Zh8NB7yxTxseHR5yWpc6HcJsbFoYUoDww3t7dgojw4UlVjOYpYykFj6elGma8v3/A3c0BH59O5mpd4P4HmBlLKcgpYeGCQFaHG9v2WPo9L9IAWzuilmACc4R8WL3rF/OohD9+v1qiX+EKl8NVgH6FK1wK584WvxXEW8IzQN351w6z5raGAnNpXd0lF+3VATp8jt//3eF51tS/L3jM87QxAl9qTJ5bW+PF7EvVt7oTvbC8b3XNjPA1x05KJtzcWt3dM0GHUNud7HzfInrXUtvzTxsVOvNrnXJrLZ89mrAagT59ZQwHPmi4lH8JeG25yz9PEBAWqAY6E4PBEAI+/vEOb378Qct3ITpgcYHdYjQBFlc1pQNAzT7m6cN9jYnukKcMDvHKT/9UG5YTPiCBcCPfg7lg+kc2oeKEeZ6BP4A3/+cb0MeTMvXLgtOy4HQ6AavY4+uYZNECvQqb4poN31NOmOapxi+vgigWcCngpcVdrpaq1ISlbpU3TbnFOIaxnEyBQLX9CQkZ4P3Q43sMtmfhrOW5P9kq9c+nXppCxfYqJlJGUFm9XjMsIqeE4vOQpQo3xPeyAKRx7ipDxpAQ/6bzp4J+ZzmiWnxS8HrA1VI4NQZ8UiFtMoaVuyr3tYKEalk+zzNubm5wc3uD29s73N7emft21BjfgLoyFLPQJpLqVpwogylBZuOgmUVJQsKUMlKaQBNBFsZCBfxU1MK2uCt4roqmPieqEAK4eI4ZIE4gKco0Y4IsC1iALAW5qFt1NpeYDBPYTROKMHLOYOq9miRSIR35/gTU6txctJ9OSxWiPz2dcDqdrP9i3ix0som0rJx0LCgRyPafECAmQHdFhpwJKWfkPGHKGgc9m/U52d6nlFFNPt3dvgAMhod0qIvNQEjdNwsI7jUfZOdpSiAWcBZkytoHwJQgBCkJ5jypZ5CcwKJCx5kEE2UspE5GC03IRHgAo2xYwjjOSjBh2QUKxGfBt1cvS3x5ASvY3vl/FhbatTzfStv9sF+dK9GRwe9irW0m637h7eGKQTzMQ6rNkP6eaz5LGWYVbenccryelV6Px1AnP05V2H73/RtAgFIW/Vw0JgV7WAhC3RtcignLBcfbG4gwTg9Pioeyem5oeDowmCN9FBSSEgFTThrCwRWtpFkWCiQu8M0x3TvlHIq1I3uo9n6Y4ZwE9vLqmdGE2iCqsdQ9pnjDn325ozBmnPbZhEuq8BPypr6cuLJceN6IzXX5bjU/0tuCZo35ud20/x1gFG7fwvFm8w4W5zDGRI8C9bEc2XnuEIXnBBVq+XwKmkID1xQKE9zbSHRV3dZVjBrC0HV5zqo8wiVptGxBDrwPVzL4GPLvhVLfskT/Erg++M2o9cXxulRw/xC+b91L29oYy9vmdLyEnn8EMFlKn98ZbyD48KqT/Ii1W+/H2haNhe7gtJuCzhpBLbHrnqiKaU1xa+SH3g8L4XvRuNrvaL0G4n7wz4gvyXCinyGMQUWgv9J1rX8gwa20/bPALc+5llGgIRUchxcgrB1VEPm4s7DH2V6n8p0dVdReD7dWQLTuvxX7TcD3cJpQgnKU4CMRsgBZBG9//AH/8ftvgAC3MK8GRk4L9J7BrDT7+w/3SJwwz5Pey7OGRnpcFmRyBTi700BDQ0GAdx8+4uYw4zhpLPT3Hx8sv3JNi3m4+vj4VPFrIrJ7M7Aw///svXmXJDeSH/gzAO4ReRXJ5vToabSj1e73/1DSvh1pZ1pNNsnKzIhwALZ/mBkOPyIys7KKRVYYXzHD3XEfBoOdmA5HPNzssQMjKv3ilS4w6GhfVLxdhOdlUfV02wKYF14Iq2J0+67nMczp7ytc4Qqvh6sA/QrfDJwjAi4dJoXQ6LS7ubvlrRIaGwefWMj05Eubv9U8tBTnmDZrdS/ftVF6tgjolbbizCFeCrxEZq1fAeYE7JthswAb24Yp9MZi58TmdjmEJYmyNoNXuMLXBGYhVC3Oq8UYULj+AF6uqbp1RXvN1bxNv2iy7DS1gHPYZobMDHOw2MkvaMr5PX++AG5+lHLmFyVt51Y93FZD74A35+3gis7pQltQs3x2MCagnIuVHcdgDD+K0C79PePjP37B/X/7rmt4Zb7LYe2HgHhKcI4wHYVlOAxybT89P2H/8EFqyVnGwTkgZdhhX7YCoAJIuaB777Db7bC/ucHgBuzTDe5+lHX56+mA0/GIp8NBLF9zLrHazRzBDC/rBXq210o/lEWu1q/e+aJ1z5zVhS8XgV7W2G7iTruOKcOEkfpscw+zDdMR0+/qxRY2EqhN3IaXHnkvTVdIrpbJuJn04q5s9+Hlcx0zgZViy5UM2fXlSJqGicF93nkRrpl/m3XrjAgXGNWbwKwAsrbVRyLCMIxgp99YhZQqVCUQgnNwT4TwnVOBu7STM4E8w5GHUwt0Hzx8CAjDgGEcMI4jhnFECAEgIMYIZHUZTBlIEEtreIlF6D1y8siHDB7Esplcg8e9l7jf5ORbas4goArOYcoCs3nSNMyyt8R1Y5J2lCGQcSAC4iSW204FzhL33KuZExX3yI5I5pYLJpCyzLtEUiv0mJDihBRTFfir9avV6eDEcpy0r44Ab1xVO9ikfvnuZVy8g/Oh/Cbn4J0HvMYgB8Fip0O9ARCLcNIYbt1y0bUo0RorjvHaHkaCYyfueL24Zc+c4eDhMhA56ryJxwCmDCKHCRlEAZknMMRtv4cwhc0iUDFZWc39yi0zWdtKzb7uPH81O52qm+oWKkZbf37ZnegFaezgfBW8791giR+3bovz/s88Omw1a+V970FgHYrfloIGW0fuEE8RsnybOeVyNs3v4WahXi2huemenm/QvdcouQsuktAVFQcT/BCQp4TiYYYlajPbectVIGPbtKXJHJN4tMmpbUaLvsv/yxqdEYMvWQlcxqh7i0QonpjyTNjviVQxpZxczSrYOE83zqemSk3QigDFsleErFWAmmFC71mrud7PMyyutzy3sc1r/hcKzy9uwXY2XgaX6IlLZS3346dRz+2eaMs3DO/BJW45Y0NArk1Y+zaid9VOoIVbf2r+tUW2+bK2qI19bicolV8Nff1OQDA3yYWKgt0gRgBgEkG8bsa6l9s7w7xnn96mc18urbG1suzvDXoheh1fgVpuXftrvXtNG1qwee/VsGTECYwduMafX6mjrbcIz3U+ihcQyLlxAGMP6hQ52huSrdf5GF1SlJ8DbSjz2dqqvsjm+7vpJeme7I7b+mB4sp+BFn9KPRN67xutdwdLkyBW6QdXqpaS35fEeBU8E3Az07p+Bkp3TUEg6N8HABEOB53v4cM9mDNu2eFoylmcVeGOyn0lM8ODsRsG5CiFH04T9uOAIXicYiqxzpHFwpwzYKFhGIwpRtze7MEMfDwcMPi5rw8NT8RAMI1AT4iJcTsOeDqdcJpOuNkN4FMW/zUs93TO2/4BRHlXz3ZQS+yspG7eLZT6dPXpEjT0BlPGt6sFNvbfWnW/49r5Q0C/ba/wjcBVgH6FbwrmBOOrMgKNRYNdxrm7TLdXgS0gQJjcbAR6bVW5RuQlRu4J0p4ErSRezZebdFyupP013d4ua+nLpxf5a92CrWv6el3v99zXP7/ktbD1rdebvgw19Xpp59s+v8pcSruc8zVwpVWfZNPzIuCN36/N/9p2Xk7f7sqtcePylWbp11u31to/EwWl6+ZFF85Le3AO2+kuMRjmb0TG4NS6oG0Jz1PO6n5veO2aqb/bU8Muc1t5q8ax3Y4v44nLbVlv25Kl08/Bl1ztE4AjHrt693iAHcX29rf//gs+/F/fl5ugMQ44FilcA4wQRhVCheXS0OcwDoinU6n37ofv4Qi4ub8FGEjThCEE7J5H3Plb3H1/i7v7e5B/BpFHeH7E0+MTyBGmnDHFE6Ypd+On5ITGJ541o7kcg6go37Vx4DizCOxEqlAE9E7d2pLGojarPuZcLM7lN9QFrm/GQRQJElvs2Jb1Zn/b9bN+bhm+XZz/Dqvp15/rSJU3FrNhbhL/2RfmGiUp7zz3MWC79KS/y/dtWmUdXzGAIxg7xQNGkDJABPcdkH9t7VDklx8CxmGQMAIpI3OCS6jfnbhO994sogFYhFrOAHmQE8YRnAi4wyDeFsZxwLATIboPvtCUMUVwYhGIOYCzgx9FQM05wwVChhfa1IT5pO7MvShx+eDURXgCSL0nNGu/uEtmFcLrKJkFvPNNXG4dJ6PXHUTgRJONlYYCUYlDYHVP7hzMcD+rJwb2uWGcukLLx2lCOlVLdGkHF8ty2SJqQetF4Oyc9NeRK+iJTULmZK2QU/fU3sGHIHs6+OKy2vmgCgiC7zMAIraBB3KzpsxCXc8O4rw8K0XCD8oEchnsVcDuhaXr2MuS8xnEJLiTAAlaqbGUCWAkTAB2dwPybxMIXhilFMFExWLR1muCKkeRClWZy+ko6ar6Tnsq2Q1oISBfmKDXnSFPKzFJaZa+PG8cDmUdoCLq2fnN1D/3+ddxQAXSe2eTnlr6ZouuMcE0yf2tzUGASIR7WriqUKL5pWlrxkXbjc2fbQCLFqOeTTPRmcypq0WUfFovcccXJsiaFYux6nFimiZR9ICcb4ePTxLSwHrVol0A3gc8Pz9hv78Bgsc0JcTpBPc0G8qSX/rlfUBCBOVmZBygGkllrMxrxOg8MjIm9V5jSj4WRoFtaGbn1nIm2/FtTl1Cr0zZftNcbTgjs9CczaYKaNpdZe9nw7EB85OpHb4IEcASlpbs1vVxNsdxMQKf9lzWL/XfL1vgrj3PqbW1tNabre9rdb4dTFg6KI40YVpLP3hsewwyWBOeD6hryMIAMBgJNYa5xy2AJ9z+57/IPKuy2PFvvwBNW2Jpg/Q5dVgHql4lTw4iADy+Iw1X17vAwcomFTa2U0cVfW9j/PeFckzNlkzTpK7+2+ZdK96bu063PEtqtV0h672q6GWZewsYMtY23lGtz2Mzv5dghta6L114Dcj6ZwB3TE0/62kzt5/evonMa5Xn32iNlhf34wDwgSuubcsrpTRDR+04ch1ZNHRLz6FjTErXOJ1lD4l7HpoWy37MGCBW2VJSLhbeVuuSqujPjCW84waECtG5X3MWL/4JWcItEBUFjADGrc7r868fO+8WyYnyGzMXtzZG18eYcbPbIbmMEDwcEQ6nE272O9ztRzwdj8g5wUGUyk9ZIskPY8DpNCHlhNM0YQgD7vc7pQEcHg8H7IKTEGwAduMA7xXHesGI//j4iH/68IBfP34EMsM7h2ma4IQ4RzQPVBs7y67+RVGkftG/DU05W8NGYnaKdWynkijROpqlx2zueX2tzFsxh8+FF//I8B6UzBIjrae9wu8DVwH6Ff70UJCMuomsMR+hB069ThVGtRFqSpXJBd7+9QUvYp5zk4Br0kLgZYChJkpsZIGrhLuegpuieDth7Tea5yZRPV5N/3d5aNPizUp1dujO7o9c+lovjX38Qrtytb1HX8iFZ77wvW9ST1AADGIuLBwhJOrXaqk66/vCBGN9bOost5eRcyn7XOtp2gv4Wv5Lz+9L9P4xYT5n9pyb53n6S/kvpf8aQNehue9l1Itah4c2rkvGwJ+hFgOx5OFSx7L2RvGgvbgZTlDcWernBlU2ZSz6RBU/1th6VHAS6XtSa0MrvGcNdzt/WUfJtZ5i+W55Ka/X9/N1UBGANvt8Ng4vJoxtmpvq1izw1y7P7bdFFjY3eO1JsSzYZuOlhP6nXBrW+gEAv/30S0HZtxAX7r/9919w/39+kF0/RbghlPUYj8diqe1oRBiDukwXARqnLAIrgrzXi/rpeIL/IeDp539gxA8I3gnzPovwb/AOuyHgbj/i/vYOH+7vcfOf/0nK/H/+DTvvMA4O437E8XTENE0SmzxlxElcvMcYxZ2c1tlahVv/i1WMulhOGZhiQkqMlIUVaXEwxTKM4JmRITHQmXNjQUtK1sj+MjmfU0EFZwaTU9fNzabuJu715/pbn3ltcRtU1FOeCw4ynGbbbQO9l/U2x4Glz1vnt+xrz/3qpVkec69HhOpet6mflckh8vAWx9R0RcgKljj1YI15rg5KnXwzi22ndKa46hf2JnFdVUoWS0xFVgsiauKlF7pRBL8+eIzjDrubPYb9DsM4gkJQExIRtCaIwD27hJwYnEVIHMZRYhmmBOKM7MV9ooVJYB1HM+zIKSPGKG7Rpwk5xWLVnVJC4jbeLpVwlQ4k1tnBl7PKQfpDGQCnsr9yYhXKO4AiGAR2jGmKIrD2AT44BEdwYUAgGWencdVjPOIUI06nI+LxhOkUkTlJW6eoyrKs60EF3k5c5Htv8cypWN+La0mdH699Unfs4m2CJNY5+bIw5DhxVVmo9hii/GCusfWMIptTcwGpC4AdGOLSHjxJiAxiMLH8doqTLHS0yMvBLoNdBijDkVdBYsZwOyJkRoxR1ibJGGezVPe+uv9lIKG65XdNX5yY1KLwS2f0jJz/7eavX9unLuQBmi1dDiCjUZb5e3/wjA4f2HlezIrXTtVLz/qWZ1eQ+S1ogQP7E7KlzbhFZuu1LZ6NXuvpxDntvH6CL0JTdCDiWlF8aU80UlynZxrJcPqiSNiAjblaPJvyA3lSJRm1LHdAjllwUDIfB5L+9va2FOs9hG5MGVAvLgX32xmpeDC4gJgncc+uZ6h2GplNPGi+FIRhTVxpcQed244WPHeivA6s3KweGOzIylTrtiFsLR7NMpJI8rqsVp3EZf2YAoedGmV/KO5oFUSI1RNOwS0o517paxPj15EK3XhOSa6NyvJ5iy5vW7r23bbGOfqgfW6Wnsyw4nXbj2RCPKrzj/JcvxfsXBSeVuDclgUWXh4mmJv1OadHoBXwnZrfQfNa/OrW86EI46tAiwBMoFIeAch4AuG25HGuqsbIKNxCVttHeIiwj6lVimq9SfXYpK6p+W3l5bcKhnC/nH5LLOLV1ntM5oYebIui9oW9345r/RKY32eaYhuvKdtu4+d/W6WYtbTzvbFt3sOzNO1bO8v60pb7brlo7a31aO6SfY0MN99CbatHMI6LUSH9PyHpHEt9Hk4Ce6EKrdUDSTnct+aQF78vbMWSph2BNkxi96t4EZP/mzpZq9Bm3yfH2GWUGOGk+2oEYULrnYMwoVcftC7uGXjWzbogG6jv22JEuO6TBRbdwJd9oiaXnUe617x+vlN8+pHEIt0inNyxKLB6qAKD5j80blsGCihhzoDiXYWIkGLEECSs2TgGMOQeMQ4BN+OA59NUGua93G9TiqoUB5xihHfyICGuGHf7EcfTCUNwSIkxjh6n0wlPpwn7YcAQAr6/v8GvHz/CAThNEYN38KyeoYwGmA9TnY7yzJkXi6qQcg2eKHiWNRwO2TlKZdkL60yVeAuC14Ev80azP/W52y5tW1b60PbjW4DFycPLb+eee6zZqdj0U8PnyvuUE+kKnwJXAfoVvh1QCxcjB8vlq2AfuRCJe3VNYc/Zvtv5w5r80gVP3yqh7tq6QADNIlJzq+lPfQHyQR5XDj47VHuiqKJk17x5LXTNsSKr2T0AKtr6PTGO5t35seLFKbFMv3VZlibV55bsWxxIqJfEdRJ+PeU2tEfZ/Ejt27L8i5Xn+VgtyRPa/F7B6Yx/Tsvz9zq4LxGVr4e1OVyb33PPL0239u13AmMstpcpu+Ss7v16qSNn+We7jOvuqhn3WxsAACAASURBVBryFduU0VJGI8AVb3a3Am2DFcRN47S0qoxieM0YpeKYkvSdK/1U3GbKTW2/Fr+2oO7QSzPewyxHlWxtl0QQt6XU1ruF1V4BDVpZ68dW8jnMV/5FT7TGQG3yXcb0b38+NM8jgI94LLUSgGf8ij0+AAA+/o9fAQC3/8ct0hQbZqUw8XMGxtuhuzumlOBD0K5RvYjqM9RFnLgr9uBpkhjo3iN4wjgE7PcjbvcD7vYj/G/A/j/t8K//9b/g//u3/4ndLmA37XE6ipu303HC8XTC4XCEOwLIInDM6p6uxVsiHKSGDySKGDmLsI+IkFjcJxe7OG1zpnr6MzM8qQJfy9AhG0UCqXCOqLJU+3ntz37U0rvn+ffy7Na/01b65nm+NsjGRrtTth8tL6lrgvPNJU5bLZmf4TVV0n1dybNz57TRmBV10OxZ5qI5wazNzDChVubKlAZYXfiq62514Z0ZyLnBzVaulu1QWWWOAUcMcqHQfeYikYjgQkDYDRj3e4z7EX4cQM6JdTZJPG4HQi6CJgKCl3jfuwHBe3WfnJEowueElHIRQgkHqFrKpxQRp5Mol6SoMcslfU4ZzGrFjYyUWLxJhCDWFk56Zv859Q9NjiR4ctK1PSXAJcAJmz+TCHKzI3CIoHEAdiMcEwI5UTAAYzodcDyeMMUJh8Mz4kmUYGSOpD05yVnoPIkbdufhHakLdolj7oOUSSoglzEHXPBm4C6hm23ezEsAuWpdZxuhrBGZN6dngjNlCDJ37roGKYPY6XjV7zEnJEpinerE8tA8CnArSNe4KdllJAKYsnwnRjqIIDMl2d1iu+PhXQYjQO16S3gIJIDVXlXcbIrpvBnueHVFb+QDzbYYNQdWFWaiCCfsGlfvBrM7BPPsDTcb08ZLX7SHI7V52r/ye/OEp9nzxvWgK21O5jQIzvapCT4X99PFgT63bbb6VCDM5sXE3vd3qjkOpGICSbN01dpclLgIrU2qU2Z1DRmkDOemP4b/uJm/YQhNfxnIERkejh0csjhfmCaklLDb7cBZ9qad8fAOeYpInOE4yLnHUI8tgAtBlWzEhjIMA3JKKhjOyGbBr3wFdf1Qz1dWt7opoqe1+zWwVCTtR/fS+zWoQWdqXrMEZ5LvA1embQ2LQZjac7Qu/mW97aHUvAtZ5vOkpQ/a8qTzZMLlE/SsKaSKeU05Qzs0z42vgfX0tPzO9n9qn/vsi2cdAqMvyPBcUQque6P+KYRa89yOU+sj4HUgY9WXN2ktgmGtXNJ3VM74Pfp1sW9aMXeZb5igranlWCUAAwgf/9dP+u2uthHA8OMoS+Tv95jwEQFFptOUKjNQreTX6aS3PB8J2LOcBAHAiQT3hCxjcSLCkYCd7oNTO2xYzg6vSgpfDt1am3+zOm2BocW3il90zqu3NS4zvLFDu7p7XwRraUtN+mStMBzQ4//eorvOI6OuJauRQdjjsmeB5ZhD8Ui7avt0JyUC9myt8Kr4kZHV/8Zlzqe1usUl50MK2HzaLSnouwdtxyMBrvPfoGrprl0JPS+jPZMnYoxR3ohqo6W1HhF2IJy0pV5rsRAXDsAtC0n9XM7wM2tw9qvl4HZfeJZ+Vmi7jVrSiCCCcrNEN37QHVOJj04MPEHcuJvSdgCXWO/EQOKEBPGclVKSMSUCspzNcYriTcuLAu04DkgxI2bG3f0t+OMjTjHhOMnIeSf3XceElIHg5e7iHME5qCI51KFTllBO5l0GjMfjEbuUMAaH7+5u8Y9fH5E5Yhf22A8eU8yqGOzUVTt342PjOCOfKi0PqIIblQxGYZGtq0IvaakMoVOKlk2GeflCUYw2hcV6HrY8j0IbYANmePIiv+hPCi3VMd9b556p/UUbaZsxXqMH7Vz4Rof+d4WrAP0K3wzMiYG1y6ghJAJQzL94hvT6u+9WZYtyXUu7rmgeryHA90CK6wicZ8j+0qVk+yq7lnamC3mh7MuW5m99Xmqgvxb663d90z61aZZft9q2fJ6P2dv6/TnF5n+8Q3qdXHnZ8xUMmFkv+P0YzS/45wxEgWX+/n1/kaTZf2jfcn23RKVfcpUaou+uig3M3vEcn3zK+qTZ2bSW/m3l69XqQvr3xNSvf560RUPzjQAc8Ctu8KGkffp/H3H7X+7ALC6Wbb04p5EYTVkuMzglsPfiiTj4ciNMpwnDEJBixM0P3wOcEfYD0vEZYMb09wi/B/B9Qs4Rw48e+ZSL9vk4BNze7DGMATdxh+cbsTifpgnH4wnPhyMOhyOeDwccDkdMacI0RcScEaMI03OnxCedyJyBLDGJbX8SxDJXLmQMcRldGUhiBcoioNPLNAEibCTUNWrmvCSWztuX4y+9Cja+0nnm0FZeuvB8GZ+sUZQdJdmlVV5GzUVQoTn1paiQ3CwXjNkhpZwAjMhq7SaWG1TwMKtEwqzfWi88RahAUEUkKjHyzPMBsliFOhLBKkhCBfgQMAR13T4MCGGAD0EtosV1unRP3P4bM5XMzXixsPbCEPLSMg9Sz0wqujOLTmYkZKRsMcbFgwIn84Yi/xYrhllGhamcXd6supsTBtD+moZrymBW9+I5ayx2p5bwCQSN962e0afjhOl0QtT45znbijFXow7eAeRIheYB3nkEL27wvQ9qhe405ruHeqSWeQpmZa7rypTHdA8Xq3pVlHBFoUnmriql2sJp1lghM8VnAEDN/meRyJt1u4NY7pt1vAaFN6U5UzYiMgY6Abp2smOdW1J2tsSkRxbFN8cNFeEIlKsj2so0khEl4hUhd/vXet+/m6dZB2vFVv5zZTHW2vJy2L5hvDhbedGy2i7dv16LMV8O56kh8xuw3ZrKHNRvDYPR6BMTfxI1a6hYPUtIExCw26mNrSFbLZOyemNhCTnhNQkxw3lviLlroXMOiZN6PGpsQFtajNHqDHT9X7vxfS4w1DGvpwq16jenB6i5LCbQ7Mx/Gf2op1aZHfmkSjLEJRzcOj3RW8ACcwHWmT3NL/veorjlheXc8zkL3lfCZ7pqmiW6VSKtNUvFqppg52y714AlJYOV93P6aMJjqdPEOVaPeRfxPwZ4fIfp7/8oI9jXxaXspKWMs6k7vXHMngnYqzWthQ6YY0dG36Zz8Cmz/5IubMno25XX3obbvTwPlVDTz0+0+Tlxrn0vwVi1/LWbsOHq5V5+3aRe4mmZa36l7Equl+/b181uu342sWNj/FRIMe5T9ZS//axIUnCqhtFpkmRIQCfb6aKWWMX1Bg4Sg/y5nZyVzV6bpr9eQZbMR45WPjw3ZdiYPdF60b8RcMOmECzpDSdMJAr0JwvNZArtkHM/M0sIMyIMIYBzhvcOjhnPzwd47zECmFJS5WJzpSR9ZrV2G4cB0xTFwtuJ6tApZ3x/dwNABO5QZbpjnOAoIMaIm2HA0/GEHBO894h6j2vHeE4XAK1yUT9GgHqHW50DxfJ2jwS6lb+WSRTIGsMHbvauTf3autg6IK7w+eBzE4lXeDNcBehX+KaAgQUBYSRKvUtVUrp1hdZS2JcFRUvaQ45Z6t4VGqUwDJcnk7T5ZSdWTyaahf054vFlRKW0vx+4nm3ZXs+w8n029u8M55k1L3t/qfQ5c6f+ulT7a07ArbQLEvtM/p4M/iPC+7R7PjevKfWPOnIvhffrn+3rbk+w7P/eSsII/cpwnFttlzKI9LrYCDsYwqgvl5bm/TvztN6KI34vWLsivS1fhZfgayo3ri8J/WS3TEPDfgf8BgKwwwMYwMd/+4i7f7kDIJa1QGUvgkVwnnNrx6H40zkgJwz7ETlnsbSNE/KUEOME8gH5dMD+rzu43yDsDU44/McjHv7vW9AvGd4R/Bhwc7PHXvfDPiURjp9OOE4Tnp+PeHo+YHx6xjA+43A84PlwBE8inMtJ4ksWvE5e3WVWoWXxyEYAmJtpUaZAcXEHZKdCSxKhHTkCnLlNJqScxUI4s8Y952KNWF1Nvh+8ZQXNXRW3uKNPd76cwhOg2TMaFLVZRs+gGFjd0W6kX6PuOuE52fTpOlQXhQwgeD8r4QRW56siz5RBYHLIZE56ZY7rqrZ6GovyQtZxWTtgtZUhsZyGU2vpIWAYBwzjWP75YVDlC/GAIEJ4WativSyxy+EFb5MTwSprXG+L21rN8BNyFKuhnDM4yZ5idT/Pupazrk1fCGkVwKpAFwTkmMDI8MGD2RXht00dsbmoZVDO4BiRyOm4ZyAEYPBSX8qISACmMlZTSkg5i1v5LJ4jittjkLQtOO2zWJ2H4EXxQH87L3EayTm1XCUVoDMQfN3T+q9VM6MS/7HOJ8HwF61uVMJa+GUCsVmGViGktYVVYA5PEtDWCfMwm0KE/nUkngck7r0Hs8aNtjQsQsmIjHE/gNjB5wz+eMDROVBW7wAq5jBLWQdz5Wl9b1jE802lnL56W+FiWNbGJK20CfdlsOyl5dDN3/DKe+r+bJoWvxE2b3Fm0dTSRW2OGcPevArNbqMN7qv4SNKjKX+7v/Py+nTb3PiU9bzSs2z0ofc7reF5WtqRwcVynWfzaiFZzNvKbDS6FgwhIMUsLsvN40FK8OSKVwxRtquKFSaQpIJ7UBnYtvUywzuSMBuGgzsPCWs3tX6G69v+e3larH15kVSBqrV2k8/9hMZ6aK7Wu2zRvL5FVgAVtwSdRPMakUqnZc/5eWYbz4sVb8O5LdaRRGtL9GLBM/7GfLu/sI2fE1pLdHP9bMJyw/sm0NwSJs+xSD1+qJTDMOv1WyQ8aTrjFd2DfnBIfz+B8YThLw+d1aWBLMc7EB7htO3VAKC2763Cc4MDiSW6YyCAkIhxIIl/DgBHdz6/wZee397CG+osXwTlRg22mNXN8GyLY4xSqF+28fG8FVs9bxXoAfEosdMvWdvT2n6Tfj/O6rQUN/ruuYt43eS+sA76fVjXG5fDpKd6lth23s9V4qLAE4mFd9CUxRuQ/r1XFPFMtSeth4G2nlsWAXOPUgkHYtwUxUeGh3nykVjoNpMOhACHA3KxhE+o+QjSVouLvtbTSnmtj0g3vmfmos0/T1rxEkqbnknxBsu5faPjcwBjx4x/OMKoZNyRgDHLjO6Jimv/GCOcE1znnVieZ5bwQcOwBwCEEPD468ey3vbjiJOGTbMZEi8jXATxIQS5+5OEXcqZ8evjAcER9rsRd+OI3w4HZAYOU0RK4pp/5z2ejhMcRewGjykzgpO7wGmK2oK6Hm1JtIpNbOcU1WNzORHN2LYKf9zuA1LFwPrclVEmutJY7TrsaZUrbMEnHlOvKn9t/17n58vCVYB+hW8LygFiP2dEfUtZNH/n59ZqsSt/DYjrwXg9mK7wOcBI5fe0PDfm/VvbcoU/EBjjb35lMsalMi2rQKYl9M092StWywzxVV7eunV5a4te40+2V4Qr/D7w+59eJkSft+SA3zDgFgTCr//zP3D3zz+US6jF1c0cZY0Pg2iMl9zq7roINzVmsTyJNa73oOBws99jgMfd3R1ubm8xjqMIHP/q8fS/noSJSam4UDPBIYYBDELOwuJIemlPyJhSwpQSyMVi/Vl6SFSN45TrIQxdu3FbqATj6LuGiBEiRwxuM4LzKiRVt9AgxKxusnOWGNXqUv4S4+T3gi0h+WaM0c8IJvtML6zaOQevAlZvcXiBIiQuig+zfBXznUAYweqTwSxVRLApLG4GIyaxhpD6goYdUOGuYlZxs+7g9b0PTlyM7wb4YcD+Zo9xt8NuHBFCkLOAJb4gcxYreF1DOWcQWBQz4OCC13KNOnAgp9YzJNYhmRNYrZVTZnHVmCJiishZ47grkV4sJdCeQzomRdihVuEpi/Uymfvohs/EKMI2sUYXO66cs8RpZwalDIIKyVMCQ+YmJXHZHmMSV5JajsQdFAtyp9b7znl47wVvDAEhBAQf4MVEHZ4I5BvhtQNY3bmXOLq6Esx+t45lObyFN2Z0GxdZVdGjZQiOYMc61tBMaj9YUAypko6TMVABN5woZ3AieJLvorggbFFHBDiJQ43sQBTRWruY2+PpaZJ2ZIbDgB1lHB3D54yMFffjCtf70nvBFtXUKNq8Y200+9Ux1al+KXOr59u5u7cIrSVXq4TUFaI5c8qo2kJ9y0IIyDEpflFh0OkI771WkkSZbrOxK8IGok5hQ1tZdu/nWsVWw8qHzSo3+PFQVL6wnltkvADc4JU/C8jZ93V2yujhhBqexdRITLgncaOhsclljlrhjQnfgSrsotl3EZI+GQnarA0G/5zAeJJT+CdGxG+de++6r/sx5NnvSy6/XwomMCdkOBBu9CxkiGXrS4T01OyF18OnrJWad40WtBTPM8xSBZhvHcQV7z7N7zkfkyDC8YB2vcg6i+DNVuxBOIDx/A44sR+p9vfnuQs8UXXZPgfZdz3cMlTdpE0oI9iyn1uox4gpJPQzmnXWExg7ECZUy23Lb4qItyyu5bvCtbF93RfOqEtM8TPQrpvAwA0a63Sl3a2HRyGBu/1pAvjicYH7JgEoSnUpq9eYJCE37m72mGKSGOfE2A8DDtNUzn4iYAyhXCESp0JbBO/lbqzm4MfjCYDc2yzOUMwSy96rdy1m1nxKBzcyh60104H17QXjzKXjQvTP933nd5ahob+oXWCvg09YA1e4wh8drgL0K3xT0N+t9SAr/DbhNtnB2QlqXkDYtcRPR2Q2l8+84gp5veTXEZJb55cxWefnHDf/v8LXDK9hZM1ZVJ8GrfDodRnfofIr/D4wd1m5cGF5bl1UKvzVahc0+zEj/ufMm/Vav2V44QjY8P4J9+gEces2Z/BMeCpMnMe//QMj7jH+dQBcKJfZnBM8BrjgxfpMXTSTMwa6pHPeiUBwkLh2w25A/veMIQ+4f7jF3f097m5vMexGeOfAECG1gwisABRr1PYvSASWMTNSzphyxGmK8FPEwB7QmG8ZVPcCqSjNNkARlunprvGMTeu80j4kVsJqwV6sERvBLQHgnBHjpO7w3sgAnxt+FBnE+wloiuXfwvK848jgSxxM1s25Bfq5fpIKWEWg7cs71nHP6g0AxWV5i5JPAACmU4cvFz1lYxVLzO1hCBiHAcMwYPC+ZCA4uB2py3FxM04BGHc7DLsR+/0eu/0ewzgiqHvxnBlECTknQAWpInjVmOhajg9eFATg4DgDxMrEMuG19DGSrU2x7E5JYp2nJC7cxY27tFcdJ+jaVotUkvjq3Fje55zBnMBMyFliJ8qwKONSFRVsL3HO8k7f55zlnGEG5YQYxSI+pYQYo7qXN3eSdna5EoexKC74gBC8WO8PQ3lv/9rLBwOi5eN6l+LdPDfnM6HuXUAUZJAZ9l8rWZR9L0w5Y8wVPGJnhCIZcblPoCwC8+QIPjvAAZlY4kSypHPeg3OWNUAMpoxEhIgTMiaYGo5HACPLMwFwCcSMHRMyeUyJERuGcruD2Rr3BoS0Rc46LN3fljE5V17TrtXnlQq3xUWXYc50teeyJmwfz2k2/esMxyuisv7V8B4m8thq3YxTvXBTvj7AS5XLdTAPCiUpVffTbVbRQyNdnwCnqlQCkO532ZN2DorbC1EEYQ214DQWejpFHQ85f4lQlZlsbwLIMdYGcBWHd+0v5xFgovLgxL1s1LipBVGUP7zmFmJ1JAWWM2NeN1g9SfRzargO3bt5MXMyvK7j+tzO4KXVmwzffOLR++bsn5vB/+7lvh+tMunfAWjcOkNPpoo7EsyDEyFiiV9aaMtg9E4ialxzQsIjMlBink/4KPsAJtS/VQHYIxhPHXmYSjlS7o4/XYi+azrF6kKJQcXl98ivEKJ/WlPeBFWRQSxvH0msm9u5Yizp6jU6sC1v8bkZ9z4vla/cvenr2utvs5C3tGIRTUjafkvXzvNNk/6AKlRnTXBJCaA9khgV90r2tuXLPNQ9nYO1HVHfVuUUKLXd5yCIoHhtfp7IxrcGvzAvF0eSuOEWdXtkwa1Rz0Vi1vsh4MEYQTg18xW0TIuNfs+S1uq81M95H6zta7+XuZdg7XIQRWMH6Z95HjgUzzKMPQOk7udvm5kSvCLfD2rBbudM1DjlwXnAER6fnuGI8PDhAY9PzxhDQGa5TXvncH97g8enZ2QWMiF4j904ILMMesoZjiC0fHTwXnj5+yHgcJzqOGSZvcyisLwfVMmeHMYh4BQjQA7DEDDFCaJlSlg/+AlOGTXZiHXq910Rqmt20kGo9P5s0Gn5gpcfLsL7nVJXuMIfF64C9Ct8O8Aolhz2POcHdIcT13dvJZrnl82O3OLXH1zvAddD788FdmVy77SWukvZGzkf72kFf4UvA2Wmqwla99wq/pgQvWAwBjC7jDEvkWth7K1eiFuH7b0799+HbXGFrxNaNl5dF0OTYrmy5F/r9tDcrzII5Gtu5z26KKEMFXICYFKGuFhaBiaEu3s8PNzjw3f3eLi/x/f/+gHkHMKwQ4wnPD8/I6eEnDIe6TcwAZGbGljcs08x43g44HSaEGNUi1ZxAZ+9w6D7TfTczbV3K1XQrWbbLgPkVGGvxeNF6GaXcxXQqvvrnFRoybkwovIi79vhPa3CX2d5vmQLvje8hKIzC1xzNS6CVV/iildXgVnXRkKOUWLxqfXznK4sbr1N4EkmjCqBCgpzx4eA/X6P25sb7Hd7DOMg7dF2cWbgVsp23sF5wu72Brv9DsNOYp6DGafTqbj3V20OsapW62pyXqyWnQiSg5NQAc4cjarbRCKIsDtV97I5J8QpYdK9EGNEUtfwIggXd8sMia3rjRnUrXMUQRqp60USVw5wrmGuEjT+uAjKgnNgL/1yXhQOyDl14y51T9Es4tXyXOeVNG44afxvFzz8MCCoEkEIASEMGMcRQwjwPqjVuRf8YsiJWePYO2Ugt5FlG2axCv3tLamra5WkaQfL/1Be2D2I5bc4rhDGn3w3t+wMchkue22P4L3kCC6TuOd3YoHuQcisISGI4cBFKO1AyMRgSsUlZaEnmOEQkCEu8MHTwmrrc99Zyp3vHcvcwgOfUs9avq3y5P1rWJ1fhsZa1kLdLxEEyVPbN/OkIAm32PUM6D4kVkUeFk8RXoXYpF5eTImm5OTW4wxj3O1KeJQ2zWr7uTKz7QxuPTnMxOyzZzQZ3wZr591qLfPlsLZ4aPXnQmCyVtwVXgbv6yfuPIhb9KpAKXoa1AgaBewb8LL5ZJgwfE73VPfxCb14yOEWvql5vovnePhFOiUvAS1QLKPXIwN/qpv4y/B+J8ye52Nenb1/Pujb387V2n0rQhSaDUyZYgvltOtwPytx06vGChRaqLTNzpFCXM16YS14f6ii8AvQ8kjAzTOB2G58vecGDxJBvZ6LFrRJFGKqEJ1YhO2exOV71AIczazRW3IR7b1CbxzGB6qdM7bPMmP7fgOetf4WL1WoK+JAolxxz6KYbDhr0vqam3qTi8vdwDEjF8TG+O67D3h6fAQR4XiaVFCecXuzx/F4QsoS8skUcU/ThHEcABOK73aISRTcASB4oYHz6QS5nUlLUhbaOejMBO9xnKIKxQneeQ3LtgS9zSzwKpjOWqKXux4AxxI6hRqNPtIxqKmx4Bt0ZX3e7XGFK/yh4SpAv8I3BNwdElResTAPV9Nx/cOvP0eMiMhQXlWjyt0RJfP6XglzIvbyufc219xX+LLwsvVGK7/eB7bWyOeip6502ueGCyPcIZKKRcxSr96OqGMmmhuoBVbh2V9Lu9Kc1kU7+pI3mXpvwcl/Lnhh7+2u9A0jfbmk32H3z6MI91TYCGZQCNUaj1ndEaO/eALKmJeEDkAYAr77rx9wN+3x8OEB93d3uLu7Q0rCOkwpAT8Qnv7HE6bpiN/wUSwDsuwUp23ILJf94+mEKU7iEjpnCYPMdyAwnBfHfxHAlDPMjLDVc5HuaJs1gHC5hhv/yP4QStzmREnjp0n8V7O+rdI5+a1K8GU8XwyNpSI1bX4PMIGxtWlpef7lwCzPA9ZduM8V0hwRglooD2oR7jUmNljjfOeM6Bw4JUypx59tv1sGVGWnHtGyMZ0jDCFgt9/h7u4WN/tb7PY7waMscb5zyuBbtQgnAjng5maPcb+H82KVyVkUPmJSt8cEkHMYd6P8JhFEFwUBcmrVGeAJYHbInOD3BM4JPOmaVa8IYnWfEJMokqSciyV4zmZh4Zr1WVZWsaIVRYWMnBik8dRF2s7IfizenEnb671DCAHeNWUFp14nxEWjWJonUTJR4XlKGeRJ9xPBBbPadvBDQBgH+GJ9rjHkh0Hq8hIDnbROkpYCYA37rIIG7WvLwuTMgtCNg6r71EKpEFFx2164YaY4w8LaJRJXvh0bz6I9ZLM8d4DLcOyQHUCZ4cghE+BJ6nPOw/kElzR+fOsa3sYYTl0GJHBKEMF9EKG69i1SRGJRdOoEMw3eqUNwXiDRYoF5bNI8S2NFzkuc6RBerMvAr6Zaq7fPWcdsHcvO29fw2TfaaXiAuwzZajKLxYLjNX17TrQ/rPwSOuA81Px9eu998bIBSBgLWSNUx4Cbjtk7XQfFY4O223mHFLN2QRRJnHe4Ge6QYsTpeEQ0IToDYRgQTyf4ILZ5PgTEPKlHCELKEpaCAFW+MZP9ypQmYzwXItTOoUoFm4DBa9iDlM6s2PPLeWNklxmomfNW8FSFIcuiNkuzby9gpHdJeKMr85dzxsWF5G8GkyqcW7BvqGwuBl+O4/Y+/pJwnD0P2h51VDxzv17bVzzqdJiJiiVrK+AWPNs7p7YlbemiunR3uFMhzx0AAuNjl8+mSjxHMW5Y8q9ZoosF6nbfR7uylrKl9IzeMt3iQ1+CNyuAfqobBqkdDBGeKpUDQlVUqKnW5rNu9BLpaV5687LFFj3lUX/ZqrgFLwSg0i6Jxx1BCBBFR1tr620UsPPzDiIkflqk6PP0W7s+yZqk8nZeE22U8HIgPLDMg7U5Nu3/jYz22crdC7Hb1rDO9S0cnsA4kKR1qMLjgVn3leQyHywn1DuqKTEmMILupxOMbGzUSZqzqx3Ldh20c7bA+7MJ1gAAIABJREFUbCvLe6vfltT224MikVvN86h3WzMKMjI/EIqXjIFlHFrFF+NJ5UbbLhEwwIMJ+PmXX0WZVemNcQhyt8iMp8MRN7uduFuPESlGjX/OeHw64Ha/AwBMMWIYAp4OJxwhirS3g8eH2xv88vEZ7eEXY8bdKKHZoEp7RPLsHCEZ6T6Toy/oUvMi08xBN09KfxRvcpD7u/MafolmJ1U75WipAlqkeRE0OHYty7ud41e4wlcEVwH6Fb4dWLu82V9GIXBp9vxW7P81Cit49vcKf1ywK8KnWp5f18IVXgZLinqTr7bG5T17waISh7e+ofJ/e57XQ9gm2q/w7cCa9fl8TUi8R6cu0y2RAyGDpwkIWkpOgHdgteZkzeycEwEcs1jMKgM//pxAf5kQxozduEf+hRB+3ON0OIg79jjhFCf8fPoJkTMmtSxmAF5dxDITUgaO0wmnacIUJ6SUcMoJozIFXL5Bds/SD0ZhYs53JTkq7pkX1gEtaEax0EtizQrW+G5qmc7VtTXP7tZfI/weMc+3wPPSlTuwTReuMRMFt42K+Z7P5GmcJJPMVWG20CTCa08ivB2D/hswjAPGMKiwmREhcbzJ1TkvcmrOiDGDkZGyWGNE9ZJAzmMYQ7HgdCSCJwKpkojTPmQwK6PHGHZKa2dSAXfOyDEjJvlrVt85m9W5to0ZoLo+CzOIbWS4sSC1U6JZz1xdwYugXyzEhzCoRbp0PnuIdXaZGAazWIbnzPAO6h6a4Ly6vg8BzjuJdx4GkCOEoELzEEDByz8f1EqfirDQsYNGARelBjAsRiYVwTRLnbkuKLbJL2MKZZJRcVsr/6jhoOudx5F4rCgeYqQ90i0RxDvzOOMcHCewcoadpnPkytwnEJgzMifBl8r4daheFzKyejCQdjNnYTKyvG/htbu63T/9vjKqmbt07QqZ53kLnEO7XwJeX+8Lc+jgvGWMlpSdQDm/uCnTlutGJS2e75nJdV2LEhyrN5iAGGODdzRvVu8UKc9whXjTECF6OSg1kwoZ5lxuVTCDbUtrv3bOlbW3FCAt+v8KmNO/y7XXikBWBB+/F/zuDRB4635/Dzzxe4HFSLeV2FpxAu2Koe69vOFyF7N1Lq6ja5rWmQqa3/Vb612i4mIuaZeKH3OvJAbnLNR33NdrMBdAbZX9tUE/IyZMl/MW4Mbd/dLrxfu2osINluO3ho9apYs23eL+Msu3NTd7XlOoWO5I7t5uYb+3jc89y/hXRZPt/pyDW23OJQWOfh+iKoA3bRBX+Q4eubiSt2ITGB6kAXQkz61e7Nbrfh8st8W3WXs3xxuACMl3LAKrARK46kTbY2t7xBS+5UogdGgmBjjDk4TMOsWIU4xgQM57VWomIkynCSF4nA4Rvz0948PdLU7ThBQTPtzf4unpAPGYxSDHCJ4QUx0vBvDr8xGD99jtxkJDSxvNIvwVA9mS7ZcWFpEqN7sOl7JWWpxQySVBipwjxitc4QqbcBWgX+FPD+UsmB9UDaMNzBoLfXZzXwjRX3ayKA1bCZ4SQ7S9vfek3ZeDP+q179uBV6yyd4Et5srWSjnHIHxLq6702ueCN4xsz3FGoahZmCrFJdS58ldwLa187122U8OU7O3Ra01b/XkfnPb1r8NXtvDr79AnwCUsJeBgwvM7DP9pX4UAqonOJlBKcolm74XRnkWQROrKPEvYZnGpR4T8WwZ9IAx/GXEz/IBx9z3CEOC9sAgzAykxYkx4jD/hOJ2QUsYxV3sRp0LGrOVP04RpiphiRExRrMM5wqVBhFl5D9AzHMSaIBGqK/cGeQvzXgT9AKm8zDj0DBPISXqhTVJOZY+rLKu4G68c/7Jxf3dYi3leWbECrO9tPL4UmPV54N4S3c3Ymh2osoJZCsvvEeCsrrlHEKXCOu3QNNnf3j0pYQeCA7mTuFUPGW7ICEFcsQeNTZ6TTLijjExNmA31kMCckaKux8yYklqHZ7Fv8WGAD14FqA7ODwguiCDaMLeTMyQD4hmhWJRn8TcYxXIksQjlcxbr9lQE3QxQtakxN88iULdY5TIqzqETlAvPLBfFAk4RKTu4QUZLBNweIXiMO/ECQM6pW3FG4iyuydVnbXYZlLPgD6BY5Hof4J2HD+KyfRgGhGEQV/jOw4cAp67bnQ+gYAo9VCeRWYXo2hcWpYUihQYJzrJ9rKawZe2URQERiHcaGwQiwxdlU9vi1PqlDeQAzurGnTSmvSoNJWI4l5HIgyiXvegdwFnsBs2U3WziSSfNkdPxcyAXgZQhDt8Bxx7MBMcMT6ZIUF13milj8UqZG6RXe9LRsSbkETxbGYlzFFbj+XLzTtdXc5ez8rvTp/nIqNbzuflQY5uuuxDG7B2hCkbastuaShsMLes85FnKpaXsrHaaf5uNZylfGLgWQxyGbxa4eLtfbS+C9127Be9BFVJqRuK6XsnpOiSSkBapiV5v5n7m2UUV3rwPIHI4nY4gEE7HY/HWwixhWwLL+css7lbFE0uWsARO+0yiKGJhG8p40ey8VHCKF2x+Bu/FYjAZDjPCmJTZ38dynY/f/OToeBvFyn9tF8ic2rxn248b5b3HSXlW9HKhgs92Uvfocelp4TVFze80DXz6OL7nTKzDBIuTzhjRz5dXjJlmeKDmlTdjSW/u3Gu0acO7aMquXkW4vPF/Ccg/GY6Wf9WynUtZgAga55boE63Pw8iV9rfQMK6eROX91OS5aPSi38+5Uf6ccCTp16A7ef/DA0BA/Eks+KuXiUoJM9qTAhiZitWuWeDb1xO1T+050apT1JWyZ6dChPWTyebbRHj7H38ACJj+/nMZ+wSJxQ0A99z7ybBz+q5cQ6QFzyQW2TdcY4rPp26JK99/0izOu1OKJ4PxSNJe6Y/8PScYtzUPALdZ05Z5qHQTADxDYn4DsnZP0LOTraQ697kZyZbeYDAGfbI46dmq07PsjoGPVOluu1d0Y9rQBPZ4iaa54fW5sjjoTr/flXGr6+BIAGWlbNx5lZdyEuYMp/d5IStI45l75JyFBsisoYuAU0x4uNnhME0Ai6ccMOPh9ga/Pj3jcDxiHAY8H4+49zcYxwGnacIpJjgkfP/hHn/7+VelsWtrEmccTifcjCOeThMcUanTxrcQtSvAtahybtk40iIVK4LKJXxM54VBM7XKfShkyMZCXSMpziSfw+c/za5whS8PVwH6Fb5NaLgeHdG8huGVctB77kXYvDiWD5/nGNkiYPrv1yPszwJvvQ587hVwXWF/bqhxIpt3il1m9+9tIHTu4gDjfVKTpP19hSuswfnF1jPl5NJNRCAv7pUBAjKXuKhQwZ0ptxXr2cwg8vL9p4z9bsTdhzs8PDzgu9sHPPzLA+6/vwX9pntB44ozMw7/8YzRP2AYEpzP4OxFgKZxlZkZU8rgmAqTwi78zOL2cv/D94h/V5aiSzARVdL+tPduowMKY6Xl0OioVAtVvejzOkO9jDAt3rwZPoeR+Jblefu+dRn8OcGYQCbbNEv0wkzW+RJBCau7fxS37ck5sVTIA5CPRcjcMeyphhLgIjihps/6T10Nk3PwagFN5JBZXBQf6VTdkseEnDJiTCrPFa4WeQlFYG7KM9SSQy0uvfcYgscYBozDiHEYMBRFEgBQ4XbK8k4PCVEq1b3CAJuLdQaQLbY317YoX6gI0+w7SMsg0z2ArPFKERdPCoAKxRwcsgrqq5CgxpAX1q0jUiGu/AZBXJoDADl4l8RTA6pgz3sRlPvgEcYBYRzE5bQXN+4ueBGcewKcL0LxYj0uhyOKvouJFIhFywZ1D+VmTcsQKWfMXLXbH+E6oikUpWhdO9wUbIJSrVnbRCVvI++UNabrN6FaFxelYe6tX+2czwSZMwCZp+KZIOWsdZrNmq6i0o+XYyBLZ4Kdtts9Q7hSMOY2uKo5LZVeeJF/+W3uFrmKBdr/V8bmHIO1qbZg8655Jv25UguO0j6vlT9/93p0bvtL1kLnbcCWJ8+ebbQqEgUn8U4xb4jQpyJIkP2ruIK57mvX0ALmfcHcq6aqEJJTBjRsS84ZjlxdxKbwRF315TyVdaBeHJoZLvtjMSrba+oitOffBiP+Neff2lqk2fe2rX3fX78uPwV+L+b8p9ATX9t9Zt6LKoYTmLAOlqZaossbOwcALP5aPjvt0k89nm9x0FIRSM6jkS/HLD+RCOyAXpCup/Xb99lbachPyaswNtkdgPTzR1QMKOfWnkkVDOZBHER43g5bG1Obm3Lmb7YgdKfYEh9s4YF6LgvcMOFZcfbaWdhaebflPdPy3RwE3748hvpL4WE2FwDw66zha31Zg6poIMLjR6AM3iNxYyVOOECE6C0ObpXe7Nc8XIy1RazSudQ3QgTxZgX/SMCAH/DP/xTw73/791npL4fFtbOBZ1o+3yp97/jyuE0vGVRd/3J3CXUcGJhSwi6I+Ct41yG4Kcr935FDjAkheEwxYQgeMWcEZuzHUe5JSvPnlAC1WH/Yj3h8PjanvdAeJry/3Y04ThGk71i/v4TWsjtQ+buSZ76P18IvGtVpRn0Nad/krPVY7i95rl/hCl87XAXoV/imYME/4vYvX7zBvoi05OXhT6BGUF8vXu/Fz50TSWeadoU/IbzXhby9TJ27cJzbB9SRW+fha2Mk/HngDWwlxYFzApyofV+JcqKGnF5Usz6zNHtYWqDXWwEtc6y0V1fan3YhvU/HPm84kc9/qvSjUFfi1rzPmb0BDwg/hiKMcxp7GBABGafYcB4YCRL/VCxL9aL7jwiTTYZxwN39Ax4eHnD3r/fY394gDCMSH/EYf8EuPWCaTpiOzxh+GJD+FsWVM4vQbhz3GEJATGJtnk4RHE2QmMCJwYkLA5EJoL848N9OQN6J9TwBoAMmGG9OWSl24WUAakVQBBbNEIrwsO65Eu1u5qp2KdVYg9etgfd0td5aYHR0UCMMBIDWOPBzoosiLCf57dfoQRtzFcwQhIeTUxIX4AA4M1KORdHIgeHdDRiMzIciONcCu47Zl4SjuGl0DwiDWkY7Qs4HnE4BKSYE58VleozIKYlbcq8xib24FzcrZnKifOLIwweSuN5eheejCc8HeOfF0lgWmlh8sweyxP4j70DRhMSEEgSQze6s2dvFTNA8KehrVAEWs8TXbGMTk3NIp6jnjNoKkQc0xIF4fWAwV0G6MbM4Z8DXhWNyMu884MQtNKWkVvJsy08E594pfgkYhx2GcYQLDkT63slfBC9tN6Gczlw5gVVJgqF/TTA+szJfO4LldcvuarlgWgbZuhJrmD61rk9DJqVgCXlB7LRIcU2dyJ4J4jJS5scxIcODmiid0oQq5CQADiMyS3RLYsaBogo/0TH5Fu56i46G7nUbOn1tFmL1nfTMLCbrdW+JEVpryjk1tWAotogVvCI8n0PP/VzHR2Yx3Cs3EYoPhjJ+8xLsaS6A4llvt6zy1pz/yt6Q367gVirf5LkvZ2H5ToJXHDQkis6rszVjdKWeZ23PRdgtE55iqjij7AkTyjd0pJ5dKSXklOCc2NZ6Zah3rqI1X0oJMYr1eAZXnEXmpUX2TvABDPGSkTn3fbUmlT5UwX3FzYyUdKWQMapNsPdyS/RSb3POtXiiYZcXoa+bzdtFoL7muidmzzNc1NEbzW8AnROc2acXw+JcRYcSL8M84SsJg0t0zLmv5759aT5NKyAf0Asrt4Tn83xAtUi3HnjUOMZAi3cs1ccFp4Ca+i22uVlKm7DY6zvGuiB9xxXHC5VvCqdSm8WEH1AFiC8GurxMVi3U5xvgDdCu79Q81+rmirBS121XJeGuoUlbS/+aq+UELeGGydSRtU5J14apIIjb9tYTwfHvPwNUz16Pikfu2azR+/4wqgA5aMse2MaAyxqZwwOL3XsE4yNV7y9vgVvurcgfGmyvkb7AAL5r6Ffpt1ikb0451bQmRB+gFvcFZ1IZ4Vs9556pWqIDGiqqLDrCiRi3DERUQbm1K0DG2dqXIXtAYqkT7hn4hX4C/62ugaLwC7vbNAoorOPjNka3JVfPLP0n/XuHqoRsHicOmtGCWN2om/ST26BfqN0XhJRVpUfph+AcUs4IQ0DijCF4IGdMKeP2Zoc4RYCBwzRhihFjCBi9x+MU8fh8wN1+h1OMglfImbM6nGLCfhywjwnHU1UMygyM3uMUkyjRqgW6d2IdH1MJ+rLoC80exA377Nxt7pP6Q9Prqmro/Q7XspTCqN4fq5cQG0xsC9HX5vNtW+wKV/jDwVWAfoVvDgqZYdyR9kKH9pm77y8qe5a2Y75wdYXzpeHtpOMVvjaol5SXzeiXXm/rOsRX+CPA2lppaO/Ze2PIyXOL+9bSz5kki3ftxdlM4Dby/y5I9Aor8HVNxBpD1eEOw49BXSl7FQo2URobRoWwFBJyMgY2wTkg/qwWpuQQQNj9OOL+X+6xv9/De48UI56fH3F8PuGYPmIKDs8ff8PhcEJKExKL+2iJAewwhIBxtwNOQFJL9RRFmD5FcY1dtNKVse8IYLVWdTDX7wzP4gKvl601AhDqn0tvSdw517fmLtAGpCV+eJb764CXWJ7Xd6iur78gmHvCDj82302ADmawc+oKFQA7SFxoIJBXV99ythJ2QGEDV0ZRB1SZIuKWPyElh2k6iQA5HeBtHaUM3DDixwjOjDB4OO8Qgge8ukImRhgGBOfgg5PfYcAwjhj2O4yjWLi74IvAidgEYRDlERKXzY4IHBzySQVSufbEmFKePDw5JJ/hMiFnFXa1zF9bpwx1sazjQ1QF2zkDQZipxRKdZZRzjojRIU4eMUw4nUSw5ohATsZc4hoz4KxfHuQZzjvkHMSDgDGfvFie+yAKOsN+wLgbQeTEklW9C5D3Ne55I8wy1/ll65lCQBa8UXCCnr0OQLZYz8aK5vmerWu+pcw6C8oiVBfswqQMveJCc0Uotnii9Sfl35nFLqeElEVxhFWBocStBiFT6hTpLsKFNO1wGiM5N+/m1pb1ucd5S0y4fj1cpaGatiy/9Io/a3C+i1u09hLXdcLUzbrWa7uEOdfO3vkbo/FK2AKpsNGRaV2bNjmLULyuUxs5ObOqjwEiLZ+hnjsy4jSJ0gu2z4wWGIxknimYkZLUZviYCIiI8N7DORHoM7gIyCujuRVFVSUYp2eRKUKgmY92vb4UWguyKtjpCIIZbX259DZFkc9w8wxl5r+ipUZamOf697wlrt0vDLZa+CnUwJ/xhjugxkd/S/8WaxBtCI0KBCCLnW3z7hZVjLYsd57frJJr3O/+O7Deh0+yRH7poKym4xftu9eAjUtdx7Ij1yz0Ffst1rwJwltlq5fsi3aMHdouM0ydyM7Zqsggzx6tm/7626MKq7fwYNstf6Z9H4lxx3ZCtCvw9XNwNjY596X2tEKP22dZuucMEcj0Y9mmaHjHRJ079xYfW5CCJ6r7wwT0gCg11HqkpgRuvDSI8P1xpaXmkv7jZ0R+jwQ8YEmzrcHItYVzq/SKM2zsKmcyZwYTYwexQD8cGYkZd7sdfvr1ET/c3yLGCGYWYXvKYFcX5WESN+xTSmAkeJKwSvtxAJgxeI9h5/F4OhXF9sfTCYPzOJ6mYs3OaulOS9XQM3CBw1ruDii0ElAV6eUOQYsCygrbYvhd4QpX6OAqQL/CNwOVgcmN8Lxwd+wTCqHLKG4yX0I5d0zRWZ0MQLT2WIu/wBIx3sILaL32wl7qWv3NncumK/zx4Y9K5vxR2/31wRbb8j12uXG7mqtxcRc7Y3CzMWXXEVe1NF+2FFDBIggtU7Wj8fnCmjl7o7gMX996/MQWGUP6D47sP2UULO8AjzCOcCo4J5IruRz7wmBnjZUq1qfqcvpnVlO5DHJHBHoQZhGRCAm9A5xDzhmH4wGH/2Ac0i+Y4oRf//czjsefkTSOszFHzNJFhJMBMU5gFgs5EZ5POMUoF/YsbKhIwOGXX7C7f8Dw4wAwgX9O6tF5j0iHGueRqqtq2T/1wkz2zoQYJpQo1nvVmjEr68uEAJv45JXrq3WR/T6w3PglDviZKl5O1X0avKR8s0IHURGmC3MrwpMHGEhqx6uOx9Vic488E6IXNmGZZClr4gMoj8AkQqUcGRSCrAoGcMvgYwaPAMBIU8SAESkniZEOFsWPQawoQwgYw4CwGzEMAeMwIAwqPIbtsd6bQf1LMHfrtihNMAVoPEknlvI+ePjM4ABwBCin0tu+aFFAMd4POY0TrhOQThHsPGgkpMiAd6o8QnAuYYoJforw/gSgCd0QnFjTewdyUqG1TdxDRsEDUMaw9/BD0HjnEgN9GAZABejmPpFCwyY1pVpurFBa7y5Z+kPKCGUWC3jOWb1pSKxHzxrX0XuxoLdGkY15tUAVt9U9084E8qY3bLL9wv5t5qsXmy1XuXfqGltmpt55zG2/Cs8zZ6TMYEzIcJgQ1bMCl5JbIYEJAcQLw3KPt5YyspYAQgAjLliUc3HBnAHOqO5EC0/Syuc2vzF5uavjHGqsyko1bS8IWY5yC1UcUFnEbdvr1216cItksnq5e9f/rVdprW1mCVboPX0f1PKbXHXd3g5o4fOS4W/bm3WAmFkMyIjAmUs5RKoQZ54jCOUM55yRYizW7mAG+Wr32A74dJLT2Xuv3hEEH9f+WKxUxVdJaIEwDHDOI8YJ0yQ2uSJIp0JCu3LmqWiJHLz8QWQJ41H01mibjp7Px9ocdR9bJRntQzkfNsopWdee55ZuHd9klmGlzVtr7q1k6mr/N4Cw7K9ZwTesoe3ML3t5oYCX9bSmfs/73GUwi3KaPb82fwsDGOZAOUGWdKbHjgYTTyEiPK+nYO29CcdGXuJ3QN0/N+/N6txGsP9XL5OvdeX+0hnfXONbZPQsw/zeZjHq274DMp4Pf/0OT3/7BYJduApiuVrsW/GmdDDgDgRCwsfG/T7hVu8OuemB/aoW/K3gmks75MlOHzsLqbxvy3X6fffjDzj+/R8dX9KXsrR+IjyRzOMDVw8yGRIq4A7rAm4G4yMx9o1yZv+3raX5NEcqzbPTu6O9I3Dn5Ybh1CI9lbcWymnZPvmfqYzcsijbthb7dm8z5/ZJ1+uNejax8bYY84fGQIsgngIAXRdc98sJQo46AAFUPAU4VGvzO8h8MXOJy25l36ly6rOj5p3Mg8Wl78dJxw/zM2Adv3GhibmMDaHO88H2tQ7sjtcVaawuE2LnnEDqGYsYeD4cQSAMwWPnAqYpwRPwdDwKjaHn55QyODG8KshNKXeriDQ0lQ8e//vnX3ETAgZy+HCzR4wJz4UuIBymiN0YMDiHSRXlvVNvXXCod4ElFDp0NnqlHUWptqFqmQq91XrwWpRs9NjmrNQXW3frL3NKXeEKXwdcBehX+Cago4MKpT1D97x8Ze/N/dlZ2LhLrqV5CbxUeP5SeE3aK3x98FLL8ysRc4WvHWYOpe1l85uuC/kKnwwEwP8obpPJuepCtZGKmHVkThmZJQ50+ilLyGCQKnfc6V8H96NYnH/87SNSmnAYBuBngF3GFH/BIUXkKSLHqbSBSQRKE8ll/jROcN7jeDyJ8P1wwPPhGYfDEacYa1xYInhl/g+7EYADEyOFCUgZ/BMQqWEUXBqPloZRYR6bletKfi4dqM9XOuJtYKG75+BW6EqiPRycWCc4ZZSpBaaxJLcogZaBZkymnDOOhyNS8Mjeg/wAl07qUplAEVX4pAydFKN4bMhZhcYOwzBgN47irn23QxgCQgjFZbsJusBZLdBF6FQE28qFM5vpZAxVIrX0NkttgnNe/2UgZW2rxCHOJFbfbUim4mbSLNplcYvQSxvAOYOcV71ZBjmJLx9jRIwTTidlskEE6E6F4AGDMMlY58sEghSQUyp7R1y4qwV6CBp3ftC+aV8dFdfoinp0fTSRMDkXbpfxbIkIlHNxQwkVGkrfxDuBJxOiO+TEwqbmmt8s2PWFsGDNtJQAsAModZvcluf8SKYLv51K4ImExcw8qbJSLq7zsykrcS6x5smZcgR3ZbZMQ569a9d8+9cjIGHqXKq3fZipEJQURmmvqwksMa0JCLaukDVd//sMK7+IIuZf1/rRwto5sDVvW61cy19Zqy8nzFrGeRGyc6uqpem6geCVRcezdihOMS8O9pV0S6iiTY6peEkyYXvXr9kl26vyiezLrGEE9Jxc67YSE5mz4CpKyJy1XG0t1/GsSkNcaItAvaCrtVf8Ws7bNbkS9F1rJNCmm7f7c5PzW/WuvdsUEFwBwPuOywQRC1m4jzVcPhcMmSD4XPvmN0grS47+VjDe00l/5Dlv+23/fv3bP7oemkW5iuI6Qbb98n/xyD/lFdfe/c5o93OPo/rzoBX6miWzzMXcGTx3bT39/R/F+tn6k7B0mW75raw1rwZzuNEynmkdf33qs/XVINGc/hDB/9aZaWlN+eOJRGjd1jencWxc5/tlC04kgmW3kse8AhiYRbopryXw4r5CEOvzNgRA+60Vnm8p7y/bLAnvWKzP23Tn6Km2L2tj0eY3mkGcVGX1gANVwhQF5oHqaJxiwug9piTW5Xe7EcE7PB1PSNzQIlqpV4F/igk3Q8AUM4Yg6YNzGLxHYiCmjB/ub3CKSZQDc22nI0IyD1MbfT43Bu07yNUBVaOUIOHcMqhdtY1EfW0/lWfGQjn1Clf41uEqQL/Cnw7ml+I5U6UmbH/LRbclM0mJvY6dsHF6mKVCYdQogZGlQTXvpdPHDufVy/p5cukcoaEFvKABV/g9ob/ozZl0L4P+6vM1sF8qfF2teQv8/j3o8Zv+VqYcWFxTvZunuEtKQ+0ymzE6S7NmYza/ZK59K/CCfrTMhNfC7z+bc3ifFn1Ry/NPqWuju58yCnOmGpG4i+2Ex2yug/W3xULOclOsMdQIHmJVG/7iRSjEQIwTHh8fMU0njMEj/5KRkTCl33CMk8aSzhidQ/BiwRq9r65qTycwgOfjofw7nE44xQlT1OiGjuBIXD0ndjj9HHHz170IAjIjI4GQ4FljRTJQRRPR5Zu/AAAgAElEQVQqSCix0nJn/e1MeN7ejDVlN5ZKxCxEKutq7L8T9Oecucn9I3iiszVZYgqjrjsiiXXniDB8GITx+FtuyEkGYwBoqnNO1mcZk8JsU6ElcQblES5HIAPDg8QER7RzhCTetgrdnSeACSGohbnzCH7AOIzYDzu4wZfQCI6MNcNAZmTqjgQpXt2YpymKoCpnIFemka1NR2J9KrHYK3afux4szFmzrrY0KrR3wYESOiURAiPHJIL6DKTk4FxCjBFgRopeeU6EMASACC445Kyx6a2fJPZB3vtC9ztnbXciSPfiyp1dv0qJtE02k5mbPsnlgYzpBVKPWZWys4Wdzc10TrP7TD/wFiu+XEzUhNoE1QSoooNaiLdeuUqdKOOiQ1zeo08Js46q+y8JM10VKjKLi+xiAar3J08Ex+JIOHNGdpD1mCsz14H+f/betM+NW+cX/IMsqTc7i5Pz3HtnfjPz/b/WfTPznMR2vHS3pCKJeQGABFkl9eL2khMhaasWFneCIFZEAjiQuMH082BRk4ygbI6MdGKrkrGYsEHGARa9MpBbQ66MUZmAx3AzdQOuI9y/724fptPNgjO5HP3X9jSstJD1uz59q914ylitzbA/tHl8ut7BmLW270H3VsN3qtQhXlNan4VArialztmcZrVEl1AIVXeESJjhEK8Q86zW5KS+jVaq6U/2JWcQAaVkBPXuIGEcAub9wY13z0XOyeKqm5KT5qxC8xhMgUd6NmgMeEPUpHW+CBMyASmnSpNI/1gFj/Ww5uNHh3VFE4BS+ndYu1nNtbsY54S/r9fdA2/53lBOV0mX9mglHlXp/nteffrIIr4WPFR1X2levj6GR74WPNXy/CEwPznX6OOrj9N7xOPjOeZYvSz2uglvM/zc62cvufTfqj8fguV+0IMXdI/rztxu++sMs7wnRLAKS5tSweHdxyq0jniFhM8AmkB1zQuJvenr0bA0ue8jCPHXn4D3H2q8bUDGr4BxWdO/xuZNQHr3ocsrQATL9w7/AM11+E/cuzq/tDOQpn3NhE/kw2JobYlr+Ai5l7434a182wS5vm2+JqagMUautu9IhbFkluhD6CiPX629N9zfV5oMcA6lhDbLSgMVxZ33YDQ9SLcXMbAnxlZfGh0TtClCt8roiOcCwtWvhPQX4w/SOtXWtv6o7dRxgsv3Rmk5cmMCiHDdvrNv7ohxpdcTA//3//E/8L//3//GLRdcMUBB+pGPWWSrh5i9naNAuGDCXhdU4NbmDtWqgp0de6ZAmEvGJgYwInZpxj4J//9QClI5YAqEi+0GKWU5WxAh5RaE5Wq7QSkFh5zFujxLTPWUCy6mqB5ngp7vGfdzxnYKmJMoLNthO1UvWw3GeVyY65zw41LT66QVfoYq7QJNcTi2Cc41roojxLuzhtuyF/vVY3bZM3wr+Gb0zBkAnAXoZ/ibwXhgf8gVun9dCSGXR8fnICNQqBIy9sr/2nXN2giII3yQttdQ26QeqPv46qX2qTNy/XZAkDGnxdPT3xgYEyYMKcYxXB9TPvrmsXDK0v3h6XgmrJ4Ng6DvFFSGgzIhi/7XGBG8SLvMRN/QgF+7k2NzAS1VrBctmVqUUUvtBDouBhsBZtfbsqShgiwCBAfnGfV14EvcaVdLq2dK7B/ypnH64yYUr3s0jbPqGnHaiEVo6Jm6IlQsKCmj5KRnyIgwAeE3tVanUIViEgcaAGXs9wBwi8NhwrSJyB9mZGTM6SMOWcUVDBS1YA3ThGliJHVBe3t7i7u7OxzmGYf5UIV3Ul479BdmcC4ACubyGVOaYO6x5z9mZCogXGHDd+LmciR4YEwiPRAHdSeL5taN3dixHswZRWXkppDj8x3X6o8AfYW40ljj/Hrpij+Oqf9YaMoNAYFtfttcLiowdWxmz4mzp2zMtILAhEIiyImbCZEuxf07y7w//KVuwF8JdhZ35FJujOI0HiBMMWK73eDi4gKXl5e4urrCxdUF4jRhmqLMyRgQQgSYUNTfeFEBZwwanZFZ19yMnOUXBWJd7jg0FlqAmVGyCbdLFfKOYyCW1I3dSdRCElT3ziwMpVLEwjpwQMkEoox5FgWag32rgtPtxQUAEfptIXFCMxddp+q2McRqYS7tY0SCuo3W8ioXVPdFE3XqdzamdeUbHyuVyjTVwRU8YVboVeCtc74o25sb06vFHbbnTWDJRf5yydK3JaNwBkyASACCuK8XV6RiAU9FxygwiinmDHO+j/zJIghHq5cMtLanzWgUZGlnYQQqyKroFAEkqjMSIAbTDAaQ2VM6bTUkMAISSEXQAVsUHFrxaGc5/2dwzHL9W6M/b+FnrE1jqBOWAigP35puouHGzkGLs0sds7buTSBuahElJ0DnayByblVtrcgzjqx7nIR9yDlU5RKpg4Zk8C7hdeTF60FAcFxiolDX1fHG6XzNucZXjyGCcxrmooVuIxXgUF2PRRV/xPVqY1qvnfGOjiNz9fi6oPZfTJN2HQiiLCSjVUdE7BFILPwMLxNW+nPM7xgt6te32wOqQsLaJzg999fwxVeDlUFd7YonDNfLhcF5OjzEdzsGpc5xR6/U3372PqWE7qjqrvvTwQj84ooCp4CAZgrsa3Gyoce4O82Se5li9GEROgtvdr+yr3yu1crwU/W4OMbviTQ8J4gCQ3n/QUvvywNEkE4ALv81oeReOHo6zKSU4C3QrYwRTIhu2EeOLc6dNUk/3mg+r9Cev2LgVpUeb5hxS61HfDvrPbX74712HAgYXMG7FjuLZ5/e/5oCgaGEYhsvZH7tA+OCJW76Ffc0Ty0HQEIBvSdc/tcb/F8APv77HZhMwZdrHHvL+waEu9AE4r5+RvJeM3APca9u42RtNYWXrX2fC/6f//ov/Pnff7h5ZaZsy3G2NDd6zrsnwiHoN67f7K+tmBY2iUDIxUoRYfak1uC5qDFKYMyZMJWC7WYCUcIhlTbfWcIigYUGyKVUpUfYe5J1mErBFCSEyxQmZJpFeU9pgSlE5HxK2VPHSwvXY3qdg5GAoqFyOLjzFJxS68IrTjtvMXTzdh1c6mR3k8yNAUshRumc4RsDkZ/ZT4fn7uf/dDgL0M/w9wND4GZ1cmTxe8NvoCd4RsK6xkXqsmqUlvGYeyaGprCNzH1fiUXH+Kp6fLpZrdXdydcfBWvn+1PPnkPcneH50JhH/sl6ugUs5uK3PzCPJT61Bt/viP/S8I1aMjJFTijceMaD/Vfq1ZfUYflgEVe4Ci6pEuRVe7WrHS1+7BuPg82179i4o/NvpY6PwWw/7nx8mZo9O5cnMePcJlc3wOfOuOVh7NFfUsOtfieXdyJo2WAj8YvrN3JVTHieiwjPs8SgZhRstpNY1U4RnLRtyqFmMEoBEicwCnLOCCmgXCbktwccyh3mUiTccQi4ol9A0xbguWNezfOMnDNSTkhqrc5afTuIi6zUFGMCbrmA/tjh8vcLoBTkUJDpTiw6rXZ+ubFxiViUAIK4BI/BWPViyWdC2Ro3VpvLFh/eOB2eE/Hd4bGV+FqVPZLvE5naHU1aBZGACAftZQEgbsfpNcCfZBAqU3DgaVgeHa1KhBguEUmsJUW+LfkEEPBJ5gJeAyE2IbIJnUKM2Gy2GtN7wmazwXbaSozyKaDF+Bahsglti8bpBmIVipdSkNVt+jzPCNw8IoDFgjTnhKzxi3POVQhdOGtcYvOy0qymjb9jrE4L20Bq6c7MSEWEzzGIMAslIycAE2Oe1bVj55FB4hpa/PJSImIuIFUamGIATaSupKX+3GogfaB1Y2WimWcBWZ7K+CCoP0ljf4tlPpcCKiYcbIIjTkOEUfOgoeWYRbsx1xoZwc0i1lyp17+MXGTNg816nJXpRiiKAxrDTP6ROgTXZQ0nV7KA47BiDAMRzGZQZro9iShIuHk1AZsr5HnG3Yc7TJjkW2UAbsMWXICZDs1aS2tDAGaI9d0GhIJNFZ7X85nCBhdI2CNhfhbGMCUk0jAG40lxoSg2HiTHc+Ai/yZ0tfcyS6z35fmavTEDmNqRGUBz1TtQaZVRXb/uFOPWaaw1pl1QBY8Y1aGwMnCrYFoeLlobAmmIAt2HqmRYLMwtBEs1lioZm4sNOOs+RVyVOWwPBoAQvbPa1g7DHYECQhR81WhPQi4Zm2kCmDHnZsdvZUxTlPURJFRBKYJDWC3T+mEVLregF8EXAaSeMMRVbCxS38K56+kaerfwci7ZIPQXQ9/y2ldHYcyuX/NDCYq7i3I42FmykbqY6EJHjLXklk9X5bXE3GgUSftclnFrE42LYA0ek+YxBeoGVU9oT0Q2x4Wm3xKeX/pOv95AhFUGPu41AxULP667CYfhyQaGHyVXhsZf11LnFxnQpwOZUhqW53kDHhbfBk2wPe6xAaPQW3CK7a5GS0TdnwsYk0QNr/ufWYgHAAcwLkB1PAzjWf4mwCz1edsvWPOP7r2Pec0ALvV5hCgjHv54D8Lr2lobM8J6e1saarHeNcWV0pz3xCo4tz3Z59IzFm40pnog2z/bfvkzAx/JXMkv1P27ew/sygmq7GwWwwthOEsM9Gt9Frn1m6UTmq7lr2QmwOZxQMb8St/fO8t7f7UniYm+I8YFr8Sah5wjExj53291vAkzCK9Z+vyOWl8xJOY6Ue9u3wT0O5K46KTtu3dpLP0rHdCZxAJ9/9/vUABcUsDHIPVltH18aT4kULQ9V4VxS9CwV63/PFVktDhAyBrLPExR56944NpOG6RSMHNCgXh6CgG438/YU8LlRkRnmyiecFJh3O7EXfvN5Ra397vqAp4A5MKIkVF0vplr+N3hgNfXV/h0t6tKeAWMGCeknLABdRSpE3sDaFS3P7IQCJGEInSiEk0Pd0ahZc5EQCly3tHcLM+u/BXDhVqr74Na/7HQ9f1z4Cw8fzacBehn+MfBKAwH0Hba7p679KvgNL/7rW15/Rj4Uly29vna9nuGHx+oI17WqZHzeJ7hhwGvQaT3TSh0pqb/44CUHWWMwedksaLN/BJgYpnpjQruyNhJwtzlXMTNuv4xCFHjLlNQslhP2+IGTRnrpK4NC6sQqyCWiFISUpL4pwESD3UTAkKMmKYJYWJM04Rs8rnCTrikcaIr26unJbz3vx3dIvxBiD8TxGl8g8CqKT72ReUeSM4dFbCygZid6BpJdIaX6gUb62NsuLEkruxQY1uObvkBaq7gyZSUzLrxEs3tvrFCuSmgvFJ31bcM/GTCLlK5eMB2M2GzbW7cq8C7ZqcKGkGFZFDhlAquzBrbvD7kOSEdZqTDXj00K43DjHk+YN4fsNvvsN/tkHKu64TrulmOgz2TrtCoqxZrO+cqtAKAQgEojBjNhTQ5XMSVI5VLwX6/l7wIyGWDiQsib8RqlTbVUpUGwTuA6nq9ulQ2K2zDLZ7LZyNeF7/kK/UrlfFHLILUAsuDm2V+EUFiKV7ArjjLhFiKa5jbdWEfrVTyzFpmyVkUEDIk/1LE4lvMS5siw2JEXD8QIA5CVXSrtIIoWnjrUs2J3fxKOwARVz9f4/CXOAP2obI8v84Y81RZG3PtUj80Y129157jUNmv621cpHsuePvC4zXp94kVpRk8VON16NOv1eL4nj2mploJw0uAVzLp0prnB+YuI+/uvZIa+vm0FVEZq/KJ9VouGVHdv7aeUZzLpaartEHRyMkm8Cje9wA64bnlKcpDE3LOdSE3WlfKK8yKk82te6OXKkva8SOOjVUvBHhodnwd8HWz6za+bsiUrhlPrTINTJjecntOS8ajxmNgkfxLl+lzYa0j/4Hgm52PPH96TjKgM0TwbBbmF5qqgDF/l0F/Pixr2zBMWrzzO7Gla5PMq7kZhrOdz1blHowNzNPLsg6n8L3HuOY6fk2edvGvX1FKQXordIrFQbd0VmPvmr1vY8vPhPUR/Tx67NIKw7X/5pqB25VvHqIn1mpxkrfLqqPp8tIdpT7RwEKIIBxUObpR8g26OOSWl1Z4D+nTe5LfNYvuBFk7EYTtb7/g8O4jRp8qAOOazXqccEAT1ZvQl6jV7X5lDD3c26AXxhbin/DSKV2ZLjggY3I35LcjeT49Aqe3JHLVdiGJkS59DMQQUEIAmSU6lP4mYJ8Sri+22M8iYA9EuNpuME0T7u7ucbXdgIqGolFl1lwYl5cTmBlzynWdHuaETQxIReoT9KwxxQkx58d5yWhHlgpr3eDpbOHdNCG638vbr3Z8Z+6OfkBWCzjDGf7z4SxAP8M/AiohyO63crK4Mqs65hXQNP55yImEYQ1y2aDff2o8wa8EJzdIeELhDN8TRo3iM/yd4DuuoGMa6qc/+ho1eRDIXRjT/mTPrZ2q/fO1Mk69wzo9/+PDD1DpJ3fcyAH88qKfx0Rd/8rO4gE3CDF0h0bmgpwy0jxX16uAMC9CCAjq6t0Oj2LZVpwFlbKZSPPKerAuRdLSJQrdSSzfEFGmHcoEbKeNxnM2ZpWGW2A5tFfhuUnVHbgI0UgAPtIn/PT+BhzuAJgFgubA3AnRCaWerBliDYtSpI2wuMfaOSoAENmb0j16qi7dHrbs96+PdZ5WQhM2nHp/ZP74/quc+q/VwmV/NnYmYGstf8yoshetY3V7ThdgHJpHBv0NlQkq18JksVjh3lKTwLcEfgXEV+ISN6gySdxEbDYTKEREijKvo4Q28FYKUrZYelII6iq9YDNNlQ4uRdipORfsDwcc9nvMhz24AJSbTcQ8J8yHA/b7Hfb7PcQo1AnWuNHW7c/WPWn5whYu2XlRgFiKVgtG/RUP7wWlEEit4a2cnDN4higIxCYEY0hbSxSr00Cx5temjFoeVSk5aZ/JGmeQCKRBIDI8ovOsFEDxTpt/bP+rUk1TwoEq+TAcPmE0a3NCE7qDK54RK95S87ZfYqBwAYooHzAzOHO1ird+qIo/A85yM2N4WBaJagptq1jsZxQQ9p/kG7pq+IgBzEj49X/8hs///ZeMISaN/SqKEklZvhMuUMAo2MNUCrx1nNErRe18jjLdHf7z7yuzn0L3lLsUXQYd1LedldyJ3fCEwlnbJVZwilMuCV192q7m8ztm6VUxJw0pana6r6gCB7NgoFDXhPRg20O1XiGoFbfGltU4oObBIlAQby9OWYig3iHAyDmDwAgxIoSIadoAg9WzlSlxzpuD1QWZrQu4Lj14JrIlka9DjAgxIs2z4iezaKSq1FIgFu6Cglk3bDJ5geAHh7d9P1Y+xGIE2vXJnYmGi0fyI46R5X4205DA8927axLLPqNPqPYljbms1sGXzcCgZHGacvT1HFMqadPrlX0r+OIyv0elXw5mrbYJuTf2HMCXtal96wVPFoOdx/Xww/TfWA/ufk0QGXQV2L1ZEau/C5iXS8G6fq/y+J2r8FzWh8U7FyvlLTe36wHk3O77b1rt7DrUvGyP6b2ZND8zjLs/3rn69GvcrKp9mWPP3Os56jX7XESg8ZqplmP1u1O64ZWjoYv7bQHl+vpYC+Ng5WmhU2w+jQLrhzCzL+vakV4gdIoEAVzruXX4MoJVUbDt9sxNgaCRoDKuAVRp4IPSPDtq1uLWD9b/B2vt2w/IBLz612/464+3NVY8QLgnxi8sc9BoqZvffsHh7YdaUxN0X7NY1yfX8ImBrPdXIOwI+BRkhr3WUICmWGGW+Ve6b1o9LH76Pcn9//ztV+S37/GpiEqkKfOOtGabt3J1SEnoicBVIC5etzbiIU73TevTGALu9we8ur7C7jBXeufz3T1eXWyx2x9ARYXwJdVY64DsX6+urzDPCft5Ri4FN5eX+HB3hxgDClON7c5K65gHPHJ5eFCndUs5tyWo9J/hgRYGp6flNHSiesiqdI99p3OIRzrU9c+DNMkZzvAfAmcB+hn+46FuOux+HZPYDn8Dzbr8Xclz7Xnnuv0rwelj4xqwIxrO8K2gMbSePh+aK64z/GPgiGbnUXdvMHb+jzFTjDz3B2jjP9qhinwTG4V/Mub5M0Nsn+EB+NI4inKWfv6R6UsE6Efr44DNYnJ27o9LFis0q7dwvPUDExCJG1WwxDSuczgQKHBtMyszl4sKk4gRcY1LugTCDkQaH1oKRili2ZmLWnXCXCYbs8MdhH079F8TfN2Hz9jyFTLdrjBc3E5fh8asT4XtUkr7iuyw7PLvBGw/CG75mrC2DmiY119LQcdTZu16j4ILdc1sVrVSnUAEphbTETrvwCL0FDfHjaHR2V9xVIEOIPiZEG6cFYI+N8FsUJZtAKpbdrFOzkglI0KE0pGD4m8VyNcwBFytwHOS+NopZex3Yl1+2B9QchYrdJa80jxjPszYqyU6KIBi1DpxJxDv+pG1kmAnoBF35LavcmFQUKt0jiAuKAWIykSS+PFUYyUTS3zElAsSFxAXUC4IQUI+FBMmcwGxrj6N/Z5LAgohFFKmlsSeFykmtXpJR3cCO3JrEBaHURED2zwpdm8W6KWFYYBaiKuA3r5SPwCt//QcxEV5dAyNVc4oicElKW4rQGZA4z6Cxa1lDflg88eNxyi4aqw7VOUNrpOqMecLN2u0GTMKGK+mazAYM/aYrre4woT9/b07wmWU2krvBjZgugb2dz3z39J4sfdpLMdH0+Qhn3V4/B7pUz0H5Zwqxdr9UBkPiZce1xJakLN1Lxm2p+pFgwhOW6tjBlfrZY17PW3M+lw8wUi4CVWIC4SSm4KMhxinNm+4zVxzFy/eKoLs/1han1tdOtfA1MRVA1YCs61/E1TZmbB1gtuNYXv1qRkzrrOvsUOPc8ST53XcHpih1uaWh2PIVyG423+PMlao0mBPNUr40vX0VeEfLm2Yj1x/XfiRZsQxJmN7vtxbRXAqWG/8SnY5C+VBw5cy3e7kDOByt/3yilGtxv0ad1hS/231tbTe7XiAWDJ7QX1C39vewj2AEPEaCR9rPS2/NYtjhz1rXn5fC0P9rtnibrceObX3W35eyDqWf+zbEaiOVl+nNTCahNHihAsVK1bdW+WtBB0VLzD3v2ZlfgrM5b2N1wjSByZ8L/j591/x6c/3nRB9Qm8FP7/9gM2bn1HefcANM+40rztCjTVv6b2id9D6WPpPQZQdIoDPZIoSfT1veDn/d3++x6vffkF+9xc+K9PogoHDSl+0UW07so1LYYiieYyIISCoIvAhG01QxBL9MOP68gJgxv4gvi0+3N1jGySUz2yh2RxkVViNMeB6ugCBMM8Jv9zc4PNuV0PPZFUivEBTAGqw3DieupUcmx7mAepB1FjPYI9Ie4Yz/AfCWYB+hn8UGH+t4nt2f8bFwfB+DQbX7Z7gBJaHvDUGE+CZC82V22NgSdK9bPozfDkwjBnpnzwW/t5Or40B9PeF71j7EXc47c7u+YJV932hxnV07lf9LCYsXbmPeHaBH4/8/v3hx2nJF2Ea4ip0e84MFGHK84sf88JQi/ltAr+RGOBmlWmWbo4zj6DMdxEWeceDKiB6r3KvNwHMARYfGkC1rjU3yBETiAjb8Aty3KNEKagUxjZnfOQM5IxcGCWLcCpzqRZrYp0uVaia3l3XMmYCZrrDls1VorQvOQt3QIViA4uEiNTVtubGrp3akd6tPBcgxB4t0bhwT47Il8Ba/o/P93jKXvghv6jdZJb37fp5cJxJ0b9nx9preH0P1MiG+tUx5SreADRXIUfReRHoCsYPkWE2t+2spUpcPtwxcCPKIoHsncQgDzQhlYxUEkIC5pkq97OoMEripIdKDBN0nWX1tZAzSk7YHWbs7++x2+2wu9+JBXoWpZXa/pSQcsY8z0gpSVgF9bFAQBMS1z/rTLH6DCptJhNaGQ1WJ7jGKeaCkgMCF6QiArgQowh1E4uV6BQRGc0Ceyt4o5QCKqEK0IuYkoKyeqsIBRQyQKqCQCTvWYR/VKgJkQBk5daa5QmIgczg1NxDm4CvuoJmqIcM8WbBBeDMKkhmtR4v4nWAA0AyFiaeM6uR4gX5FqqiAGDBUaJwxDXQJDOD9/4bx4n1hN8x1NAppridvWkQIPCEeMU43BdEAPuPLcptutsDqghSkKogwf587jN24DtuFrC+Cl0Vaaj2UPlqubNsS3D1Pg0ra3fxRkvndiftORXsoc/L4xA/JF4Q0s6Dx3b/3o7dftdChKyDJJyV4XxBkwqzg8pPrVWaby5AYYQ4yT6WkloqQ9YhybqPIWK62DbvGTFgd38vpREhTpMUfSANpxKqnLYyhoFuM6v4QSHGCYeDsKznMncTqpYbqIaxSHNCiKFazYvFddtXjMHc97SMSAgmMi/V+4UIt0bRgH2m6Xl9Pjy09EbL9ge/G8ab114ttSS0Ta3jbHx8WqFKrM0tw16ZTXP5ioebb0mJrzbjGaRzG68HR/yHg7X+bsLVr9OO47l+T84YD7/L52aZ3xTClF5Ao+CAJW65DyyW5ExdTPIZ3mW7xKT3cIkWV1xipd+68liVxbgKTvtV3mpvwvMCLIS85hkpuNm7/e0XoWfevUbBJy1fXIMzmlvycaQ+KZ3+M/fW7kYxZt+dFcH09bHrsR0iQCZcc6lu5K/YXMoTRC+yKTutg4zStaa4c/hweQZQr6b60CzjPU2TITHKtyCh29GE6KBe8O8F0m2cSNsm3gZsXlxwa7M7BiHr/f7Pv8AALkC4Z8Y1E+4C455kXpiCw5siQvQJQsJe6/N73crvCXhdekt0AKI8C+CVzqs7PcdOTBIfXj00Wf9kPb8HZqfoAPwVgJ/f/oVf/vUr0p9vsUOROc49tVP15eHxjijEEoCUc92PAxGykrhXmw32c0JWJc+cC+53ezAzfvn5NZgZf7z7C3Mu+OXyEp93exARchHvOMzAdjPh/edbbELENEVcXVwAEZhTQiBgzjpHKGATChIRkJaqMkAbv6BzwTnP6klx6ueZ/KpCLTfqUjupL6Z+qDfk+owddfq90OgZzvCd4CxAP8M/B9j9wR8A0VNONd062e2tIe3yhpuboGYl8shqPePM8Ni96nseD85g/f+U2WBuutbjBItGhLUAACAASURBVJ7hnwWnLM9/PPDWZf7x31sZ5AzHYbTSfeq3L2nVOzIkCm6F6fAOILoRV3AUEX6tDs+rkK1QEQET2xxWy9m/UC19hRmvB/dg0QSFTZTfidBqwoT4W8R0NSF8JBS1VLsH46IUpJyQckLOGguaswi5nFvkjq3G/b059CPiSjhEfgVCQaLGLrH0NPyGgdHdnZupCdVkbEw4OTiDfPSYLcVDX8uK+7mwbnn+HSqCNYYao2CHgEvH8oSzPtd0JmyrlsyMSATCRZ+AfCnmyJlRboswgz4X0E/CmIskSiAa2wA5ZxwOO3DZIpcif7lg2kwoZQOKInwOpYBNQQWiHFJ0rqeUkQ8HpMOMw24nf4cDODFAEpeYQOCcUYoIpeuKsHjcVWC+gnNMcFPa2uj7x2Q4JowOyPora1qs0ckkYCyKIxQjphgQYqgCn+a+HurCHciJHdeq4UURkql76lDUfXOzYDXlBmmWeqMA13jjXHI9j1gfAKo8YAJ8Fpf5nJtFOjTevImqALG+B1qcZhPEo3oKkL6uygm+n4mrp4Cq1Gd9Czvz+NjOOg42HMwgOEWe5QiK+3mWXHIzMK+/VbEIqQo+vW3XyPsby1rbqTyz8YjYsktn16fOVsfq8RzwfbDmnv0h6J1/ot5ZTmV4fgqeUjKNv53gwubhSMtyUyKxZPoVBVmnJWUQEeJmg3l3ALMwpw3n1LXG7A7rR0aB2/sQCGlOiFEcI6cVy3OpNosHGXZjQeRRzoMw9s34/KhU1XjWOD3/XgLW8h7n/+I9r69F+2bcbx8+Gaz3A/kN8G8KHU56Phn9N4Wn8US+LhybsT8iGMZsPEYvKCM0JScGkEkErKMHNy909NDvcbc1T2+9vVlJ70fTrr2FvC++Cf8Jk1EMzCjvCoDPXZz2EXx87749aildKeUWqkX2OKnlGC98DZ+Ns8EXtxtw71Nw8G5Y4zfDmPjX5qUvMiFpz5t1ekFvz95by/e0zBU3vvQpfL4jEaKveeVh9AouVyDsABWiA1fcap50BCIkFnphCSn2qrR9axSeWzl+Hl+zumjHOA7mYrx9N1rPfwhA/Pd7XIOwi0Mnr0DrGydI1ialnDFNE6YYxJU7uKYvDKRSsJkiDqXg7YdPePPTK/z+0yu8+/gZt7t9DeVC6q0ql4wNCX0xl4w8yznqcrtFCISJJ6Qs4YQCkSh+8imqtG9FVZFUOuHYmNuasJjuxFyV9e2YKPuSZeRmkJ2/frTD/BnO8I3hLEA/wz8IuDLZbJNozKDhEO+4bnWbIAIV3QxdaoJzMcSlEh2PPR40RvUj0j4yT3ZXP8ox5T8BPJH3Uvmd4UeC7z8ix7xXtHvuftv191/pTXjeswK7NMCjqkp8YjTG77//sH1X+NLmP82Ve9/57dPH57Fk578sGAPHco+4VU39V8jvhZ0SnBCxKQJQ557VBOyAWOoGPbKLW/esbpPFejwj4+L3CwRlwG/+awI+ziAKzT0sM3IpOHATQpr1ebVAX1nKnqYgsEmaRPAHQuSIQmJ1Im2XeOnV4tgJCjoFFx54tyYIULqHlEPB1fRQUw4cudMj+JIMSlqfq0/N2glAfXb9tW+zL+Bh5HWsOpUXMeR8qoc6MSYxODQ86/eKQBfY0AZTnBBJYgozWKeJCpcI6uZYKBmZUyrUZfGSEILLU2uUc8LhIKG5M8TbQi4ZU9pqnGJdKySxwkPcyBorjBADUk4iRM8ZKYmlPBNhPswiMGNu8Y3NZTmKdg7X+N1s/TFan9fOI+XtkJL7zoWiEW+krtypgOKEXMTtPRdxdl4gdUaQsgKkz8QKVhUHglif55wRQhAX5xCX5CLQlvUNIsQgnSMeWkjDQOi9vkMxrxO6ylXIzznX/oG+r6EeisZ3L1AL9CJuq1E0Br0TYiNDvIWIEFKEjG0S1v70ijzW7/q+elOqAnz031QcJooIRV2/V7f7RqWw+KtvbOE2Nib8nPlQ8TMBSJAYlTJvNES83ndMekNPjtenI7MQJI9TR+Koz8MbS9AUA5a5HMcHRBoCgfovzFp5ueClI8g3AG6dP4jnlnUx/NJwTFOUOlpv++5ZKHupGJeLrKMw9T1o1+IhRtynM8SyK+g6EQE5YX9IuNhuZJ5QQNxMQCnYTlfgnBFrmIeCNM8AA5llfSJD9+U2d1stBJgZ07RBzqmOGdd6ak11HUsYi4Jpkvclmx0gq4eXoGMmsy9YLFZF+HX9w1ROLKSBJjFctuxa/R2p7DHBI88CT0i2OhX6abqoU2Xr0yC8Yn9WWAfBl22H5IrbdT18S5r/hcuq2ITbqhT4/me4rwffv22tl9fq8pJ06pHCrQi/GPzGNd7rT3SI2KySmVRZyH1qK+WS5XlSb0J7DVJ9WQQjNX8uDTZYCrxb7HXJ+/LNa6R3H3H5X7/i87//QkRz6m7N22j+DBHMWl5m5Wy7vuH+DYD53Ydaj4vff8H9n++7NhGOC8/N7XwGO7fnnjciVvhSLnf9FSHC4dZ3vTt4y++Sm/Ac2q7rB6az/+YewNUgBx1XPA2/YFR/QY1ilxcFhAzGxuhzAEnpsxqeia31ioOHUuoer1SS1fWSUct0VUGBeDoLkDFOLG0KAH4pVK3EbXwPOh4XRZQACgM3JILxG+6xQaNPuBtvm1f3gWT+MCOAEYvWWvdBi4VufPj7wMiuhIsC7EnWTCulL7/t9IScJcQbhYiUMrabCTFGzCkjUkBCFtkyM/YpYRMiKBA+fLrFNgT8/tMrvP9wi00IIGYkPQvs5oRUCm4uLnB/kKAVhRm7wwGvri5RiHFzucXdXoToBxbvVFs9zxwGvGVjZDSunde8hb0Mt+03/XOqe+roScIGSPdgk8Z7XEN9+raVfcuN+Qxn+H5wFqCf4Z8JuhkvdnG0TWYkYo35dirL51Tka7knO3roPcMPCU306JlLZzhDg9MH/+8JZF5q3ROPf5YO3Pv3w/WP0KQzPAj0BXPvJc9ZCY2YZfc3nPlQnFVF/+cYDCz3QT8OGr0tUgFzECEaMXJOIuD6S4RDmT5j998B1//r2loICsBEhISAXSiIRLhmYFfUYpS9sKtU4TWf6FnfNrPITJQ6pb5QU6KmprrgqOPe1FRKDxHMfftzBSjHwBNSa6PzPYFxXInkZet5TIhu18tS9wAuO9xvih1MUOUGQggRm2nCxfZCLMKDjDMzg4pZVIpnAWIC1NJXL0Fg8D0Dr62MNk+E/yMeFHifkXNBzAnTJiHnC+W1UHWDHmJBDAEcGZGDCLEAgBm5MHJKyDmLwKxwqyd833B1f16YtZ5PHQdCIGHeedfhFPoo8cXOAlQQLDRDYRQyoa8IYHMpKCmpEKyFcDDfiSZ8zjkjTQWBqMZXD/UbcT1tMZ9J82AdiKYMxygpOSE4o3q3qhbj5kLeLNFLfScxoAuqWSipQkQwH0eNCWbxzyU/wWdm7e/9YrCNwwbgnQrLtfyiFvM5t5AWJYsiQSnNwr31O2uZXNtt+E9qkGpfCAO3x2js7oGl4G7td3ngU4YjIk6L8/pyHjsLR6b4y5zJjrX6dL18vW2vOya2+4Jd/UlpGgOfFklsWcUo6+zyciu4AkDcTk7QoEphUZRguKidmCwswTNUEFRRRrKXtde1kxm5iDgl8zJ2afsOtYO2l+LlY39/D2ZRruGqNFK/kOw9P+GRE+FH2iGfA0JX8bC2jreoKi52K2eZvlcK/BvD332AH4S/Y+OO49evU9bjse9oQQ0sa0gqXDUhWqiTzEI9HYcmVD3yngiEV2BmXL55jcO7T12N65lkBfYkQnRP+bd9nWts7/2ff622zYSq99QEpvckf16YHSCCb6vXSDN4zBIVP5mrcnsX0feBxej2QuaqXMDrZ9m9bhWXa0M8tGts53iW859HiGt7iTPPGg8d2IKwd6cEy/eSpS727KEVuXP1bnHtuZ6RC6R/tvou1/qKEN223mICVm4u/wsDN5X68KEJrBz5izwKaPt0Zilvyg7+vZ9XT4E2N5olOjNUKVbOBTEECTfj68vA5cUGpTDu51mUARm4iBGpyDlozk19MxfxdnOxmXBICcxCb9ze7/H65lo9TEk89UAEJsKhFFw8Ghc9x08RGsHF7txvXnYasdVyZsAU3PhZBZ7hDH9vOAvQz/DPgUpJcY2FLkzEJsTumVVwhzQCleWmDv8d2ub9EFQXl4/c5R+zNx0leh9ZpzMsYSRunwbs/u2vjjGuftSxOtNG3wa8gGB5rObu90cDY8jbAUrue2apJ77tsCJPu7fDN6fLbLn8HeBlV9KX4acvKdWAnyUI7xgGz2zAGv/UHo2xcMdyj7ny81Upep7MfItIhMA3yG8z6Hex2C0lI78Xy87e2TGDSUq4+e0XpM+7KggyK/PIBXMpEgfdMdztvVSkD/7hBUwGmYFP9BGbmr5p8E8MZLJeIbGaR1Et/FjzYLNS17SlGAeEe3qH7Z8vPS17FtoLgVfFP/XeC2+cFLvDU92EfGQ9zQR7UcrzYCwxYwdiRqTLagVpg0MkbsXjFBA3G0wXG2w3W0xTrJaQc5oRDjNQBa4MlAKLBEABCFdR8pgiYgwiDA8BPtQC54LEAHHBnAlhTpg3CSAGBYlBPG0nhCwWl1QEtweyGOnCjDocEuadxBlmzmA1Ng80MGMqnSxzslpGy4cmI6v9FaOGZ+imqDoOJzRRDqs1tlqON5fqbQ0xxOo65ywxEVMSC5wYkdTyPE9Z3KTrOjEhcd4UxCkjaoxjCtaWIM+CeAiwnc/abAJChlqds7phd24cRUBoZQHgjKyW4KUK1s0SvFRrYw4kLuiDMOWIRZminmEK6ncgViFiljMKZ6DI+MOs0jODiyhB5JyRc0KaRTEiJX1WMkoRK/oqZDccx56mMfRTYALRkfltF2aFvqSPpIs32GLPex15ycWYtbWcYYFmZIh44XEUxyIV9YLSoGNb49YbnaNrNoYg9XnkAfAhDzHLk8V6CrNQ4iE/2w9H5nufN7r+4W7vH1P3+UcLWzDWT7cdU8ygIDhiMwlrSrxbkC4F8VLBpSAfZhRKKDkjThPCNCFOEXlOItSggFTmeoyX7azI/NW1Hola3qzeNUquc7RrjVlwaYbX1zcIUwSDMe/2+j1bis7C3RRtSHE1FJ8KaqNekvDgVrPev88GR6+vlTIkWz5za3h8W3HoQC96hrw/74zC8za1/Mqyhc/dmvtq8LUKWHTZl9JCP9pJ6EepxwBPXj7rc/vZGXb+pp/eR4YqDHbqpu1aPUQFQJUF1QpYaXpzz71meQ6IRXE9s0OswgNu6vpNuAUB2L/9qBX5WV2uC0T1zSX+W8T611P5I/5o5BlXgawPilU9H1X+gHwTIcLyY/hpzRuNd3HuVwnDBNDLevpRzZBY2wzguvNMppRjPWPJv1dD5QgQL2RgMGd91q/XcfZYXUcaiABs3xAO71j7R/q7Beqhrg9IHds/JE4O0Pq5doiighBbAdCY7wIzRIBuZ8wImXdlOIMGljqZtTwD+Pm3N/jw9h3uqLl2XxtPsNIlJPvEPYAb1zY/pka/XNnRleTZJVsfsihf+F5XWhKQc4efA7arpZyrZ61NNCV0rt1ZlO7+fL8XT1MA5pQxzwlTIGxCxMVmQkoZhQiZuQrdYtBwUOqhroBxt9thihGRgFmt4C2kzF7DO62Pn80XU0IeFGWo+1lZi+rOXYXofTFuwVXFNddbdo42AvwMZ/iHwFmAfoZ/HhhVMnLgPbUCR9SwMmJWNodHnXmPVOIlFajXmEn9v2f4fjBMrBUgJXXPcIY1OC40b8ee77nOyf3TDuKngeEJ+pHRdoZvBU9z3774GD/KDuOt0IFxfvXz8Vjc19oS5irMC6Su14kBZKQ/A8IbAr8XAYIYAN8DRNiHO1zjGgwgq7Xt1a+v8fHf75C4IOSMWQVOqRSx1CwsaaslJgBu7lz79b3e1zMJM8O3KQAwx7JgBmt7qgtUS+ndC5sFrDa8hbJxea8wPB4LXzTXXgSWNT9tee5/v808HxmPvmTGDgURgYIyXwiBgSkGTNOEzcWEi+sLXG2vsNkyYrgEABzmA3Z392KNWQpyKuCSRCiVxYolRBGAxziJi+QgQvQYA6LGGFb7auRcUFIBY8ac5lrHECKmzUYE72bprAJ+4RWZcIQr40UYi8Kdy6VypmQ/CAAhnqazqV/D5vp3QV8bv4eoCrXAVJmhbR00bxSFC+Y0oxBXV++kSgUhSJ/nnOscMoZaLhlTnlTgp65WAwAExCiW+mSx4lWQzWzrra16zqWtfhX2N2ttroJFEXR7t+1F74vkDWGCtnIbE5cJoEJVsM0sAvtC6na9MAqKaOuU0sqc1fI8JeQ5YZ5n5Dkh5SweBlSIXrJZp2vd1ELY9IQ6/MtG6zSG5uJcdoKBDgAHJybg4Y+GtC8FSwa4sWGXz81Ky7uKfSp4Bv/jUj6cyvfLY/rrKZjcrNdGR6GrOWkSIpln8yFhmiZU629bp9Rc3XMp4CLr0pRQLCOCCOIBqHUYAxlgFeqHEASfFVTr8aEq9dtSGFdXVwhTU0CzeOhV8O6/D0HjoDY7OcOFfZv7B6fn6MvuoWsk3NqOd4yWOjXDxqzXFCiqAt/a+wfy+4+BZ5IY35YyOYPAWm8/HiN/CXSWyaMrI62FWGBT58J6f2KiWExzOzPI3zUARnwjnlnSu5Y3AOSUMf1rQvqjrUmzJJffVuAFiyB/7Bn5Rp5GVzHLJyrN4i2M/S+jCatHPGU4qgmW2x+75/bdBEL49TXy+0/Vbbp9T+jdvI/leFgTnq/Vaw18fu5EthD+z+9aKuvvLQizUk7+3GftveDeBf2x8j0wmteAjGX/HyBz58KNwa3ygK6Z21yBxEE370P3f74X9W09OwfuhfNAe07AIvy2zVM/L271/aXrf7HQ7+mYUw32tM9ir2Opfwzigc5im9f6ckFAxBQCDinhIgQwA9sp4vZ+X0NkWSiBlLMIykOAGbQzA4eUJRa6Wq+Lgh/XcDJlcahZwlPpXGsf9Hwnisl0xPvcMIMXFupnOMM/B84C9DP8s2DYgPpNxh1+PddF77szbrUU8duu5kmLYrp3UOaXwZtff8O792/X0688e6W/n9eL6OAUwXaG4/BSffYU0eb5EHwGYDkPjlueP3T/jUCLNSs+I94Xa+hl/UH/o+Gle/Lpcs12xGxb2dPmX2V+P1uTbFnph4To41fNsmyZa2XsskzdzLea9hX4vZ7uAyHQDmzR0Qn4+PYdfv8//yeYCYXFClP+CnYlg7MIt0LJSEUEc+J2uQmPpNChfmZqWy3UezCmU+QrFLqvjWlnXBW4cWuTWWEXjalOrJYCJAoAAYTEjOayR5hj31MQfrLoeOLdal60eu07uFpfd9OU2o/7rjMwWivv0VPds9A8nWrWiw3XFhaWUgwR0xRxsQ3YXgVcXlyqsHaLzWGDQAE5zUgpIR8S0oGQOaFExnQTlXEzYZoiNtNGrMk3IjyXON5BBanCQJ2TuNimw6FWOUwB0yQOMDcQS1IKhDkl5FSQ8mCJHADOQblopWswA6DCEuszaDeb9b0tgVUu0TrVWx0zViuiALNirGNvls85y7sYxII6Gzuufe8F6MG5c2doDPScAQbSnECkVi4UqgA/EGksZM2T+/OECZvV3lzWquMIy5oVoZ95sRDr8FI9DBT1dWlMyBjU4aea9tS5DYAymuU6GJllfBkFmRmUGVQK1NAWvFehYcpIyQToGSUnpFmelSSKQiknpCLC9Ky4zhQBKk6rgjSnSOC5to6UtsfGICZMmECYcXBJ2zzw7XzSmegBPDfF0O0Tth8mjXFeXY7r/IiB1FLLwCzEulPoonhjnI7WuWt72tCALt0xitH6bM1F8Fp9mpPTYf8cKhJi6NapWeT7drQ6qFcIUN2Xps3U0ltf5ILNdgvO7sxtMceJsN/t4AWx1RrcvFto/UtRTwfZvASo1w2HpM1DAAO4ur6RORqCKLawKMDFEAUXqvcHI36NHi7KkAaJ9wfD2wwIXoPstQCOMsj5WAfbU2vXE7flurxOfDfWqEt7jM8xXh3L3+P6ulapf/8VzjXdtuHQzGKLf+Giazk0PHB1+aJ8n/f5t4U1Yvsrw7frnyO7S3CvnwAzARsGii7wcGSBz2ReeZR2P1bQiqemGSIItR0GABLuJPm7axS9zmhnq/SucR9Zs7O/ZcltIe0VN140NKnVImzf/ITDu49gNOHr5W+/4NPbvxa5kWvC8elkvIgWR9zSvHrzEw7vPuEARoL0F7//uHD9PgP46fc3uPvznQilrdDQBL8FkJjzaPRb87aSax2gLZO6lM7piNXbxsF2SRtHrwgAQGkdVNfo4jWgeTOysfBtl5jsSwrIr41+PxYw5YuLlfp61/eE5mL/ngg3LPMl1XNjs5SOILwujE8BuEKjO8w9f3HPGM3rgLdaDwBuIZblV44OMUr9M7V47iMqt/3UwhzYvhtWNsLCqB6eoinQmiKpjQ/LvnV1scVEkLjnh4x7VbrlIl7rUhaFh7SfEWnGzdUVykHinROJYP12V/Dmp1dgAPtZXLkjBJC5xLOGuostC65wFFEd+67dw9jWNvob5wFqWRY1Ws4yGtOf4Qz/EDgL0M/wj4d6OPUbBcO5ijxyllp5SFRl648rEzgqPF8DDU950iGPkStPYhSd4bvC2fr8DMAa8/IYMlk+/+4ELDV50lJQREeQ6Bm+K6xZQz0JjrHmH/Glszx6SUhoVhXAkqX10L7oGQn11zF6zSYgBBHCFROoEcRNsgpTJAYwIZWCq19fY/73eyCJdSpysxBlqPUbloKfVqe2qx+reyaJHRdAiHyDxJ+rLaZ3zRfY3MajHnyD0jrG/5+p0SgRhISCyIRMD8qU/jbwsOV5/6y33P82MM5FY83ZO0+8EoBAUQTe04RpM2GaJgQSYW+gKxwOG6T5gIMKGnEAqGRMk3wn32wwbTb6rFmfi0WoMvhyEdfdJQtq30d1Iy/5ZGZc5ILNZgKFgPkggnv5yyglaWxsczFu7nl1FTBV5taiMxR8jPYeqFqc1nTtRi2wYxMemSt1amlrUSQCTyoZKQDIbUc26xBWoVqg5rGhulEvBVNQQT0RQhWgk1r5K3uvlmucKbME1/6oXM42/xioFuFZrcbBTThYY0FLlyAiIJniBVmbTegnfc9ZrM2ZC3JJyFzkvrB4BVCrd0NWZcfgPCOnLO7bzXV7yjXOfS4ZJau1OhegxkLvvQSw+7eNJLk+OQ4FCeS0Z04JTB6Pvh72iRMUf5p3BqsxrEvHHFZpo/X68fDsKZhnLe1jzoPPKeNUnuT/HUhAoRVJ5hSM+S39GGIUa/DM6rlBvii5qHt8tHVnoSpyxv7uXstqjGZfhxFijBJewAvjbc7VB20zpFp2w3+y1ponqIpXyI+k83Qx9JsIOETI7uVsvHI9whqK9L9fCou5OBb4iIl5rI5fBlLwKBxZE5YcqwetPOvgKzFQviYFcQrvfVs4PTG+Bwn57fpkxNzPh80jK22Cdt/r8xOKntEEpJPLw4TnthTMsnltLa3BdnAlbfUzy2Zz304A8rtPCHiNLT4Jjalfvv7tF9y9/at508LpdW7gcUJTbLXdIODit5+R334QF+3wQufe4vrTn39hAmGCWMwfi7/d94cKMNnC5UhtQqURvPJf3zet3ks3+LO+3SJg6+6N0vN8xBG/PaTc+xDYmMHVp+iZkyBn7owWK/5W52SAbJ9MquBuCmVoAncfw/6egJuhHD/Wn4O8Z7Rf1u/GfWpHS2UNoNvSV2FE/WxtQPNm4+vEEOE3sygNf7y9QyiyQ11tIjKASKL00GUK4GK7wf3+0L3YHw642GwwpyTCfWZMIYqHLh5rJ3c3eIVPnVndw5tzzclc09UXoxX6Wo/Q8vYr7ZlnOMOPCGcB+hn+9jBuEx6PV2LEUSbm+lDv6rPuiXE5lELKgGimW8yymnkv4jq+KTOqTuAizfIjWrwjvAbLRgzg1r19hTVrdF7J41tDPzKE00TLS5d8DMa5MaavFgs1vTJPsDwMtBwfKvW58CV5fklnn2I7PfSVlT6W/3Upq+fVuP/6S4FXrh5Xtv9yzGXMixdpxr5eI51H5soizbAwxLUjrWbmD32k31aG6Ni8I+U/Bx5keFmi789BGuBl5texXJ7b3JrfCanoElfanikv1rywPKrsL5bEHi9vaYneO9U1jN7vk9S9t4O/1BXVdXDBZ1kX+VpV6mXys14WBj788Q6//6//kljoQlBUt88hTKA8q+DAC6Tc6dP7ras1qwlxbCZYKARiAuESsezUbtZjiIJYhJ2Sqz/kOqo4aP4bEA5KAG0RQCS0R8LJ6fJIeN6M9fG4vxyUmbVgEozPF7X46kyCkbFGcA+wB0htVVRIyyRC48w7ZFwiMDTGr/TZFK8QLzOIZlH0KIxSsliIJGhM7oApbjBttpgmsUS3mL1cyxL1EUQCZwKrS+Q0z9gFQtxNiNOEwoyUEqK6lucMzPMBydx8z2KNjGJz1loNgEKdjRR9dL/WG9RxA/udhWG4pXHXbLYFnx9JHOQ60IFAUfPXTmei6m6SmKW9ysRiBnLS+O7MyI4DasxFTlnXiwjNAwgIEls+aPtMmN0OKPaPWnsPNDQg6AdVaKftrvUyTxPav/qRnGGCavr4uI/cilRL9lwy5nRAKhnmLl4E6FYdO8cweBZheUoJZU7iZSAXZHVlb4JzrvHPixuaQVjZurAb1S0ucMC+64cJF5ixr1+X6mgVYHKKDsNM8b1JysW2GRdjUAsuUyjiZummLvTlHCN9Ms/SPzEEEaRqOsPpF9s47Dy2l8gYbTSOdilt7Bkyx0aGL7pclm1be17nvY30wHylHrF0BzQh/9ZL8G3S6dDT39SyIzAKcw05QbpAWPe8WkKBej0ANlcXKHNGCTKnrZ4hTiJczwwKVJV70v6Aeb8XV+rcPFyM1bfbzWZb3bkzEQonEKsiSm089Gy0GQAAIABJREFU1MMM4fLqWh6HoHkXLUvmM5M6LibrCxcb1woNfSWqQJ0IVCR9VIWMpoSvvUo2t9r4ndqCHqa1104Dj8hw8fm6U/5FQlfMWkm+NoQ+TUGjFY2+YWPwr1Rv7dxj83TdEHhFKfHU3v81TjCnQxQv4PHj+rxcHleJh75ff/89bBV9id/WEdpyhq613j8zoXlbB1SFyWH45rJQtU73bskDCBtVTJpJLFQPvt2DJbpXOPaW0Sa07i2j5XrCDTa/TyAA6c+EiFvsXbo9yXrdrHS458dmiAA/gHH5WwTwM9LbDygA7v/8CwQ5d1i+jUJfPwkdxwVUKYS7dx/rMxr6zucRCOqNR9JNRMgMUFFX6dTjlnbONMVQciFnmuC81JFtNKvvXxPOeyG79IO0YVfng7m5ZxX6c1VIcEFwaoseduV+Gn/stb1m2c3aB4XlvB2UX2SC8QOJzb3RmSJsb/M5sqxHc8F+xapQ4Wj2ovcBwLU+uyURuhtLHpB7y8ejph0kdnqHuavHl6G9C3pHnueckYlwMYnb9UPKsHMLWX0L8P7THX6+3OJq2uBuf0Bgxv2+4KdXl2CW8D3MhINqzH+8u8fP19e42EzYz+LNBhBX7szA1cUWf32+wxSFTgwUNA+p11UhpeuBjFtcg7DTesu8abjBSD3W+rYWcv0lcUsn41OF6u6j2k1GTw6K5WP/+Wn0TLz71N3im6L3HwEeScKd4eXhLEA/w98SnnL8O/auF0PZk+FDz1sAzNOi3D/rLDV+cIqcbq18DcInvXvtUv405PAawMf61UNk+7eAkWXV/l1r58vdn26vihlWnj/Mnljv1+ftXl/X8nyNleCfP+V+PJY8dG9sCX90+Doj3koeWS/fB75kpflDXH9lb/p+XCvLHyzXjkPHj0jUCGvNpI6gMb6MTlZkSC451f9aQp8dnaj0+qgdm7+PhREPLA+UX37/nHq9LKwxEb5l2ePVo781q64vkogeL/e4EL3/9lj/2QF0uVMwSmYwZjARQkyyPgKhUETwwhu1OuVICNNUbSQpJyAJA0GM3460g/2KZzTm46lRZxSSw3BAczUIvQbUxSPJGTlTOxsX5SYFVgsWbpbty94x+Jr7+bivvPRsP4Yf/LPvA76ltRbKBQlqDlHUEpIA5ByRUwanjKLusqEWziESNpsLtYAW4XlKEcyMUAJoHxBuxGV5jFHjfAeEKPM65yzCVGaUnNXiUtZwKeKuPMwzDvsDYrhHzkmuY8RmMyHShJxmzIeDCNJTAucs7o1ViFVdo0PpBY0VLgJFDNu7XqjySuMQYSGMEDqdxJU5EUBBJr7J0gdLUStHhN4AglirU1ShcSEwShMgs/Sn7Y8MIBQCF0JOGWbgTYBaqgdx5axW6OLeWYVvxVa7rc/S9l7nJrFa0KjAr8UvN7foKkQvpbaPAB1/CN7S5ppQrrqrVgHk4XDAnMWNe3VNwbrPW0UyUJCRZ4t7npCT9EcpjKwCzVzjnlsd2zAyS9TO1R3VcUK3uMC+sgfXzm8Pgz+JmItL6U+de8o8rLJO9m7NqZ8q+p3EuHf15VZ/c90tzzxNJHkFyQTs3vV3rTfa94/Hn6ctrTon9ytvnwYjZl5Q41y74lFYNYQgwmmXYYgBFKi6bydVaDns96J0UA/o2ld1nFBdqQZVYLFviUQQXwojZ65KFNbbUeOdhxhFeK5KIeZhopj9n2sYGT1QiqPF+x7p+kAn2Ul6ngw92CxZ9mMZHjxmDD1d/9QxP3XiGnduu7AhWjsOmLDlWD6Wvj93PB5WjyCuA7gaSBhy9O8fe+/W4dr9DwUVG+ndI++H+bKOgch9/1I1/bLvv18UMZ1ftDxjj2DW5FyTLC2R/afm1p2pHxvZX0i9SxEumXB/pP2EpXIJQ4SZE260BncdiZVwiy1+AcDIuEXADSJuq9txE9rPj4hb5C2+DTb4CQmf6vPg9ntr/1rIEd+m8bfl1c9Ny8db2NvSNbwbuHdjP8Kxfc3Ojx5jRzShvV87dt8L9OWpxLYPEJ9llo46pQZGI4WFSqUuF0CE6PsvXAc76uONE+S8HbWgTE2IDsh1VeLT+keg8yoANBfuE/q9bI3MvyOxQPd2bWtg4+u/Jf9yaMf4bffcFAHB3XwyejQA2M0JxIzriy3udwcQAXMuiLH3kGTFfry7x0/Xl9hExqzhZEphcGTc7/aubFXoYMnBBPjmMYIA3NdcS00zYmca7q02VNghAenwzmiMASITsrMlQUcXu7r8cFvdPwgef0J4/v15fM8C9DN8Q3jsgju5tw8+/8aFbReeZqN6Gha3qWYlVj/wB+6ageTRbeIAqEhsRNa6GHG7dNuumxWNW7Bnavjad1HbXF8xXoMlDikIP2mJP0HYP9tff8H8/j1eo2kiom6tltNxt69Pgc5K/whXxtzf+VYzXDQWrzJYm3/ivuunVkqPytfuAeuHUuvjxsATBg5GDV8/Np7gfohot297ptmaBjzVe99KL+x56ibXw1pNj5Ht7d4I8F5wS0P6Y/fLHm75rNdqnKFrM7b/ZilKaqPs58C3gVYXXnd7pPgHrmfXx8H/295zVwJWr/1MqBZ89di2nDXWW+zvHYdBroK7aauo9XTr+QiqArqRU0FaxfUDpl8FQzVr84YUw/tunSnOIDYXVLxyj+6eQLIVVNQz3FcmhbundiQ5Dl82Dx/82k8vtH72H3q02vEyum9HjNTSL/rctkj7vuLoH4GkPlUHs19apmYsXdyRPgtVi/4ajDtZdcoIIzC4XIBoh8zqpSbK3Lh7+wG0/QW0BabfNrj5/Rf89f/9qVbfImSCXA6r19dXICgu7hgFThDlV+3064QQAtIfCYwrEN1VTfu6L7uxD7poAgAqMvezmt+Lm+qCov1WYy0uevGh+1plLMfIzT0an63l9YLzzOG1Hv9oudTi166RPJF8z7taat95wvCUokjdw+y7llHtFAKJi/YQa5rIFk1RMgnYNqFcIMQQ5G8ibKeIKUZQDCpIDdjf7wHeId5EBI2hLpbnQQXDUq+cClLKyCjifj1ngFX4FALAhFIY8+EAEHCYZ8QYhek3Tbi8vkROGfv7HebDjJyEFhcBsRDEhnMLCaPILA0ZAFvsYLLuIBgHhwGxHicCuAAR4KI7QuAqtKZAiJtJvaQQEBicihPeS34Equ7PqbJWg3I1WT1TCHsSpWi8dF2trG0AkDlLaAazsiUglACmgBIsJrrufoNnBXMJDV1vZglMGku7zlgVSBsSqbHQ7SSg0nuzek4F6glDLKmYoN+jWYirxfg8H5ByBsC1DQzdN1nnZlYljoO4s+acRWiuHg7EgrsxTXUhiCt3CBOuqJBUhKXFtu86/RnA3lmfaxcjsbi9LN3WYzk0GsujHIkBL5bm1n+kc4mhAv9S6vsYqS7h7vwTpWJEBSWQKgiY0JexUaFrs5yWBuUsa2aaemp5Q1Ota7VsBpDnkcXcaC67l7/ivtcGa7LWn45SrhZEqL3VTaya+5KuWtIKI452ONHmbfVkJAVO2wk5S9gBp5tRl1rezzJP5izCbn+OZqDkjLCZWp28ZbYK3lv/t55jImwvLuuzqOMV1MKLkljAEwX18CDZFs4os8xi8aogSkSFi1iEFVunQA2RUJnQtuZa11i1JD66zlMCsokUnBKeQbcu3LgQmkVagcMjTjFjkY8NN1ebbrjH69BvcO5xIxL99l29gIz5WrxgataF4xbfduThe+od7Hd7MvXZLPJboYntZkHjGqz5PV6f6o+7H8t8McvzlQKOfnGM/vKYheu9T6NYoy7YNd2zo/dr1XsiPKb9R9MQsLYevhnUhdc33hvBbnSREzECU3XNHdGsdg28AFLQpmISAiYWwXpSPLJXk+8tk7p217x0fgcWHD0tcDuQ8RkE4OpfP2P3x4daNgPY//m+ps/4XHUSbb/3fId65brAxkPoJWD/9j0YwAavEN8QCK+R333UPrBy+jEel6O5V7e57BXgLvAK8U3E4d0HEAgHMCYobY0WO74TbnPDOYUZB0CUr3z5bgxlR5ZSo/bCpCkt8rns2O00GrUEQwdNgN6rb3sLdb9Cew9rvneMBmrntv3KohzXef90bc2QxFMnjVnumAE2TuqTBVcA7oKNO1e365btDUu8civtnmQOvy7ArTpwszjpBElrtfscVDhvFtkg3A17LGjpobXNxb5t5p59GoTd1rdzyhIire3asHN4YTn6H1LGJhLmnFWBmXE/J2xzUUvzpJ6vgG2RXFIp2EwTcjkgF5ERHOaMi43Mzv2csN1MIIZYqeeEGYR7nQjX0LmrzWGqtQPQcEPbqG28lCfpEDmzCeoZKEWt3uVTYsFN/cYd9JhK4FBEwZgg1unoKUY6tkmbhxlex9Ce9jkKPJb1nw3j6hyV2izNMVz52PfH7k9hh38KnAXoZ/ihoVvAttnVQ5+moYHQ5yb661y3F67WOo+JQzci7SI7iK9Qd3U8S9touDXDmAmVTLLCCnxO19qSWxQQE/4C4xdifGDZmvjdW7yhn1D4I/4C4ZWSYSYCtZ6olhDPhKfE/iTXGmt9k6fZBupQ9+K+p0abNYDLY7FVWt81csfyWHvq7yUneTK6iMLK/XpP8ModL956ktW3wrdkvMfK+2Mlnx7hJWG9fNd+uZuL/Rx+6N45u0Qj79fEuMt7qt+u11zyOfZejkJr3gW+NvTzvB1cWr84ATq3/vezpLcuar3B3ZGOhvctfZvX4xp8mDRqBz+gCjQcwUvqMIxaITBXlQEM7lHXainjs+X7lyDHSAXe1LST3b2a4EnKtXtXs5P37FCX75ShLg+BnwtfBjrban2Gvib0wjk7Q5k1ZR3qhvmq0J3cJ10Wz1tnL7M61/pt5YBWN3xZN37VeCh19nvaAiDcVBqD5Yiuc16EMbkUFL5AoR2ITXASgRgAimAA+z/24tY4ZeRUMOeMnAsKEbyzXk/HSD25f07a4hXGq1iJM+b3CZtfJ9AbQngfalx0k2FMfAUuO2RCjTPdDtqNNMmaZyaJfb5Rd20bljqXI7TQ+r1rF/s0ui6pT3MU6EjjnwMd3TGuC5v4rp70tPnOA+EyCtCrcKm6p7W+5+5ZUeFlMDf6RCJEZ92lY0GkWC2aQ7jAFAO204SL7VZim08bbKZLMIDLq0vsLi5xcXmJj+Ejck7ATAhXEXGzwXSxEVfcKYsXA5b4filnzHmPOc1gUI15ThTVJbxYLaeUEQJAIVYB+fazOAlN+yRMxGpZ3RQT1HtgpceaEFkttYlAk+JZBqCCRsNrIRICTeoKGmAkdZtIQABCIMRJFAooiA1QDiLEL2zzUmhnJidYzRnMGW3/DpUCoVLAPDe8CwAckEpGDsLsCuqWUU3CZS9nqMt3FQ4ShDGlUTLtbMDEMH/1YqFeekG7Cs916TtLdIuV2GYwA9IWyQ22Fk0YaMJzEaAzOBeAs6w2q4+63EfWOOs6BuWg7uJZWP5mdW7WueJSnVGCuivngsxcy82cegt6cFUIHqnMtWt7YjSYX3sMuDjb8ht0vClQnUMAIRIQQmwu1Rc9qFSR+n6nGIBUAHXhDsg880rSbEMPo/Bk/vY56phwUQpWBei17LEe/v5IGrbcbd/z1Da3Swd1q1yBhVKvx2/BtcTRCt7qzrVShNbUHBt0dbBPirhp9xOeSwHFtp6YSw0/AasBZxAL593G1cY/xglzmrG9uKjtIFtDRZRtrLwYo+Lfok2V9ZBLrlboNscjotQ5qqKP4mbDcbKEqemjWvcbOlPcYGIyP1q17bYxUz/axdYNufmkNGBVuPPCdJv7TqnBj6sfJz86HS3Z16zdu+lI7lfwYyulkQAOd5Gtj+NgbbEQHmtnji69NsjP/L7mbe3XRUldgnXNSv9+cU/r9y6t9clA3X0DsBL5gfs+/QgEAGHo17Gfj9yvsZJODOHJNKNF+WPyeSny8blw/ATiQYVQilPNNXaGCNa9RW1tTl1DloN8V4hrvPEAEdIfi4/u91rNspYz/5Hq/UZ/17gSY1zwcXkAYp0+QiEgsZ5B3lBVTApvfgK/k32R8anj563FII9Ylm1rLf4+oZSCgNcoGmvd3MdH9LHQlz3jtzuHW7E+mrYjMVjjrAvVKP0nIbLmSu10WLQrtfHR1kJW+Hq1f8c/QCy2L1d4DQ3nrtE8x1rX0t5TizMOaN+xKcE2l/G2N1l5I2q1e+v7T6EveRwTj7Esjr1vQdB90K82s4pvPboOVcnW7l1ZsmcYD6+vTWFgCkHc/JN4zBE6mjGXglebDbabLW53O8y5qcTknBFiQJwC8pzUaxVhNydsVelznpMoZjIjBPGiNSs9IHRUW709pdfGvCm1HKEhjWZik/1rCJ1QNSBkoZLm4xSPBbcHcBCBe/WI4VdJXTPUdz61uT1uEMsZexq+5W76o8ExfPTgbuP4DT59vR/pKH9/ROnhnwBnAfoZvj0cW81PoqIFedshDWSHUkcCMtom5w/7fKKoijna4bKerdgn6LdzHq56ob47jowF2z6iL/yB4Ccldj4SqqYcgfGB/RGU8Y4/1G/CcBB62tbzhbAmoLd6c2vbqjVnd492r9frx/jxntz9kiTkLp1AdRc6pDMyb434X2wuQ4o1MnTU5faW6MdG7KGRHAnAlan1aDhNQD/nvq/1uMXabD72pRy4j7TgqB82awWpm6XHwEuRW0P7uoExstun40UP9c+fOisasRq650auPjR7pddDTe9+WRpkjDlzp0XG2GegcYyfNwsfTHWcq9tyYL/Omm182xcsnc9r5R7j/cM17THFsetjTVg6F38YVvrjRBYLRyhra6/iaLe3wuHl4TCKlvThCjy+qo+AE5hxaKfFvNvYuFL/xRrmtxft3S0INwCChQ+GTXmXpTLi5VBcuCDlgjv6gIwJVK7E1WwSwWQujfM7oY8r7mmJrn7uZoF5iz/cSMIYggjR372qh9nAIpqJv77G4f0nzFhaNbDWKUIY1YYDAgFbEObAKy7dnwLru/Kikf5pHRZuHf8i0I95VyDpQ0eXBBoTPg0eEqIfy9rmVCwiqAukDEVTdCLCRGZxLkLtEESBgyiCMKklbRHLT4gAO4aIOE1iLc4R8SBKUjwJg9BcHSNkIIigNKcsDKRpQqO5isxBYoATiKYqjAUBh7n0IY8YMEFOwzdGA5OsI2fVYvGnJ4oioEQEoyAUYQsTieAzhDZXSzHhdEDcxMp0iiEiTBMIjDipEMwspjW+MWACZTdGKiAGqWDPGqIKuxLXmkBQL1UMiN/4dlaox4piw10qfpVtShGKmf4HZSmat5SArk627k1gLgJoeei3tSqcTrnNa3Btu1mfwwvSuVQPCvUYpV4DZD6yWOAzgyODcy+kLtaHsD2um/hSRxWxy8kl6U5oQkSfvnZ13y6/RsjmTquw/RuinIyCKpnEoCJqkg/Z2qlfxBidVa8dBRkWV7tablNAnFR+HAWXdLG3VZha9ANx2d83y9Mc/z9777oex62jC78gq7oly05WkpnZ3/1f3Z49k2Q5tiV1VZH4fuBAsLpaakm2LCeNPLG6TjwTxBmWU7IU8YYfx+wYqusrt3mRdohSWdav9b8/MHrvnxrqj4Mp+9ko6f6c5BU9xUgYdGwARtmgEZqhsN8hQi3FXwzO2r6uaxEck9X7nJmxzDPyfg8CsMwzMM/Yv7tGzoTd9RWWw4RiHlNgNUixSjWiwDgipeRpFQBdM2o0IikxJEpAGnfafhLjpMpYZjUwAbBUC6arI5OM76C2tnzwqNMWVLtU/FeL5FRl9zw/IZRMMgdt7erZkHwAW71qDed4RUtl2bwy/DoOMbS03XdaMNDYvg44vHyK/OJG19p1fM/WyWZQulVZMoTkdIztM8eX9l1kvLjh23Ar1NNHyotnfeiyXBjhFy0fuoV+4vw+QmQ2D9sRbV4TjmPwsd7vr4+/w3F3n3S9HRlhC45auEEfbZX0WOnPp+C+FsSV2AaHIGHP9/rY5US63gjAQowhRGQzo1cNkAMmxqJlZsieuE+sZTbXmjVYGQNWocx1D0z44u8e0JQHR/gd7UYjd9tmGdnOjn4UGKbkZ0yao3z3278AADM+YUtaF/eveJ7L8wEfYJRIwSdf6/P//hvjf/6CqpzhDoQCUXCPaOlbfDy7WgQSgMwSmYbSMRogNOxN+oWZEo6c3HtfoDp9EWGNB4U6ln8HEGZ/GvAhRPpjMamKm0wInbVnfiT/+fG+ie042lMk5zVDQsJfs6YDg0U0AN5zi+J6S208zRv9YwJ+rYQbcCdRt9DvHK5P7emYluB6jVQdXROuWPbDzxX4K22s2fCLVgeHof5SJEbM+90OpVbczUv4TKnXWpFTwlwYV0PGHaoYnzPw8fbej5OcCAVK7y0F07zg5t01EglPYmUCwH4cMGnKq5TEgJ1SRi4FI1fc64rbg3AA40r/xvavKEIflzZO1OgFJywVW6tsb72dPQ1fF2Eo1ES2FwjNUM83SXcuEBTvrOb+7GMyLtZ/EKy7fQqXnP5+vfo3vn3gPHfDzn8gXBToF/h7gB2U4dJ/rzyBtg6Sk2CIHqGIs5FF14rVZ9wOnO59uf6gf42oeA/g8wmGp10xBvwMxr83n38v8CF8uPknr9sI0tnXW4RvLC3aXK4ZbNq4fy481iU7rmLApad8/5Tr78skPsbWPty64/F/nAx4m8CNiGwIxJnSY8OCc8QBp/Z19L1fs8iPkVUqKDy6p084rFpSgpnRGQq1IKLfCh4qe83Gr5+95PoMeC7C+CrA53f9bwOn1sJDIoB4fV65Ipi50d9yPkcTl8h6EK5BmMFFlJRTKnK8l4pcR8mTXPao5S9RWq3Or3MhkCQdiHfJO4y/Ds0buRbgl4z6p1AS6VcRqAzjiPTbz8DvH90bxWiNQiwMP5qAzp5/m+V0zuZ5bbyyde87n6iVUVBQUoLFyhEdAiMTidKcVMjYRcQQRWmpM0qVXNWL/s+AeKerZ8Q4DhgG0QhaaONE5nERhLQAqJpCUQUsJvhgU+zDFfz+F+YhzU3OwlIoE7lAh7396qFcK8acgURIw4CclXU1QROLAr0X+KlSK2Xk3YikuZOHnFSBrtEjqkSDWBZgLoy6yH2uYqQwmAd5lB6ZcIkJTNVvdWtZNFW6cWyTVVheeuknVlFOuJdWRut+FUp6XdwuLOR8VHS3heMfuEKbVBHP6g0OV5qzKM2rfqMTTtAIXLoImpLeRhrgHcMirdtyqBTC8JsSWYsFQRV3GnadNDMpt2RUoetH0AnYulwjx8+tHjP6s9ITkoeQt5e9RyueMdpi92ARNJpXUhhyH3dppoW3NMOXU70zisbOiPYOkXjNr99tJ9y2uepj16ztW4Ot6DVvLatiATAo7RhVL9t9cVxAwTf9iM/rv+AqSm0xfMni0WXvlgoMjDxI2pK7L7ddrWbMkDyKA0EiWuj3tYrRQSmYlhmlFAzDoKFcOaxxYJ4ObR1Hmks7ImelrXfrxRZdHfpJx2m+TgLpugpoAlZGAtyLS4iWo+Mqvm/KcWuzG8Eevx3umOc6O05YNc/vranxLceBE9U80IL+fkSTD53MHFZs4/8f9nT/ltTGa5T/duAUtfp14DHM9vahX8HtKq7TfqUmiBLdFdDqkW7euynQ7oAI+a9UgSdn8nEebDkj9ehH2ylRqRl/M4m3uKGatHp+Cgji/b5rJFTYmfJvBcMpORa0ZDnSM1oodydP/H47JSsYC/4SI+BQdwGD/mdGwWeso3zcg10h0kKk63gD2ONnHPDR+aAREuloneYTHNFviIYK6owGInQkX7gf2wGwKFyP1kyMIGLrJdAL+v89nbc/1nTXuXgyeqJXghtZJx0j8/7+QhBzdH3+R2J80EFdr6E19rjR9Xm30ajrE52z/vs6JXRroutjqHCr3/FeorZL128vVebhsBRkknRJBCAXicjF6p5v0bOYJW0QV8bVbsDt/eRE9FwqPlzvkaYZi9IrSSMgDUlSS41cNJKChLGP47Y1n8ctbjtws78W6v1ocJyBczonGkX3RF5EONzRG82b/2HK9QJvE77tKf924aJAv8D3g5fuuE4CF4sNjC+zCqia4O6xzU6BaXaLbhMone3ZCm/bWfp2anV/gBBslsvlA0Tm9g7AF73+BFGqD2hEx0cwDq48x5vBaHK8RmJ1LTB47BovuN5WJK4Z/E1Yv/CM8Xy6Z+nrwNdu1av28mRlb3OsX74Pz0Mg5H+PvX6eCuvSeitFCs9jE5/jSf1CCIK4xxierw3drND6yRkSQn0r0YaA8SmwZuC13q1w7e336QpjTszNis7r2uvCiYm2IVgAjBtn95qRNDayiSTeQUYkxma4geRCvwNw5V8mdaXjWlEW8QFhKlhSApU7gK9Rlk9Y3NO1nXTrs69dHZ9eba0cPyu4BaU98jCK929SAflvCSklDyeddyOYB8z8DgmMgltUaqnNKHh6RYZ71vvlsRw4XxVCXd9sQ2sPifrrR0VI2/DVh4fb/1wZTAVVzaVcEBnbXpOsQQLKIgr3yhWliOK8loJSGcwFOSeM44j9fi/K9PcZ8++LOE9Lb8RDu2hilixuNwx2b0xWmrnWIl626o1pzxMl8VbuTojgyYiGBD1/MCD5jFFA6nmR04DdsMPuaqc5xFUhWqp6FbchYJb1n3NGypr7/Cq5AlJ8djKWRbyfiSuoqAKQJdR4ArocxymF+C4mBNKYlaxtN290QOaqUlCoEYCiXmDu1RjEqtHzRY3UGIBJv7m20PKAhF+3plRG8wh3D+OmTq0aL5sZKPOiXqjqdbvUoHyvwgNVVf6ru7yFiva5115LSHa9PzJ4Cp7n+oiYwEjerjhRvQAYANW28zi8Ghi34+21cWLJpgBB1mLLpd14MvN/X6dRsFzm4mQvRho1hPlIWbOWmiGI1x6FhO2+r3r/Q8cdIXgbx7HNPdfqIcr9VVuH9o7ytURJjRF6ztgV+77njpkboubzzT5XAAAgAElEQVQ5Jq/3dKT3MOxPJonqYP3JNGK4HnC4P3h3VbertI7g2NaCENI1GNBYbykR6sIoXHH97hopJczz4o0qpWBMe03NRri+ucHh7k7SEjB6GgjhWvGVKcPNIIFZQqXKGolhXWQkatUQ7qqY5+iqaX+5vxWnutHLrJ7vMuBdJPIjWg1q6NLmqpsQyLhZCoy47gHuvLu36UxyYXdEPQ1skcX6243ICfQGQa2RFjSmPaKjTbxekYRzjPZsXZtxr9bXeRDS6u9R67A2YjgycD9FDp8iD7ZiS4cPT8/F14bTxPrrcWoRE20P5VlFfI33O1z99qAZs8a9JSB0ha4eiygFcsV3fJ8BVM2jXqB4PZRFAHbBOC8+a37L4Qw2fKtfmGJ60XYMIaw8Q5SnlVhDtTca5BC2ZcxT3qIPNSRhZ9X0x0fx+kbfXjtb1vcqGLvfEnb4F+bfP2pdH1DwCQCj0Cev10ocIZ7oBMs3L22yxD0AcMC/ve3mLDAQYQr4PftEULfUrJ2LVlz0m5jn/hSKkXFtM7RgzZ83DGwh/JmlHwsqJhKDhSsmV6K3dRIN+QI4jWDPNlpnUxW+NU90mX9ZOwPE2EIMDWTdfCHGDQg/W9obEMZfgC9/Mr5oeaZwX9eeALzT9fwl1E2Qem9W9yNYRLp3LOV8XpVvuoJI96yBIHnOExF2SWZ2DvRVZaFzck7YDxnTUlBRUTT9UaqMoRJoSGBND4OUkIhwP09IILzb7yXNW62oDJRScbXf4TDNmIvUzbDMOUkNYkszLND2jESYnOaDf3fUJ49oFehzQh+Bi9niuqOd3229m3UfGcLgtrNJ11BTq7Tnr3gQ/a3htYcx4l0Of/9JcFGgX+CHhRXrdLx5nc8ziUBjkk4ejicwQDOQegqKeFx5vm7HDaR90Y6+ollevgvvfdbfHyCE7UP9+p7QhG12vY1sH7s+973t7+jo6iEi6WuDrdH0JmfoAt8MjGDkfl3a9XofPJcIEUZLhcXPbGori7q/5wC/jjToDcN3wr5k//QsuCkKjtpE63vPXW3x92vP/WmhIHAsNLd74it3DFsjEntl1+mXBP43YFnLRQB/i0Tv/AtiUbiUZUFlbh4QtYLqvXq8ViwEUE5HPRgBDc/3PBhwI954mVAlprHncyaSULQeorlo1neuR8skeqHMpwQoF3g9CMSKkLQHgK4gMo3kkUAIkot8WRbMs3huCyrIKEvFvEyY5sm9xIeUkChhHEbs9zuM70fknDDkATMmV/J6LBJSmtYUpvpb8gQ3ZaLktQ7K1WSe6BKaPXrqAnCDjRQFK1IxJB+6KEGHYcB+v8f19bWEqx80dHWRMOcSeaH3eM9DUkW8eJ5WZpQiRiyoKoxS5V1UpEqo8uOkSN5wgii0Kd7uDZcqM1JgKlxJDQIVVcJRaWetdlsCvrAqnlXopcKsaG4TleYV7CHWm4eHvls1LHoVpWBVJSBrm2X8TEgvCkWO7mgWVp2re7dXtDlnbgJvM6YwA2bvO1pUAlfk8mkaSDHqeuQ7OOf0IUi4zMb9NUiau7zW4AnM8Pzuzeg6SmqpU752fmx+v/W5taITdXfPZW+0r8yQggBQSmrw4QV0xjKiNOj7awMY6cx1+4/HaePcxIlwy2YsBkDE+0k9slo4fG+LhzXXFgf5q5V+iqIoi0SHSJTBhcWop99wWA4ThnHs1ubJlvunjnh83a/HpKhRzlKqRxgIVm9tviIjyaHsbgzWc9Cq/xpgnmwAPPVFTAvCXYNX34Y2bgtRwl/DEVG2QWHPGu46UU8r9TEf8ONvNp/Hs+TMb9pbx1jnWdPxJNK/vRjsUJ5Z6bd8/2vDQxT2d2jK9x6ORyCuZVNyxqBCax5nnf4QaDmgs75AIJEjsvBCyWkdDf7NJkd4GGYChtoPY9W1HMOTh5hD/u6ee4yy3ja0el7+rMh4j4LPsLhLGX20O4IpvdllIBSeFwADPiPjveY9bxFn7Dvrd/aWw8394lyYIryEugdtcw73Y9+yRu+rxOIlTH2Zdn5vLcuj8XHsuw1GkcR1AzAOZtippbTxiXQJVq1/3uFUAewh3vkLifL81HtCObSzJYontmgCRp9qbA2MRgvd8LEi/Z6AK/1wwSlU8HC/rW5Wo95aefO5KL8T3l/vcXuYULmgsK1HaDQq4b+JSNO6ifyAiDDmATmJrGGpFZkzhiFjqc2cgiB7P1HCHsCh9hGAJjB26MO5WyPX6U02O6r97I0eEfiLE4NjhIBO6Pr1xif1WOCNo+ULXKCDiwL9At8dXspDRkLK+NcmwKmO1E24c4p+FuFOJDygFuJo2L8lL7TKux+dF5Bfn+eFbsTBp3DvWv/+GdoYq30H4C+INzpwXhil1wQO/6/vb/3eun45HIuGzlEO9mEWn1rj24S32q7Xh68/Eia4jF4YaxGNQRQhrO8fC+AebiuF99JZXzwMrkBfE8i0ce8bwY+3Ts9jOE+98fRhPS0FinPUlRuExy5s3SziMYlg+Mg4uG/G+jwkjY2nYX/+dgoGijukwfoM6msyIcUdCO+hix8uZOVrsOYEZNwCeOfef1xVAVUqZjs+ShXGXxXoGAaQ0hYFzUDuWAB9zJzLP31rTai0+48xWHer8EoVG0TJpbZcCkoR/4qFvhyNhVnq5xOEi4Xfqz/eRt0G94zcxr0vNUp6tPqjO8fqgJQTsuYAN4FGUgWCKbCXpWKaZiABSwVErMIS+q8UUawvs6yHBAx5wDiMuKri1ckHBmcgv09It0m9zsVHJqUEngl1qaDEQE2oqSKxeutqqHJKpGurdUWETCr6cuW5CoZT259VBSsyHTLqiQhICcM4Yn+1x/W7a7x//x7DOGJIyRW2pG6uSbRsHhoRqlxeSgESYZonlLKglIK5zFiWIoq6paDMC+oi+ZkJJHnNa0FSIWgpQXgVvTFOzV6NIr0w3y6QIq0rfEnkC45NGGVlOt6We547mYE+DzpD09y7uNiNHSqjLEXerbJ2zBkWWo7ne7cP9b61ROoz5ZXMKatomhlIV0CtBNwDxFXxEOC6/Q3xaNt5FqS15Wt3j/71UJ86dlLyb+y16PVSa8WQdX1pnnnrT0qEUhZRCOTsBSRrJRHyMPg8Esm6ANhze9vY2bwsZfH3ASk35kNn5tBegoXI9xE6QSDY7RzWRT5+qw2UDsG8aOQCE7lzFK0nPerY79n8RUW/Ky/NvVyhThVZ/QXFo36j4cZWIxjlaIeIAFKNghh9qXI+EdKQUW7vkJOEx8h5QMpJDX0SlmkKgtnWrJSTjHlUPkSyRdESJTcVEkMbE1brwWupKlwMkC3CQULSEKxro49aGTmvqQvB4VXXFSXyb3uTgn4NG5lpigaTZwBKO6xyuyaitv+Pp0D/cvv+eKZio9sPrZj6B5EZ6cuycQt1M9b7uR+jLbnBVqPWRkWy11evdRrGxpxRvL1Fax5Pw1ZTj++fQRfJ1nkeAfV0xXtck9+SXn9KW75jO16bbn20vp7em6m/3tm5rnSBearv9DXzgr6uopC0kTVl64BGb5mHefNaF5xnCThMmUtofMWdtmfkVmdsx6wIPYaKJ1aFOsm9SuRl14CJs9IDFWJALL8tCk3C/j8TvvyPKAPjKWUrSN5n/wsA0+8fNRS8vFMAJHc5amcaIIYGCb3xctb79s56lY4gLHpouIyQWxh5U8oXYmS+wdX/t8Pn//5d5sHmhUy8TMiw2Dy9yV2BGTroyeyoqw/kPlM0xYPi2gSw+NXvGDhQbyDUZJsc7qjZQ8R7MYTJCjrDP8XvlmddcsW3YhKLPNveuSML5S7jfP/nMT9pSvA4/gVqtEAtbLt5Xn8OjNoXal7sjBbR9S6QK1eMVV54pavV8Dilbc6vVMmFfrPboybGMk/ha+O8xVN9qRVX44ClFH9eIcaxBKFhqj4jIqRMOMwz3l3tZRQrkAYIbcQJuyHj9n7CfhwkakJYHwTCFYC7QP/MCPIeIKyPY+7FztLVapJ1TmocqTRarxVv65aZg5G0bAxLAUZu0dmeUziI1xGnvvdJdYELPAQXBfoFfmjoWM2GwRU5VxcatbB0p0ReTSh1ktY94lpOoXf214n4rAOAIcSEKc/f670vj3x3u7r+vPnW94HzGOBvDw/xuq/FR702v3aB7wPGj5zywngMzsMWVtdafEVNWabteA6cDHt5gTcMuhYeE+ytb5/wRnsczj0Ln1PWVplrIe1xfdQtehuP2PGTJ7/+29Q6dse+SL9KCHT+taL8ITussqsfkOgW5PFhhAF3LwlmUDXFuyjXs1mfa/kW8q7SFlN/3NpTj5nZvcytR65EN+W5hW5Wr9RKItzYmoVTCvK/jeL8hwHN5a1KIBFATGDsm20nV1EKTxMqLzgcMhJmCTvMVQQ4RZR5OYnSaT/uwZWxlEUVqSS5hnWCmdmVxkTiPWOCFKaKVBOYogdvULCxqt4l7R+IgiDHpLcJ6sVNattBPQ7T9ZzHhHHcYb/b4er6Gjc3Nxh3Oww5NwU65ExMOblXvo/JvGCaDyhgTDOwLAXTPGGeZyxqTGKGL4AaJlByXZH6hoTQwNTSApqwaaXcNkWeRUXsPTAqiJIr/qM/prSbuliqpt9xz/paVQDbPL2ZWx509/6O+J1ZwrYzdznTuarw1hTlihdg4SWFlWpthwoINTS94BNR+BIA2qEpGHeMeg+vCxz6eeJvE7u1+w+dLA89b4oEuBCQGEjmkV4lf7R4orcw9kTJ0HMTODJAGmK9loKUcshn3s4PC8kKNHrOBIgAkFPW36ZkZ9/TzQDiaf00zUQUZrc/4SuboyYXhQsxfQdtne7bnuhGP1QUkKvu1+YR5x8Wtp0oJTdCcBpF1+cwjliWBUSEYT+uhNzcjGm0fynF8P3xVRMKNAMBG3v3KmMtUz8x/BCjXBjOsTXfabXDONm42npa8wptH4Sw9t6rR4BZ8qpuPmt/+zlk/5fYanxkrhqSOiFD0XXaE1L+s+9PbMtD9XL3ykbRp75opZtkXoX3AK/GXe890pJH4Qkk8Es80L8e3X6BHxM2+KIADdfov/qaG+zoe+ZhncLfWEOXWgLGq5zeIe7NHspwdKh/K7V6EjeFP4V2GPYb/2PAUtu+JPRe7kXrzF53u6/JWZD8PYR/uRs9Rh/5q0AUj55KJPy1cRoRjBH0+QLG4KcuY7Dzgxnv/89vuPu/f4DBWFLrT5xJCmWdOu8XkpD5EZe7w++Jb9aRL7fP+P6cPxdTbJXl5yXBDSkKjvvLkHD2g940Jfc1t+dbnuRWLq3e3wJToseQ8Ab3J+6fCxJhSiPvbJz7lS0qXTjDuEWVrcxIjeiE0yL6DREhkSjZASifBgCMwzxjyEPjDXL2SFMRrkCuUI/wGF0NIBAsaMaS3XO9p+/5O/6u4p9Ak/XfNWr/MRr+Ahd4a3BRoF/g9eFMbHgUTj1yX4pVaf3clee9IKmF3Hu4LuexIslmwo4jjraV2ZghdsvizrL+BNjj9xDlN0Gs9Eiv12TyqeI+AfgJ4o3+9g6b73cENpHQ1sM1MfB16lv/2r5+Xfi+tb8l+DYjcWp/EoKQhFf3T5RzSqxER//Kr8jcISrQnwlbnucXOAXnDc5Dbz1vtnqh4lGZcQ7pxP0Xg519T0ecx+z89pOH6t169ZT3vf1cwu469tQ77ofQAxX1jwr6TQT7+ReA/2CA34HoFuaBx7hFVEXAvAqD0ohhtEFrXIIIRcxbggnYAZgeG4YVDEoPkXpfMqAhvAmUNYx1VbV+yO86soSgr/iCqm05NSI/MirYXKX04NNO2HgOPHUrnFs2xZfN+xw79WSA0MKlgpYF06ReC6roLuaFbfRxLeCUkXLCQrIj5nlBWSroJ8JwNYA+ibIeZIEsk3qE90IQUb5WUbqa8QYSUlahreXsBjV6XD6WsmtTXJm3aq8EFIV+HjJ244jdTpTou/0e4zBgGAZRHIcYmERJFfZArQkoRZT8BEx3B9zf3uMwTzhMBxzuJzAX974WCW1CXQoIKvRhAElPVfWuEN6DvV8mPHKPWjTBsTnoxvDSSBAlOoAWaJPU+AWyTwkqKVSBshITpIU2/sbynrN/a7yI8D7iqe78CgOUCWDxdCZK4CV4Tuu8gdEMj901RMu0/8JkWSAS5qqfqyh4z4LU7oOPVciRGPeeKYYk+2h42mt8VxvjATBFnza/lurjmHPWEJzVfxO1kJxlqRj34hMHIiSuqEXSI+ScUVSJy8zI4wgCUJTPtNCeMVWBGKA0o6kjflTHNVHytWjv11r9u+4TWzsphPmNL0bZrI49Adir0rnovi26Zpofk+QzN2HueDXicH8n+GY1Fe0sqyAMdgjBTAmYgZwFd3gUOD8zG/9sBTPEY7wuzbuPkkTDKPOCPGQwVxlzG/8hC64rRde4rJyUyI0eOuSixjV2vxnPJ92XoX1sFJqUB527pAY2SQ1hfHyDB3xKydcfkkVSaM/t3ZyT5CzW+Y4RPNjHR7clN5yyBqc99CLmUpYzIypeWjuawn4tcWhz0/MZ8H6xba7Qho5GC12O5TO6zx6G2Fktr6P1HkEE8U0Jb9DfZ/XOTOfEn9+6v35+MhRgwwdAT6OeA77TXiyrWCGIfxS85T6v2ybXk+5/A/s5E2Nkwt7ebi7KnWLX7YH0w7SSG6x3vdsCKQ7c2RPDBSfWr3nCv6t0tDUsok/ronlrS7j0BIl8xTDFdcL0v3+AIMpqK7Epq+HRi5KnbjZle/O2J8A9v81DvBsbsI+HjcWibTClb1qN2Qx2/OX4HU2pPrB65YNQ8Rn3/23490bO3/oZhPeo+Iyq1I61aY1nXRHJzfigKj1muFZwl+CxCAmEa4ix4xUSDuEMNAx8nLiCvMzWR+pk5PZat25C1ROAKxtfLcgirBG1MOoGFYQRhHdcfUwJx4pzU4RbuoGCh5XfMSf4HYAbJi/TDNUJvdG6HNWk/IOskrUnujX/MM8gIlyNA0qtOJQ+hLrBMGTQsniO8QWkhvQQXilnDCnhMM1yQquMIKeEZSnIiTEvC4YhY8wJJWcU5QUYQJ0n5Dxgl7PwIaWZQdyHGTajf8uFvj5WDaLHOgDffZ6mS/edeaLbHIPgRojcL6BWkjkVrlHd2nEntIs2Xr/ABb43XBToF3hT8Cg/wau/3TOT9qiQxwQYfv/hOnsi8mmczXMtiQ3Mc5wB3EHymp9Vb/j3bSrPFZ7IKH4VUEHNFnP9Ws059hK+wD8K2OW1m/AQYUir35El3WJ5PP/XCe+QJ8OqkIsn+luHjdX01aZsW7DzVuGcpbqVE32LqTRrcWEGm0C6F8JsK1stPLt9Yw2j1XeRPT883vQjcPkaQRVoVUJRA+7dGxvHzCh/VBWEn86p96PD36ZfOn8WU8CVI6wPmVG5YCkEnhhYVJhYJXS5rYGsYfxZRXULSV6+eV6wFFGmp5Qx5AHDOILKgsoZxAxKFhpdmsSsQhils2x7BP2R3qvtxIpnk7qmuzjPpSpNYEgkyrTdbodxt2t/xxHjMKriTHOAM1SJ3WtzSqkoZcE8zTjME6bpgGk64HB/wOEwASa0U8U7wzxe4e1oLtXWNoYoCdf5saPupDErnXAKCPnMw3OCjLN6pJvwyZXnK+3oOvev3fO73oUW2t1q69rMQbENVSyaBIyDJyyh8VTW5pC+Q9gsy6UecqrrmNFeQ0DeA23WdQRN4coim6vc+hUF26c8obfAhbr9DwmJujJisrXb7Du44UZTtoKQcpbQmUsBqoR5N+/liGCZ1ctd7ZS61CJE3oZaGo6WqWANX0s+fvpC1674bGuVHQm7ue+rFSmhwF082o1f8UQeDLoHRlXTTLjfZr/R1pbMmakgjmEddruVYOcj4UhLrGcbDbl7j1kU68yMcbfDPE0+HynnI4M1qcr2MLVL2PYmUUQQkCkHg3wKC6Sdq3FfWTu7tDamvO9HYN0x602/nzdHbxssJOpaiR9rNHztfInhEqzWD8Wv0MIybxJW0XM7jkHoXsB00Rn8vKzjq75Q37NTSoDtcuB7wQw/ef38Aq8Ir60a+dtQhA4zMXYb+J27Oz3fkcLdNc9jXxhOeM6I2fd21c6EVmcLsEMtPUr4ov3bJB72joVd59r4LvvC+LUYxSP2oeiTBeye0eLF3mGwDhJIc6h/DveAOIIah8fvJLRjgHCDQp9x9Z9i9HX/3wzGp+DBzp3ynBHbHXCq03Wkx2PvpCV4Wo08tV8HPQt3fMzr2bkf64nnwrlw+lRozwgaGj8sOD+P0NOlpOfEuuArPYds/T4VokLeFOa3dKzQPxv0bLNUP1TWMRvkpbtp3rR6ImbMpYISYTDjhpQw5IxaKsZxwC4lLPOCWhnzvGAcB9A0Oy0i40pAKaCcUZMYDT+GWQnHBhsRd5xaAcZ/djRNoLONL2xWYrBlG0vYIFL15wnhzWufFBe4wGNwUaBf4NXguexJJCo2IXi1iOCJ3frfPa0Y3YHTManRKtIEIRwCzkQChWJywnjfbpnn+WlUf4rhMy/0d2hih8f63iwu3+jh4jIQwgORn75Z3TIfdDw4D8zPmpA/l8V/i/Ct2/VW+30Mr9vSR3EWtpnXLcL18Wtqwq0TnsfPgS1h2Xo3PC+M4I8ML2csvw4YYl2fQ9vzf8pbp9nRf2944kitXu89z2n7tQ0huqkIThHCIuj5gor34D9qsMwW4buN3kMMPa/qZb1XwZj8o/P6L4KiKIpqCvoKiBfeLMEIa1mw/L5g+I8BzJLNMI9Z8xtLaVFsY/0YuPdC/5Hga63k7Fj1PPhWnucGzIxaGCmJL07BHYCiOc4h4bRZFJS1CM1buaIyo9aCTFlyCSeJRJBTQhokD7Pl4AXEm3IYBuz2O5RasZQZlBLmCShLgXm5MpNrYhiEXrEE91Soqtx2AdNxx8J+ZZhSGoi5lu1/o8c1jzcXUFFlaxXv4Koe9rVW1Cp9v7u7x1QmTPOEu9t7HO7uMS0zlnnWcOWS/5pSQZ3N81k9k1NGIjvnLIe7NV4Vvmj0pciVyCd5HfawhWvvQ/B6egU23LIaLCUMiJLgD1O8pqT7mcFc/N0ou6qA5OxmyXdukQKs3kqEnGUMyyRe1RpfEmDxGiNIvmZKCagWrr1Ryhz4KyZVklkELjYei/3d1nWPT4C+RAvUuq2AfYzCEtKfujsEYBhlHSbSvNlEoEoohdt86bgOBPVSzkiaKmCZJ1ABhnGHnBPmaQYYmCfNgRkNFdySQj2hjRdp7uAtxzp0D+qBVPVjSy2QB8vfzb3U86iH26MEX5IJ5uVOSeadCFiWRdZllfQB5oVv82Qe6hkJ1/t3uD3crjzR9SxUT/i00/3rqSC0fldYRx7LhiTsG1jezJg/M4zbMIgCOxOIM0jz2ZfDjHR9hTxqyNNDDMyrIdgDYinLAhBhHAf3Xq+oGmZf9joRWoQLayLrXrQFruNvhi9isJZQK2O/H1HK4rYP0n/zbCPMS3Ec48JsIhQXVDcRhpF9FiiiTTQ1gwjltf0Es2ELY9+pTLjtU/j75D8N57c77TUmyJoJOZsdf8GG2gyELPqA4bnHT8E2XuHOKpevVNcm5iHOvptAhJ8qIzBpis9D+PIh2DYGWY9Wg+AI+h0gVryeg7fAC1zgqTCpEv2gHulH65YYTAmFGYnJjfzsdO2MfPW7GvbSHJZJYjfjxHUVXHO/IoBv1SV8z45BhCZIJLmfFdeZ4pxJDNU0EzS+kFBJP2sD/0jieTyoEHEkwgCL6AEUpyDk/+KcjdCMBPaQ7AzS6F6Nf4unEa12bcuj3rzFyb+TL68gXtSWeWdhxodfEu7/NDz7BYmBz//zu5TrvKN4vw8wb3zuwuYTgNyx9CSe9/p/tU47ym1GmRZBaQ/BNQeS/PUTAdEWrCnR2+z3lNMxxlC03nSg2qD43USEfUByVf831iGGxzfjhcSMTwmrwloZntqMnompwtm/Vpp3XujWQWu70kNplSalaHn304xEhCEp/aQro0B4kN/e3eD2/oBlaZGVpEAJ0T6mhPtpVoOLiv1O6Bvha0SPkTPh890BeZ5xtRuBecGkvH4eRgDAjvdY+AAMAw5lQb+j1XhUr65Df9fGGzAvcqe7PA4ZTMcCajxanI9miAv3UI8HXjwZpTmMZmlCno7ACvR20fFajGBGfhe4wGvBRYF+gb8NGDIXHlkOHRfscH9A+DnszP+a4QkvG3wl7BwJNlOa21+Dx3Kfr8t5u0Ddn+eO4XO9XynWz/F+gG/AyVq969xDF7jAS6Bj7oJXUzp6+szyT0RseAyeZ6d+AYOn47cVd3FU4LpcO99SuM8vQ32OWp++Xo6/eEb//ZOG3H1PHBVP3fOHDD+CTEKFGkDBF2TcoBOuEiHhBhW3/l1XhnoaxqOvUhOenIzy+RhwpGBa2QBQ/6jAf3o8Q7mv7xMRqioMZBwswCuDtQ+PVr1R5wW+PTCgucxFAMMkXqpMvrTBDJQq/jWe554rUAHOtj8yhpyRsyjK5Z6s00TJ7+/HnQiCyoB5HHBbGXNekLOEcqdUPXe5tc/K6todlMKncJwoyQCRwjCQkiqbmqLHDFeZ1TCgFNREqExqJFBRlgXLsqAsBfOySG7zecbd3R2mMmNaZkyHA6bDhFlzo5daEatmhodZLLWKsoZG9Zo0BgOu3GNmFNZ9vsItFgb6uK+WPxk+eZ4jMGxtY11MSkkVEqs04DJSwbPolZKoR6mGMdfINAliJMAJYMnbKGGoAVjYeCIQaZBTBpDgIVeZKxIYlcmV6Ca8diUZsYbsNw9ygmuRGY5r6IrAd43f4o2/T4UjIW9Ya56bMhyZSZXnNucWUtwUkVybgUKbixDa21IW2DlaW9lRkNj4yuO1IOdv+4KL7FdVN4hwPaVgt8FNcu59C7LJqBT0v2ExWRehHvWVADMIh/Iqigega5uo5f2uJOdFpgEZg3uoRxLD+uwRBWIb4kEYBK8tgoUJ7mUfUFJhKkelBmt6g9ivQBPn5EJiadJw0rEAACAASURBVNs6VzQf/UyJwBBjIq4VyBpCnUgV3eTzbH10Q3qy8exXLet4pmSIBf38h+txGFDq4nsUzGBqwupz90UzpNW9l1q0kGbsp2PpSYoZpQAW1tzqijRdH7y2HzsyvGGoUd0GzYPf7RWCcU1TThiSeZySiBES2p6h7o3zQEviBFO2ewoiX2LahyeUegrCMj9uSXfziTV9P+37N4DnYv1/KGwslR2TKzGB9e4geBoKSp4/2ooiNC9uDvfsSKzo12r8puoNez6yKNsj/+SQFB8QkNywSjCShYpn9LJYa495HtfQv9ge46cYovAe/J61ovGL6+Fbt9Xw3YAPmPEJAz5gwSeY0cBRvwAPwW7jugD49GfFEOqr1Npp9RY9X0eQh4nvZCkq26mByM8EFDtSwuHbo4RG+xne33MLsY/wbTtfnULTNofoQ13Jx0fZOcCAGxhA/17rulwghgnbTlZfHz9cteXgJd/Huulp9YpBPJBTEp6CbQTl/1Kr5kvvHdGZZRymUiSEexF+pFZGVmV9qQWlVIyDmLnMpeIahP0wuALdWjrcZPCXHSoO2OUBU1m8riuQxw5iSHj7zeFe0zLBCNh2phhbViCGtncalZwwPVai29DqKvLFxAFHtcetzofXXCSLX3pmX+AC58JFgX6BV4eTCG7jrIqGjXJI8PaJbkeVJQmz91aeD7T6pBNwAOASJCGrukzwAKAx1Fae/3yaKukzJFx7AXCj96Ioe7Orq5o+QHKgv1lQapxwikB67PPnKwY7moi+Pt8ZD265lquL4vx7w487/muc9BC0cO1fp78vV8G/tP63Bue26AWIZY1Envyx1R3DDBtweJPQs+/GCm3Bef15+Xw9s4SNz04aIWzcd49PvV6Hc49Ca/u/4gsS3vv3TejQPDo4lGm7OAoM7EEJQuf49imgB662PxCl2fhf4qGchgQuGuq6FCz/WzDhCwZ+Bws9CAY4ne99vsXEvia86ChfNTY/cRM+1eP8awADmHEHIhIP+aRKb1KlEZmMosWVICSPmUhEmjyQJbTxkJCQ1Ot8FC/lScsZEgbOoDFh4BGHw4R0r30HZO9UBjK5hyhge1DaBoYIklyyGyU2undWwqQobLHQ2cu84EAHjLsRw27AbrfDYZzkvRGukJEw7ox5mTHNE6ZpxjRNuL27w+FwQK0Fy7JgXmaUUlFrBeWGCwAgDYN4YhcxNHGBruWurs3oxPtBQXjtvIhceMhM5TVMcU2xbJYciwxEfabX0gwM7EbLyUiwvPMsgb8ZYOSQC7WJe0XgCskHH6R4MkciuBt26vk9B9VdQVP6c0WpUCU6AJg3ugnNbCjtrJGyreEuor0CcMeOg1nL2FIXRgEar36t3zm1h6sq9h3H6xojEgVqKRVg0rDrzbSpFlMa5zYPJOu7LlU8w9OI6f7QhlvnrBt0/S1pFyosaC0AECUsZfZ3kubsPlLMEtQwpu+4jamsn9ROJQojXjXqAIWxZAAafWEcRtk/S5WxMCEpxEMqD7I+l6UApHm/NV+4104ScaKigg9SRk4ZIEvhEKSi9od0/6hLdRs/mQ83iAueX5JjPnmKkjxkoCY3aJEIHOzv+jnPbW3VWlDZIjEQqgqaWeu2cfPIDRrRwoxceg96+V25RagRebCsF0mhAR8DCv02DywiMQZKSZQjYgrT1t8WOCVHig/IohzIeFlKCuO/rX/rH4kYtZqhSMQbaEYy9okTNyr8NiM835KNouTwen/dmUo8eOqu6Z62gnpxuaNHJniOVYRzul92uv4JIGvLcay559AzfvLauuV4P5ZtkVzal08B+fapRMg57697/VqEzveq9weD1TBZ6PZJPc93qoSaCcjctmUUVxIInJQe4R4vpO4v4S4dz8OBgGtFPualvtcypiSl2VdTq1R2hrZjb5FKIHjeqAPDBzcssVKWJIq+qyq735pTs7w3cCgXAIooYqt6MSclQWalg6x/GaRKb8XdaOm2rB0Vn7D75QPqn58FF4OP9jGStH2uFQnAh//6VaIg/c+fAEjDxUuo+MysnvxiYOTh3qmNU470MJReUVySQciQ/OKZuFfE2qRVnXRqqnMCodjRT0FZvvre6K8tOmuFRo/A0oL4eyTe7vEDRjuz7Cz4otFETHltiu3jVSd3H2vHuXDntBd1nuetsbyqxBD56iBRWJR+GHc7pJQwLQuM+icAH2/vMObsOchHXX8LM8alYNjvxIi5ipXJl/sD3u13GlFLeRUMeH99hS/39/h0d4dECftx1GhcFUPOmL98AWGPDKGRFk7uSJhDe9dGcXbdZBT9SDeeReiplnKoCi8Q5zpYdfZnKgfPcj1zjZ4yOujMmX3p/F/gAl8DLgr0C7wqnIP4/B3urxnoBZfOzAWmTzhgtVxHy7fFkWVbF3CiAQ/S8A88fAbtb4TjOZ7n6yretPIckMOUjkf/aZ8/88g0Osj+Ro76b2XFfYG/M5hXkl8Hj7e2t15GVnZ5Oh+Af17Y9nNhdWCdCe799pQ6uuvje+s5pKP7HP5uzec2GxtL86tn4Gba+PX8Qo7Fqu2d89Y0IEr0MVx3PKH//wVm6paoRX4w5V3/LlRIHoTK4Z1nn2lhXrL+b6HxFv6MgX9SBYfJzkkNA03BwJjxpZvdr8GQvgZW+CdjHgkvLAot9zomUoWbBqck81qUFZdMoZ3FcziRvJtSQs5ZQpSnhGEcRBmYkyjIUsYwEsYsSpi7L19wm7J65BKC/9GJSfHVB6CdV71HKDUCPfQRaOuRmCS08jThcJgwjhMOuwn73UG9viUUNUFCjFfN+T5NMw6HA+7u7vHl9gvmeQKDJR96rQBXDQlo3u5Nxee5hGsBp+BFYV2VTYWmnFaxY4w7uMJJFuK4mpDIyjSBqo6ReY3HUmRc0ISf8dhnG9ukHqzVPUYY5pVEoRCI0Jyqh/Gs6hqWEOYnWbhTYaIk8IEp/FSJTqTeoNJSQvCu8TiMISuoSosJKvy9IuBune20gRkfPHQStXej8NaUUxyuNWIASdhXhtqSJBKFpeFLajlCU0peRjWlug56rdWVoAbGfrZrDkPfnjAkmgSrwjVtWOO4d7t786z6Gj4hX0jqwc4AaRQH98YmqHJR1o8JzG39mYEzpYTs3ufJ5zQlSWmQMIBSBmjWKQ39R99HE3mTM+7HpwxXFidkfTupJ5e1zQxEm7dcm9+U1CiMEpBVcR5pMK8y8noMC81u+ANQRXllzMviY58oOyYtVULpI9JqbPPa1pnNeZujnraz098MhWTNybOUNCoECFtq8/U+8C7a/rfxSknwWQ4413FGRGR6ppCNXUsdwDrYboDghoHBGIENc4W1FOibbp7DXxmWB2i2M8HPiLAHnROi0C5rNfUckqIjmNFOx1+d26punW09PvHAlumzScBTdPvfBc7B+v9M2FqnOybPhU4QhTqBkNnyhVOzeVFgEgW4GGq1pCkx1PbJbWBl9eik4VvHC/Y8nmUdJgErVeTt4lbCgG2lqpigMQptrxJLcRFTazkm6L5Zt1PAFIrLv//yh7V7Ax6KnNT1vIaC2MefUEGYIRF8EkSZba8Sa1Qy+611W2721l+gUAtBn1nPSsW3mUjCice2utGUqXLZw7lPgSeNOLKnuc7bf1tLZM9t7Hn1Xiz1sPr4LozN4yfg8+GaW11fEyoDiYAhZyy1onIbybnU9iIDI4kxBEM81M1YT2gt4G6a8eHdFeYCXO13kv98GHA17nA73aNyxS7vcM+z7G+28P9qzFmreLyHZ7/+9AFfPn7Gwffg6ghj9MRlAKOLtqKMNaaFnUamGCnmaKzlfvftE47cC1zgLcBFgX6BvwWsD/smqG5MYIfI9WTvLKm2TvhVeU5sBAaoE7Cdeb7/DOAjgH/ptROtZ3z7I7EVTk+/4NTbOrTPB37CgJ0/sg/wFW8CXjjkZ5X/NoDCX1rd+z4Q5EiNKMX26tpCOWshz7o3fU9PeKA/B0kQXrDPXgZvZz0ZvKxF374/fOLvjwJvb8YfAg7/iwCcVC4fBDCq4GxCYvM+bZ4LTovkvK7iSbAL7TJBC7EYARz+9y/sfvsJOSVwLaCs4WlNvqKK/zYDd11HH6Jh1h6yT4WXin1fvGpWBeTzReXy+Qu32UuUBSkJHZQpISdCTtfifUzA7sOA8qmioKByFaEpEYb3I1Ii5CEjQfKf42DrEECCKs6p5cezfH9EyOOAnBLyMCBlVboPGWUyb0tVPkStr7bYzylT7JghR3fAUUt7HqApKBOWpYCXBeO4w2F3wH4S7/JhHCEh1jOyhdrmKvndTWFai4S+r0WEW0NCKnCBLVs9Se8xxNAAAMYRqBXMkocQAFJuoeTX86ki1MAjGM8RCQDFAyYoDMrPDnwf9ko2L0cV1KY8Y1T/bYo9LgU1iGHJQ7UDiZOPs4SFH1C5osymgCUQm590BauCklkUdYmKiFuTjaNRIeReNoYnmasYfDQEhLXhxBrW3V0/2xKuPkW8ypWxoCAjdfMSK4hKb1Nu2tyaRzKKePPbXJkCmNXrniD5xGstotR2CwMZo1qrG1fIlhR+1XOj25jVJuo3pW7SHNw1eMy7UFyZ0hr64CJzpo5fJWI1QpHzIuXkBmEWqp5ZDUkyI6eEYTeCCrDMiw+ZjaIpuIkSknu8yRspZx07VUcwI3FW1pycRRfjguSG76yCXVlvshZFWUwoZZHUBNqALkrdyvjAQuLPUxHaWfFELdZPmddxGECJsCxF5qhapASNuMB2lrEbKvjS1gVEAEpl5BwUFKZk9zlo+5aIMatXfQlzugZeDXgi8rMBpOk4UgIoQRzT5X6HRMJyX1BcwSIGRTrv8VX23jYaRsc6UWpMjw0M9fhLyqqr6q3MTQ5m86x86PzU40x+r0LdbZ3yx7jC7jzhlF4VYjPv8ig1FOgjKRKa/+lbhweEYq9S97eq9ynlfst2PAWO52JaEaSTChyuVHl1l8QTeNDXLLGGKUrbOQ2QeoIv1BSuaxh5O6XDqTPaaSHqDQMPoSuWuz1+Z571A8SomQj4RMCNkzPSuiX0iQFQYKsYDMnEwm7uWSC806ItWQJ5FnmiBcD+t5/Bv3/s+hcV/ZlbEB778tP/+0PLaV71DFbDbDGMStxC0QNiyGeBmkyJbifmvxODEvBBiArHcWruBAZhgOTajqs0MzdsS5Kjfq/nOAG4qcDn0IY+YUWMAyQ9cbyKh8HlUtwNiz/zHOOr930sjL7qRtpgi+o7f2fGd015fl0ZdwS8Y8LtGejYDMxc6uZGClL+UisyEXbjgFQr5kX4DoteMATrDctfX4RQwH2dcH21x/3dPXLO2A0ZVUO311pxfbXHYZqFn6OECuCwzLi52uPLQWMYJEKpmvqHxWCi5AGHecIdgGtm3Pz8Hoe/xO3O2UAy2q3xNtJPxxD9GAZ9CDMDuY2D6VrMiMR1L/YGAYjK9dXacyNWO0Lj6xF+hOPzAn9ruCjQL/D3gTWCtZPAKEXqX+5uPRMZx8PmXOU5AMxdS6T6c/Oe26+3QNKfBy9RgAcBwLNqtqllPbubMOMCF/ja8JDgN75zmuF8mE4kGJMhe0J+9QKoLeH+OeDeM+7tc9kjbwe25oIfeCZwag387ef4xHnx3H73pd2CcQMJk0dgfgfmz9CCT9Yfw8nGvGJPgdjqA4SAtyxnFuW2MsAVEsaZxNsxD8mOQNQ/iuMawTfXMCU6r8q8wBsCSkgpg1SAYvnIEyUJlfweKJ+LL5KtgIcMllzLgyiMxBN9EE/0nEB7ExKJICMPA4ZRlOemGJMzYoMSXctC2gu61JtBiYUg9z1gz5n7baG5ype6YJp2GA8j5mnyXOemvMopiYCqZhkjU9gDEpJ9KSrQU8Wg7j9WlxHzkrV2IiUky7W83qumGHpgC5sAiGKuPxsp1pFw5bkNwNME9aKQS660k+KkLmagckKqvHpfpLSiEGUxFqhARVUvNeqcbMEAVfGJpZzUe58k3zrL+JSVUCz2wsaZVIlu3t+iLNV86PfRCx3+r7zZ+2I9SWC6hetZvNABFfKW6qHNbfh8HLWmlFpCJga3LGGIPF+swy5NyCr/jMOIZVlceWw1VJgQXwquAKDeSp4KwQSVWo8ZJsieqUFRLhEqTAG7jlTUeCFyzQGzrRkrW8sBNPSrfGdpBpZlFmOM+VjJ26rqaVPrLKmy1/TDzOp9lTfUMmHrtG3W5sXPMMvZvpqGtkHbuUsAylL0LJSXay2Q/Vz1E1HMSyh4+D3b81JNq6jLuR73s41BWEvWg9B6lFK6xDqn+ICHwL3OCR6RJAecTclyjVMb29CPQgWAGlwwoSrdQLXlQDYDA9YI+czi4Ra1Jp2sfBUu0IT1Xee+ohD8qUWdOq6eW/dD8xW2G8yc8iL/PweeuhOeAutFuHW95ugfevc1rx+G2NKJWMO5N1MmhijVCzWFbVGFl3hBb0vICPCw72e1ZIULEmnqGkWkeyZDlbAoF7Fe88jeVeBmK70Nek/t+Ey+ZyQwiJoS/YAWaYxZ7g2r7wDg/vePILTQ1x1dQy3aTiW00PLo/2okeeRff0L546Pu/UBNRLo4UEA2B1snXwWQwaI0J8JM5HRenJPE8YwEDkS4YgkdzmDcMOE2tTNtXRN3d06vR15dH4/kaXja7u7Lfg7+3KrvnQ7SDQNfXoCUfc2pHC1byPbSeDKbU4syAACL1j/mjFJ6Q8vCLKH7c8Jfn79gHAeMaQAzcDUOWErx9ETWhiEnPccl5zrX4tEK5k9fMP70Hu+Z8Nni7ge6+7TZXoP1GG6NqZ1wFtXACAMfXo9QZVG1+udHWDdshW91GlzgAk+FiwL9Aq8LaiFtp/aRAIJ7ws0dFVgPerZQpIpPnaKx5+xW4gCcqWQEYQIrWtcDxCzRO+Z8JWDfDokb4IgI2XwMguQs/wjgPURQzWjKc/t+fZDxA1f23Tc7WJg9pFzsXxOOBEIrjpMJqnRszXrdGelApJuwhYIlvR3ra1L+eIy3R73dPWbkYUJU83A4SZSdx+q21r7QRe/Nw/kM3OPrcZspdOvnIBTcYtnWXgXfyXm6A2EC2399kx4ekUY8rn81P3MLs2rCMGOOOj71JUyA7Qtv8bclV9/AlK3g67bo5Jo8cik8h3V5CLZPiCO21iScHN8I35L9s1pIdtiuhMHPE1t+O2jkRGsjoZ3n3SjRGoPY7V6UQN3vdwBuAdyi1nadUvY6K7fwu3F0PY8wAF55B57syUYDRyYsKKggTOH1BWGafp+w+21AUk/GqjmfJXQwI+EaFqJX/r1Gwd2jdARbJOO/+TFH3M97e9CHev2GLQDQ72O228woqEBh7FJGek+4/3jvHqwgUYRK+D4NiMxAGgi4BSjL8wqANHz7MAygQbzLc87ukUog1HkBgVzpLV6p1jBCymQOir4Ame0Ul1NwmQuIigpL1bNUFdim9Il5oy20cmXJM50xoJaKu9tb8YanhHEccX197TwD1yoCpVI0TGdFLUVCKWrTlnkGIEorIOS8HrK8oQtccg+zKg1lV1T1RCdIiHvZ8uT9aB7ostdT1v1fWPtt6JVAg4RcdzWj0r323OjUkUjD5uvt2nBL9vuENKqPk/FPtaKWKrkZA5kevajtdLczodaqHvfcpNJVDC4YYoRAy4KlLKrYpeZRHQ2HeMODzYeWG+0NMWaotbrAT2atebD7utd+Gc4UHApd27rK9HrLOMqiCixVcr0nzxHavENTknQAA2VMmpN8GEcQpI0pJSyl+JjbuCU13rD1T+al5LyrlF/Kgqvra52vjOnugLu7L7C0GtJOUn5LEe3C2rbgWqfrwEandt3Va1eGk38juzl3gkjjj5d5ARGQ0yhzZ/2EiVVln5RasN9f4/72FgD3e1/3k88xar92CahVTLNyTpqXXR66ktn6ksQwgNRoCIpHWA7d1i8d4Bgu3zusuNJGCswoi0SUgCqWPYd7VU9+ZgzDgDyMKIuESbV+t73ZIi94Cpcj/tEU12aQIspsUda3NyXfuuAupOaZ6NTK6qhp9Ah1ZFxZClIiXyfRLonQ1oONXSLrA+lcDB1/LnuyoJTqOVhrLSggVKqC03RWPMKEt5ckLD9TUBwngIum1utxA8f2oc3teawMb+73UzRMo4cZLgsArJEednb9/UmayOaLG/3ecGqYR+PfQkGuXHgGyJm54i4jsnng3vOgnRmvD4EqZUYcWfvF8VV0yymA8uNsJ4yV6Yv00esmK3xshXyLawY4acQSXVPetv7asDczYc9Gp+i9VhoYjInEs3xg8RrNLKHdgea5LtSgnWkWShzuTU1YzYNC9XGM66e9dUgBRxkKIWCO86trmCA50Qk+k0cjZe0yte6SLSS64uGidIRjUXYTPUJTalqZpsD3dUXab6VPTcYTebkYW6JYfvc/NRR80phXivdd7swt/7vgT8GRv1Zg4erj2E5l1lGo2LPwgZwkbDaFNyoAToR3zOrlLs/vqWJk1nPJ8DiHL+P4tjmz6CoBW4e3+jlJgKTHUZouBe/r7vgO39h9C0l+Gu/Gk3YbYnS4rbUJhDDuq0IYwHuQK9T72loqvLVewAwXbw8TdmPGOGQMKeH2MKFCgqsTAVdMHj1hhMxRZcZ+HDGOwutwZUzLjMM040Zzq99PC+ZUcHO1BzPjbpox393jer/DYZkBJFG6J0JJSRXyhJwyMgGHZQF//AQQ4Zf3CXefKu6op6uRmulG3L2ybsN4hE1LwTDV7/qA88Z8EaDGlMHq8mmny/c4ii6wCWas/lRq5kd34Lko0C/wqkAkYjmYMJngB7cfl7anuDG+fl0bw9TymutjdQ1ovKIyYso0Urhnb8TQNC8RjJ6LBt5DiKD3+s3nM755B1GwWx0fAPz1zPqfA0EEsRqnxgAeERTUDkoT+JXIzFmuRivJLOVhgkQ9XFk9PlZtOlKenmq8Wk8cMV1maIGtsi/w7SEetz2Tdew511vsr6MIvI5C4zwQsWENV1vv9NATqj1+ijjL94YZmBBwhNPoZev3WyvM//4QWMsoxVzdi3P0sCL1ieAFrwRpD1wdLxjdbev7pM/egqXKE+DU6BLQPGEV1nphE2okAAnv9OoGzF/gHmb2LqmQSZWTXTmBSQTEsvxB2BjiHcOFNdmE0/qqKdKt1IIvqPUnUKqujDS7xcrcQs5C8cqbwqJvF5oA9XtULvWqOguFF5SSUD6SCNgo0mFN+FfVw5NSAidTHsnikfznI/JuFMV5HkDDgJwTkmhBUF0Io7nWnY5jgCSEr0SYbLQ5kQUK7Q0nJVx6vyatzUk9L0z4xkoPDjljGEbMy4L7wwHD3R2GnPFh/gAuFWVgJEhu81IKllLEq1PznddaJJ85NWGstIXB5mQuSb1F1OfvsO8V8TxmgFvo+qTCUDu/a7Ep0vzRKXu9LjCkhJQ1b33OogghkvGIikRI33OSefN5VeU0JfL3iYA8jLAw+gwGKmNZFmBhCd1PKpRl9m+cjqoMJm5KxMrieSrIArUWD5ntdDOH/KMmPDNBd0oSGr+j08RgWXSUUh+4rRli9jWkI+U4kJDBWBzXueDZ+ooVulwpOATPUwsbbq1iiJIWSXkNGYtSaliToiBOOWuf4DymeFOr4YcRqGQsh4rylcclSDllKdhd71HmIpEd7iU8p/NXZny1Oh5MPM2AK+ZrCAd/DlRtVcP78DqNT5L2mqFMM3QwLf1ud6WxbissTDaBgx7HvrddrGekHlZJfRuJEipZGHd9yw4ov0kaSrzRu2ZnYYYGq0jd8BViY+5YqI1XStn7ZeMtxjFVDM50v6ecsZTFywBMjqDPqW1sitL/2JpwzxQCkWaQfRFmsA1buw5nta99cwsnnT+uqDUJ3jUlCtFWk4SW0TQXYuCQ3Piqqhe+GA0QciqohVALaTQCRikJTEX3a89bG/7zveD9IhAnn95Ubb2dd5Zuy2eO1/15O4Fbe+3Oc6S/WtZTqPe1bva5sE5r12RpG+37W7B0EacHOQ76OW8GEevvDb9WOcNX5TSaJlzHNCNHBjrrQX2t6xraqovW2sbhmgkzASOL4vLYr1x2U2LCPu4F25/KXwzctuh63a7HPp21h4wWCGe5P9vgOQFHMlEhJ98duyjICDUFf3NjsLNK6QFCZ3gW+b5IZzDUw5yo0dMkOcelrtArtogt0jagKeY5Fh5/EkLrjtA+xt/eA398xgRoWhbto4ezkLRhI8mYdPnVEZYKSNGyvHANMcS4QsLBeup5scnbHxu+jUbWsyjXB5I86FZE8oZsLxCXzxudzP3Zua4znjkI30VgBp6L/CgRbjseGeHXsYsLwrXQN4TDUsBZPMtzJqBIqP2+5QArXQ0zNmTCbtwJ/a6GjCklUBXnwaVGg1Hoc3Ivc8DodJboWrUKL8IAp4yKinc/fcD9x7+wR5fALdA3q3XbWttGg/wfXf9mWKBr7QFcEHmYpLwPCBod7GjQW9Xx9rPO6wt8bejokKd+C/zQSvSLAv0CrwbCSGMT8XHjxOxG/1cueiHd+nurZ8VIdIecC/j0sAvh9Kx8ex6rd5lMpHBWfev6s7oXD+Lb48+77yLcIB5k8u9aef7WYG1daGNhJKx4/qcj3tkV6FCCtgrBaL4iZ9e/+t2voK8Lrb1/c5e8wIBc4DWAuhHvhW4/Hrz9tr+kheHseXlDnlH3j0CAvv0VALTQ5ZEwZpig5NbvJbwDIYFxC944n6IApiv/iH7oCJWTcBU08lmFWtFb4op74axhjWikWCuj/F7AK+ok/ZKAP0k9BR6bqR9jHo9g1ex8SpDzjbbSc0dtvVxs5ioDAyVMmCGqbvNsMclFnwNx+jhjSQXjKCHZc87Y7Xa4urrC1fUeu90O47jDkLMLUZCUtkkZ4zBit9tjHEcM4yiKaaXZl1IAZpTajCKTKn094oIKVaRM89hmUBalinvtqgCm5QmWnH4oM+ayYJkXzNOMeZowHQ64nyZUVNRlxGGacHd/j/v7O9zefPa62wAAIABJREFU3eH+/g6HaUJdCpZJsl5aDvNhHAAiLIdJFWEq8Jzlvawe6abYI21bU5BrH6qEAGf1XpVn2fMS5zTId6Ys11D58pdk7pIq1N2YR3cvqSIeKnA2oaLND4mgL4Gap6/+LfOCQQV3houawqyBGAkUlGJYTsWnzOqNXkSZVop6pVbFh6xCMtJIjMaTaW1EQPTKVGEmoeGpc5RWW0I88pZGMIMMbvXJDamCeyVom3Mdr6WARjFkmJZFjRpIlenQdAFmGKGe96w5zINRguF8LrWNg45L5YrD4R6lLiBKGg1BW58s3UBD4CaItXlqsuyO8z09dickmG7YEIWcoXzvT0oSBjbw28yM6f4+CDrDvKdWQ6aMNCawRkCwVxliqGLGDEnXD/v+T16m7K3U8scz1GhF1SZm9OAyAcU0plxk9vUu3u7kw2Uh2k1ZHOewlAXLPKv3eZDmUhs7S6Nke9MmvxmL9NNzpGYNghCJVpEBYrCK2D0D+ZpHtl76j6PiEJ0IrHw2YxtQWFOQSBVmTBBaKfY2Cei8GiXjLkFDzpuCgh9ahbHxKppnSPQNJhjaXNm8OKx596eeo01ushbgrJoG6vrxWD3shEKUzPQlbkkeGLLe02pd/DjmiycEYK9W97eod13mU65f8u23uAZsjnYs3uUzAde1j4ZlXxJaSPa49hmBlwgfJf1/Adwbm9F4klHfndPpdRJn8dzVdNtQNxjADXoj5bizjT4ARIEdQ6FLKiK4bNH4gBh63eSPBcIHJgDDrx8w/fkZYN27yXK3ax52VbCTnheVxLP4VhOcv9PAIx5xxM8PwwFKG6V23lcGpj8kV7XkWyePCBChomrkEhIlOzRvPAgzIFFDwsAkmLew1L5jYNLvRUfPnm7HBtVtNLCFq6g3JNDfLVe7rI3ywCSv18PaSSa+yd2boX3UX9sheBbGeADxX3HL3X4cyn6rdez08aKpeK52O5RScT8JzbfQKmFRFcebkgryOILB2O1GoQsLu4GB0VGlVIzD4OljEiXsxxF3hwmgZiw4XO0BAPXLLcb9DkupKMOAUj5j9yEhp/f48PEvfNbu2PqPveuwrrfj1Dn6AJaONzWEu5PhPr4br54q7wIX+M5wUaBf4FWgoduHuK3Vgw0leswD53c7bKuM8xZ+DyaH57ErZ3B1T4RP+vcG5+U8N0IOYPwECf3+K4A/nt+EZ8GxpR1cuOj3Oov3SM2oMAgm1KHNCRAabuULx1quCyee0ub+7+UQvsC3hjXx+ZTvjn81Evtorz2zngt8bViz8cDDM/McMeBDZUVB60swXGTnYvlbXkznihnfPpyyfrW7xlAy2kzLOXULEynHb9b/x7K6308YuoH7PHsLNUW8CayOok7qv7SKtd77bFjPGOkXQvrTwtO/Hpzjze1euT/+cnshyFyZAKlwVe9oUwAEDwAAsGDYDJQqntlIhLwbkIeMq6s99tfXuL66xs3P19jtRwzj0Cl/zHN5yIMo3wf5f1kWlFJgaXBK1VC/nSFr8zJP5nIUFIIggidDtvsihQTBFLMAKiDOGAvmUjDPM+Z5xuEw4XC4B9cRJRfcTxPu7+9xd7jH/d0dbu9ucX93h2laXKBUISGgJRyptF2EUrov4j7ScXAvZBuYuKeYJcS5KvG83epZkbOExE85i6J8GMTrf8jIqSnV82CKcp1Pd0tlmPK3RZ6JCv0Wxl2aJn9LEs/mvLTw4lHRJ2MtynPRRkvcnFQZnr9AvbEl7YMqz9UQx0PWS2PVw5jdqEJkteSe5mS4ktDCJOtY0zWBb2Me9F6Uf1KYdybYMHZ8JNpyNFy9lIIBpN65gBsurHCUGU7EddApolmUtdXC7YN9SFNKyCljXmYspSBTQlIlcQv7fNzD6H33XHC+6sxBZIsSpnuV1Bhkmg7HY6L/EGmo+IGO7kuZgQ/UtXMsE6BuPP07Cjk1nblTw4VicwIwEzKlMD+MlBM4J5R59rpSyijLgso1lCl41HEbeTUatlfVzIrPjGpK0vGW3173qV3bQDQemLvvZTjC/IftH9/bgni3M7RgdF5evpbVsEm7KlEy/OxoBaZESJxRUEAkuAqaEWIBBG/UEtodPvf5buMHUDflbnzANgaPH/DPojytDqORv4IgwDwNT7fsVCXSECb+BsZ6WxQnnoc0/ynw2EJaP38u42374ZmfP6UOg60pb8azvPneOt83Y6scS87TnvepJ+TvyMBMa5/39tbTl+R2m9f3Wi1GL5P321pTVYFpKN6CftTV36Q0cPnjE3a/fkD54y/9TtKKJEgIeA51UijDIIa5X7c5Lqk1RlkgczKiebNbqi7WZ0oio+p75ilftDVZ8a4bsxpODuO1Y8IBjQaz4AsxMHMXBafje9s79uY1t37Z+wTxSj+EdRrTdWzBNn++PnHUEC+8ukVLPQUNRuPOe3rw1Y3W9bAU4dOGnJHToizPcUuq0o61Vok8BaEXSy2oLArz+0UO4HmRiEy7YcAh0DBDzlhKkXRDVdN3qSH03eGA3bgDM+P2Dnh/8w6VKwb0RgLWulPdPjWGBOGpErUMUEfPw/9QVqObmNXa3GrLo6TwN0OwF7hADxcF+gW+HxiHqIi0F5vEd9bv8+qegR7rG4wYAU0gh0ZWOXO6ZvTMm2SzzScvu/rWYOLpD9g+YNbvJsgGZQD/CnX9gUiYvD5vdO751BGyziT3fx8rkKD5Ci0iopXo0gVsCpceY2PbW08bvTX/tFL3f3f4+m15S73750Dvf/524a2373F4CFM8t3ePnQoPsf/PgK8yCb34gY44G7u//ubHXwFbsKCdvUDfU9uZp/LwdYlB/JVeUHDKGGxrNBdaPQyfzv1hhIHVEZCB8ueC/J879aRsCppe+CHiluXPBcsrK8/XsCVA30qDcF5h27dPeZ6/OqznlNYPtiHuSqYJFUDGNRbMABEyDZ3gav686HeqsByAvB9w9e4d3n94j1/+61/48P4DaAYyDxDaF6r4rKiqrK1VwqG7wC/Sb+s2soaNTwAotfJAIJaQzElzfrtiTCWxpK7JVdzShUrXh8siStxSFs0NOOHu7g7LsiDnAdPhXhTo9wfc3t7i7u4Oh8PBBVMgy7lOmG/vXXlqqRcqGHknY1CXIg1Sj/W6iDLRcjwv86xKOmr5qAmgNCCnJMKyYcDVfo9xv1MFFiGPA1LOGLJ4ouckinUCJD8mMVCh3j+NBrAt74owZ1x01SRJDir6TlHOSJ73nXiRU6OTWUOG2z0L3V6WIoYGVcK0LyxGF7UWcFFlOldImHtVpKNq7ui2eo3P8nUKuCI2hm9fU99roWj8viurW23nUfr2phkYRCUeCBiG7It3yE0kXkqLqiBdqG0cNZw/A86PMLOH0rT0IEwJtS7IKYEdF8NTA1iqAC2hx8/cmW3pvXP6Sqvr1CuxO1zbguGWUpAgBjGmXTCv8HG3w3yYMGiOTDtN+hQ0TUTKzB7ZYBwG7Z+tTxtE9emKVjvMgO2twPMzAJQqHryUAUbLwW5fV8UV6r2e1ADI1l+tVaMDKE6smoIiVYmOXGszHKA2jpTaajXlv0SZyOpVqJ7a+owADOOoUQYYtayTuthwSZoMWwPHnuqNbuhkG4Yv46sm9Q+8MSDGBGSRP9TBgJl9HEpdgge+GuWkJkvJNICTSiwGgDROcFW+vJaKozRENl8B79jYsXbDDGnUpumrgldpCrygrSZqHvqPYY9WTn/jmH7bFPGfLFXObyCtFD2tlIdH5KjdBN+v/YAjIND1Pn0JnI93vy709a5b4efPyc9bdIpvRQp2Ic/T8Qj1HNW3AeMLrovgYskDbiGkGRtB7B2a0057HqNdMSRE+gyooVlTFlu9Yxje/pw/XjcPjQOvftnpcq/pP0YQJn22YxLPXgYmqhhAnks9RhkCybuyJeR965/kf29tXkjmMydCBlCzvDn8BPDHMA7WD6UvLELOHgAToWoFpJYGdzpiV3r+JUqKtoMhp3a7okVGs5zZs47arH2SPrDzN5O2ISMq1NfnRaPlFzwCehY63utQDKmX/zF9lhi4TcC7qvJsRf6HNb4zctc3h9CISWeiPz2PZa5bafC2fNXXq+9oLz6Czvxx9G5nKF8Q2lNkp6UsXuKlFCRKuNrtsCwFs/EXR/2AplQCpnnBMEj0r8PhgKv9DmOW9DNcGYdlwc3VFXbjgM/397je7bAbsqatqkrPLUABxiEjl4paFlDOqEyYbu9w8/MHjL/9/+y96WLkOK4u+IGUws6lspY+5877P97c6c49nY6QSMwPLAQphR12OpeqNrqzHJIoiiuIHX/g9O93fkyMRg67YHuk9njU0vhgGA8wK1+gk8y6mhjolD/P8Ax/I3hWoD/DDwfn73Y8zO3+KFzxYgyPDBh5A7mWU7hjNO3ZneFc9r621+hvA1OeW5tfQYiaPbG13fsTwAzGv88051c4d8Z8XMBAFOv52AR/zcNgVBQagd7qUWFrJzBkX0NGdMqfJmhx9oCFgPX6o4fU/T27qNQzPEMDM6mImOmxNbUa/d7OXnuG7wWPwa5770Tstjd33/6dp1sRTbg+Kss3ykw/yP++6/EuZcSCpkTveHuo8H2vPv/baBjeef69QULm3YB5bvdYz9M/swvUy7uK+u4HNUrhTkX5mXvUzcB/H8R1ZLSUXRcUDePuonlYtmMJDAiAxGMhTYzD1QEvXl7j5etXePXqFa5fvkC9LchJwghL6GKh0zKL0nkpK8qyopa1eRkTg9m8CIMnd6f00d1jCnF17WFA6cDkQjyTGJqHBhdo+0VZW7mAS8VaKtZlwel0xO3trSjQU8ZpOeH29iu+fr3F19tbHI9HnJaT0pDqjVqb4phUOOpKVdCGJfF2mdwHgMUdroiKQFmvKRGmSXK2T/OMq+trvHjxwvdbPsxIRMjT5PnNc7L8501o6uPIJmSCC+ratiAdWsVIOgfMDCo20E34yKoYLyBR+qmgrbIoz0utqEU80isXrOuKZV1EqVi5hXGvVTzXEf3ZpJ1+JEBlZRY7VEM29ufFdj/72ROFtQBM/I87395Ch7cphNy2Ocuk8xomvPY1955N8H43PhaSQ57FkCB6S4NNyEgtzD7g3tJmfOBc0Hc7ShlRiW7t8Pacuceu1BV8UmrxsnFcK/fG5kRADTFb3Zub2zsYytv3wmjE/7gRjI2x3wuNlz0sc8GlgimBWHBMrUXWd+hpo3U0coTiGkmNkODJdG3dmhGOGgBJCPqshg6irGaIwnxdlqZQj2dZoKO8S8whPULDjxGLtnmT+1a3pVCQiA4BHwGeiiCn7HNWmQUPaiSFWosYEiQCpwRKjITs6TYoAcwSIaP49wmJKqgCK6/QSMWIKfagLa9hqrvZJRKFkuOG+xb/U57/5+nWb9uCl7ZR1692//5WXVCfroOugoiQH4I4f1UI+GBzG/eNX1iXVs8T49uovL9TkY+Hz/U4bZe8W4iRQBo+uynOS1C8GhiqW9GnSPFjHC33N6A6srERer0QcNjwh+Mp0+5uluymBDt95JF+ACxo586JKmaQp1dYtObua6HNdoZHxW3667Uoxd99RkNNUk99XyV8PQFEr0B/MG4/fOmig4UTr/t90q9dDT27JXYlujWvGzG9IaHomzJ8gvCnxC1cvHmax67G35lDjnRuhgJUZS6v9NvHYcDa7JlxH2++09NrLQA7QJoLXfGdGzBuz3+7z5vxixRK3zZXCpyB70ZOhfrv3+eMlRmpFsxK969UlG7fli21eqqBacoAE674gFpZ3lXlPAFY1xWHw4wXhwO+nk548+olXoDw9XjsRqUSATlJWpxaQZQkDUOVNDev//oD/PY9vpDMv6/BO5AUxx/U1gWhD99//m1NGTDQhp2RYATq/pxvzzM8ww+CZwX6M/xYOIOQR3E0j9IY/RlDyjHQQs1E5DoKY1lDmVJt4dpq+2IMa8rjNy+E+w7qN5Dc5TFEEAP4iv7siH8ZwH+GtpwjJb4nbIVZ95fvr8NhzBpe3wWGKlwKZeNoUkqYSLx0TEAyktviSWD5CKt40WhIynN9cUJtmG/qSmLnvoDlPP/VPNCfDrZz+Aw/Btpe2ArdqHve/x3f/++ES/HUP0GahKeTAal+qWNs489z9+/jHr/navzmqnlLKwywQqzmN6uELGwhd02JId8HiubSFnX1fQvocTtULgumvi0AEfKfGSDC+vaLt9mK9c3+fvN4l/K8M+ag8+VHMHrlUo/z75b7fGzrpu3nsPg+GE2TIg2Mk9I1105PtRrF+4jylSp3r8UTVsO73345gWpCYsKCBeVUUMrqNLX6LeLj+w/4+OkDjl9vcTqesKyrex8wk4QpZ0ahpG0QAZCFmC/q7eiKKa1bjCNbhCGLllCreDrLX0LOBC4JnAFTcp1OC25vj5imFSklCet+e8TpeMSynNR7miUPuIZhN4VgVJaDxYsSRB7WHQQRMp0W0FLEM51IlHLMnkvd5HdZQ7LP8wFXhxnzPGM+HPDi1Uu8evXKeZA8JwkFTcmVW80TX+hdsCi2xIOtZVt2eSEAsyIWXX4RT2mNElCr5u2uBUspqGtB5aKGD2KAUGtBWVcUZpR1xbquqKV6KH7UKmH616Ie6ezK9lqbH5vqjF352HFyVa/UK9jGXoaXGzHT7b1eQNvQUAlP4XejqPYu6LcdueCTqxkYkM9nZAl8uAMyZbR17S1RpXtUIDLLHBARDocDQISyLO7JH3vbaj7XkzPSxDvuxrEyI+TeYLkZY1qe61KrpRbXNhLydMD165c4frkBWD209X3zys+5Bf8lAHUR/JJI8FFhWc+m9DVvODc08OSbIUy7PhcNbvXxJYKsUQRbB8Unpcp693DvBAkzrhPrUVio/Wa0CAzRXGCDmm2v5xa6v3p9UqjUIqOsHty1FMUl2teO3yRQEgwu3UlYyyot6BZsME6wPRWqMdxA3L5rbfJ/rdNOGIhBQRWjiCpGU6RGPUji3R/D4AOiQKOUQKzK9koeccHGwzzyLfJHsn2PCIYHSOdcT5o7DBr7t3s4Jxex1BIRZ7i8iNtKO3f6Uv9WXy/gyrr2fdtZbUff1QvBneQKOHvn78PD/Xg+apzreH1uHTijZDjoCdp7kc3HfXXoXxrujdXutXYcgz2Q3NYSteOAhMQqt2IxGIq7m9E8kY2ti7QSoYVqN2X2VxKP1RO1dFLdtxXfGQ2zPdf7v3soV75HzUAQZ0gHwD3OxzEx/sH260kfmqe8RIMA+N1nFAImIiTyJEiKJb46Fjt++Oxe/eA2fmaE4OcugpctAE7iMZ915BmMU+jplQ68KbGvVLlOtQoFpN+6+us38NtPyBDjCJu3CaIkd+9ytJz13lYOIex1oLIOapSZjvvKWik4uzkxtfJy5l4Pk3Ik4IWWYB17r2846sLJGIz3zmOZvec9tm/9ONcf7NzvFtoO+Bc6S9vt81XP/6s8oTJQKkv6JjPCrdzsSiHh3leldQ7zjFrEePW0LDjMM67mSeoEozJw0vDth8OMecr4+PkGf7x5DSLg/ZebztAaAOaU8OK33/Dx4yc3JF6XRXgXajv0mglH4s37GzBP80BXVQDEQcY+jgxrpWY4F8bQ2Qjq5+THnS7P8AyXw7MC/Rl+KAjeHJmO8HBTGg3BGvXg90KGluGwi2KCQDt/e9sf+a7ZvVve85e4Owe65Tu37/4GyZ/+sw6Ssd/NkzwwlWSEJhpBwTvvM/sBi3Bowz1E2uyZh05KEgJTBLDkZT0EYhVBQC0E4oJqIWJim4OgsjfUPs8+/30Y2Wf4VSDa7H7T+zSsUHpej78mdFzkzt+RFRhmUYV53wL0rRrAsUnhUKWxT37537EaV9LQcwoMEb4nbI65ze+fCU0YIgKw+o6R/gx5e+0Hj8Lt7weX5zwffw9r8ReF7y5ODsIG88gkmNCiuqQwCvGsRUJDrQAKKov3wnI8yiuax3sl9TqOHqXM+PD5I26+3GA9nXA6HUXww+K1SJIosoXJDApoogRiRqXqnrlGJ5ryPGcV86nUj2qLNyD5pIX2Sxnilc6i8F6WE47HjHXNqkA/4XiS0O7ruqqySEKPp2kS48odPMuFJZJyaqHkhdUwr2oWr41AUbonMotSKVHCNGfM84T5cCXCrqsDrq+vcXU4OC2bpuzeb67YYrgxAqWkSlhdS6oQM0GWDS+YRNnNFaUySukV4BWMdV2wnBZwZTUmkFDNpYgnbikSon1dS/e+hXDnosp4ZlXU12CkWpuAU88vE6iSCvesvRXtgph8XKMYnK4J6bZ5yzd+zX41D3R4GdKVvc+Z9QL0Rvsj7I3owGxPenYzKMTRXmKQ9qspv5tyltTwA5imyXmataxuhEBez2U48THQ8T66386CDnMjVxhAQj4ckIjw6d07HA7qP0ck8zooj70efd1NE4JAdCvM1qtA8tqcRPxjZcIO1Er7gznnScZV8RNz0SrYy0h8jtTdrxolwLpAsV/U3pOoEeTNGqP1mFe6D4cZLnSS+VAvRIZsgmcAIpQeoiBIcQphUON9fWqIgtB9wsOyQ10FmMUQqEjEiVoruBZIPHZGyopkOIkBREKYDPVqTwDrNyupIQ8YiSsqkxvrGG9u40dtGvyMkbb1ph0+WnfSxf2+38p4rL96Lp0p9S0Qa+vP/ku/I4cN6576NrivgrGlf0fw1Q44LujHnuINh35snMJ45FDcazf80PrQN6XHkd8AoVJmFsWph1Fu3whHXu9Fr/9LGlmjrW7y8pY7+bQ3Ju7pPvbu/p6dK6FiQ6eR7tt/ZO2g7XSbp7z1u49PYqdgW2kLSc7zBS1E+qZ9/v44ssAJjCsmnKi/b3DqkACFt9m93wEgv/2Iw19vsLz9iMNfv6G+/STt+dcbXP3nI06AezjbfjAKFiAxdsU4HjJmZhAx+ptHequnvRpcczNIKhBFvQ+8npdXOg5Af26Oo2F0coRz58FAoYXetN9PAQ/Zk+OJQ5Dc5Wma3QAzJ6AYnRnaudaKtK4gAqaUcXV1wJQzlmXB9Tzjy/EofB+Lx/ppWXE1z1iWguPxhHnKuJ5nrEprVm57+PbjJ70HfP38GS9/e43juw+4/vN3LG/f44ZkzVsodyXv7x7EgHiT0sbEwTXRKnECnP1cZg7YRHmirujw6ac7vZ/hGb4NnhXoz/DjwBnzYCUdDkR5bNSM3WwSDtqhuwKv2O4F5AvmgYHtD/1mjLplxvwHD/fOdW18N8CoLLev7XlJ/w4g4w8A7/C73nt/x7d/NGw8zO/wsqLw14mcMMWWt80s56NXjoTE1DyROUkut0xIlD2EHtTKfS0FqRAKVqx6j0Jutc2h6xQ49UKYTV/7+VT1/WYM/jnwT+3Xj4fHjWQf0yCKC6i7gy1l+Y+Bx5DIP5esdo86/2tCuzBBXV7x7zVxF45DGm+MmFLX2Zlc6A9vD11w99cFE1xEauUA4FwPlgd27KnHgRg44BVyzqCcQCoZypPk9+W/5Iv1HZD+ioKakHM9NsyUJXcpYZ6i3eeUScPtzfK974Vzpe6Toe4SmPd/8bGjdPY9og5rVKVdpu76BOAFMgBWZXrLx1mx1ILjckD+uiDRZ3BlfD0ccZgmFKOj1hUlFbAp+Uhw2+3nGxxvj6poXUXhBKGlM0l4XyY9qUzpm5KsPwJyza4Y1u6oQtNCJkMWX1WvjGoKSXYcJEpA8dAuZcXpeAQAzJPkFV+XFaeThHRnENKUkIrk812OJx+9GJbTlXsFQC2oa/X2gYCUM8CM5VjbO4CEONb2mGJ8ng+4ur7C9fUVpmnGPB8wTROmaQJS8rzvNtFE1BTn5tGunrXST8Awjo0JVGDGtWooR0ZZJdx6McW2eqKv64Lj7UnHtGKtq3rarlqHKs+r5JWvGtLZFJCOFXROAM0hLc1ADaSzCLOHXJVsXue6UvQ9k3ybt/ZdQsmzQvTu2XbXJPWcnSyHfW0REIyasj0CbjkspVxThlsbXOHC0He1jOavjqFHLBT31fU11mVxowWu6pVr0suuD5fSL/sYYnM3wTkVW3cMNKONAay/SQ0N8uFa8qfWFcfbI5iB4/EYvJmBFJQipRQQ5HypqK7HjS10mjV8T26JRx6ThJl3TtENDLTdNvxsPGRj9LmICDqz4IKKAirU2DuVyhJZ/nZRJ4jBSm34yNsE98SX/upej7S5dogiLwl4OPso6ejWKkFzrZuHl/2vaiqAvYkdvss9FWn41ozaExTXUHKe1fYes8QfqRbhQ6NqVBTpMycUSuBEqEmU75RYDaIa92vzkiijJquXkGrViAMJVSMwlMpIqmRnE56bgidIyqN83Z5d4pW+3Ue2APff9XV1T9X+mDcL2u9Td9mn7hkVvXtgK2QM5/54GCuJ1N3fheL+juBWaMCj+cbvMIznZu3Sd3tMs6VGT2Q4c1vzld5KLHh2tTDoWs3MFSXFPdB/50rx0a4S/Q4Yz/4R9fHQlYbvFI+qiu4+FNHw+naUY5tNAbxAc6OzoamKQs2MT/KQt3G3f6MC3sA8y09UOyX5ueEy6sA80Q+kYdz1bFkB1LcfpK1vP+IA4PB//sTX//sWCaSKfc2vDuCagQISw1nIEkikvwExlNJ3tnM4zpJct2ItNQAgKQNkXtrYMsQzPjuOJz9zxy9ZecPR/hVu9Mm4yltMnNba+7DdRftr+NBZOlV5m62RoiiIzdiQWZTo14cZYGBZFqWF5SPW51IZCwpyzlhrwWGelE+SPOrLKqm0DvOML7e3qCyr4rdX15LuqrLwRVxxuyzOnzErf8+MRIQFwM2nG7z6n79AOeP3//kTbyrj49v3OJIYlxBaRAQeB95g4NvtyiMyGJ/llsHSmLaSQorAZ3iGvwk8K9Cf4cfDhtrhhmUd23K4biXjUd6RiErbufKc4XVY2Ljx9LuDvxpb96T08gvse5+/ghBo7wH875+EP98Bb5/wu98CG7FLUHLrJcwrPZa3uXDinoNghNXymiCMqNZ/T5VlAAAgAElEQVSXk3ouJUKmjJxTp0hP9pfEW6dyRaKEBdDQ/AzL/WmMfoV5oFAvfNlRov9zlePP8N1gD7c8AoSZGYjRM0LP9t3x48/r9+fAKAow5LczH53UjR+xYPakrN8ifVMGNHj8bnKe2/1/En68QDgL7IwskQqX+icWxvCSWr8Hw2gChAlQZYSevCOe6GikXhD/s2Df8zz8/l5x1p8AdmXraPNR7yh3KTAGr8/Rg5VnyROOikyT09E+zYWwnBZ8hYQMPi0L5mnGlLPXu64reFIPZG6CtXJawOqtKEqY6h0iAClBPcX1dkrIWRToiRJoFvpLPB5F5FY1/y6IQJb3nAGwhrhW2oyhZyKLiKkyS5jmJAE7y7oiTaJAX5YT1rW4EqtyFQ9z107szIBJGXmIWcQAJ27j3sjbpoBJhDRlTPOE+eqAw+EKV9fXmKZJxnaekadJpJV6jqeU/H0O1r4y5tTaU5VWtpREHqK9oKwafpkrVlWgm4czqwJrXVYcv946jVzWgsIS4trynVt9XMQ7vzKDVFnemfKpJ6kJu0wRFo8u1qTnzCYYbUoh8UgnwD1i4HjHhOR0TaBbF4nb8gr8XgZ7sNLLwPmPEMKctT8jSrR2j3mcm6vb8E4w7raGWmj2w3xAIuFbbJyNM4k8x1Oc3Lv91sWaKLUo3GOJeLzb9sgZU5rFs6msqGvdtK3NN3vEBIewxYL/ka+aPdqhv7MdCeffB+1qfE8UtaKwzWly42sT5LubNwwnJ1+jiZLG7w0RJ0LZbq6o0eMmFN4zTuAwGL2Hvj4Jt+IyAloOX6+B2ijafoikRxeqnZpRTxe+3fajpmeQ3OdmEKP3oKF9WTLtcgKQSNcxhCfPloKCYGsoUYL5pxZLiSDWFyAkTQtAsMQPLtsBwZOstP/0I3jPxrDx2CjGqM3AWH5PoHOvjOfCg9uilIhhnhmwRSy27dC5ffE4GOsfBV8RYf3dIY7r5a94zt1vwLqP+PJ3h701HPFQPKz3VgnQQrTHOB8GEwNrpyBsv3l7a3gwtm7/jN8HpUfIj2GlOxuOiCK8bz1T445JgEeaTuHeutMjgxOxGyRImTCa3yIYCt8sJDRU0vbM//MHmBmLrW854QS7Ki6a//oN5e0nPfeSr4fm+7xv6GMnIW+ue0MxhmFzkbwWfWqy4f7Msr/9gHR4cKC34fSE0cvx1Nyupt4VZdunft3Fmu+H3TV79mVZoNbcwsCyFhwm5dKVvFEWSPkuMZpdS8GcJzAk1Pr1C4kCNOeM47KilIIXV9e4PUlarSkL32XsWVJjOuMjmCw6mYxNYWAi4QWoFKGTE+G3v/7A4e17vANwhQvOx80waGQ0lblXhCMfY4WsfI/RWAOSGjb0KDbZzMM/6Yh7hl8anhXoz/BT4PyRfTfZY8pWv8YOQlWkLTxUtGDmLjRah887yUjfnD08/BAc/RvaAXkubLsQH+Zpzji+e+sh3H85eKDg3wjPFkCoEW3qV4Sc1Ns8m8I8q+dERk4ESlkFsgk5TUhZw9Ixo1YCJQZTAlOSHEAmOKN7VtRGiT4SUuTtlL58b/XR42p/phV+DfjWebBwn/8M+NVEDMBT75RfZ6YuFBvc77ortZ1Zg4O/DS4fgV1R5tnW/ohxva/1j1m9l3qeGwP/PcAEQPlf4m0OhuSo/dfQo0RIfxHq2z4OzsTYqKn2lTBPB7besocd1L8msHuiwfpeOvhG1wzfQ59j+ZJ67isd1w6Ha/K8iicwq7egprIRySijpILj8YhaKk7LEVOeNPR6M2TkqSrNLHQVAUhVlNDR29IU4lwZOTMyAcwSkj2p8m7KGdM0S+QDFg/3ZVmxLFVyQZfikk/xNrRRtDDgDNSKouNoIYG5QjyoS8GkNOO6VpS6oCxFPCDRKDempPpzVVcwNAyxrrXoGYF2WRYJe45JPDldkKk8RibJ/z7NMw6HAw5XVziY5/k8IavHKyqLEgok+c1FAiye5kajVgmZzEnzjiYGinxrPS2af7wpzEsIwy6/FzDE22U9LVhPJxxPR5QiSsTCGrKZdexrca9zy1esAda9j45MXCBcmxdJ5I10rmKeUrnWZ0SgWj3vOPT5XceWKaPGtb9bXB+kZJ78YU1BQna7cM7WlfN8wkPY+7LGWqeZm3DelKyRc7W9wmqAcJgPSFP28auVUWrpGs7elr0YZJfDFk9Q89g2jQMafm3/Va0AAfOrF7BFSEw4ff4CieTfQrB7rnIdtqR11yJqUfG80m+raJ25fddE2rtUQGd0rW2rEh0gRUMh1vkhiR5gXtxg8nkHAaWsIEo4vLxCOUnOeVhZRMG7eLw3I3BJI0FhLs1L2cZS6HNVTkPx36bekYtsCnmXM7BGSUgAcUHKCahAHdIUoHtPwH30qZVJkAgXUGNzS3kmX9M9WdWQRg2UuBYJ3a4LnMKHmAqYCVRJvctF0E/aAE+/RuTR4MSgAiiU1WCJmmciA5xkn8WoFBSVItRkNZd5npsygLeyBSfu2olql4SmzLj3vB0Rzn1kttVvK75ts1hkZyc8hJb+VjDc9pTfu5D/eGIYz4hBPNiVlIfnKLUezkYD+M508LfCuVll3SVgDkYdDY7USnag9xfZnuGt/v1LPc/vH/ndVoiFJlvKhy1dADQc5I4ygBpLEFqIo70vtVbd6qS/YFH6Ve3zbEZSVbzPiYQetdN7PMXdc5wl2kcCa6j7+wbKTsoelmRPBY9da+7sBarQ/7fFKKVmBGF0jsHbT/7TRnBW1mDM1HEi7OCssZWQM0DPy2u2Fkp4+LhVKiT0vaX9uKry/VOKK6pfXeSEsd/wr9uZwXYaOi03vO8nTQ/b1TPQmWO4W28HdZdewq03+pmzcatc5YwmQqaEpRQccsbhIMaKEjWKsdSiaY/kvbUUELPa3xKOt0fkKWM+TKBE+Ho8AaW6nPv2eMLV4YCcEw7zhP98+gwAyEljZjEDajBNup9OIMyfviC9vEZGVrKUcfjzd7x59wFHSAQDRsAT44LYud+NzeAE1OjvNmxcCcj9VP/Y0+QZnuFh8KxAf4YfDh2jA7iQxR7eGfCKqDvs+uMqhLmsO7XEw/gHYmb73I1e3+yU+Q19mPYP+PscHmZh2N/Ug5D7o7AJckgZf5Lw7Ckh5Ql5yphUWU7qiZ4JIFWopzSJgl091FElxCcToShDb2GWbNxF6NHbebv9JPenuBFePW3woxjbZ/gnwLesF+q51H04hxiel+l/GTSc2vi2exbBBWukefyOpyv1t02q/dQJAX8g3MdYnwPiO6mU+9//DkYylqfdajalBgD3GJZwtUk8id8z0p+E9FcCvW3v/ujZvNfzHG3tfduoPy1EMjLt3LP7CUKPfGvLo2DQ7+n9RNf6fQL4AJOoNANC+W8pojStpYIW9VAlDS+eWoIaEECzeqATMJGoIHOSkOisObHBAFIFs2ijKcEVOHmaMM0zpmnG4TC74qTUCl4ArqWFDldhjocuVwtIJvFqdIkSJP95RUGphFwqypSRU2oe2uuKUjVfcVbFqVYgAljlElyJol6oAy3YzVdliT8ZeAwCkLSPV4cDXlxf4+rqgMPVQQwTchLFGHQvmpIJIbQ+mf7KvP6b97OH1F8LTssJdRVl5bIsWJZFnqk3eqmiRGcSBX1ZFizritNpFUW51e9e7OIRXYtGFPBVot76zpPpjzBWHoLZrkVrJPW7koJ9bWpnvE8yhhY2e+AP9F89w6Tdt4fOsXaJLC9za4sVthYZr2D9au02z3P2uQLYPYaANmc5ZUlbAEKtYuRQuTYFowrRfVyid/MF/bsEiJq3/UbG6d7T5DzaPvSCZw+hrnHUm/dZUF26Irr11Ywo7jrvthjt/BNbH2y/4vwA7knNtWBZTpjnuV/fug+sPbYPBPcQKEnkjrWs2hfjH9W7myxMOrxfPlLcaLHWZ11VJGWiLT+Ttd3GtO8nwvs+GmFIGj0mBgTGE+eU9doMnqTfpUrUCsl9Xj1dgyumusYBUL5axlkU6RIYQ0Ptk6QHgKVFMCM4AMgJVMULsY1QU24RtT3TDKcaHdsZIwzK9I1inbo/fhGlRDL8bZc9eL+NiOWbNmyTgG0rfIa7oLE5hqfPlNkMJ+/M2f6Y2zLZY2uaycavCw1jtGuPHMOPW7iengfAg9bq2JC9ui+uy5FDhxPCbSRKGs47nPGBN94eQ/scT6QaPWImJAc6IIoTDRK0qW0GYQltMNx/DeD23k7ePxoMw8HyuwBu3OQkm9GYRp+QGENZT2YwZlgId4l6kpTMnjhiJ8JJ7UbHdDuRVlI1uo5mf+4xJBT9C+UPZEz6Mfe1tcP/mcFmiDIfRqJFFjWHOYS6xr0wwjl68SnBeB5KMkK2Mm6XBS+uDmqMmMG8ja5kxpy1Vo3AmkFEWFcxHJ5yFiU7kZSDRBGb52vEnk85Oa2PWt0ADspvfCXgNRGW5ROm6TWICJ/fvcfLP95gef8RDN0Tbmi8DwTIWgv0o7ziJmWwCD9mTEjx5YBlxun2eRonjM6Ue4Zn+M7wrEB/hh8LI3ZjaG4z7p9F74cAJoDw6526W249U5NqvjsrHepsQo1tfU/FLzEAs/17iV6BbvV9Qg9/50NgT1jizD7QPJ40PFzOmuM8ZeRpUi/zJHkjSUW6RJJrkuQgT4DmyaxiLGE5M9XzJDFp2LgHth2duKL79Ssq0n+9Fj2DwWPmZmTnztWxix/u4xYeDX9nbPR94Nfbd/ecUG4OfvdcNqHvWPvOfRJBfGSWtu3Zu7q/HfwLjnCES7fao3vxiBdXklyECcDEr0WxmpJ4QBZVoFcGqKC+q0gkeZzBwITXYPqMVQUx5/UdGynGoyCbfMs1vD0X/FQGBt8z6nuv0Bm+q//ME2NfTHceRkHx5tumTFfr/ozkwrNEydQyTSEOVXYQO2mNKt7OQEUphFSbdyUnBk7izUIzo3IByOivDKKClNSnhJIbPIryJjsNN00TpqxevZYHuhT3uCiuwJW+Cu1OIAsFDrjXpHlVVpYw8BJ2uSLVhAJRINdSPU+3KYLck9TDtFtuSBXMIUnO79SLB2Wc5TdBBXRV+Ij5xawKNTEqmOcJ02HGNE+Ysgi6sko1GeJNT4CEvLbqmbGahzsBxZRa6n1bS8HpeERZioRtL5LXfDkt6sm/qDe5hnS3MYYoxteyYC2reupqOHtm9zw35VlTcnYrT3mylnyAIMYLUlZXWGpCTtFlNjwzKrpMeb5/vpxTWACNk7N29QXGGgmEPFnucz2biN3IgsMLphAGJe+5CeI5KF5h+cvVMz2ypjKv5Mpz6X/1sPrWaPvs5pwU95vQ38cAaVXKW7miHP7bcD1DPpmS7Lflyw3mV6+wfPkCVN0PIYWC9Qck81pRPRpFUqGwYJiMPGtI7nVtwlOSda8TIi1x5a6sm5QJlClEJwCgKQ04TFjlJpgnnU+fNMDbK9ElCGWNHKCMvilfrP8yTvrdIqZOyUOusLdVRwIeDtUVB/DzVQxmyD3Yqhl4B+mv7XdmBhfx1ltrERMfo7/c0DyeBeemXhXoWY2hckLW9AFJZR+SykJxheIZSQ2hPLnW0wm+o2GmImPmCpQEkKTeqCAQa5hYmyVdWzUBuRCADAaQLTQ8Aynp2NjK1G7zsAPURn4zh23vyft1c9APdAo3ClbayKEYnXtrGOc77t2zabeta3dcvvCIjf/fqTQYZTODR/LuPPVCPp9nbufOneNvyyhc/spjvqfibyiI7idGn5j9mnkb1Sp+aks/93hwAwxEV6q2D9iN5YSckb6aLfE+5RH/CnzVyyt9yRxyLL1eAiO/eY31o3j4Jq24AJtMQeIjLW09sIRZf+zasWpvh2EZx+FKx6eGckzNMNHO1AxF7ZRQqPq6yQxUNcS7YuAYOkXhi6x3iCzcvSlIAULFi7qiEuNWy5qRVt0xjt70ldoP2ad6XkfGSyl5+RVoAZ33885Qrf17X+c7nu2BjX+tRhcPz5lRSgFl0pSjUvPt8YTXr15iXSXf+WS0ujIMpQKVRVmeSDzVmTLmSVR3L19c493Hz+pcRm5Ua2lc/nrzGu8/fQEz48QVV0TKi2gErSTXlRnHLzc4vHqFdf2MefoNCYSb9x/x+59/4P99/x6ARBm4jZ0eDyDjIcy4xS9lTsyAww0sA23XUvVcOOjP8Aw/GZ4V6M/w/WFDLeyQD8Zt774fmY0d4i++5xbVfaHeb/3HQi/cafCKRXH+B4B3kcEeX/zZ1PoeEeuCmv5e52EuP7ztRoCmZLn5RMgqYdtViZ4n8UZXAgCEEEJPySE2ARZrLrfq3jUudTXiiQKzbec6BwL9jtM6KRVEe5K9Z/gOsGWH+utz5ew2t+eumPnREJmMx9CCPcm/T9z/gurFny1N+NnfvxNGRL4n9np8B8xJqH1jr9BldXkrBgZ3kDN2lW6zpP4o2BeH/IjWCO9+h4DnAnh0OwlnaSVTF1huZQmZXJyqoESo/xHmOf1LGNv6tglOmhhiL0zit0NHF8T754TTtHdW9y177JxfNnP3lxqFLfZX1AVPC8zs+RhFl9TGxDLRivpZRH5WPkNorkq1UcIqOEkm1EBSb1l5yCAR2twCmFkFPxNoSu6xzYipdzQ6kKbZyXlCShmUkoQaX0TpK7m6W/hgUdQ24YoI+HRteq50WZU55yb6qgyQKfty668pe7RX1tmoxCJKvn3ZZsqV6A2c7kxhrAnN61O9QKZpklD1aUKeJqmXxCAh7lXWfpg3pnmCVkg4bKi3CSB/j8cjyrpKvvNaVXkuSvRSxPO8rhKyvoVil5zQtYiHv7JEjgcsbDuHcfaOeb/hSnECPOJG6Em/JlVoWtnCX0PpbK2D1ZvVPH4ZaD7MewL0IJx9ICYytffIAzJXFcaO6qvYF7Q1FHoqa9R/dW/naQLpPjCctS4Lam2ezh4BxN6L3lVyozXgQoi9S+4FHOqyMjvnlI+Nfm/58sWNzisEZxjvZc2LeK7zLKemiO6PJispN5u3dmib8nTefRBA1SupVfz8+jzikH1lZ4MbbzBsCPpZ2v4245acm6FFw+G9yB1oipMYFj2h5X+PfG8fRUWH3vYPsxsBVNg64zZthtN1zmTvjfuj9wXV4BbCU5vyPGdJN2bzxqwpIATvuqDfvz2csc7b67d8uTAATaFBasxeEmq2vOj6epJntSbk3NrADOTMKMW8Jo2nl/kYUVHD0XCcHg1g4iyNYxR/das/5EePc3M5PXA/3b7FWWO5iF+elpvbYPMzBNLPY5m4+2t4/mIsTxFf6K2h5vM39Ya9H4b+nJiH4rPNOfhrwTjVT7eyvpVXZUzMIdR7bxa3rfGOb8R5DR12XKfnrtW8iWT1gEEhiDK++c/Ky/nN666l3qSRr8F2jc58ecj7h0LfFna8GhEpQ8K2J/3tvASUX1SMlHSbqEkYzJPcaMIdqhHm820za2aJBJn7mck99zspfS9I1nOTnB4xetS5F6NNhMBxWsRtNNFyi8c23u+Tbs3ZlunG9ux74WH4eIjT0+G7yozjaQFBDDAnKlgsspe+wJCc6QRgLcBVSmCN1FW54l9//o4Pnz6rsZ6Mwe2y4jBPwGnBYcq4XVdkIjcEKSw0EJu+JMk6z5RQbhM+LR/w8vfX+PThE27evccfILy/2MLLjG6tpwHT2+E90huBvt6M7kAiD7fbpvtOe+oZ7oHLiad/HDwr0J/hwfAte6VjZnZxJbf7e/h6T9AQhCKe99wYQ42z5/ncklqzueDifH/27l9a1lr3BsDHcP8LgNcAPoLwGRK6/V0nmtg5WLqvPOzaxuGpdMBCmzywMiV2JNpb8DpXwetkgtckCvSkwknzbnGeXn80ISm7cFU8j9Q7wL9rovcYsq15ErT/jrashPTIVX6GV73wzacq9f2+//1gS47vP3+Gx8GPGr+fvY7OwdO06/5a9nD3OVw+3hvfv+S61bH3NQplxpadq3mvj+d359j+/S80NUnfbzrT2i5m86buXxcubeFmFh/VtSh6bYIKEUiL2KOUBXWtWN+vmP+cVIkkJet/GIyKqt6kfOeq+LZr8TgPc25knJ/IHF7bF88A2PUSeuyqaC2l4dsA0vD8DNiTDAuH2FZ+Cr+/ta0jtL0qX1hRkFQgk1BwoIMKqVhFUIzCKtAio38tsaIINLgyKlWAC8Rjj1QIxyioSJCIBjkJMUc5Bw/sA6YpAykhJ40WNCX38jwejzgtJ6xLwbKuWFcN3e4eoxZOHpILWL2liyp9LAQiaBJv+6zeqCmBUgYpfZ+IxFPF1lowMKBu5NhHz+6zSqtkexh/kLoc8ZQTUspYjyehYQ8HiZZk+Q0tDL4J72p1Q1Dz/LBcxJUZZVnEC5WL5nZXg1D1zl+XE8q6opSKUlYspxOWZUXlgnVpodvXZUWvgGCniaH0snlQy9iavKr6eBhNbZ6nFqLfxWAUcrZHBTPJGqrQcPsWYJRYQ/3fQ3tEtufs477AKKM0qMYHareK5r4+pEkEjGl8R89OE1oO32nRDMgFlC5BBmRudREljbRQVlnjYwPvHoVzHOR9palvy1CgMmPOivcRcnHrxEYFvsxcBThpFIsWoNYMM8TAxBOydkpxOpj3fWt78zJv47ihMfQ8YgbylCX/uhqSNHa/qtJc31e8kogkP27S6ABcfWd354xL1ht2Hg0lyNobSnYe0nrPjbTRBPtpHHtWr7wkf0tpxivi8SU4ec6EVcesYhBr6PedguJAn4VjVpT2Eh3EPc8pUFZshuby/aLKdKujnfpJdSw6xmqEZ2B41ZT+YKCWjJKABMFzFNLGEAiJKioSMjE4JcdDmRglVRD3Jmau9upIRWth+GdrJqzpPRTiVWwIh1CaOIT/5eGv9/6B19J/DvPWnUv6Tryyd34MnBspe3bu+m4uoz3jM8/3DLEeNq7b9sQDZO8ZFGffcw49EL5lhYwzf74s3fP87utx51A3Rg+Z83F3Xd6ag76WdteEEHxbqVxfX6KRmg4jGZqWiMBZyBoCSTqVxAAl1LqNR2mGUfUMjXKCeGPfKpp6oYhp/fjFkwLJ3pb3J22K/W3daPPNkDzqgOSW72HcZwOEfgLx/NbHenkb6NdrS+TObay+KlJ6ocVmrpJPnRmVLPc7Y4LMzsTCkV/DjG6lHvFqb2tLYlIxija06gFzBdl+hQgHvV8BzZsO3FJcD1K58B8U8KetX/LznPwV9ao38swdrvpx7NdZXIX9uJ/DFB7On2i3nBtbKOmU1GjBjNEsUk2eZjdaE1qR8PvrVwAzqBSceBXaSg37CleUCkzTBK4Vy1owzRMIwLqsOEwTTuuKqpGBCjNO64opJ6HJWahyq2/KGaVUT8ECACUlx0uJCLcfP2MmwgIgM+NfvxH+82nQJ2wGKuxRt/zTRafjwEGJ3hs0jCbnUVp//tzZO/ef4efC3mlx7npvKd31/Fea72cF+n8ZnFt4F5Pt91rI0+ZnPBpTd4fbgde1keNF/+3Rut7KcBNY+jNF1JFYfUoB7CV1fEKPAF7rPTtjk7fHMshYyT2CdI9pQKMuYkOG6z2r7bs6s+lPIEq2ZdovDy1KrYXGh5My91OeME2mOFfPc8oqRFXha2r55lywB6jsQq6rCsdKUQ8cMCrYCbrYIbK2MdAy9URiiXQGNGelHd2BAKCuxvOD93189/6JMI7SXczD3gIO+yTsAdL10df5vSG2PfrS3f/GXcD+n53731Dvk0HXEPqJ0Rr2GZqHvf24FyNa3DWGNWlgQyhNCInogbe3vu+6bnd32z+ereGad65j23titX2hb0HPvHcfvrDt+z0JTNhZ0ntbXyx57gQ9d/1QiCPiLdWbd13364OGuh7QtvEFu00A1eZVttaK+k4ykZa3Ffl/E9L/JtT/T07KSkUF97coiWG+6MzwHK1GS915ffGcBxouEHCtpIXrazQbx3cVt3doxtvStlg3zrvj3tZXt7riEiTt3VggXJtFP6FXoltrt7n+RpK2z+cIfWf0bNzA0KyKWwgFfAXGEfTqGvS5Qi1IpS1cg0BKaRoXqlke89rGyHAbM7hU8ATJPc4ZGUmi+5gHqv4miKKeuAJrRcriPX2rCnQJs16wVssKb++ZZwmhUgFXoEAiC7Xg1mHWDOfqPw+tTYZnQ3luWTFtX5hnPlWCSwMh6z4RmbYbROKtDsRci1KT5USmlJAJHva5GfG2pS7LVveaepOvZUVZVtRVxsNC21f1JK+lYFkWlGIK9KIKdVG2L2sBc0EprJ7mDS+655TWJcPQPNSdpnYCI+5AbnS2rQZTPOt/LE069PyoXkvbQAwJH806sBy+ZOedfCtsumsC38Yz0oev9YP36etzJ4yFhtwo2iip4UWsr/0y/qKNQfJ+kN+Fh89OKUmEgLKTyzK2JfRt3PvufXwH0HDhCtRErvAnAEiEOUtEhHU5jW924+OzY6SK7o1qE7zzbSbtByU/BZgZKYsSnEIY+OpnUugnLJ1XXDusqbosgkb1ei0sut0naioZWJ55kMTh0D3b5svaZ983Q7OehjGluytGbExg673H0yDpQ1H8Q9QEwJvTkAWtGF5onyZJV6b4S9FHS/1BrjZwXpoV9ySCeK6FdGfGu7Ie5JVFaV6q4J3KEtnDcQXBx4h1bKBjafNk+9UiD/jepwqUol/llnc9LBKPZKFhDRI0NQincI71vqgWfaQZ19m3bT2Si4NMwtO+2n7F+/5qCGEtCvgwW23gQl09fmzX1J43pIJtZuTtfg7Uip7N29L0gGsfQ2r1MYzu0cYNL+6jmc2q3Su0U+YMQbr3nLa34HPp2BY9Xo7zMI5EX3XfiuDnaueGEDV3N//s9RjBJEz9hdfn4NJmXLo67Xm7O1R4tnX7rW3r5dw8bFs3B/zbjHTbLqFwr805D2uAQ72hPosuqU2xpx2lSOZYJWGzixvKjX07P0MLtZVo1PQy0KMjDjLqNg+zs38CPy1wW+4AgK/mak7AdSW/bphKZKYzWMLsM2XbvvQAACAASURBVByPFAATNZ7QpNTEmgPe6nH+S0YiwaKhyUlqp6KU7eknw1GmZJaC1P/jPnS72vU6rpMzEUrXRyO9fsRHA6WGimi4g0CsDE/ojmfWHv2d/Ay1NrXvGO1NSDgtK959+IyXL66QKGGeMko13kxqLpVBpaqxHuHTlxu8efUK67oggTQfutDbKQntdlw0+lzoHul3GRBDk0SNJ9JO5EQ4VTGIuIV4/r9Jv+ENf8THnUXsa98WRzxO4ywEgZTRjn5WAUhVpfje3ob12quk/w81U9xlz/AjoMP+AYXH9R+ppHht74/n5F79e9fnKYAfC88K9GfYwJ2HPEcSZv9dOwh9owTi0y2juR22rAe4nRVOJvm30KgBz3m20y7uPbKMudIgcF09ka+4t89D/8InN+9FUvA1gM/h2R8M/CfwMb8DWJ1IjGhFWeB26uwgiphrDW2Q40FJgQnh2oReodwY0mhvVik8o2RWf9TSiCmTjjD+zkQTiYMACJlEeT7PE64OV5gPM6Y86XpoCnGqYnE6TVnCjtaiuWBMsKi5HFmFjbCwlHLIVkiImuKMDm2M2IWgTxrGyEQHltPOA8sNjIit+9FjHV7yUkvG7ehecvefDudGazyGDXSGjMgyKvoHMywjRFFQh482JYc9qxBz/m3f6RmyXwfIBWRPXO0jYI8s2x+zhj7pwd+KGBsN3WErXNA1adweoJxLa9NjIl44Mwc0YQICA63PO0XuzrUxzPZOCzLcdl0UJN/nJdOrJG1vGn7MgYEywcUYxJJ3/tLO/f3z+K637rrGcG3zyjvPgOYj7/VQ2512jTPXmfq672sbba7D+aKKS/PyJnoN+gMovIpx+V8EfgvQX4T13wVAAaii4Mbn2mivSnqem+cgwfPW2TohO0ztGsGLXFtn1xmBxui2RBspDuVF2WkDw+BqCvUw8MNWjrKvUQ62lYtR8Jps+9Rz4SL8x2nU1isewwlDcEcUmcv8NooBwzNgmOuhkW6ECIBqq1nS2kgtFPaU6IAJwKxU4RXWT4uWSWAuYGJUJCQNoX347RpgwvplAYiRX2TUrwwmzdZoCigwkAiZJuQrAEhYWUIAEzOIChYqyHUFnY6iRE7mJZqQvyZUZpxOR5RaJe+6eWnYftE5Z2ZQIfWCFW9YBkQ5OBOQCIVFOUls573kBTeakIviqQystSqV11anRKBSQ8ok858LgRP5mqwaZhKsRrlEiqsUDybCPM2YpwnzJPkIc8q6xLUeFs98ya1N6g2+olTGWgpOt7dYF/HEX9dVcxNreGWWMSq1YDmesJYCLtXpX1eE14rT6ShKf1XumqdrIhn3ajmgSdouPQz403KYG9Fhe4NlHGzPmmcNqxawKYKhNYpKjnLLdc21yrgyqydSyz/uf6FKRe0Ph7ZEOoqhymyLNID2bizbNou0b56y7M9aQ15z2bNEhFpIjycT3Df8kFKCpDVggMSbrdbq0Q7cAxqQVAVEEiKbue3phlDOwq6RzJlXvKQbKRPmaRLexxT+LHvP8G4tYtaz+Q4zUk4exUvGXfZK1bWecwJrHm8/3GAe1FDBa0WijLoWpCn7vq4rgFS1PaRRyGTfVq6Y86RjLP0xJ27xsFpQK2PKs+AvZiGZzDO+Ci+ap0nWxlphuduZWUO0i3HLejzK2q2MlMRHzg73fkgIQIuawWCJJg80A52wdpyO0elgN+Bt0248uP7RaBUsYgzSiA1kuELeFfxnshLFXQnQcA6qKCdM04R5kjEkjd5hRgG1sPPlZmAuJnOMShoKlwAJj59832tr/eD03PDdsmyCdmJGXRZUzpjmWcPGW1j8KlE0StGUEorDNMKA034kbYqyn15pZku+0REMVWRulN09B+70PQId4TS6lWPIRFMgNIb923lesK8hcwhxOoylbR0+Yih93rtIWF9J6S5TbFgf4pjfd43hd6NsfPCGGzsvPSkM4zg+7fJw67j7rZ3r0Ph4Kjgt5COyJQaNEmO/CPRoHKi7rrtPUD+cjJ1r3n9ugR/c4rp9q1tim2vZk9F47KF/pf3jCome3eT4qod2EjcDllBXV29/fdLarnTjWbovuWoGu4Ygbec0s0/jQxsdvMFINqfaNgYwHya5TKypJCTyVmKtacBrQ+V+LlikEGIJvW65x2flF6JiOFZh9wugPJDQ6DO1kS9g985nACuNNXVN0g/1LTZs13bbMDrWT7VO+ZrCnAE4ouFJUro3Qw0iSbyWV7QVYv2RM0QcwMxbHZAoA7OXy8IHEXCjWrXXrONBwALgNun5F7rd1iu54aZ5LSdtCCtOtghZxjOKnMLubeuMODiOYDTskI4kTYuz165WLtFWEgyWdQaOfKDuK5OR+zoTPmtKGYUrltMq+c25ijn0POHWonXpzih1EaxHCf/5+Bmvr69wOi2YZuFHllJQIbRpTaz4ijAlwnFZdZ7EuL4QI9ck/CEzvnz+ghevrrHeHJES4bNGUjoR498fPuJfv7/G7x8+4x0kGsHROm64Vrcjh41h5y5rMaIgY3IDWzS6Ma5pMz5IceD1W0pLWrkKzR3/DD8F6IF//WhV3LSJanDmugtsgIbjfgY8K9D/W+Fu+vZucIwXKgonjeuz/KxuxLBsmNaIVtbEF42i8Ka5MIL79na/WQnV1hBDw73C89tgs/nPlPsdwIdYnlnynFtXSJ6/2bI6aAdFoODjKWOlIjMQ3yYASGFqGCNTZ+9GsoHgfEssFKbaFOhhzu1UjONiwl8iZajlb04ZOSXNFzmp4FGIBROeCT0swtlk60O/IcI7tZwPQire/AvCPoQ+dBxFMPAI10nHrVdo2Sj1M35u7kei7BkeAneN2bhXdq5DzlElvZ68hefbtsd6wtvCY3tsG+0JUO+EH9WnS6Epz584St7F0IyD+HHDs0WjD3oXiOeatyr8pXYdzzOyE2p87651Ptyh8KWdToz37r0efm/X9PlJll4aU9PesGum2PK9PXNuB22v99ba5W/ff/29yvr1HeP+oO/xKBZglPcM/rOAElDfVZTEwHsG042/3xv6kAuzljBvjQ6j/Wv9PQogOqv3cf1uhNHtW919tprCAo/nOfWvY3h9c03j7a2pxwjRr8SUsecYtojH96i6nebc+W0AMA9MUdrEfI5GOMeWHgFcKxEnwkliC7sLqGpaG8sQpUkNgnv5V5X+as6UOpdrRj2ocrcwUtKc0lSxqkKLgkCDIEqgShLW2vHGQFayj6mZ0tq4s+d7p0RGBioPoWuXZd22sOTqIVMAzgxw9ugEcd2KoE3Gr4CRagJ7CmsxNiBAw3abwlTCdIshaUJOWcMlJ3ho71rFU4Qk5H1RP8pSVqyrhltfFxxvT5IPfjnp/VW8R1QByMyoteB0WkT5ZEplUzRreHTLZ04EV0wBUIWUCI3jcXMf8PBrm/vVdsRYUlekCeBNY2DDzKyGCAO25/DDXnUvdDtN+raPrGsn1Pe3WhtFaKdckCbGdB4lSZhMW69ESRXC5GGuE+x9+ZuR205SZWrOCWUtO5v+flzRj4ftkXuoETIljio/VQFpwkpShT8g4cP3ImHYN0whzMYAQjyYUFNrik2prqc25NoOPdc9AkSirXZB2SdbQ6UWLSMpu5igBiTiKQ0AlYvud7hAn8B+zSQG1YCG5y/SuFpZ+gDGNE9iWEK8nR9qjQtLEB5y3nlMbrgtvOY8uLWRTbncK6OIEqYcUwKwGkoNzQGQ9V1KYnROIA1Rn8Ek0WRSyjjkCYdpFp4n7kfmFq7VcUn19AZGe4jIhFCTKgL8yNWzYU9Ztzmm1TOwSrtlXbbc8GLzYgp9gGN4OD+TVTVAhpcDdRLGp5EAtiAhem9uz/sjKxIIgAvbjbagUP9Z49/zSNP2Q3tf74cOigiC/X6MN9Up8cK4tnLnW3HfdaN1zuCZ3TuP5oAubNUOElfhecfMjM/HKoISuKe4fHV3/43P23QN3xnbFa67dbhniLB7vdNXMDZMS2zGcIZtz7StFJP7Amefj7RXKxDaZAuxuwZMSGsS2jb+40e31xGDUIgRKpRe3J/RHNnaG6/3+9UbEqPRYXptxpPxdqLeSeFeUHw4hlsfV1frdWy1rLmJhZ4seiy6ASDa8p8ZWHbO/QGL3d1U9NPRtsv27Nvs+KSzwKLkLvE81CIZDIk3oj10Mo/9+RHAkYArEDJlrVpqEZNEpTGIh4i0Qz9NeQr4GhxHwugYL8NCg3CVg2EcNzrzu78rtIQYIca11n40dOAnipchBqiqPDk1usIjpTHU+FJMFSytChhYS0VOFfM0iXFtLTjkjEJVosiwGN+nlHBcFlRm3BxPyCRe7FeHWSIhrSvWKiHai56wa2UcpozXL65RasVpXbGsGrlVWDkUMOqXW107fXoVALj58Bkvf/8NL95/cmMSP86s/6G8nX+m9CRqtJSvSwT8VAHTXUh9EtnGaHhwarQs6f6noSHP8EMhjn7T+e1TFNv9F+dyp9CZ6/bNnzvnzwr0Z3gw7B08NP7liNhwntoAgrU+b55fSjyY54fVlWz7MppXzUjlfAOce53Q8p5HxBLp/tYMxodHf/2uWehBiEvqmLm90p3yfHif9PmGmLCLgT4nJWaJEjKADMtxnkQoYISHhflzxlr6xkyoEgsUxfKb6xyKQAHILFZ7iStqInAldMoginVaZ6ShHmqaIxIWYWz21UOBBejQ/c7o3UWOXQ7fuCwfAT/+i4+Dy7CA/ffcDvm14J9L8D147B85WXzH1Y+BkcU815anvJbvcVjovMN4/wxwESE56yv3KXp79YfFvtHFE/fn1xieR8PuuRvAPCIa3itY35uQ4wZrGOQoinA/4/A8M1CGSckb7Vu/HntPiEjAtfCz8vx+Ecbda/9bCbeRUh3vP813DCOMIohID+wt+/NfvZtVbGMsc1Gbb4+uiRR+myJTQuTmF4T1ZoUpEa1Gt/RmqbWgSshzmLBFQgibF4W9TSmpd3pyb5/KljFSa3dFUxutpnRRIZP1m5p41SIgsRmIat1l1b5mFUyaLpNbIGAA4hltisPAopjgsNGPgskSWHNnau+IQCljUs/zJCaXALQdXIF1BdhSGYkidjktErp+lbDtp3URT5F1lVDutXhodx8f8+LmwCOZUkzzGU/T5GMLqkjqAc7KfxGolxa7R9KwgNxYtscTHv7evGut/lLaqcdiWJACLW2hqF0pS0a72z1gwzjcscB93Ya2RTzWtTmW0QaaYjzuMA+j3r3XdpKs6xBbQufUPNLs+yYkbWv46eiQDT5wpXfbTdM0Y1lOqLWKx7j2g4iwrttw8tpSWf/JlJ0yCjmLDxqRepY1+RbAwEnX9jSJYHwpFQlifJIytXWXEtKBwGvb1zFSR1KP68qWO75iXVfM8wxwxZRzwxtEqgwXDg0EFaiK93KeEiQjREWeJUdoXYsaR6gHPJF8B5pnvUhkBvlrK0DK52kGJ+FNa2lzmZJ468tvUXIv6tFlTgLOg1Bb8xYxojMsT4RaxSiqckVdrV/iOZYSISdJdWbO58SMUkSknKilQItpASSXOgueqBUVVQ1BbA60jdScF4CEqh7shgjNKKVDHeeokCTzTZQgedSbVyulKji7ks9DXG/BtxWWfK2GO2SR9myGnMBpC7MzQK12Dhkl0iiSdlfnBgymgtif8ZefV/fQB50ir3s6nvb63bPyAmvvHr10Htqp/S1wDpP+atf30YcNr7fnfRnS2NPfL+PYWHE4dx87Sd/ybldJADVgou4RDUXTznoef+89k1V+0LN+6/vbCLB+1bc64neN1gDs/NvOPGBni0Z2YMaUkhuSWqQPrg3vG27o+2zfGdeSgCnTF72+QqMH4PVJVDAzfEjMKCCsYEwgBKoSVemKKUskowp2mqLUGr6/P1IbrqobVxuogbYL8JUQG49XlsObeYikJmrVZG2jhtEYwDtleA42tSRlCYSrKqaph3/9geXdB4DFi5lBOHYDHLHo/qK/azzkToysIO2OWGD0LW/4k/3tvS9HPMvY8ncjGP2QKMENUCCRZyoWiR7Esi4JwFoKbo4nvLq+wjSLeq5o2HafC5Y1/vrFNdZVIlbdLovwCcS4Psy4mmZQWXHUdEJGIyylIGeJFlMr47au4iXPjMyMFYRTJrx69QrLlxswJdyi0XBfCUgfPuHNn29w++Gj2ZY0mxvqr0eqwX9zbz5j9KXcDJvcPmD0dgrnYmc4u4cJnuGfDk9D9zwenhXoz/AIOE/8x3MYPP7YHknmKRyMSh/+dTWfamzweYLosXCppYuEZb+rnrjlL2ncJeXvZu7sbdDlX72ruo6sIXThuEw4YPnOExESkoZvz8jTJMI2t3ivQIF7Wnlj1QOHIR4U7ISceTmJZ1PipKH9at9Obn9GJjRGOUB4bn/HcMrb9++Dkfn92XZS/yQYV3ATxuyTvD9r5PeY+nMc8FO38b+UgNwlpi97MTKdl4MjEMetfTvOfu6ye3d9+VeeYhr+dtCEJj339Eh4Rqzd+DGAihvx5tL7FX1uboMU3olQ7pMKXNiWrlWPNfDYfY12fj6k/p+3eR69XG3LBNkCEOjmjaeWinjcgAGIoeFja8zYxbwVxUCRWs5pCH1GBapAV4VWKUBKAIkHNIqGHTYlmnp8Ni+N3gPPlSc8KM/Ds64/SmsyVLDJQhsCRj9K21iV6VxEqedObiZEZJZ2u0gQACqY1d/BpTkaxpwlxCRlcjp2mmahZZME6GQGyrKCK6OktXmME1AsTPta5F9dsS5FFOdFcsQXsHjfVhXomueoKtLJfgdBIPk4afh7hPWlc2rhx+PikbkOIVE74xgO/20/RuVZe75/31VjZyUcobWBmSDwcLaNNFOGZdfcBeZO2WUes9mtJRpH0J3XHJ5Rr3CPcr22Vntuk2tFcmXmls47R/k9BrLGOrd0CVBv834eA/9rQk6y6YpzrEbOqapHlPJAKSFlkhQAJGdFsTWzwSEkzYiNlHAIzWubIhfVQt+Tam0pJ2TRWus7st49PUhoN1mUqVrBVfYxF1XUEiT86gSvyxTLa1kwzYfQxOqK4mYcowYSUhEMD6QkIebFsU08tpLHnaWA56gtFshfk3FUGw8iV5KbZNgU8wQAUxIh92QKdAJUgS7G5wmZyCO52cTWUlFTRS3aRktxZmFStV+iOKfWPW13WxXU7w1gWPNxmcn62cxznG/zSicJsy8C9urrqGG1sHzA3drd0tbtIIy3knstbs94AtRwXvsSjQSDwmmXLN252Cdp9vnPqGAAKKaJ/fnws3mJ7/D9scotNt7e/WHw2P6Ooo8H1NsbuMYHZ+6fqfihI8ZQb+R699uPmYlxnxIUrSnCiNcpJ6xOK/b1PMXZvH3fDFmlfnHMAWYA9NsrrJ9ukGBKdCtvp420yvBLcqOjB7Ql0vqPWG+GJjPEiKoYvwEZ0wnAypoHHc1XeYF40ieQGFSy0PxXVdbBbyCUtx/buQJTnvfr8LzEVM0ojWbzs3agSchYBoqvhj+xfKOkN4URtl14hbtyl81NNI5qb6k8m4SHMer0tKzKZ2TkLN7o82EGM/s6BgjzYcbpJCHd7ZA5Lguu5wMONEmYdq7eicrAvz98wv/++QbXVwd8PS1Ya8HreZaUV2vFsVRclRvkl9eYb77itvT09mcCXjDjNQOfAFxXNcAAWj76ODKb/dbiS+w8biPeKcgjvT2WjWWe4WfBOPrfczbGNfOU/NVD4FmB/gw/BaLwTH/AWSlXqF+wJVTwYge1iQCitVcrh+9OO48e5b8BeD988jcwPgL4E8C779OMs3An/X2GQDeRUPTYsfsy/IFpJhHsZLVIz0mV59RCt6c8iWCjVhQGJBZlo27E0509T1otmocomZBDyLUMFS4msuStLuCSdfTNw/Udge64eoZvgcaE/Ohx5Z1/sRV7JMY/c+Yv3npP3f0LFXXUTQ1jKwH+WXD/yD1Ief5L9KnB3YKt7/CB7ww/Gs+cG6/Yjug9bgKcFH7bMd9Ujj22yndOykN7auKKC997cnwQf+8L1h9X2Y8FZqhiGoDSNmnAdQyg4BYVQMYLEzXBvZCpKYcsbDUzo95I6D4CML+cUG8klHhTBgIompte8yQXRvMmVLpPlCSq2FNFkefYdjK/rbStxzl7T9z5QD0zms1NKGvCGgbSnNtATAxP3AgGc1CiR2Wytj+Gxa8q/GtTrW1KqjifZxzmGQdNQTRNGZQT6rrixABo8UYxJP/wskg+56qK9For1lLFQFQFXBKmHf5eLw7UcTIpHsv41MSaFpkb7RuEh4j9JQBoikfikfcK3+m+3QwMgJC7eEB8QqOjyb50jXbKL4egKDdZ6HBvC6pU7T+7vyVZolZFoWetYuQwZdUapiTeydQiMzDghgWVzbM4+QggwSMwRIF25SqKuQrklFHOKPgvxR7NS7e7KU0gQqKEq5cvQES4/foVy+moebDD2gawrqt7gdk6J6jXdyKknN0Tz/aZJK8kzFdXsp40DPzpeAQRSU55kOS1Nu8+iutMJryWokpned/3dlW+TF0IaxXv66QuX1VTGFQGSq3ImiM9paTPxOOd9P5yOoHQvMvLUgAwUs4Sxj0nsfFJGiae2b3PCYQ8z4FPTLKOtYy0k6XNIKxr1a0tfailBtzR9pnxwgC7J6H1/7SIQcKUJS+v5X03nEME5CQ50XMW4XkmsqT0yDkjkaRDm/OEKauXGhesVFBWNbCpVSJaaA7famcHERJJigrLNtqty2GRmsL5LpKg5YQPf+1cUM85ZNlzMtepGWp1dZPjL2sHD5rmZqwfzvKArs2FY5/TIjeOZzAqEUC9p+LOEHR4xEFfGW1BR7Dvee5nPl9+z1C/nQW/GCF/MXx3iv/7wt902Pea3RlPht/3d3F75p2HvozVfeyzTOjnQxvo3DeG1e/peORv9vg/+vUKFBSJDpRIIyEJ7p9ywlIkGsiseKpFENnv2xjXa+yXwQJRpjgPZVSN9YsqCkQRffj8VVLEQBTPBc3pau7IU3Uy2lWgG+7raTajVngoOeYXHi43/flKQgpcKcElPGFvqGmBhTLEmQkAXqquVgOOyOywGMwRASs0V7XWcTyz+MaUMym02PK5dymt2AwWhACtxF1+8tZHWS+VRq9+W2ftDcZ21kdTL+dn6Mz60MGySFyp23eERSMEzVnoqilPIACFGXUtKFwxqyKdWSJOOW0LMaac5xm/5YzTcsJpLUgEfFy+4s3LF/jXH2/wf9++V5q8GWN8/Hyj+0GNStYVVy+u8ZVPODAjpWuhP0B4kSfcrIuPCQB8/fAZL/94g/LuI27iXqYzhrN7C+0cf8Dh4VjW6Bgezsu/KZ5+hr83PCvQn+HRcL+uoh3uZMwRBsEZgnCtvRKueyHP5gt8Z2agJ4e7aMiXAG6Gex9gghlRpgOPDdv+7UB7h9gIgWrYMJJBAG3z6fKuoDwXoUUWQYCGmptSln8qAHDvmlKF6mXyfJLWDGaxnvfwn2TMujW1Ed3MGubd/mEr5Ds7LoGpzm5L+QzP8BAY2ZbxGaHbXJtnf2dgZabo4V35xq77iCtueDTmp0vOs3va8B3gnLL8byaGOguPHXN//94bPwZ+9g4e+VSgCSkG2ZWXizxu/PfLw0MWzU7Rc/mH763qJwzOOEeuy6OmFAOC4JFMgDbkqwxCuIrqYcnbuyKYKje10XVOW2voZVMUgt0LVHRMSscTi2KLmqclQZUqTsYH2t8USxxUt0q2Wf5gEySKR/d4Vg7aCFXYJ8ooqgA1QZsLJOPYuuK4hxjoOyUxAp2mCXmecZhmzFdXmOcZOU8itKsFpTL4tIC5SsQkiAFoqRW1FFEUjr/d4LN2Oc4j/W3GojohXoYBVbjXoDiX1EcypD1GII2tSMzgROLJz8Hz33mz8JYq5uOQb9Jtadva17jJvppWK5A/1L2rq2lnFnDmbg+XbMkoEu0MJoyX0LyZtubl22RFvCMewQDoFP2JkpdJ6Wn4hw2OSqQC1uzhsmsp2qZ+z2+HXugy60qyrVQ1fzWxhhj1r/v+MwknWd+4jaHl4kyqjIAZzlTz2I5K/dYgT08AqD1HdcGy3NO0CWxe6ABX+WapFawGCuL1n2CCbUIzGaqoqGVFmrLjE1n39n3FheoVLiiwhnWs/7WIEHZ/RwDgSmP0a609FxbXJ0S3lURnU7yp+DJlEqV5zmp8TmqQ1NbtnAUfzdOEKc/Sh4UgwdxaCgjBMyUItJuCO0NyENu6H+XdrbGh0ReAGfPYuJi3PXIWwx01HJDBB9bK6NIkhDE1Zc14htsaZ2yNyJp0wlsEWx/t/KBWlsY393s6bse+/h72OLrLRrB/k3fv/krw67bsnwqX0q7nSo32PneVvbzWCyAYvsR2BNLtzDeabO4hLTPaM6vBnJ3tYidPKHaO4VLMdj+sEA/z/V0sOKgCuAHjJUT5coRhP6OEWn/N2DVT1nP3snEYKeX4xrkdG47nDo6JcGCjd9TMkRkHAC/+9Ttu/vNRFLsaIn8h6YXnnjeDW5URGXV1HnVEs6qIxwecTg2TtxOMfR0lEMpGSd5GItMF8z4OSri+bN0MLzrZ2fiupheJkW+EvwNLqPdSV7y6vvIqXlxfNS90pdOmKaPWjNNaPO3Kx5uvuH5xhf/z1+/49/uPeizLw6WU7uxcAVxNE16+ZNzcLLj98hUvf3uFw+tXqJ+/eH+vGbgl4AsxrplxzcANtftqve3Gs43vC3veWQql2pTnu3dhnlukY9lneIYfBM8K9Gd4ONB5HHYOjMFt3hL2IAhwuHkO23Uss0GQZv0VvtJLa7SOscg9fTtX5i7l+e/ovc+t6Bv9u0KskD+gCfF+pPf5U4YMazS4HfpynUg8A8wDPafswsc5T8h63wQjpRQJEain6+R1CPFbLfQMzJMpuSAJCGumSq66Wosq3Js3ziUeZ0348iOYwT2G/2fAP5Xx/Z5U1F118wVl/skwsm1n4LssO4Z5kt03/ntKhMCkZQAAIABJREFUsMcq1CLT+/hZ3xHAxebc0TRnOtKvt5v38OlTt5HOXvx4uI+3G+Gha+6+0mUoEL3Io0JQl8u9gpSHt2C/9Nm3fsJ8uTL3orI79x4gbaOdXw/9Xrxv8xZEUPKXLS9zD+bd4ooD1pzDEAXa6fOqii8pf/XbNSgRTh+PTaGkXzLhIzODvsrKSS9qGBBSugyBSGYASbMrCfE5jn3n8WxKdP3rypPkzvNS1pT9Jx8A0Cw0fyKoZz2ASUO5qyIp5SzvqUCPEnnec0IgjpP1VWlREKZpxuHqCvM8YZ4PmHNGymIgWkuVMOxVQiuuq4RlL2vxENHs34WHVbZvcFDatUXQxjWpgs/H2rySlI/yMPscRVJoJ5LNpXpjuaFbltztFuK5n5c21mxTShL2fVcouyOtraW2OR1fuADomsC3PeMmK6oZBgGwVMb3RmWxfbCq4ciVKvLJI8/oGjAF/zDOYUSlvGaMslzYngIgZ+QpgxcTgT+u/yNCSCR8FVECl4qvN1+CgpEkQgQDeRLP+manIGvHDAEsYoSHDFcFJ+laF4WqKcrhyvKUJyzLgpwJYMJkivUkdbrhADNALFHGYOm3Wpd8fZoym2TtFl3nFhY9pQQmMUIharxgNFCgoNAvpQCmrAU85/by9bbfV2ZsovMtdja2gJshRPuIiufJ0kWQ/p/cKKcJ/dsqaXZLMtaSj52Rs463LqK1FoCB64PlXSf1PM+ytqBGTEnnCoQ8TThMMw7zAdM8o6yaOsKE4gxwqW6oY31wHKn5WBNC1Ig74e4Cbohjsp1u+GT9JQCUs3j+VQjBQgBTARcKa4M6YopqO8V0Cbe6h6b5XugQkq4npUfNe1EeRdqdu3o2Pb5njO7n/qKap519nSxjp4YfI5P4kbB3gjw9HHTkjvd954cN74/p950tONPX+7l28yqlh28Mq3/XA31LJ28NVeSG0Tl96R1QJCFyQCCnyc91ky1bvukKgPTxWsoGDwDm0b3X7/2GmCd5YUYCY4JEITFFy6zfPUHWaNaKhTpVJTsHT2Wl17JGVKm17s6XYw99kM60977lbnVz+H2KL+n4rpVBbz+KQYKS3Fnpi0p9e1aIgv1QgYmA/K/XuHn7WYOObnG1kCwU7gSMbPSr3rUzwc+3sF7MA73H7PYzdfRIW2lmjGeGeUA7f/bWoN7z9dmfX04HGI2d+rXUnNAaH+e9I+NBgOOyeuqetVT/ffP1Vmm4ipwzfnspWeVRpc7b4xG1MA4541QqiBISCKeyAqXi1fUBZS240sgwoAOuDsDpdEKtFTllJAZeTBO+luL4lAH8++Mn/D//+h2v333AJwJesCrRW+fuxXoUmbs4rh2Bb0NMvt76iuOqvXuFn4908QzP8HB4VqA/w8OAOpz2IALfleIulWmMg3ukjHjtDkTH8dDaNnODtO9HrzsvXQimPH8DIZA+AXitvxOAT2jhB9/oZz497lPfBSIJ44TJOM8j84p+/kkt5rN6oDfvHRUIUJKzvVaUUiWc5SqWdAkJPPfeG26NlyFCAA0XaAxo1fCXpRQRWprQALWzm/insaDPcA76Hf4zSKT/OrLs58sFGowStgvB5OYPf3eP5X44jMzvfw3cqcy8bDBo8+Pnwi/SjA2Ma9TP+PDsV9jCEQZe3G9+q1D5Eh36bpEfPECRGqJwLeSzCl6Cwg9oNDFRCxvLUAFdR3MP4qD/n703bW8jR8IE3wCSlGS7qrp6Zuf//7zd2dmuLl+SyARiP8SBADJ5SvJRZviRSeaBI3DFHQRX8kbhwnpUDw5KMWqpCEOpHFx0u2C9g7yJo9LFlFt2jwiqgVeBEID9SNUxuGpKc+kEAPGKrVleMnwZddA7QbNjlmLDIJ76jEbHppQlpzqEji2VwaUILVtm7Pd7zPs95v0sYdlLCQIbeDjiPsUQt7rVoME99klysJPmTmJT+C7KCOW4Qr1FCQi3dYQsJyL5eqqFe8lUZwhhPw2/cSaEcTwGB+mEXji6ulF1AsfrofUuqKtqw7+FJGVTiqqGl1USaApf6JjIshOvazZDB2c8okfy+a1ezVtKhCllMe7QyAWi/GuPMlpkLtiaJbTQ7DZ//B75H5ugOXhEsXqRV5+TkHzb0PQKtXnIEZEYDVRGqc1jvAmQGxai0tlwmogsM4TjINrGM1eYAVDEkUcaC3joladNruAMbZinp7z5YhkNN/BwtNGN0rbg0F1vlXvuJ1k+brSAjMoVacpueF7BIrS2PQfk+MoJSJwwkRjwpCzvsArZvf++j7b+MiR0u6vuA737ImGyGaurMY/No9b7weiBCJwSwMXHnxKDmCBqfd2HZMNUT7wWvbB5sgLEzUyzGQ7JZB3Pb//N3bD198L3l7A1Y91rW9rhd1rNPyot2eBHbeFLDJp/XLjE5vbQo12qjTPfAXq68hgckrm17UY243P7QhhptXFkD4207RdVjZiKO9bMc0XOku6z+jprn681d6KhH6gZLtvfM0SxniGKd+ur7WPNiUxKSUkiMZ1nsN+fg8evrt8x+9omZm+04T6FsPKZ8E7TD92BMDNhFpIdMzN2RLhjyQGf/p1Q/vNJe2jnKFrdZCPBXr+0jvR2P8OIItkazx0SmbIajfZ313pM3bsdHgYiNJ4N7U5jKii8ZY0UPPZ0blTm1spIyaIZjY2UXhd1EhMFekWprU1JLUm3mwk5ZVCW1tXKYrxiKVIh0QCsGfv9LLSHevrtPn3B9sM7bxclwva39yifPyOlpEaEDWqt+PDnH8B//sZn6nHajZRN5RRw1piHbm5FXrbFFDIUx7D9rTI+MrNvcIO3gpsC/QYXwhXiy8igKRfdKc7tU2mFkflbLTJw3HLQ2qZbYdbh3fOt+d2FQzUcYqCOPf9ePz9BPNIJQhj9NYhRPgL494FyvhUcYxrXniU0QqXRPI0YJ4hxnYT00/BzOSGnyS3qDQGVgTLPmOeCOgvpOGVG5WzkteY1VyLDvETsYIUoz+daxetH/0qRnDGjYOU0LqTc9A0O4O9/xH//FnxLOFNE9satuBz+caP06h06XODaaB7LPdiI8Ovh/HdXniQ05flPO/Dk///zvGa+H7w2JiNTG1nO6r+vq3ExfUdF0AuFf2v0yhqzfqwMu/4SnB6r7zXHak0I33LWizCqhHsUhRBAlCodEfKw6pupCStG5flASHupzwDu5Zql5JGw8o0mB0wIohdcFhhpfl4qcFQRyczATjx4Ru91Ms9zEziZ0k0VmgAknLwr9BR7iXreIqlntSkWWdXprmW3/I2qeKqMmsT4E6WAa8G8L9jPO+x2e5RZDTnLLF4wIYy1KfEV82EcWvhGItKzQBVImeDKT0huaTFaYDC38aGIU6tD+yXFRQE49Qp4BvJWXLHKPCNCDC/pEyAMp6+HMQqzj5cR/eEW4IroMDP9G0GlyPcEPHGbNi5aXYFDGwAPvxV28wwwY8qSW1JCvaJ5RkPa5zmYgxDZRHoSUrwgTxMoT5JPnCTilvEoVGWcrsv/0AgTicAlRh0jEjoPcH3NVIsU1pIbCTKLBxPZffHAAzOmaevr3qIIgEgVtjL/KjMoSzmOZrZIETrfWTzPay0+xxiSwzPn5B7wpUrOcpv7tYpxx36/V6Vy4/lELDCE9VY8mAe7pTxY7CmdxHYJnss0vBCV/xZKPucpKMrbPmIpGGweWZnWplRZ5oBGuHjez5gSubI8pQxKhLucJDc9gKx7mynsEzJyTqBMyGFd+z5a9XuF5ky3P8MX+TyyqAmGl3XM8OEDb8Adq7d7UaOheHY0b8owxqK9Qs1V87GLCtz6ILt1PMMM6dS1Jajm/d9haPOdFQcxw/ilqrO4tUQ0HaNL7J7lKm7b4nC+/RQ0dOzppbBG4bwe7E+VtxJs4p8AR2d/oKFOHI8r76YThjaygs4b1bV5c+jJaO4ZaNPOnHTZklKK0EsphchNjEySH1s8uQl3m4x9KZhUs1fszOvasHZ+Gz114LzR/dZo9hnAFk1RLntA++2pRkKZUm6jfWT/llQrVNtVry5iQ2nIjAwGobBFnGnl9vtWG49zV7Xt8VsGZtJ+KP08abt3JGNYFRf1LzUkWy3QygVMprxkHynQNyx8wOIZnTdMzQhgpTIZouWu35Sxcb71ZRxaP100q+5F+eKRf1LqplTlCq7kCmafV1A6ghtOzPs8J4m0YLQXIJ7q2wmYJom5kpLQ7qVWb4phlnMGQQzfHr8m3NVPyO8ynp+ecX9/50aRRMD23QPmr4/4CjftAADs/v6M+z9/x7s/f8OXvz/hgQlPul4Ikc1iaWOIHlBrYN8G/Nr3ZigeeKVIA3IzqXjdE+QGNzgNNwX6DS4C2dyXgrURegGRXpPTQCzK/Rq3e/rmeWAETDz41612X3NjPdZvgoTmMQ/z9qQQEAa/AfjPK7bptWEkSGzMG1FDTolR+CQL3Z5JlefK8NspqUKZUmbMpaCWIqGOiFE5NTrDCKlOca6eERBBQa3VlfCz5ZXkCgmJya2sG/x6oMzD93PpHYVxvw6cy5C/Tc22cVz79rcZs3FaUtjzbnvWDa6BfMHU7QUNP+9O9T2Xyhl6hRfBWK6oO1i97mSvyiS5HOUBcmUXgIXyovfsVrLKKqnsCq7mabSk8ck9lhWeAXpozzn9naijfU3oEdsVlef2doty1DwZ3eOAe0GXKM9Du3oRVis7vA+KbW2Kf9eVGzqCByMreooqrgVR5h1D7n0+z7N4n5ci3k7V+qd07IAHG1M7C8h6HQ0FmD0EM9SThiurUjd4kju++teHwVMjAv1OYmhMJP1LRl+vKB6bJ1R3uRvP8fuyfjQPbpC3O0j1up89krByY1H8WWuxUQm9t6zl2Davm+Ztfqg+8vdqKZimDWaeUfZ7zemddD1Ix0+wy61cX7/Le6akXWuWr1tte3uwhYT1VABtGoQ6dfLoUrI0A3nKjji5Jn233OF2k6uEFa11nA/W2uE6Wz2aLz2nTi4AiDIVkxjGJA+mYOJt4Sk9/YDuD9XX5nlg/CQCjzqChLevbfIQBoPMlsbMvfxjOTbX0TwvpyT9Lbq+U4aPUUrJjSKM35brhIys+xZQ5wpOM8o8oxblfat8Osq7tcO+ScgybOHRR6xcdLLZ3jwaRIWzKSrVCQAnzZRbE1JS4yBmcFL5UHV/9FaWn1uExuVTm4d+xB0f/YUDG5333lq/r6FB4tD83HBjVn4+eCtGc50+eA1ItAzhfgjGXhldlKcsBo9h3zbl4SZn1DqH7Wqk0xrNuFrnQD+OwBBj1yeIzWlBC/Uej+p4rk9ZztLqtFdTW55L65yCWPfaPZ8pPUkaNlA563Za0hYEy4iyAUmffa9lFFKDRIzmEA2cFkEnCl60q/21MzV6itvJFg2k3PBtUenKBXbqrc0LcEcTUnh8fTUJlWLvjOHDza6y80RndsM5MSRjcewiM3pd8Y8f5t/zfkZRj/Np0jSqKWHHYlQiEX+MCiaNHEPYAKDHipKTGwK6AjwlPDwwvn7qMWjzOKeMdyyZWe4BPOp1Jz+4Ra9vSvUwHqwG3KT4OcTIhInZZhItb97gBt8Abgr0G1wF5yjRAed7mvIcdRC6DF/OKTMw6R7CSz3PATk4rX1Rvqg31/sz3F4IKA68+kE/v0A8zxmiILd3PhrZE17ehPfH3OlvAS/Pf36APOiU5+p9bqEuk4Ztzxnm2VRqQdXQ7fM8Y67C8FNeJvF1hb1+MhioQmDMVXJN7rWcYkp07kO3nwsMRgq27G8D3/tg/971f0uIkiP7/a3r/qfC4XnUHK2+41wb95EzhuL6HOjGWB+rpDFLxxtxZRO+G1D4//XLPfvJHwRvr9WMa8o5pjwfy7Pf5oBju1XByJhfCK8gl3tJ/ee8a3TKa9axJuR5WZntCg9X5U9GrEDyLI5eRUb7LsozBRua93GHDBUC5fuE+tSUIAzLxyjPpvs20Mk81weNBI8Eb/welC3eDgZ4p+KuO/VSfBbFWLoTUVhKCfWp5X8UpbR4VMaZ6x7WoU5rjinBGACSho1WwY5KspowK4xEKbMoeCojl4SUZzcKLaowL7NEQJIc55G/qWALFUDo2sqkyk7zggkh162PbDkvrV/G08QIA/61ed0swApRA2bz1CXWHMs6bikn9wIVQZaFt6/DSI7iV3YDC+m3GS40/IO440Vs/5HPnlZjAPxsD9ucPQ5dt7n/SsM1uzCrh3RSpeJkXjcuNo9zywSrAokSKlfs9zsAQJ42qLtnVxx3a5NoZV2MHVjfDRqv3fO9KSX3KF4ios1jN6JhWRluUALI/AoC4FKq5OvUwZn3Mu45Tzq3+1ACiRKen3fYbESUZPOnUgZNGrVhX9TjXYXCtY1HKcC0sTkmDaFE2CbhkqvmczcFrIUQZfVwHw2FquYpT7o/SO502T9cWY6Wu76ox3tFRaLGq1rqNfEgrJ5P1cDGIzoAJDWUEaOAyE8ux3yaMgBNSeaeZeqBXSs2eULOGzBXz5me1ECdQOBSsYf0rcwF+1mMd7hWce0KjLBNh3F6yXXyfeEqCMJ/m6HuIbZ4VJ8lAmUx2UkpYVJDMILsTbUSQBpJTnO5tqWjYfQXNeiaw/oKO9S7NTmP1HIejO+3Xez78IBvy/G+pYLitco9wX+n9tT3ge8hkxjr526en24JgVB1m+hXyHhu99+GPYeXe9CxVnbfaORPTrfa9yOwp1ipauRj/a6loBJhO2WhcObW6FLLIGtetnAzSQSbKcl7Zoi310g+dlpuSOvTNy2C1G+/f0CtjOenneA2MXKSFB9p0jzdzNiXgsqETKwpXAJdtYI3c9hqVEwb9/PGvOEwlrt2VBh9sqPli78Hu7O9fmMAz8pSWCuFxaA43IEGa7PM+Fal/jtlrF2T9xlEFWXciRfzr2kN7D5rjXbGk79IIDVkHYtbOAwSelqXmpc4I0ROGQajVkbOAY21yliSzAmhp1no90gTBwUHUYt8sJ8LZipCvyhdIvSu8FWbjdBZu/0enAib9+8wf/6CL5+/4v7dg9PwiQgFD/h9epZy93tMkDF9+utvPPz7X7gD8B8wHtDo/oXxhSGAlO+ApQ/SZ+3LoER3g0VqBRn9csl8buhqdMsNbnAt3BToN7gMAr3UeX+vbUS26YWDQ+mX8Iwdkby4Nv4Ota00ayCvBoHLa5D+LlQKMOa1ARrR9Gk4vP9QMZTd/xeA/76wTcfgIKkeqKKX4sSE0sLgixChKdLFC52ZPef5vBfl91yKC9kSpU4YZLj09qvQr9SKuRb1PJ9Ryqy5jQyjA9WCl/fvBj8z8PD5PeFS1uVa+BFm/KFYIG9TF2CCZr20wuCcKuO6MKun59cvl9f8QliqbS9A2CucX68FP0o7LoGRbvlZ4CKDl5VHX2Qw852QxTDvSmm7C2CCwEEEFtRJLsSr08L9BkFPJwwNz3/VGUH2HIUqGPURoHsprJTo/cDNc1I1ZBbOnUcpqrWDlbbbGQ8AUFWRStdWESDRfRLlkHZbhDCpU8SLYtvowQTmWfoQKEoCNN60CKLEQzdESoIJcJIYfCalVWsR+na2Z0UwW9QQtKji6qBQhuEeOOaUHjkbKhWcVEgHwZ/jiYy25SZb8jICg+XeztSPMdkjrW2mYwsyKWfSuLuw0hVu+Dzlhb5G9RBw1MP7bFgR2o6Xx9W+5AWbIG+9+JB5MwreSBTGpRTs9zsQEe7uH7B7fsZut1tt18FumDEy1IBEX0pEmKZJIxEApNruPGVMU8Y89zkpo/Le0EvaEc+HjrBtDE0ULysVgJpRugq2JZe3KrXVfYgScH+/hUS+tb0Dks+6Vg39nkGm1CXdU9R6hQjY7WbcbXNbC9T8rExxbQrpliJC1r33vzPoNyOT1jH3aiLDtSoi2KuERx9QaXc35iQh1dsOInfNM1LCmKuQe5Aas41rMDji2C5tQ2y/hIwvkpoDaWi7rGOutfHVc/REb9Wnbu9FWOh0hH66cGESuQHKqZM1RiCpmmLCDLEAduU5ClCThVNufR6bxdonCcg8KEPW+hWLiItheOfc3h+Usfwj4Wehcr8Fn/194BTtenqErqH42/Ot/vWaFmcr2Yft2+fVOD6WAKyQFmeB9biRTMP/zChVFNdCC8lZkVNGqXOntDtUuqf4kYMTa/sJQfTzE5pxlvWVWVIgaVwgWHqYKWfZX9WjuECVmbxmunAKC9LjS9Do4xbedJrfDWebw9qOxBO9EgFV6ACAPKz73uTyBybCoekRZ53t8/HPKXd9MDF1kaQQ7o/9735TG49WY/8Gjb+6udHoOKiBrOEtqQHHmOLEqrC1VRnIetYLnWNGfowpTzD6zgaipZ/S9LVokb0kjRMwh3bw0FZADNI2963dz6WAv3zFw/t3Qo9WxmaagAfC/Pgk3uoAPvzrd3z570fUWrH983e8++sjHpnxUIGnEKr/2I7sZ3ZlUE6X79xO8/5Td/0b/KhwU6Df4G1hZHgWGvRBAHSiqMTCPDvjCvZDg+KDLoRbb8eaUGUNThEpdoD/Bslt/gd6pfi/Afx/+v7fEKW5hW9/S+X5MThOAl9Tnv1LICQkaCh3zetW9+Khs9/P2O+N0Z9FaJkTkv55yHaIICd6S5VaUVx5HnKeW+h2tDB6Hdl0YNxHIuJnYQ3Ph39ej44DD99/BFIqko/x92F4+ai99rhfW15gDr4hUKj6MqhXMuiaPdoYLxqZlOPgipCfBn6c/fKf1IZryznkfX6sPBH02PcX9mDx+nnlnRS0n/neQmB3rM6ggLgOXk8we0kr+mdXTJPEpSBc2LhgxcVNboRqAhbBhUXeKfu9CO1CsiFShQOCcoeZga9NUEX3ScMri3cngyXecmy3CfuC0EgU57FXUpEp02kr7S5PoiCbHkKrKMjforKXgPlJvYHvN0JDptTlUm441XJU6V9KAVkudEoq7KogVk+kUl251tsDmJc4L8KM9lXqvSrixEqA5Qk0F2AGgYp6uBABGlGphaBv89eMFpzXqcGAwvHTGiBjY34pDC4FXCECKwJqmaUY9XgHDSHdXUjX0zSsZ9/JZUHaz0vWz8qjjNJTd0dIvVgb6XPdo2HzqGpoMhfJyJzUDaj51ZryU7yGkRC8mUVSuHt+xrzfI282+PCvPzA/7/D89KR5vWVtxHZ724IA1XJmq5jUw/ZDf7c5SJ3y3A1rNHS8G5CzoD0n7Q9X/2TWsh1RzWADceyZMe920gJVMiSdH9XWH0mu1VolTKhEOFDDlJSAzKjzjDRNSFPGvNuD93tRnBNjttzZAFAYtRYdF90vLHdoHF8G7jabTiVgHuqliOBY+t1wZnSa9ZVJRkWiRojAWtrPbWDYFPjk14wvFd9Me5+BLLlNC4qPLRu+KgcJfpydDHBBLYQpJ7j7exElM4iQEnfvSUS3KtHX5hn7/R5FPdBtjMXmxvaWFeDh8wgEXcnKPbLDtf3u6uHl3m/R50hyvhObZ2UFqbLIleilf79vejwPLeDtgWRMwRHD97aLjWaHItHPyVGu0HxOvxWMPOevBv0Z42RCWj4FnDX1/2Ewyl6ve5sWV9p1oUNWXnb6ZanEtZQcSenYnGQ/kTNOjJPWFNNLDqaXO7DSdKWIMtoik5RalHYwTqigFMJ2stDpsk/RlDFz74luteacnbaVP8Y0mQJcije6wgypnvXvHUT58vXTF2lxTtiAsFeDoufnZ1SIB/GUs0YsEbwW3fu7jq6Mg7/g2JWt1C+j7edrpfBwPf5uhrOhzqBEB4CagHvW40zpEAZ6T3UrM06YFcV3q7v9Lyey/uYWVcAg0vzRzHAg34erRkdHYrGVPOKjXR9qN/pr6Ikp0atGeTKnsUgDVi5IyH7cm5EHGNjPeyknZyU3mgGxpH2B5y1vSnSpN1P2gbMzer+fnS6aHxnEn3WcCI+lgL48Yvtw7+uSEuHuw3uUMiPnjKe//sa7P37D038/4t2//6VpaIDH4Vy1sSdbwzagPh+Nr2GMmweHc5vIona1ey2iEvVDeQbcPNFv8BK4KdBvcDFYqDVgfeNZWDodUpjHa7ZJdif4AaIA7QBfHLWN538ziEQkQQ5nO1ALgD/Ariwn9Mr1uijt28Ghc4XG70sa1T8oPB+DZ7rwx6zR9S9Twlw5hFzfo85FD3uScO95kj9KzuzHGdSU5wWl6PcqoTJFgGcWiZZ30AiK1oVj0+Gtg7ff4FeAcYYdYkX+4TB28427HYPRCRPC3X513jGge8VVhwa7UJZx/v4+tu0XmR2rsBpy+hz4hZbVCJfkPI+wJoL60cCF46OgxSQK43QZhED9S2vXrpw0PwCTPQq6Fj1hVSqol2MKe1PEk+Waq/pszGksy4q8POv3WuhCcEWtCfzEwIPsfqW2hABNsRdErty8zk2WwhR+EEn4bikAtAVifuRog0tkKaF6JYuFfubK7vkZjQpEr0TIKlyq6lErxwc3r3k1DKjEoMpBFGnNZ5XBrnueR08R6w9QAQu1rmdWp/BWaRppG0d+yYvSsV7ySYOHy9hiBnhQZrsHLmzIR57N6l5fAxzO3TXw2lYP5dZfL/7cpba2IHh5+zwY+Fa0tSK4Nq9+M+Kw9SKK9QQ1tti3aAxEhDyExTfFbeSjmpeSROMSQ4YqCtDQDyJVxnJ1gSJA3dpFRVNGp76tkXtzb2hEflrpGLZ2RVzI+iSNMlaKhBdHSmAI79aiPQCUJ22ztjFnVVBTU/Sa5BgJzBJ+vXDMr9463rXFDFliCofKyCl7RDKTqUp0id5DiQzvSXPLh/kb6zGeFMB6uPyVtdmMuVvOb4+J0Sx/4NjWOlJq/eJaMFdG5YKcGJmzvhvWrDaMq3ih11pFOG+yFBM2W4fR1rjhFMP2dDFQH3EuRjno8aJzrVZtp0TsmHISow9iJM19XpMo0c0DD7rHN//y1tiYek0E9LonrzVVhQtOA9Hair8cjr/9vQjUNe7iZyKY14RQ54zT96fRzoPx4Lrm3UtAZ/oLaFhT/oY+AAAgAElEQVTbx69vwzEI9F4jNtBW65K+ONqC0EzW/W1XCrZTO5O6aDwElxum3IydmBkZQh/a3m7vtyG0SJrUFI2sKtUaugKpI0Hyg2eIAmbWHu5IFKIGFn1lLhVTzrZdd+krIg7WR/a8cTpnZ7CTdrG7BlqZ4jnNjBly3uyJsAuPjm1uve6pjpHVoyPf2zVLdNVS8Rxj+RY4JBm3xHpuD3zPwuhgLNvoBW7tiXhrtNzSE73qPDcaiMPcj1ivHh0otl0iKdhSsbLjztmd/W7Ypr+JkN8x9l8Zm5wwV+BrKahfH/Hw/gEgwpQSioaCJxA2vxM+//0Jv/3rdzADU5hJDxX42jex4RC6NsYBZmiY/Na+bnzsWmSnQpk3uMG3hJsC/QYXwvpJNAps1ug0D1e2dh1o8rNDVXN/eCenUBpjZAIif+FAaeOBshCarFwffzOA+//rf+Lx//0/IWikwO8A/hreSWje5z8qrGFrPOOOvu9MuYV101B7pWDeS6i5qoIXC9+Ws+Z2Myt/ZhHwkcyNWgvqXITx1lCZtRYNl6TjRSRyCCag1p7Yxfo4Y7h+Hql5HePwdmzrz8IQvxR+BvIoMnyXwY83ii9s0Rt3qDdw5eYsdG29vC50O/GSMN66wVzy/rU6vGVBr1TOd6/ox1sBx+BbDt85yvLL29Ns5q8y6qPuA3SkBfH8PQVOdxFQoMIraAhHW2fU1n/cB3oFy3ntuHTNH6OPXpOJHxUf58MGzZzQRIJjztg2WpvfJ0dWSgmFC9ZABB5N0FOgtN6TJCVKINSvaGU9EJjJlULMDH6yklYUF6G/zeNAJFn8TMDD2siRK9bLkyjM05146tQnyUGZ77N6r2qUqh0DE1SZR+7panSrKTkJkDOBlI50FiVEKokKUQ7tDt1KmTTfoL3CsMOqyc1UUObSORW7qReWeT3HiEzSFlofVeqfa/OyeaTImUV+1XKt94PRnln+5v7RSxf4ocViQjQCcE+ozw3fq2vrOnJLaAUTcAbiv1RR4pog28KZ29i0/PZNaU1qjEBJvHxKKfjy+XMT7pHxp+HdrgNNmAqo8YdUtxBWm4e5pBCg5T5n7zBEmWnlkr0vX8oMn7PMsqmakQAzgTYZNsMqs6ZOaMrZWmaZy9utlyuh3ZMY7Ziy2cZOha5lt8PMBaAEET8VgEV5zmCEIGRKkyV/H1DFvtFcDCSWiARJBa6WEmwzWeh3xTXZHqbKda3F9o+cNSe5KTB0HRp+a63gUtwD3yZQ1QVlyg5T3idL7qZ0ZeWKnMjxl1JuYw9GThs1urD85QkFBaUWVGbkChAlcGbnnUEmB5cIGrVWHU876whELRJB2MaUZ345HRON5lOYwwutvO6VlWWvqUX+kCUNAqvXZ0oVXMhz1lNV3l734nGtm5LEhqRi3BVjE7hfd4aYFyDBXv2ejhENjm2EhyRa653f6Of+hS26HA71Ibb/9IY/9uqQ/Of7wTEJ5OVwzhQ+pjwf5Z8ny/K9azDwO7GnNOOevq7NNCmdKkeDtfVuswHAmDU1xVzmM1q3pIXMsKewnDG2FxWNHrRJ4vErqVJ0/1HRsoTUTt3+I5FhqhgOkURmSUSY5xbhhQi4U4V9qS2WDTOjKp4miCIdYKRJjKRKqdhsJuzm4gr5qmdMzpLGSOgAoUe9QVpOD0q8GDp4bayVHg3XuH/7KmCIUQAD2LL8dfvJyJCZUdwKcUjDd8NlAg/ta8rq2PaYajWC5VSv4X0rpXENsQV9fas0c9dOQTiboSKcc5FPpR/MYNfPEzP4XZSqtSl9v5tF9mURhkxGbkM+6fzz6C9Wh9L/xKTRlCoKgLv8HkxfnAbd5Iwv+x3u+R77ecZmmvycZwDzR5mBn//7Ee/++A0VwDsGPgN4pOV8G/HTOBPLhc4SJiFL2pqDc8/3slcgYoCFwebNI/0G58BNgf4rQtgrRnnISwgxGpgmD9fuTL2EJDMmdr3w9d8U73kjafnoAX7oFfbYVchpwrv/9b/w8X//bwASpt3bovAb5KD+C9fDyI8eU8C0PGsjyTAQAWzlyLHa8si0MEQSLsWYZCNP7H/5NuWMKU+YNhM2m63kimNgnvfYVwkvNxfJVV5VEGMHnwh5VHBBMk8qANQCqPK9lorC5nku3ueFWb00lMAZCDE4wcDqEQWfi3pSo/W8f93DwoxjgHPn0Y/Hrn1bONXvy1fjsTcWeQXJIhO05jhJbnN67XdgMi7/3a+zkeAfO9Ffe615Qm2vfUkp12h3D0kszgVXRgxFHGiLMQGRmWqKBXYBtAlOwza3+tsEaj6mYz+6s8eYNJk8zrsqU2KMj+9Lw/zrOLu1zxEJ//Bt5EVeES/FzatZMrwNXOtpfg4wLMDoIIJYQcmhIfJpS63MVs5KKL5TY03kynOgCTbGgIV5LPfIMMYlzMydD3G3vE/Nhe88VWgg1te3kDAQSgZR2Nhc4KlnlnueE0lqHRWciFfpofr7asYxlXyVBDwz8KBzYEfeHnANgpwQXhnWZvPWFYWQeNwS6hMj3UmYd7pbboxRie3CKjb6ICiP9wBSVQEpdUdwF6oerJ7D6kcTzoYonhuntCmmmEX4ypbZUvEcHHacJ7KxAcGV2+ydKqpEghOh5lkfBUg+ro7frsHDuFEne5LXqoRzZwtjafNlAB0fL8sJr4Z7rypcszOade75ePlnC0XJAPiRG31/ZN9Y87YfaYmunYjzY6VcFu9o97hyNIf5z6bMJViOSCL1dk6QqAdD2NeRNiPE+aB1ab7LbrLpy9k8ukH9Wgz0hHuyGz8VeJlxH2zKczh+aZORKCNR0nkpSkzKWZUCYszBlYFSHC/MjJSHWF7DnCvzDI4GOjpdxRigqJLAPL5DFAhpRcd/ERKYaqsfakSZjAxLzdih2zfX55HkGo0GCf3a6dDNsaQ2oo3+bIoiL4IZpUpo4vGYaeMhOKCaQCT8ry4SVC6YZ8nrmlMCsfWZ3BssEYmgXhXwQoeKItpD4VOrj4IHmAv0h7W0WB82l4LRVUrB8GDl2ViWz8WU3GihfybUu1jAy72m28S+MbQw/u33QQh8Qds3X7tFh5iFYxWxhI7WXxucpzRfU228lO88Fw5HVzn+zmu2MPb+kjKvaXt89yVwbt2RPT1U90hSnFfqyNjGu5r6gyzKi+z4ObGkmvEyxnZJWTzst1aq0Zi8uCfyzHn1/NcnJPiFGjbJu7Xbf0xOSm5AJbcarVm07XafGWASQ6oCxkQqd80ZBDuzJJXMlGIamQZmDGt4X/u0bnhzvW3t96Hp1HBlh4PRJn076MQ+ZoaDBMKeoOln5EWjqWI5rWGt/jYnCNnk0HAyuPvetdz4B9h5LfcqEAzHgme40aROlxp/0ua+iZXt/HSaydrqmzsjFAkrOeIl4rPz2r8EFFcm5o90CCvNYtFeMqVGu3E4dW2t5aTGJYR7EL4SkJhRuOJus8Xj5y94/9tv2M+fsJl+AwDM8ydMv38AffyMrwR8/fgJ/+NDwn8+125S+PgY3omEL6K2c+hUEVNsYp0j5OO02n2ro7IaKJDTfy7HOzDJD9E4L91jb/D94Lxz6HXhpkD/xcA2sO732jOHgEOIMNvejm1SxgBaCLtaD8/yA9cT4OFQaji0RIghAtFRwIruwAoH4pEqIxGy9lxkmK3vn/+f/7sr508wCpoi/Q8t8zU8zy/Z20flOYVTzHAH/aRQdkILnUaEQdgcwuWhEYZTnnB3d4/tdoPtZivW8POM3W6H5+c9WBXntQQvl0QeCjD2Syz6qwj2db7MtWro9uoGGB4KzhrCUmYkShIkPF+ttYXT8Xlw6GhWUowNH2m4Mz55GDj8fz38nAf6Gqu6bk942Mryovo64Sh7LmoXfjF6RSfCyLzC7+gxaATyOWRx4CNeCWJHrwC6vkUv6gctGbS2fgip44Cpq8yE/Gak1XmqGDri71iH/2hML3zfC3udjXmK80xmr+pFpA824dqH708daiOjOG7sl2403xBeryk9y3vVPslXvdVacAWz9Fr9P6ecNeX5y+sXy3rzf3NDuU6JuVLLmUK/c9q3KsQLClQAyPqlmqBeH0sMpLXXx2uhIeOtMVd1WlP0owlwYpmnRLDHKevzx6/b7rr3aXgiPrdtwhxAjQWSXwOA9EEkDPWT0GLlUwG9lydSMs9lgErtGpBz9q3Xqm+KYhG02AucEvITi4JkR0DSPOmQcJQMoNaiip+ghFHBIquBJDMwlyJ1P6ugaQ8RruysGZbvV/eTnXqU3qnnKrNoBOLZPxFMcZ2IOoGadbLlim75jMOGbT0VzHoew/68IDj70+hrDaXgAr0YbhqawZcsIpN49XJVr83Ae5DlOrT6TUhIAFdIfmFrE1kYSwpKTimJawVKhZQuZZona8pZhFmGx3BGN2V9T+WaYtbw4eNiUaFMsa3jCw58YtjQ+THGPm08X8/VNBiNO6wP58LojbvX+b+Zsgrzk9djNIJ5DxERss5vwXfChCS0gjOVwTAgCOGdPvDuipLaBYGs+1OS/K2Woz4qxWMvjZ+iJOvV8GAey2UuDecwIxXIBK2EtKtIG0LR2WYi5vKkntV30uY0ZXCWNes5Nyu8rvETBNR59nleqnoSVoDxjGlKSJyx2xcQGBa0gavt/0mV+rpukuKyKK2t+Gf1AGwGBIAbVIZvjrU46Da/I23Gbe24/ALt9arz2pTY3r7BKCZLKA7MpXkVyhCKgqgmQq0Z4IpEYnKTSZVIvMXMO1SekbmiUMKUBB8bSqiUcJ8TKhOK1l+qeFpWsF7TcQ6Cf2YJ+R5nEgfcLBUmSy/z8ZqHWA1/dt3WecpZFEdqPD/KKtyIhsWcnjU0vT/HoW102OP8rcHX0Lkv2KEA/Xh9DTqWO8KhpxrOZv1tyvPIptwN7zGAmYCtjqsp203hOXbpMpX1+c8eot0PzgTyE69r4zo1dRoufb5j+xaMYHziVAkvg1VDl6GWYy1q8Te4+zwNTanX821SnuQ6B7bTBgCZAyoSZVCWeoum5QFsX9d9Xs+YwnIO1VJ0p28RlaYQ8QNEmCYxysxs57rcmpUmJE2DMmXxXXaeIQe6UsHyk1fd2/WI094pxUbiaMQsaZPaMcLYEIE2oooR+pexrxXvHu7wpPLTx90eDODD/T1SBraThPmu88gHkM9za0ZnTBiJUUe/IPPYPsrhMxyPR0G2OxlIDnufKdBp3KpMSB/PX9IopSmJo5amgCHtozt9sfowK18ihmhVzz84Pe+rjpoXNYHBRemiyuGsgcjBkyhnyYgcVKRKqqAXfUbndAbSOoNsk1u9A5b0/zY3Yzvts9N7RBRpW/fqmCZnpycxxV7prMqM7aRphZJJt2QQkv5OSXA3fXjA9PmrGBso7goR0qdPuP/tA7789Tfe//kHpuk3gBnbzQTaz6gAHj8W3AN4hAQN+wrgHQiPih8bMMEoA1WNGrQ/OZGvIU8EFlEW+Q2jyRhCjGcAOt+6KT7gvHcwXIfXVqTfPNrfDpzGxOWn5EvH5aZA/0VhcVge/+kwKqrM+vzwhsMLovpSaMLRSHYdWyq8upiOLTA+8gyvfpcn9xCr3Q1Eef4fAH9CvM43kFCXL/E8d3iFDX396FaIHedwgQzXtHw+AWaB2QhbsT6rHDzE9bcT5naYdox46yar5KMRfuz/KtuBG4lCqJIsEI0vwsxwd+B1juLx4rpvYPByQcjAGesU5mFRj2v84Hid2xydfwQeKN/TPXoVMm1lf3zF0i8C6vp/Phw/Iwamr+OwrL5RCBeEATz8Ro+p7hr173cQ7o3vew5fu7aySYjwZCjcBTvfRwh4gx8T3tLzHDgSctQZ+F5Q1m6/3Tw1JdZa204Za15UT1fuacarUw58RzBljP2KsNYHGq6JolyepvcE/qL00hdG+tALbkYwT3Ur0/fVBKHfYj2ENo90X6yIEZECv0BNiJNSwkbzP1dmEUgWpT0phDlH3C/bZ3dC7A6fRTyr93b2AJjLzOa6gfdp+jR0dqAzXYEY8iOvTlFTrFUCEbtgCjyENVUPZqii1pXOKlw0UzHU1Bpe4XS208uVnSZOVlYiV2a67021cm1MuR3GQdhK4VOEcLomqqoledwpDsDaAWyVn7m8Tq3Za1fpyAIJ+tjnfVcnUYsLCoBygkVNAOBCScdPJ7AzIS0B3KebirwQsxihRC/3JTSqhojUyyusDgpj181km1faL13QDFkfIIgDNNm8WjI/ZP1TAlsMObQtYikCU6oRAZQz6qyx423ALSf6QKO1cSggC3LLHO4PTJneoWG+IuDSHl3OnYBDLA1qpJ9tvReOBbU90faStegHFeLRJQoSWceiSBfkVDASFxljNQaoYCQwCp41FGoFF4CzRNQXwX5FgkQ+SNQE9pTYTGJAzChIroiusukoHhpeIn7OBTHKySElmwmwg6J9/UXfyyR8uxh6uMGQ7WddY34+znohvA/fBAOv2acLpR6haZthVWXAU+dEqGjh3aMnZTOWCa1hnOjjFX2/mv5727kz7kbHn3pJDS99//xyTtHFL27K4iL7t5yS76s2r6acnNapNfRImepstE3OqmyPNFk7Awmkxmg9HaqUZtsOdR+ncI8othKeuqJomiDZqKM80xh8SUVJKSGDQGoFnJMYCFhqFS5GLwC7/Szt5AQiMYhMwVgzU0JxJfCKTOPKKf9yHivMNQp/4VakT5b1SsMTTHmeMWVToGdPy0IASOlV+3RZD4lXcjUyLcqTmVU5rNQy67CFMny2kI07tf6oR4ZEhfLYLa0PVt4pLDmt1yFhgclDCl+n188BZuzmPbKm2Mkpt/NeyDAwgN1TwWZLuH/3gK9fH5Gd3iE8EnAPWZtF0xd8/vgZmfQeS87zdw2Nuq7CqlJUxflK1m8OTiwAkqefCfOCaNln0meMWaM2HsfgJdFAbvBjQFSeXwU3BfoNfkTwkHyMF21Stg0KMwkNRUKoXHthntTqb8Xt82j1A+UxbruHX5UXP4PwB0RR/lnv/AXgX/ix8p2PxMkShPBj4iGvqBzyTuANyOy9TDTceinuceLvdEIYPUGlYBf6tOatEAowkYsx16s9uBhsDr0Rq/AC+NHacy38GATK2IqDrTJ+55LCz3j4241mR5ZeAD/mfDsnF7DtCcvr4Tsd3fmU2LfSjKjXqgemb62WU3Pm7Pn3w8FLd8e1N19hrp0nsXo1+J6r4y3qPneXcErqGyHgkGJ/XdEZ4ML2rdF5NNy/rsvrb70V+tbGsXmOBgHiB/PUNA/adQE+vU+uWO/qUQGU03tk2yW70aPvmSrE4CCCL7UEjwxGJkgeSFO85IycE6Y8uSClzAVT3WCeZ81N3fdx7PmCarRNfQX5zAya9fUMN4DyREZBCKM6Zm+710uhHSZ087r0vnnn2iFSq+bVVu9fE8cSQEhBYGftrA33Wq6HfFRhnZHMVX+YEtfkTZWhuZvFKCF6nUShoV4YsThguRewSqRoSwtQFwLAswQU3GRgcRDbV/OoaWf12vPXwJg6tEVV0AgNVfCWNSezuMPpbDejDm0RqXC1cnU8u7Gw5d7mhlFSYTvIcKqR2gANQSroS2pUQgTUIvVRbkple78pLyH5pdHmZ7HcsQt8yYVaLJqBYrpCvdu44/nKU0G+n5y/S6awt2gSm6nz3gIBZbd3YWWtMo+ThhYnVRDUKkk7LMe44ZVE3QDzOgMI6Y5QnpuHNwHNiEQtz8o8wxQlAFTBoQoIhkfMMHxvKINBsBhpDMnZPs8yjluNRKBIb8pdN7Rp7wEtzG7kVavPh0ZlmnykziVEp0gAF01rJus0s+5MLKGOUyIwVVQ27zHZEzJkLkwQRTlXSYcyqxcZsSh7OMn1ykn2aTXOmIFmixoEzGshnMEthLwpvGxvOaaEIVeek4bUreBiRiU1yI5MbrBeho3/NfCNycdvAC/riTiCMB4A2LjIOg38EZrAuIwFvDmM/TvGjV0ix3sdGOt9Kb93yIB1+dypgi5bH+e289z2LcrXx3MU98VvQWktP2UfKLUip4TtNGFfiir8ItUeaF2TKy76rp6tlZElHyUmpYP2tXSdn/V82CitZZFdJJy7tClG3jCjz9YSMy6R33MVj9usF3LKTkfXKmQFtJ91LnreNDxvc8vRzqwRTgjI0wSuLU1llLkyL1pzYBWR0jQ9uTaSVxHbx/hHf28YY39nYK4OGVtJXvmEnFWJnjKmnDXvPDwCEDMLEmukV5RyII22RuTjxsyYmSXSVa0+56zvhhM2WnzgpSx1nxsLgoa5eGRdeiVhfiMY/q3Q39YfMBaOGct9xiinoX3Kcwht2ujViRIKV2xYZPz7ssfEG5SvT6hoxoKk5ew+fsb29w9IlFBKwbYyvmRynuW+suQ+B/AkyxAE4AMDn52nYZ8kbc41/rJWfc9Cs6sQkIzgb8xRj38zzByf+wHgRzHCv8Hrwk2BfoNXgWhd/1rUKgGrOU6j8EyEhVpveOIM0tIfva657a2/h1YBwH+vKvO1QQ4S11fDWq3fzuBJYkg2P+whh1aihJQlSKgJnUqRUEalFIze6F4HEShnDVMZcqDbQWrjZwRPbYSPS5ViG6kn0ppC7Rzm48c5ZP9JEIXzg3/ayrfrBSFjrX2pHUV8filqMbtkvw7/tjyz1M3EbwTO1XzfuXxIkX32u6PZLinRTP3uanPLvRLX4NTgdZX3u0c0NloXBA7E+ZKHPw6HuM5r4EaP/+PhAmrmm8HKLntdOcGC2BWDciPU9fq9XyN9zsJzkCqtebjwcP3loMKt88nZw30Ycfoeriw3j9GzWrSy9SHsmSAdS1MYkQjAuueZ1TPEfkrLk4aKd36iiBKTy0IMd7KdjosBKY2WVcPQAvAEr5e8P00Y43SzK5Ss3CgIE8UZS8FA5SDrCbhlMy6IQjsxJM2UkBKpwaqsh8rmTaV10YABD8Ot9RhOwZriykI39oorAkQRGvDvSvkojDKaffCYkboqSHvDAT8B2+jmVffz3J3Dnmtqm4tJnQs2rKVQ0gy4jd+klW4ZTSLpCqoKZl3Aa4+vGCDLZcG/TR2zGOrTS8j4mPHDopzwLNnE1+mQKOk410ankXi2SRhvDVVLGlpT17ELO9GEvfy0F/5vmwD1vCdm+V4qKDcFqoWc3z8+S87yhkGZl9XqMi/0mNIp+XPtPQY/94HYye+Kv3bj/IJ0wPtBXTQ0+6yyzQouyBQt1cfMctw3r1vgqJtZR5Mv929JaWc53JsynmzN6rypqACTZQjWNTuBKSPVrOsggdIeiLgjkrC2CQAqChJSFS94oiwGGSDMrEp4jYpBzE3hAKPLwxzTPS96+ptSw58ZwBUXYa+J+36tjKL4qFWF/MELfYHUcNT87DBsIwOMfT//7LsG9hCBsOUVjqkRx1akMM5dqga0s051Nk6/9bzaP2DwviMcnzdvCddxI629vLjSl6ZPOc2jPDnYnaY2OWEuRW1+uHNKtdKTkkuecqOjfYOsRvdwApbyh6E9puiLBkIt1U9dbEuyVcqzuVYUWwF6zrgBkp+VDJQiSt+U5WkmD0lvhfrasyNNcnV0uLYu99snOR56Gn7Jx6yBr/NhPXs9a+8eKO8wjxJaFBBJWn8iiVQlynHBIYqeUVTlBGxkLNQmTf6iDNnSfwLDZ1O01wE3y67JDhlXRAzb3vD0svVKZFF8qNFk4Z7Va3U2qifUOtCdkr4qeVSjHTO2tQI5ofITGOJt/jXy5MwoqZkycn3CTG1sKjMyCPcMPILxwMCTNoMZ+ICmRD+EjBgVYLEz2Ppc2YKMTiOly75fYpcb/EpwU6Df4FVg4Ynx2uX7gSaCjKpCHqex/LCq47aL2KJx710T99j1tT2esH4CvDYx+9oWS81+f0nARmCGe6F3tJcRaYPQKCmBSABQGQUFtRTMpaIUC8mmOcxUUGJEI6WEHISsLn8rkdxWxprNI6OR4etepdx9O4Y9pbF/MPjxWnQaRiyP4imDQ8T0W/b5wvUj1ODJFq3dd+Eys8+tH380X6eFvv+/oLheSQ4o/7iYH3zykAl7wFntYVhY3fh+Y+CHQpy7a2zKKfiBjGFPAB35dWk5L+/0sRJeWsP3GJKTdeoDhdSb7IXHP618G++bXCV6BiyEJIOA6lSzDgkMjNlei2QDXnqmpHE+0uuvpbjKj4uoLRjdSttX3qDhHOmEUyf6QIsvp4GxQ9KspVWFjlnDHwNGLycVePV9KB/nk+V3uNe9sfM81wYTqXepWW4mwiYlyYVO5okq3h+1zCLMVEUsAe7Nymjhza29iTTfpKqUrM60zSACyrMqWdWD3HgEFykZ32AhyA0Psyw4MuGLy50sx7qtBW2bKQy4ao73hmfxopB2mMeS1cW1748ppQmiPCfNbZxS0jnZCHFxNqVuLZIqmRgMroTlaSVetcQEFNaITwBYBIhJc3yWnfBOpuRq0bgthLl5mZC3m2sFaw5jqlXDaBretCXjBrb42eh5IdjZhX0EO7/bykzIqChBYD6sxbBvdfeGen1lugVD2Hic7hAlKgE+vqVUyXkaxo+55bxOKYFq9KgK4Y1D7Va30Tc2HzZ5kt5qDvSUU9fXnNs864Wi8r1WzWhMpIbH5knPbS34fKzmeAxOmqKhNuMOGT8TPPf1MTGwA+puJ/v2QwbVhJQzuFTM8x5cKngn42C5aCmbR76UUTUiA6OokiJ3aRMYMypmJGyc2iIA+UEMr+evs855aSuVRpMxzMO8SI9McM5tvA0XxTzj1dDAlBR5SgG7UVAtkLKsuXnu5Q7+XCKQhk8HsUcGID14cyJvW2GVbxA0AoHkL2ciTYGhhgcJKDMDuaoQn5DpAYJWo40JCYTCFcSPyFyREmGGKLKTpqLITKBa5LQguOLePM96HpokX68aR1UCcs6Ypml5prN59bEbk9hvN87R36UWCU0PUZKxKtFRG8+/Jgc5z1DtEKUySgeOn/xvCUtaaa3NjUKZwJgPvBnLPFSSeQuuQYa2KlcAACAASURBVIGMwzbwNk9QowprBXmcFtzptd0KTQdgqcS7GFYkPNSuH6KP/fLxlN8Ox/B1CVz/ft+CcwzRj87UVyKSV7hf9DuCMQzHZ7CvLh+79VhT+zqDAGwnTZWj82pXxDDqXdoABGymhM+Pzy3Ue8iF7vWZfFivGCkhe6/QKgni4ZpIaMuqETCyG6m1s3KuFRtI9BVoXm4zPEpEMINFrcZpY1ulGS1VCZdZ6s9JzrtaUYkwbS1BguB2N0vkJovYYnvolJOfWZUZ0zRht987H5XIzi2Ta9hIquK5752ODXVrdXXvGGiZOK7x3bWdafXakXnq54XkPwEgdGmmpIaFrF7Kyu3YXPD9iVEJLgOyc6cyYyJCVTn0rJ+FxASvhjMrGovFk380GtLjXJ8z3ujwvrKI7KJjtMyR3pBnxrEdLdnR2+2P9R03me36gJYiK5PSuYwnADwX5F1VgzjGQ2V8diMPxqx0VuWC+sjYK326SQmUMvD87G17IuADhL75agthGGCX4Vs/BoOXUqvQwBj2mhW2wnsYjJ7HcVpF7YGz6wY3OAU3BfoNLoT+GIyEXmSyTajzklrA8Qg63IYGx5ilY2RgqPNgSSPDdU69rwvXejbZa0LkHGa6jkNPNCdKyJMwzzlnpJTd87zMM+ZSUUsVa3IOvshE8rxZrasXelRaJhKhnxObgIYMrJ0SXQic1kl7VkJZhmfWcBL+v8EpOLQOj8Olnuevk3uJwpy4vpRL3yWYYPvYPvELwJVdXyjgub+3ZtLQKdIpXLsSzGpZvq/P1/iDuonyC4/5Dd4ECn5eAv3Uajjmed5E2fFseOUGrsBZpxwdPrMOfe9ed2LsSAXj7SAwPgWdIOFgJY0GPNdW38Im9l4s4nWAdglEGn5P6TtTsNzd3Xk+51oK5nnG824H1tDuu3kGiJDypF6S5LSkhK1sfIW1u+srZVW0DIJZHjBB5kHa5xUkIrAuuC4vcChDHmz1mkGCJiTuxoBr1ffIhaxcLLS6nXWk+CKkTEg5ISf9nnITJlmNAy3L3LxonCYmiOd/aGPEFyojaY5ODkEH2vkbvX+snKRtlPyTrnxMGnqbueHTUkAN8z8KapdTmdcvd/fNfPplwYOjAcwpWsHH2X4TPE1V87iVUrkb0yFEPoz3amtFcs+Tl59SBix8ta4xoSQJhYsbGVPq55mUTc5DmRWUYSwqvyszsoZVF88jAsgUv+R9tP2g8gwgg6jq+KryXvnyCvFiZmLwEyPfZTc6JAbmXXXDk4Tmocxg1CTe0WJ4MMw9mKc6kLAB0Ix7zP/J8bGg08w7sIZxngDMMMMYSR/RG5tIsymMSSeyDbOhzQXBsxrAHBLC2mtRmK09BLeoBsxivFB1niSwr29mCUdbQEjYYubi+UGtblu01dCnnnGS83wrCnk8iSI0vQPwJK1noNYk+yab3AZdKNnYq8nniWSmN2On9rC8b4bz/l0NY3wtwZ4rft+80e3ZuoJPM+ZZNGwV8ddAfO9tiQ6bc8PMOlrvhLa3aykvqH/5buNm1FAFwL0qQfy+KlSc0+2MiS71RL8MvnOQtX8s2Dl0rXTwMJjk7wyeYPhh6W9s34j3a2VsskavhOUG13Ovthk2Thf7XVlCsCOJoVlSQ8BEyY6BrgdcB+V8FaOwnJMo3WHnbKzLjNEyQCEKTNWTk8JqdwOjsF70szJjytnXVk4J+5m79wmEu+0W8zx7BGvZx0e5RhuNc/iYCDyu82E9d0p0MmPjsO47vLadJlTseIPhSfs/K508a7keMcvPC82ZTgTKyY1sCksqE/P4h5ZDWXiTyoyJNXR+KXJecsV+noESeAk9Ygs3+iAaItDwycO189ZU3NXjibDcX52218LjmPUK46Dkj3Nan5lrwSZNHd9UiLD98IAvHz8js0ZfSsnHc/f5C6YH4JnUUJsshHoBCMjarAedg1nb/1AZXwmOP0NU7LWuAj1XIOuiVqeHO9wYGaB4YJv0wwlzTEF+joL9Bjc4BD+rfO4G3wnaETcKc+J3PawGguJSECJHvmcllMTroQ+NaAQIgP5wGVgNYPXY7vsxfOPwq79HfvU1CE5jSCKBF2EUFpwHK8RJ9LS8pDzuCShKIiSapglZPYsKi8XYXArm/SwMMZsow3LsyZ+Fb3cPdmPE9bAke0+tAY2IlUMyMOMDZR3HKzLsARErs+IGp+GSWb6O3SUzY3NyWKOvokh/YQljm0694MRsI2pvcDm8xOOWo2W1D9jpAl0Ijn6cF4olo9sX8xUmt/7h4HSTXrvRr4OIHw6VL2zQpa+bn6GHT71wXVwvYD0gPBnuHhJQ2b2FnMR/H2iPC0+aQGjt8bdidK3eY+Jrb+Fqm0L71wTTliv4ZPvHkWOrZP3p4TLjWb+Jb9ioIJ8/7rVsWtw7BqJAVU+AIJzRlMItTx2RpOfJkhc35YTNZsK7dw/YbMS7ppSC5+dnEVTtd+BaMVcR0uQyg1lowTrP4KkAz6ZkM89uhrpROwLmp9avjgoMAkPDqlPvUXDiEkt9MgyzCSKBRgPbhCFVnJdZwlq767YgCqy5q10YFOh6F7BRRqLs+EopS1ROgniOMyCRtcTjqXnlwxO0c+iZzbPmedRDU5KRe8TnbCG+5ZmqntcEySNNKblBhKHU8kqXEhS8R4RVx0F5KVX40h2BnxlwfsUUx9GoYK2U4/zYQeX5gQ0ueugQxPOLwkMPHz5gngt2j08As0RUQM8Py2/L72j9sXlngUMBmOK9W5LiDWehYEFigGK4rlWU+fZeqfKyRUAQz2LLPW7K2uaJbjnJzeucVODcdjM1WiYCcwGx9H+jaQFmx2fF/MQSHQBhH7eloCXWUlHNCMJltqQtBRgFvdi9aLuL1jQhI4MfGbivkj7snlCfdP/x97L3qYKRsYH57SZMAGvLTTCr2g9PNaa9Yt3gLCKE3XcDCR3PRRQ1ZwPMo03wvt1MMHWQjQVIcrITmhygMKOyKqkhfvgE4I63YnzwOyS8+9cW6cP7/oEwfzKlTjtFCPdwT/30QddKRS1PrkC3XO7mB6m77VJQqPM7k4bTheRS3aNFnStrSvQBzNsveqDD8aVVxT0XwxJ9IZ/VAtX3fYxxB0xxAPR+s+s+tH0bDfbdryBN0nNmq3d2J9pr5kP2/P7QgyfgEC1i5RGascSkrZ0BDUPNuEPzQq9EQm0wd57oUZHeVcXnDJvuK6fIkzM9zL81jHTy6ScP/V4v7xj9fQ3Edl4ivuhopK5dwSjW11ED22fGCFP2dNGUPXUuADO2WemsIg45m03GZjN5XdvtBs+7PRKAlBj7WQymOsNLImynDZ53O2wmfdfOUa7Ow2dA0+gkp7UsKsq+yArcTmIgavZfsxpMpsWaEkOopJGfwCze67BITABxRckJiZXu0hQ+zMDdNgPIKKWKjDTZqYJGVzoRHtacLjLS5zolNqg752JUoUgO9z/G9UztulPdTalv19HNg1CfE79L/snq5Con+AwGCpCJUFJCRkLqaGA5M4QOEkNPaXsF9AzqDBQAUBZaa4OWrsWU6KXWZsiFuFsPUYSotbWtg37W0/A5Avv8Ujqc+lRXRgk1/KZuf5V5bU9xM1SKZ6YpmDnQLVp3hdARm5wx14I7Vp4xZXwl4IEI7yHrjgHMU8ZMBH6ClinripTvQJIc5u8q4ykJjXMvjcWG5PrXxI2fomDSqoh2rDML78HRpLLBaN4YCYKR1LgpyG/wFnBToN/gReAbVeN29LC6XrFMwMDIem0dFeZVHm4d1kjMtefpxP1Dd1/Iv317MBSunOh2xiQ7DNEIKujBnCDCmilnTGlCzgnkZDCDS0EpyjybFbkKGi3HY05ZhYSqUG/0E5o2SqvlpkSv9h121q6NL7uAMPi9ryDiXNHxrwKHZvLbYOmtsX/13qNz8eLdS9fTQNJ9Q4ik+veDF3kXjAQyNSVPvHfMi7MJyNdLPYSdtWecEbQN0/hJ21do+e63htsedoPvDS+Z/+u02M87q38ERn31FFi9eFhUOt4xgcsoFDXBDwjupTxNE6YQnej+/h4f3r/HpELL5/0eIEKZZ+ymCfN+3xQpmpswJQltyU9AuiekL6pgcUFbv8NL8EWgUYejD0c0rIUKfZow0I1+kUC5Cc0S4MK3HjkiKeTUh8XWOMyBzj4gEFdhX85CQ085I+fJhaTmVRPBwnGbgm5ZqBqiktDwFevPuUDPvXLUi3a4n4gANYSgnCXXsUYR8HCSGPKzWzuCwLLd6Ntg18Ym8g6gbRBcnq+NeAPoaQ+zs2jAyM7DNEH2Gh00hlCX0oPAO15dMyrl/l33RlLB5Sg1tLCebQhaai5bz2vrvO89IAGci/bP+PIE9pKS50u2ldY8Vk34q97UKxEEju2YMZy7lDNjRsHkQabjPeu3CsmRwFQt6QKqeqLXIQC2iNoPLSoN0zuMUBSuRxy3KFTNQ9dk2PakGbZUxDLks8LWbpVwsmhjlXGHovnBUSQELRWlkxPEIIYBzIx5Nv67hUQlShJCnxKIJCpApgTGO1V0P/dtRpv9ZtDXFByKHSIkZswWiaIWaaN58wXv8m7uamFRTmDG8Rzn+SijiCqM5ZS/CvLKtX5ONoOScc7Z57iGxjktM2+EYzz3eR1bL/d1IM4FgqYUCoquBFHoR/ENEBQ7B+H8/t3g+8NxqUK7u352tG+XSCfEG5wwJQlVbnWZktZqcFEAEd493OPx8cmNxWB7rZ/NUs7dduvyZRM3NkUgfK/0PV3LT93Zq8puM1Tkw7S/ncIEQk7ZlfWlCk1HkHWURvwwwwLF5NwrPjtsO2Iv5z1exK8EnPZjT4uvy9VOGK3CQ2yRXgZXlbInBqeKSnI6Cr7kzEgkdOo0bbDZbkQxyxUoBTzvJUpAYadPE0SBnjU1DxWhb1gGVhS3tSc81fZBeJBomBYPeHsw9OUaDK+vFd17u3Mvrg3ZkX1Onml1P5eCnAFKhFqkFEbFewa+ahm/aU3PpeIxEf58/w77xyeAQz91MRktbB7ojyTe5x8TcO/nOwKRYevOzvwYQUIfcpwacxWMY2zuO41BnoLpBjd4S7gp0G/watCEUMtwNpeWY5Z8FghGCI3mX+JKFTYmz05q+R6JnyM1HXxisYF7jfb7MlXRIZZhot6E1hjeMQzWa8DY05F2ih7BblFm77ERm4RMojyfpowpNYs58zjnWlHm4qHUKatQLyUNnSN/KaXmuWKtM0lM6L+F5jRrflGiR7EDdb/it5G5O42V7wXfox2n59bSfvRyWMy7MM+666+lfDg96AfBmZ1L28Jo1vJ8iKV8a7ikza8835aDfBF4OKp4zXfbfjzib/btk1Sn0R884wjE33Tgmc5qyH9zt2EOdj5vDoequpxJe6tG/yj76CvDhd16KRZGYe4pHvhwfa8zHuMaWROSXQuM5nHXymtCgq6euPZeUOcaHFtbR8XAneXf+vllubZfC0a6Nsoh4nXbPY1KrV+Erpx+mwACykfLdtqEjbEEXvlf5JiB1gYAYsmdSxJCOiXCNGVsNxtMmw2macLDwwMe3r/HZrMRj9md+Nk9Pz9jyhmlFE3RI/RdquKjWpkxc0V9ap7yWbOxuhcrm2BRRflBCOPY6KWS+mG5AdE8agxvhUC5Cc08KhIAmjLMu4qiyC+ptxJX8RqHCHiSCmarC3e0SYTg1a1pkMy7WaR8rpBkIy6IUUsoI0onnY5m8RJO+h29AtixYLnYqeefVPYlpaeERBmUzDs+e25QBsAkoeYrs7eboGH9eVw7/YVDa8vmGu/kIfOmkeumrgnlmGL5TFprDR89B9GXX4oIuHNWT3xq9EeihMdPXwAAaZKd23Jc27K3IfeQx9zCxXbLqNYzeOa+jebJlTeTeKV3z8j9ea9rRcd0TIWQNDRsUc+6ZOXqMzIVRQntoTKZsee9KnsBcAGrH7K0oK1XU0yTqoUJGea33ro/wYywq/vgsrcnYQu2cPEQxS8B4CcduSfpGwGgB0J9VB76noAnz4aKmAAgqeiLeQ9gA+I9GEuvYsOL4zTJmh+vN4N/3afUUzDputySzTtdx3NFwoTp/YTnr1/kXgJqYdSasElioFDBSLwB153ueuKRhVpEef1AkmBUee/0gcAVqA8Fzx/3aBYfhDxlZJZxypQAi4oCQqIJhA0kPsAzsuIit1b3s0u/VJbwt2RegLUi1wouxb3/ilHlC7cwdDy9jIfNO9svaKD9e6/Vaw12PcKPfpryirixj4Q2H5LWZV7ZFaLXYfSxMUY8xXtmELHmNX5aXCbzqc+QLNAr0V/Gc27RRDBFV/KkdSQA6U9CSu81YiAh/Z9P+KSmKaDmiW4Kjh0OybIOcV9RKXIE3ojdOMgTXgiH6ORzrx8q77XaN9ZvZR4q1/aABdoHEuvc/iU1eDw0jrZfSMhyUXbWWjGrXDEVi/ghn8/Pz8G4LeQij/IBBsqs51xqZ6gotvvIRB5phMJzRNhS26OqRk2y+yklQI0ci8lxVcFYWbxpWSPqzEWou6x9mEsFE2GbstIHQg/MXMVwUSN2zpoesyGeDVkwD3LDQ5wzpli0tZhSBpG0a2HwYkpQGBndEzOjJ3p7l/rx7iZM4+vafk5OcBol7eS7VWuTkiuYC2rNHonU6TaGGqNmbKYJ2+1W8qHXgrrfY+YCKuTRUECERBmT0rQmh0YpHt3HjCiMbl1z7mjzioUP4iavap0/vlLHu0UjB2Xlp8C2n8p9NzQz/Nt5pMaZ3qqA4q4+5sUNhtC5U8544oqHCjz/9REJwB1LLvNcgfzn79j89QmPlVE/fcWUk3ijQz3jibDJGfcfPuDrf/8ys0u8Y+ALMd5V+WydDvxL0tlT+r2fVZ9jfXNeCBzmpf6n+idWj/yR3vgRjNtv8M+CmwL9Bi+HzsK4bZBm8W5ARL73HS9uVJjEo7mV3e5a+WeU3f0ayzz2Rvu8hng9/53WiTO6c0ZZUEHa2h37bsQYqWCoV2qPiu5pysgmSFRhWQULgRJDtemcsPCfHgIyZfWUESJBZo0J4ZQ4UOEBQ8O8GWPNRjzZc/Dn4znq9S9mzgFG4JeEl8+wy2tcx/zrEjev0KdrDFe4EdG/CqwK58MZ8OLyB0aAjH6OtLPeeIuZfGhe/ii0uDP9+vsHadYNbnAQDq3TU2fD95jb59a5qjx/lU3CpCKHd7dRwSHfRTG0fFaVWe8J+HKamrW7swqWTHnYwj4yoN4xRt+llJCnSaIUTZMLGaM3oj2fckbOGcwQQSGRezlL7wm73U6VtADuWRVm1rIWj6hvcaAphzud0I9WPNEVR1aGErhgArIJEUMdYM0prbSwa2HQj40ppkEi7JtyxrSZMOXJFdRmhFy5Nu9R6wtb2+GRm5LlfCZTmlsdABXriwo8EcuLX4y2RxNoknhL5ZwlJP8k302gXNVTx3gu1tDLQI/HscJutpkcbLw+vnSKTCWo0ULD1SVAK9/HWSRfm9COK4txTFAguNCX4IQLETTfeePGBMWDIl8lhGu8r9etralc3XC51Iqyn12ZHoEBMFUnZUdDiTWvaw577SFPUp+DXRtnkGZojnNe7pP/k6enhi8vFJ2sINbalOqT42Dk6ySMe5XQ7lbG07F5EP129yDagDTn+DFYM/QElrjibsKrYBdwhUeybNYETPSAilnf2cs8sJ3HjFGCcwKBQRWoSc0OigqMUbH/ryjRn//euRLH1jMXAiMhEyuyJQ+9hO03JXJCxh2iNzrQlMONtVZPtSphcutcUEyAXTTQd9Gw+7V6AP4eaZKmYm2UCKJsGm+2dUa6d1xO92csz0vSoRk97e1eiLEHgLwM1nuDWZm3aU25vkF/Yu0xTqm1Ho2rqoFdFUX6y3j6ZR9az2YAW4IrzwHp1x2S7yXRHC8RYaNr4tpQ8zc4F15XlrNW2uEZeG69y/PmGEgEneBMRQlmAsW6r7pBlRIiFuJdlMNBAuo0J8HSxLAWZGv6HGcRq4dAboxl+5Ec+ybDVNmpK6NVzllZc6YvcVmichRqwKLK/KSpP9bP415cZeVaGqA1UZb1Y7Www51fFGZ9H9u1Knc9mx0S6pvSpHuvypApS4h2NahIYDVQkPtZI6Nupg2QEsASxapwQZmFf6mWqkQjmsKjCLAr2LnKbm1h9EGQ8PrQHc4PD6FpDMeCUsZp658zMBCQdWis7Aw0YFaa1Bp9gm+0dwC4ERuBmtwdclY9AdgR8I4I2//xL6QyA/iCh/weu09fPCqY0A+E/eMXWbNGIzDjwej8buKz00BgamnA3DKzkdLSFVXUe9vRLSIjtfzLMOFG2voGN3gp3BToN3gZ6MZb1WLONjq/B3RH6SkyL7ERSq0MgnhmB/GQWrJpdJfWFL1/vQBFS1olFK3UY30w9oG738vnjbEykskYNCe2eMkYHhIwH4bQ4q4wCv9LpQRyoRxBcpqnRH4vq4AuUUKeNJxjIjX60tCbbkihdStBaN4aWUNA2icFN41VwQQ3gVHlOghg7XmCKcpZCQaZL9wKcTZ40fNfAPpZ9C17viCgfY73d1pI7tdr3bWspBB5l7+9vsp/HWiM3/gpcO7ILnOX04H7fd1xtZ8LYw3nzEs7d/o3+75eCi8RfRgPtfRU/ofucd+5W69d/Tke5zR8J6zl37yuZbTyB5jH1fH1e444bOVI1xs9Tbjmeb4UIqwLgw7Ve82aouFz+UCkQvu2dY8FD5f43GEGvi+1yQZ49f4pEIpo78KNCRPSe8ufJ3mT+TdG/WQ5i8nfA5o4UYwkLY9taf03g8qJ3Hsv6eYotF1Cmib/buEua210nHntTFnUEUlDhUtqH6GICwFpTk0A/2RZeaW9pvIyqps6lUVEWOhXEKSYJ7aFTXfFwFyBTKZngqlAzIMpT5IZtu53cj8nZ0ZEwW3VVjC3fO0maM2UMGVRnm82G/HsJsnxLl6oLW+y98CEeQnukZTz5AavIO0PK16CEawU0I+x4YPCoSbhwAFiUaBP06RRoyY3gvUwl0Siu7PyfGMyaRmWizA+vwLyGvlCt7aKMHMK4bdtfvZ80iF12rsPvwEAvn7+JN8JnlLA4NNffy3em7DB5mHC5m6Lp78fsa+SozvnhFoktykA7Ovs7AgQvGSJxNMXaDyO4oAAkHn0q5Cw1uLrayEDZJnf0aDZcnNbDuukXlNzDTwotTXc8Cm5q0vV3Kpa0ZhSOBo1m7AzhqJn6yI2AfMzTLSUkJ06SsEoxbzJlXPTBcNIdVLBbcIeT+gF8ayeizaxwi7/aDht+2R6l4ygR3m0cVmnS6VvG9zBDLp7j/RuVnHc123Nm2C9/dYhs0HoCyJRmJevDCZg8/4BDOD5q9SrGXxljvAzMk+oXMAavJYrAx9VIaQVFS5gEKaSUGb2fNUyQIwNEkAVVAjTvzQSyWcGcUXiuH8ymGT/MDqAuj4xCgMzM6ZaMc8ztr+/x+f//I2JWcOytzRuxLyg211EICEPWiSpEreN4QSkNlrs/P9lp7yZlCV9LSrTrQlx18x40Htt3lU8upIh0k1lpSyAxDRC6fTMZMFEwEmUFXdAqFEatgjLzm1er33e6WfprgImC4s7PoCw5x/GX+xDAbAD4/kvRsZHTJCogtaXbP3U+WapT4gIO503Wx2/5042cyFQ9/FmcKj8c1t8kO69srzx+WX7jnPaNDw1vmlz+NTINMrrOIz1kRMHcqXRbeNM1vsa2nyuFduN0FrMVSN7AKXKCskpoYAxTRIzw8w9zOCSIbSDRfrcz3JOE0n0FeN0CE2pbedkTglNhq00vR54QhJyo1O42kkm3ubaGzmPyekEIgBVlLOVK4q2M2v393PBXCruthtQllgtzCz53ZVWzinhaTc7rmQpJzi93qHSFkzYAcwIQGlR6zNRi8rUntWirKtBiX7YE93SsofT1WUpXjJ8ICLYZWjEFJ03BCDlJkNOuseQHtKJSFIhTRmbjdCsxBI/Za4T5mkG7UmUsywRCkopICRUak5f5gCWtBMSURVm3+jAaDntk0azquBOH6E9j4PRrbFDQKCQ+lReYLTzt+PVnB6ze0Nkh5OLVVvDjFIFx08JuGeJPPKXvv+VAPrvR9wxIf3rA3L+A7UWTHPBFwI2KQO1gJUnsEhGlcXkxSLavKOER2IxQHWc6rwL4eB14QoP43SwrjvjVRxhfUIvX7PDnLTfh+R8rxnt9wa/BtwU6Dd4VWiW0gKXELqHidZI1kV2eqUAvowoXRKWy7d5uHq8/PMtoi9q51XKxXg8rdQYhGbuda7K7vHalMSzKKWMSfMiAiLwKaWgFg3brgRhIgKnhKRWYymnQACpt0wQilvOxF6BoJaig2LeBImHifwg1OiYyfb39jDOmreqYw2+TQ8vgW/jef5ycIxeSEw1JvQXJ8IYbkk6XAZwemaOb36L2WHEdl/Z+BvrmwcBEg74+nE/Vyhxg18TesHOdQKscyBO7/G919jVvIyRgX2j2X+OsOLSchbLf015/kpnmgnE2q/z9tE2X7h7lr8w6AP5M+e1oQkIa/AGAkHz6ZqHjarDmFHmGXsVVpRSXGluYThLKdjv99jv900o5ArtipqSh7R2T6GuZ+tg5y+HmdzesMC0VpRJZXpv1k7AUlhyCwf6WRQGrQ21qiCyRh9DrApqrI0piUf3NInyfLOZPGyneM2INzfXGsgQdiFsylk8/KcJ07RRobIYJ5Qq+Yd51vzJRKCA48r9rIphUO0IJBYDhpQlR2QyoaUqWhnVPZUNlY5s+xzI39gPxeTqJOxn+bD2CCCWwJCHKV/yEV07k02Rvga//fmnN9beLPPs4br32AfhZVtjg5mC988UzlEoqHJAsP12oV7rrxkmiwCVXEgqD+lsTuaio6qJUryiJem6FHD3e0O83gsnk9ZRh0JF9k1qHAIwZtQmvg3lGZ7s/+iJHqIeeCukjPSQkB+3mFWRbUJ11idiKYCpThj5IaFDZtdmw1+f+52tn12pG8Grmu6cOksOxw/nqAAAIABJREFUeesfgzZvpFeMJqnvSiJGwQ6ErebhFaU0PhDKZ3tTeO/EsifJP1Xz6r4xc0Guut7nWXq1Z6QqqSYSCET2zix7B5r3dOUWGrlUdr68zDNSKfj/2XvPLjlupE30CSCr2pIS9d67Z///n7vnzO6IFNm2KoG4H8IggMysrqbVjBozVFc6eIQ3F8cLFNxLqxaR4tSc6OI77EfYlzafdILRf2WJ3uW08huInuZWHvX62r9IuAbwANtHhGtUaCoHvZZv5J0MkWsUk7do5YllD1QKco8XSIf1uDKnSqQfXqZLrBuSOqEZx0WFfgW5QUAzJGhny8651UgknuhLyPBWxvK9aNbXtvlzyxKXLK/ZL5irprshDa0evIB9vyU3/iu1NrjDULgaTjaJYlvAYgy7Pch5DS/rzdop/YApWWoedM47ljrH0kwmhWU5CW23dhKNMs0Cnp3WtvDtoyLQU30qTpSMIdqe1adHMgbyWKNJWR4s7m+WoETvb8t9oRHp9MZ6oTlZSlKjBTG9yyqXzqSe/YpfKleUKsatpQivYQax1hQRROZc1XDBUrAwIXFSr3MxyOBp0rRSkNgaxGBeiVBgBgdKyxJ07jcOcMQ5L53xNbR3KiKQdKE3jX0NJGk0PEuqAGbsh416T8DNh/d4+PgXrj68x8OnO9zrc8kZ33jFrn9oxmWPJ9Z9ARUM/VPDKBGb+cKiny9m9kgQfzf58lv57ypvCvS38v3KSwzT4v32k/T78evmed4YX4DBaknWACq7YCvCfR7IlRaQqgesowyoF4lwD7jPG5K314sxpSTKoX+jyKjdiV99NS5Ycdt0ZB4U5a44TxRCQxImDc1pIR1zlvDrtcwompeoaP4YC2Gd1CKtQkLrJEr6vSjhU0rdSJvAsfkXGEPt4dthoZciRbjBGAYCOi7uVwnrz9rS6y/FAPXfv2wRSVGE/CtYslEw0Yic7p1O0BXe/sapWrJCVv8580Ddlolfn/5KVjkN7/5aMcFa69uQbPRCXCsLwTS1w9XlLgxL2zGlQy+2evlN5Wv2TyDG272NPbliNf1NgxileOeURXuj4C/ePbMPX1VWPlyXiJzVxouvrG2mH1B+NNt1bq5zWvw+r2fjObMtOp5+z/2JUZx/Xon1rX2zBYFGPOyeDvY8GPeN70UScwuavXZr9JBvHEnA3hEmxPfGhRrlR7QuvDrdn+UN2nhhDa7SsOpGIzMY9U4ESNO7HcqXMnwD5N80zDIzuBbULwErEqnyvI2JoVF/PBczXIE+zzOOh4MKnARP1LlgLkWEnWjTWpklf24YWWW7DnS8KpJ674NIPRpPYVdVhSyBGGRymrP60FTwYnM2qxe4ehGT4jjzkJLXVcVEgbeweS72np0w0nyNpgDX/OeUUEE6HzJmHzfDFalJvcJ3+x1200681zUEvhkmzBYyWb/z+fFx2Rw1iGJCX/dMNC/3KbnBq+RoB0oNu0zXoZYajB2UGmJ73lbHv6n9fVM2pwTg0sKsEupzFQEwMyLd4Z6VKwd9TYn+eHe3uBfLe1OeA5iPM473ojidMaOi4OlRFWkqVK+z5UiVOcm5V8HC2jGhovfNZl6VUDUIGwmYdhMsUgMY/tcU5lZPrb2vKfl9WY+UzIvJvN8lAoTEtZW/LowtzWPOYR33ZI0ZX7S9bHPRspwTxBNdPi8gZJ9tDbjqCzZdZ5QH9dljxuXvF6jMePr0BAIwP0m0iwl7H3cbqxFMbTWlbfGqztPUhLgqTCUNJSF7lNSzjb2/lWdQmAUb0Y52YBxhkGOM/NKxoaGPvk4Ot+WO594mecfC9D7f3Qub7qFLbT7tUEngb66kedF1LW4VFn6Rr574HtOXG1SygLPPIFyh4AnAjSgdyhGYxSCnzhW5CFzLACytGmhCpWcZg/ZbPM81Z7lGOKhVcp1/+vdHMDH2RVMDuIJnne4gA55uFCJPUgaY1aiEl18brPL5T6FWHlsBsv7coeE20lfFCxxh/wDE160OevRrg2ttD1574HIp1+rNHvt6DcaD151YFAkVqgCCzFWyTkEVYdrfzgs9gNw5XE8DLXSh1xV9OHcaZ47WzH56+oEB7PWO7YEWttrOtcDtBz1bezTFIQg46pk/asWXAECMZXaFFyi280mnH1pe6gYPf/07J3D7Jy/RrYtzs3hniwI+Xe94P+KRLZo9frM1Dy/NT8R/AFb3IKAexXoYLMLp2rtzFfqKj0cx1NCIOfZmYaMThD7ZTSK7tNDqpYjHcdV2cmBEmJpM2fAo6SCS0mqS9xwuN+XKYlwEBnGSfpNEcLC86jZ/gv0i3WSKcGCuRfBPlmgjsxqhXuz2YEju9ZwSSmXHxQBJVB0iHI5HGLxkan72OpR+TYxGJLixpa2V95fad2Iw0HC5GRWwvsg2f2F9OVaocw9q73i0la5fSvfUqh7NzbM5qWZVop+KAVkpCaWILNrC1ztdD5FvF6iMulRUBjSekK6rGI5OOp+pVhSVjbfUjG0OGW28YtxpkWMDfurmstGCp88JdUrxuBAWob3todaA03lxrrfKoORO8X0WI6mZJH95VHo/ffyMq98SHj9+UeW5PHyeC64AcJ5wpAQmxiPrPUgdl0qbyjxTZ5wSRg72zpCDS6cXrMXA1/TKc7TUL8abDsYnJ6fl5NOXy98ETf1zyojAfnL5RynQx/P62uufWf7WfdXGXEfJPNKF37kxoCNNF4nU2+lZ70aPbraJ1m0rWQvP8/XD/Nbvv77ddZI7KcHiYj0RjCT9HfOep9SU59MkkVUgoVpKqSokLS36gAkLE5C4KsGqYeHtrweHkyJEV1ufON8MjZYEOHPWk3mBtGYjZMxCUW4ntjdfnq3XlZdWNLJU6wzr9zznNPz9dRAslmHsbvRgxGF89o11d/fXKn2JfF1jVdfY2P6afccqo3JyoX7QqnevrWWheqF8JRHi57TxVGd981b+S8t4xF7mGP9Ly6+l4taWYA2Sje+t/X1NW2NdY3uvred0zd9jo23B9Zd6FNqj8T6GZypU68VS39DX9dLPRvO0dIx7z5L/3D94uQ8EwnSTQGlCfVQvHA3nHdWR5mleNayv5TInkpzfhEhhm5KUESWIo6crwM1bZHP867uLgUBl9p6+8Z1xBvp7WncR73PkppBkGTTQzQL5esc+mWAtpQxTossckoakhGrbpJ+1qpIqKAKRRKicc8YuixJ9v9/LOjBwPMoazJZ7mNgVe0ul8XLkJp4ymJASIVveyZxc6cNEiDp0VPVD5ODNxW3vSa1VNyIHGj7uT+9o6ynBDT76Pp4+sf2YgqAtjHdUsn/5+AkM7jzUD3herdOdwUO7fr7UENjysIZhgdBCcwJNmOfnwEjiIGAeQ58uDK26A68zyf2ZDy8AyN6nNjOlG0PLpjxBgsj2NXRLP86Nhm9fwy+2vxgScnd6Dxw+W+BnCykrk7AwsBp+r0MtRn1kMGaka21teDGhpQGI9Y4CfOp+Tfr0YKe56wGDXfGB4fnIjyXs9bXDyvOGIdzQRcGjgZTKVXJua1oIM2ao6nzABBxwj4kuIfnMrwAiMF/JXucqSoNPBWBJh8EVSKpESqpAJ2JUOiIafldVoINFSVQh/D1UMZSgyl1uipselQ58nu1zv9FOZKOF1vaB3l8c+v79zO0bSfvOYR0YIPZID4z+bIkHKSBe5PZNVKbD4VPrV+uFfTfSXWn4a6FtgT7PPEGU6C13+DpNMhMw8ThP4/k5RWucpjmPiMrz9m5LbbC+Rgbb+zHIvP4qVqDhCoOO/5nlZ8zf9+VE1mofIWN/RSCALY1kgMdBW+bKtfBVrdDUNgmlVLiiUJtkq1NvsJ46Zg73Yr3BIE5fseuc1AmK2GkjEGHKGq1DjYyYxXva03Jyi6ETZ6HREtyAAYR+nnJWrCX1Tiljrj327WMgxTllNForwuBGh1lbsU/t+zV+kPsHHY2mtBVTmK9QIpw9sZmZhZ616KRO17BGvmChj+cyGwpCmjLyYULiSQxSy6zGnUILNzzKIG5JN3ISXmWXJ9Akay0OYW0GYnYi25MWgSOOK/J4a6u8tuabEzTcX8Lb/t0Ie7+6NNIDe1gMFikzWroQK1cDMc7MeCbBQY9gXDBwyUERHwlobOyPlQHQxuPI53VRa/TAmoHHNt34Vv6by4IMDddxT229f6r8rRTo42C+5/UItL72+kf07Xv1FeH+qbbWn55ZDHu4ZV+zuHIrrc5saKUMu9PyJfXNyLfVSXUhbLISv07vBKFNHNGSmLCnMbNTFADEr3tx0+Dnvjqklw6dkezNc2LM0YiOUMyaO8cqTWR5c+xdZWTO0lhFwqhn0Y3oc2U5zDpMBWaJPIxjniZM2TwJCBUS3rDMFWWuMjaC15UqwCQe6DllJMrISCKUs5lwwRF124UhQjqGZk4iVaITNS/0YXyOMNV6XZToFJTnKby9DTJfOhFGdtJwvfx6XJvg2TTcGxnt/lz3ZNjYz9jymMPwb1GMasUGQR2eLYnOMyFojLKw5c65sh7bdcuJXYch69ftjIcuOQE+vh+hd3hOa7vgFMoP73vj7NfjfluS9rR5HUUdTbRV1XtmQ0H/d6BQvxK1vbaMc/ct5fzwnxGWIyz1kpEKj5cPFrdfnizq9nJf38puXDa5si6niNvuWn8M6PLby4LueG0Ze2QdVTz+AtW29LLqrxuu2VzRkz0a79lf85ZKhGZlf6qOwfV7rY0F7HuhT2vFPc/H+1ZvdNdAxIw80A/yJIFMRDbWpP/t8XWvZLOYIljBKT28XKfEY29iS9yWOdQVqMPxlLd6CKtPljWN94Oi977Vfvx8CLQRI91mgBnzZwlXTddKlz2rd0YSmhDqeQrNEwlVAtZ6gOm7F1EEwnVOe1gOZ+u4fC+hiJshpirmN+HjGnfW7jv3QOb902M1/X+7N3otMFQGq9dF6yjVP3KayyR0iWDJ0y0MsoMGzfOOTMjZclFrfl0GoIJXmAc6t7yhEqI0Sfj33YSL3Q77/YXmwZZ3SqmYk4r2moRZ1sfnhb2/4nE6QBmSaTBBtIVuzxoKuqIojc2d8tz/kTXJmv+4zWVrX+kJbl6cLdQoh7dsALFksIqgow+ovLkOmbZ3T4RphIe7L2GugC0etum7tQe657PmzaS0/I7BmGvRUNmN34lgoNTiURGkeXmpLpIiL4t5uzmM5DY+NkUfBYMMAogTGBlgMahOSEg0iZGE8VPaG6vbzyIvuWHxE5whGWErSD2ne4U04enzsfvu+dOhW/Pkp4rDfwMeuzZeTnO/pgQuBfwo+/H4IB58k+dBN6G+5GWXMqNqj0lDthMAuiLwo/TC9gIRg7FHZtY1n0HYg3HQ8e29v0yMyrJgk+eCj/nfm2dcIoFR2XLUs4WBVYPcKi9brldv/cssvX6vkS609QnXenibcQgTY2eSkyrfVzWMSEyS45UFbCWyiCCESjsATzpT8Hy8XCXsu3hTt+gFBOsjUMj2jK6pSbF9MXuKpFE9AT5t4dTgDdhOrx1I+WbSNizHeQPLup+0O4mvdVUekHDr54WQsP/wDs8fP8s1E/KHhPJR98uHBKKM8n/VwESV8TKOBzcmzgCmD+9QPpqy5l7WX/t8JKENdqxYmMnhJcMU0IwJMbx81fPc4zICOQ4iZo8FQQAODnvbnI9SLgBuMmS72SIUPQ1wMvtKyX+vFL7MPjJdPWbsYeYiwGPYq+eUc0PbL8pIL3Rk+o+JBzg203cnUqptZ4+US0cWDs/657R+zUYjjs9fLn07p7/cpnZp9ar1sVdLtxQ+veTKI+EgSZQLJQ5yyvJNFfrLc1dDzsdcClJNSFOSXNgl0EHQ8O6FJYomSCOjtPQ4pUoI6xxkoVDalIww8oGRwqIGtUx8kxV+P88zGBXXl3swCPM8N0NTbvRhTlYHBf0f4zDP2E0ZpQp+ENq4OghNpNFwNKJnc+RoMJTsvxR2hefMJv9OYKgRJSNd1da8cxZxT+lWbQ/3tRXqd4LvBq2Uws3uTeUrDH/E1BFgSVlUNNIp0Yzj8Yh8OCAxgxOh1IKi0QdaFCihlWoFyHLX5yTGqSkh5wnleESxtErOGwdzTEUgBpNrvD+MMSq9DccN7jboRx1T5ui3TnL1PWkpq0KDvn6MK42Q9OC1rZ/p9hkDzHggUYxffXiP249fcKcvPBCQ/hJ8dMnAEzESmnEBz8Xlg8bHPRJwocjxqpoivc1M3wc5Y9RPRw9VWAzgaqCx7fyz0b3EbS2ii/piwBgq19uvRBAdi7Ne5Vv5jmUBTfjEMzgL0Ixo0K9xhG+n2hmvf6kCXc5R6/JILH3LNQHdqGmYza+9trP4d+zr2Letvq7tlFFwSWg4tH0WUagiIa4euludJDoCyQcY8UHffVUMn0fmRdJgvB9/b5F/3fg2W2lvcfjLJ75a3qXuvgnIFv2nvk8WKydTUuJNLahMwV3NeMA8YIpRGptjIQImUm8hpUBIiZqULIR7Dl+IkntSQV1K2XNfzuoVUwskdDu3PFhG8GTKmrNIvFemaSceM3nClCcQWShIy1eTNcZZ9lmTMJ8il0o5i/iXi3jlJJbQhy5MN6hYjbqSPV/g2fIsn1e/PvEgOJn5wsq2FeTV9wjjKsc6R0F+z6hQ980WMD/3+lcWAnpdsJe1+dS/PM6FzSOdeW1VNaHwsq3x+3P6du61bcmvV6nS4pf9NRvLEYL1VEActocyQiAWODyza+pJWfOGYm5COL8muBfV4vlXj/rHlOVcGoyV/1C8SYTFVg3fjqux/cZXlLOV5+GT8Het5a37sQjzel6/I+HZ3Qet1xH22wLChc65R4peJwZGWxhjmmmkfb5xv702Z2lflmPuvansb4M3S1gfGPIFTOqvqbtehzBb+GCkjRLUA1Y7nIAup/FW2QpD6W3QIEgKI+xw4Eh7Dn3tHgcBme+dqMhXIZvg7iVsF8FY6O+wRob1mzijUW49vRet//t3ndJjXWOy96VtViKcLUuwKldBYuDHUaDLDTY3un2L6v2WMuKSUGyZwc3QEe28cKkoHhI61Mitn4t8fWqAQfpeYVEUmne53Ae6/Hnc6MrTZzWuWvxlTdPi7cUX1rcQZtOnwqeJFcdSt2mlBu63npLTFQzUgpRJDEinhLzLYoiqeRpLnVFYvPaP8wHH+YhjmVFrC3EvUZsY05Sw3+1weXmBy6tLXF1cgbLkcHyCCpCPsseMtp9rRSkMqNBWBMM2PvbzRAnIWbydpv2E66tL7C8uYFtavHJsfqqvNzHDVfgEVTYCpBk/G8xWQxIlS8yziFDgCk59CwwPFe3thVosl+iWAr3fL2u0nsGm5fev8eBp77Gcbft+BV+aZzqDkViNR6j1TvKeJs9vqgPZHIGtCchCtwOUehi1PvKuU56WIBoYy8rOWI4inKdVmsngqhnTA5oQTNdano/8vuGMdJ3Bjwy6kvv1oXp9Xv9lw4mGdwCAcka+FuW3GGe0U06K+Rq0Z3AQf3UwgxqEjypaMQiwuZr0+QSCheFutVTVDFiE8UgJyN6ftKYjTNmdAHeYTCp8tvMpSm4G41k7dwFA4acyWr5vg/DdeIDo6ECI54Z8vLIHNVQy2zneO+ZLePJ1i7iPoCHe9bfx2c30p3m4NzyuULPGcx0+6O8Ope1Qsf+h7lFmuGe+e3rbeYzD5rg7bv2RGQVUZmS+QaV7ZNygfJQ2GQT+aKFyRb5S8Ki8kdBStp+ZgfpXRU2PyHwtBn2kjiAsyvEIQwDpV6UGmSabs24udPz+u4u14nNk8HRCmzXZEE0a0puy9O00r/i2dwQaJ/BwnwL+j9TFWjnHYLe1d7q8xHcy93spBxrtZxVvSRHvmkI9XmP1OkSU6fbvcM3rz88pL+KLbyhEqeMLpLA/k7/6PCVXThpeYiiNCHHwaTDaaEoAti9ZzmJKyQ0gDR9UBlJlFVYnB7pOv0Blo0Gp38J49wYA9p2TiEowMqp7uhMlzEUUsQYwO7xF8h+Hf6HCyoy5VMUnilcIOMxioFXY8AIFuY3Be+vUyjlSQwvbI82sRXFJyLFudJvXwnCeJbE9jdhdxpPRMGijcQIuN7DV9VHnN0zoNE3YZUldlNXgtmqYfE4Jeb9HJonMxIlwKDNyAnLeizEET+As36RSxUiMRf5cWCOnVohsPWewGrZe7i9wLBWlzpgpgeaCiurRXlr2Qg6bR5y3yBQh4CCmVlyMRnl26+JzoPJtMJpVaaNV+xmNtBH8HqMZLT7SCrwd+bNYg98nHD9+xgUn3BF38gJzerzldi4JjDvMuKnAHSrAhMh9X7GTKt5Ti77Efo99ShciCTPopEatNgNlpc4oxBJiXxJQiMY1TET/08azOjOhK8PXI7x9Kz+30MbvtevufjSuoHamz9Wl/loPdCJHknLd/fm+12Mz1EDQ1vX4/tr1r+rrOX1b66uzUSPWJzjTAX0uhvAN2TXGU2+xAHrxmFClJ7XcNTE/on7Qj9n6pHlsYuEqFrsxN5tZ7LENwBALtW4aEja2LM4b6bthiENxtr/dYYR7tPrNdmnkR4IyZiSiJheSep3Sy0QS1tE8v42aSOZBoBNSawsTKEzyNshPSO49wlxkBVkIO/GGMDWz9TqBUkaedph2eySdczaDiZkl93mtku+H+7lkCAGSslj0TSnLP8qiXDdioDbCwm0DJZYlUEhzn8v4KSVQBZCKewGZx0vAyQ3IVXidKfzre/kSqB3nVCvefL51b62lHhLHkzISOy/1klbu/ZoSxk5NSLv6fHVut56vPTt13UOO9mzr73af6IXna2UJzfqenSr9HqXh9a2d0PYQx0+U0Ynv8EBFxuvGCLVP/JriO/Ch/32V5u0cLfIeRcY1vHsqP9Jp/SK98Px0WTceO6/CLWLf8N6CzogfAiL0ikaMi/fa3lrrkc3bgqGw63Hq7bk2a4Ln+D4N32/RPlLP99l/r1++RlVYDczA1BF0EbaTColkxWJuvSUuWn4bn7chc/d0bQxCd8RnajCXMsbaYy/aesZ+rJ93BlwBnwbs5TKjlQOy1uc1DOy0m82dY0uhOVOAYVEBJkxP7ehQM0TsWeD4/diLhiuMlmvzILSKwcMWFNqKeTcGfEM8XLfRWNOmjG20ah/2b61s3ZdesnqESmQjgviIiuKneUbKDwmDbL0q6tEpvEELWMhVBSp+PvsxWShrqdLWo9HXzDOIm9HmqRK9jLbHGfFYm5O4W0nHJxfRsCOoTAerYYbBqFhR2wO2l7h7p4Jc96jqmCQRnTIlNWZNajxRMRfGXGZRoB+PKPMsUZ1qbQYFlIUnIMJuytjvJ1zsLrC/uAAloNYZ85yRswiYjPOgLD5WRXO5Sy5swGJjuIkwQWj1nLDbT7jYX+Biv8fFXnwRzVB6ZvEsFqGz9I+d4mm8IkMNXMENRjP8HpkwjKu+z22fshrlFqhwzSiTpjg344pxzXtFT1x76p6398jr9vdWDcLWd57toQkXYKqowpws9qztsEkFwB55weoxY0Ru0RbimT/MYmhiudZdGVAFxuQpOTFgylLjhQgtd3ETkxPAkv1zd73D/GAzSx71LdEOBUcwEDxOu5Ue5riVBAJxRiUL/DzC7CY5Z4MrRMCT4ownVdqqLKHqOJgBPBHSjYyXawU/VOBa0o7xk6wVaXWu9LiWe/VBelMBFMyYNDs2WOvUkm8MZyUwF4dl851kTXXDLhJRbr7JQEood7POKwBMToTJniXk2yxn5ktRL7qsZ68A2AHVMMoBYAs1y7rfGYkvQKzmJMyon1ngwm87EAj1S+0AX+LoKdxwSmKLJvEAwqWnVDM8Icb2vmKKxy7V2+wJozR6//t7lI/VjcMID4JfmJryB4YxtZhCYYWGO02PKeyAwi29IqjdErWUbYDlzdV6+SbsxYrKFky5qYASEtIH6wch8Q2OdIfLP37D878Fb04fMurHivSHzOP08Z3UQYwZD37exIH1UQxI6BGEG2QA6UNC/XjEHveYITQMQXIlN3jXU13x2vrWfjeKROicdkUAdjBKAA5voe3tVmY/tsyAxmdohhez4iXD4GNI6uYtz10/9wAqkZ56KHRZFhp/bGwIUdwsDaHa80bXtHrWzDp/bPEZcKMe6p7F3yN1Sl0NLYJINzU81MrABQOHeGOjX+Pv/u84s6+ds56WbjNvB3L466+KzK+U6tdCS9hstB1fuGLScOq1Vkw5CzVRIamDMqtCnbGj5LynyBTF4xxcO6VzrXIOpyxGbuYZDhY5dM6pU6gLzVtQq8q/tT+Xe1X0J8Ljs8RhYBbjRuNriEhpPWm9MHuO9mnKSClhnguM28hTQqoZDEaZ5UQmZlecV1OoA2AKinBfSIUuHOFipFcC9OmMT9p4o8yi8ZiRn2lQmnT9IkQL4MnnAaR0Q9jIFr5+2u0wZXHk4lKVYhADqokmZE2FRLAoA1WM0HR+LdpVThmcqvMkzGIUKs6AYtBcUZBJ3iUUMTCqACeGCaUtpWgbI3l/oXtL5r1qRJoWdQQcoGIgN20fmS5FAXU8FPHCoLlfxbNq/Xm2vhtNl5oxyrq8q9HrDxD6kInxDoQ77V6ukm0qEeFO27xgxhMBV4WbzD70+FHbug6sgHRIoUzlVTrAp8zwC6EZMDuPKf9SVJ5DMZ+BfTkkoWHq/nhTNM7y0F/97eKbCHcJ6x+/lR9Weliz/syvebivtHm3FcJHp67t9q9VoP9cGuatnFFWl8SBnnPobjn0uppfU1ovGL1AYuudeI8X9/svXgKSm/1YPDu1gftn5hEC6hX5Zt5iHuGkwrb1GpvHJ0GRIANrFqZOoMVR+yC4EfMMseRWZNTCC1L7pAphVjl4hqiRXPX90ViTyuxZ1pkZXCo4696JHgycvF1pRywFJTSP/DPLdTEkjczSEmQa4x+ZgJ5V+RYM9yOw4/k78T+n/B0B+zinI0l07rsvXY9sKFaebV9/y8z9jFn/T9+Zb6WVpShnvZyzp17e2SvXYcOevxbGAAAgAElEQVS+9vtfXwjrs7d1HbDQAlnT6m9aPBtbp/B7veWMG4ji6UHvETJdo2qwzpFOWjvfp+Z+DRKes59ie22G1hl6eXYBwnNnvka4BPDsggRXGnZwtNGDbZ4iLRlpiZ7Ci89p8f7GwFb6fvreeXjopXl9Dew/CcPXt+JKb769MAoIZyrRV1p+abzjnLx+DuVOvD+Kk11tYTId9CEZKYvx6rSbsNvtsN/tMO2aJ81cCpgrSimYZ0mJVC1Ep3myKG9gsiIiSHSnDFGWk+T+ZNZvXRhcUWeg1iIKlUQgkXxB2RCIp5QIC3f7CfvdHvuLHS72F9LXnCWUfFHZYakicJw18lip4MIigIxh4yurJ3XjMdh5DlPLRD5S75mMqwJ45sV8u8PAsAXP58LWnvcKmBEOnTISvMAl6ILAx4qixjpdr1kFeWAAyRWUlXt1WKfn4b7NzuhbB9/ZvZE9k5stz/qawXdrM+IMQkt30d45I278Rp2Ra7Ycyv27EWYbn7oGhe05jxUM7wHg6uHX5S/AjxV0vTzVFUcNT61G1tfL5FdmBESav7b1t6VMSGYypgRNuk6o9y3XuY0vXVv6tQbJHIez5GZn6DlXnloU5nADdV8rDS3b4E2SUL683MtxFse7bb6fAFyF+Yk9t142oX/GZRAdPIJwJWP4PaH8KR7xhEbnWL8nlpzd36ew5ziPYxmprZgIgGEpAPv9uYb06se289IHQvoIHP78C4RrVNyjfrwdPmEU3G/ip9ZKUyinDwn0MeRvtb5xq7NftyXu8fHqkY8G1BTrQ9u1I6Q7B5vb6kdjTNslhiU1xmG/V/XvDn0MtV/FR57D7/yMEucwXo/P4/Up2mft+jBuwK2XT5bvt1rn8AX2t0UwWuJ/0h+JVXEbEGQF4+k4Y7+bZG8qDGeI0rqqN3oiwuE4i4KdYh1Lw7xuvwe5bKKBbqAsdFb4wKE9M672ezw8Pw+G+0AmQqEIZe2bMHpuMMKVv2Tt0sklint+aWDYX8fndMb7W9dG76zBgh5nDw+Hfit6hJtQshnxNBoHiST6TEryGwTKScLkA2JkV8UQTWhnwsQZNDXpeKKEnMR5zegCQH5nEqMfcUKrit8s4kFLaSP0OYXOc7eGMp/kR8q8+C12UT8H44K+9jrMIwX6cn2qN8sdAb9xb2RVkuDyxwAaepzQ8O3YVjvRhjW2oz3xOCWhuIEkwsjDvdinrlNfAfxHKNS85UO9Y5tv5R9RfnkI91+94V4iRP5O5Vv6dhaRzL3/TP+dgj0egMmJimOYIhjzGN5fy32OQBzEtkyh3CvSA1ZAQ/ib86QbbkkS8sYENUU3szEnIdTOyg4ePR1aPSq0yn1uNw+dbwps85DqiN9ox6vkxOB9PXq9OvOHAZEsaFLyf4QkhCllUPQQqIxSNXw6JEejCPlMABYsEoM3odEEZhVZS0WlipQptN5EJwwhjqLyvDB33e6Jkb73tk6iRCd/j2xsCzQPDBONt/Kt5R8+h0bUvxZad1zVV0L6ceq9L99eHNyFqv9OK73KnP1Hlu9EgZwrrdALWn9w1k7+O9NMW+X1fV6jFJvQfRrOb7N2HWd2a6bPKVJpMkM3xYhWb6zPfhfPftaeFjxiJdZFaOHlvi1ADfXP1r4/556MTMLTjgIl4BJGAYmsgvRePwMxvzDQGN7aZfJcY+7XaKjxnVYiJWfp2NyT8tQA1x6sNNbB2JFMXvkszvuEazAYRX3hOPyv0URNLWIhluuDUtbBy1roXXZ0Mor1pRSsl0ZnmfKvH8eMeI7MT4OQe1p3sat64Zx42hAs5ZER6b6mge4nHY+80Sh2qSeehHa2erqz8R1xDiOvZKGTJySknJBzxm6akHcTpp2w3VXzN5ZSUGbxQBeDUfHqFteeoOQgUajHCFU5pba/K7s3DZSOBqoIDkFIKRqvApZSICXJF7rf7XBxeYH9xR4X+wtMu52ExSwqhISE7pfQ8gWlzuLByQWs/IEbVxtPRQA0B+ViXrmt0AJvP3EIL2rrR0C1XJ/Nc/R7lAg923q2yFgc+BvtDva4xMXvV3j6dI+SNSN0Se4VafVOFxnMwPPhCRN2cqZSO0/C9sn7sn4m9DceGV0uVoA7TyKbXEpNYVBqad+j1W9CyQqLRECYH0s4SBabwgyW26zES6t7PPXJZw0gzOF86nNu/HHb2aLwhnuPM+hKeFF+kHEQJU0bofU9yp5K1wl0S77v8MTIN1k8waEKcA2lC1YF9wNjxxdgyHWTMBPqfZNZ0DVQ1YjAPOHpmoD7tk/SlYQl5sJAAqbdHnhfMc9H1DtGfm/rRB6W3WBRAuGoOcZRYqw9m5adwmbzKGQUsjDqrPKIi3aWvlTQbQLu4/x2i9itJwGY2BTnPXUSv42qdAZhej9h/lR0zq5AILmGwGHGY3i/SUK2Tupr6KBdkPUQoEr0Bn1b/xvsiO0Xug/3akhzdaPv1DBy7ftHgHANaB504D3qx5YrPpYYDj22vQOQcQtzB6gfGekPMXAUPz54woQRt5+iQwzEmpf/KL8jjsHdG0tozng01LUsS4kWo+U07z3I2XOnz2AcYbnUN2D8DygXBl+GQVn7B+r3yU7ftxQEz+txfr+pjOu5RoO2d8bZbrWshn1eKavPo0Kal2sez/jYPoMX+zw2suxTb0Yo8NvGpZiVFjsVgOQ472cs4mXCPu9Qa/XHBFb4LiWTnvOZJa94svcgSlSt/agRXcTqiFy5XjR0NnnETsV1Huld+lZqxZRbvK1m5EQoWqfUAw/fTsS4utijMuPpeECihCNXHEs0WxNcaWlcJmSB84qmUhK6N2VCLQzKkXqVHOsA/IBb6kqnoRiLndW+72dcYIUh3P6ruG/7VZLVr1BafOUd1jEm7U9flqeEATe0rPbb8BJpRa5E18kCMGsEJ4mQK5GOkoR7kTDkyV28QMhIKXt1cdiSboeQK4ETAZUwM8J5FJwuUUYa3DedQeR7iNThzADxMI/fu5hc3vQnFn7eZAinjEMBCbteAew//Ibbj3/hnkSp/qESbgDcgS2jDq4YeEzATQ3zB6B5ilv+c3v2MsbxedEfcZ6YAVR2ujfKXWy/RyTXsXZ0Hj5yHB7HA3R6Ia//jPreyo8pr53777VWv9YD/a38uhIAuAGoRRQd12BzuwYvkOmLxepY0ITb9aw9OqfV7YPRI6uvqftbCsHxPJrFelOsy90m+PXeOmVj5NmSAO+RL/nSUvx0IJzlgaqWE3m+chM4WFh382YppXio/qpESbWwQ0rcrIaEYagCvaDmLMKhqhiW+xdNQc9VvFtqKRKikIIA67V777uVX9XuW3krf7/ydhq+X9nyGjrv2+VajFD4NLG47vd7soGz6/4Hlq3IMcP9r5m3JuRquLYJJvp8Y2M7I97fWtLX9CsKYF8r1BuFLlYSLmHql7j12i61QMMmNLfciT0F5FcUlZ+XC8/7sU8vncKOgUej69bKqZQQ55TvDWPjXmn/oujsV0H1urjDK/f62a/oFe8vl6392l1vbWbmJn1cWdct+pdSQp4m7Pd77C8usNvtME2Te5sfj0fMxyNmpXXHyF4eIpAAYs0mTQk5J1CWsNWoVVNpSb5GripkrKJMt3yeSZkCC+WeSELLT9OE3cUeF5eXuLq+wsV+j/3F3sNsVy4q+BO6vJSCUmZR9tbaolIpb2AeUjafLoTyCUag51VQFgxlOwEXNUFbq2fLWKObeZzez9vPo/I73rN+XOIS0+0eRITHT/cStr1W5bksVZS8n9XQYz40b+7OaICbkJB1b8VdZB7r6L6GzxGhKTiZm6LVBX3ot7PzhNpOxYwUxEAqk/S5jrBuWecELLzUQ2vB9UkMZXIn2Gz9ZOARyNfZQ7DXx+oQ3koicsVCusrA47B+T0BBRb2vnnas9Uqk4kyMdAXwQ7sHAPUBaLhF50GNiQgA35B7Pzb80xtqEaDebnJe6Jb6ZyZljSnuHdsBCbuBvWU3c7N2Cwxy770XPj/v1KjoloA7+ct3/Ryt05oL6cFQeizMi/eW31i42oanv0+h8LdRCa2XPDyPLTMk9GwQaYWu3y9udXsPQOIbLMbKLKHrT1Dw7P/0DTt7f5rx2i0q7haK7nNnTagg3SfDR+Y2YP92uAbj0c3WKtaw73ZL5/Qr43wI/b3LVp1b+WlpfP6rGZoXJ/gr6LSB2IkRTc6tTeibIe3IOd8Nvwz6jJTbEpr059rOesMY7PA3gVxRGOFnqRVUgYoYQaQvmmAHiZJG81l7SyEtsaYukpNQikTvcU9Ybv7aos8jgMTznSFyVmZ2nFG54bh+HZYzS4BGChJzqmNtRoknXMZWy6+g9NfI6nP4RnlPUovUymJMFjzrhDbW8OxZjEFTShIS/zijcNVoSFITQdJYIWvKGzOo8Uio2ifVdYi+ncCVgJx0tzCSpi4lM2ZDk53LXqhqRKBjUFqNWSMXRBr/9dP504rRHJUrbv/4HfefPvkziyr0pMO8YgnR3uHcLb3AWS23XxHvN3jg3ASUsVnlzd7KW/lR5U2B/k8rC0vCiDTkP84oG6fhxMnwe1E19cAyeItLaqwB8a0wc06EKJPBGh+8y90GOFO24IPWhrz5ZBuFbxEZLxEem1ZVauUopoQa+o0IhQNS15BArjDu5pi6ThnDVMzCbHVE1PJ/qVRE6ENha3MW75iUckd8kOZhB2Q9aqmqQFeizZXooki30DpAL9hv/dHQ76WAUxIhgFukar9YPXLA6t0iOdZrrS2cfVCij/tv25qt//t15fXk5s9C42/kwn94+WEL+HN2xq9gxn5m+Vn0OL2gDHqxGyNaP/tbEd1uCp5eqPtby7fWdS5zRiu/XnjxZMlrmKXzPE/hNtnjF5vr8eZQffhlggMTCtizvXpS2fWzussthMJfOfFrwuVTe+1UMz1jfOlZmQFCfpdc/8Jf1NvrHaF+JjdCrCpaySSsvCn80jvqJs9oxvkOyLiCezYDrlAf+zOO0cp4UvrAA02c7/QNtRE2qve8dTgFW9c+i/eOHrJfQwnLhgEFlYz0JiFdS7hjwJRaTaTXFCCE5trNPpztMM9xVzZ+YVt1M5Z+h11ciafk4fGAxhHU9pZrRYwWNU/l5u0MYMXzyfplZ5Tjbc9HCyDkbWyCmi6/e/AcdjqdEqY8YZrkX86S05KZUeYZx+cDng8HV57Ton+6CjrtIBKPdsoi9E2kaY9EsS25BKuvI1cOWhTzzieJRJklVdRuN+Hy8gJX11e4vr7Cfn+B3W4CV8ZciuwAFu/o2TzlZ1GilzJLGHczqEXtIoct2EHjA3XufF/YfD+zH0ST1/vcAoBFGgDavtSrbuHCG/Fpf6rWnve87eiJnnmPiw9XyPsdPv3rX035zMmPRWJCvm5RBsCSS5IwwUSSnto+yXelWqSIvv1E6nGmOVNrbSHgwcBuJ8E1Wd2aaik+Z3H+2z5lH5eNubo3vzxJIOfDe8OkyIfD56Qr4bIyI5uCWqMhVNr5d8Si8CYAF+8nAISZzBg7ibeu8ob5Vo2v70miajzKmHa7i3ZWbytwJz7ARxa4RAzgjpBvSRVABUyEdCOf1fumPjRIwGhQ2o0T7hm4EflGuvVJde9HT81Wixqdyyvz54J0Q7rOLllR/FU1B/sR7ZiKB/5scDbsUQYwGf5SOETvlFdXkGSwp9YCfGl7XQziI8QcsXbYF+8J9XNvhmHzwQDK5xJO3Zjiov2zDp0jo3mpXDBCmwCpd2OG5d8l9e1m9/obw7eDht8k0fVA6BTPEYJUfZYgGKV8+gzgukWM+KQbFA8gwE84D/W0vfUAwlU3G82E4nUlfjWmBRrlQQTDiAkMwg7XSB8mPH384nnQx37H/TJ6Rl/pfngc+mR7eAeZi9rtovbv0M3Ot5cdN0iUdEnEW7WNnwFc18HXmvq9e8Gyj44/wBP9VPHV436+x9PTctuvPQ99HpiNaIQWDyyHN4aerPdzw1q0xxK0fOCwb0FBa3dJlZUJEom7KRkd1yTybjpedG20RKy01DhHxYPi6CPRMogIecpGCmEuFRlJ8jkniepCGgFGDLXIFSQ5Cd9RjRbxeSBPx9J624ZMkLSdpgAGhKbKmiOdEVIfKE6XSKBSk8ld9xq1qIt+RG1aSxU6zb5TsmNJHdFwrd8b7hi3fftu2G/cP0d4OuKDryuy6sxC23CpqCbM1k3ceBqjQ2Suk9IOtWqKIZs1Nu9yPV2a74KUsGGjcNStWOaPkQiY1Ftd6DwLIi+KfanXqAaJCFXAnlfeRsPhh/MJ3cz9uCJ0ZcyBPmKo9fKk+4k+fcEFgP8B4YmAZ1TcfPgdz39+wiOJ8pwhHuaxVm9vMGAZWyYyOl+fG4kT3+RGx9YkOC9ZHodk6/eKCaHlb2f/Ns4Jhvtv5Z9d3hTob2W1CC5n/cHxpgs+1nLUbNfXOKmEJaL29/DtwClWvV0XD39/cjHEr8k8SK+dnQ9TW8FIzE472LqY0rojfEjFPYr8jcpysluoDmQNKzlNE1LKmHJWz/PeCKJq+PYyFyfyxLvFPNBD3kMAa4YVsVRmpFqBJCH5GEqUV6FkKjNKESt+mEeOTYftuYURx7YXZVtlPvne6a/fylv5Z5atEzCK3069+1Z+cBkWI+LWl+Hd62Di4t1/NCcRBUUbgqWvtMCIgo9eZCYi695QbXnyKhjF/cAWnTqrD2vn+XssdxyTXFM33mB6IIz1+5ZBN5mY6h2BvoiwJL9To0QVqjVJBdQDj0G3hOldRv0igjFXMIaxjmMbRJLLcdDGd4PSybu08vtHlrPWavOlqEbvhdDf0rIEJH7Z581yozOaYlFFZBo6+jV+c32PzhMVL2vpKMioRA91jR4XNm+kwlRmoZvnecZR/83HYwu1qEas3j8K8RjUCJeYOmGRKcpZQ8JXXvH/W5x5yQM6TRP2F3tcXl7i8uICF+oln3PG4TBr+iYJSX2cZxyPR/k3H1GKGdDKAIXV6HOXmoLNDKGFF1E+UqeRn9hTBgAQo4VBkGXzHP+9rsTdu02xuKcy1/4egB0ucPHbJZgZn/71L61huyfC1wD10NSW8X1e/Ghr3kLG6yu6yXq4mVwBWNfq7cY1frssrALoGH53DSa2Z2VBPTQ5e4+j0kJgLA9MMVurKSXku3RNyEiY7wqYGOW+grlgut0BdzKPJgi3OU1qnG2iVFb+t3AF3QHpNvSRkqc24PD+wqA/QEHiSFxp/BMTqCpfXblKBIh7Bm4J6TYBLi/ROmtrhSC50SU8rQXG3jmsE7jRAuNbf2xsyeLNhu3Szse6SDlSDou77/qnW7t7vN/2lqhULZRtolMn5LySud93KQCFCAsYjBpeNG/9tf6OpVKD0+P7TJB8t3Sn9x+Q/IVrAMu21tpjPCisbBSPyXASrgE8dB7h5/Z9cQbDt6b4t/vpQ0LCLSglcJGdFhXdHNpv/bZ91XpSN3plZm15+OJH0zw9nu3ngIBerqYPGX1edvPIf11cmx9dvg+DtR554ueWNVoZes9sMz1C5/iOGZBxS51ALLDU5JY5JTcwG6E4AJcdWu2X+514Naty1FJNhi8Gp1YKSttITbTIKNJXgfkxfLbsM27h3Q0n6KlrfEubk67/hv8ZXVuOQRlO9xn781obkHHevvdueW19QtdKeopC4q0v/mfkuN/2tcimK2olgJQurQCbER4Amysiq0NjBSnQYFajG8AAs78LiAFH5YrKBFJEQ8zaRhIaGAZvCIlaQhDfRxxxf5yTdvWjTqns461TeLo8kuQ9v/jjPaaPn2FmrLGmp+XBO7v05wzBaLZFVGr4kFs0Lcga0JmAO+LU2HepBxtrs7x+K28FeFOgv5WXZArODQSFrSsyHc+80AZ3f9eIuWbh2hDYOhPS6jCEBNAmQd8PJIJMa+91YLFn2V8uSRF9tIaVhsVSOqvluvXRCLlAwsFcNwjAHARQbY5Cf5zJp9YO2i0iEu+VnDqvmJxyj8F0rcyzZS4lPLJQk+iU2qxr0u0JXR9n7FnEp1SKrzWzUc4mgFACaGRmTZnuxCfCrtkmCprok194s//qrbyV716+Dz/8wyr+ll0/EqT/CcVAHqEHfz+3DyMrsvLOxn2HZ4PLybp49FT9G2/w6+v62ndfXVYUlWf34JUdy4s7UUTZhBVxHqMXYEd5nOj34rq70fJXA0CiSzAeQbgC4wmES8wqpG0URMOQ55QXBc0n+nqqbI2TcKnCS1GNpvcJ9bNamX+umsNblN9EhPxbS2qYfjdFozDb5TMDxOJZhuqC4yMKpjvJb1dIvE7MayFprnAbu3kVsHqm9+u2MT9RkWqKIlce6VqNh/IrD8bY/qlqBBQcIf5gUiz3nQvVSQR+6UZqmx/Ec5NdGOT+MQuqd5sK7hVEsd80iOfb/RR+tbljVbgfHw/gwSCEVOS9PicWnHPsmq714gzaHrC29QR1/BG7txEZoeuKs6DQc+Fbb5Aq4c4ZQMHhcMDz8zMOR1FMk3wg34dviCxalXiLUyVYnnciaHQoyU1eatGw6s3z2Wh+XxdjRCBesdO0w36SnOe7/R7TNMHzf1b1Mtdw8/PhgOPxoGHnJV+75Ea3eTLiv81bjWvGYf6fGi1vzEHbYQZMde8RAFJRZMirucb32T5qfKKNXK62rhHuL6NbAbfv3gMAdhf7WIHjWuMwCAl0JaH1K1eU56p9tFzeGYQJbhgSXcDQ7x1Zg57D88hgdiprb+jCPcIIY2GHs7bP4vyYu3+p0pflyZETkcN8R15qpJ1MMWX1pHQh4eiNdSXJnkyVwZhwuC/IxMiUkG5kbJUZ+SaBH6y9rB7jLbR5LQWUEuYvR+2lQJiJLDKAwDILl9t5RKWE9I6E37y3eCbSL/EMN9gN0E1yLymfESKUwqh3FdM7xrTbof7FzYDljrD7bfL2mNUj8o7Fi/1OPOUSW18JjAOAAxIukd5TgClxbw6KSYYYhhFEYQ8gO8XCoW6AyDweJVJLPBHEQP2s++w9gT/bDMTFreEOdbuh0Ryi9BYdQ69s2i7rb0yB/iSgeZ6zKK4l9/ej7imhw8QDUPsRal7DlYav2zno3/fZsTpZ6ky4QaV7HC10i+47U+C3HOP9uDJEKZD/0LDSSjjO/2Zk3AAaMWjSLyud41dnETLamTMsuwMh4crTStRPFcwPINwifUgArmBGD4cwX3ZuTVHi8Gdo+UrHbjEsHA6hV2QeFjtlu+zCiI8b7+49CW3rX1SeJx1Li4+jcJOAJ2KPxHHJ1GAS4IYRF7ovDq/VQp4qr6L5tto9xTGcIjD79YlvcXdvDTOq4nJwrlnvBa00rzuKeYEn7L1EGQTGlAVu1Vo1ZzkpJRdp7PZtzpOc4aPA/5QktLr1cy4ViQRu/vb+Bk9PB+EjsmCynJOTLUa/S9XNMFDkkmYM1GgTQDzEdQAgIhyOR9xcX+M4x5QtRvZI9CBURi2zyzBN7plT42dM3mphwEu1cPHiYDSrc5HgM5WFI6a61D+BRu0eLCghC/ej9FrYJI2+CbtozdJoqPVbT47LimtBoqyGlQ0nWoMMi14qHWfO4oDFVc92iKSl35pc3v75rLDBp6ZsFxpP6O6ChMoJlWowdmo0r2ETMfJVBznbu4qsvb31pXhx4r5mXkcnN+dlrU9pXftcmXHDwHMmfCGA/vyEHZMbsWXm07oX1/ls990pXG48j23bVYc8vW8nVYzfjCJeeb3fvE6zx/aHx6swcqXTb+UfXt4U6P/wskXTSb4OQwwNsnMN14vnPdPRFW7PX/JSfl05lypde2+7H6eenOr9aWaRJZR6h7lXUEucX/tn9M3QR8L4+UAKE+EPCKL/QkBO2T3PXXmuYSVNxWyh2iXnofyLnubtb1Okt647OpRnRk+7QEjyn7N6m1ewKM+LYLXC7GHhzSqVgRYOp7MQfW05j5V/w45v5a18fXk7PW/ln16+Nf/1ap3hL9GVsvjXyrRfgvHkgtNTvPg5WHBkIL+lbNOYpKpswNSm9bOMoH4xIYaqMr8ITZDep9UOsr4PSsi3hHpXkW81XOOdtSaloGJ/O6HeLZl7E9kVvH7u4ppHpjyu248qr6s7GDtCaathv64Kzc6A7NsCkg0FBgDSANftHvlfFdNAMgo2dUjr09KjvaOL9aq/t+wfDRfm+/Dy+0rPb9Ruxp7zPDdBEYDD4YDj4YD5eEQpRbyUcm+mQ4CkV0qSZqkZu0r6p1oZiSRUZS0V5uSN2nwYU9KeiTuOK/pBhJwnTLsdpv0O025y5WKtBbVCPM0PEmL+8HxwZf98lBDu5kFFIKXz1YiAyddkhUUEt6wJPp9NMM0uzG7P2u+1v99SztnVtrL7qwsAwKd//Z/uw7i/04UI5ykl8LG4AcFry3hm+v0pKjITGJ7a2xifuWFGs7iLBnxJ9/ISGvjbXS99p3W3mzGJZQ8wj2/7nFlDmicCowCcIVEMTNjMGhYdqNeW1kwmnTmDHwJvXCvyNaE+1CDMVROpG4368MDgO/a85G6AUg0+jLtA58MYdZ9kxUsm5AWQbsjTMsR6TNbR1kf6T7eEehe9Dw/O4hP2DvfIhMhhvnV6wd3GDV70XzqfRgAkRgJfeije0pzAz6esmfaXCPn3hPJpLcd984OPc9X3sv3+XvwAcdhPXm8LIs5ohhtjX0a5yfh3TcC/Wg+JCAd072Pr8WRrbzyT9tzT6vmbDY7aHRvHS9AjftPfFwVy64eeKzBYA7DXPxn5j4z65xUIj7hYgScv0RUjllyD2z+yjP0zCqGgNwKw8jQYJKi9UIgosF7vf1PZNATdev+H9WRNftloJnshpicY2SqBsS3RACB4owSCwzzBP32+x36aGk2kFbaIqut7nysLHk/B8MzgfxcSW87Dw+MjpqkZrY6wIToA2TUgSvIpZfRYROkrnxNDoPYtAGIPW/6tsvU1WmJZ43ltnCttXe1HkPdWJBSqHp7dOthCsVfUwpgro1JFSsV1F8Iry/tuNk2N0xBw3o0AACAASURBVCMw0EUbUrNbRY8tr7kaTEBk4bVWFE0HQdWIXOmL8bISul/nyxF2PyuMeEkwL/aX5u1bVjk6jbRzs10eqDkQHGGpOfDNe63vw9A3ghpLAO44F3pqRrsWiUJu8ktDeStv5buWNwX6P61scNuBXvFiDCDQIzQW7eri/XYd7rqCtSGttVI6JLaNICIrz9wYx+33tsprfc/tqxeKAvSGCDQvp6JgMkQLwHKwROnSyHg4w6t1Jc8xKEKFCigCaV99YOCjYBf8rkTXZ0ie9RSU556TUfOvw+uS+i18u+U7Hz3L1xCoMP79/Wi5H/dTNQW75blXYla80DuKuiOq41/fUSuEdbx5LkP4c9i+t/J3L9+dDvv7V/iqsoFGAHwb4/SzShf445eW0514WYD18lyv10GL/36P8rOndCFAM7zL1IX/HUv0UFoJeNzq22hJhDoRv0Qhz7rA5yWlOg0Xa0JYub7UK7O6NsX5sv4tvLcmJBnpjm8phK3+E4ALz5UJwH2c6V0KuWStN7ICi9zQRlMoOZXei9enCD0S8m/tu/whw0Jn79EU8J7LloyeAPiOVVUruWYrnhZijyh8az+7hQ6CbaV7dDI2UkiunuFT53pLyLVYb4re5y0UsH9EAD8ycK0jJHR9F8W1ebc1xehLhQAkTLi43qEy42ie7QuRjYmx7H70hGi+IJlMsKhrpXECEosZBtOaZ7udCvZ70eMyXtsai+Gw3becfFU73HiNqoOgRK4YdHrUaV1R6BWu4PmIWXNxVmYcnp8xz7PnrGYgeFWocC9p/vSckaeM/W6P3X4veTwLwMeKmUi9zgu4lEYb114xakapzCwRqBJhSgm7XcY0aQQqZtS5oKjh7PPzs3jJPz/j8HxQhfoRxzKjsuRbF6U7d1oKAqEedDx7Ah+Cke0+ARcAP2mwX+6jGxhvw7C/BSY3jsqZ+Ldfdx6ux+enr7fuN+X5/110gqDnGyJsBUku8vq0PCsjy9R2o+5Bbn/tBfMpllJBXDu+kLEWdrkJ9J1WM36RxGPUjB3iO9nlvOuYYw3OdK9rO8QtnKmM+6jv7PSVvexVPjpsEXAuym4CQJo7nJIa7oNRxUFXQ6MDT/fP2F/vkacJuJ5BD9LDdJNAOaN8Fs/EGc8AAft66ecWlKCpaJU7ZyRc+PxFuJSTzNGsBl6XHy7ARDgeDuB7Bv0uI823CfULY/f7TvhYl+kSgCrGFUSY1Tf2qGHbNTt7WOUC/pIERyWLl+IL2S8CtzDdNaZCAEAkHvJjlCPxvA5w0fj/dwrrdb4Nj5a/jEpqdXTiADCARzE8o+aBfX6JJyHWK/8moM0BIBFSOM6sfFfC1Kyd9UjnxGvBV6dLFNuMsnqbXZNpjBFl7YxmHcfx3wUX/2uH4+EIgDF9kCf88RoV997W1INWb6fxX22U0bgAmupk98eteOVWWRD6KGlu6ENC/ZNR/izIf2QAt8hgzH/eK91jtfRRPvp4AmsRQKTEPm95ka8V8z63ei60Rc8Agn7eAXjUAXtuxTxE7d48EpAADnpvD0LWF5O1961E8KK85kS81Pj5dRnsj8YOTYlmK6pwM+ACkzEiPH+pvxE/jCfZzETa260I2kxKp5vBVFNqjwZKdv5KLfq9wj+lH3aqJZ+LGuQq4j1otJ/9NIliVKNdWlj0ptgWfFRU7rlPYsDlkYZq1XdsvmQe9zvxiJdIRS12U87J26nMyCmpIlZa209y/t2zXCeoqiK4VPk9Kf5IyZJZsS9opiyRhwBPHwNqxl7dAi3KsP6BJ4ql0cvrFUX4+s3FFafV575F6HHLUAnzDgbzjKrjdc9x5WeEr9QoTrYLGb6/Gr8El98TJaQskWeYTHpfBepVlYmjgGqMwCGQXriSxjHYl43vCPSbH5pXI82vmVIg7Bwf95j027qk/7Pz86gTd/t7/97jAraeNxAfuqdRqABJnvk1GNjRxtBIWyAgt4gCseU1HB2mYPGS4ZIxF7q/tnL/rfxzy5sC/R9W1oBMLAJUg8KSG7JsYbvRXZ9TmDkoVk9Dn/OqXGfklu+sUcJfpzz/2rIg+O1H5dEc2YsF82GSXCopJUwpOcK3SADEFdWoBWb87//5gOc/P+L/hTGWwEdtIlFCTi33uSvPASVWRMhca9X8hiIkq2VQaJ9RGvGrZIIT4ghe6vbbAmayh24SYZ9X5oRt/Du2tx1eivy/L/T6VWN8K2/lv6FEgv613wFr0PWt/NQycAnfNQf6sDH+bnxDHjZbNxUrG9EYn+jr+ZISfbssZ2MTB23cHwVOUYy8pBvkLfdQA1zBG+vaYiB/VulF9eOzi9B/+V96R92XPhfUQhNa+MhoyEkg6P8B9cqloLyW26TeurV9bwpPAOVzccFiurV5b9/T8Hd1bk/SHafLD5HTduUIYBcEoVIsnCEA0NW5PXiN0HbCclXbNbp7RqmuUWomkmtKJAu2LGXptT32tDMaWBnReOaaqNlqSSrYsdMXpPkucLH57OdIaOni8KVq2PNSCooJO9U4pBPGpoScJT/5ftphmibs9ntcXlxgN+3c86nWgrkWUZCMY2cGNB9n5xmbJF+oGdEmSh5efi4zZvUyPzwf8Hw84PD8jOfDEYfjEXOZRXhYpL7KVQwzDjr7OwYfZQwVDByco+zWhy7EpJgfzYCgAKieO1mMo8uqYsTHgSag/NlUBy32XQ/V6ooomTwAetnurSqfI16gEDidhogLZwus3fO8GXhEoyQT8yYiN/oe6x2vm19WL1A073Hp+w6MY4gg1haUwQDtwJjRQu8H/HHPwK3ydWopkG5Iw7i3sRweDri8vQRNE+im+HMTwHc0gSqOTVljg6IbTVZx32a6ib6VX609LCFm8F11frSUKl7uN2rykCfMc/TgVviwCop6L6tk83HHkpc8EDOk4JLvGLgl+auTlpgAjcDS4FHLaz806fjTntYv7Pi43jHye3mh93jfLra8lb4fbouC67XrRR/Qt01YnpP4OxqhbCnRafxNTRC/oNO4YbQUvnHcpmH0j/86gn4P5l1hLWIY9uhVv9Y/e78/yzID5c+KZzxg/+FW6v9A4I+M+rFFKSl/impH8qNfaVuPHZSKxiSt9uUixLl4jeJ8/GYfalpXpQzthnXg4R8g+/F4Ihx+7GlFUKL83RierylLRqIr26vU7/rXRNVqEr4VHmnjfaOBXHkbnzN39P82fyHK9lrrxht61pktWjl6bMv9i3pZWdIvlCpmpNM0nsTmzCXoigBqisfKjFIl1Y6EJh/ll2KkZXMA0mClTldKPxtfNMreh7nWywTNJU1COxRoap8T5RSo/5YjcSYKWbbJaHybVYSG3iozJFy7zn8SWXfKpF7rhJwkKpAp0FlThNpfq5e1YkoSlTUlAuWkdIMY81ESI9jKFUzZ++Z/DUEotRZxS8uJ3jzNHW6pQx3z9t79nuVr1/GJgIs/gemPv0T+8t1hpOx50UMZlb+MEsRQIzrTejtvb5Tbehm5y5GDiAZZcY3i37fyVoA3Bfo/pqyRMTw8M7LFGUtuD5oHcEAW9sIG/aFcsiO+FsJt2ZtsiEWxYhmQvDOtxqCdpblvNtatxa+D9iMztvZcGCqbE2WAlRhM1PKudEyr0QR6L8PQhb6nynEiyZ8zcRLii4RoYE5imVcrfifg/3z8BBDhdzSeWwg6sabLOYRtV0FJZcs5LopzC1HD6oEePUSkW2fOoSM0XYW4ZqtUtIRKqpYDPey1jkgJ7zs5vdGlqGzY6OR5Y3krb+WXlh/DyfPw91vqAP7+8gY6DQx+WXk5t9ypj/sXT39Dw9ULbzd+ZLWGHz6VGw0Y4ZpeMR4GVpXqUo++459vrMfi+0BZrHieU7y/ssZbMqmY0r61wtjjFvm3jPmvGRYgOApjxrN46lyfjcfPKITFNly0RbgA4xmES7QRCVvqCg0VYpB63ZnHHgAXoJk3ilYgxBWbYMkEFDa37N8YB8yRpniv119abtp6ZxU3T3Rp7albYxNmtUFSYLx7erX7Zpi3tbncYtYXzP7K9/K8CRFc2E0MWpwYgB8Bk0Cbl7opAN0/aejImtzEZoyQMKmv3eFhBlg8xRmM3fUOIOB4L56ns6qWd6okbIrrMFJK4Z7Rc0q7rgrxU+s32lrA78R7/Z2Y09D6UpmRLifwMyNfJdSn2bknl3URObCMNGopFfNxdhrdIy+5J83yFJrQb5omXF5c4PLyErtph/3FHrvdzpXeDEZ9rq6U7xQcSi8nlyuZNz4hU9J6hA+wEPO1iuf58XjEPM94PkqI+ePh6N7n80ORHKMq5GIAlaoLuOqh5xZYQy/QRTPUBQj12ZIk2NuqUI98JXYqzJrbWRgEWyEQuf9CqOFrIVxMRQUAn//1JyoKYhqB5UeiNJV2SfehvWsYq3S98vOpLEwf8lvG5zmrQShiqSDHAk3Jtg0X2jq5gRE1nsgMjjIZB540v2UzFGFVpUWxrin4ooGD41cyKJBRcJSeOw9YAUyKR5NWsDPRPnCZMD8cZe6ugePdDICxu9H5SzpRD7I2V+8uwczIecLh0zPyuwl0I32Q6A6MGYzL25tmhAU5i2acBQIyTTL370IkPAJKYfAdY/4ivqym5n76+KTjlhV8/Ouu5Z+/Z1S+BL1LrvipX1p0iMpV+Fwcfe4SLnxNQUB6F84LM+oXUc/k98llDExiH1MTJFQ9gGmawKiYSQX3Ia+o9TfdKowi8jZt75VUUO6B6WbS96SD+V0GETB/nh3niiLC9huBcYUdST7yolrP1/MV407WZQ/4zEqlh/AmYcfXONL9yTMfoYsMw3b9eb3ya5b5z0natMMx9tPaMgVKwjXyhySpC0weps4GlAj0BwD8hvKxouKumwVGgx72zwyzTIG+/39+U2cHQp4Snv91kCY+MdIf4k1JHwjznxJqOOKM+rGCNSS+0D0P2h658idGLYh9G+lVQLzJX6tEd4/z4b7ByQMxdkw4Wg7z2uZ7MxrHGfvwSIwjAVdWH4ss7qpKjt3n75kLfbWszeCyNHryNL/YGTTByBOyI9+dgfjleN/gmxlVneIFlw8aDqkc/d/XSxe6XUtRw9fKVfofzo380f1iSmI1uq1V9626cmedkFKFYixcPIoYa9vm9c0QAzAlVWQUzGBV6oEkos9uSh4ZIeWEMs+Sx9xYEzXyJSKNsCoKePMqj7RpZYk+MqWEuVbs8oTHg+CHy2nC8zyDK2OneRks3UatAsetzqye6c35Tc9OZTAKLH0PEaHU0vDCsDRrtP1yz4QXub80o5cF3LT+jDdW3us2Gxtd2RrqaHjmlh61ApwqwKL4FmNRieZktE+trIagkNzq0eKLWNOaZqQsinhQAighF0IqYScfpF2qBUXnG45aCdEISnBAM3+M9gC+TjzMz3cqPPyK/JH0JRhlhs1g5JYBlCtV/H/MhN8/Ahd//Ab++BFXFXgk420aXn11HylpxJSWjK5R4s182egkp5aZUVlMTaPxGexdHq7Dcg9T073HG9f+3bDv38o/q7wp0P/BhYa/XrgJYORakZNhZMCt5D3kXKgr1mcMGBmTsNpgbPrbvMN/BPKJ5WvrFgKffOxxnhpDpP9VS8Skv+VewpSzhpdiCVnJEhYoGXHHYiXJDPzlk62MWzLv84ScmvK81CLeMKW48twZffVyP2XNuT5HKqAOzGFHoVEYrQ6+ou0VDnlm1gwlhEg5fyXekNtbeSt9+VEw8keLGd7KsiwI+++JBIe6fiUs3a0wOFv9WZuCNaHA4rtwMxo3r7fQHqwZQNDG/VNlwdQNNab3GTGU4Snl+Wvb/dpyah3GN0kzbZqgOb/LoEQeItZDr0Nolqb0AEpRRU6kR4hUqkyq+LHb5OERm/1CL0klShqal5Het3CKEtqdNU+tFQZwqfvqudW3OSN/p3IEY+9XLqxB8+J/qSw9APqd6rInF80AGGZP6MLqShvZxeaBbApxE4tFYYn59jTvT0lmFNM+WaokQnLFQOzzQvSxKOPZMwEngZ3P4ac6vBvqNTqX2py6B3otqtCTB5SS7u/2niu1iJCnCfv9DtfX17i6upLw7bsddjsJgV25itKbK+rcwsCT09w64yxzztWiMbQ0TkmNaEut4IOGaJ/FA/14mFHKURTqjzMKzSjPBaZArIMHjSjqtb2ozDfpFQP12Qh8BtxEw/7a+wXM2debqV/BkW9C+L0m7PoWVCjCkZjEI/sv/2/oBFE7U70hQOv/Vn+7SgDnb2xumof7hiB7qwTjI2vX55AI2c4Nad5OZEi+8nZG4cYtlobB+Fm4gfiYCz1hJ8JithYkAh3TDowDEik8YksLkUBckSZCfr8XRS2ZKUzoOxFwq+kG7g2+y9nL79T8PEm+9ZT7sO69gZvMAqvxh8pgYaP2VyM9oP+1lW2r0frX1obBX6pDIcT74a22T60O/RVggbdOrX0AEuKeCNNvCaXEaBYZdCtwNofP670YiIHgOFXmTj3ybI5B4PsqvRsMSSKM3MrW+iN4gFF47soTvgLRIyoxmB82z9VWn1aWeRVDrMIWBirdI2M9V/nYF1GhPaB+ukX6o8c2ZmBSP+peBSHjtlOix76autXMkGRObjxSoKWsETOWm379grUAAZj+J2P+d0H6QCgfgel/bjH/+w4UxmUwI665PY+w9ltLHKPVa/8qgD1bqHUKfVo3gKjU+n84UwFeFXXHaMrpew3uV5WR/j0xlsUjRXLRM/w7dOXkQxpOTm+j2kK7W1lQePrDHcE6QqEZOEY+xGE6NfPLqsxfhOlxs4tyX+nWUpHShMoFjaZmzEVDsmsIdx/mYGjpEUwAifpJEq59LjOejsfglR6iuwyTGWX20cB4FZ6xKNtfK9t9TfmmY2OKfgDO5Rp9vQDW5HNq85IAoFalswlTztjtdsgkRhW1VMxzQSVCKZFfIVCCpE3KE9Ikjmfq1o5cCWluEV2Efq3ADKCIEt06JrR4y4PeczDWXhvGOiXxffGp16x9e23t9wTc6CczARP/hVtex39f2TO5oma+2ejpVtb2FuneIDVa/BF0yFrpaOq38o8qbwr0f2hZO+yr4HRAWGz3MAL9yAS2T/0rE+psCB2rIRjHlH2drTvraHmL6aHhja9Xz49k3bItwDx4+q8EuYsVp3lF6Z8wPhWRdF4CigQSqdf4hAwNH0OaJ5SEQPvfv/2B/+/PP0EqqPjAhI+B88oqsEspeZ4+U1LP84zj8diEeGjChpFYjetBgblfD47VBJ8RAbrXjfYDpJZ5xT9TQVxvThE90V8qthPTT0Ztb0j0P7t89/X75grfdtT3KF9hEPvTilmFf93HVodej9I2vzxd/9bzLQ/017Nep8va8F1dMTTUwXaK99be68tSELoxL1Y1DfWsS5i8LHJcU8STduultVjWbNTL8+fPTQSv9IPZtJ+9Jmfsta03RgHnuUV6/ISES6drEgj1S0X+LWP6LXce5kIrkd+z1DIuWOm8E0TodPxS+uFRa9lKvhWB1/yl4OqPS6TdBC5VvQcrDp8PqGDsb3fqjW7iDw75AftNQXQFaCh9eYcWRhcLz/UT83rO3I57Y7Huq/uUFt+ZAaO1bkKLrEpos/uPih/5W5CwDwKhGRK2XSoUb10RRcaQ6/NjTJbQ1uaA47Dv5fSbJzuBQJfqXfQI7G52Qrs+9iGSbTj720sAwPPdIwpq8AU2PkNXK4wdaEKXSNkygPpcxGj1Yof61PZY43XqYk8CAJeCQmL8UUvxvbtLk+YPF4GPR2DXM51Txm7a4fLyCjfXN9hf7Fu4da44HGcQSqOT56rhDMn7w2CgUFg5cmHilK19QikFx1JxOBxwOBwwzzNKmVErozwX1FJRyoxSq4StNH4O8PZKrc7jST7K5oOULhLKU5G8xRW6F1QR6XFULRQ24H6WZEq9FvxyCd96IWQskT8d0eP4TbzPgPuZEwrULLn7ots24SfXKuE/icAUPdDDuEJNpAlEXADpQn8Kz2UkFRUm8ueFMkPrPRH+MzlfKb8ziYd/ooSMBLpOwKP5m3KsVaHABA59Db5A2K3gOIPzDGCHvcNy4BIthGmDKhWMcqcqQQWx+d0UwpFD8ALLOUo3MkNcKziLItyjO+iip5SAW3gktUTqwa2AL5GIwEox3CHttFyykm+d7yzKgnjq042eM1Pi40JGzQTL37kF5z2iAF/iiGcR9rMYAPCXKuPi9j4TML3Pcq6qtEk31OAYN9lBKcXHHdOacWXQLaHcVdBNy13NloT1nhV/yV63VWYSvDbh2jYC0vuM+rlPehMVtEDLRf691DOVgMSWR9ZMOqS/0++3OHy60zklUaav1BHvJQAgwhTEWzUAjFN0lB7Pvr5s57/VPwGamCJGTLrB7n/tcPzXAfQ7UP8UWEh/JKBW5D9UIfdROpLxTuDRh4T6kVHwBRWAYb29trX7n9+a7AZA+SjGhvl/zCCRfD+klHDAQSHKI8q/pY75o4zh+O87P7cTlrnEgYZTRrrFFNlfE74dECpqp1DvCYw9yPuQoMpsSG54g+tJ58P6AMC9xl8r7zNP8yumbu/uLJKDtnH8bh7pW5jpxBfn0O+GDvyOGQUJbbrl775UXvcYbMnL9L8oXHKobxlyvC/Gz0iI9NYzwTsSZXO/m0IqJnTvtfZk8CkJBufa6PdWH8DqjW9USk6K8xz+q9FaUq99pcssEiiH0fkIOLal2DsnTY1TUWpFyoRSozyUne5h/v/Z+9IFt41c3Q8oUurNdpI597z/4907M7ETuxdJZBXuDwC1kVSr23acpZG4JXGpvQAU1oRgRsOTRU+p5bAAMM0RTEAYAkgo43mlV91qb374gih4euHT1F2r3lpZnefX7fYK3XiPun8wBzLSudK2CYoMGJlH0Dm3kxfpXBIEkAhYZIGBA3bDgBBYjUY5gokQybAZGY0kXeOjpTeiEMCBQBwAAuak85Ng+ezNAU089agkRHE8oYa3ZIiJXHZdG05sjVKz6V6CHc5DLqeiFfV1H98+jU85QagSXUTwBUD8JLincp9frbi28sn5/Za/cOxS2tHhABHAoi/Q4r3yvVmXZ9b6Vi70ct57Uefe4G8Kbwr0NzgLiu9NfNZT3Quh5J488wwKy/RMac/cWxOJN6jxmfK34etwplq2eW7zvjAP1acCNkYwYYdaxBIGDhgs3KJmY2ENnZgItynh37//DibGTxD8BsFvJE0IdxVIF6E0YN4xczQF+qw5z/2QRWzM4+vHCyj8QiZ8tScEsVNM9TQn86QxoWAy7xnwMuzoJlSH4O8edesN3uAN3uANvgmE7nemX/11LA9D5+hDdxZd/O6f+Zaw1a6teuvnixhm+U4xNFxvuV9drX/FkLEfl60y19r3HPQGA3V/+D0XgzqgGPm536Ir5XK+aH0xe+GL5btjAr13pYE2jpg0p6spwrMQzTp6+HjA1b+uTQgFMAsCAgiWy/bOwt3el/Cl2tKrldHaAzh+t3W0BZdzZ1J90vIWFWFnLShfCOXynaFbl4MV1YvZs4jwovb3v/3deg3xNWWFdWPQWT9jgkU2Jb7W3gd877PeLndNe8V6ej0gHWIWxpYnlrtIAEjU0OhJ1M/eczF6uE03DHFhr98bxhH7/R5X19fY71SBTkSYpkn5dhMk577HWjhq+4ZNEGVKNuaAMAQrq3hPTafJcp0fEWPMhg4CTesUkwkJpfSrCJOUyU+ihhLuaSUQECWko5ajzUirR0jZ+K5QRxro36sY/g0xr1TfLsFzQFF1h/yrp05LqD1lJEvhtp/XVsdVJWOP89fefQlk/AqPbqb71yOREQjylNXzALnpTDFKAdgiRMzFZItUMMw02JtzW5+tUS4nXwDLcPDZx170KSdvxXCnSDCzUseMrRL1ygAqntUQVX7fVriiaETaMc1GMJnI5HqsObktrjgvntHtjBRaXQvLSzmuYie7QBCkL6YeXjlzZ4XLgzSYhojKMnO6bp9k17xWykYHVuaDQO4A3HvPemyntC4rA+xu+pJg6Vqb/n5r2he6KVIlutVFTyC51n580pDjiZ4uUtj3PEzutWAj2tDzsMXH1fnLB9xhxhdM/xYMuIF86nhZKkruskKMcn0S8M+E9Gktr/ptacfHercUOZOQlhs/JsxixiZ4hGOhGRoLZsglS1acf+1YvBTcZGhneGArB7qghEbu23k+5PraKaD97WvNf1OzO55/f8lLbLVn/UQyusKUNPLWXHlkXgYb9JCyyG2Vf1/8zhe+P2db+kdZZpijTggwTTNCWIaSF78gLbYFzNs4SfewfRWAqOUtIa4E1AeDyR4TpBg8Oq+ceS/kvZvxr0EIDIoJwsp7JSmGXr0RjkDzpFPT0OUsJSm4UXFh4RaWlOjr4NIz3vcAN16oCfySd7RnzBg2sBlDiBp9+hrKhqODhWbnKtGTKLYTpMw7DBaliYJ6oJN5oFNKGjFNkhmWDhjnGRIDIidQqozora0lfHsxRKr5O+m/S3/ne8Bz/PLzIADuv/Hi+Fp9AwDdw0kgOf78ep96PqC+ntl3aq+tvfsG/1x4U6D/Y0HRuBJ/2GHVPitLr9qqtfqTEQyxmOku/Dydi8+HQcvT4hLx9uBFuBHg5qefcPz4EQnA7w0/I/k5PdNWv3NLyt8eURo7lr+7gEBQHUrrhxfg/U2dAcE6CnVhsDjbT1o/E+cweR7Gsi5LLYMJzBY2BmTh2wEQ5bzlmgsIABJSAt4D+C+A/00JQoJ/C/AzgN+qySBiC0ljArMkSEm9TGYL2RjjnD2+lVlI4MRVGHYPi1IYzrJGAIhb6JcQS8XwQgqTZ54H2YuMbT4EQBIT1qmnix/6GyaDyvqzkWvHv1ofb0Tuj4W/8oj/WVpeBHbPHbyXQCvfXlT3GeOobctzWCjDV1W5rKffzysM9TkmuxYsrj6bry/f3er/N2Hql6V+n6IysrxsNby0FVnY9xUwuOQLzhZIs8xz+dT2gdq7K7/WMXTWPAAAIABJREFUIfMhWBcIvFRIUJpKuYn5QExrrcxPL66dy71J3Sew9ARatugC6BSPaxzNevv1by88L/f7vVuukXmeOzfGINA7zvOSkmQeCFC+IM6z3UvKR5Eq12Os8sneq7fcYDlancfx+/xOy+c7RrpPSF+qXG+A1hGCCtM4YPgJSB4q3p6lO0K4J+VhnF9xHogA4GD94ya/XSPkc77kGVzSz+hzc7LG7y7LUaWXepyNcC6uZBY3RfM1IT1FFI9z56Ocmy1ZnT30dsIMxoD9zQ7xMSG6VzR5OEMNcNvnLPfQ7drOopy8utkjpYTTYbLVkrlNyAGYMdv60f+Gm1Dh9DJC83SCR6tiqMpvTSSpntLc0YP2HCG53YJ4mKo93gZnbttgp4Bk0Q0MxxFzjpyRDT0yL8wgdqNSV3gzBvNG1/zGgjmq8j7GYvx6svDrcYpapzUpOySLZ2BUY9UoCYgRAlWeT6cJx9MRp4fJlOViXuwaLl5i5fmT17bAlZSwNZEqIbaPc5K5HHW6z7XQjO3nef7HzxxbfNJz5ZwrXVD7wUQE8xbXdwLKTGug5HAbdP58kBYStwBI61mzVFC5gbQqpCOqsFxn2u0Yyddf8H1T7Q0NTxvMQFqNpPkqAAdvYjmvgXxU1XiAweDrAHqKUL/QpPfEaaAK/oOlinCl1x67vNAFwO5OUxAcv6iH3YlO5k0skJgAYow3oQguCUjvdN3u9nucDkdfVJBHAd4RmAJAutfGQUVa8zwVTyqLOepn5xLZBPmcmVLE9GXC+G6ER4oTAPLFVfjFYMvxnxtMCCznp0iZ+w3KLjDBiBwhtMcgewQIImnbrv/nCtPp1OAoImTPc+RrJh8gX3/VmiCP2iI+sVm44+gpmdJcP2E4PiHkcP3tKhPD+MFWlmPlxMnwjM5LNM/d1C3/fv/VJV/Cs5QUAT4HBKIniNzAZRJBbiD0uOqF3mJlNJ7n3h4hWHjwcp7Zwg95jMT3mY+jgnueE0p+8gn3+f2IBwiAgDuLQGD8ik3Q+K9Bx/O/xi/9wogfZwy/vEf6mLCzsmYAN78EzL8qrxR+DpBPgvDLiPljzJ1OH9WAcPglICUg/ppMZSR5tQZrt8dQnNGGuF7Dom4yuK+eu/zEWmC0FVWbKZ2spDFzD+Uc4Os95uuKvZ6y1lv34/k0Oz6LNbekv4/mOnqddPZUiS2OKuvNlt/XEOf9CcnkV1ReNI7UF1DXLvG7ivOqKhS/dwrktdf7cqnUKtW753j8+sLaieYl5yV93pxyOo9qb2a08JMDjRVvVOh6goBFI92MIZTQ4+R/dOURsRpCsXNnGqacWX8NFiHUU14MIWQeTEDZw30cLHJDRU+9H4p7kWkBkyrpHQPwMFhEE30gBOULUkqYE5DIc4+XE5P3IHOpzbya7FVEDYXtWggBKcazjkLUf5H+Z3dSyD99kdh6dLy4WUOPbamiO3VPpHnK8UotUwY83ZA9Y7Sr10n43JOFyVPjVMehGgGodr1SFlsV44EIMzQajXqQk55SiDQFjPNIrCmPPFpTAjRSiPPmIWAYRyRJiMYjaNh+669AQ4rDtybZEVLyqShz0NLjV8La5MrKtx6ek8UuarKJj3ZwzatZjBo4Paxeq43V/bLnQC+RJ+oVbjVX8s0kxWjYeTILU9XYn56lw44DnLdJAmaAkigdt39i+KTZE7mO7fHql/FLcd8b/H3hTYH+TwSnP5nOVVkGnUilZGFs3OLZuBqnaNk6uz7U2IXKYtvtzhMxKCyRz429d/r4MSOpFbp79vq5u5cgu0IUrN2VYruR77iyGBXSRvntAmAiQhIdNc9Xw8E8TpLoYThFExoDxJoHdAgDwjBiGAeLbl6U0RwCgnmRQwRCwE8g/FeUrBOAf5sC/JMps92aPgTGuBsROCCmiGk6qQdLjBaqMeVO1IxMrIQ9bq3Zj5vnTK/D3wABRAkpMYgTkhDYIzUSge1gQ0zGWEaI5XSc5gnzPGeFPeV2AWIeO77+AOhJ3Raf+Km9Y1je4NtBP5rFq6MwTd/E9f8fPG1fM3pfPWx95bT61XJklitqXbtkRZ/rS1NmdcB+DbiRlZaVvzQVlZ9tPWsC9i3c8W0U6t9vgS9sBp574Rts10thqOU6hqtrut/kKa3eyzxIJc4p9EbhbDcqxfbaEn/JEGjdrvx93TzWfe7LXvu9aN9CMvISoOa1uo7+uLv+9mV1ts8doV7apXRnJ/P5txpPSZW3MBXckOIMpmDeCQz5kDD9PiN+SSo4uVPhmYhk7/Ncxq29c59yy+bPEXhvQi4TmMCUD+RSsgev3wXrBGSVskCsX4QdgFPucW+P813scC6EzNeb4qcEWVdISGDhIqzqMCKTCx/Ieu+cvSp1c85tCBLmSvjhPGSrOGyh8vB1ARba9VNE0/U1qfa1pTSyayKWC/lsvQ69J7rX6AIaFWTVZieu6MgUr6M3DBfURqQ0ITBnI1gP0+nCJk9bwMw5N3lKCXPU8Onu2USsfUwpYprUY/x0POF4POJwPOJ0OuJ0PGKWWUO9cwJS6YcqzWecjqds4EEA4hyV735ShbyOiJ7/cgjUTnC5dmZS+mueVZkH7/Gz+y5vq8azwO5CpHzJoy/F8WsQs1+6gLMByIBwNSAMKmRNImqUc0ITZr3GZcASN5TbGlY852FdCZju5+peGA0gK4fHTrTjBitFEWVvHPSuB4ePKZoANJkwWXEFiCEH3wPWAtJ8rOBgMgAGJRP05zb7fAcIUvZ4H0hr9VQRRPpOSCP4SLmh4YYws67DOJcIZSkJ6MY4AsPZXlcIjHmGKphFz5y4T8BdHSGg4Ilcni3sRkl7CyArrktMDYjOjY6VKXi69G31rKK8afO0B+EExh4gBtn5mYmx319hOh7y8yJQ5XktUDZjlmyoRd52LmvGj2OgshZFc6F76gQ3AHBVKGEP980rxvKCPnZHs7ZIrPw9BFW762fsrzS/14+KYbuqjBuSCeFDLtn2jrin+nYod39+LUSr1n+HRPeL9vu+W22TLK8J3HxsA/8QkHAPwi3wmz7jitPwS+GRAKWJ4ZcB8ilh+FcAPt4Zjn3Aw8fPGKHh4d3wg5ix+z+cjRDLurHG4NH6TJmTqdttzcu73a/QyhyWpy/EsR3yG1FT9YLL9iAcIZggi2f6tnrrmmdWGS6pJoyqf3XtFc0iAplRyGCvrPN1tPp+r0Aip4+bGnAFFqedet/liE0z/bNZgNTe77+frfVrYFlJfYVz5gxbJ77hnKVYnNOrvMeOswlAEkyYEYgNd2k0Il/4OQS1rQ4iTYejYlPD9Y1hRTmEEMxjHEr3SnQW9AvNQr6rsg7knwQOxQREYJ7msNzlzMrlUqVodBr07Oi6cXEZEvFw99Q/W/FQK/vmJVDzHP1OOdfafm9JN3512XpfCp2S0j/AlKyi0YyEU6Z9yisRxM8LUrhNYsYujHmdeM7zcdDc8mKGqUgJp9Mx6zyUlylpwwINCDyowQQRZJ40nVFMQErgELAbR5NnuyHujDlCbVZNNu7Gd8pz6zmUoWs6paT8DaApgKysdvyXK2SFu7Thff2MF72BgodkzzqCpv7CkNRrxPcSQM6WbEIxvrVzULKdW6XB6dtXf+a6fU0l4wIFgEQImeG78UjK49kDeYlayjUVKJ0dnzd4gxreFOj/cMgIyRmW5vRTMWV2MPdLxQupkMGa0ciHLymeLDXcGcZ7IOBagMksyH5fZcvNNr65VZPfQmIKIu8ZVKqe2obaMlLqOqSvvwXHxU4IQrYWkHwwcpzd9k0hmKVbCIzArixH9jZRwYjl5iNCSgH3nBAkAcKYzIOL7IRUh2H3/OfWDcSYsvLcvbn6vuXf1Q3Ja6W914QtNO4nh1h1guUErLLw88NZEvOKl2RKcGnHvh8zKiH8nHEupFYWa+17wj+R3PbjW7x98wX78nXHtNfP4+Xvfbf5e3XB6y9eapNw6SHn4lCFtg3rcHb6t9ANfU6zQ2aGuDvH18f79qgvubxFbmFcvoKK8pwW67Dni/u2n/O8P1/p16yer11563uwPtBcUtulrXhta4duaGvUsNZGEVkKi+xumTcnJ+1hz0GairrraOtdu3YOlkfVbh4uLGet3OYQ2tXXCwrbqy+v1eno1psvL9nxwpX9PnT3XcncCUuZdS2YwMr5lGRGcjGmbAAIAIf/zCCKWSEQ7tTzfHinovToedC9FiaM44jT8Zh5KHofVEBpYd3jl4Tdv/YABCnpmooPWsd4p55gp/sZu3cD5D5a6Z5b1Nnl1M1RJyBajNSlI7oOS8HC+lv6a1AfUmEkG7fBg1OTepwHKP8fbtTXJj4q3znejhARTE8TCBpwWvlZVXztb/eIDxHxKVmOZh2fft3W67ttpbbDxJaqhCKxXLwlr6NHjgpXGsbceWIXsgkpz3k6TLi+vQKFACLGhCmvuXrMFnMlRYlO+U8RtDqt6vtRG9HUUU9yyHLzS3GklccjahjkxoO1Wk163kmVkEeyUn2aJhxMaf50OOB4OmE6HTWH+TzpWnQhcSjnuixIpBkiCTTrPMWUME+zGk17nUDm4/VrZ1RRyH4eUKnWRXmnKHB63FaP4+LTDDJalc0Snhc9t+W+FJbrVRXNAYN6Zd+oUXOKMQsZ5QAIpxyjoRYS5nI6xJBXEanCuoT6bPdz8XNr77mnVSD1Mi9V6JN8PUCeSql8HdC7U+oOVq9yD385wA1a3PCGEW4C4uOsOd4Ztm9DtT4KLiRy3z3zErZ1PpMKSEcQmNRrPVJCpGhxuu28SqrOjRCkGPOCS48Jg+FmVyCzsJ1poXnCbyzVAwC6NQMEz42bnQBUYD0MA+ItVNNDGm6XoPMo70kNrfLehPEvZQW3hj31dd0PCRZFpYr7AbnSM/otgC8CEsLpeFIlG2sqkeRG4Tc2ig/abp+LOUaARL3gkHJ/RWxNeKQfw8meykQkIWYf37IGI472XYyW9wyctj1KbPpMdA0kXX8EWZgt9aJwgk2zLKNXRSpKdN8zOZCGfQ4EU4Q9QQAE0RztjDsEEZzowZuay2jwjeNi+xzkBpEekUiV2j2+2MoZ7YXm7WwVUadvWOKRQlFmPAAAAm7hcrP0sTW4kF8T8DOB/zUg/loMeUbcQvAAD+MuAtDPaqwFScA44vTvY44ckz4laP7nWwR5rJT71IzT5HgC1FH0YsZqsVtwQvFUL+Y+Z6BSju6rJ+ux3dln8Jo7PJkxmb3unufP8lbZq9mfPP9ZpEmqRL+JTp2NT7UGnBbe534O9bfFcBUbHlg2dqzWkStvD3bhWmrOAIgLSw5qBnCLP/TrbgDYG8Ysxm9jQJeX6fwDQtl4oG2JXSACkkXNEMEweEhuPw/AeAzBUKV38gKnaUJKgv1ul6vMKX7IvH6JLSqH5DjbMctN9Z1hCJZ2xIwaA2OeJnDgsgapOFYZm4JxHDDNE8Q86XOaTPGIDpSXR3Y+MKNMJuRoIQv+oKLiEGCWqPWFoGejwYwxzQN+jnPzPkvB/a+Brd1xrryGKlbbrZhjAb0zVg91ii5kWl1/LzxVwWD6XUAw7bWdE3UNEJVIrkhmSmzy42i8tUDAFd/LQ0AIEe5GmOaINM/Z6YsBS62aIDKYway2czbvajXoEhSSYHJwv8ds6yQVhW83lgs+OA/ychx7PvsceDG9EYc3IXWyMceGbqTnBiKFrhJuBXhyYw8pBrV9K6+S5OfcsEvT6Jj5aF1wcw6r+9jSB4+E6+ey1dODI9/MY0h1izJdEWAzF/obvAHwpkD/x0PJubQN3wtnPJAz6caMvwTzLxhdNJ/r8KIKljVSPr8vrue8bEBB/jWKrxgBgjLSwsa8Bc3LEjwwpQt6Qc33wgvotZ+Y8Z8UICS4p2ShYZQAs1lDBmYVJsIIhZR/nYHnynC9nO06t5ZySJxK8eFCOw0XWZ2SOkq1qeRaXP8j1edfu6Le4A3+XrC1+2jje762cmh47aHvDf4csFCed5/+fev31vU+nONzwqL6+iXXzkG/dr8G92+9+71pylKY+22gnrfmMG5Kdcr/COE9l1MqkFPcePuSGfZ5Ghs38KT3pkq9L6LN8ScNbw0QJj6pQClGVcYTmbc6FW+9qnF8xxZiEZBU4yA7ersgCqQ5ak0o5yG9HU9J5Xnej8dr4VusAy1jRhFJK5ApZPDUVSLS5lSs+Nr20yNWWQhkJCRMWYxVP7/1W695rm3LfGqyL8kj3AkADwJc+Ty2hp+uKJ8fZgy39dHWhf51nJS2XXTm97LNl89LCQnJeb1GEcA9OsyFVWytppSKF5UJ19hTL0nCdDqp8vxwwNPTE54OTzidZsRpytGbUhIQa1SFYRwQY0IS3U8xJWCekE4m1iXSXI4pwjNLMS3peCuGWhfaNd4kKML+tTfK9YKtW5zRnqekeWsNXorJX/MGEDBgd7NDCAE8BMRZc8Onp5T7K+SKfzei6MeyboSdBwUghNwmTUzRh1BeG4taeAyQcD4vlvuAPAnqHsuTp+SqNX1uxEgWAQ3FqJEIgBpry0GjO+QMY+xKITLP5mr1ZCMtF/ALxIxzAAFjzMYv4ZqRHmJ+n661EVJ5P7migM3AXKOEVP0wJM+3mg4hxcJJejfcOCMPo/UzDEO5UGMfAviWIA+Aq41XjSIW0IpvBScwrtCKnJWWbZdQjsPm7JgF3mQCes8bf87YpO6RQBBX6FXNc2tpR7gi3dddq9ZdL/978S5eR/0JtPVt8SDPQaRHfU/OCMnPdM5vvQan5DbgIRcfTDEOqFEA/Wz7nBjhXwHx15IZnHCXa5VPAP0MeO4OArD/370q0X9mpE8+iw8ofrp6JSsPun5t9ddh1+Gol8DWmmlpwbJNimfPt3EbtiZ4yd0fSRNWECyqgeHknlZ9C/B858+Vtnl/dfF9zYr8VrDdo8XcO5+fNVio+CHnR8tuq/FhqavCElSvH3NCIv0uACzPUH61DiUdk4CDKtU9xVRpdzHu80gtu90e0zQp/QnBlKyACBmNy63IFTIDMW3PEkMdoJKnDEkMIY9KBAtP76lBn52IPxResivO4QAl12Jrw/hKUYerHKRdKoosen6YY8QQgIFZjbAtDdIwDEgx5fND8VBXz3EiwjjutF4L3U6WWkyficpTp4KDmAiBGGEYND2I3YySQEiIUXmqPEXu6GY/AzMs0E82DipcS16tP3wnb8GdvLxtT2tBv2jxdRPOnttE/4jteQEqJyRB7WDh0dL80oLPMJ6A6qLf4A3wpkD/58Eqn1GsqlHdLixKsTpF+5riIsHyfSJQSk34qltRj/P3ormbrkUDQCYADxC8r9BhW1cpOIdOFL/jZKY+ptetbAU0Ta6wFagPgss7Dd7deGLjmvihV21Xs6AijOBBc6loDvTiQZkFGN4769J7ANf0Mw7yCczK2AsRPhDjI5tggjWkYAgBlHOfm7Iabt1XLPG3oB9fYPvxfmwaZbopz0MIOaeMWGESk4WxKaPWiHbcC6b63Va11qCvO9RcSiy/l7DgOfij611d24vN8OdlMX7UPF0O6y38FtHwXw3UfNj3jXZ2a2FxGDp76gfq44Isrr7Bj1rBvfDqEnDFeSsYWRNPtQLP2ttTqBYzEIhummdg34lcjPFUlbS9htaEg2v9e37dXSY2u/QQuLXHLvWwfEnNnh7mpW/3Qp6l0GcP0KEa131+Tv3ltNTwjsGsXpIqgCqe53qx5feICPM0I84zwhAgUTDcBYz7HcI4Kt9koRPDOCBOE2gcIaKK+OmoyoKijNcq+B0jDAHDMJq3rgBRvWCGdwHxCyHeq4I3WgDnQX0yc2hW5aaOKArqpWKiHq9L99KSE37uOQUmgLHDjFPFywpccexK5tOT5hhncJYOyKF4GY+WqziJhiC0gINwX4xonsXxcW5aU++pLaEggO65oJ6viIAZW0j1BAEI1xZe/ijA0XKy7wlyNLqx1z4MGPS6KaCv399oyPPHCQxgrupdgnOcnJeg5zU9t+7X/XvsKcdjDSGvpOSVZ8xuHLHb7TDudtiNI66urrHb7zSsOzFiSogx4nQ8aej20wmn04R5mjAbD+1FE0MV98zqUTNT5vXTVNqjirlU8iXbKYng0r6+b4UXLzi2rBvK49ieoqT7LBFTSvoo/V3eWfOcWp7z+hr658/dLefBfn6peUZ3PKN4d8cYEecZ6SmZqluxQW53F4Jn0e4VGqn7Kubvoer/0GRhXULbP/UwFyl7uu+lC+RrmktECDJCKIKJMfIOwhGaO51AGAEIWBST83XQ/UcaQjeJ3lOhcZ191ATVAOLBPbHLSDOAxIJ0iHDPc7o1emCKgvkx6vDudVXwuxEQNQxBEgzDiAQpHuYpIX6ZQDcE5gGSLBKCKH4PQdOpuQe9R0ZzD0LdumTCUwIHgdxpWhBBZdiVVMKRcARj381O2St6fQe+037N948AdnnP8B2rEYUL1hnqKazuiY3M12UCMSXzfhOkOBvKEYzjTlM/EEDEiHHS8/W9AKz+8M+xFWV/ExhHcPZGX66+fEWj+isGsYtFP9XuRK7qD6Je5/33tTatZ5Yvu0LlBkVm0eOJHh+QuCegXkkdn8rWH/cs79tT86+5XFkbpbYN/fCrwhxIpjSP9um80/zJ8ULr2r6UfyXIJ+CUjXeqmggIvzCmX2erqw4vX/jmugbP317nGlc+oB0Hf+f03MIyGCsM4LyUzy0D2P/PB4QQ8Pj/PjbYq8ZiCe75/XoYhTA9U4bXsQcBTMVbmJQPJFFZJhg4UKtozeY2m/w2VX8VfDwJwLVdO4bq5uKNRXHFY7JqRydF29jNFxX/QvCal9Ehs0GrG8sSQIERzROdWZWmoQ5fngAJyPJRArAbdwAB06TRdfa7ne3DYhQGVPmxYayGZw4C5ToEJde4ptopZ4eWcqmBIxFKyikr//HxAQJgv9vbK/reYEZ3YwiIxnf1Xr4a30B3g6f2CVD6CgZiUtlpSoIpRQQijMOgvDp0YGKc13dihwC3+KO8XGXJby0pXP2C/ewKbPnFdVjczway4j/1T45WygCnjLucdnqQiZRSjr4aWHOVD2GwVCsJGtxFjK/WEO+ZLxZkIwU9LKqB63GaMM0zUkzGb5Dx8JqidhDR9TkkECVQSoiUQJgxxx67CmD0R0hTrSYNS6WGrj6Qea6cOK3NxjoOew47Lvjyfg4WtazRUzJnyFIOI7NuZ9pZpdRpWlAdB7r3JD9j9Bqu16HK+E3PrLWBvlkFo7Wip/zxOrz2Bv90eFOg/0NB5UKKcXJUI1PwOkJncfa9PbYbjlqUV1+qApVBoErziKI8fyINSxShSvWXxMaoGf7zTzlI05ZzcDk73iJ6/U7oGUR90phoy7NG7iFODB6CeYrrP7Yy2IQWQi1J+2D4f/xXwOG/hP8DRiTBgRkfkyAYIXOmIQQNc6ceJio8SCkVZbrnZ6na2ljN1xEKqpBJ54emCGZg3vIuoGALoUOkAoBkloTqeVOspsWIndi45hatuc3nU9WayO318O1K+vvAswrUN07kbwd16o7F9TO/25uvrNs+3/binw9qD/OZNhTnWF7rD2kEgHGjtBEEUGvm5tfXUEwRnGoIT8FTcxA/R/fP8QNbyzUf8+jcU+3z555au7dmtNY+XR82v//O2GpF+3sP5PCv++qe8TMg8DtTqqwYQazWmwVf6lFORIhRc/MO44gQBlWEVEPAgcFhjzjNgHnzhjBgnqfMt5ajuOM1E5BE5W+Y/WDfM7nq2YiHel4FvXf3jwRt9XJNENVrpbS8ebGahuIFJM17/Yp76Up8TlCDisVcnDsIWS0AuPJcv2eF1hVhCANqT0kNxzyfbeFz+/Tcs+vv2h4mDwlY+H6PIAWinLppNOX59fU1rvZ7jLsdbq+vcXV1hXEY1cs3ao7y6XTC6XRSxfk0Z95eYKFfCeDBcnhWXfY1QDZehZVWHryZXd97shy1dmfUI51W18a5cYSdN/KzZxfSFmV5OQ6sS1pGwyUkGhrBJYHB15rI1dMbSBbfLaMaFExNq0p6f4ayYrwVZlLzzNZ6K33Pzzu+fCqK83p8N2lzPmdG9aTineYI5RHEMK/LGcBgcgIAx2Se4ANAGjo8kvaoPgkn89vOV8jP78XrlUkApuytV3dWktV3Y/haCBAdc02Vpng+IWXjqPioczO4goPMkz0PgO1BF+CKoLLgVoGrhYolMRrFqoBxwXs7I4BGIdk389ljzOJt3kUEeQDoFpnPyTIDZNGMhqXHch319NQF/2J7mjno+RqwNTtVrT4PurqRz9WtK8X6898TLsHTTXQAi7/6EtrU75WzGKZnEbr3184vazQz4UFzmK88P+NL87yvjNZoyd9dP6H77osfI6J5n7d9bDmauq3L7LfrfZ5eOPv1+Lii3nHx6b+/57WfUK/DbwDVwE8kFynRAag3eu2KWE1WrZMp1Ti+WzOiuxx6Y4WLxqBZtN9k1L4amnMbFeVZBhEzYkq5n2pYWwz88hvKVFXl6ec4BszT0o3KHa4ct+bczlLvJ8NuornQtc2K+yU5TpVCM3LF5JWsdroWm4oAYQgaOl6Mz66HoBsnP4ckEeyGAad5zvRR7E+EYBBUcpqWJ/jLglndFSW6cVsi4CSaJicxqBoPMpmxpKRe5oMqt0MYMA47cBh0jUENYWI0BXpSr3JPf+TsgIimPHUF+mmeMKc5R2uigcFBZdsBhBS82QnECRQTKEZEAURmpFSlOUThvbRNFo0oOT9TeVA3ERb07dU9hK+d92+4ai5lze258zU/X5jySX1EZUE2UugiW7zs1PcGb7CENwX6PxkyYbLDorSE173AMiMoaCwb1wi/8jVULPIMItTYLwJ4JOAmnxwEtxB8JuA3astryiYqPMoK8tsWOiP36RyqvBTXu109M0Es5DqR5gQDnJ+i8t3bVzECqtxWos6hKNA9vLl6ETlDRLlxv1g5FAXH//wXO3zA/5Vf8ZMAn6HCOLHOMGkd3i8DARQxAAAgAElEQVRVnEdIiubtLRYOT1oinBk9aT7hh/rq2cW7/Zha033ugvWbTTinlvPKuMSYGuZ0yURWzava1jDl+HpyuHaAPQc9W7NV3teX9Npyvx1kZdWW4pTsT3WY+Jp2/iVZmxc3egNffWdJ1Ca+65rD5oWztBxfWQsrXXlNzqBvOe+V8fmfBJ4/Jrzk+R8BtaLcafOuQr7ncGEve9JrN8icRrWuWuUZlecr4yyXXPmRVMtygcihtNHK6df8udFd2x9Nu6m+0r730lnber7OKbzewu2a1u5kXuoVm2KNvjJdVdeum7ZS85+Hs1aBRpYqSeEP0OGUOmxiVrj4QVuUnwk0VN4hznsKOAQIEwZAFTBWDg8qqs0KBbJ6Mv/GUI9KILwPON2r5+L+TnOkx/vkVBDF3A8AjmfxaV4qzw77xgPkI3r2KQBAwpzHvHimaT+IOsWN3XdufbjRHOMpRshBML7T52ccO5oRUPuh9X3fWrF9uwMGDNcjpif13E+peODWXqzpYMqgK0I6iHqcA5BjqTB7kfq7RBbikjDejDg9njAgZFxhosmmzT4a/k11UX7wKU8sxVnr/WyeM4aYmDCwpm3ioPmXd/s9rq6ucH11hf3VFfa7Pa72qoybJ5274+mEw9MBx8MRp+MR02lCjHP2NgVg6ZtsHUMglquR2NIn8Q6DqBFrTAkpRZxO6lEtSNkVkFjQ9qoP3twKtIlSHveSIXExsIvzY/KNUXui52tU3stl1aLugvnLuNfz8zwTteBrAOQgvT6meoJCPJjCnHSQ+hDtUhXiOC2LS42P8kK1m8F9/XM/uBPJ+A4gz/u6OBnzog/6VJ1kYn29ZtxKQCDzr2fN7R5owBAYTEGVCUSIGCAymYB5yO0K16pEj09zJUcoEoFiQgCITFWcB+srzRhpjxkzRKLKHUgF1/ExKn6GKdpZ843On2eACPw+GW1hCA+I8wRAEG4D5oe5onPapsAjBhacZr037tTYK83RDEkU/zBr22SeK49mjVoiXyz8K6CGLQCSTjqC1yTI8z+8HzB9VpzsOyOY6yPf2fx/tkgsronLIV4FRdlp4+oGONXmCDQUpb/RxhQTaFBPPPOzzgthC2+tnUJ19R/B2EE8ckGe3fYFSnskKnxX3kP9Eu0aEJLigt77fIvOJe+3ACzX9ixhxn2uaxAt04NrrJ9Fery2DnTmGV/l+t04lZVQh3UZyx1bh3C/BeQhX6+L6eelDKN7rN/Z9VZNI0iIHwsPPXXvO3aJtsoGm+O4gjkEyOt8rY2XwGzFXVdrqTY0qpXmfV8JOpcTLT2aLwIrbBTCINqWrIA1ZcuWZ/uJVbm2Ex2nEwn2RAgCBCLciPK0JTe6vrdThKvRYFAMH/p96NwlE+CZ7hnA4IuY1OEplp9Nt8oPpzPS7fk6FcMKvGI4z4P30jyFq3YX40Lks0CMauhKlF3M1fAwkKFFye9aR6t87gBEMIwDxnGHh8cH7EeNTMKWQqfwK6p4HWmAiGBOlZkCqXNPCJxT6oDIziOeF7rspZrbcP3c1f6qxX/WzhiNXjFhimaQBc/RDlOeqjd8gnmZzxGjKd0H59tEIwcVEAwcEDkZLqkmksi8swueWoQo2KQIds+er7eF47MeJ3mdmYcD8sjLyjtbIB62JvMOMBqtTmAxkRq1gbt9IIqAxWIHhSHL2onV4DolwTxHzDEiRTGjOHIHd4voNKlxQkoWUoUxpwlzFW1gIBtTVt4bzOAwYCRg4ITICTPNdiIDZmjKnzY+gNJtoirMuzsyen/sMw8JYSmjX87CNmye/9dnpy/R91w0Xi+nGrK2eFSFZTW+Y4oJqhuSeL+ZU+UovtaeYhJa+H0/jYe8MPN+FLH0wBt99mel0Ja6tX7vXC70Hxop9A1+GLwp0N+gOvQaUEFMBLycO14Bzy72SMA7Qc57TgACPgD4/bKCXszgSfPtHNn4GlgqFVHVJvlU7eHwAgcN2x6GEtacCOQ58bwc6Fy8h+CjzdHPIkjyHv+WXyEi+FWUORM7zOfQtlyIWjLFeXQPdEnLeffWdoTZLbfWQjCtjQNV6wcwBtjDSdo/sXKjKdFTihqCSCrW3pmnDWtVvdvbUn89vGQtrLGd3/wM8ieAZz3Py4Nv8BeAS9Z4LWAFCpP4GuXbG/z1YRAsaVNP97BNZ1uaBhBuszAW8HDS9kylQF+imL709ggv+Zkr1Er0un2XwPPPbuDEC8u/BM77Tm0LPb5lG86V5fyJtkKq65Q/CRq2XYVhbtRngtOcSLeUmQWy3UEWUO9EZhWEhGHIPIJUPEeKUXlYNmV4JUEkUMFnLoQwqVcxCGwkjnAVV7pPzeqq4c94ft4Ubm3e7Vc85Wtfu57q/VdfixDgaSq1i5j3rArddPbEFE4CHAC+aqMOAM4HUmOcWXdFAIR9QDpGVDMMP4mcm79LBX6r71beShnvEWG4NqNZ0dCSu90V9vu9Ks/3e1zt9hiGEfMckeYDAOB4POLp6QmHwwGn6YR5nksEKfeShWRDAljId5BGVdiNOwy7ESONGIcR0zxhmlQhOs0TJEZ4vlEfPh+X8+t7zR/3pbAywhuD3u6+ZwS/WdCGRRu38LsgAdSGVl0+lzauI+M4vd8isUwDJWSvy7Vdh66PtU/dkibUK3Q5F+o/35ZKxBbhDBjII58BTAEjmVE3DRjvAsIwQJJgOA6YEyOJKcqhfcBJ6xhuRsj91IUr9kzLtp7IlHXioTcBoQGBggpUBdmTPBs9EUOuzbvc1jeIEO4CPEpG9rZ3wS2TeqfXQ0MuaLe9QkCaDadXBr9OAkQsSpsIAmfVKPiWkB4Y0igwynj3sxc/lzQXtHIfAML7wvuoYTiZsqZd4dr+BEaoDBF8nAkIDBLB6fNJr91apAnrnxrkjcsc6BczRjUH2INA6NjhV3tLlkLnbwE956eRiB5BolGNBI+oadhWF7dxwTO4v3qx4X19Ls+8/xo86XNet7dec4T7dskDcKU6oCHc+dc7jHjI6UxaXOh/12L5lT1St8F/j6AXeaGPDe/fKstj9b0Gr/PwDTUWdQSSS5foyTzXiTRsfZ28oTX99UqowjG1eUO51sPWHF8EPYlshuvHcKurZ0Iq4+Ig9XVR5XcSNwjTPxEpG32pURtAqR4lwd3NLaZ5AozP93LLmjV5K7kpm587VQEYY0mR4S1zo16PsC3I5nawQ0RWoguQrXcEyO/oBY2O4lFAHbgyIKzpZkwCsDkaIT+SK1IUrwr2ORZjgG8jq3mO+9uY22ffvKBW6cpX7TeEuIooQ04Y9VnHx8QgVhk7h2CG2zq3c0qYYsxRUHUJEUABRConjxLNiCHlXOhzmlV2TgxhNdINTBCx8y004svABGEgcsy8lQ9GBMDJU6kuB9GjHkAk48UW89bffcF93Z7+2rn6VtAYQry0QR1TT0ULj/Wzblc3mlFtrvu6qgOQrL3/Bv8seFOg/1NhDTt1XqMe7qLFz9JydV0xDAuVZuXcSSFon6kwirMImIAZgt/oM96L3t9uLzImq8UaS/S4RI7nmM/W/n9bHOOWYR76Jzcnu0QVtlmglllECcG5qdxQI/ZO3E2hPGQegDKRV+Ev8DOAj9aOu5TwHxH8lD7ivQg+ZUuvkgc09zupRX00ZjDFpB4pyRXVxqBVZWx5lNdK9Eshe2GQKs8bEuYh5GO0kPICkVTKN+6pbs8iQoIU5Tm/mnxJ833Jyp/7vSS0a/AqK+ln3vlRxLrPQWxfqieWrN4bXA5/lCWj5yBsrC17ZWgWDC3nfMtw4msMKs5Fs9iCZgn20snvJLD7U6zt79yIuvhBKrKFLuStIviLmtYK9VR5rrmrepUIgd4R5IvV+U5fIhDkS1kjRLX3XTGlaiy2LYug4GCf2zT+XJu37q3JJ16yip+fxi3RhNZETY+er7sRFtL6e2f7TPv8VLsXqJmL2vM8vFfhQ1Zu5krIvEPsDaacCqiOfKOaBFUKckzYXe2yQETMZYAG5X3SHI1PU44gxTrHclE2DsOoRn0wr0bLM6v5YSnP6+5O8/6me8nrFfDca4URJstnm3Ogbwzi9tq7bCVshruvWrJ4p3pAw/cO+WnJc2XCpUcV0A03AbhBJZCgXPraGttad2vPt2JOzfq8wx50zTg9nWxFEyJmMA3dOhXIAdkTHflpMtZZLOIAsheoCCE+TlYnw9enwPNXl3aWtibbW6aeymx+e1Lo+9bPr/PUvqYTAKSE09OMMAC7QBBOmKcjTqzPpxgxTZMa2Er27cBpmvDw8ICHp0ccn044TafuGGdrkkpueJiH+zAMuNrvsb++xn63w0gjDscjjocDpmnODvZ6NkB3PpTuW/27z8nbhXGX9kvh79uzBOX1+Qx0DxYPuxb3+5r2+S40IQfGLEVuVMUU0Hi2dD318vQ+599rp0+ncVyFbNf31EM7bLair08AD6Ve9Yy75/wbm4f6cBOy8oDJojgYQdezmYZeHzhg9/5avR7DgP3VHiJJjb7f73D49QEnGSByMkOL0nIixng3YHqIWrvTbE/JQgSWUKgDeZoyQChByD2S1FCKjoLAgwqwLaRuPrtSwvwo2FmEjJQS5s8T6Fr7AxHwHSN+ieBb0tzoZkguAMa90rE4xYwLtA+WQ93TiZkxSoraJzVU13Fn4uxRPljaEh1za3+zxsoZG6I5z+E4RSgbz9dr2b3QlAkS0B1bGHfJcplgKRsS1AidJQAgjHcD5hgR77W/LqZIXr7lmi/4TMpG6DZh24s6AgShUEJ9KcLjNZyHxTmHyxo+F6rbn9G9ZHuenkC4tfsM4BbDv4Lq3z5dI9ETyHiNhh6Rnn8qCtLiJCgRaeQ9uddtPzL9sPJ4YwxL+++sBuVHhHwM7wE8XDAXy9vS3Q82JuO/AqZf68guCgOKcqY38SgRMQqdq0fvtcfUPciMd6SKS9HT3naseyAr59X5zwXY28H3wIVeAMDk58mNFaht0ndmLk8KCImMCgjl+b8WBkgw67YEJTf2tPG1diTS74GUgkSgGZ+ipLU1l5tH+eJaiyVbi1YdaHaBtPc34HnudPt5QeFbl6GoC49EAIYwZu9TMqUlCAisimG2Pal4LGGgUGagcszxKKjZYSe1WMU92X3+Blb6rhGyAEQ1oCM2GpXH2RGG9mMY9zgdn8CsEyxQj9ph3OF4OlpbE8bdHp4mZBxHTKcJzAkQzjwDM2OaZwRmRPN8z3g1adQbNmekadb4BO4JPE0zZiKMIWC/G4FTcXhSBb2er2Yzksws9QZCceNBBre3K8/15UyuFtU8VY3kedjY2m5kR1BPfU913b8rUFpnNhjmsW/vJsl8rliaWpiMWnkdpesiSecBUKU9CDFFVaAr2cWUCBJ9TZR1zDyAQjkD1wjOz2OSBLHmoMUfW54qCDCeogyP7hv7dTED7QVkBrofutLGs6+XdQAsTZDz+1IfJczT33Q/QKGHnPHDZc2n/LfgbwEQJanxnIXcV6dFztEL1IbCr1cUv+a7qm9bzdkan+fGbYkH3+CvDG8K9H86yAbiqy9Ie935hzWGN5fh9+1dVZ6rQl2gobdy+D48ozxfbdhXP2iwRGTbqM2PH+VwnMOh5s5TRZOcOCOH0AGUWITKGzswN2FIM9UH4SdqD6O/i0BixJQSfkspH/A19DtlBB0tz3mMEbN5n2uucSm5zzc80DdHKhOdC6DSbLnipSYeOQyPMZiuPK8Dj5U1VLVRWvZCQG/hU34AvHkh/71hbU89N+dva+LvA9nbXPSQ85yXRi9gRPfdgatw7bXynD9wftiFRfyhLZSIQO8J6bOA30Gt2r6UVlUiJtSewi8x+voW8Nzh63vAS+vq5+WSnUvN99pckLr7lfL8XWXkQOU5cgG+2NNEeao3axdRb8jqQO5pYAKpEIkDq4A2sCpS2Q06jWez5jIzhmHI68uL9LQ2uc0iSA+tWKOI1Etvi/nGHzvvDlvC5teXJ3kOW37LIS7e2WpX/3utnQkCfqpyX4KR4LnM6/1sAudKec5XjByxQiWoxj7bW6modblZuaq6LBznMof3a04Ti71V873uzZISZJ7Va2oQzIcZc4w4nk4Yx1GjUhF7NgGACPM843A44OnxEcfDETHVnrqUy2dWYWnggGEMGIYB+90O1zfXuLm9w9V+j4G0DhLgcDhmIbaeDZJGs3qFkGf9jXNiqJfV4SYsbB7LBEKkCPEUDCCwBSAmWxs41OeK5oSxaA3gSiVfi2Gjlb3gsXikC2pFWcF5riav8UVtdOR/19ecKyZn+zVX5YeGxnmZZa0Xyuhpwuja6OlJ6ws3aqyha48x8IhxUPE5hRHMgMwRu7sd6DEiCiGmyQTGgyp7TgDtGPs7wvzk7SQ9A0LRP9tvOM63fSuWAiCKaB7TY0Sqzo6g4vHNzPAUBRCYgkDyvVyZCMItIz5E8B3bPuF8FncBajPKdi8ljdzQWGhW+4FuCfJQj3nNA5W1ltOTVHKDhk82fJWFvYXIqCI5ixYo53f14nKKitAqOeD1EjXPuxEQg7JM4dLd5wZivmadN6xlPgnHs2VamvtV5Xrtod735hzUYVXzNQDJYlwPHwLo9xvM9Jj33Wo5K/tn+cx5vukl2KzmReoObMnULq2j5sOThXU//XoL4AGEO4ioF3r69daefFjMR72WdV615Lruut8vweCuFA5W7tY6rD3tm/7ZsL1aeV6VGzfm+fISCkyGq/ZSzjFUbT7qFk/e5rZ+faz9+9EGysWCUr2/Hsnh8tX3cqr7/aH1RF+eIpXmF2NEgvLqOYxLg2UVeBi6xCeGncXp9NIBiy1SAAeCaOLqQr+MjgoBlIxWELC7usZ8OlkNBefudnscnh6Vz6JiuDnPni5KcXp/rir9LiBQr2kmNQ723jBVKSqg+bwxz3bd+sKMOc5AdHL2bVfAFs9ynm+6tP4lxnEj2cQClnIOaN6ydZLE05eq8jaKgMWjsqDQeHdqI4JIynRckkbESV6WePRWj57jRMtpuK4hDuqJ7vtauyGlK7NGUdD0KsXAFtWnP1pH51iHHjO/bm5f9uYL8E3e2pe907FaZ+rvvznfVSHNzOPVehm/3eozGsOSN3iDC+BNgf4PhIwjeq+A+omKzvXHjp7pQPW75FqBn28BaM5zPSCrJeCXANyl/OQmOLOgCtZS87I924eermeLa7Lxfe0ZPdCXcC1RKkEIFcFxPqw762YMtuY546q86pAOqLBPNLT5TxLxiQgfiPCTDgL+I0Xx3RAAKgIJzXGekGLEPM+ISb18xMLR1ZaNqNtRffaK9WzVWdXZ5CCnZRk5nDupoQBglo0pZQX/qke89bWuex3U0neL5q0fhJ1zei2sHSFf2obX1/Oj4HnP85o5B/58R7Q/G/z4ed0Kqfgaz/Py83X9OqfkXLvzRzO6X1/dS0v4MetjrPCpH9D7ULNFmLB9PEb1jsJNFUaWsmcl/1TCqrJ7FAMInn4EUKthTVKmh9MPxYuZ3uuhNX2pRYel/qUoxr+3K7X2XOw9FJfcDzKtPQc9f9Rfa56k/sktcJ6ilPjcG32dC54Du/xUrQjeKq2oZcrvBFU51R4L/K7lTUAAiXpQiCj9D8OwUDIA0Gg6ZminPS4eJLXCkOzZOM1gZhyennB9c2PW5sp/JKkMHkNAIE8jo2tKYsrKRzJBiith00OvfKtNM5Dbm/Ej9hAIUh8it3m6XpvUXD837q54WrnzLFfjApjaj1bnLSFhxog9YPMIiHpQoKzx4ml7GQf1EmGMAJib8QpIpqBXxWgRftR7k/ZqKEHV/smOEaK5epWvJIR9sKgFdj+pIC3ntQZg/k2ofEJQPIo9egHnO1v7pGCSMgieKoDMQCNJApLgSBpKkgNjmGdN5WRGte5tpcaxAUkSTscTpnlWQalI9h5uTmk2QRrZaocd7TDyDju+whXvsec9xt0OcZoxjzOGEMo6FF/j50V2FafeXOvn3XH7god31CDtempxNTftUNW4JgObMOHn//0fHB4eQfeEidwTeFTF8VWFn2/KTMVHjyxQ8FY+v8HjIdR9cHOZNmR7z+W2Crj+r0IylY3+CytPbFN9gSvPBwCzPTfUHJr9pZzvFVeEeIjZa40t5Gg2uGbG+G6nHumT5gTfj1cYhh0oRb2/3yOMI0gE8+mk5bwPmO6BRFGVuhLhOdHTQSd0uN4hBML0OGVPwqwwdzxGpBHaCBBiJBKMpFFDIqvPP98IYgSmLxPomjWSqgh273e5v577NrxTWhLnWfH+fQLdMviGNYLItSpGAEDmaN5rOiZztPzgVOiPeP5boKELBAAPrgx0fqGLgUZlTRSKYYqPW6dj7nnlRuCVoUNQcwvHx4nU447euQJIwExmiB4BNkMEw3vDOKg33Z3mzpVHQe3hHjBixrRYeQRpNjEBlvv8CMZVpv2ZZ2m29R6RDmeF3wmaL3qNOtT5RV0xQWcKE2jObo0ZUPgDQQKRhl6W3wUJjzaKjpnrfdt+1r8IVBwbKuMFgachWMrB3KPYPTXHdGeRFR6aGiK+2BAuMWlTHu4AAIMZk8343e7fQnC/+o6X5Tm0CQ8IuMXwC2P+mEA/KX7gnwNG/qA81sfPRocLXdNd22K80t6CAWu8f2kY92nlWoSGQweAnZXPhCb/7NeHbtdyD9T+fsnbZUQqLtjW65H0DKXO6QUrDKJ5eAW6Z3PcDvZzuOFBlBGNjIVxiOeOv7T5C6VR/nPh++dvvwB05MqZabliS8oOvZaS8TeiFwMzIhKQkOWwxC6TBETI9r4azcZ5zmUzB6VjgMpGU4SY/NlTTHqdbO8TCKcpIgSq6ABnGSgBiPNUHJEICEHpYJwnnedB04hM0wkpReW1uklNpgFXoy29FljxV4zKMzj3EZMgWh+ZCLMrc3NqrIzicb0bcThOmScQSD4z9buo7Gb9FkzxmHGm47WKMDh/2+6JMqNSPfc1DreZ5uTCK+cvnxegGGG78twdyOaIaY6YZuObghrNEgcw2HQMDEHMnsrKngSApDh8ieh5ScyDnRIkGkasjOBCCkiD4U/SyLBDJd8m0ogfFKMZY6gjmZ85leYCkdpZ8Wg9GUuIFuZ9tonKdKkesuegnx41Vmn52vb55pSzKKF41fv6qcqtn+vS4BDqtDUFv25DR4fEaa9RJTemNqTBbref+S2vrKrnEvz40gF+g78lvCnQ/+EgjogdyNFWy6lR/9wK9Plsbuyre5ffihLiRMB78cPhGjnvyj3zxPm3n6faL6frRVChQoHu7gpCLUp1WF5OysS+f9zb814EEcA7YwbmivAIgM9VhZl5yMJO9UCfLRRkTEnD0MG9va2cbkLrvLP+0YdQ75Xoa32tx4GAnP9cRL3nk4iGl4vRQrdLPqCueYiszdEaG97c/B4J185Af5D+u8LavK8uhU0zwrWj/hv8CKgFVv215rl1pPb8M2/wlwJXntd0yb+ryO3GhIeCosjVJ1qc/QRY6PT6iJU942rluQl+UdEe1e/Wh0cTUtdExU/nAkj2Qq+hP9ZfgXA4w0fQ6ve13/W4ODyHybZ3x7l981wNbkggmw2g5vsOUikq2x6TCWr606M0T9Vv1WYGzhXxnT1ZG/bBaUS5zswYAquXRNOark63IO8sxWsJPxMBQ0CcI4ag+XoRgDjPkFiEUE2frQhXkui/VklcerklaG9b3AuhnoP+vcveeDlsrc3iZR6WT5atvVrvc1z711H2CGk8f/V3aYmA9sXwRiTB8xu6cE0fNgHKURFb2kcTaLlBJ2PGMa9+9fRISOCswD834s/N3doYiEhOcRVNCBpjBGbgVPHyWrcaiOpe0aP6HBNinLPAjjlk4TEnEx6RCkyHYcDV1ZWGbN/tsN/tsNvbv2GHadxhGieEUMLki3vrJFmcD2rYmv/n571/c9u/Ro0XSmj0ca/e0QDh7u4DABM0Xyew7BGGAUkShmFEnKeurBpnq4IdAOhgAr4rIB1K+9TwpijTe0HiOTpSTBpKj2tPS2q+L1eRLJ6qYW760lJXUmNlIuDK7lhY22CSQz93BvPiDhyAlBAoIAQGjwGBSJW1AMbdCKYAgoDGnSoeBBqiJhHmeDQDJdboCm6sdEpIxLa2tB2eG578O5XQucJifCgj0gyYh58EHQ2mGekg6hV4XQtiKYdS95HgEBA/W8oGAiiocDw9qkIdOVWIKaUNbyRL/UDdfLtXGmAKVRHQnf2+T+BbBh4qnNPMpT7HHe0kWxRSCbyzl6rzNqQKWU1zwll4nswoiMiUclx4sBwNT6BGMnMCc8KEKdMlgqcjqRQdG1BaXWd5BpbYr+zrzaMfXuZdvtWetd+CJzBu8tUkamCgnOo1EjSM+zklOha/1zH8OqeyAmL78wVEXh+7XVyPOTi+h6pv566uosY3hDLmPifpk67J9CmBfmEEpkahnap3PPpUHW/GeX2pnnFlveDludDXwBXpvgB3VVqd10HPsX876M++E5kSnWweSB1Uo+25nuL5uAl0HCfDQU3SkEXT1/qyRTNWW33hc18Pqy2l9XSRtNKsBi1ulmq/LUmxSxOJGMNuzLx+MlkoscZAkBRbnCCtPCSJIM2q+AYsH3bVmuw1DFWqDsHCrbNxAmYonKKnCqlmyY9tRCApJkDOl587c/gYshBSpTDMhsAgHKcp88tMBCFzrtpQoq/UcPYp6b4/t7teu+KUJleqWmllxv5Q1j+QPhMtz/lpmrA7nTAdT8qbMUMsZDsHBrKTnlikVjOQCGROZ3YPmoteRJRfiWJGkaLZVr1+BlKMEOO1mAg0DJkvd3k45glpMm7PUsTU+djdfDQbt/bCudUBJZyTB/woOMcTnIeXnZD9FbdnKNd8v1IZN2e47OP7UIc3+DvDmwL9nw6ZC1csUsvLaoX4RbivwpDvBfjdynknma5hNkT1mwkr38Mr7ENEGdGQNZ8o2fjWH/C8nHP+jV7feh/zobyymgc0/ApAOQePWjIVQb8eZqUpicmFHGEsR0sAACAASURBVKSWtTYW7OMvKiATaBi7TyKaGx6Cn8x7ACL4BYTfqhDwHpYPUCZRYkSKUXOem8BO2NqYLd1aAUFWnlsdrVePVAZ2ktvxPMEhY2x0/JK1xZXn0fKfu7wAyRjR+vXMRbaz47+SaDqAft308/dHcBRrIoVFXumvruXHkfktz/N8vzx4VvjavvEn4/ReC39h7qtGU4v948L8rTlfCAzX9+k2vOwY90fr6b9e7PKNG/yd+r9r5VXNPwBg3Bqt4mY+kuUBLH6ZRchXmmz/mVCePrDSPzcmgwvHioVw4Ue0xGACDLcO11B72kD6oFKPVOdH70rQzyvrz1KRXtOc6mP1GW1qaXP//OUYrbSyK32l3Fo4pjOj/WpPf+eWh470Po+5X6vrqj3Ia1zQ07bwLiB9qTOBG6d1T9j9PCDOKdM/5S2KAoctb6uAwK5AqGmGAHBPXRMGAVAlDMii6xT+cNzvNBQiAburfW4jEeM0HVWmwSXCQRZVSS2GljyMpa+SO83QkIi+7Ep+ynZe1gT0ayBYrpv1d8pza/xE+9RKObl5ekW57hm14pzgCiiCZidVRRwxYTqekJ5UEImc8bcV3D8HLRd8/hldg6PmIAQQMAAgU9IJAgLo2nlx7VfJlSmQmJAOAr42HpUIdAXIAUgH6+NdyHz6/m7fbMHpYUIRbxcxdzLxd0BolHX9ru17tDx51KLRlm/N4UndUBUqpMv5O72/pPuFWf8R1DMlie41j7DgezmJemPNk/4bwwgMQBgChnHEMA4Ydzvly4OpSiqPmXauL5nNFaB2nzjPkdAqzwt2c68gBQYjHmeI9en+8fc8bv6eHCeoV2oE78mOH7pT42PtWS6QQ7t7p0OCe5nnFlG995b7tW93+SYltGfVvpam1tS15TLUj66PdAEQRiTMIPM89/3qd50useU7BwThNig/HhNwBPiOssFEGIKunzBAJKoxWxIkEgzDqMYdUwSPhGG3B9OE6QSABel21CTAT4I5ncx7LrX9JmBgBtOAcMOQk8UpYc1FSQQIa46CgUaNTucKkKjKikQR2bs8JsR7y2lgeZTFaAekXgnA8GFnxlHuw11WL4HAQwASI8bZzsWKW+NDrPaiYHw35PMvM5kCBdljEXcmfL+raKUI0qPWWgxAAL6lTFLy/hbksM1lqinXGULQSBkpwVwxbVk6TrCQ9xk9SG5DnNVgKKYIurU4Lg9uIkdgjBBTdfo41XyEj1vCEWwK9DqEssoptB8zbRsnvhTc4zihUyKiKHI143DhOz01kM+vyyoyb5LZpJof3G5xwVZVxJPqvo+VAOZZXN5THK5PT/Qlt3ctVPoaCB4Q5J2FK3e6nYDKiz3hBuqF/lDhSMcktyB7Vu/dqgf8p7uMN4w7Q/yopmIBdzjhPguEncfZ/88HiADx1xlzFe69z1/ujvoJGl59FMJUHSxH5/19rEhp1tKjfH1UTnT+/vOw/V7f1rOl9PKc5nfhHmeu7tve3EGQkq4FZiBSu86OBFxJiQYNgSVFWGl+xau+RobiK3prD3y7Ua44nHqspG5/GQXHr4VtTTkth+ZOVs98eHom4+OYzCHL5bQiOYqIKjADCIzpdERKEUSMcb/D6XDUUTD8FywdRjQckg3PAOOL4SLUpsMEwm6/z/j3eDhgf3Wdo5xoRLUSIpqDpvGZp8Jz5CicFnq9ntf+bED1NfHIrkbDoqgHeQL2wwAIYbY0JyGYZ3uKDb3YmslyX7q7LQd8br1cclZoOaCupordd7zack++tgqPDKIcnWCKEYfThGE4ARb9VQ1FkynE1VBiTgJYmlMOHinWeAz4nJRaxcaHUs3rC5BmTNOkfLxH/gEslD/BPAQg8JRhM0QSYlybZaAT0CGPvjXHTAzL+L1EU10bG1eQZHm6bd9rf/T3nS47vYhWHnvZ1Okg8iflVA1tJdsnrf667mfjv4irrlno/pRAIXRdEJxfxW0t+d1XMj1bkX7f4K8Fbwr0fzBkEUlNJCslr0JFlM6A53Pxpz5XtMAtWj+TeqE7vJNnLJIJwMJD6dzDDvVh+dU4blnDOe3NgrGu26TcIsNC6fl1QQ4Fk71BRfBeBB+TilB+E+CDKbx/I8YHAL8zIxjTSK5YB7J3eUxJlecxqhABACRlor3afFDpgwuOnEDnQ/mimxcAFQ90Cz0Zq9DyJX8dAUjNAT1X9szau4z0fV/40fV/b9hWoPYXniupn61NFu0NfjBs4rvvsNjfGMkfB648r0O1o/rO0JDrgKjXuADp91rQUQSUDvVPlipn2wfzOrdDZOY1KvLTn07WlluPRdaU57VAC1loCgBXqERTm3X00GOtXsG8rP/S0rah0EL73ZwjqUhQmpJ7T/PdSt155i5qXdt382J8x5i/LHNhT59mhHdcTSg17+r/FQ/kB+YKB3g4dbH+kSnAwxiyF2CcI06We3DYDRjGcZVBIRifFTwlUDteTTjAfLCt3vVyqH6TsCypKhOXroMXwFfg3S2PH4Wym8pJoE9y4A1QFeXLYSnqbT0CfT0GuOqmXTe27q4oS/ebNemCJSZVnnutIiVcv7d+ngsOgoW/NN6Yrwh0aH0/BFDFPRQXDtcj4mHOraz79fwUWb/csKRS0q48hShJFeMp5jCdGrpUwBxyiit9wZTnwTx/fZ9EDVc6jROmacJup0YmzAG73Yir3R773R7zPGGeJhAVgWw/TzW8Zn1fsoS1TDdS4DL33dv5ylVRyNdoXZ4EuEpIh2QGGXVra+/yXlS3rjTT371ocAlNuqPqy+KcUgntlqdXbWPZCW7sMjTj0a+74SaosZlrYETbkwIB1ypAD0Fxcw4fTgQE844aBgSLLqOCX1VQhGARIcyzizkBAyNSwMA7zDghJa6MrFUhLxRALKATY7wdMB8mhMBIbMp7o/0DqwJdTCGrHn0JMwlCYJCon2siVb4jywYkK1aKsNvwBbOGan/QuQq3liu+MiAn0qNxGUfblzeE9FhCuEPM+zAXbhNaEwqb+3xsxQp9ddKbEYdAHgDcVoZr1Bdfn79rP/I62kZbTUoJIQRM00nTVQTOoYLLo4yAEQlTu5orfjB3t8PF9Vr2fbiGC/rrCSUs97eAvn1e35qsorS7fXar3PJMWQNr09mX0V+rx/FS8GgDWtb9og7BAwg3eTmlpo42XHwyJbvgHsGMWwkA/cyInwqd2+EO0cLCNz6wIuCfGeFT6YNgGwOOJrM7p5h2A4kfAhl3lAuXK9ErnN1MaMVTr52biXACMBIQRddEb1QxypKfyEWvdKH99dc8P/OCL9W+qMe3rsLAmjqj7qLyb+Y4ZDLDVr/J2fBwnmaMxgOSEeKUIqZjRfnFjKKcJ4uWEiaw5hh3h6H6yOU8JxEEEafjEeNuB3cgeXp6xG63N/4zLaaRmbJ3s4Pj+OdmU6De0IvrhvhSRbeUxC7jhX1LeCl+uxTIaC1TVb70z1RyBKf/pNGZAGCaZ4RpwtPh0CEwV6InxCjmcKb4nqHrS9eWp5MyjNwxax55x9fFzJLDxbvhf6ic3WDrzHmpKAJyAzlDCAWblN/O09V/8926X39yaMQC26T160GAbLFV8cMqd1oOlflmvMEbXAxvCvS/CTyHNzcRg2wjL8254YzLeYvdTEDgodo1zPhPovmO7kkZ8i+U8E4Kgfi9YloXPs0Vp9KEVFv0a10xXB/wvKOZZeoIzoKZt1dySDS/7EI3OA1OmYAvhbfdMYoJYDLLYrNAQznUEoB3dsAHAe8SlLCK4CMYzAm/c0BgAodBw/CZ6W+yHG7JlOdJEmI/Yz0T6sK7qt1Vyq/qGjUWac8RmeYA4cIGI2AxzpjtnzMr9QpYrrFyiFtbqWX5tB4IyzLqCb+EPV37vf1efeBewAuo8nOW8evH9VdV9UKwMaTyPdtbNLW/FhP17/5FWJkXN3P9hW8lUFJ4bWG9YKCe53r+V1Cdv9EraXz7Lp5/WRufM9z51gx4m86il5o9Mwh/MOTpeQWM1XuLMRSA6RZBCJFUACC/z1aprRVRb/LENX12b5OCIMIH1XhlpZErkGxNUb32WL2M/fDvtEPgRnqSpSVFCeZ4s+B5P2jWGLVcu7ILxxeunT1cS0PWwP79td+l9h6cg+l4mIpcSY0audyue9XWRwDtG9qI7km39F5rSd2HtbEhAHKfQHeE4R1n5WxtNFgXrV6yVitV7IC1NRsP2h+C5g4kIqRTzPPPDBOKKfc1W5jmw9MThlMAEWOaJ7z76UP2PhyHXfEytNblXMAEEBhCCfNn5ZaISPPmsoUx5kpUIZKjKOT21mPSfZPm1/PQ8KVrYAf/l1DZfh16G/V7BJsvn+8KAsDXjMP9AfXuWaovLwOp/rbto+bT2yo5tpPn5Sao5zeDrghyAHAFyGOy38pBMwh8o6E5SUww9pgw3IaqbPPkOxD4ChkfCWmYTmJGGEbIbYLca5vDrQpi5yfNpzljBh4JV3d7QASnJ8WHRFS8hmu5VrfH8pHGvTCoGMCi/hBBEiBFXX+JBeASTpIcBXq5ycI/mlCVKSGGiOPxpIa2VwxOjHAYsN9fIZln127cY9zvsNuPOE0jTmGChra27ODemc1FZyehLveiv7SMSNNfW+d3/XzkJzNCyGupcPr25kHyb4d4TABF4FCN+wVAQJWdnHNdHtKfey/1DnLo5AVuLb8FAJHmaR72ASAgPeU7AAQu7hdxY5UEqtIYsLWt+KkTwjWb51QoTEEgkBCGoMpjiTOSAON+r0oIsUYnPZcGtjzzol56OBJoB6SoOdI5DBCZwMSIT9EUIAymUfN0w4TUNOhMmYIcJMARGHkESDCaEr+EYktAEDV0EhNgxwAcImgGsNc1zzeVV5gLrsU8/n1fISFFWxMPWtYMQXqMiiMAxJh0hdmGdCUN3VqCGiLwDZmBe5lPZ2kk6btk3pFFSWpr5zblduY1ICjyBOu2gEC3UPEAs6453+O+XjJtZVUKBGCe/j9777kdyY2sAX4RyCraljRzz559/+fbMxq1RDbJygRif4RBIDOLLLaTmcZMi5UOHuHNrDuUbV1Xp6i1apE5APkkEQLcc+l6T0kKGk5gOsKDxqpXuoBwDGN/Fy53uK3nUNe8t+w0RV3zAf48/fa81ufKa84VusoS/ZtJlcaT3GFNcQlkF686Lu/RHvY5/wGHOji0l2m/6oEekOiX90XQ6GHnK2/vDu7N6ImS/NkBdlwBVHnceIJ7JOFMU43PVZle8AEg4PB/KgI+/Ufx2PHfP2H5tcI92JvvcyJM//4Z9VcLNTx4uPf2Jm/TtvmV0NAHnZGt4c93L8nid6FOub1V5JVQ8gNFE/RlfygQnArhVtTDuVj0CP/Wv6/wqJSArA6B13nu2GTzmrMlVbDmHL6krPmF3E+nt10+wJF2Yk1F955MzPHeMi+o0lO6qAIdUKcbgztEmt4GHmWlYDpMIGK0KuAiABHKNGGZZ/VQF0Kr6tRzYDb80wJ2OgnkcB5Gdwmpd2uZNJrLQgivZgJwPF6h1qpK08Jgs9IiAbiQhviWfr5rrbuzP1kKltYk9hXQ5bRLVQAUdIoZArO/QKRpUhiGAfT9idXIbl6luunzL/65Xm/2i9dvuET2wsKvJfprLLU34pEWNmIHkJGCEsNUk70T+wsUv6dpgkgDmmCZZ7wQBS9KRECDOnLViibLJh93HEonLfbmyW426f2iRhrxyT4vROqJbnt0Mlzemhozlkao1WglA+gbOtrpOTivBqN5PPD/uuNOE19WJMGh/F2Q/yKbtX27hQ7p/a1m9Jrj3bFGoNheNu6j012Se7YHgDvCC26AkCh4Wyvbr9KaGjIEIHwfJvpaeOuHJ/rfu/xQoP+vFscIhnCVqe9goeMvZxw1z8cuyjMrQK/W/96LEvSPBNw24BNpTm83INe/+6Q0+X92GqTh93kCsIPa7E8ykHXpKxm+y22J/dhDU3DERp1wdoQ7iNYZkY+uWV3hX5CU8B8h+ADBrTHREA3e1aThgzA+EUClaPjFaYr+icxAU8+RKmpVFyHMnAjaTmUazMgYBDEiHVUCvsznc6CHYmVQkOiAm5hiv1UsZnEXTCYllGzTRpJ3Uydhsgjb2YXtqq2LrP7ulc99dr7V7fcbEiVdr/fya+9+7+u8ObBfdu9fSmqs5/dz+3qubM/917++pB9/5bLecxesef56hQNyTd9yN/8on1fozD9gnNtqOM7ZoXgmTjNQIMk1hgXU61xcoBTaU/tnSNRDkGYGuvNMsgWNWF1/AJByoXsfel/2fm3H2u9dbe71sV+he3gnQXeMIKtr/fr9sF1psn0Gz2scx3FcgSKKF9YKy7VC1AXRbei50Wj3o8X2iPu7YKff7s9daEYruiC/KevftPXuDiW9tbnM88B0Lq2CTD3wx28fcX1zg+kwaf7DE1SJLl194KW1ZmH0bFZu14ri9Zpi5+keddCFB+t1+p5lPAP5LrDe+bJ6b0sXC7LqcG9M41p+Hs3U1SLjOxF2+3l7usdermj5JPxxVVN9NgFNaolvBFx85VyAw5oLMc67f8Wm4dFw+C1g1Ci67rmP3fAn0bkASNQgRLjvNC+ei5zgXi6agiCEpCJBj8MU6CHovG6QRbCgqqLoSRV003TAMqvxKrN6ql8dr3D94QYvzzPKdEJdqgoELWQ0Evfkoq9xvba0a58D+8qWatwRezTZtuiu8wyylObP/7pRTT7f+3vvLdiv12zwcWssQxFUug71XXK+Rzzrqb/epmMsACh8xGz/83lnMMpNATHAVDQvPOl+Y/ToCgp7izOMGsHAvbtZIzFIE4BFDbRLQbmaQKy8ZmsCRkUjBr00DWkuFnLTcT8lj0IiCBaArszbvIBZQ+syFxA3NMcbzCi1opAai0irKNRQwagoADVN90Gsnuqw/koFTElXwKiPFRXNUjhY2HQi0ENTT/PHBrllEKmIVsKovMtA3KuRmNVAHrAUEuu9gKQg97RnfZMzaINPfcPkfajLocYDVPqOcLyZaQeFRdvd5p6HXko5AE3XWO6A+tgjBg3w6Y4wPdzYfoF5+l+h4jl2v3vknSuZZrwER3ahPDaRi5De2Rrdni9rvEW2OPQLAb+RGS9s3+2U0CXYar/Bc2d4hG7ZA7YhAOJu1Y8gfIgesYVgJ6jpphAwtZHGzV3a4vDenwipiwfQrx9A/y7RJuMO7deG6d8Fy693itd+3Y9E4hCppTY8D3qelNfm5k8pA4NyCfS9vNqxpLrZr7V8Io36VRPG72ujjNDaQGtDI5/pwfrZ96I7M24be7T35rkdmviO4CcUFjennfwMi5/zTmUTxHJ8A6VMAAHs0VhkXOtpmsCloM49KdFpnjFNU9BonfIfAYceXeOXag2jKGZWHoMoPI89baePOxTbMWAa6NM8K50+Hakp1bOyGS8h8MnwveMYm7ugWvxcEr2yCluq7NLrbVnv3AHrndkkuVYa91VaioHusokhiKU3UtpdFqC2irosOGXdg0VuOs2zKdHdLEnphSzH1/YSXzFYxhjudTMs0VgDdVnA0PY8DYBGjCWQMEQKuDQ1rqgcxoxkWWyiKSCMkfZm6etBMBsLrepb6XY2bZ0HSK89OPvpOm3LXiSZ12qTYVYSJxD8GUelW7nMj/KjvK/8UKD/GeVzqJoMsC+odiTe+291gtbK6gLz1PE8Mpr3wz10YExda00t8yBAaybAycRyM4cKwU/NLN0EuP35Z/x/Hz/iQwV+R8Od9eJ3An6KaGicYHRmDj2/lv1esTk9KOz4N4lC47+AehUIEIIuiTFQagHB3UWNlkMjQk6JekQpQ00o5AivAdTznXXyxHLqtIaX1lCYUaDWp5NMEc7JmUkS4ASAPbQLusXx7wRMjtzdmx06lgrBIg2LNMytYpGGmgMXupDYPPjWhC7ZfGwJKdsbDKytpNgT2Vm9vT4ybwVGmQqqVLSlYW4LFjQ0khDwSLSi00fNZlBMqACxJbF1ERd8pn/xfCQ7x5JPwXsP4ECqDTXuXUfr1jnd2t5/vHqtTIK150Rwevba9V5dl7FVF1zT6pkYY0G+ihQep7G/Vsq1se71dcpHS/k5Vu+/dn2OfRtZ1M+rO/98q+298r0JtfezQAQC5dC4ec3j+KzWfFWbvkKdaIUxAEmwKKuPLrlOdHzK9zg+B1/GUgSOkdU1cN4w6BuXL2n23Kdv7cpD3gLjlHTvXDPE91yrerbNrte/ESRBRt8mDpbbRwH/KypVQM+95wTq6ahh608MFhNwk3RvJaJhW+axDvTPMKFdVTEo5ZG5s6t4c69s6oe5sAZV8oJOrYz1yHBOZOdubyNfULq77Rd1Lygc1h+BdRKxltfkUj4UtAfL6XpnM5Sif/oZI0pW+wNHK1hTYkMPXRnh7/fpAqAhgp0eIzGrc08ybvN0OBwBmFdiKRFxRz0Seg5EL6oULEMu9MP1EXgB6rIEPeFh2/0f31lIPVM0TPesQ7215oQgj6LXpB4X8gmR11Zz3roPH0HD6AuAE2zb2hqmEAKprL3t1oz9W2d5DYfX32kf3H9ngmCx9y28se8hslzh0V/f34KuDnJMfZ6OuoTC0nzi7tk7WSs1nTX1M3FPk67SHD0GCYTpXt9wRVR7auBrzWnsXjcmhsWCOTx/3OP9gCPQNEw0AJTbSfdnVXr/5qc7I2cY+TTe/9812tzw8PuDKcPJ3hGoMM172/GfK9oGes1dB2Psuq8KK4se0TzEVFkuaQsHlO55A+gaghh0bdEWmFAXwdPHZzzIA7gwjocjjlfXus9n/bBVPU8TF1QR88oZIVuO7eFAKGNd9zJ35T4jh8TvRr0EspzZOhE6a6qWUeXmer+9FvS39Rdhcyn5hs+9/933bw2PW3u5RroCvV9DzUG2l/ZOHDYePV6n8t4FxWnl52y8TqkPetoaedSLAqfrWQz/WuXluliuTahXnHmcBf0l2t9WNb83XgA6qle6KrU1cgPM+1taQ3sWyL0p7VvFy9MLuBDq0tCeanhreY55gqUUownM6pleCmEqEwofcCgTDrcTcAKokBqGcdFUZEwQZk09JnoaSQqkCMokEXq8kUZWEBAQ6b9MNUlqkFBuCfLIGqFCEPEs2ELDQ4D2WDFFyHTpRyjoGd1tlJwL5FPC27dKAYG751lAJr92PLxD2Im/JwR5bOA7M6ApU/C8rtAGNK+8n7LFcFgLOQUZGcPprAhqU/83zU0PlHvW/PGJOomjcqf0XX1s4A+Wp/X3a6iv8RMIV5HrHEAY1StcVWgw4RoNL1FnoQiGsUObodfzSojv/Pc1T3UCcJDbdG2w7KNDKwLjBpCnONcA0CKfLgVdKYlnAbonsIM6z2Hd/B6cdpWhj2J9Lra/mnug2rmVpuxKh4Wrb61fGeIRgCNUia7tdzy0oQ9oez8/bw2A/IH6HxuntVzxgPafu4Rl+4yqLOkh6Y8UipZ/fcDpv+pR3735VSHUyNaOAgtqn+zHnPqV2ZFvcR13XyOkLizOO80xwQ4DKPZK3hDieJNUPXQiYBI9Jz16hcAcilGJUFPYb0Vn/fnZcfi5ibck4FLIGP17ZDx4CcWWi5y5NCOv1VkAN0jTXQRyOGl0UCwYDcBCRA+KGhG64a1G5hEAZI2UEhXiMBm9ZFW50fYcETs0nSQx4+H3j5HORj3WNarV4epa0/wQQjYext9Qw0YW8zYvBbUaDcuM4/UN6rwARChk51cMl3h9UBy/iMneIbgB8IQOG31VqqXyvJomwCPGGL1XGwUecCPg2BKGt55PJxAzro9HhUdLQxNgkSXtESu+b0GBx0LGsrP6tprD0+4P7Qaj5iaW4FFQXiu+0M9Aph11KAwx+oK9k0R2HhpOy4ImgontBIpFBwABU7H88536bLWCD6zGEoaricgcvHRdT/MLMKu+oCbDa0/9pDnrdcQhpyaYDoVA0tAWwdIqpM6oywmH4wHT4ahRgRgoRfcul063xzx5nwWdJhixKAhAoRLe2m68IYJBhnYJfMw4WtdtFQHK976sDfdH5BV1JfpXguBxOn6NWTrOUF1GS32UoF+R7lHUPrbNDDSn4pNhJ6jDj8BnzQBwklG0xHN4h3X/roAtbX7sXF1eNpHKfnik/y3KDwX6n1guPWy7R4m272SAmK+BTMupohysCloPWeNCbSbW8C5QgFyR3gFC4OiVK+1ojKZo2HYA+AmCT799xK0ADyS4ExWN/E7KOExk+bB4DbzH4TkedYA5At4udZcAxDS84UjekWfAcvJWVoL/DTZwjCbo1IS3qbbZhm/A0gLQu4Vfr71BWkMBo6Do+Fn9GUrqAEMwG/HzE9T7rwD4mWxuCaY815Dw6pGijMsiXYm+iK0vUr9T2YaWfB1gM7GGumzJIplJvR0c1Zr1Z29DCdWlVSNO1DugESDcw7lkbo8ZaFXny+vLgkEnzsKu08z1Mnrt5N04ws8v47fjDuvFhSURlsX7knIaucCgH0e7JgSRDZjCqNdg9b5+7cIMpOvXxvG+69RSELeU9tbKLINM6AdxbnJV5/ra762f4zOu6cw17bz7ta4/l3T6FmUN/XHZtZ8z2ntHVvcz3LW7a6vmNYwZLmXjYfLatfPb564zg3vpWX8L5n2v0pVVw9331XHhPS8HWZ0KWp88MsuuZwA38aQrTRSBKykgA8gdvJUI4J9VgeO5v7owBIFfg4HM/aboiXXUDarsjSRdlD/8kwFRjONBD33XYOq0aGMLG9askUP1/t/+K+cdP++BbnfNvWonHXefg3P8ml+7cloO4xukv4qooo/v8+hHm2sBUO4tLHAsx8hAKrlBsW7deMbnZMS8Q1/9u7S4EcJWoB53ed3PWZGQenR4Luu2VNuCyTsh7RWx/OmAeqBIbSjT1IXjYuHZCWmdxO6bCCjcABLNeWtqM+nXMOa+3HIo0Qtggi2CB2OOTbyzP/Nl3/+099owz+t75867P9vHUuNOzafAR7BWnr+3nOvbmlJjUPj130WcnAAAIABJREFU9ve7AnekIpqGcx8qVD6lPanQsT07fWT8if+OOvperlggTxyGQgDAN4T2ZAakH+y8cYIELqg7sgk2t9lumxuE5kJAd/WgIKF8lBS/YXnO+3UYs6R+kjDoKlcOtFMDCmnoe2YU86Z9lheUuQAfgbu7e5RySMbL2lWy0Klt8TRL3iuOfbIW56lgPO3iwC8+J8WMrLLPYh8rkSqF2UK1V6nRtly49wJPmJFB90y3/kFPJ62+SWr9gGiVAFADYaRpLsHS0tr2ZoJt+RffWP8id7vAPe051nyCmwsp7owk4OAbNXonZhAJChX1eCKCsE+gwjUyvp5u1DBD0x1ofcoqNOCTQIoALKifZtCdoL2webebmm0V6jTDffdyL6VgmgoO04SpqAJ9ahNkMi88IoAbCh9BxKi84DBNYZwPNMjS0FjQuCcja0worUJQQGKiVguniwYQF5Q7QB7cDINQkQWulormQTR0us+kAFJbx0cC1Cddf7oxUujWIJCfV1ID+kyoklcG7AhBk5LDhqke8vqhC8rdSUpxoq01QY223OEh0RNiHSbm8ZzYRX1oKPcW/S71SaA8OyXc2WGsI2mLPGR8uojz+B5GFhZ63uBV2g9rExXCaq8AaEQ786Qln95zxe2OfE68jfabnZ1fFBa036BKdMBSEj3BR+GR9rRfZsi3A7IdprmSSM+O74cugRJ0BSLJHYge+3TGwveKXSm2mZu0muu5G42tdvqavtngXzMQySmU9eeDvfcwmJoT7uCQvJ9Eikrrf/9Ah+VjX0ORKsMnZ//ujeNrXA/Phrj776NqHPdPtox1nNh+lijfhUV28DXTnVqJwKKe6GQ70fvGUJ4p9gA5XknnNxbWaco+rkxLO2jfDH3Vz71x9mka5ymUr0nDmtc90wBAB5FOhW15dTWq8ohbjiI8pYeYstn7xOR8i8QUDFNhOGGZZxyvrlCKRlCZjgeICMrhgJ/+9S88P34a5olLQV1mg782IiKLlG39TnI+jxLkqypNDX1bbeAyBVysi6f6URnv4inK7BwSlMt+RobB2r4bmamHuxneiIRhlY97JyU6AI+y1VBY99mEbpjjYcbFcFCsha+MjHTe+vfedd9SbfOOrjPGjUe+P5KctANM3XvEAMxTG52nrE1D4bdW0Vhpn0KMYvuoMINKAaTLrqs0HJhwOB40hPpUVGm+zGjLorL0ecZihhEgWNQcp7UIbhzbarOoPbofpqIp7bA0SKuYl4qFgHmeUOs1jhBMmMDTBDblucrzgeCtSZ3P3DgPTcxYsCua8/yx42diRCQa/5bW8//6dV+vM5sp6qP1bf0btNGW/tnyDP5tP0+XlE6vj04ITnu6YVqOyrOXSsvPsphsQ5RA0j46qedwK3c8AZp3ihx/lH9Y+aFA/weWcwAySG4RdZiGAwA2BE0DXpOwwF6hwAHiSjhzAcD/+69/gwA8/PofEHo4DifciAg/uQkhADRnc52rWAHFTp+lZ5m46xaULnrorBTijYaVgi+8Zd8C2hRv9UCGmtekP/cqEzFofyWNrpMTmstHLdw1tFwzC+afBHgUwYemPkIM4D8ADkXD6MHCwbTWsNROHM2L5hWvrUWIu4GiTBjgMjS1ngaKOnreDkOKewp6p2iNCFZLPhWFNTHPeLfci9X1feFEc9q5qYnYS/bV/ni+P0Zz4jGTgV7O4dktcbr39WvXfY7Wzz9rnd9VXumheHSC97C5sn2+Iareun7t/tdkyV9r+/LymmfF5eW1Sj6PfD7/3P+OO/ot6BJw/NtvyveVrKT9S5T392TvlF3aiqyu/V4WhBCeoDbyPW+2mBCE/APK8E8L/8LdsMEUqaPyPKMoQnhleiVrgyA489Q7HV7pP9mHD73X2xFmJOLzdr2COnv7Ide1Dbvb2dpra+H5LLynfHOwNuuc5/565hN2SHTQ2HNVQhHojkLhkc8rrXru0xKeFnecdLxZ4e4Kf6OwArafP/kU41l5ivu6G74nFyCA1CjDXXMlxAUmrGpotWp+64ekxLkbBUnHqytVzpu3AE0FWJY0dqUtNHyxgInx8ofmuD58OMQ7hE7zaJ9JI+RYQ4kkAojCG10+NbCYLzodvUVj1t3zeyxbiDrO6b7gYXv/LYWDt0PG+rlKdMEJBGCySAzdQ71AxuCs6USdC2x/vs/5mXuf6+8lPTUFGZzmVsNToCvFpmvzNPJcmi49TJ4OFQ0TNK+wC1zGSBoAop2KhoqCKcbVnvRvgQpEqXTlZJsXMBfU0wIRwfHmCvPzCULubZ39ewIixuyPZe+0jwY763c28SuyJQoAOjKo9ADy5GcLgvpUcZIFh8OMl5cT5tOM6oJAa2uEmp7fXVQhb1BGoPEBfFwteWczumW0KjF1DxGVrhiOtwE3COCjGW+/NIiF636r9Bl1zxPb59RNuVxI3dBDr2spMa4+Xhn2fD5na1X+pXi3n+/giEHXhPpsRtc0hslu1geS0teQChoaKPl5sRDAMXsAgNpEvfPEAJQImGDh0rUV5gKqxvMLUNiiqjFZfldd8+Vp0ageMmGRJTyRNSpdUwGydGPnQgcVWvMCEIOoaJtEADGO95p3FqcG4ik8AgtdK087Exo0/CnIFEkokKemwSGudT8yiY4HDa2pok7hLaMUQr1b9N4nqEfanStqVTs9KH4cKRNQP1lEllvWfOtmFKWRSBxxGR0g/RR6yN7mwhDjbQ9F8Umtc+xBV3wx1AvaFS+tAOH9Turn3KQCYuvFqsjp3mUd/ooIpGre8x6GVTQawQdg+V09AfmWIY/9/Mkj7LxYdI4/HCaL9c9OlYxUhNM8YdiAlxRtAxvg712uSBIbp98y20hdce6R+faKQ4Uprp8MCt3r/v6ZhsPJvxQAjPabnp0iN2j03I0xUy9HE5vVOFbR3Tp+DqI15p4AVHwyT+yneBOAKlTJoeqawuwwuxlBK+iRCJ1GzvT2Gku4jORc3dh55n853S+4B/2LsPy3xbcOWnId3Y0iU8l9nfb4PoHmSG/oeci/XZEzf99XjrKds4O4jBGotrnDFyI74ABY0wCWwCWdK6NdXAnm0bfghlM5pH764YhvRV7EfogAf9JpBHR4tKe7eg23BRjM91K9Xjo1tqZfZPgmIjJaxM+IeGnTMJui1CW7B7OEFnHeQgfiBkLMCjOlNbw8P2E6HMMocD7NmH//HRBBmQ6Kf0pRPFaXYT50CQRLbTgcDgiOiOwd0beq4UFeJuRIXdJa9yYGgCYh+wRUMep0btUBdeqI1NisMGuIcQEmC0n/fHq2t5xi8f6MVCOT3pomNaA7NcbN9RUODxpqrBjl5bFDlr4rhrXenhbvpbcnw7uS7vXBbyuS1QsyXsL3tORu0QjzAraQTQLDaA+YkZtFOiIzzADMIMPodII6gxVCa8rjTYdiSuy+qYOdhnMTzfYqmUe5yuiL968KmkVp1ai+AKzdVhfUVtFahbQeJUvpLx//vmx9r/gnvof63cu+f/ut/fXe+z7vgZAXyfqL/uWeBJ8NYNXQOWi9Q9SYM237vbxHhrDwSDSIn9NNr/7c8sMj/e9RfijQ/0fKQCwbUw2YgJE89AgPglF9TRJAHsmgde7zu8RUPBLwQbqFm6cBcgs8AuGPxOM4IdBJjXMAY6QQV2g3AGu/3wHuKBb6RiUoy47t3dMlM5gairxBqoalCwGPaNirBWop+CuUgWUmlKlY2HQNNdIW0fwuteJUFyy1WsifTlToEhGQjRbePaQ0h5cA9iQoF+oEo+fjaTEfrkBHooZWHDXEQvJYH6T3aNiLnze0b1hk26m3OkmrJfqMQUn68debk+9V1rsj3/+nlq8F27bM7raMLPI+dnirbNnsL+nR/3L5unPTrc/jLwHAMwQ3avoVwgWVpLnAtocrJfAvFAwsJc/zsy4P3vKADPoAlek1D8a1e4d/TVtGflRDZbpiXwW9piw2HYFj9PX93MI1kksh8pz69eeyQz1ce+5PbodAt2xe4wCF5GxbIo+uCJqn1DHz7T7F1gYBnve5h3Md53LVmaF3e7QDoIKHFMQkylqQUpeqHjnrEGtjdShlQrHQfB69BoCFJ242H9aCPReCeZC7x6kkoNN3EK/QSoxa9ByQpZCgW4J8AsRUhV6VU6Cvrf16hl6Dfe9h+kdou4B2WL9L9uR79u1bVPzbLfWzuzcPMv5n6KDE//oZ3zNNMRVcXFvw8IFyBwhFiioYa9O8mutRiqBgipDR3Wt64LxW1/l+Vlv07zpUGTml3H+1ediZ0Rh4+l4ErTQsXDGfZpzuXzDPS1egD56NyrnRhpj0M82RGktnKptv+PnSKzYVS8/dnaGzwRYIxHKSuqpAW2e0lep6/E5res145Bx1JMmIw99Yr1wXxn0G1D6D74hIQ6nHHNi8x/5tDs3tqSq63bvGvdHluUGuASnudU+qSE05UQiERmZYJQBY07RNk4Y9ZzPaKuWA6dYEx88eEl8bdAOX0A+3hlqben5Z6HWtWiAkGm6V+z8XaEMI06FAFlPemwKdmVGXK8x0QqVm4ysAdYOHBlNIQCOIgAjtUSNFdK943evyCaAbALcc53gweMrrYDNeP23XV73OdR2d9xYLxy0pLm2T5MlNug6FCog0VKgaLrR4DgKkAaV4Sg/RsMFu9AWdM5FqSuUGNDIjfRsjWng/Sgw9wRdrKCuJ6ZPej2gssUe2dJP+vYlzwPeE9qD9c++45EidYOz5c7KFwOfLOh/qXhGkyG/RPpTmjDd6i+WXAvmo8JblDgs+oSW6dQ0nhmtK96TfF2CQSyB/A3ehgO2d3KcM/8aypk3f4oE29VDu1/h9W13v4tUYmwD/FRB6bh+X6a2/s3hzEKgixw0kCF3tm7+ZxGRdJJtn36a8h2LalkNEO9SeMgRXokZMbWUAcAbqp7/6r9ocdUeSbkalONB3kSvWVjjWcTN537wZOwfiytVEeRI2yu5OG+2PY4N74/vtSEfMLsP97Zv7Rc68QuuXUjOhSLebtc4WHUP/V1uNCB4OM7iUUO5F1Cqfz5A76v15nnE4ZP4L5hVezLvZFeaMWis4kOW+vLIml/GKHP687xClCiVywjdLA8qGtxejWJ2q2kyZ7QvmQ9A6n55OClcJYSY4wJlLgc7OS8PVmjbH3g7b669XQuM9jDTYYERqRvpwI0HHfQTLOy8aqSnS/ElECiKnU0oBtwpuAKigwMK6t0R7kiQYLtEsF6WnDgf7DsoBBP1rRo4kDVKr4u6qsvvmEJkSbZDm5TW6c3PKPoNEvaxQ9PE9bVyi992vUjaX+843md4Za9tt2ueWxq22saP79sjoR/kHlB8K9L9r2ZEIXHLmRUxIZNZ9HBZSFMybI5fBuzjCku3XeyeqNJ9+/RUAcCsacvxWBPciGrZbBD+JWrD+Rk5mGSTz0JlBMOZBnmFohqcrRE1GdMq+hdMeYXi+UPzXPSIK8eqNc+zIWMRCyTQCqlHPHooHonruCg2mdQ/BB1JR5wsXtT6MOtSTuy4VS61YwgN9MW+AzpRkBuZzi88ngYY94dEKAxkFEZBIaEEXsjSJfSWQ8HohG5d7B0Q4u3P9+cLx/CjfujgJeOFK/WMX9GsPzGHdOynZr9b2F9Zwjqp9bUxfYwrPCbK/QtVfp3zfnrwpkCMaViSwm+Nt95wiFdLEdz9zWHQrP2OMLEgZxNzqXgNay+AVpiIEYzBD6UvhpeZ/2h9IwqSMtSXdNiEJBCJdQTF4Wr85d2vv0F5vr+fKfmsObBt+fNGNEGLEry4IkQlu3ALbQh5TyN91TfjOjSJVkMCc3mfNgzsIPEzIwwUWis5y5SZFs7ajdbrwYD0DK941zRXCSJO4K7lqbSiHQ3znwgz3hB+lTRY6tpkCXHa8cKwU89QDdYW91DaknvHQ265gZwIOhwnys9Y3L6ZUexDwPXeBWzQmwx8QQT6pN265M/+1WwBPuX+6b4vti9nC/adB4lw5B+X3js4+fezXE5r5mPhdF+8XHI1OzKKb1/t2iULxHOV9rt8qMCyYMFlf9Iy+4AUE4BrXoOse0aA9bSlbF0h11Vkfk5i4ce8E954QBNV+aRbb5bnicGOKAdF9FsS1qABN0DBBlZKLKRy1J2+HIO9exWsB+f58jd+OT2Kk5soptaES6V9pwIt6yvIdY/rjAGkNExeUMmEqaijQIBEJIvfdMlruhGd2WGr8Izxcuxb3hRd0T8Zcs6DGlxJ/JfgOjeiwbhPD9xVAMZVbDU9ziwhwhuHzyxp9lYAdEuN9Zxk0tem0kc9QjuzRw9frS2b4IwwXeDM6LPNZrra/CAV4FtANdWUsEDwaM0cbzBqVgC1f+nRQ77vDYVK6rApQK0CEcmOpyZ6hilsgPLZqUz6utYraBE2qekorkAdzhXqeG86nCuZJw8BPBVOZgHtVHrenpn1kBnPBVBhLKygVmHjCQjPWYXNFBIfDQUOs3pph9qem3umJ7wWsjbAOQ+AvVXwI6qcac9Ys4g2B1OP9uuO9nHqEoOnMCNYuzLM7cBcBoooNTV2mRn+FFGZoFwR8nHA6vUDEorgSLGiAoLYZADBNR4CAWpcB3nZcjPBoj/6Re2J2o8Jyr2Fsl8eKMFZBOmcBa9miHKQKbU+vwy5nZTnjGsBzCvG9X0p6+FrKpkvlFZUUZx1sfRzmEB8AgtEyMHwvaL9VTSlEDBHCQT7g+feHIfT8QHqs2mPcouEJYFOepPd8bwkAD6LDDaCGrmAdaIgMR+8geOz1CUGoxX6JoDyE3fldgze/btSvh3oGGLQdp8S/R6zLmrPPWCv7SGflvUDlfmNCDf32Ki38y9f2RPc9+xU8+GYSHMx4tAh1CE6wdGWappJEjQleziBsj5LpZSHgaDmH3QjBz4nzUX2+xwhc/tefdzxibxIFr6P3V5RPCO7OIMZoi8Y5DDiG4Z7TlF7luYhz+3ShwC20WtVrx5mTGy/lmbBw3gKTaRP3XZ36KgLMpznmkYmAadKLpnnImvMUAUtN9t0WHI9XKHwIj3gfc6sNZVLv4qmo53kzBfqyaESrqUydP5ZevaevdHzWz4OOjW3dp6J41HEuoDm/NRe44rdqRmWc5t49d7lpBIP6sgCTRmdpS8NCHLgG0D15nXba7HMXu86vx40h6b/5vQyPBljhxN9nHsu1gfwI8MjwqO1wkbVaAdKUUlyWJRwG3dC/FEatBUROyxCoOa+7NZqnNH/RO/NoZiLwVCDC0Kg4BWWaUA4aRTYirdTF0jUwqDWNkmATRbZheu7uvflIv2W9GpfM56XvjXTVJfUGHyJ75jTjNZPzB+P+JZtnj9CLtB/P90jnLuOiiExB1FGC13MuBMdrgzvX9DcqlPb0j/LXKT8U6H/DsgdOLz/LhlQcNbKHF+Gw1gMc+Vi+q51D64h/j/B+SMTVJICwMpSPBNxja1V8Hj1sWj0/pv3bf61iTK3mEhcwKiq56Eln/jcAv4ghDmb8AQX6d0WRcGsCkYpqHueqOK+oS1Vv9AhNkwr5fz5/QgKJm7thhF8P2rATIpGzPLBm60px6ZENfG+5QEEV6zBvsTXp1QfzHfHWX6x82Rpe3ga+YjuXUht/tcP6OeVrz925+gexzTdqa6/dv3sbP8q6UPqVdy8BHY5DMWwofV1y2OzNEMokHACYFxAFA+vhk7Mn8pCzXNK9sP6XTn74/RASURgCtt9HgdBGwUupbsCEF/kkjYKC7QyNQoLMvJ0LZN29uLogKZ/YYR5Ae43bs0N61pUwHu7Q7/I9xdyHl6wrwi1/HtaGf5k5t7yBRByhB7UtjvZ7upW+R6IeQoQk9Fzi3RPe31MyqBQLmpy/B4Zwh11QSJhKwbzMGs7QhRtpDKoIOoIKA8Q2THKJWQhEvHguVzID0gj3LNBcvK2BfqJEm3Qyyo0+fSxEBLlraI/uL6SGDXTblQ7taS2K+vIi6e8eHZ5bk83vBc7+7X3/dtufgXfCmCbdWvWVUsh4F1yFAsvbfrEvrjHsg64sP9sBPSfJa1kgaGDwxu84wxF9a3kCyrXzPva97SFioNxaf5mxfFpSqx7W/fPKW+sjLwK6ym+E6ErpbALaorzBsiymoGs4HCbMclRlunnQlFIgtXry9mE+9/aSz2G/nwTXQHiOT6sRrKl4v/JV0LOmd321Rh9jQ0HKeSRFt+8oh/9ZVf0a5TT2R9Dx2HvLnkAuDJlWYea9J5RnTsYV70rONbbm8OiXZ0G7UeE9WR1iOJoEoGkCDJ4XZhyvbxQGk6Y44EKYJkY9qei8tabf3Qo05KigPYmFFBf1njPvLE3P1UyO0JXnjkvgsgWHsaGMIUx3B3tWUItgPs0acpUZnZdc4WBS5RXbe7WpRxeeALrua802jvYk6qVOgO+YcAgAEN7+jjtvCPIE845PRnbU10DXq4FvGO15tV4eyUGcznDjM+WfiaAxhmm1TUIJvL8zg0awx0wcGsn6uxmMfOjGRQGjyMKF23fNQs9mQw7PA8pCBq/sLNILCLd6P3WWiZDPvvbvCp6+JugenC+uzB1Su9jU7Xks7137vSwtIPR5dYdDZpNX/UxoHwX8C0E+NvAvBXf/+gnzfxdUejrbbu7zhBtU0tzJA0xxesDvkY8vz0X2Eu5F8LiB8wrftHyxA4SJblwBL0A4buQ12qMj9tZAVu/kvxF+f9X3RqoYXo9lb64PQpi/eVj39xVX9Ge6HoBNkkHz1OWDAHManFM/sqLBvQqvMRQ/lGnO/qavX6an/ByGoWd8YO+QhLtx3n8ecerNknCa08QAkoI89yP3CP0AXFJsc63xnY/NTXtC+WnXcW7J0jJxN+DS7vYZ9rQUbqA3pKNyOI3ufT7PJ0zTleEdBNzOvM90OIQCvRqN1aRBZFaDsTWsTLw1JFEtaVMFx5DOqWJ9n6TEb4sbQaV6Voc0DIaZMbcUbcvm72WglHo/31PGc3EJl/A6dTs0b6/mcOASLzitYDhbYI5kOmNemhtizzq2woxSJoBI6SGuKCVHDtvpWyZHMv9qHwmp4SLD0xFoG9Okuc8bKW6tvk9ZjUeV1uBuzCV6boPHFG90NYN57Te6mkux8evly2q5jFt8q+49/PhWvWPSi/06L60rl/edih/ln1p+KND/7uUdp75H8VGgrGFF2EKYGLMrAEy4GF7CZ6xe1rjtTkaAdG/hXRsET8z4IACg3tedmaD4NQxo1eT6/XUPMolBGJHsXjn3bNWLlINPuifSq1++8jSEKDZmkUQswkL0EX4nRiHNS+fh24MJR9M857Vinmcsy6JhYCL3uQQTF+Mwz+6vXUKJTtRz0W4ICok87UFUWnQDt/IkiEaYF78XPd/O4f9sodXfvxZz+dllYPT+zmO6RNSTnr451HdynN+s/Mmnjr9whGfg9V8Hlvy5PclMoiCFYR+EMCYcxCcAdyE+EjYL9xwilPIPsv+ThhHtCe+ScGOkItzzb1NWymYhGc4QfQDkcbtTCBjq9FrYPJL83paNf+08r6mVLorIwvb8XRYpURqPjgUu0RzmvYfZ7nW4UIfZfTpJFbVWZynqAevSXDZBvUd6cc877zEXDaELw791no2Zd8UymXd4wutWH1FXrHPR94U8D7IKLTScunqCOV3pY2qO72PQ0oebLA5KKVjmGQSykHc2F3c6Tv+6TOp9XuuCibvRARGjTAXtVGOPeyQgLmUQZPkqlmnq9AmXCFXMpoj3cL5O5zQi8AfSCDtO+2RBVOwapZksMPZnwbX1Lt+DIHtUgoTXqt/XYKz67pT6I1AzV8+6uq7nM0QNrwjibEfr+pon8hK+jKreKhHMUvp7z3pf4LOqf1UJW0EWNlzFUgXlhlGfGviaIc9iOai7zyRFXd1jXD2ZlUatEPAzo92ogpnZklGZsk89TpSvuv1wCwgwn06ozxWz1Xuu9Bl1I4ytx7W/mdV4cfdl9fYVbI9X9YJhxrJULB5d4VlQuaL+rHt6mlTAdzgeUE8CsVyg4yp1+NXiqodcX7/tO1zXcz0a32n70STUC5bhOcv9obFMG3juxT3Pez1j7Tl3r9c33kHitfZa2L6/7gkl3OL1Qczz0JSwTQSghmIpOUZIkWGD40QBSMLDnj23uPf3miLPLVmizwIClRL8IxNhOh5QuKAtGqkMh4MqJuaGGcDyuKiA+UrPiPO9EkbQFg0kGUU3adFnxVnOw3dDaPUAapg/zRCGKusZKB8mC+GuKcqIGIUKTlQhLJpajospywuEjcf1iCLMqA8ziDRfaXtSLVG5ZcinCroh8A0MvzXUZ/U4dPSsU8auVtddLtDvmHWcxlM7Wh1oESbwjUbCmO6KzoMr2gkWNUXXVQ1uNOy6QHEzlwnzxxPKXRn2tnwSlDvCvJwCHwecIgqPSa97+rl0bztrDQSLvCJoDzZuZJOgFJUFJwiOFnZYq1Gzomu9vgfaH83Iiry3OWrU+XQl0+iJnXf3WdmLpL8XksVruCP4BMIt2pIMmMjoD/tdfrGoi78Q6m9Or1DUt9c/x4ja/6d4f0NvGt0VJDEbDNIQjLYuW+zt+Ms/q1QheOw3KMQpm0I7v9evZU90/9EMl7CM9O/e1J9bksjLju4Yw7gDmUFAwGn7McY/6vedPbgxmaGgK6wFwOm9yvQ1veHXSZ53YUXxSwAUGa9dF+6K8ol0jMtqtvK85zUiqGd+IvuNRjXoT/61r5ZjfoEL+owb620kGlsRgtVNFPy0f0jBKnTF8WcVWu9N3+fr/e5d7JxT7rSCVzYjWwq463yLf6k4QGL+CxGWqka/QZuzpxvrtKN3R6pFt/EImJZzPYdsL0wAHQHAUmVYP6C4hFjhK5tx8ugk1D3bT9JwPBzhhsmA8dn+HTUUgtGI6nVeawv4TURYTH46Fbb87pPC8NZQTPHaDNc4nCjs51IV+1yBGhHJbOGDrqKgmA/2vAF4sUUtUG7hHO3vrOtb28d3WMAa5yd33s1HOFY+YIKEiMF3BKUPSQStNlQqgcwxAAAgAElEQVQhNNYIME0E1cOmNzMinQ44apAXTNMUKVHmZcGyLGi1p6fx/mbDSrHw7nVZIEYvHMqEq0kjxpbCSlcfjpgOB/BU0CBYWgPNJzVqlYalNbRF91BNQFMNygbzyl0cKjB/ht3yGta9rPjX7sl9aW2+3kwexejM/nFiYVXc0G/d4u5+SRtrDcn8UdgBVcXRPNkHzrfnpi6kQX6U/93yQ4H+dykriLE522eQUDyWeA0OTsiU5xH20p70MNvYp9ixvZ8ZmTsBPO/LR9brW1FC+yAaduvLi0O6bnfX4edn+cdE+TJUc66MFtzRjkgAdoHNY2a4XVgLC0ffWuSfc2KgRu7zfeS2Dmv3ZcPolPJGSOS9TpaqTVQ53poy7J3QRDLQQBe2RJ17RPdfH6d9vz5+OVF0vnyrev9qbX6r8qU74M/a5ZT+/R1O24/y1crKyn30Erf72QPB3ss6X/7ZcAATwrMXXUiyxn+Rpwwj9t44RQQDud6PSQDw4HfWbcDqHMVWBBnHuK73zNWISWWAwsPvEGxdQSxc98Zbc2VkoB0F9hTnXjhyJKqSQOmKzmhGPWJ1epSAEJa5sSRFaFuxcOoQ9VTt80amSHePdBNikWCKkO4mECoafFKNKfq6EBCKZ49Skx0sQ5UviYZI618OJQRbYoNgAehepUPuicJmOFC4oNaqY0+bKOZGet9EBK1WlMkVH0YnN5hnTu8sMVvaHhk850VUGV7M07JxNziV1tn4fna6oqbvp/eVPeGJz3Wm8PffDvOX3bp1D49ePZ9Xtrij04jjW5xiUvkOzgYG7lniPev7vOMqfdeFzJ7JPKtPGfLc9wsImoOaPPRlQYJUGJXdBBVDmkf1k4mrbwG4V+0wRgrhnsIuVfQnU9yh5p7YgJCV92tuYeuTldq9opUSXWtuIiBUM3RqkOeGxgBNahwsrYGmyTzQzUtmnsMYd93jc/vVFZDu3e9e09u3zlMVWeileYlbWpHVeHe+3StvUTAdZm/p6cu8r7bvdEF8L55nPF8DRXHdCk514FCgQeQnaOoUjWTgOT49zbOGACVEnnFC5BVnh42kIUojOkxoThpE1ICqvbS+J55ccWyGz81ghpgQ1f7KsGp9Rjp8U+V5awIufkormphg/1MD37EKrkUilRx7/00uwVy0TVN0NDYYuzTljwUA1fDuJCbgjhX/2abbXU1bJ3YB7nWnVQYFCyGlpUkjNQ1xubH5RMQYUDxg3nD+eiiBmqBKBXEB33qfrauWiqU+NvA9xwZxaqmh781Q7IMBVv46wqE63hyIkq5o8FytXVNxAujG8GRfV08h4LjbPT99ffts9LMqO3/z/kB6tldKepfOvNuXgbZP00IJugd6br19bOrgIVkhvq0mw77NW3RrL3xK9+yrNLWd3pP0Ti9b+PX4yrOxf5vo27QHzex9X1bJEaWwMXTI9edx03B/xJJ9nh42OL5hnMe9fkXO9E6ypja/pnzgfXUdJO1D2pnv9Hs031oXB8565bK+VXrymHM1eugmHWSNZfCjZzypo6UbcI5roO2mrbkqK1ixHltsZIO7q+vozwAX8u7pO/K1c5+ft9Y0Io7JEDv8MvhjOIyg/MeBFY+40TATdbm2RcZqiM8MdvZIqs63Or7L9JZzbo77yBSyiHvWLgCPNhK0685o+31VBM9EOAhwgip2g9/xeWDGVAqWqgafRECtikfUmFpQmKMvhVZRf8jl7nrQfI57oq5+Tmd/Rnn8wAHA/MrKEdYrffman60zwcnuk48w2pfV/nN6O4z+mvG5Np+tadRWzW2ufOI0TWq4xwxPcb8sNdKktiZ2dpKDmHYu+qAGHRUiTc01pgmlFBwOE46HI45XV6FAryLguqABmOqCqVZMRWX4JBrKXc9v3qgw0JFwXZKVB88Z7+5hy68HQ99bm3zuBtCvo829fmz6IuO9gd4QgTRaB+KL9/a+uaBrP8r/aPmhQP+nlASgslVnvu6Fgrhw5XkwZJ4/+5zifFXujPgTdAtdAvC7EXUM4IkU+d0J4WMxgsf7KLnrhHMWSiOQTGg9iP9MppwH71lcv/+CM7zjG9sa1yzFfoncOpnJS8JU7pJ2Q5gqBCnMlmeR1LsLUM9z+9daVes4z++5gvxuCdmRT2r/GxWyPRVKdCdEzWOhOVEDUUQWJvdZeX5+/fd+/3nl3A7aV/V8fvmeo/2ObUVT/xQKZD13Z/bxm8P9M3b3OdL0O5QdQnavvJv8PyP8/mvAju9fDjuTl1GGT9caS6ynUUxQSLjDIOWyj4PJJK+LkkK0N6LMTK5fEbkMZtSCcKs7l0xvUzrrs78FjNLwet8SCNyPz+XxHO2QGGu4ssvFSF2JjmDAV17xW1eqYThZbci33TscgClJlJR3T41Wqyq1TFjCif4gItRlScIGYH5+6SOh5I1iOXEFShtySfl6AfNeF0itiXYTM/pzD7guQM70nfgmEQIX3yTZcFNQ50XbJKWHsrej0p1a33w6YZ5PuL2/x3TQvM4g9QhvluJGhWs+2WqM2IiARb0fmRnlUHB6etG6BSaAI9XcEIDw/KPwSiFmzYFNBKpNBSkwb05T6jKVWEefj6+D+fp+H8051s+33/UnJc6r78yWRMFrYUI2BLkUou5Rn369bmvCETe/3EJE8PjxIxBerd1Y1vvQbH6r+TjvKXQE6tGuXukEeqak6DU63ENhR97pdT9NgBpKXc3LDTS0ZuGkyXKjo7NPZSqgWwCVwC+aX3hBxYRiHp5dqWy1Rpvet0zBj6XDrw1UeumzwaWAJ8YRhHJdUJjBpZjA1fiJ+CvDTspq8LEFXwlXobDtdT/vhLaTQfzSfe/tf2no4ksaGvlG+5XgqxZZ/aThkyTjHE7hUHewjEmpKgS+BtpzVz2we8yRQIhBaACZqIa7EhysClAmAp0YfGP8/KTGROzaebawoE+CxhWNLdcm6x5YMKOQetYt7QWtLSBMYeQMCKrMqiSQQzpXXYVGMCMi6QoFSAM3slP3Ag3x3Y2ulF5YII+Kt2ppmO4mnH6rGgbaCJNSGO3IwKL8oioUCmpbgCcBFfPQa85DEupTg0hFueGIfiNCKKzGL60pDzqkiTlmvKbKFGKLCOHRVmLdXIChv9uzQGQxozZdJ4UrPVqOCvCV1+2GAWrkUFtV/Pho6StuVYkOAFRKfF8OExhAXVRYn8PbdyF65/9LOQCtQu5VEVX/OAWsc8OeBQ3FPM0douRT39AgD6MiKMMsLxXPEbek2BM3B8oK1Fj8qMl+UeePev5kGt7eQA+iCCfPAAruQD8nY1Aqkc6FmkVO+GiQij5BiCBOI21r3+Itekr9uYlfHkUox60QV2wKIiIRpXnNo+kGY70HjDuIdC90HQ82hQjhRS7Sw6S39K7X6tEfey71BLi8rztzoP3ZzoljZknv+O/p3x9w+vUPAD2eDUM9Wddz7fxA5EiX1CXycOhfh2K6vCQKyfiP5tElrKMNZuJk/V1eJYcybZKr141PsHND6oW6sH4TeyYmOs+47z8/Yd1wBvDzZNxGWFf1NAJZP6c8k3rR7hzPcUrWCG6FHmn4kT+W/iz61Mu8LHClpqb8bv1LkZS3msZP3ciIVOY6sRnFRjpI81A3eAGoU48rqpuYkY3RQO5VHj33KF2ZIiPSyFhcBuX5dDhgXhYg5J4Nk3R1ttbVQFXbFsuzvRj8y3B2aaoML0VPzGEqEBj8bxoGvPhUu3GcdOM2hqa3ITOiIybUpsp2W3GDfbouFYRZsT8A4MrmwOH4ETx4ovv9gA2r/XBuG71desjywHE2/x4daPT47zJkEcXZXRbR/yIMwSQiwagxYkGxFEalFNRWsbSm7K/xGLtjWBkZ5L2pBoAFXLgb7krud+clQWbY3hhMFvk24cPt7Izz6udjW7aU6HvK14O4MtDIW75Az+h6XC2NyaBbf88q2u9jl7Dk586dFPR9ANgaNAHKO+ZpA9++femGk98bF/4oe+WHAv1vUC45o06ADt9lAmBVo1tcRfh29LBgwYAlQmE4sNIJnwLgd1JFuhPWLg67E8KjdeJWEEh5b3yfDQ5kffFFtSUC9WuX7pUSgm+77/91xbPnjmNmCGtYVkA0z/niwmAlzJqH0lsPwwQfPfTQSJi9t1wCsIN4cEt9mJDa/mUmP+rVypXwWTMY2O7974yvPrt8Gdni5XuP9lsh5b/Lqn2t8rnz+Lnz9CUw7++zNl8I2X+UV4pjzhyejDY/EOwLDXgLoJ+dQe35hTNrmVOf5DB5uQejUKm3O7BVWfEtGV+sKBy75A8mKHhIjFL6ai3AiXHdj69F8/cEPI6Yasxul+/1HUs4QjDvSBQ6F7b2PEd6QtBQsUSZSaeYSxeEhQEkutI8mjRFd3JJ63MV3ejfxFxR/z4+cHzdRpztV6rAtru0x+DT+EEq3YhCXxBBGBFKM2Zbep2llNGIECpg0vDxfd3zUhNpdJ/Rg9KERDdXmF9OoMRcuyDMjSurKYiI2EK/mYK8EIgnSK0o9wXtkVahcl8x3ry47MHsNcV0oeQllbwT1/fH628zAi8tqVu0TxVuIOsCP0nPs9f2up/dz0dDgmP1rdbI6RSHCD/Vo9d9uxY0AMvTonT6NTRSFGuY6WxCqekDCIIFctXQXgQHO+ddxNOiXoeMbGK77ZjGuYs3uv3LcN4bBIUKSpnATDiawo7MMFf5Aw13vNSKmujwvM47VPuqjKH+12vypdTJXwrvv7Z5V89yiFIFh7aLqPNIQPeU00dkClM2JbpKUgklUkiQryPUixYE0MzgW9Y0HqyG2LI0yAmqnCykHtEE1U6TGXgTTJi7oIkaGhFOna+UYsbPYufIx9aNqfz8iDQLh9kAMUU1qZFJxQnAEcwNRAW1qrSgkEBkQntqaAdguiuYf7Pc7O6JfmJ1gYsQrtYuMyAVEzEadfOWirpaC6VBWp9+/c9RI7xpKNbWPayTAYXA8o1DlclDND9/76ZBnhINIz3dG4kZQ1R758YXDGHIx6T5Wvm2oH6ys2PKHnF5iwCtep77DMW0Pk6pWFwx0IX5hFZj4Ia/dd0KSk85I33udBgvBhVvfNF9eKvWCYwrm/3nIZe47Pzeu94rb3EnqhBzkxOAf+b4kMScD5LXLIFCsa34nzp9c6bNgWJ0uoNudK+kFwa8KD1hy0BmhnxpO/KBfgIgeHxzjqJa6n0DVC63ds7M74mMkSBzjnS/jqHY3wqkWDHb9fNR+f32a4cVGW+5Mj3Pq+dN38UZtm2/d170Y9rjzUOqA2Me+aDvO0x6vSgFk3M363/TxJO+V0QNHvyNDd0liIUa9ijG9fON2ml6w0kbhxUbxcDvred7xMjDmGX1nhMzqZZ1P7f3xl01PPNzJmq2RZIUaVYcBlbz2hbbPOpNLJZGReFflQoWT6diVBd1+O+RMoelkt4Hf+DGTx7OXdEr9VDcPjdsEMFgAxcGKlCK0l59KBKOZSKCxQ6yKvk52ndHpGrfOr27njc/txqFYx/uunELATkJixro9d0JQQ/n/t6ypl3f/zUAuIGInaRQmneltEbUsdZS+hohi1DGfb4AXcYyFRyPR7RWMU0T5nnGaV5ABCzwnPY7MDtZoER0N/9nPAEn4zv1aNfosU5TAeg0uRn4QSjSovqZdIOCDNgFPv5z8zX09sz9v1K5pI95p+9/oWBnFWdtb/NlwETbui7Fvz/K/2b5oUD/B5Z8qDdIy5CJhkrjUJ67dXRL+c32ijPwHcEC9wkpe46jG9GMgncCPBDwKaz+GghjLnEnFkbCKdiP4UmQbcZQjiPdI/jGck6A2QHl/vca6vFzSiJolIJFF+r1lnOYNFdCgwgHLpjKhFoXNIHlb6nmhd6hf/d283F+vaJI+jyqCCs/eLh5I/4iFYAgG2QM3676Ou5Xwt8PRX3JzH/OWP+q83Nm7YZbf3Vi7rVybt6zCCG9/c2H+jnE8Z+4dz4PmH42C/DXOyXfp0drz/NNq4SVwERLkucP30y4t89ceKEMpHwU0C+AQAXnxGYBzyXhB6S/Xr8MDVHQFmsM6W31nno9IhgU3kSAPJgo4sHevR89CskHOXBLHXt25VbH3cFw3xn+fuw97F+uqIgY59zftLpIBOCcO7Z/0LuqP/g6K8sJ03SAh/KNOMDmba3fnzspBCqMw+FgXgxtEAb1OdJ+eg5zx+EEoEl16U6Mz8NuMhPa0mJuVT8gMUdKVlKSniWRDwnEw6fbJLaqSn/fQ6UUNMsPqPIRttznbJ7qFP2t8wwQoc4LlmU2zz9Oq6Q0SkMDtQamgrqogYGGhNfcqSKCpS5YHhZkxSqDwDc6dzIvKFOJUJH6HMAtQT51eq8mD93X6M3XS96Z+2Kp7CXa3+2/1iGmPXf0dIYlHOnvt2HXFs7sf7Punc7Rgt9/+xj3M0b1/OYu+pVNTefbADTntHtgKt2tiMhzrrtHreea9vkb54VQsVjYcgI9mzDzhlEXDYDJRr8vs/rrlGmC+/hoe+ppxSg2PhW8NlNQOh+ld0v0pPNFWQG7P94G5RGIWUNJXl3haDEqXb1dW8U8Nyx1wWl+wTLPkOpK1TzH+3TNOY5DMO7M9ep/LqXyPSjGrfd57sG6rE6EYBCqplcgrArvjaqIGLPhhyMdwBrKwI4MGwy1dF7sKQgExAUTJsVVBg9lEaApvmhPVWFpUfatR4YRiFTba0U9tGE5W80OKXJdigBYwLCcqyY615Qc1cY9aX/Mi73goOioFUUMmgTapuQEkQOYWD3hpaFVAsgMwhf19ip3BTxrDluXU8CMwBco3GYiTPcF+EPxv1SycPEN7ZMa4cRS2HjKVdE86IaDPdyvvNgwqNM+tc7gMgXOblXDxXsec/ciByzE/F0/I7ISahMxUAjlvqZ5BaRphJfwHmQGf+i5csctqEJ0WZaAS81SM6iRfZcf9ITo2pf6h8O1yaBHJ8CHs0WCJi9xXXAVT3twel37TgVqO+HZLlcGsV7MoGGrWvTRrUNeC5kHu2AIK76i3FDgKSNG00n5OEoT5BftW/tN4DSjABB6ChycYZSs/q6L0G2MWKMafIq50nm/tX675+wnSBp/phd9DStlxXRvddwBW/jKNk9DCdLqHgUPINxB8NgVsU3nXFa5I9Y50tfiHudffVepsk1znft8rOdR8IiCO5T/Kzj953eDcGM7lWwsonVe/fsDAMH86wOW9LyYCCrXMXbwbZpkeO8Vh5CjKV5OJDiKRVKyCVAP8326Wv+73qn5qtO6npAmPUKuebFxT6L7xOH3ZhdEFaPJMpA8MEmvchSq/U4KJBb+dUy7cao6g+C3tfTdMZyxOOgd7wgEqOoJfn08qIGfw0WydwgQ6eOepgNEGk6nEw6Ho9FjutyThYMnmDI6eAWj1Z1PYQrYXpsZgmWvZst1LSLRn1lmHA/HMMCapgltVujXrL+lFKj9shlqQUK5y0xjqHBYWhyP5AXFo8UiYjGb8uZoA38W4Iogz5qa4WSTO0PxUGH1ghYSzLM4ExB0WrWt4VEgerqhvj0bABY3Phrpnmwwtb/uY9mALdq/70pj3/uUHgSda7xpk4ZaCUQVE5RXnMxBUI0KKf6J6Trc2HCyFEatMUppuL65URgwnzCfZsx10Whs1knfwUQEKgVsjm5TYRyK5j/XbooZRxCWZUEVYG4L5rrgVD3Peo262MLwb2jIC4ru7YxtgPFgjjT8a7VfRuW/o2/Abs82632mBYI7Cbyfc9hLV9ZEo/MRe++MKm9i6dsSSEqdlmET/ij/6+WHAv1PLG+Bgvec0w0hsroff0mFnMXCtzmCdi/grkTPlbjwc+tB/ECqQAe60OeRzCO9CYQJPwvwG30ruLNVsv8lixEsa08548TSK2bcYEp0t/JvTSzf+YJaVfC9WiR8Sy2dhsVJTELwISrK40ScdMt9zTnTmofASUp0t/IMZL5n67onyPonln/aGC8dz5eSZX/V8jnj+Rp74LMwxl+s7JHVP8q3KgHTiQYawX9k+sGVTW4kxdJzaNLPtK2TeYDfwQTvbb3MQBvzmNXSGVdkz+jIl+iW3KtYcnxPhms2gxvrQjoRrkze6eZ6f/pV/uvjGLGzeaCj40Zkw4I00+seEQjEJbpORrcRw8L0GkNoArUwTkwdchM71aHo3+k4YXk5qUBh3WH2dtGNFYlR5zl5XikdkEgYgAh8KN2LfDCISOPK02i0jrjhhdOZTJCKUJ4DaqBXjpoPV6ShHFTrUdJeldZARgvVeVYBBqmSg9AjLeVeueEBQ+fZQ8C3JhpFp9bNNwJAnoF266F0izsMdKMRIgtFbAYIsuNJtKr1bQh4TkCy6tyZd7YygHUm074j3y+ueOXZ3lmzklWK63M0GvjUceu82SMZfukuCv/VOKfevmDb/ut1er51AZ6ToOfaBJ9POrd87yklZAhn7OHrJVRN21b6WMeVu2gOzBP2cDjg+uYat9c3EAhqbXg5nXB6ecZpnnE6vWBZFix1Ma9kF1hte3LJnqC3+nVJHX8y7f+u1scNu33suVgBeEwKhqbiwEv2+nNYb8pQqHJcPc6h4djNk42YUEhTAVQGgKaGP0zAAtDBvdQpeU02gNi8UAWCRQ25COo5bgZV6/3fsBjYXiksARB5+gRGQ4EqWk3ZapE6pKnCvFYApaI2hlRSz2sCqGo0hEYtwu6WGzWOKn80SCndRY4I82kGXtTgCkU36iiaUPMUNTATtCfAIsijXBOWl0RfCIADunqYGG6RoLwto1Y1hOn3XdjKHRf6/WF+KG4QEN6PzGR5fTUKYE/Oa18Vy/meFDcq1O3Qw+GY0m6GX8yIwXP5wp6Xe0Z9aL2eTCIEL95UeR70V9rL4iJw9P7EiEfBt/vHa8j+F9s/qz2T/yZ669JMPT7bbAooTwfUXQnsPSNOiHKrT0F3rSm9HKb8fNEw7pI8e93YiOiTxUvpg1Ulmin86Q6AoInmOF+HWc+4KOZkR2i/OYP+mxBiIMY9Gh70t+zRpNsygLEz7/ZYIw+7dXiIdn3rAdJUKe6hprP3ee5PA1B//R3l3x/A9r6/EGjoG1uiH6WbltBFm3GfphkpqPTEeZENb4WArwo19G/Ew7GqcpfIIpRsWqWxXQcrLut1I1YixUvuiNNluwmKncPB0nkyXRujF9Y0gp2/XcImXW5aaXqg8zMmivgnJB451evvcKqUCRPX3kdRPqk2oBCjTAwWQbN8BlOJT3uP7BvA4KgoDvbHMUNEOE6HSH9zmFQBOpnhca0LjqWAXXlP2tcwhyRXojOEWiiDaX1C7PxqJE8COQ9TBPJsRjGWBiahc8UWiRirtYf6X6+DP6kYFUOVZBsh4sKj8W59p5WOu/zG7ltwL/TaGtgiAdCixgoePr0woxRNW8Ssyu3aGupSMZVi4dVVCc5cIMK4urrSM/psZ+akc++Kel97x53TVDBNEw5TwaGUvnpNUOERYwVLq5iXirkuWEQjPlWxnOdhTMGgZIitTTmOH0fvUxMGeRhO76p8CT19vtb31PBFrQgGeOBzQfnebn3bWp1qydKXgH4GZ9f93YVTew3+KP8z5YcC/R9Y1sBkJOw0V1mEGoER/5K8z1sHzll5riBcEffPooj2EWo9my1D74TA6F5Ii3KbnfmCC3zXvfMeXoACBsGOf/eW//n50vOsrAHt2Mv31t89omCh7SQpK2gQNO8VFyZr6JcaoYh6vrMk3EoEdiccEUzc5xZJmGpdzyAo9vx8PubWc77tY5/Xilvl/zMw0t5ZPHfn713OjOfsML8tQ/z1yrkBZFi1Hct3T9t2EaH7J+65izzPPxfanq/pr1O+X48O8kprg0zH2YnufbV9nVfXNNwNDyr3is50g+GNgckLbXDarzL2JffPhQKB30Cd04GHK+3j4p+o18nDYPWV1NY4KSt8LP2637L3LJz7HqPltW2uyef52IVPaUaxui7XHMyzjtHytE2qfCmTCtqXT0+mGBaADyZFoRhHphdaVYUwEaEcJhAnxbh75dsQW+2CKECFSCwtep5DQuZ2+mTksLY0jpeG12yu+httaWhNc7VP5QD3oASA1ioOV0cU86hdTjMEgraogSFRz79eiirOiYBlMfGvCw2NNiWaYg+JCalaq2i1YVlmtKdOr2p4bVUyltsumIGkvIorY1M3UKi0rMAa7fzq1zJcXY5b+znp59b9lvdqYfOBq6hqRIACCeXutk/vhWJ05ncXtG/nwaHFGgtcJhzaf6uar/3x+oj23Pdxz4Hec6F3H04PZckRXp6GOrtSK4IJP+evCfODckjuyTaFhzvQ/cG7jlBHpMazo3GBCV7TKqzXx++t/xEAKmxwmjAb09ZaxVIXzK0OwsH+ZS+ejmC7Wtu+7O8S2fTzPeXS7y6hgs5+S+/gOjaumvv1gfJjM0VLAPBIluDMjjmTqps01ZqueHifM0MIYBIcyhFgsX0zachSJvVit9ChGj3N2+qRFTQ6WIOQ8pcsqpJ1fA2obppRUKUHbQ24Jq55sCCxQlY/RRukwWPRRPvUiFSZJw0QRmsKq4UEOAKyWJ5hIpTDAbTMKLcMqQXUjA6ghpflBa0A0/UEbjWU7iICLoyrDwUecl5q1ZDyJwEddd75aKF+Z8WD01GNCmrLSuiS+HfBNF2BC+Ppv4+Ybs2T250NgvdlC5Xr/Wl2igROp4A01y5Bzx4JoUyHDovI8AVJ4CmXbvSIPekcOX1ErB6RAz/OgQcJ7tVIJi7oUKXcT1gensHmcd7oBRBBg4dwPwb+0LoY/IFQ/9AILcVT6zg9Zm2xXNlcPg9K9DNH5c3iWDDOik7Tpq7yS0H7rWH57Q8ANzF/wNqz+729MOU50MPrI1NvEvfXsFCV6J+g+8C8YHcEAwL0UOtxb18q1jyftVi47xC1CBoeUXAPgFDxB0CWA12gdFmqn878jfbSpJG4GYfY6e6v+On33wKg/vd3zU2Px8CUYu84j+LfHf+fX3RO/3WP9t8/QiN17JUAACAASURBVAHoZOm1ffuyWbYv5xVv2ljpEUBl7edp4DtSq7H3aLWV8kXH1UQCJl+h8U2v5wCVnwo05cQCNU3yFAR99mD8Vqoftgn8pJDTCxRtEokZfOR86Z3odwX7Whk+7IkYXqcTZP2idhAOD7LCy8taHBBtOMxihcXNZIju8T0xD3xJM3i6zAswLwBII2xB904TUjsrAMtSNec1l+7R7nRJ8J8CI/H1WlRW68+ZNUrIcToARLi6ubEqWn+nFExT6aG/HS6XguV0MjslrbOG4VqmrEiVq2leytSwvAiu729BpF7NM59Q/dz7PqUJEzOKRyKRNMbwdt/CvgG+YoxEV0BBv75V9nf/9pSur9dsdzf2OM91hIy8NjTW0OgVmqrDYSOIUMqEUgCRCcuyRIO1VdRa+z1raZomTNOEZZlAnILWB5rrXuP+TxX3DA/l06SpI6Go8cJcF/NAr2gQNF+akJ8kDs2O7ybaw2qeR8MPX9c84+dx3Dk6ebte58y+6ZWn63a6f/xrWHevT1lW0qHn/v4d+719lp+vjZmU7JKUYmOn9OP8p5VMl/4of175oUD/M8pbB++CM/EWHlvjG0qH3vNyFLOoq9Usq9wCHS2QToBzZsjSvXD81wcBPpLmOPfBfSIlsD8I8BBJo4AMGje05g4T9NY0jEP8CoDkbBWvI6FLCiUaRuBB1MSY6ZGYkQFT6Nvqga5K9BAWJGbaSNgB+UTelK8A6DVkXQfcmZFwgYtahPc8kz0nTUewnTg4j3LJ3gtB1t8UR7w97X8iBv5RvrB0xlHLl2zSr70P9kjQv+Nee40c/lFeK+vQ7W+VrS55ZOT1lqt0tvTHVv27vlrl1jMPY721fnt/rw4Kb2NeidWrN3IB0krRv/JI9+64QCnpmLXaNFa7kYbQBVAw4RPuCfLYaRrBePq64BsADta2pmMhs/XfjreLqQmes1jHxuaZBrNWd+Z6Oh5CiSythSK8y7nGcbXawEWFQO7pQwSjCfsI6my+U05qtG4tH57hLrkJIU3aHFavy3GcbnCxnn9BcKVC76fK5CdVMthH7hFPq/EQNO9581y25tFXmKNvYgai8UGeb7vWkO2I0Lq1LgOEL9A8ta5QJ2aUMqW9KZaP3WiyTwK6AfCUhAyjPGvbnZ3rs2Xz4jmRyHiu8j7do7v1XsE2yO65TrxCzVH31Fi3xaGoPy8S2QERX1AEcM/f4G9cWJxC/Jq6XKR7iO9nWtenTn/3LMzacxWTddq3ie7lRt7utnf9dzNjDXJuATTUNtLQLqQaVtkIaFeMO63eCitPZ3S6esFI8AtEEi3sjXpFzQ99WI9jv1D67070qQulU+v26JVn7y6X9GHvEIls+j/2RZUhjI586IogL2ZsZvw5EVTRO6PnPHecSWQpK9QLGvZ+8E2cYSRsKySliMBglIQBvYiYwLyr292wphviqFK8mUK986EzIIwDTdF3MgV+50speMLWHHerErq2qrmpQ6GhCpFinnuuhGAuOM2zGv+LOgEUUsMYauocoH2ysLjVFBoeqlOSMNrmek0LaN0aIp+YILWFAdfzx0cwqQLFc98SaZheV5ajmeKdCVI7XPG1HlOmoN9jP1F6biWMsfo7BFcmSRi8EUyhIw1hSDhuyA6DHSRkRVGm9bxfBiz6XBmsEveKtXaFFd8CyWNXx9A90U1RTJ06yHQJU4KDlE0weun7cbwe+msjIgjkt4ZumPQEFz+9hvf6qGzOUksk1wAIQk92102ZboZxV/P4ji9DOZnWFr4jti4fHinCFetr+5yBHN0bAwEkd8NItCUN5b5+NxcGwPL/s/em23HkxrroFwFkFamhu21vr3XO+z/dvdvbdrekJlmZQJwfEQEEcigWJUrd8ha0qKrKATNiHt5C6JNtwXcQ+thCUI8dkbaW3g9C9y4XdE/0vnbaBzcIO4XxNOU7KWwq//oAQffQj/vna5STTXTMb+5n5cioGPA1fq72/gAb7N57zX8XABMIS9slLdZE94jx/9t572sQuBjzUO87QeE9N7qgUzzU37M1WO/Pce5jCiIKBzAo6cMEkfR+xTO2fwb9Xn/SPfT9/CcAJNIxFbN6D9dOrzro8sio41jJlOcO47oCUwxXemPd8Fsa7wN7lmjlIOQbqN03z22nrRzetse0TykxSqkgsrQcu/NCKE+C6eyRBPT5fE6Qi6C4lW6YyESp032rfeezsddWCc8oDerzSLvwOTTZyv7q3l4GA2S0rbR5hgCNEgagVICSIBEBmDSli1RkoHmYN17P9kopBQstiKIDN4TzvxalpVt667aPYx8U16o8R7WUYSJY3PO8LmowoYhb6yGySECbSnEN6m0d6bRznbc4OmGy2Qdfv7x2K84RhVGumliPbTPWlav5CA2Pi4HPTr+9sOc/yn9G+aFA/w8qTUkefu8R2WzIYY+hroJm9czUGWmxe5FY+xh4jd5GByW/OfGEnsulSAw7Zr9HnNTHgz3ARKs7ZIT7l4EwZ9C9/WSWj97GkSDpqKyf1bWwWoRAWUUTpRriXUFtF2qoYKsLHlwZHS30vG9etw8iCppRP39+JDDsI7IJBHaTPjTq24wyzOb4iGO9oVD49mUk2R9fxl177bnjCA29pu9gNr6DLl4vR/O//m7wI0qCboIYX2uCIin4JyifmfNcywtI/APhxB9fvm2PDlt7YTdcjBGFZb2atUhl9a65ZxAAzVMXCAh/pwmVgcHqr1U9CoAaxjHGkiQKI7adiKFxB9xFnmN2PCNHjFhDc/5Vem/orXZAHtbnLVIQnntboGS3Mvir2YALmIgIdA7CsRZiTr3KpFYIJx1H6s15qPFaa59KEc05K7WFKIdI87Quy4J8OgHURbxlXoCV98NQqgBJvfiahLFNjit51Iscido9DV0r43tG26xpB4CQckaSDBdC1FI1DN80AQIsTxeAgGVZzPhTx8oWl1FqbXnJSxmVwU53uScHldIU7L7ny6cSRG5Aeqs5GWM6A99HzQhVqobRtxflQVBRNHP3hjDszHj42D7UO737RBTHPXfII6m5j93Uo/QI6o6n5UgEt1fzXs5ZD267fXxo//qwdy6Mvfd2dXUtrPodh3YI8uCmrT1X/bZ2h4jGz2CxrnGjwaNSPnINqlw3r3IhEHHLPX8ktJH2qe9KuLrmgvzeUAcBRSpKWTAvF1wuJxMIWhbWlMA5IZeMBZpbuQblSO/Hvv/oiA9uKRsscXD1ln1+XOtzLe49/9nU0gte6rlC1SPV/Y7rk44rnxNyysjNC5rA96o8h/HtmGER5KhFkYuRwICexsOV6h1fWp5qVpxsZiJIkhr+ZepRDzwKBYvl327PqWBevckVDyTO6oUV8BSR9lWLhqFXxTo5qmjnBQSAFWZX0dyhahBlUUSIkE4nVABv3t1jmWf1HqukIU8pAaSK97Ko8YsbTfHEkFkgi4AmdEWJaejYPBoVpZFGajC84EL3WgvSnXoUNm81VlwlDwI5Cygp9MjTSRXoU26Kk+VphkhFKaVHRWFX+NcVDojGNV0Z1fTZ7uXm+8q8F9kM4FJOEAjKokp1+VgCLOmUiG/d8nFBsoS6zpuOqSaekHDX8LuX9IuGuy+/VlQz+PEdHutS3+FHJKu34AD/HJD5FP5iiXDK4V/FQ4P186pCDjXQ6nNdBvhHD75LQ1/fNDrQ6QGSn0DQnMheuSquxdp/C8HHYW61/m2ftmPb62MYj+iucc9zwdu2zgkMlneo9HGoK47nXH9BoQLIT712+QkkjJn/3UOvh46Vup3HPfpC8AmEd37EIQCmv7zH8q8P2vbff+75iIlQ//oe9V8fMEGV6GoOcX0uvqRcSDCBMDd6G5hBOIvCuJaCQ2yPsj+3v3vWu6z/v0fxI1BBYufDY+FoU0VEo3ewq4HDTu6kZotsMnAh1ke15aGgk9MvXd3mivqIY6/LPde0Rrsm6/Xff8vTKbnjzZqgYIOPpShcP0+a43yMzAFApEXVGtvRyWkepWa42EOl2wwYrmqK7kEmK4ZnxyhqMb815kuLECPBYHSQj0L5gwSNOLLMs6ZRRUUSBifCxQx2PYpFZo3jIOIh5Qm1EpbLgiqqeGfOYFqa4ViFIBv+0vzahGKGbqcp4zKXtu84Z+MbFyCsvZcZwIROOzsmfyNq/v1E25UlX78DwLrlAbZlMCwboH/fUY5XhXQ92VLAlAL7XMBIqBKisJhxIrNGNqvF0otK34sAkLLy1hqtrTYDw94/aufO5dzaHoDESLUqeyvUBuO6cSJGSgbPEkNsD1ffc1Y/Hc7OOJdHT0QYvPfMtXt7z+5fvw0aez87HOytxz48V5vKRmIE4/E9Dr8ZlgkCev41YGGHbX7GSMhkB+hRmasMllOHbPcfXH54ov+x5YcC/Q8o1wDeSwttvq8ZhvAUWa5ID7PaOiRwa3Tn0HqIVfteAhAxAagTSm9rB0qfQrVdHnqIJgc2cV2+F5DglobRMrGTd86sd3Ga5+xaGhKguETtDzBEUd1q3zxJ6hahr2erefy0etC5788bpLViPi5NUUVInEwoh7aP1h7y3sWIwKghNTIr7hX1vPr2Z8BhnfD7kt6MbMUoSLil3u/lZPxvLXsihaOyJ0b6snLErB6VFbtt4QN736sT/ldywkn8QttWX3OEtxL9X9ZGh+XfU3mp57kX03VHVNTvuYilPXRQh1W09g520UwT1Lh2deCqXOIS2Kww93EZmt61moDCaAwXDO16YQV8Bb9FyszGI7gd+4pO8qdan6lP3hsCPeyxlNtJo1hdYCudcVbleacryPra0+7QEJrew7GrpMO9oPVe4gQQIVOCVPU8J06NthPzmI6hx6WUXcjUvS6M+eU0ePSB0HLqqpBLNI85B6IGPncS9ltXqEQyQD3kMNCbxRTdMa+gCzGaIsmFTUuBQEKoRozPg+DS64GeIgLEvYn1Ot+boOOhtv3VBatOO4vmvb6z3LYGT+u6/pvLrfDn9eCU9vLI8/zL2jnCjF8Hno+YwqmtiO/iaPieIEKoj9GLPDUldy97GLZHZnD7EG8ghvNV1WQFkBs8fW4OuqjJM4CqaD16CR3iW2t/LgVPlxlTflLhoJ1bz7nonr4CafDD24vK8826HezpLxXo3EI5fWndz17/GkKptXID0pQHbjiVmFGfBOkugROZwFUVrikl8Fm90lNSZTaRxYVxmIT1/IfZFGnPUlLBckLw9CQCUUIyjF0M6BK5MbTuCIYKrTtv6+CczTjDVTLdg5pJ886S05iQFtkMk6bfgMQzguYNrlOnXobTaWqpRWTpaTOYCVJJDcVIw/Y2QxEy+mNFEvCEFlmt1q6iq8UN1gXzslhEFxkEtw7ya1U+nalTORuJqwDplFHmAk4dV5Eb0B9uF/fjHnl9tadwFZvRBxZZo3HqIhBRwQ2/TygfSlsvXYV4rjt95GTZegcNCuT3hPKbgN8rbqf3DPpAqHDlzBoqEVhUiT4egDV8Pi5rqOsKqlGU7q1b2Jc+kWEkjVS5WnwEtL4qAuA+RJAQFDF/YfK90DFNlbcg82ZhYQipJ3aLTeL07Kqt6A29OxfSFazrlz33OeGtjaM/S0RYVrDtvv5iz/c0JV4tk4BFvdH3yoIeNSDO63r+JHjnC4BP//qARCqEdgMZj5xU/vkBpZNmX53fA9zYYoTOlnH6mTe3e33/mfE3rV4T+HYSSxmjb/kpzwSLXGM1uMEUNSjQPf69clO8O2slpLLAnmICbR86/1HtYWdrurHNagxD/8dVX8/GuH57FMtqHkK7CHC1y5R3qtIBwEPSOyQQKC4QQMk0O4sCGB4ymo3GXgnEQmi78XM39CLxSK59d0dexAfhOtFalR8SqLFvShq5SupieE2gNs9afw4OXE4nJvdWhoUNhy0q1NCgQiO6uKw3phSZ5xmnSSNlTZYD3PkpJqxXdpjYBXpGHSv7s2nzzqoGQlsLrfGatL/P+rYfu7XDoyTFN3Xqq+YcN4V6JTgDZv3q+FmNzArcQa3XNYFTsrS2/T01PnTrGXtWuvG0GiBZNCfbq274ANieqSGalNHc7Uyawfc2BcgLi/f5+IHrUG1Fk1w/sdfL8bsS/kcwaHm++PwMmD/Ki2D0qJ0/N9pSfh+GpysSeIQfofVxv/a9Njz+7Bh/lP/k8kOB/h0WoxPQmIV2csWYOmnQwxlLDffGirjNmq6KWlctpWgINX/H7gcdujKHifF+qZil4jdtDj9b2wuA32nLmDS/CCdqgrDyiDnAlevb+y9DNC2MJPXfw6f1LbEjTxgTZG0NCgLuRIJbjIV6GtNJ6gUiIsiWI0URKzeYzSYkySlhShkJWvdSCuZScLnMKMvSEG5H6gDAfa0cPzxH87+gdA8CtPETASll5JRauEC3yBSpLWQkM5sVWA9l2fTpZl3IBIh5AETq2L0PCBau9vWGdMDi0PHNvedeWH8vW3+efqczTvts/jdE01804S95+c9IflxngreeEkfjfW5cr7irm4Bvxa7uDmV7UUiapbbnuvIzy8KoVMFyxZVcpJ9tjARte8SbP7h/XMY9MrJNAf5u7t9Y+05fvkx5/prQ6vm2vLXD1TnojuKfzsh0XwS/7xFj7IKMMLy17NwKgCi8J5N4iDcmjjvRn41CpBuVFmJtxhyUDTc3xj0gRTguHqUvXfGwKrbdXKDle0zElFimKHPBfBvEILcN1ynu/J7T0XsBMt/Uc+gC9XlWL7goPAOk1uaB7Th6Op9VIc5deSwiLWdfPmnOcFW+qPe5Cs0EWBZI6T6SXWwU8D4TpEI9GEFAmA//cGVEygyxpJvE1LZIYgrOc10ATk6/VukJNIUAzw9IZCEstT8u+Ojzxfa7wyGQpsiZPxRM77one39PethHcuNSuyMGE+1ElMcKfpsxvfd86dT2XVPGA+B77WOttVm2L5jH9Vttum5Y2J8Yyo2w6KXYpu/Bsnu91UerO2F+1zWvBRnNKxbAECexvVUP+95P8f74ZdOv9XN6BjnAAAawPKkH6d27OxBpvkwAkEdVbHlO9AWzCVuLvZ9bT4x6te+W63gluCJTUA+8DnGImDXyI88VfcsPD2/uxF/EajSjRjIFZZ7x+8MDUk6qpHV6gQnZhKvEyqvUQiiSsMjS1q8L9fYp4AF236x8jrN5fLdf8L7cUrdsvu32++B6f2MU9I1Xt78HfHmlMLN6TwEWchSQWeWvOSVgIfCk/OL5dEbKGac8YZomXcPihvC2K8QxOKFmQSkLSlHPqFoF9bFCWOFUtlDAYmnbKutnytzyr4toIgP1ABQwLeYOmrCgKH6gqvKCScBJ2+Ws6h/iTkcS1AOywfBMKImQEwFZI61VEZTqNKyem1oZRNXCqQvqPGs/OaGyKiJEUjtntRQstYBJc92qkUjGPC/giZpygR0fsRop5GnCLG44pnOn+cMLypMlUbhTWqFW49HYlc2iDtahlLIYznO8qHiwlAWAKVoMz3laNkoWYhaGywioNeReRTQMpNXRMRrYZAq1CEqZsfxWkH/KSm+YAsBpZfV9VBmH59pVWu2x0Ve8OpcVyqNPnFHf61q5hy79JCi/AoSKCx40mzq90Wpr5yeGPNgH5Nf6gO9BCRJBqQsqqTwl0RtLtHGndB51j/OOrrbYZOS5AeAeFb/vct9J3qLyRxuAy7AqKlWL7kAA98g9AmCShIUW3W+FkHBSfF8/gPAGFb9fhWcDfdWmZyX3CoQhCZDwFhf6CMgnEN6CQbjQR2RRL/BEHxDNMmb+Nyb8rLiRPoDlLRb6hMmfRwLwFpU+Ge1LJt/R92sdlehxzgUjpnL42HgW6Q4e8//3P7ov0tbD2msjo7s/v1Cfz83E0/CxEEBCmEQwE+Fk8142O6PTsHtXgU4b99QWQExEXwlI1XgSi+GfQHbeKhjAXJVeTsmifOSMbJFIRhmZmDyg2NwS8ukEooR5WTSc9DJjKYsazAW6V+lwQq3FFL9GrQQFbhuf0cF+nnXvRc9rkx8wmpMMWd8cxnh347x7UXgJpKlH6yKEVAGBD3XlabJ0G/p+Ubyw9ITmfcndYFj7p2mfGMTSxqkG1hXVU3E0ZbqW02lCcZ6JlK8qpeDx6bGl2EopKf6ttctSje6qFZYuhJFIcCbzsAdaCgwx+M5DxBlLv1N1iqcpo17U9KXJgcT5PODN+QxKZDg+QRbdR4tF5UopodTSD7C1STYPs4jFJ1HTWoamYLgTpV+iJ3qjdZmQLDxaW2tRHBJTPUTqyiPKxeipgcSx385PUHsuke5/FmpGoWT4UGXU2nwtBahK9zAxhFTJLlUCrUsg6hFbUk6YoMbpZSkotbaUR65jadNmNMx8eQKqIOektFrKekY5gamilIplWfA0zxohSnSg6k2v9z1qgM+BGshp39vx8nZNHuGTtdaKbKHl8f096j4ezzXdC6ClYVnLb9bPbynpbTvXNDrdYaL/bpyd0MD++d6okGaYBYgjVBjmBirMGNGcCXzv1ap6idVgu3Pp6vNKv792Wcsqf3ikf5vyQ4H+R5YXnDsKzykCDaQZBTrMlJCq+FUAzyYQ4uSewvpurYJSy5BX24n1CBhJutX6BwbuPKkMlPB1hDr2d2RRtt+PJQzPTceX2Gb9Qkp8fWgIOjC4ALrlnitkQh6inWY7QUyDUNwFIkzcrP38XhGzVneBAsFCy6j3Qc4ZVLtQpCwLalkaMQlgqM+H0fjodScF+BLg3gwDBoROSEn7ClOol1KasEbE8rCyzyICMYiRQV4R5YojA2L87J4fjSeMK16n1V74zHLr/pTQl6Pv2ze+bXnZ7NPOt1vfee6NP5ogeO1d+HVKVAz1EhiR/mBnKIMFuxO4+7N9fQ4aTLINHI2NNjW90llrLTs8H+UfN5dolfw9FiLCJFeGcHB9fbnvHxot00VA9AYHvggmPOnMidvrN48sq6O/uO0QHV3fUZoo0xgat6vO8Adux++YAOvGXALDMdon1Jw6cI/s5uV2L8CDMXMyvt1yZzrdYBWxqPLcBSy15TH3YI2yf6ZGtImeB7XPmV9LhqtdoVdLUe89AO5x0uulRleCYohFVz4HYwTD/74zCCa4afWI1dHPvEBjf2rk9t42EamgR6pFwjCjnqD0Vma9w7RI3nhOWM8922gsAPPHBfmdKShcEd+M9NAEIJHtb7vnjoBHaHjlHNimRmuThoincP3RvBAC0+816+cVL4BX5slvwa57Z3pbyyDJgu6DLR3VeJRhHIxNrSF/E23vvkqJ54ED7CKYEot9j8hqEgIcQZyjOKgxedQG60ZBYHtmCLw7vniwUHtCq2h4QBsOrIOuGHK6SAEvavjq51ZzbqoklpjBFRDufEVrl0IOyHVbXyywiSfjtcr6HB8/df2qQ/rr7w37N/CTe3XHPTEYfRHUxoSVF0wlYTpnnM8n3J3vcDqfcDqdkfOkfCJBQ5Nz47AgQhqyf54xX2ZcZv1N9wRcGOkuQS4wj22PNlCAihZ6HaIGz7UWLFXAVFBFA3Dr/pW27wQSjKwrygIQV8tR7nhIed4qBhtqaUb5RQTZwYAJ2WXgzW0zqsZbPbqYUcUDgQO1MpalexVVCDgz6kwWRZUAUU8/V1CICFJOLaUdM1uaD/ckVMMtPtEQwhkwQzoD61IFuAC41z47fpdAoAjIlDC+PQhCpkxynAcz5rJ85s1wrxWnzlf0l48PrlDwqWKAaktPB9L1Su8J9YOtnziNptXrOT5B8BSqP4OMCnHjBh+DKwVFBKjdeJegU3LCWMhCuQ+nPRgdHcHSOBPuCakhhVU+ZQuhMTMCDRoJYk9JOOKrQF8BINzDFerbnuj4VDn/ANQ3cF6J4TSQzWZQKBVabL4eIHiDBR/A8gagdyjyYeiP98QjQhyRAYQx37g/l+Ut1sWNA+7kXQudn6Dh3Lsp1luQMApplIJCvxst1ygjJOQ2n53e287SCm20PiD0mfEOM31EEiD99X2DRflvGj6e/v2h9bWGyooYxv1iXu3ofTq4TQCFs3Jzvfu0UeOwI/Fqp0dI96ooVAaBWtRKiCmjOSFlc7rJ+semRPRdiGqeuAKIECZToDOzGkMFmpo81jH0WSFdqdr6q/0cjdQdb2G45vBPNdOGO2vfA/pMDfXaNek8o5cWtcw2W8fEsktzNINWU2qXoqHOhTTqVsyBrWOtyCmr8lgvoJ0YhyM6IK3fDa/g7Cx1ns2e46QGiqUWSAUu88XWE6BK5kneo8oIxPgsMm/l7i+rqbjG/S7WTyJCsXRRBA1v/3SZ0YwJpDt8cWInNlSRb/ii+DiIdB5MxrxHi1+g4dy9Dxf4Wd4vBDZDNTMvdaDV5vl6cdyy97jDcTecU9ynSvMYdddpcMfZUoFCGsm14S8X3JPSGk5f6Ptq1JbYjAxZ57QGZe3g0S6A1BJSilmKAlbDRHeeW6oaJi7LgqUsWAxfq9d7T30aKAbjt3VfKu5ePXGFPr8yy/g6XNfnlS/R7QjM7ojGESUazZpWIFfhSbsY5sN0Xx5ZJpa1Er3V/wwf96P8Z5UfCvTvuPgZjcaY8dwyugUu2XPRWz1ClSPA1b11tJ5fBPgfAt4L8CEQ0Z+2MKbV655FBA9X1zMfroXi/rnHMPTvnch6KbiNIWj2Cjcvpt5Og4mD0mdFGKPzuykg0yK1KdAJagGfjPvoYmBs6tUQW8rs11qfpzecxlpzNfhy9DgoQbSjwcDg2ovStln3XUEj3K8h+75rfea+t7KPSf1qFLv66JwRv6WeP19ZUxh/TC++vOx3nDbCrJfUd7TPv+YkPUcYy47ivIuR1oKRSpY9lkTzYbpn0TWP9INefX45HlO3hP+jmYFvs/FjqHZGF5Idldt7tYVX+3h9vC6/Cujnjr86r9dxZuM5QC59WOE1r/Fojdf0QsTHoyCn/fY+GP/e8Ioz511ze9xyk5h0Iel6AprQmlQARW8E8uj1dnMCODNn3msMAp+pjcaFSE6HsHmrKCIlcLY8jUIbMwAAIABJREFUexZO1wV67klBk97PNGG+aB5OYkI+n8CJMT9ewKdJz3SxUHPQscVZLZaLL1toTRizLqU2IUFTTJIg5YxSpUUaGtYAISysuZ63KD8OR0xBoQqWKEDzdXSFhkcD6vVTeK7L0kvbXwJBemNGA58q6A1hyhnzZVaFu3sSuBdP3Ejvbdwi4Pfqqdjm23L1DrRM4M4JwIxL6OgaqvpT29JoglcCJ+vWfPs+W/1GUE39o1kvrOlz+4/7FfI9vOpPr0+u5r+9GYPaBYkDDnNv+nKY328j3OtDBd93mlbajvXvdi52fM/2itN3GSP962U9Ey+hcCPo6SIf93oM+FgEpRQTyGkeTK4LEs+4uIeOnxHfz9DPItd5js+lhq6XF2Cp9TrfXOdz9PS6wusNrGt77kz57oqqKa+nQo3WKgE5ATwxppxxN93hzXSPu9Md7t7e43S+w+mUkafcPMQ7HKrmXbg0g3kQUGrSHJ1ny5F9R2BL6QFSXCBVNOmpABDNP74IwFIULpuXuExmHCQAnXz/hTgsJObNJ4B0Hledy6rGcigEJo2Ap9dq4zL97NWqKjQJdajBh/ZVj7bOpIZfrSB7T7OSdE/glFhznGoHTYAOU9hXlEUN1RV8W1h8QssX085nEGwTAaVYbwWgBwHeWnj7ovg5WcSXcpkBESTP/y4aul5sDC38L8xLDhj4Y/kkwBv95HeWggVAnlSEV5eiZ8EMzjT0f0Z9X1E/VNBbmyene5pkw+ZankDQxRRcWtuqwHtCknsAzp8Sln+b5+LPTnkK6gf3LnzECW9We77TV4QYQ8Ph6vPnTOml/lvr0W9q2vGARO9ABKRfEpbf7PrKgMnf1/bdeOAeQg+A/Vbl/L099RD4dgtDLvfNyKKrWnwmqJk2UUOEdkJYFdO1/o5KBcI8yKSaB+mqn3vzsS4kQKFPLWXMHlRKgHmivwXLexTyUO99jmK49gpBRo9KxfLO9s2niP7VCM36JWL0P94C+NT663QBic4jwSIQ/OsD8PdfdO/9S1A8/HwkNdD3wEzASYDLqyCg5yuZSeeHCFhYMAmp13yk/zfV7uAdj2ZEgRpowNFoDVa4WkjPRhZCImAh9U6d3BCJlDfIKeGUM6YpgSmZ4arBYgtjLdBc9QprbD2ZISkrjQBGYY3WUavPMkFTeQiQUlNMAbRLk7ZzORCC1D6JKq4ja0E/L+vrsGg5nm4DjXfTNCIA3Gs7aWqcUj1ap0bxVMqmYMoZnFiVrmQ4ENKUsCprdaMj3XXF5K/eDqz95DAYwGwGirXRW55mU+H44rnNLUpKrmrwAIu86biph4QPcxfmpE+hzldqabwEIDWKc8PQKgIpBSQWYcz6/XTRuTmfTjhPGReLvkTEm2RFXnsMVd/OIhFSSN/aV2ukg/pMjvVeo+vXxfk82Hwi4MzdDpNjOGnvVDfyMrzv9STWKKrMyQxSssEx49oX5aNrrSi1aAoxp9u5p8PVcUpbJF0JTbuWUka21EkQUqNEi0ZLwiCjw140KV9UOkTdW5+9p7HzjP8uMu6Dvirjm0f13Nre0XPXrlcZ75AREgRCge6HKhUt5p4AnGxGnNAT682B4Vbbm8/091uVHx7p36b8UKD/gWXNfD/H2g/3pAt1/GUHgkrsdSadpRP3/m4MdXl0uJqgNsANEuCddAaIvC83WIS+ntDl84HBMA8vrtkFgd3Se+eJ1kJxK3tn0igiKrHQ5h6enIzA8Yp0kt0QvcroISYY+xqV55vlXD/8OcURpFvtBQKvPxIYfscmjngcFx2i4F5GEXq3g/7ei6w+Y3luX/55UPNe+Rar8yJy+2t25DPKHjn49fs4eDasGNvatBX7eamOTqkKPcI5bx6Ef7Y5/1E+p8Qw0+HizpMdmrfd/RvAP3dm0hXPPQWY3zNcImsc6gxx3Lc0dKHpvE1x6ylh+v3wOwgfVOjCTYiwGdfRGCXcCx/S//Mr7VNvEejelOjxPgHuuU1gpDPH4TY6ANKFSeoh170inPlnjctqVvQMqp3mkyo4nU+YLxdVBkCF+ClnVZYERr+3HX8QEqlASdfJ7jIDFq5cBFAZkCv7+9ra7G3qF1sjD8HuN6KAZnzJ2xU11jmgZVRZQq2KpiyxDeNeIgVKk11+u0AApDc2xxZeL+aVD0sGwKMGuUBG09RUde9pxpNqkGAKpm03wzzs0zTfBaVzJEQYzlP779ZKOy6J5SuQPaocMZqL1Fil7CTVcfFS9xbuBrVR4TB2swvP+q/nB9Hwa6Dhr03hAHc3/ehGKgIBFfMkkwIuhIW5CVpbNDLppsICGN8XqXA/Tj2FAtDPcvcUeo6DGvt8BCO+XnluT67vr39fgZlf1Ifu6VebAo1ByUKAnk443Z1xyifcTSdMZw3lzibE97RtRQTLfAFf5oGnKLVgmVWYq+FLgZRzE+6W+aJRO+7Ue688EIACKgKYt6LmBReUR4d71PsuelZKMYHkpQK0IJ24jY1cuC9VhfVUVbFCFeCqXl0Gs5uQvBidkLgxw4pv3IBLQ8UnCEQYtUQcJKuZ7cZO0XhOQGg5RXzum3xlpFmcSU8Wya+Ykp/uqCWjbmHNIyoRsTR5ik8VH6naNz4z0CfWbz9T9ZN+lo9Vc46DOn+NTvMAGlWiFossCHE9JtL7bmCj8MzmhgAxY68Wah8OQwBQhQiZA0T3dNM+12ZgVj90I4gjXMZyh0qPfdzAasWul/hsgirJfdwu6y6/1kEm0sa8o0x32RnkDdBoM3tVAOAeoIcBdjHIZDuMEdPbd+Lht+Bh1REAiVrbOzWsBr296p6nDCDJGwj9jkrPz+Wbv/4VT//zhAQCyXuY3z70JLAqTc2TXSBYcFHvcyjNqhEA3hqOEgh92vRfcezHDudXg3TYFLOti1RUfGj3PdIAVmdpsnZfrkSn1eftxceRLRZ069utrTV5oc9OWKjGQ9tMEFq+clekg1yyqB7M3NI9MqacMOWsyj/O3bisAiJqmlIKMC8abTQRQyxFEoGwUAGL0voF1ZSv5jIurFEqnK5dD85+9PXZx5e02eWRCo4UVfzmxr39VRGHynavSjNy8slzGr0a7NN0kmpAOy8LWLgZXmlKqmqGB9RwSo1GW27p5Ap7G6/UaqGfx7HHuVK+RNoai4bc0n7VgpRV4e/WGGvP/MZXRHozJUtrVTvMt4liZiQRFEYzhmAwJotwQkS4P5/x6eERT/OMu9Nk3vIScN4INo9oMp+jW5RIn0vTRWe2bY3XznE0bB5bd1qpySFIDcVTzpimCTlPKC16QwUtgQaQQAsQDfKSaMhYPRoLqVFDSoycMiglSCXkXJGLRYOonj7hW/N+48p+fdr7+VX7spq17NXv58jJPh8ro+/jhmNXTIrD4k1ThJYC5GvP24/y5yw/FOh/cAln8eUvBXDUaLNw4pm6l4ETrGSEQEMuVwQeboEFAu5F8AmC6S9/wfyPf+BXUkX6x8C07QHHLmgyJlAsBJY0tfLN438N4PvbwfXO9slhI2PId/tNPU+Nh49Rr3HtcW1IHJ1mNoBNjUOjJsjr1C8MgZfBEt/L3qq9hAl9aeke5NTGfWg04UJm90SQgfTeCtl2OuwMShREfmvy4jWKtH97GLiPa0smriHD0ar+0bPyrdq/ZVd/SV/23/2iVGu7bXyNnUztQ4VGogSfoQIiNOWEDNKIz+tHHEE72eQCp5fWefT8jfv9+s+vUP6Y8zY9sw+PenWDXdtuDSudcXiqC3KGwvpS/aAdTT9zo0kc56lUbBSPxHr2QkFvx0Atn5nSNrJ61oQ5xE3Q0a+3H20s67PAIeSsbegm4Osfdo6d1ApzJhIumpK/t+U1EeisgrAW3ccYaLFID+71TaDmLdGYdX/W8ajlfUNi9XRjzbuXAEierF9Gfy2L1sUH825dSZRMSNSFBYDBE+a2nutwqB0WReNOUzBLnywNIy9tHC6oVz04oYcxjHhw9DiInt8tHL7RGi1kou2FhmHfq3cGv+E2ds1Nxz38u3fEx8yqyBHUFoa30c5rq0YA8gjMmFu/x6Mb6PXN1dvKLYKOa/XFez1z+1jvc9DX73MUXvaMBHguVcIBtg3fHa/Yuq+e3PZvH34BMuQGFeeFrILLpwsIhHSXUB8EM2ZUVEyYQFCPUVcux6hBK6hwPJaNYcjRynfY0FiQYAC0V/bb7mHdBSpfJhJNw1VEvTFLjB6hb60jH4n9N8C3gzZ3Q0cSDfll1++tKZCvybu8SqHNFyvXe7yl3jseavNPFFKrqaJ1WTTM7jRNGrZYKhYRLLAUYIsgkQCTCs2ze9SZwXs1vsvLUgrIw/ayIKcEThnT/VkV1Pd3gAjmhwuW5aLw8PeLeV35yqs3XqkVdNL6pZoywQBn9TRjtndKAbAITMsJTprTHE0iYakDsCjOtpypTJq3kk+d/2uh1+fZlOjq6ctmK5WnjLLM6lVIpaObwKvWYu2t8FYpwFIqUkDfnWvrdLujPgFpLnRSL/PlMhtK1BD4adKcqS0MfGbUSzFjeA0f22BIwyPacP0ooLcE+WS8Y1Dm12YcU8FpQlmW1jcAKPOljapWQf3kkWq0lN/cN9nmA90P3VajG4qhw0nH9er93j3Q62/6Nv9ERjsQGPcBZnjEnRUWDHDlljMflZW+c9wEgUBI9BYCQfolof6quLsCKKzznKh7CvbV9G7dtxnRqX4A4X7gZbSP9wDpOwzG6e9nPP3jqePCOBby9x7s3gjxyHKmk3R4PTQmO3KS1Ry0OTaadN5FFW8QEwje/e0OH//5T2S8AYQtepUZRQ1Qqu//FMTEfhpVzV6UlpW3qOax7t3fw/6V1JlH778Byyec//azGVMuaAxDGJeQealb28luPBzOzHPlJZRWLAIRDXnNpP3IApQNg/UMfSc+z4GfaCxANGrTWaqkHvAJSlOdiZBzxpJIczOnjJyyfSpMJ+qKIake9VKAKphFNMe3RbNKTMiFsBTCsizm3V5QqhrkMklLQ1Tcq7oPBUauHJZGwdD2epjZzfwMKU6AFmJ9EqfrVUIoIqCqA1ayvRrOUm9hh59doS1D/bCsS9UNqKDzq5FbuMFlN65dLhaixVJf1MW8kcXRDDkQMV5kZBN87UslJBGNpMIEyjYAPzmm/M6npHScGRtXUaSaUjIDCWm1AgBzwjllPF6eALa0FYl7/nXryJu7U5PjTkSQedmcfgA9lYr3X3p6C6GewvWdAAtg+dCvboiwznv0US9mQxdeOPA6R3zG+2yzIoopiNCiixEBZUdO5cYTKWkKGAQb0qiHd8MLEHXDb3EP96JRCMqiBuUSDI9SAucMqYTFjDZSSlhq7anKvrAczefxPI+mvtdKfIJX1zwlLbDm1aQ9H6awneu4B5z+2Gvvlj6Nv2LN4ar0e1H04qcoETcesb9UIRKYW9+8jce7oaN/cLnVwPlHeVn5oUD/huVo67ZcGocPjN8d+Kxv6nWvTJFFgllpB5JFqgqDxPKcyRGx3pTcqjx3bHL3yy/49dd/46Mxm2+E8PutmqbvANjslUHGfE1xTMFaM8ypGg6M4RWNRe1EsxErbsHmHk615ak7RhcNpq+vxzHcMtDdYRkSpC7I15xx1Cy6OqHRx644xggLQ1yD0CD2dWVpSDDLcqz3+/dbfMRxfW4b158V6X3LVRlEBqvv67JPPP05yvP9+pKeb3Tj3MMBKh/Uz1d/h4bPa/06gjGNQW0KTbxcmf45DMSfdZm/YfmSKVBhBDX6gBD30FjzQFsMLUfvCiDm9qYggRWgeVh6fb2J/T243xdTihm+jftXWj+pCTR2Feeb4UkYx/NlC43GKy1H7B0gl/iWzkmyHMSQqgLMhkejFtL6H/P2uQDOcG/n5VQhvSwLsoWNpZzAhns5J/VIEw0xyDXSHdYzF5YQLK+oWK5wGds2WiUq4ZksWlGrYzVDpjRwQSEYLbRgVMA5GVTHuGtdaW+hgYko0B39WadYo8DEKtD7tUJYLNctWu5b99J3ZYbaLxjG9rCWjcbqxFbfc3qhPqKPEV8BE4UN+hr1XlPQPtdIzGmvX8cz/GX9Cz5LtE1s85J69s51MtVLK0/ShCMMakqFap6un9euf6X967u/+7Wm3/5MwZpxE8FupRPqfkYcBpQgXBz7FQAPOtxzY57nPNEPRxsEj7HeF4+ROu/xGs99aSGoALfBNPIAzyt4Fgg1DuurMtgFixASMeZlRr5c8DRl8JNxRLVgWU4opSIvGdMpQyghTQlUgcwJhRNAGTWbApc5tCGaM5czUsqqRDPPdJxVQTRjRr0rgCzABZDqYXTV862HoNOcnjDQL3MFsgJx5qQGZayhbYlU6ZxTQqWCWllzrC+kysRMyG6IB/VUTykpRCfni1URMF8uEFQkCCgDgODp8gTmBOaKWmm1pwwvRfqD3cnA+t8QISClquGUrZ3TR7r3AZeyCkiVG04TCQa86LnBa+20iojin27A0qgFgAjpnaB+7IpuV7a70aCIoH6owPu5/fZr/N7xnGjYd+v13tbvHniEpuhenWd4flh/52MF3jP4J4Z86NyAfqeWu1kMjtJq5/scOkR3b/+hh8/Auz4qfZbR8XyXo3TF30AD2jsEgEVA5KHmw5oRgfBodJAp14kAPIIsdHv+Off2Vv3SvNGfhnojFK3waDbcZH7s8pBRa9SvHcyBp2+a6dMhJnGaWAB8+uc/wzivpU1hCEpTnhcsSMh9z0C91X1zsLzrSvQrwNztS/Wxt+0MlH8UpL+m9pxX4dX0kOl65QQcGAzcUm6goXZvdHlXj3y1xXCBFOr4sN05oAidjqUGqVo9rrDLKWGyMNPIquhNOSNzQiINCZ7aOdDz15RyBFMOCYSbczmKEAonJFqQiLHUBaUyuFRUtvzpQIcxGPeyR81o4OvaNCpR3SCCp7WiYMBBfQb7LMR6xc+zRsqI7XB/A1KL5aBuzfaplh0ZXDhj5VKQOCEl5wsEFQsYCZzY6l1J88jgvneZ3FHM4dR2VmqtIK5GiwKertP7SARQYZMDG//U4AOBUkJZFosQJq2OBq/a2sioOIQacSVKShvQOOP+ubdTF4zGMYb6Aagy6QLgLPtK9C/hhbpydgsbfa4Q8pKH4QIEowt6hDFyY5CqBouNp7Uc6JqbvKCUxQxHQuj+lMxBZcTztaizm5Ri68Wtz8RqPJhzAiohV6XdUmJwsRDuf2h5ngL/HBr9G5DcgRffu0Gb5xocijzByI70c+YyJn894udXMnr4Ub7f8kOB/h0VkkBYxbLhPRTFMZl3DWFk0gGoxVQXGNolraPXNjYjgo//+ieo1A5DAHyirYdII7KoibMBiOWacO/iKPjcjNb+H+w1O6P5hSUyxL1erK6u3tkI9+OcKiHCJFiaZWB8NhDTMvrekyHjFspdjAEuosTaM/kIEcfxhdPThKJO5K0spHUc3KIb9A64IQaGay0GvVE0gyf6WqgU/l5nlb99icxFLCty257tu81ZiO6bcevojzbG1569W+qPtsXjir68dytK59XGt1/PVrDwZ9+NBltaNy0HcHjClXy3762xrM/k/s6T9r+QIDHvPvX9lD9m3b3VLPvXjxDuy6EGDfthRx7UnorXopVufGWbe8nuN4Vvl7REeUB/TVb6pg4/BjbfJCM0PGM4lPqrFCpfK86HcPGrcVNrpgvG955zYa3KSqIgA+ZBQ6A7ALMote2KKgtnC86aS88QQZViCltq/SMiDfcJafe8M+79IHZPICjzotds8onZcrLqMDwPq48x5nEjDgJ4ca+FQM+IqOB1mCmxPGOq1ObMkKLZU4kZCIIkqQAlXXixMHdC1MK5e/ulaK5pzuqBkVLCfLko3YGeq1AF9j5XAvdgjPTWUJiBKkhup8DUlEs+ZnHD0cAsu3KQ3avkoWrYXiv1Ued+Ub+3bbuvAUZ2BF0vrmLnmxdZfV5rh/fO+caz85iWPqaU9p/y9Y3HsAnJrr3v5w0CQmrCyoXUqoUlw5UL0ctcwvvd2PUlxfmJW59TmNiOGaBAlvdr2Ju9LcmihgDdDLo/UQ8G1GjPBjO97vWJ33nXlW7+HXs85bqzYwufI3B7Toa14UtueOcFrXsrwxVl6aJnvuMeCn9rGOU8l4DKgoUZdDHYTIJlXnC5XPD4mHE6nXF3PmM6nXGaTzidJkySVeBvfL8wg4Ut0klFTsnWxLmMqi7iBv+Y1atRSkY2HP/0dAFOhm8XgDMBhS1HrHm4Wf0EAKeuBJOQVzLnqc1FEVE4KkXZQwIKJ2RJiouSwmgBgx1Qa74zMyYvhtvM0KlmEJ6wFG45TkHVuKlqPKwa3BGbwrlqznVQQZpS419r0XbUXku64RZ0z6Qpm0K8QJCsL3azWnsVoKICc8d7ur9VqctMKB8q8AamdJHO99t2cEW4G5LJpw4YCJq7s3woSAY3HL+XD7U9BwCFLISwActqcC/jDgChypPxn2cAwIJH36m6j+qEiidUeVKvZZNTFFGvc4ed5TcLZa9vGi78HRlvN+el4KGRcAmeZ30HJAAbgOA/3fxJmDHhrfEmhPprAfAAordIoGbMEqv1toQIkEcQ7lZ3Oq+jedHtXfGc6AAl7krU0GG99DuyqGJ+sfcjFHC1s+LLHjnHP0kMD0X4MUj7DY6gnWLt646QaKHfQQByfYcsCU8kuKs/YyHP47sOQe/9pMHzvIdwN3qoUcahTyF3+pHtdE8a8AmEt5j/MUMAvPm/d6o8/OtPKP+sqPgIIc8/Dix+LqzFz1eeez9e/kYE1Rc4rXPET49wf1Bmd7JyM/PiSNMUeQlq3HRmwh0n5PMJEyvMzZzUVgkAULvHLAEgl8fVlgpSlX9ZaXTofuEqSGAsYBAtoMrgUsBUUEU90UUES1XvdAgajdRW32BzhF/6gF+0MYcZaVxM29d9JsTnC9Jo8MHhRsRSSXhFnSfyiJ9jjdv1iGdpvQYEQikFpZZGOzKrF3e2tCfVPOJFBJSSdYFQyoJlWTR8vK0zgXpzZHRm1Ygy6oxkedBLQam10dZqc9XdoBMnFIvwUo33STnrmlTl+ZZ5xnQ+t7RacL7MEzVUwfk8oRSlE8pSUCGaG54JtOhcz8V5GIc/Mvxko+80s7yOkQBk+30X6L7PjxaxKpHgN2X5GlW03877Unf2yimZQZhgMWLb16ssBXOasSwL5jljKUo3lEXXxEP3p6RGB0JOr/d891U0/Y24Mpw6LZ2YkSipPIwIOWtqHlXsa1qxutmJr18+l8ZenZ5NHU4PjvwaAv3j7/dz/ByfeQuMjs/w8Hvvm3XJN0rt8IpAzVZQjUXVYIKTG61K58U2FR7jux/lP7v8UKD/EeXosAWiaq3AofCnD3VA5FnGOuPjAMH+/E6jZczSrQkLg7e0GPALOSWdaHknwAcA779o8D6ar48svkbZE8oK0Cw/51K7EAkRKTpbGQG7C9MtJ2FTNqkor4oibkfQ6zbj96sz+plTvWGsjNjTvgbFi1uQBytqtxh0y/n2PRLKToz1BtoM/SfhIz1z+4swEH2HT7x+f2L5vLl+rufiIqNvuJZrMu/7K4R9GHO9dNhtfFwjUFUINMKc9v0zpMjP7cb1Cjj8S8PV4/LiPgUC+D+5vPbo1viCVswo7ewZ91SKlQSqI7zrSnCjH0wI0fIKGAej+iGve+yfQw1ecSbNCI263CQqxrtSwm96n10AFsIDEgHBWz40HgQGQYC508M2h910OXxIo7lMPj0oT0Acwsqp4CJJhrDYWY59VSGLkAz0hbelSuWiCjPRkH/EhFoEFAKjMfmc6NBdea65cavlVRdIIkhluPdb85Zrnoe04YB9rC5sMGA2zB9ntfKv86ICvDQa2CjpWft+FDTDwtPpjFIWkHjo8NQURtKA31ZQN9QPAIkgbMp+7nPYhY7B7Cusq8qjbO7uLHe9COTRMbyA9pTnr1Q+Dzds61h/87KHPdsxXhOZNPal981PWwgL20Loj95ZwCDHPOzx6OEu4c7t1JGHnF1xUfB18+t97/gZ05DTayr+JWVPSbp6YjMvx+/v17L3alRm+1ny0mRBB/sppp0avhwIymJb4/ur+tvB2m32q5TXU5ZfbSW0F79v76/fiR6yjXaz6Bwazn3B0yOhLCrQnaaMeVah77mo4hJwg3mFaRItJEhhbsq6z0v1XNaiAkLLf+qyADBQnhYsl8X4vQymSyMqJYxRFdIq5HcjKi3evsoRSjHDealqw1SBWjXyAYjBVZWJnMhwkv9O2qcqENYQ9VLZ5ONWZxIIJqRlUUVRMc9B2hqei5hhOgSUlDaRisbXVnO5VAWp46Ju7DBGVZKmqBBBgyM9L73RQlC8UUGW1oCQ3lnUmdg51vl0Il5qzIfrxnljpIdupDHurw6jXE70NNyvQ/KO0AXH03LS+0zgmsxorj8vH8wo4f0aopqiAQzCPdyH3wsBmHBvEo5HuPwqKtE3tGmsgcZzRkSqqDeFtUYreaOpN/AGZLnW96KiMNazNrYZO0F4Y582P0bwJMoohvMFLkgnVDxiJvfCH/l/abNi5k22nnHFXMFZKc6sf7E1JUth4NcioNtBrIUWnOvPAIBkivMavNBfogRQFf+4g4wcMs//fu24DlWiA7rvSQjlnxXpr4z6z1HC0PaGzdPnw3SnQ56pYHObTNfr80yB1tzB7+TvGO3jUXQcxsIMS1dvdx2Nhc9nNYACAzxl5NMJk7XPrCHY1bZWaZRS9Vx38lyafjoxI4FRxfODVxBnsMECJkKqCYULljpjqQQq1eSP+lQjA2B0sqDrv22RmmJToruTzbsxCU2/FgQWXdk88jf7ERiODe6+lLRoZ1U88kcFi4BZgEVThQi6nJ2gOKtKxbIszXAZgEVmCTCL+/iqKD70aCTNwKwWeEQsfYmAKnh4+N3CyzNqUHDrHlN4JBA8PT0i5QyP+AJCd2RgwuVpRs4JBKUVqgiejB+bcgKYMZsB8x48jmfb7wm6IQ+H7wT1SH9SqbLJAAAgAElEQVQ8OG7PrdWhAab3zOiWCBCG3463VwKOKhrmf1kWPF0utoaEeV6Qc9Y0AMFxTSSkVludAe8DweAYVFE+JcZ0mlpe9ZwzclYDvCwFKWWklFr6MDeA+Yak8aocnagvKeMO2lIqr1N7/7ETpeBKm94zTXkRz37fX2rAU0FI3gSa8MnPejsU34TZ+FH+JOWHAv0/oKwBRFeec1NODsrO4Q9d4dkUoJ2Rih7qH6ytAg3bLgT8/gzAdaY8tfoQ8vHeNjaE8b0WeHfSrhPoxhiRMzijstcJpU09xvycUkaVisd5Rk5Jw76gC2LZBAUEJwiVAGO3TgOr1aVUFFuTPcX51y6DIgSjsFD7y0ikRH0L4wgxqzvLtYg1Kg4GGrTl7Wp7Z9wXXwOdf+3ixOT4ex+Fx6gH/oQzZLcwoM/35Nar15/ZMolXij3W/R3XIpR1G/sj3bb2XPuvs1OOM1G8Num3KlGPdKWZ/bUJNyXesR3WeIlVxet2CHETflHplp37jfVxuCDP2ez9UFZ/tIL8a9LFkbdbE2S3NvvS57b+I0fPx5ofALzB/lkYz7HmxgQ45ELX2wEaCgFsghAxOLhn7NEUaP6TWjQeu20CGBd0ez8Ma1sHKCh9yZQKu+va3r82P+F8DbOwfx1BSaI5zXkwQuOcsMxzy8MdjdFAruglDdln0iYiC73LgpQYUpQmU2v4qh6D9h4ohgq2vHukwn5KPR+4F04JwnUITytQz3CBNCVBr1LHnFTKaIYzJhSy8O3Vw+JKVeW9dDVlniar13JOX2a4EgHMmJ8ulj8XJmywPicTUtaihog2FjFDRjGBFhu94p4DTcFvizxQe1GY7cIRUiytgl60nL/ypELo0nwx4l64tnNuK7eDnTWFfP3NvacO37ADq8di53xi3DuK83tOyfbsTgNO+xzPyNjT9fO38gWKGtVzEzBDFQiqrZmdwvZ8bf2v7b7TwwnXvEX2cOxzK27+fKMc8KYS8+5ea0XpgLBiDoucLwvP3uQJY329Dh93lvzwhfXzn0+/vk7Zp0dfHotgf0GbB2lQhPqTyVJKePaMWitK0RylVQRLWVrqi5QZpZw096sIEqrlva1GzDIICcyq7CBmpGqjEEFdFggEpahieZ4XlPkCnibwlMAyIUkFzwlEBQRGSkDMDwv007jlV0cFocJTggihVGiOXa4oxfCCaV+m6YyUyOSXhGQe7PN8QSkFkwg0By5MAQQsy4xlmQejBSb10CukeCxPjEKCOgNYVBZR2YXfrtCEeWyi42MCiM3jvNbmoZRS9gVVJTAR0pTRjPicACcBJ4JID7uuBnEuI3GaRHF4Kd3z0Kljx6nDrhJvJtALCLDZI9a4/gQnRNpF6z6bkwVBcAbwBAqqX+1vN4YWEaSfRpohwuGt7CTSm75fHrFADWt9lzqMiqVh4nBO+k2yoD4EIfecv4fgEfzLe+BXwknuAXqEm5mMfLbv2wckvNH7FDh2g29J3tj8ME7/dVLvU6nI92fk/6M1Pfz/vys+Ie0D4aGNd49n07MwrBQQzklTRol6O65hvO8XQCM6rKMB+h7z5yt/hOZ6B1gYfVXQcfuqiP0X8YqvrfdaDTGaiw4Y72w/b0PKMzQEdCJY7nkfE+Hp4QIiYPq7nqfzf/2MD//8Ncgv0eYFUKWcALi8EF++tBxV3xTA9r/TN4GCtjt2HoNDks65wsHukd93guMFhnodZzZckBPOOWNiRnLFDmmEUakVQtU8gyUsWN/xmVQ5WiyCaBFDEaCmqC+i6S9SIXBZsKBgkQWVGExqhMhWbTUauO2Ppm1ciSFW87grSTG+YYQafYbbu/ayi6WbYVOjY2QNQlotazrz+tYJ8Fukedi60vXu7g4pZ5R51qeZUOfaUm+uu+5Gvm7YlhJrnvYiEFla/y+zRQhJCTlP6mEOhbnk3sunE+bLkyrRiZASAcbLTZP1s0UO1VPzdKnIUwKz7jP3rodAjfIyw73hXfEuEFzqYmNxelHl//FcKm7SvzM0vcLj6n5ch88pcc8oPcE7D4gDxna5G2EoTnfHNPU0n3G5zLg8XVpnXantzmst0qrxy75D3bENEXebQQsR4cyMKWecThPO5zuczidMp0kj2JSKRYqGb3eHNJvF2hHDF5VrfNExn7CV3T8HXtft9PXufIWeSQ9nr/fcIAGr979mGfCYIbeOx6TBCKdHWscsbRBqhbSUdgQ0g0Y8P1F/krIxcP5Rvqj8UKB/70XiFxOqAqZAx2jJBiOATShYg/XUWOfWbzR64gAGL77SGdwH/i/3/HjtEhGoFwW2+q3UqkRodUJ2eHv8xbo2nJL+uSeVAJ4DvYfg2ekLtkjuEDEeY8ybShTyNO9zzyna+tvz92gx1GkEgYa9kU4bhD23h3voyr3vpXRW/LhE5fnX6sOXPnPcvyMyywgL+94FKNuzsxIHfWb5/M39HdE+NxUaAMOWkdDL+9+/RvH5lbYDtnsmWpMfwYIotPnfUI4NOV6vxG3SGJ+dPdMNpbS0VCOI69vrCRWEJ6jX2YQeUNzAvBEiNVaGtspd76bj3kEJQf2meo+O98Vedgi1YcRvKi9hL41ecoMz/1NJBtyznMg8rJdFe0aiOgoLzcrmMU36I8xJNy6YzicV5CweftDoPxcwuZAqCNVKWZBIwxIS08C7EzGIZRCM6R8FXWPYGWYs6f1aUyZs3nWNgmzedrbuK0UCsYcXNUxSa1f2s3vi+fzZWjcYo54jbiiBRvfaQKLicG1Ual6HSrq4UEbavmrvPElvKyjPrx3d7Y452kPrWtZzent5jvy7BQdGPL09i/1sd8Ey9zeuVf4ZtOneK7dWEz2cAKz86Dr9OqxngHf9qaNB7dFC154/fvXa3N1Et4inzFqt254yCkbHy/i7GbeRnYW21p0PlFDX9yuYufVc3XZe49zGOYmK8n1ribjXuhCvVIGnhhABUlIP9LIo31VqMf5Lvfyk1qYE5sRg5KbIBquBkyppPeeqGr1IrViKhhQtZUFLaSEw4yEXIHZeTvk/ACujmTYeGueASb31GOr9hqKGTdUU+wmKszz/ORHhdHfS8KgeKj7ghbIs4IkwXzQ/cEkZyfKQujKJwUBSr3fVulYD5wS5CGQyeiAlQCyEZ1BMOuTt4hZqioaU1SAuTUGcRmLTYe8zaeqQnLvy3PPdVo3E4rQJ2Rr6NNbfes5d30ObfWV920Z8Corv8KTOM6HiDMBzlwMZCZB7gAjpPbfw9wBQfi0atp0wRjjQ6dgA4GsninGPCQ/DKxrGdhxP9zgeYZbTqpWoRdXxdfY9k/5CkH8TgLcQ+dQ8ozuF6b7gGHJFr4tYj6f/UiOO5V8F+S8Jy+MFeZqs76b0JgA2LhreX82NEcwOU9v+st/s4xML6R6U61vZUpgzV6yGT4ccZO4uQm81XUI7ScdSCifhnd7uI4oTtYJ98JQoq3qsNK95AO6F7pEXRATLP34F/+UdzhV4WpHncZu9nBL6/Lfa20QbHPccJdB3bCN2Abi3uZmOSMjWQoREhBMnnIiQmICs+c9znjxj9urs7LQd6BYCaVQNaLooQYVzXeL0OmtMhFp54ItEKqowJCX1koU0WV9ly98sB3tos1gWKtkNfaizF41vM/r/Oi0hq3rHcd9CDT73BA3f/Azq/i1l0TlyWFxrM2KLcls3pNJzyx1ukhot1CqaNiTwJIAraAuA3BTbOWdcLhfMsxqJ5ZyR04RaSzv7e3I2n5JlKciZATHzqADHa9WQ8BVVvaIJqDJSIrHWCmlKRvc4F6iBTFxy/7sT4KGTM8+W/TO2hjnUebEAn7pBGhoPpzTSAhFdu2Wescwz5mXGPM8AqNkEugF6qZqCkBODRD9bqHZTsHtRRTgjkYZnv88TTuZxPp0mnE4n5Cm3/Olc1PNcjcK5dfaWdK1fr3wGM3ZziRjhddvY8EKyunpl3400Xbjov1s1+iVQ9ehhEONLP8r/pvJDgf6dF8J4hlVp3gWmtBJ2O7ksUiFmLedKTmBk/AnGA0p/E1Dm7LdVTpR18cuJdgDLDfBz/cjnKM9/AvDbwb01Q5x4ZErXypq1VbU/S1Bi59EsER2JVkfi3lqgRIiUYU3MSIktr0pnZHrecxUWMBHqSggRx9H7uGZ0jotbH7Y1dYU49lEBGZPNxGal6MSGWV3WuJ+8lk48SiOw93vXCX0Z6N/vVWmmuPdle7bP/ciqxnLrbKgw5fPR+va955iZ7XmJozkSJhztt9vJktvneP/JtUr3G+23F+rtro/SlEZEZum+FWjsvrWjlPwaxfciIEFwMs56V7xtBS+CDkm6V/LX6evY8uuXPYKLMHpk3FLo4PtzJahE9N2DRb91z6xWBV1IpFdSVgGjKyWduWlhsluO0W7hHWmWGGI76rrFBS3iQhOYYIhA4t59I3RpZ8RPutNJq9FEjqp5km1m/GjBzLPE8LxAWt5uIsuLGoRDebIcdqIC/XzKkCooiwq4itFZbpnecpQ3OkW/P/7+ADLmHaSeK0PxJYnjZ9LnmFEuczOonM5nSCl9hE14rf3roQ3DHJCKUbSbqzNKZPn8wjXzNCyLeV+IWO5bhRSea46gHnkp00qwoHQCmVWBK4xKyPUe6S6BESw+qkbT6vdmUDpQKaZ4IIS2VXFOZzKB0dbzvK3L5uo+pry+nwI9TttTeUQRPgcTtvDj6LxfryfmQndBsEZaCiN9BpmP7a+oRAp/4UbjacL1PdrJ5ywjoYI03C71LPUeBcHfypbFsd1fzfmtkTta958x0LluwBYHvn91P15LL9VzQkPXx/1K/cz1bS3tdzUY5uklGso9EGrrfIxnvoHNz5YGrsYtu1efXYfXxuJHtOpgoIhuSALxeUOby27opTCYKa4JmVGHmCJDeaqEbjTFHNfFea+qAnfHsaQCYarqoSZQeHo66X6fnxZbGkYtKvZmZggqaql4evyk4WiJsFxmcGJkmlDnBUUEUov2Mhgl9Ugdis9O9/dYni5o3FBQApJozldC0rDzlCyqiWgecwAQQs6qOHCy9nR3BugOT78/oNaCCRmcCMuygBMjpQkpFZQ0IdWKUiqEBZ5SghMAEstjq4bulNQDvyk/EPa0K2iNH2diDXsNUW+8uqAsCSJFjd0IADHO9ydwYjOEV2jCJhdwACLEgNQmfLdNAIHiv2pR3dJPCfKbKknW511V67oD03vWMIHwCBpiKJB6LvUQyl0sr8z556mdo+XXBSDWukhDsYvjxZ9VARSPdPm1ttpiMV/+HdCvayEQMO6x4EGV4O0cWU2BNvPcyy1qQ3hGWJXoqdX+AMIbLL9aRDwQBL+Dca+510M/AEBs2qt8xF4h29sFC7LkRkMs/yo4/f2MZdGzc/77PT7947+hHvBae8vjvGm1z8nw28anzga2DwA14JIuR9GKIu1lmM/P1w7M9T5NeItJcrv6rIzC4YxvbQNcBZaLmT61nOq+OtH9JqLtNh50vK1Oo5+w/EOvn/7rZ/Bf3mP59wcU0v2ewvsjLgYmGfOhr8iEzfXt+FYvHD14oCjpvES/1/mc0EgD+Gh7W2VqoQPGBylMYiARKKt88MSMN5yafDfBIxW4Ipxbfxy/tE+L+KFpOxhCAiY3yrERkCp4QUBtzjGW25kLJGnIeaqkykgmcNUUI56ToxxspZGE60a2u7RE06h3qiwa3osvBbVfIFKP7loFRdzA2xNDSKvlZaWfDDeS1b2qxg2PT0/IpbZInAJVUEutm1rU8Mz4FPdardJw+bIsYNZoE76fSika7Uv6uatuoAxS7/XLjFKq5fjmIFvpnyLAslRMSdMAXBbNlT4lTX/ltERZqvatFiyl4Hw6qVPUos/NljrLz20Rbc/JWxbBIwQzNDrEGT01xwLgybb+WYDf18fj5iWx0cfz7njC+TnDd36WIOqMVkoFzQVFCspSsMyL/i2LGiBwNxpp59fmW6poNLbiMu6uQGcipJw1YsA04TRlnKYJb08nTElpk+TRBFICOFk6APP2R8dzDt+7QcnnTNJYrsHDfSxxe72Rb9rUEjz4dVxuqNlhnP4ez/dz/d7rx3YEEiJz7U3mli5pn0TNGNDHoWkYkhMKIc+G+Ib7Uf6Xlh8K9O+5RAFFZDAMqbDl2Fy/I1UtxpsQVDoh7XRiEwg0wl1/vq3Ar18RZrxmvUfKcy8vReJrBqVZugUi2kPfdO+wLlhqQJvIwo2qRVpKCQjEU8yr0p6P1As6M9GurDHBtvMvHG0vKsQmE8q4hbwLT9RS0sPN71qNRiHLM4iSw1x+r8XERS94eruur9GH15zCL62vK9THmXFCLH7e3tL1OX7x+X5By1+zvMQrvJPe/aMOAoX+48jz/Fuetb01icT8XlciaNve/zOs2PdZItMwXu+CoDWzqp9jHfFtes9NydsZUWdq7RkXlENxXQuT5nUFRXE7lY0ndoGPmFDCgyCqoIgo9C8oKiKeBvU2R1hk91teVyd0Rg/UTVkBDgqTlDh1WgBo3h6umCeQ5jcUHiokguJaP8wCy7PXaYLWWvMUME/BdWj6IFADXMBpuDyp6Nlz6nFShQozb0fsa8SE2nTGgYkktrnYmSsdfKymj8Mu1KWotyQzxPICVgvr2zyUYPyr9L4QNBGEXpJGC+956AEYvL5gNLDTwjpF5p1h4yJ0+qU+2XAvMK+H0UxNVp+x/X0vnecIt3CbcH0fPl/Llfs7kPW5LrW9jEjctvoGuHKtrjURGC9R52eOXj3C88M9BwQYz/z63Wrqy3h/bVTsf9fpi/7ENXx+9Z51m9bXQtvXpjXu9912wvnoZ8AFR3ZGGoyMYwkAb1A49vHIBk79MeVbtL5uI+7XJnwPSsDtu9182It7QvmC+ProPTEeXhXEy7JgSQk8J3BRt3Nu+DPi8h46HCa8L0sxIbEbPylMcwNuVbioSFL1LwQq5rtrfJ1H7fB+g4Dp7tzqEBE1jDJhapVicgYGUQFXVdwvZcbJlLpat7VfKzyX+HyZscyLGhWkE4CnBnOYM4guqoynRWkIFXQYPmVUCxtfUZshOIFVAS7de88jnzdzGfZ+2FyaEDURm6e7zpsbTxAMr0lpdRAzWJS20NDXulYO48aTBJMn6CV+x6gfq6me7ZkIl96PO8n3ylaJ2yGHf5t/nTH9bJ7U702ob7nd43kmIlBSBZoqwQHQKupAwM29vRGCSfhk6UJIAVAafedGIgHjBfkW4Hs61O7TYkr0fudexySOswMcHV6+h1D3HnePcrFc7U//JDCSeWoKSpmbIhQQvP2vv+Hhvx9QQ/goX80aVndYBV9D6RxyVKTD9oV7yJeoQJduiOqwNxqpRPie8QazfMKMT2B5Z21vOV4h0TQKYScdF3nmb784mRbnJ95MWelcJ31jyGiEnvm7J1El+iTAcgDwR/h6O1bYPLmiBSJ8jZ/j4zS6iJMpkNj3N3U8KpruMjpApcSYUh54osaRkCqLdd/oXojpIr0PzfDP9ouau7Km/Ig0FhkMZIZwgiSByKT3a0KSop65UlCKwYdadH9WDUHdnWWw7W+cO7Jxh0OhZ9JhCXW6mfocxYo2uNc+p2lCnU3B/yrFz5TKVwSq+JaUA76n9pwPgYNSVgznuIe6G1cnZlQUNZj2qbChLvPScA07/m6D1vGVCpzypGc3HCh3vIKIRUX1tgmliqZPsbXRXOkVqQWYkZ43va0LWpR0oEeS8F15sn1cAczQUO4Jqkx30yWC5UR/4ew7XbqCVu3KCHFGuraKGhcuxdPhaIS2FmqfyHhmNsU2odaO45V+MeNSczh0QzhiNXDJ04S78xmnacL5NOE8nTDliEOlGdMtHh2nrs3hEHjEP4puHmHrUbnO+8Satu+NMVe3q3p89WWl4cVQ53hHi0dQaHel/17zTp4LfdNJGemxH+V/R/mhQP+uizPU9rMJart1o3tpNZKmETi1WRPLAFoUKrwR4FMEDuiE0S1gYv2MCxJkher2R3S93luA93Pvb9m6kek78jj3z2YpFigWFbhWI3R9/p14ilZPiqRTYmTOyCk3ATYEFg69UyqK3GXo8B7j4bT6pqzWGLDcieGFyFS2l+LzRliwhXpVgZB7n0vz/Fp1KeAUWRF/EcGN7M33XK7v7uvvXScp+r1vUfpevbHQ3k/fWzJ8rtsJJ+glLV4tX2eeXqF/z3ie3ypwpr1fJiFaE46f28Zrlo3gyD4VUmpu2iPYLuG5/wggEcoKrB8/9xptXfndRUv7Kjq1zr4bniYQ0k+py0EIoKYwDiK4kO+KiJo3egtr3rzQASDkb2z4qSFCuJKnI7ve4yDDaAdA3Psb6iixCWlunlkudEwWTq1WV77rnpMNfov9AtxsWRXinkuOh0dTVmt+kCqLhQSlFKPJapu3ajm3aqka4s2uSRGw5VyttRhTrwoKz5XnxgfjETdlOSH0ibriQzT8+6YEIOKGDpyT5d5bP+MSIxtuWzLPxbk6u/54zjACBZ70t4eHlUbDeshICgtMRJrr3FciCu6CcBn+fieB27Pe9bJUyJMg3SdQSzUjkEcBzjaOJ2r0Xm1Z03an60XChz24tzmDAuzIu2+AC7fRVrejBD9r4YVGPO507ggRrSdKVjfCR4RJsjPBI907UrBsgMlz1D9HF2xOOdHuO35tLXxZP+FCuADCrpfY2M7Da97l6n4Litym1NtrcjB6Heffv4717+xYGoOHRsXQq5SDeQvsxdcpn4N4N+9Qx0tBCRgNqxBxBaEZslcRjU5j/GatFYnYPM4rlrJgnhekxCbMZRAlVKqWW1PrFhOOS+m8OOD7Qj3MIBXUDLnJPK/UQFojjQH57g5SKy4PT8hUcXl60r6Yz8/5zR1qrZgfntAot8AnS60oFUgMVNG+LlUglxnTdFZFPifz8pIOx02x4zl7NQpKAacEVeImpJyRUsZCGl6XPa1HUAwxa8Z0KjNAoqHdSc8plfF8uTFBFcLplCApoXrOW8NrzAnsoXuhYXVVl1RBVeuv5KqGrrBgJkjVa+p8ziARFPEcugq3mG0PJEbBAlfQLwZ12ADi5aP26/yTKsLxWxftCQSgMwRPwzlhcNtnPsfM3Zd7NEJzozK93j3Pu1TH8bgr7St65IR+Esbc0LPBiRPuUPBoG5K6Es02aVMiYTSmErtfbM08lDrLAyACxhu4VzpBFfZN7kHrRIUAyT1APbR8NI+r9DtI3qqxHoDl38UcVAj15/7kHi73OTnC82u+SBBCtUvvp+OjGGcsKtHXxa8v+N1+i0VQACpVJDEDSgrrSdKub8YjwEIzKn0CAGR5j4V6mpBeh821/X7797/h8b//p52tGgZK6Mq4y3//W+v920+a//1fH5pSvNNrHQPOpAr0O+jWYWhe9F2w7bBjrzwL52n1q//ekj2WgskUc1G64TW5I4pHhKkmp3VYxcTIlEzepk42wgSqFZUUpvhZYDsflrxgXItgcKFoREBVz2GCrUOknQwAKoxiJFL6nIXAtaJI0sgelcFUQUUnW41qdGmaMV4btSvCR7qFgCG6QqRViRQeAmIpdPo4qmjEUN8GZNcNa4GIkROj/D/23nM7khtZF/0igCyS7aQ5667z/i949khqR7ISiPsjDAKZWcUiu0ejmS1otVjp4BHeNDbcdcv6YlqjvOlDbGmD0JDpCiubyW01f7zDdwRL47jP8aymDiFzODIDiVrBwlhbi4Zd8e7tMztMGHSCp0Jx3ioPcUt6N4tmwqJpMtbewOhgSzPia1XrSaOS2Ye1qNFZLRUCwbqanJo07pau3Vi3J/vuDGWt76z9TzLypBcA76Ce6DFPNxeBeAS07aAP3oXxuJ08ms8wMmcqKNwhpYC4gIuuKXMBF4Ek24vQkxgtFpEgSkGtFafTHZblhOVUUZcFpVqiBenoTdDQAVohBKy947xq9IAjPcOfVS7hjFu/Rfo+X3u9+lvf8OgJw6HTceVIo3JU/2v645Dv+rcOaax9O9ze3zD+sUrYaE172QyJBFJorvItfMK/sWwNnf8ubyt/K9D/HWUDdbZC9Jfzn44XQkiYawim0Q9KxlKKVGCe0oMKh2HqIxA0rJi/keBdJ3zbdDIDzn0ZXk9yAHrHdy+Dv3n01++NZ5dUd97mhRoG3JyYFQAhPnWLPE/nCRGwdDCrYiHn5yJnUqG5hoqFQy+sodxccOwh03JIPA0tIkfd2/EFW4I+nl8ClocIIG0MSoQ6koU9AIjm0RvC6twBSltvEMC5kzM6PWj+X1iuIf+31jezShca3NwiSISJDbvhH+kIfhY+v7WWo/fmUw1cHk5mnzLRdb39vzrif03/Nov9VgW3M8mpB3SpPpr+ZA7xB8p2zC+tnwvaZMCDK/KNy13MJPtffV/83PLWE7q/3giI0kLo73tLx0KetQ/11wr3tMr+Uzm/o3T39HJhUl5j26GJhiHikWI7bc6AEYbMSJxhmvdN3AnvDsTzMBJ2Jkmy6ECb6+JCqBl2EdNML2322XiPDV/y2JYAuJoQDIK+tsCDOlUD6tVSVFi+NlDc9c7bTBitpvoFU7wnr/MR9cbojuT94jQLkAU9m9QIktB0GqP0Dq5FFfRiefc22HMnTCREvvJpykwQFsoaGvSU/o/H2oQETMMhgkjzBoqHHR502ZZO89+6bdI7To7YKMU8ygeQMdaeBTg7bjZclfZl9tO6RL3GNkjKCGx+XT3HvjRuuJgH+lIhuund1yrQ/dfheCflx+Z6W80lOmeiZ7ezfNvg5zdVwcG4fepGPYQ4LNCd6YkCBJqzeZhxTCdmF1bztmk2mBak8v6rLU11vA4YXkQbejvuhYeF82HjjDDR2HugODiyrSO+SFG0kL57S/k5BOyPl5e22/Y5DahgEPH4O/F3x9y6wRZbLtowgM/fyEiT1dcOWRp66xqWlM6AqAEQM0O6fa8pujXFBSR4/96a5Vo1b3P3IPRxESBdI4GonsC8wgkAmnmt2fu9Wfc61qdnhfkdgGRSkFwAACAASURBVHTDWSrA703Dl7au/CR3AXpDJ5iRU4MIQzpDpKgyuSve610F14W0PhL7axPv/LQqnSzksONApP1PMMVNYBUwMRrN75CIO86P5fXz1AEi5X2JGXJ+jn0w0xyBYZQkCVqGwMUV1POHkQoDSHlWRTti9MsMPv19NT4jJvCHcS77Z5iv6V0o3H1vlk8zTTZDrzRuVxSbR+c454N246Qs1zE+g8z7O9/P164kdmWi2J4PaOryE+vgNi7O1ktdnKYj7yUBeKe9E1WmuxmVRH0+0u8gPEDwgJ7CvSeSAJ2+qpKdAQjDhevttx74kOWdfScQfA9lsVM0nqIh1tjbsYOXHfgp/jmv5HUNb/RhpAg43Q3/7ZOSiwCU6KtrpVEDS9ndZ3nvVe1QucMzNykgqCdt/fUXPP/2+w53ecnGCu3/NdA/GHe/fgB++zIagO8Vff9e8hzpvJwPRzJw2e7+lTJIvXRuaFZSE403/ZnTDLq/92HtVY5mRsQQNfSDG4rbc9Y82WwA3BWvRKpUjnDVgXPIcldrT0UAWGTI3p2nqtEXIqVdwq0p+CI9fQxCIYBqBfcOog6WnoyzXOFbzICFwghocAZOaNvOjUUfu2Dccl7Hz5y9k+n/mHX3pM8mtfP8Fi4grNPcZ9r/sHhFqbLAHeJ9MvjRByzTFBnDgGHMMU3VjnE4jDMv9LKAiXBua8iBCQPfOJ7w+lyRHvBQZuqY7Bvfj10ErQsWCFZQ4Hnlid1z3TaP86MOeqfJmef6DGAxOjebSi2ihiw1TSdDlecEPbvvBfiS1iOTks6v51nD5hfG4+m2q2RVYT/2l5DhqAIUUcV3IrKV9jL8ykQQ5uC1gWQc4TSaK88XDeFeStGQ/iD1chdBW1c0M+IQ60MXwVlWnNuK1vvMFpozQd6Cr+VX/lol75bj8tPGRzM+ynPoT+Z7B+27nEVmPOzCozhfYqhfxFjszdm4NKhxXN9crmOsv8ufWeqWmHnL9YZ/fPH67zKKI/+X3pmK0yRy4R2njrIgFY4CHLAMpitCgJKHDMtMDo2GTGj7dUeLzqvsBON4QsOjJwANOZaHGBF3y0xcAjwv5QK81Fs3MIhQnAmLu9VZhAZN4wh63JBrDwJ25PdwgUgQ05aPkKE5jJgowjUxcbICFmvC+mKhXCd4/oqDtF0dq9RJv5kBsOeZcQ+C3gh0ynNkvlgaks63nud5za2PHtDm7/b+S/deKm+CMT8NMF2ClH4etmGDM9IfAl6/dw2eXoLN+d6PlRug+Q7wzO/mt1/iW/bfv6Zvf8WSVob9ertKt13vjQqMidsSbmoCvu9KIi53+4WO99Rrejo/GRVfCJI9/R0ixfTmIZ80C9+ut31cfv4Zua281VLxR8HSEfMLHMOMyzU8IFMq/MmjkHDCBfPZ7b1BunpdMzFaW0EsFlpWvdBBZDnk9BsKhY7ikAFBBg71nccy2pz2Ejn+8TpoCLLjr35RCOFxJQDEBPR5flyCoLlqNby5h8FTBZWGo1ePEg1FS6TMdQhC2Ggo6Whn1cZ2678qt50WI6znM8LYsMtQHpMebffEDs95HooW7Tclss+FbKMoE++k10wVjLC/4/y54tuFQu3cgFCikCn/ARFfrXRCaQ8nNIShipAjCo4uTaI5kHLzqbeHhHBNRj32vWjcyOQlkIQmmItHypn0fgSUd0WXwepvj0P0kik8xhYGHZ+rfG/M8RvUiZc+oOsvXELL2/m4vT9bSHLcBcI8F86GHLUrRx9ty/ThaDnqtOcFLlb3z5Qm1aNDseBjPxpkcaFIH3tmiwPn5ApaFhQ0rBMWnmk2E9aIw6Ux4mMazp5tDCQSyLs8LReK5lKdlR9ifE0Umid/jx9HR/zNvulApuynkyHz80u4J1+/GSf/KKJ8ofK5b7O3PYCg24GRfzFDhu2aE5AE8vqHDcdQKSjOn4WCUJUTEAFahxQVD6shUYN0xTf93EEsEB44unTNiO3qDpKmjXPBen7SnONi36BFTnZA0NYzzucz2to17OvTM9SAqWFQn6rI7iJ4/PJNz1TKI6R69p4GreovAWCBVFBJaYZmfcHa1NOXCzT1tJkvibVLKryiUiFd8CzqMVnrgnVpKOuKRsWCmui86Rp0sPm7drN+V4MY9YYHWpJVjNKbaJ/FPODsEC2ne1XiryuIBOt6Ri1VDepNQz9ClmZkbEJ60bo9+wmLaNQcciVAC8/U5VNB+9w24EAhjSsU5UvXNDq20YgZ9MkWwXOtA1j/uWrYd8KI8uLC4LxRIzS/DP+K8AD0va9jy1h3QJWk3N5cA4QT7kEAGp7QaOR21q3vshRS7Gswn2PXBWU4lNAY8BcEVPlu7z5A8B2MB5B8i1DJ3pmRk/s7SN5NOGtO0gIIfY/rLu8V72QyDgTQ18BPJEFG2s4b4aCzcm+LZ4ZR45hJ9xruvSdcoQ0MZ5ptPRmXvY8bHvpb953mxm6W+FDog9Wl0SsIjJXOCOXw1GdTYlqe7Y7hke6r+fTb7zHdIx6D3jCR4wQj7//vCa1p6OX7f3zE4z8/g6AKOxbSs4/5nwD4WQG7XypO6WbZ2VQU6du7xicY3GRyz3OXu7LSlUzoTeVoDwTcUUXlirtSACY1vBABCUO4A6gxbzkssvMyvXUNVd3VsKYygXmFr1qEEweMflY42Y1GIKhRUiHR1ArM4N7UW16bN3pCrAdN4ZelwxjUjtPlOWrF/NcnbUDpDEPGmyNSV3pyQCMSkYZvN3i1bXdX5MLvze0wYAag3uScCNF4w+4PiNgkQyideybNm65GX+pw1UVw7mcAyhsuy4LCBR5p7HxeAWjo9pKinJ3XFUUEpZRxpolMidyD7nsy3FloeISPPQQ8P58BbrhbFnBhnJYFKMDzecUafN+Yo8BTogYX91bns0W5eLR2TvY+A1ig5/jd//kVX/7nt6gyR9ialOcbpoo278a00jgFmqpDpfqd9JqJgWLJR/zb1U6P739omHYIUGhEvHOY5TL9Uiq4Viy1otaKpTCqpxOTjue1o60r1vWsIdtl8BudlPp5XhvWblFnQIb3fY/dsCF/oBzXODDFSy1un29p+rhv8xrRVOJ9TzdhOGhjXJ71RzNtcdyu096OXyjqmOnvGUMODodAkGTk4xH7DJiiNVI9DBfwJp1u1E/p92Fv/3rlb0/0Hys1AOHBw+293TXd+N6Fuo/u/zeXDe6ZEMP0G+PFozlS3KLgIBPISpDazBq0F0MOMMYomnHJpRNxLhWx258JwXiKfzxQ3QA91t4IE59XNuzwkFjt8Q2Nbwa+vLYrCJM5OMbBv+X4jyFvkZPND5QJgId68W8gg0pzTkjsd5fIF6qPTCHOCOGcMxmwsHKFGZUZ1UOotQ5pTcORtmbCPGNRBUBXhNuzVukCzX48F76O2QrWD6+v3VzPIO4VmdSiYwK6Op3DPCESWhKCCg1EUZjmkZUJsQQFdND3mTXbvnYZ5V8rF0XWtK199CsQII2tMhjs4+tOeWsdr4QSflqpbK8FStiJhhpyBiZEdyk32fVrXQPOndyRN0fXqa50RvPz2b9o/zyvxgSTbig0/f0xzPAjpICkNd+XW/qVSboMM/P9PRG3rznP3q3reARCacC27XvpwuEc2f9zzdueHPXsaBDuWXuRbqBLa3U0Ry9dv37V/2X0h1xZMRrPMx2Q5+L21X49HbUPf3n9XY+YEgZUluPcFdwEaIi0xCQ1UUhRqqq1RDoKF1OmGwQxr3RVDkjMCZeqW5a8r6qkJSFTsA6C1UMY+tyFQIsU1xavI9pJZIwoTovYeBBIGLkoXdEFKXehjpdZx9TRgd7MoIwTrlDRoL5rxgFMaOeG1hpc9MxEGlavO03k3/kZFA2HnhRqYt3V8XPMTeQ7lME8dhENO+8GAKWkfanheBW/E+A5ximF0rdmVVGtYR+70yMuZaf0ovTAfwR9HooIWyCBK1NMHU8U8xG0az47YgYO0idvXCbG6t6PTYI8G3mCN+GkY68nAx4bg9OdlF5Uo0lH9Ok8RL8uw5pdm5v7ryrTQf850OqYMvnRSoe4PLfiHsw5f/Pck6zEnmfsWv+2MC9DNEl/ZyHMcT3Xrr0j5AQyjf1SiFCw4Nn83ShoMABwQdimjul628b4fdgfwS4C1aUysyr7UU1KskyzbV7dgFv4IXYaYdCCQIZ7gZ0nOJHoqivXBpovrv+PpJ95SUg0Gy8kGoPmvvmsxljzcz8JYVAkE+zyr4tqzENJyGX8phRa2zoOQNDFIGex9GtdAOkKVM2ICL7mAn1ODY2CAx04vwNoZ/W0EShiaYImmhtUuiqqR6oyMcMnVg92acr+dn23OyTvHtKWQrgvvYOKwene0R3tSkdnAhpwfu44nyrO5wWQjsIVkA7mBUU6wEXbl6YhUZu2VcTyUZ9XS0ei5vilaG5SsdC1vSe4btk81CPTlceq5HJ/dnGPejNqV4/6AkGL9e4YQtdSFvS+Bv5g6uCyIElKYi2dJmkWRSUtdJwpyrvJ8dKXFpAtQoKTTPf4g9M5agyYc5fre0ohqPJ8KL8ISptpBB6JvgZxlXCknwOnNRgE/khon32HiYXq9Wh7AentfR2Zm9EJvis9R+NcuTm+Gz8No5SMaSjonnRUY/YGLLqzd9+Zgv6dtfFNaQAadQ7FDMW1O2YyUgj4IA++AXiAh6/Jdn65b5OzC9nKinupzrQGwWBC2jdZiU+uKHea1uAsJcAeBhFpd2kPGSwcY5x3n9hqfkhzp1+t5JnIDbfH/IwUSQChG1ygkHrNMJcO/m7vgYC2Ctb/+YxGGqadiOPM5lHldRao1+v1smvtsFzCFZfou+AzNjUT1Hja00msxMnJxtbY+CXHIYUJxVImUsGwrDDYroan6h3ONHywRaAKud6wrpbio1u+5QbUAhQqwTOx5X22I2YwRbkbjaipEkMPs46u0TaSbZTlSFcXGhbN5X2IvB1OxcRlSm0zvz6VMsYcfJvzcsTQlDyzWaqLraQLChWc3eDK4PJ22RPo0GvZ7Km4HjuZrXNqwzwioHhNxQygmgzc3zHOJWzNCzHe3b8zHKs5yj3Kp0Yn0VRdtSgkBQGNm9s0ofWOWor20aN8pflwo82F2FJ+DAnwAsJqY5IQABu87x3r2lBFQFQi8hV1nZDtyq02vhNGVIDF2vFoBDoHNn9QJfLzP38fNBchzWPeJhsaPi+YqIqciFUmzRahgwQijAb1eG8yPOQLmaEdNIkBc0GhgtbPlk7N6SqbDjNcoDDchsnwC2qxf3Z2pfcwlFhXzXXe7F9ErCUK3Ll6xB9iePoyn19X3AdF4GnFNmcrHZOLNPNRufw+xdxef++46JkZ9IMkRbNz+/6iUDaGk/07U61XCuW3spZjtBWtZH1VRj4YZzNXO8EXAWyjgahbVEKysbgOZIvvdGPvlo4c1r2IsOb6ZNTzui//Lv+KctExars4l645bRBgEKAB546u/5eXS3KQl+Z8lJkp6wCYxBSYgLASPeLh2LsYjz2sCwcrAgsTo8wx2UnvRj2MrhJCeb2FBMj2jzNU8qA2Ca2PZ4kT2ebGQnoSV0r1IQQzxvyIIBTeA+XQgE2GnCURPE72i3QQq6G1Cqg98MtA4IIO9crPsdy0Tq4uWFdiNNG6wWQAxkyyIV77W4gga0dbBa2v6rW3qnCkBzIWZfideEz1+99bjpSLqZ141/A8pDnKRCwZkgTT5cQcM9QjolSb9q556oy4cy8froxmXgjdiRCXVEAsVNW+s1uiiab7o/f78VxHIAPJ0OStNgvCZhiVv40WJ+R8/doJdDo4H4QkSHPGYGK6E0YXgEhcZWMMtu1/ofk6SHu9lun6KICoj47216E9zs/ncYxLTt/vnx+JzK+Vl9bzNeW1RN/07dUPbyVdBJtdtIftZHNkTM4MHfO31/+OQGCuhJpby8M5qiHxInEubmt5/9fHFb/932bwtN1a8Y7E303vokZj6VMLB1zFG0ruzo/Wlk/WpWvPD+jewNuR8ub9S309ahs4YAZc2KYXE5w9rC8EQvdxiz+qUnxS2HYNrTrCC1KEUYXREMSsAiGiwYzD8oC6VZ8LdQopg2KhUTVXmdIonq+7N2Vq2XKN+0gIox7ynLACTbiaGI9gDs17W7ug+2iEsB35CQVQ62PrCxNBWlfhgOfDM2E9FwYvVSPG6MtorUWgxG6wXZXDiFVWhcQQZrlQjDxKqLgw2YSuHplZ0tqK+cB3Cy2r6CMoMC4FEEHvPOwCLDec00di0mICgSqDihFHjvsB9aLh1AFbv3G5gQxdgt4Qz0kI6CGIoDveh2E4SCZEhBQN8+swSobHHaW10+9MKbDpnv+/modGd+WA3e/2P3lqk4etvxJw+QX8MCssBwwjpEU7KlcOtcJQij1x42dXy8/5jpKhbnrmOMSAhAqDZmgmkNi3Qzhpc5XgE2jAy20f9FwmGg6IfQRICGd8lTPM2y6jpzkYwh9/d9DEgqFCeJYn2/LGFZDtR8ojtHOcOyhzOxdDvN+wQENOdbApbX/3F+tJuHVC5D6GeT5y15zU8DO5NYOQiGQ21nXUKLsxbmmHbnskt+kKz1eXzRzN/mC54USP5TFvWN+8BzcklwHSPuqLF0bkMZgHGhcVUBci5cNFFdnjAMnUZkcDo6oHoinOXeBLBjNL0V3aHR5atBevRABUJnQpKKJ1tqZ8XV9XnJ+f0foKmJJbIr2YoK3uAd6wrqqYVrjcAGLLtdoh3fgWUw60ZnwiuSe5jqyvSjNIIzx+KxAQllpxtyxY5ARQQ2nV+GvzHO8r+qre6uvaIERorYOgeI+JsJQC1AqIeoUDSqc4CBcDHirQJhQWXYNFRWLrs/G21v/eWtoOasxOILTzGSLAcn+HQncxfnRYPnptzGFIN01o76SeTGSUgc2v43eY4j+MC0nD75MYHiSCQA3LPIdwhys5DddDDQ5ICESWPqarR3v2goY9g0XIozRON6IED75ePovlXNYNxSDgK8Csp6HhCQX3gIVvH1HVBB2PAO5BIFRoNJomFKF9vRxF/dATlHBqPrYb+OSXKwGERyzyYHUZHfBLgfzxHk3UU7xTqkMIBe8h+DZogQmwjWu99ah9kwd9JN9VLoWBuxoN/OEGpiaNG3KBdGaDrMrzQeN3eHE7fCR3lLGOdQkDkUz/kJiMwJQbLAjlJAEo+BUCQRFCJ0HDZxR8RGEL/d0pDB0YBfz/mUGpGwP8TwFohaDEeL39TL24HCbWK41NCHj6/St6KZHOKePfrVJNAHx/BUog3kRlSQqfeCfV7Y9U/rWZMCDRMfabyeh7Ri1V4brlyj6VOp+vwLt61peivFOrhF4aiIsZo2ibhQj3xGhMYCq2vupJ3lrHuXWsbcW6rliTQ85ZOhjPIGjUL1X+VdRSUQor32LKeDG4oXLVrv9Io4Q0P9F2YEUEUhQmsSsEjQZXp5RBO/V5Ru3PduES4U2DfiJbhFLU0Ef5Ho757/GZenO382q5ynWvdRNwBCxJ8CLZ+KVzblxF6gPghjSqnIcbV0mmZyn2g6Yq2Sr5LaS+AHenwVtr3QIuFbSuKm8FlO8VAVtO7Tu+Q28dT2ex/Ovu2KQGY24cAUf5TVOegPW8d+Phnm3QxcbfgszT9VrXM84NuMcJzIy+NlVAi+LL5lp8ElQonHV8klfUDQfUK11j2XUoBuBPhPrHTJflc+f/dkWctkbsUWJG601TlBChocPiyVjUBgFDjRSICyoXoC6oa0MrK9a14Hx+0lQ4rel5lWEA6SQcE6MQoTKhEqOAVInWNFR7Nxn4uWnEnm57JsZi4naBoHWge36dkiLhtYbmkFMQOo4LszGhpt1UHczr5ZoGprj+3pUSApTc7lCLTylKrQUBLD0gUgq9PVy4Ns4xPon/Y/rlMMRMsGj0zA3YJr4TQNawOx3GLiigzYYnq5sSSHPgs42AQfT6eT0Y688sW57qb4/020q9tilfKpR+0eZm7CGaCcG38L7/jeXaNOy80bcLJGmDk1nuesg2+5sJZwlSXQbRb4eaTRk9vMxTG/5zNLUFR+Ovtye0e64gjbzaFNpvfOsD3wehSkhg5u4MsYjZ1qV3bdIGc7EflIHr6N8IsXiMauJJZtrsf4Sg9+I+R81muQzCwkUV557jrjuBCrXib93y0ckEwEKptenapT009s+m76A0GToXITz3ccCUEkYscIQCNMRqfes9Cdds6oSGgUZP82e+cod9zncFs6B0Guzum/3f7Ts+Z9nK8aj2DJNk89rR9fb7LaE38KVbFW/JGNp4qntIYmdgbB4m4ZsPJp2bzaweGalgd31p9g7aetPfUR4E+PYCvM89Pu7728pb8dp1D/SrX27+bu/PsMgZLt8Gus+24vRtHZeubQ/u4lpd7uXR9RHD8prrw3M4gfj9aZpg8+GKzaSwq9Dp4nz/eLl23g+L3HzCJno7GtjSTOnvdn5fO9odvRWCvbHbjvruJXuf51y5AEIw7tfMJZChmFK9lBLhuKmocINNKSvGtY+5YIsr1wAyrwfHYa7UJVMqQ8BUUIr2SSJ3m7ZPcCMFAvrwGshGgUSG2yDonTD8ngDPOTg8pbWnZPhEw8XWEHwzk+YZJEBaM89paFhLXwhicAGIC1rvkcOS/f9EofCOkbtAPc4PYgwMBG4uJhTsZgzH3cLSGXJnuKe9Gy54VTon7qGnwEhxfJFixl0MYQE3Dc/ZWzcF+rwbp70TUimDbEEfpg3vEdMy3WnL1AUgy+eqL/k6mbEoCJ7LF26EkegmV+UFDezvuCLAmwoSxoV+sYWi2qRnf6Fcw7te7wX4/Lrbf3L5OZ27ZRqP4Sjt4NiWXGeDVM2CuHruY29x8/oNJXuDehuY7hEsapDVPuCpBH4PY0nK+3Hsz9k7WW7cZy91fYYT1xXOx8+GouClrzJdo78ZCrv71LaNFy5KG8r0o1MjSMK2ePCDpyGIryTQPqiTHPfM9tKHv4+us0B++i5dBCYltwl3HAs11sq5qpO178C9qgxtFqZ3XVfziNHc5goWJWhLdXQYayWaecTqUCWzoFuKEIWFbV1HXyn3n9TQSgAXJqrCSO+LeFoWjVIWm7oLpEjsADh+lg4RVTa08zNYROM6+LkRQWdWQTir13trzZRGTY3U1lXH3VYz8Nb9y/DIOL6fR5SXaWeaxtL3JzNpHnZTSofhpiDydOvHFolHdN2UztDw8K011FowatV3ehuBpt24aJZiWKfUbt8i7xBEdF3d1cDhyfA8BORLB38s8xyLQMiUaVZ5wE/Hmw6vxg5D9oEWox3k8zAMIhDoIyCf0zxiCMCzIFzD5HdT3D+B8WB7kVDwAMHj2O+J/nE6Z8zMkRnZ5TKoAZo+KoXRfwHk9wc0+Y4tNeNyb++DK1EoXWPzTaPv4z373iPT+fyMEWC74qm3lwcTLF46G/6lGyhlpeOQ+Tkta7nd5QGAqOFA6mPHZzA+RjrBio9Wv3vLa73lH0vIiUQE+KfjGqCgAPQBHV8TdtzOwfi7xQEZZWy/HShJ22vYzuFLxWGgwVeR2fjgCs67RacwomoZTDdDKcWFDBZKY7bdTmJZkeysWB3BdxgsnQzUvC8CiBnVtNaxtoZ1bRoeugmoK0x/NvqEBZBOZhjlMERThmgY8Xn3eV8gMF5JlbBkikpN3VFQGQaje4QOz9FBCTBaXueYIg3EdaowJLTOe3r/NEdGKOo9IkdWXlNAEp+ovVoOMu89f13y9UC/m7mxqAi2fwgwwzgK+D1Xpj9rqVjqKe7VWhV/6ySh1gXLclIF/Gq4QggupycuKFwt7zoQEDIOyoBmhdkDgsJTZzlQE7FpPOiqw7CR8kqNZPI5IcP7qy1hI1PIk3t+a10nm+OThfXvUK/1+sfRrHr7Np4LuUoDS5EboUjAvy4WsVXEjJWUDmgi4A4Qi6V8ghkcFsX1pRq/zugCrG0FWRo1x42FGJUYlQtq4Yioh64po5qYYV9XBbnF8QlsPVIbaH9a71itr11ko38mW3b/YmDY10K9f3W51CMHqTvl9Obbo99Hd47q2Lar+gfnMGh6T5PBOD3neJJCV7Rvfdt+GqntizDspwswJstlZXN9ZSyHb/z1lv5/dXlrak4tl/fB3+UnlzzNCogVOKnyvFjYn6IeQ4bAB9A2pacLCCXXagSlgZTZ8kSv34vmPU9o66BX8/WoNfc7sVROHMv8HNP7c1sOe5JY1EK2jPc/AfjdeSVvg9JIg2DaA1evaohXMltLw2uZXGDnbThTN4hcr9VDmBUCTlwjzx1AFvZFhQzd8j11D7mU1+jgjMnmbzEEFbKzGQ1HKFbE/9V63YU9TvCzCQGYi4UWLKkd3z9z64K8Jo5IJE/ozWXHTKX/+6/rCPe2Nm6+putIbUPCTvePUP9+h/sdTgJae3MyGNmfrblsBQvXZubyud1fz7X6WbhG1hh9jm8EfDAF0grg20F4G5pqeO1q/jg14YzC69q+BP8O+sLzMyd+PceX1/MSZL3WssSM/3j5uSj94OQkJWe+fdz6/mQKslz75THvz8NLbex39i0ze2nOlhfe28KzrY/qSyf1pfv7s3s7/PS+MQj8qVjeNmOCzUK7lhKeAF2aepQZU+ph290rg8g8iU3AP4c9VGEHNcAFNl2G5wXBmVi3HiZwZRQTYpAZbwGAeF5w5LoUJ4l0FTwQgahBwGr1zGrmFvpa8yAkMwBgw/9knj21MiqfNO0KGtq5gbhZepOO1oYQXhXcbB7z2qfzekZfV4RRgCnYfQMMLw4dn+aUF1TLIU9Gd3joX2fyNe8xobfhOQ4Q2ioaYm5tON0vpktwPG2MZPCFul5Pj494eP8whI0kYAGWZVFhODOkqbHD8Kj1d/c7TLuSIg0lWm7apALzPEd4a8Qucbq2+/xIeODFPKb5G+MiuILdrfm7APKs7Y8ge2n/U+rfFkBvyk26PbrxvdzeW7/38mbg9RJGpkukaXx3VMMl2HP0e/q79b4rywAAIABJREFUG3hsCjVGJd7vJSfQIROfMR5OzAcyB5Kx9fQKvE3A4jdB4Mqh8UV4Am3aZJqv5wZpEJLp/LzFGeB4znZvXL79yjb3FCEr7F6M3jmLeQUNI9E3NXRDT/ac5LYV2s/P5idt9sd2Tx58NlqnzEen/eBNpn+UL8RQQCkgMTjpyn4Lt+3CeRdMdlHFaKMVmvfV9qHBTh8jm7EY25l4tllRwyHN19mloa0rpLfgA4cnfZ4usQhlgucVMS4RDZ2ukdTNg5oQEWoADc1c7jRajUdziU3fm3qRdQY1Bq+EZh54xaLIMHWsTQPG997x+KTe5RD1iBc0oKknvUY7Ua90ER+rDcZTjgT9oUrvdbXoc/pQZ0gwIuBAhtAcg56XLujU4UoxNeyDjZON/rD57IjwnxJ9S2G6O8z7vYeMp7cOFksdow2bUtrx05Dt9M8N5ZNaSBRL3QIgePmB0ja0+K6kUyoDX4ei75Mh448SSnSt9x4Nj6imJOePqngn23cEVbBoD5y+u4fgES5L0BRBibMhpxEHf2m37cxdp2W7KY5VWW/KoD8EqrinQCeEh1T/wGD531EcmZCIECLMe+6nxXccoxanasfXytvMbfp9V3CV+EvIMRGm/YNEf/na5z7Cwtejo+A9HAqxMBb8kvotkUs4TEjtvBIR+v8o1dSpTZOfZUEb6g9A9rgfRYMvvUfD13k+Ma81i9JzjfZ1/IyyQ3+pHckPaMxH9jxWT2ygVJX1afhmYFmqzuGajXccTwiWpQLQiBqghlLu8G4pOK+WFqLqeSbrhBBZRC419qLeQb2Bm4DWHs44z93zX2v0rtqBtVBKFm/yx17A3CM39zBiIHOkMe9QMeWjp1BCQYOl8OqkBgJC5qkpaR3duMh4L5vKwFMBdEcZu0gsVYAWJvWih+WPnpyNLNoKl4Kl+tjatKGyncTR/sn7NtZq836DRfIgi5LAHo+DooLCBIFG/WqR2qSEsTOgMDngm+G600mV670bXyqC3lYzpNJSa9W9AZX7t940pPuyaJh9M9Jiseg2IHSLMKA5ty3UOBRWWIaV8OT3OejSTenMOJVivLOdv43BiY8DRLZPYIYSA2Y+kuBOxnK8s9/fX4DfLxUCJt1Ah6BJ13MpDBaN6MrSwF1XtQAWbQ3qlV40rL4UwbPtG3csJGhKlEqMWhgLaypWYpd9qFyhWzutE1ZIBBNyXjUbKjR/173VkxIdti5b8vit1PL17/bU+BYOHnTlpvp9z4Y5suOjWGyjk5zOdNpiQ5P0Q9hw+ZrS/3fvkdMc+f0NvZ/a13PgvyXGweOoT0azEjcPu/BieeNnP7X8SKqsf0X5q3rEV+DHF+ul7/9aS/HXKbfOWyamAQQjw5Y7oxQF5lyKEhZuwZi8mf137yk8OQBsCJAPAnzGvty8f68N6q1nYCLO0+908RHAH5um6KA/w9Nci4fDmkl2JApS0i33GH1pkNvnSgiVWlDSM4ESfL1riDhVnktCJtoWManHXtw7aPKgTMyUKxScC5CMLJQh0tA0pijhEgSCWC6lYbGq/9eqpqvLvaDAWzsP3xyWzRFPRl8zorsdntDu61d8/Mr3tdsDaw4mee7DvrqhRqZ0563d/XcXAXAvw/P8ywvu3D9GLPw4Un2bt/lR+3JwnX/TdD2P+TW7+n93ef0sbb+4dH255tfAm9d8e2u9x8zB7WXL/GSGdvveTDjfA9BQa6a3VcavNbgXtgqOXAhiIcwtPCAXDZfmnjJtPavwxQ2DSHP9AW7Fr/WQK0Y7oZuwRMPDq9U3FVdKlwiXCPsuG6ao4mHAVoEAxGAMJXyEZ5Zu4SLNH5wrwEPwScXS25AL5PUbIqhwZyEQdMytq8BDejZKNIGTjHmutQ4BnNFsTp90yyvvFuhMBShDmONea1q14pveXfGs8yqurBaApCecT8CGYdXUIDZXrJ0kwKwYKAT5wqzCs06QNrx33Kp7v6dmycj69Ix6d4r1cIGgj0mFGTZRovNUmCJawczqD2/GTFVFONz0R+dBYq/Ic3rf/t50rrb0yX862N71/+UBTW9kQcOF37vvb/hm5xF4pR96ksUUSoN+2nA6N5YttISNUebL3CcaaaGyV+Hk2UA3bpUtKWBnIBSpcVsm7464L3LzOlztBrnB8jwXl2o7pNFPGRIPxYHAczgPxVD0f1cf7ZyQXidMOcCeW5aAdw1sKPJL4z6+63jmYgkl+J4KZBheQxLIG3/V++iXe6D3xjifz2Zo1EBUBj724RJHvlsVD3DAPCYZYXotLKsrjx1faZdHOHIBAaRe48xsPKvNdB+eaXkzSxxFwfPzGXcP9/pt60EfdFGv96Gs089Lb+hdFRGqkFdlUGsrns8NBDM+b0qDCJSfbq1Fuhevz3U1trnHRR8REWY8ph6iRIRuoZIdb1GsIZvRuGX1JoGGTO9oXzrwwdCtmOIf6sEpksXpikFdtgOxcMG+Rb52uIG+0zjjPI39QwDoPeDeURQYMo2JMBbWyiywPsDjMrgYn6n1DwtlbPcA36mP2KRu1pzrIJQvHvJ/mmJdZ7ig2nY9ZZOk8U0h2qRguEzFT7TgqFnX7xOj/04TeA8YS9/hEPdS3diM0WG/hx3PsI1y3QA82tE25li+znSN48OeOqRz5I4TntYmD4aiNgJQ5IMpqAXvPv0DEMH6+2pK/+EGksc7ovKMXVZ+1bzLjTyupUDwDYR30Jzw/vbLuGc+aRa3MZ3T/U4c/XgT6/4SPjQgMXDu9FBhIgbsvhTdcChUfSZsfsnn1SmV4bmvyurR1KMMgwkAgMByN6vyrYNRekcXTf3Yu4Zwb00NeqV3rNJRRSAk6vXbARLCmV3R11BbRSnNUky6oa+ncLRdShaRkpSuqqyGQF0EtajysBrP0nq3FCMeSSKdJDP0cbqfbM6DLp/g0th5cQ544KFhvJDWB9YnLpBaUKWinSVowaz0eqlsaZrjkqMIpbuezyfxHyBgqWpSXywkuw93GPaaIYYZTLsDnKdHy/TdUitaV9ytRlqWXtNoNzZDcQZpOtcmFh1g9FkAjT5AfaDCPDoxRT56oldmuJLxz1mAk68xFG41JHsNAE+kMkJgby86ah6w+qWypXm9Ao+U2kn/NhEUM3TbUJi2r2rQu9IbWlstJUEPHEVsRhBVFekCy6TTRaPI9q5GRZ42FxKe+0qZaOf0O1Xy61qbAr5vDLm3U2DXt83M5fKj3/957d16WjeN+aeXaiS8aHQHOH91VDkizTEzTZFm9o3d1u2f+Onf5U8qP+aB/nf5t5RAWCZcLhZOlIsHJsGEeKUl5XlwkPq9GNPszPMXg3QOxD9smZ1XWoIE02WhLSKImAzSErtf+3Lt2Qfr0wcAvx98F38zcextGtHqdbdkmZ7f8ToIiDlQmnd4DkdIpvSuC44KaV42Jo616F1zy0kzxNsEHW3yHAgvPdpGB9DCm771g1kaltsEoR7cSQBoQuRnD8/BwqGgWNcViFw+aSGc2HhpSxBm5fnEsOZVsnsbHnBHyG7oi0vlbQzWbY+2Qgv/HZZ2t1ebvnplh35qub2de1HEIZhDtN+JEsde2yfRaBDvhML7/H38po2Q/LXjfHl1XyLajvbezeWKfPR660PQlP3OB7Fk+2fTrbHHZnHYZcOV4+9ffPtCu28uW87oh6uig3vXGn5tC5uZ+onHbwWwvAIoxRqnPmxzI27fBfZT/hIsonzT8Akb4x3vkHs6d/NOKwHPnXEHaR62WivAJaKruLI2p2DR/NYFzIp7NFSc4Hx+hnxRooNNgl4+aI6+Wi0iSlcBhEdyAWnbTDCGxrKXk1rqA+ox36UoM1wQOFgVx+bxJOq9HYIuS7Wi00MWOp5C2N5FBv1VqnkWqNDj3BrO57MKs9YWjFgwbVywVM/vXjT1jp1uEcF6XiFt1RC1JBr+3jwIXIGvAifLS26eKEKb5DFG19W7ivVpVQX/uoKpqgGAvce1jNC3No+nu9O0WbL39mAqVcjmucucngSg3ulF51+65qmrdwtMuuGVIotLQoJj9YcyPPUhPou/o18OXXuX8C4XAOVO9297mnPZjv/nkqHxwSl6I0w4VGbeWFf2rn9do5gBRiZcdt24tf5Emx49dc3XdO3CUaepEedsvOe1GyXlsI6OeuY7VwWCvFTIuccZ2Xo00GatB3W/rTMRnptnZPueTay9oqESh9K+jeYGXU4HVR2Vw3eMexCE8HTuzVCix/303tX9Qhc2wi3deqGoApmAZ4DuTAgFRs7+GinFDtqboIHvCYcHl/okux9A3ofXGMuDy43NxPHLl6rMa0J+dg2HmMB/62ETZ4bMAM0t1jAEwUQjNDmE0JtgpTWel9YBOo92ARUKczOFiCtHTC1DmqtTo3mot3brqhhfz6vmRTdwDMudDDNuahZZhVhzi6KbAB9KC3h4W4gq7T2nLteqZ1S6GWBFUlB0aYB7tPt5FaBW9bInLprXloDz8zPWNhT/JILWBO5wvSwF57YicA3pHiRqEDcW8zXoiKhpW9jFNDwANQKx5dvd0EuZ5lJjh6ZG8x88LLIFc42xdktzgzD8g/0T0TQlp7uKp0ddz/LRPPu/DDg2qTYNZ6tjRdn1y+mP3ueb7kE3ypaSHHSwfNZ5dNon43H3aPTZY9xDQKi/6J47/7OBP5qCkHJbPoZHG8cI384EFCW6JlixESFcLfndoC8A9M/aCvE7AN8TPMyzMMtyfM6Aeb39U8YI2d4232XPcl+vImxGE2Lp71Q+lntS4iTYNQGabGG0n4sr7vP8ULSf8IddLr9WPP9ukZBA4F89wlE28Ehc6296Zs+/PUNYIOYxrv34Nurf9CvmQoDOiFR9+b2GL4D131vO43SI2InAouHnf1bhjF/z2aFBc45Q4gmni+N4hSdMFNFwGGR0veaUJjDe3T+AADw9PsbI9Fzqjlnu7lHKiF6zWL2LCBYI2lLQhSy6hphjywpqgrU1PFkOdKwrIILaB2wpBE2UIMCpA2cmNGKs3FBWc8QqGp66VM0TLWAUFkAsNSi7oQ9p/uciQ2HYu/IjwlibwdSYow0iD3jlr4ilz2OFnTKf726mIYH7yDziTcnvaakioZhF+uReUAVocjY0kM5XOhIXYcklMknmfkli0snGKYaEne/9+P6jhr8/oCNK8QgEehZ7bziva+y9LqKe5KxpNd1orrihBo+0XTBeC13xUGFGlWJrNIwWcl/DAM4OquML6h0NijdK7zgtiyl+NXe35mH3l8f8Kt2u5zRP2b2142eZaVau/2jJEcjc0L9TQxd1BGvUwB1QkwCLrkeEavRRsX9tXbGuZ6xy1vMG/YZIZREquygWWaaF4YinZnPleROYMbzTUm5wlMLM23fBf8fC/FllHIQE1qZyC669VmTzyz26g09yOsTPY4AJ/cFBFTpd+EKPiEG0NchJj6M3MzURxtfTvh3md8FXJjnZXOOPlz916f9DSj7Xf6XytwL9P7k4Qi0VpWjIIJB7nsOsx1xR64ryRJlsN6MI3oOMjEVYtZ5dqPqzuj26P3XhpqMhM4PxUbYeSF434RcCPjsT5DnOshAfNH042LnRQZouFdAaH40B1mf7Zn8eVqcCkCkXmDS8TnimiFmodRWGD8AtRoSZYPqWublWfKhiIyAJYr+Wkv5V66cRC0RqaWwbKrH5+ld85qIZzHcGIzIpzy/sJ+9jli8deWpM15cmh/bf/kh5aQ0uER//LeU+DewL7dfh0RbPwzH9YS/k0O1fSfBBVC3l3un3Qni6IX/3zyx/JpEyK8uv7Y9rvZo9AWR68t9PdP18MvXWFoGfcaLXV74/wU/B3gvPn134ditAOyoDV82HWcOfa+huDvyJQNgEzw8+5xzmooIXEKOdVxBgUUwGduxdQNLRV0HvT6i1YKmLCZQb+hcLu5YkVO1rBz44g0W4f39v7j6qWBaYst48uzR8onnHFxWAu0eIoWNVOqwa8UU9yRlUgMJL5JL1calA28ZnIYm5a8SWUy04LQvu7k64u7O8kr3j2+N3fPv6FY+PTxq+L3tMEKEsC0rhEIi4YkVgHv7QPJ2lNVBRmkGXwEMBkIbcbeqNR56LtqswVimTbnhXcXm5W9Aen9VivxDI5k1RuCkPJMzkjKk1xsVy5ahTGIP6nMEze0d4fRoy1j1saLQRu0FSmLq0W5002hICvq9FhoIrCXuSfhY4+6Y1L4mkTPf7x2Zrfnp2VEZ6/vayo0duBmhOaW7LDf25oY3b4Srt6KqXfkdkARp07LQP8jf5F5N5hNBuH3hxtU1f1dMkQbXdu7MQ56URb4W/isM56HqAqCK8UXmzNltB+4+UjTIM8Dl1RiaNTLZrcKnOmxp+xSvzuyEHTDkBxwkc83mx2ixoT19vPeIvMxKEndDlUDi5/56IDtIU3r6Qk0cUYXJGJ2CntNxBGjI4T847AkRdFahdI49oOx2eTlu6KmVdAUyRiqsDFg4+FD3RUQKBAVJR8hSm27tP6o0oYtFZTDjsYeKRlGyKwxjdVDY6VkIX43vNk9uPJxFULmEOAL019HWFpV4PPCK9oNcKkrPBe/VUP1saGUkGZeezm5ATCgmajLMTO8dlBiHXcKLA+No0RWQdpbSIJUkK3Njdo/xp+H1vML0j5tDwtavw+F7X0T0CdbwWfUeAUod58YjQZsYX1g+feY0i4PNPkC8C/pS+NyWciJgxg24GN9aL7ZhkEnnGBGIKZ79yD3j3jz2GtddCnecZhu1oV345nuhkdbBBDUl93O3lg2qn+35jlyMDQ75Cm/eO+p++s+2TUwSSwWKNF7Cv1bvDwmBJtclIryAYjhAhW7pIjmQ6dXyz5RLJQtcDwLtP/wcQwdPnc+xvgMC/FAcSuudnbKx75h9+tufxFXmv46avm5bn7vq8bYufqCNPPtn8BaAetThY3hfK1hAxO8cc9WnssxmOBPXi9Zny3L/ZQ3hKv2V+tO2BwQCHU37KNLoFW4oQhX0M4LkJWluxtm65zxuorW43ZP1VOePqNQnAjdQblwhrIdReUDujl4673tFKh5SCZkZXtRabEBjPof0pbIbTpkDv3U0K1QijmyJrMipLxgrZ09/31piRBMOQ6H5/TmMNBGLhLQyXEaMsi+KrVSGMwqUe6/QzysX9aviYifH+/SdtmxIfari9NQ3F3lvHuq6W21zhbJfhEtVEx0e9RRj482oGVlxwOp1wPp8H3UMUOJaZsVjYdxEGSUu4TUOyO4bpSBHaqIMN3zdT8BbmSSaRYQFgjgJQJaQmRhvzso3K8VLZRle6VILmssPpDoG9dQhxyNch5sDmNAwZpjI6hy3E/rIsaM1C6Zt8PlOw1rk4o/lW0BGWysaN5Zp7p1stAjOYsjQuMm3sv8u+SJyZH6/peJqP9AXzvSCM49nhrnyBxdxggW3tf5f/kPK3Av0/uCgBoyEu2TyUACjB0t06W+ZQ7mJnm3gSRjiQ+Crz4f4dcniqL3k57F4NpasBPxhSD4JKEfXeG2EPXnZvyD5sey5/eH/IiM80Fu9n5IW3cRQLGzYHeVFiRI3v9W4oFhK5l69VlEBGQBE+EeMTFXwl9biL0LHGxGruEzN8QBLAyGDAj0qOOJDHlWjVPTOjnB4YSvi612AtFbVWJZAyk8GpL97n1OZU94WuBhM48+ZB3GcGZSKSj7DlARF9xLHdhIxeibFeen3aM5hZp0tv/3uR5vXW743Q/EauIJ/L1uv8iNn18s7OzreUr5igeZHuTcj3dKNn1GUSJD+/fPd1odtTWy96nh99TdN5POw5OYHO8Z4Xif/yPUzvXRrOW/fWX4mQ28LXf10rl+re3n9581QoI3mr4nwLNwATzDmck8vvHz1xkcQ2Oq2DU95/Ys8HTCog0Ec10vMY7iIaJlyFI2bhbl5zvFS4EpfNAwAi6K2j9RXyB+Ik8AeCfCW00kLAolIZx31jvzMR5FtDfy7ArwB1wulklvCtQZoKR5gZZSkop5OGGbcBB9treTV9ElpppqzmoYBlmJBAo6+AAGkSVudLLeBaUE3vcH93j/cP93j//h3ev38PEKGtK3777Xcdd+t4en6MXOVsKXaWWlFPi4Zxt9x37jlb1hVn0lx1pVZ0aH8sLiCAYvkPYflSBX3ygLA9YIYDAmB9XmMuuS7aDxGI53b16So59y7mSMQhO1O6pq3NaAMCL0XDRmbEDoRisTcXWkk6Pk5Q7I0gnSaL7+zdyWdFMPaJ1bE+tWh8PjLueXFMt0ydngiV7bO3l62hymhrW/+eimC6BPnG9xvS6lVlS4ddK9c8z3dCdwwhg+/xEHRNHx/xDvqAaf+Nr2GtBbJqTkqBhqPcT8CgNS4KO3bdcQFJDGLQ62jDdHa7ppu5kePbN5bNeiQF15HyKCs+L9TwLyu700ImdH1Wz7oxd5fO37xvslDcVTY3ex/QMFQa/TvgVbZ/XfkcH93QHu1/U1Lajkcbr+fc5kahw0QGNynORe9q4KW8vXnIiADS0RtBeIWsBCKNHkZS4Bymzqcaa5F5oQ8Ff4dIgXQKRaqsPQwxiAhowzhr7D0VCBMxzk/fUepisBWgFOq8t4a7dw/orYXXaVvPaGeJKDToq/ZBPI1LR+8Eah2dVsCMw5pp1sVDoXvkti6Wb9ZyDjfnpW23yfCO1BzyGs51UCNpf5iAJPCgOSMQF4Vf0uFu1AJYyHoMD7PeLewxANEcua2v8Jzw3fh5NhmNR7BbOxJfDpxXixRnCqb+2YXsBDZjQvqisMjnHAkf9ta0rhK7L+0x995Ma4zR5wwp19+Hf6DPEaMgrARsjoncO4vAeBjw0zxDyy8KMSveYTQ02nEyI1qzfrH1twir0pSC7NmcGxwXcpmFt6Z7WJf5EWRpisZp9Xv39nwUsXaMZNH5k/sJcrEIBI+WO5ziu552GkFDSbPNhYf1h3zfjYMw0+pOAR7iMtrDSIdod7/c4+tv/6Oh2wE8fx6pEqoU0C+E/nsH/6NM4xE7J2TEU/+toaNbGOQ8c8O54lKh2FvYvSlA5I33iske5CnJHv7nn4zYdlFeLtBrNH+kfTWY7Ya9rsCDwVFNy2Fe/SKopUJIDKZJeCCfn54ghfDhfsGpAOvZQnCXApAapEIEVIqFEF4hGksdrXXU1oDW8NxV8Xn69QPuC+HrPz9DpKN0n8dBhzcCSmeca4f0Auod56KK8NI7nlk9zUFqREUgt8lCyBGJ0ZnRuaCywDlf6dDoINIw0gFgt65+z+/TuJzmvpQCdDGDaV2N1gWlpF3YO9oZaiTMjOV0Qhfg+ax5m9ZutRtQmM54GNvtuzb3ZPNgYtAdLio+IBCenp+gTlTKB/bWLFe5Lsh5PWv+bLOIG45UZHyfmS25PN2eu8y/9Y6npyeUUkaKNWIIqay5N8VLtRRIb4Cw4UCNKHEqFc2M2wuU93SGSadLoVkoxZnRD4EuYQGNSGv2Cov40UiQUOUkHYR7u/uY53YD5F6KrpSV6AJ1Fuxs3ucO8w3/wo4qSUoR5HQXE5ZlMR2KnqtukX40HWqiFXJfjf/xSHgu21fl+UjPOmCdRLqKmKqfDdN8bi48k93VIWa58M3txXn1IV+y87od78H4FW3Yd0FjSzwjYDgkJmy0T8FxeR60bkoGEFpKNOiY1PVY8/c5ksKLc+TrTdPli+Unb42/y08ofyvQ/wOLHnI97GzCbaYhBA6L525eXWYBBTgCI1DvI9STvy+DyXCFe3z0rxnJ616XG4ANJUBoQgvFbcYIWEWBOK90QasYgNsFGkg15Ss2RoMxhBQM/feNCYUdBM+tRIg/GgDaB6wheV7jgT6D70AwiTNxxX54nddqCnQN2xS8tOheaEZIjFzx1i9xhnT89S4487OZzXFF2yczNpmNvmh6d+sdcsl5eYec/6SiK+ArfY2E+esjxQXA5wudzMrzXD7J8D738sE8kb4cLJYA+E4d7yTP2IVFfWV5XQ3btdqSSfnZ28tRDUctvvTNz+nNf0L5q5+SfTlSnN9CbAVzSfPfrQL9IkP/xjJ7YtynEMQ0cOBO6KE5MD3vOUg997pZvIPUm7q1pl5RNE52+2oMuQsIxDypmUz5QpHLTVyYWgj0rM/rgwqgSrEQnyIh2F6WE0ot8NC2bV3RZFikE7NZxrMxzBpaVpUMCr01DKPC8FrVW3xZFvtXsdSCIozT3YJ3D/e4f7jHu/t7rGcNvff96Qn1bkF5LijLglrZogSZ1zmpcKcYvo2QqN1xB0CWA49N4NJ7w+nuTvFLKWogSYy1NxQpcCPFIRsShHc9zENRJyEUBEQS4fZNsm7fMiQU9mmPGT3VjZ50ZYE0QakFvZn1PzkWxMTIKl0QhGYQJjvhQYD/xAQHc+uSEH8RJniToK4uYQ9Je/3gSfpqQ6+kt+b7g2G/pWTP67neSyd4c/8GTexVTJXlJLe0t3k20W0bxZ+3SpPVxfH7cR309PRg/BZvlybSNrxeGgCyqBh+cggg2aaImcvL1EXaVzRWOWh9rggzwCuKnH7btrhYJuXW3DO7yPlaKb2TRWPX1/SohEHuS/stHc7pzaDjvf8v9WfMcHznvBuGcFSP/JYBSLjK/nJWTE+C+/2CbD1MXoVLN1t99PfyJ/5OGIZYv8g+7CKgZnB7PhgKopHTjo0DHUo9dmMt86oqlpIrRRbTcRvcEYGQQKSAqIdSVYXRNPKmxpySOm31BiLGcnevQnsmSFOc0Lp6uBEB5+/fQaWCqxpZUeBqWOoXjZpXqgb5J1KvaqCjm1RyfXwEFzKvLg1n74oq6WoI1ltTD75mOIwkrYXsFDjuSa1C7OFc4FFRXFmaYZQkGOh9DZrN5Qqxic1kxPC77+OQ5ANY1x5yG4jl00wrLp8b6EP2Rk8r/h7A14LlQ8HzZzU00P4J5BuB3oXbwFjvUECkNsTx5owcJmM1jPma5QvJLIaeUOQBAKF85O2xn49stEjpTixNeC4SZp/xee9j9+22ZGxL/mbfARwBAAAgAElEQVTCwY414n25B+gRwL0+y/IImedfyxMYD2k+MhUy3h3xeuZ1jK8ynT31ewsXfT5mxw99SUbfaHxLApAI3v9iyvM/zkZvEapYKiYi0K8uKyP4JEsfuY8JAP9a0H/XiRB8jX52+rYbc16DrX4xodeLdFp+daAZ/bXS8Xe3lov75ciCYXMj05DD0I5mxQrRtBZ+oaDIFYy7XTDWQnwt7IkAXNTgKOh81nzXGaipklLA1pf1n1/RytjhzXfoAEEaZRIdZSWAG87GizXWtCDMhMfScEIHt2Iy57EAjsvYlOdSfI+3UOCqk5AbQB3Pfz7/HgXGYfM4D4arbEO5kbCPw6OfqJUZg02xrikqNWIQQ/f1OCcvl9eRcYIBUZU2a62hVA7v8rWt4fH87fvX2D8OS31Zx725F7Ohhzl9iaCvglOtlorUDbbVDLF1QS2MhTRXuRu5aQjzAiJV8mqKcH1WzXCsmeK8925pwnAQDUjn8owtfNNS4IlM5tJxpeRK5OB8bsqsRJegFzJBlnNfCywXOdR4gLrRPlxQTyfUrhEdsAo02Jug9ZGCFRj0ZikMdMNbB4T/ZEBqezuG6Qraab3/28pmMW+E4Ft8si0/c7a2EUkOvc8x0K7LqHqXYXSJeX/tvx7l1r7HeZJxvfv4RxDi3+VN5W8F+n9kUSbJvZl4c3LUEtrya5giPR+2rMRtYSkpeN8VIHyjTWVHPbhBkJff67IHn8dA9Li919zFtlay/1F+tmXBBkEGYIQ1i+dDIR51pDF5LhW3/PsE4BsxPoDxSLBcNZnZ8S44Q6uCDc62ys7Qp3eO5+DAkj6VLkN54fXUYqHbl0W94czznLnAwzB1iOZnd6m8EwCJ+ZELbcYcbf7+FGSXKqLNdX7nans3Ipu34iRn1kf4oj1bGQz9T2/9lnJb3Zc8aB9k9ki/F8IjqRD3Mw2G50GA76Sh2/Wa8J0E7+3vZQLjpf7lDbB9//K3h6/v3ve1epnIu7S/rn01MdW7l91MZZBge/Zp39MfLbkrfzU6bMzAPNpXirp/YnnbrB9FPUiyFQDKVK24nTCzQOVDkOP17N57oW/x3kPUx59U+O44rfcOJg3HOvCkKoRhQp8IY0oEeF6vLykkXMIYBIDdIrsnZasAnS3HKlRAQEXzdNdacXd3h4XuIK2jrw3LLycsdwu+fv5qoWuBk4WFb0370M+Kx6QJpHXU+xOINOc6C6OANT8rW551Jg1dVxjLcsLD/QPu7u5wd3/CXT3htFRULqpMXyru7k84ne7w/PSE74+PWL6eNB1K1X/LacFyOqGWglIr1udnFfx3VQRId489NXrUkHMSuQ6JCEtdRl7FokKTxiuoF1WwO66OCAGaKxFQbz8V7qs3PYW2xXbOoiEBe5ORexoFfW1jP4USAJDeNA99NY+K7oIfU7yw7io3xCRH1E48hEGnJG4UAXLdE8MfuMLeLfsh6cxA0J/6FTg5qxOvnwAX/h2fpEswJ+7H4z1BsvXQPmr95m7e8OgYSl2WGE7Y7hKyObp9Iy9wqb7Dr7ftH9J3FJ46rjxvIwvmLU2/rOh0eGf+BcUCqorY/jTB50KMFTmSg8Fj89p9G5LWtUo6VmvSOBg/Oy40jDFtlemvx+k/+r6KbL31a0JBOvqjv8nooGtzl5W9QBg7sCmL41P3WNn8TR3eVnswKhwozPfvDPF5fg8D3np/N8I5/0qaoBdBgeYjB2dlpFi+Xlh0kJmIdBgTynOuqFWjjGl4UhqGCABqRH9R/N56txCxKuzn0gFizQHOxXLNCgQWbQbiSdL1fXvOJtT3vyQNctbwuT3QgCkZzIBLWFAW9UlbHh5w/voNHQ2yqsKoPwrozukQNQiDCIgNnTChVDUCaM08bKmAcI5ZXpvRH3YoFMf6nHkodKgSWhJss6M9jA/0XAsRSMQUsUMgoDivmvKIIvcsiXqhta8WRvadzt1SVNHd2giRDQHogxnlvwfOXyznJiFy37YPFlZXM9Ejn7es5OviWbkl/QUy+tV5sXFFXeN3/trfRyiynnDEz46w4sPozvuXd++z1X2HkZu24gHP+I6GcWYWB3kxguOyZa1Gr0w5TgDM79HzhgM+F/cAnnTeHF3KpDOcEKXZeuRZUSWKIClJZoN6yspuEMQU0AKgyjtUeDTJkRecoq9aV+639n14aMZ+BHCSj1h/b+g0aKQqNWAi/aJ9ev7jjNMvC0ACBquiicag1TByJC6cDD02vymNP3AtjZ0nBNz98gvW334f3J0g8ppXfACgedG3df8MfndbbsZ3W2MtDFzsMJ6JIX6Oi3sIN7AQ2nmE3Hb42CEWelvr7QAepQHPHi3KWiEARcNnU9eUTqtkWQHgM+RniIxOelaIjSpiEQT0DCpto+92NHN2trRXxGgm86RS0LpgrWXkgC4EmHGueqFrOg4pRWFWg0XcUM/qNRPtieS3CUQCn4ke0DEUi9LFRGhNw4h7ZFU2Y7EuoqlAuqc4Mb7BYEexZyR97F0F6rYv84G9vst2T502i/7rKfCzwMzKM93d4+npMXDt3Ulxu+dWzmSJ2BiOaFRvp0lXozefLSI8r2dd1zLOL9l5duP2YhEkuqgX+7JULKgaEr51ddoyuS8TQ9hwV+t4khX3pwVr72qYTpojPeOJspkj76/DrG7vnO2bXXTLWw+5QI0pEm2caTz1Prd0JfDlnWljgRkfdEGznVGK8ttrX9UBwEOxA5pL3ai1MPKyNDcgRqcOahQ8yRwtamyU7V43qKtGINcYk1eUl2qh6Z2XoeDbe+WYzszhiDf35/pHLvjjPo2c6YNSmZ7jdlwx0TRGY/t1zoXOlPkH/47smRIlRylIIPMwfnRlnR7531gm3vcvUP5WoP8HlrCuN2bZkYDyPmKh25t5oCtmm/KybZGyCH41gPC7MdTvBZEL3V6ZymtlZkevy4X7V4tsRTHp2jr1EcBXIJguAswaPds7z9/mcHdzv52So0CGWwBG1pZb9xcifOeCyoRnED6BcTaFAJIgeBoLDeFHrtzX9c1CSq/HzD5VUMAjbLsrzy0/u7/bekdvuo9aW8OKVHlF/y2HgOxqTwmTImn37jz8sV5ZyI60/y7g2aDTf2za3lz2+2jeXXTwzl+t3F/AUa4Uz/1/TIs6DHQk5I3+7neSSYne7B6gSvbblKI/C3lea+tHV+eoj2Li/cv9H/zlDOcuffHXICP+nDLUruPOf4oS3Qkt2cA/pFpcef5nl2Fc9aDCCKjyXD3g1AxImu5cds9lYDxPzJAyNmKh6ToEAvpAKMxon9UPZ3htJCGBrS5j0DYTkCdVbNdasZwq7u40dKZIBzVlzD59+mRCP6CUgufnFX19AlpD6x3tvOJ8XlEqo5w5lAxUVBi0FMbD+w9YasVyOoGXisWMAe7vTri7u8dyWnCqFUtdNPcf2T7gEiH41nVFa6t64Vl+V//HRKYcR+Rla9JUaYIOWSWE3RE+1oSWkccdoqGrnTNbG1ZTmhFrSFti9czvTj+wgLuy5+gAKutamvDDjR8gHUSa63Ao6GCeSLCUQM2UMwR04NzOI32QRxKAK8/HPiOnGyTRpMEIAyAxj5oZ8g0aY+wTYNA0w7PwSE13+xl93Ym+pbZ/f/m5Y7I6N8aY+bfT1VsF7uH3G8ECLtR7U59gXrLR3lZ897p9AGioYiYLTxqteF0EQbMuq0fUghICuAHjjgWgt3ZkMrq4kOt8qv5Amf62phVR/bic4rXrmGkgpYJ2QpPtnqPhce7XtZRQMm6VHlGX8zMWBjyiromk/NibztEtIzpUn8eYDitIqK51D/PJGur54H1XgjvuVRu2EhFBclQzON86SWw3XHRaaPVa9pDuDIGgUIWIzXWhgLli0e20fgl8lZfKcRFMUO3jFH9u7WqYWVXcP33+jHr/gPb0DHOJAwpAhhOFPD6M8qlcafIKA8wLntK6AqH4dsWK50B1owTHeTqmFMOCFEdqZynkKbZD4UZdsJzuAMx4DbrPvnbQOwLeAfgK8Hsyw0KHJXkxtL32uaF8sL3/db+rRGAGCwA+MPAFcNVQfV/Se2LjGfhWBcDHEpgYS9olM0zdfiMoKWw7fxyLSvNreu89gK+DR3SDzQo/YqpEPON7fJr5ZYeI16A6HfwedahnvvKnyoMOL3f3Pr+3lX0yuvQu2t61Q4CwQPDo2zzlBx7K7+28Cb4BeDd5bxe4gnqee0p/AVd4DlA4hTYOowWTDbKAhQApFno9nfVf9uufx+j0vMOQ3i0lhzCI3qPj6+77PNKI9E9B4g2nghuRC8MCzWzqfksZNMrxs33jm3uS4Wjui885DyrVlMsiDieAMD+wjUOFUaAerQ6vnecahmEDlhMTyOBtA1kqAIIGgjdvSHtfAJS0Ec8ATjBvcYgaKWNERyAgPHFbU1gS8tPebFQdVRhcBAUFXGB8oEYjU5CpZ5qNJhNhrK1hXUukzHSpdXjczoAm1sN23jQHXEzBz6brtRDnbjBXLEWmQPkWMCtPI+cB8w6AR1Kj/6TiIzVcRcDz8xOe12dUrpDe8e3xW4y1J5rjpaMxcUiBa4cOQMyJhYlQzEhCR6drwkWNrtnoAjYDhVqKwjsiVc5Daann84qODpaxVkuteF7Xieq+peR0HWouty+HholT+q8L83JA/3qK1EhlC0z0Vhfonu/+bgeROZSVirpU3WNk8g83aCTf+4aDuxqsH4ERx3FhvEjj34Br1jd53Xz+aPlzW/tZ5Wef1X3dt7yVtpEzZf+a+ZT9bzp49Hf5c8vfCvT/xBKM9ThCjhw8L2gzCzfPW+aFibBuDiCI8BuA93ARJfD11WjRe5K6idnq2KhJIyjpwle3178HoEomfMZRjlezQjQ0JWQmc5NwFnC/iYoSRA/ghPdGAU8JDxKZdx7wkQseC5uAnfEMxlLqYKJEiT4n/Kx3YFIFm/qhe/+sbxvCv9Acd8BzsrdLcylAeJ7XirulWqjbBbUMwUszYVJvHWtbYy+JiKlDkIQnx02Nfvtc6SwFA3ggQyJjaSGzUOWnlxsr/pntO5OS6/33Kv5uK48EfNis8b3slef3RtfmcO5OrH8zRbl7oGuYdsKDEL6SZ7GaWPYbh/G6+XvrbO/hy23tZNMcFRTOEqWj/mRBya0tbuu59f1LorC/fpkxjCT4+bbyQ+KY9Pv6zK8AqjPHhMgHuhVhZoLs2GN9K4Tb94KAneHKsajU9+U7FHIY7J7n1SzVVfgBqFJ6J2SynGFzB5JAGYRaFTuth+YjiixkYzyTvQqRmPy6LLg73eH+/g61Wp5yISzvK2pdIGQeXmsD8A29r/j+vePp+zcTLKiwfF3PoFJwqhqF5f7hAQ8PD7h/uMf79x9w/3CP5XTCcneHQprLdFkW9TyvGg6wFEZrK56fzxDR0O1P5zOez2esa0MnFXAvpxPqogp0EVEvFNG8aO3cINTRVsOxhn9DYAboWhg9prSGh+gtkHZGg3pkdBINIccqwRUAVCrWtamCuwIQtZT30IYQRD70Lq7Y76CiuTD72gDSnKrMZN7vQ8ojti/a2lSoVVSx382z3k21hyEgdHdmHEIYRgWS94hErl8X+PdnJy4yAy1GVh1Bw9nSfYRNPj4ReyHqz4OQ14S3NzWTz8QrKnjTCA6587mm7PW7f8sXm0a0g6MmVFo3aEbb906vgqDhTF8YNoFwWgrWswt6nQJxMDT27DUByVDOFDAI5a6AnoH6rgICtKfVwqSqB5hYOggRQoPgjk5otIYnHYFeDv9xqUQY13FWo5+UaQyaHuTUW9uQhHmkxyXP0wUy6+DeET2f8fPFLy7VlZXkFzoyGUgzq1GP/faIWn5f4SUHz9wFoXBtrQWv092Vqm+6RrfRGAQV9Ibp6NUDb+cj3VUeXl33pIjh0s0ZI+eRXKnA4R2+M2gxHMTEw6DAWm6ujBY/fKbEYVKhcSecz2cwAYU01PPIJ255H1vGSS49ICiKIPCpar5ay//prZPXJQBYDRaYCPWuAljw9PUb1vMZocxWP2T1kIQYHnMDD8J6XhVHVU2t0FtD6wKgAQKUYu+T86+qcgrlljSsIxifbbexCVxpE/x45nEpVj4Eqe4JN3vDieLdd8D6pUf7ANBWUYLPcFP/3MDvdaH9BBMY5CnEgakDpRLoE4Et3RuXojjd9nMpJfozec9a37fKzP4lD9CxrGj+89S+QNDwDCYNY84fCPIVKB90StpnM4z8oPuwk0C+AUfnohNp7bHnHWeaUJriaNp7KWf6ptDmt3s9nuAw3uU9g65yblTDst+j4WkozhMMzvxqTBunHL+GXtx7PfCh99vaakQgfAPBcId8VCUbf8ZJ3lvnXSk61poAVBAaASv6pIByWJnTFXR0VPNpV7kNxXvMHGf2/te7oDHIcfKEN2FGJQ0r/ZHGNhd2FJtBluP2dLv9/kc8z+GMBcCKL0r7/v/svemWGzmuLvoBZISkHGxXV5/z/o931urdVXY5JylI4v4AwCEUysl2DfuaXmlJMTAYJIh5QHMqdm5uoInvbFv3r/Fs5T+ojbqU0UA3yixV2q/z5jWwQYQJ6jzqzjqAOcDAI9JR9bWOoWbRlNlS94E5/ZCVuCLFtdlLUUHxcCF9rsPgTIQihGK+TJkIJxIcRGlmqPKoQatkiLQITHekCCVCYgRHUqdbCwwKxKDQInIDFWRz7ikQpJSRQ7JSkL1Tk1Tezw30dWY73qU6R5a2V3uclbPuXncockeS6uAdACoMScVmkVcGWcOBFu3veNkRfd3vm9A0wtDZkS5l/9OimS1Sdqh2vWgrJ6IOCP54g4cXeK6KHYy/LRCUQsi5gLjBNRGjSEZkwkSaVYCZkVIymNT7GQLigHmK6qxRCiTD1kfrgjOAyNHkzqK42LZKEuAKB2RzgvIa1SSCIwGT9GUtWtuZ3LrgDY6ggrqWfQS6vq+OWXq4q1gfcCVLsbT1BQIuQAxcy9PFSfUKNatU7VsdYJgZlAmZsurfi9OW1XoZHvHEQUKErro9apBfh7u/tb0WbluT4b7x6Pdoo9vepUjztdyyua8Ac5qhSp/664wMP8u19/TI1wDwDC5nw1rRDbJSCaiZPIZnOk79BlK1Ht/P9vdqPw3o/8DGhKoUAGApRfRTa35qOk+t87JK8NMJnX37IBp9PrQq/L19jFub3ZFL94CzK19G+LLx7fkR0PgT7pm77ravfTb0tDJ++c2O3IgIN1DhL5iCPrIS4MCq6A7uqebCqEj3Z2lcu0Ep0+2C+LcjTzXwa83VyEE/gzIInk6wFFM85NSM5zlrWrlKoNr4ddKMIanM16UBVF7l7F0GItFd17c+FZzz3PV+2X5yW8+/nvT8k4jglaCWcbhb7wX7PNicPxHO0y+t2iMBH8RSFNqxJxJ8klt8oZbnQiPTgbexPe9l7dr9+rQfvzID44jtN5TV5892qW0rMZ5r1RO8m93vt+4vw6OLzD3TJQbKbxnFJcHgUh/PHSccLDWlqRU88txrINrNgdWhrCnSLNW5EsBWK7EqvFVAZtboc6aApVZHQ+1DnyNgafXEnKaejZdUkeMGkmmOCEFnkwsh5ggKDNoBZS6Vns3ThEcKKFyUBloa9RjVKL7f77C/usLV1RVurm+xvzrg6lYj0cM8IRAjp4TIoWpuBaq0WVLGaTlZlpaClBfkkrU+OzNyjIhQJQUBltFFndMkF6SiqWaL5Fq3OVoK+WCfEEA0JARFFmBJ4BjAAuSsqR95iqCcq6EAlrYupYwYyCK7FXKIGZJNIVAV/a7OUJqeUwEsKkYg4Mg1SgFEY3Fn0dS9OXf8jBvQaVR+dP6Kuh+ZTKmT6vq7kgOuZHPlmvEYrnAaOZK+NWH6Mt19275f6ZHf1s4Z3+Hca5UVfz0fYzMvqA6X67bJzVPDGyu9Veu23kHjBFwilGfoVpCXPJ5/TSTH6hJ/HFukWGAG3bAqtqnUWzw6PZlhz1u4CoiIeHx6qu/zpnXrh7thEB0jhT1Ce4TLet36xBuaOzGc7a4Lr7JeJjeQvsTJvbfVyHM0msCdkTyEUMtleLat4FHpJlPllJBSwvF0AlmW72pkXL3va43n9f8xw+TF69eyKQBzZMpqGAGBRZXZQxS5TawbCEJg9LXN1aDthnXLFmIPkvqenRwHd1JyPEOVxkvW1OjV6EEEIEMKw2umG7UHmws3cT9nvcyLKr+JG4tzQgix8hylFHDQdLuSi84FWxr0ijj0XjHBsqSskWOd1jMwWcr2gmzWzSJtbOqsZUZskzuL7Rk1WHXQa/2KReVB1KjDtsjNDNuU9AzGQKW8Pro0uKhnbVq9dird0IAjBQDdWBa7iiJtPPa+agzt0o5Si6ls6PfcWF6f0Rn7AenKYTQk6S7+3pvgtLkz8p2721tGonsBrkdPIroi4GGU6z0VqqzgvF5j/1uga0PzLzTvRj81yhzDsb0dby2YAYixB2N0PvHZaPiZhpTqpRuT6icI0eEVlW0GlQNAD9jLbR3nLLdANa2cvweoydHkc7EymtdnoPH2gGjqduuZP7oDUufsYwDW+DTf71Anx8/lWXmlHnf4JjWoM646ekwQy2+5JvX97l5T70SwFP4/iA86cz4aX7RODxoe7vdT21bmDEyGV6FfEzHmConU7WM7JjozbDwxQeWj+o9gvLXuUYZGlW9H8DYDZaCGb92QGQBMojgmAmCRCrMshkO6TSMwoykp3vfnC9R4BPKd7kb+ArbAmwyty13KpI5rKNV5rRRBNocx6lJtN7ehft8LXF4hOI+iM1jsyWJ4uqZuNwO/ZNeZYxN4m1Ptixzj2xurI1on+tT38NbrKkcD8DP4+sIBpzVZrBSLrTMzGU1goxGEEEyWdbrjcB/MeZs7ngIKQ62kpx53YyOgcHXCKhDAPh1nTea0diQNviEAO9EAnBd39gssfe8g5rtPoBlVcy5IXNTrjzUy3zsVGG8AQRHCkrLxSepMHhEH5wwti+OZW/V5JanNJSdN+a72l1L5gYqdGyIZ9pdO6/cznr+vvTDB/9A20v9XtGemoTrooMkJI6e70dWlB/cE7zWtA6Gf7a9vPw3o/8BGnnrUEbcIyCOFi6Xd9rR0cOJHVSlCK+RwI8AXyEjQ/fONuHTL+Ok9ioxpu+xouxffjroJWynvOhbMsFnzvnZFj3l+2TGt90TVM7SPHroSnc/qbSnq+fjEhA9MOHJApIDIDOKAENiEZ4JI1vT6bjwv0phVm4FBKFtZz9fCw0v4NziMFIBEEEgNGiFMprQY4SiLMxvZIjOUKXBBXOcLw2cdizQhvB+PC3FVpgBW4uhq/P2P1UNkTUBkmyiK/9dTuGeozo8mSLTx7c9t28+9svl77E4/XBiip273a/yyawHuN/Yc1ftaFcJjVwv9pIUW6h3NeN7G6zBXoeSd0zdCUb8aroaW1dkBCF//IOq/nOPTH82evnZ6/rkM2Lg6r1Fs92u7juS4JK681O/6rKKX8/XevFc6eLjAWK/paD+et8DP829x0IhzqGDNtxp5TqTRBYDWotY657YfxWpB2rFW+89SeGdPp6cDnaYJIsCSFnhK1F6QccW+K7jdCD9sI5c1zYAQrBb6HGdM0wRipdMhRoQ5gmZCTuoAdjyetB5uCFWryRxwfX1QI/w0VwP67YdbfLj9iP3+CvvDAburvSoQCFieTioUw4XsAkkFp2XB8XTEkhZIEU3dnjNEqNJWNuOHK3ZSySi5ICc1omcRMAWk5Yh5N5shSA0fYYrIpxPEav6BGKfjESHNKEy1pp2WZfGUkVrL3GvEFrI0dQZHBagRLRCru25KkZJypePGLtb3EGmqLedZpFOyBxvPQLNdKVS/23GGKnJy1ohLN1x4lOKgSBBITZvU3B8HTHDGQKzj0amDofNdsTaQX9LRUuv++baBIOi5jle3rrv3bXCJ/3u5XXrupR7O53Ugz6uxDOzV2srXn+sft3qXSxHtev/q2pFlHmClRggSmpHFnk31+m5c5EpHf5ZXeTWFWTGFoZBG4gLIpJHuk0QUKPwKgKfHI8yCefFdXmwDC9TNrMjQn0hzCOsf4wqeZuwcZm7zkWf0rvLx1CawB8yL+6Pj26iPuNzap5ebTiFVpXo7bvNqkWI18ryLNFcHKStRFaJmLdntMU2abYuYIVKq8RyshshcuuwXRmtexwes3m2A8fMJG/fKqi8CkFUezaUgstbw9MrQtZAwwYzkATFqyQ1i1FIaRBZ5btHngNFrz0gnovQEhnMHwwRbqmallQpjVI0PLKQlXRynGZgFSuDI5jul/ZXi8jXgiaerkcSj2ovKxESMp7sHiABhChDLCNCnp3ZjjXT6Cq8nW4qgFKPTZqwnuy6XDMcNObXd7/qAnN3JTLoyIl4aAOZAg6pD0TT2mtJ6WEtDNEShxgaLEOhay+B4Rj6nYuXe4p6vyOZR2nyjRbLRtY6DOQyKeKIxVTuxxojXdLX+TqXR86F1grLcifHHUp9ccARhX4Haz7Y2wyuY041WvqVrQO4dSDveu74rNAq9ztsJs7RSLmHlvNCoua1Fh4eir6Md6jO99WjrvFG9hnEA8LTa6/orQkP+978cIBCk0wK5b6mn/Z4imhaeRTTdeLc32ngOAB7qmMhKJhGuNSMiuvTtjlLadq9ZBrtuq2E/oTSa0+tgiI2XJ4RPjPJF90P4SJqKeHC2IDXOYlXu0XRhmv7BnciukXE/4jIfV/fujWxouvrpXxMIhNNv/UyP3wUtbftWWz/zu7QVvT7PFuQlG/xo58yEbTrh8+91uwjmHEUCNvyqcoHUFOkcJ4Cs1BJxxa0UdE6sAIPq6WwtCjSCnO1aJiA4XAJae5xU/Cn2XlwE0WS5+K9blPwVc7gF/+ePep8vxkLAbOWmFiKACybLFDVB92Dy0hA2RyJqoMxS1I0oTro/SzEdY7K66AWSBULF6I/JiNLoYeMolG6RIkJ1WJFcs1QxC8IUsaQCcSWwyVylKKg553wAACAASURBVL2vHkw0ygdMBOKoZT9ANUOpOqZglGle0XqVLq3pFxRXB3cSQ3O6qjxd3X7SUHQFqu53d6K/REj17SklTLO9FwXV5bLSl1Jy5XM8y5z3GJjVAS2prjrGiFwWLR/g2JkIUwxKe1nT95ecMYEQ0GRFAEgdTmK0mucMhaETgL0Qnkiwu+AR1SjihTl3qrnie33pCgpySXYqAFxqybrSzSBBsGTN7RHYg+AiILE+X50xg2XlM5pYyHiRbLaX3knRX6LnA891UNL9/9e1jsB2R/r23hHWjBZGINZ4dt3v655TuaSzM/TM59nVnXfNlo1DeWM/bxytRZ7XEaxgr/IA5HLZ+FLPOf9donPfnfb9A9t6Hf6q9tOA/g9s6lnOdTc6sRYTJN2QXqN4jNmrEdArhuDrqv+bIvi62qXNkPXe7fv8fT8CKZx5kZ690+sQdI/I/LszeKr/d0GP8EiMjyAceyU4MXzmrojwZXi+CrdNMJWKyMmERQY1r3K/8U0T5uvv0YV8lu6vuPOFRZznqpRoWQx8BKO58XyuXo/T6JlfXTuz1J/rqLYe6WmTfrbtdis42+eXmqdu75tADfDnxvPWrsUiEDCmeH8kwX6TexghDcM3+e7r2VRFlxiW70ug/2rW+J/fOgPJK2ChRQCNR8djvVT6EoRdQr5rWN1uEVWfcrFdOuc7Y/30tzPaXq+yRTcojWiGp34WmLgq1z3KjwLXe6rRE04KNXKiVUsfEbR0F3tNTs06bmvbC7/egzmcucHf+RkfH1tpkjhNKLkg7HaYnp4QRaPUVQGQQUyY5smM6NeI04TD4YCrwwH73QHTNKlQDKlGFYABBspSKbaSpFpzxHiNQMiFNDo8ujFH3y+yGnQ8lfDx4YiCZEqV9ldywe6wQ+AJHAhhmiAccHx6BEKAZODw8VYjGgqqQkQVZ16znlCoIHtISc6gXExYozrXIKrOca6eyCWDTSkvUGcFAGZkBzhyVc4742lmgqoA0p/d7qrGd6gjRmegcHanRUL6WqP1l3q4ed0+a+1M4+Sg9/Itz527hAJeREnb43nu6r8LzXgz2/kDm1XxvDg5anLcOqnId5NnrKiqwBN9BjC0lqkZ5PYKs3zUMkstYmroonXZ4alXtdUkC+gN/PQPaM/B+6s7+EGwbvJd/+dGdDLaEmLU0hvzjN1upw5XRJotZFG3zpSSpipPCW6xcur40njrxLxiftpU2rfO05vsfYBOoSpU8aIq39wobGOshL8Z+1tN9D76PFRDurDi8VLI5qFFxTa502plF6vuTVprt3gpBelKjJCOK0DMycvxt41dAFhsbkX7UMOEj1nMsS6XBMCeldR5r+QEYkIpoY5Lo4993MWM9E0FHkJESrq2NQuC0SCthZorz8+kxgp3MJPOM0eo0TMRjZBsa0ZGvlxhz7ZO1lE1nttSc0RBgucg5huCFKA8mA7nwUDvpmWca/ueakaD52BrzeO68l7u7MyNOUlUfNRxx05vKzUHBEf73iKzCbsa7alwfGpj9F7vL42JLAW9fvp5EYcQXaet1L49WhSoY45xZgDGGtn9Pa9tHoE+cheNM3IHDyKvM7/eu/q9dHRF4Um7itgPfBbkynRIerUbzitkSuuD4KihGa+ctvlvj8jvI9PbZ4sw50+eoai5aKTPJ0vNT+BPwfhCh3t3aCwoXzSislBBkfvn+YFu8hOpgVffg5px8bn7oWu8NqIvhpsn0e9/VutTClfthDzPRwpclrP9ZRklq3xnvHCPo1weIMBK11gGErunFI9AVyM4QdnjsnquptV2xxICifH/pgPOTIhFcBKB/M8Xfd6vpZaAdGcNMvyYTZ6L0LWMQjZ8z/5izrsQC2FnZCrKP4nV1iYtG8KlgHKbQ0hBKV4vXRq8O4BVzx/FUDXi2UQQqvPsjixtHnzOlqQZwjQw6hwzFCmIFCsWIy+j+R1aL8MCIz9I3V7r2/fg+4NRyOPxCcTBSgeI6qOJAGItMRCo4jZ3ks5FsXzwACsBdlPE8WR15N0py5z0fA183CqyPQwFP7z0xhpWe9w9m05wAiH5/EgrifKmZp0q3S8oWfn6jKKJ3SSOBszK/0Od3EsGZoBpAnOEV3EB1IDOzJqVDsqrAKglgaoDm/1B2vo7wej16C2grnRHf7a/U1Oc07ICe6v4xuCfaTsryFZ7kWfpQeairNuev9npz/bD2k8D+j+yNUG5EbPOcF6KpYFzJtuIttQEO3WDiwAfBfjswqyY8fwCseq9bp9ro4ihd6KKXTIQDz/74xuNTgSA1UTDGdGS4bMlLbsu9vYiuCf1xr+FenzeCmEqWo/sFoQnckaU8JGUnUnI6tUIr8Fn0WwuynYKEZh3nBBARpDZBPd1c8ZxzQ+4oB9I67p4qkNyA3r15EH11CzFGYA+dTtMYbB6yIqQVOH/hZVYC1+vxvmyunf9ux/WsxLeG5/7ze2vomrjc/ua5r3xfC+ain2/Wji/ZG08x8ZxN8i3VOzq/XwcBJZ2g3uhjhHsvhNGFuS1hvO18LTdqkhjAqZ0R6n79YZ2YXjfG699byjilWZOvpPQ+M3tgmaiV2utbrDPMlzbSVEb145XNphQJfLWtZfh0PDoO1a81gfcvLU977mee1RHqz/gYMcJYjXJPEUxgcC3Sgd6ZzMlQ93bCrTeFxHCZAZWU2BopESjmFXJzpr6uOSM5WsevY1N0iBTvICl0o5KlzpjbFXGkyuaXAmghhK2dL0a8a7PnOYZu5sdwl1AkAACgyJhnmd8/PgB1zc31biy3++x2+8QYlQjMVTBrQohdSorXRSaoFTHN0BrjhKgx6yunNYdBZgKpmnGbooIp4DEAfmUcDrq+7AAKIJpmq12r0ZKTtOEMEVIFJSUsKRFI9KXhLyohzybAA/RNOs1Y05hUNZI90CMxLBUwIwiAKPY9CpRJ1Kjy/6wQ8luAOmi/7xOesoQyQ0enT8woq88JCoOFdMiug5Ma9P3cCuWhUe1grkUIOEMB4uMvyuMrn60616gBBd4gzXaeT2+3ebLLvb1jOZ15G88w8OqE9nGgn0fW+e3VXVvaGeXu/vN+UWbXuIby3LJwFzxUc9Q2qVF1vwBjBc8j+qo5ytK0Ss2ujV+AKpkA5CPBFmAeGDbqHpx2AcEBCxPqXVANCjkqlMLv2D9WrfGnqhBpiretmhZo0nVyblHsi8oXV41ludu3NqEw62vp4c+962XlSThtIks+1dvOKeWvt2Nxp6VZJpnzDvNNDLvduqoJILTSY1/y7LgFEMzvoMvbk9af+sBx3EgtTWjahobO1lnb2jGc+dAAI+3ImoGac/m4bvO54HZM534b24R6OxzBcBq5IoZxwHUaP5iFiEigIVRmEA5tXslA2ZEJ7YSIiCrQxkA0vSlauC3jetGf5e77VktcrhPg6nfUkogym0OBXBzqUdVe4aUUgQlL0r/mKHGmI5uQECkqdRFgJKT3auR7Clb9ggrMdXu0REpXWrjL7mM67wyfqiBVSC5rbNIQYgaq1lK0tIogarB3Ba5Gkl7RwrN/qLcWhaNonc4oDp/ej0TqVNPsXe90xT1dMMo9wVy51GepM/tmty7TkYgOFb473egsilaw5cx2/lZIZG7ebsG5EFNceHKnfGswwdBQa79al87EDTyPOOoDg22c6LpQJYKL22emahGNrqhZoUx6ri9OdVYY+T4ISD9sUfBsc2BRd4LBMuXpeupnzupxQsIBxR6NFokNYp3oj1EngDxaHft1Tlw/ZXbnqdH46Xan4dgVH4TKy2atOs8TbeOQXD4FOG6PWU4WZ1IpOD05WTznXWffQb4F411Lp+96FSjLZkKMu6HOV2zUtLNrx8vBAR5gGSP4mx0moChRjrQyl35sZ7kLaQG9D/FiC4drq46VKCjtvCSFzbcgd9xXWPlkhx/AtaXraE9o+QMkqKlRiAg0/mRKH7mXGr2A4iAiiCIGiHFny2a+aN0ECJuvbRxZBJk0j61FjpQ/ucPzP/+gPTfO5wY2BUC4RozHmr/bPM+/XKDq8MO6f6ESIzZ5qBAM14dydOHe1kNzXaZpGj0fQWMAikEcScrfw/LmEH9ThVCSgJCMRlNGm0yHkC6yF/ioAFBFt1fpGi2qx54K55rNLPY3EruHII3+NYXAcfGrKTE+c2W8U3xqdSxAY7Dm9x7qdtoX3ttx+D0bszUJJoRI5eEKJqZpzdKe4p2rZmukebuAKdR+wuYCTFGy8bivAIAKQiFzVm8VhtzVngYrzuFJAGWLvrf38GdpjzLQgKwB+OI9xnPR35e362wOpWTfTIVkDCEGw9W8VzWsgIcIyITOEbLJGvrZJllAwWIFEvv3rK3eiI2kZZhYIQdZyD0u4jC/LbT77e3Lbp4ub185Wu3QxNFaPjd76uN7fjmWVA9iJjOhpAhb3rnS2RkfdxxrKft751iKk9jjiV+/VufvSlyyWXR68dAzD+j/dWR6PGH1ZP52S62xm493y4BRSkZqUbliGPqaowtRSoj5Yx8S8OtnuR916ciQ82mLcL9WgNWu371o+uypqUhR0jPP/vS3qgouUrgNDx48B4noKyUGWTCP0Jjhx3RO8FvteMI1zWVo37cCKy+qSLUCGAiAps/L4rgmgqCeFqvVkdO7Fmu8ACaQOnMlR5rnuRFBFyZxn5F5Mw+xCaaBjN6MKln/mRpDQM3j8NsqWeT1QTMVgIgm0XDn1/H0y1KEyOMAappwfRGf89vaqv71/vnYu9/MWprjORrd/yPb3d0biQHdHRe+7xP1f6W5sbzJvLIEHW+1Q7SCcur1ivX+qIP56v/VuLZ7lnf6Y4/37paHTvVlJ5n1hnqP3Q8/3BuaP2Og/JhOG6f30JXhnbJdP0ek/ZlN7HWWzvf23leahkq/BLwYiS6P2UN7bQSRoZzw/crrFNhwlJSumMX33Y1z7snkgsk7XWVjoROVUkG48XSfls6cTegm+ZcvdxX43QaUkxB74pdv7BGIgAaSciMXDLuHx9AIByPR1zf3uDm+loNJEUjCzlqfTfJGce7I3LOoKllWEFh5JywLAm//fc3XF1fYYoT7u7uEGLEfn/APO1xuLnCh08fNKqdJwgJkiRVoFvaQCkFOSc1krOmdy6lgBLZtKjynZkRY8Buv0eIETnNeHp4rFllBJoSNpghBECNfstW73za77HcLTZXzQmQCAiBMU0Rh/0e094MRFlp+tPDE1xhGWLEPM8gEFLOWJaE0+mE09MRT8ej1gRekjk+UDMAElUPfvesV5gncwaUria6mBLIlC0iFU6IlPfsm/dlCBKUzWHwDM+vf28Af3ddTy3qJYQBnt/bfjQlHyjaGaPzuqefCeXSDC/DcWzQJe/jGb5twHcXcP463Xh74DMD3WpiNS43rh2wo+FTBqOQR4BuI9hzutQiCxptqupAiJVpkiLgYFl1nmB1h93Qef4+btyc4oRpnhFDAAdGyQUp58pzq9OzpcdlN44BJAQ2XOA4x9N99nMwppft9tVqPGt98Kvm6JnrLlLdC8v92iZFkGRRY5AR2JpxpBtPKaPDXCFqxjSjV8uieDOnBH58rPcupxOOT0+4f3jA49MTlkUNsRUfdXNQM8L2Cv2Bb5O6cXNWB/be0H9WV8zpo+HQkW6vH0D1GS4vKk0xeW6aESMjxqkzno9/vv9LsdJcKWl5LqixxR0Gm6Oajo1D0DcmgLKuQymllv3wFMRFCnJqdW3ZDEDuAFLTrWdPXawGk1y8hrcAKAisWVpqqnNqvAJQIMJWC13hQudhstS7rLVcu7lVnG+OZqS6EHdoUfotKMcCOrjMqvMrhSrBqOm00RTsFb6dT2HjXUQAsRTsIg2QRPEG0YRMCR7Zryhdxyul0Up/QMNTqKoHlex7KUvsFqn1aatD/bU6BoRrQO5EI+wB4N543CtGudfrMwqKRZvH9khbmQa22o4gzIYrTxAc6loVAeiKq6NK45OdthPUQN3gu8cirdBPS0vdHq4PyT7XNiNrg3gdr73HWYQunsBWB90PhusAudsBOJrxUWulE4Bww8h3GZW3kOZ83b9HjYjvXmjBk86n7OEUiztYAmQsVTHQoDZmQIb36j/7AJle7rz68EnHSKHqYsQM6/m3pVP8q2lPs7qok034JaB87sr7IEPg6QVocFpYt7bm6LI1atqBLd6sv0+6z75F0Wh2EdE6y/L6SL/aP1E1BPbHnmt9VqXquAtoycdX8JPEZGn0NcuGgNWpSaxshMFysIj0GALmacIcA3ZhQmCGBCvXYXhVikDYSsmI6337DKTZMnsAaI+wLF/2OrooGumelbak/94ZvtVsCCJ3bT+KIDGwJCAuJzySID8+IcTZyqUEEOm+j0FNvMXGRiJgEbAUpMKdzOwO666fLiYvrvgzp0emjw3MyNB04CJAIB7WkTq5xaGXgGYwrnjJSlpytHlSI6nUHETv0R+MrWbXsr2XJVtpFGDg5Jz57Jh/uqAgaKUqnofdDC8bQDguR8yYq5Hc9cwE5y1a+nOnaYzQsl0YbCZPOw+gkK2V6ZjBLaW14rV+zIJl9T4dhYTvfC9JkKWg0MjrXlwM36KVj0HDbcYvK69IoC5dfRF3gLLSIQaYDEtJj4LldFJHjBgwTypDz9OMeYoAkfFCBTElLSMXkpbUKApPJKVuQJFiWUp8/hp/o6YIRhZ3AmmGd7fnaCacdk5Bq7MpvBNaR3y7hX2/c/sBjxBBdXisJRCGR1K9ULp7lEaJOi1t0QLn0zv3Bld3VNrQlyqqNLXBk+uA9bzBva+bzYXztGQDv7iz1/P2HgHrZ/su7acB/a9oI1dcWx8xXo91TLW3UgSQZPfYVYZgvfYGOuRLQEtbJrDYitbuNsZSh/pa8Fjd36ccbwLMilxKQygYrpbVlf0jVuoF6gZJ/dlmeHZDMVnEGyAthVzl9FcimCGym+Jsls1nUQQdbPxMwOGXfwNfBIHusP/Xv0B/EDK+4lYAkmKpa0hT3K1eLLAqBLIzdORRLCPjFuCGuGZA72dD0BQaRFp/yKMxQqdsCKbAc2ZOYcJrnqtSJeWCbJ5zys91xLpbid54rtet6s8QtVpGq/ZqrLN6z/q81/b3xuCf79oMQP8OGNYjzAEdVm8g3xs839mx1xjPL13y2DHIO6FV9DnQxOPnnjWqhwFUgev8yecM+cvNGaJtLCMXnrTZNhQdqtBuRwWdkD4IeX7vgLVe9QbvbQ1vbBMhNkX8UDLiDX1fdBJYKZCpruvbdkdTrmxpLr7X7FH3OYp36ycOdwwWi3EkW6l+OhA5a64gXeP5Zpyy307jap9X9TodTfsf9s2/862lC6QWQd2uEBPqOnhpm1DfsDNe5JQQp0nrcBMhLwsEwDRFHH87rl7aO1AFO0mbuqZc6wR5IhAzcs44HY/4khMeHh817V60WqMEcAwIKapQbEaC5f6kCpyIanjOIri7uwMHrSeqacoFoIAp3uNwOODXibE/HdRjH1qTlRKQT4sazWFGeYuuZmKrl8aVZhbjOUIMmHcz5v0ek5VJ+fK5zbdQUzRUowdaVH9JGSVlzPsDlrxASgaDNJrD0idOU8S8m3F12CPECSUDaVnAFDSaIzD2ux0OhwMEQC6Cp+MTHu7uAREsacGyGN+WtOZlYKtRCzGJURUF4/7QOnKl5aW0ObXanCmPcGSfzrea3hc1VTtV02EDk3pff9y+u+Gq8iLbeKZ+rPD15bZ9Rdvnb7rtzY02v3XqcVphmFcivnUaScdYPser2b04NlcUtI+OTq/W2lBJ18GIR9ra0HhshUp71hKrS+FaCWq4Q/tkeBrakQ47vfKfTdnsykCC8q8ohGmaMB1mPH1VBbMcBcIK1wF0UZFPFhk872YcDgfM8w4xRqRlwbIsOB6PeAKQc4KWUm+AqhUidG+VIkDJFqkjdU4U9yhu7r3xacgKgu54e02pq0zDNbXjfoKr0dKXZOy7LtUlOdLPX5in9XXFsqjBcH+jZzY2VyjatT72EEJNp0lENdWmlIKT32fjSCnp/D894el4rP0orfNsbQ6uJjuuSl+1KOlRJlKcS5V29eKlVC2a85+6GkRU0/YqyArOYzl9j6lTWZwmzPOk8OnlR8gMNN1DNYNKQSnmJG1/RQS5bpcW0cfUTHwcnBfRiELkgsAAgqijljnku/N+KQUplwaPNq+lCvxiNdYLPELbI7m99rrDZYXZ4s7sFp1pZdHCFMASgEX1IiHGWoas0k/LqsYUwczm4FCQMwDRTCzyWMB7AohVTUoCy3ncyj30DJu4U6DU+dW5C3UeFTZy/a7ZKACiWOlZzsmiTlt2QJXNVbeQs0b0sznCV+i1YXh5N1foVlwuAG6AmmUADLrlQWb3/a/Jegu4S2HO2KPgaYgMrHWR/a3pBGBGoL3WcAdAJeP4cMT++koj6h5Ezz12qZmJEOhgMHG0/qm9f119jTwfaVJF8voOhvc0uMDHDlx/ukURwfHLHRZond2MFslNJuWFG9ba738ojAYQMloNaXUU2OmeQJt/Xz+Sjl+1PtkGkW3QE/aOSTrext+ji7oFNPocgMhB1wz3puBHbQ0WW3O86HAEG6/i7NDovOFNJoJYtqJEdyBcadYiMOQPAT7Ze5HpluDOF4q3+rnueQVCG6uWH/Q5vwJAyJ+/DjPgLeJa08IbiTGO/GIddB33Myefa4MMvuIXL/F2dWNQc0iCwmOfHUtgtLjvE4Bn4sgZ0GwD3HuCQSBIIMxQQ3qYJ8whYg4M1kVAYHWWlSKILMhkugqB4lBRPFck2/gKaoYv8rT/+ixC4/eCEOKvVyBmPP73K4IA0y8HyH8fcG8G90OxNc8F5dcbPP6/33AKAdhNiFPBXCZgmjHFiClETDbPqRRkYZxgwT+9w5Tx/dFS0UMYXjFrvTecZ1xKBhEQYfjQppGcITZAFzNWcgj2TLtQFKMFctrCmKYZ87zT+csZOQO5AMxSM7WIZ3zqDLTPA4qvveJzjb0SL2uPXBIKUeM5qEWk9zpPka2CFv6q7bqRi2s4ux6ziH4sJ6RSQCFoFLXJvtF4o8rXGdDotDFOuWA2fgqkzuGlZHW0N/7eKViji22XX5quIwGzqH5kD8JDvVNapoW3NL/ccRUAt4UUMz6rc17uZAUAxFUPwaQl6hjKU5zKAjYH12mKCEH5+f1uB8BLAJ0QQ0CcIkIKoAKQ/gcqneMdlB/K7thRF0/d4ogJ5KVTnadcGQ2qyOvnXmk8X+Pct56/dM/WkyvcbejvlT/ROzwLy7qa59tRu88B14y9hhqNb9rYQ0YHIYobg10L9PYrMnljLMlDDbRQYbwa0KF8Afl7OO2HZXux8Tp86yD1ytUwt/xn3kv2/je31zh7/4j2M4X737BVAag/sLpCOozjp0eE+3wb0yb/Q9vW+F94pzWpuXT5DUYGxAUjdzSHAJE+IiLg9PtvapxGxOn3/2IXfq0e3K2217k6xFM/Vd1w/w5nFIme49rGS88OqJdlNGM6174s5VL2VPItlWrtyd73R6WW+dn+nPbUAcXaaE0AJtwC+Pru/neu0DBG4emC5+yVEB565nbVGuS1TbAWDt7f+o0lG8dGnPq90OM/Hc3+3do2ZH1P/PScONJiTr4njPTtpT7pwmf/vdaw685Ugfu21awjq426NrSX4gphwHQAo+GgdEpvUw5r51QVSWRCx+7TjNOX5XnhjS7v8uZtbVlYikCo4HQ84e7rHeZlxnJa1AhsxhMpBafTSVO0Qg35zAyKQSM85h3ipIrsKUZV+kvG4+OTPuO3zwARjqc9dvMeHBhpSTovbMJ2IFBQXoyKKblzqEZtsrEXS6VOBEuFXhBDRJxi9VyuwhZzV17FYMxkOGYCJYt6JTVVc9C0g2o0IUtdzJiCfgoEklWQj1PUlPBq7UBIodaNDyFiClr3TSMSO4W9VA3J2bpUp8QuAr1i7c6xw5V83d36z4XIjbTt469zEf09Av/L7e+Prbf2vbf3zsdraezla1ztdeGaN/Cvmw995tb6zJU2RxUWZi5xJw7fUF2HvTOXJ/7r1X/BJuf0dNTUoQIzLAAaZtLHg7ZnA0CM0aJVZkxx0v0Wm9hdrExCzkFxleM6yFl6aK1hDVOoj5qcH+YIv0VcXrxwbG9Z9UpX3QhhBjJ2Q3S9sFvT/lk2L8uytLqUOashvXNO8Oi07Ib6zrGEqr6yw2UENUiUlk3oLFVvHRpDfY+o0sOz91RNLQBzWiSr3w6oEbZYbVFqadn1j80Rel3j3FPQ22gKQaio3o8EKbmTtBqX3Um6rEt1kPIDBQUiuTqgUE8LAHO69jqf6lfepF3xSan3qaKwd77qoKL/Wvqd17JC1H0huv+8tnApnqmGIDU1sD5DCFZSRQ8VpJadDwBOZkqyZZKTDWbvmSgaTnPYavRMLJV89w7U5sfnspG8gpKlOYNYFotgxvSSWorwft+bu391THfj6FpmqW6/Hb8m3VVDIIajQVDNTEjXDNzvIXgCYwe238DTUFdbfD7aVkIzmwjweITHWecHUxU/SINLABo/vB8XvnV59n19zRY+aYba7loiMPbYWUR5a+Ma4RqQez3GNwy529k4j21eAdANQ+5aNqVL9LdPEx8tyr03qa5lh6ZfEZCleK/8urg9saWl3XqmQOmC1g2X7TEyAVlQPnul9QJGwCwfUeBRvx2P/9kiN8lqn+NhgLq2S1/mHfij1Qr+0o6N0vg9GDcg3A19rQ3036UNnnjbbQ1H6+/VOQi+7V0nKxXnUffXPVz3kG3W6mwvVOkAQM0hS6ij8ajPHHrs6UeX+n1wzDfc5XyL98HWr2cWY7sG9knUKtfUtWdodsoiCKVYxkp1XGNiMBVEk2ECawaTLMmM0Tof7jATiFCYNZW70bcWdetM1pidrF8kKSp71vkmshQYq3VDb0QzJ4gi6nTG7q5hPEYRaCJNlznLAKtvaQLUtaxjcd5hQEnv4439DS/xnzW1P1yEE1BJHfv4vQAAIABJREFUSFCDYURo9MSIhojzAercDYOlU8rYzQFxClhKQQQhFwzGz+akNI7Lc3dszeKJLLuEXe9j/h57vo+sHzIWKRBDK8ULMjGCZV3zALTAZM5/ZlwtZCnai/FQzl8qfxRCwG6ekXLBKT1peRFpm6fPPut7sTmlfsvbOnS/F0q3+/wR0rX3/KNbDz+vccL4UICHjT3ouL1yP7S1VRuOVtyre77yzM+0unIvkKQ/Y85+tre3nwb0v6KtdtWZwVu6Le/f+0tohRI6RL1GFr3Q23fzo4znW5EYb+cNXoe8t8UJv9++9coywpmn0wcAf2z0cGfnBMA9gA8QM4oTCB8g+ALBFyRlA/EAxhMBv8JSuNMvEHxGpE8gACd8xVcUXGNMRVncM64ytjLoGZxxJHGvUR7IpSt/eiG/F/vd4zqGgClGZXBhEQMWtV7cc9WUSeqB383iWgroeL9RjB+v2Wp/F0Lwo8bx93FMOR9EH4Xet0cCIF9x6NbVr/v1l4/47+9fzm/q2pWcp8gDMESf76wW1MNLOatt7Gth/rK64n2ti0kD0FLvyRkG/R6M7dvZ0e8NQs3A+cLONWa+1UbX60q5NPofw2RfamuIeLWH8ksT2oFbWzUZTgPAZN/ShS4nWd/xuvGdR86On6shnj2bPTU78TAnvo/4Y6h0h9zb2RUvIRj3bjMqnTLC3oFjtDSlZJEOlqaVdO94ylYV1AW5qDIlJ1XWkQnjdPauw8Sf0WeBC+EuiFqEG2c8Hp9QULBf9si7jCUlnFKqUeDH07FK5tM0g4KmUo8xYt7tMc8TiEmNLUVwfExaZ5QIdHeHEANOywlXVwum/R7p4age6DEiRPJCcKreiYT9fq9KJIuOMAJtSnRN9UZA9fyPMdaa6RDU1M2w9IwUdM6X47FGVjIxphgBSVZXFao00wXTdO4xgkOs0QUlaxac2BuR7Hew2vFxiprqOHFNJQlTRhUr6CbiCgnjQ5hqZok4TwDEauACHlXoShNPT+1cajHFRM6l22nP7ZV+P3U7v4Y7XbjrRUR64YLn7qPzfps9k4bfb27PPpfGaeifbwRm4NkEw0DHyNmRNx7Ei/Uw1loDWmOrdtnzWoAVjtu4to9y9rFs3HqGLwG09yX/4R1YVG+nVvG6yK1/O98hWI9ELQDwcELcB6Rji24GAYKuXvaAX7XN04Tdbra0j82ATqAa/cDESCkhJC0RkYs63BSSAa4EGp22TuFeX399qGrcpY0Z5/Jmf9lFT/4+RXU3vTWCBDL0tdWe44HWuxtmyPYSEmSZOfpxjQrycczJapwRrK5sb6Bm1uwjRkvO5G9ytOJr3AYnVYnW+Kf+fjeIBBhttDFTd17I5SszijPVzD8EAnEAhZYNyOGXSOlsMActDs1xSg3qTXXtKXeLZCvnoRnGcl60DrfJmSKpplkHNIK/Gt59xQTQwOqCZdFIx5wKcnL8LdXpi4RRclblu7TsAKMOQjpg8IgwaZedWlSec+o0a1r1bNlkStE1pUyVFjEzUk5oxnbfp4LyZOs8WQrrY8uups8lm7XR2UY8/aqtROlVs653cecGm3OPgFIQWqdalxrRDxjfRFA+ICcY2BjN1Uex8Vy6CD3M6bOb5od64IXWW7YsDXcZfB1Q7lW5wDfuCMIIN6qDCDcMut+bEVlxH0ON6gQ3gnTv37WaFvvmCoEI6Wuu/J7U2QMyFgi01nmAGtB8k/l1RK0OsEPN5DDdHXOU5JFjhF1NhX76rFXT+YYBHCB3D8O9OntHxHiL4++LzsedWJr2EVcJdH2UP/Nx9vA80qNeslJHR9aINF/2mtHXq//2z6Puf4BwBRYB4RG9Eb2NQz89LbBy9i7HCk5fTmDRooL0yXDSR8byRbMTnegLQrnRjEcG5yKC8rmNiwXI9HD2XOBc3+cZB50Ei71D+bIdS67jvULBPURzYQ40otED/T2LGtxeaq+4RPtf08bu3jFr3Gt6NMjoaFMx42PNWGDXqUHbI8QFjGLlCmKVy2C0IZBmRShEVe5kISwdoLkLdAxB00KbvqXy7nCa049U+ywEhP9+BUSdLyYhw4eEvQD8yxXyf+91n/3rGqf//IH5/3zAFCYsv98jUEGmjAJGJkJgAlPAJF4ik0G54Cj6jlkIXNTpmIQAIQgpTRNL5d6ShNeFMtpJ9YwUrQ9fioBDx4cQgYPWXM9p0fc25xGHjZa1Rp0Y2R2ziBEnUuc7sZrgR7ESIU4ngPNI9MsM/wDPRpuqk8WaYepTiTzTHN84xSdR/Oz4wTOkJmr7sQBYhDBZBHYCUI5iGUigtN/2bAieTdRewMZ8PGVEVkfTxbg/BjDHgCQqywoxStGU171h/yVdjaA5zDTM+O1N2YzmDAEiIBcIGCIZHASMjGw0nAmQEABodlgpBRIBLkAuGalkpJwQks6+FM34EELENM/YFcHDMYFSc7Zyei0DzwAt4QCsePUN/lxcf2L0fQUmz89s19ebrn+OY9/u91IbaOJw/fmR17fL43O+is1pp5YhgM77Gra+MvDvoo6g952OugxO/6oZVLWItOfUdcW5APTMq51l1VtdS1ufMp6X/th7pvB/afuzItJ/GtD/CU1G5cigPHADqgi2YIS2XWZ+aHs92v1OD/PPFQJ5Lirjpvu+ZUS/tc876zYa9xnwyRg4TctzB619HqEJt/4gwoTPiPgFgX5pqclMvqxKE2rpc3sF5dm8NW5+WMfhzQYsaocEzRhBqBEKgZsBXhVIXQS6KfN74XzdZOPzLXi7F/r+N+H7G9dZ2PeMbWP1X9HWhvP+974bd3/NRwE88fJLTgEPpP0IsJGyHdgLWf9r0RhYQ8HWY5po+9KVz7XWy8jI9+MYMdf3hNE/FwO/rzl++qe0Hzen37fnl+jhpRmnF65R1v1gkHt+NRHAH6w2HPsVSqfATpdUcVFE4BUWNXKnRVC701bff5g03aMKD6jGCOaOTplQ0depHSUEG/kgNGzQHHMKU0cvUyzlguPpqEYBq90dlwnzckKIEUykyvSgvNI0TQiWfi1E9RQ/7PegGLCcTnh8eoIQ4fH+EblkLOmE+4evWLKmWt4vC+SUIdhhTwQEiyTVPG8qSBWppVNgc5Kz1odPy6Ip1VlnNoSAGCIyCsRSBVbFEKvAV0pGoIhpt8Pp6ajpbZkQKCKECHekDFNADIx5t0PcTWAQYgwQM2YU1vRzxKaIF6qRr2pYUieKEBgxMARkfIAauRv8WnQhcTXat0jMjm+o62xvJCusa/xKU5GdKw0uNYePvwKfKqvmWsgV3XqVY9g3Pp+2MInvalk5n9Bqq42GPnekkO5862146CvG1DXjO5nW87MyNL7GmC5nr2Fj3Lh3Q3lB63fs/6deoUJnuGhLD5KOudZY9BLJDhPu6OpZG/zZ8zRjt9tjN8+YZjWgh2CppJPi3pCCpYFckFICJcIiSfO9oo1H55BMmYwq9+n4XKG7KQSOsgN5H2OExJaouF43v4jrcZ/Vl6uFvmaHVAg3vOROW71TQh3H6nc1PKCtQ8PBHewHRggW+ZtzTTFeZTKg1bR+zZi7fVlxhMHDSDXdYN7qtSoa7QzlnXzYjhstJzeYe7YRHt65Nam1yEtOGiGYM1LKmro9q9FcP8VoAaCR5s1I4J50BDXYSBHkRWmJ91Wk1FIlTsMUvgpEumj90sb2XFMjNyw6XPEa7dTw52i3iEXFoyAEjXov2bMTiAcgAlAngba/YVHmekx5HjcUSIPhJ4IcOuOvszOEsw3i0UNtoVs5lv6NW+pxlbfZItCdD+PAyOLxd2g6HxsAEVS7a2m3a6QqRjgRO6q1lRUZr43efO34sg6pnbvRefTl8proNvUb1Ieqk4uufSuZ0fjSZkRk2kFoUQMZoaZAr9fTarQVh1MdF0GN5566WZ+zqxxHmwUgMg91btsceT+E3aeoaf2vAbpvuNTHQBDgXoAbAt8wSheF3l8HAAFaQ73N0xMIV2eoRCAQErC4g02uOKDvU+wH4YAgjzo/1MaffU7M2Uog6Ll1wSMy7dVI9ln5+iKCAK2JHuW2LmyjJP5NI89rXeHVu/o45ZkDOk6G4G5z5zOuwJ8Cymera9+/d/fZP3e2g68xpF9sZsQahu6wVHFNj1udT9jeB+uRbzmjrfk3JmolBUhdCTT4Ro3mxGRZI718gtMG5c1ZgCQN37iTWBRBsfIamjM8W4mlntKMa8q/XCH//lD5mDAF0L9vraSGYPr3DUq+r9DhMmP4JIhcUO6SOtgQIMwojn/MAWCmYLCkBszCLmuoI1smgUiwMQVwzuYs0IzibnRUpOVr0oxZdX2ELBLf5qy+dasc3q9Do8VdwQtmSAggEPa7A56Oj5aVrZXL+JamIlCp/NRzuurnGkGN5eYSV9/wku6qQLCAEEQNw0tp+zsXzThDTJDUyoMpP6+ZAYgZqRQwAYHJ6H8Bw+rTlzazSqHXbk/bTfGzjrpmbX3XjJw3nWtz2iaG5IzCBLLyYyRUM5j4HimTYtJqQDfZd0oJMS3gE1umGD2fU1J5ndl4fC2VSrmM47DW4xc3oqtOvtHjM957qzlO+U7i5zluex7bvbV9Xyn5Nb1t7ARDJ9IdEKgTUri0cV7ZfF0rY1Uf1H2ndu2lNyA8cxJopXGdVX//kH+2b2g/Deh/QdtiCvWEjFcZMtWUct12r0IRqkeTM8/tt0eSNWHGn/1RgM8v6AcGBv65l1hdX2QdMf/9tva5UNVOjGLHyLyumZNbu/fOft+sJuLWOhf7zgACPqLgCwp9QYbgDyO6oTJ27v1L+EqECX9gBmP+9d8AEZb/Ej6AkI1g1lRuxCCyyobrObX3KjDjAcSeZymUgE7K7pqocCZQj30GaS0bVobGvRZdeaJp2/2vo+CG9NfjWgs3w5gvnVjd7+qOH1ai/AJwfytTdiOtVviNAAEfAAAn/DGkRr/6G1E0N4w/kRrD177ghPOa6Ee7nn77cn5uYxK3nAUO0iK7719pYKCLmOdcBfH61qtWLkJtpzpoTxjVO7K+5ZnWnvYcT0arc++GzwHfbZ3e7rl6Ul7Ely5cNlw0NFmt14Zi+3u07yVMvbcNwo+ojtd+VSHWIWSlNun+x9mZs+tfmD7/rfr9gx3rlQSdlzKoCcRFFZaBgtFLTa9Xo5cBU7a60sIHR139eqr0gTlUclFyRk4Z0xy1Xre09IEa/Xdp3/U0vdE7V6LWaGdYSnkAhVhrhDGQl4TTUVBSxrJkzMuM47KoABvNBUAAPoRqsJ52E+ZZ0ynvrg6Y44SnEDQSEYRTPMEjGB8fj2rYyglLWrCbZ/CJETgixmBOBAQKLQIuBDegi9YLzBm5FKS0IC8LECPibsZ82CP8EUGs58QEcQoRsFpoAAHMyMcT5t2skalFgECYIgMsSDa/wYwqkgtojtUzeooBhRlLHxkuhJQy0kmjM5i0PiGTKvJFyDLbWIq6muJXHK11dW0VUGQQElXBJ7b+dfUFnbHd1j2JwWzf2q7oa4Z2Jg40iCQH3efh61Kj8etFqtNtgWoge+ZJW2jvTIGyce4lvrvWNd64cAvv1P5XSjr/3Zsl1/x1+7mdiq43VnZPqn32/W2l297i0Sv/6FNsSoez2V5PMPt1VCHl/FoCsclF0mqDwgyn0r36et2lZv2ycdZl6I2iPpQ2A2GasNvtap3qGCdwCGZEU2ceN6CHEHA6nhR1ZC2lYFi8vQcBNcW7GdOlnFHl4d09/XM9JtLWpJsnj67umxsC/HhVZg/red7Xa9vWPvBl9y/EntFjfIcBD5gy0tMdwyLMCYqrUva6sAAnQpxkVcvWH8dVXqoTANTrzsZdHTGaJFON2uZgUEt0dO/iked9nfIWvUlosf3a1OBKGmlnqXqJlN60PhpuLUVTtqecreb5UtO31/Tr8Ah8rbmZS0tFWp2nbF/lrBlFtOSXZkgQOIwaXbC90Jz5i70/dcjV1kQ8IsxpEoCTGD8q4F3LaFP5B8NXxSK+PBLOoznV6czm3GdDADlJgy0CihB4B8jR055TvdaoCeTRjOs7W22L+nJju8MFm5Gl5NScFKXRRbLUyCLc3sPmGgSEaGYD1nkvhVCM7vYEyd+AzOjSjK1GP8n3jkc4djDKjGgRAfzBUml/zYgfotZ4vb/HfH1j+NOVyUDpTLEdlA57VLAgIQH3e/C1G/gCpg+hOuM7b0DM4EdBoib/E3m6fLTmhkwbjbtqwvlD+wtEIOzqfKgB6VjXPgM4fG3P8ejGtt8Jx99Puq9uGMwAbnUiy32B14HXSuwRuBeNaHd6KM67KPT5koV6FNWAVF/PMjuI6BwwEYrVxPb8Apriu9hMW+V1IgA3YBSIPNYOCQcUetTgWmoBrE43mAQiT0ov6GBigajj5sB1UOXZHK4KCRLuBhzosDDe2b1f93zPiiUbBQAJV+CPjPKlIH9uSefTir/zvoodyKTzG0CYyNjHod9XNKddIi0CdD2+zsnJ/+/p7+Y940Maj9sxNf5uATBjjevjFIIDCWYiRBBmaERxMdgIIARR2FHHCdf3diU4oKxQJAIYSFlMf+jnz99XAOTPD0o2QRXPCUEFf6gMkD8Die5x9X8/4PifL2DSVNeFRUuWfCCURzWOCxhHLhBmUCCEIjouMA6fBMffBVkijqLRzkGAxMBJNGp0YUIoSSFH0OQhnVksRs+nGEBwfaggUgCCQHKGkOpjhRhgMrlGA5+Y9L4QWI2dzBX/i+GqyIy8LCilWJp3pzW5OZld5NQ3Jnn4LcPneRbadlrWGwJN/zsbTGWM/IkboPtRUj0ngBCCy2jkeNFi2ElLfrKwlibry7MJaqmYwITjUrCkjBiDCmGk9BCSwTJGlPt40Y3FXY0K1AlgB3MIoFfP7Na0De/t+5wqn6DZbEjt6ZoNAbo76/4gAUhLu2meeqVYS0pYFnXt0CwFRTMbGK/JwQ3o5ugoqq+og+mIJ4MBbofdhqP0vMlMVbauzWlaDzeE98zYy1D8nlXAiqA/13p8v+WEuxphFUReOy6q7BsTNftUxSV+lVrKrv/9CfLb72f9fyzAl85Y0Yah69WceEaLhuMTIxzKl/U0egXnZzXQ/YuM1wzHXzvV/z9ul7KvfWv7aUD/m7UqjFYCKlXw9FaKqGNhJb525wo4qvJEOqEVhC+++fGD996LOP0dSH9lKNpSnL7Fm+/GRvHBPtexcs7sAkC22bpDSx/WIslNJCNFxl9B+LVT/mk9mfF68kiCwmrUfK7WjguVVcNHdU03r6U2luYlbsIYsKLa0pRylYSbgg5+7me7tq14La5gABL+GKKzDzZRD6Tfd2gG979D21K1rmuiP1GLTH9cvVuApnRz8NGaa82ovhMlKqlB2quN5z+6PTcKh/m+nS/ba/HVX7dfvsVe7caAn21sMwgnZ7uHhW3CYFWyAHgNjNDqc33u0vF2/gqDwRwA3xLkq8JA+GisXTXEApFjM5wR1Xq+JReAzYPcyYPX+nYDug/KuX74dRpRBQLSkmyAzZzfBJ9+ts75FD25DX8uBEN0XBkYvIBKKZC54LScwJKxWDS1G81nUWVImAJuPtyiJI0A2+92atCy954PGfvrA/KiERvppKnd5emIkgvSKSHtFjVYSYLkrFGSgEUFMk6nBcuitde9PAtKMS92MdrMCGB8+PUTnr7eI4UAMGE5nhDnCTFYpLz1GW9ulEZDo9I5MKY5QlDwdHpCTkkj7o9HJGbjTRgQQfY6vyUjlwwpqkA5HROWRZ0FlkWNLOqkQKaYK5U/aFFPJoxyp/S25fRjVSHka0bUPPWrMt3Wdcv5r/6umob6/aU98y0498xweuGibeP5K5/xznP66Jdw8/M99NEMZ4bsdtHZPVv39+fWT700xl4htHX92V0rPr/pT2jzunpczl5jvNzhyPCiR8w6r9z6Usbd4bjrfhi7RztR5e25G5PWQG+R51armhgUSaMP2coohGBRPjCHmwSC1XTemDcdlrT9JueyAK3mpp5fGQaa8t0xdr/O7dON6X6g9ifjunyLkmK926mbz+4B414nqvg3Wnr2eZ7NEKwG36fjEUvSbCU+xrJ2PKBG74Ib5TpnhU15qzqqbewpM7Sp7GWfnoI9cLcuMJqiqdOLaEpfmEqXDVa97rnSNjeeA4CVNUlUlao5KwypwveEZDXhWy1QAahFqjuNaCkpARGlbyKA5EWjsaCGNk+R3wzojJbVQbkSj6jq2IpuCc9hZKAPJif314oUsEVggzT6kpM6aHkK+bM+T02mXS2c7V/YPvdniM27ziueDB73tcdBP6M/W+/18JPNxZX9Jg9okIZzfPv6lmI1+JBEZBGQRfQ33gnw+m5CoY7SHR7ddQjkA6OLHuoFgvRHRvwQsL+9tW67nXejUYrlvlMVnM0gFMadJsqazjSc4VkAiDRbn8AMyJgBnGyOmszowQj+IIJFKZJH7QJYGc+BMXIxboy5XycBUHBE2KjHPl4rwz0ehe7nmsOWf9Mo9PPZEhj3au+PuoL+zu3K/q7G+6hTw3UdEwOAHMDyYPPj6dxpWDOdo0eL8j5ArJ75sFaGO0BXELl/lp9ajxFArZV9Pn8PZ8f4o+LrXMNYxr7X/JwlU9A5IDV2xHeQmU3e0fVl/t3lHvT0bixp5rDvRzZpA6QzqOj+0MTQVHlpzwcZreyTl37yde/xoA3IulbHuZKzORR5maWRx2aY84FoBwwa3BkqXJEa9IOjN7FXtpcjUUfrAuD4P1+t9AIqDIVPexQJQD4iJcYTMWJh5EKYCle5kYix3AliIBAVFFL6FghYmMGUzPG5WMpsq0HO6mhUSLOh+NiZCIXtvalA2Ay4lnmkGtGLZnvwMlrFsoaVkhFC5/5ua1KklcxUkqj9ppw0i0NXzONb5I7v0TLOg2K2WkdqzH3GgsDgEexOOjRlvcNzjLHuB4HtRVjq/N6gSei4lpH0OI0aXXS0TYIuAlybj+lb2no/9hIlzEGEiuFXgvIvonQ5hQzKqhtRB1UtgZdSwokXlJKxEKMk3XtEQOCAaZoUt5tzbLbMb9UJ1eUM13kMenxCl6rnDa3nAPxNXzlHaDBxqe8VJu7u+qsh/5XtVcNUxz4Rwacs+Lzim4SAWwG+riZLs4E0vns9l1KKOSFJlQfWvNRI/X+2f1L7aUD/C9slRcOgiNzwVAtMaE5N4/mBiSLRaAM0D8SRZX9mbPa5pVTZai64VB0NmtBz3hz5dojYh/8KbNcrs5yRbe/TfSNXlzU/YH/qnd/XpacSAF/tXk/hrp6fH3HCF9yheUbXcegAVOAz4uifAuD4+29gfFTlmnHGtyB8ptYXO+NhAqcTU7K+XQFBsHXs39dvGmaXqjJPmdPKsneCnq2RjLAg3RhcAVLPvbgyfUer39R//LNIxbXo+rih/P/8+9+4+8//VONynxK9PwYAX4lwK99mRPfn9yxLgPZ5kCZsPZJgL7RKlT62R9Kx+fh83J6C3se5pXd5NJ5vJ2ow30rtrgLaeSr317/+auzvnjcZvj8Pu9vnBa4S6dkb6s5uPa1Xp1xuFXV8a1sZIMaxjs/rvzldCb2UXLs8v796IQ+1jHtc/GP29F+BKdbr5sbzGWRKHBpST/aUTNvzq08Xflx6V1/TGnFecTmqYEuwlLe/qLKCODRDkI23N4p7bVbJZdANOd73GlIVuqoATfV6kaKRV35d98qVLhNBikdUjfQTZH21n+3+M0lETKlREKCp47y3jIJYNBI9SQFn94iX6i3P0SLQ44SMhA+fPiJwwG43a/QBCIfAyBCcTiccT0c8SsEpafR5SgkpnlDSrip48pKsHq157MeA5XREWjLEIv2cgPo8RjfqTxNKTpDDHryoQM601yjVKep1MWJ3uAIxoywLQBohToExzQGlJIT7iKfjgxrApWA5LcY/2tyLrlOyGrgpeRSiGk9Oy4LldEQ2JwiNkDPM52xZxzp6fXQKtkDZUjKaMU+Vee0mdxpw582S3ChgnXp2gwo7K/xKwHnM03Z7Ha7o8Rxeo0EY7rzsZOR88jvbWjA3nvgCG/XMge2m+stGKwYaYTzkOtJ8eM9qxG2MHK14z+pEujHE4fm9cbwfw8VnUwUTrMBlMMB3tKgZI3rKbNc35KkGcEL91Mf5OPUmNexckGS6d3LjOXN7/mT7PYQJgUNNva0PEk3ja8ZUESCmVLNJOP5+znHC8fXlcQ1H+ymskuBZ7z0e97kyebLOsaCOeRQgnh/vS+Aq6FJpmtGt77uios4ZpDeehxgxTRM+fPiAeZqQSsGyLBoJ/PBQ8d4Zf0tG71zZyaHSNAI04t2swYODwaqnPrW9GkpR4SKaYxdbxBuBIOSlswANYtao7CIasedp7ENgBG6OYVoGINTZcjzv2zGXhJQT0nLC6XjSKPTsanK7vij8pSwQ0ewmXnJEI1fFsp6ocV3MQqcR7BaFRxYdb6ig5D4DjRpM3CXbW/H5sfGSzTuuAoI0PFpl1A5qShn1F8V4jJwLNDhfHceKw/8OkCMhzEA5QiOFCVhOGmHveIUATWUrriPoSxwIPJO57BwkdXQlazQah47fIoAPxieX0bQhLrsb31NybtkriKpTBxFDWA0Unka5bkT1aNBMBMZ8NY7QU8/7mkjrr5u3+cNk42s0mkBY7h7qddPNAYH2IJyg8bBLNYAEEJhmZOOOM54Q47VG5QGWyQb1vWAf4SYCCDjeP8H50kTV9F+N6+LXYwYRo+Bkjtk6J/H6oOt+V7p1atlQ3JibbHwzGPHDFU5/qDFXY2QbXMmdgK7Z+EUBXxPyvScWFmgd+B2K1UgP15al4avtP5s1rm+yg+AINuO8eEJqnwsbXx9x2OPGpnerI6xHBbAU7IJiJnUhQsQBWRTzFAEKPepKdtlT9P7HDhIaPvBFEnmoPAF3123xNn6WDU86leTVNXV9cFVlxZohBMD8ywfcff7D4+037wXU2OZ1nTN9QwZDp//6oTo7ojo2Pa70x3lpBIuaAAAgAElEQVQGItW7Ujf2akR3/umMH5L2HKi+USNzTU9IzYjOxBZlzpaZQ43FDTYajCQpyFY+o4jtYzHeXTStexDXG5FGltv9rqNxCPM57ksDlN/vwL9co/z2gPCvayy/3flLoUAj4UvHlp9+u9NI+RiRkIGQwDlgXhgTMh4giMyW/UZqCQcmQSkBMxFmIsiHa9z9/geoZKRCOElGLgSQzkkgz5ipUdeLyR+1clgGtORFy0SkjknQfqD8mdI0zf1QyhEhaFYxshIHPs8hRiBrqRApouV10gIyrwSzG6PdIcPHur1bPljd6I4Yb+nRg128v2KweQBqgYVKqQXIkgEQKGnpoinOEBGwZagRkDl9quNfnNQhoQC2GFzpxWz9BjciGi+3E8dnaoyKHwwq/5AauPaepuzq+dy4ftub7kloZhegpvBgy+xWcrYtTOBCSJbNqJQMFkJKCVIymBhxiprRz8ulhgDOAqYCIpvLKmM5LegyX60dQ32MLtyI8Sjdsjf2uMHja9oWH17ZfJ+rszPP3O0DeYnBX7WaqYd6Gb9vq2ONUNnPMsiWZ8Myek72DxtG7jYYLYJ++PUTvvz+BT3N+6O+Hg1zpGNvY3JcXXzoVCWBNnaq/w287arj+nX9Obyf3XcpA9/P9mPbTwP636UNBssWTd4i0jvB16k22vHewN6UG+4l926y/Se094+NaH03vYjAb97wRPfOE3w5S4lD9Y9qorPRsKHPURHsC6iqhXRtmuKHQKUZZNZjqwKyE9ctQlEnQplwrnXyrP+wMS9roztVEgOHvzHJF20/+82NNr79/VtvGD/9Z8EjqfH6kbbTlz/ZlHuk+re0gvMocW9OcwOAG2k7fV33fD02oEXLHwRg3GDBHa5Eo+e9H6/n7u/R97nl9bplPL/c/hwIqELBn/AkX4+/M8b11qdg/dkut3k1P+QSZhWdn/cefWl21+fXdAYAGAc0dntFb26pw99em1rvE9H03ip/SaM7gWvkuAt14nxHLwsxjWifmpKypXaHcfCuLGrGH6+bRlTq2PX/UVjcNL6tFFKu1tbIS6+RG+Bp6umKkJ7UOJxzrp7zMWra9nnWT+x2OD48ItxcQwDEKWLazQjzhJQzTqcTHh8f1RjwdDTjs/5ZCT8sxyPuoA4oMRBi1JrouRQsywk5Laq4IgJCQIwTpjhhnmbsdzsQCUIMmJcFp+WEktX4PO92mKYJc5wwTWokYSbw7TUAQpiiknsuyMsJRTIEahRXo8appuWd4gRiwpISUjohLcm+J6SiaXyXpyNOx6Wm4XfFkmSN/AA8WsEVXm78g8v0cKfN0emz8aVjZOFz2HglQXbwsiHVv7HR9q9Xor7XYsjvivsJnjn4e3S1cbDjxczwpIdXc+X78DnDaH9uk0W9MP/rcdDofNacYL2dj3FET2Nf62f2xvGm86HugJylc7+k2DpvzXheo9Its8elqauR+aB6fX1ncmXvai+5nLjBw/u79XNRzSerPdQM4B2xWM1bn+ms78/sK8O1L8HIa9pABcxwUfEMLNtIb6Q3WarWnowR8zzj48ePuL65wbIseHp6ak4Lj4/IWWtVen9V0bVprG8Q1Svlz8a9gmGAKl1iUniYLLVniAFMqh4uKJCsinwKmliZ7dnqbBGa8Ty6Y1UzoHt0ug7ZI8cLctKsIstizl+dAZ1MXlQZTw20paiiuNaLJ0ERdX4rJUHrmatDmhtsisFBTglhmtA2TQ8T5RxGusaexr6j9YLRuGkHTRdSKk/RAIYguaAwgc1JsD1G1NAJj/0eG4PgCaR7o5KP48wZ9kkge6o8oL6y99yu9cgkMcN7i2BvNLOOLzcnGl8bcuuaQA3Iki2TjQ9S6e1FZ5V6rz2LfA7rQviF1UDgxm7vMd+rYluVxkudncbBUd1/AiDdZdCV3e97tz0F8iCQa4E8qNF7Ms46Qo1yQFNut7hdHp7pLiNM6ijKVwx52Jaw+1q6AmhNaAzDwv/H3psuOY4raaKfO0BKsWRkVZ2evnZn3v/Nrtlt6z5TucUmEXCfH+4OgJQUEblU5ZyZRFqkRJHEDt8Xxg58w6c7g4K+Nm9yk+MMXuV0s57PmNbViIEepFgB7LEVv/cZPQdbFIqnVRvqfEDwHezzI7iG4hGEfcMlrDeIXWz025Nn8h3xBPfWdW/tBU46ob/X44yTPjphEGLtrls/dfMeYIYu9UP15yx8+E5NKf6avGSnhEqmQP2WMhpmtTO3vX/unc31am4cIZ5E2qFxRbWF7Q+FPcGNAwd5W/Ww7vbGQAtFMwi5pM+BCqqUpnSHr0f2eRKldo6jbM3mQ7HYzgoB+uEBSoTlwz0SDb+Ty0aJ/dxaO5bmRkBSIZWBUiDeR0qMwoQJFFkMwGBoCqOZAmCCPC+4niaIMLgymDKqVFT1MOWhBFdp3sMALNqMWPuJE0CuJLen7Ty4bHTckWGILWVBlYrsxm2dJuo4KyKIJk6A2rugU5z2d5SXJQ6X3jktitNYGdtSpIKYcFyOyDn3yD0u50tsimWR2s5/mHyNheERDoaORNsdbij0c+/bdxdVo/lVV2dxS6oomXFL5AoRoKX9gbjTIsxYIAw4BDDaqQooDfuALDVAThk1K6okiJg3unpKhWi79S3mYYAr/fuKAjlz3X+n79iPb3trhBqX+vG15fX6Ivw6NvP1LWWEp2MRAp7//IgMwm8gfOTXx7feUX0EqzedVmw450xfTuv9Vf4Vyi8F+k8pm2OzAQjaCHN1ocnwihpDGIzFqYd6tODCFhcQ8Bmi8FxZg4Mt+Xva9W2tI7GobzKL2bb4NWVkREZujTZfDZy9A/Dgz91eEOTe+a9deQ4sMI/1jM7YRV4uy63Rrxmdd7zXllILTMBnEK4JeHCi3f64EdIDPm+jI1Ioua0hrZ8hjMyGM01EYDZiMXlO1sTpRK6liL0zMgHjnIYwxgmPbcfOLBe1itftrO6f+f53lG9t73YzTgbwiT4BCKU2vaisBkwh/S0lFNyhrB/Xu7dHePS9HDnHb5ROPMNfK5/JLIzH0O17NY/0vfZ2d0Pup2ey61Fhfkl5fvFX+lF7YcumU/v2vSSe1TGetHMMzOAdhdMxffUYX4HXb62vKby2ZCNRs/YPnwm7S02gNr71Wvs/+jz/6PpiHmKVvobJOPr8TCCst/d6xddg8RXim1YfZ74TgD147SeDMNciAOkuwsCGELPnYnL/OSwfLUclE4PeEXiyVB5SnS5ghkqIkNdeppHXu/WNYIZeg1KLc3I6w/DEKgIZbeagMbCnjMR6bsjb0vU58MOssMg65vVpygl5FqSr7E1azjKoGQ+EUmWed5hms6JfasX++hrw/HacEna7PcCEY1lAzDguRxxLBR8JVS3f64GO0CfBAYAsFjo954TdNGOaJ7R8ssUs1CNXbSg+pmR/mHYgYnDOSFM2S3ZV7HY77Hd77OYZ0zwjeb5bkHmfMzE4EUo54kDAftmhlAVzKXh6WEyIVC1EPTODydanuCd95HA7HI6otWA5FgsFKUYrqtOX4Rk1Gk2bgs+n1z3NCOFRODzvyx5eBgFjYu3Or7nvetrAqfEBffFEXSxn9xm94ZmzT2yptFeqDgHNq/WfKcPcX2r5q+rdKLlpc7aIXZh+VhnOK8HOqs6tYKBJEWLwF6z+T5SO/ZOH6/W4R8Cpwxx1mDW2NYqiddXOAKEp5sMFsg7nCNrD2m663ZXcfq1uxIMI0x3CcfNqWnlTD/VFSO1tA6HQivUYlYsrutynYb0kp8T+ak4i6paun21zsZ7pFVuwUvLQOI51XW8/Txfukq2prLzeuzLIGuzGYpwSOGdwSpjmGbfv3uH93R0ORxf6loKyWPqN4/HY6mNOqFr7vsNAA/VZGbbd+X6vRu4Lx2weWhF6fZonpJQ7TIfB2upqBtuGIfTvEcTYjQPsb3IPdE/JFQ2r4f7wDi9lQRmU55aiw2F24GVKbjAFqJoinWoFQc0rWE04LFKRsisNXKhcQ5HtOXk5B4/gtIgOqjoNOUaXVTAnu+s/Rd80jEWcXmuGeHAcBW2KEsBpBFXkeYZWRakVLAXMQK32LAHQg2Ehnm3C5ODGeN7LoIGVHUM1OmZUjXt5BrCPsQ4wZcCXoGRbYe+e6M9qSnTXUjU7RYcvWgAlmCECLJqOAuBEUCWwEpQjwsvoYHF+Nwbsin0ssKg9eIgRE+gmcLqFJE+3CZksyhG/M5i1fO6Kc/QV9TYIiXcQOrazwmSyhljHmBt5MGOLw+Nzg1v5NhuNpAlyLyjwekYlPo4I6UiiHSLcu9xXEDGO+gQCMGEHAEj+GRWkURbxUIPKRfga53epj0s9H7UL6/mGQA+AYAdyVU94VNb7e6jMncbVU9hgyve3ERraTw86xfTk9wDzE33yvyuPqUgAGPTePIzl043D9kdXNlwDyph+z1g+LFC9htKjKU993ya9BQDw7xax6fDnk4X8pogahNaHka+9RJMk3IDfM+qnUKE9Ds+7svz9bZM98W8Ju/0/8PAf/7OvF21CSqPv84Us1O6stifKt6SH2yjPG80T/AT161HB3nAxsMLhq3o3yvNxthI6XjOZoXu+t/W2sTEs/zxDMEPB7ghVyTy4SdXSE2goK7uRanie599voQpkYlQpePjwGTLQPGGw0j3+ta2lteVKcShIbN5jTEwWNSL4QDMusfcWGDybq6BQabB/jwmJsjtj0NAXBhJQKUNIwNV6casEvUs4fBEcHUdXEQgxCtUG1xfHe8jZlJhkoDtPjHoQBO6gAZeKhxGgtmTqSnFFrQUiBvsiN/qanup7J3icVfleYdMbS8Cvr5FvjSHRQ7Yd+3jMVR504JgEQpSQnV4wG32CRTlTM14AcCwFUzL4f2x420oN1O/zHuk1pjYeIN3dQvHY5C3f63jU5iWU6AGnHfE2VG0EfD+vZFHtVAGInbeIWdTSshFAMvK+rTIQMVLKmLLlqq9ulM4iEEVPzzOcx7EEDuj8ygAJFa2vjYYIXN8Gfa7Wl8sWzr78dr/7mpzwUjvbusIog/l8fUQ91lMYe9t+3co3L7Vqc8jjwcd6vEbXAjf//juWWqEfPw01xN5gjDs73k9maYwS54kGUzlt1GWviXrNFybm/M/6wr1f5W8vvxToP6u0k3sqGGlix6Y8V/dECWBDIN4IXgJBNY70b8LkP6S8va8neiUagdv22Q4k32FzD6doJq7HfCwCnMnSFN0eLcDXaxEw+gGhlHdiXGGKCRlyoW8V1OeKE+djX2OMiiDEyZUePVRg5FENoVATjA/7aySkbF767DSB2XdC639VYL/dmeeU4X/V2Bg9RPolD/RnMsV5IOvYv9sSSv79MKBQko91n2smvOl3vq8jRPytEu5/QH7zkVH+Vygv9fdfZSxhCQ90VKEDYfl/Xvn6lYnc5+GB3mQIrT67MjFWv36pjNhiK4xaf983KNzVzpEXkpDuXKzooa9GeE4r5qrTBAQaGLJorGOE1gr5NjiDbENxtDLcUwwerLp5Y8U2rHAugU7nYRBuGa/YBTdNqTQqo4ZSngryTTbhreexTZzM83veYTfPqMcj5qsr7HaTeW0sAkyW5409DLuKYpomTNOMKWcc3epeIJYfrSzQIqjHI5gtNK/UAikzNBjA6rnPkNoAxb3Ea62DFf9gcQ4T2mQPQzzPFl4+cmgRCHnKvloJqSZwYiS2/Mq7qz1ExDwV5zwYz/R5V8+JvhyOFtqY0OjOoDmNqIrUMdY3y3nrMIPXhhIWMtT3X6MZOlOK4fNs8Ydp9cP557Z3Xqv2pRsb0cSrpQlTv14+8aY2Tk7O4H6+DfE61vumrpxRVq+uRzp6qLv17QyZG++ebX+rZB/O8Unbl/o0dmTz+kr4pdvnh++DwGwUXISXXtQ/0uD2pLhi3ISucT5o9b7T224EmziBEjUPKIuQMRjIDnMsagpBqIfJHmBDGLI0WOy7NDzVI0Sp9WNN7a0U7EDjUQhYwZk2rxiXxvbBOYX+WNc4t9Y7XU/5N5KE57ZYGIZtK1dQww20eT6E3zlnFI9EEn+Rb94Uzu6BpjSkZLF5lmEQsW6X9tgYKtSU8tzWnpm83UH5zWZsYUoPy/ZJRKggMAmQjF8zL8Uetn3sfygEIgx6GD5VqSuP8+qpO0QsSkngf8NNzt1R5Pm0cPIVhrvgxmChsK3FwrvLqMBVILvh2Bbmj+Us/B+srYLbPFnQ4X3yV06CaKqaF5gr7quGINbDa+7MQx1HC+Nu7a2pkEjS0MQyHvbzPHALOsv7of7bSFvpRlC6h3ujK+hqOHiOdgW1RSUAYJF/AIAsBKkpy6iPV6sbLYrv3ZcPnaqaMKIJfs0YM2QH4RWa3g2e/arQlsBoXUyBe0SmPRL2qDig4ohMg0ixkxIeKr/DegJwfHjC7npvKXBuGfSwgwIQV6Q33BJKTgBEO++e1dUUQeNYcUCEULf3dv77sY39ZG7a9/47EUC3BNwDOtTXqFw6DDB116hsa8FCD7CnXTotHY6BetqKqD08zx3EggZPdGqK9SsQBPopqMNQaFqOc+ARSsDxA8DwCEZ6DTHqsQ0y/Z7tTAO277QbPo5nmobr6O04lYRr8HuGflKY4vx6DctBAG5aeij+g1FFcDwsSLiB4gH82y3oo0Do8U15nb+2dHlb50e2yvK30oPbelsElhcQIPmpi3DtgUfEYTg5XmIoChSzVAhxC/MubCsz312j/vMzEhMSJSiboWxTiBJh+fMB+vsNiAkTJ4gbZ/U81Q77FM0ZSNG9zAF4xC1CBzH23c6p7YlQwkdSLYEZWHE10zBLR8LYpdSUoqNxLRy3hpySfJ7kINhNiqyCo1h48KPEubGRqHqUT4/EUtUMgQkJ0y6jHM0LXt0Ln11uTq69XBlCIozaTOlZa8X+6grEFr2ilMXb1kFO//OKzfm3KZrHcO7hMX7CW2F9/gsqkpIbrwfWJlQx3J89Og2fYZGiror1vcjgZo7f1PjAcx7s31q0/e/nrRPx/huCyEPcUNgeiLOhw197ii3yAZiRs9FnnCy6XxY703nYS1ks7Ub1cA8nO8j5DfWD+DpWR+/zD96Kp23HL9s7b+rl6+1RJ4fOwV8ihmq1dLTc5VvH+jVYwlcw5OWbhh4IeGZgv3yAfAT+/Q/Cf358w9iGPUUruIa+7RDndK1Mb2P/ilEEHv5Vfn75pUD/meWc8rwRQYMgZMWwKhIDIls1Wb9PAxHXlMiNqPPD+6MVJRuiUYf/zzx88t7XECOjYnwd6q0jwdHj8J0TxV8A/ObgbbRb+gLgvV+nXhMEPSf6djQN+cW6bYfn/bhBR8CBqFkADcX2QMy311WHiAHr+0HwG/PSrdTcGcM91Fx5niL8n3muBWsXVvwi7rUQnzGORlh06N9/x+VlfbHQ8P9fiAC+oeIIxb4t79SsNkev7hvthGcopF+bjvAe/xpP9PD6vtS3bXn2/Oexr98p8IXG++vPS2Xb1nh5oO4Vv1PC8nq3zpZxL4XgYCQrtu2+UMt3PvENpTEHPbhjtHOuvTcv+QV4nM7Ahktt2fPcBE7r0vEFN2bVOpjgyj0XANDQzmk4u/N4xzt3oVen8/BXw4FReQjEKp32b9uPKeCUP7ofetifXWOC8Fo7x2I0AUF8oysonoZar4Z6u7KAhn9xne5MYTr2oVaBfhGk37PhFn82BMrT+6m1FHl1icmtJsbckT3nuT3D3ft8EDCNEyHFhbgu8O/5O/tzBMsRTneE8mWwgScXkzRNP8ULK5zY4MEQ2jiUXaHo4DZngDwpaOe1XSXw3kLnzvOMaZqRp4RpmlCkoi4VdVnMK8EZs8QJmtXCuk8T5v0M0Qpmyzlejwu0CkpZLAc6ETRVkCgwWVh28jXKbAwzyLy/Sik4Lgs4JRMyif92XAC4R30y5Rul1L+zCYBMeSGO52098zRjnhfUOjUBWJqzjaOYJzmz+xKIoIqieNh4FTjdYKFAhY0BJAg4ZYh6fk1VpOSKe40wsq4AijVXV0A4HSHF1kR0Ld45VZS2zb/98qayBU9vIVFG6HixtUs3KM7D2/r3NeWs0MIIveEgnDZ8bszbp4JOBM6tAZ19Z6UkPNdfv7+CtNTfW3npvNb2lsbdiFLWyu1xu9D6c1OvfV9TFWv4BIdtQyoOIgAJcC8wgNbKsfaOwU3zOGdwduNVTi2EeyhLLVpG92YS0Rb+sbiSs5SCWszTKpTSStSNp5siyeBxeDiPCm5Rca9hWc37as7Qn7dLxXqBhzkefl+j947TMLy+VaafFjp/FV0afqOWb7wrdeDzgfgeuyX4F+eXLSWFRddQ6XkSianlZ2YRqMTaBP4h46vCwIlHvNdxT/Bn6vPS6CU1eGth2s37POcJeTIlesqeksNnT8TmS0iQyPKsMhLC0yVCnLdw7o1njPFGCHZL21FKxbIUlFJRSjfWqu5JHhFRAvare5I3esXzwrKKUSNKgJKn96g+174LPdyahjK3bRRpys/gNe09y3+ScnY5RXJjEYCIPUxqRTuJHh2nSxNsozVvYff6ISLUsgx8s6JWYN7NKMfF6k8E2VXrGwgiBDmK4WGn4WKPNL5+tRs7vURAC+Uesho4TdXxme3DKVvNSwHMuXsw1CGbK1PowLz6I2e60+hgac0r0Om/Sij1CPh7oXxf99Z/IfNixQ1BH2wu+TYUqEbB5nf9XGo0pkCiHQiK6srnkI+Ep2fk4I7K5FHAVxTknf9KoBuCPipynB/YOi6PB6iaqep8d4PliylOJ6fzisOTCR576ZrX8pSHGCWDrsnDuRMURzD2uPrHDlIFh4/3DWKZgwS3+SEC5N7P7zuvzfkHZoK+t/moXxgFz032E0pnDriB3jFTnJv3a8VhiFzoHvLJcY2fm0QM/i2hfCww5bl56Y7Ukwzkt4Hs5+GueaVPf0xgYdSPg6c0AVUf/N0rED1DyZTbSg8oH68AAdSfCU6J4N7N6HEHgufP0Y++zGAYz6C/A/rh1tu7RcF9C88MPKJ+uMH0jwzOycJ8V4HiAcANCED+I6N+6P0YDVti/Mpkede/lg6j7rgy/nbijT58tnD2q9nxs+7z26M50mmnyHK3M2LvEwpM4Vwo4I7z5aqACuYqYA9vaUo3ASugSCggyJdnECdc/3ED/NdHPOoErYIFAhZAPjyiMkE/P0BJMbPB7YU8hLTE+bVTwa4xj/sx39Ii+lBT9MT+wzAvsQ9CIVrdGIBrBVRxlAqqg7/oZoqYPLQ7GzxiEOD8U1LBXBlFGFILWAWPmiwSgc99KRXKwJRmVBXUQ7E9kgi1CMKgyTzQfVermsGPgUiUWpCnqcFkADh6BJvixmga642IY7HhNEYAPJQfLYuKeX5+7cHxMMOiEyQMcNz/EjaK+CDt2t62n4oUqDKmlC1vuAJg4/GrhxWwyDhG4dSYR6928oojrkmcsT2A+vkeVe3ZjlFW3fnqcu69hjuABt1OwMhIE/l/RrMLilRkSm4k6TL3nJCyy9mJkTIhgzCptrRoombAglqdypGVBzvB5tuU6NYHo2Y2vAfWsGkYzg/fZ6dl28IJx/pNfRj1U+fer7U22o9BjQ66mXZ4ODy2832qR9peBxxzo0QnVALH3QlQPgC7f/sNVQTv5TM+MVp0tjCspU1Ey3AgSCFr0YCD/YwE/UEY+GH//63pSEZ8+6v8/PJLgf6/awkEFgB2ayU7eH424PmCAuNvLd8KRd9Ydft+gXomIre37eA0FOEEC2/LuAOBseADfkcHTMGuh+f5OXURNQaT+jroZo38P4KC6TdU3OMm3neFRFNKDAT8iRLqFWFUV8zYVUqM7EK8xIMCHdT63IVNAq0mGInQNA2de30jkdPG9Vq3/oVKKIRvHOHdj3wVgBl3WPB59U5Yb4Y399azO36L+kMpfaN4c2j1hLc/a+30FAKXLFL3PsbwPI/vX1Oe3hCu/evK6d76UeWvgobBj/xsC+RvKSE84AAHg6LcWJ5BSvO/Cz75CWXLwMX37XXMEON6IJA7Y4Y+o5u617kM120SRsOwUJ5v9NdOxAvoLohzZ+pFN0IgD5nalJm9vfAssWeD+UXPAxdGFRdwrZJ5etdSVweueT3C8AwRYb4zJe/ypZwIxMaLlYdIfPJw7YoTU+BWqIZRAYH3Ng/6rKAr9RDvHgbXjQKe7u8x7Xc4HI6QYgr0tEwoZQZPGWBCTqZ0v5Zr5JQwTwtKLTjQE46HZ7M8T4JEXSDevD8AZ5jc01QV6rnVNRhqF+AcliMOzweE0cK8uFd7yeBkY1X0XL10JKTMMP6RMU0T6m4PhWKed1BoE/5K8rDzh2MLA6+1QmpFogRMXaRMbJ4ENo8eMh7OADb3hL4BVdZGnSF01w0N1Dxz/sJybmdeEih8m3+Rv/vCOfhry7DHXnxqJStb3/sO5fm5hmjYC+vDfPpe7IEIa3fap6YSOVvFCBd7iXyjpy9sjW/auxtle1d2Oa0b7433Xem9NcBqhjwRpjsnMCfLoZmSK9bHtAvchD4AgGpGa2OI7THUtoh2/TYNmCUUAK60Tzm1eQlPF6Cg5X3WFVA+gdHh1a6b+T93ZE/Osj+4MtjGGaHyV5QmRGw4ihCsCwOglBv/0iPouNdYtVDsx+MRXz5/9lQaBYfjEU9PTzgej6YIrjLsAfJ9uQ7pqcZQNSOFWMfRMKJ50QXc834kz1HeUmjl3JTfoTwnV/42BTnVFr+Y1cXjW6N0VfMil/BlQccn0hXl5n1e2+8RTn2oCYC6Ej2oGurrKwodtqoArg82OESqMATUz6D9mfGGteC4QXQFIyyHauAORd7NWJ4PayOEzh6jJwrBen3cWKTDebtbVY22VeDwvIAjWgORp2WwN5jJvD6NSV8Ly18pDcY+a7++MllAzNEJ9BnlNd7pRnu5sMAMZSKUPQBNLTVEtzP078yY5h1qLSCp54F+CCFGWvJmG5J4jdpFFPrQzOwBmDL6tITpyvDfoGhpoECbd2oAACAASURBVHX09LwlLI+rk93aN6XgI3a3V5gIqPdm9MK0eH1ze1YeteVaH/ldAiA4oPpvCQeoTODMTabTpmWYJPI3e+fXT4TBXHrHkC/miR712aeuHC8UQPLQ8PJFwLjq56HxAz0ySHi+lo9foNg30VLnLZymVDSl+uh5vzodain8Jtyg4qE9I+RezvzUxm3GkTe20qSe+9zr2xhqDzPU5wV9nRNuwb+5Kat27qfiARk3EDzAcrRbrZaOwVNEfAz1wQPqR4Bw3cKbX/IvrDC+JOHtygdgoOE2tNyJ5/nmjDTHpPH+K3RtAiBELmR35bmawk0Azxl+2o6qmVDcqgAirS2FAizI5HxXSpinGfTvf0D+8wM4KXipEBILse4+4hEOXqsp6MnPasyvgpB+v0b98OBjg6/dSHuhGfMBlq89jH6YyAyQoQ1uc+DV2McikFK64pzMOSCoqiDjTIludbEqhKjBVK4e3l4VyeGT6OhsBHAmaCWUKmaQpYqcGWVxOOR7JXNu8w04HpSgZxgEATNjt9s5TWX0Fce6B+74SeUlOd9by5qaPl+CxqH+AyoE2RdtPBLMQPH9e8IWbK7DlD4McSy+mRlMLaSY9MfI73q723Pm90ndyFubHWnDUNRrMfl4xVKK3WcBONk+T9TqrFotuixnU6Kre6C74j2pn51Su0fyoKzvBnxfM/phlH8Dv/1Xlu0+WRVFZPZZweL9NOP5eI5GuVDNsKGDwonyiYF3qphEoPoZV//2Hp/+/NSefbXuC9cn6QiDH6WAS//a6/Z/a/mlQP87y2vnY5DRBHM8WgP3x7r3o10PhCBgDHAwZWsS6GLTnRH9utIYzwE+XGpJz377CjKkKZo3tWyYx3fojHHzyIUpjZK/9YxPSLADIOhIfAzZ3qzSz4y1970LjNaIL+4Boh+hmtzGFrglwkegjWVkYHtLiggMzNvb3mLLE+lUafNGccvLyH/Ono8R7j3WhB1hGSdGRHQrWpvrsJhdje9ceUH6EMxyq/ZSHd9Zthat6/aHrg19DIX2tdqT2+5/BnCnXwAQHgm4cV3CVjl+JT0MUtzbW5olPFHvQ3iwx/dzJe5XWL8UtFJab8teuyABMMvOHW7xie5XudnHfOrAZU/0MAQ4kP3dKfB58+w27/mlcpaYWBEuMA8D/Jh90evQlqtufffiBv1xhZwE39a7Ed6v2z7txOjhtK7GVzokHRui61TJMzCXRC74lSYwEEcvKTEYiuqeSWJG2yc96x7xwTQYGyA/mfhrY94KneN+66+uroca3Pu8Cwl49f75rRKK8/4v9vb6uwlLwrdqDG04Yugeoj1KujPBvYhCPiv4zhj88qWAAEzvJ7eOtX/hBZ6SCfBqLZAvium3zhQ2LycAlHpuYyhAKQy5gFCObMMeAsBycK9pTq50l1MGwIdCyp2xI8X8bsLxvpw8ap8d252NvELcPsOLQFWaJ3UoMuZ3e8y7HXK2UOgphRIkgci8PJdlwbIcwCkj5QN2xxk5wuOCMM+Wj3SeJhzTEcdyBKlAygKkBJoU5J56tsa+hsSgBCAxShVoLXaeygK4wgMuLHo+HLAcjyYMZMbx+YicEqZawdU8UVXUQxNaDs8d7ZDTZP1bFPvdrntowvF11ZaDsBbL1Q4yQwcVQc7JPQcAiKvnKmGaMmo1gUIRgZYCgUAXWy8Ri02nPtfhr1Jrpx3UNS4ha7po6Hj217i3vfuSOOYybfsCiP2KQi9c/djyYt3BcAMXibEX53QjMF6/YwS8nnm+KXoasbppqx3eoEOHetorl9t2qHtmWNs+jujTjWZYcSKbiK4qWijmrhwf+6BNeEHREe1wEkR+nnHSgPpSJEoercMiPoWiPHG2iBbJwzq6QWvwdYAZ15RasWxyVdcizUAlwiybItnGEtGlcs4Gr9xYp5RiHoIicP/hLpADOs3QiDCfuFGi5E/zZj5HAV+8ulqb4fe3GqmMXVnN6+ahblxsdEbggj4sU54bDU5YaMHnL/c4HhfzGCoFz8/PODwfsNQCEUGO6CoDviXAogU4HmR0Q4WWDiuZwQIlmzeTpTsecm/qlMOAmcEedj3H3kBXYK4MxbhleDRvQHJlZnVD52Z4NczVwMOFd1yt3RPdvms3MhlpNzU1oyyDMbXzf0IANIFIoYMHYuSPFTeqsurMhzHvJsNTh6MpHNT3OZFFNWFTA9ZShj4olqdnU4K4kjjnDIUpK1SqdZtNzG7KE6u7euj6mLeW7UKrh5ElN16jJnRVIsy7PVQVy/MBtGOwVuBo5yK4XAWc+Q8Dk24MGbhmxLYEQJ8BuqaWwzNui1ZoxD/W4RxxNwIEBc7szxEUUj0xeoUrdQgksY7UaG/z3pQG5+IMzjPhuHR+nphQv1TwO6efxIUB1PcxHhTiCuKEOaCBK2zVc047PQiFYGm0LruRQvI1Uc/d3GE3Y6YZSscm4UhEIGVMmMEAkud8BynYFSmMGXxjdZaHZxDtoE9WA2OHyGIujz13bvw9fewJ+GIFzdvSlN4EIGeG3sT8oc+Fr6MqWhSffMOQhx3Ec6LHigqewNg7+lDove8T2kTg8Wo5ILsns1aPoU94NtrKJy0P74xKc/H9mhogfgbhCsuHpT1FegVq+9Vyn3swCChZLvow5Bz3rA7/J0R47rgOyVQ/czbnAvkojQ/pUMOU6B1aXyMiWjAbrgxDGKvrGvSeIZ+xOi/jIkbNAxeDa30PheKJPm/fWL9O1NKqDFW2e+Mvqg3z+ubpvGPsj1EOO0yhzQkRJj+LsdeITKG9ELf85wo1xfpghLWriomsDwIYTqduJM1skKfcPwGl4rf//m/49B8fMYGg769w/89PYAVmUSwELLC85baWwM7henp/g/rpHuLKcyFCZA7fKmmZ3NRDFUkAEsMVldRpJDPy7pE1+5yKhIGbzx/HYq7DKcfPgBmxEaOlpyb4HFEFee+ELG/xjixne1lsV2QQlmNtcnCm7O1YuO1SzDwgJY/IooopE3JOZqS2IYBqLTA+RzrRqifihmGjbTbE+nB9Q1m/uA5xTpv7Z+gv7e8VWO7xhC5bTlhHlyib98ITPYZetSJrajgrjOjCuGBKFtHu6Rj4xz6XzfgXbyDUn3uYfPE54Obm+W+ZvpF0b4be7dpOc9DG6riXPbpOvCq+9gTjqTVlKKvRdSGfIYGWipTI0qpxQk6KmhOkJlROqFwh1aKL0JhwHtqWbdhevf+jgHtI7dVe+J4JulDGPujml3auN13Q4R0a+vM2jgDNAJMbPbxuQB3mRGQwwQKFYs4Zi0QqogF/bwp7OjzdyGnHaF1WwxdM6Tcc//kJ/+O//Y7/788PLWoUACQKfDXiCnSDEw082Y2EDMnzap03wzvt9Q9cz1/lx5dfCvSfUE50TyPUGX/bfndi4FQ70++3XDUD4oNaSGeA8CUAxzf3/vvLKbk5Xq+xATWgpZtnVmC6QetbGMOuG+kMoVvtVZiS/HaoaRuufdu7Ndsc/3fgGERn4ERFIGsPxeVY0ejwIZfiIJTsdesg6FuNctWf9knaBDNM5hHI5J4v3MM1azDfhJabqIqgau3h3B2Rj55JqtRCsZ4D+pf61uftdTzwd+5HgimUx/ziN9q9zwmhvLa/Jwolu5VQRiv67w+bddpGLghl9gMRblQHz/Q18UuwvOIRKt6826nlHT9HLDO6eCeBcMS9K8LJx2H79plO391eW071fv3Z27X+0ypk/V65E7pn6ztfXgJ1Ucu3lDWx9xKF+a3XfQ307LPbnvzF5SubITIFGLv7ucI9cTw0lXnQAcSERcuATP7PLxHovFshr+Gb/d2cvEfOyrPGN9sTBkdD8Bpilq0526n3+VjyXW6KT0BALvgcW7fS96F8dgX675Z7W74EYY+NUCDqHdZ4VJgRtVyFWwXoGG6LE3u+VK/yHDbwn5jMeGP5UhA6eoA6Yz7gxBNzplA2uFKL2DztzxmQhFA6krGpAhDLLQgPm0wMlGWxv2lBLRNKMTxIWpCJsZ9n5JRRRTBPM56fniCl4pifUUsFLbWPr80lAcQttFtwyapmlFLZFOpBO9RSTKngDKN5Dqp5UFSBwrz6qod8Jh/jlLPlds/BrHMX1AMoS0HiBUUEdFjAnIGqWJYCcmWf9ZahydZNuHrfq4VvL8UE/YMbUCiJLCyvzX8IqYAQBA8I8kcWCgIXA3f+CuzWl+93xe2GnjwD27dw4WdAxtb2DwfNazi0wp5xps70Y/VbY03s/A4U5Ml7/fNMTQOLc3p3vS7r1FTnS5eLNyCFUQi1qoEsFK1ajFIT4HLyUXRxURMQM3vuc7a/nMCc/YwRKCVQyqZ4DQ90D9tr9Hdt4bZLKZAa3nl9nHFOAQXYFFQ5W4qJacoIdYUZR0nzmHqt/EzMfrJaF/mcDvMbKlFtsF/9mkRRYQLzgyo+f/qEB0+BIVWwLEcPw2q57TlnC3vtypswUEgIPJk9TUZqnv7mVe757d3lVJWgIq4oNbiYBm/18Dq3UPDxznAeHM8aqjIlKdTzxmpFhfRw/yKDoE7ckzvCsxc3YrJZM8/ziGQQv7vwMObsrBGsmqCPDF9SVUR+MPPKt5zcNl4Lpz2SJKMnH6Ae3trrbTt1FG8GHqHhmaBHYiwFQTAoOkjnIdlqCPglcK23T8SudDF1r7FFEWHAKgwP+wYagNP+NTwh7VtAL9pjlIuiCUpbPeK42X4JO3VCmya/GKJGUJxnq6GiunIqgVeNDcu2+c2U5+qK8s4H1i8V+Y7XA/Xv6S4h4QblcwHfEuRewJgQqo6T89loH0XSaSWaCkVjeJBGVAzG7Ip3C2mebtjD33eATFcEPCsIU1Oe92OzwUXX7KHbFYQdEg5N4SvoYVPXoXrtut4/Q292kAexEOR3vr9b2oFYUp/DBw1Kp/Wk12m51+33tbxE8AzCfjXhTRFLfW2UNtFAdLsftzh0vGttNHJsMAFuThahKEL8xdroqq4u+NeTtgJ9jqvBrb4HKG7a+4Qb//boM/IIwjXwCcDvbtT9R0L98xqA8S3n9hkIK0/zc+TPds71wrNrb/M13dMgQDM2Q79Gp1cCiunwm3nDw78DJG5U4s8nwOgKGgz2Wl/XMLFAsUCQ3etZB7hmMJXNiIsN5k55wvv/9w/c/8efqImNTlDzOE9EKC3EsdtskO0J/fTQ8J+dx5jJ9bWdW1vVUJQGvCWYIUZ1/53Erqhi9reshure9ATz9hV4/wkIVa5Sl52FIaYSUCgBDFQSdwqyUPWN5yHCDqGIjZSU6ECDBeTRGQiMoxzNmEEsdUgpxa9Nia6L4dyyLGac5ilS+tl6udCwib+HzjrFR19X5zq202kdEd1iVMiXC8+OxRyuUpvjZpC66jttrl/vt77hma8qW9pf1ZwZVviYYA4AnS0w+XnQFwqIosANGWuFJIHk3BxHBGw500tByoLrabYICMzIlCDJIuAlYlQyI0lRgxEAmuEokZ0LVjZaBtImZAXXtkDuLyrjml2gFv25t6zu95fRKLhNgcNqm1u5bNTSyjh5W4rAZPmPnxT/kE/Y/7ffcVw+rkd3Tv/WBVrYyq6M/HXcScb+taxZ1J/5ltn74eflV/mq8kuB/rOKrj4GztA5OqUNIHBhrAZKDTYuKgpO0okdCmZZca3A5zMWl2MJy9Rz99YdXRcamz/z6La+qsHQj5zjOTXCmlh+S6cIYb3veVHVCUPqooOmKHeMVb0LDycDO21G0b3VAbNKGxmNppRWASlw695ykbvq1j8fV1UPc0EwQYsS3pF1MbJSaTP3DcZtw8w4RA59SyJC4iHfk0PrIMIjpExVF86rNARybpZXspYNQj8lk4aHBjKKTp499/7bSuvO1lBt07ftSwTzMIkw5gcyD3IQcKuuCPc6wto6flIyFjmur7R7cm/nInZ1PPPs879vudQVt2piZlO+K26UIG7m8dAo8K3yfI38TeEO/OP39zj8+QkJhP0f77H8+bHt1QWjxzlhPHdjXZ0MsmvzNI/77Ip8E1TsI8zkmfrOWv/R2a9ndouVeWD4Et4War4TE+f38YrcaAT/ls3uLPHbYmOMLLRd84bAuhj+WoPu6mGXt4YXrY5VeyMN11leq3M9kwrLrYnoJQ8vOyyYcrY8rGoKQRZCTmZVWyUIy5cXoCuiLvX8/FyeKGaa4c4Le+mlekLA3IQpdHH+e/9GXNO/j7uacTvMQN/zpEB6H4Jkbjh0FPapAvpFQe8spGPMyTjSEEQQAHrnXszNCprco7wDm+nOAwOOVDiA/FteWf9H3vQwoiJicGYLuR5nIBTm4xl1JsUsdqNdQigvIix6mjLqsbR3oOv9zsOEhKJ8usvmrfYgDdaY5a4Zv8XB0BgfhcJq8GpwY7HaQtACYCBPEwiu1Ci1dXu+2mPKE5ayoErFcv+MZVlcsS1YjgtkWbA8PmPaTeCUkVNGZlvpIydAzHPtKc0QLpCd5R1Uz5GeOCPljDxnMJkHKpaCqhV1EVSp0MLgFMIwoNSKImKePgykKSNPU/NahRIoM/S4mLIGiiodykXuWJ6SebzmhLIsYFosTDQqmDPKUnE8LCBK5u3CqbVBzpEvZG2ICOqxokp1AslCFksI9p0gCM9L85Dpltcx6bav12V9NsZTAKxgxBsIhZdOdYMb1H/ZsN1vqGvE/v7UCR77FurlFO59bSHgm5ToZ8P3bq5Owpn6ve1vjQKlEW/ZeYwUFOLwiQMzNxAWnl2bWSRaGTGt759ZU6+/j2sIi0zNkbS91410RhxKrUEaBB3xkHr9o1dE91JkgOwchVKWXLsq6p4O7mmXsgkcldBzUTd63KJiRDhyM4jVZjNiHu8mgMt5wjRNmKcJ026HRCbAxrN5oUeIdxLp52BF7/kAyGeUBnpH+0yPcz7O1eCs0XBCPw0vb8i27zdE4ImRlj9rKIr7WgLmmRbD0XgWgMCNgS10O/mcKUzoGZEzLF81LM2945WUfMe64DSlCM+59vZP4fHvyDI8z6V9Or3lodmJTBhL6J61tt3WexbghttUBKhjhDDLZW5e5uI4S5uCPEK3q9NvRMnvVbQgyFpBED+QhvvdWazNP8MiyjTH5NgnKBa5zE+tGdSYB7QKQZRQH5467Raex94GK/s+lBZefdqbonF5fPK9pIZT3Ig7zdm9CTf0WPAFyRUuKpaPu9bBqMsjKx0VtKu+X6xvy/Hg933N3PWtGb4rXMBuLRIi6oEAVww8AarhaauNNrbwxQS0cPmuRJeNgbHPOUm8GQYN1rY8uAfWdTzuiqxGqomNJ/aP2pK2nMQxT3HA1D1WfW7jGVT3+nUjFGZueVcB37N+xiygsdWX3PigoZ7hmXGcKTlEKQO9S0C6dSXV02y50p98QgajXvL81gog3RodVb4Uh5szCAy+Jos+UgFOjHoD6KNAPINu8ja70tX733aUjaGqgh4U+Z3BcKn9fI6FYi1uAHrQtiYVDHGufc05Bj9CAJ7WFQGo+rSiLsgRVex4Um0e4wygeney82NBHwdntwRo0SeDwRppKXp44taewCIk6RAlqK9SUwJHZKXGSQUu6su+WfVHD/v9sAqXT9iGz3/0yF2Wu5oUyL8l1I+C5eOXhiMVDq70tK0OoGzGCz47juwK62ZoE1ipwbkV8kfXXgX+62enj83pAq/HRJj+q9p6kRImNBDvbdsL2b8foBAORSx5XeohrC3UelXGjBEmdaMnUbhcL3mIdILWisOXByylYpoS5PMzdjmDSmmKwVCUZlALjQ4yw++AGofIK+8tJyVU6qGtbcuYfHKBDTQoInU5p4WMt0gc6jQOiD0EdsBNg+NMPUJ95HsnhRstBkFmDBhRbddMjD0lCFVPpyjInMAA7t7tUavi6fkAKhWlVvPWV3Vlp3nJ7+adG5m5cZqWwRA4ImEAh6NF41hqZO0etsZoZHGGnu/2QDHDI+S5dL2WJcUecszWm3PckRB0JvoTTQayDsM/1hrSBIGxePE9AZ0uxGVluqqiyIKJMqrYPmntao+G0o+Sw8zoKwX9tK754M8TqMu8z7SPNq7LEiJtA+kRe1fUxAjMGq051tB/kCCWxFIkjLb74eTgdobIzcg1mUmkKFQqalqwsKU7UNuUABkt0pkUp1/gEXeGPqzWP6bW4QfavMU4tqveZ+7SfF26Z7BzrSLfPtd0B9EvHWdvPbGnAf5Pizgt1yIzNUMFo/XSlBrdFLQ1QTGljKqCEnTXxki0nTm1MclAnxGGaIwA/kmKf/vPP7H/9z9wp3/ic+AX4mEeelSGvj7U0u5EatwwDgweS0WcD/FoHTF/Z8r4++m8X1jqX+VvKb8U6D+zmNl0Y/6bOXKcfdihDovFCCrbSMQGQb0+YqeOyQnoUM+OYo0XVCEjhP6O8hJ4dBvxzROnpEGnmnuHmtBruK1QvNPARdqht7MXHLNF7mU+YN/7gf5ZyW9GKdvQ08DnSu7cpsFcqAn+xdg1cdxYiZBJzRIzEzh7Htpq81DVhNSi4rQhOYOXkMiIlxuosSPUnNQaI9wDPNo+CSA8hnwft0gls2pdtGKRagr0EP4Q+r7yfdi8F3T0o1yv9Kod/zIqdUjd4mpApd9bXkS9dIIzx1tdwa6mPCf1UEYKfOZ+/xEWbj/2TyiX4rPN83A9du6ZwlOdhlDqxj7sNcK526zeBm0GcsW+eXbbJ3DtQl0BbUKv24pfK3D88xMUhAWE5c/PAAhPxLhRIK9IzvH7atOfXB+IsGvnjNoze2e6DsM6n76/IlVXTynWPdlCgvG5Ayl2Si20/BgSf6x7C1Euk4Lb1s5dy0DkRQvnoNrpuzSE6HxLaXrfN7/xcjFhn/UDQOsLO1MbCtkW4l4VSylgJg/XRw2ERg4zeWvnvmbcZ0b8mpL+bXW+CdOt1mgKvBqwYfV33bAIR3jf9wz9JKD31BTPNr+pCQnMel66kcSdr8M7Ar4o6I6CV7LyxcRW7LnOKYSkw8kJYb/I2sMwmNV2tkKQTeSCAD+9zOCcgFDQgJwxpI5cRc1TkmnIj4ou2HcBN0euXzZmUFCtryvUGfst+mW3w0Oy+znAlA9uGS4iXWGeunGCzbV79hFBcwIheT5yC5s8TxlEISSZMc8zZlc25ZxtvxNhUTFmWATlcETmhMPxCIIpoec5gcnyoS/LYlbjAKZpwrvbG5TdDrUsKMcFx3JAIvNQvLraY39lLmmqgDzeoxwURQqOx4qcGRnZcG9xJTUASoyUMnKeLPfevMf11XULCbscPcxztdC7pSggi+VLT2bIkLOHkeYJWp/wTAWHwwGPD894fjpAxEJKqygICVOaMM+7JojH8xMOhyOqmKd6KO1snQGRI1Qs5KaGwITcE4Q7jgeoMfjcQs72E3lege5nd6VgGzBHEHG6Pde0Ap5r/DEC17gj7W6/+RpsP+3vN5fhbH6tEn0b1o6AvyVIiE39adstPPhG4d7lZvGrrl4czLk6NzPiDtpcD7RjhytRQ8e33buLG2+1wjSuBDfBXihM0eEwBUVlQl8iM645liNyzpjTzrabALUsWMqCnBSTG8rmlCHaw09XEcxXxfwOOYHyZMpVJRSpFmXiuIBoAcBtb4fyKpSzpACYkFOylBTTjDxl7PZ7XF1dgT0NB4FwOB7BrvA1pbyHoFYXSMZ8hoLFmZqmPB+Flrre7cEf0HZ9XIEe3qYRwSQeMRain+0NCbvaOGMqFnVjLUX1kIkDH0ubfTnuwVh3NeE6FMafwbyWzYONm6GBJkbjw9XO2ZRz8zo3b3+L+BG57tkF7Or5LaVWX3dxwySCVDNUNm/xMOYih6fUQu8D8NDoAGlFFY9EUGqLSFJraWHabSqleaRH2HZTCADGOfr86Vp1FfDOFPEmK1A1BWuEFU+cfN792fiuZjIOmF+hQNzgzdcL0hRU45lrUogGzu0cLk+HFlKzPTfwFGlOqEfP7x0S6wD36uGIFdDw/gcBC0AToB6WneKFweBBVFAP4gZh2rZMFYv4Mm7OeEShoMc+l42+ttUDBoeFTktKi2QR5zsUmvJEoD1Bn9Xi1hKgT14N7Hf1/vI1tdRJ6nKGIFAtbLpFzKABnwxUF+DnEX6G+JY7xiNYmH62ntUvzhmkBfVJkdIMwdH9SP35DbyPeUiUQFdOE2c3oGsKyR51L2UGrl0tex00ooeBVsXy9AjGzhTp2dcgDTNODD4AfMuQRwXfOt+SCLU9ZbRli4MS57/NjDZaRHGA0h6UAq51GBjXxAwWtbm6I+Bhj6SH5oFIgCsfF9/9s7fwPNAkB0D3EDyB1E5pCGCN6yTn37xNif2l3WhBe9+3OFMUSGdgd/zUvFED3vvSdLgZ69hpKt+5gBvBRAqNgFxWxY2b/fcETMPua23H87ZXHc+5AUziBP4HA38Sag+24l7bqyPc6uyhvQnChEzdg7lFq2p4KF7uxk+9tqDFYi0H+LXRToykJPl9QvDObqwCVxQ6Tk2wkL8Ci5Ii1aKUhALeqjQlWpNjDvNIBDfss/2hiZGn2camJmcUFMxEyH/cgf7rA+igyLXgKAZvcuA3EJQYiUx5XgM+RfQVVQgxkjP9FDneYs+xedtmVkC4sY7m2k2w4OqERAzNGWDjE2tZUJceD4LRDaoJBFJxw16yOVOPnkkWSQ3V5nNCArGCEzDBlfbO5zIRcrXoXXne48jGn4lWCzUPM4SK5ysUh2LpJJhj5QXc0gKZ4qvUCs4OV7Tj/TBC28LC2ChBgpoidNxfDQu33eZYqM1HxyWj4SDaGWWXUYUivKo7WQlWB6+3ilZX8seYeth2AM1og9Q8+cf3VmMMg47xu3aD6shQTw7D2pmJI6jrY0XjtxOycuzF5l58j76uflSMxpoUm7cBNGp8CqHDCsBhh6ClljC4a5Nf4We72mmmZGdpmjLybo/9PGE/73C932Nyg6wlMbJW4Jjc8ISQ0gThhCKCpVZPLaQ9Go5av1J0gIPMCsNHGQPdmNGCT2pKowYg5mKYv5sjzAAAIABJREFUq2HN4tdxls/P+OXfx3tNarUiPwjrjdmoj3N2J0Ohi41KDR7D58P3CRGQiVE1NDOX+xtGh63OiJBhSAogwj8Z+P1//omdskfLWMvaEKMJ/KEYjLTQDEZF3Qij1GZUbkokl3VxyAyp9e+cYlw3U/Li9P0qf3n5pUD/GSVORmM+N3/AQAAHUB/ZUho+A/U6YgpCy+9fiynrdFXbafkK3ceqnu0B1oH5iAc2w0LvzVjb5qWAs9ABsfXf3g18zsp6Zwg1TqQt53nFOkT7e1iO63EsvZHOnGj81NpCI5wCmCmpWTqH8krtWqGoFIiakP35Wyj+1Mg7HqGBtCN6AF9ArrgKQsCNKEYK3ommkQwPgtvyJXbqTp2Iq2q5TYtWFBVHNFH/lnoZ53PNdIx0TVuWzR7qjM7rYP7N2482n9sSSHt4YbQIBnp4dqgpZBMsz/d2TKw2ly7fgGKdS/xsF4bfI/w6oYdAj4cs/zrhyhmwR1eY23s2iPF9H8km9LvdeyTCnfZ8ZRm3KLjHrdq+zzDv+vtzi9TgQm9lVIyHEj080ddh29d7Yr3KwQT00q30e9HNbzHelmOd7Dude3F7/VXlFHKdXm9JldNnWhe2APQCQG2zfHL//ABePxf2Xgi4Gk1IgyDGlY6jtUeCCXCrECAh+hiVDUbwJSaQoKd3uHDIL+KVV0cS6zwqi7+hOAE7KnrG+rZhU80yvgP2Qu49MPyZl4R9T7cmNA8CWX93jzEXgrMzJUw933czpiDrV63FhnvnRLoLDkEA3RkrTNzUFAhgQjClObORa6KWewsAlo8L5j/M0p85vO0sx7VCwdlC/IZSIwQRTTnuS0pkoJ5dEEGD5znHeJyOCIV9SgladWXFO8K/+E4+54G7UkqotSLfZMhjeMKfB+x04U+hlmc4MVJKLaR5zhZmd97tsN/vcXVzjf3NNfI0WajlGViWCc/HIzJnJI7oDwQpAknm/aelguYM5mThU33+5pyRbiyU//F4QDke8Xy0ncPEyPMOeZ4hAlNoEJuXCDEoqXsvmmdayKa0cUvWj5Qm5Dx7XmXHy0ogSmAuUK2WfxAwhQ0YeUoAWf6+WiKqDHA4LFiOi4X3JUaY6Jngx8JNG7/N4KPl9VRXyARlZWDDwtDauSnN896CIo20g+MTJ5zYJQANUupmfzTFwPqMjqafIfyPM9OIsthTA9CimE8EvqFV1PcQeDUlQJA51PutsV8x1j3uxm8sq3k6xQF62uCZKk7Px9d0aVs7eb/OkWgU59LpoAGatvvdaGYwfA3IS7bboFthwEhtAE35uR3buFGgTTCuUQcNDzmcDGE5Jd9XAvMAIbjyHN2DOOhrGubF4SHHcWweWuwpLRhCClKxv5xAyc4eyMVEEkHEyCSzEd49pTan5rHOzcM5JYaKKy7DOEW7NyATI+WMeZ4wzxPyNGG3n7Hf78ApQSA4LEdwIvOESeT4pwuq28oFe+VtaCOuFN1IG43v6CvQYXksUFt/7f60YYw7eo8Yn9NFxX3xoypar7mOu6kLAK0D3KP8UBhgrHaOwSkNUa4/R2gh2Tm5dzlFZAFCCF1TTk1ZPirQc7YIIyloKefhpFou+yQVWqV5n4ciuwpDUT2lB1tkE8+JHvlXVTzvvVQkTSA24SxIoUuPpLJWnncleny2nOe+2uO5Dvy92ggR6YAAOB4hWHoTcaN+6dsAUAFTclpngOkulLa95R7PttPRVAGkEAF2N9cox6PTYRmipcF4eGqWupR2vmMbahv/uNIuqicFFscaC0B7hh4UshiezXvzVNZaoAP7EoqvinPGBusyek514z+fw3gvzpp7sZPThfokq/cBhXgeb3pCpyvbVLtSjwB9Ulf+AOnG9kvV6tHl2OkzNPRESpar90FANwSGmFGDWihxvQfyzRX0QcHveuSDnBgHUlQcwhwSi3t0ZzLvVdNBGFxKMOV64FQCME0ppgHwPSKPaop1v6G1h8GvT+IyDBszXRGYdmY04PlliQjK3VsaBPC1wfB059jgUQFeOrwM2tXHkWP9NChr0+zYyd9BHxVyIwaztNMbOXMbjDD7OWUoVVP8qoeJV8ttHbud9Gj1NrrO6Sl6bjg7D0hRtNMggJrhAQOp2sPZ+7BQXPcjSbhC1ifnY0KR33dy9z7v+08U3Yh6oNnaM/6OgcVucM3rN3wuA653BfoZTrG9R7hG/qO7fhAUORHAqeVCXoGp4frcZXyv5IbMvnihlAgFWeAODL3stMSAJzXgiqJr+4YRaW81lFYE895m/7S5oubVW9WMc8JTV1UGWgZtjxVyJacfqPCqZ7LxVRj9chXerT6KKmJjeHgC54T9uzvQ8zNoOdre+ucnZBCOFPQweVtkdAA75meHYQRALBKgonsixx5RIiC1wBHugW44tsL4aSLjJyUxRBJqMmNABlDUw5xIpylSC62d0CJ4OOxKPstXbFEaqybnq6xtzXbiIwFAtokC5YylmJd5TgSomGycGJoIWRNUKgRseI4VpRwBMrqsSrX0WA4/gw8e5cOrsjJiOtFnr06ctl86PTz6tmL4tmKRESHXFTOoQZfxvU66reVydZjdETIV/767ITBfY/ny0Nd8eL/LSLXh5kaKqTtbOB0iyl1ZG69ED5shTtyiIB/6M9T+QyjqdXUPTYXSlfox/pCba8OtRDLQ/X3fBYVvzXUoeRrN0f4Lzhhq0eAqDDdQTuA8I+cJmS1kOxHAkrCkjIkZMzGIEiQBVRlMxiwoBMWdL6pq89QfNSVBV3TA0A32xsklEKBBewNNAN6Y5e0Y+27c7lNs9znReNVL4JiAt14tBV0zhgHzz5cMyDtk7jtk7Ic2IiMAJZoBNYCW/oGUzr5/7vSGEbLhaW0yjE8E/Pd//Ab++KntlxgGR8QyJTfmVE9VGNPVjRtJQ+5i/Vc3AlBnNjltkNzQ2bGnW8X65Vn8Vf7q8kuB/rNKEF6++3V1tLdH4hy5uL0O9qzfV5Arz4dmv6fPL5QteDxfGvpDg67j7xeUToDiFoZsI3d5/P5yez00bvRtnOX3sFRM31OCGDVMOVTuwlIhQ1cJJmwJS3pTnlcL8YFYf/NYvHJkpxhDy3cybEX6B6LqzQJYe0fHPFQP9ycQVLXQPb0eHRCgtRLCiW3ZKqRfW4O/u4x7fNu3d9rDGj2SKba3YWbjuSCAuzd5X4W92vsvF8Iz0ZBTvBdB96pWoCnPtz0n9FzoMbK90sCSm3K8wMKEpfZWDwf3xfsQCnWANiHRL8EUKwffSFd6KY7ApYlYw7ItHDoHl1xm3czNd0o4Dhtur2TK9SDaz3TBQtld6NKrfX8LrO3XtL2+CMN+VvF95HBInPDMOUNELaz1cmwKVXVlqIkZQuhMnnN0ayTxr1+yD2gkhEy8cgVXQdinh3htVuAN7a4Jc2CrjGocnnkohqDb16F70HXDrzi/RGih/fM0GyyoFTnl5pkMmKdbnl3QKKagDq9i5wHQkBNTy9fSUNdAkdOgHAgc1vBCKH+bJB9YjkdTGryhUJtAmPJdBPPdDIBQHjy/92gdHgpHosaIVwioCkgIKWfs5tnC6+aMeZqxu5qROGGaJux3++aFPk2TMTZE/uyEOWc7DwJM2fLNq1jYv1wruDJECko1hTGDsNvtbD6YsN/tsJQFV8uCUsQ95y0se63SPAanPCNxxjSp5wdMUBCqKLQYDo48t6VUlKVgWRYLJZyzhWh2r31OCVALz5ymGeL51JelQp4XlGIK88PxgKfHZzw9PqEs1ULwOgPXWGZVz+9nCkdm2zecMlLKtpdDUOCepeIhhLUZ3g37vH3y6tctjDx9p18aUx+egD1FDiu5p1xskgETBb8eNMyqtXUbg7519WW8XtGyI165JGT4QcWO1V9Vu7fxQ2o/5VFGTEhn7p/rw2vPh0dXo20HDmcj+kDADKtwhMZ2Vnv6B14LroEOjyWUv7YHI/rXNBmMIQ4FuCLTbGfTYQ8zN4MYISDlCSkxpp15i1NOUPbQ26IQp/XhcDXlbP2oppAVFzA3ZUDylBk59fznHsqd2DwuOEKmAqaMdSGlNqFXh+trJOUcBQ07P/BapItweIymaNgYPTQFuAvkycJYxjqGQK8JvnizC0L5Cxei64gP+/6K9RsV5/2e7xQiF16Sp6ZCw9lMHk4/9ZDsTVEXAk/HH4kt3Qlzsmc5uYK54yRSU5Qn7fMk4nkyHc9aZheDqZkZk0dD4cQW7n+lQHeD6qqoxXDPwhZpZFkIFsrWBiQyzmH3uGp67WGpA7aM1yCD+QiDjRYFjxB5zJuAdtguqm4I5sByjC4A3pxXMqoTSNBqntO6LCDRoS8m0m9NBO0ySOdXxuQaZEQ3VJdjh0oKgJYwRPHhqLZ4wZQA3jH00LKMXihbbLKFUVsoNMCdzRlTBDwbfqFxavuZCrg31rp6DwAeFLgGlKXBt2iPoKAHa7GlsiOsRBQMgG9Tj9oBMq/gG4Y+zLBYdX1OLah09MMi9VQcV7C452uNUXi7V/ZWX85TqgA4QjFfFAHlW0sppU8+Rh9Ifaigqy3vjI1SCdgqIrp8ZAau3YgEaGdoDZ4M7o3BOajVY2MNXrsHrBeE97kOM7TiFFyxEHuw0dk6Pt1pjjVWi29X9tn65srN1fXQPEyuY3rSMELbTJ72np7y0RcWaFWu/anH1myH49eg99aoqEI+ukTi/+HWZshn2qxRD8Xf6YA1zdHuDY3FVjNdk99wHAAK2raPuRnxGBEKGtZL1//1+fXLUCyH8UIGDX3p+6P1y39vJ576nhr/gPWMr+TE7N7ezNBk0c9Qzej9+PkR+vwMHA5YVJHZY46RhV9vw/ZxJoetMrRn5nSMZlan/UxZIJ1YB0DbnFrPY08X+NwzgVIGiXgaz6jQ8B4ToXp0gMmVUDWxhcMm82jPbBy59YcQ0Uzt3JlHufi+zgxcXzGensxX27zfzTu3qkHYJAKkZGZuUqFaLfqKmjeqCpBzRikVYEYpteGUs6dATz/PS8y2v710rd27dlW5le6UstmrrbLTnh5h8g5CD+VO8RtfAdRTXQjOy0cHAQjaSaQ4B+cg1RsgxwYtnMMS28ffXqI2Awj9DG4rGp/DKZ068A4xP9UV6aUKihSUmiCVWkQQEkUiIDNjTmZgZvnPDV8KM6qn/TEPdItY57GjNljj3AzE55AuZd1pbOmIS3NHL9zbtrp9r387t2rb316iq7atndYnqm4chU2nm4sH1hTZ95X//88PuAPhPp26sY4d2OKgPoYB14jTXMMzLVDR+Bu+do//Kn93+aVA/5ll9EQHcApUXgI68ZgfXGfoA95H2N1zvqJ/RTkxJloxAfatM4Y0QJkzIGKgY7cCz3dD9ePbDzDFemvDEXn1uh6UOoEM8z6nof6vHi9tVigqc0XUeyJk/g2CL/hCpqwPT4Hiof5EFddQfGyCI+B6nLNmdRde+Gt2rFtgaVAug+Khd8kE9J5LT8VDs7sHg9cW1qzrZeiIaFyDcciXykBav/rsi+WNL57Si3G2TqtgWFSGLQE5lnsyT3WGfW67Quie7M+v9PGJzNN8r8CTE8N7XZPDzytOtfcoFN3x/JapivNtSj/zPBc84Jl66Phrn4MYE9CV6Zf63sPOj+Po/dspYcIN7ul+eOICaUG6sprbnvhzXZjBpjgHYQdCUrPOJgJ2TqIfW14Zp3XRScjzw6Lv2Iibvn4l4Ojw7GLPAGxgCjpcf62czrwzNoSWmylgY3KBG7N5NifP2QrABObuZRKsEZEiJ0YVZyxX/eZNw2uMs94Jl3vcBFe8vn6t9Hk7P6+X6sntTDt80h76j3AFdlOUdOdKxViHpqSz9kS7ZySGzw6adbVXUkqDdTiawYKGKC6UE648nubJn3P43rz6TBE//57BqZNxRIQ05SacAK27QIQ1U6gDzuCuFIk+RJ3m2dj3iVRBOS4WYnizp88xalajKWkC1KWU2rOBq0IJ0pRe/vZYWTvvnDBNM6aUzENwmjBNs4cx9xzy6qFwlwWUsuWzda9CBoESW95gD4Ncilio9LK0MLtaK1QEOVmecWIPL3hlHgrLsuD4fMTiyuulLKhLRakFzIyrq6vBGMC9ZJ6eQcxYjkcsi3nHhidirRWlmFdeqhURPr9FEfD5x/FoSm9miBwsl/tiOd6rhxQOZVspi3lLkrQ9VkXAtRqtWArKUpA4IbFgypPnaC+IPIHRhyYYEnRvWWyE2HT5Uv2HHoJtELgMnkAK9XQ5Bvhj70dYtFXFTixSmHj7rmpeRa+B63Mk+ElpasPh0WFTvqFcoHj7/Tae045QP0Vva+xiD7ar1Q1WxmnonsZYp7cYpO5Bo/upRZ/AoQUidLfP+GmzIzbwsz9n1v2hrIv6Ak7FO6Mitfkz+r4xcDdY+1M31Gt5qRUDXIz+qIf6NuUnuycSE5AndmWseZKLG8xEgqqcM3b7HXb7PXa7vSm/2SgUi9hBILLoGWnKbcYqVVTL8QShioiUwv5szhOmeWepKXY7TPMOzIwiBSlnM7ABd8+c1YprP2/knhTBnWnfWTRqioa1Wa1LnAVdr13DHxQe/92TdvX+gIPUcZXlETfjAnElUDtvhK48x0l1q5GONFoLPd1oHsMbmdlgnYe7T8kMqDgnz1+ZDc4TmnKdhz6HwtIcmsi94SwfOJyvivkMwyTDTxYpZZ6mlk8dgCkSwoBCFVoEpSw4Ho9AGC+FUQStVYMXRNxt7kN5Hs5XpnqA1euhg41mQA/Xzmx5sonhIYgGIqKvYQ+5j3bW8m5GORz72obhZUqWfzdSuFjMehCF51rQl9GWHVRSM2yzaQr6U9GjCDmPCwK5+6eBmw4r69E8D/PeztEiS+t2DGCrdPUt5LcHHDVOwnB7BdGcTowGeG+f8tynC7qG5qFgD/PoCPzb7fIJ8iCgK0K6sf2n9wq5pRbdwDRIgukdEEYrMYZ6X7F7Z9Fzyn2FoiLdMMqjIN9lUyw9RkQei2pl/ZkgriwX58Ny7PvYXwAKFiTJSKkH+FaohUf2+RNPB24pfyzcKhMhX1/5CBWVTFEuV7Bc3SDUBzN+EFoAIujDhIAO+qSYf5tBtAM+HqE4NiVhKJjC7CRRkOUM0gnpHa+WlxwXJlewNqMUp3ka/nY6NsQyOvDvBhLJoxb1/RLh3sMoF7AQ2BHhQdu+6TupOsmdnI6ZBng4ar9JzeB3goUzKHEsJUbV+xj25+GJOpZxD5tM4TpOUNup6m1Y6zfuaT3SJI9g3AC4Qf4jmUHRRzfM/s32TPnwuWEfAvDlPx/Nq95xcx3ubfvVRzTgh5eKhnGY0b0RcUR9TgIfmkGUTVDzSfWDHXSlao9JTWqh22MuWcPw3OeV+vwalHacSxuatG8+uCQQiP+H4Wn7J1hIkZiRiFGUUZUtYggJSmUgPL9T8jD5FhFt8j4cYXtKYCHgSdUUyoDxaFVcdmqrMJHZVC0wuB9hiIsDp+zzUBjo2qCIrkngBOOlCkFrMaVjrYb3qiA5/5nFFNwGyxhCZgBC2eBKYlP3E5uhXVJbk6MKQt04ESFdCcoDYbezZ0stjU5kx3sCIDmNkoSQKWOpFjWm8WpskTCEAOLaAQm1bbDZl329gU4bB354dbduHtCT33qEOAK1UNUsloIkGqFodBQ2UIeJo2I8oSuCnr88OmQCrgA8+dvrpHFreTE1vQM1h7WqdWjfR0LU9BIdlgTN/zoDpjiZ7n597rUTNsloke7F7b8O9O6IkQ0e0Aq2j4VgWFoVLe92KRWFCgq7nO1/sfemS27kyJro5wAiSOYiVfW5Njbv/27zY8xmTpWkXEgG4D4/fAEiSGamqlTdXX0FWYpkLNjh+4JOfZecMBWVebRmlJjoHiw5g8ybHdyQKauzgMOQMGbUcXRaHQEoxWBXAM6r3R74HVgF0g32bvGWRGN1K0rH5tCuXn998972odtrfsHTGUBk1lQMlLrsi80QJ9scax50g2khP1+33eV1hpttQkeZmX8ne240cuu9HynJ0QDS61Cdy0hCX2GLLvCdDH/vAo8PoMKf5ceWnwr0/4ASAlZ83xnSMNI/siMYTvqbkPTKu50t9S490m3yeAQ036CK9W9QJbrXwVCPdcIlYFoRsN+pDBtf9dddoORC4QRC/kcB/96fq6qBAjPjIIzsynSo4OhOOlEBuPf5gMyNyO9C7JHJcGTdPwOpQolVzaNXI+/6GO7PQ5bcJhX+M8oT6b73vOMED21+WTyI1Ku949e8CNZK5mtKZ71+eXFEkB+dXWfUGi4ZXxUUPMX6uXe7e8ofRJXno9f8/RtH9No47oSQ8QDBEwj3H++0lVvErz8SRgJEmATYIXUDAdKx16G+kagbz/WbjMqf3Mrx+nfCjI9Cwwg5Z29FTjzqRN7Hiolo0ljfOE9k+ZcpKDkRtV5n6Rbx/qyIWB7S74bsf4vSx3qI+epKgs5YEA35I13MYqEd9QEn9Q1Ge4hWOMMk3aN/KDlncGubEPBauLnyNEGEVXlbClqtAPUwlxoSlkIRNvg3RDsRsiu4LxUmBKMy4NzOQKhAwxmDejyrQVZrKwB2HZatxWCuuIqeGd2S7gj8wuqIH/hUOxHK501JKWHK2TxBp/AodOMQVYg3sCmkU0pIUEVIKcVCrhfQmVBbw9IWbddDP+aM4oqSrKFt4aF/S7ZcsWze6xl0TKhLRauqPGcR7OYZ+/1evQ6nySSahPnpCS/ThJfXV9DxGPunLlXzne8qctKw/yyC5Xha5cdstQbjm4oGKAULmnAYEOz2u/CwFABIhKVqGgEmgJixnNXTXY1m1MM9G43RjFZhtIHuMAgwCCIo6Ays1voqNB7e8cvBxNJouCFx1lR5ZXnvHW8PikDEb9s8K4X8xwyQPlKuU6O0+lhbkl6ngz9EHY9NCVZn4M8r0cd21mPqZ58uH7vS5NZBw999a8ovzvJN5fn6etDsRB182X0a33dpRyeD7RqtnlUeQQBRD8Q+JjcoSJZGoUS4aiKAcsI8zZjmyQx1CKfTGcuyqMCbFL4c9gfcHQ443B2iblkqwKaYz6qoFRFwymgpoVJFssyUVM0g0GB7ykVzoM8zZlfO73c6loUifUVypex23m3fbPFL9A2uVPdJE8BSlHTBz5UF3xiJEZmnt9MeXYukZzmP51zxi+YQ11zfaIAQ92fosuXODyFgiljOSg99n7A2RkvkYaEVhquC3P9U8JZyXuER38jCrEqdEKB15Rrbd/8tAjMsU4/2UjRcu+6ZWaOfmAI95RyGU8LNvNAFXBjprCNmFsNfFSkBpksO/s0/34J1MXeyva6wv7+7TsWgIXRNgO5C5jhHQSHFudRzQ6FcF2Zo/mSDz6ZY1pRAPOAU32QDrUISUWPGrSYiQDIlh/OvV8Z89Zq9HzTa8BTHeo8UXt9n7/EU45tDNNHegvRfOmdyBU7qS/khQb4JGCd7Y44w7ulVIANPKU8JuDdFNZFSWa74s2faUwv4pyIaguAEedmbYYjjZDLVvaqLVdVIyNiB7hPqy3FlfDXOoACoL6/A3QElR/IEGxYNTwESwbr3F2HBk9PVfWpXuKBTGDbJLgthz1k7I+O88lr2ouZF5lH/0PfoSPOu2h22pnosC/C8ifNo8GAca9Amm+vk9NOwAzVShvMXhtup8wgE3Zsk0ufqGg4VgLCH4BipCzXc/sYHftiX2+2XcLAx6U13segRrQTh9Q5C+pwgX27AnM9m/JUJ9Ms4we41bHSojXGx47ySsVD3Pr9ZDO5si8QZGHCTjyV2m9KdYZwqYkjXzqZf264lLA2a9IDw/sm4VDgqbevr2em4oE3kcs9j890GFV8TESQnZChv0lqDECEVBlpBLhWtFWRmMLkRASGJ5kT3UNHetqSkBk6unBr6ozxbN5bR9DC2fmSKRDL+bsCHzvsSqfKbuYEtGhYzg1qD1IaatDJyQ2Izjmpkhng5m6G6pcLSDgPMEXGQmC11DmM5QhXypUBAmOZqZ0yQCzSHcmqWsoEhZmqn/J+HYLaIbiWDa8W/QyEipfGMH40w6aLKQ5Z3zooV9zB3A6OKHt5d7HvFdZzn/LXTeNsmuwG0PW/fb9EmIx8X14bPm3j3vRL0wWW7ozH6teudluvyt+udV2Vuqw0tV1RSI5OF1GhECTaN2OPpgNzUI6EhiZjRukM+XRUzvQSDkQRhmNufwUCm6JegU9Zk1DAdW2N1hTtyBbZdKzeq/ZeUDQbtcjMoL0EAciLULSD+UM3XS8R+2uydHyRe+Fn+huWnAv0/qPTAll05voX7I4E2Ks8fzUr8yb06R572jbJii8T5thGirEh3I8ZkfW8QTkW9K4EMhZJ8W8a85h7mvaDnPL82fq/TcY+Ts1fh4MCg36rLmU8XxnxORiz+pt55j1DrQIIi29oavjbGwoIzCx6ZsYiFmSONzvaAzuCMQq9tx5zpDcEFOjMhApCoEq62ZsoEDiFNMITQlYl86leQ7J8pHyKA/iCVdPna+xU906Uy+Vo5Ut9zz6TKaNrcB/S6M7Z7oY03+fi84GDcq3ui+2997+2+AHquBZ5ffc2wOfF7rZ5Xe96V/HuDDwd534PeywsJgG94EMJ5SC5wq/gZI8JKISvAkMvdnoVatR5JcAfC/OsvqL99xYQHuOLubN7uI5xzgYf/Tl7ZDyZq3Hr5e4+CdyXdBKRrAhDoHiAAIieWeyZ4SNLOhF9p0NrTfHBqK8wsmmPH4ERzLzigW+cbE5sSuufWAKNZBLkky38s6wbj1zZn0aUQ6+ZE4ePz6+10WOeWpm9XEPM88CAEmy+4F4xWmh89LDqH0NFzj3txz1y9nUzIZF5nJkRm8/JdMWfk7Rsb0Dx3klaQrR0x5kuXSCDNvNDyhEyThge2dnV/2rw3y5K2ZW4ZABhlmtQDABiUFMNzNl79p33i1rAcTyhlAre157mf82GB9OrKEoNMCDPMf0qmiBekA4Ffe7hAlbVJKD9i/QCkTOYRrp4cpQXsAAAgAElEQVSdKZlSpBJoAvgkaGhoqWI5n9HqHlzs7FgYXbckJhNWLkvVus0Dca4NVAooZ4Wt5IPU/nNt4NqAnLDbzwAxXl6BZl7bBGCaCu7u7rDba072CK1sOet1TdRzXD1T1VL5fDqpIkVYPdtPJ5yXRYWqFvYQPjelWL/JPFI1B3zOGWDBs3nXN25I9GKRehm1CUhqKKhd4ZOJIiQkYVDSQIZ2fU1FBV/XBCADvlzRT+Rwu1OjRALKGtI0ed5QUuGCGjMojGys3pCCrgwFEHOK4QzYjXXfhg6tjsZ30R9vPHyhNVnTsV0Z3Fv3ubkJuah/9q+XffgQ6BwfGpQSY2NrxbUTwJdCav9NQ+/Xc91xZscLmzEBka9urHPoTTzutG7AzphLV7QaHgt6g1ZDVoOMUSmre929ZsZx9/zCnvtcIWHO6nU+zxN2u114EDcT2rjysEwz9ocD9vs99vNeaXsRVNUIIKWCnCpaLsiN1dPS6XJmpKZCb4KolYIp3PM0YdrNpjzfY97vtN2UsJs0VUUx5a/n8Atzi0HYBqfNgEC6NnvwHUkpqyJmtR8GPmRgEhWH9rWgbDAldTytxj7q4a3Ka21LBKi1garmva6oJkQn20O3ztt6T/ajpzCSkVAyIRcVXqphESGl0gXA2UK3u4c69V3jXt8QCdzt/U4lR5s9dLpRscTdez2p0LRME3bzjN1uh3nS0Pspp4BpqkDPGlkEDK4Nwhm1miGC07mi43Nv9D4PqlT1/owCYNB4BrohlMKjkb5jVdKZ1yIJwW0s3SDNgVBKbkjosBhwQ4Z6OqPMGiQ2Z1VG8GmBIJmySqO8CJGlTVgbQ3m/WTRqmggCV3JqGvlEAOYa0XcaLUEX6zb38euVPJMZxmEEJrHvg88dkZT3xeZnlFqULd1r1S0vOmHTIa3wHwDwUUB7ghxl/Z6RSZoH1SIaNUsnELtxMQjaFen9T4AXQO6hUXdcKzm0UR5tnp4YdJ/0txTwi76jJJnj9bP7bZm4/qxtv7jy2TxQjXYaQ70LoN7jD2ok5NrQ2I+2Lhl767uN4EWQ7m20dw47uvEL7ozefJkDk+T7hPqsueBbNUNMSkj3BDzTMHcIGO8ewslzyT/peqV7oy9Tf2eNpW28iZAeSecRCSRqYFLIVRtmKGL7ZYwQ50Str5srZwSApz5wOJ0tuo+r6l3pMsOXdr8R4lvdAgCHGHlNr8jQdEGA5ecmaC5u8pRvh9gno9K4y52erWd7EBLSLwn8OyP/ktB+/zbM13qy5EsD/qE0mXsFppRQ6wKCKsxdZiGrN9+mZUZc/fFidKwroDrhOLTqv4ceyOY5o4U1B71oBEPxPUah3orXSO/rOCmuBSqGzzWCxnBgEv+MX6KhfeerE6m3uXsENwAtE5ZMqFNGY0ZlgoFNrU8EhdWBZyH9ncUMZr3/ZHIWO4MVyjMkpwGI1Enc4WxnxBH/fC4H3Cm5gZugESstXzUiZgEiz3tiBpN6s8+s/JGUjEZqSJiTpmgRiEV9AUrTfjSIpaa0M7mo8e9uv0Nbmkbh5NbpHlZcXbLKN6ZpMtwDtMaa4sSV+uNuGrbHuBPfpeFl83v72DCPGHaBP58G/CsCJMPnE02oraJAPfZbYzN+We9jhzEOl9wsIA+/R5iVaIjqSObjT91AErg0om3MGm2JSD36h/tORyV4yoZAEAozReL8bOf2ewvFf9eLDHMcXuiyvtfroou6nM5iixq3LIsqxEWTnKQioFwMD3nEo4LMSseIJM17ntQgAaT4RCOTiOXNJjS0dSqNgV7v+2owKvaIXXa/45n1e2+Jyrbbdby+nZnrT/6xQhffnEdwGrvfV71GxW4+mKxiPJdqEpNIU0Z03mBDtw3fiIDGThf7sCT2/RMQ8qI7FnO8k4AlMtTulCWLRwowWaDTQQZ3vndefsws/yw/qvxUoP/Nyy0F51ue5XdCpgwb6gHw7Xbi4A92Bt9/wukKyAzB2Lo8ga4q0YGObNXC+DPOV7Kbp2Cce3ve0lvI+iOI3OV3D6T5eogIBQmLM96myF5aQ2XWUOqW6/MLAwcjJJ4EeKBxGrsgZLXWwzyPQkHXvTnTqASJhYW1sK6Nm+X4kRD06zvdStbHBLiF4X8W6H4/f7kq2d3j+U4uvb7dy5uG+vayfWYt6h5vH4Q2z76vzPY+uAL6zj4/SQ/Jfq2eMYe737+Wm/0j5YnkTUMBoJ/hrfP9rTcOxiDesxIv9bevAADGN8z/9SuO//f3TX4ua+dKnX+G6H6r/BWWhn52kylJt4oR/82AeSS8D2S9vuxS16jXQj06W5Y8bN2YJ5SC4PPiMMLDdCUitP8AcODwX4Vqh1Fkgfyoijvm7p29Xhkx/ptjRYRbKBmYVQCt3oMZ8Ly2Li1d9aMzZ31dQo6i76hMTj3lLER7t4R1BsOEzK1FmNRbpTOygzfroKyIELvOeDCj1QoSQl0qtliRRuxhvOiFjIuMkTABDKR7oOsEmvddMiEK3IvR1iklCw9qwnBTKnXhtv7PZ8V5OAlqqhqSvVXMMsfZKMVyfJvhhVqRLyBK5t0N85a0EOmkXuoxF3Crf+jzidCaIOUUYerc0323m3HYH3A47CNMseZHZ5yXBSdTli+yxNpwa1jkjMoVx6PmMj+fF815zhyGBAKYAUHCfr9HMe/Gu8MB0zzHMnFrOB6PoQyUpsoJmMKEW0OeJuSU1WCAoIKmpAIZX5++7uTcuglch0W+8nW8T1BG1KW5uhVMuSEeKNXglYfCyyawqYTK7cIL7pY3wWoTjgCc+tG6VS5vdYrx3fLuY+uz0yG9xAyP7Y/GAm/VKJvf29KX4crhxLV5pC6oGafvSuVro9feATK6e01GSijOt3UNZhHRNcKgpAv+YOjzKPTwuTL8N4o+vVsywLrII0k97LiH9vRw6GR70cOue2oEmHBFhWMWRjknTPOEaZ4xlal7mYspSgtHGhUah2rnS1yWR71frpQuJaPMM3bzrJ7ok+cmplVubVV4JqzN7cZZ6BDTIHLfdzZvGZp/NOZyEC6qgLwr08N41+Ytwoz62pnnec5F4VVW73438N16dIhoWMzbu/7t06ACtO75M03qvb+OJkCxRwBLxzJ4mqs3C9vaSYxFo3RwKOFjm6rGQXESa77VlHSfzNOEebfDbp5RfJ0GD3329ilBvYu5494Q1KpxFVuedOY+9y79DWOnMCj0TSSrukKhCVKFNA+qH1cWOD04wM3ufd6XgGi45/uJkgkfbQ8UVeYQkYUa1nqcDiA4vO7LmyRBRiWAjzXZswKjH9YBpGNcEN/QQXvA+5cI+ZDRXmvsphx07fvErRv1CpSZkrsx1Pq63BDRAACS5QdvL+MDotF4qHPjtiPcbBSgs93bRT9CYZwA+cbIj6q24ydBfhgMTl+UkxKoEpqPgEd7UbIvmSKtY2LvRzMY5fB4pPd85vTcCMaoHj4HWxzl8NkjNYU3vLfLQH3RUPMQ8/K9S4DNFwFoOCO9TMPsEQgzCGff0RerIi99n940uh3OAYY15CcGW93dd30wPbpBizjciTkbJmN8oxt4UT8X8PMlpjgbDspAi9OnDHyx1E12NeMegmck2QMkYPQwzcCd9jwMaV4AOQB0hMKTndVFAI4gOYB/1zPHv/fxjPs0xowXEP0CQOliQI2RU0pInx+Qvz71+bB3xzQK6hjwzlk0HHp9zq32AQboFVnnmR/gIS6+R0V61qWn/fNo5RkU/dz2NhkC990RdJHjy9WsUced5AbwawWqMp29j27wxR7JRATJPJQLF0gRSGtBY4oAaGp0ErDX6shEoVDt6QZsHCCAsu4FchqBABoUoAJIYjBTGHjd8vQFVPk+omAi0rl1fCY9VHOrzVI5ZaRUFD8QAZQgTUB2EpNF4RIATVTJnxJhP004EeFcgdQInu+8MsOjeSRKyKSRQgl+XnXl2KKnXCtx+saj+D4KWZVYb8pgaVc9yfWZZOnkAA0J3enYkks3rjDP53ajz+5w4zhllBYIulNON9jpJQ1talMKbEK+8U65vSc6HHv/6veVdw1uBN2xTwaeQd5+ly1KW2sNldQYJYlgJkvvIGpECECNpDwVEGnlDg6SWSoICDkBkGz0LwNMEKaL6OwBOzoKujpXl853b23Q9zfv9Sf+wKb/cLldd0oZ53pGTu6132k8Bb0JSd7FIleL03jbvogInjb8yuW7TmH5L3ubsM1m9rP8jctPBfp/SPkognkU4DnCzPbydatQ/2CFPbCIRG6lDwOrEGTozwcAT8Y0PqIz5PDf6B7nn7FWaHaGADjjS4Ruv2xyfdUZ01D49YFd7+4GJrpwEFCL6WzWZEIJlX6HK8iqIVkxj0Vu+nfPjAWMJ+hc3kORaPj3jtyFM1JGlDvxmzwUoXmRuVBPmAESVBYLncRdcb4ZYEfMl3vjz+LGNwmg76SM/iwh9b1tvVBXnq+ZQwTxc00Z7x7lRxLcm3Xg2vucVh7Y75WDEUc9J3rPwe6K8HX26XUZ29p6ou8EOA31uvLdr19L9fCW8jyKMUdyBZiM/XkQd5rQ874Q8JyUuToIUP67AUnMSpZ0/ga60dchinwcfl3p8ubC91W0JabemqXkHp/JhTijIU8/dGpdmZAzqZL2xilQQlzzorHt2AhBBvcY1nenuUDDsBGW8xm1Ne2LhepuTRlMDxtOJoRgFxwn85wyIcMliPjovA3UPwY4LNu7ft8thFxg8b3ro9bujQiFEDmVtC1CfsgBUwXQcLuli0Y5vM0pYKqHhBX0HOeqnCRQKfF8znmYKAHlEI9glHgRTDHvwnkCylw0NFWeANKw7iyM8+sJRAksDfNuD4gK/WtVj6zJFCzeh5QJ3LpwQ5ntwWgihN5ubGFdc656WKOxXmBY/5HDIx8TBS4ELDRoUqUPsIOIKujzPuP8bVEFPrkXkf6R4TfNTa5tNpsnzYVnIZkhSBNFOEB2Rb2NOecMiCqI2fKbcwjh1cK+1YrzckYuGSA1Gqh1CbwrEEiC5i1r+vt8PuH0ehrytSa0pt52y3I2b7xRga4epjolXUGj3g8NSITT8Yjj8ah51dsCZgGxqGSO+n4EqXXzKr2bdOErG80BH6NpqTRvs+0NE1YBWOW4w5b5pi3lRRs4OUDkoJP8mkC9y9evuGeghJewnfdBU64g0kLVWjujzsWbU4HBJkLCVpk+dvVG2eKUfv36S+9hRFcyvt1Sf2L9pEG6QalytY13rmynYK30potrUYPJ5KI3sp6HgMuBfDcYwdap1237zNfZagtyN56TmLeOvvzdHo64C9ED4OjzWXEWxi6F8LrjWyLpqQJG72nzwk255yAvkyrHS5lszwLTrmGue/WaTAm7acI8aU5ysj4naLQMdqkxNDx3COBaQ63cUywxqweYDVlDkKtCdpp3mCbrAxTGpWweLmVCzhNEKiAcioRRqONj9z+3Ihh3l+YlXRv2iS1+CvyBgOvuUR1e2jZ2QjeAyXnS3K32LItGlEjEGKZljX9iT/SdEvnIhz0b7/pTKWGeJ0xFQ6dP0xSeUaEoWbW32q7QYBe88vZWelYsSW8CZVMomzGAbr0CSZpKI5eCeVKl+W6aMO/myLlu3QCRoMGjz7SI6OF7vkNTGSKYYM2PqvZ+UAb10KoRRUQRgo07Gf7Q89XOZxucenZTyUABpGqO9JQM19gksQXJD+OVOEdqcMWt6RkqliW4FPDxpHQRNNoRCcVasAGZ6HNyujMhkaCZIUNO2RE9NKqK0qN5Mjy3dIjnSivHhbG2RiPxSZAOFgWmAUkYdJYr+V6BfGfGia/czwxcad2Vo9OhRyaAzbkwzOucwEc/f4j6sKJBbe/FPp7t2cXmfRl6BcAUuQl7yAuQ7gzEJYCfGxY5YcIO7UmNO90TXZ4YeDA679HWzNYvYQfCWWGEn3FS2mqyM9nQu52GyVUF6BnpOIMeCEWTpRtNLBHtClDjAXodIlG8Ctj6GDQlC/J9gpjCPN3rueHEaEcBqIbcCSDQnffkHP0Z4ZzPdLrTsbano3pUpv0F7hQA8iygOwI/D7KutAAgVPE1BgS6L0l6Kz5vTnuIr5rTIh4xwt+QdetdR6XQmoZ90fAKgtNpB6RPdi6/Mub/ymBbnEk+qxFRU5y2/N8zNP0a25oLBC8gHCB4BeEAEDRiFgDguJoP4MVm+g4uRRrnVT/vkH7JIPqE+bADRPD8v55j/vKvCcuXJxD1XOfaV4See4J5xwphuSZr+G4GvyvDhRuEzAPW4aE1IbpR+/eAo/p+Eek6Y/urEJxI12gSnw9d2+g76Ww5vCD0iC1AP3sOQ0MxOuC1OEcGv6SsFekeTt0NACVlcGawAIs0VENbCwkyK69QbM0qUaQJ0H1l8NVxu9NXpIp3H/tkRnqLzyMD5CFCnOaD/WQ1rOm6aAoeuGV1PMpJ02Yl0rmGpZQ7cwOqepX73OQEzJQwfRYcfyNQA0iAyoIKQSNCbowpZzBNmCbzzCYBJ9LQ90lpkCZ+LMnkJwIkjdKVzBM9POo3++pqoRt3t/Q3Oi+bk8I9EoInXhBRT9rYE6KK8jCMDHjqdXjawwrHETq2dU/c3GhBxyQy9C/gpO3QxftCI3+intvduSuOThhQlqRRZ2pbh8AP2ssadeV1lz/f4rI+XmJW1oRhH+s4JyQhCxpl4w4jVj0ixNoobaU0OzU9P4sAS0oo0LUUVaXH/hGIGcEo9CWyCD8QJPYzTyBpaKxvJFGnAPHobB5TxfDLaHTiQ42xjku/eW4gQm0abuznD5U/vmK+Ffrqawm53wbDeGmsyvGccox5hInixJBcGlmu2o+ldURAxv/5OjscXtey3TPDFrPaBsNkcXxr9OItmcTP8rcpPxXof/cyKDA+Ur5SD9fyI8t3gwEa8Cc68+25zIPZsLINdrE14vH238pU08VmazC4/f09xdFZAiEj4YUSZg9PmNwvz/rMrARca7jnhrOwIkhjUv3Ba8GxXTA+Fg8zSYkixKkT4SIWrEo0dGttgwJduqcCbOwkAwqgdVN/Zn7+ruVe1qGMRuX0rbnYept7eR5CtwOqSHcF8jaUuV/zIugKbUJXcE9YC1pcrLL1gF/3Tz9dce71j81vPdfv5DKf13ve57fK9o27gYYm6B5cfO8NTFrF11Uto8L/Wr3/SpLE6aI3n7H/CUAxWCF26JyJ64pkVZ57iCLPObXyCrKGCcpAEVTx6KEWW2smsO5EqHspqSdUAlrrwksilFyQsyoAS86RP8w9lhMRUspYekLOvwWcKMPnmiS3+X4S0GOPGhI5SgWqZKFkQmAVCMgXQSUBo2H+dbLwZdmEZwPZ72vrwJUI0mQF2JMpjXuvlJ1MxhSknDUFyGLti4DBZlghaMsCJ+HLNMGVJN4+QOYZRCE06srvARN7P4d+w5TQsKf9I5iDW6s/AJhQJLmweSo47PcAaQ75xpoPb5omxVMA6nNdM+1EAHX1bqtqUJItDz0BYeVNg7eqM8Jxbkjx8XI+43Q+6z3S8yYiqjw/qTGFwMLXL4vlIffoLmwGFCrsX5YaDJ2wgKhhOZ/w/PyC6p7mprhelorzsmgoW+WS42xJq6jMOJ/OeD2+6nO257J5tc+TCtaXpiEJ3aiAPFx7azjjjFYrTidVwtflbCHY+9KwJiRUQVLOpmACth4wI4z542dcYg2TexEC6JYZWK+zYQA2gUPAdTI2deA/CebB6a0MyrdLj4c/MILgzm+//qEW/mQ3vIofDWff9dDY3CbqoGuEM2sRgkEG1wJKf9eL0vmDInzbCByOdkGy59rs9/sz/cIAb2Bh2jdj3BpV9G+p10eEVEhzj0+TKq2nCdM8hXENCJinGXLQc0Q5YbffYSqTKnsGT2FV/vY0IsKMWhvqsqAuZ82laH+aM9ozAsP64krybDm7zUOeKlLOSJbHO+UEYkLiISqIrcFA9euyxLwivFx83UavYp9a8ZcsOkuk0cgpPMxD8e51hFK9oHhIfCJQExVuGY7VkIeCrcA3QupnC21tCmD34nbhfk/1oQr8aZowFTd4KKF4ZwuV72K1ZHWmPHCaMihdMHgjkgq4iRApcrrnLFmUD4TBRfdAny33uRpWaBOMKgkpASUzKieAemqVGJuvwhDWWrfQlucYlNDoeD2M5ZznYwblpPgrUhRAI7vYJ8MMspMFp3ajQqNfLr3R/dyRelsNdGycMVPAjEoi308q69R96fRTRMpJUM/GwX2HiFSZJYBsGP8Vf+9dGM+72NyI02WIdvP2fTjOIjVExWXZ8lGxfQXAUVZPXaKAjlSUtoBRAgto9AEc4aPzCdGeCfNBwIu+kYxOqrRgxg75IYVRinzSveXRJkCmCE8+B8pneF54h/cEiv6t59fOXVxdAC5IpdNflAhMFkhaU2132s5pCyLUJ8b0qdh+HMZ6IPArI93l2FdMhIwJ6S7Znlnje8JaduS/PSVAf45W9IeIQF4AoQXy6sObIThDbA76+sGMZwZZz8APbQ354lyjy7maw+eodHzf37XnSeefYGvzSJBvOq/5U58HsmhjIAuZLAL6TJGzXP9/te/rT58rV+x6FDIiCl6QTYk/Pq/KeXtnQPgNz0i4g+AFIvcXpFTe1AOBegNj7eE9rhmGuXmrjHieWRBAAwhc40pyBG8tvYN2b9SfOkTewt/oJTkduqaMHH6moFf6vvP5Hct2eGw8R+Omxq+lG96O85PCGFB5dxY1Qoo6Renqadh3ZHQVQffzCgeT5t5W/Z3xRKLK8I6/VcGnpHuHZwSlFRpoiHqpPFtOAGWgWGSf2fDnDEF5POD42xOqqNMPo4FTgiQGjM8ujwcsX5+DxvSxEQRJ1MwLpPULBCUnVBtbJtGoI+bYxHBZej+ZRLrzSs5orfY1vFG2995gFwLmlNRTkfmUp6RyBrYQ6O5kIVCjMQzwLWDQgBycDmFemZFFGX3FGSoP2fqP9z0+XqSurBzHKZ3u8HH37lyfgYvIH/bSOGcfON5vFu+HG+b0fimudIU9Gf8fzmnRvgzGbJ1O8DkVGExhBqEiSUYFsNSMQtXSkbEZiyKMSJo0NEvZ5LhaERVbyrKMykoKsu1l5oQkMmRosf67PGfo9VgCPzscw6AMtvF2uQjdXK+/urx5tt45eNvbMkBmld9fOwW3S5D6N+r83hIoaNOB9+DJz/LvXX4q0P/GJQAnAZ9UBouK98NT38v6mc9C+HJDITYy41fvbz5p83nNQzAIFGPaHoyQcOT2aYXAgswEo3ueuye6e6Z7OJpro4g+DYTmwEdjIPUve3uBmBzkjSRCFwY8EmFCD/fojTwByMz4wg1NGM3C6zSoxfv9lX5v+xMRZsjCR1k7GnrIhGYmSIKoZwsLUKVFPtVRiTAyRusxD23+Vfj0g3jo4+jqz5Jal7W9kinSh73pU+Eh0MdzNCqVj4Ni7CAUSnh/wvOmC7p3uVflTIzYO37f230Uve7hl7bGJO8t16hkP9k4HgSW02V971pZKc9vPOPCU1P1XfTJQ7Zv+/xq790LsMcjyq8ZKSW8/Pdv8ZzTg2914Xv1+937bn39u/d+AD4/Y5cPKEM2hOIibHKF9hBqJRecl0U9w8Xndd2vRBThMb0PmdTqtayEmEZQJrXYfD2e1EtrN2Np9SK0kHusCkRDZxNhqVVhi3RLSkoIQ6AxNJ62SEPL13aCxHMd0o81rKf1YkFkxapdlC7kdYDfTWG6CCUyqiM99lz0EJgeTj1auQn4SwWbN4HuQzNWIGMiw7NY++bCApjAm5t6piG5UFh7EQI9q9PXOJFAI21rrkb1bEdXwEDhfI6c1WTK9nXeNkq517+Z3lDqQD3eKVMoZMWYdRn2wtYz8CZbwp1xhY9rwJVTmfDw+AklZ/W+XBbURb21a9VQ5Zy8XajVdmIQA0KEZVnQmEPhDqjSIlkYZUoEtBb5yZbzOSILcGvq3X06qXe5pTkhSjidTlhwRq0Lnl9e4jy617guGNn5kBh/a4xlOWNZVJlFDLy8HlFrxavl4IXBNxUkAXWpts7KNJO4V6rOwfl4xHlRz/ecs+XR3WMyBUxeFuu3evO7l/v5dAIAnM9nvDw94fX1FaeTKtQ1ugFifxAB0pp6tSTLJeruxiMtFh6DHvTP9+nluQ1cGV/0nIZxg++coQ9rDxzdQJq1Qr1xNYxyAVEXEg+bMDzZMNA0AmArlBzhxXfBdzF6dqzv4v0+/puPXHbjA8Vh+xqevln/+MAGrH7Y8/zq945nVsrzizp7w7TZIh0vDEo4dGHuWKWHjOx4nxDLIL5vBjw3KIVCmEgU+etcubdqZ5Vzt+/BnDOICna7Hfb7vZ6xqWj48dTheiJNC6EeyQm73V5/W4hgx58o6qmYczZY1Q0DfF5UuKxehBITR4Dl46Tcc3crjcgBhVxwrn9Zc/pBOtFAFF6SQuoRGl6TIlCOzISLAnVFJAJSDxENX1mDETn1sPa56KcquAG4Ua/NkaeqUTsisTyGCqMbV8sFvg6XGuthQubx0xXl2ekcSrG2idTYqJQSIfmDdjLvH7gw2v58P7Mw2NQ2DM+FzgH/3ZiMQJCs40y2fzzXus/FVEqE81fludN+Ib7V72y4IbavGQ0k995PmhOdMoTEBORdaUEwqDxs7TypEYeczhfCUg3t273FAYCmjDIVcGM1ciJCcComa9B57MbaftZDUAs9a0IAn06AaOhvVwD6/oFVTSCNqjLAViHfqwBEvfCQerhdFloJJVNRr0Gqa/hrux+yCMR10U6bz4aHQZAzIBOBdqo+99yyckKMjUWQ7xXvtufO2RCg9QxwzD/bUfdJw5qvoz0BR6cNB6MH0tCvVU5Kv/vs0w4EAdNgKUAjX3qGYAe89nUQCHbpYDQqIK8eoUdDtwNQD9BEmic0E5a0gHHG5HvS5hpD/8n4zzUzZusyrC+/HrG7uzPYZ3j+nkyJicAcgStiPwHclLfY7yY8//6MjBlytFZetZVECflBo35AlIWDcrYAACAASURBVLauLyefyE56DF0daVF54vU1scEFb9pDwPPmt1gdAEIG533yCBFe59iPRBQKfecNRCQUyLbd4SkQAq6je2kOW1jX9YmRHqnjMMCUpb0f9TeNSKX7HTb/r0EfDRTZShnjw8iESE2k5TV4Jvde13lS94+m7DqW3yxHOgEVL0gCnH9/6nM4zC8N+/ns84lL+cYw9fa90xJRRmOZGBkAYXDzsTpp2jlBQ0zDa9opN2NzuZufwkY9DLMAqBHGZAyv3XdfV8FQ7FGfCPfyTkHz+GN9n3n0jFYrWspopYbjjJhCzucikeLJmkZ6SefhBAFIcToli/MlPZ0KGV0w0nZCiAguAo8exBAmTExgJtTkzjmMMEBzOp/RI5CQRqwplJCFUFJGMY9lIs1FnJ7PuJsKXrnhXJvVx5pnGh1mMtSQRlICkoCYLH+0IDWBUAa1igRgP804wWUYGp0npYSJgMqM2irEPNNVaQnUVpHn+QofMe6ut3/3QsP/iCh/LvvQcOgSRmYCSwdHSpmwtH5Ohn0vMB4JzqMYfLQoaWfiFSDy/rmxWNsMrUD3YTNv/OjhsC/dAG08diV3xX1rDZVHy7ZRUWv9cNi5qcdGEReHBDOr+ftI6ThyDYv9Su/DSAf3+cXmHIywxY0ahBlMpIYtpOneFkpIdhY0ggF6GtXaOg2ZNFVSEou6lNRQ1uwoVdYmmrbHCZ5uKj7M6Ti1A/5Zl/UM+M8RxnykbGr502W7rsHKoa/bDh5X5rJtjzIWPhNGs8zTrA6EFi3ypjEHDPdBwoii8woDKtnS0LYSfs/3qK+SF69rxP/6zsXG/1n+RuWnAv0/oBDUA5XQFXofPZaPQhcept/f/iU4vQVc3TL1YehfsmtP0DDuiHv9fwFWDOq6/d4moSvXrz1pvNbqeVWgrNHqtv8jib5VGLj85YEIr5Tw4KHUrbgn+DcLB6iK7U1oQHv2GZ6X1npCayV3/zThinlNJAs76R4YbArz2hhVzDOO5QKBUGAJG/tAHPxIsP7vgiaueXxfK34mlHntnt6+N1wJrd7kl7vdQ7h7cSZwh084mUf1yNRvw68/kSq1MVwf962HVB+V617XtfHtN4y8l51dfytyw/p5wumD2umtMNzn/iBAkeBNQYCGYB6e9agOwBCm+J9cfjSR6MJZghNSpALEAVZsDXyYBbt5Rq3VwrJrySY8DxhqnlhduUnDHzCevsiVJYLX11e8imCeJkhGeBcMKg0l/Gs1ptmYdXAo/53p/ijx/WPLx6FKdgbDJm49Mz7vHYG6MImZwb8zGjGYGIIXpMBUxsSA0L425E8Z8FDYNHj/DUIDbk2F4LB15oFxGYWwwav5OWghIOnF+igcaz/CdFc8RFc1mlXgLGe2nTHzHLads/I5otgzYRQQlV4vK5hPjrOsf0SY5hmfP3/GbPt7OZ1xOp1wOp1wPL6iLgvwSDg/LbEOUjn24NJ0T86ThlX23ODlkJFbBnFCJsbpdEIu6rXUTEBWlwWvxyNOp7PCl0yRkgAA6nkJz3IR0RC9Q99VEW+pWBxniuNzGc404flZhT/kqVaIzIN1Qq0VIAsrDwDmabCcK87LCafzGdwY8zxhN894fHzE4XCHRAobzudzKNCLKfaYGefzGcv5jJfnF7y8vODl+RmnsxkmjLSOK24EEG6obJ4mlupFu6TCnIQEQQKT7/lxo/YzdHEmB0A6mskEjWP7jKBGGyWRWeMTqDU0P4PmLVly90DzMXQO16HsuE83/R27Ftu49+ZmIT8Hm7GtXryER95yhBz/A4VWnb1yb1PkvQf81nfUeevd7rW8rdNhqtO4Q600/N4Iuvv7nbIJEOWCjbF9UJzLEeV1oaTt+NFb+epA1/d0rxXM8x53d3c4HO4wzZNGAjGY67CA5uggkHo+8jwos1NOyEhISNhNM+p0trzcCzg3cC4gDZoKMSPbKs0Ewzo2DzMPw/+NG5gF1QxMvN8pZ6TazPhTYVPghfjESiC0Vv/Z+NhoFSGwCbfHJSMoTstFvb3LpB7XHpLST7x7xXkEjiYM5oZaK+qy4FzPWJamioFWB4UilCNKGcXC6CeLlLH+bjnV3cPWYHku2QwNBNya8V+e0koCLgM50gloBA+F7foea15Se97zobtnXwnBawIyMGWLUGBGBZPNSeSntzD3uBDoKexyBbXuLZ+7HPUBYgxKBZF69YZSktz4qeMiNSowJWbQBQiFtiqpSfEQuleUsKiC1fCAkPZ3TY2Pe6afHc8nL5TM2LLTU2sFnXuk2xSSwBU7um1tbwojS9b1QDcWDYElaQqSW4E6aaYIlRt9MWlsULzkHmkCSLPfwxhdIbQBjgKoMnxP3Sp6JXXtz0UPiEB7ghxHPKhKUuoWFLZGAmCJ+sj+W8ExkaifQGg4otAeTF2+4iuU71XRqtGNNGVMKUqPlocCek5G0wCCoyq0bOAywo/ozUBPYL0jtI5BfkFkXuWint2xQATBgkRzrCdB4d3Drw84nWvUTESQVwEdNCWRsO5/V55vlS03ce49gZ4p4Kauuz3/vH7rrfrGdWBZ/3ajgzGntM9YsrORhudFRO0TBRCmCPk+8igeTYVkj/QpreBFnPcguAaDKTCA157rl65J7iwcOLq/HcnB+BdA5Hm1/QmHmBMet6OPG112AnSef6PzWXl5+kj9XpKNgm+Yr6vK8z6Zw87z9gQiNWCfrB/Xpwf45PnO3Thc7Frb9GP0TtwaJI700MgDxXjjPzeE8nujgZLT6qaYPC9YUkZZatAY3LqSSM8Z9RDDLH28Mo6cwnhKAMyqUcZpMMgPZx2DkQ4XBYRs51uo44Ue4bI77Gjo9i6DTASknDFTQSGNeFfcEE47DGLGLAJqGYIzwBzKpyYa1pq/vWpqG0V8aIlRDd+Lsl3IorRRJoLkhEmKKqUtdZfu8QSu1fB6g1nF6XqYUUrJxSKevcMnjHvqjXua87yHZ08WRW3cEqpQd35TOg/aibfeltEjGM8E9f224vvQz+fVosBXjRWBeHfMf659VfzhkX1ke6iisqs39K4ZDGzLiGHG3x8tId+48mbMnM2XRwYZncvWLwzOCCEj6vSiQKO5MREYDS01VJBGXmiMnPUsLK1ZOraqdGTKESlCYIrglJByCRihs98gQmDuJIZAPatdNjP26fp80OU4HM9/7+Rii/n/uuIrcaIL0uvqc158TqYygc9s6Rrkw/JkTW905UYgCgROuOlE8k4ZqvpZ/oblpwL9b1q2ik/CJk+xXD/SCpJXKlo8vaEQ28qytshMjANfE9VvA9ZPoMh5RpTwDaY4JycZ1+E3RsHjV6i39qehrRE931Kek41li/y8xAhuYJIVcT/QAqOs8DUR/pHIcgQRXgDcQ/AM9WQmEfxuxJz/u0P3wHoaCFRvk0VlZ5Du6RYErRFdOWUVsCS9I6KChNrUolLDyq73QxAXRkCsgPiGufkjxXcXba7dkNdelL8CqTwK8O0DFT8aUjwIIjecF58T90AHrivRCV2JLsPzJ3xdWVXL8OdlNIIButJZ61wru8dQ8O+VjP7uiVR5vscDvtATdh94f6U8f28eL5hHnYNPrMzwyGxb1EYkKBxIDBz+8Rn8G+NsnuczPuGVvnbYIrf351agf/UZbzuYxw4PgUsw4IblF/rLuD8s2rDRrzH27j3sHmzjc7NZOp/P5xA8LrVZOEYbHDpxOBLDK0Z9RWymOO/zVAAivB6PodBrS0VtDXf3B5zPtcNJIzbVuz0bE5lwrgty0hzoavHpAk9TUA7zK5vP99ihgbzfPHdrw7290sWETzVeTyFUcphOuAsBgVYpmHY7PP2fJxQpcDFMloT5l4LlS4hVzBudXbwQAlatl+DhtMs0AWBw7aYyOsVijPI20KQz0SoIEVHPb0kGyWVkpHUa3MBCRFTJmBLKPIXigEK4O8hsROBBLpkFOQF985hgG2R5IpMqfH2MvRITmGxgoO9tC5lCHQkH/sqmGBARDSGecyiAqDHQGNN9wenbokYCIHBikBAalDl1xfVpn5E5I58ySi0moCDAvAFDyAQAjbGczjifT6i1IU+aV66ZEKqezjbnqljPlu9Yx6PMNkOAnCC1rpQx2cL5qsO2Ko3qUpFEQuGjiQB1/tWQxozfZMANDGRKoEKYphn73Q673R67ebb1UiGXpxRwj0xALFRcz6Ongks/XZ12TBbakHICcrZwdDWYTbENHZ6RyZRpfk08ONpwvsb9u/pGRisOZ1uXBzlZyOWSUaZs6QwA5opWK2pl1NbQxY42x64Y9BpHAdIAD10pdLPQts/joDo108Pfbd+/Ua+sx79NRXSlsTeuXBHs3Cg3nxrQlMOPm57noyKA16Ko1TuJhhHSUP9Y57AmI2jfCpvjOfvPFLvOGbiLgQrqBgGzw6OASeP1HqJaX+jeszBc5957Co8KioVCn6cZ826P/eGAu7sDyqRe5ZqvvFokkWT5rnPQJe7VpUfcYIMNLCcyj2KNSpFTBpcSXiyUGphVwcoCFS7mhFQ057ZL9RnqIdVaQ62LKtNd9aFubBi9O9fKcwovYUVB/pwtjJAKqOMaBSyAjUnnt3uC+ZyrLDv3dlyICwpjYmFVUHvud66s0VtcgOywFm4cvNlQsYFcfOX9U6MGV6WSRQ0Jz2WD024sRYnUeNNyuSYSC6u/gJtFfXHFqb4Kae4RZgZ1GTF3KbnSvEQ4+5xyGLdpHmgdK7OOW3FORWuM1irQxEL01nXUE6frDAaLaIodnV/towqyO6KnnJFygSw11lCcgPa1gNFwKYFKMX47IyUNJyrmMaVE+2CgZH1yeqAbZUisNUs3z+8GeH3p1IAvgbInFqZetwCuWiPDUyICNFe4mwfvYH3sZ44mMuWJWLp3w1cW4SCXgpQRuDPmN0Zl0RX2A3dGBDlZpJs7jUDB7okugBwZdOf8hONYNbQLuL+3syaOj9fnR4frMA8QLD4D3oUVdlVPZajiHQuAGXSXkF92/exBUO7V6Oz1+QXyStjTHrtfJixLgyQEPcwvembLXQK/MJrsARzVeI5E835D90qPqjbAfBtGBlCwi5Qw3uMw1BGoApyUxhEAifb64BGxDufTosolV9pYNDc56B6YUoakhOffn1FJA977/HfI0ItTJ8XSU9H9PpSkfr5EBI3OcXXkQMYxrhQ/ogqq5HtQ3GhBFdceql7D4DvvsUMmoOGk0UAgoBa2gxBPZ7CiXRwuA0RHyNOdhmG0cE8sDEhDmXZwQ2ftUTUwfoDH+O8Yl3RjAvCQ7l0x/gw2pXsbcBjJHoJXvQegDvIP5yj8invXN/Sc59s5BTxce6fuxrkvQqs2bhr+3aKPbOFEEOmhogNDa9kEE82N/gRxdr1fvqckVnjs7bhD1nX3Omjzfbyn3wKP+r4BGaxgcKs6l8uCJWmu85yz4orG0VzU57yZIHIce6+WBHAi7FOGsGDKQKoNCYSFCJWGlDMAnMEd040FHLO86t4eW55n5dFMjmDtasQzDeNeUsbkhnABpxNKUmOplBseMOEkjEN6RKaEhiMAzXUusIh+mDRiBwHPnMAgVG4QIhwaIydCW3TtDrsZSGqAeDouQFHjpYkLiC21JtRzuFBWemHcTxRTEXQUhs9bJXYGWTqbUjpuCmWmrJ5XtrAbngkLuheAKP1YjQcUhIGfkEY+aiQoovizDSZmt7qpR0KNFt3o7KKIG1h0mMnQNT63prnP4WPpPFk/iENVQJ/MK5M19jNIjRt9X3URwDysERFwGtscnhyoDmv7inHRIHNLtjDjXPofw5zXuAHcIGTp6QSolk61cVM8m9R4rcxzX3symsgiPDRpyC2hkRqsMNzoq0dOjP0X07hCukH2x6U3ZvGj8/tXlhE/6KfBGtre0eIGanPpyUAU1mtkq5QILIQMaHRGqKwH29pMNhXUrTsMicFgMpMFWeMxLyFz2sB9l6X4mQjceOt83Si3nv5Xr9f/X8tPBfrP8k8tD1D8oEwCmdf5GmSPBGbCZ8iQA/keGg79E0aC9vsByFshSz4C0rRtid4mEB7RrTSfB4bpHoIFop6JBkgPJpxy3v/pah9IQ/g64gvcYQR26rmOUlYhIESVfE0YlStq05Ct4pSYj120wlGcPXLyV8iZD5d/BwR8rVyzO7uXteGJe2r7GEbPcB/TmEMcwFUPdH2u74+9dEbyiXq7ntPc234drnnbY4j3cU38+pgj/a1593HuBKEwb3jCQW5bonq+8e/xPI+y2UAHUeW5M9jJ5rpSJ3azQMMz//cXJHrEYnUkEezlE07Uvff/Hct7lpwOHxK5GQzZedZfp9MRRAm7ecZ5WYKgVuvj0bNgZCbW3mNqzeyWqQjiOVl4raUuaMJIFu+zWTSML1+/mTGOwRVKGrLWrGg1okVDySVyPyvHNuYT/IEr8wOrKwPz4J8umPDP9Ngt8bkxdp92qF9qzG/6pSsHk5B54jr+sdX4xsCjh6xUgQKlUZzUi4Zv1/CkzkCLSFhzBwMp3VtFYTf36A5X5nwUIhER8jSBT10guBbvmDDaGN0I0WYbmS0EcOCMP1hUaNqVj6Egu1F6CGBYnr1BqM5iKXg1lOEymWD2pIYipUzIaQkDMxDM+1ENVMSQ5PF8wnI+a0g11Vaj1gY2pU5bFkuLkiBVQ2CyK16g+J/Rc+gBCE/BRHquwytABNJahG5WQ4ESyrtskWREALLQujllSBEUaL93uz3284zdNKlywkLvei52Xz9dSjFGP3VvzUGp5zREIrLwuqq0SaIMehIxBdKwHnpzFQlDpRMwydGWcbz2u58WD3XqkRmmUrDbTdjtJqRckBNQWT1Sl9qwnCva0rDU7tNEHvLQz3cIogaJgT23ovU+spej635uBkHXd1Szre72Xbl9hS4V3X+mbL3hafO57Yd3hqwv18otGLFSnq9fuHp9/VP3V8AlACvFub1AJKvfUa+/Z+cMhPAAJpggN3kUp4xiXr6lqHJ7mmbs5gP2hwMOd/fqWU0AzmrQ43m5SymY5zkUs/4PrjC19BhdyOV0u3pvixT1VrHc2iBWxRZb5BLzOqeUYnytqRd3qxXnZcFi6RlWqTvsP21Tv7ho0NU7fZ+56Ej/Z+pr58WNAfy7ECFRj6Y1tu1r4LRNeMCICRir8ice1pLH8wpVmkZYfeuHCuoV/3FD7EuWuvKO8vCsHgo1Nk+0r20lUdybICZwU+X6sizhYRVjxwBnICATSvuWy6nvn6lMYSyVsvdJQFwt/7qgVjcOqhqRrDX1cJMBty2L4iTuinQXuGt4dwGzwyXbz4OneSrF9nkPEj16gXcFeo8uNB5A3zeR/1wHMhhO2T4SVx6MMFaufF3vk06RUMf3QiY8lqAZBGa8uQiQSc+F1aU6ZIE7FkU3qq4XTYh95MYQHgo5Dgg5/MoQMPjYOq0N0vihYxHZpDz6IMd8DOyHcpfRLE1AvK1k0ppSIwJhgrgSdAtPfepkglO0ujonaHS9HeRFQA/JzitB6IzlS0J66PCEjU6CqLEm3RHkuSnsWoU2H+jLzfAc4xfMyHdpfd9Bh9NPZArCpKFuyUmJg68hmczD0gY5rUuICAVkSqdthLixPyMs9D9hCVrH1QmA1ifP/fdqbTb1bVechroIHZq6EcU4a3rlBGAX5wjwpbCza9d1/68V3IDKhQRPoG8Ewh3y5xw9UGNZ7jB/yK3VPcy97DEWcXrfU+hA9wYl/aJn13KmU/f4X9ex/n6LTtqujc/paOz/w6geAURU6iYBr3r9k3Q+LQMgU7hE+742cmM8V3mxzSMDzu1YrdMvozp+/GYtqzGTABDzPKcEKRzwTJhVLgjqYxOF1043jX1JFr0lUwbIPMNrRmYOG1+nlTznecpAJkKmpLA4UKuAWDECOw5rjClphBwRXuGuO/e+TQnFDRHJ8b5YVEJBkgwhNSgkOpth8nCaCAASKAsoTaqUZIPtmvEMzXF3sjzrUwEnQF6a8duEiQoqVTPyuFzh7dmXccMO++kjJWCf1+eKZsNNjp89533J2RyzDG8bUhTWfNpsUTjcSFpEw9e7ESWlDJEWe+JWNxUuu9EEHGBfod0xRLwDWvO+++y8VW7hyg/i0A8WAXBKXYk+9uwSXq0k4R0X28MdTpmhGcyQy/A14nn910SQLOJCI0Zipf+bqDEic1P6MGdMU8FuntRo3dZP4S6DJaNwwmJh3pnGXihaZuoK3auzt+GF39wB37GHL8uPXb/3ytjSGEFAZWgp5AAqB1XYFg4BAMRSIL1dbFOPNDFGA8fowLv9Hbmb1SSL/DOn7Wf5geWnAv1vWEZBxCcBvtLG+1wf0s/hYN+LCn+eSYn5O9Cb3udvlU43yAbB9M9tzUSk3tgQy5Rkz5CyFJrPfB0KKSEFgU6kTMWjjH5OvR33ZB+V0YQRNpEBVPu1EbSu+7vp/cDgrcY0fCOohZgzh10540QNcC+a9/wLlPG4j5ZoIC7HdruF33YunQB2ZZeH6XECSnjwIHVL8GCojDq46q67Xc3vK9fQ6Huy338G/rg4I3btTjogFHSG8Npe7srzj/ZYxTCu5L4TUyQP9WHz3dsQaL+ckXwl4P/75bP25bcvUa8r873Pe+n5y3eyzmXuIdt9PBVrBf5xeA/o737Y8xzrvuiYycQIvd29PKLiG6ZfP+Hbl694NH6n2vk5/M//geV0BH5X5eeCbxuC6Xbbzue+2b8QtPrpu1LHlfb6nkib++sHtoJnP9fFwrn6M/M84fnlBS4lbJafuFhI1FpreBkZoARwLVy6tpdNmO/esxCEoQ1RQp4KXo6vECPmI1eZvb+weqC71bmAMU8TUirqKeWCR9tFmmd16ZbyDk59Hoa9eX2G5frVP4iXoh6brwoVGLoCfVxIncrISLh6v9ZFBerEaHjBlO9x/ragoIAS4eyxTkIQfOieCt8EFUACY/eP3cB8am4rABALIZtyhipazXvcFAmp5CFcu7bgjL4LgAMD2xq7IrIutdfFXWjh4x4/XZihof/UcCCXEswjmSEG2DELANoy1IMg4K2DZxvElSnMjOPpuA7luyy255XZd+/scq+ecS70JgKyZIDJ8hRTCJGqLBpuGOqRVyYNvedzrCIsNkGNCh3BOuc56/eSs+570vfFzmY1RRUI+m5rpsA2oYfonLbBQr/VCleASlPL89ZU8aVpWBg0KQZKKYFytjDICRMXpJSw2+2wm2dV7E0T5pwsnGPFYgo0rhVNVMhOpsyheVahGzO4NtRcVTHuCsWkzL2fa6WzEqR1hVYoIhNFuN/YRqa48egGayYRHRi4UjP2yLCXoAr+aS7YHWYcDgdMpaBMGa1qHr26LFjOFc8vR9Tn42ZfjTQSra73Plhf497IwN7esuuhOF2atreGajb1fhchdHlvdcr8HPej/8dlHfDjuKKOb/SRYo69iBPEV9DQik42WmkFL7aCZhoub/qn9bkStE9oRHyxfo0pExy4j97XHp2Bcra0R6bcTIRU1ON8G267FDVyyVnTJ8xlipQloBrjUkVm7l7nrAJ6jXYhaI3QGqOWBjQBmLHURQ3ZTLAs/inmmW1pntSTPEXo9pQoQjJDmnmfV9SlggcFOsw4BX0KjJfwjdNPIiDh9RhS4EQgScgQbX+lVB0MBIRQmTQcqv+1hubrJGJpQax6UeGgNAkexUOZEwFIGRk51n7cF5rjMwFkRkzEoEYA1aCvHLc4T9SSeq+TOBzTvphOOyIBaAQvfU895voxC/g37k2iUJRP04R5Vvg8zzPmeeqeZR7hSNhgqu6L1hoWx3fLokLVVpVug3qSctW1XepikcRq8JFjP/o+FIhoJA/35EdVBW3O3g9dt1wU33CrgbsSaaQWve5z4OeHLA+5zkJb2tARox+v8kUS7fo8ABbqGhKpiNhkE54KPcJUw0NpEhoPYVaDj00drxNpHnMBxDwNUbQ+94j0DaVefCkOhxtfiAVFlb3RacdFP08ayFZVagw5I9I20M4jsWzhISHdAYBFdjlq2HECgV8FjTu1RMNcEbpCOJNGpGJaVjIFwHkqsn5ZOGBNKq/zElGrTPD+zLh/uDe5iha2+4Cu/xFnCAR77CAvDKIFMK9vhk6ZL7uLnns2Vv2eMSPf5VDChMEOaa97tBH1eKekHLer2ztaITAprcIo8IgiAFAOGe3lBDno/OxphkBp9i1HsaZUgYRJ9/aLIN3r+UlOP8q4CljP01DHuPP70319tnRwihXW6wuUxynmE5kGkgggJByw0EtMMMtRZV6yB+iILGrgJKJ9bHgGfwES7kBCqJ9OAAFlmnVvfibgC8CrSA8+hld4HnPCAQRgoRcIBNUMgT2Gob7W876GvAnreR/3xLUiN+6PyvgxUh8ATEIRuW7LX39PyR52RdT7Wq95r8j2CIW80c3WCSqLaBAs5PT9qE65Xi5pxIFGGuSP6z3kZ8FliPa+ALAolrU1lFojTL7nQNeUJ/aeAlegGTwV6kayBvM8gqXzspwzqDbD/UprNQBn8yAf6cQMmHIWkCRoaGhsziKixm5LW5BBaKK5tTNUYU4gtAxkuBGb90dPgMXTRJYHnOkbinDkNmeIRbnQ+WfziBdRT/JdVQODPRUwC14aIyXCRGxenwnUGlAmiEV+qa2uFksNUQwpeTorMiOsgY4SX88V7NlCofUXX1+xeVIeFhEiPmelgVhIFaT2LI+HhjQVjoX1QWcIFC/CzipEPV1b64bken0DoywqQCjQrYcluYxCT7vLlUBqxGnkptF2WudkaY6W5vt2yyis6YILI9qrs9ivvXv6hwfOw6adobB3rLufrb6ASspQnAm91unmre7gspMMFuOjwRFhMNIHCSNBnVWmkrGfZ41oA01PUFsDc0ZmjWhXCBoNglwZTBGh0ijAGIORq/Z7Oy++b4ffTnsDweP+sfJn3r1eQlyX1qt1QWX6BkQ22dK4kFr2uzscTy9RAyFj2USWiFPph9p+j7THW8VTnK0/UwAAIABJREFUYHokwLGvztOM68W25/JlVd9V3jovP8tfV34q0P+mxQ/K1w/CrAdRZfl9N29WovHHw7w3D/Ejbnu7jmUk1BJ+QcPvcS+hE9eDEwKAS0/uXtvtdmDv3wz9LO9NE+EhkBZhJICD8bRPjSCoDbny/PlGrWMfO2/lCgh0BpWUAEmUuneYdOtFZiUayRmBtSRUlVWyuvSDtsWq5/+2xcfaAEz4pAwkvqJtnhN0D3V/7+WGos+vbkOrCz6Wg33s11jqb19AeERCNwhQkU4v15Cxh2wnqJL8mmJdNs//iDIyw4CGp78XoOKbepf/9hX/9esnLL99DU90fVFC+Eh4hNC3uOldGxX+2zb/ArD2p0q2sYzKc0qkYWCBUGACSge+nk447HYqnJ2A86Jkf8qugLUcpYCGyLZB55xxPi8a8jSp/XxiwB3gTsejtSHBc62AH9FwX3BeFqiif47r/Vhb2MLUpWoU//3ry4rZ31x3HELYKyn9eHlq+EntgTPu0EywClwKx7zW7tNnzCEUBpMx2Z25VaCdhtCiiDc6PAdBBeHUGc1csnrewYXGdrKMya5LxTRPppzdMKU3wHGEjrOw3602lCmvpDZuKAfoc3+a4oeGHn55ecE5a4i8VrsivVZV9HroqzAQkG44BvcGBULhTGZ53HNmkyoomMPa2N8trvRu/Zrj1zTPoUSfpgkCPYPH4xHy8gKGoKSEpbGebZYQ/nEow3Q/NGETB/VQ/dI0mkMiDdsMAqgUDeWeEuZpBmaE8cs87yzHcEHOCfv9HkSE0/kMOR51zkTQFg2/XpIa0kx5AozZbq3p826lDbVeRxKQexaJeSsZQxrwmzQEWuyl2EobS+yrxSGyKnjI9pp7MVJCKND3ux3u7+6wmydM84zGDZUX1POC83lBbYwXU6Cv2/0Y0Ln6lAsP4r/b7741zov7fxX5MxAgwxH9p5bvGZrD4T/cxVtL67gqHnNieKBxSWFkIlUsej7yHF7mCWUqKNOE2RWhuzmU6CKAMKFMk3qKA5DqYZvlct5F8YMrSdlSTGjUiaQeUdxwOh5xOp+xLOcwGGqVUasa1iyWfiHPxYxqqOfOhoVwZIQHsytZ2SLFyOp0dtROA97u+HGdH9NXy8MvO77qinMbo4VDF1H4sLiimbrSM+ad1AuKuRlcV3jsBmMgV9CmMBBwJXBvVeeOV8KtS+FsSppjvpQCVc+qcjyMKJJ7tsOMKVL/TBmJ1t7eft/b9HGVUjDvdtjv99jv99jtdiYITZGCwukBgaDV1o2wFosacDrp2i2K71w4KiIm2G+6JyySGJtxhm9/l+MC3fhaoySk1dz0TwAW2hUAwAmp0BA6X1VfboztUVFccO/nKmWl+cRx6JXTvfV097X0HdaVRL5TO4EfCikCSgKq4VLnd7sS3focKVFiU8ckDTtFBdgLgYqtj/MYNERniRNw+Xv16yzKO58BNBNmHzbAypHK0YzT1hKHsaOr63nT6IaSQ4KGSF9wDqoz7pkcoPf/bAqzXTdkiYn3qEOE+rRWkPn+6th7fd3LKsc1PlaIBPwsSAmmDOvr7fOkhgO236iFAj5hRns9AZjQXhn5LiHdJYjs0F5OF7jG+69/09iJftZGfgjnVeS5j5Rr4x73zlatvqMDgISKlyu4UX8xIujPZix7CB3hIRAa1h7zIIF8EY2Y5TScrOsYi+6eV7jcauRfrp9sM3AZ7m2fuzUf23PV69NyNnnK3ow21Digr4NGrftjDGYRU7Ayq5fxDeYwwXJqwxTp0D2fQZA2xo28XdZ83c2HdCRkUaOGca3OoX8OmkoGaaSs1ELJrhOrsywbA1HH3b7Gqqy2yFfmhS5Gu6SUIDkhQaM0SErmUau8ivM1mUiJd2FkEYjJAZjU+LmoNhCNWJXmpA5GZgcOIuAgCZJg3tXaWYJ7/hNKelDjkzKpsSEzhBuKR0aDxXYwvJ4h0Cw3CScQmjSgVtDSwEhoWQ0MSiY0zqrQTwmNxxnHJXjGmMJmoDjJ53b1aOeVbyx9RHsZsYKvkwHXZLAwjEWHc67tUtBgY+QhAZAtJIyY0WljxlyKGWwijPG8Mk+n5rSNt5fdeNJgfja6ooEt4oFG82EZcLvD8He2/z+DZZnFFOhWSICJFGV/T+kwUQJw3NSdi0UbEk1dQD43tr6R7g1q2DiZs0wuCQJCbRr1MDOhVD1nifSzkkJoTQVi8ywY0srentWt7jxoLrrmkPPPKX8Fi+znxiM2+tCOxxeMRvRb+PpXzcCH6v0Xzf/P8ufKTwX6Hyi3gI0TTNfud+smAYla96/FPx9vMwQLIkObuKjNQ40Cmuf8TjNZ4Y5IlXhvIIDLi0ZcgSIvijNhI61x7VUCVMEM4Gsw0gNTM4zDVc8Fn8HyBQ2/RT0sCOtpV2463ngK4Ya1aQRsWDUbARSW+VfGG2SQcVLdUs+YmcFZMYm3ocJqD5Xq/fskgiqMs1mcNROIKS2S8CkxhBO+2AgCx6+gu3oVkBG7vJ1d8WeMwIF7natlonoPXO7LYHo2ipF1vSO7ty5dEHdjIsdn0ffG1breuPcjykfqfybgkyizVjc5ysf3XVk75jz375rvXHAw4uqVBPeS8EyqMH6UB9Qb5h3XinuWe14wgSrjvxCwl2+2x9SakrFWJI/5zF0R7h7t2xVyRfq7CvM37ndChCLMlBPRwJoXubOz08jmm4D2+1e1JhZEyPbX//2Khifs8KnX4/uOtJ4X0jkZDRLe22/Ywol3hn05Sh+TbO5er2nKamUqghWMm6YJy1JxXE5X4W1rjNfTCSktUBpXjWWawa+cUm+TEMKll+MreojbFkLVwlPkSfO80XHOB0nsFo4zC051we6wB7UubArlhVl6qg62h/3q3qub2bvAU7S670YBWwXArTLeH79P5m1H3jm7l9L41EGZaVOen759xfzwacX4ZTt9C9QbJOHBs6sOAzLhv2geMLL30mMC14q8K6hnzeVYpqI5VLOGzNOQgv+PvTddcxtHtkVXAKCUaTtd1dX7nPd/vru7JqftlEgAcX+siABIKW3X0NP5Ct2ulCgOIIaYYwUDK4KfmxNXZSgA/kTtHSkLVB2ukf+plfdfToTxLAtTr7zut7/TvA5Ho9GkTzLKTrHHxCumudHxI/scBm2fkJFV4M9Rg59vKthqxefPn7k/TBHXNrIYgxWKoKRiLNGy5W2ju0PaYdMFQOtKxVW4b/JygsCcJSlZfVp3piWkyr+1N2hrhFXOBecT646fzmcGoV2vjBLXjrpuVsuce0BTh1a+X+u6gxPObpxXIFut47VWdAXykgl72BW9KUpjPXY6/TI8OzunxIxYO+5OqbNlmG/rhna5Yq01ajKnwhrOEBn1hh0yuPO7XlfU6nXk6YTYgzK4LGTzY2uiY5SHiL3AH8alsbyGsBnG91iPlI9EO0ri+n18OOPhgeOuaOH4L5cVL5+vOC0FrSta85qcGIEkE+2ZeraXeeYOTM3v9Vq2xP6Od37CHXp1fMy8975ZZ3Ya+yXjyGC4X7vt3azzQ9/uZoTofJ7xmDTzU6MZs0g5hAPbA5OsGw4ckynhH2Y6osMABc+qTn4B3BisgDkuAfEyJGKw59z8Bqc9nOfLsiDnguW0YFkK4drDeb6glAxVATRFWQ21mnqitq+tnrmI8UIdRsVmMNy9NxQtUM1Ao3P9cr3icrngerlgva6AlY5QL8WgVs3c5jynzHISII9splOs6xXr9WoQ7hsDaI02KrxWrgStSkDscwOfGfqBP+8QGDDovR0XCeIv07y21oB1Re+NWd1C53k2CFLG5Qxa0i2TTiencIKGBcwzuEVGBicz7bo54DV0jj1Cj797B7pA0NGTcEwlQbRBGumzOq3LiHMVljWvuneu27rztcWgi4LTUrCUwjquJSOcf1YTtHfCgdddsEPDVje8XC6obYs646017gMbl1Z5/XCe+9zsHX+z4b1ZaQ/XT+eZhDAIz+ecQSIddeNztLeAJtdExBRtgOSxL2E2gN6YkapABETNLdZQ8JFdTywoa9AWD/sYYoitFWjosuGsn3hNkJIkkE4I+2TrPxUZwlMHEShSj/fgxRYoggQoM+u9y2Lyn5wFuM7lS3RyIlaIFHvneT0OeSq9tYzCPsZBL6OcQlNHfxGIrjFeUc3HDOjuTKR8uBlage1RYYChAsjvMvLLA1ZZUUXo/JOK/pnvyproBH9wCby8zUh4hKqifmqwuFsUUC9ThSERSdAXiXflfSIwVWi7KHlB17GmfK70BUiZGeZJWMsY8H0ucQ+FBU0o5b+GCsjGLHIAVTcs8oj6scW60nlp2HBn71ccl6j7Dt9vqsCnIeMoRs3uY3aFYIzbWEouKxHi2mmrQGmvUgRCIbvQ40nhQGyw2e1Y9IH7FYDKZR4ZVADamU3s78kuKBQvQHqEQNCM9kgS6HuFPLPHOs2Z4gGCC0bdc3ajAxaIo2ajY5+NzUUG5BjqaW0f/nZ7K73zmwp1/wI6toqO8xKG/SMQDxTx3iMIZ39vb82dkeQClA+nCUzOEzHEH/JIDUeMAlFKoGLoOi6zeGDPbiS8f86XHAAS4zqnM57xmxPLGLmcDyCc/eiGCgKn9R11E+7H1tAzgwGT2Gg5bzAU/2QoXU2BpCn4bgUgdcMF1KGQM9qSkXSxNUtd5ixE+mqTgzVKU6kH3loppiQMRCuZaFqW3Q511C8J2allQXFdSRAoax3MuqVMrjjjPVb5FS1xhroFtFM3FDQL9steGi9XKDJqF1wVSJW8bbsqembwck0Zp9NC2TBnKCjDcM4aAKJ8UbYUq2PQYSA4XBuTJ3Mnn/v+imOy+ylsE7ZeRj1mk3N9zRuKKDAcr6GrAzgX5uBfV8urtuO1NySwvrwCKJkB8QyUUIiwDF83audoTP4ytOeMUhutscyZUywRwVYbXGLynffmfDIZ9dZ6LJPy1/Vw3B8UB/GnNM8+d0e6JxL54086MtI5ftNHl60O9yQbVJZX7dxgHDVP+DF6DxmlZnoKlCcGLzJopVvAbKsrSnnEw8MZrS9EKtSO9Xq1vUP6W3JGa3yCqK8VBqdm7ZCIvJvlL40/Cp1/MHlr/B5KvcsxwN1Ao6MvIXja7ttoEaiGI83Wu1M97w27w52z7NzBjOPv+3dv8eOHZ4h2K+XnOs50W1WclgXV7E0y/Z6dH7vsOK1nERnlFKHhC5nloPEsLiAPTGlD6YqzVKnT5W7280nm8ykxQmiX7Md+PPRP2jR/tW9ufznQf2ebmeVrkYa30d8KGMROCuVqvofvFP+su+eMOg+IbKrjo4/Efm4uLHq9btKkg0M5NqceDgeVCKN19H169mvIuxRPLOtJ90TzGcCTzhkRQMPPkdG14HtsloFO88T36Pg1hJDBf91pEhQo+ufKRTs40OeIJEzzNGeXBJFvnQotJaqI2iu5YMkFiyQsiea82pWwe5X1VDerkYqU8AkdqhlvpCPpqDW0p9gwpd6Ey0w4xIBo7BTeXCgHaICoSgOfZyqwRuP0Xhhzu5P3dqOiN7/tHVW4USh3V98x9L7mCPvzSP4r9//GB6wYxNCrBc+XCrzm+P5NEhDOc4BD4o70YMZ4wgch5PObO2N2dAJ7ZrU7xd9O18zO8S/t9WNT7J3kLkheZTijv6UdTwuhwQda9vHZj0O/QJ4+O3R+VuolCjongY8oasq2AOf/c4ZC8cs/eL+3dt8Ejsu3oFn8O5o70BwKaw8Dyv+23nDcKvN69UxW+yVovwhgSXBxPtdrImcxIqWwyFIlVCdapRFxItLx6QsbxTOTy4lGq60ZRPhBQAemwInfsjj9Fnpw0rqAfejaPVpyjPhPu5Een1wpTHhEgtB5LkB7duh6oD/T+K7iPCvd7Pn59QSWcYdhcEkA9Llb7cAVHgDhPD2ZE8IDpELcVo0gETc4hUHE5t/TwRQ2bcaOy0LnuTtIprBkO35QVhSj3qbu9zLXmdKBZPPfuzkXIBboILGufXznumhHw1KHr0VTvFuj4x+m4OjE76Y5lam/AkHJJSbCYZOL1Xp1R3/XjiyC0/m8q2t8Oi04nU4W8V2Q0hWlFQ5X3QBhVP+yLHjz5g0eHx5Y21g1MhdVO7aU6WCBAL3j2pvVoqMTTFNCyoXBdSWZI07RKwPpem1osiHVgpwSHfJLxnI6IbfGzNhcIKVACpVvl99EaNDM9l6qwMvLhZD4lwtKLngwuPfzwzmc/r62tlrResP1emXGam+obQN6N5rBcVVRQvSFw6pPzq5Z3bxtOoSn+OM6HqPe7Q5dUfuGpszcPC0LHt6c8fj4iPPDKfbMy8sVKX0mlP35jOu6oRnkooiglAyRZA7OHjQo5cQ6cWFQ7Dc84yiv7BXgWU66r+z/lnar9B4P3muTOWGI4a+eFvxmvvc0XbtL5Q4q0eH7LAvtjsfzZDoTUZd+brsAHDWap+4QNyO0Zwbb/5wwdQv6SgI68uzZzBol/UlC2pMLa4rnXLh/UqJBQhABM6UULKcTTsuCcj6TJhjSBJ3qOcpC5FRYvsQyh6uhZHTtFmjDZ7lx0A3T7gyvraJZSQ2BQCud6pfrFS+fPtOBvq6WWYcw7HjrXZkJ5n0Cg2E2bNjWFZ8/fcZ6vVqt7Dr2pvF99TrtiVwsiUA7dRJXOR3dwyHVm7bhkLVJ1qRhyRlOfYn3ghJ2srYG2STgwB3mXMuCXIxHeua5I564rgIA2RBz7LlO47L10ccfDeho4WBnDVcJegAbRlVD+PDghB1vscC1nJE1QzPiOjcmJwvGyIlBTGKBS8lqV54s0z3nPLKZvfyNBS1t64quFet1xbZV1GbraDNUjVrZz97R1mboAuY8brPzfLdDfYUc9FUN2wCh6cVQj0yWSSkc6CKOnt8g0rCt1Cm7FY7VybjnkQbukFeAqEYd6LWbLHss7bKjAId+AwJ3CHFNedC3gnIJbY0jSCrWpPExnjNkzznzHqfOYBqTyAiPyrFxRCARGixdViGQjAIOfY5hCAdgTvRBSF3eoCDCxAi9KORhGgPhy9zoTTEjAB4E+MzPSVdABM2lP6ddAkAWZGwABAUPXL9QVKwsbYANKoKSF5aUyAqVbte7XaTRIfmSIgkhiULeCvqL1VI2u4HqxVYYYj04Yx1yOiZajd2xoe3IMJZ7KbnEtZXEq5Afm8+cBk1sBiTOVcPA4qaKjx8+4wSAdeIPd7r5ajaTKLuDQbcV6JabOKmz05see3hPu+jD/yA+fcJ6zvY94Uw5M+SJSQNIPn4rBA8AvFxNQpoc3FlTwGTTmP8wnqmP6HpB/fCI8h2zGknriCIk6RGil8H7IRC8Qfo+of7coBYsLMZX1eTurv4unAuYTHu0UQIjazxN9GAeQd/j8/g1mPNcvMTDkBtnKP05EMIDLRzmel5LKrQvVE8msTU868x+3zT1ZehiY71kp6/GF3LeO9B5lQbfdT1PIujKddIpHCCcVGKZqJRDijnDAWYOe1CxNu6VpgptHWu9YgXiutNpwXlJofPD7AfJHPNd6dBTQ31Y1w29bgzQWhSPDw/IhqriRR56Y43wrOQnPQl6lN3Q4Fu+RkrKEaSYy2KyWCYK2LYhZdKCVgQQOm3V6jtnl+Vs7xOx8xOSKtLTd8jPb9HwgcEfhQFJ5+8y+icmFHRxSPeO9O4dsjZcf/3IclpJ0NaOVjesCkhOyKcTek4okoCMGKvUFNDKzS/JEmo4R1tNCPpnAYXq0KJTi+U0OSPHbwd+YMLPQAbjvmu9G5S3lz2x9dWtnyKBEFPMMd46s8YvFkypPe18j6FfJ4f0p61g8Ac66olYmuIqPnYESrjlze0ByWiFIy32KMszv+kke2HWCYNQxllfVYm+oRnrjTsuoLP8KsCp06EuoBP9mECkvaMn36vHpiE3qe0Fcds8qCUmkyOSIWlAG3pKKEIkqpQoy9e64Xrh+J3PZ7x5fAREcFqvaNuGj3DZjvaMVApWqWZHAP1JiWURUkmGNKdTMoTLwc7F7H/h63D2Ot4z5mT6exsOMY/GNOZfmLh7suE9W949p/rdgO7p87CVjYN/f/8OHz6+sCzmjJ4nU7/VaEcbkl5Q5eCtTquMh4R+sS9Hs/M97cbZuGzY/MYLMBhN0dUCAAlLOfoY6/d+G/N2DOL6q/0r2l8O9H9Le53KHPmtGzbmxuindJ+o6bgPMKDbAQSJeZbJKbGTamciuof1CyetK7R9f5yf77dZ2Zq7KWDNcp2+C96j4sNO3e7mPCdr/g4Nv+4F5VeeG8+RiVlPF0jcZLrDPAb2u7+j1x8UNYHBjSpiWSgpQfAdMhKq/kRiqxrG509QnKF4C+BZdeQji0yRinMfNSbSCbSGsdEzXw7cwAR9NaFMzDFxAzP0O9p4lo/m7R1vnOdyVE5ufv7ntjGEX2xXYRR0xx6deF6bCuyyzB9V8Mn2ltf59rdf8IQVH/G9fodf5EM4xe85fGfn+aPuFcQHvX+NB5c4HPvxXbzN9dEBOp39fT4Jf5+h6o/Q7vfaq8Z2+5NkMn5gjJ1n9rfp9IwnNDzbOwve/5+/o7WO648/Iynw6//+LwDgjd9D6XD3ul9XeWUN/U5pYhJHbn+bHJD7zJ6JfolFaItnIfQ4VyAoC2sTuwH2sq74/PllL4TOz57mT83hEMZmDHJF/a0x0nymjL5lI+BqWqevjd18Y9u8l8sVSykDfaTvN5a7pRyBI3QvM8gB+zpCx9ro+/d3csZn8M94lh7HyJ47S6YVrLc2C+MCGjESgCQZ+V2OMpjlqSA/vzdBW9HwwtcHAziKhW54PlREneJN9MGzrT2jHR+HBkMZPEG9DlkbwIRuqI4ggMnIn0oKZdQN5AqHfx8Qu8tpGmMwCwsAqhUhi1puE+Q7JuF+GHwmBUAHX1qva6wXRupX5LzsmKqrxSMb0L+P9T/eGTQ4d2WgQqcS6FRjR2NM4YYcgxe4llPOWCzyHQByY/21BIusN4dHNkcHs0sLto3Z2tJ5196ZJQhV1E2wbRtOyxJR5nQ+0CGExXgtFKoLjQvNDR2DPnSrP8hAGMu8rMxy15Sh20YHjiRoS9DrhpQbsz0KDdopJ8LrpWHIqJXnlJSx1orrhQp3bx3IHPOcM5ayxF7JOeN0PrH27roi52xO8YamirZthpTD+oBU7ugc6VaTflald/Pt+8GWV5JhfAFccTSaIRaVrzSeKYBcrJb9QVggagBQCuH0zw9nnB8foEhBotxQOTIzpsx0eHDGyBaYYVt9/7iMNLdb2kiHre7W5iw73lxw0+7zqumzftNt7txp0IzdUbk55ebzqGl4kOXniydy/xprPTrXg/JOhuLdeUbvxCdLgTmix/mtmyUknJoCEa8LPhzus0Pb93pkHggCwr0YPHvOGUVGLdDgPGJ9Mxju3tWcvk6DzbhoAUatd2YkJRoOe9yCkKVEzrF7aAO8lqdM8oLRkhiabA6SBDNOyoAFF8uAzgXn89nGxqA2tZrTgt+L1WZ3dA53fXmAoiRY0IKlVXGEg87uoGCnRbMPKfM14vzaMt9bRxdCuAI13q93D8xhT5KkMRYlRZkbAFFjnKzODOtm2Erah9FKsKMdkSEoEu9sQhT8oweK3byG1Xoda9ckKi+NEcEWowZ6yTnerXfjIZV1VddtRWsV27ayJEVrhOn0JWfGfQ9UgjmOezOHZh9O8rF/rF9kQ2GoOwZ/L2eWNmmblS/JEsZEQcKyCJQYusAidFKqOesDKcflR6f33B+pFKB2QvbOy+MefTimMQmhp2f9eypNvNPRxeY8bi3kJXM9WNVYsaMPMmTl3j2DD1BuKgBeq1IAy65LFpzXq5VMejCUmUlS1bGi4uhOZ7Ra50OS1ZhTXMa1Ttv0ooZSs4HZlfZjSujYkORMGRKgY12Aiuso3WXOC9IFBpIlEaAkZEc6tP1PaOSTjecacvKCRzSsO9qbhJnOo6+JSrLqZJA+TvZhQ4Wh3tak9cPf0fW+gWzj76lOZQEATSoggoitMXvGMj2/o0Z/o9n6cZ26vKXMIyLIb3mvrkD9vHecDxncA2P3vCxu73R1d9xlHJl4nyevPNp6pqM94QEbLgw4AhHZfHwSrpT1AXh2eHnKaM8Nqo9QqCES8Rmki6wZn/oDur6g/fqA8n0xWV1wSVYDlhFnQH8IhJft52ej+cYzp7kc4sGgma/JKbMvsWPoFD60jloxn9Mm7cCzy93u8fieE9V+/RjnHFfdg/K+VYZtxM8pmLMf2ZxVDFl2r4vK9DeD89yhuMoYOkCC/3hQ4H0r2/xk++6DKLDs8xxZ6HSwOWqVoCdFsvrvvd/en1t2IpzBKwa/yDKQKsgGh27qDjoPTgKAWgS1ZyyOvgJAW8NZlaX2VLH1jhoOWARSSykFeVlY9iY7WhYlABHKSdnh41UQGopYNjpGWULD48HLx18hUDzgO1zl16B559MT2qKoHz7bYHCcSkloSNgS73kSwem7d/j44y9cb00hFkgsYghoLhMJ+9dtPlUt0A4Zp7JgrRVqMPVJMjQxUBcAtrpNtnUdhE5GsIxiklXUaSPHPVkCVuuOXkNZaSwd7qfaGkoeqHUlFwsA4PczCqViSaiTPOAyoAee5p1uzpNKTvEOzn993TRHKbPuuL71cDqHvCUCJBXUflz3GHYz2f92/PQlHWje/8fzxh72TF4eWe2FTsq1de7A+oUydJPU99WmJldGMp7tackZ2W9hsZu+noa85sGkDb1V9LYBtgaSsK/Z50ksyC6sWLeW4bCL3eFTx6TP1xHNjg5cfHFCZPfzrZznTW/OPcxjrNFh3XPdfATjfaUXpoOI0B/z/XdP+MfPv9xdMD4GNEuYP017rPdxXx7x+NtR7dLHcO+8FgxbHaBTEN40Frv9aGu+K8QCCyMd5zVlG0eZ46/272h/OdD/i1pAoOiXN9bcPk4GkA5O+Hcqt7XT72zGW4FQh8LwG/t+ZKXvD79n+33Dh915s5qmADb8ipndf8QwgsZHAAAgAElEQVSXiOrrvwn2PPxVViLjfIdNdoE0ZxMus9UmTAkqHwB8F0KtkiYD6lHOdJzPGTlfarPRhJF+zAxzgduNh86UPUow3l0MFqS11x/yV4ss74OaE+1bMp39/EcVNDzjIoAo1+u9Wt33mmBkZ7/I7b65ynCKu+N9hmk/Pken38+6d0C9U+Dj4fw/q/Y5MLLtBbS7JDyhyTMEwPsOPPz9B7z8+JOd8y5EpPbjqM+UlXXpAdKGLjzWTLD/Fof/n9Vm5+LNb/Y3u0HfFGw60wVQsazSjForMoDrdUUuGe/evcXzx093n/ma4HWrmnxb+xah6969Z/QTnTLEvAkS1PJgZgfTUES+rbd/xlQudqeZvs98hMYoE1rVjCMfOtK7W5iojisAGrrIDy8QnCfD6VwkRFDe03Ex4NH4W9g2TCh2o4uPq9PqCFDwYA2h49Zroc8LQA1QjQ4evpIL9Mem7UDBdsZ4E/X9P6oIR5YM9TmF/DHdxgw6R8fnyBw3FSEcVLct+JdNmJixKxR9HxveybolwJRZ7QbVwScNPj5nLA/nnQPd4dtzGhDMXUf9d+00EtS6Yd02OnbNQZLNiSKnBQMt2feFArKhDasDswCarQRzonXVXQCJ9o4mir4pWgJSpSMwgl5Stv0l6AWsdXyhDFCsrt26XlE9iloYOJBTttrNhfXcTyfUWrGuKy6XCw0xtaJurLnczJBUe7V5nZw30RcMRVd8fhFOlTl4gocSIGmCAAXUHIgcI+6N4tmSAkBYZ1LcQZYzlpLRTgvrDJ/PzE4MI1MPZ+dRYNzte6PFEYg0nf4t8qwc/g4pS+/98PuaTLf5V+rH03OnQ2OMfrPQP+kJTjeAcPRyi9yhU71HViigI2tvClR1aHb/7Fnr7jwvuQxnec6oylq7vveL0wDLMlcd0J05M3uEgW/FHJl1R89l2t+qCm18t+5lKCbDNZFH6AJhFpnGek3FjMuZvDOyacWCPAREk3GDECSeXVJCWs4Qc6Tn6wpBQu8vO/Qb5D2Nd50kJjj6KBBNzDS3NnOwYf0aNbq/1royg8r3XPd9pzQQu1M0+VxaqYpccnSvlMXKkbC13pGT1WJ16usy1rz60oBcD7llWsABOXvnPXQiHK5TJSunknM2FBMiFyxliXIavn6bZdWztn3Fum5QrdiidIatJy+r0Spqb4ChgYh6AJzeHec50O0GLW1nJEWMrxp/9n0AWFmA4nVUbc81oCeiJIRB2G82yy/itbYb0lKwz2r6bYRr6jFmxkgnyuuE55tJkq1djkeKNUgK5IEw013D+eS8TKfjd2jW3KFXeup8sUuDagCDQ1CGjKoLmmWRJxnyDKnHCYoVKiN0JbaxzwcEkA24FsibQaOSjKAviu4bjbV2py6C/nkA0nsYjcp+jBPEyjjsM9jmceDXFdDXTYtzMMJ+DG8tIvMZ937zsI5+5/e7z1aFvijkjTnj56m2735oWgEuqnxxwQ09AINu3vYAvvI8umPBAzquuzcQUOfwO0YXVVHeL2i/9GkdW1+dUR+c+d0yVrVr0PjjqyhewtfXb347vsHrw3DveOiORju8HUsSKvaZ5gKjAb9+Qv7bE958/4TPvzyP4xhz0yfxb7Zx6OF7BJzcWS9H+c4/hzPX+bC4zDsEztmZcm8UhkqlRkeH7iCJ/6iP5Cg1JTZ2STO6yUPkD6N3cY+DNOWOujgrJcB4rmeohyxjckxXRxijk67kjCXRbiEgHTm9f4P00wesqpDed+/BMlMLlvMJi/HtnAtSSajSUSyIWIUyxKJjDAtGIKOXW4gY/OlvQ0V2/dng00tK2GJQBCKPlDPrhpIyWu5IOaN9/Ez90eh7hWJRHfvGHL5i7wzVCORRIOYlp0w90ddHooxHuS62NflkmiZ7pyaI7V/qL5504Ry3tRZlbvaW4uGQayaXABr2gWwZ0dmyp0UE0qz0nyjr1tu6Ik8M6gYPmkpmh/B5Dd7usq09f48uoXCUvd738t3vaX9ElVLgLuy43zcByD8I/g7g0y+/5wkjOPP+z9RZSy7k3QqoFQNRWPCUzjyPgZMeZJlytnJQRALItn0B8qxI5DvKvXpf9prUr2kUfv/c/NH2O1TJbzxt0OPerIxUTvifv32Hn399RtiQnFkqgoeOXfDtfRxyOIm703d3ntsfrkezZUxXH17svmz5V/vPbn850P8r22uRjl9uCcDy/fc4LQUffvrp9bvPBNeZvjHaiGD8Dc99Ah3db8GMc88Y6HbHmXjNQmyP79+hQLDhlwBAUrvnq+/wlePx+xwKBASRvXGlmKGpJKqzWRzWj9ljL8Jo7f8rfyNkKIDnrjhbhldXxWNXU07ujd6kdt1oLGowiy60eJSq1UU04evGiDJLIbdc9N/a/jxW8efc6d6adsXLYcNYc5vr41Ep6L+doNoB4OnvP+B/f/oRDyp46/A9U1vwDkU/4qPcd3i/yIB0f2PM90XoKBbsM8pn57FnoR/veYRtX5TZucea6f8MJ7QrHgDHsBqMfXadIknArCk+QvGE3hpO//cM/f+A1c6/4gPO+h0e//4DPv/8kymTHA9m4AuuoxAN/x6/Hrf5q3328yfHpv9mhthZ/XZaBmAYru08z8QXCE6nJbLh1nVDX1c6PteV+zu6/O179J6R5o/u8Ns7mkCqzISttQVE79xfypEci9aaQXlZzUa9Q/N8Dg/zErlfk7ApMp8zH596OysTLrnufh7QcJwThX5UyJMpj+jQj4J2N6r3jG5QigKg4Rq3TshIT4SQ1d4If5ap5MhTCofRgFyzTLW2zxKgg7Wz3qg7+uAQhTC+xIxHBmPxGW6OIwx3xcPDA9+HUjsmDMa74+9jI4ma/2bQ2A9v3zB62s57fPMGdb1GCRQFHbkl07nrRHIXZCLzw6Z526k6iPXPzO2x70RBJ5ONYa9ueJYwAiUzOF0+f8b58RHrhVl+APD27RvWEzRHWjZY9VzoWD4rICmh1orL9YLT+Yz1uqJ2NejdDaVsdJC0jq6E3e2qAamoUwZGzpmKEvblF9TeEcLnEd6Nzv/kGWeqgI66DEshLPRi0PS9N/StolpNvs1q3nt99nVdrbY56+hudcO2rdi2FZ49A4hl53ar81ziby4ZqXrmgRnK+1QyRmQqXwOIQ/ra2h0SqYz5E0fM8TVNuFjCiPq6ThZ4YCKKqDnHm0GvJWRRpJRRrN7w4+MDtAtaV8jGLM89LbA/ZpjkhhuEhkq07AxArk0fkTWwU3z3m0gOn/T2h8Ptv5XJTjT1C2fMmf/AuP/NZa/c6Eahl9vjo9bonrwend9zVvncktBBFygUYaAb3+fMp+mOsY6SZWQlYQYtpprUkmB/UyC7OGyoozb4fksOB251RrMFvcKMynRuKiSxhrQjG/AZGWL9yFpiX3g2tHOR5INlr3O14FkfOTXIbQGzSnJK6Kmg9oox74mBeCkBOSEvC84GFS4QiJKCLklQlgUtJctgVaA3aDXY77qY0bzHXiYcKIn1jjxbN8P4aFnpyZwCahY/p2V317K4LDT4lyph7KHJyn4gDH2qhHTOKaHkAb1PqHo+JxttUrsmpQoPpGizMdjmeIeiMv8eL6g7x43GusQuezWytJ135Mw65xPdzBaoAexLRGx1Y+muWukgrxUKonis141Q4q2jdZb40taxnBaD+uea67WFcW/+F/12I93kPO+R8TXQDXrt6Oh0goijqJCWJjf6G4x2ygnt5YV7PSWgeeY714tCGYjdwEAXAMvDiaXF1JGPBG1dD/08rpP9173uZZtHhlOMrFMCZhsw+Qr7deh8yh88Akc0AlICSAUAtId8lAuRGvheHSwmSpkMCuhqY3GUD23sOEIGja+CHc8QQC+j/I3IgmpVvxuaQbwqIAWkezBHkkBAlJ/GasU7nSqGUgylwoOT4GX2FJITVCQcJwUnXHElKoFqZOJuUil7d6fHhNQQ6eQBvvetfyPoQMe+BgNKk+WFi45AG693D+3Qy3iLhAJ3LgATaPBBtg9R1A53EyC7ybmh3x3WVpTGEECwGJkYEP4uF2Tn4eLSqkQGrGAC3o7C2Pu1R2TCITAnWynqx5006tXe/Mx1gSu6DBdZsVtmPYe+IwDKU0J7Jk3IJeP8/RLIKL0rIIr+TNSlLi+A2PX+/iZb5++J0tM/PkBwBdIFwEPssdAb7Mk67bFAMTRb2Ky/YPdpNDUlZtzHbWCI+aZtwN97xz6xwqCWf3mOOZvUkjjPV9Bsbzn2Z3+dGL+eMkeBCOJdMPrRIYHSN6uZEt9tpmzbQMaz/PeBECGxQlwuzolIUgywn4IEIzhCp2fb9XlkDueSQkaKFw2nkJVTkQTb4VO/hhynSqdTtXfxRJxV+KgHGLpPWYD/+R7bjz8DyozeBqL7iMlfj5LQrVwO7BknJKxiuoKqyZUKSDe93ALdxNed035lQLWttYZPsZ8z3uLlJ/LMigfTHRPknVCOk4Ikb5Fkg8gVFcmQ2AB0Re4dba1AzjifCoCGtU9JDz4wSYwvKMqyQFKJzGvq7cJyYKrQisgolljhLC9CJDmrIq681umjl6iRJETnUUMmsH3pZfPCiS3kTbVZTfS+D6iJoCoRLFZuQGGgEwBUZz42AuQdUdVlxd7HGSKCrJzTpn1X5/zluiIn6qsedHhf7dBXPt+e5Wv19bN+e3NeXX9m39/+TXD5RYlgAVi6BIZMfOf63ReXeY3I+qpQ+z0hTei0bI4mRah+rinq+0BvLOfTaudnQ0PK4iPh5aoGLXE+DDh9GLrc7eAdRtTFrUlW+uPtdtb08Pfu0jg01zWA0T+vZX980rGssMvldVtNhk+E3ZexsiRRbs+J5Z+6dmxO6HWg2AFWqk9krGmHqgj9CKRTYaez60Rsv2kg3wyZdh73id58s53gtr125Z+5h/5qo/3lQP9varonb7PZcjq42y1vIPg8HTjQmd/cvt0IyPbOuvQO5pA0quSmZQGQ8B6KD+gAPmDvcOfvgo5fmElt9/02gsDBmAXne72/e6/pPV0pzV7/Ttz4RSPdU854SHSie/zxswk63QSN3iiAfTQFYlaDhx1UgmHcdMyNeQIzOpmRUBzadTK0BCN3Sf9fSz7l5r//Oe29DUXDbaQ1MDHk6XfBqBEeNbMwstJl+nyE2Jq/PSgFql/ltu75sb3VAbF+hGj3VkADgf/sTnF3ts/HvG3YE/1/lvOckPbDxdsNwurxb9+j/dTxIh9w/d+VYydA1nfoeAbwA4UNPMe9TvrEsg0/fncnssXfY3Ki/wltlj/n4XHl1mEuwwnjjiL/n/gxN2jR6PD55WUXnfvHSisce/fntXFnV/Q61nVDKSVqPe2MJ0Z3BKxH7PpZloSWOtC/4T3lQP+wlyV3dPwOH1rciHa8Lfb0f3bfDmOIYDaOevYHgHCeH/sAAOlJAFGkLOjIQGtoHzryewYQUBEeRgp/Wu9eZ7aHoUHD0aSRMS7FIETVjeKgEx2zrE26nw36dmcEC+eBP9oIhthIzMYxHUovI9pHBp8b392B7q22BgEdsvvMjDGur0dqs58jWlwB5ZidzkvAzrt+mEtBr5ObQ0e/U8pYL9dQcry/Uf/XMlIXiwwvhXVCl+WErW1Qe5dcCrZamam9bcjrSig2qYTVqxWt1qhvHE50CHISqEHAkq4Rqr+7QisIRawDBhvYwgDSLeocZnBrrTCzqrOWXU/Mhm2t4eXyAoXgoRLadFs31I19azlj3SrWreJ6vUZdOoCKJrMyPBvXnIm5IOeKlPOoUe+LadbpBLt6YmNxTXvK14ArnGFY9vqqPj8u+5gDUADA4Oy0o2uFKuHqchEsmnB+OOHh+oDaFFutppg2u7vRWk+TN0OvyL5MCTDJXE4zjPaIoRGM1xqGzLFoX1/O0y3/QPsaTdcIzoorZIz9/lb373Xck/f37uGG9kAPRLq51yv3TEmgTS2zUnbQ6wB1gr5zNPsa4XklWdkTC4gQq+s8srZohCYalGV+pOFkb8aMSilIxeHd3dlkRnKDqM65QTWFATmZvO28XAuNI4580bw+qdFgiND5LKR9rTdmHCszjnsfNapFxNCrhoGTBnWxzK2MVDLy6YTT6YTFMlpgBhoxRJvSu0GMKrS2yGRvtQIKtEZ65k5dKzQxTasO53lsCJtpl3tVrUyLo6kc9c69huVO7SYMYKjdA1H2a8Xri5eloBhSRsn2LjpQvtxZlFNCTUS18L7He5gj7QZ60/vijnYdtQ11licLnehu3HTnvtdhX5aC5WTZdV4iQCTq3jfLLl/XjTVf7XutFSKeldXhcLm9jyxMVUywrmNufB3ONdAj6yWm4ehgH3s5mSPD/3lwCevKG99RpcOjN6xrZiCc0XNtLWQ9rgDrsWUie9XPGOre8Go46IEUCXDI6nUteNg15mU2sjz9uECm7PH5VmOIbN+azOOhrw4NPO6hkZk4+ukEz2jV9IB7thdyOb15TwCsc35x+W3oRTF6MnFQodslyyn0iiNPYYbmCR1r2Ca8j9kcIfoWSJeJ9xsNW8AsRRp3xzwl01u4y73OsWevj1XgfNOhuJPO4XP85yCz8+AIAL0IkpX29sC73bzdGbq4rxyPjL4fuNZ02kjQsKHdPysJpN/vw9x/ykPDMXJDYsD1OZfii8xnly0gSDgDAJoodILMD14IRYnMc1u97/hbfmI5hVZXeAap11zvzx744TSQ98pCEHgxRANVOtpFrvtXkAFzftDAduOM4++2Pu9lm87wv77udT+Jd5H9js+5t/6Pc5UhdMoK4f/74bz53LllGUHuAisrAUcokqAVfq9Z1PEg0Livybs+/jw0Oc8TA+M8EFXggbfFbImFgXopxfOPsqcHOvNa6lZE1HIMT2tWriKBmfMeR+qyeSCIRMp/ZzDXwYEjpq8IhAibxje9JAL3kJWLMSd6zZkoXfbcQWkn+mBrjboEdU2KB4kygyFgUdgaNexh4niCJxsZIicAeU+7TP1QqVfJlTDxiU5yZAFqAsCSVdI6spUQ4ztlU4/FykExoD2c3UDMR8ksE6bGxFpnZFZOmf5567MkBlQ5ooDbB4cjbo80172MC0hDswVC3SgwcLmVZRtcd8yJeps7whm8YrXm7boEmA0LY3OZbO4Br2gdqfcIUhRIlOcCxOzZh/7Y2pgd6/fab9WP7u3/P9piXyvw8L3g8y/7Pt/SwXFcBOY/dWIwzrflHvK0WPm17HYJGG805Lti+6aUYkEWDWgNtTbaOgy1AaLD9ux61Pw8YNr+90fMdVw9fL8hM7+jvca3/+ymuGezdiSyIZ+oMuFH2wgkctuXGENycU/RcQyIG3d+TTbRaYjV5CGxYB8e05tr/A32NzzO1j9jvf/V/jntLwf6f0kbmRrj2D02FUqpf1fgPQQfhELl88+/kPjccVbsmuuORrYDSKYDIvdJw91+298c399D8QwRxYL3rBeOX9FM4XoPMvh30/UOX+qE5Rn79nTnmIv8+156BLfuqKIAA+53EhiAvdCZMDIJPbLTnetdCELd8QsN6qqsmdgJDava8SwaSpjP3a0/UG5G1t+7a0dJI6OulGLQskIIwOm+Gv/748zxtzeJcT2ulH8Vo32tuePcndcO3T4qEu8Z2IInbLa63uiYm/m95uG9/vyzVTkbQppnhScAFR/iN88m9+e5UKCg83z+zZ/lBLtiL1N7Hx4Oc+3O9xn6vYEO/I4/33l+nrLuTTXaRZWvP/0CwROefvgB1x9X1sMCUOUjir5D/YnOrJ6GsqWgolLx627MEybHuQjOkBFBOvUBOBpfvqFNDgmRUUuZx4Rg5XJ7X1c4XaIVAMtSzNBO59ccuT/e5/du0tdMC6++2FfvNp9Bpy5j9VvvkNasbvXEk2DZ9jp4lNNZp4Vf604odzIOiLhBAzhNTE2E1SIB4Oz00jp+3JeRDWvnuQErQZCeaJj3vla8IFttQc1X3qGfd/07jt72sWJ553DbipwFeM810J4b8js6wD0jyOuajpe0fkYWrkSt6yMCQhiKLQtGVeFwDKWUmC8okIrToKEkzeNHGGRBWTJUGXEunZlqqor1ekV+YxBklpnl2fSjRMjgkdUyoks2AP0DYxvusvvrTyfaeno8x3Mkpajh60Fk04vEBnSjw4xQ44YfSUKntyk5AA0IZcnAWSAXQXvshGx/ONMIs1XkUgAxmHNV9FrDcdZbw7ZVOvjNCJJzDkOQpkwHisDTpKZuJ8Cc7wjnuWW6aefv7lCM8rIMYtEO9NrQNtKRas69VokcULcatV63dcXL58900innMedMuLjecb1esdUtMmiLva+aMa31hk0SYOeLK6C2lsNpo6RfYuuve7S9K+vqc8xxyO4ItaWpOjkgdYT/AQIk0h9fHCmxhn0ua0A+t5T9RtxDKVTmWH1uJfCADvarH4kFnzFf5tNnvwyzhY7rDu3uCpdhcPlD4pjzFacNFjQ2ECwPEq/cuBPj+PHzTb/nc4we44YuaZx3fL8g5QoguYHOs8mZGekZnjLJ3gNmnQ6/U1lQcmEmOD3aUwa6WKY5IqhUSorsc4GgKY19eQqk8WzN4LxpMhD6cvP9mDIiKM4E2wyrP5kEXVPsBZ1ePDLOxI2osuObGnWZLSPdHbZpZMov5xPK+cSMZ4PhrdcVvTZ0y4T2zmZhRvojwOP09GPbNqzbim2r2NYVrXdzjNpOax3NS010CVo0yyYKQercwx7ns/du8j+ym3QEDWhmoIoMWZepCt+1lIKllJjDwQs5Jq17rciO2jp6a+iRmT45nFWnoiqAB/a5k5tZzD32e4n5Ugs8sOxjMee+9W85EQGAgStW37xWOq/6dO/esW1bwLj3RjSApjqc0eoOjI5q0I+6bYa8gYB0VYEj72JI0z60Y3ZGjfR5D0uc42UERCzz3MY0pYTeLAPQEAzEkM28RjOstEC3zrXGYMhUWJajbTUCNnprGItjWha+yw6EaP4qTn8FcIQGv5Z1lO0CC44K+H83TKuimbPDt2nKhc6XjJDzcmEmtGcFO+KIc5xuULee0dSuFTgJmhHYtEOfIprKeJ8OghEDelWkU4oBEAB6tqtWBodEMJkCYtnnGSe+s1R0qcyaF8EJdGQXOZFXPyToxQJUZi/eJBPhMvQXFTFHWkPGKJEQud/h0BqoGk0ZoM09NSEC+rnz89TnChCp0EsG3ozjg72qjZxbdNpurnc8Z5L1Zra2R4SxntwwrzFfvhMimPNx6hMASEJ+c0Z/2SadOjSSsTYwHqOWMRqnGY8ZTnTZ38dofhfTK2TIqf7+fBvKKdHvJwm6CSASMfRjR3/DMdCPPRBCgCudlgnI+sbkNdhTFPrc4/m85QNUBQmP6PJCfcv4+yzney1zAdfIpghnpr+l/7tbLNCHAbp7n2NzdLnXZCTnw23aVyIGJCHM4E+wwGUM/dEzODkKJlqLwovFDeQB3ouZ2C47CeqMjAVEcG4gxczv6eNm70kdinLKUoqB3jBgh/13RMmxjtW8ew7lTB1SkKSMdwZloJwHPc9HxWsaM8peQDG5RSCEYbeAPq+7PctvSehITomIWA/mWE7yFqf8CZtYEELO6ElQoESPqqADNiWkQh0nwxMPTM5Xjrt2Bnh0BTIURThvlI9YUiu54xmcoK6Cio84vX/i3hNz6opCm6LKZ5RE57oCFqCbobqhgjylqkLbiiwFrbKUxnlZyIuhSJ3Bm7W7DUNRW0XKC3mATHtjokEpF5wCDYD8UoChx9oEUk3JkX3umdvMngf1r9b4/Fhb9lENXt4c9B0jKE+Q0JUogBq6GZEKYpkaXXCHPmtsI86vGHsxQbAsDNDwEj9LGfXXXR5iOSHK1a1viAG5WY9G5+Kl7reZis7X/p528nvaDbrR38sHxePfniDyYf9sVctW3j85bICHv95fBUWg2iqqCJZEx3gpC5aSo/Sry/olC7Jk5GwlqBJRHmtd0Xo1eUZRJAX/KZICdcqD4FQRPgzSKAswFdMvZNDqMf53NcNXjv/Wtr/Pa/Omh9/nK2RHr/nLdmNwlZBx/D1FgPW6stzSmTNfSsZ2XVEsM70dAllcVzvlgq2NEjvzm0TZnxCtScD8t3ywdwBAU8qFt+OgYePzfsSrqU5f/pz29d32V/s97S8H+n9R+5bFfzwnH46F0P4Vr2oQlunCe1HXX2qefe6MMOE7AECTJyR8QEHGhl/RsY9oFHBhspo48CN+wXemZHy485wvtS8x4Zl4y/GTGHEzAp3hWaQmeEZ2np0L1ipRNUVLlcq7ZRq23qEJIdB5v740mqEmUpuJLykl1noshfBCgl1WmBvGwvDrhu5/QZPD3/+0dlTu5jpac/P5Of/9BPz4hAued3M1Z6fP7aMJXY82HxmsM/6oI4v9SZ/wLM941P0avJcN7pDufl7FCEbxY8dr5kx0j4J/1NGX+bc/u83OcwVrn+NwDHiG4m9QfIx9r3AnOrAJ71OUYTR6p1iDGzQSgAczQl4BnEHYtz+jUZm2KG/f7zbpDvl3u9C5mpx+uuO96VwXamTN+Lv8J7WZNs1/e++M5DZ6FGZO8XdQ+78JvjoMnV97xxt+48ddcYnz+P2EYcyQ6Qayu3b8lbiHQJCQnsa3FgYozg1l8RNUrwCuYM3zy53esbWPivKdve+zQt658A/UTx0VHacnRSnLDtrbGDFUGzTR0U6D/DDV9cZ6uQFzDYl6z9FlAEfy7g4ONwwhxkumQWNLCdCuyEuGNonMxfVyxcPjIw16SYBSoArUWg8PHDerjY506XTm7Joc5uwwYSEnLDTWbJ8vNFTlDHeGpyUBHpQ2XQflXq1m7D2dT+Hgunx6wem9lVAw5USSIJeFEfsn7st1PWO5XrFKCofJcE43C4Sj0aCuG7Z1BZR7nHyZNWVLL6wh25zbVHiqndcbZrybhlIGmIPcCZu9k0S9M46ftorWDaJZG7bK+9XWUA26HXVDrRUvLy8W2U5jrNeAd8SD67piXVbGA0EAACAASURBVNfIiHWnnQcItNo4prWaUWnM2ZALw3U+HOpWx5o/WyAhMGAGS0KBEA4VMAdNG/XsMfZhQGKbTJOSIC9E/nGH7BzUgTBg740b3td5HQ6qokHTuAj310Ummb28zCt4NrJ8AyGfnc9/hO7L8VMk3e/7PmdZH4/f3OvOtdFRn3PZXbE7b6bhZmqwA5PhIaAqLSMHMgwf4G+jtEBGKRnn0wnnhZC3IthloDt8e07M5s5pQK2LGSur71uHFZ3fzedDhhtnwLnTueMBH3NTGKQlModex/o3Dj/GX2DZRfYXDdC9U1eACHBxJ/JSCs7nM5bTiXXBRRi40xqwbei2Vwd8oYQzWlxWUcW6rriuV1wvV6w5oxot62bIrq1BOrO2ms1BMu+exLt1dPPmes7efk3drokddLr/8VJUiTXgI7vb+s3AhxSZ5+R3zI7WxrriJWf0kg0NxVAtYEFnE0KKyx+OUuGO7hG8nKweZTKYags69rUiQ89yyHZJyVAEtpt7+uu2Vok24KgD5oQOiclQLiRlZCGANT1ApLdeLdN5Df+NDPQZKWZ2ns/aRPBZSbb3TFeNmXJ+JDbPNAYOh6i9l829l6fx5/RuULQTQowkA65WTJk4rzfrAYL+TmtnXjcCh/b1e9L5MEuWHhOxu4eO8dCwUHp2qb2mUJDyvT9nlfl3SfPz9thjclz30zGnP/P7AgI5C3AtTIi0wgGeqMB+JQha0Fz+WyCoaNhQBNDrCfKYcF8sVZPJNebTZYAoKTQb/lUhHgDihmhVpN7RJcWeCj5yZ2LnICwFl5KXb/HfVRXyYDQWMvp3kNpvedj+GbfPvnv0zpEKyMmCMS0wwGUrBdLjAr3U3ToaaCtcI/cypr1vFFN0J4OMfmg4OwRzwL47AADoOfZoAqGoHV3Q76Wf1PgmgE/cD124d7nmDTnL1nR6n4KG6LTPXMqa2XmKTbGXnzygxU8N/S720uATr42PN/cNHPfNH20e0uGa02yHGP0eNILuwIR6QK3brUShFkfIZAQ/JFKD8Sj7O3Vkd/0o68YAv/P5ROSPiJbiuY5Q52vIsyKH7Y6BYbkwYWZO5knuyPc3cDnWvrscLSnB89TFkJ2kNyv71Hf8zDrFrFjtSImJAB4MmNMVXRIDE0QYNCsMvquqyNJJd0qGagp4Yxfv2cUO6bDjGnIgAz8+QdWC0HqLgAgvYUabCqhLC3UOZmMraq/Q1LF1YMnUzfLUV/gYW4LTWLcc32QlZ8TWd9BSgCg+a0WyAMW5pvw870679zxpWmEKHLfAbd3wsZ5FEhGAbvT8/Z5TBZSDCrRuCAN8UG/d0Lk4bp4t7ig6Yv1ypBxAiCSQJEoaeZu/H3nyK2T6N7c/l0LsG1EvgdwB1Y8sI/mVB97IBq/0sMMCLEXQdYGkhOW04HxaUBwFr2SUnLCUHGHZbIqqGwP+zZGbZejKAPWfnAXSTD6eF4WruJhJwCQL+Ro88PCYM71ZYv+kdtwdXzp6204QbN7ZwzQIuIZzznEsJ5bfVbDEpG/Q4AsTzyspobZbTjbOncgIevDCGNLdFvY98ttG9Z+59v9qf177y4H+H99cwB+R1fcY1DFo5b0y61wx1L1PBu+UrQblt7VBAPh8uUezbtoTBsHxRy0/FKw/VXQ8m71P8avd/z2oVHwCneYdgieKkeZ239OlY9a5TP/S4Vw5/PtSi3Mm4yyPhSSF8FyoQsyLl+w7y+so3iiwQCJi6rMMRjePiR/Y8Te4kmHPnbiKZ25kg6v0+8khdtoFUjeS/bPb4L9y9/h/Qns0IVym7zPPu6ds/eOnH/GI4RC/B/uO6brZcd4AJLzDO/0Ue5C1dsbKdWf3gw5H+OwQP099XPAOio8Y1TL5VDredXe/432O7Zszz7/hvLPOLgWDF5v6nfAO5QdDSvixouEZ208VWZ7QbCxc1Gliyq0Cio+x5by5sp5BevbGbAKqggco1rSf4299wbF+Nb4ncWhEHk/qmjTPvK8p+CjwU1lKwLY65PB4l/Hff107Gna+7ZKAy3VjjCv3dkoz5XvJzGj2IJ6dMdQGRXUaxld6V4zspUmOdaOf4uuCy5x56WtT8cAaje+SrRmgfqShsuMFEEHFCwCZarMzAz3LYxiOAGYgOp0QyIDlfSfQz4pN6zB+Ww/aVKu5fWxIb4fTPByztUIgeHh6w4zAphM9B1JJ8U7qRnHXhyaF1rPC3PEjQuNA8JGUoL2hbi1qdHFsRyaNOnyY75GU6FRWZpyP+VVnh5MxSVHrhqVE7Pc0G9O8THvo9GAGRONxzSK1oWr1f+29xDI/Ww+jFjAMooT87eFYSuZ8qtUMRQGl3FiPG2J1kRecTifI0wR/YRkBHWKO3gEJ5hmwJWWkhTDoajCIWxLoOt7PnRHx7jmPrF4fDXdQzTCcvYcDECsd+VurqNuK1m1FCoMetnXDthHlIqUtDHeSSHsDutdkh23j+d3q6/m4KycSm2yR2a8KtE6lPoI4emcmVtNRYlwkjPTeelJo6+E0DdnH16txR/aVxoHidawDapsUpXU69ntjpr3/z2F2UzenrI+q7S3/X2S1yWQAmfruBu7dihXTg3V//Liev6b9HxEl7ueGf4Uj3NDNvWFlftbckhwvNPrg7ySvX3vs9/48py/TPSf66fTRDfojS308P+qpGrLSspxobFoIm/1wOuN8OoXuI5Zi51DwacpIT9mybSObi47KyHyyPsU+luk+KUemlTvRN63olorTLRO3jwVDx9SUgdaUWdKtN0OpWEmXksNxZuTeLYuq2fkNXsM4WWmFlAVIRNZorcb69bra2lm3eVmvO0MRAJRsdd5zYVDBaUFZTyinE07rhtoqHa+2f1ptO5h3Zk83tFoj4Kv3FJCeor4h9sLZHEihGovCf6VxKtt4W7bNkh3ekmuJmcodXqYk9DYR43diullGzgaTqgOBgknIQ/fRPjmydTih+Tif81Gn0nU+2H3UAim2bSMtdvqoGvc9GscUOrLS3bBmslKUXrD1l0sGOnmTlUidlL8EFQYjpUJHZt2m4Dt/ntpTnWkATKJPAOvCErlEBVjXipKZmZam0l9NlevK655Dbe3RedEq+VDKmfNr0LfJ0E7IzwZFO1Symri/7L7zMxeMikYguFOSqJisw8YxMmMxLJqHxpIR1dZhGjYUm9skzju5jlkGxJB5hPMqAsgD9/bpzYnOmZfqYgEwlTjYyzd2cHJeCDivqkq5wIy5RRf6OrSa3lKQHwVyYca4azxVqjnLbHwB4GIlFZQZVWK6U/DiBwEuQ8g47iGIITBYpihrEzuNNBtR79YP2519BAnN8r9Mf3fcwifNarnqxe9PDKmuTDzw6xSDJ7npw5scH3Yc+jtt3y8AnzsDDxRIF0Aeb8/19z+uUYWGlSViHEP4HGM0Znzk+eWA2x/P8gBwwTneLTmy2bvRG4d2xpB2sHxXoFBcf/lgPPZhuvMFLD/yYEg/rKvsa8nRLfheFyiIqT9EUbm7p/y9SaKEAUjcgJQfOiBi6ItfEmLuCRO/4ZTZD2pk3OwZatraHOLC8d9s5JL1XRPnMx+fJBzlLcqwqK1/jmO2PZ8DySZHFvpMCgadYWezmBOnFMop2qCdtGY8ejjBg5dme1mTb0rOvN5kcPbHnJdT1vpAZRl7NCei/ngIUM6K3DP5fWqojbiGavDeHqAIADWxTNnnD5/Qe2OAX2cGLYSIcC5XqTKL3Hl8WRbLsE9Y64beKi5tQ6lWekkVtTdsCXjTEjR1JEOCS+kZCtYCTwK0TLq4mEyac6aDPQnwoXKHysWy7W2M+rApLSJoEKwARBWlPSLnE3qnjJUL67ijNgsW8PVM+lqWQpCVPvjtoHd6GHGXfXmU8u9Yatq9LnLCYrLvqltsv6YtZJ92YyCOx1nWvX2mBx0QZqjnPoho66BzHUDWHmVMKojylWCJK4tivShKGnJvE8oFxeTTZsHhvk7PJ2blCwSXdSXiS7rTWT/i9OdAJ+Tw97Vj39rULnRkytMQkfD4wxMuPz3j+VfF3/8mwM8adJH0edJn/H5OeyYaOr+dKq/rQtSlDkvOELtTSkNXFdKPksSQbRioWHLCsizWd0HNGbkRCaG6XC3CEkC9Y/Pg/uByw1dD+cDXqa0NEqjhM5r4+Gs67H6F32/7+TnKxPtbD2yP23Pu3eXI+j2c3+mrR9gozHlu5Qwpm9p4quLT5UremEbmeOtEjhS4HMVgJp2frCO4kEfFD8OFU+cvflWMQOjCM7KS7S09UIt7g/BX+49tfznQ/19psidZLuj7fnyrgk8eDQMdBopv3KzBxL7xAj/Lzf0PP/wd208baxkDSHgfcNbHa37FyF7vABbcZg7/seaCjO7GzNkPBdLhLBqOEGtGNOk8p8EHPUVNMJ3vBRJ4CcYW4CqvdS364M9MkIgIFAxDTzIlfB89odE/NSPPeLd/NmUeLPI/lQd4Dx26vYNEsGMP4+7tnTJr+43umeKch3DkeQljva74iATB5+kegnd4UGZVO7z73N7o/dpgHR/RYJDnGLDs/4xM8m9tD+qKpv0zWTHhbZxDmY/KzPI/C/o/3qHLM5I+xXuGUhcX3ApNUJax8nl6Oxnb3HBxUsH2h2qhO10Uy1jFcIKGwMw9faMoTc2dd90gVFvAgI0x+W9qjqKRJyPksXndMzUa5JHNvY/gL8x/v9AsPh7uDjtCZsUtXunLUCX8+wNp7zuPwKYT25VbnnNGxwX7DDvPQB9ZF8AVijfQaed3A0mggjqe7vpO/+Q1YBXpjSC/tfXxohCDuqSDb1pnOaHXGg4dAaI2ud8XIkOZj+7MWjq/qgLNYMnn7Cw3SMf6NmhCqKJkwooK7HhX1gNXRVkKLi8XAPv10JUQ3c7zWq1YyhLv5XxoP2syOcYA9I5UCt4+vUMuBdfPL3RUKYBEY7+umznJxp1EOIZlKeGoaF471ojTVivOVoe2dVeCqAAlAA/nB5xOBmWorDmuxE0f0MYJhKQ250/JhPjNOQOFjhPZMtCBrbFeehOMrD1hXWAxYscsAg2nBsx4hWQZHbWhgsE3Xsd4q5s5wOjyba2hbqy9W1uzrI05izGNTEqDJW6tRUkJd57nMmq4w9abdkWvDUiZCmay/ZxIjCV0cjGnjQzF1uZTc+b7J3UUXoRBmB4miBgMtUfolxzQlnSMmXPSMjw9e5dzb8ESAkjay3WqbY7fGXvM+j0U3UNtcR3UA2LGlb7bXbd0/GuWhoNT8d6JX7vF/tzDTjrQyeM9X+uPzJ9vrp0D5G4unc5LN8f9Y9dxXzo9jwY1CQOz15o+nxaczidmoJ/O4BqxB8gIYJkd6GLoCuMd6BTqvQ0YcHXjp8nXYnVEc4mMMVWY06GjYjhSa+to2gZ8fCkoS4n+bLVGgMuM1JGE2dVR0wYw3tgt2CcbslSyoBHjU72hNSuroIptXQMi3AOaSrZ68LnQIX1OKCljWRacHs5YakU9bThtp4Bw9+eqOU7dSbxtRK+o24brhSUeRAXCvHma+bxUS+hRt2tCjnwIQke5ZdmXCBRINu4GIWr0QDRFUKUR9vickhBlQA1GVN2p5+NqQT8OSetO9IBtND3K1hHLhOS479xrL3cBC1ygL1AxQ7ZHS3s5UW3dqBku74kqaclAE/TmznIAjVQ9SnsAQb+OOuvIAus7Wu8Z5wo1/t/RO+Xn3sESIlZ6oJtsV1tFm8tawAPwCXfbVR1PPsaQ2f/DgBiOuUMU+9GAii983j/d33P/vscf5gwgAYZj0+QZd4AEXeiDPvAaDzYDgIRkBZWTdriCM+RQyxC/05xOykmwo6Ouogt5STqZ3Hhl34fUKOb0XJAcgHqyPQiALGeuD1SEnNqVmcgiKAKDWbZgkGlcvH5qssBgY2mUuUwuTB5U0fd0X3TQ7Xnd73a5yK7QyTwGHqDmcrPCHcg8Z2R7H+97y48Ak1u/wiSPW66jQl4K5DFBHoa4TApn/X8s6C91p9/7cvZ/dFjug+18ZTiXSxCbJ6Cbyf9LvF0gkLc7AgpAbtc8gM+/PuPNd0/M3sWwAXRcEZx4LntlC5BBFL4gfLNeYrAEFoAhU6kmGePt3wPyXP06u39AXv17NNyvPdVtEU0sRGKH3Mj/xsgLNb6ZX0hyyGWDTDcnsSQH3cfueh/zvQNdLKCJdtgIdrb/Bukynugxn8Uh4K0/aXKeCwZfUpDWz/YqwB3ugIoYpD33sWfLmhrEewiiFrv3LaUUz3R7i4vSrXfUzjJgVRVLtnWZMpay4Pyw4HRa6FzdVvRV0GWDVJNFVKGtokpBwscYDWbaD1rlemI2OlNyRk0CtIaWlIHw9rta9rQmQYbNgd1TlckaGz6hY0PB2Ww+VqIzSZS5EYEFw2HSGXy1YMeDMG0t0m7Oglp0nNeu5r7uhmIgQePdTrxbr/AAWEEzTznLruyfGTwSI9Cf0O42eoRA4i+25qqQhhIdgy1fNBLcvLnDvKeE6+USUNgj+JF7SUEne9O6e4ff2+6ITL/5BjrdyPtSlMgdSYAnBeovivI3gf46mOWOVtsQhs0FRgen33y/CYBAbfLpsTXl9MBlkWKBE1lYlqBBCT1eSqz1WjPylrH2DukW2CE5bHJdFa3RDqB66Lz3cxeAIZNui5188a9Cqr3Xfu9c7+UszoDbBXpvDIIBcDqdsG41ylRw1TKIUrsGEx2lOg9rd/KzDHStMGUYuvDg/07VFfNeurnr4WXs551P56/2n9r+cqD/hzcxQd331DsInqF4UsHzpD0ct9on2ecCu5zowlY4BA57eRaYqDyPz8Eov9LfdzoYCQAkPOH60z+w/PAD9KfvAQCn/yn48R+K70zJOEKzf5xIzt+sHx93v4/7HwGev5kF3NfWMDvNHQoydILZCSadUaTJFHioEd+Ezymjlo4TOq5Q5N6sHoYbPKi66uGeIai7omsd8ywTr3NEPZzKmWe9dGPYnjcYd/0nEeOjWvvvUprutUcddc69uZNWwaAMjwD3ljGvdwlH+Dvd7wNgOMg927mDjnDPiJ7MIdBpx2VQaHfGKsKSbBerLXRWCXihXZ2vqb/el4fpun9H88zzBMaRCICMp1jjDc8jY//Hd/z9h4zT3xesPz2BRoYRvLDoE2a49nn6vMSb6DtAPgZcVJIwMwHWl7OSrm3fEs7nys9sTA+l4HitWH3SvLvcFUjAslW147yQtbbeUJaM62cCy+9Vo+OnP95mMe3POhOgQY6O2oLTaWG09LaFACkuKFrQDmunkSZ6Db4kgt41lEivtTj3YoGvI2dYaSfQFn07OIOw9hc/yjSQQ/UZ/EyQ3+Y4b/20DXhEAehgT1gmx/hQaKmISvzvzVBEBDRYTBqaAHQiW4262P12Sr+MOnMO3bl9ZuZ5ect6u5fPF+SSoS1iXam4dYWKQWHvdKA9MowkiedCEZkoUEC1ExYdKW5CKFu+D7PTO1IeTo15lSRTor0d2WjvGvX8Sl5Qa2VN3kMTkeF0AMIIlWYny1KwfP+edXpXOo2ld6wTFHQ4YZUZfa6waleoZR5utWJdV5RlIRy7Oz90xG0vpxPysljt2orWKq5XKldbrax5rjqQGGBO9CXbvEsYbErv6IUcpVcxw4U5+nLCel1Zg69beZcO9NaiNqF21mGHMuuUDkCDlq6EcFeYo16wc643M9bMuVApSTjnkinUkRVvUdCdXsOYY89SdeeICLNQRA6KtjBrHIkwiZ4FTMee9a2ZQaF7HhcNmCKWB8EC15AsltHrznhf1DRDt26ZsurZnWr95SpqEAyrha1XSUjCwJM5Oz72vtt//HV00Jc4z3m5WzMPdOt2cQ/Fet4bd098/Rav/+bGG1fTnUYe5Lz4dmQyu/qyr1wr00vsp/vwjDvXi51o1yVoZLnvnP5BsMwp6vUBvW6zS1iqgExOMhPIPdBNZN+vm9BYi9pwI7ELX2LrNdAOLMPMgzq0W23QVi0QrqL2btCtk0ye7f6WuV23iuu6hixRUmFWeSatyMnKEETfRk6GWpZIqx21XgG5hhOw1WoBMnR0tnXDNXlWHIMPqmURv4FiWViDcVkWpJyxnBaWZ/CgK2igcWzrFnRy3VYE9LmyyJbvAxVBUs8+vF0X7kR2vhEOCIecteCgZAZFhaJph7Q++G1tqOsKMYhLp9fXdQ16qG7UtSdpt+AqCoq2DvyfxFqTJIRPT+QxZXaCeOACYIglDZBtGD0xOd6nY/y/xtra7U2A5VGM3gOu02vAJkvJhNGuNebZgxuSQf72ptwjMiC4u8HQbhvXQ/LyBSmTVk20WrUxs7oLcrdgx8QMvs2CJbroQPboCmhj8JS9hztOxb3NUZ6DBvNsZU+0eeAADiMxdmh8mvb02LdqsorvCQ8E9z1sMoYDijT/Tbm2RKB9gm7vXn+efIyLgs5EgQX9pVkbhMlCBnqsao5H/ovx1zmU2t9wzL5AoNce38ubBDwA9TIC4hUMPlWl7KcvgCAhSx4Dgw1MJizoULRwnsfqJgKAKpo05J6ADKS+QNNm/Te+D+d9o7cFJygEDZewK/izQ0YID5vD/c7EeNwr+OjEP/TiFhKEI50BkWknt7qjesdjdp9l+uiQ0Hv+NLfZCe4B2ooKvFA/0zcDqlkA4KHsZQH75+s39G+Xmfw8F6V1/7zylvrE9ukFAtisjaD94W/eM9X+wfacBfweESNP8gbXXz9CkFAo4FOuF0D0EfmdQazr3Pux4vbj+4iuL7t3dhl6OAfnMRGr4801J/S62iuQT+hXg9hfk26+dt2X22a3dXvEJjMPoH7pQ91AJ1qz871baaLtEcotiDrmJZe7DvShyezfMpzcQrm+C0xGNf3D+ZJYMKBMjlwZASkpZwapQ8Y9p2cmBWuBm7Nu7FvjxcHfxAzBAoAlb5Bpd5I69SXlEOGyBeR1YVBv7uS72X4/CYOCt5SQWoPmBDktOJ/PePP4iIc3D3h4OKFcr6hXyjMXFaS24BN+RdUG6YImjbWjBQy2k2KoAU5m6Dgmls874COg+ITUH5GWFSeciIwiFuIk3LO19wnNjoFeHYZIoD4XDJpUSzOWjgj+LzlZMAxlQnG5+P9n703XGzmSbMFj5h4ASGamVFXd833z/o9X1aUlk0kgwt1sftjiHgHkIpWqb99phcQkgdh8td2OBQKL621dwjJo8k0BOZKQPTMztxHBTEPXEgn9aM5MDZlGzdnKZleZs6Nlt8Kjh76Pdaan5Ag3gDqi25ko5xgA0Gz83z1f0LaGUgo+X6/mb1egyZrvtTXoyHldcD6f8BYZvk5Ql1KhBGytebucT8xE/9ExE6PYR/hXqQOwktEAAOj/9QnLf7zH9b8+ovyFUMoHvMgvaBQZ64NH3u3r1Jn2jc5ZoQjcswD4bd3ACnQmbGT0f6kV/XzCaVlwcnuhiqAQ43I5o7SCulSs22b2mq0B3UJnwIKugq2rre0uaYukiWZPLc5/92cppYhDB7NP90+Ze/ylY38/Hb7dX6e71tC8loOef8F/EUEklQskNYFYY2YvKaVCHD1pqQUsFugsJioibUUhSxB5EIikvJ7v0/vR8xNGa1MO0rx+Zu3islXIG933QQZMT93+I9b7n8e/9/jTgf5/y+E76dVhzj5+U0AFnvVeoLMjiJZO3+yv3ClBcct3HpOK48TwV1T8Jb/tMDjP//c//x98/sc/vvqsDwB+ykb98eTka0QqnOcl4G27pHIVRvunhIY0R6m6w6QUBbSgQE1oF6B1jwgErK7YpKgl86MQpF1wdmE6CHsJuMFQfkWsnmGPOkYj03VmYb9h+r573P74p/5xx9yyi47PUYf8NI39R7KM9Hmc5vv79F2slyCcw5n9AWdVdHx098D9c+a6XG+kuCjhSoqzc9gZCj2c56Gws1rSRFWg0b+HuZ6VEgr+W8fF2xyKqsLa1/AxBYZwnjOA1aHaT/98j9N/Lp7DoWB9B6FPOOuHVAoSIRQwXU9fwGCHe1ec9D1W+ghCKEGR2TCO35SF7nspDJOFyywKuyHIRLtaC7bWEuq4eZ1gBTKzK4z7lj0qZujD4/n6ny4gHWnHbbOayU9PF5xpwW3dHHXAUTLCWI7BUyJiHhSO5TjnMz7R9TBDpFHg4Nxp+innq+BlGLBTSh33BveJN+qrgl4I7bV7e4YhlNTq2SqGoW/mkXT4b1ZD2M1+e5oYRu4wgjjfoDmryM7pZ52e6QEIDmcS9VjDEJKRJIe33Ue4HgCiXbgXjZrqe4yLbLVakMPIZMNQIt2YmvCEhT3jwe+l8YeowSP2vqVy8OgIHleWCuoKPpljg/x9S63QLuBlweYO8U7mFCWHAw6Y4VLZnf4RzGFKZm+Wnb3eVpxOF3eQd8u6ghv9mXG5XABmh16+4XYjrOuWJRisDnqDcEV1pxuRm9jIjVNMIAVKEVSvUVyrB5+wgr2GYS/dnORijhGrSSxgtX5ZDS7LBlUAvTuKhWcnwjMiIuPWpjhKtoQx17PnvL4ie7Q70vAMc4BQZMdPywU6DDU0AsHYAxZIg+KSK4BDNikOIR3GRSWFpAPd4ZC1w+r6MsBWx7lMwRT2WDdx+dqXlHWsDnys4QhSCVlJwvmZ9o+ALXXDaC76iduTpjX8fifF+FI+L+/NTXZPyR/x6O9FcPrWMfoxAvHinYcLH9776POXs9ZtfO4p7OF5X3hunLOhG4aF+b45aHT+rBiGkLjXsoMIVCNrSvdt8kFPZxFgeyGopIShZdQDNjhWr5Hua001Aseaoz40tLZhax1crN44FULVChECF3M+9t6xbhvW9ZbZaktdUn6napnrUa+d2lhLgRoBJah2rOtqRlkKfuBG1oCST30EqLXitCxe4sAcr+enJ8uSP7EZDokSznw+RATb1rBtK663K67XK7brFevtZmUR2IKFlQIFwGqhH1WyeR6CN4fzvDh0ezgJbI6w4yGx7rpYtj8XC1JC13QoNxk1uWdUgxg7yxaL7NuDnktRM88hWQAAIABJREFUM5bB1dvjfCQcIVBNHpE0xx0dEThRqpXsKB4kZP0ZmcQh16QT0e8/0oPeLMtNJWjkdIXG3ITT0+q1AztxZ5CjiRa5NorexGUzO2myqsG2MjFQC0QV19vN1xkyW1/z2S5JpVPJv0tnrO8scqcdBp2UlDPSfbrr3H79TNKMzufDOBn7A+7A00FP/J5Bq+EBWCZRqs9rkG+QS2yhcNGMnqF2PbCTXYYuMLU4HzhfhUG/bnuEHiIGimYAMAEeJG9Or5hYE/EY/OQ76rqgTmt9x5sU6UQhmH3F0BII9MxgukDeugf8GxpMeDCYANaTBU7obThudCA77Bzq+U5N+ho0dEjEE0/BGK6xVzfEoo0xDeSyEDdDRp6P8Uz7HSGCerjuS4cCqZsXdJC5nhHOUg65CJZZaSPkjg201Ge95PgeJW5yhOrMkAFcX6+JpjF6cEJM907u+ix5YSwt/aSgD4PB2z64AkRgPXn7Bq0hUsir8Qgogd+5DYlj2Oc3XsDvGfoROVE5/tEP3c+p6TzudvGgNhYPZPX6y7F2vnj8C3LQ99z61UtCjsAo2UMA5DAXRlMj0Mtof611lEGiewc6gImoKWK1JrhWOM1dTk8y7tndUeqlUMgjk1M95dehX08UE5T9GkcEFme4jusoyHI3AdNud7FHrZbUbzgD4iMIumkHC1BEwTSFPHkJqs0DC5Zlwfl0wvPlguenZzy9mCyyFisXsfQLbtsNl/6Cm3wyGw6ryRaelcvFnMbsPLY4Nqkahzd+hQrRGyqW5DEn2F7foHgD0FTQ3EkeY8Q5PraGCyETKYgWdKzorSNKcbBvBaIcriwJkNnbEVzt+6w4gTanJpsN2WlNyJuEfTJBBDaGHhc0tImgEqEwYerKQ7lirL5o17AjR8Bn9CUzlFXRXAfbtuZymKCWgtvWctXBdcMYPyIrzXO7rS477VvzbzDb/0vHBks+EgJEPvl8R9HZfVLV48Op+CQLBc8Mmhk0IxAeVlotKcHlMhZBLRVtO+HpfAIul1wLpRjSRK0VTboF8dEt5Xwi07+7KJZFsfUOYkN/yOblujkIK9NkjMz0nfD4Bx/HZ/9+uv+1Y5T1iUBp+yyikL6m3eJ0GvqRTEkGYTehSYYNmeZrfCzHNx3okt8rkIj5eVDwhNlOeTc1/6ZR+vP4o48/Hej/w4+0l0/HTBSD/h033JEsft6pN5qZzQ9ij+y9/jtrr6Ro8vWt/c4v/0jAh8mAJRDgn8DmEO5vfzci1QBUED54OyITPSDcCeZE/xUAiPBeR47qO9xnn3/tmOSe+0MnBe1g0AtjpYTCMylIn0E4wTKLS0BKgq2uCTEaF5xLhbYNm948YFG9noa9OOoxmmAYbZ0FLFOumc1oF/U9uipaN8OeGfcsM2uG2vpRCT9Pnbb68rjL+P8tx9dWwB9kH/6XWnHxPfOklslNGLDnUfd89WsZAzEBCNNT/D3eEus43hxO9ROsjveKX22NTNddSfE0bS+BOc6fXGu+ulH66LSW6bsnryvYfY93Mqf1678h8/xLIxqOfsCc7BkRrcDlrz/g7edf7XxYc0KPhE7jQXhSoOMTgL/g9B8L1n+s6PQJBYSVPkIxGNL5Lz+i/9RRfjQDJwD0fxIUVk8+hZvpPbG/GQblvk4dOsLR5byGIkT7wJR0UJAZ1MnrabXWsG4bCgVEu2AL52ZKrYTrzepAbe4AG0L5f482Ma/V77syjmEkocNl5syF0Zx1M8O2X2sQ28ZxhiFKUckyZMU1vll0JCLUqH8rsoN+BMIofYbRxZud4yeQZ+YI1J1nlFlywdfYoRDlVa3WuDPD7XUbY6MWLAEFGiJCWp1eFBejydfXWD/2qJliWwYtzwOe62couExAG6f3mpqPTX8VlBeDu5Z1tUz+HpBT5JYYxd4pvTP72Pu8Bpn62t0dR2N0ZcdYVsBraTIzSh113tVrtZE7YEqp6F47O3WIz8M6wc8+r76fWjeFnLMmOiZFc2T/kSKNVLVWC7RRRa0LyrLg7edfoaJYTpYpHpH/FAMNcl4+0XR3oncZtMnqpQPgAnhkP1Ub9w5FaxE0p5BuSvC2bQaDV4xSEQhdyQxKBbn9AYdFXC1jNbP2zCJhqApRi711aGtZM5mXBeSpIE3Nmd9VoE1yPI3/uIrWB/4GARFSnYb9MJBwjG9k2TlUr/paUTWI5jBGa9eRqT/R19xITIBE6BLC3mP7wOGZh2FRQUWhYloiUTizC6Ad1G3MRA1GuLUV60oAdSx9wVIZWxtw8ymFhvGPdWSWywStO49BYTNmxVodPRn7hkeASM5ZTJzLaPswgxwU7MLM59M0/x1O4a/wgO9gD0dH94zQcXx5Pi6Mq0enxESL99/v/5iNtkeHZLzr0XNjW6bzyY/URib5GghY824lCiCeaVzRvbQAKPa80SfmAxx4Zt06fYNmveFEXICvU5rpxtR2l91FxGHCDWqzdIIURlH1jPWKWhbUuhgEuwe+lN5RSgVzcQOa0YOlL6jMWArjfDqhXc6Wadx6BsJ2EODGYnVnfOst91jwFLjTqXswgEAtO4UJtK5QAspbxXI+W2DQ+WT1U9kCeEh2C9MzM73u5urlMmDjoEyW4UsxXw+W6cS4B9KJX0cDg8naalnQHQrShpF3jqRPzWluEY6HOHknzxZe3JFKaQgU1XR6Q71GOVmd2NC5AnGAff5KrV6Kg5NWhtPcasEbje4irg+G4c1GwOBeSwbLBXRtCZSiWIviCDbVefMCoJmzUxWWTa/dS3gQ+LRYCYFGw+kC2iskGDRsOdU0wJu8ZUEABMukt3Z4NptNidG7jbFczh6YJGjkwWWZiU6+5xikHshBI3AF6mvPeZNuln0oXaYFMMjjzs16WETpOPC9mt8DI3M/KLDv2d7j+nDmjjVIZI4apaBHarIGzNE3hxiqyxKWcWhOhgwMyPbJgWcYssbEKcb1q8tpZ/v+dFpyTQIMOksGCRMItMJqLRPZPTdfX55Nj2cPDhOFvHUwKkxSOcrrCsGK7fMGpYvLcsX3oEDSYSNgZnSc0OUtIYrDkUPh0Eln3xxAhSkYbdKZojdBzxWQt8GPFYDSNpx546bcJxFYcDweBZ4FjHF6mQ6HPvjbePjIROeb1ZqViz0gRGV9Mmdh+hfeKghtqHhwRK1DINIYC3tj+/yGhYDmG8CkRh8BCvuY7R3BGxxXDsAFBQR9daSRj26YJ0WUlQoXf8ebZR/jjOJF3SW1F5f/VaBCoc46HzcdKNGUyK87juPRuh/fkWUdCyQj/dlhnGfEj9kBcZzH+7k+TuTv05cjJu14e6M52GkIgwRFUUA4driPkvM17y5KoVFaiApKITAVl3EGydMpe3E8Db6PdG9bzHrd7jgP5zk8OJTGHkuZxtdhoEkd+xrBY3Q4saNfOnhyCPAEd1rXmkF/6mnLXIyPcmMIi8sNnE7kSoRbN31GnY9u0rG2hpMj2/TWsHYriyP0hl5vEFlRvRxL9b4KWSmKQoRK7y3T2fk4QXH+ywnyU4cSUPHiqI52TlRw8wCO5w8vkL9f8dY7Tu+fcf3HLyAQqpJxEpeRRQSVCSdPRlo9UNCQX5B6tMY4Jd2x8R/INaOEGYC07VrQuqLWMomb1tcWSDpOx2j6m8EAKc61IKwRRITSupX06YO+0rwW/LDMZg9uLoy1NUMw2Ux3XwDgREl4fTaNXwG4XtfUm0UFLCZfCxztVBVEHZfzyTLEYIEGczDA3v4w9JAjfX6sQf22Y0gQXz+aidngn7z2u9van/5mGeka/AgRGLXXk74UCG1yzQjmbL2DaHP0xW7rWAS6dSyVAWkIaP9aiyfrqYP7KEQ7urh9QDpEjecTEUol1M5232au+QiEnxM/IrhqOJkBhN3tMFrDvvX7jsej8u2ZHUEI9/d+7e6qwGYTNYiberBJrW73MZj7hQhcC+pCuBBh+/w2lXaKUTNY/S6CykuiMWEqhTuv1ZQrHHHAkBz93PFiAHqImCMan4PXTBdn73/vfPx5/HuPPx3ov+X41ir+3lX+ndeRCy+PL//6Q16SdPpnRdZAByZ5+ECdJpv3oS1ffz8dPr1TU3UrFIQPAMx5rgAKvUfQivjR6W984dydYH/fzMfHrq/7Jx2HYRctjlDEUzVESDihvDzHM8iMV1cu+MCMqpatwYXBvZjjs6+gTh6NeC9ADKGdJqO3QSlF3TLLeHCDUO/orbsDfUPzbIZcMUToTPhBzT/y6u/6doTd9xz3M/JHCEB5/E6OEQ7rR20pANqka89z/6U1FkfAwY865va74eNuncb91wN8+JMS3kjxzhXp2Sn9tUNhzvQnz07/TJq1v7/v+L6BfNYZCsoOc5bbMyLj3PqqqGrqyu2fv9zByyVxOTTzjRTPCBgpRf1rhfzzBUqvuxpzBGD96WcAL9CfgNPfTCE5//gD1p9/ngwAe8Uwfo8A2O+jGARzpiUiZBIin9UQcACs22ZG8Yg0fEhIFdvWwEy/dxn/jzjmdT72jG2ALpIO9DhmRSMU8si+F1fOM1slHWHugnaHQMC7My75UN8xdr1nmyLrDQVShwc6vAyBkwDwC0NfFXgB+uuULe2Zwk2b29804eDtGhmZQYgsIatf3j8nVoIZFABU8NTWaUBoP36pKEw8RaDgC0OvCn4iyKuA3+3HNrKtIgMtDjNtKDKVRWXwcLFsZqg7D1wpT3tLKA4xKI7TVhdzXo9a1ZhqG/qIOHRdRsi/PVrp5M0a3L03g8MtpfpecydoE/C5WkZ064A7RpfTCafzGWWp6K2BawWrwZrzFFUPItSlukJvxgrXRdG7wahlVLJGbVmrdUpEIM8qIQAa8IkCGzt4neBty/4zBMruDnKnbXPjmJXM3dC2ZpDPvWemfaw7wLO4xXi4itX1Fvasjw6AxGqau4ONQOCFEXihKoqmPfvPzGAd0I8x1wGEHVZAAnZZW+oTaZDtZhhTAN3r/iJQNdSMObFmKGijIksEMFPOS2R1BqSnQLyeciBNeDvI1nd3p9nttppxWRfIqUNQsW3m2NEMgnCDLxNAXpoBBNrhxWjuOeZiELZRHNL31NG0kygLsa5y79mVfOD/01L/LlYbxuph4jheMD3n2Ljpu6NZYSe1TqfSyXC8fiLTx6CyR0+dP/GO4esemn1+bjaH7qDzrZsuUZPTF8DqVjtkdBcvSeBoBvZAzbVW/fseWWG9uJEXmXmlqolUEQFDJqu7YZqj3rj3YTKQBW0RZQSCQ9ECLSNLZKkDbYELo/aG2s0QVrhg6+6MdeMX/DnLacG5na2medvQ1w1dOkgMutsyhNyB3sIpDMt85wJy7FSaMtIVFuS7AVC1DJfT+c3G16HxzUF7hKq27ETqI8DGjKbhtAsHqhn/IpCL5HEwSMrCc9CiGo+ybHNGJ8nahDTTp6DRbjA0Z796iYYoqeWwukwZNDEc6C1LWRg2r9WDDV2OA77dA3wCUj6Cw4Knd5FRysP/hsIz7mz9MjHEs4nNMe90xulh7FKFQsMRSsiyALbeLWCEAHPEK0GKIeSwEjSyzQJ6Neo4uTwATEE5QZrFdMACc4ITqzsBJOk8fCyXywXbuqJ3MVQPjECEpHsxL1MWN5GOShlqcWFEngXZ+6Cdd6tj0If773T6c7+y0tXoY5syjO/zyIiL5gZ9i4zCUffZ+JY51geNTz7m9CoDveJ3zGacn5o81+6eA43GCsAoQZVoRUNOBQC6MMrqY8YAX6ID/jkCPACEtzLQyUBA0QpFM96tFmAnuILVnCLkzq5whquy89Krl5CRHPPYuyNAIkjvlHGeI7Cnm+PbvSE+1ugsdyTXOCgZdxnlu8/3XOrRV8evdfodr2MQcCbH6/XMta88hLDYGOczJvmHIpRWg01NbdeD3EAgupmTm86HFl79+eZEn4fGnn0DcMHIdHvzdXZGec9h5zdXo2qObcjF8PdHjwbnf+BoCdVAkXOw65Y/i8GGrBh8nHy/TTaDMYhfmKz/A0eKKr45u9OGXJMYtCTqYnMp6UCnQDLJMl1AFB+X2D+hKYa87GNrjjLjoyVLioTjnDLjfCZm9jiXnXw97WwgIfPMnZwWfvBAzUm1vqYT3dsWmfWmA3KiiIQMJawe5Gu0JZDIwukd66e7A3H1cjZUCG3brCyJCDZCwuA3sQzxk/PhSsDlhx+wBFw+EfCLowSIov8sWOnX7GLYWkIfjbrqXQX87hnl10/uKPMRoxEISMj4j8F3fMyzLKazW8taNvot0i34jwhAt8CHMmTJCExmdUQLGsF+oZ9FyZV1XZPmHsDhvH0uj0ITRY560PKgv5rsbJ76GD/RcT5e0WF2UaKKUhn9tuUYKcxB31VzLR7ihXIV9S6opwXX25bfxTB+h1p0R5/xhc/H67/7ON7gn8tf32eSWjS8fuHFgyYcTuwFFUMnUVhAopdAIxCEGQwFeoOsG1phaO8gApZSAF2AaqFd6sgeEsH/m5WU671DmUFUhk6SdMOQC4OeIbswyemEh4MXdrgkLr/1+B233Lfh/kHf4haRkBKiaqDPERjX680CQSQQxSwZIoIlznXB23ozWYUA9eCvoHeqDcX31aEq3J2kkJTlsBZivIfJ3mluypchc94PYU7F4eReJji873sG7c/jDzv+dKDvjuOSfExtkihpyscHxysNw3JqekgjUZCrFOC+RN3jbzUBLkTmyc6QSvR8vGhWDoRg7zgfu3nfzxT8ZzI2KweqeK/AJwY+qGWYxzam+dlDLfI+xvMUvzqh+CsYDT+j4ge8kmUAz+qW7p5kv9/7d3PG+etdz4dzeKYl30NPJh1hwCVhOHQIBCEGSHJwwiEUUZNhoHnjgh9ggvmvSgALqnYwGMVnMcy84sIsxzPJMuuvYchzQx9Xz7JhzmhGcQG1t4bn1tGkp0G6whSCTgwSwasq3nk/fwXwI4CfvzQQX2GGx7HMOZqVre+473uv+K284EoDsn1mNIZ0EJno+/3XXXj4UmDBZxqO+VnQAw4wbhir/0n3K++NFH/78UfcfvoFz//5N/z9v/6x69tFhxGGD58vSsOIgT8++/yshM+keC/vcKVP+V28740EZzWKUmBOBIGtL3Mgfm2W9oYUy3IQyD8Fy9+qQ7PHlQDrC4BXEL+D4hOEGIoPZkAvhNNf/gJVxfrLL8OABI8mBWGDZh00O5xGpZFf81/AlUXfT6qUfkiDbuOdU3hrzY3VCJXzQLUGjbcAF/WaVTKyg6ZW/Xccf7RMlYKqC6SpEAKDgwzGlvyvzBB3iKyHYWQobIZyInOedzVDUsWT86Z0uflenbmVOcoR2Q+vwIpPUAAnPEMByOu0U8Ox6qtHcJuylGYOZoYqW+O2/rfPZpoU3JJn2FPOYDNRGnWhWTBWlKdq4+KwCB0BKWya+XZtZoxAAT2PdqjIaFsK4uoZ4ZQOj4AcLqHoqqIyPJPLDUIUSr1BiWOuP+4DWeti15n2BkrjkBlNiGDZBW6cu48ByjAzWwJuaBnGXzu6dHMEkUkpRAUqHcv5bHuy1qxNy8RAVxRiPL17xusvH92uNFYUl7IzqqsqWBRC4pnXZFmBEzEyWHagVHOCkw4lS1QTwjbXuvPiuljb2DD/zHmlhC5WhzzqJa/r5kpvcwO4Ob7MKWWR5KIWzd99bkPuCgOcuiDJXqO5lAoqjL41NBKUbkaiGPkw8qs72BXmUAtDO1FkpI1x0m5Q98wOf+9OdFsXBLjh0Iw1PQ1wQQFtHxt0p7iDxqLtzbGSsMpqY9PF4NtDkFWYUaptNm7X6wpRwal19LZAutVQ782RGJhRuIK5+Qbs2K8uSgMueWYPi8HFd2/7qHP+FXvBbChJgThNDXc09VtxbQHtaGuUHsqq83NiqYahfvf45FNfeNeDv+fvUjInALmPHhgv9P7e41P3lFiPp20eKHiwc83JcBD8QNWMrtrFgBqogQhoXqc6aFjAj/ZuWQYiDgxRFNw5Gy4eScdaQCXolRu+3fg0nOdk/F+HrMBRR7Q3l6sLwJJGYy7s+3mUXGJ/dtTWbttmzshupRpQvJ5oPaGfBKfTim3dIFvzkg5qQT1YwATUYplZLWpm+1iVqPmnBYoOaECjO70WxbZteHt7M6P/YtnvpVQzys01qj3bqq0N223D7bpivd6c/o9MORAQJZ9FktqkHLR3Hc4ZyAQ4ajQprD42jUxi45fhIOwgMJgLzueKulTL9Hf4d7uFEk2jFMvAETFe17qV6/j06RNEV7AQwCGrDKShgDRNhC9KcmQ/EkFLSGhNoxOWYdK7gLmhmJJlkLNccDot5nQAAM9CTHsAAWVZoCpYb5vJO4srXApwEUN12XSgbUTtJvZ9xJNEPVmnI6s691IXdFJHsDFkgd6aT4t6bW/LcIrAhpHxFDzQyqIYn7UyKcYPHFUE6oF05qS3becUa9KXZqo5aO2QnjXum+TFkCZDP8Y0hvCs/SHXCKiNN43rjceYrOJCn8owMG8+9hUZlGODqblWg26tbysAxfJ0saAKdzT4yCfBEx8XQz0Yc7VuXvvWa8YSjVIohloHc+b6WCgIuAH85E2sln3OxWTH5amivxEUm11LfdqBzp1VLavdZUVF6G6E4ugMEVQW2ebxfpnnEgBhAZGiIhyzw2Fs/W6DjxEsi94bQ2eCrrFOxxGjZiTFM0HpwJtydY/754CwxwHM8fRxzOyI4PWvAZyJoRdzWBCAft3smnO1Pr5toAuBnq02Or9VCAbyUsn2ILZx6gXJrhS5fxVR4gvOBm9IB+ahwRL35lc+RriCcbb5pCeQKuqPVi5I/T1gJBKHwfCHXAeQhtP9YjLnxxkl4BtCTMg+k5KnIM9kV4DDyaZ3c/XoOMpA9wfdXUHYz+ej33Nr97LQ0HnymTpK5t0/YUg3BM+ILmVAcLvNL4ib5xJbILD0IcPH/fCALZhtsZLJsgEJTy5HALH9wl44EVT1nZ4y7Nj3uUbCARyOU/87s4MnR21rFqS39QbpCiqEIjVLiQXKQgldJwpiA+iFQJWxdEInSkQc9AbpHW/SoW1Dbzdc1zN6bxDpKP0M7Z+NzhSzwRQpHozGYHqP/pNCuHkZF8/0F0OL6/LJNGifLpsCo+8ihmDTRdD+/jPWdQOeFetPv2aQgcQ9arrAqooTCDdVfFbF1qyEzFILtlbQuwW8dEeNIDHZsDm8PZgg6FZ6DZN9gkzW6FuzzHSnxTa/6uWsItt4lDvJ1ecy69Y6zmezcRi3CFQZuOPQ+CMz7Zx9BJPf1mbZ+m2G+QZwE6BcFQuv6ABuagGSpQjU4sVRfA2B4MkyYwcaWgmwtgbu/q7es059LNFaq2Xa6x2lwywHPKIUevj7Ea2Yv3Pp86vHZ7IynhcxmUf11dbFT84zsRtEfzFhEO84MTfC+6Emv8H5K2Al3TKAUgFxtL/msngXK8kkMMe7rFsiwtxuK67rFVvr2KSDSgV7+aqgGaU4LycLZnKV8XAcrZ82oTNqwQNO9OAp3/f3t54zX/2Yyk/tcjnwPvNfd7KCoUEAS/UyBWL7c+vNuktI1MLzecEmzcshKJbCaO5XiSXAZHKclX7ZoyLt+p0iOeUFk3S7uzi8bVmDHVPSV9pSp2fHb/0tY/rn8d9x/OlAj2NXVGwm5cfPirB02qKOzTa7it1QkOKML3wd1+2+j82HsUmNaQ3YCMqNNYSxXQQs5s16bxDbf/4OEukKQCB+vnN753s9Eo8YG2NtR/JmcFmEf1KAhqsJGnif13wic8rPbZ2F5C8eIT+OJt9N1bggWjjG7GsGTyOxnH/NYQIhqL6bjEtmYDMjedQw+sSK6uFotTcUYnM6OqNtWSvK2hbKRAHhByIszPhIlmVR5uxzF/wsM8KgBnfZY4XRYcaF4hLWCyk++RqKai8fAKtMfVgOd8zhweg8uvbR5y8/49vHb73vMr1cgazPHZ/tmZ7ZQfPa3e1cAFGj3K63rPPYr+ROevscgnJCPM+r97D+/uvnn/Ee71CoZEb63N65z6lzI6Dgf+8ofunp9vmcwTSKj/wpP8fYvHmN9gJDLhYyB3486aSPnn//9jhzJQX99AsWAk74S14zqC3B8DMUhBdELGxh+0Y8gIXxDMHnvK+4WLIRsLics8VU5DDr3edSPIOEgYAoBYbiA9/fBsneEXBmsRpmajyOWBO4q+/5/4dDEYKiw7UHv/B9EsZN0COBl/JfxRTp70a5oK0EgPGUHNQg0sc48wv7c3ysveZfKAABeh5Ocvv2BsLFM7SuvsrvZycEZsF1mmnLiA/H+fF6odXWZ357ygx2JkBuHeVScjMUy2HO90dNQbk6/38JAyySVyWlIgYVrxPu8MTkRpmM/pduWd2l2veeURhO98n2MmYmjM1OfESAQE6255rhmkFDM96JSntOGe0VNUGT/B21LmjdsrOLDKcyE4O6Ynk+eYag10MPgwMpihZzJutizyuMha3utUGwelCE1y0nDzhjLg5lOc2ZOymINwzjlxmUumd9igcSWPcYTEhezGzQ97ZezPG3tc3qra833NY1HeqFrfa41dwdzkDRSXlWoHhAZKAhSDS2mHxRPJDOTgaQ+8gYiEw7dSuK1Qq3TLst5qJaGyzDUjLzQg7GnUHOB02McVAPdsnMMjcUSjjLRdwoGecGTHU44ecahL0L2taw3jqIjNZua0fv5oSHmpFI1LNewqnfPWgQA9Ui207INR/Zk6zDsDzg0/ZC7XF/j8yt+GcvC85cYHDT+fy8Hyg/HINPHlHKPTdGvo2ONyl2O2/P+vafw7iVtHO6y7pHqW/A5xg6tTc7FIK0X7eTLyifGJDr8f6jDSqpvuMmWravG/9hRswemT3eHioFSxVIFchia9f2ZEC9+7oDUFVBYrTEt6Hv5ZIw7sGzwoHOHiyj2jOQBgywhaYagkatYK7WN+8Tu5E6apnC91WXblDt3rxSGKelYlnqqDUaGVKqXkvTg5yYxjxTBIUMmHnriwf4ZAZ592Au1OpnAAAgAElEQVSUK5ZlQTud0EpFrV6WQboFHmDs+a1t2NYV63rFul4t0IXJoH/zPyvbUAjo0zY7rlmbz5gK2+MEtVrmE981yH0FimfKwjJqSq1YTgvK4ln+UW+cYn5GQFGJIMWoP3+74Xq7Yd1WKFmG5MjAiSADSvrFE80z57kHO7j+bcnkPGQbVcD1LUMfcQhOHnVjjUIzBN3XkTmYSiEAFdoVhYAtiHKwGWUIdXdGwYPWPEh1iv8KRJKkSfNEuOMTSuhuEJfWIdK8jAbBDPDsGfBe2sADPTX4ivo40AjeR8AVqyG8SOhS4SSKsdIRFqv5L7BfLbP0NVPNWY4cskdSQJ3sDJmeb+8Neq5qVXLDQQL0gfwSYkCl8DtnAE+UsYHLtbMTADp9IEqI5pnOWsvnyYjfnuEsPq/JB5z68dD39GojRpexTs05YvN1ee9Q7rkngYLFndiavEV9LYh/ZhF0JrDXRw8Y7nS0Tt08RpUFPyAPdAlDb5Sk8644mVxSHo0WZsb0HXO1fkRgqNwxxmFDiznZr3PC8ZHfOsZ20XTwRlZnlEqjm9Vp56eYJ3frE8Hg8z0TXSmpWQS6Zm32h++1/sX1IdtDRz8JFwiuAK7jGXrJc8lH/af8UCa5PuxJEfSkYFhAjH46ukdiZq6TDICB2nA3Wccj1mboeSEfxvoeQagxAL508l1Hmed7ji/zHOSg76nMfjceZbK8LpZWyBhEoy/B1z1AjpisRjez2WoRgQruYNZu8nk40EPwYQuyLjC+U8jKR0VAX7ZIQ34ZMnXsp+zB1In4dgw1udPHglM6FAVuk0AEZxjPbF4mZusN2gHu7AgwFUR7OpxZ9erdCVknZKDOaACoGeLOJg29rdjaimW9OuqCacfAE5ReQaWAVbHwCxSvHoTOWKlD8QoSWMAsjBBa0HHwC5uXzr62xeTH1i2YrneBto7tVbCppM4d80rTiIo6LfIxt6BjAvFmAX+j6/kuu3bUUmb10g6+o0hNTuvOr0PHCqphwcaD3yVv8jkuFLXByHUuC74iR/PKBeCTpK4HOGk0nkGUWdG5wGMPkHpQsWX9n9XWTVuBcoKjc8QtA5LuqN9EgkjxYNI+6Sm2NwhLKVhb5AxPx7Rw454Z6Vqx38OYvk92kKSKDi38+tH/aQlD/FfC7Sd/z2Gc9o2cVo3OvGpca7JHyBF2rnbJ8lIA0NVoS+9AEw8Q77AAud6x3lYPkAVu64rbbcUmHU0U9VTG+o2SDy5/Wik2GrJEjkjIJtPgJSPxcxMv/yLtP9DX4wjlZdOHO5b/6Mvfeezoupr+dV4qTqcFTGylA8n6FUGpGuUkC+PpfMJt3SCieLqc0FrHdW0mE8NpHDO0B/TTsOfuOekxAGT69IDJ7XhQ8MWJsWeJDlGo63/jnkCL3UsZf9CQ/nn8huN/uQP9uLJn0fTxZ9IHd95JykflDxPztT9kzgKfzg0S5zCdKSgxiARPAD5Ha2hH/9KI80aKHz3zS4jwTgmfIQeCOViNPct2bfSvu5ARfaU7qrc36wGKd3rczJGdGmJbODc+ouIHdPyCH717v/iL3/sjPuaID0ZwHOc7AfzAZQnHCFcXFkJAdqrEMEmwRDSXG9139lW1DCmI4EOpOHkdvcoFFcBHBc6q+AsTzrViYcZfFPilE0Q2QKOeTwVTRyeLim+kCWsKWGY4ESySl9mMdKWgLAtKLei94ywm8JatAb1jAdyoZnV7Qe4Amgw9BcAPat9/ij7hcOgQEfbMYR7rYfwawt64MAWQwzEcaQ+4ySPKPzGRMDLMN8zrgRAZ4orPBFxcG/xMhm5Q8QM2/ArGe6z6KQVMW/JWO4Zhyl5RWxfPiNp+YxMoTEB+VuDNF9aT15Isfpm4xhjnA/L92XvQ6RW//P3VHfT3ZqVHwsZ83W89How2ABOUb76+b96WeZQVtndePMij4B0av+JKmlFz8fwb26aaDeOqhMkfnWvi4m/patlVN2xgfZdlDbiaEMjvCNvHBlZG+6lj+Q8FlZIQvKE8sDtwInoTABqbY/8Ey75MITta7OtpRppIZZlGdi1cwWnNFTENh9U0WyHFxzc01nrQx0du2gdyt/eHp73y4PjWQvi63IuvPfpwZX46CnsKq+1OsFpZXKzNBpNtSrnxkwM2wUQwiDAUQp8g2+9LGhwIQH1XcP30CYyXfbte7UFC7mgkheANzvZQDjtqfLomNzqei79jSu23OySw+jlKR/++a1HsIJ7Xcj3CFVisQDlH3Xi1oI/VNgkTu1XDqa+OeYhMSXUmb4gkPJT5yQlgDbewNUyR0JUZvCxW3xTA6XLG+nb12uPhlLDoZ2tyNcd/6wYD30NygWdceO3WV898KoxCo76bfvaRfB5zbM5wQKWjUGTOd5yWM07LCZfLGfW0oBbLPAQNhY7dEXI6XVB/YB8zc6J2zxxftxXbuuLtekXbGgKC1iK0w5nVsW5b6LVgNp56Ixh8dO9oW/eSKA3Xz2/YttUU1MXE5e5ZoqwjAh86gtlaGEV8GkWRtckgDbTF4jLDJtich4UBiGLb1qRRqgAVM46yQ1ETMcpSQeJlA9gURVWvd6tBd+CGE8sOV4dkb82c8OE031G0sNbHWibbAwbdrCAqFvRXhrKvWtLApyroXR16rjhksvMDwPtRzHEvgMJqDHYWbE1Q1w4u5jgnNNxuDaUyTqezZe02texXMojJTQXoQOsts/apDLoz03fFRJ8dIjv7SrPRYAhHipCNbUTJUQeCVsQx++xjn8TnqJg8EE2SLORzUm5y+rWLX8D87KObPE4GDLZ+8ZoCumvb/HfIWkqUmSa5LkZdlD2BTF5HO7l61zbAYS+d7sfm8/lKPuww4zH8VkLA9nCpJ/epewCbAL0pFB2iVgu5cAeVlm0K2tFaRamKpVqpDUNaKD7YAYUYDvaaZUfU9QVxh9ri9SSNnpQR1Ap7v8IhFpVQqGKpilJuINoAMeNp2zZc1UpQWHa6oHBBPZ1whu0ndDMAb20Y4KmMcVW16yJrKeAeg74RyB3ptr6ldWzrhqXWhMMvpVr5kqbY2orb7Ybr2xuu1yvW63XARnpmfATFhBU2s2xpDtuOFWPBh6fLk+2rgIcOXRgGXWp8ydpzOi84ny44XU44n04Gi18XQ6aJjL9Sx77xfRKZ5+iAYGRSzjr48QiajGaBPJF9OI9hBHAkn3O5B+q0nxmlEM6nitOy4HRabFwp1qjx68XLirS1QUjRV6PF5OtLIWhtM6N/2yBiAVfmhPGsb/b9p5PBvQsAARyWP9pulWyM6phj3IysIAEzoXXbP0F73z5+sv2k9rzIvAeFc4AsAJzUDLMqIDGkCMzyiG9sccScWRAlhIE9qIJO54PfTBLZwWGedpA83AlRK9AMrSJoSyQucLXAina7gcgQboCREJBw80S+fwbBD7h8EDJrrlSGKHB9W22cerRRfdz3cns8YrhWFHIT8HnMFQDU4mMSN7iuR5e9A29HJ8mhf98zVKo/XSGd0N8E5UIAEeQt9ptrc6qAdBAt1irna+VUbX1fxQNqbAwVDSNtQxzly2uDUwNRTbsWo+b+r5chfY9NF7M+J1nYHRoGLOhw3iJsN+rXeD+Cd5gSmM/Gbn0cXrz7ZPeGXUiuDXxhj68T1IuNJzsz7m9+4SWa23xOK0AtHRWRLV58agXhxNBhx/A+hzwQhv1CChKA9GR8/IXRPpEH68a+uNnTcrwvKB9K6r9bc6SsWODe7XAatI+OrpSdsbZ2XHNIYxgnTSJ1mLFb7WwEe1mbhvNFCYZYpOyBeu4YnB5MLuDss+sfzdZ8TFcoRhBN6Agpk1HKzvPnHU2KkkSTzKLza4iGXEOWMV7DPqgCaQ2LI0KxB5KiWca19IbWI7jC7UIhg4JxrgWFijvePVgMjq+mI1gmEMBEjfd25wfGf6rJKQRE3d1EzdIh/YnLaU3HHHD0D+6IVkHXns7m3gW6DnvKaTmj1upl14zuGhLMmH9pzWqOi2BBx4Vf0OpHNCVUUqg0tE7QTc2WWQs6vZk8LGbvgRAEjMvf/mZZzP/c0PFmgUMAxKGq4XLPzfu+pDBgfe/SsDVB64A0y7LvXfG2bXjbDP1qE7WMfi4ole2HLYjm1htu24q1CbbeQGS7fTmd0EVRevO2OnKIz5GVsyH0NHq5fCtigeJEjhqHpPUERXdeyr4emyPGPZ1O9t0ke3TpuF5XKIDLUo220GyFp6SzxSOyFDbHa4/A8gyF28n+3AXl5QlEgLxesarg/fKC6828DRHOHYH+9oxAnfGtE4GeZHJZcVoQwVzyYHNHAGWkCs6Z4zr9zgAA3NMIia7rUE2mEZmOwWegwAazgS5Q6D8DrcWShJ61QImx0pR1LCY3zOwmpjo/I+xDNMoDcTGHeZcM9iZeTJesCwQFt2b6Q+vwYFBENQiImLRdSkWpQD2dUE8n8GZyYiEP5iHDMNSmEDTTARxFS0XRtTuCpveBKEvKWSCcJG3dBdA/oNM5f4fPd3z/wXcxRxRMML6dxjGYg3N/t2/NNur9Koilp4ixt5adTyeICrbW0JrgfCpp4yqlYDmfsZzPeP34Cl4qLucz6rLi4+vbTiZMu9ZhLMY+IqAM/2AEsjwckHkkIlJEQ7dI/BG73+kfdG9fD5kwgpHddPgV/vnn8e84/vc60O8yOoMSAtOWwFDwJhHYKcBusaYOGELa9PeQNaa7dKc47h6k8Ag2nXasCU9vFILjzCCmHQ53eoWw6j/p9HrU7Umyzct0fznBYNvfpxEkxmTqTxCCY3/8J9r0C4C/BVPNNu4J49xMgsGaf3zQ/LxWRx+/dE2QZAKlEc+c1QM+yeDYOQGDcwrFIhmfVUyAJcZCjFNEjU7BDuwZbwJNR5+9hlCEXLXyejYwBTJRuWkYxakwfiiMz/67MuPvbmDr3SGXYp0wB0oYFBZtHnCqKvt5fOdjHzXRDyOZgQM7fval8ZxOJL+ZbwTcAP2FBajjffF5fgkd7w9DTDB4v94UNXOEx1g+K1BBIHx0RvMJFQYSWWEZ1REGEsJntkSRcMzx2t06nQQmPXy29mGsscMgCuAO6/14xmOmHZ8K+s0zwb99jAGcrw6HeRw3NxDEc8d82/0F8Ig+U4pX+oQbRTYOcFLC6s+Yac2+BdgpyQAyf/cJhHXdRuaK373qRyx4Qf+1I1zPKVCoBeSEkkjw+tF+XcEQ6IgsA30II/sxYs8mDSU07gnn77Lw2GPqLno6GvIOi9V/DdoYs/c98xbtJq+f+YXj/4CEdNcDtXWytg0gy6YDyDNkAEQ0+HG9HmTyGTJz1M6zkxwZF8x4/vAD2gQzmNHdmJQ5WgFisCoIl+m85Hk5BKzMP/HdiDMd7duXZwHgSmvJ5lPSsDt6SexZGB3dFyUpQCfPTz8N4+gY63CA+N8U2ZDhhBr8OmlkOH2idm0pFjylSGhb6jGGNmqnpwv6ahCgpIK+GY+2R5iyVUpBX3uODcgCJSJLK0YwsjKCbwo5Pfa2lFqwOIIK3PEDP19rxel8wuV8xul8xsmVHqoFvRk0qIqiLgtO55NBuxcz6hAzlA2arry9Ge+73qzOHrMHELihqHdIF2zrzWqPef05qHrGuRuR3NG8bhvWdc02sM+BOct9fYnkrJkRqkOa1c1VlTSAaYx67l9NsZKT4drgd+0W6UZhRPcgh6jz59C8FHW92eigvbuPtiZVdceGmX2A3lFrGavU362qoIT4izuN99o4eeY2u3HGA41UDNoQMEdJF6tvHEamQgR4UGL0Vx0tQN0np+LR+F1RN4VQN8V36+Ygei5Yns8gFBSGZfLSGFMFAJEBN+2zEs6/3JdEbiwPbucvzznZUztO46r1lcGTLDP2fMiKE0nL82lkoOBVe5qTnycacrQrZHvyWfvnjBeP4IH0S/hKoISi1t37d5q5j9H+Kxri0bhptC/XqUtDOQdhEPY63RhBawo3nGpHGKyt9mb1wA4fTAUIli2uLJDOnqmr6BDIZtMnHWgOy33sT69ADQsDVXDxe4hAbjAzp3masnPt+MvcGGb0qxZzuLMj1CjcQCVGX2JflOKZZW4Vly5o2JLGtNbMQUeGCgE1o3iDWt3z3nPubCztt6i4kWzvJA5Hxq77ouitYV1Xh5WvQFXUWg1WvjXc3q54+/wZ1+sVt+sVrXdos/rf0lsGLsyBbbHAzMij+TnWR2GrS6/kZS1kCuyJuWYLgqlLxdPlCU9P46d44DDxWBupBxA8g97GqW2bzUHSWvUyD5zGyFj3xnvUkCuYIToyosJJnQFsGs4hM8QTBeoGEhWsVoPqZ6asi5uqSmaWac6l7wIoLIgiazO2ht42C/yKYKRoR86vIOqYR3/tEs61GIgE0HBywwKekrYF31EjezrRSoRxVbJOOiBJU0YwekjeIXvAHTmWSTUUIjIn9ejB7rdddjgfNhHdX++7zBwqEWnULBCOHebegpt8iXjgFmHobvnSWQiNd9HcFBpOv1gKFEvC14XzfXUPMofgeOjpkJNsrHUagkGfRzNEAVomWhp7H4RhJbU9UEuxoBGywEcqBfwyZAZ95wgKXHxvACIFXHk3BMlzXhjcCfIm4CeCXCuENh+RSU8mdyADSQNS79JoO6bW73nYyM/2/TARrB3wPe3vSANxMFt3BPw2cDaXU/wxHRugJ6+hHOtrDAo9EfSq8xTmXhAsMDfMmJpdP3fLfcajdAQYQtoICs6gZ056V98T+kcLUKIXQv/oLix985EbWZ/pANYIjJkCBJyXChRCN5CcUyakDwX4uN+V+3m6l1OiYwETbNfNe9gu3iVMhFM32ER4wnYP/d5j8Dxrn+/R6XWzY2aoSpRtEedjWWMcEcQB28/TPYSRVcvMZq9wZBZWL2UR/KQ5v+zNE3AiONl4AhOb452KJ+uYw4sx9Ca4bBNOL/j8WQCb/a5VwAVGlwsDTTNhRvrgUbNMqCQJTa35muE8b9IN0bL3zKhmbmDn46EfhGwT9hfASjOxApCO0w/P1u6fCF3ZdSCFaoeoZ6p76ZRSiulhYs8hseSF9qtg48/oIBSx8oscPEOtZJWKovkYR9B875qBh701C05Uwdo73nrHKiZvNReSmEaJsEKEq2fj925jIWIoK3B7LsgD0qCunyFlYdXgUeyJN2ORRl3mLrAgaQBQKwXUfS2OEn+U/0bZkS5qqGHMeLs152n2cna+e+SlJgbbwPTJcx1zf/wsANrrG8rLBXwBaCVs29thezoCyOH+aK+qvavrQCdJ0LfYflltS3PsXEnIJxpnnYPtKJ+R7df8Nr9L/nAYyV2LD8ziSpE05bafZLOU+x7zc3b3Hykm+f8usbPt7NDVuhh9KTQh0ZUKIUYTAF3Tnq9KEA+67R2GAlUZXBm1LFjqAu2KluvX3iMEMG3mYUhdSNHJysTF4Ck8cTCYlmDQnVxPo2e87+WYHT2Q8Un3/tKRTmbKIUPsof1bjqvt60eMe3GkHsvzsJV0qgtuq5XVs+WmIC45v09PjuyiinI64dIFn68rAk2ACrkOGzR0309LrIl2Y3fuy+0dF5LPeUSBBP8savxSPcli92T1afNrMwbzN4zZn8e/dvzvdaADwBe35/F7evj3vFhzaessJuNuNesXvp+/zJoj0/Y8um7uH2Cf32lsJvv8GYKXqaUTO9rfGwqCi/k0ef3eK/BxUoQ/0j35AAyK/d3kjItD8Gt+fqdGjBt+2csgeYTmYp8C2j3qpx+vnP9Igny8lh78psF0Ac0aWJk7QHtFD6TuAC+obPDqi0edR11Ng/5r6K3icwWgbtRWM54UojR4h8PIjLLAeyf+AQO4+G8w4y9cPAJP8aKKBG6NkDtneL8Q8EPigumDsUU6l3/9Ts5Eh7++tjPuTmiqvl+78jcfA57OPj8p8Obz+SR7scYrz+0EgIAT7j7miz+qTcJWxNAP98i+/c+T4WkW1KK/F8UOor3qO3T65IIL8t64/7gj423zM26PUvu/eCjOyriR9SDuvdwJgEfqNgIQKqwOeSPg5nXQCVbGeSVNJ3pkyNu575tnBiA/OawVfUKbRrHpa7h6UPGC8oHNMN0tQs/eJSA8A3jNLA8CcPa1QcPTYP+GsRdDOB5KoLdeh2LYtubCa99Nzj6A4hC5jlB8xnrX7NduyL+8HY4azndvm+8W137n8w6CsfOn27oiovTDMH4+ndBcEb9rxVR3W6Dp8FUoWD2LReA1l00A7q8d4nS64w0dk/PaiWjU6kYpUFmx4AkgoKlAZU1j8t1oTPNme/MMYEWA6YlN6PjJ4I3BOwhAwQmKzSKuQf77MKLa0WD11HXtYBCWy+IQs/6+iPKPoA5Q8qqskedZmiJ9GH6a72V3tBLBMjqVsHajbL1bdtnpch5z6Yp/qZaR3Ddb729vbyCQw6ibswOF0zks7vQ//XACvcU4UvKiqC97fj5j8Qy9WioAy4js3cD1CxFKqTgvJ5wuJyx1wfn54rWQzQlOTEBXXxMGRxusr3gGusDqyXU3BsUaFVVs64qlFGyl4K0UlK1kxL9lkEegmUP3uSN9a5s5zxW5llUleXctzjEUDrdmTpEuHV0amjtzut+XK3ZafAalOq0Rd2xEnULL9lffCwylBkVxCwk8+x65ZtQzqwUKDss/DeOcZS0gnSi5xlInU4wLcuFmFikDKNWy4QWm4Es3eFwVMWUvZBLtICXnswIWd2q4/BPQ6qxwJISSGfYgC8owRxVjqWfU0wVnqiCHZjPH3AzNpmkE6F3QWsO6rVhX++kOXcs+5javACIES3g3FzPNNqcUwYqMTifwmJbkl0OUHXRjd/c3ZKoHwsHIiN/fMQf6zHCkSbtnZxxRBq/dHWG8nZ7PpVjwwPSdTs8njMCFMLCO9g/oxzTsweYeWoaxOXgywZ1hNd/VPBs76IuVtqa9UzMyi0LXcesOxdqwnoTNHEWKGVrUgkmiHrr64HU1QwmXgggKsMxptrZHoJs7riHuxFXPYPas+xIOJQ+8gVomevwE3Ur0Cu8nEBk603tc7pdpvZPT5+KBSgFrzsVKdfQuaOuGm/OUUiqY2d7dWmaf37YN22YZ0Fa33egHBe0K2QoEK1fldIkC/QAT7yOIdkOylR4pLiAm1GhjOKCrZW8Hz7OACwEXgqrROU2rm/VZPEu/tZZoIa01D4RSXC4Xy0D272OMRQXoAiVzhkQQ1rT4c1yhOtYXjK+y11yvpWBZrB8UjpU0HMccCWQV9NY9u9zmjwDPjNu8hEcDAiKWRlZZwE2m5r4XPZG8xOkzZT3LnmtGRaC9GWINTRlo8/ZWgpK9Z5QpirEASPsEyape2iWCF31FEAG9IYAPKL3X87vGPtT9PymL5GfCtGfHuMUVkZ1MpaAoQyicPuQnxddOzKV4/wHK7HrLCJTNnk4g0OKE09/dV9OfyrlC2NZBZm/HhtgT492hqwInGw86EyKXz74ntGYQ28zFw+oVeoMHoZLTS5cJ4MER/kpJOYeGzFUtQ9xoIqGtFiCynM9Q3y9MvG8jMHgBA+Wd171/IuAarxuaUlD3idtAsYGxoDyNeU+Z4hZznN6TiSfuhy7neeYh/jn65VLKPSN9eDy+KN6rBOgqkAsNEZaA/llBT4BeFYqWmff0VO07aj4OC6CahlTBhgZgUYFQAnZ4E5ymZwOisMkCesdOHzn38vIDW0YwFOW9PYzxgv4qFigxjc+yLAAI22YBD7139E/BMwHAi9DzDapnhJg3z6V9fDyYu2R/GBKf8WGnC4fbvqXmJiLn4YLj9fetCV6qIwDFfxNhoN5Nv+fz1tZZUNsf1YdrXm9HkwZn+zUbSGp2E4vD84QcD9CNwMVChtJVvXSMBcEOuSfk8zlIygV1l1stEzvQLtjLvHAxexWxpHw9I9mxB141mEwjMF2ndytV1boFDPcogaaUAcfbtjlMezF0G6crUaImgnWMURTIpzd0aVgCSUgJKxS8VCvLslhZFpPtTY9REZw/fABA6D81tPIRHYyGDjSHpW4NTTd87uEY9zAu5zOk8ADG5oiBDRDFTRXXbcOtmwNxA3L8CheztzKj0hMqf8KZASHGzRMmNjHElWWxMgmlVg8AMf7BRFhAWNtm0PyODBd7s0NyPG3d2mI81QpVQXHv/9b3tpKAem/d0AUUBgH+w/sXQBVvb1dDFg1h1vl39RKftZpcvW5mO+nJ9+93VJDqG4APpVqgf/sMacatBG6PoaS8CEpN01/i5Uks8CCC/u3ZqZMf360hV1C25cA+8q/53/1nu/dobdprMF8+Xmns94uaLLsSPCh86Dax9gfdJNcLgNCxU/fxfkcSnbqcDOLUd0xGKmAyRImyLBZ0GmhEOkoRNOngDigIhQXSPFAXyAx0qzpkBnCjURPzmQIUBu0/HkEoD4P3+KrduD665dEjvjYPj+6e0TvDZvHoGRGgDZhucLlckLgJYgHDvTVHB7Tvu7zhdDqheDKBqgVS99axLAs+1IrbbcXnmwUfC6nbdsa41sIWBA31gBG3Raecu/fbHcctziZSHkL8VERQanE017njYaMPNvQbBvbP4w88/nSgf9d3XzoTkZUhdbmCpb7xg5FOSiPFH5g30f4dtRTPfNyfoPkiGCz05zvF4KCgxH1flhnnlt016t0jSfjuIZOk+uAFoey8m/rdsV989JXfM1P92vFd19x514fyrjRFEoopBxkRrYp3MJhVcyp4xiUGBFx3obO1hubCb8AiAQ7zxgpyxZ0Qpluvh1QKuFqWiBnBCqgUSLHM6k2t3t4+C8EjpNSCDXQWcmam6Uw9xulb9Ja++ld8HgLUNMD+ah28+xvvmq9J5ecb7QonevbloOCN39bKE96j4aOPucWNm8GC0GBrMaPoH7zva591d+99lqvCMrjvTe/jGsHeQf70L8C2z8LHKREQjiNz3xZOgxXAeA+BovmyuSSswP16uKWg+fX2zIcJ5kMYKrBIY9r9+Or6VUF/HRRBIQZf+KmDvIU9bq4AACAASURBVBZ6jPRRMDShljLLk0HDIEqxGvxaF5ABi/oVDbSKGJev7Jokn/Hc3ynRfGcAwv+EQ8MooSY8kivntDnErdemhtPTiDrPHnZBz7AVSvaRhnQA8pqAhwkrNwegZFYauxZE5FD/kZ3SIUxuP9V9w7GnF7YPA6o9+JYjgngAhrqWpHDnetbB3FCwTLzKgkNmfhowguIx9ZOZGoA7TcN4jmkFJfnWXT1ckZEBZfZ7N/arQdLBndiL1xxvrWGp1ZzFqxU3Y3f0SxMvn+B72a1NGsb5avMWjtQ4DGKX/f0j07eUgmVZ8PT0hMvlgvPZ6pqrWK3rbTPY2kqM0/kELuy1bgvW682c/J75YA11GcozA8hry26e4dDF+G53yFVoONk6tm3FuiygdUNXUzhB8Jq5bfRzUnqkK3rbfHpHfXCNGnZE6Ns22ueyg/SRydEz+3lwyFS+PdBhxDKHMhT188LIbxm3Rf07r31aCJmhkmnc8Q5EdLnzYRVAeSdIjbqMSNnH5BxgpE8PWmT7ybJYlkIolcyIyg2NAWq+H+CZMv54yySeUJOUpkAQgkoBeASHJFd2o2IplgFzOp1xXi5YTifUuqC7oSw2QxjzYuy3zRyDnz9/BgEZEFXdaBcKrsFDOkkoNGVH7ekwEVmW485KM43P9C8eXaIzbzjePb54WHtuvlCnLyeBd3Zej1sGx5pXYeokd3xKh64y7QUAqFhQ6r26uHdy7N+aSABqMLXx3a62KKwd7KUkwilNClB157U79KMm6JBuNI3iZrxjn59w7bkOJrZOmAt66yaHN4ZajJYZn0nA7CGV6sWmMTI4AVsf2UbfN7GXRD1rqY8flahCGjRFHD5Qsa1eb3wz56+Vj3DUikzuI2AyhCs8SHe3DDxgqjDqUrBUM8LVahCf3Wtfb82eINKzbIc5nxvWbcN2W7Ftm5WCEE0jUy6qAKYIfYiO8pYbsqfllJnrCWpBqIV3bTQnerUsbh9Tq7ttMKzECkYxA7SjhUA1nefNnefdIXS708nz5YzTacFtXbGuBoUsUKgbHhUC7gqUAnaang5cDYQUjHXKSId/cV61lGpwvBTZq5r8UsV5QeiDreXYWpkgK/kRPMXmVQxoLvZhyONKI6vN+ZHpkznS/nVkLyHpTe6ZoCsR7DFutXtS99jTn3RYynx2rwdYW9jmyTMg59OxR6d/drxIvF27Q8cfts9p197dc2AGyFyxSlMpkhHCGpn4kZUbjwojvsKCcmwdz+WH4t2DhiFlyon+TX0Y4QYKuhH4oiPwO669KRJP6eyBE7doVJAZ9hgAg6HfQc3Pb1PASkwhA2dUIrgOCVs65Mu9vJCS2/DuggpQn0rseMh1lHvZB1MBhBP4ErKyjdXedByh7Ifjt6g7IQP7qCcd/B0q0271hkhNSAesUAOuFmrPl2VP2FwHIFSbh4mXkQIv7y7YPorlopLpE5zXnUAg8DND3sYYFWbnH5OjyYPKQvexhwD8gTyIk2xdBM8k2N8CyGfNNicfjDaS74r8zq462nNCvKBxSWa5HQ8zD+zvTyqRcoH6Ox/Pw/ccg7ZNL4iuTmTpi+e/sWCCdD1299m56mMXjTF6LbCsYqMdxUs82k9gGRIqCgpG3WJzrs/zpDvkkugCEUOKZSQa+o0H8hGBqFhMHzgd6IVL8mPWKEXngXraLTmgdXc29yyDFfOtMKcrec1q5gao6Z+1eGZtBM3z6AF1g20veAb0ExoURQVcC5bg+dUQPGspIEfqqqXae2tHAZs8px7oKjCHYut4kwZpguooLRFgyGqB0Gs3WUC95F4DsHmfm4YN1hHTPMCBiYAXQvn0hIU6NiaUQmgKRHBS8FH2OtMl9GaJnWPyT+FiNMrtbt1rX4fdonh5KXsOoUtPnXu3zrG32IkALoZCRFDKCLrXKdW7eGmc4o70iVM+ROrQ42cy1LlKETsVGwg7+rvD06DB75p0X5YR9oYcv9yEvshi99Chr4N6zMPi/DQu3LHku15MNx47fT/WMYMnPZ6JoKqDA9031ozUtfteAdCkAwfPdL4BCmSl6vvI0ORKrVhO50wwUPXgV3eiM0xX6b2DPVAUMNmneCBKVxklQ6IdrjvtAn6y64exI9o7ZI+nvzCq8d1xJh4eX3j2ty5/9HnwKMq+qBiyFi8FEEVhQmuCUiu22+qlr2wsZF2xiOkh5BmYNo4mj53PC4iBt7XlvgWTB7XYK5dSvWyHeoDMGNZ9F+dwgP15mn5cEjV6G/3S+8ABvbvvz+O/+/hf7kD/n3lsXkMnN9AXjqPzHBhQN/PxOjnmdsIaZoI4KYIYG/uTU+L3X23xeNLcWsvneI+Oj3jxB350ZeWDDuI32yQ/hSYDxfs7hvb42MnGhxY9Ypd3wopG9rlniatAlMEUrE/xrCaYLmQQjhQQjmB88gxz7YKuDRszVvXsWo2IfjXhqsCNShaB9p4BKGXmeXEB034iO4fcOW/wRFY/NCBiR+RT9OUXgtWjV80IwuLd5vvl8ZXRuZ9TYM+sjt/rUcLBXvf8ysus/Q/edzyf9yk80xt4UTgSwJ4pxbrY8HHnfKu+4jcEHNv+vllRLNP5R0ICwdoAWDZ8rOknJbw5RDpjz/AeHQazbk+fM89/z3FW8j6MnTG/mxQJfQXYujj/9QeLwiuM6z9+QguhcOrzNoXCfSsj/rgn5+ONFIxPePnbX7H94z06f8KCFxemu9sKXgEi1B9r1szszVRb+djR6dXhz14geNt10FpJIFJU5mEQTuue7d1S2B0+5vjpEZwSsiYd9kCsMZoed+j0Y+wHP36rpPPNZfC96+TQ8N/Ynp3zBdNeCKG1DyfZum1Y1Op/Lu600GKBYeGEURWwQ6zCaSsrg5WyjVoE0i1LWHDzGTsDuJnSnJZZJEyzdEK1FQTl5lmEGvJotnHu+Ky8hWIXEdQR6S8O2ck0jITmD7Q2pEPBKcSMeGDDrlN77RpRwXrbwMooJ3bF254lblwnRB0teKYb0lELz+LNHend6r2DUbz2dFi+bU03aajdDXDh8I5FvCLr91m9csKyWC22siwGmxcFR2HBDVIV5eJc8jMc4riYw/N8wcvzEy5PzzgtJxADfTOHdWvNIv9LxVIXnJYFIorlxGB38odzBeRZ573j7fMroAY/37oZgKIWcMDhZjYrWbCNqGWGE93Q2ualBjxbvG3JyuaAh947IJJBdTo5WQJaL5ToMcnqxg7JzOyoVRxrKRchTQrStH7hsNEpF/UGCEPZeHkx7MZcj3BnQEAPBpQvhWFhtn4Gf1ZAyOvxhfU4lG1Q+s9n2tA9eI8ypJBhkIZeisALqSk4n7WD2Osub7IJIdZvW6Nmd6iIOrW2XS1Kv5aK08nqIl8uF1wuTzhfLlhXc5yVYsbEcMKFY21dV7y9vaHWCiLC1q2uPfm6HlX3vPtOEzLBfAomy6M8EHsmg8RXAefo8Pt4OLOcDdp3lJ1od/8xGDTsU8dAr/+PvS9dcxzJtTtAkJQys5buubY/v//b2XdmumvLlMQIwD+wRJCSsqp6mdvjW9FfdUoUl2As2HFARFb/fNQnnIBt+Rf1QBx3WmenKYIbdv250bW9zmJyIQ3nUUJsU9LZ4VVooGtE8GKdprM4j9a+aX392T+OvTV2gTjrfpdp3gSoBlJGZlKN4sF++AEAFgAbhlXRIZtrrV4molmGiDSQWK1w2tQzFaznszms3aitGXTiAbzq2c/DKiB4AJX6PvUgE/Za7JNneIVzuraGhubQ8Za5tdY172cIDj3oV1rzOudybbShmEfGKOP3wI1bgYMKEUpnJBfCNM1YliX7yJ4pbwZ0oy1NGloVoBJ44nQYRLkNVWTAVPZbY2/aeMy+72N9iVhpCaOXozOvB1sAAIXTP9cqg4utfRvfgmmeUlfjwvne6mMqHjSwOrpAbStqE8/sD/QWThokqhkAkCVnMMojmgFSuklF0aF0i/gedZ7Xgr7Zxojal+KIJcMUDaOALYGLMb2hXNfVAxu9K+yZshw0fFg3gDsIa+38TgWFPSO8o0EPj/eHZh/sWeGMgvO3gG1XgRuOnW5lkNYETSeFz7QodJXkfT1orBiSz+TPD+YEoJ5DTrB5I0TQWfRRdyvfgiTh2qS8KMgz0QG1THco9ALQEvMGYA6EGLUa0nNBcRnaFouVheHgYyF/qxvcq5VxGcfe1v+g0Q5620b+A5JH5H5wR5EqLLscMc5xr1j59sWQaBT64uvvQNCzbmw8r7XkIeMyH7o8spaOa/LtWlC0OL9jnJhsJaKQk4IfZoRDGCDgtPrZFZZzOvkcm7ZBblFgLGgVKA8Epclgvgm+LxSHpyecn79AVcGPBHkWCM6QzwfbP49OS8Rkpqg3HSV0xPdZGCgiuKs18VrMgHxsjmDQa6iz75nQi/v0HUA4I1ZglJjRPFO7yhJjHvKlO8UsUEdSjkxx8sa80O74Bs73RrsvLg1y7e9orN3+QwBW37I7SQcFJkOBgEa2EraIR+6kIgtKZufHPNn+DW2Q1UDbi8sbnR66Xhe2iAzgchmNDK1AFR2VK657ZQzUx0oJ7kSvaNqynFVr4uUo4CVTkLIZYCgXa42gGVj5BzK+DXjgY3HqpYFeSGA9gZv12UrlEbhMmCMr3wPsGwEsjPXzJ2gTHP/2Mz7/8xOKKIoCZzVELz6vWOvqMPmCi3Zdr5AFRxUPiD67w9wBdHBWdyx65i9CXooMeADr52fM756A9g64rDh9tLKPl1qhUKyeZZqwEh74wF4u5fCwQGINpLMYmEtB1HM0GmPjellXhElKIA7B3TPFmSjXDNSQxpiycIahu5WC1gRWp52zxJjJpZ4AEionGaPbsfdsETCyfvgMejTb4QygOuU2n8T1bpyc/hgCW5fvE9FmINAjj9Q45rIuUw8IiHU9mHdu9PheGznCNplpewf7dAynKXrs2EjvYh7399k71DUc6nEP6cF6AIPFUY+I3HnOCFUZLqeWMmFeZjQirKvZg5oYQsS6riiuIwQPzPIfZcI8C3Rd0bKEkOsJ4qhDQa/3Q3U1xn9827Hy3Y8jYx84w37A8+t2JsPZb/YdGLIDLEB14gXresa6VszztCnrFLrtWq2ExWGasRwXp8EmS1EpaK1hOSx4uaw5vxEMZ+s2dLZ4Fd30WzdfdfA1De802PB6/P6wUhUe/Ilr3fq1sb3R7vPTH+23tB8O9L9YK8Q3oW+/twmAz19xcN3bTHH8jRq8ydg+0f4sxRsN+Pbre6ln/QLAhLcgfEpY9u/ZtPtzb/Xtay2zFe3LVuFVy0oQjRqNoXAHYSPMZBnhlklphh0C8KYxPsOE3ioE1IqqAjiknkWKMUqJaEave6dqMPCqgxHMDDMhYEZBLm2aBq4WBvooHqrqgNdG2N+rw0/qlmdS/g83J/+aNN9ZIy6QdYi9ZA95fEvoh3G///i891c5wqChvfihBuCFDcK9aBcI49Seq2aN8QaCz3lOw1Yhv/XIceieyZz35c758SoK4ESKBx8l2v0e378Pnv12Gx3w0U9ggBy700eCOc/rPwXL/7CIuxQod83g2ukP6W9knsz/MUF+eYTiS4giIHpAwVuUd73+czjB2SGqCx6RGIMIw0BAABIWAEKe6eijwQGf5GsyoTalZVSi3awbD/YOiU27+omuaMv/r22/VXNFaIfE5qmAl2LGYT+h1hVwQ0DsUO2XuuLkygdd8lf7v2VOm9DZDUGRBWJ7maC6Ap71ntH8g3Y29n0zV0EkQyEKB4E/K5SmPD2euyOuGzYZy0oVoxOKXQgHAW1tlr2vhGmZnE+oRRb7y7MfUzfC23gwts6LroyOnczVrHB4u+YKACWfurlqFWms4dLDgIgI9ESoH1foW6tHXp4mlLVgORzwcHzEw8MRT28fcVgOVtuYFKsCrVaPwPcgi3nGPM/gMg01q804Mk2m+AixZwT42iBziFSH727izh9Vg/2ep3QWM1kt9MgijzWwrqsFd6hm3UTy2tx9IYaiZvO04YpuwIngiVBwdODRGvfyTNrw9LGGAR4bJj2q/72eshkndVVo0cEZgLynqsO9D0tYA1pR+w4Ks4LJIDQYWPqOuMWCu9NMunHAs0Qo1onTPTOwOnJHGk0GY7Tv1IQiV4fGdm3e3i7qJE/udDtgOSx4eHzAw8Mj5nnF+Xy2us7ThOVwMKdhNdjJ9XJJJ5qI4Hw543I+d6cwje96Y+WHDOhWHCKTwTZphMNSgF7TkVGfBpDve7Nt7QLeqy2PDUV76OLuFkGjCLdOZDfepQiMTt+i2d6CObxJe0b+vW5vaOHVS+Tzgk6CKGFNJ5d5Yw9ZBm/L80YZOyA6A9GpSk2jsw32YKkII5V/ZXfWHg6L0ZvDkllQmYXEAdPOm/spYFYNQpYbsZ/NKCUyZnN5WYFWk053qFl7t3D6nt2BHk5VGifG97cqkieM48zp6DfZhr2WuAUIlPynsDqhouLG3Qasmigiou5MdNj4RBfRyH7TYd/3OR6d5sBgSKQb68nvxz6Xy7Kkk7+UKWnq6EgQz4A3iNMJXMSuJ8+sJe3O8ywH0nk6gzBPM7h4xq5ng6sILgBao3Qa9D66/hJKU0y1I40FEsY0TxaA4TVJw+kfddUFXioFirWuuNQV63pBW80QCqI04FkgifN0kcxGC4d/9K2Xp+j646iRjPoWxd4dd6LT/z6n4wQh5QLQa66Y8Y4Dr/CPMZzKoQPC+WNOMMo8WwBdyETucwtHugw699VTm4KmbqBG8mPavJMPU1/Drh8DnqEemZb5z+cdjB5AFjw1ghl2e8D/MkWpvXj2lo+Ta5XmlBTLRD/kC1gQsypwVvCRkHVFQiZWW6dfnk+YfD8z9WxWkzU03ykCw5KnZZmxUaoY38CaOKQ9AIebHeYtrgieofugK2DUdzb2hkM88f6q6qt4e+y6l0g54y7P/Y6Wt3DHJHzNMhH0gO6wP8WDoqfzcBejX6zdjNodK8Xm3AMeyzQlr5qWA+rlNIgShIYzCMsgNIz2gkGvcFneAiC5G9+dpsjH5kMTSFrkfbTb2Iq+AHrMdRRPoNAffK+op+NToDVQn4OQdUPyTXuQCYD9OPqUdT3pej18zZH+Z7V7j5vU7EhFbexCBhnHrDu8rUyjioKKjQtzySSYUqZ+vRhyU2Sgw2mIDvQqAoFDBw15CXB000GfU+3INUmZm9ER9T1spdIkUciqVA/wtUAvIgvEKC4HhfMWMJkngneKL0jljkRBRP18srJRCrZyA8ywXcD9/lkXHl4H3ngGK0GIUP+x4m17h8/tF5xldaSpCl3PWM8rnqWhtOYoZHAUL+P50hQXqVhbRVUL2lmHjCEi24c8FUePoVyfooKXXy7gN4z6qWEixgpzbKYMGGs0vsNkKNPL4aWpkEhHN1fXQFYd5R5F3fmNa+SDcLjOzI6YJnk8ZGTj+bZepNpebc3KrkgEifnDO6W/vRcaAHrW/Nzd5nd2ig9gBFTHugztZWu7GWSVoBXDcQz6zVbK+JZ26612cwZgz7xGq8e3PC90E7uVU4NBr+r3cgooCiVDbgN6IH3oJ/mmhAwEBwB2WPEWEO61mlyc8oshItHkpV5pziBR0/PaRuaTCNAf9RrqMuVWKPyvar+xD11kSvGJiNDqupnvUTfp9jOb00trkJPZE2LcXk5nEBMWVRyWGScvh5Nz6PJboQJBG2Dbh67txzVk8RuvcStZVl0uv3Vv7/yP9l/YfjjQ/3Jt3CKDIPMNxOVJORkwQ/GktMk+3zwlFIS02XRh91EJn8mc4ntl5r2f8ykNruRZ49u9TDDBs/lBVkDwKZ3sHwn4Sd9C8CmvB8z5axnTt9/77Y3XUWwd6r1n30mSXZn23HGIEh61Kx80waSedKL/BMFHg3dvg0ArDZWAEsIbE0gNotAC5hVPAJor6QRYDZRSEvopotTMkSQQbRYZJdVqtLqBvqrPnQsmY2ZxCEufCfgp5uebBuS+yLSZ41Cadmfsj18bel95MnVl6mvnAr3+OWAObUWPJh6vDULXEFB/5jzfR7HHNS8E/I+ff8LzP38doJatR2fSrIEuMAc5YA7skTmOzx+fcSLFgyuZvzfTfN8OSps9G9FyQN+L0d8nIQiZknj5Z8XhP2asf69Y8dHheO0eRbH5LkDWPz8MGu/qHxcNN+fYQtLeUokQqA8/L5A2oX7yTEc3FJXZjBRh7A3hZXo/o30UtE09M8+cI4IW004YAcXOXjbYDVBuEFnruqk5qsO9Nm0viO+Oj6/5x8o0f7Rge2t1fs/VsQuCPu/u5IpRE8FlXfP35XAAM2G9rK7wK5bCXaVThSpjefJafp9WO5YlFX1giT3aFx06cTAgxzxGpHcIw+GwHUfAdP6g0Twodm4UGIVv5vClbRlLKFPoynj8jT5UaWYsuTF+ANBcTQ1HSauWThVKDk+eDeDKs2WnAJhNTe1O/rE/0T0CFYLU7pALZ3kqgPFLbG6/TymTwVoT4XI6W5QvupIrIsBBIbXisCxYlhmH5QFvnp7w+Phk0O1vDhkEsNa1O258zqJ2L0/FjCrz1GGWyZRELgUCgrSKMhWzZcgoGfT3Yjc4TdMEbQ3qdbUN+nxwjLuTJjI9kmM27Q4KjWhkV0xtgD1Awa4PCEDyQLdQkKS6U8fXF4t41oKt9TA1dLoTxjiFEEFq7X11424492M952qTCJ8blUVbY+akD0cARTxerpNw8PXMc9u/YQKR1h0Q9jy2DJCLV8UdlXo35hN8b6qPCzncLUX2vo+jEWR7H9/fUS+QtaRBltnWQJmmzB4GVnNcEgG1oswzSCRr+BIb71gOC44PRxxfjjifTlgd7jkgUFNK2skxCgwGak0UijE7T/N/2Aot+YbDlOjm6P7g7iIMazLm0z4zjaf2Lzqcs7HkIBR+DLVvKU+79fh0IgIWIWg3z8DepDc6ksExcHLol6+dMBabwTXq2k+Y5tmDnAK5gVNMiDrZhRkTl4TBXmuFrnA52J8TtBmEqMEdGcjzNGNeFkfFOGBaevYzgQx93I271n1bxxb8MhieYr3EllLLPDf0h4q2rqiihpYRDg0deKVEaQixIKhAk/Jx482kUN9Tpgp0yFfnT/G9OHpV1lLFqN+x14BHZq+KBL+Nk7yPHOea037MG+3BG9u1Y8Z3M+7bFNsaS7rotDGCoSJgih2yNcawLxjbkZ1XhXPagofEET0s+Kl6QEXNJcdgiMMhZ4iZlxOJ9Vlr3ZTXEFH3ABstYJcVzWlvmanTZEgphazePHsty+ClCjM4qxgKwXQ8YH15dpQBy4hTBdbLOQNBA0pfA2ZzqJEeGywCR80xrBv+TITcU9paGtWThAzzi+YZjRo0D79RtBwJVBeKQ86CNK+XG45cWyPxbuwlfGiKoNieLR19y3s2yzA35zk8IXxYeLCM66Czxq9iLRnhKhODpgnr+WxjKL5/CyEj8hAykfEuShQVgGbno6tnyJFn8LusGNC9vW58b3G+udGtXoScbW3TgaEkoMXd6+eGcjB0I0UEVwou5/NGn/aCbZDWQG3UtY03R2DIKB11xyWSdsU8iArQgHqy66ZjQD+zZ2Q30OZ+6ncc9Ajtv3eoeIVe/PjIi+7pUb+z3dNmdHOGppwecrPlkFdMWPo1J1hAA4BGjsgEo1cmq2+fZ/LT1H1CJwI9AlB2GUxBxWhru5z9pIL20uLipNvyYrS5PJXMLo8goNg/zVGUfKJs/INne5wmg1w/8nUTQbAJMRv6yDl3cp/ZYXZcDokQ9C6W2LoL8UByVLdOc9fczCZDWzHr1pyNYtS/wpneyOwbU6DfqSX8VPbnmzhh9ZBZ8QCH1fcBU0jyddUGEivTCCB1keDLUfc9eGUXEO2H/p+Pn9cZ52JOX6jLSL7fmrgM1Hrw1WjXVcCDIY3OXlx+al4THf6MCEKdptmy5d2zayVnmpeY2e3YkP20z3hR9zOrYn7/Bvj1k48xpf5LarxWQahoWPQBos9YVbG8eYuXf55wrh+w1oq1XYx31opzXVGlojQv4TXo/I0IRW2+AsPlTNZJ8sEgIhzKjHmeHFZ/QgYeycFkIzTUDxWqAvbynZ2/j/tpgtQLCGo8Xz0xA4qyTFjX6gFwmkEK6jraJKZvzfOc9gZNmcfmQ0VxqQ2FjJfN0+yrQrqu5mvE9FLCulZMHjTe1OROUHeYN5HNhrsVGBmrsUEdT8PXMWJnw6kf8lxDbfJxcrSNHXdwmaTLm+Es953gf7tNAOh7749q0Z9j0OjBVnsixaMnNoy23As5osLoeEU/lkFrw/uMYxP3F7fP3+J5TQVtkP1irRq6UWD2W0lJK9GyJaAzDEmhMLusDBRuYA5kPu3lr/QGAoDL4IP21On85oVCgPhtnPvbpvL6yfm+uv2t85erMwEoTucLpsnGhpk8wSJqmLusn6YfTZ3zvFYUJhtvf66cLzgeDpgnxuq2y6lMqNSgzYKcA8addr3qdj/v2X7fDfKT8cgY55RMgZAh4Az0xlq7O2/f2Dbr4kf75vbDgf4XamNE83afbZf1G6Wb2eXPJHjU7ji45zy/1ejO51styHBknsfnsXm5JnyiDtc+RtfdylYP53ja7O5s5z2heKu3N/6tY8ncNxweaTzuRMv/SmQvm+OGmVDSgFWgYFOqmcyYDFd2SNCopKAcRi+Q1SacQCmIK8GNYBPm8hOUPnu9X82M8+qGulo9u82ZHmk4CCOCvzO6+PYmaS71991NMu0+3VoDG4OMD88+Ez2HlbYras9Y9o12X/L7V5Zw/BzuBIU5vx92OmCMRcDZy+76/f0eFfjPX37FcejfsCryH2DC1okUJ1KHBOrtoIQz22/7DPHfw6xGx/V+ZMfvQl15Pe3owRe2/prj+wvwjzeo9Dmd+uTXHYfZU9wOOrgQcFD7exkGyz7envsXUvAvH8AAlp/eoRTG9A6Qj4TmKvn5lxXlLaF+anj422EjYAgJQEeonhO+yi3N1mNWXurZRwAAIABJREFUNyawK8LdcU7E6RwjoGeDYrfGv7ttFYPvbd8SKPVXa3th1gyMDpm6mrHnYTKqrsBQP+j6XbMmnM+TIJx+oVj5HA4lK0bh0U7tEfoEh7wDEMblcYuOTqdR2faD7hS4sdfcgL3/pfAI+b55s/C/9NOVQJH9447TfR3hBoVWAYmp66NTT1cCqkIXQeGpv0/QenR5e5png/gmytqrfb5CSem9nd2xRbCab3Wo922GJjvZMgEMUnRaFrx9/wbv3r3HAx7MWfVg/VqbwRUnvWaCweOaM60UyxYuxAajzeY4necFzITzxWrfWX8Fapah5Gu5DkpJoVYdfSCcvJnZAXcGhtFRu9EwIBTToOlOgayLBfJocjd5hQGJKftiU6vdmAzPytBwDSkYPVo/lNuoyzpKIQkLNxgggG6oDp9orN34TH4f2yYdIiz+R04rFZ6JDuAKN1XHPSqpwFndeMnfDd1BN2s7QmNynwxOzaRx4WBLJVnNAeAGp6yH7f+V8B670229XNCK1yAmwjRN7lRr6XiKYIrZ4a0tM+NG21l3afebAtYf2SI1fLNdwWnYGKxi+2gY7P35Y/N9vH32jvp4P69g3sic55blv29uPBjua4bC8VzKrTLeM0XKcOJhkCu1X2vz36HaA950mi0jPJATags642MV9TyLwaDGnG4ynYPAZfZmN0RSyOsDxPk0TVjmA6a5OJ/pA5jGO0d36iWSNB3rnphvgTYOGWqQ7dXrjYsF7vjeoAHaFgjHsLp0r34zdSNl70+wvHSMeCQZAZY5NTjSc2x9z4komLqOYLzWYEyt9Me1nLGno1kTeeSVvko2PDP2N/XgCABO13uWdinc4eVnqy0c+7izHzNaww2TUa80oPUjkKlWC1a4OIJIk5Z9YRh8bsDoqhuOzYluyC7EDKodbt+Wjzk4iO0ehcj7b0FcUbe9OOR8BOQp1Mt0WCpfa2bwr1AoMda6ol5qQpxG4LN9adZHf+erzN+RvgYtjr1Ju8nJeYkMLyAzkrOKyxho2NdA3GpwkW2Vpqt2n9jZqw1zSgCEwGWoM89Wq9eWf6Cn2JpLOHcvCaRel6vX2Y0e6+ZTf4egB15WzblhuKYEuntFC5YjBH1T420bighgArgaEh0FFG4w2hyS2+NC8ZxB+Aw3LpFlCRIUOIs70a9p7cZYH/ekQfeXFhzXzh8CDJNeepQRhUyEQHny85Yho15aynk5DuoOBOzWTvzsTjZffj7i7W7d7Nfa1dDePOl77moTFlQyHTeDTNud68Px/SN2BvGuCxMMCv3Qj3gpIVUYkosjnhhCiZfgof6mTVcUKIiWzj9Cd/GHEghlmgf5u/dLXgDFOUWZDX+7JV/4YmFE+bv+JsgxcvSERKna3quPKlJ+DLmzO/p0fFzKWnfJS3RR8S9xogPjyniNugHCnYaq2po3O4I5aNgTbzY7hHK3p9x3FWiIgcbbRDvseSDKTL6/yFFvgCYVrUoGhEWG6nhPi/MzWaa6DBDExRz0ViJpmWfMywFTMTQx8czzulYQWfkNQwca+yu2bqTLDAft8tf081vgwxdMbPbN6Au7fRRCUP0C0idAP+L84RdAjlaCKcufVEf2scQhK7HiPMEeZOhnRJYFKqYLZLifCZ/gyctBzbMjexZIA8gda/qg0E+CRgJ9AHDSRCK5uSDI97Xzk9wbClAL55utfHK5cVBzvNwWZx+Lwz4WNv5Yvfa8wkrBTPPUkwKkZyG3ZoHZpZSk+fFvb4H4moriq3WzJ+nGfcb7Da919Ztuztnu99DDuy44Hsd30vbX2pbKjDzlknFyIS8Njw3ZK+T9vFoHp7M7Nje/b5+cunzIcMPvybu1oQ7oWgB6QGzoy77Xxv1dJivjYoGeBIE52ktZwewlAlKQGAWKYVlr6AffPbD/Be16fLuVb1iLarrkNHV8WNMTFLXpUO6p36i5o0fQZScCuc5EmFrFYZ7R5GylIVQxccHaasrbhcaAwzvt3kDfWu9j0IV2Poz9HvnD9sqP9r3thwP9L9S2pG4kv9s2Os9DEXhUwjMpvtDr8O+hIOXeC6ZOnQB9oh118f9/JuCt9ozz0Xk+1ngGAMZbKD6lczvkZiNW19DXPymyznRUHh8J0duB6Fkf7fd3+vvox/WlXUmNuu0FXUCKGlFMlotfCCBmrDDY9C+w4HaDzVaE0RRMeEuEKgwpE4CGNqT1Pv3H/7KIM1K0XxZc5O+ozTKqamtYHa4wYGHVsxLIjW8SA+PKywcytAAhr381jOdeQHp9NL5hDAfF/tb1fxZ5j2jCJ19TChv3MSv9SbFZSxGcAf87Qr0DW2HxOLzSyKQffK9FtjehO7T3O4cJeEA3lD/8QRrhvbsQHO0h5f6uBo/PDyf56FQ/0afhPjQc70aUB1De/xjwP7Cs81t9uSdkx/2eSW2cf/3oitcTKp5xIsXic8efLEpc1SDuLp8vUFot2h4KVbLQS+4KMA/vD4Qi5UoPmQOttubHQry/7vD3ypXfv973T/hzJdm4+5Vd5TuX5f6yPV2JzLkqAlbBl8+fsVWlTKjlUjyzGVBSXJ7PpswUg74knaFsdQdF165o3Xi+HXBDukNmE5NDPffa6/1KV3AHmh9Kbdy5y6qx/7f7XP03Zs6Kl+HUyWzhdFTCa7067aluqA3D942RVBU0UBqQIwMpS8WTQiuBJofu8pszM04fXvDw/tFs1kQonsUwlzI4ik0JZwLAxQwopdcmbmtFvVzc8GNdk2exOmnPxtz5jTkYjssBx+MRj48PeHx8wuFghkBpgiaWZT9miJtTryQ8LrPVOn94OEIJVvP6cADcObo6BLc5UpwfE6Ohv7u05sdtv9dWzfntTtW0fKujXDCHvdxKDlDkodk8jopvD77TpCWA1TazoDlKuhPw62ZfUYAD3jDcXB4c4e/TFdlwSNuA93XpMJBeBziUb23hUOwICrF6KNbJsC/DP2NOKQKhZznZuwmwMQAORgCYI7GpM1xIfz//G0FKiRbiKe/hJI33jcAAZkImR4RDSpo5XSTqlXkQ4dpwmS7QE/D88oIvz8/5UvPphFKsVITB2BUwYBk3zeDsMtqgb+/eck49U3Mw8uYliiHQaneL14TQlLmHoJugK1EH70ou2PEBsvncZJlvHu/7nvaXdf4XcuDA7eLG+TYJT0dD1hARWtVNbeF0mvr1Yz1Pe+XgxNbXqGEddMiywmfM05wGf9UKYUkHtlG6ZnCc7BDpzSG7pTvp+nA49x0W/Wi0CqdsKZTOXcDBDv1mhpBhdDaymPuY5IjZGMZe1/5vtG0QCDIE54RswERgMCYmNGUwC4hK3yOgvJG4oT3Gl4LG+0OiFp/4O5ijRtDUUTdU+9+gY2TBKJooDMA0EepaUYX8PaRPX6wk2q6P28d268/HLevMe4CcBIJWc2hz9PPCYVDmKYW5yJxXsSCA1Y3sAeUezw4Hd5PqQVnw4wDPBUSKwgoic5xfPAmUCls9XCJQYUxe+7xwBHiVfIfcQ2rGzyYtVK/sDzvP4TJhrc9Je+bjAVIb6upoLO4BC72OSs/cz6Aq7XwATlOljrlgXqrGs9uIyTK3VVB4hqpgPa+5zdNRlCmRmafqpcDV/M9+7DWZdC/bGw8bDrhi2qrzDkQZJjhdKCDVlAFT/Jopnd0iMeJD+QIfFx8Sh9qVjgrADOJi45QOL0VWNalbCVKd1gCAVgCYgDnonysiM4CLoGuJ5hwxfgHbTzfGSnFdDkvOnrN78HW/cN7jynFICrAFuhmNcFlhcNSYXUcG0kCDE11RlFPaBaEHrpDPw6H3MB7dxDKqJGZZY0o1US04UPbOABZAL6O00K6dL9G/gbbsqcat779VK+r6QdzFPgU08QEEwpTyiJw8UOHk85436u+y4XPQ7jyjAwQX01leLFiqHY1HWqmgao4u32dEBKFL8ugZi/OTEwqORoOd54YsGugwRITL5ZJ6VkyPOt2IgPJ9oICELq89sJ5AiKJPWeEmuJwTjXv2nWgcPNwe1uXT3Qy8Nkfere1vu73AascCTe+3rouxjfeITPSmX1A2N3d+53yquO1n9V+NvzYIGKTkaJGGHMmO9Eca6FXDPKAjT43yZuqUQ/Cf6VHmAA9o8/VSHQHHslM3TtTQJZDhegiWT0yYphmHecHhcMTheMCyLJiKZUZrE7//ilKKB4JdEAvNdCrP5FTgECGz5Gvv44uhtxxmKJmDONEf1eqVR7kJhiQ9Dwj72ixbvq61BylGgpL3X0rBA08W9KbkRi+BEHBoEahsDkaZJxxKIN8wJoahBjwdIetq6/6JcPn0GUWfgLVgaidMBKwKjBS8h4UoQAWKhoB4P71Y6YTM+PaM+SC1a6DIgUEiiXoUoQnsCsKyzOYgz+AIzzSvFgApKmnL1yY4LBNaE0cD6/KCojsYN6uZ+rodm6DrCWWkC/c2D1siWWsrkhHCAtFBUc6G8g56tdtp8+2P2M+vtXgiM+EI4AWKIwgndlRRIkuC8mSoF7hMFbKza+8FAoBNd43AIR30rfGJHtzbOSMGfVtRa0MtVuf8sl4S0Y4LGwJgcWSaKNvqcsrk9qXCjDJNAYqFabqAeAKjXc3vKP9FX5C6ml7NwZVMHzqh9nf5Whv59z0eMIzWzfP62N25g09sBhgyodZmyFOtobZA7jM6IbtLobFnjc5LzBfZs7+cVzyI4vF4wKcvLzkugS5iesOE82Ubnp/cL2VVu3+3Q8baUde5t+cHT2hi9iou2wD+fevc9kf7V7QfDvS/UOubTXfHd7BKX2lPLtwxgI/7LPRXtJGHVyDfAcIb/Z5eAB94m2muAGa8w4qPYLxFxScwDLZ9JNwTyCL4h+7uiXBAto8KWDzra7XRafhLN3+xDOToc1NXEMgNWgRUfADRhJneQ/lXkx2YkuBtRooMNQBBIImgpXhNIT8+lczSqqhQfQuRfw4RmC4kqxv2XDgeK+18oi3EfXMBaG+0fW1UXhu6Hnk7aL9+3zD4dAfTv4aEMyWapj2Xtn+b2j5oACbaoiB8jdmcyLKq47wMVPCLzw7FHvcYs+BfG0fd/f2W9qD0Vbj3gFpvu4dH1ju5cHynOtM3NRMbt3uxi8fX7VuMHycCjqr2F8+WwQ7LZJ997y3v3wMA6ifLwoXOAF3MuC/qdYhcu06hj9IIMhp4iYDqtY/vCe2vCSlfb7eNyd/Svmao+Cu3/bo3odB0yzUNvkNWAhEmh6A1gVUsz5XMiMgGomYKJNcbPqb+xKvR9rklVRwPBzR3rMrWMrm5XjfHrYXjJ6AxS2GYacyMlZFxV8jUzlZrGpH2gxMZkUT2vqW40K4jbY0ujJK0vadoh6IPp3uYqSwzE6n+Nmk4vn3o55IZcKi4cuzZeWUqkNPF3tVruxK7kb4NCt8XRXlDkC+mZMhz3JdAF856xewQgOzQ3aE4WpmEMJ4zpmkGwZFX2OCcn56eICrpvF8OC5ZlAQhY1+48KvOMutY+Vc57qUqOW0DhEcgd1R31IIxVafylUaHNdL1ULokofMW9RETApntmDog2MG1xrYZ2pt4Hw2nu+/zKcW5z3wM5+jok4Oq6jMDOuI+tsVOHPmU2u+7O8z5GVzPDrh/FZocMhnlTaSn3sw9FX77ZRyRsejheOWCzi68PwbYuszuhmhvSaq3A6YK1NLw8P+Pl+TkzhKeA+neI56lMTlck5aegF11WGcdh2K+Evm/8heKcuGbfXuVzfp8wVu8v2NDMe/cA+n7bPX90mmzEzuG8bbZ6f/jGwB6GGw8sScQWIjCrBzoMzvXBcTp2qS9RTaNFz6gwZ+QU2cjTlOd2iPz+XVUgMBpRm5X/kHBse2aTZfpFKQUrldTrEtJAVJHnFDe8ArGnY69Y+QxzAEjKTEFDY6UQKchpd0CBQgOqMca0Oyty5EsBqxrdFQukFRnoZfTHHesRapzOc/ieVBgUKpFlcxGBIVDmNNiJakLEa3j4Y7Vpn7tt5nMYsmHBIur9HoO23QhkS+C2rCOiIOrZNOFckdZQ1TJmDZLf/rLzAS1T9qdwScM/FBkIVWs1g75nqY0Q8K0wuDJabShT7bVX54DqsPxTV+ZS1gBZPdFCgwOdCcwe9BaoRmTGaxJ2OEjLHFJRCCnqukKqWE1if9/5eMTlfM4gL56KlfSAz0/A75qAAuWRhquzjy7HxlqK1UhBr8KY5+tVCJ4B6zIMnPcRkjfu6YWgDc7z39N0+L8fUeMFtj7Q45lcLpIW8g0AMih9O116vzX4jGsitH1ersvYKxoZ2uFK2NJ5G9ytLGVNoCuBZhq3L8YxH9/uNbG9z1S/PvbWGExGkcWAzQVdBIQ524jZUXUUcjKaGWgTvFD03tbKRYGl6z0uivR+xzvo+NBd0A9pr6fuNK7fwG+6+Dr0e6rXYP2j2u/Rxqz194lWiMDHZSNbGc0e1knqjCP/BAgzFIMM6q5Uk4VWMA420CcFHuI2vs6qQE62nm18l1RlSN0B+WLZw/wAELuOMATwCBnKh/hmbc8NoPNGttvTZd9W1otYc5sz+uKj/H9/9+1a6WMzeAeGcewy1mgV+i3tz85EjzwWgcBSYB7NhkI3DOQD+Q2epmq81TLErd6xIUcapHtjAUeyhYa8DABq6kbI/hjGkSnLyhRH6eridyCxWCCZBYmGg9Lvi5C/8psHf5oOWKaCxZ3nDw9HHA5HLIfF5CKyQOSyGvIPc0G5EE6JtGLv3sQsSaLARFE+CwDb/SdiyMSGHBWJ76NikDL4c9rWVBUqDRcxub+Xq9R0OoV8moFtxGCXr4v0YgyiVmIApWApJm9SscDaCYqqj1jbiqaCdbWa4XQ4onpwkdFQtrKYCCIce2AB6dl4GHMG6W5sY/vtsltI6n2E9sCxKPkTOlWgjbLLBTG7NRHIbIeJ3N7v+MadF5Q/eGTY+b7WupzX5WN7bNCCnV61G42NnuXXjf3549r1HUPknUC4UE+6OpPZfQHgIIYgarS5j6m9hwWbR7C73TPWNIfohr4Dgzc67o3z/yaCtVWc6wXT2dDSyuSyYimpg5nIb4GfrVGWIAJR2lBUkUhJNrbXSIg5NykM3LeD/ns0X7UhJ1OX8tRtZkRkyTzEHV0L8ASKgXZqzNHuCap4WStKYbx5POLzy8n2LbGbCKiXI/qNbVydo/yVtigIVC3J8vfZp3+0P6r9cKD/RVpXCq2xE8z3Svj1rnsKm60+bro9xDsNDAtAr2kTAvmosA+K5JusMWzfx3rl+7rj/VmA4lNmcCtMSP1MwE+qOOAn/JN+xTtnMOHQK8OTJ1iUMA/HRoF/gjnex2eH8BLQ8l8jMa/9vtFjaSv39YwTRcUHUzT8pEe1qDZVg/8gZbxRGNx0RKIFY/WbMt6bbcuz6vAzgVYG/s9bSLvgXP8Bbc3rH4XjfIBn8ncfnefv/CVIt/CtPcd4fP/75PiWIHMv4zwM6LhxzWuNdp9p/+Mdzk7oDt3YIS9kmeOPasfEBZ8vLuS88ePxnL3NYvx7QM9kHtegwjKxga58hZP6ODjUr5jw8HkPp/61VtT2Yr0xsIRt1vnoMO9/7dgIz/4tbX9eQrSjZ53T8NuiUX/K2l7XvtdO1O8xtpVsftePH3H86Scs7w2+7vzxAuAA0GpOQTck57xCB6MF9f8TobrBEtjSz7G/39/0zud926+2f9cW4xdrbDw6fPcMibaDNC8gNK3ujDFlWJrAMNqsPiSrKcpNF4SxqsOYAiDLXlUoDtO8gbcKfhbBT6Gwmg0hiPkgSNNWXSSKGnZOox0mLZzYAb+eKaT+DJ6KQ/u6k8dHJbLhyAVuDqhy74ZlSmtmiUurIJjh25xahEgfYLbsrMicNt5hDvTinVev91S8pMG1NqwJ6TwfD2iXmg4lDgWEuqEHUMgXGSiJ34MNQrt9aVgfV7ycXjB9niCtYTkc7MrWLFtwXR2+0qNtPUuMC2MqBfOyOGSuiaXzsmBeFoh6Nh+HXEQdRs2VJmlm/lKH0jWIZem/pUNOu9LeTNkKA9ioWHloea9XG0bqQdknP0+H8TJI+23Mfc8Ewcb4rAB0lzEQzkCiKDtg/7PX7RxqrL97g0Ff1yyMK30TqBteb/Hr0Z9MiMy4AbmBAKKQ2rpgFJH4gOZ+ioyYzLvwPUCFHemAzDjv4wB/z8g4bbVhXVes6wWn0wW8Wpbhy/MzTqeTyWHS0risPtdczCEHNdpzOp1wWS+A2pqV9BIGQkSsiwiIcIfLji6AedwAfSb1eho2p4WRZWdQyrMGMfsWhx6d53teunWC7565eT7l4yK7PO451tOOABjm0p+nDEWvcdj7cu08NyNor0FNMIOqBdjYfSevZz9Nk+8Bq39emLw6QN+/BKDC96n3v/A0OOStBES8w97YbvvJaTqbY5YnzmzWMDKbQYkdCpXArTsBzIHdJ7b5XAnb+inuxBZfS0ZDFdXHg6wjIFiAELgAxeojC7aw9Ar4/ua+bijVBwDo6xdIqEdxFJQwqpGqZTBpDxoCYE53AMfjhPVsdOByqZCENxSHgfd+xCxGH4d1ZHOuN/+25vCSLeApm2fVmYM70CFaa5hKgU4zuDSUNlnAW62ZCdLEap235k7r2tK4rNqLVxl4hdGPJoKJG6RYLpWNm2UQmxPC9y2Z07yUgimCesizHWNO1MP7xA1l1DKYo6mV8LIgZzHf/OUyiAWEeek1lkGEaZ4ymygMneS45hkcFwEPZM8NuP9eGsTmo0wWDJfIER5MSuL7oRkcN5FBjkYmNtDtAEmaMos6iDE2c71pCuwWwsBPbsu5OU8KUFNIW42k+oXimXtJ0yJwwfuhjjwR85lrrgokotxCapGtc5lg+qmuQd/Hd+iagzXjb7oW8EKQi2dLzoZsJGsMjAXcjHLBzUYuXSj7ffwNgp/s9TJC50krAYdYhyZD6Nn7c3Qsv5Pt43DGq38WKGgdMv8Xhl6GfhJAhzjfMuMBoBw5n2ej4+sLHZnERk59bfm5ZM7zfJcb8sV4gAYRYrNUbuiLhP1q+vY2XksAFguRSVhkeekOMMBF7eFdVzgf2/WAMUP91+R3wxwA5gzXRw+4VE75EC7LWkb1BaQLytMEwoT6pdo8v6jVUyd3mHhdXHJbETGhfm5QOm/ejzY78ADgnHwMqlA6g54P2wHy93aJd5DudLO0t2+HzHrPdec/BArCOPZjH8e/uPM9j/uF++SA+1d8XzvRZwBO/ug5s3DHFlREwZZBzgpj+31vmi7hvKE1aCtQMqd6caIb+yLOFw/AG8umGOKMycdwtKhEvBFBjQC0WtOeQbmZIkhVk46AHGmHKEuSHA4LjsdjZqBP05wB4RZY5q5cl58MKr4jn6gomgpYgcoGacxkutzj//zZnHifn0FccGli2dhqeywRAslklkIW8BV2zVhz4doTxye18beAdSbbv8yMovbbsQiKClZVMCkqCCiMx2my4HcCDmI16/GoYBRMOqGyYm0rRCoEwEVeIFCcRTwr24P8yWkEAcACXV9AahDygKKIyXRTIAHo1qk+qFY+17abImFdICjMGRARttaXy4rJs5Ix3s/59/P5jMhGtrVoc11r3e6Z4LMhk8aK8ePV34OTw1qruTa3+0Kd5zIVRMkjAB1VYfRd7F/ev2/Dscd+0h+0vfvon4hwVE/aIeABjALgjXL6IQwxQdCgOPHtnGeb256d7l7UdKaW8b1HGX485t8aFLUZohLzCU1nHGB174miBJWXnIQFznGUpDNcdxAsoGrC5IHJxQJCpOsVmwCL6HfssNdkl1dG9GvtthT47eenmZxun7fvU3OZj7mY/D97CcF1RUFBbdus/Ai2FpVtH2+Mh6riXBsO1IN7SdDRPVSxzLMhm45O+eHTNgA2nmNrnZg2fbOrnI+7/chK2zG+5kT/3nH/79KukkB/Z/vhQP+LtJ3amu3XsbbkKy0yx9/qa9vqleenUeTW1da7z3du/IW8zvZwTOEOczEo9w/OjSs+4VfnJx/9OkV3ngeMe8EWbnvfG0HPuObdb0B3Jt/r8/VNO3d74wph1HFXIKM3Q6k1oddgicgFUwXhC6vDEdkvb0RRyet3BuR1GH1UwXiPlf8J/fvfUH4250oTgy2idwL9T8FU3+Es//CITzgTtft8pu4UjnHv40Ddbuvzs7ex9jPvDMuNY2OE8eYk7QLfNtL/65OwOeMbaZvi9p6J9QHYGmICjjAndBuu2SvVt/r0Wv2f8dnxdzx/f/97SuO3tJXMMf7GPfajIz0SKRXY1FgHdkLTH9yi7vmf0cZuX2DvePrwAY8//5yZiw0vcG3TgiiUXCLye8QMUTcnGNymuKHnfnv919tX2DO/lUH/NxJtQhE27SQNLFCDryoFmDwzUSKz1+c1Idvc6E8bxc8NhDCnsrZuwhnnbxRKu5EBu424o4pOKCMTEqq4rCsKG7xssgsVMCIzRN0wso9hdTg5d56HccAM3macQIPXpCv23IsbCbIOrPfHI80ZFjDChdMxLE3x8vkFD28esg579FHatSKlw1iaYRjdYTIY6g+HA7AA5w/n4a1c6HejfWsNL/94cUe/4nI5Y55nN4C78WXtyksJIz+Aw/GI5XjENBXM0wQuE0CWuRhySRhquRSgMCZVg+sejE/iGMrBnyLAbGwSBj3taAejcz3WFblVI3ldvnaf2RCX7Pc+9/lbOK5ytPZ8Z8c9RsXOoY4jIz6d9HDHClGO9S0aPwYIpaPTJt919wgoGTlU9K4fCaFhy899zQ4cUDdyZ/+URoaBE7I7PKPuvd2mWTbVsD8DJvJSV5xPF0zTyTMLrSyDZbBKGiDNceu1zx0KOebkcrkk3H0hAmvAWruj1uWW7gS8GtL+dlfDHTxnYMTDKPQ3J0cp2t2sL66r68ZZSSSJW7TqRse2Gehx/dZhHg7t4nChUXczDAvhIGdM6PDtPdtwNDSr70GVHrAShqVpmjKrPWBJS2bUmRPJHOtzriozIpozl0zgdePujr7pAAAgAElEQVQIAW6ozXs5xDa7oRkIOtznyAIConZ4GKcB9/wgsn5KiYDEviZsDPy+BGgL2qpZUkk8aKrTKw7lITOzCBNQCDKJGXH9dxoekP449DkzWmZOwpHOAYCAwSRAoJn4f6pIWM/NuvAFdXpek3Z1nUa6Ghj1zH3FxRrSXO8+xru9EvxPtRvwKjWUsuaaE68fr07HpRhkKbPVK20XL1vlPKL6GIfTIPZu6jkIg7uNgRmkG6RMKBLOafi6bOhlHeC0dKgpn0uaclxG2i4iAMOzDC3T8HK+oCxzZqEkJR32nA+O/fFgClaGlgGWP+g1GEICbZHdNVCR3O7UURSYc17jWZFZW6YJ9WKaT2Q5Bw9MPa5P6TCR+wObSX71hCv5Wa8/Gtn3wLLiR0JRjfciRmR17cuRjPTSIG276089i5Bif8cV65bzbno8vFPnb+xOijhuAxUJDsmroMO6GRrt/3bZM7LQLcN2CIZLwu+0brmhx1HIKdtgdh7vL1122XDnhXIcAEAvCj4gDepjk0uHmte8/yBbn4y388GCDNxN9+06brz/frx259wQnuz0IExffwyc09j7wLGafL0paHMbzg0x7EsowuEFt/xYaNfVwhzmkhJVyIg65f0t+P9g68m4hZNdTl4UfWeNZ6vJgqIWLLgLTB6m34fq0PnWcJIF5NhzM7hz7DuQtPcqj3wf7KGxlm0PqEZAxTYT/Voi+v5GfSv+y+qjA0OPxz1C5MHJ5EgwRgdUgMkDuFgMjaQ4dHtMUNcDNVGUuj2NPAO973t7bc9eVYU4ImWt1XQgdLS0HtQ4yIUELykJzPOMw+Fg/44HLIfFS2r5s0IXInIdzHQ1aVZ6RNQz0ZvzWtVhSBhTsX5M8wydJhAXNBJMsDrsmSiksS2eAPrY+6tI+SZIct/+UQbMg/NcniA1nMm5dYe/+PkyscNgW19PamXlmlogbQQYitegbl9e0NiSVbhQogT4G6JhRbhOol+z97uXQMBmT43LZ8s3rneFh+768uq62+1d0/mQpgy0fd699tpv4Ri6/9zhJiFzEIMGG/WoT3X5x2+KPp4Acr1h2AO/r2mO9Uh7CIpzBNSqgbPMSmjG3IY9aviH7LTO/Pm9T7272rdZ0CUgy8Cp8+jQW+EsIINR/X2b25dsf5sXpLXm8rLZxkakpdB1VRpULLmO2XSiKIHEoiCqycdSB4+X136v63n5921BN4y2DIiNN3QVADjOM851RZV71v7eqgi4VgsOitIMow6vwFTKN91rbHs5btwGYftK29Z33flH+zPbDwf6X6iZrvf9BIxgRuA3ep/vaKeWALqiJbA60Z8h+IwQninh0Mmv/by78fb33nj48qSwqB8MggQBb9EzoQnA4vXSBd0BeQN4xN+j0/qxbvroRN9Abd9pdOsb2XszXf8atWmsb0bImgiI/XluxA+h4UEtOqnC6ssKUeL0KCyCDPoeKxrQ3qDpBfx/CKuullnRBNIqyk8E/F0w60+o+ndXAt+jqOESvAvB6WqcuhAdTw34rv1709WRb2tbok+b41ec6rUb704ds8KvlGb//KQWHHHcXXtUygxzIAQZymCMFGwHRXN8VKyd/SNZrw04NFw/1jYfzzlfD/qrLeqqK7bO8LPXXG90LZgTbkVmh5C2f8tva9d06P49wvR887c0NH2bWaUL3Nu7n8kOnj6eUHjC9FSgz5TZVJLPcjVrdB4gDKEWuAKFKxrXAstdAZKuPtzpf6g09877Tvr+p0lL1/v2j7477Q+E0SCMSwDUYdpWncAgzMvsCivcMJOz63qA8y2HQJ3dybquNWvWAsDicFZJ2m++J20/jXRfbc1c2orudFdACIUMkj6yGZs2QAmz1zfcP6MUc4pnjXL0TUyefbXMy8boNC2WaRIR5YBloExjFrwb5Zg5HYkols0+lynrogZBC8dGKcUMCrAAhCEvAuzQ7nU1A+HlfMbD4YDTh5NnJ6jNSSoM5jQzKF2B/F/B+nPFsgRknmdFimUYR5arlgnMC+Z5zhrpFuHfeXFrDc0zLGptWB4f8MSMtVaUueByuqCuBluZGdcKC7IgsmwdVYhH9CvgRqTUYof6g77epEHJau4a0oB2WSJ5PMwIFNnTSePDcYTBINbNG30jdDmrH43s/nDqmjO5O0McbUHHqwEMRjProqZSPxrCyDOXci2FEXRATAkFf2NwiPWa2ZFdMd1ojZG5jVgbNha5ZtSGicuEeZoxOYy3D6sxMDfqRt10RUBVmhO9nE5mGCDeIlr4fKiaU66JZ2yiyygBPZmZ6qIgpxfClOszfCVXyHe+Jkf5dt9Std2RGvIxyTnbyRFd2IjBz9nof8kNqoOcMfK4TW32zWf7y8QeVBDwl8WMLWFwKVPCrG8yz2ESJBcb93QWbGilpsNcvEa1uGM0lP8wxJZiQUPFA2tGh63BFs6OTlA8o7cO8OP+bh5QVKZiZSfSiW73Tt4ShlF4MI7Xho5MyjDGj6JOOqVAoGLGXhEr/xHOuDSQqVqQTbxzi8JT7iAhm3t2xyyD0XzbBOoKtNeuBvqYa1SfZJ97KETZs4olkS5sTHxehgAHkPNO7+aYvZ/rK+bY1586RD+7rpJ9CnoTDr8r6bgHsPhyyN9FAlmiZiDYmLHXAwGq0ZVC0JO9swXd9YAIuM4VkItBnxX9PmlE9mAGRYWIZQ0SEWqNAA/vPfcQEFWgtubZZGxOTRW4qOHv6FnvNAQwqFhgV5Pkx+Fok9bSSWUPsfdKY6vTZg6Co3C4daAoA6gWyMb9WnaUCKuzGzR5n5VCXsbEmEbwj71e1vuFHMdbIiqN8zoa+q5PvdlU7t8XAKTGzTTrtwMeFIeB3OQ9fA2UkrK9Iaoao4kgk0QUAazuuUcZ0OZeoQtsLBXeKrQyaCavK+3zNANUg+aTy3HSLw/ZM7eJ04Wjl6xYFTopqBkR0uaS8dJRMQobPLKx0JAxfA+NNcsJ4IMHqpzDgd0dLwwyT8FFIZfmWZR2fTmYASPoAB9oQ+doCVnD7ifagDOBIyPe162uDJDsSiSNw7mbfL19WoLY7H7M4JDd70GbvrYOI0HD/k3gA3XZWgnTcWRpBDmtGN2+006DGKWmLgUZnbb+GAIFY7FeaucFygx5VOCly4LLo3VAnKfM72ZcPl7s5s8KPDrMvK9rg5lW6IuAcEFo4Lncgu9jDck+exu6suAMwgHTI6DPJyjMIGxhEMg1RwiapL30A2LP9PFIJzqG5U/2frF8Q0P/Vrqxb6MUC7XEgj+i6Y2/479+nqZeGYFOhRhSCKqUCRpN1WuoD2M0yAEKSRsEqV6NJW2eF7KVJi8XNeST5lmpKXW4890CQKjLjb62lIB5WrDMC5blgGWecx80aZDq/K2Fzm37fppmHI+KOnkWZ6toVKFqDrrmoDrEBCXG5eMXaGTCUtg/CdwYiuYD63wUX1I/mN/Ott59nYcHnaNcB3ugAFkAZiuExgwT1SwYTbXgAEIlwkKc0OdNnZ83//ehoT46OloTrJ8/Aw+LO/m7nEk+14U8qFMVomcwFkw4oByBy+niNuDIpidAmmXcq16t99osk5+ZLZBmZHBO86fCWB1Z7uCZtIE2dFktJ5xdjja6S2Y7hskx27jJLa0KGUx2fWuqmEBYfnqyfnz8jGd4whaunXfVS/OtVP2+Hqgobcdfd10ZVKXYY6mbA8D4+Xe2a5aiOAxHhIDD395h1s84f3Da53vnCLO9hvyvu3cqGztjl6Esw78Hnno0hO/HAVXQz1cVVG2GdCMCqP+lQD+cwFyHUlXGDMWRnVpt4AkAGz2ayoSJG5o73jdQ7mGTDTtO6AfYvsu/vn2dK4QMei8xTKGWHe604/TyAoLpf2sTD5bptBgglEJYdELTyzC/W4EzDjcRXKB4KAWHecKXl4tPbUnkRgraC2RZv9v97boNI+TL3KHD+1LK9n/2vNy7/2/l1/+/tx8O9L9ACyPf71mkkXEtuIZv/46e4JrVXMOh0/D3UW9dlbZQVPya2efk93ovBjH+kYCCtxB8ggIbx2eQc8F1JvreWT72pw6/EW5lomsncsPbvElm54Qv/vrnMFB2A7c6LLv1TRQuaLiRxaMzGzoDjbqmCrUa8Pp3kP6EC36xGjcQVIExThGQvAVjAv+Nsf7nBbP+5A4PTqFjdPbq0F97Z8L7wVjQ1bXtGOGV72OLFbrJYByJ/qDJ7uFiXons+Aq31u05fv971UbUH6XDgVSKaFirtOnupoVrYOxWrOevtf39DiBMYv4BAu7WMT8o4Uy6cZofnLueSRMa/qqv2tfB5Sr7PP731UG+agQMzPx+izOKUtaeWhQ4f9fT7vVhS1kqEYhXCCoYD2B6gOCcgSlpHMu1FoZnMVgd1Y2AdGtEeqDRb+31mDfw37vdX3V9UwZVRbMsMVnV6pUGRi4GGpx3HdanC8HzXEDNHK39LJvlXq8X3SCL7QwlDQ2juCsvVxnMEJwvF1c6KBX/EtBqbuQPBdBqg1NXWlywJ3fihjNntBCak6ol5F/2MTIC3cFjyrfxozLAP63rirauOB57JnrMw1QcHtcfZxmbozMUHi1t43hw57m9u2LbIyRdN+NOxeVC0JOiVqsXNWbcMrFnmc9gUELgRudarRA3iKMBrTXLuGy2fxWWPWFG89kyOC/n7gwmD54qxeazNaBYvVl2aOhGO97OZFC+IGS2d6y0jbasYfPxjNPBqONzrdursd0BtP3sfYiALXaHTWRCdk81e03kuFI9G10xOtjHFhnAoZiDixurKHT40ZKSvcuu9cndGJXjdO+W9WawcwQKAzkMcKzNGD/AjV+l9Ax0hBGnBxwk/LuaA6hVwbquYGbMavXNARj8vyKdsIG4EPXue5+QSnSOLdQyjGGO9KhbyZGNPvY97hVb9A5Vuw8W5eNCdD3e3nSckxuSSTp93RiYgs5wRZdd90+nNMKUcJ57/fF5WRxOvWyyxMexAwDiwYEefdbBoOu1Kltr1pnWjFp4KQQQ3IHKPr+dHobzl4kwFau/WcuEOlXUWqx8UZXNztoY2tSM0NC+d1IuVXWHq+0/1R6Y4UTcjCpD2Zso2+HSPlKA9v/b/veSSk0MjtzrkcZJZkzpsNoxd0UYYIPabDv5JvQSg2+3p49AgMYyzABPPJjN3aGaGfX7+XeBVxE0IVA4xrHMTQxGsYxg35fRr83iym3tCCAeeRLroaOrqGd7i9UGdz0oSkPEFBJZdrlSBB85/fUMP6KQ5gYEGqfl5HtXfK4TjUIBMuB1AASRvv9ifZMPhGWgVTeCe8BHn3HLNlFJ2FpzFCC3amYm63YKOCG6fbmF/hhjFmwix9deLIIwIwguaBE7nK8ZAAsAyXm/FyQYhlhCD/4eAx6g+Go2528J7O8Xf/tPqgCaQpWAeZirsSTJMJac1gFf1+TOeLETFeGQ3++0fT9SS+z9yCaAjlYIApFCJ4ACCixkNWrXjxg+U8iU5Kfmb5r9DRjlIPGJPLLZe4TuNN0alGlYCzSuqwNBLx54cCgbe0SIP4bGYrwy4LfjziINerFeypnyugAxfX2FdJp675d73187f0ObXmlhJ2JM4GO5oif7++y4L3j3fnHdXoeIcJwNnULMFiwwCQqIuux3gWIBiCHPjkr4ZHeZ38xotUJfYLXRudt9COY8B5mj/85ycxWqyxzq7+LYUnbsBWm8H21we0f5Lcf55oFq72c83eVUhQci3evhv1nzCUjHBxNEndeZVnOblgbNLgxWgrQe8BB72M6z/0WyRg8OkqQbCk1eJxIyyi6FYdB5E23HZet5njAvM+bZZXCvl1xrRV0dnUVMRilssvrEjOl4RGsT1nVFXQkVnoSubch+N303+lJFoM4DyfmaqVnOfwLT3fnR+ddfkt8lj1KXHdkCFqiQl3/yfx40yayozMAELG8Z02eCFkYjK8Eg0lBbs6AlaWh6gXxW4LgApJjfPuK8roZmphawGFNC1LPLc5r0gulooTUa490qDI3LdinlXrteRreWSdgqQgZnZkyTrzntdH6c60TgwrXs/60t+hOX118/Y3r/ZmNP/5Z7bG1sw2/adfTdD3b8+7r7m1tycA090/moKgq/RdFPQ9Aqpf8BUJxpt1fxGu/RXAHhPA/9B0SeWOD2A7cnGKKR6+zwwFurW5doC0DsA3LdxssZcU1ZmH3fsqMZxvFcczQEEGaQSu/zv2vrYnaEslmiyzJPqZONLWUrtWDFic3J/rUmagFsxzJjmQou1QtPENJ2sdfN79sFet9feyuLb3DZVMQSYP7AIJMf7be1Hw70v0DbyJ83GOTr1zqjdSPIJ9rWKY3PWwVy66y+biOD6LXOo7Y4ADyTZQF/8b/7e30mc64rmRP7kzOfdwow3oJA+A8FVnzsNoTh+aNis+/rrazz6GuH6Nq/ibWxbnu0J6e8cR0TWdDAYJBkWLTrezV10eqbE1gULZUPE/gOzeCbMBpymcDKmPEzBIKT/hMNgk/6dzTTXC3o0gXld2KRgM3rtDII+Bs7LAtBf/kZVmvsQ777piopUQ8KAN10OP8ZKs2fR87p6tvDYH/q6/1655iDwtcSvd7HkX0qrFbOg3Zlh3a/A1bPPM45Dc7uEymepF/xGmveQ6+Px8e66kDfEwyA8YRKX66uC8GtC6zfJxqpC2hfm9ELwerC0S4TgManfsOz83zdHsBWADHfmu2z6algfVnANMBx7q5aa3UFY3//fj/sr331tb/yLl8fsuvn/Ze2WwPwx91lP1oJDaYR1UueCdjM0EIL6ExWlzE3DCV9Xhar23dZL8MzrOY4gTBPJRWXcFxHxmnW/SJKhT3uUNPw3u+5RdKIlcwgd0hbZpuiEIGoJIwWiZjyEl0ndhhYeyZzwEohLTFxdwKhNcuEkqYokxv53LCSdhaGO/D9yuYOg1C2BTi9vODh4TGhXK2udPOMeBvQukamjSuUL8hMQW2C88cL+NbSCEZDPs7RDyjapwZ6aw6LMIDEOOlhAYFwfHgwIy2Zw3+9rK5Q+niIOc1rW/3Wiond0Vcss/1ysTUQhim4Ey0itAkWdMOeBSjEKGySQxhkAobLDBBeucwdR/vFG5kg4egVle7Q2FE61VFhxbAxQqbojh/uHukO2S8KsGXZppNPFCpmkiHtBrlUpseVqgPHMsEynxnPv/GKeWzDNgj5znFt1G6PDHUaztPUzpFO1+jd5A5cnizzGQCouYOCtQcIUnfyNalotaCWilImYDIZLZAdzCkFkAqowQJAMuLA3rkQ5XFVhTJ69jAz2GuLCew4uBtWwngFIq/XPs7n0AbZQsfF4P3If31BjZeO23v7gGRuw0LaCb93necBGUuEeZ4z63xZZstCOlg2UjjVEeMEpAM6HkhUto40N+5KOM0J0MjY9XeItWg+PAtUYAjaIBdFVkUpbDXRMWFumnDdba2oXC3byh2YCqsbSK1BtKBJQRHLqqfCm7UeC0lFoI5qQbBsm4DhDsmAKQKe+jBHTWyiLp9HsEBtDbWuqHU1B7obhS0QwQKWIuAj5imCZLrDu0uttlsoaYqIl73wc42tbGUjsrQsrwtKqfAZfSggGRB4AnVhmEaCBWCFDOfufsviFkkdc78cg19avNjgFIbxuHku/izpmd++HmyJ9UUs7pzWlbyOoc8IuQGRaXAeM6C9X/FurVm2tvhvRAxtRkdaQMc7xGvwRKN3npnimXWFwuAPwNdaGvSbeLCFZXwzFZsbleTlhUsauEQC8cgck+opxdoMYUR1qxVEIASR8WhdgTIR0Jplsxd3ovn1iMCJMK6H/OJ0SzxT1YLtpDvjR+c5RqP3tTZ+T+TV/QfdfR7ve4vRbF7c1mF0TSHA6hnkrBZ8MdmJFCgZKSvZmDPZOihFgQK01Zzn8bwegNMZH2H7t4cIhtXBnSgUPJudbzdzqiBkSsPP0wy/3j3Ad5aslmpP02Ry1UpdRlCzemQ2mHeTuQd+YtiNKXH4fgdgGePU65wHq2qX1cYJE7AY2oc5Te2c+tI2ulFbPLDxEiPh75R6mnhvwglv7uD9eOLqu+/Zb1A39urcNsjslXN3p42/NVQw2AMExpPtLDn1cTIHyppjeOsZ90Rj9nDy1EVKl8GJyJCknhT0fLTxf34B0xH8aDRbaqBLeDAfBlnf+Us8i3BtI4sVGOLKFn/IHZH+fXk/4/ThvJEwTDUZZi0cdBw0188JOO54bmzgsAeQITFu5Zp7o/l6i+l36gugI17qXvB55a5ff9L9Zs/38ixgEEnShI5INcpjxrfYy3FljfFBZwIsAUGgPSgLKUoYbxE4tLOdoK4TtIRrs7JEo75l49VlWCuPYvDOkwewRk1taZJ6WK0VUKDwhHmyNVjmGYd5huiMUgouEbRVXVwuLje6LMMKcLPgNQtus7GJgDvShNOCKmUm7bk1nKSaniUREAcv1+MBkkwoE3twujsWWSGNrSQKAe0FmCaGTqZrSzWEtLU1oClEKqqak5KeX4DWgMMC/fJi+9HlshDqW5Tnga29SgRSRT2tUFpS3lef37mKh1NYMET1/dN5pn2KspxREOIw9aBidvSULleRcxf1kgDqQZs94PA6EU/Hxw3NFtmEvn9jXwkUZwCnD598lff7bHkPckz6n+vddYtOpnrm/24haI79/K279jU2QwAmF63Xj18wvyO8+d8/ozXB8y+fU5mKMXeTyUYHymDU3fOyVFxmnfv+KDAULA/+iFIegWwk0kwmVME8zVgCzchtBIFAwJ6YIGroV2217PTi+jYPMnMg0aRy6B3uAVFB303n+AbW/N3ta/eMvfH1Z4e9xu/bhae8WlUNRQKKtRKgFcsyWZAEEUJzKGz6ZhPB8/niCQyevX6vI67znNeK2hrePT6C6OLzTa43MA7TjNWDrOM66ymhU+ftAG1XkksOYQ/zwyIC4rLxnf8Z87Vvv28X/vXamAT6e9oPB/of0MaN/9qExGY3Ba4rdAHh820EZHOzvEIQjuFtNtmesPfLr5+0PxZm4chAHzPRn7T/vWKOfqAAKPoOlT7mb0UNrp3xHg0frjZkKBzR8wnvIcN5Vzo6dkI/nKmRRdoyDAbtSR3EirzPyQzDaBTs4zpiUEEQctgkr6EMcCpDoV5eIHhsiiompIU1IBQ/EkajC1Z8wCeHPRxrRYYhw6IfTZDJGr9/K7j830sqClsVyJznG5tqCKdDFmMPHNDh/7+tjes8xyC1qtfPv33D147r7vfe/3vrO/eS/zCOT/y2d5bH6SOzUGwDE/TGNQeHjVf0rHFBh3X/8hru6412GKwLo/N87BvDlBTB3nn+57HTu7A5av1puyCA37/K+ttsnsyEej6jPD36Pp8gqMBgvBJtBknmCorc6cefIRCMws2Pdt36nG4HiemYBghdAZ1sLkmH7N5hcLso2h108UMYyBWeyezBTKOo3flw5xlbSfHGRNKO+ihB1GHFiTEvBlsXkOIG5wqDmB6+98eMorRmJHLRkhmO0+GGmOb9Nfg9xirr8GZxDuF0esHD8QEAHNpKPGDLxmWignAShPKmGuNH4Ee2TJdxzDbP0FQiAZiT5BHmzFBK6FaFAsyoa0Mpzftj2RDhuGsqWC+XdLSEcwoxJoXT8DMts8PUuROsGpRgGBcLGDRN5nggRvXABom6ogQktLd98bcLg0NE9FO+Y0bR5/KwZ2eW6aDs0LDQwiE1wivbmLuEleuOHJKP+jgPzySXF7ZEizb9tPrJlHCa8Z655mOd71oeuXLEjsq3B1mQKYkEzzQFQXnkUNSVdgzvD2QtODMqFncieo1iol5vWKK2uTmmWm1oU0sIRS4F08TmRPXOihjiQMJVuoGMS8Eyz+6cJa+BLAb3Hk5aN4iRO+wgrY+rzyEUg9Bwm8CnUhsffLo2SD3jybtjN8WnuGfUe0TMkRskMQT+KLJuogW32D6eZ8s4mqfZPi8LFv87TdOmBvoYOGRBN4pAAxj7FHSzb37q/7wzIYMRbM0U6tnSYfSLTIsyDbD+k5hRluy53CjrjI7ongoFqkBLDjwKAPbAk4RNLSavX+rF1pgHzwi6UzkcZOwZzzFFHJI25UNR19UNzhfU1ddQNWclvOY2D740LgwWRqBTJU/SLsXapZLoDgKHbiV16HbO/RafmSnXxR6mn0VQSoGQO+AC9tf3V9/rjmhCwz4N8uP0A7qV4cOpjBiX/VpwUqDSx2xcoxlAtmvq8Knqy4lYQMoWlOGfgeYQ6tE3zWy8WK8ljPnO94uarpdzGiVQojxA0NlAKPCgEBq0hA3S1sAHCciyB1H7tcxTOtwjSEM1+mh0WqQZIooOwRRGXHP8zGHFYBWoB52U+f+x92ZbbuTIlug2AO5khJRznboPff//1+5afXJWKIKkA7D7YAMMTjJCysyqrO4jr1IG6fQBg8Fg47YFVRHOJKNP9zOlp4QU5mpo0xzGXidxkpvcxH/FgG5LyUmdPvGYJLEYpXH1cfdMHvuU7WkMJS1Dg61yTT6McY98WNaGzJcEng8+TJDgafs8RsfeT/FRoaUMIJmoB5FHZ0lr9IRunp3fNGiwi68WCZqxCwI29sx7e0LXIBbjleMVZjcKMjHP/RtyxPjjQTY0KKOrtcEaR5sEDrHxPBdaTW6xQzEyuE29jNR3a6eMMo6QIw9ZaBKgwvh5p8L5VxQt+yVmn482kRjMg73MgiTkHgKjyt89adCYH3I7y+g4I6w6IqSHoYuYPGxBqvmRUJ+HjppB6LV5NjoYyI8J/NyBR5O9bAwG/iKFER/HFDIy/UpYkUhWb1X0L8uyJzbMjl1fEGYkzgHHv/t1bQQ5r5JJh/sEI/bNWb4/9TC9UF411lxsoo8cEcaSIA3kht9z9eTopNR9PqcMTronIdrz2GXuKEvG9eljHPZRQcXquv9Z+xNyRqj9vUerkn9yJwsaCpnDLSEvBWUpWErxMhm1VpVHKs7qPOfeRTYneIa3OZvY7NYqmxMYTcQpRXFWH08AACAASURBVDeS4Kai760sjn5w8vEuZIKFoPd07th6x1arwKnXKrDUaruhRCKjanC8OCQlkKwbcidLIofRlgQikMuoMXCss6QeVUi7QTI//fkFnRKIxZpEWitdVESeEDmcLIhGEJVzO7H5EjMKCX8zaP9ZhprJmAG0LsGFddu0TIOUsEoqTLauOtLVU+a9/O1DqK5CnEA0nZV/1uY/c3za/UILrrMCY+EZf/2UZ9zkPcbraeIDyoz13Rrc9ESgY8K6FrQkwRdPkDlbR/20N/sYQ/Ui+xD/ASN1Rk5dZezkch7lpEhajK2JQ7yzlr5aFiy9Abx637gz6lZdXqecYKXUhi4zgk6ueC0Zf7g/vlHO+aSD2XbyT5r7GbXtnuy0u8f+Mzaj8NeCtqEig5baBaHkJIkyBj6GYW/753/9gP/9409Ycsal1k9qu6hUHYd1xel0huwNAKkQtqSMc4+2sxt9CTrY3EMWXSjs2A+d8ZKU93aAs8mlnzZDb+2z9+z7X477xxcH+p88JuNCkM5mRhWUCAKow43YIEZzfWEoQoBka/+mgkA8HPYVg6c/BzRRgDxrbNRa0787QTgR8EKiDAOjtvkTWeb49aL6iifV0p/nS50BKw0KMD6ER3Stfl7xmyi0kzA7MxkGUEOGerr6fShgHxPwntkVGhChEYXKTwB3EXZdqEJCghiSRMhhfLRofo6sa4z1RYEXf06Ef37/A04//+JteiEx1JAyZ/cnEnD44QfUHyue8d/4nbxFmpFx3XfCNyjfSWPbzx21dVR9ZgIh/UCqEP4DAOPlJ6mPLrIej3lAA4PwkUY/fPyi4yOcu9GYN5kr3f1y/bhbP8a9UMhitMwUbAA+L1GEtCXCAF70w2OgUbtoxO/On3n3197GGNnn2P1+q5vxu0V8P6dPi+iLcO2mFu/XV2xD4rnNG8X3kPOTzxOq46GZPm8cK9s6VT5IkpV+DXD31tu0v05nk5oiApDW5ZRsUsLL8xkFGQbFBBXdWu/guikc51ttuE3vf/j4D5dB7jdvr8596jHfZ9+WN957/f2IzMmNv0yMvjFQ1MFSMmqt2Laq7xkZvgZBZ0YTgy3svXnduNoM2l35iFtM4N/v1RGeSMMdreS2vs7i8E157MupmPNHHpC0Hre8ksZ7WbLnje/mJE5iJEJ/2aQ/3sb90A+nf8rC4CKPt2AECyLJZUFOIvL13gWyGQBXGS8SPVaUjo8N+SGjvzDSKyVhrO68QIYRcNTaxwqbPmWzktRXz6ng+HDE+3fv8c3XX6Osq7SjDRhoq58MFhiu8+mEtklmQlkKyrLgfLngvJ0VPnmDIQ0cDwdwKWKghDjT6GITqU7zbnXizJHEiI5yVqfMoADlPZ1AJYOrOLbQ1FBWBk2bkZsAh10bGY9COx3smaoEUZyT8mxRpjW72jPk1XFsZBtplcWoZmsgdRZnY9e+QwMZEuaaqohO/661eE2hGzWQbQyIBhSuZSKRyhWsfQPlSZawvdkz1VOGZWNKFonQY24NqSZF4WnYtgqu3SFlW25aFkci9Y/LgnU9oNYNZdvc6WvGzV6bGBFJjG/v37/Hw+MjEklJg5eXZ5xOJ5xOZ4WQl8h0g3A3CHwf45Rc6BjhrnDZxcZBhSV3dMegnFabOPxhYxcWtBuM3ATglKdecaQsfUkOgy4Zpq01ycpWWrYa57kIjF9KJNkMB6l5uR4OAt++aGVXFodha03uTcMB55nWW0Nr7P00B67Ns5UNkIzpUddc/mh2+VKwWM1Nsvd2r7ue84JSFriRszFATfl3hQe8hJINUFp0HumQoIBlf+VlAZFkNp9ezqj92Z3XtpasDZbhYXInd6u5PTJQiEe991qr1wQVPmvCbENr4sjbUB0W3oy4TbO7zelptNsZ4KZ6jdFFUreVButYPXeD4c85Y8lZ5wTCT9RgyNyxXSqa1tJ2erJ+6xiZgZYAhYy1fmj2uqE1mEFoZ/ghaA0/SLAFmAXdJCyjFOhKnH7sxv3Bb3Q9WWaZMFH/oatzwhzlwkZZn08AC7x9Nr6XpP1ScxKArglSHYz1+QUAp4S0SImTet4AYpSU1WGhPN3aYAbZRFqOQmEzc8LheMS6LFIypDd3BmzbhlolW6gWIHECtQTqrLVgx1h5sJbOCzdh/K01cXIovaScATTJbGYS3m4QudBMVRL+LrTN5ru4KZ4zoEET17/Fi4bUN2uQ/eZ97H0aegzPv3VCWghcjYsGTBdz4FqvWNApiGx/NfmCXBbMNPYkhvSXJmCSsefD1ozpMAA8744ZUk8mSZpcIc2zVkfyKi1r5xmDJh3E0N3PCsd6EGigdhb5tW86P9xk3wnjySr3xv3XaLyZo9p5L7ydQ94AaB37MwAULIh2qFobsKlMTND9ROoT+9hoeywLWuYkw0Zgnt1rHfrW4S0wXmpPsE3UyWIE+Jh8Nv47XkomA+/e4raiuMWi4d33X8OCEbbzReGmCf1ZnlyOK/gEMYLrmAkA9Dx+jO2qtrGkVSz+NgYhPQhfEsAb1qzU7iTNANJjAuEB6Iz2UdEz9LwMDYMeDKUlg4lwOZ9REqF7fqiMoWlHQvQY9B9O2/jnnIEHcTY28SQqvScktaXZvZ3C+mBoNrFOGUGwvOPE2Dc2x+WYCtujbHoE0SMEZO3uj0+1Od2zLyvxwC6XDi5C+lInJxfO9ZuLbUqNuh58X9I1MPYnHnsKEqgYYgkBjVHVWdtrQy0NuWjWtb5HguwANEbpVkJKbLBnC2ZuTXmABja6XCb6UFkWlNqwLIsPrMkvXZ1rPQGZRPdc1wXr8YBlXTyo8nK5oPezlPxqli0pwZZrWXBYD4JapCV+bAxzzuBlUQdPB6roJUkDnNdFAjKJCNQaiLvYuHnot+1yQe0Nl/MZ57qh1YpLazhfLqiXMy5NkANzziI3HlYJTGf2QLnaGkBNAqw08O2ottvDt19h++UDtia29qp8PuUMoo4zE6DyjNh+BXGDEyH1hAVil2+1onWhB0ewU3pbmZGOB5zPG4gPSMRaC1zkuMaM3DuIGQvERmauOZ4IGgAJzZy6yLtLzqBmpYYAC27qXWii9oYR7ogReOwyLfw997dyWXcRpn0J2gcBOOtOveqKvfgvt5+6P7vnzXu5gTHQnzDxU0uc8BHXtX/7vbOuav0eaz9rgOkxyNlP3PH+++8AAKsicCWF8v7mf/0TOWWsP/4M3jp+TlUCUPtAIrA3jmCwUX7IdF5BAJEASnIbVEfnjJIEMSurPlVSBi1A2y64nM+ie/WOUjLWtGDJGXVZcTlfcLmcUVtF3Tp6W9CXLrIu4Os4ZXI9MPcuZQvAbuMhAihlZFhSBWPPgmfp7vr8/pAtZy/d3X/OrRNDLrh1YXCQ2y880zvpZmM8iE1HIHLdtiri1VIIh7zg6bcPOKhO3MGorfs9AEagXGwRCwLEMa94//iAn3//gEwZ3JvuByJ3m47tsg4N/xzrXqS7L4ZdMXQIsr4/EmkAsdJw60BO8j5FIvwUZJ8vxzj+bCb6Fwf6X3WEVX13MiKT33GYW3f8nu5H7+51hnvf31pPV/dhOM+f0nz/e56/77dR75Je1Aho+ODQ79/0EQVu19/aivfM145bMOQfvGbsaDcgc+C2BDfyxPabc52mjZu9j3OUqDgXurrPgcrA//fjf+M9j36ssJrnu0FlwvZjxZl/xq8acvWqY5OAzr9h++U7LN8XpO+A+mNDwy9I+Fbqvjnd7DfzW8dbaq31/Q4xmjDylhP9xu+fknm+b138ftWUnZY+rpNPRwbOFJS14ACPz7/1bMLINt9fe6fprqjve84QCHfC7XHZH7bSH8KGam3q4bO9M9t523z9FX9sI7jdqPvtXvl2n//oceve+HyzoQ5lVh0IvaL0FazxshJV2GZjwR84bnPeT7vzyzHT7+3f5xHOyO54NHrvtIEb0FPGAqmdXbXO7KgR5lYJDAcWJLJehWQTXCfjqRk8vKFDqL3boR1BiRFs7Pme5a7PZb3RhWiiEeC1e1ZTh/G2iQMYDKwPixg6njesj8swwtwY2aUsuGx1xwdE2b7UinVZ0DRb1wz+Vhs95SwZd4AbmRlAe+mfQM0Cz5ySGPmYR+6HQFBCp0SNL0Wc58xiiFmPRxzWVWF+K/r5IjWQm8H4AZeXEz4+PUkEdxOFMq+LZMy3AcNsGRcA1DGkkec+D0FRZwhkL8RsbHOZHG5/9E9+CsEPNsd2UdazPCA3yeoi0nBmxZkjzRaFfgbYaxWSOQL6sPqnlBxNxozpgr6BgUpDNJyJ6tyBOovM2cTcwJ2GKMqKQKzjNMG9Ebw25sgsVoMHmwyqDiqxGIQxGHMRswChdMFdFEByg72iHjCDqSj1Dscd2IwT7JDfJWc0NSR1hfyHzoNlFiNnpJyxLAuOhwNyzmghK7RquZ1EErTRUnInoSEDWR8kq0XGcTgCeCABEQUn5l7QJeUxg/ewjbPRhfMjGu/V22N5a3HoZXslzKDbzBGcQ535JHSWS56yzC3bWIZL900GiDu4j8C5pmUfaquaCaNmO07BKQyvn9usfqV3ffB0CzvgQFeD3gnmV59oxQzwvoqTyqKMWzs8k6I2cUc3ZtYaKJE4MqvArhscPBGAZBldLQQGjCCaptDsNKZczjMLD+nda8DbHBmyFbNCsBtparYzq77oCB36zxzp7BG8su7YnEjKT7Ia1EsWxJOsDvQUNrHcxVmcCw8Hapf+giVL2wImvLyBts95YKRDCiUjQCHYQA4zRs+w5KzXJjfsURqBRQO9Y5p12TPIAo3UaR6yzi2znHUupJm6/nBLflOZ0RAQ3CDmQoGsLeVhPQ8esxQZY6kwom0ie6YGNNCoPbmWBcuyovUmAVdE4MrqkOnaN6UFDTyRNiRfz7csYRRkHVY0Adusxbgv2gFbUHiPQWBwJzPMYbVbP7bKwiz42AxPbdRnhuxz/+CrT/v3dmZQGXsEFYDrLHLF1d4ukr1Fi+xHBotsTTX5bsgiLMZlzSQcfSXMBvmQbex66W6MqvUZ4uDC4HHK0Kc+o0DxgGcH4WiF/iPFwDPeWQEUfXoiRZ8B2LLWV7ItWp5wEZrkg2afRVlX+0oJ6E35S+WpDUTiGB98lsDoIC1rY0Dirm+GvePeYTvMfi0O2SnM+Y27bwnd+ySK2L/5HfvfZaqzZvxxZxwfDqibotwcAZxlHtIDg0/jIUTr9YP3b1R702zID2gwsHWt0Mw65hYQ4WxIn5oeKDyHBPZX329lfoxnyYUyMcRGtYNv0/R8k3UvoONRkVnY14xuWqOvOzmEdpeoQB2/xEGZ7rUzFIcRGPXRo8h0h672cnS/cZ0HH71md6HdX8Tn0vy78hQLvJAyHPoejd1PCeBEoC6gzLYP9j7qlI+mGj2MLd62lIhU1Nn6wp4lb7aPEfymPMvk78DTPOOdZO+QMj2Lt90CAC2wC4AimkFkCS33k1Keyh/ZswVRKINTA6nu5IF7MhEAS5ZmU197zgmUpDZ6r83fb+VwemvYMOTupNnvFsygUeIKHMMeYCzjSRrAxfrOjgZGZUXYYMYZ7E4PKQUoSFeWbFFVVu1EIt8FnVGJSwKW9Ws/bSg6ecua0M5QPa2jEwJK6CgOsj9EjuF5XQ2OOyONdsawhHP471972DMLRjDSZ7/nleV362F89WXsEXdfQTfWEgIPCDImAo97YXOEz+9IKYFyUpm64N0PBb0xzj8yPrJYGbFzos+IADNvE1maQL3PMPXMiljBWlrO9oqkQZ3DGSr8PyF3sfvX2uQ6NkQp+9fBjkxke76hvQnawMyvCYlEbxTedjUL/9qDd6N/S366c0xX7UiEGRoYNx7rwfy76wiKdNg6iqKYLTkjUcKmgemvHa0zLtuGx4cjvnn3iA/PJ8B1P2vnLonO5PA7h5XEevVgBieLCL32cXw5/j3HFwf6330wS3YJoErU6+vLeNz+9ys5kKc/rjzzbsOwd72/uWDlOstKNwjwm7DtEFny8b/+gY8//ghgOM0BqR1+8+n6oA96zh3grpoOITz25+m18cEs8Nt5+ydRwDOstz3vtZzbx86+qb3Xh7tzU5WZDiCxKZqEh+9/AAM4/7xhC1v2pATu3jPaTqg/V1T8goom9XTwK4BvBTEgTLoHC0BGLfvn2+/4q46//rk3nrhT5KLvYn+cVdpjEkQA1kjpB/3daCLOc6STew7xW/0kAC+vZGe+NjYHJq97bp8Nrt26x5id54DW7ME7sEK3v769f87xaTO5d5w7fSk5numPbeaJ5pH3+aCYzRfbqtG5raHgAFGsZNRIjVVzfafrlcAAtn/VwvgPOT6/e3+OYxxeuXOeWZ1tBggH3wxkBjsan1X/JjBX4AKv1QvAobNrkyxzc3rZPBs9GfzlpxwcP0QeM2wS88YbHDumxGyXTZ0xZjizzXrwMAZjWSVT5fxyxla3Yeg2OFkaGR7rY8h+McdTbIO2aV0KGiR7QSoND6Xhsm1yT094eBfEvrAh5ax13EForqQTyIzyd45pdIPx1owASa04x+MBZVlRL5umQhu09OIOrQtIIdk7tssZl/MFp/MZ5/NZHHm14uHdgxqlVXklU5ThtZyFTq6dlG6c6gYZp04dgmYZq7Nar4lOVDAUTrkPo1dxLdeVdQBag52CY2tgiRDECJryqEwZnRIiEhIEr1HnXQ1FlJN/tijkyHHFTpD92QyWur1QYx5r/WHycBPtvxrmQMERR+p8V4NBVNY6A2SGvREI4Ea+QBi39gMz3kUDqNgNkmZOi3HQsrZBJFk5GLWQJUtZ0AculwvO5zPM+GnZ2EnpwBxnSZ1dy1KwtlVgt3tHz0nqaE8oCGL8U8JxPjKMlfpoddROzhsb+0A7QhfZ++qyDMYlwzFPgf+wNQG9iwHQjKdNx4EBQOu/i9M0q7EyBHBY6QJ1MjcvQQR3xu2RY6wUxeAT5LTPPjRivBGD44AxNykeDK87nkAgLkAeARHGM0RWYzfuWi1AIkHYYH0/qbETbjw1/ipkmZrgLiXu4GQoGUbHcFQaCs5mCbiAwNf69LLvLYyubRyOdSst4TxC14fUeR/8aYIxB8PQJHxJOXHY1Eeni4yiwdx7MIT+S15PMU/w/oAYA0vOPp6ps0KZy4tTTmogJ0gpErFyE+t8eJqf9Csnc94oZLxneIw5k3+kmVKmd3b0nqYANVKj3i0nRwjtANQIjs7O641OzKAfnRMTOltwuLfagUIoZVznY2/zSbYtEdZ1RUlJnecFZdEgBR1vVnphiIOz14pcFuXtGZZlGGUTUx6FFoV3WQkvAgFJDKPC8wOv1SXXOqNrACEV4dWtVhjSgjnY3ZlOYZy60XxCJvKAvevBT3DT/aSkqvwytqnb8xah9aeLDKZ8vtnJqwbWUuOv0Y1g8pY4dxONtSLjJ0ZlHbKgKOrfonTdfGSv+2B7lnfVwuyt4+ZOBlAJXGJ/CKaR9bNkIqa1gBdItlB1aRFQbZ5MbgDpd8lm7eigCpRVkHSQAWpdrQCGuEVOG/k4BxFEtiL9YbSXEExBIR2BRrutl5Ez0vQd0/f96h3nXbLQfW70fFypspAM8/yrXW+yRegLQWnFt+C5Fe4nCbwlA8hpweV8QS5Z9n1rHw0Bn08jUJICxUoWulGxZZoPGhfJ9cZBA74dANpzR36XlQ7byBhmBp9EpkoP5qw0WQPOb6H0XnJGf+joJzWi67rLDuGLIfvadwYEAthDXHHRms/QeUgENLWC0A3nwXWlA32SBbhbJrjPhdGBviWIEzfH643DqHxvF/HW2PP9hz31IvCFzz9M7pZSVwRmzfyLrwvXytalAZvcBS6bCD3JmD1+/S1q6/jw+y8wGcZ4gpeaAlS+MhQzDgLkaFOK64Hg+3OHOKxBsXyVOImlobLZ27novImZ903rlztqjo4lJcLCUjaLMeg5f/0e9POvoFZxqR1oglTWUkbSrHMJgh6OwG7tTyQB0SEqxWS3DgumY5V9da8De9DB06+/obPYyyTj14JMOzbuSB0oveNZ5dYS3t9NbgFU3lR+LBxaHZxA7UpnTCgg1DOwcAd1SCY5JOt8uMIFma/r+T1hMUwelOx10jZV7qG2tfIThfhudcZYnKb0DTqOBLvfmUfZC989AYj9r4Nv2M12gsHVy2c+gN37bjbwJpN4RQCZLptlYbllvPOBgY8Ann/6FQWEr/7f/0eQXbOW4LFgyOV70AF4Kv8t8WytSUmk1t1xHpbCpE+xe1AN9Y5A1DX+YZQcyiQyWaIRwJlUpveo4t2aTFIzAQzh+TkJeqOsV7G5TP2f+LbKaTqxkUPupTY73sYiff3YP/P1WbzBn305RiQaHjI1DUoGRP8AOoiy6BBN9WHlZxYY03pHToSHQ/G+l5xQcsJxXfHrs5VI3dOvHJdWAYg8kXOG26mVdkvK2Pqt1M+d1MhangejfQCPZAlo8D3Gdw+I1aexbQZ/ZGP9H35cIWW8FcCgxxcH+t91BIV078y7e4v9HjbJW9e89Zx9E+y455TeX3evbYAYBo7ffQf6+RcUrXNuAna78Yz9qbj+bzXnHiPeH0+qYL3f82GWyEO7e5+BYNlUI2pI/vvAqspP8gG7sGoCS1RFCYzLzw0Vv2Bj4IPeb7XUvL975VCfUbmi4zd0ED5ABLt3LO6M7ZdqqifK9wEO6xXu+Tm0cev4ozAXr75TddehcMGFyXBJ2CjCdXee9wDg5MqE/JfmS66+3/p874wdL8S4EtI+8e5zmPToPAfmjfWWqpcg0YR2S3zWv/Iw57m97UJy7kKCvjAfn9um29ebwuCGJhWAzMmRGKg06sBbhP29OY5j++8Ztf9Zxz3efUsfkjk6IGklwu6VGM+Tu7azGABIjcVd4cGbQ7DF7B75KwrvJ25aty7j+TNj5jmqN09968yorSFxR+rZYWPdmcmWTSSZQJYV6RmWKjSfTi84Pr670SDlZnvmp44vIiATKTQ74axOc756ghwpJYlYBjwwIeWM3hrKY0Z7HvBxARTzxgAC9BAgHfW34+MDLucTAMLD4yOQEnptoGUJ3RUnFTdxBlvWxuVywvnlhLq1qSbe+eWM5XAEaGTZtVrBtQGlKIyhwh2agy1YJgxOcmTzx42C3HlBTJ6N0TUDmnWs4UpNGAlK07x4VpwKT6zOSpcbSKOkp3aNASQCmEgdXMkVKHOIsmZQ92rZtJr1Ah6wpmpE6GmUFIHV8YuOByIfM8umNOh9MwqYg0xSPIaUAzbFPzvUpAeQQNrTQZpp2b3mWO8Ck5YmBTGByqjlTCkjp4bUpUpfToJgkEuZoHt77w5lHg0YwiuGw1MyjgmUM7I6xpZlAfeO2hOoNYEqVUc9MxR6NcCTqkHb9iGHIg3eweh8Gs4kI4cYCMZjXbE5GsIqc/40rB/mLMtZMsqpd3BrUgpCfy9FIL3LsnhGsp3LKufCnNyW2cPm+OoCZ4kh8zvJqyFIqcpsQ+7s7o1D2YyxTowJNQJazhKAosRlRsLhNIfTR7eMdug4kxgiye5LYpz0jHFtUEcHNRbjk66TqzGdvitPUKl/1BwV6rWdyni8OHOhdTXhsNVG75Hnyj5hGwgPRWFHFy6jOnHI304WGKjrlJL/Eze9OlWMu1v2WeAXzg+zWO3tvUlpKFjIxa2nxiWDSzdkGHO4l1y0TECaeIOVARAjkNEQ63dG7+SbEAGTQyiOgo0XqwGpc3NntWXTuMG8BXhcwGuRszoF9EW6bg0ONysQNYOa6FXDIaNlH7LA1pacvNyBBCwkUJYyFIA5qwE+HtG2DaZT9tYHfHtrmuXWHSo30jyY0V0PkjrvI5DGyfPmYftJUgO7MZF95rmhAhCyOtN594wwA85uhm7MGvCmD5zu2sMgur1gun56gz6d/f5betTQCY0mhY5MGGsbkA6jj7jh8LM1uX+ykOEunSDwZb/O5IKpz33wnBpo90oPI6f1+fmxKTv5g5XHywqGZZq2zuA6eF2vHakMg/CQDYN8SGNO+CL96Tud9dUs3U856HrmhFtqe674WuguNKBqf3J6bgim2cnfcBlnvp+m/85z4NtSIlgMgSBiEPAA8At279G3R9kOgEIEhLZZbVpAnOny3YOEeNA6iNBfFK3qQXn3OWSBA2Am4NSRHkllxTT2al0PdFYZS59PykO6PUf3Q2mL8ikC0mPWOBDbyVmhhu02AqaVMfYUW09tbDUwlIfBNQJvsHkCfF+x83t9JAYs2Jrf85bXjv3zrg9bK3Mv50Vqe/idJ7E6xHUfnZwY9hjj2ebgVRkkty6lnnSNkgZP9A/dS0+Q7eWqK8pcK0pHb2CmgFhCgdnq+9MIMJ0Cuc0okjTVxtqnQbUOPW1lZVSma62LbhPSc8a2QApmk5BhCG4yJqfeQT/9CmwVtVVstWLbOlaSsk1k52qVbHSV0bYksnCy4pu6d3dSfs3iXPYMdAuHZDZUfDCApPWmwSPTvDKjqTO9BvSX3hkbQ1E+GBdICZBRl3tMf1LaIB7lNwetENBXMF2mQI/m9+qY3aDrQe8TqcGDJWYStLf95Udcl/b8juGjuL/G3l59n3vYHj2d4/hrOGya+OrC3TN54kMN8DViNgMwo/WGnAv6zx+QfvgKpRS8I8JHIrRGACq4seoA1+isk3TFEkCqtQY085yQksjEjVSHlh0fOROWJCXcOlu5Ig3GVb1L0Nqk46YLSmyMJWOy8qMhX4tsbeEcQUbQjYGjIf7GXOjl/6ZjcOf92XtH3IEi5TCggQo5yLb6WxjDX54+Yl0WHJaClBMulw05JS+jcO+lrTO2TVAeSxLkCpl3eVNOSQIoX2s4Bouee8tXlz6y2NxFdyYNFBYevy+/9Pau+eX4M8cXB/rfcdgi1pptE5kPWUgEgZ1QOiLDdpxAr+hWT0eZpsEzMTisrFk4lnoLpFDrcs1T2BAY97PPGWNzFcZOICrY8BUqfpucDAiL255h9dHfd8YTkcOwG8t/IsZ7lutmp5wTLgAAIABJREFUtf02M7UgAIrfSRzPoyGh9b65hLM+ZuP8MwnjIjA+6mfwiE8HJOrLzG0rf4NKv+HMP6MT8DuNaKIISXlLvQeA30Ag+u3qmo8EvOffYQoRgcA/fw3CNwB+v4oU27Pgv2oD/JznvMXEmeBGSwbciX7rTbT7EOkPECQ2k/4IUsMcII+QvteWGNEsr59VqP19J4pzeH24LeUNxc9qn0dVdVYqZ7pnAio/TUa/3Zul9X+xpLPyyM6/7BtI8Ph7Dv+917rp035Cw5EdDlf/kc6lOirBwAbGovzCEqZmyKm5LXuB/MDj2v+bstH/fFfeFpkLK8rkK1cmWZHoON18xgQBi+A8N6EyjRVR24jbNsdvtCXE79gpo2Paww2vLM1bfeGgoZkTw7NHyAwmauQgFh8vCKTZLl7DkBm8aU3f1kLjRoO2FzHGHx4X/8ki7Sk2aNqnaVqFh2XBViWfhJJmBWZg2y4oi9Qa3veTMDLRy2NBe27ht2t8jqGaiThje7wp/sfHR2QSx0MpBdR5ZF4zHMaWoQYbrXd+fpHa5l3P11bBXeqfb+ezM1hx3GhN7SxOHYMc7JqNZgqzzZE5FziO4UQvA3LYIQkV5o8qwEWYUiJyviR/JTvUjGNuAnatTXizKHSQupHBMC9NGZlG4qwSKLllWdw5TSBxVGo9XDFOVbS6eV+JEfxu4jQmAgyd26VKNRwkkvmx9qeUvW8SrKTBKzSyb8zRTpSRS0LJC/JS1PlkkqoaqZoYJVqv2C6bZGe2Du42RhnIrPXgMlKSsg6cCrI7bYG1LJqhHjNYwxowo6Z/V7pS9ILlsCLr2i1Za55xB7WMlBoaVaVhdog0oxsTTtw5aQZMDAOYjK3M6fgOobmUdvsyjb86T4jGGDeEsxtGDYbTsiSoNvSitMnds46LIjsYrKbUklxDljI5nUQmIFkREX1C/soKFaXdeJEFlHrmccionXqpY5UwspXZnhWGgsiMROywmu74SxRYjwS4uErjzN/0HACaeQ7Aof2NXpMyK6LkMsLIODInvekshFTE4cDcIfXIIf/ROjqSDTDTn4fKUGyf9jWxZKOEU2Gwpqk3oWZkGSuKgqFEJKU1bzu57sIkTm/q4vRN4FGuAnB4fzus1jugQU0GNw/LPs9ekzQn4UuW+dj7CF4BCCPmhJBInMcxYMjWrRkvhQ2OrBjpu9CiGJ+EQFLKHtgEABV1WKiJULRPrQuPSqR9Uf5WrNYlST3ZmqrQLRrESy8BKIdl9brmZbH6mAl5Uf6eF4jxTJBTWu/IpfhaYO4OizsFFzBrEFGbeUogbwu0M5qhJPuJwOcXKVuhmeJlKe6QdwtclAlsD9Matr029E6S2UsAutXltJmz5TOMrTK0kaeOPc3mzWhUeJ1kQ/b4UNg6GbIOASCWNZgWoYPe2Qo5qz4dV4hlGw45r7WOTuzBHNZAX9eA0oEiUTS2lhjJ3Dwos8Zf2P6s95ENsxF4sH5kklr1wECm6SwZ75nAhYFqMlSdZQfjtTQHg/be0S5jjcf29ipceVmK/9A1QK5XzZg0hB1t4pAP93tRcJHckpvvqQE7ehO7fXQpDX4WHzP0OXvl2PPiq3x0Q8CcP5DG+NlDHQ589zZibRVLcMvhsCIdEuplE2h78chJfXKnHisHse+yjaJgCso1i567YOoBm74AqVP6jhzRh46a6Z0y0hHgE2P5asXHD09YDyvoMUN8oUmdm4xazyrDyrvGGtFnYUHWdki+KwEP4nBpraG9nNFfoHvlEvTkOGYSRMQYco3syxgBCIEwhGeR9mXM6XCsz2Tk9p3pr40Zh+tCgOn06/URz3sAimyzLn+INBrlcXv1DYLfyUVwWVPlH3U4y5gMW9wYQRksLy9VG1oackgGAUz4+PF3CZAgCrZSw5gwfmMyldwzSpbA14u0YaDUUBroQ1MfjKOpnOMBra0Nnqptbq0jp6YOwzT2XR1T2c8zGIyKLggGgKLCdVx6w6FWcK3gS0XfGs5EoFSBXlEVXaq1hkbBBqcyGutnq9/XIDXExQnePSMezF4adOtiR0iT45FxgVzfVC+ver8Jc1u3jG+fPBALiiGr/gJA4L1ZYLmZBW2U0JEfjqIrPTHAKxZeQDjhAi0uqGO7EKERcNnR9dhjdA5UZl1ynuREk62NJyylgJlxUWQao8nr43p9xcPuueinFOyxgNm5x517kdZOmDywD0CZd+RPcMjvTt7mU6MFfPdBelXwTtp4Pmp5zwqgbQ2UAVoTWm84rgdcfvsdVBL4l49YtQTW2frdLd3DZGR5MulG6xZ7tj6LrtsJmmBBrtMZTzSNeeWCsma3J7Wm72jdkYQyJQjuO4sD3YJqfcOady5HTrC9lq6DmeRLEK58YP/6448+1acxtN8CnvYUZ7w6UdKa5huK8cSg77XekVRuO28V7x8fpBxiIhyWgpfL5bq9gwELDbWGouXRJPibBR0MhJwyzn3b3TeLTiY3uZwZrjE9yY4XguvOEmwVNtLdOphXyZfjU49PDSz94kD/G4+xCIICEv4OoeyN3SE+8+rEW/fJ7/eyz98z8FF1vne7VbhXLohlYxeDxAePar3XxvibvT9mjPPut1vPuHVc/0b4SAoPv+Mx7iyfDDvhvLbisY/2PKqQ4hll7Fukv+9Mv4gjBeL0dkeL9+u2SuC55HtGO7ZkPNEQ2K0uPYGuasS/pXR81vFHH3Ktfd5+biAKGdv7tz2GCYxQ9Qy44/qBVaUkAaEjGpGU97pyJqmhLs+alSHGyBR/y3n+WnftMNj2Yc6Gq8F2cDhnb3R/IgFbyDa6Pv7aLTMKvPGIzvRPfaN0YS++zTwwp2F0B4YSLM7zkBEKG6MHZLx4aYY4pvG5tw67bg0X/9/kTP9XHIXHGMcjCrIynGckPPh62u9oEjGrWRV4wQA8k+utphnvTak7YvsXyfl3D3MeARjKo7dFlGoz2IGkrx1jn+ncIaB3BssHdAV2IwANG47HB1yeK5aHEl4z8iMup4pyLEiZQqukIcY/16Xgos560xt6ZTHmWvM/ob8yZx0ZaQefSKCHMVeJCMfDCpDAV1EWfIGUCOfnZzw+vHNFgxLjUi8yt63j9PKC08dnbOcLuLPAFLM5jBl129BrEyWlqpNia1KDPCXt94Dul/rFWqNY64OJom3GRu1H0u80uBJcNrOR1TGIForJgWqK8LAssD2Tuxo8OMx1889WUxGsmUYGm6rOcqt3nEsRKL9E6C2hkjgBB4S6GF5GfWCGBwhIR5F3MlkieWfORR3oZdT01f4lhRqVZ5vzx7JcxDm7LAvWZcG6rljWgzqp5B1Sn1yc8LVWnNLJx8TpS99nQVNgDUIowMLSx0Q0HFjWNtI6xeuKVR1U4rDXLHIIfPjlcsGpnHA4HpBD1I8FLFjgKWjsNZ7F7+v7NpPxCP8gR8bz8Hl6RTGzZ6QAB69GD4LAOls/l8OKZSkaKFJRe0NuDczZHYTLsuKwrl6TPWuwADDZDoIBSKEx1fFn11gWs2X4WzkGv6ePDKvuEJ8cxgQgskAQraUZHK2+DtVZPmDAR8kBCa65oRjYVzdG8hgzt24jGLjkPIdsXd+LyJz74ZmMMWfGX1hhNG1tdbuHHWbcacnQHuTF2kcGcwZIQxI4TEjsE8GdPhwQmwEx3nEiNCZwlaCYnjTIJNBsbwENILzG/AeUNKgBmtElTdZ7Bsw80kz5wxgZ5bZZYxVemDSrhUA9XjeyfoROktrIOehJBseqhuosPHBdF6zL6jR42S7YtuqwsrlI1njirHseq3wo0JzrumApiyCt9I66bfJPy3cQMUoa6A2eSaaZ7qrkIqNoQDSrw8GCRxrqVsFtGPhbbb6uLBvdBtQdTupEt0zE/SH8o4/yA7ou457jQfLBoS6Ocx13gpYeMMIfsN1sM0cMmMNO10vn7nWbhwUz2O3s2dqvOZvO1ubQpyY6t61v0/W7kPj9qv1Gvo/ONKwOrMZIq6EwyBtiHXP74Fli7r0b7Z4ebF/hJBbIlkP/fNr0dpYSGrt+Clw8gDaCau5rSsPRbd+kzUPmG+0TNxtBypykotdWRY4AwGYRoMHjJte2LtRofx2tCDz8arjm/XOsYzkSXz+PlJ/FHthrDZp0TxtTIJl9v7G/7p2Et35PAPKDofnAs2XNME3QZJOHpDDu7Bl95hTx51oPKMxJlAk5jJ1dH5ysiaS8Ep+0DQ+jzBQR4d1X77F9uABHBkHaDIajV7TTxded73muVW9IWJEejromhfabOmAtQ02maDNuIvoMhbmeZmj0265PkGDKab7MiR6k5vgMD+wykZRtuIb8u9ce4bxkpg4Cbp7fH7d+J6IBBUyYeukBeH4bXdFhdLLCx31/KH9SHYQgcnLrXQLgIMhQ1BM4mx2IjcVIO6wesu4x9t5m9ZtJ1k5XOpSyLmUKhAUNNJK0T6+JgqCfUnmuyT5GkADawhl5Oeh+lUDEIpPr9xH5xoKW0TrQGs69gWtD7w3NA+ArqDdsTf6xZnoziYNR9kIJ+E1axqojBmuyZ63bXurhTN3K++jeqzJa5a7Q491h3qV0ipZGYcMaio5FKYXZWObGAgSMbpxCzNkc0JIkcOkBRB81zlJswV2fU4hQeQSqGJLBoGujIowPToYDJeh16v/rjrhzvflOovtb3Ge+ddqWbz420u4nPHG/z48NHAxG3SQBYskLDt98jaeffhXnNBIoQ+rdQ2QdQxXy+91+IOugD6nK1zSxFNbrapD2IHz9Z/RVclJaz2hEKGYLZQlSKll0uQSIbmXB9YpKZtw7BnnLBr7b7AGMbPWZ///9x7z/7H+bbcj3D+uts20M2a5DylpF2vr5tw9493BU+4clytzPIDfZodYme7WXfdO1qnzmjwxt3L/29gVAeU42PYmnPl6NwRt75Zfj848vDvS/6ZiFTPsEmC18wPTcvn8Y4m8vyyHYc2Dj40cRrG89fD73FIRqyX6+3R4AWL/7FgRg+2l7tU0d15niIMI7Hpnu2vgrFnlLBY0b0P23yrO1BJA4Ye38lXqq7wgC+jMBD52n9zIL1M8wYIxWN71n/DBXkfVreW57x9zXtLvODSgY72QAh+8L6s/f4YJf5j7gjzHue8cNdeTutW+ZC966/9YVcfsnABnvsXxf8PzzrwCAUwIedKDdPERjHOzevnseYNnI8rZ7sOinT5UwggJ2S7Ij4Aq2fT8S8XsOj+j0V8K2vz3+qyq20YV50I/nHe2/JvAM9RueUbDvuX1KSWDB9pt+bZqhtnvP4dsDTr89Q6tTQmaSA71E09EDOl6w5y9GFxf69ykmn3v8+9s1c2CD8d+vScF+EGe5qQwNUl+v4QUFjzjjWbMj5JBrjTJM9Rjz2uLr92T15kDsdo64Hv+MIKlCsRnPszlOzfhBulaYR4Acm1mJvR6SrCeNMsfiBpRIpafTCQULtpfhRLe9hNULYgaZPZ+JftN1KS4nWO3H3kXYZ2akNMRAyQLrkoXeOh6+fcT59xeFqlVn+em2OXxdD56FnpcyDHIJXpvZYEdzyWit4Xw6o+YN9XzB+XzBZbuAwchFIbxzwlKlPdu2oV7U6EeEumkGkI6JKIxitOLWNcOhodfmThm9Fa7YujUsZtwE+FslQmoAJ5okZssUJM0Mls9QQwgFlqdGQKU90vmZlDLWrKJgnDfDij5C7nPepHXS1KFOWiPT4e5r9Sxed4aDJqhxM3wbTHxSR/ioIS/tajmj1YSa1InKyQkskUKGLyuOxyOOhyMOxxXLukqGKhitVbTWsW0btm1DyVmzKHXluOGJ3fhijjfLNE8lCQQbAnQmxMBWlgWHtvp5y8xvmkFba8XlfEbOWeukK9qFOzTjPzNm6ZhryQWG0LFFZzGZQ2YsAw+QsHUPGg7YydjPo7yAnxvrNZYDMANbTgnLKk7xw7oKmoM620vK6DkjMzQQYsGyFCyH1TPlpY7zIobMKvWPWcdZDACijPcqtGPjUHIWJ1pX6GmbH+2rZZxPtcB1NXrmeU5Y1gUlF4XQljXjdG9G/tZB0LUaoa4VksR1nbAnzKiDOvaJ/P3w9Qj/7o6jyCTDYTzBeIs5XUAhE4BGcN9Yv7LeWqtA4wlG26zfNq7ckzscR1a+dcbGEOo8DzKsGeaaBsmgg3JC78FJZfSmzk9wD9nlYT9keb7A/zUxOndx8LYuwRJCY8Z0pH0+14FoDenBM9uU9m1yojPL6ULbKTTONilgBhrXafxykgzyw+GI4/EIrTqAdE5IdNGst4ZlFWNikeKpqJqZtWhQyfF4RCmLIrJ01JRxSYRUm2ZOy54u9QyVxr32NFA3AnJC2iqYWGthCr+wmpbb5SIOd0idc26MxhKU0mod/M7oE4pyANm74jRFOF1WhAmipNex8nfo/iDjaRmRgJZX6IGvMSDwH/YKc8KpA42SjC3UedMaiDW4QPcx2XDNKQ11yLHve+LwtpnbQ9NqLpvxSA1GZpWrdDiC9DbjSU16BEEyuxleZgC6Zl0LcJ5s6xBj7H29hcMeH+h2jxgHjH7bZKXdd5lskypUCAJ07LrLg6bGXcvUBFoEUQc5YTtXjCvHtXkpPm4+vabdGu+LPI6t76P/IleMPUv6PYLyZjFvbynR4LDYOtvzrB8A9nqcNSbb79McYyDbT/vm+OtbtDre7HleUsXp0YLsGfzCKN9I8GarEZ1Ijc8E8MtwaiUa4faEReWG7Ypk5nYtY+9+SCi6rrsiVSQQ2nOD+E/Ocm96lMy4Bbh8uMACRoxGW6265hn9fJE2UUJiApOVsJA+JFrBBx0XMNrpIsZ966s67xMk4cKBQpjAmkU8MAuGQT6Rnmen8CA/xwB7LY0RlwsiksXYSq4HMUy8n+Kgb82XxvOD3ej+YgIzAl+BIWtovynmyMcn+xuuzsZDtvS4b+9/F9QlNGlT1eBWJEbVQCznf7Zw/L8haIbZZaHeOQRzyf6cIPpgLgVlFeShZVm8zYaSErMYbaz872BoIxCsVTAYqSaAC7AcJJCKNBWFGeAsAXYWFMbsexWYUVn6yiYrsgVdii5Rm2A+gAg9EVh1GUMIoiyOQYPClwBFLYnSpdzQQANgbJB9eFFHO8XSUcweOHPBaA8zS1lP5QUdwJktSYCVh2h99NZQWaDiqQ+I9vbhdyQ8IrPIYOWrRdr0JNnclsPaWOLDjgAatF48gBMH8g+OMtFnPX4TIxd8bGi3zRl7ghxzK8+dOPaN67F7D+GFGAs0oYfnq65tnIOKr8/Ou/m942rXjSdutvX2mbF/s5f25CRyw1G2abz89AtySnj45z9Qt5/x8dcV9L/+ifWbd6i/PyEnsWdkJIAzWstI1JAoeckrkcfkVUZXIDiCmWUZW/AL0UCstX8G85+JUHJDqwlLSuCUUJLoTokSchG5OVFCSSpLpyx7Gc24OXHwX0Fp92tev+CvPSIV3n7tWw2a5RafaQ79ZwG+p96RLClDEZyYZQ2XnKcnOtJDlvr0jhOp+m+oX4KmiAKNGtZlATZBQ+wcBzvuqHd6QKKHux1k/AgL2sxpPu/rYpJ5xz1xFP/NU/s/4vjiQP+bjimaNmwKg6GoEE40LTpfBLuVcH8bvPHuT7zuPc8O7ZiBPit7cmy//Iryz//C+o8F9cfbW/hr7/34iQ17/bI4Ete7rZ153v30Wia6XwPs5uI6ElAUI8ITBN5H9QdBYtw9yz7NsytnTHWz5DSoAMe7+6VNv4P5h5t9Ze3rHtr9X31ctfMVSWmaz90mb0IlgbQOPSaBcf1hRfupwaKbHzgo394AmpS+eETzzDn8eCug4vMP38mufrn3/NhO4jA24XK+1ZH9Oz+BI6xMMxz71e/yV8ZI6PRWxvktqr7frnsrcz6XMAw/9teyd/ZjVyECz8N33+H0ywkJzwAsqvtxenb+SiCxtg/iRDf1OQZUWHAA40sm+v6gq382vjLW5qhjzPNU3mfQ03tUPOvZAyQbY3C3KPTv0TT+k44IBzbMHJGLCYXzdPb+2tiwYcGKhBUdGnwWjD5gnpzopIxtOS7Y1FGY0w3BPMjhiQx0VAxLvXbQIu+orXpEczyWdbU7/G9/kcxhqc0o9y/rATkTyirm0Fykzip3RifJCra61pkSFjX6du44vTyjN3O5AJSSwmwBOUvGYOsdh+2A8+mCSz6htorOQG2bZG8nQkkCJdh7R63VM9Zbbai9CdSr1n5NSbP+1dkGoqEPqeHHMjGQWJxhqoTfc3YaTyYb+DTkB9JNzHd6Uv6mSjyb1m2Oic5oKYHbWAXMHVuq7hA1Rwtlx6xxyO6eO3rOI0tDnSjgLoi9aniL8xoh0YfD3XRFISQ36rJAx5Eq8CkVLOqgXQ7ipFoPkoVOROrQV7j5bcO6rB48IHQCgWo245tl9QbjIrcuRsfEwIWBIpCpXcfInP/cO1pSZbg2gW1kxlYr0vmMy2UDEUntxbpJkIXC4Hu94tY042fIgrd2U3NUubuK2eVIKC2POtS3NhK2/+s8mNN3zIHdJSUQBLq9aJCDPbN18YbV3CR71urEE41yCdGwDHX29Sa1Jkkzp5usnWoOdOXGFOpmR0eUKf1SdzpBUKLVkQtyCNGcM9ZllawoDIM1a7Y2kWQs9Z6Gkbg3dC3bYDRi8rZkI7E4fYzB6jvNGCwlFPRcGrW6feH6hm+OQ2+U0J06KJkGCooEqowyEQJpqk5DRbhoTQOTcpdghCYGX7KVRjpuqfu4EiCw2iwS/rSLEAEh2KAzA7WBs9ajJ4DaTDc63d4do2ehbYMAJXWe8+CbraGxZrt1gHJGzmbEH7CiqSe0xhB01aT01B2q3IxPvQ/YZQ5rw+jQ67UqHdlK6szgltGgQZDJoOuTZtmNOuc5F6RckVgw9UmB6hMRwCT1Vkl44+Gw4nA4YNEM9t4qwNCyKwBTR7Z1lxLA5qTuzm+ZGKgEypoVpwgMnMihb3vv4NZgWW7iZNegg64zzGHVRydnSuAe+T4r7PqA7U0poVWde5t3vdad6jr33NRTrgZcWRQ0DHBsgV32LACK0MAYyepI5uQ2JkDqc+GJ1ig8G0rN0WE7ZKKwcKOkGLDffUx4PGvqqzRV4X6jgVrusb3YJDSTw4b6FGS2nb4/DLKzXSB21mhWvhoNG39xYWCcQ/w+giWJgcibof1IRA6lf1tfJBBs39Z1Q+ZonyHa95lMdn/8c31dfM/4FFsSA2FG243MaLqbdkYIAmmZI7smWEJo0Nho4niz6cRz9jv5cxhkYBEwvityTta5I0XakKdRB3CG06o7/kN7PSgLAGFRiPCLfGdxtZWH0RKjPPZ2yhrJ7zLQO+i8ouECVoSHIR4S8oPCWKtYyMzgU3dZxJz+Cas6MDeAFtCB0E9d5Sm9bjfNTn0cHd9idWJ00RXcHgZvt69Y2us24cGEq0z04AqeLh1O9bD29KHx3njNmIzb5/da0ETrzrtMVnjdYiH3DxqzsSely7jnRvsW63xZCShQAzWg1YzaGojMHRMz6PdWlJlnjTJIXYKxdAas3BMSyR63ruJAX1dfk71VdJZyHzkn4VXQPW/VmVcUJpPXQIpM0wSqOiVCZykHZs5smy8ZD9kviZM/Kym8NEBojZGzIoLxkDckWK+DkxaY0YDBpM5zK7NjwcB+T5NxaD0EHyq9NDadrYN0fwaz1yZuABqN+xzlzuy1ylyUAw07rv2mIuJEJwA6nsFgFLx32gEewHj2axiEDeKQT3rRjKRwg66nn0zYpSBD7Cnorzyk1R1iL3zNjnvn1v/ow7pTIaola2kdel9xenkR1IhagQykXGB6TU4JvWRF3VIEM3WY2vqPgTW2pic0GaWrqBp2SMDLVoHetGxCylKCiQT5qJSMJQsanfwz+V/6QZ39nTHYfJ6LoWWYA/b6mn/9sZeObh+vXXFNZBz/q7KwTcUozTfOiYhAuu/JM57PF3z1cARIUfGm4PDrTjDBkcdyJkFJnVppFq77xzRXJvEEPuCx2/o000/Hvft9KMpTwVdF18/+cvyx44sD/W86KCzGqEr6OZX3RsTY+G16zk7xS7tFce2etQyn/eKZFy4gDm3LCrfa56znCfO5xADha5z+939j/eF7f1KwU/m995gmAbtSSFGEvH3fXsmJSvm96x67OtCvZPL7kFAC274fffao3E4S6Uz4Fh2/wSIZ5blyb8yaHaO9A8pSpeZWtrpcT36OIP34lr/Gyy8/eT9Z72dovYybI/J5x/W9n/+01/bmSVGlIaAaPTzyqENvgi0BuPy0oeMjAJqywx/txkTYIy28EOOB5yi9T84sv9Pm279fb+4HHjkV9oz4HMs0Z8BRsRLegfERhHfa1z93HFhalhg3HejmOI9LkWHXytnz3YgMVRPc0KDPoPHroOBxhV1XckZWxZR5CDwGh+kZN2FYmYDn339TmKMjEh7R8VFX5zM6GIsqNZcPHwBVchLehZZ8vOKV90F7/n3HX7Hu/hWHrMHhPI/VAg1CMmumPwM4Pz1NM23QsSZachj9W87zW5Gb8bg/Kvfu+3PjGPti/YiC+r33enaKrqqQ6wyAPDvEmsfcII6BsHe4As9YljyEA2/T7lr9uV6q16EV5aqD9qFVOo1xHzx+84DTby8wwzs9jEvtv7kU6IJ145H1lwjodcOyrAqNKxxwu1yw1TNAhMPhMLIO1El1WFccjgeABUJ3yS84JeCsDs9cC3JpWseX/TpuDCKpm76pQ1CyatWBo+20en2D9bNnBxp8dK/dS9FQZaCQ92nKhpqM3KSOi/HdKdjmTqHtmQBkHgqQatS9VqnBDXFcXbZNa9mrwayz1DpUg9eiNXqXo4j0vUv241Y3d1z3xqitirMcYpiPDl5ztk4wYdE4bqfUsmsO35SyZIJnyfJc1iOOxwOWsqriJhmt29bQ2qaw+hpgwfK5tgbmhlo1AKJ1tF7HddBruWgt9S4VPNWQl9zwl0DUwD270ZE1I52IcD6fAMj7bFy2y4ZaN8mVWkfhAAAgAElEQVSI8YzPeS8wJVu+B0MqaCjWRgdEQEqhhr04XK/G1snONlxSJXk4n0dQQwpQ+StK0TIIkGCKRIRcq2bkF1H6U1zb0mLW17E59pQDGez91jbJPGK4Qy7lBGZxksMoOYyFQO/raCicoNCF7gyaPWxQvV1rRpujfLRQjalh7bWmGdTmhIU4znkMu/dOhlCd53EedCy8lAMP9AexAQfUB8KUsWuBNCkrIk5KyGWRjOZc3Ihu41nbhm2r6FWCOhs2rUs81pD4aIZTXBw6XeBcWYNIVMB3fU43F+4NnUjbT6PPNHQD5906BuZAFxQBVj5NkpFhhnIPWmie+U1ZeYLWCe3M6Ft12+0Mww7n+xZslLTe0N4oZGOQnE4sQCO5Q1ZKPBiPgffPSlYQhQAeykjUgWS7JwFWYgKs+0lBWVash1Ug4AHUlsQQ34rQmdExkRhTWWHtjSYNBhksBnoi5MOKVhnb6SRjrCuEmDxbjpXWzbk9+sjKz40H6HjmEbCSUgJydqhaIviamWmKBrpII4GRt2DTMPx7P/CwKwQtkQIkbsq+BgCWYVU4/pGE0/1ZA9ZaXmYObeMZ5oBJK4EvtiuyrIei9xGDIuDOBoF230wqZ22xcmFN/45wrABP/AFEQJWAjFvjMB9RAR3je5N32+i5bmSauY3gXpMnH217PzHNdptg7PCSEFeONul9qxVMCcuhiMyB6FAebYeuoyj2JpMqAy3QfKPvc2NkZleo7U++H+jQTQF43obwaBu3LGuNeOdk3d0Pol3b4OVNKJC4fSImQT7C0HWJEvpWkUtGr7oGn8M+H97hjtujlJjqJ4V79jGoIBQkrKBj5MPkvDsbwhMIrYuMQgVSP1lpPh2P6CfgxB9xeDxoMMiGhAMoZaBLGFF/aQA2yYCkAhwJ/NyBI8S+cV4loOcCgJpmvLIsKS0l6PMMSfIweXTo6+wIMwnmRGeVayTjOJGvdpl/9fv7emJFgDAlnRDec/+YqNuWUfhlnye+31Hsu9FdJ3gQ3fwi0kAi3ZsceWF+zrhx3rM0ZMXrdA9uZ5Y8fY4GPHFvTktJdZGk8OSyLqxkUegbzzbBLgqJBqh1kWl5OLtJ0aPWw4r1cPBySrZx9lbQ0SWwMllQm+6bGDqEtTmpsw4QXZ57R+2kQXJJA85ETrFgFB19tNzQO7CWjN5FNyil49IZuYlDe2SQizwi75A57qxIU2kEB1imuAT4dS+Z0npDNXlOZ89ku01lkYM62FdFhKmsMp4GD7ad830O+lCdkrWcjJENi52u8Zgjnyv92z7oHs0ZpOUFAUiAIsSBL+F+wEEhohmjNrrR3aboaUsp/h7JnLU2C6XklAAdT0bc1+elR4GvAmNdXQWshLssgYas/wAO+pwzdofRjTqTb26voX9vuhVf/fHWBXz/l7iN+kUyB08kIkj6USDb+btHtPqC9XBEef+InE9ITw1IgqiVSkaGlCsQ+b6P0mnAhCjhn0w+ojG6FIIzbM33zjj3KkhKSaDjExEKIBnRpYgOmDKWlB32vQEg7kh1BOjsx2ZvR4v0e1e8+QsO2n2+9ao3p9qPEPgWbDCR7u1oGhCxaPDD6Xxx/UX63IFccL5cNMBmrI+n0xnvHw84HhYgEc5bReN+s6EmWtVa8XA44On5BUOOJCxlkTJO7dqSuR+b6TfvkHqP1JB+ZKuFDk0iCfLuDaHWbV+4P/5fjs8/vjjQ/+YjbnSuVOHzCPyzr6e3maUx/I8YjnJgzki3NicGEr4C43ccf/jBFXkO91j2+r3XXi/5WdH8tP69xYKFaz77A/ca42A0+0x0gXAHPhLjkYOqrAYoMdt8jY1/xVOKMxIdtXs1bwjLLoLzrHLvlUYAU/QjA+j4/Y1+/7njvuHgjcMHyb7cuWZ62e3zH4m9PrkFY8ilT/5ZNhX2x7hqRCPS+kUhS60EsDtHPn33frMLV30Jh7XD1k1sAwC0PT2Sra/3KN9lnH95ay28vWLiuwcU+/x93w1ztJtz/drxvlclZp72KS0G4M5zu5m13hf3+/2p+pCNGAd+Bk+rTf57wROAaH578rer6WDUAw3tWvhLFno8yP8Z/Dq5IU6+J+QgqEv98xcIaNlQ1ORgFfwZHWdTWf8POa42jjfvMOU3rlDjBw1bMLmyGKtgcasVjIzzyzOOj4/yFBtwZYhjrV3vHpMCnZLUAscwNmRKqK0KX0yLXkdi3CRxOD9894Dz6extXxQGFyCsx1XX6bXBihk4n044HI7ipNVaXWC4QWhZitRZhdRzL6WMutZlARhoqaMuG/KWkZs4KkrJaF0de2psYYXRZYjBZds21K1qDUjLVjMYusnk5UqVQVFblqtHBmehX58/d36ZnGDmAIt6Fo3dHGIeBcwAEaOn7s+J8oba/9UJXwHQiIA2I686XyQSvriRxTL9l0woS8HSCmqtOCsEPjbtg96bktSmzrno3GjAQ3AeVs0qtX8xWGA4Gud5J8o+14wMtARCQgUhpa6BDg2VE5I6KLkXpNRQsjrJW1H496aoAgIDXxuJgz1m6KvTFepsj2JEV4NF6x2Xy8UdfdGJbu9p5uAK97MbXcXIYoED5qCciB1iOE9ei7wgZckauMXc5ijxgLwSEQGs/jYJRHu2ucsjwzclyc6VtSuGex8fhkIwwzPMq/Y3tsMcfayycUrSYUJCyRIkER3L7iQn+T2XjJwXLQmgFCLEhKZjLiL4gBUXBzn7AJDBtmvGkTgBMY+zMb4gCEeaRlbYf0mRlnNkjtEkvGDKBJ4lFc/E5VG33jKflyLGaeNRNnYN0GCOMJkk75CMYPZ+mAwLqAEt9t8NHayi66BE49lQx4b1G0TDYWGGVXtOSgH6lNXIx+CqU4OBjGEilqBTMEqRoBiB9mcQS+1Rec1wmloWurwX7vw28ORBhBQctyo9+BqaOHFYW6Ks9s5oLOs/B6fzVjfPSrOxAcgdzoDAbhpt5CzlKRisPFX5hvIOTuawFz5CHSNgSOcuWfCtzt356SM6NHMfpFnRhi6gGcTETs823azvBKAlLZIi40YD+aBvk4cB9viLOXBLDis5QOJBdAkX7Pa3MNzze4SWgo1A1+TQlVnLjMjzfI1bf+y76dHw24TGoHwjF9ADob4MEzxXCL4tJVkgnYE69k1rNmu/03LtLEYwSMd+mcH1WiGhwEcCHK6+c3KoRCe6G26C3rP3UHuL4+edVuQlF+R3GjVafM6TlXGYeiRX5IXQNzHqHtYFFyL0xtN1+0zwq6bRfl3GS2450eOtYw2Hx13dG1tvspL0F+bnu87qVNvK7YCAeSRiQK7TnfWbbZgb6ktDRwEddY/QmufWL6s5bSOGEwEP41lJ+a18qwAXrWneld/LUXIRhCGXmZKvCSET7cNJ9wYiXF4uKLa1JQmmG9glDUwJQAEddUU/Ko9JokMBAw7bRthQVygoDMkD4eRUd3KZHbfk/8Y8yN6lczLNF+8oczxt75y7msdJ9uX4gDfv3d8PjHUDWOixfI92T9J1L/x5fr6zCkOxcfrWYFHVYyzI0cbFtN6oW6ETSPfKSqKPJJJniKN49McSBKwNvp2pbMudpyBAABrQV0TWV+h2Q4OyPZSLleqSYE6buJ6lNFbKSZFjOOgY5OgqTffH2sQxZ+8n7pBANl3jicQRTkAmc/Dr1ro1pLRNMpEHREon0ThBweF9LcmYdNSuSGIaCNh6RzXElzDugGaCaruby7VjfsBmBxpt8HlXHmKOkbFqnLs4eV5tpZD9reMJmd+HtSOTnGjMaXXeKPdE1Adg0GmkSaLwrun3QfeflSH+yjH67VWrpr7efQ3f++H28Wpzebfu6Xpcrh/2egPi/USEE4AHDF0gffsVGE+4/PevwDeMlP8B0IL28wV9XdAgwS+CvJZRitzXahU7JM/B1+Fl1qX4FYDJSDzRGphhImxP3eXtRISs+lbJBUvKgxa5g/ssD47xY2cqkU/B159S/x+19f9bjxtUEzcuP2ZZy9aeyRt2PUECVfaP68zYtgZKHYeliA5Sb6dVdbYkSpUTSLLZLbhf5JvBO/ZN9aCpsJeNTHFtd0h2OUVat3Uyvo5+7OXjL8dfenxxoP8dh+6Gnc2APuK/uy+CIBROGuGsSNm3feb5+F133SBAM9+IzLzFlFTffKbhAI9XxfMJhOUfP+D84wUdH6aM0/f66sjOopDuQ3LdAj97775ZlLnXJwo37669wWCi8hWNA89pFqDk7/jU8AFPNl9EuxliBB43tdGEuqkNPDLRZ0VmHqtHDtkC4THx8xiDz2emb97xygU+3Ddf/XltObLVN5fNyPpWMT4zgEcbIyN7/S2znLPM9KcbkMd/9NgrjvGgoLWtQbrNuuGK6gBciLHeXJdAx0cUfCWf/+R+uKrx7znJ+4rCvhyC4BT7c+U43yWs8u6OCA8TRcZ5vV4/Q7LYBiSqOFSgEF9DfbktJI3jfOuSq6tgQNnhIBx0zRU8ouEFBEWVYODyyYLIv2id/QccMzKBZJYnfoeKBqYXmTc8SlS7XimGrUfsqUtm9IzOj2CcpCYV2A1Gn3tc7wt/7o63n2dqj3y+Zm9xzwkfeLcSaH7S2KtYs9GHi50BnF9OAIDD4+NQBjtAKTrRzQg0ozUsS5Y5UzjWWhuWnNXhMbKdibQOeokOEOD4cMT55Txp8mVZxNnVFCY8CzRmr5rjQqR9IFX6smSrk17XGiqAXDIKSb32kos4H8uCZZHa1mhNHXSSdb71hNILsA4HEOu4c22Sea7O803r4yYiNBYHZ29RYRrOc25mqGIJNNCag1TGujanmvEtouRZgZZp7E9WeO2ho7KPcyyB7jIh2DPqiNQ4rs5yvyzMcyVC3ja0UsCHo2ZbSk1yczRttSKXgsvlgpxG3cik12atM2iZzmCBfbasZKndyH7OoUWhRiF1Qu2hi20+SN/FzChrAVWpI1h7ExkzCTRdKoSF2WGQzWF+2S7iANwsC1TQC1IeTmaHX9Q15FB80CxVXWjn80UgyrUmYmsVWxOncq91yE+qZXs9chJHLjRoJFnG9Y19QeDWJUtg0XrlBmdvUJc+7ZMDnbSmJcSBbu/QWudV12YqkgEhxlyB9ytVa1Z6zUdIFqoaX2tKKApRL/Xhq9dClxEbG3umJDSoe3IyCPa8BCe4jG0ueazVdVWY0CwQnDo0tVY8P79g2zYPtmiKkOABL+aQV0OiZ2ID4pCUSp/jfs+uVR7jwSAJ5H+VPsqAGRenZZfamE1gTAcylBr71eDBJIEJNn9lyWqkLshJYcQtCKAPaNGqZQAGfHeAjXaHRjCWEcAKN2QZgLZubO6t35YdbpksZOknek0sg0CJBvw+W2ARHBYfGPM4+g/klJEyCZpEKWi1Sg3AugGNtaZqHyNGsmtH2U/Iuu/WBwNs9eQHH0W4d/A3CnuXOMTrVnGm84Ra0GpTOpJ3se4rFiiQaGT3mhOdUgKa0LHMmfC4RGIQSZTQDWEjyQgxsgeydHSB+O+M84eP6K1jqxfU1lG3i5Sy0Cz3gbsofMjnu7PCPioPzBnM1Y1syhzQbA1raQCDiUw5uV4xRAaWNW1rg4K+as6vwGug+7PNIxs9Kh0kCx7TvUGME0ky/fsI4gDL3RL4Z+gJyVeVyyGQANnOjH6q87wzYNmuOlzgpm0sRgezLkHTmJJDXctcD72dAcANnzIKTpZGjFcKuOnb+rxcwA0gqq8YyH2Tf+WY5b8hSpHPmU1Urx15yVIuYDOav5ZMbb01sEA0t6brMjw3yqiBxASBJkoUQ8bZXeo6HYVmmKE32p9s/ca3z+Okjmioa4ntOUZPgy7M2euvnIKmoAEH8x7s7TQbDLHXvk5c5Ny5ox9lb6VHgF84vEV7QEoBp0CUAWtLJJEKooIlFbTene6okPAIiu1QZCDv30AuWKH84mBzkhT+epTOkF414FTQPbBz04xa5VOa3Z5Y7UKKOGUG/Wi/ikEpIh6Rw6/b/5JaoRzeHUmDYGIgsLy72/4V5ofZUB9iUgqma2Qf3dsJ7AF484jBG/aEzOrEoPmZpIvOVxGx9tB347ltkBm3fSRndV6RBmDstjf5JyPSu9UnMOdoFSQpEpmCMmnAZJrkV5NHdNv2DGwvA6KZ3xLgKIhDh/WAdT1gXVeV6bM7+AEpY5JUpvMyugysraMui0AOu1MbLu83dywJqokjGeuaErR3RbAi0sxuIHVGYs1uJ0HUovNZ6FFHugMaUGbv7GDOPpSABlmz7M+1Vc34ldI49f9n710XJMdtNNEPJBWRmdU9nt095/1fcGbWdldlZUgksD9wIaRQZGVVX+zxNO2ujAhJFC8gCOLywVKvDKR2IxnnRfDq5xDLlT5sn1uGOSS6TtdkWttN8MVoZIOgYTqzh8QcxjDxSQPE9zdA8FlRDj8B9KUaWoHSKpuuD9ZexZhTOmnWj3kS0b895mFvwKtF91lFjcprcuomTv7s1xkm5S+CVAemQ4OVN1u8V5wXVXd+C6x6tuT95T0lFltW+8ad3n5yQ1pbZ+e1N+cRInj9L0Oy/LcX8Bh4e3vDwgPbps5Nuseq/qKZdwjZ4Z67YIwjF0ltSvtn7JH2RQ2kYnQ4e8BpTQLGi0qx3OeqSyHnsay7Uhox677EOcfPVDudSXJkuWv771Tem8bvKuK9mfsaMFeJ89BhfKA044198sGZsmlW4B+/bhv+8ukZzIKLpU1bR7+DaFc9NbDYnl0KYfSByzIRAakQiG0fvJNZjiOTfieAzBk5VrWzHbG+RxqM/CzFufpYnAb/mNn+1y1/GtD/ASXOrv75sPh39/pBOC2w39tL6G5h2Q/Ht3okNgC0/9NUYYRfgOPzXvIGiHsm+n29+vYWffaenbdq3pUP1TmT26tlNcf27r50LdQ6R4ZlG6S/TtL87wSaXPdhvBOZPOzfWbt+q/KjG6vshJofejFMXt99F+h45/GTk7+hsLJnmWaU+u9RclvnkiWFTT+QmR/uCJoRGpRzkqVDBAEin3H7m9LtLiDhvbYc+MT1G+6pd/Rm5VHU+W81igQEtFgIMK4Q9hPbgXf8HsWj8J/xCndWSU36H12WA027obzjs8Kcwo1Ot5gqSvexuQJNpSSh4VP8/seJ7r9lsZ4eFk5SM07GLgiorcPTu8+CI6nvPd+dnd5ubxAA16ennYA8zEDk0HzHqHAi0kgC+7FvA0ur+3PnOwT/9KxQ68UMSAAir64aSTlCWtiNVW4MLFWNf6UYTLIqQQo0GmOxiMfWWsCJD1Oa9G3D2CxHtR0KavNoQoQyhpnV1cANpB7RagcMwCBkiczI6wcMCp7j4+SGtOMB5LBNg07oIFx+ZBoFZrSFFl8R+kJfHWSH6TlfgK4th8dVozCiL2zzrlHU1SLSGaBizgpKM7UqNL5DzWkeZx/HFkZjj15246v4OB7oKCsuJd03LMq51oqZoV0Hy+Ha+1BYfc3fbYYQ8kO+9dGiqhdpYF7AbIgCXd3meIzTNBuS2uRvV5lbDB5+ytCeGgSHvRLeP8ry9jTUFs/fbJDPeXCqG13N2KqOIMuEawaM/uXwSodsLwaoMI3AAFB7h0AmHDynWHubYzYj2hi8nz/L0SwetWNRPP5wLQjFa6u+Tr2fFZfrM1pdjMYcxwWWe96g+y0yu5oyQpXIAsI+0t21GuoswCiowXc0StyVlFOJXw2CPeqMvrvRu6BVjTBWJUlROHnVHO/WsEcLe07wYWkExAx9xXKdl0ooZjxXRwGd11prsPXeO2Ro5N+whRsOIYYwURbtn/c9/h5oQM8FFHXvI7PtPocYdyNL6hsLg4bBBJKlNkgLxKPuQq6U2Wftt45XLYoesbRFI9bs4CJSzYBLEBqh2DuLgvZ2H6MD8xlMfExs54sIvFCAz9pUUc4gcxLx4jSd30GivEHXykRqiHktpDnnmc3ZoAM0QEXRKkhYU3cAqIblzmm+AiHBHKyEBZa8EiQFGACXYTzdkrUwg+wMoGdLp1uY8XzKuMJqAHc4fWHWfrSq0aypr9rvOd6K7pIOGuKR036GnNdmJDAgxn+dZzhCC1PCYypsm5YaO8XylR95pLNDY7n7w8oDhZ6fkTFOoLz7HKugV3fuc3nL6ChHoYbyMATSed9eKLqXPL0/pWCmjQJMXvDtQtJY3nfpQ0WS4RzYRaBrvXQ339FxANLtlOtrqufxnWNJhzr3NVEYfnf8Jo1lbgPFnE6nJ/XkmY5C2YCe379/i8lXd+dl7OctteEog6Qvd79LNNarImhMt6k93ygUOsf6p81j1jt53WxvgSM2lVgzpRTLib4fp9BlEGvwDBHoWQ3SeJN41tPpECks86F7aRA6pBCGSCBe+I44Awjm+qS8v2AaGfQ6K2y7w/thOq2lQY5/wykg2iMxgjnGx3ofYzznaNYoktu43zd8Uu73F3/FyamR5ryVJEvLgVzEeIec1OPnMNh9YpukO9Qp/DalO53m5h4B28PUEU8wBqGvGzbzeiOLYo3IZFiqIt/fXFSyD2Eitn1T0+OYY7LJKG44FzfsEUXE/Oz7dE5jWw1UEnqO7Xe8Ka7mTD/CwHA0AoQsojKIyj0wqHf1ETVZnvbnsNEHujlOxhwbf24wFEAByKDa++h2Zphyq0O5i0zEqTgH2jg6ehFEDd8EBGS2Bxi5w4kaIdWQ7cZrJ5cVwCXRx9zpdiS3q1fd3T/jgp9Rfgb48ycIXkEQXEDo5DKNPu050SsVdQ7NfOdE3y+Hv2fXfqT4W51aXNI/rr6z3/x3T7v4Pe88tnnyFjm/8aSTkq/TY56xe7fv6yYgbfb5CueLsDQ/A9w7uGiKsFI0dZ4GGUgE+riDcTaa370smmm7ksuT1kXnWWLrZ9h5vPeOrWxolvscrl+B0vUQQTcdyORBSDJrdjSZPCfzlCTG/VOVtKV8uNhJ5f458Qjx2d9S9qlgCJPG//blK35+fgrkqgVVz9cnL/TghKU2bO606czW3jsedeLB4IcuehLr3Ys1KFYmPzvsp/rYA9n7z/LD5U8D+h9cpufpPGhCjh5bMj16DxuGe+xNpYkd9A6Ly9eYmEA8D2k0D7Zn7bN/jmfKL6QGc+csOSK94Gfc/vO/gDKNgulW/Swz/3m8J32+F1/p5EryCD9v/nl/3rsg6X13N+/FBBeQchUVP4NA6PjF8qofKqEk2InBQ8v9OLiCYyfw71qyM8s87N8jweZ7yzfr+MBLdgesfDr+riK2Mc1xdCE1G8KfRHOgv9gBcYpv+r5ffsOI8w+0OCj32XKee6+baD7zTjPq3JEGkP6uyUv1RnsPO8GMZl+/wxkg06/nQef0fEYt8D48ijzf1+oty+R/bNf9vBMs2ilkTVssxaGYJWznfMIjP1bOVsjj9gOq7r+AdoeH3wrK/b+r+LI3/r6AQBhgMOkhcDOFwiU9o3vDq/19DnijbAweeMOABCLA8YjxcMQeXP5++f/9Jx5d3f2eFNFZZM8HuDx+u79+WPpGN+e+J5iqKsJtWw0yeR+hLCSQIQahDWyjazTh2uOwSOnEyayHwuuLzqAbRdRYS6EQ8X15Gh3N0GiRLrU2jL5ZnQfYdCL13saEIx7bwMYA/aSG3GVZLLpODRzbplGd27ph3TR/NliVe3VRA9IwRYxHnXvOR+acg1ajQZgZVapFehpML+h+3wbSKEMhjBdT7rg3MZUkD6j84FBrscdneSwd1vMBN5TkrjhlAVlO8110VyjTNQewGhyG1amRx6MPcFPXMs8lX8oSSrZluUR0txtMa9GoGqe1ddvsbK4rFMAOapochh/7PmlEN9t/HTwaejLwkQ2EKyNUIWZRWyTqQW3KBO9vrQVEhkIAg17vmqPbUx1kQ3lel26AzAaFMTq6SMB6uwLCad4NPBF57k+akrqWFvDpxSJ1CXq/v6MYVPSyWK46g9YkwkHR7YpG2DrxtVQiCryYARhQY7XnZ1clo4RSMqIMXNli0eaxTolQhkZ97hSitsZhtHK9XnB9us6oeWjO6ev1CbUuBv3eA3rdoeovFzWg15ois5khGMqL3FipxARX7ErkA9U1GJGyrtCBRvW40w2b4pR4xBrys5TDc9emkPmRQsDqjfQRhvCwg/DnoXlqC01ldGuoyzSgl2ZoBlVTCLBFngtm1DwKUFBBFSAotKrn0I4xMYXcgEO8qtHBoYZheX13JyCxZhtfroZA0ExhDqizUUc3GHynRknrb/IRVbrovMCUR5VI4V9b07773Iiufz/METGE92s19ilv7EHMmkaS+V3Xs+ZKjwh7z7Uu06Shy1QPAZts6NivSxiCii7faugCSutoFSJL9F9zpqtDn4hg64y+DfQ+wKXg+knppTQ1jA+jW51DSnD4mouWedgYWDSr7a1hbKcRfEideaeDhPdQxghjzrit6Xxvf21+eLA5loml95g8LtZCzK++hEoFEuoFOcpTmShBQQsEcCFgTONGkarOGC53FAAc5odYSwRS+3qjabjwfgosOkr7rzzWaQDRCm3KicQVv4c2wVJHuD7ADDUlbsYYbBDMMwpZoXpoLirKL04N3slurF0c20HBunfw+JGTt+5R6TNS27xWV/LGlB7foU/yNh0BYb0mP9F5Hym9I562vevEAB3XvW1xPU57sV/Nu3F/P3bVx28+Zr46Yq5mt6Keabz3J62/k9RBdDD42rWS3sYEFBrz8ptCogtlfkMBLT+L5rzQnjbNaz4zL6shsVZsWze+amvPxt9z4pIZPgsJ8EImExD4xfthfJIFIEVowRtmqjkbS8EAQkle0MUbLDtSJJTJT0TgdhevZ5Kbp5yY9CKYazSGgvKsyXxd1EXhBKlj6WbmyRcp15fq3Tvi7K9Nw//++vHuZP+PR31ZkOwR/AiP9Yl0+M/fVW3PLWToau7AldanbknmvOgcigtAjK1vYThfWtPrNqbChpIT6DD2n/g+N88OOra0kzVbnY7HMXdGH7WWnZOgy1rF1h2Fp512hMfQaG0R1O3megcAACAASURBVMqB6MSYzmpajcmpRdfGAOI9Y7DSfSEQDxTRegYrIhhNIoHzJ+8vWUqwPhRNbJg8O2zv7ayO1JHDnMgccGFny5RqRgSdVIZ5NhnLsI3QDdq9lb0DjeOIOcLlzUZmEaWjKoIK4O1AM2yKyl6M5r/8HUSfdB3iBZDPFgBDIfMB2u7F308l5Kot2pQRVOa6HGzrPmQr2d2H02/5d71yTN04sNdZeHDJgomM2iFY7I7t4RveL+/umImPyeH7blGeXXemdByHd4yIImKZ6oHx17+DRPDyv/8C5oGVB9rQVAd6/kU4jgA673UwOrlDHMUGklsg1vbZMpc37PyWuhdXDKVv2zbcRPlOAQF9QNrQeRJFMugikffbj37OC6aMre81yWmvj0gSzm9ZPlrro/vOqesekfchnTufsJV9WRoKM7Zh5z46nE9SfQTgbetozPj06QVvtxve1s22yUmgef96fnmCQPC2rhAAzaD2a6lgOYb+zTdOcTRdlyn/7OT8w0j5fAKPI89/bXlU44+t/v/+5U8D+g+VtLwIvuPPw99Rits96sRvS9+l2d39Z2Q6b9qtr+N7Hv1+rFUOe83xNXLy/fgfgCo/Qyzq3FPoyOGx13zIOW/afUujUd/PBI57bC5y+LT3dj9vnMnvu7tjeITA9As+30nghwOkP3M4kHg9kQ87tz39JvSxiNjc93d9APNcONmm9z+kq7MXPriWFQ6P6vnohvqVgCc3RthTV1t2bwS8QfDkXq9pYwWpsCuToP6wcjwoEoBBX2JenmTCKh7v82hxSvcd6xS7djuLoHjQnqPAAcw0AUd6EZzlOv9I+dAKB0BIQXnzsAs7eBpcr0fs6E0HBuXfd8LyFCW+r1XzPoXVesYwqHIC0OQjRvSzEX6/fIwn/mPLcTvoYAi+6oE5Xd8OQpsfuARv5vzyHFx02PPiJ4o/oO3+/Tjm3z0HMmlV/z3fbQgTHDkfXI7e0Zli8rVj23UMMz+Y0UN6UHLvdb2nO0wzAVvfYl/S7UwPVH3rCrl85d3LvE0edZiNhApB60oY2mG9zdzKVoMdANwgPA+WauxrdhD1/N2q9NMcd2pENzj2ddWIYTKY7KWhtQUMRu/T67q0DtrWNCZmcDTYXTFeEugWbvgwRXA2pIaiqVEcXASwCCOZfZG57lWk0zsVNnPOVlZ+qeES851e4lA264/rh0N5qSWUt57/sNRq8sJUtsHugQCwKNoaEO7VUmaYcZLmGDAPhbIvJSKDHdbbm+MGdR/ncI5gRmVLD2AYhu4QMMyTn8IQou/rfVMlNCSibMOoXNXBIvKdi8Z5uEFYIHvHz/TZje2OlhDR/KRR0JUKOCmXPRofMpECCBTOBsWdD2oBwtiuL6xJQdpqRTODuLI5HQePIAIddl0zBoPU2OfKGoJGGg1zIFAHhbGLKvf85uu2amS1z6WN7fDoUTi/mhD4y9KwXC64Pj3h5eUFl8uCpS02dwWX5YpSG7ZtDRQAdnQJox+yOQ4jvhmn163vooSAgloJbKaNYkpYj/jXlWL3WpsLEMZzMGuUrxsqCIDxjlIratPo8+KORQSLHFsCYh5Q2Mtt67jd3rCl/kQu0eslnqdCYUBXurBIaPtea4MsAiLNPdqohqFd0QBUAbz1rnCc6wrpHQAZjLcE/C0FvRkPiF/032KR9u7kUCz6s5M6OnFhjGAXZdKUkVqBWF5LW3cwpVytqG1BXTTPO4m9v8LWl62booYdweS5nu8PBmUYHZkcE25liSOkKBQw23tyjvBwfrJ+uPNAHIzEj1K2qwpDhMCsKm81YBU7V8nkU22mJ1DZ0vKnwxXxyq+dvv0/Ra7QHIjexuE5YXk+W8ygzCmnIkMQsFHkvN/GRvyd08gtzBOlLPB2k4QSexPCSOznSrG9VrdqjZJCKSD2fcT2uNjrtB3h3MIG0T6cFzkP9NQNOp6FyHhqklHIZXgzZPp+SQhHfi/ie4w3OlciLm+YtCSY40ua+7z44TLEfwEs57vYuFGx6EnPl5ALYf9bFg7hfEggMe5JboI5E6Q++f7wvWWu6vT0QRbQMc3vP6/pKEX6H/J6aH9/vnOfApDO//X5lf3TkzudDDMlXpauukxUbJ59XPMdyP1+oAw+RogfG+BG+bsUh0nZTQDKU4HcjtJ1psNds1BeKuSLOWAGr7VZEAHLQJGqY1Z1bZN2WFFRUm/F+RNgzjKiKN0MRVKiVevJZCzOR92lds4+EcCWmk15CIz3u2whAOvZW0Cao3u3BOfYFCgqh/J/fbuyOPvuSBrAbjwfzUWsV/hJaM7hzqEm5kv2ZJ2KnL3k/FY48QbLudOZuJ4h1XG4RZ2ZdJ/0lEBUnEdo9L5rmnTqONcOHoyOgVK7wpILw1ws5qtchjYeGFucG8Mxx46g81OKoUuZEZgNBYyr73+OvOX7tsKqizujmJGZ4DIqdH1ADeO1ENh5lPHFUgqoEmoltEhbNQ3nayDzAIMI29YxujnXmrOiiKAdDI4yh8HqGjMljugZLiLPWQ369yL/3JecdDYBFiIMElTxrCA63wzczQNhbxTO2wPDAsVk0rqQz7IWjWSH8d1XFDyhoELwExhf5tokMsQXwmoz7uOv47AnQjn+NZqwI3qYILzBRyr/aDnuJl76XUsO98i93u1737krkq6d3fDgerCPs30jy092jyT5CVBHwkYFwBeM/wtwLfjCjAsPCBtiEGl6OilAKd2g1UlRjBI9R7N21lmltrCXRO5e0eeLEaao0x+znW1N1hyDcWkNS22RHsCBkPpgQ4XMQUgyXw0JRxNvA3bG87OJOB32E1579uBh4n6UQB4+vm+73N0ze3+/57jsCDy1itet4/AoAGAdHU+XJ2zriqfLBbfbirX33QD4eGqKqYbnlyd8va1TT0g6nZUIXVzrLunpRB8mcLnc5W2eW9S+hy8MfCYJh9a7Mac9Q3B1RRbB5734s3yw/JMZ0PM29Xt+/y1K2srCeJ4JFmcr/e6ZEpJrEmYAWHIWTBbsTyrDK7YoyQ+biRlmz+xiAooqN/wwMg9EkMOoHHfN1IcCizyX+V09cbEPzU5VvNL9qH9kFjJbyc+c1fVosz+Vu+nk2pFMHrTlpBow/YJOOO0UHT+fVHSU44P1ycNpOG3fsQvv3X/W3YIPPpMOGEeee7fqTgf5+1bhiy2t/K4sGDPU2KzeknLXpn/UXvAkmrXEDznu/SwA3mgehC4WLZkjyXOudDeOX4R2Uem5b37tvTJzLu2N4lc5oVOowuErCa5hoN+P5BTH9PdSzqjq/olq0LduUMhEo3SvvHEYjKVGxriUecJjYyDyiPyKWSf1+tXh/Bpe1T6PHysPDhe/a3n0pt9iz8zQjC8QCDp9hYCwvb/R7XLNXwBw+PjqU/e56I/lG3v38dWHg+Mj/n//2/vvOb2at/18miaNkNavhjqSQNF0HCdsfYFGvLDLBXb/nInEdIG5lxMFlPQ0YNpzYlFkYkZWqyf007kbROAikG3g7etb5NgqpULcM58AGvq5mCAPApaFImc3SDB6N3isvcd8MTjxarmgARhcqxnQQArxXhdADI7cjE1b37DdNgxRI1QpFa1Vhca+XtH7BoJFM/cOyDwU7iPCLfKNORBhHOqwFIv8TjzEDZm0WERQHjiRGHO9W+ZlETvMS7w3twFAKKB2/G+3eZni1+c9FE27YVXY5abG2qU2tMuC1tQ47vw0IrGBiBi+Xi9oVefDI3NH75Znu0BwAzOjjAJpNeWn0UjfgIkkg3DENH660Ukc0q4SqikZQaaAZEapDWTRO2Jzvm4b3t7e9KRJ6iRxWRYQEVpt4OWitD0GWCwqGaJRkmzKgnCkS+NuKQM0sku/F0MRYCLUIiCGGTEdSt2GWRhsa601NaBHtLMZaankuaQJ4950fjxFiUdVT3kqFvWcelAYgNSwDKP5BmHGV18fZqR25IExFOJ+23ooHN3ZQR3SzKhotO2OCcVg/C+XC56envDp0ydcr5pTE2aMa+2KQgW3taHcbijbhtG7RusarD2oqBKHB7ahhvzbuqJvWyBl2YJPufy0Da2oI4KT+Jk0McYw47kZVpnBxGF4p1pBDt2e4EzVwF1wuT6pY4DRUx8d67rqM7cVPDpKqbhYFP716UnlgW2DkIBqsXOXpaCgYeNTUGrDQjDD9qLpKFozZwfG2DaMvmFdN2zrhjeTYnuwlTEFZjOaRR7b4DEWcVaaoUk0LO1qRlblXWOo0nm6bU1a1ny4gFABERvDMUMgVdSiBvTFxkgGQ8bQs2jTdA9EBVxLQFWK7TMarT00otzUc5mXpqURk6sxZqoYZMnGeDEeImF4phQh5hF6k0KUz7KhcOjaLqi6eHX9kK7BAjPCViM0njJl2AEg6oTSB3rX/OMirJFw3Qz8nvoBEmkWiACqxZxXhq1zk9ddX2aK1VjrYUxjg263Pon2eUYj7iPIQR5VOjmdWPSb8wxrkH5v0xEJgEawp/dT0dzQ27YCDCzXRZ0E+oCwIa2QRVWSySw2rx7N5/uVKvVTdCe71JN43MFAcEAuPwgpYnxBjJ6LM+bdmc+j/yESiDgu2lEz47rnEqdd7btCu0+HdgPQSPZd0/DIgP7+qWz/lkel1ALuPI8536iYkG90cvPZSvVC9x93ojrWsjteIeLZp/IVfi7aj9ixlil9ZHHnfMTy90Aj2TkU2L4VTuX782CeLTeFT32Yy1Muxy5oL8X4Zt+/n9zZdLHl1qDAzE35cK0oPymCBRHUwfOrOm0+//sz1ls3OqyGJKOoFyWi5Cn6BxFUgjm3CEAaeSss4JV3g0K7v7O3ZPKjcaTktJvXHMIhhFyo99koUCOOaK7zOCfQ5LtwJ5s41Uyja4YG9ndZ13aFLO3DkX7P6F/yRdnfKfZx+rDYvwlMIXjKFD3n8hGDqz+sbxv+O72cR+NWS5sStw/j0xQ7kZ09aHInUd7EBeg8QGPg4gh7qVsCMfkpn53obqxCISYK+90KRSoXsuuDBzwjrvNYNgj0wgR3/NMLTkMMstRfxcbPZcUCMmdWbVcxGbcURz+TFHk+MLYO2VbbEwjj+Qnj85dAqOrCIAGGr2ciTMkBEb0/LA/7MDlDf2fLxT4dFu4YY2wFEp/VXZHwRMDlf/0bIIzbXz8rL/iZMP4q2GieyS8wvZz47qu6s0VmUqJmtLFiL9cDakR3J7OOVzR80rMCfkaVX0Ckhn0h4AaNaK+iQQcVhA3AhWhnGPYc7Fv6zdFjcgN8id2Pjw/P+QZyWA0ReX4sC5I8drh2iiJx8h7gqLG9f//umiSWta/I1tjJ9Qe3n33294oI1lrRa4H8ok6eXyEo3MHcQrfhRvICsXVgRvSDI44c/5rc6DxTSUQZLok6cYlQIDExK4y7DAY3RmfB1pIBHYizKgMYpU4kBniKg7lfZmfmzLOOzhfvjd37Jc/gUWBx/u1UmfFhprxwvD9fz88f38kelHbnST8lmbV3XBd1ocnOcpfLcm9Ax54uRAS3dcVlaZZGQqKZMe3iSFEVrRZ1FrKKwmmtT1lKIMGDlfdMZ7W7sdsJgc4DCV/8jlgD94vB9z+/nHWB7627j5QPiKX/kuWfwIDu0s7Jb7/L9yQ0UibE3Ii94AFkQc0LT+o7bBjBAKJ62V0jF2Btc9WFZ4uM7aTt0OummPd1Q3AYosz+0nt273yHnB9xwyyhy+ORJBPSB/2CYkbA2b+joD/b9NEFFl3c1XE8AnqtJwyA7tsuqWH56Kby7hS8oqU+567AKrqxed1iws0Ouj1IaA+jyJyU+Sd9PR4l/dCb79n1Y9/c3d+zqaWz32V//VjZZNvzsEfpRto9bDR8pJmzyXE4rhhzr+DwPfXmKykcuqvlvpLgWVSg/0qCn9LkugCsn8kQED6+/f/a8iRTuPS/g9Rw7sUN0zcT2K/JCJ6N5l4Oy3InElCq71H5Vu+PTxIUvn0t57G1x6fvIgEOn3SJOPTi9NqfHaOgQQ5vfZlKsFznkcCMd2djhED28sNOsPD1u69yOocQtjK9kquEA3+wZuAB2bo0+h3ltxM6zriuU8hBALXIgalWm4s+f4/rIZlVCF4hKNjieR1A55WPxvUmBlOWxk3Sd4uJuruOD3x3HioJWXryJ5rdS0OzowGIKuUesKKz78d5cwP1FGIzEgaFxKwwlKp0EJLp3R+0rZ7NPqY7Pks2UsVdhmjOlEnELku4d/sYjBZGdOyNGNbeIkBdqhqpaD7rDnk6Vubt7s0Rg/rrHbVUULcctg6MXgitFLTacGkNEMG2biBskSubQKiLuhoJM/q2QcbAuqqH7+ibRSuw7S2aY29b2SDPiymGWGHBe8e2rhopu67gbcRePhVjk2f4d2IxWO6CWjRSe/AAY2DbOOB1BJiR9MA0iMZET56V11E+NANQY4kboS1HYZYBQrdnRquI4PfrpviuFoV6cejlRR0UFGJ4aFQD0c7gm+Ee1Tirc7VcL1gE0yhs7d62LSIPZpTONEDX1rBcFlwvF1zsv1ZbwNxTXtNU4j+ghyGKjR54DEA4IvdVUWfRxK7sZ0HHQB8bhquUGEmusFHnuXo8cnjYHAi7w8pQcvAILVc9y6yIqKCRwrBVqkrPlu+7hUOIrxcOh4RWdZzD0GVzH7DsFMG9O9lQRBS2T0RhL6lYRJo5JWwd3NXBxKPBA7adh+V/Tu+xaAaGRt8wqWGdagnUgufnZzw/P+Pp5RnL9YJ2vaItGk2tkZyMrWvUFFpV58Babf6AjQfEoDkjt7gZ97m4w001w7lGLZU2U08Umiko7iUIGzcWVFOkLpEPU2K/1VyfNSDISy2opM4DVDRSZJDRFUjhqltDu1wAMwpr7u+GuiyG5AAUETDNtFpqhDbDf1tQimbuVEOtORMYZ25tQa0ahdVLMfu/oJaKThUOLe183J2JTCetOcyJg+dqPviqRvS62PuV76MBvTNG6ZYzXml4Ksd8YyKA1BlAikxnEdF8j70PbYMKbbqOpep6b4QiquJxiFhFPxjaAxnRG+eTkRKhFIu+VEYsMKP3mEb4+J8IpGTHPT+DTDlP0mIXAYqQzpVyWrjZ1g3mhOl48nZ7w9vbG/rovluCu+C23iDMWNeuCktxiF6lsbpYHnJOhiOTN32PAWE6cLhzGGw/kRnV7nueU7rq+iXya6oBzlfCREdRwzrjaIRG8UgqH7UCBZCg4J+eL8nPsQE/RbMNYN3r9bNLFwgpxXMlewoYN606DU3jm5oQUHTt7k8D4j538DNdliXdWhvPCAxhosQLwlCVzj0uw5E1nUCQIaAFkM5I5kDv9DR+SVJc7oS74+m8htSFdB64O8MfqzmUvZSe5XRJvygo9pTs/WXzXhI3QPmjNi++1Oz+jHyQRHTlWSeWh4Bp9rbQPH/7UYvI70uyy+6zvfvYYSsaPed0ZC3ayej3RnTfT4F9lC/E1/1+3PeQ9Pl3lXXcMYMPad58SMSAnPOJiSCQUlEb4OfNWhoGOr7+/RVVFsiLBZkQIK2qAyqR7pPmfOhyNkz+E7Du2euG8XWA7d0lGlSBi0DWKbsGX5fDWNper6KMmHzktEVhZJiR5a7H05D1Ug1BKQJvrHZxeWqO6JA40WidIRcfUZjmJASdZJKOuTrMY/qQ/ackVTF1CnbGIo8Gnb0UzL3QDUmgub94bfqIBDl67nMBVAYy3uhw5F0YA6K62aoMrIwKMZQkH+NBOgdftxWDFHL50hZNVQSTxVFNB2L/MwtZMQfCEZs1Y2DF+qZpcy7XK2ohtEJY2iX2UT0L3QKFqRKBzek6BwWw8VOX+4UFBYxrLWCahn2HhF+qOj5WSxNGADppahmmgQ2kKDuDMQph3TqGsKE7aWoQInU+a+VnoN7AhdCJ0C3SnHk607HNGbsYg3mmtc04iIFEvxcpEyoeangmESzjF1D5CY6+z/91z1f9K4kazd24vhVBNRIo9p8rPiX2VJM3XIaSgo6vqPRiZ/sXsHwFSHtRweg2iCyEK9w4o3vioLkruJxw5KeTtu3zCb/9VvFdyMWC9+7L9//acqzj+D127EcbqiBoMO61uX54f/CvOd8w3rAw61nJzqJ6zCD03sNwrmf3yfXInNPh52/JK9/2zyQfhQNVbjw8BQMFX3L5hGtFj3OS8p7N6i3k9xF639AtzcHGmipK0dXI/tNzqqNGibhDlJYpsd6Xu18PP5DthfHzgYHv5Bhx6j7sD+n+GJYH14+/cHou3keYex2ZTGUO887ySy2Y6dy8/f5Nn329rfh0vZieiFCpQEjh8j1+Zo9ew2iVFLJdCCHMS37HfGb3rzs9wXfrAj/ZuEznc3QF8KXYHmw0MNdLoq3kGXZE9tnprB6tsd9iof+LlX+wAf0R25Tf8XsinBPBehrNs5R2iBoRAQ6C+/6AIPvnoYeZ6l4maacrxkTVo44hBumYI89VuLMNuyjOJDOrISqWmC9OSc/vIbECLi+sQbPQcajmUzFANH8MFssAXv7//w+f/+M/ZrSUlVfaR21mJ4XjzGfTcm5CPuodmWyuQ3BfZ46WTrvY3dM6Us6+VMic+UL084sAlwpwKXZgVcNap31tUY8r3AWWE+pIE96ceXQ+9nm3ieWbkqRwHAP/+3ocjNxrmZ/leO3BMy7E5xc5b97Xtd/AVKo0GMm4QLt2xJtlUocAeJbpnPAiAEjw1Sbzk5TYDF6k2CoQvIbl4VzE+733gJ3xXESjiEg0X7vMe2CHAS9fQ6CYbVzTmrvRHNdHXO1RXvQMB08AnkRh7/1Hr9O9TX8SQgcCveK9socWzOLOBPYmWK5zi5QqIQz4QV55KosKhRp9Y7U9ktjOmuXGqbQwsuzgHHF+9j4cOLbRuoiKs5U+YcMXCIAnKF/ZQdvveKN42FjU+d6u9IiH/dAOJ8DEYvDrblE+8ntXqDm9psWcROCL0yRZzfQGgLAd404Cvk7uvBqzU80K7K4jXfdDw04HHH2Vw3fafXcDowCRW8z3JyD0xruStuHo9THn316UnvcXYN9/SWtFoAcV8jbm2qbR21eAmkX275rPpudjTDwKTaMKRBioqpAr1ebfFHRL1fnvY6iNpVUPXtc3a8gY9OA11HOW3aiq69Lz7k4DoEewCF7fbqgCPD+/gEoBbyscArKAUFrF5XKJxnPXA0fvHcISxlxAsHXNH8luQF9XvQ+q6BRog8ewXOdmQBYWNZ5vG8bWMbaO7e2GbVs1GtOUNORyj8g0YEMCjp2gRtJWG0BAHYQuAPeBYRGialgyI/COmJI3eZJz4iCUDOfx+9D8uK68plKDjnUeZUY3h9fCjDapkdd80YhyiyZ3yGE1rg5T/g08Xa+4XhbLE12DTkQElVRB6LDk1ehG81ibotoNDIKgL43KNvh4N6AvFyxLQhtI+wiRGGqCybuiMORseaFV8eDjp4a3UisunkccZIa2G5g7hgAyxIdmtyrDggB9n9LssH1XIl/hXGJT8vJ1rLxPjc1qQC9YSsOlLZrfvLWYX2aNitfxM5h3D2tN8h+hBPRyRO1LgcgADyWgyO/OqtgvxEDX6G6NNjfYdovad5jLyb/MaFZJDd2kmLBskatSDPb/otHWT8/PeHp5weXpGe16VUeM1jRSF4Tb1xu2bbM5ITUwy8x37/DxvfeAWVdeTAAVMLHa8lvD0nT8qqUb8Bkbll/aNaQhl9s0VihvF6M/NdbP/O/Km2Z+cHcEcSMLF4vg4aF5t/UB1EsDiackoEht4Ogb7mgC0nNXyL1EaMsSCuXWKjC03m4R5xqZonUzgNoGSh+RmgDkoJ0uNzl/8TWikWvktGq8p5aKVnQsC2kfx2A0aujUUKiqhHngR1kmA6Vc0mRRVczAbYN0Rrs0tGI55Ison7K+zByLAxjF6J/ibBuUXhQVoFUdB3dCGIaawEbDzGNCodu8eJCcOifM/dD1UCrmaroPX+oiBVREc5qnvNukWzTG2DCG4OvXV7zd3gzyHQG3//XLDcMcUiCC2gjLZcHWN6UJERBVcFFarUZfdjwxJwx1WPIUI2ABUVF0iFVj1RwRw8vUO5D9X+leHY1ckkIIq6VORAufZBLMdC6257mMrbly7RwmBLnONohHQ5oSDQVG59YGEYyRHcOsjtgPxeTlaaAT0r1OjF+rEwZCbSICg1ig2X4i45cCEE8DeYq+p5jL1AbBjKwPhxpzNNgG2lPDuPUpOs2Rjn8ZwBCXhBOt4Xi/T8W8QUnTeHk6FO/kgzSFu/qO21X8YCNt+0SpCLSEnSwqYo5l/rxAYbVTRKpTAeV3FMy30T3KfZwN9NdAsTgoXvVaOYzN/nr+fve71W3S9+HeeZPN6O66iKHG+HsJUUc2JGlp8LjRyW3V0OHIGkQeVzodBcRdBwtQpOHpL1f9ddtiM+I3Q5soKUofrsweEClgk/WoaWqMwgyQyrS1lMgNPrqg9xv4bYAwUNGU/sXpdAOvgmE0GHwiDb/bAEPl4OdCmhGxRIQKjYoPo0OxmH1GyHl6FjG532hGSIBAvCJAGA11GjfN+OvOTgUCkTp1YDTnVu36ifcd5s3nPLvfROSmT2b89f0UceDzZTedusX4khq73eCgjm95FI2IRDcO3eMVkr8Pd7pkDBmWSsecQQlAKRH9PZgCdpkJqEWjSW/bii6sTo/XK67LxfZI3b9Kn3Tqjq8dBClD6zNZdmwDKymPLES4Lgva9YJlWdSA1ju224p1W1PqJTI98v4cw8kxwIegQnmrkMIYA7r3NEtl1MxRTETTwpRaUVoDNnWOHkMw1g3rZ80jLKyOJ2QIUwWEhTQlTWnqLsLmHMCdFfFlSETjhgOdDQ6h7PYVGH0r/VOsgSaCDTPt4+tfBSS/4OkvnzD++jkeLTSjy4NVCsJ47gPzRjoHP4VuTdAAfJVJa6o7IoinhwIg8ooFP+l6AEUE+6CCSoJVtIHNrw11+vRgDvcJdl3fLVrlYxPLZEp6e5Zrvzo/2W9KzrvSKtiV5XDfHt6MrwAAIABJREFUenpXjN6DWvx5Ob1r8ufD8ey9t9iH2H7tn3tklTReLrTdXQXeRAAZk2cJACYQ9XgfQx1hqZj+wPQRKIS+aQqD3HK9xx6+05vaX++8K8GK8zQC14JBFShk8opgE1a0Q/I5Fax909ze5pw6RIyNqZwvgkC6CGdVfzWZW8q94vUbJXbUw5Ae539+166eBEgdvp/N0KSL+V3iFwn+e6QksXOpo+5U2/Na0fRo//5yxd9fv96/M+RsTTy2XBc9+6499mCVxSoKCd5ev2AM4Ol6wTpGyAWuN2m1oY+cECG33uZSEs8hgCTJvwD8XLMCkQKYQKF5TztmMvC749y9Zj+v/fsR/7OclX+cAf1OAsrl+Ntv/f1Hi1Ppjks/uE8O3+nwaV4iSZFQqcUE8y6eW6EuIJHdb/rc8X2yq4cpHZtiBc5Cxy9y//vxM0Ejg8t//MeOTbnx9r1RP15Tn9f3yp4RvrvQD+8/24Tl9Nf78kmAKmTnfGWiRACYMIoYIPE0Lmjlep8b4JE34fuGfKQZ75ZcRdqKP1TlWVPytW8xz482e0Kuvff0/P4sQPNQgpPrTgX5MuPsHfmp34oPPC5maorvgnO6/vpOtPgZSYTAbFGgV7nvCwF3UegXOY6R/z4fWkkPFoAa9zfIoRfn7XuvHMehldi+42TiAp97GWfB1z30v6d8tL3f+u6/vZE6G3g/cpqDI7c9Pv3e9bOd4azeH/ueV/79+GXRaf+sRfLI+Tu8jZme7+/bc4zvabsAOJL0j4zFbzeOH//uR4e7cRVBOA7Zjb7Dc3ruWJ+pP+/nB3Me3LNaAAgTOoYq4kQsmoEAOsKMz/Y+WllunBJAjXlwoX72xdux9W6HLatTZt3kjWOBDEa/3bA1hT8jUkM6C6OUC7becXu7hbGXx8C6bQbf16GwwVOtwWCF1y0b1psajEeKeAVUybPIorDw5BGuAo92JimzI9F3i3YgNYyQqGJNDfyAkKBSjejWrMjTcbMo+VhHM8qInJ957nAAMCO4R6BXjzwEIk9zcWMsKPJuN8t37gbzWhTq/BillaFZ3cDkiATruqpxiyiif8N4X/YQ5dXaJqZ8VOOWRupelgWX6xXX6zXa5O/BYIWpHwPDDHVjDIWwXlfcbit63yyPtyqhR1eFpI7N7EsYjsock1GbRoKkvcxHQBF/TM4lmrmEAznKvosP+TRoH43+MNputZmDgBqAl9ZQW4WIRlgyFfU29zUvDLXDSUDH6zvYlDG2ugwKjoVjXUBcGTbnEFaPRpmr8rWPHk4ZhaY6gswA6bJpKcUcWaw/tdiQqsOKIjdspgAo5sjAoKFGN4Go8pUAoFhbCoQ49gTPwRdwrjYv6mTxhFLJaKugtAqyHM3uvEWmUPXcN2rYnWMgNhEB9c0NzSH8A4aUIhK9EIEqRYSmGhGbQrCasYtNGUtmMKSikdJIBm6tVwmlijoDCBWIN9QGQFMW2Bx1Ru+M3teAIeWhKSl6V8WaOphY1Aq781aiOhEQBmgQ2CPSrd3DeKQwBYTqMFjuWiou7YJRNAoldhhHgxCGSFO5yzXPvnaYIaVg8EDjqgo3SMhsEb3CHjXOKQe4Oi+4MbMaogeBFILVcoZ7xLbWMSwFA+D5+wSuN9TdRunDjEghYqT1bFzYI36c3lW5qTvpMLh+Hra/rDdst1Vzsw7dk9yYTPbuWtUBTGm4TPmoaGSb0guC1+vwsSJTLEvwT8Cdt9KiiH1W28y2trWvfoBNO7WxrBmxTtMALgjkOk+BRMIaZSg6Lurs4ns4WV1i4y3BW0ACYjLDpBpmjIUaZRLcpC3FPpmjApEa1NwY6GsMJotI8FqEEVxRpkwuSoYRDDd+uFSprZmy1hyWvIdrvmfjFTYWAEBL1T6OaUQ9CgAhv5Vqa0/StVSMBvcy1H6/uC86Bl6ldjNJeDHXWYqde3fkSE1XnCcR5tDNPTC75VD6nJ4FTL807/ERmRD9U0rdm9SPUm/6N2gldR2pgbkf6asHk+wh27WdGY59Pkt7lhAtOErr9yXGgg6OWqnsZXxzqrwoP9jW6SgqJGDpu2fUMDEjaAkwgz+rY1CrcJM0i6CPTSGtR8d4GwCGdUVA1wJ5O5i6aM6JpN+OnSzGTtyozmkNKkmSAdQk2kyyT6Rj8LbkcXE9osPSi4+A07rxBUwDkyMugb89R+clraNM0Ejnx/x3stuzmnZ/z8s0YsxoTRjyjjl9OvrPGOpsK0P3RTEDVcgwjorBENRoHnvbCTEn3igyvkggtFpBlwu20lG6ytKDGfDz0LbidqsYrPKcypUMZjXyECl2hqYU2Lvai1nVxB2nbDlou3STcwesWorCxtv8e7StO571PiAm58gYGOMJQ7oa/TA5XOwR3pbDecwnTp003OCZbvDzV57c8LCcv5OoI/TFPqtDikWPl4byv/8d63/+DWRzcdTXZb54pCM/lWadiBBwI8ZFZioFhoT+aMNnVHoG5AVs4MvRK2t+jBXNrhQouMFEuEtnn1SJnBH7B8u3uOcGwWIvWn/8Nb9boeNnedwfSp09yhEH0WB+DUOqWPowNWBrSiOJ1GXOK/VZ32vTuzLhHhsoU2zyZrE/b5PPYIgUkLDKykyxNjZmbMPkamFLfyDhEOmbB1kwJkF2KD6/qmTxZffj71NiRzL53ffM+3cfZoN033NEOmZWZI6TZyk+auBHsxSH4GEoBYjxG8JgUR45uANoEVhKmHsJwXVzPGnvuHB3vNAG1unZiPcTCz6X/QNFZtrRuGJ8w/viMmMeoT/L95d/Hgj3/zblyCEOB5ud8O+3zJwyYguRYLxQkuc3ENFIhfZVOMGH7Oj5TZM3br7fS4m/+Xo5rK7HXcpnnq8EfHIPclKm/kkmg/dbX+TeiH4mG+VCmAYqv++RQf17KCZkrpOHPsI4qkzjflRjylAWZbg6N3bAcyFb/BA1N8njQe+sWe8fwvN9mPoGmWP1xR7fR0ji9F2Tg+6Pn1kQuxNIUh/2j9PZj/MZ2RPEt8b+64M5e7F6/PnXe9f5/QO70+W9Ufi35D7PyVhdRVDkE5i+4I0Ez0JhND9+P20udE59/WbDeD6A7A4jVi5CEU0eByQTxFdS43nOPHMVifvfEgGEUuak7H1w9ne58lOV2Al2GG7I0Ic9ampeBcQ84o/r4EA+u7HIn+nsJnxsre/qsToGgIJXVLxAoLmskK6fPfy90Fm/WoAJYfx+xe/OnDTnXO84KKVCEJz1OA0UvBjEnyDnMb8XUO23B/P1rW58/P7De+kw7nRPG9/bnm89sD+7zqiVIz+a/XJhf4rmoagiOo6gnZrTXEBVbhbDPOHJgv8PzbEogqU1i2hWY2Iza6Q8cJ7T99n6JMJgzddYDoQu6a9HSRYQbrcbqhljHT1Cg9sFw3Iyt+sFvXeUWueBpaoR8OsNqOsGIs3/2PsG5jHz2bamFG0GdhaNWOcvBsQogq1vmrNVWKM+G1B5op/sjBSh2RDjswwx5YpGwSLeV5eK0iwvfLVoiVLCOOU5e2VQGPOYeMIIAhqVkvIUFjN+L5cLqsFHE2lEqzsTiTAwBIXUWN3MQH1ZLnh6UoM1fB4MvtehgcdgUGEQhkXWmOd5wE4ySuGIYgdUlnSDvFjuboXN9UhePQBWm4/Lsmiu6OuTwbZXi9Y1uUgYgxUVgYwWFAp8w7quuN1u2NYVI/IJG72MgdbqdD5I+xDBjaADtSr6QARo0TwkDuIwoOuaJFtOin7idBzw1aRRRq2q40SsO1GZDgVotUbk+aUtCoNfLL84qaLCDR0EGK2NgGx2SHslmilNDUORUCUsg4ca9dy85iXQJnSgYh2GM06C+NcD+5TFyCBI9RkJulE/B43Y3bYOqitoo4hMozBGW2SRvVQNDiP2OzEljEZaJbkXQCkV16er0pOFFeswUHTFDRjuxFCoqPOFQX9ntiX2UMAkuvHP+70zfNt68/WX1mFE7w4o1KtZ+Iob2MmVzR7/A0j1s1tBSUYAgaGIOdyoaDTe19c3fH19hUcI6Y26I7S6ZAx/TSvga8GU2RY7r3lLbUxZAGwM4Q4uEjl2fV4VOvyKPjbI5ns4RT54X2cR9c2eJVGJaQgDous98qjGf6JKIoNYDUOB7VWlVEOqUbh2sXcJMzr3cBRQiHA3+PrECSAFMEWYG14mzZoR1g0zRhS5hU5HrVTj1RqRoUgNK3rXdbTeVqz9pqgnQ5TW4MNjDhtC4M2jrNUQXi+uqKNwigkHGQHQgLZoHnl1PmqhUFXebGsEnrpC210E8JRFPCY2zU6pJgibtO4309gRhzVDUxFh0ADQCiopukOkABEk4z2mUT7Wn8SeqekjBKXNvPcsjDKKoeVVSDHqdng7gkUE6t7NUKheKdOYOGUh/yZBpzlNyLyXYg27olSSkTvYtVU52QFBxoi1z4BiXca5aPJrXe9u2CJQLUA3k8+JPJuPb8FrKbf4WPYHqruzPt19CP4176XDvxJSZJbz/f1hDKV9fRmRqaTzYDxvlbmYNE3nFN9nP5OTV2rDrmtEu8sxHKnP2QnAS8jUcm9g92iuORI+JxRngbnTZ7wnDVhRA5ryG7llh+0BsRGZjq4DhIbX/9Ro1fqse0JbKgYJ5M0bbDwaHXzD3LfY995NHcquV11LlmpHPM/zTY3n2pQKugJyE3Qac+sAJbk8G7XtROcwv6KuuGIPuuwmbNDSPlY+fsnCE+MZKE1z3/W5mnMUNczniEIpJSI2d4rEoU2UcFaC83k5no0w5YijnrNEU6xM+pP01VN6OUsh+2cHbYv9et1VG9NqfFtE6UU49kFPW9O7pdDhHjzWK1cnBD0fkCiKl5gkakHuqRWT/xIc+U2duVqrKKu6k2zG51V2GOjbhlsh9NHRxhZtZ5tQl3VdBRN6UbG9085bwu6UpvKX5pFRhzh1LNufZRw1TNMwqTMBmwG9jCs6/w2rMFYAKwgDBE9YUOFZkAsILyB5nULtTOSdtkEbn/y774vATKWV7ncK7/Y4C+HZ2r3959/1dttYFwgqBDdMlEHCjPCM6E77/gpRQ7nMJgM6n28kuBDQIFOHTPP55d8a3v7uW50EvwFgeIeqm/O85wCwiKD9RHhqf8HggfVvv6BjL2/nffVRYcgdjZ8VD6zJudDdgN8A9N2qyeX4/b74HXntPWqTHK4f35rZAGE3/Yc6k6BwWOhn6/7wlN1ncoyd2ZkZFxF8NecTMWM6zQdOO5On7ApdZvMnwps7qNj6db2PmLwYaRgtKMFTbaw80HnMc4TJzbNq5ypTcv6o3eH9kTn75RF9UOL1af3+QAt03U89kC5/Ol0Gg9W03LvvsXr/YAYZkgZoL9vlsvWBn18K+m1Fq1WdhGJwxeR8Qa2CQkBtBdelog9BHxoMQtD0YcRpXpzfh/xwMl476tDyhYCf+Wfc6LPSC87H8XSNze1p98y3V+6fxcs/gQH9f0YR8U10D1uSCT0rDN6rB3LcMPfMWOuW3e9x2eCR73ee7yuvpIbyXPcj2PB/miJzXN6Nbg1jhgp4IzMuc+FlEYtKd4FuztzReJ4j1fbz7a+7P1we/dn9EJn7guNvj7qDA/N05eHxvoe/78fr4X0foN8f5c5usntOz5fTO3/jF3+wPO+QIlwY/rJ761MysH9f2+/LjWRXn5er0yM8yjyDwkjkSr8kB4ezkXFl1vcVigMx2YGtUsmXQ6HjRhOieXh2hOVz15I/sKQD2GbfGa9Y8PJwvM6e/WPL7zNemW8IgLEznj944o5ZfeA9dOR4/yIllEL7SB0Qdjw009X7oyARjTPlBxO6DdqvEKHzQBG2HLzFIhVwNy3Bj8w47JCxuza4VvpYstJHOK1fRJ5UzdmnCqa2XUAAFtFI2NImvPHoA526wvZxD6OiRhNWVJ5Q7HqAlYDA8mZ4DupaNQ+ZoIWxRVjQTdGleHpjp4FjqPHTIzqoToMrNYNLt6jspTWQjakbR0fvZvjvGBggnlE3gCnAzCjn+RRzpKKwxjK4AVrbUSDF8vhG/vIFl8tFI74tJ6MrnsVoANjg0HNqcHUqMQVg13ctraEsS7RH86mrAYFKwWXpuF6uqlSzaBchirY/Wd7s6/WKy+UScoFHULMp9pBk3uEw477/1IpmmqVSSxj0StX80pfLBYtBpbdawYNRh6YaKGOglgqulldRYL6hBAhhSAnYW5fpatPc7GL7zcxfi4jYRp37j6SDeR8D67aawpJRewtYT8CVZ26MopD7FCFhxERlw58bngY7LPsIKHuXI9WA568xQwOlCGnfV804704Hk9eQGe+VpsPoDFKoTNL2bX1DWXXPJrunlAqpDGmmdCGXbS3y2JYQ1YIiFa0QCtfJIohQSaHivQ0eVeWRQPd8hULL6zB7pZa5tfKUHSL/pKfHOmNTtvZc6evrkPxZN/Tm36JeN0q4BOULbq5NX4Q0PxrqBeF6vVqO0GRk9Xal7no0MVtud2YB94Httir6hsDmzAzQwyO4OwqrcbxauofWmu4BvaE1xRMKiFrn4+awofzWlN6i61xE+eAY1VI5mEOwTOfgPFeFaozrbIem7GFWh5htW4EOhbwVVgOrry24inueH4KGhaaB3scXEo4YACwHvK5VzR2LuDZYUIfC2KozlkK139Ybeu/mlCIoPJ18ALJ+q3LfHZAIhLpMOSWMY8B04ICO/3JZgt48+meRi+aAbRWVmxnUGTNyxvk3DOThQCwCSPexyPTkf82BSwBNw6KeRWMMjXUVAsjglUUmKeTXiEkX9n6y1DSCiWZTWGmfA77W9tgq0ABvVuWuPVvKPAOUUiynPAXv3bnQBn8UiDmNEIDSitHDjhDCsKfL2I3+MGcY23mywbUQxCNgPTLYxjbWYy1zTAqFM8DuPO5f5PA9zdWxvCvXUf4w14AbvajSLqIg15WRZvy5SbE6pm5wpd29bkwvoMOJlI73EkW9Xk/8Pbz/rFv3EO55wL3P947TRzj3vLaPI3E27MdWeWBBifmce0msByRenuoQDBQ0uMMAD1Z5o8xwBXI51Ikz+tEhUsG3AXqqGNsGdtj2McAraxR70GLVyPObOwVRtPPAgPfjQxMZiawvhQQMmkbnosYWIURudZdVyeUiOP9116oZQX4MdHHOzaRpaEIHUNQpzM/4kSrJ+2h9yV06LKt5j/8W50R7bvcERR3fPn0azzq8z0vW3bm+1WHEi8u2Q/drR5UZY4ClmwNUelOW+zAdxyQZ3IQZo3AgQoTMAkKxc0dxfgDnZRWlKvIUNUc7AXgMbMLmeKipO8iM3sWcOKuhSBVQRM8KYA5xHhQkmGk63AGR7pwQFdVqaIqSvmHdVkjXz+ivWHvHym5gNtk/6Z9cpgVeVeSCOQ/6+KRZcl5/P3dyR0O+L56dq/23TtB0hbgPWvtoWUnw9IDgNOmRpr8hTMMY4Sv63yfP5dSfTIwZjlmD8Aj8WYB/V6d4gian6HSQF75RPtpHX0uLaP74/HB/8Mw/VUm697vfE6OQxIMABA8D8nQoYhKxno/IdCpuRL8K8MWdUA42mjv7jAiuAG52oYjvNZNan8VSezqvYo13JxqAFDApstBRdzZGxxg9nEuChyW5wjFdhHKap3nvj5Zv6v9/x5L37EfFzw+DOVJmMDNuvYfjdKFjJPq+/N9fvuDletX0g6Oir5Pf+x7BQ9MTvn19w9PzE95eb+hjMhgRlbsYHDLG7o138lTuGQVf1p/U4ef83j/L71n+NKA/KGcHAnr45Rvk6sKY1yuee8c2bTGFqcwDRDBEP5yY4uJ4EHHddjDHeJrOGxVr+DsWWFqPeWlmI/rvYTw/CtP5tx+p62OC9b5020h3x0sb9C+ww4QpL3S/SoI3sNuM8pxEP1wJlDbr8PVOnd1FlCeh8HjIe5aU33pX8iY7D0O5DZD97/slQKf3SerMUbG2f/ePlZ8E+EzTcH6M2v6+eu9n/0y4/t7ydEizUGx+OFX6HmT7j5Y3q/N6Ykh/UmaDN3OdfREExP0Vc3rcs/QpRa3ncscHg36V8qYnvB/XVRJsBv2b61EFgB6/WaB4vGPSEOUXPCiPRvHX8IX732jngdjtP5LXeOYqGp3eDxVIXhB/aCHsOcGPPD/LFZNfVjwrPeMVbydP7mqJbevH2rEjpw+V71vB37/ef4P6BQC5KSz9JnsIyntV0KP6T7zHQxnMCks8YAqtzQR2U4RYFIHXVmozZbPtQAHn/e0e19rQQJBu8LHBFQLVFa0WfN1uaLXhy+dXXC8LhAoaEUBqiAYV9LFhWzf0rvmcB8+DYakDdahBhrxx4ggWIww3/pdawYKqh9xaNcpcGNjUsEzVlOKEyF+rYegCGgpFOwajXiqoKVyhG3KXyyUiv8WiMHsfCunpxtV0eBaTFWr16Fc1NrXWcLloHuhaG5gN9nhpmr93XTVPO0iVX1Wj0JfWcLk0XK9XtNYw8+imCHQ7VGk0d4rudkO4kp7lii6RR31ZFkMuKKBRsPQFy9owRsMYC8iUWq1VXK5PeH55waeXZ1yfnrC0xYxuqkhzIzpEc7A5MQ0e8AhTkCn27SBbPUJaJNrlxnmHkh8Lo4we8MgaCWC5HClJGqIQazMkxWizESBVHbgsWtgF8qCtg2XJ9HUa8bGuEMvX7jnjw7Dgi4YoFNmOTjBGjiPx6h1ajwMZYDCjm0JVDGWKgEgloGf8YkgPmjN4Kkc9RxolPjrlSnc8YYts9shT5oHedS/vRJHTT4RQKqNKRTM4bLV5p3arJlwNp81BaV3WtahRMmjv7EwnFmAkSApV8UNSGkcyZ4pmylOxPH4ue99pptK4mnIqtcMjUYMqbL7vlCZxsGLjl1M6KURgUkcDMUUcQUltKvwV4vTpeoVcL9qWbAAjzLmyHUCV8ar8Gl0jygiqECfTurAojGAXRfVQ+HFL+UCaWiCcYQajb2rw8Vznnq5BrJ7RBm59A9ZVIVglz68qgmDRcpm3Tf4GhTovM61Ea82M6MWg0zcbSkFHUjAaceezjo8hQWnKIbf93SBzT/Vl6uNHAhGjT3EYdq17jIEVKwYPM3wJtm3VXLbmEB2Q1vZPwczXXqrtLVTw9OlZ56ErxHIttFM+kjn+VDO6u4JujIFhueDHKOAyzVDMc26PZ7McbbuPgjxTdLrTjX0z2Tocdoo7dInBBJtBCynS3/IXO41Kkh10ukgjzokiB7k7HUDYnCYKap004k5sTNA14PnbbT14rO9E4SE9G7g0IQqV7/04OnCLwOgbKr8Ix1ouzUNQ7R/fimzfEZeb3FEEhixQS/AAauUA/Q5rx370M5LTmfxk1KQOWsPBjCvCTEL7O0FqWKlUUC/NIlGB3hWZxsfKDbrT7Otrahq9p9OQzy2lV5Xg27u+uO4p1zdviHuPBvzdOIVVas5dDNJu3CR+u6uL3HFJ8mMgENjNuf7IBFNQ/Vq8TeIZ7Us1uiNgE7gN3HOey5wtFFQjnREnLH4bYBkYtw2EGm0U379Syolou+VYHzdALmLyJ9R4jgG3cJMtvELAFlDuukeJat6Dbx5VOIDyKTcQjTFM1vM1Z8g8RPC8jmToS+YyCiLDgLPlp5g9JeQyl/HdSXMOuzo2cRinzGGJHT1Ax4Rgjiw85TJHUNK9c+7rYp2Lc5VfP9JxogrZfdv/nYOltFRk3nCmW9AmWW53FnUcYrL852wR5+m/oRhtXldOjyTpRersVTRtjyPpMEBFeYLvX7WoAbxWTUniOhURoI6OOqqhW1GgDGo7EKmOaq1Y3NDuBnVDiPGGuhwWDnrGU2Fyiqa/qZoSh6ac6e0fngZo29C3DWXbIL3j1je89Q4mglANx0xfm1kGIrxA5BUI/CPbQ/LECEwewST+1P5gI8dnDuXNuv5srMOh251fVKiO50b31Xm5iC6hDUDFjDL3rcanewUi17kXdVJwRJrc1vs3EVk+de16OAv3MbAYXfWjnvm+5l05XkmaOhAcJXOKrG48bxaAQwCeQHh75x1a20dK3rdMVjg8/+gt95rPyTfIzgpnRY77kDO1bxR3fuEx4cKfoL8NEVztjOzjcoGJEYLp3BswBYKn1AqB4ALg8u8/YfvrZ7AAz3Z2ZqhDZBHgrRCEVO4Xcfl3Nr5bKoXcvd2YmZCrY1S0cdjrEb5dPjaz33P/R2p81LK8Ro1FnNbsfWMWbKL4CcPOI1vvivRHBWskZzh5l23BIoLrsoBZcBsbBKojKMOCx4z/CjNWg34frI74tdW7vpzSugscSbb0C0qyhM/0JR6OM+wHp+d7Z/HPsi9/GtD/gLLzGs1/jkw7M/v0+VnIPJHOKn/8w6PFEQfI3KAH5bgJvxLhRfYw7X9U+bWvE8h+/E8q9cP5i9jBnmSXrikrzGDCtSsiYjqT0LeLPqeDcH/4rs358V5+95ZG55vl8feIdPrA83TYBj6yFX+rvNhwfv0n5PZPsl9vnrfPDUgubP5RJY++pF9CsMfMeZ4N5vnAoE89jip4/+3a8YoJe3q8g92g4krU37g8OvB8+PkHAuSQ3MMs9v/rFe+nF8bXd0TK48PfPzIR8fA/pcj+43HE8gHyXkV0f80xL9zQ4rC8xwOisyuP2nPY90zTuXmPpiS3ubaGbsbjMYYaRO2+5fmKJhe8fn7V/cKMVe1ysdzZT2bo7RAIukMDD1Woa45phRvWSJmpNGOL+i61oErVKIxCath3g7pFLW99Q9GE1AG7OJWeeroV0cMNAaDaUKGG3aU1LJcrnq5XXCzXdyGKKPjeu+mHtf9kxlI1Fs9xlKpKOIew1/QVQ3WtovcOM0x6FDIEoEIYW8ea8tmLiEFymwLK86i7wrxU1MpoS1ODr1krHMq3lorFIrwvl4tCDreqMMxQmM3WFrTlgtYHWhuaJ5oZy/WCy2XB9XrBcr3isqgjgGyb5tmFzZf33GQgNQwqlPLttqFvq0b0mOe356F2YxmJoJuRWkQgtaEbPF23qFmHo58GSX+l9ll1AyazuQHYpfAQAAAgAElEQVQVAEQhHQkc0PSApl7RZtP8KwIUPXSvlo6gdzXiF4uOLkSqyHRDvueMhyFDYEbTuBzKEakwYb8FCv0mtahiHoYOQfY3p18SwZAB6hpJMDy3JRWNjHO4dFcCumHZnvV6yBU8pjgFQ2nSYtF0/QkK7w142UhNttZ0HkoYrClFKh2jCavhq7LL0Ym7+FyqkQ6B9MDG2yaihiAbeqKGREec1jnLjBwRICKdPAoLALgUEHMA+YYsZAxPnK7cIGV9CxNW1Tng6k4PJSLURrf8pJY/Mcv7HkHthuVSKy7XKyCiBmlS2alvm0KQbxuwbfF+j/yurWFZLkATLOHgoTyCoBDkwkpPGxlaRXMoWFGHI1iEHXVFEjmMKYwu61IMGUOdcKqt18UU94MZS1O4w2Jw/Nt604j3YYrydFb6pghAnuPeUmkQoVTd2AJO3nKr69Jn8IDlaDWeb2gkZ8pqAKjurELTgcOdLy6GpMCbGtoC+tpog8w4DFKZplABkzuqmHFFUjvZ28tmfPH1tG+T06ciqCj13juPzERtkw+6arYEHwTIIOPnXhoG1DINKIA5jlt6AIEozLNHZNOs051zikH+CjAhnE1aKEKQkua7+BqUGEly44iPqfcn/baTeXIIesiQhNYUzcT3BeVhk884VGaWu1w+AQBYFKmwGu+LGeajGUeBjU4+y/llhZA/vP3keQIBKvagGrJKKYTLQpACjM5xXznw1mwoLzvDue0L6Z5KJX6DIAzlpxHox/O+37MzyM+I9929IXMiBjAbfneTe3xWa8VxUO9k4zKXtUrEx3qsb4mv+5rQlULpTsS9et0Ne2780/sFHHLCHOcJB+u0OWd9gFegXApkTVGM4op575zS85BJw46eQ97GVL/zHHg/7H6fU38PAbYWva4CkmFt1DU80lkC0Ch2EZoImkogkJG1DGTIE7A2qElxkpCmX3AjmeZCx5xTo6PZvwkd7ytFyPjInhLm8w/LXp/lyJEmPuyrSXe7U6rLHIVJHQyS3OPOiw7da2L7jj9nPaDzRgGDaaCXjq1UjVIuFbWIOUO26eDaFjOcisrDELSl4QqFdq+tmQOmprLyVFm1VVwuKufPNhtKDCW+KqKLhwQoOkdusK+tqqNmcdkyySwH4/m2qSN07Xouchl9UNW9xd9l46x7+ScEepLtI7o3Soyj5EWdx/GOCHzvklPW+qg4r/C1/V65uKeC0efFnjuVJuy+DgTsefEzHF4h+an8Me7RUq1d9edPgLzqubtOpCdgrvGYZ3wAETQVhvp2+VB3ey+gusHsYNBAd7z1x8vH2/jtMldv0M7JHQDCyeesBXJcG6k+ZkMTG8CF1K3qIoLrv33C61//DrCg+fMmmwjmGWu2QeaYGs9rfyEwfwaJQv9zomP1yWIsDNyK8/K5P3vhMVNjfo9eTfwM+Gvm47ecyg+XvTB21l1Jv7tETLZnFtt7/dlaizk43tfh97ytHU8X0jOPJlPf3ednzevzFSKCT88a8PBff/sl6uA7wqT00ec17SEu3dvZ04nK97InEL6mvv1DpuJ/WPnTgH4oZx6yv6o+IJijy9P6OS/HJOCmg46XryEUZOZgn0SQbHixyGZu9IOAKASkA1NEMEW33+/3sx0SPNf28Rx5LI+uZYb2rfLR+94rIWy5Is8GxhV7R6+9Zg1n7ORFbY9viuHenJnc/qdj/yPS3PlfvDcd7mj/XDDDk8E8Cm4Fmpf+3rmB7mhH8H4k+qMih/tyxPocCkr//vhq+vxbTP5vWJ6E8Gbw6cBEBnABacHPuNHfAWjU+UuKDn+jx6Nw1s1vrS1Ao8+dBvwQcCPgCrIcTpPPUHqGoPmVqv3+5dE4HxQzrgoIRUPQyZ66xAiZsIcxVsPSzGF4mi/8ZO08GodT+nqHufwaclpJI/vd0xhQL+T1n4xGtfhOc/zt7Pv8fcFeTaWfv4KhntTvvpEmOXzUEYgOn/eRMd9RgtZ/o8n4ldXsd/f0++4ANT+91/L9XqDf9UC9YCrmGMAGVaInJfvhQfZNKyBNBEQ8Ff8PO3TYI1K7cqSAR8kIES6tQUTwy99+2UfzFdJIaouW5GHKOzOOscEIl1DqCgarIQzOT4QD8hpwGFK91tqMmG2toW8bxuiR49iVYqH49b2eGZWKHj4X1tx1RKgGm75cLrhaJDpZLta6GeS6KZFiPxSo8t0OzyOshhUYmqddRDTqk2aUJcy40tfNFJRqWCc2x6OL3jbG0IgQKBS+QssvEFOqeHR2HRVdJCDlXalbakEzo5dHjWaIea2jYGkVfWmoo4HGAETfsywX/dsWg5EsNoduGEYYh2ekfkc3iMdt1c8AwVHQPcfpGGasrwVl22aUd0mQ+ZF72ZUbDDEzEIlFExv8s8vIhYDSNBKHx0BkQ0+aIK1F6Zym9jronLlDBmEURu19wllahFCJtu4Pvn6oDqMuzFGiz0gbsXXqxs5i+bdrQJ8jggXEzwRDIBgaTMYaGV1K0RzdKuqrvEa0h4ksakRzu7AbnkKiNAOfkGjEqa9N640b/2EKFzfOOoS3R5xXg0PmPqbU4MYYG9dqzIRjLjO/0ft3824IFZknlUOdRxQIEoGUgiJTcQJRBZYbMcWjzZk1ApYV+rZ4zisxjhoACjTnK/Yti1asAikV16uiJ2zbhtUQMNA1UiHnbff1H+or0iaUZSrRPV+vRnTru7MzgYAsYk0diAgECUX5lNd4jP/H3puuuXHr6sIvQJbU7SnJ2mff//2d8+04joduqUjg+4GBrJLU3XbilawdM4+jVqmKxQEEQQwvPAf5NK+92L5BhJXIlX2CLuSrZD6Dqs8tgUsxNI1lcYcbM6AXR8tQEVfWB38Inng29Icwano+cQGhFErDZ0QdB20ymbG3cEEt9s9SPwhUS46HNsvLGhQvvU/jMPeF4Lr7IQ2x81QaOV+JyFCVio3r8c1rQwnZnXOInVa75hwFDUIVvQ3nKNGedGepIozGmSPiNWTtITsnRwnaDucgwIzblCZ9n2tPAcJemztQxVzYGc6fdVqXyeiVClWdZDpSBMKGBVD7s8zm0IM83IJoCrgSnSKegmLjHG29q8d7rKeHoSSM+yIi3PlkjA0UhhrjNFOWxcZCxHL6OooHyOY57XUTr4n7ocD+iBYGSpqb4w/STDS6deLxqbhSZsk60qtMtDK9fxv9bS7JsTd3UjN29K3cTBRx1fGsjcsIBA8Hj2FIZmIcjhVQGBwpBW+b9h1/BzHvBgLjHtp2YDa+7++P+0wHcWV4bpRwhAOMnuKsMuTcoWvzr17tNJYg8MFTWrg8NMxBPP0fOYZCHTGq8U8VYBrSN3I/QOpGJPVLdj3g3QkKOTt/ssXraJS2b+Pocmq+bJ7jMbsRkR5OKuF4FqkgCtsJf5w7NI2+Kt5rUpOFnAcHgof6OxOBgs3YDiDhtYk9at75lcTgqS0mc0EbzigRPUsx1xcT6P0NzpcBCCGkI+lpt1z8Wcrr0zLf0Ngs6mxkjelHm1+rJc4L0juUzTnRjBbk64ltfRYXHaLujQE96ra+2NgbQlRvHZ2b5ZM21o9KgLI521ZP3QS1PY2YUaiCYw88LKjLgtYazq2BzjZnlqu8pAG+e2qYiEDn6CcrWNnD8RUQk6cKjwj24shZQcgh34s4co6ff3DuoNX/boaQI6IpD4eRuuZcvQZR3aQYMplk2hdD7orZ1jHvk8Q4XXiGiUylT9MS9Nvh0d5X7o/leKdAI0IzqSkNofHMAtOXxPcwhK5QHEDuhuNrFkgaPAxGlnscgbC8eYX+6Ys7Mbw15+0Pv4PV3m/r1HqxN6Rf9uD6GIUh94hki2lInvt2BF3RBW3loKuD90QZ++60f0zfOK+53eLCfL/tTxj+r8HMJyXNMsYzdg+FORGwdLAWFHTbwZ1f8E/A6X8+gKA4vAOW3+2ZBl8nmNmdU63LMgLg1TsC8xv0Xz+CfzG6qgrc/fIGwBc8/iZgUTSC5bruSD38PhCvO3rZMKI+bUS3c8DQW2wn7+Vr6c8t+/du6eupVl3+FvvTGAfxs605GPsnDAk6nItuBVIp4DnmzXxKRFi44NwaQFMdAPraIGLBDufzmggiPWwstOsXjb0nJbiN7D/RK9l+ox7k+YWGA1/IAy8tLxnXH+Wy/DCg/w3KJJd4uTRg7tdyHEIyGuuizji87JfR7qC332xDcr5RvpAZaIERGfwtkejf8MifVjIa5sK7wPr2OZRTcdS5Mh6y68A1Qf1moc2H/00bGqDd73vONh/kJrC7/Suw57tXm/PEZvFEE558/urh5j+8hPEc2I4/gMxhs+Lj5hkzoofQTU8a0fflJVtgRIwfdfv9NK37w8UrQ3A3mrsaWXxBgC8vfuwEYYpswDCqxMFfrlrPkYf4v67c7vzFOR+7/FB/WfkDE7arZa6NcAfB45/obfxPLs8f0vYzOF/b/9axOv8/OOIDY02Q/YDo0s3DWZ/ppmydBbzjDq74a4r68yBGCcObKj7//tlzGBeHCF9wWI64u7tDDSj0KeJaPEozFLUEWNRND4XKFt01jI1E8OiNUPpUG5tJvhFVN7xaJB+XsvkdauCB5LhrgS4TUVwRKR0DqKpuCHPl2i6COv8BBn/OnLBy0gWN2lZ5IwKqFpYXTkYEi9y2/dTabcYjHtHPriQzmPmaBpI+RWgHDHRnQwfJyJliUOAGxQhoa9nu3iPeyHIxqkcikmsIuwqaIwcQEc7nc+ZBHBByms4F59MJa2uQ3rA22TkccI5Bd2OXGfZ7HiZrrVjX1cg5jNahKqGJXgBzUCTLKYliil4KGEpyuEsK4xQ2OYx1CvJGGIYJIPH3bpbUONCKCgyJ1eYwjIDwT4tYt7nvTvPKbkydlIJm8OCMrg3IdjMyqgkbkbQvDO/+v4gqY1FoEctpTOTW2LEeRsR80EFNmHza90kIrGE6V4e86xkpNDrLGV0zEGnFZIDCY+kkzU8qHoLH25MfQcboigq6uBNN93yjQafzWHl+zmvR6Kqeu3SKygfcuJfzGVGw4axAuQZpus8yEOikFZ8MsmQ1BV8y23DA+BsCQ/N/ASkePC51eUkEDtNfCpbl4MZbJLqBALZGezdoW/Yoyd4cXWFI4SlPqdO6r0tx/gVVR/KopgTS4TigPt8oY41wIZRKqJVQizvBsEBaM2SQ1qDLwesyAbgURq0F0g1JwnLGAhrRMj4vFN4uuR7IDznupMLFnH8CLr5UR1wBRC2yvTAP3qwCaeJj1jN9Rzg+qCINyL46DMGEy7Q+ONeH7S8LcOfIK6AR0ex532cVfxihRYfTz4aHMHkaisnQiXBcoKQrs5WxwT3HXPrd41TifSuRM5xzH0ynNO8vhy7AFW+j7aOMc7LL9Kl09v3Sv9uWaPDPuTd7c3K7Zj97+9qWYNSuRibAoMm5ALLdG7NCvTyt0ByI5zII1wXQAhBD1nO2I5Bu1A/wSXvb4bssuru+O+A6ex2XrlSyuaQT9wu6n55PPuJ0Gk5dkcaG1JAyxFMQDK49nPDtEedqsRcN7o5SCdBYl64KZENCCJknbPzmoECgvmXitsfxNIAzigTlZZofiF8oFL3YDiZuX0p+C6QPwlAa734HoGkKC8QIWy20AnxHvn8QTBXasXEO9yI+CHF1s4f5vjvTTxiew3ge/Z1RWLbPA5R6AQIfPf3LORmVUcpsfN4Q6xj3nGPqMMOuPx/oTd0jwIkM1cDXsCFDDQcTBkFcPnLXVOQa9fdovi97Y7/Nean8Xaq2/sNRaoY0HiM7KasCPx5DZ2Bdna7j6UJP3DM7N+2f2T8X8oO4PKTKUx3msBupK1TYPn3PD96/t9GnTABF87UWaEnGGypqRPEUc8yEI2cZilKkXnIn2GVJubb3huZoNOznhFIcep9MHmMOaQeJOEXF+QWbo0N1A32pZlwSd0ZSH5MRmd89nYx9ikfCCzT1YrEj0vTJcIfLEimYzAHWUiAOp+x4yN4b06+59nyS/Mch58TnoJjbNEJXr16WZQqIKRqO0XbvHnZ8wVa3FjWeoVjm9+r2uSg8ffZPX1DfTpH6vv62qYeeWxFPFwJw/45w+t2gxJd3b/Dw8XPWOrt8/e8vW6q40xCDDHpfNRxRzWlZGrCqrWf9DVhorK/gKZHYwfyLjKMGGA3zG4h8whmK+t5uagTg108o/3qLu58/AngD+vUjmD2wTEO2BwZPjF0w5KUrPVOknkIc/QzJp+I89p82y9s1u/m2WWi0uRQpRuL62jruDgsOpeDUrrlfeJVqz/bek79ijoNQxdq67w8mW9VaUFdGEwVN8xQSx7XV+xTvGrxRb6Yq+FG+b/lhQP/eRefN1aVGHZujqLpQP7xHATLY9vBunQ7kohFrAwCWQwcYQmgyPpe38zCbAjc5rNP4bvcPL9GrRvTp6xeXPQNS+7ss3ekw8g2PbQ6iY0h0Gpf5cDOeIABvU7incd+kWBDa8K5NuTCk32g/TaM2/z2fi6a4kQtGynnPVujfzMVeMKP99bHp3opEj7/nw9KtiPXwXI5H/z5lOpjtytfQruUF2gpF85gXvLXDtn6CEHCPUA0Nj9Z5Xb+svLCFftucu/pEDjEfOSwBnCYD2b1OHpq716TQfCMwNZVFmzWE5DUjh5pRcUZJqR3JU4t5dW4u/O0u1vX3LXSTfk2IfgXgy+bAtL/9+wug+/rnkfr2d+9rCeP5+oLnXvLm7zcqT7/95i8XzPHPLbc4zy3BeKaja89E6Zu/zygoEKy7I8JUwuPLFVCFDVpWBWi9gaTDtjlFLdWjscsWyuxKtYBDOrsyRQBwtX1TRMxjvlhU6rIccFgOuDvYZ+Q1bhFd2rrlf1bd0iHx6LF0z3vpyp40JJeEMIYrpII/KYZh1mCUm0X6BTRtGDQ0FENXUpioppEklEfdjUBt+hcw06Fc0lEJZsN6cwNzGNjVn2MpaUDMnJcgtLa6wc0UKEwwAw8HhLJFoByPRzPUumKl98jL6Pu89zFgJ6tHZKsMQzdcFhUxv/lUwrrcGIp/FUFbm+WDA3A+n9DWNcch6mjN8iCfHh8tv7u6IbQ3ZDQaFaBfRvIH9CRlJAxnlLOWAqFiyuKUa+EnWAFNEPqpSGQz0zomus1LI1jez9C2RZtsD0vnxmJKxZxHmSKGFRaxzGrwvySZbzsgdM0hoKBJB3lEthmoh3Il308AcUSzhzGMNlqBVJup2h5PlMapTmpwo+wwxmrx+ZEnnXMcC7i6sdDTH7DLCArvE4nb7s1pImi8Tw4jZgRSj9y2phb1qG8Gqju0aNC8KzuVhpSb5x+y/OHJulZfS57zO9ZcOtSQRUKzMorqcDjIo40ri5hdgRyc5VKG20RrA6BJYRpzPJS05tQzbkauj3BOiPmJSKwuHU3WNCATYDQCg0ydGuLjwJbPfKk2hkQADCVjbR1laUYWXpcK0JrRvQKec3ScfaL9pvi29hvUtRnMqQgInBDfBrsqCGfiNOIxnF4KylIcaUAh1NBFgfMKwAy2oVBiNmU8N4/uhtFzV4+KdvIxHwc/4RC5EwgA0hHdviwW9V4qSi2p3BeNqPeSDkS9NzS4UX9G/p+CaW0/oOSpIHde4OAbFaUyChWU5QA4b6lcEVkVxHmCwbYbjfRmBklpffBTTMYIVddKax6azLg0DM1h2CaQG/N2JJf0aZQcKC/kqR/CEWyKTQeTGUnU95GMYdLuCjmrnea6Y52Ppk4KfONBZsRxWkkdQygIYxeyT5Jx1cZEIf0MhvGNcM6Zjfj2fn8PjL8pFLJ6jnLvMwB3DGnOo7Z6EoO+NJ4eUdxjRDGPal7ey0GziB88nraPXCm+h9JIIxEOCNPRLI2wVrfRQIk16uPB5BH/MpxvwiEneY+3KyMIQ56Lut0xpC7GW6oab4iGlFqNd3rOVwm48uzNrLfyK3uj6mRE3owEkfPP64et9K3Y1BbUgrHnxIDl7S5rxf2qbgSe2owwKJIxAijCiD61/KLNwEQhGnloR++szmjFFBlI7lA+d0iRObhVY97sBbIaMgMpT1GLhPS8cUeKcDQLjeKQW9nP7va7pQYBqDDYw9oDtJ18HJSRtKkS/SF3NNQcV8CREESSniRHnlPOBLnxXdn9/azD5PvNQMRR79q09mbneqev1N/plRzJSthRQI6KjsveJmwi++P++V9OkUbKJ3NClVImgyXcmO0R/arWV3E49WYySu8C9ihBDmcCiMlWag5RjRwRyM8+hWk4G5DzKWJIQzoLVt8Hl+WAulRE9vVSqslDDrle3BmsqKILZwqUmV+ZgweyH4VN1i2+Z6uqOaH5HKSTbciD+c/PRO68VmFRs4KIqPZ83kRYKORRxvEXA0I//T8bB6t/O8dD7sKmzPPhpBSTt73/ik5mBKBQ3hq0vqenCsJKgqMSjv/1zoxk7z/mXYKAaB+R9ud4Pvh61uoGcAUYr9D006av0acFgyZVv6B/0My5fvj5LfDbR0N7E3O2W2OdgTbvo933425slQwn4vy7XX39378AcKfl9jseP45xUBhs/XOIhF9T9vvviDjf7seXmsHrZcYT0en7vuhEGzpdsPEesj45Xb355ScoFOcPn3H8paD9bmejLx/s1lXNZatT0JLNYf2J8PBbOCQB97+8BYHx+dcP5lSviv5eIAScYLIfESAMHN5/RPnZzmb41zsciKH/8xsahg1mjMuQ96xbcQbB9vfJeB5oeLNa//kAptu/Pz0zL6/nj9ydO9aNIC3x/gay1Gld0RydSVWx1IKzIyFGGRzMyqfHE14fj1gW4/e557juoveOw1LRe8Pd/WsAFhhx/vKIZVnyXDibz0OFcVvqiN7N34zP34HxuHvw60b3pvT7o9woPwzo37HsBbFri2JEYNivb5UhMDiGpysfW8z2ugu+W/kTs0p6jk4fTHN4yP610Z/fv0z7i3/fegbHwSo3ot3vgL446j4OeuOwtv+dxn2XTz5Z7vVrN6toz3ZDzd9uzL3S9lB867799b8HM76+HX1LudP5wLH9VAK6fgTjDSre4IxPIFgEOgF45QuyKnCPrzWiP1/MWD7aM/Kbm/g9+9UH7Lhgmwd9LkR7RcjLyjzn+x7KpGy+yP/yNyqpLL5SBEDDF1N24Ho//zcVwe3Dx/VyRev1kqcI30Rv/zHlypA8x5ni9zRiT0rC/XN9Aiubj5j7e+Pvho6KYgf51qFFfZ8SrLqiMEEdInxbx40DrIevmHLXFLPww0ktBYfDAce7Iw6HBTXybROhnc9Yz2eLyOw9DckkHaqcOYvDUGWHXI9q1bGf2fAMA3UasnvH+XzG+Xw2KPd1TT4UB2YKrVqOmWZuv4isaL1jDYguN/6284rm+QZP5xWrR2BbntqhXKTdJ5NFMcfhNXJJq0edczGDxsgL6HxGwpDlBgbFyN+c06OpPAtDfs69wy4rBiRl90NiGLnX9WzQ96WY4sGhuokYBep5a02hvq4t5RrpknMokV+YeHJcaBn9z0RAYbDOEVIDFjTksYjaXpYDlmXB8XBIJw3pLdueCmyXawIZQGI8w8DKnOiiXXvCTrbV5lNivh2+PAykUT8TWQxWGM8THt72WFLPJZrGfLL4eCJQYUsBcFywtoa12NiZElJBa0TcuENKt51GxCNgyWTFWWwgV5CzDsNzRPKkEdLbEk4WkZe8MIM8sokLZ/8CShMEiOczJRGs6xlr7+hqOQDF6XG0JRwFrB1Fw6A/aFuBDQR7rHUA6dDBxYyrkXeamDesM/ZdwphrhUN0w1JUlDKdqdJ4N8mvM0OjIYG7zRqJwkFmAGCC5R90Q5zK5DzhfROfy4Db51KAYjCrDI+8RoXKASBYbtCuoCn6d5Y5MnJNvO1EZjQhsmjQYtDiptyWlKcC5n713OiYofY90jxskRPDM8U2AVQrSrVdv4lAWMHdRjwcZYinCDzYOmgd7iTQ0dYGVeC8ns0JazBodHeg0YmQtw4U4TAyKQCZM/I28qxH2om9AT2i/ZZlGby7NZzPZxDInKccaWXjKOFrx4wOkxw7rzcCqDqChQK+1O2mMGh5XZwyt/GBeF+srVDUhRMXyeRoqiMSyA5roSmQzTtkc5+TbNAfFX/U+G2kOEje6nkIBqQ3NiWM+BfHvJ3gLhc3DDkuzhyhxAz/n4hyDRoIJ5UU/wK2mWlOO45BrIOepo4njSvD0EJirDDMILOhFx6FL2zrGX0rKU0q6Qt5i54Rc2/LdbpZc3nvZgDGVyJziiL1dQFHhiCn4cVho6dxynzowdMAj0KnjUwS95ZSck2z5/2gMhytkr81Ty+wG4d4drSdNr/Pn/vrQDgrXx/QWbFvF7ZjNHzKds+7TJGPXOhKBLQW0BGgIyDnwNqxVBZxrrsm7Y6tI9YT+96zvZsslNb1TSMeMfasdDjRAW2OOtYOAHdAmvVyk9NAjKPh2g891sTgQ/eXTqCxt2PGfwEGCLwOfY8Cc6ZjhWc1TyOTvUTyXsooVY3fQx859yHnI+QFm+Phb5Pcd9NGhGHQaTrSI83b+bUlmZQxyZUBOT/37dqqjXaJy2XSOzqRr5PYKzwdAABV40PczYnP8iV7uhZ/4cg2b/KEiEWzNoRsY/WvpaG2jur7mLG+kAXsbGCiYgcaPA95Q+/NHVhL0l+MfwkkifzP9yKoWQO8jUwwOSwQiXwQI2XIBmFLNOV8ETGG5P29dv5UuMMRGX3XUkDF9slCr8E4bedxWtrzmrycqGvXr9388jLTVfPK0nmDeEdD/tsFGV3S1grFIdMvbhsZe/q1pncQjm9fbdKKWlYDwn6zjjX8XCH/ZycOM/hGYSYcDz/hhN8u5PAFzwdW/NXlJr3sr++naPp+1MkQL4L1w0esxFjfdxSizTsC+ZNhy/RegbMq+L3i1S9v8Pje9MLr/3wEvQMO74DYEwTBBynng+Holu8VTX4DoKj/512m37pWNnq0qZN5DohziyJlzeARXsPNuv8TyoVcdZ1hADC5eN+ePokAACAASURBVHXnssLsjuFmQD/UgtM6R6HT5uk5sJXD882LicnGF7kMmakwp1OuAkDruY/NxvPby/bKPqWaa5hg+v29If1H+T7lhwHdy0V07Z9RUtDEJAD4tbgYMIEuCH/KswilUvGNKj6Nllr0jUdwbqOocfF9379hw3WhN6LcdRwInujKv52xXhy8nrx5fO7Oo1Y0DvVTvhh/yavcJMcBJg9IoFF3KkxfRifEMe500aCN8Zwu53COGKArFsfcqKdz28hlvXsXD1qxg8Q0p1OfMdPA5kA/bx63I9YvItHzf3+HMh08v+KpPfR6zP7mYKAA4TXM15YTZfVebR2nwZyu13mtvITK7mD1HKfzQ2yeBOCRJ+KAe9r6TnvLeJ63E10OFI3e7z3yxu8AdMD/AsDIAoRce37jzSa8hGy+w5nJ67hey5lMoI6ehSdxUaB5lIGVr2OUBx3Cfvs38tjIeT7DTxpfuUfHA043nrvVxBvs5+Wjwc/d+bKabt9Fz93wXcp2FT5/fdoMxgUa+all8nh9aQsICxgGx2fRDuRQrgY/JRCLdGDLvVjnA/hNpYAbFonBrNBHBb3yX5gt1/ndEcfliMXzAS/LAcxmXG3r6kqf7gfIoaQgcWUVdoZgdX7ikaZheGBRcO9oj0C5Z8u7fT7j8XTCeV2x9o61dz/4UNaFMroTv0QEYRhZ11JATFg973XvHeeHB5zd8BrKq4BmDj6ZEWPRVrfOmBJKNpHqqgo0U7aVUiyyMQwfEo4Bfbo2PeefCkXpxQw6rvQbxmijoYhCjwh1g1JWPD4+4nw6oS6LRaWVmrm4IwplzL6a0dlz0IdycTaohJJwsHtCYbI85B6RC8LIdT+RWijvLULOouS4FCzHA+4IptQXGXKJ91F8TEOZZ/kiCaVWP8i6c4TCck82o791dfj5dXVHgObe4blrWaQ4wY3CPm/qRETkxlBOZV5ECw9HgAWHwxFgi8gSMSh37t2N82MP2MLBd6hHVmYOUQIIVk9AMZvxcRgCQ+Yktnz3x8NxA/tfSgE5Xc/zqrneCerGQllXdDSoCvqkPE2DvCrgigKmS84kYvnT29rM+WQdDjP2kEdChmFUqisabKyNxwwDv+MIeFtsPDq6RwMTqHSQFh8nmoRkv1nHZ7aXTaZJjqvw73afSPdo4mbpDiBJ86KO5lEC2cHGsdYCYqO9qgoczbmod9lGE3vz0rjo9CWtmzNEGJXJ55fc2aCUcUYJBX+XdAbR7k4pDpceyhaDTyUstaAu5AgBsb8ohAGWjrWHo0cDgZ3UfT3VCq5LKhZbW6cUDhYFXtjpSyuKpy+IfNM25AzinmegiJbLs5obfw3FxCJlIwJ9qYs5bhQGOxMPHsVkuQ0DLj/6tYIcycNeOI4umnsWuVEbbugXtXzTpZZEcMgpc81XrFuF2Nq7O0DF0E6KEloLRwbknhA8HBj7OkKJqpicNMT5yuTkLjNs9CSren0d1sd0HKKIMAxj7FDq2VY1+HTyecU4D0YHyXmE/005du68444BoHAyMVqG6iYlAogy3UMY0ouGQ81wTSUeRreQt20NM1Rart26RCoP8mFQR9mgfHeOkroTmsvuDEAKDFUgx3RiGSEYzAt1vCrvye/bo96VMs7HLoVk5HGKWwnVTv4i+wx6GNue7W9cCNoGPzH73qwfIlAlUB/jb++xMaqu0GVmUPUzGhPWR0OSgDrPKDmB2X5z2rro4tA3TG3Y3BBzPNHw/tw1o/5sTptOrOLnazOShxOLz+oMlZCy7DiV8l0Bs0WBjXMqQKhQ9KS3PMXSaLUNMixE0IckohTV32f7I+YnfP1bjcFj4GuTFtdLqc+/p2kJhx2iYebO8aTxPOdaMQEz156PsYLMoYoAEkpfGPL7IzNzjr2/I53vo7nxDAHN1zZzyXUeejT1WsKJR4JPIOSXGBMecgfccY+c9jfkMMfi62YBzm2cR3xLLz5cLhvbmtXN/flQ1OMG4kjT1EM3VwIFid0JJZAh2PcAkwN6tzXYxSLvOxTcFUom10EDHcvmu2mLSUHh1WSh1ZyQmdie9zFMQ7w7Np7XhrWZo2r0Z3YGA00pajY0SwFzkfRGcMdTly1nOPpJoEcY5GYnYBHF4c0rrO9XrPoJ4ZtkjmX2pKFpvHX505wMncWhA2nQsyXgKGKY5ONpzsd0XZnLmQaeKGdHWThcCZLZFwXw26+/45DPAge1lAcRfR6OJHc+XCfaUWScc1Wg+IyKN+j4lHII1CKZxedheffG7scn6MfPWP77v9BbQ/3pDfTDRxuX4A+TLSPW756vhhNqIANgx1/F4ae5FKgI7t+9ARHh4cMnNGgC2i2gjRH96DWcLmbhmXJjsHdb6hNzef0Xcjmy7+0atH1iJmkAuIONUVFLLcU/v4Wqov32ESvZvAkIn5OfTfr1rE/xBSk2Yfn1E5afCOcPfq78oFh+srW4vv/o+IHAl1ifZAZ4AFgDkEkIRT/h/v/8jNeFgf/7KxRzJPr1cs14Hg75aTzXmXZuDvST5U+OCwOw7dN+lmnz+55aMM4R2OoYQp/UxRzgRG1OCcC5N9TKOHqU+LkPVJp4X7ypixpqT2y7GtcFpRSsveN+qVAxvc5yPOKnZcH/vP8dIKAW14OF6Jmykrfzoq/bPc/eR3gtb/G5fMZRjRYuxJ6vLFdG8ke5Un4Y0L9jeXLjdsIPQYVAuCfCw6YCq+HThkvEQW1bO20fudmQ4XHuwnkIyLRjmhcX/kZlyzW/umRkwFT2BqR81fQeAtCZ8IAwwj/diP0BcvPbrgVj/p6QJHavu4GubeXiRHCtfdg4bmb/adu3W216SST6nun/JxbCNvo8rpGaQt1gmADgMwhvoFBUvAFUTSjGJbk+OBz8c5Hoz43cI2ka40NYv1Mzomfk6nSyPHuFR33OgH7549csuVhhM23lAflCnL98z7Ux+7uUEKCutbGo5iH7a0ocBL8u2vuPl4R2zDbcQfGIjocNTPhLyhy597Wzd83B6B9b9ic72vxx+dONMtMpYTvPfO8RR0KQxz6MAmrRcBrKxzD4Xn2XIiiolGLKnXuDGoRHk9al4rAcUA4LllJRqylKmkckd7iRpBZUVKgEvLnxCFGBdnJjqb/TjcAGL8yWx9SNhvKoljuQLcp4PRl0+Hm1KHczRnjUlRK0ukKTkMrHUGx2j+ZsvYFWN9L7oaX1MJivkIjAaM2UhAo3bLqhBBGxAjvExoE1xjWNorYGIlpJPYo9FdBEGwhuZjcQBvS2R5LNBpGMWsJQWirghvMwNJsx/Hw64fF0MuUBMaggId7Joc/DQG3tHVJTIQYVc3aYD4Gi6hDIjLJUM+qpolFHoAqEgTmjMv3+Wi2CNyNqZ3mDGFwsGo8jGgdkqQi6Wwm6R+lywXK0yFXSEQEmotBuBrbTaggC59MZ57M7XJwbhFZ3XgA44K9D25KKDsIlItQkPzHSQGYK8lm2ciMXFCRIJQbRMLRh3sdDXptpyEOq2SjOFMQR0c0MFDaDozuwmAHdInctwpccTtQMhjo5a6qPq7RhKBaRzLmmGBH+c2RwQO2HgUtCuep0Z44pq0WOO83Do2/jnzAn7Hw6DxABhQHPM1oplNxmZBSP0o1IwoCJHmtvuP2FL6FESLpiKJT9/ojcHOkKDJ5UuriRWzOHfVfx/NjV6KKYsbZKwLJaVHAhhizi6U51QMxDPXJLIEoAGKUCBSX3VlUfy2ndGKlzwriLKqSFMjty1Q+Hj5i5yra2WUueQ9npgcicE7hUVILbomxcAva/lOrRp7pNTW2Ly2DqwY6o0dBQvX12M5diUP/+EE0ya1BgoCIUd/gIx57ijh9bhROlwshYgqeoAJmHIoBSDIGE/PxtThDG522E7e0ZbW8Djd471pVQliPU9wZyaGJSzfUf82RGCZ4M487PMYz8yQDirLQ3NLqhZzr6J/+ao8lngzcl4gKyzlAiZ+ThJsQemQMzFKwANm3UMH4jlHZDosgUBhkIEHXbwSgiPTMNgA7jzVbWtbVJm6j32PeCqLLJCANayiU0FNnRrogOjnbHw6NvmnyAQZCFgSbT2HkbwoA/nZX3slA62tz4/VoZstm8R29pIB2jRIEu0DKiHlUpHaWY4LD3Jt/EOHBhQMyQazKa2D4D2jjoUaGEjPbKQUqZmmEO2Jj1TymeTNdinOc+ZJ8398UI+L7q/d7qFGii3dkZbzvOMY/x3vmEmV3y3wsK+Mjedoc6J93MbbQ9c8vvJtRXyeaUQxQm6GkunX+oK+dTlht3GZ0ubmhdA22JwRROHqGfcyj6zdHKM5RziA6z7iVMjJMre9Cxf4bDVs5t8ACXg0md5yB0hXv0ptGnDS/DvFbsWwFl5Hv8Gs9rGt6jR5qVjGEc9YdOKaWQ4IfYnnsuSvKJTXO3t0xtCnkvnDED9YiVAd97uUxrlQkEdgcmSiQgVkHv6jKO8SZRdzWYzl5dxJxoYShgHIZ5GJqX+v5bVN2AbggARJ6T2de/5S+v0x5Ntid6p2e+OShp5j82ruIKQnFHvGslaCEj0mM96ydDLPL3FbjRnwhMr/yTUYshXlh0+5es9YLX6vwlrm21i8kfZsXmM+Uar36Of5/J96vp3tgf9nrZlNdpvnBlL9mN79zdWNfl7Wv0j59AIJSlovWG+u4tzh8+bu7b/32tzG5Dc0qE3E+DFvzM2T98AsOM5mEgJxicu2adxqP+DtHpIadcHYFrtDSVkJkiqYd++IiWZ2r77ZFoU1FWN62pGH6BB8Z8EFsDIdd9MKeL1fefDuBOFKeSnM3E6anq9quC/tUnPv/MOKShfGssH7JcyG0vkVr+U8rNHQDAmDVRAcOdPnU4N5/WhvvDAcfDgtIID2u7Os5xHq6eNm921BAoWBXn84paD7aHSJzLyQM5bH1BJPe5p9p865flp4qf+Rc8fnj/5Kj8KH9u+WFA/05lK0BeFjuruMCnwGsFPrEpV4DBpPMATEiBDrhy0MqtcAi12Qaaf6f8LSTIiF6ADkH1T43E/7PLNzbNNr8hsO7L/lgXypN83v98pb4BKiZkgBtlEkS2b8mfr7aEdt9umRw3MGV+dyjJZqfHWdCLl85wWvNbg+5udml33yYSfacMGgq7v6Y8tQZfUu6veKTmAY3GZwPc+9QoQghY9DUYr9HpM+796TCY3ynhgV/gWnDrhul6RLJfhW3Jxm/F+pvQ7fmHU8yu83tK3DuiBCux/MYhmEsKFhFBMQPDbd+cxPgsD/2rikWhX3OA+fpWHqYlGH1dJuF+xCVta78xaiYUYspt79cqdjxg+r4/8AlMkG/4+h4l26AbI/JUhYRUeH5reYprPfv+P1T/H6toM59XDnd2CBf3mKXN9Ze2aSiWFP2ho9yV/MEOaQLWEja8F74gIohsn9OzmlL3YEg5pVaUpeKwVCwHM2IqwYxRHi1XSsGCJaPFsMJzHBs0M+DbSqwJVQgRuAPCgk4KgpgiXASigq4N0hta7zidTzidzVgnYockgh1aQj4CYs+KyB0Yn/IoTFFF4TbyP/eGdjaDmquLUnFjTSWn52mNKryPYXSYFSRIWSHGPvdVzyceBgEuNq4ZnelRmLV6jvAwLEzG2NEO+y3zwQfEukdfr6tFvSxQsBtezXA18omvraG39WK9huzKYRCFj2GtkFqxRI54h8M/E/m4jujjUMKRX4sI29bWAb1MZPJOjBWPKDB4cGsiZrpxgLiAS/U2EiJvMTz3+7KuOJ/PWJZHlMcCOp1AdEZvhN7FxrILqKvh5UoJ5NSMWjWF4zafXLaBbec0pwzk4RmwOSxcEvePXF4fkX00aMQ7N+etm+URJD3YeHL1yH03oHO1qGD2fPJBc6ICiohXN7QqBqxccwNOEFPuHeEcMRk4I1c9e/2qCup9gv8U88gPFAIomMzxTHugNxAKCcQhPm3NDkhbJYseHLmv1dazaub9Nvh172MqMMVTThvBDLPXDk9Hh6yjMOjv3i2vaXOI1FR4i+cTh0CdhrkQuJtDkBmMLZq2quXMThhzp/dw1iExHhVGCxAblKr3I5AoQnYPiNVSFL0xOpmzQ9PA/HGOH8pt5yVUGDTJnwQzYBBTQvhyAUpXMxQQm8KYYc4XhVHK4r4XHmEc0O7OS9d1hZkTzLlhGArD6EeOrCDTsxMUsa9TZkehqOyGAYtYy7nFcEeO86+oQdLXUlG4IIxCtVYfA1uvXQRtPWNtzfmO1WPrwVG9xSDRVRTt/GgR8gaR4sYFANKgXd0oCUgz9bFOBBWQrzl/mxLrzgg1T+884KEp+FYfRsU0mqUEYXRIQkDA9bpmznQJNIRExJYliQSRaZYoFK3BxEJ2Rx580kAd8gJFZPwQHhKW2c1jAhm53fcyDqk7JfTN3qhJVbFHY/Qnn6bM2x6VK9Qj8v33WM1uaI41j9S1AKg8H0GyLnSLIM03Toab4Bvj/t3z+zJNfTTZ2CrNV3PuiJxfeWgjEeX8GU8EajgsFYb0jrpYfGRfV4AUuppTSMK7O03UUvDq9T10bTamrNCuKJ4TvXhkv7bua7oDOxkUuV/trtFuzvad3hQ250TDIx7U7A6P6bSRyo1JRxNjOl2IrXKer8F9gMOheOSvO3DeFehJp7QCLlPclH9pwy80qXSij5BTABAFZoojgCwuN2mgChhtSRFon7EQrcWR+uZSNzPGxdQvwVe9TY62JNJ8P2eEv0zM21av6GM36XQiWnuSbK1NGBHl6n0GF9ONiYDDoO18SiHOs4djDQBz8AhHI43GhewUoz1kKWA6F8e4ORNKWSj4h26j6uHtcWEp+z2k2C3XCQahgDnRQcEiKBhoO8oEoOQaJjhaiTBICEyOlkRi6bJUocIwsKKZjyhUCAK778wNoHO2yRwTi+UBVEuBRX0gUkX6DyYC1Zrps4qjF7mnCCiE5GlkRlQ65ZxA1eUX2ThVbuRR//ughC7ASRVFBO3DR6yqWN2AHvRcUx86+NXyrwMAgmiDYKZtr/8mI0Wmzsm5RXL1qX9PVJDPeH1OEk8FMqxOvOed081cT/wSPrEHcCxFrL7ez1AcfcSbmgGc1SLPI784585izkztwwcoCJ//7/8D4zVWD9ChQcpJg6qKQ0hde71sDKtu6f/1zz+5cc9QFKStYC5YP3zOXhYAg5ttRziMgKRbw3roo/ZrcV8uZ0pvXN/uNVnvhRPCcDa1n6f68kwwysFEOLz66S3a7x9xxkAU6Ai6SDdD498UzkVb9K08A6riM2w87mBBNtG63wh4g0HHDxQBlVZCp/vaZSwm0zP3X03P/NN//4zH/++3FOkefYsc++cwlN82nm/H4N9j+nn5S55avZe1bNe+7r7va+tdISSo4eDu+wjB9ByvX7/Cp0+fcSgFaw/3OOSgra3bmeRQcagFj2vLd7Zu+92pr6j8CJAhd6kqDrXitK5jjyevc977royDJLLr1B8C3v/+HiDGnU60+ezo/Sh/tPwwoH/n8iT5TuvgYsHQrYvwA/MVQWPzlXZ/jsNZeKIPuCc/GMZG8Hc2nn/nkqN0ZQjyoDwJ6hRKhbmOODymsDjX/PI2zH/fjzPOs22cP4HrkeqKr9nC/plln/P86pKciuxk/UafUPX18Pie6mX/DGino0typ2uT+h9Y5iONyEC6gL6U7vaj/Vd/v10iSgAAGg1l7nN1Lxp0NccKjO9x5/z8te8bmEFcX+/XWjQ/EwJ4xyMUWwP8j/IXFN9gIgpkurRRuszXn6/SYJiLA63po+KkK453C84nU/iTmtFuOS6uZNPJ2HSFjig+yWAcWS0SuTH4zqIxixsvLWKaIa3h7IeHuiyoSwH3gtqK0S4x9Hw2A5uOSM04ss/Rrxn5pg5jqewQ3ZS5ty3PdUNE0TAKChNa3+ZwJgzDpqodVpp0cGOALeJD1PL4qnS01vPAEzJB/A2MtaqAGye7pbamMI5SKjv2skI4WEZj1Md3jjiL6JQwPi/LISMzoQbnTO6AMOQRP1S70TSMOd2hF8N4Vd3oejwcEp49+3I6YXUZJ6KCow8ZIe89SQVXGPBUN3mJATOQLcuCZVm8u0PpEfWpqhvuzZBJbjAongM5CLP5Pa11i/4tFcuh4tgEy7FjqRa9WqiCinmCl2KG5upR8MTFvteKtq4Gmy+mVaPWgT4pHwJ7lxymvAuaNDTpm8WisAO5qFjb3LkjnAWqQ+lS5J2cYdhhe0KtjgLQJR0gwqEjjKK1OLz1YcHhcDCla60ZRcI88p4PWHBbPwaXrhbJGDuRnx2UCopHqWekNODjZ2NViiltA4ab81mASt0MBinAXDICPWinOFSpZxsYRTCFYWwhitUW6/D+LwIhAbu3vzkKhIIkcmXPe+00SZP6gdx4QyCDsF9tzroIVG3uxMcEogY9y5zQ1KGkC2NKGjOJ4Ck/rS2qYBXLG+9Qf6pq/K+bSpnZUm90sp1ZiQDiTaqHQs141NLBrdm72OoQMvh0KgJmJDJDODywo4akVDDRdxqqaThnGDS7Q4NDDC2gMBgGY2/rTzwizucKZiAIxITiThGodfCl/A/b1ATEYAq6pU3e5RH1NniHtDMaw3giE2pZpnzCwxFjbQ1npkRI4ODjYTgoChaGcDeY3bVjOcTkBT3SMGj6pJPzA0VEqTh6Q0Dqy2gzdCA7uP7Or097w0yvvicrNCHO53O7qg4Hodi12Slyw5PE+625huZI3KGb2I5t/jbp6NT7EcKKNcWkyguH/Jui9ZBmdWNho5y3+dmtLOL3hwXQG7V9zaCbcO0dBnlNZ4SdK40vCd22e9eOZzMP7bq5PeZtHQGiXRujln9SB7T7WPjeQ7k27VkuNesL+Gma7pv7zUxop7PxyWprOuMRebSMazUe7c5b2+HZ1p3XUzjcd/8WARBoQz9I2tl/jvfujVjz2egyEj1mtlSGNkCdTzIz5CjA2XkPefbvK+fx2e3IFuz4mDp/ret2rVDyGXNes+uWzseII6Lion8RlZ3RctN7Uo8HQxrQeX3keI2dbm79OFtMPJ9iHkbddKUOc57xdQRFJNSR6d2bcacR3DFfv6SPeayvX7/87ekgk/1ve6PRtfq3Lxt78lyTEKEToRRzyioleAjZWYgIHQIuApB4qimGBZ9PPCXYENR8frSjreR7la3/RTpKqRCtjrJl/IwRkOgE8jQ6ROQyWRnpi7zTEmOl0YZdI6IlOvasdKyaZMLYrAi7OVVYiiQNtBwdie125536kyNcqck0Ba/BWxxWEIBFyRDxNLbe3Vy71fBiDkOmuzbh31gWtRRoHUNfp7u1datco9CnaDzK+bffE3GACTgrYGbZ59/51O+xVgkmIjAZkkH7/RPK29fWPkdQkrEz3N7Ccw6GTuu7lNzg8CIFiL6QBOKW9uEjwmdNATTnjV+8Twc4uhrNTw1+Rlc8MM4wg1vA+0f5lGv/dmlkfjNxXydHdJCO43/9jPb+g7U/5OjdmTtQhmZZLvu8G5j/HfafPYVep9igUeZwUmMsvveJKj5//oI3b97g9PiI/niys95Ghra0U4BiqRXnZjw+3+r7+3ltKO7cyKXgsFRHWtyS78yJ9619dlYIeADhlcqUyvd5/vCjfHv5xxvQZ4/mry1DUJ04m10AdgttFjLm7+rC1gPTxnvplVguDPOWHJUbYwxouPnwsDu85KELk8BzYzERpdLixeMwb2BfUZ4SdL9XmSHu8lpKYorX/icjlBOXdUR34yATt7xSuBhzu8Tc3Or1ZmaCbPzAfJ8y9hBIGM/At2PLkOPd8/uHsmX73FNzE9FIlw4DtKnzqfaM92x/+14U8fTI3y6v9LJVT9XyxSHZN+/eCbkK5D2xSYbh/PGKIf2PjMvXLs+8f3/w1x3d7OtMj397orBHd/rVEBL6xvPxa3oRB5T5+8xNr3zPCB5vnz5z//ydnvp9+9ts5iYAVdXzlwfM3m0qtwh2F9TgygWM/GYxRoIxH4QxzrQ79A7Kszvunmw5QLhzXvw4lM64jF5/ttDUL5oOKTeltqfEua844bz4yefrfO7A8BQax3OFLv64ecHaMv/qk7Zff9eevnWG3AvjFn/QIQnQP3Khzgqv9rBiuT/sarnRXodYhironkHdDVdl5NS1Nih6O6OLWm7YWnA8WFRsW1e0UuxwKAKRYpBpDchclkyWNlAjAx4yT6KogM9mDGpMYHEDuufAFc9LnnvVvGLiujoUpiAPndw6GigNpWHAVcUEKz8guplHnsEYccWWr5rBYxiJ04iZym0gYNzBblh0wxv8t1jNlsu64nA4YFmWhFxXETQuALfUHkQe8UKEyDnNAfua+WKnGXcYdQBQzwcWAkAo61OBFsa1MFQ6PZSJrgKiXR3u/nw4mPGQGUutqMshDUI2/lM+896xtjWh1okLqJhHdy01ybPlfDu0Wq3osrj8ZGO/+EQQVcDzGtdeh5MBD2Nub4vBOauCugBNLdK5T6sy4Pe6RSejwfKXEyfwi8KgvkMh2TKnJGW+W/ZoISoFZTGDadIVEQ7LAgL5e3rmalcPt435Oh4OWI4HHA5HLIcFtdrctd4RCAbk0O4hbProgHO/V59bp0lWiFokeuQ6hWIzVpXD+D9OI7FDGsRwiTTppvTlAqmTV/8E72yRiAqyJA9QRs4fFA4ta1GhyAhad9BQRmGBaIEWM8gVdihzYOOQBBq8dtQ/FFAktoJ7l1z7rbdBo8YIUtHGzBBi9NYh1ei2NzfcxdgjnGDI+btH0fnZDmFAL4q+mpMOlWEotZQNDGgZaXrgyj7x3OOFIOoRqdSBQlAVkDqKgKpBxObeTcmr4Ggell6XUdgGiGsBc0Gti/ElIjdEC4Q11//SFjw8PoAfydPZ2PtQyFECyI21BK6MKoHeoJniIY69JGpR6MX6bI4ZnIYlk7FppzC0FAEkDjdPNY3osSYrFwgUdV2NF6s59kAF0i1SWn3+hTpUjE8qFbczmyxLc95YHoSkEo6jcAN1wOmbY49GvmE3hxlPygAAIABJREFUYIvPQTiKUTgXxHqcjeOKjJSF895oA2IWVQBhSDNjJ1f29rpDCAxlImgtI6l2yEqxOjUOpoo0ZMa7zegTuZYnzCQNzqJ5zZuKiIYXiO91CtDkDOQeAJrj7A5yyVU0x2XIWAOKM1OZxJvVJVxajMdoGJoYA55ckyEM5wb/Xym2hhxxggSb+mkj/PocTluEjhudz83yR+z3ueim677PY+LFBN8bnBcwg5fqPhIEEKOvllpGm9rTtJM1vK52MrPM/f3iRjYzwKuoOay4PPP4cIJCQH06WyHq9BGY6s2+5sf2mRgV3d0c33mCz4u0G/A1vqk8/qaOtOtP+e7z7EPVKdkcKU+nBqjg/tWd5SBdzZBOhwJdLUUJT3LvMOjP0MeT0wo4f5/bNRvWImKdPN80qUUqV+d1fTXnv9kZJuQrH+Fce4k6odG/8c44ktlwhaNIAKS7kcwhqBmaOkYldqSLcFK1e+xna0fBQNGYXM8Ad3qLaE1ldpRGnUaREEE62eCwbM33EYFEkCnQ/begW0ndTDw7ZiBMFxu6ovmCG7d9D9a9zmbu0+a6tUN8YIk6qCPPGiIFzB0ibIbtifgtDQIDpaMxQ8j6Brb8tzkmACK+kFUh0tEagWh1+VJQSx9IJf6CWovzo+FwOqMBUch7UHfW8Lmd+jXv/zFc4megJoYIkohCyZfNqNeUct6r2omypb7HpwmTztLlBsLkxOk9V3wBAVjACQEebaognH3e5z3xpWVzzs91m9IuCMDqiAVFaaMHUVVU2LWZtxwkItFt1BiWN7s5/yqwtRM8I7iBQrFgS3sANtQnGPTQ/daiQH0N4GPcRTkiSkO/COf3j2r8bvF9Odw/Ml0C2fNdFUcAj26IPUFRf/+E6u0AMRqABxis+Z23PbQIzeuNNEXcJZEnAKDCdFsCfVq/NCNR5CjPfMbWexw/ubA5J+7X7Y42gt1sUrrQ5X3jAUDJDGRNgc88HJEUihMCaW06QIBwN1X7iJ0DgZruc/YFPgI47V6twbynpx8BvAYy5SJFHfoJXQAWRadxhgn5dG883+u6NnLItF/9ESP63hb1kqJ6/Z0vUr3RoJBJasA8grccXFo3B89Dcf6n0X7F2gxWvX/8iPu7I17fHfBwXtHnFGcKHO4OOJ1OON7f4eF0Nsj/qT2FbV/V3nF6PGFZKrgw3r55hY+fHhDoABt5dXRt7qbpgynIdtcbTSkkOfzecTVScW1SJf2JzkX/tPKPN6B/axkwbPHvNtuYdJ8AnPGqRyGkZDiefqXT0nDpmFBsq6R5pe03F6SwcrvdXum0sOI4ullrRKNXrtD4wyUP+JcLf2p+CgS73l199ik2/9wmoFDcu8dvKDOzzl2HhWBRCbu6iQhvAHzZcDrK326VFCi3++Q4LPn1/O6bNakb0FPS3Y4T54FhF6WoCtkNx9c4MvyR6Q9lyfbd23pvtWQSl//t5Rr97UtMQ+Qzf3Wln5N8ld9ZkfnThSwaff+uHWl8VQl42W8t18d9PmxsBZLNPJIpbRQBkxi8hSeeGU8N/rktvLuPrnzHd/ruysuLNo37LjkZXbTyZtHdeO3W+iw7z4eu8fgwvpuqkSaeNbcIV/+2EX8MGwiAIdB3+krxd9qovkVw/luV7Qb45K37macbvf93jsgtfrG9rlAzCeeV02lNRWhHw3J3hJwGXPbYtxVhVCOEjDA8d7kWh00uqK8WoBT03nE+iUFdlZL5ApkLDocD3r57B66Mx4cTHk8PaOuaTiQRVUuxYGhE80UUX/SonwTMHasrzs0Qa4a+LkNmErX85dTJIBShBkmaERbI0VLpWFXRPD9VGLlSSe8RhuSG4RmGOI3GkRuXQ2E3vUKREKAmkolHdTKO93c4HA44ehRx7w1ra3h8PGFdV4gIDgSUw4Lj8YD7uzscjkcUj/QVEdRuxhr4WDIbHHZEpdzd2TvU81YDSAPW6XTC4XBAOx5RlwWHZRnQ3mrw7gCGoRHDWz9gtfO9k2Ivlb8eGR3G7tY7Wn+wcfA6NK43j/x1NIHeBeDVxurctt6E3j6aDeFsxpIuHbSSQTGvnlfZ84BHZJuqopSC490Ry7JAxBSW3ihQM+hxbZK5sLuPMzGBlVEXj/ommMG6WgOLR++KWeU8+jpyRNp/HWJK6p2Rigq7oxXceFlQi0OCAx5NbxH5tVqqBIsatDzN6kYpU96HEnTMZ9AnLxWVK+JUADF0AoZNcA3gVt+2U86ICFsdURkjAnE4hYWxuNYF1V6D3ht661j7ivVxdQWQR10Xwt1iNBhwotIjl7qNP2SCu3Vnk+yPLQaIbB1fc1yDx6nF0KlHsqtH94fRTt35Id7ZZUIAcFh0M4BKGtlP5zOOh0fUgxluzXFhKLWL582bUxCYeOQtVVO+z4UKWXoMKm6gb4nokOkY3MEn+ssefaxCUOVM7WDLxdvs8EmsBCWBwCH1Y8zcuYad31l0myEeqFq0uXTBmUx5HsY97ZppLtAc4UMcPSKceKoZMdPg0jWRLZgMIcJ4Vsno87S/OI06M7IeMaOSO3BNZ04uI4q9Rj56R0843t1Duue47w3r4+pGYTPwigrQAIq17BsSF6s3ckXH3BEbPDYpobWGcHpK3oSto1DqvTlMpWPsI+2FRagO2hiRuFuanhEDfCn60AiEaaQHmPgzCOY45jDAWZ/3Mwx2Npxh7N2+F1AMvQjGHgeyM4Eb6ACTFxQW3e8dt/Qa1Abv8TktqmkI9Bke1cd4mAffFqI8aILIUTjInaEw9mpiM+RrmALiLdPfAZ0eRhdyY/ssLnI2wWSCaP4kvafEnnwRLlc4b0gj5yT/2B8xC+M/MlpkJqf14veaYVbInId6H4btePe2XnNMqZUT1QVkuikAGblaI78yxRlvGqIrJ548F25oxH6JTzjvGU+PPW8YNmfd08gbuj/d+PFy1JSVjrOnfTOTlnaxU57KhfOjMJkRfe7bNN05S0RAQnnvxySIf+x9IIt0s9eaTFtqcZ7YbT2wy4huVLZnNWkl9IUKl3/zLHn91DlH7ue4ECWCS0SNh5MqTevXZNvcRVxH5p5sYo4XwaWI2PMfj/OqupOT+ouz1jTwYOxDEbU3yQwafR9T4PJDGLIHjcQ7Yqxz3KZxiHdHWihg4gMxNlNhdueoLSVsxlI9BdD5fEZrhmwVPkRjvZnsKzFfsYBiv/B/IbPGJ8jcB+EOwOtaUGvB2lYsa8VhOaAeVhyXI5bFHEkXl6sDTcmQa6wtXcwxLDs6OoQQQIbhf0fQFAZ05J7Uu2z3JtcTM9P4J4oOcwaQzgbhXt55GpgCwIIsyPdBpjco5YTaPa2LdBRHCiuw3NqihDNJ0sdMIwlVPtPSjhaCYvTadR33+44GwXhHBFjZdSRf2PIbl+Zp7FXzWyosGnmFJhT6ePpyJc/IL6b+f4198tB8xkg2DczVjXfhkE1Qd5KxMpyBFA8wg27sVevFPVbCiWC+lpDuwe+8Ufk3hvG+4oVBGpvNZj9/M7y9XjYIkwxwWfHFGMeWFFtIIUqndybkfjg7XFy+w+aTnCBeT/MW8xqOJuJdm43ncyCabuQRK2cfz+Wd62reK9YVYH6L3n5HJ8+zjkGPYTy/VWb6Dz1tyLHfVuhiHr62fLW+fxbFtizr+eL7wvFwxDmcDv2nUhirO+8fekdhxrvXr/DpywPWLjguxVNAeXoUP9u1ydAiKijEOa6dBAvMWW5ZFnMCDx4m83zodRoL2Q1AUiuN/ocx3njTNLdkdYa8Serns3g4zsE/yleVf6wBfVYMf0sZbDQ8XQYHH8eg4P/uLRzvhgtRrn2KwxIAvHEmKX7jponEEwO/FAgud14MLrLh5DoEV5c2J4SePNwnXNafuLBmqK9ZUN+2O0xEl4w0z1643DNfwnb3TOKBDB59wW5MCZkDPaKpNoLM/r27ekc0wLi+PfJtK9j85l9e6bg3hGAQUAU44GfwL8Djr+83733jka2f/KAa0O8P+5d8ZdkKibvfnthsk+b3ws2N+/Zlb/R/rlwj968t+0jya/XP38PZ4W56TjEM5Ave5vrs+JR8gXU8HwLVRoDenWGuNuC5QpuP29XcmJ85h+O83oKu92ZDdhhQhaVMVY10WjepH9c7+pJW0/Of+sL7omQU3Cy076kqFFpxyCIMgGM8SXR3e9oKHu/PFNwDAFZ9yOgw12/6vjCUaYw7AOfN4iLcYR5PxQMi2lzwsPF+jWbu86UPr9rLcnl5OyYveeKbyjP84w+XPQ/b7Xtb6nXan9ZWKMX35VY7b8Jmxd54Y93m/c/Uf+3+oNV5DyXqMN/+qM/+KnfFjBouIuaaCJkl92D1vdEMldwJdalYFleQMGEVAcmK3pvlZi4FzAYrWKrlpS61gU+Uh8wwKgKm4O8eBRE7sGgo5yS/myJSLuWmaVwRCoQpP+y876dKUNUimmiCQMe0PoA8YCetTEb0MP5EHmtKQ/qYM1EdUWPRW6aMzH/1+jXu7++xLAvW8xmPj48W2Sod4Q1vua4XLIcjDscjakTx944iDpENAhxqO6KFl2VAfEcE+tIa6rKAiNIQ13q3XNquiBEVM0ChIpSiYQQitShrDccCwJTyvgewR7kzEToFTDmnETLzyasbjVTQWsO6rmgBed67yQRMlsOZJPlVGI+IDIK+1op6MGh4y4Vc/V0eiU0dZaU0XhAPI0NG00sBIlqzC6hUaO/QqmCPdgcB2jTbkGszkBn8rFGXA2opaNwBIYsqad1pwdvv8Oph+KeM6kbglgNcPA8h0hhCDj1fAkqbbe1ZswNKWsECKA/lI/xgTxoOMDCIWYtNQ1dXlBNQmFCY7KwQxr/c8zzXdxzepx2Upr8N6YnNZkwMMCDd1o6sHefT2ZWxgloqKhc0ZTRHShCHJBaHBw8uQEqbNW9KavVI9q2RRtUVfczgjhE57Pdrl1QQExRdaUonYcbziP4PvhNGe2mKporeG7Cu6O2AelpB1XhBqQVcq+XzLtXQBtK5ZFLmex8iH3m0nRARpwQthN6c3rpFqkckMJxcmCajAqW5ww985CISTe9VtGZRcZ2sH3xYwFSMv5EZvqunXDAluELainX1yPx1RS2GfCC9mwOTR+kHVHpBsQg8KAoUZvjrRl9KyRuKpzcobClASqSxSFErZKQQktjlskEM4lHsEICL95Y9DQab89BhCZpqOJ8aHvEFvUnyWst/26GrrWfxeSARCAH1sAB9tRy2blyK6K7cIz3vNsFpT80YYLarYcijkFt9XyBXJJtSfqxZ68ZWUGAwqBBwOIDW1QxdKlBh39vYjAA0DOLGogxWWKDQwMrF9KmThDc2/5SbwiCuMtKaaMyLAkSWh55pcARDWQi5WdEFqLwYOo6K95cc6cUj6Cf4cFU15A1jbhndG7nmedKXRE76lPNy3MK5KeQdpAEkx5lhvF8xHJB2VoWU/2gaJ5/3mKCQ2307HtfcISpRXbx9Uac5oPuYkgdgTAg/zAw0CUkIgOeUVkMeIAnHet8riMDVcyiLmiPL4eAGCZ/PUsxAKwKuBa9e3WE9nX0/wGYO4my3kZGTVLaCWH7N/sdZZZZQ53Pn9vkYI53oMs47A2YaqbAehkvbAxjFDRjGyx8f1uyzqrrjG4GWYn1rvr+UYaQNIzYRpQ57BFQM5ASjce8FhxhgzxMT2qqQanJPPR5wPrXcz8PQvdHDxfgRGZgCaCBRJJn5+vJ5FtmiQthYxBmXU4Zjin3bDISFTemPcLKDOY302F/yiOgIU2Sw1jq1P7mfDLgGzTnVlAegChQ3wWnI8JPu0euLLppxwPhYnANC5ypx33yeIxpAdMidHvNKnfmcBs/FdO7xOscZ308f0i3iUBXMhutFNIzN7I5zTMX3YJfTPPWUREqZ2fDrL1ZYhzo6eoeh6kh3NJyR6oVd9ghH0TijcKx32P5iDoLDEWl/RIq+G42L/5sGnoKfj/WyQi0nOGYeGLwrxtqmVEhA/NYdWx29RrrrnkMPDkOX4mZ7WxiXaETfblwK5/blrHpbNTs/yX++j2KMeZQqwcc0I69POddGP0ena/ZHh7Q1zqHRTg1aAqWDtuOEgJVwooFiVvAGCoXoJ2dpY3VVjEhvQM1pcTeHqZPQWAeEBQqwAeJXb9vYh+xfyGThvJUONT5mMq3bWYr+7H//lKvc/p1dzqNaM8hLu6A4lmJsm22iqU3x63GO42I8tAfcdcyZWjR78XVoKEKjmr3j0EwjgOZep04s4rLQ2W+/9/UTO8oAZxt84WoRc8xi0Y0DEWHkUP9y69lNNVvavPN5XQHQe8Xyr7egnz5h/VWw/MucqZTMAcLodrsv3DJKX6q99PLiv7Fc2LV24tr1Z25fvyAvHfwBsLMxwfQ2S11wbitIFa07Ml4pEBGc14bDsqD3Fa/v7xAp1syRW1BKwfnx5AhOlPtEa2J6CpfHVBWt9XQwPiwFX04rCjH6Xn7xfm/QaGI/cv46EKKQTnkPAO5E8bCBQIr7yGUhThSllCl+lK8u/1gD+nctL2BAtPsEzHA3R3a+0dnP7GUEfnHXc4/9J62bcb77U8orNQP6tSGYeU9E2+yczp81cnxLibpeXZVwL0tALc4lI5V2AsV3L3/hxrsvs2A5H5yeK3e6I4grfbo1NfOaTkhPAB0fQXiNjs8mSAXdzGeTF873X1VePrO2sXcZB++tUBSdvCVB/5Xf91z52r00faMNLVxiZjz/btp9V3N1CTH94q5UserdproNvXtrFI9gN8iH8bzjR37zv0PZr4J/Rwm6umQ1DepG9MPdsrlDpLuR5Fohj1gGyqGgFMZSFhyPR9Q7M6CrGnR05HcNiF0RiwRZz2dI4TSUrm4gjihzqFjOvlBizPlav3b0dPT+Yj/cK1luVJ2QyZMi6dJZjjLCxmBhh5JxDB0lLHtAmxOAWgvqUs1AVQ2a/XA4oNQRLV0fF6zratGZzGk4sDymNo8Bzd7dmGB21zKi0BM6Mfrr759yJQKm4FlbA04ng7COSCEdz5nxVNPo3d2YFy/unis5jMHRNqOLEcV7MdZep3p0a28dEYkILakorB6dGs4ZhWs6cSw+jlwsh+vD5884r6sp6QhQLiAxKPww7ofMoKIO1e65nBUeJemmKHdGCBowZW4oiykVhQQLT6zLYgbAtgKrry8YXCcDGWVr0dnVlK+hAZ3oBh5FanM6RZtm5KmriURMQdsJXc0ZgjnqJJcdjU5LLSi+g2VUKsjTKXTUsqCQGxVorGGSgLv2NRRK2CSSySEl5GgK+ENTMrfW0FZb/31t6GrKYTQFqmAlmiLbND31SQZknTrEPNTmrVOYij3Xdhj4vB3ka1NJIe7kokDyHnGFs3R7T4xD9yhlcSO7kb+gq82zQMHazUDLirMqVl4tUpndYag2lFoh1fLhdS6Ts407ArhgT8QbWL7ZOGlz4UqQ7BMB5M4fDDD1HHcneDArgOLjz7kuAXh0nkWh5/rrCrCgUEnIVWZyGH5zEmkY0St6d4cmgsPB9pLeO7QHkocbgSUcOgQdVp8ZMYFaYM4vjuJQqq3nWBPmeKExCLk+MuIabsR2JSt5whIuDao1UUQM4jYi4avzrAWFz1AI2rnlfDdf281pNPLHL4utC0MhMIOUGa1iixrSmP2OdNSBqkX8qyFXkPMM9QnO3YTM2cYobBjAgQlxLMeg2J6jAnAxxX3Mve97GmuDaBhULDcKtKd5YVrDOsm2ewnCGxqGjum5cabZyth5SaetJnQfBI+Qn26axkGNHTvd+x6cWkAAolAepuTcozc1jS8qYRAuPu6BnjIdzrpOAkHs5eO26FXs4zY8muttc2bweRzoADTxW2Q/NsbzaQgzgtxaMd033iLOHzNCeRrrNHJNxkl4uwMvbEbUCQWuOtRp4mT/4fNqNGp8PHHXxdUJQ+GZe7F7h0XEhjx2EYHaHGHFp44Xozntw1l6buvFKTaWY4iHE2nORTpQF3NUXM+CegTuXt/hy8dHBH1li8OIPvV9VEpTv6eTY07xMOIbq9xix5E/pi6zhuwzIHDjPjOuFZhRLQzXgK+IXAeXY3OrxJ4eeHXJPbzxsb6vnbEp+7PhEAAcyp2m/vnDmmO4pSB75Y6OdCevx/tD3iUC9Q5JtDqDkmY22UZUbA8uAAlB2Eav+B7WuWf9DS292jN62Q1wAPn8bPkrAWjSUVwW0ZRZfBtTN866UUUBSOTrVmzGNEZ2IHuZDK9i+3b2RZHZ8EL2Zc/pCz9TKA8DLfb1xx4RhvmY61gkFD6iNIw6wfe858F+Kgjr157/MNPRthyuIEDui52SzWgS8tZKlo4vaEkB36u37R7vHyN/1G0wQ6y1PRaKYBjRzwB+e//bkyk8CZYSkhWbbPKELa4jcJ2dz79HW66Hs42IaoNnj0A0o7EOd2wtjOqIH+uNeq71IZzvmOZ2DF5Hvs6CZzHCSQCI83W/OMjPMxJ/X9thFHOWrv0d81MxbvcKFB0IBRCFAzvlOMV9YUS/NhbXdA+PBLzWTcK9ab50Q2+EcPQY83+nVsc/qdzq7jUpVjzw4u54wOl0BrFHjzMDzK7PVhyWBaeT4QYIgLtlwXIwfUycvaPUUnBuHasoXlWPZofVu567p8Sy81OkLnoONfnZ4rz9pXMdTmr/MNL408o/xoD+74InuCXEB2xKHJRmQe6NM9QCTaE7VsI2WvuyD+HRvF14dPnXte5PJ8B01No1Pt8f9/2R9U1X/t7vZU+VP8hb5vJKbUN7/YLDGwEoeAdAUf7FWH/9zQR039gfpgq2gvjLaG5/V+Q9D+Hm2r3lvzwiRLe/mGck4ZVfDePxvW7b8zBdn7/v33N1g5+uXkIgXQosQc7fUlxdcfPxZ0fYZfOXvv5EuokSDiVM0ELZvdMOJqMtl6swopM/p9AV9yhNAqgOnWCjOCJ+O88aapsbdTxzeRsovTUN26F0W0GZ899OT2w8mP+jyn6ArvHeUSwOywTXrhr2kbznoNjO6O53wh06Hm8eZuzZOJzeYeSZv8f2yGqGc8I92LkAv2H0T0Zre+P5flucdZFfV/4YvT5Z7TfV/I1t8YP7ZqvKNky8fTNI4zj73Ftnz3zgyn77wnpulf2h7qLm6eC2vacDKDg/rqgoqPejTyoCKteO7J4nHKacKqVguT/geLxDXap73SpwekRXoMOg+tRhskSBtTWsnXB2aHKD6xZ0cahuwJVo6kohM2SISubim40o0Tn1vIJTwBpS/Vn9JsLmF+/RfOd02LL7N04zPGZryGFBL/68y1jEvGGDEXk+Q5sDBgPGk1E88h0TKrSqGdYdTjpysM3/InKZI0oXY09mGnnQQZSwiRHxS/47uYGWYQaWhFlvlqOzsOXpjg6FUqxP9UkfkgvzMA5aFLzxijBmqiINeHE9lKfdIWURY+5QyOxws7VWLKWiHszp4FArlrqgLPZZHc6S2GCYHzBgfJksp7cp/hyW3tupSXdmQJTwVCcF9YjQCdnZlESW790lhCnKJoyOFslf3HDY05Mu5m5xqPx6OKAubixEKDxHJE54v5Mbw9nzaztVwyJZxNIgwwzBXQxyvkCgxBnZHPyH0wAGM44jYLKddhBR6R7NDvKoSFMUQWaDsrdCR6SPhCNCHthjRwNEGtbesZ5XtHNDRD81NroiF7SJxhrcOEamYKUZ4RzrDgC0W1R/n5xygqACtWCMnfe/e4RXRLp3g6cPVIYwLHtclxkAxOD4hGz9WLSBRRVyMccVQ4aoKCKQXhItgMjG1+BbnX8EXyCLWCKEUp9gwWZm2AoY65m/KBx2kpDOFgrTwBE4HSRI4WtZnd5pzHEXczBBTwh8W4LuCFMNRYRJwc0M0iIdUs156v9n70vb28hxdV+AJdnxkvQy97n//+/dM9OdxHZsqUjifsBCsCQ5TndOz/Q54UzaUqmKxRUAsbzYL2qUrsRo3EEGd9g9Mqd3dGIU0QhjkCEciDuSLJr73CLRg865oJzz+HnbYO0UCubq0UW9Eao00xjbOmTWte1RwLY2e21YQVgrsApA1CGrpWoge8cy1mKVo86lQRwLBNTN+NaNzkXuWhn8omlflA9wzLfDtQ/DtNEKC4Ua9lYK2u4nRiKCZJhi7byOEi06VEuK8AzDhu2AyRDuZ68EUReOaEiHHj9obSQPyXyV0vyMKHivhJgNhcQ7KHPqLxsHinBSj/J1Omygrm5gl/n0HFzE1g6IYBtJeU7QDAkYVvX1SKexBC9Io9KQm4Mu2RD62dPfnY3YgZwCDlrk94z97203Qx0NJy90oDNQSCwinUd0E2CpVGytcXq3zRP1wWcPzy+WOuYK7lghIthdLSAqEO5g0fpPtRJjgM/JzdvrYdH3cY2BzCN16dA4rhMw8nfbWlCI4vkMwwAkOTf4ytGm5PXjsOHOcwTleq97kS3NRG6Joc6IdTC/U9QDL9JrcWHUtaEsxfZbh4M1MDOeHw/RhiRxAnAkCzcaC0IrwhztEYdUj2jzntbRkEt7h0bE9QHfSrC9QpZ4TSjRKW1TtzQpyg/UqSxM3iJD1reWD9QMYDpP5b0TPZGYcUfetEFMhA7KW+1nbw+ELEjBHVb1FZxfl3SYF1buKJRX2JDffW6c11LvKpu2Hmea6LPJaGE8NzO7p/UAF12pXdCYbC5cmKY418QJxGSqxl1TT5EA1MC1YSnKkxT5SdGkhLrKYzTcBESZTMpfrg4Rjkvicpo0l/M9dZHNaTHjIMaaYqM5pTE6ERoR+J6BlzkqOWCrRdDxhCJ3iefM+0ad/5xTjMWw4A4ND1HfH9VDe5s2XCq+j903r4PtfcvPd6i/K5rk0FGOJ3ZCuP0/P+PzP38DkCLVg8fqfQHhvmGnbOPe7N+VjcdVF1SiMCj7en6xBX8t46/v0Bsh7Emjl33/LKnu3E9HVdwbLVzt/h6TNI/KCzSaewd1wQ9uTvCks9r+u1vUxy/Yg7C7v4M8PET9ALAr6tjYLCJfx6orkhYfcDHDAAAgAElEQVSA3bLE+KqjtowzL3GgNaKbQV0GDpbDV+deItN8yetB39JEZUZn99dikd1243XX726ovBHVAfbouzkmW63l/T2Onx8COexd13E5zNOvn0MWG3M5TsdA+enO+PoNIA9gIhxh+hG7xw3oAsEznRpUt3qnP224pflzJuF/SbmwPrfKzFPdpt7/clxBAO5ub3B7t8fL83Ok83Ikj9pU9t9f7S19oA6y6q0abm5vcDiu1n/drztmVFHnYV93tTasrYFfDri+vsaH9zt8/Pyo81jrxPdEJNqsDtNJFkDqsy8ZW+uBohT9zsIJTgngj/KHyv8aA/p/VqE4OJwIAi4Anizyyys+GM5b3uwCf+iQzvuWvckb5luI43/Qhn1nDCnyjF8gKLT555Rs+fkDjh8/pxtPHz5nPKczny8Ny2vDJQTUfzUsv5wabs6941J7/mx5G9OdKPsfKq89+eo4wabma4O9rdMFltQ9SX+/9k5/VRbC4/qWv9tvDvfu9V/JgBP65uKKqT8x5d86YyMK0yFj50PUXyFH/ZUkZtsnX2bbfFHb37d1ADAodqDgGjAjen5uQJddT/tYIKp0h0daEZb7Be3hZtR9x1gf68lB6UfZFNcynVw+Q8e/w0I75bt/zerN+3q7xwUNDtneDg3L9WLXL6kSBo0phUFLCeNlMYhQMUi3Jh3tuaNfqyJngaD1iueDRtwcD0e8HFesVeG6W7PDtBFwVz50iwZuolryreEot89payb/WcmG6bfTWiaaT6nOpBCMPGz2O8SjQmn6PkFwwg7+Fr3sOdG0ix6dr8am9biCQJbneEWtK1qtyfgBM/RZtK1FRjJz5OaO/ITRMTUMVoFhK6rxuzn8PUbbamua692Mga3WyKHuKW6IzPNfRiS6hOHHNYoSUOSl7MJYFIZzyrOGMNjjSNF2lZk58n0Ta77xpRTsdnvs9mo037lhrywoDrkrUEcQqLHJDb2a79kg+owJ++FXPNzGD6hdsNajRjkatKnnex9rBJPxfMDDe8S/KS/NCNtas9zYCu+9u9rj6uoKu/0+DCXN3ude8h7Fz44kwB5hbYrWyNfdRzS3rVE3FIIQ0a4ECoOl/4s1SqQ52wWGNtEDSr23hiZqXPa/qhMd0J8KCW05MG1NDLhSm2tp6FXhwnutGi/skaSVgNYhpSKMRx7B68YgW9PdYAzD6K2X0SwNg2BAwE+U1xPYGgsgSBjP4Z+t3b6fukG6e19U8a8OFlqRGh1aV6ehUhb0XUdJRv7ukd9mfWOYMd+RECxCX9e9ucwZKkFh37qKzNDqyAkvrUORO4ajSO4wkY+dQfj2CqJikYUKne1R+L03CO+wYBirhyEdke/VFz/ZulwsahxEYK6otUUUByrQWMeQO8zhoKOwQtoTskMNbI2IOmpQAzmxTG1yTbwbLz11goCUflmbFS0A6pARRkWbfhaIWF7p/U7PyUKQYlC9jSBVIoIbHYpe0Rms+Oe6l0WRG2iRQSOcU7nxN3Kp9pgTh/0NckgG0WhOHwpJ3sMByYddv/l4OYyv+KiMCoPpDUN2TuMAc3jJaQCiQeF0sjlMBVMZ+zCttDiLhJOniw2T4dLedgFVRiM6nWbkopWFIZrG769KU8GrAfQaYoxIR+QbcfUkDedYCDQvFU7lefah0akdHyT139YkG20lAFgUCcKhP/XJmNRhbMeQKeJd8HnUPOgEQqForZEhOTHaT9HvIKCpYhbFHXSU34w92BEGWZY5RJKAkzmL+je/0byn50V5ucwyauLJ/omMZtvrRkQXjPfZk3RWxI+1SPm7/XVnQjU+m4OKG4v3bI51+uTk6GLIQ6NeAZfcALZ7vG1myIl9MRs/2evythIihVCOlibK7cjKd9g6l+CbBETqOAgZGo07W5HtU9+jvt+NXqTxHy9I+yRNWnLFnfbnIEeDnqsOxPaM98noEojU0Q/mVBDv1D3Vg3+nl9gHpQ361kxLtsvBr12iH0PG6mrkZOURMLqsfgjm5JX65+1azPHUc6cXMDrIfLqCwUKYBrkcw6MOYFW/NKqoht5VSkUtBUtfQNTBvQfsdLf5UjrAccbQus0ZFTCkp6ZnsLUq6gRM3gTQl44iJehSKQzuC0ppgJ05JKXm3p6xxGSf4nJgGn118sFwIkzOZEp2CEJ3IDxiOqsZvQqSF/T3z5dza8CrbmY8LzLObvGc3XT4r9+j/V7fxI9ThR2PYNxNZ85sNG32veAOBU8TCb7UeoFgJ4QK4PbDPa6I8OX3T+deDyDv0/Hbdgx2J2+BOZESKhwafa6rAJCusdAVgv7weFKvQBQSu2d6MN/hdJaZw6GV7f3uy65pVvzsJnHt0pKY5Mfgv+o0uYOgfLiHfHqI8ZYzfx1ePdYGHA1LAj2gALj+8B7rx0/6JrFrMhviv1a02ieA70Eg7H59P/1eAFx1oPxCKOU91v/6iHtRX+0uEoFyOSJ90uP/ZRbv/67yNpkiF6eRhQzRDcB+v9dUb7Whtg6QouY9H4+4wR43dzcASBGpasVu587EYw2B1GmKmmBtHYujfBkd/HI44upqD6Iy8R0xQWWgzqS2Jl4fjafpA4AZ5UDbs61LQt6IxfvGNfijjPIfa0D/qyLGv3sxSelrrSdS7/87onHIAVC6aGAKT+ddCAS3AjxtmTVeOTgSkGRTPVDlSuGC8HwgiW5Mh1yafj/98rUOp3b437yj/yK6nSPOu54Zzxb3PNvhPcqvBYVJBVFT6rvn2DP7wWUMRjZy0abf54bsnTEzjzzPCv4QRPzwA2W4R/od7TcKAhjiBc3POcO82X7fSLd5u50IN/9mnkr4dtquB+BRwbc8fyDBjUG5ey4k3oxBQOdv6naPQxeSQrHogjLPh7T8rF+zACRcATjGwfV8W08v+0LjeQwu3u/Xz/wyPZw9gk/hzRTK1ozmviaTsvzrLf/zi+y/RwZ4vcZ8uMlzmp/aZfkU88FIrynUugo57wzO7mWqr+AWBMLyQaPVDh+PAICOLxFprnUJyvsSHuyHh8fwzvf8bN+n/DX8+S+TAozwTis+eB6dXJs+y+mcn9bv/NbWAHm9f27dX1rz83Hw3E2XCUNFww4L+qGBw4juO38ckgGK6GI2wy2IIKugFXXRbnbQXatGlC+inuQCQW0dz8/Pauyrqrg5WhR6kxZKFmIyaFnPQyyhIO0HU6Kxyy/WtmYjG5ssMWILiRgHa4EbWSPijVJ9LjcRIAaN58Y8wJVzHHvLHcgVUTuN/9Qgu5zkKoddVdj0FaUW0OHFjDead/nl5YBqBvQuHbU0LK2q00Fvyo/YosfF4XnF4Nwpos4BQoMby7LBW4VGZjVGjQj1YUD3SAE26Gs3AkYdIjHHfnAbqx+YoKr9fdkYCnUYEBHNGV5K5L0uy86is8mi7hS2fdntIhq9sBslNIoW1SKazbDKUGg/gRszrd0soLLo2jAFJpICvreG9XCMcZ32LqUIYl83PIznHkWm89vC0cCFKyYOx4TFItHjAN07pCEizjxHOpeCxXKfg1L0XCddCwC4A82Uu0XYlKgKX6+GY881qHuYqcAjIr0wgLZW9NVgnkXCgBx/E5z5iGSXcFRorcZzjkAxoupMudobIE0NOiIKIWr7sjuEMKkByQ3NTncl/SPRPd5F0ElCOe2RK3ADeMi+s3KBTCE7rll/bJ303m3nyEY49qheqHEVGk3fTdFOjcCkEWKVAHZLrr+LJODmS3FgTKe9IxpQYd1d7he0WhW5ozodUOW3kJhjiIxcub5GxGDQbUw7bG5EnZQ8tUIDYZGuEeitqRNFM+eMtQWUqRBBWo2oNV52WK6uIHKwCdaJFi4QllirU7SNydTFjIqS1gZEo+N6oeCd8ZgbhNNcOPKDiEa5w4zoigygziAtEESMBrhhWnw/MlAK2lJQWjEeN4zxPt/daDYTD2N5F7TaNTVCWSxFhKNbiKaCYHMMMLh8SXQ4/lW9xr4naYB4xnkvr+NxwDe2NiJeQYD0qu2TMqJo9OERIW/LwtfXROdOxJXE9GylarvYmjAU3y6T5rny8Tg5Jjjvcj5i8plvucFPUl1Q3rJtWpCy6M+2CKTsQPWg97hsJqPDbhxHajfl3w26eRz8hszghmuV+9yADjNmjXZvz1TD2J0CLhKfJFCkboG9lk1p27vE+TQi1r0+rycTedMg16NGQi/7naJ2NEXQgDtvEaEXG9M+xiKP5aRLmPQiiZZN+qdz5YI0HU5tc/BAyBhmNXRI8LOYxS55i7ZFhIwX2iuSMb2uDRFcLYAq0nU43CEPLGBezNjsfJCnsdDt5wYioBSJzyKuFJChIJ9Ei2xc72EE1Xb5jZzG27hrJq2kiE3Unb6l8wjBnIf0d+cz7vbToY536qRtaUosR/ow+prL/HghwgiwsWDp/HvseaLZQsbvezgHeBv125WOKTqInrUmMgQsB6va8vIko7s8J6Ig/i6rSXrPTOt8HDO8rsu3NnYNaDScM7rJsgyNXBQi9HCsQxirW1VUlXruQG6EfezzsSZ6FzRpQAMqdfC6YimLGtC5oJYKAlDInMfI5DAAVNhkMXVedt5dyhJ7vJlDXq3V0rkAhQsWUhmMiUGFgiAWk8F7KRBmdB6Ryy2WgjuDmJOG6KoKI7rJjURkSBlsB2Q3pHdUPIYMI2IZkIIPBBXeDmF8ow2D2VIdpyYeaLAXNTpeC6EJ4YXUGC0QVKghuXwg8CdBwUD2a0Ag7DAcE2a0yd/7bJ+y5oZAILnVb/QFALCH4IiBgnKgx2m9ClQXfdWdj7i7k9612Bh8+fSARQS7OwLoFr0/YXkU7KCw8CayYmd/3WDsui03VGcEwwUjgtzdtmqaCQGwt8/ti1513scy0CQAAF3QHD0HEvLtuZIdypRPC5qlKlC5mUCm2O9VezJoqq0h31suIxiR6Skv6wrV3TmfvALCIcsdj8if9W7YG3YClPs7vHx+QAUgH9Vx4eanDzh8/DSg2EXH39PJjnpGpdnozQDaRwH/kuQnken+AwO3/AGtdyzeY3OYue3AI58xnn9nJX9IoRvy9u+2JQCZn4zS7azaWgOBUHYFRQpEdHc0c3hGa3g+HoEnRQs8Hlfc39+CLV3hUgpwXNWJojY798Oi2RtEGIXd8REh04Y8mQZonKP1u+qZ7ILR1CnYipwmAC+hA5L0+3mD/Fbv+aO8vfzHGtD/J5fE12Nz3JmM+ZEHHIgzxJPnzlb2tpdGRJdsf/4Tkeh/o8J2QD5HRL3o8eweHQ/gXzQvnxrPZRyKBaZw2T77baTo3StD+7WaskB27sdp/bxxCs+9k+g84/vea+O75mmhzd8/WMU54zmAs16ueU0REIZkAFOu+ktrb0ZGfHV2X2/193LB/db3AsMY40aJv7i8tq+/Zxnz/A4ljkOn5ZyDTgjeAAg3EHR4plNXOJLlLvec6HKhZ6qyeQbjBgRXphHq52aewfOB6Ed5W/mmyPONwutN5cLeoEvE9rWqcIGevOH66T0K5R5G9LWrcriUcW8sXkKhJaJgAaB1hWRX5RHQ1o7D8Yh1XdUIVvWQqxGy1a43zdFsUZQtGW0BGBSuw1JLGFMd3u21DlPQUwxtAuXbZ+V9jnzZFj28JINwUkJn1Y0+bgpJM/KZxm68h5RWahTkEEiEEHnEj0c9vMW41IqD5SLXCGsGVuDIjMUdDyzPNRGZkVZpcW1ND9NEpiSigG53Y25ENrtyVYZxvTWLcBWBGCx1YYNjFzFjsRkKyKNl9bec+5y5hJHROVxEGMEPjWTRtHPUsojCRF/vr+I0WYgHDL44tGc3gxnU2Od5re2vc3aPYgAE3FiVgCJqKIv8rwgDnkbFrxgGdLL/K93t3EFSsFmVUTxvaM7TBzeGh8KQ4l7VLUqMg79THJ6zW27ntO41pXEHujp6dOgYCQiFYAj4NNapGbrYJQ7paJlZSIfUjsPLAethhQvD6gxgEd06cUPB7I/mOfXIb8sd7ukFgo+SgLqq2ArLMK525XCeAssdBTos2pg2O5Bcfve15YbBPiK/rQ3VFf5idCCImyQN0JDpXeGXo3XDXmF7Fy730BjfwhTOEVx45BM1eqY55HVN9aq0tFEBc6JN4i3TAwyltkoXtLWag4shVPQGJjUKuwLHBUylzT0GyxXsHWpcaD5WUIMJbAx7V9pcWwOtq623DojmWW8WwdZaNRouY3AIyiOoqUNU905ZvlhfNEShdOruDELq/DGm2JxnzLCVz1yCrhGjZqiIKHtyvRPFvtb2NTN8dFRWNTETWySv0u9Cnu98CYOEd8tRNSAWad5gBhNTkjWdW10rNGSFfK636sKZwOXnfh5w2PfBtOyn83260YxtswBIST5PcnrQJTNsxBFkqyw4PZv43pnnQjs6nRNt/E4dy871Us7eciIjuSPXRQFtVEky1yZ+nfy8lmKcN+exLDNxphV4w5mDsiEbYbzzcXCHsHE7pbn1qHMKmcPbCN9HhW3vwCKmRWH6LYr0rPE80S5ADWSNEfzU+zX2q9XjUGnnunlObj75b77/28TdcMaI/zqA8gzVGxHW/tIw9vte88+E3GSnEfG9a8qTvnbQ4msZA+EEUL5VKA75xLCMCeaIKIKWDFyAOoVqglwJRJzhTCIaQCNjfJzuqGNR5gGSRiVecFLElF6+3mM+CBbVrTwVZvyLtB9Ccbuj8qkh1MQ+jH2T94PTO73KGCkcBmpaYm32tw+66Tw15v1qfHa0BpJkJKAwVkYrYo/ZRdvjw8nA655J8jSCQRpPIwLF2qy83PexmBFYkXt0Tw+5KKMUnCsZKcLXT7zPnFhchuzSUBs0An1d1YC+rmpkIw4nLcxTg95VVpDu42eGRz9biTlI5jRMjc15uRvsuNETQ8upyW/pdF4RsqxHobtTn79PDauMAkdvckcEBBQ94QaELyZOyORk4U6PMd+D3UxtuVS2v3cCFoksS1gmumP3fPJ9M1rhg80QFFFDv+Ct7xcAHsJvDoQgFNs9SSSdpnS/qYuhetRdYuHezh3fon56iOd3P71H6T2uAXN7NerdDLdnmPWCOS2gc0OnM12mpTf1Yd5ndo6g4XCHdK8+O2ido/AM/uGysvOZjW76G3hMLu3zI8qHO8inR1QkfywBjrbmO0bgFKW+vHx+jHFu9vfFDOl+nQTYk47hlSik+yWnshdSx45KAP75Gcuvd+j9Ccz30zwXAVr7FG3zc6c7QtyZEf1/kl3nW0veP5lGiC1YlwFKsfRajTQSveiZ5+W4Yr8oasLh5YDaGq72e0NNTKK0sqmwOQEDQaEw4Xg44vrd9UW930nEebo+6ZO+1mGX54YQkivbjMSP8tbyH2dA/9tGngPTBtguRyZXUFncBQG3QnhmJfb3DfhsBJnh3pjArXQ8EnAHP/zoPeMgMQ4MwGAfei03wu53TrypBwYB2qO+0aURLYSZ2nxroTOft/X8mfq/Uu7ksueYFxUY3gMg7H/+CbulaOQSNErn8F8HuDc3ANyCAiojM/7teMVZx97p0ea2FCIifHpMNkMm44Cg3+8BPIzDDQ1GDSI80/Bsc/nWPR6nQ6Nd3+ZB93ZsGa0f4FXJkpUjF9wHtnnxLpRsPH9nhoqDKaOuzQv0m8qmj/QNz/v4e1DKgnsc6QFFAMYdGh4hNIzrFrA+vc8V25Gyb3MP7B5Fjh17Vo2qX9BJs10fT6TNt/X5bbfT9sJcDU3fkuLo/HuFVBlf4bEjf1X5nnyDTsdlUyTduT3YAHp48b2apy9HXmjUudVyp4JVMag+v5foAwCFgIUI1o8VfEeg8PnVyPXlvUZpHj+taDjo4cXe8+eM5/8efvzHxYBv3gCTzDGzqEzPz3++XO/5Q6AXOfktK5ovu89s2fArDTh746X9fvY545W7/YK6rtjvzJ+cRvvYc3QT0LqAakNnAR2UrtW1Yl2PmlOvikZhNkapxSKtG0CCdV01/96qUZRiOWDZoibUmIaR79c0eMpSJbQYOeLN209xfezXMIqJxO/6jPcs8TgBpsi2GCaTi4L4m+KLtB4BhhE9GQyIOPrBSPnOgTDeskGyOgR+DwN2nyDrIi+zRY3UVSHfmRmttnguYGVdSW8GsmZR2Z5TLrS1SQD06GIvvQ9FJ7mhiUYf2fKNSpeIkCOiMDb5oRJA9MMNsAIK42mHR8vrmBFxRLzEWCb51aHGvW8Ok6lQ6Ro5z25Qaz0Z6dWRoTCj1wVlWdAMjo1MZusyYMHzGvCxVjjrkZucmFHMKMKp710Ey7LEwXjpFtnqOZ9tDrRduv56bYioDFJFFjUzom/WpR7UdW9AFFpxGLL8iOIKaFKYdAKG2WiqDW7MUwP6UaOWTAna7fMpl88G3tEe6raXktHa7/LzDseb2ZR+PVomaW5H2qVEES16SYPbaKCrEkFEFZHV20ae79X6QB6x58lnKDRlQuSWgiF/Z2PYaAGE+5CZZURo6T+2FAuai7Q3y6DeeqxXEGwtjVy0miWgR/8hgy4BCFrZe4sc0mKR956rdihctF0ie1sFzcZa56hJN0P4qnLpUtDbESSMvuxQWwWtbHU2VC6QannridQI1xvqwZAyWot2OZiD5hK2NYEGUDFEgI7dUgBiNHNUKbtd0AdijYYrzACzoi8kxdPs0OtON670ZI2sb54GgRSiUVjRKEijSwqRoZmoE4enTXCaw8SYzkNGz90ZSUzh5sYFCDTPuSVmJq0ErZnhpQt6kxFd19J8bfZURDb7Dkk8BciKtrGPRaqdP3y90OQA4uvJD6fOJ2dNRrrljOSCfK/zvzgQIMYQ5A5OUAOhpSoZ6zm1yZQXSl8sOlFGHknddxblPs3H5bNJCANZrrN9JG0NOcx/5nHHRB3dwSOfhSaHgGjKLDM6/c6R5QI1XrkDVe7HuE8rdt8nssNk1gWRyxlIZ5OkfA0djtMtv4dT50TnR6Th8HLUVAalQGqzXOgMWV8mPcZFZ8NpOJLsMw3QfO/m7vNnR0cGCvI3TEtKdz3iWTvEbnAmzPchyEZ69xw977yyN8HuemfpMnrwbgJSahaVEUox1BAWG3+tw/0MyXitQn0PBUEYq5kiSnceSxnRkc6enJeTpEH0/UqxHU1SHyMaVSe9nvFL98foxmMdbUppktekjlkQH2eXHxCRvhGo4+1JkZ3q7EgxXxRGe58rCl2NHoeup7WgrPg69fclFGCeO7ojDUkyfBPL7ERzsnxP13PeUwyCEKeVlIu4vx+ILAWCO0VFWzd1J3pwvpDtWYE6CrXoWOsqq9TaULii8orV5M1Cip6yoIzjiShPa13PWd0RFABoxurT/ojzKHdeNnkEPNIOuAG50hj7IoIFwDMJGgR7m/8qgiJPKPIBjt4iIhB3REt0b08FnQu+cAN3QsczCLcAHoMEJVJ0Omn+5+wNc+lAIJISNPp4JTVYEoYh+ECiDgQ2pm2scJ0TwPJcj7VPwIgEtuL63ophhGl4AOEOwCPcY6mI0v2jIxjEzCA+6U8c/YDx+wMBR1t7NyppYdnv0O9v0R6ewHfqRL1+egDsd4ZGmfuad8PwMBSpxEgA9vaM7y5NhaX7vpss5u+nRWtypJ1rYuxs/PxtBUO+LoWH7QEulw+GwTESRsMCJgTWIpWpC7Ome3M6JuOOXDr5nGrf3HfxBcDu4yPe3d/g+PAEPVMp3PdVV531C0ZaWK+1GQ01sDu8e38HEOH50+egxjsMnbc7KexFjehbHuj2ggp1mFgZwL8esfvHPQSCdz8xHj9K9Ov4u+7tT27kt/58EJ3L665w7tddLgatbQPabmSGBZ/KGPo3lle5/Gn1E195S92zBOtPuSO6r1Mvjtj2+OUZSyl4Z7LK4XjEzc07tNrARZG3eu84rOokfH93CxDh8PCA58MLrvdX+HI4opCe/ZrTWJNta++oR4VzZ1KjfD2uuNoteHw5YFcWRQGx9jjv0j1gfcn03Psrov540zDMfEVljzSm8fSbJ+1H2ZT/OAP637n4Yf715ai/3sRhlPBOKIQPLx6xylDY8ddre/3KtxRKjP+kZEr07RX/W8uNYKSfw/moYkCN5wRC+ZnRfu9Y/i8wSIwfXAclIjgE+7d3kNLfmZyfuXfTXnUCf5ieB4bAAWsXSGNZt8TzUoPOsTXaXHFi7mvloodUPEBzJOCZ8s4E7OeAzrV/xgTYDqFvLXFkIaQD9LcV3c4qojd8TvXqtZIOD9NzYgKZ9SH7D/gWSufWqWnqlP5FHTmETvIr/VXlj271SXSRfPW/u3zPd3xtN45y/iCthc/+QulgQljeL2ifG/qjgO6HotajPuWxY3nPm9yteZceQJZDvT52NLxM+Zp+RJ7/+fLHjflvqBuzkKt59Mah8i8tLqybQq6iAdJBB4CK04RBAZU+O3x3R6sralV6S0ygDhzbil47+kGNlNwY67HG4bjW1RSKejBpvRlEpoSi3xXNHWIKCzElwTgERBcwE9th4N6OpZx8mnnfoIBhS4bTc0r3b44fmZ4TIr+yG9H97mYGWYcKJ2KDIl8UlnxZwvCWFWyuFPCobj08qYG9rhWHwxG9y8iBXmvMrddLRJPyrBMBFoGeFcLbsYnI9q5GDzbjYOQk9zYaPDZZ8uXg41YHG7S5KugkHQQNwcTXgQxqR9b+aJt4xIE5UfSO3j0/NAdst0egN4sENcEpYK/bqtD3Qtq2XVkUdnlZzKFJ58eVh5offBw83VBGRCDLSc6FDbaZI+KYItc1sCwL9vu9zo8MZ4SyLCBmyz9dLRJIHQDQNfo+Ds6u1BSyPOwewaFzHZD41j43DmsFQ0k5TuM2/uHIoOPksHL1UBWy26OKxZXb8wGdYmMw3MptYKIQqAK4MWN48gLkTiSgMFB2y1fu+a6T/Q8j+g4QNsNSdkCU4cgiblBnHS8WgbSitMQj4c1BpNt6DOM8YcC+x952ukzW37H/1bAy+DcI4RhRSrHc4EURAUQgRfNTkpgynDR6QW1pFHDjgmbzLRBLbeEmhB0AACAASURBVIA+4Ps0uryDxLJRUh9QkwAC4NGMl6oAVahCf0bAENsnTaqOFXmO9isdC2mo1eTbXrGuikChc2vGpa5Rau3wErQ8IwBkck1+kBCNYu8dqJZ6o1skx6A9ZPuKsVt2sbeKQV/nCOfeBW1dUXuSfggqXKPrWupKOYQFLAxhjR7sIEgFVjNOuJNEWRTxYyc7W/4DRaG7A4PNz2K0g8hYjxtwxNZ6SisgTU4g9r0M20viX+TKZCSnJ9tltm4nXXLsGcwXCGao04bpetW9HSZ0n67xn43REWnDS+w5nzjSxgbf9H3kEazny7kfhgEpoH4THxjGa5o+zzXINA4nw2Eyl/J2c9qxhocEYs8HLzuR7s/LbJSoBKX/gUizKACA7zVgGL19npAQXcjQQhINHM9og9najMJAbWfP5xdFWnP0EOnoYHWGJAJ7bnUVxF6p4MKb6PTS3O6TKbswmvn3se9j+9sSDPAG18clGc6fzSX2WTRkwHK7/DHeQVEL04BfD70QEwoDrTvKBaIuf94N5uKCLBB5syVMMd43n9d0/ovmK6M68SGRbrmAYUZqve7tMeZo65pCXxEIjeaIQBE6Jyfv9bF2qgEM2XjQGHuSOfpBaULI95sAwoNmwKDiCVfRSxFRiHRmwNB3tFwDdFDHPp/zaMa59ef7cZb0XyOZkmkXnawebIuk/1kFcauTSLI9r4hcYuk/UpWU8rWbPOLIKr48uigiDNfV0mlRGNCV5dkatRZLF/TaUVud4K0JiBy9RFDH5W7oJf5cdwe0hkIl0ryEbkLGX9qMoa/mBlgO9IYu5lwnC9wlYeSdMKfblIpFxYencCSaIUJsLed9sHn/10jWJZ607Ut1+Q9D/+d1Z3dW1+0Jzq2Q03doOwdEO1mFMd+pZGh4LycGtE3xKna7HeT+FsCXWJcOxZ7TEfozlP4NvA/9bQ+gguYo/EzfAZsbv6Bz6+dPP9un3XX6/LYH2Zjuv4g7/yV+Akp76mszcPKWaA9B952jAgsQslZ+JtiijKAVXyPt8wPKh/cWyT/2Qi4E1QvuobDu2zYR1IDdRY3vjYDSH0F8h/q7TPrxemEhiLVvgQbNvTYq2Xh+La8Yz//Dy9eanfebQJG01mNFKYyXteLw6QHvb29CPhNRHUxtHZ8fHvH+/g5X+z2WZcG61rC1eL39zCjvdwuO6woihYcvlo6tdU3j1XpLNAHhtJfbHL+n6nNf3BkDmNngdv1etPf9KF8tPwzo36k44fTSJ2HxtHj8oBJNweecow7AAwF39oUAPJ7UYwc+XCAQX6Ea02Z011hAvWaRvOd8k/3ZPbZ9fitV0IXrf7K8N/7Z0ni47LU16jIA/pmx/t5wvduD/8/ItaoHEc0x6kZjJ0YlDbaP1zs7aD/Dv8vUt3TMiH/bEr/JHM3KZ57NwkgWWLbRleeG1q97dPrWI+3cGnNDCsv8y7lgc2/ba0vS30lQhxLE96GAv8bbo9ApWg6Xtt8aCD/q6DAnFo04z+uGcWt3Pem9ZwRcvW4tsXcXwVl7jl9zD2z3eAWUER6/Kv1/0+WzdOnkIJn3jCsBz75jnts5gubS6r7U0m/d/Ofrlgu/vq0lX29zAXD1/g71cwNwA7Gdfu4gNY+NKfwtcny3v0LFM3xnu2BDzKAuWPGI9kBYDKKdwOiPo4e6Kxjr54qGAxqdF85f6+3p93+fpPzH3/z92jxF6ND5z0NJvNnLk3H1LUVCseR0mwz28XxNdPFr/uV0f9OgX2cbqMqXYsqWsQ6BTg0FBb1XFF7gegqHUYMAtWn+4oBetga0VtEPBmErCjnepWueXhkHX4f0dWenbkdyhznPkLN+XXiaKRvOQTgpvspQtlyQZ0Q00nTwZYoDuerzBkxo0MiJifupadRDNjbIryaYApXNuKKw5rtlweL/yjDghiFGFEa/iES+bCKDP2Zta2sVa11DPoFoRGlhxrIU7PY7XF+pQrL1rlHWluuwWVR5zkXusO5jTdH4SzDDsXpzl6IeFg4H7RHoEI0uKbCIabE+G4/T9a8z73DxbpDyQ6Majil9TjKJjzlD4WqZLPeiQ0U21ThIS6vE1pEZiz33s5SuEbvWjlIKwGUcPkkNafOeAWBGWiYeucTdwMfFxsl+KyUg2XvKFz7G19MVSEQWi0VphvOKGTprwGWr8RFi0LBMJ23ZctUwQhUaxgFRI2lv+sXXPwGQ1gziM8kpyfGBQGM/EqnwBIIbMHzvdNG1wAYr75ElBRyR+wIBN4VA7TbZEtF6gEesuVaZ4iP5LYOGiyuW9C1ksObcdKxa03FoBlfqkKkKXyoAk41tqt/zFZPzcpe73SEEMa+lFCxhPF8CjcBh+EvvqiyWBrF9AVakBZ1rNWIIZOQP7RpJBp+HbnIyE7gPOGBgIDhEu3wty9HyoLMZTBp6q+bE1A2VgdHbClp2SoAaULvmsufGANVhmGkjn7n0hlpXdPWmir0GEHphYBW1cJkjDqhDqCnssXSIlBhv4oYFRXPZG4KB2Pp15ToXMgW/rjVmQWOYA0I6d1nfOwTNjAe6XdicgMgMRpoHlkHgRZ1iChdQoUDX8DQEqggmrG2FiKB2dVjaLRqx62cXEoSxvIuDoUpas4Npka81+5NhfzV638/s9gAGrQzO4+MVa8h3tM93jzEWEcuBPJR0bkQfUrnysoHiNZifw7eL7zvxeZQwhOhYDz6u6AtIVoBMC92wr58jeheYc1X7+GHU/2ok5/RnUETl7+rUo6hhPDEYfQMPEpD5e9Rh9QXUmK75QGpJ7Zv+GfpM8dy/1kaHbHcHRT85cDGa2pM8KginEBTnsdAo/53muqdgljF4m5LmNSZdeeCyS/GHbHDcU4hvGuVpmNOaPpGjRwM0ol/OVTeJqedOhirnOHLi6AObJXggKtqM2V4St9gaaeIsqvk9GOu9rjXR1TFOuobNYdTqIvG5E9tf1k/W76UQmnlOucNYOAMYf2sRgKbrROk4g2BoDtZgkhTZKR2RYoiK7WcflzEOKovriEZvgs96W82NpLsDzMBj6DQMaW7gMzDwoMEjWJ6ibvi7x+j6DzEGoP1o61QPTDcJNDI0B5fx8ALoyBgcvgwDo/cndrxD7M5rcFtcjiUMXYbAndsyO/FFMPqjshFr48VlK1E5tIvJZ7rne1Ekrl7UWdANfr03OCQPGX9QesEpn7fKY601VCIwVUs/ov8G8pHSGIE7BLbg8xB10mzMFqRisiMROqtc5sUh3KlTRA63VtFaRW1N5VERHKVrcIkIdvAoZR2hDqCJKEJfa2ifOuTXpug1rHG4eg6FnlvI04ENrfTEgSYFdUhieXYwx4ifL4PPIa3R3O5Zf9hJearr5Xa2d9zw+b47WoHW7nRog2M2GWAIgx0KzNCa1p63h4VUHsKIEP9CyZRPc3+QPn/650eICD788gG8/IKXL7/DebgAWIjBAhwhkb7S61oAlLtbtMcnjWbHgC8XMuO7RY7D9qCnOQ3HN1vHvRQIBFetY8WAh+fioSVOkxQme22jIc4/RMTSU/nYEDxXPLkDr8kOnnu9p/WRV0VMrdEo8fO+AHx3AyJGeX+H/vlxzANpLfs0Rluq4vceQYDB5PvcVgDXNlc+fSsB6II9HM59TJ4/+4zwA0f9l2D3D+D6Hx9wJYKHf30yOu4IePOq/0SCdwDedcHtrx/w8K9PeCc6Llnvv9XWvzm16lY83JRpu37P4hWG/PpqM2JswjFRJPaAiODp8IKdpXQDCA9PXwDA0AEJu6WgdMZhPeLh4QmlsKIANj33Oj9rJnsp+/OztvLJwpoeeK3qLH/z7goPX55VLxIMORnO/XMSNXWfCKrLf9ZpIcLB+uL6o3j/dswujtKP8rXyw4D+31qGmHXuly90ylBzeWTg7qIl5PVFf+nXAa00XzsH0/1aJPrfZet5+zzinIAT4yUw5qH+3lT4Fvfy/1r950fAid67vATO1HXuaUrXz7XV5IK5uqzlTe/39slGUNhWe47xxxwTnb3fXzfnmqH0jAuNXzOfj3Lt0JtIQpQxjW+CcP+TC9MPb0Xu0PEwC88QCJ5AZkRn3ELwNI/fhXm7+D5nitjM/3QoeGvLvaZvL3nOT65fJmfx7qFaclH2f17xvOaaZ/wZbPnKveT5Oy1qlhC8gPAO0jv2P+2GJ7cYTGgXtAcV9xfcACCU98UM9l7LeGPDwdblj6jz71Uu62K/z7qmLdWVixz3K/V885umooohV+qyKesEQLEoRDuUE6nhGx2FdxrpXDrMvhfKmN67GiTAkYdbFYkdrSmygtN1NzLoZ2tN0MKhWNzKJ18jRTT9JdDufL+nOpLhf1zKhokxlqEM8LckJ4htO4ayfOQJhym3lmXBbrfDfr8z47lFQFvEsstmRBTQxcKMZbdMcpt7Mq/rOuVBJwC0LFh2O1xdXeH63Tu91+DLq0PD27yF8tjqba7JFZsPGkbsJaCph1HbFXMt4KQBqlBjfevY7YD91T7Gzu1bOde6G5D9wMhEoGUBi3p+u2JKmyqnh0JxSjgKm6LFDZOLDOO054XX86qttS6mpUhGENsLvkwBE3fMWPcqXSBMueBPFq/AjOpqOG/SoWid5kQhggUaUlZ9f7YWua+dfxABFFDhBVI6+lIGfLBr1wqrEcacIML+Y9HMED0lsCmrhVhtTHao1/s9gi6NvclqzuXg42JKAYedFrboeYxIZ0VAIFU6Mw0kFVsk+iiBzKkhDEy2zzxvN8L5QJ9v1mWFQLV9WoClF1AxGZ+hBl0i7X9WJvm8pjz1DFJFuN4wpn5rQGd1mlhYQSdjXxKDxIzngI6WG2KIwFxivhpUPux6MAFII8a7qPFWSYXtwMLoQiBqKk9QDwP8FrHDR9i2WiAZNNs/fmevB9Cyg8O35qhKn3yP4gcAaRW9VrSuBnR2ukikkO4eRa+zpuPVO6gIRBit2vip5cAcSKyR+X1dUBaGuCEMg26oUZzQhdGpQZpC3AvUeK7R8WJzJyhtATPA0Gi3WisYjAUCWhaDji+RUsQRPogYInXQ4q8cjN1u4z1xw4jA0ksABi1PEUEazzrHsrEhnzz/TezcniIZs9PZmDS/12c5NTrVGxImpX6FdJulT4y52ij5dK6GEhHpfRMMd6Yh3pRprSKesxeeRIBfNp6/VsibDoWq6MiHvcHhfSz0H29PtLLRFaQc1ZMBzOmHOxbQyPdLnoeNEl0BD7oHlSF0TyVnB+NX7qTRWc397M4/hSwk2x0MbA1QavwY2FkwMn7odNlp1bwmtiOa6tpMyWSAjj5I9PG1c+vFX8kNpGPth5Ofp/bJCnZBjKt4f7z+pLBWnuIvyW3cjFjIdE63YPPKgd1cqxvASfk0wyDLswPBSA/BLGrkJeMLIeslI/oWvm6KHdVWSlrLxoIR5wwaa9/9acTWnqNEiL3GHXqFyKLUbbzD50PpUqHhiCOWGmcK0MnjlhcaCSKbc1qjWS8yghAE3fgmi6DLO/T+rEbf1H93G8xz5TQXMe+Srs+jZ0M1X6e0hk1WcEPbdnW6LNl7V9j3nkCdjccvxZziSJ2QpYoZqm2ODImFQIpmg+TAaTxPujp8VQxHnaWoE57TmWJRv11cz+DOfiMneWdH31E6U7ggx/lDUjoOQwZa64p1XRXNqTXjraKOvhgrMp+hOtwxGuoMWpumMbK960Z8MoSra1lw7CtapsuJj/lchFOGb8E8kXleTmZqFE5//TEWhBOXX6wAllRvylAw1uplUnZSMsn198vmN8EwaLMQiiPZpOe20ct04TMA9NpA9A7Akzo22Nt2RIF+6zKHQ9MzE8qHexw/PYBvb4CnLxAAO2hSwTaJCkN3SQC4CxoPw7WdECKaehvh5H3uffCJOAvwoLmZRqghlBDoQS5/AkPmTvWfiw4+GafHL1h+eo/CBQ0IWHZ/8kgaob19bktTYm1A2YIb0Zf0TsJYezei97zQ6frwwr/YnjJnd392J3PQoA6NtuSZdMz7Pz9hwUgP8NayhXb/u5Yh/tiaybxGgKOj95A6/ag0pr8XZog0NYC3hkOtuDJHw5wWUOVy5zcS/KS2ht1ShpOrjH2SeePWCndGRRXrfvSKcCWkqQCCVSXaiZlmfNvs/yi5/DCgf+cS5w6/kEKHZ4ZOmtfc6DnTyJH4xe+VIXRs6ZUrR13AT3FC87uSgGFV2l32PZQhs6AL2USi5+QrqTHfSkdPNqtc+uH7lCNZZLmPU2a2Vgie99yZI8W4LhZ98fz/LMLUPeDjNGJ15DHJCoTp4CCYydxpt11oDwEu5leS3Lr1s0wHOXu/H/Blqnl83zpuZGY/H3Ls99MFOCnvBwHPbzRhNg5EXy8MwheSgHR/R4wXUu+4txrhtRWjHXpAkTevsXdCk7HbD5WaqxwQ+oJHBn7qDM1Z9IRC9wCATo8AAJJbCL6E+DiP6y26Ra57KXKLTk/hKc0mJHYQXh29zcHUTw9iB9qT9RXL93yN076gMeIBVed32A8Lj+hAPVC6QpDnObjU/tMOvdKic7+fr+HcGv5exetc8TwOiJlWbu4X4GSe/BBxPCp4FjOpp+3nio6XdM+oV4UvNTqEcZFG1LkgG8//HhLun2/l9+vnZCbd0nPMP9B0nTCvujN106DHQ/GZ+LBkerV559zIzZv8cDj6EBHI8S59M20qGnYhz1GtucWaNMt/OUc6n3gNCyJvb289Imp7b4DBUokfegGIdPRnAEuIQBGd6flMPfoVZmTq0tVTF163HUuOUJoeHR+KMD2zpPFGDLz+Jnq/6l9snMIwqnWK0dEzRxiz5aSJkDQxaVZ0f0KjywyC2KNXF1MAeNT5frcP+PYc9T0iHVsYl71+j4YMozwQxqneu0a5WCT7Ugp2ux12u10o1FopWHoPI3qtVXMYt4Zem1KZPup3+cMNAF00Ktb/idVV1zXqVJh6RmkaDQ0Ijgc17mp+cs9TvoGDpLQnZKi4fd9RHu+tdsHvTzKYQB3zihuTfY7s3mLrmy1nO7NF8kRe7Y3CPa1ptXASqAmkEywoTNu/AG7qIc/nbsYIZgoDKmAyn0Uma5SPRoJ5pO4CAFV07Vp2cBaVFXoTvc9hUNEjWombgIvC8HpwJcOibkkN0mKQ6cq3XZuu71ebjeUndMUlRJ8JGNrUZwxlu+4nmeieR2mqgd7cK00xxmJGENNiUDduJ4hntJ9e11CBOcznlK/Tjeomo7gcQ4sZ3k1eoWKzJILmRnAjUsRucIDbgXU/kzu5+J7f0GxRyP+FGcRFx3ojJw8O4uvZDGVOW0UsXyxFZGPkYC5FzzNs4230sVBH5wWgCkGxsRgysURktkTeWzc+T8ZXv2Zj7kYShS6XOAuJAOKYyb1DpKGvqzqBgODJItz4rDzB0w7o/8jXHlle7OBjSnNab1hqxa4vaK2iFKWbvBqMO8/rcFkWFGJ0UbOCmHGgV4ftlzDwC4BG6nRUDC62rU2j+ECoUGMHBaz8ELjc+SgLnNK75jVnpcGRBkDMYce06yR6oFCjvRlaA5Je17KPce8d1KGBjYKY72RvHmMJGr/JmHvd3w0EN0zpw76/2Wiuy6uEwSMJkuCZkc57eRXD9vE4F3ZDdhDMMs44RhjssntNez2U7onq7SKd7DRMu2/Dh+di/dsq6yNvQ4l3TxI7bQzhW+Q16ShbGU50PkFGb6FjrTDMyaBuMM45ITkh0ZqQ8ZQOMMEizZNsYnNHAqB1iEWqs4+jIU0srBGCw4jmBucYnqiPWJ3ysFbUVX/YXe3R64r1pY5xf2W8z4jO0bcY4WhkZuTnT4x0uoRGe0UsP/X4JdiEL6/gU2nNWltOYFJFNimV/OZkck+XXW7XHNHK3133EOl2kkypmAI2b+YtM6DOvbE05tbpgtGfgQaRJi3a3kOnp21zqQAxt2IOdF1gjhlq+JToEEBlRC7bKOn7LTpvOGVZOwsbQ/GIcv89yecxj64X6RC+jq4MQwPNC8ifZkJx3qTEA+B36PJsjow2Xlqz9Wfw25BNfGHogMFpy/juLdys60R//JQx+iX2fqXzrasRpkH/LrWBzPKqaDeLjq+tH2Hlf+rs5a9jgAnUCN0cjt2hgYGIJPeWeBQ6YRjQiRldgIYedRYLY3Uzp6Li2DokdegpsChM9sjJkdJGRHBcVxyPRxyPR6zrCmlNjZR3Anx0A8PIbe27vMsjqN2hlYr2mVF+LuhF5VUiDF7MjIUJK1EgHyRWO1GMMT++XIarxC4hQR5dDgKwzzkSTRa4//kuZEBioP7rc1S5iOqURRT23OfIIdB37rBjpOHqp3u0358sRcJ5mpZeP31WbjTqb1Bo7gWCq/f3YADr5wd0AFfW9gLBNYDDRn8QIEpGeT799hGAOisgjeu+LCABalP6vrdznuuVdhj8qD19gYCwu79Fe/qisqmtw2rP7UnTFO0IqCJAb8qL7H1SFtVFexqtGGlLj+Nyqjl0iAgWLlgWXduHY422+toa29jhsPUXkR7pEkJO5EXXNMScHnxtmFMjgKsP77WxTFg+3IPaI46Pp7pVwRjHoIknc5qMsFADegOwZ/3ujgtLclK9EeBpwxYJGshDuAURY62fsOefcP3TPY6/PeDqHx/w8s9PuCE9Rz67XC+Ca7F1JMD1r/fY9Qf8v4/mNH1J75TKm4znpyzpu5TJ5vBqsf3m87nRv1L+kspaK0AwBI8slzslcbmAIbVit7P10wQva7X519lfWxv8DObkZzyz9Y710PDuah/vHoErUGeNdA522xwZbwxlBCGyXgwTh+Bg9Nv18Rm5aQhBXxnCH+Wr5YcB/XsVOcvKo9D2mwvesYgvP/8917kLpSfKcGAY0Tf3b1nFd99352SLr8sbb6763PdM3xn34J8Zh98/4vqXn9F+a/nsEkJ4SYezgmFkz2fpradPftdr7crXLv5mzLUgId/RfH9ES52p5608bethlg/xUZcfFoOjpwNoXkOEUACeKzeiBnMvBepYYmfEP1xOls/r2zPK9YmngBq6Xc7O8Osf+QF3XXvW6HE+/tMTsrjvwh2nOoHcJAHjBkJfpnZ7c/a4AON+7vRgi8WFyW8v4pN++T3bxZq1I/73b8mgz+2c09KhcEtXgg19nHe9nFzxVXENl4M88i6UyxhCF0BoBlFHD+9iH1GI4ldoOIzDw4/yh0qmTxdl8ws/XNoaJ9eIAj0EoJSrVKbJ8xV4jiWeyBGpWaGQFfst0e2prmz0sWdK0QiFhobdsmikAgTF7i2m9PV6WjP4Xt4ZtLDlqJPEMy3SRvYAjhJKGnkRRWokM0wIQCRDqZm0ue6M9jYJxEdtOEAR0Yg+TweMVzeLKYzGCJvCyqK/wikhNVdkMzd53IjCMO7w5bu9GrPdgcA/U0A3WyS3GbZbRG7q+1svNn5uBPXI5hGxTxYZTkTqpGD3e/s8ot0jPXIe+tXgnKVpVC4Xc8kzehUGM4xDbTejuSvT3PjvBmkumjfRh7eL5qEW62ez/mV6GhHoMAN4ar8BI2zWuEYQOjw8CUUQtDouLIaoYAZVqKKuOrym9c/zLReDQPdxdQhMyFDunMy59dsdSMggoidkAKaAVweTpsIhl98AMKOYfEWdgS5YOiDczQpTIFQgpahxsxjkKqlhtbDDeBZTlmqaABBpbtMU9c2F0WpHJzNqdgdAJd3/4QyXgHIJoE5THuUIzbAt5GeiUIJB15FADIJQ92vIKWKw9h2AuJFzrAZ3xhF7N5DOJ4SRp9OedeWFoxvouBTLnR2LJ+pRR6Exn36kcyOYQJUSGUXCv8OedxndFR7MDCoOhJqNmmKBtwK40wBsDYLCsVmhsIeCPOC9TVnpiAgCQEiBMLswPIMsEUGKSZ7SwuHB12ULC6yNoREzN8K6Uocsh3wYf2whhHPUSDqscP/EaiyGqKGnIyK+XbEVjq3Wg+Zw8815gRqvdQ4qKjFqXTSybimB1sFmQPduMBNwfQ1alml7Mobh0ufCI+eFzTjVGW5sBguoN1DnQE0R946Bw7i3gN0lJjU4QA3+jJkeT3Qt2gH04spLXWtjD9i02bnK9+c4dXWb70GLYWvPU6L4eh65j9N8y7Bbu1MG2fM6QhT3ueySzzNaz0bu37Rj3J1RQub78qOTJE3nbt6eJBMfPm3C2UL5ZqdDFsDgBgBJv7scxb7nbSxiTxMBnWedilmMXFRQhB97h9F/j4J2p4nsaD7RGLi8b7SGzNAger2bw5nPndMPJxUwVDcWva48xxA7NK+G9VVicIhhTkIAL+QZUAAIeFkAWjHCLL8+8peWyTCef3s5eTKt0Tg98YjgxuQcYt0lhNy5NZ4P5JGZzZ/pRfQxZFgXJ1zOiPzmNsciYDJDsadCSjoUz1vuvPFsP5x/hqyb7jde5m0iMnk8nsv7Rqb0RQC88UnGpTTeEobq2I+mU2QSCKdIZSJowPx4s37oAHYgOQKW59z5NRndCcMuEFHv2YlPc56LOm2BwHgHwjOarfcRCYhY277Eh8w4URyVZ75pPaZ7fV66oHE3pRGhosYCqmW18Sx29icwigIVdEHrDWiws5TPSweL8oXWmtEhl2+0Hxohqc6zFYSV9cxRqjntMoejPRGwLMV4vTq2wd7f0ULOIjA8dZXPnPKRbm3pakBfjzhaFDq6RqAvIoEAEGPrvNCmQ9Ah/RGtLWiffsbu14LyE6N8ukWhzyYjG5oS1eBJ8+wE4RtfX5m+9czc5nXPAOq/HkE/A+tHwf5ndVItMEe+y1VHXdMbZOb6W1rn7545uBpmHKqdk9KxQ42u5dODyRAjGMpnyd9wJcBhU2+WAnK/HYrdocHdsZLFJX8X0QW1t6ijQ/Dl4RGL0YEeNHScz3YAlutrUD+gvzRF0AraMvKnU/obO1cSHeiCq72itOleFuwW1YiLnSWNIqY6kOwaynOZXO7Ul5XC6K2dmR2lTK03LMUcXXpHKXcAPZxwgUAvoGQbSHOSxzy/q2BeVx6s5fflpGFecU/aTwAAIABJREFUfK7ZnAqOvwv41xXH3x4jlcXVr+9Rf/scTrvXMvbGIkCDmG7iPa7lIwjAM2Ynsv/pJc+Jr5AQDCjLBIPXCinNvLra4/nlYMhRY+1t93nQPTf+Y8hw8e7g4QyHTmMQWoTQjRoJxtuM54LskaCDyu9Vjrtse/lR/nz5YUCP8m1CfN4iOZo3Frm5vLq+bzrjkoCMLHpumvddUAE80dgstzI28B00D/qJ4DcRO7p0aZwItwZyf9/Wok7j/tc24LdszYgQeOtDl85Wsvl5W58odPpy5tmeni8EEO6x+6Wg/SYoeK9K1l9sbohxPB7Qf7MopV/0oFt/b5HXB1CmdG9de4r2TEcVPJMy4ywwOXMkZA9BTM/ld3jfiN6D8HncQ+NuwoxG4IcqV4Fuh8RShU1CTBy8Uzllqi4hpOvRWMKVVXiwg9ClNbTYQfHWcnf5uczbc6D+qkB8qYj3PcG5DoXOzIym7zLeX+Ki5mTC+Ip761HnMW/nRojHkXB6j79b33eT9nWKOE738piZ6R1f3Uo0/blYzg0xAQF9e/pGz+O12HKnwbzhZObSBv6W8m3M/9w8fFuZx/hcXQ6NpLmfCIQDGOpB3/CSlBuI/Sjx+dqu6+/LsgOBcPj9YAcXRrdDhdizvhn5ltGfhkCle5vigDOLWqdr6Ovl3Co9d8+l379O3N+6Xr9e/tgsX3pK6ejmGuXxSPQ83+i0V/LBba6DQCNfUfE6jDK4Acqj+TBH/A5F7phZF8DJ3qd61gIu2kKPCvciknItesSryRIcuTf1gRIRcDQJ+MFLTDHb7VDZa1MFjGqsTK+jUGkNDUXUQN53AI4yxpUojbeEwnC8cLy5uwFCBO3FDDrYonr46MRR5wzPsT1xBOhqIw9F7kjMY5fq96iWdL6a5loAPayawRVMSh9sDQQEODOu9le4urpWI+0yoNC9v602QyfarDVT8NWquYiXskSeXk75ulVRONaRHww196/mfOaUwxw27701tFqxHtYwDjEzqLqBXkwhrPBjvbRotxr7W0A61lpjvgsz2PJouzFBpFsqZMvJaJGcoewgDMcAmwXp2ncN6PI+234gwDFFmTzSc/Bzj6qBz0Vhu38BWrNHhwJBbBxj3iEBgRnGXhmys+9bAaljggioqXGbOyyqRWJteOSsQ5hrlLL/bpFoRh9YLIK0dVVuh0FVnQAAAVkUo+aytDzsNr8ly2BGHigiM8SiZhv6WlHXg7aziebGZLZ80hT3o2u/HfY7FIXNx5xCaBUIZO0QJnQsKB7RLoBYhFa3RVuoADbGvdUU3asGAaHZeCspUsuj332Y7c3oTdIaEVBfbJ5HmoMuCnVOpWguUvI+uUpkrH3QQDQYtMwNXAAJg0zr5cZ6sv4JGaBAH6gN7nwEN+b6OSlGb2skFZ1PpnAE0LkgQ1oyQysxqAiokUbRt8xjEtVKNI8IEPPsivklAcvYg8wOl6xrsLtC1AkPE/pax5lS5lfZ4gkCmuVdT/Ohe4Excr0r5kIXg3ttBa008ErhMBI8zeaj9wY/ezg6CjGrTC4llOJdxppx9AU33UhvaG04HhGZc7XPSxtOBe4Y01pDkwoRhnhKFKcT5JwLo72iayucaxogZUSdqEOQRhM3R+gwRwtioPTM/QTSdWC7c8jeAV5g+Pv27sHZONazQMhyGTfjs86nxUUQnYxLx8EYGWv3ZHycHpJQ/oW4Ksk8Iu7EPmj7JJVTfMpXgckgu5VnrU35O/Xgj+T7GWK50JG2x5BZxn1KFwg6X46iAQAB2OUr0DpQwonOZECXDbgkWWbQlPEOibZpCgtbj5ZixRXwZLRAbDw76bxGa6wPpRTsyg6Hlxd0t5r4PYsaFXb7HdqqqDRsjkeuUFh2C+rqibrneTiZ6u31kx8pfpPNtdMK0ufYp74lJdriclrqVszbSB8xIrRDGT2No71mWu+O1Djmd9pL7PfYFVv/y075ea1zXXko3Jge294FEO8rweTksYYHjRiDQrblKRpphnq/z/gpwQyvZNFxZFKz0+YYUovEH0QgDGzRE3eqtPvJokyVH2AaWxXGzOGE9mO+kGgpcm7jYZbwM3dcZTv1djakmnfo6ABevOvzGtnM72QfASDdWpAXQDxsuqxkFNXI/nHuc9kEXaO9iQjoZI5qguNaIQKUYg595OkbKMFSGz33/W/yuYoITVvBThVGG3vvIBE0Lup0W1fUWlRGbqTyl9GVwgXw9FnWvw5ngjLoXqJD4QgmklCrVlRLI9Raw7E3HNCw/yzg+1uUhyeTvTV3fZPAOALLF3R5j44jujTUTx3LzxY5Dz2LOuKViyjqKjFTiTyvU8n7zO66FpU13XkoT79jpbyw4Op3lQ3qb7oWdl2wsuqM9/00Cvfa+IojCbyQGo4Pn55iPh0GPRdvewZ4LQD2P71H/f0h7nOXVr/vSLqu3ejt+kmv70pU5xzsFMDN+5/w/PmjL08Q1AB09f4Ou8cnRbR6t0d9ORp/kbEHSJ0n6oOmqtxZLnRObXP+JwCIJYxLum47CDssrPKB5nfXMS5A4n8bUHVbf2xrtXcJtCCPBN7vdB6/HI4anGLPrL2DiKFgLHZGIhhyy0wVlmLnWUuPEYgQRFifnsH3t0pfHr+APtxjpMTScqChLxYRM4rPOgobxlhrB1JkBLIxXKFpAQpBkcZinjUK/Zk0kCp8GqHnguO/dJ08/vaofbVxW0oBmy7ozuiXD6470xz+61Pks2fAotP1pU80B9Odg24/C+eexa2xfKbi37dmp+mht5YLosLUFB+z4GvesMTogNDTceapNP6IKELZ45dnLIWx3y0DzQcIR1u2/ObVPA/d8T9Sc/g89G6/aR373YLH5xdFWyBFMPF2ukwDGjyNMPiYtoGCJjr/Q5L/Akwn0YVz/HEauzO/XSqXpuIbZ/RvU34Y0DfF/fP1M87OfEaDvrx3jWlnT1IvQpE7qIoJhdObgQ+mxAlBDYQbUXh3/z774qVdPshT+u0VKvNXlnOU9JXdtf35XC8ubXR33NuOBgCDdVfjef9NRaf9L6bs7wAXVTrW39Ja+E1Avw5hLp+dMqN07/RLIz5mg+JgdNo7v2v0biKMIfHnxlDA1bvifhDIsV42NPSkbYAyRkCZYxbqndHMxiU/aJE9a1FOsHF4ZekRAR+E0GgIiN62F0oG72/lqdOee/vDMTcyXzv3GRgCbXZAGGM7xn0W+cec6BL4Ynvfj2IASMZnq/FayISVLfXZfJfRh/C0fHMRf709f/6uodyZ15MA4en+92WaW7H3tPhhSE7uHb3WtXEVsPwAUO4Y/VHAdwbr6yvhjtAfE9xlqs3f0J7UO5ytZs2o9gKBBEzqnyu5L+f69dr3fP1/WdmS6u2PNkwDLo3iEOVwYq4g9kO90q/sSZ0YmT2f4de40DDAUh970oVqMpnB4W7NMFocBhzQQ7MrTESjIZa+gIq+P2DLU9+EMIyFbCtR7MAqHRn63YNaNKe1RV9F5/Wfy/oxlHEonUf18g7dXN3kPpcjTstrBP5tP9kBB3C3e+2bAbeqFTMiJZkZu90O19fX4IUjT3IhVQJqDlwY/LnXZ+PFShHWtaK1Dtrp4Z8sknoouxySXwdTmuVJXBW2WGGQLU+2j3EXdLvnuK4QM2yzGbM8T6seRCuWpaCXBY0VJrn1jtoq6nG19jUABndmMPKd2HIeqhEo8i/2AVdmw2nygx4ci6F09F5xPCqEc2HGshComJKFzcgrOltDTqOAcgUQKTDiLlKnBgTUtbZDo1AbpDE8H7ortd1IIRbdLDAnFVOIikGxs69pQeScH0uG4rCdo8GZGGZl1r3ZO6ibUacKpOnce8SuQ3SyKb4DlQAcxkTAo4csuohNXU0NxGwODw3H4wsOhwN6k3CeKFQ0FUDK4zT6b3VGyIQbpDgi/7sIaqsgISwkgBQ19ht9cFxZZoFUCceBZmgIoTCXpnnibb0o9H8Ne6yncfB8U+4wofZdUmcDj/RnxmKOP9IU06mzOsb2pjnoWaD5wMWNiUnGPyPUOj/3n8jnwvoqFgEKaaaIabbOzIjeu+YwFiBg9K2+HjTaoP9h9J/Hu034giooDTkCrPDlnYaTEwCpDaCWBN4h46uixudYFYoOH6/9Gk5YvWneW1fwe+Q/sSrpe+3Bh9whwaWmIaQ7LPEwDjMXLEsxPmk0QjqkAp0EvejaYGaU1hT+1WmkQaLzao5FRR1AeDEHJjJkjg5IZ42IShHaBD3AuVFNIs1Enw2U1hN1MLHxYQBNIlJPoEqyMCqnteNpQ0R8/evph4vuVbJ7RLpGo3QxmZMBNHQz9ngYuTrk2Vj7icRoGnqPM1kSI+LLdjkPuWNcCL3HdunL/Hf0ydckshhk9BVnil8c7uQ8XTcloi32MP9MzZzNK0Msc9ow3k/xsJ1V7WaVkzwS1moyBaZHxsZ3K2o35bP9mlBUeOQ/H46S6dyX+NLYmqMtRAB1AZHNO7JBNZ8cfGs1CLMazgydxcylwymHouP6nEgYy4POOWO0RvXkAPO1QvnvtNCGFEenU/n1qtP7LzVlvp5a4vLa61LddEesQtr+op+J5msh1kIdqXrr8X3oJ3QMVH5w47mMSE5TuCvdcV6QTNeToTfRMHKaO25z5bmyyg7IMMFSbO60hijXKvkSBH7+HcWNzptTi411MjJb2wZa4aCLHvmctR8+i96CYjRAjYAUOY/TTMT+NrFgnIesupHj2cYLs/6Vep9TVqR+i22jEzIolHiDqNMkOS1WBwFgRe+CZa+w1r4gIk2Qy/AxZnpmi9Qi1VCM7LrE3h9OgLU3cFW4eK4VVBZQM1OnOfAWc66E6F7uzeWPluZ5oCUBUGQYqFzm8lerlvrJ0j/13oEm7ssy8ocDZgzXdjZoCJmO1zWAJzTswMLmvDQQP0raRz4HJD6vtl5j+gevODd382/jSjea77x4+fU95F+f7DdFxtyLoBKlp2daG3Go3t/07hFwdZ5S+fr0gKr6+wMaqaF5Zxz/dJeP/bQt52C2v3z+ePL8EYB8ftRUbYmu7ABcExvkfyIiAJbbG4AIy/t7lV0fn+aAD+i8VvJVBLTjGrx8iXGaKeA0HkNcGg5LNGSnbuhGfqYmANe7HdbWsBRNeCq1pkjwQb/ch27LipgJffiEAUSoomNfPz9ieX8H/vDe5LGhr/aWNySIexOCQr+HedYP1veYbwxHBN8rOTCToMbz1Fx0AAsUIaGa6LHrnk/eO6iLcWc0yWnmmkaFBNjDnUBV97+CcGO/OyorQcxgPu8f1Uu/QRB4c8mjdcJ9T+/1TnxjyfNyInek146h9PQZmM7eTAnZD3YegPuq6owK1DlcU3oMqbN1QXH0K1uDTBS/X5ZP5utb/dhrUo3zJ6cfX5eAfpRL5X+xAV3mVSfj2paYO4N2E5cLZ0YqVXFlR54GFRrid2f8TGHMvaXhSfKFgQ9yB6aCB/6E96KKLSEVSN2wpoeengQ3GvJulCRIBhXY9lEvTwRDkvCauIrnvkESxL+ZTKX6hvemDxBNbYoI4UmwzuI7TuhpkJhx3gBgcDT5dwyBw73miisYfylT/0tRrVvrHft/qFHi8E+HI0zGcVFmzEmK8baQDLGAALwzfdjSR7cJI++cm9NYEIf3WeAajKLJZxOwOYSK+J/N5YCVVKVKG6sXAEYueFsLmVnnYX5n973Y9xvrp8OuvzPPviy/5r3h06+M93T1rHz++lRMiTdfu3iz/jc4w/kbtwKNf+cYoJm5EDYe15trWwacn2W5AehL/F7kBgxGQ4PQM1hu0OgpWlRiPMdhrJPgCArpb5ZhztArGmv1tTKLJTM79QPQVFyI9r0jiIO/R1VpbtyBeqB1nReIvpfY9b2EgFgy9PX2VajArBHjNr/GVvLhvOEF+w/3gIganT6YoVyA47qiPwqEOhq9xPiaugt5d1V69lgUAFfwaMfZXWH+S9N4b1fp6XeyDki+h7YHHF/hmOugzaHktXLuRhf4/0A5QVAZTTpr7BgP2n2bjTJBN6VDs7+LmOfvdmuMug+vPejGjt1+gTQBMaEej6BiQnnHgAcWd37qpgQbDklau3IxgbLnZWGURfNnExMeHh5xtdsHT0udCuOLR7LksdHIVW10KSUM9GojE4vqHWomj/iEyJBLmKJ/0kdkXu8d2AFyNEVKt8MlCUAdYI2U5P/P3pe2yXHjaL4AGVml05Ls2Wf//7/bmdZ9VWaQwH7AQUZkZEmyPbsz081uuaoy4+ABAiCOF8SedVpAkFQFIkQkjoCxeAFROyDbp3XB0FturXv+frVN6IoSUz/yU1Tv6nDgYQx0SUq+Zu6sKcxYljssdUFdCkotuHvyBKfTXQY4qZruaHuAbU6IEsZaujnZwqkj3ee9mh5QS8VST9YfhdfPsvlpreH8cDGj19qMglRRl4rT6RSS2t4j5qxC97UWc/QJIqtVQFTMWd0FUro7gF3mdstyJM92FP9JpRifpA6hDnXjfzrp3IE4aJWtLrUiM3VN2eLBOiLrNOqWu74sNBsuyA2TdlNzx35kXXfVERUelO0GG3OOk2Xodds7xWvJ9q4gd4SmM5kF5IoDwZ2nHnxQmCHCuYdGLUkC2BxkzIZGQETg6mgCYv0hUUAIpFO9PjakB9JwJVlfxPlG74omAFPzTP6ycf7F3IGsVnGXyCZyaGpREHU0alhEUIqZvpwdbM8TNOmiLgei2h8pwIsbtciCh4kIKGYUjtkXKEg6tNnc9N6sJp3TQ5cO1Y7ePdpfBdIuyJrqzm+ZPN/et5EKA2U6z5ScLVSnIYUhOSywrLzevQ9qWc+h4pvObobu4I/BGyAOfwpHDFLLSCyVAK2+HzukE6QJtIkbo7s70HsqopY4YlnkagcKM5C7hc0y/kxWADpQEUQgkY+qQdGGTwPSRDjQSnlEVKebMEgTmvFxifsIqiuIqvVFJ+1Gmq+hZQz39eL+ODWZNkebB3+1zYXMyKZJfucPNXQBJs/YD6QBC6RIr4iqO4mDN9ka9d6y9ELlgrpUFCqI2tWJokFi8LkZMWqyWL1UA4PQmwUcIfizYqJ1d3MUToN/9MtqIUvuh6VWD2gBwjlJoHSIcRiHRQDtntlvwWndnffi8pKJIMUCLlQkVdYsBaAxizTxhoFTFDpjIBylusIwx3yl4TAXoz8nw9RHcsGSUflec/1wI3ozQGHomCFsw8JB/pzQgEPvUsQ+2wZF5chCx4rNGD82Kmpcr7mMdk2+zffGoNENekveE85vvyv1jvnp4x7T+9zIGmOK5xLniCJQDDS/b6KVnJWpR6LmhRPOOvboFnxn8Ruz7ofcazZpFqQSzge4U950ULbgPFpRT6cxZ+yw4NAcl8q0XocttNWYwKC0+Zziq+q6Xq7H9aPyjvglM4UnZ0V+GXQRerDaHG26gemd0xAyeCZfuNclQ2PYBlJEPyNgzzLBFeu5O0mHq9bviprTu2ek/aY4r3SQjzTJRWAM3KqTczef3bZTbePzcbjeiihdA5geC514K1KvkyyvZP+EjHuM7HDnO4UR2Xh2Loj73NRsfvtRomQ688nklQ7Y4dARU73WeQ6Hg5lYnUWZzix0D9LvFjM22dw4n5PuTptBXwMmC2CLoOA8GPq5J/SAfUvofowxWN8JXWxVBN3nTiCto6uhZJYJ2YkckYq9tBHibDnZYJNe9qLVHa6kglUV3DuoNShfPNO3oqAggCQimBq+h7sq1JEETDSLg5bYbPfWs2xJa5GB3iZUk2Fb7QD041ecfnuO/vkbQJaRXykycwmdCERfUZTR9A6kn9E+vER5VVHfP0PDR5cVT0D6AFKgkYHMk/Mh8nPO0EdHAEfOCxQPLpbunLdfnA5q8A1/QPc79d0nKBNOoighI35/gfLuE4goS/edY5/DxnX2g3/AZTMPdBDTWe39FYqqg5Yirvvp76+hInh4/9GCD3J36Ki/DrM9wecaOhAh4gR1l6WPbKwCq/1+73LtQQUnWBBDJwt+fvriGfq3BytPSowGQimUAd0zMsX6+QsIQHn2DPX5M9BXKz15geIEoHXT1+6ePYV8+4a1LlAVLGAs93dYHx6gHmTbABQ1XberovuesLFHLXTPJnfn+Hk9gxTu+KcMlCzOc5gL7phwDsQHiiAlI4SuI2mgMKF1scBVt/tqBD3CZF4DwO0ruDyF9m9oMAStOyezc+oyY72Ch4eNYiM+ptahGxv4yRcx0AqCQ7I6qgBFRrl9fve/XqH9xwecFLiE+UFNp44gJ9vhBfDgrK8ulX9zeu3w8xcBAk5kA6O3GJHx1yfOdyLxUzCc6PeOXPgwRy2llIg262E2INWJSW/aXi7OWA1A6kIKPJ4sNssTDL/c1WV2XQS611KSz4aMALxsjhjs/2mpKGSUGpnmqlbHnCnOXRaoO3w+1hdRxXldPZOdsBQrTdXcPrYsJ7S2pk66CRSYUHtDvzMQSjIt3+fkXoDvWUIGee6KKTHkGb0OGpsmKdXGgxmdv7/Vju7/n9D+WzvQHzWM/7ApNrjqKYCniKu8bijZs14aTstQJUHhTE++kZ/PCnsIbALhpADA01sJT16/xuXdBzSyCCM3bdsjyBhfdsaNtdBQnWeFfhvHGe1aWR/3Hlw8OSPjsQfbgPbPpM3PcWtM5nACqr8jDf5hWNFrZejarH3cTgddDJW74AWWN9UzlmztluJ1VBSoXNB6g3xQ8B/21szAmtb/ZpuUOQydY2TD20IiBIYd6MJxMp5PE+FQPjOCMowmCvkB0UE63R4KwI2VcSjSPV2PFiSUf++ufAByzUmvw0vGEei4OW/HE1xHqhGOP4+mfvS4/nz8d//5/TTPX2f4uoN+3fo75mC37Q93iU6fT8eooXbQ1+wB61MAgKBB6DuqPsMIbZgUC2wPwqSKe5iScxlEtOvF9u/Bn47a458TnF5vXBb1jTg3sTqE0zjc3Ba3R3//tfZXJMF100MWd9Q8DnFw3FBes08yYFVBEK9BKA4vRdSh1CFk1arMiMWpoO6RLEJhjSPXTo0cTs3D+Z5pZNw5X59GGApZsn/G+JnfBc+6qZUetL8ku0cLSdiBa7n0yDvmkYUx/FfaLYe9PdseGtnDMcXEBvEEJSxccH9/wto74IgnYSAntQNkd/gtQ0UhgGTIVbXs5AH/XUFs2ay//fYS7eJOn6jP6sPj2cGs6lm9ZhANKF4Vew+5cyn2g1JoFCY3W1/NQai6pSoPQGPmhKBSl+0atRG/AXRvZuOuilKr8TzybEuaMyGuKToPNGFcy6sFegLoEvMUYvNYBmwmxy94TMeIA5TCHB0KdghuD0aI90SWSGHUuuDu7h5P7p/g7u6E0/0JtZpDp/WGta3GHxSgau8Iu2brgvXS0FuHiqJUe66IOVGYDAp8qSecvI66Oc27ZYOvF/S140KrOWhLwL0z7u7vjfZqsSNzk7TCuDnR1qSbwUHaCukNp9MCrQWChk6WaTpqvFtgolKBoHvtVDMe2uoYRFyhATcPd6JrZmeTwZ5TsYz7Dgs2U8VyOmG5O3nASEWt1WvHU9ISRXS4r0MYV1SBy9nqNYazMWuThSPcTuKuvrlTqBsvXJYFp/sFJIrOHa0pmmfMmrORM3rWHNaEWg1CsxRzvFRmg79ER+++rlB0oyT06rXLF7svHGjmtHBpwOYZtox3C2ZA90xXCeev+PhszxYyw6zt5elcMPE+M5Q76oHfJ+5IBnkmcKJK2D5gtozZygu4lNwL4ZSLM5WiIgJQwYCw94C9ExLr0bGqoF86ujT07plNarxMvE/mWBYL2AiYeee5EWQT7yfX+s2iaWcmCzNwiHBmMFeUSuDijm5R9NbMqOyZSepGPAMIGOeHLh1ra2iXNmiKrN47MVCWAoY5uXpn9E7o2rC2jobVnbPBwSjnH2RQyoDxAW0Gs99j3SZYhdw7PgdcTPc3o3ezjAlfa/JyAYDxdOndMu1dDyVX/ARhGw/dQDF01QjGMUalgGf8uEF7BhzV4Jvs51fk54ihEkbwDgCRjotqOqkH70XuA4VAugVkdJFIyE3HNHMxzlMqunSUVjwz3jPxwqlZihkP1fZ8d0ezBZEAoms64MxvyOYwn8pLMBTNeUjw2eApTIY4siyLn9FoeNiAkV3vwQADucXy1rQLVmkQceeGWF1OkQ4hQfe9jwhECk+T64IW9GDBE0Sh12ueucmvmsoa23vjYLjxZFL832liOrDCAkHzfB97MM8rY81nwR7lqYjM0J3PS8ugTmhyNH8MZ9f5yPm2eO32BGh6VBK/0x8nXUneS0Fz4XHV0BWHypDO+3CM+wRaYPGgM3P0xfOmufQzf/HSG84BAPhZnjE+m9WSqZyGCDwrHdDiBmIZe84J1MKZou8Oyc0l9DKfJyY7g6SEkNQHFbASIuRoDiBczmJ9nIu+bjvq+jA2n41G2490+nxzzw2dbFPaYiar/fUU07DpIu3eEXweoM13aXO+8p46Yfrvec9Ef+OaEfxHUNcRzeNhegiBYPs3aCECmywoLvZtgXKH9Omc6ka6kHlxjot/WX4lNkTuCsmODlOJ70ev72d8UjE/MgK7A/BnDhiOOdLs13ZNLIN7ZgK+OzNoXcdaYPD9rL6g4/x1RBXz3o1+BSfM+cnnzv1DSKlhcZpvmD/a3DmdP6J2S3TVp7fDEG1QGKQdl7WDO6P2gqVWQ1thQq0VAHkZJ0Ma0gy2nHiSwvkzcs0itLi5ngZZoQ1YISjS8ISe4L647QEEYvXgzpKlJJp0SHOdYAqi1clpLj0c6YGCZDbUSoY0FdWkGXY2uS+M1QNwxUsXiVqWqwVNCtCbyflqZVf4JQHvQy//kmvKE02pQ9Zr6hw+6z6WmYtlaQTZJp4F/TAsUuQbCRbnhRtbDgH97RdkGQS/ew4fSVn7SOP8R+n8VsC1Y3spMQcok52tHXa+6MhSjrfk79N3gxvZPjtNju/secokyuesX75lffGRFGgZsugiUIvIAAAgAElEQVQ2wqaK9dtDUCGqR/XMj9+UNwUAPDFHIiyAQB/OqBhBAHFPUcm5DrZ5VUKSQud2z4AHjsaaMkepA5sJF8dA/hV2UfurlghdM/2RYkLzper9VshXgF8o9Ms4X8a75zQWAtJ2GhQR9DEerziJOc8B5P62dxnqQotnYdD+PY269sZ7bS/fv3H5/EGHd8hR3ZgsWGVwKcJTJXzPgCnyREArQSDgtOlkYF9SusslGCKapzlASK3ksP/v3hfkYcPn98ofsKWUA73gV/7Wg4//ZLv1KE1JYi3QOGot6I5UZd3xsktRii3H7fpaZhwEn4oAdMZSK/plBFNXrhmQkjr1FJShCnBlTMrFQEZWCwiTiWkEqc2zLWLBk9Gn2R66Sard/7bZnP987b+1Ax3AXgP+iZaUtZU0t9QiHQS3vWQisOln8dOViNV6UZcIWzYS9U+BRV/YgeQ14+UnAusL9Pcm8KLej05v2gaCulKASTkNg/IVYe80wGG9HE+/OjBE9Oe0gSZFbv+KvRNiONHhivV0E0XkkAk0iQO93zcrjJtn7ju6G95TNUUj1NioIRKZtIznqMSoJRQHzvoxzOxwogaTxL8Dl7emDhQQ6hsXJ2p/AybkhOydShYZNjPfVNCCZkLIhE5jWg7SaO/f24E+1n6bdzfEVMxFQDoRhryanHrOULNP0+Kpf38d1zV+f6pbR9UDmZC+m6JuN8+GmUwfSDNj/YEnpQMDFiY4/cawNrU7sai7Qc9x/aDF8aniiT/3OxncTMxnzMN+bNFfi5yDZUdNcxAHKZ1+30OXAVsbk2I4Pi0y1Z2h+jTUJTT6Nt0zGMv2UDf+VgrnGk1zFZR26++jrUKbN86Z0pvxhEFofztsPkvAeE6vjgAOQCxTZvPYYz59zYV+rd3i/j8rFf4mfevqmbESy/OK9iX2JmE5LWlkJSZcHnoeZgTG7+faZDPLBLZ0NsCAXXk/dOo+9tnBT1/UQTdh+JsvDUPRxLeMcduBavem+RCwjsf+qRZ8PXq835Mbh/qNFn3edDVk4jTuw27SjT/3n/uzhkFNh6IrwNqaO9dsB55OdwABPTIuXUbkYaU4nw9e6M7KJoLKxZw7wmht3bybwcMxBnhWXugOfsqDoC4V6/nikd4w54zDjmeW8EGTLhNMOk06Q0DDzzgUPs2nIevMR8ihcHjNXddunMdnLV43JCTJTarckHUKXCbZ56H9dLftd35+2q7hFcejIWedE3vAmV3HcSMImGp1i8tMyyC3A4qoZj136QqlnrUDbbyMBV5rFAwWRSnVMyUVypLvsoA+zgw66R3SizlxvE54wHJDAWJFIYFW9TqIDKaCWgqKKJjFDGSt25q6UzjrA4skdPbaO2rqZwQtatc7akFAUg8HDiLCxYKFGgDWLYSxO89MfR76T0DgF3E4QVXPjrN/ogINrhB0wSHVKJ2qkSG9nE5moPLs+ND3JGoLw50JGkFEE/9KnUNzDSJjvMtENypWv5sITVeUKoAUrynvp1kdWZfsWY0cjgmHdE9HKgxxIOqpDWO1GVxVFVILSjdnLrWG1ps5frt4jbaOvkZ9wflQM2RToFMQwZ33BBUzpgy4f95khyF0R7IsWSVFi1oNvqczI43cYKpi0e4gRNG+QNtqDn/d0SE6jLjWZdPCiOBOHZhBOuhkUtwGzyHnvZYx0FeD2y6wNZMGgArunjJYS5ZNYCJoLYA0qO9nkcguIH8eQ9HdMCvJI4NWbPnEyyAoFDxYRWUUKUBRg5IHeRAObE+nYY4sC0xt74T+aHIh5IzPj9g4qQd8vsO0RpCC7w0O1BM44oQCWdfVmeksCtnpIZyJxvoKwOYdEHTIenHaYYhO0nfizeFQjjgQogjwpXSeS2TIq11vAREj8GtTTgou1xwJRNTGZ/eKwyUyVBtEOorYvupRh9r5TzoH3dlNZIFp3AuErESAdMskCWNjBDRLZO85pKiomkMijMpO1xHgkfC7gQTjQXKBGgExhziL0Yv07rI9HPy2clE3kcqQkSDLHIt+EIVfU0cg5hykTU5FaUzfqutx1tiax+fTLcZZMtZsiHb4xs7nzd9ktuv0b6wtJeEEzDPFpkKaEJMeNg7zlODxHgw7RH7Mmz4x1MuTuFtDZXpWzA/nu+I5CZ3u93LOo/NFCsf37bMUXIcelX+RvDjKigR9kuuCVBmyyriXzTWoKqnXKROUGIi9qAotsynckVBCvofdSBRZAKgTykLgUixYpgvKUjECzswBwYXRmmwz3jdUMq89bb6nzcVbp/XWILVh79O5iLbXjmXfvJemlx2vQ0wTQTV0XqRNJTK+rUxRXGu0M5SDEHkjo3ysXQ4RAcU+kTQi4x2ur3eJPWHvimCtYfwm30P2V+xze8d0nYbbeFqb/F6zH/tTopH2jDQR/ZfkzbEHtvdK8gSNoLVcBXjpSnKRNS2KjmzaAKyOUg2bs94k22dbSeiMARNOILDeQejsDvFxfiF4MGDcmwsaahGBNULFZhfYLcqhsbbzVbPs836rv0R0PDmQS6zkUugODCELOAv+nrOVyxl6lukZ6kxQPTsSnQBitz8p6rqgsDnMpYiVduBRd156T0Sc3rvr/B6E6dnm3Z8d9JWIZaxQz1qGk4cocP70BVxL6hgBzy5+kZWhI0C6IZbJR+jH36BiwYeVCcIWfMgenxryHepJG5gWEINmYk2ghJPa/nog+66KoSgWVTSyfjWMjOIGZMa3rRFQXxP0nU2rqNlkl11C0Zy4pTQ5rih/QAHcv3qRNc7v/ngF/Y93g3JUURRYQxyq2Zc7DTtHwcg4jxrWBIP5XjE369B3l6/Bl57spGUhu09VUEEoRLi7L2hnD3yweECjD1XPuAW+f/0G0oBljwxmawWE/u07FEBv/iYuuEznGguKjSC66C+5TgRLbJv63rrk/gGQZ9QsceSB5fF9LQWFCaVWtNbw7eHsdGslnIpfe39aQET4dr5YDKOPd3XkoUUtu14+fbVgEV9/Q59UsI4yYUZywVhTE8LFGc29Eu6UYsfiAYqTEi5kNdFXUqwwnvbU2GzatWSiIwHQ3n9FeUVYP8Bh3wldAWmC/vazrYELEYE5zaOTz5ThYcgWpEVkGe4A7oNOlBxlgbzGe/igLNu5uDZ27wh6zflBnMDvXTkbJQW2Unzom37HZj//WgveqJt3af5OmALO8rNZlxi9Gygq9mEERpv8dp5QLBDovDa8eH4Cmpdxg9tJWsdSLaFhbc1QIpjznbM0YSBRxCoXQFcYXy0gKp4Rb3fGf3X625UI63vITTW99kwTL9y1TTzgrlNH0m7gS/kojpSHf6L239+B/qfafsUf37SptDzSZqY21ELKf7Oimt+pGbgbPkI+EoQIp9cV+l7yqZtDAoxwt4RN299p/93fRN2EDfP5q08dPG774CvY2c31tw6ho0VNkfm+SU3H6XWBvpdRqw9IR0E4GTa1WvNeN2BAvW76S6Ma/TQi4NWE2Dy+DWPOyOKZUY81267WfhQKxgt0fM4RBWysbvp5PUMGv+Of8/EbbrWfueZWu9f93Y9Rzfa7gIQhpFzYXh0H/qSV/f3mRLfghB/T6yzW92sH2L4+TwrQfnWOnjU3ASCZiT5fp1D6Nr3riDf9+t+EXeLIjabTf4++u7X+P6KLnXp0883/E9rBjsvf5ItHvIZyIyPrFwL0r4IRU7qVI4+1awfxzyqeP0E/dPT90Yr/3Boe79C/vx0ppv8/WtB+9IcxnFSEcBoAYRheTieU6thhpWR9OQBpeDWDuBlZoj5q8WvP64o7AMrmaC48pGAo82FgnwPiNo5xVXApVm/ZDTpJUbM3ZdN0s7a0mf1QsMNYNnG4s/OoO3tPjCP8+enXx23+dM1Hb62633sBcDq4hnY/f+brzQHNIn83JQAUlv2pAhaDUlzbCl5HBlKp5twJo5VlSdOo/euyprsjXBUGz+onmIAGJ5hzp62rGduZzIHeG1rvkOYBOqWAuIC6opOCtKNxQasVWqzmaW+WEd27ZUdD4ZDROozmZBmRzQ97Vu9b3eij5sBRMcj5Hgdim6sIHIAKhNuuZntcG7qyBwl4lqe4LBdVtPUCUUUlmHOc2TKCAWwUbbgTIhwazLh7co+Tjj1h420+Znd8C9wJSP5/zwaEQR1aMKIFidRqwZ+slhEmIj5Gc7z1IijN67+7gzOMqASgMlvmtq97KZzoBUrI+vDSxelAPevbnIHFYXgBdzx3Aa8raGVzpKNBEbXDR8Z9ZKLNxlvRyOQ240DxwAQiZImIeScG/wi4c5GWNay3m8f661qrBwBMZxrfL5Y1785EMTQodQXQEGcZqj+h1WyEQHAmQReyLOnI6OJwQBFwJshiaAZcqiO9W2aAage60USQs5AZHcV1UKOXyJgGChO4xnstl4SjOA/b/C53CxatAFl9vHBsG+M1R6r0hrZ2FCFoYwj3sJR5SQFbPzPzeWYYxMphACgFICoJT521VimcvwIVQuY3EK7/IWDr7YNwtlLQslgWv3fbj7aU+3m7MJ7tEAemmdmHmNHxe5xs7BI6PAyYjDNZGVDU4nJMKOrLe0CXIwgwHIafbU7S0OmO9eKZWOaHEBD1PGswBR/38cSekuGUCb4RZVmsxIQHrxGN4Giy/megGhTUkQ4Hv8TuUXL44wI4QotlpjlvhsmbjshaDVoay0BOo3lmTNlOU9/nXb51WIdxDttLpjEP3rL5zs/OY/304HtgeORj/XX6C9N3O5rZ92VccePv6XXuHC/h5Obiulk4wKPrsT8iWMC+IMBpaRvIPmf5xZwfNQPGiFwvpxmO2q5B/z5BSkAPHc4/Y/XzvT+fyS2yCu2hjTo9Zd9cH8Q2OFK7OMqcQNKpO+mzwf/EgrOiX4XZ6j13vT5CHI355h8/caMOEU9TH+fvt79OH1617ef7JdLddxsNl8Z8EHA8jnCm540DVSODn/J5lPM82zZmnTh+zuhwGoEuwcMUGPWct4MhcudTMB//QfsLcb3mOZsHKILIvvhPKlOg3aYDvhzbgB1zSoyOpJ1zor8MjiaTplZCh1KMYP530ObwkeQmRywPY7n06u5psD/Z1GWdbV0LIAynW1cCS3fUJzu3jXU3OSFEWd4o4Otj/ZQiPGLoz6owxLIuADWE435tF0OsKh2lM4QLmEeAjdVC76lvJmKYWqBad1j5YH0UhxEAqjLspZs1MEePfabpWO/+bII7SslEmgW8Rp1gOxsu7oAqZPqKrZciyoFeaxhTu8Fzq0u15rpKJ8Xq8xqstYcOou64x97uYheOWRjSai/+9k3kCwCgkUL+8QH11cvUyQCzGczatuS+GE70mR5jHoonAl0mgr7F+ebWoY52qz52QjnL0BF8JPGs7E/MS/AkjC3Ypp02Qpot8/oypm9z1o/Zm6X1UquPkgwBYRp/sBPxM0fEsA+4bbtWxJIE+GKBnoV4wzMkzuDer/kIM6tQgoEMuQ+piaCLia2CMBKoAFggh/9+IXOcn9xOvrhdOZzp+2brCzzFmK8OgN6PiTdHv+nrnQj8irB8UAvG8KdEstikth2+SxHw7FGjfSxU0F2UFLCkRdrE0EXyZzzj4WovHv39M9T6WAtZ+zPPmSXBY09kxM5PxzosaLZ4gEfvgloX45+qOJ1OOPWOb+eLIwUO/5L38mqkwW9LmVBMdCB5PT47vyaTgJus8V/tF9o/qQPd2pXg3VPoD/bgBk4mPnSuGsxqZqYAWYayn28s2PmjK6mKqi9M0UIcy+Y79z0ewmb7Kv8v7fr1o5Ya5Y3v9WC+7EWbz1Lgzhe7hm0B1c6aSXEnOpiq6nZDh5amW2F6s3+EjNYKQUfwTGC/p+IFTktB/4PR/6FDKf/doIvU4ZUJXoOFC+7+sLVYygKFRV8yM/rvbtT5x0uIfto4vK6GDjhy5ICG2jvSxfl+xXY+rarmC1QA9Q1D329pYBNdf/VWHcpsHM4GP746JNBOnuz5q/qtTyYl4JYQ5unJBOCpRibioMsHGhnj4WyfyfBerc/3IDzMRdu9D+PAoIGcapF7/ownioyoyzH53/G+s/dnrjfD+hxKXzbnsaFCxvi245ara4xq9xmzgNVAB32zgwP4inZ8u2w+N4id7TsPG22vOdyzm8+PVlKvxhstIIMBGgd61yZ195JQcAFcH+Z3DOeI1h5rPzMHP339n2zhprR80Xt0GLTV3HmZA1aY8f3ddwDwyP4zGE8A3IFwzjmPZx450b3K7o9bDvjGTP6E9nQEa76vFT4hkSLOWTMbibHYger2uKItGHtuHEy3n2H3+aZ/2ZGD8cy78+bwj/jp9fe3vyWYQzXNoen4Zod9VRHPMrbrmzT0taPWBaUWyOr1Ej1T1jLYzBnYWkvjKZcFl3VNWSKegQSidMDztEBmZ1dAzIEDMuerZZsaXHD3uSnFIKnCgGJj4vH3eCq+P3zHaTlZNq7PUEQp753n8Ss/GRx0lG2xv7NmJWCZFADad4P2G4EJe4P4zMduHIwuuln4zUprrF18ObJKgCmLKHCCgc0ZLbKK7HcBqZk5rF4ggdsK9tNmF3VIb5eJqkC1THMuFbUuqFUtu9j/B2Z0hx63jaCo5p2BqHgmu/g7rX50OAqZCorCylAypYG8asfaOkQtQ6W1ji6ehdLHDlP/bxhuzfDgeTmqIDIoZXIdLw2ATCAJfXTwExGxvR26y/Qza3/S9l9kGLeAjmTLYm4iYFXLGJo3tQsny8YEkIa/7TtLLUNQkcOm9Q7SupGljAgA6ACZYY+K9VWLoEuFlIbezAHfukDQwNIhpWyg3UJQmoHU+lIroVaDEo+gAKigO7lxZ0jxOaYCroYeYEEGQRaeqerWERt7ZBS5k9cJOYNknDeBPDPZ6wwShTPdnTVcRpamz52G0xzNs5OMj0nwCHdOEjMqPIuOhjHAt1063btDuKsEgo3/U6svSYqEOZXMTPea8BEomY4v5M9cRYtCQWvdgl4dmYCVQZezZVYtJ1QoUAxWldWcUOroB4HE4J+YAVsMED6gUdMC61nV2hoaM2oZ/Mcy+jnhviuXlAmqXiO1d5zPgbiA4bhgePAEoyyRter00ShpnqGodbF+KHLtiAmkVn4gAnhifwkA4mIGY4oglsiOpxxfHM9I3J/vTkdhMzEeoZZsAyrjlGvzEfuAwJYtqMBI9QaIDOlBZGQ4pqzIc04Eh1gQBjlPF6KR3giDnFaYg1IDJ1vV6+MSpEeggteA1anUg6/5HOgdjnP1ABVmo+dSGEtdNiUc2DdrXh97tCsg3emoe5ZfH+gDSiCyeowogAqB0c0RzgCzgrWgkWR/CJbBZ6xw8GGb7yGvgMispoQ+BeVR61iF3NsXdNpiNG7cuBRovmPSk9VomzD260YWz68dQnmrZDot2Dt5d8/Ec3mbMehxWXauYQ9co1BHdk70PV9Jj6oFsoQDHekcpWskr+lANM8di18XezT+sY7UW78vZjHWVAQoRaBaMAKkBEqcAT7EmvtWYPtWe8fd/R3auuIiq6+Dn/5EQTX2LKE328tLCZoXtN4dNcUcuJXJSwlMTkDeLuLsHNys4dWpYfMlNt4Zb1FL9CoLerpud8tB4+xTvsfvnPkMirut3ME118bOa51OIughkFNC1tt3EcgTw95IwuSb5MaYcAwFBDXTCKYdaE/zFGp2K9dSRwYziMFs2b6UN+UwcuyhKwUqUKyPasyNI8FkkI+P2feeDmJyHZdcf/dAkv0+LPB+7uglS9gg5yd4iukWMgKNxCdoMKKJDoLeBqrjpnGgJ3mwqoRjOWiI8jmEwdX2jQ7/mHRpD7SCx0uLKITE4qFc5pIanyqOhsCqw3Eb6xTzujMeWcDe3A+TL1UFFzKEzcLF+ZX9jKszwDMCridvWNRjB5D3GSpN0ABBuibCmZDJxTOZTrSoZ/2r0e/Fg+9OEn+7ykiMWoD6ikCfnwP8GVReopYVRTqob/kgYLq5THOt+XPwXYZlxz4VwgpN1NAvric/8UdyzD8NDaWTZaz3d+YgjcxvwqCr4v25RPd2NMCDBGwu3iv4NYE/GD0XAnipuJxXQD+hvn6JxfeJdMH6/mNmmheN3fYMDzs7ZbzmTgn86gX6p8+WWe6fRx4rx5z4fC3e0ep649q7OblrhcBgpCVKWvm5q2LYrcl1iDuMIAN22jCZo666GJw/gTPLPlZrhA6E/B1ZuTMfJBmlXsSfr2IhoBJ8xtejVi9VpIq2Njx/9hRttfJJWe5UYWdfEtyfFlzWjuYBL9XB9aX3pKWB/aI59ggOuUBx51QhAJ7/9gIfP34Gqa3JvEZGL4rqWefL5Dg/+Tp1DIA/8vUPGS6w/guA+99fWJb92kD/8QUPbz8bqg29gOBz+kHe6AgcsecTnrwmMD/H+vYTFl+TzET3dTjB0XaDjsho+tskxlmHfY5B8Opr+MjAUx2100c2+r65zDhQ/G7e4vcNKTQFGKWuOGY85IhfdaWP7N9jH4udkZXQJjoALFGBAHz//oDCDfd399N5HKjE6KqoxeioN7MfGNIjZTCuxSBbAIKhJpQIFXLz0MneFUMbKm32JcZE6vaKaW1kGidNUxJ6/6+2WeX4Z27/1A70/9w2NuRMZJMcTWZTX79Cf/8BpzcF/V3H6fcF7e043O3vvX7LMYPZKsX/yS2MartX5jlp14973Y5nr5SmgSK8dD/ZJn9VMnnAHekYUIHw3qZAE0V/J+A/GPJeUf4tDgR+pUOhmW1QUJjQRVHfFKzvXgD4/Gi/Ui7owedH46DfPArR+s1vCHB4270RmPxBe4fXZH8yhUvJz33X6j/F9Y+OYlwr0+/zz59tRzXPj54RBgyOCGtXeCODI/piwnqs5x5Y7Gc7SPrsh9ecyaDpN3R+Yyy6+4yn58c1VZ/jQl/y83kPBcmsMCXm722/Lv5m5WHk2JomajRma1bJI43/tr7+12sdWydvrnkecAHgAYR7AGTOlTzWec1zdynHfvoZlv2YAzqNJvm0v95uKVhHDvb9GxUjAnfBj+lhvn8f4fvYvNz67jAIgA6uucWI/2QznmVMvzB5jWivWc4ni6R2w1CXcTDt8IO8Oyy6OzK58FB6VRO6eR55KQazS0T+HPVsv0EPA7bdjBXKk6HMoYu7CLxE7hC94eSems6/6eC6CbsKGnX6vPEThnyfMp4mp8etFdDdTyCMF/t7Qh4+vpZ0IoNwn+HbsRV+8+e0/zvZHm0iSGZDrKSO4QEAbinoomi9W+21ORqFCKUKmJF1szflc4jNANZ7GjUj41pEsarF+0szB2bPbFlCKWYMICGDz/ZHdvHsWFJoK2gOe9wd3nxu4+B/IAGczph1OpAi6wPb3z6LTg4JS+mfDz1xGKP3mVqsxiu7CDjhJTX/bTtsf6uIRcK7YUw3B0lb2zniO293RAQQstZ8ZOewZ7VzLSjF9mEVQWuehetZztqt8nsTsezGqWayOWfMeV+JALK61OxlHZgIXdlg9wngKlkeg4tlyBaHHLYDuK+FeAaSmoOjNw+SiMxwtmAEAryOM4G9nncaRqNuOw+HTrANg5cf5qN1BXqzuWqto7XVjAS+fswErtUP8Qzmax5i2Yzdyz/3kQnlFGbOxm6mNQH62ka/MM4HojqyLDE5o5zewlCmanCF6RT2eupB88QnK51ABLAhB5jjwiH/extG5gkOV1VsTmGG7yiD0HXopwbNzzbPpeK0LFiWirosKFQgarWt26XjcrlgXTuImqOYOIclOCylIRuACMqK3m08bW1g7Za9VapZionTmRdapSEUEGrv6FzAPn7W2LseNENDlsVGnTWMAkCYoGpZ0oQBZ77dlvt8Yrr6Lk1gyrnv4HsXMONuODTjjMgYpsxoU24coHAodF9vdd6lgIjRJEHREQ7uDmm64S0a9TnjHQTnw5QO6+BHpbA70k8AkdW4XQw+FwSvH9udb9oe7a07fXXAnRhAlC6Bw3HD9y+gJOjMsKoeVhO5qEG4d906tzSsaorhoKGh99iW2a7VRrWY1PxxQazgOEva8Wx7js/fDg93cJsp4ap21o3Lj4Q0YZwTg+9sjKbuvAxbAs+6nrozwQNSwoFuzx10Fu+Y0d4GX6QMhgn9yyf4kVJY1sewPSTPchQKu92DlWgftDhQHILeRGhDr+Je8gx2mtck5a5dy6WAuGWWqxOKBzSZA6w7okO+w68VVayX1RMOYp53hisg5cduBTefP96CWDBo8bF7JxJwbnfzstgDaTvYXBr8yktETPqYtQGB7Y9yeTP406yparxvOh/EPADuIM/rJWls9HV+kgfHZEqm05nbSQwFPhDQZv3UOObolyW05Ih1XD+fn7boVbEn9hNK87R5f9l5pNO47tAYkreMHT5zW805sEANFkcFAYHAXrt3yInxuNA5t5tnR0L+mV/39xyZD5sqoL2nk99UQYF0259FvDSHy2phwwDqKhaI6mNDOHin82AMTGABlDTtU5YC6d3yKKUb2o0H/BQafNdQ0SWfFzbTCECyQBzTOWopqLU6fRov6L0b8hEzVmmJGmUBfDr6qpiy3W33dA2HLqOUhkVNJy/8HIBgKQUsFSRtzKXTo4tF0x8P7X5Wp3mFYoHBYjfdQp2vk15yxCnqHy8NhfIfH00/osEvWL2EJ7Y8bu5JZI0rPOP+9xdobz9DyDKP17eKTivqK0DeE+j1FzA/B4MnZ5o7wElRlAB8RUhcG+M2a14/fEb57Tnw+Uv2p/kcbDWvkVk9246iv0ELkT8bc9zo2IGkGI5eAlCfP4N+/bpJbgIGQo6Tl/WFkn3Ze8PL7fpLlhSY3hX8Pfjurexj6QK+Y9zd32H98i3LAgFGj+w/l6WgX8R5Z8zQWL8Gs8WGjrlPaInPggc9BfD9sEfYOM3XCeFUSBM0b9WR9X6UgBKUK92QjOobAr21zx8+fE5nOcieU9SCOJbXz3F+9wVEz3J/3r95iadMoLcf8Y1GAhhgaxqO9W+7jbcPJ9MAACAASURBVBIxfknfvoYVwCsZgRI2vsec6P/V2gAt37eZBgUARPDtfMapFtzd3Y2zQI9EBrPLMRk4iN2rWEox/Qqc5/TCdl/MqemtVh7rWH6Nn0fUfzjddOPzH7Rb7/hnbP9yoP8NjTAYcHwy64f7A0Pk4ppRhcDvFafXr9DfCzo+g/gPAJii6m43nX+ZNsRNn/OVwotb/OF22x8Iw6iyOyGlITS5gAn/+zwsmGL8mxA+TRHtc3T/7hVX44ruP9MhyG7NGwPo/7CMleX3ivZWUf+oWXOy/JsZNcobN94URkTEWj09QntnUdf130xF6O8Eis95XhzHKmtFQymz/1a/gPSFKy7meD/hpY//M5h+86NBAb92wxkrpHEeCsZczyJ+ND1YV8qOjfWbkeGOpm3/vU5HL8AFLMHO+LQlI1OMxicz1TzDllb25DfUOLgBbxgHItqRCFb/UAOKafT3G2nem0bU6flxhHwyOcLjwKBkiqlNnz3nPCll19D0x3On0xepb3hkeXEgnk4CwRG0+7inY1tb6bBtp/Pqi5/f3nHQsd/3dKYwQ3IJ5XOivzhAEBEawlBvz6t0y3m66184OH66v8ft/5V+FtSjdAbhHqAzIJR7QWFjP3/6NHhbfI4nEHxLvk0w5fxoBn7OyBR9QmYA/9WZiPHt3193dDG/G7imtxl2q8Bo4cXzZ/j85SuA6cDxSFMMGtrwn3gf0eZwMQKMaPrs+vv44tjQuXvh5kh19PX8TkpY5ifPbL+L1zhf7u7SkE7KBtEslmVNzKi1orUVp9MImyEy51bvHXU5gYjwhAvI64Ob42qaj/jdHRlxUM2MDXemSQ8nj+3YgOU2/xEnzyVm0JSZYTzSwhzKsjgP0InOg1eHBBxGevnumfXPaGTOx0wSEBHdlr0y2dh2I8zPk/8dXbXTwS5x1wFdkD/j2jIYNvHs49UVaVzExsAl7jQHYIep1tEqT3V9Q8axZ3qZ06WUiloqCpux6qFaLdLeO3i2+EK9PnnUMLTMUnu4ox6oeDayZIZxwJsrzHAWc76dEB+X2svKtE8ImgFTAbVujrfBBaxuu8+fW53MueSw6xwOBwz4Quab/I7I0IGIaZpv9azlcdPeqR46Ze+u43lN7+JQ6JkZqg6ZjslhCsBqKXfX8zWNK+T9VX/+omaeEg1jofXBsjhiLZy2E+4dnoUqqLVZ/WWyAAqzDIplAldKJ04YkwAzKPXe3Fm+4rKuWFeD8G/i0JtqRnJ2ZKUa43dneQTPEJd0mAZKBYEGrGdRr09pNKESdGXzmvqeW8GIDLXCyt4bUoGRZch9p91mejkiKCJoppBlcDczAIdTntToLOg2nd8gFNg4StA4Yo8YtLlCIa1BvTaiokMaoaNjpYZaKqR0YFkMyl4KxOGKCWKZwmJOfcuqCjoTg5knggpDGKhYQLUaQo9naQPqa8BYasWyLIY+QozeDWUhyiD03iwgw2vZp07m65JOtkoozGgrod4ZjRW250eQD1NJGHFz9ldgXS0gpTVIZzBFsEc4J2L3miEps5DaCmRGkl2UoSGF7SvWQetQ030j0ANz/+EOanJHrkFpMo3ThodKAIHckgpWGHrj2ljt+GXwFlJHnIjIYj8kDVhaK0cAcT4hw4E9zq9IBylteGGgvXimeWGUagEMy7Lg/v7eIfoJrTVc1osFc8DQKlq7oDfLOs8zl3peliqoLlYzANZvIWMqPgXB5cyZ65ksKRNdZo1wFCQtlRpmc/+G5udN7Ujh0emX+DHE93wRdPeAdMpQ0PRe7iYHSHrf37+X9SkTKOZpPC71WKa8f/ZMFl+zSYKM9Z3sG5QTOhyIClhAUylJH8Gno3zP/M45iNFqD8BQBZRzHozPeaVbrhG5n30L2wngciY1bAuMIzYjLXtZjOFYGDIzEB1Ux71e780yH5vg+9fvuabL/R3a5ZKylKAu58Kx4WN1oAR0YGvHifmbhzJjt0XGv/dzctjOetfEQKYnx8zg+sPtr4eNEPuN8+wb/Yn1KkqOoDjmnYi3z066dHnkOp6oQeMH0QSyR+jIvdseMuSfiUN6pre43SYyxhThRGUQjcAHIjY5qmLnAgwaH7NAEX3p+lhOsPd5oDzNbTu3rp8YU/blcoTDQK3B5PznOPcaJyf1TNOJj5iD1pzAPMEkKjTta6pIZCOlgfjCYHMe7tBBGHcQR3eLM6I9KILlAvXFdTqyusjNzzmDg23b1TnjAAP+mua8LI0a3HG8VyAona0EFySDcRhqPMSW04KrZApYgs/NjmFrFwhT6qniAQbkGZQFnA705K8xudP4mCNDcgQCFWbUZcHdacGynAaimgf89t6tnJQCQHM7iKJhZD+H83sRwnd0LGKirSvQqIPXCxYpVn6CbKRaCmrvGVy6kRfOT4hgtpc43wavgNHZaTIMR03xaAFF/WS3jCuA316/yDm4//0luBTI/3lnstu3Uv39JYgJ/R8foBgOwjungxyKr9uyLKDfX4Demv23/M5ePg2g10D7qFD6lLDy85qPtbfnC0bm+wMNNl8BLO48f+LXPZChbj71DVXI1kXU6piDAHpOwBfvt9cAP3ugcBF1dKJJzs9/Y4vmKQT0r19RnzxF//5t8PvMBxgW8yaCWrdnvzkwzUrbScqcUXPc9UYg9UEQ5dmUnLfk3Kni7rSAmexcwaaDERO4y9ChhEBs5cpKqV6mynS2gLwnWFDCnT+7+2en58/Rv37B94+foTCfT8OWnyRU+zXryGCDgLq/V1vP2f4VLD3OReQMtfBL4M1nnN8ZcsV30iw72p0WFwXO77/gyR8vTbYx4SsBp2L7eVHgucbKwMfgPqsbwlSxzUh3sBo8+eMVnsACbC7vP+OB8BPZ6L/WfvyYrR6y5+mz1AWQNjIJOeAyxQLbBxoHwEmHChtjd3Seu9MJp7s79G/f/a2mEwa4n7r+tNSK9Xz2shSWaDUHPhIYS7Vsj+8PEYqx4/lABgYnL6QxTgLw6sUrvP/80WUsUj/elxb6m5bkn6L9y4H+FxpNTHlSP29e/9QJPIOc6SUic7m//4DlzSuc6ht0N7Lv25eJOR3255d6/9ebbdRZLZiV8ON79mdhIqs/YzWrsTE8/0rbR4ERsAlEY7zcKB/treQhXqRnVDoRWSb6/y4JYRTZeRraAijr3nWPlc33xoHhYPw352T+73Q4L29ssjJDkMw4mM7j+WB+s20Fx/VnB/2Zvk4YEJ1+n5+we/V0HvrBW67vO+rZyB5wJcHh4YrTCU19ggLf+Dpa/0fvnfRsgL4eXnenhDMp7nZQ87/exuwpvh1+O7d9pv8+OOTWAe/H7WfuOh7lnJGWto7dXRGBWoE8PP1PbDr9CzrK6gJwfuIH+GgCC+DoeNjwrS0/He1wFfYfXm3zP08Z4zG3139+1a232DivuxctnOfxnH2bJcpewf1RO5zHm4KTfsBDd5f/4JtR63Qc4KDmNJF5FKootUJax+qR9RzZ6rVgoYCspXQuFi64u7sfDlIGWIsb36fZeXQ8QwhvjdOUNbStL7MxcZrTfM2QqN++fsXTZ88mS8ZYr5H1N/O+nIJh11XsSgQcHXOuRpI3/wpPvr523sG7a4iOPt0+j7a/zxleIM9ERegbmpCtMV/kUM6t2wG91Iq7u3vUpaLWilItW+TCF7Rm9c7hkIsG3d7TkB3Q7Qd+BzMSggz+O+FitwOJml1j86n30XSiUsahkdwgEo5Z5sheHYaRTfaJv2zUeh8Okrmm4j7zKfVsYnDB6Pu0ejLBTGZd4nBi+wH4/HA2412tWE4n0N3kCGPLZop3x1wG/Gn8FOWEo8z7dhOtUHOAZlafwwR7tLl2c8JKbxA3PPba0aWi9uLOGHMHR/+LO7cBC+g0g1KHdIMl771jXVesbXVI/ylTGrZDmBiVGXUxx54FaRTAnU+z3Mr6rUC+J4NsfMCtdXPuqqQxzWjF5If6uM3RjtzgwRNjnTLjPIsPjgkVAOtqWY6AOYYtsGfQR8xRlrwnq7te4gMVtKADt0gSYHU42R1JzQKGmnQsbopg2D5gNpjlscBRE9SCKsKaSCxeojycYAyUYoZxh2QlFRDMmV3Y4NurB4VY3XOxrOS12b/WPPBjhKHN/yvEVk6Azfif+jLMsYBinzH5fMCDQzyYp3D0FRYcQUChAmUL9daQQRo8xzK6Y1OKGx2phBxlCFvdcXHtyGI9BqMPuRgJRoYSYWY6ddQFGwTnHrtm/7usaQzVh5xX5O8FKJUMoQGWzbHZsmq14EFW/mI9r8k/ZtQKtolM/mPoFTZ2zix/4+Wn5YTT3QlPnjzB/f29O6uB9WK5b21tUG3oYvu2tRXSJWtxZ0AKmdwn5SnrXQAPXLF/A6Zx2CRo7A8EFDPl7zl3G+GFg3m+0UJmX91C2B4iH38MJ8FqPvZYD3Zpf3DuJQ4ZQuPqNCpPn++v8Q7S5ChKx23IhZAz7HDS8d2kR9VSHGlj63gPDroZj9uBAFhAiCgMvcH6xL5O7NmoUAUVkwPqqUsJya1DPsY6F2bPQDfjPjHsABZnNb9OFUCLnqjbFRzSvHe3nPsYiPHw7YzlVJJHS8hzH08ExmXAuqXP5lync2PWpvbLvD9YTtdEUGauY8z/XzvmTH2JTHRFhMeFk9gCImAw4TmiWV6OAQ2ddIyC40CA0BmmMezGuJmG/D6EnfNy0Cgl4XqlNQazmPOHaDfBOhgk5p/TX8EX1N85K1ib62Njcf451mdk3uczMkXRaElj0LF+inSy29gGXVF2aryDk8Z973oNbsW09/KeO6iescXGmOYkJjw++RMGyMFJ9hR+8DZVh6V3dB01DDpyNBGC67cM22uqKJ7FKFMtXskHTkMgpMyGMoQU7MFpqyp6H8guwfOMP01jIbIs9cIoHnSJQM2pBcuyYDndmUzjYZu0clUNl8vZ+hpBudPYBznZp1W8416uqPeORs1QdBpDXacoBEP3aRNdTzRBlObazWxHeBupJcEUtX18YctCj3ZyFXLiVtk+vv+MpwLU319gffsJZxqZvBw/mU0nR+z37TMCGntudVkcFtuyULkU9N5Ql1e40AdErumO4wAAhMzZBiARpfbDb7BAjailHn2K62R3j12/HX9R4ExbGPH5p+zeWp4+gX77Dn72DERA+/o1TQILTBwoHe+Rwnz12braLJDr/CQCgk7Oc+cJMs3UpktbGSW9g/3sOxqlXDR7i/Enu6RAYYHITJRzFj89xC3/blCcQGhfvoDpKYBvIAD3AB52995qZzq2ZTyGPDlGa/xQxYMXrr63tpLRJBcLDgYIv/3bKwv2f/spM97jnj7dW6aNHAEn3wmZGBnXxH2995RrDLsuAj7+K2Wjz/wpmqhskAriDCCzvAAQK6Ywnt0gqL1jWSqWpUIuqz/LA8VoyHgLdi4w9A+2YJbCWOOMleVrHqEaxcY/c9Q+fP4AgvlQwtJCuzuu7j1iiNOff5Pq9d+2/cuB/ifbLIh0/8W0OeLv50IYeVaKBa+w4gOECBf6iKe/v0EtJ6sj+F6mdxipf6Y9qWPzd0ae/KjjRxviFw4hIzJm94jp0DPOqsMxEXv/mQIaEfIAnnkhjwLCMwW+0gQvBwyj642BvZIXUFiUV0T5nfQFVhqQ6gzg9EeFKrC+7VB8grpD/VQKxKFLk8m/MQNhb2ZEKaXg/B+XHCe/IvQuaO86IgBiH4AaNbnFp6XghR+G4zA+HYgAKD65MvvSFSIfsAL9XUd5Y4ZA0wXG9zktmwO6bvujQxhGtNqsRG2es/sjM9MpSHnLpfM9vF+ioEePJ6cbnBjH5Lf/Ow4b9555EiNQRkKYKazWyjcMiLoN6cyHBIwa1nOPBpTRkFuhFN/rqK4XsNTbJ+4OItjuExO0Wwf9NH3TNcct+jR3+vFZpc011289vvNWMxmuXtPFawu55A5qtAOw0b0pB+RCxt55y5G+p+Po4QI1qK0f8Kf/NB3siHh2X8eBCTjDEwq3xj0AmAy2UW/0ynhEI9L7SqbEu3Y3DYPSiLQFYv//9VmJw0+0yDyPbM+g23Q6XXc799D8WR7Udl3c7wfZXb+PwM152vXH9uy0BvO+TME8vqTd9VeDuFI195dt938hRqkB385olxXACnKY9d7McF6ppqOHPbq/eKZxOIEIDjPtyvbsUOytmyjZK9e7LZ4ymeHGFZtR6SNz0ywIPg4mz0rlfC9UwMKQGVLU6Z2FoB7FvZl01c28plEr3rrZB5oGF4Mo1fgIx8cbpFy65pu3OSMAr4cx6yuUzxpG0Pn3uC6k2v7ZO4WPhu6z1YMU5lAP45lpbm1dsZaKdb2gOQQ4kSZMomiHdDO0g2yuzWsiIIf6DENS75FVBpgzh7IGL9wAOWDQuzn1iLKGczi2AJghk1zuuQBKuFYdaxIO17AMW3l2ArQMGOJImQyhTHaAz0ACI2Q3XowM+cwSgsG4m017GI3CcU481TN152zMOYF8rO4Uhx1Yxeu4gtzJ27pBr/fuTuiez2fPTiIFejhQgNy/CutDqcWMNWR12sPBG4abyLaFulG0NTQFWmueGV5RFq9v7nKWVNF8nizj27IhDD1i1LIOSOiIlqfCU21tTJn3A3kJPO9xNyT5/jGHiqC31Wpxi9ORz2/0IfgIE1u9Xd8Pc5ajggwuOwxeCsv29TWB8zZyiPg4UjARlsVqw7Om5pdjmg2p5sScjMRZc3rbgqWQ85fWL5ZdwIRWVlwuBUSWByc9xukIIcSAtoHkAR2JlF4yoCMg9U05ZbK+s89RgTtbk+nA4eE7pDVIa+hthTTLgFGH5c4gleQvHsihZjjjUg3in4sH1DTfw0j0CNWOUit6X/OsZf3wIF2y84/NLUHZ6cghwo0+as57GlF15ufkyA1O+whZrol8EoEYxMPxkiVH3BG3XTCAwIl4sJXYY6+bDmpaRwTnLEv1kgTVghF6iCcdSA4Bqxj1NuPRNFwvSgMCvEQJhECycHkd61q8liETTQbbyIZyWafdg0tsP/XYgwHl7jKly2rPWcpwonaB9uZIGYIuI0PqmtiHEslMKEs1eovyMTHXvp/2tat/2NTWOthv1IHERN9XLaKyfZ/HXnBNdnw+9WU2Zk5HHDdscv6OOAOmEmqfscvPDYw7WYwJezkM4qEN2t/s73a6TP2dfNyWvV5LeEUHXRYeGAqb6ZrkFCics0g93hBiyKGCadB/zgXl7eql3VRhtpW15z6MwH8qgXxivFmcAWpXcLWAKiLG5Xw2h5jGHETghSE4XM6aukQkg4SOADXdgyd5EipT7vCofZ366lbTp8khu/mZf24URkSQTEzQEan9nD90ZEBT6GVq2V+qMRYd5V6Cb9Dc0cEnIhgwdUB3xI9R0IaOUj9c29QfYBOsDtOhCHautvuCX3q9dDV6IUceEupBJMjABgDqJ6pAkrH7ou8zffrvnCDJOcvTtIPIHJhBb0xBb2OPaKydBlJY6MrmQJ55wLw91MebFCNjPCIdwsYXsryOwsip95E9SdXkp//d1VxC4gEeyiE/ZPAtZPdGxuwPaGns8+MLySdL/YxfXLdW1ckBEjyAsjb8Ui2btOlMmzE3s0aEJJYM+Ixgmi4oakhN7PxyLkkRtxKzocegpocwAuhiakrhRDECbC+01nB337C21WrXM6G7I527eDkyzTIsBMVCwQ8IpBZIyiRY1xW8GnIPszk0CwbSVWF3C9NA+wvanOXQSclox2tMd5ij+IGGTninQFVDQX06LZtiqmnOgL7/jKhS0cn+3f9GVs+8mF6iMGd8OFbDzHuZ45EJ+Pjvb0EAnv7xG9Z/fMTX/3iHZ//rDS5vP5pDNhGaQn4o5lEKRpJK0JXCapjHZwrLYH4g4IXaPVE6VfJZifeBDuCbKv44/QbBRxQAH+G8oTXnAx7u5i8RIi9LaDrN+ds3EAj161esG/4XnbLnPX12D1HF+ft3sCjWYHDdEaVCzjHwcBE8fXIPwMqbDT439oFNAIXJIed6bR1LGSXv1rUBa8P90yfOR602+qlUm6/WQGQoEIXYgryZUEXx/XLJBAghwtlpx+iD0aCoMuYd+OZ0C5yneQjLaXf6hA4717pzJMTz73UkTwVP+0YjS7z3T2B+jrosgBDWfzedu5DZxOenxu8rAZ//z3vE6Trs4QLLgJ/p64uL5edide5l6nP0LzLLjS5sHe6cp1/efcLpzUurBf/7b+jvP2YJhXC8Bzz8n2nzPnisxT65foDvh0lGAl7mDoJT9RASIrAH0BOGfOq9g7kizq2iirV13BOj1IpFFWtrBteuAm2G5qcwNAq73hBHIvC6UENo82a7MF5oaDbO7YJ/7kc1/0kjqSftbzz4/lFS3k+1n9Kr/me3fznQ/4bmxzVsKOqQCufIIsXdm9f4/v4Dnr55jcJ1qjs5mO2A4n2EsP3Vf4H//OUWQnibQbZtQ9DNZ4kpUhRxZBvzOEeSHjXBZzDMiR6y50KfJ+jB8R644eLoqBUKq3Q7FKVjYTogEcx5HhkrAzjrYJwxHt1+Q1dXjXECL7EBvnaGF1G4imDwlMbwuHe/9naUfwYNBz+eT0efx+u173uo+AXacgVTd/S4PXr9WjvPBwuK37xv08GQ/b33MJiio7dFJvm8RnrwczekVCzm7/dv+NmxzfeNA+34bn8tdtf+Sru+/icDbXYtrg/47esLbH9l9sThu3+9rT++5P97uzWXR3R1lFlje1pzznYsYzL2Xd9LSZn+N2HwuL9ZwTnq+4/a1Xh+9I7d9Y/x1v17bvXuT3T7l9psfIgVSWdOZPzJBDEcMLQJr+31y9nLhmyyXKyFc4vSsRFKtW54bcrKacwJHRmtTBCHfC2wA7Yvn7OTv5tMIHhfYFmoxTNmQ29JQysF7Cdd1UUPA+GeVoas/nsJmU5Dbs4EdSVFZ7l6/cvxs/37GZ59+8s4+APw7EE1gxEXc6CvF3eYUTo5xaG4De5eIWSOF4iAyAIb2GG4maOGLrzudjzH+mCxEAYPbWrEgHmHG+PDgUXe9TxWCjxbFsNA6voJZiNp1m81+lOHeLXsT3NsEpepLji5pS+cqANmfhOMRJLQfDZ/btLw7MBNtrsOOgtauvoeMQ7PhFZB65b129YVzR3o4ZCOg3RAU4oKqi7QMrLpmQuWSugs4IT7FneoMVQLhAH0lo5viGKlQKCoKBfLDC9LQYbtuaM5nhcOc+kCgYxtqrGEZeiJrkey10434yd7/VukI9qc4uawNXq2Ugu9WRYGdXf4Qd2QpenQB9Qy2QPKFzqe291kpwGrbmsj7ogIqDxg8CsmBtgOqXR3QjjYVWK9fLC+v4bxd0D8h2Ffp//Z5VY7O/AgrcS0lVrgdc2sHqtF52NTST2TyTKlRT1jbtrT8DqiSradWGNO7D6O30NWmKcbkSHTpXs9eUcR6LYvbCl3dZVFoWzZ01zgtUkL6rIYIsGlp3OU3FgvIGhvYNctGF62AwywGA0SOw9XUFnGPimxray/EfQx9lXwg6hNbs2WPIJp7QxjcJ3ON0hhlnoPvjw6N016kvk9OojmnKmtbjs/owQcLQOlLGjnlvtdVW0eRW1caY2jPM9AR7+Z2GpVsxnHqv8rbHtKnO+Uall8SKchAMhAXfD9EXQcvzcVN1iLOSIIIM/yZ3dkxrlQu6DrVFJAdMMHfPbzLJn14mXApmvSv+09z7P/Ey3OZ2P6rs/uu9PP/Kuvu217l1U00Ari2qMM9CudBWO98nd/QTouI1jQ91WhMWV25qOswRpzNTvT0ykI57XMHuA8HKJhqNypS4ggpGBQGbzv+zueoepQtY7OkM/YLDJNYyegyBgb7H7bl14mY5J7ZvPopnt6YI6wZuarigfTlSkgXgHA6JygYFZAQ4YrunTLFiRKY2/2O33O41T0w3PFdCiYEziC3kZA7LGe+OhZaKZP8gxDDZqIgLzoK22eZcbs6xPKmPnZoT7T5rDfDPrcji/eacGN03kgMc+HbmabG9vriLw6gPPceZg8aH+z0adzwk27m0O3b5bQG7tORM5MiCkd1DTPnzshUlEBAOGcG41++ZgUyKxVWw3LRLWxEIqolYwjstqyUy3B2Gec+yscUIO/xPnpR6eMn7nmRy3lWMrwa9rPOXJko641iTj0PyJ1KGG/Jw+BB3tJI1vdA03Jk7nINuOMmklEFqBQgUodJDB0Gy8TFqgTxCYDS/WA8JPi1Dua6y5w3b1LR1MBXVZH3pGRfU8B1R+Ra15+oq04/4NQWMAVIC7Q4kHCjtQVzvwIyhuJBJjIytaeFLjAILeP2pmAe7GyktOTNg7CC1nG7r5dPhgaJgBz0rpKWV4R6L3dcAR5HY86v/2IZiAk+PLv71L3Ca4T/6oPLWDwq1I+NzLLZ/oMWyVgiT8KzWvmPkziN//+/PZDBnZUABWEKazH9pNTboduntkAKx3g98Q7lwM7Q3DHCCaZeWAEp4nzmt66BSar6S1ZpgZA120f9tPdRUEiiUaVsg3wc4m6PuAapJ9r40xY/LwLOuHr93MoNpu5YxgE/gWKAkr0xcjcDqd53DEntIVD/ELXBBaw7QQLxhBnbbMNNhAvZ1lEOM5YD7qIvs9Z6qTY2G1nBMlozedp0UEvHcMJ+50GPHvQ1Ld3n0w2yGcsf7yCqtpeolGykmCO9Fu14v96+3nuvRNrV0+58vsosvyYld0BQGQZ5OQyitnH6vYPjNPK+89f8PTuNHrpD66lWKkx5CNd5lPK4Hmej/qav9HQTAbhDk3lhzNzY1L+Dpn437n9y4H+Z9vk9B0tFHrsPp3oz7XeLh/BeI1nb16jlhPCWNs2EeTpSj1409yXq6+PO3A4jkfu+4m2NW4Gc94d6OZXiQnOYBTRdYFFsz1RHXU0glFQRJYNofXc9DkIAyLbbPN5TCbcXhqsxtueClJkuQRDgx/C2LWh87+fQSAsfxQ3dojDMtqW6e8Fgk9mTMNgqo/EDwCq6OG81uH0BREYL0EwDu9vQgAAIABJREFUqEerAWUZMPKuQaC4vFuh9CUPi8OIMIEFxWeqFlSgiuXNK4AAeWtisvzO6O9eoLH34wYuTMxzQLEAlBGyoWzcGKJfYoq5OKLAEXzv/J7933HNQ0Y+W71ywGrwjFATF0VE+B6HLJ2fNebn3k9mUfd83hZ3r37D1w8fsq5NKHSBQGdrPA6uc9w8+8vmbTiO3NZO+gIKgH8j9E+Cji/2NwjAUyi+Xm3FUJ7d9jjmapq06639GCP42Su2PCyU97h7ccMOQRMS1M5VkQXC0GKZchAHHXPjqQEi/cT797/9TKf/H7S5GzNqgGyuGFBPCIMbpoMBdnTO5PxAr9ZYE/IWqQRdGzZmKjDqJBpGh+Cwj8QhHY+VBkpDyCehQf9zpvzPLs8+E32eQ0zf6e7z2At7/hA/R36X7akIvBh2K9rIqishfbNt1+v4W3jgmM8NmxwhIlTP9Ioa2NK7R6vanXU5QVXQ2goVzcxz699wFgUjKKioS8X3y9fpqL+bjM0f256r16Dt3JHZPjqyPoPQIjutVMuqU6+FFoEA0dznabQhPSE8wykw9AGXkjuGpQIQ65WjNE0j4Zg7aD9Sex5rW8PVrd8Pb/SX8+4Z0yVhcJ90oMxuCzmROo3/FDgUd8PlsuLhfEb12siAGRCimGnQmFKg0jAUAu6MUgJ2XNwhM/Sn2AMilrXc3RhXPNs7MiEVmvQZjnEKQ1ux9QhHphmcPUMWALlRuahCPRsznL1RfzzGoF47HOFQxfgu+Gg62/0jjQwFtYzRyN5h1d16XNNM1IYPWHVVy8QPGRZ9bK05pHJL53ksXG8NygVFBNoVUn2exaEBYQ4zYjbeSeb0Eh5jYRUzABVzwGlbs2a6vdMd2dpRtDrctCaygPr3Ma9zMAB8DZIOOerq+meleHaxej3B5nMRNDPr8+EAt/sKGR121ZxHDcd3KEyu9ARiRTjIu2cMgwB2K45OtDO6b47n6oZSKgXlzmmzd0OLWrtD2CvSI6MOAVl4OLdUoB2OOGCOaJsve4+Qerb8oHOooLfmqDcComJ6f6QeqTlwuRDgTgDtPeUi2OR4BBdkUIcHbTIMtZk5UB4EUPYAEzgjmPgmzEDLNeqn29iKebt8ymI/mmFcM13Oz1gqE69kD9TWqVTYZMxXcfnF+T6egkPS8VCslnfl4nRo9VmtfMSgISaDkTUnRvBsc56zZ3BH9qRlvhp6SzfrqdOy10dXykCNoRVN5izXScOiqFCACdXrwyfMN+zclyUfvN+xJ4h0GMIyPyfOFhGc6AFBuW/CNMlJp+ezGW/X1vHwcHF+L1jXjtZXnM+GNpK8USwgQCMAAwqV5pmd1Zwm57bjcu7snCD+Y5104gUARsk5JfTm25UZIIUORH748Mx5Hdx4VtR2h5yr5IGj5kbnQ/lKZoCOzP3MPsdWb7t2hiPXM6/fOCXnn8MRv7nfu2ZoYwyOmuwh9+AoCenw9KBDCgemo24xZ4DGvE/imlHYHqm/B4oTMYBm44i6xVSKO5rg/Dcysy3zkroMB/hGJ1M7tMbcJBKAOxx18F3ET5elqJZJpbCsqHZZfR8RtDkPzARsGd8pssyD2U/I9NgSdb5Dj7PuDUABBXGgIdmHArMXXIVw0PQvVlgnWsiLrumQ8j9Xn26aqmXhGc/0AAEil4PbbEerla6g3YlmnIhic9CY58lZGXQbiAIhZznP0x5kI/FscToj1xnFnaBxvWNu+bDEFfPitanzLKg67VcaMtsRj3IchCxpYcePsQdDf93OHcZ9U3BHKZMsAly/cEeWDcjmscQW8Yzikz/zTK4TRiCA1/MmdwoWtmOFKqj7nEqgnDC4KBYEPxxORPK+MgK5Z6xZBpllrwdlEU1/PNZifjZ2YsLEdvJMmxdQOKKmAEGybG9y9y+BBsJUF0OmkpjzA946LZA5dz1Q3yHAI5DC5hbGMFhAQugWaWFlmvwdpResbcX/Ze9N2+PIcTXRF2BEpmR5d3X33Pn//23uPV3lRZZlZQZJ3A9YCEamXK46p56ZM930Y+UWweACgiCWF+e6Yamr6nRM1oI5lB1ujgCpo/i5VZWVBdiko3Q1ukKAysDSlJZWa2MTQesPYHlt6EQElA4mRWPxNEhu9NRzDBIaUDAJgDyQRlMv7vUfRxnBOZ+K4MaWshsBCSOi9pHUiO6fXfJopK/1//uIau+FgPZJx3uj2Zg97bFQg2TUl8WZRBZqiFUkR5dKxJ9lvxfR355Cxhq/ESx6HzKlU3Qe6uuCoXtSs2YcANykERUAi6VL2KwnJ3vewers8ap1nsV4+bcHzcl+e4v+/Tu+W/q+27sXePp+chAsbVfvqV36/K021NZwe3uMc9xaFMuAe0dtrluYJ3mrasQsrDKlO3adn04ACLXVOCc3T9kKwJGJWiNzQOeQAwSI/h+hDgYNKsMcMXR/3pJT+p5N1rEgehxszM4AVqGLCHRA14bTiUuiQvpsgTktfBLwu2+QtgIdOH54jdNv9/NcJ/rxfvpvDcNJxEW96iKWwNCBFeHAf1+hAU5hc7GHfCcEkoOfMIoA9ZPgxf+jLVj+8QHH1vDw22dsdo/kRv3B8gPON5W9/vGiuFy009O6I0c353Fv6NDYmk6i6T5/KIoc+HD/gOPxEGnxxOpy2VKRBsczVP7Qul12OhyPigwEoJQF0rZhi4lJpCRjz+MyX6qf7kCaQNbmuP3RcU/X/+zY/99Y/m1A/4tLElWB9L7gDQ7rEQChm1e5e6YA99iT5Z8m0r+IumcBOh1O54uma7PXTG5et2vYFr/nQ3ej3DVPWPd4oisG4GzQJryKZ6t37APCRCretgFTFgpD64kQsP3aAnLQZ1AmdvSThVK98ZVD6IwjI1HB8p7BDDQSEL6qKBGHRTu0XzECKW29tJYK2seO8p6xfFBAFuaC8vcF9KvW00kg+HoBvezzMsaSxg/RztGROJ+FosUOKx4xmb2j8fv75P6aG8/3I/qM8LA3QcQjC45COHGKNTLP+IPNdTa05bVJILx8+w71c9V76TE2Tb/mWlzGc/O//96FnnYvKK8Zcn+Hjm8Abo0mXmCfE/1a3X9SvvipcgRwSs8hjA0i79MXbdopB7o5PXAngI8QOQctCZ712fhvUbz72et37zSTj3Jj3AjIeYX1S1sjquXyQ6CfsuMglDYPQYrYsIPr4Cl24DBJVKbJGpG/f4SGyNouu4nfKzX/DGX+Ed55rXYXYwljDc9t9NfdzpSUoaMtdJW2/aKrbSVXOvgzEDza3w+tC0Lh6Y0PA5dozjmHPtSHeaS5RI45MqPt9nQa/THjhJNOGNXN42bQoNEGj7ZARgYzNoU596EEhvjeK5MQM23HMg7i/alD7rJkPQZvMqJPt/vxHbvv/XF/hK6ypJWakd8f5gm9uDobDa7WkJ7l8wskBSgNJVso3IcCHqZQ8Mg2td+5c4JGop9OT3j6vqIwY10PIGKNiG5uWEFIIxoJYvyiD4PlyN89DOleeu84n88ohdFai8hoN5QDCMVsRFU7MUEjHZsZCGHPdKM0EynsvA1BI41acecAEYHYs7j3yDs+hpqm5xJ2+dhdHuyARosaXGiK4ssGk2nGRB1ZmkVR11pTjmyJdrY0fpkCBArN3VtF6wD3jqWrAVGWBWXpWJYFLAptKaTRx0Jm7DBjNnMBFqN9gcGxm7G+dfTa0URQKmFZujkQCHpVhanby8WilvO2EcgHMGO9zymz9VV/dfh6h2YckYk230QGH6/7izpUMBq5oVHn042xzCXJyLBo3mE89zzZPTZMv06juMXgcLWpajwvS1GF7OGIpTDaVlFrw1bO2LYNzRA4CCMilBzy3pZmbQ1brYA0cxhIuzMLIGltQp3+pFq7qzmdglFWg+m2NVfAoIWATdALwdVmEaEKU3ITNLVF0UhCYoBJHS18r5YuFgk3NmcioBQzqKySwrJpzDMhDC3SAE8S1htU09UlDM4CVRB2ixwHYND7DWjVnIgBGBqF10/QyCpy+rHf6hOwLgtg66hWRW0Q4wkQO1MRgUnQLacPkxo3SmFLI0AAq/JImADZlDZYlYzkvDVYg30I5wGMMyJhcrgSmLNC4gFkBm42vuSOYtVSYnRRI7YqTX2vtGckHuNzNaFXdAFRt7FoaOcG8Dk5aAOApjtoNm4CmLNO07Zbh43FDeNkOLooBC4SlPSIpAcC2pkvUaB0nJyP+3iQ+qAYhxNJDrtJTiKvzBl7mgp/hvQrkr0LIDQkNEl35QjR4FUEuPlqbwwPWcs+816mTn2drhfPKe66Ct/f7DKGIUNIfO88VJ8zYPjdSdD3DTUcp3QbLmvt9qNwxPK9MhG2dmM28BNGAEE+ZwtB0yok4+ykJ2HCRUJgF+Mkx1jaurPcnL0PWaFVNaSLRbsSEdDVaY8d/jiUygjobqcDjfJrwMJpERskvUjMmQhH867K2Gk+98EDgxbyCv9ZefEZmc6lK2O3KoK7PGH9E3dcADJ30a018YfUs9nI7/Jwdvrzdek04/0OCd1klCHbkHskiUn3MSwUc+bOrLofI9YzkiFbjashtMIFjHx+mh3r5jY6fxyjKGFwncY5fVRzngAe5e+yJRHoMBwpxNZF6A5F5UaxNQ1S2iNRwx71gaai6TYsOCdQhBD7REc32bygSo2xzcH5E/9MXfjjp900djFWg6FSGk+X4VWWU8evxZCamFVmb60D1FA7MOKwo7p53P1pNqddnO4GLxhUJkAvUCeybrmUCUIqC9HGirZyOoOZcegHQ1XSOSzLguPxOFCOesO5V4Xr7hVoAmq6T3p7Yx6NmTTpADZ0aUBnUCMUruCyhGOqLlDWFCZoYRVWVklTnz14I5ejEJ52xsrvJAEn7fqdHOxxmI/BEWEMAIe3hP5FDdRnsjSQ9LyuK9PRfqau0Va5cl0BwiDOKjIFQuSewrzOHMmeOAuyg4nAnByslgVDD7xBsDHhYM7TSHW0uHdua0v10ncBv7hF+f4U969wvePQqzNZRL8gIfMiEHY053zXPddlhp08Em2QbABVPu5yYuvjDHZtHvx75RXDbdP70wGUO6B8G5/FxmlIompE974djfsBajgXjBzzuGJELzKjGPjbE4Z+tpPCtYtZ5okIN7+8wfbblwt68rZn2tj7RzqIxyMBt/bdqz5fl9FBGXM+c3ckgczPGKxeIjXDf4fi53eXt5+9DghHVQJQe8fSOsphCXTJbDRfCqO2ju/nc7IvJLkQwHZyrbyeSQoKev2jWnQ7m3teWgAvQOG4QH72/IEQFq2T8fm/y/z9VeXfBvQ/UfYHU5n+zor5IUbLgCYU4OYft5GHKmC+4IyNLu7ff36Wzn/vJPKfLYQQyv2Bu7OBvR8fbgSWE5wgrmgiP0uOyAQIQB044jVW3KPIKzzRV3yDL1pdsi8EuHv/Hv/89BF3QLbNXolw5Ni41g8L6qfX6HKPJvdgemNRCBoEVcqC2jYQCMd/HFHrhvOvQzIrb9kOKwphkz3NBpDg63i+CiRfbfNgEHgSyAiEgjfKaNFxeLfqdUzYPtaAthG8AugbhrDth6V8mKR4bnlXcDis5qmq47verDg/nVE/bqC3hPJOo0rOv9XwpCwyhIMzeR+sXsHIv+1jrrLpNP6xNsLA7Qx7GPby/PhGnTd1/52ghvOh7hDVI6bnd1PGLgK8sGFYhPCNhtAmkp1TLhm/ANg+bxB6RDonqmJE9DC3h7PZ6eYTvb0ApyuXN5aL8otGzgv0wNct4tyN5lmgyW289noQ9Wy9xguO9ozzrn2jp/MPtwAW3OFs7TnGqRix1vdV7BUw2bVEDAeoiwF4UtX5k+FyMuWz3ntcXtmR/fBwTRCsl5f/l5RnWSghUCf2fF4PJpy81/XL4nmBYRDdQOTPIzOch9HHTpKhpBCL8ohlrm/Yc+5apiLPL6xejgqjSEFViOe7WP8DGXAqgwdp8ajKy3Ei9GuTl4cuKfmuOx1cCvIF18tokzIEsf3F8Vt4aqMPnn3a0/TcymsvV66y+eHdtzZ37rGs0Y/KzbLiUDsheLy/t1uvKdmA9fZGc5167uaIoPRxoPR3GGE8wmByWSdA2lDkloXQaw9jAmCIIV0jkNzY3mqLFoWSNJ4/1mZFw9I1EsEV40OxR0luyA5oaUBUktfv7fTVTpn6rvDIEBzyFf4r7e5A+m3+uHe+uGDwFzVo/WyKTHeacKVhwMHh0oEs89ZSSuQsLmWBdGDbKh4fv6O1jrIo5HbvZgCszaDy9ZluAC7EQGHzbu9hAGwdQOsXHsvsEOmuiHUP+6Ck+XpJNFbd0OvR0H0YJlVBqXUzu1ugxD4sXSN/PeLUjcEAhpIXkp6bSdgiRbsAJVwIdjMzDrhqYEZ87q0FLHsz43INWkUYwvyUnw0ggx8jIJwXVqMJG5wzk6IGOe0oBDmpFc9oigAwC3o3A6p5pcPWdnNlEGvUMUEP2cVgLBvc6Ge52m0OPMLP+bsGVFnUjgzer5GlqhiV3gP+T/WRKmmxKT81mlAxeVypKzaRvTcVGgUQg+jvroQni0iy64YtYSirgnu7nGl0WMgiz82IvpSCdV2xloJN0r7JjGJjUZaS4Oq1X91SFEhzvtkCQciIw9bhohFehpZgi1tly+a0JkA1pCouKLbPkGiuRLWkcNAe2X4txEDraNw0xUJj9ecsAsCi441O2fKAt1atDm1rYQaa+IxapI4bAwe9h4Ghd/RWsZ09v3WLiLVwbnCDW29TjnbvfGH970Mx+AKSUVkbH3tSV9qCAFQE/ewjrZyDU04tJkaxcS+OQrE0cBWVn6SaAwfrHMiIzAWGYcidXgIBI4yvw/i9rIxlXVGWBSTD4WbbNu0b6dZY2GR8KWa0GnmiPeqIHKvVOuJU3FrTOTeQgFqVz8DWTZZds1EeJOjVIs9NnuttAwMKwS8V6ECjFvyJYMYuV8IZD9dzSjf+O6CSaTwMIJpsq6qctut9esgU6Ql6XA0bM0/0Mu2uSY4Yo2QLPBmRKbcteKzA84urn53PJw1ZjNzQpHyTgFmQzI8mv94dCoz24GgK3hflmJED3eVHd3ADDcenSCli/TLkFBJNwcNunfNuhVFSQv6KMbb+ubxGrPTtZ3sf01iXYu01LTQVclRlrb52gERfLcWHjrc50XlPw+M8K4Jt/juwHFaAgHo6wyOXpWubeAHWxeQGkdB/BC8VQQCSMIG6oFUATktdItd0OMCXJG34OnMFNI3xHPJcmmKbQ44oe/vSZcL5avx+MdeHZIlxOU5sjYg/FwSQRLD/qN/3teT8kFozWuFr0j4p3roifwChZHddQkQk2z6jBlaE0ZeL52r3fcJyU4c8Y3Rr+6eueYo2ZCckfd7c2tinp37o/bQ7w+t51QlzVGOSMfz07OcLKtmxRyCbXWcG36kpJKDG4EMHOqFVrXUtQDMeqshEhC6E80lTLbq/J0OREbaqgLqHwwpAcHNzQGsdT+ezrUfbX2sILzGvyrskjdN+9n9MbWI3UidLUaFj1gUg6Wid4KZZogULq4xZmLGWBa1V1NZAdQMqUFFD7rtoT+hdhl/NtfO7v3aTa5rAopQIoBYpMhQtreFcz6ATUGtVmdfmOpwxiUClqO4XgidSefncGQ0Nhw70loJ0JOsO9bVTVwdUQM/A1IGFQj4EAQ1d9/XoUNKly+i/6+UdAptkQJvD5Dn3X7sVjbYdUuqApfayjyqvn8WCdCwq3e7PUeK+fgSX9OJzILvntiv3wscMGdJdo8F5f5249kEFnfX9K6wgPH3+EhDrEtQ82lUSBY/rbJ66TPmru4x279ElS2pPA7DhCXhMDga9gQ4LlqpIq93ObKulgVhKgYDRu2Bdl5CvgTkt2YuDxsCHg6zJh9/P2tKnbTOkBEVcK6UEfagYZbzI9qXmhnZbM8WCFxbjs93SOp0IoEfg9gXQHynm/iCzMT2XEwRHUpk2go6gRnS9HrHd7ddzt3eLKGT8N9I5IAD8UbD8YteJOuBk47uMauN9/g6wI11q7hvb2itd6ua+sP7ua3hJhO2GdJhTiogaGx//398ACF7+z79d7NDAbIT/I+XHfPfPVGj83WQQT593Wdf1mPbaVGdWChuPVJ1L7RVcWPFETI5g6tgMEsrlVeldz+BEqM6Y4A4droEGstZVZRWrN60DXbdK57fQ4NSbN69x+voVEjzwT4zannn9C5Z/G9D/k2XQkG9FzxcSjQ4+fFiH0ioUzUl49bp3n39U6OLNX1suDYh08SMR4TYLRvbbkLdNeJwWIuGMryZEfQUBeAnPTTWkGGLC33/5gMf/+G3XjrmUd4T6yb3WCEJflWnhlW4cROifOviXEgcjssNzWRZsOI9jtTOxj6bIxLz5kNWZx8TvG7nlyHquhaMGi1b5DNC7eXyVCbqSnkY7Q1FLqb6XJhBoniiNTtDrj8cDtg8SEJ5EBHwoOH98hU5f0UmDXQgvwfQwjacLQtgdaMj/8PjsgmCMgsDgAK/N0HWS9e/Gpi2g3bWuCPFSMA6BQx+oEo1Ggj3/TKHvl9/KvLqvlXwAIbyIOXfhpH0WdOqR74n0YSDcAQm2fYFGpP/IY1UwDOMENZZfM5QTRr6m+lzDrQzT7lzOGLBMuZ97QSVMLnEwMy9ywPLSqsjXf28Ar5RrXrdefgYG/q8ojuQ6RzXNByNKC8T/UqbJRKNx+ITT8xzRQLSCYDBTRLOSDon+kxd3KPBhihQxJZAr9yFmOPmZnQUTM7qMPJ/HYX/L8J/54xvT77UueA+Uj2bFY25rXGxQyHO0hM7XUKhmxvaDdW+8OAy+9i+MTx7ZasKwGDRuXkmCMY7jF3dII7gygAqhdzWyisETbmfXVMogQGDMr835vOMMxToAtNpTS3J/7Q6ZjRXD0ml3yaD6bHod/GA3/FZXuSW07+Opudq5tVfGfXr3c/T7XF3XSlK//PguW2dufCBfT47ycI3uZa6Ai8Wh0mIOF2oq3s6bQQA/gXlRY1ZiMkSAlMWUCxZ9sAwDYAvIbEA2USczh/q2wgbbHsZ/g6kjh9QEVC5N1hbfm6QjnPO6aESlRwkIMZgVitGPeOL/TdkCsSgbmckqy3id1ElA0lQI5ErOUWBe+ARHVnAYPjcwetR0rXZYJetzPMOon2anCOyuY8tpVspiUdIFhcuUdzvGNDkpuPEZ1jZmBhncc6/N4CitDaL3Fi6RY1lggcWWl716BDmaKuw8AlSMv6u2FJ0ExSLC/fvmjgheCqOQ0mBZCpaiBk4fE7EcywoV3sGtgLkGfKgi12UZT5/nUOauyGRRdUvISL4+XJazsSpFHUrWZcW6Ljgsq0GFC5ba1DBPBWDRnN/LavueYNsqpDV1IKnVaCYbZRA8lgkRXV1KAUjt4QrDXdVhpRMIK7CsutZKsXUoMR7Owf0cR0Ni1kj/VoAill6JIgJOIxuSQbh3SGuAjKhcjczWNA0eKcs8+KkjKwDqsNCqANLCkUYMIhxGvwJVrnUzfBEkGcw1wpzZ1ZTmnBMWFBvLjnDi0KigDqCH8wKkjyUJiTXMsOjzhVF4QVl8jQt66aimwesgwOA3PdhclcCAwgr3GHFXEjm3AaniNfYbMgh3KoqeUZvl0FQaLW4U4aFQV4d32DY8zl77okZGUjQE60drDXXTVAy1t+BpXgcv2v/YYWjkOSZb80ykUZzc0c9tIBTEmU+fz+Z93lmNw85fXJ5QehzIE3Fv3t6yocpowJ2KxvIciAJRaEytVtMvHCMRjxr7ejZyAGPdM7njhijNA0OxDYp5UJqgsQdb6TQUnExDKsn35Do8Ml2vJyw8YJvjWrY92tYoG0KDjj3HWZhhqW4kyzpjzMM5y8eAi64RckSVcb5NLPHq6zT+zp/FOZxAExe7bOZPHLKJym492uWSm7IgtcpTYYOIFhAPI5Q7qzCbET02dYPdlUHHSvdNzyaBkpMlTAzHmgt6uVYuZb7s3DbG5OKyZ2u8uIoAz387j3duldOVJNEj0be9e85Rd8j8g3ppVGSfzSuAbU830o7TYnf5RQBwtFdEDU8dNo8QDTT3iiOlw+4Em4hsnOX1t5AHMY/iOC8NGtc1GcLv1O8RKEODZxPFmcasu/kBw8AFAg4mz1oUHdl52KOMIbqOu+2lBNa1kOSc3gWCNmgk9Y1Zjbxb2yMPzSV/93NUtSsmC03mmCRndWqRamsx51Z1sGUwGK0toG3T9eTLXFTuB/WpvSPuVZ0tYg6ebxoaGT+irsa3BqAATEX3tFZBZ3XyYHN6ivRExKE/ZaZAyuCi8hVbKjAxHuR7w75NIpoKhrhDNE+n7fkqnzqIUe0NNejPxBR3/O5iMg7h0mXfhh2GAHu1FT8uPvSEYUR0w3amD9pdH7Jv+v5acR1XDm7K1+4N6wdRPVuc067UuX2+BwFzEEu0la62a3qunQP/CN3n4CMjpbi/fzeQ/cUdU/0eAXegUceylJB3eu/mdM6xdxY2JFWRYJcavDAelNvrUNm6o3nP7Xxi69CSBgWfAWDICIi1Ou4CuLwA3Qno4TH6LNCc6NfKCYIba4NKXLg6rh7JncdwX+MTAQv5+bkDUiDyANBrlNSW5+bsYu2l9z73LIPOgaF3bpjztN+KGWhlGMKfCHgpFq1v4xpr1e5z1GF//2eM6H9dsdEzUfo5tWle13nN1N6BrQaU+9N5w/FwMAdnlROV7iQqijMh6Rczd9rJQIA6HU5y9W5vSZ4YRIR6/xXHN68tgEef/RwfynX+aC/8Vyz/NqD/wUJIhwSkDTGffHblpcuTDHQ8oJS/jU01GImyElE3ST+PQEB4pFmA3T+FMLaCOEDPH//ryoXkSPPHVG4FiMCD2DFHHbK7iViF6aXPhkI3cEh6/rdff1PGjplp5cKAeq29q2AmtN86jn/7gO1XjYot79R4LknMbJ86yjtGa5aLFjKirEVQP6niRuPJX6GbkV+bNkOh54Gp+ALNca5fLGborriPy+rHVxbFRFg/rConVIK8AAAgAElEQVQYtIb6qV/UW/ASboB1mnCq7J8E2y8beuuRy/D8dBpGIiGshwOIgPrtO4oALNqXDsIKwlFe4UwP5vQBcHmJ8pqx3d/rFCadTECdAaBdLr3bX14rNO2n+8lXK8honH2mIfP6MshL1gk4VDwFfVEos3w9HoXwBDU0Z5rItLIXFnu6zj9PdEX++wtr4yMIL3B8s8ah0BXT9b6b8NNxeL2gf0EQs+c8P7x+jdP9fdDfvl1O94JLY3mmieN+MVkfbqLvM5X4MyoBggd0E+Jggs4htSXXzOnubMB1vjgpqJnhULtgicOe17cAmDM6Iia0pOsqFF7+r4o29/ZP71KzXLh1XrOnoXxgivfOf/2v0YZDHY/KE98nDp6jQnVReDIMxR+luuMBSch3MbewJpVz3UIhj1zIUQmIDSL3EdgfrJ47fua2UNQzjeZ+eq8caICxjocYR9E98WFCpl5/nvFtcsXwtd3RqZ9ClzK3Y4zdM1t4aj/v+mU7tyvrzQiqhjs7cqSNyw9oMnczYEF718iK9aDwZXU7AyCURes9b6ehLLU9yRUyEBm6oiv9cNh2AGmd0qAh640rQSQZv2pVRANXuNZaAeEpsHq5WeM5I9LOnNdM+SwkIx8jgP5k0Jh3PCZ54lOS/l7KP7Farkn2PkbpGnkC6GY/MKNS8YPzcyU1xPkfpXUUxsvALxNVyDaBw2oOXm9GdC4JRh1ovaE+eVSJO2ZQQCsvpQAHg9lmVUeI8ZgwGNgSl5gDGWu9qFHWISF5KZEHXSN39FpXyPUwDqnyockwmokZ2cM4YMIAwXJQMgMN6FAjnEYOzv9iaK2ubtGy0gUsbA5oOje8FPCyxD7KFknuBlg1Go+c2Z5f2CHZiRnr4WDXj/HaO+PlNvmrR/yXsqCsBasZtgtrBLTz4WGwMWOYja/DLPua8jVYuWi+2MbBH7gwlrLguK44HA9YF8032ZMjALYNEAuS6ro7UjFDfpdQNIEJZHMXUeQxfmaoX5QmitFGOASYMNVqRRWN3mhGq0zaXlXWu9MO2TjYMmG2OWnBrzTClUNmcEccEgaXwX+YNTLcjZJNFOq+mdOGGM9nGhHoCnFdlRf2FrnXPVIRMKdVZjhceWGDJS0Ks9d7R60WlbQ1zakKmDPgAiKgyPDsn2kEMdaAQspqVFyDSAmnDgahQkC7hJTNHBVqrehbi+ju3hvAmmIDLNFusMubunc0zE4j0juaNDXiC2KsPRJ0QDoPQ5TvRZ4OwBUwHUDfKnpvOD09hbG896YROTKiNDxazbvmalcutl6gc8Yml0gRczixfbr1ES0XUXrGPwUg0v3V+a+/940s6HkxRAOD1xbSunklSCUsWCCkjgmqzyJ06Wi1W2R6iZQC7tjhxRWoE70KYVl0D2m1gToDXaPyChcsqzncFFW9lLLgdH7Cdj6jbkq/C1v8V9d0EbIuCrWfJP7gXb7e4MYkGMJDEJXtC/o50AfsCi40KQmaG4+67bVK+ImvZSW7ypDkdOV7mx/Asp7E5d6QYdM5wWsUYGDF9+hj9Df46qDVoWSkhE6pxrPQqwRfZrjNL8bPDPaOvuEGfG9nOJr5exj6gzmYMHzvoWHUjzNokq0iHc7geZIOvjNOwSjBR/ebk9hvXYyV2z5sEpIQqe3a9tRnqg8ezMX4VDPnFNY1Qw43b/tEb+oI2qrxuq5tDxJyWHmL3HXZiMaw7kpI+JNS/bL4dTt6iPf7q6/UkscgK5Wnr8Z3vpf54y/OMmxA5CHfKw3t4dvj0Wnt+Rrwe8PBzuob+q4RU0qgQJZi1qhMUHKMlh71UGfjTUoPnhN9KAbVASDabuthtNHmz3hwRivwMd+PrUbOidbta5GGHAq4NEsxWpLWoOuU6AD0s97HR4sqD6xqTDofzQ9ufMvCfrsQ2qbOH77n9279heaVL4vygt4l+CYAHA4rSheczpuelbkjDtFzd30YY5zSMSJdmAgIvt/qXiYgsCgqja8PlymAhtIJrRcsxrOYCw7LgtYMxQ4dpZmzrI9/8JOZtrVtw6Xa2xqUmng1MCLRqRPAXdOMFXWsESjqSkuw14UtIrgULEvRvat3bKLOjN10cwtR5PmV3g2FUHWOSKcB58/OF5vxMT+fgoBeCkbAgRPFbvxljKsQsIlEcAnguhyP4yR8vzhIaokczVBDdb4fAL6y4HWnKdo304PfcrL6191jKNWVrwfUafYgalR0qG/X1byQkYfcafEgwPLmFb7df41rN5gPkygaJMP0b2SO0cFvbH07nSaZWaCRz4wB311TW7N+zmfSJZaAuk/fSfpeBDYHHPd1EVBVWR6kQVBsfNvl6NaapTXQWtd1SUhSguPicpbKbd9Pp7T/AmdP0xSpWnjsWVBHTGDsf42Nr5D65Xj7Hx4eQQDuXt+BIOhfH6c85WcRrKCIRj/YavR59Hr2iIsnVn7vengvYmP0Im3tHcD513ss716h/SYovwjW96/QPn41Pe+8PAjAI4khMYzvCMNgfk70zOlZL0TXRCc9fx6g81/sIavR7L3Rz4O93glQRPDtf/0TBMLLv73F/W+fVbcqs047l51Ee1HGOvO98vnrfG3+qJ6xT8L2MAndRejfpgZarXZfd0QsK1vrWFvHzd0dDseK749PgDni+7W+L7QO3N4dVcb8/qT7oHk+0Q72XmDym624IYuM3wHE70/GVx8A4P5e5WSkdAzW398b5/kp/7rl3wb0/4JCu9dc7tKhgAAc370FkgBz4fXmEtAUtv3McyfB9v+AkhjGrVhODowDjguPJAPiJmCtXfkVcpAeFuL3JAjF43C5oPefeSk4MqHWBn5H2H7dov64CMDCy+7wpDkn9ZDEoLeC/lHZTMM9Cl4jq9r19RUEX39ysB4AvJzGLsCt4yCuitT1AwN4i/rxPvrf8GAwIASi1waDpC0qH3gczMWhHbWRwmJKx7k1Tm7+WulB89CIGvqXN6PO3Odrh4bshRlRjJjvzcWN6Pl32f0OzIeV/Ua3f86N7wIil3VdESYkvebvr3kGqrDLtuFp1PnIRyboXzTqvOHBEAEI7b6nU9JoUb1Xmup4NKP84+UGCYVsB0YeJuDH0eU/+Gm6hjALLXuh/0f1EKCCpsGG024OidQbXOYu/24JyF6oYLmm1w3Xo8/LM9//Z4sbzd1r9hrPufZ+KnYAV13GoFcvUxSFaU607y2NpeeMw8QHKR6cI+zGEdmVKFnJHHuOUBi8vK9I9eY1kSHRc1/DMziqofR3Ny6EC0XE721y13719BlABlCii6uJ9m/m4tziZ0kz0/e+Rh/1sa2McfU5yZwood4NPhpKPTHFDmPkHkz9yxopvzcpZqJep7Vpp7qsTvXiib58dFij58mgSmcF8Ewji7tO0ICcHA/y9mRan+cr9vhr5JG+m/vxPPxUPHuvJL3yiOfL8xyQEr+bHuH7rd1LYaCyu2Tcx0TJYKn5gFtvaK3ifN4sx7Te64bbdVlwWNXQ2UuZFV/kCqddL4wBS6rrcDxGXlf/7zmzm0WtAkD1aO4Ehy5hKHNaG/TozhG+JzKxRq8IgyujczdDBnuYIFxxi46IaPfxot7M8UIfsRbGgRd1avQoWYdhBwBKEeeWZ7hZ3vPeOw6Hg8I523hFhDiN9QLr7zA4S0CHL8uCdV01Knw9mOFVx23ArGpd6pyghvDFjGARQe+KahnG0GrzACIztq1YDwfc3NzgsB50T7A+MVtqmNbDUJSd8Dwnr8KbM1ptqHWzSNaxihQmfbFnLfp+KerImXO+iaBLA/eC0prWXRitD6SjYQgnRZ8xGRaJD0ko7vP+Z3PtRi2bF41CLyo/uUNE1bmsXaNdadF2Lp4L0WHwoXRaW8PCxQxeZFGjSpv6n8OhZF0PZvBPDhysjkNs64YZBrdO5tzhPNGhkp2/6frQddQhvRicfUMXVtRjUyL7zAncyUEN0k1aoJd06aAKyNKBGFvlH9qGZuyuozeHzrd5a13TP1iObyaGFHekcr6ta5EtXNEdU/QcBlNWSqyn0+nJ4NV75AbfK28Udsgjl2FnFXuNaDVTYYs5MxQCV41ck9ZDvvRot9hH/OwDrw9wK0ZhxnpQ9AKlcQYver6rrakBhQtoJWheZ3VWdJ6tY7WB3MGiqLOMwugucTabhTDjd8K2BxhfaQN5YlkWLMc1+AeAcJ568jXSu9IrROF5RVDg/HuWrWM8AXO8tnOetIBmj7yKaV9PR6O8AMdekuUcHn2j6PheytsJI/6G8le2H6YNmOY/Gigf9dPFHIPmKPIwnhOZfmDISmFUpVHXcMYYn8NphNSZzU32DoXvzlnZqST2C3b8LpsDt9bRPDr+XOnzWTLLn2Lr7FrZGyu93yFL0HyeGGZ0b8sg1uDRxnU0yp5iHlpVFX8BQOb8BRGDTKagQ0c32e//qRHRS7DLILkTdpnYh6vCH5LApm/2xvIhS+7HbJbLxlkgPXx323Bqs7bIoFnnzfnZY6+fvxt6ufzQ4YQSsxGX6AMu2zzaANuX3HgYKSsk0Zc5aBHB9gR9VvcxzuuVADeie/ty2ynRcP4ca3V/prKmZjlk9GN/WBlGdLa+B9pmsJhB2+T0scAwhkllDIjyDLNxd4GlpgHInH87mWOUWwmtbZ460udMbH8BMUoZfHCsoesnDdq9/72zpBtfAjGAO0QCa2kY9zrQQGilh+F4KQWHwyHOBU0aam0oraBRU4hzGXOJXasl8UQb9iG3p+lhEYA0AtzTM4g7vBmPq61DpIbzbLEIc93XVuUTXVHOelXnvVKKwewj5ErbGmNPyoM6cS5z1tOAfJORnS4TLc7nQ+M5eeMEcCaZAk6eYbtXy0HUqHjYkTQA3LOkgBUtw/1lLvtgmFWGrsnJVRJBNVKd+plmPU2HBggRAHr9Etv9Q3TqVu7wnb5N1wqAleYc6Nfo1j9XXDcSXbvnZ3Vw3ser64nS97Z2m0Wdj7vVYaY2lXHZ9iLdsmmkeUr17pEXLvSRuw4xWZAc03BIHOKG1S+DxOy+ev+I8uYFCkaAUIcaz7Oth2CQ9gQcRQIy/5oB+YkEt8/Qq3Pv7mNHgMg3rL+8miDH91DuXm6eETpWq3Mz3iwwGHcZ+tlfuuZI7wQ00XsqFNbdn+MR6bm9IyJecBDBq/dvsP36BZ2v08T/1pLa3k1H8aNWTlKMeC+Vz9XWVIYsbA67AiqmJ7AzNEGdwnxv1DNIj30+9uPUimkvdgLNeqG4zvljknFG59KGhyG+76re9/VfvfzrGtCTwud3rTu7Dd29IBOtXY3QI//eD790Zx6iErDbLqC5YrJ9HnkJ7acQlEfTUwRLFjKBkERncXe+NytTLzq5/3Yf+kdmTInb9c0rEJoQHikZz8Xgw0WGgZaVeWheP2UvnqWcRaFYmimsxiCIGTIvD5mUmrcXZgGoh7YJn+ePDbf/OGr0jo2YZl4ZeUPXXxQqs/7ToIZIQO/S5kVAweuRm8dynld8hRrF9doFr+zxX4ewirH5HN6rI8Xpo0uwAkFVL7ffgNt/3IALY9vOYGacf92mOSVSxY8e8oH1XUH/KOB3hPa5g9+NA7+0BrKcoe1XjSbb/nYOwZc/MNqvmscPGuCCVV6CiFD5Kxh36kRQAMZLAA+z4YrUS1IoOUbYnGwfH2yEbTp2bDd7Pjlbn4wCduD6xuopV36Sa58Ndu6mkqFbazv3UOJ5Def5UWH2DsxAo28zDxD3+NIVnr1i66cGYYHgm9GICrAqWL7AYk84vnmD9rlho4fo78iLbi3i8RRvpwODEmzMd797G7NwDAgWvMCGR/jxfaSH0M+M6YYhKO7GKQ46Dj9Tsmh4bXLm75hGXqdrV7sgmT1WgeFF2/YTlmrJHprPCfKXXI6u/rDslWDP1Wf0LqYUYCGL7vKZs3cOyZPq83kKqFbrj7JoXRCep9iVYiPXsM/slTYmxeJkFFfpC+RCIAlIiqEkzLOR2wfA8tterpdQgHlPYzgv26c/GK1bBZ4jGbv7vAxninH86PBooH1E/065lurysd2dt/U6wtXv52tcObqr3f54hHCMWTr9+lyCKAyMYpDKDtXsBsrD8Rh1Dt2nYDudLpVWsPEXQpU0DgSDrE281J8v4/nWcjj8vSuHSymWk1Gj9dCGUVPsod0ge5VPqqGie7TSNJiXUJbB04jALxjy5OM0Q1oxM7CmfL9KsmpMOhI0b3SKZD0lvheMfn72YBtOhxbVEKEqtl80iQhX5ZfuGGB9xJLTmqZ+jzkTEXQwiBpydAiIsNUN0jvO26ZRNO7dTGKRnQKP8CYizWUu1QxkBg98PuN4cwM5HgE6YjHveQHUQLWoW4MQAbWGx760BjmdLG8rW757NeJyKZBa0UThh59OJ40+bi103K2mvMcmt/pYF2LU3oB6Rkc3Q68ZtM0YVpYFvCwgLgp/7GNFGimkKDI6soVYD5wWTa2G6wViUgVbDvFwAjDFRm0NS12wbeqI0MKQ3gGpuLm5wc3NDY43R6yr0m+tFefzGafTCadtQ902U5qbIpoI51rHHu2Kayzw6HRe3CFBo3E8t/VWNzTT8LoiXWxNqkJBIYCXw4plWXE8HHBYD1gPKwBSGLiQqVV52nqzVzX2N4gas0GgdUUnQT2fDK5b0HqLfagsmltzWRcUizwvRecEJgeCJCKE+1LQZUWtTemyeW5tmEHW5Aqj8Z4MJnHOIqBLAzWFrI6UJH3so85HalVsmlYrWu/Yti1orfduxmztBwjqHGBjU1sFLYzDzdFyKrrBbHjviwjQBA0VhRitNBwOYjm5ASKNEUFtKKXgsC4BJSmtYds2bNsZW23Y6gYyOuF1QSEdQybBcjgMtAeigFIn77vtDWKoDh5d37rxXWU2KGYg5YUMVUAj0FyAdpTusmgObxFG6xV1MyQLM/yzLMGnxM++IqZ8V7hB6h3bpuNChcCG5KBDpnyfCJE7HgKFchfnWTBngj7tfW6QJybNJ16cgaqhtzCjL4ylM/qpB7y+Gm8XwBC5ABhvNhrgAi5ulDG5iVnlsC6oW4dsm57zGgLpo2CBFI9K7INmmXG7LiBD+yBi49GARzL37uhetlyKptoQFegAqliOC2TrIOMJh4OuZzfK1/OG2iqYgaWsClGsOwZIRJ1mqQMVCvvOPZTDvtDE5UVPCQDonIkSTkb28bmYjNCRPsAkmoPWrevGUWcQe53rL8bO103BTLYHKmjo5CBjO2bMtAk2jlKjP0jQh++R2UnAz1hu7FVez8Gbp8JQOdee47KGnwFBs0Oh9mukLkAYppPTgJ2lEVDuFG1UmnbYe5e3RpRtbhf1NIfEuh94hLhFk4fXtjVuMt2Z0Smff6gAy7GgNwFLQ6usDjRsbJxIkawVNAgwGap7nlcB1lVPWmUpiv7QOqRJSuOh/F3Tjeg68bHnMMBjtC3JOmrsHCMR82b/u+e7h8CT1YfM6Cogtr6m+/by/r7EWYT4md/m84GJbUbzKosqIo7tmVme90YFJPqYI/3dYdXJvkvyX9whQ8dlz4K3YbL42Cndx8iGiW2fkTBySqxddb6VULYH1Lnv0fksauubi4QlJjeVOI3frFhA6BtpfPRzx/5EKX42FgCrpz+gsG8SCP1sSCU3fo8ZWVXUUgc2py8h1KbpY1oVSFX+jtbRzXLuMoF2uqPbWaXJCY0Ih3WB6y+cP4oAS2Gctxrj2JmCPmLuff4yDTpp7IZLiDDvt2nMgt+O6tj2slYrToRwiFvKAoBwPBx0n6PhANsMcWerFbWas2bvim5kD+ui0eQgWPqKsVjFaKFD6ZW68uRqcouiqAydlJ5ftb216h651arjZjy7iaUwbBX9fDLdqwTUPhnDEEGkxbSZh2uNq3wDOuGMjjs7n5Z1wdIXNCMn5Uvb2A9FEEnNoRHAvnYWEB4hOFj7tQmmh/Z91eluzCAEwJMNlENMe+zmwdaBR7Afd5/39LEvZ8Kk2yyI5oKhhsmNhp0hc7QwjLrxHMD2WVNyEtTI82TrhwCcQBEJ/65bBLs9u5Pp4uE8gCKyXKxdmu5EHWc9An1Jcly354Xcj3mJ6HPGUDCAZvW9uDni8XSO+1xW22rFi9sbOzO3MGqHTG+VMTOECfW8mShHli5Maffu5gZdRCPRgeDPzfcgs1UcVkVoPRyP2OxafYzypGIOzLXZOcWueGJAHh5x9+YO+KpR6dVGkwS4s5FoCP9xnFhwK2OHvAHBn7gmZ2d3eohVa2MokgPfAPoo4A+AyDeU8hoHS2O7d1rwbUBFj0Gv7wU4/v2dPvM/PgECfDOCu4Xy3zOU7ghKtwL9ztvhbf6+m/hoo33efvsCAfDif7wHnz/i6TNwT5f0si+Xvzs96K9yQXchfYDwE/VfrFPfx/v0jacg87+xP5hsu3XLhc4qPWznM3prWNcVp/OmehcAW21QXYAhPJzP4FKwHha0s+4PZB0MuRhA8b062kG2Lbnc7tHtvsOK5ke3+1XcYhyKyjK6S+oelQMpVF731Ak+RqLnRRrP/6Pl/6gA4D9R/nUN6D9TkhAfulE7PBLlJTm/7t/7RkjCgHAQHO0vimWfxQhM3yX/1WeaPB8og9jhApSEEuL5SlL79+vCH58afyvKSLLxcX97Zqpk7YQvZBc6yWGqMAQbDGbmEe15E9kLqpk5+isTYesNQveQ/l6Vuq1bP2fG6N7U5b0qR9pnixD+uPcNu+Zre1n2SvbRsMHoxvdDyYEQTvVQr1vwSxA9JGIkFHoZednWvxPOv9YYEPkM4J2MA/RnY3ai+WHcUAG4Z/zLMA6Xd3pw7p/ucHi7mCCi7db88QKhb3BFd14PeS48+vFipPJFGOPgBkKyNjkiwXOecjF0Vxg4pe/9kHSNnEdbk4AqL/RNeUSxqBynrS6qfOPXGlkuALgUjY7iDsGjmqXMaBBdlkd03IE+F5S3hPK2oH6ZadaFef+CaHgXRp9Se/frYN+vXFa8QMX3i9/3NOwb9diUZ2F3/4wRVZkO3kTGK+1eq8RzID0H1XONMz137bX7Snr9sxHphXS9PQeplYsbzkueIJSJRz5Hm4P3uXBjtzEBTSFvPcpy35Ix5zR/doVjJpLxQP1X9EDsBrucgmFq37X+XvyWDckYsK9Ri8yECuUJHrHp112+m5+Rart4f3FljLdd5cIiaBKAf7bwRY+HElofNwzoQ1mTiw2A/2aK+nCZIDFJ1pUSFLmWiChggh0icUgJ6Vi3mzCnm6GcxDQVU9vI9lyigIga0esIIdr3RhkTGdDaDQ3lXCBHOwIkRTLyM/dDc7ps+xhTVuNDKcNmoNqycWg2GeKy7h9xR7si7bUOG+73jkh6a0+XGCNADxkl9S+emH4HLJoDM1IQkUZydsPJdQPBFFEHSnULIA7P3NANsq43PXQxM8qygiV5Jht9eqQjAejbZkMm6GYILgC4dyw298Wi2jUS3g2FG7atBs1LSxDRgqBNZt0bqzlbKNTd4MICAbMazx0SGRhoEt5uHTKTs5kBLmrwXRYsa8G6FjMaqzwjQEDQF8t9XEpDW3qsy8oMbBva6aTKi1Jwc3PEy1evcHM8QgCcTic8PDzgfD5r383pgA3i2x1EqBOoMyjyRmh9Nmt68F3XUPIrlLgaRaU1dSCwg6/Q+K+K0ANujgccb26wlgVcijo+iOWthroOqFLIIotNznDjYQfMIKgGaD9AS+8BSc3FI9xXhS73sQNMs+NGIYMv7ppHXWkZZlDNh3pbL73BFavii9RlA7PERYQkmY7TozuhzhPdIsdb7yhEOJ1OeDqdRm52a2sxCHCxg7xGbmuUNZnijQtr3t0IDjXDho2hVEErDStgUe8MWDSySAcOmoOxMBk0KWzcWxhAa60qMxjcPCJYk1DKgsN6CD6DrrySi0IWL7F/E8Sg1rtI5BaHj69FzJdiBnTSeyIqklx5KKBia3NjNUiQR8dK8BUxnuLIDxpspmMIETUccQF3ArE5TNmevT0+mvGTUBabdyLNOdoVFcH3KctmrmuBYVDnbrwdZwS1jhjft3noJAGb7urF3psZr3VPKCvjcFgsXQKrgV/EIDcp8uUqGVIY+wIdw/gUSQN3hU9c4HxTc+I6A81nCbCveePdRXNac2HonRbJeUuBQHE4HnE4HkI5fWYGTrZWmyBEJzN8iO3rbAb75ggWcVbqyovN6dzlhcIl1pkLdgQ/iw7DOYMthYitFXPi6lA+1bvyro5gcwDM2Uz8zKwWrZ5yeMPRbHZFaYDSPJgpht1UkmUGjjFnM6q6k0RAqBvPiHmxNeKbyV5qHPJafAXfrZkpKQdpyGe+JVsfGMN50yMhIzKdedrnhzJ5GAJdrnHzjA38aKM4r3IZLxs+Jc7ZYSRyx5lSQFCUCOLh7MaF0LvC9kohi9a19UbdHMoIsqgc1ZqiXwjMNmwPE7EUGtWc+kyxoZD36sCipDsfJkIRnWRl3Z89h+1ArqAYh10U9HSvfx5G9OdkvOeM7Jle8q3uGKJyjbWBZaA7hQ7CZDvuw0HFoevT33SEDlnJyz6V1nRkoNGWLNQymQ6GRPULYRQvkeu5m/7GZVpNCZXoED2N1P5dXisxWPOlfbohycwIWTaPcbTe6EVI6dHPZCBzzpbc58sSvgrieyvMyVQC/izLpN4gHS7fizBggu2D9A6x1ATCHLyZmXFYV5y3zfQvY4RGv2y8Llnd1SKwNpPkAbYz1iVKmJisAFFDeuGC25tbrCY/+8A4P2+toTZNWdMFEDsnkckmkcYl2pwWarTGnh1nVP3fWou63IDua5lt76iNwVxBtBkqk/JpIUBa07E0+SL4eO8KDS0qFTqdInYEGk4QhgzEhbEuKzoER+movWKpmyETtZDT9+Z4d/Y4GxF7xKfyZku5FmtvzLLnar82zT859T9VnqN+RoI6x1iCDEtdZ58zt7i+iq4/8/bNKzx+GcipdHHFjg9DA11oKWhN9QuryZSFGBV67u3wqNq8XkatjBRIIyOo52Zd8V43LzIAACAASURBVLRt09NFgMfvJ6xL0TU0ze64cqBlaSq0fN5wmWOvn4mvnCckozURcLg5YjtvabK1R9f0Ft7b9vURy5s7cHsEHobx2wOgOjCnubAx9ZjxXLcjJuTHEVQ33gkTUoHAHCp+/Yr1l1fWhzsIHi5odd5dtLzqg9Zq/XzZQW+7/fdUBJ4DPddLAF7r8QNfeP7Nf/dgqt4Fx8N78LsK/ngf1z9XfkzfVjtd7nCDlv9o/c/sS9O+MCTFSWax10ATLOpcX1vD0/mMm8MhnP/VSXvIP+u64LyNM3yu19eUUePVcQg5EaY/5NmZEVC5woMoGvSMpXKhnktivCx1mI9da/33B/J3CtGsG/vvVv5tQP8DJZPKc1O+JydnzETA8laVbIPoTJCJxWUKOoyo2XH+oPgtSa/xKZ47S3iX7TPufEH28jvvc72p/S+ng4PmeweS85+d1YTH/V0sEpWiy8/mEPK+DfgZhUkPp+1d8/y9GupeutgMCMB4HcKV31DeMdqnjs0isAVixmOgfxKU92rAFhPyl3fqeXb+9Cn67cJALpVVIDn2N6B3ZLnTi0FWEU4fP6LIq6nNwAMKNDJdlWgV9WMFfSgXux2Zko4MJlG64PRRBQaIQD4J+L2aKnXKGeU9IkpdZQk1uJd3jMqav/1okfOqQBLg3TIZCW7eH7EUwvm84Xw/KC+axiZC9Nxc2Y3PHToGtNB+UwWScGHFvTMj93rUnMdP4W7morWPKPjZAy0PK6eKVDnDAZ1+++Ytnr58BuMOgm9Y3qqhYXmr0JDnj5uhEIx2TS2xejoewXSHp/tvACS8ymU/wfbpTCqk3Mig9X2fr/Vl3tcIDY/TNWMFz0+OVxE0AAej+4t9UgDCCoFHVJVkyyK3EU6F6HKdL7hu6HZhM34zXrekz6Mdc9v9/TMiz3y/FU5fld3nfd2AeVFm4UlydARnH4hde8YMEFTBr7ePJ2TDl1Ntj8hHiQO9iOZockWr3jvP1Uz1AldaurGXfGBzFMPU30sR1N8TEJpVsmdEJK+1BZFfSf+2UBS4MChD6ZaecnX7IsYaigNV7jJ5rr8UfWttGfVfRthfVP3c9zvCp5g3myNBmndCr1u6+vKZvfvxYz5SesR1t5xcbDnP27ZFLlhxI1mqttmBMWq09xHpCLuPAIIqKYP6KB0cBUPhBgRcrpgiXw0ifii9pA7XfY02duTIn2gbDScp/WF2rtJoGjXA+yE5lKk9qF8Ndd/1gM43gDzN4+w0d7kGL+dEgGcRRC86ur9T7EdK43C17Li2KdJ8HZONna9TsVsip6ULU9iPl+eCq2EsjiaT85KiETQWsesISGpI1Qj0spRQYOfId2LP0Z4isUX/jDbZfsnK+7wJuu5GLluynNlshjSXRTU6isAdAOv8u+MdsRlO2PJjW2Q9ibbTIdZHpJfxSxk0m3mrAEDXKP5aK+q2YTOnAYenzjmk474ukZdc/xd4TlzV7XlkeUOtOs+Rn9PmKKJnRSJ/dPNnWQQSubJOkoKIhvOfRz8yqaGsFDZI8G6KaG139fk3KwiTRsmyRZp7JP9kPDdFrPNxMkMZkORN22AC9tdJP4QQhojLBDDDgkey90gZMtiqGouxFFX+N4M4FzNCEsKJgT1RNSt/8KgsY/MWLagHjC4aG7Mej+i9jtysCskQ0Z68aIRxzmVcWCHvV2KUmyOWwtYHMqOlGC/VXOhYFN50KQp5vBSFjGcRrCvbHm8nER836VhQwJ7gtAlQispDrmA2+hjCBKE3gDg4o16X9p/JoUd0zt3RIWQA+A5kbWE1yHRW+guLafExsX0kKYMuCmnEvVgkETGDpSvhCBRBglkVRBbJkJHMfK/poso0sEbgg4b8EOMH4x0FuseQOVkxKwJQJ6zHgpFmSWI9ZwOAjyAL0LvKQ5rnkXFYDImhLLqmzOGQSWmyULH1PQy9xIudGRyFSvfmsihdONLIWNvD4MqFAFI+5EGasPQQvWieW+nq2AQYCoh0ddgVRfrwtBqeIiOWZKYNcZ6ga7IsBRoVrt2ttYI7oTPABrVH4bQ3DNT6yZxRROGQ9Yw8jFbO67wNg5aAfeoAse9CQecQ1YQBm+5GczZe5eNudJz3vlGs3ZOic7dJSxntijsAz5ke2pJJAKbdF4kPyrxGVHaBLUgKeStkB50UHWs3nu94voQMaKfAojzDU9s5xHdEMaeqo3E2Xj3NSW8dTAXb03nsd6bd17o0NYbkaKSJf9u4LkWNgCa/+vNd1iSTNbTfBFqLojMQxv/UztzeveFc225ryG8WmdozKkGSn7xOhGLZkQT2cnnUw3ExovOZfHaskC7eJVl5sDtDXtEIXbenTmdGcgO+O6b1uM9s5bGepEs41xHsN3GnRlYkoK7O0sbk1UhkvHQ6rJsjRBCfvUbqu4XM2Lsr++S9MU+770RR2mK4iRCuXUTAwVBXTsq36eDN0cHr7qQFqHFW7LcCUHXero4CHh3sATlRDwSEg8nODeBusivw7bseJO5evABRBzcdb+ct4UTp/M07GGtq+jiNBvnv+0P6lbJbtgB03Gs92+0LQIR1KSAcFB7d5PbT6YTldMJ5O+O8bbF2hMiiD8dDZEen+2NQUL0Ysk+0Rv9yWp+ZT5c60hEJEdq24dRqyDTOxwrUcKhs0Xk56b6qgjAK7iD0ONJI7PkumQNTIXU+T2dlsTr2o300kvfUfJrj/NnD2++W007vuP/8M+WJNBgt70HA0IH5557eh/FcxjV+r+vMT0Dkr/ZrbkSjXYUI/fNX3GBE1SPdO4rTB6EBuBGBNARYSidFxKhEaAIspKmDKmiiZd+unF00GF83mag+nY2ve4f87KioEA7b7vIDF1b5XqCr3s4Kvmf6rPYOtCaD7mw9F9NzbLVG/7wQEepZEZyWVc/NpSqqE5n3Z4mgCe+PPu+JCfLwqI5rpE6ZHhAmAI7QM5o77GSp3Ec7pxk4kcLArzJ0pgJDREjj9aorSuvygWKM2m8PMfn79f2dBC/McYTtmZ2A0398Qnn/GoR7MCwVsVguc1JDO8l12uw0+un0eSfAN1LIdy83RpMNuoc9/cdnLL+8xt3f32H756dAMrhW9rv9c99fv06GnErzrn9Zz+U+HjXaPqsfM1+caxIQismutVXc3N4AAtzcHIEnReU4HhQZZTHj+rad0WrD7d0L1G3DadO9JwfQXO/Zrj07XZ07XLvj07EDCxMaOJzR1cFs7m8+Y7vcAbk+dv9K5d8G9L+w3CZaLng5DglRhncUoBuOem3Fz2MBuILQWe2P5a8fluG98kduyvfrF7cy6mJ69vI4GDEA6eaF9czKE4y90z9nDzt9VRjx555FeIkVenCQLmjkSlyJsypgni80mCS/o0lBQx+0kSIAvSXIp9Gw/Ub0XBEI8Mnv+Pm7tn/WLD1r3+wAtr5/jfYl51pX2HZtXTcYEAI+dvB7qCKACYGbbMKuR90REVa8RvlQ0D62iCrUyPbdZEDQzCvp+Po16n1HM2N4nk5X8F3fmL49OwyhePiBV9LPjmKMX1pPl7S0f76+JjBmEIDzl82ENAbhDhBYugWDVMXD1TYPYR6x5zaZxVNfQ2Pdj6g8z420b/NFu+214IUJJY/x2zUhYi/UYve5QnPaPDtOqaKBspBmhrAzjD4v9Pyo7A8TtPt+f23+PqvT9nHH+zjp/dhmYX9fZpHErmceRpRctxkkwnFnHEmBcD7aHVWSQei5sXJaGQYEicN8hs66XCv6zYB0cxonuHeD9v35WVJ+Po7SfqUrP7Pjl9P8qHU2AA4DPubJS+8JCOW9l8KMwqQHH9F6hqg7HYN+8mB82V/avXPe4MoC3UuG0mYmmL2HdOovMO3x447dGjVDRIF5e8qY03HHzGdjDGQM3hjzedU4hJ8r+rNQ4ZC2oWzEMELovaMF/tyGBjoRcAS4a8oP3c8ldUwPdnTT0Z+UD/KR4gC9l2vUWNtBFtUuQsDBnT0ypeX+/Q6HeQLkZv5qMgrlqtxhK6q1N8ba1AlF4IaU/YFKh1bguVeBeagDWcC+y2t//3t+vu87w4DeAm4yG0zCCG6KBc3vqG3kosa+siwGVTz4Rxh2Uh7gaVIIIIP4JouGGkru0XaXpZDbYlC5FK96TQdreglWmiG/BpZjnAi8FHBZAOlw5GDpDlOmTiCwKLtmntROu9E3WH50izKnsxoPqsG9d1PSSBjhzdnBopCXxeDZXYEtAmmiThHZONEp5sQNoUIeNUzT/HnbOY3/PA8U9bpi3CPJuXX0UsCtQcxAk3mXOzcspWBZ1FliXVbL314MJtGN5mQKfZsXN/pkL7fY4mkyCoyfGUQzjDOYVIkPCkeR7BggXaP5uhtem1guc0R0ftCnOQtQd4OTwpJ2cV6oi4lFo2kp0eDYl4acQmnfitzrYHRmiHQUdsN5j3zvgOXRJqBIwXrUqF8uBWtZYj0sZgRV/mZGELBCsS9mFHRFWTd4VGloRJBmPKYnlSkJ6qYfy6JjI5WwHKAKs84oq1VnTh+uRNbBG+/DmQBs88MQYWBhyLkqpL8uTKADtNj4hWyS1Onm8aroKWzrl81IpcrtxXLal2XkV9cUCMNhhdCDdtR5B2D3H/ZtqlBAt+t6HA4tfl7znOUSfbbuk+1pbgsUvb5ZAsZuvHzxVAYp0g8wQzdSFL3DfrsUwGSyoPOPbrnT1VAdvKoNfqRD6pD+rDyAofnT0dFZULoayEtXlU0vmkpBHXO6Oem0aW0RKJA+iNQByQ0M2iWOaOrRFkGrAkVhaEBjNJJ0vh8yhDhkfBg1Bh9256WQFcnZwM4JI/1WjL/rNpf3L+2LR567ocZTEbhRf0Y/8hn5sQTvn71N2pPZeQlEk05ilufGdTk6yF8nOZjUAB5nEaJxJnc52C0ShGSkMxkuZAGLqFsXiCn+WxuOjXNEz3yKcTpTAD6TNWTc47Kec2Z37FJEDLfc7kbB+04y9TejNEU7knxACymaC43xc8ndKWq8uV6iryE3Dfkvry0RDMQL62PAFMuIRMXU3stHh9OR/3rFcOpOMrnsnY5y26LVu6Gl6Ys0bhFEYJuvRaIz6XyBgd6MJ5Eh11Bamx7N6DDk8YzrRE7TZ53nOO9cIYe5E6nPaUW63ODGsxhKSqeVw6jKlmG88RzoAClKQKeRhDd6Q5jj7RwlY+hdFX2EFNGC1Xkui/DFZIA2nWF+v+xGM40jTUMJPHdiueRbnsqGDG3FHccOpWgkqI3psi7KR7/r/HYgUnL5Nd6/a4/NHMP70SGQ2i7aqTKTr3/jL54KzB00mNC3TfO1w/asPujf4d7FztRsckSMjaj8t4ScNo+P7hFmwHfEiOBn5pD9TJm54//+kmlhf7L90bUe8OF7S4ZI9zn06+MzqbGbQOC3hPVLxynVnyPfrxVCWnKkKIx+JiOQCm6txrWUFoWvQT3v5PZLQMaHVOUMKO1TeRQGvxW01sMQmHdy5Xt5//Q9YqwDNjmm2xmRxHmdnSdrw+bovdP2dxlFK7tXn5dm+8765iXw+Ws4Kuxp+lrZ7N5rSL/TcwkgegmI6giWX16B+wPa5wHjnjn/I2l6VAFwYuDmDeH7J8H68f7ZthA0iGiVK3xORp/sOH81QMEdRhhQ3vvhFbZfv6C8f/V72/5/vlxj0H/0/p8omQoJgu+nDbV2vHp1B5CmdTqfNeiGyFDMYGuCNFDk5vYGW31UhwtbC0SGKrR71tTEtOgzL8ivJwIaEY52vu5wp0y92fes8RBJL5cBKv9q5d8G9D9SZBBM9gLzsv9c7Es9fD2A+ZcdMQIw4V56R/vSoTmT9ZouMnns7Mu1n8jqTefT+VrxzeznOMAlcrZuQnch8VMcrq/K0y4QAWC8wkZfYQCsEfHccH8J06yOsqAOFGjUOQA0fJ06zjI/11qIwy/q29haVyHaPM4OB41UqLWpV9pvHfye0D6qgElE2H5tWD5wRB2JaG5rkEA+yczcrW8kLwF6iPPwob+GEFChm9CCNyAwlve65FZ6r/351YUbhUYvHwr6p47yXpUfp98+o358OTpHjO3jV4WMJkJ5P2AE2+cOi6XB8ot5zDrcbUMcJkJR2hnLB8JSGPyLedZ+WBSmsgmEO6QD7XPD8mFFKTDIHqB96VjeMgTfprwnoZhyoUS0b+4x57E4e+GuYBZC/N1KryAEnOkbTiSRQyYN/1RuTRB4MgfWE2lu1bGJ6F+vJwuWXhgv7Hsxwe5FRMyXt4wCRv3UUQ2eNkfTXxSXHENoE4AebR0SDq9e4vz1K3xduUFTBQ/Cy9evAQCP9/fWtrnnL99/wOPHRwi+q+6FHq9sanbQxOBbQ7AbUOU+DirQeH5BP7EMhRgBClkZmX8MOo5gCskOsty3MEhN55yG+GmRyM8X35jyM3MZkO0hCk8HD83rPfrpasI9f9q/Oj3s+bvXkw8UYrC6OZpmqOz0boe4uqBaQnxPoIiQDiOBfW6WC5byvXkcuvfSrmfzMIRYnlC93j1u57Yi4AnHwZ6Cp110Htm4N+odh5zRvAHdOPfbIaK9dINlc92n8w3a3Rs54bpGgpWi/HnhYsYpvW5dFjV2mKek0iLBPbZYfI6Mj/u4PCP+xaiQQ5RRgk7U6ARYznvPmzjWm8TMUPrF60sPUUVOayAzZNZtg3SNXutmfFMnKK2nSTNDYR97PgC241UzSg2IX9uYih+/wuCh90pynvD7BNhFnl8dIgCWHw+r3nMW4Gh8AGyRaYm+BZH3fDgF6GiJANQ62veusKKF0Zk0EkQAOio8GwTgWwA2nzCDuJwuGmclH1NdaBjtyrSWDXsz+e5WYdo48qE81xfObFe4mGAobicjukV3XyrO/blq2O3N8i+bVqmFkVyjhxfWyEeGGZ6ljP5Co28D0pvUyae2hq1VnLcNm0GPi+/YYVTWaEiwzu3gWZSGM6FbwODVWZ+nNF7CiO5KVA3CG1H0uj4JYDXS+zhaTMHgI2QGzmR0VkN4R20VrbZ47abQqbVi2zacnp7Cs7vWiu2sir5WrY+2nzlEK3lkNqmnvtja7KbAJmmK5CBiOeUtWlqMBdnc1g6DdTdDmGHkODS7Gy48T7SPV68KT87LgtIbFqwqOzdCa6xzY8ZHHVtVMC2LQokXi5BeFs19zm5Ahx3OTTsv4sbzaQEkPk8ILTicn4nKyOKz52veJEQuwY9DKYYeEXMdBOodLaI1R65cLhxroYtANktBUBySXR8hBscsDSGT2AD6goztkkAaQd5FxRRP68QFTIKFisEqKmLBWU42txbFsgILWU5rTzUBBpMaiVWJrMZj1Uc0dAGWg/bfESMERhCuCBaNPu+FgOYwy2PYu2PQdoAWaD5x0fnmtRjKA0EWweGworWqa8UV1zYWnoNaBMpnewctB/TWQYcy9mA32Ex7PLlolwZU69a+wRxIKOCxFS6c1ImHAFAzGbGhi+a17M3iKKmAeEhhAX+4GKKCGeQPR80T6LnKYZyoWER67ODBem2Pga9f5W2lmuM6a4fJhUjfKwob7Pvg4+HEYkYXYnf20fXfQzYjlKWMPaEJumiKDDFDuxoSFPVLn8CQoqgVnTvEeLcra30/7qIG9G3bIFCPChGFUgVzQNnDZEGXd9hkoiyTCDpqd8QKzVHLRY2cezlO5R2HPjZHIxlrkUYOmiETUk5fN9aA11gWTe8Ru4lflw3oZE5dvu+w8x6Hep+FFK8rSogds8aBRXJTdf0AIRfntkxj4XJzrOW5xKWWf44EgBul7T6IGCyfyaEma4JoOCerpcPozJyyW9PvOgxRQ5Tfx4Pcuc9P3GJQ2Ava6Txg9/fCdhJaxfNIh8EL4XhJhHA+6mdHHZkEKeiewaFJ56LONX1rY0xj3Y7z0KyzdSPJ3DiyfcppJRs+J3kvjOxJBqO9adW+SxOo9Q9j3DxK1+S5fG/irbhyv4+NCd2U2upyk8gYB08f1C09DhlyGYiM7Tr/UgQQtn1ROgPcUQzdQtijMHXf8RRifh66emzb94uKna8QEevRziROR5DM6LR+NF6pLNbXGUAipgciyE0fFYjE1LlNNpArTQZxp0KhDslOadEWgoeiR59JAFnQqq0ZkYgElNYi/Z7zQts1glYAPBuJ7qKv7zVBteRkOKjvubHeF+kdtTYwN5RSQ6ZXVCaL+DYeqWxGIn1QRQV6S5qC549zuT35Wg9AGj+aE0LWb5gOxHOnO4PhqnJuNVk4qjA5kjDScWSHa9cPLKWg8BJISWKyXj5XqmNuh3QKxFCtKjE0Kyfyrqgb2K0oGsTpZyfjLyoOhe1Lx4fqm7XLfUoOztKgIvr6TvWE26d7EIDNfpsNtHqtG0yBkcv6+NnOqaa4mXfS8c5zc3t9K4AVho6AjnVZFJabYTpCPecG4ITV1mgYgn19ClSj6PIDwZyKueDmsKA2TTUGGQ4Cuo1T8Pza1Gm62zrN6EyLwb8DQO3NUtGIyVFjrTMRWu3gVfeI3jpO5y10KczFerVzbt3NYwf+f/bedEFu5EYX/YAgs0pSae2ee9//8c4Zt7bSUpVkBO4PrMHMktQ9Y197xrTVlcnkEgsCQGD5gJNR314MYgMAf/pqtlfnH0jeaE88X0ExeCTdJ93Idb4xCIqa+rd7tHeE8V5w+o832D9UWZ/HswOC8A7g4ZNgJcJOwM0QbAiywHOZfS7HeSWo3+sja4b5Imkz9Sz0a8e+7+jv70EgbB/useLp7PN6/Exe5XWuD9k9RU79/L6Uz0WBnK8Lu70FN8bPygN385swNOnn/v4rbk8Km94aY986qDFage4lJmznHevNetHWlK+HduHyK9V7Du0FlAbIS+qMDFz3PbL3X8uyWXDJL0ut/9nHvx3ov3gcyeVn358d6FnrRqeSJTWFizRyy50o1b1Yo6biXbMu8GQbnjrc4PprF1+7/7B9oMtL628Nd1jeNfT3goY7DHOGMwB+x+h/FGW73C920d7vrzz4ehcId/pci6zvfaB/GFh+Y9BbwnnbAg6SCOC3AKBQ7USkxirIxB8vo94uXoqaEQ84X7t+n0drYxyvMCPsO4eyS7eO6g2U9+Mu+jDeD7i7ZlZvkBvhDwJ6a88QVTx0o8pqkJOkTQgwPiOfaFH/IgL5JKDXbjQnkEGaH956fP3h9zLZToq2CRLbLPlaGfiCiPr+kzzb5Us4RCbamVvjf71Xgq9geYGB54BlczO0LvoYgp12SMny/lk7quMxoONEjUErXmLDvQomN27afeN+YMdXhKHm0H4iwovfXuDr+wf7DjCeYeD7xEfqZq0+R10Tz9HxHb6ZjzERFMhnxPvYXhQudarZBi5g9ZB4mG8j3SBlv/9sbf3kOPaHcANX86/xaN9w4OK+gwGkfP7RhlMAQ3JAMQSVtpGvnVHOXulHaUCOyeUbCZmk8qNjUpSIro8HJU2EmnjRvKqpz/2LzUl95kEhp8OgKinMmTlOZ4AHBFzOh7UO5rfWrKsh0YZhzmulf9ZsaNI2h2prhjjy2mtHg+eVl1ZlUfmJZ3h5IILeIwfDyvFIfpl8rvbLN3Naw9DgmgTgyK4Vc+iZfiA/p9f4LnU92kxLCQKAG5XkgGJgq1muPPSygxjYQdQgNubxzoPzvD7LDYb6HicG0bEYA2BBGwyhBhlmXnCjplzThX4kJC5XwTGQMLPHkhzIH2tCJChcMlfLg4fieW5gJHeiz1lJ4vIO153o2eL5d0U31vpyO3WQlXYYECy9a4anZZZjESxM4GUBU9MgFXdYEJmDNzPLe9+x9x3bpv/63tNhCXMkD4nsSk1mJ5uSeRx9THStEJgsazva4g5eRIfJILbZjRJ2H3FmUeqwj3A8RQa3ISYMq53de0ffdzOodOMXXQO3SDP2zucziEjrRgqi5vu+m8Mx+o2oo0mWBelzqM7VnugjPedZWgOj5Xp3XX8IyKCXx7D65eakYNhnX+eUckX1YQILYyFA5IQuokgxOwO0aday06kFRjRmLKcVp9OK1la0llDaHmyRdO70W2cSMR+gg4w4rj0iUMC0U102qidEzVt4Qydd253TIu4Q0rIDzcfAnE+9K//eDYEEzqeLrkE+BlZPPCBdw8nnrUsDOkGhIhvZGAkwpOPxLMBO4RgVGmjLgrWpA5eb0jWgzuKFG7iANugcq8GsmXLHrUBRu34kupaGmJOCO4gtWApiuobrXRaAYs47X/vq0G8QEpzGjr1rcNd+3gOqVmWuTYxB9dcgqcjuAwz9ReCQuTF3RHPAGwDyYDIwuKlDz5ESWmM0K8ega0lKGQOtXa8yVDPRedFyD15JQISxLr4XaFh4wc3tCeu6GiIEh2x0uGg2JzooebvzDRbBIHXUSLP6k+44HU3RMIoWzUH/lHytMRpZ+QFyZ7qBx4uEPsNwAxXMeT7SEQ5d4x7IBBGFwxeGsEO+p/FPBFg8sKkLOnd1mFmwm/ebgMh+B4nSJ7njESFHHQFgDDVqD9IgDdZZgA6EOY8rOwChQyGVFfkijcmhPYTaa7qPZ4uz8/eUt2yBPXBnto91LStBmKCCc159TpIePSttOiRpezo5xIyeRYabM6fOd/YlvxPRpAtPmc/+N/SpRCUBEJDrFnGiqk+UdpF0lidrM12g3OujXfYNVOjF55xMlkVLTB/Wh+LyEIBa0/IFZITnrKcgndR5tRfC+XHA4BMltitzODF9jn3WnB/aoGRTQrfSZ7tj+sL1W/pRHhu/ZfOKbLKuHcdwGor6e5ABlTmw0xfN8DZf7tiiP6Fg+lfrFaVMCxovNFdfIUOD5QBz+CIVSRJFr9B7huroV2rqXvs8DZ6vL5GoW55r4nAvxTDHedVTjYfaHmH4tYUEQ+fN18LVRGEBDWQwMV3Jkivjq+uptFUQ4yqGUuk6mY6d6yrawl0k1nA8E5fL5do5P+92XYcpr3Ec0Xk88YAyqkOGltgwvW0hdXwwa2khLRWy6LgKrETRCvRd+7lngoYfcvhEh/NUfo75EA+oPVwT5b1azQAAIABJREFUzVUbkdOsELAMCTtJXpY8m60US7fn09A14Akht+03tGWHkNtFLehRXH8jDUAaKq9yfcjTw3oxDk/N4j/uOJOWq7yk5sujzo2eUKencxs5XOvXP7ckI5bksAL/7Lz7x20IvmnfuvGsgZxXkSzf5fzPZjwePmCQ5DZfDZrQ5XrT6ihPptdu257y9aIlFO2p++jGFPZ0N7pn/+hAISn/9z6wmk45XLd6wr5z7fBWVS3Ez3ntbx+DqpH87A0bdM/3VAa6QIMi6L2A31nix1vC/uFS86kUX/+yKO/mdy/R3t8nr8ZcdtPLY3SkM9G3PQ+keQ2Ep7PQ/dT24R4MYPn9FeRvn7DR9f7914+QLNP7f+G2X2ANSYP1ubrN1QH10Mmtd/DOuL3RwPhlYWy7JcrUQFB7yLPbG/Rv35MHP9HEeN+hVT86vhNw1zQVLUsvYUISyGe7tlXWIP3C0PwPPf7tQP+rx4WGMR+1JBDhDuvbBZPKWjR31Rmsfl/RYFJAmjT40SK258UjfP2RL+Cf9OOJ47go72yRHZlER9aTAZARoqy135kJHQNMhJO8xBj3IHmJ8d4Eq/ygKYzYiKeovGw+4w4CwvKbRvIPAcaHhJmTDwL+zaBKSetNbLANh6iDon+wTKD3O06/rWrgdFhz+gK2zHJHBVrkpRpSRZ38C2kN8S6fp/EDAH7L6O81g7KjxybS/+tGAgd50+jL7Kfw1+BmBEJ7pV/4HWNtN2ACtv2s91qkskPi8e86cu2dPm37YNA6xXgNAMM2Yad3WtPaN67n9xrTKASMzxYp/FHns9t8+zgTnoMkAwpUOasO/twk8mHePRstIvJM2WoEPAfha/HIvR532GnO/j7mIBAdNyzWpoOSmsrLC8Ah6elrgbjOzuyfO9x5buiWk1O2brgu1p0b2vAC7eVxQbtKmNGC93Q9u90jEL9++OPiPQPfvalRI8cRi6uSFsoWvl20s4VhI8I2pvt8AKsDxB1yakiGKgLNFJauzi/feIfqffjuR6cMIiAEMhtWb5//RgDhBIHVTsIZKJz2OPxHUrimPAIawXv1AXE61W/ADEUoxh+nX3dUVguBb3KGgNvsTPbNwV6gr45t/5Hz/KK5PjdRu6YYJ4A01P3yEw1yzWtVAkXXo8NdVWGPBZ2/S2bGO/zuEhBGSQ++mQIyo14wZy95Q3rXzJZWop8FwNBImgxMKsY4hKJ4OQr5Nh9HQCy8dBgCAUQdazLKttUe7TThT3D4575r9pAbg10PIEjIIsBohCkh1Y/tE4CgmZIA0A3fRQqteQ8Ag4JHrV2lUFBPbQx/pDboHKbiITHiNqxh3ABAlBsJpP6gcyOW5SaancWELh0ijKUvkAbsQ9d3Gy0dClTklxkzj9Gx3iY6zuSjfbtNSlUHzGHOBZrRcnUM6nMlXhi8v9B7zSzKBxjtFVLMTCpDDsB1J/voXjtbaX7f93CcN6vTvZ5W3BhJ0kpowaMomCfDsznUGbPv6nDuo0+zRDDnoUhk8wyBIieNeR5UjyGQeJ1uNe65EcRr2U6HrQHNKky0DM9a9WDB3nfsj8Z3NQpQZZg54fq+a8bNvmPbNQig910dVpaBQwKtYwelGecVft8+9d/4ggBjH9jOG4bxGMCyfESd9l5XHhBz7lAiXMRc2lgPsWAEC0owqPlB5pSCORX3Dm7QzEwi0LKAqAOdsCwC4KRBeCeg7yvOBkfPZnhi1gzzdV2wnk4RNKHIAy1kUZB7rCElzwB4NholG4+aiJlBVBl4qtNpa7qIdtcpPQ1J7J282Lo2/uRj3LzefR/lGQIZmumvAaHD5JHykSEDbDDfoXOGA+tiaaoBSARdBsa2Q5aO5XbFsmqpAM3+lEAy2PpZx48Yy+mE22c35rA1Yx8z2kLJtwdAQ8HkmXvqyez6C0GYLS7Dx9Cg/gdj9EXXmghEuo2hPqPZemlLw+IZxwtj4QXucOe+YMgO5kX3FGzOLQtYkSEG0Wo1YWlEIBUBVkddEI5N5tAnglDMEadOuaHOdvVIa21SMmXRDZIy0Dcb175b/daBDi1DwGAIDyzrKdAHmsHhMwjcFqzritPNKWQ6GR8b3VBnPJDLUHJgfAs0FPp6WSGPj7bvTvmuJGX5QRb4QHAHu5jQdYQv0SAHYUM9smxyTqcMxBBhdv3e+8C+e6CO6QisqDrNS22JaJC9O1AnOat8QsaANHufcGQUO++El9iweVLZYUEkYwRSzxALYhgalAgY3xKALMuZgmaL/BCAuCl0/EiUDm2q672CyRKHpIUWCBP6m5blcbiDdFxfZJ6HQTzRlLx/KbuTVxz3FrOCZL970E+5Phz41l51kltggnp9wlFU/816AeJZTl+BlAIAZBvnYc8ThGytUMRg46cuI23/Jb5Iq9WUKDLz4GNi61bRNixQRiFR4p5QXV0HsXdxWzBcYxSjBaMDESr3uiKDkNde6kDK/LSlQXZ3sNdmV52AUjbFo6XwPr/HdCgXM/4bubRFZiPbM7ji4MlsTg/VbaIP0+F97I32PZABdfip3AZvp0lUXwOuhPjElD1D6HlI2VVlK7l+Yb/HrcZvxXQiDeEx9D3XRwSAZaJnSHWV0WlAz2GnpDOYvJAMSz5MV/Q/rqf5Ihbde8lQWohg/GKQcRuOOJn7/EoGvmWQAblnOmgygtJMjqjDX8eSRYPZw8ZiIzFEeTlDg7Jb8/cwBMUh638i2Ncd/WknmTUNC0Ty4ffmehsd2chpxdeX94MZakaxMkZiWeUGJR2lQoyfrI5oEUN+DFK54IZxzimxUMbEv3J+LYgg5NuRZrwzKBUfKO/zNSXq3FyIwPQSBM3K1TX2AIxbrHQHIcZ6WrGeGGiLQdKb3tA7+m6oQIV/eSspejIR4nScBHio5Sf+fz6eakdUNLDl6uFqFTGyi9kkrbvu4PHM9g7NYnZ75Y2oDDuT2tY8c7YbvS4mHrojBNp956QMAHqvADjbHotZS4Q6X2AzmAfSoLWTiLAjaX5pVi5sV/3+9vbGxLWi/603J4y94/v3R5CIWjuKTZigOvdidu/TaVWkwtOq+k0fABlSGzO23jFEcFqsNM4wGUPiwIK67iBmf5l1nET6uD5nm4+jyZkzROeEcvy9+npdcSehOQP9IFecg78QidAEpwl/0k5KMyKCZXmN9rvg6x+fYo37Y6+Jro2UFnZzngNKUwTEfC0pfrQsL5SOXr4hPDe4eM8ify7XV+BH1mTTW1GaO7//hNu3hPHpr63GyEt9ermX4xIF5Km3zkEb9Qm4ev54RKk/0yM1KKPj8fERNzc3tmcHHs/nsEM1e4GX4lqXhq2PdAeK89KnD7ddhH6LvDdkGaW9f++OwoAMnK69dWCYgzz833r824H+33D8iIZcbWBeAVID4LIs6VQBdFc1DL5dKr2LbZxQFNt5wcd7ymK40G3pyvdfJfzjvcFIrB00t0ejQ7MJq1jmvRAG7kF4ade/BCFrcvyZ41rTGXcAaIJqFijkO+NlZLbE9cwG767H/reOjgHPJB8Azu/vMqOS7n0AphY8pYxeO8aHzCZ8KmDAVEt9RQkaIGKFSiLN+G6vCOOzgN8M7J8E7V23+jOppEa0vymlJIL+cfiAAfBIZdgeuGRAc4NAgwfojc5zwEyHYqoNZrozRv7VhPO32JhEfF9RvAHEJhGwjEvrshsGI+I+9pYznd0I4TN/xXOZzx8/a98Oyrz9IMdrAQDfVImPCSnKGQHjUzppwsAeBo3SFv9cXiBhaLSrvhD4FUHoUFuqNvS4eKGKy3UH/TOgOM+vbGuunLk2NvNVTpOM+hRKaijtcYeswBRPHxqousLcEp4WuaUCLvZhT7T62m9Xov7KX2d3jBvMVZ7ykCc+//i9+u1oJPCXEjAja5DRgI0X5elDkFNuwZ/q/xU2f/Weyehz5RmeJVMtQERlHsv5dFjTQc5cUfQvvpZADL/XFTGRgEaNtVr25ktrtkFWQvJsH0E6eNSYpJucZgZsMZhkN6xUOC8iLztwjEC+clB+oDpHZdFM2cc5uNMcOyWKpNPO+aBDUJOVDAlIqJJt6+qyIOdFg3c0/lfi93/MEbSW/wnlRWUc2WcysVkzoOzyujFxJ5cbhCzT2mG91aDs8PyX7SFKs2PUt3yq3TY3lY+qE914kk1vGLUo+/dUQJa24UALJhcqjamRVB9WZYcbRNPYLqGrVcQil6sY6gDu0tG2Bm6MnRWuu6+r9scc1u7wa2bY9jGAj5kcOmLrlZs5rklB+j12XtxQZ/9G1EV3h4c6vz0rtpkj1+HZrx4Eoxn9onPBZkRU58WAZpc7x8/Mt6QtMWeQlEz0MTQbVI36rJmfm8F8W5tENBjBawlHo+wYIti3M/poIf+lZNASs0FNMmRdYizd4ewIC8rGzJHhzid7lhCZk8Nr3Jf1YmsAraVOp5birBMOD7qxebeghWVZNVOXyBzoapyNbhaZDElqHULhpLiYKyZFQ3BG4JCzh403kcOOJ3052ceX+DjrER60Ee4E5wsyTDe3mRjDAi8GII5UUPTZxQJAdgkZ7PCz4vsvm3cxnbi1RaFcDZK79459dOy92/hq9vl6cwJJ09rcBIMpJ8uQ75pZOgitWfaftxceBMThCFA+qMaLJgKWhm7ZL+JjbQ4AzVY2h6IjT7DP/aLwidLBndE7o7VhSAkSOrzKQaVhkEB2BGyza/nMHmTDgYjiFjNtAuXcm4zjAYzWFMrTjLtssMNi9BD1egVZegCenc4Km950nJdl0X+rBge11uwzg6iFg0iGQJbqeDTNVeyZBIyhlSRH74nor/5m75C20+Wp0YQ6MLQDXkudLbhbUaVGZNc6a4S4DFcD/4ChZHiZCBtEAgdNAd0HJdoRnqui4YaDpwkwFDreHecuVzwL0HvjwTtdHJVjYAyFz4fJ12ADtjZJMouYyAI9THZgDM1SRuqRqYP4M2F6gNKHO+K9ZISxMLAH9cS6oJAprWSdq4xp8Zs9dUbBCoGcvYlAUao6FAEY2scyaaEXO0W7XAPCeV91CArZ5nOV+46JdQZ9DHPkWcYkCBgmm0nAw118o0xGcLvQpkOvptSlch9lI14CTYkbuAv6Bhu/vDTIP+63dW9rvlmZh5CXw2mi6O6CQisHh2azwFbf/xSaMlKL9qYufbQZ+Gf9zZFfvLcuN7zt1dGqRmoqjp3U52VaWzkGGRTiEzDTlYwcQG/TNGGIBx3mph5FoZSydm2CvI1cLvNyN8MnzsdtKPYAmZ2KLRiKHOnCWpQuND973QMUtijfwRS1Nu6lOnJ++uIMwplp6ziGS3x+CtqCnZ/C910nj1d4b2jaT/tvqpI4QZscMJ3SLY8u49wXPAYU9ao8g4nDfpgJGqH0XKzx4/dUj5xfmL3L59WvDxKk4C/qzLAgNKSeOtxRGfqU8dTOIb+PR/Ll68e13yYe6EHzrlslAvbUd+1C0ovzfSblsTl/MOe5I59kyR6FcX8E8AygB7R1wbLcgInwAGCYHrb3YQFcvv5SvwTIkAouabEe5x///A8/HgiGdfn0QcisXpdBQGYO1+Miqah8dpoYKEkj5Tq/1nd+Tx1sv9ckwMs1WfhHWbeA23SAdV0y8BDAtu1mdyKgme1kXSDfHxFcv6wbIOUdoJnrHR7gV93L+u6VG7bei5zAJD9cVq1Lw3nPEXD9IGndqfz6OvIABkAd0M3lQblGjCsLZmSAH5Gno1F6wqZDx3s+Qv8g4N+UXxAxmswBFteeL1DnuztwvY0sen459LP+vRHg2wfBrfXz4QfvAdRxDugaXKxt20f5caf/8vGPXejHPgs8GEPPa/AGcDJ7oIxErILZwE63J2yPZw0k9/XkQkSAa9bLp2gwzlsD3JXlvB3Gi7UMGWOUMiNTL1xNZpN+PyPS/8HHvx3ov3Co8nZd9fgVunEBpzphdSjahnrs6J/HJPgGaa2SSwK+/s7aPLpyzXEh/1Kj7WK//rkJk3sS3FUIKCqE5Ih5ZpBob9k2XgI0YJd7NHmJMT6D8AI7fclgXG/c8TsCNTP3GaUfhLtYw6ffldFs+47xQTIAAWSGGxWS+96x/bFj/U2DGdpbgnw05sYvAbmH4AsYL4NFCYCd76MZAkDkfmpXN3j62AwCAO7Q8RmElkowzXSQTkg1gI3ezeD9EstvTbOmPt7Z9XdojYFXABFjeW21gQkKlQqVfqEqEEOk24ZLGfTt2xPGGMq4ITh/3CBgLBb9ND6oyGdi0CdRg6swnr27ASB4eP8AgLG81g1b/9Ax8MJ7B/A3fVMEhl7faLgIoMN5PhCp//68LJLnQvhmG9oXwocbXKGh42REa1wJrUfdRvqG3G8lqMObPvuGi9wGWxDwU51wAxdBoV6JGIxnupEHgd80bB/PBlNFsYiJTPGgy9V/I7kJq10ieg4WwjD4dmAWrMcs+brBlfrd157v+y+yfKlcL5PhJSWzIQ6IZsL13tGWNZ6ggSDLZETWGp4SAj5HUWmj1kRH6UvDbdD0gptoI+HhYhM7Oc9N7vfye/xEc3+n/se4UxhlCKVWKwgSYbY5oOYjQ4V5r4jvHlhTt+f+On83Y4XYNudCSfrhzthqgoLKG0yhY1Yo0yJAfBNRN+FRS9Nefnx/ba++sp5Jg2SlrfrC6GOMgytmttGyDU0aSX1Q9b5GDCF15O1WN5bNoRJGsOHGGTXAEmA1rBDz5+3maq2amkrBU7xeFoiwjx7t8gApoG5mra7oUMdPBiolRCsgkVkQVCCIrNA6bjUrHwB22XH1kOOHP6fpXurGPjdG0D5PMd9dDWEPAnkmwU/Ul27G39jIqhZOc4+TdiSnmG4xjYUab4HxrYNuOcazPddaseN79nYmt9L+J8bDA6SunxGoA8V/KruQMl7hvCuvmZ4SBlu7wJy7g0gDBqYtdHDdAolJRh4C6QCoI5wCLjuY0fZdoXGlK06BBc7NDgY1uPJCaF0r2Vf7p9fZ3Q0K3eFhRlcjltYLH8Hf2Oprt2VFWw3euukGzR0tnj1BtW9Te0gz8ix7VZitxrAYH0gHChFBmjold3ZHVPJggljmAUUAxm7hgGOTdHwAkRGOMj6uu4/e8SBZu9WnXyz4pTVFmepxu9VlbFoXW7OmTRaZg3wXd5Sbg0eA3g3W3Z3aJmCJgLEXeEUmNFrUi0eEwRog0aEIQQqdzcrrmmV3smdx6mfyerxkxq9h1QPD2STBP13vcL0mZy5p/HI9KY2HcbOuO182bNmwzhII4EUDjqUrbQ22ZxivdMQXfVQoXyG8NfhkWH9DoqA1wm4pFN4mQco/h4Qd3csB7Nj7hn3bsfUNe98VHQOrrpe2gHmxrHMO2alo7qROo4WAAQxelLaGIJxmvo4NacHPOc9cQGg2fso2dQw94LRCJHuGLDd9TlsWnOiEPjoWyzh2VCuXYwSFbm9Dsf8VkrtBxq5w86dnMWcCQAbj5tmNjtkQ8zj4X4ZYrWcRsr0g2bgvqvs4eTTYvmQE3LBC3lubDKqeCEq7S8OyNtzcrliXkwblLM1qfVPQqNPC2AfEHORsqf6BfDC0juQgANyiD6Hv24IQ4/VkQWBKLjY/4sGhEk6dsQBsdV7RdVx9XQ9b20MG+u7oCRJ7MDcu+/wLRtKoKN8alj2swYSWiVodFaR7bQgCGt71G4XIH5oxL7pfHH0Ebw/Z4SpVccwoH9PzjgYCm0sNaiNgzaAVRZUYSq+czw11mGHZ2xYgYUqhbynIywxQoVNb1+lw9f1VmfaiXKYDdpbzqWukw1c/a59rBrpnfIZTB+bAZzatxdvphk13dlbbSNU14OpD8E8im0uCohs4nTSbg673C0MDq3wdou6V9AwBtpYEMJQJ9Rk2CA/A0TloAfGmzy9qpA1B8IcYR1K0g7GPyHRe1hWCXdcH2EFjIljG15JnoEeQgdG6jKG2ASFDxMDEH3L2XP+xPUDMLyY9MOSMEbDaUziuD74Qkfp6T7OgHnXazIETs1FNLk7NJkEq+yanMb9Opr/zr3kmgweRNbWh62sqd1My6t3BPa0x66/rCCoLXV/J4BRxBhOKl2gAj5TOEZSG7F3Tvi7GEWUvW9dZqsfWQ6UDsXf7hbGPtnUpyKQKc6ITaQDTbjKembPMFcGSHkj3AgPAdxeYRodQWpPJwpMUZb03vVawCUA0sK66P9t3pSXhhkqH0nu8Q/tq9Ol7hIPd2GnVt5fBv0Tit2Z8xvVYL8Oh9sBE7oDJj2GBotQZbDq5jA4x57KXLqotuaS/mV/K4Tpfz05+JDZBxrcrl3W9woUaEbAZgtodFIjFboWQohIKP4CogYixsDrUdc5uQfQMN4vZKtllYQbHOmLWKPLW54R8oAXXOv1PeZwkVVpAm10zeAnAan1pb+6wLgse/+8H8Ns7vPj9DfZ9x/dPXyDQGFE2MULQjORFSOtkQ+dBBNhIcBK6sIcK1JG6D6hDrTYMaT9TJE7B0pbg2HXAF5PzijBoezgLzBwiWkoKqq9s247Fyl/pPAuev3gOag2P37/jfN5MV83l1TgTD/w5z241s7cxawDs3gOKvXlyWdM90NYVDWixWtCttbDXKLKbtrM7cpa4PqSItr2fY3Zqz6scG67jwOzHIpF9Xp3gVMZ1Hu08jvbcF+9e4/98+ISXpM5oZ+sdgPxxHz6WZ//xBiDg8T8/4rE8PFA/7HlfSfBCyPA8EfSyWMcCoUDmNvr9GxSV4FbUlv2dgDsBXo18lrbd/AKk5QdGeTaQDvZfqYc+Hce1Ttd+oMO3/95D1VEx+aZr2hMY9t4Boy9uiVbVWtPETtOb9vOGPgbW1vDs2S22+6+6n2JDUpHD+w7H0b1+DGx0PVjGCJsJm+zxUnrus6wB6UXV/sVs//+Zx78d6H/iqHTim735Vz1xe1i8y+v0ZoZhD9DrbRG40QpQZdAf6Ua1qF0ZToNfoNorl9CBwf/sKPpvAF+9sA1C6N2HV7oeub59rcxBxAwGmilOABpe4kyff60Pvum80mhfzgSgveGABCYidHzKfhw2L+c/PuDmt7fx3f8xvzwomgLwlycH7BqfFiCy8DXY+QvqQF3T5QRKA92ykfqHjtO7rOkHJixvG8Znc0AINJv8rTt7BKf1hG3rAbHIyKj5ZgZnVYTFapKqARAAzrRDs69fAKBQuFps2JR5egS6w4zIPcCvBNIA6d/BeAF3FNRo3RiXapSAKzzpRE/HxOVYHwX1Tw976VHp05+K8aU8k6bvB00WBLnHZLiJTZBkpPuVJoRDhPBg2YR3dkG+8chfnuqjHK4FAI6sGfUcDSiYuR9nINzLF+/C9Xe5w/XadWkXkvILhQPHA1YAj64zaFYTxl5/mscwI6eOg0IEy0WDjm2sY5C0lqo7G2i9O9dlGo15Df6Mlo5jTSDjM2S15SpfNUeIGxiRSr2+TGJTeS04yi+5OAdgYANhBZkT3aNPf3Zco5f5x1yr0/Ir88BBp+L/x1E9ywyfy7e5AhmRx5c/6OG043RUnDc+u9VxMkcyE0A9oVwr6kiZbF8pGu5wuW6rTJG42Y3IFLVKiar5hbxJGr0ZkaQIOqjGVOeRYwyDJrXSHZMBjspYVxmYrQLSGfn3Omb6ybG/OCg3lnEjEA6GCBQoRMO3lMMXHTUHokVfCdQoNr4L6BZmxM1WjYdhjnMkPf2ChBB7lxuGps7GiXScC6isg8r/lJZcX1NxnXIujZE2n15GoVoXofNOjHDMuFFOH2HZheEkNKeupN4IMafFIKDvoF1rRC/LkjXcXP80pwkgFiSlxu1lXcxhtYShdVjd89G1dq+Xpdi2DbxtOGOzEh2w+toGr3xasSyLZRbO+o+XAVKZAUeAtmEyRyATqDUzIHoWegMGwrEedYPtucu+Y7cs8HC2EEDcQXvH3gHPPup9YNAAdQqSmTaJdaNJarjbz7uOPRcHrh3MyQ/JjZ/2r7HiRJAMkGXri0Azn80Br6jYqt+p83bFcs3objwmuKm9a7QFzArhTtwMUp7is5Og9ydOWHasZy6lA125o1KHqypT1JfBkx6CIy3TyBEnfLG43urvjzWCpr8RQRYnEPJBhSID+DPcCKVaVawvd9rYOhokkEFoR8M+A+tKTq7wWri+jtUpM0Aw5I+hgSO7GWo1sFWfQ400w7m5Lq1RwwoDTqAGM/QTxKGaaWgJkOE8xOUWwuEEuAOKI1DEWY34eo/58z8UbMsdZ0wK5d5Gs1qvwNg128YtagQCW9kGDegYGJbB3UBoS5tYqYgAfbGudA3eMVoIGdwIkAYy/Eq2Ou2pT4oD4yqULxFgUJieBc6DMGTHEGBhAi2Wcb6esN6sWKxMRbbLea8OCJ8aRic0y9IMx40MYAc4DKGjyA0Ev4DVLJz1lcq/XTexdbvYLYZ6o8gUadCPrKYIACuOZW+7iNKHeFBNQqxrtngP6HXfKAV8vTs3yjMhw/RtKxFxgG1XuNKhwdyWwZdG2aQv1WkKvzUnEhGhL7Os8gz2AVaah9UPdR3A5oItkz2g4tn3hLMjcXKeszsSXRFymkPuyX6gCB0z4mLZG2Wy5ELz5eWkr5k5ut49K9R3rjkulPwN+dedoRHcJhIQzhrhbxrcEAQctZ1SXoHUS6S2ynlWbWuuaxgMtdNX6vMueWOE9Unk15dMb8vOi3kAmwgYiiZmsjvnhXIeKaH2yecPAIYkrLo72Ms8T3OGogMhnWP5Oy70KNcZUaC3q6He9wBEXLIdZR7aeO7hqOckv1cprSJVDrc5v8Hh+vqwa687yP95suOaiuRUZxe2bxngnP/jqwhQ8VB0cUc/DIZQ5E2sk/KIpxZfvQ1UKiFzPsr4hxY58VVl2bT+Ip9HDz4OlA3jS+RZ3RT7Yp1jv890AuPZDKUF10XBZMgQqldowJMFbTODTH5rOBsA2XNMyhgcHRoVgS7o76B+Va6k64ADRU3LWrRwoLPLKL9H1IneRwf3ZghKGqTVh8qNYXrMjGL21FTN9JY6HRkP9w7RWe0MAAAgAElEQVSVOSg9CJ4S/M33yYD0RMtwMvPAGjCDWsNKDavpzAspIRI9x7LuQNMa6esAHntPCHcL7HXUptxvQSH7Cdc7/E96lBGeDqXMidOhf/yC9u41BMD48AXy++sJ5cu77eN9zWYkpJDhT4nOmj391FHfk1pYniS7aBSnn3SJ/ZvvBfqU5a227b2L7vktWFvRslLGui2FSAMvYfKk7x3tpOgR3aCv5TCwvffY0/fgPbNcHaKQ8CuAcd5qR8Om8VdJrI5Tvf98zdlxuNad6K4F/79vX+Phj084IUvqCjRrPOnG9Vp1fs/O7HnNfyXBC1e1DsdXu+85lE8vmNWUYW04Or6DhiUd5Y6a4K/5FXr768c/jhkEqRUnun9VuaN2jL53DSy0tdC7luna9x3rutheH1GWN3pCl+u7vvdqL68wFhELYgnbtCKasYgikmGgRCqankBx799xsv7pj3870P/SYeog1e8XvwbDIgvfFpgj06+zhbR/3Mt9ymC+VidSkaiuRB/t1+SQmsc9yDVlGfNie7KL5bgTi1aDlE32/J5iW8b65jUAz/jWRbngFegVsH8YaG8Z/BGRkfOjNSiwfaWU66Lhd3AVji0TB4AZ2BWCPRQ1EPaPPWoSPbz/gNObN7rh+aiioyNrdxMBw75rRvQdutWkJrVHYTFI+o7PU7MyQdA2A7gDoQH8zTaR+uuz39+CAHz7zw9at2oIHj9tYBD2Dx2Dv6J/uMP6+6rK6qsBkqbC8w3FGDMTHs9nNKjRfHzUgIX2mzrhl2XF3neruSx4/PiozBoDne5D6SD6Vvrv25lnWCaDDeP05gZDBvbPO+QLQei7KjnyVTcdYpulVsi3OJkjqinfFhDxE02a0h4IoLDAAKigff6E4uclv56iLCr/5nPP4fXNY0MZv5FmueJ7Qvt731z5ulhvCRMGwOBIX6AZZOOgbylYw2ojOAlMQtocQxWh2DcdXrNjrpV+BCpnIpwFuKEcFcIc6eiv9OudFzWcbA4eM9PeLdAGpTh1GVrDWLsSmqb2wxZGc7hZooBLU0fNHsq2PswF9eVsDuup1kAHBGcQCAtusVsYkpADU80qxRP5ulMfpu/FmVLpgq0mp7dzt3FZ0nJvxoEKFy4Js2uRNq6u7+MIlHWNfn2bglkuXDm8FuHTKmMaLAgomegS/YyMkvLu2o5sP6HbLuVoGHDHqUfO5xNo0sKmdopnaA8w2DLUkAZVINYHEaGPgcaagRzLxz5MmyLf0EOC59jpySAQGTRIYwAIyFrHuVk8ratlRBxG2u6LTJySISYi4JbjmU7VnIP6NHLD+hPzWF6Ip666Rgn12pyz+XmXN8nUv2uPHg8CfmZUMu1ezYlgt7rxVKyPQoTmOV4nAjPQvxnfaFbD0aA/+LlB4Y805gDmmAcgD7NMSSo77iL8lHI935TXBTZltYkHedhVojVzZwWlOtH9MeK+mZjv6ij3sfUgIo0OhsEljugjW43tVunNHFWucyi6UVeHbNkcEWBO8wyQYhAWQ6lYjc7cSSzGv0e3Gsld+fi5aeYtk+ocgBo8TqdTQIY79BicBg4yvo5PZqxZLWc2WOrFsm8WssyctUD5zrDwYwyMvuN83rCcz9iWDcu2aE30bcP4/r04T8U2s86zkibSYaRrXze6uo8USCAitVLfuS0N69IUYrrUftffWR3swiDp4Th1Hi7D+ahl/PsacbQGEaCXWt+swRQkBuVNen65faYOtuGJ6Rx7g2Evc4NlvJAonIIZlxL5YEnTB8eQnyMgETcOTCDopyylWCGCCChW8jSd4LxBkSzsPiLNqNJfjVoFYSZ3Ru905v2CZaovjH7eoEgxiDEcQXM6TwOerd9Mwd/R+w7pO0BaG5xYM9SINWZEE5o1f2RANIPfHVDCalRii1GwIOIIzBSfZYANc1HHhGxcOfjcFHg9Kc45hxr0YG8QWO3UhsEGUd0ALIuWDijS3J1fXTpWQ+hiy7Jtp5POra0TEQBds6CbMEbzwFAKJ5cHdyytaSOiFIXSgiLBEER2bGcdi7Frndreu2Xb7hBp4EXRE9j+LacV6+kGS6NS510gfZgRTh3+bVkw9mYGWc1Cguh7ZGlYh8NadgiLGl7dga+UY98DwkxpmS04EkVfoNQPQYgatWoIK84tuyaDv3TMhijEvxp5CRhKWEMk6osPyybUrPF8pvNJRwjaeyKRKKKEf3aEh9IehvYPSAuroRwIp85O/p7gyyoXiAkNVpLJZNrYNw16WBkyVCdjc9D7uJIZzDWT2+jSMkyP8jnUi6DBYeNGQedsn523zEHMpg9MehGhUfJebZWYreAYpJM8zwPoXCf0wJDYOwMG00zBt3LNmnzhfKfrB6FbBGISYo/sdOLPELgjQGIuxc77GGhSu4ZsD5MfY+8Y0iG7QEa3Ekc+btZH4yM16M/3J6E7MKGtTZEMiMzRx/l76NA8688m14vSF38ShckCzVWhmmYwtyWpPwKeyRcTqXNJBKBHtjzsuWKd9HmCDD8bY+ylcq75zo+H8nFX7I7O/dyf5WmJfs77y9nhVJ3tDkcs/r3oiONKIynkuuk2w+t9JyqAkhzlknH5EW9CyJ3Ug32UfD3ECcwnDu2ZH6vrUAus2vgU/ddkORkfDt0YEqUyfDWoHCcMaEkEWEYfGxqJ1j8nQNj2pCP0OJUDFH13ukBpKqlnH9umgZFMhLYytm1YQpDS8nCUg9gPua4v0WdqwIQ978PhupP3296r68bKHrXyD5kduyyGFCmWRQuKsR6mg2gQpmdq90hi+CuHmKO+UtxUornaR5y/e/AqEaRb0JYoDXh9aS07w1ibIlWBG5bWsLq8wQsMfNUAUaNneNb97hn2A93K0Lg+UNs1jfm/wPFI6ph0cezirx6biRIawOMfn3D7H2/MhjZijwdYEg1p8ow7KhnAZk+8MfuJO2xfW2CnZye7U3QzQXxc5S6hOqR8zxaHLklm3zvvardze8Cy2Jr1fYwh9YlEEDQPwZd7tW9qMF6me2hJAMLt7QoZwHmrbTN+O8Qc5YxmpSO667nEinZESpNOQz7qp1X3r6MPK7078P1xiz2rQIABDVI3R30dKYlxSH7XAOyWfX873NntzELf/EyADnrSkX4mwQrCrdm/v7//bPMAPH9D2N7rs3ros/rc73/7hOUNob0h3CyvsP/xaXquv+2ZPXdALiDb9wMfG6SoEgDwhYF3FpPaAbyQS+j/ZtfuyIDNZQg20kx1AHhjKAl/OvP8cBRxOZ84nHc2cRBXF8cTj7l6vY9ZFZXd9oZsyRBhbzQddjmdcLaScyKC53c3dq+gLW5zrDrFj1t8bG/RJgG4vaRj33aMpUF1Y1YE4zEwqKucE21DBof+6/DTv+fxbwf6rxwiFwvmR0d1MDNewiNwfT/kjFSDj03o40sRTx7VRHFPbGjqBuSvdOVA9j9bBP67M0FG2BOme1nUSeyw5xBg+zCwvG1mOAToFaN/0HrP50+ffvndMSqHbte65+2tCtXeFWKzfxwY9AUsd6jANC4UWF5i0H0MrUAg/CXeWyHj9ePdD9s4KZb2fW7/V2hOB130O+ovYeD86T6isoE387MJGJ8F7aVKRjdMhoFrANJ8o25KObdpzkBfg4kKXmDQVzBeAPQtNlh6nTuRXuirbYMjX5Re26um0tkFgO9wYMzVFCLPZA8jqkc2U3EuwDZLSGisI4lPxu0YQwnDiI/TfE/urQnzj1T+1UPrt9cTBMJzEL5h4DuEnms7i0JUH+3NDAMXVaE37PevaK/e6LhdWcupvmW/GQqJcxT019jAcRz8StNPjS/RfF1s5hCbynp9uez4WNskHU6HAahe6BlZI5yN7oxUWsiNvnMq31wfOdU86zOKQTfn+bCsc1eI67j+6Lg2prEptPmiUOLnw+tkVtr2ZobpxDcjR+vCE8fx1zr3f1aJqUpdUK6vRdR20zSnYSA/vjD6ZdcVBSvbOv+XaiPgmw1fONlQghtEWjrfKJ6ixmevvQwyWCP9LkbAZPcMaPaBOxg46lSSGamyQW4EdCPvkQ+Jy+CpwR50Yvysjkn9nzv8JR1UYYAx5BAgZVJmUJSAI3naPf7U4aP263f+RME4MtRyeGACA4Ac152gf09DTvJhFWReJ9CP8aDR5kJuaGuYMtWMIMeDbUyeJ+HJd0xvvtoNZ3hQYSFsz3adQaA1SX29m5OvOgwFxk/diQ4Xc1431+bRM4+BMAwenejVkVuDTtx46nxSDQ08zSdz8hQ1HIyoE2iFegO6rpuhLtY9AWBGM37Q4GuscFozRkhX41UYy5ix7xrIwMRYTyvWxbLPLYNVUdENQq/w82p014xbi35mq59utY8VCh1Y16ZQ2exr1yDbbTJdtrR2DsOjXnMGEWE7bxg9s3AFKasxLHvBDTnupHc4vwZg3yOjXB386cCqmfcaPNAC4s8mSAMejsb2YH259mHzJ4drxUrBeH9Drnq9aQIA55cp8wcA6h3h/LP/TjCj1xSicrihFzTrY34vOY0Wvj7pwCEzvZ4xnKgVC4Rhzu0FYx+hGOc4eHaJlHZ6o11+zX3QgBXjDY2xmJFAaVKRmFpjnJYVbV0B0rraQg19EAZ6CT5hoFHAsxJZxosM3R+JlkrS/QV5Yr9ywyHRh4Tmt0AMEeN91mZJPsHOZ0MO6PjrH1fUyl9kqBgBCiEvWqaJvAZ5r/IYqsuSYJUVgJiTdNfslpubVKLFEHcs+KuPoc5eexiTO1YBagvG7sGQqZ9p/eFmgT0LmAe23tCbZvfLZjyVGki6GdUdjUIhytuiRvdmRktftwIAvACiwSx0OmE/n9ENtj7kvzBkADw0gLEPAUnH6Ba41NWXKRCw0YnauyT0+aQvmB7hQWHqNN72PSB0dXwOwT5V3Rlaqz6c6+bwcR7eLcOw1ixXHUDAg8FtoA0NZgjeITPv8PPaFIp6tqGXuKOu90Krdr05o1QfSvQlIq8n7U45gfCCZvQoZqyWIRg8kiMUXu9w7XPd65kN+RK40KnLdVHP0XV0P+/7J1M6xfh7rABtYGF9zrFk+hM6sWVRO4y9749chkWrinqo8nVec643x169EyJM3EobPHU4XURAS3hWrbHGR6UbBKfL2lH0P3NGis8lnINWXp19J882JYZ0DyIlaFCSyWMf21JWgsjqNw9MtWnj2c7M/D1XrplkpRx/s6BV8fFXPR+ESHHT7MVh02Jyx2hpjFnopT741GH8V1DWVgmcJYTTPn6P/7hzZXrarIPEfsr1OMTfSXf3/dDVFqZtKN/i9yFk9dyIQrDTT1fmrJD5LOCvNmb+Qs5xWAM8QweVCHJgGhFkpfNUmu40JmR6uevGScMEAp0sQOTRqNrWrceMMNtaKPWxfT2qrAiFW8WLVfqIEmKOqiGXek5kPNvvk0MXyCz0OOO2Nl1njVS/DMf5shiktfatNbbSiwg6dl1+GKLR5DzvO/bRA43kacpB/iLz1A0CaMxYZz4fdZ+s5UgSeSJQRiizXnOsCI0bTo1xaguoLRBmDUC1Pi1YALzGNjpkfNFAsN7RupUhGRJlcTxQuI73n7Pc//XjdHBE/3cdx9b7d4dwdykR9jbKNSvIZd2dHn/yPtXOf21p13um9rkuaHSu7XC9VaVcE0End5an7PX+LOz7YtX5+uOmfC0hMaY2bOdd9cLWAiWV2JNyEuU3WJd9UIe6Q2hfWkcUFYkCKWNZFjwnwsPjrrqiB0OabjgwnlxbPqY1aYkwj/Vh+/LTw6Hf6z0PHwXrG7akwEIHYv6bD8YDfi9IM6VNOJwbh9/qNd9JEZerVvyNgDfvXgEi+PL+s7LRQz+B+Z5r2s4/ZuX+/Y7jnCq/RPBsIVhpDdW1fW9wWhd8f8gUOA3g2LFve3nwMWDv8qiazUH7nK6RMRSpkIDWVhBrKQ0vkzGGIWPC7d8pb/z8v/xk/cXjn8aBfmGQ+Sc5+OrZqhDR9Dk2K3Zu4B5M/4/+ars8XzAYlMYUIDbg+QTX1LUh11RcV7zyxGEcnxrW49r76fC7gYpic+dMQSOdAR7A+k4zz7ePO3b6Anl/h+VtC2EYm/hxB7F64QDAcodB98ft6/T55vUrPH7+HN0c+AKWl2jvNPNn76K1lkUgOIPlZXGu65OWNw2Pnz6iyUvcvHmjAu3TwOD7aeZcLoZtyu3pB0Vks5robVQ6eBGZ6mzKged8EIDbd7/h8f3fAAG+//HBBoAA+gqmO1M8vqHTvSns+lQmwvKmYXzsaG8WzUgcA9zMKfl5hKNhfbOafZVUmf6k2bknvIJgYKevIPquGfR2nY6rKruMZ3Dqv3lzwv5xx44vYDzXft/fg+QWzA+A3OJELzODRL7aMzVkIJWQlLS+bQgjjW3oRzgWcrtJlCEQHRrt6BGSzyWhbPIeFKFt66nQ9wn5PKctBrDIS5wpadKfw/QdDa/Qpeu8Sm6YmhsuiNPJB1uTxQbT8AIgYEjPKPuyVZ7WNHngDEXfPKM+2ms33dzp/G33O4bBt/s2UpCw7Q7V4zTYfdNWOJY6paIHsUETPIIoAeCP7YVgCm5RUjKwKNvcRgkHyuxONyjqxlVrvzZWY2/UdDYhXV41Kfl5nEA42++Pcw056w0B2HD9mA0FVSGom1sKwnKFJPhVGLwE67JGUEyOlhq7GrNtMCg7dGhJ/eGCPsRqoNOavZHjWCB8K25kC9wT75r4c3UD6vPQjgZif7bD8XqzXS4VelcnCMXvgkTi8OWgOmKVhd6FWW76X4/obY1V9kCM3sR8gvrdDbnhRIfEfDkfCEKFZnv5ObWV6FVz5mlub9KpaeN6eIf/0PseM6f8TT+r/S7jtMmcAprVxBgS6a3Rf/JxjlE2/lonJ9brfP1TO6PL2uz15+RZTx5hrPWjGlWKYRqzI8dJpT8MSFYsDMO5byAG6xjwM4I8CLrmhcbbtq+7GlduFSbaEmXQnvHUBhEB3eozrhkBBWZ8cwPbbZnH2O3YE4OG5ickPeWP14z81857xvwgMee7baoGABKth0pJ787PfQMGrx1sLw7HjsmjMcRgHVk3X71HOQuQRhmPIRfb/TS+hBU4dQOQyr6eRgnl4wuWJQ1oy6oQy60ZwgYBNAa6sGUSFZoJo7sb4gyusjUs5jxXBzq05vTSsC4M99ZS9BnxDFit1dYMPr0xxmjY9x41bFU+E2T0siYcWDSnmM0gCFZYzZubW4XWXBatk2fOdXbo+mXBut7YGLRAcgkjL3HUGlebkq50ZjZHsf3DAJqE6AuD7tCocbEsdO8zt4RyHmNg7D2G2DPPc5KrrooiKwlMgi5I55aNqzNyOtzvdJHi1uWBOYEImv3s8SfluqTpzKp3x7qw1mt2R14YzqeWF27jejrl8mUhjK1jUDc6UpoiIixLw7aZgW5pWE4rbm+f4eZ0Ai1r1KXWdGjlDdQamijiDjcGWIM1tr4DzJaV1iEk6GjQ2tnGuS3wRJElJARr76o74jCGNASCHX0sygdMDpML4bIH09m1cReT6RBzaAs8UCTGzlBdUpnUOWpLg9AKZivlIEA73Rj/sRxXK0EwpGPpHUNa0ECzbB1HkUAf4WzQNppT12h9yA5eN7SNcf7+iE062sroo2sWraeo1OR7CzZAI1Aj8FA0hQgs99IJXlJjMEhYA6uFMBoZaoNgUIMsgDxq9qI7z8HAcrugfz+DTPrI0Hf6WLvDwNdlwqpbtq8ZnmK/aO1jVpNL7xqIM4wmRAb2XTObfM+oDoEeTnWxYAGxfwDQjZ6EPbMn17muy5RPoauY/um14bml03l0y1S0QKcIclVGoM508oxhwYKmckS0tMeymhpjdWpVrxxAZ8vuVTcQm9M1+EyI79S9qXyG65ZX5avovFPhVzC+wgXhxMej8j9b4571mjsMCZ0l9UBkbeLyW+wNgIi89/+m/L6iWrmqtiyKclHunC9LPigWNKhtIzuHoLPQsx63g5O9dpisnQT0RIdgcX219MAd485vq25MFHqs6wa+/pXW3ZFGtgEp+k/RaxOW2taZy8WjDlvHxO6PNTbRviDVIZWZgXQCskxmNWDraSnPvXxXjlsd5OP1FO2Xw4OUd5quLtnGfG6u9yNHT1sAkIW2DgTlv5vs93EBvN8me3DQhVX422eTH1fobx6Hw4fCX2q3Lh7jcypGKxaUoyx3lDGTQqqmz5HlakSORu4ZfGVGUNBQXh465UmvGE4ko2upBpt3YaCPlFFwnYR9rnS99e68UGlmWRaMLuiWEODIcznvSS+6VkaSzjQFybN02RgfWxht4SkD3YsGaVCmAjTrnlICxUT2Hbv9670rUqA7mFOrf3Kb99T0QSRiDcjbTTnugRgVJYta8kqXyY1xMtuZw0szM27Cac7YqZRkEsHAPboA0m+B8QwyPlm9947bAWDQVJzPS594X8Ro7tijML88NRB/8vjvdpyHeWUa8/zc3rzE9uk+9MJv//lBobTfvbQHaPyQH99IUS1XqE3xma37bm33THQPMDlBix6eix0t356Ht2uBJikMu/TmZg3ZM0RwPm+qypm/o9s633aXewvAZDXSy7NNNgyYjyH4ouqw3rzdggtvb09YeYnSBY68U5EvVebok5gbFhB2UTLpRjten937fnP7DCDC9viI1hYQ7aq7g7AuLdAZlmWBsCJJ2uq3J8z8fgnepeWM9jKyl8XBnj7cgZ5zYfzuo0zXANo/lrwW0ECMc3mZAHgs9OBc7NbocaNL3vBAwDNocMwzUaf6p/efoz56E81MX+zvc9F2eCZ6s2cQ9LdvBN3niJplHgi4Bf2lbPTjqgy7XfzquuKfe/jFcw/fPYgn7LyeUmEJIM2QKIcM7NuOm9vnYTs9LSv2vWOzfQS3hu284+G8JU8otPnnWp28Fch+j94hjUGL7W0B9LYAhuDqCY7eJ10/VxA3/5cd/zQO9H/48Svz/rNVcuV4JlXQ3eH0pk2LM6PEYFFRMOeSAGT12iamm0R/tSF14VNdWT9mCGmY+3F/qr4vMD3bNnAcDPkOPAjtnSqT8lGwmSNyxz32D0Cjl1heA+2dMo7946dpHyD4MrXc3xURdAC+f/58pVeqkG0l2lpkoL1tGB8G2rsWi3wAwEfBglcuhmO8LobhyvDRE+f9fmKktCp6R91jnV6/me7xS+tj20vG+PIcBAYJob3icJjKkIjgA5AR26IRdgZoq0bYARB3NSC7wgvALVJVIdMPVPZDbLWzvmH7BAh/VwVIgPayQT6TXm//C7BXJsh4gYFvummAZ4mbQ+24QfSxcyOHMeqGO+z0JSCEXBCdCbiRSvY0jV8dR98f5juAk0F+EcnhDkGneyx4AQIZlL9vbrSuu9C38j7JkRR1hLn/pbZLcItFGpZXDeOzbqJYEho385hpHhnSZ3bKIIzar+hvZHU9TGpXCDu4i4sO91Kwi/wlf3fHffbX6p2W++bxvxJqdIW3qNMwVcTIKiPGui5al7bUjztyv4v5jXPiIze9/CkOWo+nfqs05WNQHalTW1wREcHWdzReguqvPt8FQGUUPznmq6+B0D/dS3cSuyPHnxX81w1as56v1zCFYYi8IZJ9C7qjvDGuNUNEqqy+TnJ0n+p53YA43G7A+vo1kwEqHS19dJOz5G+dh7uMWe1DRs/PF7qjPut5p7xJJdlke3hzImYz32YDnvZiCWdGwjgXoTu1ocrj5F8zP8iR008HPlfGK++nw5kfrJnibLs83ES3Q0y1HA+C9uyoz9QnpBPUHbLhDLoF8KDILFH7ECbnHuyJNz5vpRWSGek/OjRwZwbxVCMf5gEVZP3OQgNVgrsjmq39nik6TFbNUs/6aQQZ5R3ciQ5HybFxMSXCHY6A1u92QzXZNUpbIzJ3Rid06tj7HlDA4Yi1tigk8JgXvhmhenHUKO/jGB8ZCDhhd3wzE5rVJm6thSNNRNSpDc/m5JnP2IZMa52bEa4taOaQbgbzp3WmKZ0yPv7Bu9LpETNqxOxZTr6+/QeiFrCtuSaLgwAEJqshzgQswFIy45tly4PIzjes68lqv3OOJxJtZUgG6lSn1kSbDhrQwgV7Sb/FCW1Eqm1uzRxtgAY+efAThaPJFh1SsfegBAaLowtYsFdZk9mUbPsRacb1IOcsWb4E5Z6RBli4/mTBdMxobYHIjr7voInHerup6L4SxnT31KcDxqzurEEGbW1otKCtLTLY1kVRA25ubnA6ndDWBbCsX5AaFDQwpGFgQWsnGCI4ZOzosoD3AVoaCBLO1GyxGa8F0KBCX882SrbexoCVg4Fmz7FnMHOMsTv5RAQcRg3JkhDOpKg42fQPDCXevvsasjljgJeGhUkDNwBgiGbll2MMAfaO0RnScm/Fi2WcVUhx17M9Fgcw571Ck/dtA/OCjc+JqLXvAAZG1/II7vZSePYi+4kCPrvZvJNYQKY7twEgsk/J6vkZzTFpviMLBptrYQfUc699oJuTQsALIGcPBDMZPby++EyVOmyGsDQciaVmKOr8MplDmVTu9+HBphrEyN7fiYKMZ0uiBUHUAdWgRmkff28QIdeYZzszk0Gn+18OxLW+Wz1ZmLLh8Puwe6F7sW5rDhaMAAtmZGFIG5BhOaVDnfzV/2jJ25HFDHPS+rz6uMDb7kFYyP0plz65zhPfgzdlJpx+L+hKIRvIWMbIaM+Q4WUMrf/pLFd5BMuU5caWzZ3r2o3wY8hsF5D8CADY+2FPVXmtuMKZc+K6aGTN1fHimR9L+Xc4TPTGmIUuUY2rFBparJs6htx8TJpzcXgGetQ/V0OCyXp994QmTbP+Fg2vRnzne4eO6HCMi/7JcL3SxZVfYxzT+jzG9RSZqWSGj+MVjTLtaKmzu8yb5tN4Rb2eKHWO49RPaCQ5CtOzZuNdZoRNDTuOF2yt+mK0S+jq1YfDmpBLtUwoYf575Zgz2FLNVrsCkHD4CDr0xIFsgw1aL9/BAI1UaQrfA6l8dZWHoEhCGrBrPGII9k7hSA/6IKjz6QIAACAASURBVE1w8sVZk2oIGtApXfcQtfRaLmWC08NxFnygyPtgi9F1xEaswaRNA0oXduQciQCWDJ7xgFbVnbbNnOh9R5cR9uUn2MDUquPn1C4pvvsePoLlTOYsje2vBpY21rrmTAY73xfcWhD8Yk8WJqxEWIiNd9n7ZYRcFBH0/gljPEOXG4zxBV77kwE8A+PeF3oZE/HJkuRh/yrHtXmqPRgf73F6+xKP7++DmnZKu3C1e/pxpnRaHp9J5a1FVP+pY9J4xbh18LPkux76UQN6HFodALxsn6+NYXvd0WeNyK+rx+gDfe+xPsZwnWnur3PAAUn01MI+jz3LTul9jTn0sD5GseP6Bwp7268e1Rk+t3U+To6AZSLGR0CTwBA74/aa0D8KmmS98c3+LrYmSAwA5/COR9sTP5NLRIJr2eLOW1qy8NhvuIz7Yh++EfACateO+5BJhi/sRe3wrlv5r0O6/z2PaZd81Edg8xm2QU0KGpuXKpOw/wDAelq0zOPoECZ8f3zEzbri4ZwO7Zqwd1U3Ca5PT1yR1+19B4+GFRK2idYymAkicITYsF1MWsN/cWKe7sY/9fEv60D/q+Oc0Js/ea4pSSTHmb1+py+dZoqBm2XXZU36EspNBFlUlAxI1C+uRl9XTH0z42zIsrfo0J5wLPgLju0uoiMxU/IRdQ2UW2NjF4yxZMnRHTq+YB0EfqPO84ePWYtjnqR7nPgtZFgdR7kD4x5NPLM34dPjdZSKgDLxO3TJGuUsL7H81kKRFxGcH88qmInA71qMyf5eM7DUMagN6x86Oj4bHOOcqezMnQ3C3GtMGxIdpEo6ICPoGyD4ml0/XNeaR6tR3b/ob/RC+2rQaADh9t0zsMPXDqWD5bUpIyLYP2osX4PWIl3faq30/UPH8pqgNRk7lpcN+CIYFvu30AvbzCgtLPQSROqsYGTd5EbP9fl0B0AgNDC+dD0vgvXVS4gA/d4yOvmbCgc8x8A3qyljWRaV3pAKQIwVAS9+f4MhwPe/fbRL9WJ3vD8X/6u3fLP18cINhXbHrRAepiJNVz9ekL3XP/czTBy1p6rzf+ITPpVCaScxg80qC/iVboboNYNF1ceHz59sY1eg8qyvHengXK3BQSPeTjux3X+Gxv9pixjPMPANL/ACgGCQZqXfmALb8BwO2tcx0C1rnaGTcUioLOsi43xjzCLMv4yYRWJSZJZTbOwchhpQI2NjxrKesJ3P5mhV+h6SCrC+WzeOzt6OvF+iotMlAoiL+Y6qfF/ZUFUiLMqBbhQPTgcyuVDbYpiuizlnkoXqFRpZ60YO7b8qIRLX1RYWvUX5UPE4+doHSoAEZ4ZqGDyvdC8d/box9brHF8PgrysWDCrn0yU+M7Ewvk3vVloD0nDm40QuaEFOAJdtwbwZqxfUOBgiilrMmilFAb+r2fFSatSXfhOi3lacsr/Kr1NRDXgwp2tYxmdEQ0vcP/E2xf/TPohoRojtGIgZqJnlUPqqm4fdf5ekF5TvR8PicbAcwutoqCS7u6akaxMl1t01dYLs92uqs8R/jaq/C2DZ4PleX1+mLzmfEf2NrU6icsN8skr6kif8IKBnFM8J4x4I7I777zUkwduVbY3PZQOTTvBQ3hDuykAgyae6AXpaw+5ERwkZEt9fJwKC84vKAygjmPJNEivGoLUQDgbmAUgzlixlg4Wox6uQjhL11hy6a4yu60KSxof9pjWE9Wjcsv4tqKicmuWtmSbGg3zXTWYqEdVrMBx/IC3qamy3gMzGoEVrUrfWwEs+u7HTiTkcRSI70+EpXXnc9g3bvmM7b1r//KzfMYAGNoOt8qEBy+DxIRd3nGeGt2YqM5bVsuLbgmVdNBvBxqQxwKyw9cuy5NoUHWtqS248yWkqaS/a79Ye6wuJWOZVCa6VpB41Mmkmg9e8jdstyAFQB2kyALL1mzqgerU8MEjnpsXlNCselfwBQNx5VPmYtpDcyM32ZIE6OcV6RGSCwQKgABA1MA0Mi0rlMK5mkEQ4pwCDr6dYa15PEVHrl9SY2xa0dbHMJ0Cg2dbLzQnL7Qm8LJolzLs6EoVAaLh5fotz37CI7V9YjeuDBbJ37I1trIY2ZvSpHIWYMxLoADFoaSrTaYAx0Hfj+RYUI0ygwYqQoF5I5UBl7+bBOa6HZDas8xQJw5hANKO7KU+XmMuUJ4HOIDZ3IuDlpL8KDPVlQNYVgz3wRjN8eLH68dDalV6/lV1BqTWxRCHLe1vQ9g0rA3LuBlO4YfRha96CU7yt5pTWNe/ZD8poGKQQ78sKcEPfNqv7Cq2VamA9ZAg44k5NJtACnPiETc44f99BBJzP3xV+9yw6Zq3WEUcJAlLjLJPXpN1jvbkclaBpsoxo7dvYPJt/mDNUg164WaCRLznAeLy4GmFJhRKIPh3Dyqgp8kfAixN0P8e6Fjx7JLID7TrAaWdXmvaOGl/y9jsHWh0udwyFn4cGKrjKEBToTj1KKZoKhenS9m6xEgRK0xS0AjbXm407e/aq6xBGv81lEonKHWqxJmBj6E6q0Dn9fmHtpZRMXePR0VoinRxzAAK6nhz1JPZKrojE+hcETB/UEBmcP5zE2uZJbUv1AtalhGEuf0FQa3WHOp76mJDEFKTANAxR/jg86BsenEQWeIcyXkX3N2eZz4sj47lfmtmDrpIXBaM6OP3g7MB10tJln3IMRGCb088xeBYigdriY+7Tqvqpl3Sy9Q5zahAl2gDL4eX2jikb/Dgl5gAuk+X04PLIaT1lVXZWxiHw+Djf9pFUaULhAi7wjXeHBhBBQtFCmzsNwMo1ICVIJCe3vlvK74g2z5BVVGhm7sI0PbhylHnPU2rtGszpwIaTGlmVkMunERzZzlIEiEFkdMhO9/q05qoVdOhaY7AV95Wto5GqPluXkrKJZLZk8ykpS4lIa5GPoWVfBOhjj6myScyOk7482JuNlotGIg1oYo0uigAjDxq123MuxQLRuvHgofeez2ectw1936MeugfV/vw40nzSM6EELrGiWHm2uZZVUed5DSxl1gAtbavgZHrrCkU6GqRzv0KHuY2BsyiCku9bxHTDgc1kTu5tlE2TOtGNJofkPCHKtl1bzQh+9WccncfjRigcjv/1IyRGyhKJ09igTs1NgO39fZCZX/L9k9rHu51zxMXTxfrObysQAeA+z8vrl+qM/axJTNvRcHAYzX16ctK8WN176R0SM6HybpCKxVp6bNs7Go/YP+3bbjYbhfsfxpf7yExxlzdLYyzriodvD+E36K7r+ncLyFg90100OLPFfkSv2XpXOckqM88PD4hgZ9tbk8mBOqRMyo2W1uBUC3DYpVwD8lt2NpRRKfqiPwuXx43v+1w0Anj+9g6ekb//8QUkwPL2DsQNZ3yaWK7P2s1/vIYQ4fT7a9DfPuHR1OxHmgN+WLIdHcBXulxHBHVs39lNnkX+TNRezZhroZ/smT4iNUnMnz2gqAY7xO4Vy1LP9eHv/msr7/KuOj7+7GM+5NOP80DGas8vMlScZw8QK/0OcUxAlUyudpDxtMZsActaCmvrIwK19hKBeGGLPdAYSG0uIKVPPcxOLWqHJCJFrRNt98KMndwL5ftOW8G2DFQnnUftr8xF6qr/ese/ngPddWhfyE8Ihmv3+Qc1gh6EJs0LuH4+PmSqR1p+ExjUEJyoBWMoLOKk/yKV7/1TPzyhCE4qnb3ax2t9vqIA/4jNyOHpV75Daiar6ZXQhXaSl1jeLTj/saNbTfF6xHiKbv7GJ4DfAMsbhuA1+gdBzT4XQDdCJtgA3Rv6PqdOt29ymdkYkkJ3qVNDXNsEBNgxQnz7iLS3jB51Qi62M/b967WTl8cPOOxx5JkuZ6TRHQx4ECwEeu0bXIcG1Ps06wXpeHhJGPc+VglpJdixf7ZIVgLWVwR6RRifXWGn2LhUFqjGRz8hkdmS3VRDhzNsh54SivxkbYM5FAdrf0KAAGaIm50vRIgMTB+f6Z3FKOV/fZ0BCKPNgOBMwInyt4ttXcEbVyNPGkTCQUI+Hs9DZLtZuR5kClXwJClzLHc4vV7sLs84USFb4dimvkpG402KqJ1bysXJowiQZwAeABAYL0KoFoACpXnkOj49b3gs5M24geBRfyfCQhSQ+to2mRRGEjdwuyBFjIUrgxQ32OqzWlWV/66nE87nxzBIVsNNbfs07le+XzgRyxP+jICmwzdX0LM11xpAeV4uf84WGo2bMSoy5/7EIdYqzyGrhsQf34PgiTrW87rw+tvTUaDt7Cr7dvld4GgTTtW/MOoxrE/PXQrOqwM7XRrGP1AN9sx5CaMoRQYjmfAPBxYQ8zmKoqqn58h/hx6OppYu1b8hS2O9exYZFGav9lZSPyiPjedc0v4hQxQ5DlNAA813Tcdh/Gn6kHNZgw6mNl99cuHSD8UQDwLdmhv8ImiCwJi3BGnM9u9igV42igc9DoBmrx+O5EWlxb5hfRDQTUKq++a4GoXBwQ30GSUJOl8iE7kmzZKv/iizor+6DLCtigkQIQonyjQD0/t8/IbCR7MV5rDujcEg1nrl+96xnzecV4egA7Ztx7ZtUSdRfXzdshB7QEHG27iZfuDZ5QqTvixes9Dsva47SP2rn5W3+8BROD49y7ctzaC2GWtxnkcyNwSQoUglMiBdg1G6G1Jteve+RwBA39UZ2r32OTN4jAiI+//Ye/fuNo4lT/AXkVUARYmSbE/v7tn9/p9tzplu25JIUSRQGbF/xCMjC4Asu327b8903SsTQL0yIyPj/TBneeWmxeniVh4GYaGG43JIJ3pkoafjkjkdeXCaEoq1Of4wnJTs2TpsjteNrAOoEkYpc1/LAB9j8Ayk3LLbiEoQ7XB/XDpcLLs7dk/gv2WJqmeIipdYtii9OB+P9rTRfJHvSeV02Br6J6Et23/spQwAhgtLXGi1CuCGLWK2gAPpoO4yhjs+IlvNYCruGDMDdpQcdkXAnku+rxdGOyxYjkes62KtS8hwbVkOaKuXbm8MEnPgR3FKBuHu7RvIV0mZL3jAtnWTN7sb9EK2SSfkgHa2IekCNE55sbGmXF7CDJ0/mHMAMIclCFlG2zJodWpZA6UM8EvRWxVE5oi3+rTmXFHHq8gUbRQcnDzoo5lWErRTBbIeIdwtQ0IVUQ0i4OKLZW0NqEFL3cgIRlykYXOc0NPJ2h9sC15NcC7lXy0jKTLzogoWNJylpd9qW8BtAYFwFqCfz1Omqzp+knrAjToOdd8sAOQkFmTTaHhbIjg3dRAt7WNsf3V4UI+Ewd+4sqNh8hEHje1nJm+lZHJE76ZjdFFvRTPzHyXL9LOWO5qZ20YX3Cm+WCUPc5IbrBsxsNga18oX+a/wV9t7jsBBuwoRygoIMuQrW1hJGarCCZF97qhh/n4BqNkeRpV/qxRTtE4nJ0Gh53+Gl0GZzMETErLTR8ZoIxFKdDiDgz2rgtCt5H/8qLZYlMiDDLafR1uc/p4gENVhwGKG//OWMAjSN90/MfZBoWP+IzhMk6ykV91EgCIz+VorQcjbfUTpd6cxJqZcg+Q0jJz4oN+jhHsEVKRjnfy9TABmXANFIDb5OoWcE6s9Xk5hjK5Bnbr/MPbfcHiqxXGpPzF623PR3MskFQQSN1zPJ5wWDzmtyp/XZRugBi3GULWcy4cHHpQLLsRIezrCVnn1qv1NAY/8TJfXlWfpjd8vfGVAbPzg3AicwO7ayaoz4fi1h14ZPxyVdGSoErSUVB6VJrLEemyo8qYWNkQfM7Pza7agSWWHL8EqzmwdQoIGoxfdKziOUnyebeqgMLLi+8kNVlr2d6KvTlObjuogix0YAZvNafUIvLVALRHvSQursnbuZ2weHBu06rxtOG9nbCV48nJzXwB/+rP/Oap3RIBjI0Jjzyz3VklLK/+8H3XIumGOPbg9YXFcHeqCehKHAlvH2UvQW+CvySkxlK6w4N+Aia/zURln1wEmZ23aHut+c/oTPC7XqfD4AoAiXV0crzsP0PeCSn70eKW5mm28m2HOyppJfu351+jJ9VobyOCSkIIYwPb5EcuHh788fmbC3It+OOntocZnl2iVVMZZK1Bu3VrY7OJ3ZnjD9x+QbbrCwS6Vd9KYTQSPadpzjOizsutBA0c6TEZszXPnGyfZAcY+J4efiwGuLu0qwmCG5xWum0Pdr+GqhBVuB8ZwSJ9+e8Lh5wcwmUy9fiC8fnrC8af3UAybb6xxVnNyXaP98gD+/REd5qA/7ZzowNyCti5B/S40MuDzfqeJgX97XIrrMlcB1oxzf3wv8/yv4OffdSRdSDJ7ba0LD3TgEI3Wfae+eaD0koJQWxqOdETvG4gJh8OKp2+vyRMBS9bdSkawrW/IhCG3BC6HRFFpmdYbTf+WDmizal4wH8BGhE4hLWq2O6Jqu/4ub/ke4G7j+3+F4z/dgU5XpbXvXB9/g7nsOVuJ4Bm/6/yZUHpehXI2REM4QYZnCYYwHsKYvaaioj36rYbQi7xWVSFu+IkLTW+zHnAa0chqY+8UzLu6LQVRzI5q6G6deISETMeexCEViis1TexwBUQdxiDgzn24kWMShHD9sAAwA+bGVvL6G9t9h3iXD7URgQVYfm74+m+/4/DTe3M8fOzQz+8AfXTYGAla6D06vnjwpy+2G/XMyejZ5z73obxYtHH/NCLJzbFjDHvDI1jf2X0SAvpgLmHrEUeuRStYhkQTYNuZFCuprKsDgHD34SMARf/UUxCNc4pnKN6CPPvbYEeZsa+bM24d5w6N0Ykg7z2rBYTTpzMIikYmmBw+LBYFRpYdsFCI6mYUO9OT4aMbzu7evwcRY3sSNCJssD47LO/A7xn9aQOBLOP9A+P0eMKorKBoYWwSKyneyJz4imK0UjPWKgRte4czPYHlHsvPzZmKMQeBMdOuIxuzlqsBgFWtHFTHIOYLFC9VYQ3pCkBT9mi/qCsZDhtnLhmxajew79V4Gms4QezZ4XyLnpSLZ6Iw3mJ9v0IezQi6fjRBqncBZfYx3KAKMO4g+g2x+SJCN/Aq1k6IfcwVx04gHJFlQxUQPGPhd1C6B/AMwh2ausuVjH6dn93550YnUz8aDnQH5bP1yYX12lVRkLaC0GYQYlAaZeB9fRUAJHpwAiDO7J2uFuW2rge01rBtoyQNMLIfL3qr7CW36dQK8VjbvcIhKQbTfP6C7dDFzwRk9mH0GL6gzNEzKZkRFaPQEJ+YGVu3TkdG/02yDPo1NO+dO9wJaAihKZKRjYQpqh64oFTYwXyM5wORAV7OFd5FMOWcib01hvV2CjEsBO8Y6dYFS6Ox9mU8kVlEMjt5LXsusnx3jqALUUqLgIp5ggmmmpM0jub0FPUf5qhnaG7fhJMZ3QKmxeHpMsTUVk3VK88owtCRfSF9r8XGDD6ioV3EELxEfo9SgJorOs2Hxg2e2aa733H1em9HPME0/hs4HHtrrEXhjonfkpfWvyjfHSsQ4uWQh4D1vo3Ahpi+SJY/HRlKg28HAcz1TTnOs6ZeAdzZPfKs4PvRE1otPTBp6MyfRxa1qJpdX8V6QSHKE3I6cFBkEFGFNknjTMKKhnw5NqFCEtdDW3G8d0KuqEbqskrudRi0xHCxsVVQCJyzHrqaxmorg+7OEwDbtuHbt2/Yes++4ukg9/ut57TgdDrjfD5bdosM3Bc9Aypo1LC0Beu6ADhgWVq+19iAZ8EFXMj3p5M51W4yBQmI3GG+Ll763DNYItudDeeiFJ85AdQzqzdzpG8ySlUqvPSjl7E8d8hmCMeeBY1uEdwaGaUUDkSTbg3HjOd1VlAH1DNHsyd78zGGA48L3RZBVx0VV3SsZd86mIB1acDhYMNxY604LY9e6s37uAMWmNBWcy5bf7+x2ywAwXplb2eDSWbcOQ7DnR1Q742oguJtgIKg5IWg1YR4sY1o+rh0y/wB2X1EIGpAC3pgcBOXWYXUg0HCoGlwZvXsbQr+5xkqXtqb3AJFrWFxGanryR3lVlbOnOgK6Vvui94FbWlWvtp5jpXFJnBrABZoW8DHI473d1gPR5AbfY0MM3hhWzffj8IM0IKFgPP5FcvhgKMKttM3y3xkw+3wHy3M3gOULLADmnsqnEkdOvoziuCwWpZ29DXt1H1t1R2li8FFS4Zn0A1X0iY+A0p51ewoRQYhskpIztu0W8CMZd23hJ9Ih27ixnwP9iACyLLt2nJ2x76Vue998/U5A72DwIbfd0f0yNR2GLVlcaMpYWkLhDas64plOZv+wNZCoPEBtDTPFGw4Hles6xFtMTxHOL7JdBegQYSgZzO2b+czNndIa/ZVNf1Duq9B37C9niG9o3tARjsy0AX9tDnuOO/g2lfd+ED37GurVGDOc1EzhC3LYuugBg/bJJYxaKWJ7XncGA1tpOOQIvpzBt1lzy7KtWjGt0St2kHzdbJAAqe1iwUULK04MkIZ98N6ioY8GXIYwKJI6cd1Nqv2MfqvSwQLwDOAXYPq3TPwPUtQIUBz3lpE2hFs7RVJPKBa3H6QXiowuLvDy8vrW1S2s9DQ4ZvmXgTXME4yvstOV2zphvzm604OZ6oZyS4w1JLycN1xZHQacYsgL5MZqnzpcg2t2E5n9/eOIEr4js1X+l8mtxvBA7fJ3ktk2UDi+ryc7TExRAabXMjiZcQ93JCc3mfpY0uJUG4p9aOMKRxLKTdpXTyjBVHlKWxkkfmLGqiRwWB+e1aiSHT31w55VCMCKewFwUDUNbpQ3YeQPHiMFKk5hioakIGGfs+GCKF/mxgwxtadpo65zRnpRIReW43tgo+v9wZ1nux7RWsmLeLxPARmmKwEghnXY07lnaGPIGTP0JPUeCyJAUGiwos/I8v/x3tQLaBFSk7HuY/LsSLUx5pTOs97BPrl6RirGL1RvyZsQxkcAsOTBWwJSSErOI8zh5+6rcaqoMDlOQJhXRhiZAdtYZdjzbbQmJ0nzrmF3BhmGuleHc9kwm/ftgHW2O4a8qCvD+AOEVhlSiLILuOUUk9H0qGKTwFLi/HxYFKnY7IZX9k2C3jNylLOAwReDcTflY5n1brlJ7y6dUwj8psi/KTB9RoFiBVrY6yr6QLGWjqMEzNWBg5rQ1T96KLGj1UhvUPUAsU6kQc7WDWW83aGuF5y3ozPbI5HoopN1Zd7877X3atxWWb6AsbmOlUGHwiQHvwgJYXOlcle/F758ASaq/s78GT2QaSN8IcgX2iK/+X6uf6IQhZ9qzaYfN+A3RjmIYRDdfTPtqaAArJS8AD650e8eWj49ihY6LLMNzB+y4Axf2n0BLdtbXZGs+d6NrtIwrVxg0KxbRsO6wpmxul0BlTRXI85Y8i3gMvACDuU4ng8Aqo4nzaXQ7rpGx7RHXZHA1pwNnfQq2J1+5Yo4dBWS8iLPdQVjQnoPcnzsjTQ1nEW118iIKQ147tsOCBZJgrT/qtrETbvpOMwOUZgTvOz013TrzyrW42+CVnpfv39EYeP5tdYl/d4weehL+hY/6B8p3/9gvYz4XD8GcSMFzyCAZx2gUhgW+NNzTn+1veP4NKpvQZbVauJGng7wuUndp3Ox88EPMhw9AsUh18+gIjw+uunAhXgTjT7pY+j8pmZst4idzuuZcH05UXliVefQ7tzaUqMyggOe9NxBx/t0j1IvkG8fRATQc4daCEfKXhZQbw4/w+dTr0tnL20O2oxyDsQBGWrMgWlzEAUa6Fg9AyGpZh7F8i2QckqQaB3LEQ4MGdge0QkjyogzodHnqfB4Qa928PVhrgPO/gOsK898wYt/o84/tMd6H90JOxuwIj2WH5xnQtlU7SEjnsJKTqmWJP0jgsjHQTo2lD20WIAwB/C5XxFuIT6Zvvqz/YtooqXYtifs6bi7viv3gDQ97Z+3PsdrNxPkuofEyhYH3JeW5TvxtioJ4yeFccCgy4dDQ9mmMvGF7ZGqecqwB8Z25fdAEBgeYflp4bof2fRYCacbp98c0Mu4LJ+bGhM6L/ar0yE/mUWVqiMM28vBHmfFbiH4B7S9fvx/UdT0HUIafHkBusZfni/plOBnCjSQmaM9lLK8c7mxFlVoU9OFKmnkWfkkTjxZkIo/OGkj+yAfCchS0VF6c5G7sggAp40QcLel70RZQSegj3DAxnhW0MMmEzIzXJBSlh+XrDggwkaoZQRgegtiJ7xRxm6e1RVKE6YfpiviNJsRXCenJn+fcqopoD9Xajhvl+/IWK6kgWQZa2H484EHqMt4RTaHtXLyFrmiQl0LwUj/FETrjhWCE3rOyoIMBRvMntVCdjw7D3d3wBOXyJqjNWigtHCeOQKNwiCVzRarDeiAupl4KJUOmHNfdHcktVrqTJVZBRcUT4Uw2CgauWEpY/MFXOeXyf0tyhWpdv7Zf+zbLU+xYbtzokrClTcsHdsBz+J/0ap3d4FS1szayvHnIa4Sj9pfkkdXD5/XBtGyIEtV4Z6aw66+6AYWbBQnyCVc+Pa+O+6XIttvsUprwxB56yHvbB97TfaCU0EMyzv3zytDTu+Aq5YAXDj8Pwec74Mgy/lWQuimnldDQ2oWXjqz6dyRV2hDPByI9IwZv3xkQE49b27owr2NyvM0e5DZIUFY0jUDIUg9tz8CNo9Tne/13HHFdm+guZ1i6Ey5sAKZ3mlDJXTwLvgZ4R27/QxSl+OQfurxroDAB0D/wj6oqA7yu2o5BmZ2VLF+Fotgxp04gKeZZ/YIR6kNvhERkH5HEdhlMAV8v2OUvWlwCsM/E5Xw1jBXNgb4M51c5Rv24bmPcrNsNjT+RLyRFfL1o5evlGiXPy3oEEZkU/IUpMhr6oO/I6VJXcukMu15iCOrPPVyz6O1gqZIaoRQDSwQ7y0o4hlo1tpPsu8jr7u0s2Rb7AgD6EcPEkBRI9f8qy5kJfiHhL1DNrCx9QygSIq3/a4lwt298hwQLj8xGQOe39xYzKncVuwcMO2WEYmejhbeWSMBCx12AElHQUdoOYGIy6wAIgUDdaPUlFwwgnDUEfIaX6YSo3QB7QVCktaogAAIABJREFUtaopJc7aUo/s8HgW09hDmYHhwQpRtjHZTRQN8BdpOJ+al5cG+1oP/DdHGUGFPcOy7CP/l2MnWABqs6AaXhi8rFiOh3TOqvO8QX81rVOH1Rzom26ACrgzsDULEGzxWs2ssUbNXVOSRjXR0Ts6WKrttQ4sDa2tTr+ctrJObbZMPoOXfB8OeyKrHiDhFAqaEzTB4RplITMAVwv9VoDZgzV4sYe7gRuobhX/y2YUJzK6ALE5badXqM+RPHWPTzR6RZLhiO3pDUwNEN+jvteZCMvSsB4OmYHevFXCsq44HsY4zVncXKcynOyblV8fDnKxQIOzj109IFkJcIO70QgFpIOaUQBJ2q0ZWMwYOG8lzq3iFjtOZza6WiZd8AxJBHenN7rBh5rpqWVnmVyoSeuTK3pgDys5fY9nqQd3WeBGBNcTzHHEHqwQwUiDxSu6qrcFclzwzGELVBp1jWxtBOiSmUtdFaLmPJcec7AKID1KagffDbgEXgyji9PZKCEf+OrnBNAIYoz6plCkyX9sj4vv0f4kYUjOl5ynZ8ZaeutstjbGOasmebKOUNykxy7qBekxFmpO5AtxjIDl0LCdNjc2RgKHyyFFpqb8O+CXD/HvGeA5EfbYqQohBtPgfaGhRmav/cb5eQJllYdD//Uxse9j5uGcyGotQb/8t3ByFBEneXtid6nOGMAlLUHBPhQLvpeEWWYWpowVa+MzyoUZcrA6PyLA23rolKRN4Sx2I7bJ5vnYWUcJvL4qrV/7rf7utEVGkIL9zAMeCSKHX8UB3x+Y5g/X/QkVFkicdjzKeuGD3+WYko75/AdLd7xDAcJ+jnrlc/ltp2MNDjXjXqgcQePSdJX7lQEWkIw9DZfpyL1FDICWZmsccpLTG0EEclKkBiSd5dY80DWGrNk2w4yTHrzicO/qTmVy+QGXeDH+xtxpIoGgISFHJZjsge401PiZOdBfvUUlgMlpLjqc6NFaI+zJKQuhgPsWita1qHgUf503MYxftJD7dfAvgrptEBhqtgUBqjv3yWV7cfuhKMDilbLCgd5jTsF34EFr6sF7MgIF1NrVMIAjGC85V3KGUA/NMVVY3HKqBzR+DHC3bTB/9ngha1kZaD5tv3pQWVs1R2cnd0QOFmcyqN8S4R2RcR6ltidcAUB0jxVf0aGlMuZ3jmRRiqy6UwCykcmEGyzpICuUwMqoXzyO2JtC0TCVlXdVcESiQnb00DEei6N33kcjgLfOl4jQFpMvTKfmHLrEs7tagKFXVlCJtjU61iFeOo1PL1HH/RaEYUdInu7wDhGBQLlG4SMBSnCF/6cD2LYvWBU4//o559bUrnVxPR3xxgt78uDvtSPoNHqcXzu+MPBBItDGrl904O7+VkEkKiaEAnq5Nn//ce2pNyb0J44Yc9qVKPCvyBLOaywgPfQnhQUmb4AHKiecyjqol1A3POLB26uwikp9FEk4QsbxhbCnjDoBb1XxDc03SvcoVqPpzfXahSMJTs2Jzoat047V8Z6b9sYA1sVeuH7pPwYH/r7jP82Bnpnd/55n1C96Y9FurEAlQLefGeakQOkirO7GXksj25l3F46XdBSQKQPmwL0H4wk1r3GY26lk2ut0dvfk/chzrMPZEhuMZphcQ+bd8UIWeXRxqKJ/EQievOfF4BhH379v4x2wqK1NBcsvADXf/Ax0/YrGD4ACnZ7AeIvT42cQvUXHV1gQ+zu0n9hKWCsyK6x3BWB9h9afG14+fULDQ0YEhxGT2KJwSa33t5X+EY9sn5W6gNsoBwzv0cHpXPqj45JXGgldlgOWXxb0vuDl0ydX5whvPv6Exg1bj641JmhUw2EuMyGNpNsni1DOKDYCVL8B9A4EwvnLCUTA8cGN3a5AtI+m/G6P9uhGd2aQwygFZcvzzp7vGdT06IL9k0F2YetVQw+GYafHt1B5BuENFIJNn41hB0x8MtwB0rfov5tRfvlpQWNGFxOuj7+sOP/6gDM9gn0fCkbPc8D6nHsNAmyw0u1TSbgb6xIZAAP196s1drygg9HQHhh4dEdCrA/eYn2/4OXz54Irb0AAOjrokXB4WIFisDw9fSmCApXSOmN/Sp41ZSTmaKu3pz13YADLO2eAIVF9eTf2vgKMJQ34rIQevThxBPTkaz76vqYRSM3QQmb6MzpCG5hWG5MTqAYAnkUWZYyS6pBFVffzZkZTRN9oN4pMYmZE8NlEwrm5kxNy7ezvqXyzi4agv8MEuvx9jyuE2P+cDrekI+G4VPseGZ5ce3zCDZEErOuK0+k0NJ8y/uGgpDS0VofTgCCVslL234ETdrA6HaN41cyrREemGin2ABxXExIPAGDxzMYoZR50NUu5tQgSg8HKp5SKexj8irPPHuROy8qX4nrAszvGTgn4XguWiPUJm9mgmDrg7pPNXnIJIgIVY1JcLa4YZanKEOhTcKVRUrV3W0qZI0SByBwac8419zSa8zb3Ph9jvfxWXeZ75f/W3XrlfD0GOf2O8KS3zk/y+XSP/b4hDN6xpyKKPPCrPkN3nxUj4GEU3I7rYmeol4cH6I1nkqAE6kBLxhfAd75BaqBOaOZXyr6XF37nuJQPY2x5o9osiiW5XL+jcdP9dkYnfDKzh9GMss9pfAilXkS9h5w5nS0b93XgsRLWdcXheECUX12a9XSmDhANJxozg8QyBhbPkGktMh8JUU4ZiH3vezbLusIN72v+Zs589ow923dQzUoM6vskpumJhOlYl8gk9woO0RM92sHAM8tZxDNVxWkPuyNjYEcovNM60KBQIh1nz/CO7Luz93pcPHvXsnzZKyDwTBfV6Uo4qjI1yPE+0UGTj0aGiIri3LtlDbth0ZxLJgPzttnYmRHquvXSjDwcwgiM8l1Ghe4mYxhmtNHfzP+mkTr4op1Luhh3atFffL22Dlh+izkl1emuOdd8R7coO82e1UQAdXRZ0F83KJvjJNaImd3BRSm/BDAZzWDjaTnkfaFB1pOT1uZ7AcgSrMkIxeVEG6NVBnAKVnis9A4LOGruFA+6or7YLnupZZIzE2STUf3MjfWhNmncGvAHQHqyvRdGjZi7WylGBYxEHcwl5iXxV736UujebVlA3bPEzO3rAZOmXyQ8o4pHgJcbsChYBK01y0pvLWUikGeLbR0bOlR7ypQiRoMaM0jE20WcwQvQVsbKB2xyHo6E1SpUrLyg8YplWbEszdpQcJgUAd2MTnSnC9umUCXoi+GLxP5azPiOs+E3K6BNkZ5w9izAKEOdoapIBzWrevEGhnLzcqoKEEO7gBuB3T1jOzFkJyS+qtsAts0y+OW84SwdUE34aGM0sDuV7R9Hig+8qpvTXM62EBbYnJ+9KgJQ8IJotAAIfILzDJ83MAKyYltYcJW1TxHP6EznuTsDxTO9RlWvCIAKM/iQKZTYSyuT459PM/hG/BNkawYKOdQr/Figja0tqXrLjdhUNEQXl/VSdkPhl0n/i0Ey2FdszOQLLvfFWJ2OGt+b21lUOYSCqrAOf07Iv8VJnc630I1yzzuldmKhIklrwkkx5CanQyPlFXmW2H8fXW8LFR9Hih677KCgc1quqbCYTtDuM+ab6vdw0Aa8ojqMX0JBz2I5nFha8YMknMh0YcKoZuKykI1RS/UoGiPwKY1rqTjNNYc45kuJ2/O0Lq8d3wddnxwEiZs6BhHzhvPkenEAQQPmQDZPzffF6vr+yjgd478DN2JC8cJ43m7trtq9Zpl3PKeMc//8jBqFB3PYHDhQSodtpufaYsgeKHo4UW5SInMwaQZxmtylbI7b0OezfIG36KgzUAWieoV2zWDRlGx0DCeWoHt1mWVtXm7c9lIG5FF9eAFnUhPDpXCeNw+Iit7OKjaOTaz/rboTQ+EOdA0nupSMdM2y5vkXsxV7tlXfWEKKfRZ4GDhn32MP1nPpRHI5PvvHi/U1527toUQsmzzoyxl2rXrrJTrbXHuO3XVwtfduGiQubGhhqze4HRQ4EQqUr+HvlblfAci13/5Ir/47jkPZQk3fgfCEM431yTXUsaskeKF/DwdPOkv9++KfhwOIsKrilQgdI4Nd9QkMxaKW8APaOdEdOOJy0grrGw6X9yLhSDerWEls7b+ObXUbC6H7/qwgXRpDRHCSStfmdayJF1YFKPRBTbtc90z4dM777d11qNWrIY12fiY79W7vjUz6u4PpI+fzZs5nAtbjASevtKYcWbmScrCmsmrywcjaRVpGQsc7wDLJu85zXGJdYdVYcx+H+aSA5/XTVzCA82dbp+XDOyy/P4EVOLE5s1UNRwSA/Kbo/2L+g/tfHtDlCfJJ8UYJ30hxzEA2Q7Jg/QQTsd7o8J9l0FHBndK5yaqB4DIA46uPfaM5GIB+M8fEtUzmSlYvT3pQ2rVNe+3ykIIiIK3YpWLs8c76nXbXRAWV/K0SW6psTF01NJl4dR305XTGAYT17t6nYTR1WVf0bcuWBCnGEaAQqFCRUcoYqPwr/FvhFa5cIWLYGjQ13dxC1kdlU4XZuDsNEc0eZLyxBt3kdPX6ulXYXDt/S0L8Zz7+6TPQ98cE9yLv3brme5ttvwlo93leyO8v660NdiszDBLq5bP/Zk8YZTFm6bNGAl8M/g+PSZJDEbvHs/4Aa/evGxnOuPr3RJaBHsf6/j2i1+JwStgWPf70AQBw/tRB9BZdvxrzf79g+ww0fof1g2WdkzsJmbyMKiSVGW4tBxBl8EICJgXkd8+Wgjt06TkRKAXatBLN3xe8hZJi06fvwuXWkf41Ec/sXXD/088Q9XJ+bpiL7DHTFTQJoHSFPgvaB3b51MiWuiDbHhrkaUTMjejcgs+PKIrujeMpxuuq23t32UYpT8YUJUVkGSZ4JtA7z8zje8uWAIE8WsrKmQ5Ei/s7Pfk6vTfDtCuuGmXqMAh0PUy41Otzodtf93v81pFKFb4BeOtzJrT3ZiiUJy+pQoQ3D+9x+vrF/df2VAZPHCci0MbzqfzXrlBXoM02SmhuIDVmOUY8OWbwAsWdKUVPguXBBN2oqCQqOQcAaZhXf45q2o+Nz8KNa4XWEODZ6fCygoCig8kylgYlMMeE7oQJhRnbmAld3KQoBr9hbN/D/zZB2uOEdQaKwJMfZ7/X1j/hUJTYgMu+BKYJRr5mRUqKQBRSQu89e3RqzWL5g3Hp9O0Hj+8wO8r/DJqY9yD03pnHREWC3LOhGCDwdDxL67PreAYVLvLkMHLkOy80Ui3rOxwyM2QimIyG8l7WaLpf7W86+Ha9zWt1mH0gdGTAVoNsZKkACm5uOOfg0/P9FAD2v5p3lvMz0KZvhEuarYBL0T8upfwAm/+bj6qeA3QX6z7j1dXDaenIiMWl8IfiYr4Llq3F8Lmj9/F+AuTFf38zAmKS9uam2CkG5c1xssQMXpvCxbmZZxWNhCJ3GQmb2CsjU855shvOdqZtRNWAeL7CnL7YkLIEb82yB0XAZNnfEXUfJeujHUI9mMkikxtjbUuWMl+y1HhLR3oYQSOoBRDPkrVnNjdaxN+4p3dzIHWHXe/xaYyG4YGFAX/nIcNhqOXfBJwcXzyPCmoNdFTPUnQ/jJqcKkLYuoBP58z+Y4f30lr2Q2+RNavNHPfN5R+Qz8d4e1bAoDEnoZkuWmlpG2tngmr3cvWaDiubyAbAZMi2elaulyDlEgRWs/ImJAUhFOxhyKpU23BLHWgjMGAEFhno1A2+M07GtW6hjmnbTvD9Q9UJ6PAkZ1rtvALLyTIl/AYFZZnX8OeUt4IagdFApOBlsfLkXhI8DNb5cg2jFMGcoGqVCQouHI+M8+sYbwSkEUcILAE8jLyZBgMM30PUXVfNjF5RwSK+88mckwlAVZfNLKzS+ByltXTkzo31CgcQXL+qFdSsl2TIKJ4R31BaJZhe0aVj27oFg4iaQVRhpZDT+ehBIu0AMEO2U8mSsLFvfbNrPViaYf1ZaRNz7MINjk63iRjkJc8ZHqjj2Q+LB+3Yd3OeW3UCM4R2DQMmACUrof8682JVgW6eIS0KWhyHBWjqQYpie548s50czyYHKjsWN7IMdQJIvLQ0j/YTkChzThg9YqgUZhr4VJ16jWj0MW8NLeh6lcn9O5M5kRs1z9oPGj72nQ4ATDJHOqEKsySh0tmh0Fholiq14FdzcFhlCTPCZlUMFUjSsT7RYybjgCZbC9QrWAU2Z1dcAtK8XGjWcBjGeLVEVflmS8ar4zd/5uCR7kgtvIXKG6p0EbqPZcUH7XNdL28edHIy0yQcvCUCM4Q9yyf66owFsn/OmCgyjlwWiCw3BGh0vj31rqDJsYZjxYe+5XO/7QlymhgOysvkwDLmely/8PItgSv+HwVGyxPHl7BxhOOh8vv8O+at+cBBG8er6vmCK4FOOcAL5jh9j/UUxeDBenn9Hqx1LcaUdcw9rnNiQB7MlmNOR+bFQ+e5FZsRQhYOnkQRrDJodIKivGsvR6cz/sKWeQt34NfXLzMmGh8rP9Zl8XUJI/4++z71Ryp0EARaOGFqshYBYlnPNjUZmX8BJy2vj+GEZ7KAOM7P+zVAbj9YS7o+6FXVzyYcGXybCOlo5Nb8n/NjrzgiXk46W784/ocDvbsdVIrDOcPmqnz2I0ci4pVzRbFyapJ7dQS0RCsTG3PQZtM5ulVI6gKOKlFOj7cIgt06ZPMgVZGU7TqNfdN12I46Cm/BDscmaP/XO4KS6pW/9R/TYHuKkWVcUbWyjQqPkEp4ukrR4VaXxzoe+y0Lx+6eHRZe7M4NFlkrlwxSTMCoPpk15f/KqrleTEY/k/WnhKw+55H9XvXxqrtGNZ4AYqK+0yUV08+WZvbOhRe8bj1Lx4f9PvWmCM7TGT4J2wcCP1XbrP09wNT3cDzT/t6y9oTQWeP+r16JwBzYkUEeIIl7iDxGFvO6nUhxVzyde3wiIFvcBh49MnCv9p5ld19UO9iR/Ol5ktfaGvGN677Hpf/6fv/3U4oL/kw0TwAwfEoh0z70PlqXUgT6Y6zV1nsCUWgXDlVki2vHhbO6ADCqRBsvNdw2H4DpEYDhTTrUdWidRBiyMWa8vQXJa/T52vf/Ksd/mAP9Qvj6T4IU3fj8x3eE8KtJiOPXO3WhDgi2U+LW/boimELJ+wn689SFnnJL4viV/fdnRh1jzEjCC8b0B6ismIioXeHOtC/m0D1/JrzxAR/9thMBr2RRSgDw2+MXHKF49/NH22S+EVtr3l/NjYz6BNZ3aO8t42KlB7QPDa1RKWtIkwE5snqYGCRvjcl7hnX/ZPf0370krz5D8QDBo88kHhmGXIx+pzFfAjp9dcb0/ZXYQ9GOe2yfrD8QPpwBITRe0NYVi9PF11+/gR8YbXFm71kf27lDHhVv/+Ue/BPh228nLO890/dRsTws2B47+qOO6lzF8bV8sD6brTHoJ0mcOn0+gYiw4N6FgsUrJhDogSBPYk6/R8NbKzceGZwlXpCCaHboV0D4xRQYP8/EmS0fNzCA3hSiz5ZJg7eZofb6b2d0ep42gHjZOYWVNNrDWR3f7H0zaalCC8o9wczrHqsPZppdPMSE9qGlwNIeLJDh9MV7b+u9CTAwZejN//0O22nDy29WcutVv+H+p19yAAvurbqChgDj8+IRuRclqar0MGxddtHdhw9QKE6fz3aeLTtpc0M3IkCHZBgrFVB6gQJouAfTHYQ2EypbNfCh7Iux/mF4AhmzHz18YA4WIKMtuytG3YWDCA7IXs8O9L1juZYRvMaUA9YKoKfzfJSmuk0x6fZZAoibCW5BT4qRfRqFC9HMJWDA94+ozpnONLIVWhsZuclRtGTc51AcH3R29CZ8wjDn35n06pwW738bFw8DUPCDfCKAMLBF1qm/n2j0yfbDTJ+U2a32LC7goelv3B/GjzAgx74PJXgupx4QAlZqCauEX+BhGf8FnCrfI/JI0XGHGQA800DLUpexJ5wIw+jso+hbN+MNl+vi6Tp+yHmpzWv0T5xlieo8zXej4EE9oftdU66/8vv3fvuewPtnZY9bz6OkSRja837f13sJ4DdGnPvLtXENR204R6Ur8KK5P/ie0d7QMH45Q2hvY996IF4M41WhTFh/Ohjd61pfiMLIdgP2DxcA3UEwLtNdQKR5Xy4c8pfXhREkOJhNqTrPazab0eFujvTYTz7GxXtupdLGpeKG9xTvXbB4iwb23vDr8YDjejAH+rpcOM9rJoCIuvMdzj8sF8JKyCuYrZVH9NZSjbLs3eQ6p0mxjw7e1zcZdywLiiMdGBkwDh/r7WzSB5WSjmlPF4AoCpvZ+EEMUgGLy1tdcKbNxoixH5nZnHvrinVdsS4rRA9g7miy5IJmdkSLMoEOk9bQOqOHLAwM57kbYS3zeshR0m0MqiYrRvb2Is16Src1qzSF8y8yvuqeGzbeSkcBbwjvFQEssBOZxU3whr+z00bdAOTPNCWcsgaFTMo+ec4zvJKHGZAjsCIc3QRGY3MoGtw9W9YrfYQkOkrxahrpqLE5b1vDuqzDCRtOMIXNIfOYRiuI5KY2EVjwlQ65YFmh3oeY2OEBd1oDcPe7jSiclOqA7CjZKZdObvHAYiJyHw8lrcs5q6flliPMgdUxBB3OT6MLYhnfTKC2gCWqQtjdIoLNy8UubUm6oV6mngjWm9w1XJGOZWF0blCycUdgczq+vG/D1iMTsFsLg8AvWCY6qINIsK6e1U7W6mBxZ33jhhbBxgqodGznMyT7/CL7vXZv8YDFHeCvnmFxJOhZAe1gcXmURqn1qArRnE4ZqrqTvMh+gFUPaPDAl2YOUZYRpGeBQwBq2yoMYzURsESgCCG9BMvhgLWxyaJMlrWV8lRZb6fXXAzTETyjQX910MXAElA4sMuzgl+68U4K7pgzMyp9yHi22L5RhfUeVTMqG5My3F5Wq/SxbWfjz2mVjiAFc/mQtwYo+anxf0Njsb7jUVJ/ki8E1sNe1SpPhFGPfSvEdnARnqIudOjJansHRFkeNYND4TKkGK2wwKRgGJhbq1U2PdQBPz9kcCbyNgCEaD+QGeVElklPZOedHhFgzoWz03tFSj/w/Y1CRwKEdekTA9zOMUlfKY4OGWHI6epEnUoPcwcmhixv9K/ylAHDC7NTvCR6kgQd9/+lfUyj9Rgys7Y0QfeyopIMIAIgNdY0NBmP/m85OcWlZdnXGpxy16SHElD1ibBbzQAsLG6Aczo/REOnkQln5FiNJWvu+1zZ4P8OqwpjDThTJKf4Z1/oDIoPGYnG+IzdO58ywu483fEgxzbmdW1NJyliQrAhp2WlG4o1isH469nFQYqA7Xm/h5rJ6nTMM+zZnVmiVmbZqhlGqVyzZzH7GLJUIQ2Yduv/Kt4XGQDWlbFtgq3nRh6Hoy9Eso9zW5rJzUXeRuJfAU7sazJ7EXmlkLZYMOpCC9SrmIgoet+s/ZuvfDjSu0YAmemx3W08WXBgAtz4c0FDb6xjgGjsphIAHAjg9j2zHdi+6FtHZ29Xx81bC3V0EZz7BnKHkVX3sQqSIoLuPdB1E5wgBcPZ7ONu940KAeJVCsKCRGFj+u7s/v3HMKmUDfE3HQcdckJTS3zZyDKbqoMV/nlogoPXReBBZqbHef+8AFjfP6B/frRnkFrJbVgGuhKwgbC5nf7gNOAVA42rRSjsO8LAcTG3UveAjy6CFjjret7iMtLr+YzFeyGlvUfVejCn7kvYZPMtE/wk9q37DbwMeSR3BQa0Znba7nqMVapIaobexSqfelWE0KWzqo8Tz8BtAiVv611wOKxoSzM7UGv49mrVMEOPG/ZnnWx5WZ1YvJ4cvQH0GYOv+vqSZ6GrwYdh7XEP47FJa8X/buR20M+KN2rfzxhVB1b/TQCc/vUT6CfC0h7Q8RaEOUEwcCZ8QNkjnRzndARldBr+nnDcRwuBzVnHonYfg3D4CTj+DryQ4snB8ZPHFJ4BHH9+wOvv1sc3nhuQScfvjaMmHXzvKBQa8866dv7yd93t+7gu7AhIbIz7nDI5A00JpXHqR307W9s1EcgmOJ/OGSxlOLVjQvG8H5rnPJNnoFTeG3uLiazFHMx2QrQ5YRkywX8f/wUz0P8Zj72MYkztEcQ/73aenRUV9M9W+hwYJPMlhPMq6ZTjdiToXxn0n33GThr27/3ziJRh//eNKsEYhwA4nzdgYc8QnxW85SNDP70DQMb4oGgfLBPUkwYgomZUIGR2yPa7GUeWfzGlXAHIZwJ/JChtaMoQ6l720I3MriwMXwgNRaHYpajA6lKU/zFYRSFAUlMMWvPIqk3cOOKKQyo0lNkE25O9X1TAWKFQnD+7m1AV5y/h4A6SXftSuDIOpKAeJfaujRiwSDg8lTn7wLyoX4gQed4SYry0jO4cikVRywykhKWV0TeH6jMU791I8jyE06KzzNk2l4OfDEs7/jKdu/Kcq4pgEcJTCaExFiJAHiUzehiM5aHG8AHLugJ4heAZSsDT7/+WZ02Qu8fmTvRGJfEo32mwTmcQXZk/YaqulhFhbiwdOptC8OI05G5yzCRzjbVOy08YNIqwHEYmcgMYCGC2rEhxAbbgQd/GGHLsFDObpnH1oHKu/p0DlGJf1uzOG0+kvQhRT425teZF0nf0u5ZkrHi35wHxSXpPZwAicxKBW2HoQS4CEW4DYx7K7kvwhvFNy3xdNbnQ4YFCc6byk+4AKPt1eiO5QH8hzNH4iEEz5mF7X9iSwV5LzI9r94AoMJv6TFJ5H+YPVEZVhEzN7wMmaSz0cWREdb4o9sxYw+l9hIt9ZTLnHHJ3TdTdi+H77OIrYJi+XoPU5XP/2nGN6/0xJ1yCy+7GdO2uPX7sZJzvyCoKGgE8pGbgvR80MKLME2Y0MmvCCFrBOe0AGoFb0wg0MMPODLZ2XQHbyw21ROg0vXSiz3Lg3phLiNy9ohZdAZFdP4xbuXcIVupbR+BA8Gxzyg6nntFCxrKsVimnEe6ORxzXozs9Ocs3R4Z1OL97j4jqGCMlbY3s8zRUkGcheL928f7mVO5jZtBdBeirAAAgAElEQVQqIFhwgxlSR4BQZJNm+54CL6s43gDaJtzIDM1CDDVoEsRkRyjIWzr0zeV32dDFMvxbs6zvdV1xWFdsh4MZb4m9xcWooWGl/CTLFxIZX+dlAXu1knBOdTfkSmugLtAsV4pcuyjZic36RxPcKQdKuA5MrFg1+PtERyuOYsg65JZtigxXD8wi9iCTYpynAttY72X1vSQ7PIy18Ix5+8qZ2a1qwQFtWaxfZmaTWeWmtixmWAingyqYLYO9LQ3LuoD97+FwwNIWMwg4vwtDnHilAWjzeZpGwxpBjN6Tmy1Aofc+Kmq1MAB6ljgRoBFYZl48M9q7WOz4pc4HRQBuXr2nwgiKDVbOMslL+IoIsECQsmYwmW+spZhwaC91uMcD2n7JDfdFrb9o7yBYab8ulgupgQeQfE185aVBhaHa7doOKMsI2lCr1GJC/wYiK06p2r00qKas3wyJvSWCVwwQArpAqIM2c/L2TUbZXCXPxDO6Kq/uBCF1C6JlS7PrIeSJz6EThvIV/jxqhHSkTXtgGMAUAFiyfQ7F2nmp4E4GoM4C9G7OaSIspe0FkwUhnrcO6RsAwmG1MvVRmYy4YS6hPLg7O300fIgKG4FblgUYdESB8Tz1im07/mdrSsPf47QosiAjMMGyDPvgG6W88JCzDL/T6Fa4rEhUyXJZSxTcvC+7D8h6mWveb4KOpoPIKhjw+D16SjKlbDd4o+3nWEeiCN9Byr3hPE8xNIzmBC9tP3Alq1jkcvg7g69HS6aJLrp+5OseJThHdjU8C1vTASKkg87o7NCNYFd7n+Y5zbGrDUM9gOOKszfGFnJplYWNNA46Xu+ry1zU+j0m5XeVKw7pmIMCmXHl8wjeFvRQEQFokgZcdXqW7Uxyejr2KZz7quFbjzWJMcs0eD/kYqz22EprK7TGvK/L23r5TSMYwH/gco26zq8KlGAcoOgWRaYL1Av42bRq4GUEIVB5ko+jBBKErpaP9TW/kD8d32/Z7G+L64FUIzBkSCVjD6bkEfu2ysrw/Rt4yYRFvcWK810LUCFr/dBa8jKCOdmNLorBXBCIfoHjAeeUU3wENBArxwMqGfO5X+bnBI8JPkfleRHwx0zgRhb41xndizaPCivhiCzOc/E+4E7zPdYF+ZZpKCETX12dSZckwPGw3kujWlDBRcCCrIQUummWAebWwKzOp40P9i7Y3KFu4XNWwl3FZf/e0R7egn47o+OrV2bSYWeE8YmzjEqG7DAqw8SqhC0l7+tz/mc7wnkezWmCio1aXONvHMYnBgnZV2RSWEbwVn4/fHgAMVtJeJ2vz1LbOu6PjOA4yMe3T+9oHmQWMkeUl489Ha2BtpQdLLuWuWJe5RzIvTXRm8J0FLiYcIp1RfcKZ/zQn4JmD6cgkznbxQNZw08RpCFsBoDxamtBJKP6Dyxg6bLCIW4eQ1KZfyOYI3kt35f3ZGv5OPNR2d37SpbMmOwl3lMAK0CWoxdV9F+fbhWQyffXDHJ2nFp0ZLkHjsU1Z1jp+UUtQKM7nnYo9He75k4JT6VFJQE4gvD62xenQWMc8fF7zvPvH5c0/q8ef/SU2fI53xdBfoGrU3UhZ+gi5jzv4kkGweuFUt6J2eylkZvHRNzjY8jB/o1g+rfLIS2qqAojaiEMvei2HPB/wvEPc6D/s0Uo/OnRpPFtfsKeHb9RLc7FFDHAeDvupoLoCohubvQZr3uZ9rVvsUkIvj6na7i7v8P2BV295o9w/64YDOqd7SfG9rlDaUQsqc+jvunFCeq9GmM5Pz5i+fABm5fnjlLkcawfFzMe/taBDyOqVNWYkmVKDFk0DAD8cZTnZBDaT2MUZ/5ikXlEpe9SGAALTJyH1/LVsZ5ByK85NmbB5nK9FF8BPFik2aNCPyhefzsDUBx/PoIAHH46eISpRc1JN+Hy+PMRIILIZlGwSXXHwNm5XsdXrHiLhvucjzwalT3Ra2IwEWEhi0dbPhgJiJ6dTAR9EOiTCS3djYKL5Sdbb+8wHpAbHd4Tzl+eXJB9kw5jkDvwmROH3jy8xdcvX0DiBkwlK43/uU+QiyVII0s1DsQ1GMy1KjXTNTT/EFUeQmhs5aG39tNwCGM4hnsHPRCWxwZ+IGyPrtj7srw8f4V8UQieEyfsfUYXNjylwrqQGf8y2pxcqEsVa4wvPjPu0PGCl0+f89lK8HcqmO4AejEhVwHFK0CEN/cP6FBsX+HGSXteY2QfWqajB1uY0z3GhGCqiizLmWvDNNoUAKYciaLDhNGoRhhm5ej/c92dOOZ7TZ6jvG9AZrulJiUJ/j4HiLkwW8nMyCKS7r1l/X4r0z3wrQrX6obZ+rZmIe8psJML2RGJK6pYlpbliy8HFuV3r2eiB8ZG9Gk41XIExQg484BB2YqNLyOJN3fwzAb5Aqvp7ddGZWfY93cNeAinZVd4ywpNQfLWERULUqF0o1rgx8LN9oA7ujJ3QWsAwZhGKP2xsqEUhWNrmpfzwHAmxv2xqyMCPIxW4TQkhNGvvBfeg4hmg+cIqPC2FXtC59eMLM4K63+2Izp3zYdlO4eTKX81+Drv6dt5vkm/TyMa2LLUi/CfxqpQTIA0cqWy7UA2hVczkwxHAGfF6dMr2ttmmYgW5WUG1ItphazmU4mHX1m/6a4q21VSVvfrdH3sx5LlBWRW6OXzgzTrtK9V1TJdssw33CDXkx9F5gDB6NeyLDgeDu6YbDiuRxzWNQ2Y8dzhOI9SjdvA/ZC/ApfZHO9tZ4ize42ai1h2QPby9exhbQK0NhQ/JkSvxZx/0LtISY0s4sbowpk1Ewijas4KqBnso4SmZSUo4FlRxJah2/uG87aZ8YTMSdzdsdR1OMjjEBEs64rWGtZlAdaD0ZLMIhXPyhd/jmV6cltGr0An8i0zNgpfgfUZb4fVs2GHkzpIRu4Bb7NCutcvwgEW94SD2cJUAPH+nKPnvTnthpHd+KZTNKIsab+u65QZa7AvOpNnlnYRyNmMUsyEzel+lHTvzi8yC9n3NxNnCGlrVhHgcDhiOa5o7oA/HFoa+LgNh71tQc3ERqvGQCBsYLX1J7Yy2doaZFnAzOjczWhJxcEdxnNiZDOCiXw5rwONrFoRCDHAFiXc+zaqBwRN4La7X63f8yQhFUrppCr3G8L4LmhEkD5OqhLEHXnqQSzhITP8FnQUp0Dsk/NWdAoGcYd6/e/egbauSMcP1NJi2Jzn1Gx/teUOenrJ8bIHGRLMAN+W1WmiOQb6aUP3SgxmjGWImrwSAdaG+IaD/bmnnghVtE2BA4HPAK8DPtEzkxg+BwukEHemBTDJ4R16aELe8cQOmwN3Bs4nUB97gVvL1heW2WH0xmjuBlVzoLe2pJwbgd3xnvxbjMCGt2bcDRrSu/VYt4Akky9ba+Am0NaMSxfdjIDMsFanBVFyd9s6+tah3RznIt2zAMOh7iVYfRMtxwMggu10BmHQmZHBnYNOtDZyramrA3DnaQkUCfZKsPK/7LSmyGNlO/jcjG/mMvoDjJ0OGZDE90nsmOAfwWk85YoAcFtcvoz1MB6tERjlU7MWHpgqAFoZeKOpShbQ0r1dQFa8if7malsoSji7m8yrsgWpHk7nCUcKfl7IjCFX6aiOkA/0dUnnOZD4H05bGgQvb4p2dEPejcCJ4bTYq2kRBICyR6FeplnVAoagnmHoshZ0VLeA4WrIK7HmESfEXDKwrf4plA3ZsrzvtIfGuKdzBf3mD7kzdw6e2LuYf6/wD9yi8b7I8DUZBJCtGy9ynSTKqsLbVQy6M9ZhvG7IpmGgV3LZoC5EMYInz4/Novar2RSGrAfsZYf5oGtfaMghFafyEtXE6+jlXPUm+xA72OZhMofz29ikjkfMzXGu49trh6ji7n6xtc+KK7avYl7Uqjw609eBDgOPu2wQ9XDhFokkF9tt4JuDFlToUdALuBzkAYQKuWgaHGMSigojFkCppSWePVgj8i+fLQWeA2vH9/ovfuXc6w51Qsrj0ehJAUAE0QeYRLH5ORYBs+1PFcUJghM6VhXw/T3605M58iJ4VgQsHeffPlmVNp+KlS22SiMC299NBJvLFjIvk+Gx4qbN9m8/LhW2v/SYcJyHM1zcvh7O6nhqVKek8j3U07qmwTmFZknx1TPP48LBYZ1POQ6H9ecFJtUc/PsZM/VfvKoWFCkviMuFqjEvwtllXdKhk8JxKhxyjRmdBdpdP1C4joS0m7EnuESbr7DfZEVEXw9usx8leEbYaaI3euzz7n/P3WTbDtNB1SMUouJF997s22bJbC2qcyVMKW2lwBh36qwuRwiZg3l7+gZhgIU8qCSb2RgJcNp5/lI2cfy+Y98E4Oj+FskErxJg4beK38v0DqffHk23wny85P3muP/4//wPfPmfvxrMCWhi1p6sjGAsG08OinsAJ7Wy/09k5d3jUETfd8UvQjhhtG9jAG/+x0c8/9unJIEVr3dixJ886hPqaG4fg+8POc6eMlPS/XWmMxRbfvkdUJx7BxGw0goRxes3s7e3lXH69orXc8e5d5NTE2eBhRdo110l1x85hqyWLALY8Twgqm5x7yCvMFgT61Dui4Dw/xOP/85A/6HjNnY0zITLjrfJDIbRwajVyO5xRHbRUAsVjK1YjfERzRLGslvC658lKNdIyXReJ/kXoVdUgqGwiKe77zwo9CMCrF/s2nD6fcPyoQ3hzuHDAPRjkCc36H5R8HtChNdJMXYReQlXdWUNlMIzR6FIv7XJOxfehyN+SPMxzyplVuPFuOw2+aXd30Hql4eWCmUYD0OI3rbNHZR2bSiiKcSLYnvcADwnrtjI7sub36S4TO8JeBprRkA6siiESleUUmFygQdLA5M7rAqe0QOBHqlAxH6bse4brh7OcLbHjjfv3+P50+eB3wijinqkfwHhxHDmN02fy7pMyxmGEj+ixPdKl7g9/SVM86zvSEeAAvTeGQ0oq5sCQP8S5UbvXcS3UuodX0G4Rwqqfn3DyHZUBZQ8o4ZoEnzjELyAcQdg1DZmvAHo2XfAS8KCQOgxX2bLKkrEV1hRoDDQHqD6io4jBK+u1JoAoJ7BYxUTuOAMhWaM6hwTN3TUlasQvRbBOsF7d/34bf9rjfW7RRe/Txkp/2fzGL2yI8ggaLkOugGEdJ/4PSVxlyNLGTt4huHWnYoV7X+AiN+6puJ+jLsK2fH7NXjE9el4yWeWTIGyB35sQIPDBNwacWaVTNk3uL1O9N1PuJwzYmk0BbwylEJXXEnHULSGYlneVQ29CDzIh0E1cCfmQ+U1Y47AEF6Rd18/Mnv6D7F3d993nvmPPsgzz1H+SwDorsTTU8Wp4GWXT8pZvFyc9CsY9KYy5KGogGAJmGzGyGz/UvjcUHZmmCkAHOkPgXix1fOH+cwNkjDwzYWo1L99Aw5TPuX14ztd7MFwPMUbcx9ToY86cDmcUL1vOJ83L5Nsg2iNQLBS2nfHI47HO3Ogt4aFWz4jsxM9e6R7+edti7LxNAkhVOYdpd85yl9DvaexpMGhhaM9stwP6wzjoL2efRiR0+Zc3MsOhMxkB3mA4BzcEzCOfr5RUcWCfiwjnTBKI0d2k8Kc89tGAJkDNPa8dDPeHkSwrquNhRlECxrFmBpaG2UujUYoRM/uaAO6ON9F5b8+bopgiirPxZKPErdhuPUvBTZ2jXP63EnJ+5xZV4zLygCNp6z/uIejLGlbcDisCEQYzp7QbTBgTgTdOvppw8aeUeXZi9yaVWcQoK0L5HyOWViWuqPEslglgOPxgPW4Won81rAu3mM0+R8lDwqHjGJD45Z9pbVv9m5qoEUBWaBN0NkLEYogoJaGcI6AmthzBVddmlMIhB03yBMNhRPvcv9CzKGrPdcneToAoMcmryszySQSPMh79gqJv8+D+DwwIu4lWqA4G36fzVRKi+GtemlaAnzuOVpzzpjHy2lJwNj2I602R0Ndw9/ueMTUoAuA7QwiC1pitrZSjZqx1Q7IZj23IyPPAic8c7xXmcJ4cu/dhqSS5V1b97LrSzEqk/Uej6pYGi0C1AMtgvZy4D1n5TDb55VP248bnNez9XMNOnZYD1hWp6Pemqx7wAxEwcuCRoanUlrkJK76/MJZPpy4jsORLb5tTout7UTMM3sA7xicOq7mMyIgqG+Q+Cc9nfHiDmNRc7RHkAZUDU/MSziyacubhhO98CaBBzBYhiF5Jnk6BjwY0+5vI3NH+9DJODLSHf8p9N1wQvp7s8rLtGtiSL72RUIpYkX9l/Jd0rVg5r4r3F4TMnjq/4A5RjWeIZAt5AGbZ8bM7uSQKRM6cT0udVlTy7mLB5SHxtrk16DRhZ5RyM+a8AzsofLffD/IebHTKdXBf+K6mg2fOJ2QHLgMb2kRvZ95XEuqlvHqeOb1aqb5hiMiHCfAkL1rNt4EmvrtO6Crv174y1RvXJtTzufXSxjI9gGqRn/yWcCoIuA0R32tgibHu6HBwQccDffUnj+Na/Acu304rob9ZDiTZ2fUOK7aJKn+XnAqMcf5A0UTlZJJTBHkUJ31xV4UfJydf4hAmKHb5u+CV/cYax+yBOB7r3v5dcelCYZ+l0RgjUZolM8/ZaRhG0jScwmJskKU11WZrQZKVfjFXIJ0jX/z3h7LEWMf3Cip2zV8vHgfUlYn0NBVCZ5pG0GtY8y5m8Uc3e5XRFOgNXiFgPGaswL02I0/ACnz5z/nQe3nB+gnheo3c9J5NR+jjcN5frH94A5fJZz0+nr8sx2Ha+N00jlVjcBoWQlYpjGhOsHz1vweQf5jJ1yHWf1b7Y6n3XOAGzClkEPKi2BO4HCiZwCOhuzntrehjuT+SJoVj/JnDmoQfFgnOmM9zJPh7vjboHE599T7xKpUhP7H3pIxxAaYvS74azw6WovEXsuApx3Mr4Ars/sr76oUua4jprOX5zpqG8tx/gxgIYwqOzFuANuvj2BYdvito77n/f/7C16ff0VbPuDbv35C+5mA30aY4x4HAXtvdZ4HvkYWPKti9XHG+WiDWWH31zPPrx+31uXvPKp1+vIcBmIT8PXbC+7f3AFC2LwKgtFCgKO9L+BV34IHDDnsR4/LK8eOUhdQyHWFJm4ziUC+EGT/S1DVf+zxtzvQ/9kyz//ScSENk5WVA4Zwh0GAAGMOIUIRCMsH64ZcL04HmURvl6BkenMnE8jLzMV3TESlfp/v+3HCQMDsuMQgsvXZZZ8bEyPgsYwrmNydmkMdAN7ofmuTGZg2RXsgkCiev3zGm/cfAGCUBnIJfuvGvI6/3KH3M5gZL7++Yvm4JBUmAuQ3wfmjRbsLCV5+e8Si74YQSPfWt48UoG+eCVohEMJ4hcss9A1l9/YxGN8QW0nvzeDihkb5LLj7+ZC9mQACXCgNZxrzAqige8n1/ihmxNQ3/lzvbY1ndNxjwQIFYcMzFnoHfbTyjdZfy6OH02hg0XL8vuH0+AVEhLuH98AT4YVeMTLUgeNPh1xrKLD+chggIcK3374Bqmi4h+ArQPdgCESfU/EbIFRs+Ab5gjF3Uoiy9QMn9dKJGDo9zYLKHtbf6HKv/six+aXBsKNXC+8En7sP7y0C0Q3D23ZOriePoXQR2kMwe8syOeMFIze1xsCqwyk+23gXd6pv+pwKWPQShT9hPzMtwQp2zzOAOxBeALyBeZ7sAQ2WsfHt6xfcvX3wLFgAOKVR3rLS3NmO0X9KERm+w8lv1yON9WmHURn9ncvSiMpu/S7MOtOxpztRPqoK+YQobXVlzZMufR8faPeheyR3EwsoCEd6xb8pxiMdSXU2vvd9jU0YjM/OJfIZLgjJcFpUwNW9Nh86n9/dGTQ6epuGkWKcdYXBEazvSk7Nb7kxhB84yG8Mo1soCaaYIJWpq3SzPOf7+fc2/lFO3glWKk1j7LZ1h6M8oqBvzd/uH4rNJv0Cp2KOCqBF/TQ1esBi8oCF03Ssh8O4iQivLy++GjUGvGBb0Jqbo7sNk//oI3ltfvLf38yK0JhdZNc5fMX6Far88QymgBcELQp6NF4UgRoARnCLKwGKuQKOqoJOLp+8KvR+99K6u9IaXmc1RLkJRX5U19AxyDT0Xdynw5Ad7wmlBgQhcacPleuL09SdPwC8DK9439wTFl2AZgEQS1uzx/nd3R3ujkeTYZgt89Azia3SiDnPz+dzOmykyxQdHfIPwulMYYhr7kh3R3UYz2KPRksYGmAHRXnykQkDDuMOWYkzZrAoJCpcjOmDyHorqxKamqFaencZ3Uqlj3sERA2khIbmMliMdaivfevYaPP+5tYLWB2nxMtXciPQ2WDRW/fexSbvtsbo3frz9eAp6RwJ43UzPhLOvSJ7W0a/5wRp7EAnRW4AHtUCbAxWaTocZoP/TFH1OtR/Mosvkvek4ZiRCdIJY86o9WVZvGT/KAAY/QbDQWayRzdnGxOUgX7esMkZpPaMLlZxQv2+5XBAf/V+cV4JYFkXHI4HHI93uDsccbg7Akyjv+jCPg7L/IZagK16xRzbU9a3Ga1hITInOjMYC7B4n2cRKLnz2rMFczHge4wCl8x5iyixTZwMTUXQlcx61cSdAdGjXWxuEDcYW1aOBW4oltWd0FsE4BH44AFMCusrjcFzez97z+UDNNeVwBRZ4gAvDa03az8kGwA1g+HpFRoZs7H+XUYGM3nrKLKsauYF2/llwC6M7azpwBWx0qtMsKxQVdDSPFDD5rA067bezx3b9uK4gyy1vpHY+im8YlIEQ9h5Obtj2n9gAsCK5Y6gwplVbJVyyLMICZ2cmviahaxr82VE4F3qxNQK7pM7W8zAsukG7hYIRI3BK2M5HAwfyWoxWRZ6d302CJ0504HYH5pVC0QkK0hYGVsatKb8C0d68IEsCV3k9mGg9mxVqAdW9XSgb9GD15+pZOPpXlabl2b66nkDQbFt25RJngbl0AkrX6NYb0q9XDYFi9E6yuuTyUOb4a4i5HFv++D0g0CxtCOw2ec6yFulczu5aSeDKCKjkcb6pCExLtIMnIJKOv+CD6S8oNEL1p25ItAtggok5VOrrhDt2vIV+UE9WKWKipPGfUWMSv2tnlMaEmYgdHxJJkP1VcYnnC+L0lTNxDJ5R6Z4lZ+xuz+cLdHjNYy30eM5qqKo7+0wDKjEmgVvtM0oUeosHCSi6CVwueU6Bw+bQDgAvIPddbsPIQi57oF6/THjYaHcFz3FhwsEnyR3M5f0USqagCYuu5xQhEULGFVvGeAyJRTRWoTGxrk2wELvXHdzVBtVNn5UqC0HDR2hvCrnrQGaC6CFux1ZcR0MkBAWArqyt8yx4DuNku2tgUSwHhq4OX8wYcjLgRPW411We7DM5jOUyVvA2/5cmHAOeuDij3WO2Bz06sFiRt/2jkxgkJp0/oONV3o7nJBnL7au8xx4JYXAXarPysAGjHVzmjrartCUEXu5JleXK3UMgqELUwS0srdYsWt7IegmR3Vs3i3Sqhc24z2+F61Pc9gwfX/HPleA9Q2Wn5vN/6NAfhfnJ0GHDYcXjJQdxXASN81iwzgo4Xx9J/7jjjQ4/Ln37ndVdZ6/Xm3jMmztBx1Z6fu3LjB4HN4/4OXL44Uz/fIelwdh7z84fetkQY/RT/vsd4fOvi4NoorNdbytWyY6M0OJsfUNkI7VW0AdvO0UiQXwhpxwOFrloZeXk21P1zfZdZ/eR2XEkFcIVp0reGA4v7tYkExCjWiyFRm7NnobLbfinHjQsJBCu1W3irYJULheg/QnHg8rzn2D9JDjbi6101O3G90Dje/x+uWrUXg1OEev80sOqjh8/IDPv3/B+49vcfr8FeprdSIPHIHiHJnglb0DaQvZyLPgxfeMD/mN0mRbXxRYPxK+/s9fsfz0zvi+CN7/f/9iQcD/l+Llf/0+VUUArJ3vG1jf9WcyJ7pgVFqIN5zI3h+SyAsU8r9+m/aDYvQ+/2HOkwb0/R0D4yfcD3nkBm/U3YcITKUb+/0i6AzznssA0wijIOD52ys+fHhnthSvJpU+CJSKChS7dO9niVnNc5zGn1zYfnmnDzjh25DZVFMWtyCXUXmuVjj6kxLA/3bHf2egXzmqUJK/3boWVal4gOLJGI9n10wXetTc9llSft5vyPg8UNSEZFXs+s1eH1sVhv4O5L54Bg1lp+NpOhWM/HsiA+Ee/bOYA9zr0Lx5/wH9c0f7wCn8qWJEkPk4lmZZEPe/3OHbr69YPjY3hAuWj2upoPKMpm8d5JIwWT809E+PrgSXMTmj2xusL8F9GwsqgTJVZlzLYLTM1DYlkd24Jf6iYWiofStD6DXlcVEeZW8AZBb5NAona0QAnmHZzt+g6VB942MQyOOYkjwq2nsCfZ0jYak+O+T76qjKIzBWMTl2Y0REiOASciM1EVmpLgRjKBAt/KgS7fltu0He+v5HRygeGMp0MrpU3JGClj4Zw+J3BP46xhsOZCsPZi4zVcsIZ7yFuMIw7dfc20AtEUwYZc6nQV6Z6iRWU8B4ZE7HwaQgusPL8xNWfgPBy4S3ZrB/hTnKz/lbmNdC0Yn14N3z66Ea64p0VtWrrwn5fzS3/f24cv7PHHu6+b3zoUTO9jIdCwikwKFaXXuXY9yXhbv23r9L3RMNbL79QuYoD7wfR6EtgZd7oniDJ8Ux0UJFOqCkwODaXKuQ+SOwCOUh+Z/OGFfXahKWMdYjBcJKUy/oa/xexqoo+8J+YwBtYchJndqaIVRPAB2vTZzmT38A13/WQ4EpozePMOJMV/pq0XcEfQJwRxdZ6Fr+hlO0ZkfFyWrYVAqFYDw66bZUHLjYsTuO/n2M/BHFYo9zFXcGezWc1YTNjIsXDvZ6vZYgHRr0qOLzyGQsTibAnV2ebb4so8wdvJfh2R3k3RzwI+t8yyz0cLDbO93B6tGn0Su9NWu7AAJEYp+O7HOQObWGoV1dTrtWk6XwPra6Q1kVoszX4OZGS1VIV9QM/ZRiYn2cVnFadg3mxNFPt2SnIrIpkE7CiX747QrLENWlmfPJe3K3KN68vpsAACAASURBVA/eu5Ux9Mz1NID63ECWLQtu4AiK9PL6iwcj7ATStKxRIH0q9JpwTtERkaU3QmEsAKtgn3+pAWa1tHucY6I0XlVjw0TeFCMrIvp6bua4671b9rd6NghaCFr2nIXTgdKYsKwHrAfLPj/eHXE4HEBgKNv9TO6LyIoUhvvmdLWexNK7r6MbcAmAelUoZqx3d9Bv35ABAZpDciM3DZmXYCXzXXhQtaBWjX7nIKi44ye2oIajGolb6oG0kamlApxfBcuhuVPVlq+/dizrAlBD03BwaxFw1dtkMOS1W+DFPfu+apZhtjQsskC2mVYodWhHttngRmDxCg4i4Ls7d6JbcKx6WwiflBulyLOTba9YAA/cUepOeDFDPamVcCdVyCnaQVRdgNLAq7H/NPp32nvVYeX/MRKkgt45F4yJvPUNAWQBOeJrlHtcfJ86DmnQkXg3VXOgV0VThTRFkxVK3W0CNPV2N/KRXUd9HzoN3MuaOvZQZH7v/4bjcQTdDFrViLC0hrUZnVhaS1oQrRWsCrs5ofp2SddVeqRkWvZQ8I7oYRlr47aO+CcpFSQRLLTAqa+TdSbygIphwCNvakrs9N3vy5ZuykYDwwDuNNoq0/m9k8My9LqRQ81CU+/3GC1yvV3WEw+cThgPB1/IG1btQBE9wwztevEUOnWl+IzQsLA/EopV6CnSsaHGcI6lxqaxHnFNQVG6fOYkt1D5kraJ8uMeNylmYB+lFMbY6+7jvjGAUUY+nGij33kEqkVf2SE76UhqoPglJj4D0El4jDCBMcLG8u4Z6BXk147E+3LV/Geec1ZkQ1mAwQ9j/GZTH2s854PG/Vo+6iQLCsTL6ZLhuAZfGlmS9f7IoEacQ9X1w2h/MYBy/Tysvb44cIfG+6/B6Cagy+H0IHi0UodSM5nKHXdK7shVmzVn+5gxLvLBFqoN4Yb/n703W3PjVtIA/wggyarSanf3zbz/q81Vdx9ZtZMJIOYiFkQmWZIs22fO0vAnF8nMRGIJxL6UIWrsHSPCCAor+zphTaPcA0sIgr6F3mMupcl0gBsJizv1WRkjWIRfrIvMUjdeuCEvkcw3J0HG0Lnjv3hpAq69kk3SHcE2brlhn1WUUSoFpVSUqs5t0ynHnAekb17lQRZCbkDfOgPs5+OOsF1EM2FRAX9+rzLa10c/6po9SjSytmGus0e1usjxFv75R2tnmnWrgXd2Xh+/89T2+dw8Mn2uKXC+f8Dtp494/XoPYB63/V9fRyAbOidUeH96La8vxSHJer+5x5NOuJhCBHgerwLPELbpUf9eCA2Tj5i/Oj227xnHaSdWhsB5USs9MBFWOiN2MtLxUecQ2uC4uGj0pTCrA8Fu3XB5+/xMtxDMjMaeytzvc92Wf18+fQg5+f7rE27naK82tj5jLdO1AfPfle2FG6FI4Q4AXN6DftVbXr4Iitzj+P/8F7gUtHZG/fUD2t8e9lsCYEbF5zmthA3/7mPwsTa7M/f3Z0egX2t/5isyVfUmu9/dqZRhzkNEWM8rlrpgPZ8iqA+CoEfhnCG7Tn+yPdI9FqmhtxljaCk46LnjwuDOFujgUejIBPHfsv3LG9B/ams3jLP+t7rSJhGRdzIPN5FF0YarYfbxmoORMVA+Ms4PD4arZTLMm7snEVDnqDAz7oe4Jxmbt+4P8MV6vLVARkjIDu1krASM90Hkbo1Iv1g/R3FGQH9QG/kcuQAoH6yeQmGNXvqqLOKB2dJgpsgl3hqjzut5i/y/CkCMdq+RgUJq0Vw+F7TfvG6uRgLKbwModKHAIyIcPn0wGVDQHh6NYGWlCOGt/MyMu41x1Mdb8H4mbLwX8Ieh6/YRlt4UOH85o3wq8xVQIr3wAibg+W9PELwo0ynv4LF8EqnbGcvHivbwACJCxTud/6eCpfyK19++qKLK6mE7c62lpASF3hkxe8T6SFjoPQha65yJcf7NlGW2DPxR07eWqjkXilnVu3nKC14mvDkMJeWFmyLik9UDhnuqhzJa/+3TyjixPbvieCfV7enKRi68snt+XFcmVNmKqQLgdP+wPUvpnI7HW7Ct6vne5+9etRYdgTsUVKx43L5dZj8gYLXnZp0xP9cS92t/N9C65FnEmQN0xpBEYYRYMUK91X07Pz2igNFxQqEbCK+h6yIS0KgQUuO5mGKdoYr+qUR3YwZfMJFqnBhA0zAh8lS8adpbpvKS3XKm2gWl/IrweL54at/HdbiY/OAO4drR9veKyAb3RApM+6XLTF8KN5rY/9toWHiBGyf8/c4FbZQlaXwAwT38L7Ls/d5GfjZUCHcjmBuufR1bH1eN57kj3/NNkxj0dwfiOA0E9O4bamNL0MBp197IXnn1l+1VV4hq2zud5SgZ91x+q3f3Dr6YEV2nqQozXl9Yo98G1Hiuqc2BFSfQqUJMPIh3OiMqCGPLj834r20/wz9lIZZuMucguHAQoySzEkVkll42+nHlHdVMHvIiamAHAKuPRzQ94sUN7463COBbSo5oZHjr+l4jP74nJkASpHcQsZOws4JzZ9ZV7mpnbPUe6UJSt65Z+R49RgmGfd5e29UjY6zUjRt8ryqViCKCjkjr5RIIbQxgbZpavGuUYW8tjHl9H/WYjPFq5JBIi+yGRsobL5KioWhrfDZGwGuRixnC1DjuBsmE10l1nyIMYgEPd2TTdXTDubBGqndQpPfXYVR00WwRsW9hkPJXaPrmwqz1M4lQDxqt7+nCi6W551os7bHVxo36ltOYCnO8YtLa3b3W6UTQZ6QDc+q/zHTkII2u1u/TOJeNQJHy3WE1DD8T2EQldDunCY/KpIkWmqW1fu1RV6xqNMYsf+LpGceQzRqIuJOGcYIW/d1aw3pe0VtT47nX4wbQh8o/WtNQ09kLgOV4BBVGezmBa8XCjKVW1KrOH4dFU8eLnbSYugwLPCO19vjchhkhLXUdCBjdMzgRGBVMA70UtNV5J/XaHyxgcWcBXyoCGKEw3hi0BBCwRdjYcehjEn+yzCpuNJX5nGcnaCcBLHOVGxbauWGg4eb2xtJQG+xHZiA17g0BaAysawdzw7JYvfqhNbLbGBjNIphFgFqnYh8SxkEUtnrnft5NcT0GhnQwdQxmNXL6ubezCrFSDkQYRQ2YsHNYiMGlQgCMNgyO1BF0wI2pUD5UFCf016GZJ6qeGz7obyJugDMZ3q0hQqCijhGAKog6KDI0dWP4S3WHeHNP9XlYLcyYkE+NtCgTAyAeGIMi/S2RGrjQdd8HBkbX8hUiAmkdo7UgKZlHincYTuo2L08B73gFBHMk0nJVnnZ3WRYsy6LR7x4tDeX1+xgYbdWI87aitY71vGJd3YDeQGHAV6DtvUX2CohYFgzEWCY/bRmCaKL6iJSc5BtWnhrEJl/qFw1eZNZImELhnBMGdIuM9JrjPv+oub4RN+RibWWkVMCyuQKxdP2im+kHF9NJgQDyFPY2LwvZDaOaRbj11nUNwABPl3IxyIxx+RnTwYUxYjpSxEDntPz/ho8C//uzlm0kaItMOIq5gmNPsjPUxgAav6f3B/8qtpEcY808dx514KZ8zSJ/h0XiD6NLYg4l4dCd+gr4I3PedAOO3aFl5t3xZRrdlfZu1zHGIkDm2Zz2T5OQ7VyW5WTO460Way1bSUXhxrUPE46GzDMEIII/9pFtU5hwSJp8ZV5f+O+5rA9SVJvjmuQ06fOMV+3mSGmNNg6DG9gxbsNw/rwJdk4AT6jw7QVU8FoKo0PhhKSArJQJlQLpPdbBMX7IJGzrT4qjL/YrFQr36P1hWUHY+5tguyl7rPh4xLvmTRRZVYgIhRiVK2qpVuqkBG6D4bM+xPiiDpGuRgto1Kc7m2wMl3Ze83lL4DW/Z+NgljkCxowXjU8w3lRxcWFGrTV4LOcLVWe43Wsi6PxKAaho2RSb4yCKtN6AlTuB75ngVJ4swIfUSN/V0FlwBw0McjwrmzKqMWWbq5FKHPD/QxT6T7QBNRLe4mnz2zb6/Mf78ojgbIB9/XqfoXOP/ezaPLtbWkPRn0DXtdwBLy8qZ2lWMy0BNgQ4WObKtasz5dH4xMDeRkvqMuuZR3ZYJhyPBzy/vIb8vcF7TnqdLkGi1NfraknnI4OQnpZDLZvss92QQaA+u2+pFSKCtTdAKGQXdxrMeqXRB0otOLWGA4qW6XL+LXh5mjIUpn4rbAVcIdJB7wj0ZDQPs364ZzgGLJ3+1wcMaL5RN07PbAF0AS8ePDBEwvHBx0HQSHTBDNraQ1sB8Pq/D+qYIorCXwlo/+9/gwDc/edniDymZ/X/t6LR6/75xdiI9y7mGAn2dcl6Xc0SO3sjzAj0LWL7gRbCe35uy8NsbnujG9/3sacb/nzqOX+/HM52PGtrGEVpQBfC6+mkjoOi+LCYwzUZLO3p9VaRNuHnzTYZCij9z3zPwMAAh2yjeiMuDGoMZgmdsQQx/J378S/S/uUN6H9myyByJ5SQoBrKtL4xJjqX3XmFglq/lxCCIZn3lc17xOoPUb7+HTi9Bsp/DLS3KGGLft6h4GlzUM80U8k4Ac/PuvJh2Nw9fdjyaVGCcW7o9wP1gyEMMkHMML58BfizGW4FENbI7EbDGHRjAJlN0SKAvNNIi08F45HMyJjmQYjf9FXvIXiyzaNAsyyeImy2EobsW2wjr++srskUWOBCiAltRAX8QSfmqWCGp7Jh6I1kisO0GyVEL9IrmY82AwV7mkokD1G456el5/FUkYZ8N9EAWcmFKdxRKEfVuYBCeXcCiUV+2fM56pNscSWY+xRlJjDleGbAJyxrqlETIGwpJyBSYv6DV5ltdwZp9yGJe9MLL/8uF+JQvEcssl/eqvsO26P32NSj31xz+LrCzTqPCHGjKwHyCvL65GkqGXMw3YA0kb4+Ml7A9AH9RaJGrB69tlkcEaDhZHUbGUUX3tDUFleFMiIMYjoK57WdjO8VLXltr+GlfQogwvW9/VYfV687XO/ZCocdusZOzUiyyx4J2CN3InCpqKCImvBVKVZzeSqT8v5uJ7k/Az/eknonGObc9XVY3s74Ejd6f9cuXES07vsjGwuboM0UTNc1HjTJRX9J8/MU9Gf/8viYMQNdu2XupTO28QLAlURzR1oSDqbxfMRDhgeINvvz+/b/79eu7Y8gOyAp1Qplq52vPRhtO7jEE28KIPnz64Trckdb/dwNMF4dO2qP40VAN7Mjx21vz+zbLXTom9ER3mIAZ01XG1dSME8XyfSo9ZOo+OXLr6yUG9smZiZAxtyTmPE0Zvr5U+OfGsnRGs4AWtOoREnGmkjl3nso58XofX6PDIlUou7R7AblDRX2ZwwxZtzraR6H1512WjYm3xeUkJTP62Fon/2rQ6Ea2AsPDLBFouvzTB5AmfbPBEynhQKaymykqFhT4paixr9SGBIJDxHzL7w1ciufQ2BhVGaMWkG9h9Gu1IJSFo1eNYMjFVUGFdZ3cdFoyzAaWcec9nfSHcXBFOvlc7OH9vTS5OR9vUk3CtalWraCkpw21CDaWtf0z+mcaYZZ4xLGUEcuSxmt91uktYHt6GKpmIvJ9BolDlYDLA4HHA4Vy/GIZTlgqYv+LooPoi65iLKeJJhp+qbhVnnUAfShDh+sDhAEjRIzJB0KBxH3WRngDjQMgNnSZgdQx15QMHumLhY1Wg0iky9Io50rG/60gfl5CFiRSKtrGwGvIutH/XzuYDaHgDQAVwLNSGpE+mtmQqkVpZsRlxnLYUFvGq0+AGBZZo3rK4pdNn6dC2ntc+MRJR0pBX2ZvBezGhUNNzKqwm0tKpMZ30BFS5qFrGcyTLfsFh69zMzo5w4aqvCZhg/BWEQzGW9wJ4HZVPrkhjEK2VBTh5YwAjt+F9o6Z0A0Mt9ru7oM6c8IqfMHejdZUrN4SNc64hhDnZN6Tws2+eCc5hdQA2OuHWvArbTQjMzCGnnOpaAuavxgLihMZoCXwEPdUslrVpF1E4EuQx0pyMo4zIhOMyTbYch6ER/nhkYZAZz0wcpYsKZQdcdVGYxC5nhgKSQ1dTCltMcTrmtlEIoJETL7Txk5nO+TGI2ZCIdEKnI/a3GdBgYTNHo00+DJpXEQWgnSr+RWJv2xdSYznuflmO90o7wZtocEGMy08vM6ZPfX78hoOw11c0/iTrccZ+btLUPDTj8QEop37vK+XzWDA2i+c1vmChvj8EgKWV8D3Qpz2JJ5bT/X2MkNv5XGsmubFZDL35zW+xrF9d0rhSffL1fW99pbs4JeQSUF5YjFCPqiBOpPAJXGHD076wKZeCfDMOWdntllgp903BR6BgeYzJf62OfALmRCv/cqk0+Bxxxf5hPkepYfaZqtbwQdoaHExdPOSvJBY4I6gPo78/pfG6aoQcyilkBsaeKN8SEkEEvzUro6efmgEZB0m/1neM4zPLlzk/Nc7jAy+kDryg+tlo1neFaGOCO+hzM4xdfTdW8KFzRTuMcexymOU0KShp5nSYpzNXNJNSO6ajiHDAweVoZIA29ASouXZcHhcIhI8IC1zfKI4d2gpGGIi89krAY92/zsYSIcP96B7p/Q6TLinAx2GYi01v/IzaPQs1v/6Rqc/kDbP3aJMa+3i2tvvF+5F4E8z7M9huNg133rnUnU0S7J9M9mzG4pikP5PM0A0daGw0I4nwUXiG8Dx7J93mCsFtOhCzaOY6XWqYuy9O+RFdjxXcwz6c2cfzA8p7IkofeBag7irbXAE9dUAG+t5rXMam7g9isNmkO22e8dApNOLAX69e3yqG4BrOY4dnPUYDVO9xI0Cl2gMPhMghuzSbl04wZ1QDC+XEKVZ0Fou9+FNK37OY3PIcASE+929a9uf9+35aY8mu6c64xP69Ayc1funTzHFv//3jY5pck/uRzR+wDTMHuP8uZMbKXvHEISW/Jv2v40A/rPbOBf0b5FNH78+RxpnpEppfvcCKXIaxU1JDME5SNfpCGZ3IALAZZqxt4WDLb9ywZTICum/aD5J9ohzb2haMdYeR87w9Z+3Y6ihtoO4JXE4ponE3g4VJxwj+Onjzh/fcRR5vh9PAz1FjrInNfhoyoonFViJtQPJZhPZgLeM/q9oH7UukBdplK2o2N8JdRPBeNBDe/LYQGdThgPAsY7LB8rBIL6q0ahiwgGPYLLL0khu0tJJRYl/pFRPxdU+YST1YoBEQrudF8kCyN5Rbe7UMDgD4xaC9YvK47/cYCIKtbcs7gyMB4E9bPthfEI437gGS/KnAaTe4eBgcPHBXI/388fTckThvy00yQgugPoSX8lgeBFCTtp3w4bFe8TdJnRnYAKjSpaoRHuS9Fa9affvhic3gWzPEzQExFbJ2eyADeY+2zcs5FoejwyJYOfC1tew9Ym1WyZyaWfmUXTp7/ZHY4kAvtT8e2WGdhJaJKgAYeil/guAO5++TV5+gPr/Rnr4zNCaIhOaTNuNovOkNcdrhEVSCQLFidbnyOAEwpuLWJGQFCFoyOMmw9HAEe8PPw2hTgz5g5IrPkYEik1dQ8ETBaltcd+Fp3D0P1BSpM47KxqRFUBpCGbhXJaqOwFmdd0szfpy57Jutb2BmCY0kejj2Z0nCt7spJHBW6dRxsNGISlVOtm22+u6jwV6cNqMfGmfIez37RRNk+lkC4pmdBvz6VI9Dcm6t1sfiyFsVcuuXCtd+jfPi4e3jQXdn09/e/wSDddFNjibYzJeXjuSBCGYhubM8guAxn4bM7dz7UQ2QDMmuUl6q7qG8Z+7tmguKON3u21n/2aL3kf3QQGE9Ulbkl0Y89bGN40iSsLNf9MLTPkvEs56Qa8y/sp35SE5Al3cuUQdHSoG90WOw/RiKOwe5pv08DA3ad3eL0/GcxJnHsAGKdp9N2+zZX8NOF0c31PUSadcUNlzFO2d87HZTpOhFHJ+pHUY4JR/T1NNOMngUWuAxi2fjyNkQyrRx7dUuBJiBlkPBpytUiwAazrirWtatoKR5idIIeJK8NA7nthY1IjiaXhZdoYXOd4zDnLjTXiBoVhUXwENhw1aBpT5nKY8S7haYjVBLW6k+TOBKzrpIaOyYvNw5t4PjMSBY33fTYFoBsZ2KJ02KKyp5PExHDxnC0cG47iUlGtb98X4orlcABzhdbJplhDjjqaBC/4S244hhvU0zuReLy0h75ubqhQeHTaLbEsgu2YS62oHtlaSnjLA9C1IoAaJedJX2td7z7MYGcKY00Lrc8Xe2QYHq9U4UZgjfDVz8eP74AuOB4PONg4iJTyiJDBc4emKYfyJ8rca+pWR+JWdDJKCdgYtRSUwWJXJ1cZQG8do3XdE1tTpzPOY2haac8AQMqUNoJEmmKl/cMJDPFGizTTgxu1iBBKWDivXaMKr3ELi66TPmLd1RCp6zdGC64sDGOsdeq5APWgRvJVmg2b1Whu53IQzOqVc8VMw3OpwPG4QEbRmrKr5mLxuchoAKrKfbwYzjOnK4dPS+Gt0T9m4Lf+1SnZ+FDjV9sQ0JEUvsSik0mN4srPWESrDI1K9f0uDvtFHVCINOU4sRqh2fGYI/+J4+HnYTgeVKdVsG/e3CcRq63LHdIVCIftUR+eHp0wWosIdAkcZbmumDc8bDgV9W68p9mLyZ0vGFGOY6mWfrdgOSza/7qik5gxSeG29YHWuv1rWNd1pm93+gTH9YYpZMRYZpMJtgRkrYpnTxGL+lf5QZ123cGKoVlCZuS5G9AN31m0u+MD1bk4LfMzAZubBTzQCL57RgM7/69GJhqZVxOAi+EB31eXeyZzF4Zl89RQ32PPHGFQ0htY1P1dOiwSE5PIi8OZQEs2GLZNxqU9J6k9Oy7BfJ+f+b0hLe/N1c/aohQJJfrh8J8ZGNJ3ewY5BAs36XbuXgIkZK55YqzH3mCeYDxokEjQBzeO+PB8Nj5Er5nrzE9cSzxJ8GrBe/t+YLumAS8mKw6egR0xhejh6voGvAE72S5WBa5j8wQf4dy1mdnmsdlvBI3pflxkdNJdCTw7ubY5z42sK/vf92PI0XA/3vxuXVbZrG+gkNAhTR7FM1F094gagCeABgB4SQubpUDxwjqsHA6M30PS/yUQVVy/4Hx6hbSZhjmjfvIjBeejMPWXRt/6RkNhOMn+K6zZP5ZaUZYlOVNahgUrY9NGR1tXnNuqEYq9zXIG+TxfHt9Yvw1wkChfaMDnR5n8cppnxvH+SQ39ViqoqhHdTrmVlRGU0tG4BU9xOBxwOB5wbmoM9Q4LTWwGETTRbAKuX+32ckkDEQbqpw9oXzQahUE4/voBv325x4Eo6s8DHqM05yiYWRD/0ZtADTPPpHr4g1ymZ/+Rdu0ReeP6lM0ljLYAknxCm7v8+Y6ZSr9AnVWInOctaL3b+bCAHmvVHKi78c6uDw6dmDmsqKN1AcvrVufnuDHxnIBmbCIi1KrOjmtXR5suk+4rXtRyRM5LBH0QzVr2fDpBABxM/3fuDQOeyVEdEnW1JLJiDSAcAG+XitfzWR2zL1Z+ttXkwaeHJ400Nyc7z7zq9HIQad1wmcZz5b4FDMHdL5+w/u0eWVLwdjQ+2m0ZAsUzVdQA7ly8n5XjAF5528+zEatXUgesF2hE+ZM9NP7nKwBEAN172+pm7602lxvrk0XPL4vg0d51Z3N9IeCzLdeQbRbal9h3X8/feTA28OzPZ94otLWbx/ybOwG6zkKubOukqz8wuhiP4j0mtgxyCPnTgWAPSUyMygVtvJ2PNfit7w3EUqRN43nT/olM/ivg0lVG9GzBNpqt4+K/V/u/CPR9mxpLANvDsLktXScogjmA1AtoF13iDMwU2nbsNSVCdTEcmYr73wWkmfW5fM7Eq4uxeHNm45UEt5daY4w+8OG/fsXpvF5luN5eN49GVu5I9UkmNMMQ5kNH/bSoknJY7b/RghiRjZwALFWjkPAgNm5Gv+84fK42c42c6ABOX79qVMpuDQCYYsfSQAEmzBMId2BYmnERE2ooUrZfW1XGO5QPGimzflFyR6VAGlDqAoyB899OaJiMJmDe//cD9YM6B6iR5znG0KHMCH00BemDhP4sp+sBSD3fC+P4ccHpIY2Pdjuelec0o5WGM/x2reAdBM8RvRKR6PDIWg6jOVwJK+pZGpFGb64YhZCbkwOICSVEpOm6cEn34hyGQPPmS368OZEem6+bbt6UWdwDUwTrwwqNUqfdUw5z6V0ABK+bs+rpWlS4UWP5fK86Q6jjxDRRxjUyeEiDJ7iAN/ufZBBoxmQSAbfHW3ApeH19DoWMKvM4hHMRQeEk5ZhQN2RA0MGoECwgmv6HPhxn9ATTkH7pfzmbL9VldMv+vu0VV6qJRaEU5hQNOeHYDexTpeCZFvwMXBtReiuZ8SV4CYnbPBnebHsxJgvze2enH23TezGnrArBX6bReK/U2uPqCTMOp3Rx0ddt+8B+RP7O69RgXhFgF6H/ZzZXOHxblLl891v78L0xbndarlxzGKMrkPD2+P4Z2jSeu7oorddm2S55iou+3uCJtm9zx6yE12h/l7bnr0+IiOfXdO2QxrQfJi7pypu4H45P6crv21Fn2LruRezGXFwslasHAdqs0cU6kyqkaSRjN2DMneEdIOrYjtHRB81IcxmWRkxP8Xo+ayRiqVovNo03DAhO1BI+8yxD0kmVJe7MAnVIHENL24jIrA2869vXaVi6YnJ6BIA41RJnmjwETcVMbpE+3HkfzAgJd27cLqSv+oi09epk0DVSlNQru/WB2hpGrRFSF3XAzZAOeJ3iMec1BlDUsEuihqGKimFRSWzpievhAC7LlAnMuFFZ6/8SoBGx4YU4oyTcaS7zD3o+2c6sO+dthWPr1L7ZHWO6H7mBpZSiUd+muIKYsZIFBYJiqbgdxxFg6UmNrzb481rMCkUW5S+qACuic2BC8DEeAc9FizrUWjWCuhbbSwBWSEMGIKQ8JoPV/mUhV1Yp3M4C0PsAUdda5QLQGNPByZTcQgUymhp4RVN/W/0ACFRJV0rdwJFgLoArs0WUb3QnKKqtKwAAIABJREFU1GzMcaM9zMnDrHgKs+wJF5Mj4AA6EWpKBUsyeXuPoKZS1aDQnQfT6AI2/qgUxuoRvmQZurhgDLZ03y47csCRHTk1ZoKBsoAW5QJWDEA6hoX5iJU0oTjvsHNofQkAsdruMhRviPIJejJZeTpHMWL4wcpBgQu4AtJJedEDQxqD2tBoQgh4AA1qBGNwOItOY0lSzkY99MkLjqF9QwiDxsQbMiKSWYwX924ggDpkmNFoDHRzvJQuINFsDVZfwJZBDQuDOUpSBI8nyVnDrsGN7VAFNDO0pIGXfSjqKDEMr4vhs9b13WN0G5NFPVpmiD4GGB7Rp7jTeashLtdPo3Rm6IMc2HPuXOX0QjP7sp1ldebQDBMAk55lHb/WkKfCYXjSLqYxPWT4C+7L26wvPKOmAXRb25GeJV0fGkY3vMfRN2VDVMHN0+Dj0fmGf8IonEfkjkQG99NgiJBtYy3Tc9tAboIbw7Z3OQ6xCHhnDRyF2GcIzBkmBJdd35NOvt0inCTkH/HFcw7fj4aXYNmME+HAQUPm3mD7eeJeX5KZQeUazwXgisMjdvdJrHV+co53ft87m4nnoM3PX+kr9+c/0/63WJVLWelqpLS/S7d/++40dnfYm/pIp+xu9JYED9c4X8e5mRfIa/Rt4/kMWIkfDAcmWJ+dJeBPk8Jcc3cyDB7Fug/5jtRZjtn4ODu/rlt0pYievGvJio0fHOoIVQ9HrOfXySdCnWOGTP7ZZR3lKxCc1eVO+r0cpXhqrWGMG2Oow5vomNWpcDoxyegXcOmfYy2wve5Oq35efBt9K8j0Dfus+rkzYzU16IEnP1rKTI/t+zLG5N8JbkA/qkN56xDHk4gcPAGXIj6erDfwsab1NN7JedxPv3zAy5eHGKsAoXN0zOQU4bir6/yP2HzWxz84TNcJZwzpn3OAnv/bBDVcbaG9j2fz58jaBTOYu3wGRRte7tN5e2YGCozfz3RxOiqxlclig7Pub/PsvBdwO8eg4yCsdpb9XucX47kkb44h0+FUL8bNgsmvxne70+0ReRo3xwPa0+vMOPfmum7b/r6BraFO36vn9uA0gBnllw/oXx42MtbBRujlEsg+exT6IlqLPGuPO004uBbQMqDG87fmc4lR9bcDlIfvNGu9V6ix/cFwVEl9q+Fd1799i4j/4XaNe/r7toxt3bHQhYZrU/dsBQqTP7c4WwyLoDsyOvooKGPAocbhba+b+cfGpH99+z8DurVJOK4IEdEya6y/eyYuZjZdzF1C6vnZFPEROFkZwTO2Ee/bJmHA8l4IuIjwmm9JXt7XZkH7+9Ob0oniQWgE3BFBeMvo8kdC7x3nv51x/M8jGgRHvMMZ6kXFuEPDsyJN2b9rekACokZxtpTHJOhfRxDifm/RT4nrE1N4HY83wFHQ2mrebnrIGx7BeBeMevnE6F8Hjp8+YtwDM2J4yyq0rwP182EqR0SwfPwAjRwRrPeaglKi1vmtPb83pN9i+aCCvprvGxhkiggxJTGhfq4h1BBUYdfv1VuuPWiyFcELbn/5BUyM1s5o97aOTOi/DZQPqiztDwPV0gs2PKDig0GAzHovJFOY8fR2O6ghEBoeQSAUfIAarruqyFgZ/2GOCsQeKfKKECVsPm5ID2W0TBZ2wrcrDxKPktbDDcCNEAzIm2TCp7WBsrdv/VYLw3Me1w/04YzGy9cv2g/2phSXUp3wTSFQ1+Xlas/miz7fQwKOvBX65MAJx/fvAYsMHM8zt8Drw8nu3RkmjIFiOaLjBDcOgBSPvZ5fUFkFO43IsZEaU0vE5kyh51iNImSZAQYYVZWEVv9Z/xawJfO5FuEPTO9KX/aS7nFT2TWifXVf4yyPEOhc+RLRKjY/KdPoDNCsbeaK6fSOrbBKoYjK7yQIXJHnEcaOyydMTV9fFWItbY8AHgkZ3V4gcL2idYr1e08Lw1FnV983jUJypZc3Fm8DwBJrBWAqZjwG+A264oLsrmpGvDeiLN8cx7falYWH7P5q63JNFLg2oh/7+a0bIzDmrUfzj4SNc5G89cw/VUtU5YaSM6GfO6P/YSCaQkCOqlAa8AYCjjYBVCDgW9Z07jcAV7YUxzOHi6T/NgLLacekEEBHuoDrHxGzsmnc+alrsL03ol/75VLEyZemEd0HR/snArZkRmxBz8JgCQVE6WaUNmNwayva2sLQ6331iHLs6hBoikw3EnvEeBaw1CiqIx1jxAxLKCxsf4yuCEwZh6SYDX5R8Vjv3dAyGR0TiNWeZhSgqENTKFg2WhY1yLqxki3tnpY7EaOUjGEpsv31YrTD18SNRh4VLzLQG6PXgtEbugxUx5GsCtNqRnRfx0gpaOeDYBHdxlvNyHJGKQsOh2PwVENmtHspxUrpOM2QNF2yyGKdyFSo6/+EYcrIYcGyl9AdqQ2R/jlhsf0vKTLJlV1kazNGwbLUBBvqRECdIGPVDDj2ZrURz+wnBE2P2KUrjhgDIK117GBRaoW0rspoLqi2hrocloEqxtwREd2lWNmhofXszUA9pIO7RlmT14otlrZ8AGCGUMWQc0TPw2uYwlKsmnMAs59I/ee0WIQh0mJBCf5XYToyMzj+IJUNBhGYBCDbbyp2repqedYG71dUZvKMTWSa8MJFo+d58ruhjBE3AQBUSDN6WKmmWtkiwoFRKoZFP0wjONToycDNcgcMtvPa0XoDjaYpci398XRQtExLSDUrXaEDgIqlgRf/S8GgC4Auok62A3quV9I6nEdSjWATDOoRjSxQQ7oA4GGZY7gkvs2MCobX1JfFHVFcrtLsAWhu2BCzp1Ecmoiy3Z0rCUPhNJrAxn9B89zQlSim01A1umjdUc8cBfgZsnUtNQznjqtba2rkNeO7G8nFIs31r5dRMFzVu/u9h5HebMNG32kTvXbJNGPy1RIAb7QDMzV74DTSLCLGq3PRFMLEDF44onXgOF42rwJi3RNWS0sb2UCs3jaC1PkaC2CZWsYYRhskPUOBp/TrxOkere/yr0sbg1UyLFSCLpH3n2rJXzAbjq8lwH5zj8skYWZK8Oj4RZzO0Jyj8qC2fqYfCIP5FcVsqnox320v17El/m2/6A4nCb592zIf7PyAEx0xA4ieGcSOqvxsvJzpOcI52FmHbhmzPI1/8BKXjJ1DyZzPPEuyG7eOS5LhMT+b5uzfdkdaBCmL/+RIfd00Pbzi+YAHO88Agp8jmnTfO577HDNSnE6U3qNrQPFprsiGC6W84ZOZdTjM8yZK932TS94114kO5y18BSXxGuYXRR0z2EPp4VxbwujdsrAZLArgafZCxnDL4hWcrKUzOrhWdSo6nw2fpxvJHa5cBp5duV5tHxM41S5kZXcKStEsRR7U0612uyV00BTuQ+lmb83OweWZnBPQwbhTkMtTOYsj5V12NEOWxSW6zncZX2q/MtSRqRiPla2ShBkBrAbSmcJd1oEzVohlRjpDI5cXCPjDe9z89hVnEZwANBE7G2JZeRDZlNaHJ81+FYBIaF8eUKD6apZcQmTSX0B1iVX+8Y3oDI0+vzVQ/Znoc9hzJYkY3nduezIzlKuJI8Lpvj05z3AvpHXsbwSgRflfLgwmdZz1MgqePaf1jtuDZopqnnEHSpNFGOfzGSTqECsyQIsWwupn1Z/f3BxxPq949/E9zi+vgZu9bvTkt2RTfiTPlpmx3Gjmz2YR544xD3VJvDfBUyJ4H4UZp7biUNURtZizqVh2MgKhmbP3NUjba8NFBA2zfJif4RVz30raDzG92/E/NCPs6/98sfuUBzsK4UyiIVcEfBQN7jzT1Dp68iV3nvZgyUHAzQD4F8LLVx2hp3L3kyfQ7MI3hkMaAR8+E/oXnVVLMOWw0iFmRLfU/7biBcB7Q9UOd55uniFYQFj3uDrW8a9pk77a94R3M6303c00U7DHoEkvSPnX9D7jMbooDHiZlawC8ecLV7TejLTpaN6qyf7WSs05+MB0L9oAqAuIZ4mx0E8Yn36VN/0Xa98P3tH2fwZ0R2RJaNnIL8HNycWiZrhZxJHbM4g+XzBcrvAcD4KB58mcQ7LsZ7dnKE1NptfmWxt8GXHjB2Tb+/Vn5zgcYYMumUHlJwWH/1jw8r+/4e6/fsHogvE3ZcdXM5772/P7zl8fsHx8Z/KAp53OQxVTpqiwCbH6Hh8L+sOA4BGEO1shQi0V63mdaRhxq+vUxxS8BZDfoLXpriCSgneonxd9t0AjO8Qi3+87Onm00EsSXF+nyONIUQgLHSwlDYN6x/Kxoj20YOB99dmUXGISrdyrCtEVKcBLrBFAaPeens9MVh81LXH/qs+XT6b4fbr0EnJmWtO9qCKgOHMqpvbwOdCdKTF4vp8IIDPwJqHf/7oRzOFzs51w2c/QteQrfjXBAO33x8iRLfMCNbL6ed2fnTy2n2kbskewmlohhm4YyT1sT+jKhvGMN3S1pszhPs0CtvSVflvui0Ho9GqwSoBY1gW7puugf8eT1Qa7ZciT1faBRuYQ9Dy5MAUAA6eQfomshqpNbgyHSTcmTYIOmUw2LDrLI9+YGIM7MLoZ/D0CPdQ7b647vnFd3rj2VouzRtNQUpjRx0DhqcByhb9H8riwFmfgjbH4Z6IZwCH5Jls7Zw2dKfboSbhy3nu0iAaL14y3yMVb80rNM8e0zShy+cS3V48Sw+Yw9da5jIiAHzps25Pi/W6UrbiGG7B5Zj/aP62F8p/2P397HEl5sG/fWuk4S5gr4xGi+/t+BN5zuYCfbZupXpn4db2N7AY4az17pIYbwSx/2AXTTfbbPKsFgom35vu/vd97gcU/eT9+/YIv8brcyPDvtErQRwcLT97Qe5CtoXJ2uKcK/kv63T7+rNuIvX6z9FoX8u1ooOmggIA9+4Ihmipy9KHKjD7QezO7wnzLjFqa7woDclGf8il45qh3iSOiqW8RWUDcAN9dwVIoIhe8H38nkQrf2gdtYVKGGkDR1cjmac7huH9oPXQblxu1AWAIA6z1kokIPQxoYsYjhrQVQNlmcDEjg0Z560y7RXKua0OtCxZTrnitSwImnTEFyxhDo0v9nxmJ0Eco6MfQ1ObuOBuRmxcSNtRI5Xuc+DIxfjPoSYIH5qrR2XYtMmW5EYO0Y40+YpRaAFIHLjbjxBCNyhferlGtDJEKFIJ0NVDL0LPVejMFcbcan4o3ejPlxBB06caLzJTnQzjqYo+hESrDorbW9axGcDMYDuNLCOpgUW0ODHVQGAIIFS1ZwwK2NIpjHSAeKFyNB2aAVbbYrA1U2T2oA44rnBab8UYzzWp0+1RGpAIUZjAKp0o3DI5mHPt2g4lSbhcBZKhjwGABhjkiWD9kjDK7sxssDXYhNegxq4NC78C6hhEw0Fkga4+un3OfdaEpeMYiArH07GKGLYYaqkfCCXq/RzY4TlHjtBoUjUsgN+az1rtNchSB0buYY7U6hKjnA4Dj5I+FKgpDzzQJxtpNKWbUoVTUWrDcHAGu0MSYGm3PbDyaLYj+0XEWKaBF02v6cYoSBMyaJhQCd0z18wjn8txJaZgDqwDMRZ0k/JwLZsYke/eQWa9wdEtbPIZFekmkPE+7N+sbEkGsznm3M+Mp4M9txdkyjWQHH6XhNGFeLLtJoBCyOc1xTopMCVfaL/HX/rHj0emwwERA9T1UQzoIoELT0ciceV1OC/wWZNprQovBrkefa5S/ZYqNyEdx+uLGb+tKRld8Y07FEHV2BVFkBGiAGeDENKZ2RsmcOoLp1XNKY5gMnpw7xZyJhmeFsawnQjpmuOOF8f5RYsMXOyakaxYGVcvuZple1AEMIBrA4ImrnO9PxDXz+mrDm7QjkZCL+7NsErKMTF5g3jtiH2Dz0i2Y/IQ7QeX+xXCDQGE+s5bxCkdTsccDnt9kTAQ3pS1bf8Q4h8H7pKH+gMvT2/nNz3OO+H4Tlwcs1sttpfbecAh0+d3ezXAegUwHPvUNNNLcbf7TeUBSTXrP/uX7mBy7afvXV1h90AQeCXfJdmYMsLuSeOw9HAGuDzXJQTTro59FAqEHDhItzdIb1tcTmhug4U5qWwMqkckX5K5IjtfVGQYMsBQtVwHN3uLOYqVw0FW3hngCAvK1w6TpEzfZqIltrRi1VJQy+UESQbe5tNaxtoZ1PaP1Fg5qzOrQlx1hLwREJ9NGM4I1DJ3wPKyU1991HsYfl1Q6yYGeiFBqCb7PHTM9Ct13OzuGqnOnmhjUKKh8k2mV7Ldb5fk+3IG/PsZiksFn7x0uKzEUx1Y4PKgxvkPHP2FkQp6f++FzNCQyUtoGif9fQOpugX+iyeR1Nj9fIAXlZW/Sz16H+o+0/Lyk71usNSPVO4CzK1uhAXAeLWyuYcFFyq6vIG9nQeeBhZD4b+MDyTMWqCOxO48Uyx4mIiiloI+BtSns9z7QO5SHJcuCUAqON4p7Drc3eH1+MT0fIEJYu9YhDwfw4PXsIwGJW9CaAqHnHbH114K3dJ4S5R3DYZgYnuDOcXcilfFspk0bgqJSZ3JoFSwAVqjDyQFzL/Jejt5n3zR5zfyucgWMbUlREhkb0POyAqh/U56h0XynY9MXqJE9j/7+i+BODDf4uSJMHhGwHLpzbDmjqGA6juRyC+2PnsGfaG+d/G+dx73OCgBCty7Z2e56L2L8fxdCIYqsqKp3mXlNNu8gskxmhseVMZn6Fr97gwgy3zLH7vYp5wPckZUtmxv3jibdMni1gPO//+7847Q/bED/2fQBf3b7vaOYjE1i8U3w8cMzGfoJkDcSrMeGCK2ERPxoMyCCKgq2StfpXTkgqJamrLlXoxmyJqNnbxJniBz1ZJduEw82TNVuZST3l4jgjhoSv0PBE87pDd6fK/oEwPHXT6EEWD69x3qvqXROtojHxDsw7tDxhH4/sHy2CCaYoDyAca+K80oV8kAhGBM0FdD4peP05Q7F6jwTEQ6LprTErxYd9MVSNZqRjEpFg0BYjfC1fgSIsP62AgIsH9U7X5GOMtIyhhqm4ULbi/GZAsKdIcWTEdbkwUu3uPnPIwCLQKECtIGbz0esXxrKx2qE24Q5InTxCJsBV/TXjwXj/g4CQTufVBEIAlFFv+9mXmCMj+ZkQM9oD+9BNFD4PQoK+n2HsApMSqhUGdzt3QJ1MKjktbDEGP+KQmS1ZwiDnue8AXRzYGDcQvCySU/j5yULu/kM+F8nqrFuGQ63oKqI3GuDAjF+9z53aH6bCd7C+7daxdbjEkAo+eO33blWR5P3aHiMMS94jxWPEBEs7+7w+vA4hUZL20kMSECQvUs0uspXg005wHyDQkCXV6jRXZWlJEeQMAS36M8dA69g0X3CAORmRP/j2WpeutdwoCEJbz+nnIUq+lg1Gjwp4rMwXZcFTITz2qARFQwqcw8c6ggFJAVFChpOyJ72et/WtOWRGmwI10V5Fyb2SdcudtZRrwn2XEqkBXalSKkVN7e3YShSDdeMhIy6kyZICCaT7HiALUXqXg5yHaMrgnRqKbrWgJXNyBFTdwcHsvMxTMR0bj9mPmFGlc0CgKN/NSRIvH7Cbma5r69fVmyQjetSLbXtwyN8h0e4Obz5fvJWiRvQTimax/uSy/V8k71IzKikef7+JsEs7pVEfv2PNYduP+3b3rEzpIzdPL47K6LNcf7ZVfjuMr/RxP63uY8IfJMkSVfMIg3UGPaADwVo9NYQZUFE0F/TOXpzBGqMgHCGXoyX697f3uq7gvbs0cyYynx/XgTUhhpcqG9hka5QFTse2WCfUAAudnZP7KDKbkrPucJTfI2vvlTP3xTadzftlKCaKndi3dYHejtfPEdXCDPzXB9JOFr6ZR2ua2fSSz8MsYhnw6uFi9UD9shdz3CCgBPnU4Y0VBzm7+TGqK5GNxpYSoFYPToeEoYPVxrr/C17Rx+opaCjB59uSA0iAwMD0tTwstTDhGeatfB8kcZQJ4Tz+YxlWSCHgyp7jkczCo6oWdxaQ+taZ5OZsRwOWEw5xETo3NHWhtaaKYdKGHOJOaI5VUFlTp52Xzasj6ymiC1xWqSwwFwA9ghvtsjJEZGRqnAcKIVR6wKA0Ea3KCSOeQ8aFklaLN2nRosvREBnNDTI2tCk4bzq/FvXdNFNLJrW5Ilh6eQ0QtfKCcAU29RRUJTeWrmiMQZOp1e0rmOshyOWpdrM1SGuloLDonIBuas/qdqqcDHe1XiFaV2bfMFQ4xb61B7186p8lckcy7IgJLdSwLWi91UVwtKDr60WRe98iR3f6bgntrdjGL8hgadcKRI0k7TuaqTqF5U/SACuKjvo2TMzujn0VtbI9dYHhqyoHuVGmGm5gRmpDC9BoOnYJxZxOXmgrQSMVVOoh/QxQDQgYobZwaZoX4E+02IqjRyaOh9QfpgIYHUqKcOudTGFK4FIU4urYYUhPCBFDWSFLXV5LaAV8FrdrQ9z/ARgDiHLzQ1ubm6AUrXGLti4G8exlqZdMMfKhIIaxhIiwun1hEaqhC3FSggBJnfB5FOLGjcjerdzxiAtQ2AZnjgK7qoRoDWNRhy9a21yg0fdc+X/egeoau155wHdaad3jS5vTfFKGCoNkM6nM87nNYztgMnnhaEl2j080pV1iY5ng2ecAEx5g1XJPDNrFKMnlsHEWIbwbfXyDKTOLjAFteI5BpWCUllTvDMsw9uk+epcwyA7c7C9G6Or04Gv24DJlOpk63i/Wwk5TaqlsjNzn2tiNDQM+xCMNuJQOj8PKKwLE0pRXO2lGigCCJxR0AGN7plOLDLdssSIGUEVKp0iJplrgqedKbYAXH3OawxjiBlNGMRJL2WGqUy7fXxeQzr4uhiwnkN/p2S5IY1n02FEG6d9SHvkRk79YvqEaWX3zOnmSC5oVjC82J54rhuXGy/q2ruFwXGdwcvEx9MQPXHt/C2vzFyH/Mnx4X7y89XOaviCuHI8suAJGS6k6dgO3XePButBO6wMiyvqDZeEDDmXDttsTwTiHr97KRiC85G7/XZeOWRTg7PE17ujuEvvWa6cfXgqdliGFO+CkI4WzDIKIZV/u5d6oemwN3o35yrHqe5gpMp+MbiNrDSx0mTn1J0lCVIYwILeVhRiS0ChGVzWISjFoiPDKU/Xuxs9jbISxlOV6nhO8dQYyutVVhwPUQPhGEPrna9nnM9nnNc1nJiIGctBM7msrU2gSgw6pf8DABxPJhiO+r205d81WxBCpimlxDnSzEodZHSpFuUXQITCFCnoo0/nmb1v0kjcYXy98xQCNQjSR8L5y9eIkl+JIQVaTsP2cJhR1TMHJTSA05evGs0+9CwsOuhYjeJMkpXU8FCOyoio1jiC+0aYctxPNjH+9Coi2DWP5vXG0CjfP9I6ZrIFgdqJ7esF9lLjefoBgjOR6vBFsNL8/QiTA7fHGmvTVS3MGChYaSuDL0vdwN26roEv3Al2XZvWYRbgdG5qbBd181GaDtw/POH2uChsEmE5LEon+tASOEYzCpeJvyFWosZ4IhGUw0EdSNdmWXiGGvULGa+gOIwt/bxmUyJUsoxnhbHUitfXM3pruLm9QT0sOL2+Gv+muNrx0Fxvxb+uxx6AZmN4dwt6fMFiOpDOwBFAk/C90/cOaObiL1p7vNt5LaLvLKJR6Ccz7NRPjHZvOv68xbZvm/T9ohHkg9S47tcVnuYcXqHGbu8DULuPB186BfD08R5wdfyFcP6i9OqEGXbh73ghrYeO1MdBgAWqGcqBNy+/83zEnDc41Jtj0UtLQmTCcm4oOxnHd4I7lE2862ff6afzbEneIQr+xvmZUpJD6WCVbQjhZALyclykAa69KZoznhxGkp3vE7iMZWPxM+f02fjvAnW8JVYb0GE5YLk5oJSKU1vRpKO1jlfvyTLPfh+7/XXtj9igMy76mfZvHIGelLrGHO+hwA28eW0dEcxeFEEsAlTcoXyaqYGjH0yE+ZaR78rw9M9GUTsZpjcf+FlI3nXd8TSFml3LiCQONID28BRM2EG2nsZ6t6VPF+dpBsaDgD8pcRr7c2D0eflUrW5liZ70zGvU7nE5YO2rCRKGCEoFSFTZ9x+6t+NR0Cye/vBByUitJZgJoQICYX18QK3vIXhGJQLRApEb9HWA3+vb+wNB8ArgBgtUWXP4WEEWgUKiTGcpZab5IJjnnUTqDRfWtoywT18RZPtNFaj1U0G774n95xi7b5971XmkVDfD7uxxKuFgf5nuQNBUkK4UCZRPhIr36DJrDHk0vp8dZ4qJaNaPcWH0J5BbBsUgeJ52U2bk25yN3nnVAwx7w9j15pUq/U4999bX1kdl0wQI47k/t+IRBbcY9Iz2NHD76RNOD/cwsTTeo4KbMS80vwfg+7rClUy3GLbuREcbjwneAhCO0+jAADoF7c5z24yfyJRH+t1TiIPIUt2y/W6GLlMUcrE0s0nxGalXmZWBIkYbHQMDCyoOuMHZig8nUh7f/dP0JK5wkWfD13+jOcw63vSIOQJtvJndo7qZp2o8bwY0v2c7tkyst9CWQYwIOzhUJmZ+zh3K/GvCCcVMaffd/+ZsFrL7x5q6NHmBqxD3/XWLEXvZByAUY1eB/8ove5qRV+vaW0Mp9JMMzPUIiZ9sV5jpP6u5HnyefS1rEPjb9uln6XfQ458d3+/8/XtjiQjgK/zLfq/Yo9PhZyfBDc0nf+DF22dvGXjLiE6E9qzGwtn3NRiXwIcum/itWfFCF11cPy+7nt84F5d3/p6diAikHzgTgUFIlWUBR5QyGeV5+w9OI3bKuGuRa5vfxenE9j51XlSFopAZhax/V1wTqYF3dMHgAYYpR2SmU1dDu6ALg90ASDSjC8yAIILoN7hymXhbYVijjkjUaEfGr+1W4hJiRCIauiVj1eXvHa2takwyRemMdnXAmus7uiZYdAWtE/Zr+xyp1yCmiDfkY2YTCno+HWLJncKIzbjIlt5PQOS1l41GEocDlIhG3Q+D51JYDUWoIFZnM43AL6aUJouyLWhNU4m3rpFfbe3oTaPSqU9HLAhFZL6jUnRcAAAgAElEQVQbD0AIflNE0EaDQI0pbQgWGRhjsaxSGtk/OmP0glLMMMZdDYNiEbld+RWiWaJA1o5RWY2ZZiRs5xPGesZoDW7Qzv88kkvEUrMOj4pDnKeoEBmTgco0AkjroFrhUS3OFmb4C7Eh9tozQgCgApihUqPizcglmnmKPeLReDmmYtkE1JgpREAVDNtl6RYJ29UQjr4CWACvoy0+tEnhNApbYo4kAJeKKmpMxPC4p1liIKTLWo0m6hoqLijQUg0MKdMAIkONq0JFa4R3U0CxOVgAoN4xRoEQo5PiGM3oYIYscjxIcb7ENHU6N4vy7h6HZRFHFjHPfjg445Akv+Tp+X5JWhtjDpiU1y5E0ygPU4T1bmW6EJHjrc8IcoFHjXDgtHi/KVibwbgb4iUpdgUSmSAEiPTtgSuROvzBJgKtIW7Gov3zW/q3ZYDUMD/5CJcnVY42vGeKPyLWfLV9OloBgIq1is+8tAGbowwJmzLWsxwYPM0BGIr1/VI+2vn7WLUu0ynco/Y9i4oARANEAi3boD+S8xXWB4Y7npvDEkako1V6NWxs4jbmuJbpVl67RALAbCTQ5Ga4jBLiyFbK8J3If+eepj2av8Z+z7+y2e9Lyql/B7kYZL9lWSmtk2T8544SifaFPOaHJr1LHK9gztvpp+T1E9nML0YyEdzkdeas09pc+55/m3wVyZyqmropOvV+w/WNPDAmzS2vLbmL9dytyddMnmaO334jCpjWi5qnMHGGgaqCz/D9crrl5yPkVcOLrrO5aJRZsm+2fIvZEOwMaAdi0a0RmW0dZxystHMLswLMkglIDmwwp8y6oKPh9aRJlAtj8lzoEx+BLFeJ4qIC0rInotHXpRBA6pyHtP5qUGuaUUUEXdRwuJrhvJuhXPLeUeILfa6bVb260rGSbhQPOCBAxHVpqjN0h7NanSYLeh2zXEZurA6JdVms7BCpwXsMrK0pfysNvWupze5lQWSgiqDLDc6/PWDNxqa04wHPMrXnbjwjaGRut7Oyz07h/bDcqSM2HjGiTzVAbiLDEpILmebKev7Z7Vamo09WM+6N6X+07XH4hcwC7INS467THp3avX6ktiuup2gA6qRmgXauU2q9h9OxQJ01ZAz07plhYBkixZLACjQARTOIMTwzDOH1tGKpCqsiQeB285ozDwcluDOJ0Vdz/vbSWGxy5NSZ6TOu63ReiGDZNo1PIgCtrRco+kInnfBvvtYA3DCjvgPweFnOsts9FYhQpGxM1nPgJW/VeB77di/OnsZZyeB/tPVRwzlNZ0/MZ753Hvz+a3qsilkaoH2ZYz4C+EpmME+8lzvJTMO9rpVHy/t9R6O3r6zZG14prfmVAf/Ymb68a+NMd+WewKlwtOz8/bUWiGYru+8PqfdseHjS74mj3Il/Xa8s+jdb5ps23B08kNid/WWIpSlIGalojl9Av+/V/0Ltpw3o/yiR5z/bgrHa/yjX4diBbG+HGEQafT4EA09Y+HOkhvSO1PPOBaLnhNQFJxPcusgOjLfvvSR/2xEy0ebqtc+Xk81v2t78yNsTcSv7/pXYqQeLpr30SFYBsNp4lswIiEYyC9R7dH14RME7E2wnQUmiKZbP6v3insrKSHLgp7WdNfXRg0ZxHz4f4HW/vU73YTnos58BDGCpFSIdEE1fWnjReVlOJq6fTUj/DLKI4CFPeO2CQzkAAPpHQrt3pap5XIkJ2wLUWgEBnv77KdJu6q5rbb5SCsa5mbIDGFYVBJv9FpzvtfA54w7j3ommGlTbQwfoOe3gi7kHsP33DmMHQe5xpPjP1okKbv7zRj3mSkFvK27u3qEw4em/yTIivgfwZD09b2CFKRk9aUZbOIHP7UewRoY8J97X+pqr9Mebx88ttB9DFljsj+TzOT8zbgAiNNF094R3AD3j/HACkFJdGYFVRfD09PazQ57GO8byiuX9e7THAaHjfCu/GsTcgFUbjPLe+pIBHkB7HlrHno6mcJpGO49Pd2W6GyKIOgotEOlTiWdnqVraomLClNYoEn/cxmvCCzNIhqagR4/rLvxMkRLI2C8E3PAX3q73t5vO32sjZsFPlXjKxr2+vNiYVQFaLaWaRpmZ958x995vMEY+y40haHr16/mazDagJ1Kvjs0cuilkS+H0Doskt0UNZQC5MnGOQ6PyOmY9ev3j86+L0qKX1xAxbbgOXD4+e1+qDxh84BVmdINVsvB57Xpqlwzoz/ER7tymSuwrQsrvbk5THZZdHNzTye33Szp9fV62rah0QLlhjBeB0ALBCrKz/yMKJW/7W/nqXX+/NnEgodyYt2ukMPSbpojt/4tVE8MPZkydUS3f3lkFPXMmE6C+LwgHM5o0YxOFm568vl8CORtGOjpTSNdBNWB/208es1+ewtV89qJbMbP6fpgX77syjv00vtEy7opHwpB3cdgvX/WT/L8KZ4DbU3wMQySMyDIGkOiKPajR6kwAq6KuE6mjonUmMCMzFxAPpYlJ0KThOBmhEA9O0/BsKUXf05qWxAnnDolU5Q5VmZb7+rmeXQ3eHb039N5UsQJPR+hG9RXruiYDNltEJkClBo5T/gpR49jpJoezGyyaeg9cNjbz3mHWlNRqEDc+kDQVMjMDVjtUoAb2bvtBYsZmN1jRhE9N2qTK4CEWbStObynm5fxwsfSlta6otaL3xdKWquK41RXrmUEroVnUdWGgiCp3OU1JrN7mGEb/LDJaSNdezCDPLGCuWr6l6D9XAmhwkGWAMiOxyhodZTlq1BoDIlXlAyj8jhxRknjGOIaRBhWp3nXeG6O4ZrCOrRviggSkdzMUmvF+ePSbhW9mhthwpcsjw37zIev9Qy0BotrjiJzlgloWi/ISMBWAgUKEXkzpzQNjNDQMjDZA4HCE9nOthhNH7a5Y8ewgAEizAXEdacyECKuR+bUsi6YmJFNsDpizBAO8hEH7fG4AAwdeADKFDwTVItYhKms2QHNRpqwN3Qbf0TWFriWXZTLFrmUjU+cHxYvBk4nA69KzsNYshqBI2WWIi4nqtmfjo62VVgbQyPk4N7WqMcbPXW8Ac0TyiZWKaGZ06b0rz8+smS9ENv8czyouauos0pqt7XSg7b3F2kZ0ukcDk859y6nP/d+3IFU7w8/+3AQvYHMVsb12loyTM4GwW88nvfLPQhY5JkFbIVA+BAIMdfwBqUEIRSCtmxMzJQOlZ/KzGveB4yfNcIcvT7uJMbR2ZSBG40tInVGUbJkhPHFrQYdEVDYZXjdd5RRVYHY7wtMBJ0qgsBev4wCqqMNKCGU/TPaM6zDua8ffTyMpTbZGgE0e1g1D4It8jR8gZCvL5g5yedeM2uKc3PwrsR+A16kXG9Te9dDpsJfSCtDi7egyjs48vKLPzG/MG0Xm4LPYlA3R87l01q+sCJDpAMUIjAsCmYObxDWFNU7fAXWKiyCMzWy2XO3+WjzvfKqoc4vzEXq+B0CWuSWU/HaDZygp1Xj0dEYSv7XlRb7PK75pa9gvr/Nq5Lweg4aAimUTGn2b5tyG4qXUpmEoIG8rCViGEne4O9QFIX8LaXTrRaNZ9rCY048AXEuUpNA1Nu3mAAQtNAHKtypPuJqh2TOAyO7gMBQ3vrVcl0MzfjIJH9npNfoXQi2MpRQcSkWtnrHGcJbhNn+GoA6CXDTjjtdE730kY7mWhjq1hpe24gUdNzJw+PAOz//zN3R5inN+NhxoxSTQsZXf/K3esk4waJPeaHTYLzyDcIsi78z49vQmtvp7t4P4/ltaeiCybAJ/PPocUOP3UVJKbEdPu76/B08ZtwB6Xjd4xsHUS81wQSfLMnBc8LpqhOxp1cxTn3/5BAhwen0FRCIgBwQsy4L2/GLRs8Aa2c0EYMYC4Gzv60Mwzg0f7m71jjHAMp3PvAY5W4mY8zp1iiDg4f4hZCwidfQlMudBSyZDRDgeVH6JsRgeOa/rpj/CjFIvSwW3ZrRgbNbLqbbjIIfnh/tHAIQDTaOz2P0ZV1XDAVVmhLcAmiksK6itdZpnZb+XgPZx9+k9nn97xD1JRJY7D+XqmKAEmaBu+lO+PzJQJrahgNAhOEMzRZyNa3FnkQLggw390fr/5Pts/25AlkVnRrsDwO3Qsd6KzvOFEAb13PZH6so0tk18zb53p+sj9duwA7HJBj25rjh/F3thXrt7nkXl6rmvo6u0UqQAIoZ7E2xbY6aQ+QHP8Dq/I2gBLNOcOxfZ+ekNrSv96n2ETOA2i232mX++9rOBW97+jSPQL1vGO3sim5FfXvITaXoJvy7XHoZu1Bj9L4O1a0zzX9XDBglbBHr7zby4ECgies1svsfgiqVrXz5VZYQiBTCgyUHuALyglvdKfIw4UZJgvD64/jRrFUXtc5W4Na1iPUBGQ6GiyvqurBoLgcUVWQV4Ikh5ReV3+tznBYULHv/3FQsB1VJWMhGWXwoi0kegKefsMxnlYXhl65lyQ43L+lycXyKU8PydDhEdt6pAg6WRSXukhslbEF7Q8YSCdxC8QGvER3yQvT0p6ULGMUMhMUZvKAeNYOblYJEbhEJFveHxDDf0ML0H6AnAHUSeZpe2FiQ+N8mvi/YWpGU42R8hF2KaSkNTCIhnc+qwfOX3t3gvkeEEuXak7d4bm88rAEJ9X3Gsv+D1yxcQ3ca6K9ORegijriluPEWtvciFnqhN8yTzfgBDXiMibMgrCt2m8RmxpAJBT4Liap3POzXlp6fzmx5x+qeo8hkcadBL1YQ7nnY6UlpqLtVQwDOpUxBbjVEaZtQKaUdTx+8J0HbPf5+gM8Hbo1RSjS47e2MY8xGpHgXUtRYoTJmozDZv4TR9cYF8M9YM644TNnORzbfJbr4xF9K6mr57+fF99xNepxCC3TPfax41EBkkNo9/nzYEY53GP68lepD4rW854W3mt/2ifzeL8GdS1Z+jpD8Kp45D1Zt+Shf/xDxoNKYGwkFRDPPmPM6zk4mQBL80wqDpktuPvXPDo5FFke22cJpJ9/vkv+wI4xst4+ar3fiXULrrhW/jsWtXLxXEl3cKtsaYFNkUR0RCCZal3n0E+PZBG/MbfQNz52Yq0HzfZYYBf+echdGE/G4gjFMMVWAo7fCyFEOVn71isEWnwzKKGOPuNJbRwVYnu+B6m5F9YsLjMOPEXAuCliZxA4NHMPos5shtZ0wJOMbQKOqmxi2P7FV6Ca0xvK4WpaMRzKVoqvPePC39NMAFD2F9s9fhhRvBpxFC/K/MaPxZtRDBOyk/bcZwcwy4hvnE1sKPidiNjsNizQga5Qkz8Vt0bi263x5JLSBUArgQiCvG6Ki9oa4L1nbGWgoEU1E7etcyNZLST3YBSFJ5EAKZwXLIgHRBo47eOrisYbQtRKiFLBUlab1sNxSSGWgi7FhTlzIXLMeD8gVJQFSDJencoMby0QfYzLBk4xpm6MLQ+KdtJMPEO7qEun8eHcOe8tqIpvh5se5coeKRmc6PCTRlJESjbDVvrO5RsWht7gKyrABontmALSW/RdaQ2tsHSJ0TyOZqf8OACVtPOHwwMAidAGBAQ4kGpPv9/k9hAz4Xw5kyCNIGuBaM3tTY7YZFKhDq4KopO5fDAefXM3ipqKQpfEGEamlzAWCMDoJgjIrWCrhotL3KYOoMSjZ2sb1QuNCFHpbKWxVI3QIxHOFAYd3WTbX0EufSXgHPzsTGg6pDj1jqYTXqykgOthsy4khnGsS9Bnoz55xuRvGS0+kGjptxShF9PvSvOmPMU9/G0JrykG0ECuacXc7SY2S4cSOPvZFZ5eKnHRMb9D+9T4+YpiS28iGBsxga7ckcRvIwBkvim4dEun9mNnOzRt5y4UjhjiiDYm7nTKZ19nknxw/RshNBLpw38NzTAjtTBUxaKkCzLijuUgO38zzat5fC8895v8NgK4Z3yRwjZBpkAz8kWuQ0IiKoxQ3riSeHObmkzdhnlBEvKWgMW4YxMj1LJh4Bw4nHTQCSfpp8jOOAjazkfcRwJ43bNJnnbfOzWdQdJ2faRb5OvmwigUtDVx18KdK9Mg1Iu3FI2ow9Lc2/6VgYm6kByF5RgT+IUvrtmcNu43yZl0x8hvOCO5XmwYRewPHDJpxRzTLu8KEyvZtgdgeZAD2MnhnN4SPn2/MbHW52S5N+cB5jPx83rkIkyjUAJcHFlif230dX2ns6N9zcHnQUdk3PNUGGhf8EbwRwKRoggJk5SEHdmaVJ55k1EpALo1TW883FNzpwkliqXdhxjDTlvaMZPu+9W0DKlI8kDJM8d3IPYPm82bguVt4czpXF0XPvonQBa4ag4nXa2fRLkx7ooGF00aOGt2dcDZcd53XF6/mE19MZr6NjHaK51r/8prRlDDQZ6MYzARphu9lDct5U13CffjoD08ZYlfZ3/kBhoBZoOVYB8Er7hfz7tLO99yjkJA4ATO/z5zWnqLT7LTdjha/Q6G/1uX3gYvlh2atOq+qqade9fel9oFTdWZdXh8OdwWaoGQGgEtCM/jmtSrQBMPrjL8hsxl5vTA6vglpcTziPba0W/Jbo4XQq0ns8M5r/kM+cj2rqNWRz3WmP38GOHEjPeYGWGsi43MfeAbxi5gvxKO0TETzMKu/HPgDNd8/Hcf7tEQcB3hNj0OTEUoLAOa80Cb8nw9k1eMsswAmC53TDnQAgQpHp2Oo3ZwrSISggLL+qc8bL3/StQ8mPGc91NX9Penf5zjd545o3sv9n+9S33pWH5nh649QSupWg9hrcZuuk+Nt6M70Xc4lU88GfY7t+abBGgySYNQFPftOe9axbwj10MJ6BLo4AfXO6/9Lthw3o/+wR5z/S3iYyyQszeAVnPl03cWdGRgQGyfXSZAj6/fSiUwX6NGpW85IPVReFj2iMwb/pGdLvnjB+e2xmP7Jjz90DhdIvefa0+aZtSYej4B3kfgCfGe1rA/1ScfpyD+A2xilQz6hruGbgFcuHO6yPT/MNApy/rhB6QcU7EN4jKn2zKhwArafoM+u/dQwaOPyygEtBkw4C47Ac4bUcyfLMaC0SoCxHjKaR5whkxChFvS0rM/jXAnk6gJlQuOJgNVtu+CNQXiKFpKdJGZaq3RVgLG7Yd17zBYw7LL+kCttE6M08zPvAuFfS1s1bcjzMfWVzEqgfC/DoYu4kVR7dfvPpEwiE0+OLrj8KVuS066rQBGa0gY9F6Anr1zt0Hnj3X+80+qg1gAnlUwHuaWNYAz0brEyDv18bhpAdMdPvwKxbIiuRcgl7BL3D2EEo7Pf9rd9qcTnNLxMc9wD08XF6UJmG1zTmF6wPNzjjQffAPY9tbNmQ5AYIr/3n74hkDEQgIU0niht0jGDsBk4Xc2xyAgGo/Qbyold7HyZ4nY3oEgodbfiuNmkQ4hm4IQ4fA1wUvogZy/GoCkDHK8bcLsthRsUYYa/sExJI62BiNDmDRODi+J7wuMDgqfTHDnauZR/Y7KPjQ4um20b1Wb1NY0iEkFKcG6Pgc4CAaUY/llLgWNsV+/7cAKI2+t4wmNmuifVpCgIGSCXSWRmnuGFBZ6R/CAQb5SWmwo4SIwZElMn5vG7mObk0Sf0Cgh6MWKY4Cw7gI+HldLIbd8ylzLNy7ag5RRmxAvb77mDu6et2fAJ3Q4pzwv792/gl3i8zuuvaPfN32f3Z9x8MwJXbL8cPJUGh7BoYwCvQ3ZkFiLOz6/Jq+7P51D/K1V2D+sn8O07G/BwvnAZY/bdVHEZ0xBvv3LMXwR2Rrmd7mqVO/PztyB6uzX7zy+Fbxu/tlbe/ZWOCK15p0+nVd+wlzlDy0NUH3jRcW5Tuxe+Gny8M6aYMpwybqW/KcLp7p39/ayzzPo3e8/ExpWirMSDMqvSMH927m/4/9r60S27kxvYCQWZWaWnJbY/n/f8/986Z5+nWWksyAngfsATIzJLU47Y9nnH0UVcmkwzGCiCwXFhEN5khZFiD4Ol3TRZvBBUGOdR0RC7OgTyMgbpRemkgVfRLz34mvSUAXMYkkMyAqdhOEBdFRD703vH8fEFSIVe89M1yXEbkaCD4cEBoj2F0n8w4xMAMKbYN5uvfPM/JI9Ejl2wowsUNR+wbRiI8L+ox7ajNx9ISAqPS/52U5XsmIqAUbrCWqdgOGHhixqLLlFcJ3hdvky5oi+U7H6NjWQZaN8N7RF8NsZzrM0cxgSKHvI8qLZ4vnNngtdWcF4YjFAAAL4ylr2ACOtuZy1LWuVKiFXnVh0VFPWpe0Z+8/TTzXE9to0f2h4xAQBfNvMJhgDQDfxJCAOHcUlZm5FqJ0JeI6AtAM9O4IxwpVPY8Mfa0qGKoyU+buKHbI9mHp/yxfOIAt+iHoR9MpwQ39qIZbCYZmhCF3MsM6gOQAbQFIdjYkDOUZrQ0JNLw2F4FARjD13EofQiG2W9GRBIFZHhucDdey6TkfL4D8wJmxXpe0xhK4DR8NF+nlpfajMdt2bC0hrFE5kW1DhWFqJI5WWpsO2gaNKWPaTQgG3SJM6R/DzmMjCCBoEh/GLUId4oxFNhaidRfQV1dJgi5JeibOk0Sify/5uhxcdjfphaNmetFFdrmqTEM7ZFawniSy5RkEZbpvOJrV0QBnTnRp5yKClg0f1OXeZXS6J19C7pa74/+hvQZ0AbBo0kNdC5oGZFFpTcyrxoiWEpShhn+fH8JmXNGI5CwO3abQ7AZ0d3hh+DOC45+QubApEIg0uIw4ecHVUjvTm+s+WzJkk1HEZMFhWJAiTwnrFhqOdj6sr6o02ZHvlBx41IxTDldCAOh5ljFWBPKF+t7GP/n8CYNtnnzyGE/L7/Er6s+OHWtc/pdHFHctEHV9QyUPVPmXeJSRJwmNTOFuI9BkEObhsPLghwf5RGXt6AyHQkLV6vOTDFbOxE+pEffB7Nl2D1XS34v43bzd5ixIG6s8lY8PuWpw/OqAAnMahBzF2tF59jmXgsZuM7FvidTpVIb7jyGJMXOA7OxvYLbMt8VhDvVCupCcB2IYH+/5gxcjYuqmp5PzRF/h+QQdxIc41ss8lSBp4cLzvcne5nLxuR7Lh5RD6ghGAqdIdy4L423kZh2+sVGBme+riuWtaGLTHhnMYj2cIwx5zuDqhZHJLLczB55HjosJ5dKzpQIBUbeh0rLvGMeE+oWI4TsMh0uAYKQIR6ELoqa5b+tMO6hkDJj9+aINup9sTGEaGRfgsDQfPoY2LYNz8/PeHx6AqvB219kYJMBjOH57ENeKfscrvtz8p5q07ksADVftdAXDTXjWujPtI6FPkCKQypgcxnpWO/U0Pee/0GG9GdSrPoW6jDzdu33qn1/9s2gHHceiCO5oOQ/L+VI7qN0WJR/DhnPh03O2FJmXgD05ihhTsQ/fvgEAuH+/gRaGrbNkDFP64rL5QIhApgdXt31pPBI5F6ciBxp5eHzFwtquzslxDuRpfLZZXfYyTCT9lKz8ehj4LSuvvAUWx+54BQzsC3OrCaKGAKv8SF79/l8MiXf41MMkBGPMqCVG6ndkci9DcA6n5yYZyoYMP2owtY9lXsc6/RqLicn2Jc7MWCm4KFKdu2BYj/bc3fv3+Dy6xdsTgfPhc7UdyDOhv6ykLLbHwDgLfjXT1AAn2+0D7Dxqzu1YyKVxvwDCvxiK+D+Zz/7/goMUmwEvBF4mqbZxmMkerZby+K4UY48PvRZ13zfOGzVDdQ3RVteRIoM3hNPZoQBXC4XvHn9Fk9Pj26TsJZJOGISsPCCoaHr3/cz7A9HeSSHgEKutH6Y7G80fqiC/LP6WBmyko/brUr/m5e/NvI8yr8i0KNoXfQvlbnEg2CdFVjwOiFC9SDgD/FcNlAoHuJVUOxziyxObIJx/m78s7S7fvuRJwBgLQYXAtB+YozPX/H0gXB6+zrv73i4Iiov1UtMYLxC+6m5AQpQPKZxHwh6dg8ZA625IEoG55icq9ZLdviOXI4jBGIX4lUM6rMRoX+K4bC84ktrFonxxSLYeWkmRL43AyhUMZixrCvWkyknerf3j89Ae9cwPhgEO70xiPbeNzAvWIiwvPW8gu7F3f0wJoWfMjGm6mUedvxYBfmsbgyNNfQKGc2PV7vDYxjBdkK0E7tQVe+86HAPpSes7/+Q1w1OaRJH3o33vUNS6175DfOgE3+hfoc5vbQ+jiUOE7sD3E6JWX7Iw2Sso727yIvvO66n+lfn5yJ3mWCAg+M2nlHfeO2PCLxoXFBcDYD5IT6DcIbiyeEho1+mYEj9X0gKBMvpSU8gPSGM5+kk4M8yCOAFoXTKW5QsQgxU4N1nN8wj3hWMDje280RW2gka5mQSo6G78br1N+nID66baZByxTDbfm4Bq+auDgJK+NOpqLQ/E8aSIGM6N9gceHw+xZnVWsmo81sH6VpJEP1P8qWUB9dqYI97q507akjKUHlE7Isd3XSFhG8ce34PITWfiM8NpuWlw+8KucQ+v16g0+HrVp3FGF9+uBlRDjgNy27vFUNFc3cd3f5ymSO/p6i/WwnBWJ1D0vXPMSdWhtPHGqF9LZD/0xQqdBELcpPAVnuOOh9WRn41ThVe5GGAu1WOq2/3+c5akQZfH9V5JHh53o9chA4/HmHW5z37u2+Qb7/+jfenpuf4u6a8UCuv7w6V7tHt8ch2U7kZSiryvanx23xr1rQjj3FinPTse44rx0JFTiBvU/RFYgjYFQUilrO1KFQJk++M4DfeRxXKWVYlcAPCEGm0uqLhTCVi0lH/MIbu3pfRlRn75HKVairpcj6STktGB2+9QqqF5zah947LZcuc2601wPtWmB/CETOdBMqqi/vUBUkL7gkDjMuxmDl3A5Y5IpAIzY2nvh5cbgtnFsvDC4/Mt7MNR7oMv8cUvtEIb2djNJefiScPNUjPGDedbY8RdD7NDtccf81YbwZl49GcbRJmsOfRbiCAGT3HxY2MomjCkGY5QIWDN8aNgHbKnMrKZuxS3y8q5NGeAPFw6NyZjoeZIGpKuqEC7YCg23pdkBHUFPusPBcLMIykNv9iUVqqYdszpsoAACAASURBVB8xSD11Z84w5gwgJU+NaB1TegxR9MgNq5b7mRtAkRcdnqpJydJGE2GF6WzWbk4ZrXFsVAzpZlCWMCoyGqsF/xEwQr4aDoWPDsGCsXVo36wNdjpwY7EZECHeJzcyKA/rdxiBCOYIoYDKcGW7yaz8+GSIWbyU/LImkSesbLN0HuGQAQCNCW1htN5srw6LKO+94/nyDBDAbYFFX9rmEO9bOHvsNyAQEcWAOXzPHwDQKCmdY93PKKRIXRLGO1sPTs3ETL3wuRHPdS5lvwUdYyJIoFi5cT33gU43+tG3zJ8+wsEBmmkixs5Qi4zC3zm05ftziWQhb9csQTmDdqLY9WxNOIme0jNZ2jDb0+SRnO7cQWaURwsodwYaQdkV1JE+IqgzAyyGosak0GFOyaG/sVRHxTiqzQxL0dCQoR1dCzA6OkRMe53FnZU9byt5fmXOOSI0tT1O5IEBIDdISc6T+meDqLa9IYjfCt8sxt8pCxCO+cXSiDxZN6ovT05XGIgPAsfOIFnmr67XHRLNd4TZSndtrv2a1xlG8xSZs8/7vbPTf0a/km6oRfv7V9Naa7m9fC58XA8Xcx/E3ylQzb6o7rq7i6Q+tFHnR6NLxIZOkAN36NONr2lohynOI0iHi3wX55wrk/9RiD2UnS7c13qa35zO2X22Ti29YTxrBqtoYzogvvCyHHNf19G+SQtpN2ZAjK26aCeJfpkRc7E4TSh09AGTPeA/iRAevj6jNXEnOU5EOkPXM/4WsgnBnHak7GMiR/lgBUjRGmNdF6zLivPphGVd0JxmGtqHIX30PtLpSTwFR6T0ERmJiqc5VzTlcC06iTqsgdxZ9lVu9Zh2/8vsJzKXPdSRfSJl1sKGdFmjdCk2CAJpAimLGc+82Du66VqCjz4+PuLp6QnPzxc8bxcsyuhE6EOwqYBkoKtAdaCrlvTVutvv9dR+azUtqji9/wmXXz/hOdeI74+rVQcQXgF4yPSI1aB1Usqo8H9EsTSZX37X6HOrd/8O0i8QurUrf1uJKTsaBeNMF7qujtivnHfELPVtoLtsR7Cz0XpagYvJZOJroob55Vs8aA7wPd5anv3ZHU1UwrY/eTmorCvnE5Ha9LyuflZ1eZEC7tr1rR6qH75B5PwmtyWVIKjjADODCgoxlb+KfZDQUJMdLOyO8p5KngVaDOU6bTXlnJGvnhJRPh9640ZmRN8IWP3csFDJwU6A/PoV558Z/YPc3FdzVuZ+DXEEAMavAONL9vpYR4qEOyY021pFmHAHZQD6C2VfGmgGaZkolvv8zqv8PdIifKsk7Q2ZiMos+6CY/EQ+R/vfd/xd52K6WxY8PT6YPFzmWcmcs1ZaDvw/5nq/+6vuuLKS+QT5fXb+Dgd+QvB4+PmwZXCh1fmPo5v/yLL8s0eW/9bWv3i/71u6unMy5CnZaG6CM1575LApcbYPHcsfVz/0jFSKjY/Tt5ZwGzZm56+Zh4gDwaG4ZFdCxOUDG6s5D77V/9rfa7K1F1zqLwPA0+evuH9nRvQOI8BRR0StH5+3CHPG6V3zHI6K8SkiG155pO0TGl7j9N4gmEN4bNTA1M3w7vBC2y8dxITT+wX9o7gnOGFdT4V2EeSyGUzTZ0JrjPZmMaP0V4EwwA1oS8PaDNZQWTA+CZa3ZnRb/7CCNvUcWwT9qmhvGbIu0AcFrRYtIA8C/qmBwNh+eUaj15mDOdYYYAqk8cmE7OUd4/LxKwiEFuEmNA1ewdANnvQVIiOaQED0ZGPX/mhgkvQKCzE2+rJLSTWDxY1os9dLHpHD7t1PjV25YKS8fxWgPaSgYjVEhMODMWZV84gLAu6fo/3fK3WNGPw8oJ5vPQz0Qyux9nGkKVgcjQi19r3B7dbb559Qea/5EuycBK6ejwNL7tOgFwTFk7WxWGBCJxMC2+H1+SXuS30IWcYYnS77Ph6MBXfY9BEgQzGI8TCvTQbR3TwUUfj3evQSRYSiM3bPv54HxSRKAWnpL0/YS59zZpASTqczts2ilauHP2Pxe/tuXcTfWF3hfEH1+61xz7GiFNYQfU4FfIxlCLy2b26zPMnxjFySMfgZVYdwLom8b1PRI6NGOIcDgV4JsvtI5zmRAXk9x6Msgt3zx5W4P2jmu0OoSYKzdwI4JsFicJh2UcW6AXN+sDg0pER8dTZ4YYccx3pCX93Yibf2WaB5RD9zn337PVFDHISSBl+V40qkw/eXH8tXlvQjlTfbb9Fua3O+Te2I35J/W/ke0sLfq/yYXHUkXpT/2bIWqLY0ol1HqCAVYEBV+sxrYzciHcCymzHfbXnHMVJofj5E4PxIHy8KnI7rgfLb7pP/fEBvv1muflJcGem/1Uq98cvki4dIoFSGXUcghYNKsccUQ3NcsxHWq//P98375nfsno95RqFNsyEzos6NlzBjsNlE/IDs9HGMgWYCj9FLz/GlEjC5JpsMZjDbcZsiRN37SO6YQEFjYYG0UJN/qi3ALhLaQmn4UDTopRdo4zkmogAPgZKguxxkRgJxaHZC78OjpCUj8MEeIZmM3WpmnrBq4Zh2pHWqxpPGEMTeGUOBBsutrDNS3JJzMhY2rmwDMSOoRdwIqkjjTUR/s4cPW/CWoyeljOQRzGQObK2ZEX2Or0wn4wONtb7NtlcFCvlaDcOTYuRZjERAzRGm/JzQxM8hatHCQ83oy+rrozXXsdc9YvNvDrbNZKrGblwrcpgr5MPxzXJXG+KBjs0jpAdoaOrxRzfjMwGZh9HW0AIO9ALvr4gAnjsUKo6c5VG3wQE1jAYuX6jJYqIWEWs56wSXzdMc0LAzERMaD5DnBmdVy3GuhJUIGOaworw4+haDmkX0hlHPvSVsHaKhkYkVogyIyafCqzk+iGB7fra0ZR7VzGyQwLZ2kIbzIRYJLdrTUKU6oDA4cdGRubrNTr0YDPv5jNZOaG11OmKpEFprGKczlnWBOaGI5bqujiBhQSVz8OxdHaJdzTBkxMTRBYJfhzBu+1nnEjZkMxT5PllCdd2be/cKESfOER51D6g7f85FGkYWb8DcQ56vt+lEABmq0OHK2rKfxhA3oLvzgPdtxJ5Rc8bhgBvXyD8ffZ2OplPemXv1qvghdOfUFvSMJr9SkDlQKQBRtIXceO7yfGN3wnO4fCaDcqXyj6nItcZnbG95OhCx/QBxA/1AiRgyxyOQAI1AQp52KtJS2Q6MiFJzvAgjnvEphmJ4jlVuDUwWHWt7TgCx3Mjk7ZyocPC5jfFWX6vOmyNyTcKYC0SKNoohzim2LzblPmkavM77W3KDhfLTEJCmUDsh3qds66stjjXl3uL4ehSnf0CO9hbk36D50zha+IRvsNmeKSuG6G20al6wfaVJt2NtuI12yok7w/jc8woUxX68j9JxvPbFaEQ1qof8s++yoXhMuUF3vwJXA1roxJz3PVKQ7U3OvuR5I+U8zfGw7zYWO7nPu5lyPGHfl9y7ztsd/p1cHkPy1qB7MRHBv3CzhCx1tWxiHSthYWATS30lELA2258xDzlHKEs3+qiZvp3UAVAAXC6e3kMVcNmCl4Y46/NCAFbo8wXM7NGQto6GWpR58wAcbg2n8xnrumDp3aKoRSz/sBh/gUeij9Ex+ow+HyMIkVpkfeEVCp1kLZyI6lJRpKF7qhc0F1aI3BQyWswVYo/ZDcyt8ByTycwpVVOfF2kzVRSjD2y0OVy91bf1jsvzBc/Pz3h+fsa2PWNsHR2E4c6PQxTdnQhWE05dHz5pwOqtGDCybgayObWnt68RKTcuv37C+v4t5IMZ0dnbKoTMwWwgLK8h9NX64SSwni5v8q+/U/lCBp+9wvp6yV++Qz9/sOwp+RsQvsC5ad5z0ttR6PHUsSUXCj3pvMZOnxZySHE1OfTsMnzoVy8ynM5XyqcYw2SP129fY2wbPn3+amsvZBKYnv7yvKUsDgXW1VMtDQE1xrZ1269Ls8jsZxvRPIf6niJ3gmNHhlnPK0CEp0fLzR76yCrNKZAphZgIp3U12RXAuiz2/stlCoNEWJaGPsZNA3F1NgoNkZBFk6/3wNpeQT99ReA4hYPF3j0b2IrzXE0lA8Adf21O4k0MoLMHRmIa1EUttW0rtH9jgH4BXv/MePigM6ofdW1Ff5B7LOTgi/ctA6gO6yzo2bGuoAoMN4gfrofrfIzJ+WfvHb8DmPD5L78WDmQ50h/peq8fZgQvlaND4YE7pqwCNWelkXL+/l03+w/TQmeqX/9n8gfw9vUdHp6esY3hyHc0EXroIJRFvfSNl+n1/cfemz69pa2IYbL40pql31A5Dt7/qvKvCPQov3ERxKZefmKMT/a94RXwE1ueNFc6BOJOL+BU/+hyixn+aKmRQ/B6giif9MegZ0KRVA9KcfDbeTApQYc6PFs8Y9Hc6cvGk4mGQKBFyRjG4jEEoAWn94sTdgb/iTA+Wf4VXhrWtuL+5xOoNfSP3RRajwKVBtEB1gV3P63oHzvu/nwy4nY34deeP2ymHPoywN0E1fNrAprl/Nwcb0XFIsqB8JabMKPLO887JAT6HJ2cY8JvCPplQG/MYByP4th3IKU29ghGSbPeK+vTPFRVQJU0cPkBCzeEgZfKNbt5ufy2tfnXrObvt2MnGPzg/XR19fqbws6eESmch5YUofZPHA/YETV2fEeOhjPOPEPmgSz2GsXREuFBqS5kGewtV7nR13g9tE/FhYg5rogrfltbsPUt81whlP+g/5KB8OXZ3VELj/aYXtSZP7RUEobtm3WWvIB5aKSom/MQCTeyz3jyF1odBO4bvYq5ijWTa4deWteH1bFTRPLt3XC48Nt3zNwJjAY5+Ei/tC+uBeu/7oj638bZz7bMfiBjr926GbfGuzr//C2p2N+v5Brm4Ctl/12VUA7PQ60dtm87OujuuHh8L6GwMwSTOu7y43q8fsf+QJj3HwUee2m5vK/55nPfbcnRxP3SndecPShJVabueLXTf/vuCurQLO0OhNbrm4b0eFf2e88ZK5nbRaQd21lZVhnD0MVGrkcUXhORtSCCkEWxxMEl5l5kKmiN7LpilQgkYbgNw6ZR7l1UEcMMFIp929UO/eoGjzy5x5jTROsRDcWqz9DwNXsxmY/dsSuijqpynN0IRoGaQpwG9zo/4WgVYyQeMTocytkuz2iPgGs03qtllpFjEevDuuvzfjACZLSXj62IoItJ/o0ZbVmwrAvWZcGyrFiWBctiDrDTmhgGkcgrDaha7k9xyM/NI1IMZWB4pMw0ZAxfD8HDFYHAM90+yfuhBOjwSHp0MDcIOhpbpAovjN6BdTUGvCwGod/YDOnMYUD3dYHpBNGWBhKDDYx89ZG7PJzxVNUi0Icp2tnlK3XlSqTtiDUkItDR3YjuMvh49vMSoHHuSVnEFOGihnog3SAnt23gMiwlS2uulAEj3XOtMncIcMW+EEQ6pA13hmB3RnZjXqxfNwwSA9oW6HaBujOIjG651Zkgz09u2LAofBNyR0aDSxePKjfjoblKxR4WZ7Ce61sj+tzGWGCGS+oAcwcvi+2F7jlq24LTamuwNTMKGGy6Gz5VfL8SMNTgZvUCheJyuTg0fAPTYtHPtiFsr4S18kg+MemWiEWV19wtpt+i/C465v7zXVkRv1JWd9lQnC6NEoUeUSItnGw8AktUbQ2R0SShKWtIQOf634h+BizaMZEM0lHD1v8eDtzlfpq0O0cgx4NSf4yUo4OO2u+BnrWTfFxRVxlPjFNaUogNvt2vqRvad6cvJUubYHmOAFUHbm9glfRYTH6DBmFzjCXFdDIBQUhhvkmCSHkhfdiY+JnBjDG2h2NP5/hAIMPbT3AHLnJnJqcTwXfCaBuyEeZ81L7FuSGjruvgWzX5LIgyBcG+lGedLs16yvtQo5mDT+R07dbEbzegl/6WM9HMAX10XLE79vvO16ORXhBpYIYBmFD886Clc4xo9i2NuG4UTgmyGNRR2roTBfLKda9Tv1WuB3+IOq7FRG/LxEgGgDzzh1w999d81xS5nePvnCWQawseRa5Bmw6vD2eAKh/Uu/I8DOSa9wMyKDf/CyUN3TrfFT+JE8xyb4oQgUqUg0bzqHw0nhOBVLGuKx4fn1NnMnuivtasLwYjLcC2GRT7soDUHOnb0kCDQejT+QnhONiwsKUNWVrD2jyNg9MCdR6n4XQjdb3rJKJB55IG0lxlqhMBIcbcv7LzlQMFtHvKdcvR7rnNk5bA9dURpESGHuTCucl6wZNKmhcKPmaR6Op8+rJtuFwu9m+7oHeHpBegw3ivRZx7Kh7VHSRxXRaHBQOg5ga3MRrDPF+HCE7vf0L/9SMqKFLSQQJILSinYS7NAOO4vQf/vuVC+3Spv2fJ+Cl89rF447Lg1x0i5LdKvSei9Ss9SzaE6ewABI8iLL6GZ5iG4rQCl8usfKg4qpQ5oS2NMQxey7ZKY6j2NESn3ny1E2E4PPYxzJGizTOUBNkg2tEuULEZ+HkwIdpL6DuRnd2IydGwTP4akSbNaVTzqGFutKO5TGb8jrP5POq+POnyALS3geW3v3NBdbTw8a+TUOshM4obYtR+rhgmikiIV4RMoVDL1oA7MqeJcLSo9P9W+a376tZI1Hc8kudLB3brVr3t4xefgz9+BOSt7ScCvvqNr9Si0X//SHS6+lbXWuVV6TAanCj5JhCOW/5D0cNQpg++NUbieorajD0LpsOnwjfzejh4u0Nu/vPUHmiGLqem76fhyGE/aAP6n1j+ZUD3MtcS4bXahjN6Gh6dZiBWGHN4hH1nj9gdCrT3DFWDIZnws4r+8esU0qEJCQIYczmrCftVgWpGYofwUS2C9Gxv/aSYG+3WfcfrYQan3fdZKnR7PG9n1+rVCmwfZ94Wxe3cGLUt7Z0p1ZtLxJePHYKHhEM2aPBXaG+be5+HQmweAuSzor0PqDYbZ24M/tlyd0+YJeD5l2eoCtpPpqhY2CLfQ0G2/p/F8pJ9AU4/G/wSKdBP7PnfxKExG+6IwWcG/v0MKNAa4eE/P2LRO+A1of28QMXyy11+uaC9Nua6royHy5ajIp9txJZ3Syp/T+/e2tg6hEprBH5fCGweUGPejJ0SXkOhePjwC5gYK7+BYnoWBrk1w/n+wAPYAXLgESd6B4q8hbB13T8JQI+IA1GN/lQ8uBHJr1Wl/WHO506Y3+u/GQ9tqQCO6ycYkSGxhTA/fwvldbxxHo327bhu2cule92Rw2XKUeU5RSAGzt819mN91V68TIYa05o3l0NkGGfDKHrwZFMg0x8AQKMzFM9QnGEae5tbVlOqdX6CAlhxBqiDqVke5mKwimVmTNT3oyubTXmrfmApgoH3h5cV1IDeN4dGJKAtuPQNgEBY87Bcyy06odivl9vlxi9FfliWBQTLmTufIM/rySA9AmXNeSPvU+g9ylk9eUE8Eb+1Erk4eyEpxIShRw/r9FhR/q7h8U1lrKcRDHQYAaqCl//m8KO3BPSjvmS4MeRYr83DPAiITn/O25wm6p8cCSgKnyslwOSDu1oOhtTZtf3+OvZj3/Laqh8U8r5z2+51OyKlu8tXzTKmmYegONB+b53/M4mmBBOy7fC4zHy6lWjRpDOqgv0RfE9XkL900EFUNYP6muPGrhQaXz1ya3fAG5hqk1tHvnI9P/p+uyjo9OIiu11H6U8YTI7m8as5VxQ+8a1XHNt5s7aDdHejSB2juQcnD0BeA+ocRkSWP3lL8XpQ6Mbztt49Ijh9jwJazp4ZHpHN3Mz5ioGmnAYjJYLSdOEhMQOt6gDIHQ/JolxY3fAexmQYJB83wugRlXhw6YpndoUw+kBjAa9rttWFt3gs6bcZQ53XqUFY1wj0Go1PQBrWo9/U5vdoNwgzn7ArMKMe8Qim4VCIIGABGdqM50E3+G8B6YzADufNmZ5jzqEAmN7twf/sPstxaRCkjRkgO1ivpxXrumJd1gLjPteBJmS3GS0t+tgMgn0M9G3D1i/YerfvHuWuKtlfAjJS3wwllOhJ6jlHg6iqG7R1WHTpWAVEi6HuuFMBkWB0wvlsKV8WbumA19woNzBd/4g4FdDUuOSo1kQUAIecYJDfKmLPKaEtK7QLFMORchgYYZTbTMnuBnQAEBbL/0z2bsr5Yk//bOgBlktV0DdTYj/3DUQNy0po2nyXG5StQWM7RLnnHFcGMDrGhUCLr8VlMbk20tssPtYeDWxKwQZoR++KvvWM6JGLIw2NDYqeKXLGZtF3ZlCQNIojcLUiEk0BZm8bhtsu1WBwFVBqAHeAF1Br9nsfqeBc1xPWxYwFy2IG9XVp2R9LvUTobgDo2zP6EKh8BfOC0/nOUwGd7Lzoiljm5jQyjHLIqN6IXO3DECb2fEVzz4U8NfVmU2kLUiy+pwY05YpIwWB7RXZ0NaLPEYaJ4bhBRDOllrcmjO/h3CpuQKegfQSIK1pToA7nJJFpTHO5VjRNewd5VDNVCAq9STlbE53STjrqJzme6RQs44DRd1psTCiQpcJo7p9NCCeQthxvkIW0kxu64xwlzbQMoAa1H83U6CggJHD6wIh4L0OgcESJbVh+dQjgkKwqfh8b6D6JpS0g9rB6GoZU0RQNbG0YZYm4E746nQ4+qk53oWEMZ88XPXlI0LmUJ+t5UmNsg5d4nWxjEu/yKcyHQ301TbwTwQrlHfmuK4G8VjqLHj5MZ4Fwzoo+R3913lvu2WP6zr7FgNqWlDxvVLEu5ZyoC6XeeI9q8j3jXTFyRT5VLQNRO6XZrirf7oYZQLg21V8jyvLosDCd5a0YmIzTINKsJ9tAhICPm+0tdcV5UsP4Q7vDlCJogp/3HK7dRFAqMuLc02kY8hsp8vLEuKGO1X6853vzLTmWSo4Qk/M/qY1LUKjw8SDXVhadSaTDMd5fxehwjqHdYu7bZrLdaogsUIt8VUimbiB4+sfFIl3XpeG8LjidTiBibL1be1QTtt2YlyRpjRJOQ5HyAURu3NXc+xQ01RfQpKiUsmHKlHNWcobCKWBpM9JcYWf/6WBjRsdICRC8wsROnkhDjkYkYrhCY3RPTXTB8+XZeGrvGBIOQO7kp44h5LRuc9qruWfszzPZfjuT5TqPVdQA8JvXsTRw+fTFHvv0xRyeNFBqfGV6nRH1GjO84jUGvuYYODXHWekflAs9KMJRw/HXl0qRg6YJffFrcf66HX0eW+LGMQ+A50IvvD+ux/qLvzEn51f3uDw8Jn1Zljtsj1/RI7qcG7Y+8PnTF6gI3rz7CZCBr1++WooAEaiwUXgK+wiwXTqYCev57A6nDBHF8/OGZfGAIO+pJm2yjqUDqxIev1rO8vNpxYizh04EQ2pG+0R7DpCdgT3tEYDRBee7M2hZsTxtiepj596WutwYd9vLe3p/nP0rFFUNzLZC9+r9/neF7YEN9mF94b7zv70HAFz+41eT/dVg3eP3dDT5oLj/0zuM/7Rc5kfni+gbgETGUW9HFXeOJeqKvt6XBob25tUfCPSroSXVdiUbQpwigP4LcP7DF6xg3P3xHfgvHwAAX9iM6NdteKlVlULUu/e2jvh16jPLb0Qpf0Zq85nNYF9va372dLtjOq4TcLlsuD+fcOkjUy5FO8Qg1A5dmbyE/F2SjFuTGFDKUM4/2JG83Bm+tcXR1tRSG7eBjRuoBgH8k5Tf29j/LwM6EOeM+rUIuS+X8LIS//f44QtWvMHy3oj3cAPkA80cDEk0D+X4vhVGVDdf1N/yUvpeXbvfgvj8QHXH+EoCdhCpwB4C53j/LWIZubMVFhUubjBleoUQslOITuaEPGBlQ7yXdvAlz7fIaG1JD0oiwlgE/NYOGqdlxWldHWbSYCjWZcF6OoFfEZZlSYPhcmrWuTeK7WMHv2UwG3RLvL0xYawnqHa002u0bcPlg4L6wN3PJ4/IBZQVCw0IW3RSe2vEyJi3OpS9dyui93zk0gjhXc/oJgCKJwCv9wzsxpjP+49k38r9u/d28BcxiDmKft5eJEeT3O5giz2RUp+7v7ZEa44Glsq4bhHHlw1s3y917d2+4fblq7vLpFR2XBUdevXkPloslCj7V57QiMF3DHkc+dxsns6DBIAFJ4C6e4FuUGB6Wvqb4mC0a75q5vrcR2bbYSUhmrlBApopehXKGyK8tJ7quMwj7PGX28/U/9d1WSOzaz8CJvFWTTFWdcdojGMeV48mv2Mbr/dNGM+vSx35/f0A8jC8e0InXTz2QtUiw3YUJBRiV626Lkdj2Lfub1ig6C/eU48DL0WO7w4FL+zfed9xTKdw+Q8phTbQ/utLD7zI96P8s4iidPgc3xkEvg8vVrq+ATFOvkfi9Ij9fp1zqqiR53vetuyuf6vcPrTduurXXjrlHW/FVEh8603z1+/DyF9fOz6F0uFC28oe2RvEp5NVNWrvnPIqozlAt954aZEibvDb8u5bJRWzhcbWMVfx3M86ex1QeRGpJ27IEY8sY4lnkZH1qQRXcQWprTdeG6BxqEUxZFEOUDVyW12W39aiMm/014csDqkZoanqJ/ypFov5MJ7qubRD2e3OogGTGQyJ6tvcmhpbJ6Ct7Yu3VTTT82Z7ad9n1DVRaZnznHSIrB328QzH0kA9YTdSruuK03rCuq7T2I+I1CDLLSyErmZc7NIx+rB/o2PbXOnqsKZh3CC40RYGO64Uhuv9XgolrEGAi0dmK0JhrdKgnoObgEy7AgCXi+CutYSKJxGPIC3zQ6FY8AgzIlcoL2DqptSI+RWLppFhUknGx4uawdeIneWqdjhI6Q53PjpELGp2UM/c85GTrgWTp4gwB6Cew1rUlNZDbS9o7Ek/Hy0RVbAAbUk5IqZZAKAHEoj41lQLlnU0IVWOAHHPhbph9A3bZYNGwvbesTZzP7Wctci6ZoSz7yePVEeLrUQAhqNKRB/sH7tBUpZTGg7h+ynaQsQGZ+8RFKd1AUPBWIHibNG4uZGc/RAvGNuAsK3rTg1LUxA3NM/FvbQBFOMDAZmnkwrdiU030zzY3oz9vY9AKZX5XKSSeHvLiAAAIABJREFUNerTmXtbRBJCfBrCtRjYh9MK2jkImSFwJG1TKfnO8x5zUEpLTbQ/eEWlE4UHTt4TZdJ0KpeCzNKszem75lhY6iiGpZ9yyHY3rkdkJmCR50iH/v3bbTIIIDX83tDgK4EEUGawCoTMlYJVISzAIIABVtNmDGFbn543vqZxqMzAlqKkU7O6sYtVIQZVAWIFjYbR3AjHBBplX0ARGpUwLE+jj/G6WCaKKT+nPlSRpxODXvYf/cyQckA+r0mHgqHMR6oEr7lA99fnurpijIfvtd1l6hOXMdqedBzH54ucWOrfv0Z3n0WLMUoBOA8HTcX7fF/5GzUVvUYa+qGlD7prj+7+5mje7H/q9A7ns2+dH/Zl338qRr/jmOhsxq66b9kJ6/68evjQyOM5Lo06YbSOAfFeql7rM+c4Ysoj5X3TySea5bIRmUZROgxqVhz9JVO+uONdIWWABbS6vSu3iNVKOdddBrDBDWPGw5fWIETmpJRzF4R7bqV09osxCTmPraZmwqqlGVIypwaiIG0zpYLMBt48WVA4X7mDV/B5inezt4NwvjvjtJxMBvDnkqc4MkuMm3VHQDrhkdPRk1umzQEw0QklHLjc8VHCUC7oYs6xlphl7qkKy25/df9dC82Lz0x4+vAZTXNFpWEKtb5C89h/DxhrxVcwXvm9D/kOgrllb4f1+fcqj6S415sz/V8qp7qtDr/J4e9vKVulNzfqVlSXdY+8VkD1EadX99CHx7z3/Poe+viExcedEOcU3w8uxy1Lgz5vtu+SRkyu2ZgxRkejxX82CO3LJmhtxsTXM0917KtBYpUeGe2Y8kk8FzqOIVb/6MNTy5I5tD4/5PkhZFeCQDQct92oajUiV32hr5R3ofzfft9emJt6vnsGcHb6ljI0bhizp1CQjkpVLH0ixVkJGwD6y+cUt57IbFtRD1MNZptVH3r4YrvD4SjamUZ1AM+/Ks4gPENx8lF58hoDWXcc7m8AaHzEGZSyxsNv3l43HnD+WWfqe7aGva6oVEVTXI20qzFYU7SymViWhrWxIx1pIswBk+dMieI7fcj3u7Oo89OIQm/MOx2FpUK1VcSJkPItmeV/fvmXAR17ggMoHqhmfLZy9s1yITiDc0Yvilc/v8On//xgm/UnoH/8hDf/50/o64avvyjudRIChcGch5B5r0aEzrqHPQlid9twXjy+Ig/vAaYpabF/j5wk8SAdmHTUuGAaBCYMVrTnFZ6+PEwhWedBJCCWVK+JpGAyU7MHM0YXPH/8UiBNHkH0CuvbBf3zMM8XN+YREdrJoj74j8bwhnt+3/3xbIK6CJjNCE4E6FCAFOtpRVvN2H1uK+iLfWYm8MLglbHeN/Aj4/SHE9alWRTDH2fuyfU8wPcM6R1YkIrI1hj99Gj3PxAwGk5/XjGG5QHaNleiibpxX9DAeO7uLxxQbgTPe2frST8r8EaxOCRfNaQ1ZuAng543weEh1woArJF//StwfvMW29fPCEpcCbwCWPEG5/dnY/4yMD4r7v7dlGqPvz6C6dEEALzG+nYBE+H58ycoHucSq4dPvX24rIxay19FML57dBdiLVbmHsMdK+r6tH5qCv61PmAe3qZo4iuX9jXhxteb7EUtEr3RHOHjfY2AGsscKK+5f7P+qXyoyBKp3yh9nONDaOz9cYUW+WFhwQntvuVZ0uCBDKSTEFH58AgLYMUdhDZT8AKpeFrcgmACFu2ZvIYg6ZFiIljWNXOOqQKnxdbodnm2drBFCzIzLpeLRcARgMgZWfpXyxGguQqOt2bn+FuOnfqBancQLFDAUF8SfFX1TkwlF5JdwBaNPKYOL5WRAj6ByNNcqYzzIHDV85KHMPUBNKMOr1pF8zHU+yj2YfyPUwGmRKYohykD6IbiIgfAFd9zbfqvh/bkAZf6bE+p5riWlaqCswjavJ8/habz0K51cdApHJkoXqQ5H9H/a24510feBmAvmn+j1HGPovNNMVTZ50M/j+05mg+jjBv3/i3Lbz5D3HiO8h+BsHjkJhI+2hzDpqEtYDTV11goqlQVzXld0Mj+eD0i9m7Lg25/CYoVy705LBIUdO/z/BT8YWYOs3U411E1TR8PjNhd/UbxW4537r7fqia0mlcPHW4+7K9YbYqIbPM9ImpQtvnIpHk7r2gNRfz+kB7bwehjRPseCRpNhf5Lp6ZY/8HYvIpUSCSd0KxvytKYHtdqUbthsBCPSlSPeIlowYh0nM2xZ6EKiCkrmCVzTLJHd9v4aEYihyIyHQ7IZfSg7VVhr7Zy0mAhHmnoC2Ea4KcCXlQAIYMV9h4LDKZwjheS0IdcONdk8P9KW1zmIguWEkh6pYuK5bWGQjaLyl3aYgZkUSgZnDHEDh7iyDIvOj6oJryzuFKUAIDcK31ZzHh+Muj2pOsOddhaA/GAdrV2DcHoHdvFjOZ9bBa5O7pFfhRtNy92kG/qfGMMiFqEeJzd5i72efUznIQyKOWt6VQyOY8psyEenSqOcKBmPEWiA1iUSWttyhpNwUNSuawCoC0pg9iYEaj52EFBDp2ejmGi00A3woDeoHrJPUTUbO0SQbhZ0G3z1UDkRmqFDDOgj+GR5kKAeloAZizrCm6r5Q1vZrE2iFnbM6IzIhcgoMU5CCBScFO05utbxFYBAb0PbNsF4pETPMSU9L7puRm61RQGfL1rcfwcsIOqutFdBRZppDCjtUHMIqLfnGZo9mGYWNU3PMkAlHA6n6FjhcXsA3xafDyMB61rgwhjrA1DOsbooEGQATA3jHWgccNgz63e2V/vdCNlyikAkf83jaJGS1I28tzZAcMRhqYQJAYk6w3+GFDrlkvX4NeHhJPIsFQBce1gND/uYxTatKfjUz5UQqa+AOBt1MmfgvYRcq/GnkvjetDQkL0JrncoHNbRGUAG02wIHGT+Ko38M1l0uTuSKBHgaeopeEM0L+sN4qm2t9nGkBoDZO8Uge3F1mwBbQ75GjmVg32pRZBa0Jvvt+BrnloknDlG774lHV0OBBZypzBrB7tjAJTS4TVngYqROtofI0aUUdXEMQfw/RKOKbFXabKtMsW7KOuUJeZ6mLqwZNyFLR2E4GzebuAP623efy0LO/V1GhdV+cHBfi2yg0InSp9fOeo0FJPnzDfU8XB6yhHhi7kXSqMn757fq6XV5NrZ/7mX9mes6xGbcyZu/I0uxFrzngGYgfZxek49ne8xKSlvspJoRXEym+cyzHp8i1BZZ3srQJHwq3K+Ki2aZc8N2T7yt059k8+BwuVVSqV/OlJ5qh4iYIy5PqNfqnE0tLGNuWViwPUN1DwizvdjtDVyxS4LQTdJP5qFcmUYXyMAxBCM1I2qml7O3Uysu0tB8CE1xBTVTEs5HDUnhrHKDEMF6B5JDiNLC0xHmKMe40Ph+DAj6bNReZ/Lg+y80Q0ejczhqxF7ukqjF/fnO5xPJw8UClBoQ9XoMpyPjKTtljolHBGM77MjeFoql7K/Qy4cxo9G/HOZ5xkDzy5XDSIs/tzi6+geptN79Hk5WU4MKOykd//uLeTDwIYHjA+f0X1ddAB3eAX6yWj49ukLGqZObrCtmikz24oWAKA92qUfo9AU2Oo2+DuXx98xAv5CwGstenp9A6Ev2ecAX3jJGPu9sqjz+FiiPI1qvmX9BG67SB4Up7cNb39+D6jiy68fbZ/CjL0mtU69Tn+2q70PXDZzUm2NUq5XtT0porhsHafTgsfHJwT/Sq2xd9gg3idPSAdZvyrO7IYYfWKX0dZ1ATGnw6IFq9ieGyJojjwTbW3N5JTTecXl2XAWGhGUFzAZMtVw1IdEGtOpv47SAcBtLjaKNkKj2GDiOhCOIpM23Pn1yPt95zJMjDlCVtPJP4MGVRPRGYRnVizDUtM00M6eFCWQ4nbtBzxsEkg9vt9yV9bJooqL84HiQr77DBBOICx/AFp7jxOAh7/8AgZw/+ef8eE//hNnAL3wgMsHYCXC+jPh7S8Wwf54aHcd38MvKEJJ6fDkn3MYaqV6dSUuaHKUIjbl+ykBlYweTQGuNaO753VFFzXnJnE9WeotNHn7Du0z5lNLT2i2lNmCW0kJ7OjM8c/2W4yTpcNKBJNA2rvu6f+K8i8DOnDYNd9eCGEMj0eeP3xyouYL8/MXPAPo//cvlq8BM/JMsSdKcS2M58c3P/9Q42+1d3cky2K+1vun6l1H0flbb4lNOiUoJwgBaxf1158VKWRePn6eB5tSUuFA5jHU/OAiw7y8Ik+mMbCAFGpG1BeDW1raAjq5EuNZgYvlql/bgnUlLM2iz5dlQVssbyO/b2BGRj2ojjyEt5/MECYPAAuB3jG4mTInPHROb8+WC8gl/oDhgAuZpnyBC6JT4Q8Fuhv/xxDIZ7HD0hdCx0B759BZqdSehXEPdR+suD4+Cc5/WLG8e595KJ8+/jrnwm9s+gqnn835YIyB509b5tKzaf0KLZEW+lkzJ4oBrDzeWGEx53vl8bcK4b4cDmMNPGIqoOahcbdWq6LhUGM9wl7ZI39LIattqO6cW2pRTOSF414iQkEUgClQfM7NCDDvDQ/aXU/puk7G2Q5L99E+b0dhjoINjc62F+MwSFsaM3fRy2mg3As4IVDl8LlgBl/LUhR4CsVQzTw6fQyg7yNHv1VemsUfLSl6EOXhNqPRUlHkfX2hMVf0jXw24k8IqjpbrKo3nvTfPSlPCIdXv/v1asQr+pn8ftXgIuiRV84EyPDZS9i8+tofO5ARTHhSU+H+0AyQH1djKK726K1nbmzK/a59+b4X2+Fj8feOSJ8r4LcRmqAX/3PETgLdBVSafd8Xzb0TEkIobq+LlvuOZS+y5m7IDTEVbKEgihpvlToHL36+KPTuZYpU1/7xCEWHq9/6ll2hSRO+dd/NhtzYM7o71OrVbdNYvq/nysGArvu0r3t+P8oqt4sbFyuTOTylnqez1r+P8ryqMmo2Y6UbnQJq3aKOQxESxlN7JgzoBh19oF169QLM/MHlIE1AOkb6BTo+e2yyzohuhGFSZOaanDfa2tCDjOPvNWVPRP54X0XQyXP6LYKGFUrumU8MNIO6Hw7tbIrQafxFMXxJGLd1RpU3XvKgTUx7mq2zfwETOvpIeE/7t6F3i5q1qFp70IxlYvDURNZnz3usUIvctCGZEU2Rj60If60F4gDQFgYvJzQIlExR14gsvSJZnxlIBARpDdABdIBWAqGBwWjwKBMI3D/RI9NXWH7mlvPJaAhnEBBB+2aGk3XdHZIUgDrcu3g/DBU60GY8SpvI8kCSuUuCAOLYN2zROqJQHyuBOxEMBVooEk2lfOUUpnDnCvsuApNf3cAPIjtzwdIgqCikd3cS8PU0GO3EYAyD/oPBYBIzhBoGuhsvCYqOIWSOnWLOMtrFvFIjGs6j4DOHMdyI7rKeKTwZxAI+ndGxQRTYtg6CQsaG0YFxIWxEIFGMcLrzqDsMk+8YjIVcEaoCEQK2AWUFsSEEWNQdYabctg+c52GAG03ITxSZTudcW7c0nwmhW9X2SBoVc03P77kvfZ+OSHcQKQS+V8LwgiljBaUfB3m50tkw2gaxo13ji5Fxv6xKqq98MOeyKlQ5UrbxjIKxufX73HEB1LKOhDS+Ep7jg8cxZZJMp1HhwBJdQKwppwnZQpiDFNzByvkCw3OcB3ocAZrKnTk/tgfJ4LbVIbtVoSxQ5nI+u8X9aP6t7ZzT6HZMQoWFrWM/nyvXDzqbeHPleJOvH5DQbkqttyVZvfGpXilHKcxVN6XDel91RAEBR/5/7HeNOk5Fsc7+aBhwy5lFXY5MxwItSyrfeZRjfdQ0zs/HXt8eG+QzcSafl+uOnOMQV60NggmpHtev3SenHFzvmu/Yf/rWlT3agWI60hCCkaQDIpBrZ7cAiY5X5hsIh5GbcmeUSJdiRjAzJggBJCYrBGoO0sHfDOtwXSFolAr18Dd7CrgsZWtorschAlZPu1Lzmw/B6ILOHaM39Ma5uMNxcV0VBEbXzfSaDXCIG6i4ozEwZQEUhxjYMIuvzzAIEzSN59Pg0Rxm15BqIsUNkTnPGYT7guY0Ng003eC4a15mhhsRPa2j+Sv4m9Uc9cRTB/XhaEKBuqmmSxUVc+wsKRCuJh5TZgv9qerkUSYbCdr7BZshMeMMM/o2KBQPYPoJ/eOXqUdTzdSQ9a03VuXVdcByfP9joNx/3xKBf/nPodvreFxuP/pDpZM5HLxcJr0hAO31K79uLRrYo4HUU6eAsPUxz2U6HW1C+mDA5UQjIMNTGdn+9XojqCnkDucJydNzMAjqBsJsj/NYInuPBRCZsT4YLKcMaPu0tVbWEuF8XvH4fJl0Uezuxh7o468PPXijYrDEfq0WKeomV7G1/zLXOa775MPWQQwmNNGrCPVnj0CffG+WJzK7GLx/xzPxrTbUEtHjExVvf/auAZjBy+RXYPmTvev+Tz/j8pdfU2Z5gmKh/d4XKOhXMsepkBm/1agXW/7yYidvX9WB3Lwvdcu0b0eVZf178AAmTqeN9bSALltG6Kszz1vhUVcSJU2n5nkHgZyv5etprg0ZgqGBNCI7MVtDHvqrDC3/vOW/gQH9v8qkqvD/vXpv3TP9CqdYifzu4lHmkpZQ3KjiyRlrHLK+OgEZ/jmbpzMC4kpg9Ho5V6xiEOHOV+eTt6llDuQppDLNSMgQgI5RjrFR4mAVHmaNFlQCFZ9CRdm9XWcEA/F26h2Ah8lwYhdxGNxc0HSmNaGhJyfgFlvXPaiz//CD4AOY36G9b5mbUVSgMiyytYsbeeHEZhIa+aLQBVj/ZDDsS3MYuD+Fl6bijhpOf16wMGNpK5ZlQvilsCqmEGrE2D5cwO8sIptBWN8u2f/FYRzf/PF9IXKE5+cL5JNALk+g+zPOzACZV3ofgu7EkDwn9OWXDUMf0OkM4AlMryw/m81iKhRHrFPvMr8hjC8+97ngZmltgQI4nc84//nf8fUv/zHnh4BXf3wFArBtF4wvIyOoZMguEtSYwVdLJYB6RNvvwJ1iO9Z8HGLwcrEePN7Yzbp7V5Q45tu2iRzPpfe6H4tgavPCrdF6qW0hCMQ79/Xm62I9Hn6IaO7ci05pMspbZh1cnldFenI3ncgRBGDoswl/ZIJofzRDNaNB6QxhQcMJ7f4EvQzgaWDgAsmIa+8/25qO8eXCWCkYN0IQKMKAS1YMApQx1JS+OjqGEvp2gajgtJ6tPmaIGynqfL6k5tvJEzcmKedg/ycVbpGnKwUYw+ucSv9i2NitrjJ5BLiH9VTehV+orWuDSiWanvGxSmzVchHKD+0PGdF/DOFb0xhDu75Xug9EVK8/rsD0VI86ubzSeZciveqnmkwP352fwJT9M0Jcb/yhMvDq75zC/+6BwwBkxPiN8pJhfX+P/8382lkzAE2ekVEEh9bUmvd/dU7u4cHjUrnZ9n1jfliqOR7i/yvl9xRdf3tdtqcaWipluLVUTseBN5TJESEVgniFTFNVyGMgqxwxKSLyfF8UHf2RLA/bK4I8KugOaPcN8iggTzUQPbu1KqecElT6W+47Lx1N4+fKDG499p3n/ZZrI3qpR/etDMUuxSGLkMsZiEj0ujwLDQHm/CDuqeu40AmdsoY6QY/rfnneR1OxnD96jWFcsiJQLfSybL/dQTT4B7lMWw09wIGuT+UbfL2FkZUCthjqSCrRupATDc45IsVD6fuS62mgK8ThNkjF5KXGx0PBE2E7obxRePSvt2mIYFFvGxHgtFh0nlLy0Oqzi+TlnH1LCE3YePFie1K5e9SUj754/WL1iiPNqJ9dkOuCDGI8ovvVzibsSlXjuwBFvECs0zgXjDD2We50y3k+sG0O2a4GLS3q8NMMNGpTLlF4bjbCGA0Y4u/1PStudBSLWCY4ryGL+ASZB//SGEQLSAyK25pnkcu9DywLPOCZjecLg2hYoLTLBJb3HSBhjMYgZZA2LMuactsghfSIaAN0dEAncoxsIzmuiqAHZL3PmagZM9nXGFTMAMcLBILGANEw4wFC8UGOAsJoCzzvotVpimxzDGkhz6kJqam0dgcHEMwJQAU0XBHuOfZos3c0bVB1mPUU5hjcGpZmaFVtaSBdfG/Aoy0JKobSpSBQF3RfM5mT+9LtxDMG1JEnQCaTCQhoK3iYRNaWFQqbOxBhIcYgxsKWg3ZsAx3A5mMDsbNbrA0ZAqgA3ZxNuDVgKIYrC8Vhu4kd+aKzy30FVr8ajYjAvE584DFMehwyaaHL1AiaofDIaIaqG8QDEUIO0Ym+6yM3bXWWGb27Yji331XZ00nsEI8UAI0x7WOwiPAw5tCxHi1vmYJ40qiK7mHrl502qaMncD6XEdDN0R6ogbiBI/I8DkhsRm6mtj8gaLx7cijfXf4eU9Ore/kmb+XYBpT15f8JkC5Je1AN5OzG9MCmJRgiip+jNdKMwCXToWYwFzGFvhrPwJjOLlfcXouxNpfONIva/83olU4sjSdPLqxXXaaICOzsh/oNrv1PIyWFjBF33pbnw7FFKtR/PeN4+6ucV9eJ9c1ht0MScwaqeX9IaFLOotPle9ZT+hVNIeQzZnCM3KH+TjcAz3eVv9ldzf5FLvR5ntTdu3X3XG0PzY9lUrQCaOHKJSXpM+fjPo7BFCfEXfaHaPciH6c4F8agBC2YSvxU7Ptem+dlndsLNK/7b9MIpaXeSn2O32HpF8CGpZ4d2gmp/kjIRtFG+9/S1pQvhc2RrTps7xBo1JAhhth6JX9fGMtjP8/9Zsb6dBrgcJAy5EtzGjf5gNw4vPUBboTeF3AbWCNVCjfoQlhdX2Dr0NGweACjmYwgZBGFvu8s60xxoXBkF9PnFrgNExEdctehrhtjYTOSzyAfnsbzpZlemcjSsghDWdHQPLI1Bp9Tryk59k5LxAzjo/fMfz7GgAx3wFTBiH+RRsdrXYtxfPP+1aA0VeAZkvcxgMfPX0xuKUsjAsK6Av3jx1w2ooq79z/h8uETgGkMjJGLOjv2fLLyzSta/KPlFtP9m5Tb9PhYnv3nk17feb0rf+B19WEAq8Z4hp3jIE/4hlr8nvH1IU/2I+6nUr0qluRLwGVTvH3zCn0MsBI64Pu4OB6pIUUQ1JFni1NbcHpvVvM0SL1vO7nK/rjsAcJyWqFjj/qTZ2sAp8X3ozt4KszhuDpSKlOmprGgOe+io+oQES7blrJ48z4pNBEyRBQXRErfOa7GZikFNdr9Sqn/2gCcMJFMFAArYfUhHv5Y/38WCKo05e2QJQnAvQ9T0NUw3r72ejO4zvniAynuchqnaTda+Ra2/x7ZcpKvsEC1E9n12KdhTzvPJYH1Z+C0/tHGdV2NNv2bp9ogwiMBb/3u88/vIL98ztQA7tKLV5gn+ieaa+C63No18Xc2qt6VAQShuyglvr6kBTV+JViWiXLGbDaDu/MZy9rQFsbnhyfj9RLCVmzwg+P/4VpAsEeKvIrIk5NNsz8qAmGzC4mGTqGstiqs1YF4ibAcf3/p+9+oXMmhf2X5b2RA/60jd2Rz+sLn79WhZXkFWahiLFLhRIALOPOODdP75pGAOxcEn2nmPa+MKry9ji0c/q5owV7gts+rKjrVa2GSI+xXIoFeXJmMfYvwYnRtfa69YfQv8zsd7rg1i/sZ3X9b3ryGfP06r+9DPLPlBuPncJ0afZv3hfpoiZzm3NBcUASRofSoYv2p4cQNKzncZLMDeAsIKGhGwpAqNlWMOwUuA/QVIGas7y1/esA5KjQjm9RzL40vRowWfg1tYrnUN4bIBUz2nlCKmb5MfP09JfMM1TBDMb4MU3IIQG8n0yS2mgJqMZif0bIBEUrlR5i32Os//fRT9vn50wbmJzS8AUDo0rGEd7Mzgb32/d6878tcvrTbYp/kvTSZf3wXfbyKdn15Dd0uf2Oam2VntMDkN6CCYJT3WmkliozVzbCh3PDnqrEhhJQohDNWArrjUUyvOs1qDPjmDgqH23K3+tYYl8jmVBREFozhVIPsQsB0cRF2MjIO0/C5wCC8BApwh2ozz2XhmbfUBYehsiOlVafz+5cquGse8vKgf0tBVZ6d6gWnMcV4Xu/bRT8WFrQ3UP1YO6/bnef4XV9qG4qt6ijDHWol52z7yITyWL5h//3WPccyO/7t+/4+pXolG50rSBq7+36krd4v5/nfep4Of/83lf2uWIzupcJtf0OiQChy/+hhIDUjFIDfuqIU5mAGobolDc798VtPXtdUCdYtCZMOn75dz+F7/ql85BuGcqpvvBWVDhwG2v4QcC3/odxf23erL3UcsPscEvOeatV2HJ89fvdrOyu/3xNYciHbZj/mfMw26M2WByxf1DT/b4ZzM1ablJ3RuRnl6m9jixiUHX31CGKiaUdxjeKOGlK8PSJQp8LZjOjpN172gkeAe/TEGB69q5XGzMO4wHPCU1B5spy+MTIuU5oxTjDQ0cTg2hdZTFZdzGAauSzNeA2IjlQWSTBtKBo1g+ccA3ClqrbIkxbOuj7OMsdNIdChbjTv6NuGy3bB5bLhsj1j65tHXIcEFX0zODllckWWGdZV2O8i6CjG31gzPlrcmuXyU5PBAsa0rYvd2eGyiuJ0d4L0kStNEG5wdv5QUVADGlle9NAsKQnAcFjJBiWHDCWCbgH9aiuPA24+8tzHCtWQ4O334fMGsXEOgS+3iTiyAgQDAmbLu2xrjMFtMVjYQYCKR4URWJqvrwGibvKfmpEz5LxUkBDANKAwpZZ4pBnpBhJBpKFWsTzc0IbGK7AyCIudw17de850AOpOuWzjIGOAyHBuRMxhRUQd9tXWWBgFEMaZ2Guq0O7OGKpQ7eZssG0ACP1ywegdl4tF+plzp8HqjstmqcEaoy0mARts7YZtu6D3GANKudhEaY9S97MVgcE0bE4LPD7BSFgfW0Irji4WPdgjYsnWLruylnz/tWHOnyIdz5fNkTLgZwJytDVboTeReSjoviGxScg/eW7eEclpHDrUJVCQO1HMqh3ZAvPyjDIyI6JoULyXqKR+AAAgAElEQVQiCBN29UzbLe1/DNqbhjkgk/iWJ3INTFaav70kfyfn8flMJ9dwvFFbl1G9+h5FBKs6PLw51eiECoMZrpXjLKemJ7rJ9yjHNiKpks7k63+jFBljk0bf+VN1sNoXvfEJabA+sukc/u+IY7vz0NXr9PZPqpl6Yco6sx95v8L2obfIhmoa0UG49sbWOe7ZN1+XR8Tzq8/xu3kchK05f9PDA1rmAN7G7w5Y3kHXGXt234tbp2K3wDXWTHaI9t9vtiXW/JTgvn1mdc6UBvLD/bGhYyp8H0ffak+zBRpcWnYDG+vh5kYeSEcXqPEFDgcv0Zxeaw67MY/Rx4bHx0uhVb6PCY7oeL0OcsRiW2dbTOcXjn422uYoIwTIGOidsbWB1oYZ6po5ajUwTqvR7bGJIQA1gQ6Lio+tJwjdQtExzNAHb4WWMSr9AtKh0FA5HTreHTADGUxcJiFI8v5RDN7m1EEzZSCpOzHGPjZZoIs4etCGbYQRfbjzV0kvMkwPFFDhxxURDlyUhpi5bjZSNJ26RoUZLIJ+7lbJbpkRZCjW9z/h8uEjFr2l1Y/R3Zfv79zvl7rrSH+fOv/aciGkQfPHKNSPlfaN2nakotwVnzNJW5kU1glpDpgYcLlcQC4zpQxFtvc45IXg6+GU94KBbLK6I10LOYOyTYnAEnKJzohxCceSMJRKpIHwfjiUfSIikCGbwUUIdUNpOKfshkHDgY0AilBOp8V+j0nnhDU0lz6322E6TtgjDFzInRn0epiUDFGAYH/rXgm55XS4Nsr3JwLeeGdeAXggxesd5LKdKasTy32MD4D7P73D418+4oSCb+uPT7chxfiVoH9WD9Sw68uymPzllYVVj0Dgnwn4dc77CnJZzco9gKcfNqDX60X40O9IcN/6MRwWoh6atxMB96eTyfY8Hapu7br8TthX8gMl9eSqc086yiwpdimjIoUr/N8tbdBfU35P+vS3Lv84A/rV5OqOee5veul7ebZKPvX+KlDuZEndV3c0FPpp1CJXbOOyAheaprKLH5ju1TzSXwG5wO/SdjSFnL1sbJ8enARZRKcRqI0YJ3/n8H3wCmz5jtSIw/CcW9NLyIm9/xcOwSfDPUNP6cWeW9ISE89ZWZJwFY9Vv2396Q3k05fdhgEoIyVqPxXTqDHvPPsQm0C36Cts9AQAaHoHAmF8VrS3hDE6mC0agJpHfEJyOgkAi4IWwtoalj+ccDqfwSCc2gJ5fsZC98B6MQP70xnL2xWntWG1BCU5VzIExMjc5QFVQcQG7/gsOL87gzuB1gUKxuXyDKhD3olifBroMtAagbSh/YGtD8TASuDLhrY0XJ4HQhkeuVMG7gz+GgTgMUk//DAidJcKnfSMVQW9JeCLwak3vAaB0fEZ8pHA9Aann1bwcgdA0fAKgq9Y8QaNFzz88gilByz0BoTXaVB9/vgBG3NGE6pPfqNXucbU85XvdqFOL+5dJPrBIWK/RqbnaeyN2F0NpigZuYOmx2itqxo+dXe9LtG584Lt1Vbtd0Ddq9OYXAHJW+GW8f6j4dymj2wfFSGtAfPgppaiQHU+mcqhGE//vtArQBX82tESyjgJGMvrBcCKy/PFlHiP3ZR41KGJaRAoEA7r5XuUDn1JNZMGLfEoGCYoj4ykICKQAI0bhAqcrcLfTTvj2W5K8FvL3pM0PxwqMsWlRSvl/hnD0joQYVnWXKsJm2uTY8KYR70FHNoYppiNQYpcugCm154iETWMHpe1RIzeu+UNBXaCee0AUdsJTUCsi1hZEXFdxacSMVLzh1MxnjtbZYdvlYj89Vtzz0S7KZ6ffMs7i3DQCMG77re5zYNf7Cdmfo96f2wF7MekHoD2/DRrV/Pk7T5+dOT/u7UecShwWC1c9xs3xgruhqZTdPhblulUt6czO3niB8vfqqkG3067Exk5nQzFV0TuAGU+PYeSPFoP+wuAcnPV34pE7wBWyJN4ZAUwHsf+lkPH59g53T3Ql+PY6rOCTjXC5UYDkWLjjfe8UHxcbhpF6sNxX3ZGk0aHYaGO0q5RNxvqHM5zOF77RB85/LHeOno+10AZv+CqV53Yj9HVeFdeXWXUIjfohGcMj3e7Mwxu9n2opk1eIne6DkDFEKVUZ6S5v8coJ1vkq+cKN2M6F34WQ2g0ZgfWkYap6Md0oNNUxPioKNx4bPsgonmrk5atyYAhRipdFKF8J8AdMxvBDOliMU6WH9mig4SGQ3EPDG1YZRh8e7McvRGtbgfl4eNMgIorJtTGw3NlGx8IxJc5OToGxCHFQxncZeByuWDrG7axoV82M6D3zSKR3ZCLiGYnh26GQh3lRnTYDnXGQxwOBDYEFkXvBkmPuCI/4zVqFhlKyIjdbQjWhFqFQXNTRPDP/KAKU5YlbgENKC3+UueTHjW7eI7QMcTzhNs72Z1sI9cq20DZehJbX3DaSBp50Aks8Fy9bopXWP7E3qGtgWhApDk8rY1FIwKfz+iXDRgDw1XmQwQ8BqR3dNh5k328pBvzk75ZLllbrB6Brml4t5tGQQUIh5RwxFjQuOF0fzY6zIAOX7fj2aIOXdgQtTOgnbsNzWs4jH+XgQVk0bTheACTpSEDQra3xxD05wuGKLbnZzNSA54D3mZPaWCgu3EDWJaTnW3EtxWp0QMxZX9E+BEvc49jKq3E4UJtzdk6a82MJc0NFaPvncRUzYAvErQ2lo+lDaPudXgE+uX5Yo4qfiMTgZdAeLF9EY6t6vX7BzO0Mxs1j7PYpHC+Xyjp5FQcI2XlzfMjKCKSBo74o0jKnhGjWj5z4VFW63RtIZdD2ffa5KFtJWjOBwHM81xS6DmVhyappd35KcZsJ4uQrecc+JLaKtpmaOqaMPWRUz3rcpncSDqZ4zzDotkpRoUdASMbV9RJLmeQO72r6ZNAplBnNyDWvPMhjtc0J5liweXb1N9EhLzmFrPmxnN+8ehYl/Kv7kZwN5alAhQbxm7M5znfefyxsoMjh8b0RFS8yzf5qjg35qvN0c2iyeO50oybQpZLdW49UxiyREQhxxkp63E5qmahzYjvIulEB6X00RzXcRhHX68pY9Sxj77tjehxNKx2B60fMmGtTiSZnVdAlbh43p87qMhx+U7OvRT7bhqNvGLX2V2tkjxMOvJC0OqdftHum2/WzGNPzjtMj1bqjPaF35EI4pAWvIc8Ol8T3SOM3LZ/DWWyo29x5tU5wNG2ulCD3tRZUvj6qY4H7hZHlv4FHqFKnbG17mkoGk7MnuKGnLYx+rLZGu4NjQWiIyOrZTjFTISlGPsyc/+fvTftciQ31oOfADLJqt5mNNL18bH//1+7PraWmV5qIROIeD/EgkCSrK5Sjyzp+sWcniKTmUgsgdgXMT7C5uO16ckxkOsuDM/WovyBB0mxsDoaF+OvuKOx1kDvUXZGaTeZ7hjEwWt27mjC2Lo6qW3trJleejMayujc0FjATMaDAkxKCVZQGLNdyyBQPVaD4CiKQ58gWISwGa52fmyxJfHSu0PvPUBRAJy/fov3ePS8/zahi931QrHdGchxq5nv1YUh/pqjzj+75dPrf89X8eZly9gPABahFMxjvEP6PZ6j4U5c3uud/KARywcAywfVaz49PhkGIZQjsFkR+k+fPoK54/HhSS0lwQsKUIryirWiogYOJhjPzjIHwZCeDxJLsy486Lu92+dz3lTbXMvQ24EKOgvO24a740EdPLtJBoEzYQ7JZrMQpY3HZQXVgtPpZDoqlw2UjjTuNiWVxXzMXZrhoYEvAYQOcbONuYdGcW+Ox31/d/v3aLzDeyIcRANCq+h+bKRG8CcS3Mnoo8MzCIyIdj2zHjSqv70X4Kf/+R8AA7/9r/+D9wkYCrQE7DcAfxRSuYQUjsTmtf3ts2UAUDuUB5ftIVAAtPY38J+B9U9/ADNj+9tn1F+Ubr4Pmg08//rVcI0+dwbw8//4D/z2n38G23zziiXqkL5dOSTBkwzYEkFkXIgegl+lwDXe27WjJ/DMb/r94/0d1lVhB0WzGLA5jnAqIRccReI992+YdEyJxIYziQ1QbGaKzzV7sopxbHRb5p53SzTtmPOhfpvjRV+2G9+jWxqf/xXbPz0CfdIb7uFV5t+yzXu+IUHDBMD+OaN2wdSxe76laxqRYl54EHj6LxJlBPYSQgdw/PQB/YsqEzY8xnU3XTEUSblYUCbyQwB5TSNRhtZ+ygaZQPOWfsfRwkB1l4sZQnxM17ymWJJgOLdOhHU6bDNKCWMpgAV38Ojp6Z6rXzAC4AmmaLNbiOB6gPalo5SO5SNr7Qf3NHPikQClQuPfllpxqBX1acHdxwPAQK13QKmoINx9+mDKOU031j83NG7oLJD7jm3bQAU4t7OlLFQm9vxbB8ozTutH1JOmhq8mrDYtam7RBAVLX1FqweEPiypaNmNYW8eyFNSNsFr988bdUho6uvJ1wASq+ssjBPcaCW/PlE/V3g1TkgnAypALAUwNtRH6eQNXYP35CJQjAMbGTdeeBoNDH6wm0qMx5JbqRuf7AaulkOp4gHBVbyRLWzPARBWs3f668oZFPZcgI8LGFZK6lTMcBrSTL4LOecVgCOYzMbcLWPSzZPDil0IolsGYqQBCgZi4dZ1n6riLe+Sl80W4HJFOXoWZpWKxFFsw+tg7Q3h47opLBtYKCFQ2YwpVaVtAaE9jMEKm0LPY8UX0sxwJOBc0V/g57gxHmqGUcgNOZBwAQELolja096YGCyrYjFF0HNBNkQdmS3WmCjV3EqH0jrc0F+LHPg5GZbpi38Pz2ucBU3AWL4Fhayak9TjNENHdGEAIz22P9iGaXjgpiUZmBldSzHgpY6vD4aACtsG7K7N8nsGgp5Z1CGlVdlcy3h+hajkqIrp1hs+vX9mOOXJVW0WNGZW1Yts2e+Mw604U18+DKV4zTPl13KA7rzWq535cMTKcArzmcQxkMLf2lvG+NBRJFzEYOc82Hc+n3yeqGPByu936eU+jc8veurf6eP2q3RgXzWty874rnwl67mqtUbZFmwQOEGAyCo477G/Aavr9ymKO5GH+bx4PgUB3ew6x3RKB4Ph+zETf62UVKF8HIGcBHb+/2mEojTEM56RhDJ7vuTbf4ExlvhJeyJSEknieAUuVO7rUEUwzD37K+rzGQqav0/AmzXXMZtr7mTef7xeZ1U1uGPF06K4cZ9FIWDCMpyFLc0eQbQOLaLpmqUp7NGcnGgGlsfFw82S0xm8ZvO8koDt+VdjtJBqJ6ClmmQFoGnPlbxT2PSpIoAZxTRtOcENsvNxor6cVLZYadKkVh8MRh8N9pGkrtUKd1wgkFgXkdXsjbbmA4VHDAo+8c6U0hNVgelalzVY2rIcFB15A/QBaBdIKerFnDYctjugsxTlLRz+ftTZz2wDWCqxUdCikzAy4bPA6wJ72u3flrZ+fT2oghXqyS2egN4g5hC61oK4L1nXR9M1EYXhs5YS+6X5FxNnhgGrn13EP2Zo5bzdqcEJTvHPHZp9bY/RV00TfLQXlsKLWRessloJSFoCAUpWPqAtMiQF0NF8elaDZ9qIxpKqz2kpHFDoa+yrom9Z7FzNiO19bXAYyB2EGo0gH0Ype8hnTj5q6W8t9VZufOoVQ9KmwpZF4tZL22xknYZxbR6lnneticMYazQFWJwWycxT8Qu9Ab+jdFJNbQzsveuZs3Wst8FrpbTuDLWUsuvKPbdvQLdJ72xp6U76XuaE32ychCC3BL9dDBdWRQlyNsIudw4LezuAueHx8AKLsAMe9juG0jLsATc+QskLdaiNJnCWXwkQEaJtFDxmfTGJRT0r4FXWQKmibyeTFr7vTjAQvFrUDxR0lAKI26AEhxqulEgb/QkTAlpRcBgwubzk+UWPJpWF8bzAfOJ2wp8mascDxnU6UPZOTr6rzOoRIyz74WTe0xcvh9EX5c80Z504yy9FxceqjFKDq3hdLb657prJMLRVlKSCq6sRiPGA1J1nbRXB32dH2r4iOlzSjBZeieAiGsxdYyQIGquJ4Kqz3FzPwFVYB0FJFecYoskh253gUhdpIiCN1pq8JFcfjerl3xjB2ahYEjoCB4AQMrByuYHuCKGk0DIuKnyI1fvL2zE7Ncd7h8uyAmyyXRD9h2Bs/um3cWfuAndzcupyetJlG3+N8jDu8rzCnc/7d4SsNNqLP9Xcu7gg+xiFkeyWw1LOS6ojC0WjiDcj20c7yWDBA0qvT+sUNE+/mfc1XAiz8osskvgsTTzbOdvcobsdHsWt2Rv1+kyDcqS94P3FuQQJPDtl0pju6rs635bI7YkkYTRbsQ54GFC4zjvFoTek7B9d4l72bLXNHl5TZQcfcRc+vpPEW0wGy6VHOp2bZcopFc+qY3WXE5xzTJX/3wPljjQz+jfdozr8WwkJV6zgzrF5zs3T/NfjMxWjtsnTlASAANcWzpaAswMIlnBd772qUtu/6qrGnxfayivINDEbjgoIOwoqlqoGwVrKACU2r3raG9pyy8rm+rjO69CjZI4l2uLMORI2RnimmtYatKV1v3crwWJrfbuV0lB4XdHLnFxfLB23ztS1ihjzDpU7ryDbIn7VkBBNsupZpeLQj2QqGg6dvs49hh6FiXARjDfxq4CTMz1xTouza7iT9U9t+7X5kXC6BZ2zLuJ3N1t/VH1QHfHz3DsAzhB/RHwWr7+I9gGftyM9pOIhG9pc0DpNRyPTTkWLC5aWCoZt1mHL8V6rxB5l3oSE/QeU752+I1NHj7njAdt5Cx1SM9ytEoEWfqwuhihvHOfBMrYtmljXZlAujSApeIueyKOh13ikj/yhIEfw6OpwgWFkN4btlmp4HgE6Cs9MIGss2NszoZ+yt4ptFgPJHQvurrspxkKBgX8gdJJ0cY5y9j4AFnhr80Aw/jpe9NKvPb8R/qrPC9pvzoIT262fzHdS717w2vtUxb+C3//xzRNR/v710gidKYWTXy+jRxZ2Zrk+6zrTWuzgo3N3f6ZyNXyRy2yHivQL73YcbI5bgySAU9GuCMcKwJZozfLFU+B1iJahg56ng7lDRekUviv+rOOX3vrADpIRpE++YYcO/B0s7pvFi+z3w6tXAlTe0f6oB/erYaf48GF9c0bvL+CvXrg/gp3wvhnlHgcMYX2MWgviS/nZgO9B2y70QnjAA45kAfP1qcxIsuMeDRVYfLLIDpN5eUa2QAKAYoTYAtt9XAFSN2Nvvz4ZID8uCiorGWtfTD6QbjjgRhNxWB85uKUHM07rE+xGHa9bbSBBFrX/xDsATOlE8W3CPbkb0vUf7PJIz2teK+rHEL26HcoGFaShXCYT2TZU6hYD6bnjKRq1jFlAR0FdBWZVwlWfCcf0ZVJ6x1AMW+oD1UI25Y/BDB5OgCePUz+i/bugHQecWylFPtb3dMyAL2kn3UyNNKoRVsUisiovDuqLeVyx3K5ayqLKQWRWOIHQLYa5QzyGt1ceoH9RRo39zOJFQCjgJ0RSQg6AQAPnKKO9d+BGwxZVAWOk6fcPzl3cofwCIC5Z1AVHRyIVvjMNPK/rXBYwHEBGev2qqy1pq7F8tBbV+xIEWS0kjKLKgWwIZr8/uDKYIIu2n2JH01FBsQnsXgT5IlkZLYk8FKcIy6AGFApsSxB/svm0HYfsSy+7NpbCrGN5T72QYHzXNzIBiQrIUdTaJCAFAPY+9X+/BuvMgG2d0nEGrVFGXFce6gEgJfG8NvanwpYKf01IB0b0qnAwJ1vcWAdcEIEG5U1cAeiKU+wJ+7MCRsB5XW3cBE2tqGwC9dxxxpwqFRbMj2NSHcowsQhtAa029BqF1IEGq0CmmHPTIZ1cIjvSyOl7FRV2VqMJe9etVVC+YXNfSYfzJd/mfoTR3uKGRet7qWpaijLZHahMbLBSNQnPjuddvzqmoyfuTwVh3cwhZJqWET3BWMnFElTjOS4JezGNeGE9RGI4NiYLlvoqdVxe09fzO75cASIvuEzFHsPzCweQaNAAA2mCP0Le0fROehsvYeQLKvJX9xtFErsfvRqdv8DOD0kX3gaNi/DzwByc/d0jq3xZDhC2Cccfo7uGT0xxHNwCGR7fTzdzXW9gy360rKxXXrv0mu+8/0sqthX/h/YAKfoVIncqMmGdjwCwGaRNAFaHO5j87nBlOCh5i91ZSBZGmPSuBd8rIm4P+7MqtwfnltaJQjdRI6xwCwjQ3O3+Y+Sk5W7TDAUO2pfFUjD1eOIwWLqjMKG08d20HMn3EJJDal3hRXmOjr4Hb8++Jku7zh1L+Np/H3I0rTgNLXKDo/Uw8+mjw3j4cF6DD91+tEXofE7gAhAaP3Gapw4jQG1AqpKkBsIgoveE+okgMKZFFG0dEr+HUXVzl4F1EzCFxGKjiOnSMbkyK1eKRrtv5a3fgil0T3R43TlGpKGVBqavWp6wVmo3EarWaksbTyevLNPKoGw+qpVMsOZ4prz0dN5uyU9Nma6mXCkER5S00ZTEAsZqYFrnk+80QFBa0tqFvTY1KpkwNngrKO+NsCithNEv3vrWGbTvj9HxSpRENiBCbR7WIqWVdcHd31PUo6ji7bRsKGGcX/qvjG01XDoLRNIbX7S1Wk7xYKSPdGlVataYRVyJAk466LKiHgiNWlEpY6kHTe1PV7AO14rAuQPE08mq4qA6x1ZxHxAx00Cj0tVasSw26cHp+Bp5Zo+lNVeRSUG+aslvaBuEe3EwppE6WRMOwJUDrgkpea1Qsmlph11N3M2law9Ya3JkAjcGy6b4tK5Z1tVp7pBi0a+ruwqpM8WwDmua8Wzr0ht4qetNU7RoZrTCn0f0dbWPjowFpJ2xnNZZv20kzEZw3tNbQrFTAyAJUjPdTxwYqZiBlcxwgVb62bUPbVDn5/KRyWWdXSpqh2lOqw7Ghhjgz2AyrxtcY/+fHWqA/cWd4xh3AjIymhLKhKhy7DdwQocvwxTIeOO8hdm5dZhqGQscehkfE8g34kgyOZ/xfHF8i8ck6l2pysRtcijmDCsGcKpynHDKVaEdgFtS6ofRqqUl171220WkmfEqk+gSPIgZFOnvDdoFHSvWsELAITR27NIALIipdAdAi1UsJeQOlqHGuiMGWpiZGoUi775GXaqATFOKdAlfppXBRB3IhcAdg91ExedGyKqjThKjRnM3ATQQpPXREviul2vGp5AQFcWBpyLZhDExzFZgDR2c4X+1yvTtqIXWpcFYGXBECD6MUjeZ3WuX41mBm8EE0p8x2vVHcv+Mr7KcRIJ/4jUQXp99F4dnfn/uV/M/5miQXOH+o6gJ/RqLrWMOLrJWjEwHUAS6FOflKcnjEu2Ec9tl4AdrJW35PZNEw/AiXr5L+Js135suA4XRM8f9gfeBwaq+MuYyzQfYKndtQ1Luh07ldN0L6U4oOTKkYe6NOW9nZiIiSEVMznoCgcw3DlOEpYx70u8rIzhSLvV88Y9ssFGjmHyJ0y5rg6YAd/+mZHvDjCLoD4NY0+2R1fkcNWGgd23kDc0clzSJUOgctYBEr+yGR2Q/GVzpPN/OuFFH+CnKsDuWGOwsVHUPTgBB0wUaWJQFnCAj3d3egumAhAhfVh/SuFXnBRdO5i+46C6M1QiOAXRfp+BYI5xUi1SOqFETKd1I3e14BkWbUpKo2Qg8IOrczzudmWVWNBpkTnp/fLohz5ydODI+XUqPUi5caaq2bI5yVIApdn0O7ni+2c0xuoLcD0iFYBdiMJK9weq31rsl4Zj9Pm4FvxUgrzdByS2zy0GrbSHZP+fQR/PXrOCNieipb15GlZSDLc1IEDL7/++1C8gmES7sLv1fb95fxoVzcyVCjzwa3R/ydb3M87vowGLS4vGX4c7OzslCBPGipteP7d1gPK7bTE6i8Q8Nj7Fd5NkNqokOOQ5bjAt6UH3E9dTNHnFxqQaA6eU9+Pmgd4KkDVa+qPL7jfneADAcSQ7Zkn9l0ib03y8ppckhxnWiioY5DASy1WnYH5Wu6CI7LMqLjCXh8Og1aWdTOw8Lgk8rLYso3svd05x+JsMCcemxzVingZIe5tn8n41/fieP+obdhHsFPAUUmut39x8+Kc//4G2r9Gac//xpGdgLw9L/+gkaClchsLGK6eg2uahB8I8IHMd0RCIdfgPPfRpBrN1uBGGommL4dUDxq47375WdQAdY//Yynv/yK86+CdyDUP3zC6dfPaBjR8wzFLUdjG4r1KbsFujwPt86rTL86f6mwMnhyxOpqCz0bYXo+eBbL3NqtVFYpSrPd4eL0/Ixty3l5By/hRnTZ80CuQ8qOhHCSTBHMSyQqe5MGTXkAAsGdyAuWxfRvRDiVqpnGTCqI8nZJlxgU1fFCvp5ZSD8z6XvwRvZgXuvdsr25Bd/0g/j4nx6BPrf9ZN76/aX+5Mo1QxwXv/u2S/xzxfwxA2ZqZ9v9Q1wZB4wAPAe0JMV+MG/XW1bpLnD18v7+8X2kXLr8zb9J/pYPcwbm/AwBhPuYx/KpoH1ROrS+fweBoD88GVICgCOA09V0LvvehZ7HXcrJxD2EgvatqeBvqJYfTdn2vqIuBfINWD5Vq8tsAnfXKOMCjWZa6QPWT+qZfv5tw5k3q9PTsTX1ntz6hva1W9F6QWum4KqaUo9FUESVWdWpTFekppmZPMUjReR2saj5Wgq4VmjwCkG+KJPB94L2uYE+EPqDs4wzWsx/GU8ouIfgGYS72EP97x5ixV4J7wB6tlV9RG9VhXoGSif1OAUgX7rtraWDmhTt91DUsOhvn4D+IIA8DsZpMkDvd3jA/uTJCYSgORRE1yFkf3L3HmP+3DgXs/AZ9znza4qCTNZccRArbUKbp3lzmBxei/MLPMZM3yPBnzn9ckODEjQGOquDiDGXnrZ1aBfGKwpKKGn12sBSqqQlm49yNnScuWFuqtRpYU/StDmECrYah07r9l5YwcjBDOm0QIrVJs2o8RVNo1luw8ro6g2dwvdvvqaG6uE1qkrtGuvrzIvAPFcLgXsbyjorWxBQInIBT3EhbAIJLmkAACAASURBVAE7HBsDm1gVA7XEAkxw5EyQj270kfH1/o55WO4pm/vEeMI4FE2eUUDM0/3X2v59185fMIYonqfhjTv5uraXP2m3fvnFEzgbvF5JPnjlJa+56fvtNkV//b2XEDRzJQBSDoD/u20e84p6VwKXTtEnQChAc+aDwC/PwKAWDT/S8npJrJSqYARv25Nxv9jzOyM6xtyCyb9Qvr3Qp0kH8xO3n5cM066ASo+p3kguD4I9Oyz9+/dd+3uLIl9+p/y/lIXjEq+89H0+rALazQXpmmhGoXDyG7skzBAq6K1D6qgLByh9q6L8YGcJugwAbMYejSzlC4HKjefZEU87t4xRO347MPYFX59X3nlv3Re12bCV+igooukvPUV0keIJqrRZVHy3UkO9dzPID26rtQ62tJrFeR9bQrXh6LMRPObnk0nrUts4pXeN+DJP9FD6FDfiWMRst+huM7h2i2wSNl5704jeUimVO9Ho8brov3WpWJYFtS6oywKwYFkqnjpjow2LOXgWKpp6flkitXTfmhqiPSobABdCxcBNoAomwsKm6CgFy1JR62p8e0VdFpSVULAApCnuaSGYZ0CM22k6CdSIrikSjJ+SCM9RPsRqx41E8HZKOGBsH3NBhPguxi84yx28t4zPo2zS7nQ5z5bOuSuEO3fIqaFWqyzaOwqbEd1TuRMUBpo6aYCHsh1gLJWA8xYG9C4dghpLzudnzSLQOratYWtaI7Uxh1OiJL5Lzy5BlqqKog6IldzaTmeNcrMaq88Pj1Fn1TNhDZwsBqM0+ka4FmGKEklr6+vHFt2p6DPj7Pl8x9I6fxL9e2hOwsPTHuWNGudT04oiBhSOPUj9O/wlgcFlFDIn0ErDCdWdgifWNBSnNhbHf2NqAI3MVJJGEugzMSRXIznIHNCiPwQhm5zKtK6B4pYKdaAgM7jn8MHq8x6KZ+V8SxhJiQdODjBNKzhG6TgBgdfCucGfcMVjWqnhOMVje+OM2ZNGb5Of7AVZHZzFeFfmXAJu7P/XtFSZ3x1ODjLm5jRz99x40zyei+bDwiVeiVsSDA/1zVj4q/3a+7VrGoO68v4XWQfBJd91o595H3bPpMco/i835IGX5wVggoX5XfvBB7bPb7WfB99q0DT18hZ+dt8G+3PZi+w+XYbj7N/u+M10WAnYQ+8yd2w4LONqTr/sZG7CEHJI+UAR1UsstGomivACdD1acuBBAUHLMbK0q3PeDU/HZw5k81ZqgE+pizpvCinPUEcU/yDNYhHkgmqOg7pGtuMFKKJlX9gNG1xQimarqIUgYnwsEYp4nxKRm9WcB4oqIZVvquZ0ZHvSnFeMuuQyxmp75PidxeLz49o4p2T9aUp2rWuu/5SL0dxMGb/sj+8sgzhUkQCbSKRCD3i/OGCEjdgyLM640N/vFPEMNZbp/r8Hf+kIx44be/6PbFfRyD+hebr20w/2c5ChTxHo2jejMwuuYQddeTeYllLAZhRvD4+oyHs41ouAcJ5SmNe461mXNvDReI4Sz0HJzzzdZ7pT5w8jkyrFY/MEpqZzaL2HaJ2zXyrPb2V07Xdm1nkbP1SrRsxz78nJOp2RQqioALY4DC5vXBuS44RNLtf/JVpx7TxE9ofU90K2t9WzH/8ca1cAVFHdYksci5YXzViA8I0E70WslINg/eUn+/0LAMuqcsEr6bn1jM5kn/vfPgO/fEKtNcHPR/Rfta9wsDEer8uAL+DldflXas7bDx3apV46HE4w6Ksve+YjcPFXpmuS7yeyLGMlAmUARCDiUhcclgO23tGc+PmfCQivUYG3t3/F/foXM6C/0C4g5taNL3HcqSO6viF7BvBOVA1bATwX4N44pDtjME47Tx8CYcMTjvatk0xK7lkAJ1hV5OER4Syr1Z9xh+aOwXToFWeS5lk64vNaEuGF6o8yzwJa+l3gno1OrAASxvKpBqN1WBc8EeH+w3sz2DM2OOG8Q/1QALzD+dvjblxzE8zCOsMivAEUHLHhScdinqzNkEjFe+BJgEpYl4p6Kqj3BWUtKM+EZVUyDXpGpffqOWmjYNGIlsYbemer3aPpHLfWgI1x/tI0jUwpQGtYiqYU1doTlgSHOrZvjyBecfi4QoQtIsaRh3rHLrXi/OsJrX1DvT+Cyob6qaJ9ZsiDeonyV7YVf4pNGoRsfGEAbFkNujzh8OEDyFZRjesGH/SkSkJb89O3rwABZakWvfPeXvOgokZCigqb78x4W7F80FR5/IUh5RkhlAfMycSAu1JWd3cIEnv4dKbL55WR+yC3JT1Jkbr9mJ7zuw4YzOGC2WivzLinTDT2inwksFqMSF7uVi8rlKSuiNqfJccR+p4qYtGtQ9kEe7cKHAIwq2OF1dVhyUrTfFII5Q7ACVg/LHALSikFUjrW965NF8i9SqJ8ZpRjAZ9VqAHpO8lXt7oA0afxuYINu/HWql5o9VjHfougNY92G/s1VuOyMV8yRLmRRcWokSL3eKtfuvhBICZEu8GDA79r+kmMFIe2145nw/GmWNpYFvNELZYnyffZvM4N7xaLXI0oD+e/DW9nQ6JGUKnwWiPl5F7AtJmE9jKlCTSGRQc/mGn4+6EegnlRwqfaasF6FLzW0FQFuUDriIZsYQpXXTujI2YwaZFyj+b+4UzqiGgC1EPYcXwe72zdziOemfZ9c6WIU9OJybd9K0EMh8J8vIMSjkOc65xS/lpK08txXH7P/166V8f/uvtiHbHGcx5zRGZsZoyI+x9hLr8Xff7isyijnhgoUlC5gWBEF8JgWYFfnvR6y9xRdnDJkEH5c5/ODJFRuvReXeMe12/NLgSNMWIMswLt7r0ViW5Xk7A8BochTUzdXYECsXdQfvjWwGV3jtwp7RI3Xn/dNax9Q9S+MQya/pcmT5iFfGcskWOuLiSs9J0xUp9L/KRGdMVHYdzz/mF4vzPEogi1FAeHM1XvHRqZY5HoxgdoreE0YF9XpxcWJetpjF05GUMjN/rniVNskVjNyYHCAxHCcV6kKqdmRmXPmiIoVaONK7shmCMrTGQ5cqOm/WMgfhfLHlNgUaAl4TgZRg+2uptcCMQUhr5uEUckFtVWUoYe04J3M+JrxqWmSlXmwP4etYTA2YnOmBF9WZbpX10WXU5e0M8N7XTSVKhUNN17rZBIq+30vUDkHDSyooCNLGpUcMdKDJGqY6kFS9H61eRZaoo629ZlgaaA9DSow7lCp297Lk1rlROBPM1zNRgpgPTBH4v4STXjuTMAbBGutgeR0po1I0BrGkXnhjk9D4MXF+rmiOmn50pzPt3OIoNHJgQxOO1djc4QlGWJ7Efc2oAxUwRGVCedUEgzAahynSHm7dF7B5/P6lDR2KLOm2ZEMJhPJkPt09ZWNjUGM2uZI2ZNQSsiePr2CBadszuhOvy7w0BkonIe2FCwGL9DFiEe2YEsU5xYpFBw8vZ7KTtKO5WhoMkheO8wOoznGXEgeFG7C+53oftBAQ8umSj6sAfNuO01z/23papTyJSu3UmQ4+KMboMJVTzGYdC0t8qgqFHihyiuhSwksHSpg0oGhpvod6Lnptwutufw+fjYq0WzGzJlJ3skI02o7bfXLgchztnIS5VI1bBhxXjiGCJNPbZFVbMOD2mT9W+Gs+LZonLHyWjjQ6TkGiMOEhLvZfLIZE4PusHZ79MscPqTIBw8GEPRiiAJ82ZPPK5Mvw/aMP8+3YMZbidbBvZGR1+eeUzB6yU0mDDB7p1pT2j0NQJGpjfOPOe16/Nq+IA0GtGgdrADFDoOH+8YEFLFNY+Und/xMgM16MEov+KpiH2Edl30LHnvbhRIHCmce51/2f+d2368e74qj2J6hmAlLkaEpgiGITReK2mPbG1FRpRywjNDMHYELKHo8S7I9kLpR7OSeOaoA8LheMD2fNYME6wrWmtF75ahB/2qbyONoQAADndafuV8Oll2QIU1dRKzjEhUFH8tRbOaQNPLUyfUZUwDpBGFbmZX3sHKwjAwSoV2iBSwEHotqGCdmzkMKr1rpiPV67VqxhsqhFrViF6qyWEilqFIDeie+UZg/lK+j/BzmPR5CW+5QRDgyAbjGV9cr+GG+aH32wOaLvSZ9I4jLPV24D/X7emXeyi+98CzZrq7RprqPYGO4W7XdOlablCdPeEBhHdYPn1E+/Jlkpkd7uKUZVx9OYMX2x6k3vb079n+77w5MKWIZQMY2EmgKcIBhKFURLMNHD6+05rVD096FpwOuMBUiksIAJSHFBHUtWI5rDifNaOSb37or+1vdxwCMR7QcI7zS4Ehh263lAr0FrxMAey8Asu6BI5X/krtNVsTlZN4nGkhilKcnmWBihnSTS9ZTI/rJU3J7jseFo1utxI6p/MZh7rguC5onQ0vDOeX0NtaAJZzO60ICgMHIWzOR6SWsDD2UEsA3otmBXEK4rn93C7Uts/gvwmWP34CW/YSQM9UJcHhjz/j6a+/4UzApz/9BPzltymY8j1MFQ3V02+/fjY1q8MIrD/CBq2rnsfncyhQnMC/fgF++YRu9KeZId7vyc800hT0AmCDXD0pl9dounr7dPmqyjRWf2Lo2PyMDH7Vr+5prAB4+PagTt7rEvs+jcEJr1HAbG+5ptYLfFec6IXEYln7BgEvRekJARZkWUYWFKguZF0X3bPWBmt5i+VJ+tV5NV7/Hd+5763tRyPR/30M6P+I9oo1ywa+YxICCMATXdtYQYN6wDkwbzcAagxisL3fbz6a64yvIG3qCx3SlbH7I/kMrB/eTb8//e0LfvrlI7ZtML4VQMEdYEwdMEf85ZGW94rW+NuVxbeXC0562ODKupECjfEEoopD/QnrumBdVyy84nh3xGE5RDQLFUZFsVSXjP4gmkryfELvWl+odVXobE2j0fmkilb5BkCaps2uqtTurMbDpSiWF24AL6YgtbTI5sVPpJ6gKF2ZWn4PFA7PnfKxoH/pIHqC0N0gpHnTdsac67uOiPpc8B4FBQ0PV/fVBRAhBol63BUCpDgOvdO0l0IoHzUSQETQP3dI0Qgul2JztMu1Zjq5i+jIzFgPQv6adknE6Er/3nJUepr93GMssyu7Z6FdI1QuR5mVQZpK2AmCI2KnaRLfRcQEuK51JNnqyXevpfqdOFJ7JbOzF7txCVAO5hm4CKhlj9yMW2biNUVb2y8RFWR77WkXz+cNg0Jeb/kXZwydT7jVmKdkWi+tws0Wc6D4X/rFYN03xqP+CfA0o87U6rjTbNJwwvxj73DHnmDm0/kl+NrCpYwwvLsyF5BdPUF95WtWYRqi7MaMG0Zgmnd6jDTBQ3xOwqhgRPekt+zHEwzb1VfvGXWahKeXWoyRdt/9007Rsx/XS8wcbC+Uj3wdJnptu9XbVZpL41jR7t5ZJUaG79WoXiAQasiKtTeP843zzncXrFjfWSQujKdwhXdqQXvggvK+1zbdOyB1xuTXxpphdtynxvMLXj4r8ncizq1VyL9dGNGx45fSYRQgBUe5gHNdEHjNDlwIWBc/Dreoq/3dkkTe+uLXtowL3ozadytt6+qwoc45kbhsPCXD0K3pQ0XTAZeRkeQa/YoIzcnQQ9Nf7HB18DG7i2PfTanBEsY8h/0wpMGUkZ211rvxZdUyotS6WAmWAnEDLwTc3fHT6miKRC1k2BrArkFEI5WqKVlL0Shri/rNtEJsQsMob0ZQYUhTXsX561KWMBgxW81Oc0j1dNvqoKZGsbXUmJdnafJWqvc5wuzdabEQcDiskPfvUEmdH4pFv7M7N4gqh6UWiFSQSNRO9tp+AqAzQRYM4yKRrnFVBQUtFaXq+izrMmpnFleI7ehYEYAtDxFpdh8US+0agjnUUGyG9N4AbkDbBGDgeHTDC4EsVa+nww7cYWDrNNPT57JFhBETiqWirIc1eDiytadUbzYioP0eM0ITEyyftXKNnW2dgX7eBpyzRciFIYNQikXWW31UIXW4LqWAT6cwlnfWcgNstVJR1fkY4ukjCe35Wf8yY7k/4uHLF32P9e8ySO/AcEyQcT6Df3f6bzErKQX+WIcROWzdhgFSIGYdMw1A1N/0B3AFIauhwc+3pOuDdd7RRtsPt/8G3z49J3EmNFjbMCGNFO1ueK51wWqlDeamiEfceOvz9HrngGWKcf7fF2U3RbhstDsLidm6RjKCH3aBQKAOKijhpEkYUeeOn1SpbkYkkYj0Cl4DFBYRzcol8LSrV0mOn2mCpeW//Cd5n7/Txnuuv5EsL2zmsQFb+zAA72BDkhEdCkn6M+22xAY75T+PCUy3DaPk7id/Ju+n3cP7OubeVboe48kwn+a463KSr3fM2fTMLIsnViK94Boc7o3n2cHZjWujXCMU/+yU0pMS/BbT9SZ+5kq7sk2543luzuFnbjNW5Magvse0/cgEFJB0qdMJIPUDU1zON/bGeY5LGNKeXKOS8a2dExoBBwLlU3rv6mhj7+3bZmd7yN9rXSCygZkg1xd9gtW7d5pxE6QGNCyL6gybpUlnASw7JcTNNIaTWcDFxmY8UavFdDdi/GuBOv4OPYvygZbRx4IsmEsYAd0h3x2Q1HhektF8OCFGZiDLMtebBgl1y9TiOqk872vG86Ct/rkr36Ap4ZvxiUozNPPPyATzvTYKB2hbAJSP78FfvyWZ7nrzaOeDZBcpTIY65y43aFbY/mVkx/M8BLeNJj96uP/rt7xHkr77ynV4BLBM90Ce7PtMGzT5ixmj7Q0LLELb+JzeWrwjP7/UGnSMnG6YMqqYATvrkebdVb5ozsCaZHyZL7Fw6AoLqb50KfrXZRpmtlIIQBUaCTTEbBgW1DN4QuMHpA9HVSKcewt+p8XgZehWYwqEJqPU7qB319uYzlhtv1ZoGGHz8408q4P+7/S3L3pmHTVDeVMiwgo13n/56284YoYNP6MeHb5BcPQ3kTrCQOagUx9H3V2zUMnk3DqCSl5zgl9I/nyz3eQr39q+04n/3DpjWSzjnmUlINp2p+f3YEcMYEnMj8X1D+Y64WyUDNhYCuGwrthYgNZiDNfw6qRbSeP93dbzn9T+HzKgZwTpnwaydhZa04FheEgahji+f4ffvn4DYJm+7e+J5t7Bgk7Aasqu8w3wGFdpXChJwFe3JSxLDWG2QRVaMMXUPL0hgDjTYB3Z7+Eqre8sajn1cVRnlJLCsALghyccfnqP3kXTnNM9zmdGXRZw7yil4vjxwzg8liKz4h4MQbfI8nhzMTaZngfydhnYhAo3jliJs4QQCcAdalmBekJZCXd3H3E8HrGsCw510RpuxCC6R/lQ0L929K2jnRtO5zNOp8+aLpO7pTUyRWRvptg5hLKKvzL4PUXtn/5tg6BiKw2FVizvTOyvBefesbaGXhfwooS7LAXHX+6w9I6Hx6eI3ikoqFTB9M4UbzqvkR7UDUzPJpdKOBJoKtN78ANj+VCwfloBXrF42tIv79HxmODCQUMRJPMjhMgCkgvABhokqB8IddGIY2FBf+jo9QFVCkSWQLIcXIWJ9uJRG+GPDE9J6XVoPMWK7P75rl47ncBghLvdccbc+u4Y+P2r9eDnL5SSGMjchdT8N5ZtyK4OuflCjNDT9sxZJvwdRpQsCk1N6NCVIEDTsKoS0mtFweps8pMyZMrwUdQBGhHOykNpbe8kjNSKWgR8bsNIaBMiqFIkjMBUAu+54ESlxB6IiNYbq8lIZilToxYkbjsy+CK+lk+5NPFeefjilnRBhuCs3qKq5GfWc+7CK3O3WrOApoukoXCO9GcKoSEaO8+a4EU9yW1/JIlvbpAnjFq3kBS9mIQK61jSVBSmEsNBY98mpUQw4VrawnjPneJCFUY1MZmxWAAONOpHQxBKc/aIrDHQGLfvaj7D++0IP0WHAYv81NXSqADYmgy4pEGm5mEOA3qCKceNut4ETweZIwVFZrjKEVEewULpRdfW98YU04Xhsfv3NErzm9+xWL9D3KnJEUPpa7sc95sHMDO3rx4zikUj6uioFItgJI3o02JzCPzpyspnCQ91z60zaEGKYKMeYxsZeoAgk6KOLPVY0U+jFpqALtZzh9Dj3u/PdxaoL9rZzvLhO31lYpe63ZvVh+Fn//zuIBjOGAbel4aZROZdN5cDvPY4vRIw7BT4vGKuf4eIJMadx17rOSc/6w4zrmkPvKxzGTSdA28rnhkG50hRVjQFXNSzAywlPEE8CjbjiTSd7EQ1R8RZNhMyBy5fBsfxZRhZe1fa1Lmj9GpK0Yq6qKFxxaI43iKbt9bRmtaRDmO3z8vGTr5e0FTntWifI+NKCeVSdoZ0JwRmHjUte8f5dAa3jsNhxdIXlEU08sqU2G3bsPl4bH6lanaZpRQsh4PWzE4GdEnAGDWRxTL2tB5ODYfDQWuawtICihlqBeCNo957qQUoK7hVVKNOqkxXPgBGr8tawR2xDsuiaa/J9mSpZM9AU5SDATIjvRtrWRSdoQLSvWyy1Zmu8ArcDMH5dB5GA8s85jLd6UkA6WrIFmg6cmasdyrBSXseMEeDTxNRx+DCGvEmpIq6xerWeVNFvAkB7E4alpKfrNyNCNA6uG0GMwJimwMJxGruCaCZCMhoDwuWpYAscWNn1prZUFnBHeVEBK1tSTFPECqaBjfhByICN5UbGjOef3sOo/uInvcjL+NA2boEihqsikogxgOIGZpNiBk28dSn1531SPTRy3zuAVjWCePFg/3zmrL5TpcDnC8aL828V5DEjNOTslXvL2BCOIgU0owcNWB5CX59vCYZQmQ4rYpYLU03opszr+/1MGw5rgXCK8wu5EsAhdPJ1UjcwR7DU7R7JicCwnBe7Xop7tiqC1ArRamFcHgiiuhPGH+sKhuPCPe94rGuZaz3xMPGJGUyor8cnWK8hnvqjEXf3zX6Ih1PZ0+t7xmiHGdjgEzg5mRC3YMiKS4a9Zo9sv2SQ5d4fjenqDWNgIV5Gk5bbE2Q8EyChdGdjPHHkqSBR8YHe1+AbO50GPOmMez7BKa1V+cX5/8leH7DMrGInPbYcYmkLHUCaLkzAKOIrp0njKjbPN+Jv/tekzTuOPt+Pd+nzhYScbY5stDGe7XzPKDRl67r98aYf0z8uY+N3fFglnxmOdnfN15dKMGVXEw0fUpwQPnecdZtF7TEI2GqYaz7x1gsVbLAStDROPdjdcZ7qRSdmzkCu06uYlHcKc3mxoBULUvjcCqKN6h1dOO9Wu+ovaG1DkdldVmsxKSplw0nt9YAWLAFVRCNTco4PEfO1lqxriNzTynL4GGFtVxK0/ezWIYRjHMjDgu+tonIhlHdkEI35ypmi0Dv6jzJPM5D7jv2SRyCxvUcmObos3/9hvrpA+Tz1xnCb8BprlMOqLFyI4kIdZ/VhkfNjEBjBM4vsK/teBsA4CiE59uarYv2lmP/r9RuYIkXW1bRpBwp8bdDswQQRvDgkp4T0YhmAGgJpgGlOwzCWhbAs11532L6qYQ3FacA7yzQ7/HxSetFg/QYk9fP1v1elgWoFdt5s8F4zqaRPQ+Q0Jc531mMfnTL7NW74ZZSrPY5Qm7qZkDX+Tm/Q1gx9Kie+ckdY1igMo+VMKpWn31dFjPIa8YoL0nqy7IU/b4VUici24NWgIMUOyMDb2YrkP9lqLPC3R8/4fyXz3MwiSbBQCE7sz5eAMf/+BnnP/8GIeD9nz7h9NfPqLXgTMCdEJhUP+841l1YxGDEQ6dOtjsPEBwFeEq2rXvD1Q4/Yn+77c3xv/8pyQLqMJPnyECUCAg4svnyEOp/p3YZ8b9vWY91SeiRfgsOCMyCw7rqfOSMdVnx7fE5dP+5jcy8uz7Tbb6GxrJPLIgfrWrlzdZ1tYV0Rm2sdSn6e/GzFP0LZhIwAqacD6N0779Cu+mI+Z32/5ABfdfE2U7ZX941Xdj+5QEf8A7f6BHPNIzo96KR6N46aZ3071eY/X7z1OiSh3k55L+/ZWZd5uNMAAruUT8OBllAqO9MaDWPKzFGmoyxag8dFQXlfYE89N3rjhc4IyOLCYTJDIouOLqykR/R5YBjvVej+fGI4/GIw2EF0YaFVkCOqO/UUNYOG85/bdh4w+Ppi9ZiNILkBvRhPGcIP4HN/UCgkfLLe6A/dqhc9giSAsE9NGpZ8PjrM+6OR63z1xqOBwaqp6KxKBxDHvzNjI9mOCdyo7hL9XkV7gCrbZ7XBfIMwTtlTN3DwB6rnyro6wcwHkJWdK885ZPF+GSr54QPECkXUTP9G0Oz19v98OdMOS1XkEyqZbVnSL/XZPcXCR4uPO7S7/ur+6MylDW3Sduc9nHs1X4mMdaQMQYxEZGoz+KKMSdUKiAp29BkGF/naO/LtYi53OByySkgKBRfPp89oXJFvxsf4vm0p7keu0dlO49BRKpg476DUc8McWVdd/N5bXuLLXB/K0HrC2naMz2DpRI6U0Twa1Qf4J6twCUBzWoKskmow4H+cg0ayc+5z8GEbwVfhWHfUxffVLELi0a/JOLZYGzDmOdNTsfyuHfjurqelJ4f7xowJdPLCDs6dPVduzckZlGPluPyNDa77teGEcrmS/vZ7N5/bXKEmzD0Q4bm3ft/j/YSaXf6ce1XVx45vvp7WYK3pG+f71xRrfZoLkOZcfV+Pt8bI02QnK6/OEaCnAbe23suK817+67tmfzsxOBj3d+3f/K6ePS2d7/m+sUd0423hbTXj+2lWf497bVPOu9h+CFoZwmclR0+w3kjnX/3np44EleWO5HGoJkRmR28kIShVcSVmzTBpCtXyGiAD11T9QrAmr7Qces+bRgzYxNNIVgKg7lY6ZPhMDDmI+iWBrtZVJT20cMowTxSBZZasVh0Uja0FYsGD0cCcueCND9L507Q1IRb2wBSA2GFgHhE9vfEyxBZXTxT8i7LguPhoNFRHn1uaEJ4GOwAdxDW/ZRCkFJxWA+4O9yh9w0sgm3bIG1Tw31vyvvYHGpZsKyafYC5AwWahq4UlMXS99eiGWGIUBfjfS2CV8jqNC4LKgHLqnS6FsVbmgAAIABJREFUS0flAkYf6e6N/3PjKpGlc8qORMb79U3QGtCbRqFrNKlRfB4GDZMY4AvE/psOwy6rDMHEkeKSvOSOK/LFTRvO6w0a4YYsVXpbpKAp//QJATqDrXyVtD7hPSoEac3knwKQKdabR6BrqnUqNZTTbOnXUVJKZBvQ49evcWZKKUCBRqpzRxeApUNC8T/mQICmyU98VRgg4XjbTo0xcTpfxHrLhGfcaGAOwTkzlDPCiVhr/8YjJwbNHWrixsxL7TRZOe2pM0cDdWvHw5lz8IKFKM6yOscUlLpYdOOgwWHY8fq3/leGowz8u8spApPlHEGa0jpWVNcp11VXvndQhWDjyHkChUZ3ihr8AsIQ7vUW3ZHFM4MAeqa895FBAuYUQQhuPfomeDSNfpw5x9gO7D+Meyaexv5mI5Y/mLkdB5HBt1v6WMx9+Z4KPGOPD4AjleYwcmHsZ6bx9lpx4InDoSPxIxZi6vgwT9XpUHydf5cb1/OPE583GaRs1H7ekrODc7ACVf6DMKLb8wYlZkPSHMdi787qmFLIHP5Ol80dRmY4kOAfpsN+ZdoXS3jllre0sa9zVL3znhccU8Y5L3JjeWS3uMr0my/cxDPv+heEs8ZYpfSJ8j7NK6NxAKmvSUi4ITFkmBAYf+EGL8VFZKnO13VFZ4B6QWtNHevIVzA7OV6uQtab7Mft2Xsaxhg8s50Hjnj2DiZCsdI5bdv0Xu7qmEeqj4i/thbM3fpkzXRZC5jVCOUlSsTpg+FMdzBaFs3EqQ6SS9A31TsNPaeYl0rQUgw91X7pNWP7bDzv3RzkxIznkiLQzRPG+UHA8SUSjrpsDgmqhXkHPwksA+ZWM4z751tBaR6Z3kiwClnN5AG9JJp1ky/w04CCPQT+/+2yZWxQoPaOczrSBXMG0LyepbwH88PFdSCzBUYbxdKdG58y01A9D0tVZzuXO9ZlQRHnZQuWtYLYSrTqAADneRMRmbmXa23IYMorqZNL9OA8tZ9Tl02NrwKp85A62CoMDtUWqWF/MfnHo9xF+S4NNtngrAIxBVx36/sowFYEBy6R/vzansnue57v9tcvqCAUEZxpzugAmJ73V+3hCOD059909IYPl190vw5//Amnv/2WdvJyLFu6zgAeCbgXwmPRM/hO9NoT1Mbmz82ZjS3oabdrfh+u/P092o/jiOtQFpTYkLcQjfJU8D0jtNYM5l/v4HOrBX6OoRkf7hlN1lWdjVsPR/0ZmQ8d+ujTxpz4ZkxP/NfBsf+GBvTbKO7lttuyIXEjk4ScguYAmOeFQCtvPOJgQsn9Lz/h66+fUaFkv4VcSPAaVy+O1AU7H51gUkRvRsy7Db0uC1ZAFUYYTNASCjsddy2JWYwX2TwAwNIkkkW9lKgJeYlQ68eCzGoUIyIuxMaqmuKlPwxlmH52EYVibXysORVEECdCRAs4k6zvS0pTi8StdI91+YBl7VgPjGXR1OkkB9Q7NU6284bn3044tTPO7QHn7YzztgUB1Pp53dIPHSyFnRFvuMLzhP54BuFog7VU9RD0bz0YaxFGl0cQH9C+dbz77/c4tYbjYcW5KQPuimBP/VhAloHNJ2+wSEART6Vyh0HgTwY79wAe0R+A5eMHG5dEHzmtSvRnu5XrTBe8x/JT1TqQHtUlgv7AKOUJQEURrddSLDWmR5+PVFD+z6LNpcOZ4LzDMn0b7RoT5Xf6TjCA1ZSyHoG+WEctPQfggnEgW3NXxMxRYghDp58aj0L2NIEjQsu8qHw2Pn9bM1UsX557xwuriHrzFda9YIp1UyHFa+Koor7hBEJBfTDXfOu7vrcRJDxFNPCW1+RZ1gJIQdsETdRJhACsyyHOFKDpU7U+LCBWL6u6VyURRLpGeVl5gjjCaf/yP8L8e6zx79RudkXj18BrcDylp6cWTxNLEPRQ5Pujw9hiitzEBHgmELEJlcB/MhleRuo4mgZHBSChCe+JpyCToWAbcAqkkKSgKfs1WJJDhP8Y6CBwwu31dOWbCxR+vt1g5F6amqvAShZk2PO/NzZZI/GHorWSpl+utg/MXXF+SfSBVJAoVj4gr2W16CqNVJsZyGw0E6NrUZHRmHzBSFMVK0rz+vn9fzer8UK71mUWAEpcW1Ci8pQOiFBQ7nQ/t6cOSWLqj9QxB153RunaZxZTeKsin+CGoRGB4srrorEaoDtCf96mnkKVSWOfdFyDz6AdKJdp25xZn2ukBxO/W3mvAbXf5mEsn3+5BIdxJQunbmgY0ra/UHZjUJpyDSCuuxH4Y/OZnsaVhKHXQMM1fPJ7tUkPmww60Qahv9FBvncoD4OvNRzs3s4UwDFm4/gYGHh1LoOi9BYY0ciamYQAi0gGlLZWlpFeD4azAzdRpCGOniNSc+AZV7JQpYj6hCmIyGAmDB1EqL1DLPuRiKoOukhEQbRNa0kDCN7V05prNggznq8albSY0RyW9UNsjcLYGgKv7xmSwtf5DK0zKK2hLNV4+cGPhHEr08NaNeqqLpZm2Qya5oTLVte9i0aTmeYXYq55dSk4Hu7RtorzSXngZjU4mymiXKnstFiKgGzNPIMPEdTIWFdVrFENulPc6N0lFNPqaGBr0QuYGqgZV0oCabofUf/a+MgSWYJ0P2tdsG3nuOY8CcMC+YBhMLMsKpGxKc6BftCyP4IOnU/vQ1Hse7k3dAU+qYulaR9dDqfLwYsS3ABvvH6fy2gUNxoXQKPkPGOByVXOH5fEkzpcSsH58XHwPaQOj9tmjiC967patD8L61rHuYtJIV/Il51Ho/h5wKawwALHh6LTYd6YWIJF6aeeI5J9UhYNJBb22QmvXSK5yby/+1l8Pi7AIfP5FAQwHDWJAmfVqnKchzSKrbvLKm4876YE878ccGc4NjIYZCrkkg/tNkBxXGR9ciouopkKQJqKnASaaa2YctC4SaKBf2tBoWplBwY+LqWqfGznG2YEIXOAAYyWi+sIJK1w4msyg+M404mlP1tKFOH0+eDi8eEAdcEP0ORCEDyNl27zcx8wIwCkzRBi8CpZoJIEG3u5wh+b6Iy/W9LDGPJmutffmSNS494xoBFhfSPyfESmj/sBWOmK9KpgDDD+5rE7X8OcxmD3iKQxCcAU51bGgbY70h5l3BF8k96vfIPvncvknLKFzWOXaa3c6p/YvZd4mtTyvHScNpG0v9mBemTL8PW7NAns+fNL7CPBH14+FUTsxRHHusqgGbqFlsqwjDWZ3yIW/Zx5JMSmiNMiT5hJrno1ihR6Of2xQuuCe2makKFJZeXiuIXYSkDQdHym85HmHXyQ8S6Tw0ZV+ZM7JxZ8wKQg4VkiSOtovYM2z0Cjdc+LOffXoiVjAECkaA1l7ljWjrJVlM4oRUCkpf+8FJzKWspnLEuNUj9uQBc3dotAuKsOh12TVud57+lPAmQnna4D09KX+my39O3AcPILug+X/ySRDDH8ZfjCdCEH459UGnxE+SxoIng22BroS2LXADWkQxCGdW+HXZkLPyWhJ5RxNsbZ85TyPvVh9PTv/2XbJKh9v63+mP0lqI6zOLzYuXBD54JhLGUA375oFt8D+QkcboF6P6HeAb0pTnEH5m1rIWsRadr24eyC0OUvhxVWHAEQtZdUC5jpzNi2ZrhAg1cYwxFwwq/WIsrXkCkH3KuRkbeGp/MZhQiHVc1pOXjSYV9EcDbd6nFZY85sJb7a1oJfURlCZbjOHbIJ3t1ZgJ7hhG5HWPXgZA67fmZLWlXfp8TLYDjLnUkN12KyncCypTkvQ4oxiv1d/vQpaOOTGdCFgNNfPgPEqP9j0Yy8KCjEbrGIkTzbeb23JXVsRAQ8QXBvDECl5E5DCkckFKUfqq3zdjpPfMITad9eQsBnnbNSBH56AeRn2kk+kpltSd8d6+25woCq6ZxlGJPpvumqPdM9+yz0THRmsxNcM6A7bp/7c/VISjQ0PeG1zwucPtUobwYSNNMvdJMVQm6K0Sv8ZbdbJ7gqyTvh3TFK16f/T2+vDbT6NzSg/04tuOmXiaMMtIROQBFNOQEWfPzpJzx9/gJgpCQBxJKSzkjru0O50SwoVgnTG+j4/oBfvNPuuva7IrZ7qJJyfianOC6lQriDH3yVLgc4zsfx6vXEiep1GkiIjDiEUs7eX0NpcEatRxSqKgAJo3ZFMtt2xvOvJ5zbGeftK86WYnKkA3TPyUuFE+JdbvQmkLNi5IjGa7SZoRFnCB/DI1MEWNcDemuAmFLOBWlY6kQy44ITQUfsN1fqDoJnAM9xP38V1A9QFEW2Zh8J9ev7yaDkAqInQycjssWFNsuj37/2MFINxYoMha9TK2OU1XA+nyIPYsC49caMXo83+/dvudFII+mhAlW8T8ayE2Dpgixiy5QpxVKoqxBhHl+sadeFu/4VNp0TBSHSv0a0UtSy16ucBJUb+GcmzreaQPZaOJ81WSr2ClAnFNMaqr11CLjikSZuzGWGUAFb1FERgjBlCf5ftvmZDeV9GnCx1J2RCUI8Q4Q9KYNZA2zfiBLcDechlwozPswRJ/sxwdccZuxBklv8/6nvzOruz8qVnb69GDumGVee3zOK+THHufDhwwQlokuceWNc2SgTawVEyt1LNe1gybowFq+La6/rXfGTs2+XsURJmZJm96OR52NG/7hnS2LHKOaWWXZAngG6ew1u+H3bfvwFBLoDXDGsWR8omOu3r9blufn+ns3s68VavHLP96MNAWuCx0uc/D2f9e+959o1unnnG9/7hqG96tYL5f132vdZ65dfZ88TMAZohiCvcw5z2CBCOFjGu9OHMWwroxH51PU5N0DpvxK1uB2eHdNoKkyNeM543x19IoLJjdnG9/l3VfLz0Bj4qBIu9ehxCIy3YrBoTWh0hUk1VvYRvZ2eHwbsGk5dlcrkDEDCKqPw4NndMOCRVb7mtRC4aKYnN2o5IfTyJKCUkp4MdxXdHxFEvXZNZU9ObkPZqgK3jYMKRIo6MBAgUtQJylhUJ1BZyQ2BRmcQaYQztBQRK1sTygFaFiyloiwVVKo6G8deG6+36N5QNUcDd3yrHdQWNRgbz9dy6nxGipwdDpjwvES27rDU1bBqfSJ9p0zQSW7Pj1oCoNLYn9grV9IDHV2VQ6aYZ3OUrku1aAEv/UPh0xGKx90ZrYcD2nkUSeLWovRKyHaiMbJuK/GMAcKwiDRL7SsC3jZQXcDtbI7bNBnPAUHbNOtBd0HBYQPDITUUZGms40iPixLzQ2oJuwl00FG6zI17ycjnRjI/V86w7V8CIDs1vhrXpTUnKMz6peJnx6+Q770MeKcSMJSjtIvXOwMsShBJFpXJcA5WhxUxI8tkRIcko+SAm1h/9nHtqCONNfbMG7FSju+iVpvO3kX9Yni8FE3RWshxl+KbKauMn3nnl4liD68ttY+NJmMO4kxqR2lPMW939BT4ffCZaSZAEVC2LYvzz/NYhzZJRxFwx7puWTiQHeyKdyxwxDa9b8Cin5uEX/MaXYVVx8P5Fu00gkp2Ss/dTHa9zY/sr/vn/M+BRcTpv6T7MqUYXNiMB+ady6s4sn356Zp7CRCN4+6DyE2fJBpB0eNNPyZfxF6HUc/oZPBd8zt+/I25p7EvF+B9Ce7R3Mn+oi9JGZtsPh64obisDHww6d8Ebsqcl3d8U0d4QOC1v9XZX4jUoaIQ0Bnn7ayGtmVBF0atBYIOq56HiDV2+TQbOHwrzGnSjdwg4HA84Pkppc+NbRuOtyKIEkBaigaR3UX1iVqayx3tHC+UQqCyoNaO1VL2Ego6N4B6HJS6uIGjGp9XUeqin2tB74CWWNBU62z/4BmR0pYNOrg7v6EjNVoc/cy0hdM9kxOPf9rhCj+mTj0I7iw48I/jLh9oS4rvlvPvv6ENGqI77yUe89hy+33O1n+9FiTq2m8YeEmghvM70CD5V1pGLwKganza5BSa+/eN0ZJ/Q58XmXBdN+W4SbSjGvKPPh/O/Bj81bV5eXr22UFYsC5LlDm5PxwgFjXOrQ8VCDQLV2TtEYGwYGsNnkFHF6Gag/dM7wt5iS2VQY7rCjmpI65g2JlcR+kBhxBgfcMZ8QJNlQjF2QtoQFzeu/KHQSCJCO/+2x/w7f/8qunYSctrCRzX6QCebTp3u/EUXEaFZ30jMj627+SsWmrbXz9j/dPP0zU3ogMjit7AYNrfHLD6mnaNG/iHtoRb451URvnU30GnGa/y/q10Ui3Oj1ew9JDpPALdnfXZSs6WOuTNict9QW/0X8Ex6d/AgP6PAdOsqFdhLhF4WGp2ACvE6iqoIMkE3LGY4ZzQ3fvaUoywRbCeA4nsOVFtbEXTXPnmvNjiPJkjEx8Qq9LLGYxh2M7zGIQAbP4wq9fSUx+/wsO4EPcRQrAY77X/DXweyg2CMpddmtZr/KTfKwqev30D4R36EIvs+ROKRVNz1E+muX8QvBRW7E82ngMWzVJBtaHQ0SK71TsSfAD3M3AWPH8+49w3bP0BrTVsmxrPESkjj+Et6sZ0Hc783or7GF8xQ7qPx+uSg4CF7kE4GvMHPD89a73aJBBRMYIqGiGjDpzZW3yGGAKBrU517M/M/mvCt2+Egg58KDjeraYIVM9OFgFVqGLSBT/W2o6Eooqrrl79/YHVeE6Cig9QBR8DUiCyGZM8Un1K5hQsiqiJ1TbxlOLh7X+b6RowMn/eM7YdI/LcmYY9dljs2uZQnuGabjxEhBVaz8bTnbp3cK1LMGhshvNmEWC1Czp7+n9dChZG0cJYUxr0Dmf6VFhbJL+eTFFpLJ0ARRY16L8bCswRTT2fLO3DakmTRiZpasYSnpqRg0AAsKhXpkfUiaXM7Ho+1LNfIXHjEwgVVf0PwebL6+93Jig7Ufw9ZPFCXifs9ukVdIDGfteqQqorlAGNPvMU9OEAYzguKywyw+zOJBTKSUtVJiNqzz1UVQlo9/WkuAYGHiA3f8lg4PLCkeKFMPg7PXCEz264363HdTITba9f0qPL0c8Y19x3nYxIgBT1GXXhmne7Xr1cgkVkxjpZpDw5ISGCcE/7PAtKe6NQjgTwtMXxVhl422vR67Zb2i8TpCYGPc15v3wERHDw/veX2ls5lcv+CYd3K0BAe1DxiG0OMT8Q5Hng09+DO3orH16wxniIYAocE1C72N5yRMDdGqmDwhjHpUJeECT2YrB6NlxJPein36dvnd87Itq7/TrXi7W7rlx7HSS8vCfq8BQwOfXnWMG/viQkzQdZ8rqZwGKoJN0q8/O76bwFzudX7ZFY4k+uvjuN4UWPUMWpaicYo3KlJplRJGpqA8lxKk/E8YKNqQz84sqXarUkPYqn1hr4JoRVw/mRMtv4iVpqGHXiTCym/GBLcwmOWpe+/+E85MYOaHSRdjAMxMpCCaR3dFIegvuoST2ioWjQPyLjXZLB23F1Wj8AI5DNEF7nkZ5clbp6PtbDaryMZW6KfdV+6lLDYERlZK4iWzuPjO9pvoNy2CeLJK1iDlJKjNAbo6/d6qsnrpA0CsTHJLZRYpnUp7Pjy6laOV0HkNZktXuFSCPlowZziZFqitgOr5conB0l/AUeda9/2fZb2UECl4JaNLJkM/gNFAmAkopHDdKCwgSRRdOYg43HVFhuzMOzvwNSZDJejGXanfeEULNzMgAshwP6ecSNcE9SpxAsqF/32NZM985qNBYCm7MElQLpXmtSjI+NTVdnFKQUteaQwV6apCT6Tok/y/zIYAviS+hsaGSNcgxF7J8SBx1yjONgW0fnu+1sDD5ubziauvOFTQueBhCX9OzHXen5zN/RDQWUTm+UsvCrwiqb+Bl1pVdzw7mMyPOcvj1wkOMeSCSts5gkEDFcWcGS9kN9QWK981oMh4CxLD43P2MRwZ75cpfXDA85oxjwaus5QDt22MYs0ylwOIKIOgS7pTTIkMEAeVYqU71aFGvI3WQ4XMZ6AQBTgVCSNWjMPZwS7DWDlxujG7As8V1/EvO52sHABDA+dueBKKYj6WcYDRvG6Aw7ydCeztTgu0eKZn9usOhjLMwcwnlOwzwrS3nUPidA1EtprLdZOTl4k2GcIx9LnO+BA8h5BvtLGH7frmXJxthR/sWf9o6c8VA6LVHeYqyf3kahy3LLzEsczdQujvQMv9EZuUnZgh2mHy87+h7/ljOL7J+bUJR/KPtOM783nzDVLZCdyYGL/b1IezDuGXjEHdGGuVPiVWFeNToeznxKWQFi9dFigNaKumkdYRChnTd4xOnMFtIYd1qfbduwHA5xo8vypRRw7zgeD2itz/gblrXEztjWO6pYLWVSPN5BIwOkLIrjivFLootdq/I063oAqKBSQ+s1+E4RzdhSjPdZikee1zkLkmhGHzHDtxv01cuHBq0cuxdYYWR6IOM7PF27pfGN3ZCY74RTdrA1n1H9vIjT3fEEi+DRNAqrRZKPCHOayODeGObtbE4CRxl6MhYJKc/zY7boY8cHpEGvQhd11n+4Bc75nfv9wZYNxN+9FwNfAOO0DrdERO68k8HSwfkZ+z1xumABVtN/bs9W7qqaY4U5+bpM5uPUUqkHy5g5HFRAHVQJdT2gFEJrCk+l2hlzuCcBhMKwDvvJs/osS4XqsMl4JB1rUeSj16BOL53FUs1nip50d6R2ni56jjp3W0PCYVGzs2v3q2fkYu2XUFBDySooZUGBoHSdQ4E5PJPCeBeN4ve9WUFoGHC+40oh0DNzZzi2EkBCOIhmXXYaCwDyG7D8t3WUAbVsYgXAmZTC8n/+b1srpafv7NlHe+F7l3/hfLndl+h0TwN0/rYRoYraKSBKExlD33+reeS5vpOwQSwr7PXzdykdXG+3fh/4xOF9xrMz/Xmpf8+ogqRH0+s9yTlOTsZ67XlL68+esS1TEuSoyJLHACZvOJ9dUrYSYwwHnVYZonfVT7qjK7l98dYC0aA9PofvMi3/wu3fwID+j27Xd+/a1b1DqhOODo1OByzt+w8QRz3o6Z1+nXSzXo7EvS5oA8MT59bvdON3iAq67Zsqa8TSLjqmKVabTEg9rwodMYRo2nWls+mPTuxuzCEZPBZCpBMppWAtFeui9X5QCNyBhg317g5UGk4PmjBm2zb0/jCMhIApu1KKwemUD4xN+S8wlKVkflOJ2YiabZZCBaGUgEaPmBRI1qlHqBB1aKTKQG77EV3u06WwJEZ8GQL5xpCDMQzGcNKVp01/CK/gImDwQ4GUBzOUVoA0zQwjpddyZlnGZ49ecMFI5/Fyuy5+7T9f7+WtkejDgP7yPaUQlrIApU4K9cPxiFqqOrwwh/G8t661pfqG1k25K6y1N0VTsoophDSSRus4ajSIpqhBjMuJls1/B5aTAjRgZD7RIhxrGnkM7NlqqYDscYN/htfwbNzRm56LigOUqZVkuPD8Et9f/f2uTUN/5XOv96yj3WcKxWlWBri3uP5mhotsONh3ZUzzZKwzwh+GCnuU7ExnJWaeUcwl/kj8v9QSThU6FAmcIumEUNpZ+DvT/MYw5/iWaIZL8xx1OpaC11fPJzX1HjePd7l1meaomzzfiVEn2l+JezNjL2lt9uOfWkYg9pciZJXG5zSeiz5vwNjlKL/fdkv7A80EMeHU34ADx/X6ebN30825vKrtzsrVW3af/V8x46OnZXaF0mvYnxffRzfEm908B52gF+/L/b61XaNTNH22/28CWi/7vy0f7AD45gDkxrxfuEeG4Hv73f7xGv57a9uvyqVg5+0C1m4AX74cmXqgwqSWHBllOgqgxknx6KZU0mCiqYMnGkacfQR6TWWNTNg3p1iBlVASy1ZjfF8tNd6ZHZJqtZR/dUi6rogPvOQCJ7nhW+uUezkEIqgBDIJqfGtnAXd1Yoz1MmUsIPNc3MBjRgD/F05fhSLiHWbIymWs/DDruhCkq7MqW0YiIhi/pGlESymgasonTxEN4xWb1rXmULg6xBjmJ0vLz4sqDQQAC070jDDcc1eDQi1YsKgQzx1dugnzxgcUirk5P6QOXTSMeARw01IuDAEtIzKbjZfffP4GB2Wp6Fb/WyNECioBvQhqMryT7a06yOq+qsBkhiAaecpU/+XGNgAWPSYMU/Q1UCWwpUN2RX3J1g3nSXxfPdvSQuCtw52Mwvj4Ai70aJ4MW8Cc8nDIVANOfF2lFBQ7i0KqwH96eFR4TXIDYCnpXZ6ARAkiNZ5fMo+7Yx2ob2SdyeMzxScJ1HNGpv5m5bmfS5d1JHDGuGucbT3Ot+jM1cuXuG5GmXnwiGHvbp1uYwYXNaxFxGPXGrosnhnBcQZHFjG2SBFJZzOGZJkjAI301GPAYeAJvsrOJszJoQTPjIE7yW+UOG96fUShkl1zWUXT0yPOsUszBlwBE6F4Ex+SDL70hc2QtAlXOF34q/SvwzRCbgfYlmdEULqDNXlUauLTIDROKVHIaTOB86WLyYRjajjcBV2lsf4Uj8ONWbD9DKeAaXYJ446b8zAujImYzrmNjS/7jJ/7PJar704jy9vov7sDR8gH+zMj496YRuorxp5vddi7Itc5HQuomDsaI3cZSHZrNc31CtNzrX3ntsg6EcPP3P/f2b77ToV5f+PLHe35aZq/EyZ49OemGcTezfB0ATq7NxfTaYRTOTSluxQCoAYqKrrXW2vwKH53vvleWw/rNIZSa9rsUQbo2m6QGRdQyHgTRmnNwIqA3iFcwL2BZYVHrgoQuHqpBVgPmi7+/2PvPRccOZJz0S8iq9DdY0gtJZ33f74ribs7pg2qMuL+CJORBaCnZ2aps3t5k+wBUCZ9hjdtNaVbt/R60iXpmubORKk8D5rSlXQS8irp6OHIEsBHBySsZ0905DaPiDKiRm920UG7lbW7qjwvx/YIhYDLe8colj9bqPzF7yO8ubbTjP71vv3UYftzlInmKp+ESwhyC7Ioz3QVA7i7W3F+2UwW4nTChJsAnLcNSyrWk0QAnJIO9ojUeZSV3ZHONicR0uElHWbYc6ofDaZ8UCEtYWb3JB+RzzYL/eAkj3c2LZQJjQxa4hUeAAAgAElEQVSfo5yVnrndPaJvmcXgXQJfC8xglTXNhgAoFjKls6hiLURNkl9lwleMkPqV/HwiyzseTmqsodqeV00jtdYVUguwfvVo/Eap7QZFqTD9VgM8wmW2GAQ+JOWsmuLb5d9/vUpwPxHwoeyXBYT220e8/PVTzou80sfrvb4OL26SJz9QjutSP6GGIxoRdq302c8CqgIJy1ya4WDPCHJ776kzAOD8nEc8ayazFnA6qV0QgSFrjM+f0JP+s5R/YgX6H429roPzTCkevyWIBLtxun8wId7LM5wkMt/MQLoHgPy9Zff2w2IrN6vU4zRy8BoCgXnz+XCMjPTRef66tlj2Ejmb4L01sxEjCQ+MMR2EyLVsYRxiPAoAXxX4aFxz/yI4/WZe4H137xT/T/BoHudOhVRWQPDslQZ3aqGBQebxGPlnFIQQiVk+woa2rGjrMgSMvYHu2fJBSkdfdux/szGHtwuI3CIcUD2ZIjNIqGB4b2y3sFJmROg8Jx4FyHDyHopJfZ7gSjAmNiBNDP2iwFd1A3cFlMEfCPLZrMxMkEpJBAj6gWAI66t7n0YF4RkhdFs+LI7UO9aF0/uFmwmO9s8dnUyIxfoO7QNj/6JorFBuaMtXNGpOELB7Pj4h2H/SQaiob0P77uEa1YOkqSACVNZ1j2vXiOlpvsv3QEazZ+LF3at1xHrysdLj8153hwl2FhfirMygyCG6LCbMVEFrzpwsFkZ119VCmfSOXXoq0KtAru8CFULX3byGyPN90hDwppIXI1QN+75QKPYn29PEDFqsTgBoq3tIx7icYjKBlStiCVia5QESzydJxCbg7+7pKmZpTMQWtj0FQVZ/x4ajN4kCU1SMuraEWTjx5jKtL125/vqr0f62b2AiLIt59AZzOiIRWIVdLaxbW0rYXhQmIAR34YlYmPZJfKDjPSiK598lEQFV92xwrx4gLbsRwnenG1H6ChQr7CTox/04K1ALXQco9mDe1cIXJ/Oo6oa05ASPC/jJaop6gtSfjASCkVDLwT4fL5r61EXBjUoOnDENQISxC4/HMc6lDc/gC3hRuOCq/k2mItsYYfsv1iDOGUbodMGGYzluuz+CKiEATCcQgP2rn/NkzBz+5tNBjayIzG62RW7AwfL9WglPqWt9OtZhc7WCwWjvzOs8c4dmWKnxJFicESqw+tkwL7P1/9ivaoAxy+cqBUG51xWDOtPy3KWRiV/nt6zgjFeOWGb6fRO4Xacvr9fncwetW9s/L4W+1/DeTTbqdjdGeeumvom4D7Daf71ZAHX1uapCgSsSAVFj5thzh4dnQgMg5PRHeBGW0OrHhuL6pEB3mo0QipyxEkOIEx7cvv90eEMNBdBQ7ms5Fz2jHal5QKtRWZYDnUYu43U1T2gPT961m0eyc/zpgT6zBJ6CBu5FPZT+ouICUFOs9X032tjnL73WfQxaxoy9m7KazbByl7PDeM0QrtwaTqcV6+mE07omLWMW6qY07+JRotRwXc5FYhhkPyYaAsDLdjY8FhPpvIKyhUg13Ol4tHvIelemU3M85n0mpwWE3ZukNRO47wpS21PiOUoFlmvU8Iw4/R0wbwEvOnIm+ztmuNomw11EznA0NO6gE6PvAiE3gnQ+SDN/Z5jECtxsAtpDaOEeZYDzW5R0jZAJvCPqEZU5JSZQp0FLF3weCmMA2J4efd8G54VsdwhZEMS/GR7QUCTahjPvPKl0l79Y6xnK8zDAtbnKMweyc3+rOFhM3giBHV2gquOMEnVACVPEDM3RI5S09q4CwSMODT3g9PEsUL1WylUdz2afY6hxQcejMQ3pvVTPB7wfIpDm+b5F0N16n1XdA33zXLXIfVgV6DHXwasmLWUS5ckry/aT0YaSeXUx1lRgaRNiw5V464a7gt6MNu3PInAM+ppbROMbsJYCxlGaBOfzR2w4/7rw106YEZMcS1qjD1DQQjSfG2aj1ZkFIsbJHpWHzOZ5rcHAq9G8StXocdCixu8PZXJ+19H3UFpraSfmpPq+QouhSJ2FouxSX4T0HC97bbRVrmuq8MvNUJ7rpETXXioEMvrT3HvGCMwr446wR01z5clgDECeFmIydMFcUsFQWiMd1we/B4QQngCMEFOKdGtDHFNfoxR2+DV/fsAYnSbwGg32CvTKao8ljL1jz+c5rS1c0ISvlHrOL+55Hye+mMaaJzI+vJw8FF9ejvemwXsIcw1e8sAfu6FNgH+NkH7lhJTOJP1FBPSulo9YjS57eXq2UTBjOS1mcIlYZ3gbZY1jijBHrIvZOPLwcZbygVwWtXNjFZkHbe/YCVhdDiFdse0eBW8XEDq42c4NoycCY1kYoAW4AyAmL5Iu2F2eq4o0XuaFk9ZTqDt2dOx7x9537F0yj67kGs0wVDBgQ0/FeRhcRuj2YXQ1zc9huXPrJH1hTyZkprFPOoyLPU/nXLHR62fn5QZdEDnQoz/uDpRtFX/j7L+Us1ttg85Xcwy/Xup8/CuW1zzRV9xmFYNW76o+z7bea6yj13vncD6NdMlohO7pSE5KaO8Iqhvu7iySoJ1lGiBMkQYkQccG3yWiIHScX0yZLZ4GiY1Bwod/+xW//8/vHpkTOK3L4DscP8aer+dEYEbcShZVYu9Ge7OPoYtgYcLz3gvo1EwNIdoR6TzrfBgNDNyfVudNLJqpedY3Tz/KuUfRzFDcvH3daTHWhQBW/5Ky1+HpDQC70xchXYpc5E9kdQpZFFlWLdElw+ObcP6vv6H9+y+Gp3fCu3//BY///TewR34423R4BIIRAv7BPyMvOZeTIhhxABc3uv27778H8Zkkmgy7w/P8/D9/x4ZB194r8OzvCkIhD2yq6L9/GjKJC0Rd9iNeOb8H+Bfl8twfnwp8c6P92kS9rQ7Tt93GsW1uDFVbukZ5XO9g4Lnj46SUtEDQHF060IF927Htm/HZxQFAERFVyIy44NSdKmp6K9NrhTzlyP0ojrjoX6n8EyvQ/7jyltwHY/Evj0scsVvVfM9mOB5WhREUp5v1HK+GUOBHe3C9jLGRH9gXAPdoH5d8wrwLxBgdtzqhd4A+Xu8BfxgW2KamvTNaHabc2Q38mmJRh5AyPHsILqyMHHA4gd8Z8tr7DtkE+9/PxhvxyFF5FGgOsq4SeNfLBd8Ahnr+woAHRwUvPaBYhJLl0yZG5EAHOXP9tYTnpcE8X+sPB8opPAdwD0s0AOxf3hlyIkX/4FasyTwrgEfLxYQHKL4C+Ah1NTnRM4AgJHzMCfDgPLTmX87ZjYm7ZHILcX3j+YpXjuzS21qx0jEI5kDWwJAtEAVrPzBpqoWDMRJFJ8XiuUbdf8f2nwuMlRt0WbCqmkGNmFdWd88wcUFX7zsYHX1XiHg4/osdiLHRcn43mFpgEPogAq1lsNnpgr7JDFkG4xfEhKYniSkARuqIgGcLVrA2tAfC/hjtkisWvw+mHD2v/xGFDr/oyj0VhVAoUYZQJr3bypzYsaP682pLRwZ66gUV4SFgzmNwoVkK7Y7v+Cdz5mYkj2xhISwtNFP1Qhg7ZlRI5d/pW+wLreMbgryx1TxkZ1v8+bjv+M1fDavZ8MLPs0qlB1WgQ+O+wpiEtgzW9ZI3owxxfL3oJGuZ5zTw8DByO3pvzE0dZw0Q7GAsYLiR2RVF+h9VKj1PV3fgoDWO7ykWUwzcGOv30iHALbI/+reCwGjvzeN05BDWsS9SeDIiXCiQIbBfx7Wvr9m1fo3vdHPAP+J5PkqcvCEGv9WQbgo6Xd67zTP5mTuCm/I58OEbiNapEk34Bwz8d1nF9T78TNH65dV6af56dXOkyAEgTxGgPcOQmyFQDcNv42YBeLG3Mz83BgzhougOJTq794Ex0dahxiYKEBe+nk56ELIWxpvCM91CgRu9aoIaYsa+7x5e2ekKIe+uzT8zoy0LFs/FTqDi/dNHmoRIDxWaEafb2JVfSyjQgaLEHtbkm+dyJyKjT7jlPCR8DJq5NTRRKEd0iSFggtPtCzPW04r7+zuc1pMZHBIy53Lfrc1t37BvOxQbRM+JVwKbBa0qIujUwcJGT1FPwXQaZyrQZVjFpxANZjjArVl+ey6Bbwlgsv0TClLLIxqK+G5hctOrVqDSoF1ArJ6X3RT02owPivCKIj33IXNLby3AohspN2Ru6C6ueCBAN0fVNGc0iFjpGAKN6lUdStyO3fKMu1FH0ukIg9wQPFYhRskI6tLmDOfXNXmRiWguxZSqzijsHUrw/c4AD7wfxhhJGgVtK0MBNTxhR1NEHv5e1MO53zBwJocNdYEx9uk0nWq8UXiizwbuRjcHAiNFiuQMNHq/U4k12r4KsgphX8dXyLLynua9CgKHfmYAboKaYJMZ1HvSXTaPxmeqmAf6MLDRTKcS+yiaTUOjwJ1kBuzkxukxzjSC4BAiy0ysaflL2rLco6TMbBzJZ/L4fQ1RlGhIx3l+jY64VaxP19eNEHvP1pmmv7EvTdbiyv+yF0QjMl3Qyany9/p97tLYQC3cde2LFsUy5T85r4PSrZMwJn8orjDQQ3ki7h30vpPA367pVH8+K6Wdfn3vHxWQo0T0MlfkOcxRWGjrqgSAwg3yfeBTrvfDvkMYIRx6QwHXfM/VOYCvp8LThsTZxgWsS0X5BGcui06fw+Dj7SUgZUQ2mNf+R8vUiyt1DfjsZy2bPY7g8uWhPC+yoldK8N5jRaLeaFHLOpZPk8qX5se5zPM2boEb2VEKuGNZGKzuQzcnw/BDuUaSBl3UZUiRtD5IlGFwg/eRLpBmqf26dAsl3DuUzLApjOaJzGyuLQ2ntoIWo60UcBmTJP3Yu6TckVx1YTyXpevYuqUaDOW5dDtpgkj5E6HlvauISCMWItjCtWtGDIo0K7cnap6tYZhQTuaVPXILWjS3hN8vZNtzWdX2035c18N3gkXcPKYWnfpyuT3+/1LKBrPnOEKCgWPI003cBpUKgN8T9q+hyLUiap61AKBPAD3Y08N4KMrAmHvvWJcl71uofnW+AgOPWrjVLL/9+294/PR51guUPR74sdIsXPpgaGP8jv21y+t7lQ5zkxBQzeiFnV7uIkYrIORmpogneI5yMi0EM5sDkFfYMNPbO26vQ+27AjgpcCYzYNghWKFYEC4aVjJmlhNEvf8dzL9k6HjQDAYIjoZp/K6fOP4mwouHok/ZNDl+LrRWpZnxyhhjDY9Y7Fb6h7eWY51/CMxQzcjLgUNoMQfJ3Y0ufmQQt/ta6QSTN2ybRdfdz5unQTG5tOngQi/HYJLks7sajxKOuQBSn1Tb/5n5/2cqf0oFugGZYN5sKYPE7mVl16DfMQ5wf37EM4C1KhcBqMdklm9sjSB54nOGufZjRWEUkmnXBGYEC5kAhXl1wMKLKwAN6xQaiAHAyG2AAQSPKiiGEZoAIF8V/HHkRBy9w8RUf/rr7/jLf/4fPP/PC9ZfVmO+3wn0C0HpZQi86M4A/lcLv7m+e0hIZEpNAj8ZMbvqHdaPDfvzSwLrEE6SM10NJ6zvzHtEd8G+7Th/3szrAADwYrNMcE/wBx/h2VYz4+OFwKXMBBW2NoB4Wb8QIhg4cWJe2a143Jrtq4IWs6KmDUDkQvLAi8IKEnJFpqSleiB9luHpELCS6voZZQBN264gYQj6BdCPQGPC/vcO/sUs9QjA+mHB/vmdT9IjLKR1SyZqEOUE4AHk0QKqAA+K/G7CS9/1eo39oel39agAbqcWiJJGw0QXAcSr2DwU593rzNwodijSIpLJdkEvjdLhWRXzDuq94/yyobWewvUQNrc2IwSR1UJlFQX61ne0F8KmMAEsSRIh9SxVZXbCJCIozjg/RdYmL9vBU1p0CAtUsSwNRJYzE6C0pIywXAA5wWahzfZ9s1yb7lkq2KFPw7Oz31AmNszE1bGoj22apLeUCyZrnudvlRAI89I8HGwYicwCkghzyJlgaGL/CuHmbVcYEFVx5Eer94xiHEpcMtnsJJQaZET1RE8BN8GJaY8QQMCwXi1I6eoE2G6JnFBUlEfZRxgRbntm5AkPr0GCKUb0GpUWQmsUD7YYK9FFW4uHJB7obPYKcRDsHlM6GTpRMPoYwuBUynvoq/BkMsKYUrCRa1j3Twr2D0NC8ZAHwDhBcnf/MaTeaG1Jz9dob8D7ASsUZlyRxhnH+r5xQL51fiZjiCvvmvIcWN41rO5lCiAZuwH/B84y3Bnro9Dn8DRSgCIH+bW+DJwXRcvTcb2BIY43Q+FBh0Q3Oa7jGTg0PBjm67+RM3+9zxflSoWx9+jK7TH7lR7FxRPf0+SPlONu/1Z9RlaOt1L1PFU0s5w36zxyplOtVgQd0odyECgKZRR6d3EKwOlG++pwGTR5ilcvbGDAXgJZIAXwJCwOQaPByxGCuirPG3MJa27tnLcN+2aW3DsRdN+hrB4S1KIFLUuz9z29B1Q8Rcxu3o/k58NDa6bAVlzI4kp4BPzcu+U/9v3bXZGuKua5xcaDtGoYFQLdoPkiF3go60KYGnR5Y6yR8ua0etQXE+h2EfSlg/cdfHaeRQRdFii6RTY6bAqKSABUwqEnDeP5nFWwdZs7g+2MhRir5363FDwWUcl8HBznBd5Ry8Mr24uttCFpn/MdhAYhAroAXfEMwrt7ctbKYpYEa0YgdFnRWNNjV1iwv7hBpZhS3Vwz2VO0BH0xqG0bO0FceBZAVLqFhFXAcwe7AIUAEkJ32iHTf5TQD2FAomLeJVCA2mq5TVVTgh1wWyKfvKoZcVB4jQ8cDG5pwMIVH1FEY7AQ/iKK8/kFORSEd9vI53p0CUk1kq91cgsH/EScvc7rkxKNbP/GpWSjfQ7YFQgie75daQRAco8f2yBQenNfi25xsISYvl2At8JbB++qIYAaA7WW3WihqaCLv7s076vRelDzVgwpcM3LGznmg8YMOjPnligNT3JUynb2pEPB8IbHfJYx6vjqcwkoeBo3+Q1VeC5yDJ4zp7Aqrl3sHPPkRigz/q4rVL4Opsr3w+UaENFQnhb8Hm1bSFLHF8G7y1BeRWWsBAm6XWN6S3805sQV6d6GuCf6NBSf28kw12FFCOErdSixvvGolveTGKN6Y3Q8zmG+G/euXxfR9Dif9nLx1lSM/hxxfcrHvBnxSYy9Ix7dIIyiEvibj6zLimr3tSjJNWFf7L9Yg5ELPcZCCKtdBWUo3zHW0UZMmaKmPciBXh3ndRONer9+CV5l2pmFh0TuqVmRcLuM3eHyhLqX6nMuexiLTaWCef9evq+oPr2F3boAdDUmRMqu5g3k+G3Mfc6147w4NAQ4rMOg6wg4Pz2X9FcK6ebdfXdacd42aC+4quzzY3l5fsHdw73j+nnQxISFFjdKGry/TVcxC/DlFE+H0nuHMpwmUQ+vrnnfaFKjGZksPeXi9GPAsUi/03vP6C3HlJoiZrDed/dC9352d54wUGBGZBQwwT8Eh/Dt3fOeq6Asy7y87KOPyrU8kzApeFrfwQqDgWr5rruOzRXGYLtHJFiULpTjgCnOA81aBFjC8dhm966sNHtbthPnrZ20yetH7NVy4xj84eU65fH9Q3nNE/1ae/E5siYHTHc5Ftmc7wD4qyln+eN7yJevPv9UFODA/d1H7OcnMAi7CKixKY49esSymMNXTYnFjdH3iNQ5jDi7RyUzPszGs64taVtRcyRhJnRXABnfoXh+OeO0rkm3RCrMpTVDH6JZh8k1woAGdmZVTFfj8+JZYAbv4PObqcGYrb9grM0AqsL4NAWwrKa32sTmqjGj947Vc1EHudiDfAR52PZ5PVUVJxCapxALufRnMr1Xc5n5RNs5wLVIrAtIf4WogDV66XCPyDzdiVLOXuFi2DMEjdShKbtfYTjpo+sUQpITisoO4AsBv/oUn6F5fhUWuj3aevKxVLrvXsez5x88328CDbEFaL6Q1NsB3Y4TVHGuJgz98viEd+/u8fyyuYz2srlrsCbpBY9ed+krUXCs6/pEPWquWsS4/byj72fjkZsb57NHXBOnihtjV3GdVuzvoUe7ZiSb+P8nYe3/zfKnVKC/tWwENL39u9KL/0iUuQEYjqY36qvnTS++fnepgZjsMD4DeA+ghFspRb6OI/vX//p/8PDhQ76pjwalFtxh+XXB/vevab3P7xgr7p25gRGXjx38fsFyf4fFhWfMhNPDPfbnFwDAen/vgrEFp4d70B2b1/kX9rCU3fuuLkwagKquTBJ1hKFEn/LnYvAFiQfH+Idi/QrAwxhThH4DFHvx7gkmg98zZBfwFw89GgxTzuKor6KwuT0qz9h/7huP/llAHwyAydeeGEu+2pv9cy8KaBrrAQLSw/8Gczjth+tg+3gnxnFtjx7HiyvfgVlhfizHe/EuhYI/cl/H9QNhOAQEgY7NAnfbjCBb15EXfV1PQ5HOYTtPKeANS2B6Yey7oIuF0RYqltMaxgFDcF+FcRYaM2bnMG9JlFAK7wG4pXCEWTSBQw9vH+ds1Im24ZXmikgMBDf24OueuEH0/LMVcSEtu5eYD9omPHKrhuCkOeMVZ0+/KZsYzJXMp2MolAURUm3IJmLR9OIAWL42/+57RKEjUorae8H+H8/kMYxh1msVIjzHvYG8l8RNMK+kkyJ5CDvnOpMIpAGzpvHQUfgz2jneGx29JKhsLWbk9hrkuRRavb10V5i3/2WS6NZWu5hThHVxIUrxxzPoBtlcef5gAh3yfChmhGLKnhGhZMDSKKoKefp2OLzvoaFfe/ZHafHLc3XJbBireKMNqk+93s7xQvV0/N8vb+VgsqOXr0e5Vs0V+vHm3p2J6suK3Ysn4eSumYMcsNQV1AnKhvctrxywsHsae8qS6n1evQ2tu8MgCCBQc2G+C23MAM3wZ+R8NYM1NdoJljczFMrMzVPpmNW2hSOnodTy+W/ciqCnQWVPIem+dzCZIjVB54FJ1zKmEUI3hLg+tW6dYvnEBaAGFjFlccByEZDPWzxfiWhTyo6875b3fLGoFMuKpS1O3FjdLfsUynOjj7AHzA6DBmuitSVT56zrYh6hCshunlXbvrk3vwmH2XOBNjXl7bpaSHlTBBp/ABJ3+ixIRjvU9zOzCegyfxs0514lUgEZXczcoEwgN2hgEKibBzz2s3unkAnKQImD1dNQyR4hoG9tdk2eRHZc6D5SwBvHwiMEWG7r8pyvj6ahge9vp1FDwDH2IbIOVbEx0hxhJwwPsx+kk8IeMM8gKHDezoCM8LAimiHFrf9Wr+8AH07AF/JQ9b7n68AIadBC5QBQ7vhqkFB7doDuGi1SVJq9EAxCsEZTSqNIqnzQDBNzbOPH4V45TpOW0h6QQo/GuIksPKcqoM2EtBoCZE8BQOEhXLyAAx/nGuZQKSOixdk0rxL2nLw+j85TEDNYNHkY63ZYXwR96VA94Chomv+MukBmsKK+jkGnDiDlL2Q6vHh/Xj6UNdCDl9m1Sb+OXWn6sK803Sc/R6GaS3wBFNFBhCsd60XlecSa5N64RKJX0OSBOa4UbqWv5jrGcU3Or+jOdapyRKCgfP5QfdYEBXT3uQwETnl3eu2SNr9dgv8CoaQqvPXiTDlUWjifoOPjZUUJA369RveEnCj/qfN2bRW+Va60lZcu+3DBIyX1/wPtfA9FXAHnRajO8XsyTj4q2ksVRyW5FZNSXX0J12ZXp7vEBn/M01xywe/u7/H09GiKNUxYANVo6LUyweNbzwYeKMYyeUQjbVCcPRcoWPhz6wDzAqgZ/qUxpigo0hEtFng8I1eGkb/D8d47ztvu6WZGJ9VlXRZpyKIdWa51uFI8drybqVEeD9vbMnKghyNI793TKAw8UWnBW+e8npUr8Zp8dr7N8eyXmqbjUuRnfK8yKUVNGjE/OyjveRxRz0kJ5294wP+ZyumVqaDpm9YtAmAo1mMvCAD9/DUNh45V9y7gdgK4Q7dSe6blGzAy5W0BC/ycEJGdJblijk6u2HfLqt77gBGJP+3fbd9xWi/lQimLcVhAmTcciT+o4HV1RX1SukyJj2vKHYI56J33jtMyaKgZrY3Dx2yGjWPOL53NbhVWcyYj2BrdKfAEN3CAKQi3aU4KXCUbZ/vtI/D73ydYApohfDweHukBNzuCzrXnNwALLJWqKeH9TQ3xreKXA8lc5+ZBgefr6Kg8S8OQ7wfKd2DTHyoVLgE2V9vese599Fpn0vCnGqNRjyo8xVpPY+p939G33SPjLUN2IsYrMBSaeju285ayYZroAzueBeK+ReD+T1z+tRXoFYHrYDa/VdK6GQPJN7ZjvIcHKYbF/51v5QevftUILQd0Z/IWJxQyTN2Vzlbhd3R+bZwWSwzC2e9bznLFed+xOjCJesm9ZuxCMJnWH94dUIWHWIywR7I+PyT7ZvOgrrxNT3ybHyH3jCFg+/IEoodhNZPcGOGO3puAyi+fP28eblxB723E7/7PX/D4X08wyzEqQnZrkd9ZzkB2is4E8qbSu3/3kAd2ce8SUbVcscvw1lc6g9oJJAriM6A2r4o7gBoIu63icCQqn0UI5NCcNPqiuWfsiyZjwdzQVg+7SRbSlj80I5ZPCll8TRYCP5qAVO7Ngrt/FuguwDtXnj2GRbum50QNnTzUm5rsR2XSWYenX9hUyhdC+9jQHwWk773f4gI+8z5vRGB+ANE2hEMAIjQ80wOggOjTANoaVndIKK7OuYdjxGQMoMnGGzGvHgg/FY5XLKqC8cj7I5xJ7NEo9XtEinYHFRsNMTRCViGs4g5MtQN8++swp7Bu3j8EqDTzrIo6xTx0tLUMET7OhhnaLGoWclBTnncnniIbXG63K0iEXMhkobYGM09ugUlMmQeI3Fs4mCZuhC2F9Mh3g3CJs95oxYlWdAV2egL0ZJEUQOi+/kDkaR/zvGjDC/aJ2RzMlZ8bLUTxd+DH10KqTc9duaaq6Vm4bRZyZmluwS2Whz7nNvK9Zo7auOd1udDwpshCUd5zq2qHU7sfDALl/gnFhgkjUXCXfWnLAqiHI1YFPCdY5JPN/UqlR75vKA0WZ1IAACAASURBVL5O+MWJ+njeI5aEMn1gE/bfmsx/7VdY+Eau4XpWx/qGYdCAYVHCDok5FOc27+nF4/PXfJxBhIdHtkyCx4HPOC3fnTHrHaDibf8Goiy92wvDN0VciIl9Y3lNvHXrzhDfUyTUQPN+df9d642dEGtUieyr9b/x7F07czaXq/fPcC977rBqeR2IIGTowbwOkBi0heXpfW1GK+MQv2OfzwYfy8QErQ8N/UmQIuA4zzmY6/OhDolHFi463L92BZ5TGa5PHrTDt/eATr8GI0FzXeWlJFXKKxetXGNEyrXLcVx5v3brO4B2NQCb5I9VAXVtf03tHObjZvPjvMR/lkaI0NFzjzCz40j26MyGAIeXOSdMZremnpRyXszyn5zsCyMrP4UkIDKBZcC/UCi3qpj3fjQ2eiHoJVWD+ZEPdFkXCyVfYHQoOAjGW7AowA3cfPTe2Qj9HqHV1MM5K5ly3wQXJmwKgQ+ifp7HreWHikJZ0DuMvguPewwjg1SAuLJNFs/F5/uZWjMvoWXBuqwpNK5eZE7UAfCoJa1hXZbB5wAQcc9u2lMQ57rDEVquufc6E5ZGIGronZAZNp1uTVYGLnxzYwtaCHDvK8DwinYTEHT3aDPamwOluleJe/krZfoeVXXhrdGgpApuirbGmTQlpkH5wEU++R7iWUlBB0XGpbcici0DX24vZxARutMcqoptO6PvAqyLeYWLYDufhyASQ9ENo5iNVwytXOJbSTpYRNBV8PyymaGER/6Jswo2BX7iK98z5lm052ZTBD0Ab6PnXvUT6GOvm3Q0c7wYeZA1iF9QObvIsQ4kZS8pM0LKN2PdWn2hxzQbm+r3BUGtQksl1/D1iAhQsLvTtPa+e+CKeTWpmPixhzKr8DFxHoM2S9rwMG9UWrOmBdqjyzrRVxGetVYStJOW/PLJS09teUsBeihoQr/HBDQCo01GnKAaSWjUO7yTfaYOuZhjfNP6AiBPBWFj03HD50t1nEKD8Sb0Fg9VKcSgoYG1HhGAxiA3Vg4j/CMdk3Q6wYTnErgRkM3pp2Bcx/KN7ytBzq5IXRwGt3Ig1CIyRdSBaQ2Cdg/hpa/rtF8Oa5b7ZQfQ4MrzqlhGGmuEF3+eq1HDqK/w+x6sz/ALkTuwO60b18dip5GYBD6MfhdQQ2V3Msd+CWULxn4hj9Qhlj+6AB0kjEt6KGDIgYZJXmiGxVeOdZ2B8n0QdkNBMgYTMoVrYK56Ol+0EEoccroCvjaTXHKOGhL7ANM507H/ch4ulfqxp6sH/+WYdayrn7HjBh3XYn39LR2RqgLXWzcNx0I6aDWaqm9nLI19D1qEGurhAS65vswLQDsU5vQA98K03K3Wq6fHJzy8e/B9o5NhR9B1u3t1h5c6ETlNQI5DrcmuCuru6coMUMeymiHy/vzixphO24GwbLuliBEFms+75zuP3cYup1Y/6wJTAu69e5QhdUNFTeW5ffezQwN/5anOZ0IR72cP41zXPZknNGnUIUceG3fAfYaHZ1ZF06HEIliO4jG/QBPKkNTwHfCax2iEqw6FBmMozkN5HiAA5Xf8VS90KnX8bLlGrvwR5Y+qf2DCAj6vPFPnTkBgX89O5un74IAm5EvtwzvIl0es7x9AX59y/bvvr+3TZ9wxY18WvHv3YHR44mxvy5Fvoq4yCcu6Gl0Pi0RBtFgaB1eYB8p7fnkxg2VirOtidI6MSIh3p5PhisKbEPzMq5YIlsP1e4bZ5khjdL7RB0zsRqWA8aQ5mMCAgBI44EvwrB4tjAnguxPkvPkZJWizqFAQYB/UHgg3IoX6QmxEeCbjiT4EYiealNys45xsALh/AuEXdP2ERr+iNetzp7EX7qxb9un3op75rA1ZFmMYWpz+8gv490/4byjeoXiiT0IQC2kvIDRVfLkCHyTaJUyGcxvNhoTRl7fL+2a8f7PUA1Teyqku98v05xxFnGNRxdPzCxoTzrugheGpr3Qaf8CxsgxjSIKlyDzSKsfRAI4rRM0IGoB2Qd93yG4GJosE/49s32j5IXtNHi91bUV7pRWXAHC9zD9beYsOAvgXVqDbZtOLi7fWgsrBK6yYX3HGSSxcnkLQQeg6h3SvwOgFinvx0DEAhC0HRdiIXBMkzl0dZIgBqUHaVgJeVbGpJoHKdCCqc1g01Xp9EuCn1xWFHsYngFAAM6HRXgJRGNHIxNi/dCeon6B4wPrLAlJCQwMpmXf1V7hCqaFvG5ZflqxPHaUEuF0C+MfBghG8SzMvl+GVSeCtgdHSw8hozrMhMt3BtAJBwKqFoRDpF4jXWqZybXzXukE0pq6soSueT3crHu7vcXe6w0LN8lQwYe8d5/4MXXoiPQKw/LKgb4bkgqCNZUkF1DuGfN6BDybU08+O0KDZMXLQOi0tDSKndn//3AsGjDUkED6gEaOxKfbBvQDgQSwDz3alEuFOdZuFkqDHfjowRfGchfI0e9O0QIxUA6VUoBXOvQpk3ihDPDQE0743VMu1spacwiMA4GTCGWNP5eRFX6Wjd2BHT+aBXeAnZOo1yz9lKQLCW6wxWw5CuMeGCM7bhvP5jH3fodrduhCJXKJ9ScHZgUkOiy4KS8nBiIaQkl0IrR72fVnYKCyy3JoNJwhtNpc0jBCMWFnNekwFi95ZuEb3VCKfZxwFU6rYdcu9kPnF3bsqhNjbtplVJ1DC2Hy7xDmfFMGxRPW5A6RP5J39Nm/Dxs1TLiD3hH3OiLvuhYnMuAK7o1fqt1UJVX6QgsG8D5xfXnC6uwNw3PXAPBTzipc9kNkguSZ5UQqs6hhGZewbfwhnkL+HOQrD3OvIiHA1j0RrUUalQdyVNhPGlPkJQ586pHFGh5FVpHwIBQO81iLnmdcGA9olWNZ5bKGoqu9cpRHqfJX5u/nYG+npG9vk1bYr+WXk7gbFCkDmSACFyZjZVadGrnX+5r59jRaZn6l4pL3jAY/UiXNfy+wadAiFo24V6HP0/vW1iE+Xx4xqD2M0EfIZjdZybgG+J/RnBaEVTPPzpW7JnH0qMBJIuDx+T/8codXNti7gHI+ZqULPq1NZt8b3335bIQVoUnHMjFO9Ph64XR2+ccRofnB4WI+2UwmhYuFlnX6OXN2qiqYtmbz6mbnPPYx7lOHF6bCdhpcAgAz7zo2h6iGto5MpdPccl0XgbTSD5Sk3JfGaZygMtrqHKA8vd3LFkgmRTDG8tMWUlWUsFi7e8pN1NcFR793CDjqyivCcIMpw7yP/+fBENamsmCIeMBqmi8+pnUFmM6rq3fKlRR40U0Yvk1DdDGAb+rLY+W3GjB8FDCImlFoaY2lLGpaJKFpz+McAt8VDk3Y3Tmg2J47kUiekZuwcgnsz4Oy+LwxXE5vgd/GQ5dLPnjvUBAfY7ZlTM8H10hjUxI3dgm90j7B9s3z33VX2jpekC1Q6RDv23QTo55cziAkteCxXnmX0LGp42jfjQcU4SwsRH0Z1QBikBf/a9w7hEHLM+NoUTpr7pUcodZGI8Gd0OjnOUYv2kEYpixkzSB8iOdl3mzMX2CwdlitezbhT4Xm1XQIWNFkYKGR+bacxMjW8eJQD9nG6wHLi2Xxs2i9hfYoPg48mU/8eBSOkgU+cLpKBpSrNg1AelP1ahULZbiEocgUSnynqx9xh9dzrXn3yLsHTJClmezrC+mus7QhlGm2Ewj3IhtwDqgATenjuR6j8iCYwqhhdTpx/Za6d9+MCW6dKHKmbQk8LniQ3ojHDzUZmgDGFTXaZw1gP7wJhpKWjMH4yAxa7F5OmSEOKUAZ5qMpcSofPBht7eosTUxrwEAmABo5ID4Abydg8N2LQOqKKZN55Nf5qKKJyWA533GCWTYgdoNfOg4IWyimXs58FVYSdp/gicRgaEdBWkzNEuPtM3+CzSD4fYVRUveTGefHPzfZFep7Xdc985oWy0zHK2DPjnIx24nlRS+sQi2ZOHTPtPn2/ODuVQPA6MM5BcBhphKQx/4X/P5Siui99qKv3rW+3y0WLTiNS/lv6FsclaM1aw6HvecygCO2HKdHnSGBxvBsZ7ggAdTEfCT4Dz2jCHgV5iq04aHa2q7KnzgYXGlaVMhhDNqWDZhuQ0gwUg46KkTNF5H3zvm7r6ngWee5z36sZn+0e7jyMtpd1gaqFSqbe0SEWdeewuWQ33EdhjJhzHPPsuFNMDpRKNmYos3lxk8GVDsO1xA0sjsebG7cJMtoK7TtevA1R6/vpdDLHI6dVAZvrfRe8nM8G85wO62L0xd47MpOHz6u6d4vEXoj1rHK3GFfgZGK0uF7fO9RxLFU+wUQWyWR6ziGPzs4zRITVASA7wI+3FsdXW+6RuTbc+K1X7l8rg2LyvgC489Qc25tq+POU1/jIFUPhWZzHfR+5/LX8LURp5BA8xA7gBe5U+PiM5W4t/C9NPNWyrhmBNjpn20+wbTu2XcAt6LcBa1Ke3RULA8/PLzjdnUARQdR5NXYcEsbUBi8jshWcLkXxLg88bTC8eZ+aR0FlsmSZHBlxsngESI3+27lmYlADLJDp8MC/Xxc8n3dPvWAwr5e0EiWI7uUaadwfT2woRiMUkfaGMj4m9/w3QPDJrv32CY1/9fRCw2muKskBcyYjAAsI63/8BZ/++/dMC0Gw/RK2g2bE8wlQ4B2ARzLn1YAUjdhhvEGH8JR/r4qnSstggKYrgT9nugWv0wTlqdt3vhdE1Kq0roXPYpW3ErD1jov2Y88RZaSuQYsVXknLc9fkNKmLMIX5MIYdqUPEDbSYGZ3ZU2+Egycu6mVuKf8FkLKH5Bc8KrOIQG/u1H/u8i+rQL8oN+Z/VnzClERh8+8HJggVOJMFJ8Ia0WD01wYltzoUxYO4J7ALEzeFe23Hxr/eIXYJQYTzWfIQm9L+zgGFbBsIwClyLRN53mHC2paS+zwU0+4Rb8PEqsHcxNgpmSuIpiUW9t3uiQJ0B+XNDqXe+afm68uHlgDp7tcTXj65IlQNicGJankUtPcPAMyj3zuIEOAFoa8vwPJAI2/0s6LdwQSJzNi/dtB7grJAn2HM5P3ZhSENom4Z7vmp7RBvRiiyCxniwDoZxTW0MoJRnfcRKaDpyVyEtcGIg0yo6Z4yS1vc4wjJdOzigOarXyMATwQ+maCS3zN4M+IMpOB3JggQAuijM9VCg1gohGYIfHIMhbWKO4MNCY7V19IrWT7eYV0WyOcd1Xq/4T1YCaAnxMMKpJJ8KMXtt7EYTnTbtEPMtNyEEhjPJuORtbqu158J4UFdF3FhR0/+18OCeNBxTuZv1BWrJQCWzB0Nz8Fj4WFCyTrRLxSMzGAcY/MnA4bYr+NcMLcURINg0RRUIPueIbBEFBOaoFgZIzW4zHXsL2LG3f29tX2294XMvtAEOyMEkIqCCdifI6djA7Sj6wvu33/Ay+PmxIah2AUrBILOgiZBSgmUDZZw3UM09thQKxgpl55+rZkHXPOz67mIXqW0bxQDn57v+eL9b1WoGY6JMHs6p2dUMNtXiSWNm/ZLizdtJcKcaBgeTV5k7It4hohwur/Lh1RcSH4EPok3CLy0Eu40CP8gS2emFxgRAFIw6QT40WOgvkdG9XsfFKi5glN/zuk9PtcbO7W8nvdDwDDGNIQ4Ja8phldDdCsEgSp9CD2JPEJMGe9h7dZlQaOCb45lAM8CLafLZTDlxjcKlc/v2+qWozlEZx1nr2eDYE0YJ+ge0WVYMg+B/1LGcaQ3CEYtLKg2yAPvjf19OZ7i8ef/WijBlmHSiKxvmfIEieKzXlVN5XlwF3LdHnrCya8Xmr4tDy0FXHHmA25Uwcnb1+baPF77aeflqDx+mwJ9VgTlM7mZJkQGQj3b8DOBmWGjcfZ+voyVOPYUcfVgWDWNuzwX4TZeY0zns0MXV6Zbpb3jnKuYt2akUqk5I1MI7Xnl0mvIac1j/7X0dwgSvC01es6U57OQGv4scqlcmeL9XdbFDC3FcbcrOyOvmYH5ymha6HFT1pt3b+PFc6WvGYkmolKFId/kCaHlfIVwkgBymsUMVe1MK7wvoma9vxsZqmKeWqkgIliOzGZK7H0744XGfC2LTv0hYrSlYdXFaGdpA2BonFXNNWzsCvTW0KWj72aMum9G+5zWEW401rZ5lCrmiod6ToAaQWnnx2nYLgoIg1mhsoN4tRzkIha6bt+B3YRn2w40NuagwSOmMKfhdaSOCW8Ahjpf0syggbXQI8DD3QoRBsTgqpzDy2Y+QnHeDUd51JwqXPFHBcZ/hmIxq/B+hut9GroRYtbn52F42DH05TnEwPnxI6IjhI40aGk/TFAMwVcYz5LWVEXI/Q94wBwKr53i/RiIOtwRJyjvtAvgqUUGv0NZhxsNorSJ8g6NenLuQuhUYGxVCo565kJljhKuHB/KCwbQQ/E74d/jWhMyB7y4UiRqsaxFozchvwgai8KLUYdyPWlYchPn0ket/4SCy72mko5LPGfYl4kn+DkZflVIX/GjmGKI2Q2AY2pUATKxe30+tc0UCnQYnTwT1DanYY1N811oKM3ifuDUOL8EIUqDlZaG/gRAAA8ba/Pq+dGrUDYY2rp2GLQxledoZbAqFJ5qQe18mCLVn1/JBE1eiyiALfZZRBtzY6P7xeQQT5vB1MXGZAZmN/bsNu4hZpLi21HEWfh7AMFJ55MB01P2ErUWJFGAiCL2vjWqjv+GSsJgdv1ta8Tj90RFOuRy/iFgR6QfsrM+FCrjYCtCgXgRTaL01+DMK2JfHc8hZ7u8DzisSYDj1wuRo+N9DuWExu94ZcAPHbM7tQXfTxWO5FhxySPaPS4AmYa80Gk/bjSBX3Xe9NJL/TAWAojq3E6V5J4bDCjiONq4Xd5gddY1R/Ky7bRCXs5+b4QdT7KayWSHSpaztc6Jl7vTab4eZ5ldUiNi8KDwr2koQDAe32kXUCi2gLN2NAZEFzQxZ4OQRxOFc0bHvu8ZiUekQ8X4HDMAFOzhbd7NOUX27jKqju7pbbrLqgN0x2xVJbjAlYDFODTPvSKFaixI+V8sXZwv+15mMN6dcMCgJRqGp+mY3mHcdvYF/0iEz/5UhA/fiyasnqxIeSqHz/hed8rx76iWqv1iRDQl+ikl+nz6//XKSef5i5KK73LdKO75VJHvOZIAty6TYwb/8gH75y/z3Dgd1yRi/ZrMSWG09mldAfIQ7TDDTKg7O3m0RCuK9WS7zXibjmEYCtzfrRNuZia0ZcF2Ngek7grDcOwxkoOL8Yj/EYNUPFKj01QU0M1gJuX7Q4bCXA5TyPhLFAc7+2boTG2DbABgUdW4NTTuQIdHKCY3yDW9woQeHDavGE4rBECYwKTQbpEC7hR4BwKxre0i5hj6UvAWwULELwDkrwD/h3q0iAFxz75R7sq+ifvn//or7mCe71nKcwyg/xW4+8/fcP6v/8FHBST2A4DTb7/i5fe/x64AAfhEGNFECnp4IuBBrX9ARKowb/VrZ/HbMpSKt65cvvXWtdcUyW9EVLRj++KyeAaDGXjZ3XKSA3eXSgmZ/mlqSwfuG/TXMBM0+tXXRwSdOlqPPX/Z76SNIhpdymH8UfLIf1Tpn3/u8laP82P5/44C/QdKIuBbZ8EnNUIu1ynuMCBx/wNt1noGITMXPjwj3ubaWiGyNf+d9H1v6UQZvAJodJ8Xs3ZV9C8dRHfg9w1h1SlQ7J92CGQomD3sDwDwexuBqqJ/7VA6l7ZdmUl3ICLsTwLBGYyTtfkE0HvrQXvPkGcXirJamHbcz0xGDmnMiZ3tkVtIwxPpLeTLNWq6FE5g4cCrCLuTsBRjZUQ1hZ+BGKIJBiFzMrsAlMgIjeS7Lw61dY7L93rnewanXxTyq8xbwT+HggaF8g5FeQWgXpdeMm6JMH8AMB37AyAFNqkg9PvXAHSdmeqZrqpYvNawhJx6faWvNTx7Dc0Z+8sE2ybMbW3kYlXpqfzX8pe/E/kB1zec99sFn9Q6WAjERgym11EI2cl3mHa39B0Ez8uXLyC6A0BYHxbszx18T8CzGfPQA6E/mqIOJB5Fg7JnNHfLcq36VSYTWhM3E/C3EbrW5vRYwbdLCIJ+pgQBazApQuFjUHH21PTOpAQpAtRx8eKV8ayG4YXMCMXvEWjkS/Qxpu76aiHPl9rLgSAfk1fkczuJW5OWmic9iaGpQavgCBkj5CtwVFSPp1THHI3uObug9TnNe1UBGAT9EfnWcxWTpUHhzU9m25pDP4z5ONzS1+vlG8D/JwthhWK7At90+n0NHutgI2/WXuuyspTPWYl+7eljbYxh9R2emkg4hnK47VBVYn5Snr/Szs+WxFGHvl/HnG+r79YM37z3Bvh2u16aPt5a+bWr3wK1b6cR4vOI17+n6Pj8DhxweTZi5eqdG5Ud6XjHjWn8xjSUEkCmOZrrOIS0xYAvdcsf91MV7IeSCuVaKGCYGMIdLOxW3aZ0hYfbTBCZymqk544ppBuW1Q03F0vfQnyZzz3pPJ1pMaOFGLSMd2p6DunieeLVcdSe46kh8MLrSbox3C/nLds4QQG9A8FD17tnKXtutNYFawiNmYayTV0BTCYsa2wK/n3fsZMJDpbmHuxEF55UtjMM17b4pXDhnQVRZCZotxgVHQA0vEbFhYHm3WX5Q80aX3ejID7v5jX2y/t7KDzsv6e8IYYr6nIbgRkZESB2gzzvlobKFYWq/qACRJaTfdvNe6x7SEZJeq/S3YEfjc9gC5yJbTuDQDjdX+7tI33bty33bjmtM44hHig60oUNq2z0XRGeo8nLupJR3OhCYm9lfnVNAXtzI5QQTMYm0yCSIjR4TbHlFE8q1Ce6raayyhdyZNO1WJdjHUAQOAeQUvsxzti3QNvETx2qm/tIcIZx1HnsF11pj8bZHHDoSvlxYH6jBOXpRDXNsDkFaLXjRL6nOGGXulH7rQm6xoNMT91S2l2tM1+a7hmsGmfR8gt7CiWJT/EwEd3hH2UESrqw2yzzApR5Ojw1b2sUt+OBg5xnYAJ0IehWaN8LnvVAC61kSovgOyzJ6GXZxnuDPdKc68ueu2HLoWUta/amUqblB1jFN5a5ZuPFwsgy+PDRiWlMOi7m2Mayzi98p7D4Fk36bYrve2fqO6jvI9g89iHmzWFznYaroPbqAz/Yt4QnQYxh0BAA1rsT+ranUpuYQY3RVLGTJP8CHNfQq+eixD2fcVoXtHVNJyFmzjWz+kOuFEMZpmjD8KGGmDZ55K4AcR9Qn+J8syvFLTpP764Mbwymln0Mw75t2+y705DSTYG+h+OGjBDvFb/fBInHv7JcmSddX1+x6d0rD0ZodeDbO/jz4Tfd+H5Nlhd9iWdvbesIG300677kQ/685fTKveMSEy51GcfrEySTRyi9zzWKtZz1H2aA0jgTIhVo4r9UD/zcAd7Hk07rW451p0HKKLgxuC3Yt/2CJgnngeA/7KLRduL3mCjTSMzpfAMI0EjVFqSRlj16PDdi0b/Wu8U4FrdQJSF35We0RdHc468xgYQHjV7ogxPRMGTwa+fiNR7zWV27XFKNEwh7oao7mepi8TldQGk8KDcOTZgeEqzrdzqU6LUP8b33/dA3613/3bzfj5T+a+XC4eCnyrcx9FurqeNLvBJ0MoCRt8R+cjgkwPdR8F1vbvwGHlY/G1BALcVAJjVM/RTln2qEe7coK3BcaLnRZYo+d02vEnW8wq38S5Q/lwLdN0hli00hfIXwF8Xme/eFAPSOe5gv0BnqeZTNo/VYCJiEQgDQ2FR3CVTTI4uwgEDUMo+LMVNOnHFLy+Y7mKWRwkKGAcDWt9oMVn8+lf8xVAfw0jcHYH6jNRM2dUJ7z+iPJxuh2hxkDgYPPy1PiuW9Kd7k8QyWe/TPHcuvDbvsKRzpXzqEXiw3WDIWZuFOIAjOAMyr3qIAuJKdV5wfn7C+fzfmIPNzrxPHSRTW5yFMqcD0DioWvj1yAQWQABWCMl8onGKJfVI9QtTDuIVgkNHQ7hvaiaEv9lB/7NDeQe8XaBfQQwMtDbQreG3gs4fIJgIrZehtVYF8VuA9GTAiAX0FwuAgvNDwgYEv6TMxwpHXNfVxUGBmuMAp95eRM/J5eOQ3fACB0X61cJj7359AiVz93MT8pRJ4/IYagpLMy2R9685wcSjXQhCYJFL1kNCxDD7nlMIViwgRJb2MaCDdmcCOUSKtz4gOxJ16fjvYeFiHNWoyQOFBBRjx4eE/u/QUvKUHh4rnt7HvuxuVqKcTQIaxD0aOEmnmuNyCkciIudYahATraoLj84vl9m7LYszYvkOVjOATYMeO9GQBgenezpoNwKI8+E6pRFseK/cuEV9re2bkq4KfNXZGtrEpzU9kAuVOpbIxzd8sVeEeJN5VxBt13rwwly4Wpg1E4AgrofCc2eSe21qMEYYnYMAYQDPs3FFQN/JT5kBKCHcdDGeZz6hHJ8pnDj0YNfLSXLHRXeB+hQV2givh4GTAMFjHwCvBcETbGYabjpNJBf7ZvXW1kMP73odwKd7S8Iy4XLvMq5qh7ux0xtke14rHPwjNBQfxXCXzpRor6MzwX5Q30Wixx28/f6uJ71ds23j5niEvAnJldeBHe0OTnaH8rqXmwzkDsL47QZ4sZGDNnUtpox97bL86HirPR9vh4UooShzHCaBgdut+U+iLTAKpo7EIHb7rxXWaftf77PnP1feT4WKjA873Z8hLjLvn/ri9/DHiwAwjQs3hsezJwKF6AeuwK7Dc2At08cV+HZEXKsaOZ2h+QSUp2TzzWdk8snwFA7dd1JdFLy99d6ksYTR60cSbyjjt9Xepmmjap0Hv2CMGf1N5LoTWlqHYKXXGa2nsduxspR3V23W4NXmrO02BhGFIOE9EHvrd3t+zBU2aPTyUmS1EYKRMIADLuljo98UU6C2N1VxQXOAuu0Fmaw27dKOzPeT6qmp5ycPojchpZAshKt6PzHcuBn8ijVPS2iLo3Wgc6R6evPfUu5hx4cg3G4Y3xGQ0SFH6By0pfYS8j8hSoeAnECiDbjgs/OydDgAAIABJREFUIqQRgtH44kIiUz4r4OFmy8kNmlrhjnY2HgGgffec3Q1dXpxss3yp6JYAvXODJUNnYD+DiC28viPA3j1/N8iFfgRKvxzFvgukK7ZdLOR634HdacWusdkQnKnNNaa1hXpKAfdmCeOLCMt7fn4GVa9dhuV+BSDPL2MtMAsEqzIphHzHw2d4YBycnE8ZynMgvmsag+Q6RToopwmqUWymbpKILhC90dn4hXwBi7JEMQz/rOuU5zZJmMhT7WMgQmGSpxPvxGihexWZ9kyk53kHDjRPpX00MeVc0qPT4OQUtdz5JIvuUg1y4pWhlMk4UT4vGcrUX8h0FzGvGnRF6XvUUuZu9AWXypAjbqh0bOwJKMxo9Yjr5s1k8NuINyK1cPxElsSGAGWYlzi70Q78LPvGmGDsNbqt7N9K418UsrlKejTwb2dwE6CzRecSS91gynQT94vzdRrj8b2p2QHHv1qmLvYnWQjn4CNS9FBgrCbN7u+tY0AUY9/mIfenPWkxEnVYqBa7tRJTh6nQ/NTDfTOrnjFj5SEc1mq5W+b54jrF8wa7QkgcnrqFwvL5o1KPjrObT9p1w72ckfLqnIAo0/NFdIxcF6KERwDcCUIdLwwaQIr8YxBU2UJp8OohufL7OqEVdzPFbp7V8Tv225vKlceq4dRF/8Q8k5V5Ggpnui9/JxYpl4CmfTOfgrG7Kl014E7A21rHfLApN7w9Q63sv4juomoR/GCRdnhdgcZ4fnlBmMlln5yeUXdmMe9SyfHUiDHRe3aajwEsq2LbjJIbIYldua7I6Afq+KaLGyfCUtKsS4tBmcK8754r3ei60+nO5Drb5pFbgPPZUuZs247z2WWcnrtZRTwPenfFuvU7PqfzPa1MXZsy9b6kB2J2wnF6ePvantrLnNPFc1ZGPLXSM62nG2ClnOeqOI/64tmqrKv1RZjq2odWvtfQ0/Vd1sOFHyx1LP9KpR7zOq+Rl/5BMe0Bx9R5fUWEZLe4ecu64lEE69cG/ag4vX+H7esTdoTMNvag4/ttww4Cn5rJJl2mfz6b3iDSV6X+YTdtingeg8jpTEH7AiCRTNsU+GTfduh5R4jZhuFq7c/YCLEHFcDd3Qnnl5fk77ramQ4ZWhwjA1/qRndD/hDyGoFaFFh1I7WuOH96tFllBS2Gh5o2nLiZge1KCXtlV7AbAGwcBsbDWzjmllRxUsJGmka+IaOMgPidbHzLb7+gySc8/zW1AVB/rv3PZziHhCXXeTh9EtzzmyyUe5zZBvu9kYV2777JYn9tv3/K+f07xR7TDPcedCz5/vt6Y+9GaH11gvGSpriJBa+Unz3BAWmMh6v2uJynJjcJunQIEZbFeDf2fHIpHQoUPBNfN3tbHaOO5F/scXGEocyeatZoAEtVW+Qa0Ez/RRqpjkJWqCWC6ng+ePvoh2T6qB+czp8sP+p5HuXPpUB34gqoRPfra3e8t10wHVe4kKvliIFpql+9fxeHQM2yilWx4wrBTEBE4Xn7VqiCCDuK7X2busfvCf1LEJJ26PfHUGIS9kdJoBQHgsjemwWQl3OghMzlHoy/OiOtaiHk5VGAjw3tHUHPIwxz/YspCyt3s8ohBwJqYRMlhHvFeOGwFMeV0aNJIwWBaU/xA4G7Wc+HUpdAFq/kqyPbLugkIOUkAkKwikag7opIWLgV+ez1N98DAtB7Fw5/LeSuh+5LIs8B0rwrTBgxFDHXC5UvVkcAb3tL9Q6glyTMI5RiWCpNntXTvSAJBrMSa6UYRMnUh8P1i34WwctR+B3F0dJcctnmevM51YwwATJjlsx25YLsnN8cL3I+qpBNmMHkoxYLoRX5dIb3ECYhTgqPx+hSoTIQl4dF39x7yUPJq4ez6i601hAAJONDENrAdIIJ6RntniwdQiM7W3BhBMhyhRKgejALKtKKQJARKikU6M3XxULtxDlT5Hb6zvI9iG1WJM4nQTVCuoenGGWfhkWiQzKfPwGSMEGBM6XW+ULAHh1euBamLggiIIRyt5BNKCVyBHWPZ52jeQDFOHGGi4qBSka9mtftrPoEqO2zCuFmXHRBZmF4OFLeN8UREKHGx3N1LW2vcSgViJ3B8Hma5sYNOULQ5TELtQi+eMrydFuF/ZZCfIkX3vzuzXcqnFrcBzJCt/vdZ6BRg07jGGcoyFwq129hV4IZuI2wuFfojby0+O99OmuhOGcy5b4+K9b3awri1feFRDjg0kJ6sT7/jOfyt4tgB6EhwoibqklT/sZ3DDmHDW0J13ujU9+17N948Ae30Kj6SiePym4GoNesRW4M8O0y1utw9ALf3hyk3vh+0dAP858h1E7PRv8bxoODWQ6vVyFyWwrH5US5d+KYqHOzM00DVK1H0Lk5DC51IGhgGnRM0GZErgxcwY0T/zSvX9mM7jiMXNlg20Ie7t3h+Ol0wrKuaMxoy/DgDLwW3pIKNSvwtoABC5tOliM9BMaNG9q6ZISdfduxez7r3jtUOqCSnsDqqW1C6R17QHZF9wTX275jXV2BzubJsSwrhIZiM1LkgJEW7tPWoDLZXsyro01h4SIHoZJip459U0A7euTUxqA9iAbtT2S4hAuNP2g7kzJLDVWv3QUdCqUOEcKXT5/w4ddfoCqgLiBWaGPI+ZzzNMKEFyNUFffGNiNTA6BBSwSt7BETgr72/Z4YNGBvnIXYoy6yMnKUnL8KukfNKyXCRfrE8LqYZN3DUEefgyckDnoi6IRhtJBzSRTyfyg0U/cMRZd4E914Ik+vEAYBRusSIqxuKO4kiZVKE5U9ctgnGuGICx6tc0QpkBxwLtt+rSR/lxcGfVuA2GvK8/q7VFMGNFNTwShNU3Ac70GQO4HUMqT6XH3mCMLHvbdjMJoaRWyIqbZoOVJNgCK8I+XAiUOJHn0eq1fnKfjHZEcIyLjfr3Y5NujFAnjxSGJsZkIQhbKClaEsgDLAkeuYS5oGM+zhpgYrpzDIdqanNfKupjEQAQCDSCEUIufjHBNYnSepZHfQ9oi9F/OdEpmyU72scPcw/cZ86eFbn27pNH3X6dGEt1euzzTEgNO15TRIiOsabWs8MPoR+wbGf5oZ6ty2CXkHhDjuch0NpMdx7U/gg+xPvvmPpXS/Wdt30E7fekwvZuENdfo05bE8NnLFze96C9doxQN0ynDdhieJCLyQG7VJykJGOwReGSzkKb3C6IMsCg4R4GmxJtjlgGXInwr8cpgV/P0Bok9nPgfr4Ejd2ICifh+KKR6APaLjeVxrBSxfMweAYyyrOxYRgz0tz75teDnv2F2Jvvcd4op3C2YUynMZ/DOGgv+4QldlLfXZ6PMVua5CJ6iV90PWWq4f98HF1sFQnFK5FvHTLtsez1xr41qbQWkFfKh1XMKgGeT+GcsJ85GudMrbwBAhXCDuEIpUo8De//tfsO2fATyB+T3WD+8hX79CgXTcU+gFSAmeykAEuezJFZKRtssV59TYZZre/7IvGZa6t4uiMXmUvWEwVI8FOd5WUOoukl6DKQKfn55NbkIMkEX0zAD0caRhcMqz0qQDYfDzgqBPL+nGwIkhV2VSgD0aKBXqVwXqyedXCs9xM9heYuw+Zx0hK7JGzgzcO43wQk4yaPTzIwiu1FZAySiDrZATd//xb5D//hv2w4EJGXuVz/NvH8G/f8KiwAqySCExn1Ccy/MPBR6Rz1EvFGvMqxLhwfH0o6/75fn9DiR6Ua5Brdt1XdILt0vwI9Zfp+2cP4/NY/Snyxk0nrwlEfzOouoBkQVdCBRh4j0NGbeWzoRBD/Uu0EYgx8PsusoGNWdfGbqi0FXF+ZdwbKWfk93+3yx/KgV6bnXPpdGvEBSNCSLAMxR3ahZWJwWoMToxmudw7U5ZDKLC/l2aWV33tKywzS868q6P3pDljHYgxkX5SM1yrjMZgOSTeZBtfUdTRVcLAdRlWOEAgPbNABy7eKooL6AKWlbPp+DCPzVLcWaGfDWwRQrI15GXB4DLdxSnX+8tt7c+Y8U7tF8ITJ4bTF3pDgB4sUNSCEpr0JQnqj2VPRlZSQHGnR04OkOeFmhjC5NGQ6AzPK7hn27hCRO2iZ1OIMIwioU2OhKKM9EUWGo+yiE8qpOsZwZ/ZLQ7ToU93zFoZ/CDQrpif+zm3fKB3KOcwNywNEbrDb3toE6Z1nj5aEdxR7fJYEeyMX/RrS8K+sjAFwvZeIEenNgfyrhhPRvgdjIeocivazOw/3135kgBfTThc4SBUsnnwhs9AKKEUh31jA1SoFEwrtavNYRxGEoQQoS8Gso0IxhGj8ceQO6Deb1iXa2lBvXQO4Xpy3lAhp0ZwkDCidwwgs2jOkQbqkbMkZin+WxhrxaGFZ7uwRXo7Oduc48ahNcN4quNJXIIVeVkCCGB4dXUuLlCvYGUsHuIVXGPiOaxapQ87BcZqWFnxd7tJJBHE9R2dEdyZ8uh6et4gdBUE/ERwZXnnIKxCEimOqw+Q2D5Y8j9rSj128/Z0hjTbJFAgsMdYUWzNuIjCMg2UuA6DtP8iPrRdWXshaen9cbrsoM9hMhIGAuirC8qZ3dF6N1CuoeHW0bgcMtASuUGJdEfACSElGZxb+NOuZ0T4AaDbR7CyyqdpQDLDQXydgbpmoQqW8eXtoIaY9+2STAxzwlhWVfs++YKrUtiNJ8tXG0KwB38Bf5VAM29iKpgpSzhcRmm3xUzXzxPhQs73gLlel6/b/86+zX6j8D9ikbLnBIlO0nTf3pFyFpbSuFQ6dsYwjXr2xVxlRyjtHcN+qTgxlh+WTzXM5Aa6jgABvxNSeLh2uke01xEbqUtXaQuJvaV8bz2lF2R3fpiQqdhoWv/SxlvfKlaM1wBTnFhfm7AjKiPvt31S85tulBJQSpIvuLoSQCfa4ZCRx4rO675GFMKAwtDNr1Do43sGl3pRw7u+riuj/vG48fP+H7rvjqtcDEvlw3aVnVP1lCO5xjd2wj1WM/K86p8Clo+6H2+Mi+1pMEJkGHzxI3puqd36b2nASnZ5k2aFuzW2YsC0kBMOJ3usKxmOJKW4FSMAYjA68j/F/A4cPWyruZxzoy1tVSo923HGQQVSU8O4gb0nvuyq+UEbHCa3jUSKmF0pyDHF0SM1fOXR4QXXpaypzEU/0STgKtKthUKCcWnuqjWlaxMil069m3HtpsQWcVCl3LQh8wYAi/blOGZb3RvDW9qEaFsbSwcqqVZWkBkfhQWicMdlimU2wKIZwBeGKQKOe/WZ+nYOhzidyg6LIKROD9iBpYENe/WrmPvF6NLEQUvlDxWzA2AkZuWzDgN3fHJ6Q6yb6YMdFjIwYzxgAcDHytMYH+X+zdo7e352YTz+zNULfpRPeOaYdqRRggatEXwDZkj3r3itPSB65j0oIOOyghhMZjsmJ/l2H85F0k3YzrL8PMw9I3z2X1NDDVgQW6Ysk/rT734Xsi4AcYUoCoZdrrSKf+JRgq+KQS3MW9z2/FN55D0Pv8R5nhonwuvVJUdgS+mNYCj++v0WXpwTW/M8LlRGCNrrlusvRnjmkGQCR9gHucohkyJdUovdBhL3RLBBQ44km7Jx86jKbSQ/Rv8YW6ZIpEN/V7k0yaICyDJ1lbZo9ZRvmMcb8DrnN2CjseY8i6T67A1o1ulXCL29Tr2DwSgc9l9K5zGd7znl6+QwLi82icceeudIw6N9QiFudUxWog6M1UDlf2n43NElChi4qifBvyLkKGqknxqNTAer2o5/xF6F7mHE37BDZ0wOltBS9KDh7mo3b8sl+dn/D7sREI4qV3WMLbTJRw4tB8yhGv9vaw5nvF+5tpQRshIuKVOqZR8vbWa+H1s8nD7QNfFoRrncBiD0IDxPj+By7ktOL+8YD2doAo8vTyjsU3gy8uG+/t7dBG8//Aej49fDV8X+BMGilXIDzJP59W9Wk0epxhGu1bE78U1dqNGKNxgA268Nc9DRMR8eTkn/x/yNNGGfe9g2vHy/AzxqBetWeSb/bzjvL1g2zds25b0ZBiMqofWjbSVeUaJLuFgnknN9a37uGLFwE3xXQ/3Sq0jGpyOZ0JxvcPoSMYInb6WvUEYigkq97u/JzAv19GPuT4t7w+zRGCjAcnJI2RmmOLDOK7t25MSzv+wONDHFr+v/KN6caucdKzFtfZiJiPHdYU5VSod1yIYd/BNX37/GxqA9//xm0XRBKB4xId/+xW9dzx++Wp5vf08rl0Ma54BOhEen83T++HuZJ7o2xkEeNRONp2AhnyFEDEQYv+LiCl0nU/rougC7F0SrhLMcNfGYtGkesqSh74Bqil3Ik+JtZ8d15PrioJgjUKUEb00z4vpg0ICSwF/FXj4t48Q6dgeXyA6ouVEJDJse9IFkobVZiRACmzqNBg0o9Zu8DOhAHskj+5KsQWEDx04s+lT9t8/gx3vhdl44O+NgAdlnP7Pr1BVvPvPv+DTf//uT9lfh3mb1/3Tf7ckDXe+SxooDSd2n65weD0d9qJA06zPUeXwQg8YDk2xXayVOUdpzjswcOjbSqXOBjysd2up8KTC05AJTFGDaVCf6r+5jpps9pldpuH4L/Bm7cklPKvQuz4Xsibfc+o8dkSMI7YIj2z7v+I3dXkGhACPBpo4FQwS1xe5LgBU20LS5oPu+N8rP+t5HuVPpUAH8EMLxf4X4SlqubYM18jkWx1RAC9k2VGXwwYfh2BcZRRC/sAIz0O70QNVU+yG4E4Bgoc+waXiLDZafxR0jHCBy3vG/nWH2ZoMBmSUOyjFbB1nZHynYAac2RF9cVxjnjp8z9DtDkRGaoXHzNxPu59W7Gohl7ta7pSwdJk97Wp5ne2ZSyg86SDELgyHE/odAlYBi4WU4mae6y2Fh0jhUUL64piSPfJ20nr7a+1rYUlo7JjR3SBn5vHp9LaTCAHQiKB6D+DZ2wXCEycYmQxlRkPorKXe9FxSrT2cZpzIwtzUPsX1IWDDtN6XyO71NQtke+TztPxFQ5GvklvD4p5Wu7cgQDInWfdhT8W81E+FZMhKkxPU8dozXJYu2MV4QtwdmsgQ5+Bpw2rRGH0Gjdw6HMY3rShdTHmnZ4DfNeijTP0QHcrzMbVjHXIHUd27PJ2B8JwKZq7ixz+qvFp1aVtUwU5JKQ1vVTjMUNiZbUu7yIkZ829fx5pXpVoVCL99wDqve9IRlKFGLSzVOD9hIBRkbIQtrgLX20fkcC9gjgPhhIJklv3cFvR9K7uxLuaMXyLUT5QuAu37haLrCLmXZcG6rnh5fr6o87USeCOHp2V8P0EcvXXlHt6/BwA8ffXQWjfetKtBZl33zGZyb/CpnuFDMxO5t/ptIWxv8QJHxejxuqoaTnvnXroPxgi2xWCIeWWOsLw2FuuTPCfLN+U9Rz75jy/GNA3FIcitc/tli6/yR9e384xe31C+F8xdntHLt28xdmb0UjDqgQ68WuWBeZ14+Vt797WJu5gvvX79Dy92ZgYcHcYscWLSE12GcMT6+v+S9+b9jeRGmvATQCZJSeW22zOz3//rve/a3e7uKklkAoj9I04kk6rqw7PjddZPRTIPJI5A3McOVhNuvzO8UfA9eS+5w0Z6l0ccmSIfGh/cBxp1r08pBlGrlaf7qRRXrABBq6gA6+kkKcETzXChNRmjoF7ihQhtiAGk1oplXbFUq5++eFq4dgsnp+3LZ0+r7jOs47F0bWWIIZl74nNYUhJ22tCXilvbULbqQvep1skBFlQk/aoj8seA41mkAOdRGcBt23BrG7bbTZRwqkhe1FO+LuIIIF78AEqBOGMaoTUns+DDLUpRjOsDtS5af9TSbNOOJ1WY6R1sqdXbpgquoXIAiXHfU602KKcUag0tdWTOhxLxbgpwmRuJbCFP8+orxIDFXLIZ0hkoy4plWX2sfbtJTdchkenttkl959OiqfQeGyKNxwnjkxrMlU8Z3Qyew53XisaTmWw5mD0w3+Cr0qRCAqf//auLNwY7MEEBLrOKtm3ChUZvc+SoHVFe5NdgbUayDMT/h6B7N5IZQe8QtfH0iVXzZ/xrwj1I5yY5dI+zde2NzUssa3QpnzigZNPl3XnDcB+RilIkcrRWUcJVktTUpYgsXAspLpjnIwkdE6/HgChWFdaP6dQOhg4GsH9qWjGGGFATfvO97jJDvp29TZOTDKczeVhEvHvHp9oaxDhVnjNFq8p7+/cAADUGPygbQyu5kdkpFX3MIn8TCU9bYYpM9YYZmbMwOmq7ncFq7OJ8+2R8n17HB+MGdowMzxfZ7wqcn1mmtNnuM8+kcfIx3/7oeHzvxzNLux+/5p2PD6UwhKmMUuzyeb8TUnYE4zNodqK+7+w/49gvlmX30YjISopXJKPX6XKBZZ4pVDAKMFr3qNJC4iBIpQBjRKCN8hP+HmPW8jBNOal/ji8LuXMLJxzIqmcwUoUCEEuGP6E7M0YdbPoI3aeataX1jq2JBorKQK1SkmprTRwHN3EY7EMChaStnDaXXSezG1H0Mx0ZTd59mhHEzz9y5Z5l1D3EP0DFD+8HwihukGr6eCBydjwCx/04jq5nkny/P/49j5nLeXzs5+nR+sp2KcGv6dF6R1kWtG07eCrW299FBL6xl3CBnjPnQstSZbS8UGT8uoNvSuzlrtMzSxUZxYojUZ7gxe755fUVT6cTliK8r/F0Zh+xEoYEqL5P2jlTQeMxZxnm4B+MFzny3xgJ34CFV+hpAAsRuma2qiBx6CGObMomBPlcSnuWteXA/yeu+W9C7z8DeHmoa2IA5a/fAQC6pmf39rQlsYGxZtm7H6t1Oee2tfeYY4A9+MwShW6iATCPgzDHbv86Q/pRr7797scnKfpitAapJAVB5VPL9JkG93sP028MxrBMxypz1VJQSopAR9IHUpEyQQWeoW7i44yvcvnFW5Aydb9KZ/4/6/gfaED/502ksfTB2rPX0rSjq7D/ieHqDYJF/g10RZQmHpn906LZm9bMWfSCeSRHCkEhB1Xrg93GwAlSm6UTY7U0kyzezHU5SbvbFUwktYZZIsnlxVbzTEUT3rEUo7vUxACoN2AwxqomGI5EioNuKHzRGbmivDyBXgnLpwowYaEFvXUwBvrngfqpqHF6A7EY2YVIDvGe1ahC6Zd53Ej/2BhSF3DuhbwC87QyIVI2Z6UCxoqZlbLjLIImXyU14bCajCG47ZXHtpY+axTpjqxDlSrqpQBXNQiLxchrTTsjYcTjSVPCxCnkaFFLy40GzYcCbU/Vd6+skdPKpA/zoGLvd/1UMD5HR41pYBAWr/ydWBZWakhm1C4O+wUF9VPFeFVDIwGMC8DvAlPG4MOoJkMinXHAbep9pNkBmDDUQ+qEJxAIG7/qnJAjW0Ziv3XSCofgFAuEhIgRTIrdwCELST0Z7ZUpghNDYAmkF4rIrFqrpACrFasSjNYlYsxSVFpJBTtKLHKYvnrHpp6OMiuBB2wwTiAVNrJsxcy4XW9CwKoYssoiDiujbVp/VIkpDakXbYS3FFSteckANmYUyH4Y1wEuAl9dswoMnSshatJXmS5lSPIa+DK72jbqXJoDwT4C+MFxj+2Pma+7+756w76r7PXQa63zeArJvHBHRY0Qcn829nBWupqgDCCiqNR5wOlLD09BuYEUz80dNiZb2oLjLFMYq74QVCvAPTxWNeOJRRnB2rG2rI8Tg8YoXJVv1vXqllZWsSExmLt4ptreZwJKRAMAgp97MkwZfmKwRgDGMSCZKGw8VdMRAYxlWbF181OOfhoUecSnI4C8tpB6wIgoAh+tKV99PX0h7AZR6j3UKCbcmV5q/Xj+9IK3z4HL4o469xc7GqPX1qeogcfvhK7Yonris3haMPl9P914Pp2Ldx1Fnu+PShXlKSXCJk1FBsj+6BY/YNTY5tXGPbfbHZMrvvzKht2tylf3s72v1EgpNTqLcO0w6MEhyotEuwTKkztvj/Qlr1WcyJ1zEfzjTh9dSvs0v0NOp/Ml9yU4mdDQye+cvWCvAHB8kF45rRkdPAMcwAsd/8zb6w+S5w5fpHTfBDtTSJiwd9RFP6nz6qnPdynYH77ZIoqI3LhM9mkKm6yZ4UQPoPQRGkHckoMZW83vAKtKydDsfZa/ZVl0eoV2G+2V8RRXFhFJzbRRC1Yr30IFZI6BakCvtWIMxno64f39fXI08BI1OgpzDhCjqeUfJPCm9E4QjQRkN0ZfOratgchSkEoNd4mAryp76OQTA13oM6dsR0Z3Ru8YXTIzEatz1mBsLQzoW9ug3obqJLCoA9CCZSmoNWUPKIsmoiBHEqSOCQOiQNqYMaoowZa6SB9H90jHYqVghuW/gqcPLlo7rtSq8CCR9CIyqCJB14QLg112A0bROSAHpd0R/PdEsnQuzVjGkCirkQCzLCvMkRLQvV2AcWugVeXARVNh2n4icSgFMdom7bQtEqoyF5gixLL5yJCFhwDgafVtLxlfY/Uny1J97YyHtEwNci45lCBjQA7lJiD8hsouot1JM1gENhVM5azjC35M/vUgx/sH836I8BQnWZ+N7xkRgW0N39Oe1KTiFlci615zXqIk2fP+9YGYKIz0nNd313vn99OFSf6axRf9CNritdypoCzA+WR7XtZZ9mLRSDHl6/QaLaqgUzzWO1AVLIlNPtT3TpO2G33iy+/6/OC0KfgMvw3NGBZRnZI1whyaBTelVjhNtf5vkdDGXzKNUEgnmcJIuUVMWykRm9Qip2Cwl9cfRMBpuCWJNwYGeU3UzBf63Hm/Azdknkk+U9r2r82dzd80n4k1SAZ2T2nrfLX+kTjXWJp/1wlTatvamfj7zJFSynoBx6mGDzEQZSlGMlpy0gEq7fF5yOPiO0g72g6742jj3IMkTVcUXpAdAwOtAdAa38dvofRp/AAzogwApFKglv1WmmXOZHsHsX1HCaCQ64Iv/namj/eUjZOugB0gsKeAREJ32yZK+2UNZpNA7oRNxOhtaFcleo4HsG1Xj6YzWGMiqfU6hmcDgs57rcJXEavBzh0LzdktStlpjGmoAAAgAElEQVSY08FgRi3V952Vu5HoeaDzgGXayDxjT4ZvGh21AEwNK1b0MXBaJUPZdmuSUZMZRBXMm2fJsPVnQTqARRGyJaCYaZfteCMTewg9WlHHE7Z9+ejq/PSej2EEPcvhPXbOYP3y1+/x9vcfvQ5yAXD5/juMwej/+AUMJN2a/FmK6mxgszZXpqCju+tl9/z++v+U47f2KaHTrx4nTvjDbB2qmyypA3m9Mvzlwx0l7Zoa0V2b8I+fUQHUP1fgF8Y7fpb7lD83/S+D0YhQu0WrEwYI77dNnPJSBhKiiuv15nSHSfS38nrBWMP3RdMxCH+2WCQ5m/5F6YTSjKr6MMMtrXWY7aKA8HI56970Vp0O5fkCIoK7UsFgxooiGVPB2Ez2M138eMN4FWfcQoS1im3FsouZHLltHWDJdkswWsaoVNAJmvEqapPD+Oc9g0dqJIfBAns24QJZvErRTgdQfmCU739xQz8Tpr0LAO2Hn3V88MyuJcGDWHUI63/+Bbe//WNK0645w/xeQAzknzhwxjOnvUsxh5blmBNMHjmk/tpj71q332d3+87ZDPlianKqx/0wPr27noCmmu7sked5Fyb7lQ7ay25h1tXN+1b5X+WJALW5afm0Qmmf9fRWNltV6DzDiYK87OP/i8f/QAP6P+cwgJPj2xazgHDSW6+EzLf/TuL68abdA/jMKJ9Ang41ol2+djxi2Gn3tz9O31l0XEXrHdwZdSlY/iRKqutPVyyfKtrPm78nWNp7lb8R40ko33VKiFlsQjM2F/NWL4rdkQSKeNI3tRjzcpTCbm53v6f+JUJCAMpFWnblhxJ1USxqOnXCBCQifLMb1EwBa0y8Md1ZfnAUZ+P3vxisvUGM56YQCyGQ8k2OGnW+wG5az/NWPkWErRFV2TNnVWa++vuzLSnquu3mcBoSBSOGdwBPM0xP78v9Sr/p7kswdtZGHrY9PwY6a4onMqVG8jzT9SwkXlYWEbtqhBatK4gIt5soamXihzBzzO7pR4ALWDkipHHfz8aHxzR3DESq7uowQYBEO42m/RdDkqRXAaBp3i2FuyiGhiriNC23Coyk+8MUBcMIqCvwZ0E+5pXFo1rnffDA6JLpwQwE/93HR1jVthD5DOd9KinSwOypke4PjjqwO+GSEkwdMWQ8BqgmR5/8eppPOa9hjBYbw2fKI6AsVQwKOjBzJuHBxsPM+0eHzDDfAEJOH7rHBvMvG63AQsKM+vqCQoZrh6T+hRlbLDqKXHEmLcpiKGT52aLar4yTLQLn6CC7m7zVGPPdfY/b+C3H25dXPL08f8OdM+dx2CNTykTSDwCG0Xlq476/5a51pPsiK8DH+5EuCkfMTnKYgykG7nlgZgZumPDdTOstf8fhGz88e1TiO99TUFBOanhSHsgiHX3Wvra4+fojBumbjlijr43rqwflNYsHv8Yx5l78aplwd/+vEiofEey7F3x4wwfX7/sSFHfPtT7CZAdvS/zl41WLLhlP+agNN7BRYuZo/jJ4gDsi+hwWfURiRCJxiCpqRHJFNrE7jzIIGKJEMuHY0rkZM2ZpCWtZXAls95fEo1g9XwZAtaIPcRB8+/wZtCySDt36VRaMsQkvYbhh2NjJDRPCF0v5mq1twndo5BczsKwAFooSUwheXdLaN63f2T3ynNtA70OdwdTQPjquW8O2SfT5tm3q+ElYlqr82yqOYb2AlwrUqry1OJuwMwXhqCYRJgOVCF15dCFppOWvVBHXNpTzCSMshiiVQIPEQEhqlFBE1jHUiF41XXVVxXwFRgerMr5QwaAwXkmafaGeZnjLtHSCX7vGwHa7YT2dQiC7o7cJTxShvQMz35azKdg6j8EwyUeuNfTOWJcFXIVHum1XAOIwYvvjtJ41zT57lMLpfHI5CFryzIyWW9skXaZuvvvocxweEYGivCsn3lXX2h0+8vzZYw+OyVhqzNSHB6f/4WtAhqApcSzpw3DbkaOcNeRjoo/wFgVQpKZsTR/Zu0zx+aDFr2NnXydWJxNzcjJDktEXcrxRiqUXjYmQaRJ8Z3tIlHHymWXkSQeS4df/Q+yDxFvn0VjaY+7mxCNlHHprUW7D5agwvrrsmudYJ9Ll98FeOiCcjfYwFbQkhGq7LxTyBRaUIc+Kfj0cKGONjDvW9eSD1dsArAwcB//tZugA5O/m87gBSn152FY6bzw/gWZ8hLRH6KB/nPhee3ckbJng+tA8zHD4IWDn7P7feQRHMq/nrzz04ZjDaGNfups1ggww+ZMyCH4Dk/RrjyzgGsrmwN2TfCQ/SzFZlLXMSkMtJ1zf3gCE3uWqdIeKVCGWjC0D67KC+Qoa5NdpsJakZE8XXKs4ILojfRVanXOCWf+WZdEocV0l5Y1EP2KZ2TRCtkgtdjGcsc87M0NC/mRsQgdlLkaXoK1NvNdwvW0uaw8eatSKtRIgJ7UID03bzkp3YwHztv3aFv7W9Txq41Hb9OkFpI7n+d6afr//8CMYc4jU7cefJ2N/jkS373vXn8P3H/zez8cfCu7/QoeVrbXDvm6Y1+ex9DXPX6ZLiSqprKBG2F8Y5ROBPiNxtxz0wBg0mgOtBrNaIYtnmzBe1xBXoD/ysgb7Xhv6McZwzysjLsl+rkWdIUmderuiiuK8LKAG+R7OyFbWIcqLSBc6MxYqOL1IgNn4/EV6oGUH+Is46EqNdQ2mk0gnxR+KR4c5VM90tKpNw8ynm/XI8LwbUna413mNZEdhKY26wGQbORqA5UcJ1rKx5r2U4ciyfzBJ8KlhP0/h/rd/+PsC78o9JxBetbUXjvPWj1eSdO53e/yIgf1NR4bm/bmPn/o9h8l+zGKr+OMPnhwKs1xfVXaW0rUh1xmPJo4mRr/lyDJW1pXk44Gb3r/M8W9jQAeCkQfMUzqiEjyFhBrZPnPDWZl/rewHQyJARPv0EUwXCGjDELs8YQYEi1Iwg1hXgXIlQiWgGdxVEyMF1Y22aSQ2AVSw4SrK47Ypw2Qmaqt5rh/u2lIcsfowVFAgXsBoIKwAMdaXC/ovxq5fpP9Wy3EUlGLRIUD70kUphIHWGOW5oL+NnQCbPLBUGO7zWb0ms5Pip0Ao6LSBr4vUe6YCaF3nUi7o/K5jvTiiJawwJGARkyF0JTJuVCvJ3ZPgRZr2G0DUl5Tz5SLp6GROQhlq3p2ibKwYLEpO8163KBfy2oKqKB1SZ3J8iRRMgzvKc1XiRWK7ppEERK399ELeP/5sMKkjdSVS9vHM4yywevQ2FyCgflL4+6zEkbWeI5/1yYNUywxXIIhXGXkKFmN2zIveatOYF1VkZohIdG/UJz7umeDKldexwnsS5nORDN2+BSCp+D2CyyKW1hVnNaKXy0WV11KOYPTuWSg6M6oyd2zMjdb9tPpcvTcMGjInhdGNc9A+F4s+otzjUPAxQwUfTVlWLBVQceMliihwSimixC0VVEki0iFRSGeWbBFNiV3kdDMvbGXItA+uvHecl+efXeltCMHT1I/hSlAb14dsxQNjTRb24Ku7W9h83pjRdJ8Zas1RJcZAAW8+0TvxWPcPs9SFHe5UIEfZP29QqXMmTIi9Z+rwtNR7eHe2TNvtrXnGioykyiIG/3h/VsBZqm26UwxHZoB0UveYvDfwZ1a8+DYkmx+Zy9a1JjqC0QKAtYqh4Pr2JrDEts8CzqSNjrpIHXSBezXwlILeG2pdvBY7AJxOJ4AIt+sV4YRlu/nrxuLHiumvHfdw+vbl1Wm8zH2d7su4Zn46zrS3BlM6F/0nd8ze/DuKObWVz88GkvheJqNscgFxhaHu+aqOJCR4pCwVBClH4u+zetLvYyoTYSODCkHA+u2zfbe9+8Nni2Bt8I3RwSgngpRo5vAodwvDzAM80onGvjvszm4N71f00TgOb7kbK/m6ZWcENxjtn+HjZ/f3zc9TjI/SM7R/Rl4wGfH3DX+0qHfj39Hzrz5A6S9dtp+8x5Qca42ED1MTADy9ueGMmA+laRzCo5yO8/J8UZ555yTlTJm2Z1GwU6ejraHKTO+X9sMj24ncWB40kCP6SRW51pbhH1aHOCtDw4BHm5daRfge3XFrXk8XmofRPON9lb/cwUg2/LhBjopHD4IB7h0bGKM1cfYiwql3nMcJK4syt2rpCuGjO3qXtKTbtqG1Db019K2rgkiNqaxjVQN906xAvTWn2aTrJPXGF/CoAK8glkiMUYZmrlA+LNFh4V1SanUbo825E0EGt6tEZxvdURIgBnSgFHb+jmgFuIOXDowF3IC+sGbJMnzPUmeVCTQS7VAY2ac39mgwnjGS8TbbbcOGm+BATqm+SbO1JApDaiCsp3UyWtmcBIxqPwZpHXeGBOXo/tG9dX56VtZQ6EbfJK29RxZprciixnvWtogJnTuoC+8V/JKpNGXu/Wzi25wfSswKgzNrh4m3Tjhp7C1K6djzUC4EZ4KxPziwlL1NF1PgiilSe5tBnG2NeSpXQCA3eJWEE8ygnHsRpveg63uDeDb8yvhmysYpTb2vt+IUl6OcFx7Tu40LEfjPpSCC3+AB0ILAd5ZOn4dbQkQeE70KETxbiEV3EdQJgA2nh6KcpVsADKdx6oP+DTZvYT9n5QhYs2GYHNO7ZunSyHRdKBmp7t2S5gYwccJoB2kXCE5WyfioAhRxrEpUDEQyBJM79orJSVLO67MSaJAjBMkogN2hJ1YA2/5yn2br7hn/nOmj35XWYEyRAckBlDkiWGF4VTY6D3YniaGK2ukdNO/b6EnCBQRNU6v7msNxLDINTBs6emiGTcP5etn31A7XPpJf920HP2F9PsAP2p7zqcSeOcn21n4u4unYF4DO49fyW6cjwFWg0FjHO+7NagBbxJw5ZpDd9fHL+O6LPm97xHBqTNQ0RmYGFanVSwTc3t6dVwGAW+uuqzsvJ8+MItn6RsiXtYJ7x1Dla63VIfR0lqyfloqWIXLz3mQhNFGMU129WoQPM/wa47NIdMKCPjgCK/Y6Fqd2soZb775HAMboDU1lew90cPwJ/05clL6ExKvkZ+bf8gUEvbZ7jnBBwqJpZewrp3t4B0DkUuTb5y8+WsYc+W2zNgBoyAou6bpdA+6joM3AO/cvumGR6XvDB6VrE7uwa+ePP+522D/12L/lW7CXGNRZ6qInHZgdEUmMKTpYGlDYKJGDTvxRVc/hrBsDvzCcQIqQ4yltCkvEs8k/tmdaH86jrFSxbU0C/ZAcUVR/Zvv4aCYmZ2h7DkOyVSHzTACIJSOx7RHVfwJSctO5awZKqahMaFo2AkQRQKjAPAajDADnBaeL6Nkv4w3vr4y1EC7ffRID/ec3DKl9g1Kry+oSGb+zU1TJnIFuTnSMorpeAFhBqgtW2qL4ftX9e2Zg/Y8/4+2Hn2YIZdWZA1j+g9D/zqi2XASsf/0Txt9+nrQ3A7Evz//1Pd7/9gMYQCP4syZFXf7zLyAA17/9hAqxvQ0wVu1FAWHLvMQe3nQt34MpgOuAmLFk0pLkqq/T8Xw82qsZ29qZuY8hmTh3IZ9Rv9PfoOAOgCPSnNU2NYTn9ZN5H3HMTpYRpxEkWFcCClhgVZwESIz1Tpb1PqFpRnsUhmkAHFlIAZVXRtk5fcv1QoSx00X8s48/OrDv38qAbofVGHw4mYl3u/7Gtc2PUd4ruztaEoUmr458V1aqwv3/Jwb/ISXcy08syNRq7AqBE8LVPg+UlwK2GttUBMkXrd+jG228CVJe/lQlJeXrQMNAvRT0V2Og7iPmYnSZf57vIIrPiDrYQFRFAVovGqVBAK/3E2v4w73W5R2e/twR1T3Cyl1yxbQrWlMSWlNkDo26LZI2xrxNayHwIPWiUGMUyKPoPZU7AYQCIlNUWNv6njf5KC+E/oWQwwOy0GDzKfN9L3g8wk8ZtsjaMeTLDHoB+LN5uQdjn9dvYsjTqwM+Q7gXEn/21GG5m2aQswuZnmRDgPXExm7K4jym6Xd6z9RvBAElSDrpRZV667piXVeczmecXz6J9x6JQm/bNuB6k4ip3r3uytAU64vVF60LQIT37QZiQmGN3nHBKq2fCS93bD8UTCWqSeBGYGeMoUr2jkoFGMCiKRBLrZriTSOulMkCAVVf3hmgrtFArKmBSnElkr3Hu+HKV/kcPEBe9xLuSS2K/eF9/y3Hr4qAjGm6/+1gI1E7ggsHCNXnOrJEDJkpixYBPO3P8Ag61v4hDC7avjm1TMYswLNZHJKAdDhcHuByiSw3Zi+eYBtg4v/I6kxNa4e0PXPjRy9LfU8DycrW2NMxItmjlnvehBF1JhrdM2/0lKrV+thbC+OLrRgzSqn6WULwyTjbldip8xR7/r/3qA+vzMYKO5e+64/hoiHmuf0NvXm4h/bnDQd6+n8oOJdQ/Bps6f/MjPE+dngZSGqTP+Q42jNOE0Cgsxryb6wpj2N/7p8JR5nH7/raEVNBh/M7iy17ivn48DGletr5MGfP+YH72Xm85Ml4/rjTd4YUw19THx8N4qC933xM8LY/nfDEwXsCrxj+KcjG6f0YS4ILMzaxGmBBYQTydJ/DUtDm+Z47YjwR7cZh/FXGz8I/hFLXIpRLKQmCTLWnv9VZzQzTwg8wzCldlMwSYV2VH2AA6OG4GA5kxp9C64kCtS64vV9RT6vOH6FzQ6kLeHS4UszGpUZ7ig6Igml0NGZsWxelsUWkE6Esgl/KEPrQuqR8v96uuF1vuF7fsd1uuN1u7uRYkmw/hqZ2B0tZKY36AoDeGOCB3ivqMjB6BXfGcgIGFRHaS3Vjrinlre+hkyB1CBTrlqSXNodlvSelJIel3h9NDOEELEXlFuU6cBIn405aU10j9Dt1ABWjFwwaps9AXRbhrVqDGVYIO9nVlUTshiM5rbRWS0F13RtlhycZ5DSWSAy7UH7cHLsAqydJapTorrQfYKxaUoyIsKxnMAba1mTuALS2ybWygIlFKcOWWYHAKGI/5S3GQCYJy16WOYkoGudnfC6OaZudzkUJ8rHPfnV/3b/NAsS3ILrDrmVcbvxOUH4zZjGMl9k57fi63UdJ2WXnTPfGbzNwsBlXYtSZesushzNN5teykxK5sZ0CoCj4iZk/ZeTSNiZ98SB/1NcMgKmizXkoyyWEIoQxyX8mPXFKs24XzE7u9+SRM1xu4S77nVW2b71rNgzGGM0dLcyRatgnSqoxrU4a7t1gfKlGrcHdZRT/2qeZIGLqCmQ/up0y6Qf8+Wntba0TEExHOrkhrXbMzVeeuvt+z4cDj3Rr7PBnfUy6LAeZY91cqPsf7byPeTxxyDl4Mu0L7+NdGybv/V7m5uPjjudxWvsBU8T4YL0zCvqW/j/Apfs+ftNUPOLef8NBwLouQZspD5qwtY51EQdmgyULAIiSOAXns2Tlebu+Q3R63YOETueLv06cDhVxqK5lLktHqKo972q0Nz4KbmwLg39gvAKikfCmXpucwmKP8OjofuvATWtFE5kx7H7RTSdmEfaUFQC0A/cDmNnTAeuM4cwZTxzLe98qBdpe3t991fML7iPKweFvsTd2W5s5Gv0RRGc8ss8T+W29/3//uH1ly1oIloVpPTomnuQAB5fdvYHt03kGNrpPz88sgYxj66pbDnpUCu3g9fFhe+J+ayiflGTLnF0p3zdU5185lcMrNCUme/Tedr2BvvsEAFiXZ4C+YP3Ti+p+GVwrWhE5kUCoi6X2pqk0EBUCd83IUQQHSRVYRuGCQZmOGj8TciER4QYG/e0njAJUR7r3E+kYmIRXKaXi6X99j+3///vhnPfeURmSTl7PifHc7DPzK7YdJungKdL8med9vOfkxVFh7slvUC/vjj+KB6D50+GWYHLopLfy21jkcaoxO7+LNTHZioJGgDRlu2W2PbAHmMyvun8JJu6e2Y30OnF3OWXs1uZreON/+vFvYUA/gitX5Ps9cpfVogEI74dpbvW3OUoNa4+xpptGwsbTHqCiQpGeMyaLChZ9zwAkHSEYsNS/ZXEkQxDlkTShgD3M00hrhvNQDx5FlurpwSZ4qscULwVYgNvPGrnFQMc7FnoGgbCNDqm/vYoRCoTyBNxev4A/P8kYEhMfNXAjpbsdmeU1wmtzb0jQ2ExjfgdtWEiSjle6oFIDlQtonGF1hETIP0Ei5a4YuIWIShpFT5LOyesFUbwvs4oal+I1RKyXVMRjLEcmMUsE/hgDuAFUK+gi0by1FDCLglM8zjQqT4sbuhz8ygjPaUZlAqgCBJRnrZ1MO2M+AHpRj/wvphTSWoxGmA65WobXYDYGQ5rH+EUIcf1Oa8p+UgEdVQmQRpK4L+j7jrvJyi52b0QRhoPNZc1RXOkisgm9K9wp8XRvWnLCnN8zERWHnt0em7slhN2U50S+xqyzJn9Si2YtUlPmXCtOdZEa6EXr9ilhs1qPBElbQ8xYWRkBljbF61E9EMvAGOIqU2pJaf2BdRU4K1oPuo+BZakYnT19qhGiUgpWjRDqXSJXpQY6T7U5xUmjApomlHzZyaPlB4n3F48BrhW1K8u6qHqH8xySz2XMeqQZk72gz1Pg0o8I+r3xIXbbsVLwuM3sRDK1Q9NTjk8KST0X6TcpryJ7uKqRnIYojc1xYfTh8+uGZAYi+kX2YtHaZgG4UKU/ofUGMLCsyemH1IBDwOjKoGttVeu5RACn8ZZgrqDzDjWY+D1HOTizEO27JMYksKECAhOo2l3y3OB4nkBq0FcGXvFOLRXmMLTdJGNDKVZvXsZ1Pp+xbTeBTwjdk/nfiS0EuDHekDWA203SCF+enzE0de+80vBndioAzJByLxA8Mjp/zJdadpT5rj08xq8d02wCzJR/5f76r+GOJy9xyuONNsxwaLzOeBsoFxK+plqZES0NMmKdWGG7XAr4qsYMksjMo54+7PXuwj25MkW7iUv2gAmmDNbwBKm1pXmCXHGfV+B+3Hf9uOvoA7xyfPO3HxMOTWu+F070mPqbiJygmvTMlGAgtxUZDbKTz9007I0ju/WkScXxa0Sej9RX+f3z2fvfYQwjq9Pp+Cv125gBgtc5L7Vi0UhsN6I7f644L0fxGM2lSIfuBsYUTQgOxYobwqaRKYIhWQdLZV527ylFMndUM6ArvyFtCZ1iGC5UHo+t3XD2Mke5jiG1A4tEPtTefcxm8KGhtfBGRFfanBCJM960OPoXNgRKeEHaLTq+DgBevxqovKGPRYI+e9T65MEYRQ1UaqiSVMod3VK4K68FHiEzsNEkxkAP+LSwbRIHvzIYoy1oOq66VPQ+UPvAWIZGgGrmJx1qH2E84z4AYvTRxdhvMEOE6/UGIuCyLspDdJCmYWctr8IABovSfPSG7dY8wh0YwSsonzdMIaGe/eZP44oxQOoo494ha3+UGqK9LVlrJpMxqjpLGIhKnXmJzB+9iyxj26lAspFU2QOVGaN2oDUQwmHP9ov1j5S/BAReSaPNrUb94jWvba4kGr9rX7QV3X/kTrVhsAvkLeBNaVsnyb4I3MH3ktahRTLUEe7zGu8PM6j4uxPPcvDoJKvoxpGfKfLcm2aN9FfOhUzeTK1NhpBMCxIvt+uD9dLnbeof7+Yq3azX77H2jjtP4xNYERmnrjVlIVMjsd1XCKYG97FadjbKWfsE+IvhHagr6gCwSp4ze4aYHH5gBlBGrJl998hzxJ/2i61khDnGK04UfNVTVG+su+EyU9Mc8pAOiuxeucSiFAcIXFQWKey4jZDpGumzHDRKF5chz9FI/G4GzYOO7KFA/u8hGmByL5jGwGks+Y68jbI9fXLQ4AxP+l5dW6PnPL09Petn8lsDE3IediAKvU1hw95DmHQSU+sZB3Byg+TMbwi/O0dj7td95gS+NfKJdf7LUufRTvJb9MVePcnrD3thZ+Ku++tz+9l8L/QHnrzOW6B46qusoe85x0qK63g3R3ENzFiXgrpUtCamzmWpLo/ILYzbFiWjzucTuA/01rGsFUQnXG839N6x9ebp3Zkja1iBZnZLc8NE6tDEMA9FVlwh+hzh28SoITqEWA/lizjPtUB3IXFoSws6L4++J0pfKJ8yhHZZJg5m0R2YPjsmRNosNEdoTsb5aVni/K4T01eG6a4Zrn/Iz6fv+X0mq1i1iDMIC8gN4JNhRT9PkL43zBGcWjloT4H9uxllDGYHwkAelDLBNCTS/SjyPN97+7/jmf9PPWZscH/txGJE97nKOBVzzr3clu3EhYLuA0AvBSsSPwuggFG/I2w/MxoBZwj+qQj7CoqsoaUHNwNstRs0c17TYJiiNcJ77zCXtamTh5ibvdb0ovr/7GANIAKXKCDDU6qr7YhBGlod9ol4Rex3UnxpUdgDQL9tbme4/OU7mC7rdF6wLiveX99R1gVufGSTFcR4f1pWgCr6aNJ/3a9chL0weWqQaug5OUl6x6QkzI+L1Bc3TYxlTOoEnAah/wBNDa/OqaRyFxU8/ZVQlr/g9X//OOGZ7Yef/XtJF+r3fwJ+/AXt7z+lXIfYaR34zpnmVZfhE8fvTLueWNdQ8eLQNaAY8I5Ht2U92hFfJ28ZKyUKN+2vfEf01V7Arrt2PS+Sk6jSSWFzw5ndnFLc6Yt5atf033dsiLGXOubhU0UhdyZ4Nx2/qAlFluvc0bT0ERjgWmA1CqR0SUEZIzLW2qs1sn2MrD381zr+LQzo+6NQwUcM7T0p/2OPvVjQH2zWSeG9e3hiFjIPm1rvTp4CqVjaB2EcLY0YR+2JL28C+J9UkNMU4LUU93aSjX8RE9MFGG/y1v7Gd32479U8PrpDLTouImXSVTFDZ1WIXtSouGszMXO5taIGrrpUtAFXHArSCYVAMGh75bLN270YIlEwrBEbOsuloPBQO3lGzKT9JzWSZaO4ETGanBHkkxyZ4SmI9hGaPgQjQ8bYe/TNN9Mn6QtDJoMNgScmfxYXrfKaNGX1Y8JLmxUxiwDRpzaUcBB7tOjEyBHhkVJnH3GeR5OnzY6ijEbxFKPz6IXJCFgphbCUgqW+4FTPIhyRReHE/eEgYIyQGqqVlexmGj4AACAASURBVCcYETLlaAGVoalX9DlS7y2ytNYygtaa1zMvXs+8aDRYROUWHlN0IqmjCLJBL8+lK8I1PRkk7b95uZuSXpTbw4UyU274vgGr/w07Qc9z/i0R5PdwSP6/6YwO76fdObo77X2eWidgyWmPXGBkgEcYFEfHIKmJTqREniwCC16LyRhGWWOea7reMWcMUfBnMS/6L7c8oDoK1IPZGUGLMKQikX7k5wGqe3Ytxk8IL0/jKfdzbPuSp5qJpHQj9o/1i0iN5IqnHZJYFEx1WVC4ojdJ9d5aS3NFrgTJEe62Pwx/Gv2ajVWiZOJt28ES3w/scEb283N8x8fP1cM7Hj2zpyBqDgva/PAp3n173P5+HP7Mo/ERQKiyB3KZEV+EveCZnzXE//uPDFbzUZFjEBxGte/iEGf49v552s/q1ybxm3v6a64c7MlMiz5Ym0fn87Q/vi8hQb6bibjv0RUXmna9/91zeNeBb77FeCZlLnwezYhn9xYSJ0b7s9TmNqbH+50Ur9GcVt1SCHdyvtGoPQAVfHW+HEdpi/bOQpJSj8w5UHjBWhdPaW1GdKMbDIDMqVfXMffVSKUJx8xD0l9XkvTgmto8801Cd6Rfw+k8Oz4PuLG+k6LVEO6HRjWbAD+sTJEy0iO9jUiV3WA3IAkPwaDOUfM81T4Hszsa9s6aMUvdZ0wpB042aOVIreva384bzAFhaVLXtK4VtauxkiTymc2RQA1lozePcAd1RYXVU1OPosqpMUKxjgFioPXmkf7dFDejow+JyLbobeWeQTovpQKlWZ1Dwum0omu2nMaBAy1TkMNaOlhlOtu0ZnBjIix1ddjOMMSUIteNRVF4Np7THPfMkURgymPZRbFYxXiwLJLxoI6KHAVPgMM4UcGyLDidJc3u9f0K7pLGv3n9c9vqxlfY2htGIrjCaUL+cxyK7R1ij7fR88m0sMOnk0FQbo6Ld8c9QvRn0l7Kdzv+Oni/7Hns7vcrPnTDVcyISl0PujZHomOaK5+Pg8cPOvHwVKkaHVXDPZ5YkrsaNmNmcGPQElQnaDo5D8MWNVr0nCU3MqFLx6yitGSWZnPqRchiqrRjDhyW/6Dy7dBrUlOVPaOWlWAzQ7lpCuyrir0yDpvfhGiz0z0YYiwfgTcNLu0hh2zdpxNfDFHSu/GaE+43mH9IS6N9MKa6518j5bz7/OiZyGxwf/5Rw3k/3OOz9DxlTmW3f8DqrIR538GoaFZWH6hreX53ppVudHz8NPYzIut4z/flMx/O+6zUy7356KnfdDxq8Zve9g2829ff9PFLqRDWswQOGN0rJI7ty1oBKtiaeNOezqu+STLynE6L1w033YaUT1SZ2h0kScpXJU9Uj15Ux/pieAAI5zAyZzHFL7BQlqH6JClbEhnUpA56Q3dj9aMMKMKPCJ9i/HsYuEMedoO+NqDZ4p1mudMoEnl/sDqPDBnT+QnJfXDfVw7bC0d4pUOKRRKk0sT+et6fua17d2u5ZkZKOnjGvjdinJRHyOqPP37H/escFoGe5y0fPs86mXfZApDgjciDBO0wrWpez3eIEX0PH3vYClhmX2ehf8nm4YyR7M+PZGr5nLmtMYbIZFnvrPq3TBcYtt0Ex4wuzjRi6Ey0Pe1FG+/RfGUaVohQlwqqC3jrYC2PKP0QOsHqbGz9MPnDmALWtWmGrzjNufIZJ8Mp6TDDfsHMkw4w1u8JpX4HooJNa5ZLwAxQyp99fHmMWnh4Mp7LmH+JOdL2Zd+K7SDDxwfB/IeHzMNsU7C5+cAM+OC4p+nHb+QHvz5oOQDM5ewwohuMKSyNIdmrHZa+pV+Pe+t6auU7PfhAM4QlLs3742W4umUVHRIIBsBKL4g9DJL1IBvQKYIDGTvHxX+h41/OgO4pmXmm498COsZIj4khTl/088LAO0RgWjRSzgwP8q4QiFJWbWwATgoULfeZAPHADoWXKfxCiJQ0yp9A6AR0NUqsVdiH1sRQsC5SLaa1JtGNS1Gs0ickEynHra+p/1TFofnJ6mYQTp8kMnJ8ucDShJnxb10uEhHyBnS6SQ1SIpSLeQxL9Fp7j/pDgQjTPOzmxKZ8SlMBmoiZzZf/6fxWWK0FVgPgDcAJBSclyu8iWBPEwKWMqymtTBgzzx2L89QupN8pTR4z+EpAYYylA8SozxZlIWJjJSHamxGoVwYvDF6GeL6/DvB1WCEYsFaSL88V/MooT0D/ovNTAtHPE8gYX5Q5JFHESb3reYJ38qUYu0B+rZDUPMcbtM4FYfwscFQ/acaCTxKh3X5pQcby2vlaCoGqhhAhwgehSEQUPcmagHXcbxPKL0WyGXS8aT1vuoMTO4QZTnCCRHxomiZXpBddoUnJjYBxS5haoeOlGzYQSj8DJBE6GOwKkVIIFR6mCyYh9IWHpN1qJHnSpRMoXB1PFBLBS1KFp3GOJORodIKnc1UvQ/F2Fi9INN7tHWh70a4BtI5W4V0mqVABlyGKhx1n2QBgDLVPhFJ3sCqbdiJMrKPAlylZc7PKy8l9eb+ldfa2zOiwx+wHjG5+P/J8Tk+L8qmgSArSvksJPr2ffM73Ee722+MDXUEX6Z2ECcn0ibCs5r2uimGrK8MCi6WaEl4fGUO84d0dM6IHzbDBQIqIhK+Vd3aSTI1xZd+0Et2ozIvCtZT3MOHcMp4IM3XnWc4QAwQjary5s4HMQ9cI8aWurnCw56UbMpM+fo0MGX0EfWSFa+s6CNu7KEyqKTwOEcDRkXGYMo06eeaIMD1+NJcHhvPAg/OD1t979tDgKDOw96/d/wpwzeq5fVzO3JnoCc92Br+PUZ6rGgzV2Kg1DiXl6M4xCgBdWcsTBA3dv/fo+JqC5fjpYFMLCspJcWcf4Jutp4nisf7Tzt0hGNp7bt31YI957t0cDDYnmPMNjJguAu4XaPcGmumTt70DrNgPLqPEtYdzf7wn7mBumqM9/uXd7w+OQ1nuER7/SlsHN7hDIeXVUl4QyXnMInnVqCNpw6OTvFsgYd3IeSWCZehRb/+EN/dkg5GiDcj6Q7BIV4JEKFlfqUo0rvASWje7VtRlEV6MzFtc1UMs/vddcSAKTWn3QGrYZykFQYOA1jAsFSly/T+bQ3Kly9a0diAVtNbQWvPUpVSq7DUFvJLHT8Boqgxei8+jG/xJUsmPLim9t3KTTC1QQzQGWh/o24ZNa6C3bcNt29C2DX3rug7yRpHD2A3qZpQjXxcBDAnoJAADfbDUZG8Ny7KCu/Hj4tTGjDCgj+b8gTgJqKGdAYLybWqQk3cPQEvZWN3G7bpBA9FkvYjQtg1tu6HfbuhWF14j+KtHc4pCrBRgPZ2wbSJP0V6IIjUgjD7vtWk/BI0GzBFWaXRhT4UuPJ3IcJRkVCjUhuOm0X+jIZaZSteCQqGyLAuoVFRXvDBOq6jnShV+4eVPfwKx1JnuW0dbJOuAknnnDWwitUoyJsOS10ieBu2A6ffrx4DyzTzNkt9DCU9PaOdjkiX3FzOeBi814e0srPgn3f82smTjcPKWFKJ63tZwBgKe+muOLI4vbbg7I+P0Mk6kyx6c7gke1xyny2L4q8bcTxyKxKsNZnTW8gulolpOPR4qb5DgNhI4xWCgyl4bPaVnJXX8Hx1W2moygLLsSY4TyqfDDeWGO6D7mEc45Pha6nfx6bF6q2km0tS4gUb7InOkdJRZo62N/wdMOcqkBrgRSt5Hil2rOYlha2T7wbIAxeLNM5C+U/5tgykAelzbGZNZx50SUU3XU6CgjCuVWiCoHkblCXursTbm/OX7xkrfAV7DXu6XiDkHzpylDokfykwSqbP7UByi8oaVNIv145jzB5Pva+ecICF4+4yEDtmt6Xzmg6d7nfYrHjE+XN8tzsemYbl/n+s1Hrzf3ugr/+BGdy4yOTPhBnsuO2t4mlw33s4ojcCe4MN0cD4HnBvdmUeYsa6i2+qtS3YSBuoiNPv12nT/A6fz2R+zrBWRoQxCL6DpjAdrBRcBgtNplQAEtvmxfRjGuaGbv+j1SqJTOJ/P2K5XeFlMwOXXanNh2zLDmP4JThZeRSfT5Wkvv6IJgsxRzR16eIC5i8OZGdO5Jv1Z0X02IvV1kOUwyFv/KLKOya2OZTK2yNRmhmWmD3/b0cBokChze4/gEcEbVeHbosftXXZYHj+DlgrRWVUk3IIw/lkbhqOzBC+GRZmDK+kacvCcFixzZsL1NzuMf+2539ouEAgx//51Le/X9UoSfb7qhTcCXjLeV7iFykZ7FrVCcPlIBNJ0HbY+A7L+BUD/hVAJWExWIdPH6j4c+g5X92g0tLbWte55TYEsIEQmYEdIcz/zyeBZ5BePgbfrhlI2PF8uygcMzSoRji9AOPBHthx5tzi/BN0NvjAc6DK5+fLLZxQiPL88g8fA+XwSmZAqSiUQNoytgooEBPEYaJ2N8GKhDZ2BbevyfnW2raZv07/OQ8oTK1JaiTxwjsCehvuVgL9YcguVfSCsCvo/CMv/WlAKYfzndwDCAXGMn3D9u+rLEz7N3GSONO8/BC45fU8YPwbfWP150qwUgjueFR7fyJIKZRc5o8+xph7pb8J91vU5T6F9SvaB+8Mg+H7n5eOja3bF134IVTS83RVRFe0nJ7hi/a2PwXS1fNRf1dspu3NvT/E9rb1NihWTDyfNF4cNRP7UToRkF1AYsEAcSi/OjpAe3T52NP+feOztP7/3WGZSCPwxv/fI/NG9f8zxMbP4jW0YILHVfLDD0q3hsPt7og7AjedHG4gffLf7CWcsuKL763YKfWd6jj1xaL41fpsCnCTVSbksALPWLGeUwqifKupLxbA65q8M+k4MdgTSFPIF9VIw3k2CM49MEybirYck3YhIgolA7MGwZIWDeV9nQ97e0434pHMT6ADajiuA1KDLBCt/iEkMoTkSPfc+I2ZcGLQpsz+SAQrGj4eBa784mYh5H2FJZth/+1V9pjxHyqcgv8fM6dGRe1MmwCCUZ+joAHqJcd95bOkX12Gk2TGHEHAodSqFoCa9fgLjddfmJbVx1O8LhNl6n/qx/7TvNrTQs5D/pSr28a5ssLD50TILRGow7kOjpEypKkp5i0a2Y0BSaQ2t83IbIXBTYVdQgix9X3Gi7ztC6+HJcxI9Z+nbpaxAGAjYVdkckejsb0wpqeZ19LUj29Xsbfr8jBF4jEjWkmJ/AiEQ2z0gmozOXdO47tcIX/tta0Vxh6NesjVSBgLhHWlZHwrBI6oY6l2uvy3FEGlbxTxU07tA7AYUc7AQJsZWBbpjoQZGeHSjGDHyxFjHH407KW52EzV6B4XFB+kR6DQ5E/LIg++OOk8MhDnSaN1Nnbcsy1u5A8CgKnBPIcM/xfGUjkiFiaJKxzCYsM6jeOhKSv1BrBFqyiT6/OdoFqsZi/SbDuY1zeeHuPF+3x/9juM42vz+GXpwfr7jWzmgfRt88O2j545x6txeOecSF3qd7++13/uME7+Gm9tR0l91OE3+hgk86vfhY3T35Y87Jjr78bWZnt4fv6t3BNBHfTnoz6+8/Fu69MHFD/YQUZqrzL3ZyhqDbBhaANoMgVFu4ZH3dhiHChntgzjBDQrlNkKFLU0Y/6YY8kgEUqWLGeGlD0VSHlcpF1KrKEoqVZdHgI6uZS6oqBGXivCfZM5eittVwUOs6T7HQC8FSBllZBqTAZ0Z1+sVt9sN27aBSwGXgr5J3e1CzUsjCK+g5WwsAtmixgsrvlfaoll3mKStVghbLeA3Rt+kBI3UP29oraONjta6n+ttgHvHos5soUCwiFCdb5YocEbwBVlZx0OVSWdVmo+hGgqLoGZXQg816o7e0VkM2HWBMx6k9Ams9nKL+lBDzxgDm2ZFIQ1RJUhqxt707yZZAYiBWsVBoig8mrzC0IxFDFyvb2C1TJgjh7J5jqsZ7KUNHLsyooYuAaY+5iEP1kV5StZItwLc3t7Qesfp5QlmjBOHqjDsDBrivF06wAQuA6zricGgWnE6r3h5elY4ZS9hU6hgtShBlhS7G92w9YbWbrPTom5047v2uPqxw1A+AjeQ88f3R7bLzxfyDR+9L/FGRPd9y91HNrx9cGS+kKyN+3mwb1P2Mn/+AbE8GooJazZf+mg41Kd+aDeoiPMj6R6VfU+O63zttM1aZeQDkmECHHoDK1+kjHfKhGPOAxzzG6hdjmJGbp70ADYocxrI0efDrLbMbrdzo7oZt73nFmVjzUoHDCwsnS3rvJlh2HkplxVjj8qQEmdChITW9XZKL9W5JPbTsbfzLLMxars54HSH0TDWGuvNr7ghPjVhmeYc5VrLtj9TF23NCQVlNYuHzF8FYWwS13bImzKiFude/zAQRlsCJj0JBAeTlh3aM6iPWEZB5x9xs/dPCeWnB1eP3uAj+Mozyl+oTIkD0e/DV3zzobD7CJ3lycosjj95/3nUn9zEHm6wm78k5WG6i6T0ipR2GW4IAGvZmalXciSfcr3X6LDua4aX2TuvJ9FjkOIM30uKw4j8emFO+kF5R04XbnDBSnfBQ7NxlNCNMQMYUjaQoSmqDRfYvFk/jY8Mx5+7qWbJ4MN9uFOQIAc1Xtgk0qMdcL8mD++bmji6N93A+exjuuk8mv7uCK4sQ8J+hxKA8/d/xuuPP/m9L999wvXnz1PvDLvaVhqYe/4tHMRuZP82x43EiG5Hnrv8Wf78CfjpsztYHa0V6/P7Obf1EUcJwvod0H/mybZRPhGunx9j5si/EjiNQOITlgnkrldKjaffRlfkO02D2MNxxmBGrppml1qoYKkLzG3Fx02msU28m9J8KN4wx1XBF1KOq1YpLVrXZ3DtGA2ohVCXFW3TGG0mUB/Y+giDeVoAdR3D0O8nlsIt5hyXR1cAPLEYp2+kjhR6T3Yy9IApk2tJnJOuP7BnahMHC3U6SrBQEEZtm+jIXRRc14LQQ8ozwjFaaQdCpHLfr3RJ56y41Lfu+ePjHhMYO3ff7iNMk6mTUQ45nY3kpPBMqQnn+dIafL2/8ZXTp/fO5s4N27qvXY4JaWXa9yTBiX5W5UgQQMVKgFFEodtKO6zQfUnFf7FjuZe67Pg9vynB2dEE0d0ifu0wUJt/5/cc9mJHSEmRdXeAABdFHgKs25AUIuog7MpiFyb1hWPwNDwGcGNgIUEwkrqPPfWzpdSQVIbk0aauJFDhZlsagAKylM5q7TQwbV1qwFaqoqjixNIZFo8pBhA1eAiMMoBC1ZnF+kzAq6RYGF8GOt5xen6WpohRqIJKxegN9EwYX95w+3zC8lxx/dJQWUbYX1OKRkR0PWcPFqKYLyZXRhE0ekHTbFrN6qVULOUJS11Ql4H1BNRFiApRA5WBQmcspaCWBaM3tMGohXA+n0B0UU9OwTZX3FIqpYCSSIsRzJvNmCtC3oExCEVzy5RVorZrJSzLgnWpWNYKfge4M+pSpC7LJ/LoSowBeiIsldCuUjdtKVUUd2+q8H0TpNRfjYFWyvqkhjt1eJhTV9p9BURGmuZhWqRm1V1QGShPxugTOvouPSYUwQlMUZFo647PEI+jM8BXLHhCQwfRVZh5fXbBRcGRwfSOwVcXMIKsmBEsE5EnEN6lFgcBC1v6T9ksBRcAV0BrIhrRsf3scYhEYVjVqFaPlCTy+0wBXWvFWisWTadq8DtUuXtrN9zapgrWMB7XIinQO0uk0zaGMDFFlLbd0wFK72oRpfVSCb2zK/T7kBTKtSwolbCWgsvzCy6nM5gFnngAt+sNVo8PIE33WpzpEsIlKeF760LQJo5W9ps7N+yNFf6T1aszBJC9Ysmfc5gJQU8iMGYNQG7famJlhjcDLNnF5OCQ6YWlIMo6NzBEAetcBjSiUJ1uNKJOIk0cocPTG2sdXBoEDMGJxWvlmdef0QMxGpdSBI+pBo0SUZhiE7TjZZqTmEVTqE/pfxmwxBKTgwLI6/F6P6oZEMJNxNJQAvDabKP3aW2yR6B55ZuyMa9bYY251/+s1imBJGJI2zKHhDEsOkgW6Hw5Y3u7SqopS5mv97AiMyKByzDmB2NvGSKgCva6LCggXK9XnR+bR5m4WgjMhK5RantmlnROw4s4NXJ0WITzA441C1eF4XS/Q2v3Xgr4nR1n5ZRjpM8YxORePObMDMDNoChny4vQ1fEGRW9hZGS/N95VzlIKQOBDs1yogY6JwJ21dKfURyIUlHcGJGEIxs1EI+twZsaO59PghqfRPZzYux/jJhjIlUUIeKFEwU1Yit9IyILy9nf8MUlCWc5BWnttw6JKTEp1pf6Myqb+OR6A0l6iO4e01OlY5hiBplw+ni551w6ClIHNMGr7ZDoG3FBq6zgpJACwGwU/UIvdXcjvDZyY+YzUef8svrbhxmNxKjPzPWJxbFE8+lwdqBagVMJyWrCUCqNi4uMlfLRHDGXFCQb6IMnwNFg1nkNTkmVACbU6K0D10YQ2st8iffaBww3fVEiVEbJeg8Q4OTQykrm7QpUKoUKM3ARRMFMRxftgcVzrPaKSpIcR/ZhpDPeOAaC1hm3b0NrmOFHqhJqTlTnZqPrCaukprSVmcJNBlsWccUJILgDQGe22gamjF3lPZ3VO1AgSm6aiSzyM7hLJL42SYBhtZ8Ai+ZUPJJDKT/pbQaLfNtzoHW1raFtHXZapBjdjoLUh88ddaeWQIGhLJU1mpNd17DGnlur5+vqOQqIsX5YFtVRJld8HWjPDoSrKQMo/Cb5VAERdTljKhreffhFMaevv2WIQsp/WVTfuWsbETpPlnui/Mc3MDFYezyJaq87HWleN5iHxj7PyUxZRRgK3vYnhbT2dcDqdcL6ccLk84Xw+43K+YDmfAGa069VJQ10WXK+vqHUVBw6SDGvX24beWcsK9CniRfjOpMihOSLDjyMjgzAQCd3tqGqSeYS9OXDvMtl1RxPkazwtqT0PqJmTa42o19/D8DBH8+Joy05jjKY4/ZoatfY4Dd/Gl/jL/FI2bBVj8XTm7HfHOJkdJRo+oGhY4Kaao7rykm4AYmzoWFBBZWBA0iejkGThsL/TiroukiWEisjP6rhhKZSJhsK/KX0ZjEUcObYBU7tbrUXGAHfAtdMwY3Hwf163VHGARay5M7TKeyLzqhOT8kGkXvhkaS6LRXvKeTeucayPcT2jmRyR+SWldYXVGGxAonyPEpIC1VlUkWNY0lwoijSmhN2hSWdC/pFGqhrPxgygSWp5sMNjngul+ioX6NruoHBMwCR9Nd1ZoYJ1rbjdNqxrBS8V17ebsSVpzgzewrnEySaMT9O142w2SdvS9ovSyTBASkvEMmeWst/kkwmXcPAkRtmnRUrnjnkgvvv21VAHf384atAgD6sP46xkHWHVk9laOma08SuMHL2TSCIQy5CZM3gVn35Zv6KZc6Dw7numkN+vaV6iUZuRvJa2IGlNoTo5N14ZbQLrfgiDQgFQ64rtdgMgzox1WbCsK663TUudnNShRGU9BrbbpvSyO94UOUbqMg+SsnzLsiR8FWnQeQzHCcZncCF0WLk9gw2hgcTsvKPotYKegoryJkDbuuNZCUhiB/LAq6ILBUtmIoJElDokcWTQMGOEBAmooYpIsgr6XhacJ7xT0t/oF8ZEGvYgqfA4SQ/+fE4FDeVoZG15poM7kpsDoMw1vQOTgS3eHfvQzm8MbD/8w+/ZAKy6vzszrgD++tfv8PbDPxwP23uUah6R8j/8INuLCoA+78hfEnb4EEk8OvYP7WjK7o4jNmbfgtU+3yh+D2NPIdu+kkSAt59+wekvSvt+0khafc5qz3umALOn6G8rX3tVANz0eTJ+GgB+huOX5uaO4MFlTuVCM8AqNu8Mkw1pGrn0IiBqdooa3GxrYTDhtm0idxXZ/0P50dCPa5bbsuLaGsgqhxt6hMrsw/SIwtTlaF7L8XSuBLy9iw6pVrTtFwz6gvPpBS+fXnCuC8bnG1CA9XLBOA20W8PAwI0K3q5X4HSRslFMuPUb2hjqnCKdMitBLsU59JrgUpmNF13LysDTf/0F73+T/dSU6vz0//0g66prffmPP2H7+08YJFkkqr0n0WrhYQIumIFOARdPy1/R8KPviSj/Ks9YcOkJhBvYDf1xxEqa7EeAOy05f2v4T+n/cdmko+P+auwnf/N03q+mjTdZQ0bmFd1dEzUFgvGU8kV5UMPoRkotiwBZI3JtOIfAUBu3YGsCLKO00MnimXFbb0JH69CgwoTGldckpMAm3cPn0xmniwRGDh54f3/HZnoF1wsUva5rm3RAnKb4a7j5K1zVP/34J0Wg2286+J3vxf0M/Zr5oMQw75ubGJJAjsVBB06ZjXkgFsKQo5gd5abuH8joynTn+x4PxBD+tNlYHxxD+VYO5RuC2VR8PY3XNh4QffC+6/NmgCclGnyVFk6fVvCfGOPVomXP2F5fsb68OMCzphoUwW4FBmN7be5d5Y4MpAwDFU24R9qn2A3+fZiRDaAq6dWtXqUZOK2G0FIr1rViXVesyyKM8kZYULHUVdJfUkFTYZGo4HxacDqdcFpP2FrD7XpFH11SU2qftHewiBYjJnpWkAkTyjM5w8/MoD68PnVFxbKo4VUjciQNXYEErpB6RUvbpMrJhQi9kKRvVDgOTyBNC89Sk7GPgYXFUGrML6uAmgVJwGplDpjLhSteEIpQMkQ+CNC0lIyCATVom+e/rpO1M5zpgLZ/RgHh9LTg9np1ePT9oGcqLiB6UzhXYOULckI01ha5sBM7yRSghjBAkT2h0jMG3RTRJsFfN0Y2okOjxs3APEhSphao0lrhbi0VSwnjedU1a32gtSapw8ZAN0Er7W/HfMxoY4DQMUiE9L2ywdKNFSooC7BtqvwncVJY1hVLrTgtFc9Pz3h+ekZrDcwDrWkdTSWSlTSbQrXxiLezdGqgtQ2ljYADS41oa7gzcBkjBwBcgFJalLvYfeoDunYqlJkSTtty77KEOyk9++Fvn1P7skOrhnImUkJhdNV5rxCDOZMonkbvqKpwFyVEBZMK3kOELxRGIwcVLQAAIABJREFU71Kr2xg/owGlqPBt6SVteFr/dcoOmnB27nr+xQxXvA+2vabERGmR4Q/LxAF9X9GSFFkBQiwKaItKnPyrmOf1s3nX+qTw3obhxd4rNMQMI1Xr4wDZWceUjUVVAwPwPmEAp8sZr1++GDcoeMcdPMjnzIRoI2DMSO+GrGeTWlB22w6SfWgEmuDcmES//lV+Y65y8xFDlyheos/hOUsXQr/yXX/p7v/5Wnk2Jz9gvOmCXggkSTlkbp6SAu1d8TjB96i35vvQjFAFoqNWRfCi0aVqSIHBVFLIQI0A4xpGtEN8YhBPx7OWBVbp20eLkcWFGTaNr/F94O+k1Ac4/csyuO/t1E3rz/63Zfmw+01JxvpfoWiE8vNk8KvPG1zinku2F05oJN8TL/xgrr7tuOdj+a5ZxwsJiWV8driyDy/Ei49woglVeT72e9eFQEB5HzNDJiZesZjwomrY0UjvpYrS1GptMw1Nk6nDL4uujfE6RWtxDzcgiBDKM7yqBC4pMNXorbiHIXi3lopaF+1XwF8M2BSPrHVyAY+MtvTGNk/GJ5mRSRWqAyzR3K3hers635KdEBizgcvq/A5mdzClUjwTFwGopCm5DaYtYqIU0FLBo0hacoVtNwxTFtyHpC9XnlKM5915h0KS2UccCYR+dXX5tNkxD6+iodikERBFV0tZKedFCOwpAPvW8M7CaC9bw7qesCwVZRExmHXueu/YRpN07n2owy7dwZTMA/uEGG29vV1R1YBNp4KyVqADo7OkjzcNUBH4UosiLN1qAaHUBVTFqbIQpDa7K/gFQosZ9XiAe/O9IFH25vwYdIVUGU+qBASH+tBx6CL0jrcNW9uAQjhdTmpAV/WpZmEiNRrWQrg8PeFJ/87nE07rGeu6YjmtuL294XQ+gZlx+9LAy5CyCkXnfEh6/a1tUgO9d/Rk3LJU8eJbQqrgs60404OP8OIdbbXNt8NX1u5hC8khbWqUvUGEU96Mp01ecSEO2PX9gBeY8IS9k6J/BwxDZCN6gMzhmoTA58a7s+LYSNQBc8aIP1P8wh1/rK+WghLq9NOUt+wImZkWw1tS27MsVWsQa0aEUkBVPsV4TjDjCRNjOO7p4EHuDBukQiKrBMZHApY0EYTgQcFK32QyBpLBGYyBrik2DdaUljs/rjioxLpZinav2Z7ezTzCcJbe65zajikgYnXuF2V+doCy/QylG8Lzx/qLcwBDOqJyBsSQLuXjTM+qMhyZ4SuPn5PxXOWIzNtRxHXZcL3EWhugtaANcbIRowGjXlbP7GbqEdOvyJYMB/nEwsFTgiKU0TZVNi3mwOYzTtM0m2ilnzwZD50XxPGhM/3gqrVy8PMjfshvYw/TNOdeL8NB5LKo8yBB9aKFNBZZl3Ry98YRXwFYpjWoSKhGYMr8uU5kga/7JOLv4Ta4uGlWIkNjwlNseEUhSNfq9HTWFsQprFTCuq4S9EASXLHdJDjjdD4nehwmWsNvlQhiyB94ebmgtQ2jdyynk9NWi6+xDBkiS2tCcULiveW3JNEgdcwQmcCMU2JQI6CQ6GzUoDGpUHTt7H/S2bIMfFbmpxbBaS4DjeH7FlDazByR1hZ0gjCYC9+XlpzvQcNX5ABksiSZ6ddkWlfDW9ZRf23HEPaRqJj4ksC60bfgxeVYANz+8QssrxAD+PsP//AU4fk9+7581Lfff1DQUgQeyo5zceWxgf3w9+TEa9cPEM1e//GNxwlhQM/PJjLrpLT/HPjZ1tKcbuyZDIemB2c4yvPvQKRIz8+U3VjyeO90PEAAod527/Q0r/wEY1Aargs2IHIEJZwX8hQ7LiwLYR1SXmmwOTnt+pTmzXyQvAQiWPWLFStJINX4zMDoqH9hLMx4Pl1w/q/vwK9XnF7OGG2g1SZp2ZcNZyoonXEbHa0PFCx4b01p3dD3xgZiJaRD8Yc5ZjOANwCfBtAJrkcHBM9dARQWfcoGxgrg+vef0Ej19Lpm5XsAPxjpyHRMgjsJQGN2vcj1f/+o80tYAK+BnqGfIUb8OV+JHM8s+/yXtOcqcMcv3C/8nk/8lUcAzK6n+Xf+ddeT6JDh1z1vQvvnCKbzCPi16PV5PN6W2yQ0GwGb80dx2RtgtN5xvb1jlFUcwWFlkBHzZQ2zfDIY67ri06dPIsu1huv1KiWn1RZmNhZzOgfm/bubiaOpm3DQ/00jetIO7wfwO3/f5Qd6gLq/kcE8mqNJ38oHG+NBA4bUWBddFAlDhLEEiHnTWkICQfKxZBbvt0C8bTYdS0UBCtAtxa8O0k0glAUCiQgmEG69hyKWgVEyWxEe09Ua4dg0ANQrBGkmMse0ojxJ+vXlUiS9EIkhZHkm9M8dy0sF0Qv4XRoemobZolkKFTAxbppSe+EnN7yWS0G/vsMq2/DUA566EyNCzAlkPWRowqCXUrC8rKhdFY+8AINRaURkhEbgkhvhxdh+PqkiZ9uCiXKlnhEC0kjhrpEwQxWKln5aie67xbYp+nopIbj2ga5hqLxo5O4Xeb48S6YAfgfGIvdik2ioCkJ9rhifB0YRZmgo4jMYGFQkxfJ7jvRj316M+2g0n02amR53omCAPpU7u4bPO4D+S9dxEvgLg15UTf3lWZdJBJ2BjvH6PjVC0QxoiDBd6KLCtRn8Zy7YYsIFTX+CqhjQ8Qo2+CIC0U0Mn8lS6fIyCdOWsxhoCJrvvKqKPy8LUCtKqSi4oOKCzkAbA7jdUEfHAGFrDdw74DUnVYzhoR6WQ4i8plmd5XfbjYpRFEk1q7EJEpinAkJB1f4zi6f16XzGsixo2waGRB6PLv0Yg9WgrnNTwnFiQGpajmSIlVqd2qfCGlVVQukV3fWvwazIEQyLjWva3XE8pGl7oKOjsw+PB3R27rdaRgliOBGpiRXupFajG1ZJ8IYpKyrTpCAn9ZY3Qi+K7sC4o3cs6+L+T5PRjecOZ2Me96Ahw+r8sX0qTvR1SaxRVpwya1p/UxbaK9W7rw83vps3r/0upWB0S4Xr/A9EyTbm9dD+eH0nhe9aqyscmI0+CGNUlwXcmo/n9vamc+Lxgx4pZOUJbGxdjUXCZJkjEU/z3lsDKa2cWFQyks7fDlQAzGOYqcv3R/BL8w+TQzLv4ZEFMJxLroiKbDDaAt8zj/VldWNUqSryj+FOboBGQT7Hd7uvdzVu+Evu+bKJ/+ABiyqdHDSG4Aczqk3cBAF8Yzcc21vobsK/gbE9wJWPngvsld9pZ/bjtCbn8QqlyRhs6gqOejPdE6Q13p/2RH42R5zvr919T9van6HUfrr41WimuccPRvLg+FZ+/NtvRMZf4lyYFCvGjzkupnQ+RZ57LceslAmEm7PLCB+g6n+NznU4VUMHo4C4a8SVUDmC4kkijKKG394Q4qmOxr8azlUaOEgYHgYssjDSGEP5gzbtd8nE0WH5BtmeVRxmpWPEoTPNNbsIrAYl9nTszAO9N43klTToZnD3PumnPWNGdDvv+JPhY2R11SeIgRcQww6IJY33kEhSdMmOUlAchllrlxIA9vqeqqTmDu6MUYpg4S5DFfuX1PwsRWsAUkUtCg86RzwshWkXg81uXaQvqnhuwtPhdtMpXFAh6cypFCyL4ULheQZ1EEdUldCXaD/XCuWto64Vi8JtlMQwuUFTMxJ7OjvZ0kqjYSUGwuFzxnWkkBgKKPuz0jHFFXzWx8CpZMSbhf5L5KpvpgArHWNnMVZSE4N20WLsvXfPHLBeLl5myAxS1/crRh+4vr9N7fLo2FoHvUrNSioF2/WG63XD1iyl/xDeVfGBbIjM8wR8EgC3vj067iwBPJ/foa9H2Iz31/bPJcSdt+k+CxM7Y/jBi/L1QJTpJ/u4czf8qbB67ZrRCbR9nTb4/hHna0rgsrt8kvrW6IMjC8ezIvuRGsXVeVk/a1Uln++pAcscwkYXStVuKt5h6ZywzCRyepmj+sNR1DC3jm8A5lFKauky6ii12RVOE/1le4/j5pJoWEn0y9ZDo7uGtazzUeV9UL6qLsVhmJlAmqVsBlc1KIMQxpKgDb6k5GbuBAU8/ZkRijelESrR2dWR5y+Tmf1y+/7B9LbdVRO5wMTo2wCtYkQsmuloXVdgBd7fr8rrhssaG1TN2356r2UEEfpOiuPl5pI6JfRc5rywBIMM2wOGUQ1W2LILkM/vnjd/xHn5chzihYNxzHcBO/ruX43OW38MAwz2vXPYH6heaG9wsvk7EKRnHMfqBEHudOpRlGxQbkBjPJgOwynVCHyh8/1/yPvS7cZxJc0vAqRk51Jb9znz/q83M11rpm2JAGJ+xIIARdnOuvd23ephHqckLiCWQOzLZODPLw6wHfqcx89aB7htW9Q4XlfVA37542lqRTP1aWPbdQs+htIr/FjXVeVHQMuJJF7H6btYpjad6xZyKIw3IBHDUaLZZiiC9111aXoFK3cClRU1Y53uQY+WH3A+DKhkUTWttVjP4NOQcV0aHyH0cpImdox9xtSOV2+BaE9Vjq47Ye/xtvHIuB5wQqmjNCKZp8cAc3ZUo9kVAEjAMgwVZXd/7m217wUqGl8AXO3co1330TQAn77/jOff/gAArKLRrBleuuGSezzB68dETd+4/hom3X8/upYxi0Be6fFrLR39XkUj0bNp0HvbaWQeadB18tDzVcbcCQ2HiP2suONJYRrOXKCgZhbnh7PotRZ72v53nVHyksg0K6A3gOUGWqddMaCdEv4gNHP2AgrE9zFgJT6bBSIwrtfNsuTMOHCwsDQSa5IFtDFZECABTVCWgoULTqVgPZ3Q1g3XBnx8/IDHckIRwsO6Ah81Tbzqn5WfeDitWAth2zZwJVzNzLwZDu9BVm1kLGCTPS0uwuZVPx9s3hcCrr/8gWbOlCyqRymkmrMrRG1fooZ012F26Wg/Dwh1Zzzdp2MtitGST//rP3D9P7/EeXMtjij0vOcdDglqNH8i/VygOOD7bnpr2XFF+cdY+kNMd48P2B8D49HNeYXn+ezMLyiADF5kwPWc5Q4HAJ2/j3MteOB449DXOTsJ/6Mo+6YT0cCdwNRRST/ZSnGG7kx8t0jit70bw8EyMtBlPc9Bz/+7j9Al38iH33YYXfpzJOL9x54g78+/bxCJbB+2fDSK/XUn6/7e8Poz4Ml6o/f0I39KPnH32LGpzrTt+yqD9yUx5dXBtdyn/AaPzXP/VMIKAqE9W5RIschMNEREHgj92ZQXJo00Mxr2F8BrodMHUtek9A5+yAbZbdrSN1OSsNjhNSA2GxNhKQUsZkju3ZwELN0sl0iPXwgQi+J9eHjAw/mM03rGVgbbxZYmPgxJpJEztTds24ZmESitmRD1oJ0Mg6sxCK7cIgAw5WMTV9oOg48LZJomlyDd6rEb4QzEIggkmg8NtGE1KMd2kWBM9h6IoTwjj5hDSmPi70mwhfnzNcgnGg4H5JFWxoAz1HOOMmUwiYqh9W38HTkVyF6PlR0bvDfEjwBeLA29w4UZCbsJ0EaIxqcrYNQoHW2Hot6Ru6Y/XT6s6BVA1bTTvTVw1QiIakbrSPvm/VVJypQsEkJtyCRTOHLGdR4BrkyPjiXBkxBAGil3Pp1R66Z7EGqw1Yh0TTHYmu7JrpMGQg+nHoUdimgznSuLNvV55GEsBjylym2ULA5+v3W8hY//zPn7v5PRUBQi1UvdlNOesYFoeHeneptiXIWz0FNtFhqed24QCNZPzCkmlOUzhbntrXNzeyqzI+iE8bsHirZx7syFNLdF1i9K36ceCCBdDdcwT3YX/sX6tvcsD0geiAc9UkcSAIY5wcMVUcuyhHIMSaEZbGUwMWMoYfAyyuUG/jFUCgZNjTy3CnTf++7NPD37xkGHon2+PlLk992cZxyaf/ODdoOJIA/qTIXpfv3OHzTJHGHApuPbqIsYzwkoNL0ARNRh4poaTcR3b2B28Y6NTkSEpaR5ykaKZswyBuwTdGn7vm0ab5nVN7v7+N56ZFyZz83cxJH+8Hact98Gnbi9cv+3w+x4h69xPudtx2/HF0Fwb90M9jt67LXdTr8zXW6oO7hw/6H9bUdtvuO4e9/d8wieB7l3ScDy+Qoai915+25ByEjYGE7i4fiMFPdrxJ/hHzLsQlbyRlkZhS7ZRYEE3rrBsPYySXReDfW+S1ztPAyfiEhyVaQIOnd0i4tRw0ZyM7R63ALlJznCh8RwILTEguXi6xbR7VHnvWkacneAiV1l/Cns043Q+Xscxnc4VnS+O49feQlGOS/aJ1aexrNadJiSyYQdFqWB3SLr1ZFLI73V2KVrHKn1SCNVl2VBsXJJxaKhpTW0raLViroRGm9A90gssqhWNZzU7oZrQm2b8bGa+ad0T8NMoIXAFsCmmTfEiabNmyrFxMrzwHl9AFI9w41lFCIOfOAZqjwsNfDIxFhoXcPWmzpbuPGf3Ngozt6jMKE2cTYUjsDdHJ+PzCFMO9OA3baRQqkQqkXhN1EHByqMDx8/B6/RXrREUQkkCDy/vEAAPJ4f0ZrWghc4nOk616qGkN6cpza5yxxFunWEzCiasOrNOMYYDgRiOz9RDMc5IrPYlCflTVXE6NTUo/x+2d0/XXinwkYQkWuZdsRCHfR7GsLhRL1+7CnsICsS0Oo5PxwBaxaC1GEAYX0Hg1ki6oSJQIUidftwB0c4jFMaYxirSfm8xVK5g3vad+qQEqWoRLQcXdIQKrqZZevIrGV/PX/afpzi7ongGmYtZcDhiM1+3giPGxtGpPiYM4/KG/31d/m82VoSwbNy9NROrKlHuxt9yg4DCdH7F0hVvUkoPYlhFVCNz1YyNlK45yj8aAXpLa8CUrcu6z5r6BbKyIumpR7AlvmATGElLmednNPovJYBkz6Fac9Meo68/zGmKbZK8BLukLQbVsgr37ix7PhzTx21I7vfe874T7zPQd0eGhJY5uEVTrgLxGU9pMwPwThx0PHcCUrwnXubjcEOxhEVWRuu1wqIlQ1jQqsjuvzhfLZnFSau120akqRrAt3CTDqicjoPWdNpeBhMXE9l14oOWFoPecmH1oCk67NoVTIZOphQw1ndosth2e6mniLevSdHPfZ3mq+YP9vTu72a7xkz/h5Cd5dbSMdtywCG/i+uuGNM7tVxKy7Je4IeTwvdSOCp4pfd83vq6p8E4Awtx/qQ2s97vic+92iUGyTlP/qTx83Djsxkvi6769/U/muz+u29P6fHr+94PGDUWVgA/MNn3f+/fdEoV7rtJWMiea8ew3FagtMQJN7oHf17DZJv4UjGMgXPJcFqxh4VWDZG3e9c2LJFOf7MLJviMIFn0Jp1kAtrcGIpmqlsKQWndUVbTqAiuD5d8NOnz/j08REnXkBNo33BaugUmEG/VpyXxd6vwYErqQrnQprNdYGggrAwqeOJAOQ+QmkxZsNviMrG/pkc/h/fAf/1a+zZeZ7VGcL3dgFZ+nebYdJsGetP3wE//w4YV7L+9L0G+XQNAqL/WwH8cdMfj2ZnAJ9k9JFAWKGOHYmLm3jcPVz8Y7bU/IZvfc6PIyq+v+c9bdwesax0e0uwyqJzj87opA7p1IFOrAzdLsB+dlS1ttJ+dPsLMVuADzCkXqNbwTP8PY89Pfrrjn/xHLrau5jhs0q1V6ro5AY5CbX7vL1cWR6GVLvqgpgTmsU2UaToSq0c0U2tcUjGNBBWGrISAGx1MyV3if4LJ6a15zfox0ASMhhCQzNMBH5UCad/7Tj9oOxFk4byuUCeVDmkBnFCf/KIgJF2oX5tKHwyxY4az9tLR6MLFjoBqDdbPmYsZDxlON2YF9fIew6ANJVJYdY6j0XQ5ArCCqIKMIF5DUQutlGXUnA6nbAsSoS6EbhlWQAilFIijQSTKouW1tSDjDfIVSwFizK88qKRnotFKxMRuBMWXlBkxYpVPc7PKu213kOp0F4Ews1qCjJoWZXIXSvoAvBmBkzpaKasc1UFmWdrN5aBAKuD5mwpkvAiCUPeTP7wgPtIEHPeveE9BJAvMgmgeLJLFoUeisKUgJ1xQqerRsCYkOXGnWYvZrCm8cvMNgB8YODJk+YlOLEMB6qsvaDQR32CAaIrmAxu8YyQ/q1NR9wgVT4O46dzeLYXeGQsaJcXyFrAnVGrGqGZNeV78/TpTb1ti9ebEmDBCZ06XqCTWmwZFpzR6QoP8mkO4rYOXkvHHWMKa3S8ZoaVUJ4AGqEsGNFiEJjCcSjHBQCL7VnS+WZX5EobOi24QFlA5jwQuE88UsO9ym5BKafWetcRaOkfYSy+5Sld44jecsbbOF+vOe9CsAtRpRjrZ5MZ4qckpjnOjREtyxL1x/01QIBYvj2NS6yumhtUdlHoZDs8rltNtDQnQ2cs6TsSzaGkwBgEZfTFHT0Uz6gewaPMzdnA58/OeducHX8iz58yXq1puQHUxA6aAn1Z1uh/N4NwF1hJPLFsJ4r7IgWvKSbKomn7XBlyuVxMYMgCigtVt2nF3ag2IlF9ll43mI/D8YtDQY/3hgEjXR9mdsPhLwJ6NFr3IJDLWC+6ad1wmKVSQu/Ay8656mXwKOUTR3Q6P1j/LjOCn56dDGBITGxAOLJtmxIMMNSZi04EXAmCFn3Xe2clyYjMmvezpu9967jlIu7+ooN3+BonZVc+/21H5geTc8lrbdHNl2jpnuCfT9N0nm6+R5QwHd+XG3kP/p2ezRO2z1Ai820Jml5pV+90b2TsxuMRp1H3PPc9GSHcgEt5TNP4B93P0e1qkCV4eRrylHlufPE97G15xg4ZaQU9KvL2cFpJyfknKMIYi0W/Od8pQuiN0LmjkipdiimKvS3nBfaytcAUgGRKjaZ1o6s52MWn8QwkI4MH3FgORNT54C3mXTmy+8RixOK4M1NhzyaC2IeRCQBKLwqv4FKUztr4Sm8oTaPlY3ysPD+bA69AQGVBYeXfl9OC07LifDqH8H592fDy9BWoVeuWVy2jQ4A5F3DUrxcjyEIMtIpt87F1FKwRIcmFsdCiKqgmEIuSJ2j06/nTB42ev1yCGEv3yPsCL6MkYPSmEynCJhcsKH1LcO/Ay+AiloFFnTfNpp+clCj2gwAKx61bxBqidIdGzblxj4ZoZbACIOg/cGvs8Ig7kY7aG1hEHTlhipbelC/tHX98+QOnVWugX/kKuhL4zLi8vFjEkBvQG65bhVw6+KzlZ3rraFXhVkwuVAfjAeeEDJZDDtcUhTaWvletDX7FZcn0OLJxXfJ5v7YnTpmGiLMSCfN5JgKLxO9Ry9gzmR3QC8l6BhiiEXj5AkpIMKTi7DBImd8cNGGg6ISs7yLn/Y87VPng+SnyOpf98msMiAx867KzIgkOOAYRiLVEmeMago9f8pJhPZ+Vd9w2491tFQe6RVjislE5Xfa2fL6UrxGtwcvq8NO6M3YWSd8ZzK46VgcAJraMfCq/Zadbdp7YgTdKoZmMzxqdqg5LDCoKy1oZyvZkT01kSCEyZ6O8Drs9ImneNuP9ieAl3yB9bhO3K/8KNIx79vKNkxh7cHDXKnO2rQIo2F6uWM4LejWns2BF7a1p6hDnAS7mkGT4isQzaun13odj6eDYjI+msT/mvScBc2JO5oEudtbKcNy9nYlXecF785h3d0zhvp1E+/cmyKmGaHIKcf1aHowbgw45mKyYFJUJFUwsoxWJ0i+YxrQN2WzwPzBZVvfljA8MZ8dr0p403kFMVnr89FEd+rZNa58b71KK6mwUhmTq97Zt8V0y7Bse8HrmI+OawVPQRo8MVeeuwEFsziXWBjNBxKFaU02zzT+VAmkNCxdsknSvRJb9YuhV3Cnapzzoi73LmZdmJSc9JXs3R0lf5z2OCweZHb0cY3b+WtLVP3/4Ct9vZ3eHdcGj8sXwrkcfE26Ndrklv8cPd6VwSrAAOP34HbZffsf6/WfQb39AoJGoBSNV/Pm7j7k7uO7SHfsxU4//P46M9wVqUPd5CvHI0E0qOa732957+e0PMBEefvwOLF8U/n7bOTQCoO8JzJ9w+fUPO0G4kOCzfEZHxwVfAAAX2u8Vh9+Zr4tIWwx+F/EMRobeHbKdbrUzGStrRk/g8XxSXrZbpjFmkPGe3Rxqv/v0CV++fA06NGsfXK/LKIvx50woVABidQ42fmn9WFBfNvCyYBXBsi7Ynl5Qvv8ep/Wkhk0w1vMS885MoBfGpw+P+PIsqCJYijocswhWdJNKCJrJR9OkdyIr0Tuczd1B/YUIi2gddPHgGZsf/g/VAZY0i84PiAiqwYk7Yb+QvntNU0Ig1J9/BwB8+d8/qx7859/B//mDOgiIQH5iAN8DP/82wZB/X6CGeTfTCgQbdAyRGdp+fz3iZTHD5QwLiT7uDtn9us1vcOe5eNnYbZMe9zVm4k5HnE+87cM4Qk9pr1XLi9stlT516aiiNJEWRmeVA1UocVuVOYDZPpj7Ipr1jlxfo/rrwWN849j+hcc/6hT572NA/xceeXPcJfiSBZB77SSGEANRvE1hj0HaifM/Ak4zmr+HBM5Qr9AOQkF/sQjp9LxYajF+HCnKIF4ly+bwgbQeR/Re/S2vL9dJST2Na4+ZEjFWxpOjdEQuLwSoMLtw0eiTvoBLB5qmjiQmFHrQdMzGdBKpILosi9bfWxZNf12rpoK3CJZiijw2z/hatVaDj6F3jeQhEbSXyFFsxvnF2rL21hVrWdSQtJoSrTW0MtZHp1O0riE1lFZUmbgUVLHq443giWsoBDpVULjX107lc4v0E/Kd4WGGCjeEv/fgT4z+pQfiG4KuLiIJg+QMwQsI56ilBcCibpQ5daNSZvXpWWBaztRTRviN0iVGy26swwOcZXNXAtOHh3LaPz1DwTRJpkhfuJhQtphCRAlvr32kjDHD0bW2UR+UPE28gLuPz4Qjc73vcok58tRS9rDpoG1teTgizPtElZOhLMiXEsF1ZahOm84lgyCsqU/J8gVlt6Dw1jfixoVDiKUudwWYv8sRimloLXMCtLaq7yn26BGt7Rpp2oMLd6O7MyTjnMMYgGGTqcLoAAAgAElEQVQ8BoUBmMvIkiDAkCy8bzCnCVvXiHh0600KznCNBxECP2eDcK5p7worxwm3qYfGrk2iCPQ1rtjDDIPp5/AAtj3scMypfSs94WUUoqMQ9ArUeo3IQbIs6cXu8do7vTU4+iB/HEBMtb/NUzbG212ZQ0HIs4J2GpN3zQqzvO8YRjsCUB5P01UG0Kw+OZ1tji4NHkbGj5jnlsYHPbA6U4UxRd/E4bZ9gK/Tz/4k+yGCHmbDtQDAJSm1ApdTtJ/fEXCe59yMFm4AFZUgb7ibYEqnmUuwaJvLlVf/yHEbJbT/bRRletctTLz/hT42GkuF/CWvIcZ3mp/XszMFH0uzh9e8Zjv4pnv35S7QdPr14d1MoE3X3M+JVCGhuTt9d8NJeCXf3DdHnCLux/HzABzypmhSx6vu5BPwrXSRhIInUVylmY3EorhVd2l0UnJEHnTeC2HsqTmCpUtCoEE7dtk8XIHKUMMnNM1dF7a6f2YEiGX2wUl6fvxBoMZMsYw0vUUUem3N6nhqVh33AhdP1040Gc73e1G3aR+8CZkgjeVgXdPuEs/Ion+asnhFMedWL7vkKeZ7XzQNvTtbmiNsGHVJ53JZVjw8nLCWEx7PD1HOCh3YXjRWSFzB7I5xIIB1bC3PHXWAFvStwjlTAZlDXFG+aGGoKb5DmqgTpCm3exeLoB5Sj4iMuvHlBF4005RALDsRBYy7k4E7ZMPxr9Ni8ih+NiP5PiIm74uxXgIZRq0EM6ExyT8xShvIaBAuDHs5gPP5E8CMpy9f4Ub1zUoEXK4vIGJUruBnBjcGrbpuT09fUVuHRu439Nax1aYG9FqMr1EnEOdju3j6dpfpbFyv4C53WklnjmXy6ZxLDv6ZbnkDT1LMUz4z2hgwcfv6TK9kfzE4Mwn+UUHCs4ntOrYHhtTo3CN/+SsD+pOEOOQTQpoTClKl8GylCdx5iWByv8N9aidwfKY3bngTaw/mZCTheKplOaBlCd57hKFK36GZKnxvsqY3ZUITBnEHRPlFtvIUHj1WUpaJQZ5p5v0ZoC4oxEo1+kgrxdzVw9rkYDL4jbIk3lWSkcU9M8nJ4cPphgCqNRaJeQ0c77zbnziOQGWiUDs4y/daoUTIpmaX67WNW8X3uJsAj947G2V1KPo7MuPB8cbApwLBxKWGLDP6SDCn3XhTsD4hFw2nclvneaiv77G3jqP2vM2j76OXAcevvf7dXduvXxjlCUQerb17RDCdI/KGhgTgbWlXeUKEzscsa8H6+IBeq5ZFbBWtizngsRqQLjnFFlBOKoddr9epv6PdW0ii/I3I8C2CbHBhoBOenp8Bd3KxlMznx/MIWhBCJ9U7MrPyVBapXqigowVujD2IsW79dkEPFiPP8wyjeY4JI8jrZn383BG9+IuOHdcRxz2s5CPe914wnHROAPjzR4gI1h+/g/SOF6iRd2gY9Zn2+1eUZES/d3R7sYcvnIXCmPs/8XBjueTfhi9nfYt90vg9s1euS/8Coo9KH3/4iv6rgH/4BJGvAADmTzfwegoL+NOxPArc0oH0Je+OI3jBwfnbI+m7rDEyEs3deDMvj2h7HiJYipaWWrmguTw5sYpD/h3lJM2eQBYsWBgPzMBWsBS2ABOglAW8LGh1A51WLGwGTVDIS8QF5/MZm1Q8yAOuvWOpyquU7tlYzfhNg0chsbKfLEBL/LYAD4lbmHRwAIDPEBEsPzHkF3NGJI12J2dczMHaZaNOmd56kBxNmc74p+/s/WbUNcN5PvgnoP+s+Ftr1GuvXJPr688JOr/8A7zuv/r4Z2DmKSHewTVfEud7b0iQO/lDnUY6NUgpSdMx01d1KNy1AdNhmBMwm1N8jzIoo5W9E+ff7fjbGNAzo/3q9d3vvYq2ilYtHhtMIamZyUzinzFTu0adKXOPt1B62181j82F9byn3glZzRWwPQEihnGx9R6puYmUcUzJnSGwyABH7+55n9IwEwCy2jlsmnsH025RwGRC1PUP9c1ZPs51X7cnjQohFpSHBf3S0V4arvQCUMcKzUtLwljoPJSZVnXG5Ywk4yVBy1LHhkDtjKxtfiIsrCnblk8LlrJg5RXEGyDquU04h5JUjVaAlA5uDBRG6w1UVaC+Xq/YNk3ZKCF8u9DMKMuia9cqSi0RmSxd0M0NnJhwWheczw+qCFxXnNYVvGpqSSY1nm/SULGBTyUM8bD6EQsz5JHRT4J+XSGroP3e0URTZnBjEwIJeADoSYkPdfakWBim3ZDUx6Kb1KeOCQYHH8ygZx5lw/Nf75eoB26M0icCnuxZS6MIkEauAxFFWZ++AjhBK58ICk5gekTbKbM4dU7ru3vKdQ/PVahZPqpStn5pBptu0HlEPryfsUtzlC+gHsOgkT5UxFLX2RhtmyympFmWBaUsocDxmr8Axfo1EUhvoN4jLTozg2XFlV7QpaqXlefBIWBLczw+XJ2uA1GYSRhGnCh19E54ebniy9cvaLVi27zEwIZtq5H+NPaNcWrhPMAc3o1s42VT3jCTpVVRxZbLmdIRSulRcy3PfKa5b5A9w4ezqmJ/w9tN3N62Z6jvPS0xDzcGPHjEOSJyKXCIjTvm1vUTrujLWMyEUpFu3uvGzFoNR0d8lNqd9CGiKZ9abRZdDZAkowyNPqvQTuCFkj5cZpnYQc6M7dMLCbOx0fsjuW85snYYVMWUGEhML0yp4J0hAGDC6eEEEaBuW0SZuwIkBiWa0aN3rR0lqT/sv7s77CjEbeaJjx1cRjSeRfh4auLs0JUPCoGBZ/i6ufkYcpfHMt3jAltrXTOQ5DaDZguWRelrs3VcPhXULxV4sDYe03oRwlnCnXPo4R5XPKJvgtjuhU4Y8/zAkKvNX4YZf4bm7TSTl53X99XmPiuskpIISGYphyOfsnRfRELs+3yDfw6HHm1HzWm/diBoUwx8lhzy0t+uuqSH0xRPnXsbl930e9fgwZLd9D/elHH+/r60BNN7XuvP/ZeP7weah9mlZncIDlP037Et4b66w9YqhxUYve8YlwfaYni2JLI04sX+2JQRCpM6bnUrTa8Q9cofS7uDQ0VWIR/omGTCi0hPSKSfNDxpxhbfb2pctWwyRCBqQZvIgIzth0ctQqsqmaDq0Q8dvVWtTd07Wq0jjTuMTQqju/a/N5N5dosSMEYU2Z00S4mnTEb8eT+CFkJC4CbLgAMu4dRazHG0LIviQ+mQ3tAa4Cnr3bHVs+PU3tF6xXJaQvkk0tHN8fV6uaC1ito2bL0BtQKJjrqI5DTZUy6LAOCCy8szaq0o2xXresISzrfKdbe6oTfNQCSw9Pi1Rn3SVqtGiTd1uFgXha/WjakS9fPX+oMEFAb4BJjsIc1cLMNoDXC36LaiCjWNWGMI9cjU4rRSnSMU3tbTauml2fi5pmsmgpz2o4f8GSeM/1X1SXO+iEvQ7NarPicyIv5Isx1Jb2i9YduuKGUBFuB6uQDEGtFQN0jvqE3pOF81K1iTPhxdvEuWkcbhCYn2+IaXMP6nfedC5hGOyXRqOj27i1KC5YkgJkZrR2mg+ISneb3tgvGVMv+eLouE7CZw3YLxAcFOaj9GOmTFK3ME6aC1b7Hp+64Eyn/PcwBcS6a4IRhTv2j7dcj56h6enO8yI+I8c2hdAvu4aGsOF4KQLcj4/MJWo/SNgZqxTp0TDZ8SQaiAqWmWNOO/WPS8ZtiwjCBw+cqcj7kAlsFp8KQ+lJFJDxAQi6WfVoW3RrEZPWCna4ozOzRVdHfZNRnxMg10WuTORrFs2+BU9ipKQQvaEg68eD+4HN4nu61iR1Qdsf99n7CFBDc0OPF91S4ltt6mL4jMB+TvkYHTjK5mHslTsuv6jZHMUcsStFnLG6a+7zeUf/i+NNlpz99ktuz4MB6qaCYRX0PnnbwX5JF/PkTnb/0lIqMz9pzLrRNnleBmwiNpLvw3eTk6WO1hckcen7PbcYy+ZWeHPZ/qKnoE3qNCKOuKXhsggpeXy3hGhnwOAi4XjUD/8PkzAOD5yxfrj8z8TO6g6f7m8Y294fvBeevLy7NtM/29LgUepKPylo+gJ15Tx1N7QynAQieQ0WWvZMalYBGVZ6M8VwKrgGfLOlgKq5+bZ6iLNcm7X/dZGDMEacopnTiAwm/F9994jOaPeXvCiBKt0LTpGR8tMu8pwqyTf0jfGwD88RVVuQM8fP8JI1eA/v1uqRg/C2H77Qsef/gOX379/W7/NwhWegM3/Tse9/r7hjiYL18IeEwSZIYgR4ce0X+TWtv1aL8LgC8a/S/ARgB++5Lu1Mhzd3DwcKmrnZ87d6TTkUjnrl2imW3z865PyLoIAK6fy+/Ytw9QZPv6+vQCAuHzd5/Qa1O5Dcrmu+Pqy+WCpSwoLOrEnOQ/Jg0MFBBOy6IyALPKRcRY2WRWEJYH4LR+APoF/Y+O0gW1N1xeNixyAYHwcDqhk+qVmBlSNyyF8XA6gZjwslVsrWPlFY0FmxSjtT2HRiY+2+YwzeiFgE8AWATlx+/w26+/42xj7T9rhgcP0PL9VmC10S0joRBhc5oM4Nl4uI8/fobIH6g/T6uF+vNvAAjLj4l2AOAfgfaLvm/7WSIDQs5044fG5yuO8XIQH0Rx5RPdxYj/5OMOgo2hjmxgw6pncPonOmfk9BDb6qfJVJkY7l8lgMBKaUoZhncAwgB1ikzJHtg5+ChYadmKQqvSPJP/Wxsys9/773LcBCm+s3N/CwM64RYg3kPQpqS3mZfa/f6WfuxFkSModwF4MN03Xbjb/p87jp90FtvTY3svwlMag/nvXzv4A6E9C8rjIEkERn8ZO5KhjI4fHUpQhi8xHX3czEIYzUm/D8HGDLpFiQq2CvpQsFIBuKExQE3770b44lEavaNRj3QRtVU0abher1o3mmBKSAkhRRlzATBHpYdBwfrJzFjWFefzGeu6Yl1XnM5nlLWoYhZaN7vUhm1jbFuNWtVuSCJiYDOl2MbgjbVGY2cUIQg3cDejLwn4kdGfxRRKCIwThosANMR5diHgA2sWdONwXBERm8nHhvGZwUgI4A/zQjrr0Z/9mSGcuZIu920ISQ4/x95KGXqPDB/Hh0Dk5VgmSOvmSskgYzIMoYU0fftSVElIDKA6Q2SpTHqDNE9YY3NsJQEAi7gJ5ZDPhb1DRhVUHytAmo3AFItZfxTCn6gC5Xq94ukLRW3TWr2madNnobW2mvS0h/xPvROZALLo654UrmQRvyATPG286iT21/uFvQcX0sE3UGJGXDFr6x2wxUOJIjfERX9E/R0QQMNDfdw7GCNfVzIYR3pX4ojGPpAB3xpxzUMHsmP0mUmVJ5zx43xP9IgIaFYrzsc3TY++XBU9I0VxVmKS44bQQcyKEOe72ARRD6RxFy+CKiULL2Cv9apbJTokgKXSGo5hAEzISX2ZvtvjPlF5ROL9plHf1MaVoXgsybzoR7gm94ut8yWM54kTMBxcykE0+weO+9ke6wMLYP10QrPMJxMOIcVNji893f806JsOz1zw3nDqbUwG5TOFgXGPw+bdZbBIWh4CJwGu42rABPbznWhobvGw/+86dfeekSp+7H27sLs/cySy+3Y7b7fvm2GSdmfH+fvvzShh0FXDS5ne5jFQHq2fpnlSaWzcvLf24H2Ptk7n6XZk3gPdzjeNzj+9Rut0PgvpB4fJdUfXTDwzvtqMHt7DvKQMELmDphoqmIumCLaIRwkLh/8xtK4ubD1SRJ+NTW72n9xKgGac2Y/B7yo0p/n1EXURzfzC+gl0LGXHgwJmcHTE7oZ3TwOsadV6a+i1aWS3RaALNOKdTIsrQNQ738+yjpeDzwG0nM3w2rL5sKlT3mikrO7WNwdNErUNacalBcu6Yl3VmK7zqtJJ3zTarHc1JjMbb0wMbg1b0zroxdJAa6o5iQh7rUeO4PW8PxBoOAQIZXGeSA171fgqIcb18oJSC2ptOLUOnDuIThDSVPi96ZyKpSInc1AgEbRaIUzoVUDrok6kzRxBe0O4e3aHfsuIw/P67ph5uAP11fg1sv2dHZAcIPVdsEj3rsa/AEuLHGyjRIq/Y4LRgAn7LF7qRq9v12qp2zWDgTr7CtpGqExgqijmlEknQr1uoFK09nm7QroZEElL34T4EvwqAHa5QXmlMBZEV4eDrni0et/D8f3jzTvvyh00E4pXWr6NiB9N3H00Gfr0VWOdVLHmLtRG4QI/xSTd9v+Vwd6ncmb23YPYvXsDlAZeGs86fGPgMu9apCEeYwQkeOHgYXeItHtGDBue8y29dcAcPWfnEP876D0p7+hjJmZLjc4oHoZV2OqpM0Q4Sj9pBLrT7JRBzfhTPW/dN+dO1z+4swoZfoUwwA3SdT6lm3zomUggln7dRkUJDrCj0cb8Bp8ccrDiDm2iYJg8Vswanf0K/ylV2ZtHn0wuvp+PjK4U/8t0HgFTblwcsCUTz+xyYBi5rRmXp/xGthUTM4pO0czGWh3xTgPaJPX22w7pcl+n6YLa4SUZ9xjz4RyWS/H7TE8Z6w+yfo8rm3U2refU7dYe7aHEaciOJ7Q5JeLhKC4AFcJ6OlnmGMHL80u8k4vDr+D6co0uPn76BBHBy1eNZL3J+uEGPMkaGM9U0HE+P8R4B79m8OF7nIHCnh7ZHfLJWD/yDiqfIh2qnBSwpboPfp5Ujm+pD2RyvQYwqHEuZxHPMxp4cH8x5OWjp3x6JUDj73CMfTogUtL3mevJe0//njEyPrbfsnFvftbPdQuKee3QVNADhk5CmvL9f+BxhO8jwOrgnv2uz+uVD6tiNB135UB96XjZri9H/R2lv3bP3TjO7A5xPuLwUlDZwKpGT8uyYDmteP76ZI52AuGugZO8YOECko5ChK1p2JuIxjmGEw4RFi7gxfTQVLBYwNP58yfN1uWsr/H/XQS9VaA19KXg68sLpFZth9nT+oLLApaOZdHyt7yw8hlQhxzq6niwEbCJYAHhQh1rp+zeFOtexOf4D3z3A+Hy80iFzz8C9AsAYZQfBfhFsQ7/AOBXWxFxHkYm+CmlQOR7bPQbOEIudObdMiO/6L38E1D4B/B/Apf/+wtcmhGowb7dQB1QfgT6z/O5p28nz3/N8eoGeefz7zyCphutNQqOREGguysYobHF0qucf62tgcwphM3O1vsxf/F3Pv4WBvQ/dez48HsGoRDcklCmj9PNc+otnyNnB+MWCkWROXhues9o15n3fWQik9ZBb+RGGEWai7UnWQq1Fm8Inv0xHlW5hAuIHyC4guVsY2naFws87ySQ5yFEeNRMxwWEE4oUNDxjgaDgPMZD5zHPtCWiMyaAJ8nZcLxFyLJ7qIsz5mrMLLxoyvNlQa8b6PwAwgM6VU2/2C8gFDCdNbplWSAC9NpUudZUyQNB1DNXhVvTqNzC6I0gyxLKwvKxYLmqt8xpXVG4KLGCKu8ezmecziczoOsnLRQCGkRQWNBcSUda1xoM8IeC8mHB9lQhF4GY0b+UBUsH4OifAGnd1lrAD2aEfRLgEaBnM+JQC0eAAX+kEeLMwLMpoL4ahDwUU2ZQMES6fjPjQdFfWz8TruSrgB4BeTbRjAjABpaTvicJGdH6A0GeBgNC8b7hHQ3LqNC+WgQMGkBXFIs8D+8mzWIJwXM4CXTnftJYWFTpuNJH4xWeVUiz9fH94dSppzlE0jcooyLg1lHd4YJGDdfCjIaKkzwCvABUQFQh3C3KW2up7V0zPSpcBV1ToJCRJlsLNwherheL+jHPdNF581R1gBE9y1YxSiAM/KRpehgwJwE/uohFf7nh3D5F3+Xe+gMf6juH/9ju2DO6SHBwdOMxf3x4BjhmcO8/JWhdcFrPmolCaKQqsjmL9EGs+0K6xNprCxQ1t2Fe0M4IhnGJxs8wzoRiILQ3COXOTikDey72Rd8rkCj2yYiaM6UxeBpHjI7n1/vckCsWh3VZ913UHZ+mb27T9+y0hymUmdxNAQ7SUhjTczrfpRRVoPc25s/2ZDbgu0FoGAm0r63W2Ce6bnPGAH1aDpno0Wd/awK+MJrlu/OzR4nL5PDe+Zj7ocFRppiDhOF8NG2ww2V0SCzS7q1X7bqX996klCRoenkHTSYsZVUYZFNuTRJxFhwHXtLR5Xkn4ETAJtNc63PDc+JGt5823M3wskL+leHeGHiD/ijc7Pm5ufl7q37Qj4OXDw5nfj7jkXg7zc/5lzz6uY1kaI4LSaLadyui8uKN90b09vEWskXGBvtnMcN1Oq+fMvEtg+ZJwNi8H29ejFBU5+1jPAHD+J+iRnPnMT0ji+odR/1X8q0GxR/Ob5BdDMVd7KFZkoiyLdkApheGwgUSNJos3V9E2HZoliMfjklkzaIQBq3R70FH4FF3xj+l9O1eo2/gxltJnIwvyM6FMFpDpuhAHxGXvdYYT/D+yRlV+hC0/T5NewywWN96A/cCj5QqRWka9Q6sC6Q2NHPE7KRmHo/C4uUhsqAA5hxrdd5bs7F62v6ILrVxE+KdGS8CQH15xuYZhyyTTIPSqVPfIAJcrxukN6A3PHz+jK+//QZup7GGrVkpOM86BfS2aWmc2qD10J1ujT5qKZli92gGq946OjqKM2GWzl6kgzTYNYzKrakDpqaeJghDPfyt/SyDZRjwsZdSUK9X5Xf9vkxPRVBNO9I8S0KzT4P5drVMPV3XvFWDn64OouJ10+29XPauN4ZJPE8ykRkxM6++p7wSsOqbMfPwfr+kMd/SbL12g6vcCeaI7kh6Ot7jPbqHsdL1I1Im4x7FMwNGb6nT3sHtPm28ueWbyIHjLBhfe9AgIXje4cglANhKT3EGVmtPgUmdXhB1ffXqbiyG56PEgDlttNbUGNUaQKocVucUXRyFy/vjcrrh9J8JALPKnd3Ke7DiZyYARSBgUOsgcgO/ZTOxsTOS7OXd78N4GTJAyGkUMqmx/VrLm3o4THb3wRBddSKEoU91Mxby7qkQk2yRsf5+MtSACAgWABVEdbolg0kGnTcg7eaZ25nXQ2UGPeO0jJIzl+x7bdfUAIDgJyNTh/Gto7P6xUtCRLkXK1PWatU38xCUGIQWuU8T/vM59b5N7JfjyzHAzNcdkNxXjyzu2ERFEzMm9GHKzKclvKHdGjoXTPdm3Yvh5agmsA9w8EyAjhMRuHEEOuxkjOl1O57fJzDLNQBWVh1S2yqul+sEQ7rHEPql60WdPepVI9RPpxUA8OIp3I0uzUr/wZMAwPn8cHd5iAjXlwuWUgLGMp3ptQIiKOvqPcTCBZ21tjBAWEj5L8+Q2QH0do01EiKc6IRLv4AX5VWalbMZrjijP8wU+Ac42o9ZU+PPTaTFnvomIrB7gx63+/v+ldfu6ulXS+c9DbNTBk735xH4HFygLkACYBVYlh+9PxvYNnP4P1sWjwbg0w+fo/b2oxCa7Gpt5/6SOoLma3/L4xV+wKOKAY0+f60Nh/7rjILwfPOctvgIwoGmCYnMAQAeZJy/3uFffO8e0SrBToexR9NBZ8YKD36KZnkIUKNvaqd2zZh0fbloUB0rb656WXV6dh0xiMEFWAngrkb0AnUCBqtzEBeKtO3KKqj8c/ntD8iy4PGHz+hflH6xObQWAToTpFagd2zbhgqgWCZcWlWIFCGc1xO23nA9rahF0C4dS9OKMZu4EyzhanrLC6nslXHQQ+Z7f9lnUSLILyNzBP8iYGjE9+WXjq/mSO/r6iVRn0nh7ev/+XVau2VQrXgfoDJZ/Rlo+GWCl/1nxp8FhPYLpuPrnk9zuMDx8V6+563jLZxhmoeZr3j1oWO8e0/E2DeV7ZFuTzE2ctqQnjHK53RkmobxscZHiI8Auh+iTJzvCY6SB3+H4+0ATj3+UgP6u7r4FgR/A4QfIdw/d3yLSHHvbcejX6FIICU6GP/HThhb4oBW2PdHA+iL3ac1mUN5SbqJeliGUm9fRqv+9m49UubkBYO1yWk//Jn7KxuyNiiUdSPTpzKLS1nAhbFYrXIlLiOdZPj3E4G5Yl0KTqczIEAvDXXbcGkaNdJb17T6gBlwKnopaLWaUUcVQAygsEXJNDVOl6peXgBhWQpO5zPO57Old9Q0j8KWLjg8cyki2GejpgnRRKbYbRqV0wp6EchZIE20nm1waq7MBMiyAhANYTMWPRg7Ux4TAdRD2KQHj0jdrcvOeCFfBbJA6/XGdYM1AuQFQ+C3cxpxKiE3ako4ipTEHR4t5hh5L5ZTeo8AdI3rjpKbqMOEGjRnD7l8aCrIM4ha1N2ootFlJAPxU2pfuzQEQDFJUaxuI2QByTUYKTeea2pwQevmCGJMUxUC8RWMBZ0cWkf/vFafpucb0TahuIdARJmo6+WC69WFYbZ9YobTUBRRKBE0C6CAOkG84Axr3RuPQvclqL2hN410b7ZPXLkheZluwezf4ngP7Xi+POO0DgcPAKDiaSNpNHSgLHX8AlMgDIUpzNhov8Ow8j6Cq8oAABDLMkuREs493yNNpzOTpIqnws5kj7IVkJbefStE54OZ0JvvOYUffV/ajWkfHOH0qOpgZ8hgsFuZCoikNLu7jkSKz9tO6jg57Uq//J553YlU6RnKr884x9ueeLr5XevjenAt4S+ar9x0KS7ObPoUsRHNSlwrnguQZk7gtWOMcWZSPfpkNtYbiVCE5sBu73QGXhJ61rVx5xCdt3QfrKtnglyTci29L89Xmol3je21Md8YcXfwMhzD9re98933bjN6kKB3vJHm9imPnQYUTn2h3e84n9vJHtpzXzIO+NYxvyvyPPqvnR9OKHu4yjB+5x3SPa55uu5G9KhbmkrthCf+vcM3upVuYWRDpdFIo71uc/ByQVHkNHjZEbUQzoZ2j0jmG8Y2ARKPno4Q7En75dmRInLcDbAY6ehoAbgTehnp251fF6MFYSy3KPSeDeiteU5PmxqK2mgeARD86Y72xftkdob0iEYBwCnCs0tHJ8to4rXPAXVa6wCxKodrayi9o8CUNpzr9mnEdhfvZHCDABGWUrAsqwnmAkgb4+0ul+PzM8UAACAASURBVFjWgbIMlGpWKKdlOv4OYTXGCAQ1GYSrKbKX3lFrxdYWEAR1a7o6IijXK5aHB9RtC7DrXdMt15cX9PMZshR1jjUjfn1WxpmZUSA4f0hlicR5TlM8WKp8N58wsaVxZTTnBzKQecSpnRoKSbFSLmzXxnNhgK9t1A122LNvJN34U3ewVOO+lqQStJcKOpHVtcsALwZHXuseSGChbQ9iFamJgxB35/qHggfpt77C9usuXXoG5T/Nq05t3G/lzfZFXrlr39HsEETBykhkG0j8J2UOJvG1Qbf74Ove6qMfe4Lkp2l/k31jlSdm+mR4QjAUZaFgG3JWF0GBZ80wmAfHs/tyQr27c4ll0+gN3WROIsejU/d8Zg4GOhhdn2qHfmNxtL8iGg3O0PJpLHCHHOah6Fb8uJdnB70PPqBLXM+On6rMZ62BDtE0IWY60r6Ileuw95A6unhq6cDRicfrMH2EwU6mT9NKBrwcTNM7ZvIfOYLG3gM8P3tI82XgTCBwm8vtgM157Cux/zHPVbSms8sgi4ofBpMesGjHeOiQGYnT8vp97zlk97m/IiCL4k70Gb7YYwxe2i2EPG/F67r4751oNjs0kOGUPQ72Mc58xODl5sw9Q+4ZL1/WBWVdUN14nrbTupYo8XUPmwqAy+U6xhrODqMhCh4Pw8GRjlt0nidHpQNAbR2n0xrjarVhWVdQAcpSlGewrIBR49jey1C+pPXNIRVUCtZ1NZxoiXCFZzjGwFODVqa+7kawBzXDbHdm7q899luDdueOxsK4HbO3dYEabxfMBvm6ixTvGPk3Lr/+gSsGRL5WAGSD4JSkohWakvrveDykbguGsdzhrUONmxdKMIh57h3PBarFPwZl+2evOwCY5enUpwOZ9lvR7v7+m+fHy4x+ELat4rQuICYULmitY3G1jdN/kDr/MoGqhA6a2TJysWW2ZTOkw3S1nrEWgHy9AAtjFdX5FTaGunQ0CxbcWkXfGnipKEvBmXVeFtNTn5YV62nF6dpRl4ZChEut4A4w2jCIJ2bBIf0kOT16oPvE93TNxgOXq1WO7QCEx65+YcJDz7yq4ELD6cXbLpIcv6BR50Tfo/3Xrzd0IMOi5x9cf/wOIKD9/PvEv7+1v/9+x7futsyfzmddf8QgNHfMhHNPSH8yfY8G0oZUdldhc1k6pMjQV3sVTgB7vcPf9fi3jkDfrU14FtFu7ZA+X8OcR4h1bMb3ictqVBuARBAlpt4nE6yaK5vtfyarxpC8WcmenwGacYV6z+TeusdmZvz1ffacM12GpBs9229DTDgDYHTSCF/mMwiESi9YLKJcx6T9bHQBYwVjRUqmASGGzGFqmKPib1TayAN25rIwqTELwyubbI7YlGa8FKzMKGArFSEoZ6B/BUAjqqiUgnXRPvGHE2plyHPHy+8aUbIwAeuC67ahdu1Lx0hjSQDwQCi1YP28gh4J/Dujr0M5RKxpW8jqCLZeIbVr+sneNQWnaFSIRwWRSHii9eeGKm2gIK/fbkSucEEXjVwmIchFVJnUk2Dw4HAqAK4GeQjcKOjoTzBCr2whowAvonALRvmoCsYp8lygqU8tnb08wwwkPYSvECWNczLyivJgHnjmdKECvEBeQpbzJ3eQqxeXjyog1a/KjjI9WDsd6vwhAPVIDeoAn5MkMhEKPSj8lE1T//MVoKLezU19qHqX1I5FYfeuqU0tArm1rhFNlhJQtNiv1VMZwhnJAxiEigsEF1S6olJFpRYGprxNckpbjUSweQKGVCcIBTl1stSk+gxTR2cGk0fsMIgF0rwmpmWtMIakALEniM2g4BFjDk9NCV2t1TzGxGAHUVv1W487u3+s1vzxTzh2LckgzuyCPBApUClvGMAMyrNia0gF2SN/zCUw8G7sD7tfDQI8wf7UR4O9oEWu26DhCKGKw5F1gDpAhSYFnvQRrTLNBiOM2jpMh7HUFYE5e6jRO7Idiu6RiKInWJ1VY9qD2GTcIRhpZQf9IzNSBNs6ePPcjdjTip9gtSd3SyqizkoOuzcH2SuOKXhWDrmBOZRs8cheYjtsKrc6biJgJokynncDHAaMRPvieDjTz8SRhHGC5lt2x1GtaX21r1Mab4zN4V8jctbzAoBR6wadJfIHb5Xxd5ZgKNRn3gT5+Ug/+npzaRD3L+WH9wZb8NHpA4Fb0v+Zvxq/70Pc/O3o571zk/Eyre1tRKRe56TtjPU4dPw59vJ9l8PA4T0eRfT288FLvDnnUNrKij+y0d1fRTScEANP2luO12PQ0OCrKQuBnh0heVGT4QxLKSoEUHcc40yVaG3yjGNifxsC6XMkZTYQwvnbNI/BTZFGUnYilIwvuhqUC6ApQg1FaGYlc3azUi7Ob4pI1OSrvU/RnXnO3fEl3F4TTnfaR8H6jXXzNPHIYxOEsVez10gswKhjPjzPA90aniCLIHXjOfOoiexZh5gJZS04ravVIK+oF4ExxoHb1tNqUdcAbYyGq0a8EKkh2CMTpUOqzSU0yrQ7fNVmpajUON7qRbdYhyJ4UcN6pu0MoF2vKA9ndYSr1RwEGKACcbqGrk4ghdEuL5YamgK2IpJfNC08ebTJumCFZs7iUkCth89TVDFUjdaw2RIis9KgpQKJaAF9rvdtwKdFbDrZbu7kAcH1erUo/wZYdDifda7LWdVr/eI8gwJGRByIOgQTk9l2JfCd8rUKB+IeHtLRKSkQDWomfiEfBJs/f/WeC9hjdhz/ThZqsfVTZ1anZQkuD1o7Po6ox23/J+OVy6RElt17ju4cs7KLtIrmx6xNfTjAy/e6NJ4bFwMP6w/b15lt0RcIdUA0m4KnKQ0euQNSrJ44DEeNrQzHHcrfCogsI0TTvEKtWakGaTGc3nriO3A85elgB3DncQMrZRrEoELoIIhovfBl9ej2XYYpz4oR+M/QRRdzujZ6oZtbo8jMAbd3axMEFcCdFjlNIT3tmaMII/xLDO5trVVxOXfNJyTzFmJ7RGmjmoFeZ8CWBDYCkGUiGd2YDxvOno9KrM7oV/CF0waYPsiptQDSJBy5whhr+8VJNqV9nB0JHX5LKRAC6taw31ZKK3o+ZXN762i2dzC+OwFvHnns9+7I73I+xFdWYj3GuX0D9o6EA27QQUx7DzoRBlvnvWS0P01dqqOur5t1B3vc6W9aloL1fEbvHdfLJfq6ngbMMTNaa7hsFQ+PD7hudVxz+Em40+cL+Z7Q1woez2elm2wR5k4z7ij0a6rZer1uGvEuAi5K9xiEbrSu+DwSgNo0awKUep3OK5gZL9sF0iuoa8Rob1puZWsCoqYrbYY1p++RHc/+RU8pjVnGukg6H9xezg+frryx+f+Fh+JNhubCMJYziknMWDmHa5mBFx/xB75GpLkXomjwaHNvZT42EhRj3914Lnb+rZmI5H3A39Z4/rjD24RdhPHuft+7bgFgu7fZw37/W9rC58RH5H74O/39vttWKBd+MtJXU4cz7sn9zc7Og+11+ki7+33f2GfSW+Q+DTlJz1bjN2rr6HJVPpcIi0V9F9P7Pn78CIjg8vQECFDKorpZEYCHjqxEBl7lYbSyJuP0/QcsLxVlXcClYIUHVhQrJ3tC214gm/IdtVfg2sBV5SUQg5hwOp2AwthaDafH61aNn6qgJuCUBRU25tXpCWGyt5UfTT74hU1HT9OsOZn5wwDmgxCedrDg63Hugj94wJ/YmjMk9nv7GSD8hm231g5vT6R1zb1/9Zffoy1fw/IjcN1Fou8Pv/+//Qi0vKPbNJ8Kee6AV3C2ULlI0224XWt3p+zeZqIj3DmfdnyYQPWQ6qRvzl4iaNLQxPmvwcKICKQ2VK5Y2goufaKtOfvg2xj33//4tzWgE2YYOjKe53tvvpvAMrX5L1qvkbj8246jp+q9a35iz1kctCEH5xVYOwRbkjHF3nkxA3t+em5dcI1Xy+H18WsQr1vZgExhohG87qVpBkpSj63i9RLLgmJpOAHdvMyM5RGQlxXMZ6wfH7HQA9blAeUDA92MogDWDwVy1WdKWdB+7eCqaRndGKMe8QCXBQJo6sQXgM6mSPHBME11+zydXG1VmWxv0+qbOfXJBpKOEeHrBJRLQYFAFiVkatASVSKRGcJdJiPviqYbIt5Ackoy24i2uV3DW8FnXm9Ho0Op6orfvKmOGSyGUAedcZPDZwhP4/m9MKhTZAIU3IB+Sb2ae7pv22FqKQVUOpbyAczV5pbBK9RYHFFLivjRO1qrJmCqYbKnFKi99VF70sfuCq6zCpv0NLMQvt50p7+6RsMZxkslOKGCqCKFhCziwhTvhVFkAIGnrXMFSm+iz1maaNUzDCKa96G/q1rEmhvQA4741kjxlzEY7zgGNLnAT9gbMQGPRtxHPuYW9IQKobLDX6/gd9/vibvPxst53pzFyfcqE8KAptXtAljNS42q44iizAtJ5uGZnWHIlGPepxAEDhivZVminqkbjTQIp4xe0+jvTVStwGq58gRfCEZMx6GHDJzPFAyZRtITpJNFfMyz5U4D83Qfr0VElMZ9sHmduVHHz5NSGIQwugIoD9nvNr885cgPXtPw+1MLakgPFsEU8BWYf5onmHAWSmP0VDpA54Ln7h93a3dDCL7sUQ2j63qwAwZAjNa6GrNkgHMw6yFMeSTPEJQyXaHop401wyXG/Tc8QczMPv/AG0eaztvxz/Own5f9cW96h4CxPz/GNj1Pvp67vZJw0cQDTPAaBD61l95h8xtsLVEa/+6+g/G+akTfjSdWK89jetd+xjItxv79tL/b2heC13bzeQFRGFLHlA3DKgVfP0ZMkfZ99D0wiWD6DlN2RtrYYunJnJa6QJvr6FoUL3kGDUcsO3Q1ouIk1jD2YaLbzidGHXLx6HMC0EJhLyJhQPNz3XjObauavrxbyaLe0WuzzDJuVPdyH46VJix4UKfe9/vYuzG8wlpDW8QioQExo5HQEKR9PclqmBevzUepLZcBCoMWqyuMbjWALWqNNGprWZYomURc0aqgLB1N2Ora90hdCFiGFUHQwd5h5XTUqVnnWw32QghnVyNaAGA1z2vMF5PTN8Hzly84PT6qA2yKtK3XqlmPABD1mHF35OCyaHQJSdBxgdaUNeFh8MgiKEWxJnuUCjEaWUkoA79iXhfbc4fYuLGyGiQPtvpkJBAJehceBEDwpgJGRdPy8dV44malD5wuOT/KpJVHHHTMAO0p9zUdNmlqbHu9r9fAFwRIj/TZPq+Tq7qfn8aBMDhnmjnB7sGv20u769qdW8PZHUPL7ibM9X9fI97JSTPvkbwHRQIfRhaYwUVO/Zoc5f5px4TQb/FFOsLJRgAv+TLsxxI4wx01uzn7sDkhjazvZkC2tenh2OTGUoq07e60xMxo29sZewgH+8PH5aFUBHPmJAAefQ4tlRBGK48NV7nZ+xdNG47Zv2paHutMRMlKs+1oDtiktMRQBNzpehh1By4JGppgVHUsw/AMDBiJKHACIAX3aqHP/M8CQn0dxN4Jf7Gedx5yyiXAsKyIysRgmJzk9EtiDvTZhNN9Kzltdx40eIxhis7Gcp+nbg2EPJ34sNsd8NpeP7qe9vjBvM388EzBJXUgvqbmp8x6LhcCiCwvBj8OUy5+uUF8/+Z9m36e3Xi7i+q+hyrF3kmloNaqac57N98UBfTurBaAet3w8OExGlzWRR1PCuFqqduR9mSsMazEjQPRDr/KAAhbXwAkKKWgo+N68WyIgw++bhseHh7snJ5cCqNVDnkcINCJA8/01k0XBZz5AdiuEMtyqTJZwUqEBQteLhflr4jA4FG2gdTY7CUYfO4zKg7oMLyDcQlKP4/X4686HFo6hiFicKvjoN0zAHDB12k3+OdGgkUI1T6B4yj0qxnSF7w/MnWDYP2X0Nf/nuMhwU0ewn5+9+nbJ1kM03YKPUBc3+Gf9x4TriF3YZ3fnfu6x0E3Tsvfpkl49XDfzlGOJfGsTkdEjd9shEYva58KEwQM7pZ5jTWS3G0bxdpkDHJfyMrELAVLWbByQSFCt8xO6FeICDYrKVGbOYR1xnbdUNZVn2fCqaw417OWNRMB0RUNgosApYllvSKw4c4CwoUEjzLW2yp8gAhYyo+o+GWCo4CFNOlEhCcMoHvhRIsAXMyB/oXUCC6waHRRLuPABTzOZDPDEwEnERTXB9hfB1B+AgjfQ/DrX7xtZy7qn9UisOMK0pqFGJXuOzzk+LpzASJqU6u9oXQGi5dhGvrOfHQB0Cpaqyh9ASY+5I2+/M2Ov9aAPvODb96Kd94+E1VDaLK/x5deduf1//n8LfDTTpGehfvs+5EZz/w+ZzolQb5ueglvL29AAFNGjOepD0HaOqSffRhpPVGSAOiiBslGqpgpoindGac8cIxtA4glrhntuzdn7iHNj+fZSryGK0o01bW25/YgN1ssABZmrMsC5qKeV6SmpAYBuuDy+xMIwPnTJ6wnVc6tHxdQIdSvDVIarl9Usbh9rZCqjDZ/JpQPej8vpN7MIpC1A8uiaTSfNBJ5pEd2DERRC049lLsplBquraK1C7ivwAOBG4E+sEaQ23PULXWojMgKZ4oLmQfrhcELo3xgtKq1t6UR5CkgCPJCkQIUIGvvOq0C09l0Wu79KpAPjNIt5Z6NqT93659pvlj7O2oOWd1GBy+HVwMFpjMm1uaBDHnP7Nh+dzGVceWB0J408cvy+AnyLKj4Cm3lEaCOJhfzDkRIVMRWfw4eeU4ovKgBfTlhKQuW8qDGPVyNAdLoHcEzulSIAM1TbvUVnTy/iACWspIAMJ0gcrXIcIl99/z0Ree2dWx9ZB348PgRAnUE2Z47vlomCD+KKeObRYjdeoS54l3vbaTJbgur8wZ7SjPR9OvsihbzHCfiEIQjb0Tv6i3mqV5bw1Yr6lbRatUo9oisQHhD5uMuwQu+9R5mpld+vXL3O+nCvTZCIQDtm/K+Bv9pbE7Ye9RAp4kTvGtw25+ncT4843dDUZxIYxPFdU2B2w3ZzzhTZvLjzxKQV2Xoocl0EPOKScI9N2tJZJEbtr+chiXpnCfm1+aTFc4pQtgx5k48amxwcWoIcwUgg6mHEaI2p5rz2JzOsu+bNiv5wrDkBoiBssccOg+Q2huTEJgzft01nmegdHLrGQwgoAdvl24medBp/dCUxALpDURsKfDnZ3ZgcqdLhP3eC4Okf8otJs792LZNa8yLJakTfXvgXYwIwHjTKYGmfU5pQbx8COY2aLc3fKJ4IUg98pq9f4yohP340zxM5xMNm3p1e8ypWV9DR28zsUdObZOiNvp228703EQG1THCubX7+PcdxzRPcnzaLx0gkcloTrvz6bl4zPmp1Jz+4CjX4wYRx2mjrYEgKb/DcIZA68dyV2OzlIbezPhYNHqXi0bGogMiDSKc0kFL1NH0+nAkajLmkg3BOvuRfjPDwW4tfaQe3dbdeN5T2nMRjbA0mCjmSNW5TePvXZUmtVXUuoXzZscwrms7PWpkl7JEu6qYdkOLf/e5dePpgKxu89K2baTrJo/4dZmHoi2VVdwJtmi5o1LAy4KyFC0lUwrKqhmmSin6TFfFkpgBnomxrCvWkzrRavJic6Yqi2akEgGwQqiiCsDoEVHuI9CIOl/XZgp199JHOOW2iV6S0RPjgReCFnJSmLg+P+P88YNFilu6di6aRYA8baM5vQXttDXsFsXtPFuz705/2WiR146L/WW0OXDY6K87uYoIxAyIwWYk57MwuAVvIzE3WptcsG2WiQEE6n2qR14KQz13Yc6IRtOhETljfwq4EdAZfAI6pTEaEhDKUeU652H8SDxa4OmIDM3c1DAK3M9OE4OPp5BZwME4JbQmo4ZyKH5eaXu0fNO/+bdfl5vHBOY0KwChaxat6XrK/pBQzZ76TMb2/DravTn/OGQK843zOPdKbb3NGqEc5WLR6IDyEgw1oHfFud0dma3fXjecxHkP77QzdnkNBZbQXNMhn07qOEQRzo4ddUk0AkipmgDjZ5kKIE3fTe6IzCBrU0SilrZPbkQsB3jq+9jSqPbWp/ltpnegxOMGy2uOLEyqSFZ7pO8LUvxsH7A9mnkIH42m4kTQlaNVJDQIGCBXAQqGOnCUp4g2SR3N9H0LQFt6brzB39PH0CbQSiqVeDo/Kd1SwrohggmognJic64Qc8D1cZkeJxAeDo/eWuIXjoBd19TvuUnfLmO+b2F/+rjbhzHicSMVSuXY8l0+PkqQ779SC6GXeZsPjddTvlemj4Obk1EaMUeScIDzAjvRerSyM7pDBLws8Dr015cXePabdV3i/uW8Bj29Xq44nU93xpSdrsa2TiItzo8PMaJwtDK8HxkM7Joa1t/A94aTiACYs5iyFqy4ugHNZDsxI/6yrEBpQCE8P79AesfpdEKXjloV7y3LAlTj+TDWdVkW1NbArEaw1rSitEMpOT4w/AyZaZYmzhy6yAFRSL9uf7//+LYn3R+mpO+Zwis3QpZxcaamjJGGPfaGvXZJJUPu7YarAUglCT38ew9P5X4Sinb+seOf0cbbxzlt8zxfGQ8f3Z/5BhKdexag/PQZ/ecvEe3/as301N7lBtL0eKFxn6OnvTNgJpl+DHhPUB3PDrx1mznI6LRPwOSMNcYdvKIhE4JlrWoVnRgraRbYLg3G7QMCPH/9CibC+XQCAapndV27Ks/CFqK8hwRsczd+xHiIE2tw2MIqFxQiyFXAIvj0+QMulxd8ffoCdwBstYIWe6Ys6CT49PEjSr1qcB4TNulYuzpcr5btphOjWoktn7iHDiz/+R1e/ut3kADbLwB++BmFbN+ajOwhN2n7zUdao/m04t8nm/ZHGW0MjCKBGwRqPH+U2Yj+qy3WD/aK80+q93r6WSDyK7582zb/px03/M/uuuy+KH3CkK2Tzkpw+3ymweHkgHlfD2ovaU7Hl04Sjq+ewUdsw3u5OGoqi1Y4H6R7quFW7uq9QZpYibmh0wjaOvX8VeHj3/74yyPQ78L1W3Mqt8/m37w7d8heHkHke48MNMdf327ijd9/9jgmUUftC8SEpTCUo4IiGn1+Ln/SzR3DI36PFPYdceOnK+9CSCCtW12YsQbBsKuWPqI1wcKE/tIhsgG8oD41LJ8WYBVc/tg0QufZN+7ATPIioCujV8H6HYNWpV6tNfQrDUZfZCgwvPsEtN6VzopEvcmtvaDWiiIANwZKAb9wKIjDhVTUa4edGJPNmHm586IROU4853nLXtq7yTzgW4c611jwpw48mkH92RGzDGOSPbNnLiZ4IW9P+z+i7MeaihDoUdCfZYYDDC/nCKh/xAwvBNAHAp4sNSSZ1x4p2nf2x2uN698jChUQKbxw0TlcF017U0oDw1LnWGmC6iU+xGurEzo9ARFllPtEAK4qUBuhEEDT65nQ1iFoXYKg9C7oLw3luxP4gYGv83K5Ul5Tf1lkjsyMYET+AygWfceW8n86RJJCnCfCmX+48dw9yVq1zAmmiPcotlgQJkszT7G+/05k7lt4Id+7rui99/TNnjMpY1b4vP/NdPNlnsO8fcTbN+YxGzx16TwqWWsleaO3ygoa493vYRo4IWq6E4zhl2CeuucCinETShmKOqsWoA5OFtEPyJxGnLzNnRAkGGktiSAWXSeARiDt3p1xGGCRfJ4dIe4x42FmOufZiLl3fLePks1KXwHQL3V6VqfvlbUXAGcCXQQ4j7XxTBBO36YoXaihqZsi2KOM1kXrrouMqKL3HPu9GmmTw1gyxjr1G4R1WbFdr6HocdocytcoSSAz30OpSQPivNwR37MbQ0Tj5pPt9r53jXuWM8Z5On63K6aOG8udounj8N6jH74OB+/d98c92ml3z2jV4OQO2hqmz2N88NocHB3ZhBS08E6f3orsHxH6mD4VRtKfwQ27U5yl/mYgvlPukKjT2lB0pDSeSVrU0jrKs5G0yOiiTj+aaQHcFZ8JINRGLTbRbDUQsYgAK5tBgkLLzVoEeou9djsXrpTvlu0ljBG9m9HY8IG9V8u15Aw4o91qDi+1NVXMAJFJxOuiixk+SVSgVcc6CcdKn9NsDMtRiiNSXn83rzVsawBgZEHGMKoxF5SyoCwL1mVBWVcsxcsUmaGZlWeL+vSNEAUujVaXosb3tawgmEGD1KDFWk8HpQBa3oeADvSi4+RCoKoKbHVwGv12emFsfMLzRnwPD3dFdjw74JeJsJjMUljfXbgoP28OIcWdWQUQ0Rr1rW7oXXlHeLkWUi5OfUy1fbE9QZwcHd7BjO0NKkPJIencuFO6hJOoqFhiJY8E9flZHbxMS8Mxfg74LJxebnNMIAgDLJbukXwNEBZCzzhAyVGQvHM75ZGeD+vhZPR4azb2X6fZsXcJEDAS595sOx+U5vUO43fUsxCAdm1lRoeSfIoZ18wr/a89uJTRl12/JS1KDFnGGquBnNA5R6Cb4bzIcIIw3lHHNbKP5HErLKnc7CSXOU/0AKZgT+4tpd9qexsQKykHRKmslKXBBus7Z8BswiH7NMrHr85X3KhO1l6PaCwdv9G83o3HopjbzHN5/ynBC8HwyI12O5uxKoY6cMGRET3D2B7eXtslx+MfUJsju8OF/46yHSYPyWRuG99oLOYkw8R8+HsST+WrFDKYjPlDtAmIr4E9nzOVH+2/1/dkwhVvoJjXdvhNtg67ldLcxvW4pjxOOOWZ7L+PEtOfo3OTYdrmmNI4Yp8ddNXndD2dxr4GIL1jaw0iwHkdsmg5qRx0fX6Jzjx91WTA23XD+eGcOzPGuaMJ7jTm+hmBAFaq0Kcr91Fa19KSQhhxsPOcbJcL1tNpGqfLpeo8X9CblkbY6hW9C9bTOngbJiwXxibKj3I3l5dI7Wx7WmyW2GaMGUxN3YYM7zOys4pEfjs7kadkrA/eBLn/1mO/Bf4fdd/aJrdtpPsWALJHtmInu/v//+DJJrYsaaabRNX5UBcU2OyZkWxvEviRe5pNgrgU6n4hjOCP18ZaoKm+BSMdu7dF2eelrgAAIABJREFU3J0AEZF+1r7HCO46mv/kOuhu8L6cXPPWjL/NezH+0eQEeYqd3sk/vUZXjnace12CZdh7KNPOAzzeRfkPOR+LnjOKeSuNcON3ckYGWYkQhuy7jU/vE5NpC6lzWyl1WlM4bbI38m9fIU8XLERYfiyoN5WJ1JGNwIXAUGfpz5+fsawN+/MV0oAuHWSCbTU7Sq0MaloOo3VG2zcsvYG2HTsVlaNM57sbdW0CXAuAv3+CJeIBQbD96k4sCgNsPHnw/CR3+zWpjWzNjvKy69cFwA4P07wL/QBwl+g2Wrf13P4huMrRDvGvaWMMAyf9keNyGJrgCfew/rCJ8gCagcCN6M6fEzoxiBgk+3DoNjadSRK/ZPslZjzvHI6O+h7j7+nfYVf+mPYvN6A/ahMgyOET90DyGGjk/LrcH83HjP59G0T/NalsNEtIZsoUSu/L4J+HN9iejGxEw2ZCETbkLz0+JE8QvNwd0rvEZi5gJMLiiiXGLd2o1SdGVYo8+nFliIEzUZqIrhGZMw92V8gUgqV81KdKaNZEDeZSINJRSkctixJQ2XD9vKPvHdt2xXa7Yd961HUWAeSLRlUrkr6if9khrYFbQ61Ps2IRQBdl3AtWFRQE2LtG64rtR+87uBdAmjHHphCsNn4R9EoQRkS0GGrS1S7qVY0iKCzAlSC7Kv9kF/BuXvBPXvsa2J6/6irTYj3tAGmUPsGYu3xAUFA+FPRnj6jWH+qHqqlJr7prI8qFUD4Q+OoKBFVedryAaEVBAV0IdBvEzmaj/ZSC+qOAv+RwRKB8qBr1/gEIJZoA9APZHioEVfwABoNTUlMBoeEHM9jB4MRTaKpAspdntNKw1r+gmOddbaQCUZJ0lVlZwfIC6YxKP+h+l6vVbbQ1oHEwBCOFoBN5diIChkYUqXPF15evEBCev9wwK2TthJHCDk/MgwCOF3zziDRloOina4nc07lLt/Tuun6oKYq6FFRqKqTauzzy3P/t9i9ql2b0w6KZ5P0A4x7LxcxSZoL7O8b8H/C36e63yP3rv98x3m6UqSWUIixs55xC4A0mzgyO3EcEl+/Xa7Q+4z3rcFJ0no7TlTDTso8vLuj7+ue10bICJaU1T+Ix4S4f2RiG/lGqKVI8XZ4r4AxHBRKBG0wEVCpqIfTOlr6nh/FDxwvkundEddpvj1DnSePkSgDDHkQGShJ9Tptq3+8iwpwnKIfr8XjmDBI8HiCGTv46v/Pw64WAF6PiZjzX2r1lZCIY/wuBT43V+vcQKNTok9Ou+0LGep7AYhi8c8vKP0qzonlR9+tV8UVro4/gNfTvSPFP56sh+iJtbV7x8UqCRPIA3xmFvwPncz/Bqbd3/hx49dD1ASVP5fIyr5/4otdGpV3KFJEzvecttDYN5vAdA7cejvGfJH+80WmsCc3Xzh47giPGjMIoDkQq7GL8ULF1jL9pRKQTEg4R550BDSX3sSgdJiZwHbW70Dt609q5XiJBxIwKrPRW7dmDXmrQp0eie1q9t5cpc0QDB8lIrW7Sp58vSvizEIFLAfl9lkbaa4q7cLrv3RzhNK26p4MXP6/2DiZLzWdR9MMANZ9kSWcxeGYZNJJqhRWx1lTekpymCCBqEYmlaQcr2lrRWkWt6vwV7I1xeHABXRj7PvaKvHB3AUqr4M7ot5F5hKB0DKJZlfbO4EgTL9g3XR9hwb73QTOA4JcIuu1s0ReFKnbeAFHeb1kvYN6ca0MlXY9lXQIWyRTe1ZwyNPK+YGkafV8LodUFzeagYLihwyJSWJKMIsbfNYQdUBAGsjAkJvzt86oLGR8/Q+DZ5/GukGW4A2TpJkW05mQhABUkjEoVAsKqRRrDABPn84nAt2S2d9RrX/w09Ch4PWijlgwadErSc+EELdnFVwbfGQbXB4g28QOS/z/s8OO+Yxev9Tt3iniY7n44LH4weeNsifMvBAqngpQGNBYyMYyP8O5r7dEz39KPiJZyIIKQOtZNAa1plSlgSK+EESsM5QqBgwfEgBfLwECFIFJQiuK9cCoh0oxjRKBawuFJ+Uon5hK8PzCyFXjGruBtmNUKZecNDlOpqDjVGmmX534y36nvFtDIxmM8bgke+J7bMegPpwCHAeeOPWJdHfALOjhI3qO9pJVADM2Ep1d8OHoap5TtfcB53L5gjn3G9ImoXOy0zjPi7OltqcsD3zKgRKKP/FtpSmhLKUAZWaZq1dWiXjDU5Yi9jzUJxGd8q4z7xHgNIs0gQIfbQ/aw4x8G47QGlJhHmn45b0fWM54g3/fD9fT/Ob/QoRe6h6fT92eZNDaEAMzzTw/EOuSty+MYVNV+P7CFd7y3XxOgLipvcJdUikF/zsbzR3J0XS3g53o9/T23y2UNfEqtgc0L3OVNkcQX5ZU4LEyz7BNqPCc/TLaUaoRyR7faGgQdJGylGX1HzcgE3Y9tG+XzWHrc4fyA86hUCK1V3LZNVUWMEYxiOCYcDdObNFXPRAbf1w6y4OP77PN7aBGAq/X/lPhlwWMDukBR62LfP/t9hNBaV6jPwQFDfFOTV+b1ewLPv3kf/qD2aA2ueYICXEC4EizjkvHaAnTrgKFrc/3lU5zZQSUev8f3caSRN9xpvLRf9+c9fbi3J4P12+EFRww8yMHgqfMdY5z613A+oel65usyDHqQhgdCsbA5vmrmiX3fFf6McHhkb4E6H7ZSUAUQ06u7g5vbo0R0jd0hmkXQvwjaYtHppaBBsPzlI/rf/xfPn7+Atw23fUNdK/rOWMSDTQra0tCWFQzB0ju2vWNnwfW24VJ3lVs6Q1idXEEEJjWeN2g0/K3o4ncoXOTVr6JcRMDBQ770nk6d3eaG8f+WYcgHEJV13mq/0UgH77ji6/cggO9sxzmdzVGp7vnTodb0sihGG6uzR/I66+90l5w/PPDl4bCc6Tb0vHj+ORLNzCHQzKjCBEEHF2gWFBhPQkDvrLJial00MKG7HgII+jqY5//DTfkT27/AgP42xaV013tqn+dPSl3nv8crD0IBIRE1ZYqGM/z3Urt7dvnIAsvhNjrOLH1VHYIJCAGHQwQh/xliKCcJpY9I2oFP7OZt6arNLBT7AXstGumttSIYASCEUuj4u0bapmgOU6JCAMEWwm7IQlClZMeOTsC+7dhuG7Ztw97FqKMROi6qWPW6fDYnFcqvYChTPMdk20raWnPvoxabRSnlKPdQ9CZlpxs1RVTxqB4CtqpucId6lGmU8XCwiJW5SXIVdMbdFQ4Ue5l1QP5Zf9DKIKomTEg0jMQyxk3jt6j3meaFI0zY2ro3LAA1RAqDfrCaL89QozkB9IEG8PsBkHzaTYAiI+YAgCcUsvombvwkTWXvxnMqBTDlZavNIqAKal0heLaj4wz6CqAnI/YO19yQK/NTTWcWjigshxnBiNQBJODAGSD3UFViR75KaV9o3q/E5IVjgAjgBn34uTHYSFy4e4+L7RMIURNWrK6owt6od661U7WmyfHYaneCIoj5AAPfKPF3DmXGc9lr/49sZzjfv02Q4/Br90UWiQnH2trf0aH7ucxcXtqkR1MMR4fRz3E56DgZOfme9tDxojvnQMach6J1Cv96Y5Bn+JrMu5RAfTi35HeIqMKyQ5UEUw3Tu9ZBlDN40GT4OhoBphSGx/VyXG0w9xp4PWLJHtGtwG+Pu3z9twvd7yfc65hi9COrgMOVBO4uUGeDnZOLm9GKwLvAN50rfzOAqWT7fI+dBbK+LTo343cC1MmK+XDxuJ6OziX1bb+lBSoLAT2DgNEfvAatb891+n63Ial3sklk+MvnGodbz15wMlCHovPP9B4aV3OE2rGVtDd5CI7fnXDkx31KDyPD3xRYjF883KZ8X0lwITG/s0bT2o7B0cnvoBF5XqxW9vTPcOk4BwN+JFCehLDpsKlcsIDEFBDMgc89PayQOqJZzjzAatNpylgArBlqqJtTGhUU7oAsOGrQAm0f6F+mKAp6Egb0TE8zHx1GndDcU6QZr7VGlHlnVgc45z2shnDv3fgafUehASgMQT0pzwIbg4gpbro6GgxeV4yXHY4Kxwg9dw4l0hppXru7mJHLRWkR0ZrpYOysJWg05XyfUjp7vzAeNVIhG49Oxq+BB++qfJnWFWfLELVvm/L1TelRwJTVKy9SIq1yKc32QXlJWCQ4XPkOQbMIXHiGAk9J39Tw3WpDW5pGnteCpS1aU7XIKP9kBkg2OYLNKZeKyiiMJCYEDGX5axjXwmn3qYAY2F+6qyx0z8MhcKQEdx5pMhoYnDBkaBULoYDBwVOZc7AQWCwmp3iJFUJ5AviWHFwaEKl9Df6cDuo7ofUXJTmE62B1LA7HWcDxqTkuT1/PZdD5ajim2XOuqNfF8nWwPsOalhodvhx44FebzLQHQOgaHPfm2unzUX1IeB6/C5jeF0plDBiYydBJeuq5UzN2lWEYD77mZGx0vDT28qFewsY+RwGrkXzBEviuWMYxACZzIoxkSSQHDrsPDFgO6yURNLoY8NIJjtMngz/8bySnp8Q4xF4alRRglMUYIziHGMdhQ/PptctJaJxRIGqyerRQ8JUmrwV//wpTJceQCiJAhor8lCdbCLiNSHkRv5Piv24POtmR3L2P7Q1e9sjBIeQcO7OFtASfYchx/n139Ys4j+k0J67Z34cZHuecHUoHtX6jHXi23N7GFIMPyG8ceP8B5JArxWdnVL+b01ly2EHeh9AtpqczbcdhXcps0s9n2rpOIwAcyy6Wgn25rOqw3Tnok595scdEOO6/vVwB8IS7IILnz4f0fgBm/itTQh/8GJnDb+huzBmRADw/P0MA0zMd+jbcFug8XRZRJw+gWtmA4fADcxwlYSzLCtp3w4hV+9ud13Tk6TolUn0MDVhwNQMHQhlG9Dzeyc2BHvOqd+t0sp6PnBnsxlf7eatlvJh55mw4m2AQPwJWB30u6nbfh0Aj0gFEyvE/os2OY2+0b7n3j2qZBiZcPEDmfkBXsjTqGOnaeepr7lowUunfvf4EJr4VL2acXAL2M+65v//s+qsDeKNluBy8Gk18hq8Di2bIrQRACNw72rKozpoIrTaUorLVzunEkkZ0R6R7HdH/OvcUNGbOq8vHH/H561cttyoMZnVyZnErkPIgkdGNCOuyYN12PLUFXDdQqaBqspgQSDo6FaysGXCYBB/+9hP2f3xCtz5DHjGkskDDLMuEj054iERP32rLf/+ElQgvf/8nCIQXw+aPIs9jr0TwBWpEBzBqsL+j/Vn668Nb7HPQ9zMuZOab0h0Od5SPt/J9blaSQ2/jbY/bxMuaHKh6W4XVbh6hrjuJbSDjEIxwZ8dYiNJUqrl0wSTUvL/96fvyfe13G9BfJaqvPvjq13c+b8gmGJhE7AO5ZU5eLwrE0uSo1xCLKh+EBGCLChMX+EbLOPgYN+VINeoElrE2JUXRAICIGQ0MSNXD0JlDHWHBUEyEMiEUOemgk9fCtjHSi805R4WL1hEsqsjKzZlrmLLNAR8AiFdI0RSRYpE46nlSxkI48wkJ5ln1vBQK3/CycsHUhT7fk1JUaWVKwrYseFpXtKWh4ALmDt6ewdsOkY7egZeXF/R9x9ZuaK2hlqI6LUtHTXKz9y2q1Cs7mnRgEWiYHAFUwAC2vaMW93a1iHNaARGNOmcG064e0LTYuukSaBoTVRKWUmIsno6zFK1fvfOOre+osBSPCZEIBLXpGm/cIZtGhOy9o/3Q0Kjh9uVmCjgxmKIhMBFAVCzdKEUaJ11/AfdhPBdoVFK7aaQPNY/0qhHVSjdMYwNSJP7FhICLQK4SKZzFBREXxq7K8ZcfXYClu0PutSFDKUHAVlWgami6Lj82CAPb1ysIDNDNqmF+0DmXCpBgLT9irQu4XtEWQWs/otUGKQSmDuYvdg4LhHaFt0agKqi1obULluaZBHSZhTteNhVyKl2AcsXOHrmgnlo7GE8//IDPnz9DMKeBh0Xr+FkgkJUB4JS6Xe8uBE1HXzyyXrBtHeu6xp4rkTNFcCmgpdl1Qe8aYb13rWuzk/oFttbQSkEpFQv0nb0zRHpESWj9Sx14F1XOC1sE/CHSocAJehZTsmDmqU7TOrzS7n4/0oXXOOsHrUDrvupYhjdmsSi14cCTWWJtanQfErHj2YBV3zEfmKW9rla/lbs5+aQI94yvQ+mXp0FGCQgWGVEgxWiVwLJaaMr0SSGaxRi/XnI173yP32q4t5hSJepOEqRUhck+UnnrFDVCh41OuKHJwcCNxU5qg9YRhWHHFTSest3H3a0GrJhbvRBBuDsRCXrlSvjBOAbE6e/cbQ1t1OJ7NBv5ie1a1tcDk+J6hohx8QhysYdPs+KotTrwJ9v+mwClS+F1NPWs6Rq6c1ABd54NCjLO1cxIjpHe8WF358gXjmI/Mmh4+lN3FiJgpIEnm8cEtGlsDimHrAj+zmloTa9Ln25N/NQ9ZwUAYf9Jet/TeZ82wmT0zMaFw1xmi0ruweCNxq0J7GM88Unj8+6aj9vh09+Qh/MK/szn6+GNsa7nv8+C4uvCSWQocZwwo/4xBIdv/z8dr5nD165Oa55KvdSKZVmUd6o1onmPW+P8TxdRg20f3KwrKJHG59ihVI0Iam0BCqGL80SsZWWJ0BZPnaB4tzNDNq+ZDRAJSAqWCC2U4PmU39TrkudL2fivuL8VNxgP3N3aMhwJqjqs7H2UiYHN/WjMcQOyRyqMsRqPno1lJj+IjdnH7nvC3em+OtaNs2t4zB2gCiDdcXJO4aj9c+/oRLhtWqKmGw8Mo8W9FfTe0LsANOqTAxrJLcuiPLPxYt2cVlGMVglj37vxYJqinfcdvHelW7buIqSGcbgCSXE+OX1X9hREXqLE1q2oo1hbGkpZQ3YrUPnnww8f/FAARGilQPYdS2torUWkGGE4YrpDglgfaqR2p0tDQ+Rp7g26uqdwHk6MIHUcZSrgFKJVir6PicFlGCIktFkAxA3rw9il6KOg2H4yAH62iLinFrwCuAdv192hpFWF8RtrtKs59NJFzzRDwH0f0fVOJyqBxNL3QtRRIU74+FOI1KABn0N2HrebEsKdjcMJxXvPDmfpNYQRETxIgn03vig6C+UfUvMVTQovmW+jfOcYSIyZ7CHnGR2vD/708M7jcnm6grx8PIy2UdMwr5vfl9l4xykHQhH8K0QnxwRG16wWzp8VQhFLpW7CkzvoOYlSFKAlHFqrqE2da1o7cZgnGuMNvKr1x+uyANcbaquB86kU9L6bbCU2f8UVR34pnEa6wBXRBWU45RtdYVbetDOj913x1MHA6Nm93NfcDcglbzwA533jubydNJxhClkGErESZlLUgaUA6FoPuAuDUFFYoNlRgIpq8CqaCp+BwgUoDF5Vt0XSAS6aOU4EhGpnY4cHDjAAlD1wMlsZEIXVBuxDDppgSCj0IU1WPbvYVWdk6w6RgIVpGUFgMAqyw60bISn4UccTrl9Qys/mmEW5Qzi/5+VhApicNptHq9j6B5YUiujee2ece/7vvhlRAUYk3kP21JHA4KmGAdq5zWFcARA6wTyi8bfxGKG3md6CcEiJqHmnK1Y+xPWAMTyZ+gm5KjO5wffZCFxxcjc6BA6o6woRAnetpnq7beMGw0/hrALg+qwR5t2deG2OfdvN+Y7NqIRwuMrj9mCE220DCFjrk+o0aJjXxcrT9L37FR2RiEWF53n4pFNmu94NR+hqa6aEgtoqFl8Sz6QAAF1TurfLBfvtatlpGFIrKo3SKRDPlCdWCdJSRKf5Icr1mP/X4LRBRFMKXYrxD6ebyCyassMFjnRd3gFnTfelw+yQNS1X4I+TDlIzt1IsoCnKtXwk4DcJI7l3czPj+aN2PH43Mwg0O5+PUrqfdpRfbH2t76ydPtZIBogDOMqtRAj4+V1GvJNHM7zQgxu9RnkBwtgqNn6xa1WAm/tS2/2ukV7tu6eBz7NbE6vG1vddyIfLSPbdDc4HNQF+sPuOhtQVwO108gbLRBlljffa/yfcFlfE+HKX41xX7vgaFoCn9BqlYOuqV/2wLKjFMg4yK+9SK1aTb1gYjRl916hvgtoJfqwVq2V3rLXh0haVRZYKqhVPf/mI3jtefvknvnx5Bu+b4oBaQSQolxV11ewet30HCqH1jtLULnBpDX1dsT+tEN5RuppG+aeC66+MvexA6WBR95SFGf0fn3Aruh/kCmHRs22SAS6loJWKzyyqI4/VPe7J67DtW7D/76f0XZ95oVfIqd9l+/311bfYu45n8MHo7mZwcj6P5yvjn7M+6fD3zG+MXx1/axlagEhPRKFqTylfLkLO8MNtcqfNziInyCcoT5TXenJKJ42AB+k5qlV5djKaxtuOvu1DBwGEntfxXyG1jV3WVUvPuR0Fg3/Ig3wNSrJj3O/AlH9I+2Mi0N+lxPR2ADUZhtfpZzw4LAYArmwMRYA4uzkElenzhCHWA6S1BgWaNpFTfVhnbu826aAUPPV0HG+xR4YRTWUOSQ8MoJ0+M8VFImZpvaNuLDLDMDM1GeGfeh4a8zxSihhw2rqGEDQmNRRrwWxm5m2+z+ftRvSzNfL0h61q+sdSG1qplkrCGFV7F7Ng3zWdOu9dlVe1wrXfHtHoAn2ljlo05ZiIKhmdr2TRuuSeGln1fPpj7z0iflQgJBCGcmIYEvN62BRJjV7VlL28F+x9A7OKihTGBneg0GiYHAXoZyOnAx7qdn+RGWjFlBQgi1TdQFjRvwrqkzljPBXgmiLOS4l/1VK9z6kgxSc6BBKHHyLg4tvpKTGVwIqhaDGFn9fWhXvSx9kbe+Sp1HJpgoAai44tnjIw3uiKQK+JXkZaTWN2UBpKKeilYCvqVFHKroZ3EEpbsLSGZVlUKWMvYGHwDsCEKlWKXMD0EgIF27p8/fw59j346mAkNQLda0o6/pJEsHQOpnCNiPOC1sjSn2pElS7jSM8KOze9d63Tt5thQRidCfu+KWO2mLK8VlAfAqH7P5YUYWjFWSHQGrKuzHL8cc4UjL2cpIQ/tQ1sc8cURxYB3RAijJTjfkZowM8wztLd5EK5YYo9/y1HdgYhZ4k9NYnXvk1IPJ4rVIZDkysezbHDDc9udI6U7UObfkIg71dkrNJBvA0mWN1tdI+dFmdldU4Np0rMKTLI3+PKTFNKDjw4fidTOhyXQtPBauRPgRpeAmekeeSoTQczSr+DaFqS4eiV6GkiQc485v054zlOr10o9my8Qs+r17LLc7Tdjft0zrA5j7F5WYbpXfl7ORvN2b1HQB7wEtviPE6hO97C99jVk+XBsR5nCbHvMdsBHHfPoCIMcfd9plYPv9V8n1dSHO2o77rv9RXk9AihTDccMF/A3ESZ03UEzolPvWEoHu379Or8fQDseBepwBw46Q4JHqabfndj4fvwdMIlzscR3cHodDfNMHH83flNN+JWK7myVDVCVjNEToZfDCMyFwb6nJnCMwt5+QTvm5rW5G7rgmbpt5WD4xRhXVAqo0mBcEUvNWiFZ3jR0hdywDmS9qbouqYDH3hwLKCmZDusgZ6v4SS1+zxFzIioPXDwECMaC0rijOcdilECYDVgxlkWUSOz1zE2YOjMo8TLroKwpyJ15dHUshGPEvwSNNWxKX37zhC+AVRQm+5J3zu2uqOYY66Xq1BFgb6ves15McW5MAiEjh5Ra/ttA/OuNc6ZweZwCmZ4TXGCOi3UpjVNa1OHy0LKCzAE3BqYWc1JpaC6gmCpaFWNa1RIIz2F0dpiNFnXpJKN0Z2k4ayZyiG7eIkfxf/uYMdw5YLz4aqUcM8uZtZagqYYKbWisoCroFjad5clvURRQUW5sDpT8lB0iQiolqBFhSzS3moeitMUMxoLgGVZNKvXb8+qndwwsmAZ7nAjBN28XqH9fEnrkNkb8lSXdm4is1PKauERu674TPf4XJK5euYRUkkZbxKfGdkprE2sVEaHSd7JeoRHOE/iPkqpX23cwQdIutk++YRG0kxHjjh6jsK8n2em69P9uc+4bsYRAg71hE4mmbUcJq+x8ljFAhHg/E0mfEm+IT9L5PKO3Wy8X/xLxMtFbD9vIEK7LIjsXPn2TOPu1i6tGwY8IWSpsT+Kjzq6ZbHoOw9jvI2DFA2rbA8xRxsxRaeezMDFYazz9R6wR8ETDAW/bq2OiQqBuKAULQFRuECKZ3lQx55uqaMhiqeYWAM4OqmjrJick8HXeVcZ+h7CWTShr1cuobGms6B3l7gPcJk3n7Epvbcjd5h8E5z42MPovzhP7MuvOE+rRnuSZpdkfRaZ6qrTmKRz5ZHpZHud50s+1vfki7XXzM+fTPj+kZiDOsGNdwd00vxUOKY/Zk7TGB7dI2PMog4YkwE0YHJmFmO/KMGoj3X8zx+OY5W7uVxWlGVN7zhxnAKwXC7jmvF+2XgOAJcPH4KfISLsu5cNGNsWcoEIbtuWjvrAYgJRmidqPNd7PKNPwgkxtQTjYnvEVu+Vx5oWc2ihZQX2Z9M9FEv1rE4+tS1AKSiV0HfGfr3a2AqkVWz7rioEE7zcOaGY4/ooe2hy9Thxwd8PpwjPPECxX86HH9uUleBwz5BpT567u5LWTR9+l2HYXeY8hTjoRwC/ZZL25jvzzh3v2el+X7+3vdOGPs1baUL+deCp4YDyx0XCugSf8Y63i8x1zz3iOXQpSh4M3gNqprnkWTxajkwpKOGQ6Z4kB/nY6K8F/Gn0MWH3QwclzsjAFa9tT8aRWVaNq3G2dC0KjQAcHN6vW6U4ksx7TmUETdnu8kazrFSqEy8QYtz6btmwNN36h2XBUqo6kFG1v0dQnjw/43q9Wfaxjm3f9e+q2hBY1pred62Lvm/Y+4pGFSpeqNPvh9aAZQEtu1avWRcs/8V4+eVXEIBrE/z88494+d9fLEW7zqFIUQd2CyDzhS4A6n8R6O+Iorv3LZ/K+zsy3WEji27ofct4rvvwvjPzWtDFEccdnYcchr/lfJ7hrkdXp3a+TDYuh/MR4WaYQ1lquccOO3cvAAAgAElEQVRPfu4Gr5TOZsgJSoOA8bz43+rhOQK6qtpbyt6DHjNz2GBgOowKPS+1FEhrELHsds57O/9v7xcM/vB+STL9/te3f2kN9JG+7OQ3IFborPa5M2h3yDj6fAeAzo8p4S5qUNCUqhQMthzuPbLp+sPxLh83patyAN359uEJnaqOi5FApxyOsJFTllkHScDT/pQAWJnHaMe0OPU4GxEIrnCFTopxn+YUs3yNgqZGcCRlR7VUwAlLa1jrE5byhFYIS0QoD2ZYuWAG76wMqDB2YQiaKWegRm+ympVlB2oDqtZDbsaQC1t0UWd00rqTVQDpVvtcGgRexwEAFggzblYbnaSaknMgWaHhDere5EZatMagMUkjulARhSIeU5i6BJsMHhCgPFVIF+w3N6RZ6nFLgT7k4Q0MQqEFwA5IAz93FTyvDCI1Hku5wPikofi7QjmRAAEXM0ZkAl8VWZbVPNi77UnRO9wxYfnokfqG8CIqAANWicBfh8JsPj36rX9R4ejyl4sqv7+qd139UIArYf14MQMjgRYCtgUkF1U2GLyVQqhLhaChU0ctqgkshdDMgF5qQ7XUOiMt+qjsxlZhyT31G63oxBaJccUVgBSgiwxjk3jKVlVuknfg+WeJLHqI8HK74i8/foQIa9rR1lKU7Fi3bor/ZsVYPR27qz6KR+EZ8zfhL5E4pqYe91/S2Z0PMZ38dY5V6e7jffLF/XNy9vs7mzPh1VPHugEi8W4CU0wbEaHpR8dNYrRkwIIrEc6EiHCmIUGpzZwr5Dg9ZAGJfWccMQtBwABVuLJilBMQ0ycovqjNLYmDJTqugxzuGLgbodjNkwjFNo1I8Yh2tP7b0lI08mDJNArThEB/lStdiEYa8BhGVlIMT//xzrmdXSPAMkIc1/js2wEwJz7hblsf9ALQendFFVFBDw3HV40kP5+HMbnmcHDkdKe9JICs5uzjRt/w92GSdFhb2y/O4yI/J/PjwYbQ6GvwZ2mR8zAyL1c1El1EzMX1cNMb7Qwz0MHgfq8IzbHuD8LN33yrqDD6iiD2/Y0O23aHQEbt6Xvk8v1v9a6SMmH0TzEsgqeD+5a+x80FAC0LatWsKLWOiERSl32Q4RvFf2lDPXjYjcUaAqkONxi4n4hQm2YyWtcVl8sF6+WC9bKg1Bp4SWg43YrV/AqU7HBaANciCRACIfyyGUfvmuFqFI2TI5A5AKjxM1JrlwKirkpREz67KUX63uGp1dRp0bp25yruYHPyFChOd2cYvdHXafyDCPq2Q4oqal3IZeZUs0wGjhatX67/YEoThxG/12ijmGGNENlKYFl5+s7G+480f5213I4vWFADD54XGe+r0L3uHbfbFdvLDb1rORqwygOd1bguouvYlgVVNJtJpWpZCKrye00jOnxNb/tY32KKbeXjBMbkg8UyDlhJAF1TREYBzYLiPD4sMlblFYfL7hmtnFaaQXFpFaVUgzGtEU+dNXMYYAZIUsNYIc2YNpgPhMOFw+1GcJufCEBPmHggvWmASb4uQBj4mRl4AXApSvcLqaP5bUc4T5EapQqROpaZPOLOn7p2HMYigWU7KyVKu4jAMs8kehRgKAmcOdILzufNYC073uROJN+XJkvjbAMYfo9xpsVZNiTQn8nGIHrBV8r0PpneQYThGEAYz9zP6r7lvUus1nSDHK+9o73zgWkJWFRelIF/XWIigwF3EnL8NGAurdG0AbAoWcc3DHHYB7BfN41Yrpatq+ZIF0APyBhvsNZH/smN9TZ2IXVu8nMU/1hG+SFgOH2IGaVcRnaaAnd6HxzhUA7C+CsHw0FfPXG6CE/PDUfVzL/TqyVg8vyPtzgOHvyvU7M+Pfo6OLhTl8quqp3yCsQq95f43Gx9Dx07rrXv7aIBDiw8FPMwg3lKeBg4rhHIgpdDJZaB07/a/4THxH0fXj0owfoqzJ7GROU5EVK/b7NkwcERgYlTgiQ3lB+R9WHhpp7kOPX7JvnP5LhzvOnwGocXyZ/AOD/53sPae7tclml0LpM/f/0alxfjA/bbLToSUcex7kQsTzm9vrWqznMA7qwGhyVQvMOPljFN5AwwyLKL2RoKmYNNH8OzdaFa0fcNRMB227A8mV6mFKvBLurI5rI8LxokUQrQOwoVrSXLzv/ZZ54LNGNe5z5whm+QINFBwqgh5vTNF1AdBjKPnp2uYhV8Xk6Ljytz5CW+sW0Y+NIxEUHFwvKXH7H/9uWO1hUotqkAprgfqAHOB/qdQ5pb6m/14Jc3D509Sp7B5V23j2e+dzFfaZ4/6yLAtcxGdAIim0qMQ8Zv5W8fIb/+lnJwaUvabHyw9fZrz6T9exR6/uetA2ihQ9dfyl8J/Ivgw9/+AioFX//5aZrHB5nn4xHyX+nBfjvcvoGfp/MlggVyB3f+O6UnVEdMaHA9uKgM1wWVgA9PFwCksgcROjH6rvtcDK88tYalVnz46S/Ayy1StpdqjjYE7KLOtZsH9pnzMEOd5frGoHLFZV0tg07Hh0vH7baj1gbeOgiChQrQFpSVsaFgf9lQeoe0FZ0B2gTXXz6jmSvSXoxDML4HALoRXRJ1TKF/9FinDwI8/45yCb+c+1f927XXhkeHv+/vfcRtDejy5453dOM7K6Uz5TwV7FwY0TYsbz2f8woe9kiJgw8+Hi6buy1kHlMXzYzkMg2b3C4ikH0HSlEe3kq6FRFUCLh7VsH/3PYvM6CTHBDpGQxhRuDxbL7nDBMGFnyDSX7QXrv9SdQb5lu6HB72729nRysMP5R/eScVf/cb33FnTi/75r2mZEkMpnuHVjtU1RSpmspNI8+rGZ/DYdCZ6KwM7ILdlUdI0cuAMnrk7y+oVCGRHnHXtISmNKxalAQdiDS7nN9jq8OWfhvQdFqevi0L3d37rF5zsUAshfapx4dPkDGMzJAQsLPR7L41gMwzXACQpSGlHWFgt99U6NmBqLGufxNdEJFUieBNb/NjFGtB45oj3vCI9W22SJMwqjlDKMALQB8A/uqe1oIjwHu024Ah9a7zyDKAUD5QKMzyXFWp3SFsfRQ1VLcm6CZ5EQhUamQvUEW2ANKHMkbE1AMrCNfJ6YRkGKMlJRCaBBEkB4LAARapYOtYPNKLCF+/fsFlXVFbVaEq5kKx1p7G1P0WPHpMAt4Br7UVi+rnZ2wOKpHVuDnZ8MmIMrq5g4sZPF658P72Xobk7hc760IUSu22DPLmCjs6dOTetkcFSdhE4/JreHYIqYrr2N41PzM8jNU1I8ae3pHLYwiPSLfJE5IANwId1yejl7vRnk0hzhtAljIOUFw0pp/PNaFUSuUk7I2Go9xj3g0zYXjFLBRmvDaDnhk1yfHNGYM1T+Soen5EnybBMF/3mT74/bSPSKcvNkQ9x9VLaRh+uY+yNixg0fgeBRj47uzFRAle3tcm0AihcSY+GVeRc+DBb52w/1OnriSnO0Py+Dqfq1PzQAWID9FR70YgR2J60lw/nMAo936MpPrWliP+M859NQL9+KkPGG5Ke5K/H1HxH8HyAfCUxXcR4wnmPEFJztpBcT7faI4a7aum7dWsMM1qR2vK9lEDPWpGutLO/hXSEijVU0oLIMQgK/lAJBrJ2ywl/LrgclmxPq24rBdNn+cGncBVYmUdYkGsjIplvAll6+A92fZqZH/SSUY0Z2JmHM/5WnQ3orvCqDO42Hd2I2vHvu2W+WgYvsminP3asWY4YDzkQfmWo65YGMXquwtG/XQWWLQ7pqOgc5R0zn0sglCTkX4XYbDVpm3CkFogZvkmSKQmXQ2meu9odTenCTKvU4O5PiIQfDXZ6r7fbhuuL8/Y9h3btimt6sM1uRjPWWsN41uBGqnbuuJisFGWFpmgll3H5oaxUiTWp+8a2U7QDCNs8NzNwLz3Duod3ZTjlNfc0KYqw+aMCh4Nr1HvzeqLsyrJdt2TdakWrQKUfY+U8nm/2SPcrdTK5LyEOLFOpqfD2bmDX/ag1z4+iODl0+ehKLHnStesOdKNtpPRsksNox6l92qqZHUf7fDSAIMnFuMVNAU1TykLnc8ZDiAhHcXZAmDnQuGPZJZDnG/OPNbEB0rqx+EM5lCTnf5yVspMQ6MfGCunX1RMPMhT9iLPZqGXnA6kNhlw7BcfZHjn6j2eGWg4tL+Xdh7adz7m60d5WPlz3Aj4uk5A6HszZC6H05GBZPDvzICQlkcL3VBV546Rtcm9S3xvA4rn4QAhu8MM5aqQNlzVJbKUSJonYPApLqsLiKyGKGDl7ijKRiCMWP7i0YlSVD0jUVae9ewMjDZnQXSVKNJZOmvOU2YnjcHr2oa9knngkRFnjGpX/J5onEMhmo15S+d5OrNH/sFM8YYbS5pbRNFSHNnjgMYxwXQcx9mfLg5gD3WyhWxJvO+evxluDDN++a6WWQ68NrE/qkn6/9z9+OUBrwmXD3wZjf8LOKCJ5mX6tK4NIox2eQIwjOdfv3yOe5bagneaUHc6oxkWnr8+gwDLOgl0HoYb31nXu1he8zCcvXz9ivXpaSZqeUFsEJJgxOdTm0bKjSyFyp9xggiPthNA09tmgLdWlkUj0qF8CougtIrKC/bbTXmS7qbBBI9QuVIzXlh0JgG1VDCbUxpZeZs45rZjDtuBS+4pxRkJ+HOchN9uHcpd9k+fUf7yY4ztbnw4F4X8vnenav+GFtz9NyzNkAiOV+/H5+fgjzSi56Fmg/lU81wQKdyD3bD7ohzGN7zH2yqPf5eTawDAv6icVWloLQ4cUfzN07Vh8Hs8vkf/n+/LehnVLWb3puw0SHCHFH2uAKJGw0owB/GKpWo0OQGq26sF0gmggkoaRLguDeuyoF6A/lUser2YQVSDGrQEVMcujM2cqPvOwLqYnGB6ZfPiu12voGrObsyooo7ppS0oq6BSwVbU4UcImoa+MogZFcBN9LNj0O3ETiseEyuH9gBeJ1g2BPlaRot/dZszeMz8zWs8wqt94o+l6N5nNANIkcTWGe+ZVHt3zThliIwMP2S8uj83bFJAMo/Y8yq/sahjeLGb1B4mKCxQ85fJ5EbPN9NV/Ce3f2kE+re0b15mNzicyAev9bWx1tzL4ktuL4lRj1fZ/x8Rg3HX8CPOzOcY1T3BPPdJPxFqQj6bGbas4CYMw/AjwHVjhCqJcozWYCaz+OHe5fq/uc8zxboz26owtdrPhTSFZ1tQ6w6qO9A0P3jfb+i8qdIReiBFEJHj0jt6rSjMqFTNIDlqlRCqpfamSKW0e9SOiDHfgqVWQBhUnzRNZKQU134YAuKOIi3WMuq1sUYGA11rj4mg8w60Zssy7wEAU4QI0IdhXgV2NeBWKhr1cRNIkWlMhAqmDq2H4exFQ3sq2F+8Zpwv+o5SFwg2aAq9BYX6EEaN9nNxtsDSYYka4wU7IDVq0YRpNhDtgJt8Xpi79ssjDIYE4BcTaF5g0Qt2vxcKMOBiPNv3J53P103Tvf5Q4en/SiFsv22otaCXK5bWsC4fzZnhBSwNIK9/WUDSNC26pWitVpfDnRs0tSZH2v6tay0YlltE5Pj57LiBIdhP8MQgtUCrJV03k4QxRVrnVb2L10U99rtFl/M+vKQ9q4EI0FqzujumdiEa6UDjdJHtne0MJYxDundMyg0eFbKhbLW/p9R79r88P2/HFM+TDvCkneO1w/Pv+uHwXVwRC/QNoSAnJwZ3tXXP2PJ7ZYB/9zPvj3jqRF8XZy6PTHxERvFgaIhMsBeYct1wVqT1E3gaAkrnYzKm2jq7AuKRoXUwQgNjKDwMLYoqSWgy+g6mx+Cmj0wH09oMRBCwyqz16dgViMCACcnvSM+6QtgN6agQiyIcQr+voz+bgE8OeDZn+7B90c/kbAUAnlo2P5vXL0eem0NORIab8hQYtfpk0z2vrY5IdHE8qUp0dUZYLbJPhR3ePYldGt0dT/B6m45I0J3XabOOzyA3WRSO6zhqKJ6PIrr1I2K1mENxE9cTPNQBhjGUd4gbGVe92fKxMNRKlM73o/nEeA5XSc7XEGMN3qlzeNzyWsYRovHDe/o+uWcoaPz7oOkIhYH95il34+Eyar4moZgwC9ZZ+CSGBgaSpWxvmrK9loLSGlptVv+5TLySj9XTiNdaUbmgcgVDUFFAXcBkabktFXxbGtZ1xfp0wdPlCcvlgsvlgmVpGkCYaqerg6OAzFkpFA+lgmoHiTpXDlqsyo+IAIx9kfh9gpZkSGWLKOLegw8nuDG/xLrtnpaPe9SQ1vmX2KPJ+eigZHI6FPgmSb69M5gsQ4bjKjEjOpIhzpSwJGLlcWxfbMpshrBwXipmBC2KWbvJX2GDLIKyG5fIWjKploq9Nq2LjRIp4bgWcG2opaPXHcX2d9s23G43XK9XvFxfNJXhtivfLhJ9VEBLErlTZF1QIGhLw7IuWJYVbV1QzYDuBrAuymsxoKWXqGPvyg9PDrViZa1s3fZ9D9mr9w6G1maHSKRsdOcH57tRdJylNCyLOY+0Ct53VFbHYOX3i9IXIpRFS0Lt+45SKnpn40EKwJoycpccvzWMzf1l8JBM5gzwwRKl3uFe4PbpWflwEcgKyHMHrYT9tjmjoJmd1gqpQ24Ext8KL4orHYZHxLk6khBgtZYZ3Md1kGfqcsOpF16QaZw6S10nd+J1h9tw2M0nw1kVygfazqhf4lHLD/60L156dpZ9/dPPu4y/kZ4F0HfnI713WOY42zM3qtv5vXNkpYxfMw4a7W3qme987aHHvegYSizlpHSM+c7cdl6s7KjseC4UdT43cvih8QwIyhdqxrClkTrSw50e8phPHDB9n0IuHRE0bAppl7c5DOpJPrVuQ0ckg18lUgMbFYVV3vTML5Zhxx1UhzMawzOd+fIQmd1P3FRu6wxElrsZ1hGwICAzlg26HOwDIWrQhrzgTFnwiX7mBn89s59jPw2zQLUCahgoq75xv7rGwDKvmV6hWIogFsOZqLGGAs98NcsTPhBOshNs7kW05JPfGloJk0mibJTkFRn9EAioJtdk+DdZxPHYmWEg83ffyubFtIrGi8lJtqrXn0Qc/bdvl8N3f3m6kFBbRkvjvsF3jvX3bIiDmczdL8u5evn5y5fpBcUM4fdZtjJuGv0fZYwjeLoTxnBo9PsS7cgya/rN4X59WkeWoHwfM6SMwB7PhhQOX1RAVbMpuPGxWtpaMt5Hs2aQ6jB3LyeIwSPElD1gStdeIKhFI/h8KrvJi64f1edSxiLPUFlYHZVPAGbQMRn8twdl3N/sC3j/m62/LeijCw+b51F0TObazfLpMxp+QMdX5T3tevZpWzBj+vfRvvuWKdSxLR55/n7ietoc9x+uwunHdxkUT3g4//Q1G2/RQEAfQQVCpltAKH/7Gc+/fgqDOgTYCdj/+Sn0fA7u5fCeTG9weM+j8WUI8bPbDRHxP39D+5+/YmiDgPXnj6a3JXz6f/+c8shdRKa09LGu/k2cRtj3OG9n++HzMZuF0w1I9COmX9asEgCXRdekAIVEs2kZolYnP88+AYDU7kEEtKYO5ZcfzYBeBfsmGlhn/B6b0XHvG7ZtB/cdve/ovGuG25cOtIpNRHVmEFx++AGlapnPTsrHFKheupYVlQitNextw8umWdlufQdvHa1UbDuwMFCF8Wz8QyELLBOJtawC1P/6CeXv/wSnTX14VO4Zi9/dFN39cf2enUU5fL63vX7/gfE4/ORywLg3Ek27yg6WYkf3hRI0S8paQrn3fOqcFwYEbNnjoOVGUNQh3csABbvgvPoo/xZDASLLXiegsmb/dd05u+3DAlf/k9u/jQF9bPiDGw6IOCPEb+n/e47We545u+eOOHzD+/Oz7/kl9/0w+0XilR8x/I/ISX5OEYtrxoZHJuAEyaOE5z7t9qRIyjUw3UPLjOCCMGaypTzsnq6ksyIMtsprnTV6owikFNQKaBpkU74WMu9MNVK4UrH3HsbIMXZN4ejzc8Wt2rstooXc0xxhbGKLKmJWpljs/ao9lhkRJ2HAnQI0DQtHLSUAkJtuZlbGPGr1MiqPDEaGAtGpkpNA1H0TzGnO5+91KOhOuFDh11BFUsYGssQ4h5NZXQYRIgByNbppdzjy1/ldbYZPKjjg6QRmSNNJfnDhjaLue/E9CYX1UMggYJJQqQFFFZvFHC5qUSGepQG4jnqgfTfFyQKPMPf1Hfv3oMW43NA4OIoCQiH1CKQCMI9a515vL2qeEQAUlDKMlv5v71oFjhIRCkENY1POI31VYDs76IEDDtoBh/mZJZ37HAPBad/TAr3ydXw/4COav1MenJ8rcnOzoMU8afzLg50kooGpJCvw8hvvnkuKVh+DKfNipQx+s9LBDSauCAIGTgxwITtPd+so6YXz4oVS6NjiuviXEFYm4kTQ2km3DSII5b8asXJnlmIzpUyN8UMzG7i3LZwRlQwUblJ1rs7Xn+CJg8iUbWJcJHOf+QCCGrjs4p1BM/D6cSlm+HZcFNdXAm6J1XTjue1veCXbJpXaoEYcvY1FUGlEjIYR3UHK3l0sS0dpavjpe1cjWdEoVN9qB8V3t0Od9Lvz7P1mr5f8jrhPBsJO/SDdRgZLdz/kdye4GK94cP7lePHxxL/BfD43Swd9dC48e9PD/hO+me484pf4iU4+87kdz02o705DO2D6e6NDsmJxgg2aV3Tq/0DD8j1zxOeMmzJu8wjzavXkimV/aW1EoAcacuIq+nep+lulilYX+O73UiyLEIFKw7I2LOsF69OKp6cnXC5PuDxdsKwraq3Ytg1M7gioYywgSGGrNVtRS9czy1amx4XywO04zPmePsV9gEVLGp9nAqcYPnA66g6dIhwp3LlbxiNxByvLlGPvCUxqcOzvQSyd4tyjEsCN+CClQ9wVr3okVJwJGferk+GAmOGIZC+zerthDIMK46SFku0+ArBBukD2DqpNHWaJRj21orXVStnMwbaaEbriervi9qIG9OvLFbfbDfuuKQk1aryg+hqZc2aF41pHpGUcPbXA6fDZy+2MqF4Qq8NB56jF3lP6fWaG7Dv2bQv+ivcNLPqciGBdGtAqCFYD1Y5/iaxH6rBRUDVdexNIVwMrE1CXBt52dXowR+BSSji0RkYiPsThrACuwyksYzfn751X9Gs5Ol5EgMU+heCZkBwetQN1AK1sZsCqEeCZ7uZIvjBU2wEXo/uaScHkPVGDZSWAi75ruAGYrHWoHU5siko2OYM0kcGwjfs58KHMaxL2n2mYkt6H+/uDV5GJ183XZo5bBp4ggOG47ihN1LFOTjPDKJ3Gnniu2FO8ThO+lY24aweensrggeYfMLPOhz5m1KkOvi6Tu4Hc5xziZncDUaZ/AFXCdtsMv7wqkb0xN3WGEcuSwegQ6aEg1HExRFIMmgxa6tHvtRj/ykilVuam/KPtcWKfBiS4/sNmTH6Ngs89i9jFWB14xJxmOBrwk5+FRRjlLI/3q6dXz+DK+2LshjfaMCxgBzxuTUapjEyLtOfhzD/R4wxAuZxQMuyXRpCtmKI392BQKUjOBImmRb9IMEazHBT7lGFRcu+J+N1twPva2b22H8dV+ub2wOB/9vfdmOj8wiT/YWQUPI3WS7h0eVJdjvQ9ZuNreVnX+Ls01TF52Z79dotOBMBl1TJ+t+0GIcLWNXtkoRIGLCDDmMQyVC9JBsJ2u6IuCzxZrb6zgPs+nSmyci3TUpI6uisNNaoU8yWQRdMn5kz1lMYjoFWTzxjdsgyBNGNlqcXovpeKgTp3iuFag0+Cfq8smkXQHO89HkWmPfGlGDpLG+kdXPvOSgz9j4uA/pbmnMwRFPPfmRRJ+n2DYp39TxhXHpMAVpziW54+wa75zPx+Cv1mE6hR20dUJSpjmcPHx4GP7SwUfATwOZ5/rW/v12fyFjo828P8bCeg77uWVyUdL6DXnn/9HMZzpc76zEW8ZvZYT8LMG812Dpqu5YG5bOV6ZppGbNl07fdCXu/c66Wb3Ou8vpeGEnXYKgSUxQPCClqpuKwf0WpBqw2oDEbXsqDM2HbLmnu7Yes38NqAvkAaoX+6gYmNtwSEBK3t4H3D9XZFpYK+m+xSqjpKtIrFAgo3Gy+zoN02XNuG0gtqyG+Ehay8AhEIPPEOigO1frrLLopLh53gLmo7dKLfQjTfaMHM/wH9AOe0Dbib05/a3kILWa5RgeFAs3CHx+X4V5DMLF847zlo9mw4VwA42ha8hc2uqx0PVcumFYPn79Te/Vu1fxsD+lnLad7v+LqT73dAYHfRO4iSM8VHhD76zig+XT4M4niXEwI67/X+fmcmXaJPzL5+JKNH3J/8/x3gycwTfuBN+Br+2fn/ylhO4zCPZ/aIPhr9KxNXQuGn4y2nyGQo4ySITWgrVOuFQtU8oixa3F/CfgA79p6id7pFKYjuWC0M6QQBRwrIYnXVSzGm1ARkQInXZkrKjBzVmC+qOI21IDUiNQHRCrAqehm7KpMKWR1GU2T1HRt5Sdexf5wM8gFlItD4dzeeM8jqD+97H3ts6TKVYFlqeFUNwisG7deukdYx8Kzi7HatQcDhBJALxgp1RJ1FACIqFEMEjIaRFk+9Z/sLg1ZYTfQbytOHgMes3O/PtsbiZ0X3nrOQ4WMQQC3k/sMKB2hXeAoJ6KqeciCgfazqwfx80ZpSdFM4QI1zomOSdD4UBqUMRw/p1Tz6GDt3VZp4enR4WvdBKCLq+wDz7gEmBufVFc9EIbwXNyrYM5res9opHmlNIqWtUzACWm2qLjCBTQob48NWu52HsqVK7KEMgI79mRnK+TNaGXc4k20BhTM2O0POr93wgHb+UfyIO7MwqfNBnPGMf06YaG/DiUbvDWH0oGlVA6E7LBynJ6irCtQaWZzml4wxY51MmRMRL4K+aymGqIUurlQrJ8QjD2DgGBzeMb47DEhilvTGumg1p2Ka6ExSR4TRYLK0t5E+daSCHzAYr091JL2xra+/z/cnFNJGE9zIESTEpx3dJyBPu0EAqGk0oLBAbgJaSxjKM7MPAmewQv4AACAASURBVLCactEUL35Z7P0aga7KlGIOGjkFMosAvaNaFIZGfI5IBd47hIx21orteo29oRHwmjn1t9nNO1w0aPe4JTYrwazDNmL84wLFPRCE0T/680wqZowfa5XfTfHDfaaKc7xwj5num6abO/7usPXwMW2WUirWjF9702E/0h9ZOZtHEM4hR8R6hmiPdBA+rON+epez4X/8OvN0D+eS1/wVATYr2Hy2AI0IbDhp8zMq+eEJHsl4k4h2gSlsDLepEb0EvfZ/Q4cuEIsOby1lAeKCwmx14grW9YLlMuqeL+tqmY2aZn3Yx54rX2J8ow+XACoayS5NeZ4evC/N2ydjxSUGmngVIIwv3ZzyuPNcZ5k0BSmAiHrs+5ZKs2h/zASiggrWFPc+HlPSiKiSmPWlcMeV2DvjvzxyPvhhi3xzAxBfexjpPeqRCOjmwBcwIB71lAFG51M0E7nyfMWdJ6pichZ0aGQ9dcZGmrq4VFUkUVWFuNcGLwBqU0fH7XrD7bbhdr1i77uljGOro6uLwMwR/Q7jBBdcIa2ZY+QNt02nTWW3Pdpx24fhPNZXdnNo3S2ivINaA/cOIpNFmLH1jmL7vfeuPBi7qgHwskmEEUnte+d8ZSECsSrkmEjXQSxT0tIi9X4tAiq3URuWKQzQyivY+WYAK0AWjkOrOdNKvB7gDtkyLTfjuJ/Bq0H3KqBLMecPo+/OKzAgVdSBhUgjZy1ln7Bg23dAzLAoKsvkM8QGE0OOdVCSSFcLOf5uwKwLqmePOzT6r5rh0s5FZFlwPDKy2TgOAFy+Mp7MnKEzNh367TjxGDNBZAwybmKMNCnifM7Od2W0yyYfC7NGaBwom4gMg6wA4RzLMz4fuPrtFqxAovuRccTXyBcuylUgYEyVwmQ4M9MUREYdxZG2eKm7geP1Gid8ojzxcPzxDD6SnTcAAAW1abTW7eX6wNiTmZrxcXqXj4kFwsNQ5vKjO4PMNDHQHgjqiKNkjIxf0n87cyjYg3AYKTJojbUiIHBQ0SOO4Qhupcw84tRpQML3Kmu6Q5OPDEH7hi5I4rnMY3rkdSZSY239bFHAjp5jgNDRb7DZqH6iNMusZvKP6yuKR6xfhg7CncC8h+DzE/+oil0OMKBWIJ0fBo3wESZIpqh7gVjGyUEbY1KH9GtEFGVbjuJVLEas9hvN7q1Lw+3ry+TM6ueF4u/U5m3ICcRO+89MOSE/fsATA0ys43SZ8g0DQ49rNtIjz0cFdV0n2fL56/NY/zTOUgumlx7Y6jEOwdPlguvthlmuHDCqH2NFRETTEpOlQBdBFQGL0gzvh6gEfdO5jKwSMeMyMpuIl3rwbGgAqBofEpHhxhOY3od7B+8CqoofaysTnvG5FCKwZaITEhSoE3sAeu9AITTlCLFtnJaP4Hx9z3J3Wks97jki3TcpMwgYmRfu5LSzA5Cw7QHtPmwP7juAOQRfAQy90+wuGD7Rf1rz6POHwWlvNIeQ9+q3fCvedGL4hoH4vkc0t5N2jFTtG34D/kFomafA5yhblDFAfv3JkZ1RCs63mh78tv6sF/dPwO3Xz3j675/xVAqu/++fEPmC2ydzqvmJgPIR/M/f8EKjYtsHYyRejKY9WvdHNdFdRxq0M2isnwu7z/RyZFlNQ0/MAmqwUn2WQRakeIEIpVZLT291zoXQIkvlC7At2KHnszOjPV3QX34F+oLy9AHb16+4Xl9wu1213Bd3cFX5kAXonTQLZ9esY6US0Dt427UkGxUsFUBtqBhjvJWKSgVrqSp/lqKlqmxNGhOKFNyKpuZmDJtDoZ8g+AWAwtMHQ8/PdA8300K/qax5f/u9Tj8ZnnOfd3wEXpnTg36+azzxgkRXU/9iKQri/BhidCe80I3aJ9HJ+U20RzMb2Xv87MCM4SIq50pHZwKVDuplkOE4M/4+tcuxlTUupU6JIN1p9v/ECeFPav8+BvR7Plc/H9z+CDl7X2fI/g7Dvz2M726ZvRzXwsz9fR2+Mf53TO/d977dj9wTGDudZAJIjuwOb4gkCKmYZWkXPQLJ+TKLNu/bjn23VCV7T8ZqMQG1aAK/4qurRktN012C8HkKFOYReR7CMVSB5/U4iaqmaYIOu7VmBnQCSQsvURaB2pllRKCbshTcgS6xFpxTdKXFFWF1Duhey5AHERZLkeJRlg7YuZ8AWKsDRW1iZiRuIYB6gr/MIOnfbuS3gdk1gdZUP3nulsFy3nO90w1SiT0KRJ7f/2I9ZEU9IHID4aIMs3Ckf/N+Ztk1pSqB6nsqErjlz5xFwJ4QuaLzDpGqES3MAFdI8mV1YtNtbzhdH2BNsR5hgIQpF0mUaTLBRVNYWsROIRQUSB3KtWqpbY19MU9r88Ynq8cpBN62mBv7uhtREwARiZ+cYRyGQ+i0uRGOezj/4UJExh+PcOZrdPHRbw+vn4wjPv3ayef4N9IdTkoAOsfIgasT4+H/pkHIQcWRhR5CKOTuozn1s2Bk89ATwPBjmJJ8xNhdAHJLZODLtD6Z0X+zuXSRcKrD7cxUccCG4pkhSnqtnKxsmAy1Mg9HjLs7egQ7XCrWG6eokjk02XaowkI7FfAUmTMxmqSORmU14xMVS5cnkEX7aB9Uwffy67O+/8nqDJsir5bmswQRoT1per6+7aFE1n0sYIvAVJAZis3YNxqofI5OkpSRIO0Lzu59tIn3vMXdXqR1ya/w5yX/IA6PR6ZY4WGYCIBJ0ZSY72kc8ezwSP69zXHs8ar+f7zh4bsoPe+eQd8xivF/G1VCVnT4y0USOtw7FNZpRmd4OL1v3tfjbn7rNOZ1jPpXmT7oD2OP/dL8+tTHGEUYXOz6cLTRDESehQjWvRuQtX9RYczOeWkFDZrCrzCjMqtncytYLgvWdcWyrFEHvbhxPo/T8X4BiItm+oEaemtVnktY089S70NCjBnTULhjOMf5GjFgPARHbV3nO/X1VlbIjEiR3t1TBlvEpbBAy44IJgnCiBElB1FAUEWjkwuLlsMOWmU8Jfv+pc8ZEOCsgitGRBCR2hRzzhs9Hh0Qnt9Bpgi2KDDeLc1fUYVzKVrfuxBAdcgLACAUzrC9qyyw77t5tTu/4ud9ZFxiJqDUiHrDUiH7rjJAB6juYSRlZtwsrb8wR6knmONkgdEc7sC2DQO6OfT2bVOjPXnmEHeMMx7+9AxlpYXydpoJoYCYjd6X+F2VdBT3DnpnNFHcOO7MiuGINb+Ypi33MY59HOOGCLAOTHI05IRRxOfh58N+0ARh7kjASvjMyVOdHsrgS30SQrGDrsiZoh6A4FFAAvLAVFcawcei8DMZJaIvHfxwAnTnwbR+ovPNxgV75YHXkzF0X1Djg7yvyUChm3m3jkhn7djiaNlaZ1oaeOiAZ1+nAK/wEoVApI4umrVp8DPMHVRNWWyO1u6AFmuZHLB98NnRKmBJxro46IQxJ+DKv1sGtwPuZXMm0Stvzfl9TZBh+R7ez/5OYJTKepA5ilAiG2MFDNQnBaXyi/lg2jOBCnVhMgy6k0PsRRxBGXoPH1PiRZ0h1Y8cOjHw0VFhPBkR51+m9QN2aGSvOUztmGEinvJ3pSsxbhuXEyGXOcTdVvQ6W87nQoNH94M0yPzEpYzzkXgb+NKlOQY7lnozEIfzbXm8PpFXTtfDtv7whP22WUpcgtOx9/Kjr0K9nP6pjY5f0mEdGvHDjfczlPngjpPq9I9InbuOgyCgrcvJmO2m5Gx2fN9lXdUIDeD569c0Doy9PRwnPZp6fbttAATt8hSclcNAdgSgOhw8iv2m/KjqiDr3kN9rrclhS3FcqQUNFS4PqjFcorRhqTUZ4dM8/awXg7/iehcbV5LJivedexB3QKFxxhOK9D/jk+7pyBR5eb9L/yctn15J13LxygwdDRqF/meN45ufmxQ0eQYDf589487DR1b797T8tibAQgPFlMN9RXAHL8e+jn0eiwfSyX1y8hxwXJnR2k8EKh/R+ycQ/Yzy14/2y2c0R1EA6GdC+yQRIOjy9Ac717fArA7PThMxPn0MQZuHLtZ1akedimZmtGA9KqiFrCStlRVzzwTjP5kFtRGWQqhV7Q3VeF11sPkKfmmQVQDp6NyxbzukELhW7HzDft2xi9dAt1TZVoO85PF71kiTnQVA6YxC6nSqmVAJOxVUMmfdUtDKKIG7gNCFNMOLWGAgESoxuJA5Iuk1/t/PcNoYmIoSrcTANRPfSsddf7udsstJnvredjem3GeiCzkSfbTvf+/386/Hd8r91+AhB2/zqEXQRHo4+GJYFjImgLQkCBWlh147ffBSBu8YEejqBK7rKEY/hdno+O9Zu39d+/cxoB/adxOsu+8yH7Yk1OnvzrAea2fNfY5fHqH6k5ZefDSeD191mr6baIrZCzi9TuZRdrteIlryIOjYQfeECcUF1cNsnYFUVd1gxh7hosEYzASFEpHJ8yOr9wwTiokqCgiVCIspAmspQG0QFHBn7LsqHN3A3Duj90GGHVG7faGQpoGqrWFpTQ3pprQDC7p03HrHbdsi+tyVKc0UuK19iKghsvVoTdOplFoArtCahEtE/dZajSGGGem7pZyrmjI8BIt5rcQ3U7QGG/duNd49AkIswsDTe2KOXspw4fsoO4aAl/bP30nxZvteBm8XyhkJOBOLxHWmRCAoK6lgvBDKtULoSSM6LwR5tr35wQ3HKigweWq8q6ZYxCCq6gWskdQS160mMG42d40IqPSkdTlsRP0rg4tAqqaMK1ADl4DQBagFqEQoclGuUASMLYh7Z0/+xgAaSHZAGkSuENljPP7PE4Vx+pfhHBgEKBgvO8cFZKlYgbYsCI92Zy2JsNYW29XaorXR7dhw79j2rkUU9RhF6vpx3krIvEPBOeRh3ROtq+njcwEydDCmGPtj2oHFeHe377zxXbeZklQsne7Bs3y6Mwnheo8rsbPSFdNEKD8HJMXvcJxRXErxLO99KEPtPoLMQkt6HbNliLBntJbSULL7jXfxRxQjnBcsK5b9jwzFBpcR0ZKJgSQcJmN987J4jfLDQIbSQEbpjEm2BKIGfGb2XHFYaoPwPtYtnhu0D0ZD61KwtCX6C8OI5HHq308/fTBFqP5YTDnj+1erG388atxSdLHCiEYaNTDvMRpNw9eV8ucU+ASQR3KLxHgBmdOqp/m/DegJHunR36e3pzVLPwRtJVsvoxNTDXQXQsfaR4QVsrCU3z2+v0tceGXaNO25tQDz+XyO8zE/P61JxX07KjHPjhcSvxVH/DBvkul98+c8Dr8W7N8DGBCk/g+LSfeXHszj0QIrzfU7IqrXmQ9GpFzPAyeaz76IlR7BUPJzN5pt9KuViqUtEVkuoim+3MnRI7E7dxQv8dMIJGpAZyHUpiny1nbBuizRXzUnSgmEggA+dwRRC6lG+aAo00DGR5TeUTpD2OqWdx5rK2KZMxLPG8dCo3G7WPSBSJSF0RSlDM9z5/PTCPQeWTZgSjQiJGdQxPvU2RMAKdfjtfLQOzqxGmL1Iu7dVsb5hagDDyVcH2nMHS8QoVRz/OMejGgoawL/e14IsuhUW2tjYnx+k4efR9wSAOoTbhBhUNE07p13jfoyQzhI+akCc0SzcXjEvw6wYNt2SN0sVbponfCbZiry+sY3BgRsGbCghn3uVlO9aErnzrj9dgP3jvVpDUfZbd9Nie0R5mJnl4zflInm+B9aW974isWzlHCUnGKyjB/iNIY1eqQMPsDfM+F5GdJmiTS0Tu9nPoBWgG8AFkGphP2FDV70nJdSNSX9dbc+/DmrWU+JlposBAK4i6WnFY2i9fIrjkfCEKHvCXoipkhkGT56qcUYYj4HDNztnFfLnMMcMBjOyTTWIaKcBaDEu48I9NHuWJrEU4U8L1n5lMedad7sPOFzyvxOmtFJP4nPOSj07PI7Fe8z0Ym0o9aBj01Uu6u3WcrkCQbTPg5exruleI3LGdaRZsnLUeeOv9LEjSs6roLhEsb2ch39vkn03rcix7eFcT8NTOWswFL6f1szFrF0ynqWxXCDR6OBVFEd+NMWYMxVDvRZInJW93woLBm+xrbpivJgJVATBhevRDZwPpT0dRtDXrqSYSj9Ten/edVC1nS+J+UpExEsyxorlZXPIR8ZX65kIo0kUrC7PkTAXRQ/22c2cAvb/eaoGvuWYYMkzmngI/896WqExPw3jlzjo2/f3lzOqq2qE3NeDx4ZXo7s2qPznTHS8Tod5gFgohsDtxodH2gmrVEQ+nTm5/7ZcdR3Lw2dfeB6u+GyrjFWv/704QOevz7HvYFP794v2C0jWjHeZHLiOozgbImH8VxGRsxwkCdzfLT5C6PvHW1dQo4OXVopwecpjmWUZlnfoKyhn6uB5wfNWNqiZX6KZiN0fDDgRHGN5wsbEduSUYXh+0FX1CE9ORP4Ow+bmanun9nqXz7CDS798xd0DJHMMYyP5/ecxKBBD1ruW4CR2OO9C0BIDOB87vz74K8kfT8Z6Hc2Ofy9AXiymW1QR1ErLIn6Xz8BAPo/PgEAnv72E/Z/fNL1T0f7nhKMz4y7nv76E/o/PmGr81pLujeze/0fCqDtfz6CQOi/CG74RXOL/vwR688fIfIF/RdB/etnfPjxf3B56rhd/4HtV46wJ9+m7FShsD0RiOD78vgdh/lvBWpAHgZGCqO5fhbUppHlpZLeC0eVKuPt3FGY0C5qPF+XRUuIGt/avwhK7epkvHfIvmHvOz7/+gVd1Cay7xu2fdda52B0GA0vhC6MKsqbO69LJOibuhA0YdSuqxKRxMZzFahjRQXCWZdJsFXFd1VEaWIFSIqWxYJorXcQehEsXNSYLwIh4PMBQAZcvA+Qj3dluPozcc/Ze51evHbsj3jx/WN87c5ZElAeSv+O2BpJb0yE73gOx1vEntd79/S8c3AC0wOIukRqcKjCEzpb3IzJpy4fUAknae3fYJRZAxEA1YN4oICI+0j+R7Z/OwP6e2uav9nPa3+/wXw+uj6D8Rtt8KIDcL8XUGT+86yLu+t2jr79da88kc7m0fCfr8X342SdoFi6vKiJacZrTxkpIti7Rpt3IxZ+6MSiGsLDCuYBVorWUW8NrTUsy2oKKqAL0KEK2W3bora1j6GWkerd60yzGVYLFU0RXmEe0Za619fB0kMXGnWXlTiJKcM0TCJHaUzMmCuIUwQ6u7XPfh8I8xsPhzPKR+krvRsm9Oq5mN8Z+8vqDED5uVGqT/d0/f/UfWuXHMeN5UVEZnWLop72nLP//8/t2TO2JYuUyK7KCOwH4AKIrGqS0sjjmbSprsrKjCcC70e+D7gwJch10UTMwaRIEXg4hpRk2VmcIzKuGkL2BNUAjP4PY3cwR74A4i+GCVyCMQcswojRWSxHIK1BJlPP5T/Wprsjsj4hM/8761bOIVNLAuqwL5hNXbFiht1g2hTY9g2XpyczHrAeu/j5OCytaN863rz9Gteffi4MX6ZkMt7IFImVKacSnkpMiVnm0oeMXMDmEQT+Hjnij1yvYaRFUfcKS1+VvtMNChLZMDTqE63XyoSgGkheHWFhTTTPXZO1nYA5X3thpA1bKIqB5GnoPDMidbhrLE5Mv9x5AX8JBViZ2nKGHwp8EjBozHMRJlorUYuFTU5AXK7ETWxhGcwiFFskjSkgpEsY6fKkSQjW25Mp41hXLrzwhRHu/m47QVBVQvovNKQHDNQBsS3fZ3XjETfO0hYlLknDIvFRLGcoShIp5lp/kWRfGI1zxPpiuIm2MtolG+Bjkk8kyrpPv+6GsjOILab4M7L3rkqzf/hy6v8731m/fNZbmUb19JT6dLukY/G39IXEI6ujYVWUZTvlz9Jx0hJ+Iz77whWVx6v26Te1ntJlvo2pfOH8DDLy6Ly+hraS7ro2w3gw99oHYDWyxCJ6yY/B2SLxshzNLWwKhJG17+ZA2ffuacGJ+5Nmx/rRQUDVMkM4L9mwuSG1o8vA7ANjmMLz0CNxm+NAm3NzuitZ3qXMmSVhxjGA7s4HvSdqLNmHtBAQgde+9pIdWvhmg18as4hiLe1eOCjSgKOm5LAKGa408SwjFQNUx9G4ohwH8aMZSZmYfHo9vIojhThUEXhVkWsGN1irCGRaCSMlvQy+xHloGRgdYVSdoxp5C9XiPQXAGm0AIM2M3E0gs6Oz7I3DxVTgdtwMxzVF7wJRq4na0SBt88wAIzIJHO4Moa5EV0iW6WCWDTHD8XFI8JQNEo5cpA08T1qFX18HcWaQT5FHbNLRdISyXQRoXW2PHM/X9JRnfpURTvPqe3sF1HN66k6HuNfxCQ1mJBCM/B46wKrEcww3GEiJwnc+uwHpFFwoRjjT0vHTeHmeX+4tJE1ERDFpHHeZy5U0cheNfs+/02gQawfnFwu/U0jnaS3SgTAskYJilMwXHtc+hznuLASj8AqnbzUycBHCvoQ5lwefXeEbj4/pkZeaDodqkSIpw0j8+VS7cZUxxD5MtTyyk+XBcrC219bBOtVct8jUhAIby3Va43p9iuxLToyGKxrRSdOi1nfsRTCzoEE7eDrnUxTE6XwGAWviMscCAiB/XyIS/V31BAGLzF14yqx/XjKHHBIyIOcQq+0Ia11r/842qb+oaxfTzrnnsNw5XXqwJnlG/SgfCtlMTxMOYGzHaQXrwRPmjKIBsvdIqR5bzExC58N6AoHERrF6MSjO5xwFSge2GuxCNPkpcPrUFWunNnadpaXXsiI9RsmfvrjupeOKWfS0XmsQzH3XzIqgDrdcFZ4R1Ym+7XEmmLELyH1+8/Xbk5HQxjRuL2jbJeXiIkt+fHmBiOByuWDejohgv2xeN93TpWvglBx3dSOcQ7E/7RjHgbb1UBW9blBPHZ66geDl4zXwcWumE6TLA0uX9cuGcO5hnSidmIfh09A7AcB0Q4TDQBglkPpFKeejNYGOBhXPmjOTFt3JNQrnS+SER0l2VuNQ/OWe/RGY+xOu+e492jdfg7BRSc754m80avxZddD3ogv6M5fh7LzyxUb0P9rfg+/W21sI3sX69R++jbH1H74JGvRo3c/cyqt9i6D/5VuMn955SZK8OOOH11SgC9p3AsjX0J/fRxCSAOjfv8W2bVDqWtpbXL4Hjp9/SR3oSSuWOrkVca9qEwl9Efz8GVmvWaHcftCbZy7r2LaOLsDmGSNEEbpw8TZ6E/TNnMafLhcL8utmHJ9eAmoeVvv8Ng/c5nD7xxFBhVMnZFp6dtka+oTrMRVt6z7WjAJXmAPexrQtMjCPZvKUAlDLsta/F1yeOtr/a2gNOMpac63EeQBtlmmq8kXqq704VwILLN/jlnNBhtevT8HZEuD0B6+HZ9K+AMgsJA8dV/9l1xdyF0HiT7ReT/dekxP44UF3CpOTm06MAWibEG3mUFHsN+c9YKT5HAPDGx4O56pk1P5NxOVPuP7nGdBf+fxF7+pr74h5RCg8ctWYm+D98PoWfkIEu3vmU9/DsIAzyARL6t+IZKj4AqCKqQWR5eNI+YECjN1vPr/DH11IiNSPKfgQSdbnF9QmZFKyAdZEZc0/pv5tJ6OUEROhC1cYrrd9s1QmzaL4LPXlwHG74Xa7YR6HH7iZChGfaINYrcDeIwX7vu24XHbs21aUpwfgtUBuxw1jDNOLi0fxFCPHskwnpX8IogJ0bFAIBg6INAwZGGIVzSeAjguyJvB0pVEaJNIwnky5jqx9bEy3s/2qGLhB0O8dTEJp6MLlIw6TUh4tIELqbh6n6t540U6MQM37QHuyr55xK5j7Z4OWjNwldPtghJAMqIgndksB3dZUU7iG2viWNeKYBYoboILBjAZC5UQ6X9DQbNEAVrNd1QRxi1Ty+SkiTdhUj3aXw1KmdovIanPiKIrtiDoPYRpl3janVLp5GksImgJNvd3wfrSIKBrfWMbAm8fT/oTLvuHlevi8zEP9dhwY7lTycp2Yoxgsmliqah/ACgqhCXDjYbfMFVNtmx10OkKGW5Ul5Vrm/vD7+uJr7Xzp79nL7/vJjBKmrI76o6cxnqN3YvOAiDheIgztl+W7HhktEOK+1jToQk4TAjfoUGAt6YrD6GTA7AwcmROWuLAaSkktyNgLHoZtPVqgkwL2UwxhNdjXnU5PXM73QTf+NIX2MKY4MWPEURjD5jqeUEoqjdQdjHRRnSH0iFg2E1WNGro0WkR7lYnnnHyQ0R9reRehZxkHx0llhFjNSy5BXYCFh53VKEGhwb6rotTSWhdwjhXOzu3mBDjH3JFQzsm6ZzbU0opyXvVdwhwf4PbSaKmOqmXZd/YUVOR0sMPg7l2FUf73MnvZ2vnWeuUBuX+bZ+3BC3fH4NVoyHObtZ3XJvXgkHzq+8PX5XzjDgkv8Lc08Hhsld0hTPFqXADiH/GyN61EI4I4bd6lgGWkDeB8wElRqeJprCOkpPuY3IjuvDr3q3kKdNbKRjejYt82oHfADczOfVkfM4FOnB+S6YumrtxsZsTX2SBtALPhmB1tTBzHzTMhjRh3LLnTeXU8AzUPfEtTZv3S67oZI7KsTqRvHyMZTZXAC03MQNvcOC6+BmGEJTrHCtOkGapMHe9npnjDULlBp1JMRk56ikJfyDkHXWZ87lQImQxgjoASRrZ0VnLnRiAU2+HoKGIGf4erOcn32mwwLS+heqqtcUxXDDmfPGzOS2pTJzjHcXPZSdH6ZoquXQHZzHGtZI7bt81ghZldFJ7twB3sphvLlaWgqARQz04AqDZMuALJnYSPwyLue3Mn4b6hi9WYtOwItqKqKOn1qZgrBhzHVcSf4YDcjYcUAGN0Dzzz9VPFeNEoz5J0OFbX23fe9kqeWwAdUBF7/zWewA+AwByemyo6OqZYFNt0Q0E1ltOxAxwLj5/SYL7iKgXCMTZfquOw/nViNe6qGyZEYu7WnnLY0Zycbkxo8GOkc2djTl2HuCVlfJxH+c3YPyKyuwV1OabQUHU+4wHtWpR7sRH3+5QdCSiL3T2xsHdijj1lf01hLSG/ysJjSs47eMrSLYpB2mn1+AAAIABJREFUh2d+TsxxQLvFvAHqWRLcIdplHZGiR6iGIcqVosvenlbo9PeVn5eZSCrGDf2a7CaUUzl/cZZIEFb8YviU+G9xDFF/pwO9dTDxWPhnUn4P+Hd5Dgorp5JOoPa8rwf31cca7Bpz8A4f902KUV0Dp9ifAdHu/XoGJclaz2QfV3irk7WBpwwhC78lKpi3w8Zf0/yoeppbL30hbiiccDGmONEonMaI1T0Hii4lx6KeoXA5F/HfsvdSnCIoi/D8Bctt/H112OXhFMB521fg65Xr/PTt5Wrw5s50fesLbYwV19fbWKYViKfcP+PvOKaZ+aO5ox15+lDnkE0gntRch8Rv7rBUxtFbD/mW1/V6BQArydXqniSuGdcXAMA8rtj2CxTA7XbUp2IMqorj5YrtsmN7esLt+uJjOuP4Mma+C+Dl5Yr9smd75V99rwYakK5YjXNguOFJJ0JXYGyLZy7D5vymZRCUrePXXz/izds31uaYAVMQxw1tonnWmCa97IGG4yQd9sa8Ou4RO/NU2PK8OpH12PIyu7zOhtpwsgGQO/gK1J30CH/WtfYqoCfJjjcY+M35+nyWz5cij2bcUMHxX4zKO1Pf/+pMH8md1bGJOpHo7E9Y2nsOwiON8RYT7+8epsPX0/MleM/tP37E+//8R/j6aYoQD9uv0NZaM12o3D9fzx0NUv2HbzB//hUKz9y5fWcZyWCgtu8bxvwWt7//EzcBnn/8LmB2zPfwUAYo7te59isF0shfkNaTtqVTcIvfJORVAaRZtrPe8Gbb0IXOxdOju43GhSyFhjEUewculyfzkxoDGMDRBm4A9n2H/vqC2zQ55nq7uuFcU7ZupBdWX108WKS3huc3X2HvG26HyWy7R5DjzTMg3UoZbjvw20db0+FZd8VoQWsCtIajiddLEDOAzokOi0w3Z254Jjlg+/E7/PafPyfHGbTkAc6540QXpvEPX19Kkc/P3LHjsH2ehTbkj/IA33167J/Bop8Y5dpuihcrYohzVlZAYLJTnNUHh5Woxq0OwfNGpmI/LxNmPLfSaFbbXGSGY+Q5uKZihqkKeAmXqZ5Neo6HcPG/7fr3G9D1deRb/57vv/b9X3J9wUb/LlD4HQ9/CZDp6e9/x1UNLiS24dkVf2QhRP4iem/YesPWN/u329/WuynUXEl5HIelaxxrKiuBHVhpPT2/PPp8v+y47Bdcdiv+N1UxDwVrUc7Da4W3hr33jOaBMcDTaxuKeo1raRAMU0AKoh4vGdq65stnVageUC31gyMlqsRyKBDRLVEzUFfE+JqKYFlsfzhQbvwnoUOnQhuFchhL7YKyFkaYAhw97AEXKj1Vi94AuUSWNO9YoS8IhlpFlpyHFn0DTCc+lX+cUQagKAHidxfO+QDM2EwBdhV4JgYjcAQ4MLCJ4BBBn+LRYQpFD2eHqLPlaVSBC4xVkDtmy5h2rnDdE1k+xy6L750AFrXlnopN0PqGJt1hw8YbkXzqno+iOMbEGDccxw3HcVj5AdYB9YjqrKvK/gtTCFeOi6IV+DPF+ow1sfVLQZMNvoZfz6Rdo3/ekNOqfPq6x+uvY3p58MSq1s9PVHY1pgj0wUrUEViZ6pjMa+N5mNajOE3AIyYW8BACdygA9biBygv+bI9KCCzqnIkAJWKttlcjkcj0rWv1xZcIxL14Yxlq+wWfiJ/JPK15fgPfz2zD0tG6uCLFqQC+1FKg1s947klZb+mh7BpTIUL2ZWZtc6zRQtZkMQ77GHUq2raB3q+Si4eYXllKKkza1jGPgbbZOrXGh2z8XTw9fbxe/leZWL8iStbn1RZrvEfc38Hjg/0lDJ0yJ3AMy/k5K/78ayrGtb4OnI3rzF/HdO5hRNfoScXx2NrTCk8aqPpBusXPX7nqf+y6zzzBVoE7JHBG+XiwC1Lmh3WuSRPIE610gg/lGTjh03IO5P7H8tgDILu71t9znwWLd747c7QKPz6MBjegk4dyfDXnxJAJRN1w8kLGX9FCzpTmzDTUj8OVrsR9xGfiyhcYrRbHKU3MuNndmUhgTjM0qBMtuoSYEah8psC6wiN31ZVDjLS0CLdOw7YAx/W2rPHUpJutubBIvrDycbxfxhHnUmG8GWthipjznvNq4hHfdcOq00Ig0fgcDxp+K4pggWXVEEgoygVuHHeFwSzzYeklGbrCX6F5Bg81/bMbmoryIWq6+34sbXD0AS+pXlHA0huKGTPmVI+iR8BRg+JwJY5lEECkhlMoxsHsPU+Wql8m0NtirGVvbdsM1ztuY63S4YZwOjncXuxz783xY6nXqhp+bNNLMjVpTFqSWUnUjO/H4edMe8oBRduxyFFCuLJF7M3kkaEWgY5pvPy4HaY8/ALEqqrAbkYAzHJeDTBtD6qCHUGuYDIWs2wx4tsdIabVwBOVkGuGvyyzpcEh2qGsQ4nHUv9FXdmXCbmQtjvubwqepnBWhniKZlv7dFZL2E5HMn+/8HWqdAgv1IATLjBTYXaxNPH3+MnPeH051rMeWKf5QKbRxSni5dR38n+5bnf8rJR/JeV9oVR2VqadCyF5D76kUNlP0R3goaOZIDgzG0bJVsKIT8VqRJ9jBD6lYhi1DAcjBypSerimX3o5bW7Nou2FMpKne45WJfDospxu+a4Om1LH5gxagAnKlpTl454HvAABWyLu9DPzfmag4CpzbKmTMdJlhnOOy8BdnZfzbAPlv9HtUiKhrFaFu5OceOY3lVY9tc/RIos83/JJ3WyctY+gr8kg+V77WMXHp3kMHx0Ba9PfCxJOPtvovyzzL/2LxHlmlhQSkM9j2NeviKDvDt/w9WPt9xwOgPMurPflwQMVh603z2eFcJEK9/vOUhNlDiCEw+yJeqMxjCDrNMeI4ziw7zuu12sY3jRfTtxbeyO+fcDTvry8uOMeAPF0sa3hcmlQFXz8+CEaS1A53XCczgwyS/T5SQcXn90J8jgOp3vEYQJ4LWOdiuNmQG2Gsz144w/vXqBQ/PruPfZ9txIEFSk4/9paW6qTUGfDdWqSqfKzwKLzzoVWpaznPFUicqPDp/mdjen/7mvAslH13iDfvLWZ/HLCneUfDehH+X37E4zovP54Kw8PFFY0er/2XyTOfeZ61rV3QWaoBN5jlnEF5haETCICaBO0vWPD74/sN1Qxvazpep/jqJwg+28/vg057fqfP2H7y3cQAOPnd9j++kMGG2mu05zULUu0LFBcILg9ks1ReEkh3V6fWWR2ofzYXQa1DLqMPt+2DZsA0OmypPH50i1D2rZZcN/lsmPfL3jyQD/t3ZHqBp1e7kuM9z1u5qw7xmGBXjrTeUQoy9LobSdgDpPDVRXHnOjT4/BVMd//igMN2jsu338D/eU3p8sC+aeg3cye0mdDGx2tDcvbqoqLiOOdlbbY2v8MwHiMDuZ6TaeQMz1P3qdqif44Nf2vtPDaO4lPy0FFRqJXRuPfijadHhunlXT5PCSS7WW+Ih7AEJDvZ5B8r7Vivu0zdDT2jMKCHewAmrPzdL5R/baVVNPjCNkwshQWTPS/8fq3G9AXxvvPAMATFFMkfZCkt3y+7zgYvHLY765Kwe87Xb/K6Tk9P/f4+Es8Ol08ekXJfeL7IpDHkX5NWY44948Bl0LEo6lV7zkeBvHPCEJzPxuFMcQdDZtY+pJ937xm+Y5t340pnIIbhjGiXvdc1V2SpUWquyZmiOy9oTfz/mIE+rZdsO0WUYLjiMiEYLJMi2VEjQQMlv5p6geodohTiSaKm3pdwq445App3RGJR1nMo8CJpzqfE0MFZnw3pcDWGSUqni3BjZuaHqyExTtDSzmq9/B6Zo+KcCgSisKMBwIwBbOJ12rLs2dKHlfmxuYNNJgBWADIhYjV4UyA42XEvqgC+rFEaYUihpOpqYoAEXU79ipMpac/0+6ICRiNMTeesUBh+wUFTGVnitUGtCmQjaklAZHdT9KqCDdmsWOMDziGGddDuaOp1hO4y11M5bFXvnQgFMlRYsCizHs3pss6tgg+CIUkic/Da55fr1fcrldc3Yh+3G4Gq2MuKam5f5NGeZ5zKu9FAl90SHilNXQcS5WglcF8dD0UvOp3Gqc/2cr91f2UTqSCT9nh77ioKOKa8l8oYwWmPFJP1en4cJ231AYBwGuVw1NcAqHMbsYoH6ea2UT8kzVZD9a3dXiiYtz7ak3QNisUFUxnjN/aEy4K5xRSpOCsMD+TnPuFyvVC74BH1YFC/BkRae6tYoWTiA7iULQas00xO8ZcFefEhYT/znR6yQTyL4O3bH03hKEKHvlXiCwj2qnGtGhQhDLUjEfTj7Jazq26JKRjZJhZA90VuiB+RSQyt/MVqTV9uXy9oiZVMYwAiBqtNMgHXXbhsHufOpbX7rYw+HspdyVY4XWPkPdDmFki319TmDv+ExqnKLzRYCSBZ7IvDXi9xxGJj1Ys9mWXxO5+8iEO/eH7r752h/9O4yMsnuH03O+yH1K++6H9kvfOP+eivXKof8cV/RHH1CwXZhSNIgl+vBhA3ffdDOhFoTx1ojVzIFmMXy7ctWlpu+cYOERwu92i9i6mou+b86gufI15GivPUC+KjJZrK4hzrWRsHJem4b1582IGuFn2WxEOAQIbk86J0buVZOjd05g5TSVHpeoZianUSWMWeQjW244we8chNNhN53eNPW2Bhy17ThpGQnh1xK+RGQRAdcKkclfV30M4YmX0s+/NsDJHGANTaKBH1ARnnfhq8rZtr3iGv/iSMCWpYq2/GqWXDO6qG1ZVAGTGAnj0t4PJoZ5OXYlyzOHVDdnq67+ctTEg84Bo83UhrJS1MmYAbevoXUxxBXMumMfE1IwAIc6fN3MU2fcL0AT9GICXdTKDHCNHbS1NXvF3oRgevT51oh2GWxWKEXD+6Mja/8yxRNGlOaEQDHEP/5fpTE6/b+DCXZJivLL9GC8eZT8nptg4DMKdrl5awp4At9t0JaIA05M2KznxQv/9+9abRTGUFLucpc7pvHnZf0ct86PjkWsx7kMgT+Jr67Mwxjsc3kz2Wp2SAVO02vP+XXWJmNHz2Ggs87NHmWDhf6Ap5ji/pmQGNPlRb8CoaZPgp6ymq0Io79aW9dxXDCxwDEkKf/8Uvxf77x+VwkLQy/r26bd6URYK4iCrHoeOCQYQgEzoNKfygjoNN45hjh9iREa1Bc6ac2DRV3L4fu+LyaCcPvN7A0TNeN6kYYpCZJoRf7Z81fc1nCO0xDwGDJbmJW82PxuVJ1FNOazmHxCvYSyEH3FHfGeWq8HcMjMJRtkzqfzGjvR2vzr+8Aj1RtpAeks+jUb61xxwOC+Xe4gf8lNedVT1uyos/bRaZHrgUwCyGcwHv84W1A2GFWYn9QeV8eZLaSS0Y+cGelfwSlKbu9Ear1M4U66hrGP60usORkm/YY5UCmBzOeB2PfwFAvnjRhauNJ4P1iIncpplb5nmN4YC0nNZ6Cffdoxrz9fgCJBWcz4r6eUYh0ehBfEVtmW0SgQmVyvcuTkaP6/cPX5TpJ4QwPPzV3j5+CEjCBXFEJ806uXlxeqqfw6BuPPccbPMf9Uxcd93sByOsRATxzGxbeaAqWOE02JvDTqHZUpqNk9RwbiyhExH6zN4Qgt+WLe/CXHmWGCw7uEs+6PBq/Gbg7+fnVhT+Tcaz0/wza0fELT3v+Hm3y/fvoW+/Rrt3W/xHEkL3xGYYWOWJl8zon/pbBX31bx2Fdy+pIVCtD6jVqsv/Y7Rff46UfPIpFnxh0AgPyDOXO8dZK7mYXqh/S/fQ/72T7yE4+LafiWpKJ8//P2f1uwJn18msP3lW3z4+d0DfCp4en4y+v+jpZXv37/F/Mf7WJ7+HbDt3wfP9vHndxAFnr7/BvrPX/HiC77BTAcvlTaXgSSqsZm0ZCjjQfLz8ExpUX5229C3jicvH9tF0Iad5+6lvWTf8bQ/QQTY9gt633DZLXjQyHsDLorerHSUlany7BYYuI0DaWj24iFiMrrOid4E6M0zVjTcXl4MR4yJtlkG4wkA739DQ4N620cJUGzexuWbDf3/bWjjQOsDcjSojHCz604X4fxuU7NOjX8kTb3byVdwyz2UL9TjdB+v/Pb5fs6tnMdw/rxkt5CMRF/aCXpyP65zP58e9aNRnftTx/1OM4knHQH2oBH2g1cQMfkjED7IaCKftufrVAhbAFxuF1A+HjI9G6g7tU4BZAKtR01zBflA4wXmmGgABvURZV4R8PC/9LIsJ38QUedB+dT7jwmBUgnrwsirxvPY1M9fXTxNyP3ry0jOqUf09O88ZL2/dd/4l5zvB89L+ffoOT19/9zFtl5DQ+uTj4ZYCKMC4QlbGPDqvR9CimSvqWRbvzd4/Y9Wa5bbv94aujhDohqRGNNCIkxB4ik3m4h5pXdLRdI2poQvdUi2NMS0OdHkiFEx0pfRU1AT3gFjflU1DOjiFpHWGnavh8600Ea0pzMkNm4aXW1ZxBRkrjS1dC8PVlztfUYzUUFUkgguz+c18NlL779WuSRTNflNT8UfKT+UEaduiL8BsieCnUovdmsghFpXnBSogUvv9qQwEo3fbf6QCjuEtVT+8nswPsoz4tEucdPqS/VuBN6QPryWlELEvI4zSsrSkozhtS7d0Hd3ZAshPeMQoDiuwBkt2dAc1rbNMy1sHVvfLF1oUVAQ1gGLsB3XgTEmrscVt6uVHrBaOMM9Q52wx17Y+AZyvpZ2SCim59qpMxsQHDJOiHJlKSqjWee+Yv8iHMSefhnerl0KxBWJEgQYlaC/Mq4KFwJLKwtkvVhpDU2NiJsCyf89MvYJYBo1zkdPz+EVok9jE8dX0nE5Lq0RkRwy18uUqd2Mv8EoOUPPc8BVoIJWc5gZIfGYHD2mxD5WttXaumdlo5niicJEbUzCiPUYUOrtibp+BSaXeXFA5UVBKrSMm4w595IbgrUJ05lLY32tnXWMIsbkbb0YG6R+0Byino5KLoClZlYBdEOkTHYkGA4cVByX/a1m4DRkr4yPtOXucg7Oczk/F5At9Y08K5W/WY8+n/Q5RF9uRGdbpP3ljK5r9Ljv+37WsS/zOn3XuCtLf6/D+OPr9yg0RJIWp0PDMrGC9Or9gjOEbZ1gkXQv8Ev2yz8L7qv9nif8OxfBxuVRsUL+yDIjMFqb0V/iCnOBuOJgQ0SJeyYdAFGzeKg6T2GXObxpRDFwHtMNyNvwqHbIkiFAyaAU/t4UGogyQvGgKoQGugLUFYM2xx2R/QbJ53A+ll5WMWeDzImjuXuXlPUvAqFMj34VRF1nhazPF55CwLTnQHDeTAXv8wDghmLHLcj7MV9H3lHnfY5I2w2tNI1pB1sof0iLrK0D6A2bR00H3gL8vBcnH+FvBaYTonxo6il1fe2NITGlS6HXFnnMDECFefCvNIAutabB12t6VXPinPafODPcdxEAY0J787Trtl6Tka9O/4yHb2j7BlFgXA+gCwQbxsePYI3tgEGP2hWIKQilhaKDGUqaO04y+nzqhB7TsiPiBhGTh9As6tWcDE5u32XuTdwB1iP/FYB2FIOB5p5cyruVZotCLzAliMstGtKMZ+9aJAbuR/ILUHU+2VMAT3JsaYSueaJsi6dnW6j8tYYjAdTljysgl9MSLKCvniksk3US/9Cwa+NY38t2cl7MwsXU2KcRh6OBXvTUDvkzghwdWjirlcAww244isinUTXHEHDOPvx34RzLb3wvIOBBtCkA18GUbB+teS+VFpW9vxtcYT6VOKq98ng6YnCsVVeTTkQ0oDOd94BV7arjWDFN/YUKxUyF/spFVAoYOzMQRnRVc/yRLua4VBMYCYLGCxKOhI5T/h/xxpPPlZLlzf8EAwWHg/KsnwFxBRkz+gRc8vz5d3U6RyeOnKZDC3H1a8vxGcXzWddX4STApK4tbykeg5GPl7oOZYVM7sthTm5zR6Rlh8I0loef7S7A4bRKUuUtpQ/JrurQQFl48rfgy5A6kdjzMsGyZ2fx5PdcSXOZveOUvCE2+hEGWWdif9bFtaOZuOA8TNbD/oOjLx+1JkQAoNjaFvCpc6AxnbucAWAB1LwnwDxuZkT3dtX74sPG55gJ8OXjwPOzETnZNq4ALs/P+PjhQ7bNhQjcYP+9frxm5JwAl/0CaYLrxw8mhyJLOoxjYCqzKwn6vkG8BjOzD9F7c4zhRnTP7MEMcrCo961nmUlbr4nWTF80C6BZFiKgadIWEZYoU3QRDD/fNGyR+9TSCgDPOMjzm0u/0hdC3aecYf6M6wQD5RoAuo/oCs945YhdJDmjEeOFj12RZsY0EpMb2BQ4Pgn2+srn1yjhl63Ioy4X1UbB54mLz4j1j13r+qz/Ho0x8ZpGFHpxa8T212/x8o9/+jcsfx9zDOp1z2XptwHY//p99CWn+cYY1J1RYPxK/8s3gKrrnN7iuP0EkW8QcgAA4FeHGVIq6/dJ5BQqhHUjXuV3Fo7Kzx9tGR3PngW3t44mCp0WDNS7ndO+WZlay5a74c1XG948f2UlZNX2e99Mlj1EcOAoum8roUo+O8ajAMudQhBZrkwPbs6Acw6M0TwOn+UfTD888YTbTwf6D8+Q9x+sjEfrwLuJndnlDrNbNOrdCjvZf/wGYyiaKsbf/wlaPlplOYuczO1N+xGCRq9QuvKpr5+Bda/i2x8gygG3ujqG3J3AOh+UucRDf+S8Vjz4ubk+fu781rlFefTwwhNJ+X5y9FmM3hKGefJKBh+e4Zk6iMpTAZ7d2fWfEMDPTup4Hs370az+Z10lAv01oP3Edzn//ilE9AAxfVbKWXus3x8dkeHeFouQXWBO/eU6kjOg0RDK68mn+eG1MymnQ0YiqGWMhaqQl4s5lHMhfLFcRJjJDJ8ZH/8sKVxVpol1N8I72V8Yznx2T/khNPx6xAINoXQgl9JhKFWUNcoeG8yljMaIGVyBZ0aiLmY434pxWY8Z3p5mYMxxC4DWjXCxTkfzSJq2b5C9Q7YGcYO6efYaCbUA9jSote7/JCMLp04T1vRqREtMiaUApE/07Rn79uSzckShgKWWcwba19X+r2H07FuH7j3XVUu0OczoyfiLWGoFxglepycnYi2xM4O83gO21qJdFUAmoF7fsuhuQ8iNeUVot8OUK3FVGvRmv1FJbG8VZTcyslZxLbOsZInjVJhiQB4a/szjzdPTOEPBPSMkwhG6uttVkxa1Rm9DgWbOE80JQ02RJXpAANx0Ys6bpdQcB8aYGDoxpjHfg8qeOO+Lebesvq1JhxtD3SuQdRy3raP3LdJxT1cciQhkZspPVeDDx4+4Xl8wDkt1y/vRkyAI0ISmUtKzQmzdjKHTT6Cg7pnvQcFf1dP50XXHTMRdWb7lzn3+OvM6c/nLeqKfIxMSbZGxjXquMGX2uNk+m/NNj2eXCJGG8KxPQ7fPJRa+Ogv5c8g0Rbw3x7B0sGOiM8VNMJbO/EP9nMGZCXE4bUWbYgasiMaKWsTWV6bdyUjfB5Q25ljT6ta1o+wvyDnnz5Lz9t+0Kmzc8CbOXFWCS9xq7WukxDUntqT/wZSN4YYxNwww7LAMt6ZbnUw9RSMfNBRgQO6nVOelskD0VRBIZG5Yo+qt00965ktJVe5whVMq6uOWAlEOwujZXRQ/EA5dZRPWT584XOxFy4NpzstLy7MGG3V4uvz+xdyhw8iq4jfAX551dE7nq6rO8118ONY6xyqonX87X+dAqnsh4cFLd1fSO+mWLWc5l8SlijQ88k1ppzGutDDV26cInvL9EZaNr+fxv4o0CzNcgIlw35obWcXSo3ca0D2Vd5SkFSoDekQ1zzkxhq2JOaJN1OhIGtWIgQ5HOjonjmPgOG7Y993ryVlWIaGnc90sMiiKdY5R/9H7UUbXAZToWHPa5mvpv1USPsijdncgMFvmxBBEysA5s306XCrotLXuEPEHkIb0dEzgSIzH0OHKKgE0cJE7jyqVQD6fqUCD0fMJayHmDVPaTnWDvQIzaR/nt/Utl681yww0JlQPpGezw6ppcBNORcrczhBWpBSeBTcsW6YTRFYD9Xonc7qiSxHp3ZI/nF6yA6kvaj1hwG4AOqGePYiw0WDRnG1zGaPN2L9DR9Rkmy7/NGlWL10FHQ2Y7gRCmuIG2nGYwadtG562Z1u/4wA61b6k9xbNztSN9NyfcxpP586QrXWMrbtjQ0PbdkhqoaBKFw8NZb3tRHNjiLoDly26XBwDU1vI8/PiRnM4zb3Z+g/1FPXwrFpq8giPW8ZH2+fq2AqoOSZKCxqS2WcMnrs0r309s5a8p+QOvBC8wIzzqlce8jOl4bMuS0lzpQ4jzyvKSOPNpHzmfFSmd8/MBNPlCPW1k730fnvAXW1+RkgLgk+6p59GVyXkLdbKZaYHZf3hVucqkVqZPQeqq/y8RyLYCJ2KNufLyP4Q0THytJXzXdZrHf2y4PmZE1seKTd8HlWmxemTTkvtOsfA7B2zb1AxB6cBjSwLFq3frPTCeX0XkqbrerPHT9B340ds/4LWNETtT3EawR4D9r0/FcvkFhl2yP8s6yLRl4Kyma+L1GXlZAivCrjhTIlvBVA0oDFS1WS3woRFg1/C1sjpLz/r+WbMGgvzuLLnEny/cBqKAn+nznSNFM3bhl/1xnVzHuKWvKEe1pBGC3yywFfpLiR2zbFZu+4ctjDA2Rpw3qNsOeZ5Xp8HKx/PKXLRiC+PAwOC7cnu9W2zLIZHuCbdzSfWQWtD55Gf8U8ZTXVIq9MOXJzrQeMV8RXWn+Mzj+ZXX3+da6R1f0z3uO+XZVGJn1uvSVFtNb96+xYf3r9H1Jx/YFz8+PKC56cL5riidSNwbWt48/ZrfHj/PuaYMB3EZt1DBa4vV5z3b4lAdEcW6nLUeVhpLkOqRYaKWKal7kImHfZ7Exxz4vpyxXYM9MvF+p8KZR1zoJQ85DJnxk8F9Tyu2xypMpgQ9GbQQRZpzjTJB9rWFZ6InNJd6wEm/RKE8kUXEbjWTbnrpGrZ7NgIFMPSiq7aAAAgAElEQVR4HdD50uCEUGbpo1dD2AYznk9Y5LgCXxY97u2RawDSMH/9QvvF+hBlgMdP/tlZAN6UIZKtaMqiHQkzZqJ9u8ipwUPwbMNlHFNcAkBkKWUfw2kgTzH1IoVceNtAV8u4UbP9bAps3wuevvoKTRquLx+N1/UAu5rxUyczcH6D4x+/GK748Vu03nH720+ItfZePYkW9juahqjrztnPqegANi9zKdLQPchr0kdQgCcIdgEu0nAR09s1d4iCmsy1bR4wKMC2bbhsHe0m0Cf1TGcepHe5QG43qJpswEDB1rrpo70GOrwfCwQznkgAi9Q/bphN0N3gwsj1DpPdmwra128w33+wUjXftsi+1LRhdgDa0A/PlkV7izbXgfu5cga7N0l+OWiAmN2isJRBlStTUC5yiGs+GD19x4Pv+b6c/qJ81rsezr/fX7Xt6tx2V26gzGId14q7Hn2v7+UYznxI4Wi09pKfabdk/E04O5R2HqMc112U00l96Pom6aWzSXNA3T6oYPCeldzi49IblBmaVKA6osSXtGZg3MRRyWu7cF6L/1nXxq1Lucq3OL4jfw9Czuc1/inJGD1mQeWVM//lO3OcLst1PlO6/sS/ZIQFCORIby1LvTVPDFJhFqQgcwqQ/r/pZkboytADit9i/85E3oWFM3ddT3J5lH8NUZPwO4PUqgqViD8GGwgr00d/GVAl0jr9QAxfFCNVhlZnsG14EotPxh1whVbpgPvDbK5Mc0jCZJ8NKXaBKZYYOS5k2ahMGVmbxYkBDyr3pTVAtoZ+2bA9WToU6UbdhhocaIPXbtnQb91TsbtCzZXAFrWgXoPNU2CrKUybCmjFqwoZuwaAGcbROQcwJaIooB5pEnMyp4Bj2HtDFUNTaXXMTKqjgEWzaLKyZfOAykiciZG6YhgNUyW2n97W1A00tVSUzAZxBxoFcBKE1d5dDAISh8z+EEsc4XXPCALVipjdkOjIN7pVmNGQ8CIETl+PUMIXMsWId0VRqNnaHtPOVBNGYElR8BmCH2qMy5gz1koBj3J1xaALj1S2no9UwD6AiEX2Y7u1DZsrrZvX7ppDMeYRQtH01LP2d+K43XC73UKhaftiDcaanPZIgcDNNIg3nRg+Dkt170p7Tdwfio4ymwCBCls4X0l4V/z9aIU+fy2oUogzZBFg1mGlU0QaRlIZ0twwwCjI5lFgj3Aiaf/9RXiO5T+NGAG4QiQJOIPPmpKmnB9YmRrWgaESM6KknU6KIz4pUZaVOQt8/VqqxWWoj/cj7eJpdFrWOtL8uZGBfdMBIZwQCgCpBrwNRjMicQjpXl1FS3aSdERABYLDPJd54U2SYkVzRWiyJyRSums+cr8O4HywGLXvn6snzv+2lt7/XSK9d/IulYvJj5Y+GuGxaR6dLfYzItJPwYh3Y2Kzsxh5/YfGB0Jrj6BnrDes3gdXjrAVjjdUMAYPWJ3rxAVp8mUEtaLcLwtHeKv7cj6PxP3LdyLUWL4WAsNrF0G+PrbC9hecm6W9PHVNCmUWyXNB+C7r0Vp3Q7QkHzVldZQpA5VcJAReeTD+swKqCoqPv5MfQfTHfWjdomC3ZgZs2Ro2RsK6w5eIpZlrnu2n9x5Kn+M4oHMszgMi4nzM3cgBtdpY8BqUQBqltz6h++bOlg6sLYnUUEUbw/norMpnfIkpBeYxjK/wtHZNABkDHrZuvILjIfIH0gQ9IogLwJKPcdpMwGoO+4Fx3NjDKCSdE6LTIrGkYd83c1p1JZ6lJlZPVT/BnST0MMqheXRoOHLNCZ1+dimEKow7m64IEvWSGOoKIEHrW6QVP4YbKQzxOHwCIltxQKh41vkeVUDSEFgjCuhQFvJErJtCYHwZOUd1BX6UylmU81pkCyul9JDuYgaudBto4DcF081ZK0Mn2gR0DgzZMTF8Lyt+cNljuEFePTuVr8WY0/cC7uTRsW8baN1XNdUtp9JdSWDlqWBGr8POSmQTGhMiDcfhWYr2juf94mV+bPDm1NIMltEAmQD9i7XAS2uYgxAE4CmWyebGCOp4RKFPCrzkKxCYs4QrAqNuMF8NdF71AupnzVGSW4HVN2Q6FTEHOq/xrggelNF7qgij+ZLpDArKQkDis+nPzsu06GFfDIUA08a+sqVqIW27mnPBHpC7LMu8JUnSW+UyFopm8z0QTgmV0ATKk/I9vlLaXQ204m3mqA02EFS6QKrzShHZHDQfmK5j4e9sl3yxaH5Ontv7bK8wG0o9DiciK2G1DcWQ6ZkRwAR2CKK3zsCcruaAOP3ofTh+ymhNZmsSmcB0hxHyeBUpOF6OlSqG9sqbRlaodeT514m2bF6OTZ2yF+Yx+ByupRI7nhos16xr5cpH7tGM/fB3ma2KODdPwZJ6V8srdTbn3/MirV1fIqzXvyvPdG4oGbZcCwWZQvG+ufVxwgJfuMP2ieerrZcu7JR4xgTy2fGPa+lKvvIaagr2s96e50krGBWQFn9JcxA5LufbmZ4g3lGajOqJWk8+n1+ycJHf4FicgPYuFtThPEamSq8LVOUp/i7reGv/4hBUgTU86bUM4BOXvv5ZdeLjr7/i+e3X9+9xCCI4Xq7Yn5/tXJNhqG0KnS+Ntopn51nOCZQJsfDy8oLLm68w5+Fl/uz356+/xnG9xgm6Xg+bf2QsRNAplnUrWrgcuPdHeN93o/vzmJjHgamKbducXkvgn3EcaB4Z35rgGGxWMA+FtOHoSSE0dDv/Rb6DMjkNfQGEKp4RivcaWnF8o6MVR65oHtntzosO35N0wTlq0usF/nlwi65Bo+UH55fLRrjCum8LzqXdwdEsdXz1BDHHR2sN+s3XmL/86qNNfnNoilT5W+4m3RtTYuA58PNaxpEzYubLHItA8AQ1I3pZYU468GH9iYBT16nyx8LjJ8sCVjr46Hp8P8deHQAY7sYubE0E/a/fOw4xx13qdxMXuh5aEtLq32VO5W+UBuG5cfQiajLKWgJTsX/XCJ0ODC5HDXOpEiqw1aOsXRd6+ev3GH/7Bfu2Q5rgqLi0fI6MI5ACxrkeHIeYJ3UR/XgWFZepGM107F0VXU2XDp2QoX4K7f2tN+wuV+/dMrZdtobtuUN0OK4xB0JVuBO6O5iq7R9cbz0wzXEYGplHq/6N570V/GUn2iY3deJQQN+9Q3/7DfQ3xXw/oZtnstAJbYbX5nzCW1Xc5sQ4Rjo6ck9Ic0SdH3No41+urO/1pH1HDQj8zwKvlVY6ZX4AXedrPX+0liysFp8q+Lu+9eg6v49oM/VqxM0aX18b7xlHKBIP+D4JFl5NQre0YEkwMafh5mzfWBGHcy38WJn/eV71/SUTsdrap1wx79/Ngfp4hjt1e0YdccdmvhkTnGCOkOqMV/d+2U9ZhnlHZ/7d1wboKrAtQitiLhqbruV3I+JmK1S3t+pnvxOawwQXwMNn6lUjcOi9VaJJgVCgWOotJ5v04BWrnddcyceN5Jx1GCOlYcCz/z4p8BGKD76BX6ngYxnYonjV0/YTCp0YihrPWl+JupIg2yLZZhiD6jsUDEqqMIQjWO6XK3euAJ58zxqQHkGibthRF8ANqLnr06MfA4Sd6gnXDcDU4QcWgCs4bd8qG6exV+K72ABg3OzeZccmgktr2FnXWqcREwzvNwUj7lckTNeJBos437+64Pmrr7BtOyCK23T/QyeAfWuQ7Rn9djXDeRf0rVsEfG8YXucS01Q9Uz0poAKjTfTe8bR/ha0/udc3024ZTFnEzASU0cvDCcVua+np4KaaRxiOF8C9eQ83MI0xcYzDYL01KNNLl6gkS+t4AfSAV0kM+HNe+wSLFv3eIGi9o0tz5YSfS/dct/NUkG3lnEI5acY8dTZMHV5TwPFWFYBHyTMle1X8NDI0SvcRcQar+EAR8MXno+qRpBqMNVPAB3PJ1qgsUqtBP6FW0xNWZW1rE7I3aLezoR8GBIob01bC/NmlN7Amnqiio2FYiDioSKrGFHEv4+bZFHpvzv8NSN/w1eWCzZXnqsDUA9frC663GzAzE8RUxW0euB03HOMwpas0SFNkrbmV1VDHsezfEI86w+hCp9rYF3Hf4YURHzau9GpPdCUk+8maFLz06NJFyXF/SRnC2k4KjCeW45MX8R+zU/R+sRq+mkbtrFE2QtC9U0oGjcnz4BOCwGqbQySU/YxKbA0YB4Du4NstIpMRbWN4HdUxyxqmIrB3E21629zYL04HSM+QdXnj/FQKwlU6GRoeck55tKRuJ4UZP85hRHEFRitShnm+F+7Gad4Sie1/mSp3uMELakY4M3howJwIsO076NEf9X6c/xJFGL7IK0AIl+6UAvcYdg7+GAf2/QljTF9PtegAGqhPAi0Z00w/60xpGOA1+k6YpHHR4V6MD1HLSXtadNz1S8ZZVDBviomRfFco6tjE/XkTlN9iA1rwrfUkCsxIRmdCcUOJSDGIK6CugFqMXeS5FFDxulkhaFPw9bG4Y1T43FLwrnMRCeNoGBCcp57E6Aqo11sztJbzt2w0VInUTdTy0fuPzBJJXpa1a0VcOyvyQqlS+3HjfyOuS54N4Bm3ufUu2PqG3nePLm0eiek0zWlwKHuLt6edJc15O84irY90wQb8qZQvZ8OakNhDne4oRvjwdXzaduz7hm17wuWyGy3bBKKWscMyNACXpw3bZpHirTWPID/wURXHTbIGN/fYzwKd1hjFIP47HM9Y/W+mYLa1aX1GCY5wzFM39oqn+B0Gf5CGTSzKd44Dx5yQm0Bk4LJvQO9ODwdCieTKCaEjp6fYFmXds4np9c7nHBjXA/MYAbvSOxr5E8/SE5G7Y2D4Wh+3G3rruGzPDsuKMQ777RhQ5xlD+ddYL7th37bEtcwE5JtbYgICdxHAe+uBuyyaoHtQ+sA4DhNg/UCaY6llFGhtD/5mDleeCAAx3tei7gGLju+Oaw3LzMhcJB5x5Q6Kh62hpblvIUpORiMPymCJj2IenqlqunHagu09+lLNAViIkL1f6ERXp+Oi0OaRzzwq08oJyf5kTi23w2BDAek75jwwhkY/4+XFz7hFX0tr6FvH1jr2y8X4gDE8LbllniLecP89zOMGMx77WFw5ZSV5LLpn23c84QlPT2qF7dR67a0bb6HA1rvxE55tSH1MGuvWAh/PazVWu9wCYMpIzuGmPkibV5uAPlXFa8JY4ktbSPPnJjwkjmRkkfVtpawoLwWO8/Yiqk7hxnPrs0b9CRpkF+DqCJxhRFejlfri63BxwHL8OK52jyNvrZkTwQSwpZGjdLSwNPK0KpKZ9UScb55A6Cy0KIOp2J3u8R00OGgiCbMrXJmes1lKzKk0FNMVOtcFxF1AifIhLRHUEADz/ybzRE5RLfI8vGbV5M0TL7xcvm8L307eOnuHjiOU3MZLEB6524mnVIE5hukkBtD7wOg3k5M8Jq57WlIAVjZFBxq6l6cS0NGaNT0Z7RrG9c6OgqkNXpXnk2syHZ8aPjTHsC4SpdVCFo0FSJ5L3fmZP8SYg0/nPti4R8FzPA8130P2ZY7QLK02uK8+jnB+jjPqPDXgWR7socSXpmchLlWlkwDAknAGFYSHvGiME6zwzDELEGPgjQpNAV3+nwZgdkBGMWbkhzDwEaLJm6KObHIPEkMRFgEnb64HgFqEVvDoToS0wquQV7UVmKlgc9h3aHHdUov8/tQ5lvHfOTX7aXEYbCnUhKwzP77YurUGmVaHeBBnQkN/kute1/u09stw/AQKAFl59ZigltYoe2nOf+E1+XIFCrbkfJ4ew9KbHzfnNw0gzEl8uAOaAEquh/AbDYXc8PW3XwMK3F4+Rme368d81oH45cMHXJ6/srqrveqe3IFPFdvWcL3dzLjn9AlQN1rk80lHLHrTgj09Y2cXi7AbxhPvl4vDuzs79Q4dR5bVe3kBmP3H4UrhMgwa5riF0XyOYXqmCc9OaPtBh13x/cm08YUG+TJWugQFOh1busPZtBVRV3QSi6s7M1CWpfGbWYHYWcUOK10juCVAhO2kwNyMvZ5LG5zAE8Q0wc6zbGJGmTC6iKC9fYPeGo5/voeCCUMMjxMXGe0s9Mn73wBsEK/LC7wIaYfLVt7CrgLtniHQW7G5061cPclPgRn/PTYGBcw+c4Vc2nj+OoiXSbriSC7yqC73pgLPCqAx1b890YCwRQjMeN74glRaZVeD4JgDt3/8Eu9PKHaRLCBaWSg/Pur2FuI7y/Zltej3H97i9tM7dAU+/N+/mx3Cnff1J0X78S1ePnywcbQNAuN1x8/vAAi2H7/JjEeOK3sT9P/43lZeBV//n78Cqvjtbz/beviEdhgrMJ0/677o3FHilu7ZaS/UN8OC3NoEuiiepmDDRMeBNmAqbx2Wwr0JLg04WsMGwRMaLk3ckC7YhcFcHdulAxP4+HK1KPM5cDtueHm54bgdOK5XHMcNfd+hELzcrhDn/43fTH7n0Inr9YqOiadtg0jD3m0sF9jZeRnTIut/uWLbDzz99S+Q3nD8NDG++Qp49wHPz89mH2nATQDoxDEHxjgMF3h2M/37P9H+8i1EFN3tG+q0rMF4ZPI8ZvZf8XuF3uAilbpsP60RL8p3/clQcPCc+SPU/xPTqJZdzdMZdyr9OA9IV16Hf9M5oPK+5Gz1rtnEPFK+80osmll7Tz9lvqmk+xGk6DiL2d1AnG3vRFBPLkeMJ/tRyzzHPqgT8MkrNEuSUV8HiTKo1N0E2iztDjVbkGX0I19uYxjjwJyCLB8YTNZJ54loWx2lrjq/L0Cs/6JrW72dzwM730swyftFIPrC3yshDTuLlGU4DSHWUu4/A4VAC4E5mT/nf/L+2SP9/M+ZmI/lfV5fqeCDH+RnCLqf79/8qbttDM7iJJqWRqX8+9S9+C0Yk3WRCmsV1wssAGE9rBRI6iAq41P6FcR6mZDiwA1TJAXWqvtCpOMEyh25nCg3bGLEzuqFWFSM7ZulKDmOww2HZsrkyKiUZJTJ5GFzRtZCPQh7E4cqZJi3ZczLDZvN+5aWcfGJYOz9iACEMc4ksrYH/r0r2hT00TB6gxy5NxPqHmaKiOjBhMaIYkNBL7M4ZaHl5+/Fs8xpxsIwx97mpWpmboN9Q3imauTTxYEFBUVXPpD7ybWRSXYLeZpPYramhzuVAwZvqaChIJrP4NzK6UC05XeNZfG2vL51fbUqdgCPdBFgu6QwLWAqzFrrMfuYrnBJRQT3v7qKIKLVLMKrgXVGAWBOwd43PF12bPsFW+8W+TU39Hbz9idYB2c6MZtjBu5YNoKILkarOfKF2leDELEfa2sVIu9fw6DGaYZnbWDZBxvD5td7j2jI77nODM96p4yhEgMgFNtSmAk+F/O6H/3DO1UArNecasYOOriU59rWgWEnyfY/HVYo/VTHAKA6TrkRwCYSih8TakxsCc+WhRiu7dVVe2V6r140KC3pj+M36y/oz5xJLBaaRKU0z72CdTabP08v6PtcKnR2sDcTu/hIeNvvmGsrF5/GXQmlPYXQ43ixiFr2MjScRuaY6Fupff7oUkCj6DUgrSNq+cA4OlGJMQTt6HDHwazPHvS1aKKFBtOyGLGkcXvdSBr0gaQFecPHjHqCvQX619QWnTYKHL/EtoYZOPB3jF0tpVngYRVQEb206/3MMo9UawnoZBeREuZhYbQp0J9NSGQ9wDSC3mkmJHnQgMXIOlIfWxe7/vdReysGEiw1oVHXPM/p1jpapHDeLe35vnkkprXEelLmucvsNcTDuZnqC6I02KLgWk3eNZT9AFjLOjlU4wKYic/OayttJOA1EXRsLihZZIsAXoKkx94VVgEK9VptiB4ZhZ7KTknYIg7lcdBCc1UBluKYA8o08sSPXIsDUAygGN/laNBuczNnNjcqOk9uTj3DI8nMeKx9QjaLKoYYbp6M0GEWjS6Q2cBaaQVEUFMLh9LRjc28L9KAmfXC5hzLM+L70cT5ZnqVpxZyZfXCQaeUmAmlggQ0BqxMX1s34HKe0jZPN8j5O63rFjF8HAeOAxbi4yFfaiBbxHsU2gHPfkQ4dOgQj6KSwucSDgqmWskvaadfDWCmjVHkDeXcfR05QFZQsRrXJ0759gJ6WzU3YuntaqPYN1hUMzCXlP6sfejp1tX2QZz/M0OjZ6Jyh8sR6drpgOtnNfAAwOxXc5gjbm+mKGvS4rwToydmPk1ICRaPmB2esxVHx3sNaJeGqUB3I4j5bbi6RRG8M/8wwtvQ1Ioj1XES04bRQSLkcn++NTEFzA2h6D2x42Wg5/t5LAQKvfrPoWgH9JpnVXZiQle+lraUbSU6QpAfAOTLyF84kIdMVt8HXJEvd8MtvLo6XCYJ0/J7OEORCzqRptDd+HOJY1aAyLq5pBcS75+fz5Twp8XN17A68a6zK4+VNcszyf9BcjzmoATjnSc8S1ahx258k3J4S0u5prp0W37wjday9lr+1kfrusDolnuCr2ta3woaWOAsRxJ7RN6A8njgdWCpB18HFT4OJ/R//lfffHTyX7sUh7e7OorkLDTGwd+Xs3EesazLW1tZv6eDZByy0xGX0lhwGaEgN3liSjqzCuTh+Q2em0cldIBUFvObfX5N5K5KaMpKMURdaZbWd5M6LmtUdRrxqt9qrjyTZnW2WdKJZeqsDUWSUI1zhjK22nYss5ArWOHacIyfVSkvx2Sw9BfPLYDD52xsjDCtDsNcu+nlugBBTfN+XnNHs8t5AYD9YtpNVeB2vcYYXz58wOVywRjTDE+i6E97cYKLkx5/hYes7Dv5mn3vaPsWwCSSjn+YitZ9oJFNEVA0THR0NUcKnYfxLPuG1jdLJz4ObPsF5lDjIzN2y8ZQAx7qofY1aZAC+/5XnWI4jY2M8IKsYwyXlX3trARFSEyOLrU0au3Vax2OIJw66/1FDkv89fhasZjAjLsZJuTUQOiYor73EzT8Ugfov/h/Neqk25rRKdCzWCHM0w/HcxN1I6vdpc4011twyGlzagsV7tefl35ey4SWQToauhmu5Tnd+xo9X/H1qW3JteCA2oP+BSYDjH/84iVGM/U7EGz4gkWqGuO8KgrgEIX+9C5xyOlqP5Rlqbj5p+kO4MDLT79gB9C0Qf7yTfTdmuC4Hdg2ahnqnAg/QBeJAAvKkTSkcy7m+A1sntWoOQE+4oCTmTCHx6YTbQogE10b3nz/HbbeMH/9iK1vuHzbcbls2G+7Oco+fVVkN8q7pSTLMXBzGU2drh1zWEYxwEpdNNObWAZbeBYzm/cxBq7HgedtR/IldlYAgcoHQHZMUWwug49f3pts3wUTDbM1PDXBizTsIrhyJdXy2DCIFUI872dOSNcltnDBUcuOJ96oBuhEFrr8Wb8XbrYyICBnyF9XfQT7WkbySje1VX46n5Skv+f3HiA8Oc3rxBNwNYJPKQ6FlQbfvV8HybMTxDqYlHv0U4YqUJyzEVu7gXAebeDavdQdrWMsSKncT51cZhxeOuDzp40plOW1Gf23XNvnjB33AtJ//fuyz0AGsD4AzriEgtfjJ86wW7bM+5AUOEsvT/7t19M79TMAfBDFG5jh/KMzGALWRvfjGkr1dSBKhmQZbYGlKhhSsVh6Zzq8HFn+JbJPvGOM6KX1RB9Cr09jSuZCXNhxAiYUJjg6cRGIpQ9RYyAmJvoDLBL2H9D4kghWFJAOr5u5WQ3I3swjUi0CZYzDa2FmPT7uVyNSaB61pgJtXp/avQfXaFv1aF9rQ9wI27YNm9cVERghbcpIgQlorw78btum0p9GHa6neArHjjG7zWc0YDY3uBweyXSguSKOipbWxLyGWtb3TnRvnbNXG//0SOoOQYcXACuEpnIuRcXhYWaMTElidX8WCIqltYAyvmXJGFsysR7NSK4/0Bo9n9SgIWsWuWAVHpYc/hmgfGxU0pNZ8XSG4aE5FW2qrX1pLyIePUUq53X7eFgkvjtgPH37bMbqX19s3fz8DW8r+ST7olCDQRdGInV4Ny+rnY4ZNOJuHZfLBfvlgn2/mIJ6HPj4cvVo9eb0wYjJ9LSec47wfn+MoX3+3PYGdOlWp0Y9R5jmsvJveuMmXay8RsBFeNOT8fyvEarf87qCNZnu3CpKg/dfpdyec6JBse17fE9Gu0XUMwe2zI/nBSbkAoiIYhGP0i/RkHxfRMyIrhLKA4g9w5qtTU2cS8WnY/s5Ib375nDj1OzmGJ59wleHxuFlDWrqQK7iAyarsoKVmQmBWfL7sj5YNjEhk8J19kGaFMKfCGROY/ijZrBmH+VNDoPRcggnJ963PWgesQ94injO3enfnJa+uXlUKfGoquEQ0XgU40jj+J0xvSIVzn1mIn6yu4E7Zd0BobGHvxFe+F8pzy7sjTz+++DrAgZl24oObU11XpkledCgAuLFhnkCzXlLTsw160kn5l/AhMp4EUudF+/mjvJTBM6fZp2fHyGQOns9/bKeZ5WTg6Ei+ZNPXZJ0NA10xhg0xgU6TVuoqcC90VvwPPu+o2890syRn820nMYo0YicdnA/bQpTIqimIhVEGXmf5WTsLx1K2EAD2kQX1qbytXKj6hgTvZszY6fDZDiEiTsOeZRN0Cur2Tb8n0rixcAfZU8W3IHkrxajh8LraQkwp/GLc6L1DW1zXquJZ5CycdBoqDo8kpYR5dtC26ea9/Mxjoh87r1j3y/QOXG5XNB38q9+INTG2fsOTFgZnqhfLMG/hUFUNWptY86IbB/TDBYWgTy8RqUrNsRhklEjXB+FGZUCvyQkTyNIxpmSnsSP6tmYjb4MdUWNRy9PX08IMivTZmnEq8F+qmJ+/AiMEUpiS9VG/EeeAVHeBqpornFT1p0Wbi3PixhdY/3QgMec67l+asCsuDHenU+N51Xfh0TEAV8tlTlptOFWzdKuyyQwJ4mpCoyJfd/tFY/SlvRAsXEIpR4FMNEa0NFdCTbMKH4cAOvAFc6ahmpm7RhTMY4DN2nY56WguAa4E+tqPuTvaZTXq0sRLZWsVHClLB0n0P77VfdMCsii23UAACAASURBVFZP3LL5ND/P04Li5siMXYIw7Ft9eaPLqkZTiXfSedjaUb8HDXW+4ZdnxG/jhTS5yMNXh29oRKqTBqXQhkIKcqMFYhHsJHOSZJAwwvsQAM9b4h9Gy0tiLYV6dpiEAaBsVflcf6eOIJ38jc+xFLozZUHNvQL0ZNjWxREvOAqOXdYBaR1YWSC5eweF9yxP3/FphV594gp8T9YSGn2Om6Uv3TwrSD7nu+3wIVNLe/nXT+i5w+R/Kj8gjmuUqCKYn+SBz4KS2mgZaZjtrKsQ/9FclfN4UwkidoR57tJvLeChvki+A5iI8iUjx5F96T3D9IntMUegDsUBicxvCmBDw7E4WfNkCe674NQKixJvfoqfq99p0KrX3dkB4SK4+DjV0U9hN7Q0oDG3/F7baxyxAsz8Q7neMnucV8/bUnUe7tGs8nO6VpybSGjmzOKuCubN8N+kA6FPbH+yWhHjOBLXFwcPOS18jCj8bZ2mE2ZLGlUR02MshjmB83uOq0vmEQNrwl5CSGZzUos+v2XC7IdXObcBd1K/r2vEF6pef7/suN1ukGKgqA4O1oxARHF7Odz4Z5N5fvsG1w8fjBeEBs188/UbM0qFs7JT0OnlgQThXMpMIeYMnI5hzEoRWSLmROvGe/eN5QSRerdmad2rni4gXxEZBpmBhjxaa831RSPUyfTLZoZ8xEqauWLC1sNodFnlEzqx/ZAFb3J9BY/oQ6GnFX8+2PKzEZiD/wgzXHf2AY8a3zaMMfHy07s4tgwMouQ+/N07XO2famYdru2TmjPm7QHOvIliO83B1s+uHfKgnvr9nP+M6269PvksgxXuKTZb6Pgmbwgw/vEL2g/A8fdkI2pwDedccXa9f26f9zsSjm1vBJf/+B592zDHxPzbTxiikPat7yvh0mBcYOn6j0YuViwj6D/eQf7ynfXpuqHjuGFqs6xqP3wLEeD20y+255tljWuQiOwTAXY0bD98A+h7NPnasp5RrlAA+g5NBf2dzafBMh12decTN173LugC7FsH8AH7tx2Xyze47E94ulxw+Xo3IzUE42Zn9RjDMo0Mw+kT08YoCLyvc1qN83EY1E7L9qWuy2y9oW8bXq43iMBlPVi5qtlQMwC2b75G7x1tv2D88xf0v/6I7a/fY/7tJ980y297a7bSXVfYERTHKAW2bQdjB6kXtQwSQJRQCj1p7m3wLQ/5yy+7Vg3x6fA+ooNxW5bfXuvxfP81jreer0dtPeACHn6v54eU+v75BzIxx5dMp71B+vCpldLSt9NTqpeZzYOMnoq607CfDbwWfPRgrloHePo96LbkIF69Vu739V3511/bv7Tvz7T9h7uWM+OajX0ZbckN+tiAr+bdr58F9XuwWZ+4S/FOQZeGAVe+fib2bWm/Es61+ceTFpQyb0jPu/Mzy3fHAutz6/GnUnERF8Tvnzoxk2+DdKA1r/G39YhAFwgwLVWPRblYCvTJVGxhCSgKTSfqJHIUys1QWqKXQgmtUDGG11KTNGQK8IzoolI6WfBUukc2AmVkhpgycQPmtFqgYRAtS6CqxbtzhqFNRDw6v0U0ayhmdMbnlEu4/zXyUHN7HhymqhyLnSwGv4WwcZ6V24qfndUMhRfcSJvQq7jrCWboI352jKwzFJnZwWNMIC545No4IQgGX4LJqN7XQBE8xI2TEIhuZY6azFkh4uesE4zWquvmI/NIOIPB3kwJ2Pc9FI+AwcXz5YInN6K33iE3QXu5LbCVEYlYjHtBbsQNlVTY+bORIqc1oDWrFaR1gZcdubOPPl73ymR8CkuXxdb8EGl579jpL7/OkY2ffDZfsv1ozSMXq/hgcjDPOrNKLO+/csWpE0BV4owvz/jWBLMRQ/Ia0k2hUzAowIZQbg404YgR7+faSWs4j/Ls0LDORJe76/0HsyXOd25Jyr63kkKzTtSU/WfReG07lMBU7NO4UoeiISP4o3XsK/wl7kkFElMExxteSoGKoTtGUT3jA9SMYXxXLHrwEWMhjmNi/n6f4zlnIohjQTkh+JV6JiSfQ32dNysMyfJ3mSvOHqMZFZ7f7983GpqEPtLlM9VfGc9C75dxuqNcmceZ+a1R3sT7Z1pRXRFQP53hrqxZXaOc7+u05I5fD8e4Al8PkGKkoTNiwgPukFnOgBR6DLHa3c2E2qf9gstlx75fsO+7l4+QZcRxMiodIu9CGhV7lGcKyGhTGkV1KubsZuyisXSkFzZ5DgAlstWcCGWa8by1htEaekc4+Qlrcfteqpqjy3EcOG43HJ4WfIxx4lUJGSd8u4Bj2Qfxk0IFMTyauQlaN5hr9cwVw/AhAp2WZQhqDpMWZW6ZYdjNVMVxO3C93aBzondTQHZ6+MPS188BdO2m+GxWwxyqGJMRYZ5dgjyIL8xwN9WsVUdnC4u2Uo8EN0O6FoIugfZinQucMAp6ucRxDRmjCUBMyB2u4JlTzIHJDbjqqcbNENCCpzVHAjMW9745XFgmpSaWps/Suhv/xPlpcVAbc7oQ7rjYNXnBrqpGVJShC4GlrraII4vmS3itVKZijd4bbnqEA5dNn2YvW0QRmEFcVni3CHENg25kryGce4kABSDdI9PVUtZDzRGYPM4cjM/JKAzy63PYuI7BtPkWhS5Cns1KK0FM4S5bh3R4ffqbR+nZfBmdYvNsEJkFrtzM5Yvcny2F+nGt59DP4EIH7J3mz2u3M6+wNOzSeoCUOTgL9KbhtBz8AB3aSKBt4wJ/cf2YclbVjOCiAJ4M99B4/EC6L9cjbvA1DtGjavcGvU3oTSGX1ey6Rl4R99rH5oYgG7IGnOTaPR7GitfLb1IfTSdMSNJEPQ9H1rYWuR/kQtYfzs8V7IFlrU709S7r0ieVKZ/aI/a6UvrKPyhM6Tx8TZvzk3Se4WhjxEX2ebyoEv9bRhhMhcbxYLaKYEbYl8RjKW/FGIijNXFI2Rg9P8sxkF+I/shD2Ofc77o35XMyRb/7igwxdwTjfA0Ik6ye5EwjJY/5qmXED47FCdoeXrqgo7I25CZVC/6rv+myAcFj6Mr/qvpeVqAqIyVHomU/qiNsniVxPqO0oZqlVR6c29USKaA+KuU8/+WVIwkAkVq5lL0BEMEhNARyDaZnQqmZJEOWXia0rhu8HQYrFNEgpRZGp8lpXqUFcYUPa4BTP0JjK//Tty3WJ/V3HJsuLadsLbg8P0GhOF5u5nAO48FePn5clu12uxkfI4zazXF+9fYNPrz/gKaK52/eQKfi8vzszo9eUoxE0B1XVOFll+75BVssiT0Oeat3qMygH3wf0iDbBgLkHIcFgvQcq6g/V9efu0Y0GMgqcV3gMKI2XZZ0gfd6PpsI1qw1hI/Y2oWuobz72YtjlIIdNZ0ipHSiyiWXBcQ6gPb2DQRJl2vzdPLpb7/Gk06M97+V361P8iCcQ/P5Nr/PI3t/Wa3zyynTGZOrt8fo8U++co1iHYP0lzPr+O+Z6M7XU5HG9PM/ANCffkH78dtCc9Ol50v2+RGuD18eQZz/zWHz8tfvQk/I7e8QzH+8Q//LN8B8D5Fvsn0/YurzDXgUxfj7AfmrZc6SBoy/vUP7y3eAKLbNsokNFfQfgdt7GxDTTwMWab5//62LXt86HBA2XIaQt1B9jwaJYIIGwUWsnefW8PWP3+Ll/W/YfcH1Q0P/zjJVtWblaPbN9MO4mY3D5Gcv/Uo53XE4N8zZUXNOHVaC1m6Ys08XgbbuPHSD6dhtR+ackDGgHmDWyWuxFhEs+xPeKdAbmiYXVeGj+f50EZOxCYvNncnP+EKA/QcAPyf9TPpd7+U7lcX70qviImMdKsLy9skLLBC6EvlH3T6C6fNzX4oDK95+tbF6767h82geje7TY3qt+y9CX/5Q2MScJ6xZD0l76hjib0Ws5bmHgXl/AJe+vhr/2mv77+4wD+brqyT/wtWoIgpghOaDINNpiNg9KN7AlFW/SjIbH0LoKuPX9WCKCL5ybPAx7iLT4rgwJt5fNFHnLes4PzcPXsmM24fwHmoSmy0oHmFOmBLJ2EVmaql9AARDPLye4F64bZvCunnmK2CxWp11A/cNrXdTcraGKYJxTNxurmQaGb0Q0SMQoLdAsEbYutdBbWFkGh59PsfA0ZzYBYZo2LYdze9znhZN4HUJ1eoWNWxhbKOSnNsnYtHvTQQYwNgE/f+T96ZLcuRImuCnAMw9IngkyaySmfd/tRVZWZmuSjJ5RYSbAbo/9IS5eZB5dPeMjGUG3d0OGA6F3scmymWJ8eZJoTkGo/IGokh7aoJXqaTGd1FSd6/VaozSBjf255k1qkoUMJWhwyUgVcQPgEt4GZlQaQJjrJ1ct5TmbmRQBYuv7xXioyRsYoLtZB3zyHPrrhPiHSQ7cte+lxIOFMbgEEHXPdozhOzeqGzjGQBd0CzM5U6UpE/PT5O3fE/fXfnngp70jBJDSBCG5LQoXFWpi0mFUFpDpQXL+YTz+V5qxjaJZDZDRB8dm9YZBTilxk0MhW1UIlTdl50MfxS0WrGcFlw2rcakzMkeOWTDaPA54sSyYfNpZL/juo1bRygSDEp/hMSPG7Y5vU66s3uO81dGpaq1nkxpXkJIB02GIqnFrUaDOrswmREkokLlw4zLzIxSxThFxRQWKaOCjcD2ga5FITpQUOav6pBRyrXxSYiHA8Os9DXXkgPi8SP2z+DKakOQbZbw3o8MBwqvvU97mxgaZR31+QBKxjyZs67wLUriHZelfWeWyFDBsRYBPTN4OdGlCI4DPDpKO+m8i6JJasoLVpI93B13WTfHWAFNs0+oWjevRJfSLE6pJucrB78MR9r6QCKgB9xwqZq9qB888caBRF2c8VNGhx0bJX4pSQIOf2W6P3GusY6Zt7UU794OOR3O47TwBseF1gn3mFKBJfUT9hyCjka7+30+w+7eeWCiV9OV44Nikvy3lXCZnKM46O++ZZ8qErxp6b/1ganHtRS01nBaFpzOZ/k8ndSBsDlt2ePLOSUf/Nx+J1sGHHMU6bbfmKWucu9iNPW2BP6GGoJrVQWsZ2wwjy1yR0BuzeelaCr6Ws1pINKAe+kdc34cmrralajWj3I1Rp9344kQdFe+S+QrFQINmnEjIpLEakpj26TWOTMYLaWqN4fLAi1Yhz46Lpdn9K171HXvJ+dTatEKgSzza8blsUmtu67RuCVriopGLndN263ZLYYp2+WH7I1haepNAJW5qhbxbylBDQ8UxyYyN2kmXCFh1wwfsFR8BwFSUUjThCtDyyTxO7YfqsKGZU1wPFMKlmVROOsSNaJpTE05PMaQmpqjpIgq4dn7pvQS7BFaYoCQ2vakG6wQgztrinZ21MipRmPe5kubRVhRQHXHL0ZEiAijJ0NL2hcYDE5OccbTWT1DockADUkHaop2BiT1+CDUVkA8sHUOqGQGdL5671j7hr6tkpGgigK9FdtzgDmDjcHYtk1SJW7dowJHjzSPhnclyo0crVvELDtvH+O1mpHTcQp+otTYr0SEZYlSDWVp2LYVj9+/O6z2vkkJLVUOilPC8P0bzgQGdyqLPKfzKivZWtn61nPNWdh9zcPRS59/1tGd5P38zKCTkiF9DRFApzKtufE3Mo8SPeg0FOROPLatvRYtjO/I/Qp+K+iytF3IlExKD/dUi2haE5s3ovYSOUNA8Is3pffYIzMdlCHPBiYnR0YPDzWbM+9zs5ds+zYCCIb4squzjOgFqKqzjcuKUzcP2p2z/Vl3rxRywe7MfIk9RWmtCgFdM/a5cTLNGGNKu8q21QnBV92aFQ5nw8hGFJeDDTM+itSReubtZxic37n/xdbuQYeimnp88vT0y8fEte368nNHakHp216pavs082fBr+k9llmI0r62MTKH07TtO4bSFfY1ZXunza0RHQonCu2A5RwSmCn6y+9zYg1HENO0JNqt+pc9PdtPkeMwiNPWerlMc1RrxSB18DceIwUEmfHcdDimLzG9ljvHasabvvV4ZocSfA9w4Difr3Rvdth1nkcfIAJOp9N039zXxAvrmkXa7pjFdhbnZ+ErcjCM3L8s8g7uQ3ALM5bzWWFn4P71vVxnVj4rcJxly8oOBUP1klkfaQ4Cmc7J3HYHhX65oN7doVAD8yrR5TRQewdqQd829HWNKPbeYXQkZy8oFHRDHCVG9F9n6iVsbI5zVyVsEGh+Wgc2nD3DPzkduz5ewhs2j8Yqd725IWWHg+wL297ip2Frovx7q6hMWN680uhI6WP/8k3a/foNZgyf+qP7fkB48Sm0Qn8zS+QsA7jccDrK2ThKOnfH5FBw69k/e+xx/R+9V/1p5z2qnx2fHXbGb+qs/DHmdU+G971wPXpCAQwIPtz1gwEs72T2nv79Ox7++V6D5cQQzAA2SMDZ+okBfMbpg0SXlw9vsH78jMVws45BpJevAN5hjI7ldEZ//1ocbTj0+u3XNxgAGn/BgORdOb1/i/X3Lzi9qyj4DiqvRT7kge3TZyk7x0B9+xpEDbW8Q/tAaLWABqOpTHR/PotxuVScCml52GecfnmDZVkEbh+fQEPk6ForuBSULnKYlK2VzLt9W6UWeh/YVpXTiMBUhOfpG0o9i2EHFcQDdBa5DKNgqQ3gDYThwYTPpKXXtGTu+PZdMtDUCmoV+PwV4OL6R0CaJwAXMDZmLCzBP5vhP5a53377DLzTbFXvCf0jYWOjj78A+PRT8Jqo5x869rBJu01/tB8Cr91+4x/txw+fpRkf7dRu037LR/Bk8923cPCtw6bAnMLNvkdp1078X5pD549ST4JCx2Elq146SO+zBz1A5W84foZv/buP9jLZ/U8+KBi76MYMWeT3we+ZmM6/OGNPN2b9PjEa90z4viOKXwh4SMz3nnnPXnXWaxPS98ZqPxSwjoilA/yhMHvVhB85VnLsftt1I0TR+R8AozLC06YuJIowu0H/rZCa56ZQXhapBdpaE0UtaR0PS2mp6XiJJKqXLELbowEswhXwAFMAllKcGZKuckiENGdEQeKBBQQTyqoM7EP/ukbVQI1eqnQWz9MN5nNiETtcgvDMyGSojSEMFaUsKforGHBPE79T7gkWW0Ck0S1Juf9SfK54sJoR1gQ5B9ZoI72PgDRXqV1mH4MJk+5OQpZNIT9lKt4Erxndaz9mcuBoehqHeYWjJXjc7w3tnwuD2QCh14ffygJfqlWwuemI/bVnGGNk8o3Sb1u/UsXD0OC7FEnrT7WhlRPO93c4351RW0MhYFs31KWBnklSkCIyLlQApAb5dYvzZjgkqsK8kCg8qiqoeTCWKrV1uduc3071ksc10A8uhjLz9tO7mREgga/Wkebm6u3HZ68Ma/6RMAylfsIyApjBkVL+GYTCFKTp3OU/N0ZfCfP7bibI5uEGWncI0V1xZBB0po4sej1onhnkkZQN11552ncb29Q6xzuuiOJPcDOpiJrXQiaNlMj4wZQqCm8iDeu+AymOKMGwkkK21Q72ftP0W9o35WLcI+uihp09PxAtYRDQlpNOgBjUXcCiwG1Wr3ppJ/TNlFDmfMO+B3jroGJpjbPPtt46gaOtF+CG7PxinV6/UzTqhpj8PM8D2ynhy9X5+O0TGOufcWG+iVLHd/Of6eihMmzuso6LQMRXDihAGG7Ip4Kv+s7JaLY/pIu0m/nre/LzvsVu3G80/ZCrsdOJvh4aeaf30NRcVhrWWoPXOZ2w2HeNPm+tibHZonazkjO/syR6dqBsBKAKJzVoGU9TE59wg1fMgmX2Iu6aTm4/B0WNq60WFdYZzOLwuG0bVjOgaxS60d4khx1MuowreJ+0z1i95wuhYIDZ6Jx47RcO/MuQkjzM7NlBZNjJ6AWl1YXAHMaawVICgrqmptY+W0q8oo4/bQxwa2htQW8yXjDAPDC6pO4zqBXdUd4spPyizHtngPoB76w8ZURAK4gNFudHx89H8xnzzNC103S0zFpDWFOTWsS78dPZ6OnHUP6OpAarlB0oaENS9nMfWHWth9X0HmrgQGTscWeBQvDoewCWA7YyYZAYYKHnxQcn0qYShkdtO43lNB+Y+06lAqbELrEe7kSjErxFQ49SPZNRMTmlNtTTCa0UlNpknbVmfe8d6yqGcBn6wBgSRWbZF2wNqhr9rTyC1DhllBIcb9FUwO3uHhbdx6tkChgscomn4BtSgoRL9RICQpsL+thEfukARhGn0ZPilRSJ7tzByWiPZlCqkhmMSkVrMg+tNolyqQWXtWJsHdu6aX13WYeC4nwQ2Rrv+GkzNs7Gc/m3XwRWy1lxgOICmniToLUCP9ebwNrmC0B3iTZfsVMzpg1nyeCl/FSi04fy+f6eeEX6rhF/HG851rvsZZtdo3/2oPTJ05e5+T3L7iLgLTpy3cHD7io/aE5DbPOhlwupjI3Av+504HA0AKMBqslwiq44TzqQ+Jq8XkZelK8ldQDMDpnQ85ORSRdMMlf6hOhY0nsOELJHP2lHBAaS8jMuyTykV+5bNP44Gxj3q+js4Mzq6dDIx+5RX6Yj8D2i/Uzr7W3sFZ02z6YzeEEn9dIhe80MkvO1WXo9bl/Yujnq/OaLkPg3pSVuEHP+GTBltsg1u2Zge5d9Pq+7t5du8mXj9djvzF2fVjK1yYMlFbo25nw3EWptmiVGaT9hyhqQ5cYsBzjHZeXmDDPZ0tpIFb6PxkqGmyc+yyER5uRVhkEsVAwixcM65yVksenTWqX9blBDKAkdv3t4wNP3iDoWXaKkUiZ9aeBt041lXiL0i+zvU8d7BrhL6nV3SM7ZSUbQD9aTkgVP+fKnJ9S7O6AtABv/sKFyldr2RPF+awNB60ra++afnPc+K4JyFPcSf0jGYthz5HNNqb2gs7HkvGvn+kRCC5hxAkN0r0750yBcX6PzXxQnsF8HCPfpEYvSF96WPFI/92Q+wtFAeX49b6JvDqK5pTW7EOOsCKHr34lfAfRtSrx6ZkInMT7+/UdaeUUcBtdnBp5JPq9zJMJT+l+3Nx/CqvGVvSB4l5d6dUB3/Gng+ZME3VXlyy///h3tfXJuJGB8+uJwVChk95NIgihMXnu9AGAtDWhBSfcPD0HjDLxLgVaLRSXG3a+/iH7nF8WM5bXzBeP3r3L/GNKfz1/EEfXtG8lmNRi1FrTSwF8fsT2tOP/jA1qrqK2h1oalvg4n9W/fgdMZo0i/q62Fyg+9b3jSEhKrOlxLQouOddtweXwSmUblE/SBel9BW0G7q+gseGkDozzL3hgMlx+YCCsBhc1Rl1DfvQa+WOGDJxQC2j/fof/2FeX9a9R/fcTDW8LX79CyM4KDBqkxXylnAWu5pwGmdwA+C35/d4snSHaJCTIyj3Lw2E8dIkcbgPqep5mnmZ2D0gv/4nYNHH4DB0XXgg2Pq3/t5X/huOL1bhzGB9jNRuvCWRqO2tkxtT3L/smuA401/0v913/z/P7s8ccdP+fjvy8CfWJ4BZwJ8wRQ/seZrZ+dIgNl/WWC2SRyiKH8UT+/6cknksh0QdDSr3tndeX5VxzEF8CkkJyBQkY1RRslhsW9aZPgFp6UcKZOBxFv9FPBbSU/Wz/MhlRBuxk5IohyM2t7ear7EIPdUq1vJa1j9hA1rkfXTFNbt1qwtIa2LGinkxCaoorPEXXxbCsWrUVo9Tet9OhAnwX6YUyX9HeMLgb5LoaUVjQ1GbOnZ8TgSA86GEj1O0eXCNBR5nSDnVdUFEn7Q4QCIVqF1qkeoqUJCgUlZG2pwZwBCiRCmQeL8tQEGCP47uWuwgUIDIumZZCyfxOY7RaXjFG+UiiwZxwQvUKsuQlR7tvvCvABL96WX8BzmkM7LT2P+TiGtnkf5nOAIWCFQWaP3o1aO+q5NhJhRGKqDI5YqlR0KaCI+mqJdxOhf98ACkWKCXQOzpb9wNG0T4DDN0GUj7VKxE5tFcvphFYXtOWM890Z5/PJU3beMeHp6cnrokr9Ko3gIUYtFSCgkXiEDw4DX8dwmDBjDRHU0C4K+G5CUZ7u/afP17W4cERIY+lzQweN+tN/jJRNLRxoPa9ao/kHQ+agQBnNGtGlRITlfML6/OxwTnpPdhpxvAcVzABPBWyGB0szKvchmEGiqFcH8khmSsYpACn9e9p/xRQVWQBPc0uipPYgdLklGf9vTc4PmANOn2nOTXEd8wevPe7LQqTlA+REIWUlUl02RSKpR+FluW0bGFIDcw9xppQxOMjellRUcaSErZC1KPu2akpboQVKF2A1XdW7tp10+5LWuJ/fz0OyfphSF1Aj/cFhMDDRXd7dYNxyek3eTwQg1+i2f7NTVYx/9w5CikxNbSY6Hm0Cs6ogPWugFAuMvI8ppyoBQIVhDhPzmEltZWk8NPdNzgkwT3bGGbveYPWScjcraPYK3t0RO0JpBSMpFIJnkdTU+YlpcLImQOp3KEANH9fasCxhNF+WRfie1rzUiynuREk081oG99LujAvtXW4UtIjnEeVhSinC/+zn4MYEjYSjDA9ldG9tlip/DNbMLqqM0gj03iWbytC05EX75rwFzwKLp/fU6wVQ44rOutJ3lIIyBtiiVXg4+RFHy6K5AZu3ZSnbfS61BjYRaY5I7YPBgUkHbn0IB8nWmhjue8XSGrYWCjvuQ1OjQ/g6gxe2D9kHVuO6KN/HWkebeAjOYo5yPsCE/2XdlAczDGpIzmhGjMCBM2oLKyyMKvQ+G6lgTqcsEfFaf7u0RdrXFKa1AlyK2L25gksHg7F1AneDI41I13JIrI5YhQitNuFRuqY878PTn9YCDCohAziMKDxmftigo6RyG6ppHTquMbqXTSopUtUpUcr6IQ4oA1wFdqSvC5b7M+7OZ4lCrzVldejY1hWDGetllWfHwFg1kqZvkNT2IqecNJpfsmoNl0NtNGT/ZTxOAGpFVf6EeUhd4lhagWmlbUQ9nSsqZ7BEBxVTfKVwboOb1A8rTyDOzaIIbK1JtKDyxwzgfHfGul00baPIWYUKuELl1qHrPxy/25qOi0Fo5vMj89F4YJKitwAAIABJREFUBtr5lOgRoT9Lv4sZxO2vQJTsSqMKEXAndwjMAcYnC4iw7xXj1wiSQQBp/kdyugyYif04UgmADJKz83z8phQKz4gIkIlHVl4rUD15Rio6cFD78ZEYxf0xszpxyhTOdkOmywcli2b6+KMjeIehuJu1XIb2Vp1Thnd/Hk1iVDVlnq9j5mH3vUtrIzClCnGXJznKNGRnDahDqBlmnZdCCJlGf29Ni8MRaxYI43cOnBF27TjnReTsGveAmpk9MT5ZS0VhqJy/i7yieCaMqXDYc1C0vZHxQ6bJ2K387t5b0+FD3Z0JckzIyym42NY+dd7bUbqKJG4c1jbBDMtp7IQgBXu210vEcLzPOqzkds9xX92X5yB0gz4AmD6Rgamcw8R379bKnrUMDATZU+10cn6SB2OsW7RCpBU+yGHNZBZjIzI9sHvzlBil2i+o4zqK3k66AhLdCG9d5zRalOdJ9xchUg/HkY3ePnibISIxdAH4/vWrP5t1UdkwP19nmw7P+ubrkfbNUMdQy14kOsQq8z8GxtbdCG5zSE6oCbVJpPwwfK7jtewyvYusKexMGM/NuTOvAzveGbGWgVpBkChY8PBMlg6R+32gONF5Qz0XQz8iEvY1aKo59vEOB+yz5A0iWJATADTyKZpeVSjpvlkjmxlgPIL5NZ6fLtIDjYK1ERLuUV8TxtfvwOvQ1BOA8ZlR3rwCPn/BAE9GDxt9T/czgIUJ60Ek+R7/dZLa3I1fA2Cs9E1GzFZARnlSberyk2TzxPO99luM5NLu2eEhYN7sFj6X11Ps4872i/L+jaz/b4nGpPnBrh171hwRpqoOwK7MAKegNCkre/eO8PTvTxiFsP0udbaHkrsBTBli+8cvrrspTCgf3qCAsH38LHIjE8ZHSdu+rStMf2byOMCorUkWrf/5K7h3rTdeUegVzLlZX4gBDfAGgXg4jcCXrxiFUKiC6oLln+/RPtyhfn8URx16xPL+F7Ta0E4SLDe+fQdVcdCtAKryoHRqGF+/4euXJzw9PWOA1RFd7BetNFA5g7YnjSSXua/LCVQrznd3giMAjP4E5gZCQaOCzl0dHxhlMIry6LYOlVXv9l5KNNX6Rg30Be0fb0UOZUL/yDgxsHGRqH0iLCQZfytIdNEMjE9A+SA0Wncnnj4OMD5GJqg/cPzB2+dnFV/sj2yf83O4Hcl9THWur4+Dc3Rwbs+KXKnNds+O3TWe/jjdf4BQdNPvHSF3bP3heOL7fOdQ2jxxNWTyEs/np5mY2zHeaeI3//JBR6zef8nRbslZ/1WH81M3IN+u7z+vj5c3ws8cDwyYD+OjMpUgMa4f9asaQ+jMcXSsAPiWohORmRU24s8To33Y/+CoXrwvYqP3vcw9mImjCRDXm+e4FfI/h/7pvmLSZn62iDGp1YZTkzqgp/PZI9LNoGSK51o3ZxyhittokjXoQkeS3enslDNViBO7KXaFzhgSQaX1CcWIHuKCeYiN3jFK8XSpeZ44tbePOgI07ZDVQKmSFjIrcCMl3NQgQgDWObX2DTHmTsyvxF64A1UEVsX1fOxO0e7z+C6D6X2aFDMw2H7eeSjps7xv9apfqf1UU9WHaMyhzVeaAFt7wuLPCZN9SkRFmJKh3CdDFX4hAgGsChY38iHWAbOAWUjTnxbCSVP3tuWE00miz+/v7mBOAWMw7u/usG4rni4X0KpOGzw8UsmM655SeVAahxo0AFe4976ph7R6beLPHxMhyorC6Uva6zdQE1098/I7X2jg+s4jwmClHEhSJYEgBg7FJcvdnaTAG+57qK+hlF6ddf+Y24TOO5shRNqaMTukzMCuHnfmnvJQnKkpM1NHvtiEHHl8ND+2RmIssrP8whM/OLKSlEqkLjRU7MqBYMgszbqxomDI/FsUOAfjGlFYNKEhN0hqo+YYQtn45YJ9MGrslRu0V2SKRNm9VGSthubhqiWtTTagUY0InNHT+Xkmx7ainU9X82rOW+DZoYH3S7HDbxTAJ05ACGO5UyBXwmM+9sr6tC75nemueftmOuHztqPbyIqn3V5JrQouuhZOwlDwEhzy1dhmQ8TBs9McIZRg6daJ1iTebN5rBmN6izVQGZTKqPhIr6cX7Hs1HHJabailRrS5Gswtle9gBqlxKRx4jtvPfZjoH2nq6MQbDs2gw8yaFm9crUmeU0v3fsW3pHtmBw6e+CtT0o3EO+3bdKN+Woe8WAGT13sKQGTvSXNCIFgt9larauKAunWMFgYYW1KJEE9RP01KNYgTZVo7W5/R0beO7XLxfcjDshJZp8ukuMRgrxmTlVk2tkIkJUVIUxUzQN2capEimMLQ7qIF6fqCUCwTkfkokWZGMvxrg7fPATdiQ7oNc9M2fM4Mz9i0bRtIa+WxRuOXSuijgEjSmXOROnlcq6yDGpVrLah1xWopGc0pVqesFsI2xtxL59dsx0aabwI7bStUwWUofmWHKSKp3+f73Wq7D62tXIwu6/DJgEIG7oYypeuWtr0uYjg+nc8gFFR1xiMi8Q8Do/aOUYtEwhDc+EcZBnyOWeGggCuDuLi84yl1mYNugUBN+hKOwsavSpr8MoUSRUQINB12UfnIYMujI6yDhnuJXDZpWqJgWdpkQNe4LYw+sLVV5LZaUHsBF9njJY3D8FDeDxHl/fIxnhnlzGkfaTuagcAyE2Seh07F6Z1tJeM3AsEbl5L6lZ1vGeC9LPYzx+6RmefNssfuvDOOhg9nh4brFxB+Zv6OWji8fNCU46NdC7ffvL8i/OuhM59bRdSIzoKbmUn/ZMGtLuhgFuW1p8Zlx10+q6wwrr+BxDN4t66dwQiY+FBbn2yQ8QYcYRkgp+/zi+QVI532iYyx0zRlfL1Uxk/zjo+h4OKCLuD4cDwJ54l9bnQ/zHx5eq8PN/DslSIWc7cZmFOd3zhmuApe2d9tOMr0GxCdGRnTM63x7HzpjBESr6SL6gEpsDFSlJEyeKLAD84Opzb3c80OSzQNJd83fMETPyc9935EvXXjudKADmFD29GSElTFac+MwIVZnKZa1T2m1LUE3slDm/aqrbPBTX71AS8+iQ0+BxT3K42tbcGr1vD0+ASQOE/fP9zLim4ryrKkuQ68TdqnvNCZDWNA9SOMh9ev8fjt29VkBezMh7dT4v7slCHpaBnA8JJGNl9EJLxVchTLnTKeqhQCURVdjOIOhmaQIXE0M8MWEHjN5lqT9thCpXHsxkM7h5eMJ9LdkQ0TCgfBOVLOOseGNdO+51iTq6ADn+gZBx/JXIdrgdALxGrkrRRwi7R3rDSItPCI8RUorxV+/P4HAF8BAO3dW2yffs+thsEWcBOE1Taf+y2H1ULPmVsbv8JGX8OYvJt3Svee2NqZ5+DE5KnfTyyrclZyY2m81T8QZ9cLh3OyrIuMKutUcqr6zDIqF3WwGvMK5XXY8wVHGJ/SxauShamv2yfGSHqYZdeo82Ufv4qDMliN9FrqgBkVivM+vMH4+AWmmzWZjjS1Xlu0FJXKxOu/P6P9420aC6P/9nvIqgUgVplQfgiPC8JSKlppqFVwwvl8Rnu4B39/RKsNy/sTmsp6RZ1vqajTPJTHHBv6ZVUZXeldLajLgqfnZ1Af2E4rxqgqU5sztCBc0zcZ/aBngE7isDEIaFJHC8Ts9h3Z90GF+hhYqmX0ASIgUmgjvXsFujyh/r+E5R1jvQPqBdj+Jfxcfc/AR5JSokwgCTmXeWJIEJe+K+PgWd/BimdjJSJT4F8/grcPvJR5mXCaMszys/z1iy+Vj91pni9f//4J/im9BMe7b9+Vv2ceTUYRXiIGwAUaKHPUvxt9ws/0/M8ce/7p547/4yLQbx0CxrT7DSXaxqmR8xK3kPy+1b2PyYxI4ng0RMKSgsW8m581wvZREcE9CCdmdBKj9QMTvk/NSW9G/p2UBx49YsxLUtLuo9Ctvu4sKaT702FxtU5aXXHysiEmenb7yNXGzLOLgPCahXnbhbFbkLF9J60f2XA6n7CcJBp30dTF3IFlqeijgYfWNmIl+BRTKNEyFm1RRQjaAUPXlOzuYYkw7BMAqzcpqRG7R01tqoDe+qoTcwaVUOZVE57jTU6QmRk0UlSSTJR0k8gJaa1Vori0/tbY+RkRU2pAhS/DV4PBvLkgaLXrJwFf18fWlcgYJYne8gsutFnzpviwf/dwEndmgREUBugQsI15CxaUvXvJkJ4+HE72DhHeJ6iiGP4uZ8SS0ssVrAowEqm/QISiEwjA+nV1JgEANlw0SlXm3irBuflUGZ+cvl6yIWhkDKmCtRBqqzidz1i0xteyLDifT3h4ePBIHihzvN0/4Hlb8Wp0lMdHQOtebn3TCAnBRa01bJeLRJoj0paF8UeNMjofpTQsVLBuF3EyuKEUfInQmIhSQIdM8F85brZGP7rj5X4IjOle1P1NDPUOB5irtyLzMrRuk2wSc44phVyqknlg5VuTkYvZ/V6yItcUekSEcLaRG+pSdUuTRzG5kgBwZa4ZpUNInYWcI2UWaPqVZuTHa+dCbl5n1jdTEpphOB6+/3iag8yKRqSkKde3vnlfc787Szp9i04wlG6MtkXyWy1hUwDaeavzbEYniyA1o7RkzC+7jASKj3RdQWJA6Ku+KxvSbUREGNtA1Zq7puSz2oHkBO9gv+2WYs+DTAZ9GONrc60XyryWGQam1xrNcKHB6FAgXPb+QpU5e84rMs17WQGWud3TBRu3Kcy8Q2xzx94/w6AxhkSTkGAw0ZJ5zLuxp4HPjHDwVR5xnhQL1jb5+seTgyEppmKy9GtWI+g8GYkmjTxvGsFZK9rSUJvS/CSw8ZBo0izoz9tPszRwOMyBY3xiYBzoW/d9y2Y4t3rovUsUktUFn+Yw9cXeka7NRvMYrpD5oQkmxOGMNZ13H2JElb9sPJsVGjprCcYTfO3ojM2B88hpzYXmVq9bXojQqxjGhQ6IsW8AnlZ7W5XuD6mP3kd3pYQ7frLcu24rnp+r4BA1eA+dU1OgunGPLeoL4GKOQ5xAmlCWChrQUi9V0rFPMDowMFQRscOtECMTTHileO/QiHEi9owP7iDh0eACA9QqKgnvkbgkmNGq95Q6cDCWkyi1qQOlVJzOhKpZlLgAxDL/rUspgtY6tmXB0rvwUINnOBgMXp/RuUb9dVlQ6ZHyMYOD5yNA09sDGJa9idXoTKqkLjLWnnhxknTm6IRTK26oQykoLpkpkTd5YAPqIunam+7b1po7XtVWsa4bnp8GCgPL6QQmQtdo9KVJlPoo8r6C4gppwxGlar13sCvgfD199xNKqygoaKV65I3NjdVfB+B+arF/C06nBX2r2MpFDN6lS0RhIDLZXbrdCpFHnC/LIvLZsuD+4UENB+KIuG0batvU6C/9M9rHYHe4YJevzHFD8dMl9xSwyPP9MbACzw2byjp2LDg5z2t0h5lBd6H4IwIadO9wyG7Q/RnzZIaEwDnOkzGr1lmNeRpJPDa5XpYSSAyEqZO6BhnfjcRLgAh9dO1vpGDOSrcgNyq/e/OOEA5YjB3/9jPHrfvHAJQnmO49VDTtz2XBMmioZXVhCH4VZxWCaOCMtnB8agYLFHaJUfQm2fBegjYZvTzooWWmc2d0AggFFo0OQMsOAGbksj/an7MxKp+6n4ZpK9P1tTQlWbSf53k3ijBo6XiKOFBZGltrzIzPzq1PNISmVokIxFWZuu7Lm/cEkxjlZmVz4OVrev3yca1mDb4y5Be6Au9K1dd2D4IUDx9Mpt8Ed3JNHGjMV8gCAhtGf0WOtPlGmgdAZKHiTHL0zR0SjHfJXG/iy10X4LgE1oHpiAx/rHdkZlXKwQHxWS0gpdWp7OFUeFT7Z/yJzW2BhAteG8+P5vWIP6fgQUj40AZGXRr6umFZFmx9AxHwrMb0u7s7a85hNhtej4wgqQuKtwnPj9/U4BX0CACevj3i7tUruLHVgD3xJtKutJO3L7OgQ48Od/5K+T7lrdrStCwOAFtxZowOzXCm9LZULdgHWE/F4d/oufRxcNB435Nk45XMP1L60nAROV0I2oYbmzIcjva7LaN54xEDgcXFCSfZvCb8mteJYuY88+V1j2TWTP8XtvQwj3sErvN+kbGJmUG/vJGsQ6b/SUib3sj9ow+JRAfA+I5aXmP7/Ysb0RvmKOhbJDIb0eX3t+n6ftop/Vmvzk67gvafr+RrOUreDzq3lm3JwRmGimzG5G4mjWYNVDX1q3x4O51b/vELChVs//Gbn88oaj+2yUC7a3swgs+0B3VfjjqXPC0g0DsA9DrGDKD/9gUA0N6/xfjti/AQ//7sngEM4PHTZ9yhgPEVtX6QfvIAVHYSJxeZq8ED7R+/+HtrqZOzOQOQJJ8KhOrQ2qhgUTl/UdmgfX/C+e0bnM5nlIcHtFZVNiXg+5NmbRMZ1UptmvOgyKCsNc87Ls/PouMaA2MboOUe4IH28ID18RH8bQNwQXm4Az89gc9ndXwl8MOd6scuqOcz+OtXcTiwIUDxXBojM1CXBZ7JhOAZwUbvGOOzyJbvX4MfG/rHJ4xLrNf4ZJtUdvj47bPrzgFgM3hLsIuD3yXBr8HNEZz97HGLDUgdcF5m3pE7WqafPwpEy/3N2PQIB+SDb/z68bj58C6lvIGXdbldHbjrh+GuyLz78vtFJKLQe+8jb2/01TCaLfl1CYn/s4//VgO6CcO+4tNF+ed4vvPZP7vV5HjcMRp3THgkUT7dHdzfdPMZI+Q9StT2jvciC9KmDcF+H2Gzv//qnAG7Uc7p2vx5/ewxcuGfuGc+VMnK0kdndpKi3QVBFeyKRje4kmZZPOIDRGgEDJxwMiRPAKthm2G1B4Uo8m7DX/WYHaXDqWZCIlIjWtKkbF0Y4KFRM5bKFMhpTZHO69uVq3ZURqR1KxeUskraGI0WKlZbsNSIuKeiSm/zttf6b9qie0YxAzV2gbJMnuJmjxR9RiaM2TC5QBCpEi9FeEJ+G7mg3FCCQ2fi3Ht/J2BTCc9uy7mvkogjUPgX/zBEn9ubATMxN6z7Ru/rYyfwsQomykRXNAEBTQHJT7qulvqZGJ1Z1kS7nQUF8xx0UitApClHWetXapRZEj6IAB5DaqJb6mhl+Mf5hHurHQoh6NtlA0OM6IM7tqeO8+kMIsJpWVwhWWkerxnbUlkRV+DllFkOFz91XCsYf3A7kjbKn4+yDvs9+zNt3r57LwTYKwYYW9+w0OKCm3ASYWQSfCSp8WHe41wCCKO7+wG+2D1jDM1Am8/7d12kUglu12K4wsHbTTwS2f6xd6SassXphxn3/wT7Sbjec4EApggJj06wt7qEtWNEk5IoK5Hi2MGw/ybss9Acg0GKPrnSRJpxSporxWplzsZBj/63eQdhOS1iSKpFlb7JwYkIxANjXSXqw3Cn4YuYDFzNPx19DWq7VwpNY56u7Zh8W/9EuG8bnYPjnUCFLBV/XDNYm+5DkAO5R2DDaLgTWXvHBBuIpb3eODodORoixjfNz24uiKIkAh+kf5Tzs/A2v/o6Ne1QySMMzHDc4b9NStHmaq1oyyIlajQFskRIh7NF72JslhrX3WsGW5s2b24kA7y+dBgYAr+w80OI/mp7Q0vTZAN5KUWNEtcGdUrfLb18GIDEOCm1nQlFs6SMIc5e27a6oX6KaNsJ7Pv1jP1DkwOJ4zpAHSRJ1kn7Jo4KauBUB0xKMCZpyAs6D4y+YZAYraBKp601EEv6bSmPotGOXZwSLpeLCIrbhsuyqOMa+3xjMLinWBPFhzLXtkEYhRijFBRW5VAhd6RQ/aPwjBgYKKFgimmAmsxBLDEyZlyW8kTDhV821HtQCoSHpu0b2UGSJ0eH0knGVSUtKcaQVOWtARDnIhTCiQraIoZdKuI4OMDom/LQw6LPDQ5kJfvW8fT8XRIhXaTeee+6/qWARHWPbWySBMRkrFJQmxrKhkTDF03pTwCGwsS6rfJOK7lhfSi6Zo6zwgER6Y9AoFL1j6R9zwAkpTwMx5dSMGpFZcYJwAYCtwao4y5vK3pfpIZk7ygUDluy/lIapmpWqsz3St9kf5xOJ1SqWJ8uQGeU1sQpJDk79LHJfmfFBcrPWPkCVKBsLI4dJDSxqzIRDJQmRvCq2RyqZ8tQJTVLRgYmcyAZjluoiPNVxmNDMzUMFscOSYUkxvOQT3/MmxzdMS6Mchri0GK7j67l7Ggj+DCnAQcy9fQMW/Tp3Cqv7PTR0T7HPs4H2XtoVhQe9fCQIxZ2NTi5bLSwx/4TD5Nz/4Cw4MfklGZyvGZsYGbJBgXGIJE3uWQapfU6nW4NKWs11EGJObT1qvD2MmywaZmh6zCVucKFS7pZrjeaxeaEq/jWz9s4r1dvx4JO33l30g20Rg/kJCZElZ9wRiw1rPwUX708H+TsMZvcTzaUVAZOZVejNy5rAB55evUaClpjY3r5OLpOaR5vzqaf2SuzpWsuoLz4WpcJUutm2hOcm/Rx+mn92tfftvb0VgRzO98hndz1Wbsa5bhy3/PGl583HdgTIpI1E/2LOdN7pF+VPUSV/Zyta6Tf1h2gG+P6lcd9mNacDB+HnMiQuu2lEOoiGWxwEcORzbFkfRxYzJDuuaCLgz2PMU2L9YinsYpTTIhrYbiVo6QNI7x/dqZm31AKz6WiPz/LOzWawR24FD8xJ0c4iHMpXP4POuXOJ7YmBOElauobAAu7IiJsfXh2HJW2pj1gzvYSeR4yVxJpr1DGvJbzBXOYyfeRYwQACTccHvTC1Qm1hdl+lp3nyPGie0HGQ15K1dcz8dKiF0mvIpJMDMoLgl6hW5kb/g7gAYQHx40ZjisC950BTeN+Df9mRLfcntNc3vh+tIv21/er47SNgs+yu4mCZ7GZcRjT5250P957gN/tkSPe5miFj/ota5h+p3eI84ccZ076oU+E8iH2zVDjeVHrf/3wFttvnxW3yNgqaVlVAPyJQf8DLo8WLd9q+JtKdSeLUgWqRh/Apy++F4eDFwGpXCNrZqfWGlppWE4NS20oTQ3qLo8C+PoNrTUs7xr6N+GTzbguvLriQLDKOE0cP6mAVmArjNE3dMUxy+mE9fsTQCcwf0d9ECeQwVqmyeBcYb6+ugO+fRebA6COwJId1eSd1ip675oJS/j/1ho6s+AefgXmJ8/oBX6F8uGM2jcQCBt3xZufwAyMf0NFUEo8D3T+g2O6Db8Gij/im186aPrQ1zvsTbxK4r/8fS8iuL92CF467u7feRzt2b+v8VhYF6kwoXDh9WHy0/Xbg2Zr/8ha+bM9pYCfP9HEX4M3oP2Y8f37D0rfjlhlJ2y7u+3XH+nxFWLXzZwFGL2A+wE80sB5EB712vlgbgmivHkshDsGHhSJfydJ927X3zLjMxkJ5Jm4kbOyU9viiRd92h+ZQNnvfWLZLGgUjxgP5jm3U6ZnKBhISm/g/ZoZKydIO9Lq6Xk2ZlraLwyJgDEF87KgsnlfSn2cyKUkfRz8rApaUTyboGzp0G0OmiJ/w9GDoQhfiMVONyv1T1TRxqYM5lBwG+MISAREwT0qNxDkzxS8rAJIoYZKjEJCjFopUk9RGbZSq0SgN0JtarzDwOAVfWwYVi9SXSwt6j4QzSoE3Fc1CUHpz90zhNuSjKI2dqoIA7lGTOYVZWMk6ySE6EIi87nKqvjedMOXw7iuodUp9flSJWQsc35FIGFOe0J/W/pUv+JKF3itV2PKrDdDkwJx0fl6kiYt6n+wZRqAwKBLjsnIBmXQWnXmVCIkSCNd4hmAIkqUxbuvLYunVScSRX5rC07LCa02Te8jEVSX54un3rVoqnVbcTqdVCE6dH3lHV1rCK7rBYMHTm3ReZaIAvPvHMZcGxPpzMoNLKpz7niWjnC03ehUM8mLxhAXfecex/0c9qbU1yMasJOj9Lvt6Q4JeFYcw2q07poGdIzkcKB9pETMWTxNg7Cypls+6ksQCGNIvdkkVIYiMTrtM+tKfb99ok8Z/mWcsX/FcefFqXz5SAztdNq6afM81WSPzmQy4b0qRWrcEmRPdJJIEkisJTm9sBazsVZ+1aWJs8kmcF+bGMJ9fgbLde+VrFtRYVoUOUW3ZWKUFbCI4HRE+mKOMArIVeujam3JydjKA6BYZ9Z33Nop+TiAZJk7z4ZP07UrI3Lqrz2b23WQK0fPE8LLJz8f9eFd+TUJ1uS3kvItjqaLpb9O7zCeweY9MyvT2BNOyvNH8+ekmEfsC/HwnssmBO62tos/w9P8RrtAFgjYDebGFwwWY5jhZWcvrA9ajmZZFixtkegfCjrS1SjpuJQ0ZXSNus9AGKDMUNXHmIzTOaK81Rb01WjhThAw46GvayFNe5ejdcMRZzKeE6khTAx2tOkadIn6Ye7YVi17s21hZLxaZzgPYDwhkaZALJEa28hILAYFHVInxFIL6lK1TrPUk7e+2mODBiwi2/rOgEehWyaXrUv/R9ca1mCMdXgN8PW0oD5bxiCSlO8k/F0PtRbMqcmMOugyv0KzWZQ2KQsBoFkfClCYMUhqWLPxfhzOhjGXhMFSpbFAaYkpTtPeYs3mYVKtO36MLop42xtWs8LpimQvGBCnw86sEcca4V8r6nlBK2egFtBZyjG5gwigxjHANHZFI4U6d6yXFeVzQSlPopheNnFg8z4pD9xVDtHxlyoG9KLnaoafQiEXDImY7bp3sXVBf4OxaTaxVklxkoaujO4RlqYrKxCevtr+LCXJCYIDaimgpeGydVQAJzPo8sDojLV3cbAYYnDeukSYtAbwIJgBPe87gV2FpyLKttOyoJaK/ryi88D6+CSlptRRQVC84MyhckShgU3XoVZCYXVoZVEk9iH57G3f10IgdWwuVNQJVPeSy0gWjaWGzMz7a6S29X+oDNW74pasLIO5U9iIG4DtGlUAYGyg3fWBFXwBcDrLelWL6FFY175aKlqTKwwn9qee3hDfCghYaCKgQhKlESICFoAtYN5wUzF66EyM8z7mXB4bOd5ZqXgzIuur3DTVgEDKOKM9DD0tAAAgAElEQVTyy5Vc/ncciQanXjIQhlMbr/Gnxs/TvhlTnVmEj0WCdnhUud5aJBmTRDgVeZfhMze2A/GdnU0RR5WhC08MGuL05qy5LYeREFjkKav9LBmv3dmXJCsVFck+5HQsjFP7OZpkE4KmzIv3XwH2dHjn0jxmGNS5ysYF6ymRZBuxUhzA5FAujo2MXMfL+RzFdWIPrKoR6E5/ZcjXiuXMl87c6fX5bLLM03AbanOLtjbHT1eao7Htjv39noXPgYId585srwZNiKACc+S1fQwEzPr4yOZIZQLjRXlecndGUHzqvOsBDxzpqyMKN+D4AJASmxWzZ/yS8pydQeggrc9tTp3Go5PeO6w0hu7B0ANe45rZcf/gPGVYkxO9d+AZWM4n1LaIY9UW9dmFNi5urK7ns+Nuf4+2lWFrcn4mwt3DA/q6yswr/l3Xi6JxFbAA1UkUh3MPzDfdrCoG+uV5Ghuz4BzWlPHRJImjpmcDMlkorY7xt5YhCRKRarvLnV6tXAWbjorRSgsaq+nkrUmXF1gl6yHnQEDTQJ2Lho3aLt1Dk8lVvSc840Jk0B1Lcc4wmpAbifaPDufxoTgdFOUyyPZzIG7PQgdA2TZ0AOdW1Zkp1mWow1W3clFEqt+xsjYAFQaNR4DusX0BTu+a3zveFoyvgUdNmqw2IpoDIvJxIcY5RaLbkemo/RkYe3R7Om/zezx38o/TwHweYYT0a6QZNzievdluPOJnzQhcQdgg8sb9P9/j+398BEEy/ABAff8G28cvHnVs7y8QTGrnm9FcXfBF9+HpHYHoja9X4BZdF3UOV/d+9I9fUD+8Qfv1LQBgfJRFqx/e6GMM/k3Obf/6XZ5sFfjwBmOwBK+R6ohJdESlAvjtC1AJZUQWRAaACrCWrGIqQCvgWlFaw7kuqCfJ1FS/PaLc34ne78s31HdvgbbgtDSUp4K2iOw3CmHTeaqaDQHMsk+rOCWPWnD59h2DgYs5y+o8Lm8eNMPbA8BImeUI3LtkY2j3uCjOK5A1PH94i1aeteySRPe3InKblW5a2uK6aP7X79ien8Gv78D8Gp3/FxgnlA8E6gWFq2Tu/e0LGJKFmVn2JwMa+V7weFSI/AgOaTZgsgKk073d5ptYpv1hjyBwTWbajLabbmvmqQ/68dK7bowlO41c4drU4L5dVueuI94Ju3NCweajkLJ8NtYcUXd0ZN4Ohp+C0zHO95rPm+eI1bFdmiQ34+2Xb3JS+MEY//hBCN3aH3vyrxjPgf9dItBdoJgB3u/T/352cn5qSnYb8z4RqGcF5icC7naNNQgS+k5SLd1qpjCAN+xmZUnrnpVUaaEeWMbz/KPxTBua/VTuejae7zc97/5Imfqckj0/91OH7TGGK/3o6oa5RSoSdVJrFWZIFV+kEVnQyKKTMp+DB7bRQZsyxBrZYpuEtAZloRJCjAvEIRwZEjBkYwKCpW+2aAnvp02s1iypWrvU/o7mokAjzFvDcjphYAOVitE3JwaW5ru1JsKuKhXG6EKMRijnwYqUDMEzu9Afa/UCes9Y74raVGdmDR0W/W3eyNasTOWOeGWmjNNnwvx+D8d6OADauuwALukrdsIw+fpMRvS9YAcTajNznxQBBqwABoUDhK1PVhQ4I0ghzFv6EhdkakXhgB/i4RGtY0gUdNkIl3XF09Oj1N3WSPVlOaE1iXYaiekXpZtFYIgg58KS9tPGNdR7ceubMGcqUBAzVo3yKKR4k6+Fpv0xEUldV4ve+CmUS/N3MkzDtvvGwY0vtUcJDq7X+vow+pHXWuFM50qCEEN5JuCpgnBWFmYlgaZjBaCpPE2oMpiZmYxSq3GAu+HY5kDM8cQt0UT+jDmeo07lBncAy01Yu9NGOyCkh8fxfdmBKgs3Pg5g3qs3CAppFGZXXHbNsMW7/F8VqoZnbU/XiZwxdsFbFRmmvGHa93na2amre8BVoUvvLfUMABh9zZygfGiqU6lakt69l3Qn8TnDS+oFXX2BjSiPP+aUrtdgxxdM83Z94aq9rATTkwB4ogv+Wo61MFpMB+26chFpW9hWsxHSvn+q0Ab82tE4CGJEtpT6FrlpacgEZxc30oqvHnlETzaeA3CDBjgM1VvXeth9Qy8FvXRsW0fB0Ghu8lTPi9YMtuhoV0iaARxKo3RearH0gwhcku73aM6dEX3CBaUof4D4zGvP8b24spfBXNRDv3iE8oRbOIzPvYjlaLDUdATBU7Wv64p1XSVTUJKYMrrLxH5aR1vXvYCcx6jtFZ2vWirMGMIaFW/8RO+bGA+VBo9NI6I1lXspA52GyxG9Dx3Hhm0bUAIBrh19a2pArh49jiGe/FgWKQsC3TcgdxBhdSww0KdKyqOS0JIhUfF9GF/HvqEYSJHtaS/kEgpD+FeriyebSSOjfI5LajfaHszYni/K/w+J2CmRNUX2csCM8UfCVg88fn/CYGC923AeZ/CZMRp7pDYSbGenFgxxZDqfT4IuW5G53zpK01TRmuXgsq0APcNSNdMYoshkMVCczmdJwU7qvDiGpENVIkhQXFNFQc7krlroDCwUDrXuzIGgu2ZIGkMUstu2QZTL6uBgRmWoApyARmYqrEBj0FrARdSIow/QBtQCbJJRXp0tFM8QeeYB4d/CcE8a5Q9d701r1JvDiq01iLH1PjuwFJOLBhoa3NmikEfrmBMCaeRM9ZIoHdsmdLtren6ZS2DdVmyasn7PM/Q+MFg+CeJADrAW+8yGSDOOXqdw5+n7tvutlPQyUE4FE7ZL5D3Y/zD1Xwkc3gt9eGXgtMdD+k6jT40xd3nmjSk9aHiPDE53rz/kyqY+hoO0wGYi9i5gTW/9ew/b+17HKHO5AAy/KD0AGz9EavhXhbk6J+Woo0j5G+/KizeGlLMQ+iRZtESiYSmTVo0vEccWaCTp3j3DupnZP4kyHT6v9kX0GMFr+7M2zgN4v5r7o5zu+V7H10Ec2Yz69OOV/NlImczp3hQByHgs9ttAkbXJ6im70yHP0ad7uN+/Yg8tL/V2ejeCRwij2hyhlu/x9/G+Z4bj5Jmyb8D56hh/yefTN4OrrIxPrp76GXG18QZ5eSjU87tvr+PPz106JtnwmAdnzeTQmmbzYZPSLROXPFs8M9/MP85NzrxzftXMocsxxtBI9IK2NHFsUycwYmDbVizKxzucM1xxZ3TQ0YQbqtNncvA24/WynLCua2oXsRXTnDFrXXLnwwXvdS37Y8Nx/RIbzBWAw4htSb6yfgBAlFokLcupvImgFsVuGmXvpUQAyctDAcdX821OMpReQmk/8HgB2nRvJTyQpuXHByEH9NvMz23ZP/plwl8UKNPwjMwH+3hkX4bMvG3dyxfKOukw/d+EO4I0ybx+YQDf4joYpTTga46ITtBLAn4nENYX9uuIafenb2U3tqXK128Zzg38p2A4QOCGOY02xniEn9Vd9Cp7h++W5GxEpFHNIO8nAFz+45O2Q6jvAf4oztbL+zcYHz9P7yog1A9vwb99jvTQZOwCaVZQMZ4DylN/+pZSSctby/vX/jk+fhU9xMdvoA+vp8nNDldyjXH6H++w/q/PPk5nU4bStt+/Ca768FZk9SoBUQWkjpEEqoRuUedU0VrF0iqW1lDbIuVoVd7Hl+/gWkFUwd++Q1NfuUwxCmFAHBJ4dGya3bCwZLBgNBnTtgl/Q8C2fQfTyXEzMwRerTgBdzAI27P8LkUzYGjfCxUsreF0OuO0vEYtxZ1PoPqeWipqbRroVTA+fXOn/t6lxJms0zNQCGMdWP/1Cd95oBO705hiTVTlufsE/TMG2jvnTTB5hCf+yCHKv/3J1AXe3U4J1/3Jd16/DcCN1O8vEvaX+YIfHVdP8p/gI3atzRql63OBs/VEkMcrGuK8236cfBRG/POH7DFv6r/8+G+JQAeCQQ2WldPv4wfi3h+3bULXS/fE3jHlT5x8o7LjtudHQdjwBa+54CtB41yjVx1CSF5BAKOYgMY2QvEWfPX2Fzx//rLf0leMaWa+j/BK0/c8aR+sFroRzmDjjEmRKBNnntO45Ashd4J14i0Cr/hzKjBoNIsQqus4A5Ccr02IUBkdvK7YlHmty4JKpPXB1e+PBy7KvFrw1lAG1TaMpEI1zxsRCojCQFO0dgkPxihKlk0ZDWFUB4cRtOjYe1WleymiiKoM0ACjg9FhddsITRh1KmgAeCEMFDDdgcqK3qumYpUe1drQasWA1f1ljF7Q+zPGdpHonyTAjyTcEBk0c6wNz2JZJhQiyLRrwQdhYAhhS702Q06YGM/5Jbq+DE/5ZJ6FViuy90hHT0PS8oXHJSMPwYaRmXaxUxpnrnOxA3yPcGCfFVQWYaSoAplxkRTDeJB+Uyi27IN1ng1+XXGke6CSpuxJqWKDFkeKP5s3HgPfv30TWH7zGqALvkMYfuahMPCM8/kO9w/3PqM2/yZAmJd0KeQexVZbcR0bTqcTnp8vYDBKrTjVContZUj6WJvQbDwngwCYISWvrRmfzDjAFo14E98en5/wqt9yS0y4dczUYbpC+3vit41wsDLpgNdCk5qHpLDLDnjxlM0OJSHeIo/ZFYN01RGOOQS8PqtLDQRNAxscjcy1+ThnDMyuPIgoUDMYRBS04wWo925VMycB4bhyJE69PN/58H1g1+n4zjBDjKmEQfX6e/Z8AQ9o6iq4gBq4SN5Xm3hA93WEYaSk9xPEKcR0KqR7RAUDBrmhLxhkW4gd4vG9X6ZLca/0tbST1jJNdDhCxsXRhWNcSXWfZsxE9BvroUqEkvcKYZob12kpfBAMF87R9PkVU+YA5wz0FjZaWlLEmxzFoiEQ05YjE+R/TX+puH9WlM/vAJJRlKM3ZoScpgJK38l4C5sDmwdpvC4NpyWiCUhTCpM5vmk6YosSL2ZYQmxPOzwCTiO/+yYGq23bsG4r1svF57uTYVatxb00j0CvSitgBujetSwH+9gAEr6SYl0iCoUnw/l0Xj+9rEh2tMF8FJ0DSvNAWodtarMrg4WgEAHnrMZDBvWiEafyjBgYL+h9myLjSWHT9qVDhPGIivfcgEnkClKLNjQ+g3L/Ncq/UHGhawwxxA5mNy4CgvO33jE2SQ/KLMZK+dMZ3yT6fGwDY9uc7vXSUcqGuqoTpdZAZwDn0yJ4TefPFLDEw+tRk+0LSISRRLxLtoGVB9ZtA0HwoERmSnQzPJoo+CEqDO4U0cEkGXecRtueKpxKKRjeJL8Hmv1kjK7KSqFtbCjNYAKEQYyySXuuiNTo9HVsOHNHT+oBy7AkexZaM9twk7RdG+F0d0ZpTeqhKsyR7pUxBvq2oTw/Cx+8SYp6GgNLq8a1oBC0liCBWehsUWfc2prs2zFQukbcGxKKD40QFr69WFarhGclG9QAdzGgl1LRtw3ZiTX2V0Ul9fzXCNR6V4BB2NaCUTuIGN14z409LaNOeigsqbgsU6gIfJqiGENkozE0m4Cc37ZNaGXfYFkPGCzGEaVrqOL8UrUEgO9Ikgj0omWlLKVtKeL88/z0iHXdcLkIn4kiqfgv6wXrunpd61oqNnME3kQxyJeItDRzuc1cNpxP+Bc/d1hLFtFcCwEo2Hp3fGo6+PHUUc4abagGcr6EzABYRiqgSPJWxUcCJ4zhKe+JCnixnrLjhClyCoA5XAJGD8v0jNwJJ6ouT0WHwrAKw4T6HjW8xGRZJPXP8Hg/mlc7gq/16FlAUvEbQbd7lBnxsleUShMV5dOSgtvaF/DPq2COZNqmORhpxGfAzhA2alSM0VHQYBAt251T9+KlZiBTaypiiaJl+Z+l30McHwxnVCIPMJfupnmxFgh5Em8fhuDttc7acvo3mKdcLm1+4+3DeSthlue+VQI2+zE7bGU5fDLY6wXa36wdznqGLOn9XI8p3TXfPUWmAgDt+nDUehqD7I/MZu3ew3PEmPEu5CtiDqSczsX50F4Wr+/MXnIndymtrclDNnJ7H8XdGXx9LYFpQkPGsIhncl5bUn8rblBjs2V76FsHVeMnCqjCDSYkqBSmWzEL3t5gfoVuKI8ojc/5cnFCK9uG5XTCcl6AiwTSKPeLddtwWhZsT48ASCLRB8AlZt5loUrq0F6SMX2gnU9SaoRZM6DtZTNzzFU+kyj4VRY5cwxgbFvscY/at3ESGGPeH2ywwO4Um51Pwr1H8VpAg4kKzgeBAOKCVotnozRZ1G3rpPrLxLfbXqlUJEjE5Wwtd8PD3xegtDdq0wy4SHxRRiI6byDLvBBUPvbE3E7QStNz6HymLBu2H5gJVV9XQChvgKX9InPUhzsOl0bgzqhgjCFrVxcp8bSt2zQWIkJ5Q6AvqktVmBe5W/pcda4zRpIsP4fmMADACsaic1T5GiMd4b8932PbmhCGt2cCTrulAQJHDcBl/2eXSSQQ0MYg7cfOPCJP49+fUT68CRjrElzW/vGL6LW1c+O338EASvkF+FUutKWh/PpOZMGPUkv+/M/3YDDqP9/h8T8+us7g1T/fg4iw/esTyvuA2fHpq6qs1KlLGcfx6as8++nbRF/w8Rvo/WuDIvCnr8IH/voWUDmQALQPb8Q4/fEr+ANh0C8yxN+/iW2ACujzN5VfTMZCZFlQPcJaxIB+Kg1ci2bQbTgvC06awr2RRJGbyCF+LcIwNCKACp7AKEPKxkIdcheIvqcqiupFItHb/T3G42d0Xl2eaksDQzIEPD0+ukzXNcpkDNm7rYhD7PLrHc7nE5ZF0s1XDdgaXfWJgJTEKuIMjE/f0FoFr8JRbf/+gu3yjO35GevTM9bLM7Z1RYfkSqpKS42bl+h6lsBEUMIbBt3HzBErcFsWItge2hEZe/rFTA0882FmpwrnN8XRqW/xGgJ44Cc4jMN+7ft76zneX1diT5zz2sUlvvErfgfuzJ8MVr53psz+dNK5RL9CHy6/+KrdW/Zid4L6AdOXVYh/30GB8/7Wdn98/LdGoN86fjgHLkT+jMTyc8f3XZO3Wt7wBR2C/N7wvLHNeA4EQewAiKXiVGHGikCq//jlF/z7988/BU+3+hPgT9M3mq5ft2PPveCycOOdO0Txg46bUUq1r9i2Dt6693PRRopGQfDQWuHNlN7kCq6I5tHvUCM3zRu/QIyuPkYm9zB3pupKyiGPRDXle61FGLhidY7ysYGooRQRUAc3TVcjR1FjpGZmFyKtKSGpa//4ImliEbXf8gIJ4lfWmxFGPYQzhDPqCObKAwYcLHRuyIxFrN8Tc8UdgERGC73ZR0PtV3U+zFDlAqs1DACDnaHIUJWnn/fAprThCmHrmDi1VUx4UezspMYJpSl/SLuTBJmdosAYu5Bb2GGrqLLfogaKMeBqHLVUUiDC5bJiG4zLRQwM29ZRakFrJ9zf32HdVvTBuKwXPD09Yds2zTwgho52aiAmXLYVBEuTLP0SxW5BK+QGyZizULXc3JqchG+92xX0ekuhF1sAfnj1zxx/vUUGe7ReNhZA64XpTfrJsX7ZSHvVJZkL+8o7OH55OHvGKmHmaenEAhNCscKuC8IZv8uzA0MUbKpY9S1vKXr/NvponOnVcNIhEW++x/X1R/pdM55BlTgidNhetX9stHC4TlycK/zjXrJL03v2FA8IQ7TMlf1TdjhzNzqthes4OtVetP3/81rU4+NF6N/P4Q8fmB+b2ey4eKSAz3TB94Qz4uTKQjcgYj9t6ZsKxCXRKXvA097v1syUgUajjP7nqGSQGNNqXUAkhh8i8pqEpVbNIKM1s0uRUioWbT8JeEIjhnqGW+T5uq0oF3V57F3SJFvd1iow6HWD0x+IPCp0aCTr3oAuhn6acUkSdizdpmUpsb5O0dmp/1eH4jY3QmspETOMTpE+pryzRwe7MRoASsqUgsJet3LbNqnDbIZITmNI7zBFpjk2wNczwZeNzyHVHJGM9zO4kLVY2aLklb6um0Tm6n2e0UdhKjtTgAjcuwvtORWm19VlMSL3Tu6QthGhb8mZ0eAVkqrcFM9FmQfLemA4rmuddQJC8cGsZXws3XpWsFZjm+XeXAYE7FGasl1S+QlVG0CFaKGBA2OQKo/ZN6yDnylPdc3MuG9GmD4GyDMlwcdv7zNEb6rUzixOBaODIXX8ahuoWw3+i4Uv7r1jVfq79Y6NJHtAGR3QGt1VnWOqjVd5w23ruvc31FKwaWpU3sSgWqlE2t1i2TJ0P1EogI2wDx5qDF7VkVaVTphVKx71XwIuobwGD1FYc1fDXV3QB6PTCGOF4jWJejHalXATxf62jAN9615qitVBR5TK6uRCw52ZgFSWQ98lfJ85bJLykOYcKu9aNcJ8DDGWXy4XgZciEfWWkn6YkdP2UAf6s/VD3uoRfQB24dt/mkoObMAF4JPg++x0bEcxw88pE/rrtsSYr2UILgycjM4FrZvXPNiQWHMojjoe1C22wFG4y2rs+5HtC4WZzIfgfNBPEP+/cjBglmbnoNTAA+9TjF8+03wMMyTFLTcjRJwGGzxh+rR3WakYv89ke+U3swLeu2PPINYvBmhtyQKFA1f+rn0QNBhc5N/JXkePbZFfbPtHrOb+9PFt/eB84AEg+PQXI8LmSf3BO4+eB0zO3zczGSnzzenVDovMV8/l3eu3WkY2iv1tcvV889SRdOlorIFgjBvm3X2H83FjP2TxYgeuxzgm8+h7Xl75bqtNOwgS2CAMOIpab4pnQ5KX2O8rkeFqbo4HQ9N8aNet9nmtAFaJijTnZwIu64q7+3sAyp+VImnTfd3ZFf9UINltijiZE0mGH3lmOFhalqWyqJXKUFSZ9TaTHgiMvq6+qgY7oicwPlXuC9URGWG4WtbQRwaeyVvcqaTtBTfCBwINvGM3RURvHAwmCR7oxEfb8uax32sBx+kezNt93/xLumR73p7L+NNkSuNFheWkWBuQ87e1RpR+dDcaM8dHg11OTgagB5S3EYiQe7WHa5dXibAM0lroL4yNHYz/0BGQ/eeOx/RCIkIZjG8FuAc8u1E+rI8S1MTBa2hnOAEmwRxid3YCXcC+iQxTS/EU3lHWEnj453s8/esTAMU/en58BOqHeCexpIQHvqJ/TBODtDeA0Dt8/BrPIs0dEcASlMjlrZ5jjE8AqKP9WiVNPxXUX9+gUsX4/auU6YLiEpW3KhVwIaBWLKVgaQWjLdhaVd1CFaN5IbmPooTo4AHeJDMxaaaqAcY2BrhvYJUh5Z1NVsKW4cwY3zv6YAy+gPkk66CrxSpvdBZn2mE4VWZWWlU9xOmkBvTWUGsTvr10kSPHFxR6AH/8iu1OnJdO/3iHsq04nyu+/T//HwaGZI50qU7+O38grL+x06luGxe3YdnwVsaXP61HTccf22P/yTzy/6VHNrrLngeCd/2/6/jf0IBOjlRvXI0vV9ylXAiPuHyapntl7zrH6If9+qoduAcJkdILX5xZlbvvibAQ4GmXTaBnQzDsad2/EvDA4mD9+PF3VSDuBOSDw64dTcnj7qwg2/lZhkU0z3fu58eULDI1wqSR1fi74pz3hyqEN0g0jSF1Ikl5TYI0123DpY8w0Kmym06LKDlbQx0drVSJxBgA2BRLksZTooxJBAAV+gqFxyYrs8tK+I2VZ0KkwDGFKQBojWmmBQWiOKs5Cn2v2PJoVBEGCFYbxqVB0Ap0IoneGUOV9yVSkTOhD2gNR6nJzckrXz5XEE6yentYNQZDhU/KYyUCo+tWaj5+dzNIOeMqVVXAdr0aSpLYMYnbRwhkxMnwZQr4xPhYLcBQjEsjkyLiAJLyMB0OkxHBOW2Y8TyB507gGFh1VIyCBWyVaHxwoeB3gSlFK1p6SyZJeVOS9/awlKzo7rCxNIlkuTw/YzxfJB1o77hcNlAhLKcF6/palJ6F8PT8jO/fv6uRZaBzx7KcsLQTLutFU8QzeLN+hoJUlIdDo4ZoUlyKIpVRy6zwDjwjMG2pO3vvOLeTzNkYAIrq6m7t+4PztP+RmPOfPWj+vH7LzQt+CFHXDBelwqKzJMLePJDV+CdZ2AQOatSI87ft08dxwHF0hH3PZCnRlMncw+Pau85wY4lFlDI0QqAUMKWo0NwnbUfQoTn2BHUwwY/opR324yNtj0Pcv4eLo7e4IUsNk1YjzsYk5KajUHW8WIbdF60OzeRBBFGEIKLMuhoXxEFJI1P7kEh22PpRCFuTcpCCAzTBz9eII30r24gp5kKXhJJCO9Td+TiAlf2METkec/qxr2Gk61AcFKKdgJHjN+krFHSs3SQl08F6+v3wMXuUCxSfBNKN+wzmU78pP5/fi2zMjnWxdbgynls72tdSxNmOCGHArhWtimFb/iTNWjNDd42IViBozQBP0ediPBfYGUMjfzXqg4fSCq3LbfW4q9ZZMwUbM2sUexcln601EQZL3bUpQ0BSPtic1ZwO2/scBldbyb0C2dopmvrc+Jmi0QrmEEIQY7+160axEfXXOjTSk+SHGNA3dRJQo1kRmmiOhlOEtv45T4Uw4pGBzeQIxvM+LQSqRfY0A33bPCW6ZwlYxbBnhnKn5WS0nBznQPmWDfCIY4u0t3dWNR5neKlF0mfL+Salm5ixgqdsACAx4pU0HxINNgBiUThoFPGwNPRgcB8eEQtIFghnag39K/2RzEnw2uMWTSaTSQBtsa+8fTUiw7L6BKyZEjk0j5phR3EcjYG+dvC5h7HfbjcFNADoeKBZdyRTfEFbJFdXTu9u+3vbNk8dSBDXiT4YKA21EFptaMUM6DJ3RMB6ESV3HQ1NyzzVrvHxi9IOHaXwd1LfPNZJ8UwCvc6MpjiAaZ0yqYQTEaSOs8kPDMXXjNFZsh6MgW0MVJLokd43bK5EYv3UsegajDHAvYP7QD2fUUFopwVbH7g8XqTk09alZMJg9C5rzMOM0za+kNlK4ksSphG5RrM6WF8GS93YwbIfnp+fxeEZhM4X52ekEYGpwRq1xAkfEYFxuc4chZ9jBxkv3zuwgS8WIKlrcpJdyhdJJV9PhmcZvKYIdO23/Go+J/ZilxtJaJzjZ8UdIx6ANFAAACAASURBVMk5mebW01myjmxralCiFf0XHY+JGV4DEZpqmTXKzuvMm9FG5S7jE/6uwykwAZEOmAIXJ/71x6+/3S9XoB6dNzmFk/HcZfS4MYyj6uhse2kQSgunEQBaaxRATY4WrPhA6YU5V5dKWjZI550NZ8MN9W5Y2Y0/uW3/uUP1L5kvmUWNG3LHQTuGv2dWi5wGyHmrcpuas9c4HUinX4C1oys/D5nCq2T8asfeWRAcO9cRr40x8eX+XBa6oPfHdk5yIoLXT7fbvPkppRmZn81GV+elqYA0E5/LMY4boy+ukaH8Hms7mpXnEn+cxmVGiKytMXpi/fRygERqkGap7Ztk4NH1/iq1uI0vM1lsXhk6+Dbzndd8f9xDBLSl4nLRWuhGk8F4/P4d9w8PyrqEQ4sfQzONuMO7OMkyi/MYg3F5vmhGLtG9nE4ne3kso617gnciAm8rumY1SuKNzGMVYzyG7vbddhR4MFmVYi8pn8PdOGpbdw5cAoguVOmwRMOacxAFHtyvA8GDBQhqvKPZydDW4zaKClzq02HnJ50jRRDCrrlbeiKfwp2saCBc0h42+mZ9ZQbamwLCHeoitHp73jQrqdXITrBVCFsXZ+X++RsYjPrmAeBvvi/BA+PzV31fxiX/P3lvuibHkWOJHsDcPZLiJpKqnp73f7X5Zm53S6S4Zka4meH+wGIwj0gypepqdc24PioyPHyxFTjYtY3Fx9Ha23wuv0PbdwhOj47AfDgVzzr6nKrd37I5ObF2uH7xgYCTDRkTWYlZCX4hTLhLtCZ82nxMfaxs7LQ9n8GkBucp60ea7/Xd69Dl+uQREdpvH7W9v7y2+60XRqtP714DhhPFsDlbA7REor/ts44FMdjSxAMml1s/BEAjQRHnldmGYVm48PPQ0ZGmkwcT8OEL5HfCQlqTfOVFS8vyiEDXmuc+OOqMuxS9ZykFfSlYyoJ9WXAqjGbO+o01f1G4G4rqpQqgpX/MYan3jnOt4CbmlM7YVpVVuWkZsf3bjvOXL4rBzw106lhIs2u5M/Z62tAfHiBUQOwZ5Hpk22APSmEtnbWWNRz2zw+f0X6vEGHs9x+xPrvDygU//esvWAqr/kO6OhZbmQ9+8xJbrWgP/4H+Xnl1gwaDVtK+fXbIccAPPzz+YNDJY3ssr2uXRa8z2BwuxgRrv/vcx95//O62vh8957HjRhMPv9rePlwR/Q9y/3QEpk8Od0IAQ48ckDlw1uFGG8As24w9LQF4ZhgnNx70z3n8dQZ0E5YMbgSwYmFHOCEExERmT31cp3b+Q683z0cVvvQ5zwS4T4pHMWLEpLXQ7ykZDKGNuicE8WSrt0v23VMokIGf5w6WofXwisyLKHiPw5fDGjsuwltL0NvX7e+UQM7WehIClYsaxktM0wEDJaPBUXCw/pPV9+ah2TfwaVHlVhvUU6i11tD3GkaRUhgnGFDvHZfLjsvloqlObB6KpVVHvJ+xbStO24ZlXbVeX29AG2SFS0HxqMJoGYXQ4yk0uyl/WQrEUiBm4BKSBGnUkFysrtuyoElHEWVsnh6RzEuSQejLUCoxM/a9Ym8V58sZ5/MDLpczLvsl6goSLJ0KswJhTap5Y5YHINJmqhe9CmyJIWnOwYHj7eii2RAIs6e29p3BoUCy9WARWscjFKhxLyyVqUQ6KvcWJc3pN0GemJdpIdsqlQToDU0Pppj2vvh6FhS+M2PkJVLYQmjUl8I+aEdWEvjaFrF93NGgyq+HB4k0pctSsCwGRkBoXeuoOhPWd2iru62xy6UN4Nk76k749u1rRMt9u5yxX3ZNTWXrpLeO8+UMiGitTUCdRdirE2mEFx3GTPui46xGg47eNUdbT/PsfUakhlXl7eW8Y91WFBZc9gpCmafG5+oRLj/Jk67I+QPgKJ5//ecfO0QNthClQRFvTzQ8z/2cmOHVAHkxIfwWfXXjyNwyCcWB9lb73b0ekY0vmbEq7vJUSrGvyJQAFPvalSv5bZHFwp/NQwGflbVXTX0EsPwQx0yTquP12BG1yTxdJgDPi6UODD1fPB6aju7Eyhqvdd5s/0Qd57SO/ZrUkWVbh0OPt/vRRvv/sgoKrisbbZUcfZVQpe8fGb8cV/1omtw6ed0eGnwKGHP+1A3hPMDXSH7d4N1O95S/aqTjcOAiqGd5Hm9fd9omqEFWLE2iGbXi4fZ/pZWWCtvGsaX05Jp1gwAqKMVKuXikuNE7b7tHD/u57XTCtq6xDyJtOw+jqae29/dpqkqf79GvoNE2VoUZ3eoD7ylq3Y1OrQnEbIWtNuxIhhMidYjqHaUUbCeKet3V0rqr4X/Mj8z/S3ThOK/2N/PEC6+VlNpH73OOwI2o0XDeG32P9WvY243Sup10DbbatIZlSlcceL4d08IO3tp6h9uDmrTQGikrpHBaK1Y2RWvKL1BnNcH5fFHnCC6ApU0HoCVWACxl0TZ5XXcAYjUqq0ikBmZmkGg6PGyGk/dd8V0y5BPIxJAe6UYfFo60elZvBos568CuVbo+cJBHKw+64hH/MowkYmt/wqxDLvKbCQQwoYg5fdqO9TT2vlm6eNS04lGQ8Tgz6LNlyonU/uxRybYvbP/A3i/wKHo1rErv2PdmEQ4rTs82bGULfCWkTiLFnuW1Qrs7K1iKVcHYE5FGljxirqN1la+EFvQGVeqQK7fFRRPl+cmpBHDnEcsBbXtY4Gm/7bleb528HAUH3uy1AYUi2lrrkquSVdNL62eDjNqmSdNQrBYhQ0xO0RqzBHUCcYyR2UOTHk4VvuWMQsWaCvnY+UQsGDVmV1RL2bsbTqTAkZFIxvZba83kt6KKeCZ4YXmVk5rxZNH9ZhF/rWpddo2IF/SzZ2aweWHG6nwlZfewTZkJhK31YcSXCVFfH3p31Wa6EXyffw0TqwzjebwyITXn1rQMGfmKeVtJnAMUuj5u8vT8ruPZ1CdXSlvrw1kh5p/GOqejsn7gWaU5NgKZ92dA45926s9rUXBzIAJ/8Ig8o7RvvRxV5n8Ge8AYpUZ0T9JYs0wQcJyjkJBdSdTRGxldS427NfiWNjlrBnVPKK1TBbIq7ztr+lXw4C1HTEeiKf8Dt/pjMZT98L99/mxtKSlzB4lbqlF3ODOZ3drtz2HSUgzuzNYBi8oleGAHdQZYS8l1NHRwZK/y+YkFYe1xJzdgxhjRdVs8t7JAPO2wKLRw/p5/C2yUtbfxt//voPMg4xFwnDPG0Q0ugdON/7ljhPfMxQ9JZq68nG42R9IWM/7lNWfH7kR81z8lPX2czX2fRsSwb4p/SA0ZFACG62c9Xno6KU8OHYl9qrO+rplxzLRrdhp4hOQdjsCWtqfcAZGwz1vUAmXODw/q9LlelyH00lmMsTZdT+v74/T8J9SHhxjHfd+xElC2TbPDILEgGnygne8Dj0X2loi+He/qJlw7bxuGBx07dygFENmZgk74mDidoJgV6x6B+mFcE93O45HxJIxHw0q1sMnbnNLcA7fyJ2B63veOeT/5nqCxpp3PHJ45HKEE7ngnabkTLBCGcgYjpeHL8gLu8Csmx3BhEBXDCx4Frc7MXqZoef0y9fYV6JXR5sR7BMPBktIemZGHy4TfX+g0rZLc/3n/yOET1oazMYyTjNV0PC6278/aIGxRvsDa79neZPTBU6NHx+zTkinouP8O0Duj8+/NkP02GdSNzvX3o955efPKliWhvH0ZwDJoUNovANB+/ahZeGk8O49LN4M5EyAfRv81Jbil1wdi77HRWjK7g3z4Brx7pbaCkGME9T8+arT5mxeaie7TPUopWFeVL3FXI2tdZ0LTCmHoy4JnZdExIuAnLqjrgm1bsS0rsBagLNgBPLN9oUEXFgxRCh6YgFaBVnHpQ97epWOFZtu6bxW1duxdHWPbXq0c0QI6aTnD2gzPG01qEI3+Z+M7PsMy1unl/e+od3e4XHbIKhooB4A/Q2VqFNC6YGPG6V9em41FZdCFF6y/vMK3//Vv6C8b2kVLRHF5DX7zAecPgpoc/8kyp9o2jzI+w1F4OEReByCN45ajyi1YMTKAzOcm/Dz9mDCEU+OsO5kaMd93693zozMPx9MY4iPHTGPm5zr+D53ejYHpSXfxPVo+2QEw+uC09+kNHu32ufsRDMz6gel7xnUyrj02x+l20LejJJQa8Bgmfco1Tz3+wgj0BC6NsblyDd2Z8vBAjPQdBxCRgenVuel1cvjRvAVtjrRmeYK6hFCmvDBwWTgBUWvfC1/QpHCbwmCYtgBRRKvk7g/MfgAmAQwTdrrdq3yTLn+7wZPTEakR3SMvI2IxgP48aq6wa4bOFpcmkiDVk+JUf+K4zw1zJDoeS2GspQCl6LT2jrrvms6kd9zd3RloFdSqtRD3vVrqR1jElIJpQJnOQsC6LFiW1WpMWj0b8wyNqEN4bW4XTtPYQiKVJMPnuoCtb90Ui4IhwKtyeEFDCwV0D8X0AM6LsM3DEhPtCs5L1bSIl8uOy3nHftEItewJzURmNGJVovW5rqUPvCv6fLEISNM6wxSXtgiDubIBOgfTpOtV91axCP1mDNlqvIsqKY6MZUSbTKdV0Sxe61jgln4XKI6G1ewtOC1ne6F6K5qS0DizGkNsDXb1uBVTojMIXJ6rMrQwpDc0nOONLkCSPXddFghEDSLikXZkinfg/qzp0rdlBbCqIpK0Bt/eNCINsFqnieALAa12nM8XpQ1UjPg3XC6CWhuICd/OD2i1Y12LCfJsCsqGwpbCNdMlc1fd7b3EHvGovWMirOtm9wwlu5uRRZIQJZ5al7BtOhd73fHi1Uv0rw/oyZ3O9/dg0nlNzMIhxanDupmufoROH88+Qva+Rw0F7jkvoK5qVsUcOr4NMmivzTdBTEFnNNO8Y6c223UTkw+6aZF9HlVukf0UwqPTxxHxj2RIZKsH69HoAEW6Y0xt0nklo8m9d5TFDIvufGYNFqaJbky8JBjZEbgdB9rXnn5eQ9c0RmLDaS7DYgoZ/c/T5/paMX7SOxq505L31cpzAEbTk7LVlMNsmQXKsmhUWTPh0YGZG0689a5w5ENfDXgP8GFDM13mNAymKBsOPtPzQgk6cf9xf8YtKd2yjwphCEkuuIYymo6P5Xh6bupw/BrONtP77JmuMFVjcxk13m39EBcQlUhDrcYvxDx4NDeHsFpCYS7eflGjU1k0kwdBo1Jra4oBWteUvEzmnLRgLas63BVXAo4+ZSM5kRqyl2WZ0rK7Q1BkjrB5ccwyRTbb8x0H6P42o7sU9NIt9fsoE8NEEDPgttashnUPw7wqdfoYR1JDLZMa0al11NZRFrlei8Ao5TKtlfnvvAwEY837iaRvi3XUpQPVjbs9hNmRMnx6hLbfjAataQ1xXf+CJprCfXBUH+YkTh5wuvZNvds9ql7TxOvK18hkwraxGmVXXQeO+Z1Okmh5HwLQSbEGQcuZaKrxaorgkflCAIgZPwSCpahRvng9dtG2oXctXCNe41T/FtE66bsIHu4JZSmGMziw77oshglHWmkNYOy6L5AjrzHWh0o5Qc+Pwi0ZM5VEzMgclFTZbZHsXSPHvPbwACLQCGj38LHncuGgIe6gyho2P7LcsGfV0II+YhhdaEerO/Z9x3Y64e7uDuu2ARuHIUKzvqhDoaJxBkmDGrkqWu22JwkQK3PQWqJnYv0COtu+IACWvUodSAhEBYBllkgOP8SIjBAzwx5R6NO+8n3jzgT2fmXTpqQVUVmE2fJjCpqWITeHDQmMqqnjnX4BC6ksJL1FyvVarVY7m9xGYgY6rQ9fiCGqLj3ssdvCrnRBpwapgl4EqILqtWAXAmS444poDctFOlZZsawDvYmVR2kikZ1CxxlRaqhLs8wNwzCu+Ha3pcPmvChAU9xLzWlPTEXqh81RJmzfOVzu8JrqFP80JWY/dzWc77p7+GSOI2vKCGGvHEah4TgczfC05Q6/jWaz4YuOrnXgLw+2X03enNQNFBGkjMTfrzolJjceMcr1qZnxH+hskq0IObr3ENFLAxdN7/rR4E+NuH2t80oYv1K1gI75wMKUMI6P+6CHOsSW8WyhoLNs9IoKAcSayQ2Ol8aAEQxXO38Xx2uimT6kx7goPmNEJjZTzLOwZRFURxshsa0/5G4A5hw61hbJPD2c8N/MFx0rjxGdB5Is+r2lO6wPPrbWR4I5VssYP8Cy+Fk+X1kFYIZcGkgWhOeJg97D5vT2cGq7YyftvmhN1+/JEN85zH8J4UoUuCmuMPzp/NCjqb2ZA+xkJTnFnPpes8w71s9uu4RIaZUrpcNhjSjtn+HU4xhnBIwYDiKKaM0opUfFHCfzSFrbgj073TnmjUzMGj7nTvfGftFvacxMzwDbD+KSlDnGDWO2OjTKrm3dTitY3DBDQRdKGfg4euDBGlezmdpM12uZE94tywqQ6WVCbvLx0aPt1RwooXzZNrinlyfDr76jiQs8UMHnfil6rl523d/SQcsKaZa1hQvawz0QTnmpN3GCkKfHsx/p1k3Gg0QPPUCo92ZbiyPLgfizM4GgtEbZZ3R2mBTXqVnfSmEN2unGVzuB2J1jZewZZrSDs+uNWfvxke+zdRilmvySsUjiIy1ZcNq7fppBWF4+ByCWycbKnCY0XM/n4GNMDNpUP7NfrGFE5uPOKDwQElsmN89IJ9JB796g/v7pinOtL5/rVHz6OnfVacIjx+Y120c3A2flPZd/t1bHe7akSM3sPq6hQcvuYMNrjSrkMkdqb3p/PDdhGw/68xXbzDjOb1+if/iM9uET1l9+NqPvJxDU6H33r78AHTj/+xnLu4L1l9cT7XJnB9dVqVOvoLx7hYUI9bePIRPv7UO83z89U66ZgNBohiQEzRJ1evca+4dPFgCjzmH94xeonomANy+w//oBhQjtwycsvyzAhwXsztmfz1jXjmXbVHe7qCzXir6T1s1kOpXlT8T4qRRs6wbZtshoJyS4WPCf48dGBKYC7oJ7y9Lm8rLz7iZAbxWXywV7rdhrC2ebh1rRvj3onPYT6EWPPS2WcRFdojStlsJTmVDQUCtw+vmVyq2to3M3+qbYvhTCKqo7Of3tjTrVNcFeG8pSsJ5W8L06PTO9ANGO82WHEHD/wegUaZbmLoReHNUCtc4Bf248Hw7jeZ1e48/JQSjzeV/zN47M9yeuJMff5+/HIKm8axxPHolEvOmqMQccHU+a7zt+H0fOQzHjH/90G+htzH7rvQfB4QpjGBZXZgrAApimdprc4u/L8pI4licErk+yT54wcdxonXOb2dScTAwwr414vb9/7tnV8b05/888/lulcH+q7CaI+dbvMoSvALlJ0ZAXgwO2ca9FcPh1WUEhgm+2c58lRnjcKA3iFRuDQV1vr3l9+L//7GM/fPeuevuKkYnvVbj+/pGI4AHMu5wKACCN5vT6jyKa3rCmOn45bbYG84z5imgYYhCnxW/AUIFWt+iGhqH5SCMfwIci3bhv5KteuQLF/++E24VFfz6pET30ZSKgUJ7P62ry2A7FYbNIpw6Rdr1Qbox3T0qnGGxK4PTwwxXtDYqEtBlkOn8MLBWL7xgsBdPLaIwUjmdNzsGQpEZKyaOXUxZStFkHCn5rl9AQBhU8bGApRhMIyzNCf4AaN0RwHLrxqe3x9Dj+7OgJmWcrqbLc6+xGO20fuHEFQCjVAaD3HWXlEPIAVXJ7dDKEIM2dAdSAoEImR9Rtt6wKTNqXQosxft0HhSwFZxheVEhwwORjkjl3BiNdOgosRZEAtTZ8+fQZz07PsO+u5DZBxxRMp21DbbPRSKbR/f7xON37+yhiXt4dPfCIOw3N3tva6EHT1UFGbWNWv9bLV4Dg0TOKNQ6G5KNCDGnfg2L4PdLB0xtb46xBufWuxBn7zhWB02WAlYAYhmGJRv7Q5eqJBx0+HzskTX8eG+j4kFyVZRl8FuEI4mJU7DNP1WaC8DD+C1zpTiBQGcot8v5PyuI8Jzfa/mi/E63CmHcHgl5Hr8BSgQ4GaLeP9ZUfHd/l8INdHEATbjynqywS03MFEw2bDHFZcUtzj4A5guj4fDWaO/8hywhTzIt7tb8ZXBaMOFsH4hLG7lK00702lNbARJoquXvtcku3Hs/zaE8OJ58w2Ifh3g2Yo59uSM9z5dMwhDd1ruFi42T9J5sOpWdjrFVIGMZ8Oc4x9Nke6d1sf4fTBmnUpht0XXD0iOF4Sx56W8NBo2i8J34/HEdhIxuxJ2WwSBik0xaEAwEJhxZV3pPxJGlGA3vHnz7s3fmtIDW2eJ36xerXjwwIAJFmZhG446JGqIjRBMdImmrfFAcxB1AlI1kEdKmW5aDA0bo7XRTPicVZKaSKHViKf1REClQPRtfeyJBhjHerA6ug7Y5ZZ0FueOXjak6V7w+URfZc77Pe0oPuCQkYrLwv9jmhVQFvFnGjsE6xtjn2FYs+j+gJIIzp3iKGRxGogqYDUWeeQDidNo3EN8VS0D3rSG/VMMMwthZTu2g0pMkIkjIiOM5pDVUQZTrceQfFHLBaQWsLCmsddH0Bo5QFSxlryN/rHDqrE4J+Mg8nShh9d8wEaDYmePYwows2TxCCMEAYyiI1JOp4t2YORaVo2noeThjM+m536Iv2AiB4piBEpJ2ImCEfoEWjsaRbFJ7TP9fJENSIRqLGRl9nrYNLj0hJdTrTOvNYACItl9VtABxjSlrHxqEwXC0o1u7Nw/DJUQR7GnJ8/HDkQKjWggK5TOrj66YY+ZM+DOdAxpA3jsHi4rHdnIbjRILbNx/hctAVHhqPT5wrYZ7/4uMmLJoNccD1kPzwoPEhmUYLpnEJsggAHegkYLFsD+7D4jh+Qv8ABT78XjtsD2PoBlA4oGzgAAJINNuO9G77ISgCIEpLtOzSjKDCEcv3RoLTlNsRi09sR41TsbNCB6E4X53f6RoLyM0/oxWBjel6DWpzhhMkHc7/px+HxTPJ1+mC3M1sfJzWIQ2dgMIn5VlR1iq90x0cWhYR3BHzoOcjx/mpRUrxEI0XDLwVjxQ1hmr2DW9j4uf5gXlI8nvlO+tYEK0YjiCHZymki8943ZH+evaR47usP/M434SfPzwm/VhrePbsGfbLGXudtZECWGaUgmblXVyzT7ZHXa8Y4i6g9YXtCcykWCPNx35WZzQ57x7IDtAeA5Ljs2MtscsXDMiBI8iYKxh/hmMfceP+GHSFCBRyxjhPsy7vaoAdsfhrEz63vUBgdDLcYZeyOQz8/dz19vEjuu8tvqZB45zTx+Oz4mwwY+PuH7+AXz7HWrbpeaVolix/Rv/8Ffzyub5fBO3jZ/CrF0iwPq4t+UGp3flzles66KvQ5Cj1R6ij4BF8cbhGoJHngKZ1P+67c/7t0IbHxl1lBdO5Jzn3eF9vDf3DZ3vuiD4fQR6D24n0iF7HW4D5jfH2T9pofjWebFO7lDeobz+g8Gvsv35KGC7ckkZbfG6M17bfPuP0yyvsXg892i7gt/rX8o6B3y06+ncKp1eBOUVDHb/YMt8tS0EtBZeFsC0rnnPBGYJT6xoAwIy7bcO6DgP6g+llxQ3oINxBA9g6Oi5CuLdOuS5Vs+2qc2qvFed9x2XfQV217r1Wa6OAXrjz+D0gd/EuLsmp3zKqKc+uWErBui6qr7b09Eyk+szCWN8s2LY3wMdvKIvZaERQ339CefMystdsf3ujzkUAHn77iF26pbgn3D9SY1lpUl6JKoREybgrFnNr1/xZenV81q1nZ6r0h5Hrzaf9Y6jr33vc2v3/CccfeszjFzum+Idgyv/C47+PAf2pq9DBid0UDCX+MCHmhjIKsKhz6OTdCeGeOk6iRnB/his+4k4i3Id6QIUYB4MVAo2toonwuz/y8IWFt8CM2XQT9B6F+OsT87WPLT+CGskt+Wu6R6xdA8I8+oB0NIvC2IpHBR2qqqtlKRpMVnODl0WVXb2j94rdalZmSjqS/xHU11tcLg1mq0pTG92uEFJE0KpFXFtEgHsbu82bmCO6RNOsD4OgA1k3ghBcsBJLbwMD6UngxGIzru2k1uwdB0WopTN2ZXnrPYyOrXkaWwwDbxYuDDq4N60r8aaGe7Y4Pgo4jzE27/DoOEGAO1OIXHyHFBMUbC8kBf/gFmIRtjROOeRltiwM+ku3cXNCGbWOeURQAhTnZ0/sdLhxzcZT50nfsVDB+nIb5Qp6B51UGV+/PWg7DqPjzhuq/JgXO4HU8zkMehphzoXnvRRfxIzbWq9zZCQAyq71tJq0YaRpApEGKoRlZZzWE9qlgUForOBL0KN2LggWEapz1SAoZQVbXV03Dnm0m6bdVWXz7hFR5iJbzCPbPVZdENP0sbCa6AQQY5GGvQ7lzbZuWJ6vAAR0qShFI1dr67r+YwZiYv/UEbTyScz1MHfTV4s87bDa9VpHV1PyDh6SqIFGwbGaUTxNlO5je3BS+EUbXekDWMpxGhHQ4VneLC1teiuRvYOMrHXNckLjn6d+hcBSNDaoEUmfXczrPrcp5E77381h9Pem354y3uOSNB5pGPPchbHZFHVSBnBqXSN93MAhgkm49cM95xcsSZkxFFUdw1vUefNxXry1MWc5QjPShPPEqV1pKfkBALxmU0Q6GGENw0VaJ847fODI0plP4+lfLR30aKQNajzuMUU6TX2L+2w9+yPzeGi6PF8v7owzGAyRK9Nc3AxuoEbGpWDbTljXFdu2YfWyFsZrATM4QiwbwaD3bWmotYIKozt9Q0697s5KPNUtX8xoz1xGyjUZOCa4FDmGszSPSPxVMPAf3Fg4BjToc4ABoxtFjUolhMDDuPoU9h6pqP27R69nBT+RKvfY1kTQD7skR5QPFuMOUiP7Qcw0zTRD11Vw7cAGXjdwMtqS8w6bZaMLaky1eztA7FHSw4iW6eJjzqW3Do/eMaQGN16zz3FZ4p+PQDelAbpmISISKxUBgCiMudIbqoy6zL6rIYJGBFRdi1633muyQ5Q3NjdGi+LM3odBXqijEkEKY9lWaBpJw3oygFAkQwAAIABJREFUapJL4EyyKCmgs9XGDvrvUVJkGNTSsceWHzwlktAgpiwZzgc2FGhqfOUnvg7GswCAixkUenKysSwTZDwydgUl5aY5VogIxIzhDMVzzITLwwlrWUGe/CaeoU4KtTWdk1rHTjC+Bu9L7zp+luLdEUVHRxVg8ZIyhRJ+HHUMiUkj22zMipUB8MwV8/hJ4PsBAcyYppswHHVBTj4ExbFWayAqAGuUa+QQEY2E0r1Gg070gsKKy2B4SwRjzZNnzxgmN50Cir45rnS60924YnJk5sMAEkYG2lnHs5n8jEWfe7mvQC8oWMCsuJ47QTqHIQpkmZzMabl1w09d1NFQCJUI7tQ5hjVjq/GPaNDtP3z8gLwIXDFdbS7VsSsbQ5T+Wuml5OAdXN9IQkIJIwIXlJz97J1Gj4lZM6SVBQg+ZPLDYjVcLXX/lKkFCINffMkLM/fZDTUH3vUPOfIA+CHfmznDFX5vfsZVc+cT7AkxxPlTOg8EnetWBgSd0QlDlzHgy4STvESDDTaGYcvehZ4nWSM9RVMIE8GcRpSfqhFyOPv4M4mAXoBuYXOZdgbaczmaaJ5Op/kTbjuOlcDTW3ua6tHHsVZi/x+fn76FszcpD70WDnzgZl4e03mLv9O1vu1px+ircxqZf0FP/bsJLbK+QAy3yhhTFbmMDwNBP8VGJmT/INSI/eUKXqcdgEfSOckdOCxH6Iv3SaAZDAxfO97R7Z2YNiHmIXfR8d6tbku0webE2zoEoLT1Ehb03xznGRbcawURYTVnrJ6CChSjeope15/lp+b5cP46xtG3eu9aFoXWBWUp6LVhWTcAO6o5n+a57tJQitXWsI0lIuhVQKS10LWsigYpSBf0NjLzhXgb/NadN9WZzeW4bV1M/tF07y6mZxnfHWDDsI+xF3JEHBdG3bVUoIIXW1Mmr7h+moki2pYson5k99P11tPO5aVo5sH9DNd9ChG206a1pbtAatV3hC5W1/mcL3Tep0nsGwvr1okBM8a9ePoR+8Q+Cwj84tmQwewCJjOEJxmFrMxCq19QXj03jKy6fNWXFPQOXC4X5RFfvoFfvgAgw8H91QsANsaSqYpVrAEgn75ie/N6CkLLXc5R4rk/3+PCznr8iHf9YLyycX2bMNXcttMjD4qVRCZDCKY+ZxpFAMrb12jvP6J9+Dzamv4GNDr94f/7FQTC8u7nkf2yd4h8go+EfAB2fND5+1m/r/9DTU3lb2+0f72jtY8geql78JdX2H/9FGNZCVj7SFvvjWeo09OZBOffP6OAsGH0g4jA9AqnZxuI7tC2C/pvn3Xtst7LYrYRAToRhAvKUrBsK+q64CeLUr8j1nryq2Ahdeh2vcdqDv6rCO5dJyfKT0426F+pYYnssRIyYm0d596AWtEtk1e77BpU+AJo9xW1d3XW/fQZeEEA/aTjJqrxUh31irbvuhfIfG+xYi2jDFWxjCRcNPChs8pEz+5OkNMGxwSFGeXtSzx8+w9cHoDLvmNvDV///T2+3j+gGTb7etAZzseQTdx5TdnlMKJnvAvAdCm2brJeAsBRt3A871h0XHdsj0T/ADn8PvSi7oB++FWxYVx0+D3AyPd38hV8fuS6A4e++sXPE5JOC/NUyNXV+feBC6Y3msLBWQ8fxvI2+hi/EBBlGMVupLg/t+j/zuOvNaAPRBendMiPbOfGkS6JCAxI+j5AdDK3D2IME57seIj6bDc2LABXXM6pqgY8PbZ2MNbRsry4f8R4/5HHnxF1pvuzsjQre9O4MVEougcA0lSN+76jrKt6/pkyqlZ91r7vms6x9lASev28oeQwpm01qHt3sKzPcGOI10+3xqmxqqc0r9b+xyIHnaC7N5gDPUGFRhJrfUtIS3PpBMhqWhMAZrTecdkvo3+9jYikNG45xeL4d5i1PIE3aNQMsub5cW/qWbEqcINRfqTKeVmSwABdqk2PO5ywqyIWZjhRcy9oMLFRG24+IprsICULEPM+PMwt/EA6Cp6h/FQilRTI/PctUggiExi9NUYxVkclq4EetkwK2eCotVrtOZY+mtiU/5YubSnquVihiuEeJh11r+ldFWuudNf6V2QCH1k0nY05aWrVsixYsOCyX9AtIkLTd1lkI7R+L8U+0Pu9Ro3TspgH26fDy57C+LKsGyCIbBEj5bClE++Zxo7U4/DUrIfR/j54SN9imJ8GUh47fN9o5KHVxiJN4yS1wdUz3l42ZT96N4eFsbmmveEp7oCIVAxlhxkMI9q3DzopAo3q6z2yGvjWl64OGDrPPLJzWJ1VjXYsUSLBAeHwRB114DJ4OSqdhqHxMOo3tVM/GNxEFuTGZ3o4AKtdZrf27kkU3RHnFnBGeqJ+BDny9et0TA5QggLemWCVuHW+P9O2Gxx5WsXWnql/0Z4x3uKv94OdVg4l6uTwgPmGoJU0j8tRg+HPo9T20f3Bo339jbnH1W8u3Pj4eFRkZk9EmgpvWRZs64rtdIe7OzOgmxHI2zAcdMbNvQuYa+gqG3NKBe48wvZJEqZGbfNhPGdzWmuJuPuMHw8f8+BTsekcEWaDiMALWlKMg9dl94h3Aax2vO/X4/5xw2tWvhIjGdRzu5AETx6dcLyT8MERm/qzfUy0v4OGe7S42H6NTCXO4RLOiDGxTSZ5jUQWHC99A9uPf8SLOKS00U4X3s2QWNxpIjCDrz8yDNgjGqWThGJcPfOVzjcRSFVs2KyckL1QU9+x8mFfL0SISDFXtIoIOhteIU/rr1EZAoBrBwpBiqWl9IwxxlOiJra/wNL9X82h4Sn3kXRZxtusGRFcWNUa2t2ceHL9NsUqhMnzizBqqgvCyQcErOsC2DhLF1XQ0ki7PNa67eBeVfncVAnUqu3jM2MvBfVyQTttZux18mvYGpoaVswRQWkR4ElipGrd71b1X68t0rk3JivDorpoZhVZHQtODks2n7DsBdtJaZO3ZWDWpJyN77bW09zsImYEUczme8g8SoaTMGFkJxKC6vB1vXrNc3dKCbWDramyFMsC4CUx9BWX+7PWWk/7kYy/RE32Yh5prPvT+5Hy0cca7F6D3j6pwdpOtudVlmEidC6KRbpilNacV8P4gctmsfLMh6RO9DXktZTifaK/E2k4Krj+/kMAWFEG0F7QIeCVU9my6+NHpGwy1gLwzCSS1l/vbcrC8MibtIVXYAnzucfa8wfh2n/mcavJt6+aea+HwmZHMHdwGk69Q94OHgro3mGTuc2YjQ50Btwgou+jQQtxY5jSuGZDu9I+Dm8ll9SYSOm7GK2y7DJhqLI9wJ0A7nM5lbHbp3fR+DkQ8EjP7HzY+2KyFANsdcx7SxnTBHAJN3DjcZJ+OGHzXN3cn/lqOs5t+vzBkdA8fHwQrb5W105Q6GZbxnXusCQYgcAwnqlpydlwnc2FCEqYMQGfItVXeQAFDcf83HfnYQkn+TPcWAUo/yOG1rVObZ764xgBhzGNnx4ZW+cLqU3+gnzfpNeY+BCm8/EpMtKkj2WWWgQQydVc+c+UP6d3CFrTkngoBbwUc1hnUGtp7Tm9AFqrKB60E+t5OItIaynrzMAFITu40cb3gGelM3kky8NDJtOLReaxFUjoE/07Gb6KuWVgWdfIztfTtS5MhSrRMIfTImaK7FX+zGnZT2sd+iyrjczcsa4LaqtA0+xaUX4F832+RyY+huM8X//2o+Mp1/kq5+fPpjO9C9qXr+AXz9A+38dvIgJ+8RMYjFJe2Jibvt8CI0CM/XwBgVC/fAUAtM9fUV7+FP0cbfs+bWMirG9eo334qNAKQyeb+8c3zpXDtcc3ZQr/o7HKUeePtfyxntx6fhjSU9vTTlPZ/u0rtPefbt7Pb19O51S/XUJ/LR8AfgvIB4DeAN3rmH8Y93Qve+C6DXqJ/v4zll9eowuwvHuJh/ca8b4I4cKpfdbgIsACwvKGUD+qQbyTlt6MtS3DyYzIshMwadawAuw+CKRynxTWQL/1hLvTim3VUp3PiFQw61rKjZiwrauWj7XvJF3D6XoDdcFd2tt3YhmBBSabdlSLPG+14lx38L7jvO9aCrQ14L06uYph/AYCQ/eK6h1VN8kmw2o5MWsLdBy0tB1pcMOm7WXL4Ne3Fcv6Wh2lF0bvnyHYFBuD0OkF7n/9X7h8+4aHh3s0kJaKMdlGhT4GQemUckd3CzG+SMGawDyM6G5UP/LywZ7I1ta8ujNtTmrHOD/upnlPDEKZv1zdd30M2VCmc3Tz3h/Cq/9njiz3OfJNv4oY9hgywD/78Rca0H3D+fcEiiROJdBwZIF+vQsc+WwyHEzn090i+AaJtIh+zuXjoVql8Zxp8/gmG4eSEj1T8BIdHwEQTj//jIcP7zGMlBQp458JcP8H1lGWiZ5y3UDAMwT2FKtDuVHG9YQrj2K2KBsXcDmAn4NuHb/dQNvGG7isZuCxlI9do880Aq0YntVoRNlVKHUDc2td01dLB8TTpFjbu1gUhCt91POfwSjmKVaWBcWFYgekrCk32UC3MKOaYQ1Qj1cHl2HYFjPWswPlBo3GITNaHohzRrnEuh6a1rTe94q97jYGzWorekSc3+ZjnBwzyDeFjFw2Y2LsfnKZ0AQYAXAB4KmOtJ1uqO3+rrNGghb2erDV0qIvtkqL1VrRSH9HMmxaUopV7YoQe95isQF9HpejUBcKWh9F6XDFOmwemniqUAWp7oFV6A7Lc68tLmhdoi6NwD1yl1BqiJqyx/QgR77raBNhjLxAFWRsSrfeh1GZABZTQBaALKptXddR79bWoUgF0RaK3MvlohFcBVpDEsBlv6C1jtNpC4G+lYYCiT0JA4OttTBXV3Hvce2D189ay4LWa9QdCyWsp8ImJw0U0dJk0gJbVDMRYd02FHNWEcF4HrOl+SS0ropvuGjjGspBhGJt3z7GmiZSWtNMUXb8/UePuEUXnaGr16sqn0rRGqqhUMGg+eIAllzY9E0lYQBTQ4B5htv1ChA8tvUgklp4jXuZs9dQ6kMx704K6+kEaTaeXRWLl/MZz54/tzT62p+iIaJhGIh9dAAmk7KErvdgNPNJgMb2hm8Ruv51fr8Z993QVyzDhayhYB/jow0hM05IF2y8wdcVkTpYAcC2bXGNr2uS7LlNUe/QD07PmZRUlByw/NyxY/YospwuMQ/OR7ugbGXUekp9UsMX+QOsj05vXPkzwI6RiRgSZUO6VvkqQ4ffk/GUpDl2Ok2H3yhoLwNRP9DpSBjdTZEddcctdft22nB32nB39wzbqllm3EACwGprD6NIFzWSMQ9spobeHsbH0f6x58JIZZHgHp1O7tWcIs7187E1nPjQgVbkiLeYCjuYlVaUhcGtYOkd1UpkiBvy83o/7CFBGj8kwzZg+EHnIhz9fF5COTrSrdMI0bNXGZrk4VSQ2+M4QjNXzLjVf49mw7PDSFwmwHBMS1hcRI3DyhCQ2va94yB02hrzWsnF0rZ7iQCPGtZoG3OyIIvUaS68D/l4pHDXjC+R3cAuCBppfMUzJiwEy0KBeB9gEeSdrJ4dFK92xSJFOi6XCwozltMG6YReLVLZjY1stNFrAsAdP30dMoahSCK938DYCFTlhoCg8d4nn8Ngk0Nw1VMcGQ4CV9n9jQQbAVS8jJI5YNicRMSzK6YuGBH56Gi7RXoRY70sqJcdda9gIWDpFi3NKMUcHC674ThrQEpW07tFp7eOWnc1ordmaZp1DgQC5mWshcRfY/+aDFIMJ63LohFakvYKYdr3PrIMGrzM5qPXDmZBVb8BG7sOCIF4AZEqqzwahYnRawWKtlD1hWL8Tylt0LDOtn04ylK4ki6MM3m/2J4BDbo9/+qyQj4vg0cVALvLUZo1SLpgXYHe13GjZybpw/mZWMvE6DjrnvLl2i+OJQmCFYTd+JVJJInuOHW5qpf8A4PdHzuO9NfVeyaZ7wtoZSsvhqDXbrDNjhUAIpIxetBH1gUgZdIizH1NkZqA0wU1rhABbU9pi4OQHdv/HTwm3//5Tx+5LX94WiS161YDjWcQxRoplj6VCEMX0338NOOLBP+hWHudxRyXaB46V8yJr7ikC/LL/ATLyOFtDdCmk2WqEgiL1enWLFvMygey3ggCTZ9s8uAR/frj/Y+8VIrtCl8tsUtC/6BUu0lP/THDbBpzoWHIHfK49d0hNmWco5K0cqFryezWFjUEe7VCn+JA588fEfnWX7mNtR3HZUdvPR8n0rUmP8W6c2W9r0Ex+CBAOLwYa8bIHpK7MZf7s3Ut6mAHIEqRgObsg8Udn+2c+s4yqIy1AuTMg0jtxBARMN5Ntl+i20Qp+5V/UNDViVfksZuHfpo3l/eJCFQsQxKPtoXB+CadGu12Gn+UOf0PEaDuu6UO1h+WdVEDkowgifFANboDwLIs8ZzeWuAidzplUqwQTgBkdcCdfmA4SvY+3tWbgMwZ1jMzdriuw/Qjfj0InjGH4708yqh4BLw9m4vus2byPHkptmZBLJZmXSwjpetXUbsjRuU3xJGtK7KcGJ3Ie9f5dd1NfyBZ4/XHj+/d9dQnKr7S4/T6JUAj2r5b8En/8k0x05f7+V4i9C/fgOc/Kda0NdCqZUHqBJAGj9Qv34y3KB3vn7/qOnj1PGWaYnhwk8MiTfX+De2z4PL+d031DoSO3k2E3pdMAyOBnF3zGOv0fXGUklxfcSHBJtd0+JYh/dbhz/c25vNI572UA6d9HJnGjMh4G/kNwOW18p/WIAQsv7wGCWH/7SOWt69SindAzGguH4DlndZM1336KfZDIgXqlP7La2zbGjxe3hLq+8949rc3aP/+Xss1pE55doD2uyTdtz2S1Kla3n/C/e9fwIvuB5j+QJjRiWNu7wmWwp3xfFnQTyvuthPuTicQEU4CSG9A91Jdqs+lZdGa90TgDjzrDd9CsDBeAwAm2zXpaNKxt6Y6yFqx7w102bHbv1aryjzBJpSC8suf4HTTmJjpR9VWsSyr0gJpoML49vEL7p6t2E4/43Q6abCD1WwnZlzWB9VRm76mrD+r/aR27K3i279/QBdBxXDqBqkR/Rsn/Y7RXcVFHG2zy9OKUz7SGiYeFtmWDqtVBDfPBz0dbDLkOl8DMUTRRkEuU+NyVT/wmeDxGJ9itFbPJO83QbpXx8Eb9GekmPTYJx1u+xjfbx+zI+d3jsgCNzg3MOZw6NXm9gZLjd/lqi2S5KSpzfa+o+3nn/H4SyPQrwZNYvnGBe6lNwF3kbRj8uT5/yUmSeCClMSt0zL0jSAZcKcm2fnscXqrD0lOsTZ8mttrB9+49h963OhT/PTY9d/ZfJO+DohrRSKeE8CIGitOaM0InqhZ1APe993k5o7z5axp3s3Y3nrTuumuRGZGkTIi0KVBpNg7VRlVlkVTdBKNumqwdFq9q/Gqd7AICobxi8WjqwyYitXHbh2a8kz7QvD0rGUwNl9fTniaADDhn9RAermccam79U1TuTtozgPs3qrZKx/SJ2aRSf6Pj3mmdUkcSZc/TQ1cesmIhhs1o2BCht9N03rw+nCUfyUysCORKyRH2rkudQgwiNTxXboqZU1QZTqFyF/ucuR0Gj8r9EmkdTbDMApnfnnc9BcXsphGrWmKlI+I7wzSyDMTsqg1tC5YF/V0lq4xL63W8HAmLliJIq3rum2o57O+0zwH123B0lyI1fcVTsDEFHlqhGJUCtY+jCakkeseqY7WLVVZH+Nt4xoe+gKdE2ekILRaLTKKUaumakdx46Dv95FCtpQFRFrXcyhsBh0ZrPVpq7UsBVJtz4bgeP2IJ+ldE5PW/VxReNCL/GwdHluzNpeRV9wVq5QEavZxHAYKCJLiBQiNvY+1WFSbrS12RV1PkRH+OtKUn/7eh2/fcDqd0NtQvvbmKfqT4Szgdx4G25HH8KunAq04AuFfAbnUfORfRYawo+0oIBa4cWlqL9EwIhCuFGmuRHQPXckaObLoD0rdIsS8DLo0xuPHYzDoY6YhDkikJYHJL4+60W64ziB9vNKNuUMRlH1PvBPmmpTTx6X2jrekOc5rL9pw+3cGLAVxSttI5lDFqYInKV3Ztk0FsnXFsq267tw5wt4HGsZ6OA/NWM3wFJeCQiWU6Up3uxlPGcyjHIYrRroIpHXjUTIcUI6z5mPuikTPxiESbXBidXv2tb9doLWUlwVL0+jYqFlsz81Gay4F3Wil10TXBWJR1TwqxUcEKcZ697/HOI35GvrgNIY2Tx69PdaajqkK7ASgxjj14MFazsKVoz7+w7HFDbaH8Z3wirVpogZ5RLPSxJwh2JTWFuE8GR2szUQjgsYVEWJlfBTf96kvYjXPNXW7pbSMqD7HFvq4cuiO4xqn/U0E5BZTk52JrbZ4w1TzmGsDmFFbHViEFGt6n51Y5rnxsSMwiIYT55jihJVhNJ3cKOIZfwbNDeWurxd2YmKGXRopBsGEQoQOQhGtAeiG9uGE4evVnGzY6RMBUAMkBOHI17ugni+ACEpfIqsAk5YgKaUAjVClqiNCbaZcaqh7xX6u2PeL4iZzLiVzVCVmCHHsCZ3nap8Ne93NMXVH683GXu8rKW2g05KsxCSM8fMxjXXWKxokHAr9GUxzqnsiRNYEKSpjkEuenkXL9paWAzC6QMqPi0W8uHHGw9CdL0AI+2XH5XJGvexBE/Z9B4iwbgt6ZzC741aQCR07AXrd0SxDQ4fRBXSw9bX1Clj6eRU3jBbbQtfxaOG4rAaInH2i4aqmsohiI2Cs22H5m+j2k7Dc33koEq7AvgCbcsYptT8fZIlJZ+DtlNA3uaEm4wevVT8/ZWQhCHKQ9vfjfX9Ewkunny4D/okjQ5YnvSTjkusbnF5lwBS8H0pXa2ugUsBu5GKEtoZFwBZ1XmJUUxMdJiVNLcV1M58fDhII7C5cEsaDYXVBLwLqpM5kgDmPOH8xHtmM7ji0OozCWCLJYBHX2VpIzkFKy93Bqkd0/MjgISOSmL4fUZXX4+Qs6nlvj/yQ3Bl+jFnGl9fPf/oKzDg5zwiBpn3g6yQbj6NtN/bcvBPMCcjnQyRhHsezAiFPq+2zOJys5n01xhvI65jiSzbsKw5oMftibcxzFFHtaehcrhhjnfHC4D8hg0xjOdo7YV9r02T8Tr9NMoGMMfcI9Nw2PrTX3+0vz2vllkwVWI/UILeu6xQh7g6Vyi977C9/vsvC+g7HOqoTKcsSegbHxvA1LuP9ZFECg3SPMd8vap5rSZb3bILTwgWZWoDG/cTQQB8fQ/1d8YTEPvXcRw2qH3L8JF7Aeywj2JPUMbz3GJcZahu/6Vq6r/ce5TYfO77Ha4/k4LGdfYNs3LwG6br4nnhs//Lt5ruUV48MJb1/A/PzcZ8MOkWAGghfv8T+8bM6E8mg+/3TV9Cr5zGo8vnodEAQ/ATC16u+PzYef4TnSvrnz8yR6udH6kn7cTSen+m2Qd3roZ9kHnsCwrf2Kv4q/d0tZXvDoE+9fQSX1/HA+utHbL/8rNcdUrxL+my/fQpdOr95aTIEa9AYDTpL0AxHZVkAgpZj+uU1iIDn//IW3379fabFNoALCM3zlqd+AoN3iGWHWBkQVjnnXBg/EaEWwmKO1M+gxvwXVIBlwfOyYCeguKKYOjoIFyY0AAWmk7YMuHtt2KWhSwN3AXUAXdQofbngUitq3bG3ii5amrPUjk+tKaZGx8V07ouTrGSH0D7pjLDp0UuxbKTrioULgAJ8/IJt29DOC+5e3+Hu7oTT6WQGdA0yxLaZrKHOur0J6q4p46Ub/TB+2UksgxrwwAC66S6COB1ke3qctkw6jGm13L4urpIxs0QuoTmNz9cZ3xaa14uvmfwcXy9XuOk2mnZn92M7HR89GrPxz3D83XLX9yUQuQZ1+icSvvwD+PG/2/HXGdAd2zlASoIpAIuAdnBDNwZ5GBYlkW7DL/APEYFf4YLYMe3Dw5TkWeJ8biqBcAfSVO8uuAAWa3grtpKmD++Lpl0MdJSiz8d7/+xyyvd5hPiEymDjITFSiBR0+UFyvSkclJUsZKbfax/eU4YdNb2OK5dF55S4gMqCtSxW30jUm7B31FZxuezYazWljkZKtN7RW4WQKj+79KgjXvcKAtu7EJFMiymTuWtfe1dQ7LUGmaxuOmkKbU/5zZ3Q+m51q0Vdp4hATa+XomOoQrAaJgUJcLhC3/414yoX8zSrraKKOQSE0GzzIT5biog9mlGf5ZM81AG3UvGUYDDGsILXSQCLgQpt5fqEAQhoZxypSwWFwtAEBoYZfn2NJ0WBFEtJqm33Wrp+uJLQjTpintSRsjWQn+8Huw8A04blWRKUkoJ8WVcbKjPsmiGGTgTsZDTARi4rsp0WiIEUE4a27QQCQjG+rApCBN7W4UE10mhbCi4Ae6s2tXr9sq4QCPb9Alg9VwWongGCwYuule7zxQzGqFcuBM3wsO8BeLQOpQlnFp25LoumLWpqtCdQeIL54YqUbdvU2BD7ViJ6zNdDTwKP9GaGIX3Gtm1ou9YAWhfzzu81U5zb0bzfOQoXlNM1azpfzoc+/PhZSYcAQBXuvXVs6xZj0EwA1+t0DYZTlu2bUTZbLBJFH9x2S+lo6zhS/ds7BQCaa6VVieEG4jCEmbFjOW1o+4562VHWJer66vwVrIvXM9LUd7A5cKVt9BmU+hwnEzidedvh1JOOW7Dpug6imOPNWE+expiLZahoyhNr20EA1nWLaD59gioqq0U8botHrlt5AwFoMTHb9yMMyTu6NQkylF7R4DwOB+NW0CH7X2QysWczdF2vGOm2zLnFFSU65mWsQYz1ZVQ+0WJ/52Gf+nNu7N945rH98dsQVAeEoul3NiESqdQAgcBlsfRgli3BIoW3ZcW6bTitG5ayIEce+1p2Z0Ox4WdQKCpDQQRVTi3LCiKyUiwSY8yGH4oZwcKU76U57H1+z4TprB/uxKd9svVEHm81F/a42hk2RlqKpqind21oi+ERElAf0aOZp2QDeo5qzAcb7hovpTT9cyYA74MrBt1RC6TG/YgfA3IsAAAgAElEQVRgLWUy5nsbxnfFcO48lTNzaIpYwCpbT0b0McHAqK2Y+PNV9/JcjLH0/gxFpvPO5CQR86q1JsNA7vJBk6h36XxeBJYi3LB+60E3Rot64FDxbEvT/JNF8hOoC6p41JDEGlYyIkn4tjmGp1MXc6yiwDUQG29bS7KMTA8QgCoCLzlPzXgyhEzfN4mmZerlKY4H73Ejsip7pRm/8b5QQTFHEE1D6kZzTrTLqYvS8EKsae0hoAWACIpauCBdM0upXkkgpQBCWFYx2rGAUNG61gDse8PeFA+31lAvWtqpmWMpelejFUNxOCNSOvfW0Cx7S7N0iHU3ucHSLcoynIHEU5ma84pPiJNUhmdgcoV3Q+uEympgLkwg0ZqkjlN1Vtg+RxkH6kM1qiUmBCLN1qzKLW5Q93Wn6dt5imgDsUWl+T9b39IH8jceF/RFfG/q4nJDOASR5cCdT3rv4FbRmLD3iqUtlupd12y3qBmpgm52i26OD14/FpWUD1LDyLTg+81LDfi6pYF1TJwJhxO/w3n2nzoeudFhfjrVUIFLQVmL4uOEn4ZBREFf9zH28gv+SKepZtDQ2ww7pndxcacEvaheatDOzAtl4v00fSjZdYPpLex1C439g48AHkaIjE5NiUhSN8T2g8pPNh6cnNQBFB403aNEuXdIOJR0CBdI8KADTAsk5FvDXTP1ytTUkAaReZE9SW1jDJKO1gUkXSPhZMjRBEBKt70iWLhMUcU5B9U0bKnB2lqTC9DUukHBnJHrJ4eDLiWsJ4JuNG62dh7mQJSOkpA59gNUdKGSmMN4zNIY11t4OONO+DjfEMSOOqXjFfOKtXlLzxkkzWrIJof/PLJh43AHcRHTfbgRVftWioznpnVAnFqSPnx8XUchqUODhwx61bqkR0hEGoPIrH1z/z0COkoUpIbxIEbXY+frOtozDOMZ/5Njxj7wQ9oJ6T9/jbaxNnWS12xAnn7X8ZEHAWCWWZz2AfGGxxa/4z/pXdegOSCftpMGS/BwlGu1HYzBg3f42Ih0qMVqOOX2Nr5H32xlawS6r3LDlUGOBV4d27dV0Dlb5wQP/tcLXDfdw9Ed0NTvADFppp5EYwispYKWRbd4b7b/CcOhxY1R7mjYsSxF80HavMRyMKc4p4i1NbhazBH8oJYy5u07R5667+3hfN6vyzrJfHjgWKtau37dNm37i58mI/rxfR2qD1vs7a22KJsj4JF5yu7d3rzC+cMnMBGevXuNsm0Qafjyv78A+Ba811cEv3ph6a8Z5edX2H//pLLUSwI+y2TovnWM8Z2v8/Pt8PtxfAjQmtnp3CU5fWRD+YWG1HpODbpVBz3kB39fup4FOPnefwMQXgIDldi4A/QBwBs1ojdLxd4BnH/9GNuC3wL9/TUCydJ1//AZ7W+vlVe+/wR++wr110+gN8C6vsH5395j+eVnEBEW0yGez+/RfycshLDfFNv/TQS7kZg3//oLPvzbbygp8EqMHjGAToTT25fon+5RwChE2LlgpYKFtFQRM2EhpXl3RFgLYRNdYznfVYXR3t5Dn6Flp3aUWoHesHuWraYO4HXfsew7Wt1xsbKtvXXc14baKs5dUEwmUOO8rgR3PihJpxJyiwU3OS1drKweTicsn7/ibln03Kql9k6bldb69A1CC+T3L9h/fhnz3U2PUqWhdiu1ZbikA5rVA0nHmEgV4NlaBh+J6GxTWiuPGTRYf5tpcD5yAMCMCRKeS7zRMVlWz+lvvq8kXu28w+/LurDcltBXJjktnqMPnWV1itPRrvz9eDxGT24f4ynffa4gR+CYjOU3HnBbPh0XjjnODoHTdY60yW2elF5ymHuMOVR7GULuLX9wBP67Hn9xBLpDuEAw0Enw3+2qWdOIuFjMJB6KAwQYjU+/Jn6f73n6MaDn9+50MqG9eoH1VUH/2G5e86Nn/Jccf/JFT7mN7H+uiGNmbNuKpRSc1g2rEfbWNXXjZd+x7xW1VS094h7ZsRmh6blNgdrNiL668hIGcj2dqVN6b4+DXmZLrQSNsmax9Cm+DkkjXgC4B3gnTT/bITOB98BepJBeUwpEOlFRw+letW9NLEVkTtkEBNHrVudTrNNusP/+8fiqDBAF96w9MCZg1MfETPwm2ZIoEdQhPOS1EMYYE6LivkS6x70IoSocLQZZVsDVOwpr2xlFo5NbR/3WwkMVAtBmYNqe2x+A8my8nwL+6NOPQr8CLqsB6Qpu76c5DxQeqcKE1dDAhYeSUgRkCs9qWRXEFMyD+VAYCHWYTShz4wgAeK3XMCZR1MURtEjD6f0lqMKGyQ2VFO9ZpIwx9nH1aOBA1Q6ZEfvVr162Nc2tC38FdW/Y7k7orYMXoO+awlAwnCTg8EKGA85TBLLLfrE2j3PbtuHu7oTL5ZLkwKfT8AGQYGnuLTuAKxtEIMxoMlKzDTBFw/CLFEHqo+RrJJRZChgJlmXD20BuDANgCuXeu647Lmh71Wg3UsecUnSvSlcP3TBMprWiqa0LZgPxAKtDqRKNmMc+fqYnDKc+d5CFQZcngO0nBwGIcRkAz9pXBCxqeCilDBrjqVFFANasIV5Dy53AdD7IaqFReo9MfEe7nSio0x+kfT4Px+gdpbNEkyIbhEjnKSBNiyaw1HxeT9jaYfVHkp5P12KhoAMZk+R64rpWgCualebOabF/9991qdH4cvzd5sWjEp0Wey2ttSxY1wVcFiylYPFo7FX5OOBRwGacEwJzT17KGNHDvcFTAAPqKHM6ncIzXcdErP+epcGMfFyCv3o5CTFByqPQ/ZwbuTqPWteZl4ZxuI+sLhO9x9jfbFjBU4uXpaA0z9IiY95oRIMvQETHtqaCsvOyISxKKNogjkvHGvR2hWHO0mq7gtGzUBCpgT+30Q+fz2bXtkogUzaOsR40QmtcqwL1mIJft5Ltf0js33k9ZmwQZ+fzGWPY/hGWwTtbU6PAVFHQaTYBnVDTa0UwIoYF8BTft5wWVKBPMgAQWLCwzS1z8KrWKmq1tUuhWo19qsZ6TVveW0dhNfgzEQp5ilIBk7o1NgIIbTjDEEVpHPK0swn9E5FqayXhrbF7QSx2H2YMRUgLWmmTI+TZicFxCIdDWCZ3Sq80cmOjBWVlderqQKNqqUV1EureQHQB16rK4XXVDEEgjSoJCVqjoR/OZ1wuiondKa+2jlZ3NZ61roHYrEqwjhZzGzTRoqH9n3QzpjOh7Izz+Wx7Xru0iADLErVtx7iOgwnorLScAQiTZdEqoN5AZQUBKDyvZ7jM2bulBtb3aiYiVZJrtq2K2lqUbyBCRLVTcbWnPRKEy/kBDw9n3f+FwY0VA4GwbJtVhnFDpAxatHgkn3ZesaLvE1+/yl97qxEdg2pt75qtR0fcjP7uB1j1PQptK3Ick9NgzXbgwDfxz6CZiD2Y6b7get/+I46OBuxA2ZxejiwcsFZ3m0tfQ3ZZ/D7JKn7/4SCbCy1xlPonY6bH+kvO9ePx80VJ6TeN7X/JMWi+19wM2EFOmbLMSPkWOLPLvLj3DrXlepa6HtkaPI07OuBZQjOfz9kMcgv9EMPhYmmZc+mAaJt9c9oY2BGs6V1drR2pncXkW4FmvhtR6ezpkmUYjI5sKPh6UGUKMNi5W58s8t10FyQxdAPeDuCQH45YE/TIugjaPw+aY9iJvj6i2Kb0LG3f7T17qwXzmqch8xpvy+9SOccjlL09eQ69Ce5waCcODttTtgf7HwEQFnNSkKl/sRYcF7HRLTOEazNGNhiFQzavROaMishEJinv7FBMI/jrmEMasnkah1sjmzMrZnxlfxitxc3fQ+6N8ZveCILhLZl1NUeDRrzLPyQ9J2GIvP8dnzsPUNxihuHu5WQAiDmpXzDxLN9U46umZGfpYFo0sMMwITAyxJkyBiJNM0tZFgmnQ/u+q6yRivwN/kyRIY6O48jHjnopRMfWYy2YxgEg0zGJaGkUW8NaHsJ4jjsyVneApbHG7RBbjF0ErWn2jiFdjP8PQ1KamgPp+CPH7RU5/31kXcGxvt6DXjxL/SFoDPB9oAVtno6lz4Z8EcjLPvRpaQ6cLtDhxa2LFqoQghZsnZclMOTsbhkjlp9fxdohDEP0sU9+yOFvf27H9fX+/Ztd5JHieV48Gv0YYX65NegYxnPCtSHdn32r3+Wt1h/vHwDC56l9vnY6SI3oABrcVXTIxx2AvJ/njNNKmN9Lmi02rkxtefdqplECrMsb0N8I518/RBYCArC8ew367aOWhLXr3/3PX/Dp/7z3hFu6rgSACDbjISBAFpVFNmb0RbN1PqMSzm4sAuoCtI6lLCjEaIZwISZBmQz5ILpmuFbU/WJlZxua6e7PVNBqx7Lv6hi87xY4p1m3Wu3mHFNxEcEqMHyByFCjhtkx3gyVxdayhNy/Wgr3ZVFH+mU5a532dce2vsLp7oTTdlI5YV3RZYf8/Ar7XgNPAUBtDQ+/flRaYjinA/jG5qxBYUK+eeglrCvlETzg8/ujbDk23BOvycEDM7U5GtkffTRGiqI/d9wagT//tH/88Ze1zeZoODbI9FPMI9FtTPFPdPylBvTDPgAwlB3O9vPYxp+urLC//UOJumCcMBADJ+ZuPNdLfgLhAaKR5chkXW6QCgch40kz1B18fX35CvVTQ8dn7J9egiD4Ypz4hfXzMWJ0ZNZPX1rz87rV6ivOVTDGCSJYmAMdTDTFFHCeVrP1Zt9nE66PY2taW64k3zoykMw0IvF4WYDeUezKbV1RSkHrTSOzax31z82j0vG4ewhyErqbRXFrJHoDd9b65ilto9AQBJg1tWIxb243gpKlRFvXxZS3DZ0WyL6PjR8eyGI1NBk9Kc8iPRcB5F6RlkrJ0897H2urxpwkFP++JEWS51dEUlufA2zaNKV178Yvggl7LmUDEFwgoko/ECwCzyLL4apbQGQN7yA1hA6GRQbos8LQBYS1mIHV7i1UrLyaGYxQjFACoLSvXChYOPqV1YfusMZm1Cx8B36mUKc+CJbnSwg1EZEHhGKHny8hfDe6gMkNwdUUxw6cta+FtD7lsqiRWJrOG7NdKx1dVamozWuxEJayoJPVeBbNpuAefa7oAYC9XcbckQpkl71iu1s0pW3X/ar1XQl7rRFZDrjfnYQg66JRRB+TvkuVvfbOWqNmFKX/ETRCHgItKmRGKvEUm0b/tL7wmJXM7LbTCQBNqYQevt0ryLTaOEFYCJNhBxg15DLpOd3d4fygNXrIMhz4Kj6dTtqny27ratz9PUDmB40BgIMuNZybp6p0oDc1KKDFWs97K5xzilE7QUSes2Wm8Db7vvZ9QYAaOHiOxO69qyHSUtaJqHd63EektNOeGfTCH2/PtYKrh376+I9RzgKNDUW858fMJtEDSRyQRmOc9mj7KL3HhFzjE9EkUsPX6aRKZgLpGvRnmVMILaPmOFPHpWq6vdpF+UrU1ItBuKnscUO/O1DksTjy8/lu4/yU9gOgNI1UAeRDH0bfyWhvdxhNIkub7koaaYN+xQ1i0awyxuvaiO5UfOyXoVQc4+HXXf/u71KHpBK4i7CWgtNpw2k7oawLlrJErd5iUem1VfSmURbCDA1XLEG7PF2xdDOk+zgyoywF27qqE5KsmBwbrb1RQ0ksc05ThXjvLeh4D/5rimedFhRYFJsG48Df7hjR9zBA8/gabtF7GIXF0riroa+VBb1rzTLf4no9RwYcgaC1ArLIFK+BqBg3qRyc5aY5ZSJQcQUeY1mKluWwWsuAprMUkau64U63hvJzPqj73rL5EK3P7CnRfY930b2YSLjSdK+jmqIAY3nHekSsORvdmb6kTotHHfauhlJmzeLia5ZSdC+AnbXufTPjuojWmNN2N7hC9NbhRk3KCljbu2UZafC5KwaoewHkohGSLowQ1LnR6F+XjkZWo9KsJgJ1WihESttJlTVSOxROUziHMluSo6hFpmOrc2j0L2N7s6Z4lKTyQuVL7rgzjBLOG8UwQRobgirribAUfc8oPZK4RAe4aImaAkLfNYK+YqQMlVaxX2DG9YZlXUDPXyj2aA28LObgoePXWlPD8Pmi5Zsc75uBOQxKuuh0yEFwJzGFo2ZYsdTisKjV1jpoV2dJvlziWV6LFKTRJsPwHVA09pbWQ1ccpbiI1bGEGbDIQi7mvMY69pqBwOUiMSffZs6ze7S1tYpWNUNP8TIuhisK0QhWFISsI5ZWMRyHRDBoJeHb16/oXbCd7nTenf9atItjQ4FAkl+KAJBW0ZqW6umGdVsXSLPINktH2cwxVJrSgIZqY5SM57auXDaQQ9QJkTvfmQwtDhrS/ry5c6+Px7j0jzHMaGtDAy4AL2wZoQZd6BYp3lFBNIzsHQ0ERlkRTFng/n5mFEg4s5rh3Od0aqco7iSiMAZL/v1HPXADsjzl+scO3+9PHHnXJxzeGTT+RjP9LWLfdYx0rEcpAIm15hHo+jsA7hBR2U9CkX3d51tD4M59HArggS29zc7JyPY6GZ0kmNwiMCdpMqeQ3DdtSCF1LJLpNxvdtCYyv9T36H3EWqJM/5EHn09ygDu5i9FBpxVCZAYDBAa1mwzzHaKGvdVtrFOXM/M1t+aTxo/jI1332Cq6fZ6g0bYJh9Jok863GRBc7ji0YxjPEkXgdE7EDGiSZsCfCc2oMr3e17avF50P6UrPWD3BsCvDggOkbd0AIJwVR9kP5732dtNHLWXIiSIYpQNh+iQkJ1rXn6SRFBF1LAGF0ThYGpGuo2CWCPnAF8hMpxDvcccM3x8eMOJtaL0d1hgmHjqe5fkcPMOetZ08243eEI44IKA4poPJxwqo6l5TJLrOS1EPNs08JOpwR6x8iwzbZIw34mgKEE6kKdvfAF8A3PnZ5SYGkWHS5uOa9GyGFcIhlgiwbDhjrBF4xksOaHmoYjyggJeiteAB0LJYqZse/mnufEwEzVAH4P7rfeiDyOQxx1LqCNcPe++pHPaann6PxeSQCUJ2qZtJNb34SeUq06MyM/BCIPIM9FVAuA/jcxjPfew+3wMvfjJ5h8O5LfSWICt3QVhevYisP44vNeRlwOy7n19GZlIiQvv4Bdub16o3phfo+HzV57FCxkje+jyTzsk6RB1c6NoQfrx3E9IIdDseM5zfDdikZevkdpvy7STDscsvYLwAvWHUD5/GdVC6YuFIIBAWUBh3yxugfhjvcdzWQFgwdAj++/ruNQBBf/856E55+zLk1MIl8Lzz47KqPuf5v74FQLjsNXQB2y8/g5hw/vUjfv/fvwIekARYmRVCefcS8uGTRsy//4yyqT6YTNaDOZ0vhVCsHJNnv5HWQUVLSaIK7qF7j7rRkT7sEA+t4twquO74Ylmi0AUENZJ/2y9YLxoYeJFqmW07etPsEntt2KoiTaMWmuESAF4S+qdPoFevsCyKf9iyVREICzP675/B/+MdtnVDKQvkX1bcnVbc3W149uwZtk1TuLffPqIsBXc/P9ea63tHk4rP/+c/0IxuNaLQQX6F4CHWg+J8kp74v9FpOzHkxnnBij8h5M+BK8Tw0y2jeub1+Z68pl0Gn9ctgt7m6HHYOs2bZHLmn947zh+vyXr43Me83vPn33/MOznLSNN+l3wVjtNw9bSrp9Pt3x+7ceqzDHvsMQJ9ahshOVsO3vnPfPy1BvTvsmT/mW5sSyThBcmYkCZPZFps/rdv2v+fu3dtjCS3sQUPQEZKKlVVu922d/b//7fZnfG4H/WUMoLEfgAOSIZS1d2+nttzN+xqSZnxYJAgcPB+yNKukouagPs0hCXTYDIKvhyQoOLdC8XjwOcXr0WB/t97kMx/ZTvPu+E3nLaIxzBYDl1+rEGPkpoi3nNRpGDbKqqOcqPPT1/xbJOB5jRUN5IDsDBwgAZXN/C048ARzrkiilqOqRzjSUHQABHsvamaz/Pe1m5d0u5CNUWajmAAloFkltscqUwDV4cLydZaRqYdu/dn7FEeJd8jFLFUpmBZ1ouGsGWJfuNarccOyCgpZlM2NsGSWYNIzWdNs/bNO6dwokY67aflHnoCczIZ2oGoCr+h4fC5tQKDA44LNpT7gvbVo/tEADxHxv+938+eAH1wTUknBc3MgP0S78XvkIDrclkdu5S+qhUmh4P1WqDVDZxuDC/eJyuyxJcIOATtB1PqGGXJRuS/4HJ3QdlqKHp+bmvejoCHZ7Mhoi3DCBLZ7q4MDxoc69jdIA/B48Mb7Mc+rfQYpxuJgy8273qkJQzyclKBXgg5Gf+lAVWA+zdvJiL1dfr6+TNuES1LNfmlkve4e7jH8/Mz7vSyPOn6dAUAvH33Fp8/slfVxLexCu0xdMkzBR6NOmwkwyGcwAgDFRoyETpB3NjvidLyShmvAT4kc+ZkGESYfUaBNDu8zAzHvo91nYwofMe5Wqrfp0/rFiOff+cy2TTXnJ8lA+Lbx0twNF9oOR9Ozrdp5uUxZv7MH5Zz4u/ee+6t+bbWzTMyBQD7XYvvB9LoxKohNhmU7Py805CN45xGTDAY/ILfqYwgCf/bb9Ax1nu92+mRSSNr9scy1+e54f9kvcfiQH/le5dBHhmN3t2JAoDO4G3bcLm/Q60VpVaPglaW3QakK9wg9fJ9fCnEyzRO76zszayaspVYb3m/RPUMHJkqu/SOum0eONH8XShbU/KbGz3T6WQAyxebAaglM90xzeF5foCCUjtK81JprXmwSz8iyG00eI93DmN4Xcc/45vMRp/kIHkADRXsR120+LtGBjzAaiA9qqKM3tVnOjrvqc6anBZOixybf9+Ols7AbCGTGFyyVJsPfdq1y+aa5NL0fqRjykgJrND7WrqTay0xZmItFUXTIxzVMu0lTEa0EwGeFb/uTmyLdNrEf+pru21blL53g6ln97SUERqGuyzjF4FLXaLcXineOw+cuggCIe+9gd9m3YJbfd0Ouiqe8eVs5OUeB8ZzUgPqa1ABeZ9iLZ2fcwREkEFHj5ortVYvSYpoKRP70DoNQh1NrmjdsLUNdbvg7u4S8+uGGcfBHih7vV5xfXrGvnu7JAa62tFyFJS/vuc7zBoQ/UtZjcHXlNLd6SozvAG0fQdUcacFuPO92dXL0dOq3mHQCO6R01wgPpPtAu3dA4TMIHpxcuf+ifn1qhNu8G/WPdAmnOAsOZ+VPpzyoBotp1S9ZDWcJ7O9EwAvRQrxAIOZZl4YNgbv6+ZmOYV69k/uB4KH4IvkqRHj03pH20frh2ZR7ciYHYfEn2Ol/JnNpn2VgTBTQWvCjcXA8ntc5//ao6MBh9NT7x12ALKd90ODIAIw4NL8dk0wd6IggpRdFxrzIzH/J+gyXT19tih8p7Mtvkx++hqa+BcfK6RcP5hkpggWuswRDjJJcWAOO6AaVdkykHS0LwC8ShzlAm00L975G5MwoNdIfDjj9ZGhLss448WSXyRm5H0AoKlb0zovXO6Uy2UGDLEZUlUN1p0fp8aQ+3sEsy/vc0vcCatdTYBUACk68dXz0ZNOEfL95s3XB+Xz/tcOgon4feIpwBSsS75sy5XrbSDL/nIcHl8G/iPRUBZqXJf0mXxtes8eC6buSOfwVAAUYpbJ6R0yiRg3W9AE8bOqCWmRI4i3zP2zBD8uulzMPX8Vxwfcg+7wx9LO5YynieX8o4VQB9+iXtPHpYRcNl0gSHX5xbFkC/LX2BqleMW1ercFvU3vJgMrSziMmFDCudFS/ZriOLX1DuyeHOE6rU180iJYHq4jdoss9O76fQspqbws7ARA6HLrOvn6h1WFgXyQpLfEWskHSFt+p+No0DKCg93WFfctOq4Xr1AmUaEra7OL5mKkLLVZgv5z8vSWPPpnjxeigp9R54nx+xyLmzAeAfs8rpPppwLQt2/yU1Zs9PuSR8a6vHsTpfotAjGGVY3j2r576/vFvkDwCC0F9v4x5M4nkCLP83Ie1xk3vzZnV7ndt/z8DIM70X/r7BfzuTmAFwm287hn0SVA9juX7xX9p7nguj+Z9dVGGMyw0rSf1vPm93AIaVmiuXz/LveA/vkd7KePMPsQa/cemXhmU2WKlNFDBs8tKCWSEy4/fIfnHz+MdYjLfR0M9c/v0T58RppB1IOFixagFDyWgq0UXIpmm63eOz5ZwwWIB0eCTbSTEiY19bU4/5MhK+N6toBEK6iOJ+uo3dtR9LBhtGaRfNCizZPPQx+vAfnE95LY9t6iQou3SS1lQ/3zPbbqznMmNVwuF6/0u1Vv56mKowjQhnzqNpL7GsRxRvDdlZcMuUi7xnAmc6XGnmbQ/0v69c+Y3EXcN+yY5LtnnHMOnJPpc1nOSziR9zw75idZ9+r2mujsxfVjDKcZ+j/2uMWnXztuYu4XZ5zkPr+ZaAZywtb/Bx9/cAn38VsqmcS5sp4xjKmzoIooPiiajRJpzAT0D6boCIzoZQ3Q/IgBVrkxdDY2BVO4yzEMR8d97ETCKwDo+IT+4XFsdHyGwPA28FyDT7oLn99+/Drxju9F0nbxEgRMRiMYwrE9TkpCF5nmeWSkd/NSlVyH5PaBjAsi69fMM8Mjwli1oJaC+3rBpVQHL73jKu7kcMMTM7I9+s0Zt6uV0NHz1gyR3X1ARVF27xfoDnTNDDkJ5ULNy5IIlaoeGSmtAYUg1o1XTRWILFMxKkOeaaJl81LBZ8UE4/2tNc9ePpqXa4zejPtxoLc++hCCQoQGMwomOqB6GnlDtQrmw2dbPpYCbPyNKP0yCRhPNc7Nld+yvxyQWWdO32FNmw3jM62lFX28PiAjmyg+I7AdekQ4e4ODLs4T6VMvG8/g2uzi462uCKEITCskov1rra6UXI/M6Mk+vKF0H9oz6ndkinhpTpbU9qzBeJXIDmNZ1xrGde8zWwEI+rG7czueoVHZAOH48jLsBPgWS+TP7QbsuytRrTFtwWkzqxLEHLnzfOx+lvLlGnh2vORe75HRYNX3SCr0NHaa31e1xvK6capRYV1Qd/7nBvMhbQRNMjIbFoYop/L7xzcAgKcvX2dCGfsd/psAACAASURBVO8zCGpRiI7jwHbZsO87tm2Ukd+vO96+fwcA+PzpUyq6c5m3BdxML8T9Q6WT7SOAKM9vbsTje8uLewxFHOypS3nAmuIigJaUDEJgx+JWPM+czkT8XYEAyLyWiiaBIo2GEVFRAsjTMJmZujizJ/K3QTPrKsqNtV0Pd8IM3DluMWQsVCF9Bbu/5cg1a16mPbMAvX7VeIZ4cFNvETG+ZAuGfE8AD9BprlJWHjWB69l4tPBWnKZkkqPTpIyvC3IPek9neXFamZybaYWa0D6zh0eP+OiGFQ46L8mL9KkMZxl5vd9PwTUm35Zpm0r+pGImQDpVu3mvOc+gV4iUyLzeFgf6oKth0HLsNGSF0MhDuRjyag4myjnJtaDx0O/Zo39jutQoH0Es5xm+nhPje8ja7Mzn/hBkeezJSWtdYDoc0nSkY7oaYlB0j/YuFVbdueolptvYAhPupKOVY7Ze0hkgIlG1Z/STdBYxMn04Fmadlxpl82tdnOQWRgfDCOhb1EUReGhU2PbD6e50ZVD131vrgRl7VE7v4SJSDGwSMxJjxYQbR39HJF5goOEIOhp0x/Lz8zh57vRhPCPuHUEbRYpngQoZku8lyk2xc0w6VweJR7y/7uinbdXlSxF1PNE79qgAYBFY0swxI7Mr/H5ROtwMIh1WCrR1oBZc7u/cKJcGdo0euWFkifnw6i+AtDZ0oElxH4b0wYSGMzJoRXRllQrPdufasf91yCLuHe7bNA337vTiEAda/F69wds3SAHUDblFFbsAkI5+jN55BndEbnXDXjf0x6jG0w7sz1dvZfR8xfV5x75fcd2v8Iy8LTWpyDeHoaF3L5W476d9bc4jRcR7dafB3NCPI51h3jNTgVpQikJqgdWKbCWRFRWGPGBwC6syJG2quhzXQavHvic9Z5Z5OMt7M7Tdq1YMR3Xg+pn3RWUaFUWTwaNoJGYFLoig3l3w5bP3DC1aIF1w2S5o3fD09NUN7SJ4eHgTpeMHb/IBz783mEa1hbbHVvEAhONoI8svDIGuq/SRiSnDqWXWsgd0tjWPdfJls0G7IQ8oBqnhrAcJ+oXk9eed8eNvPM76sMEz0fvVDaIdAI7QK46Bu3vQpE68bn72CIZy/ZWVvmYMZgDKtgEGHFFBhzKQGc/Dw0q61Jfv+BKkT7rY752ReVZuH8sqUA5IOIxk7IXh/EPiUgJHZqmA1ULEg56K2vIK5MtOox60kc7d4O9G5Xl+2/OCnN6Lz2d7JsT4WW2CZbYtqsd4FtkwbAfaGQHcQbsMDTlwwLq34ZAZi8fz2eqiGEvPugwWRKURAmwRuCnL0haWrxj7Le2TUzoldQTHA+zjHnYUWFY8wnH4BY33dL0nHS8pY75NFefA3n/umLGiE9OaDca/50BnHhNujlvJ/D4YuBRqQz/j1Slf/f7UI9NyGE5YU9fTzDR0NovqR3QIhJ4R7TeU8wzaBfpij+xxD8p1c+UtgtzivbKyzMyvRnCXANnSgDIPkclN57mqDow5XbfoAZjWcMKx+a1wfnh40JmYTUHCNndJfIFdlpUWvsm36efYOyAFzFqstUDgLUr4XsTw7kxXr9oQLRMLcbz42lHnIK/S4hhSRUOfEk+GSHpgwHWsg2oE9cTcRjDVaPcnyX5Tn+09neGkFbOp9ZKWMVfdIijYkjY19BIpBYYODWfYcX2GAbg+PYftImRY746DKDd+5UisuXz2+lEDJ+6ns+T0c4Tcrp8xXYJJGq05TvFKpQXWD7TANfM9a9BLff+YtGm5h+JnRj4A9W5Dbf5ZO3bs1yta+/RizO2XT2BNsIZPsPeP072BHv3PZ7bIN5/f8Tx3/Pwu2hnSwczy6nbjGmCkq8yaEZ3u81ySzjo885wOnBLXKp9DXcCwBA8U8H5vw3n+4TQmmyoADB8FQzzOoRnneWiCTC4QAMdPHwEYLn/5LmVm/wkoP8SYiLljH0DYPsvxZy0lArp9P9fApL35vrLgKVPouP+t3nKKNrIKT8Qr4pX13mjBpXhVPamKZ3U7UQdw6YZnAaQIDogHTinlrvPFHu+JCdtyfmhHbL1lG7enduDSPBD1YwT87K1hawfQDIcBW1DCoRJ8ZvhdQqB7O6xScKkb7u7voeb80efKq9Vd7i6BQQTNPqL/qJBmwHeGT//+X/jy9ISn52ccR8MReKYL6W9qBYVRgUCE+fGkKwOB0GyLGk70mA+jTGCVOPJIC9lIXn5bFswfpf56PjfGQr43nr1mt6dchi0d6G49d/GD0QY7fw457YRvH78NJf3z93sZ+P3bDjv/kgsspxNePtOwzvVZogyYPof4cuP8/+P4gzPQz8cUTW3AiOQ+L56lwIS5cmsYzCtZveWN+O0C9gCBTgYUTJsmzxhWwvz7W8oFs4emkS7HVwHe2HrOf9eRrw98cwcnLzwdy0ecHxkOAmPvU/PeNO7M4z0tQR3ghoItMny2Ur1PdBiJjmOPzIy2gGMvpePl01+Awh4lUOBlGukAowlcRL3fYRljujUFeV+jshyZ6WUYGVUVm7oDldX8ZkWPAsCrt0TmR/NSMC36ObpRoOd7+bSQUsmA2Gew4wXl/CrPeW2hJ8Yl4zMjmglwcuZpXWSU+6FBZxKU57vb/MGNzTE7IQmc+Tn3VAHCSLnBAGwPXsqajqUWCol2gSmy7KEA2atWlEEhAqji+HSEkTkEZ/bukzBw96xYoBLRwUAapbdwmrNiQtGSHMX1nQARKshy9WK4XC44WoNX7uXemZZCXEdvEzJnWwGDeXm9jP5255SKO51Gz8wSLRqcfo7eIM0NztYapLBHn0yO3+Ho9uoQ/vFwzEhk806LeVaEz4f1dOymEREyUTdw/+ZhpYdY6zzSwGHYLhuO6w7YKI233V8yC/36/IzL3R0e377F9enZ57MJju5l6QluXkQzpqMGOWfbtuG4Ru9x6xnww6HPoBnizoFShhNQ2aMPVHo1jC8z2JpxSWTKsnQnAV4sBKOI05kqUfEgjYpe/tdpAO4UCN4nQAL9+dUXQ8m8Br/B+DU7LeODk+aYDD/lzW3ZeFa11qPUkspOPm3OcI29purZdPkOKlPriWEIFNK98MmxTwjzzu9OfoTb4z/zuYVnRn9MXW7JNV2D+da7vfxsnqUc+4JH4tk2PlgUl+VdnDnOvBan703CEcVAkjp6QRcGA1g4f46WtIk0IHrQB+wbqxtWCRMbmfXigWrWOxoNKaoAs2IRWamdShzyuqiKjcLSu2Yw06D7EZYowffzeb2hqwfU9Xm0MrLq+cwxdpcjqp6F3ntBrQXWKvolnJPMKJVQ2mJ2Vb3Fx4wVPNtWh1FV1v3KQAov266T7FmzzAtK3jeVbBCLWP7OdWd/x+S5Clj3zJYyOftFxXt6w/eWtXk3SK45Jv5KTk+jYBpodWDFUarT8h0keJuIt6koqlmSnkZfV3bp+GdGSYyEGhoVfhqTb1CihD4gIJyJHvUi2GX3dgRasDW2pBnnARhVjUjL5O+RMdmDjiAZ8jmMo1CY9MTEqdMIIkgSyb9vZtJzQDQ2TA7cEQzD/W6w5gGsHsjavBy3dXTxTArHPRPuJL3E8yXejUGlfNfEr71724be3dkTmRdsy3IYcK1XPF+e8fz8BFhHPzqenp/w/PSM6757GfNwNAsQ2D/mbIqiZlaHs6ED+9FJFZm17b0ERzskwHWT1g2GA9IFYoa7ixvYtQq2rWB/9qBSM0OfeWSsk+V4JEp9cp8O+jJE4Ilo0GbMD3WjG/+lQZmYk2140pHRkbqsqKKWCtSC2osHvpRRQSsGvdo7bAqYmA4vpW/Yn/bYE8wv4t6Z6WGsJwMx/BoGrEnSrZlXS8rs4ThfEcGeCSNvZ3T8TzmWkR324vOZs3CeAQx5SkNe7FWSymrsw7JXMeGdvL/xJFuFwysQKj8yrJjpv+sIgTwCo+Jj6l0yy7bXEBVAnZt7jME+I/vcUBS5r8XGHlqw5q3X/cZj09Efg2fwXo/3Ihu5OYvnDxNvBtYbyoV/KtN4p3Fx3EZvuiD5+6vLNxHizLPXU+xET3FvyIv3Tph9vk/i1vXzGVuup7/8bEa136ZIGeOZ7vUam5iQMCZrYZAk+aDmlNK5OQx/TIoI9pV4ImT3RMts2wfTkYneEZilR/sBnq9jVJxXtdDhNQfubQglEzf4/FySaflv2iGnOVg0B0M4tYdeOWZlvYfMa/+qTnheNeH/3UZz0jFs4oWvbJHxvQx7A2lqlgt0TOdmFHEcXDGqP9mEBUNv9KSYHg4gBqcauvTQk+MdLDAQKz3CAEQChAVVZUNlLLIrtmlWMGSyu5aBUUGMn1hXhl2QhQSPBime6NPRIabeioZEMKYLqQFJz+89kKMnryI+PG+cW9vo1yTwvF7nc78lWc7frTvu9skOIXryLAGgbx+AT19RHgWQB7SPX5M/ztzKWzN0pL3JDNb62EOiMGsQfYRhLVEu7wT2ccK9Hz5D3z0GjbxBw+ebfOu1+fh1Pvf7zrtVul2ACGD2m9AZzu8UwwFPdqenc8bu/gTB++XeDOHlPQ6Z1m568eWdZcCOmXPcesf+k2Wl2v7jcKL7RSMY6aVtvc8gA9yXRUdp+fMhsc/r9++gH75CICgmqWPWotiKt004topLLalnJ22mTokTFIvPiLslgvHMZ9zZT0NvEazNdqBHQ0PHJVoiPfeOzyZ4sB61Z7zOUceocMH5BWIxwm6gkSDoDnUP/jp+/AX3//ffUEqFfvoEuT/Qfy44pGF7d6AdD3huHzNR0SYdQohFjPh9LHLq9IG/btFu2ppUw8QwBRYJgwS5tuRfsvw99Mwz6hjzPQJn5rWeg7ZeYodX9Y4XwOf28dr1s63yN94qjn+GK//K8fsG8D/isADx8ps44v/M4w93oPu6BzCZCODFVg0CmXSIBA7Mph7EPO3+KIFl81Vx6y8KvDHBl8lgI3kef7P8/EleYx7j8PzbTxij8d4gX0KivY1A4/6N+83AeC7pYbi9R86AxwJLOVO2RfFhxPQU/zruYYjs3VlISn4vwWUZid26Z2bN3ycDdKsK6AwWLSjFy5Bq8WgvjRLs+354OZHWkZHANADKYFMZCSRwx3wH2nPDvjc83N2hyIFdr9FTZYcAqIzkDM/S4rQCkujcCGZR4t0NuoxuLqWisCSWMEI9wHYffVDdcNbyX4v+jJ3ZOTPxcu5phIVFD7UTYMAQYLyOK5Ml54JQDMh+r4D3hp0jEsNVvlDOAD0BBmzQAUeZFJDGDsS+isxfzl9/uZe9r+7kRKKRWag4+8keiXrB9mbL8mc0pFo8vmpFufcyovvHqwONiA5WVeDJUN9VlKIjU+Ston+K+dU+lWF3xwSdH7Uqjv1IzZqRxSybW1Sh4gZb9O59ukUBHG44i2kppYS+7DQPCcMwImoyFiR7X0GihzLQmuHp+dkVMvEgDjMGH7oTRwTYasXl/gL29DEDejsgx4491uS676jWUdWzehkByGVQHQUDYezxiokH+n47Z2UOIBuR4CKgJ/E4rqiXy3gG8kZ4echM4rAMaJ8A0+SRPK47VAXb3WW6CNjuNpgBB3ZotHlYH0PqlWX4ZuYVLFRRt5pKedFw5ApwNJYxJXIO415zZ7mKRGULgUfMy/LYSQ1G6w2Xu4srzqH4Wd537MJuLRVFiUjUg1HrcVoNujWDt3Qzd3yRR3LKWfZ3PIdKwOTEE52WdwDnBTDOUxryYcm4HyI1S8Wf539dlmlmhPVY/B8j791ZM2fWT4rDVJ7wGtn77H3Gfa9Jp1P5NgJ5GX9PK5Z8ZoYes3y06advpdA6zH+f5bBERLN5P4VYC2IRw2h2O+5O5QBAyBUZe6APgzyfx1G/5jyf95cE3+N3PFUQAWOq0G5ecaNWlLrlWrCsV1PnVxoL7WXch6PbOKeTEjojNjrgQoymnNdwFLlCKJFNw17xNgXXhCMcji/ofPWSjeJJXNNLqwS9cC5EINFLUSdHkWfVSzzb3wk2lD3YyPRVrailw6obQtvRIpsinp0VFIIWy6Bdn0sD6oDdawCNZXk6jWoU2d88Q+D9Gg/wmjkMkH3MF+g88VKL3JnYW1BAUdD6Eb3kvdejKCB9KiU54Q7L20tW1wBk0KAwoENXuiRtAJAyWizUWlPOesY9+52T7vsojw1JR7WKwkKWdjpiopS3ZEPQCTGTXUGiXLivhVf/EHiSsqBtWyr+OeaoQCTiwbrd6ORxRzX5prUGqwXWI/O5BP4+ovJAOI1TOIgsRuA+GRKXwxwK9TDw9i5AkbCnrJl5vc841MfZmN0uEm2K4qaGkflM5zg62sHMgCMDS9rRM8urHQfa3mB7z70Z4TRZ8v76/BVPpeDzh4847u7Qe8f1+ozr8xXH9Qo7PDtDo6twOp+JU6j5BLMQ9Xewo+GAb4VWHJd5wGpzfIpJq7EOdH83hWBvHfdT8FXdCo49MqdbizL1kcHIgNfOux1gUCYDVgSA1AqxYZDyjJNJ45TgWRkUK7kfuY+5BgmHMQxKRQusRmuKkOlv3z7CADx9/RqY34P/LtuGo/n6fvni2ehsk1FrBWN2pUjwWgVY5cJLvmRZWwYGOv6MgCMB9tY8qEKoo4UjSQXaFV29BVY3DF4d85BYZ8GD01wlTJFlj3zrmOXz69/++uEjKzB4JvqB6FPvzHBlqQD6MdotSZGhp2s4c0a8anwe2VARmLrdXwAD9ut1ZBrnfwQTTHn1zQRwWiUWyS/tV+ftfKflfgsqIt4ZuNz/lNMd+Dn/iPPPSzDjUB23JS7qYrA+8JCB/E1hFjNucYOZt6ccmozwNzCnBwZRZZFZtHkJ0xaN25JGmT06ZoR7FK4KhsgXIPreCoNwA0NY2huc9ik2R4Y5NfNVVi0H8Qi3Rp8w+oQLHJ/JUrWH9pge/N0ARvBEBPeUTcyxprz8bcf5vJlaXr9HAMEbLrZBXn4nwUp/A39LjtuvUbAHer5D6GcL/cbnLhlobXR9iHLTaTPkJOlWemJPTWIcVUsY0CawDI5YcHjYy1iVRINRzHKfWdD+fF6/jh3xUZIe4Ogonsc2PGM7Dv1AZPqccy15ywwioAOYThAR/zIr68mYl+HFsrzXCy7CzykKwGpEQf1m6OdMjsCQXo1mOFmGzYxVWkbJde0NbKXBbEqvGiAo0YoGofd0ERQNGYZ4VzKUmH+ogQUZGdCL0Cl6yPp+RDBgzCX11tZcdh+sNBh2Mw8MPND2w2XxtnkweHN7YrvuTk+XCoXh+uVrBtF7USQfM22AK8uYeGPyYRtrMJ9MOROfldMd2NSRUrpSLC8Z1pbnKzxbmdnLMt3Pl5MPDAwe+yBtHrEH67s3sRenQEYST9zHQokxE09qUE/GEjiWBtzO1XvH/Z+/Q+uG/edfIO8eYfgCvBOIvHHcF7SzX69QUWzv/f32D+Pd+A6zTR7T74JpG7xypD02/n4KHe7ySlamTmLMAFzgZdv3mGsu6eX7d9h/9CCBd//2A375f//h1wfn5LrWH77D8Y9fxhzG521as841nsbZpj3Nz+eEAbb2khjzAceNfO7xX7+g+1byUu4/e33y0c6I9nnDx//4B97+9QefT8pN3udo+XfRgkv0V99/YpWByHz/r5+hqrj8X9+j/vU73D/c4+nHX5KfiHpbzqMU3Be3GRcmJtHW16d/2ZroJTCjfcFlr2Ovo0cL13Cet9bwZD17oN9Zx103XK3jk3hSpUMGOoh9EcIcid4PFPXgbiZI4Sgob+5R6wbrH1C/L3j+6WfUpzvowwX2i1dXQu/4+J87rs+fsR8HrtbQMeQSZ7iL4ROAzzL2ey564JvEmVldNcPnU0YX2lByNYCU8TZ4uAjb9cTzxLLK8EBGHMDAOLOdLG458NYiR2NENpzuY6xx5klW5aNl+mTeDEI8kkM6HeuHZ/73ykU3r799p1+5emWTv/145fxzh8+U/QPOTpdbkkp/5TWHLWzd17/7+Ba4tFd+/284/oc40IHR722QeJ4g63RTZHOz0ElMBcPvZ9OGin8piQbwECExrIbMMcAhsGms5rDOi0NBRRbPbPRba0jn+fm9XjvsN5yz0JJFWY4QsLMbLAP5fscuk6m3m0IiK4G9uv1lnLkR5LmDnQ9TFZSqCe577ziOA9fjwDXKnLfWICUEYHOHdp+NAeol4gWu5MC8B6NK854rhsjK9GzxGtGdfPMZ9AAjWzwzboAsF+cZcSWzyEopCeSYcc/semblNJtKg3aDtVGOLmA2aKCYQdlEljeYpt38+0U2OME+WdlshBbJjLvhRNcsCzPUd9K6wc6Uy3WQ8WwH0NOoiNUxgORwxBF4RClERmWbP73gggKfb4lROeY32BfKLh95gWCP/di/GMq9P1jfOACqSueOwKzh7nHD85c9RLwA5s4SAbJywcAIfMdwwkUJXYl6pjRu5jzTeBFR2XTQixjQLEqQjmJIc7/X3nxOYxpyLkQlSkACvUfP9hKGTii2ywX39xdIRFN6Cc4KeWYUrhv/rPcsFyimaZzMFWF/HwzwwXlYae50yEvKPK7X8TMqFgwqB+rlguO6o1629UYJjFhmzWnzcvcAEWC/PmO73GF/9tJl+/MVl7u7fPboZVYg0iZ6+/Zh8BYTNBZtlwvQpr6yAEq+x6ALdIMUd3xk6WyuPzBETfAEru3d3V3KqxmczrsS8FJsdNaJTvLB3LleqwdOKACtJZ1/kFhLo9LBSOx5schgGOiE5OkW3w2n4TRXabij49qGjJ3paRGdA1qfsQ5zWzg2ZimR/2ZZrhz6BIohgCi0WMg2f87CrRYZTZm+sMdF5uYaEhyfjcXTz5fUNZ6PmR7mF8/ptDRsrUbqMRe8JikljMacg6GmUJ7FHC7vRYfxhKPm+RtTBC0VtQzjYmY91xKO8Y52HJmQR6OZaoHUgq3UdC7m3Mw4yyjv6eBklqsBalk5RKMEmcb9ch6iJUW3DmzkUYP39mz7wgH680mrzGz3Vi49AgXcwdimUuLOd0NmIPjvZBRkxqeGg7vWDaIbWtmx7wdYEppGRpHIiDFBFUCYjRnbK3s4x6ahSCGP5vpk9riGozFag2QgYOxz2HC6ATHfNjgO75UbrMV3apA+5E2emzQ3m4RsQgkxTkPyH8rtdJ4PakvsoCmbfS6LxprLcFSTsonPwPeLZ2vIqh60ZPB+5Px+vMeMlwLjsWKHIHpnGhoD/0RQtg2q4VCGr1NBiYA3gx3saT0bVZCYgfQ98K/jKch4H5lGRnnV07CA0xHrZXzj4DhmCDNI7IXAHGD2uRtaGsvUQ1CyGpNxStcVj30KAKqWxg1RQ9sP9OPw0oStu2HIepZBhlQIGq7HDrOOfQeen5/x9etXtGOHGbDvO56PK459R4tqUxq9jXtk+DGDWcTgqLVGYIUHPLRoj9RaD9rRoP8eRuqOEYDie872Hg525yUSMjNbfwRub8eRASye4UanE8ndSzBPk+ZzBsus8yWTDgj3jFczKmIehBPVukpxHioZNJSUSkDo1SF69eoBraGZQFtUKSJWDudGrmc4GMgHfezijv4TdQlm3XBUYjL0bHWAeIZJOCuKZtUFym5/f2Sb1pyioN01cFlSNgXKnbjKJKT/2eO2oP7m4aNqp09u3bKD7Xgsfuf3L86fsIeC+3s4sAgpLbAOzIJeTvezAWNeG3zadX/ne9+41fLsvG8aRCeams+X6V/Kr1mirDwvsRb5Ix1Lou5Ejyvp2kTwofleOQo+c8ZG9mtTIYkzV4a8kk/qoYkrxvdnZHWWN7nIvNAooSznlntEcgNzPHYTeN4k7Xnzpzd0PdNfTWCiMDnWCcy1mJz435q52SY2Yd75yt9wl3x2Yvfpopz/TG6Jz6dzHPsGhQgxnPGbcQ0wdtVi8Y3gDEEG3wGA0u6E8Z68Rujom+ZvTD33dgRJyIRW5/UlTombmNpaGVMACeuhMOt4vEgOf35Hvj/EMNNDDt1sfE8a46RPN0qdzdiTeF0Y2kEZtMOrshXKt45pHz0/PQEwbBfXZ2ecOj/TIkKFfCMTUiAuz/0kMianl8mBI5FVyaBJi6A65yXOd3vikCGXgPhbnWerOE7kpEqcLxIYyZk8Uo8TS9mY3oQQtpJ8wAMypUsGtoL3MRkmcX+FKVCU/EXyuzFnQ1NcD1l+ZYCQTNetZ5/vMktoO919EGYBoI8PwKcvy7fng7pKBseyLc3bx9EewHw+Ne/C1gRuHzbim5gX6ntLbDrHrArYAXn/NtjdGwBfxrNiLtuHz8Ni/C6peymxft4V52dxNp7FsHG7LZNw5uKCq9jkRF+/Jz1K/j7WZ3pBKATPAvz0Hz+yYeAqJ4HRJgDA9cdfptAp1/SarLLtPNJbv5/f/9aRMlmA/tPH0F0nh2ycY93w+NfvB5/KMazv6wlbv6DUP2XLyEUSBU/zYFCBtI4//e0vuP7yEUWAygD16gHqTOyjTmrw6l2uQx2BwcI+SzmSBvuxVyzeq/VohdQajmbuUA/dphvwGcAdBMw4+SzAO1EPYsfYbYrgBZDUU7xqWbS36Q2CLZIFBNufBHooNqjTauvQd2+w/+c/sO8H2tGGDqSa1XBdV22hdjBIigCFlEcpGnqHTUkn8XmRkGekWkZWMMNP4I5y6xFwGzqfWPK/9KFjeCteUt+N4yY4+ieO0wa3EwYZn6/Pe8lFf89h3/jrjz1+77QODnOSErR9yrrv/1fGdeMx/1uPP9yBTgCUgpwa2zwpMVPD4BMOKcFi+Bt0TsXL8inZG9EQwEnwBsDXGaXk89ZMRhHBV6o+MYh78ywmlht6+NN3+Mcvv+DRHETYpBhs8OHCVkI8y9QZEJ+/t+XnxLDjt+EAXSmKxu1lLnOaT9Q3Ox7iKBq9lDoj+vz6UlhCdH0pjfqq556cizgPw/fR3GiVBknABYO4wPRS0jQSipc5EkS/IoN1Rhoqjt6g7cDTFd6rNYRibZs7VJlJ2yUVHWBsaoFBrLghI4BwiRLZ7H+dZgFDXQAAIABJREFUAL4pOo7IthnRx+x72JvBewL2NPLSEOf5DS58CRjcKUtlYF7ogKpmiLqdA4wngB/gToQRoQLt8P7ccqadsb3EPOrMXzlmWYGMfhZJhdEBUPSgCsWPTgUA0cNzzGln5QHSFIMNxA3gmZwijFoVlDcaQDNOMEOP1tnp/HpyZ4qKZl/C/mQob7xcvz113P31DWxvgCh6lPTy6ELOeyghaqlYHruPX8UVrVLcCHvZKi6Xiz8nMhxNNUqJ9VTwJDIO3YFSgN4g0hJIlFoDAGkCMq96gDR2Mxuavbk7MMooi6CqomwVd/cXVPFxbZfNWxnsz95n9BpODZMIDOnoJqjimZgZJS8e7a3ia98D5Cc/ifUnMyBw8v8TMQ0Hm01rPatlpOLj6jGpMzQftoxVJWMQAcywXe4AeIR2i2xBAxKAk94IBjGPIYEdlnvnZ6mAuoHd1zyMw+Z/WyrrQ5GyZhB1ZcSDgmRkP6qEs9BBrqfZWPS8pHSa5R3SseWzoKgokBo5fd33vkn3ck10YjP7dnpli3dZNjwd+3S+hLIxG9vTADCgcYRKEzjbMHLmmoW8kQIGSgxgTRk9dQyeQVPcS4J/ZXWMkJEipCWNnq7x7KX8oo9lq/5srRp7yVLJJl1xjrJix+nwWUfy5Fm+DrqZz8ep7984J/cJHULAqATgaXn5jm6ImRg0pyrobTxUsgoFD+X5IvF5rGBWkFn34ggAHtG7NDiIKIoiAnJK/PPBNDPn7VQWxa8r6pVFEDRpjN4A+Q8duj0q0RCPefBSLeIO8+rsUos7ZsrUv9H3paCLZWsFoUKs6vhB3KHsInUYwXJu5zWMvUiXR4+UTBFEsEYogOK8visgfewVxHNLlFffoLiqutH/ODygjjejTDBWeKAsdd5c6qhYkcbz6WcGBcRHSXu5fpLfwzx4zzpgEhm1PfZgVAxKZTcc7hkP1COTBwZmWhoQCu2Eoo1zRSFBWeDUycwSDyILrBK0lXhLWBWgRoCQRGnNihJZr7Nl2ri2+S7+dQnHKI6GXiuaAaoHGvuUJhIeE2cAF9lnIbN5DKrBn1RRnp6gtXpbIWu55h5MAjRMbXgCK1BOMrNJxGCted/0kCcIzME9zvKwo/RcAKLeplE7P5fFEBuYzrzsZ0NHMQYEwDGouYOZxhYPQrXsv+pkYYB5ixkG2rEnfDf2e5YI0lIcckCreGY7saoQ5030IBIBL4b92HG9PqFbRds7Wj9wHLtXVGEVkR68XxCtSfjiETio3JwVYGAgg2p6gxyxLwOLpO4x4TENfuP7pqfD3gyw1ieM42sk0jwT1QLfxaJJqfABC/oRPbObG510K8nrYMgy/qrF6TikPrPO81/wy+EMCIwaxKIqsE0jI60BveH+7UPoHge6eWBCi37nPa6n/20/dkgXbHcbgkkDZp4lr0H7ADbh2FxmdrjO51XB6GwQXLQ6b4jsvmYHzIDWjyjjbvkuYoZLVIxpNoIzzBWPIJtz1SBZf6WgXTK0bD0vd3xyjiGMF+E6/h7nj78t7+XIhfxSbZQ19VXpqXN16ZDDqwKRH6j4/PoDXM6BhSdCj+5H9FgNh1SmcPHEeUZSToz3Fn7Of+djcRTexj23j5xB388WcjCmNHnohHmWx0egPS/OUsiNmmngHoRrpAMWwZAuvxvMPFiJurNasth8r9QTbZqbySnE8b9c/xwoaJ51+4YNP1fK1+k+KWotSDfwa8yNwbE+Lx14uafsNaHDjfIdKUNTke9D4KfsnX5CSCrD6Z7fGZY5SByRMiecVlD0zmooDMrSnBEgWMXZIzoB3RFM+yvHrJwsyxCyEi9XhnSXcny6ZjjUp7GYjMB74de8P2V1wCXa4cK2ocXyvm6HcRdZKRLr5HRbSoFFuxsDAJYJDx2MROrfCUT60CuSl8T+hmMYVvEAvDAMId+YHxvvw3eNOTV4e4NBs/N+B3RQBdKpO41iXgY6+51e/P3NBK0raqUdwUK2Bu/smKodMjjIQsfB+mzMY/Pvt62mrE6ebJ5pKSHHWqNNRiP4z/J6yhi3Rw7XTr1cYDC052vohxp+rsA9LvQhUGh8p2KwrkEDXJOxV1k1UFMnHnPeY3WdnvgePYINwx6XOE/cfmikCc++7WZ4+voEVgDySwhUG0y8bUtBx9HGfqfVl8eyW8mzxO9FPKwxh9zrEjQY0xj2OcPl3cNaScc6tANb4KmnXz4CkMw25/0evn+HctnQ7+/w/PUJT+FIVxsDS1pplvxLHh+iRWGJZAQmaQHl/aMnmxhwmFcCar98xsNff8CxX0Hi0VrQW0ERoFzu0Pcdh+0QBa77Fa1/yt7m9f1bGN6g9Y7j5w/QtwLd3mUonxiAj2N2U95j7Mc+fcYQdH5n8P7lxnk9nTMHUnFerjJdHZj/a/x5F3v0OW52iat7jNUzu9/DfvqAt396j+2yAebYsP/0MZ8y9zyfqw0gxvlVgIdpu55HuY54/Wzm49HMENv371z8//gBLSVu7LF/fADEx12K68Sh+eNobi8sGoXqJyEnYqhFIXgPWIcYcPcnQ/tlBFN51biOTdV1+tbQjx1FBEXcJ1PEq67RaV6K21hZxn20FrD8n0BTt3bbfdi5E484xtuPA9ejDSd6h2Pg4AXNgI8A7rrgS4CbT6xEZcDbYHPXDlx++gQtilYU+ucK6xdA7qPSn0GtY9u+g8hnbPU9Hr97hHx+grQD173h6T9+xPXYsR/NA0+I0xEyJ6oJH91w3w2fl9WPfzTUCdfAE3yKMUXRv3d1LexvkQzFNC2b5EQ3QZfm9h11naRD0s5PeDQTGXdHqI3glI9zLGTkwE8LOEossmocg8ut4Rw2TgcxrU3XnG45pRqMHWGnv6erX45vuj7PFFm+Jw5e3l18AGsQ3glVnbEczl/f/v78Ke/aydv42TwRAFKRT1m6vo/bnDuMVV9eg4m/88jr7HSviX7O7/WSE7/+9/n6P86BHsrSbDBIA2MC9BsALc5VIEqAaYLcJNYwGPHPmSC5wb6a4cE0HZvfWrAsi7t8iCQWx3MdP3z3HZ5++jlPERG02JQ1KMSfJ0uJtoxEl9M4TkQ1P/rlJ1zmKZtN1huaSChxedag3FsbbgKF5w1IQ+Zc5tPMMpqr1hqlRyNzBOYOT60QKI7ecY2s1bpVH1dr4dizcLBGPyclIciIwkSwJzLN8M01c+Gl+xVFFZdtg14u2ERgkUVeVIGyOegAMtOGPfuqFkgVFK0OBOI9IIoOwWE7LPoq9sjE6a2hw9D6gWZuPG3oOPqB3RqO3nAcLcTIWBd3eHWK4UEIiwBDknUufhqg2DZgWk+JnA7raCSFUqJfk03MKowHFvsNUTVB+B+40o3hmC8hTAvUg0REM1CAUi9L78W4ezdoGFN833qfVQknjQIodyXkQId9iX7CueYNLE9rEJR7hT0ZSrAvhaA0hV4Kem04rgfuLxewbKpnInmEPfs5skdV9sGScPyoK8+qBdu24f27d7i/f3BA9Lyjm+Hou4tAcWc64j5dLHqaH7henyPYIJz3EPQAPNDNM6rN+0wyi5A8T0vJ6hWZFURDVO+oori/u8Pbt494ePOAr1+/4umL4enTZ/TnK9AMSme/IdOC1p6X8KAGljiO9xmK+MoXyB2o2KhIvsN+HKkgAsDlskFg2K87LndbfM6sxMmhBCxGmKV0kvEcH49q8fWNPmEZIRmA2um6RGS408/MT8+O8/F6YRRw75Mr9AqgufOnBzihA1Pzbp6HVCxmb0Y1YWB2+WVhlPb/9dbT+Umw77Y2f88aPYTcH8m18H2qUSbeHQR8MR3PtRnUuWWP5wlB8FyuMdbFJ2UKVPKNwNkFs/pW2Kkxj5r3sgDn/t4lHBgcgIFRGglXaYQLnt/CuO/MZDKyQpI/kX4lSjJqvbihhWW0s4R2KE6xNnSpI5/uc9WBdGwt4Og1vCmT8zqXh4tJjj32gsxImdlngsg+HuCSMnsyYQatupqbhiYqJ3yPaKXg5YWdT2iuNV9oepmYcx+H005rXh5sq9tULhzBO4Feg3NMGdQIvqIGKB3YE4KXCAwDg4zgQU9aBDWCkkpx7OZ7BOHE93fv1tCjtQtLapbi1UVQKxQFd1sBtg17bdj3inLsuO57OPkiOx0dXU9lwWN1SnXep+zDHTJHEIa5CEIDhqOziEQJdoFIBXRHB3CIwFq0AAlScxkBuLEuDLaxXiHsIuvd+coo/8msfS8JOZx4yTqjx3GHycgUdcflkdn+7IMsCz0E3oakw6KHM7KFcXH4Xix4T9Alg+ki89rln9Obipc0ZTlq9UiHMe+xz73CB7PQZ3r3QARvv1LGtYsCaSii2GpBax3t2PFcK+rzFdf9imM/wvGZnQBnsgdgHmyGA3qwdLageHEZyFUBfA3jtp/LQK3dOo7mFZMEXk0p5ZCo+5WiBzzEgz6KiBs+joZ+NGjdsGFkWzG4zXupnhjOpBd1Gk0tHFIkBzlgFg7a5hjN90rL0qV+XhiHLRzb++4Gk0MTW/fWQcOCG+c1MzG6eCCZNLhzPujRgxODXnpwJImMMXFj5+enL9Cr+PgsWhpZh5l3+7PYq4ixJZ8P+d3gBl3H185HDJgyo0OGI/ifeCaGokCLB+tctg13lw132xaBEG64YUCOmDvF3NDVUKVEIIE7pQUefMk9KnA9ox9HVsCgwRDmhjgPmlBUBawY+sF97CeyD6MI0NuR2N4diOYyFwKooojCLtUNVkVRLhccvaFsFQgadTHuRnYz8WXoAhwhfzt3hEJMUaRHkKUBh6GhpRwSVTe0d8CaG5I6GkwKoD3kZqbBoarCjMFJzhdo4KKBrk+BiEZ+aiPo61V5m3uf+9l+x9/nn+ff+bfcOFfyryHN52/Wnx7s7X8kHlBvSTLC+Ygd/Mpog7yULHc9JLCPEiPFfRMvzbrekGszullf7/wG3z6WGREiEQschXS0IOhlnC+JVflYwhYUhUSLNgaoM7TTlZ0h47z6QUNr6jx1eF/AKnfdOqRxP8bEh955flWaQRJjhextrbn8NQbwxvNnEgJCho5xJ46QsZ6eNDEFjIe8sehNxX3AQELq1YaWfM9vaLlP6EvPoYgA5k0vulhU6vGyz0dUwJidjJS7BqAF3/WKJAfN2TDX6Ac9nehgncdVJsvpvHXn3D7mIOsMyjBbrhkIeLqXTE5oHWvJ1hZKvKDcOyOYIQPeXHAMrGpjzX0MdAC7g0DDyCgwaAEsypkD5m3R2+TAFDjBU3FfyNCSHwjxkwpqlEMnnwxo9mIeX9gFAb+Z2mK/lDiX1451mYl5+bGuTegXST+hw9IOyLk1877itEsQY3YANso2zTc+sWAP/tIadr+Yd4OXticApV3Es7RLYl4AE08MXlJKGuKfP3/BdtlgiEA37gUdSVCtN6B1SK2DR96YFNoTWB0HIlP2ucMd8pO4eQQkRrOEsH0SW/U41SJYtQzCBOnEMGi2SMnPmJI1Y0X3UQnQnV57j1AYs4kWbNzbGKg/3UNDrMf8ycPdEmC6BKG0FuXu/fryeI/2+UvUYonz9ytEBQ9v7vD86cvKHziUCOxsnzxDRh/fBA1F8g9YWWvw094N/WOHvvN5+Pr3v6N+937s8es1xhuBS7XAjucMrDQ8oMNLh6twXQG8e+N2vR9/dp6SfGnsPcq0CtysU3NGHT02owFe4Wu67irzhph40FiRcX/Sk5HFOA0zEz6faR8BeYSa4PrTR1z+7S/Oh/b1zi94C+ja9N/vB6vK7/X0brf4e3L1oCGFO1LrtqH91xEtgnxNGxjgM0Zh3COMvaaT2lhVwKLX92wfMcYwwX7qKOIJYSB+ggd91OL2kxqVLEpUgKrCUvMRZBt90Gsk0qiIJ65I8B5WdbPQuWmXjs8sAk6v1wNP12c8Pe8e5N8NhwGtR4urcGB3M18e6tV9JLQdPVCNAbsAF8ryDwZcgPLWs+gvteByKbhsFbX+gMtlQ90qpBQc7cBxPfB83XHdn3EcYVfprr80ZsXHWDqYiU7+GgYZCcwfNl4JvbaiADkXBvSOrVRcqleUY7KPaEkqY0Lb0Q4czQNQWwSAN4yqnqYIvWNggZSRZIjBl/IzbohJBiZRxg0G12PoE6mPHFaXT4hpZynKjHTGiuYIZwaXG87yszmsfz0rJzw//SaWCmAj5MlAVBS8JdV//WA1kNmJ/lpw5PLxK8zgFkebL8H8PEXYJZABqQHlxximm8n5u/m+0y8zKcy87tbwz9+/9vf8fvz+D3CgT4vMzAzrrsibs+uhoBjoCDdYgn7EZi/MrjZxh6b2zPbgcwjQx1R0PEDwBcDXiWDoTHyNCB/gWeiI+32Ja9+aM+enDx/g2TePAD6jEfTIhKlJ+EAI9EkEDr1iOfhnl2l72UoMtpwtASx1/V749v7UkgqJK2/N3FirMjnvEkBNz+jF++7CM43S9Zu07llcbtTxe7VksmMuWvMSqj3mIh4+poMZejkJ0+8R6QR4jyGVKZuIP2MMvTsgV1UcLXqRh6I5eJv/raEAuxO9RtayTMZeF7ReQpGR2wYY+zEdOY452ox/Z18ymEdfxhwno57Ww0IoyJljLeArmFDSt41Mwyxh7pHxW/JnGq0Gbfi0+zhqZBRCRrSxzCeqQFCij6Jgb0c4QYaivmwhoZjyQ4XCdayrWvQ9j/dYgwyo5tchZJ+jd5g4VXjkqmeglyK4q94Xu0RJ4PuLou1fvCd89ywii8hFZsAUEYw+hYxKLNi2C7btAgNw7B3H/uzGiN7RrEebAGfo3br3UbcBKEhjeygMQsoJ2i6lYN+9XJABuNxdUGtFvWwDqGWSlM9jKYpaKu7u7vB4/wAxw/F8deHfI++3RIS1uMDvzTN5VYdC5pJKpq1nSeuNoe3LWkYPWos9Hcb4BQhMC3+5jH7l291lsDgh7YbyHXss2X7wgREog1ScIRKJ3WHIbgcJCVn+UhB+xwBj07AWY1r85O8s6VykuOIa3zOzVM2QWSYh9Y3OGo1cFmHWSU8elW0f6KR+AfAQgSlwYKoKJisL0YS689F7r/u+NHTv5YzIHrTBv8Yk+wN6ZM5pPpOGz57LZmn8lAE2OaEgj2KUaHCGkH++juF1lGiRYFN2crznyKwNWkOAJvMAF1f8IzreAGiFwU4OcMu1pLFVNfrYd4PSiQRAa4FErLXrVieTr8UX5FI2rQvW33mPBHFBHyOIbPAs3iyflVkAg2dN3+ZasYc7+0sPpwafpmMs8wC55DKt/TqU9YUyM3jwoS3KV4tKtB+xyOyhPBhrkEoy38WARMMy0XzSve9JrcX7rEeljWhJ7vs5q+WEfJZAfaGcGoI2ukJLB+CtNVSBUg3Wfe94CeuWlCK9u6Ev39cngTy/qITzcwr48HjoMdcSdF7K4BxaYQC2yBq2eA8qnlI8EEHMIuNYMvOavRTpQC+TYTmz9mNf0ajrezL2IrNao9oFDS2OQ3pij8z8T//EoH2220m3qREdhjFPiEXcaDctTTJVMXeUqzltFjDDnOupOX+QWF/OtSL7vHuVHzdcUJZLlAOSaUy1Fmy1Yr/uOEQcR0YEfTu6O1saI6RXQ6HBgw2t9VCCuwdLaoN1ResN1/0aWfE6FLzIqG4xxxLl/th2RCJATsvcUsN5uZTi2ZesSKDqzwcgiCo6guFcTV4SeyjY83a5wAw4jh1d3DjkGLGhxRr1CJroERWUWs/YlrEWEo5fb4nUArdmhQxgZFMdcL3Kuvc9j8xjiSo5th8hIhxHZcUr6+iHYe8shR89tdsexrBBmz0yymeA0BsDJnc4yZSJmfn9c2+iwDSqGIXTnA4VjSDay7ZBixtHmnXnCSUWlzgh5MHRr6EjkMdb4g0NGhaEQSkUA+sho8kjw+jpWFddH7S4Z6Y2wJ1fQCiI5nSeCyfpdKlSFmEkZnh4+4jjOPD800/+Xv2YevF6eURfe6I9H5uaokMh0ty4q4Z+eO9zqAINiQHcaeFD6dYgVlKGCcyd50D28m3NaWVvBxqAIxg8v+/UlUIoOc4fMm1aYCyHnD+//ZPO+SEbT/c5HbxKpsnltbNsPovP87lA7LuuHrQsrIBAi7Bf6TQBgO1CDB7c6ygORtYr6zhIV2zNlYb9GBgDB90ZPEcEnkf84uVPH606JwOtACQ2EKXtYsyBL6flc2lPcezgdK+luPzm+wU2lQDpOdc2+Df/SwOjz5mEfNRwKAw5RdrM1+ffQCb5L6/dO+hSGsGofI2U9D6KzhtIZqkJjcoMpD55OyVEl2eoj2l39codBCmleLI4Tp1tUYRXciBpICexI20a64Pd6dAiMYF4oGuBtQYTt2OInWxFeYvXaefWN5ytdd/I6YIxpzit+3LVNP/gu8t8ffynA6YMSJVMqiGtkjp793Z/VoKOIC4jQ+7x3lp14CgEzUvgNMpEG3PdotUgddYR2EzVKfZtro25LjDpvAKDTdVzbFmE+GFjnxlnOehgLcedT8nzM2l/+fZ0QYbrjz3MvT7sS3C7DysohDzhOdIt7UAy8YKXzwon1LFnAEC26pk4sv8STrfQwbOcLp8ewonz29sBKV55cGaQzmdjnCJo+46iWwZeGyeZww5GQfnnWHCq05DvFfxMIzYjq9ZM2DuxNV9vMKHOYCAh36Pzxu0+tjttevKNv0iutmDqUU+5z+SCnpjGRTntaCsmzjL9MU+Xt4842o4oz+X3LCDDgkTUV3188DdTgTw+oNoTRB7w+ecPABybOGYy1LdvyL6TKrsB7dPXtCf1T18y/uTd3/6C69Nz4jeO3YMzvsI+3kPp9G77VLlq0OlxfU6acHHRUYvbVRpc3+3Rm7p9+LyQZ8qzOEYyS8wZ6SmpeXWqT9MJBvDDgOuCR85PxOnv2OXmNvuvccpDfLvH89/8+R2uP34E8Bbtx4+4jzscxwHAK1/Kn9+j/fgRDexJHmsQT8lsXnBHr+9/hgkzLzmPvEskfwDY4DZU/QvQ7Du8vbvg87//Hdzd+uf3HgckdJJ3tP0X3N//kDpyD51UxfV0BoCoKkqtaNdnwAz61/eopeDp7z9HVU0f2/GfP6L87U+4f/OIS90APGMLHAUgoVlug8n+y/ZdTRAVXbs7Ks3gjmO3PfXW0NqBY99xPTqe9320pTWEwxzoJmgdaN3nh5UoHkzwVR27DdAnaGKo4okFTVwH3wTYvhf0owNbQ/vxZ+Df/obtEtUp7SPk5x22FRxm2M2wt4b9aGjN8Blu16ETO53oMRk9WjEl6wqKcN4lQ+bkmoX9uHlljSKKGvaMEvq/aAG9SA2KguaYw1wvcl028JMopDSwditpscdaDdE75AUlxsCHMw6aCVbyGl45EGbYPidnuS3nnnjCct/hcF9Fqy3Xz2Od1PzBjyd8mMO/CcFk/X7ZoLf4y68f5wz0tMtjmjLBsEuf2JefJ+EfGvzv/B7JM/nKZgsvnQDO6XqZxrV8M8Z8eifBeptbPOv82bd+nocl+ENLuI/XXV50LmMyIMB0zTTDMpHoOYIwT7Vlis+T/K94i3ViBYK3AD4BGGVbbl0zXbL+PB3nTWSnn6kUEmWfzs/EsTMR581tmctvbz3nYLI4t86jIycgI5qcyb3jQBj64u/GnqQBPP3csb6DNgCWYhcCVAnjZu/e25QGWw0nonpJeT7ruu+eXdI62r67AhQcohdAuy7ly8jGGYWX2doyRVhNXCygbxq0CYjJwC3PIQ3LbAu8yURfroie/h7smn8LCJonBg0BIvI9t4u4cPcADwoxmgxG1DeNwryH982m6MGoVHAaVpZSE0vjst9GljcxM/SvXr5fM9vVr9V8tqGKgiYPxQ7IPSDheNwV9V3B5e6Cth9QLagqeN477i4b2l5gdyFoQYMCYM1Qa3VnSvGsuqJeRSEjsm0SknQOdAfumrNE57MvaA+w1VqUIwv61ihrWdQrYBQt+d6XzZ3nogWteWn2WbiU6ll6bohyg7WKZylVVWxavHS/hQNdJelNGM0JL2PU6Yg2S6PYyIIMx31UUEq8EgNpe/PevydaXWWbr/V2Nxzpg0wSsfo+536jIcymB8qglKQdmz4XgdkxTtdpf8igzd/C+60bTHsYTAB3mEcZRkGWIvP91UaJnQCXGY0+7cFZNqwHQTwrDEQwOaPszdfBJDKZxHs65UQakIEFsGEAz7DECb7ZGE8kpwNJuScZ80JgCbL3MrM/MNaSUd+AK6ZUyvlOqUyau8OyBOZAXqiiwFZ8hzF72RA7nbRged0wcBVsF+DYWZLSsw44oiqekehTIFhuFYOS8/tzab5BMPPpGUDApxqQni9BlPOXUYFjuset5LD8XvxtaTxfHdmWyzxXyCHPp7bhZBIyW2RS0pzuyOfu7u6wXS5uMDSg40CTni07GJFNGcBS60W9KkkXY3JPGKVtMSbxxXShZZZQpJwIrOIv4BVhRKHqzTqYLWoIo1Nkv7KVRspZ8WuT790ANK4gR4CcjqDNpaJO0AcXg+Uiw6IKQNGLK/LbxKvYm1nCaQRLNjf2usY8Fh3rijDIgtH6PUtxI+cx5qkKzlpKVsHIJZ4UIMFyPSBZmpjGrWFEeEmHZ3so7z6cJFxTL/nN1iPsKw8JxyM/U4/2L7X4/G1esUjVZeMwinE5XKuv6hkCbgRoaYSGwAPFMEN/m4yONtaSwRQIxdzCqcpyu40ywwKbWho6QUd4qZ7RFI7aoqOKAedKNTIZisLAAA2EvJp4N+Udcqfkb1lFJhwq5bJlVtVw4BLLRC94Vh4QYHDmiU4wAq0MI/DMbfiyjMCDORzTJG8xL70Gs6nMXWAei7mz2GORmQxmOsS6NLY4md/fDAYNP9YQGh2Y6H+iS/KRCqhptG2KYErOPQ1hVUcf1N7RpLmRNhz+nZkX5CGQKagzAoa4d0UgDRHo5jg5EUdc7jEMdKoOLEvi7K3jiMo9rfgcJbwGIMWDeAU+j416Rzju0Ka9SEFCSwTJnOtB/I5w2CaOkRwzYrzXKwqfAAAgAElEQVQzDYooqpYpeDuFZr5Lskd4WUY/kdxnoucbcm7GjrdE7Uu2/QKYfOPv33Puy7+/dadbx4tzprQtZ73cK4Mzp2OW9+ASJq++NZIbwmz53H799NOo5yfMdwmJ6ByE9ZrPa5i4fcjw+T7E6s6mFWo94ux+BVzJuEm2Lcq/b12AlKHz2y1OYBu8b4J/iDAOjD7RMq3dhJco6/h5Ptu5KPnEQvNAYCHJ9aVx2kKnGGHVNrBysgvJ318S2W+gzOAJrD74rSt+C537LZ1Iz0P6VXL7vYfc/l2AxE9Q0icgDMolPONaBw9M9hRyTEVCZ0A6YoG41iY7hZyeHzYblw+BM4e4yn0z098tG49Xk1kl/tnwnOJounRiI5NWvMrGCY7eXheZec28tSWxYOK1eBfK+vwenGPaQeLZ1N++dSSWeCFV1pefv7tpY5KFX7ajRZWZntZ+X3M/x89yh/VxHKhbXR7FwADHi1MFJ4x5J+WfxK3Hnk02z5zXF+x5eq8c+3C0chxmHjiQ9lu+R4zB6Y463ouJeTGHJzJG9omfzqLTv3199gDqN/duMxIGFMddIjNf4OW0W7+HozfnpfvHj3nP/ulzlEwf4+qfngDIYkcGgHd//XOMTYJGLfUPUUF594j28RPMHpNgutkQt6EfZsDm9IZmQP3uXZSxX2WDvn/rzxrmvhz7ee7s9G/VzF4enN+LSTjRz2t06+8b8vzWM0Swfe/Bu/Vv3+P5P3/KsfaJMOoP3+Giguvff17uOZyIU4w1MBz2Jzgx//4ab+G9nmG4dMPxjwb9S8Hnf//7wpd8X36A4X3eRWD4+v/8A5e//imT/dxIQGt08PTeYe1w3UXE7TxRdVBVoBFvKmIQ+wzFI6RbJKEgdAd4hTm5sbJh3+gAiiFSX8T1ZdqCuycB7seO6/MVz8/PeNoPPO8Ne2tedTfkfjPXtTv8Xt0G9vuS+3ngiy8qeGeDY5FtGICnnzvK9gF2/wO8rq+Hb1RVAI8wNERXsqTl3oHPMG8xa5EJ3kK/nWxGvQ+e0olRTDAs9cOBDpWsrmBhFywikB54L8om6Eh99QAO8apVYiWrenUmtMEDDFSQumKHVzrsNjL0l0lZqHN1opNnL6LjJpYCXlC4nE+zXINx88B0Q8jcuNfLRw6cOPto/kn09C8AXS8CD24d/3KA96895qGdh3pr2N/ivr/2N3//gxzok1A3zLS//nxlxRyYnr+dRdpr4sfwCIkeD351Gk7xbdD39ZXvyFpGT4mPp2/55FFuSfn86dVeE0jyYk6wALechxtzxt+6YYqMlfW+uYEnbjArnTRs2/Qc8cyC3t2hSSM/ozapUAyjWDzHuvcqh6D1lhkTXtYjDMUYyggBFAyQYp4lBoIrLwmn1Qd0tI4iLUqVC1S9zyb74bozcveIw6N5GbPWw9niDKyLQNUNqd5XVaHmmWTWWzjQKtS8jDsQEcqRgQ141JxFBiSDBvz1WeqFgEVyuhHvZMCI9MRkd+NizgvH5QqFh44g1sBIWhZ3PLixWTLD0bIfoYMMjTSlo3ePJE7HSThcOe/MDg7hyPVh6Zc00DFiOz8YBuRZIVG58/OeQtgu72cQ3d3gEiBBcMEoLv0QJYsjc+2NZ7JZjL+oYrt4t6BjB+pWsq+TAeh7R6keJYcavXk3N74CgrLVKD00zX1HOkWVdGGRXcGsrzSQRyDIFK1oZqgiKMUzoqR1tNJwXy+oW8V2uaCUirJVXJ+f8PmLz2utWcwavXdsm/dLR0xvqYJSCi53m5dVBVDuavCdPiKpOyDwVgoZnS0A+4V2syyJ17KaxwwyvZSW9yMPSiaoOHmqkpXY+avhTMlzdfAsKr0z+hGdHam8dgBsi4y1LC8Yxm86H2YFaNlApzGrersGd5uPTAgLJ3qz2Ec+UI+45UsGY2b1D58dG+OaAPEYgmDubXkcR/LqGpmcLUo5L5M68ZPUAURPvHPa58y0UwmFfpU2ZtM60uk1pAIgdUjKzKAA5tcpAaJXUTNOyq0dxinKLg3eV8NI672PY/9E5rxXupOUJykH7HC+oer9aMN4U4rHWlvze3iPupfrvZbcHGTxKlicz0vszsjueKfEAjGhoVDAaOAbGRykiyTHpKFAJ8GL6GSWsdg5hJ6q7/z9AOh8T78fkjd6mwp3nt/d3+PucqEoQRMBmvd8ZL/uDBQI/qClpJOKffbQe/SJRuIdGlxV1Z2kpYRDS7OaQtEx9nRiqTvbO7wEmERFIoNnFAFwp2mnESl4uVq09pRBa7E4Oaexb4VZw3PVBpD2gp4FiLI7YZwVp8lQDWuvSRPkpR5cEDQYfEomvqexNxigwNqOqhIyCsFSonqIWTopfd9Vv8cQ80m0o8SqZdBISlyZZHcaF/0mKoqmFtHhnpWtGlio91GeLwMfZGCscIp7xLn3PdMolQd+zylWRSkVtVZs24btsmHbtghi89YPdLIQm2UWvriSrseR69gRrVD6hLdiNuhYng21KV8wsGrv5hWKRLwSUTiIO2U35xku62uU/+9WUNkCgFnr5uNlOyM6j2lMHXh46AAtKiUtWkbwC1Vgvz6jbCMQDeI9WXtPruz7LSvdCHoHFviCcBRjOPz9i3DgMv2V/20NfXJmd7a7UYlM5z6crsS62ftZvYQ49Qelo8GYqgVm7/v5FrjygJkEBnNaEWBZfwkZW6JlC8suipG/VFQGyKgb1/JVJYIBAheJCeyY+s6HaIUighQl8b1EpqNAIZtgF0APZnd6oEEXhXSgH14Ovh9HViyibgCzDADx3xWi0XdeqbOIZ+eEIQ/WYV3RpWDfrziOHbpdoDDcPzzgODb0Zvj86SNGNRiAFXKO64F6vyVfBHkaJM9x2/lwootFuUsg5G/sxzD+9TC2904jd4/1EVxqxWHAEX3rW+DPrfgz96j2Q/meTIobc3Y4/e884vmL4XL6IsX/CRsQN/agf+mI6PkJ/JrzMkRgqgjcyEiD7OxMkMC9N5Ar+TyzRMYIv+0gfXGLV959+Zvwf/FaB88RuzG6+ITfkbfEOzlfJR6dBhNOuHSUC/BK7ep4jL5YBJn4+rjH+eUYkMTvLGS5jUfG96n9TLiR8qU1lrDON8B5BZKCJB8TMil+yvg9M8l5LdloEVibdR/D7cWz0z8kfShcfoPV9+BYaaVx13iybVSOY9oBZ/1umdfTdP+eQ8aPF+s3Y1mZV5E6oubf1CXmTGP2NocyCUIhs9OAAeSJp0PGEI/y07NdTAF09cpHZgA8cz0DLsxyjs0MWkkoI5kkoJE7KSbNcJnDVyaV9iPS7HwOcev4/eVc+6+DfyTPCXzKvUQdTmTMKSCQaLnAeFLA7SEQb4difXnqefA5F/Ow3P4wxjbjo8RG5A/5seHu4QH789Xl6YSBRUehaO5TT6TxzFxP6Ikmm6GDDoet5fgMlq14qPeaBU/sg0/7ivv4GGzcR+3tuN0YP53VxhzneZ1tiI65GuBZ7tDZNWZxnuDxeYW8zJIGUB/vUwcwc0eWaoE93HmFUXvFLq6uW1EP27bNe5CTv3zybPGCB+CRfC6cWzAv2S7A8fGz27XevgHM2/6ZAbUWMPHKlz30TwHk/VscHz6NPQzg8v7tNAW0T4Q3vBTYbtj3K2qpqFFlQovi+OkzTIDrx095+bxntvg5O8kHNhoV0l/ne37VVb991mvHPTx48lm8D/r5UFF0ebeMuv7wXT5JGOTTDcfRod+/Rf/Js9G9lPoYFTPHvzVKufFznjMNGq28lxnw/7H3pmuS5Da24AFJc4/IrTapp+f93+5+UlVlZWYsbkZifgAHhJl75FLKlrruNyZlRYS7LTQSxI4DfMT6jxF0ZOc7HeAdJlKqoNR3qH+zzdpqCT3IWjMVL0IQjG0DAjXX1rsK8Ob/+RlP/3xv5ytt1DcYY8P49QHL+YzzzxX9wQuYss4B0+OHGkrT3K4zmC6q/pK2c7c+cFk3PF0ueLpc8Py8egDdCqdUxdBoo62azZvxGp8JEYQmxcJBnWifrQNaJy8CFF3Y+tMKqcbasQ7g9Zs30McPGOoJzmom2YNa0Hw4zDyLFkc3JFVbGIngeth3nkQU0v4gH8CkZNTps1I196QIStEQUOSb1ZwogWILsTnvPufUkwQszrEEdyjcPJnJxtSJgt7Jm8PHlmSb82f6hIPSfaGzLDsK3qmngW7euR5JZwQQyEr8bn+fo36YD2qhMepJK8BeHc5yQBVMoNb09S3VQcT8yUUEx+MlxKGYa+x54H7k1+9y0DwOAz/EHf/F4yXJdzwnz8/3OP6DFej/7sOm7sH/Mkj273nnl74xEukAPgnw9k9ZGF8/jj9HGFda2bWmtjv7YHzp7e0TzkQaDdDoXTgcbnd44FwjgL6/CZUVTrLBMDLLCEC3oKQ5Ex1eUOy84sF0c+YbXM+2bQYd3/sMasKr4MaAdAE8g3FgWBUeYOpGkVC2LcNKQrGjA1tVo0+QsnJsjHCQ72dofnacwfE1dEJpke64X7UUoPFvY912RuOsN1f3IDAz1IJlfu1urDoz3PyTML7D+ncjzANr02E7AwkVBlWT64tEBCqrx4lY+UhXUgtDV2AVfAWCemdBGSklAnEi5gBcVZ1u7OibZfWWpaCiAidBXUxBW9pigh2C2moE90ywDReyZig2NWPRowIYQ1GrYFN3VA8Aw3vMKyIwUJsFruBrU70HDNfKqszrrpLa+gd7VfTwILZDB9GAb82CEvDegMvpBBXB1ldvX+CKCLw6UCWTxhVdsW/qnhUcFAAu9S36m8sdZLELmvPeu4BGulkeDybfCYXbz+l9RNsG2/8ZjgfXm8ufVsrB4eiKdPGq9mJLHgGzmCrVQGkI9IkxYX0CjT4pHbz/fpolHsu5o8MCYklKS22WPED6CEce50qiEk9FIqBC3W2IK7TgHCItVFo1d0SVHHFJY45KCsieHlypKwIUNeMmV93fEA0GxTWnJxz+NHq1sOIdGEOS4qg+HlPKRYDaFqgonsfFYH77wIR79BGTNyd1TeZkv3xkovyMLiiDXJR72GhPLd3Yfb1c67mGopLmVaM6nPdhf05eH4ljPnRWhFSH1Q2a3WnZ7iAknRQL+LVi8vF0vsP93T1OdyecHSZ69B7jKik4OCvtYdBsIp7RTSfvzDRmi4vhEKkiMzjESuNaK9gzMRy9IG37Wlf/nEkbUMD7jw1RDFgwN9l4EBRLG1cGXjmvErKEwfNK2ZLWBQwUJmJh5WlJ6+CsGK0pp9r5j7W3yXsp1pTvSl4QhqjL2pFeJJFfVNgTctUdXjtyFAF0zjd5VTYKBZj7SyZtaJLJdFhMpAh12HA7ikOzVd+vxWXVsaqfPwPWi4a3r/2yLDidTjjdnXE6ncwJ5zISMGceg43TiPdagOIOgqQ/7kSGP++YVb2XTxK6qfQ+9RhJ98eEsWbFdy3eL88TJCJQTtr13uCtVutfrYrqwdpgzCQw5y2kYcVcr71B6wF6m5nQu3boEwHdT54qUxWDBD2AOmzcOqQPRZnNOxToIyGiqFcxynxWn8Fn2gK23Wb1v081JrLM3JNxrf8y/PoxJvoFZbpSW/X9U2pBraZPtVotgM4+hoFkYPyAtKBQaN/Qu/M5p6U+OqpMtA2TafY8HTXaCzBAwx7qOhfT3697xX7Htm7mpNLuCFu0VWxuxlCgDJQ+e4fb/rIWPa06KoMnxRZVyJAIsO+CHwCeHh9d2ExXuaSmnSKC06t79MtM8g6VPVWfc01CBqV1iqRgtXlVtiDAmLTIhIN0XX4ee+vG1jzqe3/J44aS4HrX3Isatqbpr0wewS5hIKsd9jdXJSmKN3WSa9nxXY5gSPk5ifbiPwfFkOeQ70OMd4np2DrGzeEGZ5Lj55OvH7+Op12N1UcsHPnBJkgGEDXEmbbFK5IOHbfP4QBEgmTsJz+1B19nazIAQt5o8nqnJB/mQ+DJodu/kFFCsujHD/Mx779LAM1XpGDW/+hx4/ZzWWV+IIgKtqmbJcQCwOwKBhoca0UdNQlDMRwliCQsIYPFzQ3KH9kPRhVaNNZOVaEH2+lK3vlRXHZC6E9CrNEesezl+bhpWKXT9aUPOH15TMk2iVYQfiL1ZdsDI+xb6g/HIIW1s9ErX554uwCfzN34b7F/zjnnI++1fJzvzt7CaASfmbaQ2xNcL51JPdQXud5cq+DVyGgQEkhaEvudyAb7sU8t5VuOzDunPrejixvzc7wDsM87uzUGBa5Q0PK35H+1uk3prWxMTx6J905eOIa1xBmXgepJpNaj+/72PCTZVd/cBz3sk7TS+HT+XrzYRd++Bv7oGMmLT/tK4Qmbu3UXLG1B7xtkWEEV5+HIWfNq5N2gh++ZI8dAdK7g/p6HYB88z0CzbJlZS43kqOGV1llWMlI+E6j2/4Z8OWfx+G6CiCUbSpHafLDJWdld5AhrUGxQNCTe5z9tfZsje1hhAPVwtg6IhCnnndyv9B2NoYZwVy3grUWADx+hj2eUuzNKKyjvC3BnenWmuQHze8uwSu0is+2CyX7xAhSb/aGGJLVuHetlxfPzBU/PK9Z1Q0fBUKs0NzAM2pG681Vc78D5s8e4+E/RlcgCiu33D1juzh4Q79GW4P7vlkSQeRoReLeNtoi3LyBqGaiOeEyGvhvtk1e7nUhXSbS7E0BkoIyKkjMExPnGGHGtva4hvYYMKh7Edx+HSKo+V/NZK1H5xD0AegzAkqlI2JoScobWL4J2yBOmP/mWQr3n5PxLbjF46gtUJhRx//1p0w64uv7fcBQAYKJ/GhOQE7FePr7XKP/y5p4ff+kA+rVY+/zZ+WgAXsGY1NOfeDafypxH9v3usaWnoKJgeqXAB7Gf3/qcLNC/iYjJs3Y3SsyCvLHsAyM9etdVqCJV4qaMRHUYK/aCVIVViE34HOtv6P3OtwFtFYQEBtSd6oAVQSSDpMzK9hiY+vn+vCHAZp5NrFtHke4O3Ya2NIMRrV5J1Pt0tCaBQgNnQDCkW0VpEYxVsdVhQrkMqGwoWqHSTZGECxEquANRBdVVrcJdB4b22aNU4X1d04rGq/mcenVXVIIcuVos20GrpiJyVOcHlV1zXhAOuLlzsne+S00OMwYHTTkelUFpd2xi9nEdMKisyDylVeHjkaHWk9vXj9LXggx+om6TqlzxDVhfmQFCu2OHoEGxOdLAYvA9vaDdeVBaENC4q64AKqTTcQOU06y+aieDjS5Sva+OKVbVoXln5RRpJabWlqtOjPMxBMtyhmBFv5hDvp0XYBOsagkKp1PzCsxmRt/SgAKsw+hl21aU1eZ3DOvRqjrQTgaN29cNXQ1FYV03rNUSQlQHanPITd8np9MZUoDLJtDLBQMGba3q0MhiSplVhcEDjzIVC7BqkPBCRkt9bEFPmY3kIOHi1ayZVwWkt6/7Mas/V5B4AiU3x+7e/GJChzPoYNWDFtwmvxpOEjeeswsiIBzVFrQzi0OLokrF6DZX05pV53sjYNzVtavc79Buna2f9KvMnzFXbggxOAM3NArcec95swkwvg2Jn9x3OtSqYX1fzSxbAFLSWqTM0eR4ovTK80bldHf4coShowKRVOlCNAQa5EgODR8Xq2SHDrq4YqJEGMhKVfiY60cePjZD/LBKD/KKmXDF5KcIDEfA3qfyUL16eO3bB22CAoOtioUUjEu3ea2zezthUAWubAvn2N8oBf6nUTh3noqjUAhmQoWPbzr45rsTNsbkqCXgtFqxlIZaF9RWcXd/h1ev7rGcTlja4ogwrEj0YFWG4dYpauzzEu0OhP1te08GWBCH8delBWx3rQUYZZ4D1xccrtstT5cLAHRYwQc6dIgnXSVnNGbVEbxqHYVVQQzees/xWqJ6OnqKAr53jT4FAo31k6imJkLJUEFtLoudf9AZJ1IiISDW00kgLMTQd+Z5E7GGbEbn9Wq6Fftt2lcjzudeYp9GkmiuVIx70tkkydHCnudBe/D3BALu0St/i7SJilBKJGcw0SCeDXdEEg47sSH2sVuaBdKZvAZ3WA6njVK4Nwd0iEP2m063ORQ2EYyyTBHMavlcUXS03lQHOgqK3zf6/LoeNni34u9fGlpb0NriwXQLdBpagO2fdZMIoEclhqPfiKOY0LnHqnARwRgbyPM51FoXh53c63fxXkhJqjppxuRhi/Wlc5lV+SN63wqgrMqeTv/RZysGKV4RgeFJK54gCk/GwP65EIB9NAXARqjcKNnkmvag73BSBc9PSZ7ChDZL7ji9urftXT1ZRSpaYwW673FxuEY1aELbM24DDIRjR7sCVTBqs1YiAFqtttcFgCM0ZadxvG6xe4+++TwavfVtw7qtgPaoNrdeiebsb57QWeCJmtVsrFqtpcZyWmZCpE0mtFSMotjIe5PMPt3d4fHTI7WhGSAQmLHbBee7+6CzxAaCjsxe06ARS3RKvCn0rFhlqPfD7YrZs1I9+aEIzq0ZK9eBbYzoie6aFJZmLoh13fwJ/5nj2N7sZaF/+xjD9HvSXiQQcD79vBIUHZqufd6qxVK9DQ2Qdd28XjPMSx06eAn3d5rFCQkth1fy6/Ob3nQiwvWW/MGBCI7X3NARQ+9xqSjViM9alkzdxeZuT9vhmwgYvfwGaTazr8D/hGQb+vgT3FqgEh7fhNPYdtSEWkbMPtTbXAnXAbtpVsn8WnfBuvhYuI9uzRnMZ6LDkNW0Y+tco8+HO3i73s1Zfg2rzZT1cn0xbvgd0hoZ3WWd8+VjT+XXn0clFEUzddmk29qPtCeEug4QbVFcvy+7v+3K4gq6Bbm9vY8qUBSVS5R6PKuqI8q5HAzdgQr/PnCjAITzm5O2STvpRey5JeBtRzdobEEJlA9/0f2EHdbjpSSHF4+rLbvXTXdzC5OTFpAakRypWkPmU9+hbsyKfaumHzifz6HXC+BBHvW5mzwubGnfEoWJi/5eLIDJ687rRAyyHWktdq8q028UazjGtGVETEfZq1Umz3qHAI4glBIeiJLGpMJi1nnmx9crYrox+ki79qjLHa6TOSfZHuaUWWKe2z9OmqJAE9vZmyJx2wRx7sfy6n7eV0z/A9z3qdMvCp00FskJMRqBlGoJo1vqJQ9AYf3N6+t7LKcFa0oAYhDS6Mz263J3xva8onkVO7cb77ecz3h6fIykxvHhE+TtPU7lbfgedzPr66VjRPshKQXoJWTOSBCf9Bqwopx/M4i5vHuN8cenaMVA8y2gptPaUB4dPL3fdBxpKLxBOsdXAPRfP0AAPKd3H7/9gfLLD/a3+1YYMOy/fYjxKqLGBw8+yNd6nYRx1FY4NwyeN1iV9c7FBKO97Z+/7+7RfLeUnyc6ihRWI2PuY9q7qoDrAzoUfbtAoJaYDMXptJiNt1rPd7YR2xS49+RurRV1sSTbUqxtGIoXJJE/uL1pIX64bJ+FWDxG/ufV5b13bL1j3TbzyW4bBqzv94BET3HyoCn+XSaEJpNnnNDupr6LWt/yWiy+cOkdS++4H4o+3mPbzJ+yPj9bAsDagW3gow48ui9m6x1r3ywWorYvOm1GH85Qi/2o6+mm+NgL7Lorp0UVIBBHxOdOZI9uwF9oQ1Fm2DoLMAqAFepJpYTJBwtRDMgdRTqVBECz6jZ5E+VFTlwF9UkyFZkJk2EICZJcdPlDqH3K+fBb+mWhf9pmmEUNWVecq23X2qdMybIvg6Pm6cKuRiLx1+PBJ5Q4de+5nbco7hlLCZOY73R9fr6/HZEjkfb7y1emMVLWAzu78q98/IUD6Lojzm+/2jKl+p+8nscjFPeQECqfOyikvvWJ/y5S26tp6cOs6AEhBG5dE5VCrqxaBhENETcW3Jk+/1VIqprgRgtbApkxTWU/gn3OQEuRgJyNqiCRgG+/qnD3w92AkeGFrhCxSq4i3dHVusFoOxecAWwFAurEFFuN6naN7DPlbIUQyipXnr/ba7M7wrESs/PSifvvNM1tKOhu2Ks6fN3Mko8+YMjGlVf2DrgISJXn8PvRKR/Xye56kZnZTAU+Gz1UpELoSQ5+CSDFgvhijLjeVegqUzEXMShFd3hLF0izQDeLiQkFZBCZpu5ZlVE1GnJ4YqskpTGhMLhLdWNPHLYW7nA0mi0BRW3v0Wq1aqciWJYFlITmWDXFpg9TahiEWdfVYPGL4FQr1ucVY+tYlsUzCTds6wVrFWzdoHgAQGpB1YLSKpa2AM3Wh4H2zDMVSIGFtKfF/3OrIRumwrmntL0zjk698IPckM67XuUHGr55fqIRruUYNmdSLbAfxjwERSo6Y9nUkZKhDV/JXWDV02btXCYC+Xz1fhiI/aEH7cN+lbmPXuDg5FsqiIB5Eetd373Vhf2/BJR3ZMeL7QM+tkCAUlxJF09AmPnw4eghzUtCPQBiDoSQubEmbuge5mm3KG5IBbmoK4jJKcA5orKbCMPZobXyiN6PdGgFnmbONJ5yprNCshg0ozDACHjwo6Sg3t4pyyC6HRteEA+fP6hE8r34cdAavxQLMpd5Vk5qyNUfwRd5Ph2xAWVvlw2wGjNlUvN5ur9VdcNxaQuW5sGZ2nB3d4fz3V1AaI/esa3iwZ5Uybh7Xzq0jeZQimUPSzYqB4bXXBmUd7EEHw/it2pBbKuGtiCdJaANTwgiv6W1ZhofA0M6gKGbJyyW2EsiE+qPBjB00q4keqBsKpjrwDkuxZ2HSd8oXnWPYp3+RIGiFa05TxSnxTnkHT0Q1rFIsSQoT8QLyqGz9nAhK9kVBTUyuelY5Mz4ffg54stwovAdaQjGHNDQlLk/AKM97f5zuNyGGPx6nYFZJc/lXlIPCpfiuhSAPhA9sdGh2QErrCSjw69gFDikuL+fCICKHshFm8nAbfUAeo/gE/cS5Zu6oywChdkxKPzM4NCLKwjSMflQsCvTDYoHOU+nxWg5BdB7H9jWFSqw9kZS0HRgDDNbe++OlCKAz+90MliyltRqlTJBAvYuY9tQWjLZpABjw8AIxCPeK9AcfNmnDDRaM/m9TeM5110AACAASURBVJ4ldPDAK6Y5b14VwDwNMad/BGjh+zcxTy3FAv50Yvo6cBw7iShA9CoNeeH8uYhXNAXJ2970yuy62L6grlaLoDhqUP4H55/qSQK9D4zN1oLrL+64KY0uPtdhS0WBJoPf6cgTjYa3hOrbTN7QbgH0bV0DOUJhLQLGmBUdxZMvlqW5g2+iCLWlOYJWAdVPKW47idlL1IuX8x3WbcXbH3/E77/+anuluI5O+YqcAjnXPCMYsAWAqmn2UjypRG6H6yZ9IrUmCCq4kvm1lEjOSqdNAj1iEf8vO25rcfMwOkfofHsbWUMsx9+7O06BPe2fycN3p4cNyZ8aNH5rTODz6PH6linOttkLd7751fHVTPmJsQpgSXVKVyJVl6SjZVnEa+Y29Hvrjpnk6ZqvkJJOX7C3Je7zgr7OOT68Nq/P7VRCr4cjuYScgevKtmHsWsHN5x0/kr1++VUHCfKLTgXS69cRRnZM722pl+/+Zw7qzjL/CGWBbbJCbxYmdE4bxsbqbycVperkhy7fSrWFGV4dzQAu9SFVRfWFs1YVLlddJ4tllxn01R1NYs5/CLIpy/b2VKK9G/bvbm54tsxkjnzkP/Vw3Uv3i+eKzy9tJojPt07IY77n4aaRkJp0J8CS3KQzwGy6NZJtnXUD6uy8sZT5rKlzKv8AxFoMBsAPkybJP3mtnyu0WwCgVmehTJQY0D7pu/s4hTbWrXURRPlxKSWSxm3s4knA1vKKkOdXMvMFvpyr4uephz3nfpbJmiqA7Qsbb590ENzxYLOH/rzThSWGXGqBYMHTe0O1aW+s6nx59yZau+ymygdKrYQogAKgLlY8IGJ2nrj9wOPu/g6Xp2dAgfruzbTRdrJgygsLFM4ENtrf9IEW8hBMuYzD75HeJYLy7rXpSb9/imuKGpT7TZHnvynE+59/OyfM0iFfzs/rTwKRt+i//gEAKD+99amYvCjQgQ5rDQDbDXJ+vPHZ1bj8vRn3YIM/0maHYrlhg8TcytuwXQHKd/Pfm100ULTgmHLiQC8hWzGIFmtPbrUAP70D3n9ELwWn2lBrA1oFmtlWUqsj6CX/j7rvfghGseI8k9Ml2igV+tfSe1C3H75PLDHZ5ryr2XlWiW4DD59YMKs5M5rmj4fCkjpeKXAaNq9dFZsqnhkE7wNrf4/af0EtG/DHAyDVUEd9PCwY3CHvkkcGbHysBth6lIMIOvRrJHSLOVKmbwoyCkx6n5AXLEZwnUMFFRtUqzXFc/t4YECUOpSg+l4qgMsh9dSllMCYHrXzbShibBMILqRoso/mvM/R8/v9Pt+r3JTbeU74TQkdN3/6UvTyT+lLN/T/2/dmu979SI58+qt0wRdU5ZfHeGNQX6lz/m89/mMB9BfMhq8+FOaA6CN/cmsxJH0P3KkFsjsEj7Om8JsPquh3AJ78Dm80bbzkTBQYfDvUGOGCmTH20nFrbj5Lr7r7Me2Nm+dJ0tPlsBh75Zhw1nEQtwaYEMl+nfFTZwwUFl71TfhCCxKaE3ZZFlwum1ddVK9a8woFr4g1x5vfVa3qKPqc08iGYjlZFVOrDbVU76dp4l3HwLptOyff8SCzJ6OlmJwCxsXlAAx+7wTVB8AdtyaUtshG630GAubdXNNOPHZXcRZa3jVrnXLqoEXl5py8yW7RZyA3r+MY6vCWZhT0bg7k5n1JxPtZMaIVgau5woArqUhKNxTRMy4CSFK8NywhNV3IqvUz78IqVIopJ7NsNCSCLrLa/X1cehFIMQVmPFuG8Wiwam9PqhiFc8u+rOpBeDeES4bnFac3YHSrHnp4fsboVilvgasy6c8hccco6H3D6MMNC8W6btChWE7NoKvVAi1wGCkUKo0LRBTPl46uG4rMTOl1GzjfnXF5fAagWJ8vOJ9PWLcV8uxZtn2DDhh06QJILViWBq3Atq3TsURFbnTLjIQ5cjaPNFugyNdZ5trD1aP1spqyFcrfcQ8hAj45o323hvZH0D8rOq8PDeMlO94YANkZ8jSkm0P8O1+gY4ROyVYbZmBu7iNSMPuolWWBFEEV632sdUA2sWq11CcUMXIabtwfKXia3if/xr0nmMaR9ZsGZp9x8eBjDVhhccOCkEtwfotu6BBaBMXjeMO1X/b5Y5sDSQGBmNMYraZRswpQDuuXfvE9vWNZHLtzDCWEcTjAkoBypXyMDhEziJlVXqsbMFJ3ty9FfJ8BfbMxeo2gjYU9NQuiOjacnZEkMYPWMgpEXpYPN49kA9n8uCOjFMipuayYRpLbDKC3YwbQJ63EHgp+7vM0M7d8Vez8YyX6cX0m/XhgJgXQl6Xh1Kz/9LJYMHCDZeYTiSQOGq1hiNhcFx9alzjNeBy8ANVe2JOTmgWha4NIteCUWMVD3wAzOjWg3y1F11wYxr7VRZzx4AHxXlsDijpRSwpZPWW3r00pTg+EG5cwHiPBJOSQO3A40+zLQPmozH62+9TaANmAPpOLNGTzlLz8TVWhzO7hsxWpj/fkcUzIgqoX4bHq/hZHkYhTZF1hvzUlVVUh3ptqYATT3XFoMDYleBSD5aFRZDLxF5FhDgkUcchP68NHCDG27hneWkT9YtO3hv/jwLnR3FkxrOLF4Oj8HjowxHUah2UtYskcjq/reuncHxFYScEVjZ7i2Mk3VUGp8LW2BLulNbRlib2lvaOUDniVM6ughyMdjKHuhPE5mswvBY8BHcMTFAS9rzGG1hqGKtrScLk8gZSgdPym95uxsg5FcX44CUHV1wfT+UCo0jGMNrPm6lBGCN3UiayPda474Po5gNGmPOY1ydgiv+NeiT7Dw/h3KdZega0A1B0pEEEthlpQqq3z6e6MsW22x3eEHlIWEIdA9DZOY+vRx1haQd82l1dG1V2sD2IkiHhlsVUzWeXb1ju2y4q+WRsdQ0AQoJss27bN0g8cSaNv3WEpFdBq9NEaltMZy6lgac1RQlpAxtvA1ZISZMLUHg/SEn1WbL0kcL6hgvVy2etkCkBcP0r34jLpGOiQcP0cEw+Dx5BfhfNIvLJl6m9M2qMza+sdA4qtW+VQK6Znbdtet/ofO66m8Jb++VUX7g+vnpOWE/z3gYpg76qOYGV8xZJT+v4ZLsLCgae0w1zPOZz7+REfzr86Ua7vcWzp85nrrxym+aDeQPp1m7o44giThWeQq0T7D2ZXEZ3k+IiwRT73apivxtNuTZcgVVmmNdvdiB/OTQQFAnrWNfIZL6WcAfUM3e05vTWY+NvmdKgeasU/9xbXH5P9CxW1w4uo71tWa837TNkI2Vd1Hd8rz/FxGMenXh3Znkj6MGVw8B5vKUF4YPG+uKb3eKV0XI9wYagMR5PjfahLApBhiCNpTtSTgGdWraDWibTHRHdROuVl6nFAXEfdKqqxfbHVURWqVJfF42o/35rP0NlUvR3LZ8++nt7PHCEbRKL9oaHxzETt0BEPfCFs1Vqdvg8BjTFQFkMj0TEwislcnzwvdNRYr4xUE/qzz+P57s7lNcWPeiUw54C6/VR2AjUKiFye8APItC+2bR9Y5rtZ/+UyZ9j58CjVYLzH6u9m60z9WV2v0dH3hSaadKsbfJmV95MkJ8Mw3uIJiX7PpVmxwNg2oHS0nuwMzKrZgsXuMBRSyfJ9n/l8cP2sKKSYLOdoPekk9v+wIPjp3RsoFJf3H3H341us6xqqQdeOWttOj1hOdfpgyPOdJmprkaTp3B3rs3nMa05+xkwcMASYeMAMEAb65zC7nGgUAyZz/Mg4KHlVaAH236xHev3xdVAZ3cLs+11woxqdy6bAnUrc96VgOj+9IzBCrLPThf8jt1pOP9sk//IOANDaCYCGTrr+nwsUn3bPiHHKPlj+Sj1O8ZWHc/74W2BtSgQITAYAqMows13TfgIUHwF5N+3NoebvBybvVEVbaiSuFxH05+c5S2p93XUolragSkP/53vUUnBXK9QD5sWL6Yq3dqpEmVLFXR8oCjzVEe2RwNYyTv9sN1eqvcEYIxDP+oAldSuL5Wzc1H8HrAodKjP4HgJ/8qsIYsO1CScaheKTKJrzxbsuKGVYQZgCF+1ov29Y/v4jRlessqG+vcf4/QFj6zj1jk9R4Ef03ZH4z1xCcZ5lv0+VKlhhKK+Tz83eOL66fgF9bhQYgQ7HW1HOON8fnqAlpaIMYIj5OYv7qItYQoIFz4GqgkEoclVPdpssn7IhEswQomRPvSyYONB2JKATeQ+J5wEoPn+HgvMdDyINz28mj4q73rDlvua4eVV6V55xdA2q65+1NPMh+5qWw8hy5ftng+nUcW8PJ4lg0tttxKO/6vGXrECnEve5df3S8fidTPQG4I0bIJ+KBdF5vPSE7bs8+euOa9Xsz56UTte5qUIMqIZSQ0NsuKNbFZEBBXeEBVTh0rBti2VSsUcgg8xk5piwTkMHpANS2e9c3BlfDFZzaREMKK5Es9/HNPp4b033cOeZw5gG3G5oL2SIVlk3ujkaNx/31ju2Yf8GIdM8Iw2H+bqae/xJWr66Rq6+noJQdl9YtWCCMAEA71MlKA4BPZ1wO+UyvKX7AcwqC7+CRrA78MJ2nR6gpFbtDZYjOdKBenxlBdBh0M94NjXYdA/F5XlDcVqp1b/zavNpLLogB+GV1eYHMyhp/cOHzxf9OerGvCQatP472iraGNi0o0QP57kvtHfjAUO96ugENJ9zvRgdbZtBe8J77Y5hfysgVbA+r3jYBvTelVOHBrXK+jph4ouZAZwT9kxSVRj8qNGxVHELK0He4jqItvuZfj0aH7GWt3hL8Inbh8RphyoHd/Db/rR9vJxPILSjCLBdLmFsQ4ClLkihnnCUx/53rYt7IZ6N6fAVEaAaTOyQLQwzo5KRJoF0T29Vfh+98RvmWPl3QI2niusEC6o+NqFVJkx88Mz/XC6mrq4wcA07j++WuQL34UuiIJ5349tjZjS9+AJ4Jq9dO2Ggp6OUF4n3XjJoWs969wzVWuBB1m6OnVqjktscWMlspQIvnjVczRlrTgI6oXdTfnjHbzwmaQbNWRWCoMOCwKLqfEdibDPpw5T4wsr0g+PmxcN5lNEu0wfS9Vxvr8gnXHmWu6x0bK1FH2H1vpDHZ5vNp5G9q3z3ROcA3Gk0QvYJbC9UtsiozROYEI4pDKCLV4eyN1c3PiWx/+d626NptIrDKroRRd4igAxDEBHOpTsDzSnvVeTpHcLYcstIRkpky/SKZC/6npMi3uLFjcjhvMHln/o80HlO+WIZ1Xlf3chK1skLmNwU1caxFi7HQ+bOazV9bcNJZhbpMVUvH4/sKJ8vP0dKI4ytLGbmt9G2Va87uoRZ02DAcbj+1Lv1cGOrFdMZczBNJ1KOZ9CP0SOQzvvlliozHe9laRMORDoaKV84796eAB6cNZ5SZ6VwNV1zaQu66y2jNmxl9tQmnKxMQtstEUIH4tqRDytaW1KSVKryTmtAxwhlWm3FEr3iHTUJ4oExBJDhfqIRVT/moObaTH5qs0kHSPEWMT5OEqHvu9L2+jUJlImXPtu7lngK2J5URJWX9TivMPh0269VBHBnVmuLo02ZXJbFvMHb03PYCqqCUbqNbcDh9YdXjG/YHJHH9i0CKaOMga1vqKVCBlCKJ905GlF3BKB1XbFuK/rFLLphfV4A9eon5wE2n2YjDO0QKE6L8cHWGs6nBcu5oXn7oFJKRIgEtudHJ4+futPzw4O1/FlOQct396+gQ/H0+Amuopj8W/SKp3/pCOhnl12RhBub6qj/J50tU3XQCXUX58+QHR1Hgp3mBL5/3/E9nhmcXBHON/Uejlm/nBx/rqcl8/aQETvbc6d63dLDgrljXvzy2V97vHzd8RsP+BBK5Mhxgx/4tVx/GF3WUhwlxxCYaq0QTyIptTmyRLWAO2CVZBFwR9Dc50Z7PWIfGoeUPrjaK6FPye5iBlLj/ZFXFFM+p3vMdTqcn6csTRe/u0KnORxfs85Ty7++bldBbb8cLlaXEd9Wgf4txy5wmT7j5/F1oZO+RLDVgixlNwnKPz1aGGrcoP9DgWgyx0S+GcC3RMURbYKkeChIxFBZJC2VQ82GwpVfgifF0jsfdb0ikkryXNyaoNDrpm46106uz3vhPhHYy5/J5O2EPi+QmfTrNlTYV9Ug3SkTLJl0+hp2w04Bdx0d6APwnr2WCD5w2Fo+t0wYsk/v7u9sXPTP0Y5SQwoYLqf49EA8ScFSiZJh50Cuv5IH5DTqjGoQc+1zNdI+sO8Sf0trw89sifWbN0qgWNyUGnZYAu/A2CrQFWUR6EqGvO54g5yQkiIkdEfqfWyhFdWhtVgBkirG0xPk/t6LRii3mBRl93/6/QPa63sASnAhIPQ/O1gEYfx/zlqpJWQCgAjI8prof5zkiWCiEfK84sG1/bt5OwIp6OhzPg7zGWucPusCVP+j/CAY75lMbud5zf/VulD/yZ0d7OdtIrglN3LwPKf55Gu4/7MtMH4dUHzcPYnjy4H+q2en40ms6PAmD0nvIjtKn5XpnEdnuag/A1Lehb+NvtHgiTofZvZuRfZ32fvZeYoPzu9/CNsMpVgA/e8/AR8e3c9Ro2igeCHKbLvoAXHuKy+CYCur2gtaNV9DVUsOUq/63rz3uCGJch0MhS+C575HRqxPprJbM2p2C+OMnMMPImgAzj4uGdY3vI+BbZh90ceG7f+8R/mvM7BVRzVlDIJB8zHh0THlLfmes3c3UcVcmSqG4iojeIIChtTBAju4ve1ty2qt1vY3ZIrzFiGlTfnC1oRFxFqqJF6iIigaUQnTP1ybDnkaa2mtQkxH8UeHUjbPkd3079fjpX3Jucp65ou61pEJgPbQtVw48oov6W//8qFzgUW9Mj7ruiHL5nxc+X/+/yOOf3sA/XsRiDlpvh1z9WvgSb7lWOE9KgC8U+CjCO5gKjlgCsBDqowgjPvX5mF8cbPePOZWdD0FUXDoHGS6s3xgXgVUhY5ePteY2+qV4UupKBCwdzKF414jV7Bv2eisjl2gvYPBbogFsk6nxaA4R8c2Nus1HP26KEl9tM5YVeDOLzeca8FSLSiwLCeDPyw1FHlWwTMLpkfVkk4j0Bk3nWgimP2NRAwSGV7FNBRdH7H1Dav3Ptm2DX3t1ou308FrFXWDMI467YpcvZ9tn6iIEvj4DgTA0jN+Rmkw1DUtLz/z6jm7tTnkOF8K67coMIFjUObF7RBmCw6fi+rkkSBMyFCTUmiOwUlT7NcMJIf0Cwdl6qzdzS+chE0ShpH4hgsg52jFwOeLG8GrbBCvNjfDz37WInPukrYclcuujHdVbN3h/xVAKe4jMqOhRmayoqFi04GTZzvXqhjVAtQQteCHC/iiQDs13N2d0U4nnO7O6L3j8fSEh6cnPD5ZhVmtAgaIAfGKnYJNOkopWNfnqb7G9Hj/9lpB6Bj17Eir3PX1Gt4LvQy3L021Vi1MVw4jC9CY/+fLBelxV8dRCdmtf1JkCIvKDPJMEREPimBMaNUBNct3pVPHkLwdCt2rVUqR6NsGAHVZQrESyMyCx3TSFMU1zE0Vrz603u6jJ+QJ37NmAxQIETp2s3F7D+RKdVWrUpvIGh5ySYEpvp+uFxuz96fk+cwstqx+Y5YZGryUDGme5EsEUK5XVfkfmedrZIYmpdDvb5Ub/jz/fg/n5owrWYsi00iyKstqKrMaBY9uvG1040tjaPQ+Vlim8BCjBymCulglXwSrBiGKGZRz3h90NDnPtx4CeM4EzQiYoa7AAKF2MeH8aKGoGScM8kOm4mr3nRMerJ4LURj8lWnQyF6vEJCOJo0UYduK2UKl+r9SKqSMoLmsOGvm40mXiCkNMiAtzEz06v3Xl8WMKmHvMUH6CaMb1Ug+C4vUboRsYwfpFISTVEGF35EaZGYSExJaPEDFubF7zNkFKN+EAjM+j5CsQzLacDX2nvUPFPOhqmJ0SxpRf769Cp0GvgW5N0kXQKpC30+3T7k9e247zECUpEpmRZql0KmEjld+HXL0+nhpNwzVfaUkRSj38ODLOY1LolXXMYYnzHRlIoTd03qPxoQn/RTwCDrYLqcPNgmYepzq1KGoP6kTKdcBmuglftdwxoZjMFcxsWKsFO+5PRMaanV9UfZ05C+f9KLh9AfollbJ9QoBq8IB0RrrGFVB5AC6f0opxvfZJ13ptfQ9ZfMyJv92XjP6wFBCakvA8jFJQZzPGG8xJAKOpW/rgW647x3hByZ3+mbB5bosaU4Rzkw63PtlBYpgWU42ny4XizSPfUgE2GptEFiiQC1MprJxNu+9uj0+Ogw5HJHAWt0YOtQ2296IAN32ZJeO2eNU0YsnedQBA6Q0LXN0C7D3bcPom1c7GR2XQDCY68ZkH6LbmEzTuWfcqTsrtDVgZKWYyzQHN2ZAaa9hgBSSqrTK5Fq7c9TTuG0M9mEF0IvppkyoGa5XwfvAG23e4AxW5kmKjn3DKq/V7cu7tkDE6uCGAl0F25jtQlq1qpW+brEvP3t84eurQ65++YLUp+719Y/gvAWqggC927zUWiLGTCc/oNDNMVVK8fm1z0MP/MwAnPN/cUwSv3xm0pJciZc+3vrWo0KG45pBxZe5Rk8mbxQFvP1CLZZoZ0F0D6qXaogMlXzX9JWMEJPfMtvMJsI1xSb9mpCdU28Hpi6+e//8yrRJhNRJvTZxwoMuadvLnmtvT351UKoPh43L5FLvCqi1AcOuC4LEv8l5PnN41EdU5jZVgW5+L28rcyvh/0tbIJPO114TdBlzGh8EDzM+GMIr0OIgJX4vraZL97pc6HFBb4CcWrTgAN9Xkdr5qAfixFq7OA0FPLgq1Mk5+Gsx+bfzjTBwm305rgAa+VqSZx3eA/0L8xa36CN0h7n/kxyg6nLjRkkVe0Hxm4EfFi1UmD0Ztoz/U0l7UOE+vsSvDnYmAHQpqM31ZQ/+3EraUAiWVqfO5ghsECbXIXSd8JvdQJnM9v/Or4BJfyN8hD6XlJ/eBnLebCIO7IIzPv1tad5izypSo2eu6ydmZ+ruPeO9k1zla4hfU7xVX94ipRQstWDz/uOtVpx/vDckz22gvBE8PT7j6XFFRYOcDOJatce7ZR8uC2Ysd50+GJNDRQrG04NLJbOxQldJ03B69xqqamg6reLTpwezx/wpdWneHkxjzcRbBQ1Va/MSrYoUdQClVmyX1fajRdgw1h4ytNSKbd2mDUD/btCz0ybpozApA6g/vAHef7QWAEF36Z//ZwNw/8sPePrHe2NNurv11TZ68sS3u3SPWGoAJ//z+SCLY/8H2zC+U9Qk1/lvPwIALv/4He3nd1EYRt2sb9sUrz8J8NsbMIiezfQCC/jf64yJKCxY/nTgGU9i1ekvHZRl7jJM76I4/fwjVDu2X//Y8RvSzvjnHyh//8H2tHBsgrY0KAb62iEF2NZhQdZSbU/9+hEiFUMErT6g/NdPqKXg/r//bmjtpeH8328gfzxAlukPrUSfE8HpR0H/TTFEsY3rdVBVaK0ePB+onpE6xsBlXXFZN1zWDSvRqLoFta1wUGavaOol2NPJlRpNXVCc33J+FaBf9iIDr3SgvQXOj4rSB2QMXH79gPq3htI7Lv/o0KrYtOOB+pbPrwh95+I5uklxC7kkGFpQiqKimK+vDEdnsz3LaMCRLKoIWqtotWGp1XQ7EWwCR+SayH3RFkvrvJc0iPQouOS2qZyioagg0oF4YB1B38Vb4wzKBLnyqDnP8/EnOwrk/TsqkPT7pPWQH1f+Ugn1JScYaro+fMV/4pDDTz18M0f/OU1CcLecMHTgaX2GKnBqDVBgHdtOFvN9iQL3Jf0kniD7X2ay1f4Oqn/tmvS/ZAU64Fl5B8fAf+J4BnAB8BbXJHvLoPiPH1kXxJc3wvEIwYJpYJE1xKaAB62pzLhyan0VO2Q0FClo7lQ7nTdsY8PaG3oxKJVkGfi450YcvbtAsM+q3+u0LNaX0qEQCaXIIFcOeBmkEgC14Cod5qWag786LGsTC8IMAXRsnnnWLXi+Wp/DdV2xrezJ6U66YfDR7D+icnRj+Xy+QCBfzPg53uqFhYwV0b0dcH0iGbC4U3MaQQxiIhlLJryo5VEwwI0s9icDygtZ1QUWiOypmUGu0s6ODHWHjCSmy8MC3hdTpgBULIDO7HLeh7DVEbCBePWAjXMETQ+oVy4qNOB5OA80aALiOFWhQwVyYpCqWmXoBmxjQGDoBDouQG2oArx+/Qpv3rzB/etXeP32DR6fnvHw8IjlwweoAOtqAcLaBHD4W/X56X3DKmYcVq+OrmIVnWyPUEvZKYY6umVKGrY03E40xciRFcoQqzjaEYtnyafdrphZ6syuBIDT6eRIDpL6CnKBD+p1MkJ2NBK2t9z8Qg6cizB6EKcHwiyziqtWjD57ZU3aVtSl7Zi01GpwSSkjXl1ZK4U9s2ZmbF83SxBSpp3MAN6tg4Z07CMflPU6HYm27GxWVUQmvKQ7OU+hQWBzMRW44ljWsfddOaYLhJn6sdVUd2Pjr7x2f+T3M/4QfWhLjarcyIj2oOBIf4dyK4B6sg4D0YVVb2pz0M6L9Q/mvG/dq09M+R4enEKx5Ji2WJ9cUsvwrPrBhrKqGNqhOqutv+SEfukQkDVO+oxq4W58k8E1C3Ibr+R2mEEn/o1wUBzln6RRqn9PA12i3CYPzvkdeVR2VPr3EsH03DP4hUOxdwDl9U1agX1tjp+yFLRWrfq8EZqYj8/BoaP6PzWLm3MuTDzw+TyeUzwo6PvDkG8sUHUrBhTPpvNYR7wRZVyu0lIPFFugSjCKmO4CZrBPh5zKgLqhSPqwqhEa1wMzHzTtQz3okDrnJf+MZAdj6McLMCuUPYFEwqX3RV0jO9kEgPaOVViB4Qa58yYhvwJif9vSlpCfczwIZ5dl0FegDNvTNH41oYUgtm706CZMvslx7gcNxJjg4zwvwwTzBQXwputBR4pYGkuac/5UGMzxQI94olWudKEjZEBQgu/5Z8osfuxoIQ7K1NED7pV7bdR8nv0o+qwHfwAAIABJREFUItGOhz1b6SDO+0oSwzH9nMF6D/y6LjQz7JlwYVUXgQYQMvFIJOnXxEKCQqOy3xOsGDwUJrjp5J9C+W3tTFqprpNXD6w1FKhVOXiLFQDeAsod8rWiXy7Qrp4sWVw/38zR1TdbHzGdtQ+zO6QbQ+2O2jFqAbQ5G7WMfetzv8X9+tZDnxhS9jovt2PQx3TCjTFCLsUcu4rVR4dIwelUDnrTXJ3pzEFsztPdne8r2xuPDw/ILahucVPqsapWxadq67Ox7ZUnhB4rTikxyUu+zda1MQlsfQnlziSf/IS0w31vfh+r+mul/fc6j98PWFCUaBcmH5j0Kzs5Y/OE4K9TYfqGgflBSfPNF8bF8uKlma9L3vzkZ+vFZEDzSuBQ/pnc50GbSphdk+2RIEq9RzyYWvzckHmkEnJvhD2KcJKGMjXPEQkHHud30lx+7v5lp31qZ1J/07w/DtMlyvvJzDXhOLH3DsRXB/nPYLLugujX133N8eK5Lzh4TSZqrOl3PWL+sm6XZRiDud5qzWVDYeJnQiEDsLsukkGBuZeKoKK6eB2ur5TJr10R0NFTpbXf168xRz2d8XndqUR4JSwAiaIQ+y4QqeyCBBWL3c+XDi2AjBGigQmUu3M+N92k6+NJMQD7hWiRgESl/EwgSTuA+28Mm0dPeBD/jvIKIt7GxvS84sDrG/qOrjg7hfzAP9yT39xEZvshoHVDUVSzx3dJZklXnn3a7XYF3o5Kp06Zpyh0Yde3joHR4FGUzon1UONMqTNXmvwc47y1wqDLh3piMJxflBKJZ9YCoKAG/7IE3tYq7u7vUsKjPXmoVbFG1DLGK9FKale8IIr66h7bwyPG4xPK61c7Xsd3UTVfBttn7vpMA66vT14eCIgxjmv5HkU9up81S8rXSNJkSx8pJQLopRRHMSM5TCnIcctbAT7snxnvk9bn4z/f2/wmG6H+9MbO+30GqUta0Kn77dd5/jy8K4CzTvlv+lCSr2Ng/fUPtJ/fZaEbd+m/foDgNQy2ffKEW6WGx/QzVpt/y8F9miHwp2Vp821jSheA+8robf31A9ovAtW3KI6mB0UUnolKJCMWEYzfPqCViuUXQX9vbRnPzXz/y9Kw1IZaP+LUFKf/92/AH5+AZoiclnBrfrztVwt461CsrK72+Zx22EDpHa1W9GptZvtQrJcV6/MFz88rnp9XXNaOlX5/Rxyy9YsX9vYUew6feac/PHSJTINGW4qulpTafxvYTgrBwNIHarUKdHm3YXyqGNKmH12mD7GybR0XLAqQELZQkYpWgS4CoEMroB7CjkT8A+0ELZRiCIetWVAWcy6ZyC5ub5o/tRgg4BCDaR8d2yhQr67HGNgcH2DuAfd9qiKaaqjYWmLOHW1888FQvnLejUKjxSR5ym51br3l/vPduA7n5wKU3VUHufG5J33t8S3XGz3ZGnCemMxQtaILbVK/t34/m+v/tuPfFkD/3ir3l6pa53FNqPcQPNz47tuOmVkIWBD9WYA3sARhbtjHw14hwX7709L16bNbd/rc7YtX0B5vnKsU7UdiRMfrS5kQj8nZbIqZQV4WYdWFRjaR9QUcWMuWDBJ3RtbqcCzGCgTwICagDAphQmzqGBgoOAeUZg0Y2prhotK8DfXeJJ7ZROY2oChuaJPBmSMY09jSBV0LxniwDFPvpbh6Jtq6bgHRaM5wPiP1pkyKVJo6H6fGePXWSUdS3RHE3ghA3EMYW0iXzPm1vyQEaKYbVuuZouMKgaobNK68pjEMN0SYKSl+7+k0n6JNh0IKMPBsz79y7E/la6d8gwac3cegPSUEJQB0eM9Qx44mLfBUGjelEgLMPiuEsKWx5UKDWXPwZ5szXaLyiQa/GQpWhQ5o9DDVUQDtWLeO5+dnjK2HYXg6nXH/+hXuX91jOZ1wWQfu7xRPz09Y2gLVjvXZMv+EDk7vmagKjK1j8+lbmtG/oGE5LWinhloLNlY9+VqoV7jV1uKeg5XKJDcafDng4U6by+US/ihxA2iXbZ6M63D68bvEsa75ywxqI3+T1995TM64VVay8X5c17pXKWojBBsdAfO5NOSMbjqGQ13noVSp4dwU7jcFlrsFrRev5jOD2fo5ziAa18vWvU760r3TrFavvuHce5XN7IealTMzzmaug60h6MxOQTRWBAIyoegiyWUqt3w2x8v14n7LYx2+X1qt8XkrzRKPwnh2JXKYHDBo7tXmR2YlkinRA1o9cAZX8vla8KrPVqHD1nJZFrvO9+C2rth6R2kFbak43y0opUWf5O7Vh6OXyNpGev/j799yZBbM4D/dZUxGmtXhTHww9X06ovwnF1TseyEt+L7aJTWJcdVZMVsSWIWNpiZ+xSB5vhdJI+J+mDyW677jw0KZYWtsCWIjrrd7pGeUgirsITadYYoJk5bnvxTjzUVnO46idKK7qaNwfubBcMh0BPkeFI7VjceA+0yfX605rx8p0cP3kQXJDZmDuhKdgsyyLqPEOkJmgIRJLKrchwEQY280kORsGgsAZv3mwIcPM9aDe3XylTS/QOoDqAE7Kcoe8iMuYC9y9SSTK5VD0oN1eG8312ncMSqq0KKpNZr/Mlg9guhbbpXAzdv3DLRhyWtBe8oKWDf5dKB7smLvm+3j4ZXE1G64LwRABNHVZWMQmus2iLFptfcgLUcSGPdIkVkV6bzT/AHDst0B9EgEGJGwJUXs875hdEvcNKenjbd42xwGQvehSI35pZkvEPTtEmNXxaSxjjTmEnTPFg5sfmhjNee7Faan4Jz6ZzvIVXU606DHGMBIFe4kbNIdNMZCGo7kVw8g0PmpvoUt4dWc9uI6lQrQnLc51zH9ce0YsvmYB7bR0ZazV4h36wcKBVo12ulGN+yPCfIS0r7LKFVEledwGHeor5WYY7qP7shWmvhjiSBDkQpU44/KRD7Op3JpNSDhSx/pe0oP0jWDAgCw38vBJ5INQJnBShNx/rNeLtCV5zcA27QDkt6mgAXKxsDmhgH5pzPiqasNCT3fJgyhiuyOAzNhJfbqldkMVLBinbNVKxmlOrkF3pLznXnjqbPcOLKcv33G4fSXz5Ibf9z6bA4MmI13r4coRSLnaYwRyYcS/NbmOjvoIsFwKtj7G/O6P6fSXA09/nJef3XeVB7s797NWZzboADQvhnNVLqeSLcSFbxEZIhk53jeda1KtDeKZ1v/WxncM0kZiDdK7xC2zrxe3C4kn5O4Da/l50km7+Zkhsqom8/ktvT8DOfs/ICyWIolGminHu+JNz3N9VcdU+e4MQvz4NSOLxCM63eUO/sqq28cFhBzzs98BW6cbzrnPtHUknVrmb2pw/cjmAHOWK/k0HafFPXs7MyQ4vVtw3mNMgg7ZWDocW6z5HffwzX7vkwJtvxSRANFIeEyHCbopVkVr/7madfnHTjC7nC8hcMJk1+w/ZAC6FtHbc0fM3l1LkYIP2Dw5v2TS7NiGQuwC0C+7+h95/PJbFD3b1wen6Y+gvl5yIox9XLb556s6skOGGo6WJnXcZ6E46MvkTKOyFVEK+N5iX/03iGqhmSHuadrbZbA53K8Lg3YOsZme9oKviyRez8zU5FTpzMgFSfAUY9aQT0teHx4svd0hM3RWaUpaK14pfYAc/GkFiznE2qxQo4xukuS4qgNYmiELPCJ0ndPNpe5Z0opaK9ezTVIOlSpNfTaoYqxddSTVaMOxT5aS3s11s/f3XlvacUC/uI6l/usDLHA7BWxvjZgQgs8AW0bW0K7m/fefv+I+sObue6gLaIQvELVT/vWqpp2oI/bCnSA+sPr4HnbrxMiPSeXniB4hgWlGzQqysM895+3AtYS8zHPvfv5LUopuPzzPZr/Th8QYHJz6ED9+a3P1Tus/3iPAauer5hV5zyKAh8OIvVYfZ6mI41v//vpbz/g8o/3iKQc/7z8NK8VAOVnoMgPLkuN5zoLwfgVKH/7COgPhvY6NIqGaiqMgA4rtKgFp/YDRvuEu7bgfD7j9f0rlFJwPi2o5TWWxfxRy3//gsf3H833VtiWQ1GGoqjZohs8LoBpzyqA2q2t4FZ7FLlsfWBbV1yeL3h6uuB5XR0Nsc+q6dC9jSfO4Pn1gofPNWbu+hwDMbWxNQHW3nH/wyuMT0/YpKNuZrc8/tZxdxrmDrH/mD+lFUi3ZFyTO2y9IT4us+HMf6WAJ7Orzh729iYj0EwBBBIMtzdb8VibwCX5l8x+l2GB7lLFfIfuux2joLeB3gvaUGyjo6glL5Qi2LpARge6u/bd/6jUygRQL7bZt+OcckkonVxmRYwkrNPrxACJT6jnUY5I3DXO3bX6dR4n8zlzNwBM6pL9x1crf0sL2OsJfKHkawftg1uHnceEZYszqCF/8YxhssJf5OZ4OBJjvdd2hhzP2dkp6bwvqJv/24+/bAW64M9VoN9NMwifVzG/7XhKyn+D0lf1XY+vfdfrDfZ113ztiTsVcPegyWxmNc6ETx8Kc2JtNlNFEH1RGTyiQqzDAnuEtqUhS8W29279pl2hZ+Wt3adOh3RS/qLHuhL+yo1VmTRhOqG/QxjV/p1apWNXc9Ct24qL90FcKUC1o3erLMlVSXT6z3u9ML3fZBwfD0Hm1fE03TMqGhBygz1H5eMcEWaOvuY7uPGQPtf5LUS8t++sqqHCXeQM3WsN6XFTjJUwgMXHNn9aMJsB+r0j6bq1w94snX3TkvFfihkPktZGPTGgIFVp2r9Wq0P1TUNAoOboZVZdKYBWjL5Bnp4w+oZtadbyoS04nc44LYsHZ6vBVktDq9a3Z13h8EFupLiQ1O4JKQBaUbB/cqvWuuB0PmM5NfOFyAq+FAMq9JUatL8pklYh6QqDTGPGpo4ViFRG7IigM7IaAnc4WJAGCmYuxPrGeu6WnWshO6M2nyiwYITR78CsOvD7c7hB1uY8npThz03ZznwGoepQqkP0UiWc/KageMDYHXa+LcqyoNQImWLbVuM1Nzgxq2+HV5hRabUApzsbHUbWHNclAju8XSGcIflTov2AcE5JRzjsm5i39J3NS0FrHgTU4xTt12w4Ty8eQBexTOBWDDpdhNXuxXpGjYH1crH0Ft3QvZ8snf1QiUApFIjWPGIoFjpcOT9VnO9OtsdK9RYKgsvlgnVdUU+WAXu6P6FIwXpZ0QewbSvW1Xg2PODD6tV/9RBg9kn2CRM4Te3mmt+nQG58Z58D3OcSxoXNZQUDzBGU8gsHg8320MTXJarKqzsa6ZjeJVXEiyQlnDw2Qz/HXbN6bDwyKmt5hvOOIiUqdvPzlY4WJOdjgpZvtQW9zyIydR6t7kQyB6rCDTqKpTnjYMVW8WeDMJRHXgNT9dm73RJiZmC2SIFW3c0t+UNUyJQpoyK2FUk/R5qx+VEAUuioFYM2jNFwhvGyUpfEaA6+0gGhYD9rD7q503Am5GjI5d2mP4x2fkdD02RKiu+YnsN1ipdLRqqSXjo2BVprFnB2OO3RNAxxylMRwRDLRI9EmHXFtq7ex3qYg02ICsJ5MX2TwcgkgVwGpXVrxQIuOiBeiW6vyuQLc1aFXPAKSKPhAQyvTe5WnTy6BdGrKLYh3v967Dwlu2AfaZx7OGCGmUDKSgxXuVIvOXN4IHpNml5UZwIAi8GYmFOMDsLB4nubLXei2gfURW2uoO5gcpkTIvbwc0eiQboOx8c1LcX6r6sm5AplBD3xEV87l3FMsGWyIsL5Opf18vRgbZRqwegbKRwAJp3F3hb3xtge6TrMQcMEElVodb1QNZIRdCAS5gAEfxFHoCDySxdARvOkATiv8YQbwOnF+rGXCgjq1GOzupRolg5h6t1DFf3xKWybtpygCpzvz+hD8fTwgEhiEQCLAOt+k9P+odwJ/a53FE9QpK4dciF08zEdKF8hTo9JsVMHoatKr87njanuxHTIy3bUS8ctFvqlc77mmq87XG6ll4h9FrIu7SzqztxzZKlJ3833vvW8f2n0nFw5Pgvz86sFmHIV3k9XBbs1ZzDtynvol08VxG07UC8AIjEo/ofYW5ygUorZ3wlFKusD1+/J60mFiT7915L2xfzcbciQiXt+uHtS7Jc0Zf5MfWn/6NUvu3f5bgf9Hapft6F880WFWxrV99GoQWFGBjFtl/R16M9idGG/zwA6USohEqgohK4330Tx5Lv0AhBYdtYwtBql9euaD9+Z+9WT0MN3rpoC2+o28PU+3yWBUz9CXlmJ+906Crzf65emcQ51R5N7Kr9xXaDz7QMR/G5vw0u80ww4aOiEgKB72zciB0y+z/sBqW4VIsByPkegfPQtnkbdTOajXbXyOVQiwWGulR9z64nZ2QzoA8GbqXfSd0d0ntDJ6NucE+KzMN+efEhrQYUlouW51xu/Xy+CJQ4qzP7Lq32Lj23bFi2QVKefIGwc5e/whFKZhVBIa6JTvopMOH+zG+JMZ2n2OxF1aimRGD02+lsRBS07Hum65iRMu46IPuq+t9CF/D9hC9K2LoKxjQhezpkhDVrobHv/EeXd66l2h19KUN69QfnjE9iYilrHXE9bvwFg/PYJ7ee3Ru8/CPC77e8K7BJhzhA8YeCiwKJTPhz34q31J0KLwmCx2XO+/SSzcjRdzbZkVnlvevUAsPwk0N/2a3xTV/+GI6POX6AY//gdFYL281sM/QD9HZCf9s8qPwMi78BWZnDgqPqLoP8KR1p8B+o51HW43yLO//sDSq041YL6xyPqsuB0OuH+fLaq52XBcnI/VCuGylkES6mQRnSoifY0vLBig6L32aLKHq3hj2DC9VBLsr1cVlwuF/M7bSvW3rF1tzmBpNtw0lzuQG6uN3VDf+V5Gfb0IRTRCvTxB2S08FlEfAPwhGRrx2SxkYpaBW0UbBjQTj9M4tixzwuKE7OFVVvMSYHZ415zBfOFSqiphjRYsLSK06mB9oIV3Azo1u2+1YodS6uOSKKOIGb28zqaJdgHciwgTGqGomMW8ZCFsPjORsVZnbssUPe8jd0+uJ3/Ph77VZh3TJ9/hpGL637XWlxKLv2uytMXjszfMX3STJSPogHM+Qh/1bcaXPj3vtq/+/gfD6B/Z1U/DsLdfstx7xvrIxR3PrLHPz2CvcFfnJF8xMAbCFbsA+ghkL9xzPm4MspujUpeOCd/mG7UPdh4EjNqh1eGN3dM9zF2LJ9GVs6WtuceIDq5S31QrELvvWPzOWi1eQDJg+BR/uiQu7AKulprOHdYIWyVPx0Gi+rCwh1cVMSmsoxZzSkDQ6wKkYwNcMVIB6oWd+wVoBeMMrMc1Q2CMbpDuXgV1Wa9tIZ2bMP7eWLSxq0AOgc3Gagevrhmtzf/3Glhmu6TTTFj1AUS/ZFHZACbthLw5qHQJq3VnYellOiNqEBU7NibOVE5XYiqZbKBFcNmIAlOBpk/LU43vE6+VjNHkmPmOwBwxBmjg13w3GlPRSDeT2xmq9OA9SH6uYZ+MI0nSDHlAIKu3XuSDRStFtwRceWiIXrq0ioQACgRqFpaRUFB3waePditEKdtU0mGDnz6+ITLWbFsA+v6hK1veHh8wPPTBZfnDVbpNysy4WuoPsfwKtxSTWFsbcHd+YzaCi5jnX1N+ZJ0YHpjJcmbhDSEgrqcdnSkbrmcT2c8X54RHgyfc7sFNd+57zXdwaXzFelmp20oktnJ6mMbaU+IiFcnSdxsGssWuIWMuDY/i4biTjENeHarpOaGZ7C91oPh7LQXcEtFQgmVaqV9OdBYA37Xrm+1QWHO+ipWUT28rQSDGYBX4kEcJh6ADiuO801o/F5i2yI7y8H11bRf/D0L97rG+JdWsSyn6aAFUwBc0dMpv5gJzsqAAqCWiqUVLK1NR6eYo6dshsxBiN2haX1EILWgYGbvHvvWLc1acyznivPdHSoqltMJEKC0irttw2VdUQpQlxo91FuzZJ2n5yeUsga8fx89qnvUHS7Y9WlPx5cEb9KBSYfhKysSioDxHEl7UGdgAggnnPE00yjMeLPkCqmsJi9khFPpd8WXEALkS6T1Cjei3MAJyHYEOQctFaFZJB6Q5xyIt0twBdudMVO+xfbjCDzoZAgzUprtjQLC9MwACR2kLu+jGiRX7Yzu8su5qaPXsF3Hrne434+BreJBoJkrTQcTZfvc36MPr4S1AIDNK9JY9koW50yh2GSup9EWbtJUH/vkT0IZZnrifmOiSQErdmwK5qtShl2bKbmafKTfeT71OCYyGDRp6n/s6zOlNVDhmeywMQ3Juq3rUwMoxZBrzKFp6zfggcyiWNcVrTX0xau2VTHGZpUm3QNGqlYJ2wd0mK61bmug/1jSosHJqzh8KFdFpnEonsjBnqdUlIXBmAaoVod+H7PHocsLooBIkWjBAIUHgDs2FYyto2+sQN9A6Pfex6yYAi/d68eUHUUcMp1JD+4cQZlzy3EZurEYelMtuDw/z31Kvhr8ZEph6n2yETmHOqC/T1FL0nN+rXzP5LScjpHN5ACrk+OdEikP6xkuIoZ8MwZqa1alirnvunbbR6mym/M8Nqs6L9X63rUi6M73vBgJRdUy51Whzxf0rXuMy3jW8LUNut9vY9Nni1ev2YbB6AXSYPpsq9abUWUHNVzFezJX78fuyQG1CHSdSQCBApDkKBJCl0bClOnjhtgx133yWdo3wXGD5ieF2bqfz3dx/tPTM2Z6RJJHMlt3UF4AVlVm+B4SyU3hSPGnjFogGLuena6s2d+TXAAAF0ccOJ9OpmnWEvKFyRCWWGU37GP/jtUrCh3Z2yrWp2oZ85NX9nOiO+sYx4+/5rr822GHxm9Th5qfsq8895whYlkP09DnQpz7i1GHk3yjUBq+0yHHF5nKQbzWXpfdncOxSYX29QqJICrPJT/HLiI9SplINbTb48Zy/BdX2r4nHatYy4s+0h7iWh8ny5O1S0EknsbrpnXmmAHkWkILnu+TzIMmaF92QEQjUUrnqVN3w7RJdHSvBk0nJemx//zGIfuvMvpNPiXrAsfvxvEzEWs1YH/sn5PJY3/R7b/leizx2+7eM3gOmY5vzlkkhvGeMq+DWNIb+bWGIWh6FNHnVAGlXpCjGM6nQw9R6nkcZkrg1slVeb7oRAGyIc1KeSZRZTqIOaA9AEzb2r/atZPbk/UXj0wB4bfQ/G0+3H5V6srF58T8b60tDpU9A9sS+qLfK15uro+y3zkr3lz2ZJQkAGins+l1tTpqn8xbpmnSwwdMyiONMlk37+MdakLYY3xru2/0B89yEaa/qCq2dQVU0U6neV/flza3LOw5YfQNfTWknOronUrERc7bYf5ZQNCWBQpDWMv53q1WdK/MFniCQYx7eCF5gWwdwIgCouGZxpQ3RHUDWI3t+9wmB2WpKGot0+gDunX0wRZ59ItNm8ZabjgPovAiSUxFClALYrKlWSQLAtj6MP7p+nr4YhXRHmGoepW6hj4x/vgUQU2FoAWSBHC6u8f6+GS+3PefbH0x6YA/WdHK6S8CPP720dZBsaMu7rGa7pHpmpz7pMDp53d4/PUP5037gwH0KiZZxjAY9PGbYuA92i8/OLJWcxRGs9dH74ACT799wCoW4GkQCxBjDwTQMXubP7zAQ44V8jytwIOpUKz+vqofImnp7v6/7H23DfrzOwgRLWgQ+0YTeQvBB8hPiP0aPjXub9eVqhTIz4LyR8Hpbw2v7v6G7bePWJYTltMz2kegLQOn/9rQakEp76C/fUD5RbBUGzETvFUR8O31h9fo//wdfSQfgBd9lFqTn9eKFfo2LGh+MfRZohyazpYFouxnLenyrGA+avD21wGpSPfnPQO4g+L514HzmWO2+EUn3cD3d1FUrWi1o9eKtXfIKFbYhmlTWEu04eZj9eHSx2kInArX50diA2K6WvVt3IrZQqUaZL64nKytoXpR0bbBA/rWK73UElZJ7wOjWeX51gvKtrmc8hlQxabFZHPRSCa32K8NzhC3yLEp86eMNpcP+b4nAlKP43vptYZFPZ5/Zfl8pT8dPw85vi9Dy+ftxPELhx5+cnx8xfn8L92nw5K5iaZnc1AhOC0nfHp++OJYvua4ugdVg/20/GWPv2gF+lEl+tqrvn9V+K2jA3j8F8jvpfe69flt/fkLM/NnidYV4h2zUL15v50jwfieZ29t2ODZmSXwZ0Khz4ZUztmJLFU6+fzZMwBN545MgyY52msp1tODBnq1Xhw0uJGc5106KqoHqqahkiFRDYK0Rz/0PrYpgBOLfJEKDtzyJUf7i8cX7Gc7hUzZTh5KAaA+15JPdiE2DcTjcK9eQZAEEJ0cffdeIW5UAT25HDOCMKyGSxrCxed7bzSGU3FnTMMrkub3ABzS2d9ap3DRwwTToVkgkd3ZVT3DTh2uRyGo4Vw0R7WhHNQMHe9jKMWrX5cFS21GS9vFFJPu2XU+qDEMHh6qeF5XLGuNbMbHxwc8Pj2i93VmbHqA1noEeZA5KWYG87WgLov1f14a1stIkDNOBTNKBxFm6JsRQudVkaASaCQqiTsMbjTf81uePei+nE57gnZlJP15RVviY0R69u7+XENwna/hHPMNr/P9jvfTOHc3KGcHAjrJyZScD3hRi2XrKUBoYA5NBFVqCoiRF0yjABCHYFMAFly0QGoFtj4HEc/xa9zsprJlhr4psBFwFoPmYsKGzIdCABTMOYzAOIz/1tpwPi2YQSiyqRlAL77fCXUc0D9qcKtLtSQOVtSLCnrdsEmxatPasW0Fqj3NjBu8Srp2qGnVmSVeLJmgLQvOpzOWdsLd+WztNZaKdd3wdHk2w6lVD8LCe95aElQtFfLsTq/NMmmj4nLr1jIk6ds7ukh/XvHCZCsZrxmRXBQVMYpwTNA5MBNHJqcumd48caw025PGe9jz0fdwYfVGEG6sbfyusxKcCC3RO9IRDvK70DFp7NUrbJwPMbWj+H4Q0gL/R8L0a5ikFM5OdygPxwFTTbRW/J0BSIXDCIOMyHiVpqQYcbh8lahMD14Dotf4vmIClE75xqDfEIdqyP06AAAgAElEQVQ89Hfp6kFQz5rmfcpOoPiYs0zKdANgP7EHOqIuRQrIgb2d3kOkHpnvC3WoY1LjrefwvgyeW2BxqFd578amMcc370T+61QqDtPmXqx4mtGDxHNtuSwYJiLoYkHMdetBi+u2oW2bJyxYu5J4KwWAYQ6w4brWxpY5bMlguhhqQ01rEkvhjubabM8QOcMlmtEyZblPQ4HDwPHv6kF26qkw+tIx/J1sXQyK3pMpBwC16kv2YzeHEwJilCttRr4gnAT8l3iGjb3PgKOPv7QaTkUT0zXxr8n/6QxWzgzpX2YioFRLbNQx0NEhmyB6ZwuHRAdxUqdCB7xNPEe+ThmCUjDW1e4bvGQmcuyCGfOlASnol27jBbARbcHnb+gInoQOC4r7Hhh9yq4IiMmUPdrVHdCms4lYex+BQScC5DkIp6Ul73obqgFPcPz/2Hvb7UiOHEvwAmYeQWYqpZK65/T7P97udEuqSimTEe4G7A/gwsyDZEpVPTNVc866TopkhH+Ym8HwjQuqMyPFVwbFPXhOVbMXPTCyjkp0ouzzxbH3llER0PQpjzfOO+ZaJ5VdLlfABS/3rzmfHaXP0XGZOiCQst29EIRmkm2ikDkqcP64+N/QvnJJp5XkpCdIPk4rgP7GlfljXhNr6EUu8cE5gfFbhzyMWN749v3r/sR3cv4glvDRg7EKlfPFtLPmnjvzt29O9psKy/zq/dF7nfWIGnA6bzLq02H7Hbo8WHuvhMoZLpr7D9QbFkVK5Bs6/uNwkTo2dXtVqAUS6Voh/PgeNYclw6dukTeN82TqyryEJg51pLcGVY5ZPMz3G5N/lr7c6JyD/xOeKyQvnDbGaUT+ToLpf/+R735Y66Mk9RlM5z8v2YeiIybKSgYShPaFAEDqsyaB/uNeyNX1rss6A5L2iqeeQEc8YZS99maB34UytLRtOm+Tqe89vveyt781P0h7XM586609/fh5zel82TcuOvOVuMccWyR22un0x5HWfvE6Id7ZIqC7sqZINF5R3+S0V4kYOJ0IU/clLPx8T1+uQfmo1rn1ukcOka5IjdZtmkGYSoBxnBZQWL2+ThnkJJ75DG0Nchzz8kdWTwfjI7N2LD3OHfs4+14iQJ8JIuOAWwagcn6Dd1OEz4S7SdMOIvms9xRksczpnWdA+8RD3yA692izZmOAFZ8xX/GumpBJDsfATFypJGaEvOB7a9pAluMxmRG8ac/g1SEA9JPA/jZ17Uk1wP71JfxdVvncqTm8+2pwRLvWpXRjrphPMbY+Zxa7zPuZhz46MO2MtoxPy0ZJJI1fVgSD70reTLlzpp09ed74ZRYhrXOAfB4cOP6Apz/yIl3+8TAA+CWoZG5RrwTISL7CbCG2oMe2f1uQ9Vbdxrz8DPGZQPUHqH7B8VfB7fe/4cPlgkvf0D9fcLlecNkueLr2TLDssNbQ2icM/Q3Q6BzhnknfFuhl43/+NZBlMwhuZgnJbpAxCgkQCNSoI7+PfwNjrTxPeXPSZbiSPnkEUpb5iS6S9uuys9B49ixUwRL38LzHD1kVbvFuIsFTmwhMZyV9z7hL3DZTIDxWkP7VtRAyBhP6TYdGorJOPhf+ifT1CRakxETrTB9Q7z2LgBxo4StsLaDeW2tVFNZbtMfS1qDpt2NSVKlD5jjyp8scNxGpaRPMd1xkSs4zsYP4uZ/+mqu27hd+/ke2zXvHe/L5n3GUZpkvxVkSZFK8JKXSZ/ANX9Z/fzD/KrPy9x//ywPof49+HU75CtnF9clEV2bKG4tEmM4zO7CqYVNL+Ba8wFMaVl9AJVrw8pbkfziec3QvCxOHSBn45bh+OL/E2jI24d9AKC61M9eg4arMnMf25ttRR6VikwEBrOPlq0VKbBocKdgwFUw6pmNOgyEOP4qhRn/fqDjW7NHFtQpH6UjYbZyghwO2veOQHRgD1izgOxahZJ4VX+kEK/jbEsZWbyMS/TM0gwcOz2C2YRwHRu/Y0ENo9BjbYVGdFO+a2WJOkeUzaOgGM8HLeAnIzpxLkQ0wYAzBcXTs+xcchwXkKqt0cu6NN1/U+aLThQ2vgfZXx6PF9eqsh522BhRl0iTXkZWt8eHccaQPc0sm6tXXM5wDDgzHzbwg9mMNtOYOzmBRg6IDSJhrUTQxQBtc9gjiEKpaRzi28ZxzdwPK3Dy/ZdlmioTHVLSto2WmnDmrxg12jHzvdR4N4i0qPTSVOm8wVmWKZpVfVjWKQLrj68sd3333Aa13mFkI+439fPtJwG5Jj5fLVpXqx3GEouyG+37gYtORHBiqhGIf8L3hlpBAAHC5NBxJW9sWvarEYq8V7JwI+tbwdL3iw8cP+PjhI7beY77dcLvd8PJywz52DDvCMT4G0JDVX1iUkzR3Uwn7/bfPcAienz9Qiw9ld+u45Hq33nG/7ycyrOD5sgjl4PDVBMfiwKYDZPKqUuLyHmOMyv5v6Tgn/ynDuAwXmQZ3KvSPfJWK1tkYTGe4RKVhU6WWWM7jUuhd8PL196TzVFabBqy/R0JJByvsEAkUCTsfCnrM28cPH+L9bOQ0J2QRyJdnjzMIlZ7Ze56GrqhGtY0S0mlU8EotskdFUcgbKkFTXXs68xWX7YLnp6dwIogWLBPlU6xHfBjJJl6QfG4DgkBeiKA6+SlwHAr4DvMtxtoa2r1FteYYFbBQ1Qxw0WmMcrrCQ7EWu6JJx+VyxdPzcwSUt45+u4WjQgTSImAWgd90XpiXYaR7JDlAPQJ27oA6LPt1TuNk5bkP8jnljuR2lpQhIYsz8x5SP0mb27aF4TR2CLTkLZMFpCm2fsF26bhcn7B1Bs17wjEnHHrXqEjXFnSVhsq5+tnqvbnfFNGXrmk7BWpmAJiLfjbQV/1izkXQATJZwJKnqCZ/bhrJPL0nzTqQvMs8XBbToA5ZqxJVjdEjkfwoApAy0lCXEegZulRCNwWaV3b0ChtflXvJ4IyBNiyVBcnjkI5V6puR4JL8RMJIcxu5bpK8Yfbm7K3jaAdMB4aeZTiTUGiwVbDcfWaA515YeRKdeOXgByuCALiV3sR5YpB4ZK9n/s21M0ckjHBUee2weY/QAxa5sDo3NMeF6RAQNtcumnGMhDanA60M1OSzfG4SBAQeVbwgDQLjiDkZHqgA+3Hgfr9FD690TGlWNVrSolI313BJafGuhaapk2dFiqaDVbc+yT/PIbzcqKTJQLtomjTMeR8j4MOT77rHvAwLmO41pCeKgPtWwVgaEzLZB6QtcaitjlyLSnuX8N8esQ8Oy36fEYle6AdRNUg+k79Y0lbxMdoOHi5NwpyzLyDpVlJn9oMYUTLXfbF8RNtc26LzyWcoFxnUZ0Ji9UT3CGS33mC7o6kF3zJArxNNA5B0ZBn2EckZmyrcsqXSIEqKZ//zSXOSzwg6O2b/7Vxvt6giN5mtY6Q1iKduwIpVEXRBJVJAtJLnxkEnPk5H7Vcb1bNdLXmMRq/A0G8nKstaAXuq0AeDzl77smg89/f29ITblxdEoHlxhGdCUsn33KcqAm8NXS6ACA7ZT7JFc19IVjKYhfXA6o/pRD29dSlpO+H186PLFog8wUcdDdHCI6D2rdbmxBvxgDAhdKg7xvGmVYVZjbyMKRdI3rqAz3lYwPesMal9i7K7GLwTIGChl16JQOiOYyQSG3VfWRJ7Ft+ALHbe5MfTMYjJZR9GGskJgQmS36RefLb9V/0HqdvYohdMPYE6Kr/nfzXW1OmjjYzWnLCifNXLKU00ZfDbAfvHI2htvm7yPlaRN4GMeKjDSpa9uXK5l9akxnWNHEx5cJSdKnhVYc8PRDHltitcQlY4fCYZCrLVCkqPwAgPwhxepsL2BgyFY0BHOMVh7NnKVbPyQ1B2TUQZ6hsP9MHWUG+pvMsM0HJjIHIGhF6v02ntuMGXz099zPnoIq9J8yILLbjAdSKmMHhdY1xsNMlqQ1meq4l8xPeTTOi1e+hI7J3OoHbrUnqiewQG3CYNRVJq0kvLcx3QSthwGATtIaOp9GkRuCERPlDoQ7PinLrKw9zWB47mTPKfu7x8W+tF9ff6ae6R7B1dJ2IGm6nuV4WfIObWHMf9VvMYfrbZ47wC2o+Dd4f2LRNTF9tJgo4kUZ7Maa/E8xlMBZZAZOp2M7n3vF8px06B80QDK15M/pOXxqmxP5XVqvX5TEIFvJIPa66yQl9MltZg1Ge90BupM7f00bByu7dE1PGcgxyzjZE2/hJAfdhyEagOKhj7HucSSS55gDRF145jl5p0gUSbG6Jmlq5HmwQYdgDBWaoSO94sJi32GmbiPxyXyyVb2CEClW7QYUEjHnxKWgPSp8OigFgjFrUofAz0S6AB9hZIckeiLO2//hUA0D59V/GA8bfPsO++K7o2/x2OD5DvAfz6W9EniGLqDjtCDzF3PP/7X/Dyn7/meOaOcAdoLT1WqD9KWhYvML35ulyL5VwD8PXXqCpv/jogf/m37wEHxs8GcYX+GGdoS78Wx5e0Nvbk8/4Z9itwzecT52DFR1mlAJaff3Qoku9hVp9zTs4cBNjvUTgUtj0mEgHPo67hDtXv6w4Og5visPBftRaYcaLTd9yzCj2CwYrWGy59i8Kl3qF/zVSEv3yG/vgp6HscGEfGI8RxPwxyDNi+Y9x3iA3oGPg95SYD6CGXGIeIPeoZRGcR3cixMvk33u9kDSE4+qpPnPVQ6o2UP2lZgkWA9J2y2p88u4lj+3eFfG7Q/+i4XDdsW4deAiOfAXfzhm7hx4akvyTRdg+z0JOSUptMui/aSR+HS1rXtOlYga6hf1+vV1wvF1yvWwTBJfjutnUA12rbJhr2W8+iEFRBWuhILEzcew9o/n3Hvt+z4v/AftxxHFKIb+4Otirk/jCf8pz8kfyGK2L+UKhZ+u0iJzD15NPB9T6L1dNRBSjic9953XFq5zJbZbx1n/nI8xhW/Uzev+zVEe/l2DQSGO77HYJEalCB31f9Y9Lq2X6S04/3nsPxnT5/7/3yoaV74J25/4P7/J86/qkV6JWNSMNKZCrIeiYHQWxEIfRFBoMc02BYFdT3jg8AfosdNZ05yzWP1zsYPKeTgUr5OdjHRXYAL8BURN64Z3wWdz9lWda935uv9z8XobKooPEEAKY0WuJ7w8w2oRoUzEenY2UZcyTXzt6UjoQfpf1Vmf8WzMhD4C3cInpa3O9wH+jSYG3AOwONgmMk9OU4UIHyln2kc1zjGBCNPrtNM4CU/7lHFcZ+7LjdelRSXp+wtRbQnFntS/k9qzl8UYBbBb/2ccBGVKgLA1Uysqow4Cj3fccxRqqWc26Mymeufy2ZkCZq1U5r+OaaPxqibx7LOTQ6ZdLnPOOchUvaOzn1PdbTshdkJVYgDLemGcwRhTTgBDOaMDuOzNgDA5E9966hgT3qJSqjRaBocLvBoGcI3twfNYM0qhN6uGcCxzhGwnZm0GCME8xZVHw5tA+ozIw4tw5RRfcBswzKq0JaVOIOG3j+8ISnpw9Ji5FF1y8dvXdo64VE7G64bls5vktJPuKdAcWwCPz23nE4qyUF2gVjv+PlZce+B105HNvlAr8DruHkF0gEzRyQEfQffX42fPjwET98/wM+Pj+ja8fL/YaX+x1fvvyG37/8htvLDcceCAnmDhwD0hImVWiwpgh2x33fg9zEsd/v6YDoEVyQqHpDOiC4WL1tAQd2psgTGa8GYFURYP4uK8mXoJYlozoOwoZjoc9VQLNS8/TUJP2gy+SJlCeL00Yl0j+aBASRtqDjpgGTG/3qAbOB3jvutxfYGOit43K9AKIYbqEU5juYoyCHCdM+VZ44xhGJSZWRyaoGbamrZkAmEwNEEsKeVQjh5SlHegTNRkLysg2FQEyzuhdgf+zeA7Xgw9MTnp8/oPUG1R4KqUQSEiHFnVp5znvTnkHHqKrUJukECaj2Y08DfBg2v0ClYRsD99aw3+94ud9xv41MUGlQaTA/cknWzN+BkUZba4rL1vF0vUZlcYtgorYWGamIoEkEOMPxb6mQM1OWQSZWWccfEzqYTpyiKcp/Oj7TmUCniE4bK3ySFlXNfA+asryHH5JwmHEPF40eVa3j+vSEDx+e8fHjd3h6eop5YUWARGVg6w39slUAHdSdchyR4T5wHNEzmj3qgo+nMdqCrv9Y75gKs9DgkKAFJgvstxv2EXvicrng+vSE7bJl5VDwxaimEJhEpYSooLmhSbZo6RFEaZRJ8RJVzV8Ba0sdRzLRo3FfKxokqtibFn27J3pMVqA6WHFkaAIwU0SkpeN7QHyuN6HzI1RgsJ3JKz15A/t0CdoIo3C0UU6zt+fUJsxx9lyn/JqiPhdcaG6hNDdNB2EU3oeORaOea22nKnWuYHxyjBF6ilOGZ+DccUpM9UWWhvMk1pJJYnQLGNZKWQNh590Abwo1S8QDCZSIlrJE2N+2JS3OgD8rfXPD4TgG7vc7Xl5eZiJQ7+jLNfH+ycsz655zZ+ZlbLM3KdygrrAcS2sNXTX4LhwjZfLYDeZ7OAXuOwCtPpL7seN+e4kEhDHQWugINOT3PVEwHIkkIRNFgpCexxFjT9SK6rsHj17lyUOPPRMECYViS8WyAwugQ6xrzh0NUQBV7U2d1BHV7Q5kKyKvwO50luReklqOk5yfeqSnASwnO0RYxZ9USP7JPaYtv00ndQTFAd2RzpmGy3XD9XIBHLhcL+hbtAp5+foVRzrs2Af0GCF7jnFAjtifL19v2DKxCgCOtCmenp5wv99nMJbvJA5Yg2k63gzoZgB7CmZVbQsPITzlng9AE16QagyTUmqvpcN6HANHOzIRArXX5uolnCJS9yXSVrCvZX+m03+Mkiduhn695k192tQbgDvbBIxKvtUeujr3QSB29Id2SEEPZo7DgxabI1CblDUg+irQHYznrAiSF61Omgp66ZzT1WJ9PE4BW8wU3CFWlaLn4/Unb4bOK5CV/39HNsqrv4KnALQF5NXJlOP1bJ9nQ7RsHKFXnd6kV2MQqq45bxk0ymjXWyajO6pSB8AMItUJKMe4lE1gRYelKwPlD5FsecTkThz7lJ0KtL4F+oLMoDnHPJOFUP6AaQO8Md/Ls8tUHBGEimAVkq/FyzHgF2kVhqVEOF83eZsDomwdkAgTeOCbk1vCE847npd6XDr+UOuxrDmfle9v/DtpQaGVxHkm0fm+WT0C1wDjXeXzow+L+g7lOHmxw6s1S/l4KrH79Ni3tkrd35fTHteHCRmr5rGuG5afNTmPh0gmNOpZlvM+KrNtiGaSBvmjaEQBgGq7wvv5ut8UkMEKtlzrrIyFZ9IZ6cURPLXmMl9OUy/i/uQPdzQwwWfqcdQHKSo58WLzHE7Ie2vL+aNvDDX6qedyTmdyBW2WOd9sx8SBV/1e2jiodZzPRPmM7Cy/yfoAOJMRkhaKuJY9MXP8yGuC9wEecMH1zl7XAFJJnfyQiT/AStMLRzvRW8oYVr+n/lfBi+RnkddMHZH3iCB4cocci5W/r/j5Yh/mAlS7QraDU8sUGdFMRItX14QjdgfUQ//cR9gGEfyXgqDmzFQxBRNqx4R1B7wKnswsde34NgJJluuZdxOApbRE0zyxMfcM+NM/j9RxlswUjaD7OBKBj0gxy/zX/VLGa84/YwHO+3Lf5t9MOABmwommvRF2k0N8ojw6nuMdfd1DwmUpFB0A2H78AftuWMnOwS268FmcD8Ki15st2zh057kXV7F2/ct3EBHsv3zO9lNxmuYyjP/62+Sff/mhLqR/HNQn7cxL7ZfQW9dxrsF+LL97fvf1Hd3myc9jxvKukYjHkqscO8/5KcY5fvmM/hMA/4Txy9+gPyKTU37ATLac+9+Hx97TTJiX8P+3pumnyyIFfIL4l/BdEZUwg+ct7QxDJOMHKtiB+/0Fx4iEfxfgVxt4Hobxcse43fDl2LEfB74ABd8etLbwR0clV5AmSEPrjLuj7EzOnkzlfmpX1HVk0rkmTwu7fCZVet5YkkY6gP4TcPn4Ey7XZ1w/3fH8/AE2DJfrFX2LhKZNzoVvKmzlEFogk3fDN7a0aLXwgbEFZE9bNWG4SscIXhJr1HrDh+dnfPzwnGtHyxu4XDr61mYyf86qZuGZ6ERIFNUohhwZLN+PhMy/477vuO933G8dL/cX7NhxTwQ7kejBHrmFKactEewW26IKBU8y5iw3eP4aROd71yLXtbXKr/aQL7og71PFAxDIFITBwldZ/+puy30fFDZZjYq/4wjeDQgUwwxNEUmcbxgP008o9W7kj//dgxpI6S3BPOf+mAL2NIZ/9tH/NYYRx6PRsSrcq8Ye2zIV0T+5eKw2f1qfB+pHb2c4POFts12AUy+RGF7895LCbc1jPr3bH4x3XY+3Avz/6EFTfjIC5FxqBYQARJCR70MB6mvP3rEYRZhZv/WE+R11Mr6DD4erwzSgUQm/E99nMPxhHiSDAkbY9vwiEDwMZhHIO0ZLp9uO49gCHls9oLQ94LmHZyVRQm0Ggw2hfLgH3EkaJZJ9hCIAGgzXcoXNj0WhWirYlsWr3pE8r/xJMxMJeGSSi/Pg4XhFAyV4p2FTX7kioLcxKxacjoFMUFgM3RiwV6ZxZBdarahAJ4xNPvM4ogpvBirXNyMXRNLYDvULRA5AGhw7VK4Q2eF+T4NKoKseLtdwB+mR+02guEASUveo/sXhKNttRMAq54qvNXafyoBaBFYIOQPHQDimAwo1AoLaFK2HE+vp6ZIORokA+tYzyBkBgGsGX5r2MrYjUIUIfieMzrZ1wK9QbeiEIRYqYgqXe/SKFsFwzApjANvWI1tdFDJ8cU5JaXT32x2XbcP1Ofqfj5cMyjBgRCMglT4ZGr1OfQbW6EidqyjYjwg6qmcyiVIZNKh2XC69zmdgm4bEn5dxUhCLYZDx6TIZEFA3PI4DvW/5DConvCb23XHfT/TPs7RrGJ0SxnhA4noYpwBcM7iR1bPbRsj+DDjmXghkgAP24SkceK2Fc18cYzj2sUd1YfKY/X7H7X7Hvu/QY8f24UNlWo9j4Pn5CWNYVrpJ9Yok/DHxToIU9cGBItXjTxI1Q1XQrcFbzmOLpADtbalsCocTgwDRfuBSSmyn04rVzSuvSwWzkCa2cCiM4wjnlqeROkZVkXpC666GKys5AoZ7ytHHoC6daCVj6MjNfRzB0h6VqhhB9zIAD5iugO+NAOOxRxUrsqok7pHJBxk8hWnpGHw2yuEbfKfg9T3lFOYaRHAHuN9eAIwIGHJfM/gmbAvRYMeBy3bF09MVz89P+PDxIz58eMb1es0qamRlq1eS4dxsMY/SYhxNo3dt9JmX5INHbUz3TPQaOZYKunG/zR2zHuRvFUSn49EmeBbniJDFJad4j7o9nW8z0aTWm33xFIiyowxywqEuMNVwOIqUc4pD9gzYn+4tlOB5HNEnCyJREcj/1DKxJJIvxGd1fFX5mUPS4+Ee+tAYEgF36n6agdjeMA6iSKRjMwPfIpj92DgfID/z1J3kNGd5OqhY0XfH69dzy9FbU+/LPXw+F9MZNdf4tXG4DoIOWbJmIjoFLXidXDpmnsPAnvI5FrDndjApMaCoa59RPsKz+vuxh3Wcw0B72ZD8DiFPqKzTqIdIJSpFH7YWqBgaFWONuo47Ro92KLpH5vywEbzDrKrl9yMMfIAOEGb4xzzoiGQnOwJ2vksHYFXNPQ3FlH1M6KBUq0VGQsVnED2KaeDjiASASjJb9fCzYhrAU1OXJk8XypIwBuL+KoFUUI70c1DO6/4I59fyaEuHJsdQyD4MKCRN0BFrw+ZegxTCgtmAicPtgI2WlU1WSW1b2zDagdFveLmT9CJJyDRQTngvEWA/RvEt5Du/vNwyuLLKnfgZtBDzg6z0h3gkhFhC9Kc89eSp1Q4C7CnItVhIk2OoheF+ykAAZYv68uU69zOwU/PuKL70in07opdsIpiMB0hoefUz5JdeM4y6ayWVmd8haGieGrQfJ7v2TecLTYIyDYIGNR2LeyIP9D77rIsqWvZlMNPkdTE/o5KPzs9sbbYcYY4J33/SfK7Dg5IqyzxXYGhF9sL79tn67sXr3atCj47Iuv7BCFQl/wQetmz8ehrH8lK1J73oqoKXVBF8nvtnjqKBxa53wmmazWqhyFyr+8cTZNK4AtIiECShYqPV/soEoVxnUVR7LPY9PyPjPPwDzmtRsnSptUv+Bg0kFHfKiZm8VjP56mb5RimDzv6T6emoqjry0qX6NCod51VcBV//WOkh7+dQwEbqBCRwBmJSP2ZFK53q5ZQ9H0WPb/wX743SPdZhzTnNX2vf/jka4uWPfOX9k7K2vxIuXx9BV1PuA+teSRtJABWvAEKVguaJ7HVutqAz5X4tfxcQ+1Yc8KBYIoYBXklk5fMSnOn0PGrUHnVUNTGTDdfK91e0UE60h+o0vviybkzgUAFck1dTh0y+ySTIk45Uf8tpvahTVtA9x6gayQmF8EH6SqEjbPuxjvfkx2RgIub4FGBf9brHWWRA1Wdgt/hN1RRa6dUk3bku+S7ko5kwyCAuk03J0ybNpE8Bac9k28aWvo5IKuS9BXbMV+ZriTb07nDpsK+3SHL0IK+AEM9WUbXbvao0IxBkZQNinVrev2mtv7QGZPWs3w7opXNqMXzqYiUQqfKteh3pWaa8k0yYUJVab1HqoNl7fDAxcOqrZhb9j7etfKCRCO1TZ0Ts674R5WG+37jvYOHXSlL66WPx5uMYOP72GQbggiAFVS1EKrcv6Hk+IBX4W5klK9EPd/RPgv1vy9jwPv9yoKjPMauxV7VsvQe1rttff4M4cP3xUyBXXje4GfY9irfsl89oP32f2zz8BNTbax8lZc7A02/w3A0rifjyfEcE/Zmn9a3g+eN7rgfTgB7nRn/6BOAzxS/8FwF+/AxAYL/kST85AllFak3atkEEGPd7zKO26Kst4flVQSREpj2XnidsoriUPyReSn80jF8G7GcHvv8r3J7QXCrhEwC+c+BIOTLg2AS2LZ4AACAASURBVHIhL274AlvasVLnzHlw7pX1e2BFdX20r2sCqaPQtl2+PsvfuH6CFKfW4YhkXgD9339E79ewQVvD/rNBt/9Cv17C79sMPfU3FcXWOrwZbEMUx1kiAkYJGzxrad1CLzNztOSLVWTIJIAcV6BmBp8gZPvGxFugEEOBTBCUGZQueln9RWnTiQhcHfBAGDCNuIy1hk6UvG7YRoP3AfNMuLLwpQt1P39NtzGWoFyT8GtzD8/vqOFRRk7dNvbwmTec1vEk694+UtyWjF3Pn7oP9/ob16621jJuwSLf/uBwZKJ0JhXux4Hr5QrKUL7/1AVjXNRDKnk0B/X++watrwgYj+/7Rxolt86/4vFP74Gecvpdpfl/9fHlzS31/vGCc6XgP3y8oxj+U49i6vjzFPp43ruaxVSsHZjQolXpjpNCSwHIzPtiWGSubQZ7GRAXpAP7UAA7jiOD6PteAXRBVL6xx2bAca4BRZvQTK1DfWYkz3eUUqbfE3qP08qfU+E5X6F4huHr+/P8Z4+69duLuGb4nUeGsjRSH5hxjLWfIN+7bh+OiLoF17ISWqTeOQIeezxDZBagiACypwCp/+UYKEwHJOEjeT/HAUfLCooYUNQDjFBgnNm3FEqZgXgc6dhWNNfqC64pnFvrkCHwrICjkWuI6lxJY6llAH3rHewf3Lti6z3grsYRptaRqmVWeEv2ehFJRzoQjhJW8KvA9wgiDG/ww+DHXk4ReDpyEcGk1lquU44z6bW3FgHEEfRsQEGRcr+dRO8C7RdQk2kkyRlWyw047IDLCMd170UnuaLYrteTkgjMKg6eQ0fDyuvl5CRaCfdNcq5rWYF4OhyZxD5RIcQs5y6rZUdSB/mAGVYju7kAqcRt24br9YLOikIB2qrkOasZkbSwZdDccNgOZniOceDl5QXaG/q94ziiStczYLxtkdSjGtXM5l7+Us0KeXGde1yQCS0AHR+ZFhPvKYhAf59JMjScZdEUWRGkyh6uitY6tt6yCkrTcJ99X2uq6VRUKsZRDb8GSGhMWwa/RmbTu42aO01jiDwnehqtonJqwadKmtwX1T9MBSAkujO7OQzFmOV45s7eVfvAcdzQtugJ3nuiFljAu6mGcQE6kcvZm05YA0wtH+CZkBNjOUYE6OAJL+2T7sVDvrG6PnhCR1PF9Slg6T9++ICPz894enrCdrmQm0XSUFUUOHAMmHo5tsSyGpv7zAOmnv/cHMOPNDQsM6AFb6qBgjIe1v0VPHvyk4CqTr6imdDAwPkklmkoJL8nrCtWfiAPYiyXwA+aLlLKfaKdgjKAnIbjC5kzb0VDT5IfY4y6ZhoMgqhC94LqEyCTbILOTSLpwEOpiWDmgaywS9rJqnRvHfCAl441Q7Q0kQlTXmw055RtDJId5Zyc3dZnTcTn/335/cQaXxtcr0zLd4zN+cTXBwMM9TeffyaZuaaJlEGHI2VTtPiJSm+25SGf410iuH7AjofK1keFLOGj16qRyT9Q2fhbViz07RIV8T1a/rTMiG8coxm2Y6D3Hbf7DbeXl6oKIpNm1b9qILWwnUcMaVYqsWUFK4FFvLZZOBwUpuTXWBB5PCvEvYLnSc7Bh8SrEkeyrc2a9b6sxOvpOn2L2iOTnuaaOvx9GlludtY1H5dqGh18nj8SzOIDGHtUwvdLT6jEHkkXqecMiYr522HoAtzg+HLbcd0yEJeQl+4xvy6EJo35asJ1IJ9fdHTRhHlfUZkMJgM2FIfG9fBEjXCv4Hn4cxYaJEPK+ancomX6TtMp8t62ezWjc/Ecx34PdJynp3jkMrfUWeYTHcH7DZQBc7Rpe2Ulp+9SOlSc55CLog3Hvmc7p9P7PoiAP/EmAhSSVQqYHDfqpztp+1xJ/Hi8eraUWFjuue6RRSddZMXbdywV990letRNHdPZ/GqGZP3b877fXvw1dBbjmXv1bNAtYvw1kb2i+VeVwpyL9WnJC0quZwTGLJKdZ8uRrP6mPc9LWuoJEugZnOuebVfYUkhFFz2VPDN/Ut9bKNZzL0+mtsxBXuNwuGW7g6owwyyte5C0p8S7b6wDgxh0ELujUD7wzj3YbcP5XqzWBMLJbm9etfw408+f2WOr7rwGBs7v9P69vvXdqxPfG9TK+LDQ8ioMBYvdIqFb1veZGDmhK0/nJxFmxXD6BIT2KCYrfuCx5AnuVkg7kr2jmVDnIiUTRP9oNkgbPLzYWjnaqUOxQJEKaV3CvWRzkG9u5kl7AEoXrb9JyRxyvsf6Nx54ty/3LHtPZnEGSbCSD2R511f6R01Bzr1HMoPq6ZyZVHr2u9I3pb3HeLKlSiX3+bKXMeVGvcPD/DxM3ExsWObOZsQXRJmATB1y8utZaS8qkAUZJnQCWuco34pKyDoFYFk54gucvjt9HMuyrKqEZ4Vub4GqlfqM9o6R/irZeibazMAhg2Bhw3r6RNIeLPpc6H2xPSZZyuncSqxefASk0N57+c9qEZPetAN2jwQIJqivhz3wP8nxuzPZgLrpDBqvn9VVOdcAYo5l+kV4vi1/2+cZGPXTvf74SNIu1vL2Tp1LGXRniDZXDTbuGL/8BsV3VY1chS8p42tNBLCfPwP4COD3oENgmYsZKNflFUzinJd1vy7Hs0dg/fnhy7feI1hX0vaPyITD7+tv/xU4fp4qfezZz4D8kEnpchK71D80f9fiI9QZdCLZpP4yABxA7TX9L/KYqMjHD7G+zYEj96uqoFnuvUSk4PHkwG/I+u+5jWPuuHa+0sf8DOvfy+Gn318rj/zM+R4ef9Fim++bPzXQUt0NYz8gY+BQwdgB6Q1q0faPvE1EseU+EQcOj/gI3OCtReKHhK+qtV6272BshMgufHcPmHWuaiD+pb/w7MBbfF8sQpyyrApjhO0zF1+lGIhbpirpU1GYRdK7tQ5vYc95IsfYOAe4OXdYoNq5J+f+jN9WHdeL6vK3B762PuEdSfcvfzAx4jiO4kNrQeT/f/zx8U8PoP95wptcqalifPvkV8fam/wLHC9wrKrbB8gpuP6U3z3lBn5ZxsH75KjOSsYibNeAFRkjls/kfwOtLmrDq51+MsrL6DKw2AFAwZzTidsWBbdEmURGGEQzIDAlsS9MGshgkBlMJ4tS0JgJp3PIMJmORUIhtoRzlezZm8o1s6KoRA4zaML47FWBvoeCdsjs77M4eKn4+Rg4EEy8YYdlDw3JauByugO1YC5TCeGcm9NhhoJ1KmGIxVgtHdKgeMKRQfSI/frr7bAEF04LvCrTy9r66UuU5J+XpSFUFRyZxCC5VtCAhZX5wNlnSxI2l/CqTJDw8zjdMfwOtQ7oBYaBaEF2ybVfjKPMhp1CLhTxUB4JkIRaB6jUeCUXQ9FgMgoKKhClYsQuHj1DwX7pQZziI/9oAI6sfu+pnIeD9elyCWiaLVAISqFbDPvrdoU2wf1+hLKbkFZmIfwvvRckph1HVtAhnEqEJpYIdO9tx34HzI6ENA1o2aCrEf6CgtYKqyCUhqgn2vfo8UnI2AhU0oi2UiCiOGcGIs24j1ZljUGeUFbNIgDqQvjiVkQlAtxv0bu9YJxyfcc4SllBru2H7Pt90pyx0tz598dNIXPxiwZ4KBS73VMZCJ4x3NG1VcV2BRwXz2wpqMqAagTNt+2SCROhZHeNLMuC2YRkAD0SLKiafb19BdRxvwc0b2qd3FJZxTj7vR3ZEoK0ZXZL5TfGXckOgZEGiMBobCMh2hBB8JqOMZ1HigisV+82C3QC7VlBnsgMrRFCVOtcLTOJmf+LMyXXgygGmnvHzTL4MSqJxcbAcRwFYRuGBvfV7F00ZaRjdSpO+/3c6oW8AxpQ7WKBkDHyeWMMHPdoEyIIWdN6O1m6AZ8cBjYchVIAsDosqvcwkpdbBrU8kgDMBSo0fCTXXHDplzw/UQ8C0xqtBa2JRBbo1q+4PF1xuVyxXbaEB57BQFbPj6Qlh2RAR7MawqOnMqErpSXCRIOaQ21UX/GSTx4VF6WRnAT9quXgRLuODApKfFw5GVyXTC4qJ8fJi0De2SroTEjFECPLc1fowzSW4VqO5XCmnDlDEIsuzwm6NfOiF4uNQEbHwaM5+2r2wCXOfRJw2zlLJrm+KdfNcdgx34WyIeVUyeVyfvAZeR9ERZ9kIBREnEi5XI5BSWNOpv5COPo1WDyTnpb1Wh2jKaOmDlTaSX3Obbcs/tR9PM+rugsk7OSZhvj8lQYWF0HdK9CDDtzve9HCpL9MVoFjHDv2Y58BZNS0lFO6qpQAYDhM/EzKAgCBttFaw3a54nK9YNu2hH+Vydepv5pDWshjF8f9dks0iwGkPOd+6tsWWkbyM8n3HelYODgYDhhScIvsLxc6j4MJG6Tpgnhsgf7CeeGamRmaTCM4+PNcc0xyOOmLNQ4P/ka0AKl/Uo7WtUqTfcUJIXq+X37CClJBGeasqOLCUbcuuSw691RSJsyxv9zRngXDdoxjwzGO6N12u2O/30LnNMOmiibJi5S9Rh0QR79s2O/3+L1TFwjZFu1DFoQTUBbInE99cPLUtkilnm8uC7tkEkQmjYFtFVwnAYsARLAA127+fVq4esyjofDHx37c0fsVW98w+gHswbujCuMIWeHRf5xP9xfu9KRDB+Addhwho1ShXeF3KzvhZKrUMCllFpkAzEr45EdHyjdFkH9Lx5mSlpLetkToob1xFLQrbcP4riv1/jOdriFNWUbM1grUlqsFB9d5lTfL7+s9Sj/ndzIr2akfAFgQGci7qI4saAi+3D1pbtnYJ95Ov6WqlN70nvO/kmROH8aTiArAVyoeOi+u1ycCmB97jIf0q5rjmfyAtt0pcbD0zYa2hd5DHl7tNxaEHDqWWflIvcBBnSZGVjYC9yhVAwn5orBAjhhWYwZ5EV86HjbHnvKDkxLSGrU2fFPndaXLTrkNBWSkfF2cuiKZAEAbGMkioIUIEnwrEoj2Oyui5/ODh/iJn1aV3KLzgbLj5Ok/85Oi5lUn9NdnnoLWr29T8160JPNEOZ0j8yd4z1yT0qMmH+byaKOvIBENFNkCK/E/mMyxVHrHo9KWKfm0lZ5OBD8AFbQSaAY4U/cGg8byOCEAiISBhKWWQNZZNhQRKTi/4XbKMAqJrdYQYJupIJuFZtLPQYGz+oH4fuUzyC9OpvUiw878wOYK5RprC5hdG47We+mQEERAu7UTzyi6xAxQQiSR7GbA2mXSwkyJWTiqZyIyomBm9a0tP4oBzsKcNfi7BE3T7hFPBILkzw5/FbRdaV6AbD1kC49APSf4W+gfYyz7b7CVguDy4Rnujv12h2sEydUA6VsgMWUF9rZ17IP95BeiIWtJ+KGn52d8/f0rdFOot2yV6YBGImjftkgYSohj9mofi+5aukr6iUrUvSE6WmvY96NkS7FJiSppetnHkf3es62fHdH2yPPGZR+ohE3VolWd9kxKZcvN9KmMl69RSbtFIcP9dlsSFRz9O4F9Dtm/f/4d23cf4SLYLle4X8L0dcB8FM2HbpvvbjGn6kD/yyfcfvmcuzxWtwLtCy2sLO/6w8dJMr/+HjDSlKeokGElZqcoSD8B8PLyAv/5MxxA+/G7grU+sZb8f+nkCD5++feG+3/GXS3HOPJCPveLzqryl0ce/XA8VqVzrOKssBdsmDtUALR/+4QVVQY+4fCZm+bI6vdfgIFf0f/te1w/fgBsxHor/WEKyfY90iKhhfyztYm+qCr48B8/wn6/B8qMxLOGO8QN+j8E4n/BftzQfvoUcvS//hYxixQvrtPfFb3FfRYYZFsNB+1QinTK1Nr+b/4865iU6uvEPjLjOd+EUyU3l9St+Nn9f/4XsHWM6wV2veLpcsVdBWiCr3bgP44G3yI5oAUsCegD3qmTMIEw+SLb4vYs+jhsYEv7UlRAJFZkPEWbFh22xV84MpmcthPHTF/MKUMayTt0WjsiwSmCXoLHNAE8UcDQGqRvYVPZlJF+GIYPaKFHesh3LsoqU/Iviu+29D7z5f85wOAAJQuoJ844hp+veGtFz4ecVKqg28cTyOwfL118MY9P+IOt/eoY2Y54WED5XxIZkzZsqMglYHN9lqesL/HGsZ5KcvflmsdE/2/c6l/y+KcG0GOh/NVnf3jdP/Asf/j5eHyB4wMEvz+c8QLH8599Iq32Vx//k8nireG/PdSHU16xktc31fOf67eVOZdVnjYGXNqpSoNMbTq7pZ4qTCND9rlFKJyhgIVqMHxARjDg4ziwi2DvUdFkohhght/5vabzMfs9pnWrVIjN08nuoGF9FolIA9qXOz4KUn/4FmCQeODlQYx86/BXP94Wu28saAnpEhnzRm/dhZCnJTRYAR6JCqig4TIj7skV0+hEJrehwdzRsUFd0T4ojtstHL1YmGf9jDGVQKVTwukYl3Ay1XsASAd0BDgSkmRxfKR+jkeDLAyldER7OOlGGxijw9xSQWvoW49+ykkPNWNCB7VX9S7pI5zRQbMXuaCbo/cjg4ZZwSOIKthxwBD9JG+3DmbKR8AnlMj9ds9K1JWOU7lj4si+Zx/PBvNR2YNRPcXs1ZhjoxKz3KuM4VQqaKSXFPVwZppHxeD92PF0ea6hCBxt6xWk5M3X6klmNX/98gXIYNPzh+dJfLKct9Bo6z0QJRayPRkwMr/yhPgfI2Caz8I+5c2EQsgiBga9ItDRW/Qx3vqGy3aJLOpMrOwavU97j3MIwQdyLgEOM3RrEx7QA3J0jGgdEUacwNij3MJxHFWGCUEqjqZteUs+IYMMHgYfgyNuUR17UQVccPisKhNWiGOdijBAWlP0pvW3ytJrUGbCCJW56XOL/RO8bs6fw4GBhHNj1Xn04jZjf9bkh46CsRef0LeTvh3nv5IeF1rOLZhOmHQoOVt1jITYHjUe0lcFcfO6kWtRTivyNRGMkTxH+QzPPRbPCfh7gRG2mSRGh45ZKqGelYfzrTjXLeGvtq0H5F2PyiwbiZoyjoL4Dyh8JLy/4nK5ABLoKXwmK3m9OZopbGRwMnvkjjy3LVDLpyq22mFn6V8yXQCxbFGQ56gqtLVCLaiFmwRc88gxahrEM5dhyhFq8YHWIWlgKxormU3W075xZOsDd5gpVB22QK4RMhZwqAl000l91kouwQ2igEmMcVhUbxiNNg1e2WpNFWPJ6H1VnSkIALXsBRfLw2ALg/5MMJuGhoun42dCw5+SNb8xGafKbB6VQbmsf20z6g0LJ/JVn8mr6KB/gIauAEHuUaz3QQS2mOhyS7lfDivJ6zx7Yo/91CN+DTFWdv754cmzlmBUYPRnctSG6/WKy+Uyed7jfI1sH6ANxzGTG5wtIQgFKjjBeir1ldzjTWf/6mARHFycZSmbZsudaRuZBc+3JaHQsz9dkaZbJPHQ4c7kAQYfJBM8+WI5t3OiXq8ZeX4tIDJ44HjgGedraYCfPk++xARjt+BdkNUhkM+pjZnP9Eg0GZ7QikmcY0S7DQblqWms8rxvHV+/3jK5KfZTuIEcyArXS28YhKuQR+dI2h9Lss+KHrLqLDNJJsZOW8YyYQzGRFEsdz7T7Fp1yfn5R8zHsR/VWoZOYgFwHHeMw0h6J514DbK5O9o1q072KS/gKCQvKdhbQLwDuC165NuH4+3vZgKOl05BjWUkrZxEyTr+lTeu5/i6jjwDC+0vfy/fe60R+dBrvvWtYyZmnmlbkImlMh2LcZpk5MgBjYBDJGPNt+HWmBuLY81zyskl6ws9HHPFH1eBAYVZWTn1FNL53NNTn1x1hrqyTlwCtjL3E5E+WiNqU+gBvXf0Rgid5O81nlyUegU/0YjkWCZN5KhS35dlTkQiYGNm8AYI20YJ+TGqQnkl5ZVkZtCPiUVL9diq+izy0fJvVgX6Mm9cWq+/ZSHEP88ETg5Ljuf0L5479zul+zv3431e/fEH4/iz3y/LewpGU0dcaLL4Iig3SLMJ96+IpOlFDnBSGLij059tuCJw4Au95FpmxbdwzhSg78ZTdghpZOExpaelr8A4hEXfZCicCHR5G7gkPfsyFiaonOZu4QFcEwWrA+aJ/JO8JQNHVPPmNl32OSirdfmc+yvHn0UmDD5XMM+jf3lVAJb+iCpugEy/jojM5JAaM533GYDzqfvaceRzJ/3OV7CS73Pd4x3m/joH0U/HYoNgHf9bey/9Bhxf0MsyQZzcx2vpX0H6sywRp5B2YW/wEX5MoghygU/BOEHqiUH7z999xP5yC58HALRWLQbZHsP3DCgxOOisBj3zA5lSL3WXbN2xvEbvHcc45hTl/LMFW70ucNL34jPKFpmfy3oBwLto0wx8j6g+hWTgLuzlASvURLOP0E+G8fn38zpwROTDjID7QuuY76efPoafx4CdPCFHPP+/sCkA3YFqgbS8G2XTA4XXd7HvBSMD5wqg/9v3Bddeb0D/XelIk0/uAPb//Cu2nFvHKl/iYMD8jwLnPFiBvr452QjfThAV5iKfsgo+39ojkVUFEP0ewOcaRzaemrJYkXx7g40IoFdLNfqfdLaDY4I+kyqbNgh+x6U940kaKv3GPGzknwH8JWwE8aCVqavEPb82wdbCX1HYSsak6LnzuNVzF4FqD/1hr/SEh2Pqb/xgkeuvjCUULYVvbX6lVG7yFiyuuNvAZYSv6uNx4NCG5g3fAXhpLZCyZPJpByDDMMTCZhSFqWWxV7THbMYkp7R96N+yCK7rkCqECZRgxgrCb+0+KYatIOc7LrTM9ZDp9w9x5lmUExPXFJBKQQHct/J9mEVyjLoHinAmvKlLyeB1ZWLaX/sM/mysLjUS+Jur/Y8dj3Lprfu/Jbt01QP+zkNV8enjd/jrb5/BwjJg3kty3t1pYiwPeXgs9df3X/D1NfX5/6XHv0YFOjMqH2aSBsDpk4RF/nsP9kC/IKrKb2+cc1ZSFwE0Jfv8WQwuFUSf35UDHucNuQq1f5RmnlzQAfz2Bzc4TVHpgwtTzq8qsLYYABTs8be+uTdZZQWT2TMHDFDle7thWGRW6zB4Qo44m9NJCFDVBjkki8LmwCMAcwDSoabvTpp7OBk9IR7NB9iGh0y5bx3DPRh/E8iQrKCbQc0xMvNJWCnoGOpL9WDM4GzzGRK05lW8oER8uXfRQErRN3tzUDDSEfJg3DzaTHUDX04TpJIgpYxKVmAgM7IjWLUEDxDzFtWQmnHVcI6ZpIMfkekNiYCOEE7FAZZGiTtcGgxH7QX2Hkdv0KtjfLGAwBWBWMI3V7VD3D+qh5gVGMpU9C/PXs3blhUSVHwNlkgIlj1s+Wbqgrto9jtVAHFPwuO5OHpvczeY4eX2Ahfgh0+f0LeO+36gZ1ATZhiq0GHYGuAaPcxG9oo5RvRIHcdIqOrYaaxWZJUu6W5kcG8Myz7REThVlchadsHLy1eM7HvuEj24gw0GLzRFVtnuuN1u2C6XdNgyeJt0mIFawBMa/kE5NC9DjkpQBJsEYrEmR0JNBRkLbrfbXDsA1yLTdCpIVGWP7G8ZnEenoxzAy5cveYsl93xxfKwJ4denSyzTMaH6o0+mZqA3nyGSgblwzLX8WYr5qqSkkcmM36YBY86EnWMc8EyoAABrWY+VE2eC6qXn5mjbhmPsuB9RUX7f7/h6f8H9fl8M4xWFwQENyG+zGeRuraH1hr5t2FqrSgobhpbVrQXpNTKTWQUNDWNYwtWG454QTqqSmbpaCSKELJY0HO73G7ptUUGhisIE94DrDgYRlCMpu0PhVUjXMKIzWYA9gx2WTvYpI1qLtbjf45bNg3f4kiexLFLy6NlywHO+fXEQmTl8xP7zI3orI4sdo+Iw6EchGNeRgZegGxsDhxt8sO9TVslTvi9VWeapmOeeEnGwL1ew3kDycGKWIsanLXp99d6x9Qv6lkgHrWPbOrbLNebdHEf2g65KYgaNa3IYYF2QVTjAHENMjUbmrkzDlOOpQEiuPcrgwXSmLwo7ja8Qe4aDGdo0oDSC5yVLEjkB4rOCViiTGYw6B6JiU2XimmYmsadczKBCGHQUweEcNQ394ZyzP4/ggwJQHks6shYLSkUjxT7p2xwJk8Z11KjytwFIi+lqDozkDVk9EgkTA7aPE/LN62SekJHiiEx4CyjDCBiB4CxLxm68uy9rZ2a1LnOcuWeAMjAfJ4Pw0mtl0slTMAdaDk940rijZMlqNZVKwrHgvCeqQo5O77zWxsCx7/DUCWbFR1YkePZAtwN2jNxzHJ6CkPsisxIRXaieFQxgDEXS/zRh4diSY32LiSJEHS50oG3bwuk1BoYAfnhB8FfmdjopY9nSIdAiGS900mkczyAfKsDCcQji3UQDZtvZRgACiU4M0J4yPTPHp37oQVOLiyD2TPJsSPaZC13MEk84Ehiigq/mqjtsn3PoyERWoOTs2MO5HZDpOY65SPBBnV9Tls33t3QCRTADkKYTctYj4QqG6pmprIMRVAVhywqUket17LE/jn2HSFSEGWzKrhMcISIpB1nhtvCQ1sJGiSDLgJpgSCYipcNBIdVagA4l6mjHEUkfrPZi0ocnWgAyqWzx8kzbiI7rN506jwbA8u/hNLLXy9Mz4IIvx2/zSweS6cWjvUM2hTSEXtQUaAIfiNZCI3lO6q3IlgH6pJDfO8xusXLTBMlhvXYGTVJfAiHcBGlrHbnmTIptqaOFuSR1n0vqR0xGZOUJdSQ+kQkgdBTRluAIhsUakz7CSbvIqJMsxKt3wvKeJzstPwiki7R72wz2TJmU+2ah09O+rn0ly6ixVAoLkokCmWDJqtv37OdXi1LnleBZdPLUDRZdWhxZ8Ugn6NRjS5dI5A8Gz5nA1FskKDOAjkwOFCbhJSGZWaJJRBs4AFXZJylbfHkog3VaazcnUNKZ3JjMn4mIVeX1OBGCorXaUADARPCkg1UL41KE3PSiF94jOIGG/pDJ3ACiitccUOOL5CMVrtGCaE3MpV7D/2iTC+UXdeVFPxAsLeyAkDPf8KmdJOMkidN3jwFkfiP1rTxeMM9nsDyIK2hofsTNUgAAIABJREFUTVJCBMehc+1YEScSvGpNuFdtdc/WI7Q0xkhdcq6t5H0oJT0XzR0QT1pL3qhy3unh48lxvjFZNua+4Zh8OSX0CXLGRI0QmTok2XqVvC58Yvm58kGTsAdCTwu6UM89siB8CRDJXAUPj9M968bFX/2kVwBAu1ygtLU0qH+F4p33m7OjDKKW7UoZN2VYtdcjOkPqVEgdKip2p05r6WesZDxI0casRJ9k+ypIwb/JG5ZxF6z7snmVugAHrDqLBARpu2RFpjuO+714DERx3O+ggrCo6sWjxD3QCkciAPiSkOio1kCt97SPPAF9Yp7701PMf763jWPKLAei3Ywvc04dAGDgiltEkl6iol2CXmg3gTJw3RWszE/9Xpls6su5GRxfAs5uwP4SiBqSQVUgepuva2A+IrE8x9q3huM+W26KCNqnj0nzvwP+4Zw06vmA/CMer1PmimIcn8u/u/lUy9qyyaenaqmlTdozeyzBiy+nfIiAO4Pce1a664+Cpt9hu17DvkifGZGpnEhXOWFcqY3rwNdbfgf+XND8Eap9/Yz3XNvfAID+BKh8gvlnyI8oP9rUNZKf5Zif/uMn3O4/Y/81rm//9kMkQdzvucaYfl6En1mRVfz0rUAywNujR3rv8M8d24doq7mxhSUciob203eho8sAkwtiOSJgLAC+F8VtRY5LencPwD7KdHJq0kbpf3P7LLP+OKGT7jmL/ur7VbD61CvS3/Gcp4Sm4LhnHOXiDv0J2H9zCAwbWsH1uwK/q2DL/Rj+PsC7A1CIHoEOPCxahxEoM1tyrIikoGyGABr+LbHwx8jC59nexIGwL5FJEOmnnXrU+vqTEZbeYjZ9fE6ekfcCE83CXxdxhtCgDstE6tVx7BGHEDDA71HRToVGZju5OTrB1NN8foQ3kq+W46QrvfXF8v1bdyl7oKglnteQqrDHOYXokvfR94f0zXG+3O8Q7Lhki9nBpGiZcwUJ27pBcVgkM7Eoj2hA603PUv/80pLvMX0ypXy8TRv/4sc/PYDOzfn23C1LkZxKF6L5e2jmCVJB9PeOr/A/dd7rYb5NMu9vtPc+/3ME9HeO7uHeK2P5s9e+uyVKsX4v+YGVCqaADYER+Xl5dijdbXEWkElNZzGhTN+dU2cWkk3pJmmYIByXI6EhhzlER4xrGavj3GcGrWWwxLMfShqeWM7hi/hUNiu705ZzpvReDKmgto4P2PHlj5cgf4qcP+I6vH+hPJxb0gO+MOLldDDAV9n05oCenYPADCSu93cYxJ8Ac+h3YeDev7yk4G1YHT8xnAhqt6ryEXT2wpMICkoG1QPaWIvhuidUq8tJAApC4dcMUoSBzSoW0lUq6FFiimGGph0KwT4GtgWGiFmJBVUoBmmKe4sxMWh9ZJ/WkfAy4poGl9ecmhlMopKbDtZBAZ5GaLxe9E1198j4Tfh8OkUMkkFKw+1lR/NWlafDR1XKrSr2K9WOCssblMM+0kD0DlLRDKJOeqOaAQhue8C406B88JWkkuoRMPZwmAkkqwrPCsGZVKc2LwC0tXTezj0Zxns8jRWm2ia0UF+hqhfqc5Hog8pgSjrzqg8akxHyKh0NBU7NTO6soDQzbNsF3iKp4X7suN937Pc9INozg74cEoJQBekw9Vnt2vs2e7AnzYey4hVks1xbs3AQwYBxODx7skoZrJEYwepyZaAzq4AEktcOHHtEsM3iO28zY9/NgTYhUsvxg4SilgYxSUSPUPAZPO8XxTiA6EUemcYA0HTAm2JgTDHqFZ6vdU9inXJfayaTH8UePdjjfBwxjlw7lYZtA1Qv6BpBgUhCifsdx8Bx7AU5zwQX8nDyIhp27iP7rjscBs3KCRv+Ji8Ox0D0brpsl1jXLRAO2uJAVtVo53C/h7GUwcIwHloldqwPqWS3Vw+Vcs7QIbmeFe9POP1FjpHWEVnjtf6L7DPLZKtctILZTUd68Mg5DsJC07CW3GtM7PDzQuOx+kroTJdJF4QJm1nasjhdUyQL7zwDxqtDjPoL53FWAIfcl3RqMrCmAphqFfUwpyQC2jPhYYxI4hjDJm9bxsbf6WQPyL/4W7M6SjGDbshEAiZlMLAL/lwNV1r2nNHiL+dZ5sHpODsDaC+Wa/ykd5h79n/2msRyAZxUzFIogmfKWVN0SBjqxzF1CqCgzWnMmx2ZLBDJBTCpJCEXgWdf+3ByZCWOotoW8D1W5yHbY5Tz3dMQT+Odio17OKchEkgwdCQA8JbnnPYYat1Uph7atk7JEXNNue9MAHWUxzwrjEKuORg8h0SFhzSBtgg8r5njtQ+qAn7yANR+mN8ZHJ7JTUVTiRgV96NOFTw5aGQusJlDMEo/j+DPm9bA5OiLOcGqsfpCMkEQdNJ6yXgA8MG9hJwfmVDxef79yCDRGOFQWdZyGc4yuthbAlQAtyrVtIX+pgaYYoihamkSnlcQCQLlLHapiiu2EBmZmEUo+5MTfxnPsmqrmv4HxzKh+edxv8OHoT9/OL/7w8tPkesQb1jcRTEeOrXyKD7n0W9Q5KhkTtkEcmtw3+eIyrZ4/dyciG++GXkKQTLcHMMj0ah6+K72i4TOx+rIt+4ooMycdFQ7epGRrHgCpp6zIjO9tz7rZ3Mf5c9U97TplDVIPRCRZDeDPLpcnyNPOfrIZ9+evCk7H4NGdIZWcIZjP2teIEXyuhk8p44gFZOotiWnNc9gigBMaGUQPVolbeg9g5QAkAkLZga0hV9LInG0qevQmQjOR+oNi0g6TQVksb1L9moiyuSceI06fmam3rxuWZPTNJ9crTEa54x+Y61Iw0BGa7zm9nzdlOkl60uWvZboJ1bH88rWW+81Oc7jPR6PGpN887Q3LvjGKSKAMIiFRUeaulzozmGTpTIcCav8jsmaLYsx8vxZ8SaTXoDUQcKnQ100TDLuF9KbgMlmyLaCoZTwPCzPKAqp93pFf8vEsLJv6qGkKVbXP/hf+BRf/l71LAdaY4DHT/yJCCSs7hb4rFhfyO+Rj85fHjZUvptUQFuW139NSTVG6ijuMwgpmCW6C724ZvItq+qzEp83J20EXUuqDjNA45g89/FNeD0k5Ha1I2QSS0wO3GU5d534ZU6WmxMhxH2+UOhlhuHxuWBC18+JWfQBx9RnVkHiEy3P3SOZIOlR0n8BkUTL0/IbuflJwTA/PfnNI0goUdy+RpFE//hcXGWMB5Sp2ljnWQnzhLaKl31BO7quLV3H5/ySr7uXPX7Snfi81a6pdyMNfIGNnnYEZmKZoOCmbRyp4yQ9fHbssYxoD1MV8u7M/mbgasrRR+qQN37nveeW+rjwvmVec9/ZcAq8JAuD/RrB+lUCrDDQf7biHJgV5wyc68P3VTEPoP0IqH4P1Q7495Ck8wj2J50vMpI5QL3/BTt+iftVpbkufExyjhX3X/4K/fHT8tT8TuinU2y946l3XHrHE5FsLBLw3AfsP/8G/PQxaOTURpEJ2MlDWvijPPl8ginMuSXbL/t6foZl7s9by0/0MM974Bu87o21mvd3/I4o/iRyXlH6T8DLz452dQyJpA8BquBm5e2qgt4U8EjIFs1EcGQir3sWbhmGIW2YlLeSul7OWyQpyGmcTD6AWfJvz0fPIDqLefheqy4z5yM/Z9zHZ5A+EAkcgh7f90S6dMdwRzsMxkIbzPFIgsIbplxgsD6KbMIHeV4t4SgfpPs85GEO/uFj8U+sd3bQL865JBtYRvLffLiQ3apkQjtO4h6YcVeRTHRZ5Pzqt199RG8/LO/7lqrxf+Hxz4VwL2Xzzwl1gSdk7mIAPJzz1vEMwZYb/sizniC4Y/Y6ByY8x7fuNb9PJXX9ZuGEJ4YQH3xTufwzx5MLXuS9rbw+DCysW5g7M0vertF6fF9uipG9CCvDsbUZwETCq9RomL3rYGexlsxxGKA6nfCcR/aBY7/he7ujiWCAQc7Iqh1jVIZbao05/1qbtqK5YIAnq0nVKxvydjBAG5UwQ8LoiNBqwGByLWUMuEagUiSD51kxcmQAK/qrewVASzmuwOX7Ey0QNISDq+EJA7fkQIt0fs2xUwh4Kpic/7fpwefKAGWwPdx8EVghfBWSlSXl/HdkW5apZBQz9czjdIFig3hDu0ZF4PHbgDeHdoMa4DrgFuarQaFtddgwkNmiCkkjiKeh8cbvrVVVvQCRfbZZIg/YWdhAAWwF1QacYUiMCoOyAkejMrRf0KTDhqBtEegeY2SFeTiYb3rLIKuhXzqOEdDlt/sBJC3YYbgdRyoldGJEJq074n5jRKB1v2Pfd+z3kVXPUW182bbI663li6BuBJ9RUIjb1rBdAnonnPlhpIwMItIuYV+fM6fz+psVc1Vpzm989utmb9CCBFqsJ8Fr8g3BugTJPJIVxu1WvIVODAAFi74aHRNhdTrxanRmkN5xf/laF8QyC7ZtcehRwUsexPsYBC0h0NWnSrTv9wiqMgibvdEFDjvC8BpjYOx7BdrbdsN2ueJ23HG/33G73XC/x9oe45i2LN9DaN8mhLrGcy6XDdt2weVyjd97jyBMaxPx4NiL/xz7kbdlFWxUYRni/ipIyMwG1YCgJ+yYIPbxcewYxwVwoLtD0AL+qor1HDgWQziiiakUSVR9I/YLIcdhBu0NagpRw+USPRxHQtYfR2TBhurKyaDlMWnU4BgLrdKRH1dF8Md8ZDsE9nezgg7tWwe84WgDrW/lxCbP/vryEjxeG5obzAdkB4YMFHqtZ/DOQ466eCQguGZgB/CxVMPkXgQAzYSRptEaoLcN1+2C6+US1amJhCGqgDl22+MdLCoStkTR6JcNTLoYWa7fMhAICYdbwOQHGgCDHdyc3GtijpY9RDmXa7V0HasSUXto/s5TVlhWyWSWUJR1aszlqE6HZ510vv9CbVOeTjs65plVF3R+5J6a5g75/WRG7mFosT9mQWpjQoeFvRgPYmKBwVOcz0CcIJNztuipPo4BHMCeMOPx70AWvULEKxjDv+fkTnnlJxdI8lgmcUi8Ax1jrHZlhcfjuj0apskU44lL0gRpuxa3pu8NKyfvKZ6BV2GmMoowZgJDau0+g6F0Mp4THegkm8/xXK8KoHMiH3g4EPzSxiidMCoakjc0yRYA5+Q6PpfylLpRtNJgYtJ0FFL2bX2bU3OEAyhkCaKaMhPYqqqRyVvesk1MZPyPMXC4z5YKY7a3oC7FILiKVg92CyUskW9GIR4REWgN2DH4UzS30ECodDLfRRHPXNaF1ehwhzZW1VHvzHUYVpnxZX27wzX5o3a4G9oWPNfSkcWxauoxLJSSHOSxs8cv0Q9i/ltrIU8ymUgzyLh7JsiOCJ7vGbh2YyJhVBEFagOgmvtMBMeIwEv0Lo3xtS16vB7HAR+j1iCSLg5AIuETqRPXXksyrWB69j53H6kXst/fdEChLe7KYmUTecnfNCWm1QVwV8/q55DP04k1sgWOA3h6+oCvL19AJBwXoPsWfHQDiM7E9xiJpOTL3hu+A9aS5yISp7qho2H/6hAcky6WkZ5fw+d+fxQqD2+KTDQ5kj7VmVimgWZDyGQzuAKb9NN9edfSYVMmVpCEM5f2bGc1pU6XefAwLtCc9ZhXLwKWvM/6nNkb1Ks6cE18CduHtxWCNNSzHnlXPEJqX9M2XtE2phOAFSUPydLrHJ8ccj7X9bQK8a8cboJ0upHn6AOKXCSa0cZnJdmaxFk2nSCcrpI6S+oxE2obKI616A5+avmQ+kDpCQs/y880dSepuZDoEV3rPye8bk3VBTNIUryqWKyAufuTVnD+gBdCKhndDUnLCpGRIu6cUDjXgXwm6M2LBvP3QsBD7GH+y0H6fJE5pHzP+tTn+ywEcb5m/WTRy3KG6nN583uetVJ02hjLehVtyaxqXgOFRDwqJKParxmUSd4jTH6W/BxWAVsFIpE3EY5qHVe9aWFHgtzfkklS+e/05hx7XSSvglGlp6QcXCdWGm3fJTiMhcY5yuTb04+G1LPSP1p/G0oM1FoLQBTICT5SiVLTVg++nhT0ph0ty5iYqMYg71kPxOnvSUdsdxO8e71WoDjsXpPDea2WeiLVNmccR9GcQ17B3lM+Pn4ewXOOJNbFyTupJ51ogZ8tQd9cYxfJQJ0krQDaeyQpH4Fkt+977eFhXhXlQTtaciw81bPSO0yHJXhOW60KLjxasWkG8Fc55K+DVPQ71GykPm2YwW6BoH24ht2SSZFRBBCVipFQSd9I8FXuvzGi57r2Ftfte8rIfJ/iQ2d5pL3ne0vSbcCB3y3Qb7YtrqFcgChgY9Jgjr1tP8DGgI0j9ql5VHJL+hO3JRFdFK03/P7//meNZnfgyDUXAJfc5/2n79CzgOMkH/N7lU+w7w3+19+Q2vIrEcD+5B9+/B73n/8W+UDa0mdHZKdWVbhhw88iDrhj/Po7XICWdz3Ars9vaVB/fDxTj+C/RW8TBK9sEOiPAOR7mP0N7j/UScMMJpE46r98xvY//hL08NMn+M+f8eX/+RljTlN2bhjF98fxK7x9D/v5c+kq7ZfPaP/xExQR+N1STxCEz6NJ2AGXtmVVevj1DwH2EQUQLXmV2V9h+D74rkewVUQy6DN1T+6HD+4YDnxJIeZzm5SJjJxrFjuvMnvl+f74u2MqF4v+UF9J6kkl44EPtVdDJpiFvfflvwzbE9Ah6Jgtpshhw6+TCb+kI0EmImYyj9K/4YVqF7/nqAwpYKb+IDnOki2p9xmQPrd5xHlZha5r4uj0bbCY47Bo+TiOI/ZC+hDXm1HOVyJF69Ei04DeM1lCARwj9u+yrzjtnrSouVgj/UmWCnXJ39TFKF9jvWiTnvWiN/eePH5w/viRN7x/lEb55n3kne/fO8i7rtsl5S6Cb+NIG+ltDfT07EVP+KPnPCY3vXXe/43HP70CnVp2KWiSyu5bE+3A8ZD9tnz1zcMRuuJvcFyXe6cqWXrk17zT312FvhDwKyf0n77+/ePqf7zF/ncfxXhoYLtj9jaLYyoUwe4tqzQcIzJ6V+mTyraKQrti6wEp3LYONcNhB4DsH2uhpIYBNfvDTYi28wyKsL9vy7XPftx7MFv0cJSKhmOLRgErRyIDvqFlUJnZtlZwzTaDNJb9e5dKY+CP6SAoxtG+b7DPxzfPPS0C7Zjl9lUxg0dKmp+89e3j9XXj9TQKehpCJgnPEofSUVPKuMG8Qcyy2l8gNmAqEEtoaQEaHXiYFZ5aVQqtKoIJqd1EIRlI5BsRapVQrycHAY0I90UBYnJHBKithyIcPWIi4SKCjFoJH+OIQN++79gzmK6pdDcVyN7ADNn9GAU9c+wHvny9FRwTFZNjjDBWFkf6sIF97KHs0DgDIF3h+3FyjEflZiiTNVf/H3Vvut7IsWuJLiAySak8lrf3ud39/u92u097e7YlMiOA+wMLiEhKZfsMfXZf+itLIpOZMSAwY6Ht5VCO2DbN5FN16brjc53mkTwnAa37X5VradSf5HVq2xSoMp9QAhSO7D6azlhJLYxGXu7dsDOPT1in9XUfx1wTAEcPqNaorE7HC9CPOzZtgSDBtdAWi1s9rSHQbRqa6RnrhOLv3L+2Nextg5hj0IjtvRN+mFCzrw3X546jH7gdB477PQLx5B3KdRKVgJAEJqynKNrOKuXLFZfrBdfLE66XS/TGJqx7IBd09LFhEO1AVWEjqlbdDNqDXyX9C0LhDNjMBpB+UmmOxCCBjQOAQbLVAkbRUvU24n/iDb55GXFmbEtghm4zeGF3x35R7LqHk4ZBsd5HGI0aCvEoevBypKWTMBVnB6p3W9FmGv1gQk+O0FdYwaCL5jtJLhJ14szG+XplMGxYjwr8reG439lDPasOKXeaTge4GdoWMMZbS5UqkoTyAJg5tm3D9XrB09MTnp+uuF6veHp+Loeyjaiyvfc7bscd4xhwAS77XlD7l32HtuCBw/ZyjITjZZpts0JpZuOWY5IGSPaoKkPdJkR+HiyBsNJcysmCR7mfBhLHuPatTAt8nvVpfOU5WAVaIDvUJM78hXNwRxneKi0MvYVllCGzOuo8g1oRRA8vyyNLTEetTmOJvDzXBkQbiIQXDVQVj+SfbFlyEG3CevQP1KXSPvUmvKPP5ZoEdN10YmWiSAWTKe9m7+d1v6ehsupiACYU/F/QT5NnlwGZsr8M/ZhD3ZMV2qtTbq0KftQSU99XgOWlHpnwfLhRH0POk8mRQS06f0+nuArUdHE2LQ5tz8XlPcvjkQF0Viy7Uccbp0od4xqLCPZ9i1upQKTT+euTn2yRlBF9y70cC3E+Nrg7juMA7hMGPQIdSwWzAJumrI+g7bYzg94jyTODSpHoGbCGGRycxIS6f1XKLRWVlcThqKo8QfAIhcIIsyAIWZkQ6m8IZSGB0iMWGsqkxjx2yRTX6rpskzQHTZpZeEcGQaoFibSqZMm9jeRdUA5FTzzx0L0GAx8ww/Bw/pTdCaCbY79ekO2gUrcfxoIOymyplhhA9sjNYDTZY9CsGVqLno0pn4RrpiLwfQN2WqOZQMgzD18r8//ktei2+/UJZgN+HPBhuN9uFWTIqrbejxj77pA7CqkG+7p/5CeWMgQ1vqTX8QrIJeYOZVGjKtpTw7gBdEGvQyySOYcx/m2vSqpCVMJg2ILMwmcI6hp+6T0X0HrF2YYk4T0GnKtyEiETI3BSB2pet9B2CcASdWmzLn4OfqwlD5PnLQNMXah4G04Q9Hl211k5dSes9p3ktVMfOD8I79pSWK4XorCkExWgLSJzbEgkkHJ6MkmUsjCh20UCktjcC5GjbE1HQET7J5x1qywTWZaqGMd5HyX3Jj4TDR/CyeZYdJW6/7J27/wZIkVxctCuQzxrMl4/sVwbYm7KOUCm/uZTxpedVjIfSBu3kuuAh2u89LeUZaeHL3N/22KutKhPvvN4tnL8cjqF8ubKGfTGicdL0rZgBtLpIxAk2gsCyUiFnSRkVqk/nl13BiEXtBMziPP8qECYuCGUibaAGcaihZewbIAc9zKrPFPr/N4uMEpeTJeLn+mXAdOo1J3u8YQPd89kxEkXYed4jdeFhQ6J2lNC2UHYmeISHOy8d64Z1uozOf3z+k7e3CfL+iPZlVDP/JeDU9VC3Mqlin7Qkx8kHWfikY8B3bLlmtR9ay6lec6ZTv60sG3X0kHEqRy4zUTdEn4ovWT63PLA0HbIJA1Z6LtFi6ZcO3Ovql7P9ZI5tpKPKQpo95Tvi7ZdIgflSXPKZ2QxT9otyU/5gKDtyT9mcC7+9d9egedr2cguCcfNfS5aedhbZxg+lT1ddKX89mKj5I9qVbZyHhGMgwHAE5+vIwQRzNZHxdJ+h9sXON0/0SeX68pGRdDZh28/4uW7H+oMElwMK98a3/8G+eaL0CO5lo41OXom9UeSJN7UtaYO8esPPxcE+ypvi4brs2Ws7hg//Er95uwPGQvv/ivV508LieXl6tRDlvdSS9GPQGtfIVAUvlyST0qaxhw+xqAFUgUEEOqH+XD/GcBXnBMA+RLTLHa4SKWSy7IGCQW+JZrftw37fcO+NVz//jV8OG7/+3u0jwOvx+cYHv5a+96Bjzb1cPPyYUvKz4f1cdogU99D8YzcG3O8PQN/VBDq/Nyn/bPqdbXij/vnwccNIZc0kUiTDHXy5VMBBwuDJu9y6kACtAi6wzxQeDz9gBOVUEQD9t3DX5RkqNT7bEgRS+me/Kl5HQRNFJtOBKKck0n4ncSCfn0YRh/1zypJfOF9YAvZ1mCtwZphd0c3YN+CdjCc0U2HjyhCedSBnLxcYdPHVYiFQOnNuSsyiwEA4NxK+g/2/B0S+NRr6gtpL57l2Fln+MuP/PRYsigIgRxaLP4vvFQkfGn/Ca9M/v3Pudt/3eufH0BflOz3XmvwJw5R4O8/wsicrBTMX59591TnPoPgVzg+LF/NYPkVUZEuy/f/SiA9g3I1juX7yRZnT0Uqon9614dnALjxcH/mgt/+7AZTpzs/i0JhMu23c6H2HW8sApAIkoBEkKv6vEoqcbznwkjzmak2pAMzoVhUFbo1bGgY+wVPT1dkv0Acs2Ig97vJ4gziwFI9S+Usna+rs25dBVnfk2Cc6QQ/7DYxZ8zKsBZ3BsyiErkbe1cPY0XooCKzwIcsxk3CTC2qMQyO9oXi/tOBgdda50+RXM65ORURycp5Mv9lS1dx7L4o6gu8lMOj51pCTprF3/AQQLoQz4gtDD1xGu0KhYlX33ODlxMgBXjAbQ+oazhDJDIFzR1qPmFQvdT4xTgORUn3rSCoJQOgwqQK88rcDsiXaZAnJE0uiNFBHbDuhuy/szVCWhPaWoROiBHO9N4jKHo/osLw+XqFu+Pl5TXWBaHcdcsKQfZgdhpHrBwcYwSktwXce8C3R+jACLuV/U2EFU77tgdEprBvIqvTmioulx1PT5eA+96v3CqDHNkfi8oQDanVkXSymYouV40w63Ky0mUJqZxolPBHcFwyI3ysZgOmoVnfmHQZT5UTr/Lle+n8u9/veHp6mgZZGYV6mlewmFEK3RgDu251v8yojqzIMBD3bQeYwSpgEJVnezCDUwbYv83QO6KC+mClG/mJKiuwa83B9gQNKjSuRIjQO2GNIhgQziDVLaor0Fj1Fhpqa5FoFL3pG9Q8goBm2FojYHpkR4824BZVdKLAtjdoY8/ztnENHccRSUAJET8IMzfGgGoPGHf2lTLzqjaK406+JkH/3XslmvTRY+16ZLz2u+FyvdZ6Hcc9quYF02mm5MNw8BiXYVrEWrw+zmcTpagyOtgAR5w3AHHPhK5vyjhfnI3Pvvwc95dXiCiOy4FtHMHLq+ojeEdV8tS58HJk9XsPgxICQSslO4Mv0YNeika3fUfbN+xPV+z7pWBi98uG+23gfu+BRnE/og+eAsa+b0He2QesQehwikrFqIjM5JQ8QT6CDqcDuwUsf1ArBMK+r4q2GE6PQdDH34Hg17G+rOBMh3g6s4TygrxYeSAXE2bqIrTxLHlRVs4Tr8w3AAAgAElEQVQXj/J6ZlJCOX4e2FHcjskqSa8+JeLKK1YHZjirFdnzOlszjNEj6ckAEUKX58/iKS3kiTQkc80g88meptHrbkvb4xyjUVeM99xnUgM8k8TYs2zkePkzK1LmDXi/fN7DGpZebW/fAwMWEjw2E1mUzFUWx0LCas5g+dSvJh1NMzCdpe4TxvPUNoebMmVX6FbR15E66OKgi8Ql1PxXZ2GqcTWudKoLA6o9eq/nNdl2B5iBqXCoZkU75VhjdUMTtHYpnVlVcL0+1dq7MJCu4aBL5CYbgk79O1Ey4t6x70LhWGsnAXPPRkJFC6Oqsmdg4U3SZpYXLvebFIeaU1ph4cdViFvoa2wZoELECjoibLD9EQOs8ODH2qIqufRQjue4H6c5EtkU435UtNHdMVh5PtyZ9T9b20ACcjPhGOMzyicLvfzWo3WHj3CcyBapd/c+GPw2Opvo2G3RVug9i2xkAkzOw8Lhs6pQTaaDn6rKXFfKnNYak05HOZIqMVSxJBzN87m+struwYzJp5zHfETlmrYGd0FDVl8sVYWS/Z6BtgPSFX6ZDvgYO2WpZTuTJWGY18mFVYMQti6ZjnK9KPqx4QwqmqS4Kn4+Z7Hwn7jPO56B5WzDnU5cKXshnXPDInmwHIwJkb4G0JbzUsFnnoXZEoEJJToRuQqZIpVYn1WU8R2U/FSiW5FdVRA50SmUiRMT3YZDLX14sYkeFnLys5leuiaTLNOcv+sbAjrfcyEywfqMmfR0inC9vUU8KhE/1kumWVFbnesSsj+TOSN5Pb8/14rIZKxan7c1Ti3PNefBM7POoRZ5ReJLiCZHoEGclImHQKzMtcH5MlTybepfxSd0yuLcV8pQSSJdPJdxvij/wGRsdzZl9dLRsgo1K8tC/llVkRqyopRtTlKfOk2H/pMHBeo9KvHTdYvMkmVd0s5baaTWfU1kID3pPGvrNQVjneNLHYP/vOLkvCYD50BVy5bOBECU9GQGZBucvI8Fp3HXpeAjtVMFZFabCiRBt5BBrcezd5Lj66JiXZb0T2Uw9mGtixHn9xQZLuPUUOqSy+RJU4UKvi2ChA0/7ausetn7Lw4vEO04g23bSpcCea6PieYS/qRJx6h1eivXii48xzL5eQYiVeN+M7Edpfvl2cxAz1pEklWLoum7SLpcduNx3U+8bd2bM+MKueino16Lm7pU9gZuDYBCxrT9abicVj/P5uhhN+dQWyEaORGv9oW3a/EKYaKBsR1e2XFOTZ0TTnvBxkC/3SCXjfOKW95/v0GvG+TpgvH7K+TDFampJzITIITrBtZa2/JdIZ+FqLzHpNdcybZfIKLot9eiETOD9YGEX8nE7thOK76/JgRtXI/Re5oyUHyGpsJ2TCs/T78gQs8UYNsvcAFGP8q2nFdHgKQ5oB8F8A+4/fwb+g+/4OmbL8OeZ/tGgRTSlZnh+EogP/kbtS3vfzFg/9uXcDjsH79wvwYTRta9kwV5NYp+BJ8hQL2BgdC7Dz4n3cBP/sdB9LXiHKAIxKxoT3++LFTqPwAdP6F98xWLeARluMfTIaKw7wH5l+DHTRvk2y9x/OMn7k3cbfwAQH/C+OZLaFOMH39NEKySDeaBJOWiUNkXP55g+/Zr7J89Q/UzbN98hu16hUDQNgX+5Svce4f2XzFG6Fbb379CIJ+mbAw0qO5RwCQ8yBuA7RvFb98FoPeTswqdtDs11OXv4iNcKffo3Y48BVLf9JNS5CeZutLKWW2aCXEOFol42JJpfw0z3H1AreEww+7ht4z5J1/F4otg60ZRRLHMbK0jfI+jQmsNW9sCfZM819QgIwAokzWrAn0oE7pnsDxa+1BePEic9K2FzWZRRDJ6IKfS9gu9PWVQ+vikxrttTJp24HCHSRQ2YMzVH+QlpQctO1kcS2bsb/0JSErdhdXHpr+xT/7k9Xj9p4/opJnTuzJtlvOlf20ki1aGpq349dYaOtuQAUuiC29tkgkVi8wCV2Sh3zej4CIuEvTdScvDz3/r+//WffjPev1zIdwlD/QUbG8zNuOVZJ7G/J+9PudRPZalTVP+edmO7HteDuPlvT98nRyO+dbMBHx8P78Tc5E/OjlvXs8ueNVJqH+xVvkvvd4e03eYgk9WErzHIouUWVzvOdvf3IJioDIeF6Vmaw3QKyAKt4FhXqgdvXfYu07e8/Py14gDT0ja8j0tgnld/Ay4AwFFnhVnOVlFh7eA1xkMevaC82a1kkV1qePcQ/3tugoWfoOOF9jPTzN4Hpe9+3pc2sxsPD/i8YkhwGuPF8V9QWNB5jAKZFYrhQYzmV/CIGEqaamQl7OCD00HayS3RXYZusFZrScyMIZMCWWCtkQZIkjEij0VOiF3BjzZ5yx5hcdPXReIt1bRoJ/R54Js0wgzWCmCAQUZAt8AHKOz+ij4zUEY7nvvUTkL0FCPuasIpLHfuadTeQbVWIsRyvU4cBwdx3GPCmL4CYowe7iIyHQuEwJ4zcpvhIdt247L9YL9sjNwG8ZBVirOZJKkpaSKPJcLUcpUDOVEeEsm5rJPy5LHNYJwXvPKvEc5I5ZXGbtFOPFb9h+XfJiEAiQihGpbncFcIzrG3AGzTthRKl/sb5PBanOjA46eEFPc+wEgWjqMY+DDhw/49ddfI2CfBo0qbq83iAP7vhPWP6CGVLUqys0z2BHKZvA3lI1djj3M4G5r2W5CJ9R6awFVtelEZpAFVYObmtVX2VsO+744NcKxuG1b/ctszICTNYCVmzoMrnFOi78n7zWvrPmkGzOJBBgIRMP4PY477v0oCCbzAYFi2y9R7aOC4WkirJSUiQ3hyIJ6VZlMWpOyxDOZaxjhuDWrT1ZnHNeYQd3WApI+HXb31xuh5wyNkd4MaLvoKZMfJ1qdjhDVHSISPc0oJ9fAZrRf0KhG5biqoqMxiENelhCAkX3bud5ZmTifnn2k4useBbiZ7ps8ZAmixhhohKhEEAyReVvBsDEwCBs3Yd/nGZvZtw+JMLScKlCkuQcnhhPva/AHQ8CoxbRWDpBcI6vQ+Dmrc6fXnfQn6UhZP3ImGOlsdcJzUJXHK9Ulb+KzPGUeg7djjICD7oOyEXCiGkA9khZEKkEjEQ+CDhYn2/ry4A5qaV3kM1NEp57j9Xui3rhHewGHVTuSdEytTtfqX4bki1N38jwezkD4WrmcayRcR1m+IGCvwNzeGP85qAJkrYEDE14fPNcI2tRtJnq4Z+JGJO9Ik3ICGhEtwombQQBPIph7ljyaVfonGs2fC6R1JbMdx1wPMmiFRI9xOt3dHMHFJr3oUAwPJ4Quz4lAmNLJQbkrW1TwC6hHJU3MoLw2oc479+jNy0nzNZ+oIEjjXnKOSRPr2XKqEoTwm8GKKbsBwVBDgwIm8DYTFVojpB8TH2UJkBXZIWkK5VdNONHaEReIhH5fJJPQ8Lm/ZWvMkL8vZzfPhJvDNPTw0eNnH52OGIu2OkwguOyxLr2nPhww2eKK7ekCkUyGivGt6x/bloGm1eaYenSdC0jw4xaoDdu2RXKbBaVk4vC2bdgQDjthBZ1uG2QjRP22QVtDvx/4w9eDXZA2kTSlDhSVb+WMbRuk2cmIzKqKcLDRSWceugADE5molXzE4fBXh+9etk/JiERl2RX9PqYuifVcPlD4ci7Xub21T9/5GttrwWfl5Fk7TQ1jlV3k0WEQTR6x2DLV1gOpVkjoHdqQcMVZGf2wDaWHqEw5kDyrAvSy3P/hd5d5JvLYOlCILbPaaLGFqJMU6lQNyk/8+d2wmQjmf3gzLll/z7Mgcw8yULXKluWBcR1/rsGd4ueZ3DgiGdodE92Ee9E0dOlE46mccQudW6l71OzW/ct9zbWqgQpEHRoYnkxMT6E9IfHPCWJ51Nfg6dnGymkXtyH6xSMF5l+RukdZzGdPOGXKt9TXKrEskt6zlYul7KvEz9mWZ+WfZYMAtd/vUPCbV/H73ExZP+NmkRee77qGYebL84rFxkxaVkmfoNTfmjSuWRXNQHvCRy9Q0xVY53JmW5eoNCfNCgrCFQ44q9jjM6mkmYyG5AquOShFHzkDyZ9nujltOpLPedHQPJ7JB3k5g6QzkTguNHhVNKeUXH1q8ODHTbMn8OTAOf/il4/OpeX1mMQQa8oHGWXKNNIWm96XYM3D4jy8fPlcgJBXSNmaCUbUh0+COZP+ksdK0Xn5s5L1+eL8TzvtQbLkWqReWrZB6SULT17mOWex6ABYfzKQqoKGFmdUo8Cizr+F3ri+2taiUtzDT1U+G85FUs/nXlarQPKBOaccxuQndrtDr5daqeU0YrweaNcL5Pla9lfW/4RYmetWSdGPe/2O0M5rDI5+u6HkkvkM3LjDjxGBcUgVpkU7orc+dwDY9h3H/ecYj3628BBE4uJyJqvVWdqYgqLTd25d6LSCD7CffoMIa4lETvvlHi0bhb/7Tyt1LHSAiO1t33wRbxsgHz/n55l0zME82OAlq75hAJqvN37gP3l9cFTv9pzBrDgPelcQrh2AyBc1vqTlcxByPdcO/bjIyxIaXI/UcxaGWcmj3Le0qRyO4x+/wLWhfftVtF2VKU0UAvHwiYVuHS1kmm9Q7UiUD0XmnjmrraN9qCNs+tFZJEGdwH+MJ2zu6MIgOmeb7R0ctHBzaqczQDk/mXit7OlFPpN8sZI567KpIRgYp3BWlBsw3KA2YN3Qt4GXptgYlxhEn+zuEI0CmbQBMhk9ZWy0hlSMQZ1VUXxCEEkQ6TsMpMNAxdNsoxACioUUR+jN/LfRh1nFb4svqWw4tk0bLFjoTCKaCTuoMx3jnRXs3lImKAyCO3mrDCsaOwB47zARiBnRpqUQ72bXyCnL/eHn43s1qPeYxn/olWM4y6gZV1zsLB6jf88Q8gwl6sowQ2tbtC1GorbMl6ZufLqJRAElfd2lUr+9bN7tXR3gz3XP/1tf/xdUoP+h/gaAjKV0tjO1WDGdVTmKCgbxqCB/gpxgVBpCMD7z/Rc4rvz890Xk/RFdJoGlgJ+C/ewYrrP573xdH0ZydWEl+l+765RTIZImM5jzPIs/0EkwDYBksqWoOeA2AFU0zx6QlV99mrR5/G+jhKYaTHgPVh02xS6NzNlnFRoFTx82EQ6zqnPZd0coj4NjT1jlqBoemdDIvruA+4D3jjEO2IjeuRiLIopUQh2NmVguWv0xh2f1+WCFqsMwoUb8jWqOmvz6flwbwfMTvM26cQ9KiiMUph3PMOIjpHMmjY7TIz0rwvlGKiDl7UjnV9LCRuwiCvZSejMIzWpYb9OByHsFpMkR2WAvCvmgGOMFEUh+hmNEtTqVmKiwDtixdIqvwgpAOBVbQxKWIKHbqAw7GATP+cU14cgLATcwaZ7mz2kPhHQUEKthlG4SwfDX2wsOY4Dp6Ni2Bqjhfr9z7aUYWFSKUZ316P952a9xbwr4VBBDYQgaD0cHq6ZpNHSLaqXoxemsTNbK2GsJSSWRpdwInRyVwuyPzR4wJ4pcCHB1sheFLI4VI82GzrhSrjzeqlbz6KG4yeIIr09lNUbnuk8rF1Mxrb1xOv/TiBfcj17frf9yMeBQ2RCJqkFTSgj4trWAftoCxjwD0nlOnAfU3fH7b78FXDp7yAsiO3xrreaVWZuqEdTetgukOdq2Y2AEBDwVwYCelZOjJB2PjdW76RgMxXNDaxv2fcO+bbhcL9Fjd1PYZtDjwNAWWbltY/a24ziiF/DVHCoN+xYVgdfLBoiyWgHFx4EwNBuDzz4MLgPYw4lpfTFsnG01WCFgLaDVlJV0x3GvnvD3W/zeWijN/bjDLGjZBnllFU3EM1QF5pkRuxhaPhW+dOYiz51HooRZtGHIs+2sljMYmgvgGg5MZ7WcxvONEMxta/jw/IR7P9C0YYzYD3t6ruqOckqXdzcDfQaxWRU8hkH7gIlC3SsZaGsN2RMXHq0cYNF33ewVx70jqylUW1Uq7pcLWovM6+EOGQMbHIQxKGdOniAvJJE8yWHsm3rwbUdAdlnwq4HsE7wEqt/xBktYraeDHwZZ9qEk/aLqZOqMpB5xkn8WAZpa25S/Bhq0oxKS4Aj0FMKTZka2VSB5Dlk0rlWk3OCPhDkzOrN1fujLPcWN/ZQ7+ghEhUGaFVFYC/3FxOHJQyK6yP2KNgHqU+pkECoNQRSvQc1/dZYbq+DhGTwfVaVgvFdF3MvIJAwXlnuu6yI4OdJz3qdIxYlll/uQw5Uifym6o4xII0nmkIS3jgz47M0W53+IVN+kURX0gMiAopEXxz74cHgzmCkN7l46T+pUs63OWR/PxBQVKT7uTIiLtd0ZaJXiv2iKXbdo16Hs5U1HgSCqW4M3Rp97UcX1com59IFhd8CnCdyGYdwPDPb7PnpnawjjGRG0bQuUo1FMEWaOnifJHM5Oh6XTiQSKgUeiQS542SJWErQ+E2FiH5GGSt6TgQhCxWsIXmweLQtcBXsbOOiY0a1FKxOMcPKnDsf7uPlSCRjEt8rspLNMWAGroqPtiBW6QyXzpGMYQfZjDNKL434/iGhyoB8d2Uoh9CDDtk8z93Ld0e8HnUYtWOgwtOsloMfdgEQMldAzstq19BXJoGW0FUo7JvibUqeNM5G6mRM9otFxte8NW7ZlUQ1enmuCJWjmCB0wcparCleW688nNnSKWIdAWYjzoqxkSp4RV9s9xei0XByAvQ4c6pHw5AB2h98WB3x+/+bAHvuU3VszIA9VbNcd45a062/HGof1pPM/vh7t0/XblRzKJJytxbqoTJkz7Z55t6rYXN8VhBNJMilx0uljcrgbZf9Y1zNvSVrXee/UtU7JaHnmxJGubBGPFkQu1VYh9I4476Ez0l4helK2Bwn+73Dvwe/8/YT+P3pFa6FZzVs0v/ycetC0q6Is1+HK57nX+NUiKVhNMKBQnYHgbPHVe8qt1TbzCpwqqCdTJ4pgOWmRyB7ZD/u0obHqOZF6v9xF/EVbtILRpG2dbvzcUwDVyuQ8Uv7FjT75VU+EfbZ7UrqKAprJU84qfM8/pXQADCyJG+u1axCdP1OX4NgrkTAORwVkclhi67rP/59ei4xY/nyz3o+Lsz7qHFjJxYhflLpR9jmHEI5WMZP6FTX2tKuz/3kluciSoLJEuxOporbLnb2UAUjY42uFa6LtGX1fj+w2eYuc3pv2yTvs+bQ8nlHJ5UKnLsZVQqIU5DkjACNkhH0+6Yx7zHtOlS7OiTBgKLRbpGWVc8rsfCIWBz3fs8gIK94lTrS8mQDYe8e2bRhHtFYrn83DeXmPF+Xz6qWR9BW+OPJuXXhmyiojSs2yWsqxCJEklPJrPiN1xgVRyM88fHUlV4KCP3xIHV7Ie1InO802q9ARFde6OXqPKstxT7TB4IUbdYy2b2giOF5uEfwiL46+5+QfayKoJRralM2xRF72c1wanw0z+O2AXPbiRlLzAbYPETR3m6ZeJJsu/enXABZ51eQD6w4/ngBn+6zQMVP2n3z6FnDL/X4UEmPbdhy3G2Z7ExBueEL5t/Y5HEDjmUxUwPBP0seYuvBiax0vrzkVTKrgvHNIEoES/fozjJ+i8lu3Vnuf9O9ubOE2balEC80u7dkqdqdf7+UfP7L6+zPgI1u5EbL+xL85qjiDuow5Xko+kuP/VPX5Z46Cac/zeOJfELSPgOiXtJmcOkpcdf/up0LxEZkJDplcvP/tq5O4C9XM0b75EiLA8f0vycaxffsVXv/xE5PhBA0MSEnqEEBHBH/HD79gtA3636+UhxFoBf0tfXQC94R/TjIzwq3Qitwdz3//msVwwG/f/QQ7BnQYDvr7FQL8TbD/q6AD2JzQ+DLns67Vo181NdkV/Wx+PFf7tD205fKK4cBsr4G63hG9zrOvu4+B/auvgV9eITfgeRiOy8DRFHcVYDQc20aES637ZCDZNavQIyi97Rv9A5Q2NuktKr03JitEAL0xKB86KfW0JtAxq87jPa12mTVJBs6zHeUYo1olOnl/1JQxWSLtrNTrIUHITYNqxAI9gLEFFybImMPU4NoAG3BhwHeRbyU3H9YbwFKxzncXmbbqQZ+Wbv8m7fuddyaNrWd1lZny9mvv3Pp8UfrkSGqnv+Nhc87TbzfnmL+ljARJ+N0VWN781Cr9R1/nvfive/3XB9AfZrgqtH/ta5E99mi0rvZKvtaczXWB8/0XOC6QUwX6v+dVGfzvvZ9UlUrqo7H98DothwM3OJ5y4Jgw7p8ezMON5mDi7b9y2P7gvk7mndVAlTFHhfFRQPjyL28QDiIOUwRNN8jGqktJ/moFGwghUI0B6Vw6VaqA2dojjKLsWd2Pjn7cKyjVjwPDe0BVmPFnr+BBKOcTAkkFEcgEoDKrocYgZHtmgjNYg8e5Ys6xlNiHjcnsQXvne/X9h7UUAAMvJVze26dVQzKgIHrW2mPgXB2RbFrATF7F2RD0gLAMR2yGhCOQe1IYHMCTVKDM4Ow/2aDSo9exCmQwmKyh8CiTMQCZAdOcjnvAsEk4NjJwmoc5HZjwdKIw2L6nELJJwwKs2aMCIFCfCVfJZIj7ccfr6yv6GGgagrffB523PrMW6WtTCI6l2v2yXdB0C9jkRfly0PEBL5iqgI8FXKJ/tDmQPdiBnDum0TW8emsCiIph0NjpTPAoB8tbylrfOWeTopjEyotW4ShpASUlTespb8h9elDP+ecbYVfPe3Ny6g5Jmw7gctlxv9+RCRwl1HljbdGfPum8MXiTWZT7vlEZFDpQRlU72piwYU1bQLtvk++E8jjgnnmMgLS4br9GH/p22ZGwSrm+ykD5uuZmNgPwmeHJxc7+rhFY14BQ2je0FgE8EYVtIxAMmNhjm0G1Q48IlGtT2AhHxnW/hLFjcspmTeO5jDKf/yKRhuvuPp9DHtg2BQxoZhDVyXN7x/04yC8VW3PItmNT4H6M6eCTeMY851Gp7ZnZmoR3Iom0ZlbnUQzcSaQnJdBjro2/O+8xgzLxddWGtgFX3TBamLtGx4r7Mg7KnUqWMof1jkFo+jAKDF07YaMGnXvK6v+tlF+3FcZbIwmLToGghx1tD9pqW+yjjQFD9IvXhf9lJUzNPSupJdbXiGBh6mjQCCLTEPJMEGJQzfn/Nwp7OdCm6S1pNDUNKOlCdVi3TKYDFHQ0ldOJo3aanQVFygQL6htwMOHCi5cON5hlNjhqTA1Z7T4lpC/6STmg0rPrXlXxfMLMhubPo0dgrmmDE1FAYXBr2KQRqj6QHnI/ovfyQB8ZMBhI5ACXrNjzml/RMdlxtrJx0rDbwIBHRYjZ3Kl1PTnfzI6vlxfplqOvrs7e0LX781jlmcskpaIJie9Ftf/U+kpWcP4JSz9lA2jAWlWH2EjUA5uQxqA8tkCx8CFom2BYx+h9jYVwrTJJwUqncbA/faIRLMmX6Ugzi2Skpg3bJc6cMmO+tYa277zOOW6g96gKDh0y+myvhqQnGpEZMAwHelQdD0NTCfSZPmVN0AR5gkY2eCTjBI/oCHjnIQOpMfpwbNetqo7iwdPxVLxuMDu8RRA8eH7sdxnQGXxwQMHWLxr9NZtr0F6LOTXKDqFOJ8kb1vOEhZyLpqQIMOBNSQ5uk/87D3nyx2QiHuN180iUNfJaVrIe90T0oVONtyLp8u9ZtXV5vqK1DX5Y9W3elLqnxbnMphwhi6cDSAQQ3YqnNyY6TeSJRCWIa4MnCsQDUDmT6LZNsW1ZPQPyYy+5m79nAuUb1QhgANVCH+BZGG6cgxWySBJFJUv6fE4FvhMSkvQLsL8ddUgMUB5OhuIYcDHgpvA9nOOiZycLRNGuDrs1DPQ5hhOloHSRk176MN+3Nva8S9g4MQaFsGjUH1A01pvJmzuVzcR9P12TCehroInHroJQyyBnwF34vdQDlfaz12PqMonnVD9V4Rmos4XTT6EdE0mKROwSQ4APSbkbYgTnlStafpinkqZP166OxnXFHIVuI5JrM7U54WeuWlWvCTU+xohzpJHevAEhs3Xen+7d0JE3RdvCydu2RjlMyGA3KJMGU4699Ss97qmjRKSAyfuIgL7PWSzAYHP9pb5e+nMynDUXzd/QRB3F8yvPHHUdSf0HTA6lLpS0UBDui9wvCHfapfA5rukvwbJHMQ9JPToDzaU2PFpjjtUXcDpOSUeYfKjIlH9MGjpPPTkmSMslQ8hf1/Zc2RvdZSaOrtsq0fOp5oh8D4t8zqfqDG5GHCz019i3VJY8V6p0szMpyGlN8kzNdf6DVx7MR2Ig7RkhzKlmkYctvFWn3HREQGQSWugCKXKjCl/m0rpHVEgdE2s4dYMknfP41/7zcdVU8HNtzSwgoFvqFin35+TqvCxTPwXrF1knc7r8W8vPlmM6nWGEbavbFmeH34/LWOSTQWg+35NvJZpV8mUO3SgY1vGtw5L6f8425z3l3OlKQSQat8ZkUFBX89JzqmUFfYttb6dn17pVEliiVUy0wTyPToZjrFT32wG97nOMyboeaDuJOkhJ4K9At99Dzj5fqS9hynNuQtJO6LXzZrkiLaGkJeXBfK67V6JrInlu3EuHYZhQ1/aa59Tz6G9Ku8rnzkwGwRPjguFj3ZzSR2XZ0fVnzOG3+QUqALO9UNx3tcHy9o2T78tRmAngNOE/0o5d0d845kwMThlVtg+Y6MrdzCD9nwXPFemynP41AVg5/kXx3EhESs0hE27OAb3HQPHkH5FUK+ZMYA79Wh1of/sCIr+c957fNpGZFOPzfs69i/2LdQ9ffBTCja7omHZDjTplKuWBm2NoFJc8ffwCv/+/3zEhespIFYF++yW2f/0RHUsiycN6poRY36+/VgF50gNy7WRZLFRCdH7BPOIPj/JWOCd4zP/1X7/H5//tW/hPv0PccYOFb1MVY3cc8Eo8fNR3mrewIUDZx+wshbw5WxVAxwygWwapnfJBAXFFs6VwIZM904bi2KcfcZwqz7MaPZ+tyO8nKo1UGwDRxrVVQAwDgt2jmNEQSYU2BkwVrga4BvQ8ofwl29RRVkkeLs+C/SUAACAASURBVCw8/nHTH1+ky5ILf3Z9vvxMIqdDxDdSqpwSNRbpI8s1/9bXzCucfsCGbSbYLeN4b3j5bqMd0umX+BOt5+018vjG/79e/5QK9D9cs5WPvPchEIqeyANjtJNAVhX8Yo4PiF4onczbBFWR+gTBonbCIXiG4GUh0DlmeZeQz+R10vaA9fpHhXT5ljz8O5+s+PuZY72J49kFLw9r9KYovRjzMsF8Wj0kgozrF2eF0uMRWua1CBqngpWv4caMP5lZPpT4KYTOSnI43wOyx1lF0LHvF1wuRyhiCOhsB4MRi7AzOmiDyQ5013J4V2YTYSq6TUZ9Hwd7mYdyomM1DqmgiUE9sncNHcMHumfVefSgNPdwWnk6rc/KU/2UE3W8eb39jM5JPMPwghOtzS1YN2beKffb+L4jAsSxWYQgmpcKYt9PVJyflxRtgByA7RDpEz4PoSCxLTnEIrPVXgfkmbAfJoC+wEUhrjDXqEoQL0e6EpZ6vrLrCQj3GcoYWjxVq96FYiS0tvltwmmLKCIpVEphBZIk51oaEQVC8CaczFEjOXqP93tHXyBjMxgpIBQKg+tw4NgI994UIi0q1qzjdr9HL/U+K8py3SOzMLTc4Q4ws/Lohs4AYz96nCsDNgnn8TgO3EY4+W9H3L/6YSGNJGDDBtkV9yME3vWyY/R5Ru3ute6J8pmKxOSTccNVlD+SoTIgSCJCKQThrVmM47f8ZvJYJ3eaVSW3+w1ZzV376EkHMcin6xWfffYBFSai46W1gFON6u6kLUcH4OMoVAmY43rZcX16xs4qHwcCxt8Gug2M2ysEiHtVm4FWfbYdWJzuAe+8tXQJAtnbN6t2Nwb1k57TOZrsdphB+gH3veQfwAoNbBjoAIR9ah2yWYybVZfSNBzM4TUP5RFeUEyp/AX/NkgGfl0ghFjrI3oGZ8uK0VkNzyB/tNsY6NZp2BhaYxD61XDIga3tZSgrFN0Hs5gXY4rBaZhkkTWo9ccgHRVATAed8+wGlIfDelSHDTG4j6jcc5np1z0N8MhQjoSdhtZsoq0kWcpM6InHxxkNmGYGFnpUsGRwpx9BT+EIiD3fNkJhtX0GTlTreYqGbQe2S4xn2/eCAK4qbtJj7H2cNMNqdE+9RUDjT4StKSz+9jBSreU8MogbO5HJPfF33CuT/1OkrBZdGtsismDBEcI7Dd9VuAgY4Oe++0zGKzmaFdhI3sjrbTqqEr409KzJQwwWlQhEHqhAAWjwcnwybx9PWBynCYE62APdR6fhaqC7nwkpDshAy5YLTaG6h5PChagMd8KAe8gisM8dx5wOJ/AMngNdHJdZOQMoxmu90tmO+v80cCYntdq3WAPPpY9TpNT9ThVQuS6Uk4JlLw3OMpJ0zC7SAeWQ5P0zeIhszzGsqiSjH910miWxDPZAM3NoAx2O4TSJs8P1AwOGtgYVKOkb9QbyVJYjofqd9iPgslVw8Qvggp2JJNqoZaiE/pGLyWCrIyqx0By322sFn6IiIqqhRw9UGVUhmsiO3gf6cav9ay0qIEVCHsnoGGKk7xHVgQIAA648iyrsd72ckTFQUE1UbPI/dWULB61q/bWyOm2V5BeeUOsiU1dDVL0WNLAte5z6o+YdfbagSOFSJzArWPj2gy2zOr/qUEjw2e6RkBK9MkOW9d5xu91xv92R/Sjzte+XqmQSPrQxYaE970xwpAxxR1ToG7pRXxlOmRi8ulUlB2EukxAXpI2EK4x2KwHZPtjjLwFsovXODBCSWLEmQXgdp6lpFcUL12lxqjtCXzcblZipCPU75KlR1x3or70q2gDAjuhxX4G7C4O495XPGDru0Q4HM+nX0THuQa9y2aGtBdqKeCBIpDxZXnOHMlgbn8+01vEw64fv8YOyQ8hPfQRfb82ZIJnJDKzky4CczDuWLpo6VyYELTQznx7fzUD4Jq3kVAYiXCfdRw7e4pyTrLTVqbxCZoAqmWm2bPNclQyopnyf1wuTLeNsv6WXOdlFaJ/WUaYcZyuSPLIPsa5JlJ70R7lqM4heqpNPiYzWgj5EEABADjW28uITZGNl+RKcy+BEJppGQulWAXRB9OIc1JWrF/2qwnFME8aa+645FeFeK7R5IeCANl1qDtNZznPP9Zy2fa7t2UskkAj6+oT4LYEKnzLUptzPFkWlDwjqwK16Qf4z6rKpUzn5rwELXVEPSrtkqeichnHuxmMF3DlgBjn9OOky1Bj5vGVdZFJgIn/lvubF8ol/LRFKMJ3qGdAt/if1VMzMB6F+Oft056uKFOE881L6ZGyUIqGeT5OtOfPpa3DnvQux6mR8MZmtlKplXX25uhLN1ml58oD5tEweXp9Ye8L9mHdNPQsoLGdHCeSVewTbyorjqWcaESPKduCXzAxbU9jRg6etfp1Hp9WbZconcwWc9IqJeJJ8txIlMxm2fJIabSUzEPkwpwrsV+x5GVPJ2loQVrAvNLHcbyq+XGufXKD2w8M/5hmks+jVrdmznJ8XIooQJUapa41FcuZ9kPZSfgcMCqHOuTaBj0DjHMeBtkfxSXu6VNGBMFgfvCLuW2P25E+89oNA7RlwQv02CWQi+CRSAGOs+4LS3QBAN8rhlLkAjtsR8pqJgqG35DIHMgkQ+qh7IEfVUqUcBtC2reivqEX4P+o8jkiQWrd74z50+wX+y5r6sFIBcPz0KwDg6lGJfr/dg39VNXh8c2Ql89efwX76tYLmWQ+QJPbLv/4Q8+ZzEjFjjET1S908hcOcM0TQPn6B8eOv4K5h7Yj53usDt2kNngNT39q//Zo8Faf9GcMBN4x//Az5GHEUgVTif56ATYD2MfZR/SN+/5/fxfz+9hWA9Kl4BM8hsH8A8m2MvXBeavBzFjlecI63734C2obr//g7xIGjDxzHgP3jO9y3Dddvv2KbOkSAVcK3fD9ucADHdz9FQrUFD/n8my/xej/w4//837WPIoLLtkP+n29g/+t7dD9tAdIr8ma4qRPlW+/IjXnpwvvx8PlkmHXJiwT6sGP6c3U4TBy//6/v8fwv3+D+4684fEQxjza6wqIvfCZsIMduiLY58FgrUdq9pA3HRLxAIC60pUWOjijGkEQoIEpMg9K3Sn015X/pFTF4cw/0Q8sChaN8r9Pvk37QGTxvSzwJHsVR4J4N6uNDmWSoEuiOkmgUUjLlLIqmzMlDOnnucsnyXr39yCzebPm5ODcRKFKP8eWr8onf397zxHJTUziL/z99TdkFgC13R+keb/R+rLpcisKlxUb6187qITLp1h2fHJ+k7pHfezg3jzztUzzun/Ha3pvUXx7gw2L91ZdgIYCkFp/6CeoAPT7vLPweh8KYEj644Ne8oQOvEjDOXz18zwHcAFyXWUQQPf5+VCXfOnvWz9/7e31vPVJT6U8yrrnnNateJ7Py/INFsPLdNV8Yvax/lyIaz367sg/jXrP3yFWq6syn3u+R1FPrUux5HYQkd80T6aWIpyGpNJCgAtsM45J9DTurkxjAsaWfV2rYfFBU8cZ7fUQl5NEPHP3g872C6t1YoZtBcHO4pbNEEXCD4QAvJ7nSeWcRdB+I7w7P8I9XFcQqLFYyX3++99d7r8gP+wwDv61yFQrWIkmsefGgT9zylLTAbQhlbOc4byfh7zkXoKDZI0BJKMaU/7xPrBcVEI7n+H3AcWEQHYAeGH4FfDrLZy9cFG0h/87nWCotBh8Kz8QzniuHA8Ohmb1bij0z1poW5CKc1YbIdYsHDz8L80y+OAarnTyMxuEeARXuc8CwTzE5K6Acehw42sGKtkY6HjjugYzQh9XagUGUcjVyLY1Bg9a2SOIYzgBCVDQfw3C/H7jdD9geSuH9fsf9foQyj1nRCQC6S8Byn2gD1ctK90QCCJO7WmSs18vkWTlXeeAhRQflRVvq0WX2By+CXp/w5s8TUfBJjNTVs1M1dFyvF3zxxedF7PksbeEAj8qGUBqiylRmcOYYpbTt24bLHtW/7qEg2usdw6OKuoFKY8LBswdy1g4o6MDVFvDxK6y2BaSlyMbgemP1qmByaR4yEPIfCknHqqTzhoqsNzQYPPujA+xPzn0nTKZZB5ihW1UpCMcpzKKiMStc2V5gMFB5yhL1mS3eWoNtjeckersNQpWPEeduWGbGZhUAFTfnAScfSScurLgaDfLlcwECgt2jUtIkzoTHzzRiIxgVFZ55BrIizSjAZsKd0ppNjESU0y77PiGdw6yEdJ5RmEOukcU5CNF3HEdlNucZyQBrBMW3CcHKBI0mGvye9HLZd+z7HskPmPxhug1lQomv59QdkGkQZBXOahybYMlwnvI45kSnISuT12tSzksqcRJnIHqyoGTyqeXDmkBT55vMvjwL1AvcKtDjEgGyrOgFIdzj/qAuQONo0aTKWe0TYk+yfQQimLs6h8o1bmkOIBIysjJ/RDsG58QtKdMNXRWQFvxYGETfJPI0HFUBmg6vZkBmej8GlWYilc+2AUgH+XTu1F6td1mVDUwdJD/M1S/Hh8t0pOUZE4FnlmnutSwaIyu86nFJI0kPcLbIcfL9hZHrMnYzSOsBVYdEVUjHWQRQzHI/IgHGrTG5jf3dSgZJyfsMoqfsBBzDgvcpgpbzTJoHyoeoQsdAI+Roaw3mFyT8QQa2bKGncsial24gGRDwcHJ2JuBFWwYmC/QN4xKJRf040DSCXyFHWPmgGpXdnW2osgoVmA6GBW99rRRLpyzybEieOpl8ExmslxOsX3KP4JGxoXlEIawSbHoO8mTAjLJgVpT4dPIvakHsPaJ6ToDqdEjaFTqnc6Buk49F7szAGBqwf6PDO8Kp2o9IWGLCS85PIHh5vePpKXp9hm7o9Vm21shet168IGGjZ/A5V9lsJhPN+zBYK0ThEEJNs21H2xQ6FN4MGpk9Af3eZvuiuf6gnojSbR7jDiDd55lPp9Aw7sMI2OwMIMhIlCzSLNEeZAfsPvUyOxzSZvAt9tmAHRh32mHFdZIHnPmQ3wzyFIEuc2dLl/52/EUTn34lDZdml7Sd++HT9lhfYYeFiyqSP4Lm1LRaR82e9aFjFd2zQi41NZO0g6ivLnqpICqms8+yAJmxln8RmWTKodRHobp8FnxvBh+LSSP1n3xXPJ8c+khCWyrpzdR4rmbv+Sl9375SJioowhmkzvXnLwuN5p/JHFJPpU1qM7m1ZFPAf0AQ40t0ObXBtQs+v6nDfavn5HqFjqTQFhVTjb+bsz0PhPwak3fkfiadkBc93nvKxtAbYg9TJ53JMtO6iHeCRWr95ZVS8s7LKW95jQgqqSt5W6aDj3WR8ww7TlXpb4Pn8/3B1YR7VbVl64sMnFQVuqQuXFNd1uyBXkROvo2knvn//CX9KFyrslNQtF9BodPfXnsNSLUkEI02GDnuRrlRAfQFGWQ+AyXD5lSEa0LaQFIudcLUGRY/VzIYOU/wvCz6uCTvn7TTLXx5R/MMrgwxdSe+91AdIwJgKGTpfpwVjStfzZNgZJLLHQAZeDufUh5OtJ6yburoZ3Vz+hYpR8wK6vfkF8iMFVLjREXg01dBV/pL3HnSHndt2dO5mg/VoLT7sMzfsfKt0+OWIMDkmElGc2yp06x7wnv68jvOc8nrUmcGAGwCNaV8lBqbuxVClehZxiYKTPUM55xcfNpEkokNgPkB2WISTsSgzNtJHS0anQHjeAWwz2DbIm/zXERQMulhLkEEJOOtSEjPZKosdKM+13JVdb6PrJBPOzaSV/sR/DTaFwp7NDPBAFN2wcN2qDZGSbMlR6fcFvkd9jNH8IXA/TNABOPXnOOk47l9ju4eevqXgvHDr2hffx5rmAkoy3LEbv1+OrbLKajjf/LxI5P4sxo2D0X674j2mXo5vyUg/5bkIYInA151judpOfsKYPsosB8c8hFQ9jdPvpsJJrPCn60fPn6B8cMvtb/rnOpkbF+VPMpXk5B70V7SovBJBPINoqiBe7jaKfUSmUmaEv8yxOcesO2drVj3j59D9Dfcv/sRAsflv32EeSQjjJ5tNXM/E6nJ4T4AW2DDAfgPgHwMf3JW+Od8QVkzReHZay5lNMWgi6+/r36d5MzKJ2A+ZXKeMYliUKaUwFwgX32B/tMv+PV/fY/nv3+N+0+/4r4f0X4Mio4GhUNZyJI8SCRKL1wawCRfba1YrDkgmoptfF6tUjCLUD31AgbQCwrcp+8ZkDrXoF/OWGgSaKmjgunZojXXOXUBl8gNB2HhK/nNJSAePJIyt8aWuupwUQwVmCqMibTq1I3r/JFvpoA4neMHKeHL3/L44SM98D1/c9nD9W8/n6SSp9zP16cse88w/IPXWbxKvadKHfgT93tXn1l038e1OPPOSb9vxvP4DPdTMe4fvf7aVf/nX//hCvQ/m4i8Q2R5SEsfWsWBZ3Yfv1Df91rgzFQDsloJwWydmW/F4eP6D5gGfUP0OX8WwQuysttxg+BZgAytOQQ3pGk5HdQ53ulYzoGWGTb/Eio8IlQeAbEpHOXhX57cxzUVAM8eCtX+3hrzebIoDVkIUvBY6zi5XkHcYSxPh20Iqpb4upBsb1YGjerGnisy/9UsqHwyIxzsSReCVzCQVQlxuDKINWxAVKPSUgTX67WcugIBhsGEVcEOQmwqmm41/mHR7+9+dLzeXtgzeKPTSiv4be4gjiowFO49OvQZYM6eOB7OhNF79OYdR/VWD99uKJ1Wezk7ps2wVQp7bmxVmjzo2gsrWalK5Rn6mcB/i8NipK+44hmC14XiHEiafOTgiH0OHZhZ9WRskoayAM5UkjIyPJTXGMsFqbIW8y38obh+UOFoz7H3x2+8L2FeHVc4IUKN+1o/LbJDm7HfUguHlw6Ha5xrhUSGa1V1hCJeXoAGXPYnwKMXacRRqJjTcR77P6qCyjJAOCJh4xjh/E44ZmlajtmsiOvGEArvB+QREPTB8GlpIsasVwYXDRHk84BtVxcGKqe41roh0O8d5obPtkvQuVj0Vhahsy8SRn7+7ReoKProeH15wcvrC16PG3oGn3g0X48Djtin/bLj5XYrqNx8bDpYfOIprgT1Ln+a2il9iDp5TzJ0qclNjj8FQXKOEOYNOo1Nrw+DnsRmAA8I44KOSJfg4NvW8Pz0FFXkWwQij+MeUK+3O47jjuwR6oPoAqNjWAfc8etvAVP+1ZdfY4fg1m+AeUAdeTo9F4NDIwMyAs/LfAYYEJRobiTBizYB+gAMhGE/Ou63O/mBoDXF3hRb26Myp5z1kcOYgRs3gIwIyP7hALIPbK58wl8rqwpTVm5O56QqXKO2NhVlF4MNEIqcZ6AHHbtFVZFE3wE4svpesG2KKy4YhNTt/YCoBpx1v5eBljDFVoFm9h+0AaWcsBFwt8E+Fft1AxTofeDl9Xcy0MhMlxaJXtZjDaKHcSjgGAHtJCoQS6BixbYrXICtYFODzBqJLZJ/nD3VkFZDIWBUL06zyL7dFbZHH+zgK8b50Whps59UICJMFSzDE5JGA1COhSqsSoeeBA80jAnl13h+4RAMEGxgwsKlk1lBuMoNfjXA9+AlEcaMhDJWLJsPOnLZtmQkXTkwBLo1DDF07xCLpJ7sW5lOG4ex+pU9hz1pMeDfxeny99ABhwNwm/DUa7VrOZIpynBW0LMqNKHCxEYkTXi68zgmOl0yOF/VHGSUPjrQD9jRYccB7x3uAhM2LlEGYFMfJFxYQCdL8Znoz3yUTusWQZdpZM/HTh9cVsxNQ2eFa2VsGZkIU9yUhmDqFNN4lzgbqd0yISafkXQZ+rHWQCpYtugoRudesOVIDhCTIq2pH0fKW0K8B+w9it0bvKzwcpRqnIEJYZ7JOz0Sf0SiwvTE++P3SpCRNAdSj3LARyUO5KpUkK0CBQNijcGdA8N22OhwCTDv7mHs99Hx8vKCl99/x+31tXp/Tueno9sItJJ7BHZVFdIE936PwC9hy0OOA6PHWqZO6wDCryFwU64lWy8ATCZqrETX0rqzYiBlUKDAOs2P0Mkj2BY3aazEALItUSYokHJ82mXhoIv9iqreGXyPnItxcvSmA26M1CuWIL7nHmQoA5VElCI/zhQJRFGBenPD/TggL3Fgxhi43+/IFgAAq7kyCbjF85TE5+Y4jiMqrnyDuWMTR/XKZZBFEMmRoVaEHFJf+KMKes8AvJKXEfpfG1qLhJrLdcfmO4R76INrQZjbbHBg5G02AorQxdJ0mhqXZ09o7mOuKw+CCnvIS7jFBUxOITIDKAvMDNgoGxB15Q1hDx63F2x4grZoy6K7wO4jU+5qHIP2VmeiEZjchYuiCXD/7UZiyd7Wb1/FE9c5InTleUbToiJnzmSZ/LsSqpb9k+hx6YR1VA3HmSkh9H2hRX4vYUOz+jfr31VbOO9WT5CwxzJC50sHlIOQ4jbliadtQhpv247LFjDkBZFP9IbGFj73+73aVMQSKQNtmahDGkA4NVvb0LYMfCvG5rDUccjky4GZfLF+EpQzjLzgSwh5n98rXdKnbFn3r9aPa7oGvnJ/aQHFpvYjjnXaGhKoTcMs5C4E1WcXUxamrwBg8ioDI63FWmT/75NMTJ4kOfaZCFGV2RKJRw6d4mAjRPwYNY4ZTF1owVNfS5mcQTLSaSb711oChfLiTLpTAeyAu6N5OqgZAK9/ocxlsDyQz0KODwuZA19aymEJ50uqrbUrD4GKef7SOVsFpLFiwUvkjFe4qC4xRK6pL/fNYJqG44g2DOgUp47tNpNJE71DW+nuSf+qsV5lX4kwWUMA8uCsqk9+PgNSWklJNWdfxorp11gOXvxon+Jgy0X159t1PZ2ZdP7Da08k78KzFlKRcsESxY18JPewZQu3eFQBVggRFRloJVcjyTlv5XBpob9hKb5IegXPkEu1fckA2xiBpFLViet0F19Y2/daGVGtcyjkmVjQKgpWnUGkVX+rschZD81nv/X5+3LN4+/kd5kEmmcLQNOsK401Sr75KLwSNj73LVc47WUnOqFQZ4KNGoVz0LFPICIasFahpHUT5zzkTNo+idTkvhbQO1a9q+bJRPXWLrGmkgHuvD+TlG1g3G7AJXSh8XpDono6ABigzzvHGMab2dTv834pJ9wdUATcugC6bYA6xsG2aBbtEbVFMFyahI2cfP1yYUGTYbtooDgRLUk00BeNMYLuDrvZguATDKfOvAo67fb+469zzSjjxi8OICrLbVm9R5JK2WUAxs/xGPz4M+QrgdvncP8VIp8juaX7r+SJsUIHwm/vjtkxgQ8xcOspY/fLBvdGf4kTUSnmlntsmUhP/U3B808yUgBPNqtckzcoAP0ogHwO/Sb1+RjQkRX63/0EANi+/RoCwfGPnwEAd/IQ4zLna09F7CN98O4Y//gZl79/hAA4vvsRYf/HF/VvXwIQ2PeA/O2n0uNiTbyqvUWk2jB2ADKiUANNg1Z/fsGxHbD/fsV9dGy24enyNfRbRdskKpqPSHy3bJflsffaFJsIRBxddMoxjwC/fhP6rbhBxKE+E5VEtILqRh8C0o4snYK6wMqcOFGqIMjAY7A0QTkzkDLYo6ivFgf4VYCPPvED9r99hf16Bf7lGS//+j36EByH4X4b2HFATNC5aTsRGlIXiBzJTLyMljgiDXDDfRxlNySJ+LZhVwBMOhfK9PAlJHEZeukiXnYujb6g9xH+zqPfcRwHfAx0D36wbYEupEI5k36KyR7JL9OX4AtK3YC449oa/awh2wyhX7Z9Rx+GrTmO0XHv9HElIkVcBoGWrZakXpfYIhLcTzmGed7XV8z6jFYw6X2uyfzNT9dM+lm0FMrAt3Jv0WffGcvjy4zFex4xTsfb69ez+YYnupPXhM6W+l/R8HnAJfMe1aW6dlEmZf275nYej+Tz/smv7TShT6z5H43zMUD+ye/6+T5FIGmU5cLJzMo9DaloaVV5URpcZdsDZSABUve5ueGDrJDt2fs8iOBJclThNnwFkIbOGfprnTBFmyy/nz4r8GFkpvmbBfM8TFyDdS34uiGg6EOQs7rwYVcy63uFNl5/WWx/HvZQM4p682CSq7umIpvEmvdJePY5z6w6z3WFKDz7woggQCznPjlsGn+j434/IjC/wD1dtg24PrECbaAfd2xd0EWhHr0Lm86qzi507gJwRH/zww72qBRAHd2ip6l5VGK5hDPbJJ3SI3rjcB5qhjQyzDt6v0fArajAmRkXTpnkrs6VzPmuJLEqaSvTzB8hWKMyxeUFx++A6DMEHyD+ssB+vGCJpNT911c9uhgXn5jVib7CiFzrOyWsEEkPta/L53W30/QE8iGMpf5bEjIFJz+P3r0XRGVRCDilIujOHobuUPMIFg+q6RZV4uFo9drrzJLLTPSh0T+89x5OANJPOOHDId8Jx96NPYt7BD76CEVr9n40MA41K9eYtZiCPYNTsRXRTxtKqHrQ0HApBdk97xV06kIDSXLDQggGVGqM53rZaRARLtuteKbBCdd+Bww4jgOvt1fc7jccDAwH3UlSLHgC8XqPzxLe+0w8nxaeeCC3NcuORz6opvEcyXK9vHOj5fdVkCd8G4g/MOHupmICl4XXUYmgA+bp+ozPP/8cl8sVT9cLbr+/4reX3yPJ5u5RLUyDrmSRZTY0cD/uuN1vcIksVlWFaAv4I1mq8lQqwBUJXeShWAKIDhwCVjMbsqR60Nnv3SoTXKDYtw1y2YIvejiRChbtfUZC2iFdeBihJ2eQR5JKwboDkC2ygIPPC1xnBZEPQxcG6zPRafTppDSjE0f4rCAa1XCidz7ThsPHHQn/lPJyraKJ/SbndFbS2KhgoagHBL5EgOR+3NGPO4MDA/3okVCVPahVA+7JQZhyBvs4Pm3CsWd1d66fRbDRM0EHhQJRTiBhEpm0amNikHBA65T52zDYbrM1ANe56YamW/W9Dz7qmHVv8zXSgK5+kChZm8738BowKSp1DM/1HdMp5oZZfRRnpbWGbQ/nSfalimpFK54cfait9iOOSpRiGgJGbPiAWsLfNjr8JhpRJAAAIABJREFUcRZPisV5xao3XpjugZEWiuWzZ6JTljikfE2eEIEFLHQMKBxiTKxRD/w3oZ7i5CnOdY9IOtkQnUJMoPLR4XQappHghHmWhCozg0GiXxr3px8H+j2MxNGjYloletEHgvsMMpaB6dmTnhyaiSsR7BY6TmQGN5BGxMrbgWlqYCqUyCAPp/mgl8ADHi2rU+KfTfnh3CO30qHrUf5wv3UESZfiVV2nIoh+ZJ38WyiHUEggEbww6opT9jZkj7yayBvZM9X1RdhQ3gJzvZ0BHeMaji2C9c7zevSONH+z9/rt3nF7fcXtFnvbewTIYV60kcl4oXMwkQ+N+kc4CtPpJ5nvO9gzUIiYIajqttAzgrgUwbeE0ONCmjZzKMJ5XoXy6sikSp56JORzY1Wn+MCwyMq3EXpz6ripiwLRv+4UQEzZB5D364IasOxNefhD3k1fipy3hwqNJ/8C0M0qKYs5azD3CJgzaWgwsTUhXYN+bfqjRNeHEC0A0eKD/NIa+RCkxptB/OIHHkH0cAjZAiOaKCUMarLdxiaRTFQV9MhqKvJxBfWIOEDDHH67A0KYwg/PkdAiCUE+x6YC9Hvwl34/An1FmXDINUyOEGcpHVHhoEw5tua8WGqF7rDbC7brFc0bE6tSJgdNDE8Ixpl0Uc621wN3STnTy+57PJFlkry5Aoi8/lm1/lZLfOR3588LEQHT1hEqqUMA8dkCan4rbZVMtsqzF2cgk5fjc4TNp8IWX1LntAI/xgDKQuuN8n6/XnC57JE46YZ+9Ph8D3eMHEeti+T5e9Bx472wgQPZhghGLmitc4kyYJvnMM8zVz51CQkoz3yEZ0ISdYKyXbLEkF9OBJuYZiZdnvc5L0h9fVjoV+bRbk3dy3Ed9haTS0BZrfNcpo4ybAC2VEVR41IddHzHg72C5qucjfVIXpjOWEebwZeUR5zrRMJInpWJeFNvSftP3KPfpk0dDLn2JXzDdnDJyh/MZyezH6RunmVjgnW2OrFlPaaeYEX/K2pBIZEk7azBP0etNRxgZcRJps4Tcj6rKUWdiyXrF+o7oetlnrvUGLKa7XzHQPFopZvGe0SCYSC9kSZSJp3g3iHVkgOSCTFJTwv4bvqAPOh9yfqoI3ue6R+/6niujrZ1nZZzI8s3Cq0hP9esFKTOJmFfhR5ry30cUspaPCDtcPWoTqxgvCxoDCA9aiDqxPqkPyj2KZM+EkVKMM9Ryt2y8UVqcpEcEVpmy4Q42rfC4KsgrJxIliXNEIY9C2ZqOU4OrEeKXBftnb8fhUb5Vs5JlgkN7uTrK6N12FwbmbvmngkOPse57JnV36iEl6TFOaA4M9oafJ9B6UpEk3xWpq55/V5ps/wfOUPZA1H5ydZemNX6DiJmpt3oQH+9h1x/OagQcNzLGo6XG+Tpitz4qk7GHFvWf2SAHzKT4X1EMBIihKR3GAtczCZCXC5lFSWkweCYyFLklWP8AsEHYNe5b8t9Yn8UU8uROa93qGbdmbfkMxEZ0vYZAuhPDv3aIfJZPSN8NJ/HOf/qZ8hPwL7KxEWOG3l7A+A/OvCNIBG/OJ04o5g8Pccxvv8l3UzB0dyxJY2RwBXzH/hT2pehz+R6p7rCxZePc/7GWMjARC47vWSuk8iXcP8Fhi/iOzZg//gF2ThC+SzNQq6PsrLINxw2z5xAZgEAANcG3Tf43gBtUbhihuHhg2n0EcHSdyKn/UX6VsUB9WibKPeoJA32VyiVLoIjTLslxJie7Fghp73O3YdmFcOneNHbWdZZz83w0lfItz10DVdg0B4wEfTvf8X4Hx+gKtg+fonf/vWHGPMxcMjAJgNdoqpbM8APtkutR+d/2ds8gtydhTIAmJimaB42ZrwJyhHOg/WIgRLWSa8pK2aUYfSwjdN/BwupoBtRF7ctdLoO9A5IJg2huG2hUbqTZ5M3qAObKkwVHVEE0xwAUUFVhOqNwcgfsbhIwTNXmnDuG339a1ulPJPyzrl41JEe3/P6e1WW/PTIVa6fXukfe/eZ1EtLb3if8MJOTh047Oyt6Zvr/1jr4bmmXZ+tNB5GX79V4lAurSxr+IlxPo4j+Nzkoye96p/0+j/aA52q6qffn/xjpapP3uv0N4WAPFDwkzl+h+EzVk+qO34Rx5OHEfwi0UOc6lTd+yZxQJ9oPD9zTC/rQJeRzE1N8XRW8CbDzpLLIPzHw/V4wN47cEDA0E9hBXwOXUG9/1TFz881lSkGDCbUaoxmNVjrbV9mXQpu/BwA1Lwc40oHUX65Mu0ka/vju+bAsKhObIcCrUEtssyUQcUwojZctgsu+zWchLpNh42QGSAETROF7jsulyuen5/x9PSMfW/xPMxM7eFhhI/B39MYRTiFAETlsSjgAxgC947sKRbzn6HIci4jmXwqg75cnb9NxoHlvdyfglnCTJYQKNpnAsEXoUz+ZghqvsVqSmhjgqngrVCrQcI2HwYAfgX8NiHj2MzgfBZvgD/RMUwDjUp7VkhOZWLO8vh9YKZ4pJEFGIMmmZzn1IjD3vByHkTQG7BUsD2g063gsj0UyxICYRCoA68WvW6aBHKCD1acj4BWHhbQP1lhPuAFSQ06AznFMDAyUxcM5vgMfMzqhlRIDSoJw80KlMoeToeU13uZtVu5Ncv2pGR4ul5PGbbZy8k9DIzX/opjDOxb9JDqowfsvNmsCsztFCml6NGQeCOI+PcmDdGw4OGD06XyzqdzRpmg6O9/vfjwSZ/ADGBmld15cHFXEVTPzUyq2VsDxsBxP3B/vUcAdXTcXl5xu93C+Xx0VtSuMN4NrcXGR6BGcXt9gduInp4OOl2mKg0zyBBAB3wkcofWemY1d2USMwhqCfnLqhev6kApJVd4n+B1AV61tRZnnUpmJnx5/S9+mg8mkdCxOWYVGuicEiIY5NrOKqPs5RX7EDBLvZAZEgJVd8oMCcdJficCMaOyxzMom062CU+2ZMLDAe8AojeSW2fBRSSijG4Y2yhns9+CvsfoUf3dGnzbcBw9xlMBIkCbYNt2qAbM/LYrtnapM6ESvduCCKJaRQWUhVP5D3kmrNRaDB3yuFTwUrAnEnYaLnwcypOYF76H9ZZvA3QU5uWL1uDxp4pGMFdQ9JMOL0GDCCF7EwVHzv/+P/LetEtyI8cSvTAjPSI3qSRV95z+9P7/D3tnllalSrlFhJMGvA+4AIx0z5RUXXVm9IY6qYhw52I0g2HHhS9FVAhEcptm4oTxs6x+sNrdAdvVugfZpMsUs7LTO3MOD0rOFBTn/wTlhIqs3zQwDoxqcr8aJz8cNWlKRBZ0nefPZ4Uek+dSr7EwWo0Bewq9rOgReIBuYBgT3UIWqGCQDvbN94sN9QC8wCummreM2LcN+67H+QDSCR6/Kx3mAd+ffcJZrRXQrkk3FjpdON2OAXffc7U2ruvJJPMny4TvGwG01G1iveIesy4TNCtAuhkFEAbiI7AlICoHzMfMdYlAj7+vZmA0NacIAPAdDuJEznLMcvwREhN+EnhBGhly0lwPGAP72LBdO5p4gifgldRjDOzbYMCWlb3qaBh92V3SWeeeMe4TBj0ARsF9zV2vMfR1nQxa+JzQSnS/viGCW9ULvSBsAVbhUd+RUSnCMScxFRYJGGIMMFuRwfRTuJBmRmeF5Z5P3UMAEZezQR+hNNWvduA7vq6WCzUvazlQHZmkNUlIQYHz597dnhum7sgxwCsiDCZbZbgzqab1oLXSwyLKUDpc6Z4Z++BYu3gls1dkxfWS39spaCOto43hcKO9Y8Hu7YNSU7bUURSKNlquj3Ld2iJA6+60C/oBcH1+TpSLl5frpCsrkzdqbiPwqfw8kgxj/88xHrIMqHiyyIILBALdfADtsQEXgb14YvG5UiveTNgLvD/IVM2/ABvQMCcdH9S8orejgodjb3Q7fVdO8Xyv6ZjIIL/0dknhJhQM7IhqIYEnDsbfJgQoM1b0WySJU++CywbvO+u/GwNJxUbpwu8NbXWb9nK54PJwwePlAcu6Yt/ZNmrZoDB0cXjcd8tCkeMJN4NJLZ7sCUCM0LHu6PX2PyvWdYEN5xVM06wVktAJJP+eV0P4fiaA7UYbzfeI1l3urAU/n/hMBpvbtKzkzeUOmWRUXEjPaAa3p7FmtWroXBybqHnAmofDe/oqCHlpVPmF4MoCC45BLQJrvfgR56f1jkCsgYa9V6/qj7Ckjzwh9bjp5Hnugo8ocoLDvizeqJlIGPv6Zt4jWWrU2NKDEPoWzgFx8q7cPyT6SU/9vUdI1FsaQBbWHl10lMMSc8A9KGVHiBQULCC1T4PfCnVN6kAIWXh6fvD2mgXBwV6CyzaXuZKXziP9Y5Mh06/nq+3mnKPORdo05wHK3s+EUEFfOmAdg5W6VKemtfV3O9Lb+T3s8H0kt4dcSBphghcALMtK29Wge+jqdqATmZ7hiBiS+yyD7DXCaWhOp86rucc1NkPMVSQGCBEFLem0dEbqPJMt6/UswVlKuYnkmpqY0gckLjwcpZ/PFeupV5z25EyCB2V0ss0BQ6JRikG6V82KevIlVNHWFaqG7WXLOWq94bpvxTGngNt8mMErcPcdvS1eJGRIf/m+D+wvW75DvMeY1+Zwy6g0h1eqWvnMfLXUeWerdTYz7OrFMMF7DYq+Xlwf3kbaNOGHAOBBNcT6ssexOKKXDsV6WbE9b5DlO/q4DNYEvTs269gcxj2Q2zznS5PuQlIc6fDrR0iocfM5yfPXT4f7XAwTtRn69wL51avQo095Ti+JZTdgyCe87n/JoodAWpFop7JHUNIXON6jQ9B+BPb32dTQ12l6z3iewnuIC4DlR4du//L+Q95H4JXmfv4vAEKeui/6KVjspD++hbOul/e/AiJ4/MFh3ve/fYDCPcpbSm5gjL/D/u68YfkRkT8K5eCfg12I91UXGB4N0Caw5oh1UaA3xLD97QPWf/8pA7cL/Vr694+Q5ye0dxd0dewug0D74naFOarA/vfPwPMzHh8esPWO9afvIfIZL//5DPv+DWxdXMyat33N+U/ZPJAJNQlrXYfcfHIkokRlm06ZfaX1uU/KRxG85bwaBC/PP6P1v8Def8zWm6KU5+q/px8pEpnIxrwFmbEIbffBWOiVU9JVa1ksEQk+UfzoCUKejBUxoN477WP3PYQNbeQbY7A1rwZX8TGqArt6geSg32k4PBvjDXLgde77ov+p+V4X9cIJb6E3x5x4rks9BBpbb8o4iyPwTQGR1BFTJKS85moYDjr23ZV2oVXq4OFs3P383jnn80/D+cZxnwKH+nsv0UOeZ7TWMkmuDveHBjJJHGaWyYrztN17/j1ue/NNLNSdl/q9utjXzvs9vP4fOf4pAfSvDfre56ls2W+fe+/45kRMX35hoDzy2J/E8HpSjp5F8MqmCvFDSOnri/7PPm6Z7e3Pe78LgNcAnr5yv9/6Cczb5vYMu3P+146Akan70qDMexiZnz/TfT+sBtaBtu9opl61boB1zzLu4s4BXRc8vnp0SJ5tZy/zzR0KNmBMJQ7or4fLBY+PD7hcVizLkg5o1TEFF0cF023ATBxW2wiSr7tnA8MzaM00YbdLgZ1UpdCP4/1PyrZNBtpMVTbdp6iOQgUA8IrB81lZtqPD5mSsWc40rzEqpHJaT3m4u55Hm6Cu0Ikq0onRrBwjNjtEwpErOJtcTgMdsMYMVO8HrRIBZmb2WXPHIo2k1l3omRDOqk33g2UVMKThOvbsL6nqWW+m6k4r81YAY1dEn+dYh8i8jaCEO89CceLcKNc4gmbUO4xGo2F4Rar5PETVZgQDQumIeXNlSenIKRqxafZiXiIADvge2scOpXAzJohES4TcicxglLNk/h2HHYLnt/ygqHpyVt+9z5HbzAaEwRBd14GoYuEeyB53QcvFWSJ4uPSee31ZvKf4tg9cry/orWHbrliuC64vV68qZ/XgGIOKHjMt2f8xKj3d6gR0V+wQ9F75p/XyDGoRocBh77knAM/0nxy1IPy89xJraITqRfQP6oQHb4LwbniWqzAJw19czMfjhc2jAlb0WKUDlkp47VxmC5JfZlA0K42cWCO5YzAQH72KlK02euto1rFQpgqNVjXusd3baYRTMCCDAtEi9xjC2R+U4X3EEXuuiQchm0PIb9uL72dmtm/DK0aXZcF6uRzoQljZ0FrDsqgHNnSgXxuWdUf1WyLUMDdIZNy23gixGdVe4rD1sfgCRHZwVKBCgh8HzdJ0C0bBH5LnBl0goelincKJNUMzJd3FduENw+GYsQtBGjDCgFzmUN1s0AoCA3SO6CCs85gC6MHZJ9ne6tnRL3pOzJiDNeEsRX4eg7Ucc8gVWH0e9JifAxkMy1588UW8p5j3p4U4FFpruWTnhJ1AEeBMuJyLZwbTT9kSFRgKjY5sVkmEvj0N+8bWDGOfoNAUu2Pb40oeVMFQf75yP7ZOVItw2scaSaFHGJwGJCrd5oMnhC5i8xpbVOK68Mn1ErYOMJCW5fjunPNMHIMVUcWf/KWSNZzIU/awojiC//mFhV5Q/MIiwz/gkM1gMmmbyUMmOsb5sOM3E915Iid1PAV73e/Y9o0Qk4bWdxjgyXfDsA/FnhB3I8e3D4fQteZJbKoKST2GDm8Lzdg8YSponCglkXgV6R/hLnCT3yjDqw+dZISqoYlSmTAk6vAkjQ3wvrvUiWb9kUJluoKBM9I1Wo0j9DtP4NtSkJvFLJ81gClJqx6TfPIWucCmK2sF3RGzofcV1sr54ugUxReE7yacq7xj7mfWEgdiQJu+z7nw+/kaRAX3yLGkRTMF+1SB3l1vGCJoOjCaQLaW7lsB0EdH6wOL9gmm2pPkmjR0dEhv2F+uHsWd7RcD95uP0RG0nL8hKr/yXYJv+XqICPMyrJY7fk7CqGD2/B77y4BcynEVemmuEdnv8th5z5qXsAYE3ZPtNsM4uaLzcbnW31ZSKaEx2+vnK1J35vuF7ul0LQjPYAQmg6fVDQwqDlOJ1OPjIbV3AEv9Zh5DBNlDZvfesa4rXj++wuPjIy4PFyzLkm0Ttus1A9bSGh6WBcKgwXbdcL0+4wVX6BZBAYO0fJrLf1ajVyuE0jV82JlafVi8bAGAkJWGIUBUV2non2Frnu5yLx6YI5v2uxkgtwA7B+6ciSgMhpbeUwtQsjCc2LOuhYTwDgW8weWxz0Hdd15rP92qJYY5xWjjrLSQT7GnlNDWs3ydJoT3FAf2mEYffMMAac6PjbaC2VGOW4xXkRiiOeSi1wNpzrMkuaJItEHSQkt7JMYc/zvvuxO93P1upsPjV9UmAJlIHFXjwaMP58f/kn/7B9EDNfTcll+y+ukmWH1vuLHno0ozlskXKvxTv/XW335GyFC5vYncu7uhsk0nKkm9aL51S24ayxs8LWR2aAWk3ppQ6higcuwskHzQatywTHlEwak7vVokCcU7NMtxROsHgU1tGQ6qVrxZ0l3te47aItElZFFxBeRbxf6eeLpFlakiUPxCjvufR96ca88pj7+TC+YWKH0xgrkiITNm+QFMghd3j2SM9/RTFFKcWUIXt2XhuMm3I8FCTjeexRZSO2MA1qZ8ABYJ7Yr9ekR3Mau4kaHYjQDojw4Bn4Ei2mCuctH2a4vvnta8HZG5Ltta2R2xmh3OCxTUlw2O2kiBnckSYECMNp7LRn+Z5bKwOn32Ogev8WCf55IcGcxZR7i3TF/77t65k3i7KxsBoPd30L8o5JeP00iO9xH4vDz//Hc8/PR9BgXvVZA6bXhSjUHQfgBe3kfSXN0zilbmoPpxfEceZTglUPCInN2naXvcvMO0wUzeQeWjn2MekL+gtLUm3wE/fIAIsP9SN0t97XBjJ/hnAZYmQOuQ3r1lC9d5g2F7/yse/uPfU58BXC/uywJZL1MCuifEJdKtNWBVXMaKhYmIl9ev0do74MPP0MsFl3WFGdAHPaGmbEEb+geT7A98/KAh3azheQuHiiMzMZ2+N15pAD4xdjXEofAX+RXLjwL7hfwu8v6nn8XnpbYxE3KHIBNIg2m3qWgpbE7nRsaCJBZYEBXDE4UbmnQixASqhvtKwn7xIrbhRW0xQNLHgEBkwESYyF7+Q0j3NkrTzhPAkyoM1AsG26Wa73+4X9kRBEKuuVnVW8MwR4r1ZiaGpuoFUrFKVnpUrl3IC/Mi2888LfSWe8yjWpuUPJqXWU6/H76bZHN8fnZ5Ha+c9ILYCyc+kvbZHf5yM/bD+OeR3nvu7fE1nUrunBOfzyL4rEN87T6/h2f/K45/aQX6P/uIvnsu5O+EfwV4MsMrCJ6oWzyRK78ywRcG0QXA46T7NPAa8Upvf0YpSvcOO/0W7OaeisSte3Plf+XYzPu5v4Jnj32eFKXfIuqgzFDC/RNWXlORi0Bdx1LzfBK44TwSoDJDW33vzP92BA71UVXguzDrsjV0VSxYASzovRFiRYDmPRuf5NmDp0pIzOEVygbB0jou64rHC7P8+8V7pNvAvm3Y2GdYqeDtw6AbYKNh2JNXFHEe1ADZBZCqPlGteTlXdKeTFyE0KoiWDpfTVMwwJ/PSzFpyMdKYc8MOhdpTBQ9Y3Wp0ihuAVUuR8utD2fZrPNiBCX7m8SS4BcCj/044wgNVGTO6Xnswz54Uy5uO8UknJh+qcLwv5QANCVVD6/N8BUSfotOYEDMMeG/QBYDKcEW7TX2yURUXrth48G5wfj3rbXNIagaGMjhE59AeRgysFAbBwYnmCKXGyhBjoC4qeRlWCjoIp5yGceIvr1rBbncD+uezLJv0mApqBD+isiZMXWx0+Dw/ORqBwp35oWukwTkZfkcarGce/ub358yyr/oqbozDr514ewR/zEq7KdOjmWQwWeAoBjBXYKJ399IXrItX96yri7Tn5yeH3H15yaov78e9O/TutjkNTEqcGSFW1wUOJdiwsern3cNr9N7x/PyU65K8UxW2e1WTpilDZ4EJKlAr4fMh7bsRsEjD0r2XZfT8a4QSEjr4WyqxQF86A2viNxvigSUzKDpE3BQaBghD1gFt5fDTgrb4GPvifFSvRbdhJGjw523DtjPxaHgiC7qhjw5dB0wcQhT7ju06zfG+w3sPGn8XwhIXTQoDihYtEhhsqP1g/NuhY5+enO/1ZYXqcH4+Bi4PFxi8ohMKbNcnJJy/iMObigDqe6YvmyvTvaO17j3UxZOomniFvkNKrViYtdxanxRKQ0AeekCMezXwpUSwCPvxOrNMeo+1CIdX7Pe8b4jbMAgzUMPzkn/7uWEIAYB1v9gTEgJil2lfkyPWzI2kqLwPmozzR2QKq7I60vK68nFJ9m2Of+4A73l+jrussdr4FnyJFZimKReCdwY8aSR0ZHAIcnDQBz0VzTistYj3sVXqF+GcLQuEiQqUS8Oi8tsoryzvbQrS5w6D9wvLFMxdUqYCwNh3r/RgtXLMh/L+kcATCQ7RR8pH5clURiMudClMZGc05rVeg9eGPCECSQSkLT6Pf4JMclP11hQyz2HNZAhup6G5IjyfeLJ6fNyl+9UAx+CakBTExHn6pG87S9aE7sv3j5eXel+xOSu9gs5fPyhJp72g9DDsQ9D3Hdvm9RiRWOV6iVec78N7aO9s/WFmroNugzxgrwp1yhY1c5jilLGszFk60r2rgIr3gs2yQhF0AZ3+4vSWsMXC30O3ZJkRhLQ0TtYoqiqLuk5+dRbqFvNjUBGIOVpAQocmL3CHytwfuXRa3/Q29MD78hEBLxs93ElTkXgxJ30ARvnHPsn7frhXwFE2adDm1QTWXD9bm2AQiaUglPwdUldXhbXu+ocVbWRgzDwJTpnMYuZ9xgPRxfkh14H8TlUQveI9CdTvuTQPkC9cx3nOW+9YbXVIRoS8iuRO1ywG0XR07DXvdYtpj8fSTvof5UleIQAuAtkXgIHtwZTzBWtuW70GY4rkT17bBKJuB4yXK9plTdSAOL9dprVfBdjq0fVTik7PTP3Obqbmi2PS+/Gw+Z68r5hAoUzgmWxTcz1cbKJH1QwMBcW4nlKIJnLgccjPFwbM3Q4SPD484PLwgLdv3+DV6zf+92O1zIpktUFUiqUJxlBcX654fnn2dSGfGTpcPgzFaDvG3rH3PXWHfZ9a7OCWn9/ME98heKxpBYrOtmzJ3tLh7h5pvEwfhdJweva0EwHg0Cs71kjKqeBjUIM2OjybZBA9emiXLgVoQIsDiaR2GlisrOsBIoioU+MYHTmmA412Ixhkt5oNUJaZKObe2uXsDCuH14TjHazuDWd8IJTB0jY9/It54JyJT2TaJNm/WCJ4HmOQI5s/BJfaZH0dNs3NTpSbn6c1Paw3UBG8UgLnhNCgilrr0HUbAq3LbSYmFlOnZ68c6tuuXzfkjfzaSReY5823SqAHBSbF1zjN149Zv4m3iY9u/V5ymEOfmnmPVK2cAdVGCwDID2AOOWxGCGyUI7yeRmqW9Igg+GslRXIQiToQQ+QXTfDw+OB+jt2LAUKHjB7gOG2j1K1DruVaT2hs0wg5WyjUhmIbFKNwBDZLYpvXKHhUBM9pCPE1nOijZVXyuNwMRen5M76HnQgh9m18HHSt03mzXuGHjp2JHpVQf8+nrMPt3u3lhdDKLoMG/RMlf/y39eGC7XrFsq5EJvEKzb4uXsG+7cgWbW3xZ7rJ7z7X65aSs18uGC/XaR6M7UGnSu2nFyxvHgGiKC3r4rQXmXbNK+MTZa8JBD15w9g36oWC3oCxuQKQibzpRvW/I+kx1HMzX89Of4UO17t7X9F0oK895xEmRGLzQJyIYHz47Doq3+nrGsPvO0yAKyp+EEdocs8kj8fvBParYXv/IeeXHZUm+kfqUgmiEifH/qf+J/TzqRle/tcvWH9q2N8brr8UVXZWlUME+3sPYsdtqXbh9Y/fATA8v/de5+PEpmJsEU84sKg7xyd++S4Z7ce8T4dgAbBN++fp/a8QAS4i2JulXPpCtt1uH+H+HvHe5b07hHtbeiKcDFCHV8XLz7+EBT2tAAAgAElEQVTgunis4PIff8WH//d/QrcrxtixqXm7SuoIEHhv7wvQv3+DYep01Res/88DtjHw+f0HbAYIBrAjk9r9mUTmYnWSzDLutJx/9LgrPSb+9XMzfAcmSRjQ2g+Qnwyiv2L5DNgYGMviBSPozhr7pG8DrCIfXgAZ4+4Ny7KWjRkymfLWhhccDvo25sF6Wy8Q6VHrGWyR6q0QiUpJlLZDcj/pREUS/TCroc1h10MPOsrXBpEqtBsjku/t6KsQetzoN27WsKJjhP1fUjxEJiHf7VA08i6DKsBf4JaTGvD5qGAdnh30/3Vt/KiBzMlxwKRhyFHeJ32d9I3say513vERPprwS6dPjWw9UQukwcEtG1SRLY7jxmP2gX3ttXIAKF3gH9kU/4XjrHv8s44/VQAdKMNwDsydjycYXqHhCR4wdzPloP5A4MH1R7hzqsHw1oCP/+oXyKfPYvSPH1cBXlnAqhSb/kcZ9teOewZzOXorW1bN0HLT3x9BmsvmwehdB2TfqcB6xZ9iAaQxi6mhLz0Fp1eHupMfQzF2AGM4NHh3uOkLIdwvlweHKQarTXbzyvXrla6ixipGy5+RKZVjDWMjnPzphI55qOxfIJg1jueEcp1e+7AQjtR7Sw02y0vP8DIX2DJBNx0MqMlIkNNdcwjTAyVebd4U82UAjSwLKyO/XN5OcDV0TgFAeyPQz3UDswhMS86hQwSLV+FqB6BQQlCaVF/FcAaGA9co6BZZWXEFyDAP3gnc2aiE4mdARnWH7g7LaoMQ56xGz4p1uBLW4Ap4VlSKYBeBjOF7jM4WVaPQoKFPCEAuvVNDVvRGRm8oXKwgMUNbXbGJdgQxn0bDBAZWASMDXPHkeJbAIbmu1ytvwApKCeX32yGFhEn/J0kWO//xe5hRKDaIn/xMxB0lTdCnDM8Q+gv7Pi7rmv8eHh7wcn3By/MLtralczvmwQg9FNU/qsa+pORB6DTEYptaKoHUYsmrqne4D4vBlDQE/ZmeoV3GtkQzqQ46dP3c3hyGHuylGqyn5Tww2Ev6DMhWNxgHbDiEerOi03jf1rNU2WFmRQ4Js5GgYCTeuFbptN2jUn94ICn4dcKvW2SXalaqe7/0AW+v4EksCb8I5LOaKGHex8HJMGc9RvXF2PZ8DzUjTPzVM4LFgyt9uGNpv76QtHwjLH0pI18a+uIGwrL65zsdUmrDs2jXhnVZgQtgq/v+FZ0tNbicNlX9pdIdwR5/bmsCDGH2LGWGdGTiWWTr9/h73hYnpTi9sdNhwkA3AzcWzsDIAA4jZAqqwN220VezoDHLsMpkJvbQjYtj7Ghu0Dp0+/RPOquYJffB7DiNn2FcJGKjRS/PCsRl2wuOJZlrzBudNTGv809/n3DIDO97ZgwORLIfhWsFk11TrAD6SNQQ31bh8GFCwiC3ynktXqvD+7HGPlA63FqPhK6dc1vjRdIVSh7IrN0hZXD0Bw9BPtNNGaYoI9K4d+eAMx8W8xByOoKnnNC6D47O/IPOMxNmOsHpWEgejHxGIFKUZVf3MK3gQVTkx7Ps8My4bJJw8+93jvTrk9EFLwoRvMU6mE3rxr7PbIOx75pOAacfX2fOHjPsp8pUOoGHAtEpLPaoqULYN7tNzl1PoqI2EDydyUYzQkbspQh8BeRiOYxrXmK9LeY4+p4FDYaONoKvcyZbOB/LBTzvt3wXFN3k89usi4YeelAwp/WdP/PzCz7eoCrwxuHA2DeE5RM6fChbRt2w0fGWOJE1Cj5jAMY2KeZ9mEOOw5icCMVQmd5X811jr0ZANrygg2UMwri5y0F/s53oLXufgkgMZCyLJyt7L2sfw6DDuAkqaFdLVuM6zmjuFYFkewChvhiBjkzgvBhsw+FI/cEEchHoNWTV8aiAvABXQDHw8NaRYPZpn4aDrm2s/sFI3g0AsgIH62evoNQ9HdJpric9zBb1fFIFtJA6fOkXVl/Gd6TZCs4g9yRkqtCM7zDJ6XjHpXmCIud7WRY8Pj7g1es3ePv2DR4vD7i8emT/8paJ2du2Qffdq2+uG8w8IN6XjnatBMo4wgEajkxT711Z/BkIha5aecR8HlMDXDghdd7kt4aJln5LnQ9+c9+hVqyoVioS00yZkN8qSHrXea9K1AUwuaelLDfpWSEUQrFJrQsCXSWeexjcpMvngw1zeZ0Q2rRZlhsgE+lFgGZeVc6fESyJfVZp0BqD4L/BCtzSu+a5z3maNn6uSzGCr8i9SEQIORRB6piXCjznfpuvnf6y07fnv+Oz+fq0QyO5QUI3k/weYRdEOyC2X4pK8wyqN3fOH3ufo+6F0veLBuodbPJTmHiyhkGoE529VnL31/lFj8kzIa9Q47h7WT1Js3qa+216DzSBTGubDC5ZleR9RCT9VsdnRCg0eFu9jDVxWp1eLhK6Uhug7Srpg+B6GieQ4xKw3Uqf9u7hvsGDYhhlo4R8iv3q5BBB5/uB7+O6RKJpBcvza5krx3H3XsHf7XhL1K6d5/8sZY7UPu9FwBNlpZ/p4HSP6eux72jLkvcyh7Wp0zm3l8cHmBl6W7Bv1ULHwOIMAGjeizkS78wMdnXPp6wLFiYq6brArlvu/dS7Jr1ijGc0ecihzqTdiPKWVb4hYwCgWbYfHPS3NUKSN+rTQt0s7fzkaZI+uiYsnWsomoBl8HxeuLS7pWU7zvNxj0/On93VJb5yzDvoKE+A9j33+a+emBkt3WJ67M51rtNPt0ka9j02mCg//qa4/Nv3eP75Q+702DetL95a9cd30PcfD9J4f/8hK81LKz6+z+9997uHvMM5imIALhA8/ttf8OE//w6Bp6Ab4Chxd1jla/Pg1BP5e2OFeF+8Cr11T2CPNgbXXz5AHq7olxUreczT3/4O6w0yGszczwxpfg1ZbWsL+gI8vHrlPKEvaG3Btl+BfceyXtBUIbt7fkyJvmBhfZcMi3c9TMc/OI1zkNiAKSmoeOIHAd5BsMOwj/dY+w/o/QfI94L90xcsY8euHX0M7MuCxWxqc8XEcSbZx9HNfaruw/JEtYBmdzvJMnheRTFEgWk5rbXyylapTDiPn3NyvKliiKU8bHCkyCjmEBEm2kfLhqOuE2LNgMlXOfuSgGhV7OMjPaWT3ZOwWhNvxzmpJkAF0Q3iiSIp45Eq78BZW5L8Mdu1taY3mtJp5uxw8ZwIXf6autZCcMl0DeZK9Li2xhP+2LM/ZeZ/qXsBjuB56mWhSiP3HyX0P/nxpwqgt8zELKarVhsDAF5B8AXeBx3wzCbACfKVFZkKgNesSocAD8Y+42fn3Okod9BJeSq1Mz+J/096K9KA/S9JKT9mWJX5EfFZPkbm8bXpbKv+iSOUPt8hS/82aZSi6UdCr+X3Qkbv57Hw0bMm28BuA8seIDNuzDRmGDUIdOk5+N7dyRW9Vrt4f/JGg0Vg6LJ4JWpbsbbuPV3MYIMVQfw3htKwNXe2mWf9Bzx7gzt/VK6UGCsgLwnDbTbTXzmX00IAeVsYvzLZGnMFzExn9+hhtp0aExTIsfvbDv0IrPYGBoPK08RM/Rl7eQMmaqhD8YwwIcQmKPegKXlmFtKrw9jUDB2spP4iWN6Rub7hvU7PE7iTIxQl+jZzDQY2r34L5yCNgTEGpAc8J3esEoJHh2ujwxXyCr4B27672cMF2/cIBAE2RgZpdgbYR0D7EJ65erB5UL6PcB2VUeOODFceNCFVqSzDUjHxPA8txzOhRtUUK1qNQ7zSOhQx4bmRsOFy1CspM/g5O1jEMLSqssKx7jNsRUszeVnQr6RzJZ2MZyI80GUYLZOqlKdVr5dckPjyJGCPjgZDOt3oRDhX38Z3XuXrUNW9dSwLIZ26EIrZDbNt26mc1fPDmZZ96UMhswEPqno/KjNDx1rBCVM8PX/GsnmvyR4Q5q1hWT3Le9te3CC0KASswPd9iEFPvAik9szyDKc6HYhdmNDBnn996TlvBgBKBal5T+d9shnrHDAx5Mifc02GB/CbAPvuVTsBIdaXBrWFrNj33dLr/SMZ6ro5JPV1e3F+S/ocY0veCZjLgRibKa7DHcZNFu9vFcYzGBCiI2C9LJmQIiKe0ADzqv1u2F6uGPvAsroSHpVkwt7cX748QSCeyW5A2wTSG55fXnxPgQZoM7SmkH6BDsO+b+zr1x1KXhRZFyDOU2KPNbSCxw9neuuupAaPsiRxp7/hPhLV4DHko1LnBr9U5f6k0iuxv8xRNyBCJBzJvVdVS3NQKvaYPy/69Kaxco9cJQJ3kk7MaKnRxGkroOdiT0vO61E3qMPSYR+9vgMVJCrP1QolIs7NoPP0u+Vc5J25pwyeC0/ob2YT33Pxz1Xnqjv2/ZjFXK0d+CgVIPvgHp8bAXQ7jNED39WR797zLe+D3CdVGQlm7Q/bnbfRBowgXvrwDmuen/hnPng45FrxgQga5eoEmko65yxHNrP2m3dJmYWksVz+Wf+ZDLv5Psay+vPc+XND7sz608EqJAQv/7xn2VnpKTpNmJrLaxkDdr1i9J7jUKLOuBOgxuPjVWTimhmT+HSS55XkaORfFbDgaU3Q+oIe2fEt9rIln7dWQabGFkegM1GboY2BQaPYkxqph1mtWeqrEu9g+YVFZYBRczDv86xaWfYK50XNm6J9hR74omZpFxgFkcskOvwFsD2mP3hTyYcYf+PEeb9BtlixuC8FylTN4FWJANCwPlz8OmXiYgYS4p6a983wFtc79NjLsmAfCm0+EZ7MM/GYWMtq8Jz6zxCF2Z72kgdMFV0p6zn9vXXODbVFm/Uf82TToRBhq5EIZkSCQuToEQY190A8mGueTh+Z10wALEyAjvTiBlmpeykgC4BrQ8cKYMfOhTPAq12toz/27IlH0r/Zg3JpwJXlMPHtSv5QSiFaBF1iwLFP94k3nkjusNNPkMl2Oken/YisUqY9adWLWZo7XUuuofZuzH3obL6RYebw6yKOZCOtoS8LLg8XPDw+Yr08YF2WRL9RIxzmvmMfA09fnvDy/IyX64brywuu1yvUsXEhDejWPBEynO2UK3tU31DXKFKsRK1MhrZK8pz1/kyQ4qzZNPc5h/dkOenRbtbh/vk+LimZTj39HDSt82NcQkQcr3iyZnW+SIBwAMkHqKvRnoNwCpqkgzVqr9P2QpzqbcXi+b5/BarFmz1vJ5J6zduKsSAWBg+gDaP+ATBbgCTtchgReFImxZEXzzZe8OnQRVIKBq+e4lb5jpj2+bxu0xwDsT/v6WenJT79drzCTt9Mv0l9craFmkRgPQK2UnyqTRfSljIUX0SgiuTC1uLFena2BYwCmoKJtulebovFC/32TNSY6pEZzr6vP08XxjWNWdpCm9TXyscTsN4S/ibzALsF7bcIHJfeExPQsi2dACjkFWHFPQjwbMkjLZO40k5jsom05j1laUuOoQnRC3EbQFj568FR2gipepRc9zuTTjjegmA/VRXGvMTnfP+5nYFfp7nWFVwN+Rc6QthTnlB7TAQrRmn86SdX0nA9KxVa8q26hU33AcAAn9UaBW0xoBz6hdO+ovUl/Vgi4edy/5CqYWEv5sGKda9WJ5y5WVayz7y0kv2A8bJhkCK8r7inchoTtdrDBa3BkQcmnrNH0rp5MpLuI/1SiTYwSq+T5KZacTkRtGVN3gUAbelu74fONQb3vesF+3XDgCTdqYZPzZ+9XHrZgQBgkvMQifJmhv7dG+DDp1u59F88VCYVA1Wx/Zqfbb+ao2hyW0Zl/7F+E9RxgI0fPEbiWCP9kKY1Cs04Ywrg5ecP+Xz5wd9/vP+A9mPDADDef8z7xsw/4yijP/8zJwXA/v5jJmwOAI8/CK6/8Nn/+Xc8QPCS2n6N7Xx8EVZXk09/6Q1vAnEykvXN12Bv4u5gigSTQoca5ug9O/+JDgY7KYuGF3+M8Sta+w6Xx1foy4KXD74vrBMhESwKCC4v7m9TGNuR+HnnPqnnd/sj030OontsBMWDOMcNgu090H4cjvC4Lm7D7g17H1j6gj7UfdXzvBvtXSoMYZOrGnr3d2qtfFoK508ahWBMOhYKbAlZq4OBc/evB9JwtIvMfSuV8KTkISoDaC19tPNchP6jZt4eDaUXejKpJ7Lv9L2478jgiH5kzc3nqzeBmidEQhXvVLDRv/XWDJ/gPH8I8IabR8LeA/D2v/0VZobn//kzdriH6ScDXjDvqVBkAhnlHkX8xjH7Nk6fpx0PJs7foa6UradbYo6FRuKDeBwiqu1nLU4a0GXBFu02+B5dPHFusLDqW68BYFrTfzLj+d90/KkC6CE8vnV8mc54DcETDI/mP/GN65/ZM512SkK//xmOR3PomBJK/ts9pYFqZX3wtQ36R45QKIFSdjH/Hc8GGawzzK25sY/hlYjNPCO4dc+k7314hSUI3zJ6BpQ6M9JG915BS++4LAsu6wVL7248q2IbA7YPV/wigAo3VCJYe3j9aT5mJ4SmUnqcq3PWaf050VsaE/G3nc6ZGVzMXxhDFJytVi2YeHvn+Vrj4ysMeToYU+EEkViDGC9+B+sSYMHjzV4J/be9axifXMHePhrWty3fc3wZVM4pJE3SsFczdGkeeGhU9mEZlJ+dBAav2OqElFYG4du2O6QTAIvqQxolYXCV4uFw1qZIB6tSoKsODFaQppBAOKejIqxVx0Zzo1RpvBtwzBg/zVNUmiuhdKO6IO/VS/i7Eu3rbeowrRGs917ZxgSXgWW9oDORSESTpoYO9n0WwqmVMXx/d5c6HkG78jzgD8v5812/dZPy40g6IcIBkU6dgIGT411ai36PDt0ePc8jSBHoBQYjDPVIY3Dp3R2PNwOqX8IxUU7xUH/owBBB9CvvS2NA1rCPFQ2DlTRUsAPNoLVCsTVfkQyKS0Crx8RIjqk1JgdE4gSXx5NGbcqyZJ9dQ8LSJ9QqJzz4sOUwGIANWraqWE50tgYYGroxm10buhrXYCHcMKv3tBF2iXM+5h6atYIhn3xvhTNCEtrdmrBKZBQsIGUZmsC24UH0JrmusQccZjkqOekgUEDUA+5OWuwzLALsyGoJfyf3QqoCre0I53LrO8Zo2ReqtXLuAMj7teEJDgGIkVBh/B3kAWo29UYYMPMAfa1PGRiYrg9DpyW/40pGsEcAWCsn0jzn6eQveNQwjGzy+vqWlFKwJd6vkSY8yBdBvOgtXk5Z1H34dIn9dLQt6fTQNKzODuMZwjTRX0IOw7z6bFLmbfoe4PsNkE9KGoxZIX86XM4HfL0iWhiozpXogTLhcxTVczGODDKnYcfa3QjwnVhiDD/eFwhdg/Kbe9dYeed7Vt0nKsiKqtk3HoQ006eTh1Tw3kCjOQyx+GySSxyFqTvoD7LBDr/cziWogWbCqGUPTWOiRgSxKsA6rWMGfUo2zcldoQ1VMG2qrBe57aeXazzJYNIU4PI3+nzuPE8OEO4+njFOEpVjL5QHzXkEjvrv7Pz1CvBaXw+ydSaHdTowDA6dxr1N1JHWO/v1OqMOeaYZFKmkqng/gTuSYsxqygppS11jThapgJXl0EfMG4h0MTl34iGChoRSDfmd+th9zTOc5Fa3yevn5AqzQC5wx2rKZQ0eWGucvEYAMUL8tUhuu0cclHt6+510DwgYG0KmU37ia4Ccxsu7qlb1Q7xYs5q/fD3LauTg5a7CEq3E7KZyKW4qhDD2hcHRmhCknAfnBSH31fkIKReezRD6re9d3biWF4GtBnupPSTTu2bgs3kQPRJbARx4cm8Ce/Q+idcvW4qOlB3kAyFvlAhW2X9X7LDXRTqiHvhm3aRoNFXb0OvqrKKTeZHIs0B0ujq9gtZOY1Pwn/dWVW8F0zsTYgTLsmJdFlz4M/p4CuCwmMPb0Tw/PePz5894fn7Gvu+4Xjds29Ura5IuGvlEVfeFjToYcLmxN6ZE0noXS5S11kAbKU6qJK/ZkfubR/Dx0DemtTgOQIrHZCWZpU2QixL3jDYS6nJdhxKm3PlKkccOtKie8rYtFq13IInQYTCvCEQF6RpCppK6Ul8x6htWuqP/wgpMTf4WKGpIm3Oec9/bMr23K8gMlsOVeI0getiGX5nncKDWZ0f5OPOp5MOhOx4JAWfUAPnqH7N4Ozwcc/r84UQR2jpSczbtm0gO5slMVqF9xPdAXM+ai0z8CPuJ6zHTTq5JInB4oMXEIOq+k7Dhfzd9n6Yl7cRpTr52K8M0y9SHkvcEAljwHQHb0smk4h6IyRNIgmlKfW8GX2el0mbI80TUCxqGwlpVn1kolC1uI67/BL1TBnVWVIvBewxTFrfeycNbDI48smRcVukHljX5hOlR/jfz1jFmnoiseR9LFImYwxJn3Kmp47SST8lLwsd0oNLD2p/ld+zzetYsC5C2Z+lCwXPzwdPaTGfEWnN6wiYxWNJ0yzWMcZ034qSzayC54YCsGM8dHH+7rJRhgpfPW0pOwxUiD8d712uGgKhCoqDdSV9E2msc84z0Rfozi/Al6WjSxY6JDpI0YTpy3VKVUcXY3ReB5nqHQGBjTIrWfSNAvvrN/XPvHVcAF+pW53sZqCtLPav9+Bb2/iMWuW2LeObxYQunjcI5tEAXmA6GbdH7dxD6K6W9g6CC6za97/z7v+KI+Yritr58h0f5EDsPl5/eYRXg0y8fJ/n6jcOQiYov3dsdBkooNFKExPlFO142zDBUsZkxuZBBvkCogji6Bgz6c8PDX52+Q257IB7ZJs2v5aIjZNP88pLP/mNU9o3Xn2y20EtC1okZPgvwDl74037+OwzA/t9+cp2yOXrkPgaWodDuAW+zg7WM8JnD4G0gwh9Dft5bx7Dh1dngvqbPQ+iPjX+AJ/kEqqQOJmUPJdy3z03YhkK/TPgZ1BXZGtN5PsC9H38zsV0H0ZiGt87L1oXhC5VCgPAlbGhiHncSQYfgnQl2uI7QBCy5mBBfgak5hb/D5a8/YCWS4PPfPqJB8BbGIHrI5aKLSN67Rx3zZ6VVhPwJMigbM+3rm4tDsNh0r9tK9DjVk/aKkI8kHdfA21+dxn3Qaf4vPP5UAfTeGq7j2P9uFpWv6dT8LIYfTPALMy8jiB4qiOdfZtFQBs7pH/kmQXwrHBW/3RMK9wXFH1fa43iweofzXewwIjkP8PAOtwHh+tzMHR5+Gyrn00MkHHGQrKBNfTNGYa4QdhqFSkVgH3vaOmKWcJLSGvZNcG2NGYoCLA6r7OPpWPsCrH5/D3R6JerDw4P3l1sW78vHquPhv0AG+5kLoHSEpl8vnR/P5NLMVLaXVNqOTolpTud+SCfyODIcS0Ec93n9l+8wxsDLx0+5NmWGlrEQVcXCDOT1u++owNLBpY8web55tsx/mCusZKcQGJo88jsXFO2NVG+Zj4r2VmgkhQ7seJ6KMsz3z4rHdwuiQgA2vYcgNG4ye3UBZRTkFruR89TEHSBgl0PTibZINx2wIewJBHRh0Jk3iUpQV6gViuEVCFSOYLtvdg0DWCDwpIuOTmhFT9YQ9qS24BERCImgSa4nV88MNipDL5QCi7U1oKl4+wJIVpVZ3CicHjQ6jAqFCCBdoGOHwB1zHug1AIqllWjvdLpuY8s1L7K9J7bDxrP8qEs4zOOjjt86vsnNSg9M3hHSPytVOQavZJ3vV5XHnj1YwfPeF0SvtH3fM1C1LkzJsMhUdCO/E8pbmvcThQ1E5nRfutOJKjZW9HfxCmKFw8EK4QVl8ft5Hqrgsjqk+UjDzmlo6Z7oky9uvvc7g8+tL1kdU1RCGu6NAdmAdVNsuxuIg4qiV6pEINKwbVdcr9eEMvKHSO7XwX7W4SuBeFBC4RVM+5haJzhnR+8NyyIZpBAwgzx7SUUCAPm/AXsorrymN1YoUGmW5hSltnANjjzDqzOcHkwML1+ew6aEwbLXfUDCybr6383XXWlIW/QKpIN+zmQ1AWTQedoWRK/B3oB92xOZKHiEKbD3lhDKXjVd53Su17qs0HXxilJrpEPA2Ec5+0FRbizr6jTCNT7sqSCb4FOCqRpOUVVulF+mNGZi91SAxxOxOt+3eqBryGKp8102M/GjISG9OqvxpTlMbcjFnso6s2GTb5RzsmwJSxoLPcPEDbMy5vi5Hc9Nhgt3FLXJwTQHqEU8kCHMZh5uHaKZwBMGJmMi+LbR6CMUbibjWI0rEulciajhVAJKjTH2swsl8+BW7K1JLZMYP/kfgk7zHCbcCOhobuiLHFW71Nv4XPNKaZf3mrpuiGPAjj/TQWcpB3RSa+pzK7r8Df01A1gSznJ4IpiZOzuoLEZVyXzkWoqmPhR62Oy0yB7o4rRWDgdMazAbpCh6qmk72BHRa1B01De8XwT0Mih5kqcTGqnzhRa03+DwG36CqgHbQCffaPB7LuviwXQm3Hj1scGGG7BNPKAn0rPS2gyEDqbu1hqaDgbHfIyq7iwQYeXG5OxxnaVaPcQcBZ/0ukghL5YMukXgKdbagGOgbpqaonkpoq9VTVpMJxT3XCQEzPoVwMAC1zpaDgiikrE06OvLjrVTVhMZyNdGj4R0PmSmJa/YEpkRdnyMLrqdztfuOvDV9sNeDt9/Tfjt4wKCL6gl54q2ScypzlWZlNCxv1QrKJPtp/J9alnPa4OgdzF0WyEmGLhiXOuURS+c6wp2xgulTsehZoJXPLp9BdJ7lSOPQPCuujiSCxNSlh4L2Y9790arlfvLW739JM/LeZdYSxSSC5hQqR5wakbnawsZEuOdOAxlVhNvHXNZVzyGbco+8b25vrjtiuvzMz5/ecKnjx/x5fNnvLy84HrdUg7t+5Zyxyufmuv0cCQwMdfffM8odUEk/YbbPVtziN/Hf70jRJKv3RJqVobHYk+6RdHt6Zo8Vep6V4jIixVmlXR9c1AWuOzwd5NAdpoiFVEpK1RCu7hN1Mh7Iikj3i7ap1eQ1lf7yJ8OL3+cF8rjRni1SGTxqnRFwBObGKQ3GNhmwjxI7gksShs3KtD99ppJdxOcu5T+EOTpS8wAtCHXwai/oZdszeBm8g8kz+4hugoAACAASURBVJxeeVq1O3+GWnJe5wllZgZ/CASS+NeiUi84XSR0cg0iIFb7P6rSXTZkq5Pk86SnclAkTwRQcO+UZwB9F8lXYyJPL3l6+fl18/Wk+Ehd/fUAutz9g79EUgDX11v0+Pu7bNAjUqqF30Br7ilozOC+jUigm7eyNZh4r+qD81Aoz0lLlsFzwKTBQLhe8rplXRy2XaZ153r48O7wA5neMdthgMlfMcgGa4am3ntdZE5gIi2HL5KwuhUoP/tOpufVywDN+Q0s0AhqZSNAkfpHJBnnms+hJ9KlRmA+iaLGmvoO5Zty/M15OIaP0aY9EveQ3rHAUWxqTplAtO8Oq4+acy+yIK+HuZOTe74B6OsK6e7P2FUBXPM9gZUtiwAEEhHYOqY17IHoN80DxLA0T0JRdfQjY3Q45y/oQUfBDCcHnuzE0BG4J9va0FfB9vJy0PV6dx6yMbFPDeycwwRwvp/Z5m+1LGg/fIedPb//mccVobfVMb/dALLl2/WXT5FzTZlU5wPAwvd7/h9/g+ANHv/j9aQ0Svotan1Z1f6DQOQdEUoN7cd3gFWle2j0kRfz5TTeP3rM7zcfkSf96j/+ClPFvr2H/CJ4/vkDFLS/AcjfPrJ9BrDDC/8oevO95nk5P11beKUExir0cBaKeByimWCYYGi1IBzbwL7tGLG3W7ACp9DeGmTboJ8/ovcV2xgYewSgFTvnUkVgMsvM2OdEA0u76laizu83z+dvnTPPO1B8IOTaRwG+t0qQvv7n3/HYFyzfv8Hl4xMurWNfOrAzkZhxlWMCHnmHSVaNNyu//E2CmUgVmvXmrTSXBdu2Jby77sMRGid0jOCDglZFdIROr1aBoRvUzzlBKWzzQArT4Qiz/myHix8MrA/aNsOMiRh1z3cAdjRPtACwiAfQY66jePGpCd6oD/f1v/1I2QvAzJGa3ZGJ5d9/wsf/9Qt2Y9U6UIF0ygDjdeT6X9N47xCA1HOTIm6P2f91POv+01wfZyKKeMKII31T1qTC7GvXW7TG8DXRA/TRdN8cj9VgvjHuP+vxpwqgzwbCV0/heiu8Av0LDK94/pMY3pgcADQfzR35O4BnGB5xn4H9n3bEDIRg/D3HP+O95uyX8nke7xyBwjAA3PHm3ykMQw1tKIaMdAJ2wCESN0DMWEnrrMz1Lmcgns3vQbCld4z1gi4Ny9KxXi54XB/8OgOzFHdn4Jq5vHc3vL/b73j3yRC79+5xJMOfq11Op7oDJHrW8boW80dG/1by2nS+z7eb7xnMajYoQFrhL26+voLiOQ3d5bW7i3b2LlczLK2jv2U262dWhLwB7LOhveXaJxygB+G2z1GVM02mhKioMdf7zqZLGBJliFYVHIMlFAJeZbsB7GurvaMZMou9RRWMNGhv2FtzWS3sT2wOy59QnxLwwx70bL1jJbxiM0/QCMHXCQWq7CSUSQNUpKLX0/xvruRyuDMP7PsUToaGNATwWvWgqoq22fknWS4BQEPBMCyLO+wghl23lN1/9MhrBCjY9t86shYOhxSlkxA9KGMy7fF4tymbcU7wqWq9jt7jXwSXWfnDALP0BU0d2jbmuEfFegtnjUJVcngOSQZfgUxnpbbPwDnSEcQARu8eWOf5+1C0ZgwYr1gJbSehXKsHqJsERLr3dDp6aGgWtwa06PfkfejUPOC5bRu2ba+KNVbC7vuWlfeD1eLpQzEP2sY1Q3DoNzT2gW3b6ChxGuus2G9MUAk6iwSVwRYErthW9dNheflLrZ/zdgUg4czJdweiMjYYnMeZS7muIKTUA6JPE7diOQv9g1Qo0wFCPhns1TzYb4T4QlAlHX5mnlkbkJNO5T6xwud3Qvrvy451X+lkWnIP+Nq5QWY0AEzVzz1B3OVcxGinfeI9IoM0Gy4XBus9IwLWjNWo8wKEaFAETF4+ZpI/MUfhzFRt2V8tgu6tMQs8Ep8IrX92NMUchvN8eiBpcuKN2RqjAuea3x+vy8HaFHDPj+P34smJcMLrVZUFm5ZyNVpvDFYDRvBijMhkrsSHSqITpjVLOrt1cnh7D/aZt2Fa45iXkvfSwiEoKROiv1jrdIQ5llbumZDvZtUv3MzH7bBeDeXkC7oG2xBIjZXoKs1qf2n0IQnZBeeNMnvIv3mU4Vs/mQwVa6ZfczXkHXhdm/S34x6JOcwJOeyhkKNnHXXSp2KNQmczgxEKchqIr716oBG5h450nWOaDNOQcWc5nLyIuks8r8sxAFkzH78n0zrogmLVY9ILIJWXCnpT6JQanHtNLeHuDkkqnDMfnxvMGnqzBH1HhSNSh1KLhjWhyJVT+muHJKuX6X1sunZa0eAHfG7aIzkLSKNdAKIKeMKbV164bnKkS+fzFRicPw8a/Mr4LRKaonflFGCknC9Y6iQFJiSVwz9osCqtJau+jHD5X51BTqDHB5z3T8ND0E9MrljMnxxaGBgY2LCiy7xPomIUTy2+O1XjI+j6dxxzsCA/ikHiuM6Hdz3ffU6H//aR/BLz/ipXv/PixgBHOdOcAZQde3Boi3iAPdbQPPGliydPLsuCdemJYCNmlC0D277h85cnfP78GR8/fcTnz1+g+23PyNl+CEOgZGfJzLkaf14fTuU0CQzKxHzzXaYQ2C1TvuMIO8/j/F1eIvHZzQ19xq3l+OdbGSzbYTQmIBm8stxUkL2TYe6/3s0d7GbeAmCUfihoXkHD5Jqo5kpyknrw7B7w5Lr6TkJvkNAv6h1rH4dzVED1mPMZfJVJDvwnGlk9c1W+78WEMjUcfto0rrQLk+fOk1ifuYwovSx0kEnK3i5P/irck4b5inzSLWmU/unGFSICHEHXDL7SJjjwz7S3gq/V78WvkTaAnMZRz0bCm5pUsYfzugjFyJ2Bn45ZP46fUjI7Trpdg9845kdPCVBtCtxG/9vToyBgcyLjDUgQERuHzsAkJZPFmrcmkJH0EI5Efx4SqQGk5YDzhRFOHJItEgDGQg40MFNIbLCJL8QOCRtMCi0HcL6UgfN88SkkO/kUjJXakqeGTV/V7fG972gOibxD4hmGTDWtyvmwM3nmjFBj0/hmO+Wki97RPJO/AagkHCPvCf1PJKHalZD+ppHoGENwXrDvHqLU4A06YMMgRDnq6+rJAHHvabwtZ7ZkIxBofuZ815go3Vp2TjiEc8RhkQc0UbgAJGJQ6A3z+UEXKZbMMrIcuonPjdBP40SWoFbzrFqha5x1td5/u0byfL9vfXeBB89/6zAExHZRfuyEGFHsm+Wn79zmev8Jhs8wvELat4pMtocB/QeB/WJYfvqO+0yKr6ICZbUKzg+earn+dQe3ZZPvYPjId5ekrx2OG9rndZ/mZeadhuApYQ3M/AHTe8OThk1cZyY/GEOxw2l4U8U29gwOB/IS4MUqvQn2//43rP/+Vyyr+9H24QUrY0Kuhbj/NvSkkXQdUn7Sn+b3+gPHPVpMm8ZO/ISfDRTKxK6KFwx0QppvvWNs3XXa8BtkG47DUwBt2MeOPhqTju2mdCpsI2/d1x3xt3thRQTQx159yFNnUZuQaPxNS875O0RQf44zhW2ReoxVm61ACxy7YUv49sHkfy1b5aCrMXguDZ+b4ZXWvEfxR0zLd3BeGava4Twu/SYGGO1jIVLoAvBd5vma9LXDjjiu9Mwn4tz8m3JGqM/EDVOjO+st6WAqnmqw4hOTXXBs7/mVwwwNrjuk7TjZgf83Hn+aALrAs8+8qYedvgFeGbyfuXnAXOGwe9Hn/BUEj6xOn4+3yUgNr+wodH7XMStRqOtbEn4x0uk03Nsqf+QQ+Lgjw+3e9zXGk3ILZAVkKt3sX5EwolEJJwtS+bV6gdnxE39DAemzWhYOlZqmXXeYKHpfMawBOmDDr2/q8BmZbQ+hk15YceuK/LI6VLtRqC1N0lGx9NUz4PYNZq5EupwQQPpRzM0SXFmJhgdArjzfUgDE+RG3/L1EUoYnV+XEbL78+imVAACwKIyhkBqfP6G9fYdtHzmX0pxJe2boQH/Xcf34kezYOG+1+K5c+rurOQzJ5e3rpBH9oqGRYHwytNclyPZPBuAFaG+Az07X++eg6xcIXgECbJ+B6qM1w4XMNO9CzdAIM826ZvGgVCjLgiNtNRo7BqTxYKNlj/Q+FOvCPsXdHbgyGm12OnZF0KVhSKNC/QAVdSMSgt69J+HCf713tL6gmaE1D3oihLYOrxwYrDqsGg/22lSohFMLrJ6OW0RwWQCL4OFkTMbJjU4lRPUElUVMCgUnuPGdEtoa0eOdvMhaGYYTyZ9/mz+qT3v6in7/UdDVoY2EIhn8ahycTah3C2dKbIrMSvT92USwNOR6Zd/zyeHYe8faVsgafcX8fhH8C8M/dAZ3RtFAUdAh5TQJKueLNPRcN6HS0bCuXo0rw+d9WbgmvWNdV1Zp+7uoCHoqdMKWBpYGQBdATaqvUotKYacRF2+Cqw68ENoTiuwfBINDGFGp9ICfG7xZOEuFX837GXmGpmdx7sMhQyP5ZJEFauqJCkxa6otXhiurqZfVk0tM96w+dAOqeaJIOLjEeXQYAu4U8AzxMQTbtqVyZxaBfwbyNPhaVV/v25YJLxBhD9mDLTMJwXp2BHcC3ikqsvd946kNogPW2MOteWbsvu/ohIqLWxt8bI08uTVHQlnWBet6wXL1eYvDIVb3hJeKf+u6Oe8KORPrxP9H6LB8kS33TG/AGI9Ylp48M+ZI2qwY13et7WgSPXcNYx8YuhfklZYTyYOlFTyfA/kQ8TYYOtC1Z4DRpPj37CANZT74oBJC2NnE7Kg+8qcK7CHlp9Oa9/XK2ZqMruQ4h+cBMFbee+kHwrAxJpAEbPvYN6jumIPm80+YQRg8d+dfwY4ZUR4iiSFRfKa38l7BbTJOhdXDSH4RbR4S6SGh80MWEBWHji5l5rUOV1Q2BlBnHSyDdjY5MNTcKJKGEe8AZWBGUxeIdZ8DCr+lt9Yz6TSPUdt0+aRX1oeSz6wpOrvt6+tKOri1DmY1L3S/A00BOOiyIC1NekwEHFomqZROWHj6McmY5qvmOeWcuKHepQJuUDo7J5lfCSWWDohwiDd6AwwA1B2bIuLIGww8tHA6wmBoTLrxMeqovZ5zkbD5YIKDUccmH2I1XG1FKx2D0K6tB1oP91UQAWfWX6lcr5nolPYGK8PkK6nBoVTFu8dY5EApiASQRVzObtfNk9WkAZR9bXZUM0EoxqJmWB5fYVyfWTVWVUAHPhX6igB99Qp02XfXEahvLImgFT3hnYeXjQhWcpCHY5q3eVs4YdKBhKSsPD+FPNGPkv6sLic1hAMmq9oMgKxZyTxiPfi9Xp9hZljWB+flz5R/fKRcfB775eJ0tRMOHsg9NB/eSiPmf1rqOxvYeA/farSoF2EV+pFG4lG1N2v+/D4z00HyJafNkFdZpHMaDG+lAWd4tHfEVUNv79MXrJcV6+WSuse+b3i5hutdUt96enrC8/MzrldPfhQ4bWpTdHQMA1rwYgTiEBDB8plPlO14HHs4HXOeLPTvmIfj/B3nVJL3ZnAz5if4H+e7WHlUyKaGf+eYeFu2IYrULv6nzFFTVl6qJoJREg59D9H+R4JHcIjSXc9tMEc+i8TpKUkTFvrDxMM5MQJgro93zkRkq6xwjvd2tLDe2UvSogpwQGDQbjRpuJbKFjaqwBiIs50d+3s0Q8nlnPdJdmDeH+IQ2QDClyMIFAdkQKK2wKQsT2rTMQwQp81O2tO+O61xLE2svkASuWlWSiR11ebKbMynsM982L0yrbkEQplkUnPoKHFNOtyTFPzFpJVsSgj0SRf66iE3v0xyfprLb6tDNVuhy/AeHjxE2v+hX8g5cWpWnIIOBECnD4f5jj1MVYd2QrcpWSqvmxb8pMpJvotku4gmjgrpduBa13B+xebrZsF8lmnxXT7Jb9VkQsngHo2eqzlZoSdw/kIXYJJZ9MyO27u6w+AzdSO/Fe2N8DHEFROt1HznpE13jo95nsb1dnsKKHMPl3NvRtBXjb7FqVLQAAxjOxT18RN95HrdYHCEk+DixfFcr5IFGJu3wVyXBdYa9qsnbl+fnlnBzke9bN6mZ1mzSt7M/SlpMwTkP5P/wIRhyXFz2RSQ1jH2kTzd99qsOLksziSNUGw598qgVFsWSF9wfX4CjD2bh6VdkTIHhmh/EXxBjMmhQw+FZnMB3R89fitwPj8j5naAZDZ9H/74Cz+4vv+Qn4cIz7ZS04X6yyfIT+9g+ADVjxB5B4Nhf//B9X/4vAw+7zZo/o+++W9fXTEGmZC3/FgQKIjIz1fznvFfzjeKrcd/lIjUSytFUMjD06cX6ICUd8qtPQCiQzLIug28+gnYfh5ecSwNXRwefjx/QdtXfPwfP2MfA9u2Y9unAHrKJL6fasYDjprlf3Wmf/tI+1UEn2D4CzxBYTfFosIEzd33Ym9pF3obsPIhha7msAADW9vJ6x0paTDYPgPFRcsJL1ZbvNCGvudsl5vJ1KGj1tjT3jZ4wUfTLMiI2FP6hycUGx+t72v30+xEaVJs+85e63ZcK9SzjZ918rTvwd7n/G4B6LME3pLQ3N3iwWOBQP/mqAr9h3fOM99/RPsL0Nr3eP3X7/Hyt19hFigQBjD5MzELqGfm33copaFQJIBJv3Klj+grFdif6S7m7mCoTveZrUFDJevFEfHQpbM9loWvPMZNe1cE2/A3cNSP2yTmkPlplxzkaZ7xpz3+PAF0CVX8zKaQn70ywRM/GeLBmi+/sUCzMP3CPujP/+L+5+fR/yPH78u3/9ceyQhiU/Oz2WESARP+xYxQ9ib3T6AwLOxdK6KHfobhZDEy86V3yNKxdIfsFQALYWVdmHbs2xX79Qrd3ZETfajDbkyzTnB4lh/XUspnRMvDi399Tm4cEDSQotcHJ+V2LnNcZeS4/iyQTzvau6WCOb98xKsfvkcwwLMBlHM+Gdfey8PxFZZ30RMOGJ8VQ174nR/6BWhvFNsXZlbh4cT45pcMA4Jzdvi2mH4pkAZJ9dKvaWGkNUIEM9u5gcFGKWEDA/tKAqINjh2xYIUCpB1jZXpUsUoaix5oUzXvp24CE8LQLMDaF1yW7rBPvQN9cZONFdghuPsY2FmBnv2mw4GVikYJ7RuSODjqp7mih6NoqKruRRz2tVNwGt/J6FFxaEcmT9BJnOv5D3Ab39r9Zuzzytrpt9ubHPdDgYkdz3d9NASz1IcARKo6u0lHbwtEVg8YkPeEgaGq0N3xHZsxiQAh/MuVE6N2mR43YAsJzqWIK+cSNJkVRGx1sApkoTOhd7SFPc/RvMZNxKuCl45FOkzYhxuVuTfMIGGANsHeBF09yzGj+8JsQ9KGCfsqT72KTMz7xgEHRSimsTWZsrC7V/REogcD8PtQ7NuOfdscXr0tgAAdPv+LraWwCaagDmAYGFMw5qwoQ2Sq3HZlSnNsnijS2h7t3txosukZDAhEJUmok+E4LnoRRLuCOWM1KHZWKiOxIegg5lI4vkAgkN17IgvXFHx/ijz+LocAet869nUnXXRSTARfAybcncZjV+y7J4PUtjmhjNQbQJj9KQxY9SbY94Fl6QzORP+8GFPcqdGx69WSYXSKcN+YoXp+nyqtpyMCcl6YoJ78BmDvit69n3vAmcU8VbJPrG04je/fPwPRs8fhZgyxlAFdezxiqcOpHX3e1RrM9koYjHUZltXnOw0xnRJRYjxZAaLOg5t0SDq9i1b970BuqFYH1U4j9qQh091iXRqQUL2sxIoq1pZVWfEsVpyKsmKcRiwhOOc5tqPAQZqjFnM1GJiJfWW53sk1Zx3jcJ/TGp3Wy9cjzNSpItkm+jhpD+184zvPnh9oJLADNSRtlP5yz2A93Mose4Jn8GiGmDR44GOi6+MYZaI9TDxqel8RBl8b977UBXTGGrgeTNbztjdaMiHWhcGFpgB6B8aAoBVwjFkmt8Ts1Hoc99z8Pqaa54cj4hgoOTlF54O0XhGfdIPhSDGnv2twOXWhZ9wz0JPHnPVfXruZ4ULdYr9u6KyeE6InCSEIG/m391Z3uO7xskGWTsQjVvaxwjX0FXc0RRspD6Avi6NKKQzrunrLi9DZACLCl24VwZRIXAPgPQO7yzw3RHx/qymGuXMqLajgTQACTjarwIiUoHkO6docVtMy0dOARYCdSTlErYjlLRhwZTVUJF1MgT1O+lw5+rUjpRI3eQR3Ur9A9L8VNEkKOO7cA6bx6cZxr9MJRw0wzrlns0SAa75h6RjCP8u5V8kYwkDT0hZP2lXF9nLFJzM8v7wgJkvp4Hx+ecHz8zO26xU6I19wUUWOPC2T2290vW/o4udXSZbEaw7bMPj8EeWn9PP7HD9uEfrXeacfzraJblOXDNlIGRH3UIM111VbJNIPOlZb0UvIuqYG63Fvf7/Gti3aHFo9q4L4f9GGLhN/sfrlpEaSm0nOabCsKGuTRkQZNNgQgH83qEPIikEwmIingDmUu9HrmvuLg5htTGCS46el9rXirJO3hfyYkQuCVqmGFK3H39O6yfy/A9v+xuaOa0+Ob6TTXKgeBg+dfgr4U+CBOkPALWW1eN7usNkRQYDQOQWgo5knmCVdll0d7zO/9e89hGO7w4e+dU2Od/6Y8rWFHwFOAxL+NSmF1pQV2qwSN3N7xSNK1E/ixgaDJ6XN+pT3gpfasAhCnv4FYbcGaRqF0WBZ8+F1Qq8JXiXRkuFG1EuNNR5olsMo/lIB7kzyCX4UtwtZo27zW1OqGTzP6pr0iWnZC/k5St+oRBTuH40gkE3CY+az03d2/MqAfBb/4DvRRp3nJWhg0n3yC/F+82CSb45di3ce1ouJ0CKdSA5uL5r6E7fnl4R7nm1NTioAt4cclegKVWBZHp1vNCRvUnO/gxlSWY97dfrQtpcXiLlOFckgIVfVovWiAVr6dSVm2s2cxjH7yHx+Bdlfnedn8qvI4RaxRc6S8tvS848dZ3Zw73l5Lt/R5crthYkOBUP76Z3b+D++y+SjWP545vgnvsfvPWKZ1NR9c61BfvreE30N0Pe/IkYZkm2uzAdwYEHzfRF2bhQdmCLbcAAAUZ56yA1WuQm8aCra8SiAMRTXsUP+u0F+eIPr3z54sqI06E+C8XxFWwzPz1fspqxqdt0j+VEyQtcO5uT/Rjn0R4rs7s7nXd2O83PDv/zzK4CVdDLg8PPXfQdEsPXQpwyjK/pokxylzG0d2tT1kyboe0G0A8iEPmd3JaujvZ/znvI9zHww/mfUzdzn35i522Gt/Cfxbql2nPSIufp8YwB92wZROGZ7FYxdT7o87+ftWg02DBvo0wVyjr43ykfzNU1sC6v+6/r+I1sDAvvfgeX7DxD5Hg8/fQ97/8FRcbmWB3KQCGOH7JMb9SP58kFPJ7cLmSiSn886XJJO2AOzPZH3OhYpHmiN/9eJposcLXW3kagupcv9lm/l/2/H//EB9FigpXHByDQMYN8PZ47PXLg31rwSHTOx4IaZveLfT5Re0Qvridf8bkJI45KPSeK9/x6wsD2OokJuL/nmkbrszQYIhWiCrZGbPXQ73hBqEbC+56SMC1KJnMbu3PRm1oJ5No5rqAu/Lp5dp4BXZXL+uzQoM19EwKoMQKRhaZIZ/T2yIJsLzpbmlWDfXTkb+8C+bdjgffs8eL94ds9kLLsCurICmEx6fOEKPQB4Obz+7z6CYYdyFA6nnO1pkiaG7/zNg3+9vYab3pZ9cyDiwcHo/zYxstDlNZ18ZOD2gOW7ln8nFKF6YF2bTecC41NHQy+7gZnESkhxd1w88LvJBshhhPSc8w6RWVwGrzht6BUkaM0di2ufjGqfc2UmLKb+tVA4xKEorrqgrwwYqXqvSAsnhQAjBknB38LJ7c++NODx9SPWdcV6WRwOkNWtYuqKiTpU1rVtkNagO1iRPsOfTnZiSMVU5Al9spECLDAkpt0U16nVPYqAHF6HlU7h6B+7ZwzurEB8vl6runra7/dI9+s8px8EeNFWicy8+o626ApAg2IO5MP3dYpoOgfSMRn3DnWmbMoGDzhlBWaweJV09GZVjRnGGMiILJ9FoZE+fWO1SmBPhKIePWkjoaMtHb11RB9qdABDMZpXu3c4FLvDw3slcVTHS+9YxKvR+tI9EMIASYNx707Am0TwaFmJ4b9v7He+7xu2fWC5rMj8zjA4tRx767J6b+vWPEO090IqGBEs3TEwCI/GADgUYh1qA2PUmuyyszjQx+e9h0ZWrBlh4KMXezr5JNbZ79OX7n8H5F5n2scuEFH0ZfVkACZYCeAaHMlI1RNwlsX5xhgDETRO//HkSN6uDknfJvh9oCqdBh0kDmvujkohCoaqYrte02AKJTy2Y1i93hbC76W6o/UFYzhtNBqTuS8s2nb4/AxV0mLxy/ORPoSJJ8oAIIYdgn3fGXjl912qR2vIH5GpH+UxYNRaSyP9WB3PnWwGVQ9AtybYx3CjRBwe2dDRxg4dDdp9zQOua1ZDDOXw2WmRBlz1fUZ00sKs/sW9wMq1VOzLqj7eSUmLzXWBMarqxO+lVX0eUG/DPwu6AwNYHozU5HveYoED5ByWqPY2ETm2tHfIS5ImJ+cxqiLWq2MZbJVUDtKgV/v/yHvTLcmNI030M3MgMrM2imS35v2f7f6YM2o1i6o1MwA3uz9sBSKqSEo9LfW94ClmZgTgcDc3t30px//cZ5Y02z0AIHqEhewROBjVB9LBrha0UveFgcLlaIIbswMW8e+0camk+f+d/6s0p5PL8HFKM3Oyy5RRhQQnJ06++xuYQkhnwZH3OTPNhGet91KLylY/o42/WjAfEJk3CrQAkOBhQGahw+egEUyBooNwXkRq59SDJsaIIImgTQ2X3PkdWbvEJg9xW69ozQtUpfFibwmSxnb1CjmgGRvg8HB+eJJlEoaRMRw757hLcJwgVInAVo1E/W8L5ATAgUNxhoEIWotSlZ1Ou3s/0asbRrnNJeebOGh5n1Oi2oRVy+jjx1lb1ovtQnIWqQAAIABJREFUg2f+Buz3CSj2NLqyKjBiDxm8MAabfLAuFmS2ixlmFIJlWbEsI9eZ8479bgBmr6JirX8mZFJaLxTAVDEZbzpeTJM9U9R2B51ERisIYIeeximx4Iup0ZXSxt4hwIsCtLvM63uGBfQwoC87FN4HVcO4HrCORdS5JESQx/HqGbNdde3ZJf1KfNI4a/bzm/ppjPUdB98N1XIVIcld2hgitMnONfs/uMEw5KnebozHcN7itIUV1+cXqwzxCQdaBrUgyn2fmNuGOXdAxPCnOck1adLJcU7BH+zshMNnRpUu1DnokntbUpO9jxpcyl1OtbL0efu+/+uwzH399hbV7Rq6kM/Y6ZewgAUQp71F0wOvHTZSL4vXiWejmjd7Yt+BsRBEJ6LHdoeGEDDc4V46F+6yt4B7VqLDEeuTKIs5HMdiFTkkS85r21N3dEXVH6dTsUTAAleCJ5PjAbV35rmIzNo8G4oImsyqIURZJa74uiNCvrMM17HWhhEIw+7xeDXjbY7bAs7yPIbwU+Byoacyz5nrmaiY4jJDVFAJxxG4ZEdOfdHHQfCV2kiiUgk1F+G4wDWx79GWw6rzKMdz8c13nj+BAAQz8qv9EXEOFPvhfNmy0+OZtP5VVYFGhpOt+BiUiF2aplV7rMmo274iCIOWAewTnoAGFx2gOrFeLpB95rwjQDj3sx+eLoSRzSnml3ZWP3Qdr3Md7eWEFkTntM+c6FQJHGT0LgMPvApP4ovqoUJF7Nc9iTLnHXgUcMzv9QB3gKx0utMwSHyv0OG20UNFgTZeex1inYrMzDad0dcuCubhtELAi2WYY4rtCwDQMDlB1bJ/d9PV0XTZTkPosjqYo6qiUxB+sCo6lzVlDbOVeF2NLdy1pqOMdQGJYO6bV+KqN9n508IFRSUwRSBUfO/4EWfc9M4K4I/JRyUerpIxzsKr/P1UwXj3GqRfgI/lvAX+sWz0e9eZ9REqk/QgS/vv16gW4p8v/sX1+QXyi2D8xK6LfIS8R0rCD//+I4iA7T9+Bf9I2NocDij5X3z1092vzwQ8Afj6f34BEfDqzz+CmCDTJE7+6R30lw+HuV3vjBPfd/YSetiDCD6qna/VdSH1ajgywnnu+jMIlzGg3pLTAlYZAnOkf9IJ/OU9VK1VBP0kwHwH1QlWxfO2QWD21mxl4KtvapU7c4MvetuBNvnS2G/h+K3rW/yn9HbcONGJCJ+h+EHNlzLdzoQ5MYmwXUNTMrt2OMXTBsvW5msMbyPK7EEwjLGbXjKj7SCQFXdSflBk5EaszSoGNdlA1PSR6T4BhsstgmhjEfouGEnDQ/4sHc+Ck6fba/a5m14UNLRV7CQd5j0JW6Qnjgy2ypmrKt4PxtO0KgRhnf5M9p53Lui8+vPPUJn4+h/vASI8/Ej4+otk5bsJAn4FHn5m8FjwArPTvVHgk8saZU8JHPqODhN3NhZ6RJzTF3p/tB5kcRw/bN6+mcF5XJZSr4w63c71sK4Ama0RAHpAZ+ofx+mcpkv9x3eve+flX/X6l3egxzWIs7To967fAnyUdK+L8KD/Tf1B/guvnO5BqPvvuc6vVC2ZPgRtkHp/lzoOol74TBSbTCxg6L5bqUNX1CYzlijhwQPLnBhzYl0mAC+zvSxestKYQjybwmoalXfrCQxTtKMUY8ynMjdMoJZ43txCvrrng7L9R2BNLtAfRfUj3G6BSmmYIoYp3akYGRNZ3r3KqFsAkE9SQ+Co3FL+ZOwfJ4xdfYXHamLBq5xZZCTdrjCEfBdvgigroNyK9IXRiUrISOcAjmqK+rDqTDiyb4gJA+4oBbIHXuxTjyw2pmgOURWB7hMyOHmCIgT0o1HYMpRRpYaZAV4x2LKJBy8YrxbIvkPJgjlUxLKQFxc+qASoylKMLSyo58obV9ADJLrAdCt+hwLFNICh2GTH3DcroUaRnSBmjAe7E88UuHUsEL2aAnbYy9+ikuN3o/n3R/uOgHB6QTiH0rAdijGQTgbm4ee+vaEdojBMV/QiZdn1cF7Vo57hxIwRSnWOg3Qs0hgY1PpXwgTYKd67EOUYGt4HyMoaWfAF53vNAESqXp7P944rO8CCV8qBQDCFMwI0pjum2atwkJcGJcANLcC8WjCFToFVUbUSsuu6uFN1MQV5Tmw7Y8OGKRO8+TzJhScwpgpoh2Xt+GHlIR74JOmgU3dyTDGqYlRCEz9ib0Lg7g71EiTDQYhSEnwzCIBmxYH6VzYMc4p2M54jUTmCVBG5J/FidSGZtGXvp7Gp6E04UeO7cGoShcNDMiNqgqBqpb+nSGbTdAWgG8Uzu17oMNd+FSwML2da7iKTyY3b3Ptlh2JkA5Tz/OhAH8POVdDIKul8noc5gi0BltLgaZnPwBKR4b6m2o3jOQ+nbcH6uGWnX0uj1uOfMd/DiY4M5wOBQO4loO7MDuOb5C3R69wMVR7kgIIF0OFi9+gEwMMCePJVE1XO3c5TwDzXRYEDbr5R3yhiCE3jR9OdA65g2nNxdoyDiLpS65kpljlvCv82d3fywoPeCoBxjkLxrt7pmnCqe03MSMPq2UB6pvGH/QwaEDKMOdXSoInC65N757CH+U5CMfbvXTHozdzo5tPEIEWVrozqHuKKvhsNRisbXA4QpPOCQvhKOdSDc+D3+MuVrF9kOlKjtQib6ScmKYIM4lCxEnLqFUqE2XgFfE4etKFQZG3OJoNlgKsIhKy3nUq0/mgOrDzzR9glzgAu05/3T2vLA33CudP2sqFF24AwLtDd/U3nQsDY36xxdDq1MaEv94xAEGIo7Ra6GYZ65WzfQUzZw29gWMazKtbVAtCm7yEDwAKj9USAO1BX10fWdYWqYpsC69PMWMZiDvSozuJSxOiBgA6Gg1w5FZNNxieXAWSfng1vff5mBKtF0T2XASIASolMx3K5PTPGc5v895CNnS7VNlqlDXre/ZNo0yFtLC06ku9w+b+fcQR+4e6VZ+PwmctAneR0kk/t9/iFjs+fBdmOP5SPdNmQcv2U95H7+Ez+tOAHzzIfJlfRYsFoYyy4Xi3Db4wFgwaggu26Ydv2coK09VbAg8l7MucdGSAPVelW0FoQhSPQdZvGW3Mr+piOez2QBNAqqe16FXeZ/BbEMaUTbOMdvkVU5/OwokYnEgdTJwfgTnQd7IE9IfOQO/Y6H6rg/QgCEktZR9RxZXaeLHxcDFngqZ1HatkJOP4S6ER6QkPqO1SXy4ljGe5MYxBbmXbN8FfN3ymAqTXuYR8bD89MLaeZ5T5Ho9E2HsF7Xie0KNed+5IZpHRY942elu85yl4JHz3f32WI4kU5LlN9eTjDMcfDIb9FPqYy3DqPI+fZfU1KsD1wR3TYZkKfgxx3MH/7FsECbmETf1Y5jvMTt38eDpUF76rjWM47CEWXiYB0nkc2fdIuJwtpc4gxAhZ63jvy+zVxggiWq3BYgsuc16s9LyHDCLg22GHPbSIxTPAYH18jO1yS91ADZH0f40h9H/hPrdqPIuFAmbih7R4PINC+zxHYp1Acy9D2YK+cSwQKxvc3RA/gsVjAVP8qZBg64VgIMQe5qwG9iD2gpsdNdeeQ0+vpweZWoc3mpJ4o0FtkEQ2D8cLQq+lt3F6TSyGTbcnnG3sFmCMfjVYDEXSLKHZj6/TAcGaGeLJP6NvRfgKA3ceNGboA1NupOKOq8vxO/5gp6V6/cuwm0zAzSN9g4uPNE3FM+u/9s7/n6u8YuHWin9+F9n3O5Uc7T/KfH+r8xD0Oe/6RMN+f7ImN7/93X+lIFsHCI5MHmAD89A7yy0fnT7ZuOTxbONjhErrpZxW8kar6KVBrZRpybrRFImAw4zIWyBDsY+Jl7CBPwEn5VwELwCcI3sHEXaMP+9yhIMyp+KjnXQs2bcEm0e6IgMJHxR3M/Afgqie7hk+iaKCvqtHaqaY/KiY2tsqSSiZjDil5gYhAgyGsEDUH+hhsAfmLYI6ZtC8CxxVWwrsDM+gAE2dGeQb/B80QyaBI+JosUclsmXNaha2hw2lZ4yun828B/141cHpAb9qRTWZkFSgY7HSGvGJYtARWHWCeWZESMP2aYe0FODBRAZG/pZQ5f4EnYlLudZVsL7mHfychuZUYYjaavC0+Tduqy9Ulq/g9jQ0fX1IyYYx1z04XOJFj5mN6uDPeISqm5/zDVBMnRvSvf/2PcaBLCFdAGn16vxsAeFTC116G63QZgbPrK1kW+qN2HCkEKPT9fQihJyzWGKNz5v7zJMD+0SvmLP7yRxBe7g1zQ3N9feHw9oGC+B3iQJvgfZSjFQIvFXvzjiAdRxfKGYqign0qBrySANwR7oSWeThx3CEysM2JMUwoZRfM6DC+z1MEMvcs7/HycsUkgOHOJm1MQ02VtWecIWJCsaUTMiPNtWB1Q7Ha9fDuDbYPn6wnU7/9W3sTykwYDwhl+CGGzq9QvGkM2T4XTIQocHbIdv2fAKxvXmMsDPmo2PDFsv59tJ2+OoF+AEEPjARqxneCgoKh8cnwpB3+Tt6didpczCgs2Uzh0YV9Nyy3/4Oix6cC4mZLUcsacluxaPQqVoAuYF7AWLDRV0wwhj6ZcZjEgwU8ok3cKIkQvqyb0cAjWIeV/+EBvBCgDL64wXgQRK0fOo2ZZZLjnIRQMd2Zahn1sMjI0LScITPBsnshMJ9VGDdtv28ojlL2Ng2Gxp5RLO7weXl5qfKXBD8/sL6bMEGyZyn9nouAlpGAA/P+5v040uJi0h75SEUNwjBK8b3jHN8YXJHRgsNbODCPJqS2nlfEGCMyEQzu1U/KHbPuxOAlMnQB3Y0mDgC0NEF1+rvJgzkWh/+AG6/MYTGnAqsZyZbLinVZwby08onmoFWCOyqnvZNs7eyppEqeYaRLLNyEXcCzpG3+UMZQwrIusUw7dQqoKLbxAiJg6gR7xvuyWE/uMZY0pIpM8NUMwUaLNwwdlR0d92kErxCgAuwmSKcSM6ed1aDdQY0ohjAaFVmr7HWNoiy2zN17pZXgpFmufSB6rC3eS5zgPd3d4BVBNpna0ARMKGUmawneTT5wgV5BkLnbXnEEj9w6GRs7hLKVlo1AiX46RNUcoLpDyEtVhbGJwypFZVB0YN0TP1UqS/Zw+rQinaNvKimgbBHrmaSy295FYk/0Mp+TwDwx5/DS684/m4EeuV6bmc3X3yvsvGqAaTo9UlNIBWZMyaN4SzciI/n7hOns8IwgiPpE3Al4o1yiy+El4dU6Jf8OCSdx0iPOZWbdtlTaOoziXqYwdIZTT6HTy9yTVL8wisAyy2wlEYCqJJZHzLX9zkJfB6kSFEbTkKOi3Hz0QJ8ZCBCGw+Ar0fcz8M6CQ8JpEY4ch29kevlOdKe3xoG6s3/f3lGTMbOE7PeUpZQxquKMY2E5Em4e0NtPYs5Omw7Rhems0Iqr8awd8exeMyQzhhgtHmwOseofHslrcZ7tzVPd0Agx/hYOTfYVOV2gCBb0ILF0Gqop75ZJoB4wSUWDNGhdnaLIWlefDxB7705imMJPc7p4SV7wwvEjjDD+e6ku5AFAHAWaGm2HywqnffTtUDlLp32bSpaM4AVmBpi8AsntfuarmnE9nX9xk78jDOYRdy1QjJWLv/lYpscwBpmc4f1DMOcCEFlArxIEEztVxD1oYFkXc6CPgfWyAqrYBSBMD1BYMJhQdWZc6uHKAlHncRkcqqWT0DTeZsbnOOvRckMdzxzc4gYoEUy1noJnUh5VCIgJ5KXpAYAf3KB0XVJw4iWecp51dVn36nKKClSn/157klmgtxaczp0daal/ndhcARslN9b8T8N2M+wZ1UJ2vSEzmutUeHYvmeM4eGl3HBMN8PAAW/8XwRFWfegCZmB5eMDz84LtuuHh4RHLMjD3zQpgbZtncAQfIWSwliIDRqMazCHYMNXE4kGimuXNSStr5J78ormPDdyNRhBKzsg1xz1Uf5+2s3HW+iz+Eehmf292wQ9j8CoRtaTDiJoYDqd8fzcYxr6lgoJyEPr7RbwqU4NpOgrbfLGUg7UjaFgv6QiERmYSOY+f+Yce1KiDAI1ysi5nDvVsLFuVrd/1gXZ2Ili9aFbItX465Pj+6P8LIH1zJXXGmajqbrWRdzb5sKg7X/Tvc459zxvc7uw/tVtMQKUszV9ynctGvr98eCh+D8Ec9jufXuayMYXDztdt20QHsSBX8B35JPc4zmYHUj5C5ydOZ6XBO+Cm6hWwWna181ETn3yc9ioD+9HbffMb1Z1kAuSBoBIiloEzczf0Et1312etPLMSsO8bSMnsDK7vHperDr8D5tm7qEB74yRvLYcO2XNun9G5J1E30Dudi4pmXoXDzkOGpSBaHmm8HygHTztrls3ucHZ4d2dCci9P9rCrVcHikbZDc8u77SX1TsPnqPgh/Ww3FDYZwGibitsOiK3FB+DZ/wT1yoqXh9WC60hxfY5O3WqtvRbv3QvLRNfNxigrFmCK4pITif1YxgIaXIyXCg5mOzWIiCqGmAMObbmKWdXQoMCu2D58wvLDW6TrxmFXxy3gU2crHPF15K01lmWeH2ll7Zf1eg5HJwi4/Mnee/31wyH7PH4Gtv52qt7962w2i3HPVIRPnwV5zPm0dfCPbzDffzq84/NffwUR4d2ff8T6Z2D/y3try+D3fLlPtv6vXl/JMugJCv7r37Ajm5Nh/fkdAIB/fgd5/yHhy3fGcXRIOqFquCZud3oQxScAKwEXMkcuE3Ahwqt//xO+/PoRQwn85x+Blw3z//wVy7Zj4cWriXmiQ/BiwOzDAPZ5hcKTVQj4RJr7mB6owH/xhAGv9mQ2MCRe51q+tUbckZ2+9cA3ngcariis4haA5acfQETY3T6yzQna92AxmGIvYzjNF4YuiqiIui+SbezSxuEBu+I2KYn9DR3Vd7XL/8yclU4iSNKSiNgCI+M/pszmDrtjVHELmlDMrsYznIDp4xq6mRm72CuzEapKJXNVjyJSrCwYxPgwCJe97E3kkGCYr4RUoL84v4HiGYoPPo/XIAy/b//lI5af35XMDsUbEOr0/rHrjCcHMevOnRGw8nuPf9oQW7JPioSBV06cmKySEkDeHx14vr5AFXj3+i3ef/wVZyQ+2+XyDH1Trvyfdf3zHejf4jDt4xD7fq8z+3uvCsL91IZ6yYji0/jNYPjdce8a9HA734ZbLkYZXUijw/13pYGIjkOdr4sC2x9knN1I8b3PAD9Qp78FFfloySMtrpE0S42YXlOLj3wZk2LM2clEYH9HlZSNf5Z1sc/dSm1ovKVicGRaD+TrdbOIf+9lOmGGyEmSDKSZzfNvI/DXFNCR8/5t/OvGlssPb/Hy8VM+70suRhAWPAoBn9o47U+tOQLWA5uHEeYoqQ5VTHw9vaPms7557SVmFYovmAAGAZfXr3D99OXeSm4IdAr0/XPtyFqCSHeNdv1WfR2UcDfAmvHSDbxRVYALCNr/F1ouKYhWhDIoao4IdaOeZLRrRBzXlg5Y31qhR0xcvd+6leDM6HgEM4cpSuSOa7L70BX7XKs5SQBKQ0jPvGBYZLKSYsrukfohFOiBFiSNOEnYKpoZzdAS4PzAOFpVpO66DAfeborTQaRH7lZspw0w0qgVQuzxzsKJPjeAmk7eKiIQLOPOywnewC2cB304d1qPjBb0/s7uAFe4oQmc5yXGtj5dXCWAqWZPrh9GP2EAoEtD0MRLWJu3QQArTHe1rMEwno/LimUsuDysWB+s/JnMiUlWspFVQYtlrxuxsucWHtiHAmKlluDKdbgZYjspSoMmrrlislygoljHwFgtqCAMjxAPBCA7a/tm/YGGRRaAhlVyMbiYYsw8sGNik90M8vue+TAkpcBMhEOoBFfVCZ1WWk6JrLxyM16G08Yc/7aGcKRbpKmks+KAbH7ej4EWyJ5EaWPRypgG4nE3ksQHqlA34lBgKRUGa3t3P69Hof2YMVtO7wOxdpipH50JFXuvhmOIKB1AN4LljdEUhZMaFDZgi+JjGg5vNQVqCpiLnoThIwylUa4/xtV25vscMnO6CS3qioqdabWyXxievcmZzR4ZtbHG4K0AED10w5glQlU2+sRhw6kR5QJjrISXhOJGGRhQ+1H7IlFOPoK9TvKazU9u9iTvJb15xrL/8mmrYqCRzS03Y6iXGIvqBBIllkkS1whFhwBXyH38GrJwFYBXpXBlV6ZlnGuVnk+HQgdL4ox9LykVN2XVfxRPRwpD35J3a+Ydtve+rb05iRDfGMXv/g3x/+ZrCgdr/MmBxPXAYbL9DDRYaJN19Rvr1xiu5ETDXefrigxui4o5ke1gcyOnTeT0xkO01IIeerlVe51AnM/ECq13tX87BeEYzvmRZWMSXBkOhZnJHFbtHUF71YOQ4sXGY4HAisg0SjoeuKlI43+KFgkqdXidYBlDxH45AirMuF/VPYsG3GZl5MOIbPZlmFFozj2/MvhFaUZbOg+r1hJzNrqx5z7ssDbh4vR8jIGxLLgsi8sHCxTq1bJio8hlsqiSAoTcojC4WcsHdxoPgEkwOSp42TAign2zKhPW98+qa4m3ohhEbkzSbNugI/DjNy72Hu0i0FWhm+tyVwWtAJE7JBaFXE90kAjrq7WCH7vOTEfnhHj5/Nwg55+G8iU3KEVQxJ19TZ6nLo/I4esbfEh8jce7DmsnNt+t6uU+jTIxSn6xbDfv7ektF5ZlwcPDBeu64vHpFcZgPDw94vOnFc8vzxhjcaPThG471AOc0vlF5bQiYpP5QJAxj+fFDYoyxWnKiX+ZQIxJarLywnnmguZ0gaLOjeMc9DgYl8M68DJ0iwN0+1mLn1S/pHwS232jM9YriaJywgQwUKy8ST7hmOotcWJpMBnbSAY1QuJzPunSQa9rKjsm9zk2WhiOsqTnnQrFLwXDQxENModoZGJFpTXR3SpLQIBw/lHQ5cg+VpfDfP0anxsOsdfQVoZVw0lE9z3s9NL7TpcMGee1y4HHfXGm0TYJd3hm7ZH9Xb/XWXSq5zp2yYaUZdnrts6HKP9OUZt7AGAb3sp7ocu8RWSLqSQZyT10+gNqJUgDZ29p0EEPCCjm2P0lZ6p7OjvFUg/jH56kMywLsQine/uHiIAYcxKJ89qb8SjOfpxvgFdvsaURl6EZkKHqwbmqlUzitoZmjgLazwpsOMrEce8hyOeg9MR6KoMcQAt+uAM4xPYHrMpRHe/K0sd1t60/ZJFAOW1yXLbUaEEdLZsmnfg5f/XPNfnVYdKnoxb3AUWrJcu/2z2ZT+8fi1d726Ndh9sTVBTLumB/eXEH1ghsyGSPrK+Z8i5A6nxPj8kWVFE2to5WPSyyQOEQFPGAdl9v0P4ZAZtkCR3y5smfaTDW2pUCk4KaK5uIDol0eV/CLmgbUvawZCw2+0XeL05Lj9txQKtEw8Kffs8F90uQh4waZO1G+gobCgrzTos+rCkrx7V3eRGNwzXgeMp3Aozv6LV/5OqjGQ7qjWxHh8NviVdM7Okt1pKIPQhq/Ajoe8WMRakektRS5s09sndNFez7jr9tG56YQFjMCTuA1e1aL3/9FUvKoqZPDU/2U25zBWHAnM0V1mrVna5//YB9kAUlHmjLOXy/cA3o9pKE1AmQd+AW+5WwON57sxf3dJ7cJPJKisD85SPop7epD0YLMJpmh/COCYarIdOKQBbBqsCye2U7qUo+Vg02zrYn0kwxGWZotUWLKTk8qoIoJ+2YIqB9AuxtmUX9XtdLQ3IxkuN2TbcBq7XgI4790AyG6Wb1kAUtQavZd7QCFUWBdyDsxFg4qhiYj2Tx915+JBAtmGOAhbDJxCejqHjl7fmUCSqECcVysDkE9aUDT0PIG30r2+9OdRD2m24apXu4Fe+i2/OfdrhOH0+vdixxG4lka8n+Xf+5i7WNDL8fEeP14yt8fv56M6//L1//VAf6DSG683tcy2A8X80A0rMj4pIz07hzEZDl28PZ89VPWiF8zC2Qje4SsjzgJiH5QyGMdsZy+4zJ+9U34GB0uDtxOhLNe0YR6tFc/YAdR63DFNFCFQUUh7s/aQJb61vcsocIzsjFnVIcTnQXpoihNJNIx9jR73DKxJQdUMuMG7CSh+KliY0gqvXns3rEGDSwLVv2o0tlWRVzt4z168sLvj5/xbZt0Gl9cnfdrLz3YgQi5jhVodhBXn8oZIAgRqwhwDy4wtudzg3ODuaXj58P8D7iOFWGeSgNrthQVLEKhSOMliIABPMzwG8WzN3gOT99wfruLeSLWJ90VQi+JsKZ8fSVOc99Lcvb19g+fgYB2D59tr1w9CU8m2DOTybI+JrC0Rvll3hyyAsw4/tEMzUBzgQjA3LCSsikoTjwLJEsjAqjsrDibEXJGCgIq98fDrANICfgAADL/tnkK5SAQQ+WbRfMTC27fXlc4LldkJcVQjuIBOPxAnkB5lCwmPGSdcUUIPpKW5sldoOj0YXo3c4YqQhNEctkg4DInJpKq/XT0TSVFtqEdoHAuzhnLpSQlW/dPVOXl1GZqYFkrsiy49a2bQbXxRh3lCOOl3KWFrZBrO+VpfaabyfjCwu5Y66xjwjjA5KGmNo4MNX6ZS7kpS3ZzleUE2Zf54DDj8qUx0ReFnW4E7nN1RXSKO0fpdaZR/YmHTywjAG6hJRY849sjk7fDZ/bjoTiI9bfaKeJlQljrFjWBQ/rgsurp8xWY7KM8MtlxfJwwfNXwTKAp8cHM55FiV8uIfu6T0RvW6OjBsVwBJpCb5tLXbHnYdGOY2AsUQWELFhIPBCJBxSMfX3B9bqlQX1iB8aKdRlYH1Ysc8Xjg1gfcofpdt0AF0hB6j2HARrDsrWjd7SlM4KGOX4iI06hWIbtwVi85D4os3r3fbMsOq8sYQqnGXmwC8C2R+a8AKDUMrJC0QhBMQwJ8B6kTXlHjCsAq5dsIohYj9cxBtoJ9IrklH8fBNg8m4kxeSJEZuOdQdvdLBX9Wn2sMHSbsL23kSaifcbhage8Z1rmOTZrRc4Uji+iAE0X/VyJAAAgAElEQVQ3fFGctXvKmEC9CkaU/U14sHoVkXJwhKIXxvTC+wvWywMeHh5wuTzgsq5+n2Y57NibKRHFbM6UqSgHehpzFMmcGi+Osxt9kue+Y9ut5PniwUJjRAUBd1YGo5mmmXNrAXGQuzw7KfvWJypoGQPVbPRjYehUlD/WI9FnBAdY1jFTODImdiFAJ0Rny5ovmajtiu2hcGKi8ZVwDiCzytIcHrAra5ZltzY51JNokZmLN/Ky4xcXbudg6DJ37Il/p8f7zordvbHE4ZN9UttjKX9r5Aec5FgPprgXgJLzjJTjzlMHAwrsUn2wg6Z2Q2BcPEYL+KQ0vobDUolAfk8PNBGtQm4Ebc4eg9uMajU5T8UyFyuTJxaQMjX6W7uuQiYfGe47bRNAxSpcHJSMNNaaAybhJ85ftZoTZR9nYmCYTCGsoFlGZvaDoLFvcAO7wzMcegLySkFutAy50+E/hslHGuWpxwKZO64v14OBIHZ6RMARSZPhJNuYhDPNCAZnEG/0FVeH1XC6YXRhTQOBetsDJi8xSsBYBi6XSwYdkALbHCir3tWCMxlY1wXjcsEgy9KyXu2SdGzxVi7Zj1ojcMnx1IPV5pzYty1x9nK54AGWORZZzyqEbdvxsl3x9ctXXF9eLNCtG97IHOjLskKJoIMxr/sNXyFq+EpezSXOTegei8tpL7AS2iEPNXrKtkmAWsujOG6ZAcHkmf91Hg9nlkJ+NPyNMsTZ4xpF69i9M4GDCnPym+HV6RMVDoUcCbJMiXACWMCE3+NqhHq2oahiaYa+0MtDfmEwiIbJc2o8fgzG4+UBr169wtsf3uHx4QFPr1/hb48f8fnzR1y3HS/Pz9BdMDerEKLTy0Wyl/dfF2sNxew4b3ivqtaCzPFj33fsADBhLXUUCacismZwX8biPMHhJWJ6rleHCSOsiyow469nvhIBYrKWuuycskfqrHVQz1LFUdZQy+wiZAWc3Ft/f11ujN124AKwt8cJo6tOdQRzXBqlJ4rzaPIAA5PtKCvVRd/ztM+IHNaA5OHT3+Hr8KBdDt6rdmZq4YqGdAf9ITLK8x0MENv+jKHYN0nbB5hAHuRHMFo2RaxEKky2tTL/5NWG4jyEk0KtCkEdrpQ/q4d0O3r5M+wPLdMovvN91sZPYoyDfSsX3jfTR254xl4+d3CdsZiYQEMAv52k/54VfnJ+8P63VHjl8hZYkRa+lJVChgmpqr3CZdk4MzlOgK05LeJntGDZe8Z02Dhirk2m6TKnomSxfLqNo02syv1rczWZsvYm54jDNrt8w+nwNho+ocSIyki5RnE2N63aCZPxb2udZXgk1x0Er8STFcGcZouY48OrLUUUSciMIQXdZPbG5gTTvnOdg4vzOaJqQxPrRbzaZ1oC5e3jiAzw2jeP7/aM196qxOd4wks/ARWCGpUCNBzMmvKRuLGNKOwtAh6c5aiDDqmq9TMHspIl1INlI3N92vM6TZb9OqM3re0zKeHy+IB9uyJYxZwWuL67fasHogUekdMVw1+1rH91uc3tV9DI+rR5s+YUk9ePZWDb9nQAmxOdMFav2Oby2SEwhIK+onQ9H2/uVinLHH8mO8TzEQTZq2GqV3yyTSoHvnhA6PiTVfXE3z6W8w11fqR23MFjfz9ovubu9ew/X+V5c9wKvSlnZJ93B0zQJHL4AbAWgpjAT28wf/l4eBcB+PCX9wbvmLfWvIEuc90/W791nc9dBPLe6o92fXS++E7M9vvD//o3iEzsf/0VE8D6b38C8BaEj26zVjyJ4GtU9XTZAyALAm6w2Pcdz8/PkCnY9wf8/PCA5yfCqivGTwA+Cl7URISnHxkqHwFcgT8J5v9Wr9xkSRuswOO/DXz6qweMkNn6vvzlveloWMwWlbC2zWuSg9nextH2/TsA6uM5PMO+1sjg4d6Qv9rP717OV54xcfnPD3gcA4MYz05n9inADHkcpeMxYZC1o6JHwpwr9t2r2s1GIzR4T7V9s3NqMv++7+mcjnUyERa2FqRRIW/uO+a+p4wV8OUxsLTqMVMFmLu3OrNWlMEytn2rXE1YIHjyeW2gTJoBvJ6mW++AeybMPr+Ogcuyph7yb76/gwjjC2H9+Ql6+Yxt3/FlKt5s4gFDCjBjwn0eAsj7jx48EOuv98chZ1LPjj/yruT7Pr+QPdKRnihkdLPYG6G95XvokfACSoYQEQy3GQUpjmuQtwlRkwPYyrBi3ydkKsYgvP/4/vD2b1OdwAv6xvfH5//Vr39+BvofuL5Bs3//8/7z8Q4H/G3UO92fGEJJtH77odOv3yCGT8p47mHqwIFw3nvXjfD8W1Oh089vT/Xw19H95+91Qp/fa3O+uaTaozBTaPLyRAA8eq6UARNqBHMKxhTsanv0wi/Y9+GOJlM4g7jLboT5um3YvTdoECIJA0JkFicM96OQnH0lgaOrBMh+6PlRiDy/86JQLbvO2aSqPlqTKxWKiWes+sYMkaogetUUR4XiuQ1CybgqYMLgbv5UOggCh8uNDOelxZ8hnJPGexw/4QEHYWymiICv71NdzCj+43wDtmfiG2Pblw1xaQfRYwYlpwMWl1IY4zOyMivMA/NFMR4WLK8AYD3sy44rGIIVb4CVIfuEkMKThjG19iX0qSwR3uAayskYwFgvABT7tgE0YOX3T6Q3z1Dbs8MW2HjruuYnKag0o5a4gqYArtcXw5fM1CzmdWaSlpuvKYCQEg7+85Tu2l60r9H2GU4jythKucedhYfze7iyHu6kivI2/CqcqueZA1bIcqjMDHogXNaBJZx47Z1msChnU1OLUQqkG+/BEBJ/vxl+xjpwuSxYHx6writ4MLaXCaVhpcuIILtgLIzLZc0s+HVdyiDhxoyL9y6DGskZMAV7eEZ+KIEhRAHI88UDlokBskj5UVkdc1FM8fKwc0CxuXP7il0YvO+YcslgA2LGWBY8XC7WQ7k5uOf08BdVsDudHIKIg5oKuEz/SN0xY8bnCJwAE2TbC9dVkgR7MbhCRVfCrKwv1d/tlkMACbpscDJc2iTtfk5dqWhrvIJu8ToHTik18PJ2fmHQFqhXj3T6584XUc0svTCWqRMQmWgZV8i9vjH6xLmqww7keenrd0MWWiZ6DZxUsZzWoRiVoao7Ny3yvwwCPcgn9jiyz+0nJY6kQqDeDkCqLQD52BQAbNUEzhur7QyEP0td8F9a1H3sIacSFmdf7uLR/ajd+wEHdp8kDliWijnMo9e49UeH74tjdac1rT9z5vh0Q2rOT7xclkPRF61ErWyco0HDp96CJcVcB3aSz+DxtdpA4BuR9PBnHHtyIyn0+ID2J87yRZwtucVJPd/XX3eWbNvfRIdPbXRUlmbjjdTwKBxCOZLTsbORvDsV6nhZLpDH9iCsLN1PkbLMPfjlGMBUxRI9zoMnOXEKwwQAr+BxK/eHHNuOPiqLSpNeh/MrZMBAASaChAFDxRw5EZwUMKSCTwTpRExAkqgm2yccHU8YAMI5CDPAmYxixfGGO8iCnkS2r4HW6Ij4mTNHtxloZhgTHAbhdo19iGA78pY7ITvY2jjnH+WC2YPuhju+SRU7W6/4MVbwmBizMii6M+hyWbDPmWcyznOWg218PJ4PZ+6+79Zv0Y1akdm+7zsWN2iICvZ9w9w2bJtV1pI5U9YjAJfHp8oYcfoQ/IUAjMsDWBUvz89AZHgTeRCgB6l6oJ9EPcuLAkKHsqSBaHFGTIajA3wDBgXkMy2l+vykQxguRQDhiYY4rR40AD4aySxQjFNu/KaxIPam8aYUsahopqhgqPWOHhgAWxunkigj88Jkr2UMb5WzWtlcHoBuUK8Gss/NW0kpaHGj4mLP2L+R+A+KClY2r8nzSOuYbpaXiZ4FkJxr0jgJmYNyFUcKijyLZ9pSLUo0z2YT5etnc4QGVSDnu4gz3nTEHsSbu6mFD40DIrNAc+D2WMppsTL7v2UCxo2RUVb4UequBQ4lI3FaaDZRD4TywOLai0Yjc6Et++gku0Q2GNEAkSUBTEJWLbL2Kj5T4gy0uxGJ/H+ZAeTG6zgQKQ3476SUPdDvXgnLykQ+f9mDrynX5HS+cb3+VMq7ZHtpelxUJ2IPspGEHRFV4kA4JQKfzrgWV+qKbR1tvxMfQn793tX4/mFFHUfbmlLcaWcuUZ0I1GBeKFOm45LPagp5YpNPB5yPdrfE33xBGyAZYSeQTiMi6rPBiYImuH7MKHjaUEYtl4cVc7PKCaqeAUgR+BPj1XtrWRpvOV6J2O0bIjs3XLLETTAlxYIi2Pw0TKw7+L5WoFVShiSYsbdlewRct8Nx/7QeLx5DqPk13tMdu1lFK4UTZBpxBg86bU5dgGrvs0Q0TM8AW2W+bdud31tpfUlkLH0u6LRMxXbdixZp5LT3q9no2t7l2hqY1etWdRQzfcyChEAWXC37NIf1GAljHsMSgQKoTWbo+B1ryCQPf9Fw2DBxJiBo7SCidL7J07G39q1oBKLXXkZGt29DHaE2lwOUFPfbpR6gZkIFw+J5Mtu6PVdrRR6be8NasNEC/MSQ93XuezBKhWbiZgf/K688kzjO9ejk9aA5AC9/eY+HP/+pjqZnMo+f30F/+RDpVWY3QeOeqll1gbXaau00QbTjB4tkN5kXiv0XYFkJQ228+YtA/xRVbSxYTWRCdwsoVBW8/8+JIWoJgGK+gZDRVSUzhPvWZZVNxHdFV4Ivm6b0D+5CInXR5u86z/2rLwRcxJyzWTymBUpFq9F4xHRA9kDZCRYP6NHQI5DttRTILPPUo8krLIHNRu4tpuIFlahJFQzpNF5UMwOTOJI1WtU0+NehJ3AkB5WOaUP46XZ6YTaZ4EXI93d9QtR0so8A3gIpl6zLYk57NZlqdbklW3kygyZlwEokWTIDmxIGVRBL6L9lk3feE+f8LJMF78strT3sDu8Qc3M8/ONn3to6SlavykD0wxxjDtP2QRo+hvz9XzGZ/0HXv6QDvRPnVN7p/r6kqExk0V/f2by495kUbxT4TPVAE2vv/v3tMe8JHd99AEXZ6uP49Y3a4Xw+Pdbk4MNPAbDCygvWvU1IOD8Y9zSF6DC98DKgopTstpOQwxEpaNlEuRR3KhBrO0wmQJqsZCNJKAbshI+8dIc3nhAF9qlYVzdmeIbvdd/ANK1ndRA2N6DpFO8D6pm+pKBBYLVugPRI2HY04QxgXRDu+sgmCuE/nQAKV16ewFnE5LxDf8d1pk1dZt9LsYQT0vlFwG+tDNryzjN6XYgXII26EQmV5odUwl0QdaHFWFYIZKH8tYOmQJRIHOpR/W+tB/X8NK1EFLW+biCMN5Y5oF/U3/UMMw08wk+oM78w/h0FcxwYiNZisINxKUWNHpwmXAEiDDwY7nqvzhh18Ywp8fnNlw1CgLwAAyvGk8/gGdBlgmjBJMZ8FoyngYeHBfNFoRczEo4vX3CZgucs1x4aUd9QM0AzjC7pHoIAAwwMCkMcdZtPCm4SVQ+cIUX58nVdEQ7Y3XvTpKLlhkhxweayLhDd8bJt6Twv0LpApG3OIXykoBbMuROIW4WrC2MFA896RRg0Q+ws4YhBoHCcH4xoKMUqRlSUwRZV2jwMMuPBlHjy8pvLerEe4TmbBHBmQmOUcN0vUckelyxeAsqdzGMMLOsFYzHFcN8ts43HAA2GqBmGLpcFy2U1gexywbD0E4RzGQAwJ2iskM1ika1qgrczcCVcGSDxzCyK6hUeuSgKIctSoVnPhMFJRTy7zUq9hkIHVez7DoWV+DfcUqyXFU/6CKhaANK2Q0GYsgFK2DY7Z4mXOqFqGeQyJ1RmGrDDqB4/AZTD27OBlnHJHkuAGZNVNSPNj0Ek1m8cRJhaRLLTtFvGH+er+JZKyXiWTdl5d+D78e+gSVQf5V2Uk6C0jUBDGSQEJzbeYqWyR2Qw3ZvzIbDvVrg+fhr8od2CMMoJ1LAu105E7ojzEZqDWet43H39gU05behOdGbOvad2XzrzDms0GiM6veKMVagwBdk6eO3T19IUtZgJUWWlcacZDRTsBpvMslOFZdrDledbOvftqxFoCvlIcnfDMFPZpy7rEOB1VVOOMHgRaGSoUmaNJ/vPpUYkvitKGrSe8vvaF5+Hkpc/DkVSiy7kaqq0fn1GN2Cg2w9KEPd33gVV/yOdGjXPyHbMm7+xBXznQ0WTW+M+igAI/9ujUYrnhRxC+apyEJeR/54MfwSTnn660JWGWGR1oePM5TB+VgkAvJwoeVaoV0WCVMAFIcsHhwPrXLHqsJeE3G/pvN3ELSf/cusg8JvI4ZQO7n5DvNPlBgrjpPbgkLNAazMYRNaTm7z3txtPGITL5eLPRmAKG4to5zdkmp03kAD7bhlF4pV+FNazcImseJ/ucCd3PwIGMzsDY5Tj09pQ2E9qZYgBVCsVNl6bMJF4t0AishJunPF/c7eqExmwp9WzT9WCAlSinYmVO933HdfNZMVlWk/Xbbti2zZMEY/8n5ZN42taL2EYdPl+Ch5evcLD5RFTZpXDJMLjqzcQVVyfXzBVPOA5nIVu4M4+srGLBZM6CfsBf9aHB5yvDCrwVhuxN/0s1s5olv23jFtB1EKNPYjgBzxYJgpvPn5UdHPc1ulBBGwp0GGAjWpqqnQ638XrLetFPchwND6hADOUGIIBgfUFFpleUn/Hdt1wvV7x8vJSexbBFWl8roDH4W0DxlhSNpw6q3VZBhf6Pzqes6IEDcFd1jcDaOm63+V1nayHIEMoHnKm7bFfiFAEp69KR/oEVEaoFi8MXhm9iQ/yP9J96jqtlcbk4KFtbKAll/vT8fbDmEoVjKp6Yl91dg8fAYdgx3RSk9O+yNJXOE5pf7vPUErKbMhvrakIsttnPNh6dtoHiCiBDFCNOfvP3PHgBxY5Zu+mZgFyGcx+j+znyEgWZEZ9oM9dI6g2AFfwRV2ZBtb2kBo/ciqitabgI3Aab4IdFXHoYjLFWF6hwUoLhF29GDXnTiFkxdggW3cFzR0zKNv60ZZ/4K0HJDOwcoSdF5c/MtZ2qFKnvQHunWNJ5Zj8XuBD3JvTa/L2ecyb5ZY7Pt/jssYUxcPKEDgddhklFKhU5xUYXlkAXvo2KIF3DGhn4uiuDbpSDrn6O0EGquC5CCg6rEnibX0LnY56oKojCTkf4mF9xCMAlJoeZPt7zpHX43uT+dU841znPuTxlQxyTruyB8dDmyzYo58anmXgcjhNfJpQq0I4HEbTW0KZw9juH4Msw3OYI3/fdmzXqznWUOfz0JJCo4qczb32w+aVlDDJgSZt2+cXEB6sXzJbe5OgiXOfGOtibay8NHQkWGVFfl+7igcgqx5A7OTWMtjV6Lk6DJNUzwmOSkdStDnA1o1tobMuP/9o/Bm29u3Dp7q/bff5ihLu37qilHuYU5/+9BZffv2Y1CksgLG2IA3scd5jGSBml1lC530HwQecz1I0apwUFXX79Vv04//O9Yks0IFU8fKXX7D4nK9/+QX80zurMPnTW8z3H0wfaBwzZq2IamkMFoVwVHkSLKIYqlhEQaJ49hIai2uOL1Bsf90x3jxClKHbB8x94u3PP+DL1y/4f/7jF0yZ+MH9yXP7G8Bv82zkXO6A7x5ED23b9CiffPcqtlo/f8eWfe82l7AAAFGXps7YvXsDDymr2xmBcr1anYLF780mE3pN2J5kqtv0kLQqZkr+H0dLRbfpZbJU0L4mEzBgVRgGewsAS2KIxJ7pepYC7vQXZK3+koLy+uhn7a3LJG9U8ckB8GUw3gEYyqYXOY1UIjB9QNRqfqfADsJC1t/dbAiMD6R4UmABuZ028NjX13Ymi2neyAIGgxCBisL6erpdTZF87Leus1hgIlXJAATNSqkKePVoYHFdec4dqrAAA/ezifMZ419mk1sGW5VJ/e05xXy+t4LfdYb+wPWt8f5eKvkv4kBXaEMoSmbd7mgH8b/qetJ7DOe/6wrSdXv9kSkJgNZx73eNf/fW8wR+62BqqilFUKUprVoKUhqvbphEEMr4nbLsjjFPwe6lfwDCVPYSxWZgZWJEId5gEFZyZGLqxFR3/7pTdV4BiUgqZwoHpejOMqvMUDF0+/2mGNX9K8DxvaPbndY33yoUX6C6QOgZwOsyFqdq8vVAiOz3VzmBjGL2ax7GP2PJmaOflkMxft/MG3P7YTn9HWFgPopLTS/xfxkFTQApuwwfn7l5nRhChh9s1i5E35sSgrzvGsQj/KOsrkJ0A71cAphmkHOUmHrF/jwwngZ0cVwW6y9FDxcs24ZFWoAPgF09mpWMiS4PK2gGA5wolkUHRcnW7VCyxQMMd05RGeWJTDgZC5hg5ePaOe17sO070qlz74BrRerdy3Yl36vawFt8OH/SBbFYDiHmfwwWSEcrWe/HU9G8VJjiYxMovPSlZ73yA2V/dPZy7yBKBzgoHJt+fiMa1XsGl3Gnu1EpS61jEMJBGAIcDRfgpPbGzpjTCrXAgLEs4DHAvGRZaWslRG54tw9oHZhbj/LOw40shdcyKQQWkRsBGqJWgqgyNwyGlfk0rfQ/3Kg/BcPLv67riss6TMwkwrpeQK8Zy/WK63UD6NmMsNuWeyxeYitl44CbC8BZLYBDKI7vPVsNlIZQHly9mm9REEE1jxQ6Ecs/criocY00kbmgnXNLnI/M7PYWjfeXoZPTKutjIf4+ILHDITIE1GkOQ5zexFwtMj/gV3ieM+6KxoFn0mGS3cB0BwwI0lL7coZpgVKBtH3eE3i1AHP43PaSs/JDluV0Ph4wOsAYmspWRDEjcGKMNHBBTTGuNZ663Lbz3PEL8PKo3gJhREUKh5l42XhRhmrngD7UjR5TwSKH7Hay8p3T+UF+h3CQAxFLb7iUxR0RMo4ZBqc7Bm/3pcMsfsuEmDA86+n2A/4HqNrhc9hqw7F2Y1M666PbD/QOQn1HRry51+mwl8SNOXb+dJAk6PgL+eFMGYeMPhMC7sjodmb24KjijcmbqBn89QQL//y3V3naAKLCoW88XJlU9bHC+JFMzYonipPxj7pBvU7YgbjGq7VhTR0Zf1cFV5RB1IKcTA6I0q6MaDXDdFb4432aBnKNMftUNPDd/hzRxsTbhbC3PtERBMhhSNXGJIwoBEB0ggXYNht7y3YTRR36WQyk4BH9vQMYNi4zYxwygJc0qhbsbPJRcpvAYDajTVTUoKmYOyUfCxmSnT5EtngY/tKJ5Q70OS2LLOa3q4BkgrYrFIKdCFDBdTdn7DZ3zLlXOUqH+cdPH0ACrJen/By1BKNbY8Hj6yUrgCRqMgFiHg+GyUnLYmXAZa9yjPevBbcID4QzWM60Nml2MKom4J3OT/xZhZCcDjgdVlJIOEDuOJoK5+lEpynbBpmI5Q6WKKGuDLBgtBLreerSe2DOjX2f2DZrGxb05Xp9sbLrm+3TnJJnziouUZZsp9YmJVhttDgRMcd7OMFDODFSXPh8WLN6mxRDMuN7UfXEeW66V6mWVfvgQWBUUmfX2NqdXtI8eNi9DCltz6fIkvJWn3NvNXCYlq+V+4uPv5bsXMfefKy+H6FbZOWhxP0IavG/FK20P3kgv8n0LGpZ3EGLkwn5WE2ma6DM91EeSeM/TAwdC5ZhZ4yJsvhdOs37WXHOYDI2ME2oRDkZ7b7k8Nrlh74b4Txv50Ip4V/odH429q7LqJrHuAeq3mxUrCk2h6hw0AZL+Sn+7vcC/ewH36/vzpc96o5KAkyZbhmFgrQzpR2CioQoWvY82trivQ4bkTQtgQU5Tr43ZQvnl+4trB7dfdJ++AOf9PR5CiV+3iLaCXX/YQ/sUKCUaD90Thd6EGHcelToTAahQaDdaG06Vhxy9j1buxbEuCi1KWHX5lBLTHp5zF6NvqqS8NYIWBVN+SFpljTr5wFlA28c0w6wMQeH6lH6PNCUtm8pm8D3NjLHY38OGxZ/OpyY+rYC4qXZpWjxQdg76ASK8MJURSLNs83M0KEYAj+/+41ObsMItusLFAxpeHmgWYliAZGqqnhcV9ysB5ATHiB4gXwSrG9fm1zjQYUEYHu5Yuo8yFht1BxX+2eRjEVnatSuAJ1qthVAfVT0Cc0ZGPq6154fg7HPaXKnPxtYdcLew3UB8PKtefXVOf0barbBhFlsPfJoHxfW8YbgFQ3tYp9jH+93WqT/KdeES4o/AqofAPzk8DU+8FoVX4N2oOhUbaRmJU0RwYsKHsVsXJtOXNT0KPMLeHLM3KHbF8z5AJk7MHdM2V2mMnnck6tB7wH+WZPldFaEmJI6x0j+Gef8RMu/iaz/DZeRJ1vXT4D8avw+tKUsbAwHLdkexIod0i7mhoRktFK1vsvXiRpNiSoZIpi7NNbtdKLJDWEnVMT5LnthZGszNf2PvaJTVNPQyJD3IGVR16GAqeGoNtk6k0dSjkDJVmo1id5IzNJsRjMqcAXMkpcabg1iS/iEyQkrWxu0/7UrPpDBa8ACNodXMXqtlAm7If9G1cqUklOmanzJcS5kpAw2DVnex+j0qXip75HW57l2Hsh+Vu0Zk4MoxY0xhifqmV1FRDGGtzA864X+PqZIdPo7r7OC8C98/VMd6PeYEoBCkvb3vrvB8Tee7c90kUiBKot+7/67ysbvuzr6/l1o0xazO44/gPDyndGCwV9JcQXw6hRRf0C/O7gY8N0jMrNLtfkIVf86F5JT4VCPdgzCe5TcUkCM/g/x7SAuob7tkRFRWNAmq0WliWCbVnZoqnouMVwpBqyEbEXRwA1RUyZ2MQc6EdKJpmn4KqHRcmIVu24upLpDFdcyuilaJsAfzDz/lvR1/j5hd/qezJjJIiB6lf0aVYH902cwvz48RgqQvoLgCy5v3x6HIi9Bfo82hSCmniWOp3qozX37sINBWN8uIGbML9NFIDMy6ScBvaGUKZheoaD8ChMvABhLMM4TaGJ/lcjKyvgUzLDBAHaAQrmanrV7cf8hA3jwm68+lmDFEywjk6DYM1NfFRBs/l4xB62YcRe0QEggXybogZdePOcAACAASURBVLC5oQxwJzYBl8cL5KPTqwdgvBiOMBR47MEWe5bAirJ7oQAmeL0nlnoFiMgQiDK+Y1hWXUR0c/SadOauGn2V7J1ywrcQuNkF0shUBVYvRVwCDpoCdYMm3zFa2H7b+tLY5IoohzAEp+3sPfHCAUfWV6WyqtzspYEjXkrnobLGFs/+Zqo+hwqAF88KZ/YSrjaH6D+M3SAlU72XawgDHjnv2exwJXkMBsawfKurYF0GxjAcLYHThQsAvCxAZGMPyzKiMbAyWemy4WjM3qMbXmKfKALnja6yC1aS4rrjE2FdvC+il44HMYhn8gArwS5gNmQSEVNq94kdwJSJy7pCHh6NhrpD4enpEdftipfnF4yFQKx4IY/8FaPDUY0u5sReYphBXgXABb4U4GreISzLnJjSlN40FM9cZV5nRRONP1Mpxl3bzN54YTgJTqXxjB7wNjMlnL2JzEPGNsV6rYaeH99mBgz8CYVEcTCUpQLvGFPnqATlvt5YSxlQ7R1d/oGGubToSA9EKTtsCOABx+LH2sYsQbtP6MSjyYNVBmMslrU53PkUmZ05Q+fzwXfVebpEL9bhArvDnQnAYoFQFuXlGztnnbW7gnmjM8xYPLM0em2Kv3ffvfe6b+PRiVxK4/kKmlYwGJZNAS+BFrtADPL+tInz2nHR1kpMli6gQGq0J4Ld9yf2RFGVe9KgHDuU3886LD7fI381WKUMlBSsvj+B9ub3b/GA7183gk2+/e4dlCzyeHlpT4RTk6iM3aogGpiu7JkcyvkeIhjfibPR3p4yamb9n1/d8Lp/k3TJdqLwhxLP+q1hRHdkNro3rUR32myp5FwECQuRQRv871gW48wXyVAvd+4fUgUTAWhZ85Xhq6wgsbJ6xy4ammNG1pgCFRDjcsVBpnN6P5wfh3J8gL3jI7MZNaI8uhJhvawW7S4bdMKUeyUvyDCxebYD+/SiZHvQWI9XO+wosVeVGUcH+uJBbySaepH1h0fKGOL9ANl5TLJtKUfx9H6krOptUfYqiw7Xm8T4yJRZ8LOHbVunZTQPMmPgLjv2bbOyrXNiLIz9GtnUPi4IQ6XRDDZ5gwljLJkFLV6dRl0oDJ7cClz7nKqEdNARWgFs8bbog3t7Zbbu+XP/fwUoHb+NqgZnWpDn3fnIIVuxXWe6mUMQJa4Pz5Bjx0eRiTlrTsuwdWU7DIX3cC5ZdAwGZGLqgjl3PLsDXVXx8vUF+9ytMkFmSVIGmJEHe5JXWyhebo7vqWLPSjnAOw91QnUPsB7UYYQkgjyy7OapHGPnIkXV7lM9O9t0+tsAnv4Qav9wI5Iho3D895Re0piK23+3K23yjNPYhi9lKA3C2S9tOBlnTu0c+BjmOLeXkwe7QM1RQZ6wHdWgutxGooljqmaYheNOtI2zyhbsgdzDHDhDQTJ9XgLiBaEEEMeLfWx2QZjVorWd/hPZvGN/ySvRQEMubAI0CixZnaXJvjeBUI5HlG1y/Ax800BKN8/Hj5CvekUhZPlv+4S5KoyZrFSOPG58MWWDYE7JdumAA4FXBEa2CKJ6/ZGXx9wbAp/4VMIk1mSAPMwhHYStJnO2NGT4rFoad5fqb+Ba80vJJBbfPf5UuErHu+v+vvY2fDewa0DNeZXRH2T7hy5rln6lVpo5lkJII3wZw41jaESSSEwr5NHgZZJwT0cVETAq8SEqVtmkKwCPonR8TCToLfou+sdO+zXkMLQ1+bAqLmsc5LoT7uc8kPANOTOC0YK+E6ISovh97DJEVSkKp3E6qhx2VsmmoWTC3WS2EWdIxTLP4xYizD1aWbZpn/BArh4k/3BxdutJAd6nGHTGzcMhyk/oibB9/Ax6ejC7h5+Vl4+f8fTDG+xelSuCm/L8BCNRTburhtyqFXyZ0x6eOuUVeYKfVW9mW/syhgcrO+4wZXZ4wIfHwEJmT1l+eGMy898+nVZ3vML5HTV3wpH+ysdOh6WPcP31I9Y/EebfPOmNinR1p+by0zvLove2P5F1G/hDPwL0vsk5/q7n87nuNOUfuG53+Y9dH/14vhVgA8DvAf7RAkXnf35AVJsNGT3x2/dQgdTfBbZHD9OCBOecWN4B8zqx74J9maBB1npHBLLv+PIfG8brz8DcoXPi0//+Kz5vGx5lAt4adgBYfmxr5mip6HsUvItsnuagT4p2oCF3ZbM7l55+fu8JvfP9t7kE8BHADwpcfxFcfmasyw9488vfoFROXJNEQoe783YNx3n8DN6dX5tDlQFMazGkRJjTepyHLktBh9uEe0IYiLKaTNiHQZYYRR5cTa6rEYcNCL7/kjK2iGIKnG+ZTMHcAuHoKOt+hsmzr6eN+Tco3hFjGQSSsD4nIQGR2XYHEXaOLHo75UyM9ec/QQR4/R/vsfzbj1BVXKD49J+/5Hhv1TLgk3/6P0l6bvNNGz8sOKHbKuL71JOiIhxFUfmC8T0ZLYIKoF7dgRvddMTKpBMVYNi+L2OAFvJKok2WjH084BDd/PZt+nHnjjv2pX+Miv329ffSuX96Bvot3XcBom1+9EvoRszfVyLg9p5XSvjiWU3/vOzzb1/PULz+DXR5cKcSw9YD4AaQB6J7jwL/A1cKtbh9deWl17tDsbtR4pvCEgQUZJE9U8WyArxU9aLq2RguSPjtIwtr+MxUIQLI3C3bTy3q0qKyXPBWQmSEdOch9AqLKwTCMlYKVxkJc2G/G173IHX/jtuP9PDh9ukL2LPLI++x32mkjLC+ee1Cemd66gLJ0T2a6KEdVfy309TurSD3AwC9PqtvtVcJStJSfA7zODqIqPWhs//tiBQBcwTYwAstCAUyMtEXPGJ5sowSBkGeTWAY8OioUIwMMFaZQAWkFs1G4wqSR2z6Avo8oItYac3rFXOf0GkOSgAgl6L5gSEqYAHm84RgB9Fyo6wYCI5G5C5kdNNWfk3hAocpmTBlYApcESwpvGOom7hTeYr9rdv1/vyAG0Z2ME51JpkMVJM2MNwZHUbCVLZt3EHVI3vwguFKcUbZnd+xKLCEA5a9X6kZvcNRDcBbGFjVgTGGlTpjy5YVnV7RwpTFPWAZtg3PZF/XxQzOqpbRSgz2d43FstvXsWQAAJN9Fu9hDMtqcscyyBxbc4uzYBkRudtsNjEBVaQ/AWHS1pZ+GALt9NJ65LzMll9ORhVxYzMMNmSlz8Qz0fdtT8PqGAvGIDw+vsJ6ubhjistp7X1i930Cm9HVjF4kAOAq6wc3vniQS7gVzHhvpdIKz5G/dyHxJG+fiA7d3BNGQntvC0pphnYCmkPbaXunzPn+MsCl41PLcAQXNkHsTth8CtHvPHQocn6hYQTMPUQRYDdEZ5aUryUEWRFT0rLUoE9EHdbHIxrCdDMw9m81+LbNOHAFVMbknF/+dYQ9e4/iha3KwrKMLDcXDs2CeXMEiqaiE2XUrbfvNIedv4jdWBZrEzWqp2qlwSKIKLLqKmO1+rCH4zwy0G96q+uRtIVyGIslp1ccpcDz2dojZva+oprR1NRwytoaRJQ05YusxHr93TFdDxjZdPIuC8cXfYO70VuPHzfJKOWr9uTN1R3zpy/yZ+DY77+Km/WADf/k+JK2BzezIKCsGvZklnCP9Uk9y3DCChyMdYn9WSLZpnFe0UGp0iPS5Bm/B8lksqfxAh+dPsPJaHfgKZWzlnKpDpesd1mGgXBinfn/0dlWxhDmkJ+K1hF5+6Qw+qp4Xzwvm0omOyP71cZ5qeCYXLgineiuKRxgGWsgTylNR2oELMFkA3iGMLOFzV51Nzgw4b7uQWmQzKmolURPnHYjKYFBC2dmuckg7HSEstVH50jWm7r4wsRepcHV+v5F1vW+TwwBhiqu2xVzzqRBlWxm2XbiVTmixLruTuug2MiNKCK4PKzgwVguA4B4BnpUPAEeny4ACNtLVYu5fvmCy9MrMI3kfzOz4YsP9+A8Y+dmHAqnj1IZte9RjqNceP6u3tEzR5l8LwO3w4mhALwSQuI+unRZAQjillf1OaZTgch4EnkpWa+wADcYLWNgWRffa8U+J+Zm2Xu8LCbzwRzcg728NpVEqiK4bhtWZsyN8NXxfN8nLtuGbb9WyXZHeesLazJYBH1bgKzCMgejPKXzjimZhQ7PmBJ3LuVRb3BLuuyyYQAz5CpNHl+OyG9ftRdEXW6Ib1uw4b1n9fh3JMJGZnsZYtXW3eQOav/lxp/xqdjY4V3lZD3RnOA52mmj1CDp7aAa0ktwkpV8ggpZcJzzn6D/JYM6fpg4ddTN/ayFDEmeHcXex5UU0H2aTOmtPEBIJ2buh68qP1F7oQW0aooFYfDuv8c44VTOagSqQIeFBtUrAB/lkPquiUzfvM7BLrn3DqgEu++bkQfT24mbrh+t2ah4fgSYAehFugIZDCNSzw5kRvLmQwCPR0RQwwGKql6xccnNzutujvo7OnIDrX8WjoLQdwnh3kzZuarQZvA93G5hN+bhvJU1mj5Op69jKZXdnUurRBMfg2JeYbfLihPkNK23aAsZSw9VcJK2ExWexf6Hvt+fTcmBc/5BF9LuqLUPFXClJxB8y4FwDCg97uARV4monM55BqoiS52T84j1WeIFCg9Dvw9zYmYLRlUdDR3JA3K8/BSRBfAFnExucDrh7U5IAKIBJWvTpru1FxHEHnKee8ugbDiVSw04O+w7OfjGZat9wDHB6CinPX/4iOXtK7u7OYZjAKOB8VHpodAo5R20mTLhAbDqRhIZ/RJ2HHbHlJ/FzgP8l5S5XM+3PsDzQAOOu3na5VvQHdbbaQXHZ1ol18/3A7BqDsGf4PijUdlBQPQGwMeb5x/1nhP9n3vdQxsj9W8zQEAbAYqKi8m9G3lXDdsVAeq9zJcJwSu8/uER+vmKOdj2hC24cZ8TOie+/nWmPmS2FnuleOUQBmHwO4Aj4NbsiVHRrniugsTmEcdV+rcnWeRbePNHr+9t65m2xweTrMHSeA/wv/dkLjrILbd152w1IXqYLTFoRwhQKHnGz4CoWPVWmbjnJ6lacEgdIALlEIlOwe+JvXpnk7P8TE6ZHpw6rTWVVxW1IAtzogPOP8VwYTR592C3cNwjpwNfmPGn1MG1sVub+SDGA6xsuzJhCptT3eUTAuHy7z9ZpUm187rC7ESiHpAB5PeBIZSgd17WDTnBG0BZJaZnkvdM88K54l/xfbBhAFlVrtuDQBZg2G0chGidUjo3M7nO4vLTSfAqPvf/j+uf7kDv16E8wenKTYt7cZ9Ax5VMUOu5R3fGPWkIRncErNOIv4UModQfDJWH72Pc+ODmk8P1SoEBRbQQf+4L9jXEoVrwxt/+OQke8jAdFlXzSXj4gcj7uQ4yKBk483DCGaKkE7kUYLQO4mHvilDb4bXnsxdfnxzFflmEJruBfMoObPDARHtOnIgbvSF3ikaUsiIFr6D3M4yATlqiZwcBrIRNpvfQ2LKcX74ACsIDotdl9Fr/3nXe3RTafku4CeB33Nf6xVSEr86IzIk+8ASRL0n0StjQzFBOQxkB88OMgPbbuWr9zniE4hmER9/DF6haRjp7wML8JBapx738NjA/l9EVAES/eBTlK9/nC4i2JpIYbsW5Kbk4CDbKyBoSlXMEJWDBE5YnLlvIi3/+5N3JImMJExu2ZOQFWldrVEDCEPayeBPY+dnaAMgOAntvyh37bkz8+mXH1Gfo89q2LAQOBumKiS0ZsaoiW4aEYBFG0G4ciCyqOJtpqDZB4Xrdsm9mlHdM9HHwWFSztIXWnocopbrgnjoZZSUP9KQLHg176MRwaw6OFZmNzCkMMZnDzZxe5ghnIrAKpsw48Dbe2skLZTZblGkeYQinwqhOU5ZlwbquWJbFHRVmUI++quKZdkyczvHLerHymuE8d4EunOQjeqayC3pEIP/Jg6GDLcNECdt02sWEsTgZDeGsAGcchGDVQwHMEKIGvO+q9psddS0Dncj6tqsbRGYzKlsW3sCyMibtABRz2zGFMCdw3a7gOUFQ8FjwGm+xrOuJjxht5uvVyyJP7FnGzgTQEQ7FZoycbvwNcTBKKts+iZ+J6eTW1kVu1D6xvaIwQcedg0UUrQRo3Mhc/F8S94wPOd6qekZVG4+A6NXe6UNl00WWj51HDgNUCI1U7wgc65l4ogBzGZH6iUqyzwXxzPzpgMibHdsFblzsX4fQXDwgFNWeXUPxHijK2FSH/nziw7g5WvDKwos5oIKwHWhWMT4RlEPZf9JO2HCFLHF2RrZ14MV6FU6fH3tUOfzMhtIUhg+jJebQr9Lttv8S0cpzuuH8BM9cf1MM/J9lnbb1hwMvjJzifGaJjEWTNXTYO/d9y37cAjOeHGCanDAqb9QeHvCiT5lwuzm5R3w0HCZfPwWM+E+Bfm+4dnPgWA/a+PZTAeK7mCTS5kI19A3NyUW1aZC3yeg0H4f9jAxkABnd3lW9KN0nELBX1UhR9obytL80p5LyanLTwB/qzxesskRuwIU9Yl8m9sm2C2SfLQNg8i6JUe2D3Bju44RBIXhjZNikwdyNGARkqwDRdmYC9Fx82eQPQJhBczrs7It92+0lC+X4UV461ptwp8o0B6z39BzA8HOgRKmsEw3AS/FBFIOHw9q+367PVlJPjcqLWHumWHztklXrGcN6bwomprj+MqcH2IXkgzIMgNJ4EwEO4WCOEoEldpqzQwSmmyQfuECh2HdzXlu2WPTG3izQ0vej2X0bT0fxCAh0Vp93qBuk2I1gUjLLw9Nj7rf1lPfz4byMhrUR2rYd+vLsBsThc6ADfp7FQCKy8r1EUFaoZ3vMZ+PhXU+2KjJ0OKdjrFAo5nULqpr3EPHRed7fG/zS6XrZZ/T/5e5N1yM5cizRAzP3iGBuUqZ6mTu/7vu/2Mw3XaUlVzLczXB/AAeAB4MpVVVXt+a6xGTQwxczGAz74s5yx/9SmnzqdH1HY/4MdrRMc7apMQNQ7x3ruqJLwz4H9m3Dk1jgbYfzIU15kzzJNprTaq+gc70q+rSqI/uyYNs30MhFfmnPs8pUOi1bU3zNx+46mfN9hTh/pHFQ48fw5w7NTRHDRYOkSfyPF36XztdDYdU+iCq/yyQQMu1BruEXYrQrsr61ubnA7pA7BlqTHW64gdO4ZBb5UhFkgE3hJQfULjYKmZqGXV8v74tk50qpMoHJ2uGMxc0v6tsgr0mHDdi6hunp4vtOGloH1M1wEzMyVpu3ARLpmJJVc8I5Li0CWyi/CfeXEi6U947GfcIm5TNJ2uTfJ11HyI78ssohd0x1XKbC+8gbAiCAtrJubjz3ACr4voHz7ZTHkDzJg3qzzRXSmHWz6sQghXqVMgUVBkHL9b8BUTzl8FyepKzIaaVsTV3Avpcig9l55fXEkqgtj5DLnwVNlpcdeEg+/GbzSQVBSH9O9ZMc4/kaViez9UCH4bAarVdV0+ukztmmEcb5A85xDyXPIQ+K3sFOt5NDq5Nzcf6WemTswCB6cbmfktsTXBU7rc+tusT3yUC3UlWHcpT6dWHx5StS+cwHlioW9t04jBPlHeYYH/n8xnEA6hUopVlLlTGeUDOp4ZX7xtyxT7UKOh1WPt3lBHVaypxJIB1aRjMWTLWKja3XPaFxFejEJxxq0A2A+dUc5+3VGfrqCVOfMOcZp9UNOO/eHGh14qrDrLcYnImHkyIKoOkknx5k0BejJ+wRvqwdiobr9Tec2juspxMUwL5bYNycVup5/vYJ8lascqfLoBPGf1vvWNTagNb6EExdeUFUOpZxDxaW8AIsjnf8mnzQJf4wl3R9g/7BAv5Y9RWwAFC4Pj/nJ8xfju9+Tn5fIMh/5/EPPa0Q1Bm8ABg/f0L/6a3D1nUEJZ/y0tjQI36pOa/PjpOnZu1dP/6vv2A8PODVwwO21tAUllzzbmL/MrG63LQBIf+1RbCMht3PyQTw6yfIh7d4/a8/Yh8TXz999coEtgcNForZFGMAUxx3gkbcQivllmcyyH0QHU/e3FBY893zh3Oi8EJZeFTF9T9+icDl6t6gLSsYQfwIXOJxevn8RTE7za8mNBIcWD2C8kqIrQ2wVlgSlcZYtVLClmo2VpF2KNM+1WTuMbw1Jdv1Turzam1NYaXT0W3fibqTPJX3A60m52kCfG4NA4ofpuHh8uEHKH7DmG9w/hdgmRN9u+LT//o/6M5i1395Z/aI5m01YHSpt47zT++x//VXTKcgbx2WvwXtc7nDn5UBXDamZ4FgHDttULRBluD6emRGO0LGYUY5beC8bgDeBsHWCEJeqZi0YxdUWLrrO77StH/JHaS+i+d/4xX1qv9cKvf3H38qBzpwFBwPRxXU/sF3dACf/0hY3T/jkPuIzoO06vcctevbt5GFMvUt5ufP37/hdrp3pp6XPJOon507GEA1hU1uaIh69LZQ9oq7SDDuwz+JLuaEyn7I1qVD2MVTdDTsGJA6wZCZ1WvlGMExY/zEUERkq+HbUwq3ND4UoAif9V9xPENLffbJ8OPrc53JjyqXjk/TrxUMysF37qly7cSjf36E4OH+8xGk/+4REcOHs0/Iokf53ogOpJERBT3EMsmS+eX5DvF+ggIaQKxifMP8ZqXlvYK13RQl7ezNGu/331LHA1Qn6/g28HTd8fj4FY9Pj9ifNgwl5m0Bi+nxieKfWJ5rupIVzCyUyYzepjOIBv9qheielblte5Y7y2DogJlIlgUPuc7PP1vEgvMH4SKAzHWQclv5HAbTxAjABTNJ5Zevai6YiQBLy17mnQEDVmPTFIg135fOCsLw8LqQXWOnuK1mWTvO5xPW0xmX8xn7bmVRx3TD5ZhobbqDvGFdVpzWFa9evbJ+4LEmJtx1dx7SeR4CYMm8bd1LgzbBVI9+dKPCPuCKkzpu+GfVQwti9dLtMc8GqBsfDZcnhme/dYezeT4IC3MKseVJ66aY9W5Z/9uy43qdMCfFiD0358Dj9Zspa2Ngn9Z6oC8Gx+b97vZ9w76Z8Lrvw4M5lF4czAbsuyuQ0lPwYgZyGBOoPuZeg8Cd6LaoVWA6SgBJyCLoyb++SShClqKl8TGzUXGjqHEsxG8bpnqfYGaJuPKuiZUQWJYSaCDSqKBBngZ4qWK0gxHH1q8jHkrcFn+3KxICREnLakQLQ6gTfjq9eN09gTaoII26cQjqdotdJ8igFS99vHr5diuv1b2s1dFNW3kRjfsKw72hwL7bHd3nBVei0hAmRYkoPEJr4FHtm3zrPB+hcNE4FjAnJMjzy3fMYLdzs/Tjy58u1oMQrhAaHbHf+7BgIKsAM6JqA7PaqsPeXqoVhY/fHdSWeo5rw7UueKua6xgoRVWxIsVBcjp8Or7uvqwWv+58n3ujjtWnekjteYHfCEd9M47c2HUUZVg2P/Y5ZiCUGaHcATkHRJopjMqAIzg5OMLzueQnMSq9c4GU88r9aJQYALwEKcdvDmZgWNk6sTYuKhOzCxaRGFcdW+HsB4pIZ0qVpQCrgILpQUOtR7bZgTeLWOY595fDUeEtZARe1p375RlYkg5pJsxThmL5fOFenhk2Mv19U+HZ8HEzFC6DTS+HPkpv6DKQdtjTBRWgVnodai16zqeiZ/r5mzUN3YBjUgtWmnDH+rBqKjonemueDWHPHPuATIGcL2bAZZUg3+PRO076AdVJsxTGfwG2nJjoowcO9N5DZuMel2myx6tLD2fvYef4mox9x2BggDtwuGygzAnfY5q4K91p6sl1vCtSRqOzqzihDnTWJ8lAx6jEcEMyuNsEgLaWZYCbciGDP9ZA8N462uIBj24IP58vOJ1WrItl7jMolLLbsliAyrZv2NYTgEfMOXwvucznMGSNM2NJmms1N8y5mjN97M6XmM0m3mbAHBfdA5u0aWBa8Bb7FZwznOgsT+kBxrf7LWSAwHXenxcqNDbD8yBY4obfcft11Qv8b63PUQFkxrgMVbJSw81LHL+lkO/kgR5bGfsunVf5XvjakKZQL7C/Z+BsDUzheh54lf8cwHlkgvE2n7bLmc9nFafYy6Fwb8o+6vyO82fIWgR2shVQMz3EaOJA04ahlhFpznSkTOkypt9p7xFk9u/NNYFbrHAVoC/4zD1W7oU/O2YkhPhxksfADo31Bo44dGsMtiVMukCCxqpXJuNJ0JHm18R+dtjVgDI7GFDj66hq7/GFrypDIxRuZF4gcf0ggQlSb0c6wng9qWDYGoR/SMBbJLP8Dm8MZ7rT36NQGDCzpTH7Qc340/gSqRM6H5cYqeEMaX68XX37csfEBBx24TFG6pxcmypvhiw3Ey8OvxInYloh06f8AA+mtr1X5gU4rfWljR2FaDUQtDHgyNn7XFiyNhc66B1lZ/Xz3BbExTkm2C4uaS98rg7j2F9HomJyX9JMm6unczFAJgqIpN5o9D/1lzldpvEWdBFgNXNAtJW2JsCuHmDPZ2rSQN18LfxEtDHSGG/S2oTafRufoMkFqYUjddoy5cCHsF2Uuc4ZARuGt/bZsh/xwpG2JsKOAWgm988sy/5JIe++AHhtaOZViVQyE/125er+P3xW4PwCW43D6U3/8R3014mJz54gx4B8oH9wvT50VAbODejPn4O3VNJdSe6fLfvcjtzLz9ir9b40alRsFeaIcwpVdFRArDy+WmWnXRXNdftt37Ffd3RxmXGx6qCqE+2DYtnfAf/7L+irtUdZRYHW8KgDrwfQpiXttU4bpLeAW6ztIpMGFYoxFIKB4Xyv+8SOLdHs998QrngXdEcC9ceOOoohGX9qJiJNm1XdhPHC+nNzOnia817J4B+TP2a53HGVMkUggIRsYXJ7y/Z/bluUbjbh5k71MQe23WwouydBbNuGbbdWVsPpHOfICmOjWeQ5K0vaNS5vkM9A8VVsDzZ9vloN1NVNx5gKoAN9NJw/NEy8gYrbGARWQZR8Zv4K6T9iXRa0f/2A63/8BXUXBGtC4Xk3K/Jszyj58i1XOTq2ixZm86AO73vKEpQkTCkWICwhxCjlr0k4UP6kPU9jPzQPLpwBv78Tcf8v42jVqgAAIABJREFUPf40DvQXHed+TM8KqALtS8dFJfqd16cKLJLse5OmgPC3Er9kbXwXmQIFWz+vdVtUBcUO+lG+CnCBZct/E43s+ZAtowycHs4/+LO+SaF9VWGInpscKAdWMsyRRDBZmFTtJOZAQxyNlrFGFLg8yu8wa+HMFbeQVgBDvYCTKoYrFMN7HWaGnhHHXUcZa9nELsfGhvcSGsMKx6BPRkBfXXk3oZbZ1DS8pfNe/PUPTvS+RWQix51Q+TuOgzSOUH4quCsuq1QFLN9tWGgEbvv0GVuce06c63GPcItcoEpneu4nBdDfmMEKX28Fh3xSGjsAwHoEmjHqAuBaR3tjNLHxt0B2f564ROCMoMkZy6uO/XFaKf9XzAAEpuxYcMKmFrG7yNmYBwQQZqwKsO9Rcs+moehUwKb7BKdin1ds4xH7UGxDrfw3BMMdm90jI0Vt1kMQAsQ0xAIg2L0J/dI7aLRtvl9ErDRyrPc0iVEgxfmTBvJb2sbxcwGX3rHtewhAR7tWTyXxgAwUlCpCPMee+8Y47mfSlOx1xW8b6NRwp5sLS/3kTrKhULUaN2EPo5IeT7ESpzrVM3DpgDYBsYm4k++E0+mCy8MFl8sF27Zh3zZzpF83E8CGOS4Wzzy/XC548/oNLg8Xz0y3ZwHwrPkW59l/vbtxWUQw1AQpq3GX8yZcWkc4tpVKktII5LZi0rNofQEwa4XCD0uWQWD120PLpyLKfn/Wr3NdFkg7YetXyN4AfcJUwdALBBsUiuvYoV8+J5gd16Q3rO2Mviw4nU7RymC77pDrE7Yna2tAgmSJiqT70wVWdwyw9CrLkZKuhPHOPtfyiVqyD0iLVL0X3vQMQd7rRh5GsLMf4Sjl2A/8iI5bsmJltOYRs83/I4cxUwAGWnGUp66Q1/oGcwWPITZxCMKp8pwue39AqU5/IKwsdESwdqjzYst0Qxj6dLrR5xBEFK+/cxw4f5T1b615Zp//sBJDeHJypRRA9C73MrRhIHen0q67wYh7TKyctMkSte9rGsVoRLbLNDLQm/fKMjCpVQrZN4xhyhZpbBpkE56xfVxBzJ8ZfdQVpGVWWnqu6iUTzcHYerfS9r2hu7JnwS47dNfAe3e9HVabfOuwMmrzO4rGt7Q4KPbxHA2JKegBYGWSpMnMaE5y/oJ8ffva2CR6F4GqFFC/t76SVRaU42Xxd9khlddIyr4HIyzxhM9yQ5i12PAeagLr0TYHxgB038FMvhsggzKGpjXT91qLvUuDI+k78uwRdDQ0tAIV0hn4Os2JMXbLAGrmUF48Uc/gZUEAaafJucZB5yI0DPSxf5zPsEQ7VCDdetZBPDsd3o6g9SJL2rFN+87a1qRx1rZDcTDCnCmtIR0gPj8rs2f9wXtfbT226+H+ITMJqGSA2RhmRBljj2CYOSciYRl00O0YM8FyvW44LxmdpgDGttmYzsdgzsNFoOzm4x4DU81xP4dnqE9zcm/bZk5O3uf0a9s2r3pRqCllTVWTWzT3It+pUKveok5DxAyCJv7asyMrmli0sgR9jxLHFSerXOcUzILecBOsTeaQBAl96dAxMGXGWJeHXtCPcl99jJeBZ7Z1ySx3LDH9jDJSAM9g0sWyz73QJ4yf2D4NGgbxikQNjdnmvWFdVzy8eo3L+YxlNdnOSkJb0BNb74wBPF2/AE87tmXD/rRj7APnywneAKIUVXFdUAEdE72plzG2wEodFhQpO4DuGe8m1fmeasH/CDJzdgyUXB0HXjvwyANtu4erkvDTCss4851DXvrDYa55PgOL4PRaUR3iz8us5bvDKaX8cZxpSS+pt94Og7JyPpI8MXGG1xHqPC0x4L/loOxZZZqyL+5OsfAQKWIaiuzC6+O5CJ1USe88Kx2tQWVP2DWrwGM6j5Zgrxb8Jd3pEiX7KSsHHAP2Guw7MM95ejjSns3Z51LBpM239VHOKEQEXK8a9BCX0VHuhKn1FhWV7JR/5y02UkZLvMvAHSnzIJzt7EwF4Sjr+A0cqT8wfxc8eyb+gPhGumYwFc1nFGqXMpOW5wmhJTmAWm2sHrd47BuK9jat7YZC1+G99XFSJ2D/eABLlNXlvAjZbpXj5nCBt3VIF9D4yCCOnFN9YQmwYAujwx4nfCSikkP/I82hJ2hQJ8jhU4Zj8MiRnxZY4Gi3SJumuo5JJ0uDepWbtDkhK6CU9oPaBDopJ/o+U9ddvGJW7cstLL3vayUuU2IOKHmBegY5EJUzidvRVgpGA8b1CtWJvq4QtQzMqc53BZEdL61ZFS+nECaDTCdHDMxngLfE1rU9GPU0Apeojy69HdBSGtvkGJx3b3PYILjOYe156AgibaCz3J3oFmQ/rRx7b85j3MkmE3MfyT96h0z2XW5o/Q2ISgCwnk/QOXDSifb+LbZfPmH13/L2i2WiU7d2+bkvHef3bwEI9l8+4vcOJurnKt1eALRpQXXL/7hgzhP2bQMEOK9r6ugRVazR6gz6+bCT+DulomMr2j9bKfdbSWTnmV/EbfsG9jkl+sJPp1uNzskCAFbmDZ1mDIxtw1NrYfvZdaD/h1ig6C/A0/4RbWlYtOOkKz42wWUMrKNhdkXbJ9b3CsiKz//nZwwFltOK62nB6vaAGH9zR6K3WlJv0daD3/JKfvr+YgSFvEUbkr8XRJeXJa0UMSgPTIBFdCNgI4JT/WlHu4h/rljnhN2yxxG8JUm9uE2uZYC4j6bCpbEGn0jYU5feLfvc2wE2/xsA5g4oLPN833ds+44rE6EYSK3GX1jGHZjew755KXbS0uS79+JwBDA7nMsqCliCF95bJRBMPF0tCaIt761SMogHCno3FMDl/C+hE3bxur0CD9aXw9rWcZEnOWX086kh+A0EOZJQH5EguYat4eqtIXpfvIoHwgZBmcx0aPXKpfBgeaffYjyguw2C9lqG+PWe9omKOc/RWm5P3L/wd46/87b/9ONP40Dn8RJASJL+CG94fInqAPgmmn3D/4SHIJ2yVhLJnOimUyQEWJoh+rTeHCcA27Oz//hxUAT9A9W2KrzqVAZumaAIbjiWHS7PnLCsSycqqorJks/QTGVBOrjD8KtGDrnkIZzz77rWZCqaiuS84VypbHpUaKZKITLbAPQ3rzE+fwlQfG8js3cFx/CHjgNH9HWXm++pk5TLgwgXUe67Y7v5+0CY9NHPvGBoBFc/CSOJ5+1zDxmX/r36P4bHHjHaNLJ0KynuIji9esB4fESTi5c1FeyPme+Nb0B71TAfTckb2EyAUMUES434GATIiOFU7BuN5M7gxQ2ggyWgihMoYEYl7ABTGzfbhprSQYMpr3JnlngUWHG6AqZXaT4wcRoZCawFqHQqqblwPUOyWb/sQB8pzxDcFfhxvBao0ZQliOkZ3ZHDZ35d7KZxHzM4+8UMoCKSZeEAsD5O2FtaeYMrp7N5hK655QGY4ag3zyY/n3A+n3A+X/BwecCyLNhax/W64XqiA316Vq1n0y4dp4cLHh4eLOuc2fE2cM80lSj7zowIm6cRFiZW0zk0G7HMnXEu9FlpV6MxFLRnWXBF4hlLx4FCG+D9tGg8K2sgFCY9y9wz+1sTrOsSBvYQPLEA0xx7T09PgNPI5k6oxbOMWWKbmfzfvn3Dt28d3wA8RoqNjYvlyierJAgNCkhHIY0+yJ3pQ73BKgnyF9nsQJQjjr1HYVl8KNPxxt9HpTsdbRL8CRCUKbi9393j/o50ouf6wNc1hVmEoV1KJQabG7Mwk1o0JwAz6td5xKfDkTx0qhvii51SfM4UuNMwdRMsE0YYBJ4SBO0G2CLcnzhkADGT91C+fVmtB3rvCUuukYRInnQApnCmdmX4p3Na1qkYrSJ902GGkTFm7AvCsi3mtGgomZiH+Wn0kKWzLQ2x7EXtMsAsjnp477PewG51tS9egFNY1ncGfJjZaH13h5UdHDu23qMcfax9MW5SPEilB6EgkXZquY6wOzjJtOAZDbSS2TROXsscjtL0HREyxnb4S+oXtxK5PP90++Cmz7KJuHViC8nz+7m/FObMC8dcVTWFxv9iEGhG25v3QoNMwMuRqZcxY33BdL2Ucd/IYTFGff51udD/z+epK/ddCk33Z6pXY2hFDuq9oRpq+RyKB6RTLJnXImCCmdyeaR/8Bfk9Iacpt8GNDYb/boLw8uUT5iicKuiw1jFRJvhmXyi8gg6NY9P4D7N7ppcohm7Jt6gfwOQsp8b+UAvIGtG2wdowzGAsZlS2vSHOdwBBj8AjRsdnIJ6Q0B0NR2X9SBPm0Mg6Z9/t6RU05phubBh+nusqaGoGvTmOASs2UPL6NDQfebgt7pjT2qKgrBvlUtiYGzwww+lR0DYAVnI6XhprVCX0lwx3sbUl/2wimE2eX//iUYnynXP1o0jQX+KOiKCpBVRFNqwAAnOuiyiWU0fHguW0YqX8tp7w5vVrnC8Xc6Avi9NoDw5v1nZjQjHmE/pu7ztdzt6vnrS58s1cpwYx41PvXgGrheNJ3FE+xgjjWlaVOZqPzFh1AE4AK/6LW4/Zf4erg57o8/UMALc7544fDvfKnaW946BCfWerOI6q+JhMVkiqslCr1svpbGKwj/oqaajAEEBCOCr8jjLNVEah5suOQMctvJ2d+/oUHPO/qU/b/Tc4zfUrBmlm0nL6NYgpXy/p8INkeXvBMchS2M/XKxHJPOxJhRk8y5MK9jj4IwlAc/5lHrSHPFtPyhguhBwC1EDZIg3UMfcDz0Z8PtDfAlcRoy0B+0b6HIoTpP7dJNarLkXirJ8P/Vly7oX+hmDk46hoE88OemmAumdro7OBnPWgtwvnmnqLcp9M0jsbATmf4UYGyEZwsUjQkudySuqBE4JDX3tCSB0osO9aqewYclaTwOUIXtBsCSjNZAGRFk5af33KqVqfSZsHcU6CtEbgB397MLR1TvDAkGjp5WNtkpXFA8FzjSvF5towkNxfGnIKP3OozFCMalMBaddbxFYp9s8NbTkMi3P0Naadi4G4hBkD3RkcE2gD6vkaG1TZzsPLvbOKkZW3Hib/DAu8M1mLPMapAWUJvldIDo50ieRVod7ih06wJBSKF/YCBNAn7F8m2itB0wvEK3Mts1Zei90SUNMEClQV+6cvOP3wzh+sgePGYy0AkcecEYOdtnFVbI9XrwQ2TQ748A69d4x3gvFR0X7waUdLIQHQ0NtiQYyHuR2Pe6LTS0d7/yb01N4b5jBYRM9zVu/DkZ5ayfag3oeOw4Tcn81p/uygfaLoPekctGO+IOvw+1e+/dZIVHKZfAzg7QNwesL83LCrQLAA0izARCwIo2vH0oEvArzfbZ2vXtmvNUVfFSILTuvJHPqnBXJarHw7ZSdV9Da8p3buB50eoOX06CUR7L/+kKwsVQ4m6xi/pb7Wwo7RUJ3prK7ptD4EsfI0px86Ye2//DlMDCJdJu1vYkkX/GHmufHRYk+FV44YwypFbVds+26JUPvuNvnpWehMTDLoW8CAyY+mfyr8I+LhnEnoS/6FJu5lj3bTJ+cyreXaXLCP3QOfrMT51IllWQM+DCIeQ3H+6T3mX3/B7sEHx/CE4h5XPDtf9Qbac4yd8z1MDKzLwnfYMxok5Kald6dtzg9hNEmGuL6szuKSd4UMhvxNOmX4UoPU/zw74J99/Kkc6MbL7wFfAenfZVB5HHeIlNMK4AGCr7RMH+66JTL63fO//3Y9nviDx0RGlAksPv3Nj+/w7bfPh9GMMTA+fobIa8jbuuns6BB0WJ7vzQTujqvoTCHWVMVx+obLrB/7XRm6PZdKCR/3PAZLoOlgD4Ep+4yY0GvCC8uopiOpUd2JzQ/ViGYTF2zFP8fG9nJ6dpsLJKIQnAB9CkdnRAU5Q2cmvBEhEnnB+KwAXmHi6y2Enx2hO7x0HCT+W4C+HMMmavhRI0YbXoFK2fmHt9DfPnH6d195Tyj8Iyg72QP9nfdA/1wI/rMppELPTyzZZYaFaeutnumnef8qgt4eICIY3xTAxbPHrwDOMV4Vscy+bxNDroG7YpzGyo8ehFNnHssCmWYIYFYP+xYGAyX8lD18BzY3hnToAWZRaplhAJp45boKWjsueJOG07pauT6kcxMOL3hUrw/BlLxIQTiqIOu6YG0LHp+ePPvczu3uBLKc8OZygjuwIgMvVcbjkUh5P/PcYU0jsJOAKjSFKUpgyjsE7SImOC3NIgZ9xjS6M+vaoEm4sCqAlUqFAAtYYqa5MNBxOp9xWc84ny54OJ9xuVywbAsWWbBtloE+hwVFdGbVeqb2eV1xulyw9OZZ8tXkjFDiltaydKAqhleyGDSFJBBc2EZEHk/xyFu1ErDqjkNGLVbDhHoJT0ZYCmmkwMsewg0fGSlLZW2OidkadA4MKHpbIGu3vqW+FtMjuL89PuLr0xOY8bL0jkUEfV3xcDnjfLngtJ68dPuOT58+hQK47xsGhhk3VUMBb05v5ximozpdZRZMZgIXAT1oMHGg1rc3WGT7EuLIrZBnzx/spUa6RCU87neHjhtmCHcr/ZaCvGGhHs7X/ZJGAYTMKQAmhmEvn+Vlh0MnM+TJPafwLIF2DLwCi+Jxz1Mwtjk1yb1WHhX0z9llRp+WuQkcfyYOsOHkWE6zd8cJlnBf13BOZiySC/xUgh32XOd03uthvMTzsXPsirkPTFeUSBMis1gAwcSmI4mNPz+cX9H73D63VmRIs5TdOM/dB9Ayi53lknUyCpiKpdGNiGdwRbD3jmVd0XvDPjrG2NGvV4zeIbtNLuSBwgbCkMgRSprEGTQS4471E65wwv7miHL45YVSkO05OU9sP3xVUP4+DzheeOAkN5dnafx6DQ2r9R4q8nkdjXnpSUacr6MOPPHMtcVbb2DbwU70CivfqCXQxwJuUpEUaWEgOADLZQUaM/Mg/Zq+9+o8M1DKNVQb+TRc1jmxz4FlTMu8uYEdle7cP/ytUQ49jKys+CDpZLeHNJdB3FjspxuAIS14Ae1B03GvNUWbwF7wQBXQ4fMUa1tyupwgreHx81dA95RjnO7OsZss5w713gXwnpuq5pTcvn0LGZ2BReJjmUgHZxq9zQElTSzoRhWtu3w5JrAu4QBYTsuhV5s08TYsHsDo+8lopQXgDDVH+CxBbCHTTsUQoyHbZvt7XRfj2SLoq/Vk37e9xgEHv4i/Q64j3LPiUE1DCRm1eely5wUZAOrlJgU3rRISi2KXOO+sfC/kaYdPOlnE358a32FbFxoKOI1QYL1cMJ3uDZdHyRtDeLUbfB01jUTxEuJqZkYIXAZzh/naV5xOZyzrgtO64vXr13h4eMBy8sx06UFjVcwps48dr16/xdAveP3DD/j88TeMqWhTsSxl65I3dOuxidYCzxlk2D24sLWG7fqEzfveHwMjgloHjFI/NoQO/emwx18+MhOE8L8htsEnyrrk61566p334LBc6srxs0ccRaPA8xAFRKHaPBhxYs7mOIzoCUy85+eDgzaerbVsmF0zJrQDMgvyqzwzmh74bvwWSLRUIP7dTrAdH+AyBEj/CoAUkuVDPQs0Wjlwk7vQFMGBnBbpgMAjOVkPwfhEE0QVjPSCFZOsuJOx0BcSdHW+I44zU+GlnSscOEev9qCIjOBb+xx5TC3hXp3okaJ8wHs6zFmoSyIT3WCeRvgqf4rfIH495BhQWmUGnmOQikAAd+CFvH2L5j6myPq9+Z7tk7jC8a8WEdTvlVxex33KJeqSAMI56UALxx/HYrkh6WQO4HFy1Ntv1uQgL1F25JziGoFK8gE4b9LARQYDWOavDrf3rIvtE+Q7TEdLYSIc0Tc2hVsngc0r22uZXDhjIJR14jrOozzk0DpAGqLXeDxfy1gQe4+BbVmK2Pga9XBCao6R/IjrWAWnEO9sHNNbmokv8k31csdtL23fEFVJrNe8y21gRrLLGTrx9PiEMczhSv1cVDE8sG9s6UDqvYE9pacONFirQ8vk9n09HQ+9Wo+si+1H0Bk1vXqYloAyUgWDAx0tALC8feW61MT4aus8virkjVGuEWWBkvHkmiQZJcbM+RXtzauUPGLDWqsa9UA35QOcjlqlPbMN2dMn1qXZFJqgS4cOxbK8xYBnlzuNyElaBSBVPfSNPyxj+Wxv1/K5XGds0ktSW79nKLCuQJSu9zXOvWdjHTcyAKsHKBRTCuohneh/Vkf6VwFeqSUHTlh+DJBVsrjXea7dQLipy76FmetU6A/Wnm3VNxhvO7ZP36BQjLVjZW9t6ehOL37aTTMbTdC72/8UaGcLcBiXM4YCXy4LzsvieqYF0gOKbR9o3Z2mdM46f6fDuPKWKnocKXCex53z7YXzt/fdW24mIR1/mNVMkbDwZ5eNs+oe5Q2vtiasuokUdeLdavb7afxqenCCOp3LYio2CnOeS8jKEi0wG9C8QoYHWU941vl2xfX6hMfr1Zzp16tnoO/uL5hg/ZBjkKZGYLPAW205KWt3gEtZ8/WY6DA8mXNiXU5oi+t0qtj+8gvk3RvIDlw3AGOH6kforx341w9kbhBYJZHx119x+rcPkH/9gM9/+dkqLUBvMvXdQBcOqOTbtB1zbSOgznlj8O86H+eTIlbVNoNSvEKJtOC9XEuzI7ZgsUzOpQ01qpYJLfUW4Lb21e0Mx0SUI6bWsd3DWV4tz4nod47vvOW/5PjvdaAH1J5h8s11ftq/+74B7/vHAuBHCH6NB/93gf7+8VVumLMAn3/9aCXt/BAA46OVdmlQ6KciV/4nHJXY51gEfwTsFkXaDuUqDw9WBJHQg3RJ8bqVC4uQFYoGS0oE3QCQQk6oFxFFq3GezgYzfmVWznP8QypfyO9ZIub24t+Du/n0/yDOBkfNdz0Tyo7DNCe6kp3RqWI40fGAiW+/+7rbZx+veYKVXX/5AUV0uHneBapPqDSVIGdWlvWXzJJX/Gkq6K8frPfRN4XK1Z95jsKHoZi6YWzg6o4m4rDkbwpq4sZS7WCNRtUWPZ57X6wfaROMgqNDNaLdcoKC5pOLzAN/TyhbLrzl/qEzOeFlis/iJfqSQSWMJZwG1bhGRZSOMVDQFOtdzezm3poJNQoTVtSd57DMWr2zuW/dccfMgqq45hyKWJV3Kp1P/tQTIKvDDtbLXiDhWAkDjiacqmNPURyfs3sWGIUxCUcWGssB+nN6Q1s71tMJ58sljBgCM44u62o9eXoKdMwuEkhZFyqQiHlZltyAV+gPQZTw4v7XKUBTjN3xSBHlpUHjrs54hzodYjS6uqINAZbmGZQuYNWKk/ZDmCn2ObGIBRpYyeslBLQ5pykUu2Was13GnBPb2HEaIwx25vQwB9RyWrGeTlhOlu2/y4a5D4hbDhJOEw2OiyLmZHe8CfFNFFEOVJh1QBqMYhSTOI84X9SQ0BBAqTCNg0F/ilGK6zVn2QMlM1KQ1zE7g3tBEx8orLLPXDXC1L1a97RAQmGILMoYw8ySsSKefENYtKIZJcwAg2GjExB/7Dga6CreHPcenZJLX7C6I529qjgzp4RJA+OfskzxXv9xJyfnYihtvPdQIqvw+yNdQBihhhu8wiHuRs/WLAsRsS/ZJ60a6e1Z3cfbWg2YeEFWZGSzOx51scbA0gQLWvTcbU3cAEsHkhR5IigjCKgq2yTj4PvrlTcAVX1WFrkqSfXa7+PHvXs08e35t8/OHZ4Q2/f2nuO+PgiZTkfztOXlDBoQUeYYLU54XzWkS0Skw+mXeknyxCGXFAq+Wl9w4jGRNcesh319M6U7ciIgYbikVCueHSTT6YaWvcPdRHlUYgnCcKxeNqPKspEtDYUOTUrkMldrLTi12VNTkmow4wctmqKI3ucNagGDs1npZW8Po142REgDwyJqvAzwzCjSUig6OIZ0yE616gDr+YypiqfHb6CTYKJm4iVUKes0D2DBCkAV23Wzd0dABHHCe2CvlrFs1VUWo2UlwEZ9D6o3Zw5nNvSAo4YSR7yp31OHODgTxCtfMTvN+UZzCh/yXZBNsQDm1jCnOeW7sGQ7s9E5tGrK/f5xoPv3vue8qEv17utv418vphPMIi80poEBbqDJah/sJp70qzj9yqGNwkyMwvZI4c/wdaeMTRjYMrTYr1ZSsrlMR9xsmH1a3aLWsSwrZNvQWse6sJUXg6UNls2Das3ZN7wlRGlR5HCcc1qvxs0qLFB2dIAfS0gcYJ2fbK6IOWmZ37PlEiR+3Qo6HFuBcjrypD6AkM/BKJz2OV0KL/ftWpR18/2RZFgPIhl1xOpg1TA6Hx3mxx9wQICoVXZgRRkR6KBcpKFXHvA6t16A5xCUBiAysSL72detJQwtG61SfecxoshSR5XWImn3NHiGo6j+cHgu66GspTrPUn8l5yxNIF2gOzPSHZ7GFIvtAlHOFcjAlJQ4mJbFsReplXKK73lm/WtxqAGIjN0joO/hyI082Y4yHJ3mDcgqWU5Xw6EbGXO+Tq2+H/n+itY4flUz0MXpm9RzvDiur7rvzXviY7V/SDxHC8xtQK2swxFeQb8piwKIgCPiRV2/IJOHF5QNl2OqPKHSI+KnqDvwD3NIpzbpp5XWvRkEpGSXpsyiRHyed9yMj0j8Sme3/60pA884jwNMANOLqj7HrcMWRvWwgLrhyUB+0IGJUXDYflGeift94BKO8QJv9bkVSKce4zTa9eKh1Gx8DT3onLIS5ojsSobNMPCavJa2iBlw0rRT+FwnFHNn4oXfH3EDLpsRRCFDHoP3phKPAisKJsWtbh94ioDLeg2rZ3DhhePR5Ae0/pJf9OU1xj7dFtLAdi8mUyDpfiyP41VUiM62h2w9xop/Uy2w+vzhHfYxYt8dF+5IuwpmPDsnN+dur7HxFKCQPzHrfHLt7Y7gTzd6W4Ng/fDWbDT/8YtlVzsNOObK/3mOWxlTYXywvX+H+csniHr1OSheKSIdTUVwGTOKYu8AlikYXSBeuaa9fwNLYbJg16V34MdX0I+PlpQjhudd1RynhJXz+Q7BcLl7WRdI6xiXs1U2XbtXxjQ6qaqcAAAgAElEQVQ7IPeU9egxfWbMAR0Dg4E/xT574Ov/pUeRNeFcyWnn0cZLOQcp78SPZYHTZiFFhjbHc+HtqkDzYO0p2NsWvJrPUO32Og80jR86zuG0dXhCBGAwV8XT9Ro/mzvQ9zE8Icer1qpmpUsUWchl0QmN6m6uijhvKvSbcylQtEQNS6pa1hUKq/Q2//VfsM0d6i29FA06fwA+GI1rQrutyVX9px/seV7KfeIoD/MIflj4YMyn0M2DLEDBEGmXqcF2UVHgMEWjo62gitkFbK81JU32G1xWQ4EvRQzyJvES7pYwdI9a/v/z+NNkoAeBugf3W4UIzwnz86c9Px6heDy+8bDZABwQ+m85+MZnd2sV7uGf70n3x+PB9wfLSqUA8woCxcAXnH54g9Yann79iMv791BV7L8NPOELFn/+WRQDwLgj8NvRbv4+XITY1oU5cJMDFqUjFIx9fgJ1v+RRAODzUrWw623tPdKZCpM/LiNFOSwjuLMCJd4lDF/zskUoxFyPyoELMjbaM6g6CDzSTy9eRqs4TCvjuAOpe1CkUEg95x8lK5U0CRipl0rS+d2Kx0+foB9fp1KK0hbgZowbrNz/7ZircCie6U01wM6bwWB+tm+YEXprEptUH+YJkCeM/ghGtlXjosmTCkzLRG8q6A+vML5OjPbk+x1o8gColYZq8Kxz0SjhHWUxQxkyIbsBLiS0FBxgEpUYICG9Y+lpUDUBYAezCaCKMW0/9QNzo7Au0RIg3ElyZJLc/yajJwPfts2/tv3Ym2WJjzm9NKRdelpXbPvu/T8Na2lAplGpLR1nnDB1YGfvXVg2cGtrvJNKllRFKpD1eDBC+/bQGwPdvf5tpO2HvUP5zdfkINo5DWDWBaKUdApFti8N3t0xqvkatsZo30zztd3f0FvH6bRiPDwAYlm1FBSaG9QTPxCCJRVYKldzTIvMdziOqdbrGAJhBquUfUGS488yJZXZK8RXAFHi1mEURoEJHVY+l7cMmWhzYMyOZRV3THuZ+W495id2U9Bd8V49257zggBiIZHW03pdARHsYzdH1T4tAnRZsOwDerZxNd8riwuXy2k1Y0QYAFmKc6JjcToupnTQcHNgjQVfFK4sG50h1WlWW9h4gDuOyHoC6xxRejNOM6Kefvn+Fh+VdMrxsYyLgmKM1/HPjD4tK6PGGHL/p+BanD/taGAI+YMCawVFoR0hRDtdC6NueUbsEdfgcr8pbtumHBV6f24xFlejpuFUcydVQ18a+tqxrN3bTnjPwNAaSXtbPCvYlCBphAB0dlRjakpjhKRmXz1JXi9igUEGv0kUP0Ck9x5GwOpQ5dRncbzaODwCVxq6Nqg2jPGC8wLqWSAKUUHT6T2jHPaepd58DNFbkgGEvscjk6OsSUQnS8WXlIsSmMdD2t2BHuTlPxKA+uwKRp0fBJm6gY93pJH2+bNb64cr47eU598bp8PUpjjrWyC9RxZP7oMJRQ9eOWeLSguGzx1NBoY00JEdjhS4AltxptAOZiuDhlqlPsHxcw6Jy+qlz1Wo7GroNixZGvKI2t5wCaYKY/FZGdzhOBiBTy4z0zA7nPZQhtE5o8ecGCvAHBYIOAg7NMBLyTcodgXQYeWvx25Gvw6Msfs8DPbf2NZomoGjdQn+KEBU+FGX04ZXvWBWuM4dU42uLb1j98pXvSP6r/eWxvSK6XN4uWcvh0ojugYuiQezWPBPbUXRuwXOMSVA1QJsxlToukBxPSCz9GZBG/5sQZYI369byLXbbg7ZhfDm2mmWdzf5tEGZllN0DnIAvkNIm5v1O++NXMZv8DnP3TPm76VPHY7bfUuOUuQ44iMDyJpiurwaBn3nxdvTUz7MjdcM8hB3MgqQ2Zya8CbLiPZchczk+CTowIGHd0A9iYOZInD9IkrbO6wVVomC562NysSyLhj77lnmJk/Rad67ZY+tIsDq2kYrcqu6OWxaj9aQ230urbesCOATY6l6ssyUTQrNqesnuS5xTWwEOtp46Q2vxPH887W/5Rn+nmf6C14+nAzmPApL00K6XP7jtbb0hluqlA2pF7o8oIBZG6zsalev/eVrbI6bdjjH5zCAo86wYjjhwnKd/B6lHcKBzxX5Ieg8UvPVWKOESRrVfe6zOPsggLZw7GkInQxCqnhirSHiPpGkWbUtC5Hd5S0JGPv4hDKnO6lv1p/yas12int9jtTh55ylnLLrSxFoStaZ8uTtTw7Y7UwMfG61nKyvEbLNmlGrAZYwSPgnPTzIEKS9sXJJT6nHVkSJkbUi5N8yHV7zgn58aNiUm9CfbyOdfk4EdzPOKSuo5lofViwEHoGXQSsDSxp6COu1kjNFriXDMXtJl4Z9OI11XnnA7llpA+FSDP8KRI9tcjFlkOIMepDdnDT+5r7hqI50o8JY49VWCUgDz2JKzg9YIl3VeGLggI9psn/XQX5W78GtWV6dspQ//+D8VJj82Fitph42Vh0TKtPpgBoei1c21KRZY98tKN8r6pzOK4YqtqtV9RmbOfKa96mV5oEHrUWlHPHxKuc13R6hwK7TbQsdugDrYhWaxr5DlTZQAeXgGWhVBFCf19SB8dUs63Sg5xWOQ65bzliXpB/7vjveSPKxlrqb+HMjaIrrvC4YGxuV2vk5YDLntOoa118/o//0zvsnf8L4mKsiP74pA02rdNqMgUXTdqrlJ55xw1cqvrbyQ92VslA/rRABtqfr4Yk6Z1bXUEV7D8xfSB2B7edP2AC8/ukHTP2E+bPis0k0f85S7nUvayw9vv38EYDiLIIFiuGU6ZXvZ4mWSGJ7VASjKQaa+Tbe+/M9GWiMidEGBN3aGYwOWSyelhyh0mGBQJtXWPwgWJYLpDXslzOkdVxZ9cSdvJQxANtHo+9YWsdw+ZFJcqxYEPL7d9ajshK5+f17IH3xOiIujAevzn/p/6myXOgUgrTDhG5RHOeNGehecQmKsB/qBKZAm2AOoDfxZqlwPbf5+pk9ti/dk5QsYCFkxakYOrBtu1Vi9UobT9cnPD094fp0xdN2tWob/lMrDU4F5nT7foWVqtklm2LAg2YLDA9wVOC1458F1wr041fo44aH//f/gSrQrx1DJ/Zvv2D75RH9x7fWxgkKlY7rtqOroHULln/666+Yqjj/9IPRFrEVeOd05aMkokjlocErKfv6+oVM5vy0BNjdtU+5HwGUn6iDSalUByvh3obxh6d9BN0PWdcJtyWkCBbym4KTpjMlrQPg7YPiioMNMs/eoO+d8793/L33/aPHf5sD/fcmHMY+/0e/SzXuPV0Pn/5WvnJL0LSgy/ee9Ww+Uu65pZYvPOmhCPATVkAkmbIhbge896gx6OlZbMsPHfO3V9CSddxxE6H2NwOkCB0oQhnqxlU3DvmG09wwFGaTWOZzA6ZVSTwIn3JAFmZcioinxrjgw8uO9BOoSkO8tjrFy/yUrJZSEY2aKIzpHz9uGefd5fgDlOD2Hk5lwStMfIHg9Qt4l9crgCc1JzoL1RDvrAj5pVz9TDQOQvs87rS8TC+OvFaK5wAAxyXPqzWhSRXLqweMbxOQJ8sGuXm/xNvtmKjrpIVg+I/AI6SQ5eBAh4Q5qHvr6G5cFWaYSApIz6Gvd/+Ms+6QSaODK9SusHOow6Xwxpmoi3oubU4Iuk+nLx0TE7q7AKTAsrgxQYG++FOG4mnbLPvXIykPDihfZAECFrcqn01BuOk5pfolgOdbjrONjOL4QgMtapZBDKL0noxSTb5WAomyTgJ1UajAWRqaeOUAaYBahPI+LCNo30cYZXpfcL5cgGaRp+bAmhDpJuD1xZwrzft+NxeQ5015ODpbVAEdGUzgBh5BUei53iRWgZu2zofvihWSILNEV8dr79elhFmxOJgtyQIFGOkpQPRGbd36TNMwI5DI3AXMiW7Og+FRthPf8GilcefAPvZwBD4+PmK7Xi2YQMxpz5JKUOuh2xRuhPEexDush24ghuOVZ5Jw2xa9C0Samqkf+OewYj9J4l7AHuVZhdAeSFDFYQWsb1LifuIzl048QEyPQmvwChoRy0OlXIPkmbTNSfleAC/NL2DZclI94l79zdDqwLHvHDVbw56RUbkcx3NDJ7/j36ZQ9dbBul7MnDWAudQSbVUqJc6MnMNYxQM/xLhQ832gMwOD4MavKVn2kcbx2uLC+pd71rcw87BmmyMc3ZnhVmlbQ2+KKR3i76pyDoUNKtW1LH70MmwJzBb9cUm/MovLAi0qjyAMNUo+h/yEXKcKvKKDHS6MYIRn8zNVn4bZ4wNzk+TukbJJbvhAeWbeV9cVuP2ztXb/Ap9w4HdEPec1Vk47+YZtRzOiiJeAq8+YOiFqpcc6vESZB02J0xMa0EmDw7Dv8mDySMLxsOkPP/dkuaO4UwNbqkFYoQdvGUJRDmNMyFm5dzPwRtFFMNSKJKoxLGcPpLfO9IOOII0oHqkrDRC2RxO71yr20ME9ItNJxjBjSil5xF6GhdXbyM1T7tkKiKA4YlmDQL2ViY5hDne1zAFz3FtQ5Yxs9xS2yAaspKIHs7TmbV0kVqmJYNt2nF6f0Lr1y14iC91kP97DoC0AwL7FQgok+J+VU53WKgfAsjgtgo3Ti7KGfNsrEsENhF5m2grTtAPMiDsSiIlkVMT/A66a3Meyy2RHLx3HagdkqzmCo7GNYzDa8eaV9SZ9vD4hAo/iumTRAIOJJHDQrpN8MPmGaGTQggEtU8GSgYa96oEjhmDDWwLsopChmItlhqzeRkM8uLbrRJPm6+FVSlw2gwcjrMsCXU+Gd2iY8xGtLVhclmpLt8x/3YMXRNYj6EjxSlpT2VHHnRY5N6FTGMzkkFwvd4Ky1DNxjvptyDGBI6mLk7bQSJdrl38HGaiYdlirWPznhOxlVnH/uso/+EnzdNAI13805uOwCOd5zpH8NwyMPm/Ow4KR4kkv4L8850tC46s/tbGEKWEhed8hSDid2REscguIyiLoOPfx8rxtPbs/x1xD38u460bjfhPyKp87YUfYshVD2Z9HW8cNWjluxiUy80Uce0YD0dcfYG1yNJzew6fQwyWnFD8+gkqN7A+NzySHh+BT3zsVNoFb7t1IDnoPO9JhnYcxmdhFzWnHYXk1aWQstsNLig2K6xHXziDpYbJQxDoeR1bWL26oNxMgErW5AwSCqDYTAzj4/J2nusylzlvaaTnSa47N6RKVIko+QnyOyTAgXGPMGehQ9rVIHYxNp1Z8o84SwkXuPVSwH8Bv12a7AwZyeXUvwlMn4CW0mzvL7DH1YXrAi5Rv9EAHBVlKPXSM6XyLdi7nBeprSr5bA2X4bmLB1MNQTJ/oDapi5YWDmyR+JNZJEhy9pY1JV6dqvgcAg9Rm9GbniPMwXQqHg2jmbBwuwsWXNk9Wlmroi+9hDyjszPgtP6z2Z+TX12UmrbQAcKOfY1jwpAzF8s5b1M2J8dEDRFGc2kqp+pmVOBf1hbP6navIJojWYQes1TsU0XLJ+jilVZOY1+QdwFLzN8f8WdE/CB5+Bh5rG7g/6fFVgDd13wCQHwH5NcXavQg5bIFi+9zsbQdcE2stMWCy8/RNJR8A+Szo0rC8V4y/lCxcbjzYO/sHwbJ+sNZry4rtfEZrHY8uQ7DCk0t2tl7LwLI3LE2wF8ezV+SHSZm/f9zjPi8df3Rted2jKM6KwKUmPibJc+S5ZosFUnascobf04zeMLyQlb+MzIu15HE+qeQPXtkMzQJIraXagqUtJTjRg12cXj5dn7CPES3MrtcrrtcN27ZZWwZ1uurBUJM/w6l2qfxZIZ3VLrwRQlxS8AIalpgpiCpfa+84L2uwzm1fce0LTm2BimCBwOtuuh2SweIZULH99VesH34wWJMuCvBWBZ+LnSz5wJEDARLVSIM6UA8+ioIub8B15OIpUa6tP7HY9xYPVtrHwGVdcN0HupQKp/6+MiB/n9kpVdX9RYlbB9Z8Syz/BuS/zcn7Ox7xTzv+FBnowbMp2+kRNOzxHHLT7z7teFRa8NL1Etc68h6QxIURef70VFkoo6gLaTdvC2MvJ5Fo8KD27CdkBMxEOs/rPNo7wf7rF1x++tEMkao4f/gR2z6w/zZwer/i/OOKp1+Bia+lNNVL0FFAy2jY30BKxgQS7s+EBtYE6jclzPjocKLpgXlxk0OrIE3YF7IR/Qp7XCc0RnAkDWiLEYN5zchGYbaEavTy62paw2QdJk3XnALFAPjNF/TB1lczQCDZ4z1ScRdKiDKIz6H/Nws+9frb+7dPO1S+uZn0K7q+QsMDOh5RY5O3O2O9FY9NJH/0b18drptkPLzL17GWkaqjbBBALxAaCYWZSy7UFyNJxwX714ne1xCsur9f/IzLm1buEcwgA86XV5iPwMC3UGhjhws8KzmVYYHZSsRL1HQvTSyL5ZgrHVkBqaJhUNt33BZBOgE7BeCMToy9JgarqRaxR+NaVsnzUq/OLFv5Tjqw9AWKPRQpNOsL1Zw5mrNoYD11jB1WDum02nqqGTsxgdnU+s149tvN7v1Dh7z4RwrKArGy7QLorkHs6VxuBb4MCvCSAWDWwYGeCvHNPlv/YcsSstKaDVMtKnX3vrLbPrCsFhixnFZ3jjdspxMw6QQzB3NfVyzLagZTluDsvi6FvjdmZIl6j1i1clR0lrF8tNOJKXbflFSPjScIyEmkGhNdkXDGAnd7RSkmy+ybOAsz8TV6DBGPR7MO8cysHfuAyMhy9yIW5T4GRK2H2JwWaWj9hzbs3nfoadvw+O3RjMm9Y9t37NsVc99jH5kSCyispJNMy5hhFHHrAuw7sGtq3gJf8D3xzz/Q8dlaN+EYVKoSFwJ2gJfHy8e24Eu2f7ZodeBrIJQtzEBCyh6JCAecVrKbMLzXHozV+BwygfJ64nhKz243j9+I6/Kl4vtb4h32ojA8VuN4gYk4fqTjAsleb+WT4Evl3YKsSspTVBQbvLxXTlpAWSHnJgqwbQan3QtvCAOcODWQZk4PwFoddE1FaU7MkbzCHpBrS0OZOVsWLIu3cvD+T4BkT2PH9ep8jLXycus6FST9hyAfvtvvn7CAEExz7M45MDDQ0D1YzNert8i8ticMz2oxQKWBUMgEQNrJF9K+OW9ky6PtsfCmAHR1QCD0oO8KEgroC0YZA8XLnOJ7MroFE7SEKYAsqWoTZPsdwlwSAb1FEL9qwTtoao2MEDfgi8KyiHUA3QLQWrM2FTUojiCsRgQaxcPF6EYS4kw1AHO17kMLsR/D0KlFLhB4OTvHj0AxGqTtGRar4sI6S1lOys8MEClR+cNKmKtO6wvs0eM2Ac/gZ2AdURGcv61FwsR+TxVMEejc0EUtk11sLca2eU/P5F1z15CfATcwibX0oGzTm1c+2TYMNRkqaImTGGYxdLFqF+rwhFqvSAYAHGjnYT3Il5s5z9cFzTPPs6Rg7k9V29cDA0JPqPP1FqWcBTobmltKG2U511EaGk7KthJW6s/2qslhqjPkxd4n5ixl3G/2Bg3EdV/zXJpbs1zrjJ6ad3DSLyeNBuCVzjQrVVEGOWBxwnF7NL3A2gTxK0FflsRh1agsQsBOr7V4rIYhXslFEFmL5kEJ3FHfM3BHiPrmniLYtyt0XzD6RN8b5tixLB29K/oikKtgzp68RYG2rp4tAXRR65eJFaKKuQ9gn+jLikUU67ri5C2BejfZc+6eBcM1nFYdiD1zj84teLC3793QmaarugaDcPJFHdrbRcuPlZ4EvKN7aPIMgr7KJseBHZ+rUpzoSYTDUBpPLoLL8fp2fGbVl3yL0nhYs/ciod7tAOr7/+g8d9mliMY+y7iW99YKBHI7zwoKyi+C4D3Zi7vyIQYga3knDrwon1okUHf2KwAW+oqgPU2YaDyLskpxqAnh6nQvsp0lYBdBGQKw13G0+SDS+7hjGwUgboI9y3ok4J+752jKsrUgUULIDgfHGecnLWRHIXFHhfMt2jMoxD+7BZoBNIwHk/r+ivTq62/KOZjRRdsA51NA9Fw4klihGGS9RDjOClMCIkpIRn0E+tRDv7cRzPhE57rEnuZzEzgN1gc5B63l35x7GMtJKZzepJzkP6WpcvNKKBHwGXJDLjhLp8ciOL2P/vEgnC2ruXVWilLLsmcbGfEZltZkRreaNUpmr27/Tufwln9ltr7mUhaAepbqNBtloSdQRV8a9qv3yWb2OWUPEWhTKGWXQsOc9SMqkru94tD/VTPRJ+1bxiumV5+jLcEcqLlu++6ygtOiBhvT09M1HNkNLse0HrJKyIy0PykdgIsHIBtvUc/WhOsbqjuwAVcRNJmxpQxWzKw0/CHdBqi6G3xaa1heP2B8eTzIDCZWOkxaZvE2pwMCk82zH2/K880F7cHx+njUcT9Mb1JwVSyAUBVYutuW2htAJ/bxBRPA8u41AMF5XQpu191tz+te0Qqw9V5s22AH4nohnt0cE6a6GqkSXP79PdCzDHgDPEi0yDf6yfeLAPMNpOf4dihWJP1VAE9//YgG4PPP8xAH86CWhf58VP+1R+DkUbwIGzQdT/MXgyurSAosZExUszKbmgO4S8PpvUA/AfNXgf6kGO0TdP5g1YLmjtZWNLzDwBPaB0FrPwA/bZAxoNsvuP6F1S8Ey09vPVGmoS8r+umE8+mM1hpOYGUVD8CH2Wu1DQxPtLIKZoLuuqbCdDQGaVQZBX/nmoQ5qDynyu0VtkcOdfxZwVA8arP8r4g51XbJDXbIxLdzlodUXaUTMhDJJXVoZqJpUb69eXJa69zAmbE/xsR23fC0bZEI9rRt2K72s0/LjJ6wwHiTqSwAZXjr4E49IuYIl7FIy+VQwYeuJmOl6rgm1jKsNay94fX//HdLchDgdDphHxuerh9w/ul/47qLBV7P3exbveP6l1/R/+298Rk07F5LYf/rb1ABvgB4q8Dicto7FXziyrhMoOISgeaaseYe5xF8Uo9USAoEFi+FP1lCpNkzOh/t+1NVsTAIGoJ16diH0dnFA4f3YZityKAqEdM5iKytNw8gTtmqHjck4Rnu8qJqvrp7UFS4ue7+W/95xz/FgZ4Kc52GC3hc7Jv+KyHc4DlTmgDaVI8slkAYHYe86vqaO6fl2cJxNYOgSGY5cgx1QVKMcmIKbsz6fQ5Ayv1BsCTfJQI8qCHzLO/pKHkiGuohAGD/zebM6B9VZnIC7W0aK4wZvf5u/+s6P34Ooi/3rzncSwXF50TDfmQEca4gCUA69G8XirtZccMdaKgyRUhmjiYU9ykwRRVgS69wbLgjcjrBjMxBKDxh5TgcBQTWL1oBdLHVMJnzxqMQtzlOKgo23DvIWn+fONxCPQh8OaYzACnnRzGWE29UrIdMdWwf3KUCZBRxvpFX2KdW1vPI/BjfZ2M8ToUGshZuRI/yVSAiyKZCxsSQAe0d8kqAqzvqm2BpF9B5lqxBXZiQA/41EbRXAv12caZz9flqMGoJpTx/mhv/2mIZauxXK4ZaQawhnr3oDDzpBZfNHWON5apq5L8EikcEupfWmq7oSwndnWqKhJW2T4ftBNCXFTpGlON2iIShezmtABTLYhHkrXVzJJR1aRC3cAjQTNE0++b0TBgtE7t1uklZXxzXJlJOGfkG31euhLlxf7966a5p2VniPWLYnCWMCw4LcYIn3RzbfVlwupxxXk84n0++fgtO5weczhesZ+/RvZ69x5H3QW6CtkwsTcJJBzdmigiWvrqCb86CBiuDY32T6s4Uz/AwQ3FfxEpPKaxU29AUKKl5++KbckwRlDgk3hvWyhlN9dJ0VLonHfeW+dtEsDTP2IU4PXOD7rDr26QirWjiTj2nV/CoTR3Wy0cUWNtqMOkTbVGrBkIjwLZjU2Cwp9jcse+WqY5hmYWTWVjVeOevnB6w1PuCOTbPjiSujABsCE9kgkZ+3I51yxsQ+ysSYg7YgzTWlrFwzyZ6Ov3275jIETcUnjicerZwUjgdeoFT6n3pI8VgrSPWyLy1zNiIJYmKDTRsBWwK0465aj6HMo5VnZYgO0k/zZhfjax0Zi/LgnVZ0JcFS19wOi1Y126+HHhvKZ97kzIxOtK8pK1VI7ByhI0ZGXCHKpeY9FvEjcT2LFVYlQOFtQBwQ1XrWcIdPmaIZH8tyllwA2zLqhBThvVAl8RV+HsQhi3br1bGrBdHyZ6I5ZxPg4wwYA/REuR0PodssrvTZbgh8Hgkx431DIAecSYUayCM4UcDbn5/lLjcEdlYCjadFeBeNGKX74m52tFdoY57yhsUlEGLfEH4U5oQW3e72gLXmAm8LKvRcQAqE9vuZd22HVcv18iqMNJaZELpvkdPexujG+NcVDEDJ3siCsa2HdZAPBjV4Hl0+lIOsIFTPDVicQyf5eXHbKBYjtb9tiIDismV0jq4E3Ra8BfEy0DbpIvBWhEycgNkppxg+9CCPE20sOsMJwe6LBkkqxYfb8GDHhQ5itONbyONdJm+ieC0LlEmPQy7ItDrk2VBB1xsP1FHAdT5xEBrCvWiLmPzcvBqgSu0P5vs4/N0OR7w6U+GTan3y3SnTTOjxrosZvhxwz9bBG1jRxsdu/cxHDq8d/VuPfbmxE7+qwDU++7pjHL4Yyp2t0nI0gFVDOe9YV13Wt7RsU8vB+/LZ7Ka95J32QJgf1QN1Et9WUzO7lb+sPeslKPuUBhTnEZ5JV9iJkvXqr2/KelHc1FAo3JMG3zn9PYTi9FDJT3SMiZiiaYD0fdj8yxNu60gVJU/yJi4t9SeE5UVHN+I7rEbJbMqmu811c1a6OyKuXec+oLrsqCNzxjnM06nFbq4/KfAtu0ukww0BZbeLKijdwvU6gqRBafTavtSFDo3DJhsN4ZasNQcRn+dN6h4liMk9DKjUZ75Mskv4fIxPFPNZRkFFLvLRiP3YREfqGdWXdPESwm/bwBNitYXgVlcCJ7nd4XOIeWZrHhjF9ffR7nG+WD8VWQivzZR4UaXVj7TK2ipGWWTX6QBNypghK2DMov4vRYYPFz2Zg9lrgfXw4oAACAASURBVH2dU51rMSlzg3Lxcpw3c7IAKNdPYpGYpwWomNytqtBmMoWpcQptEzo9ZEYsMJY0bLgsMlQjKGkGIbZ3TfGKHCUYS6ExTysVjdiDtv8ZZGG4MMVLOYMsXgNVgoNpPjuIF+U3rg0sMJh0YehEmw17M2Mq+9ZqARGDa0yeAEytUbTu2UyBu26ddxuPzJxnYJCQDuWSxXhbwgcKL7WXz0uc4L4iHNIGEk5ExPRdHCgB+jftmWKfUVTy+QhStemk88HXkzTSRmDmAE0U9Of3WqJIaH9CBEiYCEOXw/Fe4u2Bjoco7YFedKpz7xB+gFWiCTpj5XsBnxhxRVyGdl2aQXDopHUpxzC7jlCDmH14+m+uibq85Ipswjv4qvPOaTYasH2Pt4xxKxAEE8tiDlpVQCxyD3N43/dJGyFth+TrfFeMyPfUDLlxYob+Q95LWseMbvUEC8ZzD/JntXLWMhGyABQYQ0NnU18Pq2Bj8tcQC+rieiqI30w24OLOJGetO+/0Hzq7AifJPxC0ibZ3gab+7nxcHxT4mjamkOG+fsNYV5cxNHm97wbTs3wn+Vo1CB6ffkNf3qYM0ASqjksFFobnsRpQIJw/vTVsQyMbtFb7ooOWMKZtCNKs+t5gVYIS9J1bIPCv/h2g9d+nf/kBtEsGH7KXW7ywBwWMnwuOv/8ElR8iKOr03tfgl3zHBkUXYNXcduEziD2UeHr3qELF4bT4+t2/91g14vl5ifXIoKBCJf23zWn5STB/zuS7E7wtJyT0N96orQHaoNPWF3/96JUWv0CXBbosmMuCsXTI+Yyhb7G0jtYB6StO/d+w/I9fsf080T4Arb1GkwXLupgDfenQ0wmtd1xcJp7wUteqaDrR+4J1UcPnMTB3000nhjt1zYZrbabSRwPkviiSlZPUgod2aVmMEM0CflK+jM+qCWu3o4oODCW7cxu3V32xhDaXXTVt3bHZnH5D4EHHTE5yzurz4qpqE4h0YFmgSzPdzAOdY06qbj91P4zvianmAB/7wJwu9wxLdLhu5lDf9i0qZwbvmMYLupAZNyxtCbjD8QiuD/YIFicdm4cCP2NatdLz6YR1XfFwvuDD//x3XM4XLOfVqnLuV2ACbfyGRcxPxPgyM/cq5KcfzY4rRo2aagRYnVTxTtTCx8VKoUtr2GBZ9MAMXjA00gJitSkTTK8uF7pZk6Dw3IOAoJP7i/ETVjxj6wPSh29PTzitC6YKzkvH0z7Q3E7Qe8NlPWGbA0/bXpzjPqobItgh1vLt5nAxJXE2tjd5THmOUleuJ1MWJ31T7qb6UNQ9ku9OuNTz36GPf+D4T3WgH5US/4hKiLnxqGTaOf/Gvy/A4l0K7DJMpmrZs3YWBMgxtMNzeYSzIphDxiUzI6Yz0yvDoQthY5QRDRwzzkPjbMydz7aZpLoI3zgmBjRc/Fr2jfgmFkW24BjJxEwu63jCXsu+/KXvg3pZm/bWx2EtCbH6OwhZ0o1EAINXR6tycgpMBZwVjuw/RSHbxsn8ZJbpEQiYmWCZx1TaDs9TFw4VCA+4LD5Hy05c1Dt2ey1wy6gF5qMrT4yuDeLVPADDVnB4JI5FjUkI1VwbK0PCMh/sw0zlkYpxrqzqK1sHz1gn4T5C1T9NHPCDsEGePjxfbvYRjOQHTlj5suPNA19jdFOB5a3g+vmrKTEUBJVEWUBzx5PYey/xJFfc8GD4Kz2MPBSqy+o5YzOhkJFS/L6LRTXbXhOH88XXeYPOgXZ+ZVlI+xnbF8WymgF5kQukdS/tm7TEu0hB5QmCc+yw/cmVCLnaFa4MCSYmDcbO3KQ3NPWSv+LZ556xGPZAoSBhUe9NFYsq9th/7Jnr7LplNCKAYHgmkORKTq9512j8GMy0bUHSJoCxG25KY09c20e9d6BbeWPLoGZgjY2jrwYv9n8FgEUatn3Qh+aMrwN9QiY8QzoVH40xVzpejGDEXXtzTC8EMUksw9VL0T/Yw+fYncmqzb13MwyX3uXMgjKhavi4TPhYFnOUndczLuczzpdz9Na5PLzG5dUDZFmxnBYsi0c+sp9RE8zhJajnSIFfLIKurQvojKPRhw6byqtjqw/1LLQGyLD+Zcy08nXsS2b/qQuS2tJxSUGUwoAMsX6wu60tSxMvXdClu9PDe1OjG29Uh+UYwJyQYWrznFZ5I3oHhpXT1kKmAsOUu94b0BdgMRqNaY6NOScwrM875afo5T5Ji91J5VQVsS9s3iYw21wswnIAzRRZHYq2ZAagiCn0rfUoQwzuy0Jji2gBpePZjU0a2bzmuAymLMniedicHBHEEuSzoG4L4xjpH9THLRL7KXfKUcC8dzwXlchhbP83BpEIwvgrAjT20oUJzWbIUDPYkHfS2FwMVBBkL8cwiKlHE9OAM2P01g5BcDotuJzP6eBcO5YuWBqCzzcXyGesiboTcERJZoyRJBA2XoE4bfdofVBOo8O7WyWPqRjdy6M2QL1McdMOkR7wZ6+uzp5dDgcurZWJXoyOi2C04eXAEU4hVcUYLt95ScGIMneFj+0Oeu+BSDQRTLjtrtm6tb5gXYshbezYtgHF7mVPtfBTW5eqUAeqHzLAcFMGPTHoHrYVGxcgsAoCDk9Vq0BBKTydWIZ7jTeRqQm8bzCRqkq6ec2zPSDkgoS3w7Yplt5wPp/xcDnjfLngfL44rZh4enzEl6/f8G1+xXwaYO9s+DpHxaA5M/sZMJxblqC3OgeGqmf4+PpOdbpi8I0xUikF7cHu2HEZCc0DLXyFJK8MgpSy2+2KuIPIId5aj7WnRDHUgkxkKqTTWEh5jDkcNO5PU+Cn0b/m/ehEafBM4/mcsOoIYlnDsQ40jqLIO1oMtk5jdp/X2gXQhinWHmaMieV8MkPTsHj7fZY6TSIhcxFOUxt0+PvQYu0kB4bUCQGMZg5qqEt63WmkG2D2zXnRhCyZVb6uK8a+Y0x795jAtu/ovbuBZuAyJva5W4bRvocj3QJdzBBvf9MAbLS0izg+qpdOL7zLx01jvziuWVbBjGekXIXQZ2PmCguCc+NUbwuWvrqxb3G4mlw+xNoRTGhgCB9CnTCy/9yYZuKAhLNg7HA52QyHS7OWOENdvpQGMMOam91p/aSz11vGiHh2ujNNZnPFJiPNc6cS5039wOQJAQIL+ENXgO9Hj8Ag/R27Yjkprtsj+leB/n/Uvel6HMmtNvgCkVlFamtJ7WWeZ+7/1r6ZY7ulblELWRkBzA8sgcwqqtX2mePjtNkiq3KJjEBgx4vlZLrjOENPJ4eHNfnR3QFHKlhAkMbgpRmqDy+Z5CHDewKq62PDElxEelbIpR1ZnMvpNA5dOjUITj35KkUq9IpC/5GQSpHjdtjXk9XEM8MZurvz4ff5d8pkMzRwO3Ae+3gGqosbeKo9Op9CRQ7EdSXkiUhAi5EQOOVatG0hr0yMxEEORJnCVmtg3hW/rO7TaCXEbVf1PN8t7sUuY+c5uUg5wHhI8N9AwyjnlHmJd1LWmdwgmr4LS6SdSV2ZDORtYAJFywJ5rra7rLJAkrg4iT7BZtvOeQCCC8daBHnOOgZrdTF1jvkeYSLELpTYhfV1lTL5eVZ4m5N2YMD+TwAbn5xBOZsP5mhx4zzDC4+J1FFFiovTeaiy7Vl1x/hMKA2dd6ohmf9g3vayno6mIte2wDx0516MnRp2sfH2enrcX8P8nWOnUPXs+0hiSlej+4ZMZuwfmjYUkPpF5FLkabq3Q2YCm1+rWvYIDLkvVB8AtHAiWqrTHVSz8pAaJxNWCGrFuvXgtkFZzDpenEALBdOag47gBUJOqtkspRzQ2NuY7yqTr1EkQJC99yRUgkaCrQSt2lisrZNtIFMFht0v9R6jXRILiiVf8nuLKBKyRDxAjtDVxWluJmmicXQeQQYqzJFgPging7Y4go4nvglMh7l00+t6N/lyPp+hKujb5nRjtNK3zdZLbDYpbPz0Wzp/cnYW+loUsYgToIwO8Or8Fgg/gbqNm8RMdV9o6rFjDMjXKav55b3tVyj45ctEFqrJqUzNfVwDikcQ7tCo2XgH0JY3rncAp3WdNXe+HzTk99IS/agtzXQcKMCEsQ1HJnyL058AXtq0TV3HDZUz9iZkYPO2Pad3bwD3i4gqev8NANC9l3qtSK//LiCs79+grVE7rl6kY/b76AOt6mY+tQMK/UhQ/AZ+/8b37RvIhwff18DpPYE+AOvPbyDyAP2gOL8Dvn1QdLJe6N92PHov93eFMDc+n6J02gW3jmcD7E4fJN5GqciMr/6MN8ErP1pyYiOzbF7+5T1kdDz+8gkrN9z/9R0Awre/f4QAePyguP/zG/RfvwAELH9+g/V0xtcPn9BhiVvagfNfXzqrsYINwG2t019xd29WGzna3LKsWM/m8+urISyePYlz6wMbzH8hMN8bFmSRSr9suHDBsPXECGpWUx9JJuFbiXmNVp5uACD2UhQKpy7BwERhoSxAjHjJ9LO7dqxeLON35GHJKIOt2IDhyech72VAxfQJH1pIuNxrxIHMGTEcswfCPxIDZQbQGtAWCHWImE5Q933Im9BUBBaniNZ3Nq+KrW/Ytgue+mYJ9IE8QhFE9gIzYm+VZC04l7ZAFIkyCDJUzqUtqaeoDGvrMSzR0iWLIW52wel0wvu//Iw3P/2EV69e2TvBbLguAHUBySs0PJkHjAGIIxXI8EQDgJRxfkfo/zD2eRHBWSw5kJu1hiJmLK1hAfCJhtkcohgy3IZ3X0Eq9NH6izKGYHKs6J0eK4T7VaMdFCtwXhcwMS69J1tQtTVeuOHxsuHl3RlghjwZLdydz+DWcNaGy+Yt3Djko+uvrnS9uHsBJsLlV8/2KWpLUGrQgLFo2wPzTULLgusarmurhtk0fXqIRLLK0+z621Hg67+PvPGPHv9GCPdqUpZJo/07Uf7HhUxIuxsHATehLYr+ULLryjVwI8z/l1UfNJmfukOqKqb/2pFqvY3HX+kORandnQkQXkDxNe8QQR/ACCigGi4PD9OQCkJXr2x/1lj4zkiJ/hChqTOuWKusJMDc3EeFAxq1na7wKRAAYPX8/Ns/4KhyBfZIW/630lzpSmf79I3jpDAI9wj48uvvqUzHXsmwdaigOoejji/shVsvWN/1xm2eW8aZZ2rn9Ifhts7Me9vP/p7RROoD5TeUNFbd8/Gd5jfzivi8nj1dJ/M7++yMBQYDygTQvQeN1YLbe2fSjUMB0AXQOwAGgwmKdBQPBjTO6k20lv2jmBsaAj6VE9aaGqctblltfj7dgfgR8Mqh+pIBmylu8AuFgqnXTGmKuqTluiJpVBbuaPKDUlhVobWbjhSKmv8am0gAOTOgwsAKp60eCFOnkvYjx1S9Dwy2nBD8l8r3Nas5nKjkZWbRU5wJBmnlUnhdTzifTri/v8eLVy9wPt/j7rR63/qG092K9bSCvM9p9DPPALg0EMt1BahJZzOUhlU9EAjKgDAZTcrcD/ZO6oHMubtWBka4pcTSoCLcEQ4So2u/STpdLUCae4MIDAvyDbcel0ww8CDJEGx6AS1rOgMi4Mdsht96arkmIrN/ZyggYd+oKLp0jNGhaokXS2sGWyqhxAeHmU7kPhRWlBsjDxqKUPp8P0twE+8fC3O2ObrM6N2SGqhS09S8ZqLDDfo6LKQl1/hfFM8uYmzPoPY04Ock6up1rHJeH3Q9PdbzPqhJQ/vR3fqbI0jnUL0Jf1uCHRZ09hfx4BOTTqxMsudlxRZHCwSkk5agc7w+L076GbAz2oEbHXMO4xnGowymf5Jw2ceR2BNVwb7pcz4iSFtpxscQ8H3KBBJK2OT4AU/+Ft6PgGduHjjnSBgL3iKeBQxT+g3OffY7proPYz2XBoogulryFItY1SMZRDy50lHVUs0qc5kBXp3fRWa2rfM1IV/ReHVs0JHW9pIjKYrqT/mMbQ825qzKZjZoyZRXOFwXRJ6jmI5lSge4ObLn/EciWhmHv3NbFkvMkW6OTgV4seSa3mdzGVHF5fIE6ZMfmZfdYbSZwR4oaW2CxSb6gs9L3fOxD8T3kbEf20uBcJG6Dc29a9DGnHp2yG238srM/HNHyOZAWhlqOhDEAgbsAfvsDqm6q7oypcMr6sMJ2ggsvHMQskPpLUtzFAKbU1ZLqBDnMbVyyvim7B3cQXKwhAy4g4iZEO3Od7kVqgeEhMm/oJHYOtcvfiZUnO1REYGQJWX6F5a0y/auYMJptQBzW6wKPeE43ZaLav1oUfL49DTlERySdFktKa83jM17sjv/kKGZkKHDA+gQrKeTzVdWDgBPT0/mIWIpL0+5zuG+ST5VacgRh6KiIio1WvIyhpK18hkilrzgyBkqxXGV+xrTMGCk/kjxuYrpXl65N2jLyokRiRZS9DVMmjc+CkCHVbYlM7T/zIClgnTKphYBBbcRQ1aBBkjPsCoZcWhWR+aJOEa8lw3AnneyBJ++dTyOb5DzsH0hYs6thOlXW9PF7E6NQLwCEDWUEfXARC5MODlNfiR6R9gnO15+5ASa+yGq/gpX3/EOS7SYqAAW5JD5vunE8BvWfZYbbx771KvrcaVgOX7jcu7oconPj7fJ5+v8dwYw7eOZlDjlfqADKQJqkh2FwmFUnT4QaF6KlEnXb2OFCcf3CRmfpFLnCz6IIFk9XH1Q7fbBzNwBV1Mx/4hzrnbN/FtCp7HAvGC4XuNuZgo5xlZZznYdKUM45sT8Dqp1bkJIZPh6Dq0uRfxaSCrGX7SK63e0obtcKq/J+/PCplXM5PfjGakoTWXJ5AbNgRLNayjfLV7TFyr2FpV9RX4/IAlgvy/qbtT530oIO/lVVzQEYYzHP/WtGOdY0TuhVlUlSkXSdeE35TOKOZzKEabjoIzKb3C12lM5PZyL1GWZDW59+gSo0P6U/UcCr/7BK8mg8xn+wnu7O3lV3R/7Z84EpDizJgPUkhJ/niADoxqQNZmM5QydDtfEHPnnMxnTZSQhdXm7XSS/+9+qqUvBC7EqqsR8DO+mT3MOnM+yVYCzV9hzJLzHaJ12VRSjD2zd+nsvy+JJGDMBqiZZ1FWx5TLiJH9vVcXYNrR1navnvpCKeBYkp3PJd6tXV7Hkr9ucqiUJ9M/fQPeK1l6aDamPEFU09nZLrheKJ+M3ahAxXUEy2XfuCbgdl8tJpqORwYJYT+VoG5UX2l0CtSnoi2DV57mugZAAh57nV3aePpQxzCM5VWEekSg9bZJgQSUQVOYxShDGh09pm4fMaTBaa+9LEtg7u8PJ36f6+K+2az3SiDvKyv++I+WJBt0Vfu76DBGhvQfwwd+xLdbqTQPiHyAlECnWdwTVBwBWGPf0jwfgL9/AaGAQ2jsG8WsMEauWVfeZsWEPMM+CuPCHDBHo1kHEeHp6AjHjm89C2MXmOrZCnCaLfyfYLhdcltWrpwcGJmuOohfPsCyTgB0NBuKTCiwoTUAkbPss/tBcp28HSA3Iftccws7XQ97q0VEG13XB+bRgPZ1xPq84nRqWhS2XBprofzIkEbtS9DHSr36+v7Nzh+ncgboTrVvM1HDodbV7jTFKcjsmvzyKuGBAFPO250PZ3iNIu+wtS/w3m5cxoMTWwhSUe+CEgUaGiAdV9NHR4LLQ+czaGs6nM4CfobpZ0kbw2uWEJp6MpYDqnyDrB2xjQAdhZZPLKzEWbhC2tmRnIrznhgdY5X0fhI6RCdym/u4VkEBrJTk6KKduE0kLFtc0XjQ8MY0Kc1D19QHh8XLBixf3hro2ZsJ1IE2q02zcP/5LXugWSdR13Z7lQ5WZH847Uv2xVuN/w/Fv74E+98VUEg5aJAg0YXRSimuec6eEx1Ss53X3Snhyonus1ZCoC2WfWKKPQR4wV4HmG15nRcWeFGa2x96Lels41THE31GIBAKWoqPux6tobxjbJ8Xd25+MkD2iIO5Q6Q9foAAGAU+keKFIiKlQ28bOUNgf+sw3NeitB+qOUDFFZZCiKKKwzU8T6IrhFeV+IaEDOsmQdHGd1esMMuNq9UCL7Fa5Oecir7qJxzYsFpRJx5w/vyQUxDAAKpt2zo/1/b41U5N6rJLqG4B7E3yhbOvXZ2azTmxhYs+cWBVgOnx263DUaBOc9BKKL5h1hVcsKX9bEbRY3A8EKKyfesMrAOQZhbfut1drUebRVHrGfk/bz3LPWZ0rCoyvA7wyIFbdZ4H0qYnP+TCm3fTsVe+P9iWTO2RMAeFmzn2FVyh6L0NmwtIWgCzISGLGSzj/gvmbo8+MS7QOeAUzK81+kZiBfhGdQRO4oVeMkKo7Ech7MluWXDoEgKxCCKEWfCKUkd67zWrjDG4C5AGdad2YcWyKQ98MDtyMn+n22AXbD3yrckKf3h1PI3/GfufsD4VOBJByx1s0n44Wn6QMmrnCR2QO8rvzHe7u7/DyxSvc3Z1xOpvzWhU4ne5wOp0tC7x51iU3p+eYK4MKjf0/e7QBIgNdhwUf3RJntQx84WhHEJrobC1ACgsctkBJETg2blEoBqBhyMc8zLmOXuGB+L6uKwQDzavaSL3iNyqUvQIkHNsca+7BRAW74cdeETyswhYOa+aBJyYzJHrvFlx02l+XBtBitMb2viFzOnWM4YYOy245w/kQClzufKJJCUQJvZsOUULOeU4x3CgpjuGZzLPnO5YI4+tQiGzCQbqpHEwyK0eLxA8P61Gpo7IbnEFOe4jynlXHSGdtisQYT+wb+ygCdYGgk4FHR7iIakX4/mDvPQwZsSlzb+W10dPIg6ZWoR4BTc11J1Jf2xk8T3SDxXioxyuxdzo6HZfi20h2yupezGAOXA6YbJJ87+Ah1bFNUU1LHjwvFeUg4+UoMOCh5Od50dtO7fkWYBpeHeOoDulonTSShwfmMtGO2X5aSyi+tixGZ8UpmDJgCAZZgDr4jmJmW5PLpoBYtEMmxRLtgg/1mMFtIPudiu7oiwMe1WHX2JPE4nMA6SSMagwRKWOZ9FGeDJQ1jirWxs0SbRzmf1kNrYDZqoAtwE4IlJfz6WSJnt17mwWcugD9coF2SzAQqH3fN0RQmJhnAgOQ/eCNZ3j/rej7NYY7TNwoL45eJqvgU9cXvMxpVjuR76iiyyoUY+s2w2GPaJmbMm8/clTQtXB9hG6bFfXkrQPYw7SlbyL5mAKdIMITwbAaEbTNikT2ij2DzG8GG+98qHcBNYIKOdJXqFzh0AiebOfYBKgnW3kFtlhLFlICNbIqejaH7BiGPFW9e+R6wRgdsz2Sz6GqPcfHINodgadoELE0rWEtivSyLNa3ej0ZBDdZJUzfNgzXm8SrkLa+4bJ1LO5AC7jC9XSCquKybdi4Y6g5NoYKdMD7XXvldaq7zj99zi9PG5gYwt5L0XXD4DuCCTsflGOAXl5dmvvZncBePdW9eoBpZEDSgroyq1ejWrM6nIOfKLKSheeWcFtxIFrlGGShVeqJv6R61UOt4CVjyF5FGoma7pTvxtPawkbvLoeZjA7ZdXGG8XMm9SoZk0kirrP04RCL3Rx4Km5rceqt5FDSqor+tEGoW5LOGBl8XpYlE/ZUCdo7Wlvc6W7yihpDxgWxGTMAErJNvaWOVorVrDDdBa5Cj3G7bK+3REBXk3YSkShkp/rsR0IEVS6RrKnQSizwc8JjPnv/2e3jOlj+A8aqK0WBiBNs1+jEdaTijJv81XVAFahyCZ5bAQOFfVLflfaP3s8C5XxP7lDHX96j8PGQFfu3vHHN4TstT5p6IgFRaxUOX/iE5Fo7xUQA2GVOWWX7iskUiJxmSr4SSCKmQJtMSJubPCilFCXsZb58jo72dfzC+7+rs/pIFfk7xycUGmImPKXTO2xsKNz4xqy81llZkg9xuo+q7/Cye/j+alnd/rD/+5OCCAB75i6DQI+baerbxxeuJgfN66dtWbiC74WwE4JpEPnQQx/x24gHa1Lm5gP3/kulaBEnu7mfTMn1GtTvYyBlcv1vbs3Gz2ERY0aCXB6jyI9ZFc9Jkxrv5tXoEslYrkfvqsQKgcW6B5/NubvF547qlb9jfG56oQVkzA4ZFvyggSAqFTG9BWGnlKmOt+fYL+XdEDLC3iUxFdIxXBdaczzgBuiw/cgwVExSZN93lxumf5iFtDaTa51Mzom3myJHKFRvCRM6tsaiua9EImIWYw8ZvzQwmtv6AxKJpw7/Li7H2Nc321Hl1qBp58W2gQUX6eUd5Ms3pwqXg8HLQobKN/ALAreXGP0L5HOgahLwmjDGFyO1xQPVJfCdLQg13mom1Fg1sb2/ju6vpFiaoahJl7l5YPaCrT1N2oOi94vz5M8geokIRdrUEk5k/un1T2+TxUCBb//4mNSqADoB48NvsxdyszY/4ZeIxA4OO+/nN6a3fXzYgVrEXovPzn99h8f/+oiX//fPpgcNYHwETn96g9P/1XD5f3+5klCV7f1PHzt+Uego0l4kuchP6PgNT3/7FXaJ7aOnv1nFf+gL2wdAmqI1q/DnZQF4RXvP4PYNoDdQsiTep20DFNZD3hNpg0e1NvXURH4aHY9PFyjg8aTYl2brN08yivdSUVxOF6xPT+itYYwF1nbH25Imm1Mk4q7zUfU9D99LFid1vdbpmoCa12dHNZMOC005T3baVwJe7U5VvFJ7N0PU9AKb1rCsC07rasVJZ+sFvy4rlrYkYtkIG6NHkHcfQCeyJJfz/b0n84qjP9WyU+eZrveEXyYg26NXt51TxA/mT0xj/SXmOeyp0Ftj90byffgP4D5TEveDOgT6CvL2f8Z/t60DSo5WCrAKiBtOywnRLmsbPe99agsUisf/+gh6+xKn9gBZVgwmnIhx/+4Nll9+hZIV7jX3b60LQ7nhSQc6OQKKms7ThTK+EHpD8FiAIF5wsvNh+q4fjrSyLisUbjtCgfAnKqAahSRGF5c+8Mqr9rv29AGZX83oIJLpAzHM1o0gvVsQnUNfL7QJw5SpqlpVpVBe4ZaWnRc8++X//PFvD6DfPIoenYpBwBVcTd7zs/m9eU5lLR0BdeXB7wAAIABJREFUrnx5sCmDVurwxjDhRzst/A8exYEXR8dchPsDs6y/M16BCLh7+8YcXSjBLhAunx7MGeUb4SSK4U7gfDbm4+l3ifBKLX/mneIEnUIhnhPV4aq782BfOXN0eIyrh2n9o/xz3HK/f+yreV1Y+ndyeMz1c27//aPHf7fycrwf3fjcmOuLnQlSzfFbx4YZRK9TYYzv/pmr/hg3C6Ye/+U0Fi1DThxSJTP4RAAWCHhmmWLSGJdek1BF9BbU/UMtcBB7uzWQVyVHcKEZhvG+Up3ggSVPqIkARDPobzNihqkDQa9hWEB3ZmtMEfkchFIWcxhtCK4qr+LVwsEWjrsM4GrCb8azyccNhQuxfAqoAbIJIOx071mPaiOW6yHPMZZ5//5RJOZ3qZ9QzzB2bNVJkbnJXnlK7nRjD5Sty4p1XXE+3eH+/g7n8zkd3kNMuY5qc+M94Sxxrk722wILMBAsmCVEXqlkzm1SgopB1dpYzbkrgPE2pQI5Ov0hpshqOqIFBhcUNAOo9StLHglEYIKa90yUcNBa8kXTaXT40pvxQQrrzF6gwPz9iD0YAkrFMnp3qgJorkyWVba+nm7kZbBpchlCpVNT+NUr1uK5k1dWgvKVToWbIOL7yhXscHhA1YIQek07RJTByqJFI52HiDEg5/U4FgIODpPbRxgk15/qTn5GIGwvu2l3TlbPzhfJ9wmnGweOpf9LFeq18IyZsBKKMHkAysflxibxNPxBEzYsejbFuchrInhugc62WFsF9qBSVA2mjI81IA0/mXE+N4wyKIspZzXfnTOgYHS7p5Wstm8MFoeXjM/VqrCA6XBEZJlnwJjM4eJjsWza7pWMkkbDNC19XonKuqsFaAmTPlOqOg2r9wZzWrQ5I0/QYoiSV/YsBitGUdFHiGrmMPiAqMScvNGOWdE6KRwZrFF1R0wGGGh/H3fOtVaSEACIw67GOCwIF0/SMoagZQ8QEs3AFzPWpWFdVrTVepivDvdP0YueOBOv2McxhmBAHL7RHIQ9Kj+8XQ+IstITsMCo6QlFF/D3NSh0yhZPItbGIoMTRBmcjP2fQZnhSAGhn4e8TrmtuafmSlT9+8ePXQU7ZlVk6g1OI0LkPd8ALwEAPLhpsHtzrWNEu+fk89xQ5tCBGhoRELDIfjHB/eXupCSHEA4qmIG9fdAf/nTrad/QlKCrom8dwoJGBn0ZPSDtdM0xR+uZlNUuq0Knq/Os7oVTLjqRr1l1/LelebsJo0dyWWLIE65fjY7LxRJdoqf70hgLr2jE4NXQV5bLhid+gg5zbIiqO9EjyVGwnqzXumOKGnIAgNN6wmjDIUMfIQyHdZ16nuqcD/uGckGMTuccj61b8NcvYZe3iHtJoCChJC1NOU7PeCfiEUwEcQeTNoM4dh+fXVvkiiV2su/xqadFpZfl+HHeF3BdKRErZruNmhjVfHwMBbG1XMAYBq3fO2gjdJjjTiQS72aHVyIGBtAx12rrG3gsoO7V5wQPOlq7jrFYK4IIbAoACAPSJ0+1CcSeNCNx6nk+MO3fEjBMur2xFr5eKjYO8eBQ6Meo4/kDttf1U565hWpxYtH1dzu9xvdrPQWTJ0cyaD7mBtrK7vYSSU/WU5mc/5uuqAnpjXjqM/ZIVs7H7xFg9fnO/UDBayJ5YZ6UKCauVv6Q6XP7pQBoqWidY9yJD+dPN9GOrg43ALT8TlPzJqX8at5/6vDP3nM/8NufH+DF4+sa7Ly+894e2Nm5CuM3mLwwEmrn/BwD08fXmn6mGtQLCbsbln8femdNlr99ULlX8OT5zlrmlQ60lTem+S7x8VQzXBNIui7i4PCHzkjt1CEOdtVh6DkXu6+PxOxtLeDrMBUf4/VIWxplPgkzy6F8lLA4JaGT4h1xYwnLxjy8S+7hq/cL7QlXVc5mH8Llw0g6i6Hke/mfg8zHC0fSyneXwrdFPXg7dfVdCyXCpNlK44AniqhFtIKn5VRVPuzyVb0HrtvoIW+h4QfrxhvZCk92fIWnVhm7jiwLzT4vbIMIaI4W5MLFxz3nQBFIhc/z7dgVR1mRdkkC1mny1JhD8fai8YTt4SuCTuSVQbeLfAXw0vNmvFUFNOksEogne1CQo8yQDJ87IFsrDrc3InHCefNxT7T2GpkoJ4pBlngX/sForTFRqY7zArcxtGxjmgkZXmm8802rOioRkj5jXPze7tl7j9nNOAC9U3T5DZCfkv5yEIcxTZmH6dsoNuPu83/5uL3nr/QXF+uBsDnHoNUcA0BoP78Cc4P++mXuNShUf4PoO6MdUXQRPD5dsD09YW0Np/MJZ5ywkAVDh/vXwM57uyWkfP36FUMVXzIgbInhK3CFptaIsAQEd2sY7H61IZ70UGRL2FpxfZ0TYUPEBBtQVfm+oq8Uc8sTKUvhH82/YvcSBf+x79ntyldgPDGBlobTsuJ0WnE6WRHS+XzG3fkOp9MJqyfCW2tjrxjvHX3bDL1r9BQBUYGOdbG2BcSGoiGOkCPGZxMJzBOA1P2N4sHzQLxKuz3WN3hvfEJTj0D5nrK1xv6I929RVAJXmzT2tDnFTuz2MbzN09YtCL/4EvAKpg9Auwez2ZmWCG2tAmixHuz468/YfvkVGCvuTw0qDcrD4NDXMwbEURLNZmnuM3k3GjZi/Oq8TLvZKhSbJLSGkBdMYPXWD7fYdOHn8aclRV3r+SqC07rg0i0hYF2WpNnYh8nLKPia+v41/Xx4YnPOO6ZKkH/j8P2NYf+nHP+rAui7DMQqB4IIrpQom/5HOn5uN/gWwYnvHKYzmXPW+jT7JgvDb8AzPMSyBp0j1mGabHzmSVVY3KBw65QBnN68xvj0gJknmTcwZv2TMd71dII52gKOaiqYAkVzReGbb8D1BjMBTcTXsiVTydzr7YRdv/J8TWdlOViaS7J7bwXhtM+c9stvzdhR3qYSrlNZA6IyPZyAdJWpJa7wNu/1MzxfNIeawZYyqEJ+nDX7+9mbYqp+fh1gZnph49CvV9/tnnu8Dvt+9fWItyfs56n+G0xR8BWn16/x9BAqNeXo1Z+Bw3MI+yW08bwEAeBXbuB8Lj3ybtHWlSIdPx7cjUBmGEdijuvt8wZZFKeloQ2BNJkCVRTCVgUcigk5EQ08Fbtnr84rGTwKrUs6+4lbwpVFRmFjgnjWfDr6AQx3zDdesgpyYcbGVjko3j+uVh+OaPIwrWwjXwpjyMdaFCNSVyZUvLrGjBcCrOeKrziRMWwlxbJEVqA5oMNJHfyAI/gGH6v3EFcxGMzYP+m0QN2fVeDulercH0SHlUaua0rQK/5bOE1W5Ifgd2XI59ICYwbnHXMfymdbGtbTasre/X0G0PsYoL6htcUd+opw+kbFPcjoKIKV5JVTUcHZmC1LbogrsuJWoDniDBVAPHOYMcjr+MMY8gzShRldCYJufWjYKr/HNtzREr0PgeBjGZRnAGQw81CN+pXM6q4OKU4yMyU1gojcprKvTpsGWz0D5Nb3fvadhAYEUobq55oVp8ok7AhKROsCKr1xNGVHcKz4leCVxczgdUWnDb2P5CcW4JBp/NKe/pKL0eRE+Y/zcOIGkZG8YWnGd4YbN0mHzwQVOJ8ZBtOk1+n8pjmGcn2tLM/9jz1vpXIuwYPnIET/6UziK9DRRiolWL+71u/H8/4JAY8ZxIhCzyr31M+FIoMaAe3V/CdbXAS0WIHonM5gzaBFGEtm0HpvQH9enc8ya/t1jPcjeydeGE0ZQ9gc8zqfj3jXNgP9RASIwf8OGRje13j06VQzPqFzwX0uA+YNUFBToCMh3BuiB5Vn5HolY3MdiR2thNkrsH1+o7dyZrD7QhCFwViD3nupmkHLapjs9uHhGr9PSHxbT6/2bAtcTEDZAqJhtEYAPfs4AiCn9+w1T7Bs/mUBNw8yLpa9vizWOsOy/ddZYQq/sAyZ+oauA9TMWOsq2EZALUsaiJn93BjUCGMYH5wZ2ZQBG23Ns/gVIDZZvNO5aSaCBN2KoJOCvPqcKh3OyZ76djFUqb6TJ4r8iPPp2onlDoNhFUGk0YqGTB62kMIG54aoLoZBpu3uDbLKckbC3DevWiLXX2JeaQdxQFMn9/0sLhPF6WEmD9jpiWbh7VHu7874+vkzGKZTkTBEB6KfbzWF1tPJ5jV6sQXtu8NxIo6EgCNk6r3renCndeOWOhgRXLezn2VZ0NbFELp69yQN41FdFToEl2XBZbtgWY1+27KCmzGeZTUNeUgHPVlSw8ZGs0tjdHhCB8gS94i8xYq9BCtj0KwqCfkhpTdgPdQdYdUZn9+5DKdhCQHD9VT4WoWTOmyfYA3BUsIOSCdgyGJooUdHxhAPKMd0u4HV0AxdgBi8rFjY+oYvBckGwW+KbhGB9eipy56MyqmDhdxzVqGmR/ftYk7jy8V6HsMTaxWRygjXwBKtCQ3o3yzZQMbAIMK2XcyBKCMrxePlxiZY6Gx05/qVMmEMwnB6AaZjSPNfvXZLBIn7/MKfpYjWPNOhnsG7uEYjCdNlQkGYq3p6XP+Hj6Oi8geOqbvF365/XeEqFr0s+KM/1/TwQtvJb+c9411bczh38ipIR3lZ6uOOjz4OOPhb+XV/iuTzZ6WwpgM796aQ9TH/Ad6+f/7883jt0Z76sWSswzlFj62BYz0qR0f94HiP+nWd25uTW4W4/12U2v17uF0MnVDaNM8Tsd70t17dWqYU+rlSF4Oxka+vGwpF354vVuZ6/ge2G+Md6gTcnqvghnXX1v0fe3o/mYo0YvwC0gwJOI+Yc6plmuKX0LGv9lmeQn7ecd3nAI/SJNA6IgnTtV0QaPa3JSsWCDso35M8Grybm0mAWvZdyg54kFGCjzrKSr6O7pials8zIWT3DZVVdd2gzDcxo7XV/R6xdw1yOSruAUClw0BWTBekpe1m1qaQ0p9g8MWKTfq0RVUhSoh+1ntILqd/Ikv8s2bgKXODr8daaepU7D4mIBLzVIa183D9R2N94edo9IPFLsBEzNY7fY7MK1l91QnAuiYKQhaQ+LOqvjrpuS5SqKqPtlXvI+BiFfIAQYcnHeg9FMAQ94u+9Ft9UdBLAF/iCd9Mr/msUHxOWbG+fZ20psdiNtWkNSJGWwmQgUsPPwB7AD/sI6v8tcS/BiLG5cOv9q5iyRV3796gf3wAvX9j8+kBuD4eoL8plvdvQCDc//kdVBRPv/w6uZ4qHv/2ARDF+qe3AMxvl+xgLjsAawsZrG79809QVWz/+GR7UhXyERj4BAC4PF7Qf/kUq4HlPfD4t19vcmydjyp74XhS4VHl3H/1iDsc88K4fF8DpEQex/BVpneac6W/Trl5+uvbiRopCrTXnkxiKA1f/8/f8Ti6wW2vC7bTCf18xul0Mp8GAHqrGPLCURfNPvjy7RtEBr4uppsu64oV4ohazdBKnR9wm8HzZVnsPgpDcRVgyB7hyZcZkdCec0GCMciC6KkX1uTDG8oLfMnCNZA61jwIwDcmrAosZHZzA8DsyBVsie/n9Yzz6YTT+Yzz+YwXd3dY1xW8WJFZI/N6YAikd/TNWl9dts0XxvV29tjZyZLVBR5EB0/491JxbtDt4slC1XdU9F0XC6KYfnaKz9WL7WYgXULvSjFR7B33jTaayTghA8Pfd/KWWKqKrXesqyWAiyfjULNe4RvMDy0qaLoAKqB1hXpMYVkXXJbFbHoo9L9+AViwrCvGacUCgPEaGz6lT+V0OoNGR+uE1fnHUAXLgIrBzYPCHW36T/AzHYRxiBzGDgvfkorzF5cPOzVRgT4U53UxdAaxpOKVV3+OEdrSGi7D0Nesb7pr82TrFe1J2Wk4tZZCmFWdO3KYqrb/Jxz//gC6FsXvO0eqRjqzi4GAb/9XGb1t8iCUMO4tW1BAHqTi6C34r8uV68MV5QmudFTjfA6CP2iReWlYG7c2giXcAWnoZhUHXAgd9fHnjj8gRBVANtvIERt0BP/As1IxwqSJ+l+g0sp1qrbeOG/OV2T2HRT1KtwK49XjfYpAm5nqP/BOO+Xz9w8BcIlrb3x/NM1w49w0KR7Ea1OPV98+LgDO3/n+uef93mEMOrLGfOzFcEzIc/HqWGlZrTeYsagBy0dgOBR83rHiKQytUrIZifCE9TWlp5likBXoMxBiAntmwGU/SVTnrzmfRwjlyIDF/LvO1UxeiMtd8JUJjMq3KfvduAJSENk2L/TnUkai36bTd/ZshRqCeNHgZvC0GGZF5h6dgWa4Pk8zlYXQjjLrd8U0T+mN/YN0OssgBnVmUMNe7TizDlC3L7vClo5YBF8csF7f5Ik7BEcIdSUo4mUeFFR12G9PW4iqaldSVMUh0bxak8iQEH1MacPCjOgIt4v3JR1DADfkzTHhznNviMDB+RmACEafFQG7ybZFic0DJgWRBcS0ZJIb7bpTHUGDFohlnv1JyR3chKmEqq/ZkOGZ2QztcyzT+S8OuyTWN90V43CeMrMHYEqwiIPO4/lG+6acjUItMENo2N7V0PDg7xm0UjWzQozkzyJavOK/HOHc/T3+/YyzdBccp3ku1YfDeZFbFsce6Lw7pyQBOEQSRfCc5w0JNIO8aVgVJyMM/jZ4RrxnOraA5FPPv7LDPEcFp8OWtWXJLN3Gex0pEuiqUaMIOPDSjxfALTmY+gnMQBK1LPxjdQbF+IgStvuZt5i0rDMJKwy2GixSD1TmknLhWhSGLAHL1LdUFUtTRIeAGYhypwxbf+mYv4BMjwrKQD1JOeVV5zaefN3d/Nhz53we3zfGcZzXCLhZjDW+tzFM3mUJO+Ggtd8572l7mTwhwPZ1ZKdzCVKuy2p0s64mW43Z2nN1anSjD2yXDZftgm3bsPWeSWA5So5gm0+G+NqbVoMBAjksc8zJLokkeE7wDTKouqgmiP1jBvsAMUMGW5KFZ3trKiq7WT0uDr537CoOoVOO7fTPw+9ifcj7gCVlkAUziQBRr0B3+RQ6U+imHPQX8tYTYcirwCud2PTI/D2SoNJOcH2ojtF91Fn9EHoPCMtiKZnMbKBSWAAawACEBTxMZqrLIQBQlxcBOaRzInZzEs7Y/EwAZVsf64k+E/VqqyCDBfe/RQxNozkKBRw2EcMrKtypMxRtgQeIF6gq1nXFui1QBVYZ6H3BdrHkSYp3UnVY8Tar6kHZksQ7BOy5r/MOLXs6K5PalA0BQ6jk6tpw5CCE3RL66ZT/qgFN6NVYfo+KsGRBa05ECQBYdEVQhgJQ4hLfcaeht2cIvrA0Bi/sTmjfb16dEVLuSp6qJo8Ne54QRXSx9xwaMX5sdR3xgzDi+vhfa+mwvBPT8xQAq/XVDB1PobM1GBtE+Ng2q8SU0vDK9XkFICOYgThbCJ5tc7lfV1+Lnd4v9cuYBARyTH6lEZCRrELXwz6c6Y16dc+cZjp8c0tkfk+MYtoue6d7OLqvLw4a2wXFgfx7PyPlOToTdUa23fBnqCUNqVDydVOB652r3viM6lZ9JFcDp3JOvPn++1jSfVLPc36AZ+RC2DC7j4y+MqCnBZGDCmFdyZqywEfD/Ape6Xd03duD/cPf2xAp1/P6e832EkDYBla9JWKWkFhWrxc9z7mOhAvHDi9Lpvs5+p13D/smqPvmK/0uyuT8vibCVfqrCUmph+DgC0q+bbfM1ijHcavOV7/S/+qofK4OvVJjuPXuVGlRPSkJU880nYkKzZarrXRvMiKHa5XUt8rQcYtSqA5kd+9IKiCpvofyMqk/HXnKvMde/4PzWHs/g+4uT3MZPDxxhxX5/hQ2DZPJZYRMdDmLGQSPNlHRuip1dS6JBxqhwqnXVF9PzF20uzIZ4ElVQa9OUNEGZs6Rrz5Fhfd+1RpbECvWiCW8FPupBZUq+ri+8rkD+YVfR0orASLzIgYCmqLIeQnaewF69S31Un5FILoHXitIvt10fQDA6J9BfL/TGTKQnrwg1o+gYBCJtTMK2QXX/WX6RYIM6TVBP1X+T7j7y3uDrVaZCauqaG9fYvTfoPzKi2zg1aLIbhwxc9vff0X7+ZUlJmrYK+6ZKbovv3uF8eEBl7/9uvPnjQ8xGjtkfNrN0eUXmdsxnv/MkTGUg00QzOu/I3AOzHePZ8YbTNkwdQluDfTzG6Ml+QT9qKD3Yff/ZPrqz4YqZwFnBVTAC3vy6ICQoP/jV9NnRRytgVOmKqz1UusNy/s30EfF0z/+hr510E8v8PW/fsGTCLoMPC4LlsUq1cPPZX26Vyw8P1cgk0KDz5BGYq/RZiZmkwU8KdCbgj5UwOy+b/ZAsgbqJVA3qYvYmzw1VAbsqNfPz/Zt5rtpbBDd67p4BfoJp/WM83rG6snwvBAY3tLU5W4knc8f97M4vT9StOtyruWIfzJiHm0urZgnUM0mvzG/tSb/Tj9oPNs+zJgBoIW25nX28nSYP/fVkNkurSBNR0xsgftwmS0Bt3egNSgzxAHyBG9w+eW/oK/uQWRBZVHMoi2YHXw+n7A9/QKm13i5nkB/9iSPdUF7+xPGx9+gHoKNBOLm/q2IWTRidGZrkUw0EWfSv+eLHhWk6jzjsJe1oIllIOZARWF3LK1ZcmOb7UFEFZfLJX3tHW6f0MQo4eChkQSm7gONx+EZdfWKlv9zjn9bAD0nrTpsbp4xAyPzEt9UmNXntxW1HzvC6It+u5zZ8wRaCOgwWB3C3HB1/M8ZUoWQd18frDwB8I9PD7iHB3mqvgigvXkz7wdAhsK9AdYbRwVfCLhT6yn4CMVJgUcAL2kvoOMe3R+/KDwbJRQkNzOL0h3jqMfN1VIPuCjAtABalTGaNzpMVzWwXaRDcHFFpGF35HS6IX1yaXIpxsodQR/NwbjcW9WoPmpubLvPjTWJ+dH6hpQPTgZ+dXgP9Gcm6o8G0W8dO+Pn+hG3HRMA1tevoA9f8pyR5obd7ViJPtfLnBiCLyAA/fMLZ9pHUKfblLELGsedTZPO09oLoH9RMA0QN6j31xhjWNUUMToPgxKJtaNQwCb6gP9ltyUPQjn0GJP3waaozG2l8tzhrYZkOsYAAFeuRQdYFzQdaQBkEFbIcm7GrSp8X/O6MoVphF8kjNhBsmdwcxpLEUVUZpmavPWJHZBzzcYbiPw6VoP7glXwWVKCwayoMKDFAXXQuGOPMThp4pbDcwaCKlc0wVn/2t/8er5McRIoN4AjB9UrmJjmZclv/bMI5rH1wCLygIpD4CtZUJyUgKYgZV9r9kxEylZnRAQMh0kdlk2nwEyWcEU0TNdcyGTnxu/FYBKs2r8blCgi0MGz7zAQvXlMyYQAm+9QyorkEmJNPu2BUnbDz53lygD6QGDY7Q1zBrOgLc0dNTA0BpoJAuryo5tW70HxXr7PlSp7RDy79Oggdljfm3xPUxkMucPRO3UKKkQSAnzdo9o0kWBcaa0KcsDYxXcSUG9Oo61N6CsCrCKxyOLcB1UjLLcPJ0N910rne1rPMPpUeAlWfU9TFlm7gegNPqufoeZYZQ9ikGpxLgdBOJ2gyO39qDH3ZhW8MW9e9cB2FwuULuB1cUju2eqCiYyXwhV8Ykc6nPe1WJXOf6MieP/k3ZGGExzSUxTTl0j7n/nKO/ldTKgcx5CgYXFa1Zv0eFXJgAgs8+zRtlg1afOWM5EEE+fFmkRrkGXxYC1Hj6sVW+tmbHul5ISBrC9Cc1nhRqMqxvBgYcyWVt6rULUksHDezsB7/GhWFKsW3uHvb59pOldiHhavIg9UD2bG3Z0hfrQWWfgl2aLNoJyxEXcCOnT10IHHyzdsm1UD99FLNbl6Wwm4A4omLwxyVRNuWqDgVDVhLSvPi7VmBHT8lP1Qyf1EXqVql3WM4EPOE83hGpX4e+0nDdR07N4+jjIw/o4WBBYgdVtHFMqC4XB+xpcBpWHQ6tEGRM3ZYHzC5FID2RxSs4Cm/29hwlAxiLXku5QsIQMUuxFO2HX1vZiSV0vQngDZLu5EaHF5Jl6pOEqG56QBxteGr9/cy5rX0vw1uVaeQqYHNSGoR0yj/Y6k5zicWgdjqqzbdrlgWRejQ09wGSKu7y1OM4vv5xWqhLEq1j6wrIs51foFvEQfbqNLyQkL2yscO9N+IJBDUtNs3wNfByWrNsgx+7wHL6CSaB0yOR1OITvUkwNdrwndDTSh1pnQiAxBIOXTlKHaFkQSkaihmxExlnXNAHpbFktiTIQSe+fGxvPY4YEV8x0RdIvaS9zll1oyo4jLJRQ9kzl/WDEdl65HRasl8SpHXmxP6CaZiLcuDX0MKGPOhRJ0XDAuluRBZLCIcJtfFYi8DEuCqJUeoRvzTb029EaNuYUiqwznW2cFUfB2Fcm9X/Wiuf8KUR9k/vz+xoBuHocbFFt4F3SuAnyqeUiqSwPcTjKajXd3pn4YUtg19s469T1oJrdJODRVZ9IOIX+f97o+sjrJeV7w2HlN5dsxyTL5fHPnsQRT2r8Dlb9v6rpxn7DxcpGKzkmUAZec36OC871jd+p3rpsq1FwldTqMJKRMAC8MePeLXt2+6gwpJ3T3ir7/fS1F5n5S9jaJFjyn2HAKeEo4gFg7D8xn2Z09ZG96aL5D8MFJvkHncc51QsVu2+zekw5nHa7Ltd+/e3Ur7fSDW9O5e27wgpC/B4F4NZ56a7oRRKfks4AjjalVxEVlIDwpD6oW0CoIVjl75HIcNBN8fY4j4T7OI+CgP3gPbygwZNowsY6xHmlPaL5r6LURkq2eONNdnP68gEc1ILYpaZLI3uvy1NFWjfx4R1wxPWRsG4bCE+8EvK5ZPa0Bha7l/nCZPzyg5DI/EojHNgBuzsdsIkgjGA5EmyFJ2W1zPqR7ognBHVqAKCj5yPQvqYih3kRiQOoEJiObrzWBMbaLy8EplzSXVb0w3WlF1fxyOB4HHqOTPvnVy0SGidUiANQIRA2y+ZhJLRA+rBKdPShOTBB5jUBYojcC6DfnWzYuka++3C/SNogAXwRsMqG2sfWc39k/Xqnq+mtsJ0uW/Anb61/RP9n7DPmEhd5Zpef4AvnNbNPlJ3vfQeuVAAAgAElEQVSzy6+KVT+j/fktiAnnP79zehcoBF0EKg9gfg3VkZR7TIROjxkx+P1ryAfrhX4V5Pbj8aNiAWF5Zz3Q4w6JYFtY1EG6ubw9FoTFulce9aP6w/OHsWT1doOEl6JYmJJFD0SdE7usVRC9Af8MqD4YnStA9ADgjeuC5lejxhiOIGl76wG02aZmHSDpVkgFo+0TzB9ASwP9P39zu1HQtw2P/+czeu+4iPmzLioQXcAZ8LWfPoa1JyvFOaYLNy9GCToEwkcdf1EUH/i/cSispVm2qpEBi/lPH+SUE0VmecJ/+MVtvkOH8SA+Ad+Y8ZYIi8e0FmY8sVXPr0sE0U84n9YMni/LLK4BUY4nePNMhhuZEGdy1VA+qAR0rXjdqvxHF4zRk0emf9PHHz3QEXpb1c382QIkh9nFtoIPEfBKCYsCj0Ut/wnAI8xOeMsLvjDQiPFKgS8urxZQ+mxJgU1+AfMd7tqfbefqb7j8csH6/i2env4G0BuAzJcs+gC0hqcPihd/+dnG0xrAC05//ZMjFwq2ZcF4+Gw2a/DN9HGbjRW90S1O0aaudKWb1OhZ6BlIOyxOjmR5AhwdwPk9c8q3TQZWLOBlsaQS1kQXfbpsEFWsraWtBVAWvhVOn4nKKOtaWUlVdY86838Dy/kfPf69Feix1+cv9k8w9PKt+ucm7K9n+V+e99Ct3UkWTK5BoU3BkTn3B+yaHzkUJkDuj/aKH4zXN68JB1Y4R88wm4BV8YII3/7oIHA0C/YvWoXv9+8VCqxdRW4MajLeYBRxP9qtf8KPxbrr/C7hgRW4ho4D9ESgJwUeXcmtispe33vmPW7T1VRKv3vq7SPoCnTFLG4+55lDD7/Xx9PxRNorTeurl9CvDOCpsNLnn6vzNjfmqoaFaccMj2fGX5EZeRzz+OqGD6lV4brTaKigiwLDlKTas0Mwq6uCcZNrwBq2BjWQG4AJHRk/EZhECQS74hjZdUO1KExPuIyLV8bLTmA7aSMceFZt5BKbJkznLVqpPKwaMreOuRZz7tMvQHv+Gd+nIhffkwfjFA6but/RZjztV2jX2/nwDrbyHTMFo7xM2fdT7ZvZtPle7nQOKD9D+yAg4YKLQQ6U+S+KVVlXZgsaRAJUpOKGod+YDJggtAwtKANqikL0+Bl9gy+uva2PJ+CdfYkdrpUQELPq1W0Umk7A5rAbApGQEHEYQo7FXseexb54FP+WqVM3FJmmUuleeJ8n6x1qgW/LoLD+twuIIyCdd0Pv6hW68ycCj/H5GI7fQRrRMMwgnb9zGAshJhXTEekOh/oucU4ofKZIO8+2X5NX1WB7PBPArs9mzmVcfEWXQE3NrjvgFg+c+2dWjZcH3b6/H+w0N42bafhwKpzz2qwaz3+nLgJ2h355zPx37q9gAAkDXJTXCEhm76LYXzG8eO5C4MXbXCyLJx1ZUNT4KRLK3YJWsGxwJsMs8/ukzhZTXuUvYff+81znv0QGWxUyXEtFJBBNMur2BDAr2O0+atDtHnS2VySTC6FZhmGPeb3Nj3GdlJOxFq4TkpqBQwuVe809EegpRgfsaAzxBs5HaEKJV/4Swef4LjO1/d7zinj3KdtyPndOF6++bs2D+5FsdEhMLEcEytmN7NYskYKdxy6enU9L9HpfMjBNbnSLesA/0SqMv259Szh7q4gxJ4HR1oJ9BrlRR3wmvujZhoCwN8Rl9lgL5JhIoGue0LAuDdyWXC8orLJgDMv0ZrKAusPx6Zi0M9U3n19PwMt7pQPqeQ3zeMx1dD7qfE4EYPYWCFRpbCYOgGYLFxWrMtrtDacLC65bYsrkMfH8mUhBIhBqhl3JDNCY2nk3vJTja6Ujjihzl+CtYbR5tY0CI4IfR/1UIlg1XeN1boL3qp9xrOpPfq62fwNi0eTm5CdQxeibVZL5mE+nNZMqZQi2rePp6REyVowhWFZzGkTLE2ayAOxiTqYnPCXChE8GhoiB05YqCqLSAiDG5kFgkFfuKZWgggZTtuA0okLTeW/YRrkcms9PSeBO+ahUy2UrMiGSxWfyi/0bEO3kSayguI+9a7RvoAhuhbwK+daa0R9TQugGH8+EF0++g7f7gI/X672NxiGQ7u03ZED7yLUj4mzlRNx8XuG8pIHP7jgdA1g5xNK+wiL4ssKdgRsUS8qi1IcV2XpKUyMt1XvPbfcbn+/5SPl8ruLuvlU9zPit4nhm6ir1mT/OgZ4Zbw3UpI4Gt5WClGg33gjcpU1F8/uYu/w7fBjx2HCaogSp1HmJi4VacTx1zP34w0o6vn8+e+dHKlk9EbAtN76qUt5NXfB7P4JR1an9js2f54TevJ/86/O0/Pvszb7z8Zw6/5cKzdVJrLfan6n1u9TDKW2BWw/P5J6wsVXgOWAQJk+Y1AnClXoSrIVOGVJ08tBZVJznXtGvJ6CFmJhfzT34PRvg+bl+niYoBlnoNK+5FdQuFLbb1nqbdFJXuHXB7rxbQfTb7xO8WxImxWR5tE1Tl1PTKIpbUd6Aom1IpY38db84voTFZIq7uQYQdorOBLnkKeW996GD+C2Ss+Zn++sU7dT8TNOvGAxtNl/MbHLGR+TTERn2hW/QoVp9jiQgiEUVvYs/c0HwtWkJhG+bXFcJ3Y3cxJ56RehzJri5FDwhfWGVvmL9NaadIsHWEFeqDnZr63y/4Of6u3THqGbiBUX/KtcRoJR2sapB+DNb4ZHp6a4/MAC1NTJt55VvlZhXgTx8hegX8GuA8CIRPGrSfrx7WyzMMTbrHz5ceSIisPf5VSkVv+WQXxXjZ/Gg0St0esDp7WtvGyRYlbCRonl1PyH0JUcn+vDgNuknm7e/vk9eajqV5n7LZDtl0M9WNDd++QQCwO8A+bgf2wYFfyTwO0A/zmD0jx77ZOn//48pK5DvHXuijz4Riyh40ms8fvwMwiesIPD7TyD+CaJAI8FQBsYGGqapjY9b6oQM9eCkAKM7+tUFlzGA7qhvomgeFH/s5ufqrhuMIVbsAgDaffxu7ythoUCSc73ZfY/ANnkCqseWnHWa8CKUxEmFtREV9uIhCla2VwavDufxNHnhZKmWTN2Y0i5nsuB5a4vZ7MuCNZEGo+3VLX3QxhpIVVFcauimlEn9UMXlsrk9bomwNjxH43Q/otlC6vQ32ziFOmX2QtWJjroR8vo0eWrSnPObz+wtTzH9u+anBBoDP4HxhRlf4eMMCPoW6FkK1Qb9COhfFUN/xfYPSwAgKFTf2D5ndrSzNwAIdz8D6j6g/lHR3lnhUgMgA3jxl/f4+vcPOL/9CY8ffrV4gypk9Gx/GLI0EAtYTT4zDNZ9Nw87hTiEc5V7LheSv0weGb5W9fePY4yRtrQV6ZpPeWmGQjkCPdiDO9dsZGoIv6MB/0cf/3YI9+eC5/mNAq0BVihGh3PKfdJpeFQFfuz5odwzwZmOZVpIM0YcjsHv30z3lPR7xhOAz2TBcwPOu9a713dLOgmBCcsbggcEjN8eJqGSvdMdCI+E7F9+VQEevx/IO7J+qPHu3Ph1d+nV1bFhS7/xUIrnE+Z/iwEQ94sKwOFjW1Zf80tRDolAq1Ua48mCrjg7FPHZ7sWPltk8vrkDh8Lp5DepUeQYp78gvSLgc5yWuU77ke6U+Bc3IHPi/Hsovn3HGNvdLkaSsuu5S0y5vL42jJsBYOAr8PACy+uG5U0D8BL985erexGAVee6MFwBeea5dS1dJUJL4GrejSlCKbE1JrSRgl4Q8EWdoUsy5UEKQodqA7dhPVOYYR0Ybc4pBg4rDoi6zagEaQsDw4Q4K8yJTnZlKhVElmHrgnWE09HhuGRY/6S+ueBXeEWrJ66AsJF9NoAdtDAxwELo4VCKLIIWPeT3BLOrVEEwgXlO0EOd3dhDdmo4BVwwDrExuGLS3SgMlA2J4Gs1uLDPyC9+9jTsZuXMNOjUP6M4M+EVtdzLFbwN0BMAd45BxWBCLWIAIQELQflAfeF8ScWpUD0Fegh5zx52B2/heaEAevVCVF6rw3JtfWQfpMvl0ZS8sgaROSoyky8CKseC6j53FJmZrgI2MseQafWQbkYhcVRoTkMPrtwFLQAB+zvFSkCwWd8nzTlWw2x3yDczHIYaJC23WZ3VsNgY1a4RD1Sacus/MgrkUs9guiqunTJzEZxgaqDQlLV5hssCV/SomTFPRFhOJufUofLDkRpQq0ODOsPpat+LClgLTC0B4UhQl9vqhmoaLAi+RFiWvXzVpHGdZ8W+PFSZEeYGCcMtX7zQ/CTCGWyJKuQa5AbFnsKsTnYhUBEJ6vnI2dYsrCGEE2q/NPYdT0YS55AHhx3in1up1vUgesDcpXMkqg3Z6X4gHchZTRX8XikT4/Z70n9hewcRdUgc5w0AoJpBQcHUZdQflxUI/v2IwLsHszKIS7EHPblGrS95VJIwZrW5EsqTgq59jhqD1PrZtmYVnkY/fBXsjsSg1hjdIeQJnkBRkruCViJBJ/uwKzAGexKL+hpIVqbUQDxVmtkdlEHzCHIzN7TlVgDd7hMB8+YZ6hOO3oxswJxjxFb53LLl0dQZVQWDDCJdHB67iyRse9+6rad41ZMHBskZYjgaYy7TUg6UKCJzhBH8/NkmIAJ15h2lTFgx+eBBQrbEL5FhCVeb6TzkjhVlhmwdkclte3XHrFNXV4Rhmh/8/lFtmTAbnO4EprOIw/9xJgOI8/lheyCq8AFY6xPsKn6JrQqXm2WZCxlKi+z0iqlrUGtoCjBZlaA4NKs5m6wP216TL3p7vA8cTYQV0Aawlv0luagqOiEQkVOaUPCjW2Ar9PWYX80U/GAyU9/hNtuLiEoGaVv0yHY69ZUGRJwXKPoY2C4XMBN6H9h6x7It5REGSz6aYF0XLKvREbBi2y4ACBLhH3En75jJBROSsfLvcIR7MJkjEBWSLk+c2pVWp1zI/ptWGCIhNGSaYWdYJVrwmuboEefTGcu6eGuGhsaLeZkoqqDnEQ7pfH6YVAFf6uvce8/rxSEfo2IlW2sUOEjrXzhTpYgI6omrw69TwNuKtHzHmXRo+kQfkklI3NiRJATEJuuHGhZjBNG7DE+QY8jYADI7I9AaoO7sdh1Ke0RVbO8cEzvgaxu/h64cQeV9VWfo03VfpQq9O+Lzw8eHE5D85NnzYoy7i5wXFPWOaN5sp/bFvTWv8vPnjdM5n7RDMwiCqTvVIHrwb/ss6Cq/uZojFwf5aQ3ehxw5+mNUC6/SMmET6ivfRWmGjQunm5NHh4l+zt9TWVW9Tf6i5ed4xOeEXUbpjx60//W7CQG7y/bn6eHzGiz9nrizOfYkeLdZIoGGyJDQxJNzCfBAeqUdr3Aia+GS4FMxJZ7zUJdyJ4MT3hl7H02sM0LfK+u6n4jvvuSxQnQW/9BUEHbn1bGVD3QfSI/5PfL2K99nkU/HQWYQvY5/si3nzRNJCTl2GCpJ2k4EwBPSfYJ3SA6uXyeaQRBpmROiBg3enrqqOqMLvjODyDX5bDIcFD0PmDxBc+wxXxz2dQSl1cdZ5rfys7rQpkPB5NLYZlBHFTq8b28kzIIwRrRKMgtiuE0hjmShqtgufUKxh99kjh4JnZ/zFXLX/TpSCl8IwaA8SB36b52nmYCsAKiZ7ruionxEwDn2gfnGQvemmGfSuR6NQONAk3EvnG2vwuwCELzS1tdQAFrsbwVAQqmLmu6mO3ImwAsUEhAAACDKkLevbJzjM8bDF+DNS7MJBjt/sQBWi+cp0FZP0B3DdRuYfqEALw06FFsf0Ie5D4SAx398xP2f31lwTdSCpUuDbgp+/won9ZYr47PbTz/l3uJ3r0Ag1xXV29zFMtpLEgVy0t7/BgDLn946H1TQ2wcL5gHuBwUGFPrB1jk0pwoMsVujoqPH+z1biQ7MG9B+TD96xJiA6UuOfwOliYiwANj+8Rs2AMvPDtfuetH5HUH8nccHAD9/AtMblwmKvhmSI+gB2qdnlQlYGkGHokOwQPEkYgk5oWcLrBWYKD45olzMy6rNkoKctymcTqgBZC2LWkCh82IIbQ4JDnG9ZFfEYb5x09+KPwqa02u+ag+UUvCpqUMpdCZPut6h5VqCqyQae4rRyPwPCzNWYpy9ovmuLVjbgm1Zso+7JQGYHR78OJImnWXN4Lnb4OLfh7q1bRds2yX9RBz82+HerTXknBdDnWsgCZQo3dHt3lfuPDNE2p6B579Eii8EtNA5fe4eSHHyMz8nRPrUD6zYitDQcPnwK4gY558b2ntApEOko4ti9AHZntB/+WgxAQDrXwx5Yvz9N+A9QO0nMAjLz68RvgsT94TTuqIzG28iBjsq7OgKcnn8SgSbKn6FJk9uHmeg4brgjrZsrlKMz1+S/aadRGHzRBzD5A9JqYTn5sF1kxeXbZtymQinZcHT1rOwiCKZwpFOvp+AdeMoTOlegW//HMv5Hz/+7QH0W0eaXLr/9KaCm8e1AhnHvVJCvf/oQXAnsUyooX8qW+sHrtHfsY2y8qgKxGAiYwB4CeALHskEKxDOZgLhHoRvwap3AvOPHEe75HtnVkOAjhtpcrT44DurSvnf2LzpqLz15KoMYM9g/vljvvWVgvGjd6DvV58fj519dfjs1rEDFdUpVBUWRKeHl2hvKZXbPzKOGqR/7tqpdsxjb4761bqfQ/2qO+EbmWIqw6HHCWNYtVpApNKyYBChBZRrkX+meNm9F24eiKfdoMLJM/fTnNnaMzd+dESQUVzZjkBuXpTvkxBmrjgIy+6zW3RzpTAQQdOZs5/1MLbsles+c2EZL6UGI84BdVt6UbXFMx0dQtwfasbRDYjFOq4fP+jw+1TEFZhKVbxi0IVYMoU0d4C7MiE6Gw+YksC7bLl4BWb2SskGollpGmtuFXIWsInK6i6C0bv14h0DvQ/0yxN6gReybGqesKX+fOKGFn4FhIPUeV68Miyr0fQYAjXA2vyZo2HudaOTgOwhskAz+05KQ1gMYl5U0DegKaYvV5E0q6Ll/T14zpF+Mes8xGGY+hjYto5t2zIIEQ5GgiUkTEt7z4PDLTF5777veDhB8hqKYJRDwK6LoSKIQlnBaEAEWHwcQUVMtFPAxYM7kRihRLO439fdDOV4l1Bk7azqUA1qNShg+3uSWamUwjR+gejNXN8Vud9r4lUYIcfDAo80lde0qA40zjbvs9+zM/s5lJ2ukrTLyL+ZyYus3MjiWSVNTBksXTyremEzrIrJk/+k0+3AR+dzOWHo6jzv3i/2RflcoYlysHt/hAzzuUzo4OAls/LY4BR1zoVXVSIC1/BgW9e5Lm5g6G6lvQqCydo/CKBN0cj6Pmd1tUOU9d4tQzkzte2n945t69Ox4wkKkzV6kKvN4FaVGVHROueyXjOrw+Pzec/ILG/5kwGLum6qyVeDBtZ1xWld829yGg1Ziyh8cfoNHU08GWnrHb1v6Ft3OW5Q2U/bxXsKau7vm/pRcerGSNn3WyOGRH8uUegweMQMnsf7Y65r/B0JDOQOEFXFIPZKVk9quNgDJRybIaeJTIakFP7j+t2tY8q3EP0KEnfekPMt0akTeNVu/llvduRp8b5s92Eg+Vv0qYxREGDJA+4UjApdg1PultyGSEwCoodtOMOIjL+wWuaiqEGIWrm197hVYPRLrk2dhOkw8ncNmUpk0KC815dSrpBV7du+jn3iksn5MLeGFfDEQsq+poAlUjxdLgbxSF75HegL65KxsmVdoURYtw2n+3tcHh89EWe65FUNGnLI5C0yPBjL06lj/zKWhTPgzzL1nly7gzZ9RTU052R3lgr6mPqoBUXK1T4PE6Z+wWk5WbXEuvqeponq4fMalduq5HCMrndEkFujzQCVvT2rzgPxx/RtTB3bxxw6rC1M7GtJcbdrf5LzY7pJyBlRa2uDhNUF4NXwoUUbe5FEB1DMwI45Zg/7SD1JqC3Q7HNftfK6Ajul/nrlQmk7rKb90A7ic3dC0S13jzucR/jOOX9ElfdDSD0BIxymYW/sbUrfAZgBxOO3/8TDbx1X995/Nefgmi8rYDp6rkGxRSL5kpCxvdT9fsQGomd+v/X3DxyTSm7Jl0pDN+ipqOx2h+tzbt7yucftTitzF1P4zLXpq4Lp4UKK1gQi5Gg9DUQDQgzCgG9b29sCWwg2YGgSSwwXYZcHvG8/FmtY3kWPA8nJee6Vf1SWV9o5+NVCIdcZIAlLIPfx7uTy981x3taRymOu7wMUi2d/Ue7P1GOCUKwSmD1wSVST5vTG1ASv1qvHU903V1v/+p5E4c/JD3yw85yDqXE9lvpv6msxoBmFtbn0pHAwlKa9m/vNq7XFE8gFhtbWhyCQqkQIPRLChtmvSFhbXPXq7WMY/TOb/qsRLA9/AM0Ae8A3g7JVVn3DWPKcst38p6ULoMi31q707Ss9rOgxVq0eieM+msagPnIMXG9EkehLc0yoA5xH2mRXQbPr01UxaRJqQSQAA6+BNw9Q+QrwC6RPZQd75rqz6w2GODQQyQ3xHBuzVU6RWvB8J9WJcHr/U9qb3Ngh520mlN5A5BPG+A3yARAWrO9eA+pV9T6uyQ911/bA9lpqdbme1pZmAHgNegeMjw+7cdkK28mxTLe2yHO+/39XJXpszQ7FooJGM2HH9B8B6StAH7ICX8XmlZW9NZtA9QH6cdqlDKOt4TAXJISmCmojKvPS3yiq+EqaldKxb1mGtedknvZMOSI5M+Cql2XxdkYNrYVvlTJpJp6pAqsyHwRlKd/5fzwJlcueP9rBu3HgoJeQ+TkXMjt+ZWsnN5bFqviJcW4N0hjndYVkcnxzNC0bb/TArryrPiP8JXVN00cBOPqLJm2bn85sIrPPLdAatgQzZ5Jx8JVaiHGUHZlshON39oEhqJAXKti61n0e/tBsDSRqvjC1cS8tCrII+hGQ95/MZnY7RT482PVvX6F//ORToaD3LzH0wew4l7EyRg4xEkNOf3prNmHQBRTobuv4uQ1hs1O2oSBHtph7vCi7N0jE4hI5bblmLWSM20kK7NZYHCXozNP3bOtstwg02ea+AieLqXtXki1juxrmgbbv9D8neA78bwig7/TGslRlxY5orPW4U8Lj1Qn7v7/tAmkunsjEDZcQ4S4w5qne1kc14OKc6FAUmN99Pz0oJ8cxEh5hC3HLWArHX8zNtLuDMQFdv6BB8cqFUuypU1EO4t0i7Lb4Y45Diwz3qS9NJa6+bwZn8m3i2yU3IwHZs+Fg08w7HARD/MXqsDvfhisIppQud96X76m+m2fkEUG+eaX+TlEmQL1/qHigJZJkX/kDvyCZUmQgxlsfVM0d835O8Th+/hytPMP3XIjOa58779aFrs45IB1h4CsUZzzviCufJv3s3/V47aSK+Gtvnu/3m/3UDDolBb/0oPNntX6fnvca0KjAhj6Abdvy7hNy2CEwfdGSRt3Bt126wxA3gFv2vY7gTgZLZCo3UIBlgQhBxaqQu8MAjz68CldC2zF6on1AL9/bjb+dnhHKCWZl7XFPBbQyYkYPlkR3Z19LhcAV53Ti++qLr4pXOZ1Oq8OIK7i5o9Zwja76n++I4hmis4LYCd8eo8ygxY6HFYdnnR9XEBMlw+eWqZmjZQwM4gnP5XMTwtv0mWGO24Cec6SQyHuO/3h7HiiGOW1lYBsdY7NqyB4BnjHQN4MhSoOLrPqMFsvmBC9oS4OwzSMQz3VDvExIrr8rKtwWgMQDUWag63CnMyzxoy0e/LfoIwhkfTu9yZllUSuUxZy6oqmojz7QHU4Mqq4Uzx6lADxRwZTkGtjqfcO2ddvb6nuRJuxa0ESQWcikhjRbnS84dpPGfW7TFvl+hcLmpWgjqopFrU+tDO/rruqV6KF3eSDenxzvl1vGy5MY1kM8YGjZn03cIBqO8sWnxsbTHLnB6CCcSYWeAXOmTyKfHG8XvNr3dqc812V10GtUmPPkT7Ffgu6N3XjFQF2TODNZbQmWR/CEpjERAXUAWVUcPbyWpfaztioUcsjAUJRLGf+kx1h7pjRGyZoiI7SO1Bmo8ISDnJzcQ4vgmwo6kwWzVb0v+wFCWXRWoMe4mBsIav9GewcAbTC0zXtPnYaSPnOe4NZV83Fww2ldrIISG9AxE3C6Q74BDnvWsvJSfTxLa6WSE7m22W+eS/+0kBs6rA97SDuKKtLo7R2BdE56iOB5XVObKk9Q0ckLYr3XdcW6nnA6rTifTuX+rv+q73evSIolUmiiVvTecfGEnG3b0LcN3aHR+7YZOoBqOp8qBcSaxl6xDULWs5wams9ABEZlMAbUZUE4JSMphTNhqxqI7HuOvDq5FZg7CrkExRDOimaF8QNyozurqTH307WfY6a67fRd183J9Ycp5SmDgACyArxqATWYGX2inUl4gDYC5h7wAxnd/n/Uvel2HEmOJvoB5h4ktVApKbv7njvv/2pzzkxXplIryXAz4P7AYnCPoKSsyuqq63mUJCN8MTeDYccHVw7j3WIfBu+aqUdwGHKCMENE0RaFdECp9PvUqXc4R4slzPuyQwDZLAgg5ihhb2UyVYyYv+HJX+rJUJyJGioMgkyf+BQEuxk/quQGNWhzoWwQdI0b+ujO44Ft6wA2PHyThBNkbljXFXd3Lwy+fV0T4aZ5xUZCD7qDFmpQd2P0oGZzgKqAYImfWmjcAhfRq3zsd8IztkV9T6tUnutWr9CovAYM+UhhyWkI/jrlEEUgfbF+760tVq0DxvDWAZFspy7abZ/PFi+jbyX5NJzvk6bF2x0c+bPG5wKYY01cV5OD/kCJsNJU0FrgtgXFqvPanrpNOsjqPEVlOXsgPNZPBnrMmU6+FnpQjqmuy6E/SZBk8dfF0BF6elEk4MvgJ0y5bTtgJroAsW/LIy/Io/KZ43dH6viJr2n/69VHHj/1P02bpXJ1fF11IdoNNnXlHxyzKvaYTBM38Xum7X995NU3M5GVpowDPMDhvDr1rmrQPWcg/fTh8q+Ou/zT46nPPPpiJDRv+1Prrvj+61z9br/udRdc+IFTmUEAACAASURBVD98PmPvO+AYIonGszpNdknoieTBKva+6YYcwqqYSUO5gXZjmePV8vXUE1NfvvI2+xKQiy+fmZSpX9SEuhBPyQ8OsjyDw0GHkTh6zS8WpKy43CdUTjosVO6V+iKRKOIoMEycj2TiMvCynfKGtHtMymIg9S6kHjb3T6A12b5nwKs6K42G7hWBXiSUecybB5jjyXUMCDojWBno9PuqRk21/yNbZ6PH8OlQ/m76ttvIW4F2Vg9wqPNnMZS34Qn/Y5s2uoqgi8kW8gpr9aycnrq38cqYwwjGg9nfM/zNJUEv3pdDphaOcaD5GoAjBUY39JXRDcUodJBl9ar7ERX+FtAM3TDnV6JN1jxMtDbX64I21dc2PTEAyHrCU9F9Cv1QM1tJFejn0M3cduTpZ0s/OMgKJsY9hAV9+wwAOJ3u0ccAlMv7+P/cR8BtgUHIc6JgKYB1eYPxZkA+OHR6mdtICLd5kORXjQ3m+On/fsDy/h6qivaesFDYYjafprcXowFV7thnrQXqUezWyQt3vkoAzYPK9A7A72bThAZ5J8C3g1gOuTYT1WNVsP+88LF/9Ji7UfFKCUKu9ZOZLGEFnH59i8ZkPeNVrWjqw2csv76BvvW9/9bXXr2SH4QhlqwwdSpgg7VtWpjBaklYBMGjL+RMiJ5UzMRY4D4Stp7k5IUgBILytLmmqkBgNHBTr+K2IPoSKHQASDBttfhQLT5BEnwoJmvygdgbtSWBfWX7ignmt43Kc5rcjYmxEGNdVpyWFafVfDonAAszTt7i9GZd0VcrljA/OaeMckJA+PMu9LZ4Q1XX3WdCrKHLTP2ZAEft0FKYY2tSBAc8t3ryt/jcq5tTXz7wfDvNC8/890iEZ0RLLxs3kSW+LIHKx+ZrBqtVgA9veec6OH+2RAdg4H//LnivFmuSxhikWL2a3PwTbu/oKwwZhsjCBGoN2/YHGgdygqPheg/0TMBRscQdDn5DeC2MMwGfWcFqiRdCM0m88tEqQy8VY01aI3iOFxsfjSA4MWFxP9LS2HzBaui1VkSjGEPw4sUtHh+fAACndcXT+Zw6zOQt5OZWJLZM3StV3bqK/sGDy8T/yYSef+T4lwbQS17Dd887D4eC879/PLX/gGETys/xjjvrznIr/84n/LnhBMOnykjdwaSK/vFTMrQGoN2/wvbpS7wKpvuu2ACKH0/iFSa1/5K+8325/TMn/Oz22K3kTpDU4Vx/SDitAoble8/8mSn5Z23pI7WaynmHqG20oOvDwVx7Zmr9RejaaJ+Zp+P1z5/13CzVp10fWerx5bPxVbG8hPfftuAVwyuORQFqoGGVbLb3TMFgIoeYfzSh6EI+GDj3AV5ukvYtcNk86EspoZUuR6o4AzXbUKrj7/Jsc2CqO8HDUVwqT4tit7/yeW5mwbLKYeq8H/aeOipDWNcpJM25HliQqsjkmKU1qAAdAt0XC+8eRdeHd/V47rQqB6ffcH+2KbRO6WTVWoOtUpPc0GRmCDdYWy2vwO4d5/PZYYV9FAEfrw6VRaakgIARFVDDkiG2YcGccHjvIEWdYE15NgU6YLMEA+QtRXR6BmJFZpKIwjJK2ZSkgeFDVERCj82/ZsWfAlBxR/GgvO/oNg9b31IhhQDNtZFQwsYYBjHq1RmslkUZStUYtr9GN+f3tlnQT4ZadqjOwEgsGlVvsA1wt2+OkjA5QAlG5bpruWLP3DE/nJ9nQDGyW/tmMEZO77mLjgQYhn8KP69Y8RHG3kmlE9OxNXV1Tcskb7NzntoPBqFwjIsjg0XOf7jcw0jUFpGjGjSCZ4dddazgznY1MT727H9Y0oMFBK3qMKqhQ2mO3lPNe+BGZfbqFcdttWAKB0R6Zg7b5FirAEqYdM0tMA2i6TyYgYMM2CRdTcU6zp0v7H97DyhVz1hWa6vDZMp+mbLL+YrqezXDqVass0NW+wBszcu4qKyHJWtZ9FxHCW6rYlZUzudmsAMRdLIvW2s+z2bUhpMO5dr6z2DNGpjFKt59LiNru3mPequW9d70Pr8BBx8B9PgXwXMAJYju66SKK1PpTg0XIPHPySECuiOhlo2PdvFe58OT0DwDfaglRMpREaUwXp3uuHmyC7ww1aDAI9DLztOgADY1Z5nLTiCSUuBrNCDD6LVpON9DL3ANwucreDQRwEOsN5mwyQaCyfs+do7y54/5fsdKj2B/FU3lKOmDC6SuEmn5JWga+yqd8Nnu4fKm1flQ+2M3r36JgYl48C7oghjcXF6xyYrkv74OSjOQbn3bInhuMniQrVn2NcXMgEfoZj4f5ovQ+R7+epHsR4BVQvn7RmsrkzcO20kEgAH1ijo38heH72ytofcOgSEMRcIkHP2IaGCIYr29w81yAp9OMMcMYzmdcBKrJnt6+JKybcoj+5vceR2kTovDJLpuQrEaTCAx+iO1Sn2XClcoqswBhY23p5o5F7MiLNAwDIEjoE2tWr73DiZzhPShaKPDoC49SUXNCpFuiEbDW7yIt3zpfUB6T9SCTAoJB0/Y1amv+huoJlxlYI8qNRBs7uMcI3lHBmACsydS11f2n8yE0TVbZlhQR6cTPjZeBKvSGQ7nMbGn6qEw4jea2s837c/L1fneEbRNeYfMSyv7md36E1hFSugt3+M6333yj4ZVzwsdOIy3GPdzxvQV8zBsERcUV6/b3R5HWR4c6njNtao5zT1+8TrPma51oEFMpPsx0fPj+P586vP/QmHK20774eo9nZXRKDuc6i+FrgmlaDc+fOYo1zz73cXzrt9yUgjtP4jPI2iR+oZ9Fg53GZHYZV9yg1UMsmavdLOl7CnsyZo5Ti17yD/PyswdTRRhSLh4z+TJ1171B9N5dVZoHzTP5T7cM4OdVZAAxb6a8xp8dHeLHNu1Qf7YZ0lB51UvL6OoQ8jPdvo6pQ0Qek0tLrgcGuXb1TmPNjTXx0iJRri/y2GkoqiiM3t/131R5IYWmzb65Y4+XA/yKrzcvnPcmgF++zySgsYY2EQdWVQNDroMm5snlfXYt4YWs1/7qFaOfVPfkHZTX4/dvn+WXitMtD82KkSrXUyzOnHHpg4P1+RnhU/6D+m9zBvt5jvei5gw+gBHf3oNXRLgpWH0brp/CSgGq+fmKBT6Gr1/dkQgGN+QqYtNPRUZ7JpBUQXkcqraL6884dpefJccM5cCBODuv96V9YLpHESJpmj74vAEnektu1SFo/6RlUOK9s7tS34NfgcAX0IzcB3B5vRuUsE+mH5Vdl5+/tx5P3uU7YWXasH9Vt6SNYLoMLtsWeCdjDALPByF0INxprZq0qPppcZjrXGseNhbsQ1L6Hho7qMZU0IZmledXiuUYDHanPvLqNCSR22cfQygmy4YtiPIEZxOp7TdLSfT0TTHTMIGLsXt9BcDGXxOWjjw2byLF9Bky0yj9ebB/NN6wu1pwWm9wbouuFGrTD95scRpXbE2a9m0EKNFsNl9QxQ0qZqol9bWwhPVu79XtHtUSV9H8JSwz3XnJ9IcKxwmHCMSl0sqtresq/owlJGR9nqEDSlTfIX5Fz5MYsp2lm2xBOiWCbYKiIBYvYWhJ9YreXKU4v99S9h+JyzvG+j3hqaG1KX/8Yu5QngB64BEqzWotxxTL/Ia2H7/CCiw/voLxtgcyUoBiCVwkBWdCgyBhGHJwi8AfIZhTX86KBBXVbewKzRY1JUW1BpzY6k3qxdXjL7lvt8lpPkxxsBpNV9Ui1aOWvT841hwuVw/++2/+/GvrUDPXYYUSocvAbI8FYpz6bhMuvv52vsEhMC4XqGet0Y4/zKVZ387P4/cMR2M5XCT545Q9I6OwivvaYAWflkdRpkXDcXDgxzb1rE5s2oErPevcHM64ebXX/H5b7+hQdHuGePzLRiP8ya7x+vuHSjHYweXz6+9Rfwtu+9i8x3fsvyW1oQz22dK1TseoVA0igrqGLY9sd213eftztfxq/Nl8ordsJRca8zK81AUXwYProwD0C/VMJw5kxfBjYATP8xBGiU/cLTGmtso70AgrPfu5BLB9uU6xP9eIM9nrPQSZ3rwoOkdxqfp/L365LABSiCDdncOIR3K4wxdm9oSn8tuZjgtWp81gmddhiIl4FcE+VqD57B1EnPYbRiTRskCqULWE3SB8wdfZxb7uw0CsefPhSM+BHRWa5lQkTESptLE2RkNJ5zxzZXRstqhcMOCOr3sx1pVk1n0xx0TPb52DqkiDGOewKjRbTr8tGSDMG6ArNQJxZI8UOY7eFmaweJ7D9x1terEp6dRrChMxTLgd9wgMjYRAbDyTqGcHCilvnsEdOz3qskD6elIuoNBHAlDMNBh8EsKYKHYD6YAW5XjU8JoBTSvmj5iTmnM4HF3JTaCx304ZPnwoDqmYh6GIKUWBmCQ07orziLQ6Nvj/f0gwSU05606lOEQPCqaRhV0GnJCZDBBjjQQDugIQskYSAhhtYx4UqBvmym5gkRGMKh5oPFikLteQbZtDq0c89C7VWIX+s2FK2umhVAiWSQ/TWfUgVKzx92k5cqBqARTwvC0qjB/djMlN8T/GMMyMZ1nBRw3tVbEmFcSAFltbETYZua4jyTYszmrp4tJFNlfOoKNQeVMk64Rij0mT6yvH3PFmSnsdGUMyffPrEDPandM2q0IDqH/sMY7UQgNC5JEAJXJAswOk0dedUkO0xVV7cvSsK4LyCuM17ZY32tPXMgAUPyncIe6QaypumGloZ9M+RDzwlzegQ7vFagIbjDbdtDJZ8mdpJ6FbLDb8QzOIH3QTlKAO02iSh0e0GOevDeCatWpESQ8k0Zi3AomBQll1YDtbQ/OauxXC8xNORqBYiQaBC2Epa0G3SyCke0ENJ8XdBJ9way6XNHaCqJhRjYBzFFZboG9WpFv797AbiS3ZcGyrj7Psxei8R6Bk7kH9L19hoQzYe74qHLW3Nt23VCrRDX4ar8eFv7Jq0ktoUMa0AIe3eHnmdB4xeqJG+x9A81/4HpKVzOS2wKJqikiD9orGrnPPdoSBCS7IpM9RC0ZypBFZtV/j4QJjX3N6NsZgzyY3DertpXINNe5P5IHhFnzfX0P8ZzYvsWuCNoz50XQVaAKuDy2VH8XUzT/OTNwikPA8mcQM+gs1lPVdATWvDySZTT3pPHaRgxhaw+zf4f53KS9oGNmh8UTMDWDXxzAYABjBgHmiNkczkyu8E4dhMnkbRy5T9UcZMhEIQuYsztIQu9bGBBitNUShoaIOVIl+vMVWQbFcjphOz/h8Xy2ZLSlgdnmIRKVAGBzR5JutlbWE9X2QOhjE/Le9gNjwsmaKNd8KWJCk6kTXXNixkemQgWvCl0K6YjJZAaXDRlEd2QQcb0IXm0whswe40yJ8hA0E/tnOjjFK9BHtsWJNhqxfjv7Ml9rn0C1cyMrICGPCc4zbC3buoBgezZ188wlCV3a3pl0yq/1dHJHNkBoSDvIk5eC57bmgRbZ79+LFSAgDL5aVZY6QXnhaxVf+e663++xb8Ixaz0mXT5c0AwKn6E5gDrll6RzcejFL/WW+/W7duGkXYDKA402U6PCDrFnd9J8DTsnksCef3Q+t75+fF4d/8HzgPRD23c5ePsf7e8Rfz8HzmVjnbpe8Ixy0937ff+Ik2hni9XXituXMw+D8feLn3n1M3Iob3z84PAn6eG8y+uvJZFFi6TjbZO/Fv2JSLxFiPOVoaBmCCjEav4AkAVRBKAWumYxHep48tepw+2GWOia6mffn6DD9cc/JiFer+b8PimkZyk3Qk4WCBfsyDfGJY96VutIflFvMcco3roEYIfKpklThZryKU5oOd6w49ymnUmkYVNF0MSD45HI5PaPoaXAr5v8dE7zHKsOyaRj9bnTIW7DYm4WcKE19fOnHePKTuo6Q5GJ6qFPytD0DaUO668/iUpTPw5+Pobr/areRg8mwxZOOavQRA4aZxvTtg2fn+H3YvOo8ZQhoprLT/6+gW41NamgNtOlxijodQq05s8dgsXHJKI4925rJB20LJig4iGfjzQ2dWA71RHHyHR4dSS/mKuwJ+qyKiyZ+dw3jKcnrKcb7w/s6zMEY3zB9hlorwmKW3CzMZsNaHdc1gbCPfrYIPINTK/MPxIJi4U9K3Qm27jtZOs+0D9+wt2vbwECHv/7A9q7+/IO9rPadNaLnqf4Fc0gcBbeqOkJ1Ytu3Ke28UPaZIFyFXILhESmIb2ftjEUqq/Bbz9lr3ACsOreX/zS984333M7HhVrgYPs/AuOoJivBLzwMS0ERxOjbMlFZP688dsntP98h2VpwH/8Yv4ufoUhH0G4R9OGCC/XZ7S3hg5w/uBV7jLt8Y7o2V1kWfKJMvlkCdhmVw6wFyQwGwpTU0nUKrtGvG2a7aXmAfSwOyNRfYyBwZ5YnkLLBucgiZZIHzRGMJ3dfXnXebqtNCWBuL4E8/NYC7YFN+sNTjcnrOsKAWGFeTPX1rAuK35pBvP+GKhbFEH0qY9acNl4rI5oaeG6/uiQ3jHcLhZPrBZ1yvZrEa2SNGjeA//Mdm9H82R2iL/QJF0mmb11XfuJ3BIKmQWa8O3sxSTOQpnYYfZb9n4PBArpHV8a8Iuj9kEVrMDZ1Qj5aLxiWQnLfwHbb4rt4xdgO0PuBWj35o/Blone1h6KALwG1GQKv4XN21Cc3t8b3X/8BG4mJb8x8ErNzg7/RqTufnO7Oc3jfO+ZDH9BL4RSZGbHujRfGr9Xyi1rbcEt0PhMHkeC+pN2UGO8uDnh9vYGUMWyNfRIYA+sX3J0l+B1U1XeD+1Cd/zreM//xPGvh3Avx1GJtOBfOKe+p37O4/P38N6vHFOFdmXHlavv38UVkz/1pJ8dz/73qeROZ6eP1sVvhqnMaeL9JRg4hDL/ucdx3H/53RXusL1usF0euvv9GPLWb67svvz+aOkVQb/sVAzUN7ymcFwqIHdg+oZxoCrGHYDH3achOpb7lg4Hag3N+9wf3+zyXecnrd7zFWF8/XY1CP+c6XX9rX+8ulN13/+editcoL3cXyfQ6eRQC0oKGxQjdWPK1NiCaEQQsmzDoHVixvAUtIYBGgNtWQ2ulQK+2DQWc4RSXgcPWDKAQTfgW+Cu3+Hx8Wm+hytKWVUDN1cU2aMx6FSKoyst0auT9cznzyixlfrk2X0QwYpCpw6nXINX5mge8Njp/nql3RD+vFI9Uy6O4/7hlYpSPSRZcawk0EYYUHQRbNuGx8dHyFD000BjNzgFiD5k6YQFQfrAwDDYdg+g99HdJ6kZKFjaksYJ2eRBNQKGrvwwgcaAEGFQKDCeZRxZ3KpWvQ4PwroimWaF1oC1nb+JgLlnMJHciBS1zFfyqjVqYfwPg7ol9qQS9cpBdyJHUA2WCT08aeB8fkL0Ph99KkjsUD379YhgWsjHAsMacpMU0fe5OlzmvuGUYbEm01lEV7W+EPs7R2noBukoKJ9XRz1KMNsHQ+GIUJ9v/3+p5ayn+201s953Mo7qWeUa31t6GA+ArGi2jxlUL4qxYe6Z9DeH8kk09xTBDBDYvJOfXyuXKYMlHkSPvk4cfMyg7JZlBtCjH65BT02lW9xpQJHiqwNDmgdN3IGkZUYokn/Duolx+LMRBo45CqJlgmUqY1fkRmTBA/b9H20pEmoyZo0M+jedMlmJG8E8mk4OeHJFMypInxtpSbyJn5FaodDm79rFE1D6hLNmYKFlxystwO6Q7oqEWQ8I6DG68TgpTkOdyQOx7nYNA2joHWDLoMie6dUZetSPoop9JnnZ+sQejkx/428RiOewSsHs8jba4PjniKUtjhj1ABsIZmzCA1480MJZ6YF1Le8cPclaOxksIzsvCifUUKgMDBLIZtnq7IFsBTCWxRwVvrPM+Av4dguOkuo0/iM4X4KKQRjBoSNZFUTWj1wb+rbt9/dP6aI/d+xkpP9BrbkMioQ4Mt4+GYmvA+/0k7l3nG+Iow1Acr8GIRAEEi0Dgi8nxL7RNrcF1ByK3PfFZMlz7+/pFrnfgt/UfQXW3K8oNGxA7RqKnd/L96LG9Oi8DznvAzkNzeoC44Pup8kq9b0tgNgTwQemRQW+vbMWL61jnMK5iYQshLrcgzmjjZ7mQoqOnSczyEXKh5EEBpoJBRqO2QN5UVlYAnaVtVPeBq+xTWrVFpwwk9EeQgGH498wxoa+GZpF7v/WrAcgit3pC62gmWQRdFKlqJqOthvfFJAuBz3QQjQdKX5/60FPruOyB/8NA2gGnKdOYbLVK+v7BlpWd5o6r18YJDPpQbxCZPI4shYBtBc+z9maERraL8pzOj7ms/wDrUm5Oysp9ohFBUjMqRs8AGF7/HVsJw9CTv9Rtckv0o7WsMcPdrV94a961Pr14pPjAOK65GeYdPPsdVeOarsev0menmfS4ULzF9RKw+lBqBb0/t3+1JHJZ/W6n7vH/izafVKp6Nn77b6i75/7dx7qARJKJWF+Hn/ULZ8JxF6NnvIp5GDh0VkBfNQ5gQJd/aMREmZV5/wI/ojDmdc+PpzxvQeGwoXvEP/3b3v1CVc+/N5ILt4j5HOMkGgGz/OcQh/FbiJc6pn7a+JZpWr3O+9OV3goPcPrKmJPfBl6XSBS/cyh6qhJDi8sQPbqFY3kz7DVkT/n9f5ZEcDcGN1hw0kNOU/JKh+DNofLnvDv9dFNFsMR8sTb2KnpvIYkZ5XZAZ9ufogIq9TJmVMYQ73qJ3JdkZvrvAVBSyWSna7ZsUfuQ8lBgjPavLhsIJTxHuwShwkGgPF0zs/PT09Yl8X8NZ7YMT4bB5bPCuBbPodfAUt7ZTqL6zysDeOjQu+1JI/6WMpcKDQDdpm0UfQDboxBwOPf/sDdf75FFADVaVBxnS2KYkNGF34WvaDTNquZTjufRRmfTDhva6GGLMCu+lL6Wug1+O1n6IfwLNg3NbdwfGf//TMPAvBKkQiOzW2ElhLYeQMzll9/mfwi7GAQmN4kUpWKgFr4mV6B6KurV5SiZsD2x6Mne5tXq2WnK5siyk0s0KRb422GmsXM6MKGhErdkCR7R1+Gt2FbPdgKUONs8xS263B0y+7tjprzFirvnXmmivSLCc31Bp7XOq79zWwoo8vSsKxWib6s5pdY1IJ+zdv1UVtM1059a7aPm8lPSPodJVk2/vXRrUp7CIZYMD34qflDPSE/GCYIRMPsPCGAxIrKuQTJw28ETF0pfub/p7y/Jlyqr7v6gNgD5FGFrmQ+qN4aeAx8Y8Kt2yXLGwX9H4D5DRgfASasq7Xu0lWwYcNyz5Dxymq2WCHa3LaVaZ+Q8eHl/T0IBoXe//YH6O1rMDFulCDNikHf2WzjzAKI+/NAuFPgi7+X6a8uWxFIVdc2H2VLxdxr8ARdgiOIFVj96kvKWzAU0ZIMeHx6wu1pBYEgMnBzWtEfnlKnPo7jr9cu/32Of6sA+vGI7RJCPAQMkRnWpIrH3GTXpcOx+lwPtdUCRVNjygK2TCFtCEDDyAY3LeF4LxO8GipUURSLC2tvkB6Uyziq+K7ku6wrtn42B6KfQGDo6P67Q87B+8f4fe7evTHl8NOA4gFADTgonvyBN+HlcmaZzns9vmsZYMzjziCoyABFMQgDoPxNrlAAIeyrgRV3iBlZ7R2dycmjVSdyVOSgbNCiXNKdS6BHQah5FM+/m7N88ZLl4xk4L8wkfy/rWJTMq5W2uM5UjkEg++wO7XUIszmg5U2DfjRQnu4KZMOx8n8+S/ANDS+g9JAQREJU8h2vvVlZthIwMrp7BOgWc51jDWeOavyc72XzEnuMXyMF2lTsCN17zjOT9UbzjHRuitHFyi39OmW7ltHRsAC4sd3HG+D0y+0Om57RwDghICPdUUeeHeXjUibocKNsuFMRZ+BBMLr1Vg1FLqtwMtoy9+sCE5BdNfttg+DVs65U19kOB0FRtssymD4JZCbbVGT2a3iN62nEAsLBQDMg3bLi09ZpaQ0dwyCZi1LOruwoheBc99RCpvjMNA07K5wcKUp/Vml34pm05AE7HdY3VMUqt6RBvI/ueVnw8PCI0T3Jgi3wot17JFGpQHZh30MB7AE37PBisW+Z0KiBvMrVjCAGYxh8aWsgJQzq9p5B+DzvYcaiJTLFsy14J0bP6SAaiLxB9SwGkT7nrtKu93Zmi/skf9TeM1hEZBXpIKt4Tl4aToExdhVjEnD1ycu9/6bOilPoPnBef497h9K/d11MpSx9Zod+obO6GXOcGlWVhTDcYBSH+ZJtS0PJ7u2G1oGZRmsIdfmugPc+m7zNsoInvw5SiHefcoZ29zYjYMoVii9S3s2+UUSlwrzKO7IeTbxzCMX1c45mpR5FjH22o4i1dyy00Fdm8JwnLLZDU1kikt13WRrW0ykrlxMSPNL6FXMdEQaQ9aJvLsdFJh2nTK5GS/mXFdI+7hYODmNSnhAoiRQAnZn20YudVL3Hs1WVa4wNDWDJMUQABVH5XUhKoOCFErEkrNgYCzMlZOAMTju9KjDYn6q6C8wxm+EaFGF7baZoMAXcessgQfRMH8PREeZy21x6ooGIglmxLAVhwQOGRo+4dPBpQcEoY42bi8wsebtmBtdWr9iOnuqa84OJJF70nUrFYSwzGNQI2hqWIvNigCn2HF6/rYF+YLRhLSeMHgyN5gnbOPu8LDbO1QxBhfef7t2RDVwWh0RRhYwObZyyEUQgNuDDRgRtjFUbVBp0WUBQ9M52f6c7DJlOHp/L6dCaG5hg65Rcr+jKMwnPtanQt468QCttxV409BtJeRn7y5JmFA4fCIEoI/qoJ7y2itFFSWAAS3FYF17va7Y4be+OJDiXFyIAl7l17qhkVREDAywMZcWCBR0d9Ew7kMnbfS6JXBeK72m+t9Ny7BPOyoNAZnBdZ2GTH6JZGZ+8tblNhQOJiqCLtU7ZzhtkYeiiu8QhqxIbCLjzZWkQJdCpGb3JlHGhS1Y7MNGbivMidQs5pEFHUi0Fny004vJn+p7IEGhKtUVz6PPgqSKm+2HA1sPnUAHwsjhSokBM6wAAIABJREFUSpBpSYCKpU/dGKGyON3D+fkkfPMXK2bgiuq3xuMdXp/JZNUYw/d6qaBIZ/+e2cXctWUF+gYFY/SB0+0tdAjyFkS2N0RwWlYEmhmxpl2iUSF47SB/mUKJqQ/F1+WtYr2SB9C8T9Bu6B3xrgzNdiIi4pXo7thHswQMVYczLuPK6XCbaacTFQX78DrxW+hGz7x5ZWH7zw/8/9nD9cWpJ/3UVXGp65vqkL1hX1yZgyN9HE7Y2exwmoyvI8gRAOCOfBNjqFXZiu/MFc3bRmZ47NcIguhuvJNe7HrbJ9UWP5x+8beE3ZY25dyfGajYXYk5H1eO+fFxnWLAevhonqe53yPdhEDkuqNfNnWnGTwH7PdGahCobIFMVkO9YZ/HGmSJMc42CDYgQ+qa/PXq5F2bgwv62V967bzqs6n3mgGh8lB1S37HwrT81HxYXnp4enFDYJ6hc588s6YXR/IhSh4RSQz7AEVuWqPLUhaf33pCbCBPhJyg0BHC9uJA1ZBcxzo/BEX1ie58wKl7afLH0L+G4SybGiWG1Ea7eQ0GbDql2cMeLJeCJAirPje9KWc295EEpLF6ULvQ1LZtZg830zcUmi3+hge9yfWkIRZYg4dA2tKyeCSS00icE6XAt9mmtNWtuACpmMePyddS/iTt2Nxxa1bR73uqebL4eHyC3N0BfYCX/UbJsJoErdvnzQNAoobG05YpbMQRBtrSIN3eq7G9R9UARb6i8etEGNw+fTUZR1M3zHcAML4ooJ8AAKdf3gBkPq7tFVwmL4musLaG3qd/wQJA6jDKwBBLFD69fYPz3/4Av30NFqPDMcSr3t334VMSic8VdWxn30By7VU/g/AKAKH//tl0xff3KcJCzw2bjGCV+TIkeVfMgPr9jZaoBNxtf0UFfKy9+RKB1woom7n78LOi9zk+8j3Z7V+9FEf6gmJB+G4nTikB4LfAw98+ggG8/l//me9HTCBhgJFzYP6CaRsQEfD2FeTDV/OzhOk9AKEpNwYsOVIC3ebKK8X+tr735tMYbQGLIrrLD7sD+hAsrWEVtdZojmK2LIu9k5UTY7SOPhpaX9Baz5ZpFdWCVTGUpy6N5gUFmG226Ci6p6agIDSnZ2JGawuW1SrQl3W1ILpDy58B3KmtRWsN1CbaEQV/Dv7uC6EIRA5vxdaHI1j6v9GTH44hGUAf0ET3CmGlcDQAlDiCkFWgq0egUhEu4o1Cq3beF9/l5vGfpLm3p50Tl1P6x5hnsnU4CZfWMFpLxDJVBfg11re/GSJl45xf/diwLgObCga/AWvH+P0T5J0FyBuzo4y4z04GCOqIBcDT//0AgWIRAYixvH+D8fErTu9/ARGjyx8YHz3RCoohC1YZltQBMgyzSECGFZUIm78jaCYVUOeJIXO6mC89khxVZ9xs6wPLQujnbdrJjNk6yOf24eEJgOKmtAU02TzpuuosyUJ+pJP8JE8KNTx9h/+i498mgE5XDMHMhQxFGToVMdUk9LzHd9bmqEyGs1O8pwUNwiATWo3CKYnMztm4J3RrCNDY0jMzba9Qzn/7jRw22n58/vM4bpgTcuiAfBTgPYBSBcIuHBcyZ23tB7w0M7SZXmLgAYCFozeZ5C2pnMRVU7BVp8R+3i4JNjdLaM37qy7O//sOSia4f7Zern09JTSmUKQf1IPo3x9mrT4nIAOnl0b/8++3m89yNuMF+BUBX19geECccIf1vjnztkqIcPoQNdy8vcX2x4YG9gzZy0OdyAJ+o+EV2suG/vVbgQ3/+SNNDiKAnmCddQDFk4/5FkRPAL0AoBB69M84aR9Q4JX1oM6eMd80lnP2mvXJGeZ9g3Q1pWeY4jJE0EbHtjRw62iNsbIYNHHbzFhpBG4PYF4BIgxVbGNY9iOzVdw0AmRgDDeIHGozd4W6MSWmuG0qCZ+9ed/Hmf0eQXmGpdGFMaXJLxqRC5ZJE+RrVeMZIlGBb8rIFII/EjqUP0KfCAi9MOrDMW6V0HPDW/VT5FqHQ/3g2CEAnoEGD6T/fYeP5UzgO8ubC2csiLKKjFzJiop5uB4Qa9V7Bz092TxJx3k94WY7WdXZ2tDPHdv5nIYDvMIrnY7qffTIjKEIgdr8KVSjKl/2a0YAtYbOzZTUhTEcGjmDgzVo7RnGRM36CwGgMHTTCHU6U4OB1oFUakQ7rO8yQKReretdMYdYlX1jNF6wtKATr7J0CFkdgjPsvcLgWE8ntLZAxCpoxxgJ5d7T6Yap0BuhAx6YMLyfgDzT3TyF86E6cHY/916frK4KZf2SXpCKGQEJR1uNabutBYusejiQA8xYNPox2ZRjcB5bx0a+b+J1dfof5oiiijrGdmSpYdg5vYRBEgEu4xMTJmtuWH9gka0BBcZkyrs5kDhP0ag4b1ZlGU4To0UL1K7rinVdcDotWE4nLGyBFGpmeC+t4bSak0d8HuGw4xJ953yIbfF+42q0IG7IkDtOFDqrKV1xD4NFY7KIypwqRqlADVjhqdD7mqWgCP3PZAkxrErRCMl3MTud2r5oLapQp4yJwNeEG7Z1853r8Z2D5K4JI2oOk/V0wvJ4BtEjej9j6yMzuyN5YYyRVRaAZH+y5uds2wZ6IoxBIJptDnI0antdoeBGaM0g2HvvabAHzHucH0H1mlEeTpnQa+MZoQcTOYzlEIg8QZ+ekv6yf/q6GA1QZOwLRgS3ZcoYW3POTO+lNTAv9je3HFvxM3lFuu8VnskVzJb1rmINPc4wmEmjQ6MPJsLp5gbrumIbxtO28+atKRQGtRfoK54QQ+EYGOgd7kC0+VjX1XTn2xtPtjLHwbevX7Gdz55sG3wtuZexyBmlczrm5IlwOgXNse9xLZA9mqeOeWRANJmOhOxyfoZIllAMElAXiHSvegCi4srEoDuLwxEcSV3Z6246kqFA6x2NlxyCJZi0MM3MebLpHKLbTdwYDGsfwspQEQuiu93b0e2ZIhO1p2wBBUBN99NQvNXh+LdqZs7WFaFXmFPYqg2WtoCXZi1PPPMe3tpkjG4VAO6UBpByTLrReD9voGb3MzY58O3TZwOtACBsFdHdewRSU4eWjYrXkBkzmGCJX7NKIVA10r5ry/VXn58cftMcP7kcp8VkwbKuOC2nlGG9D1Cf1SO271q2/OCl9Pr2hEIk+dWEUIM6lNDjoFZNtDRk5ddx2D4PIQM5bw5MeYmZvJ4rrjk/+da7bahTVxyWLHJ+fHC+YvQ3XGdJGhOTIzRmtWRAUaZDcf/y80+E3j1pkes5TqXppEy+5+/n0P6R/Eaq1qZAeNoHXt0vsU+gifQRLZfCetlzoytzfuUT06/sGw6aAXK8aV9gzvvOORl3zb9zZ+Z514508PvflmxmcJMGSMMRjzP9LmJEjkxGnilc25bsAuHHZxEMLtTHVBM8iQsSRL0miFzV7YfdbrTx6NwTF7NLEWCilA8GlzmvVVbrwYfou+mIV6qgBoiEz0t8b9vqhI4dQXNgrts8f+rk85rjWEsAsLz7ZQB2r8/Xz8qF5Z3NRGG29jANsIQucnQtMJZFQdQsedDnq3eCI6gahLvSRJLwFh+m1wA9gn+YNLxPOj2+w6QVBRLu/pKtXuNYV964nDcDVvtrd/OVbEdR4nBum9S7+1zLnPPdrBeY8+NQNP+4/g42K+FjgtPh9K3uikBiLQuUCEnYGA06oqBFPbDtT9DQYeo4GAE1yyBAh+1hqCE7yaQ5Q+gIoraNEiZSvEPoT+nLVACOGiTeiiQCBTEl4VdTJQwzdUxf0qmDxJ4Jncl0JLvWqtVD/43v3I8Ea6XWZYCpzbZpfu8RLQpIPUELOD+e0UXRmu/jADKMcQigGFl1S2BPmvIkSADqyQDELWVSUlb6jwzOhzmQcmICZ0DS4HzNv6A3J/T+iGW5tWKK0FkyGGyzLireQmYmX4qIwwIzKCrpnb5HH/YOah6n5WbB0+OWtNk/KfC6oyuwffqC4YOLBLqk6CR2AdxPe94+gvklltYAuoPiK4a8ND+/Cs49EnlgLTcx074VptcFhL/6XGyqWN+9dllo9lyq8lr8d7vq+iDS6geZ+1f1M5Zf7zHGJ6h+AtH9bh8yE57+2wLK7f09+m+fsLx/Y8ntB99HLjUTgNdo7xX9t0+ms/selrJHYg8RrC95jDbmIc6JAPu1uMn3jpqk9EKNz61Qrz5X8DsG4zXw4Qv4LaHxK1egPoUiZXqEepJ88/aMkSQeSGESgV6FjoGhRlfwAiwmWEFNqfIf3i4k3nF2i507JmkBJk+6+3q5MXpvWNiQkBYY7wFF0q3Z3QwLnq+B6CeMRdSLdaIlmiKC0l3N9ui9JxpGg0LXxfapmo+khe6Zsg0IT1crdvbaFtzd3eLu9hY3pxucTiesNyesq+n9AsIq4m1Rwhey4UkGmIAmZptzbeEH89mIAL13PG5nPJ2f8PD4iDE6Rpfk8sP1a9Fpt2sgUcH8WAqYKKjY6j77kfTcEcl1ngyuMd9m30XpViAH2LdeXe6oY0HsMdeBKOfWO4iApcTLbvTkvpJh1fS9Y/QBkBos/n816B8N7fMCONz6ogvw8Ijb169w1o+Q0W3MFQna/QQ6rHiqtQV3//UeOgbk90/g929ARDjzA06e8DD0P9G2z9jGhqetg5+eAFKsYzO68Pe+AfBEhOb+PGgphHMoR9EZuB8aPI/cXgOghgbBzO5bIdze3uDh8cl9ZKa3jkSFJQwZSX+hawjgSRBaeL4e1GIt/7/KQdKmOjCWeQedunNu3H/R8W8TQAfC2JhV0CFQUgnQKYaqAQcAUMUdCI/xwfMrVB/oe0ytfyOAdTTIWIxBA8msYpulo5kwHa0aLNHPn7rmVAL9fZ5b6xOA9f41Hj993n3+9f98NcZwT6YQjCUryRozhjtaNlKcP33B6f07TAMLEHqwEcRcKbCqIlWWaXEdbCrd/6zTqqd0fMTrcb1Y/Xn1fVM669Qvjv/fTZXdsdMAsIFuDTICmzt9b2dGOBES3t2urQp8DMkdpLfXV+BoAKcR8coNty/2t8EsaXGS/OwuvoO5+h/AeInl3mid7xkNrwyuhTgVrlBwt49f0F6/dKczoPQNrHcAPeyerlCnU3ddOAzt+nqFYgC8I8syL8ffKOc11O5wNhvDfEjGaVNm0B1Cjz5vDOAMwg0AC1qGUiEy0D8Pm1suDkWEcJxrN9zSbL7ztNugAk6aG6O3M0YbWLih6WKVTm3BgGaQSVQgw4INzeEQxRc8elOb1JlVLQoTNJs8oalaBqJY5a6O2efFxm69poXMGm40K4oAC54f931dBw7lgMwUlByPT7wHUFV9xx6lBgWtm1FglZn+HsVIsPtK7ouoMB0idj77M3d8wITpdBBdHrkL6t7N93XlC5eFdXbedHTU8YcTmUNpxOVeDtjh3juYGrbmvVvUqhF737I/WATQQeF6maZCFKhTMhI3nqVPh8a02oAxIMwYbUCkQRqDxzDnfAvnaVS9aVbNyRi+a3gaYDAlZ7ilnA4xEFSGV/ZKCRoTlC3JyxyoAzRsfHHv0TdkL2mJKntxZ23zCuQGLEDv3h9220xWiMJSDQtXCUeMlvVq8ECPGlqEYdrm3IXssemfSRnfPQr/DV4zicv4Ci2EcR4GJdxHcTjFdTC5zYVmff1n9WRULdgAs9eozxnzdCIY7K+k0ZJOckzZFmMN5/LUA+x9Ew5dnd7CgR7JIlcYsnqVnoq4YzV2k2Vgh6Ks7LTdIsgtfmPb3xH0PJ1OuLk9Yb25wbos1mOaLLO7tYa1MYZGVaW40uxBNBrpWM49GAgymqLej7BaKH/A3zWWyZaMHMHO+bQJP5+f6lUMbuzyQjxJCVFdW1wJoYuBLEjGFjBbWlSRzypwEg/WMoFLdSiVJ+7WA4Aq5/ek5tgGzChaeoNIA5NBi0cVZwSrpxPF9bbFkxg8gZNby+qrGhjKCuCYRk8YjUSDSl/m3DK6i2fPYK6PVWNfkEPJW1UFK6NJc74XyTcz8L9633RQCjiv2Bno0iEjaMb2vmV3L1hgwX2ww0j7e6/rmhnR8OCqIODuTM6R6wJsDbQxXOFWtTkfvUNVsaxrkhhir8GhyYbxUVVzWAZsW1TdCJnOD5GJ2ODzy54sEolIfbPWF4Yt30A+H7MaJYKBJalXHZqOnH4oqpU09XE+UJ+9+wz+lk+T09nuy1pZpDJONj/iNGqOjJEVVKKeeAWkI1S8klogJXgee2sG00QUo0nCo4ecFrWAfF7r/LBpzIXNqThMX1SeDA/+N7a2O6zkTpIryQY5tzkBF4psJCexQ19bUM3mbT0taLx4QNi/V0FbbyEK9D7A5w3EY/Y2DYexmg6p3ZMPvJc7wWTHUHOKgKzCfQwLCAm7PCdki5h4l12SGZAVcqYXC6KPHCh6QQc9ReWl08tOpuaDkjfE2tk9LHllXdf9OIRA3XVIhxXlxjZXtOeGERgLJy8wv3dfZvJ4hgdYeI4znbFl/VKuBs0Xu8BE97S8kTQ13zHvFWNVGFQsAe3mBPEWTAC5Xmj8YF1a4aVImhHvXSsBzx8+iZR9MVYPcMJ1r4oMUNYs3s8cf/W70AOmnktO24tOO4VVoWx7g0kwXGYJkckxdwdCvYJHi8w47pH45aCr1+80FrLSHZDvMN9xakP5ef6j/c2vHGlPFhqOQFPQ6/5sJAoREYFTF2BolrRf0adiL8y3MDvyMBfT0XfQJ1Nxiaqe/fypiSd/9nUdN+YoKufZ94SGHJcJmWo2vvdrZcIQBrO3tdEI/CNZf6rA9Y11/sxAeujkOqXIPP/y958LnufblT+n/yJ0jbAJDEHHAn+kBKIBkQVEiuaBEtOBLMHZctKjYtns8OiuMN8FQLS+Tr06WbLplcHvLkdb5uPw5WGdnz2unLefouOXcU74DUvSGGEXMK83uwygXzzoJwZne1sRz/G/RcFLwxgTGSCZkeqcuRBDKGl/meFSnhj30EhKdL5SfCYEJKoGBCb/nc5JCUO94WHY5DnmQr9E2RJI1QqfRDwhrIvDd/tja0JgDi+C5vbdcFugBj2hFjgK9J7QocS/syC82QMEwja6BUqa+W2G+P18noaO1He/fv1m7wAFaIEO2/MiVvSRSYxq89BohbXQgld8hp0cfMEzjMiC5TZLbreJ2csSssiREVWG+9MI0m0sUYTV2AJVMgZ4WXLtoZ5Dj5gixUw6LOTjNGOoeQQdwOiCdmLoUIxzN7rrX0F8h/7pq7mgPn7BQLK4SfAUVbFzT6wA5ItiuX8Jka8Y4wtArwx+fQDQr1B9mT4l8aBSi0IAx/QOH35rjK133Pz61u7/9rUnQ1AWtcytN/UC1Uh+Dl5ie8fW7zOAl0ayTBi/AYJPuY/4/Weovva9ZnO2vHtt24sY669v8Pi3P1CP2/e/+DzbiMJ2EQDt3WuM3y2O0N69BuML5MPkf1nC4dX17PuwxXxXxfFw7HShw0FkMNMNBEton7wtntl/VxB9trjFHwqlzwhfX6LRBgG5rHv82wfc/voWxMhEbVVBtEMDu65KmnxRGf7dfqwRXLQkb3jWp78bZhxDnEsNmC7IwxNftKG5Lh+Y+ApgEc2k+dUMDAtCN0aDYpUl5yF4kIjZsVvveGqb+zKHbd8gJ2kADegwZDFQ6NaRUOKV1MxYm8G1n04n3JxusJwsYThscPWiNg1dRASb27FDBobvr0WGt8ngXEHzSxpEex8btqhCH8PRAk0njoS+EXr00EQ6YyKQ0PRphZFb1t16l7t9jVkFnzKg6JpVnocYD/162giufyT8+5RdkVRL5Im6asnK2+Y+ZCi2/jv0A3D6D38/tsTW9hbQvxl5NVqgTKC3ZnsQKVT+ANE9AukkkD3XZbFYCA2st7cY/48l6wOE7nG907qaS2xdocwYxFhlYBsNTYcVVYrzahDuYDqjgvHgepKplZTFgcOqtBCTF8lOFPRInO0yzr3jRlbrk+76eJB88GNxHY8irhQZjnUz1d/p8uOgq3ow5rm+SJdq2BUd9l91/FsF0J87VHU3p8fjVgkPUHyD7gO5f8+z4AoBpjE6lXVbuO/YhYdxAecfnwbAe3Z48LySRxik8umoQNtfp7dvTPn7+GkHoRsC/s8eP3o1+skK1Avyzk1UvqmNTg9DfW4c30MZuHqkRnf5jO895/KcK5YzRYCycoew3C7vYv+9MNn7yZy3RIr1NbvwEZw/fQETYXn9AsSWiWVB7DBErdL7imk0BQMm3cRxrVr9Z4+fmfKdMAMgsEr0GJGqQr88f31UKv5oPcIhIAosegKkQxx6EWEgad27nvDgAdeZyTr3tsFkeS6zFpqgUJbneVaVoPMe2AsBduNFSS34H9/tIB+nIUI+bnvYzLKu63mc5589yD2aiqlHhoIcpBpwMI0B1T4VFN2v6V99aP6fyv/hv2kiKKQypFM5YkcIWdYVp/UGNzcn3Nzd4mY9YT2d8EQEVYcm3VVhhPN1BkCJ6pPtEM+uuzZqgtEeRveMcsaiYcgwqDUsixutbpSRJ0eYcTQVObhhbHFQBom4kj7DCApARTwgFnPhvepG0J/A4iKSxt1UJK2XqAWjIpBY+ZZ9ZkE/TNrcHb4AcePri3n54bOKzv6zKRp8Uapc2J3uu0JD6fNz8y7qRiHv6GbXiLXcMt8ltqjzWKU5bgoUBL8oHeSHm1FWL2necJ5Ljq7g6wxkQH8mkIQxZk5WJUUXq+yLam8mgWJBw3RgG0lpap4WFLAg8rIYjNd6WrGuq2W3Lov3mLbnzgo/3Y8lHAwRTGBGFEjPfHY3WJM+9ktHztOGJwOR+vsU5UacpsirrMLR5ZOzq/YfDIP78s9UBB0j31vYE5ZsyqAww4EGwXOVp1NKoqqhvE04AlXS4I9x2Lu50U1R6bvvHcW+tqoB1YiEbKvEEo47ckNzCoKgGXIHAQA0d84UCNlJwWn8CWBJUDr5Zj0HiKAipaEf9NmaIWpEVfIorR5EdNIL1AOlxp2GG2dGz5w0zkxYeDGUjua9qDNAMANKoROB3OnSFKStKr7mCE9dVusEOP1NRI/gNxlMjZ7xY2TLlIDrpNQj2OEN532PcgFF5jcidN8nVk1Y6FVdjoW8cpqp7CfvreU8/yL3M6LydvY197ed7197NqollJAwhAfYA9XEHpgm8Uooa12CYtOYU1CzEj3mKJxRx1ZOoVvZu+35ZICg2NA53znlbwpak+HafA+ObkGjGANMpgVrCZkv5IEZLpN5PAgZhCWHAd8lZ/o1y+mEMZz3ECzpRtg9wz7fPuaxbal/tHUFWLD1YY4ShQURMKzNlmruNxsOTbnxk9pUBHWEJBNI93R/FI7Xfi/IJ3BkhHQ+0e78cMKq68HqSEjQPS924gWAXaUe4mfclY76hf9d6R77OYlWGTHC59b22lTsIPLLHErvzrsjaW4/zjRDLbKQ/I9AnvhaeIBv0kgIma+hl+ta1Q0FiL+z7nmu8y6bGBACqtH5ASxozkoYBA9A2rkN7gf2MiH2e8xH6PFhu3naHcehPuPsiHWs735xd9UMnAU/Dfl41Ql/VY/c3+vZmTw+nJ7/andUHvyz9/47j6T/8p6T4kPuOz+lItuV3IaIBAD/kooteXyh/UNwIOR/7jFVj/3vV0+040gTJmM0968WfnTksZd3+yuO3aT95Dc/OC62ml77+NkLLp77zEB+NL7r39Mx1vTjI+UJXA+kbO0DLYnMAHb6GxXi0GfmIGjbg+a0Oz2tj+yvG4f6NQTTz8kD10p2l3iOQQ1HLeIMzCFtAP88bHEtwXX/UohgYSXFQuy9zC2Bri2caqOmUWSMpFj2ec7AQKA2hs+K1IL3URxE3ZIKyJGtQJQtWfL9Xa+NXOapc80fO3nEDFK717JEEMWWSHKu9/rCfJbxrYNnen6XvI6zqAMd2M7dEmYUePj2BxTA+Pwt79JxeVyj50DrtjlzFE+ydbeAMtxO+wrmV0huqfOtku/EpiBD9YqDBsGdYz6OKUvzN9ebj6Olch7hi59r9LO8s0nuvyn6b4r2zvUogtsLhPHbJ/Cvb0znADmIuB0iHwF6bahQvtegpkMrE/DeA/DMUNyD3wMinzCyR7pZxLGijJnnrrAxvCii6oGAO/0x7PsDWb9zxmzuWFSho2TKOYkEp3h2JBds2wcQEfrfPmL59Q0Uw+na1pGjJdEvr6B/fLF97w8UACcFHqkWQMaY1IPktjrxvTd9KDxyEouoOuIaABrJDwRqdpcH9EUXtB4oWI6ktja3kSeqpqghyS3bBjo3q0LvA1vv4O0MQgcJMAY5GqXPJlU90fuZlzZNiXDnSYh9jBkIB/AggvshaOolUkzYPCGaSNCHADTAPP3EI1HCMOVwWd34/+Sl3i4M7v9wG8BTHo0Xh3jPsU3KCCTdC1tA/Vpy/q+YY1F4Et4AdDFUFGDaQeGjiSKHQ4Ky2YuLId22BlXBst5D3390ArrH0M+goZYA1AfOvUPHQB8L5APAb80vJX8w+K0CTFjIknVFGcu6AArc3NwCOsBsPhJV4OV//orWluRHDJrj87G/oAamZq2mB3uSWCTOI2mrFl4kj/QVmvkZVRNwxI1AArLqIYSfRzxBpIvkXE2xc7QC/trj79a3/geOf/sAutmFVRO4PB7DkQHghTvUv/1wym3nhoKUhzMIcUeCRMamKzpTAmg9fX6Rzi4TJu0nV/6LC6h455Zk8wWK1xj4nDDU9YhMpBfv3mKyoGtKqYskdxKsNEXKziwNZuIXV0Q00jXnSDNzq2poVTzFr+X7eD/XzkIRjQdZzppt0PWlw0V+EyhOkAfLvLTeIgr5JiBiLC84l2NnVLnC2tQc7jocIsnHo59h1eWUJ8/x1z9TGDszzh5DGhrk7pLj77EipgAh+5tvn6eC1b8KJqSgMcLz52/pdBifv4Lvrb/9em+wiP3T7IUusEwkxgsIvuH0+hXkm2J5ZVXrjZdM5Jg0UQXfdxhUBljmedfOrQrHvOcjGm7Q7hevpg24QvqbAAAgAElEQVRBGizXFVqU7MMyn7X/lrpwZIdYbg7xJ55xFdWICecWQt4rdUe+B4HUgwPFQRhJClZ9gmnAWa0juqrXY9s/L4i3SoEyXoPzLBX6Mcd6ApFCsE16VQV0NVA62XZ8BQEvSlNx+ilWEgsUfleo8zOvvIL3nBKYwu2BlNvbBd8eJDM0bYUaZirkM4/TPb1/d1xU/sgqVP+kklkJtlw7LMDHCZccGZc3NwZZhCFmzHbJzPEKSVsVqqRBZ+7pFCZTq8kDjfkOgNEUA+gKWhYoi/XR8iCTKR92PyvmmYgSFaXWXoOySi3gPK0HGnJ8CsxMafOqmZHBbLSsgt5dsXFINpBd0+AOOCCd1DHhVoFLUO8HNBL3iFyx3ZkRZm7IM1QYU4kQlHXhv3MUvm1iPp4d30/C2Tke4lF+ZsD3kRtFtVqOigPSmUSZC3cA9Jjvqg1MLrVHHfHBRnACDllNlskLTISHmEtO2PZp/MR9IllEfV/sFUbjR03UM3d9zoIuS6CKiMAtYNlXrKcVp/WE9bRiOZ0Smtr6nFe6djplq3gTtoA2mKbeE/25gxL83UInCkcKwY3QWMRwoLsD3Bz9UX023zGMBglJS0geEMMchUmoqlUpDEeeYAJr2yGbQBXW3i6CpTIDhQCaWq9tRaA/JCHtMtVzjZSsasYNFE1jwpNQok+qI53omAH7OM+eQ+moUq/2N75B7twiEFlfbtWRtDyZaOVhXuXrcyYq5T6+LQ98dFd5iTUr1iMhoPcBZuvdbokApmNFj7PoF5lcgTxIzB5IZbYA+sLgtnqGfPN1WsyAddQBIrLKZAndYC9QIsiro0P6Zv9Gzx0iY+SeIpoZ18yMhRhn7SnbAYX0zbrbrSuGkCUthaN1TtCk29yncFjrhiae/FienYFBp+/Uryovq2vh+4pd59nJO9eRYtwUDMEZezh05+6x60WtgkyUwGqtb5QZPMypaL3qJlJItVtqtVM4m6/V7KnzXA2c7MLfRKejKirBjeWqByjrnvJ2DyujCWNspqexOM8Rdk5g2fvMDFZLCIDvP0LQUEwWsgrd0AbYnVpscI5s6AMghugAxLP5acrG2NvXjvg0qvRN5Eiu+WX1pt0vKgzs2mr3hCyY94/Mfqj4HJj/NnltrkPoncdnlmRzpytEO6WyJlVOIvST4GsqBhsNTyqloFVOnSD1jKKzho6ROmEkdQGY/esPOh2Rzz0QyT+KGUAsJyJpNfZB6mxzn0aFcvDyQJhpjgndluaJUPYsGQNh7yNJmmZlJQrNzhVzs0gR+zGclZUX1fOTN1DRdQ9TER9xrCJ5gqvmVFnFugICBotAm9tDTlfKPNFC4p6+p/fHgX+EE/Jy4uc7PHdoHWDVoGgGQesjD7c70vXOn3LgdRevQDCdlIu95WujdI2DlfcKOimLUYc4r9s/f8d7nWZmxfzU3qp+c1DqAJA5kv3Z5OMGBc93PSBd30E0SR2+X0piyrUp0knXuySmf9pB5SftP76yEKlfov70Ki6dfBKuNyWNacz78bmXo0h6VMaRtn/4Ks/MFyGqGePez93k+vcxrhjNMbEC9fP8/XDKX7WWBEi3JLb247PhRDpnPBZCTZ8N29KmR7J9lpEvpf5hH/rfU9qkLjTRAeoclDmT0NMJoIngBtcvUhVD0ItksMX8PBpptfnc9P/4RbFvwlcUcO0GuhPIbqaHb5vpytbmiHbjUfdDQIFt63g6n3Mcpu8A0I71tOQr59h87ro6Kl20aCGCsqIti9s01vIFoZ8Zk8h5VsWsFAyeJwNgb22IYP85wxARtILSYssWtnDgJ7g9oRZsUSDfPZLkTKYzlhPw8PDZAtoEyNeoyt2Tsx5+Hnctw4IX/Nrep3+y5zEAuv8K4B6t3aP3T2jt1dxHwYoTcS5uGPNCrg9I+sbCzqvknvThurMdX/K7eKbii63lhwjOfrFp/x1WsepXNnxxVeoeCguI0q9vfP4p3zlSqc8fFIRP2GBSIoLrMZJTzNj7NwDUAne4B737ZHT8AaYH5exOXWYjYHH9SV0Heen3fek86LlA+gv1PG4AHRSAZV61TTiHvUQhp0NvtOvFkRKgam24PjqvZcXXD3/g1i/kt1axfz6foR+/gn8JvEyKvH97tgC3AB65bAfAA7kWbGcURAXsaS+St0XJEIB8wTZEfYHZp4MbGpvuaUhdhqy2rA1KC1Zq3kbJEsot11GzrzYRobeGzVuTWiU2ow1gc6S0XWFBFkwwFm5YuWFZmiEMeqEEyPnLGIacCeOBMhSLWgBdyZ7TC/T5GHattW4w/jOku8/cEDNnAB3QaDuFOR+Bnhe5JbHmudN17vmpee193KGzhi5sX070vVwrCsY05UjcL2gsbUj2ApOwhQDfx653sbdtdoS+pw+fAQVWfLIqb7aYnsor8Jvfsf23ofXx+AiQYmHG028W3Om/f8H69hWoNazrCS10c1irv6///Rmv/uOtteXTAQVhOVm7uy49gRkbIdvfrW1gtGY2fRsYXrQhYj6YkxKe6iy6r8f8XMNR3kz7JJ4yLNZiXazg4OvXb1hWC/yf1gXnPnB7c8LXb4E0HP9zPcb11VlofF054eO3Rx3rGb6y82EVn8xffTx3y+dUrX/7ADqAaon88PiWEZl/5HGuLIlXfbmiFeMIpv+jwP6fPSLLazcWTLbS3tz7+Oq3M3dqBgicKv9Ka+l4qx3h07UP/+TxE7vBBVYGvp51dO2TAq6Nil79xHPLhWEwEY73mw7NrCIsjsI4v90zWNwQrAoZXZ+x6YCpDEdB3KBD0V4z9PMdBh6mEgKA8cKo4oUJ5ca8yzT8s8elCXOdFJ7/nQA1xSKgzbOqypV4oqlQhSC7EK005yD7HeswJ5IbKLEONY3EMtIE5BWBCalKlt3fezc64jadd+U9TH+aTs8wtlJgF4VMy3XTBrHRJFSxFvBV/186jFQBLCDdoFgAzwz+e4/MuCUqTjvNJJAo72OYwXtaTzjredeb7bjuczSBjfAPHFNDxTGgnlnB5f1VAInSeClZvzSrKg0ieMHN6QRpnigxZkWoOC1S8m6nSzG6qgk/3GaCAdyQUkxo5ciCzPl2ZXRhRkDjhdIY9mrQUKyODz/XiFUNBhaWDRqXRZV4VBg75gLGMEg5q3Q15Y8q8gFmZQF7oBHwvlJMEM9cJmog6rYtmQ2GbufIuOSr88XxD8vbuM3zN6fk/6mQX9wHmOWexQzS6qqyjwKCFgiHTejhlPukRr8iWHl9hF7dD5qBOOf9Ndl/8j0P8hL8GvKg4mEe/FwutMjk/amY8l9AdHHzvuet4XR7wul0g5t19f7QS0JncyvBXg8eg2x82a8YlnSjOiZPlUlTNbCXs61z3rUuXc5ScSgdIC4yOaM4eYlKIJgI0SM8UEBUBgYc5hstk5niiEC5DIeyFvWEKnOeLM3lkgKRWBhQ/vYOFshhD1K3hFC395KAJmsNixsOAYFe+QI0ljISEkqfxbBoKj35nGgkuWisQ5WZJeAatAVkC5eo0tLiIom5090cs6FNJn3PwWQ1i/M8dKOBeDt15z3TpENqDUuzTG6Dqw8e2hJhRrsYhJ8olKPq2WgxKvND55ExMHo3uLjek38nHZT3J2a06a6BiGDFukMBCCdorFP8M0KZ9w6eMEpAiYiy1xzBkilkDMvKljHXo/ysmnH8NNnhMsU/593cz0SbqSb5O0fShrfEqYdCMYQADKh6nr8KlIChA72XPuOqWekx1xqTvlCEcT0HmglkLA3kUMMEYEHbyeRKR3KsEs595H2+yXqoCyZUpjnDrOcdcwOrI1j4OMiTz0L2W4sSC5zbzwXLYkgIbVnArWUvRQhA7DDy0aICkTRQlH4ArVQkjTFABDw+md69rIvtSyFQsySeqt+HzHaWlet/PKqaV6vclAOien4Xa233+o4F43uCnecHAkXoPsHvJZRiRn5PausQkMyAOesR/NvbAeWjQrf338LBQknjajqe/4qyVVIWln2m9aR84+Oh3ufcEncUsKoJ19XCXtOYN9dlVMT63cNIPANh/sgawKxPrU63TMgLxe640evvEcEuavc1VJy8RutcTB3VHL6WnElsrXMCYtHac3hiU0EbgPOafJO9WNrLnkpQP2l3HHXCZ97q6rfP6pPXrlSvH40EmtChtehpNJ/xXXW0yE5KeXqwdHJjTZ4cY969Yaimaf9r/fjy9V0xmvtl7mXTj5L7Isp557JMeStweZ00fmV/0Bzb5UDKX/+A7v7j4+eMg0icDdY57We7RaqLqnmu+ffpQKu0+5dB2HAy5GlxzrMj+jPD/9NHDQRf++748Ms1+s6gfmK8F6+VvKrwsthb+bufSJNV5F1ch06/yHCa1NjjsU/18DLBew9y92JwJZHG9dIx+izE8UtE1e0Xv67ougq1ogQo9BwBfoduV2srI4rUizJA5jr6yARcD26L8dbmSETxPJNfzo8RUkRxPm943M6ZRNeHFQGJasJnywgPkweiafoXNfXkKftFhiVtRwIv6379imDKanx70jzFJ4ibBfZ0HPTKOYH7I/QIXH4tCDSbAfBlmCH79OIZ3nXlcUdRde3zDoA/KfitoFED0UtDihKBtbdyJBoEv512rIZO7AUXXQaWxt6aaj8XYaGoOGqswitQL6ZnN8bpRwTwYfJ/423xl1gSKDHOv38Evb/3d6bs+0yHe87ffX795wKX/2T+ARn3hhT2ToEPpSq+2D1rXVM1HwYf9IY7XAbR73RWsteUA4WhnUfNnRLwjYCXsJ9EngxBiq0PtMae3GJzy0TgX+B9x4HW7ouO7BXgf8zqcXF9S7RUtZexhGwNcSCKPTKej1ExExaibQ7I20yIBfWHo1xZ33WjpcZWvbwuCx5OC9b1BD15knw72U93IhABrRF0ael7a23+2zrQuGOjyO3XpC12m33xoPlpWXFzWnE6Ld52zXp5y+gYw9pHhA+kqRXdRSHS09qwsCeXtm7z1Cbg/BgdPZHpjE/WllsxfZFkb6iY6vzG85t9UqOVXBUFVTSkKFAUzcjmS8ueOuptMSfsPlJLQgCoFX9Vsatz9C4z5o2Abw24UfO9EAjrL4TxB9xHC3AjbH8LvyFB/ojAu/0bolgYYPqK1n7Buoa9QSBqEFXcePGXof81NO7gZTH/bp/V8cyMlQnbwliloS+GTdWFPfYx40wMYFXC2Qk5aOTgAS08065dG+OpDzRHxhQ/KYs+YPbP65cv8O3hMWM5Pl22da7oSvn58bP69NLWeX/iNfsojCjsf/6Ljv9/BNB/eBxX7ntabxhCcrmy9kU6NwMaNzZY9toKh4ho6pvHABpU8QqEhz/5JiGUXuv+PQIBZ0LOUPl7wlIzzSwQIk7aTMiL6tRz2g0mmWMvkp/0hB0Qvb+30hlQBeMGwdimwqbpe5stRuaGjk0b1XYAwJ7i1r4S6CVBvlklX2RZuzqJRZqfP4M706E6hz9EgG8AvbC5aSDo1+kMmpLycg2o3Es+u+B7xWjK0C/OOjSymwjXTCGCBcPWX5ZUfgmK8VlmTW8YJM6o7HjhCvi3dC4EY8y1Y9NGltcN+HxXbkZYXvs1HniQ0qMz570cz+2SODEMg6Dza0pszChdfHebb6BF8E++OKnO1MagDwCwbOjI0Gen0y4DLAxZv4KEsVADGFjDMQ7FUHMcR3B9EFmfNFUoTDkQmf30rKrX+oBRjscGG7K8qfUY7M4fWK0CskbDU8kkOszFyd9/Swd+vrduRWMQQBmqDYLNHSQx58ew6w+OyFJmpFaiAIgaooexahYJWZ8Wsr7PA7jIut0fHcBqL39c+LifHj7+zrCfC8oaqzDRH0EzUcv4I7XqSFPqukEhLQ29L1AAS1usD+loGE3Ag6exWKyDNPRgWaYBCcyNHDa9zUzk6IM2xJ38vqeI8rzGbJPOALEmjJmGVUGWoa8qZf8QfFmgcAdZYzQ0q5DyvqRWwWmQ7DFHooaQsG0dQwZOy8mgl1IJnUZ+KJCIHx6caKTAAnBvDqlrz7Qqs6LNloUM42Wu1z+iyRhnqRm26TAjV6I1eAftLkv5BnWaMUbF3FJpJFhvU3V+HT2ja4/otiw7PiYjevDFo2LeaD+PiGxWu9I6ZP1/1L3pchy7sS76ZQLVpCRSErW8fPb7v9qNOHFi20sDB5HdBSDvjxyQVd2UtGzvsHcpqO6uAYUhkfMwcR3IcZrESN045/dMZa6ldy8aRanNqtEcrIYeLuroQ+aaymT1pRddu1IrDodqkecHHA4LDocFtapXsteI3ky9zYtyyazwAADoKriMabgOUhKjd+pE8PqKr8GCCGYqPzhBkWgb82fM8z562nFAGOSsURI1nMJgIdeSbGNErWexTCjZacMN6B6hnpUezICQgIsA3Wr/iglzoka8WkvQudZWy3jRI6pRozMYHlnladvDYO+8UUqrviW07jTjfClmBoU0PZLpiuE0MkcQ8RpXIzmaiZzN+xRitW9ey8zXjLkhIt+ZNKiruLOIGuQKVU0jx4zinvfmAAIYT9J1GqXp3K+nVZ3dkIxeBPTWzICuteLGGKCiOIrYIyjUsZCJgLpgKQXHl2cQFvSmKde7iEWdqDMVO19gR6kV6N1qlSkseZoyT/vGlvEEorVc++hoBJQmEK4bpXjwpFCnBndScZhzesZUpjJoLrhuS+fxXVEZ+Nb7uHPoMVyo9cUtyoKAQSNS8s913nOt6vS1PefwRQEcWitda/QOGmDLHRQp+pk24wlnl01EYe7zwGhAOSw6V66cac0yK2kJgVIYQmXieiMOXNRYTiBwZRQ2Y3mtWOoB5XAwY3oxnKq4igEUHsrz+fVWIgI8yxJ5fuHKlqHqOo/cCgeERBMVbes7ZSidNjIVDqOXDhGoowpZpHvywtrMKxL9O1Nkq2NktagLOD51SmYZUVyu8lqAvtaUtKAOydOWcs4bbumYP5VqNRr8532g9+6dgQzPEMe4fE5U1pop/t2hS8ZAs7I7xJoJofduUWRmqhzNUm+6QtCzRxgeGxYtJzCvN4KMbgovSlth1//I9JH4Axu+R9/5fEx87fzOFgbcoOw8jzoSEZjUoVIgYGi2DA0yHwCVpK9QehRhUvYqsb3iirC9QSQ7LEVGDQSxPjtC5o5m/Hei6689s/u9Uez5HsIcT/xFvx2HkCE4g18KjGd72ObP4I1mqPicmh0vmRYCLncEUyhxIVIq+xltdpshIhyBM+sMuJ9KMB7e/H5HjeEwaLjfZEFdc4Yagwa6MEA97Y89gt3OZ/79S8fZvOy+/1IzNP+yApSMV7O9EFFtsVSmcxPMe7xsFUQzJG26GNy1r9Tu3ZcGden4tbnRJdzupVfb2V2fmUMSaCHjuwk426X6xXX7yfGasvv8hMx9HR09I+JzLoLJ1+95bfY4W+lO4j2TwSW3vZkAuz7Uih0ygNNe5zc81TIbXgq6ObxMh97r+l11pJz01WuMR330bDw3WXKI8j8igtYts5XxxcYiGD+kfVnXpnTJgz2A4P+L02PHdzZVAyNSeisN2UbWDxkgUSdYsBrUvUxY0FsAIj05QCsAaP1zd+aF8hzmSOxlSkROEHkT+10j2D2YQJ2H3VltrpNsls2df2WIBv/wWzu/53vj6Z8eGXyJgOW9O+69AwiolgWABqG1jqvrAwDgdFoDFTj9cZ8zYJbccr7B5Z/JE7rcmfauHXwHyBc9x58elVfZoDv9sVpJv0bAYah8AIHRFZn4iwl0p/N0+MsHjVyGpuR+/uPb5t2bmBggDFzPf3wDAJS/foosnRBdN/p0q7D95VEzd1JKAw2EJoNjtmnSKpkp3t1mwZh0rwKod4SXL8ZvGd7/7kpSIs2f6nRA1Hm2ff6G8XHKTvWOQHSD/tWM/RCs9BXLh/cYXx9AHwB6bzzWV8AkFGi6dQYKcLSMjf66mChYVgZR4zgZLPlvXwvPNuFMO9HQwMpBgKXXZ3PCZQKYG0ZvWGvBsi64umpooysOoYFSatIpasfKUiy7mQCjYm0dtVacVsJSVqyeIS7tYXVc17TgS11wOBw08+CyoNaCddUyFWtraOuK1QzgIgMswDURVlZn95MwRqkAiZafwDD9n0Jj6w1r7zYOM8abPDjFUnUKUhyHHeEyfgZbCrJnQ4YiRXSZWQA3TQQudJljG9NcmPTPdGieGXJbIgrxjJhMLGPKZrD9/lIY7wyuxyNAB8JCjD46StWI/7ekJQLqbx9wjYHn06pR40yqV/5G4L9Y8BKAga4yKzGWuuD6+hq1aNT34XBQmiADZQy7T9BJUEfF1RiQrkbuUYblAyMteUFzftx5jGA4xHUfykCm8SPKXGhwjunWk10t8LPNOxfG27dv8PT8bFeyDtB56h2vj/Njy0bKzDbgcm0KRJoPZQ6Fdp//s8d21ubxH29A/9ewi3/mfcY0jRE1HoNhg5xt+B+39a/qk9X2uB/AB4p0dC4eZCYkM+Qu4+5lnkvH5vxZxw+AnBCcW9Yw5Rf/5Miqhn84JnqngNFT2w0bx1s5E2x/tvF+pVeOxyVPtBNj484Imq7dPVj7gxKFeP6VF81xvLE7zQWDEUoljZazFPY3Bf1R2Z5y6zVtp3NBKAJTv/342YoldvhMbNp3/9JwaM5UUpJJun+HHOPnZCKj7zd6cXzvJryIpTKcAjiAjSDlgo8qiIqlOUTs52xAJwDolBSJr4wrhDSzne8nMQ0jhiTK2AEVkFPADqV+CpuyIGZgu16vrdUP97RJUVPxOZ9QGHQGCealO6Mo9m3OfrR4/uI7N++2+fBJ+NnuMiFiJhGxaHkz+PfRwdaDYOxNMSyiwk9btTYpw4RnY6SkVCBqjMMiKQeoixraSQ3pw5hhLoRSqyrfuUD1khbtjRbKcL9eihpXuHgUnu04T/EvZmwSdgkHFv6UhE2J9SLAjOZ6jksNQ5UbrwBCo6ZjHx2tNTXgugE9mChMvO3Yl8zwywIRNTyWkiLxyMppnFnz9ljhV47XWKislE9UShKMbm7fK9tnO/EmgQrqVl9XzHjqeEG98BXCs8ExNjK74RZxjYiDsWOiDe52BeClkQYTKhbxTjjbAqGIJkszRSWYc40WLzFmr1dOIJNWVVBYrg4oy4JSGbUW1EUN6HVZsCwVtS66tm7M8BhikVBC+TtEBgaK1b9iTcfGqlzyifH0t1qqIA+KQpmcDQpAAqM9nU7IyZWoW29hi8Aw4bGb0icEWncJ9vtghumUll28XEcyHgMmNLlSIBRNs2tnNSHTiTCMFKMZmE42rSm8jdG1LMMY5vRCKcWwINPnfEjShsRM8tQ0EmldNIcxL3ujY/J7Ul+JTAHPKTXhugHWMOYLtBabOSW11qKvgApkCktanblQsXITmgXB8T0ZHLArGKwfYwz0tVmqR4vuGR3H4xqRFRGNAzOk9o5mHvCOcwUIg7Ir/IgZtS6qtFzUk7u58bt3pQ+tqXLFhNE8VwRgMGF4+/D9TihcLLvJAsXHHdQmjI9mtflCeNwxEWPiF19HVTpSQgtuGN/RSh8nzk5tjoh0BiC9azkGw1fZMeQir8ZeRuf8cEWnOwwPUh6sABB7jkDTUCsKw15T3RXjMMVwnphsjC3FUpYDYF50D8lAXRaUUgFuIFb+wzMReHo6dXLQmqC1qLMQL2ZM52L0kgOHqXOx0u5aK9paNkZbV6p65DJEzAFBsJ5OoXHVzGQUKfD3cgiZAXuAVaGyJ6dIe1VMlvNPC+gbFwzWui7bL1uomU4YniJy0kr7dL5XCJ6aaVb2snIoZu0rdRpqHSYujiH99tIaej+9+tx81GU1QyLBE10avK+TOXdBIMTBUw+xdIVD4cq2GoInG8ZXVaW5XhPQVXxiaR7dsB58vaPmzUzPLB+Or/1zK+dZJ/Iy+HlQWhrHoz5niWwKA6Q4fNj8KHhaxKOMGG/Md1hxZ2fktbn19zouS3Q8D2U6Qtg4JUfkb8c1lXH2ildEgQnOcvYXxjIW0LBsCBgQIRQaIXtLaixnMZY0/h2kBo+dH/LpoQk41uzlzsuQbdkUn/bdCEOF7LzQsCcEyBHnWwdCex8rDlG8RxiDzVnW5IRNfShcWF49+cvG88uPz+//okNsfRyG9ZzYmkrs3elMYbg25jFa2nT24hT8vDf/5Gh+rZ2I8NrxYJvn5TKd/+nxqwMPBCWbU6Fjy2hpg4T8Ee2jm9UUb1TdI2T70fhud1xz3Ku8tzkB7uS5MHabfObULRwsxEsI+fyp4RmkdEqjLQWjDRSG7cuJQ0afdV1laMa3YRnoPGvJMP3AMOPwGDN1sTqtaz/KUiEg9PUFfWjUqTreuIyF0E24YUlEQg/hculwvUc1OA8RYK7PRuPr+4A8swzPu8YAuOwYxrle3tawscflnmTZhMp1zjQ6UmXhETzR3hkrH+HU5XRsqPMwM6NLx+nbk2PD15p49bzzibH9ExgTUTjLnTkVGTIRx/kK3MHbGPXf7Lu5jmPTzJBHEG71/i+PoE95LIL+ebIxSkuheiYALfiI2Weim91emEfmr2op8VxEdft9wGZO8/OF1Yk6znnWu0+3AB7QP+/K1NnOrp9u0T8/nHfKXuLp3T363CnW+KJzHPo/VwLsxph5FSHC+Gpw80HP988PaOV1tDaGoJRb0PsHtK8SagEhCc+0zXOZt7QtIZKCiUixztiwMxMZk5BljFR8RqJOjp5hrQxgSEPrBUtveBI1nnfpaH01fcx06i0mo1b11oeIoNSmekUG1lJReQ0cpX3waVQDeq1LZBmsVYMphNQBp7WG43rC2jRbxbuhOtQjmQF9DBzB6OpxhNKbYuYBh1p1Yh8t5PA2xiai3RFGH5YNM011cI4me+WsGhM+bK0twGG4o5FMPY5vdu2RfUn6e2ZSR31yXdrUZW5Jl5j+XzBYdbpuQM84jawMXImsokCxQIR6dQX+ryvQ3ztGZVy9OeDleALRk5K0QeGUwYVRi+6MaoFT/esDSordg1oAACAASURBVK1YSkVZtO55KWWmyAdwqhV1kDqsD43oX1rHFa0oYKzSwR8Ip68D321ONoGWjntl8p2e8STTWd+DTgl6H6hccovBi3rGwq0EZPMFbNqM7bbff7trZ5xa0sfI7tx/2vEfb0AHEECwO4ufLw1+cD0xrLRl3AH1pOHWgOLpIC1Vzq49kV3X6OLXP3VcXzx7A8ETgNtgSKfcIIFInCHzscwYwvP5mDyxC4+wOyWldLFHiCBYodG0APGVNWLMUWyiTMqTgGCb2n+HnmY3Sr6xKxZYTd8BEUJ9q0aeZpHpV6QbXMeQI9EpxkUgrI/N3ufXJATUzeEglnC99ocwHies0DvtHz+OUMj4P6SZLrdK8ddviZhgeq9nxmlOMSG3uDlvQo2MAYyB9vCEw8f3M9KOsjBihFYE68MLmK6T0RG7dZlTIEie8FNjAzJvfCOTG7iO387IBWP4BgRCuaEwElGhMFRkvYBYJBltWoXBoAAkaE+T8RK8AOL1GAsKrgCMLfMo6gij9cVJg6Y9e6dIGNA9QsYV8Fqzy4W9ZEx0BZBtiMkomyARhlK4HkSZT1xjYKAHgNWU9cGUXx6ZJIKOFT86MoHKO/o1k/ZUgLkgpDPkUVtKGBVuuDC4MzjqeacFPTs8hbuTkA5NGDWx8vmTLkYAchLgap4tZtiMEYkTdYuEJtGoN9FXCRDKWY0gUsPVuq44LBWHumgELyvTg0KAlGCepDdAinoEQtNiDjbDuylPlcldlPkhAo2u9aHJU+VCUxTbH9Wi9aocHsRUeqw4DCRAce9wVRh5lLoL6JollFGLRrVLVYO8vm6APH036X7y71rbqKNzt3VmC4RXr9gx2Oxbk+Zp/USOFNiu8BYhjG7GS1EYCm/QrPEhHV9OBXyZ6u2TeuEMQpId1T5l8xn0xG70TCuqXzDG3GBJI1d7itZKvTM6Eco3f3cQJKOlpvDxTAzMU0ENUNQ8jWMIwIQhPdokwAR5BF3OyuOo/ep4xjIY1FpVKCrqmJENEaFQNVdzrgVXV1eoB3XeKLWo4bwuOFRlzrmUuZ0xldKRKtkRuDHJPATCReO5RTCkhMe1ogo1OrjC2OP89YcPzqPVgyAkHLXF9FNtMwXaidusr2Y89+wPEb2Vao/6+g+bZxe+RoSDAOTKZgDke1GUigyRSM+uXXdjPmt6Zpgx1vtneiQ2HEoMtN7ATLDSujv+RBvu49xBaRud51GWNjMWZjoNKtPxBA5jcPnPZsENtvacGq/V0Jg4wEyw4Rk2XNnXu6bJzMYWGgChKjodjI6uoFg9S4hHzQ5gEISN/hbbS0OF497ViD6aZhE5nVaN6CHa8IbDDN3en1IKKhX0QqDebX4oIsRhmaXqspjzyepyOwBBb8ozuiNDJyjpMlrMhVF6xyg9HE6IGcT2botAd/wffKEuYiCwfbSlDyrzmBiqIBiQgJHA0En5mOWfvUC5xY8EkW70Emh9xJ5Gukv5mMvRpZeOkCsooMC82gWedodskvVTs1ZEnez0boWzqaj0MZxeXmKu2TJpCAl4qGJhOSygzuBeogQDkmKES9UIDmKUuuhfKeYMx5MPSriqlIJmpS/I/1qsmt5NBE9Nu55O0wnH1lKjh+wc+RpJ4DvFDwyhHjJC8Pa+vkmG8r0W+1g8K9FeUvI5TXCwUTz4HAObL4bPYiXZooCNQRTDm13YWmdQzMUE3g3vOVFIAInvOR+t779zR+cplWScf8ZHuMEAUGcFw1M+UlGmR5WAqW2Gni+VYberpGDOPqOrU6U75TBrRggt+VTgZXRy/+a8J4pmsBhGZFsul9JDXrB1nU4TZqbeDDltthTKTLEB9R3saUjtdjL61i2tu9JSV1YObIQ+a1vZVHJmO+SdfLyqu3JYTRPkPOP8nQaWYPCsmQBSg17Df4pjADeWexkAxXG6rzfgDTdUmOkk+Fad6yxL+9govT2GYvspaJ/Pe/o4n485EnKlrz2gPgxzng1txJsp9cfNPkzqdCuDY5TOr6vRXJ3oiZxvSoB3uYOJr/7BbT9rZn/v9hU/OXZ729e4TCW56rdKwEXsMhHM5ZDdu/btvtKV19buta7+4OLIjNcvtyO7S7I5vc0S8Npzv7o4f+7Q8ibpOIMDSTyO8/eAy0ziqcRzL5N+C+EcOF8w+uSzMv80SymZASVnxBMxx/PJRSj6H2GI6F6v19QUSuec1sHeobRDM1p5qSpvfpih3K5bH5zOahkFgVhmkLVZtq6iPRpA8GKaicocniyKXRihTxMPEBDBFVVNC82zLzpk1YO01sEMdcgltkj5YXyIEgGNSs/8zqSpxNAMcwhOc64/M9a+xuLJEIwjMPAd9PYtqHdQrTp+N2xZGnvlgTDfSfZOT7EvSOVsBMdvT9GrgI8MaT8B8UwtiDTpyrgXLB8RzpVBg/nciUtJgGYMAKljbxBNzOhXl0ZGBNM9BQ4a3wTlozlcABifBeWO0L+Y8RzqYOlG7iJKsxkw51br3x3gxnOyTAQEnf/nL4IDHoBP7zGIsFQLdvDxi747Uo5v2Q8shgebZUpa//4VoFkzfTHHi8Nvt6i/OW9ssEKE/sc9RB5w+P3jzI7w+UHpk6+3k1gfj81a+csHrH/cqyE3WBeKe/LCP9irO5JO4t40R8auUrqfiFHu3mP9fK+78BMBdAvCvWbQtD5saocLJo6hLGWmvSCZ480Qam5CCed4DjBd5wGXMq674MiKL+6H4NAJx5WC/HcRVCmoqFiKltWrhVFLBZeK0QdaM4sFXWnmMy4he6jsNee8FCtVVbV8n8obGjy2toZTW3FatQRaHwMt6U5ODCyj44QaTkh1qYGbfIaGZYBbuxrS+9CMl31scbOfU340uZOGZ4XDWIa1SbuHOTZpKvhULjOthPO/xEkfwxr17YZzJoWx0LX7Z7xPsbTYokQAQQqqY0vPv1jZNmbGFRGaCHB1AtEV2qHhqjPat2ccn7+j3NyC6Rv4bmD9rH31QC+GgGpV3rIUHIqWHANgWSIPaKOBR8fp8zfTNRDKELz9eAv5f38Dl4rD//kLjusJp9MJXQD+JHj54yu685CiqvUGLTvCPmp31iejgyDUuuDl5QWnbnYyYhwWRnP6a5vbU7tr0IymfG9d4aserkwH77skybi+Yr7dzxW9aXcBkaUr60+y/uKi7PDvO/5XGND/Jw73oD5XTLjwNiwVoiLTnD7jz/DgfrwRwsu5S/Kv9RVAfc9o95jClziRw+yTC2e7h524Xj5+dTQ7AcVPvXbrv+F4NRLdDkfZZ0P+oVxMWi99IxDbFRfkgEgPDBGU94x2P7ZIQKI1P7Nt69V+v8HAC4Z8R8ENAEF7eMIA0L7eo7y/RX1fQqkuQ9C/f9cUpa5VwQsGfiYc/UAvsLtGu89Lh9mqwwDRvms973jW5ks2jekKiSsR7HOLUMmihCcRFqwgrhfmWyOJcuoq3wtuQIdYpKozh6LMLcSi/9y4Fd+RlN14VVB3MgIj5HvXG2UKVigKVgGky2qCx5z3H22lvC6Tzdv3AjZHsllzV4pnwzvBCCT1zYsv7PwL7xMoya6bM5NUz54EcT0JcH25x8NTcoaylzGginvwAHXCuqqwJy/A6B3r2nA6Fbx58wa4EqsjVFGqpoF1s9UYHY0KaHRVSOmiW3AgmW7VDege5WZ7iRuECpxb4aqpl7gUS/fskYUALBI+lHSWEpgAdHH23JTBBo+lKANLRWu6avR0UtQQJtferW0Nt1eBB4KxWno13/+dQHVAhA3etUZTKH2ZwRhRIxUO86TtboxEuACTSVi9dIfDwfkh2LtSkcPqRagwwamWWZJhDI+njtd6FAFIUwLn1tS4Og1WIm40nYpjJa0WfW0CtmDo+houONsAarENRB8CO6mShWS6WE28uJ1rxzFM6i3u2Q2IPRWwvTs+Ff7qsqAeaghSntKr1GJlCCj6FMZzU2wITWHW/ydmsKhIyAJUIoyhYyGvLeUR1+RDpjkZu7nRtbjg4uM0QMQ84yUcd8T/F61R2IeVa/DUYWRpD9mcYyzlnqJ6M97ZPnRHC3c+cLjnwuo880q/nPSwbzLbTqSbHGIprFVo6yCoMMtljejk3GiUADInLUcpek3HKyPXYZ+wFK0k2hNROInuRcrJ1uYz8FTKlBxBxH5j057/eaq3/bt9gTXdegeBzXeEMKiDGixFpdanJ3QoulRDpZiA3JpGg7d1RVtXNaBDooZZKF6NRg+vdVw0KwhsXw8kQ7OP1faIO8dtHA+YIa0ZXKjQN8jToBGoNd17Hqlvz6thVt8tIiCbe4Flb+EZvbyP1syp6DxSWfEOm6f/xFHZMKDtxX/RFxsUXHENMWW+zPNRfiPxJ0qDzrk2R98X+TnHpRfOz7TshrtpGqrFDTtkqVrJlZguptizOTKebL2ZFe8RQcrAshw0aqMWnDwNqvU4qIWP23BBOKMWw6+lpBT4CLxbWMu0lFSqhYgw1lXx67LEWrgBR4K6GodG/mHv3An8XoPS8U70IvjaNMNjy1AO0cw42Tjn7RK2sEWQyQPLhJ3IauBr5RHJ9lUztVhhKRkYwqAxrCwNANEsPrHmMd/WdeObNzBkNIE2POaUVze3XRJEArbnfcozU/BM4WAEfX/UKjX8ZmTchkxWdiA56NjYkWEo9q4t6i5Fu9MEv8MHFHs+aMeehxHkDFPBsJBmL5gpRaeR12HOI+pmLKa/E8a3+L2aNahYxpwZIQWIpRoeNMJoPiJyWbbjvogMLvFv52sezhj+m3JT24anvD7pXEScy3ylSOKnoDifg5aKyTE2v+5sNgaENRUpgwOZTuezPMD83dr0/W1znG/JeEQSHegGMzPjC+CKelfk6ngI2Zg4nXryPtE00IEzJMBzg0vm9wk7er87vPwDxz/42K81fJGamDyiFX4Bo7Gxnr622kbQEYMGIDkFOi35V3T1Vy7/bK5k++Pi7RdOvpJ05F92zF2nv5jLpB2bfk3as39qPk4YvSkOsT1qFWEig8dez6rwLXAjcNBxSbPkdMVpn+21nC7c+V0AUT4GDEstrqmGpQuKMFA4eN9uMrcH1ISjLSHucV58OI9iGUkAjdw+XGlpvu/fH7Gtpe32fdcdz9To8c8GO3y8RgKG0chcIs7nS0Qs+xOFs0AuJ4Eo+yKmN9ldN4RMXCa9n0s4N42YvnsCAQSC09pQRVCWJfCjoO1AYtJJN7C7Dsjv671Hy69AVO7xxcMNfONewB8Iy3KDI+4h8gSitwETWQaYdHXKmAHx6XpmmD0QSeRR1/Xbdg+3zw8od9qKf276nvg9zzLgsiULwJ8Awu3kIyYXiSFKUVYIauL1827Mn/s587kVAKe/f0W/MJtDZvauOIgNTgjl03uDDQqnssUi0l3CzO/zKHT+dEHe/9GxY42cBezYgGV8e/nyBVd3HwJXsOlwcXcL+XyPbkErBOBKgGM0Qru3OCw4V+9JYUxvmXg25bftuwXAvIFlzLIWvezoFRFW8pKiA+96Qx+M1lvEuZViOoVCqrtZNHvWKF0JgFQAQ/WSPB0THa86718KW7T6DOBRI3xXo3drOLUWZY1mevWhfRTBCRZ4QIRTaxvDoACbMmrNSme2bqXxEj7u3Yz8wa2SOc5YWUKa2iZJsO7r4KUTNXuUOTUldlAA1UNRifY4os7dL1Y2qyrCSZfxOrbRmvGaNVD1OGRO8xqMwkx4+/sdjn/7gv7Qwe8J48BAZyyfCC//X8GoFSCgf9WywcMCXUg6mKtmPYVgYUYtBaABenjR0ot/fYfSGX00rEvVLGjmELscroD/+h3Pz894en7E2owXFNUxv/vwHo9f555UnYXLwaYjlYkTAneEDGpL6Dwl/NN52jlPZEE+rZ9sT8zgxQwzed/sz/3yQXTW9n/S8b/YgP7aZnhtuRxITPVitQfzdUfaow901nqRjhiHTKbnh5TBdvtHqKD+DBjxUSP68U8KNX53vx9g3KDfP4DvPmp/p5y6FQddKPcKd+mV5Ccoz1NK3+iKh3jgZEqBq/NxgsILNzMiINj7J+ibXIuowUoEeoskbBuj5rs4jSiPLerJpjEEA52ESMA91VVRXW54PpaZ9P2RTm95fiUJ/WEqrSdr6SMdKLeMfm902pnzTSs+TVPoC6+bzYwZAhNA8Abr4zMEDXw7jbErAHl4AOEN6B2jPwg6vQBEAbfOFu3M5/GyPULNo80MWqSGF1Mden/JdEx2zY8BQX3nXr8wRlICIbqAwOZxKfPFel1D3XB4V8FEaE/O8J/0fiYMVqJJlkaXSQ0EBdcQtDBkuhAmaT26EWdADaiaEl4VMyGwGeFgJlQmNCas1tdttofp1zZ1/wSmBebnZjAPDDTrRwFh0YgZEXRpkdXbJ0K3QhJj8ra1Ixunz5aXNjfGmDbPuyDqkbam/BGM3Z2XD0GzHpgjQH5/usv76aOhC/2O3yKW7tye2KTVDkytDHbz+sxuACoWxUhYlqqpZmWZ7DKrP14plgSMxsQ2hjfc/5SXbfQvFwJ6UQbYesu1aBS6RYPHHPtakYkVbBgpCUrSlQn3dFNCEgZRWqrezwLRovQmpGdOBmbQZCxLVVgfxrB6wJEBHpkX/sRXZEZFV1S5Io5BZkwXzQGVYAe7L/rdRBhbB23dfPBjZwg8JdClSPQ8IDf+5GuyuaVYFL57jaL1gN/YD2KKlkwjbe66eZkWi0ITMUHbhBTyBqJA3zZqEMDGm15E0IaAktYrZHERcEK+asy0NYJlBSCK1NhsEZiugFUM5cZ2o2WsKbqoEMqiUbGVq2ZCsJrAXDSa3dOK7UjZhtBMox2FY7Ya/Bke1EuFITwVtC68uICz2fuGrMJwmV5n7HiaJ50ox3sT9zoPAYuE7pFycK6BpqwH5r4IozlkG7USa2YJp1mdFJz2UiJorpj28+Gxmww6mt/Ma2SrMYJZtPYVWVSrhwMQ4BHowww/pSCyGGh0+DCFm6sM1IAd0wkkeJs7y40Cc/41wjsL2GwGMiKCdN83JhTJrLvo0eduRHcsN2soJwWpoiYzVFgERyNwBYQYvetYmAksDOndUmJaera1YT2dcDy+WG3IpliCpiFTU2f4+ALR6Pya8ZnckObZSWydHO59PxVm9KQkCsODz5yV5xjU0cpAbeoAwMU3hD7j6RMjFaJoOjw2hXAo9gOeJ+/lyl13IhhjaL8AdQjQZcdU5ZwfueyMp2obnlLTO8pkSmk/Jk9MhBT5iFD6ZjiLdtIns/OEsQgqNViaFyqOt7yjbNlddH/KEDNoaVYgH6/S+WnAZCjOKos+x6ypCQ9XVzi1FZUA6oTehpVpME5CBkhK4FcubJk3ivaNQmSZ4yZS57fmSpikvjTi2U8rtlF1w/DexeW5eJzx9Ox4ZLYqaT3CaCD6vpEY6xlR65EWNNtxPldv1NIbXbNB9N7RmTc1Pt1KozAxeV7ugm5avmLlXSb+pqC9WZWrcCRJaKJwVNvS75yKwT59z9iLgmqkvT9GM0ME4LV0Raw2rVhGmh2/oGQ885m2vtYlgeDqzTVAhNPLs76yDxAGDocD2uk020GiC2bI8G0ejioBYFuFU1o8HWvkBp06hX0UustK+kOzagznKwGAkpzuNNThVzDXyKPUbfQQaPpzESVhbviJKXKChckn+JSejUk2S6n00tbM+U7vq9CmAV+HXNNTo61lpmA1Ho7VZA7XrTgNcjnejcW6DoRQNlimvoEBHtMQLZZxyvn1PB6HHBKJfSpmWFN+29ccE2fbM5LXIOYyJODgFWOyEp1IC4CACyMIU0WS91s2ousfRx8i78MW7zt9Ejdq7t+968a/7PAZo/PTr7znlSfmBc9GkFEOXm/vTx87tLXtwI9+p3OyPSf7WyTdGoOQ3brMHx79mC/9KGDkVw9ipX8bPaHj01dhRLDFDWqYVV5eTIcw4Y2thIrISI53PisyDbYiUEO14jzBSHTAjNGthUFEYDijj4l3DE+XpQJN0Js6hBYrezYAHNemtDWcRr0f1qZY9LDpjGA0RlO2Q6MEjyec2hr8+OFwAIZpXS2bEzEn4/lwcVL5bUjIJK2rHmW8PGsfQ19lfKXxdW4o5FrU+blUKI6h0CWJCNppBRWXX43etGHlPw3/lqKh2zZeDAETY11PGK15kjObdzdAFfTWLNAC2G+UWpW+t6ZBGE06SvCdok7dteL0+D1AJ96fWIJfYa9cI7gYjl4+3mD9+ojyYUaJE73TjGAnd5oFPDtagK/Pb9LDOt5X5+7HjeE85sR+9C+2Tl8smhwKt+68UKyvHbDIWJlrgD3NwJS1hHHtxvmiMpGr1a/+cofT37/C3QE2fZpDCINaw+wLRKzvvscF42/fAAgOv70HcUH7+1cQEa7+ehftadZb27d3QPlKptvUcUSprjt9uTq663u89vlr2MpVJ0/GHr41B2AfnztMVOt/AzA+f8XiBFgctgfq3S36N6vrbrokIXfAc3h3vmfKRjp/CogsJa5nrtK5rkWAxXRVZCxHRaBCYAiuBVgwsFA3mbiFbo6F0EcJ3LCxLwHwimisCgaImerIJ0N8T6o8Evp5qBG6jaGR52Y8X5umgH/bLeOZaDPN1n+1LFrEhGWd2eAcv7be0d2A3hpaH2gbXYGuSw/7GuClJtmcoZnZ5BbHHQKPBvKhi3j2juS4FBBOMf9kvA273r8UlSvhWam0PTLdwJnxfAOIkwa13lEBFB4A1PaggViMhQr6lwcIM+qdoLUbLOULOgpevnUsXLESoRJjUNcgD6gh22kdARhfn9Rg/nvBuH/Cm8M1lqrp95kZPAhLXdDEMlXIwHJYABacTkeVR2dKSUA0QOzm7iOePn/DGvvFshgJ4K4hgcNMt9nWhlK0rrtSaLYMLmL8rsKrAMYPC2CZMQFgHQP9uKp2VzzgOFsltnyPU4u4OplyPRJPnu1CG6d0X0nyDfHvO/4XG9AvH9cCvPwTc+pIewxTpplG3dNn6OExpT9qB5s7UmZQAGpMFwJefolVyEBnFUcuyCKQ6fnjY8jHqzLBD99nv+Wfh1WCCQr/TEMChGrwlbYuRqIbkfszh+/t2e5ZkzHvSjQI40E7Gbwl9ku1RQSvzcUlwajhGfSwXUNNzf4MeiJTqvCG4Thr9xfPXexT+pTd93NVBDCeBPV2D3OOXo3gk6eKTArfxBESaTuKTI+h1GByxbh73nHUehQ6QnNpSQjYHinlZHTzt19YEXiouhJpjVIKjzfijePIhiBE943hgTNqrnTUa45n9Jm+mVRnG5WxlpTqaz/DF2B/t1bbs/OIOiiyu5dgGVgvGN5eOfY9cd4oK08z7BAIdHCDszFGJnRPJaWP15hUJos4VTKfIzAAgETrNPcBrOsJzMCQA0TUCQqk3oQl1pVBZaDIvsY0aV3NEKrymoqlRZ/RwJpGqCA7xMDeFwaaHBFnY9PUt5YezIQShqjnY7W6qaIMdGdWg3hiGCS9g602LwlhdF27vJkknrCRpHRlGwW3t+fGc8dBtH18ezjLtLso2QFkMnspY/SFQ7YXs7dwdNE8Vw2fk+3Jtq6WUcIayI4nmChl2h/EmER3NjJHAtsXnkrN2XV40alQ/OdeuwH4NUxqe8Dr1YWzD4exkMN4XuI9GhHRVdgTQRHNHoBCFl3O4FpVwCKEsdePYcIRYwsPusaAiCeCm4OZEVpIdTbTOqR9R9DI9O2izcPx3pxF/XTBTN+h4CgiVtdbkqLZ6/S1qMstlhPfhZpiKe2ilExSUrtyQI1qHEKX1nv2NA65v06TdL23phds+Sl1kQaQnQgQ4/N3TgiYqSB9jDp+M1RZVImY0nxGoc+5nMbzEXMWNdFsbH5PpLmONdWx5DEEToKC9RjDMl6o80HAZtDWue55L4lFvhARegPIo1JE0JnUKFwINMxp1Woh9qZp2dvaMIapelhAsgBFQEOtFd5LMSPu1hCh7xnNnQ2M7rsRPt1HwGY8HnkR7IZoZBJbrXTF/WUDV143kG3tuBRUAINJM5kYslS+UPFRrJutD4yub2gCUUSGksDKRdmUePo0mmN32iIikV5N+zkSW5yMihv4OUdnGR72hzC0vITTLkgoRzxTRtBjL4njVSoNLlCmElZIU+JHSlRYnwjBXwV+rFbHvDDKKBgsBm+iiXKsbp/v63Ce8HWmZCD0AQdvqaUoClcUrlMp318J/yNCoQqQRLRzVhhsVAXOw8SEk/azG9+zyWar6zlcmY0J52NomhlJzQIEGhpNrcZ98cmb1N6e7aQleUpnDC4YrIoxraYgm700LNJdI6UsUrko7RjuqEAJKwZZF+Shb4Fn3mcdu3ybTHzrkTCOZLTOorY1Df0/OByHw+FRV0iN0qK43xwIjs/PW8bAVrL1BhSOdLfb5in6R4Dbt9MN+ykIRKx8kdPc2Ij+0zh9N/pTcB/KYSXYDaOuM6gCVRKD1EnHcYTjDIiVROCQPQaP6dgOVzTvGLQ80RO9zZ9n1x2xnM/DhgHM7e3vkmHrNemrP0q+p2z+Ml0MRxxY5KUAZDV3h6XiZwEGA8Uj1oJXPOdXZxS0QRAl989UIsUhkkwxLLvhBw4AbJ9bhi+xWRefjN33C1Aey+N4gOY661zo3ta58PWfvP40nv+CEf2fOmT3eeEyzR+zFI8eDtqelppSU2Q/FGI57v9zQ5n7/WI/f9CY/PAeuXjt7FbZkKJ5+pX3jv2Ff3jd5kz5NzrvRfBv82WJV5yAHU9wqfHbM5zpeZNxPVuShaYPUV7eDUgeVam4y+mg8U/+T6A8g/MRTruGQKQD4JlVMPC9OrZ2N/QwR9f1UdeTWntmQB/wuriCdWhNWE1m2PW5PnA6rXDJ10t7DTPWzMh4d/brxntNHVQs4kBc02kagUNdZmBmVDjdoZlV1OWkoGHOU8osvyTG6ySQVz6nz5U1JpigToXDMljR1QHFnFUnY6nyARX2nwEbGxjabMq9hkAufPtzh8CM0veC8nH24fRNsLzfEWSHpaXW0AAAIABJREFUTVWiqNwV+jjjyZxuCRJ8PaF/m/uFAPCd8XZfJdKnB9/1Rd/YrSnX+2+weaAI2c7Zjv8uhdEaQHQ7eUDH2xDU396j/fFtM395ysX7llDSSNcInr8DZjDlwMO6/QW9d5RSg2bogwTiWxAe4diDQKh3mFkgAJtTXKTxPzvUyCvwgMf4M1j23+XTLUZ/wLo28FDHRoY6VbgRsQO4EsExSMzkk+eRdiTt92maT0jo4QSCYvyOJYFMN3cDOTHHCcZVJ1BR5/JSitZEHx2ldZDVjhIZkK4lJSLrsSichIMvwfgbng4+Q4DRVf8nAycRHNeTpvpuK9bWDOdN/NRF0KB6iROG1nxnxnE9oYyUkcTgoPeOta9aB93KJakBvQee9vmF6brYMntphi83fHvgADYwr3hUQob1+Z7HhO54U8iMel26OioRjBUVxYUh82HqOLO8GwEETfPmFR6A90OVI+gM8AeC/DEA3AJo4Ltb8N++Kv4tKk8uv3+E/PdnNHfSMBnZ9apeqrF/I9z+1yfc3Nygf75HrVX3TBPwUrCAjEYCXBlVKsCPKgsTWYR7N5qjY7q+u0Vpj3i+V2coxU8EskwGDML1mwPWlxNOMSMyAZ9U7zdlFjstSZ4aw8bDFog4PPTf0P52w2dxIH/O6xM/B/hk3dQOAi61+e86/oMN6K8wthePSYjyU29AOO6nORRPdl8YE/QYxlTRGOjkgocaZsJMoJqui30TqPfUidSQXwzrKwjP4wCgbziKiXxeACwXRwkMPAJ0F8R/T3T1RkNC9wLTQZ61E3QtKbD2zYlPCDSt8eSAZD4gsnkw0txLbnUy3ewb4y1i8ASgP9lz72zOQ1MwV1SeBPzOCbzd40xdKJkmg8FEKO+nAnS+cTcZPzpiHIZcbmfKPwIBTzb8W4I8zscoBPJ0brdWoSTy+60zPkdixDnD69gNYNv9uUiXIs4v7RH/ZLzBwDNKYi1UWKLdGM69HOMyXUVU3fKWQ6HZn/pkn9N4Cxjlna5de0qRwACWd8q0jSeY8UMgeAPgJQgQO1GO74xCbwCrIy4iYFzZOqirwUjjC8gnhlawEnTDJawNqILV605bVGcnBqhMfCCnzTYWAFfvdAe3o469HBgFjHGaBg8VYrwjbtSaq6W4xpUHrwOqxN1zdV3gnEqSOf9uIBGQuaRqZCJBlfEdhG4pjJD6Mz8vc8TzjrnOM2GPm12sBRNkyJtzvOIM/BAQSzhFuEI9DNdEocSPvWbz1EfH6XSCG5gGKSNUlwopppxlVoM8MNNjW1u9saXayeMkY6zgTpPWLzPG8LybzNDjEXl+X9Yd8rB0hSRAr6jSgIVRrJa1bjudD2KtLedL6HArXdeQC2NZDmAqGB2QBk25LV7TBxvByA0MmekN/OjMy54QuPQSoBShyghu9xIy9fMegeSp6zf05ByOjB/Oeu3oR1Be62shBrCgry0Mj4Gf4bAmmzGKOWWIGE6VgVkfnXf9km0/gKhbF+3b4tayhGJIjToWUVmqpZma9ZQ8VRQRNgb0YhHos0yXbOhsZNooVSMSnHcl3/cSdfAGxsQDc/GmwhU9ssWEkxHNoRLTVJJ75GQiCVRIszS/hhcSY54bnndqLc+NIGUK/9GH1tRqbkC3sTCBUVHqglrUGcm9lSMyMjM0AbYzmmTQACwqTfGV6DhiXiYMTrCWwO8kZsCjgTJ4F8kyDXkpwC4U/8MEEFfasMEhF/VIR4pQzNMo4qnMFTcoHof23QQYVZS5Y4OEsbhy0f3EGQZ07BqN3jHGdAv1qJcwNnMJBQGR0Ueaa8n6kDK8QyDeXmsAD4xBiHrCMnRN+4p2aujrGtkiCAShAZLpcpopj9ZG6zNqvvdQjooIuDdwmQ51Wh5D/9RfhsEkYfhlM/7mo/eOlTW6ooRR0wzX8Ij+EeMWmnXzdBDGIzrPJgIaqrBA3kspXXdgEzdupP64QtmjRpA+N57ZgYccJ2enRAo87ft6307Q5Nyebf6lVDWg+zy4AT1nu+BpSBdTXA+LitJxIBQVHt0TdWQxI3HYcY5oholaqhnVZ9kDGV2zKmRFiMx+B1vBc1yZhwqaXDQLAJetsX2YUn+IYPQVWXEpPm3E2EQOC2bKVP+IjEY290QRFeN72A2eAMIAADgYqVLfSUHMFrPWthsCZxwdLziTIF0zG5HzyKVjSMUYQw0bYvy9480+pmMoKz+8ropbijlnUZkOJxm2tkb0iYuxiTzaEn03CKuCyvaA4b1uKWqHGyPg+FsiZaSYUghkUR7wvSxoZrBZikf5xKLpfrXMGEQcSjvImPRAzAmI8lpR4MDpQCHB4hAlfgrzCGcfuXDdhMSAIUvnPtnuSY9mW7ZH3d6+4cv05m1Evj9ModF3fjzzMcYN2Bokx5O5rLuB7Tm+Cwyd7K85LpDJg/r2FTFHjZIMGLYvRGbqdCXAyNkFxOYysssZXIjNKXmWFKJNxjHX5bixzry0Jn8a71TlrLbpazjniFJHRvesXEEhFLbsFmWjCEa8zbFq+uTFuD1MLA7t1DSAO3ul+9u9TBSPmeMxbK1tTS8b0/Hrx07fc8YY//T5fPvklfInvM+xZzNcmdl8p5eYQRU/6koeKF04d/7zZ+PIkeM/amezFyXthHx6sxBy8XxM/y9286cH7Xu329FTmIrDeZ6NQS1glqKOrD+vp9n2mNH90XGGnwB1EIY6RAo5v5DnWIIXBtSQPR3xuhnYBaVaAAOz8Ro9DCFqRye4z+YQJLlRJj0AVK4egjaaZXUCvn9/jv4oC0cWVGHjtSxLky47zoMZ6AfcKSD2dIyJYg6z2CdBq8XmxeFdDexkciAkzU/iN51PmPyXzZkM5UuN9yq1oD+3gE9PA8wAhCdfG9k5YPKArbfWaGeDCcWjQwaKKU3U0XUaQPcQcOncz47Mr5YPBPkmYL4BAPTxCMINvBxevMfkm9B3wJ08VC8w2jfFyTvjeb27VUdICI70MJ0S7HD97F5HmtvIul7g1kQGhZX9vq7lI05//wr+7T2G3IP5AwiaCQsATtZ+DpjyOfxOwBtDMi47OB9JqWfD+WUZGH//GteFCOOPb7H+BMLy6T2ABzC/BxCqMHQI+hdC/XQDIsLzH/cA32PwLiKV8pt3Rxr8M+2chnZEyg3kL5+/aYY+PKADeDEHmeuPN8D90+QvhHBtjo5rcJLn8+08iadod/wYKIgEV7bnQcpTMASNGALXxWgkD0Edd2g4X6Vx5CfjJWWoLICh97VW0MyhWwYgFvXtcCFQh2WnG2P0cPbtEJBo5PAKwXF0PL8c8XI8Yj0esa5Nx268T4Fm9jtBdQQrFD9wa+DTKTIy+twPM+q31tCaGtP70CxgLnvMOUTSi5rxvHDYBrYlA3ewkGVkOKfrIXcTGTrfOt9rsilk6qusL0Qps2OSF4cMUNcspq01rKcV63pyCgMQRX5VVOXfxpGwngbouARc0N1blP8+qRy5LMp7/f4RpX+FfGYsder7xud7oBS8/T+/gVnLjR6ur9F+t0ymHZAxUGuF6OxiEUJbjmjjBXio4DpQSoXwCyCM8eUR4z0w8E6zU9b3ONG9Bf8qziYZpu8ckAHU6wPW48nmmkHkjgOWWj7Jo8dTw+Gg9HT0prpkIlwdFjw9K13kcoAGBdj7PJunS6QbXm239iK7bFDpe9ZvZDjBVi76dx3/wQb0f+x4vshZ/mCaz6REY9pEjeiD3EDjCi7/78dLt2+VsY1IL3gHcevrT1uaDOSUO5IAc2EMztxcEm9+mfmWsy+v3XB+7Kbo8ju3UV4/7MrTD971yhz809Hurx6OFgR0o0RWHqZkkw2Fr/X6UrRPNjyeH29gBQF+oXd7kXN7jXANwcvmPjdvCs77famdy+3C6M5kTGc/VKgfeAHhjaZctVRK8l0/swJTnlTMKK7EJS8zwKFMrRZ9XgtHyk7wCbBoYO1PmglH7iYU6Fa29cP0WBRPawtEii2PQFcl7gImQbcwIpIFhCOAAwSnIOWqgB72ek1fRq6AsXkCiUa6pBSaOWXoj1d5/5s26x5G9IQ/Qqnve8/xmglFxDOFyy6BxQ96UgOG/D3AhCkcKIQsMgHFFeEwOPG1cOP4dJAxhsfXzKLTyHIceb1o/c4mfAoaNCVwlxF10JaxYDksqHVBpZqMKJxgQtvpo4dAqky4mCDB4JoiMyMd0TwKZu3cGa2kSgbfZWLeiho13MFFo+xqKZoq3pE3Q6OGzFDtcImh8EcAaqlKYJaKthJkAUabEZ6edjYigckdUjCNle65731N/zbHGU2Yyu2JOS6Lx8Hw+KVXEM4UWXfUi9LVTZp3VYijVtDoaOZFGvx26u5Eu1NAiuuU34MJmzT3jcPnfk4UdsRgiXFqK3xHuCMFW+qjUooZvyk+qZw7BQGpO7EmEw4dN6lKBrM2VjFlcx/wkimRfokc5dk4ZCpwQ3AQF6BtBG6cheErmXNGRBqleElj8Moy+jnfI2pfMoY94FEdYdTzWY2mzn8x6zzWqs4mLsT2qItr+HcuYijpPaIz1jr6LZuPCQATl+nnvI8NtXeQKelUyJzRfxzVOV0ZIOlTRMA8I4xducU8MAZrXzENCSKICPFILQ5fy5S9AwQ2esJm5KzmqBHK2ITvNG07hRNA793S/6sgXNizEMy5cN0CG2xxwhsQVQAMdFA3AyABYE1PzwBkdAwTxIfXTeMZcf4azzG6YB0tUjmP3sM73qNi2PC6RxkOEcOFyoGTRY57TfMc2a19VwP/GAONnGv3+bQ67r6ONpezvEYCditxQD6oITpuv0tcjSoT9wLqMW5KyA00JokxR5haF0BgCFn0pjsGZ+uu0ZX5DBlrpWvHXGJPOl/kXVg8TWDQEH2pO4JoWYkJUzo3goJdqSyH41DgZiFB2/eyPsSays7xZu+k0GNRGSIwp5ckm5E3aXjPWDAvgxyvQoJXnnTf++h0SSKrSXQvno01NNoOOF2atNEV3Ni9m8JB0Z1iktFZZqYDGdOZRd9vXKoMMzYCnBi1zP91w4XcGWJRgVpKAfByJROedL2G8wtWAsx5bxHLuCBsTlsUSvPMCxjXCee9xUpFhJOXGB+QibIZLFzfo+TAtJ1+806xFgTKaVbaKgJMXtDuGwk3BozbnBYidZDfpnjaHDqvPrLUF8epwce6A4w5W4hsDN0KmhJ9p7RXvRJDZo+cQYnv85T2ZBcAgGwYsL5k9kns1T51U5J15aMXb8rmrc3bf/2wvbEXw3MGjf0cX24mw5dPkOi+Nzgic1QRGpP3Mzw2eICGZmqaUaZz1PuOxJQ57kwDkM28zPmMnTC29X3j4LSwfo0UXzt8ELT/SgtgYLaD+1dmSWUmLb/kfMD8nHJHdqi+bDy/xAddOC5eT7Tmh9CyZwjzd92XXr/Wz1G6FoLj5nu6nj1K8735XU4wMgr7CYDL619euRE7aJnXDHzn6T1+y+cvvEASHf9nj0vtbGAcE34mLnAeMDAiIIgsKuh9om4gUqyT8a2lLmjNzH/G94beQ2D8vtN53WRjKP2S3sOA7/NLRKluN9BOJ/BSNb0VXJ8rABd0q92bsYBypjNy3J20uLhTm8oO35+POifBx3t6bY2sdwcYHRfjeDxBQHh5secMZ7kZvRjND+M5pnPWhtyR6qSKTerUjyAyp+kybqMHnWccImpEs/IdqhMwuUG0HjyRZsG7fnuN4/EJcpr7lKJHE4/sYWVriPY5wMzIYZ9PX7dR05dg7lePDLmC5JNqFzjVQ9eoX2UGnTd0OWj0gdG6OXwS+tftGiyfbie/qC3j7aePOP3tK/gOGF98n+zoQcyYyUoyf+tNjwBujR5s9Xf6vPbg9Mc96qfbzbhfmy+/9kbO8Ye37wb3zbsoZf+5cD8HrdR+8J1elM/zvW5c++XjlVvDmX9H+7toP7z/jQiWJGnTFHMB3d6A7h9AMsuedgEWQzKr4f+MQ8Kp0/ntdByM73C8MbzdAdS7AeIb0HjE+DpAfUBGx4kJo2ikeoXqKE4yIBVwp81eOkptarwklUMKmVN+V0dOFnP6wdRtD0uh7sGKVDvQC07oOPaG4/EFx9MR67qitQYiUkO56D7po2MVjdpvDPDoaJ2B09Eysyn9JMOH3p8u3Uon2Ro5OTXwIJ7Zydick72MWvKWtPXfTXLiCymdOwPcJC9lOTLkJII5VsAi4acRXfkLmBPR0PlZV5xOR5xOq9KHRfUJL32g14ZmgTD9mdCeBXz9DNCHcNAisUxwtWBIQV0OILoDfkfKkFuAYiVGS8WhVtNHF6UGmnIUXlJFi7yaXFo7+t8YshTIl0fg7QLCI8ZXRq8F68MA+iP4ww0IJcpG+L4Qm8cKqHEbQAVhdaEAQLWa75t96NO/wSNKe0J3kpna869T74sL1+KGBA97kMAPjn8RD/SPHr9mQN9j6kt9fm0cmWDI+W3nTdPmnPMVP5umPUtO8PTotLnDyPo8e4FBdRTZh2KuWVF6Nv4jYu9M4BsAV0LoROjpiTdCWPG0zeK3Oxqmd1cIFRCUD+93yof5nWCKKQja/SMY75yHuTDP+xnD9rfkX1eTyHiq1AvPX1ojN6xkTz16RxjfRfUzdq7c8IWnERvL1eElbbBQ1BDB0xLPKEOCUBK8nJ/b4+2fABYZR+RRQc6ihzLzVUCwN8c0TQY337Hxgdv1yZUwHql+SZYK1jZxEIm9xvXtLYYI2qN5VwazcW3MwgsON7c4PbrX6Vbkc89Dsu/niW8FC67RoQYjhtURjzkflkbkGZEhGc9QtfIbzTxARyTzEBjX6PgOwjUUzSdTXrkG86qZuJhAVQkTU5lKM585AVpZAVf2kUaIggjrepxMK5F52sLSZmsKrwFds1IsYoUJRAcwH0NJ20WVdSo4nUA4AFixfn9Ro65F7LSuacFhimGXLGtVxTCoG9PmwnFMb1rr1/Zsxn8SOBMymUDN+DijaSLSSQpgEXmjCRo0HU+hYlG0chHudqT54lUAwMH2gcN0UvorXp+KHp6rfNZYKPmLKtHJ1kPnExaV6++xyLbmNYeHeY8rxmUioGr0bl2q1UolhFKTGDxmZNIIY5QyYLVqVgL3stT3TWY/cFKah21UN1l61GH1MKv2nc3gxcVq7JIJwYp3Q5Dv3YxHI7wqa1kUnkyR0Cx1rohmXvC+RfpsU9gq8BjFy4A3O64bwqJvJjBcWnerf3QRJCyllc9DMlJg3yRloWZD4uYDTgaELLCqgCztUiHL9iIAyKMTkhKAZjuU5xjJgzJLwYb59dtU8uiHaNCSKSN8f18t16ACtPWksFrK9MTlglKLGTfNIagUwzPVzpUNPoeIGtcLaSSBTUxykoZV1VMDn2pDQBaJTGnYGiGQhubzkiI9ApJ3qcyzkUcNHoZbwyAj23S2+R0SkxacOSXkIqQGmyFmaBxau7CPHnXrHR/XWnU+TXE1ttpIbAxbDraSaBtNY18W0j2Fo9+bDZQKJ0aLTOk0YVef3WRAsHRXbgBLpqVE0wznGS4szBjMYBobxwYR5e26Re6Q2L5MxptiSISoQ0uYwPBVRa1VF8JS4s3aySpc9q6G9NaaGsgAy4SwWzv4XtFoTI+0J3imkAlOMgRdOghaJ90vClToHE0Fcle45Ui0aCaH8BNhjBa0FxDziG/qHd87qGl/qqX+dsOkGurN+YAojOy1VpCVZIkMAqKGRPTJoA6B1tAsRcHXlazpiD3jykwHGl9Dq4soY+41V9T6RJdaUJAU5CLoPc/Blg/PaYsp7QFdQ6f27rzmi+cwx5p2nsn4J8Utnt7O8YXyftMg7cN0vspLU7B9Iu2ZzG9P9CLz4yJzYWMh764ZuJlB5HWwZbIgI0VwZXxidNZLxYjTf3uMSaNvivNkvrfJHGI2hGzyBk5Pfd8GX2d9yMZTcSTtEJLxtfEMMrzen9g7LMpPYJkOBAPT+VMBWiJyaEDpyCVuTHpHN8Vxt0gYEgsMt/lznD4g6DTUcXxYel2o4xewgkuFF/0oXGbK8JiiSawFxksnnBeENmS6ZHCwvrgDFTgs6ROfpz/DFFiq4blaYt8OEeMTjddhaLpD25cZjt1AOR0oExOSep4Ve9odj+jwxVTc6s/lJRfIjLD3Bsi5iklLYbBNI3VS5rxscHFSHM107j4O6/9+2hO/s1GsBMwqpJ3Frsd6WbuXtqwdXl8TgDpZSHIMsv99JiNqLpPuC3/5lg1rkXwHIhMLbL7zZnAHmm6OGsX7I4arZ/9CdsIAYUZ7ka9pZm58zn280tIFn99pqqBi0bDh8CKRQj+P3XF2duigNKaE8fXTeU8IxBxyZ8gGpT/kJY92t0b6rOvKK+C/g5nC9vAGE2JxWKH9fVmLMGU+5asIkSkh99t5JINtoXNj0/7YwEzQBVvThIfj+JHDuC/pHhBfmYafdYr2J2T3O71GZZn9Tvjx2F/t39zFEGjJsAwQ0/gqkz4bfSBCZKzL+1jPGA3cgI9lmjH4dP7EzdalLuhNK7a68apb/V1xA3dEl3PgXIwpCysNlkk/g58C2qrRm1qOiMwRmNBb9yFaJj4br/XNabiWsGoYGHj6/t3eqXqawgsMZUNEUK+XJBf5LA700bRuuznYOtA5XtE/0z0Np2+7ZTNYZwNcGe6IMOUVEscxmilI57EH7QGUJ1x7A4sYTde+99En3ytWr54OAI4ILEOq6yJJOldtFR4a5pmJDElhQMfNhm9bV4f/w/t3ON4/xhycgSidn9+Asy45HBwFQJcnkLzd3AvAMhpoLXaVWXYaTJp8cj0c8PL8dwDv4t3lI6HQDUqpswwBTZnx6q8fNd02HnD1+we0fo/xWQFjjyqcfPAdgM+pzr24AwkQBeUMDtrfvwVcjs8PkE8A0Uc8//eXPFWa6RZAo3kO0IDCiTm2azf7JXgnej6Sn9nhOrkBXeVrW98xHjC+Eg6/v0f/dI/yWdOpP/3xDYCmsAcB3yMd9K7h/cJeOB18vp8j4Gj433HJDby2vNMR5edfvt4DInjz4QNGf4A8GBtg5EtIo9ghQEv1rIK08aQ9NSZQ8RAFo2Ac1R0BeGc6+LegD/eQz+o03gFlTpolZwNQhDTMinSGhwiqCDoxGiwKmDmya5DLBfDSAzY/FhUe1FYYKIKjqAH9tK44riYfdzWgRxDn0LTsDQKRisHDghYGZJWQAYMDFteFDvSecZzDkpguiuGlBDXIyGVtczKy+d0kcFYF52yJ1BGQxSLrSdebJiBj7hFROiN2D6uGjkGmurTSnTnbHGFmDOwd6/GE0+mE41GdDerooXP63geWUlDNgL7+X7XnvRl3qqMxBRz/9gHL3++BukC6gIrTBs02qGXGHkFcUD8RCPfg+rvCYtcsaM2CRcT2YiXGm798RPvyiOMDg2rFzW93+HZ/j/75Ae2F0SqDbZ+cujrNDOm4vnsPXlc8PT3PjFJ9GA86UEtFub7C+vwCr3dfa42MXs4Tn4wej0GQPsDV7DFkTsoyA4TI9qUGLvDMcgsk2r/d9lM/sEMEG5khnz5HGD9juf4nj/o6G/br3QqHT7yCI0UwhbK57TyRzf6VeW/9M8elNhw/vj5qq6AgAiZPKTZCfQ4g6p6cMTrQtPFxp8z3dWhK9x+JJ35cX7gWgMdlPi+Jj7FBDYilnXn7avt//jjaiA5nLe7tLZePNONvaZ7Kl1/n+KP9jYxx6YXGjAaFudTOjzv6ykOwtTyHVf8eKelg96Xfs5Hzl4fOKTX7Gp/xq2tJMI81Qii1wwvduH5nuBlvQ7Goz04UN1EYGbN6hXpTII+aSr89fUfFNcpNwfiuUa31hiOSDBB1lHAYkdwaATgii2GuRwMdrQcvINzoeCxJ6qAjAPXQW5gj/XYofW28k+9KAEppdKYsC/i1DRvp82WuYTACBEurTE4dExO6hL4cZMIVNajPl2g6cjNmuUHEmYBIk2yEk2KiDGvux5KOWU84kyZd50ES6XLyHbnXInNdgsO3+fAssz/a3OfR50ZID0nhnhTT3r1JcP3pOKmMote242RUFyjDwqZ4GgQUFaSFVfkHq4ELgdUxU0Nc1PQiwlIrCILCpOlhzRgOKEPEZQBS0NzD0+snEqMuBbUuypTVGb04+lDv5s2+l+2H88w+p1Q0VeoQjWrnuTNingSRuk0V+x6VOmtDFdK+VKropNHnRKuCgQjUibXHKnn7QiMi3IbMyCPt6xaHhqLZvku+7EoWu3Nk5vYfwbeJcAWsbgykaX5pXlLmWSPtLEO3Pp+Zbztm3z3vxITgjKlD+Iv/97/zfAK8FMNXRuxXx8EUKa24qDGOSgFXRiGr8WuMfjXDXqQKtRqwpA1v9lrgbT8fjIfBiPhaSWR+AEbM1Z76uNHHd52AAi7nbVbPewB15pmf8+D9Emza3+IpwKmN0NA6TrYeYoofse8a1a1lDNxppZYCz0YhtncZniZ74ubYi8PhW/svITDMbCOIKPJ9n6eQAJk0O+qFi7XpBhzjbBWd6t51nsAhKr4xAWUqAJoQaDgN9ZrMgJdj6F3bKuY05EiWzFmLiU3xrp0tXLAsC5ZlgaaTHrE2jns93bvDn4iqmVWhbfPCU2nEJdWZJsBrVitN5Y3xNYxzIiBzwhkQrQtpEeTDDNXMbgilCTuWDcZXI2pZ2vhapPdv4WUPIvQxUHt3AjQj1NM+nJkgNNpfKcSw0gGmvLWVHGOgVksLb5EDnuZzCynpTK7VCYcPdaX1eQFgwuWOfgZfQuBqY11HMIKBgcj2to3bmwo64/1iQmUvGwCjsBbNwIRCRaM22GCJOZQQOi2uyE7OAWasI2ATNU5wT/+M/wmVnE/OPMgkjpL7G91OznK2D2shDGbA6XOkvzTjM9l3M9EpTBlsDYGUraOtKladNmYuydI5b3grXxfPLkBx2uXBGJloEj5XfM/D+SE19vYhkK503edPQBBmo9tKVWM/7g/aZhQKAJCBJgDLxEl+WeD0UeXZQZqtZ5jBwRgDDBLydBmnAAAgAElEQVSUMSBSUBzebA9zZHBxGkuWKWfypD4fjvNYKES02OIxX4Bn0gaJRbYYvnReaDf0MB4brxFZJDZbaq4xYp4oZKJo07Ng76Bz7iVMfG8d3kRrifY786t+ngiYPBFFeQDYWONGSZHrvv+Itg35vDmOgE/QZmZs+1HgYaI5jxGx7XxlPBYEPPFISCe29PvskMun/aKk/bI3gTos7l3p5xuNrhlAhBM7+YLv1t35Ptt/4l4jxhsB5gyVO0zeHjyb+9m8xvrmtY8IWsOLQMoi5LyU/0utOXsCdW6B0wVnY/w+8flxorpzyMtrbGVxnL5vOdXzBdo6TKSNuT/CA54uX/d79q+JQYo6xrwKH7NHcEbLfg9opKFGpqcGBJt1yFy6gpph9U23Xu/AfmQZd/3our8030+76/vtuX/vhdNnvy+v4D920O5z89ZNoEzCR34LE2jQnBvjDVg91iBw+mh4DyPmZ75fnYJzSQ4Zauj0DCxq0PO9nbK1wP0xt7O8yfA0HLcpPwAi5TnRU5YN77fyjIFHkPca4p0+1lM/oZaDnvO9OZJGW+ytw+dw9lVhWBJgmQ4BApLsCJccvAWR5lbES7rQdqs6XTXedOrAYlW1n74XxIxVzEBvumanFbKUNK8TS0/j83yh6j8o8M/sudPSF8i4BorxDV3nerlhnB7PPVZewSoXD++N/r2DwuncH44DrKcT3gO9ZNq/3dnlo+FVvpllo8ZA//qIencbkZq9Nxw/P2CQGruv7gj1txusf9zPyPvdrK1fXDbUyHV8egDjVu/y0iTsFEOPDjUmLp8J/VPOZbs99pj+jWgq99eo9hmfg8kCOPkwcqvXZFiE8Q347kmdkesH0G895L4ttF94KX51nR0vpP7a4okgdLW5TafOnAZF/A4FT0HaQYSWWq2bAetRZNv/cFQBUEksQ5O/853aiYbr1W9x+AsAEfCXh5B/TzTArYOEsbK7JhTr8QCThD5CdZaKD11/EFkHrW9uBCabF3cFOY2GU2s4tZRyfXQwE1bnzYfJuQCA4Um9IKLlj6i7vjbTWnMEgvPA81oEFsCM1vbHlj6diFGYkm5ly3VQboeMJxOAB1m2WgQeFFVQaNAkE2RoLfBSCJVnyU/l+YFSqgWsmPwOHWNrK9racDoecXx5wWld1YDe1Rl/7R1XtWOxEnhMwPVvBe0rYTmt4FpV1mR1qqi/MYZYxD1MJqViuhcBwLj+60d16CqLZaNkcC14+eMrntcjltuboLXV8CsKgWvBUhhSCVdUcF8IVBi3Hz5CiHF1POHrf3/G6f4R9fYtGK4jc3Y2c7kNgpJwp86ty/viThm2PGETMWdux6Sb/Z12oWex8Lirf+Z4ldP8VzBA/4Kj7sOFNvUDMoBPnmozosmYTrZxprPzZCn2fIoG1MgS2WS2IqMqG6LjQm8Y5WbvINhEdudjI1xeGp8bwHZI3zVCAoRiNfpBYlHjW0/B7IuzmOLe3/Po85DkhmfSOhqvpZuvlhrEzEHROwKwfumoHwv2uO371y9YcAuCR6oXFGIcv8GU7tv5yGhMvySxNU1IjE0A4AjQVUxTTBRwLr/HJrOz74ICW30PfZBv2YR5zPu9LQJ4aL/EQtg9Ism9GnMfgMxU67uy6AqZSou9J8vP0mHN9JlT6ZIjacutRh+OhwlT9A4xEHkypv9GnxmPI1raKHFiMueZaYh6A8hzjE37hUCNpDga8wdwejCD81sKYza/JYznF2ic2hX6MwA+BjPuQqenn1UcbmmDCeCbYrXAdTzEhMM7S2FlfWNLQYPhyFQAslo6pHih4g2EXoBQuruxf66h4DuGvAXoZJG2FbVULEvFsiyW8trSHqfnPAMBW7qSpRQsS0FzuCvFaiACFOlHwz9d8RIB3Q3KqAAWkBwBEfMsHnBFhqo9zdl3AKABGQWdTjaXZeJIY4gsXleXjEsIUZmZcxDrO2nImSZFVztByuEGNAmYg1DmbkWsPjihwKJzTPFSuGIU+v+5e9Mtt5EkTfQzc5CxKEJLZldNz5xz3//B7q+eqsqUFFIsJNxsftgKMEKp6qo+Uz3IDJEEQcDd3Nz2xfpG7eluvhuNlXYas3UAoP1ViVeClRI34hTOMBCykgCIzVEU5YrJDV/KHhwwAQGECSQroMOEWAC02T/AWRTLskIWq0CwjIHD4Yjj8Zh4o0JWmkiQuAul5hzwKEoQVBlTzFjvUvqGD6oIslS/wjIwNxTS91YL/IigjpBNo9RO9FAqI6FayXe2fbYsCw7jgDEWLKSYrCZ0atEOUjceiALT+l5PEegUExbXE87eZzodWxJ/UvBHZMeg0deghRERWnQ/HbKhYYeVb09vu2E6T73C231vlDFdN99ZdYEBOa8AtQzPxNB675KF/1YAGog+6DxsTaOH/OLrbiXe+kpq3ZfMqcognFSwDMZyXEyAd+fkOFgGOtwxFNqQlXE3Nkwc/aPs1uavM0QyPPTzbpQSKHh6kbVpZbJ6f2CCyyQTrpizy3Ne2r+sHxc8vH+3XxMKGiIVnJHn0eTFLFG6/X2ar0p7y+tnc/pUYJRHMzvdM+et0xXm7Gu6Sq1K55Mk9VRSgCLqPxwbatkA7KUYU1Yiygo3IQZkj0LxQB1VczT79VGZglXdYaSeKevGxFzDwGKfI7OVIVcG67AgIUZmfgyHq7VtMCXKAgq815iXFLMMZON/o2Wgh5GrO/812nUowDywLGawGUSA97W2qizwUvXIcpLkuGzR3UEfGj9qz7BqNGZkeH55wenlhPNqgUfDkTp4mriznx1nwtEjrvhHET8iyuxa9WtJLbreaI0pslFNhMky/C1Tv1p4sNi91nX1tZ2Y6hlRgYM8PHuw0xBbF6aSYcNxKq7nRM9L8WoEWeITLqfYDs29lncnQDMjBeZI1zJShKEZVDKVoqokQeEl4wXMCw7LcHmg6PZgm1fIVTQIywgjRJhprdyfiuy8W0nlUwEw3T8yAkqGYRptxwfkNNcQwR43ziML1CGhbCNg+LlABZjyjPV8ApRwPC4pgxl8nO/KhCqBl4PvPM4pVNsSbzEw3YDuvN87F7YqCNSEnNi3pQsGDZN+ztedEMbmmJ87AmQCkVmHgln26/Q9NbK8bcgbHpAR8Bcv32y73A04RjsEBJnAugrGYrRvzgl4hY9VJlYRp7lmrLIqCZYZYUIWgaZAiDHJeVGUm2gsQpWqSteOFhgfcvmAjKBoGmd8biYMGyoEuBnAZChNLGRy45Tpe8JaeKxT3EHsFWlcVsvMyUAvCbIknimD3IuGOKjKaDE2dbqdcnlb+1a1JSTb7Lmewp8HAeWlFcxVaqUWj0wdwNc6YOu8KseQAQxNtm8MfENnYoNpC0yooaf+YxK9Bf2WjaP057weSPk25qRdrnO5I2HYhpZy2y7YXZRcTvWCRwJgltN5iAJDy9cRRqnuHW2wzH0ScHMeYGChqpDgMFW0+3jgLhFQjvEmttJOZ28HmXUf4UAMLh9OvZR1QmZImh9XpyZZVTtC7oam/GzVVIZVjYCC2YJgaCYWbRAj+FARW8RCFvDa8zZHMvTt+ddE9FgbQlV0i8Atu3NZGEImifWJoVEPRqCR65DttjhaNFAmjsd9Aw83uifQcLHmW1Jrw+UGpdhBUVK+KhpRxm10dIzHaLtnIxk7OOnufBtZO0/t+83RqqQEfvYj2Olm47b7BX6H/aLNNjFGXaKIWcoMGW1UmZRM7YzP0SZpQLGmrU+hSVtT/oDJBsIKWS3gP9p+EA8QGHOefegMUuvly2o8ipcF8yQJT6s0NxFlzSP7boqNKwJBu4yW2YjiGofzhrj28fEJ4QRT4SJdjk/jEEGVxfMNFGvqBmNRnM7i/ceRsShlTyaQjlp8Mcs2uUNocOlphOglHkvjOK4EhbVGCrwL2SNWgFxOtVjWkmuxKOTkFTRevEu0BkYarIWAhaMVIeeWMdnW4BwJHSLqPODGYDeLBs35hDFucbh7xPogVruykZayi24xtwfkE6yPM78vW5PiMfnhOr+B6F3aiQlRTcuz+V1OiLZOy3KAkmI5fjD9Yb3D+fMDgIdshaMAVgbG5wccFOCPd1g/P2AN1AfAnxXLx282HrJMbIn5AVn5R/28AODfgOWXBxDuUTKDWSKv//1XyBTQX34H/XIP6ANUH3D1Z6uf/vy/f0tJutOgV2mBv258OX7usfM2AO80gts90dHv+/jXryACrn4xKfrbf/wOBXD3P37JIFdA8US2x1l0w6JjLWvN4Hik9QFI2ribRruHAf273/fGdevI+g6e8Pj7FwCE20/vAZl4fniEemKRQjcOvj4+gYJFEmYhBy1U3JMALL/cWQC2qmUeu14MHqBZOurygYDPlNVvxJ99lgmdxsOG2zyhq9F2rwJFXqVpuNEj5Uz3p6XtXBg6VzyvK17mGafzGeucWLVsFTNkEjU++UD23MUz0o0Nh83eZZ5M+3Td320AIUcVzrn9HqgxRdVOb8MVIqnR0y3NpKSphHDqA5StqggoyUg9yN9xZPgfIcbj9IfNQb0cDpnwZPbOifPphPP5hPNpzTL307PSLaAROAkwB+OKDc58vsP6/BXfvz9hLO6DOBwAVaxfFapfwe/OuBr3mMo2B7VWZM9/+Y6b/7mAFk924AUKk0NFBCzA+vkB4+OdBSDwgP7tG5TNlnvEgIyBD//r30FfPtv6imJdBSsP3P3bL/j9b7+DHx7B93dgBW6vj3h6fLZWhxAcFFA6YM7V2q55kCl5hj3BEjWuDgeAgVs+YJ2C82r6YuiwpICI2TqjQm9KxCqu8zOEZqgdF3vMUQa6KUcQZGAb2HspeV7KO/83jk0Jd9pMsm2M/n0XDpMIluEcKlZCgUKgdcCaV8Ii7adAdGZJhY0A3Kh4ClpkRtN+WHlIzaySLNcdgjMUNyA8p8GqmL0Ro7GJ5tkw6oRFGDyxka9VgTU2fzJ04F5LNDQDjgsCVHanuP/Trip8HDfaymw0OMRx+DRw/n1ifAijlJVsAAhnfMMBDODWynLuxgdsnfv/CP7tEZr2X775w+inYReZg1yTq6Z9wIWdvK8/sBSFwNLXx1Nj6BuzzNU17h9A4UIISeQvPKXNt86cFLiP7GFyw3IIpH28zojqtjWfPQEJQ6xWLYQgWcEQCTAFJSLoCYBY0INqyzZkYLm7BX2fKdhkwil1iBQ+A4rxzg1T/tXx/jaFWvL7Qj0oRhXyzdQDdsMFuRGQmTBwYyVRLTQ1M9ji+QEfm/sTQAsOfMDxeMTV8YjleMThcDBTG/VoxIA5paMKHJFTNkRzqnNlidJ2M2owc4b1EdYFKiczxkbZl/XFBCb28QcOuJN3dcHHyrzYveYMYcyzlWVLm2wdmpF5hxf9fS/VGPbnDcI6yTVcIp9V4NwW/6PsDZQsqM+z0KyU+M541g5qr0nrj8hYnHA2B02mHCVh4zxH9BBzjPa1M6ei7wN3IPaSiIH46k7vPi52xzuTV+wQMQO5TAwaOB6ucH19jaur63TKrDDH8svLGXNOw8kRmXmRfWjG6CkrsBbekjUzhsB7tGkJ37Yv2TLnff6ViWSCsUKLh6WiyCDW3PMCMxgPDJDzTuvjfvDswnDKTixqY2A+gAdjzhXndcVpntx5NqHTjL3ruuJ8fsE6V5xfps1BzIFk8/DIei9FF45cjRxGj3eQiLVwZI2goxC6Oo3uhrcsvZc7YYfL+8Ov3dDuwIXY5+xl/lp2V9CxwtlUjyxS1hUw8ozgKKtfMgUAz7qIvlC2N9SNsdadi5YFRxwwFgYNYPCCw3IwJ9DCGZABckUNE1NsRMxqwWL+bIrSg1qG5JjHhIKmOcgmK2iak2m2nlMWfBLOeAtWk1lOBfbeTBVIFzy2O8cutz9HdpUodErjVeUEzYos6WwK3Aci1dCM8O648swJkdVwdFomJDGwkPeR8l7fKhM8LKtWQRCKVwLP6eXV2x98HUMZJIDEcbtE2eSpUeVig5GmPZaMCLhx3nuZkib8CAQa7nd3pcTKJE4zwrnMqjBjVrSRJx4Yiw2Z1faUFT2xegEHQlYb6IE94WBMw1bsEYLTUs5XMxSas/i8muK4nk5pTBo8sByiPYUHiPn9pssymqmCTnPciIAdfwFC0Ten/TqtpOXL8zPOc8UqIe0GPDzoK3DBYa3+TwSZGS3ykuywFkk9I0FVvW2KBwqk3O8tVdYVBy/xPpiNzg9TwVWBuU7IXK0KiVpJO/bM5dw7RMAYgEyIcNIChSvh6qXg7QzmtAClokNR1jR2jmbFAoOjZRLCHX3Dy6yzZy/wiN5qns1ARgElYLeKsTytiPzhNKcMF6arLYNxOCxeYcUM11SjwuLBVGhVAixOULIahTadSJ1HcJbtCRrgVCyCWdj2T5ZgjOZtvoYQBbP1GR3Tshim808VK79HsHYDy6Igr1LBWg5nIgLmisELiEMoEsg0o330bV2WBcflCFkUk8+Jqxt8pqIUQb/LCVZOx6A5puZoc6IEPfXrOHRbQraacZoUDrjSh9qxJ8gqTY+IUqxsxh1iTCjOMoHzyfaceIsIibKMqwdJIOegotDVXb1EYJpgCaJGiTs9sN4wNzDcX9V5rdo50zkk5aB0eAVddp5MkMIdtsDJMGSqV++x69hlEn9Fczj4UuX6uCyZ5ooL3kZOX4cHVkmKmt4gBReH1v3DaRFBhyGPdLypt7RdSw+cjkz+rg+VvIuL+23OO2OSaQGcYVOxNkfWqsICRb3fKyxcgT2QhlkxvBJBlPGPOg4pe/gj1eUehKGXGLSMGlvIBHF9wkv9uzBkFz8VEFZxI7gKhjAWdVrPAwvE9kziUSlJtU8D5k5jOcArUGFEH2J4NYoyOiigzlOJM5gxW0VlQFFlTykAnRNN+09noj2i6B6iP3QiX+EPPJhbaCYf7Lwv4JcBny4HCbydAmBtbsTK8EZp4nDSOCl1OO9x+DVZ+zU5nHbn9QLuCBlVSy8VNlibvhPyYcEzeGFpS6UPMkerrGjhwRhjyUopIeYFjrnZ3taIDa6g4I2BK7ukhYSvup2lHFKJmKGMp06TbPoCZHbZbo03kNTd6+sfO5RD1y8wewuhTi8D4Dsbap9nyhqB4yFrtMBzbeNL51yscSAjN1xMeLk7mOJ6P0+mi5HDdujmNhb2Nc9uQzFZuqoiatHX4OViNJ9IgbNXaMnWCARSxjotEDLSVNb1bLZP4pRVjL5Nb+8jThORMmU4GqcIpjt8IgALAJ5PL5blJ4tVi1GDgaq1LgoeLqpYz273nEjd3+ZV+mTIngC8ugs7rnFl1KJpvdJ+k2XdTS6dbmySdZauKZaNucoEofgMVDBfzvlsbTA3vu2B4yCXLcuWGQGzwQ9iL4ZjLXBHVLx1GFkyiCiYbwB8dxzBxole+y3QvTaHgrKTAA1yOD9a1xdbZAC3AFEmpLDrW0IwhyTKBp1ys5duVlWsX75BmbASzPnvuCA+VgWgXoY+s7NhtVrl8zYxMKhbv7b2Zuwaavs2vCa2f8YYOPzpk9H4CchvgP4J6VQoi2mRq7p/Hbz77o9ea98Hr3XsUGD9zSoraV7sztUgio3EEamZ7bhG29h2EtKQ7eLcVs7ZH80vE3IIUAFF0U4qEqCYATb9Z1LRnQhg6aQVgNOOovNEBDfLIJISxqd7sw0SGW0LmY8JOo0v49MHsAJjYYz/wVi/PELAOCrjLOo62orVKzOACHNdcT6dS9d0+23AI/hn8LFcsNXeP58sGcYChMRpDG9kgLhPBLeJAC+nFUxRSYDTDlwx0+HnEw9wL3tm57/D78tsfbVNr7IA7kgUMBl5usPa7gdIC7RmmA3A2tn1/RR7n50ODCIsNGycXgVkeun0MSzB6Hh15fSH8fLygqfnJ7w8WxB/BjA6U7IWIiaLvShhURMjhhLwsmI+n/D8//8FN//+K66n2dP083fgsGDQgH494PCna+gimOsM0xbGh3tACYfjlWdzE1SA9TyBCQwwxq9W3WLyYiXsSYHVdNUhhlPXywFyc4dv+h36csLqLUqWwbj7OPD9s4C+PmB5f296MYDj7Q1AhNP5O4gUMleTwd0+ltXlYH5VdrlXiSF6Nn+izFwHqNlIkt6UkJKHtaot/emtg1znsSVodF5LEkldwmWAog0/uvN//bFsKZkfOYmtEz0DBdrJjKq3K+o1o4vL4Qf0BAZCbTlsNmC/IksQd4UxJd5Svm9BeNqIfsAjLqPY0N4zKBdj7sp2xl/Tq0wZaHcKRIohPhDwQa3suxlI9yA1JLhx8DzuIxR249uPnd97b8qPhPXLV4wP73H+8sWIOQhE7yB4AvCIl8/IErZUfCR5W6rDIYCnEtkBtYWJHScARxdC8hZlo94Be8+Y4xN7RrpGZpdHr80HKx+xfLBoTMvsBs5fVxOEKkV5e8c2P/u8Vcxjw72a1fjakWi33dj7TPXcKX4+Msz3N+I7QoZnAaB7g5V818x6VACXowsxy5+PGz//1CZe6mDsF2M0N7i6vwIx4Xy2bJqAO6AYdwPz0aKFj9fvcHr83p64XTPCtRtSbO+ZYd4jbwFkk3vyXoMA6B2g303ZYZSAbILcs20qL42STofd3GN2UbrX+gBb/9tB7KW7C1Jxj+EORguuYQgIp3U1BufD5UiHJ4D1yudR8BFRTKwQeUZmDJkp3JQPEFZ9cgWFXeA82LU4IXMGXUCBCngsLi+ase98tlLbw9c/8S03qkXtModypblnQymg+F1jbrnvY1s7PY6Kl/0wBm/4OT0zebgT7rAsOJ/X1ACqlNuCVw8nNtSQiDT2bDjWyoEYJX9j9XK/mt/P51L7IzJnmZa8lz0jEFcRZd8JntWOKtNshnc3VK8KWSKyvPb4nIK5CrAM6y2lZELoVACCU4RAKiz7c1kwBrxCg5df9V0UegPXAG2NeAMux8kywgYx6MbYVECI0+CZ2c00sjwRSzjLBFBzNE6QZSC7EBzO3zKUwv80DXcCdWNjlKZThJNQvJyPMGdMg74SEJLGeNU0ZMo6s7ylAuaA5QusTHh1jH21UghpluvDNIFwXddm4ApBP24dxnq2bGPHPKJwRrXPvv80S+tJ3in2pPU0tzJRYyB7my8R+ToYCy1W+nowQGEURPa0qmR0qr3hDtGswuNGJYOxO34VEJZ0NIkCmACRR1drkDSjN2Uk8Vmo9fpMOaAAfSmaBvtqspi6fJcKdpMdg5t1WpAVNnKVy1yp7fcxx7hTOGmZw8BdTwF5fzH/YJHcgedhtAayzFgYZ7qQ0uhicNoIcKON1OcTbfJi4Jf4jWJMgNMxlHMV/nz1qVo8iu97d0YzBkazMko6ICkDIaLfdCg6RFGFpeAeoLbqMVSwA6wiRoh7ThMj6h1+XzNgc9IhRjnO7C+cDAOx0DJrzVMuDLriwTrrKljXVtnCaRqRZc9PWN+3cvRGpkxkoM/MiJ4SZdGL9vSqCWF4DYDLiBJ5M8u6WzZ9wNTljDFg8eFW2pOGyzsesR1yT/JpuPNYvL2BO2inmAtDZF9SM/g3qv1Mp1KENKhAI/BvMaMH23cRNMWNdopnYIkYzcd041XbzcETicypZsnPCgvuAGRaIA/II9SdDwSNiL3HispCTaN3jiRlIiKAvCc1OS/QZi1NZwr57mHJrLXA5Rn44ln9Y1lwuLrC4XQ2TFzM8GJyZvXwGwkfhur0QEGE+zb31SALIjKji+P9tF29I1hpANf2OR20UGhkv6kWHqbu0ZyagatuUOrzTT2ltUcAkOVXMwxjNphrrbMCZrtYBcpIh8GUCSIv72fIYHuqV1cLYhj0AebuLvdxowHuyEtyH3Mmr2AQaOf7LHhQ4EUJqFu+tw9EIBeU0vnpRDa7OYD6KjkobB387iVbhRUogkOTzvs1IBCpO7E56SOpG9d8z/f2SEGrKGS2the6BGMBto2z+pcl9yPxojhw7Lmi2SUH0ebFbtKYfHtOtkOKoJ0wjvsaj9AnlLI6i9E7p8HO5DuL2RC1ht/1ueZl43TnpdP0npmvrs8JLF5CHF4iaq9QTAlnKBD9JzGpzT8CnLTNtT5T/7SHWdDbJueUDkkXa4LAi7jG77Mh861CgX29+TbvVZVIKNfEMCxN/EgnSwZlDyDxsfQGivGlnBNuUHJvdj/2uyZ+TQhq0K+jvrRoiJBrSPW941xsdmrzC3mUolJGnuOER+mJ++/9eX0fJXwaxjW9M6YWGckpp9XNkmYHV+igIU3rh81Ft3DbBltq3pK2YPXP1K7b8RbUtfH8jW1La1n39+42vHSQ9vWJ/RlwRckkEeCU8NOqIxJJEqHDKQBd1wryqZmlrme309Qhg5YEXScA5A4kC/QeYFHrxauEMa0HsMzpVaEMZuLVs0TCce5ZmA3fxT8LAIhi1Qpm1NHkmca3LSiToDCHx4TiMAa+PT7lDhQ5tyCUALnXLFQymGkEMJpsFfyU3POe16bz23VrsvdjGYm3pVORZSv6g9nhOL3KgzkyydqjxIqrl1uWCQH71lmsqtKcoGFtEGUK5nm1tT0CzNZAdH18gqo5q8J2wqCNPJ86GAHwkvvTy38VPyP/nVM038/nh8dOSX07Fw9P+cA/bZIU8zxBvnqfZF+zM4Djh75Bgmb6n+sMHpPuKEOYcwWIPdjoEeMjg/ge8uUrQMDaHq8wlhNj7JRAYH26bxzHwywaJahHu8eIIFTfN6QPULp33FUPUi+7oIjg/JuvhUwwBo5//gQo8P0vvzXLxHZMF4mQW7JZR4NvZHYHCG8dd+MZJydEi9ocn//jN4QjFfu1irUQgKJyrOr2oU4vLAeraEQmlfTxt3nG52c/cbO7Vjzg99vnzwDMT2KwNzgenLd3KT8Sdka89zksbOdJFOOXu9QxouobiPD4+QGf/vQJc50YsAxlJi7AiZXh1mk4tSBo4kQEja1TcFrX4h+0hUPKIVFBoi2qAjiHfuxg7nRcO9KSvU9OKOawNV3TqkqwFgxDtt8uHd1nBcoAACAASURBVG3WOzPPaRu0bQHoZtSNgE5qgdI0G09skgL73NnHSoOSPloA+YLFEwgs2Sj8DyW7xRqFjDbV4HteV5zWM5KvB94RYYVgUeDECmIB8YLxy0er0nl3A/ntAYfTGSciAAfw+4nxeEhRwwLo4Y5nkxPltwfw/3ebWGv0zma9quDwy/u0uxx/eY/Tb1+Tnx6VQP/2CafHbwAeAIyq1uuB60TA9fED9MMZj5+/gMWDIVQtWQAKxY0HjJv+d1DFi6/r6XzG8bBgzomr4wHjMDDnxBhslQK9Gmcs/jrPIIogBw9kQsgE9DadeeWg3Rt968J/seMNL4gfWhPbE2TDYdsgYeB1KWt3j9i+EcnCmAyPfvsjQP34261CY8e1KJ4ZG8FRtz/aEJz905I29IXcL+oPEONnFl739+/D89eKv1QQ7nJsCmD9YmVv5MvX1tkWIHzHAG/H3J6zV50MONvoss3kdh/rMCf6Dyf4o++6MvHWZdp8mf+djpzb25N0NQagUk//nqnuhYfXzpmw8+xRnpcXiYgZHZP/CY63tzg9Pr7xzMqGiXIdBGA+KMZ7VwasXom5y52BCqzQt4CdGTIYN2B4n/M04lxCwhioM8oxMgI9ogA7eoYxy/wLveS2UR4rd+fjh6aBHzgks7WylIBiBeEAkEDPz5h6cuZwSsdj7M2dGGjXkHpGtF5uoW7YT4ZETpdCqXIBgF0Y4GGVO3b0ckvX4PSa4MF7QMyr0cIswUI1vrquS7/GAAcPy8jK9PmNmf+C/gaO2Icqwwd1oSnjYCtrrhajYGC4ESNRj1B2A6fG7Pe7xmfDFrIRZXCsXycAtR7CcwrW84r1sGKsExE1HgJm9AQ3hT6g4gEVXvJ8eu+hMQ4+lIM7RyNryrN7gvAykL1uU3itKXQ+m0Yc3eFX+3k6E93JStn/WE3gZXKHKgHiORkBYzJIC9SAHEZtj8xOqfuCl+9eHVV2FXjymrxFyOeZLoI0/KfTJSPH/db0gwduIGbfE5CKooTxJ43vaErkBtIuMLuxVS3LDWnoD+drGDqQgmoY9pjYnTkHLwcdPcyHB1YsViLZFQimyAamdNYF3tV5pN2P2B1tEk4fQkRch5PZykpaxPTwqJPss9em3UgNUsDl/kWA93Xn+ZtcKteKUsgIR8TmGg3jFXa45ZJN7kEPznAKm46V+IuMMH9C0IlwM8dr9BTNe5NnrWjR2zR8x9x3OJ8ZOm2stgbb0QNO5vabYUt+84SqOVcjSj5KDJJXnYA7uEgJwkH/kPt9tOzjMaI3vDsigVx7EfUtXsZOkTcFuxxoOq19vIMIU1vQVmQ+x/PoMjgxlXcCsry937uMJHWvwMEwA4rMDMrhYSXxZmSFZ9lNdWVV2phxMaZNlkxk3XrZ6kUE2uYxmIGDOavHsiReBqIJoiS8TSgzsEW9BUj0UZ8WnQ53HqpCp9GRMTgN0MNbyMQrqdGKeB9rwk4L2CtKZPYD1zVTJ+ZKoLROjNh6bli2bG31km0ZLiSKFWsGVJnjWcHD+HaUn88AzZCD2p617aYuZwTGkz/T1hnaDDl7tPO9Giumzp9ExYpKi2aGy/ryAhCyF2UPEBnLkvwwdgOgKWva9YYTkaSiblCO+tEV1JCgzXnbq+Q+CZwOHIx5tEmZPJa6JypTBtjgUn9GPpj2FOiSM756qGCdgJViN/hMeBsDhyNzBJQU/QWC/zAwXE5zAqwWMZMVdyIQLrMfm8wS9IZUMT2zMIlA5xkhf3LI9oCSYIrLUQoovER7/KTR1KJkjd77eoeDNh3vyTe1/mtyQ1CfWAeTVIHV72udKAJDI8Cr05nd+v3kEXJIloiLLPTgFyEbh7KeE08ESUD02W14sLa/zcmAi8tCrrfB6YOCfF39+W9M79XgxouJ/virZNfkNueQxX180NhL+dQNPlTVo/qK6kr/N8r5XszA92aICO6sb3am+J1TlGrd4YbKfkEYYzs+5OckLCGcOkUKGQWhQwSlKl1SMxjSgh+zIYAzW1GkIzvm+zbgCaGrbOXrgtjmyAWq+QB0QbO2sl84bDvcY46+/8OwTnXPbVBZX8m35gGnUaXrXMyaavgX2+gtohr4lmumScvfROf9FxcXasTcvfHbHQ9QvPo5aWz7ejOunJNbFGPCEUnf1yMDhvowNG/aeRTgrTg7b0DRHaB4STzHtwmMNvs+zeE531FkfE+sCyXPiBCuxkfi92FHmicwM9bZgo2djmcgpcvZqt5f2OEdO8zkHbv3zfURD9+/owcHBg47lwnBHyEPZds7Am5ur/Hl85cYpAdhGVBi+JxTqbUkskC+rACIChyK0W7oDeAV15CVLijgqhPES/VVBsyhz4y5zryHnoDxzsscXz0BzxUkXnR2K2PDK5qQeRuLR8Nwk1UhPvBw1DHfQj3zPMeJH2+ZBp6NHVvad6pONb8q+H3d22QLm8ec1leaxqgbwjNzIyjjiwIfSn/+0dgErx8htreCSrWHfA78CZDf+73v8t6Br9HGTxFJC50T1FgWEM67UcanG4WXVN99uSOnP6KuxaGwETd8N+bvf8DeX71/0l60ffDKTX5CsnjzCCkodhdBMd6/g379vrl/zCWetfjVEUo0/Hv++M6yy2mrI0S1mc9/+R3vP7zHKg9YxgeUUGsTJDEx75oUL1DwsMo4RBagHi2VEuYhX8Qo/ZlhOw2ciEdM3Yb9ptzkIy01yGS7SHAyuoBWQSSCGYN+JkDrr9P1tu/LJ1V7kGAOcCKOvNosUW/j0pqHP99+a7oZDYClBLvBw5NW2AKPEBWRALie04OPkz+F/q+KNXQBtTYTPdBnivWtB9vfmKsnXq3A/RnPL38F8Z8tmJ3ucNAVh18/Yv3r50roARBt32bX8xKYHtAR5Q6ALJG/fLrH6fcHwH0p5hD75hN5AOQR0BNUzwBuMjj9eFhwAvD08ICr+3dYbg0ecDlaAMjLGeP2CoerI16eniFQDDXYryK4dph030in65Kt7NpmDVGSgKJT20v2H7sP5b/jsWxJU2dp/fPbZw227kTvSmQHTAhDzmAHzNGgvkHLgXt5vKWUbY3iwDMUt0kg5IeLklk4jRXl+8bkXK7aMIvtjbYfb9WYpZXbSUnt4nj6Qeb5Ue+w0jd3jMdDCIoHyNc70EcTH775Pd75M4nsuYMKj4Fi5JfO8zawMHrkOvk/9ApuKAC6Asic6JZpWxm8wWCzAOS7LQDWb2bEW+7M8BUGwCC0kcUVcJeHKAFR9yEA86tt4PF+2QyvD/lVhs20+4ba69+/ld/81VvSgp8nZ2iWEa7Qx9d/G0yRetQy9nMIJtXOOkN8/PoEgDBuB/iG8js5ncHLAF975NCzAle0gUYc3MbOXgI1yiDSO2OM1gdG0qAuD7aSfDdAj0BkOZoj76XkN42MvXKdplMDMEfCGFa6ehlIc6kzxoFikAR4RpZ5oKI0azF+BesE4woZ4W6jNGGfBwiEcXvEfBZAGKQHYK6Y87tlZ+MZghMmvE+U31oa7ZNYYCoDwXRnAPOwEilkrRqiHGuWU/S9FwbJ4QbK6J2a8PX+nZuMzLZPlMIYaF9k7pCWQ6or7+LKXWYJi42RF8JQG+MUFyZsBwI4ONwJdKwxdJxEzsevi3J8FM6e2rh2qWeiqWdvM1IBIhckrGzXhCrnA3sJePa1HGyCFU3FHDXuuU6cz2cs57NnrjmEfBMNsojtsSxW7WBEJLBFFc5pmZS59ofFhLzDAlLrKUpRikg1puTrHE/zSG3PeM7o6yCgsi1Nl5UDQmhXAsHKy1u1AHemqIIpsmJGYkDxNM80S4NEyHOapZbLqNyoW2OCWYLuDf62Ofbfx+0CDzfPiPuiCWv9tz3MJgCyo76OV4MYk7YWqg1vIN687/QIHnCTjaFzbEb/xrC+TNycmQtbNCx7yajD4YgxGMerG6hYlKuVo6y+UOb8jMhNeMn1gSgfGlw7DK4ltcDLkbrCkTimnu3R1iwnZlDLPYjgF5XlE3h4saS1kS8Ox6DGnxsRaM9OxVhtnKmotvPliFM3/DgZTdphYzdHopWZbiFA5iBnBWm6xwBUr28mqw4U+mwQu8TAYI8Bc/9Q+7K9J1jVjoZ/tcdKfQhdKfdTRgsHvQwHcpS7Lh5NzCBhiHsP0rhM5jTPShTE5uiEZ09TDYiBLD2Z5cRb2fRcros/W9EpVhHIk4gMqi0Dnpg3mZiZPQofa5S89zWVaaXbch8TeaATedWYgnOUz45ecGjZoOLtJGRa37JwtCdME4/t3yjvriKQwTmOOcXLqs+cM7tTtoJbbLRR0h3RTsRpZfTNFEhmtIdTVGFjzZxCx7lwAkUJvTEW7xNnPdmzhB4qW9POurxMUcK/llKkyc1ne0DQEp2V6QVii9ofo/BaxcpDToFMgiwHjAEMYgyv5BJVM9DwS4hBQ8BCyUfSEcLs9NIqdOxVOVUkDYNqlUt3eIcTxPpcGwIOIpz9+/V0Kj4Sz41y9kDuQagFYECrXPvG4TMVL9++pczAvrcys7TBqN01cRowuSqME1sdkkrGVW3VRJzsCXKMQVwIlbhKkZDmVR4CjwOUgyPYRFImj8Ocx17CVQgy1CLmCRA5g4K45nro5t6BHJ2O5bz95Ia9+KJ1OSWuJ28zpgWYltULx28k/bEwEbMRpEM5nuWBPKLFnzXlI3M8Run8CFLu8s+WKdZaxmdRxVlcZmaCiGI5LFBdsD5bNap0Zvs9i6MFDgcctvDRLchfPTaji+v9cTVqzYzwzQ/jmRR0uPOnViVCd9fDsrwD7wcUuhImcTJhq5RSman9PuFE28JyuxdiP9d4Yp8HHxVk9qVa6dHOQFUjG730FfEM8F45LCflL+UA3+6dHIlG0KsCUYq+TS8qFXZjrP1sGp0bw2DtMkVmJ+ss2anQZbuGfibL0ftfBg0GJdOwjJQsmFJGzzwl0ymjD7LdXv2eG/DXQSHzYDs/7VnMXTgqHA6nZNDJbtra2O6CBqLJclnOHbbmDt+UaTJYh3JNyBYU0QM97WzxvKh+1qeeQC/IBz028lz4VajbBb7gAYWvm0CjkAftylcAXPdsZGYjW7x27Wtv+3HhPG94vjExdprr+7xnwVMsaPAknw8rso1X6O3wJIniBwoNeY6qkkroVMbjKtO9idUOM2ufJRDIOpNGZSAtGe+e57PZTubZcUES3/UsJmd6NUtpY8yHOY6GHImU01Br73Jc6CoKy5AHLVB56aiW97bgM8vYVFS2NgCsMvHt60Py9y2f3x5jDMj5nHJfyHZjqQDrDD6GyZEv6zn7+iZtULfdMGFdBeNgCSJKsNZY6uu0qi2wl30fh+uUTXlZcI176JVXXWpyE3nLL80gBiS/Nj3Vq2bEfJ1vZDs/l/X4DpjfAL4nyMPbTpTOpurMpbZJsHshz1NeDahnSAP8kcB8l0GnIcfkzQDwxzu/KaVMdzGuN/etHWcARyXIK7Z+AnD9b++hCgi+YnVOoPgGxvucIwBLnAFhHMzWhl/fY/7ta84s1uf4p0/gOfH825cNbOJOfyByXIxv//mZKqu+z0iosRmClbv297S7R3/dk9n9fePgdlmXizb3TX5ofiAAuEJZJgAL/LVgBtvfRyLw/S0IL5BvmmXBFeZU5aDvapWH2HnNuPfS7IDxNDb+GPbbA6wanokkd3h5sbLoh8MBRIwVAhEG0cTEwLTmY4jARSKy4OspKVVW4AklzyvsLkBngLxK6g9mowD2WCyRYBFySfBwn5cl1FvbhWhGmZVFikBunhvvszJeVnSj1KusgixDvGqQikJIIB5VEFVK+gIzwQJ5/XuAMuA89OXBFkgoE6kbD7bku559HsknIorpJeSD/4dNwfCOoAycSaGsuP7zB8zVbMc6J3i5w8tfvuP4vybWMUDwCsm/fbXxekLAOlec//oZ/OkeDMX5dPIA9eGyq/MlUsj5jMPxmLQz2uUyMQ6/fsC6rpDPhPnEkO8M+UaYJ0CeFfQpZGYLaLr55QPOf/0NMp/A4zZlaFsqBV+T4yjh+gg8v9h6DG/xZ9vGKoOyoNoTTPG5VZAZACxjAKdT428ZFeF7Nygxig8iUSiPlBm0ZMx/5ePHGeg/c4QCHP1UfnQpIisOYAx4kYk3iecfP3onKKItwMWz6/VH67Ih7I057IWnt1j+EwF3XXD7O4/xkTH0HuvXB7/F5XMm7LtrrRheQXOa//2P3R4bTrUDBAHQlxS4/0lP/Lnjv8GG+uGxA9PPTqcLQpd4fXmXZBb9GScA13aOAYzrYxK7iHWnl0vENQHlyhVOY85MDBWAB9VDRLGMYUqIoJSyR2RG8Eaw64r6buz56gbR5XCwEsljgJclM7HCqLH/HRFtMtabjAGIKRRl4GvGaBDGLVvbeCaQiilO8mK9WmSmkZfImX0ILwjC39lFCdrxvaAUTCuTsxPPm0GxLy3t5hma+0Z4QTO8aJ7ZKDKcSrutz1uKQCrRw8uYw/uqhmEwi1G9clD+g8LQGH+coVRS+tWb96rQnUHEzuPiN5vHK5lAyuzCrjtSyQWnecb5fMY4nyyIJIw0UbbYnZiHw+ICmBnIVu+PNefEOt2x5A54K9l9AEGgulZ/rV3LiQgZiMyt/Zzifcgh1uuX0lbECMHUHec0QFHalxjKmkEksRcyk6Yp8bOVWu4DiP3b7JapwG8MTN2yu0HU3WJ0phTM1zWs2i9tn+wY+uZT4A651LCVs/PelcliJ/ei2sawlzy9FP5keZt5az4bCCXBMs7HYjhCXrZ9DMbxcPQ1GqBlwVxPacAkcpoYwT4oxSMMhj88nN6KG7Q5phfGHEJbJ8CM+QREZRCQ+47Dmb6lzdtn/RGX2hqnq2ymPzzkaa0x7VEoYNyVGHNO+Yhsw5TTFlW2WlHrDMAcTaKe7RqKXziTDC8sr4uSD2wGV9poo+XFebshNRRAO9/wC9jRrS0PSPLXAqyAloUNa60dOFG9+iqAirBzuDtuko+dPEgV0bfR+xxH4NWPJLZYD3fB5vPU+Q1noEeVaavf6uZ9OLwVVdlDprT9HgEEsRccnhJlzzUVukHw8u3egiOMoHNCEZVbYA4M7sUSG85BQd6mxBTiFSubjBDBaoMItCwWnhEGYZhR7Hxesxd4Gt/EAz/ETR6BN80hrCEPXcDa5RVvlzIORwv8igoE5amooFSH+aZ0uyrgQTUkkkZpIvRyVoZpzamtjg/rtKx5w3bv+6YKosXK24/hMhc2fNtKg5cTPIP8CK3NwPDqG0HrGp6JplxF1Jw+HUZToIMSlikzBG/znUWIsuF9bwM6J9b1nHQkd6LCgznEabWkMcb4J/I5meEW5oC9qOx8ZzgeRnm+vXxlTsgWLOeBAUlrOo/9ySP3KFMrfe/DEvWkYTVjIEwGLTJNG7zqdwWA9XT2wFJgEoFo9ZKVUmXp6TUtZIu7+0zckgOMDhpP4jTqiBtvoFyJuOL11iKwJOhiCrxNFjZCUDynMZ3KFi/+vgWa7+dwMolmpp565mWslcADm9TDwnxhtzLGGzw0GWCHh2KbZf725/i4mXu+UFWviMfhcnuFIzb4UMiNolZ9wuRBwgxGfTH8ylyiLpM1uWqLV5o05gIc7ZX8AWZgtcZZBAINy2o0nmLBZQwCpGSanNvFDYEmGG6u3UMlYZO0BqmTAsjS7XW5y1eAG6Tb9ylQor7vT3e6HJXM08FM5bitvYTkwxlAUeJJzcBpYL26LEa7Qfg8g3dutyjlWm0khoYLEfzQZbm4JMa94WOoecTYNXVdQmSrsyc6GCvZ6ur5PuCGCJYMbZcaD7jcftTgtaUatSAXJdn7t52evWYI3m8yvTx5SeJ3A/pJHpBjD7zEa/PBZmFcFXbS8wad0hi2z29O8Bhe6lwQ+lsItOK9Z8PxzewjYQuCMKNQpyH2yjwgOqsiGUL+hPPqCZnmYtS5+lS6w1tBPCAy7dUzjFMegeuzYewXxSRJWducX5r7zBwsjvFq5b6XwViu7/H47SnHFwhiOFhjib0QdoJtZYYmG/u/sfewArSErGF4X8Fm2p4R+wG4uj5iymYFkx+rKAaztxACppxT1gRgln8FcDqDr44ZTJnBo2NkpT8iwljMBsI8ErZwGHV5LBE3WNYrLL9/koe/U9hBkbz9OcCy2/O5YftzGjTcMb7Xry/4/wXN2j5Dd+9fO5S8tPwb448jzSO/A/qLesuUoGrtegLG4YB1twfg4yQCDsvwup6Xz4os9H/keCJL2OvHa6RO3nrOP/j8i1v94H62r02XA5Ayefws9FjCLfg9IPM78Gg78uC8K540nEbwPYPpNvGCex+AuFqBwy/36YgkWB7G+XzCcjhAV28j4cHgR2U8cwXHE5HbF9cdLwVUuX2wf+7iuUT41mSubqdIe2+blrrA8ar9N8UVBcTlcbtR0t04WNlabjhgjTZ5QoC3AR086jUd3sPKtrsjm2bIVXqxrlF1VrnWJGxnPNht/RFobt+bXaGc5xlQGi3WxKrYBY2O73p8KUSxQgC30yucpotirAp4qXwRhQ7DtwngDAX99hXLrx8ABYQU6+9fcfWnT2mXks/fgNtrqMKqu0Ih+gUiv5jcIl8A/oirf/uIdf0M0cVbyQ1rc8SAMLASYWUA+gDgncPH9JB3Hz/i6csXLO+QNrAKcDsY6jJh8BVAz/ZLEby7ukp4bQIqAcy5YvCh+C+CZ9nai+tNcb3qVu/I9x3t/ohI/gsf/7gDvSmjAIz57Ixo0HCa63Zzh1KCPWN96zk7FkzwElp27tHvGQY7AOloy77M4bhQKgMYaqE7Y0z5BagonRjiju58UOD44R705SGR5Hl/0W46+sp0RRXr14fmniIAcc9vEHmPCeDGlaeh9yAAKx78VrcAHje//hEuxrqFcaswXTdXXWghybyv0llnp0uAggL6XfvlZpwEktDZRZSwWN7XOIg8qpCQhuO4/4jrYp7/6Ib7I4lo930Xbujy67/r0O+4WKRQfJ1EoTIeDGbEUW/heetAIAJwBaYXK7E4yLJ3DwRdfc2uhxl8VDBPVvjnwAd0wwYpwLjyZ9v9iQkqwDqtJOTGQRcluVyY0/sB/S6wUk3DI/hiL5WAmn/NiG7lSjwTYgwcDwcrh7wsGIcFvFhZZO4Csv9lhicFcwhHSlU8sOcbgvVMIwDQJ0WU1FMFzuuKl7linaszB839ncsBhSIi9TzCDdGyQlPxACbYM5PntL5T63oGEeFwOBTDosAtwtwYKupY2CK8xWnd1dFKiaejL1bOldbOxCwrEZv7RnmoiK6cYmVx6ewlZpghOsBaTSPCcLhxoSTexhxyJAjlPXr3AGGQpxS+9juIuH2nQNThN5uhv0dznJAZiIeOvJ/13Vp8nRnRJycFKIb3QPXgkoVTmRy8uDHcyr1NOScuMMijqwEw+54YWMcAUwjFmvAF4KV9gGhm2o3MAb8kKC22IoyV5ugfmcHMzFZ1xB0D4Qg2Q0D1ZItsS1mtr1w6qMhLDYtsHxjPBQEahcgsUnbrJNvRXt295kL+wfftfgGGVwZTLAPl2EKsvzuI1XGjGz8jmykMe3Z0XkMXe8xonj9PalzRr3kZ1vecF1MKlmHR+TwWRKaWuAISfXiLTrXsYWaMxVy6GtYtAOq9jDvwVD1LFMjsTQ2/oxo+1vpcAjHoYudaGXSzmfrrDLWxGgCAiBl8XnteNx9sHURNBVMX7iOjuDnQayjke4tRvb69ekhZnfNpxC0LjAKHm9M2xtOMus6ekExqN4d9IFR+4sAr3vQj3ssEhBhq8MmoHMEXeBe0kRkQYTdGdj63vdaMdYIxjAcNAbL5nk02y52v62r453PuvNMn2gYd5miXDHLsZFU52m/j/jnnkMH9vuvp5P3Pz1jFs7jdEcZsPZmXwflokXASwCOeXV9gxlDNzI6YQxgto6LLNuwhlFSU829OzLnidD77tAWyHKrveFt9VQ9QVcne66U3hBHXwS0Wuc5g4ADwJChXhgKG/yboAnlVH2bwWHA4LG5wsP7jsT+gxt9KbirYlpba91fpWpqwc1kwgndAUBoe1BeVAmCBgSinuKGR8Z0AT9lx2LOv4tqgKeEIqfexViUjqFXSILaSoh3/4mDayBlrVKZwGrq4wTcGJHPaX6tKEEEbcFxeV3cCq10PWDAoTy7YczmggMoYT3Bf8LfalOQXEar8YyeN5OvlFBGHwxEKxfnlJS8cbuRN+kDUbxFiXd53cASvRul+g1G0oIkxiPfFs73qe5dCTsb2WZqS22biOsUcqk572FsCdDqWmUNJ6x2erUJF9pDcybx5tct2YYhOAyh13Y+y5yz5Zk2a5TJtAgRFxyO3x2rPogJlWjsEUcuKEVUsyhk8vOqacqxd22lno/yvs9DN0Zaw3pPhRfBlI8U+K9quZ/2m772eIVvziVczFJYhNJ2s2Ab1WdDsgAxvZ+QyVBlnu/zgPFQjuxe5J8rh6MOO+TnTDhuRsXPPMCeASCBMIBEIWflOJYIQrCywTAwwhAnsDvYw5Gnqd4HPju9NKlFYMFXsVDCgFF1SI7vb5fi2mHX/Bt/4jTa+E7QjNqsbrDOrm7Yafteb8jk9hVpjTpaFwlT6YezNLv/1dbXs4ZrHxiFeS9UQZXfsTqfI58yJanjbe+7k8IvzVDo4c2Wf76vqBN+iEPeoyQfwz7739msVC5J42XAz5cINXnc60dlskyh0+zbhsleh9nDbvNPXr3tjCfbHq+RFY+xtHkmDC0cVqKCTkCfabw0UPcDfqv2AGAoqWTerlpk9KVrVrHMFDYacz2XXUA8gFxjPtxvkOIkZuq4+Xg9U6gkLMInMxmHjlXVi6nQd4owpxe9F7LyKeJUg9V7UFkCpQLbCErEKQuLJH8TAnIrop66quL69girw+PicMDwc2OwDAQcl17erhQ+QifsZnF7rZ3vWOmIecBjD6JFntYgH4qTjSs0hEw44wPGW67Mn2Oez1udn36+UnTeJrWLocnMN7xen2AAAIABJREFUZsJyNKeJRKvA3AuNzrOt8RZ3g8ZL7mM4PKCaJeBNT7S1sbW8Bukj6J7AD8mNf+KIXZ4ogPG+8R5ml9XMeXk6m8OZP1LTe0NYr72QeK6wtf/9IZ+o7VcRywcj52+OOSDEBb66lwKnvzygRmO4Lb8B9OsDiO4bjpDxpXV1WkSY8IxplLzPzFZ5wJ+Tvdd/Gq4/dzQxAlsprOb85vNe+YLe+Ip273dgRKAnOV7vpG/vL1577ej20uu7G8j3Z8zV5ODl6uBy4jvMd9+hD2U/A6wCAd+T90O/KXskmc36fPLgHn8Of3wHEeDb71+yYpi1MAXu//zRaYPZaTBszx4muRPdeOJ0+1zCWu15V6vgO1mhf1bxLtYu7xEwaSv7BaCCLryT0B8d4wi4FcKj98xI+dqfZ7qBbHSPHuBrz3WZg8ImbLaBwSPtY5kl7kHbFYxjvePnnFh5RdIy7XKVTaKqlTqcuHSzGJPZjgwnmEyHCuc9kj9ZpZKohhd0W1wuS1FNFbciECIIzaQT9kwB0cDh1/eJDyHHrl6xb3wizL99AVRxXA4Yn+5BzJDfv4GXD7j+94+4WhaM4XD71fqrtxBtEJNVtqRPOK0rCA9QQtp+dZjepQTo7wA+IGV41dUTFwHRZwDXmYhgy33Gy5Pg+t11Uzoi+F2Slgb+BS4REkAGtyk4zxU3xyssY2Bd1woKz31U8mbShyZfdaGxf68bHPjXPP5hB3oaaPwwnG6Cpl9kgoxmtkIALoXrdr+/50jHVyyIKm4VrcPKljjHJn/zOTvGWAv640EqgPXzQ17zn136+fXBDQYhXtW9BMD8+nX3XMXycYF8eXUq/8XHC6DXr3/VAfhDYLzx5d8JwD98TLvtD+HyhxdcPvc/8bP/9GFzbKWv/WzgNXB18QMSAGfjLMu19/5pymw4QCJS02B5hbcgapmv9t6i8JDCPRGBBoO+Tlj5xFBqUUJ8PNg/pTNwDFRk2UA40JdwoHuJ08X7v+6zhCKqMEskE8FqYJbDNoUfqjlzI9ShaKladNkqgvM63XgumLCoW4G2TIIyfEhkogCIrDgALhB1OrmP/iuBwP+3UuWrO6x93GGIJ+INHVLV7IFdzyg4d+tGCO6lWOddtm8bLRsHF9nZS7lLGCYIdNXWwB9c/bnK2B/L/xpWbQy1ocBtZKga/3aMdmHyEx94RAzaelcZxsiOE6hXFVAQaQZYMQPLOCQ8K8DAytnJVHfACHRUCWgz+FppucFUSjDIy/vbekXAV/DA2Hv76SYu5BMCMDah7EHMVW7WmXFlZ0oECdifeBbqbFmcqpIlo9YZke4pI12s1RZng+f2My27qGtHbxLHtyjnVoDu/H37tHaHdKoZHUDCubJnL561AXzD1/0Q0GkMpdM7FIKoChBlq5i9zDYI4V2LDM6eacdMXrrZUgLE1ySE+FQYSm5Nh4HRoVbVIA0qffNS7cNUOra08JWpvnq8Js928vLWYc5qdYNOKWAhYFfZxvqrrOui6yMMrOzBB9Lm9so6bQIoOi0OYL45UfwxMw84dnrLLSuyg19DJK5RGo4Ev6uxJrzaXGpOaOtnEKx9YSW4xwAEI0vQqW9miazrKea0HYccYNDsWmBfI9EysMJplVf2YOJ0gJdBVi6MSqGcqloPsB4FzU4WewCdQr2yJGMSQ4aARAEqnk5EIFEQCVgmxCuEdHjFIR5hHhHqeR6KdZ0gXsvoB89Cbw5fwLO7ozy7V6Lp61vk2cY2CFbaXKM/rWJgIFpLRdk6UjKntAf6ZcnzFjlvNMEtobLFc7Q1Vt9fTiC8ZLsHUbVM3UHeT85LhHZjiF90cYQBOwoeRFWVjYNnZ1gBRRnSHY+gcNRZ4I0wbH13RxjcU0ckQGeVKmd3pjCT7+cYRtAPk99YTCaisUDOp8yaDuNJASFkUM+aR3mec+9hS78KYFqBVg0GJkMU3d7DFAgOphv42Xm070vG3IjQ9mR0BpvTIeD63Tu8fH+qcYdspLrJ9IjvuyOUiBD9uFNW9P27zhVDLRBvGQt0YBPc4QvjVvyaUwa7M1fGSqMjMY6t3OC8D0BlXmvKPFlyty0HOz0Jp842y79gql6pCC4nvkXzabdOILb79qHuS+H9DEPdHL5oTaZFGCN2WejZG91lYo2fQ8v53Xj7Hz0SQK55yC5OmjFUoWJ0zBbiElBFOt5+3j6bxR4f2XbtTNBxeFU05ykihAlJeV7gDjqxxAyJsuuBH5vRxEQ7j4PzKy9RrwX6kH9/agljw1EFoGg43ezEVkagcLIHHA0HMxibCswuzW1+GzCKUqflgu9z3crgUSo93ieA4xctOmhvTytw7c7H50YX9+I1gdIoXbpnyaCKSnDpgewczvLuPHd+EgDKx9Cl29zvXPiWG2SLa7noSXuDLmzpQeGuYl9Z6I/ExEtKHh81h/DHwuZPHEELdFftQ7tDKPAt1q3DpE94O/IfPrM+1Ivz7XiCiFT7Ay/tbj+PoFb7TiFWQQrifbzJe1VrOcM9QG7OiTEWP286rKhkq5oMomvyp5IHzqMlT2m8ePnedt0gD0qLa9QcNFdXV3h6esL19TXCEBYBeuv5nDakdbpj3+EiF0aNonNG5n3tvBVLOM9zDXvAlup2jb0iRq6I83vJ1g++QtZ50+RN3zPU9Q9qv89okCCODU84ZBJtv9MiGIX2vre7ZcCdVXeEwe/A+PZmL/H9sd/BAMD0zmWETlfbWEEgeudz7LK9yw+eKRzl0LuzJ7Kpw3kuDQwc5P2NcXZZrR9CVuZ7/EqQvyk6ZObfFPjlAaA7MLgS97yc8yDG4RNB9QGKD/7w0DtTitpAIewD/4ws9I7Bb73/R4/9Cu7PYfPd20+daA6uQEtV0G35LHJvk4JwA75/gjwY/JYPd8ZJuJ60370Kbf2ubUesXw2fKfegObif/+M3D+swvhj7XgAcxfvUE5m9znXkW2dF7HzuzvfX0AiiMMgIPBvdCzZ9Z8KdAt98zuE8V5+0eACaEuGdEr5HIkDAxPcokwXYJsfvdCeCdlNORfJy3mSdV7LJWAaWZTFaSpLBzBtprT8DTb7c0agIRjS671AQsaRBcNqMukwTLdaqTUj9RcBhD54LWj5VMeLx6aMo92nYBkjZWtKNjxh/asGazhPnsuDwpwMGL5YM4H4OXVcfn9Gm+TcF/3lacPMYgMPJfCUfoPRoeOEAOROgvz+APhAsidbAtNy/w8vDI/T6CVAFj2uTn1+8clMxDJNtPPmEmEGDna8U/3h6ecHtuMGMQG2qPRQVETc24BAtd2zh/5XjH3Kgh6CZSr4L05SCum6urejG+EXFMJWc3iX7PbhfEUD8+uw9o2qZ6PsjNlF7nuJyQfu5Vxf7NUoO4CsZ2vYS7jdKP+x37sPtw8P6yrDVsTQYuAlT9v3ywcjo8eNH2+hfZ/0WWwa0WxE732Qyu+51NrUfqLqjNnSveE7ElU4XiaJndt7tjtuqN6MbhwFlC4/95zKMx4la0Z9l4m8sYX3zo5vsv4txdknip46aGL0D9NFNZAGci+dsFTfQVoBIJzC9gOgmcWY5MNYXNWXUpOUU7EgH6HiEnM6YnmELWOZ5V0gVtq4RTQrVzNJR1VYmB1i/Ka7eEzwOCwN36LuNMbAQQfgZYTgfY9irZ5kb42Mvwc2Wne1O8+EZ6uFMCdiUIk4pbBIATDMsL7fuAD7ZbJYb9vHHHBXzScFX5iQ9PZ9xXp9wPp+wns9Y1+kOV+/LiBTNnUE4I/ZqZaZ4CRY+pEJJYKzrGSKCw3LEsrhjjRnTSzNZuXCxcuBhdCBsHEqFEpRlZ+EK3ozSgvHXcc0XKYwd+/1CRFhdmTh47y0JJUHUeoN6JtiEOQAqmPeVTaMBl1JYCAGLMKzAmbDPzxWzwvda4zTC7NeZrFxQXU1ZLjgeEg5uKx+0ZCCGGWuQwlMoIBFJL172eF0n1tPJSv8g+J6t/fTr1nmu3u48cj9ZX/IwesGNzS6ouYEw9lYKe2AQh6F4AmQZ9ZY5WHRRxTK0Qrhbvbz8uq5Wnnj3Z5no3svXDUdzTitLjHLcbgXYEIksQj+Wo/MSosjYCdz3945kEcyAXKXceK8eaZB7BanU5103UIAYDK2gGoellXyuwIVAOG3/Gv1wHpQZk3BHN5ljim2NqmTUyNLEVnJ58XLurQQwj1apI6prADysDYXhIWWwUI8kX1eLyC36QhdQ0O2JHXzj37aOl6BsQoI7jHLdd1fTax9eMXtsxDd95TtKGhTLIemYlFeyz2M9OGHYMx2yFrHTWE+zyudFtHIJOJQ/EaT9C1bmXjYR+xHwlYbwHSxNZwwHhq9HZjDabzRpkJtgXEgOOTMNd2RKYOCvZQiiDMqBpxwBX8Fzbc+KSGZvjUFe6QRWyWW/BK5AiqL6JqeB0662gCJzZts4SzYiV9hZgMmliM4oY66aeyiMmEYja51taNFbOwznnDg5hvUdnjItuj0cO+5MFq2skSiV13EuHPXMljmKtcppFq+qKiQEV4KZvexoh5UZIiMzYLPxqKo3EQG9DH2MJxRM+DciM+kXD8KyWIDgMsq4x42vp0E8+Aco9w5Q9DaMvbnQjp+hl6HRpXQwYvrlVqYz8HZh65Me2b5W6s7KaodDhr0iUcI9+LNvA4GAlX09phlkfA+IsPOLC0qWRxmuCIfjweS1JwtIYDXjolVUgBnOxQ0kc2I9n20cYzhMJvhw8My5mfJWwJfgmaYhV3ThBMiMsNRrN4qJnSMO2katxI+vg4YBva0P7HzgZbTwsNu6G6hlWvz4sGuY2B2O5sS7ub/D+fkFUKt21A3eIatEef3oUWhZEQSQWNl3oiq/uHuqyHRDi5O2aGnBCrSsmijJjCmlhziPjXWwFzdIwn4nMl3HrCzXXu7fKsu4Iybx1cYrmJgTKZfE/W09CTo1gwjjUHeipMMsZFGnN8SEhQZUGHNdk5bHmnXDUb7N+/380Y38wTf7542zut076MOGHm4bIl88x6eYazWGO9BVLThCBKwWpNQ6cW/vcyldXCjv5dyr0xsHcdsLcQgEJMabmdy5RMYTbD0AmWSFBLxaS+ydkLWhnPsqpT5NSTKhYgGIYhUwPRhOHeReQtHn4e2bvIpFXPLqoTvRTDZfpcjVJQvdrG37sQ+vCQ8I5tJxuFQmczoLi5VI9cooJTu3Z+7ws3/ayuK7mSoyxiO+7sE49auSLzJbDUZPg8ZtgoJDzstKIC7Xv0IPc98Fo6PmTO+4r+n+aiQ8gB8EIuC5n2mTAbVeqeGPPxCNKbbbV0ahzRslM8a1f+chEvKY3ZVQY98PPfFQBVGZkFwWjy9Ljij4EEVfc3tK2pkiQF0NX9VbBdlP7bxMgazWG3bCqrjwYrLVus5sxQBQypBW0jdkJvXqaDO/C71eFTifzqlTKxMglK8h906XtUJeVDbbwAxHCirYHOJ1w6Sqxyxj4PHxhCMPz1a3cV1fXxvfa3xdgtYKPGj9tJH74L/tDgY6HjKb2KrIFA+031ZlIIrFbnSyWknotqrIwqDVe+1eh6OboXoC0ZUFai5LIrmtsdaeALLcMFRz3wXtsHY/lFndFpBXlI48sSbsKMm/+jwIOH/5FlN69djQIRgg+rnoe14ZqnB5y/Hs8zcMAPzr+5RlO6mLijyB/yF3vxSoL54f53pnlQ2Nb78La/wu9sEdmPcgfHWyXjghvymWXx4Aep8/0mktZIgIy/IJ6/p77hliwulklbQOv763ffObJdotSedsW9zqTzrRqb2265/8841sr3sEcA/Pgv7R/V7/+EeX/3B4/Vysg/GEklZDVzx7QOnh7tbgItPtrxEMfINxjxCIfPr+r89dWossnSYTnr9+K/oeNlLyQIkPty5XLTguA7JOnH7/avSHnN+L4spnIBAcFHhssuWqFowb/dWD5gxSLL9+wPlvX8Ew2jNAuFeF+np/AwCXKhjA+AVYfytJQ7EL7lF3nrPZNlkLChu+qx6AmAth9GAMSx6J7PP843oPBYTE9N5lMdtyyOS7XWe0j0sOcQEug8bFeJ85uwWqXPZcauNWT1CZ2ypymw1MBCLFOwk+rU7jBQyrLll81gKqRATq2dfqAX8sgmVhjOXg4uMD9DOBjwv44Qn852uXeRZAJ5gHDou3UkubMFtgVrQlI8tIZ/oGEGESeyUwBmhavPMXBd6HTcYqk60ioOcBUsXxnQGQrgnyZLxlPr3sbCITi9c3UBhtDcxcJ/Dw7RFXx0PjaYJxWKzKX9DHErNePV4TUfbHj/jCv8rxDzvQM1ozNhCCQWnO3iJFwqheDvQQ/OxqbZ9i4S6zNP8VjrdG8c8Z3Sso0051vhUwMuNEQfS/Fun2osKPj3+NFbs8fjyun9u6/7QNvjeAvDI42n3qzG/jVHU2DFyD8AJVxdW7A87PE3zYGdPJGBNfX5mRrT1rI6S6mkhOy7l9P5xRhU6Zzj2ivM62/ZOP9RYSgok7z6O3+ZIlXrzfOZlzaXGnOhFhGdsM882f37MyaVyID3rTmHwGbACQZ0CvrJfqPAvW74KTfrPy7aczzusZ52klsLc20Cota0Jws48kb3a65mPZRrl5WZl0GkWJLHLHqHhpmaKlffttjHK0ecmLQ38xJUw3BtCOv2F06goBgBxXICZ59lAY67fVNEvQKibahNBiDm9uwDBJRGWcfm9qa9pLu4cSRwSHlQtKUqU9zcluToJxGJn1a71dGYPd90VRElSwrpJK/HldcU4ntN13QSixFm1+Pp9xWEaVESa3drlumU4OkuYIoVzfNJDCDVDizvg2T6KBcCYavoSza0KnORTO5/PmdT2fsc6zZZ57Bnr2rJuSRoosM9dxPCJVpXBQRMPHlGsTDvPC7YZhFxrmlmp2vNt8t4tKUihkNZiG4d0cBaaIYLhCGbioJlwyR2nBLa4VTXDMy1KSkTHOXvYYIHjP58CboF1kjvRQAszBvpgjIiNMTQiNbOPBo2WtlwHRZ4IINAy6YHStVMbKJunEIP6hmlOe67B/Q5Ol106+doZ2Z9v9tT1yA+twmGszFrsUqFF6y7NLM6NQNzDLv1iTMND2fkv2K+OMTGZEGQqaak7RHA2yd632MQb8+8hjQmEcatZ/at9rpWL576jwMG6U4208Q60CxpwC4mZcK8Llji4LxkBk4mdLm6o0AXiQBy/pnI4hMOw+K5PRhNOa2Tux6dMoFzSA1GmCK67BuxwHo7yuAulcNlpk6iz7zaJMWr5v2TKd/0TmaKCVyRwMyPR5x5zDwBjBNH4/Kp1krp6ppGKt4Ekuwj3stxPmSzXle0Y0vC+b+Hgta3dmZgABGcjQnQMR7LCX4TpNFc+YihtldD6PVkIcZdv2fVN9WcshlxkzubF2kiJR8iNmth5qanQ/4AWYI5905DoPd7JHYNSUiSnOl10GswTuGIc9mt0gJNP4VWTwmHHX+hZzBIXF77TtumbwiHszsWctAGMcsIhghYLX1vYCgCL2woTSAeezBSuO45Wvh1f5cPwpIGkFKKI5czyTwvBgwgLJ9kgUjPsVutpltleO5JOvyEJb3tTuQcA4HDfn1/MJ+5GlrEvkdM4CNcKJHs5zK+fvvCoMXi5fC60g31tWXYXSqM5NJtcpSauK3on1knWaOLTJ5VmmeTtJ1Qiu8WcGjdvDu5Xazck6bYEHwFUwSbt/uxPBaKXIVvqw25E7aznHR4MxZvAXc+IyHa0naeCvKVSIzJiNzLN5r23e3Z2i20XvQ9u9Zhb67kiQqsmf22u2CElBZFHsKQP/4m66Qjh63jMkHFYbyP788TPBBD0LXUFegrk5I2iAQxkVMyxTZMp4P5sA1x5KqupZ7dS4vfP3cJILQF4S3irniLUoSMdp3AsIg2FSgM7U2udOv/ff/Wfg+BbcOj8FYWNItqFrvrchOG93Qr0pGe9XdMdZR2H77PdtX3TneZJGMsd5lD++0N1DpmP7C9qSVcAysLXJVe29grxccromL3hwzGcD8XQclOJDaLQ5Dmoy2WbCu3trA06sR6tWEUVi4tf/2bWPYLEcm9P4PY6VQ9yQzcQ6bYPQ7YAUyVMtoMQyAsYY2RKMFCDPvhPzINheZPW57jKhAxxistp5tdYL67q6PcIDUUTceS5YV83KPzLLIRCfVyndOnqWi9Nc8VYJ0+cvMJnLeIJnGWeFtpIHwjFvy2z0INyyT4/PEBVcXV/HtBJ0IR8KosKqBbLPZyTsA/p9eQRGu6CWWdzXNtoBbhzDjrul4/aFbt/7OHhEsJLxM2PTR7e3VQJMZbL7IsW9HS7BwxV9X1zKmXu9r1NxAJ7dWMElhBv0dqOvHcN/vfqdGGjtTZE0rtTQxned3vDHO1Tbl5LV9rQSqP2ymwom/vjYs/tJ2DjO0XiAAjj/1VqzMqrVT8zXxuLjcN0zaUajtVMmSBny+8MFT6b210KH/imZ6K8dP1tF4EfHHu5/eHF/2+AdX26C5F13dXTe8IcKWDSnY/8ygmkJmklXsQcjIEJR87eibWr2u7seYG8lvgG364hiwsrDb+LifI/daN0vWwfA2ukoCOOTYoxPABGWX99D//bFYWeB71DD2xsnVIHZig9Q/QyATL8nTRpqQHPHvkQGut0z2EWXXIMVasDf9YruOO/VY0PHJSJMmZmVPrx6o2Biy3tjRqV3A32dtcYScG8+fZd+kpZZZZLiSf2oVfY7O+9gr1IhRCCKnWp7Ntq6iQzQx3fQr0/AYMjfPgP//qsn2zCIfsE8PkCJcPj0If0YzkwBXQEm6Kpu+wdO//szDv/2YSMvjdDnmbG4HUhdFppkLNj8NbUbDwBeiKBgHOGizEv5Avqek2m6VwRUbcMm7NlTJFvfmVhELZCLmvxzCeP/145/Tg/0RqA6IyNn6iEAc5wLOLtQvSX8TUBAEZP6fnv1PlvOLq5FDOTqhs/YctC6/97m/6pk+0O8sJIa9wmOy1zuHx35/N2PBMDV+/c4fzHiuKARUwLWzxNKiutfDq+PrM3ltfEEn5AenXtxg/ZNX9PNjeJ7ezMohFk37EZuuhrxD1RJp1g+aQ/81wW2vDoUO35t7Ht2fMme94pMGI7jxOoZ/eOe3/ydKi5v9Hce9M5FpKdt5mUHax/98XZAHgVCNwACHwhCzwZBIjCusSwHQAnj6FFMPtgwOBMx1pcVh+MROCkmFlCuDyUBDQfgoGEE2hWpiEIlAMQK3HE+H+QVCUTBeGfP/z/cvXuf3LaOLbpAqtqv2I6TzMy55/t/uDuzEyd+u1sicf8AFgCqqu1kZ5/fzLlK2l1dpZIoEsQbC+KVLx5o3BzSpW1bBMspcCscO5WarbMCvS20g2qMc+L8herE8XAAIrg8serPQLAUQJ5ahfG4HLh//4BjHNjnPfbhPVuHwYEOnRgB325OOgYdrxzmXD+H6vFyP7R2gXTBmDtU2ZtVXanIFT+OvWTqp0C0vV+cxurVfnCHY1OvQNLo72XnWcbdUAS8LxWzakjEfFKXcsE4nB6YibxtG9h//bxfFYJUOm1t0tCRoI2FoAkHHMvG9UxoHTpcc50z4NKCBlv2s2IU3s8nPO62bdguF9xdrOcs4JUOSUrLOgrcid8a5O6CNjsAczhfvHrQkAP8+8igvvWdKYExAFCrLrf5BVAczajOKncskXfSeRvzqh6Md8fuGBP7/oD94QEPuyd+eBB9eP/hfT+s+q4sM1ursO9wNfMtc99On05vlJukDc7v1OmwVVjoM34zhV/aYsBQXvL3dHigMQ9fAPtkd6WtHr2ZpGXmKy8oAO73B2y+LmbsiIv9lF+2SprVsMFXYFmxfrG2tVKB7gHKni0kjjncuPeM1en9Q6f1pg6oWJjzdxyAdnWHb4MhuAvUqy2adEhLKK+rQ7A4y4KXSc5XOlX8Txp+Yl/OGQeiOkfW79T1KRe9Gkzscz8laej6/jQgzQFgAS/7mVGxnJdjsCVbdljg0hNLiJEsiGtSvkHcAOwdHTPvGyPTFVHh6tEKg2riDvaGSjk0ag0aOucgZKB7zqVCnNEIn1YNNOaMHsRMSDXjinCmPSG+3WjyAg/ouB6rBXM0hk7YVlKg3ScDw3Qc0iltELTqlXjwaj+1ilIVyBymO/jkGb1bwFr9jdY74FDARNoYXoUVrF8zsYJrEIltnnzSRKK/cmPwV5Wti3GMw+Rk98o6Onk3wWgCHIejsthzC1jZzJ1v86VzWpZ/IYJz8JyDrE58BltjXZxnsE1DDXQzIDhriwLAIdw9eZA6jzSomCPVIOGHVzYgxkFaV4XD7HkCiutLAmCIV4Yx+OD67eScxCCM53XJuW7VqUvbJ2OKyftN0QtdJZJ63ZnCSk5LFvPkFXU5o7YHbV1dByjzJpBA5QA8D0YadDd97tiPaL8iGBjScIyGtu+e4NRw7F8NhWjbwP7B4jqSrYcuD2l6QjOEoBTq0OGJomzRo6sdJGhgRb+qmuNzIiYsOGjYzKvC0bae4+CepE5A3qzAOA70bXOZBmx3dzgerH/65dmzQr9WEWDVYnzWWXQnKc+6Lc6s3lxvHTPWFHA7oyATBE90XitOF+rOpeaBuWFkl8gKORnBc6xVgbfVaYA2+1sL8k0k6nE/54u43pwTMqpme31w7Z/cdexHomJwaBX2ms9J2GNDVO/Qrqa7KQOD5G5zia8t+wyLSpPXX84vMiTe5V/+W9MmPHuDqYvZfbQwfv5elYes1pJYR5WG1g1BomsPOWHORHlEXvotdL129b3wc6G8RF268sRq9ksTRwWZrEA32TMbvNLU9grbV8U1xIQXE1SVep+qBzOm64PTp6LBej+KIT+hW//P6bYy5Y4yyTnnUwqfXCZF17mwt056Md+JZTpNalm7q2AXv3/1HkI2me7hetI0P8xESaxQuL2GmwdHc0WvRJoI9uj8XNKGk1RI7RxHLItghYhHGwrCkGR7GAbPV7vxNFDqecByXqi+1CHr3FLfIK1oTnIW+eSpYZsnPVbmAAAgAElEQVSVeybsfdEnqX+WddI47aR7lv0oyxt/7mBrlqBNcdm7TM2pAEnJGyx4Y10H8rlD3iBlIm2lMUtgQyfadsEg7CwvDoV6RR5bUWVSttHhvj9YQiuMHocqRDKYDSXKn71mRR7g/AdMOuVQLahh1eTsde78V7NiHa5zz2loSEM1kjkt+D1RA+gKAGNApuCydetBO4H7r1+wXS6ANIOZD94yMfY97zFL33Wl/gN0Ty5odwrIHaAGp94v3fRtHWDvWgXMwHVIeyvydp3KZz0SUV00pD6vYNGAzhaJui1Q0TIZdaU9JYEB0Ny+nrDaLnf+zMP5Kb9BeI4R16D85DoFH+B4SaffJnW/rul4vZyvAFr7wfWY5D9QxbHvqK0pgydJ8kyLM6Qvaapif2u9UAftK5jucrbC6xgeG78CuGhei2K3xeeK7SfjhV9/KwVRAMZbQH76AMhL19klZMScii+/K1780rH/+scyFsqTpz+/Rm8dn/7rtxwzReOfme/vHF9aXVG79hcBnj7Gxs468GOnPfJ5vC9Ftpw+4/Kfn0/V1rA1084HrCd674794NXIzSt9ja78Lk40EYT1Gw23Z+eHz6VwSkK3o70/3k/g5Sdc7l4ZYhfc/nkN6DvgMhSXn15ivv2Ie/oENWmPD1iDnZ0xlvZjFGjMKbj75TWO4w/M343mR5Fr8FYO7Q2gKnj6809QVRy//wGo4PlQfKqqOeUATMWqc019wSM5Ic8pq9nicOtb+vO3HgUmbBnR5VSh3nu22wi5lGOxmT/7KBkMV1SfB3UH2iS0CyZbgLi/KXQ0yr+ShN0cXWV74zJTJ+ZxDyalq3ZIbCiLSfRXTzG3Dv3wFduv7yD/+z+w9Y7x9oPFOERwd7dh2+gfUYuPNIurCHaMP96ZPlsJGFJ4fepCXYAvopFUZH76TxA8g8Js/GdvXkM+fMJXEexfvqI9UfSnDeLoe3sToBRC3B8H7i7qyMDmw36ybTjmxOb+qkHUPxE8f/YU0aJWqAKp6XUgskOln///HH8/gA7ckCLcUBoE1hwSokMisOGgsU7gfim9ofjdumU4j9bFCUZNoZnenvheZFbevC4yq+hRo+L22CbW7Lh/haASAOOPCcFLiHzIql4gK0HhmYLt+0H7Ys+sxu1fGtOzUPx1ef/bz5GvvqV2/Dcfi4H2/bn5J6bvnzqu7MYmuHu54evHsTjxAFYBAf1Zz9fSMPYJ3NWVsH24PdkgqphIJ/HilHFlQL8AeAkcHwbaC6tEbhuhpW1dxxRsW8PeotsLaA1Y1YtCOoPnGy7e31xc0F4ul6xKX6rMGeDKPn2miJeAqshCVavBmryIf5sj15Shw4ON9w8PeDh27PMr9uPA190C6gchhqlKC8i5FqPzbCzXitgIGLgSIO44JM+L83lZuGCnOkUF2tdGKKRcyVO/TyqUJpw15oLGXu4+BtHjO2d+yTGEty75qxBSN6mpHFJPj0/l6gy9fp+OWLoEinIWBo8Q3hTL+gMGxz2bBafoYEEJfm7bBU/vnuDy9Akul7tVYfOKpCbiVaoCoDnE9x06UplpreNy2bCxkr3ZuRYE8vOaRMIDEy6aptxi1WnKKpdrSz9vm5cuHcLAodAhkNWd85h4eNjx8PCAfb/H/mAB833fMUZWpI9xeMKC0cXQhLOrOjcJLpIhwqlMR0Ma6nSi66wXKK8Fp2cEUIIotxx4rfXoYfyYtGAP+wZPJBENB+ezZ8+w398XCuOcVjpz+ioVzlH9wipEEbTNq/B6BtltnTxJbBAOWtDagdY6xujYtoY5uydYdFwugmMA3dd9upKLUaWpzXHy1TxCP0JZl0Lm3DXxyDeODPzYvmYSzq3j1rrU6zx2I+PNGgZKnptObqPb6QFFOt3yCmmMiScheNYu61aENDdxS19sIkC3fuATsvS+4mQmqV9rKD6KfLe2i6EiRdpt19ew+bNztBns9GwTbUbY3bNTBFMMIoxOAPsuAqWgBmkjWXBJrkiubhU2rGLxgG3xDM45PSlshvNAfB+uz2+OVoX3QXOI+TFnOviAgM2m8duSGMPBys/qnIs7McNodp2SKCfw19PplagT5AdTFRvUgikCqGvgc07ri1vmRyHmRGgFP8eVfDo5qQsoMnjOOZo6I9DI+ef69MbWIH2Bw2Ygned2tr2Z6g7pXGeTX+7cpI00J1oH5mzo6rpTWXF7Zp/X2aBN0XWzhdngZTsN5/7MlEXkIeK/OyuSGdCgT/TkQMkxt4QYL3rH+n6z6n9PQCC/pl9ET3syeHK9jycYzDGt79x8APNmKLCOh8NpZFgA3ZM5uCvmMTH2A9t2KcmKzrtVy1q4zPb1DAt5mLxli5zH7dMcOwPllSusPHO9BhEjVMSC/MtVOUar+JZblntV7EwRdeSAlMOqbn5HooTT7sbEws1gAlvDlAYca+VH3GocEGlemavhrHIYHzQodkIlSkObA9FfL5SBmKjUjbUG3iX4hZY1Og/GUHpWF/ec48rKPGuoNucNd13wcPIjRAKHV+k1kXAkTu9xDQW0e8BeYQlGsP1KTHtXzfPuRffIZ6mfUU9ef8crjQuun/v7DFpwH9GeWG1EzkxNAFntqNY7MK0dyJyK3hlwaphNIzEe8C34SEX8Ocnk2++nDFLXT6aqVYS35snGbhN6VEJUI8BuY/fyAv/MrS3TWQURTCechoj3Ip3DeQ0M9YSzIp6QK4iAZbDTaNNQaE9SL6I9FvqORzDCZqIxVp9d6/fr5+vc5cTzuxyvr7vrw9oUgoY21WyiEkS34TqDir140h11fTvpt4y70CqTmXjStWxYA+EiDifuPDeS5kEY90SEQrlGJFlVZanwnxvDW/+MOVwmduUzfm6V03ZaBq6Tr+bvCqUdOk+s+fV1tY7nTx7TdRIg17DayPWgPRS6gtr+mhxInFfpr+hpIs7PXJaqYByHy/GKiZny8+J9bveHh7hvpec5NdHihuuYHtSwavDpgWjvcT5zEVKPtzVRMAnPVGLT37gWABzW1yrRNb5/+H2YtGWf+RBLgkgXK/S4fxjol4t/5HOkdn8LnisUDQ/7A8bXh8VGDn0n5ulJIN4J9dcGWM44PT4u/7hW58OvPWgz0Naoy+r+gzmo20smfqcStshif7HImdBjtLxBHUaRumI9ufA2wfLlbx4V4fL8Xgafge1lkVmRFAuQsFUV7bXp4JTpZenssdv1fomA958YcX1MPb3PF3XeyDGa2lqMtxZEr9/nd8dbxfYLTvI+ZfmnX3/HBVlUI3x0AOO395CfX1+NURbi+NcejwbP/xXHI2OW0x91LY2rpDzTR5494iCUVWFrurymHh+81at0nQdFEWjYvH6fmfPemlUK62C7secAPkFeu0/zjeKZvMTD2w/2VcFVksnmF+s/AcAr10ksUcfanwl6ewX8+A4iLzHevrf2kSByg0Dwo8npqZjzLXR6vECyqKyyA7jvZE3qVIQeVgidsro5wuJ2MX/+3eUu7Klaga6qFmTvGWSfU62wZBaZ8cgR8lcBNheC2yFWZJdJ4OoofcODxrP4HXiwVYnJIfdlQLD/Jrj7fxQqlkS1JmvCEt09wfOJXNB6w92PL4C73WhEgLt/f4P5xwePe1xMrwZ91bbWlrxu8OyXn17j+P0dppakoaLjkw8eIniBhs+u928qGO8V+uwTRLxNARR3PzzH/cfPOCB4IndolN2EiHfOtLtf6H4/8ATApWdhbk0GA1jpDlwuF4ha25KaTAHKNxJw0E9Zw0dX9/+O4+8H0DlRqBOjyybsDjt5aR0Xr6RBa/i6P2A/DlP3nYldOSfkdkW6vX4cNERgvcg/+BIxkFgduVQgtPzptlZk9MW9TgZFvU8VoE9fv8Lndx8AAE9V8fkvCKvnPgABSqY0DSLvTfzjjzh+H4B8RH9pPVKOD+/x8McP2F433ITEcao9DyWCijjB4nznUHxB0+cAimznnJ0NChghTP+oczdR0QsoZgQDrDra/KCGXvBK8s0y6yI3Hmw5HlNxTs9EAXo6tlc9Pn/klPXS/6Ry8v2vueLtxLp/ntj5tsCd5fehJDY8NaHNU1pDe9qjavj4MnD34i6dPwAmdjSxnh2R6Ue7RQX6zBQAhVezuyAB3L5qAnwCLm8a8ALQT3Z3OtcMvtgr6SIzzarP+7bdrD6n4G4wpYY9hW1QGeRKy7RwIVUAX4E2sT15CQA4vg6ITLQ7zzj9aJW5eKLY9wMPDzuOY8f9YYHz4T2lNZzrukC1mwGX1RTIkbiT1+if1c/3+72vZg0ClUxymMODE3+ujuL1iTgQPgQ6oDkuRVESqjns2Zi+8xsMFkZpgFEJ5TU9yEnj2pQ14HLZbP72U/BzMbqMODNxYTnxSpgu4w+HSMjhotwytG5BzXzPldzW0cEe5939Kva+dEvw6JcLtu1izzGtcm9MNWhMMaWYsKUAcOHAGp+owJ8S9rRv6AJEtbGuvbcF4oqLOw99LwtSGbP1tsq3qvxH4oD/pnE+dUAPdzg4xPwYO479iGD5nAP7MUxxhGWOY2oGd/xOt7gjbYvw9fk62D0BiCMU7DsAxeVyub2iRSF4+PqAu6dPsN/fe/9hQdusutR6f+fRhdVst3k3Zff0XlZq5fgY4/CsyPXkmPbyZvRN7YQtbpbs1xpEuvUmbhK9z0UyWUbVezu7IyZo1GGstq3j4oEJ1S1k3PTkDvFrXC4IfrZtmX3KfUeY4ayanJiBZLA6v6ONhdoOB8TgExuCFqnvWHJHUeBuTvNt6ZRLcutz11oKsk3cG3CeIhjD4MtrEDW+7xDKNucdTGZZ7+h8wuAR0tEGS2hh6yA6kQ1CbZYeg7bPzkHGW09TnbXi3wSdi1h5rJ/m96BxKdBpvJAIBiYbGHiVgO8WtKjitbmz5IxI4HLjcQS8pc1t8wqv6TzE4MIHhvOD4zgw5sAxE3JdgUBqWrUluiA0gkcGGWhQ5zwYQA/duner3uHnxbmciU7JU9SroWvgMmDJRvabJd+D68Y6S4WSO0AJuTtUMQ8zBlnZFPq/WFIT90rVKRb7Yll917969/EUWeQV45QHrUmRO6nDSDcskdkmumyLTIfTRyQpQWAlYtPkSZeQ2Rwc5wJiiAEGt6cpMEWWp1ierzp7IFEZ3qYlc1hbNQF7yLYtEwN69zYBvbnR78MNGsq2FILmlcSmPyEc2NSpS+XvkoRS9HsAxwPbkFhFPSsJ7ByrWJx+fZ2Kccy4h6jpneZc8X0HGJzoyYnCNevdHEAQc/Y3WLVVI6vBNw7uKU9qZj9QFJfe5clTAA7B6c/Avd0gUUGnIbQ0VDIIsN+bHrndGZx730zuck5iXgDMecQz1mrcCPaUFhpzzIC+xZjALFD79RCnE3UYQW0ALPgO8Wcn7xUPYs5hKbqqECY4wsXO9PVi5SLEEo3UNW5FzCENWgYKQwbUgbrSclunSelxeXJn+sznrxZA8QhMWpuStM158abPqmqQir3jcD1G6/jU9VFF8FbU68bTr/Ls27bgNz5VJhFSf/e3OR/+XugUfjlBomVEAN0fk2hf03mzTKtckWoXxIVO8q/I/XBSA4X3rJXofAY+Zb5yyP7eED4bRwRgQYTpNxNzWssezLqH4Dq2B5Y1K4i5nFCBNmv34XgP5jj2dZ0wJCHSaH0O8ux8RF3IMFaB+k3oOeXvXC6b11nmtvyugVnrAcprlfkv89nQrJLebYgMhAvoMU+6rTqLn+YJJIkYwgvzxFMRC/11Que6V3mSDzpVrFTvcoMfUK6yT3ch+WVf3tgLcvV60RRP0K8z9KgkBp6r61QucknyO56cpGXqUx8jjWlejXqUelA9Fv3b+ufVEfoykwtDCDtfvb5ePoHRjdkiJbAttbLPqYKP4Q689NPa9Im00B0Ao5c+vR+sWn/gQM6JayjYxmyMCR1Gh2ZLOf/3pNjptsHWrVyICY5sbaaw6ksjZ9uH09dqqs2LDrb04D5jYN3kkkl32nBGI8PXo4l4jqvpY+MgH6D9Kxi7JUNKvwD+Xeo4U7OitFKP6YpA7xvYxx3w/TNTPhtfKvuAC+J82gJyamvuui27UdgaFztHaOP2GI0lv9eknhPNkFcH3UUjDX8Q04cpXxYdX1LsMDgXCZuaIhswmGHWrjcgkOw4KAsA5vz1l4LWXpR7iRegqutstiZNfsjdGhFCS4TkWIkUMH5/H769qOjks5/2J7lP4R5Xx6ZeOAiEfXnF5wE8vC38ITiPn6P+DmVNE8gEnv/0OvqcX375EQ+//oEHKO4gGFC0n17h/rc/cIFDTd8Y380j7IbvnIaV1yoSFj4ucZtFf/N6nJ+gO8nKfADEsb3+MpK+1sPmlu2ESHeLjHKZw2mmP2uqB6Z9BNYrfWaCsSq0M64E5yQGed59IrbXLwBoyj6iYk5gNGC+B9qPHzDfCtA+WHIrRUuZ20BzBqB4hf23dxAAT//jJxxj4OKoFNI6tvYzxhjobwB9i0hq67+8DtunoWHOH3HRP6KI9ZUC72P6ruexTvhyGm096o6e8Lx1h253VKt4dv8eA+48Z9su0UFiivFjmdUvXoKzVZpp2lXSGG/sgSgJwNtrTAz3g0aLNyLLOS9PGrS9OEK/dLnTrEp+HANbZzGTfWnvexR8NBH0+Qz7f73FfPIEL/7XL7bXVbHpxL6/gzZDiVAlfSD9d82SKCxhv0HHwHhb9D8An5rgAsVXp7tDKQeB8RFozz9CSxyoKzA7w/HmL3jYh9uBAwpDxp2KaJc3R7aYDe1Nga1b4cDlcmfy0H2gTg7Os8hKUjetWhRiJLfZxF/UiP5bjr8VQF+zqOtx2mytYWvmSH7St+ifdujEPry7iZKz1W8+fugiYPP85wp8khzbqhLm6AK+6cbQWYHOjzW+9I0Bwe779I/3Xr2I6P/3Z45nekv5t6P9KMAfDXdv3sRnihcQAcY7fTS4f3qsPyvL/vnj0ft/AfSHv3eJf/r4c1e8UhRvnnO68r9qUkn79V7LK13GSIbEDCAe7KN09/zFej2BBcvUnIMGtSzYPz3g8ix7WbXWIENSGMEYpgBoz3IzyPO8PB1EHlLEFHV4D0F/ITg+aQiy7s5Lq3ip8C4ZQL9VfQ4fR1uEdEK0QFgRiFR0taikxYlNRVrnNMjrw4KN2qZBX9/fYz92PIx7HGNYz+thleeLIXxaePV5zuxzvx+JpBi7Z1ZXlQ/+PaaUZ8E1YZbHDUfxKZvWAo9+gbkaJLNUxlEpDeMOWmx9D6GEFlef3Z2np8EJ1nEsA/aX39et0ygSwv7BHfNIA+0qeO4Ov9bY59yrUSLA0dAuXmm1bbi7u1g15jGhOhAgw8KKCIdP3lpU6PmG8vlboZUFdp3sicx9m2spdFTE25K+L8+cF6Ubz7/jWeN8dhrYcyjmPDDGdJj2w9oRTO93Pg/ve+69z49EUSC0cxAvsNBZ+JaQDhN+kGRlDnJ+nNuv0K7Yi+PenCoKxcPX+3I7C3bd6lI86njWj0DdjKpZKGtNoPu0zHyUan/hs1TqMx5CeN/gO4SQZtbsZsFw0th+jAjYzDmsyl9noWkJ/jYvM9aLnHW2dVwizVEMFAzaUy2i49QyPIcHdPwRHCaJzy5CBbn+5PqqrutM0+R6gkmej+9S8p7HDwuCzzkXthw/NH7UglRBhuGQLtCerYUxxBFZUpVgDnOAZe9FzkdC7Bsc9sQGwT4OqKbhpEETJzEsJXAacsj+iWl03qJz3pwpEXcC0BGmYtXovZWEjURVsf5WhccBYFUmzBPgjrUZ81YXTt3ZN2Dnjul84WHH7vwhq2vcWVkXMgV7QKKbY5XXd+E1g1Na4OmwSqEMFm/OI3gvxD1jrEBkhTMgygQ71crrOPMMZQAg9KYbxawWNxlsWflm/DGIntcI+hBPYxO2nXF68PlYAk1+XsobDbhZIgT0EjyvkPvwkbN/dJe+zMNCLy0Ji+KhubO41uFFb8ppezoTZshuNZ42eSSuVBcp5ytgiBgqEDq/y8wbzbZ0evR8fspi7plATUBD9E4dA8eYtoaetHYOvsSAFypZCAbg2nryCJx/2k6QqFzjYZD4hHCXrEqIylFJ2nW5z6oIwGDtrAq5ICLdXL0yVE1+vwSo/DEMhr175QhHsfIaiI0rVwoQOtt9nqi3h6MoEojOgrz+KeG0J2+Zc1hlocO+o6kFz+dtOg36cn5mrcUO7HN40iCiN6J6UL+1hjYnhtMIK9ddxCUvgleDuL6pcPnhWe0W8NGoUn7M33vtTI0P1te++Zcgr09xJjryNImv14piVy1StxAUfc3XdrntOoYk+2oHxJt5Thn/+ZoxSl0/XwsScJLzhT8VO0ThoCrBx6z1DKt7rGVJ4eXFGL417RFE/+b7q93EoU6II4qYDB/iVUBTMQWOxOVIItPq8VpTTG3oc0Jb902nsBbp1MNcdirAnp9mDzGZpaGJIbM1MQSMSDyttEICjvnOt/1hgh+EXKmzr5acIy5vKv9eKp2QSTS3q7PO/EO5sjY0LRqdwoJuHjirukZdJqW9EnPGZ9OYg1vn55BKu4dlqDnWCK63ljJWkJWjZyLnXo3nRLHxefY1IkJM+3naTu9L3S98uewbX+uCmFSTBNUUszizJoox+cKc8Mfte/6Fg+vVtHnStwXYqhwNfgUgbfsB68cCKuOLmAh7j3uKtgqf0xOvTLdQZ9UuU7waj0mcuTdMdqsaEkIkb0HDJzNn6rojqhBZda7L5ZJDiAeprapPQdvZgukTRLsSMBnLdv6MxABbFp7HxzWo9+7Icpe+YT9GyDaIB88nINsFUxUf375boeB9TinFK4Id7LJBA3NYEnaQo/O1XOfUDVH5rxgtMhBOOWXPlUnFtC2+ebRCLI8cqmqIc8U6NP55HaYlx6kFAzdvC1xZ/3XLNVgR1XyvaAyel8RXswxWxtv4PMX3V2+ffhnB8fv78NdXFVnLT525+vmtI2WX4pBcZiknKGBto5ZrZTBwGQ1/KULfO/xsVcWTf3sD+cfvuPu3N2jN2vlN1zu3n17h8GA7r/h/qg+6YJ2nf8X1vvnXX7oZ95LR8JgjdPxQsxxJ9ThGzG3vG3QqPn/4iO3ZkzDEjs9ffI4B6l2sRjfxano22wswWSUS7gBcfrTXo1mlcvdLNaQuEPtgKtrPL2PvK4D7B0O+6NsGIlYwqbvjRxz6FgKg//SSCm2iPpe9Tm0i/Oj+dwvrpU60ou4LXhfA4suI4Lm3A2NburShJAoJAsK9GxcYc6DNhiEjExYBLy6QolNQRrRgp711bM38aeErnQodA3McC4T7cm0pz0l9DILDZ0elmU0z1BL7BWYnjyP2JeMUTRoul4slNIePRbAJ8PD2PToE7ZfUx6z4R4F3HWgDIF1V3lV+f3bbfOQpUVrSIbh78xqKifv7d4BmWy+j/xEIiom0UK4ucJ+JJ4sVjpSoNxZkv2zdE4i9xJf0X9YZ5TlIRSdN8pvy5n/y8bcD6GGkUesII8HlPJzhe7/Yu8sdtjvrGfvp/qtdB6mk01Ck8bAoDeVgBqDp0engM+K19y55ciiyoQBeq+V/6nhM9y6zgq6EAL59xq0jYWt8fDE4xfHHRP/RNtjdkyf4Kr+jz5cQCJ78fMEcP6JtlhFyfFwHVvWWKsDpGk6Bfprn8ncYXEBwczLhmEU9X4sbRgF9ET3E5zuqvabI9leuXZw2GK/ZXspJc0mlEtffOB1/fVeG+HCaWYzD79zNv7gIlOshrG8IqIzDkQ+4n1Z64CVJF3fPG/QzWE+KBsH2/HnuC99LW9+8asavO52RP00YJ8U0YX+5uKPKMid5Y4FAvyguPzTqCfGcjYq0Gsxue8lNCcyP7mhugt7oVP3qMC5bBBBq0DyC5MDirGzCzKb1fbixnS6RVKK5fq09hT64E86Nwq+fd8z9wHFMHGPH8X636vNxxM+gAx7DaT4rwh8NpZflVUVAwx5qjkDrbSqxr5QDLQpyOE2LxV+dJYKa0WtGZ2vGyqlYbH0zBzUOD05lJjIAEDpYxQB+OhqGQ2HTcVurfi9itNG88mY68yUk7ZU2e1qr2BehxF67f5LQ+b2ylYowDqcL6cTlBO/Xtg2X7v1kpWUiE6+LCgvdXYaoO3wVxxiYY6Jjc2XUFDLpHaxWjqkRMaXOq8xCqTw/ls8T+x9z7Rn4UHcWy2zu2Ge15Wk/kFn4zaJy3gMKk/BEw2Gah619a8DwtQsePnVJSonAGlYjPh0XxREYn7ssngNba9gfHuL9y93F5vNhgBUDKSdYVW6ET2NlORR4hEr4sctzyw42mGDxABqS3kOm1dSWQm88N3Q9CR2md8+k3Syowl3bJCtaQ88BfM/B18+CREnPRfGXdOHOaUEaM94sCNe3LXSb6c4lsMUGBsaURAfxfSWFLgSyzpxfi2sabFI09KOrozqJ/9bBJ10P8hH1hKuYS9/4awW67bsa0IBwfxOuudKQOAyo34v8T925JzU4hcXxKwudIuRZBCwkn8imSEuV6Y1Dc+9aBYGgbx2Xy13QRetileitFSUEUYkznCcNHQbDSr1XXccCAx+pd0xVTxI7LHi+O9oKBJsHc9V1Be7CujZGe54ksihC6lDctmZDNeZeAMhUtF4c/3S++hgXNCj/DuEzLUkkA/GtsU2InTumYo4R8plV9coe7IJICFBFwvsv+oIEbQkTF8R0L23qQT5/1ObBPJVACRAxuPO4FiRl1A0NMYzP6CN60mnrHiMdnvRtOjGE8+Y6GP+zPu0ms4c79g19oEC9ugOA42llTWsiBuVr0xaybSq8d6kpUU2Gz5dVfUalojW6xpywMJSPs7UecHRjIJ0VmvdMG4ASwpRN0nSYlzB9T72063g4vGe7YDqM3NYvmMPHE+oHdVB/bvY3DqkggRQ0+kBvm8FVTwWRVnJ9Jf5dtLSQk2UJw4nAtbZkLe4K9ilOKD3EGNtw2XhmoS4bdU4cx8B2dwGRU9i6YL83pBer3Ey4/uUAACAASURBVNXl++r0MgDAYWOnKnozJJetCTA0gnq3jha8qwNNcw3ceRUtFKYlDM05HeGnoRGxKhIR4bTPZ0OgZeWjF6QPYeKn/RApYXH0mcJqsoVjWWxH4OsXS+RL+EG7mwj5o++wSb0737OevBnc4TiVYxPyvCI7zjThYwrV+Cy0z8eVsXGb35wlOmUVqv7oL5vr2ss1iq7dWibEBLpNva7z13OQnGO44olnHwPOHyfzC5kkplt5WDv1UN9vRFagPOa4yGP0hIVZg1MCiesADnWuApnDAvQC6BQoqzznzKormN6stIXCPjw9q78+f07ZGz9Vv17Egu+Ak6yg8rnqzklIWk9FqnTi8zJvnH9zVc5vJnO7qSNeLS1pjD9Inl8TWilHuScWWVguvI7zxh6oQfvQP/jSNSZuVqQOHPs4dJfTMxRat3FonLQkScSt034KAQYYzVTZHAr51aM8epB6VQRo0/dFhjtsvautykf1MRYdEJCl6tdOmeVG9uXFHpR87pwr9eQs25vRllYATaembyOv8Bz0NTjvVVZNatBBTTaukP6T0Jb+7bDd/Du0JXSkVRvrAWDqSKkSvF2g+mDv4WJysA0cc0K8T2/uSHvIqgPw3xm/UWy1C1cNUvjYOKygo/t20gaIt8+QQV6dGygTaPzejaEu39tNDYUDlvBjsl2W6nPqHsuiFL4IIFESqDK5j0A6ABXTuV1eSpPQJUg4kThC+i/Hmc0pgF74I7WhzedwvlfIy/S3rMltNhf7fmAewxEHE76QreU4fkuYbDh+/5AanU0ZGtLSrnuWY0JOx8K7KxcSH/Ph+ZEdwIufXuHLbxbIHgAOH/6AVYfmNcvV+JI805+ptYYJRYfbaCK4/PKj6WJq+paHgKEleD7qIIETo74tj7913GRXf+EydR6v1J/lvPWiqVKnPACuVYvh/DywWJ13HJ8+Yz4TNHmV/sQmbksqmGirqjj2HRBge/4EcN40Pn+NdYd4PETIf2xh7354mrqI25p67EYPfYO+atB3wDEVXaxQsrWXMGS+AdEP0N8BeeN2tbwMn/mz//Uz9n2H6sTx9j2e/O9/h4hg3x/c12Y84vLLa1gSgKXumM5qPLD1hgfycVcOXnohw6eSaGOycp3YGgSPhQwbToIfMMk8fDpn4hDEObS7yOsHBjq6JzPae1lgQD2U+pL/eKs1Q0ezYqpBHqaJtKUeIK4olT0S3r14xVV2bQ33v/6Op7/87GPWhf+YqLP/xjgw9IJ93y05Ywxsx8DDf/2G7XKHy5sfsb/7gMtPrx1d03iZJTDDkX1yJ3z6z1/x5Jc3gI7g+V0tAeYjqNJybSwh5+7HVyHjBM9hWp6g68Q+Ff0ewNMO1d1adHkiuwrjkGbTPBwHnj57ii/3D7j07qgFthbmOxdHQIUVEJWkdR5bazi0oKJh3ePeiPdm8hTwOD/4n3L8bQh3CcwJAcvFVLE4d5tYIO9yueDJkztsd3dovWP7uAKHL8renznOxgoQBusP7BVbl4bK/l+6yV87JhQbzLl9Jay+cxQ5mYf+kALemdfL//gP3N9/DUWZmbr29M+ht2Dc//QgviXG1o+q0rCMOy3ZZcfEOTOZ0//k42p85Vm+SUImcW5d4fq0PzUKvXpnfs4UEBFBf5YpGFCH46QAUGdRrEyoi6Z2nfEwXUGUSEzzUKMpZLCMujm00KN9PytgMrCpotAfgPFJgFql2y1jqZ+qzXtU31HYprOd9xJ/0YozfHFiA278pKHUmgBtB9QgM+k41ALlchwHHo4dX48HzMOc88cxMHRgd6f3CKOlLoSP44axrcogqDvXSmBkzdTNjSBu0KTBKzcJLZRNs2JN2NN4FzhsmV82tmJaK1TQIyEBgnbX0Q7FwHF1v3pXt4tPx3XYQMq/+fKf2PGudFneTDHuqIwJTFmj8ioWHLpsm1dtN2DpN+vBEwbnekPTidkkYB8Pr+hGF3T1KtHe0bYt7kmYNfH714rz5dH53Aw4YWWN/gCIvNU+ocNMRxHJIgHAgueuoC6OjGFBkzEdDnvOEqzh31mtBzorFJ4piJi/1XmnMTZj6abcldQPP82+c8yJi0NEqcKrUhkwKw5mTVipcFAXkXE+CCcUvKA4UKg4N4dCUp049j0ySznfN6m2GABcR3EVshGtoGTIbtvm4zc4bZtCxRKIzemIqup0/rTMoG0ODQh34kwBgeMI/967jYWKPu+gqp4U5co/nZBhwKjTT0HeIB8qf996v8zO9UKcjquEh0cOkSxkPCdh1OSMukRMuKhVcTnG/F2TOJehKwpsKCDwPteTMiMNn/iaW8OxzXgpQbwR8xeyVZMXfXMOMnhu62v6MDO2RQxesVoOwys3hyOhWEsG29db7w6fbQPhlqgJp4ay4ugTx47jOLDvDx4wvuNtgobsKWisZ9BpSbhAOgWj8aRqBq1h+1SnQTSLZ1ZLrOWKWEJHqkFzW7XgVO+jroigMI/pPbrGmDEv+75jOsIG2RZphxKurl9rzeDU3clG+HURe6bZGpoq0LsldxD5oGXwXARRiSh+naTTIpOKjjYKzFl9n/PASdYQ2kCNAzQU3YD7Bpo9Q1VLO5LscW8w4QZtXPtBFlIBg7FBr9qAZnyha0tocFGrxhSFyIAl/EyokpeKB5iav2cDbj372lviDJb9HvdF2ecpplYnSWEDvmWtFVHrQVvjfkfrFzBJp1lPG8hlC6j8KYIFM8RltfVct2r7qQ1zJtJRoPwUYbXsfDq2T7wxnL2toUkvfClXPQNwHhC+0rX4xrof2EqJ48+5BI77B/SozmfSl+87TAgdy4fDt/u+GGgBpXpznaiHi6CpQntHV829U+SJ6sQ8fN3EqgCnNDS150ye6nyZs6IAOObl5iu/jTk8y7CgcVk+O8s60tx5/taZN127LmuRQj5GjXerDOG2ON10uToNnAx+PyJPykdBN1fn+ox94zIp2MobMd5kOua/cX2ZMpi6MpB0flrzf83hNge8wNJvE/DtSN3Bfrh/rOdxyC3fk6YGluQCRaBR0LCZMiGzRaIwbb6qtzQOrc5e0Z3jo6rjUP/m566Ha+Ejwc/gCbXi3y2BStpy+ex+xdgEZbfUX8Ixkhfp+RHiOerYeQEGpGnXyvph0XFvXLRe/0yQobamDiueLZ86LZb5DjsK5Bm3b1plq9Tfy1nX/O27eq3Tepzl+k4Nnp/165hvrokj5hCd47xm3zu4D1m8MNEsiK4S/nfS5DnhBU47czJRcaVbezxqeghZNydtNuPhNXCuCg/ArwkDQauo8+E669bMZ9wMvfAY0+RNE8h0vuYJ53N6iwwR0EeS+yh5JuVnnX8mPfiTl/F4xehgAi5/cj6M96hXjSL0rEBZ4T4srZTymRGhnyoC5A6g7YiJgKlXGOIaZQ3EWLHGBUy3qiyLkN4cd/AHzecA/LyTfXGDiV3pLZyzEClCn1d+n/bs+qXcbJnoRHac9l/cusxPfa/DK8/fsVLzuaOhEJ1MFgRWnQp9/xHt9Q/LFYOPe7C52pNc5yHrGG5tRQWS/8vtyvn4WDIYPwB8fPs+CuUYPOcxed24NBFGP0Dxyt3J3Gjmn3j2bz8BSDj6vvUij4Env7zB/T/e3hjd/7zjmi+fP33snIWgr969/sOO7cUzHJ++YN5NbL2EwdT2OKuJIUDGl9MZF+aLeAtO3j425yyFRbx2Bl6tFcRLHPgQdmLvr6wKO9qCvAJ+0RBRVcwZ72749I/fjQbDVjfe3IR7xAlVaJdroAdJk9jbLIpjsU6Zju94NpD2EHmUWJIL22VFy6wbcjpbn2WbxMobBobraJnUYIH5nrIr0F0mdDJo3wMRTh1S2nRHRzkZ03h2RT4EK8FhSJCavG22ZskYEzjG7+jyJp7ZWj7YNQ81dLEmm8HoHwM6Bh5mRxveGs1RV2QOsAWptWp23gQJWp9ibaLYrrdS+TMF7p1zcvo3WNHPMQ5r7yGCOT9D5Tn6i2fAl/vSYuAC4H7h+fQPTFUc01pq1n23+OAEnqQ+8fU4wFa6AmSCgQCWKFZ8CwtN/UmF53/osc0T9CQn64rU/Y00SO3vYBJcXCVkswB0cknDGAd6f46nT59adZU7n6I60m9Dg+jRcdBABRWG5r1uzen8pHU8FUF3BbUXRxKvKyIJ/1fuwfvN0M6RkBZSz3z8eOfoXv/7pzcY+wG8f//oubzkC03+QxiGCI5zKO8m8EZwjH0h+DEtz+zhtwPhCEAh+JhLe4eFJp1KIhkeL0jFh8rRaSF43RVMtTxTZZLl9fHeDIXL6+6KQXYzEaRTbzkcp7Y61RgkyXvlGtKwqiM7G2z1Hm2TDLSc9rH1zfTMLS2Zl/K9JA85/X7sc0Ud/fmase78S6lI20qy414TQX/qayjA+Gxz0581jPuJ9szg68Y4TKFrsD6sKPqyr7nBx7gjSekOtfv1Fzaep8+e4v7+HoK2OLkNGs+0/SlW/aef1KGtk14a2Ce0ZSCdvdAdBhUCXApcr4D9iAVwR44pkenA7pqUWVz81i9zDgwxaEpz1HvgfJ942O9x/3CP2RXHw4GH45NVIM8J5iZTESanpCNjlACDnvYdq4lYFduVHMvXxzO4LCACSLv4eBMqPvbuDbq+piiNnjGiAtUBwuEBFlRW1ajMjUobamdQ4CJo+4apB6gT2ZoBY1jQTptGUEMA4+X74bzYBaYUZ7qsAdqoboO4rulpGlJ7qVIGRFgZgFfWTc8wnIJt62hwWFYmbqjD+s4BCwZZByj1ypvos3vpDqHaAa/SH+PAMQbutg26GWpK7xvU6WbKkc+lcOO2ISxYJzj1PstQJps0X3vuZs+tpkGEZq9h1WTHIFRmTycSZ0L4HJ6wMgHpav1KAUgXtEH4ecE4AKI/M3g0p2WOT0xPerOHaW1iDM47HT4Of0zHQAxHETxMOCuCUfipwqsiMCHoYfAraSnosNCyVL7H91Lmk47q0ZoAOnHsJucPd0qZDKWucr1zVNVTLq2lxGW7+LxZgHO7dE8oMvochA8mNLYHEGmjqEoms6ntcQZirLrYAojOfc1JNeH0NXDsRzgFpAFzevU17Hvsh7RtM4xm9n0mI8i90NKx5fyc85Aw9dx3EnuM81J9KbUa7XoOR96Dg6iSS/w5adgFqqOmYyhkgmklHN+2GVKJ7VE3hOo4nbLIvthrsPKexuBR4x4hLeWzmArrckto1LV02OsM56GIQLpAqyMehe8Fv5OclHjedBz1rQeEWgT92EbF17/Lli1Pjo5+mFGm7vhktjCNywgYK69pdNDE5CzAZJaTrEIZny3aIofgc3B2LAJZIV+NXj12jDmx73vMweE95QxSfYRjd0rDULMT7v18aeJVfQgaRqVQpdzy/SfitGNfYEXoJMw519V1CvbOHXBjembSIGkj7itslGNzrlMxm2Jrzeizm6HODIYxBjAFBwyOnjJmcz4gU3BjG9l6nMqMM8ia/FXEA52j9HKbVh2lDkk36LzxC0c/9uAlvEHqgV2bQ+jy3qU1hCc96ByY0jFbItVIi8GDzmQnjNDb1dd9OnrAmFkZT1q2cXgFAGWb7yVl0lbdU0DyMG1RbS8QHMfAPh8guEdzvnn35M5bCHXjxd15pViKtc1ZOuC37QJpG/rxAMAq8PucGE28l71CqbNQXuq6dk0J5c/ns/6jdk9jWFOTlzOroEGg/p3pvCdoU0+vW4doqURC2ipTWZWooa/VxAnOoV0Lrg/4/paZVVFn28TnTXuP63Xq80yacbh+QJ2WFDpSB2p9c0Qf37MwHtOgHhiC88eTPUuLpPJaSlTXOxVm72gwKi00FheisDC9ObzXGvdZhOCNQ9W+G+OJQea4FnlQbh0DWcaV+72uTciXXIB1Pcp71CVStsb2dFuILXxsXLSlpidailjyiCJpzfQ2W1frh95Mnqo6wsTVkNZ5KnpFfT7ObUxbu34u8xSsVe/Ba+DQy86sLdEz5zyqlcSd4VqeCaa2DzFHNB+CSZqEloYOR45qJZm76lA+tsLH6jPlePP18tsGhQhSUXWBIVEFtKfPI1+zXZo5SJvrVWrCDTMjMuoV+7DK+gZzUHcm6ygwMZAdbYpOA5j9VOaNvG5xutqkrLyZlo/bZUxY7lt3f50l0m+XC7a7DWD7k62HDm77yH1DLed+uTHFXLv2IRGJSlSjorQJ27Z0k2syIFMxpj2ZaHne4C0MGlYZx6TknJW63nZ/81XRflRVC9aq2bHjONw/cItO6hQr/48HFia0tGbofr1D0OGlEzY37tsNnS64o32mEKtUFtLNqhfbJfJZBEiUsnj2NDKIgpMJAxlMD33fA8ZVrgiA6c9CiFw43esw/jrJi13P576fPmcK71etiuE6w/S/JyRaPViyoaEmTbhdx1ZPan4C0/e3TPL2pBobqGYCt4r9tM2YKwQWIVFgkneRbn2eniavUWTwnH1mBxM23QZr3rpN5/RKfYOdp809vGhNDHopdF+nZr+3/SOeEFokSaxVoMUUOs+/0z5olzsAGsmWrfe8DuDFmymLmJg6p1gLjagE//wt0YpaJz/eeyLn6xdh41A+CTypdoyQA+3ViyjooR5PX8PGnvNOzyxyI7pkBEZLZWodZqgU/r2m7hv0rXRIBlfJgjnb089bywb9upJJYhLfV4y3gvaz0SC0QeewvtCgLkefjjl52sX8LDpGahOuOyw1HnxzebZrOV0Tw5ZJ4PmLXIbbSPYQ9RZn9eAsz3lScWW4LKQfWLxCtig2fL/8BefbvCSLL3LYtu5fPn6GAOjegqFvNvMP++Hfq/qPtTaanz9h+nhcs0Xv9DvYOJpxX7PJdEDff8aTn15jjCPGa+Oz/SSvnmP89t7Y73E4i9O43pJMrjYWHYqHhwdIa7j8CEh7hfv7B7MVHG1AANz9+0+uEyukN0fsMl6v7td7cMHPHvGq1ooYo0URSfhznXhIm4BVzlNv6s4LxjjAVnJBQ1MzwR3WTqs1b+811VtOjsW/YcV1EueQbpo09I2xAvEBWQu5OQbuLhue3F1wuVhcQfUo0SYN3bA1RaMs8KR88wVPfADwwufREN0OzF9/jaD605+ndSSBoVEe2qHHwN3lDvthdv+cE/jxOfTzbi27/uNnzKG4+/k1Hv7xOw4RXH55HfLEUPgsiD7ff/GCHY15vPzyI9p//gPNdaitd7xtMIj5OYE5cXnzBkNHKaIC0H4wDdCTGnpQcAsEHHX5fUekgocdKtbrHSJRub9tLhfd8N8PSw+yBPvc8EQH615Rr5NyScMe9a2Ka61zfWVqBhkD9VbXiUQA9Ewy5Xe0+LPiQqlH/6uOrY4thn3DGKrvUyBH6HvlaeGYZQN6Qsq25k3nN4Zvi9G/sLc8rjLVzsajC5DL5YLtcsETOoTnRDsO9IFQsuo3uSg54Vg4vlI2xIs/e0j8e7k8VuAvIdCea/hRaTuFILL3CHJg47DXGVBuXaBTYpPZc76A4tNyx2qv3Rju43/forWgfM7qN+bn9H1nqcvtwqlzukx1kNwS5DUh4tYjXDkipLxupvO2zQXLKY2QMKP1en/pOBPcd47HFI2ryyllhinn8hSRjALPPpYGzIeEZ1YBMLhSFJRUDiYkPktlJanY/j0+HWivNkgDnt7d4eGd9YveXk5Emqxn7YtrQlG1AwAxFomKc8LRRM+UqEBf4UWjT6x/P5wZNLqAcMTFvVzpny6YRQ4zqphQc5mYOrB/3vGwP+D4PPGwP+Bh7savyDMaZ4CBIBtT9ufK9/i3jdnGwGzCCXVYfBtnK2BQC18qjD/0R72mj/jtVdk0mgamJ6hY8oL1Orf+nVMVjViU3LfkcQowmC5omBi5dkBU/dsaUqkCtt4wxXq9aBCpUEiE8zD2eTg6ktLSUV83gDkfol8p50Xhhq4H2VyHiipB54FDDYo3E14Y4LdARu+b01118hsf6NvFIPEbn9cVm4NOsu7rIgAi/dvmMWCBGNojxwbYfkII662p1JvBLBjD4US7B8+8KtqSADJPmXtMHBI1544qfOMsLpDG3FaqrJC2XrddusNVTg8oSpwHf9T4LtbfpEgGIoGsOM5+S/DEDriDfeaaOK3mlQTds4IVaooynwMIRZ0H+xrZvBdoeLU5V9LhibtS3AvMaXy5XGwuNvY939zZltVW5CnRv7fIJKsKX/mWGSBOZ8h9I63Z/Au3nyVPQHan53Id4TV6QONuzlMCXQCaCSl1f59+ss97Q+vkRwjjicda15ZO6fORVV+UrRK/8xzLUq3uARH2VnQnqSDHFjJBIvi3EK5fk3DdE1V/ROpP/FkWPB1L5H/kt93PIVqKAN6b0eSk7eYW1SjcxBk4v/FzPWUAWCWUzj8bvMnSMPBEoNLRhgXRt81k2TyMv1AuBF/2uWHyH9eEiWmy2VyTjulgvlrTZX15LTdYXMJFK5Mwiv1zNWf1lLlUQs1IajHZCTV6beHA8+rpMTxA00rmuTkKNSDJE3GD42PgZzrfH5r0wOA54Q3h+pOqAsP2bKXY1Bfrb3s9daJpIphs2xYyalSjVRXarSL6son1EoYblKQ92L4/00bdfTWIFqJazRmx73ugEjAh2Lld7Ac6Y6NXed3VYWMIQjeuW0a4V11ewINURe9XP0/qvuQm9EvMqdiP3eiN6zjZ61TjXs0TbZoiEAIMwt9lC20eMCmTDkQBpjshTICmHuaBgdYbjuPAZVwwNwskMVGFs27w7/BgYcd2AVqHoT+MkWgF4pWrYs/Jx+WeiMBpQ9jCgLWWCTj1qbZHPCmQyAGMZXR3cxBC9WyGhS00Lc3z4cvMpfWP2mbJqL1v0N06ZqLI9pW+OKw1ob4tDApBU0SWsGtY8gWD6FbBDigTaHyPDg8oxf16D0oKJ1nzxKBiz3J9+I+47mTodylvipkHnSvSxWPHTduSXlzSnK9J3ZfmJM71Ji+n7WRJdf6X5rjrfcuTxfkmn2b9CMuC3Po7LwCoJdXHvZFrnPZJ7vdqD0YAvTfn8X5t9eQywrhLgzCJZsB5Dqfs+3P+2DmmFmdyPPW2s57JazBxeTqUTytKau7BxjwMhK/Kv1dHRDsl37Jg5/Trt9YiuNVcPklrlhjN+b2lIH1jFpBkVh4y1ywr3/KZJhTaZrZy8ts3NMwoRbV1nXMuJZINDdO/ywCxBi+qg0G2aTsxFQbPtYw/k/ecF0BzL7rcYxuA3iyhqfeO1jdsd3fYnt7FdVrPxASE3e/BdJ+eSs+p52QyCABLwAOAimDj42y+VvaIlgBNJ3/QB9QRv7hWEryLPbrNTzBjj1NPDUcxMjgwHRnMEns02m1V1Jd0MCN0qXy/rIE7sLvbh9o7NniyqOGfh2IY/NP1VJKrjWH4nrlBm5xjJk/PlC+CDISSn7CyL+BgNQPnoK7lfNJ0Aqcv563KqXedmsNQJ1+berfTfQ4mv69euT29ndCkbWQJNqqmn0yfEAaSJglHBIaoIYAnjEzqOz73jTpgQyR2BeHNAbSOT+/exfvGt5x/ieshbvfP6UG3CCbPsFnH/T3kDujb85iAmBfkvPqQcw9IpwGKMGxVI5C1XS7Lfo51icAGybwoGzN5xNI6ImixJBE7PzHYa08CGBOcAAGfw3UeBfRjyo32g6B/pDzNQwC0lw2tv0C0PwR9JWvVf1MmNyQ/4ljTHDQ7XGmfYJUv6s9Sd5w/2vXTn6aErQIrxxyn6wMFHv58TUmZuwTe53s0eQVr9cMEwvW7S4KeGG96+PWPhQdcTexfPK4C6SAvOs93smEp/64n4Hpirs45a0l53Xofz1c5XVuuF6iO239Pt/4YYI0kApjNMDzhd//0xawf8i/XoaKVmSemTLZz8L02FTiOCdUDfeuQsqcFHkh8/SL4gupwPUPMZgd5NnUMG/fx9j0UwPbTK5NF+gekvUb/6ZWdNye+/OevePJvP7ltLEX3ycIvJkjRYhJYEkgTBdDNJiM/4fyTr1PnZaC9u5+OxarhA5EIkIeN5M+TidSUifZ3b5v7wCR7ofs1AxGyb+En09E8wdval162zfSMtnmSJBY0rfTRNAiTCCpSKUxuWOLVRJveasGTEcdUz5m39RnDA81qRUiU96rm0xizYX84IE8a9HC9QYFjDLRAqrRkatkaGiyB4MmPr33ffQBUcScNhycqd2l4CuATmZQqIF5dPweOd5+gCvTXP9h1Ya0CpSsUnQtZ6ErwcAxcNksCo19gjLGiA9MGE8E+Z+jdTOBscY59X04uDsXqo4KQsL7PEhYe5LoDfbz21llnii8un/+rjr8N4U6ivnWc7JHIimCWO3Te/N537gjQSJWEkaOErK6wCeAHBf6ACaSnigA3T1Xi+uq3Xv+l8angyz/eIhSuP/FEjSRQJLeWr6t8QJOfsG1Wqcq+HOaQqhJE476r2n37SLK9oU3cOgKL9Sza1qO99DX4oJCXAnyYty8ttx3zHAszoMKqON21XjPe02tBe/0c/uu4/cBr5rdVq5dWHH/uKPyBL84bmHoEA0n6FMD9be0ilVDB9gzoLgDsXuzV6OPvAtkE91+/xvW1eWBK3dGosKxQkeRheg6eC+SZ4PjSsH8eaDgs2PTSqgKPTxN3L5kxK+4Aa1al17h+vj1rRpuwwmlVvtKRQUW5vmdKh5smy7yQLsWFQjVGVeEBazf8pmVjqShwJ9CvDQ/6EbseYRImtaWhUCmwCXDE+tJoq7thXWnCDvIYXpkuYYSQ8VM5gVf1IwXNDaqgaTLVBX3z3ki9Q1UcEqjuvTKvJm/RnrTo73rIhDycN0+LgD+NCSKPjGH9prbLZnPgmenX/PWs+eZbq+MqZ49B4nSKldN8jU1hweK8kimQMYDesfUWSmj0evQ5VnjgrQlka7joxe9lQXNz4iksWK9meCnsdWI45/K4ci2edReV5rD3bBwlGOne8nB1ilr1j24JUUZFhJkxpBlPVhlzYD92PDzsOB4eLPN1EO7ZgxSwOWytOZKA59nKnQAAIABJREFUQagKNRu1e0fGHhdPSX65lyp/wRAcyv24LmHdn1qtOL+uuLEf56p6lWyu/63XUtaec84xEs2mLEgOmDTJ8QdfcuceIcMLfc0xg2fxYKYqKz+Ho1UASFjr0EVSUTSjVxd9yQLGVsHeWndUCu9jOOnQNmQAIDrk2HVpfKm9w4Qv0mwrPDSkvI/Deg86DH1dq7IfV5582skxfkA1x/eYLpDfqVxByk8aW82DIjXYZ884Q10MvdurMaI9QZHX0GxnEOupIw0+b82gAJpfx5atuTGAqOZQh9Zqkqgprbfrx415EU9O8LmEq7qur6J5hTcQDlQaK0wmEyCDn1G273xgG9Dh84a8j+3RGXthOC8Y0yqdGLwMmcY1kbLmZ8NDXAl1fh8OHH7sYyXcvBNFcf4i1oSwl62Zs5K6Ow0tVcU+rb1KazM+t4plT3xTru1IOPdSVcP94IM1fSBQH5w25qogcr9k5QU/qHzN9m9tHyHL+AXdHhJQN5D9mmNO4DgiMYM3kRgQVjuqLEG+z71DDcg/nwgnaF0Xwswr1wRIuOIyfnAqJM9bAut+TSaa9Uh+FPQukJZVyBzv+R4iA3MaBB554MR03ln6o7lToLWJrlbVPxvbarTgFrFIYs8USVqg3pZ7HmJOshq4JcSfOLTg3BQyrBo1Rq/qDi0moCTKjenScDrPObo+CDnYIW0znVys2jfRZ/gokrqeZGJ5rPVjOmAYO84frs+4/d4jrPr8zSq2v3mc6C+CYKBMAqaOiPOSZgRq1acexLP3quM0K85zBwC09U879uoJNraU8b+JGhVtYZpXV9Rvq/NltbHxDjdXmcqurknXlP9F+pru5xdLG/WkKVc0o/pI8s03ro5FZtfBl9ecR5vltcr7PIQabJeqOy6jemwf/LWj6hfXN3Fn2UTqVM5nq14Y1Kha2sWFguPBVnuPvuX1WfJ+1DkBeK91+lwmBm1nrEnf5Wlwm3Iqr1ePqJ1+Hv9W8n8tvF+RtuMj33/syKHTnzB93pKK6zWpZ9pYiMLEAMMNffEkK0OvqCKpqoQhlMp7N47KGydf+zBnmUvumDmn+TuIfMmkt1lbXSVtp4wkja1Bu4BBVw0+Z8PIc81WmBFIVx3QQ71SL/k8n6jOc+q863qa/g5It+pejt0+A2prDHuOFmtsCWwe8IElw4QU8qDTgmailjRMvwztbpvaWea7VO87TSorpsN4tPWZEUV23j7dhzJHrBsDK7RLPa0hqshJG0uCwWK7uF7pVeye0oDpQRDBXILwvEOd6gGgFeIzFUZCFad8DrmR4gAChTx5UuwpXRB3tMzF8eUr34HeA9LtvDGmJ4BGapGfJ7GNZuxFMV+GZpJHyIpCxyjPyOdeDoH5yGJuKv3wi/bPPA67LiHlcgMY2pz/yWI62lXzo424/yDQj4pt+wF4+QHzBNjaXglae+H2uZWGWFByNzp8b4Vi/dWLEuDxxwidnskyqS3sb98ZLUiu8/c4psCryP111FDAepizf/pCE/67lde3/ub1eb0EHVLo74LtzXu0/grJCIv8KLxx7Hs87/bzKzz89i7H/3214btH/Tp5YwvdoPi2WsZocl/eupjrdeoqsaRNy1NWCVpsk6Jg0R83aSc74VImc83ISyrg0DgOi6uIYOs9WoNtly32x/CR6nYhWwFgbQsFgBAlj2NuDfvne9sSf3zA5fULzDm8GMTnJXTQTPY8CnJSIKg5f2qtoWkLHfby82tAgOPXd/6M76IVBEtMHv7xFpd/+wnYjX/f/9evAIAn//4LRIANggENum0AXinwsaonOc3O/3yxKP+LPgT1xF/MpaqcyWYM2B/HYb7bY4R8BBxxQxHIiIAj56jzbPfD9ObtX3u3tegTcwgOnUGX9kM54bxRZKEvrgURb86H+tq/8++9cX1wf/sOB4DtzSuzDSGANMxtQsdhCCZTcRwD/fVA+3yB6sT+j9/D7lQAcvwBba8NbeKPjziaou2KQywZ7Kmq6WIKSHsJ1V9Dp5k6saliA3CAb1ti3BwfPT5hPdOJxNj3HbIJgAuadL+2oboSVUCVfmjbad33BNFGajHdmAMHXcwQlwPUCxLJ6pZfoPLJv8mW/tuOvx1AB0Kcl3ckJih9QvbfGDMrh/6pALrfoSxi9CK0W1+txgsFPi7j/XML9pjp8/1vwRS9f5YqpL4UN1BeJRMDIvNm/H6gv7kFCgMfx987/m8h7r8/xhurTdlPm7K+/cgNbyWTfG8Oq7ogUOApgK/rZ3lZib+jBxAE87M5IqXnGHRYEB1zHZeEMAG2rePwKhfpYlBu7lyIdBRX4JtXmjTPjutd8OWr4vg8sKHBkiSz0ql5tq5Bjd2jyfN138rZib4qTnAjYXFM3HRScKJ1nWhFGE0tDN/pTndzbB9fBtjXSlGNtbrGbrgV8mABAGgwuREdSmEZCvlj0k+tTdYU8mHwmNO3UQAB0Ec2cu3PlXPXHLZbXbE1uIV6CRu+ot9dkl40crABAG0Bm6rUbwZaLw55UwIdAg1Ifrx8v2hlcbnv7Fy3UnP+qmPZYVtFICWTf5K2usEWM3gtnrGPRuHtzjWvOp5QbM1h0SKrzhVnzaA6jThGNNPWcVQIBr6BGDXXgc5gPvZK9hK9YltvPr9+AgPtxfjWac6ZsQ887DuO4wEYWpTSkQYGzLpr2jAUiMr1uq43DZz6x0qErQu6sA1LUbCvzgTt9+RD6UF2OjVDpm+b21vOgwpt2k1bOqEUodTVail/kTrI1VgkflMhp/EdPRXpOEXCegb5Mkg5NPoa2/SpB3NWPsaAZgT4JYP3vGjlg/HME9YygUgHfmShjMZzRkGk2P6XUIbK4QaqenAonGUwJ3IdD3nv8nU9nwOHI14F5JlXLXynjKtFgMXes+B58+AGYRWdh896AwAqlllMnl2TMUBDOjPe1Jmowhw7DVnhbPwfS2CVPJeftcInLpcLpCc0s54e2rYt9VHft45mEcYTq79JE2U+a3Y0wNYZQIvqPDOYMIky49MyxSEd3THsEN8jnFdZ8cv2IM6sAY4iPWvr3qEz6hGlmOexqkfKfNRERO5pUlErujsrXcYcBqctpkPPOTGP4VXlvr7TWjWwgjec9OrQuw3e7748SznvfCxOaycm60mNmJtmdct1VozXe1XmFEEbZuz2mfcxPqwOsFpdZzYhgQgaTviaepXvL2NVdX8lf9u1wpHF9gwEJ7qlP1SnKmUEKn/kyhrPYiW/lJ+oSs3BrdfnyzZQYY4ZuDDniusbTTClo3ej1dm6y8EN0a8PGnBtcbR8QDpMw/kL8jv/nu/j1pkga5DGh18qWpBwXlX9Gb2nYGOl3zCpRQi806bIoFHHdrlLZ3Jx2EeVnr9PhwU9aAKJubl5lO8uCBxwfcmdzDlN1EhKJTVpqzqasKpoPqpvH3q+P5OQURzZ3FtF/joNTbW+0wj5okm4VV7j7GvgXR8ZYeEtOTKNV5YUAoeXf/xhycsZ9IAgEYRCLnJs12umrnMxmZBtTYT6XTUmrr8NapKSfz561NYP8cQxWI4TuT+DVRV5xmuRX1ImQSBNl6qSf13gvOiHwTtuPaiG/kObZY0DKVjWqkD6euWWLuj3KAkt9b5RiU2eC/ub8M7NA7KR5Hbz+Pb8SBGr39tnt64Uwdpl7NfBwMcHUOYd33iMON/mNoLKPrLrfcmxWIJG0BHtmPix87QJlOct1Hv9vMtgNekhDvJx6jt+bshzYYDQW4tMwp6ytaN/r85LgWSn/ZXX930lDDBrrAsROBlIoOybJXAQ9zhzXj09Vzx2Q+/AGPD2HQOTeNTL2G1crZGfkvfw75E+n8q9yrpSTtW5WZMI1BPq7RtzMIme6DUakO/i+zISi113F0ig/kEzeB66ueuenNtklVxH9fFz3OL3XvV5XXaa/whi7JTHde9QLteV0XrN1iPgnFd33hMiLNckxsvnB9CePsX4+iVoYIwvaO2pPTMkanc0EAdntF0AYJjTpFEw+de+u0q+IrQKjQUTddpGAQcKWRwG2Wn/xeV0fQ9YvsOEk7PE4Hy39gIDH205Xv3gOgSihZeIVfOO+QEiLzDfTwDP49koP27uF1B/4PEC6lGB89l6+l0oJY4BRGKWwAO0fPxy4pmnn/8m4tBtKWc/E4rxu2DiPfrPrxYprRD3/5UrnOT5+bitody6/3rWOn/1vSyMiu1UdDbq3Fd3pz0ZOu963RzHrbHlV2+e+B1hWj+mWqSaKGm9ZQUiC5AUpyKc8kTktRLKSPJydSqZxkSNRr2QdHN/l2omvcRc6cScHwD5wW0BL9p4+97gvJsll19+eY2vv/6OUSjXEn+c36klLC+93stMUKe+GY1TXZAlr+SDJr9JmecJ/MfA0Q9sY0sUFvIXuG+FclHZls79AS19SpW+a790VqI3twuGCMBqaS6kT0kmgJ78WkofeZUN9qSfBPiBq8j7wxKqhltc4/d36ACe/PQa2Mw7wFYmREFRT6g/3r7z9W7YxHnIW8X288T47QPG5khr09rH7lOxHwdEBOO3CdV3hrAS8whsU/DDzz9h/3//EwPWimy8+4iHab6x4fR7uVywj2PBvVVoIPVxE6gq9jGtyKH4HRTAVpE/xZL2wo70teHGop5l/yZdPpaE+X/r8X+kAj1YJSefm4qbBdn35S/eLX5TICbMkwftXatRdeKB93TAKjj+nAD5awdJ6Qd1eJ0/8Z0vAjwDsCnQ8AoTmYInClx+2RwGyjJF9n23z3rtpZqKMiDoPzbMd/7OWYhUrg9ghjMDy+96PvfCY+bRLQ1hvLcbtVe2xZo6zOV7CzH0Vw3nr8YbiyB0ZuswR2SOenqO8/knNSW1m+vRl4EjDSI3NtIRB0DUnLLrDSElkLhe3e6rS9ChKvCPH3Qxn1lMfssggL3YNZf1ViJVeXxxJbn5361v2DbBcexW/OCV927yoj936NFnDoH6dUKeG272GILWHrDhGToatmawphB3Mt4r1B2sm9x5b7M7tG5CrhdH+hLUQj7Dspr+5hJQL8oKjYNwTMZrxR59rgf0TjH2A2Mc2MeOfe7AvPjN7n12s6J8oRxXAGYxmEK9cKkdAtkHYUEeh1UUr/xzyNHWG9DhfQsNrpqKxazOw8cIRYEs69F8S4x6Wu9oOrHvacwmWTBIk0bHuJ9gviUoggUOdGTwqij0No4BbQ39AkRlymNbTQrlV35z433uOxEE/KwpZpJ+F1Zz41phD0eEeH9lrx4Vz/Y0uCDN3jpgpbFm/8Myvvg50UO8Jp8Qr/5ryCBSodeEKtcT37YxdFb0IZVIEQ+8aEIjYpqjYhwWPN/3HfvDYT19pvUfHUMN+tgHZnRBiGin4+F93Z1eguf5HFh2ZipTAd0c0+Ew23BVfM6oRmWwRadmvyOqqf4gCWkM9G1zOE4NpjYpfKhnTKvciIrX4wBL2Qn9WmW8nIgrAhuuhFs15Rb0w0QhVup2D3xEhWrwFoVSj3F+iQLTzmpDg5lNPpQkYXuvZfSswJZL8BLCHZ85gDlM7bzOIKRQXhgvsKxYFxBw3YjoG1oTDAyRoAEBm0WjjmMH11p0hc4VWCX4OjpcHSqAhxDzSShlvPJattJHN2mROh33F+crIDeLbM0ZMMecnXI2Da1nKJX/ho4mE0o4Z9cjh+F7A2xn0byXvffonMUgiCowCPQwvkMOyqr21hrkGEXXclkgAriDkTJHVIFmXixWuxhdWVLVBQKEU9R43fD9NafiIBLFOKInGfXicGDT6PX59EEhN4zmvAdYhcbyhqN5Ji2lPKauYedmdVQLPp9BxlLN5gGJQTr2aqPhRqlV/qdMZFCUyAWG2iSQOTE7jeXisOc3JakmUmVC6dAYn7gscdc+1uQGH4cb9U2tZcoYE1NG8AqoYsgwflMV8rCPyhiRVROheJfTTSWoz8LHSfnXerbDIeQ4QKf1eu/Ty5xbydnhvqpOuVhr9XWuBkT9u14alN2ZJGLrnzx1+p5TMUjOpgLtHiSIRJDU0amn03G6qIbU4Scd8hkAiD3QnO926vAjCuMAd+o4OkjvVvmwy1Hud0MpKEfbOjZv5TWL01sLL4uEVspeICBdv3VYcI/79PQZdFkGwaPLctOGJ8s9WzbVoVIDARyQAAtyRq3mpLOtOuMa23aoWi9aT7iNR/LkiLDthY+6ykTTAYnIlm9eLobYNg5LkXj61P/2FjIMJD29uzNWNifmOKx/5VSg2J3/H3fvuiTJjasJfiA9MrOuKqnPsRkbs33/99q1NZudbkmlumZGOIn9AXwA6BFZVWr1nD1nXVbKzAh3OgmCuF/izWq4HLTbSzlijiTHZX4KQJq3rfNMTsfAAHaU+SXL1m/v/XNXnIdFXnAc8ckFFTycxRocx6OukuW3W2+Q0ayliHhbqFpWtrztn7vkJoLmJ+607Ih904J71qIq5ayQuZz+pbaZC1TCAbIcoUAhbiMra3nlCYtAZFaUc4hKkoucf6Tjx0sP/+D88BYFqNk8y+9lsCXjRxMPb13c9zQQ860SP0TKOOoyAHFJJKqROeKFvAzCNkBeKmqJlCwzeITiytO4N0UaOaxE8puw01wRwiMAA7KWEbdH2dhJB7ea3C1cQIUrNPhIynyV/8KdmF4+fHqA/m6B++p2POpuyiBnLifmWP/Gco84uCYAaWZrlF1MXoUCsyNLsLpzwSui2Zos0F16gZkAwIxEgCp3s2R6fD4Z9KZ+FDw/k1X2Fl0nYSZqMefiup0qvIKUAqJRBp4BvumMSXnDdNY6Z64BIct6tXcr6w7P0HZHvE6E3K4FX3RKsrIDIchqFRU5HQ8geHp68gpTZk9VAP3BMs/v+gZ1nqYKjHkBptt7wCSOxwVvFYA+Kia+oj3cQ5uAefDEub71pElABIzMae2LBIJ97KGzGL4fnEfQOF/cqWj3VuV9wOgqHLiqGaTVeDZm8l0+qfZ9BanqF6MP/vf0su3OjtHfvrbPP3yCvBUAr6GquPx+Qa0fO/AJtCXYROy5DMDy+8r5oq1oKtB/7pi/X2311UUKE/Mt9876fYFjoUo3x6+fNf8g7pf1/hzD///rB2y/CASvl0mSH6aDsGHbGgYE/WcAv+fZWNjRd5j1VfCu/3ypFnT/VdKhmQ5KnwPtH9AD3h1ldWsRI0BkoV9dV/NUo2EhQ9tPz0fGLHLq+njKN8ZP7P/npzNCRlDF5fIF2/YSj58MX1minTChPktbxRxZPQki0H2EE/vu7Uvsf3xAeyuY8tqyfaedofPlPaDA/p4WVqPn1WIh+LhKJwKMf/y+4GClHwwDUAD3sCz5rXfsY+ILFH/77/8Nl/2COd9nYI7PdSIrK+T4awKYwdsT98Cz37zKirfn8iz+vnXs+x7PqdPeMUfaMI+JPinkezC93w+gTW9VA5MnWrQy8VChcfJKYS3eZ+czq6dJVKTL0xX6RZlpnmTgF2cMe8wwpUkF8PTbB6B39H//BQrFad9MrugDY74Cxhn7HJDZ0ZriAlqqFGO8t5Yhs1lltt0yyy9QXM5noAn2OTAE1jJvWll4jIH+TvH0aPC9/7efcd4vUU1jwPjZ/PAJ+ss7g8ZUNDxQUInEE+1Gr9lz/tQ3PM0dArNHMCCLe2V7OD0Bwvjq1jv2fWAfA9vWU08nTynQzTSClHWX659XIv5Dr7/kQE/hXYMJOOVM4ywJmUd5jrED6llrh+jLP3OFwRsrrFNxcOLvn79SXJlR/5VXncMnAd78ifcZxN7c+Nw+a70tJYsiY6AYHqWMdRQFKuO+VkAO1w8y1qtnqu7zRqAfDkfCp5wk7RsXqdK/+qppPT+ywOM8yGUqL4ueX4fymGVHkgw/t6zC1CmrPwDyaB8e5YntVUZYja8KeWGEyPwuLvCeGnSgMAUzeEANf+j0oQtjaxvQrVepXmw27UHATNzTqQEqUGnAWdBfWiYveofijLvXryNDJ3qU/yQYn63/irD0ZwM6e45VIyqwCGqUiKJFw2EbUtdMIi2w3tdVOQpjgpoBc9eB8emCuXkG21DosMPKHs3cjPYcimjdR2cAvk/5uJRWXqmEL2h36/jp4QBSo/vuefDB1Qw6i8joZVFZEohKlwKYTxP9PjxHC8pPjBBqlz3QFCIzohoW1DMFEgirSMC0+njCoiy35EWVtdPozqxdp6qiJeq1lfvstJEqsjR923r0yDPhYlpp18nsVi8b1AVj7BBGd1N5rnoZUmDVslS4sU7onJO8/zrIbDVY+sG0vpKzroXP0zGK6Be0u5C67xfslwv288UMK6UcISP5m/ciVJjzfHqvWWXETTgzaFBDKjTcDymK3nQjv+NaNdpFmeorFiAhG9NZNIdaJruXb1dNlSDwxfsMqprznJVrqmKZChFJR565qlTb1IxWGj3a0B032Cua84vsWMn5LuygwEZEzDDEUr8t+3jHs8XZwL7o1mqBcPMAJJ/3NKLl66nwSLmLQRapErjDLPiRy2Gq0En41+whCs5mKOuFVHGRWpB8tmaZz2yNEOpEhY4sz+kyYMHpOFRm5Mm+Vnauma0g7hg+4hMdUlJKcwV9W4zoKAaGEkVOZ4MAIhviD3j5tEJ7LZPFAmOaWF92obEPSMPToaoSjzgDMEiDWhNUalsN/mGcmmUzyAJcOZRRVFpVdwhxHGszsI8ZPbJxcDw2f5rZQcyMUo4RsHA+3FDgmPSL/We5s1IUJava4souP/f1kfaxHFjQ7II3EflPS6sg5F5WHqhBuEG7YAaU7s74QoXtR1vdSzaHlvSEc3LjUXMeH/1/nSeQzggyEMaK7kzsg5lYWd1Am1Kcin0jTqYMKLmWwI6KT8XxFmvmUBJBQc2zt2vwGWSs9BCkmXL1jvXvImfFg2lshdKHKFXgfP4Sx2Exw8dsAJmwZZhN6K7QNjGnANogW/NstHn1DtsPyj9J36i08xizAogqrJqMSmbSzwY0Nfo5yG9Mlmmto7dugWJO32+qrsd5NcG2bdi6VbfBAHbZF2cEAqoGE9U8hznQ8T3FmOWZzM8JiHVK3McasHLc+0as04RnjHVz/JU/hBzj/NNoACKYUGMcO6u8jxm9lXXHncIzUdfSFrgoNPrdl7tynQzIOq6GZI6yJhiMg2gzczWq8/Pmwt7EREWIWh5cfOKslKPxnjz35EXVDZ0O7fgAC2iOn/n/VLU44le8oIyi/iiD/arhm0PxqeblTywI1Us99hZBM9TfqsOfctifvQi2MuMYH+Vz8jhVgbpeIXOCPa8qLzUawEwZKVgvFXDxaV5lFcQbHdDpkpbLbdE3vvRhXCZ7/P0ba2+wnpuk0UtgwmGMFd55T3wu4m0IjlIrv5YYh/oVgw0S2utvyQMk5QOeaxfyxMfWFKUWXYb8szpa0oEvwR+Jo/x5DcoyOPcbuJJzjvvAwFdo2iMz+5wl1mnSXeHGUuRGn+eV7BHTUY0+22PJcC9O4jGw7wPQEYbCle+WoMS6b35+tSkEW9gYmw6oSDiPaXwIO+lsgHhSgH/XIM7zSOvtZ+oFmjBTDyp3nJ87gzWnnyrjXTMPi8Or3EfHOShMEr8yuI9lfrMVEXIugJ15D3JbeJMmb4msaxFYb3MbZ85pgZm8l78E3ZF1HM0gBLLD1k9Bw1XzxfvjY7xXAQ8iSzQ1R1O6tuhwnvoUCzk60aGK8fUR8gCIvnCZxdZlDrgGeKIFxZ9ZaMCKTy4jHWhK0Asvrw5d9ayarEKZGAU38iNNmJEvHMaKdS57VS/KHp8t8UpeFT3wy8JXKp9w9lm+XWZsLQ1bj29VFeP3Dxjldn3mJ52K64g5d2rZF/95AtyuYveOG89SzmHlka2+I4+Fz93uoWNzAth/Uwg+YvvbG38k6XKl95Tz5u836AiAF2oJfH/2Mt5kzvOg46iO9EoPKYvk89RVDG81v3e6sQALR5mgXteSRuU737riSRHMz49oLx8AAOOrVYHYXr1Edexxr2NdTWIdJj+VgKWQO8wucPnwGUb1DFaX93+g//Q2vm94DcVHC+zBWs0g1796TWosNIDQXjlbxrTJL8DU9xj6M57+8R4KxT/+5//EK3+CiZ5HfUD9xUkLr+FnXNDeNXRaAp6XBKdtsu9ear0Gy2lWM2Gy2KKXFJ5D5/l0+wa6VYLjcpv7FVr3VIwxU4bHKrOY3a8Vm4N/T12FSWuOF0bnGNRg4+8wKbIXaZG/DQCPv74H+gb9Px4scUE3s5Xu3kKvz+Cjzfne/McApGE2c0qP/YJ9Ki5z4LLvaK2Zr0Kchw2r5mb2iTfYf/87+lvrc77/8THS3xj4Rn7TPJlJnPiwOgvUA5i8KqlAcNq2aBXA6zIGmgeOBh5Oqyh28uoGYYMJHXfFoaDZfPXtg/1f5vqXlHA/XiEwV0NNGPV2kxk9q/ovvceNH6FgqUa2+Qs1JDeEtyz0WgX0X3E9T9j9MN0g5C8U+FI+f6XmqDt5Gfbz7/a5EWzBvg/M9xP9Z8tMbK1DdWLbTibIt08A3uHu3044/+NyVc79an5x6l2wPtwbjKX204tDoFdEA4e/LWow38xMdDLS7W1fegpdXcuEI5/ODZlX07+288hxZlyDpDSyvEiWnznuQQhVrQ+v3z0Di3KjR9XJt5GGzzoTlgdE1uz4eIk7+D59VMgLOgXo8G0W4brbYqUItAKEoR0wOmg+dXGjNtBkA9rEeBTgLMCDO5b6Zs6cVwI8ZXZTa6+xvfT+lG6sBR1JItY7vgk22UzA6oK+vcBD73j9t5f4/OlzcVSZYwvSMiJePP7NaUo77C+FekVmuZFpRESyAnN+xpgbxr4bc5+WnbfP3fpI6xfsmkVcNKw5i1sIU7IvFoWdyvQbn6ERTjYTLDr7P5rzhWXu57RS1NtWspSUUZ9UQBJpUrCXAoCECAUTqwSQkZJmXG/QPUKLASgGLsDTCf3BGGeabnPVUqgEewWTJpiwZky9TetjrWNEplWWkyx75nNeDKNxljTPNA0rLNkjkhXy0RxbAAAgAElEQVQzoNEDp/WGbXORhmNJOs8h1vtyqKIfIqUnj1ODR6HTKemSuMDXTzg2U45cMTcbjUurLDV0S4I/fsQeALG1Ev+I6xXTW3MjxrAoT3OcG+5Gab2FDvI9q8EcYuukomWKXuJbGEWLHBnVKyClN1fo0piYkW2qLnRC02kPYTnXGc+HUC6AzomdlVWWUpga9HzMPQ1TMUKZC3Lrqx52pPIGc+9l3Ts2LwPVT+ZIV7YEaAzK4J6SvrV0eos7PcBgDphzLnrmWuYiS9AdZx30EoZjIpm5Hqgx51pFRpF7LeJOXPbQkuW+azYkgQsVt4YqMCda65geVRoKTPRLtKv3DnSTRbQVukA6Gc9pfObTjTkg8A1haGHv7+78rrUWQSAh35UIJXE+MzBWpbmJJ2Z3zGZK3Sx4k8pis2Ax1ciC7O4gc6hgegjvVIWMiSEDe2vofUA8yzvWXcCe60Tuuypk6/H9PgYAM3pqZCblLpKfQjiWw0s9mnrbnD1Z5pTRTduvEf0LNc/opMHXZkD+BTiOee/Jpeek81FnaQAErW2YOtLwVsdAyk3VkC9AVLPQaTRgO7FXWtJZQM0IPAeYtc++icxKnWo4P/1stiaIAHanVcxonTggn+ON+Lnl7uT55llccdSQK8uV1SCtiRnlYEM574C0E2YbkXU23Jlfz2lzmYvGp4o/nBwN5myxINPKq229QzcFHSAEd80+Z2WKJit9kNzQWN931SJHpAm1EnPD+JyhGQ33Uu7Na3i2HfudC6wVgjmiN7DKRmaJG/5Eb3sdUG2lh2xuS+sNGDAnvBuStRjmEVPySga7GXaIBzpqZqAbArtXe9HmFW8E++4BUdGepchkqlfnAY0Vbzr61iFjRn/HhWK4rE9508SIIxyv5YmUlsx4F1UUFM/sZY4RRu7yKXG9e99Hy3CYboxZ7wVQ6APiH8cxNujBYV7JZh56Zue594xz5zmQNZur6pz2dcXVytV9/e64YA/zx69PKxhczni4vwv6tkDTA8Nw3vEjF8UmyIoTFU6iwNzZm7TuQxV7daFB107PGwz9xkehFjyjm9YbGXDTPDCoNQYNtnW/O9BVob1b1smc6GLBdDonZmteLCVNzrem9qPXt56j86oa50JHK+fwltPYB/CfGUgQ7xTBmka+zkf1+ZkRd//sRVmVmTj2vvK7HHmqljWU7w4ly9PBHW9Z17WQoAZ64DIfiBUaXCcCYXUIllhoH3UI7tE63TUgGAd4rRhzjf1VZj1QIqc5i+O3fu3zov4wmRU+Bvb94tlww1u7jSgvHm8uMNWJyCI/4licfzVZdQ51+TF5DMu7Kp3QDlu+b4ERqGNeI1ZHx5B0zw0R6NjRlMF8xZEJm0/q4vbdxAj5mydmKvcdEaxWHekAylr8XpePwvHtexFn1O8VeLUCaxpV8NrkWLuXOgdtOM7vKYeLlfFWzBUuVbby9l7UXZjlzhLDmBoVLSdmxj75fCZYqcYdkLBgqapHE88u+8xKcfeCjhMU7ixryMhT2DnLAFsf+zHLQwtQ9OvivHsELHNb0V+9sM/m9HeIVT4inBwFGWTeio55GBVxyhSLblAvFToICWY7uLQ5cA9YMUe939X0jH56hhnsOj9qZL1OAP31q1L9RwG1nueXPz6hvQXG7x8yaxqIpoLMskwHRpFtkYEMdIztXgq5NeshPSRA9c2L7z6+7+QPfmjAva73sxc6UBL8/J7FaS9uS9Scy3yGxHFsq4xplGb/9SP6L0aPe3uXfKPMp0HQf3mD+ZtVtvWiE9j/SeZMGvzYJOApLuuR3rAa2CLTFI8w9Q+zN1Jns6SOrj3PPbK4jxxh4rNR52/NdRhWx8PwoPtZgCvAcL2P+7j1DfrmFc4frHVA8/M1xleI3KO1ZsERrt9G0JeydaDtBitHXs5ewVStYtkAW3cB+mHi/mdge/fWHMICXN4rgI8xxfBpVjxxGNWqxsQZfk9OUPP7FMDj7/bXi1+GtYaE4O6XnwIfmhpOJgdPiZu6ZerQzNc32iouh805IolgjIYhDfu+43w5u212g2zuR9BuvNETe9Sr1zVPvqJNk47zse9pB4IFghm+d/S+YcwdrW3o6Gh9g9wBiOox9r/mbQFb655IdVVXK+B1vD4J8FqBC6i72b3DafzZsAAbBPcOvYsOPD09Yc73EPx37L99wIuHF+Z76A3SsxHceQ70qUBz/nfZMZ8uOI8LZEw8PT5CmmC/XCxoYx/QfeD+3U+4bA0f/q//BzonTncnjPPFAic0q8aQfw0P9Ayap24Xcz66BdkweI05Fyf6nIq++dgMwJOGLrb3m9tEe++QIRj7Hnp8iFOacmnqnUXUqteiHP3nvf63ONABVxVpsFW1QzO9dJEbR/5KBnpsQgWyA52KBoW4dV7fZ5p/YVIx+le5Qe+Rn73Ugz8X61SbvjEG835iygd0/ByEK+6H4vTTT/b7VJz+Zv00/kxgQpG5rj7711//SshTovuRMf/CaqgTPnOYr7J1QpCr7O1bZoXrcYP4K7w8zCgGmsPbBNBHI+3twRjDdF979FMtRuNx2WN+WoyzU9lP1Q3XArQX4gIQoMOyD06nO+AOEBX0bk6UvjGz3ZW+R0F/LZhfvW9m39DFSvOiZ6bnlz8+msHKBTFm59EJKT7PH9k9KvJUpE1ZKiXT5sQcXzFGw2XsGE8X7Cdz/A4qtlEWWYLJVPSiaHEoQgCquuuEEIpUCEMl8y0xwTZ6lsOv8fI8mTcZjSSdrSIQrn7LWcadgohSHLhAnk6Q+1smwLKgMuP1K/HSis5YvYxtGHDCQUJ4SiSkt3JOchkpAorvQTg0XaWhMzOM2sVYwKCqzPJEGAKOPCEc3lqd5JJKZ4wryIayYpqcpnAbMKqGSwcZZVAfLiC4+DD4eAip9b2wCHGPUZ06vEy7BYMQd4RlYF08k2YamrFFzb2o1GjBMefXRdBajEdXE4Yr8JnFn2NK3pTfwEoL2hyFpdodGNJblDzsnok9vT8SjSg58/UK2oPbBqfAfmGwkURWITOf2bMVkMgeJ1xIayNDHIBI9sFm1rRIg3SEU5aBMtE7OJ5lCUuW5pfivEX0FFycQb4fXIeK2WfmnJFhF9UnqFBqOYbcA1aFAA1a/vm0bFB1J5UF92RJfmYWBa5UR7vvYZTA5N9a8K4Y6+q+0HDfIiDG+1q15iX6CZQcSyCYcwfLqwcOiARudW1QaZbBLsxYM0XYInndUNZh2YTcU0nlkco8FJABtNEMHl7qKlZCxxEcLoE31ycBgLcwonKyOtADW2U4nD3oilmXLXt/sa8mRKMtEtsPoMxhCYZQmDNX8zSp17dkBkvI5k672fKFtGkx+JZ5L1dhJnTB1WoSpL0kyeZsY6T0Wuq/OhhYjm14NQTSaBr6wgFZFUb/TiSDqq7kDSVec7y6Fnf4uwObwFCFVbAJkidWoUDJp0yWCnpe3h3/1UoXt+AIAOqO8AbPhLZy9l1NYdVCQxgIkjAxApCGSpQjeF2e7+rVMF7OjBGLaZnWc9UNX1U6DWygwd1bd9XsJIEA3fq40nFuLXbYG51ZghO7u3HDye40Wlo3vOwwPgd1J3WhkzwTUG8vQmNqTjF7uyYf4VkTmRjDYJc0nv8KD/fNszU2tG1D36yMpgU9w7JkkTifuOU7IBKBfGkNB66wgsICEPw+Tgf54A2rRJVBlowPIHdPyz8/E7eMGQwgi9uVQQDOx6SZ4VA0skKOQqwdF8m3SzXUXy0113zF3589Nc9eS4B0He+ZgxBBhVJkoiK+BKEJmp/jrvOlXuO/y/o7KbIcw8yXsWNS69+Uf+jQKbT/uJYlWEgYzONOdJGkoQDaBGbTCMoZHiRo8k+DzEFB5CbeHSCJZ4F8XC4ST5fv4kv7g7yM4RyqE17nPWk0LfXHvQ6i5QRcUD5c38sS5CBNRaUFss7zsMRvg4VmWQbaf//S4laqDvYqJ0J5Ttfv1jXxFwPoQs9+bCqF3q84x/ZFy/skz3w+bzNRrLdzS1Qp1yVNz/kn3S2DxRyaV+egM8WCsAaGTszdWl+ZjjGiBG06h31ATRmJctqtFhucC+hE5r1TI0DR+uDaPx0z11ToeSV+AjqobWxW2RgYJgMjg9JiuuSzhV5q02ijaKxNTZ71ZAfyR0XKtcyip/xrcp7JcFHKleeN8iQd4ZrBDOEQnxSTTNemOB+6nRZ4KYMNVpw28NGhQpmJfNNxHYjAS2uzRb1ZY2/Vga3DYG9ZgVLm7LqXIMpKE8Z0CLDfuALAPWUwh/eiNxcy47sSAQbI8xPZxkUu51VtxcbfC0to4l4wzQDYIs8ceTeJYjpbE5cJXw7eWdEMiPVRP5hQdKE+nCvcx2f09irf5eOqerUurFndx8uCO2Bl3A9wOF7tjUDaSz6YUylyjIhA//gEeffG5vD+Y+BJzvD2e65P+fXfTz7Wg+a6erm3Hulbl4vRoUJcvc8/5OeuXcbfQXfiWnWX8dvHqzH5nj+ThS4HnsDAY5ZxrqXcLTh2elbXysNT97NWolZoznR2nrKgXsmg/J3rnFj3a+kjX98V/0PEddXvxhxWVYefff4KiNie4Al7TRLIlYNVPKLqEXmV04t6/1kt2xgiUbXk/P7TEizB3VQcdy+v4/yX7+Kr5Ff11v23D+i/vMUmphtePAyjgbKTXcy0rotmOferOdKGIdYVXNCw7xO7eGXM1rBvO8Y+Igs9wDUt+aFpgzZF126VnIBoqTL2YfZ5t3GEDCBiZcLngM5tkeW3bQs5NHQbQQSKms2vBkH7Mr8hoH0S4G2cP6fZYjXrdnhlCAGeZOLeS9l//V+/Y7/bcPc/LsC+Y74d2B93YO/o28AGp3GsEOoteeH66eN+wfZ2op3PVgb/ckHvHftlx37ZMe+7wUYn2rtXljThgQwK4KIaLQRs1hMim/F9Bc7jI57+GEGfGmrwFvB0ueD+dMKY1sZSxPTkaDnhfIBnNcUyNR0hUJH0f2I9pP//uP6SA52Cwo+4uMhAB/sNzesIzn/6coGhZkpZ38S5CBNAMoxvvTlFgee/v8VYv6dxvFSLXKsOOBK+y+/v/e83TrQ+YuobbD9v2N8D++8mMN//+wlNGi7ns/fitNnuvw60nz2SR2HCIQoj0vI+00ydsd82nsXT5Tn7xISViU8AgF57sZSLpmW5guaqPMX7+J5gKi68hrJaL1l+o/JZFZHjav7syV0yAY7DFiZZx755DooAQFUunwNo5M2FF7iJYP86IBsg9wDOQHvI0eSFPddeCFqzksRjTEhTK+G++30hvBYDB4mZM4ZOo6b/PL2cmF/VnOiwCEOoMbdt86hD6cAbL9EOZqcKpAP6JGgdkLZh2zbvC+3PtYbRntC9PxQdlhHBKIJejENHo2WBXpSGnf77pPLCTCavdHFx5fgyH3HZLxgT2D951Ll+DebRcILiElJvUS38xanysFyaHSfDE5kUos1zOcROQkdDQ2aCEVc27/tMIYbnc8xSDo/PFP5z/Mkskq2nQqOQKNse4whCkeVla9lthncN8wxopJDnjJdrB7CpO1s16Pnp7oQGwdifylMmGDcpwrQb3dVxv8GIcjr5ePbrLNdJV7oWp8qZfN82qGKpKrBNRmmLZap6hnAtYzSGZWNYD+IWGyLoLiRoOGDMmCBhAEhcKOoNhdkwLFmVhSp3L/N3QUQlBRMqKlDna7uVSBpjQKfB0fp4N2Ba2X2dDWrelqj3pEBk3IXTHW6A9H1IAxey7Kpg0Xgr3PfBSHebN3OX6HCg8SAqI2wtnMMxsDv3TVBWF8z3hOc8SArfKFmbGRW2ujgzTmezhLZnnm8nK7N7OuF02rCfL0gnrDiqSDq/N4F6SdPtNLHNLF1UKyXQcR70HWu/d3XDVEcnQ/b9pXDKJShWZwrMyOo13ViaUHbxfqUww3b0Kjfx2LZ0qeHi8EkerwpgmBOK2Z50fkVbAlA5VjSPDE6DU+mhF/8c/9UcS+G497PDaHUpUcLhAJwKbPCSylllgTKBTsXsbkjzPYZ0b2XCdc5wVo+p0F3DMBdBH9MyWMXnqdPo79gnxtDAcaCh+fnpQieb7TtLEUcW32HvVZUlYqIM1xgj5DBSKcqxGfzWrGyWG6PJG/vWTZmZbkJV0mAj7kJYdg2DF/cDUIxZNp175fOs8rLbOVJOPCia0zM9V6OfXqOucJ+LzrDs5cRsApkNOq3TGPtxLmeIZXPKtdBQ5/1UTJ3CAfHe9Rlbo2N2Lw7SSnshzrmd3/l6+D7bsxHVfAi41jYwwruLeqcRVushHZKIiG8t1d0Q04pxwBLLOtAV6hkQIoLZZuyrOckl37GsMTM2qlxqe3XUxhKqthdeOo+yBA3rs7nhqzzh8qYZaDVK2NagiSrXmwG8oSHLMremmNNaz0A9643EhPCVBnRY2xi0pby7Lj9NlmHP28uluQNAY65Qc5JvEcQDAC3KEkrZ9wWXCxxtOV75xuWxo8VPxKs/NAGm5ROFxO/ZUd/TI6+2icB34eG5nYw/hPukaN2c+6w6YoYq4ks69pZL8zxd04uU4dE7MIbJ+K0t+Gj7QTys86VUyImmnSB1Mk6DLYTynPKKKiq8d4nwA8bOoGS//2QnvHcLBmZGk4pGCwfKz9IQPW/F3zW9UgzLpzMIkXRigWNMkzgKN8hGAX0YDZAD+qxywHqtZ91fXeQIKWCmPsG9yiBmw0NZ5jtbQ9MZvNruZ0afANq8EocsW3l7tt/HbV1+I56RZmqBUNJ0PTwZIyiiwkNgT5HX6SizrFxi3y0Y13v4NyWi53fln7kkX3I1soYrrQQNFHr7nCP5m6jjD5B+BY+I+eSfaZh2WqO559RdDN6m6/B38AQVelvT7OrO8fepnnEpiBZtsX/chXLuSQI5gAClzYhGifbhDvPLvmO/XCxga2bgFh25VHQqnzdnsNOTG/CUAh+NFmEKuEO4ZkGjrimJMshzc6mO87ER4naGgYge8xGGTDStlb+sYmWHZf6BuoMIIBP7sEorhJXqiNLrk3JIwS1WF8tgdN9ZD5BT/s1ATeS93ApbZ3f6RJ6FkLsBWGs98IwjSrwrLLM/HOhwvcLxSeeeDvipNs5Ur1yXvVxNfuHPpB7cPeWEIMEDEv+BOdYKJfPJ9/PBAl2tB+yM0sOJMzb/+i4BIA8Pjs8AxleMx8LnkMksquo6XtF5HD0Ie+p/xq7EefwkyctN4DEeIUDwWFvWaMhqmnTWdSeAfd1TZ+FRbPoCc3629bSXgAJzfsH8uMJZAG9torEG8r2gAQUGxHEBcPdWAH1ZgkKbJwL5X71jXHav9AW0n94AIji//xA9prX8O14sq34km7t/9rmt8wKs4uxLrU6r/J4Z7LT9y+F7764WZd15HYueFOqPCcH4TT0L3c8DK1k5Erdf3mL89gfu//YTWmv4+nfrnc0yz9/nxmUxgMs8xR6L9WeVK0ToMFZIz4WkDgiEzQlmPz75op+kRVlyo+vE93U+lNMO5NN0kqJn8oxPrDLt/ukrvkLjGNGmyyCPytutyJXdez5blhrPyb7vdhb3ubQ9JC7QxnJ5/wEXtV7tNX+kVmWoW257pNjKh8yFOeIT4JygAbvjUS/fXX77gCd3nO8A3v7tZzz++vuCAwOGi68V+OwBDazkyng40yPd3q8KUWu1NaAYQ7ALsDfBRQTbaXM7h+u3jRnOwzKVvQoKbTtGfxjENqLCJjP9xStbzDGjf/o2u9m0m9sHunjAGu1pgi7N/nkQaO8dbdAp7zJJ7FoiGKXGD2Jn7jVLuiPPEPdvqmJ3Wjbajn0KTn//HS8eXuC1voaOM+YYaPvARQR3Iv7MwJ1Pdh87zvsF+76jzbeWxT8+4XJp6HNDe/sCeOj44//8v/Hl61fsc6K3DfswymSVEWdUJIj1ED5v31i5fbzAwEc7f8o7NX2TzvN5psmDJzRanLXegWnyxuWyu3wzA25u9TdbpKQsEFKM/An685/0+ssZ6IsR5DvgmN4fYcyJfY4snfNXLleOdE5MGjeAUJgX5R4wRV6vX/yjzOSfVZReBEF7jamfqv/ym/MYv49Qots7yy6BmJFmMsvTnyDzsD9uT1a+/fWfuv6rIz+AlBt5mPX4dToe63fHnnphcpAbUKWgemP82xMqf23+maj1JPd3iGuLoSi54KIXjRK4uiVehNDiJaVq2AQNZlxFa4LeNugGK0MGc1bc3d1BBJhfFafXdBb0zNT091gZY5u2lU/pJVtY0LYN0phd59lXsS4KZIizfBXdX74LEKvH5EcEuRtMGYHszp59OlMeLTL/UmPiTt4BOAdTNYZZoorj8GRGHcQdOkghjUKs+LMT1uukCmWx5SqIyHU94JEef5EbPyQUnBVmnLPGXFpwSVnHdImMhqHyihXW5cmr7/3DvnXrYwo3CzpAMjsm51nBYAI4Fjxg5CsN8lcSZnk5Mx9YyqkamBiBDhcMxMtrc6/MoOuKYCcvYVsByX2CWO/wUPxs0WHk0XU94C0+jFJ6ABXJXESyKwkcszLhJq6ZkYGOTargLhA28dL5ijYyyjLEQqUAk6pjRPxW44xoPQ74duSgi/jKk7IeTf6+KILFGTEZgACYvUJdtS7GmeV69s86R/slnNjLdCWzz7sFUGynDaeTBfoonaUigGQPczq3qAf2ngbBWFPDkqUYWX7BmGX5jgswAbMYI1RN2qUAG8Qkz4LBy86T9SEUz4o2PGxtWpmxRVrVsjn1Z8KcBlI6eKsDvYnhGcu4ztlCsK7G3Pp3iCMKd6JnWTCeA44bsGvMtk0lhjSUMJAmGGOidVc9NQ3/S+96dHvvGFDdLSN9ZtUGU4vyRDBbdYyBfTAKmkEipQRn7xBp2We6N/Rt89L99lk4zGlsdDlVW7PAHpZB5JhYFWlMRcc0BxSYPdQRfb8gmLInfFFovDRoVzOc6oQ6v0unStLFMGCGUbQcskMFhONZil8Dw1NmCtrux1Bsc1xmZ7a+5DwmoFKy5/2hyNwFzMneCgZTBiMcOdtR+3EKpDsn4kPeJiadTen4Ez/74UQsOo7tYwmimmq9uiGQCFaDR9srrDS1rZF9gyv9a2iZLV75stM+c+AeeZ7JTd15T/P+tdeyZxqLawAie2Y/H3V/Tew53+Waam0S9IgHupRiZ/sujiMOl2uUMl7XvBd5F8WcZqjheNwr0geZljWBNq2UqZ/fCP4qSr1ONYOqXCC7O69dTxQvLygi6B0QWF89oEMkTSVFxcy9cIynjGBBSdVxQKNzzh+Be5X3f0s5+M531yrKeo45eaxsgO8cXl6f/QVtrHRmk2bXuUbmr67UgXK9qEav6CrP5XnN9xc2arT8wMsBZECNPx8BTGW5N+nUbXAtQtnyHDe5nLukAYh2FK28M3i61xytZ209NZr8+H/Dxd6cAIrTmCJECV6tuFrmm8FD9Uxr8OA1AEb97PPvpP1ltc+Ljodr6q177YxHLVfK00C0DeJa6WwLZlNoXqCv+H6plZGWkgkbbT3I8ziZavTjiZgT7Bcpfk9FoTzLP4CPSHDHmYh3puzodyAcvOVdIWsdaDt5xw+dC556keARlags5EQP7wCKDFv4gOb8OK8QMTQ+jZdQDqUOUsMj8t2UWD1oVDLYTvLNXm4dgOv/KdMOswO4Az2M9IsDneuqcE6HeK75AMKQ9Xh/katQKqhMBuaURdVfg+5wvRLwEliiQF6GhztcFphJs7Ujyla31qwaSEecVdIj9ldNh2jK8NnrvexnkffpQI2/g/9TnkTIl1CeoBmZp8kj3VZDfrLwUEftqVYxYM4AvmB4S7U8O1bJxu1AbidlFnziYOpbLGcbQWi+voVDE9+pP0zg8tl6c7d7wXgMLoZ9H1Vts+o90PygngkAp80Chy+XC/RxRQX+v8sLd9RgDcKnfA2EnhC2PlyRpvj+iHb5d1qADmw/qhJcUerCJ1UU84OivRHM+cXW/zGzz3V5pNBJ/QSRl4H01Up545gtMsIN0Rf9tOHi1Yb0BhC+RxG597P8/SPXrXGPgQC37iHrApCJazdupDQqULSfr2W661EFhcSCr+Eu/tle6GFblCIX+d+hPx1ncdBP7n0WT6BzzXV3RbabUIGFIBOv0iFNB2ENFoQCQ0pWLOnlAdUrRz0fdqLi2yoB2XdMFLE12Wd0MAd9MGvxoq8AZkvfXY6hnZIvrXt/zatvfZI/k+Oh2NmqPADsy/d2tt7/+hs2H6OX0/hFDGjpBOU6S4inTEC9LeOk7CTYsaOr4tIMF077CbuXYQfShrTYfYcE3edltnn14KdDMFZt7xFVyQwSbPVm9tnpazVdvDdx57nbS/sO2dsK3+Ddzj/9m9SEEHs9iQ9IPJg6nZc2yJjYd8obO+5/GhifdujoODVApeMiE18ANJ2W3OFtrvd9AE9nnE4dgjOeLh13Q4En74c+Jk7v3mB/fIqqOpd/fMhqAQp8heIBztscbxlkvvUNr9+9xYff/4g1Up+BeCCS/7MimYqmiqGehiMM2iHYirVPFdI6oGzzkXhb4ffjFPU/7/Uvc6AHZL5pBHBG5gfje/fefD4HMsWXglc4Bu0ayuyYfPa1eqSXpJp3ZJJ8x4/OLHQs3EYHEvYXakR/4BMagAtWIh3CkAqmfPCxBbt8CNI230+Mf/dsimFlW7O3p31/8We5FcdMx/gyfi/iQZUxaOzw+TOvhePMeIkPwxqfHwF5YxE/ANDeelnx99+GatiSbjFfkEArsjxpKpTfP4jJZCOLgQpQLv3Z6QW2HHU5Cq0q14/K+jNYkaSKl4s73E6hQOHP1AHt661vUR63eUaEqqLdmeHX+raaMNK6BGPYmvWKZpl/LUiisLEggvPXibaZMLT1hvt7E3nmmOi9QZ4E22vrHWzlR9z5+wTIZgZ/cygJpAu2fo6+6ZDdy5Cak6F3Ojwsu47lbliSmlFiq7OVAv7B6D+ZhWT/dA6oK1z2+0Q0Tb0H5k4B7c4N8GcAgvWDitUAACAASURBVA3WC+eML2X/UoENY51zqwaPMq10UDScgqNZuTTmN+wewWxRvAgpz4z0M3Gu7DnLOVdjHhacsnH5lwVm2/7WSOE6BkeZAOZ5oj9s1grgCdDSY43ojyKAHU+dkEHDKxYA0etnccL6QHU/7Tx65LSviY530viKB/wvSmUDVgqnd+uJ0zfrd+P9uFCzyJBl31sTDG2QbnjXi3JtAhmSiKNZmfEQp5znTMLCVL5wlBT4Pk/7SL98/8OLwswqFyCDzEn5Z1dkJqoY+oui9RFZ1sBcWC3XN0fZ1KtSI/YOBpiEkbXsVzjJFuIpUW4fvlcQM8yTV4l4ZoRny1IIliDG+gOiQT0DK0SSzhfaWYx85jzfLAPdy7dbAEKzqhi+NpY1pSGi926Z1zRMAIgKDa5AWA9zhBFSI2hQ0YuhPhxLc0RlBgCZ2aJWotnKJudZCUVUyj6o9ziCQLSh9YLDrCkW0r69Z4yRWXqqUIygE9buwgKNxhxu8BOvimo0r9KTcFAV+W8NegnMi3POmPzoOy4Vx1bHpjmjk2fy+9Y7ehvx7nDStMMYqA5ECdzunnFM+gmPsJ1zLR+mY3oFAjEYtgYRlsk2mmBzsX5fDBYzop0Z8Kz0kH2F05EqzQMix8hSyIXOR9S0SBjulfJB/LOs1x5OHAf7VGDLA1VLkVKZCTnaD1Aa2Mjj8uRpjJMBAEHL3XBn5UkN9wTw3tHwLCgxHcBLg8da/UzwBTScpBOEZ6v8I0a0lGGijAOdHCIL7BhYswRo1QzZcr6Oa449J+Sd/OlU5/1J+xtpeYAmee/ijBJEoA4ks+aMn9JQrVCwLHEhjq7LLEYr7t9NodQNVqTxaeUBDU4HBcGe4SKKRU81nVvX0gCW+2IN/l6Zx8lJ3CPN9AdVoHVYJQidEWiwjCvNytlPk2kji73IZssz04JjBHPtrdcbsAF9dIw+woBnhhrKmDmOyaYdrIzRWvMsieSvOs0gMppVhkhdzeS+2ZrbeGjoIb67rrAwwWfkCK0/bugo9dkbVtZw1nXyF6ZWZ3nHq5090IP1TazAYrJRmxO6dXSvqhEVopROLtPdkw4hni0CZ6yCr9Y4o1z5GrB2lL7QMrub/BJAGNyafz8H91Cr2JB04hnBJObEv6UjS3DErH1JdZOSB8QRo+z3o3CX4x+HOd6YN/kPpNA0KWXjNd077B+89G+mnBxNbm+CZfnqeQpR7izz1GK8WBzBej2aiBY+X2Fx4xUuD2mbRqOnlpYmgpSX0+JR5baVBpUjxTQoIPDwm2stP3xx8axIoWHBip0Ole+1fIfld431XAVgrYArML+ebz0zR6epKkL2S2BYwBgDckMGnt43uZu82HR6sGe+WmOxPMtHtJXlb4UZdUk7lmvCnd2WqabTyspaYOTAmDvGvuOy75aZ7g70zF4+JNnEmrPMeIiSZfnxO9sDQRdYLXanG5tyxJkZ+Ja6loI8ZsRcVGfYV9iGKOxAQLSQ6t0CSrNeq6K5R9ZgYLgyR5bBnWP4rnjQWVlLBJsgy98HrAI/k3eSRybi0oarGGpnmGuq1axclEb0LqddASZnzZCRNPg61zMrrGB/m7uf5fVX+aQGhKk6HkE9KSRplC77cwfBV3uHzqxgEnSSc3U8F0RgQn/5wuHtThjUY1/wwQ+jwuSVmuEOON0oc0uyNCAeyHYl2iVlK+NgaSdW1YjEzwnVLO9e7UmtNczXwPxogaV+t/9LRxRtNvPjhOAz+pvXobezb/ReVnJTtKHc6MzaEiM65j4Asd68Y06MPz7GYgSrI//W9bkczSlWnh2wLPNvXYrUbus4fP64hqbIUt7IDOTFXHZjogY/wfwd6H/jm2UZn3aWAY0S3vGs5vsUwKvDmq9FCJvQS7Ws5psO91vyiVowlJ3NrBzGNb3wGTGzP9pdeWXCBg9U9IBkjnAqPJ7iACkrHe21LWa0jnRWOHwCPSDicJ9GgwiXsNlI0l0RyzxXBfbz2Xix2yep7zPzm3zT5H1Eqf7hikKXg2P2BkjrT+IGyv4BiUNubgZg7xq4Zak1qFHai7nC4PZarWx58G9CWejFoK6Q9HJ6ie6hil2BfjE9YL9YL/S7/Q77vmNrEpXMeuuuN0/Hj1L9yh3gxsumn1u37QgQWepO45VZ8G1m2ykkTRQA8MSDrW84nU7Y58Q2FEPH4o+0PVZcV4BiclxQVkJmqS4zxOh89yz687hg3wdauwC72R/nySqfQoAHtVLwmGb/MWP8gOrAvivGbxfs2wDaxOn1AwDB9vNbjKcnbL15QtV7XKDBQ4JvYj2SAsHAxFZsS0OrHMOzCuxj4O50QmvmAxIR41OA2Xj2QRYS1OfoGehNIK3j6XLJSQScU+I7ougtUvKf8fprJdxT40vlBi50oCBweSYFqxQRfvRtSSLtquWZKDjwnRTA+Okr0AiXyvAtc9Hzb73+/EcuEuwJI5r1uQisxoowTd9iygdM+XCFSJXYrp8rVD7/4Kyux+MhuH7LX7/yED8PtX/dganE7dvvPD6lz/xlnxyyqsrnJO43B6SFFYqliclhwTf3VeioWwelgaWhQSVLlcYIItDLiJKkOtR6jyONtDKN1EUUuWQJWgvikOIoknBkSBNs9w13LH3crUx0G24EG5y3leuV1nDaNmxdUzhuDerZ6CyNXDNUQjN1+K0OY1Rqn9ChwYCKvlIRu8PUc2TtYg60uweMtkN3GrQI+Eu8JQ02K/SrcsO9kennz+dGI4cZYKlC1DnnqGGcLbQ0lBdXGCWkJl+xpkAbaxcvDeq0V5ZSh/lfgtBnX+jmwACeGraHjnbXoGdAZVzBIOaxC3CX+6BwAZQZ4F1MKCingzhw3EGWejEAMMOsOZQVWqTGho7eBafThru7kzs+vciuCLbthNPJPpetWcm3MbFt3UqLy1EwKryFhp9lrfA5JSVbMrfpJ3GcFQpxy+NpWEPhS0e6QceKchZRItHhJm4MEQYQWPehEGH8/MbvgjDmigu8AgV9VzGPI13z8a8zQKpIVr4TI2+sMgHUc1uMibSKGfA8+KjmuiEdUcd3fOMSP8h0RjlRdprA4AnL2m2erW8l3Dcvuev90LcaZNKiJHqPsrwsz+5nKF7lmaTO0K2Ps2X2zWhiVvmHG4GwRzZJyCVhk1anfyv8g75wJPKXCQ/hZtlLixI2mLpCUPBtjuxHXeUyVYThMYQDocE9o7GjrHLZrnD0+zta3fuYb/ZUj1L6rZdndXkmeUM6SQB45neP91Uac01hHEmctVjP9Rbls4NWhrOArQ5mKiJOl1rvkG7BXwywiB73zb+nQ1ebBWz5uiY0s157g+57Ud4y8l7c8CyN6UIMDjDHfMq+CJw0GtgxRwMkS+qyLCAz4+cYS0n3CQXckSWDhkbuFY2LyRepNAMIuZu8mzwQlB8iw1dCnmGvygg+kKxCQwOpkJ74mnszY13r3YwO0wPvAMiUyAifCsw5PLudGcXd2sicTsFro4856XhpIbMEA8jKG3ozmtia9S2Lii2S8FmtX85rFOZE0BklOJer/ukIO5X4x6E8eJbZYSHvJHrX4aIgW4igSaspzZDWhnFVq5RQJtRIxx2Tyzsb1KO4eHvVJI5nX+MdWh3SlHucL7SFXw7PunKDre+RVXNwGusAHAYgUG6wlTL41v95sOcgjYNC1Xr0jTbQR8dsxiBppMneovl+60jheK0KdXBzz5iFPmmg8YU2VgqBAo5POg5cVoBr1/XNnbm6Ksc80tGwAOoqw845YJVuaKR0R1jAsPL9MvYhEF5i/3z+raENTbo4J2SwpL4HfkX5Xy0CCctz0il+vcZcf8q6sf7jAwUTV+fmgU8U4BndL4Gsjre0HZDHiJZ5UHchfakewjrX0HXKv7q++v36xZUeJMcbC+2hfeQWJEi3rD9klnBX1yfCOMq+0WM3PYpOdG+5w/NU+xU/d33zWz+bITeSJIlCcF1lQ8s6De88zD/ouA8SxWBdSpjqTnTxagINkZVPGqcAWPfSYSrOB0WLI4D7TX2qrlCwVJ54bs01WJDy8HKRj7tcsyaG5LmpQW/fdt7jcICqy2c9OyuPkRg7ZIAD/wlZXjMbfE5zWDRmbzsOYTZz3qrLfAAi87wczxyLe5AyjcWFShhjq/4/5sBkIOTuJdvdYU4H+th3qA6XZWfJQD8EmsdZ4PgTVVZImFGOrFnslKNKxhYqfSmfVtoj17Lwgl4ibh9wWt0yMByLrgi0vhmsRSGjnlM7E9Zua6Jm1xPPpnqvVN0BFcswDsetzZlyLfkkqE+g7CWXF7jkPKLAlIFj0+lOyi3EPVZf2wmo4MdwPJjRHslpnbqdhSWJMcAgiZDJVT33gi1ViNe+a8RBVXPkj4nHT55c8fAQizR10+T2JubYUgZ0kqZGWX84Lhuczh8/BSdbaIAqIA8W8xB0DYA0zItXjmnJ06KMLvWc1q/4JzeEe5U4hQyK0MwepA5U7QEW7OC4dhiZtoXnrOwdCuCVO88V/d07VzUH2KNeDxLQMkLwvKzABJgMqYMF05Ou8i/Gkmv5dxz7uQ5xxzXeuqKI1A9etTLfrbnwHs6d8fCcu/gDio9QebvSEphetP3yE8ZvH56dGdHpla5O9JAPJPWZo0X6aj2BM1LOtAc2pAS2vMO+N9zqrtu21hYZizy23xgh4ZR7vuM6CSmlNCnYcRzlOTyLBQbtfg4OvJtYLHB93b8JXsfPj7rgcq1vWWT7W3eRl/r8GDZ6y41eP620+nNtNRh0MC10IT8K1XvXtwQYKtinRgHP8/mM3hsud/d42p7MTs3qbqRlQGSbL/wyBTEIJOxvXOdUb8cydux7s8oqUzxDum6GYThtf9u24e7uztr0TQWGYGK3JBHVst25T/zNfHb8NGHf4K1iHaZtAjKtEsqYnOcL6P6E2Tte4YS5TXxyW8DDnJj7QPN2MuRZc99xeXrCPjsmduijzduC/ezefb/g8mtWMKz4EDqr2wZbE2C31i2Pv/+BTRWVWlKmcvaMfQw89DvcbRuGapE9fayR7wkGZ5QjdBhKbsvMKkO6qej817j+BRnoCGB/+0beX8H5Z4G2ku8wUACxITQSfALwAMFXDLxUKxmiAP5gzYXCnCtRqtv8DB9dvj8s73rGPshZPCrqcP+mbzDxMfrwUukgL2Au3+mXE+7u7nA+P0EVOLnh3/o5KRSr8zyj2pxIRh0T+ebCYl/ICPmY/1/xBVCg66v1OX+hvFtZG8dr726/jBGy1Wh560ClOH793TcvWfmTVjzB7c8NPa6BFP1WbEILS6q2qTgPAizGVF+b8gHgGd55wC5Ko0hmO+aAqOD+4d7Lk3mRFjHDe+vNy4sCIoq7bbNoxH03IslsGHUnUINnP3aoCE4P1ldkPk6gAedx8YzNE9A7tgeL4upNLOJTDLPnMBg2L5c6G9C3ht6sV4zKPaRdzOAdJXtbEFuWVTXjmwTatgCFROcv7sVUjf40CgbWsI+ZRNa5RSED+5eBdt8iQMBAeoHgwWwmZJjq+CCI7Dye4abckjQo2FO+bldMWqxhjSDnvjPDc+ubzX3WLBXbu4oRp5N5rPd9h8B6beU4NPAC+36BtCKc+XvpaACwBB3xHYoL1A1E7b5jnr+JmfGBTgW6YL8MQKxKgTlGypF2eNmhzOfXs5hvkPK3ulAt3l/s7v4O9/f3eLh/QN96VDGYOh1PN3O2bM36GM+BrVmZ7r51V7StxM6cFoU4PRM6I/gGRmsWNdrEBfRVrQvBw/lKiGoB41yZlPUmJfPzxxLNPia8/FwKqyaU9L5hU8W2bdi34b1lEcYLqFoZd+5tE8+Qt2COvnVgh/WY1R3sdwcv/TndgBQly3vDgJpSyslJ8tlcBR1LacxAhQv57oHOK1bav/DygPBt/rwio0H+aEyuzleAPTvXYJ7eu2etatAlO6+2LzzP4tNf8dUDGehQ5fxc023N6GhrA7oYJgyYdFKrImggHcvqxjF0Ket1ZZT0pwgxVb2JPlxTrb83z+kNxk9aV7NGFChleOEBBm6gq+cXOY+gmyE4ixFLZq4DqGWfCDdzPks4NtRLQ6es7eeuKK9cSfaNlvzhdDBKfHlm0XRDlvSO1jSqDvB+QDHFDDripcZoUOvNnOYMpGitRr57OS83+gGIOns05A4/P2NoGIiaKrRbWHpkp07LzDJDmZUZVwEmJgbEylSr9VwTZe9Ba6XSPUhtwByKA4D2HjSntW4ZGcOdH6RzXu58jIHpBgzseylNBzhjjL31jfHqDGX+gcMAvHJGlflFBMoE05IxxdYI29atJJz38t683Bp7U09mh/k+bqyA4DirY1hmr097c4X5dHeHvm1RprTiyyKxHggM8aK5CC2tx1yNVPRoZROZFo4HEfRRHCyGv85FhKcAJYOdOOD0351SOid2ySzZqdkDLgXP5BNXDnogKpmkfJPz9e2EkYxKI+zDmmlWZWWjjVZOvtJGdXpi4yfAwmBTjLMi6/cclz3EuwuoqwMdQSvaAHZVwKucTGTmPg0ixpMPvAniJa9zTty7fbeyemYwSKeKOQtJp9wUewNeJOpzTu/nqu4IRPRux0DgLo3zCQfi3zW9Tvz8E5eg4HaRC8t40VNcAIkgAOS9hdfEY5qGrwX3REJWFrZuCl7sUJoTKs2MnS5jd7YjCB9lSEQOmuO8DybSYnRbZVXnt16bMMXiFZBPj2fIFdzdgUs+eRhTgBLAyrNxQAsYb441HOSU5O1ZgleR+g8Oyz6OXKZzmN2zk8kKXyG3Gp6ymhjgRsrds3f9577vnsWbWbvJQ5+f7/dQ1kgtnTolYIZw5Z4JpYtqpHM5rLFWHlZeBUUSWJfhrcSHB0EKMBI30540Y3QrFT6BafIA8ystgKutuPndxWr59TowP65qWCjGycigrDJS0PEjPfrefFhBqNBqylrlLIRhfpEVr9exOpONdiuoW5lBWZg9pnPNuFXjtXNSDPcxkTw+A4ENJlGNQt1h4/reGAPTneTny8VxeF9Ktmv0WKWMOJJ3oZBJrjlkUWBpdYUV9oQdeemV26lu3jMbRDnhOQd60NziQF/OgFBGaWhzovUTpu4r6ZmWuW7Vker+stT8DPtHrr+W3DV7U8JnLd3OYLKgQzPxgmIlZZGwXyCz+TIARU1XhfpepWwPMT2C45lstEegJjwwzLbOsh1rL3QilvHopJXJjhWqzeU/L6HrVKc93JvM7TJ9yi62yt47phhNbV0wLlZNxwIEHmMu48vjsr2VbikU8/NXyMsHD6C1alVD08EzPGBDCl4A4gF6Rj9oh1rP7MonpTX0kCVzQvVMAJQhyTOqPMdnX0Jef4Z+WvHaMl+B9voNTGL7BGmvMPc/IO0VLp4pLniF7U3D+eMnHC8JQH2Gzlcwb5X1QM9z5esPnoGFBfzZ65h5/twQcaz891cO32r3ryoGneIptVy/g89UZ7tTbNv731yK+eUDgLflDcRlxxNp8JpJy3wFQJ/A3d/eYf72/jq73P9uEHx13E5R8hbdSlo4Jk9KVuwQAR6dN98bYcBFgClu41fBPcSdrTamU60omc2JpenIYEGH1i62atoqjnZ/jjGcjvtoIQ+G3DETflBE5aKw8bou2mKz0oZRz9UEIoCHQRblFF7B8AD6+D3OOOd/C3cKy68hW+LvXreX9kwp4xS5tqx9QtDk6IoXd6Kr1SdpginWC10E1sO7C06Pj6ZrOR70vllWvssBwyvEhG6rA4q1EkwNFBxzQPaUuxrEeZVXse1VHtOQI5pYy8b7eYehVvVELx7MK7d3hHj0Si0z/5WaREM5rDlvaX7WhgJ3zgBCZ1SD6BgDMgY+N0B0w4MKHh1nhk5vIWm/b45v+77jModVYXgy/x9bK4594HK+4Mkrr7GyylcYL+ZuKz5B9a3ZFT98wpNadY8O4E4V5yJ/ChAVpPdhgYd3p5MFCFwscC2SNqbiosOSfqKKaWKoCJMfZLEr8Jz5abqp3vwTZPo//PrLDnSjiLoQCjLpleEmmI4G2H/mirEPpZYoxNg95JpWMv0uSioWUrkI/GVZN1/6ne+/syZBEjTaB4Z8XJwsNdqWFFj0rTHKfWD/1Qy0p38/sfJf+sb/hRiXQkrMbPnxVy69+iX/vAbh6rB6FsiFsVZS8M+g2fMy1vV4VfGlzLp8fgW2dZW3BOZjBlN9Ow3WdR6tdzOo+6ZFEAZQlAEzkAMK2v1MEHK26WW8VJFM0oUIYbZm79ha94xBc0R2ZrVtDfpVYQlzydS0WZneJjR67/l9ayu8/B+jyo/wpXG++wbV86S5EtDQBSCdohH9fgdjHSxRZiXbzTn6BMh9woziAzcpDBgptNTfjYfogqLV0RiByLJGRtqzboRUlpSnsE9tzB6Oqfg8ZlEW8lylIopiEOG7uPe3LgUwnybafQlquLpDDr+ZoDCnoDUXKYwQ28xaEXRjpn5gSx8gA1j9I+R/N+wKtt5x2k64v3/Ai5cPePXilQVybJZlPR2P6Wzup459n9i9VHbrzaPt4ULb8EhEOxssbxyl2TQdG6CQIAgAXtMDWMltfkeHbb0BhI3tom2z/aQSuKvNI4IcujkZGzo2ANs20NsFFzc4z6mYY3fHKYNHDM7WwgFQdA90UIwpwBQr8z9lUaQViAp/gW9ESOJlgwdNNS/BlOe1BggcCWmstRrli/JRz1hFiptxz5VMBmhpwM/PQShL3BlVC6y0M1tI2LliSXWW0xdJB29kRsLpg+aaSbO0vtkzv6d4hQVNwKozb/JxBUs5WzaIeAAK8R8sf13GB8lmgVTQCuX7/ZUznTj1DFNJBDinfCeNcn1zB7rzgVpW3tZZZLu6qXSWunIs2hHZPZBwQOYOu9w4cwjKklSuq4FOwoGelwJRlnOMEUoal22BcNl3ncY7AJEFW6Pn4Xvb2fdcXBV1pAt5U1b5F34ux9it+olY6XwqrCwrjKmQZrR/iMGKtj+gGKynYkBh6ap0Eti8W+vYtkh2N1xSxRRF2wRtDKB3QE8WubyPaJ1A+DQRDBHsY2C2juZzJa+iQTf+qFfBheY8XMIBosHzDdFdmZcWrVy2JfDGssuJa9u24eTVIs6XM56ezkbLNXuMwo2Jkd3mtPW0bTjd3+P+7g7b6YTL5YJ9zJyuo37iva/Qy3ZW+cnafCACS6Q3dFYgEEd2p2FTBSLmCBRW+2BAB8+xugPX6TMdA9PXlYZip+c+P0ae09hA3I3IfrYwKCddD2uJLQzxL/dV688UpOI8HB3o0hqUgSWLAzBxN3pzJvtL2txSLiJBiyA0MsVOfJGk1XOa0U0V0qYb4ydqj/c8175vgqw60RSYzWmi4flUlxVUIcM/m9aCgwEl5MmtWTWHkAVKVBPlRmvTsaMyK2kCGbZPTcWCpxeDPs/M9TGrW1JlyON3t65bwcPpJFjHoPGFWejGs6vE5/xkyVahDJG81uQ/b4PSMgACyEDXNuGy0LreCLrjd+U9vLcuN2TMydNfv83fnxF9D3fyruQbMaLqcicAdtMmIgPe5kHZ4qXI6VV+jLGlyCi67tFiL5Gig97Qkfi8Lvu5IkUGiafsktnXGeCliqWVy2AWumd4WmZ6tnDJCdyC549dy44pK+TIip91/eVf0AungSkcVXzXxZAHEQ9EAyCei1MqLxjeG42AuhP95MGNniUXyHljjpTlvntVBH/2w5A6Yy2E06Lzca3xf6mP37wqSGKY8k8dIUIWKfzkOFDorT5bEfVqIc1/ujxWgoSvhhK4UZbyrCeVlNeSFwkQgbEaDlTL6Nr3HZfLBZeL/RylZDsL9WrYB1jCXRFZdWGPyyoYlbdRpiHsl3sKnViWp+XHkZZofq58shqeNX+Zqh6UNKFoVt1DzFkOkDcL2lS0buXuexOgdcCrQNGBjtbcqTw9S9fPCYNjyMvhOjId5SKeQT7ze2WGNTGwwsU3Vs2Vw7O44JSmPSSc6AGe3Jd9jnBOyBhuI1CMy4TpVe5E8PY9CwzVggCmwOUGJx1Kvs3DolRJo0ND3c359Qny4h7z0RwbDN9heyxBOveVrssgvneQF0/hPD8iiNwr5mN515dHyMsX6K4f0ElHmsB5Rlu7Lat6mV3pmm8xkSarnJWKXMq1OhxjG7TAQHJtQacVqp+Wt7kmFc7D+WkA+AK8cX1MXsZIgLU63T8ClCGOnHx+VLQ3gLv1wGx4BjwFLdbDw1fX+qVmOZkbb7313LeliZsy2vK+9W86r18c6HFlLyoI/bCWlB6/AfjlA0TeAPgEc6bDbbHA5df3MeNgWf6eCeDx1/cQWXuirwmPz6xB86wiaH/qwGvQQpGV15ks67N7EhuZMEW9gXjIpCSRdYcW+3vFgRLJwBksVPr6w7WsgJb7EgL5HWXsZXUl05u2mfJkiHbfRpUYt67nGiv1sA7/RXLeV/hU4PFZSr2eMteDehC/cSXUlee00uTUsffLBWcRPG5fwSiD1hpOJ/U2tCYLMDDTMrVn/nO6E8XUVCJZzKZtstpZAe3DZIzesKGn3hF6D9B6wzY3nLY73J80Ehr2YVXrViRKQClY1t5+vlGevQyWmeGQaxg60VQ9M12halWc5hhoY2DvDU860dEi+W+M3apGAjip26jHjss+sDeDNnarLDznwGX/DefzGU//OEOaYDTB7psZeh3n9kHR3nmQyc/v8Pm399gddtvrl8CXr77nh432c916D/5hOJj2UupxQsxRAJvpi9tG26oUnY32vIKmlT8Txxz/nr2+p8j9B1x/rYS7FGWMrOJIW/Juf0ZCGf1rABAwO0iWTw0ZOa97eq1gUU68R47P+QeRuV0QEEg69Gcv8pRbOpYCOOkbXNyJbvd8uHGGP+Dy60/BjHf5AP27jfbw7/dLZnTXVyZgLOXcryd/TRAPgkT9WfC46cvle47j3TOxsavI21bWfORKCBlHsDo87CcJfrJVgaylfZ9TBslgQ4Fbr8hY07qCIuZcjZmKIPQbkeK35/bMmwAAIABJREFUrls4ExRmfUXr3UuPeLRsLZHFaXhvUTQJxnA5P8XmqFo5o94bxj4hm5/PMbHvxtB6gZsC2E4bLErIjbmTxm4jjiIaZZmbDNy9foFT39BOHafewQzN3gX6SqBPzuvcEWTlPTvQRqEVCIJ6/J1/A1YilehAhTAJrut24JlVUHygE5pK6ASiB5NCIQ+GHxQcoj8OAMgZiu1ayvA5Nr2DOd1TGAGADXdQPEXPpuasncapyVJGoFGxBw4aQ6HrJfG+CaKcremyistlDyOkAlHyjz3Z1KObU8hbce0ae9eTHOWNyPRODXKZy+32PZ+tjE/d8Wo9SVXMYIImJQOJfFlTzwmhW1JAhDPbSRgCm1i/6tP9PV48vMCrl6/w5s0bnE4n3N1tnrmp4RDvfcNp27CPgX0OTM8E661ZOd2huOjZhCjxiHtFGMrNbmMZjc0zOb3+QFClBYw8qrVXq5pARUixZUHNghSwMkA6kUTVsjTcUNHVzmB3gzUDWpjxYdGbw7M2PMIdivB2d3H/qyuybUI7rIQhJqa6ks/es+IZCVelZXsoP+ZfloBLGMd5noXZEIrL+eLjIsaH77gZ2RjIVgCJQLQrhnOlbMRWaLzfSnOuKmxkGbowu19279naYx4csLU03jY/04GuKFkSAKxBeJ3QLHQrneJ1vjOMNYXYzAZ4BREXmZGHopwRf5loC+GlBiFFsINyNurt+3hGnV4uc+b6mzl0aYgRq+TA3t6WbYuC44R35eOFoSuNWboo/DQuLbKg+lxnbng6ozwICtMXxtLftSS3Rc1CgX0fcS5YqrV143W9deejCVMq461PX6Px2X3f7XN/l5EuQe8eYODjZPbg9CC1LEOpYHUHc+631j3bciYPo6/G98fsuOQLDbMrZA6gCcaAl2338rvSMut8Wu8zDthMwIjM+TkVszHzyqK/x+5l5kWwQSAq2Jtg7hfAy+eGgghB88on+/ni201+pCF/Gw7MoHmGEkY/DLaWzd0YyNKaZfo3wXZ3h9O2ofeO0+mE08mqh3z68tXLrHZzoAcP9v8PC4jiuu/uTri/u8P9ixc4nU54fHyM1gM0zVVDbRiCm0WDT8lzQvrdIMBmfbrZOxis8hCy1QC0FT7n9M1JshmIBV3Vkxg05BnLorZMuhlwh7dksKh5limNtbjxWJqgo/vRqHwos515PqOVgBu6cp1a4pLt831aEEiqvXZ1GinQfW0zaLky2IVyT8gAGbDE6hOVAFQxHwoLwvTnGuEvYlWP2rDsOmFuDfdyhsxEXgR3HrTu7xNY9pLriNlXFNa6xgWdJTuPslctXe57SKdaSLkCz8DJM1D5QVPvxUi5OHhVOvSvrsCv/C5F+ltK0bXEJ7f+uPGouhxNWcBZa87R6b02ZJwmv5ecvwBRbYr7YPepVxsxJ5uHJYF8LqdV+QPxQ6EH63PIFS4Hr5DhmOzna8+eurX10WHBLuzRK2G6TbnMziedIC2N9ZXRiskd04OV7SwYYFRqB1ifWzB4ubVV370W0WD5vIx/A40CLh4AFHQMGlU66GyODKFpGb2TPNXLUy6JEiT78dH31pU3mxhJOLpe499EYCgDcQA/lxJObrQGddoyWTmoyG10+9h+MMWZLybNS/pmW6OOsgJ0bys1LdCte/YZiT/xcsXdWytFyKh6BSfJMTFvjOLjU3eMSnLPwXWVw25vhsQYFEUDCpqfBz2Pe47y4zNz8Gfqv6kafEcmrAqPVjj4qeCcawwC167UZSRKYpsDPVvwjDHDib7vF684Npw+qOsjGuuiYzi2hPJFgO24o0dYa4HjLQwoy3jmdxqt6xoL4XcZwZ3+zkMVGrYt9lYVETRtmDLRwTLeHSIm2ygU7LvKKjnMCBcgqrFRrpsuG5gMO2NuWubMAPTgmQzODZuMV3wJPWyGTMRgCBtXvLS5pkzkeybSre2ViLeqQjj/1e0g0jao7JgXhQzF8Lq+Ri9g6xTOgzL4czvCMFLB5Xw2Wvj1MTJK9fER7eEO6k75XhK1MkPew+U3Zqia3At9AXnpuqAAG4qsMSfk4cnncI8IjhTalipWma2OMgvxKAOMHXHm9Ko7tj4Gniz4WQ51dZwzyI0QSf7GYPO8qAoe09ty5M/obxpae2W2nW0zecnvm8Gh7e+k4Uj5CgLVL1B9GXMnTnI+519/R3tnjmQVWJ9gH6MGAQSMrpilHv6q/BsgjX5wWWSPOpXrU73cjXKHlp818/urXDvRK/WwctkR5hOBG/gNEHxE+4V82Cs3/ts7XP5hDvT+y1vIbx9wLmPxHd3f+QLf7/d+vCwBSDIglQwE5Is9WFzKYMReUh3q4vb3BJy3+n8KoPmdKhhqMvQdxGhLub9Czs5MS4liKoCGKbY3M8afMUEFMN2GnvZY2h4A2nLJI+N18W3BePIDAXb1b+V5bKuzP+LK8ffjFeF/rm+KwAO60+nLMShhhLeGtqSgI8l9Yq1yQAxFBOioB3NZ9jiwjx3YBe3pyengCe3MtnQI22xUORr5c3jwJgCr8lPK+s+i67GqiM4N2hsEZrvZCEjKLPAM9NatJPk+cLcN7PuGre24yCU4OXF39ffkKfzk9E1qQooofvKgz0dH7QYLSLjsA63tXpFs4qsOnLQZ7ABrAzsU288/4fHvv3lTHYl2H0MVmGK9y9Xbj03g8pviDMVFBB9dTLqj7IAMSZqwIJQpxnfe/vwzPv36Kx5VMT99Blp39jAszqFvrq/YHo2vT2aPcT3WCs42rwxh8+sFcbfesauaLc7PTtpqEsYHkW/5vmL0FcbfODv/X1x/OQPdDEQp5P25RQmYjUkDUwXVrczw5d3f+ozCtY+jYgEw5mM5zJMeqgObouxuWaWFobvQhsMYcZBuXJ6DsJTQEAX6TwJ9n6y74Y3P7WPijQL9nWB/PzHloz//EYK3dtDmzDEhAD5dzSLgyoOPm2h5+5kfuL5/H4HpY8v6zfGz9anjfgHrZiA+yMp/vhtl0Oflge+vtLL5/IzC42ExoQw4I34mtCwwRiTKJkGALj36YOTNjnQtmbZUacSFZVXF09cdpzuL2RMnmGO3EsJUOMKRy6Fhn+sZVlenWymn9qKh7YKtdWxtQ5eG09Zxt5kDXUWiDyQU0A4wW9gEj3TEEI4s6WgONlnvp2G17qfIInhGpjeZnGYfjxn/7OCYUGdO7yUryifTHl5gfv1S6JdAcYG7EYIIRACF/r/UveuS5EaOJXzgTkZmleqiUu+s2X7v/2yf2XRPS6qLqjKDdGB/4AAOMiJL6m5N7y5lpYwLg3S6w3HHAWCywGyjkhXak+XzuRe6sZJ/Kqgx1z5dNmlEgr9IjnkG88JItRyfJ5NkZ0//HW22or8lD5wkVFJZisbXwpkDuDJSHFVBp1WwSfmbj8v7Ba16sMuFZwTuAMkkjcxWFji07q6EnI8qOp+j2Owinf1rVqzrBZfLBQ+XRzw8PGK9rFiXxWeiGbZtYBu7w/62jmaCHmqXenXfGApguNNU3XhOo5T7Y1aeU8YJJk2IHPiVk3/wOMmK8qkQFyIoMzsZt+Rv68S6fmjuYAIYRG9YWJHZS5BEVQkjGsgLZaXSqBZ4cFf4DHRsMwAUSqoLFplOJVj+FKQ/cL49IlTrvfy+t5x3yoCXFaSzKvU7RzyWwdfIHBYqYIMmf5bZ0qIdlctzUCilTjqx4E5/TN0hAgrV2XXeF/6sjagcBm/9qhOWOZx1TIJp1KNUelD9TYY6yh4WvvcPjjLIGMAP6EHDEZo1Toweds6eyZPB3u9N0NpCeHA6b1B6lZOJptNcgJDAs1iR9NyUSSFgkobOSm4gnZjBD+cWiHmKVgWxUgxMkalqmahB2KnBJIl0qkRQsXWvzkA8E6e2NYpYd97pspBmLION4R3NAI5FZZTk4oc4CNSTQEAxM+g+GKTxpA1Eyw6bqTnKKqIpVni/odDuew3BQ9H9udBYyeGytos7+3saaSVgCYMsQsgxxdAFgwlukA27MfA3tNAg9xL1/bNC5iRY9wwXK8Rbix5mLeWFCBxOv7dsrbEsq7epuKxY1hVr73i4rFgvK5blAoW3J4mKyKjWjr03mmAhe1uat/p4fHjAw8MjWne9ShKtR3JevUWLV9E4THeDLR5fDR3OIvDfWyYttEbXGDNgs4ctE5ICdEIJ/QsIcQOpGwyFLKRDc947iAhgu7ISbDqZoWzXQueCJ4VRn2hA14Yhiq4N2khnRCk5VMTRUR5R+0jiOTjui/N+Hx40S6dF6CvdGAimvibOO6q+4Dwikk1m257ob5+Bfu4nD3qHBhd6gOu3Tr9tBkoHgO5wfsEDz3z9AOUXcKyUA82EjAFMCLN0kilLzpr0vE5t+xPVWygyMkjBRYMCTTHM6aj1lkk4rQGKhkOGWqGfvFbwk+8dB8/EH5SbeRTZexAhU/82El8CY9HZD7B6XqbOY23yC2/BJDAoxLxyQlp3NAN4kqNFhWQ7rl/VPueIio4RFd75wUmjID3J4ZujMHXxJZNWRs56oZmoYGloTaE6E9sMhJcwfkJGTk33MMc+dzUoKnNEIgDCOXi7fqnjx6CPoh5SPqwQpfeSMKTs0+qMOCQxR3CLkJIeNPdek0NHImMk+kXA/ctcw/NE36+Iv6MTz0FQ9HkQbvRCj6Q5E3iidhNYA1TmDLsKK9By8dgm8VeSd3LCWJEculcMyBqT1tWvbuKJQCpO4019HDrIk6QkgpRHvJ2ZMg+TsPl/6lXGsJVNfTWnsPwmEzVgAGXsnEXJFhwTrhCkW0u+Oy/uQc5M+OL5brfxtcVYK33FzNX9c37ew1NQONaqUQYX5/RPnpO/ieEy0DvypzDM6rUxRrYaGMrXw+k35R1/OFt31f0zn2k+H/d8+c5tI6GehUQrqPOS/gNM9lnUuzknuS4hmu+sF1w+e1KskJ9GcIiyWXwltNGmG8r9ADpIAqookmX8rdJ3EeMZY9AmnOttGlV1c01SN1BD9vz2s0kznFEzogSNTALIwJcOT4KhPuJtcPgcMCLDAYKdfJuIPtytmtPOUJn5Z8pnkKW76hyqWBIy9fjkvkFjLocdotf5nKNufMvEgkmFBkBh9gzDK2+tlMFpc92O/TJc1jXXW6eykMsMkJe2BlWhPiSpcwWtS9CTuM1SE6OjsKVsFqQ/qNgwAiZccBqqHycuFzD88wj9JBIF5voG+p1mADQoZ+o0DUB/K5DmbUCnPyzoO/7fULWhuTPpyzdA8ApGBStlrJz12JBPMTdVyk6Zfzzs9PewY7/zPn4jh1/XWUPsQ0Q6XtFByrW+SgTR5TAH6ScUpC836DT4r/4M9J8+ouEtoPQbfXiH/edPgBqWn96hm+HbL58TRv4shl8ZiM9ZPi9+2uNsOY1FSzFHVbpNrou9HXwy9KYZhpSkw1ludJpnC58DfdhSf21znGjF9x62aSF2fj7oIyoaWfnbDjx5xo7CH3TYvmXBZ0qAvz7J7/ifzPU+fG8xZ0Qz472UjpXk1zL551Sd5PAUwsWNIs34JhJiNHnH8REk33CNzA5+zXh+4QQIee6AF0AIBsQh9bxP99ZxvW5Y11n8sw9HAd3HwD527GN3+zeSt4J3Nbe30h4RQHanj10UDbv7UrQV1M6OjiX5dMQVugiW5tDiizj6XRfBIs2h/60CFYQ8PNN7LF/EOPzTAcATaxUbFIsqRAeGKbZ9eLKaDZh60m6oFHFR1Y+kW89KVv0EVcUmin0I+mAFurm03+Fj/SyCR/Me9F8lxtcwkWEo23UgkC0v797i6eMnr1q3+VyDLxIVVXGIYRkV5kZ/mZkXOzYJXu73WtYVG4tPwk8X/spwWyI+B1JlSt9q4YjHgGvhrffUzH/j8S8F0KOHIsAJLu/PRygjWbVlhta8x6piZqROZet0yPFFazg57Y/HKwi+wfAeJAhiniStCDAbatjUd6ndphOAnGkGZv1/EegrT3h/LYMRIjKhjyN+/vip3ob6iORQ4qL6q8IYPPdkSof/2/62QaHToYTfYJj583PYc64CMjUex4UZ35/mfuGY8reRSycA8BVgRXqPO/42HUzydsLaTqJPyeDPxQzVrKIXKf7ZYnCkPJN6uRS4aJJ9qatwPUqWIvgzCGB8rpyJw3jrDj04Iet1T0QoXNBD4PyQFRdDcMJqpUJVx8gqnuqk8x4fABsy59yEI7ivC43GlGhJQMLfCgUPxMPDbfG+5B0AFNivA909e1gXYKhgXTvWB6/+attC+HavnmutY1090BwV3bOCfc61Q4sO7KHwRAU9yHCzQs2zxtIJEkoie3+aGnYajkgDznnGYE4a4hntEQOKHZ+w2zONKRpV8MDGPryPuNkFA88AeZQ7T5+RjkO48SYw7PYtHRUGMAhxIeWsGOZ5ne5znYrx0pcT5CeVGjrOiTzumbiEoBvBW9X4uWd0+fMrdggWcwOoLy0VJe9hO4r4cd4a6AZNGpo461fspGsPoDRcglwR++WwhU6HByiRzxPnxjxGUNP7qnsmfPQP9mA6MDblZ43/kWqtoa8M8raO3lcslwdclgcs/QKBIy0AG/aNmdXw/sDP1ysr35vDJnMupXnPnmHAqg797s8txUHOTH6bxpsx0GXNnd8H/poyyxhLnoapBzKjx29VFOTE6/wj1QEbzDCk8adm2G2gqwHNA3+tN4cnXldcSlWQgckjpLFwYNjw8ekePYf8um1ZssJMIJDFs0aj6kgxXCk2hSm1S5NM1lGltimzx2mwUd8mnPeAMKcV5RCODg0komwvEQ5fuyW4kE9lrmLqgw5dH6WSLY4w4N85fXkVteRYIjAbTvE0thngjsC708TwXulhQKasYB91wjiHzM6MfKEiKwC6wbRDbSfMJGGbRADxPoStR9JQQ7QigHjQ14MUwfePEj57FtLZ7wSI6WTJPYlMDJEGr8buKwPmgKBnVWgkN7UEUKOCXSq1ogoXZa0BQUDhxaoF5LlEA+kYkfrYs7cYg+IRjFUFdGyeyRw8qXUsrbkjtDh1lUbcTjkd+6D1jqUJWl/Qou3Isnhf65LYZcOc94YCOAjruY9sp6AQjL5AbYMNeIIOe6MvTDKI/vXuvItqYcpmc37bTLz/OQPvjTqbCpEPwgluxsAt9S4Nw90N+6EDx9CSO+uWvkDgdKmsZIZ5xY8H9hXL0rEsF6erAXx7+gp78j7tRjnmtGHYN28PMXZ1nYVL2MBkmlgzuMPPKzB9bfuyYpXF+561Rjh9IiHwd31d8PDwgHVZPXi+LFj6guXi/cu9Cv2C0Qy2NHz99g1PT99g7GmaNNUE0oB1ueDysOJhvWC9XAAIxthhOqijSEKymwgzvJXEzaQ/6QigGDXLgE1rwmCo0xJSSkwNz8TXPpzFYx/MRhdsprBILoNgGQ1tXRBu6uwxzF71uXeVdRJphDa0UNC5/YapB4ZEIVp5FSYUvNEOiyQN2Ew0sSm7VYs+FM75+J7Bo2OVOfXuwhNCBZ46QqNhHoGh4JnTIiFn8acWH+tQ9SQ4oe3HSlDpBhkN0rujM4zGrAdQiWzk2X4N2zdoG2jaIB2Z1BHDi3lR8z50ouaQzeKJE3JFPieATOAAkOgJ1no667xt0J6yo3WDdA9ouU7boCIYgV5RAxO5r5BHOEPqUWVgOskRl3hBczuYUbfniEQfvGJjGyYaAsTnrwvQm/9bBNoaxgKXY30FADRTL/5XQ9MBmDvMsO/+06VjlY6lN0hnBbGB9Bvyq0+LLJyI4o46R9CJ+XR66a1lXLAqC1Nu+lWvRN7IZAh+lc4jZoP4vHe0prTTqC8IUJU4d2QL+bVBbXD/uUBWIdIYad6fxIWvUHu7XWF+RKYbY5OCuhJtCRR3CCTWK6oXqef2pXsiJtFWmjDRVMT55L4nisvYrwyij7SFIneyBj6ENJMOM/gJlnbXSBp1O5k6WUfOt5WAjf9uzLwDNCy0OTqrzoX9Lh19xflEa+o9zW3q6onMlehuc3+5I9idvqWmyBPtDN7mCAOe6CDBBFwe0/GQyCqeiYps98J5kIwgBC/leKQl/YWOFjpeM/a+DN9aBChZCOdjb2XeqiZwpOncB9GOwpxn+LPTiW6R9Gfc7/7sqpqfHV1E/kyT77t9lEhaoF4ZcpP6Tec/MZdxXhpFO4S2oMTCHA1L3tW1Hm8DJ6yI1qxg27YN+7ZTlu5MYDzSq0USSNlxuVaxZ7jO1uY8+diMCTcu+SzJPRgr11mBQPJA6HNhE1W+W5hsdTHdfB3vhckckKTKkMVC1ARHACRvM/WESKHtpjsvdCjtz0BKunLN4K0NJv8wU4x9pM4eSelmoyxSjMdh5VVnItvYFbYzgEs70lGjDDMhaeoeMQH+ihhWTVwvJ2Po60q9xn///PSMIBoTb18o1FsC4t9of4A6kPMCgwdA/L0NgzXaAXzW/elIM4DBnp6Ttyi+wF57YDfW2BPbxVvRLJ3r4pvYbQ/nedE+LAr3pUeiK+8ztbmcGonJKfJ/QB2VSqc8OSSEG9snkF6sh6xXwDwY7dWPYFVpcmzE6gSyYiLRhL/EPBlVIZB3b/w3uwKfvLBL3gqA13xA32n7vk2+4zOAysEyMFqf5ZOgvf3sI9O3TpsyEAFlvwqfJ1dsrlz1j82/ldHYne/i+8KMSJeAHf1CScXzP/9UyvdREyx4NMO3mXkOAPhKvv0qZSa4DiV5ggZ9rHQgd46fgfaTr4cnADrz018+4/I/PwAAXv/lvRdeNMH4+yfswcsMQBNc06HBdSg+npBtTrK0j1ST90eTDP7Q7V7Aeb0AJoavrHKd/nc/Nn4SKW0PsX8AFkA4f+vic9FidslvF2uwvmAPeWvIwJ/HoVyHSfYiyCp0AIkYIJtjirZ19TmOeAUL3DT8fkF1VrUHybVNnSjXyOcgCr/ms1NXivvw28XeoX8QPH/8FY3+SwEg6vSjuUSO1vUbb/bW5pVjNLmLTByWfDISZ/WpIpO7RpA+xDD1r8kLIrqlDKBrFhV40YRhH4ZlKHtqK6R5SWnKa+qaY8RYWMSBSAachQauqwYaGYO4w6DYsakwyWnHWLz9W+uLt1uD6yE2BKJuj2B4C6kFHkC/9IUJdzPw3OA+pNDXNVBWUvpwPzbgE4AmhvcY3rptN1xg+Pz//xWXdcV6eUDvHY8i2KQT0ch994s0XNp7POMXDDSIfmTCvGIzxWVzBFrsgud94Pp3T1wffcFrAJ+EOrYJIIoLW3wM89Z/XjjQYBiQ1tCXBa/eCr598jjGMKdHASCd+h/E/bTNEkHxsq6O4Eha6Gjol5Z8V8CWv61h23YoDL0tsCQug1mjtAkZHbQE6vzlfe6aojEJ8KJt+288/qQKdBQFB7hV9w4/yJeS/1kGak7a+c1RM6z9Gi8fr7igLj5eUEiFW9PqYk0xeWcEzi4EpUfb/fPiIgYSYrDTya8O9/DXnyF4m+/t9H2q9yI4/Dc5GoXL4aL5O5eLxdEXp8nh9HnP00TM6369GdfhOjL/nWZlnud8+eaon1l90WLueEIuKp+nPNdxYFPtOAex74/uMFLePsQclTMJ5XMyjRyqlYU/C6gyIQaw8twFeo8KGwEz3Y4TSJ0mJynGEUaZj2VMx0oatawMovLgTpLmWVh01NtVXRmhkWvavOoQzZ1BTw1tcYWlS8PaF++HTs+H0LFgSziQYuyuOKyv3+CVCL59/eqGclG+5ESPh30aCoBNOFM3lmPeNYVEGHzu/PwK0wsiI7b+Q77mnqSAnhVXx/vDIrnH8kMLOgAAewYy8OwOrkjYicC9++H4iwMP43OIZFWFTEKf9ESnl4yRgWcRYCI4c0NxLiNIFrlzQh53rMotdIUFZjsq/JIUEk7/Vf7izrsg+/Ts5PZM0WqhADVXSnSPGhFCOSOyQQkTDQ9OeeVZh8CTDYYqtn1De27AFRDpObdjGPaxJayyiWfqu0PLFaB9H3SGgFDInYOfcNDpfKWTBYKZcVlmIByp4Shp5ieFoQo6CoJPzVBBobN5Q64jIpKKaTQWdVUkoY8Xwrm33mEMhATdpUNekIq5ZuCkIaCd0ymdWZ47AqLUnT8xJ75GFgp1OMoKbzvIrUmW0wDiLCjXOvaDr3fZV+VKL3HtoPWZaGwIC0u82K2MTY50b5b9n92IbBmQnUob6PxxlS4hx4N3cGFMh1ckcaNY6gcMCNFRmY4pKuFjKINxCtisvnA+WHSSImSPMkzKv9i7UhknFeqpgoZI9HwGpx+vDqWcEMKSC+CO/RDWmPs75hCT9aB+WkQguK6xn8OvHk7PSZOuEMR6KStUxtix71uOflkMKosby6TvWLdo0xH7GuwFGP20Y5+03g8BCDMDdHef5/DAx9Aduu0Y+4bQ7EUa2tjR0P3cDnRxp6/CmEhIPmxlx5s7wtSaV9oM0moY4IYMqsXEZbEYicD5DJ/NQnM2DDFK37kRnG8asHvFlNOV93LOyh9phE7skC7Yx+Y8dXPj1vJ6U5anjlX1miIPJsIIaXcoGnEBhTy/dQYYdfIXgwc4m8ODAI0VfkPQxvDEB3jCz8PrV9ih2KGQraMtAwmcTQfGuqy4XFZPXJMOHTv2bcd23byqqnc0ojOoem9fDxD5Pu/dkxbSQSRMjDL/PILnrXXynxmUmftrYMSa0mHpssurx4V6GARY2oDRWbAPxbbtPiZmGZgYZDAZK3qx985lMNKmJdLBsCkncn9Sh3EIW9JTQJ1zLx6C6AmbGks/nYCxse+aazFh8TJeFJ3Q8hwXdJWFZFVKZvpMGrRyHWnNHSFd0VQ9kB4tFaKkxsJhBkA9GUzVWzg0NFg3h01twad8j8WzizSIKSQrx6YNYZhBqGkoleCmAGO3nNMpy0J2pliFmKZOWekYRa4qdcobJfWfPl6SqqdTQj8G5RrEkxO7O2HauqCvK/q6Yrks6Otl8lgDg9uGtnuyEai/6lCIDE8mQi/0cT7alB8Senv8U8p7yzHmOgj1pSqLrE6gHNblPC9GHjjrOfyvAAAgAElEQVSHFKnpoWerBx7zO9J20nPwzJY2QyBwtCgHivm8nfDDkTps0mAMI5UCn6MgQ27M8AvU85pEKxMiNLENyCy0iYpch7se+5aQmrOqzGk+i20p8kNvikD69BorgoA05B2mCZ9yTzI0cHtNc2kRQPjaYp819iZz/hDByp1VUOFcTySPEaGG2GO+qi1UJvIBEXe2OlKGOR1Sl9UYpzDAFYnjbcJV9mYw6XNec1kteTEMWZnq31TdF65/WZGnOSfBh2kfUFdDgd+f14l55T1SDzUi65Qqu7h+LFei6FjqIHGN+VBzPwppbibRG4sEwt4PfxVp0sD2CTaD6OYJ9xaJoLEmZVtQKk7eZO7gHbsnq42xY2fi5dgHhu2eDKyzryqXLTZS0uD0pcUahI8yaCOmfhRbYR5BU8FbLJMyYnKDzxe/kR3+zIB7kTUHugBQw3Wz+liyfkJEoZGYww3ngbFGw6jQYV7Tg94xp3FPR2Li3Ciwj20mBxCmPBCkTAjNLiA6kLIylYG93YgyIDOhM8YhmutgTI4Kn0HyAmPBTaA+sOgDYoTwV0/4Fm8x43bB8LZQ0mYSmM2E5Lh4JGaIGIRJ52ahmx33qO8cSxpxcRQSvCQCCBy9gvNvACKJKezC1iVRrswEnba/0oD1vU89/+SsjbkrbB8CYxV8myMu6xyBaqkPD2M+hcLGpCnT0FPI/Cg3Z0snS5qGwdFA1H1ygcK4LCvkx3fYfv2IJm9KMhfoG1CY/VZ2QAqypEvhk6gBHeRJn/z79i5CWeTqBUUhn81ibWR+ltMSG/D4m/n65b+PdhxrjHMeB0u+/NIO531LZIt6Dzl8FxXp816xL3TaQHztts0ntPY+fX79AzB+dXs51sCrgYH+Hx8w/var2951CDgM5f7B/Q/jupydAk4idI9MeonxRwDYyezIf2dl/bzsIUk3rlJkKhBxDkNqGbH35p3KSkj6YBvq+iBfTQ4UIX2B2dfyFJgytMUqVdyhmtx2nM45U5V6ph+ofQD2X5iwxF/rYXRliWL6eW//bD753SPEkBWJ44yKf2NeJxPzK047hVwnZwpSOIsZdhZK7PtA6144MhhU938Flp06i+eJMRZieVN/Et7E1DDaAEbQjdIepy+5sXg19DzK+gZPlOgQVqJ3b+WJkvjBe+QvRCDi8i7bm/CMxtYYBjaKMm+qJ8ZEgdbQdKDpgI6ecO7WlAUafp0HCL7WrUOa+iKKd0ySU3Vks10Eu8xKdKaF4MHK8OG8+OnXz1jfveEeMqA1rOt77PgVuwUV+ZOqRqFt0UmMNkhQCHmlJ0TOALqSNzcLXz7PQ/OWZX6HnNVJxaR9Qc7j8SAdBCMoPELmKf/W418OoP/hI3XRo/C/OeHFGZDvfBdnzIu+AvAMz9BoAL7I6beSYYm52cspwWLDVo+vkiF9b6h3jif2eHpzHgbmk8X9FJ/zHvFZhd9QAN3eYvmxYWdlehpBSD3Ox3ua52CstReGf3L7MPU6IbisfaWiGeecgkLv+PfGETKZYry7e57VG9ZfW7mvHOe+rl0aOYLYa/P8O+KjOhoAHPvqvSRuQorf/zb1hxc+r3QWhqwArMJEKpWdTv5QYCOrC2AVjjG4gwnzlFWDrKxrIoD7o/17eDByWRZWmABQz7SPPtU9zundg5ciuLzxQMvSelZydvZUdYIU2DdWBQgh6cWZbhfB9etXCp8I8ErZg3Nvh/JSagQy4GesOIR5ZunUlZS2IAMuGrBtv2FP4/8CY/WfwisdWu9Z4YUcwVRgDEDHAwDDwLfDSFNxMKDZBQNXpLPO4LC/iOp70HCXIpRIz61hOeWtiqAEcd1Bs21b3j9pJ2nIMptZmXUmzdd9mgxVRRPs5tdziJt98ufD0/M6F4Ns8/sg3KyEqYMnkR+NFaQCt20bHVIdtqtn9tWnMSBCuNK6K2MqaIsATd0xsj3j6RnY9oGv3548oAErwdwZNFsW8f6oi6BLZwDUCWxjdXXvbsi2vpDg5ioXdx4rVJJT80MymXREGHvFzqcSrlE6jzD5cMzXhHYVSGeqi3VeI/b0VF5iLRorXnv3qtxNNWH0jIkCZurXnNoeUR9kVuO2Bphiu1Y6EyYtzd5RB7NH3Inu10PuBwDoq6sW2VuZ87P01ff3NlE2QH4VmdBm7Bduk8ZfZsURTBImSSDHVulKVdn7ljzYE9NdESXcYxpkguLsC/INGG4tMou8OJxyXKegj1DegyaHKqCEAdSgiZChXNsIBAwljBMVctUcU4UlE2F4IaCkaeykcy2uL7Fy+SEAwdIdOltAWGNpSWcBrxyH5YKEE2fOLcpZST1y0vcsnPQxCjpiNLJ66ayy0D3oFCVcd0A+qzr8YQP8ua0q3Za8IIJprTe0ZcWytKyCbq3nvg15YTBCim3Ytg3XUsEEAxYsrLYhb+sRoPQksyYhQxt9AAr0BrXuCVTqGBsqvhf2rfDdYH8aFRN+fnyZQJUhP1kp30qShq+L/yTgdaNPLMBECmNSF58DiACBQ8p7ZjGhluFVPolo0VBT5mGcu1BYZoUd2JPdYC2CSS6HVxEs6+pzve+IHrtPz8+4bvvsh969ZczDqwsuDw942B98HfqCvix4eHj0Mle4g69T73EkDg8mC5yn7cPXc3u64vr07KgPTB50GtQZPDd3PsE6pCnbKXDPtVQoyXynjpkB4aLmSmNgT51GNrYUyP6v3EPu/AcgXoWlY08Iu+QrEFY1+v6J9Qp+p2NkstBE5iHVsBIsdKd7CYUCC9aD+WIeL7Hf8/f39N48g3OUso+6ouR3lvM3PTm+j32vz9Y/9TtpXoHe+4LeR1aQCyKZTDOhEfD+xaMNdHR07V5d2CV5lZIPCULnNq9wYFBg6kpUylPFKTZVPE5WgM2516gUVU1UgERzE6ehWOfQxuZyHNfFDq+s8AdqfXMayzpJjP7OMhW+blaCVj7nngfounNfF1wWttN59YDHx1e4PD7g4XJBa4Kd8k7Q0czQFl8nlCrwnB07BgaietffBgc7KKmpl9WgwXwG/6QxYD2fqkwG583SNqz6qtOZlU9jvU2pFzbnE26P0DYhUsiEOVzTsYZ4zuJ4y1GblWBO6FeHhZnvDdPHfF4+AImsF/9yukPHLElywUeCf5JPzB7newbSK/T1wUoQrzq22CsiGbxJCyEcaUKkLDDIHnyUT5MVsHyYWa0bkNWWAbIG72GNBteV2JYFEpVrKewo5418MBBL5nZuIlgQQV843QpR7YgSZmpe2R56PM81wjM7OoGnsnUAwxrQ4bCi1d7Vwn+59tLC4y6pY6H8ydeVNVuKW9LW8f2BeHF6HT/gX+N9vWoYyYrP1wciwJqcadLd6V3q0TlXlJfVKUUF0JKguU8I02A2babZe3XqvxoVyyMSYT14Pjb2VR0Du0Y7Hy2oRSH3ggLCLisM/s4z1cM1zXH43mLt4joCCBwdxVHYDAHxHkH04zX9f4rTcVNpcvplrNkUjc679z3XIGWSC6ZJMFzsuLed3iOKEBiAjmSFuJnFPg76Nvh5/C8gkp0Vkc9A0042TLQbAUU1dfkIUmTPdvJVoY4cOpYqYd0bMK47A8TO3wTiiBr53JOEfFwEt0+yChqIoDQTqA0Y357mOoHBcWmuB9e98u0b40xcp9evfKqHM+PlsjjfZEC/MRHLK3g5Lu434Vo6EtW067zQheMOWWnuf1iWgqlZvk+mcaAeyc/ivjYXf55VlTvu5TgvbNKgytbfQWC4/vrJT3/7HmZAf/eGvsm5X1QH9o+f+fspu4/31xx+2EcSaFyHFfF3zmIa+oe3wT3Ktc7Pf3zOIyrDC+fw/avULSw/NVgGVvbD/Srjnlf6JoZX9tJ4jmP13uh17xsioLkc7ueH/izQnz6htR99PL843QwdRCjw64+fP0MgePwfP0JE8OXvv96dAomCnZDZoY9Pork9TkZBBJWnrhXnlVUkb1n4YeiJHf64EStdeJVAkGHOSxa6REukCO7F9aMCPHT2OUJemHp7yBylXyx00t3cH9x4vertjHvlGvAZBFMVM4nWV+W+dcpOr59+/Ui9ZH5W3t788hxnmvuEAdIbmrfD65J/nMsrMq8U14vnTGsibLOENBSA+U1qbhNsOiCDyDGDqKqlJVAWgEDcH+QTFtwYMNdTG4iwQV83gZzQtPiDqMCkFiGCEYiRzW3GpQ+MvWORHbs0dJnILrmaBkRRVNBiroIAIsYsENdUI2l4wMfwhAHYgktk0Zvh1VBcA/FkH7Dd7dRoKdfkAwTfAAgetLEAw3879DN2ylaF84Wqt30TH84bdf/ILr5Xrh8/o78DWntLPUHw+OFHPP3s+73BcPmh4cuTzSA67ZfeGmzpeLhc0JcFpoplWSDh7y5sdgxHM5bW0NEwdCMd+vzEXj+zjIMIJp1lknklcSnn4v/c8e8LoANJwBNW8B959BeYc712OZT/XnxAcjMrcvlPX4kzF7T5Ufw9hs7md+fzTD4dGCZNRc9usreA/ObnnX77xx+pKFgvHPXa//hxEFGp8714txdvJIfvDmO688D5/Z+ytlOprkqBlN18VDI5gtRkq0OrKnXlWmUZAtYtZFJ810TgWarCzHcGSNTv38i4YjzSAGvNM+wZWIiqQ9vNs12FDmVxKMp1IVz74s6WpXesCwPrrSccrkiDLHAYudcCe/ZiAO/jIWiNRkvs/Zvnrepv/VtURBq8Gr0TzQhvPind1AOFwwiXGxDUGn07n45OY85nE4G9EuDbVAi0OELFSnZ0Wa3I0DQAyuD5VPSUhn9jzxquC/neNFBf3mtRKX6eJ4QyKKGqWzrkJ+SdHXiN/36qrHKgXUCCS97xfs+gzVSZUoGy+Tqu5UN0bcv/TMNG8rljFo4OSpTfz2tKMgodBm0Dz5srYl2eIVFBHWc3gfQFy7pgfbigSceyNCzLiqV5YCjpYjeYKNS6Iy7QiSTLrLoNRfI8vsmH6EiIAathhxUFIJw0Ab87lTlPkvYZiHy8Zv482gyts7pK5v5xVsP5YfCuRT90Qg8JYS2Z/u/rQHpwh8TchUJlsveOoQJg4338vun4irWPIL7FvmaFv4REV9yZsfk+SFTmXEBAZ6t5WVEACRVo1LtH2VOOHFDtuuMYajB8qKK14UquRgXqYGC1+d6Na6Tj28+La8XDtMYnHrHHS8CNUPHCHuJGB25ZwTLGkzyBpVFa6lROh9Nh9AaOcZ7HOGUH5zpp17PPm4SDtzG2MaExq7w9o9GkA60s0nGkcljnuSZzbI4oEs56TVhNmPP9QcjtobtXzBmgQsQAJnRFQDvbA3E7RvBcKMd686rh6LsNRPWGG26eSMGgOdsiDHWofYcqB7KMOGBbfdc6zJcAE4xOWP3j6AIGp9VBZ3kEa1N2x5TarJYNX1/MsNMke7ebVz8iAn+tuX6hQUuWAXgnIxr5EcSLin+utQirw5snzUWVUtzf13/SwtH3yjcMmDgNNQiDEOn4NueLC5NrRMR71asmpHPQZWsOvzZsZL9NM+DyuuHh8gCIJ+l4IIgBVhHs24ZBqOGx79h3p6fBHmvXfcO+7+jisNkhk5QQohHYbgNQW9BZlhg63lELKKRc4AXj2c7/zBT72NNp07vvDzckNddkYwWdI4gMwpxKtkvo1PHiX+pXGLxO8AEj1ByoT/oXWfnIdUtUHoRRG58jqa+qq9OXb8f9f+I5SB0mZLhkAo1ksKoG0GeSz4HVcH2DThPphK9760A36KJYRicPGTD187ziNTYT5S11SWsGs879y+vDeXdWe8XjxT5I+zUeV+Y8no6zHmewhLv1JImAEb79bTqnyldn/fn2d8f39+XG7VGW9zhWBO+OJWqZfNp7R1s6lnXFerng8nDB44MnvEAE2K4YQ9BhMO2ZvCRdIPtMysv2EkSBiXk76Kq0XULvDDo1Ed+zpNesYjAUOuE83lUm6pOfZLHdkbxMUsky49AP6ShsRDpKdam5fI7K4KmjS26LOqwD3d8o1uejnF1ehn5l4uOplaTSJSvQK9pM/PWK0DERKQpCj5mxFRCmDRXDlHA0cgXS62r8zveReEQ6+Wxd5+A7cWG9NQx8fAzOhf6bKDOR8JcyLiCd+VrZpqIk/Annq7P1goQc12hpJbmGrXVHvAg5Rx1RVNm2QSDqSBUGc9kBuA0MSRusBjBjFsWiEvxEoyJp/1rInzt8xiu0yEd8cxTncSExO//OnC+numms+AID/UXOW/7C/xY7+mw7zoA55+mU2B8La7FGlAvNGtAGVKlVCRJ157wXDYZGHu9JkJ7smNDtu6O4jDEwtjHpOOhUJs8vQzrdY+rj97jH5Mgy5/OgKxSeIvW7gKtOITvvee9G53Wz43kZJMqIB2airQWf8bMaEwnqzdIiIe0gWle44sD7DYC+DYuNE/uctJM0wt9KE++hiuDxXPPaEoDjUCJ6OGqJTQjooq9Y6Bx0wCzRqoNPMYY/x6CO7qFa9qY1S9h5YAajs5JOhEmmpG3hhBgcyj01pDrrMS/zG7PTeeV6Cg/81PsKWNAUybBlbVugbABebV/pIeyHcvfU2A1RRoj0u8kLtJU6LNe0/I35Pia3Bf1NWz9ChiSzDLrkLVJmNspx5wdue3/i2L9/+PWPoUlAwNgw5pwXG9Nws2713UFnq3raqbXB7x03ouo7v/0eN/kjhwfRj1ePJmuz8Gjy6Ym6Mzno9vPngwkT49//61cs/5ET+q8dJ9t2KjzzIG4nWJ9zmJV65nm2EhG06IcHVmq36yH1ldjNp/XMmK3pWTwP5mXNOoPP5Q4NAMymnQrW6eRYrSSI3R1x/k3aTcl0Zwxxrh3f43T+zbzK7XchK4tqFmIsaXneR9JtRMUORv6mumPXHdveU+8d1MuGRoGKpaxIGzQF09TLNRBH4PZuE3fJgH53aYputcgOqY9428LGf14YOJYFfR/o4kiSIjLdj5Rtt5vc9do38FYLEwlTct6oTuVzhXwTFjAMHcBu7qfISvyRQXRTzBxtLs5uLPoxxQ5v2pwtdAtn+YG6uLwH7NPcItsnw+XtwCKCtqwA5VeHYH331osynjyeWAsat3335Gj6zqItzz54XvqLHPllHx57CR8tsacO9PUiFyzbOoj8ZR77f+74twbQAbJwKcbjP/C7g9AJRe+O4g54j4glFLDfuXL9c9Yw7rLZf2IVzYDXBfaVNtVR5FthqmUAbpAeCWj54JB3608OcPL8SxnaHa4a89DIEWZ8oXLMyW3jfhMy/L5A66fJkNPr43aJdSyfxC1jGaqmdxjf4VfFeKtVgzy/DCIeMxWlE718T4weD6HiaOdPXzr98NesjstSuZDWoNcxBxIca3Hn7rIsdKi7uFyizyKFTWcFrzuuhdnyfqPe2SOEhpuYQ8Z39r/z7FfLyj53Igp6Wzzg0Bf07nDt67JiXd2p3VvDGsELYxbts6/XEk4NGKwRsEeuni0a9H6i5fN6JJulkjTYwyuNKiMdmSZfiGpFZTXpMHfKm0ZFxQrVDVHd7Of4fDTx/ig7jlRmJlh/WDDGwII3gBmevn4ppgIywO7GUXFCA/ASV9+fvftvGvuGImlp0uVZ4QEES/SEZPAugvvR9zUcWhpKDiWNGaszwrEfzyUuZINuB3bqORT6hx0bDmSBrALdDH3tsH3Ok+68z0rOJqd1rXpPvpwG9p3TDkeIXjMPoF91hzSdldfR9iAcr72jq2FXh11YlgVNHvB4eUj47etm2c9x2EAfHbYsvi7q+6Ev3vMIhyWS5NM5euM6U3lK2DMqxemQp60ZVSceBJPsXQnOR66PRSiuHeCEJowcaSaq75YFq1n2snUniAErsh9x0E46jw6tHiIruPLKuQ4BN3esNpacF9CZ3RNRYP6uLvK+OfE08SBzv3jvuu35Cq/kVe5RJZu8z6HTeUlYQGkB9EqdwD0I4UtKetcI6vFZhLBCYyhacyW+9+481CZVHiqP89l8L0/5IgB2wmI3V0zFE5SkdUICg7JUcv0OsiL2cO5H4GCC3mTc+Ry06pzltWa1Qpt7XIrEEmQFp8+pQYg9VvfqS+VuwWvOAa1YIFfzjgGvKn+dLzuklxLWeuxeoYsSPHdDRGEeJ/N+TKYQ9tVWQmBBzSG40uNbFKzYymF4B1wiq+32MbCVinMfR1ExD45gzlufgSUhjTV+53vwjq5R1/qO9RDOXRhpDsr4aDigd+fekfjJSsneSgUnL519rlUzYJ8weyP6ufkRhmQkgKTeNHbfBsxEXrAgq5kLPwu6Cpjrbd+TNuJRx3AY89aWrFhUU+xDslos0JibuPNbOtCXhjEWokQA6+qoCat6MsISWTNm2PqC7fqM/Ur9YEga5rCgtx1obYIBG5hs4JVA3oO18Jg2PxuwRCI50HtKbJTPSgCdNOHP4E6FqMPJ5A0bOb597HNtYjAl0NVbJ0JRQ8BkiYSTdcwezeRLqoPQxfcJL4InVpBsKs0eTC1foHx9tuOSB3MuLOZEYm6OiQVTS5/3yICawHXfTJKr9/HDDXpPIHN9eWCow/HNx+V80PHemmHfDdaL4t0dZi7g1wXIPZxSKHnBDP7d2AQxdpBf8Bpj3wEsXpHBudZdSxsKh/SrJo/wQePv1A+Lonhw/OL2yHnnCfcULdSPeaNQcHL9hWgnbMEDBmKZ7LIsC5b1gnVdPRjLNgWxBjaYlNs6Rttz7pyHOA0kUo9MiNtUrpKB2uFP6L7xeJZ6w+1kzIBZ3PM28eEY1C1fmKXOpCFQypz5rnZZheHyN+TrlElxD0r2fJ83eUEXdifZ93wmU/aXcF5dez5/VKC3Pl9H664dlsnHYwwmmzLJI+RRtSkEWVFuJJQ6/gPfEO4FmR9KPrvNtYhK/OPUHxInYs4beeFCOHqA6GRs/eLP4GMfUcXKZJqYpQbDkAaTMZ2DrAQNRBkPousMpmMG0AG379y+CNukw5pCmnlCGsRh+w/raYXeafhzL4T6OQPnRvk9P/NzGdCs7TcSESlvddD5boI36eiNa81WIC43NSuEjXr1ZIi4R6yF3iYq3oRtliO9m3opXgO0DTRlcmNjQJW/uUlQEmCwl7cSuj2C5xsT5baN7Qf2UaDbeZ2GA/LI+aioEXeVte8cYTsnZ2NCsmkJdNexWP0tHy959sv3KINNznFIbDifaUYQodgLR9mRtDZGyjkL+5HVqtEaDUAmo4xtn9coPDVoKBDJ9rG7z0KNlZlTQQ/aRrmGItCYijqtlrznul9xWS/Yto306wnS4Q/C9QqY23TKRE0xQ196eSZeLPmS5bOEoFF7gsgDkrkd1T6clzEoJhKK9q9P/tPHRzj4FeVIJNKEmOv9IHtTnrUGaZZ6t9vcvcC++72acB+pJ6Es1ca08g/ghBKLNGRi0E58fVIXNPnRnIo4/HT//z72pN/2VrCPj2h4y30wbdCvv3wEOcpxQvPtrTSU06uDjcZn2fepP3NX4HzcS3hE8Lzv8LR6fCvnPX7nZ/e2cDzZq3tf/sH7RgW8ArjCEjzRP/PSGP0FsJ8+orV3ePiPD9Q9P2H86jfuP73Dsiy4/vUXr7r9r48Fxvx0hMF7EOw4vj485I2Cc5ijqEtN3a+gk6gRR0+AB9L3M0IPpas89p34Vbb4zNz91QxHNwAnfRZJUe+MsVnMn3+7GrC8e439yze014/YvnzNXxnHiBhLzJkBEoVtXuGI9cM7iAjWxeM2X/72M8y82Czo/7yX5uiAkgsVTwIBsEk5B/McqXPDK30S4L3dSP/TUYv84j5TLy+3T13iGJsTFMgjRBd3NcOu5ogoYFsNRcqtXdXbsLK9WOiUk8H6/4z+VE/4i7YcfqfeAS9YMMjoGN08iB6jk+CjHb0blj6wLJHEDFy3LX1p7gubvNWTdH1Mb9TwOdZcgG+tJA2kzEDaAtmm0IDlpzfov11ZaT68Ql08CD32gWXfgfevcf3r3yFjh+ItgGcYgOUnSVkxfkZWoDsaIVvowvfJawYSE7nEAKGaZWbYPv+G9v4NsLuMX96/w/XXT7RvBA+quLbm/eOFfluZxRYxL9lW7IaK4OfDfUvYtpLcc4rl3jsK27jLp/8vOf7lAHoGbfIoilA9j+eG8vyS0voP3v3FbwYM4cr/DTNg9LsL9990vLYwsEOWlKxAhO72FpDPh98dDR8/FryHYRon/v0UB+GzmPeqDPmWCcb3L87Md6asBuNuB/3fdXxntHJ+ebTwvvucf+C2k47iNcWT3Nw4z4rTUimFpMKnGoEiZ3ApvHcDFs8C7jSoI0jusMkB9zezw2IIkSEPBVQGurGyXJpnXzUPggPiFeZopKXGAHrHsrAabXFH7br666h2bV3cocuwVX/l1ecmkjA3XQQqV6gKx1toNYyz0xRnpRyfLYMn0asTNvvowOnPoa/o+GGvvt3YCy0qHFVYTfENpg8JTxlQL7ALBM8H+ojXMb/36KbKTVdap0bna83RGuZzxW9fUCpDqcixUOsToSCvp2IaX8gx2rRLSW/xHCmYDg8x35kMKgZL0qX/rwDXrOLV26frHHgBLT/jPcNJVjkx8q+df41DsE3mmTCbyox41WRAxUCEBqgHjR2y1vfDsi6EJ6YRj0kv6LGOzqO7Lt6LN9fiDks7TvBB1+vx+CKZKCX1cYH8wJh1H+uthPGFKXsxa1YAzNsUVARmUxodFDCH2tnYpmFnhadZwPwSnWGPLAgqreRFsxpx7lERT8wJtItYn3R+xxqfaOneUXVMKQHGQ8WKAQ4VeCf9LfjgIQADOtwBG/E+ZjRk61T6QvFrdDQ0FU+mSKe9O0TN2pSvCEXdf+vZ88ZA4KyU6NKxD4XYyIQNE+dhQWNozQ0nekmzTzGd+41QzRlkL89rrLSPSPq5Ui8CVf6mnFP/VXkoDk3qS0hCtZlo0MKhVILosfbHKiOZ8in37YkWgrb4b+jAdXNHZwTQsxJ9hNN+MqzgfZMDuoEqo+wLVjQ5hKxCzXsYq2gOdPkAACAASURBVCr2qK6OSntxmt62zR2v/GuEpGrChBA60ZeFCWRRwU6+k7DS5TlnH/Dgz+YOW/V1tdb9PbmecPywBhM6DU0zeSyuP5S0MizpSVpzhJnWytzAgwbmGd4KzFYowayKfI2Kw+j13JtDW2tfpiwSh7D3tidEcMBJ1w96zEHM/RbIAYFcEYGGZQ0FyH+lFmgd0eeOhiFJUZV8b3VEgkjaUVPIGAgDTYcHrDV1B2QgaMS+CAhMn3AnCSUdNZc1zcSDNzIRU4KcJ/KDpbM0aV8iUSn2WA3GzL1u5jQbFXOeUOK8r/VWdH1Hsoj+68I2OmYe2Axb1h1R/IuaKHFrBUzIV+pDYOKBlGSwVF7dGDfK8tuQ9tyXgBz5RIv7kl80TF5U9Y+TTABhS4+tM6a+5c60BunAYg4rt48dre0vyiLnEyCqhNOlNIGoOZx7yAuJRBgr8r7oRKFPWb020Yfc8j/OSnc6UNBpk7xq8POSBCnTzZAqWATz71z7/hqUcZ0cYJL//65xxydC4enzegrLhIQatJkBcE/StZAfatiCf2bi1pxA/+2E0Y695XuBhMogH8x73EYbitCtp84g5W9RkBF8NvhgmQGyoQjaG/lBTHUrzx66Tn3uo9/9KA+Kcn6c9/vKZY5NIC+cM8c8N3O5X9UH7Ki3IdYIx6Bm/DaSjs3MZSGNn4ALPidYOs+ZukOMycWeHR7bWceZNvnMYfdM9f7wmPUQiUqi1eXyulDXgif4mtuBG/WLEYkpZS+H3HVppJ4AOihfOWddXA45zx7epoVtoEI3DPuwWSMsrif5tSboHfBK0eZ8RmJNgEhoMyaOQnxvG1tOmLF6Sb3KaiYxWAbJPf6mqYOmTl750gnJKfxzGXBPvQwFAcjSzgjI5Aimx3pNEqi8IegLc96kpU5x1kFjL+aiq0CbekIoi/JfZFGkLU+WoN2/z+rzufauV2Z1G4+OfjuWfE7M13cp8KT3fGeYLgv9+UKWCte59uO+vYbhzod573P17Fk7visjQoeWODf2rOXXM2HA7T4LfRY48IqwKUPHmwH5qv8yOLoP6oHOQzTGKiFDAh2NgxCDimEE1F99HvMCKWmeEPR8faY9wYC0gDD5cKQ6eOW3wj8f+6Af7cSHyuwJ5jUMgD0B9vhMNBsPTsaPDO5IN7Mswsjn4EkxxQ1zLgGnXcveO4KMGBLmFqV63+2Wur7RT8mTc2rakVB38V7XvOYhCue+EhtapJEU+RfXiSWdKHPxRDd+3/yNJxLHuooBrb+FWCB3uE4w9tk+8eWj3sPufnMwvw66pFFH94rfYDHxXVyjPu9Lr//Z46xh/etXvD2YX533orsV0URBAeBnQP7ivKe3BpP3kL843YWN//A/P+DrX3/5Yzf9HT/PHz0/9VLqLPHekKAk/oyUUZX3uE3Gywc/DB0CSebfG9R9Gi6LdvnxraPT/PDqcArj4of1vFlrypFIyHUe5XKoqT/vqFNDvbLktX9/+N87bnwlwZfS+r/5PseQuiCox1EWlGumDpPfx09CF/c1VFNvfzMUhh22sRgKjoIS8z+Gus7GZMfpRZhcLXRHKc8XkkRA5D4P2QIA2mjoy2y9aIxVNMZQ+tKxjCX1p74s6H3DMPfbBhoJKNtE3QfwhZNQbZ14dog38Wkci8W82aT19ac30I9P7uuCJ7RdB2D7wNgVu+6e6DV+htlrCAzLT2+hDUwyUAxoFvVEYaEP13U3D5iHLfsWsI9OfzKLirdfP+Py4ztPKGCC+r7vWJY1k/sf1gVXIgMGZLtPvyXflXi2smK9d6gBO5HWDiR2l/BOBzfTfwe//DOPP6UC/Taj4N5jz+C5Q4eRAv9ZFnH6aWPpileFAU9VCfjeWP9pDnVvQC8fK//mnXn65ccfMX4Z2OUTgM/Bk/KotmYD0O09+k9eeQmBO9t+1akc0XI9F6oFxIuVa/kN+EkY2L//KAdJQTN8Gh/woehH3zT9x9NIeL/M3DqV1IVxdh5CVtMhhFEZdvLyydRjLFGlHE9nZZr8/qc7naXgYXD1tDu/K+Ovk5iOlaLkOBQyoDsQKNAA0ik5hb+gL4srFco+FJgPvywLtn3PXiBdFqzrBfu4AsJ+5miQ3bNwXSmxHFMDg5AULP2y0PB359es8F1w6T0z5RK9qUkaue1RMJ5DuaaDEo8QfMvnUi5Yk/KcOU/R84p14ny/6COe7DcqR5PWaF/Q6Jtwg149oRi7YmCkU0BBiOvsged1YLNKNjh2WE2WPZxDSF5e/YDxzeFTxBSKay6yVsUtDAwK33BwNGpHE3bcj6z4qoaxCK7XK7Myfc5UhyvBzKjOSoGE+w+PgxRBFU7o261dlaVYTsGCqBiYpOa7fGyhdDcue+48Pi9X58BPpoI8qSOmuAao41U1BI8GlAhhd5YF67riwn4sEejqreF5u2LbdrY68KzWpS/ZD00QToHiHIRnrmMH1nV4IDYqc+P5JX4bj2LJi+aa03g9zYGOuW4yHwfp6eJU6zCoCCF8GIArVWlBGkpFE/Agy6IdstJwiuA5e+4O9t0d++6VofuewXSIuMNRZ785xLoWIzNpq01DBaBxoJxPmesVAaCgwdhjY/OK1r54L/RYg1ScRdzkK06cSUeggupGeGhwkl82oIWTsnPeN3hQIxKVHPLYoeMA9NWzY7k+TRshN0MRn/0rA9ird0maSToFdZuFCRwYaK3j8c0PAAT7dvUEjnC6Mut11o1T+aZDOwJkEklKQX8STu8271t7Sra6d+bOzJ6nFEJTnk5UgRrAMIFXPNg0sBOjoKxzwkgX3U7krH3YIWAUEI77vhNme5+BzQLjHk645AGH9Q6+yqQq8v19BByYtwGwCFbGX86zdKcjU6OTdYPumolVIi53O9ezCzzxbPUe3K1FUpsH5AEGok1gA05zGbAunK075Hxb/LeeTS3prAN2mGl21jTCdQWPSPjHURLvWvPkDyl0QT3YmIiT8pF7ty+OZBPyTYdi23Z3NPvMoQaxpAtgntgwRLA9h3es6H/BU0kXUbUG0OEvgo0w6o/NwfuiinrpA2N11I9BKOfWHK59WVYs7HFtZtj23cfVHcKzkQ5c5g9s+4btuuG6XT2JjpWUBtezskdv5b8pGz05UVm1H84d13daKs4mZz2UEqzQa1QWinhVYkDFBXpK7GcP8nsQ4LptiSIi0n0PlvUw0InaCOlO/qANaDsQvXhdNDE9g3TqiEBzrIKpbwwDMoMz/1/+UrGPANfLDjRqArllQzOIzwWRKCT5Pn4373iw3gq/Sb0mrt14dWvo1jCWjr6HzgoEB7Rw/mZJylG2RTIaYGXuSNO5h6WsbeWvVV9kYlrQQ/CwhfCwQJZbzb68U5an3hj0U9YLUhLn7tkop88O0+oPef6A718weChva+JlONPD8Z+wyQmZ7Hutoaet4s8xgEH+2T0Zd2wbkl54v9gbGXw35XW4RvCMKbNidVo4yCZE9GFdubS+fobDCXXeDvvZ/4Yzc6LzHE4//lwmzQStjzF8hqOvgjAZJ7Tgk7PyZile2mb1KMsagQ1j0lXA7OaOr/p86OXFKM7ga8ydyBz7vRuePg3q9cBNsdUKDc3zi7YZzlleeuqcp/ukHhQ9LFuiH8SYVSZMd0Bi6qgV2eH882t7gA2IFiih27seNAPAUVWuJVBex6fW0ZrLjG5A9BP3gLulrD76Dub6O11MGExVS5ntuoTM98bEKH6XwfMMsNc1EhyCZ7GHMW2f+pmThOUchh4RpB0BVqPu0kSQ1SrcyDO5sqH3qYO1ooN97wi7LQMqVQ8s5yifNRATEoEueNHYMXa9ceLe0FVcs1bew/W4uNf5OCR0HRxLt4xYqGvGs8Rvss1OKHPzijiUTp7vdzBAjvLgpaB/2m3CMd2WNSL723ONm1wgHRgYWfGpw+i4sqSJOu5DcgZPyMplshIlikEkYMFa0pzCYHuEvKevMLRJwO2jrDK3CGbxDGUyCTzINtDQpQMy3A/VZiJk8OBSHpByr0HcXxRr9W0uifDZo+L3OOMuj0KfLCsMg7dx6qzw3/eRtN1box5g0/dCXtTYFiT3nk4+7Wxc8h5S+H6s5Tn5EGawsVOntPQbmdF2KPlGwbrVLEydg98o/jif+uJrBkA/G9obgfQ3mSDy/Pdf8nubP79z3NNVEDM/nxWAyBuSteX2C94VNvvy7q3//NPnu3u5yqB/9ngS4AdeonKbqiecdYb4/o/c+ZUdK96B4/uoRgfcz9oN3kLS2IJMP3vgXDxxqEvnWGKu5r4wAGjAI4DnP6KDvHQUP2e1O+LfSp1kl0nvZoYVROv0AXoChACNa7RQj9rLmhkAiAc6vdnEVPc3lDm2ohFxIJF8nJ4LsoF9/4znL4bL+7doIlg/vHe0uo9f8OYv7/Hlv7x39Ii5T97qA1j5u9ANw9eyfHjn6/TLZz7PnHPJMd6IAHR4cWhOL36HdgrBOW3OdDHAe6UrHIIcmHw5bbNYE8xK9Mhr8++LbgEPmA8TiDqyo1fx+Xz4d5Eo5TTX6MdTJg3uQwEduTDx/6SdIsenruo0vpQi1SaGfTQsY7CAbgl37kl/VKgtWMyRglrr6DKwg2hCIVUM9NHU3SopR6O4BdSHpPl8dQGsuZwwuJ6y//3Je4ib4nH38V924Ctbiz795y9oQ3H9m8I+sL17QQAV+i9Mo82SAUTunHOihLTP5YfSd8tVcSQaymYRQX/3A/bPv6G9e4Plh1d4/voNS18wnp6wIXRZrzYzJjUr6eFCG22oC45G2wfwGGWsVwzmRZoNf0wwiP/Lj38pgH7O3HxpVtIRkK9jQ/yJM5QOEXfeHAXYsdI1nR5/4PizRunOOjn0JTLCXYbCVsyd4+/KB8tPvmQtMkM/2mTY5dQptG6vWd+n4lcE0R+fnXmNVGb+gd+9dMjxf3/omvcyyeI5Dlf5Rx/uheuHEncwxMq1JcZ/1gMpTMMYCaVvigvebblvoHmfQA8ACCSz621XyCJoUOi20QCIoAnQFq+UExNEz1B34rqjK6HqCOvnAYSZoe3tmSIAc+obVgigFeGieEa4TqO/S55elPo0CmjgGSwdV2aGzb7yc9BRVqbThIq7ZY8z7+PHHujmwUPVyOo32DeFPM4KWsAgjwJ8Oy7WYW+cltmfQ5LvxOfTbzEdsfW31SFQ93x8l2M60ekh0cOO+/V4kDIDtv+kvs93hi7T2Th59JKfTVr2X7WLw7ifd6SvC6ZBjkkSAGYVisW+mATjn5+fpVzHjAaxO1JFvOL68vCAx8dHvH71KqtCTdjH9+tvAJ6wRM9NygQJfGDU+Zs06IEED+I1M8Iw4Xh+vsdxjOUQC5lTT1Jmk4eT9fS8MucxHSu5L3K65hiSBljBujT0AchDQ9/dEA9Id+Xffd/Rtg3y/OwBfQYbRypjR+eR30u4r9nr3KjshgPbDGgvVIvnUt4ZfHkVtGcixHWaVXiTcOCGHwxevtioY8uk3SaQqNDleyOU6iTZQnPmqqQqoCoYQzAwqFQ3jKFY18UTjEQgmfzgI4/MVs4OAE88MoNbVOwj2NeOffPnzIo8aej865UAo8x3Y3VFP1SIzaBbfe5JvzWTe06+HN8WuCmJaSgoGY3m0dF4Qga68p68ZgTPw0jMxJu4trojTCOQOWal+T4GrvtG57YdnJziRFcMEk/m6gGfSt7rMK3R43pgG54cEoq8+SAPyQM+cLZPUHey6z48AcpmW4/W52+6NCydyCwrE9oAp4mQh1Ks33Bw2QxEZ4+zIu/FzB16OvuXupNSMyA82EsqKA8QwnH7+0COac2dhIKyBqxQC3jLoI+AqlMdsN1v6mgVjoDRWvMeWRFAEa+MDxhSp/OB3hphzec+9sAN5yFkc6McoIyGePA8EDrUVq4/naINhFpbsrJ+jB3PV/EK42XFelm8Ym9ZvE+6Djxfr9ieN1y3Z1yfr+lIV91PLQE4tjGDQwKgiUK1YTR3vsveE5a+rwvaZWXOYNA85r4L2i2y2iv63bBd15X7thW5EsgAvt6uu3BxJOSAwtDnnEYShUQykfeOtW4wbdDGee2AmfPmWtnh+qdfJwIyLeSJhAuCjgMJGVP0IcxtdD5qQHzqOfU78hEEv5i/jbFFdnv9PGSBkdbMDNb7tI94bU/g6VNH/R3jwWlBAWuZUIZw/CRVSDDKfI4ZgCzXCXp3b0s6smPfWQbu6cRQokMoLxNVfmFXSNHYBJBobXJ8gjuvfvexT2edlM3Dd5bPHO9NBSquX7fRk68HOoUnnnSiLHDcDbA+sHRPSurbgtbdieTJMEInvtc+RPIYjF4vOo6GhR7LEHTROe8+cyoZSISF29m6fewaXAxbziwcjJbJmZGQdPh5DuTOTjnoSXXt5IhSJOfXcvqdHP5fv3LEG4s3lIOxp/yzqeu5M65JP+irwddCviirqA3z2e10ayn/m/aDX9MsKXvOb35+Wouyz+a1ww716qH6LyDckU5ql087UQ4iIdAS1tdSZgu8mlSoBwWqQaMeY0NZ3dmoMgqRKnTyM441enCC89OsoZtlwF1EAF479S+4fmo28lozeMvA4whI6t0DT2MG1WHGPRFyZMq2nPusJ8Lh+rkOQSpVLsKoO9DBmvQSa2cHG74SQegALVqOUP/pbD8X9tjdo8qK03G2s87B8/i7j6g6jwSlgVmqWHTYuKbwb8jisGsMOAaUT+OSw7TmjL50HHVqPZzqW+UU6DzbxfX8g502g6nH353WuZzbIwG5nmFATaytYw4dc+iYJa+UixaGRE6I76rKyDTt2Wl/xTAzWQOTxsIWmMGW8gxCvoVZmerjoe+o8G7XcjTXeUQJiBQbM+kZB1FYEx3k9QPG16d8npjNDuDx7Q8wAJ8/feH5cZla7lGvaYmIEL1/vQLQEL2ZmjiUu46RQYt5+PxakWbVVM6zQpe6R5J8zuNvysPL/KxQJKea614u57awP7+0N7CPXyBvBL2/QSKhncq6bqn0949CQXPEFvP+xu2p9Cecfnv2bVQ+eHr9j4zpj435+P78PTCh3M9B8vrd984590bfhAFkfjJ+EchfPgL2Y/Jhs6AjiU5Qp53r0PRPldfVv3J8nsOzhY5cP8qvXhAAZljNA5B+Me6k4gQT7ltfp9hpKHwCqG1gfk8XLiri4TUAjC+G5e0PWHpPm/rSGp4F+Pb3j5l8dwhkF5XG6dNldRa/lSDs9Nvk4x/GfOSqgvWnd5CfP0YDjjzhrMmfae57z95Pn03dLNjj1CEn/7N57+C14uxrh0KwQ1oHRoMFJCfAyu7g9i6HGpOhvAJ9n4nrIjNQj/D5aNFXpj4e9lVzvF4IOqQN7PvAvgz0MU7tlJA+tdY88bE32voZD4nELClzW8u/eI3gNwAgDb15okeDJ7l3kYm4Jg3tLwL56HMhMGwsXlqH21TrT++x/ed/YbfhCSMnlqXU+VTVe6lzH5gp3lqeNJk75ydp2yxpRPULuryDCTxYXmiww9d/ff0K169PBxoZ+8ASqKdVxvFFxEFsHHnu7Ctvif77Ii/4f+D49/VALw5Yz/Rvf8rEpSJMLSEdhQAeMLOnpkE3f/dHxGRlqnmcue13jteU4rvgwPgBJ6bnX39NTpcKnxGGBUDDW6h9znupKh4fH/Hb3/4T7/7X/4cdv5VBcbNTcJaPC5MNyp4M4Py8QFRCT0lwYBtWGbzx2/kLAdDef39tDwHYckzo2JaGmJ9W/85euzdGlRXD5OCgOz73WRE+CNt6WhzEbFkuK8yAfbvePhQnJwUPbpW4uEeThmHDIV09rSzHKCvIwNnDuXmvI+ftTrcORy3YrhugBlHAhkAV2MbOoJEBCytB1NDW7v07RQAG0nv3oISYoF86ZDi0VWseLGqtsw+GQ4VKJn04QY2vhv56VlS3V16BOL5tnIsHzu0Tnz3oaSqqGQgMY53TPQK+OpUFP8eVFRoHUIAQtKoBhxnG8w4V8PVGBzohdKzSvsPLKR6heIrBzXEVQhnf3Hmxvl6gpnj6bY4/DLBD0kvubQowC2PH0lFjYE9zA5U0Os4DklcNO7ySpfdGHlc1tEKCN/yoqmLzyx77C8HKFp/3y/z04MTWUE6l7Jx5gu7OFNoq5Zr18PPDuLz/bd26vIu5EaoGNFWALQQeHi744fUrvH33HuuyYCE6QiA7jDFY3ejK6RgeFG9E7vAexqwMoWI8hrc7UCZjgMEPgaDdMapqRt1hxsMoD9g+M4CVnVE94hVcUaUzuaz3ZT85V7hn5z8UBuMT19CA3tCb082sVLN0gl23De35GQLLqnQbHjAboQSeqvJzrRg8Dweq8pzg0dLawVDPjNEe60hEkqWXPQ+EId5694C+CBXgQt8AkE5AgQQUZBPovqdSCOmQhMk0D563KW/9epOOXYGMjE4DmTCh2QWt+7UWuKLdpbGfZVTYB0S44XJ55fs4ECt61JaXihM+0JxTV9Z77ym3KQEYtGsZvGslCDzhbzklo+gyB9lcd1QwHptGz4v6S1F4MYPiUV0+aXDymzDCgeO+UCtVwdueMNVZLZRoIHEvwFo7Iu9IlVWdQWtfs932rDDbxj5RF2oAPXXO4xMmbFXCfHtGtPTOXuYTdnRhz+mAcUcYw7EucqwsC36fLqPemebug/JemNRbY48yEc6GJnLE2PbsQ1uTfiITO2FS0dAa+1aeeXdxHDkv8cCDKltYFPjTbdsJf+/O/0jcyqxn2SkLFGZ9ymdjoIW9DwPNQg0+ViYvBd/b9+HB8e60vLJiXq30qiUxmxmTCOAIGgIsy4p9W9HFDT8TVtFfN1yvz3h+uuL5+cl7n0bgXF0nsH0/VPYJK/tiO2WAgygrkaxzeXjEY+9eLkAenPsQVaLFnCF5trcRuWBZ1zwrAo/ADKKnLkHamegSrucEXzaLUiDepwFjMLgkkzd7BVXD7J2JDCAIPHHIYewdPUFUPNgZOJBlv0joOE5IJ11jSvwqnmaidNErbrQDObytVXr1nKjOTPtJFZYVjTjwJl/C+TrZYxgw5blgknxIc7pD/rCdwR0+GbyxHnWfxfUD/SEc4iINCoUNTwCKStOYikyMMGQVXgOT1A5qXFUSbsd397hjj5y/lvoGFQFlPqOpV3lEwupg9cQYg8+qGbwUEWDpaOyBvi4rxrJjXxY/D0CXkOmYCCuhk6TSPJNAQrQ5D/VRVqUlk0Uo7DLBIWUUT03iCNq1rHj0eaduaNUhO6/NKbqlVzNPOCYKR1u8vQDGQCSaVjsRh1Hc+yx2IN8HPfNNoEIYDDaIVhFFiM6cQavDZb+a95hWgTYA0a/ezB2HB33THYHWhifqcA81ELliWmj5QBEwnw96tkCQ+qm/1skrJBexsCDJ1hetRXJGOD97IpkYLNE8WtuzwinXPGw6GdPGgNCZGfzAXF8YAlCmmhpsYTCcyDygDSWtYR+EimYUojWFtO5zTAeto+0xAZ5zdbAVCh9M9CmOWXXyiVmRbsWe0KPOX7TN6ulye2gGKidfrAHM2cop9ljo+3HOtFimrpePEfdlEmKnjA8dMqpp48xMPCxtPW4SiE5HjEMj6WwUPkRUD0+gj8r5ggyDSdfxXfybyEfHQDrKcONwVKc7AeebwVpWmudlyv3/6HGwQJOW+c2Z/dwkWuH0HN6eANUOkBnY8K8UrS1+feaeLG31irrduxd7Gz/ay2bejsCCU027oFoUCDrje7+nJ4lqcgmHS9cnPfBjwyPk8Rm7vTryXLNMHKo2SSzf8/UKiOdnezFIHUvYCXCH/3nSBF54glINX/SJ5+sXrJc3ePPuDT5//HSY7rhaIID6NYDrHugrTgvRtz0Sd3rMrbiLXksSLUKHMWRCtOrcq37RlrJx2j6hlBWaNpnfp65Wyfwe/Vvy5vT/iiAqwc2+QN4CIm8QGsX1518ARSJrbfgjR3Ktm89ipMsHAeQN26rFGeYywtzOqHr4vXvc6pp//HjkT5946Xi+c1DynDZ3byTx2bnS/Pd7pE8FN4LowfNVAr3HP9t/Fix/+QjRt9O2i1EVGf3qp3d4/vgJ4e7N55Bk1Terc8+fcG8FcTpNDLjwnGsdk4Wv13u7ew6OI8p28vNAFgr7uHMtNyJH7ORvC++58frZOuNss8RWgGAFMJaO56crHi6OmBZINj/89CPMPOn81brgt7/+AmnA+uO7o6wRD2w2QfojzcJPZHj8y3uMnz8l3RAkbPJhox1oQP/wFiLA4398wLe//eJncLxRaZ9rcZr3eLT4PMDTo+DtB27z3yTEvk13Uf6lLmEzhypamwnH6NDi3Ivq7QbbmDy5NaVvxgOoS+vokZyomr6YKv8TcZI0EX+VdggiiK6CLgyeA2htYGsDfR9obUDoH/Sfh7wG12baKlkMwoKc9wA++W7CpHxL/T9aDficuA/puS94A2Bx6ynRJ/efP8MeX2EwOr2Y9zJ/VsVVB34Yiqtu2HRgV8NiBvkQKF4uk/exA0OBoRAz/ADDJxh+YIK2iaEbPCH7R+qqmMlmEUB3lBCgvTfSv6D98NrXvjVGBMB2vzHtE9kk9okBRFhlwUXSfoNhJC+q8Z4QYXnd49v/Z44/L4BemE8qd0UwCSQ5lAhwBrL6s44qC5/vjZHjizHdhkX+5OOOUBHAFZ+qD9W/cj7/LQwO9dELBNi3r7+h/dgwPuk/QH33lYjb71+44J82XS+J1tvj986otlhd29szBHdO/UOHiMBKVsJNJrLN8+pvkEomIENg3HHS4NoWhcSEcPXftCZYl5WBclaxhcFOYZJGtJobQwDw7EG5tlCB3g1bM6wMzEr0gTVg6R2tLXwvaCoAK9AjaBFQqgG/FkfY0AJgfAXwyitJJBwU1mBywblnd8zf0fYxdNNDRrErDbPCIxyMZm5qhQO30egdY1afR0XioHM/HQ6EEG4PoTL+b+rebMuNZNcS3IA5GRGacjpV1f//b/1Q694cJKWGoLsZ+gHYMBjJkDLPyVqrddq95AAAIABJREFUy3Mpg3T6YCOwMZONhIL79Ybx6ZqYM2tEPTPnt66j+Xn2z+W0mfpGJOpvMkIQdccxuooykuUV+ZwQaLimrhWDuPNUMnke203k+Zb9gQjsAsgmyx4yCOwylnTRtnz6zi6NSypIvXewn8utXAPqRhg6lpzPZzw9PuJ8PmM7bRhHh6nish94uDynog2gwdOdD0bvMM8llABA4j19dPRjD6FLvSaqCgw6o4cRAPdKgPf21whnuFAPN/RSFqVgDxtRV5frZSqkrwdlKgwlI7tUJ8jMxTfgTga2zg4V+NY7jrZBQ4Hiqa4CeKGCnKnKuNIxw+twMzIV+EsCaLnkpelfaWe9OnADF1CcmoYYR/lptEFt8Ettm8oWB+wR8ZAp9BQthDBIOGw1gzv+WToMCHMSwkH3GEfiG0Bg1nEcQXtkhDECEGgqv20MaGshtEyMNKO9ZSoWIzKv7pNUl9YxfkGRd6ux9+hVnp8R7+YR8FKM5+FEQKAMAEdE9qp4hgLOgwtElpHhx77jcrlgP6Iu5eEKocx6EkZKpg9csGOkT2UaVdYc97TwCNofqbp6xyiLNRV5HCCzdM5N+j0Kf4gaUUOcHxoGJCJAPMpbIxOBINK4TOVMdHwK0AYqsgCkcw/ghrHeeyicPEJ/9IH98LTjx3G48TwM23SwqoKfwNODp2NFtiN2iy+S6L/ldtBIbT36gd2YrYXR7kfZz5J8iv2x8OymUXg0hfbhRpi4jqnbmUVj1tkOR5SmaG3zf1ukxkUoNbpfPGto7rDRse++/nRr0M35gIiXu+hHZNLoHfvzjn2/4HK54HJ59nSjtYxPrGdPrxv4KVKmc7Toy8jZcn/fBt0mDc89mfuVRg2Og9PJakBXnXuDmzVLXRjK82bpHMf7vt6ouKBrDhvjMNPpknM0N/IMuDe8JwwJXMV9JpGitA+IuNFTxwgFma/7haCkwvs/P6bL2EqjFqc5uWdEr89AjgKzfzieQUY+amtovcGKkw7vYZp+haKjuxNFfV9kAVBp0JNe8a9i5KnPvdNe9nQU/Drs8PVXSwkVWh4XLrR6RaBYv9n1b7eHvPD/9Yo7dBPIcYWUPidbNrhzHelS0EHlug/ll0XGCUYNtw2ndvh6FTeytW1mwyI2JZ3G6K6Y6VzwsecSoMS+YGPL+NVpYfNvp+rqRFzgskY8RzDrc49JU9fnr+vo1hzDG9bIo8RWd2bm+uTyNb4YkHNADEeDePKlxJpePka6YGwDap6OPBeSuNMEtMFaxjphE8GwSBKEgT7M5a8x25O8P/kF2wFUz+LErOJ0eCpIAf6EYcVRMPhaYI8sZULDGULRJ4LWemZSUxuQ7o4LzlM6MluSEikqqA5VAZgSQreT8zLxzCR2ACxrMyCgs6YdwGgbxhbZE3LdH+gpQ7cszyNJg0MOE78vM9RwHABYKKRhM8OapVwb/e8jajOTZxaCIOR/HC/Ma/iibxCP5OP8TJn0at2uR+F7QQ8yAv0GlwZN0cCO9+hqaeBiNB6z9nlmwQjj+WAJLGObJ44hpq3Pq8bzrDWf95bWVprsefqXYfg7XJJtud3zc3z/E+PeS4dnz3E6fP2e1WHAnVPiY9IS38aul2L0OWVjM3OZORz8NPbn7KUsy2euxPWvlf/KqDgv/TIgr+KbFKOOlWfaXLuqLucuTvBmQOQWZpaY2iYqZ68zZtSDOh18Ab58+YjHd2/QDOhy1XLK1Ms4z/H0Cx27WbneMV9JIV8GLtfbWFqdMq3GUK+lAo0E4Loj6WB1bQV1Ok39hORogOO7NIi/v4Egsm7Z1Z5Znv5Xj9s7qrO+jT8h8rq0OUZTHMeMGOuU9yp/vvrMr9dvZA+uDeZ/9eCoWvn80iMELxvN19mpLZvHl5gLpnSnyo5os/8G6E9/Bj/lMnyLzI4jgOEjHn58h6/v3e7AKPQXyL0fdzolV3/vtljIx70tO5ABTklTbm/wUofGnSPO58wW+X9GotdGvtSHzGvkov2bJ+DrBQLXCzIDZg2sMjPsRw+8AlA/yT3shv0/AX3r5XwsHHJBnmxoP7/D+PV9BlOxhbT0bD++zWYev77HATpoRCBLdK06AY4XFhd/V7jxr1+NiIHYn5nAmEVs/s1RKthy4YA2XIwPHQ3pgAeuNagN5iX3eYwsU8MMRwQLOPkihnDZdpk+Yp2g3RL1EFufjq6qhztX7i0dKbOUV85NgTIFf0xnTsGfGk5Xs4cp/gDFkB73b62h6YZdBU/m0nvThqYNvQmgbsuBKiMM0OP5u7mOQX40jP8OnW3MB523jsCynsTGucYTDCdzR98Wv8kvAMbrKF83Z7nHWuE7iY+ITxFjz72nVec/XB9G/KRpxwqdSozLSN3wzBDAeSMlJK9bdJL/lx3/TA30FP6/fY0r/Fz0GVqkrr9w/G2me0PIZeFc9w17vPEOw5475i8fr8xrZ/6phtcj4WNuuGvCdc1gHbN8XLojKjj6jvOPPwEwjN8H9EcB3q/dTqKQH9bflzcbUuCVq77LeAMAGOKR7nLV8Gs3iPEhIg1/cBI/a53fY6W1oVg+uFEDWadluUYIHF/efFPRXE2HZB3FwDk1mssxFS0BeAOo7pd9+X3pQ3605b2cczRM44fBFQRRJ80769efHx4inWM2Mutd6OaR5+PYSx+DDgGQB4UeLuRopF1tDdhCabUxTQm8xqvK5ilrm0A2poIViHja4tZaAgffQtWYC8iTuKfn1wOAYHvc0Jphe+Ok5fgUEZnwSHTX0wgEnwEga3/vQawl6qQcAfY9BZ5FNI5NQ2AwlucxcER69uM4subdwfN2AsxreA07wYbXmCXbM5A5Egw8QO2r6+lsCi5SwBqrwLiweQLwvACfAsmR6W8CnAsYJUileKlfR/kFyJR/hznEofNCRibwDcvanZ+55hi3u+GEHbvXDgJBxqnMp0IeXOhprz0tsTP41Zi7ivsW3ubz1Nj9RHvIBgYdu6YUs531b/ZA5hnKiJmKH75vWxjRz+cTzg+PWQP54XzC8fjkHuwhFPTRY5t7Dd0+aCiyBE0wVwoe4U0nqtBxVbuvNHxRsHAciMi4ZuMdjMickSMjHCqkrGfM2uaVp4pHaDf12qFegltnu9ky8xSUIK8pY26twbYN+757vyJiR2OODTMKs85NKqHGurY8AEdmqvkAYawBq0uk9sQIVIgeF8/godpgFrVjA3Sbijvg2Hzf/GBAB0w6ulU6b6GIBaiIu8ftkvZaaXcY03r3lLpmvj+6eho9Ecn03XyKiqbSEgCen58nGBSFaQPE8OnDBwfxpw1qii49jNF0erNUuDIKPY3mKEZQ8m+Z9HfSpAGWh3GaEmMCSSN9KvrMAAuTU7Aobbq8j0peSPXGrU5VSTUwLl4724OIJgCnMvLoXuv82Hfs8Y+1ckUEDw8PmS6dKT5Lc338Y72qYI0oC4Vyt0gfXNeLkobqsgxqVhM6ndGr3jhU3dBxRApsQ0NE5alnYaGw4e7VksaiHPvh0WYj0tB59IpMuGKIsTiixEKkuN+PTD967IefM09JmqVJmMkBWuZqrhcKQQZSBe6PKRim0Bh0xyPRR9Sl35O21rT8/gyNdKhIT2MVT9Gmsf9Z1oAlVSAzm44GnthOTrPdoObOSWMMr0E/3GHAo1ndOSDn1gxPb17hUR/hwe/uQGF24OvlK479QD8OHLuvt+M4ki6dthOkKU7bBgVwwOl/j7S9pAmD41KcmES87vgRUUAUMVHWu5mPh4mls5rEQnQSO7y/ojlGHZ79Y9LduQe8ZMHcd740w0g/4M5kIN2b8+M19AywhtNJcBysfR5rMRUSyPTvvXv7dAyPEOgvS1v/lqibAMF53SANi7mR6zpVLz1GJGlzfbTjqilIaGQK2caG0QaOcUBYKw4AMPGjDU+1HOx/HqFcaeqGtIlTZNlzdISu9+ZbCHgNmSGNUXKdEemwTJ3pU+Q0eFz1s2YnwHJ+js13Bu+F83UgK76R3OfT4Of9Hoss4M5PrFneIhqYxrJ0wBoCowzSNvTTgTFO2YHWtlj7EV2sc9lQec8x9aZK8GavVUi8Q0HdwNS1oX6K/veKR0jw5wDkp1FSbTsPKu9PhS4BO1VcV0+y2aZx9KlMQomWMxrSLR9gwJLFan4s8sRCh+Z1ixByPeVmTqOM2b46cITBS+Z4qxMHmIU8gA0CCZ4OL5dhCsgI+cB5nhG/BS6rtYv99YFZWUYmcA6MMrllpox7R9UzWTzXIsNN1wPbtsU6jWxBGa3u69TgUdyZ9ab7q1QUCq/VDWjIoBryeYeqokOgGvJ6aKenYpF9ngb0JWWnzlShIghZTrJPIgITXWhI3a5TBxGGczqmhRyxyBWcZ7PcJz6dsbZJj0KWhdWxvKYtluuJgUe+rFYZ8HaegjQqHea2/JzPK7iEWZbqPr3ue95XUnu743zHvu/haLhHdqNjZuyhH1gIqhPjRiuSD0y5jNjl3phQrqCjIHE86U9KXIUIVDlxMQUFnh12O4Y3Btvrry/qL9djlbpj3kTCiakVemE53/NURCHCMl0r+yLt5CURzLEP8wTSidACx0/HtEm3qFOw8o8nXDsxlvPEZ64n+eLv+fQJBoO+ehXrOFdUrutoAMwMD+cHHMcBG91LDhEnX6/5WBvdgsdokmzgSWBfbG1bfHr64S0+/PEh+0GdDkU3Gqrk8xfg8RHUPY1PnyFPj7F2LFMM5/qK/aAMmgkcUGX1Mao+iEYhygOzBvvsyOR1k/BjjhnPJ0+Sch977b9paJiY8cDgmgluMqYZPhARj/jese73echyks5szAzTRJe5rAawlH3FuYDBsv7v8tqXXg3goZysxvNrVsXfnmIJ6tXvNyz5zrvuXXf//L2r5rkv4jYIgxvLyBsUgvF7GaufBMBHCH7A079+xP7re1x+Nwg+JAZSFbyG4Ctebtu3Dq6eipGW32OqTkGxjmjrBqRuDAiZpfI5kVjrjgHpVMZ39Og/834xE4TJ1czYFaZSoH/+ij2WnZcoMjw8PQHg/hM8quLjf/2Kh5/fOrmhvBb7dP/1A7oAzd4Dv7xDMy81uTU6kyl67zj98gMAw2nb8Pl//4bTzz94ttEx166I4PS/fnF5/ehoIhi//ZH0Juczd/88pubKjxNYEMrSIF/JQDpj1ueSXopk5Dn1YxPjBd9QA8bh49HnfIm507Jb2MMBf0xnyKNHCvfss2dUq2Qq54tzTVw9gCMcQQ0D2Il/Jr4YZrMcSadTImne5OHupBkOlaBMIeHkUWQFi38h323qpf5Om5ef2wV46MDX1tB1wxtV7K3hHPLSEEbrdzQ4zR9mOH51bO2c8J3/FWA/Ltj/63d3vraRjhDUXagBGID+/Dp4teDyx++eedgm75Jo+3S0sGUB6BbJ8Kl/E8XDeQsM6kEr5C+CXvaPhIw1ZaLpip+x6Pi/7Xipxf94CvfrbZcCYirjCoj9t0jxXz1WhutnbiPOb696+ezN8Y1LXpffXhnhEtNxSKar4tvW5BDAaVncc23vvx44/8sVOv13Q5cP0D/elWd9j8VejYHdfChXvr4595cPGhP+/o34ayx6MkkqexDrypJCXN/zAvsuIOs7r5sCXlF41PNWQK/D2OJBPwClzGJIRbeegbEDooItI9osFe8pyAYxpwnULBTZUaxDDMDz8HSxwQSGIBXXp83rdzKdSGP6OwjaSUNJJNOIjvCeD2GrqabSnMYUARIlKgT21SCvou/aoK/hDO5TRHPgCyCPMYSWfyl8eRT69FoahqixapmmztNF+j1pKKcBPYwzx3DDQxqqxxbPfciI9KYCaRF9rQoZHe1VQ//04OkJ8ezt+mqQp7pmpiKX/6Zutig+Q0iXrL9mc0Us8kill0VmyedLrjEKh04zrtespIGmrnR3EnPj+VTuO0wVnCCPmuDhdDpfKaqncFQ6dXO8uGvl+9dUpYlwEJJ+TDNQGpmNhgQqlSeQE7iw2bYGGRYRiG4Q6ZHlwaK2cHIr6TBpmeL/uIinwVRxw11EAqLs61SKlCkQdjJqOktt81iVKFR8IRSOBBwIgJJ/Q0nvYT4BNEWwMW20lPeKRlQb9870IPU2MEvDLGVQhY1BLpXKOUtQRAMAn+dq6xgNwxybolCuh119Et5XAJUbjsNzvQNLWssk6nCvtBFANsmx5fXVsej2uGUMCcTLvJoBTUamuT6ODm0HmKrbKFTZiCQWjE4VLzUQ4XC9M0X8gGxcp3OP+0iWmsgoGRHKXqeB3BVFMpX45kA/dytxwJ0ah+w3I76YWfva2aB6WA8AMiycHsOhxqbh0CN/Dk/9jDnzVELO+uSh2KzKjMpbtjVCycZMTzprfOvKqgNXqihMw4gbpV0gtwb0EVHmUGGAKchPUVa0K041MkF4FgFeCXoyK4BMTVqi0OFrh+9y4y/52ZyH/bJjf352o6x1HPuAHUfyNo8E97WlocUzATTKKJBew+gk5O/uvdBS4ovE3nNttKGhiIMbq6mc7yOwekeWEImhBmkHlXRGLB8iu8zdnBRAJLLeNC+1cTrhfNpwOp3SuOGOKGMxvpA2pJBLxfYRjlB9YEBy/T0/f8XleffU98fh5Vt6pKLXBlV3Iuxb1JYcBhmRZtqBVAjhlkqC5EEiU+FadpTI3G+c1zrm9TyNJmn06ZExIeiwwLC1BmOWhYigjJVb6LT4/iMqKHDU8rsTmAxwFo1U9RZ9QdCcoEf0PF/+GZCG+ZDjlnd8Q/whTi30Z7n2CghMEaTiIMtTAjeoGsxpa9w+1zPnQxKXNm2wZhhbQ7cTAAsVW8fobvyjgpsyah1PhhyokhKXuecYlXfX5mf3rP6WAHF+FoEM4vngtXJ7z13j+HfElXrIzef7GC7ZwF35SUB3TI6EAKU2snFSQFk/285zCKNaa2FIH8Gz1bFpidINAhf8z9etOxVEFIlR3bnWlB4xZ06rnY6k82ncn5Ci9k6Q650Tmfz3jnw44T5bwWvrFdWwXuafZws+i+Yue0vm/67khfgjMTalvjPxWl7LdZ3NotI5PsNyLN0owYmnIVihZl7WZHjWHG3OM6QroN1TSQplIHHsM0ZJ8euHAkAak3XSnRir0Uc4rwb+oHN5thWA+nXuKCW4QNKwLCHn9qPUwA5eMoIv94LvvISWwdTZug3FkO5tF0Csw8tf0Ggrye9EgEHPO0hkQqvlJGRikHAIYfrymeWH6yoM6hmRXmZM1v7nfov+eD9mOve81mxdMsW5MudkzLV4Tzd2fdxXkdynJam0prMWnXWJtbk2hDjlan/5pC3fyTtjq4XDX5H5axR6OAQuMk5gaL7f3zt568T+fNfapnSSrO3spHvIvk3nHKBSmWlkmHTdcass56/Tved+v+KPVEYTh62zckWD/abk3yoNugSnjKQJ1RFVZr5zxxFwJ2MZ8AwVOY++GF2GJG52WcNpY8y51/6ADfK8Mnb5VyYpfhTg61S7M0rVnUWcK9vIkch+ihRKG/ve12NkbLREbPO5dAaKe6xcwewQ1ZjHpuPpCWbAmx/eLincOXXLPjTAPn+FhCFOnh7yCjOWntCQe2K/jpF6N58GnXvcZpCSOzZs8dK+0hHDuoFjSujoUzHJcrD0T942nyEgrwdgE6uSnvjj5GbM/r2jYA5gBoYZsOJMzhm7Q9xgOWbA7V7KpVPf+AL+yprg/8Fxffvff9xfe8JnmUZ0R78AYFEp2g/93aA/UzYB2s/vcPz2YQ52sTXXtVzP1b/ZoooDv9lKL3FLQyD3+PUzUy6bJ8oet7UdhdZdY/F/76jyDPeLy07v/te/sO/7xJrh8N37RxyYdA2/foD88s4d90KfYealJj1g0GWyp//5c0ZHRxewtYaUQyGQTbL8FzCnKOuRL3wHC00HgPbLD+i/vscBwxmCA5PG1jGmzOjkw65oSswH5ah8G0D2LZHBx/WfgDaD9ShxIwcMDUqHqZJhx/mXQaRgFKk9iJfMVmMAOPqY10iH7IdnUlTPMjQsgpFC10BndraPujnBdPwnxjMRjHCQp35CYrGKzTk9tQ3n7YRta5HO3XCC65HPuuFJFQhnehezO0ZvOLTn2h/B32yEYTwzM0bQ4U8G+29L1KZw3ivDID+RVgZPwXQcYfZFOjP14MlSsUCM7eOP77Dve8hss2wygidhYx6E4EFX/EZ0jhMx211C+3/x8c/XQE/GJFf/VlD3gnb7Ww++T73zbRRT/f0PWFO4ExAThEyGLOWu+sBo932p4bsHDeLMjPb44ztcfvuAQ1w3s2H1460jdQB4+PlHmAFf/vijCEFA+7F56qrfZ9TKhAyS7+OvnOA5LVTUeL/z/fYawKcrjPUJijfZvjiJesX8NEo74GnlMSPRj/d9+X378bpKjB81Tfg8biddrq4bNpxYh0KD3t5sIz1mRNf3vgQG1n1OAn5HsL1p//0nSkdMBuu2BFh58HnYzl63o0Xt8e3kPmJH1G5q0e6+766Q1oaje/1zO2jMtRRkAmrjhBMU7v3+8HAGa/n6GoiUiVvD+RQ15SNt3qabp/gs9bZNxKPR26yF278M0GfQFTPnYKoxz1sDTDHeuifq5dMjzJ4nwDFX4GSkc6ThoYB4EPQGozsYdThGGDwNnQrp3j0a4dgw7Dm89NwgQKPrsIFmTBkc9VXKWmqtOeLsHeNLgMCnCQK3V15NZ/RpvBWcAVwWIFEhve+zODPMDWFt9QlUkah3GUCGqSrjki2u7z3SL8oU/uTmnf65AVnDsRVg4P6YAn0IZfMWTgRc40VhOBUJ8zsAbGcaEkMJePgv26nNfDfsQipICjDDi1so12GgkjJKAbIirXEqTAbrx8b6hSurOo7ov4EC/DCvizU6a84DkAazHjVJuwvc/XDDS6MyvmVbXHANgBvrVKFEEp5OyKhYnSDCl/HIkZyro/RTpsNAjrch50AEnjEi2oZYg4gUwgQzvJ+16foYGf2bSqfjyAhxr8Pt0YeLUb1Gnpc2VgM82whBOuEwEmHakVYEL1SmkWbT8NQiIt1sCsn+0liXHRjiihiZ/DsFeY6h0Ji1RvLNLwJGbhZ0t8CXMSxLQngttT2coDTW0ojxDb4V62I3gx0Xpy+tpaIn3x//6GGbWIP1GwBUmqux7lU9WkVjYNMgVrOdFJoBVIFHsAxEEUZ86hZ4m4pKKWvePb9dwcPU5N0o9EylLjDTjY6k1xHZL5ZpfWlUPZ222Guenn3EexACRJYPqe2P/dVUU0AQcYGNa2ExyMNTX4lIpE6fRmcYnYzW5w8A1ndXClJZBZ9j3Rpk1PImbY0U7lGf08I4HeljEYkHLpdnXJ6fg34d6HuPKHDnhXySRwMK3CUeGOK0rtpVSFdcsPEZHGGQVhEcIqsRXQT9AMwEw3oqkBjxInBnNMdLUsZpJL3LBjC6NOZGqRwNDwUxoKmX3DidTjidT5E15JzrWQweBYlSr9AXvyPa6Bf5vtMzjwbfLzv2Y8fXL19xeb7EWpx9atHn1jaPUGQ63N7RxR3hkyZBIM0dEseRaTyydMCCOQ10fYl9yuzSvlbSUWRZUiOcIwZ6j2w5R3eaC6edTU/Yti0UJr7vRj886pPRmYsM5XPktTvLTpZA98TAEun0zPI8r0vaWvmz0EFzXWdCWpmM7YqTC41MuDqooFh/mEbNiQ+q8ZzdVHVDlrWWP+Q6KYcII9Cdj2y2edYJGIZ09Kjl6uQtnhOd9GGYzkxJ1zlOY7Ynh+ybKGZmaiCfZMIWph9nTeJU5CfeqihgjuHs6O2pv3VI/VCxGeeiXKoco2DBVKhhGibnvTReT4eahHHBq1TF5YJxyndvNKrWdvCFyztuu2FgnT6BmGd6kK1FSYdnN5S2apycvLjWjQYC24Uyk9jhRnFY389mBt+bnDQOC17K5+R5H5TF4Ma9emdSJywh0JrnqyZBIBgyZntjX9Gge71jfBvH+gdgMmUQiPr+b5YXmxlGZBMQ6RFJ5JhcaMgyd8b01P6lNzodsk9ty8gWXrFjj30ylceLItg1sZGdRHDs/jL/7tx7ay1LxmRpl0jJzRriPWVN53mN9C1pW/DqCHygA/RiMOI6x5Td1IIbLHugp6xc/2kSkaBZaBPHkU8va6FiNWRpMxQMbsDynTekYx+mQ/+1cdhfWyNyp1NR1ZOzDbVdy9aQ+t11Hbo4GJZn3GlDygLBv9mP6iTALDyjj8xqNMbA0Xd31Mw5D0dl0lfymut35uiu567PT+cJAWUX4keIG2evjefTgDjlKt4rYM1QnjdkcdnSd47LYvTDMhll+GX5i/pH5jompln1teZOtWWuc435JEBbcy18lLNiBjJROqSJgyGD72PKakD2U0NmQsDamjY8nVsKmTbkIwFEJoz41j8NDPuSY9wyIt1lvzE6zu2Ey/Ml8RT3gsX7IJiZ1Jb55iJgsuVHKD4vxW14y350z+jB9pb9GBOy9uPrFwCGhsfQL813jz5wsR1ihtP57M8KWUIa6U51Nr23lzV5HkfRt9QVViOdKWuW9Ms4PxwntvLOhiEUMlsxwNj3fxuivHRUxGnvAfx41Z7SFxp9vEZvuEkvqYbu3PYXDqZyr7XKH2227d4biCVeOu7RoJv74991nfRvHZ9lRsTXl9RpTJwD150//PwOz799gLVJ74pab2nP944rRLd8O+LkifsIQVqE9pNirI42ugPlxP+5TGMviwEXrnSTnI9iWp0GRazbXgJH9pD/H0QhTw9QVWynLQJUZDLFeOK2bRg90pXDXJ4PG40Nt+kYAPz6Adu/3k1MECX5WnN7xX54Jtd8sgCn0ynfyX3VNi/F+py4wJZx3mK+6ePH9dgANAguv3rK4lOgxz3uezLgMyxTnRuQzgkVH+Tvwa+nqjZoE6aMANJ0GzAPx0cPPemwHv6Wlg5M5FJAZGiRcMpJ3FXmi+QVLn8r3Ome6XzS5iOS2QladzkyeU3o7RaBMxlncUiVmZ4f7FsyKdcFNJGIQN8iYLHJHBE2AAAgAElEQVS5vgheduho/u+sLqOqCfoQjN5xES+vajhmVtpI9HRcLm4LASA/D4z+BmZ/+BhhBmHhJ8DkDQSeLXD/473rC81lT9okByyrsozxJ7T9kPyAc6rbBjncCfV8OuXYuN7mwLWjMwxR7pHWQF8zTRRj9MyC9H2Hqr9KWf754+++9T82oC948bsX3/3499+J73vLbjEJ13XQv/vef2juvgTTYrKu5z8+JDFLwrRi3KUJs17Wek3/o0N/2ma9LBGY/FmueKGHedqu/sYxAOA1EKnav3/U+/+NQUsG9BePv3RptKOChPqa7zzDbj6U7wtqK2+sQqHVOZX1Up5vEsp0/54paYel4q+FFykZksAisiYIpYRQYkA/Rolwju7LXDsqHoO9bZtHnTcNz2P3KmK6S9a6MiBT5Yq4Zz29xzOFLyQIpQAStXuDkCqA8ezM6PTG0+72MBqrShgqzjB8LeNWhJmqEAhlueOniGY0V9b0iJobYxrVPeqso3fkOVF6KY+UxBwEDJhpHbacM86pPp5DuOJcxwjZ9VKaYCOSEcaIVCgQUqHMe2r/J9OeCtQbQE1hTueJWptFAJwiVTtjhZrMRSs4TdD5GHO/bVDd5rql97NMYFYVjLPlLxDzmz32PdqwOhLxGObp+31ZFYNoKFFY85aG9NNVG328Yz2l8cEycr3vh0fT9MiooB69PfrAHka70Qw6FKOZ18MOpVfWIRTJ6BTfqgIZHgl7M3dLbxFt1dthjH3HbAuE0hqRrh7FEvWgUzk/1wYjhgb7bSOjMy6XC54vF1yiHvVBA7oIhN6fASiv9Qmr8XyBjnOG70zz9dwW/VxRZtDYPlcWvfAX5bUA1ktUUnmywOA1h6eQOqMKbwk/9ZfzOQTsgDHFuQBUEnnKcQWwe+RV9me4h2sdjzJW/uSqPNWMkHTnjVkew2odXvYhInRTWAF8zSnpraEqLJLPXPGhNNZfTYyvG9LY6eaSRpx8nkyBD/NZo1NpFAbmjPoqUcOxR7Rp1i4FPG3v6XTCRuMmCRujciMt7HWbUdaFRmaIIQJY1ASPyfXSIxrreUY405mqB08YY6bmdqWmLulZhxmse71ev1+gxzFTbTNLRShrcv9GpoujHz4WfToaXJ4vkWa8R9ryDota3EybnPXhDTA1DO3pkJA6IEbSDqeJaUgP2jGYHrUqVkXckJ/WjbpLIwJp+NpO4THWiQjcWcqcnopVg9Fq6DKEATsyeLhheMuxcsFbAAw0a9i2LZQ8gq4N28kdV1QNOqI+++j4+vUrmnqWkWPfsR+RCn9QCC44MAVk8z6FAeaI+XcsMSLDKw33U+EtUMZToR6VpCReEEsj+nKtPzJTy7JeKyPnSDlUWzga+H7wpnQvbxP5e2q0uEEmm5tvmoNfD/PIK21huA0lye2lVYgmLJGMyKo0P2acd1298HuAfa45W//H5tYWudAOeCq6IuTXV0nywEhRi0buAhGgh9MP7X4Ziai+DrVNPiuYvHcwLOAvyCCrVORKaFeak+CGgTIudPlZJqZcpk/mQLzw7u+JULfQbD3jK+Z69iR/nao8/+c00Ns0RtTAtnBo7SWzgrVw3GV/4knCSPOB1gI7CdMlKuG13xNrwsoJOteKuDLQ18TM8DAMkKYzitPYcqdDiNSbsIk801B+Z/Tyiqo0K4NOXcTCNxd8coVJ6yfi/rqmOQAyVaITM8oadZ50eX28yoyEjgGeM1qVg6mdsMkzFLCsO0CHzel07hH+EX29idOl7o8aEjLWCOfGUhMR8PtUXcGo8a8VxziDO0Z56aPh7bD5hAGXdfsYkKCbdEg6Aoe01nwt7pO+jnBMc4fHPscd8NI6OrMKARVn+eJh1LLzqzVKXFWc5mMaQldHexrMSxm0+j2uaWKgMyXpruR8Aaw17bwp8OKoGXNm2112Rpbocf4X2PiKR39TNLs6SC38/SvHucH5RWbL/sYYCaRkUIr2yeQtaTwvfxNPGhJPzuxQUfJlzOjzajyfm3OOj4SBlQ5T33IokIqvmZpcHUONMcreDb1kYUuLM0Ppb66NGFfqAGzxOLk9FqP6S/MkZX6I+8gbyzWJI7Lv4iJp7Pt6XoDEhSpIo4QdHenrHjjURKDm+hUvY+TfnSQrF7e/j3heiNkKz0satvbZ6mf7Eucs7+N36pX2vqNJY2ILJ1E2PPuLuCM1KbjBMKRgY6FDYuQKe/0E+/Ql50IAjM+f0V6/goigIcoP3szb/TkzPMM+n70U4sIvZtQnF6/BPNNX8/ldnMHikwyvs6xbyD7XbyStNeqWpxFp8hHOR2Us8c6qwyryZuqsIuNXxQn28c+b8fg7R6UrDYhazwL5gX0rmVKTd05M6uXW+u2sVHl3Of0968K3I9C/de89nHHvUffa9e07Xn4f4O19jCVNZ1/DTO09fjPIL39iAGj4AU0VJwCXO+2ubfpeSzRp4/3j2lkWItGGvGLiqvj96gl5v8XfopG7R0LyrvtuFOuxvX5y/pyOQ3SSi3WeuiZF2xSjH8GjPnoIgMzYsCFRLvrXj2i/vMtgNcAyKxjd+McY6L+9x9P/86/kL054kRii0nP2qZD+u+unxa5oP73D8fsHbD/5Nfr7HI9XBnwiLa7PJ04tz865mVAmx4b0FIY0CIvAAwQCw4k4fqJeo1VnZjgWZVYk2jSq2LfCX0t5ID4AfaSuhljMlDyWa4c0cD5Xoi9qVycwWZRQfozuq7i+vWUa983p4ZCYE8XX1mBN8aheJ71Z1D93cIz+63uMH14l3fb15flwvTvvAXsDyMzE47gO0J8AyJtIre9rkrpD4Rzg9hgfDfgZidu9j4IRZTVdj2YekLjVZP88KENN7kw9vaDi4dVBs66r7wqy/z89/vkI9Fxt377ipesqy775hXXkyq8TQ/Cp/vcE98x4Zs3IENRqRN13Gnj/J9IwmQu3/vjDmF5NDfYCkQ72XnY/NyqZ2sfffl8YnNpbJ/ryAfsfAsUPuILmfl2cGQlO1y4xhQP1w5NxfYr3OBgx+QTYmsK9vqvZG94IAOjiIOn87od5tmwKRqLv7yMERBQ1TWS+oxoQkljP69jjaeCb807Ctm1b1OwqHlvNWQcV/tPIofm6bPj1uImgndz4eOyEFOtxK39dnVBAmmDbTtgvFye4UceTjHAgjL69o7UNBnOCxahVhh6HR33vM9Iqx4pjHrSMKWZBAc8E0iTqw826bD7eXgfOx9FzKLTm/0gImxRjugj0lQ/6+HrOWnLeX0X/2qGvtxwKklefkydMr68vGXlYjecjBeiBo3vk3egDx4j0fH0aWsZwQ+roHUd/dk/10fH250doa/jzvwLQ4Cv6lzP0SZf0kxwnB2GsDW1zHXCMUtjlqnNhBDCvr2SS9AE0huAcy3fP5UCRjVGS7nlY4UCM2BVaVShMXGmUq8ymKmzIgU0E7hEHSJB4fZAEXlQIbNsJum2gdOxr7JZiCWaNs+28IZU8MRYuPPszj0tEPj62JfXT9WHz4be/ma+UVF4w7SF/p+HjmHM+uu8RDQ84PtjroHNNeR/7cIWbwIGLdhrSPDLQEFkihu8/M/OMAaQ5NGLFZ3YjDUIWaZPnD2BNoaW4J+cDnoI6AbB6RacKj5n+kel0XNHvibjMDF6aONwVRSHmRsE+3Ah1HG40vzx75OteItBVY9eOAdZusvQIzUnJeavi6RS0rwmg8+vbyC1HqqLi3pf98HT5jVEqfi+NGsd+AFHfPFZcwrW5fooTQZycr72DMaReJwszn5FayPaMcN4BdvQR6fzL0Zpha7P0QQLt8C6msxFLAbBOLH/L8S7KEsQeteF1oA1U1mmkQAxDsbasOVd1HtVwXv/eGxPrI+fVgKCLWJR/lV+uwluV1txYRb40SyzMVKYcB4Sgcdq8Fva2bXN/AbEWzf+W/lIxM2xga5uXaugxxiPSNJPGqb+jjwHtkor5GhmfKbvhvDLrlcoU/mBRE3NcvBTImBF+2jS8wVsa0mlA75ERZT/2yGTQMzX92C9es7v3aXjq3bNdhI6RBgaJtthQHBFV1wf5IXeV92NErbbkJd2VxEtqZCD4PXLNc04s1sMYhoGRtcCZPt+neUbK20Jbbe7fpHE+BxyfUxhOgPlO5x8NYwtFQhecz75R98uOMbw22nF4qrsvnz/jtJ1wOp2c/odDQaZuBjCGOs2gomNMR6Jj79j7Ec88stSFxuKb2WWcT+toS+rX3D4iEeUjSYdfOkR8/2a03FEMPLGeWnMng/P5jG07hVOgoIsrNIcympH/KMivawBlN6cgDqehfTjSlKZIxxmsMhX3O40BKwnndUQc5Z5vCE75/FhvTupeiAi0eVfySZtOVbJeNNsX/KapAlYzTbmjYVfFoQI5ABxImss9Ox1hNCNEx2EeXXYFxKqT6p3OQiN93yUiYSf6nXsEWKMziScM0zGp9570DHfX2Hfk2YJT8/vKOpeA8xrVI5BMOZ01WOP/dO47hqCR1gUG33uH9gHZNMSKeEnhi6rq2QTinYqIpAjMTVI1gzNttjeF18C4OT5AE9brdkxI/CbimTKGKhhmyahxZpEQOA8wEewx/iqe+rG4zE0cGri4rkUnEbzD5tw5OIeNXu6/3UEp7/IKGqFlOYVVJp530nDuY8WJlvyeTmoibtHOUM+Y2cHozsL3DeHrKdNhKiZjbHUFyiwBwtcPzplC0aDqDrsue2hGXol5pg0vOyaZjMdprqsBJR46uhupzDTLnejRIktPOM0cjuX3IwyrFqVHONMGl2slsrMED/P9GTyk6grSMBR7OYY22GM64eZC4oiIRDYsJCah/JXZLkQAtcyOJzId61NpvKT5DrmYf7lAliLqeOGwq7/L9M/22NU15cFr+ErlN/Mef4zNfcx9YHDj5CIyTL6a9I1Gh3BuJK3uxSheSwOl8TycCOm8OfVJsS+HK9CZ2WjtGhuLLEkE+NhXuZmfvZo26dVqRCc9T7mp6DLm667ebwqTPuWIFw4q/LPJ66/L88UHdco5OT8l20fVw8l8gvBx+ZMB1iGtZdmiATitt8iOBdZAD51TH/FMSUydZZXKuls+17XxFWDqeF53fVsV/qpJVDD35bY1x7W9OGEY0HQL3KCR3Yk03Ac3ZQDAHQNUYK8e0T9/hSAyGCEcRYNr0og+W3E7Q9vjEwSG/uULYF8heOWtjzUiKBgMyFJDEytYZB6aek8ahKmbS0YaRhhpTt8hLrdkFj3MfZrLbngJp+TZBWNZiQQjP5m0lQwqSi1+/LPMyL938H7NvwL9Yf5m+BOwt4WGrXjqoMMN6XltzV9s1DMhR3x/4ruwZi/7Imt0+us7z39pLO5T2/kbd+5L9987v+xl+HqcrqG3ZFhi0xsE+vNb2IdPEHik+IsspRwKj2res7VrT7g/V/vDBHqbrfiYaypd/agHEg8eoNmuAxgi7qweGJrybsesgf4NsrpcwHkdZp4dKbIOEovYKLhcJMoi+iz13vH8hy2mDeXzoq2MgJfYYxr2iWYbenfD5favn0CZnDwGvCdOzkj6MpMC163B3K50NT/68w8u6/zrJ+z//RvaT8xWujoVVIM5eUg6FwL5W37nwAWGmOU2MA2q0W6mKKf+hQ7wBs/kN43m0SUZECiUjj/Jj0t7Y76Sn40BQcfeFNI19CBE8gUnk3YuMiX3CDG198fTpJc9ExlPpWW30YQ6Pg92em3ApyiF8lYEZ7gOD03QTNAM6BFQcPofP2FcLpl5gXYtyjTAWxieXW795S0UHpjrcsJbsGq6BCMfANowyDuBfZjIfrJfK3si6GbalpCYTMSzHrgMHrrIWBeLLO5NyVNMkW9lLnOy4Pp5XX74Z45/l9f83eMfM6BXRWsOsM1z9ETq3RWitQZWGhfSgAZcA8hbRfz9czwi0cYKtMrfOsIvs6R7/SQhR7a1NsOFahIk9ahzcUFbEUDLAgQsbZhjOL/X536E4O3aF/kIMpq/A1ASIAKLzMXf8h3lgQu+/Yvr/ZpZyYtfbo9KvvK7rPPoAHl6iPLY98PrSRI/Xo1MEvu7jY73p7BRAeTLIzy9yVfIQqZCZm7dPeAlDGAWKZPHYe7BhkiTFa/XED64RvnU/XAjejNNIDsjxRUzQhzQk0KG4rgc2J6cUTMlqYbRIP8rhkqhMlE9AUm6tFMYk6i/K64MmBzJ/wwg0yUlnTWBYUxj+RgwO6PbZx+HMT3NaUjvw6JeKNOZrgZ0GhRGGNlTsRDvHZGGxOHWY6YH5oRnKjaE8CISNesa+lGi4FHWEtsXCqiWT/PeC84T8DxRJXbOsYC9tAZv19g105urwQ+CSwd9TtLboyusuIuQ982IazdkWNKAe/ZuN9LBS9enEM4Znus+HVruEgcC3incVKUnI9yN9xOkmeEYHWoDDc1TQAoNaJ5m+Pn52Z1BIv3ztnkEyrFfIhJhoMuBy3OMXRjlCIipuLOh6EePVGkBks1go0Pb5gqX0rcZEYJSOtOgg7uUE6yxr1blmmndKyHsEYHlS6YHn0ZUXdZRFKpoaaQFMAzjQKaotDEwjgPH7lHn+77j2I/cN+SzYxgO9GI0Ku03Ci2z+TMaKxTTJq4w6TQ0cE9heoAFMZ51Lb3XAnWPeiD3bCpegUVZXkWqVTBjtKSkjoi0BKg4IQCihSORRBSdhpGx6VTaxqMtFCMjasu7cXmU9etZOnoIVBQ2AE91CgyIjTTAaGvQbVW2evqqHuBfZ6pmhMK9KVrb3LlJpwGbc6cNaQS4PpZITR+MpG95jVCgVdDQZp0ps90IzMdr29Ig6rWkFLrNbAFtGMbWM8qWZTY4c9zjuWdbc2NehipOLEiFs5a5YZ9GH7AWhvkmaGjow9BaGLtD0X2QBrA9x3S8mXX0LPdd0qbmKbcMALqn2bIxU4ZOfu/riE4AjB6mU8S+73h+fsYIgykXqFFAMc8oIkNgbYs9zogt8hin+jdKVUMaHHI92QYVRqLP6EjfCgYY68UiFdpTsep9YgaBqYA2+jFkrch+9CghMPcY1wDnWzFTt58fHvDw+IjTw0NJe68RySXoUuq4GiDaoE0gZxccW3cs8uX5GcflcFlisHSHz7XXOvesN5klxOBRi+GgcLmE0bx3z4wD5J4dEjSpeUdpzDTYVMoHkWKWgMnDYn+APHByaF+DzB5gaTw/jgP77k515A8+Lxop5wUwX1O9D+zHUebOsfsQ0g4UkCWBCaXQ1MCf2R9DyzIYjkV186isSUQpvCP7Q2UC+YKN6dyi4bAy+zIVTAHSkQ+Uie3rsRql5560+ntZb6QHQDUqKLRZOtBwOpy8joXHEjMzC8Z22rBtDTR8DRvYLx3HfriT45gphO+3HwuPlqt06Kt0UPoRcmHEtOX5LDm2yCXDcWf2H36uPH3y8hgPz8PuEcaDDi+cf0eO19CN6156RI5y3pQOgjNTh9MYg1mfPNRsZukJXJWyEJ3HBmX+mWnluh1cW54VRyGDOSGKASDoGOlgVG5yhKGa0T7NLGihR/32zvVg9YVeI7G0hfKw48I5IekgFnsrs8VcSZnV7Fi2aI7RgmeyOVNIMEM+QeDKvMV5ILftpPmyNiHbK3VDoFJ+83nJE1TgSeKwJDHaABnYemSHGE6jDnVZTFUjKjwiTw2O35vzhIeHB2wnd4DTIGbE9KN3HOqRR8zWJrCCeTxF9xCFthH4wB3LpvHb0vGRdBegQwQNUbnQwSjnjKREGTuDRzgsGLTMWfDFXN91NiVKc/F9oxph/WY6YTFTPgB0mTSVxvQ707m2vaxhiXb43K2ZrnJvGsdWUOnp1ePvn4nGJNuBAaOjR8SV9o7joD5BgA3YqroxH2Opj6r4LvsFZBYjzzYXhnLzLAM7M2kFXiHevNb5wDxAwYZBzZ3QxRTbFgbAuJcyA4CJUxJ/zr4vvEdiXwXdTcPnhJU5/uk8diVs51xxLIMGjDHc4YDN4rjnHCJpKnE9eZeELA0twRXBh6dtlFHFZX3RsS6isA3sH4AoG+b4VSIwpAE9AobUAyF09DQqUt/BSRcgFfE9ahoR91FPAyCMLGWNFHyYUcI2Z9qITwr1zd9MVpl/dMCYoTCwTZQfgojLJGN46UXx+50GafrADwCvfohAJvN1d3rzCl8+fSrztC75iWPW365XwzpwQa/r5rfr6/1a6v6umejM5kGdFdYGSH3OXF+5bktL2Jwc/3yOZBrmAde7od73bx5ilgZIsat2MvCDfFfgOhttc93GGhl/jEgHjZvBr9+m7vflw8rfOq/fur6OwbI2cX98vvfMJ/PI8nr/8pw6WbAlCp2/D3jKdAMig0oEIwQGrbuJ43zjFGKzJ8Mi66+tjgVrp71EXz2ZDqrxhzahia8waVh8ZhmTJC0BHlVlpsDGpF8Aip/QugGvbUmknf3Pz9C3r9FiKwxzPpd0PvgrZd8xOvbfPmaD1+ylpYtVV4WJGXMkJPCtAMxaBUydE4PoOIJBwRKfpD2uvhNA+/kHiLizNsxTy4/f1/1d1x1pKvd6aXTeQR9Ml68ETSY9J9+afZK0CxzH/I3ZZgfzjHMeqAeC2wlnBhuEbBXyYPKNcFwIZUWH66SOMaCRJct57ZiOcVwRwUdP2wZtgtPYXK+HGYjVzWuKa5nYJs5btk1xPp3QNEZsGKADn1TQxHUTp5AzNYL1egRtjdBPNbPYe0j9mDPGcCQEy/o1d8bo72IdTJnb1+LkASKC8TFdP+c8L3sQya8Mrs86julAOszi3OH6CdUopxPtLZNGrM3lYsQYYPp30hPLuyZtmfcuC5gznboVTJb4PUL5f/D4jw3oCZ5j8Xm0kHuHpsE4lKXD3DunyRZRdCHcRs2CjOyj8B8EkcYCJHmISalKGCEJ8YPGaY5tH7YQscV4gzlPORffmJT0OpfiJRJk5kO0+S3cc73Br2vaPPVMEGa2L98bRhsyhNmeUCrg3U0b7jXxnsfj8ns0PQlcUky/L2s3MhKdhNhe+RX6GYBhyCd/W0Sib+bG/RG1z/XdrCFXdwEVDRQk7zVXRLF/9Ijc9lOkssRMB+PXTFaRF8isFU7CSgmj9yPqf/v5EUKWZp3UazAZigaXFyISxFYOM3nZjdJnoQAGnB7OqTA6nc44jh0UgFQV2JyB9EvHaTvBOhXUoWi2aXAEgLH3WFcRPaOK7bHBdr9+E49wfHpzRlNXWLQQqs4PZ48UgGVUpDJaMmsY+Qi2bfO0KoPRveGxz+6FMNHCUjbQvc5QENH9zwF5nMa69kow/nSB36PEQxgeHRiRoj2VGT6/9E5zZciRkWQWBvNuI1ISGcReeTYEAdQUn35zD0p98pV3fGb0YAh6HM9glC5jhGHPhvdorDsy53VZvk/Qp6tNzfm6Bme5LKYS43rZzFs5/wh6s6btczWmQWSDnItiJmkjZxIpZLe2ea1pIOeRy/rWGywYsoSzxCX23yMm/RVPTyQngXYyZ99jrU2QUhXqUjppmNG1JsONacNgTdygHcL9BqShbfSOy77jy+fP2dLzgzsoXC4Hnp8vySOO3dD3AxmzPwzntsW6cyWqjUivayMNzM0Guipa7xht1mgWLd771ZXWHBb4GVeKKegoVowtvKXY1BPoy1xhxKhUgmnT9P5nCk8a1VvzMbuY1wFG7+hmHhF2+Hg8P19wHLsrGkEhJTwOU+FcAf1sHOsHsXXTjzm82ZmqO4zo1t2oswVdmArYYrwDAujRq9FpgAtHYUQYY67pHK3bY2IBi70lc1/lO3nt5IFcq00ioj8GnekfLWiLxN4TUzBDRVXs7/ue64KKUUiPlKcKNAfF28nrG9M44zVkfR26Mi6ybEQqMBEfQzf0eLrzYCnOk+iRfRVNs9IUn7d06BFEO0MpqGH02bwmoo2By7hkxOzz5TmfdzqdcNo8G0vbmqdgP22LUn6MgcuxY98PXJ6fs1SA1zCeQJ+pvDWi0LLUQnF8aMHHWtsy7TpLOJxi/bbWMtLQxkjjJPkE+ce+72m07MeBLaJEJx6fuFMMgVEbRjPIfmCPdKH7sU/hYLiTz6YePfz49ITHx0d3mxFgv1zw9csXr3W9HxnhKobkpZANenZqEaQ7J5G1wZiCFhRa4rPkWG4QGWE8t5JKn0rocEAbw41eFhHIcONTzwi32KNlPRnbYsAwd0CAWWSUo2oDblxEYFmzXB8P5wc8PDzi8eHRcUgIkafIOmDH4XugR0T+GIAYmp6xnU4QnHCMjtaar0cb6MfAEY4MIuLZCGKdcE+OcP5ww/mO/XKZznfDnTCqF/ukbj4HujVX1gefpsAIILMVMIqQNXgp4KlKOi2M4TV5RygXez+w7xcvo7F7LTENBwwLnHd68ChNCfmiW3f63SNdLZ1TmItRit4heay6t7wZuho09kgnvhrEfYpmjrPHGNj74aUyIo20qLhh3STKTkgkK3F6pSFb+di3EJILdklnkGwgKh2njDDrbAdmyYmZhonEEfG8VKJZSdkryDIn1cDBObKBlDObOO04bSc8PDzg9HDC+XQKXOwy67EPfP36BZ8/ffFIE0514oDABDEHqooWNePkuCw9ZxR99Dj66QR9GvacNwgE1oqMmvu57M2qOEql46QfEECa82hikMN6prK2oHONEa8xsjeRmwJ3fJeW2UREgE1b8hGnvxMUuxFplN+mcpD9NIyIMvX0ktw/uUKSZys2c0UYRDISlZHKYNYAzHWXmCqjTb0d6ew5huMmYT/n0RlxHwY50oDqeMh16z5AIQ+IhNK0oG+2K9bMGAOTvE76IzcfYgIKTq6R5sRFDETILF6dGAgp8HPcVVuOcbYpPxQjHAA6chAkpTOCWRg1FJqhVEDvAxeWJYn6iegD0j3Lh6qgtRPOD2e8ev0Kp/M5sIS/ayDw6v6McXGetzithjEdCrjSbkCHP1PNcBnHjT5nhIEOEjiMazPlPcf8vlTX6HKUKGSMFT/Vw8ltz3lJuTBocC5r7vW6JoS0VaNfmOcFGF0c80zJik4AACAASURBVIsk5k58yaaN7rwmo9vNywopjX1cP4GvbPIzMzd8su2USX1suLlo5K47BNlY62OWionU+1KvOc97adjlevRnT6ePNJ7H9dQJki8dO/HbjD5PR3rOY9Ft0ajNkncG11F4yl2WSXHjOR0sq4Pf+XwOjKppZO9HlJPJ4ABb/uaejT9rSQVZZOzUr6U8BC93Z5o4zIaho69G9NCZCPdk1Gelczx1OYv/FUEr12aUzEi6VdZ2Or2yb3RKUPX6vt3ljjYE+nAqPAqQ3iMFejiJppNU6DZFstSCdPIJS1mI64C6kVyrcOxC3R0AtMfH6A+C5pVVKp4RY2viTvI6jVZuFADs2MMJVyfjLHtVZMpP+RoRbK+f0G3g8v49trdvfDzdcxMPr15h//TZ8w0mPL7V14oA7dVTPp9jk1NchLikJzFvvbt+lHKtODVMLDEXWHLB0PnF06l7UBq9ZblHm2Z5OMCyxEJq3JX4T5zfzFYnrwc+Qd8K8DEM2LXzdj0a9w8azhG8XiDAO5YDAETfFHohEeiAyIQSjuWq7qj6DsCHpacg81/x6ZyHl45vpXCnofqpPFDKHPOt9e/1sbRlaakfXyY58b8Tri3PnPzb5zKzrXD+LXR3UAxzuQUC9N8/AnD11undG3z94BlqhwGa5WVsoSlTl2npxKyR8cA4d7L2Q+A5MilX0YFvAGAGO5HISiN+bb2fRkHq9d0ZLcoYHj2cA1bMjMBJVa+U413G0cSNvScEDhRgf3aMsTXNPSDEoTD03/70fSMSmGF9viAivUPH0QD04wgnzxE068C2bWjt5LRzdMdeMiAWhYuC3jz+r3+5TuK392gSmS/GXNM8IgQOp9Np4Y/bv37G8d+/4eEnweV3wxFtfBMN/lPm3mJPiAUoK6TMABQHbCD8CWeGJ44L3KlcyiqntnQY77P57MxkKfm8XNfERebhH8MMTYNuic9NN7e3jZAfRBQ6LAIH4y3BAzdVyEkgcsp3HuNAPzouh2et8+d7P5kVtKkbz7dt85JHwzwFets8Ir0pzucTHprLl44lXIdx2S+4fH3G5djD8fBI/YOXv3Oeyqxfqi1kV0HvFzd0i8Fac1lqBNY1y0w6hzjOO+BJXV6ZO7dsxMah/wR8LfY+9x5hYA/H/23bUvflwrSlHnyMlc+lvoT144WY1+lGD3wGo96XhP2aStf9i8R21xT0r3GVf+74x1O4x5ouPSEF8UEarNEy2uSh19zrb71PAjitR8dt566Zy997z987yPgPOJGcAAhYayHDF7pMQ1UyTKP3zy2Dv2ZE+agkaP+njkqY5cV3jQ8hnP0wG8q2bj/o1Ya43gRTqKBhpG5LB+BzY0dTXji+PRYJlOT++UydhlGAYnk0OWIAh5tJAlC0JdnX1iJSOD09NJV6l8szHk4niCqO44BGPQ2mU2XaebIUEYGeFXYJZScRVVGUYHhKRXr+Ln1nu6KvUlaWC4mtss/o0mSG2ZZHYHyV8GR0D2+IoX9yYzjTvbfXDcefTJc1KC0AeILZn05MCYopUIcARcXtVAD474J5zckeseNLKk/xOMUffRSMr5r9zDpRuZa49hwgKTaMcdzi/StgpK+wpLnkfq/XXN8rCKGiPnziAm8f184LgL6Zu+nIORwbMo1tgAK4IpiP0VDGUECFrrGrbHu95joygb+np30Q/Py+Ld188Xj5d1nGzh8/25L1z/cDl/2C9qxoKu7VuPU02hksI074XK4JsalEH2Msa6kKghKKw6Q13FNW9o/FqJGxRzYGXwOxjxg1NrWkfA3osz0Mma6bcq8HjoXC1OA8NAwBxxH8QsJxaBiOy6ytfOw79ov/88iew2v/xt7xtkxXrBRyQKGjdC9no87R2h3fMxqlSwQSkUgj10iMQzrDz+elkouPI/39Hv2un+V+FM28SvJf5ZKy9MNSOU7FXtI+8Tsz+gNljyBAYZue2hXgOfyxqYzXnmuZSk1XXruCu4k7idAoMYYb1b2+r9NjbS1KJ6CA3VuGWPlFjnc0isZWNGAc0e8wCjMCvabCZAryPjpabzjaAI7pZ05FJiPJAJS0WchU4HktU0FF25liva4NWfpS5ksm9qtX8zmZ1tPmnLpRXmFtW3BMaC6D9yjotkgBTZt45gA09xI2F8QGugv1YVi08Ci2wHhHMWSvox/R7RK0NMmoZXvotNLTeD6QtT1j/Cycu7L+qopHzcS4uUJ85HDmfVmvNq6lHYkXZqCGkZmhYj8JXuMZgMRrXIpk+v+5HtjOmaYeW4s05j5OR9/D4eHAwSjWA2htQIaFopcZEdyRjnxKg0/7+EQWjIhcHJiRa2P0SHkZPCWiaDE8gwT7PaoysdKn+O3oBy77Dn32NGrTcD4vVIVnn8LMfLDv0/BN545b3mr5f46b0wXkX2kaEWk1x1ahZlTkxqYwde9vtXDtkjnH9FQXWdTOydt5ikbD/B3z/F9VhPp9V3iIss73gEJ2ZuVNXFcjeKIZHa8mpgbgSohtw5YRphbyg+OD0+mU/7Zti8waPo7NBLaFI2k4OQwDOsyVAq1Bj44u4Yx5ZVQBJi6kAuS2b9Owlp8VrlCj8SGwLfd8/T6fk8MaZyoPXTilrxyJWu9hPKdhvK65BNepvKeRMIwLoKrLD4/ydJrXyvvqe71kA9IhYI7E1fiYpVHQaRY8KpkyYeDNjJgufKUaUjNLeZFrOFBz3G2u87zX+27lNv6+lE0gbYzr8lVB2x02TsY1HV14PWls9N8M5QXxfeIIiRSVC5w04pOCy3EPE1ngvNhFUd98kvngJ3UuOMHhrbAaWDkmK48m76RzAdeZGyY9Gof7ifLqtrlzYe8tnJPq8+6TGu55DE0Hs9nT+f8X6VTOeYmyQpGhZ69uMFY1evp3PisabYaZ7zPobI4TF6yPi5dFIVYz0LXbIfpwWVsknkf6XLBeGat0gs/Pcx1YvnWur+Xc1XBZ/Ux6cLVnrVxojFCutMnqc6/olfEZxUmlz/U1IrCmj8ja0ukYOY3njBKDhUzHdxN7sN0cLQkDSjHOLxi30Gm2QUzyukHn/8BjORbxHvLOyZ1JTygvT174V3V1EhhPgt56CSxdcBgdaRDz7g4jMedmESkZ/L3EftmytufcrDjhxgwFYMp5Oc3cT0GjVQRd1WUjrndtnuvKADTD4R7KsbQFMr5OelSWSsXRk6QziAlAgW5z1C2NAQ1RelABi2RQ6RgQL+RSFcDT6IrludxtkY2Fhr7ej8waaQIv1fj6CfbpM7rNCM0r7nN72O3v7vyVKCHGeY439UTMUkBHpcozYFgyvtywQQ1syHWfuj03y5utNxiZjQEsMZapejMyc06FvhOMP+zbfb9zkEKqIfWwDkWIG99UaOF/gi56Gvw188Y1Brr+XA16f21Xfv/4q31eOc31b3LdzYw+Xw6ZsKGybrn6nkFD5fPyGGIWvv/9pwI0sNKKxInINT4fNClGDaVb0UixkZQ25t87/anHFTepra5EovxK2iwLHeYTcpxt0urPHz/h3U/vUNRTzj+CbllEnzB1fF5Wxyz+zYSMHwD8mHwK8GhkL2njGcjqYK0zQvzrMf5eGq/6V1l9NYA5z7PUgs/ztjXI//wFz//1K84//4jj9z9yHO6OdZmPG52TcGwwdbYQDLleGFcYBIiSlW7oXmgtOEcGiqQk85Kh794wD2wdiX/cAVKhOtwwHXxPxR07DJj6b/JRnWWr2GaWfvKo6waxDjNiVE/VvrWQIyNDI6PMPXOk22+20wkn9ZKFQ1y/s/0s0P89Ae4xDlCn7nLg6uTh/Z94guU6TNQD3IzOYMhsWPVeILJQmJXV5GtBBRgfP2J798Y5u1iUq7TklX0MnOJz4gT4+px2urpWgxVdE5o7BPYerfweHf6n6PS/e/wjBvTVEIdkxEvnKPgPB8gDfQHiNTrxnrBDwk8ikWaf2EPnMAwd3fNCXJrgAkB2Gh394hHhA5tuEQHr73od7f14hyS/0OmbU0+FTlCYotdFHQeB4ADwYO8AjBkFau+zpk5lcvdac/7pBOBnXH7/ffHsowmvAbiuLw4g58WNMa9g8AhOtVd5xd3uXrVnbr5QDmWyFv/l9GOAqqJUnUN2JaDX9qfhpABGIBXtrXm0G2tAp3IqPM2rst7vDWIT6Z/HWEcyhQQqoG96HNeNyTAAuCLTZnSkdazXB1HXiHC4RN3z9HqGR2g1jcif/UA3Qzt7NF4fw5WufeDhVSveo4CNju3khtHj2b2Q+8UgajhDsT0IbJckjNv5hONgejuBXnY8PD0lgTQNxhJRGhIRz244aO4BbxaeTyO8vNwY34drpN14Ht5hRqbZoeb+7d0G7JNAnlbCrmjoNiD2iGGG86u3+Prn+yn+2BSsqdAzM5xfv8HXD++n+W/4M/bxKZjoI5qEMP1FoK9I1Ml0LRwfLIHeQnpsRjyp0rlhrovjT0/p3F45JKrLTuqHeF2mU+V6i/+J+NrbNsVxjIjqmwowCjydCvOiNBEY9LxNRgt3CPA2bzi1E5iGlaCAioKpDF3bPJVV06BZFejtIaLJItUO320YsN3ckB/rDjKNiVNIuT3uUhxBgjOPZG+g08ToHcfRPZ3y5ZLKgz46mnrK5H2/+BhRoRCAf8HUTA1o08h0BaMnvcT0g/EIjznhVQnrwFzJBn0exwREs/acv4m1gKj40fAit1QGtkjt7m9gnT8qDnv3tayxeI+IrqWBar/sEenoRnXr4TEYvDiVgDTkMmrPot03M8UZtVxb3E9NBdAZyUjhmpHutS7hrLVZldjzSK94GTe/rWM+v5O+3b2es+lEMRRPa8Rv3f++RiyzgKTR3BxQDjO0qAdnsOmhb1gU2PPtPma9H06fRoOhZ+S5RKQmxGuyiioOs4jO6+gD0MNpvohCthaOeUFXgi7KlUh8HfEEIHmxIQxQYcwDFS8GryE6+gLF0tmkdwxVdO2QiEZOxWXdU6PDAjF4BKTjhal4tlJnNJZcMXjXdltcpIiMCxoKK45s4EsEvRjdwjm2RCWJp65sjSiJc8qxc/4iAsi2wUwzKo1GOL6v7x4l7R77rJscWOQYUQcq+jcs+5jzEUIvOIdlDIyaCYl9Gu0sOkjvW44PIzFDfBF/PusJ1zq3KYzyWRmhRMOKTL6FvG1iN1GPyg/HCmlO5yk0s4xKHmH0RtC4fhzo2+ZZPYKO7cwYMEamZ23NeZ7C9wTT9vbIqKHilLSrR2sJAKZM81rDTtMZwZ9zzDkgbb46tDnWmjBgqoDcMcRr2uMrcBxH4FG/j7WzRVz5kWlnD3f0GlG/3jMk9DSir3uzY/QD+/MzrHvU/YDk/Mz6ltFeYDoylnmjvEMs4fRlRmjz72D6t6sUwPMZZT1WtGArXXaWUo2mV0cFPNen+eRF7nZj03o5MaFk290BqSe/GbmPgaGhSBKgbQ1nnH3dNME4vMwCs2Awhbs7G5YxFh/zpurppvuGzQARVyZsfcPRJo0WKKCB183QthMk1q/SkaVGVCRGipcJDaMa4ltPI47DXzoZEQ9fTRYqnVkGNN/h2Q25qsPQwejVcP5woctganHP5JnM/5u8ny6AmUbZcs0w08oyheIk6dqPPL8ZFuNwRVcqAlOPIGGEHGmtwecF2aK6bEiDS8YMzGx3iQnMooxQ0Dfhvlnbgqu2AeSrq7uC4zjxNMdAZFdZjY5pDC34Q0qb58P9jcb/W/lcWyK+8wnjKvbNS+PvKPqHOVbzQypJGZEaDt89Ml94Xcj4rdDZ2hhfiyUdtkrWP2+nlrisbefMiLZL4KGCOVMxyEwSLlhBmptfQwohtL8/YTMP1XI+v6ceCrPsUpz3Pwk6CnZenZmA1di+YtX6O3JPsy3UKeT3YPbhgoDEBUYl+VxvEj8xO8TcbFgORp4vzit3dW6kMYUfFsUpuzMU7uiGMDiK+ARckShfL1bI0vyR9I38n5iNBvSd2Wki88qIetbUPyxORt3KOrzqV1nfwyKLi83o9WVeg6bJEAx0TGM71zlW2uYDiTTAi+SYwMpzYzMu+q9741/nxxsG1sdWUaBh0u6U/4tcH3yGayI653980BPP5v9XwJ/rxJepwA535EwaDYP1AT2d3NFj3wt2N89aMgyDpTUQegVrnl2lG5qGHKKIciGPwNevHokY8rGMWmIMUBNAHnF8+ZzzPAwQe/S98Jrv09T5HcTiZoGbgBaOjmP3FLnbdlrGe46/gKlqU34Xgb4SdPuK3p/8KvJeAdqrV5DPn1OvEGJ3JrL0KfiC8XlAX732+cJcomyDRFkvN4z5ndo0My9w2pz/BY+OIJaZgsCShgsQIZ8ySRYojVsA+eJYkK0pWEUEEhkCSaOWvZbgMf6Ecf8O5L57CKIMqkX07I/1xtcrbio4teI2yrgAkhaffngHEcHl9/cvvPX+8ffN/7zxDg0C8ClexSj1L1evfmVsz0oDXm5hHBMs3b14OvPE9+AZ7QfBeG/Qn/yd209vAREcv3+A/ijAe7/nAcClvIC6hIQU1+8kTV2/lqZNhxv/6s/dLTJbYZ7WciN54TQM3z4ZQO7za1UW7+tmd+66vc4CaHqWCeo22B93MLD3brNNcbsarEpvnU6/u9EhcqlsW5v4UkOeBKJ8BpbBbNsGO/Z8zrv/8Qs+/O//zj7RSWL7+QefJ0Zdp07OwFTwx+/vq4R33fTlkKu/4/q3wuNXt6viBHY1LsQ7FY+uOG0uplx3hZ/DbAakDdeFjZDTpHvWGZUOHQIdPvYZFY0o2aer8yav0ZBlmnjpIABhA/EyRJsqzpsb0E+tYWsntE2hpy3qoW/+j2XmrAMy0E6/4Pyvz/j6/z77egonMoI6p63xeaxj2Uc4sIVufwiydMWA4fOvvwNiOGzS7oo31zVfHEMz463bfHrvNzrNzCxXdN+gPFZkmqnTklusBCRPemkDrhTw5ePfpM7/8fEfG9BTnuBiJoDgxINAmIK/pyISeLrQCefKVhHBPUDP66r3RD2We+7y6vVMBbB68+vfP74IQDP0X2F2X+UDHu1NLMyPkMgxI0CkpHiZiB2/deiPCrW3Tuzk43/YevyFFvOq2+uqKU5AYO9n0mMIMokDieiVgj+fUhVC9T03HPo7xzcmIpXF35j4l34i03HF/fUr1pcKkJHE/ThgY+D8+IBNGyCaCi2mqLeILCWzOS4X6HZC0waD19BsafxxhZgIvZA1nhkMIYQgiVSdrC0DG9C2AeopLIWTFMLW+XROLiUAtoeGsXtqkQTV8WyOkjxEh78GLdAJwCUI9Pg0gNcTLBjHENNIfnrzFl8/vneGGAw+070PT/Wnw3B69Qb94wdvBwxmX/KhfGZGLRV8JUngkcIs5xJW2ERBXQmc7qyn6yV5ndWgBh1wHDQUpTPNj2DbFKNP704pzL0uVDODmrizBRBzPh0mvA6p51akotZT4SUFdWPn0k5yuli9HFOmNazCEyYQLL3Gi0cwY7naE1ejtnys9KAa0ZjO+OgH5FDos6YinQrw/XLB5ThA5xYqFmpfue5S8kxBK4QKKoiTXEVUeQi0U4FcW+9egBvzWpqhW3irhmJFI/KRkSi+bkdGmTZE9DEVlv5WjMF6nYhUzG5IGscRqS6Dz+6eYtmAjHZk6uqjH5MH8+0cgpB+UhFlddbLfl/6a9kPzplKC4OBwIankMz00x0wG1mf0sfySjS1KeS9dLy00u5jBpdkcjRZc5oYJfkRccpU3tUIGh/fqKXagk7w/ADQAtyaZYQc14qUrWbDXc1U3KkoU2oD0CZgMivoTCE/bER0eCjKmqCZZkmBflT6NvfZ4lSQg+YTOyIFYx/D01rF/DC12HHs6MfI9OecE9LhjLxln9KANRZQLEDQI9KwdazHoJJYggStUT3LNCL2s6obIkpq5zDfA5hYk+m6QcEM7qBCsEflq684N7x6RImA6dANyLrkHE9VxYjU8nQqqJi1dy9FMGC+F411tzQFNhUvG8A9mIeDOZiM/4+6N+2S48ixBS/MPHLjIlKq12fOnPn//627tJEimRnhbsB8AC4M7hFJSdX13ky7DpWZsbjbAgMu9lxXRDuElIMw3y8uCyTPrO//9QmiE6M1dzFkOVwEz4tgGu913PL7/IzGfVOes/9l7GsabVnuO/Z4mGUGtoj3q5e1uVILd7YNdac0S/0r9+RyiYDIKHcW/euh6pHj8cxwwQRv9HVRVqkJJzWd1VnVgevG41Eyc/rSI+CxSiwLZ/iKlxfv1dtam/2ye48s5jsgaATm+79evH2GDi//t0UJWFZAIYaabWo0lVbuHcfBClXeBy3kCDEMGU1+LwhEIoipCTCmM95xEINeyPPdlMBMR56paQiUsn57sv0TKF0+ywwnDrUySOx4ldnENXybwW7EhlsEJrCPHgckUSWiL3HulgaRBa0DtljyjtZblKOe5YWZGUKDNPda1VsEjK1FwIdhiQwU2wAG4uwDNuAyEWE6qhFxuQY+ccoCt9x59ZYmcNkpXoFJQoZRbtNonzgnsAkzBm7JSynrn61HWrTMgJUNZRbXPviMI3aeHcHS6k4pC1nA9gBNBOw/7ErtLQ2yjg0RO2S7zAXOrcFLrHt28wzpNkji6XQ4xBinIj0xNOVCEgzxgBmQfERR2wTQZpGlBmNcDLSbNg0EMAjErQ4UdsFFVf8Q5DmWcgZ2eCv4e2afH5XbwE7TcZsblL97tnboipQzMqfdyE8aaZnBnIHLBvJ80BHLEQ6rdN8SP7PqWYs2RK31MCr6P8rWZYme6MOd6BvprDAV0nruH58H4uLJx+fClb/jZokxyNeqwQ/7q9LqFb0AGVCSfJf/l/Lz8D7bGfj6xjwl/seqQvU+h2mRDlKtEYCBCMe/jXS2m8fE945PZiWCCvnJ+mcAKVdh3q+xbCsD0rnGcSPb0cXEBo7VkFndw7zKH6se1b7mrP7C6i10nuuY2JQ8mxjAdhPhrkmeXTFJJ+QuYDPWjvesAct1XNlyaLewvlFGrMnFFqSeVgmqrse0gcz9moFBEmTaDn1gD47zLN3OQ42pB4h/389N5WGVRxT60PI7996iCmDIMTWDiaa9YBsz0Avw4CM0Vm0yDBhFG5bUm7yVCkwhTaF2AaTBuvNhGchEnMRsAARn8KTUXTCzyHjHjq0j8A1Y7Q0yx4P952fauHh1poJLkW8bRO7R8ILLt68wAMtjYCt58u8+PvoTv31LZ1x/rIHbDwDYhq7YWIxkUmiz0CRSN7QQV2UFjG6zkGMMWqkX58LzHXIDErpB/WwyRSvfrT8L7eb9v+RS6mfDuDWG71wN03nePxiAt7kGM0DFX6k3rrjtOF37ZJAP30Mefp1vfmT/nL97VUn91+4ih5/7e129dfzY4Szzehbgjc1MaK8vCugny0oHCoCMytfxDSBfM+hxnr85K8tnTr4lFV9VGQ6ewzrGSlT++8A+M/02aDw6aA+LIK+s9itf4TPrdffmcW6gzbmpfoV+8oPqwbqCQXn7yiN2ojVkhfe59r7kZpF0RzwJRObOHpjUwEYp70lrePcfP+Hrf/2CUbBKWkdYUcM0MbYJ0D6+x/m33zPwNNlgLlb11VUWYNf7aXuOXKsiGCT9QQzeyHMh+/DGoECyqVKljyzpONLA/CYYgJdvV0UbIRvH2AUCiwCqDb3HzJqg7wKk4DyelchMIPCAdohX/ex0oPeOu2xN520O+9LRl8W/36L1Jhi04LYPmJfnp/zXsgIqDBQDEDYG6iXO80fanhSYNhwYXv75q3+/0B0Oq8WQzP7+Xe5ke/sW3hQ27EDmdue+dJgiEtkkZc42pm27Yn8mKptNvL4rEFXlyf/g69+UgQ4Q6DNy4YBownilGPBeEo0g8RVGNiPo8yY7puQCNMCTTIHJnyNLVRB05J0B4KD8eRmRnbO6It2bnLAwOABPFr084qXIW0KDZ5Qd456BEFzyJV83fM73VsF+fPJ5NwwVw/j0++vrl887Sh+b/5dvPgUFVL7FuP39BkCMefnlvlwSe7MTmLwMhv4DHXoB4AloxB0mEj2hpK5vAcdz5y0ZiyT492uWy45dltsLMRUUNxxn/6n4sVOcKkA+rBpC8OTYsjSAcUA7fJmrnreNyCozyOZGXxvqxjydwsK2aXRhFI9t5qU4O4DoU+O9PT3D03uCLOGUNeDiRv9+v+Dh0aM175YTtvXsjvpi9L5/fMBYV5we7zEuG9riwHs9X7ycTJ9RRqf7e6zrGa0JttUrPbTeoKvh/tHv9+2zZ8T3MEQqKSp4wAZF1x5AV9EeBRjA+Op78fJl22cuUikuDBqquHz5nJliKq4wmT1AbIRi+Ayzu9iDKWg9otl3SUDHySz1xBKWTnuxl6X0lRvngOVNjR5EOhKMXuogntY6TIeXLQvHqgsTN5RLqb1jgulMsxYA1Etep31ZCTr8v0ZFWWrpmSijZ/D5mWdd8rztqndIOeHJIqJEMA0bZ5C958Ue0AW7lFtMl/88DIcb1OeBH4wXufBFPrAChSAcX1t8ywzrtuGybp4lFiDU+9s2j4CX0guwoDVLZEY+Ec4Jo+O9hUvcndoZiYjsVjy/G8Pv3Z3IQDiJh0uCkbylyEYRNwaZO8QHjRilzPU0SFk4Xw1jG1gv5+iJO/y8xHqNbQB0GgWdsa/wGO4QHWrRozxANWWZVWMSjW8BYG1vOsye5soMYy/NSafgspzC+DQAuHN2mHpm7Niyf19vffbRhKRxSLftil52PP67tITdGtfPZJnDuB8NUBaGoeT/xajm2+yyi/dLo2KcIR2K1qncR8Znm45XBIgcwzwTUTxj0UsleYUPGLAsLN3V3LE9NtgAhm0x5oa2KJYlslFbh4lXFqDjk0bmlLnJuKbylFl7OjKb2GDTEa4WznOWmvZ1MFUevVwfGjIHs9mhkcnpWZsSWWW+TiOrSGAAODmv86CSuY3Z/zTYAf1KLitDIZE9XSbOjKwlOpyBzN3yezaBWLQ8sBU0DvQSfwAAIABJREFU/hgMPSKA+X20GTjDvWzSIKc7bw9hCou5b8N7ZW3hzDNmY+dtohzWzilIo3coH+byzI2z8GpNijjj01DFs0u6zAyqoMuJCwCR2S8T8DFDZGatc29pGGBwRMUzg7/5WrbeMM0jlGmxzklnfM8dz9IEciE/nmXMN9M0hKt6uVobAhmaeHCMaNuxlaoIReYJEAFuk8ZHOFZnGfep5gv2WQlHFHu6O2G9rEgChPdtu1y851hrl+Qh3tO94+HxgcNC74sHBqyr920/v0T1BqeJWdEG3lPQ6MT2QIHeS8Wg1oA+wYfzXw+GtNIeiGefpZyTdxUZJz3whs3qW9MhNbGspJN3Gs4pwl6B2rmuf3pRDNfN4PiPm1G9iZxnEJeOkQEH5CumXnrOgJT7PbJfu3mrl8X6zvExnRORQWlRDjAQANtm9L7gdPL7NmloY8PWA3OEfAMcN0nrib1aA4YXLMr+dSZ5QHbjmFisobd9Bg5ibnl2Ia4XYDpP2GMYIhjYdqXGp2FoYh3AMWfrPTMZJ7qcWICfc1A7Df1OG56V6HLADS5eHaNF9SZzGhcJ5KQ5Bg7p1mUO/H2+ETBMtYstpKS1XcWSHY1S7zRlkYWQYZOHck6s+DMiYAz1nilDQj6aRjAz10BTvlLhU7Odsa4t3WX65VLuWTFN8HPqwVx1jqHSBicaz6rO9Bl8yztO3Wd+bz4foJM8Xh/myv/gPXT3SC/PXyF64CEp5bBbT1zo++ByKB3nS09n+tJ70u0SJd23bcmgjptrdaAXYjHKx937V7RFTDf5Y/L4Q53Jgxtpx1OdH36P283zdvNzBYcyODfPA19OtULAXsWCSXfVzuaBeSy3eXtczkOqo9ayaohhOj59DS0r+viZ0sRa/C6vIey/3fefQdkXI76RrPbn9BSO1aCdsc0sc1YzGhZ6S/nnmepjVkbIZ5SqEq9e1F0MA9ukkRA+GTwdOhdL0Gb59siSVxuzMqDsbpGyBAZ31Jt5D9tblct4NONQ7WgZk5fxD/L7NI/LvJcwqKLwP+o8/j0/V5oVZya+mQwNQA+9IoL8YDH/IhMmZDCstjl/3rU5DJqQSW8t7HDMrunDk0LQ3Ok79Oz69wOAZ2CD9/41kwjECtuZAE3uIfYCaPBgGMyeATOsX31qy+OjT+mZUzvvaETu7wHx3rfJJndTqGceeXYyA9oMkAecnr4F5ngCINhUsX35iuXNGwBAe/sGY3zDog8wPRedxcdbQ7m4/703bOuAYGA5nfzZ0aqGQY/ADMxIxzI4VkSbEylB84X3a+DI5rKadqn5Qedi0BF2vCmDrGa/Y38lOQWb+I6Iv3mRshsE7QdAJJzn5bzIjldPGepEqImBqBP01oCPwPjlE9qP7//GaG6Njtf3ZyXf+f3RZtZ5zT73KraCb/Ha0+Fo8nqpnrHjArtyOf+gzSJojPVSkoPUgOlgHh5k7bqGifs2AsLC8m50kRdJF/xgVtCpjLEOecd0sQH5DECwwP06UWARS5vOwOOK5Nkpj+u8dzApJkhON7Dkd+uVwwxDK3Pcqd86Xmx5nvyMGQZlCm9CEUn9q1wKwxJ8WceIVhsMui68PJ6bVZMMGThuNjypJhJo2o8/eGyq6q7wcNp8e9hLeK/WHFN2r7K3/vxrYv4NM6FUc42uMUU5dUlPzh/rm/Od9PgQ11wxjt0WJp1MSEQbEf1BvrhphoOTOoOiBqs/qTiehWATVkEydBQ9LO9XI3YNEEFXJ74F5hUGQDy7hO6/YFkalrbg1BfcnRacTguWcKK7zO54gusZagNmA6tuePmvXyBvH7HC9acmc6UMwPbzb1h++iFxD+2UBrcx2rqB1Wc1bANqhi0SHjT2kMl/tepXtpZmvIZF9YNY8750T1hA2HaE9OQ4qIVNxeC82uAyaxgrtQAPD3cY28C3yyVK7HNvpx/me9efyY2/I1f+d1z/vh7oubi+9dLMe+MUcMiMI8+CwIQMRQC8ln1++wgfP/SKtPnrU/jLn9k9QgT98EwHAG9hURS+sEQA4TxHzc6eV8Wxr43J8AcEb2H4cj2eP5tD7hUm2D7IOe6klJHvniM8iYcRCqB/CPqHCUjlkBWX5QL3nB4szSgoQuSgDO7+vIHMXjPufc/od7zfrXW3uIdl7Zd8dX4AhaYB9GX/Xlodyjfd2OZZ4yIjswEksjRmNiyVpkTGzpgF01HTGu7fPqA1wV2/x8PDvT8nFOH7u0f0pQHheOfQl7u7nL+ZYltXd4SZAkPC+WFo9y3HQSVYN0VbZiYAlQw8CGv9JJJuT4B+NYyvK2AsZ+UC37NULZ0e5A9d3cC+Zelqg+kjVP8oSqZB9SHGwGiuu8JHZDeO650tf9XvCJJGXXkLpSsCGa7pJDKaArQ6zbjRsLUOWrboGGJ/vMwYwTSqcBQtIs7zSacYT+3dQvDFDEd+P6zpUwGfip/E2Z1vpXXR11QcjI3zbgVfvQQA7vbLfbxe42fH15MHtf2nCZR1hHVv84w+9kNvIlmeWSCR0TtL64YXPcp0Ij8nkAgsaQVIheGB/6LHzHyNJall7il8X5bu7UEwhoOELeCCUYlpyedIkn5EIyoRsxSl2OQoIpL9/17OZ5zP5wikYRlD3WdUBJimQzSdguWeaQXhONKxYJmhwDNW+fLcu+BHKqGIx9pnva0wqpHvMWuj0CMgGdF/RQQ59xuEU8dhwNRUCL2L0yDAN8dMhy1n5yXZdZfBms8tqJPGWolsQO96odkLUAML+Bq4AamH4fio9LMnJmViS54c/CAMnCN6JztNbuhbx+hhhBb4Ptt+jabzfC6QK1cG9sqjoZTgewx3/o6x+WdUPSKWAT7qimIzy1Yz5F3k3bnmcZ587h5MkLsTxlIIyztqrsMVjjF45mVtYYKYrDCy2lJW7ik2N8z/DkULBwMlHYoGQKMEOOWRWHG+94ZFGmyJPF0vrwBdFFg3V1zgWVI2vBQ3OUyXHnFNgaxEMqiHNAWJM8eyopHRP+rfCCMxjWYQV4aVhj0e6TbLpQa9JbZKJQg7uuYepwGdRsYqM4wKEysmxBiImwov5E8NA7lEVRAGnmybl2X3wLE2g8FSV2DmlztKyet6a1j6yfuKLe7Y5ES3zYM+xgBam+fL+euAZ0VVqc9AK1/D88vL/gwFXS3LyQMXzaC6RZCV7935fImyezLnB2BdN2zDnejbuqYC7Ou9z8aj8X8MRe8+XxF3mLI/vd8/zjyJeRBWHnAM6t7P+aRTCvM7xG0UxK0JVB3zVR45+ap/br46H8TzmDS3e3/y4tQ3UgFB8qtb+t9OL0ysaQjr+U71cxzFLzKIa8prEWGnkZCTPka2GkDOUoAepUTFg3ase1m7tq3oUd5ulMz3wSxjaR74ytkX3kwjfPIjkHdbOgqyLD+S1eXcsuUQJo1WI2nAt4Ing8dk9gkdbgW71G2I9Zv9mkv2SRUyNk2o5AHkWbBZHl/aLK1o2qGq6NIj+1ln5m25yIOC2P1ZRaYJ4GWBzdyQU+gmg0FI1vm/eDlk7KSbQj+UF3Y4UfGaGkMrSG2YNCtSgocsdHt1/WtwGvMkIcc799iPRozhgHkS4hSeLWVOrG5AzCKQyGjh/Ji9ojP7hw7NGIOX4/Y1J01SYhCjWszXK73MwQwQv4ZxWbnY1IsiuDCm0Iw/HQs1GLp43m6LqjV+dojl/GqLZ7Tr5mWXRwbT6g2ceHzBdj92f8cZOfJNrsB0EPirNaSBs0pZSQwX8iw5YL6P1PlMiDWKNeiq7DccQ/E7RhlSzvLVTHkG5rlPLF4wkMJqsbhXL//+DC4hLbc28fs+E82S12lUUjJWWIsV8WorxLiaGebEolA610dWZhk6okx7zTQnL688YK55Dknm3pH352eIwzMob8pn2MxAt8P8X1+vqm/f2B+b48i9irWqc6D8qPeg/r6/of9PDZCBzCgV2tUoX6XyRae5zBLLe4051xJwdOSPap4gxNe8cg526ych7zUqMQGSrWecfgN/mbq9oxnsWWENOKG5c0pGVi5p5olKZpeyDnFPhKwh1OCvBpicM3EqV65gWtZXj2Us7TMPCIc0JIJhzxC7B/CQfNjM0EWAp0eYfQNgaPIGDffovQPtjeM7AJAnyJsbdCSzslWW3zdkVRnKNspqVkmRWl1tBzDmeoDb3ihPS0AciBc06TJ/xjr4kk0b/u4cGAB8ueIl19T//YuZqZJ028pNYuY7TEVZOOVTfSZtZGm2/dMB1Pl870Ovf6CI6qvXbznPec9bd+Tnnr43npvDmTLY/zJ8E2ahF3wngvax5XpDBPr7Vw/AsK8gRDwDE7CQHubi59kxeJXM27OZw6zTH/WdGwv3p9tWv2MI+woSPNM5CSDxNf0wx9uQ5y9vHvZjMOrZLavE0o/T8OcXA0PmfQpPz3Oeh9v13aIjmeq0Qxf7h4H2gIk/qzSegbBydWZrVbYVlj6pib1iQQuB5c6SFMiQEEmkFnyfHyq7V3HTbt2qvEPZznLuaatNQCNzTAb4WhX5phb2B/OqtW0YtqboplDyFPEqZMT2+8e6ncYT4VriGIG/1qL/+dIaliboPZKCxBNI3LYWCVJq2BjQv264RHVQ+8+vGQgBuA6Ijwb55LhKm+/liGQXNUf1559/wzo23P/0Aes28Pzzb+jScBZFM+BkgheZbmoD0M0DJhlk0K3iHJc3YxvoSwfbz7n9RL2dXAaqW7ZIS2wAFBwZ9LR6NVQPSp5BV1k3iHT4Zwbe/59e/zYHOnGMABkFKaFQEkjDWGJLE9QEBAg6lpso3syKY4ikMJGBYErbsYUB3Mhk/FOM0jsFk1pZaojPwF+Tq4eB5QMULAXEzGiB4ktme9bR16vEo+5vXd638tr+bl8SRB1Hn5H68YmRf8fT4nFiT75v7RugTzD56swBAOQrxN7u7tvtLWggB5F93tP3ffnAqBtAuivIYS/H/cfF95sZARXhyTQANwjknZRJzxVsBUxNp8Rh/sYIeDIH/0zv3uOIjhJ+r3fA27m6ktQXFnLxtW0QWCVP1wDKE8ve0pBaRAUBXesC9BZCy0tieH/xBYoBaV4uozkqLvTsUT2XC3tDCUQWCCNDRbA8djw+vcHSFkAULy8vUSLPBe/To7/X73o4bDzCiL3NRQTbObzezWnbGV6DYcN6Mdw9PrgxcQG2yxnagG0zbC/I8iMNgvV5DYC+waC4f3cf4tygeAHsDu1RsH0JA2Q6+L7A8FAU9UeIbhAoxIYbGeQLBI8Y+Jql8ICpvBhSw4K8CccoBPqS3N2NO8ukK56gY7ZDCnMp5e/hEX1UMmhcSTJunWQAkSgRI86DGo0grUG0wWQqsOQnBKsVxe//RsyJyoUApWQiUBWQqATAMsIs/Z9CM4Acs84xz8ZYlYwAOFU+cwhyMqA9TIeCG/+OI7arv+qRrZFxt640BKtBm2SWtZqhj4ERGS24mGeLSUPTjtaCfiNjlYLHCu9urXvRGpMwNkSUYkimmbEf2edR0pVBDOkEEKeLviyYpe819Zc0XERvGYhA6TTrLZyWI3iX5T4bLByO7iBah/d5P5/PXvZ4eBaFGXY9l0lnsSmgUdcBNBVkZiwJWGOHwDlugjSo133IcxKOlgiSouGThsbeDWrNM0oRJZRVM6BhbFuUsPK536KBHSXJrfd2UsiHjbIGsqfbCuApcEzVqwSkXIvpq4GObiAUp9hLEeIKVxY11tCjMaNyQY8Swb2VDL85VhqAZpCU/82sDVObTpptoMkGHQu2MdCiD5faVENSAeYTslJArIkie5u7gQa5LlsEZ2zruhengpmxGf3PJTzotVw3+zMyiKgGmxTWMekZgDVXKVmSFIZdlQC/t8uW/b4B1l7BbckHrWRRhfSJSNxa8nmnTAb/GjYg5tmSIhYBEIIeFQIEEgYIyQoQlOkbWytsHl3eT0sq3ZnJ1SOgIo2RofhGqUgbM+hFy7+cu9ChoZlxQcO6mgLbmvLEq3e4jGIfQgbazIxFSfltsJSrrZVKHcEyJQjNDG7IFsMYW2avsE1P0rpG6dOh2GSL4AR3LKsZ2tKxLCecTqekDzOn07Fp/ByBVTxA6e604O7uLqK/l5lhLoJtCCADtpkHOAT/02CzATWTbjR72O6vaYSIyHEVIHHjPDdjDCxjQQ8nO+IMMPuc/3T3XaRRjzJY01EQPeatAYHvGhawuwPUeUpWrybN2J7v7QzFII8H0mhv5GvIQBHOKwMlDbl+LgvCLWjzOXWt+DmOpTlBlUUFsiJQKiG7t3frT9XOGnYXsRpxPf+5eKI+Gd8NGmitp4G56pMqlHsle5HyDZJ9n1tvWKIfYRMPttm2E7ZlpLxv6tUo1nWWGjZ45ZWWYz7ogTtoFBQnjvqkRcArppOD8sxwDZpUw4gem7/0nnjG5VboyzSep7yQ3Tjc3mYT88o+YJQ8wBe4BFGF1UqAWaJbFaP7mHSoZ6V3QRsNFqURK5zMUrlmaBp8hPSc43CH7CilAunMoXGPNocr2ir3Ip3VrEQDshw532cwW2cvcyAxQUpfMzALmN/jk3XznzNYNpbcKrbnuYmjYdMESgeCj2VuQu5JiE+2CCHfmg5yyz11GSSxp4o0kZpEyUjLsfhjQmYGRmYLBRY9oeaQAZrE/kFrmf0aVWmICxr7NkfgZWLHtje8X1tN9vvJff4zh+buW8eP2lzH+sRKI/FC7gh5zx6rFKdp/o3X3+fYQz4JPGuKzkWBZTUQJd+SOGNBD9ZrSehYOY/hSV5DLFkruaVcB32H0/h+tWSULaaRAaU5N7OWPCAJuHw3nz3YtgnJSGrm+RYtp/Lf8EytbMdiCt1mm6B9v3jk82/SQfKO6cDfBTnEXne2mQF18inbKKN39Cjz/ru/57JNnnmocMAx8947x/yOTOfzanbijn/lJ4thWsWxuhOAvzMZT2D6kDXUD+J+rZ9g8EAFReB1ng0L/qheclatwSIj0zMqZeqCRR/LIBR4wAzLqDcRqF0caxuAZ8DQXCU2hTUFbAGaekXCmJ+qV5cZ4jrXMIuMa0seOr49Q4C033FXJt90fslWJ3l7yti8pwCtBpj7OZT2EPrEM8yAZo/eHg+AtI5vn300D2+9uhgTwcnfRcKJZ74u2xfv6d7fvUnZQPnEvSHPHGPSDixsidS1AhukfYxnU2KOsUeOWyQx8Az0R2YMWlmz5C9S6KzScyR05SM/JSr8SxdZw7S1vt3pxvm4g32V9E3nL+8mUR1Dxwxy9FLN/oyZlz+ff49wFN8cHf7SbIinv8j+009xBJ9ijY8O9GfxLHRmqPO77JXOvx/il5f65djXq8vo5J2yiBpP9S+IvM0ezQaD/Pge+vtntPYWsD+wtv16T3vFkQZsh0H2I0fy4uPrM7QOWNWwADhh0sQV9yzMtcrbMsR0tqaqIaTieLIwW91iXcLKGV/Qr88wMyw/vIvzNLGRfvaM5FTDynpyGK1Mm+rbjrkb7+nJL/20QPoSeqbrxi8vL7i/n458l5fumFz6bBfZ+4LLZQVgePhfH3H+52/p3GdLMK+EhOQtENoYqWn6enzmeu2W+2A7K+ssu32wfL3szNWxme/EXW1PC4bwXxncvkg8SewqkufMMBMKuLfEPRo6SRNFM0VXynGEDuMVxWxHq051ria13EyzyLA2i9LsdJ73sBlH+9wmGehuqngYhstQbJFYMbaBcwTX2+q2IphBxydsqtDPLbtnMeyUFeoQyQUCl03nn3/DsyqGeAB3M8P9jx88s/yX32Bm+CqCt+ZtUwyGk4Ts/QGR3GJ5LonDxzbybw075N39PWwoLrZirKu3FbWCdZvANks7yPlyAbGyZqWYP+egf/X9G9zu/+j178tA/xcvyf99/5oKzP5v+RdW8LXN+Vc34/vf2zMdL0G0F17d3mUPcx7+ZPB/6dl/gdz+zEMFAPL1Lzzxla8WJWR8UiwfZrYyJPr4lX4OyD8nKiLrS2cNx75bFcRn5Ijd/lvXFlHsqgb7AvQPNz5UkSDR9g0CLMndycQJbnrrOR3P5I5SRQKc7pbI/BEs0oBmEJl9LhCKDgMYaCz0UoENp37nznJTbOeLK4MAGryE7rq+oPeWRqAUGJE10ntHW07Q9TLHHQrJcnef5SEFDdt2dmfsUGizUOpLNLUgEIXBbEEqbQaY3cHsG7avdynMzRCo2Z3nagxw8RLmNIT7Wj6APTZSwQCuwDzfj5sDdBIXxcSd2lO4pxGAxh0avJqgoacAYIlBAqrdEaSRheAyAHx+JBQZyTNheYt0qMUzwuoFKkSpGpTzNic6AShJdQJeAiDknnK90jBAZf5ibrAWOkLnGbwNoY5r/nc46V4U1iNWwfAx0yo+4Ma8yAQdNp1sJg7AW8yhhTIFSNI96YBlMwVToW9hdJ5lm8trmL1yZtn8GF5rkKWjKTA8xs/BlrozRKJ3skQppj46IKR1N2ci6Mr3ZcCdeH5/OjlHgC4dcT64Hmp7J48q9kqFzePAvS2GL35zBr5xanN9dqRe/vCs0YaG2iZhnqndvkbVDLAErtou627/EFxdsvttKkXp7CnXMdLX4vxR0OTIZJ9hVIdRTZ4OCMs9bQJ1tpwg8My+n9Jm1QLSVNyLAT4+NkBt9V6Qg+XAo2SSeZaGl7JeXfnrHWLxfVU0NGjzn1VGct+NWb1RirVB0JfpEDdW+oiTnv9Vo7ggyrIXgzjCpcz3ZM47iMMjaLeRhlxWTek5f/LFyce4KL6sERst8+OpldbXYryVfwNRInuwRD172+Yj5p7TOBifk6FoUO97riOCX4IuCr8GXFlCRAqPMEq1YdHPkQcs7i/lbLJyBJ3mNn/uNPIwYOdYVTNyvZq4rmViOROx7lLeq7Ip5YAaskOkWRofetT4zazSwBwaZ6AaefnkVGQH5Xj0+W7OV5dlwd39yfHjUAzz7ELVFayYMBhg0xq8PLSX/L07nYI+DGNbokrHwLZ4hHdrLXqwB4BCoHIBWNxvbB6Q1U9LlG7nWjmPWzcPKjmxWg9nJoiKSsC6XgJ/xRzGlhVD0n5ZxHVik8RFjj8ZDDAdrRMXCwQa2BCIVjniZ58Z+9kL3ObaVzHrWU2S1XV2ZXBJH2kc+44sn8xlTgrJ9ffrRClCA+cEMth9OW89HSEK8z678fka5OhlDxVGI0DcUiQy20RAq3V1fHDIGsEdgw5U4xoBgpYVXHL5Av96yTGJnncLEPxsU0Ubs6XKqlGp5LAmO2MwsNuf/AwsyxBO526ZBdc7eJcF74NaOlNbbygJ8rsgUP80z6pzfDfkG3q0LUr6s0BO7MHd5gQmjRU6qjpdaxD1AKLWG7p6JoM1garnAIW/YlbWKMPkubFYCw6JWLa26UiH4QEDcFxzucuZSPwzeW2Vm7DSMsP2d87nyW4zDs8FWG2K61VRi5U3aAQ8jj/X05d/jz2kko3lGtX7Xt0rsMHVSdXdX6Czl3KBWegujQ2jBNCpzUBP5x+94IY46mLOq7aBcYqAoagO4e2ICv+jQz4wqgncQMegny5JM8Q15D0zUPHmou/mWGlBgs8GEdX0KBAiHLOJxehMiHGV4GbAdn0+63YwI1hCHs783IORWAARi1LgMvWrOCve036eOcKFJDmzCMiULMldq0tJBOfPlk77s3I18BtnK9dCGBAx15/6Za5JURoGcW440NdtxbptWcpdayY072MMervei1vXq1vP8YY8ZLuOine5RpWnHb97tUDyetb5flyFX5YgAViRxQiNu5x52smq851lzHdiRCQdOM0arGnYcKhvBrZTgQf+lKQiAyANCsqyyR41+IAysDfK4Ehn4J/bSmDEpjZpKudGjDJxDvVpK+VnmZ0uMIjOIFAPQleoCXozIMrsqirEWmS4pfRCsuCULRbH2+IcRTB74GlLqCgxD3j1hPgmaaShZUaoPhvUvmIFcP/+LQDD0/s3WDfF3V0PbEY6MhieHVv+oWhv30AA9DfACB/0Eu1JSCOUS16tovJlBpJMQUA7FYPpa2a9tCwVF2dJy5h8j2aGIAlKdmfoKghw9978Y8Cu2pEer9yf8nczQftwQxeMsQAVn+7lXMqsuNuuXQ/e7h72Gl/4/nU819d3+HOu9Pp9r7PSp2MdAF5uLMnrDyUeyj/zGrCShU4ZPXG62xz8DfnQ0D/fxiSHxxU94Poz/PM6lGi/E0fHFOewm6Jcf+b69xvC9zt7v+9/Tq4UH1aArQ6If1ju/FYG+nE7aHnsPxbZQX0m2nx0IPSV2OSS+ctEE1Paxw1r8M8e+o80wfrzJyz/8ROWn37A5ZdPry9S+XunV9S3i67FzzHwbPd6OYLElbKr5mOJU497uXtuwTB1f+Yz41UhVkaqBD1WOEgWllUC6hh3pwHU31tv0K0QLiamY5shZ40GGQMwry5YN7mFLavFwDRsPNs20FbFp7HhftvcNrQpLqpR7XFze4cZzN67fNYvPrYf33nLGI3Wb6aZqQ4AJwPOMHQDlphW/8dHqCnWnz/l2rxT/yzbL/Yf3nkyQTkMYxvun+LSiCdf9O4BNbTlEd/mOCjTzW90t5xwXleCkLRJTDlTtht24Nf/s67/bQ7013j88TPupDkC0e9cwTDuomzjFsD8srrRixE5l7ErCJK/qc0jWd99geEdBM9/bRT78QD4KoI3AJ7F8ATmaZSnGLCfoiRDvftpwcuv9Z3pyOBFltrx/Yszeq2ciLzyE3gCDGjhRM+VEUdzYm93+0klTiMNxhmmoL/vYbzyKBwLIO6/M3oyhPTwvRyfFMsPbITrK3b3sZCmSUaISven0VhI58Nk5L7yPOw1E70VhscM3lQ6gjnrl9dg4fHl/ev3T/d4+XbO8vQu/MJlWYDdcjoB5sZWg0E2DxVn31F+f5iiQ7CcluT5OhTLqXv5J9vAHoNNPPv87u4O47xBTbFEr7neljBSdzRh4MGAjQZZnPENM2yXF7THJ48ohsI0aFicYeoYWO7CER5Gq4ftdAYhAAAgAElEQVTHR+hl4OXyDG2eJcge7g0XQARDDYIN60oD17MLawPMXmA4hVL0DWqKYfdQZbaDwfRL9B28B8ydIEMV8ijA14dkyO0RAJqXBDbB5Q8XFfbNgCdE+TsgnedwZal136csaUxiNswIMAL2JlNaY+6phVLSYp0ScCVCsMyiQczrSFZHZdz/btGSpWZ829Vn56BRXp/P8HPT05lkNkCUQaGmZ4VhQLo7h6RPaC0AKvpxoVfGJch1Icy6yf0PL7/yqXhvKqk5ilD6mFkh8VyWPafBqps5OMgABK/8INHsRQnsCPQsQJQwGIX8zB/baOiKIbQwEnVxpb35i04DkXWFJhgSmWripYMMM6iodXcCdZzQzEEWgDBShKLMfmeFWNywtGWvThvT2WlAOqe4F10iuzuNLQUUA2CuezVyTaWLezDpnAo2+SwzD1oXmCKcgnNfPfqTFvwAvuEwRwuToURwgxmOkq9S1R6vHuE3P7mX+Gl8ar7/vreS9JOnSjWdCzP70lJO5FMr/eY9/KlLMQYBUcK8L17GPHrMokVlgySy/fOYTUonoJdMiowb8SjlTQdk87LUvRuWdkJvdGS6MuaGUduNFaSBcJCb3wC9NWzMVK90IHPvcwtSlkgGgjA4gA4bl/1tyuQoXcVe4WN464U0Duca30CNzNjOqWjygdybJAGeAkn+xluqIp3nY2xZSjQmDaqQZkCLNZAxMGKOGg5HVQGahhMZEdwVRvLQHsem8W9AFoEZ6T0kT+wzo+NpFLMRTmMrfTbVM7ARgTHuWJbstwyYN4oDkv/VdffpRYZyygRzXugpsangmE26IB1PZW1+d1AGcX9AR1+Mx5wOusjBWBfOfwXU3PjaI+Do4eEej49PMLEoe37BGJqRzGaehd5PjveaeN/KpZ9wOt3lPo7u0fknNWzb5sGD4llYq/lz93zO0tiaMz1CPvZZM+Dl2zNO93dFBjMLXSESfUAN2LYFqp5tv63DjZwVVFxdzrftoCCTu2Q2XMg/Ma/a4FhpnhzJAAVzR6qRr4Zsw8x6b9JLBm+C1LyZl3LfH7E8amazZYIAs6f3nBydDlcOp3Bsz2V+DQXMvajG8PwpEpkAfa8XCeW5r/UGg0XwxTTu5o1LYGa9RawTJINZ+LpnMHkFiXE64aQRCNIFbRsY7HOuinUMYNDBNx0e6QZjRgwxBnGO5dNcxwpekRULqgzLzSEW448Ia2q0o0vOuwZz5TqbOd6U6ZSu5T8zeO5qu0ruBtcy19BpKGVfBOG21qDS0JpnpNuYNM8SifUxk44KfwOiepfj7lldx2mRhhk65WOh515fHfQYQevo0FKhJTkgZtBt3aNCp1GJp6d+GTw4HRkhA1D+LPgmf7c51j2mvoWrLWlmxqhXnWHOLo2IFJO2x0wqtsuaSkcMsMs89uxTf7Za/B50jt5yKmxnhZ3O4CugkZEj8QwNTEsMS3lU9ynXuepSAjAznnM8JuKRf9/e8YoZfRG576LzfKaxr/JKTDpMEqvO4vic2KTbo/5mAujwDCkAEUQ7M/yc5/C8WgQ7EvP7T60lx+N/6YI14j+uLZKfwXzPBQVn3TgXu+Xa/5JLMTNF21wb45kJ4ymd56EvDg1MOzavrlUy0Mc2nN4cvCRvqS6hfSDrfkxTVs3Ts3tTQIUuMCxmQDQ/lnt9mHIMIYMZsq1GnG/yYfKJK3qMm9Hxbbed59zHfVAi36Wcj4BYUE5N52JWsuqGjg4VhchprqFF5l0Kcn/mWEdUBzphW1e+HJ/1e27De9MTx3bxrDXr3Re9CVri3HiceUUWVfJEi7MTc3lB6B3ZfTjW2XmuKDwgEYBFVcBhHhTgARBuh0KYOIhRyNOmZjvxOtsPiAi2yKRpy5K8J6GB5HCQ0pX3b0+wJwXsGQpg3b6it0cP+JEpIbdtA0zQm2D88Yj2FuhvDWbfYHiEyBN6+HiHGZbIBuQ4pAmwWdrHSPa90UYxz0LihOT7SDmh7HtxoMmpIwDe1mgkH1LKmUmC+Xtmntv8Mf4I5/nVkw7PxTweXlbYE5jKKYzxz1daD2wWzkaNKmCNgifGSpvNCLmN9hWGd2kfP9rZeSWeOZ771z5tigdzJ5UA2GLeT3b76392SzrLqzP9pazlsa/2TVgAZJUYYEL7q8+IB2qZfoXJDxABzr9+golE+XBg+8yHWJyV2xMhbJT50ZtX+mFsf6NTnY/BK2iAlXXm6ImEsphVvYtg2pxSBu+HK7ufdrUfLWhuef+E9fNXeP/zjst6cV79+WviTVYxqPdIeGi8n8uK5UdD7x+zAlwDcNk2nE4LXv75K/r/9Q94BdwFZorLxQPAt7HhFDcdOmAKjF8/YQvOcv/TB1z++StOP33A8uN7rOsvWE4/5nhOp8Vtu4cNYeuUux8/YFkWfPqvn49bdXVR0l2/vqdLq/IxXjDUbaS15vCleK0Gz1T8v8PwQNqnjPK8GnBFpp4KoHzNZUz4UNwGxueHDIX7jLySFv1JfsB1UI+bRN5llm93kaIYw6uGPm8XnC+r+0fGwKoDqxlWHViGt7Fx/hTVgD6+w/rpCxa4v4bPyEoxEQm2/OMDZGx4+a9PkJ/eh9xQPP/ye54xNeDOor0YgK6GpUkGZHDzdDDADpOP2wXAyRO5Qq+dWxUBrhFBYmbeNtgMz5cXx+TJ3W13yvhXJtJgf37+p1z/Ngc6Dw8VtFRiURQGYa/PBuktIl9RuNlUOG5yXhoIAFwrh4fB3Ho59vLW228hWG+8/nevx0QDdoPFTKc5r9MPt1KdX78q2Pjb13+DQqfA2QsyXqcfXfQRwHC/Jfbcz3yAvMhuINijUaUC01tDpTIJHMmjrkoRmDducuvlfO3vLmypfyMCPDzdYz2vafRIY0VGvlpRAhECRbL8/zT4eIljn5UbAZele/A+DKKjlJoWNDmhNy9len55wbL0KBncU0j0JlFCb4Lsbb3g7u4BLMn38vyM03IHs5nZk4pwZAUkUIeXq77YGSCTj73ICPcGjxQ2YDyf0R/uQKVvGoufAbuP0qV3M5MgyknT7pRGgFjS41ZRYVRTjK+j7LPBngF5LGk4j3XvZf+7lKCLBIPlM7sHT+SWASLpLMihuhCPzAzAywCPLfrjps46QUkNwAD22SiTVdaBVGWKCnQrcysOOmMp4IgivxgMW86dEyTfTiM4bFaMwDxx/y1+9L3vm+3LwKdokADNk8fU9fCV84oOLSo+LH3BspwCEgmGjXRQiWFX1lVoTIl9rNH/V783eGln9u5t/ppXL/CAlSjmD1ssAX1jWX+IR0maAm24srr53xs2qIVhOHo90ijPsoc5Yfa4K/rC7hJJTWqeq1mNoVgli/EmgK0IwMjDVEL2/NbLSAusOxBsUt42xTZmyc8pG5DO1yYSfetuaJtFAaon9QbBgJlJNK76+jrYlAAosxR7rElRvZJfw7OcprF00pjt1thSAXQwqF7SvAqnOFO3+lTKjddM4Ebbg5G2xVgUOnnHUCxdgUVgHWgqsOYBJLYs1xhJIlixNTQF0DXn5A/P+gMRIOIgu9eMa/Y1Z3nePnuc9zD2ZHlks8wog3qwo9Gw0UIxaUuUzzoGTuwNP1rmIphZvxKlt9KgZObOaSTzBlwUYUg4sqLnZo82Cnlf0oh6L3tRV3YgMziltQHRhkU6NByzdMozg25ShK8BS6gP20BD/9HQVTPu1Cz7ZfOcz9KhkuuagjB4AEvoXykqqXSF2hK0Tzg93cfEKPMekxcUGs3bj8wE473tIC9B5ci8uoaYZvno1gTLcoeHu3vcPdzj/uHe8c26OtboXANgrFtkH1oED1HmWTzG79mFJUEj+KUJcJ5ZU7bt6Yy3aM2zxqsDsFIjbGZYnvg8hIMweIDqwLr6s9wQ6/cbmyZtXtv6LbFNDZKbWZhhWB9jVhooelVrs3WLHe8fmdOq0VsUjscgjrm1eVULbZoKcGwZPAOFxEUMEijFbBdHuF8vy3/HICHnKxFA0JDtH4CJ/TPQxyY/NguTRtELOXcv46e76iVcj8aSk9a8/HGWhy40GW2jGpj5FmX7mkCkwzNDwgpZZAHpukeQFMfTWlSIUS9H3ESyt2PqLzKDiyqumT8t8c0iCzoWWPae06s192oK+5NKjOL0qV5qD+RhXIEp43zu8b5JBB+GrJwri+OVPCR4F/nXpop129LB4FnC7LVYziwmjqycS8r781nXCp2XF5wBBvw39SvHPJyF8HVmNscALaGH5PdEZsZuvb+ETjeXRWblDa9LnOdjnmjsfzswVjm8n6X2QUQiCTcc0uSr5TPzHuT56RAJnm425dzukQJ+qJD55K/5V/AqBmQyI30ufQTuJV7mqsb41TOL10h48Cot/pyXlxecLxdsazhQhya9+02ItyhrJj7wbPTmpXoxW5/tSu7j9WtvFJ7465YVJ4dTvjtLxU49MPVBO7wfNAJ+DwBEs4Rq0n5kUInAdf7EznSQxuhU3alecFeSGQUcyTcDeebF6h48M0DJQCWvjP10p6UmIdK5P0vzt+Q9HI9a0b0PG5EZ6GNgHWzVMjLrasqEuu6FIzFhwSy9FsLzGM+qvHbynHD2F32vBh4yYKLK5Wq/ORLTHnEhbD6WshcKaAt9szxn3zakBHPFWZw4Me6c8j3OauADtb0Md91HsSNfc7zc5OKyLTnM9eWG8dBNeUUmuJpAt8jUjp7nV+fE3MbjmC9f8mxtxbQV25QhEnpAE0l5ZCGPGcjm7ZQEW5afF7CdokYTIhFB77pbSyNm4Vi0aLHqpZjFPKjQYI63IplgYpOgIUipqEBaiqot9gTYgNpL8BTft5dnFgU/BP0ibEcqM1k8Iz5k7p9EKyYGBsT6igiW3nZtr3LOqSMUWuI/5SB2UmPKiXhN8RVLe4edzl/oFdFGFHgD4GvwEH97YDfNVy+Zq+Lmk90J/xcv8tfaXgYG+eHdX7r7fmVu3/6vzO1796Nz/JazvGac83m7328L/qvP14YT1bxCfFMILDGnv+yv94/vMH7/EvfClIuvTD7lsfy99TmSFue4m179o978yI7t8EuOhQFn5YH5zjznqbTkjV2fkzY/294Jxmd7dRuOf3dEcEj74LpY88+s2wb9VbH95AEt2zbSWWvqmeXnf/6K/vE9LudL6KkjEwSpG5kB7eP7cEg2nH81PONnnIo+UCtTEv/rNrD++jse/tePnsR3wAbx5aIbEivMTHSJzwDTTrMnySOBXj/DYn0qAU3b2z6APHEUx4ApK4yvTiAFyfam05me2IayvzV06dDeUi5JOJl771gWJiJ5BsAwBpdPPNGaO9oZDE2bzihBgafNk542cTtuH4aLeYVDyhhTYOhv2EbPAIehmuN2/q/oP33wADII+j/eQ6Th5Z+/4oXViMoZ5P51AKd/vHfnOfcqdKjxxx/oH38IOez3aP0+cYfBsK2rtyQs/zVM+wBguKyr424Rr9yHCGrLb8w9pyz7N3D8/0+uf18PdF+JLP2q6o6zKf9ntMd07ikge1B5FEz7knOS2TEboiRjit4A/lcpE8XRAB7da/HHV9/DDR5f/4z9X1vCAMy+mHxkxzsIGhSzRDsANHuLIX9g/D4gH66Jh2rfF/F+Jw3XbOjVod18bbIbxxbBCOWbj1jf+HPtXXwjWUz8NYF5oMj8/oK3ERjh963O83x+k4jCZnSyOuCEoX3cPRK0ZhgZJ3ujcxQSpZ04iHwMFctw6gi83KodPgZgeFM6sL/FMIV9NvT3h9z9Ixkk6fhatu53PT9fJtMvIF26TAXBgPV8mU6deM3ES324kcHXzhPWBKeQBJuNWR6kdZzuOrAGGI4S0hoZW953m+V1m0dEhaI4hkcqn5aTRwyPDb0vThVDo+mMAKZR2uTkxlYDtssLzO7RTiec7h+xvlwSoHpJLvVQXzPP8It5b+aljc/fXqAmaOalbwi23bj3EIrHlyhBGspWKEGS/akV7ckZfvbdhjPh8WULR8O3EJSG9vQE/TYNaL4/k26ErwFhtPegg+xRv5zmCSDxFdAFYQmsOLGhzKsOvz/7obPsyYi+uNG31XRkCfErOtuRXzw3z1WMh8qSxFlN3aYCQY6RGZgDtgImI8ucCis5FIPENBzCs4ZBPkkwwzH4EwUC6bLrqzRH/321aL5TBCwNUIh5JngDFgIdIAFL/k7nhnggybIsOPUlHSptNAxsUPVMzsZSkyLo+TumvGrTwJLOX5nl23vreQaldUA8UGVp/ndbogwhzLMhhYZrQLpnWPSghdY2sM+aRhlgDy6xLNukYageRYlvsTDNmMGC/Cx/nyJx8tfqQN/DG+S9fb5Bv9HLlz3iuBYWNNYAbEI5I0l3NOA7+EWUyDNIG2FQtP0zK63syOZIQ5wrKacqeMGLWQkF1cG0zybKzwMQMczE86KA7J4/z2yumRVajbVhJZZMiSp0DCk9kOPekkafeZapJMCPJcZQqK0QcaefsItX63P3xnCD185ZEs+ER3Z3J1j/fClzl60K4uwsy5LGI88yX/L1zDZvDEBxZcWG96dlGXR3LrshlSPi+XEnyFxeGmCdzqK/YsVZQR8Ssk9CXrrcmZk47H8u0ct3VN5oFoFrcW5VUh6xbDME0E2gtmKEQ5f8wPoSrSNc41nXkdUh1PaKqjt9AW/VoNPZgil/2KNvG1sGHdDJ44ZAL42ZZ5Z4d+ikYxrtsVd4lTltOukbUYpOGSAQVQ5GVLToS09jOAxYXy5oDZkRfvf4gLGeMV62cE4rMgiJ8FDcoZ3Kbzg6GSzY+4K7+zvcP9zj4T4c6MEvts0DMrS5gXA7dfTNsZxX69lzKol7ruuWf98/PUEu58yCN2PmO/mAYZb3bri8vOx4YMo5m2cPFs63oDvSAwCs5zMGNgzt87wB8xw3FvvztbF5052Rnj/N2EJgH6kvwU+mQ8VLXlrzsUnga8WkKxUL2RTzapLlG2UgneiJu1GMaWUaVJh3RlTiEK6PD3InM6+1KZcf6TDGDOTZO8/NM+lhSY8txs9AHS8pjrJvlFvV0TQzxqQMv0GyugQn1J3Q3dBlCt2Ks05KpmmU/judFpg2jKWjt4G2NXee9wWCs8tGPo8BqAwAOuhTSXdcO+Kxu7vElTV7ND/bXLcSYjhMx7lnFnj1iizJWfaW8QHKqjKCWY0lBxULV+mhyE7/PoNMnBdmlS3udVZE4D1p+NpL1fnIqYulQYebV3qNtyg1zO9TH6gI2Mp8ctwph2N+GmMSQTNWK+JjLCd6REkiIYGlyFnbv9+CBzHzbzr1Al+X6iS31sJ4e66oYqZVFp3E/WixroKdPLAQbnW9dw/gSkt9kZ+2uQTxWVaB06Sf2cbG19hLg5PQJD4zxuZZrVElhHrJy8sL1ssF6+WMbVsxokR08iIzdwrG/VXLTHLR9pzmeoX+5OLcyhpI5XcofKZUTkwdxJDyrv6svK3Ka7YEUBtgoOfENTPoptpU6mvkk6MwagMKjyCWtKmvgWcgnOJQeM+uKlWD208G4LJfBd6Nas6tATMYFrPSCYML9y1CeIZ8WNs2MIZhUw9AHJsHHnnlHcry+awqL9KmGI5XA+dY9Mbc07l/zG1OHU4k56llfyiDYTOAkXOZLc/KegZ25DMlln/I8DVJ2xjS2X3sCcpA0imPyiQK63To4jydGCUrSxlXTeCRssiz60X03Ng/q0QFfdSqRoGNjJXoliV5p5lXClAdntSxeQBTbS3hCRJt17rEYIdqAAbYiy/GNwsHtuNTC7nmW+e7y8oAZg0tSpKbuU6NrmgmGNrRRL1SlM2ALsjcoyACAMAWPdLjqMIeHx33Y8C2DX3xrDvpxDGsdEEsLkUOx9hV0PAAOnNOTaLqXciHsJn1dzzHgLUnwL4l3Yk8uc1gps6n7PEgBt3hK7b78znyzBXcEkGrM3hnEhJpxukmKo7KW9/foKRZtWlHjuXvqFxqgH0278eLv34JXJw1eF9eICk45XXdOLZEpF2tZXYkeTNSHnuAwgoRYHxStB8a7n54j/Onz7flQvCYFPucWHn7IGbwYJ45/8chPsLK74+H7+wd51XqS3l9N+3MuD7ScV5py6nzOjqoqqywknjxlPxpwFJ3M/G5bTA8Bk5/FssglDit06Yl7lzcBeodyGc6Yvf8zsg3wczzGG0ESTLEzAJWZHiczXUDJl1wLSZMkPlaWYsjDeQSC7C8fYPt8xd4tUun6ocffwDef4Z+np+vULHr3MmGvf/GzHC6O0HHwPk/f4F8fA8Rwd1PP8Ta+OTa0jHOA8uPP4C+kNYaxn/9BvvoU14MWP7xEevPv6F/fO/rvTSswR+XlEM+mst6CZ7hyTkvv/4GA/D5n78AmL3Pd6tTbFZVN54eJRS6mxh2or6y9nF2JvI/rHd9Ztx94qWgE+JaiTGwnUUIYBNySaAYI+ZrONBE6E3eXmqBBe7orUeAtLeKAxynmWoEp42kVwHCP9NDL3WG6u1pNtytK75uG7bNA+M/iVfye28DXeF9z82r65qG3WwYzucLTIAtWgKmTwSYssLcLjfUcCFuCfBBHEb3++nDe/eJgTjTz9m6bZB3b1KXA7w6EPmBqcK6YF1X3JVnEwMpHPv//vtnmHgrvCalwq0i7dqVjubf+5+vXX/2/r96/av3/bc40NOwQKX1ihsF2I3+y613B3Bjg/wNKUsA/t9axJsDjGHG26+VP/87j+BP2x1bAoV3hcFg99vxqkLXvvvJ79/Jyv9x+P2v3Pe1B4gI2g8tHA5HRY8s1PKzfE9BpRhlP8pK2WtRKQ5Y+9Iwxq05yOHv8otdT6EKPXkbARpfDP3DbSq4Cbg4t3iPTBVAhoc5QwvFrTYDiXuKNdw9PKC1hvP52Ut0YhoSezCyHv2eWxiQPELXy5lSQWsss9sbWpRqbYSjuwnM6K0mYXiRmQUP9sPQgX53CpCjxQgQIs7cyOHJlxIAoMNs9fOUBhXnEVtlvoHcyYi9HyXSWVi3zvAN8vgQ/RSRWRoU4IZvMT83PsAAfVYYXjC+PaA9Br09G/AYNJJjphJ13F1Skt8zDQ8E2YYUSIUYotzJDeYmM2qvRY8rz17nfKcDeFqvp0CeWWics2bEvMIJrwUtJIwWgJnnqgPjsoaRY2Zlt87FiDnbBNf+PEvNoTrrqw3y9vXXOMtf4kFVaxG2iJjgHfGTmecEPstpwd3dXRijGzbZIOZlskVpcGYGRRiVZBp7bg1up7wGIEVr3oqtmQMT6VgUMPQEPE0ke/WIGMYw0Hmlpmi9p+NsjCjtLhtoINopcijbxfNzY9lo2ISVXvdGUF2+VG4w17RMnHI8Mv+unO908KlGkFCc55zPAGHxDkJbNCiRGzSwo69b6L7szyvA4Ni3dJ7dMIQEX3PZ0nJN+QznDfPM08E7uY+kYkt8sntirAMQa9784PTgYakcxNikNY9WXjoW65iBEC6fVMz7MAGwHv2ZIWji9AP2yoKXbZRON40AXYInw+nBNHutuzPW+ceyLFjuTtHj95Q8ui2uJNCBPteTe2DptBmhCDCTTAB3TMUZ60vPSGoqSTUARmQqULv95JmrexDnmRluIx32Guc5ytFFxQNDcSCiQdO4zDOh0CHwoC5AVDHGjFY+tc1LNYd81+ERxp6B7vykBe/lORkikYUJDIxp6DWDRgsHL+0WJfsj06tmUNZrKjAxZr2mPT57ZuNw/SKoJw2MoeyABl3LgMfWBbq0rF7DE9+6t3Sh0uyGxj6DQMozs62EiAdvsGebSGT9BK/YFNs6MLYt9hBxvia+gQEvzy9ujN2GZ6cj2jeJpHN7PH8Li3EYUlVhxcLNdXKbo6aSifKJeoYpEyvvrMa9alR3XDDp1M+uFoQ76bzinGm89/tt24ge4M2zLMWdew2OMfweDWje+3OWzJ8YgvPwtkAtzgAAofILb6dEpZt7nHg9icnpJOSQITLmcnn892zdFOuTuJ+cn3y+zdj1eGBZ9T0+BOCVORioVuQ9sRCz2uSg30lraKz6YHzCQVqKP3Ovc5AnNOzMwdRzgaju1CMwpKcxpzdvZSXB70CukOWCCw+jkSJ5D1LW9thjYaCVtiz/aPCyta17QGZWAuluxBljeEbv5saXbt0DKqTV7jbQNqDs70paFMmykyQA4qSqp7m8Rzi8NJ2e27bh5XzGMgbmt1D4tBJmhpHWSlYc+OTMGpw9m/luAZ/FOnsFA2xPC8xMPfqn6jne6SR51udrUj5P/iviFbu8IsKRVxuqVcHq0CsfMQN7zPt54Vwk71K5l9N7nE9+7bAvPueah1bv8sp16+1IIuZ6MBA516GsD4Cdrp/GV1NAmwdXtC2yuloEg264nC84Xy64rCu21R10U3dG6tW5L7k6+wFPXGvQbcu/+8IWZHUjcpHBoHvE2kLkatXouMo1NqQMZ4W96iTf/Sx7WgMoqjwR8i9F4Q1RPSPogvdxLGrAaGB3S+O8bJ4DTnPOZP5uEKgFVuE+1uUMehYAmnyc8sbXsgVebU28siSTKcp+EMPm7/EsjfKlWRVM2bpmpF5Lekrncw5tll4XtJ3crGe06gnUW/l6vWd18PPzFWPVXuzU13PvKg4re0C+b+VZuXs2vSw5pFf0mBkAFMHKQyPootwHld0VTsmxqXqmNeV/TtJ/JvYIeuYag+VrQ49L2SWOTduyuPO790mbpaVA7hdnkKRf1yNdMXnWrPC0uS7+GadYH6vrOdHvVhQ2GtAGMFomq3jmu2ViRd5JyprFWk4bDCKQVuboShWM+j7nl/JsTw2p/1UZIgh7Q0y4y1MEyn+b/O3IrsvvfKs6C/0R11YsF0Ex2THiPtfExiVW+wKRN1j6u/lmK4sVXxV5B9U/dmcKAqxXd7591aml81zI+966ySkC2/bj3ePmOaYcmA81bXb+gZw2rlBdWQTDPYDzDTkoN17j9fVPHAfHjPO/el3N8eYb+5ftxsd2pBQ8xwBo8yoPXqrzLnE/gNCXBKOkrx+OL/EAACAASURBVBsmje3p3OUJQMcqk/Wux2i4bd+fbIkgyY7vIMEOcMBxc4aEbMcFydyp421vfHbe9Zu30K1YMoZXG8+GBSkTR3nr/hHo7X0cnfB/hL7ff/qQcoQBoxNvuhOz9xnsbqwq9hsm/VM+heO42aznxxEPNUgD1uiJ3n/8AePXT7OF441l2P+9Z0S2++2wk1Y/azueKGUDbnzzBkX4XosQG83PHH/SzuE5fJJCxALHkVazZZth97rrTcAY4j6WFglYvWdraNXQl4RYzCuPNOFcoz0JLKvpjG1ANrdp6HCb2wOAzwAuY2AJB7rF+DdVbPoWY3zG+vNvOP34PmTTnK0h7FMAtkjKOP/8CSUpPvCq/xwCnEyylavzwf2Z4h4hcFlf6GgHxnnF6e0d1u0CO4X/hYmOMoN0h3mlPCJdBrpmETdMLHOlJv0PvJabUu5vMPg8KxOHgcYMXg50mYHeveQdox9pYJIJWr7/PIJ+71OxRAbwypYueW6vuKC/3fesgcP/Co+uenjvgOGPz5//0vyfzA2xX+MAkYny/4ovISpoQnAy6h8X2G/v8O7/eQ+Y4vL77zfvv8yho5sfhH/lmgl1e8Ej9mb3eoFlPv7oid74uR3LE9x/fF8AsL8GNcjCXgqGmkngDNDyPVfQ5qGa8ouC2JlRi0O5nLxsFJ0xLQ2FHH4A7Mj0YJQ6o1ezTNLssJSXffEMdE/CJxDbf8hI5BWJcaQ2x7sjv9KEY7l/QD912Ka7rL0W4HRZTtjOFzy9fwtdPZttWy+w1tDj2a11F4jdez23k6A3p5RFOk7L4ksSZ4rlg/viz2jRH51MlBWDKegEBvTFHXqq4ZBx5RiRNbCcTkCTKFEmWKMXkccuGlo/AXaC6CXLJ5lFJF4ABug9oIbTO8HLry8pQNJoWhQBDxd4gsjMJGwc+7codxpGrBn5zw14QL7wjUqyI3OlM75Yn9TcEdAyUh1AE4yNJb9lkodcs5qkW5YrLRedcFn6lu+XDMzjl9LIXPljKvExd0QgQ7RHWBaJb3pmmUYpGU1G6WVH5b7teHdG+zWuuoOJ7FfWJQwglv21/Ys+V3fwFaN78BPnjK3wRsv3vnep6jRAx3176w5KMoK+Ot4ciLLSybIsOJ1OON2dprOOwwp6dUO3ZKlqgvtU0gsDaIgqEEK51rMlCaLkD3qHieubrVPGzftOViuQHhnYUbJ3aW4gH+vwaggdAYyxOw8x0cjqCteP7gkxv2Pm/Z/TGFR3BqFsEhTF2RMAMqOAmTrQTks43eLeLHFqhI8howmudJabdyN5ZBNEewgqaB5JmSoXDj/m6/XFA/XslSPxMrR6O0Iv7QBBDNWg6T95dqXqk0k7Nono+t6wrMgDrkca4Zj3LBBpURZsyosWr0kT9NGho2M0RdOW4NOGBv0BEg5jMe+V1arhrk2jYpZWL+fEDNjGim07w6J3Mo/ysiy4O5387CynpBuvHuSlt5fIzkAYR5nxSgf2GGO3/47/XFb17uczA1YOeyCAO9iKETXfCxzJliRD59pukQU+Bmsd+ncaehgx6eCWQluYe0xHQRgHva8rct3o9NogOLXI0javaEPHlg9dYIE12ZfSg2R8nGIGtT75bWQKu7IXAwGyt1+us8B5/pgZUQxW+Z7xNTFJnFOXW9MIotuYRjsRryCzuIw0a3h4egz7mQFjlpzPIMiY9xgK9IZF3FHrcgnJPwTwvpjRJ1eHR1xDkbSzjS2CI63Q15jGSgNOj4843d25wXErfbyJp4KGtsvAejnj8vKCy4tnNoa1CFDDy9dvUUSA+gANnBXlYieyfP2dt5vSuWdJblv0yevLCRnQ2Nrcx8CrDQYWUrqWggya2aCIwI0haEsD4FVOpDFLxNG3aLg8KyYmPiGe6j2cuDvOGXKC1QiMQB0ZHMbpWwmydKqeRHfU4XioRHbzC2memMZLPh8wM+mWa6sWinkJYOJNxTP753iEQmA+gy4iKqblrIjIzNhMPMbs48A9mPK7rhsDwzPT1nwkDF6lw5zBnt6+peVa9bYnAJedFmsf1drEg2A9nobOjBHOcw8UPJ082Kkvi7es6R2XdYVIw6Wv2DavHDMQZ7YYwzf1zAovA10W4bB3dCzsyveDRhItTnTFtq14YTup0P177BvxgR7wCsH03h5Q8IoFtjSgx97UwJwZ3JNfmDRbnjGd8cZJxBGwIKfI1MNsB0E6lLanA6/o6HJuOlJnpY45FMu51bXn/7N9yI66ym/SsL+jXFGjP0czEIa46ipQkgMXBtrFvZmtehQieTAtM0iJAU1nP146GHVjZStLFYJ2GzF1r8V6SXyqwwM8tnXFyn/RA3uM4WspDYoOCT5B57obMSU1Cz+L/vvY9n1+rzBerq2kXMyp1jVE4XmR+cjbSPB1VvCy8lX2jKw8cb5vk/cxEIEySGXeH250dhkAD2rjcyT2os0dq9UpAGSpf+T/64Ig10qLXKrbL7B0YjY0aDNAmc1VAgMiA73HWef5zVL/5A8MEETgjmGTb2gEXY4a8DH3Tli9I6rnMJiXAVsGhYq53lZLGmGuwdxuyh/yfwtIwJGV00f9xmYVMASunlnf8fkMlJ27Tb7g2AQRZGV1VCnPahb3vKaxHzpLoSbP4rhvMA9zQ+kM1M+dq3RZaKAaNIxjYY/poNHQOVUtK1U5fQisFd5tvPOeZr0KxgsaBjzrVWH4mvJ251CPc8lElEygJgaIDc1AJhVo91LnWxvYNDl1zolOo5QWArSHeyRMIleOPa7Yj5srCNre6YHVQROVOcxf8bUwqD1HIOhD0jNpwYCorPOUuoKaQRRpv4SFjbm1qHLYwu5DRguQZ+VNJSqVmWXgRA3JrVODvIXZF+hnw8OPC4YpCWFHX2bR8xzv0Nq7ONNfAfNQnkPC8Z4o+ajCbJrV130ciQnF7bjSNOnRK42R7wZesga1LW0YirARJp4StA++TuP3kXytg+FH85rOczvM+yA+4jMvk7386fV89X1+Uzj7uRbXrCDe+P4z6skmR/OvS+qJhoDOQYH6WTF+UvRI9IIIts9/wCSOffle3lPmOZopEdN5blnt63Dp/P5uenm++ULhGzcWYuoM8yQlzyl4MI8PxyX1e8iWEXyP7QeeP39xWZNVG2egj8g7LO//gLKUu3jcDkcnAPpHgbR3AAStTz1wqGblsiaC8y+/owF483//h8vKbUBNsUT/7W0bKfce/+MnrNuG7ZffIT++dyfuT++TNsZQNJvOfQC4/NcvUAB3//iAob+n85zWsT+O+3Bcbq7pjmvs95wbIlbfn9fkdog4JNl9TooexJ2J045qn99Lrf3lOJx2LwnsiUyIYpLPbEE0sX1vHRL2LY0y+T1aGPbmq8kKm2Q7gLfH9Za38EBkiTZWY8M2VoxtRdsGHjcvx+5pCoYnc/zzbG57WeC6JFTQu8A+vMXll9+xjW1mp4P2NF+7oRu+/eevGCKeoBFsOsyKvkaBSZZ/fJhtzVqbsgOSwYr8/XLxMuzLaYkqdlrkldsH1224LZKyMDbSzHA+n1MGKtyxjtx9pHxycVUlwZHi/r3Xv/t+yy1irGzcyptkEtcB1pOlTpxSjOEBIiUiVOncyH54r63eK2/8iez480Wy4x8BIHn/mxz/9tW/M57Xx+GKuWc525Xjo148p1Vu3pKhf1Gu/ullu9/2EdjH+/eP4aDl64YZsak0NvibEmdeQKNEUYAByG6rBbBRgwn37DiYYvveZMMY/f2ZXr+foPkvXn6XhtPdAy7nF0xNZ15yAhBlu0WA7XJxo+RmnuU9oucqgLvTHd7+8N5Lq58W71lxd4fL+SWBYGseFWXmCsxpuUthzNLtXOtdJgCQJXZhgDWAhblFgGW5i99DIepLABdfbANgohFtfo+xrYBFNKsUxyp6AUenWIVzrJZ/f1j0zngz6d+ZOfmIQewx7vOCVE0MGN+if/WDRHn2GUdX6cjyudF7HYj+53Pf1WZ2P9enhwI++YCPsUXaTiozoXjTwV11z/rHdaTV/hSTvulU2/NbydvleIrw1+iNqVETXyCwe89Yc+XBPz9UoZc1FAkHzu0ushuHG54y8tEl7FT+EiRLAcQzZ+Gvc51rE/T3rt16hmDmE6fDda4RF41lodmneZabnhGeLDusAQy43nlObozyYEp2XhZZ6zQa0cCNkHduAA8hl2QW624O2tww0dDVYNphi2LdBvp6QW8LRDpa89AUUQVLwXm59sgMYPYps438jzRKVOd5ZiSgUKEwk0/LzKfkEYRjgGclZb47/hSKbixVNx1f6bxDiUoODOH9/yR5/HcoYffrnuLmePJ1vqketDG/EXA8n8ebzT7GTQwz3Cytv2AULG9TMUKwP2RkJwL/lHWnI9T7pLsxq6nAdGZ9eAJtVOoBPHtqWbCpQmQEzcTIYhFNgbENoFtkpsZYzO8vER3LLEaRmQGOBuiL9xodNpJ2BA1t6Rl4cjqdAJM0wol42eK+eDDFiL6jFr2a1m1gG2s6lHmuvE/6EueyZVlbK2e7heyRAA1CQ3zyQck1mhm+scZ03G+avVBZEpWOTOsNohFocKA5gezKFzPTSOcH8nNeqrxmtSpsWMpkRakSY1QYLFuDbND/l7o33Y4jOdIFPzOPBMB9U/ed93+3OXNapeIGkgAy3c3mh60RAFlVkm736ZBYyIyMxd3c3PbFZMe276C+l2NvicukHnhi7w5FZa+IxHuOdKtwsPAyZC7bIqvRhpJdoix/D341GCqEFngRlvfYDJpi69PokJLtQSY3uiowCEsYWJb1ynzG5bJwmRYAcr6ccb67x/3D2aKdwymzrA3AgFXbkcsF02Wq5c51uWhba9vDZ285cT5fcL6cISIYVIW3NP9Ta7QH4OOPCg/M9LY7aXRXzYCijtPxOR2GHuQnPDzSvQwpfd2ibCx5pQwalEFrRATISFJlmeUVaGp7fqRgHsaDkBFS1mB31HceFRmwvU1SIv/BSQmYA8vL4Gnr7014tMVQhm9k2eqQozq/ie2510cePQpJn2OeuRfSRWL7MwlzW6vgTVJ4Ly7D9ucTGLor836Yj0fLEcGz6mOG5QxmtoA8KwVrjm+iqlIQfMl4tu8rJXMi0so9H61bdInJcI4jlqVizurBFmgxsGGbG0CK4eX3wkiVjgwCeApYLBMJPViIK4iwAHLAacfx5cEvMidkTszLAOMey1vnbMxYPEzWzmXQ3DuFXoWjO0tvLp/jizpvwMFYf7hHHUXy+xPK3aMzcU2gZ1xTwn3eRe39qr6Xn0CToo/1nHovoUrY9IGXG+8RqsfmckNhZq4DFYDR5rqf4xNyeGa+796YY7f1busPo+3pPEx5sL/DJ5ywFw8CEej0veeVaqxP5MWDpyIYTfbrpVY9ocuW9opfaxR7efHn16iizX8Pg6cPC7xJJ3p/HyGr7ijgFanoIL8OpLl/SfLvCBJSglfcUAuwM4LhMnQjaiKVSdnsD9roIhCy0n522ipH2rmn52zL6CMPmudyJTutsGh+9n3JhQ0uvix3vK5VLsMlmlWqRCT5fS176MRGh92ckXSM02GrgFrAZQRukO8Ny9B+jAXhqI13RRBo4RY1HTSM7Ug5LeUBh3nxfC1Y5Q/OFcILFRW6sjpJhNX63qJy1FgQYnwu+ltrXZhHXd8JfPPKPR29c52TzlQGemPDiSiBm5b5ZrY79oDxkeVMSk40Eqw5FtsTnPYmBVmrL/IADE9+AN9A9b7RVYO5SFS7kdpr9R/HSUUoxRqtOIi8MwclzEMPbStUjvkAq7qeiuD71EShWCWbt4EqpQYMYgtUC9oYPEkAopvG2/xZbf/l4dVe7NUHuTCfSYgWXI85U+PZ/s+CzUw3SSJ1kLAsKOIFbt6XjPwz8zTRqxyTApAvZok7OqP/6NiAxH0b6stMmgiEfUSWHUGKxtkM4rvlJJitbom33iLCEg9kpm8/cfL/8fGECPHfe/yELR2pG1CUqB9Xok5f/MrdjR2Tgn7YMyxM1a9KIPwxMFSO73j8Oj3IHWETOd4WpoDHb31K1nmC8+v+3vDLXqDZLzwu7LCLeYc0zMmHX4He3Bpv/VrXVvUmpE4a+hSxyU5dTyUAV3+zXrZRGn+tZbYXhHyiqZeftg364W22kCWvYNl3tPh4CUYDx/vX7jy3cvwhM/xb0TlY21MycFsPYzu6Q4z4fb8KftAT5x69wHhLxtlrBFaZ3Bh8PXhn2rud3vNmmeYEYCHsHuR+Sq+WRuJ2tNC9ySvBMZao+bXIaM9cgssUXNYCrWVZ5rIwAXyB4qYFDZpPZTNPht+vRNA3Vj1vupzMnrwn8gl3vyt0LTzY6gKoKggBpViLTZFJBYiAbyBlSlMlzBYwBkO+fcd48xoEYC7BuLkBYAlUuWfbuqXIQFWoJGBfAcuUq/zEspZK87P1bQgQZuj/6WP7VdUROhK1w+8Bipx4ANY30R46RkAonOdjcyHh+E7KxfzJqOo6ouwDG4TeAySbNOTCTuoajbwmItgHBnD+etvE0V+4e5oyLQBeNeVTAdwT8EKB0+s30Ftg0TcQKW7evTdGtBTbYHz7f79m6eXjLBXA9ds3MKJg5VnvPkWm+t55VGPGk99x+B7rXtXEvzn5erl7AmOfoa6wjX16Yw6qku9K2Rj+gTHKyOWGM7jTqpd5BFpkrO9EYsLmhqDLxYytV9cnj4IZ3mu0R/rbjT07BkCWNxK17GHxzEhyAX/z8tuXbwp+2efhwvbIITYg0g7J2Y1ENzfPsOYEbwMPP+6snBmA03YFDMLVOOH+3nousd+75OLgNeXjx7fvIAJOp2vQiTDPF7ueGfMycdo2VzaAQQNjqyAUImRJ3rFtZQRXakxcqwwmPDKVJkAjy3tY5BtVm0HSdEiwO9Irstz7cnippNPVCSCC3Bec7bgCcA91h/r1ywHRhYfPC/QMoBcE3ALAM4znEWQhmLfT3ofvECyAnoGfm3IhIpj6DdZp7xqdOCdeiytgAOS793S6CcGGMby3lSQeGs4kbQuHaCjhzN5vSXIjrRYdaFA1LkLajI+PjqJjAIE9lCmyFZNLJM6h3gkzOshamBdX3DikSsG8EAgTCxOMgfUggBtlGZuN8Mr233IlI4TVMPJEH98wKlEkNgzbq8NhSwOZRZub5OmPu3k/PvbUNhx50Q+tnNz+1x1wsiKTWfN38usHD2xjSye6OQ3ISwQqhKV6jAFZTs1onC9vOPRckOrl63ZjosbUyQ3uTF5W1cvmULANLcdpU/qiLKLossjTbTNDOzNIxfvcmiAnEjy3jE4hFGaZUkSGZ2SAh3AuqRHkmjvtjVYcoAgUceEzDTpdPI/S8yY0KpAOJIHPxbOztI01HSfNUK1uYIrnhEwB0C6Qyk4Z7nK7JnhIYR2ceO+4QSy0/UZBB/vh+zDKRfv15OVx9ZjR7oONsYMq09voJAAVkHAKqKZAsSn4aYhT5wvuYCHCGhvWJhiTMImzNDZzl68Uqst7bAOk0yuKsO/SxhzIoqDTOeLrGvshaB8xYdsGttMJ23bC2E4AFCNhQhjjhDE2CC0oJpYQZFmZ/stlWi/vVZnnY7M5RcYkDc/YcqN6GjgD5ESADhBWrg8Bxcu8rGgwqSjRvdbE0upDTnDjDJM5zskqsCiHJq2JQ+RyWK5bOAiWwzkMT34XDe/xGivopdYj0ApqMAmHhkS5dLX9L2GIawZjbfgAwHuUI8faM/7Ey4XBsT/LpKWTKnA/nugv8SwmacZqcx439csjktd5AtuAspX3xyijoWJVBDc1x6qWqrQ847AHJumSrFiz5glzTszzBINwPp9xuZwxp5Wedk2sMr+Yci/GHE3BbFmgQasBzMsFSxXzcsGc0/D9fLb5h+NH4WvrMh9KfvAt5uC3GV7OZzARTnxteObno7XFvMR6214VCfranD5Qo+e7/Ynd2qkqtLUpInXnOMj7nZtgE61MrP+sVURRYQ94UsN1ifUOMuX8U6xyConz2tZ2xoYaOyhGndiGJH7hqEBk2ZfxvwZfjhCE00DheBMA7sCu4ykjoGWnkTlKUHBFftZ6bjHe+i14rxTf1PY7fE8MrzLRgSKt5YjxJftszgOkfGDTLlpLfg0PlwvIMw4MWSAQn1LxiiXmSDQwl7MJsoAFDBaLT9kGgqlb8KDpCGvboBCsKeCxQbF2dI4cfziCnVNX8GzpxhyJdMcsc8+47BA0OKodnVUx2Crp6NgwWCAcAYUNx2NtCOmYc7QDNMNT810mExBwDG4K20F7dsqhgR5FrpsI0nCulSrt+IcIjAnRxd8k0aeZzMfJ8S5/93baoArMqPw0qkoEBb4FjsaAyIJyyEv9Q9UDXAGIVfjyruuPjMx6/HDcOF0gT8t2ZU7vr/d9SopwQnYar4qMYrcWGMGHyhW4e7FawJbRVy/VvWA90d1x3v91/hSZ54h9G0BPuTcm0HSBCEzKEVAOJevbJ4JLwp+CAaQcGctpsrz1sS8JVVcYw2u/HMFuokMFS9njJR9uFV2WtQPz9xM4q9+APHDWnR9d3iWUfganEbsjBSh2VGsSlSKz7+CYBeXkgTmTJkqQ77WQF9mzz4P3dqeeQqtalSqWIHm5qtsrsuenJI+qoZe+xREdmrKavYu8BzogbjcgVInYuHov5efhY4vS8dFKq4z5SVHSlhCZ6Ak/Pxfb3hC96CJg+CsIfaP+0gKIBEot4ICCuniw705+a07uWDWNDMigkbUGtn9bQDDFdRWcEpgcQ++gETeoRmDQUrNDSgQBOz7x2NCD1lIOFc0zEbCQdjNiCB6Au8osNqR7DsF94k4URbM1CLzsdC90ATHZCAZTBgwXlF0vTZDljCXw4+7eTj97ZpAiZCUSJXL/RMCeXFzr8k+sM6AeyKzkvFvC9g2o3EGj1zSaM5wMl2JU6l/I32lOMKdPboNjtylYUM0RqQ2PskKSyxDL6Vzs7WR/qlA1GzD4VWaeJykJuhYn6IXLJaafz8+3eNi/ff/N6XY8J6owEMx5mQ5Htz8TccqHAk35JLGIBwYjq5uBamyGNwbDy7QWMuv3BXlHmJ+/5qgYwPyVAwRAbrU/efyVa+s48srDA+nRxz/4/ovntWODtwT1O+hNLI4F4A4A4+0rrE+3OL0hXL4sfKLI3rU37rslHfwlQY76AA/HkSqHuT1SovIa3/dpC/IF7EEQjSTm96BHkrSO/Pn+dKdPVwfhJ9idm70z8CeTLCMJgRjMrzHlFqH3ApFcCDC/rgqzGVxGoGktarbN7OH8nx8MXy8T22ng2//3GxiE0//zAZXIRLj/xyc8+48PGINwPTbfn+RJDATVL7h8sj0ZsVoM4MwAffqS9oKY67dMzW+QpOOqHIGMxwuHlsFfwK9fg84dcMQClUL6aEPA8YvmuB6jkcM9ebDZRYwGU57L5CYNnJC0yVjig1XHDnobNtvQ74wgD4QfsypdWuuSyBA38VIx3RZ2mQJey2wUakF6L5f1K/+iC1MmXtHApoq05/r/eLzFEuDH3/+Oy+WMq7+9t4QBfYmFLzireDJIyTshfoQqwwBu/vM9oqIHhV7EhJAJwq59/vQVzz68xXhtdPgyJ+bXW2xvXhldcHnv/uEBOmfic+hmS9WKfob/ZoWN2/aiOMEoNNTknzv544lA3o4OLafmn6S5/55jK+WiBKka0l5w6z91Qx0QomZ8N0Ni1r1P+Y3N2Xi6sv6e5y17Ju6zfkoa2WV1KczgHMJ4o87SPmtbifjMXAJlvsevIRdUzkQ4leyRSOz46QYEauOyz3ekeIXIPrQsvedKuGNgu/0KplcHNHABP50Ntz6Ox8iiaoLS/HqL05vXXm5mzwwAc1oH0d9nwnWY1JdHSBcEIiWc+NaIh8MNsEzn7Cka7/RNRAKcsqzTcGORGY5UFfMrwK80+z6s5eXgEFGj9r7BhDXN6HT9fOByueDEVp58LViZC6FknEes3U9yT9HrpyDqgHwDessfe0bD8czQqMcxkQcSmKFMiKEXwc3z5278qPecH+6bgc37k6fMYgZM+HOWXKBnL6lJhKvTNb5frJQHqVqJcXdEmJOPM7vc+iCeQMMySKK6ZCGFZECBGfi8P1zoN+wGnDktis0zVQgGd6UFOm1Y00pD2l6KiCZ7pmrQDe8/uuwa1WnMzbRnjBeKuYKWKMbLEuiMyirWmr5XrqGzsnGMUwiggqlnZK9YtQx3hWWx8/PwOGkrM4EqY4LaNwimyeV8M6XNRVNnDH1P8LbBMmKGO13aXk6jX/sKTaW2CxD+An80+3XYoTL5exeW0T931kQJmTCky3SBb4Vz0wwyfE1eTcDLEjFgjhA3kxOZIVcVJM0p6cppbDTLXLAB9Z1lCp0b0TptiEwBrnOdvu/KHO64adGjfEHASNv1VIazXb9fN15Hpne4fkLxKuHIaF3yiebQYPYsdnf+pTHBlXJVBesAb1ZWlyjQTd05uBCR9j7ZdNaH41K9j40ZoSemO6dAcGP4MCcIFOpOxYiwx7alILKWZThHuXQiqghDWe18gTf3Eyuole+iBEPgsI3HooVt36lOx09KZ5KELMCALiRfJLLu7ybIMVpZkkfrvDcLo+xBsedo99XmFFkeTl8J4XxfCIOkta+wv9ZOJjImyOhIOPy9hB6HHONZtCJOS9T4fAQcKGydrq6uPHP7yoI2qGbDxNZDnNkUV0LxEyJ3AC+wqGc0EjYeuD5dg4kN32Sv6NBgbNsJvFkfaSayfrju+OYTe4CMYKlgTeM17EqAwiJvr3ngSq3NB/OGqyvrfU68+X7npCMMH4s7BVQpM0Tmiv1n+D4oqkB4QMg2ivbBspGYrCR8Zh20pQ0eKuzVNmSZkZTEszlDYeoGQaNx3PEQ8Lq/jI22LDuJkPOcH4lHBEfbChV1pufyXxvdEoAp82QcTz0wRpBG1NxqRC6n2RmVVfQzDMMZke5SjDgvdeVnQd0BPSHTg6KYELlHFfTRHDT9+W3S0wAAIABJREFUSDk7LqPEUYDcGI2UcYJuK+DlJCWzxWQWLvbARRHBxZ3VxNZGI8qBMbNlqkYJejI4zHmxGDDvI69LMOcZOs0YdrlcLEuPyKtuLCwZHoxTFa3svEDnJXsxmyWDcNpOabC3rPaVwUexP7M9C3FG9UcJsyjrjDbPyr7sPPwIcoFEwJQ7aBL+bMbocBxIy0jvDwueoktcbvEAJlCWw4cyBil0DJAA00uZEgGLxPBXFOsyoayQYeaqjTesYTQy+q5bCwY3AMMM5CYr+RxijGwOiykCulywqWJsmu0ajNyT6woOO1EorQJCwML5Cwfj8VpG4pkEgywAaERwJzRlWRFFOgVCVgM5fjm/6rSFQpYP2QGps3f9MSoNZGULWRWE7fK/lWi3U5eL9XYGrHLUWgsXL0NNbniP4BzAMshFDdalpNU4t80cauJwow0Yy/SiJdP2iC5E9YGr6xufk9FXC6idkGUlsedaIdqUHOVwJyBLHRo4zalfv1EF4fnvhsOhg9i+vJzPMIp0Zc79ZUCNTMOdvBv7p0Bqz1EAU5zu2TUVGOGrS+VUqIoCNv3znBnAwtG2wHUhw0GvkOGyL9qadpxMvgDN6jFdNA2eS3BjSsLUaanWnAL3gbZ/Hq05pU4QmZxwOTGDOF3u7mV9FXTgTzEFhy1VgFWB3q3StrgIe0cEY5VoFiXeNXUMchlQHXaxJzLQ0IgZJmbiWJZ6jyVX25uWmTPTkR7PqiB7yrXPhIgcXMz1wOc6BGKtdKGciY+vT0Nu2HZAKJGk2l7kWjZGGXaMenbwU3vPGOFAlj2/9TVQWb7OUnoIBR4g57zTm6hmkdW1QieBNozycZtXMCsQRaBn/ov95UGYZlOTlJH6zEys4tQvQv9atnHjxY4vJufN6HG+dCezWTWwGmvYAijGroF31OyqNoeoaBA4DCKwOzuNoYZ81/46/qpa8LvhZFX2MOdh4DZqLoh3aJ3aKVJSdEpRWc3Oz8JmGBXJao91gYEQ+lRo1hlIg9qT0ULHlqWc+elZQr0zmxpEmW8GgCqDb5e6PkrwKiyGi0PdJeD4QcQYJ8LVzTWICFebtQ7hMSyg31uFqAdp5i4jsgpqeudoZnCSH7Fjgp57a0ElKAZAYSN1ngS4Hll7K1wyBnbXPsPb5kGGkY1oAPTr0f/uaWPLHgmKmOuRsNWYY6PdibW+3hrGN18qerbfu0kqwiaggLJn00vGOKXzkJD2J1GqvImG8oV0KLovgNATVLKJYPLED1qXOF2OvejzVcH8/HXnPK9qCagqKMcX+zaKUvICgF47j2W2Sns7fhXPNL6dIgQZboS9fqoH0npfC/Zay/SOsD4/McO2pL86fp7Q9xTPrTl2OP7sCApSXGN/ff89ZbF2za+vNxx/7rRo+QMGrCVsthBhQD4L6ANAHky0QGaLeP3c5ZUvXVT7yUwOZ6gG/FRWsgEnbIm7G3eiWPFcDV+yIU0rQ0vtg+gRKvGgRN58t/2hugYwG2hWpnK+2N6xlgVmmA2FQPoC8vIW+rmtiuudqV+IQKjkDOMRVkmJ3Q51vnhCHQjj3Wsr9U5mX7G8PSuHzV69xuzONfAIYYo9sYJ3K9VU+kRze9W46bBOTy5bfw7V7U7KDvelILl/Vqxxt/22dxbEtZ0xO1+y4YYkAW7A9JDpfOi0bdg4qnNxtc1yecsqFw7LFHcH8XZ1bbKEj31Npz0iUDCITmBeWKKW4ClRwdFpqarLPBMXFQwy3rq01szswQNDjd6dZYLmzABziGCuiYfzGRcxr596UPH6x1dEMXjytSYi8w12udB5echHZXtYxluGJZaFrXN7647ypL0EvHyObbOKJCHbr4dzW/DAabMBR5Wx5bKfqdlawccHhBLXFTrvKPk+ZKADqXZkbpLY/8ix9UK8fSjlXkY7kx/zTEYO+s0lZrQMRhcII5Mr+6DT8Ci6wwZKQ9PeuWLvQyrvWtJCAp7d4ADaQAAuyzIqKMtp7mcVAq1SEyJV8VaBKYqvXSnNbHYXhJlwB+A5DVMAmLyXC+GeUQpwzovw8PEMVgJeKvRrdB9TML2B4nZvXAAwb289UIAwv3zF1ds3OKni7kv1aCeyckgAcMqlcCT2deMGp858C+60o37NjbnDzzDshrGbyR0DPo6xuQipwBATYq49K3kMF6JPCt4AWtOUKkKWIwYBN9dXeDhbjzSz2xPGZn271S9SAaYqCFbqfURkd/zXUcNKxcONpBnGmBRfPOOGX+7hbkvXpBWnSqUvueOZr7Eu1r8NWiR/GwRyp0JXmoYHAMCH0BVZcy56H2UohkdWM1mo3dX1CTqrZDp5vzchwunZCfPh4hkzXhbapeuIVA3FXUTBLpmP06nKyPjkttOGeb53o6KCebPSnAkAwcP9PWSewSfGPC9nZop5DqMMga4UcudlfeUO5mg8QQHMaYIMAZkltb0yA624YQWk4JeM9XmC5BnopSntcGcjk0DlBNE7X+cbiN4Bav1a8dxhftpADEwRrBkGIpgCZo8rRk7u/IH3lRJ4AIJl0w43Ol+mCzqaqGGM0fEnMyBb6Rhw5Ct24Y4y67ALgKHkk5dmDUN2lMo0qzg8gyn2sFoJGia7BpSOvwiykOVwZwIPpz/u5AolMrKguzKmSPLnEdAK3bwdQAyc1Gh8K5+W9DsNCCjjYI4beV79bcvp++n6CswD8zItkEgu5jQ8nZIf2D6P0jEuIKdAR+nwJpAr9yYMBaxzrHEdlarMnqmX5dijfymMB4kHZphAlyEGIB9TpCUpZ5fGjCAvZmZrJ9DsASjeK2fHhZmsJzOKjHHbl2GgQ5ablcRrYs9ZWurlaLuS1YPJwjDhgvTOaKjlWFSBYqFKE0RWmK3fdL5b5Zsd3FRwT650eE9/I+onBFfb7ZP46D4lgrrwZ3hNKlCKthZRQcD7xG4n4yvDMn1EBJiW/brcyKfez36twNTYEiU5mQ6q6Sw8nU44ncIh7CzE99zJ6rRjcPRp0jRyQbzSBxfHHjyAzfa5huMxeLhn49oeIS/JVXhKJ3LctfdLls5clqk6LHJ2nK6M7/DItgcZNY2MY3Kc8DL9Ais1DABuBF0SxtDApejRuzn/3ox+OxWMzHNi5+8ezWrGaOfLHK1KFhScWY4k1heeMtMnZDvDdStnX4asWAfeGCpk9yKGr+7Uc5lVLKDPfJTu2AoHAQUWWiZqJIilqLTcmBy4kg6XChIFNEt0FV+2Z9DGGXwDAnQZ/0Csndrf7ty0LOQnUinCyLyTeVsp8bwsCbvhj9+ra+F0fTIYjoFwmkCsEoNENix0V8Fk1/ceigHreX/aTiBi4+2eahD7QNayPl7L+mpZFuuCTHFHd89JQNS/yHkyhewgUF0WOT1nBqVspw1jY6jLHd0JqFqlzyPYE2T4TZPtTeFoZ8r9vAv2VXnE1/oRGcVBL9jptWXKSK4L8/7Z5UCBG4XhuOD3OfJl0Cyxlagnk58WjxzDcvwRVWAt2x9EnlHm8pAi+9FOCXmGTFcbzj9btkIEFi4R0BKQt12gkdzHI+Sb0JtGq6Sg/hfJf+HlehEYqQvExk6YAbDWvoUCGuWkUfzQ95YidMVD0DcBoc3bdZUdUVvVgjmy5YsILpfKOmbXZ8Opsta0ABymChwZVgmEWFOein188V6H4sE6OT72YCiy6jWsanoSMXQQGIJ1hvfHE/BkXK0F1QXFyataWICboIKPJBzoqZ9yyuHJ4xO/gazEQpF9F45ql281gjfcmbWAiemtFrbMuhSSdNxlpmq+M2StCMIJK4JWENN+0XbhEEYuywWisd/WAmiA1QKOybPfFYAQg8kMZwR31LdnhgyeDj6v5DOdH4Ttg13GJiILYnNYroCVB/3waUOnvZUR5TRzRaCCljEXIXlTIiQ5fyO2oA1utL10e91l+MV9Aauus5gcq4gMltiNHLAwS5/JTmo8LwKJbCk0gxFC7g89WJf9FnqnqgXyQA0OomqxjSoQLKxwqu72aRCB2JdtlEn+yXG4Y0Thi03hQJfb/t7jVpWhNjTdy/uAV7AhKtkgYN+zuEKT8cdLq1wU8CBfC4pxhP1g27wH54GnhA6VQnPNX0Kg70Fdscdyr7HJ32qZ9ArvFw4PVpDCd3Mo+5xKeHde67DJZ4eTEZ7gQok2kT681spy7RYwZgHgFYBWr0nJLJeTkr6ETpL9U2PdFSnvhK4HwJN3/B0ireKijW1lNrxXJXMHunrLpS47ZdKMVxrIPeL6W9CqveuYUmuhwK3W5uMY1LIDRFRyIEIEowfgGRFGrY2HUdqUcn9Sd9i7U5gKZ7szJ/VB/43H8OQFzWCdsIlcnU5mp4rAnq7Ppw5gD41xQS3piQDodxepb2zF9bsZWojuQXgOpQ1ZoYGlPgckd/piM/bHHOL1KshWEAKr3BNwTLqq4GfPYDI9EC3gIqh9UMevAPeOWxTH8qA8inSD7uVJOQ5V4CLlZgQTBNTtoWIyUFTN7BUDIjNeBC5XUHMohfM/LtacauB/UqpAoQTZC7MXccEy+GnKBqixZEBMZBaGONxlulwz1OH3uygH56hQUjDEbQnFl6ryi80l2hrFey+XS83PbSKWCCS2zz9LjkeBTOqLctn7we2PP+M8f3yFHlFkBwskd9bjXb/8vPtbYkHxcv8WMCMA18q48otj37C6jV/V40wsOIZDBxSFMHD59AUAcI9Yo6fHF+gb8CXA9Ys68RSEM/nFv6+2Dg+keBE2+5DHyIJMgv+EAn7k/AxkUt4ObmvPayJAvwd92O/NTqWK72SveukXXH77DFXF9uGNw0WxPkeihmJ+ZGx/c5mZvDJdyK6q4I1TNiGnNYGD8zJx+vAW8/fPOP2f90lPz//4nHv/MkOOEkvqGQMPv32C8WJBK6xpegOwg0TAOVe0yVtdPv/Th1/uVNzWKH6K9T0886e6MmoduhSb9K/hlNaFLYHA5A2jGdajHMrpQI8WtVBklS+zqwsmC662soEBFiyh6nZZBQD24E4CdGJOs3cuXVmdIUxGooKpiot4v3k1HnP9jvDw2WjUSzAm1BJEnW4smVY5b11w+9tvICXw317ZPhrAInv+9fs3uP/tIxiC8e4dxsfPuJCVbA/fkwXJ2ISJB5Ysaw3q7xIfN7nOqaTYrq+gsnCZJoOaCkCWtMKRTGM0hmFJdxbAbnaGCDQPP4ib+hrfa+vtstmOQLTgmLID+N+gGT8jy/+NRxa0/4vbpQ5tE+w8uz1TUQAURcu4CCXdrzsIq//q8c/AN8Y6sAtu+oObfLYZchqnTcgVfEulQPANhFcWVZTAi3KqrzMbHUBTDJ3gKbA58mz2xr/cb6Yf1D8c5pp06QkYjNfNWLubb0XjDycypAy5CE5XAwzCurVseSJ4ZqhChbB8IwZT3xF8BR7uHnD97AogxeW8sF/dJrzv1YC/Ao5Hx6O5H+SdMASrThj14TSSz3lOQ6xNibDRloJACFHQKFEUCpW9Z0R0txajY2JMRNS2OxK83K8Zf0+oiHcTPGjYA824QmbgdMGSQXj48R3PXrxMrjQvEzIXQho3aC6oluOf1ATQpYIBxunqZJHcE5kRIqLAvRG7WBMT42w9Q9EIY1yUiI+Mjzkn5rcJehYraYp/Gk5hDhgJ4g3FeDFA8hyAZYZaBm+VljMn8fIsLyop9JBZGJkSUPVMdLjweSiVpeEcQRKx/L0/m9zo5c50OEMLZcCMU2GQbIimgFIYPyWZszwIMB7TSHKGTRLGdKMf5jSyZ8FRKkrkk2d5DLA9vxPxplwHw0xSsR0k4lR0DnCIZ/2po7iGvZ5qn3SOou23yCBr2YGPnurwFmfSJnybwS8yN8oIsOeHKVhr8avOFzKLIP4m2JrCGJu6/dnBiOqzwqMXodC1skdOZFYiMkw8W1bcceHqZNgDcv0Lmm0sWoMg2JpR+71gfqSsyaiRKnjDQXsW1QAU5fiDm9iOk6fD+PpB+y/009/8d0ZG/Ker3flmOvhgEajm1N28l/cwR50sLNnAJFh0aVWtKmuuC21KbtTjLsu44wvNDdAMhCHURpl9wJyIzCOdc+RZMwGuwYwBhvKAbk77WqlbC7zwoJ3M+lzgxb5Km79bKvozKpAMxjVfIw16o4zHT3JPDZDaWKf3HZ9zZtCL9Vb2FePIwCCPhkbSujA1Jg7kSzXfpWpZQUjYCtRLMiaNhTswyPucY5iBIHkjEEa2yEYVz8btC7pzEKXRLa4r2cYMguE81R1OMCONMvG8cCYnfuR+KES24CveVVLL8XUtMXk9u+2APCuxG9dzQs0w0PjycUndIKFxD0wWMwNd1JOYrlA6/pGx48fErIbakWbOBR7TnIrbBtZyXGf2nMPKMtQXdLaqAsQYA1YJZNts/w5vOxNBZAkD2q2RKnA5W6WctQRzWpWP47pQZLtmdFGXJQ3WzJ4h5Rm/iQfNCLSdTsZv1gURihqBINrWsvOYjkudjmR2GWyfD1EIkWWuuzLOfXwKKDN0bK6WVCByBgL4KkY7CZ2u8OY7vaJBlwGEfBu4PBnv1O4gyIEgjENhvP2ZtttNcgSknTwrMDR53h4bpta6yVqbRJBflz/ivl8LII8cGLuD4LvBwJD7t82YIpCNIKxQViwSDGacThYwWo4Ku3eJZYQDlU2o/kwe7JVRHA9apqb1rDfHY+FnbUJzAi1MpiqHnGtaMHl64wYOtmu0XBPkGdbISi8+Xh4YTMhWPiq5j6GGr+HIiSoPw/ld4JeJCtb2RV03eZSxRMAIHgWqIBQAygtLKmuXmYHNqrFsm1dAGcMDbYzeVvZJm7eak2fNWXwA6kFVkgFcphuYE3vA5qhq5Y2LhUV+nT7aAqEDav5ggccauB/XphGpaH/HI60HAojqOCVzSMohHU+OvyN/T1tMiYBpsIx5mb2rgucCd+J8ytJ+X/Cp0C/Eg140Ks9pOGozJOqXO/IPj3C+/Oqw3hr9poROkL2cQ5xNecP3f7RqQQSCPxoI1mwWGt391PDE5RLfp8NleyVvuRM8pN5sNLBtYfLnWBUoW88wNJrM5jqSG0hDv7dWS+yObw8uTlzfu0zScIkjexeIEsj8BxYQH3INNHUVdR1WduuuSWMaaNp6hO4cxt0I7Iy8YarR7HBU84RlVBeM036gcNoqVXHD5c0sU9zJZcgiAiiTJ7YYvQtYrZSvyiFiRW1MRrM9XNUEdPcC/0TuMCeUs53jnM242vdoBQXoYY/DyUGnGw35suoZyiGdMIDtyRUJG947mtjmujw7HSDo5QL2AC1rv7CyZUVUKMgEHh9nyRo3RjfwPSaPlOl9f5EY72FpQZMImb6WJljdzo7szzRHWZe4Ad3Big48DilPqvNVC573fYAYUDzFEyUcr9KJ3nXrRKfiscEDemBM/vXWOyFnWpBL0Ky2+TXo3WM556hSwZay8Q3/Q+X87sFpREC0oAI6Wa13rUPlk18dJk3VF1ZgvH0J+fwNykXTIkhhB7ucTATQ7OeElEco75QpWJ++wkrDfwP8/WFBTtgUCcHDr8XFf+GoPdAgfPh+4H10+H78/Sff49y1In0FALLC7lMjo7cv+zDtWQSM1wT97DSSNPH88TsjmElLb/gnjgd/9mh2qp8dqd/uLqUdDI74/2jg7QP95NLjuUXAeEtY8hXEL/Mifg/oR8J4T5CPCnwQsEbLT97tYQI8GjgCD2H81eWh7cNbD5QvePM7pJ0oKvgOAOffPj0pOxGCBzz+7V+SsX5xHCnRP/Oe4z1PPe/nS6rtBsePJm+Ybae18gwnuiyMxeaLogjU8AB/jYDwsvOF/r1cZ5gRgOj0XcR1ibUw3KFMECwFeLzF83eKr18+45aBF9Nol1UcYOfBtm6nd4TLR01elHuNFPPTZywIJhj88Quu3r/F+PgF/O4NLJDjSyamquNX2LlNRvTAznY+ZBMaA5irqmUh+KjZNyNYeCd3+Vr1dIeDxv7Hi/7EpX0500z/BG387z623befzfF4fi89J1PrP6f4m4zXFKiIPM6ehsHAn1B4ukPj+HqJe7rWEyNKw8IT5OLwuKM58/WH91jzgm+/W7mSZ0S4+8kyqSpujGujsh4s9vC5KH5wEOQQ3OxN/JpwNTbIO8H58wVEjKv3G66ur3H7X7c5neXCrwK4URMSzl9uPTPxD3lLPqepGHkkgpPVUMpe50Fwds6kegLBDJ4iitOJTRJx59kgKr8KEwYxtpNlljEz8BXeJ1IzS2xF5o6/mjdCVNFEIxYA4Xx3wdjsPacb68s6Zyny8kiB8PETPKMTac87nUysEM90k2927emtZYtE1kO0eCDAInJDoXDqtpaVhYu+GGgM3YzisQ9op9dnBgfCuCJuzOAspW1OAethqAIM3jBVoELWO84V4bEZE4h+ipnR7puPmDEo4GCOQ12AMHD9/HmSNxGCzIXtamBNy1zcrq5sP61wFFR0qKrg4XwGpKlnGwFTMfUBpIqhV8ANQN+vACj4xTAlbRmDkFBWw6myrPSKlYn9Dv12jSjTOVAloIkAIfVIN8V4+RLMmyl1BFM8AChviNJllgnizmrPpBVXDlQV2bGcXHEl8tIs7hRCyyRwhTl72qGQKyOu25HMyTORzbBy0G6SwZU+pGJlaEUV+qBWhpiR4xm+5mmocSGBWo0bWbDsO9V0JPpA05EeOD69XHESmIMsUqW0QzlF7V8K4eVAbf4ssTrcpKpWDtSdREUJrKctE2E7bXBLLiKivrMjRVNWmTyD1+CmpJ7sSxlQkcvW6F8FvCAXphw0QBnog/M1aT4FY/uaZaVzNqiXao4Y1evYIiNFVpblT0OjKrAWLr38K490XBATGJWBaNG7LsBrCYLmEGvzi8X0xe/zqZHb/WMbNozp+RBhHJ2S1yU4bRA52T/UsQ548ys0MqhWdkfQVw3N2g3ePBg0BrbTwNX1CSfPQp+YmBPYNoHq8JKpkpyvixrqzmcQQ7ykajjfMgK1Lavdo8jeTAyoRuBGRcYGDovLReUMrGzwXAVHq6WC85oW/UoKiGUZRTbREoVVCkAZEYG0xm604erqeie8mlxWwroBvgICEMFP8B5Jl3NG8cZeIRqVKceUBpFdCfrAWWkyxk7kEzPcqVrkeDLP3YYp6aQ5anQMy1aNHeeL6NDw3vO1v4//gr+lgdzXv5yzVhI75Ic02LgxNWSBoBHhcAj+wVyCRSofrYJJl4dd1PDtSMBgsA4QWaWaMPb3TLWOfY/A9uhQz0CuM7Qhg6uUvEWQVvZxBoqQlfAOo3bvs51PF4WOevm2DaiyB7KN5HcSkeCyMGeURSvZCYh2AFtm90b0fTgau7RbxtRYA3X4y36tDzgAdwLFHgq4EZG1MG5SdZHN/XOK/Dc5jIAsP+k0tuTBgGc9x2hQOMAJkcmgQK2FaiVneVAdgy0CWBUsgkXhgjEakTjr2YIg2jlxbQ9Z0G4Edi43OpS+5LgY2akxQQrHatsvEWixQ4r6GL3o99lwccE+UMtkm1oT+HJkcCIUUdYu18X3R+ezicfxrxai9nzMMW7zGqqJU1FPqO0/o3kON2ZsV6d0+BIZDkIFl2n7YnovxHR+ePbb2Kw625wTc5mOaO0EbB92+YKZMghF1DIhsGCtClKDSsxB0tmcV+NdR2IRAVCNtFS/Y1Q56GEB0iFXiETrJc4bN2bIYAxYlbgBy4IoBy+ywoGS6Yf16oAvu17ELoyK03KnTy6DEjMGA9vG7kA/YdtGyt9GLwz+Y0gG/qoqMKeXbHToBXGUsluYE9367OrwKgHMhQcImDq/EK9Y5XhslQDKScTefiv1zrYX4CtIsR4N8S2wGMiSwxYpu8P9XuIWQROJcq132X0NJ9JgF3aakH1ZM9BBd2Mp3plVTIJvEapqiDYbUASEJnt/ikmVAY7q1JPC4CP8/QNdpO/vzj73VRLsL28bZD5OWYhXLTm237D2ONJkHoJXG9AKRQp6DtczZXlZcTI5SkPfdRk25YUcp6ZsUzJNim2R4pmilRKspFLYq2iZQ8l56O7vbj284s9wx6XrWgIFeTsawAIlu0M25NDoc74iECVlicdLVTyzHIoalQGe0rNicaXTdi1HvVSFkh4oGTRP2ryzJUgMLnU4QgS6WLCj8RrV4mEV8BfIVBiUVQ2MIRlsQ6Fu90Vli+Cr5GVnzc4UfBdglpS1uvM8t5EiyrLFRciKASIZALDPHjd7DLzahqrh9XbaDEbLcPZyvmB5y6o5rUVJBE2tVW1MiBksAvV2edBr5zc/DO4/7jzR4ZkP/AGghxwnR2UQxzWWmJj9d6DRsfopbX3JPZRcRnA5/JDtte7uDNY31gJFWis2DdrXb4mvXpkjd4mPJQOkfd/WSPwZ7phxVEh+mjKhn9OsBGg4pGFjdMe80QCn66Tm9FCymsOtZHuAooFofyigXxT0xuEnrp83uavfGbxkfb415/XPntvnjCgdTkmP8CbeA5TbmxAtFLMSRH8IXI/SqnaWYo3DbV4m9JNC6NaCA3CbVMPwyG7JuiC+hveo9UVM/2cA+8uHPuZHh+NZe+w95bSe5HVo538iWlsioPbfdAeHvLjZ8Ahk7askZNvXAL4WnXG81Yb3Qd805LnYk41vJy7qnubsPotaUQp4oIVvi+CgI+YatLbZ3oTglReLFpSe0GUb4L7pWdewoAmF4uawrJH08cwdJulDYOBme4sf//gE4BZX7175XF5B6dbk5PcM4DtkKZheeRUjhwoZDSCPXAleG07UwdZ26O7vv6c9CACY3+yCF+XjF9wDGO8Jg17j4eOX3fj7/k/eD+BHC3rpa0OH73/l6M9A2GGbLvxX7tf2N/ZmrzoCPx8nbG6UAR47QS9kI5c5RTkd56oLS9ltDtPahMUeYAZHwHIEq2nlNWQVpaiqoxZYFlUYLQvbgqUfXK546dfRGDhtVtFAxIIg7gA8/PYRBMXNf7xHtNLh8RanD1ZR9uG331GObsXM/WytnfnjZ9Bbh4mX7ee594GGAAAgAElEQVQAVfB7tyWuJRitGmrgJKgSfLQRwggcFvcRqD0E6t1uzy4NwmWjkklRcmmu9lEuP268xiN28vp+aeOnfwZf/x3H9seX/LuOEliXLNCiQsAj8I53/sHvP3vfnzn11DXMAwzgAgPQc/zciQ7UIlYJHUO+50kFitArgPX1C/TdB4+IX6YosWVVNfeWCUCKZvyJSPd/Dl1+elcgY5S53/20J1rjjRkKrjYz8lzmBarh4LILrRysZVGYcWcD3bL1phrIjGtVhihDeUGFoWQMRrKXGNXGcqa9XFqb5wlA3dDkQmpVSfuDCR8uIIBeEvRbu4Fq7rFhw/B4fIbCMiqAYlDmjxtZCipLIu1SzAraLh670mfZaAiDnOU4gIlx8/wa8+HiSpat2dXVNbZtg1ykylW7ohkKtjqXoa44PAGq7foKIVqerq3PlfWoX4iMeAalIUkVFsmvNgfxbA4rewIo7oC7q3qJ04D53cqzzyjbJ97RQ718ryhUrt2JeIPx0rKAFNj1TlIAp5cvPcOLSqDKoCl3nuMoGFDbsCVMheE8Iq3qN3EFrMHMFW6Ec6EpdzyeJq2ZqczUrqdkSOFMIGBXtlYfbO586gb5toixrOmgpCZ4BA11HNOCyKNI+5zfQVhpn48CUQhMHe/++aOMZV2kepRFFmBTffS+nTKRQtMqQ6CTUwZDRnmONDWImunegK6V4abq2RZohpEEw+OSkf60IimPiVMorLlnFZllHgpsRPRblwfBWmZEVi+fM3q/PBh9CAGGYgxMLdNV46zPy/9D/S5khkvMm6LvBgKXkEKq0bjaC//S0XjqbmV3Xwltw7vS69/Zs/SBVP6IrKevOeKsh58n7hj9FcEa7mBVu4+9TKsFL7ghJvY+wYKaMmP4iWn4c0L5CQNRGAdB7jyIAAQfp2Xemto4hvUPN/xyEVomZF7MCQO4odp6hC9eccJWqWd4udw1iHB1dZXzjP1i0ysnkxN6e062pQDm+Yz7y0NMEC4AeKauZVBx0M1QQhqAmNlTtzq+kI+36GrCxjPQTTnZzMAiVuKbxDNCGi1svp9UUkP5Tvqdcw8na6uQFPd2J5L/V90ZLgWk4nFR3pVKQXHhsuDU0dlfZKX0kO/uxl7b//busY06f3C27A8LmAvf8pGe9Zt2TntV6Ap5Qn3+3cHW3rDbny2LJGCddMHwPtqgrCUuI0ZwmqbxNTKZiIbvPZMlT6eT71t3nnsgwp7c1jjLMV57sL67/AKFKmX2pLqc1I1oZjRxI6wvpSzLaudh7aIySAKO1z8xluU7m9wRuG1BBbH/bVxx7QCbkaDhr10vUIrM+CrBD2/RQIBnASODXBCGcne49WCCcOwNxJwp5e6GVbX2zhPie8+WrWzUFhgYcw46hzBKOO5HBQA0nkqxPrCKFAv17B0eIhj5js7ssv06bjRc6YJQBshR7EeXp0RTxlU2fOEQ2Ii8qtaAsEJYQOw9Yn1w1o9cvF/ypZw1vo+JgMHUWvHMgiPI5+ZO2TFwPYw/nE4nq+wQVRFES77sJcFdp3jqCKlBH521I8oPW/Y4m2898aBkJhXFwgU4e9aeBp1nMMzZTI5z+2oRwX/V9CcuJh9sMrMlU9AKXhhL6KvMOWgruTwY7PCJ3toq4mWKLehAPYgk8AxaOBQVGkIn0GVl+lcgnjtnpFUh04RLz0D33zzDmDSCyin3YgnaMcdGl+G6YZ6gEPWRbwq5HzV+DeEgRhCyC5rBO4AMl1Xg9gjnacbCw+GtKSuGVBEylqoHqfmeUCADAySvkbT9BJ/ojubc/+FdSXR0fBiPcfiP7CKJQ0Hnmp5RwYqFx6FL5RBUGzxdHzy8u4ulNu/H+n6MPf/b2LAZLg0+DC/t6u2RiADqGf5itLIC2p+WPbNHni9xxIMQLBBiLaNh6nxQm76RIKWQ82uzqaq3Bwo8indEqI7mPrPgH+8zfnRSo+hH17giOAfJP6jsF0q+FwJfI0DRP2sEs5YsFngbLwgjehjBQ28Jelx4gsS7XGOXk2WtnGtfZbjDNuhIPigZGnaEK+afTcC4MtDZEzTYW2+BjJ6RcjpfkqeFgd5fzF51IAKhYo8u1Uf2rMRtvyb2pIhizWUBWY7P1qrEDOWxr6ztjrdllOXn3fk/7jx7/lkFGzTQGILV+xsBRti6MAZ6S8Z+t5rw/qQ9ufRzD1JG6TVJ8jToddGwwi1tvIDg5bWKrzptoLaODZDta5PNCJ7kgIZbvvaNgCixV3YBIFGZhaod1COm3Z51pIedOD1x0BvK60S/gfklqGNFF5+6btRf/4uDYGSIANBbgPAKgq+AfgO/AYCXCYty3ERg2HF+Bd4YCR3uPY4rckpiHXe/tT3awfYHLOX/6nGj5kT/1ZrF0UlMLPMzjYzzJx7gdJBAVYCTKIhbXrYUwO9foeo29tbuLx4T788AiBTNOoeN6x8D9OhQt6GEzPuT+bZ7gv7SbiPQHg/SbvcYHA840u8nDtojxlTg68fP2MKOq9/A73bheDYGKNYnAr8nKG6T5xG/BtQCDYmdlwctJ/J2tVYiHkDeJy7Ti3wB0ZsMLODxFt1eEfPu8A92e9fFqV/P+n/0+Bm5egpf8gZNJlun1LPBRcBiLSLEk0DXEqs4iYkJb8nk/NGCGDytzolJ2OdELON8LsmEP9MjNGUbUatutdSyz59J1MrVHNMmlgi5VLGMnXv7DslqNqY7Dm95A+dxhY6RdCmhHXwC6L1ln8dFJW40Xua0QebCljYYk89Op1PaF8y3RYBnqy9pvK42tr+HIL/aSn/Ag/63HdtfIc4/+yGIZ8CmE/O8NAw+a0EWYQIVed+xAXhErPoz6hr7EyWNVrJ5ZwzUScchI5SQKdhu5skxf/v40QRH/34CMBS4S6fE09BgGIKKqFc3DmE1ZMEi8QDh8nliezNw87cbrLnh4eMDJsroFnxM3JB38Z4LBHvRzjj05Ijit4gSbnBsjCkyz5V+OKRe1r1Ujse4Y9ss0+AyBTIF959vcQXC9Ye3UAU2zzYf0fuUB07bBmxmTN/emTPYnLKCoQNCAiW1MvUEzCU58oK4G2APs1WxXugx1+i9FMrtXBOsFkVreqtn/iEyhw0yzAy8MoIa2QRAoGH0CmvjcXRQeBnowDknstEny+DIOdYYfuDydtrMue4GsnSaJsL6XMgytk6nE7bnnn3FDIFgbCdYNpr1Uxy0pWEiejHJsqyc7lAIR4ElcmgjiGa8vTw8YLvy/rqldYOvrqEKTO8JrgxgwsoL3wumPsRjbG30DkOvAQjmN2Mo/HLsnD4PXyfw3PU8AFMFeGarxNhAw4URz5IKAw6/iJ3m0VbRz50DFwyLYr/wGJAJKJZFuWqUFPT+1hG9LgvgKqkbAl30MSVmbNSy1GWfXTgGG7NzbhIGpCWttJkra2nwChzIsu3OsB4M9qQKvaiVuoJlUItGRoTR17CNhgO3ys5z4bnCe75yOoHOl0vuoTjSEdXpxakCO2Ib+EWPjNlpPPgzDDOvq3dlr5r+3CYcQSNSWvav8DmnP1PhRu86mBjC1ke54KSZFVHDCv5xUKj9V8u+EGBwTvpJ53nfePE9h9RouVpJWrjzUKQZKMnKeRu/I+vvzWKG3HAWukJOOfb+3WmRAuTBSqoGqzUXsmJGZCkS2XU5ZjM0ERFosx6K63wpQ6ioG7C0zSn+hrFxD98/PHagtH26M6rS4SIKWBWHs1gYc4iTZ+sF3x+DMTbGFV2Bh63ztllv1NhTRvRizdiqV4AAzwKlgCs46W4aYagyFo2EatKRkWWdS8hXN9Qvz1DjMdz+FY49W09mQnLJMOQReRn7cDyL9U33ihUxFRNHNGnSabNgH3GeTMt6lYbTR9CMj3ah7y/F+XLB5eGczsXh8GXnoVUNxXEhjIZUdCXkjGKsQbHDwBkBIi37TwBZE2uyZS2HQT6c/qqW+e4KD8iDhbwtgjnhNJ+Zzvn8H3LuIYxFBlTFKPkHV2pVje+UTuG0X507EWFzh1JE8ca0RaICjZ+T+pGZLAPf5YgoLwaU0zbBp3sDR5zf2NY/ev2qV/5J3pNjFvDYvI2LZ7uCvCe9QubE9TPrqxIcgCIjFQrizUuwG18ypbVl4DXZyuZS90YG05zLM5kU22b7JRzm9o89Y3PvwAhZLQJ1jZ5jZyCvIBbNfZmO2+ZEbxCxOUaLHZfrzMi+h/EO5rrfMwRktmXgBFjANEx24AomrhJz6mWqY1cEnTXnW1YSETMIVKZJZcMqW+/UlXtsWvaZy9cC17W0ZBx2g7vGZ+309InJtiCGCu6r50UgS5wvGLQMopDyO3sgtSA1eJaX7HE7eGr1LC4ZpOuKwWvTUfjUNNqXoNn2NzLnTLZesrI0ub0bULEsUQZ5OwUrjc+Dq/qWy/QXIkyX2RJHPDsyetITBX4jHSjKhIHhMODcRwRra3C6vsJp2xIWAalHcKD22VCliVM7IMB4dpfpzHk+shx6c37DAgtsTRdELaCMFjv/GtAxcGIzXO0SddsSJAuIc41phR5IICyY8THKJSb998/aK2o03Bhjc9lVAWWsIcAkYBGWdxXmBhtd8IxgJH2yvRvVBwyhx6DkeeL73Hi2B505P845EaUxX0TSfhAat3oAYwXE+nhEAYhlGkJzPxFHYZhyhgfliSAVNJrU5UNx3Y6afpq6Sa6N/y8zdyIQRx21s8Bl6+cOaFZ2Uq/KVsZDo2f7LOR/7ig6Xvq9T0NDa6+Tu+CfuI6QgafHoBBqMGGipFmhOz01GgAWZPFHo1aYHA8kLMHDKiUFrXR6EvOIPUEEc6DG1GIDHUh10WDnX1p6ChEsi0go1zzGtaMdsD7rDDUiHYGcjo993vnuoAsemFLOc00nfQbD1E1Q9r6loNSp6mdquBlVNXy8stKBnO+IgI9QBhtfNznbK7k4rMt53pI4gHxPUz2NHjxC3JZxp7YfW48V16+CnzeoxZrku0pWDtk5AqmUkPbLXPaUcySDMAB45re1BQAzNCpwRBDDzzZewtDa6VwuF3OOz7JfMBNWk4tkCi5r5lqTl26XMTBCun0wO+N4/txG/uOu4EbmYAcAwUO+J/QVUrXg7yUZ7J5BGL5upj+j1iVpv9eLESoNVIsGBqdbP+4MN549gwDe9s9oqMwF3rbC89igjsfSNl931NLh8tyrzY5S9AuuHwb1pqzQWI591J7Q9nCCRZAAhacdbQPpCvmK5xPA9DL7ma9bBb8J+uM3qdaN2H/8M0eHhn4GFLeZLSmfgfG2eG+E5BwZQ+g780BbTa+vQND1+StAL/O9nAyxdl1VXvnnj79273EB6NEVj5ybjy/50+NxqRxBoZuod1RvDPZNKBsf3kB+/1K84Pge5ztVMQdFv2KvUaeGXaZ+DLU4d9/sikzAc7/9zu06z/x5UVcx5Roi3OfmItykxAKTpTye/cGneOXveyCTIW/CQR3n095i473RmKT9PsjYoMAGevlkMx1/q5ahvL3G5R9fsb0HlL5h0BvM37+A3xnuA28RRh2rFskZvPnjv34HVPHs/7z3aqyB706v6A3WR1uf0zvg/h+fjCXEvvd9tGA49cznd5eJfEFf/r1H4Ni/tKcaHaxdokXLmn5WN4WMWvgTh2jZIYYsLCKMsDWQVeDxMGUjoSoYohgsLoe1sD6t7PK5rDqY/W2Vcz0QPv7NqGSobk8i80sBhPHmJe4/fwGcbwmMd337r99xevc683R2fcWdaC0FWBnb315j8IaH3z6nCHj/8XPC8QRUMKxTVqi4ruL4F/6yywPOX25BH95BFVhfv4Pfvk6bW8rQNzfA/TnXJe1ksODvtSaaZArJisuxmo4n1PST/4XHozRJPfz9M0cg7g4InUD7IWqGTloLrOYMM8W3KWN5/x6kPxvPPwX4P5jcQPUWD7r53O+5P7ywE3CowvNAcHrzBvPLgtL3R+MkvMTCLVjfQtfC1WnDxBfYltprdRZxqi5I/3PZ578kaE9w6T0Jqk0wXoeAY8LK5dNXEAgXAM8IgBt+NvJSm2NYFM8Ylok22EqaQQHr5g1RxWDG/E6g5+6kjCL1nvWRLSkJLcu/Dz8Iqq3dOjbPS1lT9yYhRmWtHw1Nf+Jg3mx8ReLhtrrH66QZf5rKX0Q4hQAeDpMgcmYsBcBe4s97fW6nDaerazOKIyKEPLMyooXgzoQRooYb+GnPiGo8MKM5zDB7urpCF+pBVdYpsgJVFFOXVQBYRtHXMue5aO0Ne8k9oCf74RmneBPKllhNervUlSaEAEYoeGiNKQwwygPQWtcygGvOL9YFgMNRmgHXDcWdSYfw3m7MbAmE/Sw+M+b54tlglVEXilvT5cogmOO00pyZiYPIyPLM43Pbgd2YQAEB/6qReekMEU8foRAFLnQnylMyfc8MKO75k4c/dfzhtU8rEsffFO44Og6h3f6rfdsFrtxrYOgIpdTWOfvxNsWSHBnjXBcM+rok2vmHhoE/n3LiVqAbZRnYNKZ7WR3egI3NcD02wXKrqd0zrSwoW3nUvaIUzhPNvZE9tPugXAiNwaiqBQYgSvkCys6ONGMpE77pVErap7vHt1DnA0yewoHjuVzkJ67WVPJyPeIuN8SplCFGZWHNCy7n6ilowzOH+pxmwBRhqK7cdqqeLQbyjDQCloKH0w6YsJu96amMoI8yemDlCcmN7Gt51Q7RdNIQkZU/FPFsXc/YHd5GhZFZIcEnEvJajsShlG1TkkYm1yK3uQRtRa63EAAx48PS6tcb5WuXWK/YtZa11/CMRM4sxe7UqlJTiIAzVKZ64GgW/vA5QNTbLlT5XACIPoyYE1Mm5prQ5X13Efgo5VQk8nWxDFBZYg4DLfwNh2RiG3mLi6qBZf/3vWOBbQrufWe9rPCOBjsfI6LWr7uYQpKMNFQV/psBuuEzxbspZcIYPzXYdSLAkZ2slQmZxvi2kxQKHidEEFdUJMqx+Bwf7u+xnUbbZ0WjEfQDxctquoVjtUUbPw+cdUUxnpj0ujnNI3BKxIS4VFbXwgx8kfjro9F6fzi5ukxhhkveOfd2BkignNcaNGdv+OxHyHIgzzzWxodCtouMjppuvjf6hu79Cz5eIEvGETNIFsSdI9TkjwA2s5WynqqWbbiAxfDsac86pAEeCg7LUGSvUfBHfRz/9FdkgYCnosn4e3muwyB0H2EAQlhetjOdJ2GoIn5s6Hjy3VVtIgIsVPfvfDRWQjobsjztmpnGabGtwz+XkzTgH7TQnMpGY+aKXrGSzvOAZQQKpSxJbCXCh1f98F4SvZf4tm2mEwxrRxJ4KF7eu+/DpB9HDqolQHfuvENpMtyKNgrDnTMiC7IUQgtRCceCOgyXmIfRSAdq0CKrOsVWTxXucCZz8rA2ccHHRwIIL+gyY1BUYxOxoCjL7J/pqLOH2pgXL+ObyhgawXEl00frjchI7RlQRnNMN9oFQqr9lgHQnv0fKsOKjMFHeI7SY5NWErjhdKeo8TLLzA8dsqpl2BPijlhzf74rYm15HTda5rmd2F/QeTBinEjHp7Hmkv+gmvp8srCoVIMmH4Y8lHLmT7YftfcTEJn2e5FVC1kVnsBfMm7p4jY5plE4oVEJyF/mtGPvNG9GWi+5TGMDPNg4xtfpfvY3PUSIpEP2MFnSPTzI5WftOmwLXM2MTBtd47nOv7uelqC0QIzIZFKoZbWq4Y1GsFVf6yftb72KB7IMNrV17XAJnC/HrqQzvQz4ISM6Dods09aiy2gxll7tzc55Rrt4ME13hAd86412R47v8Zj3h9s3HVfS6d/00T7OxKNYCmpzgSYuJ2XuNNpl7qhmwSJWQGARpst7TGiZ85KycATfZqAO4C3uKpAu1jad50/Ot+ARctSaE/OyPIDIKouoOA32OVvWnOkjSy2wnEAYqlCdYH4GWudspaWqu16psZW71Jn2HscjeAJFVvKK/aJhw9AMLt3RcGawWv/ZI8s/iF678cT9U3vNw8CDoE97OTi0wcJf/5WpPu8Z6+5PyDe7a8kCt41LIHHQKiDmgtk5h9duLfFnj+97eOg3AC/yTJxXBeTLt18+qcOx/33q4De1Xt3O1vdtrK9oBJP4L13f73RsNxLa/6Xj8/vR1/mpmfw7jl8/6xemrD91PNN96fbiGnYEJGwkBKJXu99yhArLnv69BZeH7nPEMS1JRPveaC/7I/9F8NOf44zurlW4T6I/l0y+EerX7p9yD+AGyOSUI3B+PkzHjXZb0Imgi/jwGttmLWJTvEiqAMgnf9Tf9lNavpdVvmaAaB//w+9241BgvHsNfvc6K2ACX3b7VgH8aMCLz/9ODP6/cTzlTC306VjbZC9jdCYP6T7J0WASfMwzziEQEgib32GtZt12nXossUBhteph0foJam0TZS63NUxc1sScAkE40MNW1XgsHqEYVIFvv3/K8EONwpZQXEhw/4/fQXOB371OPXX5HiTnr6cP70wvJsL1f7zH3W8foagS7AxgvLdIqGjJtzscWJE4IKLezqf2V7RH622Ccx5hy3CawGxtHVOm7TJje2nyVn2aAv9vOZ6sM5wTOmLyXh5I0BDKWGYAB44KjynVkVmFjOa3iNGfE9ZHrDCEisP4Bh1LsvxkWQ5ySwpeTq4ucJ+qXxfmkOu4RY34agjC7TndaEpEuH5/hbtP39pLFYQX4NcMuX0BvRXom2EbwO8RACd6DcGtIT2ZE/36zSsAhIcvX3DswrWfKeWb+q9FVI6KUQh9+8zzyjuMCNGXWS6T3Yij9AKbcpYSjxgeZsZpDGynDQQGfWPwINDGuLm5wYJi3v0Au1JHRDi9GZm1wGBsJ8b9w8V7KwGXTxP0urIuQumNLWqfHRtJwQNYUzOiMTJur06nVFigwPrmxptXjNN2wlwT61Zwer0ljh1JeuG5ObA7qGkwdE2EU07D+Bg448dgy4RYl4WlFy+JyLjarsx54xmh6tk3kQFppf49k3wbYGUrFXL2jMGmP5tCWuazZk/NQ8TU8DD+bKcNlmCjGJtFKKkqxumEy8MZc14wxIzsomJl46OkFVoWFdxQ7pxiASAdOL04VYTWWjh/uYCeu51HF5ZUQEEXuqof6V6IG2MYVKPcWxP0Q4iLSDYlQC7npmi44kem6BXJ0LZragw8BhClyQDMywUqirFtJfCr9VW0vmDsRnQ4k6nRhY5Enk3XI4yjV5wx36Z8c43FygASaIWBqsadQh0oDSpZQtQNhZtnK4k1NcsglUDRzMLRZHfVyzT2ATlzpcf746/pHCUYJWN1epJIG3TaDQjI64w+Zka8G/zRDZ2HwREoMzGiYkXSRtGcr42rZTm6RJaZG8HsjuNpglsFcxwB5G896Grk5+KuNC6R9zrdBjY35llU9cpnpSOyCcvNVoMwdu/aSDzBJxXqCRGcS2N9GyOty7E4opAdsWUFEvXnk9PQKrf41w5CIV43jpaibI5ad9BGiVvvQzunOV2GG2zWUpz17IYlAcEMT0zuYAUBEOjSigp2YTTsZuB4j81LFmX2uoDSyWw9CpvBU8tRZ04SN+4v8QjpKJlYwT3RF3oMAfP03s9sTptBVtbJs7nSfeT4UjKQgMhLqqeBuBy5a1k7FCOLjr8ecNDqD7iDwRw/UY4zZBej2UBmTzr8A8VLaG77O8cSBtSumBqspgdYmvMsXuXwXa4ELXHn+UQvgx/BfsnrRbKEsqiCBVUK0eeQGTkxzr5B1f0MspAG1czm0srgy2kU7U5HmfNb5lF5W655sFSFk6TnMZfRTeOUtIOKEO1l0Biy0zsowBx4GLSs7V8A1irGqZ5XPghiFkY58sxT7RnYFGQkMi5bCdh8fimx4dAQd/6WA73W3a4PJ0e0BKrS7zYXBSAuI7ojzSu3hKE3xmNBepU92Y+uK+wC3to11RvMBxrw32WIts+pfAKqkVHkxu0kJKa4jnihJqurRyJflYsqrjwzEWRZRD0AYE4QD2TNmdhfKFw2Azy1Xpp2TiIzWF3GVmQf0Hz7Y1ZhY3Mc/JUqHCALZbs/r9a8ngnAM4Q0nQjirYSi92zwuzFMDo6gnf1z2rMVid9PzWPPiH3visFblgdoXMz5rasc6Mwj6VrIqiUTIGWUKN1ufc0X5rIS7gZD43GqRtNpLQw1g4VlCiyTkZmqRda2ZUuD07btHBM7uMeUIltwxz+fkE1i+AfDNJE5uYe3P4m2VRMEkQo5JyANRwIu5zlgDnInGKJivUhbb+NsfSBeJaThyBIx0S71GW8lFUG4y/hEVFKJBWBiLJ7g5cGIWz0DopbRKIZbwT/y3nCKq4CcXwceccgCvMe90LGiqtEO57HHT3JeSZ4pS9TmFzzGFm+3JunsC1jGShIy+Cl00ORHnumcOzXwNOmu88OnrPchj6DkmJ385/PZ3RJvi/lrOCsfXfi0rH78/anrjps5ZCyvuLKbSpOlrWFqN9S33xyOe3ouCVPeNqx5SWKSlq++71ZljO3o3Y7MqTmfgaxiEzw0Kt7F2lCWSY/nOs1Vlwa8rKZ6UF/MN68lgz2JBWbqguvMdu4ITtK4DylXKoImA9CFNNFqc+U3mUIVto+1ZYRrZVCJDWG/Rq1y325MzstDRmjKNIAIfPH3urNeG37HQb4/YqwSckZNDKkMB34EL4Djh3+PNoQlMITziJB6auiKQQcQ1tJ6XceHsEnEuoRTQBggNZ1YiLIEuyhsvhJyT1TY8SF5m5GhVvHP6I23BkC4xOr9ZauytVpa5W+XWLCqxegwpFUACvpgGf13JbsNBjCgd4wxBMQvsD0fBR/cYLwA5o87172cz/haTsBke5edlgdgRKmaNRhQwojqJ46jJxAWIiBL3E5icrpqQ4qQw1IG9un8+AF6/hxzrh1NkGWVCTM4MTDfbTW2xrGPXV/tKMKj8KtWPcEoc6XNLYKxbJj7ioZegy750c5DGhmPh+Mp+S2xUQHVb37uBcar77h8ucX2CgB98zG+yLv0y62N95dSX39PZfn3Lb4Un0UAACAASURBVKkapPZl2unyKkXS3GjDsMQ43SgjUMKx73/SV1BSXH14Byhw/vsn/JrJ2GFl0382oz8z018dj+9Pnq31+d9x1HMdoup7ipy0ab+w9IPQi2O0AuD8e9GT5wp8f/SiOsIGEgGCTBUwaeJ812QQLGb3uMQPInxv7LgfPd4v2lBe+ZUPUNwhZBW/yElVb6F313h2YPGdv+y5D/I+5PcGSxDhmwvJz9VY9+bPXFO8T4FtyPFBIR+jItRtDtrZC0LBe/j77zmv6bASWCbyyiCwgtvVGK47GM0Oq7RArYpBvOe46Q/f/1WM/tlRu/K44//8kbhL+6SZ3XnfOCbrucxBukMY1UhIWxAye39miBNjkSIyKdV16zEEI/4OSwKNRwYvvHhFljknpgeviSJlCnUZRx1P+t6blwmwV6IEcIE7uH2hyQaNswrw20dcfXiL88fPWXFrOK+zoGNvQk6MZ//5Ad//6x/YnLJv715jG8PGA0vhjKxzz7ppAXflb7z7+AmnN68K7iGwEGOMqFCKwkvPbj3P2XigwT1EyT2CUD4yZFxgb7v+33D8Sz3QtX0iPM4Mo0YdFWUQntMiFVLR7QYswIB73OhHy9J/wxFbf8Iym+P7jVrpjxobklmFHDM/L5zehY6qxeg1HMYnyFfLKOsC78BLF2T3JGd9vcW5CXn/CiSKuD3xWzO6xTUMYLwuwwspIJGZB19nNQfjNoaV2/Qyf5tnUIytjD6Qab1DmLGYQd8J/NwNeOTuFwGurzbMy4LSAr/mciKDul8L5SCuscuUXC+75onZNnyyKCMyI/Yv4FNwije3HX/kVU1d2kMViS/nrw/ulBHwMzP2XHmpUssKStdsOh0IhHm5ePa6GXbY10JkVe+wVMhCQJbdENLAnOXYBPNygcwL+PqZwd4V0bFZueE1J358/YoXb96A+Qpn+QGmCRIrIf+of1roCmpRUywWQ5W9w0SsbJRnhLGK2xJkr4znchkdCEVaa/O5L8MzJ/erhejpfFzYYBplpPCxOpxTzrSw77qvMZ2eDQKYEjm2nqFXWamGO1HGdj9QVVPQlgjmjwXQGUzXoGuGnn0N/3/y3rw/ktzWFjwgI6Xal+5rz/zm+3+58XWtUmnJCBLzB3AARChVXe3lvud5YVdLyoyFQYLAwX4A95WuwzhXGHFSD4rDp6y/z+GRd/O2Ycw7lNyUpPx4J8Cy5uq++7Ujz96NozrYLnz25C5l/5sTzwfufTBjPVpjxEY6XEPo07HovE9gGYfU6RoDiCxohI5mOliedRK7cke9e7+KlU40sgo41MZ+eCJe0aNBtwmVZtldfaDrAmBz+jV6pwExnlX2E0FRDXYheDOxTQOROtghaPXx0xk1M/MjnU+VnjRpLgfydK3LN7mKEooIxw8PoGLfKPiyylQMjwJtIpDRob2lA1IBHYqpj0DvWHlrVxqXZbFM6+2MuW6YY8W6jsii9uZ1OzoL3kbw5/x0Kp182SczjM6ajkSWlt9pVXF/mzA607dtoPeGMTb0fkLrA7IwG975ujCAw8oOW3a3fU6nCzPyeQxVPD4+ggZkc5zaejU0oGdp3jEHtm1i21Yzqm0boIjqKFbCthT+fQIIPWDOqyhwXigLp1h+RRqczbkxR3FqQIIPmrLvuNA3lRlajFamkBKNLq20OJ2pmyWRBg1J7Icg9Jgq2a11pfG6j61crURJazT1TDJOhGUahvLgJM2NyuxSsw0SV5Rrfe/F3Ja52jMUCyiBK0y7QADfwHP62BQu/zLAxXhhGuJ32NvxAspy1H2tgPPGmWP1E9UxCKsEcK0qve/fQeJnZNXOEdHSLFNu955giWVzolNJPjhnY95JF3rhc86VjcNslFm1Bkh6ARDl6ltfclEly0lCdddvlAFHEABddhjnuSPIBHQoyy6QVlUty6zDy/GK0SPSIcES09ppwE5+Nn2Mqi2c6ShzEU5XYkl+VkpGaN0/XE3fq3QUVXmDunWPL8+LYYYCqAVfj7l50PUAte3ula5mn1bpqgTnPLltMZjFOhzOtLe2/T89+3N4KVtrMeAOdAA1O7++gzncrTrFgBlZ1m3FeX3Een7Eej5HxREg2LfTipX9m63hdLoKQ1tjewgRSG/oi2efLwuW5eQZBuQhAeD83o7PXB4xgNBIte3omUrscUcCiQuIQwCEA06II6peZY183bnfLQjQX5atC2QC0mEl7/2+cxvYdI3A2QgsQ9KR/xLBM/Vn4hXBJpvpRK2FPsZ5GJ69PjxQzRwYM3mm7yMZhHwt2KhVB1LHYIYBBRplcBXBQo2S6xw7pjSMKrGfkv52pyYjpQPIb0WHd7htSNI+P2Yr09x3fEKcV/a0MGvtKTJTnbtWLlyLcOSrU4fEBaAEUi2cqmWbm8wURfCDJ4AwNgYuEKM8Pbc4usX5N9sgWCn0LP6aTvMqg3Lv794/7v00iyeCoi4cnJcU0xpzQydgMHc4r1TFgFfPCVxiQOXIpYgfVL19lw6HDAy44NlG+axSJgBkiDt7D/QGJG7RBganNgGmGrZIG/XIMfA1gibcQX0Mfq8T1MTbEeynkDIx71vKv/Nzr5xEozL8GnveiDmPVRUAVufhsKfil5ipwH+kEeKRKC3v+7/tiVb5BHFewRYGQpmpHocsUFbCIOEXvSzHJ2nfKTomAxFNFs5dFY4Zck2B2dAbvNKjvV+b1hIglUMG1vAdDJdxXs2Z7v8G51u8ioMaTaD0kscVpt7bHIyJDYI+AMWGhh/oeI8mYtVIXzWMu1vQdsFiT9Mr87AEbuC5MYOOAPFAaDDchMRr92oCGUzG0NJK5pJk2x+ODnc8idgwtGHn9+r71Oy8VZ9LBZU24F2ATt3D9oAS5FmwqZgjMhzyADQCavZsk4ERx3d57oMnqFP2P+c3WJl1vMmz9SbmZ7vM9n46u/Ie0K/PXFT3ZZGEZVnj83S4u90EMJz4OUv8ayXsPxzZ0wqz/7ojVujyt/+G50qSD9lL4Doe7aOg9zfOW+yaCWD79I3WpJ8fl2R2ObgbdqccZWsZo/1dqjeUc+IdDt/QKvvI3aA5yzt9bXfVhXcr70JH+rOv5qAl6A9e20VrKyYB8AETX9E+CuYXs9BNWO9ktu6R1gvv3f8cKR2CRzMLOSqdllHe/zFr+489niU1ik8Uno0UbyZHTKaMaT3P2eZlul2Ldt+pijYkKz7OgUUXl5k212PMknluP8dMfBwcmNg16urbWn6DAn//jNNv74MGpqTtXBWwDoOKTRwz6PAe6CbvTx+A/hkeNPcNvX+EW3vw8r9+Cz2wJpwayWZQMoptkr4BtiCsWDB/8TuFfVCgi+lD6zwXvJZY7NcPif/+J5Hv8w502b/Isy+lAQsLk6qInALfDGZDaOyClx2iMnZ4fDWw7h/o37cnjLZAmzBy8nz+uSOIcmszbRbDJrKUOxWKBsHr9+8wv92isR+5A6MwFvoDVv0O/fLWbRFajImK8XXD6fcXGDo9YjMHcnpvS3L+lkS4QLGppCEJ6T82s2c6bqiqcmGTEdvRy+f2XhZPZr3QE5S16BH+CqcPC7qXowVs3536FYZ8heC1n299Nntf7N/SvbTigv77gnFzCzRgrCds04wOvU0svWN+WLBum5WrbQKZE9ukM8JG2luP8sHcwBL9sPyNnMbq0naPHDp7Zhcz5pZumehX72HANiLWBf1NegvD0M87+o/Wr4zZjL0TfU4LihjF2cp1rPXnBVbWsxKc3gObnHF1dR1jNxLeG+fYw2+sG0SsL3Le1xialQV3Z8gBObEfqEjD+vhoGdSt4/HxHqeT9Td/fLiDSEdfFmzbhvP50QIklitIa+4ANyP5UADbo9Oj/9fHzZ58bQy0Nyesq4s0N9i2dx1j3YDXkg64mQpdRtx6WZ4ClBWKMYHejf5HscQeS+iBin/L85Tr4kaoWAflHAM0IkeQiwswgWA5nbCtK7bNy0YWg+wcJqhZD1YnHQfOZzyqTdkL1yUnM/MVZ1/spD/VDTJPMKOF95ZcbEevZ4O7NKg1NyKerqxaQDqXbYBWhhRefhpPmf0FpCJXEkqgYQPxjIEQ0X4i9j//4Lh0WlWOeE48l4MsXv1UTBO8inhZaXcoZn/iAQEztTyTj+0imvNqZhmT13iECukydrEc//lMFGFgGTE5RhpHGI1btF9EtgaLbDZry9BgVVayrCswpxmmzZBjGc0xZ47ilFlHqh65n3OqQDiYyU9VtBiJSr9iWQAopvfAG2MzMBaOkd1d/be90viErOoH5XdFK/vXxtJqxLmqOTDceUP/8RyrV+FwB15ksCms+q9dY068Detq1U3GmMALeKSmBq4QYaCP4ORl9bVUhBCLJCvv4Ht3psGntZQD1fjchFUnPBtEUg0SsXYnlmFiVQOMZ1qJaStNvqBptyhWjWkKh3/zTJ7IcGvZN5rykzTx+Pjo8ljQVK1PrPge9Mh/4jRzUE53RlsUausdvZmsF2YQ5kZ1TGEySrwvenfny/R+wmaENhnP7CWdGqWej1HHOjVL1HHfeCBHZm9Imftp/eDnhHqmOvz85o6VuHdQbAH1ciDXZPV+vgStKRCZi9wHCu57/5307M5Q+6vZc2TGd3AjbMBZXl9kXdjZJBFw3JGBPurYwPGqlXDNgB7iBuI/3nR6ti8gkC7oLtchiEo4PFi+F0WcAulIpnFw20o/Nx+DZZ7me8BR5dGwNOfEuq5gewTyepZkp4N9DAaspcFduG4HPJU0QppxA/FuPIrqWQz0r0+NPfw8fgcgvqeGl/+lfLCAKYU2LWPT0Jeiv7iBW6M1OqF6D9pvqlH6mm1kVOF9ISXn1kuZCrIfqohET0kZWekhR//8UY2/xKkmwwB4JuWYANoM/Sx70rPUHR9zEE5x65ItFzS0xdzrnJhtYGpHU9c7nJ72lTiOg3/63MCEvuRmfBleet2zlNkqQrUYdR3Z+TOH882pEzIaNu8jez6f8Xg+e0/ZrDwWOE81eKxlnwtaW0AzobqRwyoJmFOabT14fXVWxUGaDdG+d9raKRIBmuLBQAJWlUhcFeXjpUW5c8qIurGol5rT3PunM4jLmSnpRdDRpEd2+6Znmx8ZWWqZTnIPuo/9Ao1gfAbiqqpVphgTQwa2TQJTKNKBHqX5Nw+QmFmGnmNscCe61aMhgrf58HdqrbuTXiB9+tgRvFREIGNClmbWsVhvw+RDZ/BulQZ0OkDdYf8MQA9kpb7IoEMn6VinuuPa7hMZmPy+yBHd3z6fWPd24avprEPgJu7Lak8JuiBuI43E+djN+f7h5VevWvLzI6vhQMRtBjkm01tm2XcuMQ98fPe3wntPu32kd4zzeUeDdATXNg711WOeBQAdkgEfAyzFrE0xByGDvaTMhcZCqS9lSG6rkBV7lpUI7HOFlgRY9efJbs65n4XtaDiiCUjLvxkAoT6gnfyKzxTzQoZ7vG6yvh3+Qvw8tmMpZVHJC+rc8hoGJlGPFLhDidg7121HYEWPLMPcVzYRBM224Cn8iuhLgvZMbrm+IAXLIVvmhbw5yKqqW7OCSB0vK+vonNimVdOq+KY1q2LYVKFoELexWcslM6hxPC5h7fcSfDg9yYFGfZtiVgPgOOwmM9xZ1457HyA6sU5Fh7W43G5vcF4axo8fsXY+OqdRf0XPOI/WHK4n1DnqjqlXD27hPjWk9gqCW6+QqNjgTvRCLx1mV93v2HrsecOcE10sm1+Re8XeY4JIJS0VvufYe75UPwqcAePRc1h7F9J+tstQLwldcbXv28AqqX/sRUXyBzu30s+B0cprYP5AZjHx7d8AepPy5Jt9NyXU/z88FGabblDgW5EL1v4X7cMtgLdB3RqVzRA8gfS23wH5vYjg8dPXlLsAxqe3IGULoktkebf8HWAG+q+9z587nhNu/76D8iL4Hz8sg2/9LbIanVeo/PQdU+CZsfaFuo/j4ntTNoI6KNw0R5lAf4U9PHmY5A3D3FP4L7eQH6/UaO4BwBu/jv6OxxiI/T0PfDSSlyLLl3vWxvjgk/WScbHOa1l/955VLVF4tAjuvQLtojZX+vU7Tr+/j/eeXmFZ4pGGiiaAOb/j/Ak4/fbebOgw57i/yaVpjuPu86UIlHpyyr/69zM7/x+g5z97HBbzJ08kXjnO9/OZ6PVaBK3brxp2iem2lrAqeVCoZXt7UL8afTavZtVmt+CzPt0G2TDmwLqt9s/7n6s70AMrFWypAtxC8U6tosvbMbAC6FPxRazdyQdW8VWTU9N/Qo0mzp++4ez2xqkKtA+AfsH6969WueXD13Cis0oZeV5gowvRLFbVZYSjXZDYUadCXhv3nF4mPuSIv+Jw+9m2bagtnUjrSh35sN1TcFT8tcdc/wlHONDr6+xeFL+yuRRhJEQREwSFAESnOSnGZplGksYuGkhjQ1x65nNGkMM4/pGvfnZMWGmQyINTRf/wFvrt5onC1eARLAAggoFbmBDZKygKoC8Lrj4acY9v0yOPge3bwPLeFTEaBxTeklDRYYLtn2V4T4mUppQ7AK8CBJ7eL24wASxCxd5UILj+7T3GZ89cEssqW9gfT7obFRq6NDNAiABqGT1drWxkGNTFMtKnZtl1K/9nRo592WankQY09cysUPqo3NkFzaNEmz/74ly4YqljYH6fkDcSn+/OKTTYuhmvtnFGbJgd8fvhY8reykWp261iXjTHxLL0UGwz26Kc7YrbzrHE90AajeccaOJ9z9j0XWBZSn7DsW04vTrh+sVrtCZYz2fUErsBSqb1M5TGjKUNyQA9RytKkdu4uwpEF7TX1v98Do8OnTMCQtAEMukI8xJvrhvUzlMTjH62QZFnbOvZe7ZToUg3ghl1yrqooLeGbVRFxs/0uaaCLcEHE/TRiMtMEDrP4z5CoO99kD1IYhsbtrtSaeKVlWGpWXRjDqw/Nkw8Ar5a7YVgPijUirwA2FwxP5o/n5BRYcLY0W5FHFyrVmn4mVv+imCjY+CJ5+Mnh+6HtN8VklmUuPBz93v8pFM5jbbdM2StfGDDlOlAzTg7W0UQ4KokAdT7RyYAx+brJy3bUeyV1PJeWuawioTADx5c5s4Me1ZHWwa6Ju9TL2nN7KnpayiCkvHk+7IMI4xu/nFkhtTPUCP1L6/VTqGlMatkn+/PPoDmZ2gsj0tf+l5WNcXaDYq11ESwSPV3F93ze+HKIoxC27a5o9uyu6G6C2hrLo8wJ7bzin7ygKyyVegwIXBWKLYx0HsPJ/qT6GdFZtGWMpMkHfUyymaAnGAJaJtqD58TLyPOwA8IWAmhe2lOCCGxO9G9d3rIFSi2dWA9D8vgXHqUIhMItKkbzrxn7zYyw3cMVyzcgeMOhLYj7MJ3WMqNX9Y9G5h8QmdmN09V6KChlAbwet8iFxUlmMMNJjvGYpMbM6IS7SwsMy2DEKsT6kiGGnS0c08B0KCDfGKMlolIqRzGehu2GmoVHKzMnmdOuIOUrxjE47JPXDMpNrw9fwyD2QWW5LiI44uIZbXgHIzNRbPCgjz4bPK3feWorMJCJ0ri5bpe1aA+p2KpFZgET+adPMZaP5m8NQe65HzH+zNT1Z2e5E9/4tgr5XRWprOec6vlvYo9ZcdPbURJA1r4kWpW7Mhs+YE5W2Toq7YIIBSbMJBwGvujNgvW7JM9U21P0omObi2AdpUnxAJ0yBMBWJ/Smc6IKLkrst+qLMVCGYlcswiUGBMi1t9aZVirGK8kQjqq8ySajhAe1VEQ93ZdsVYWUJ2WxdwkSu4xkxmCHU3mfZPH7dZ+93x7YR3DjPhzAjrDgRuZzgfcYvy3EcW6j0S95zlL/q0ut+dON7BKAN6CYm6QaWu49Nw7xnVOmDIxOnvCI/TosY3AqHNkxSPDUQ2zzcjQn3NGZZ06FZQRWem26D4u9DLDX2NOxsFx1Vwu9EYZkU6gmokXAY+uDzIokHPKQIvMsNw7yqN/efncKtSYnJRBUZj8nXNA3jIdT7HFA8uTk+7FewhHnQ6xIPPmAY4Wo9kiu55BUaEv1He2lNAih0k/xpEtG6UiikqkpOPk7ZVyM9ll7tftIEfic8cf6dzdO5h4kSpcZyMtkr/bs2KUnNdIitBYQyZa5PuSnFJGadwYv6Bw7E+025hci30OszcYjTUwuBDay3PzXS8HQ6F8X7Dm8d+2oS3LTpmhyNwFtLiODGGAIpIXU/55wEbIUNmvyQ7L++fVPhr2kOOLiBzoiVhJYm+r40nKdM7wBCBTY79WbMW9uJMDlCdlFHw679suzbePa86sUFl7fs/Y+4dM3XilrGyTwRyK6bRB7F2NwbujvHMd62HyXTZWo77/RhwaOwAlECJngvOW98332qFHkdDJQvcgL5u6l0lqeJa3nVMsMaVnwtFEg0g3O6ITb+JLlDn2lhjksYUfZT5B2pwErGrz6Pe9xhRgDKtAYyFCA60v2G5/gM5kQsshuqO3ERVFxo7379ZpTK+4mJ+F2NKHxMGw6hoj3pTc+edsxtYOO2zKdirKVRJERn+ldKDaoRzz1cku1cemB83Z3rV1HTc3kNevywhjILGPLtqAUNYz5iK57pN3fgJ8AMhrALdPTtGve5733Jw9d9Tq+Tz3yfi5V+p86v686mSjXrhrXYA3hC47fv2rxx/Rxb/s+Dc9pE5zlYd1EtpHQGBYK2WTt9sErfwagVcQ4CEmdK93gphL9w+vuAKhGx4SH0O/kIs/eSjMeX48Hg7vxZMvmfufaO0JiHbf3Is57GOMsZcPD9lNggXkjM/foX/93dp3Bk7OgyFo25fEkkesJBeu8VOf4Kc/Q9f/UUexX+w+xjPbpkLHVs91+Qhxmyd2OHSSD+uwYCt1e4w2LJG84jq0NGyTvc9Xs+uPYVWn6ELvDHpPp/irmRW4oeZIP3/6AmUFKmG4MWAOfgZY2ijPHG/ljR8V+sUs2NsXYOAr+keg99+Cz06300izPb6tG06nk+9BBl0b77QEImB59w7jxqqMzBuF/JcnQbbkIaqKvlgS19w2prkUu0hZof8xZvo/f+wy0PXw87mXPm7YUKXVBfpR3sMjgrwHgQW4uTMNjPZOYH2JgRyfT+Vy/3muVPdssaHjyfU/O86wfud8BZZuX969xfh+i7tvN24oRijUULWeA0Khb6MfMIYKWIYjs9EngMeHBytj9G2mkBfF0O+YX/N9GKgxlU4uE4ZuGolyqYysYyAX37rm8aH+Lvl7NSXZzN9HRjqdNijMgMpTR/M+iYKrqxMWN9z11rH0xf6GZa8r3gBUXiFYvwvwpqGLWBl3j4DpY2C4cRBqZV17bx6hjxxlyaSL4AY33AoQZVFc1FtWHdoTqdpr2c2+YHub5eZ0KmSxDJC5bZmhCWA7P6AvV3iC7FAAm3qGPcvKMQrODVRNFgxmGvPae+C8PKK3Vz7l5ea+cFwvGoVqRF9bCiDyDBGdnrHFvXZAsOt2Rntwpn9acP3yJc73DwAU58c7nxr2jpedc0i3CejqTz8B+hhCSqDor64BL5sbiuVwUEaD6GAf9SzRppFNK8GcxZ1JVpnAjJnbzUB7A6xjeLZuCypWR1Gqw4xW/sKmAA6XzwI6qaLUodq8DsxwPMjSHS8ZjT/cPwDrmgYfQShyUxXzbgIvN2wboA9Pode4mxiYOL1OFhxRkgAEV+gvG8a98QfRE4A19nlE/wvpuIVhIAFoy9KxTjuts0KBvVeLusBPAfYlY3NmcSCvIVUWnvLc8fS7w3Ol6HDxLW+chmZedEl9lEbjrWdonTqW0+JbVR0AsNRjmp1MZgB0vlFpCAOv85tgoM4bw8nSPNPdvyfgSUeP1pcq99EwjNBKImI9f5dlQnWxzEKfJzopZvT5pXNBIlPCjJhZ3krHDKyvTgA7gxyvobzxYJbeJY3t6v2yJ9zIX0CTAE8Ldl2S4D9BU+UrgsQIWFB4VLoeLuCveyecqB5YvWY/aMDL8low3xwjeqQDZpCijBNf5zDWTcvoECBAb/PFMyBq87Ftw/vFJq6pY5lT0Zo5p01eNbNlt/3chPOjcW1sLGMDRDaIumEsZl7CsGfzZ8FpHQ2LdHdOOB04D1/XFdrtHlMsuESaQKb1kB9jM0f7es4yty5Z7R17lEmV6B+Jg3HTURvXJYUkCP8EMB4fQJx8fhbaSNynk2Wd07g25ohMyNEaTdBlPnNOU8EQyMyx09ht81NoTQRMbxFvnwIP4KNDRrzkKUrjQ4VCW8dwpqtTI+DGYJ8FRE2f/10bFC9OKXSeOqCuCqAc3stoX3BU7qvrglR2dbVYP+bVs6HE6KJ78MgcjqA8E1p1Db5vspHGFXuWBTyqdcmY7jTxObXl9koBcKc4eihy0jKTPNc5Dd5WPttKaO+NLKktZPlLuCFdyxzkXHBqwhCtdTbLoYhWIL17H3Z/HJ0Etbxofb7dd/h6uYws+5vR7rwPgwS4b6oshxrdsJUHxAIBR++Gmb3tT3f+01sDFqsaYj3NGT6EaO0Q8gwAiyGxAg5byTQ/J3WrQ4lQ7hX/39ThPRCHBweZ01ZmzrM6s6Tet3MuAaXfL+LZ3EmhuwhC/ow5gAlMsdJ6LAMuau+KQ/apVeToGfAG5oQYPYcsJrYre6jS8JwDuumOxlpbLPBFmHlm31kgkqbcPNwzZEw4Q8xhv7Qe6wawIpPRSR/e5mkqZhvQCc+g1qjeEbf3rLIuRr+Rge1rHLwD+TsLSeV6158az1HvO871MDpv6TjvhY6R9CuAVwso+8Jl7Ax6KvjGHWrhRNcJK4IzI2NyerWChgVoExiWpRTcZKoHWLTgY8QCw9uFQB3/8dlqGMRU15xTK9tu8sD2lJTz6bx2+dAsiDxbORheo6Zi+9H1Ws+SsmDPwdO9NCgrdUiIJMpVWxMENgn6BR0uZc8lA3TadXwKRWao5/qrAlOIG51fqmLnPAesn3xcW/ChwsvaK9NVd/pDPeJuJUslZYJYOwhByUTnWPZYixXYAhNTL5AGnaPoz+70XwzMeAAAIABJREFUf0LnyPkjxivf9WXBtq7+fMfH69lp48Rp3fE3BphkL1jb90ZbLfCQPctbAFEJLeOp8rQOl0elCwbDSN4g1zb4Mdymovm8sKf4nvZ0cW12nYDz505Upy3q5oWAYr8H/w39KUeVNKWlOuXYyVloyUbXwzMA1MBZ2hEty8w1MlYGcrrf8eHQD3zf8vM5o1oLje1MkjnqGLtD036XdEM50xDVVJX3jT/K3WxuGZhKOiQP3QcQOe/3i4kLNXRBr56gE9qyv3rSkO3nWXD18B6vgwF+fi6ruVWHtojxQcUbSLuHzjP0B1y2voTZWLoFk81XgD4EX6bEH75pjMQ4FqsetY3hmZp2TreXAeBJOhCcYMs/nK67GPUStTQIOtg+S2JFwk76UrDdkd884LS8sQw759smX02GZuJEcEnj80BUAANtcUGTGWQGQel5bjS9fr+B4BXktZ9/q5A3PnLhs5yx+Pvs6C+XcneY/CdFFbmu+8t9kPGnAJhfb4H3+/spSgWwC7e4dJh+Z7+394B+e3p+1RmpxxiNecKQeDA530DVqywVngigfbTzty/fIXgTen/TwsEP4udegJdlSrSc8rP3+t/y8G1J27gmyREJAF8E7S/GR8ffLXN/SMMi7t/47S3k87eAET9czgb1PFk8/48ieFPYWzRnMzkscoJDF5H4e+9oF18fsx+EHRTAC5SqASFv9mMU6jDkx3XwThMv/fXuDdLhodVgQuOdL/y6+7CVmSzZ/HlnlzmbV9TdPn8zP9Bn44JroSRqrnN8Tb7tnw3hOu3psYtEYoDU78Lu5+9zrIKDy8c/S9f/+P7Y6+05oAOOo6xGWQfaTfw+lb45IM6mQFzPhif5JF6tczvV9R2hfjbRpmJ4ILjZNKwa4DYG1m3Dupk9whJMXCcB0MAqaOr4D1ZReVowdvOKM6sAr6Wb77CbPP/SgPMArh0LMVArt5YGrxN5j+X3hvnpu73rR8X8LJDfh9tLvkDaezTp5g8bE9vfv0L+8hHLckLgfsB1LvhGcV+NKvqbV0bijjlqxcixKqauUdnRJtWTK8NDCVdVcu/vKcbk5Iw9dlkn+GePfxf/Xv6ZG9drL752WCLsmKre38munq4AH1+vZnjYqSks/8zxjH72x9eh8HX/Ob7fYHn3Dtv37wGya2QtQXqXNwB+QFVxJyxKsz8Ut9i+vkN/3zEIREKPVVj03G0qwyR0Khh/ghwqCDi+Y26fC6wsDBz7u1HxsVPEDcGe5aKw/uduzLPSwzw/Z1QA9A9m/BmuFDQxYDvFyshOj/hnpnILKEDFyzNoWjdlmHdvGS2z0y1b25Ul4rmXprJmR8Sbc304oRTEwI7J17lq4cSwigLMirFvTeGRpzMPvVOs7RHaF5wWK8ENpeHd9k3TJZRk0o451gYgakEH22oBAq7wBsyfpqAKzAi79FNmRPae41DF0q+wbWcIgOXqBO4OltKErrt9yUxJgUL0hPFjQq5d6fUoZABWSowEDnUlr2R2JcwrxiFThwsKAl4B280GeTMgrWPxygCmcLghUVlJvUKRun5wwMVy1T4CFxSqVrLPljmNOaM4dmoWkTSLdjPndxUZivaiuUPd5nT9UbPMzxBcQXCN9pJZOOSW5yKN3FBZ8KwSVO30qSNd7sHbUffC/lt/H//lCn94/JzdyrNnyIXf9g+vm66O7fn7iYhl3HaWOV3cUDAx2wSGBcOwhCAdBfY4V+dLOScUhTjGFVHnEmVVIxqaw/6Do767wAyovTUsy+JAKfmrZZVl9i8zgTPbJ++1A4qxfwq98Aoas0dRjJ4ZazXaaVFihfslzyy//Sooqmsru48I2nb95Q4HDdmRge8vWx3hwdYLLiHw27w0fSsGS15D9ja3De10VQA+PDMkaWfOibFNNBmYs0fVDjOoKJJVOv9kJjDvOWOQ2GXrSIt3i5kd04zaDYD22GFN+c6ci9wTzf9NKKZYVYYwLsL2h5U7B6AT2+pOy3WL3udcIXPsm5w32k+Bu1fg3MAqdIaaQSqwjWrwL22lvCZ/Oi+mc4fGW/U9MLbNM+Tt33SNqimDSloolukg8vXjLLtSEj02Jx0YqbQBgtaTRiZaGJWjEgWSHljhn3KkuQNBJYEEI/wFE9JO1npjsZKZ5hibnuzNrFYqGvBn5LsQG4FKNhDVXpw4S2k7+zk9MHFSEPo81V1LeQ6n39bMARHKHHKvsRrGTjulLA9DmMb6DlZpQY92L/l9OpYR672lcZ7UVfZo8DCuY/AsXDgSe6XO8VTGKCyQZ1kWvHjxIu7P4BK2Zsms6BzHDnJIyqwaWGI8SCCSDvR5MIDwJcLZCWBrJiv6sqCH497vuyxocwBtSfqWgvc92JDG8wnE/omWNO44YOR50rakDCnGy1wzM1lrM7zUtAS+1fWo490v38UPmAXcoFh0wcCILEWdasHSAgwZOU/N2j+FnuLla+H7ULo8yYrKJ+/pQVrda7mvN76DCAifuwcFc5eHEUiIJYrzXpmbi908CtxIP7xvuLedmZOZgRaY2jAhszseSDpIGe9yJeCtrz0UDXu+dZRnQc8HsauqOf+DzhV79uI00zoDo6mjpPxj5naT/AlkAMDYNmQJYc/e8DWpu59aglVpy/LOkAlMq4DAgIQxJ0bfDj3LS0DumJkRvNt+hU7J6/13ZjbvKLXO3yz0A8T+UbaAo27vwdItLiVfTSy0iYVTmTMTMFtBoSt/9yniAVfIQELVLI8cz/XvgaA/9siu+yGdckUmVzAJlx/C++W9NOaOcoHy3HjDTj8KHTXHV9cg18Il55ie7WOfS04Vdtnmks5bBmygW0W0ign3FULcOSYUiRcFCPpywthWHDfIHANtOaGWL/dJjDkEgDE3W3e2o/NTLbhuL+cCs+ZMHGaoOFrr2IVrsR9m6gf2u6g6ps3zbH/AeKU4Dph8xsGI7zJ+xnrzG6fSqiMJAxvS+a6UheoO9FEDKClfs71C0JYR01F78LnSQs4KDI15iD3M6zTnqvI/ASA0MJeZ0yLPOZES30qstQlYjYfY+BmQ68h7Vz3JTyVmFatoAQh0ctwxCf6OM7D5jjacL2gJlCdPRa3C589mm50xZwQrbmPzMuqKqY84GgMUHtzTO9rK1L+GMQCREXh8ApBtYLaTlyo/QfEQ/IfvSQdJVAMp67zDOM31YoVhjUL7IhY4V1XJoIFytJcvIQJsP+78kxewKpw8jvvadK4mDRNZzSX3c8HTvpmM1n25NKvFQDPgumJY1R9o8tad6GyjUGebS9vK8C7zJ75BpcxLZ+Znr+09v2f2ubz/2d1/fnB4rJw6yYu+PYEUh/GkzBE0ox0hdvHWBb7N4rzdXoTTwhv8/El5vPxHX/I/7CDPbh/tr6nT+52bDV4gaL/BMqnLBeG4DP64nzDqoIl28tidKftfU+wKVYu8bg8RAppJ+Rs4wLUL1x1Luu9O9ONe/pjOTWPnCMq1TfDSA/sggvHlBvjtbfCF9hEYX5yuxeJ+hHfRd1D9dsC09u/Ox8TAjp/t3Qsa4/8/juNi8mMUMgw+wC+Jp3zFnPcmBrZkp0Tbdq6ZfryKGjFl69EWRFSwjYl1DKwe1EV9jFVtG9R0zgiSVHyZilfDkju6WpW40RruesM79wtZQJ3Ee4zi6qA92UUprL2WByn/5aPDC4H+RUPGCN65ztugU3FerU/5+W+f0f+fvybuEYn8IwA4LUsk4EaQqiAqmrHKDRTAmIGVjfwFv0qJVf/9Tz0W4DJzO77Sc69YlWuHzWkwSBwZREERzjJLabQ6POHAIeskF10xGGNzIwBPG4dFqb6YBLh8lOAlst9FfpoZ6I8A1u83Hnnq93EDbRPBgE2mANEb5oVvhtqxS3EHQLB87Pj09Ss+4G3Om/gGLqVzRJnlPsMochQiR9Yi2E8fz7e/LbqsQ3bXKe4h8gqCV/mOAKT2oXTgTzQ4VXH1vmHeANt3RVsEeMEIT3Gw4+siP2zs3y2UUd74/XIybc6bBQqIO4Waz0kIZ+nlhck1zRg0ppWLtOQvk1DqfVpFYL3luMXdwLB4BjqNtNHzl688FWOuYA/k6SFBXKssj46k1TljnSJKk4tCQ5oD5/bKvD76QIXUTpxjYp1ndO9zaIzTjELosouatXGIZyg5M/YNN+f0zIWqVAHXL17Yc7Ysh9p69zK9WwJSAZbTlZUJ7T0NXGNARNGvrzAeHjGh2OaDjQUK0Su0l6YcjzXLkQhMsRlzA8SCH5RlBH0mjWZrRxE3kCki8xquoCiAgXu8Pr3H3ZevkHfvbF5lYt02nE7WgOHh/t5aDFydwMjrWEdJ5xqNxQxGMF6jWM+P6H2JaLMxJ+btRHvj1QTc8QN4ecjXXo7z3ungha1raw14Bcx5HZnpdJ5XrmT0lBEf5J9UQixLNo3TJARFgtC65iHM5yGCT/9I2BU4fAHE1Oz0wyW/dFQu7P/fHUdO7ctWhlLQk6AYaMy/zZ7hNBirivV5DbnkHJGGbUi2G2keAEFjd31/OszoLBMBvISn5nDzD7k8Mbtz4RUC0LGcDLz13jG2DbpZZuAGccer0z7LHBY2WjMs6kzbemvQ0k44h+ZCCGR9crdtoDcJ4xUvLtK4/DxkJ144FNg7gmOBpfxzWRByZxwuvkRgLB9IfKHImwtAZzGvbQijFcu5A0Bvi5VzF3MIS2o5IG6RdvJMMneKAyUL3bMwZ2at70ZZHGj2z7NW4/syF5IlLmkcimlzkG/bv2NxDSFM5HQyRlaZ/cmAOBpoGfyxQw1hSPNeT4+bZ/+uYLaWeDZuDwcb0b0tFN8nV4CZ/dbzqbFqg6/VVHj5cgRv3hnr90ttGdtjg27eHmOk8y8wYbPgtQY1AzU4R4e9DDNCqgsZGm1p6DTZ6DylOF+oUEkESPSomEDHhDl33BgcZUgRzibAAyM8U2U2ALOhtRF7UGWChldmB4ah3A2H6fRKXhhGRyACwcg7uA8eH7ZcreIgmf6P6zl0mj2y9HbPldbgR/n5nhOkcVDd4eRyfcJaBXhA33CFlO2dulgAxBiZiZb7e39v3r/+LodnA8Dp6hoKxfnhcWf83AdkpaGfztjeO66vr9F8PK2tWFe775g0dPqql2xc8jSKkBqIBGRWcRSLoVw5vFODRIno5q2PZu8Z9OHj7p2uxtx/5iBJWRXj8mvnxj2ee0jnNFeztKd70BfZnOwdkew/FSrTylBPIDLQtdWFyDl4Rl4IPTmSEkmnfb7row2FbgjaYFl0X0FABKfTyaomNTXnuUz08C6V5zn/IR9nhrMUXNGElTYKfxIFvAKSGSOa95Bsjr2JR+zaLh3aNJ4z1ZzgxCNJi4aCWYLXgliAcCgUp0u2TmIW9p6WKj1Ff3iIO8YOOEaIi5ETRDr05xpvNEcXq35EaWR4eXNv6yWOt3WqZShLg3Rx2eHl9kkXU7HBe5I71lZoGIjAH8QsrBqCdK7Y3EygaeBdjIY2JrYmu5YjlKt0HLFSz66NzZN1of6tsU4xU4WeiEF2Biq/PvRMOnHFCnbzmep7swwBUATW621J8nVdF0BxpM+wzQQvnsUp4eNTSAKyKA9v/w26crlpy18DdZzHcN8DFiQmyVe4Lgx6mqCeVErt/9HxhEVoPK+HA13SkDcsMF3bhg1G533p0LZA54rT9bUH5G87LFBLuadVX0tZ/KdDGdv6hIdRD6SsM97LW6YnjTYfu0YdV/B19u5pLTTI8/NhQTS2n1H0O+5h4Rwdxur/swu03M73LWUYs7MkHgRCDmJJ4oYdFERCLQabMHiLzogsbYrEXsw+L1gpcCHHfJwH37dODjlfEc0sXhpVQZ1O9tMXeCFKwGo8Kd4hApx2fFW9cgrPdCzgGyRmfXJPiAc7HdZzN5AM7iR2MH2jJBo4T45s/JhzbnwuUj5nwsqjB234Qw13PQbWN+f58FZXLg91Ag+PlpEgL6DzEYpr00MGIP3sc9KNR2oHhlWssop6d9jGAl1XFFI3exbb2dHxreX94OKODmdfTQuQtd7qrYnzZQG8dQzTtczdoFh566lorw3TqQCn9+8gInh4PDvasHk3PcCrYI6Zdh4RDz4roghiVWbgvNLlIUSyJCiQ9sHpFX9ub73XNHD99m3Scnvl6+wyZ2Z7S2INzh9CDs0EMZfQVeUXu885S4o9JfnX355++Fzg4fEQAItXYB2uj7b3PoZvdWg3AN64PXCfgZx6sT2wuVNofhrAb94+TAT64d1uSFps6bGH4TY0pOijGHriiP21V/zF4xdk3T94FPgfK88mXZdWnPrj/d+/BNbrZYwPnzNoXFVxH2Ve44kHFZryoAYTUu4jbDNcgVhOLkDQcN6U+yr4rwA/XAYkTjpMQOHHdv3+zZNvPjN/Tw4N2lNV3EvKg8CCzo/um+Ctm8hWTKyfv+Hl7x+wffqK8cUDnbBfjwFgfvkWYTKb3/fuAqkIgB+u9zDYI86T3Y9SnWf/3nnbHbK8+KzLs/Hzv/+Vx04v11z0+nnMJTFX4J+0cbDKz0TR0ElXvDU0ZMec6vLR7zIGYG4XQOAl3M1hvk1WPrTWjRzP0s02rz7eMSf6GNamGcBVE0A6PqLj9rQY3cwN76ZloD+a2KOEA2CBsQ4dcfe3TxAAr/7vv+bWUeITZPtJx0PbtmL99M2rmCpMsfVm0EXPoD60vH+D+fUG/eM75CrnT8UGOV1D19VtRfbNdFstqe+JdyH2qf/4RRnyq8dxpP/uY1fCfads/dKRzIgB7vX6aqOIkrih3FUAfGTG/7OHwibiJQR3yFg9Rcb/8Z1Y4Lthv/L3onijgk1vQTHwAMVr5TwcXlAE//XhA7Yv254x7JiC/cb+Sc8Zm/5VB3uvA4LtZmJ5lxGOZEXbt4Grj90AsTSM73fet+7alSLF+H6H5eO1GwmKCVH39JABohIKDS1WIhL01FQjcqiyfZujaRFCc2DpJ6iO+B7AEwX9KaBE0P1FEjx+WP6ufSPyfrlKMVaWei0fTh3BXRK25nV6b871oRuaNwLgKaoK0QlmHSrcaFCMwVOtFyQBeJZqNFpiZP7YchLS8AhsOrA06+e2LAtOfn7vC9bHFXOes08vrjwyufKARzR5EYZkll0zo10ajRmE0sWVWx/AHOoggHBQkDsgf84fE4IXUAAvP37A/ZczlrcdA2ZwP28bxrD5WHq3KKpEZU8WlmCIBnz1LJ/ujgNVc9gkIDGjwCVHWUODvrQ9LVy3wujkhX/ujnTxz1i54KC62+8BHO2KnTyiRYMiV8uZTigNBKC/xnD/LFsm6H76OX7O4//gQT8f7373WsS3Rd618nPCAnPSonN8tmfnqvN9X7dU4tKRXnv3ZZYz9i95ROU7JeEIaO0+vXd0v39rHacxMfqC0VaMzQNSRkcGfphRn0afcKbsDGw2R8F/qKCXr8PuqpoltnfGsGKgjgxQPufPyKX9+5ssEC8RIQQKcbDkaczTM4za9pvB4NrnKMyrkrQZhkHuJTVn9MCALK4IthxjPeYY0NaLzTkdFOKBW+HM2ZWjJrjN91ZFlkx2g7dUWuwNaFbimmRDZ8SMZwDtJGCfaru/hVfFWpXqG0ENbgwTccOVB4jR+GOBQpZ5vjKze1q/wS6W1dmZeY5Cbv4fDWO08zGrDY4R59t8deGcIZzn1fBOo2klHxoqh2f7b96Laqzm/CPftEAIgtMWGGy6jFbnEyz5DjVHcfB+N+qKl+5aGtz4W7Lu0bxcsfMadw4JaETjWm3Qwd/Vsnw9CCOFpmGe2SfgpeCdnce6KDdxTyMIFXzh/ilbhYF62T/UghjCQuy0kL8TP/Ael7JfnCMoOcOvyYlUfLG7gg4W4tzM5CZ2GOHErZnZR0e03VsO310Y+2Fr1325Hy+vsKC43hZcX7+ANMHwMvIRTEj5TB5KsIvkPYGH5Tj2iTnNAk28lrwpx95gbUaIj3trho1jXht6G1A9hR5WnTTgtO9ElJdwnNNKpPo/BqFYZalCU1r++fXK6JdpBgzt3M92ohjgA3b8L9+fn+x1pMKvnO+JR/aKCqQXudbS0TcHjdPEXYlr22xARxgJuOeeU+JDXro8YDS/0NDvE2LvOqM8uznEa0UiwdI65tKxLB1j62DWs479fMQyscIWKLNST4jwh4LXYy4Pe8HIkLpVeR/Zf3Z0ogvE1/24j3ysygpyXmZ3jpLlmkGplFeYwGgjy/OLeCn1xRwf0/jT8KwOloXPzEoOoEHEqrrMaUG81F3sWSbX5mThjZRDgHjme8OyuFx1WsiACQ9cRH8yvxUHhlxSf9+gmIoLvW1WnXhUx5t4lAkrWE2kGQ/uiD4QZdBEeVbFs84fp79HyOPj7op9aIFL5Pet3Kqea9VUKIOS73N8cb+odiZA7zav21qeZ6WjqeerRlf5J3sgnv/sZ4qxrujeqoJr0ftyCEq04HLxlqTi/FWW065STpUdWS0oaeCIcxSAdHu2jmG7s9xvbmfIQhNbpWFgji0/bx2Bo3d6TkwunEgP35fTZHfFM8f+2yfO9IN+yr+1Uo/uz2cVj3o/lkHdHUXXCv7SJJyIFTdTpnJP0rn+xGmO3IuxrtzPpId4cw2aUIJNsQBl0nHYYQTA2K/X7j1m3rMw35DL0JLvq8d5dnzlfJMYMe9DMpbgbYEZuNB+uzm9o3fRKY5BgB71CI2MG7+LKkTHTl+feg4sEP+8qgmDP/FwZc5Lr6qouIbII1p7FS3TeL8W9CTQeY/txwsA3s5vWDHjBsdFIlalqcGCbHKHxf1C4nswp6LtAgMAl9NqvFMvBFs3AHj1cm8CUmbxq1Woef0KuP2BcQdMvUV/+xqYzZ3ohuGc1Vgyhc4IIrGiYrlfWOY9eAsA9UQfVcX88ePAGTjkHKA4vcTahvzAU6ZUCdQ/OyALXDyC/nzt3gq2m9Sfy+18HqX0k99/x98PlAgAFrh44Z7cl6I3IVtF3pT77K/bY508K/aIi8gjtKt/ly1n8PVXlJh/4fHvehydq3S+/cpzFgBXv73D9mXf9z55SnEkA+nPqQexXctg2ac78J849PDrcSHhfEB+7Z3/qQH8wje2HQXtt3eYn63MNk0xDfLEtwQAEDran77BURP/uaz/P+8IWVgxTPmvUaymSCGkcWjV/PcJxcAEy15YcLO34G3iTnM7Z7geN3RiVat+yEAU6s20BZ696uICweyuIfaGj7Jg9An1vgTkQxx1Jr+Sf5W38r2WuMf1A1VvdSRY1xWPn764vM2bpR6XAXq8w7IsWN/XIC2JJAcooDdrFqK5YIf5P+XYlXCP3w979/h5ga8AjXz88xnWxSWnsRRaHcJFyhdgo5pGNf6dB50HBDN7cV2Ngmm8gpdmcGW6jJ/FHN7470MYswjC6hQofAeYW2+YVoANFvW1lDnqIt4L3T67fv8O67eBh09nKH6gi0L0NSLVwcE3R78pQYyivj4BNTOc+V3MvxtSW/nuuUMgePOXv2DqwDY2iDSc3mc0dDUODrnH+v0MwSv094opr7C4gV+aQG8F7fQGcgO0j5aRaQak11AAywfvBbdNi2pcAVmB/tqsyNtwcCbxCuHciU0uqezQ0N1b9+hld7h4Tzqq0TS8kg6YcT54vgtdgnnrJwUcYWDzbIk5J07L8mRyE5Srl/3OdTMfwubXMztKI3vRH5GKq3ovXRlYvIwI9WijRXeGQ9xZnvMl0tCXbv0v4BG7DoC69+6jIf/kBojHhwe8fvsGDw+rlY5vDcvVKdZ/jonH+1swnD6i0a+Bdncyw+ELwbxXDH3AerNheb0Awuw3RWvMjHDjsxsrvGBKlLeiU2cdzHplD+fMRlEIlrcNS+/mOFHFxB3Wm5dJ2W8mtlsvC/eGc+fz1jvg6x/J3lIc16JYvw8oHj068Nrv+wjg2rLPw/rKyK80Jog0c5yoYnHF8qhQ9d6hrxXbD7tLZ9lPp0ej3xXJLfk8hWpukqUvbuDaQzIGLZAwVBFZi7R4MkMmHIxSo/fyiQJkZs7BkEMnwW4vHAwyT4+KfPmAqtboTsHOWyXAbOw7XgJlLgUzhKOv3CFqgAFAY6Yh0LzcewcdWBIRnaE88N0ae5/nsycnhIpcjN0lTyvZmmJzyojBJmK8Sxp6m5h9oo+OIYIVwNgsA2ky5a9MoKpE9gZ7scHdylFlIfiMwJwHRa74fhb1SHq13uBzFAA6NZwr++IFfwDpn3yVD1UUg4CvUpPmvPwXC1N5RtIToyCSypi54LjYL6MRa+a+c9nPQyDp4AcwhvdgFoVlUrW4v07FFPtHQzPK8/Nn3VUIOUFcYfxEoR3oTSNjB2UPTGWwQ3lZkoXv650yoWoZdqye4Bl4TVrIojEm5lwxh2WfjG1gbps7SoYH95hcXzwLljrJDp0xmy0s8nvwyMooGvPqQH4OlxWe7XKkG0060TGxbWuU0baMJTfrCKBDvNdj92xul2NOx09IlvJM8we8P69hSG9N0xcPdFmyP3Y40HNePZzDs6l6yaYCenH2T6ivm5Wh7rNhdEbte+rKAsjguc7/BVmC1yPTWYEH8FY4EK8aA44m932sh6tlmvTYGjOtJOSx7X8r3U4nBEsRBw4HkBrBnmczy7NmcQEKi2nzvTlSPrYmkbEv3k8jsJQWXaIQ1g4j7wiHY2m4evkSEOthq44tiEfub27L/VJ5pAPXgjIsuCoDZdzJXwmK2a2F36q6LpEbHdzndKJrGLXre/pIWoO19DC8N22jQGC9C1vbMJqtdx8NswnaEGy6WXYjYK1LAMtoLtUWiKMjMt95CzP+6dhI5Fmq4zjuoONYPXpfXVhmQAz8WjhOKVyjMmpUPk6s43iZGS1NvCKRZ+PPFgGYc+qOjrK6SA8UZc/q5gAaieOU78N1EkQWOR3GymBQYnH1dj7rarQvtg97B6YbYtjV2+jIq+KIuE7gWA62D6jftOZBEj15vxSaTHwB0ElOpziDCFQz8yWm83DQcd5YLQB5jzzHfrJsvDj+A0WPAAAgAElEQVTeHk4fvXVMsfYcS2/mCFEFZJa2KB4A6PQGGK/sywJsI4L/7L4KeGYHeweyB3rtIb+jkh39XMjuFMMa3H/iOkZQoa+lySWETOTLG4SjzpXzblazLCVOI119l95aBIiJtAjUZXBc8AR7aO4VAyXhIOR6RYYRebamczBn5gLm5YsUOjj47/z5uW/BoSmrGzhdaQajxdWTTkiBDqsyht69ZRfyQdJBsGL7IktFRvUcvk8KquSNZV144T7QFbHPOM/2XcccG/pyZfR+2Mc7eqCsLWtp86VljTgcrlVD86p2MX+ArY+3OzCRW/ZxS7tCYJDy+HxfXD7kKc61l8hqVY4ykWXqy6rF/LoOG7yPOkIMDLL7j5Wen/48ZZUcaPy+t9dwvM7LylIq8WzQlAUzgs51f6+jfXFH25fwMJKXx95Q48c29hGMI15L90+JZ4t4Qacs4lvxO9sYxh4OEHnAJs6T5/CxsYAYHVWA4y6vrNkEo5TNJ40EfysLqbrZeTx/NkBG8A+2HIrgqhWAGC/Xk2JuHWNTbNujlXD/MaLCiNH3o82XegBpgweTntHaAmlL4DsbA2WUYOIBAsFQRKDJBoVoQxfB9du3aEvDdvdgTnQxeTNBWvL1hZjdVMzx2W2iYM4O/towBGjvXmHRiTEmHs9niHo2/MmCDNfHM9h2gPugt4b5+iX09h4rJq7nwPbtO64+vI91ZaDB463hxeXVS8Matz+cn9m6tFev7Gc3O9ycE/jxA2enB2ZF8thubgBVLO/eIuQqaQ+5z20vmCxJYiW23MvuoGH84iGAftewW9cs8Qun/tK9Bya6Zsd263/uchjYTQKdNao3EHkb+oyJhuTDALDJLfSL4uXvH6GwNktzToxPI/ii3RMFIGiMffrHWTvqT8zTnzoOQpcf+fHCv3qU4NS7U391TDo1yoPHUwO326cTrODwDi9+b3j89M0qG3765u3dxLVlxW3YqiT58DPvFMiDASIiyCBwH5Hs1yA+I/5G4hzE2Mvhsvil08t92M4FtIXuAn4L773k4KPsfzrDewySiOAJmgJDzADgu5szPrg96uHvXwAA17+9h37+lvsXRnOv/q/fAQVu//Z3AMAtp8mfRVzB8vIv1HjegFbyyYSOnKbjtP3SoY4R5Ml8/PIN9k8TgHoPDvMfGIs0v8OdFBulEkW9vnyuSF5C3syERVYJjME4xplqsaYjSgS3gnH32HebDToARQemWAb6LBnoc/pnvM48gQxup+68jIEfIvi9NZw+fsCnuzv8rhMdCgzFOoa3TlMs8z0e8feoLDOn+UqWSVzputS6mf7bWlTdFijMJg5s64rzp69Ia5TttTkmxHtHb5++4sVffwMA3Hz6grf/9ZvprN8m+m85b6TJMSfkbcf5zoPVXTcOXi5H6kl6iKqGtfLZBRL6VXr9X30sf3zK5SN4lisczO+pEU90drGvFjN9kjgTYKbaV5ifg1Itf/MQILIBgINitRvF5UPcYfLC/26wgAp2sxIRnESwUdGtFKEeaQj74g4GFh+816YI8KowNPYdhY+5eaQ5y2Rad8u5A0l83CjPDQBVFHqFgXZmXNReH7yf/1FulL/zDDPSNHegh9slnqWq2L5vIcAEwPnrtIyYUq0KoLFZ0BcvWdgFsxvgPV29wDpW4LtlsWk3BhSGdgWGZqZCrpctLZ1V1QirOxrx9SThXZIDwWguK2OXr5H9FCLX6vJh5Uh766GwmayQzKqUZkxMcizi41Nn8NCJR32AnK7R22L37N0UGi8DyblhPyYIe7J29MUV8zE8u4DG8HyfbWxY3Cmgqnj5+hV0TAsAcCAw58A439v10m0NNRXmsQ1s+gC9mWi4xtANHQ26FvDhwtQMh4Ix3HgxNUpmKdQzS0xojW1maUzXyD1XCwLLyFrXEfvCnnafBrbvAsBLYU3F0NVL3TP4hgopwoiV2aMaSp/d9zEopr1OjpdUEFAhDWD8hjhB/T1dEeTat5dZihAEAwIoznuSDIdVFVK8T2Wph0wX35PMjBdXanlP8b6O1XHIo4K+S59fOsIZw71GUFR5j/OnmtmdGa02k8wgrxHcPJpYxjaVyLpulS8oQREKOCK48RVTsxyl0U2SLqyPZAF54ko7xxvG4QSBiD1W3osOR3D9NI0QMCMjHVMNCmVmyqJYYQ7DBzxgbMNKoU4LKkFr9jeKw5HGnoI70whbeFc1poigY3GycBVK+U6lakyUqePe1tBN/xj8yIGYmgcv+J0m9+DYrfb+vuUvviOBnVJ++1vGuk0zQimCl1damqrQ4UW01IJrGAxjzkSAzkTrW+kGYAFam5husFKX58HztDoN9xgGyNYPnfyg0NAYE1NXTLFy6czwCAoSysTcN9QOpCkscTpxkc6BgY6O6VnTC2ZXNNkwh0brDpv/dK7laO1/HV6+vXslhOYBi9zrknTVvP9wmWiXG2kYjW+n9RMezHihnCx9EcKp1Wwttm3zNiADcBlIPrMr2e80MDXXpCpkNBL3bop/m2LtMQSQZnJ0WRb05WQ9p/uCpZkDXSVLNQMS2NJ4rfOOicA0KpbBvI3N24FY2xTdBjAFU4bhr+ifqGizQxeWNp1Wvj5KmwJNh5X1FQ+Qc9yhJ8VYB1ZZsQGY04OxlOix8IQdb7bNdYRQvML4RUNrWr+0a4TlOIMZmZK5rS7b67Mk9ofAnJ+9NQBL9Oh2ksR+JMQ8dj0DIYGUJ1G5AcSLAlrqRASnF9cY5xU0Vos8DfhS8hOn4eF89nw+4/HxMf6t65ZKJLFFGbMFTFZkD1QMRic6+XA5xfkl9YeUOdzvQxUyNmzO7trG8s62l0gT3K8QKYGDRQ/pHaflBFxr9Har+5DjrIFAKjBH/FQ0PdJC4loLDiP80f1J5d72qe1T206UOR5AWfhR7PdmPeWmerlz5Zz7Wm/24NEG+uiY3RxZYzEeGNnlLvP38290pGolbddtxbaNcOQbRRn+XefEMifmPKFJw+nqCuu62rPmxBjbrrx6vMZUMCChiVgFC+ed19fX1iKMznsQN0le62kPzZ24c87sWztHWQV/3lCoZKl3w9HmAIeLXZY6Joyj/Jpj4nx+xNZSPkoTLFeLZ1G7c1cntnVF7x3Li8WrdlgQzpxuKFJzrp8Wm68VgMxhJRNhbdhs3ix4a4x0oJMAKjYxPOPZi4H9EBhACv2NqRB4pYCClaQZPu69O7ZQwwuuaAnoZM01ohJGp330gIbtTVVgc2ym03spD7Ugm97QVUKn1gkoK1yJO4I9SERlXwqV2cFRWhkIPcp0BHup6NBCiiVw8D2UAF+tSkoKW1dFHBMQ66kHqXB+43NNWDZHzHtDgy6Lv2OtPliroMSS+t/+nAiECM0q6I7H3CxAzPQbItdm7c+cTltfvOJBlvsFrGz62EZgHt005kLE3hOCoEGrtpBBNKYjzxhr6BLHg3igUy4sMV/G3mMR9mtTjiBlv24XxFNOV1WzfyDXA2ELYqDCJaRu2lDEL4Tw5JkH2SMKbc2KdSuLH2SAi7reJKLQZm0DzfGsniFM/dtlsztIVd2kNKmvUa9xw3HoMUg9hPuH9BhG84n4CEAE/qt4P+acObkw5zH3xLYuxPRwfgTAhOTVMmag/CeWeNApnaubvzo2GCoQ99YbK7ILmjSI83v1eYfSeaBxgWCaXgsBRq7d1gVNJmRpMBPDZq32prWnWR+9qpM7l3OgXlNDp++vBY3Y2CsxGV+Y0Cbmze4efKkMNtwODlNLqmnbBpUFmBPTqxqg215GVwgWiAx08mExrK3EjuLU3QT91WuIZ4av64rWgdPVCdiAsW22NQSRPRj8ttAHF2q9+YH2UnFeV4g0C9jVO6w/Zqz7+eZH0NDOhn37AxBBe/fGqPHHjz1d7Ve+HMa0dXfm07MAsgPSWeEEJEES3I5oi15UnqkO+M+XnnP4u6nkc585X+KfcFfkoIGQ26lGvPbh3sb3liBkd2RQLe1f1POJJYzHNsz2DdA36LB5V8l5F4hlmKKwiXK8mIr7y1P9Dx5OSz85HiSd6P/M8UptD1QrXp3/LAnt7170YOMWzqHV+fNB1lJPTlqjrFa/zj4bMN8AA8MyuO0wsPJzT+v7/8aJRTTey+F+fDPionkhAP9wkK0d1D7DiGwd+Ac3ufTtPHzbWsPyGzA/A1e/v8f50zcvj520Ue+T9rXn7139HpHUApYaf2rH/dUjbLeXvvun7vnkQ+y55f6d+PelkfCz8Bt6awhoqXYrDQoPOGcQr1gA17YNoBs6sNZo+RzmVlDN2ObEgFdUgWDOgc2d5mdvd8JWUwC8YosCMnxIngbn158B3H/6gpdXJ2xtom0bzmPg8fGMuW3Y5sDUL+gKrKzMNSf6ZIVEk3UK4OFvn/Dir787brMvzFZhc/Dw35/RAPTf3mN8+oqrv/6GMQbu/vszTr+9t+RJEYzxBSLWXvnm75/x+rcPUUG8Tnhqki+g3vSaCQRVLwVcTxWUoHz7NzFDj4/k5uMG/A85lsKTAPzkd7n0uRz2mexO3jPEo5Nc999p/e7pswLAyhNuG0IaINFr9jSp0aUFrIrfa3FQv6plclgZB8+GVcXV29f27FsTwJuWqGDsWtuAUYEvVaxnCIzgcjYa5rdDJg1MwZxUXACc8BYrbgCwHES+4yUGFmbQmY6e6HVQDJU2f/Bly4VrAO7+9gPtXfdMNz/HagL7eAcm7uONBHduKHwT2RQRqyaC9p49Ug2093aGyEusX82Ae1oWUwxgSsR6twLbBDYD+u2tYKo7dyZMGWiC3m1HDmXmg5cRH8MANHuJFiNaE8HSF9vIXibj1Jfc1AKsX60LkbhM633ZA+Gxn3n24Pl5D7cEe3zUWLPnuDmTDfTpa8/i+qFmlHfGbnPvBs5QJpl9wF1lBrBaVnpdV1y9uAaDGUibCa2MuV1fvwCgOJ/PELHMOOk0dM1kgnMzR0LvbgzeMktfBNu8D2PRwKNrdQ/oYpUHoiyN+JxIR18aZM5wahPUigqG+l+pFRdhiVCyJxrG3bRIcihevHuL8/cb733H/WmO/3HrJgJVnN68doO3G6JUI4tdIRg/TPFRz2BIOPLS1vHHPUyI2JiXt17SzCP+xw+3RIpAXhahghQm0mCl6iUz/ta7Oz/zBJH1CeIkQARMN6URZnMjksgBdLjCz2nsdDBxNJU9aP4aXxUnyPH4qcg7XKbH20juCQFMyb8gRI1i08nLa9UmLZ3S5X4KBIiac4Shn8EgIX3Eyr2JMBArDUTWW9HVwwL+Uk4lD2Vmgur07BNm2+RMU+HIzAW/O0GHt6Iw/uYyaGZ1Ch0T26m7E86zSsSM1ZHZNBvagixfy/KmZfIJWNQjwCJy9SBfrWzqjGAd8pFtjjQsPkELrkQ9WcMsMVQmH+QHACyYpmKC0Gz2T0g5XkD+RVSf0akRvcoNEpjHDS8Vl7ghVWRiatvpITRm82xxgy3XwfiklXMWyYz15464lrIWnPsRrx9BHlHCr1IeX1VcaSwTVabPsl4tw7XLhGoPw6HAlIuJAThQJ7jlGFi1RZplV4lnRGZQCDA9mzOf6e9Vs6tcWpkjKKWiJRv6s4c5SsYYrgBTXUxZGEp8OOPrTKeRMD5T9ezvNOyGwbwYnChLRQB6Hcyh1dH7gtbNkc7ggda74ykBlHyIgUstnOgQgTbPsnPaa+JRw31g26z0+5QNGNOy1fvM8u90nun0kqcbNlgGk8D2cOA6LyPPUt/mXFOMKeFgqFn8CV+OtEp5bb28dgQRp0vB2bZ/h2oEKQCVvo3PVedrYAvNz2kYtbLO5oTPVgg5TjroBcxA7pha0bg4e0kebTzBacZ5GvnPw82P3djypwdaTSsru65njGEO9PO64nw+e4/Q7H9WR+qdC0Bn1tFgU+dJVb06Sc5z5OwIYEbyfaAD10WdDoV4xZ3CeYrRtvGG5LPcE0by3hP0ZNWHrHzrwFSJNhM7vUskaNpoyxxWvXW03rwaQgYxzPLc53j2/i/KAe5z3c8XXyX2mznIGFxK5yLUgp6aNueDA2M2tK2h9c1aUfh8td52NCPaoNgwpjmk6Qy/6Agv8iN+32aUIwbgOkwz2aINDd4rz72RO+esL9eEG2XcOQVRTGnY5oa+tphbdSO5lUH38Xp6o2CPr1ioyGcp1xSU13u+L4IwQin1Le3e0qNDeilxL4BOC35pnTThetlUwzKyYVs29LaidbEAhI1BClu0EGEQAOfdZEdWLwgnf+AJ06eHZiWSHWkJacZXjDpclcWsJCJmlBLnoyoTAvuuS0eIbC9pwyBN4k44j9M2LcBRHZd6IzgZAtkEg3sHFixs1aPNGNYaHToTnTXIkXzjuHPCpeH8H3NaK6JiCwjMN3PtdTq2iHTYctOYyAriM7khgpxicp2/qxYMnFmZmVVURcp+n/MeF9mEEWVUjDK6bsaDWPkDlvVpclYg7HnvfNKqoSVxZBCGGsZTYlnNoD9aVsvkDFaR8UAkgQWpVd7brPdLOCcCfTYJnYRzv3vj46+HuQm8LYUenB8OdVm6WzEgze/+yVHs094Dxc7o1wp+d1wQTjF9mgUWM+RypwWu1kIvPowSpRcyt96D984XTLqN/b8nWeLGWC5+7O30QL2qCG3ZXe+fhZz2v/fxW2XeOW/ukCoYiN9XWt4HBvrDWQrCx2RqHM/zE32fzgYswQuG81UNGo69LjDHuf/eMD1AdEKxQqfzeA9UGXOG01wpH3Y6b45ftK4ESulZ9cBQyx4f/k9VTX8E7V9kU0Zr8+4O890bw0pl/YLkmkCmoDWFOvPV5kEZ6vvH953ZlrICA3ldPy3olBsz9wJ1Fog5KUSA/voVxu2tjf8OGHqLRT15w05FV9qY7f5Hl1vMzfeboCWBtQK9xNtyVwMqVoGGAcWNgRBIWb57TqWx2FIuj8YN0F772jkepc6oAHALyNvQh5sqlkve5cPxx2f82kG7leLW5ORnhXwEBDeAvjdWFfzeqjlqU1z//gEAMD5/wwrF1cf3UABX//URgDuVBtDkI6DmaF8/fQ0Z9O8/np+h0FvLKdeaznRHNPjxs0ne8U0E/5jYO9EV6s5CoH30U0Xw49NXNGTiHessmpmkZPmG3EHoz+Xx/p3Lt/guB562C/59/CW5S561x/v1m/sLtsLd/QgnLp+FsJY8q//mGH52xLfVTirA925PeOvjt0pN76D4jjm/xdo8/L+WeT6ezIcdbClpcFXxWJ5r8sf/3tGyHG/jCT04zCeKvP+1o5Vn16PiDLnw/UXzwvGjo4wsl9X3S/wouYkca5IP2vWON5C2Nc7ZnMAQBYQyw62Ak61eNMYzx7DqMqUa0RgT61RzpLusg1S84BgAGiosoHiLiaEN/42Jv7geNAFg2zC3FWcP0jQtIWW/TGDRtzjrt4BMm7crefjbJ7SP7zE+f8dQC9AABOdPX40/ilW2bX/56MkJ5lecn7/hIebUep2/+e0DyDdTlhDPIOZ6u70DeoNuI6rqlqkPVCB1IdUDYil7nI8c1/w/6dhloD/3IhFB8AfHDuzo/nP45/+7zFDdnHVvNxi4IYMbt3epGJVrAdssD1KY0YUjGIpyM/PzdDjXKel4g/auAd+f3ufS1P3pKa2APX9gKksWF+O8MiJ5YrspkZPimRJUYr0UXhiM4dkQCmzfJhaxkn5ojzi1N14aUqPMFIVOgFjASkxiMxzNcoBOXBL0ZUaZBvXoUwngOaM3Ht9JsuT4hTmTtwK9+clMHpbY7LADcqGIg73SU4CmYzxLK7xGXjG7rnyjZEiFkSHfy2cFAglaPZ2ukjkpDasZmcUdIG74ubq6snvSAHFhnKp0+Hp2orpTgECnoHcK/FDo1GS43baF4894xYKxrakENFgkVby1G+1cctjfXq6zMGRy7+XNG2w3NzvlQg4/t5sBfZ1Z2qqK7cYNKM/wu5wRheD6yTnufnkKzBUR2UsOMB8U7WUFkpa1Y8cVgPOOR/ky2ql+EUt+z6p4cyTEhzvmy691H11Wvi5b5E8fO576JxjTc3tiF1RFweLns4JAZ3Y6f7rzbFdFoGSMxPWtYYpDK+djvFcLb5TvczKnmo0r6WxXoPqkQKdCWIn8dxqbyPKqvISmrKgTGHMjVi5RmkV+w+mUfaeCtnY42h4SGZ/5WvEfwhy+R/0UAKKnq/dZn0OL8+Afgz67M1PYhIy88OWfuLPs/nrulFyWVAdEmDvu/Iz9s8sYhbKPtFLKe0OMDnrv8XlcWZhR0Glx1NAxQhS+n4c9mFJJeBpZrVrO5P1JazxFJ1QzUpVVYFvvaHNiDIDOQo6riUAWtiKx6iUM1JqqWADLouPUku8IHUFlSZx+FS3Hq6agTGYajg2DoNz3j0DRvPyy0PBZ5sckkJUfvjhlBahX5zkd02WKClZ1HtMsEHBZ0nneerfAAQo0sZWwiibubIqS+xJjDicuxEqytwXsz95GwxiCNqaV9vSswqwEoFE+2uIK2NpnxvtWB8Fu7xSMKq0FHztmBVyyJwVKLfy33heUxZq0w76lO0ekNC9/fmlPP32w+B5Q5f76/9h70/U4khxL9MDMg9qoJbO65/0f786dqUxJJLUw3Az3B3AAmEeQUi5dXf1916uUwfBwtxWGfbFh81ytNINjWEvmkA9Z6LGYg8FSKz6U2Rr/eH8MdxjSHefHhq9fv4Klb87nsys3eRovZ2WRdTR8Xpv3M/zg8peXrnEesimgZS3okGGwusW/gL8nUGnw6yJA7+iqlnLZ4X/2ZqV73JiJmopcJAykrW3Y2HfvJVKeUdHjOLEnLwUKHMPKPQXMIvB3jJ80zg1oVs7IBActjM7UCRkeZXN2A3GTMPj3xiwfpRyDZ60Y+4yo7KTlnBLpgLfjDkbJm9pzDc142y15xSEDAoue18iiQDwJSz+v5gAw3ZAnzvMx48GYE21nNKKG8ble7eLcMSJMzS9jMolpwoRFELmTIqPNfXOI2xuzo2wtHBEAwyXia2vli2BZqvYRsECn0X1YBo59z3/kO8hvRJmEkpp95ei5D4Bqc4PQzzKgNlbRclZYEsPx+Sz8YQ9HAf42vffV+WUOjWgLVVik45gXfTftEDHzamPabeoLpvEaUwGZFvUJlw/FlYcVF1IMUqf3UIWMfI4rlTwOX7D1rPwCgIwmFvKXqWxfVz9lh2IS9k/7a5L3Ksp4+0xm4KgorQbLhReWhtZ9T5plzzOnHXEYZFYJm2OkvIcUB0HHfa1hH+6gpq5RULWwSN+7o8GWS5Z4CO7IljivwgHbbps5LxImyLsZedWVJBSZthJn8qg1Xfi16zon/TTNoYZ0VWkerxQUFZYuOPf7erRYKGCFZpxUnpbJRhvEc3WFw2BY51rg9jjf9fsKbxffucQE5lhTKV+fWOML2PW5lsbXV/MsKHmqyhpo/bDzpmW8/CaaWTSIJxEpZGVxSBd44ICwDQBdoboB7nQ4aXxXzzyD5JfrMpmznWG64c4IMoeXXtwwxY3vHqF3Zg11rxWudOjBqmdSx0/jy9fIhse+F6dLYJGdOEGBH1ehAwxhacZ84uwroJie7aijwbNKcM+nYtx/QX/7Gh0ZuatApPrmma16jooPnvqs+PJHl4CBAOSvww6W1xGIL3Cvr5u8yXO3vM+PNzm2goaOrR8vywZ50dzyXWH70q6VRgBh/xbwoDFg7V/LyoaDMwAwM4sq2od3NpbfPqP98tZ1YnSSSKdEhaD/8h7njx9t/Joi/s/uyx+7nsG35VdGn3cAb9XWVJApvX/2YgY+PNPr/F3RfpUFJp8b7ZFe57PXVmzd1fX+H7n0SZx7vV25fvsvXXr1m1z99flr//0Ttg/v0N3hQ/ER+++fo52n2vqvgck/f/2rx/P86VkfqiE4duYTfxgOp65II5BOpgJtAmJZPEm7ZpEzBOaAKt2zM0zFrhO7Duw6MIzLT13JgQ9i/2okGp9lRx/AWQFgojldHCxZFZ9uj1DL3lMvRqAPAQQN598+Bx/xzZ1iXvzHB8uADJMjt60v+Fx8PcKJXkyPIs3KDTb1QFEoMM2mp1Oxf763ADYvRzSqzrzOu/BQ+Z1rClBX/z/5WmqgczZ6+H68fgrxPoE//+4DqIfBHPUEBz1b/uHM2SbA6e0tvnz+bN/fvcX4fBcK4Uc/gjfITW+CQ2DUSrK+Cg2LBiBn8YXWZAdi/OWOMbr3eCzG8wlBh6LJGwCCHff2IJVCh2HoYQ/pFUq+i/uUyIWj/Ir90yv0d3Zo+mZPiah5tvpT3VOjiVjdIqbmYyS1MekTmMCQgU0scmvDB8st0hvgKcfHtMgES8M4I2WpdTQxINhxRpuu8FT3ai/I0eoaNkgrqeF8vsZ0Wm3KuVskTUWKJNLi7cj7IqyUXQpvp3KNMQFRWyd15PAMcDdpaKeO/fxYFMAl8iqUA3ABIeW4UMZX0s0+42sRdKhkYxp2NdISAltMxSIemkeLIIxkFiGxn3f07kqBZkrJfX8MAgMKImPi9Po1vj88cNGxvfE65CIWve8I/3Rz41mDnDi0boqAcbZDRWMSLIsEa41qzLest/828QDBa9tVV8p1vMbAlyASZEiTUf6K/V4heI12K5j3E4pvcRJzpfk/3vniZ+YFEtoE57u97Lag3/L8uGODe0IDAv2maC8ZIaYh1KaS5zF65HhMsNHAWzWVHH/yhQkwAhxPCUyRxOcln2+tp1DN+7J6r/7Z60BOr97NcyXxlPh98QOQehZGMtOowgg3X2NpaFLgQp0R8nIZXGsq1JhyNpRwIpb6WFKQXOkHjd8u+EsM1m+JeTCWI6bQNJ6Is1giMScBLCKgpQI81iWi6415kS4W/bt1yGOz7AjNmEDxDVz2MVazrD1BxA0PqwAu2M87zGBJnGCROufvZ0wobm465hQ8Pp7LTj5H1Uv/mnu4vEGgBIqSxH84eHqsUJS0IO5GZAwJYcHjwbClo1i0UPeQ41AtqTXtOYuq9GucwzAAACAASURBVMwqzcqTVIOeNBpd3ZCy0EW2X3BD0OsyDxLmnKI5MbiBsO5bvKekj6QUjmvYjL8zx7Ba2s1o0hwT+27pds+PZ48c2SP16da3yEpTz14XZqoRT4PLZcp5rEou9xqeMKOVGwqmWmTr8LTD42w1zffBjECuEJ90epmQicjMwJqOANDV0jnb0njCWc1sNIH/1BXac0at5Mh2Ioj9lG78SXdjZN8sXWVrNBZ5indSGUGW6/HIN+LW1g+ZP+yUoRvmwnBvsiYTo82ImKECcIwJlRH7rdvEbPAUfG5cDCeiPCN5XiToeDktsTeAQnpLA48dJTtLanRizAEZlxkmAmwDx2rgnzDw+rlorZVMAPZMLRMApLFPOAgY78HzyXZowGqtRZQ6jfd0nJoHw3Vrgi93d3jtNSaTt2DK6nVcrTXs+4DIMO9/P8f7GJhjvxh7KIQD/yLazTUv2VRAVJyRHr4bF9HoUI1oUnFnmHSMSjwkjD71teI5TX4/+dtIh83z1JqXnHQDuiq0DTyeK9xkPxb13YKPFyHKVp9nSQWeS3KxZDWiaqErVIavPywBH00ahowYC1TNAVfEynqQ7sGVIzQQOJ/MyPPeGrbTjTvJOK5XwZhWS27uMxTtSqMzeQlf+207YetZB9ae1Th3py6W9lgaRp/Y+47GlPIR5T+dVKsb0Gl8UE9l72l0/b9jzFR0gCkEGRFhlG4UnHC8wpi67IlAW0fHmuGHkENDCkgHWzpO8Op98whDK2c1htXTtZTZMHyjZkDfz3tkcmDkPLPcWGT3jCh9pfwT0JgwfKmiJ5Ag3onzpsnoxn2PCJ6i6G4VNVm3G/6HhINFrMd0pNAA3Y22zDEtoxbTUDudMKpmUaAmy5qnxPDMPmPYHjcyQe451CCYTawUlxp9GZACK7kSdAkz3tLaybTXabiNfVS1dpT41ufjZ8YaMmP8LJwXQJxPSlOlUDjOIQ70tooyfnGQBRY8ESx2WKiShwLMUaK3ht43SGvYmBWmsa69BDwQvsMJY7rBceH3aCgHxvnR+QYbU3c4HYOpnjWBSS2LnAogXaOtyhMq0z1AvNSSOg+iZSFjyQHT5+YzCWnr87KuY67RitONfyxKXUHoUSrCDd6IYMDH3ZnH+OEJwMobuLhTuW2fQ3HOIWRMWPaj6RHznbRWYWUXRqQKp3N+DEESfxMIONbJMaMMoEKVHv9eljDo1GECy/dr/E41nGebrhOpsmYdjRaeWJ224Yo8lCvvWQsQfCTJ9TgPSBuul3FekWMVxc22+dKZE8mggV1gGVCcPlg2MsN3UO9NDT+tZ71oKdVG3Zy27aJAU8yxg45jVnpjeDaU6U6yCtbzbo2Rf1YSarSGPTJxEDcqbuYr6CvF4/29Rd35VgVe8/V4xERX4KQWkf7t82fDbS9eRhbI1sQMA9LweH4MZ2dpDTKGlwnxNYXJSu31S8jDV89ManvIeEUVT7Fb4On6Pqb+CeVz3Wl4vV5EOnM6yo27ewheQ99a5PW190NPUm8VfJsbWXQEh/5dSIQIsGmcjCfnBCS5eOo50qMdQBdFd/l0iKJWfxofLfK8f7gFcG/t/Q70X99C9Q5T37qsZzDDbCNzWKkQK0EKnLyW7/m8+zl2/qWcU85vOg5UVZyvyEz/iuugVo5seOQu3qmt3Zermw4cR8vxX+a/S67fxIV3CySRen+hTsJ5eNFKdxPv8c3qTFfRZrRrSo+Vvyx0qcLnMcoc/vNC05bnSruy4sfEV8er4ut1dZ679Im/f3Td+wa/AfD902dsjsd3L1ERHJKuNCAcg3+ynxrUAKzrde1aeAQgg4OK/qteyf0f2jl8ephevPPDtboyzuNeJ3eTv2dWBIevMg5Cun0aMNO4rjAYmerlHlWcbGeZKC0ZWKxf07Oy3JOqRZ6PqSYbqgWEtn5hpQHUYdJ5naGClxCcdMfXbiXHHjbjK8eceKvmGBdBE4pwihm4A3m86QCvAHYKyN5hc77hwdO3K8wOeFLBy//8JSLq+6/vIGI2vf2fv6P/413Rz6QeSNUZUnHarmabU+dxdsoO4EfuX7XJ5WfBO/IEPfuD178SZ9frT9dAB64Q4P+B1wTw9e5+ubcBkQIaIMvxChNflueWTWtH4Z3PKF7MVGC09w3zo9f2xC0m7p/d/FSLAIr7Z578+euI2Ajigq8Yd6/Q3staIkvrO1VR10KZ3FwpJABO7zZDGHcKOSGUnn3rkFMD+gbzshmGdFrzGllnnFmFfiPbZam9m5A4OFIhgXFu0FLrJWI1+USjFmU1mFxbg2fXiwS/vLtsteklylr6zXjGxjXOh9Ruaye19fg7Ij8q+12JHBmUqVD3Oj5GJExXwOR6IRFkDNWQ4/m7R4f0hn08ovUb53PUhcOsi6tAGvwasL16ifP9AxTmYNDd6D5d0A2FbFFqCBDKRQqSqchaHRoUKdhLk1BwC96E8KcAtt4xbwG9fw3F10UQSC+1JLHj/pv/+hKCbwtsrM4TL5BJdIB+2zDu10ifuqb0yqLCOX566cKRt10ZA64rPy8Y0mz+4q6N9cpDenxWllVYWvN0ak8j9Hz+2vieuy4jzZ0JLv+1syVBWG3PJ1RLalW4IagYDZp4iKLXiKbxxGoWMn1g7VZCMUxcxqgiOusAgskFVSf2y/H0syj5txkXHQexu1AUcb38vVK7OqLZCd/UmHj3TWBpKF2hzbIZVTDCYWjGSnl9SLGIe3OYkVDgTljmA3u2GK81cYQ5qZgCVadg7mOpHfhHLwoMeSh9glfS4vrCPwloT5vzuA4JqwRYBbLECZACI/eQ8K1hrkQ8KOZA15qVoGgenZewqaHEbY2RiS32OY4mjVwFJ5cujEEOqZUf5bQKgJlmd0KCCEUG/s9PlQI6FIN1EadFP4594vH7ju+Pj3h8/I6xW9rmbduwnTZ06WhbN7+35gqcA7ybtO4R+f574rQcuzjMNySuG/vuRvwzxj7weD5H6mhrz6MfN1d+UXAYdkY5+yZ2PhG0H87s29mthk4qd2moSUh2hUFjBG5DK8bzzQ3om2zpcKPEQy5o+dp0b6MKDJGOG3DnsIkm3RV5Dj1NITPriM423Ag4MBRQrwVozhkusEwTk2hwSPhdMQOz0HiYJqgZCbFvBnTFeuTrTCeJi8v6TDqZCmSJ3y2y19akuwBLg8RaDkKibEIKyRJ/CyNem6eGdmMWcayl/6+G7XnQDRif+O3+3mpF77tnKElYjbVTRY2vYb16KtXVvcUvFJcFN0aZgMA1xAI1vTq3QpfsJ5X3UFVTgGMYHyWWhnWKZSahgL4Y6y+E0+ogkGfwaKhpIkBr5tgFw/k9UrE7rJWU562nA5pNmk5ka9aX5brgBYDK5fKZ4OmBAotIfO1/N8ctjB7dsGHITAMDU/O5Af3sdaZp3JYGbG3Dtg8/790j2QVznzifrSZsRieYkqO7w13vG7btBr2JG+AbuO1TJ7pnXeo+7r51Z1d2bNv0jAZeCmAOdyxSL2UxopSD+ZMIdIdHHAJ721OucN6ZvHEYemX5OGxFnlPSR8OpEg5MVa5iBLlMP5NNIvtAGNALHuJZn9OMEmMOCMwpQceEPJ7diH6OdVW1iO0L+EWFWwT/FTRPaDQlN5N8nzajzxbpDTcSWQYza67w6aqW4QEC2cyos23pONVa9/NoyRane2BpA6zEr23+cBhTyic6DC8yVbqYUXKOYT5YE4BazcVO2U8AT7oINIVqB6alDjdHUFnOU5ovbVVmnJ0JqhGt1q8WGmFr0HjQXCnGTC+25MmT6AFnxJodCH/ywPPwvRjbNftY5C1hRoFKw9I43prBHD9Pp81q1wdPbW2OqRj7gIo5OWcNczgPDo96tnO9l3qWdFhh30NnpPKM8Yggk5si2HsJ+tcxfe2nqosXWniV5OEStpMOr0Z0LHwP712NfQrCgnKuKVtcYoKIGDqy1IQJ8rClXWND1xck3kk4kdYiKtQMM4S9vFJWS/6nLLTBNfm1yXrfBa6WddIYd9w+rANAx4LC99AZceHWL6+g8Vr2p5yJa3tWRgYoOQtZ+rc7eUbzyClmwITNW2Y61lcuFmoOOQbe9su+T99Cw0lb7+jNN9DSCGA2wdzV8ZS1Ob2/bJ3UwaevZrjeBwImpuuIxtyttJynuQW8LGDzclLucILmhnxhVixbj6mwkkBfHrx/vx/7Y30OAUQttXofAmEmKgXGlwl5aVm2CMMZzEB+aC6zm2Na+tyHL9HuERaehozrV5y9K79RdiNXGL05bha8hpaXF2iRcvNHg/N1ekLKPoySrh0/vgSXba4t2b8dMJ2sP8Bn2gdgfqTx/In252f09g7mnNTzN5Glf/KKDKSZv03IhxZpsMm3WruRzwEVcwqAV4q/uQ76ExPz65sAt2VvCAvAXzTS4PLcmuFMyv3nJ3pNXrj2e/ZyaFHd8Te+Oo1XlBJiSHrlfwd9OA5RSYt0uWeld59zSPojl175669dnMK8stwXffyhTo+uEH/+Sj3lXwf+P4MjjzylFpiQw/1FpnRcSfqeVWEkMmhTHgudgygwJ2ZraBPYx8wyrpXnVIV4aU0mih10EmN2LCOGsW6VDQ65Sc3hSlTxWRVtKt41wfeZcg4jzxlkCH+PAb3kVmacE5vfWZIHbOoZmbU4nAF4FMWLsp6tdxsgM1pJA1wPbOuosW5FDe6LkrJAfI9d5MOJYY6wUHn8p64fY6b//uuiBnq9tHw+98xxkkfiuVyyPvRXkdNT+xjpuQ795ajshwGrkPwKljhZVdHfvcVNa9j3HY9392hQnN0QV9dCJOvUZZPralTGQuKQAf19x/g0vRqaQvAGiofyrLfrkLv7bx5Qio71igN4PMD+V41AD29YOKKUnJf790WZKKhgPrjXaA4HXTzaqpuR4OWvL7BJg94pHj/ukE1wc2rmTd09Ur13yPYdfZsQvMaLX2/w8f/5DKZQfhSvrQpgbMNTRG2ADDcCV49nT4foCJ+1Haiop9CB7QTV6SkNC5kJxYAht22zFWVE2hEw6bFLxNo8TdwYZ/TtFG3VF2N9HTgyOoMMatkXb7dvrENvhjimg6uRHWQsyChQGeFZK93I7MIBx6riygBXwMRqeTs68f3bV+gckNax6ck8mYYRh74Zoh67C0I+VwqyrJO6vX4dyjuuV9Qm1c0VTUaoDLzM4wniUWTcUlduadxIYZ3KqDkm9vsJxQMUitPbt3g8e0qyB6RiouAaioINryG3dnM+vMTEV1vz2zehLJxf1AiXfvMULV/DK7u/sc+prCLCnbXIdL0X9NcN+lUhr1rA5/gyfCzfIHiB7bUZFc4P+1U8W1Ul/N0UCSZqrRFwisxDx4clFRqSde0hQBMnoFBoTRJzjWq5R5GeSKipcKDRlcI9yogd/hWBiNMoeZinn2vi0MockSECcZIzyeszuXr1N87OatP5855alOOBHAwAMR8J/RNwmHe1EvJ5oTHehP8wsEyNcdAoAIgrMbufc3ufx1w9Ale5JOrK7C6Rpra3HrV3Y8Vjv2m0p/LblAatiRnNefbLWEDcCcBjOyx1bbGa7fso0SFFVHmCSaDxONPTEoIJG/7SnL63Ut5dWroKlzF3pfNI8VgNA1wybLae6ajDPnoYjCQNkVTOS3O6YsMww7jTfxpMhEMUj2pgKvce0bfQxPO8aDuMPsG+lQgPID0re1qV/RkQ5UYDGp4AoCjdQjAIoALO54Fv3x6tpvPjo6dPH7jxPe5tx7YNTOnJ6PBTxNJaTVdaecQmAGizvSULHc5SrgCnYStw7VSMffc0v3sY0C2itKPJxGwKgRmshh8OCYjhftlZn9N/UQ2jGcGIgLDytwXTCiwtvUel9q2bM4HvZ5zzWOv8Tr4gFesScFG95edYMZbhIIfjJha9qJ5douIdHzPryouYIV7TSmLYzhuf0EMqaUmA47nIrwlyBug2BgUU6dSAGIMEPxjqGKUAOAssc5ccFxUYMkensZxTZm9qJE/IqHLCEudOgzr7tM8VUVSZQIRtVINgpZscKxW+Cb+KYZEtkuf/4lItdW1XWCM+tzHVJySOpAKgE9vidAdEZKAqTPAXAYZH7omdqTHN4SKMxe7Mk+fWGlPPIUsekSUTdK6qUBFztup9w3Y6AWVmrLPOcU6dGOcdo9BGnvHu9YjrfJ4SnnPePq/Adc4H8uzxmebp0aEQbZCuaVB35zltE+pBSdNpYcDUGIBH4TETRj9bimidYo5HY3qq8bE43kAs+vV06ri5eeEp3MlfCwQD5rTRDV67r6XDxd479jGc7k+MYQa8NiQiYAkzjWcHfsbnhO7ndObxNU3Fy7TsXbFSiffpzEN+Rdz52c4raYqrUFjjtaaHFwFkQNh+E8OZfmgV5siqUIzhihx34OtqNdNFEOmH9/MZj56dS4Gs3x5jKrxeNVI5DrCyVwPtqdxJZFOcf5wARCeaNpctLQuaSF+0usRH27ahd8sw0MI5SrGfjTE2+urpdn2XaDAfHvnM8hbhKGMLDsuRIBBGSMOjHKfhXYsStdrBUwCZxMPiLL8az+FnVYYAnmFlQfuFWnL9jC5riA5jmgMX5dY0YtIsn87PXFZz7NAiehBJOdR5ZrOAwfKJupex5vEf/2jJ+/hPpLXSWhjPT6cNW98sKxV7nxMYAzp3c+JwB8EoETMB6d2MfPse/Is4fZ1QnMcecjidbheHPJ1+fg68a+BAG+/kKkYNbvK+GjDDi/I16ropG2Pj5B64Nuq0c+17ueFv0WmkNJPPyzFiXWJdbG00ZfQSXR8NUoYo+MsMp/D02safJS2u/2akcCftIE4ymm0Djigp8nH5H2/zyrpBEfVQHXccjUIXCvzqLAE4T8R2NdrXyMhX2qo0t66v71T0R6aLzwRPppGNj/osPXv17Lb5tBzT+JhOpxuEE8hMqGIgjk5J2m/qX7TWjGfwYIehCm2W7lWHR6K7IX45tiKe/tx4I9KKMUfwdVEawedAnQw8gw58b7vAHM8LXRc1vWfstZf0IU8NuHHbdQoCqxuLgSjneHrXTIfl8uXupUK6Zy36/vsnk3RfK+b9tHrnGmYEd3xx/p17CtMblyqx4NIctnu5rnM75WUApw/vgwebXI1bm0tmZkLRoxSmjrB4MZqDsenQp/1tgVwitxgf7zDF6rs/NZ/s1TKkXjPK87nKWfM5yxRg85sfgfYeUL2HfgLwDmi/VnnnFoJ7jH/eQX4FVN+70y1TuJMmED0KTifTyT7++mgZVKfrsM2LDjf/+IB9H9h/t5rCJ59rNTj9l1xPAAH7azBVG43mlh3iynsFTy3biKTyR2NelSHH//2I4diQGRW+iFzpRtc2Km4r95f18nNsW+TPFXJTn1/cFqqABKJt39zaQWz0OtbU81Z6VFv72ev62v7MdWG693P3wL1w8vwq1sPufyMbrdd2s7ZfiZHzQWIZAQFAxzlkgWtjlyN9i2Emw+Cc39Xnnvq+/iY/9dzTDXBxkkamXnK1mYjzUZGNJ/ga6qLM8Yw4k3ZzUQXGBDosI6MIziwfdTEG67WpAtq8HUvjPpSOZsavcGwB57qO614MV74bgMjAbyqQOfHe+dmPAN54pjEoINNLFKsUFsHW4l4Eb3Hgzh2P1c9aouLr//0dL/7xHu0f7yob5GM0mSj2Lfpz5+1pAS9CJ3IRPACp0wGQKbCT91AkXg59ZryH+F6vp+jJv9v1ZA30eu+Poh658jeAS2b9D7T7X3V9BfCyfDf52g7m1mlUSsJzgXDsC16hldjUvDQEy0sg2T50PH78GybxRy/fmKDLSqC2NBWR/kXdKxjfgyElowr+7bUXqeSiYMEoDSJkEWBrDeKRbU1P2D8PvLi5MQMSDMkMpu+7n5AdaK8FOpj23RGLr2cQkWLssDTkVOKuciqfrZ9/ZQmNyReM/Yy2bSVYiUJdRj9M3aOGBGAKcKZLbb1FHU3dJ3DTlnPTWvPIu3KyfA/DoEIlLQ0YRfFG47mvQAjb/H0fZ4zz7qnbLd29zrP364qEyR1yioBMkTq/DOgrT98oXFvWQ4V5+0sLJD+npzaEAG2AUSdMt6lQr5dGw5/37IRooijLdfhSvLa65mXdDFYttTswIfLNx/4K/dbrpYpC3gB4yFNuKfkE7S1MafiAiyuNAgDwAvDTn4yhmvezCA5qY79uEGqTK4JK4s78i0yALqIIDszkZUthstb1DhU/Cc3ejJAFXRkhAYAB82k5jjUUO4WJf+qsLTyggtGrEl+vvyf+W50qMy+groggooBzidRxnsEm03cSh7FvFV2zbyAV11a/3OZpQ5P4X0hwYopkGcRTcAbPo+A9rTM8cqgytEdWOd2l6ofhutbElNYT3rcErg14occTFVE2c+cJxaOZ0rBpIVqjAnEiz6IwXRDqDy6LuOK6rwzACuOXbRaQgm/OpVxUn0fyu0/h9wsR0WGK8C4OO+zYjPw0Fh6NpohPi3yiU9mG5hHbTONuMGQeTlRAM8vAXAkULF259cEUlREBOOdaZkDy3wWv4kAtnraVzk6ssQoAj487vn/9jsfzIx7Pj5EynNGL+xjYx0AnvQgc4l01c+aT3iyyWNw4Q58p0eADYj19rJkGF84zuKHB+2yeO1TElHIdPVK4ixT65vtGOB7NIq1lADJ9fTX7AVOSuqAvSKHB9tOzPPSsey5e+7x5+ZqE54Qr0gQJgwHnuvKK1pe6E5mdT+5JGjVKuyB911CKGsw16FBPu1UioaemgyDrehVeLP9LPBtcLYz+mZyjccfG0fuGuT8usN88SpPGLltiZv4JSoBrF43e/Acg0i0aT5ROYqqI56zfS0NZRsmu/9Y+17/pQACeyQPeqCnIzRHTSlpoLfuxGPdqbduVR610OuVzwVKPHQKr7cgxXUzSeCCzdplybaahsfcWRt7RJ5q6UTlwVirQqZhmavAZyvoyHv9z2zbQLFh5y9SHTxPyPdOL1X5Wx68NL180aE8ckI53CQsgfvXlIzKnMxH5Sin9EhGqpFOdZVuxVNdWqsJwKjqwQy2Ty/SsKj5fnYopTJ3XsUvSUh0S8syYCmrBeA5ab9hOJ9y8uDGc35oZFdxpTJ1X7bLhtJ2sNj2Y6amjeZ3zqckXj7JfpDdUFDlkwFFHyhHkA5BwHXJYrLGf6SIzNXRIm+g08vs6Tod58Uwnw40ik6msp6K1LfprbsiehmLtDKsCbvBtYs5knYb0vjlN2iO1O+drxpdhfI6ko0Y902lAN96su8H+2avwwAqFDjM+m8NPx2wTopath3FqTBbTmhtoHRZnaLQob5Y04TxbWh17zIE5aLCfhSgFEvyi1wnmHk7bmx277RFQHD6TVwlFncD52xYGuILIr8obsTaLbJi4m/IlaVDsRZEdjniUv8Y58GiZ3ISyj8dLJNLHQhFtQSt+8hISngXDnBy2qKEMWCRuK06IlDMDhgGI09QxkvdNuXewq9QxXFm2yMoQiMn0R9QB6BQ0hae+zHTxsaZcj5VF9i1Rbm7Be+sz8bd6fG7VFeRSx33SqJV28fNIM1f+gCnmJ/fbYSwN3cdREazynJgRPmkJM7VEzedoM5MRr7TZaJbG/TSbLD3HWDTHwKwmboQrbCRomLwmamT7B0bY9yadStYDdu2s2RztfBXbuc3lMK+6B6rUKdEAnX0qxCO/nVZ51DfPovHeav0O59N6CwfL4DFh56aWQMv+c5yETcWAsgwgXIc303FIl7XBlV0S3weuLnkUZpGz7A3BGxdH3YV/ALP6UUeS3ViEu3fXxEspAATY+aAYZVT8TK3Z89cPqM4P36/PxWkT43b0bkJun3EMq41HA4fzz29BYw5jF0A/Avjw4yyn+sy3a3cO2GMdD1IOAQB5nzBWL8Et5NcHjN8U8qtl0Ur9Uu00z2Xta//4GZu+BX6VwKHV0Ei9I0kl8C+KQofVP2c/+5Xfn4OtK6h2oStc24rpLCAAro0w/eSX9bis8HqkBzyp+kNua3lnaXnBB5TdDu9c4Q/W5w73Cw2IjVzOwjqi/6rreCR/5vnLdf+58bWnGAJZz9sPx0Degnv6hP7sh+3gj819HYNeP/z8TSosH+4rkFbjCm/2zBTT+UbdcwxoM+cqlt/ax8DYSyCbC6ieM9GzdboU7Mbz/B8ANTeygs1AOFRFRMIbCzWBCQw12LVyTA0Dis9Q3CqAOb3kBUt25XXn+3snlrlCXFUcTvbZdZTKsGz1tkZ9YwCG4Nv//ieoZxpzz8y57z0jSPCMRov7h7fAp7tlf5Lvu9w3RaE78fyqQTu++kdg97/z2q4O8qkTcI2jvHLrZw7QzyPepzpwkkDgiINvPwWRdOjVi7bs2xsKW2Pi9OEdvv3+yQiKM2OkzhR4eLWWaRQEuJoWi15GxzVRBfZPw5RMABQPENxezNfSXiOg79qaJYN3fdWvASiXT4FirHKlcJM4hNIE896iI6jaEnnpCpaOJhvC9CDibXG93BCOaXWz3NWtyy163wAomgo2U81jUzOGnk4nEwL6jj46hky0phDtGGpKdEZTBkMsclhji0aApnLWIsidXaAwDITnvu3LpcI1WvTUzlGrWNe1pVIhLj5AQuaIMB6Zjri7uCAjXpctBQMabMTnaB+pVLOOLWqmw5Q+AEwho7AIGjVFYQMAYWSaCb3Da51/+/bVU0vCFTNwBQMgOAMAmu8ZikJI/Vy0V0Zgxj5CkX7jHtLDUxMSfiMpWGuYO1OtWr324V7cUI3IObgw1TeDE3rGqwL7vRkgVF/6PnyB4nU5KYr+pvv5adjvXwFvbA0bzID8+NlyNmy3b2xb7q3WbLt1p5AmsKolgOIbTm9ehaKyMmzW40sAFpEeKWTkJcbXCby2Td1em+F+fLV1On/55mByg4nHCnELM+g7WwR4Rq0VJAO9IvhfkZhwfOjAbR1wLG8Gs74DOJXmeV3BgenZ6N9rFgbl9+wnIiIBZDpbN9gwbWxzZwxXQkw+U/rsH5i0YgAAIABJREFUrbtCeB0Po7PMgCnL+GYwYIW4exrLeK4otqtLlJR2tWhEeBZVqUTk8zlWMe1sKCVzvdOpIGq3TjeiTTVFy7RU1DkmCeVGwIr/1gAMNEibMUYrn6CeJt/pgFib6vjAoqFW5jb9QX/E6hzoEgE0NaPrIxePy7XbwdzW7+LrmjrM/N2pVN4mnAm8rjkzrBCW3EmBtIJwQXA5KM1o1JPGCPWGbctU4BT8TFmYbVR608Rpk9f8DoOXKkJhBkDVI8Q4j8KJNkmvcnH8MKfRp6GZwpgRM3PfHTbVoxLNCGKUUoCpGOdhGRGkpK/2ORMnt9Ewm9UOtnOnPlYJY645gblhvLXlnHCPInWnKqhonsPWcJjWLzDjHAM6RqbDryeSzKDAncoys0xVApqpvbnQ4Wn3PYqUNVab/w1xUiIIBR8j01RsfxqdcVD4E8aekXCVfY/o8Mp3NDAA2oSuJPWZKkzozOHj8GjbUDrMAl9zptOZJP2My4+iiEC2ZiUabFKwGsCmUAUU28milpTlU5jmGOlAACCMSHYubOEtusx5hTHj374PRIrfYphpLZWmUY7jkEO+GqpUzSkh6i3Hs1JRwaIMpuI1jf0rTFacnOewxfmvNhUqrvmsSNIYKugqfl85VgDhzLYqk6qCMHCCc1LBA47hteA1DLbWJOklaZHxCJN1P5FrYLr7eQAOG9y2be4Ayhpx8+L82qMasAo1nLNFtH9V5pc3fCninnomKAsVAOC4MSlifLJWXe7lkU45XHZuVuLj3pql4GNEue8po/d5Thn1ZrhunYu0DU029HZjayTdnYomhjYkpaxzBlo/+RwG5gCkDXtX0ogs8Dr0kT6/8GBFecOLtV6rknExchoCibVunnlHwewthnCCJ5nKTN7WN/mPMv/mKIhYj3sgjlO7f7P68pvHPJrzT+8Nj+fd0w0T35vhdLBWtYpn5HAezBdxeoQGZeTWOqADbXNaC4cfnyy5KVs/DUcPRl/23lxOagGDhH14qYK+Nc92YMYeZwkwFMGbTc8IYetvOdmbWB4Cy7oysnkFmBUKsJTttg+eIUgMflUVuwy0KVHuqk2TGTlH+lHamjEzC3PCA+20+bnao3/1fJTKwfinhqYvr6PSOkqAEc9gfSXw3MK4afz3gp/jRdhXOmlZI6qUg8mjtuTHhGl5Jdkh0hFF0NdJ/mdcZj1Rd/6hMyN1HnP49861Sf7uqNiH0DGINDCNkpGhKNCT848zMHnizbKexOXp1FuTPOeZW5zuaCSFhJMwsNJ9suHK8CSOgOt12KDcX8lnEeyM/0LnpsA4cPfNyNRIXEi+0d6nM7zpJ2YoVxihhLVPf3eut23NOYcDDUt8aAhNG2mUyzmSzJ2xiwVnanaiKN2Rv9KqceAaXna+3ounyw0a9f1MU9chZyijc6rO0YNKQJzghrEYoyCrYvnB4NKOYbhKd8NH20YeoWODWCTeVI9Eb+GsQBGf/PJ0J20ricGsGY4Tdaa+ycdAXmbyH+zfcD6uawf1SnPCZFyd8GPo2ZGYs6NMlBje+X2u7DYnWuuRKWFOy0Z5vrea24wkD3QfODD7UKSedUiFpbKVf/TSYG2gyoyir63M5UCUPOmtAW8bxt0d2vv3sZdHXWPwPqhnNfsKfHE413FSPZBLPxbcg2fwdLmOVZ0uuej1t4uhlWt+8vV4r5i/A/KLGWrG7y6v/QKo3gHzHaQpHh/PuLk5oQaCZOMFPwOYco/9d8Xpw3tzbmpA/89/AFA8/p8zBj5boRRFyG5/uxH9OESx9m8dZ3Qfq4Ap7w/9lzkd2XT4e55bMTBWYgzgDMX5n79HX4w+f3KvF9xV4MvP3VP6cj4dwQGS8yJ8MKTK6JA/13KspLf5fumPuEw4zHK/nNzUUz1/XXviZ+E/Ova3jAa2qz/zqW9X6Kv9IYf7hxcPz/e2wv3WuskNBR8CWdIjM4Cs1Dy68eCR5/b1b70O41muVNT419TDrnujAVP8MXgYlkGB6xFc14VpvLi0Fvrj4bzzBcTo9ExbM7JTMeJ8wuyANWNQDUm7gB+nw3dBqD2aHUDTaWUcNLM6CRTfVdH8/g0Ej3EuFL9OwaN4WM5UP9PvcMbnWKPQNTuO2f/5EfKfv0R54/6L/ygAcA/IO1uiT3fA/3pR9DqK8+d73Hx4B0CcJ3U4CiXFqi85rmVpyp5pFysU+/s/4fqr5TX+e65nVvc54n35ZD774t3tcjiTIU727MmWqGB/5lJHaEmIFMDD4ZlrI8zf/i6gIgxf+6Hd0lBO1P0NVOTwXY37G4BbnN6WqPUy4Kq8kewCpKYC9YgNhfaJ2TfsfUR64r3vpiRAT+WWeFrNQjzjVFJ6nhMYYlHPMkO5Fs8fI4OE7T1xmIMB5dQqO8FnPDJQuVfqynRnFZoNWDwqOwmXCy4m1hiyHxNtu0ni6VNUf84UQTMYBfpHRfrcCcxuqREbPF0l+yyRYmPfrV7ol+mwqeivZ9SRm2NEiYFN3MhNo10YBKnUM8Q57r/a3N/f+p5NzCEh7FE/q3NgzN3rIXqsxzQPrjmmK4ckUsbLkorS1mN7d8Ljp7Mxg28E8+E1Jr74Or0CAMwH25B+27DdblDMTD9fBKDuCpEUytVSl0qDvHXP7gdAHybwtj+BZ74VfOH7hu8AXmJ+VbRXfl+A9soN4N8IL4/Lu08xbymgV3i0/x7xxfE8hsTJQSy/F07VPy50YJLN6FBgSwiNt4s2PJk/OiIgvtfPMEa7AsB0UQLWQW9unLQ6ui2M6IArjcl801DsaR371tFbL04vq7czl4JpzKP+nfQVRzCtYwlNF+IbEK9IoCBcrAp//zkMHoo/x3kGl+qGNI3tS/SXzjnLPcdb6t+JA1VtTT0AA+HFyVzgnILS7AMsh+UqpXp+blfhmev/LMT/4VbLb3WEV+C9Ch9qW96K8fyY1p9wyWt6frWaTk488nyL+ugWLWGw484Jvq+DaZqokAXCGzZroBdm1JntXmgxxy7qxozjGqhEhKkyBXEIChrpeCOSy+zEXiPRz9gYGHsaThyAAGkYmNimGZlbb+ijY/Ye8GjnyterWRYaS36QyurYrsJ4x5w9mprpiEeoa9JQqMX7tjmSiugEp2zizVenOzsvbqxQgxEzlveYT5PK+5DP09waJ+ZjIgQSGtkb54A0nlPRZc6FfpqrAraVcdKQLjk/oMwhITMxjrrxyKPq0unG+/MI7vU85PnV4ediHFJ5la2SJoC2KNNCg+SQTPHeGs9F7iUjMO3vcfjHtJWC3h3Oe8KcKVQzYrhGrI0xgkfb9xE10BmtHpGahBsFdE7cvHzhhvYvCw+fMr3EmQ+DafxrZrirygYq0/0fI0vZZuB0JHym4sdpCYgrcm8u6DASH1RFyPRIWrZPukkn0eAtVKHDUtGLpkxyTcYRpw+sb62RIj4jkek0mVECbDFGCyrFA5h8vfPpnH+K3fzFFW0F964mi2L0z9vx2bqd8dYEbTZon9h6t73XGdHP4Xgxh6Win7v3Tnzme13SNQvESlSxPrav+a5YjDB2/opjQ9lPATOcNNDSxmhOaQ1dZxoEAXNImiue5JTpj1gjhLWsTTp+uGOT0oDXcz7Or2GkYS72meMnL8ZMPwJE6QGFhT2I7WjrHSfQ4cAyVTXYmkG+Yz+fIRCMoUCUHjnss/PjgkyhyHkNGFzO1tB2dUO1z6ayYsE/eUpCCKDTjD9anVYknMHFabrR7hZZUdjW8L3d58TQgZ04yjdWWnMjptEiy6BmDgaQjAo1Uu3nn+WOADDbNyDuXETncVI1m2uL1SIAtDhclQ8PxlFgsqiECzySrpWzVJiMgFxJ54VAbD9mAQ/7cIVzI/8i1EEQT2r5Een0X7QOx64r7Ifjh8uvcw6Mkan2T9sNdFrtyyZeFmlMSO+GA0Qw94nujiz99GLpazouVc3MKIt9a9IJ10ZNHDzrGHFBZkE+AcodChcQPyOGR4/6iAI9KKr05an6nWJN4pF1FDSOJkdFxzB7ckJD7qv7msfJxygoc58QFTeaTwwkTxrvKaKWZzjxgL6F1yRgLXij/DcOdq6zHbkLqFl+WyAr1hpB43l/kcm1zFuv9WCrRH/kwK8iNjOtdMFSy+q35BFIQsnRKDPxFEOEln8A815580Sufn7pIDUep9MgdwAiL4t0dLC2J7R1MHwgTVWOCymrVpgOOT9hgXOnM/j0jAQSBnjnYTWdtgRuQHdBV3wuEo37eOgMDho6Mhum3ivm+ArjyclTSNC4egYTBtZzeXFOfxb3PfGK9fEawBcAL4vs4vAiDXJ7y+21U/aErrK+KMSZnq7+uesS95iutRVh4xJnX+MYn++DfI9Cl6hE/ZRkBwDm7+W937Pj3A/ruzUxmcZlTgUi2+aR12L/87cJ/GfJ+gLB9o+Opr/g+2+/L88Df4cR/ZlVUuBN+cp+7/6m/hyjGRj8+g747RMUQIeEoW+WtxYZo7SzGK/9jv5w8+sJsvZbGRE12NYMy8b4ChA/xJhcro3v1fxeeuT5uPjlj11/8Dj/S68V3Rx0muCRZ/a2pFt/Ak39213ViJ43EYCrWD/tHfvPjHzmnh1UBKIjVnCOgXEEahMRIG2GDWI6rzQdIif7I8wedYZs6NBuHX9TM1vtTqd4Kh5V8RHAe+crHqHWv78XTnYAfhfgwwT+2T7jViNuMZO1OE2UX5z34ElqH/JUtreuCykrSbmhOhX+/xeAJwzoFQh/ZqmuM4nrb3+JHjxzkYlSR+gilOmceAaDlMS0jvebKjYA8tlqwHyG4iUEr9++gX6+B0Sw+3Mv6vsuwPKs9IWps1jUZHR4RBXnj+fo++rayvpnU/eqdVGIxI61mNlGVrVer1D+xkak6iee5SkXuBLd5zUR3jl8TD1K1mqRCrY3Gxq87tHddAOAe+x76nFRU3wIzMtf5oy0eIuxwv/11tB6xzY2PN7vwBzobzuaeuoZRipzPUhoRVxpacoOHTtkWhrA778PSANO77fDGq8eMzQe15qiACIis3dHogeGdNtuUsHGdVf1LAUTbcBqM7ZehJtLhvR4YMIg59Fg04UsxnJwPYwe9FB+UXgy44LGejGlMmCp2/fP5pGlDqf7g0Buyai0iOJSfQRgUebgHkAw7gbabXdhWqHzBFXF+dEM29KaRcApAKZAUcW+P4YiHBjYtlMIXoBiDCrCJsb9hLxrUFF0Kpc8qtKEDgByi/62YdytZ6C/MdhjGtj9wRQloiuDPbxGVr81xrq7ok8nozkA0ZdQfMP++UVhWhTKqHMAN7ev8f2eYyKT+d0MAA+wDA8UAnPXL/6O+lcH8stIn/C0j2bc+Pwkxj5Q0qluQHQ4ZiQlLIVlNlNYcLV3Fa4k3U0Iko0DlBjDMo563ophC0AYydnXhecm4Ok+LZVyC2OA4SymLIRkBLH0ju41i6W5kcA9SBJ3GI/Qyrh5D+Xvxvw3xIPKCflYC3MKuIBfFM1kUxoEs9aA9RTdq+IDaWhDGowwDf/MMZMJguPZTQAZmGeflyt+uQ+qhhPV61nIzKit3FOJyCZOlcaOqZbhIqIbdNQHCmHJPbT/0nnoCgcQ2rjEu0/qA0Kp5/R17SbWN7vibvjcVANWah8GJw26T4+QabEfVNwuZsYFLAMjgGps61mxtc1012G4k/JOnCRQ2TZ1Gi6XNDiH8TmUWAi8SSY9zxEjKpH+Dx5BVhVprO07p9W0Jz4cwxTL0KTFEEuva7VefWaM3mL/sMjisXsJjTnQRkfvA330NDQSf4mYU1s3WDIHDo1653OOEn2T+w7YOZDdDT5C6DZHKwyFdovIEzTMlq8K3MApViGZPlgJUQKIxxw6z9OaRRp21vON1I/kMahkC+oLeIpslukhBNKIozSQ+JpHRL54On8o0KggNEeITH3vdL81U5ZqWwzJFSYt0tF7F0WgISpAfVHCGJyr7Uuea6+ccUSc2hrs5z3KEkwttXx9rdEEvQvm7DDnRaexkvBYswJl2mPjYVTEa1gm/kwDuvEvVmLAYHKMETXQ1dOXMnWpxvjEHTEBCqfqngktMn8AEC3lj91AQFjys8nn07gji7xReTt1o8JiTCl4K/AB+UbFgmcWpzMA+U1DyI3mwuhE2igRfd4qftdUfDenC9Ksvpt6OysNtDH2bo5oUwTibiwNFsEt6gZLneib/c0U7lNnycqgy/xLBlpSVE+r7nRd/bzFeuKwlquxIA1JNWMMwmCrgJUh0AntQHf4mWPgLAPAOXClTwdR31hmrH+kdVbBmIIxLOX40OE1Nj11rRvNQeX9UMw2MdoICj3GwASjrZM34WXlhGKL3cbyFI9XL0aVG0wQzwTf5GtOGYxyQxgnHJ9oMzgLuGq270yZvW2bGRa7yV1zmDwhkdLX+u+tQ042EasRbzSrebmLMHQW5dFRcQN3sLXplZIVqlDn1dEaZGiSXc05qWRbpGuQInc6jPetY2ub17Y/heOmvxlGmeFhkcqyPI4jA05FILNDOyyjzDYh4xS4izRdvA5KIz/hPJnJxS4vaOIJ8g8TMzPuOB9qxvqOcT57KnPSAj9PnrpxnHc/Jw1gVI6SZUp9RUUGTqFsaSvO8HXhIhxxUzqe2F4xQtRRy/IcOFfnochztxKZJtKtTE6XmGNstzpNhkUUmWMMU0qv9IYOfLt+h4JwyPTZLWCSzrzMRPH4/TtuXtwEMmrbZk7v1JsQp/uqqSjmoB6nnFDirUlpTwvbmniNXCTbgyLlJs22cq1jR7J0Gx0qcjPLH1JuZ9a3SA/O6E4lFNAgXoz3RY5ZOwIIpBX3KIABOkBqlKYJOhjoWyoz5TxJGb6vd2REOMyxPhfrB46BskOVVhMojQZUXGKOAmGM9XvLZ6xB9n3tvsKzp8yCixRQ/Z6067HuPJksy+mhKmYLiJ8kaBeDHKAzhj4pXzhuMScGGxPrmeqeDqgA0LeGuRuOCXcTAyrIdopshQCs+pcaTdexuxw6oRgQTadNcw6e7mRKTmzirObcRgv68HF15yFqZKBAYHEhEjwjHcdib3z/vv72Ce31Kyub0sQCLBa8IsCY2H3aQ6OaO7TsqS2xxB4u18+QY79qhDHbVQDb+w1d3pue0XGO6SFn0OXAoZJ7lOdJo731cnoujAZOHvI4bI5FYXrnIQDl21lW/9pVNEnXRhBvbUBmrFFYqRzNfnnVdZdfkJHxbliXX+/Q5BdnYCT0G9VZRsRroTdAP7yDflT0X1q03JasXUZzTniPMz6GnuVKMpafvt7S+Rm22p8vVVt4O4G9JVxYKSHkHifi/8GlF9+OuzV/S2caNjsSC15vteJdoEzoR4PS5THRlDdtXbU+5g8VXk+IcewNTUWn8wnT8RnhXhJvKpB6qafn9vzI/9j1tN71z40iOJr1Iy7qDpiZq4m4DtvpbMlWqLDI9DnVnIuAyz2vTAMQaxly+aH/52Z77Rz/1CUcs+a+VpxLfO/yyEXbusIp7W+mazO+3eiL8QuBg0UiCwrmDKfSGBbI1ljADLUHipqNN3k2aFldEbeJOY4R4J0K7mBngHzfJwAMblRRvPVz8JHztYXxccLsCLCMaJ8E+ODy7/Cx3gF4p8Cnss0flHDlvEYO0gN9AGhzvkBC59LcAWuMAZnA1493YZOsfBP555y6713BoTz/0+0tMmXhTf/4af3vvZ6MQD8StOcuBRbE/NQzeOb3f9X1FJtR5zoB6N0D5PYNTl++XEUgE8B3pi8IwS5/jz/VjZNOpCce0PQNKvCt7PblmNhWx9NMyp+5jqsgiqiXABe8mzijDo8TDsWUGXC2bsZufdCIDG3uqU/FBKPqiPzUkRSVheLKgt6tvdEattah7zfMj6b4bltJ3c5UawJT8PKAitc/nBOZtrRnJBJS4liUkTiykwdmREPu8F9TGUVFqrQnmOuojbbWobxMlelcrjNP+37GzXbj78EUI4yE9c3SYCQkCYWPh0plCk2qifCnR2ntY4TxXeHtQLHfm7JwuyUZmhi7ReOkV6BgTIW8segPS981oa+Aea/OgNr/dvfywjx7xOYI5ROjl4Yqej9h7I8hEAiA8TAxdWBOi3RhijAIzACGVwC+Wur1Ba6/2l49vIG8sRpXdY+r0EHilztBQo5QhrVmkejnuxeljcQmTnMAAC/fvcG3u4d8+W+4SK6ix2vcw/LsU60UYKZAFUeBvUye9uMA4ks17+sOyE0dZbnK2U8DZf4jISeOWGdi97unw962kytfqXxIxbkpdzPibjudIpo0tsANdOquz1QsL9OHxrmx38uZc/xhjFnLOcHn4G0wHVVGF9r5byiGT67FYYmpVKWBST1SZh8Dc+zY54hUk0zxSX0AI6ZT7nImUrE4KpgA4785s214XupALmDsuiz3lIR3ZEHZW8u9kBwpFJGK8MlrYfrsSnH4kmMhnsobZGJ9z/Zh+3jtsFDhtNxajcLH35orlFrJehBKs6vMFPFPjW6lLzaFIMev6sJS9zOmDvWSZ4QR77GNDod0viATvI9RSgJIpOdnZG3fevzzkxtCRqxDa0Br2OcAzgPYG3rf0aR7pFbzyHquGUuDSKTMRxnPoAEJSOOD0yyLVBple/2MTjc2DD/TLhxF2mcAk8av1t0BMWaxZhhoFn3f+uZOhGY851iCJkUYuJ8rMNU93ItR/P/EZW4ocKNc1IaGG8ohoUxQtRRcNGBYCk2FqPFYXQuMz/PKpDsuFZt04hL/3+XxSMwXZEo5tfyyGITJKQWehAtZM1LomjDWARjNLjlrAaTxYt+ZDcHSt4eRXtQdJVre49tKhzugtYkxeOZY0mMVaAHDc92jjWvaXTuvwJyC3kxBo5o8ENeFdIIXz6nNccUDP9IpVR6j6ARWOuHGpYyizfGWrcNhM9fLCUJmbTGHFst84YoDEUsR1xpkDlOwExAqGYAJ/+L8ebALjPzRqrTsZkCfOd9Jg1Qdus8/otioLCwK3lkMOLUsx7qGGkbnNepuhVuBKUeb4yQrA4WAl33fIbI77TWjG2K9bM2ooa9cIucxp9XO2/ezGUFncx53QMeOqTvmbMbHasMYAlXL7TR2On0YTo70WiCsAeopvSNjx3ImipaW6+MgTJpU71eWlIp5ymyUY/Lvjo5MfW0OMuZYtG0bTjcnnE4nq6c3vFTX5J7aGd+604Gtp6NYOMF62RBViyAfu2VlKTLMwmUrQAdg7kaU0HB4inI21RlA8u9JRS7THvsZ6d1pXjc+8+QZWLbTyWir81eGRmfQzOH8GALPSrQrIkCHwcOweJUp042F7jw1SbMMHymA7k7PIfsJ9xnuCENjmJ8Rzd8dcGwsfoamIhydQq9MOS4cESTFCi2yUhxJfznKepCnS2O7kQ0zpRyzRVCZRgOvQCJTy4JFQw7Qi3vh6NE7+qmjtS34nuDpeK5V/QzuyWN4mbAZUa3GW09t6J1OyaZj2IdlRWj9hLk/QsTS8DPLxPHq27bQ0IKw/KY7rhflMHHHDDqD+Ft9fN6YL7suhnM69oXjZKEloWCOs8JsR5mrwFpOZ4akRWwMfmYMRi2ozTR95E8gfI8o3NcQWM6hQNZ9mvbCnNyPLCuUcGf8WpslKaqW7BOByw7GQF/j5Fu4YAW+nUdLHUmhK4VZUq5vNH0woLO9+lmHcux7GSOSPyRf+ZizSQNJ6YdrqwqdcNzUIgsCs1vV9UqHFok+oRoZUciPTlGM4mA0zlmOiChgTjiecmcCx0VzJl8oTSyTEdwhV3vyGgLLAiMj5mj4c5oR3tdjOowQ39dAmTCruezT0KAj4bem8Z8ANrXsIH320BvSeVCR+lnuev133Mvjvb9+vUZ76/KcpJFxgd3o9FImrfjkZy4Blsjv41VPDHDMAAHsBTbrehz/vmyz5IAiHxLvGawEqanvMhK9/NB+fQvFXQTxmIgmGXnOVyTfbU2AXzLIju1NzRIqfCF34XI8P3O9urK2d1dUG28U2MmrKWKBvvyZTv2yk2QXJbJqMC9TjwjaZ9s7zOWqruRnxuXnK2p2k70oNpSVl00epGpuibMRNMv3TOTizPzRsf79Z/vvuZ6fhq9DM1ogoUehHkgiO0xvzYIl4s0rramfxD+50dfO8M+/nDQ7b12JOL92n/BUZkUd59TEPTR8R6bCfNV4EB9H8MJ+WaU8Dd6aPAhxdeKxA28A0yF311HcVm9o53EQsF/l15zPe137uBPg1un0787//9N7/FyWpP59qxwNIO1D6J+hlZfnE9az4G05b8D33z96ycPLi3x3vcL5kd8pl8Q7T8PZMyTq3+r6uRTuT52Ip+7rld//7GoU5oZNFtVfIAka5FZASKiZ83AgCgF9BPAiBJOGR5gu9HT/4AKE4twaTg4k4g08NT1x5W+lmV3eoL/r2D99hso9Gt4elu8hRl3be4RFyCcrC9BoAqRArDyQqT1Z23NGPImpOHFlvKgEwAeRFYE2T/ciwap4DTCLBqXiAc08VXozo1XfNmzdlPGy9Yw4n8Zc790EI/F2F6P71oDRgK8e+aKCftpSSdYTcS2bCe5pw/jnd+iu6K8aZmvY3m3Qe4HeAbgly5aE9/y5pCRXxc370/LdogG8O0gINqyT29y4i1xJf58b1RZkFDs1pzPzezoauEEkFFotjXX09CarUKfe4HVlO9wjs4FpSNUVc1+/fMmUXF/IcCYSN0WB1eXuemvpL1XMUOJSi63ZBHRiv/e6tG8E8BR27Z1kOraILhPsQ13x6kSsNYtiBkx5ph4eG4oWBfQLgBfmXYeGbUuFYBgaAI9M+RrrOnm+MTHv1TyPtTLsa+Wf8ZB7IiKQ2zdQWMYBgeC8m8KzvRbMB8WggZ4w51/GnTVk8H50kikbf+VaBCfJR5msKJ7BQal/vbmLtg2/+V/T94JKMSpDljd8IJKM7tKiw0OlIrL+54pEhMPDKOn06KlHo4wAHnXetw3bacNpO4USZex7nE0osIkbz/sW6UXRSko5CtfOAjQSL4koAAAgAElEQVSYwZAB0YQlY2QErP8b0f0+Lxr8F2TpwnrWEqcYVoVeiYhIl/6tt+CWZsCAKZXMcDqnObDsw51f5kCElzoTaJG2CHw6nTnJbbP9thSkDft+doa17GUIkxoRIUARThYlE1frABeLhftIId1wyraoAAZ5SQ3l+uVV+lmUs0mrqlNzPTdUsnEu2YzvkGdMqYpNnROz0WBE2poKexFjilkPszOdrXgFsioMxLtM8y6Wct0FGq5vcxohMtMprEzblE3FQEA8QOOlw1XO1/GvIiJzxz5KnVbWoKYzl4SDSm++HiIeBaluNDSYsXrtLSJeLDW9oEMxWEd8CoavUSi/C22cqhhjh45hBtV9YPh4OV/4WafhOhS8zoeRz5pDwyCeDmUAjZ0iKViS/nEcTNPbOhXynsKdCt/Mo+t8n6XlnQNgGtmsydpsrM3hPfaPtJ/8GSMaNY5fzk/yrElpuwkwG1ozxwc70/CMZGI16JXztKww4hGx4QFdeRBXJNvfUsZS1WMSex6Uc1q03RiuUBWB9nRUpBEbSCGKhm9DlRNmZMlzWI0mxhetDHSVzYgTW2sYY6LJXH47RuPVZ6vzljm6KPbeXQHsTh6zGPSfuMyZsxVoTvqQ+2hrZnxhqTWcbxSY8Hl7GueqTEoFOFtc8VjSDCvJcD6f0beO700whpVXCHJOHtqVBWMY/2b4HlmLMOQb4910KobMJRU5+a/FKWwaL0xjYpvuNKKHTZRUZtIJDprzonI7jHEBHwtCXPfcfw4nhCLPED8uQ0DCAvlsRhv32aCnzc9FCzouDhdz2rpZmSPFd3wHYDhSWvOyBJoZnGCGsvNZMcfuDhKa6fD3aSWNlI6gzo+5o57qQNeOAauFbZkIG7rQCBRSG2gsrk6J1qJezp0G82I4Zxutebzx8LPgNG/bNmynk9V8bx06Fbvu0P0cGa8Egt7PGNvmUdyOjyCQ4Uqoqdj3M+bY3cCswU9xDnXs6SRh91rQOgJDGtoWPoTZRSCQnutF495Go7nP6bRt2Fp3xzSXxZqtWd82S8k9Hs2xQCkVm/zVT923TrxsleVdM3ayWf/NU1iLeMS+041muKBNDZoUeop9JOkQCUOo0WTg/P1MVQkgMJkc8DIL6Ta2nU6Ow80wxRJdNMIyGw1Qlr/wkEo4oxMqWsgQRmPMWVqxbF80Exy2r9FC78gfxP5bX4zgMWd8o81b33A6bZYpp3crn9aqbOilGfx86XAHFI/MnTo80rO5fIzET+p8nstE/XSDsZ8hsW6C71+/eTQwPHpH8erVS4dfcXg2OkFHX2PVBDKttrrqyIw+kgZp0jdQviXeEbGS9uTvlBia/LTvW3EUsxvicIMSke5yfGyuOVImGea+ZH9zMtMicX9bu1DFYpJxXFyN58ykANB5IJ0716OrRIFQ0htoZAYUwFKyQsJZP5F7dSJGGHorLKfMmfikiGmoALywAVSyO5ysfFt9fuXrcPU5h0c8wjzQz8H7ws/BDNzOc+NGw7F72mqjka23KM80GJxR5EquPXUrzP4DwPGYhoHA9kAgbYK73FuzbDK92zHzM8kUweKrHhF4DWgqUHFHw+HjFnX5uXnfGg7ConNx4lbujbd5VL43aVaTvE1sDouDZ6Gc5/3uAf3De9MvOV8wPQAlnCYPVoHq9ykuWz955fb88Ara5d/bWzsXPfC5ZV0MGehOMXEPuX1T+EuJwBeuRbT/g0Eykj+MxJfs1NKGwnRpR6PJtX7qsTn+HmO98p4FaGngu9oWgIhAVwD9H1aft8k7a28OyxJGxzXJnhg9WTvdP37C9v4dtOV52n/7iIZ3OP2vE/AfgIwPwG8fFwPzc9tbQYPG8w6EgxjvKxRfRZaU8B1wvYUycYp3WAzExgBe9ltRnr/4IIq3yQpHc2coJj7bGkGw/eM9vv/z4zOzymuhJdSRXHnuaOg80oNw4gUiW2SSGbbrGgKCphbIkfIVlJMcn9GxCJQ5nzuwT8PnU88931pp58C3PvXeqW+hg7k2nvp+/e2mn5xXMpx96pvpppU6GwBzojXgPCa6CIZqnAtmkhzMonVlngZuuo7/OWH4T15Poc0qv4NyZpGB01ky9eBOyXEk3IWc5H+UdCLHoD7HcKiDZz1o2fIs58qortaGUf9Sjg+UGXXJ8lmdvFJnsbYjAH7xLjYIzshMLHMC9z7BtwqveP705dOwcxf4JoNSrvEp8t7P1VTXy1l2lqGpW9Wn+vX9OhrRSdc9zaJl+BU6qAMRjf6D8/vvcv3PrIF+7foDTMy16+bdWzx+vovvG4DtVrA/FBApfRwdyn7kyTXxgP0TBe31ugYqvNexHkp+Sr2x/P0Ua/MHLk+rx/hLVxEDQNRVZD04EfMAnW1G7fKtb9i2jtNm6e+21rA5YZk0kopCewo/tc5xbx29T4xpEXBDp6VgAoJY1igjm7bnwqJSfzMjwRRgbxPyRYzRAoB7QGhEv+CM1/VLjyB6XqMgDX3ioNsOKeaBEyQ2D848CVvrS4qlGrHuVCMNEIc+t75ZLfGehCVVFRyPKfNoPNAHMhyuRKdCR80w3ODCWxgEG1Q9uVWJMFL9CtUX2NBNOQR1254hV5EexrjpCNWzLZnQLM7EMh0iRmazEHqMfcV8eIP+VquewIxDAIBXvuKv/JevZeZfgSMGfwZR5FlPArAQZoE5Czw8/35lXp977hrayt9k+X45yB908qPeA94KFZXDM4sS5VpTBxazfvyICCrcYJrjoNCQR4Y1zTtONzc4bZvJx4OlBOy51ky5aUpQj4Kl1w4sw4HB7kwCHWNl+m4Cl0SEQmqUlol5pwiO3nBJZeR4VaMemGEdVDLGUhTvaZ2mVBqezs3+tii3OQcwZlG0+HiECsw0HEK9hp7qalyWXGOJNT9ujYKKi4CQC2B9jujK4dPXNRQ7V96joPhDuEn8KcHoF6WtKtJAWZp/ot1g2N24b9k0ANFh0RTxrikmm0cztu7GFi/7YYrtbFPV04zbnSUCJw15BEeJowbwN8c8auSNdVpoRKCSOWmyq0U0jVPTz4qW1O3xTxX72PH4uDu9t0iqk5oCfqPSVzwFr9BDFx6BbgiaxjtMQGVCpqVjnK7oF5E0dpQIbjqGDLVMC5FxYR4Vk3GwYi2hiqaMMneYdkct9JYCOoAuiokGnQLBhIy5gKWI0d8uXsc4jOdY0mgL3PFB3OGQhhhppnCkxaNlLiaSb3iq3OCo3Dhg549+0dYLXOFra13gT7oZWWZVXCce6yKOF8wwI61ljS8RKwfkMEpDaeCsa3gfFO5s3QKSFWEYJG6UPR0AE4b5vKSC3WF5geHC0yS/lYR+MQJqGvMZOcLInRqFkJcp/lVHnLnIYrJbym6rEW58iLUp8e7iCFPGwN85L47zOvqiEf0apZdgI3kGj9715Ocq6bnooZynfd9x/m5Rk/t5D8F9idJYUmCX8ZDXrOOD8+3DFGI1Y4U3HHNuTGe9rBMKn1C++3phecy+RJp0IQ0yeCz60ZwLdIGXmCuUBMHP0gx4O45PnDibM9RmBrCuiFR2F1tnfY5wFnnEmDMcqYi3wkgxJ7ALZjPlFUkd6zFPp/Pq6bSNz7fsATZ0y8LR0DExLE25r7Wl6Jech/9l8hR38pLHu4g6bzxHKGNYAY6pzk8nS9/epGEfE2M/Y+7TMw6oGZO3hrHbedo2RW89FIYTNt/9fDZeLs5Qjj1576SnsWeNTkXXpenVSI7Aza3QevKWp9MJN6cbM57TiN4agIbmjmN2Pp0uKyLtNEp7rTdPP85oOM8c0ADEFC0yurHmvNCo2CDdcLg6HXNx1o5KZ5Ri8k8mSnvksqdzJ33GNFmRjjIc53B+ZLhM1kTcwEuYnhGx9OTl9Jbl3USLkXeMgj1X3F0wWn4jWDq/ncZCCf7b+JseZeF637BtJy8hYMbzvnU0TyQ8/dzpdP7Z07Yj4Mc3BHCjsUbJEJZssKFpOU98V4KmS6TasGe+f/8eiJyOLxAq9yXYZXN0ml7SJQ2X3Ke6XxeX8wY8o6QfC9X2shz5Skb+cxj1PucNSEkpvrbPlyYUbcJLC5hTO0vGReYtpj0P8mBnoocDZvk31A2+TpNAU7frT3wpLjKNEEJIr4LwatDRJKrJcy7EWSNhvc+2PMd9rQsLrHuElYaob8RyR2Pbc03V+tL5CK+MB7x4jI643LlvGnwVR2o+eaZ4bmr7RjqixYAe7wpbpg5GAzfMqYG3bZquHvcAl8qdzjEwpqB3BaSFccYLIQXPiuiLK5OwJklkfJiKiYGmVb+V54UOMcmv+GjatKARO4ygEXVOkwWo4LcSk7vpKdVxP0Gb5SRyi+Na9+3yt7qlf/TK/qS0ZQ2ZkcvK5IRUIFLKCz3ddcgbyw9cS4HqPSBvkh8o7RjZWH8hN/ycfrsekR+tWV3nA+u3vCu/Avob0P7xzuD3109o8i7kHYHh1fGb6ezbr28BCMT5JdLPyQwvdU4fFfJrOq4DwI7PGP/vW9z8x5YyeRnXU9e13/qVe7xeORJ+RRRZ2LL6+Veu59qqWYI7BJRIn2zrKTr0Z8Z1Ra6pRvTg3QgZFzw3lgUnfT62G+/+SI90aPpfeVkAhmAfT5+s66MvVEAtMGK9a1dvDZs7tevgEy5rgljn0vwZDo0/v3QXo/uz1zVZu/52TX+nhaZX+mg+nYQNBO+DJWOaBn2Jtvy2iHj5qpRnJ9SzZxBCLzS9/py3Rd7b5ZQ2JyaslGcN6rrG6zFLB+dV56cK3IHvKWQC74QOa5a2/ZcJbHiP/9M+2djU8FL7BQvtzYZ9HRf2yHHj/hH7R8UGwXfRSzxfx1/3qNL7w7NP6Xfi1dr+v/G1AT8x0B88UInNxXvHk/0Xr2ebkvyI/QnG94LVQB157w2vPrzH198/4hHApgJpr9HbV/NcDGVNzvWViFc/runc7co0KoKbd2+xf75b1kmh6LgFYNHoE3fRfos3WWsBadBRXRgaIsJgruKPkF6iNQApZPsjQ9KoI/Ii3hPQWzGjnk1YatikW+r21rA/niFTcepA6wrpCtkUvd3gpgtOHg3auwnCZwV0mjKl3zbg3pjmKcbQnKTh7OlUexNjf1UiEli89sckg+ypxfZ9WICjv/PyP28w//fAeWvoE9jedYw7R3kK6L0acnxngtnpbXOGugWCBEigXO0dCEYdycJTLMNq2BWFIIUEMur0zg3lFOsyBvIRvHj1yus8N+h5LwpKh5kJq3lsO2EKNt/v3jbrl7U+gTBOUkDa91HOwRWkrVoUMoLz3T3k/dtI/QkxNTrh0IjAyzgUjGqgAKQ6AY9KGzrC68jS+tJwQIKUkC9lPFZ33NcOHrUJ4Hw+x94AwMv3Lywd5/0ZwCs0N6KfkchYsQoCCmMiFeknSea39wbW8Ewv6xbEePfnnvLM5cgSH/AM+d6UNHe1nRRYDUe0GH3iNYDqn9UD6ud4npVJldQ2+ARsn9XDsln+Luen60xOEkxszCfg9igeXbl3VGowVWpxWKHS1tK4b5GGratHc0mDtPy9uUEzxqxA1Jz0KAuNsVCRKgw4idpw8AgiOq7kK7KezYIXWDuR0ZiNfbSDYgCOE8ryKkzgE48aijTbOiJKY2qmt5uIoBvo7ksZLGSuc8wXrjThHJDRlqZswf/H3puuuY3k2qILEZQyPbuq99nv/3x7d7k8pIcUGYH7A1gASClt19B9Tn/fZbcrJYqMEYF5iLMeUTMojCUQ66AUX/hbKD5j1SneEHva72Es9BPBshSVbt3k4W9ANwm8SLZXNl0EoQPb/SaHz2KRWn1p7tlvRFEhYTlpImgM5BRGh3k2lu706WCcsfq6fpr9N3E61zxtdKOx1RkW2mATtSXfoU4746iqpgOB5N7YOpuj0vR9jGgf1ublng9XMtAZyY9v3xYsfVibkhGnmO5Y5aVTMN3Uqzy3NtepE2jdPF9FwshtxnGb4JgT27pFBIr6vgHq7r5Oq6sWsnD9ExrRpjZujySfCnUaw5qRtvoTMiwrBeZBaeZCjvTupWjcIK7pEUtDtNJxgGdPPNVmS2OWEIDVjDYj6oBSSFSfpuMApl7TBG2N8+pMm0duk0u0CHNx92Ln81TsuXC2sD2a0tCa9wmFGZRRBEstLxQ8mBCF8Dnm1ugMGs7FpNGuuQGK5IBG9ImaQjfPENO9R41RwU6BHHypVJ6pcPGBj/d0loOjU8my0DmlGN8UEJkYA7amwnNT4D6WJj+rjDywPDukGQGu6jXVZtRVrPS2Ku+55qlT0h3ySmcHiX0izSD/NUbD5XIB68MH/+/llXw1gqbtUGFxwhFBSfcLc3ABkBKJjZ7rT6MOjcpQMxQzslgguMouMnXXVqWEGSlZ6NkVIt/vsT3v/SgcltwBdAfebjggnXM+j3Bk5aTc2DOAbSqaGxiYetj2wt4fMPohfUMnHurGuzA9uqqVLhKabDxl8VBAt4nNEDEsolccl7RwBJxTLPrUEkljd3gFsW91fWzNzQKbECnOv/ju0RmshYtCNMKVn2qprxu8reB/DCNsY8N2WbFuGUneALTecT4NP08ntOZGS8fvcw6s28A2TS7p0u3ce7S38VKU8zQcqxwT27h9/orEDTtDi6cxF8ksPQ2wkh7N5Vk3nJ9PZyznk8mshmJNInGZxdK1Gw0VOmi6wbGhoS3dMxMA6D3wR4PRJaJm8lTmfJ7OEhwjpLmTloK1DrndjDYWETcU29pZOZrEza3bWnd3NAgDWMgdcKeMosjzM2eOYTxslc/1NRYv+yJ53xxaFc0jqzC3eDcdIQpujnTwld9L3ExgpoNa66YQbn3ZRZ8vnTTbjcoqmGT6JjIVuuOEekDMKdHPTWtm/C8ps+c2oDL8rPSKnYJvhVga/y4tsi+oOF+s9PMwnQV5LNL/oM1zRCYBo83ufKHkspM+BGegTNGqyRYJOQOf254k5rx9jwEJfi3xrzDzPzI3fMs9s11GsLQcme9b0HXk+3Y+Kq0R50kVwzMBaGE2JGYl4YAEdd6X/JOSjpW08ACoH9M6aXVMVehmUt4SUb5bIf8b8mihU4L87rSdrIHW92NP+IMA2JxvntBLluWQx5oNQK3ERHk/yhnJAuJknQg9kYh4mYKR+hrN/ZFgwC2oRB1vmJxh/KC6vk+8hI5lwjLYGPzdyfK2uewjAm0Ns2k4UPbuBv2aiWjpCGWCljWnEwkZaqe/yZ2kjKxAZKYRBSYalqZoKsZfk04oIktOI858/xH9haBmDAEMLod/H0UGiXIpBSZ3OoXdD/XG9y9HEdm/ZP12QxGZMcR4oC+Gyj59QnvzJsdDPtfPbzUU1aEQ9nhCGNHeXvl4PuQ0MufPkRvj5zw/9AeNCslan7teEy4dIyC3g+X4yNbNd2bsaR6R2Jh2mE3PifHbx2hiuiEdv9rElm6aMeo2GIne8QryVvDt3Xt0fYWL2gLc4Q0GPmLqWwDA6R9vjZd99/72AA9XTdv+UJ69h0Wb33Nf4rmCJ5H6RKi9E2ncrzw3/bEkpzud/vPyuIqAxRipX6TD0OL3B56eWhoUs1FDYz9YjHg28ebRQXqK7Pst6PXWGGLvI2LmibESa/zcEP8FVzpA1TPE8Z/7Pma1e+DcrgSPX5EUTizyPCOZBefTCY+Xi51Y8Twkzr8NAItn7G3S0Lti3TZsc6K5faDpAgWwji14DOBwfnfT8ieKfuCp5/XwWW48R55mZ5c7PBg66srj+xiU/OFT443nilZMU34AqOssh4c0luNillakE5mrwAq8JR9QdQ87Rz/CfGvYVPHQPKCp8N7hOHY405xv83ZUidNJ74D3Yv2/cXr3xvHKwAcoFC9jigK01zEP9TW4/O87gwABnv2ffwSsjvcfgf/+FcvyCy7yDoAi2cr9jnIfqR+3JfEnc1o73i70PJL2SZRnf+Y6wtrf9ezPXn9LBHqRo578/V993Tqkf6RnAnG8+dKiWS9Xraof/KsqwXHd+xHktX588DcrINn/Gl7u3mWbFal9fxZ/DhQoYzbxCC7AEHHLQzs+f01GDcbodeme+rKb4cCZaDMweC05r7u4eD1RaZbuFSIhBJl2X9BfN+gnoKtAPap9E6uDPqPe8cTSujNSizG4jUYAGzcWJwyLeH1M4P6/7qBfJqZ0tM9GKJhQkQe5iqXQyozM/dKGMGlrMx8U/VXuFoVg2/kZa3b3/Dkev3y28yFJ3O1ZBEMgTbA+fkN/9hxwIilhYAFkAs2F/eZKBUZXEEJ2njzqSsjmtfa8jwlAP7uRqLhh2Oy+5VpAMSAeNY50ophuRC8Eor3wLXUBQFxZbrVrXeARgbS+IzzqRITYwwyxPieXBrgv7aXXH6wK7c8KizB/ZrDRq39lWYobn/MsPsWgVsUEBYf9W38Er1G5XN+qAsfPIP+/B48eW9Idt8lIErvkdp1Cf83qnl8P7IaYCYAKruPzpf/CMIa3vCh6g5eLcK9KQugcGL1BwGhgpgtNQc85GD8Pvgeent1kT6/T1phuFpZ1IRaj4OyreV6ZIHZCQ0xK/Mzah5BDaZDZ7b1HBrH0wXQjxNQRUWpRLxBsI40Gmjf/EEMRIylAmTYpnsUfQaDc+CxAiHBkRbP/W2/wxwhkwPXa7wdemWDlTILx3s0vQI1MeZ7A6ZHJqmYgBirz183A0Tza3Glcpm6HG125twYHFvHlziBL1knPCPT8Hovi/wL/BLM8wVgp6h/EzxV5kqBoNCSoR5i4Mtns0m4wV4B1d6crd2UDBgRj2TDGApGJ3swIRZik05hlN5ZQ9keUkMOj6rBUeWK03RuxzDBek3Rb1xSS+d9ydneRh5rCCaDoQmiiQDKhnrrcZuM13B3xNGnQNj06foSDIEFEXQiKTAGRTsp5JdCZhvRQw+Dau0d0uiNdTEWcdos5KxLoOScr/zjdIYaRQwjaZ/dYH3QvcKXAlg495lTjTF3zaByx7AEQUzaqpw2uDjJPZmeI05R7Qvxjf8dOedF7h7pnQe8pFdi52PfBe8bjZC1e2z89PFt48+KEtcch2ZfNy56INRMB0N04mgZ0WRTbBtC5hS1POhuV3miUVjEnxqlqYNLIw+S4QtnoRtwGd7DajRble/mlKuwrKcP+CmPMGNgcdhTAtm14lIyIbIzSdBgnzDTP0tJrGm86QYQRGxGlqs4HN9jZEKfVLAVlZ9tgYxsDU82guCzLnlaSsauTc4i3j+mYEbilrHDN5LFbTf/enIeM+tRT3ZEhV5L1d6Mer685a2KLwNMED7h9sAzfTwWN3l5EaBsTkIa22EjvTnfm9KoTKgodtv9zbOHYOqeGM2j3YpiGfryEVReMQaAGEGpRhIMuHafT31Gd9XBHsEA8iStIO6SxjA157z180diFZg58kcbb13fMgcf1gvWyYriTrgjQxMs6tIYBxdJ6Rl7MaaW8ts2doSUdOBYhqYgxRFAl1MsjZe3r1sXSqisgLZ1zeInDhbjTkcmqlGEtAv10usP5fMJy9prnWngOtd1u2sKgVxWeImKOy0rHOBtrEzfmiqaBtjFak2PkHFqWfZoaEb4+Y4fDmQ5jAYek5U57FSWa1AxZrbegn8ELVzlKS5TSTGjJ9ZM4NcktEQQkvhh/5dGrASO2fkK8rgl7XBqWrSi7VXpyh5bW0JsZzU9eQsAy1XVP7W6vOGVD4H3AcdIGcccIhWIRwWiWlUeDIZcyhDwEyja9HEr+ejgsZeX4SeFZ5jSNTe76Z3vlTiFpvJvZH3tXBB7nmnHIdU15xKnkjJEped06ysQJ0R72XaKegdI+W7HzBiTWyX+mG00tF3wdtMKvZxui4l9qPxCEzBA8R9IKGlFpxGebWhvi84eoWq6vgeY1tO8vycXwVY1zw3NRsirt1g8rQoi5ZFuEkP05rp9vfdqdPMePE7O5EXga7VGWwpj5vG3/jP6JQ4gTIqNjAYAd9DPrReALD+KZ5uzVvM3pDqRw3JdlDd3ptgRNVDkp+pcRPFoLkEp4Ih4m7upl7+oOcrVSdgI2VYwHD8yB41l/q6EYMK/a+onrBy/cgKh4L0qwQLGpuvOSr8vD52i6vXz1ROPuNIaCv24NkfqsG7859fXPN/B8GW/FG3Xl91jvOOtsZSL3nr8c9ehx0trrfZOlizlL0uLS3nhngWr4P794WxrZEdj2fG8lVVZ8jLYHPlo09m/v0X6xNPHV4fO53q5Nfqveef2NevYvIvHs1/jssOlr9UXUDeDXNPD6e1nA8p2OSomtbl+qivVnIF1/4pk/ee3IyY0fj/pSu+rsvt/uraf+dbO5PY4boHv1XZo4/3X9Ppzek82ibmEbA5tOl7vSAGmZAo02j2FMs/FJ+4yMg7KOGP265Ub2775u4Zyf3b9buI1HjHq/tPpUAzbhbE9jIzOx64QZeU4HVns9exQRYCnhboHgvFUXYD6IoDFIUzWyWNXMeE/NPeekeKGKB1SdrAHJ7wK8nXSzTvqW4yxO8apY/3fFBZo2F85LBEOMP3347XecATwSBpF0gut2S4dURfOC7uydkr3r77ie3H9UXjy/8/efwbTf+77sOpX9x6dRFFtJsplrZVF3O2VJVQ5H3aIqCVTg3S/EUykOnlL4BSOwMzDk8oVpO1bEPvzmRu6XIjhDMR6+4Pz6JZ69fI6vnz7jfFDU2GHamwOorPgKDWKpu7xq/PPCE2LSjJkCwITcnJuI4O7lC3z99FCH7WnUkGuuAFzJa17qqfQVAObkn167QwRn3GO2b1henCwKAMB4XNFOZzRoRJFR0Gc94vPphPu7e5zPd1ggWHrDq/YSz1/f4/KokL5AW4c0wcWZeH1hCrbL5wn8D3B6s5gCcrFoC7y8w4t5wulywmW94PLuYofzm9UmXd52R3oTY6gp6CCALIAItk8DMqbVqm4DejpjvB8WyQGBMIWzb8X8aEx9e+VqqW6G7TE3QATL4qKW2G6tH80QT8/R8ckP6JsNIj2FBiopATx78QqPXz6bwZHk5hkAACAASURBVM8jAp+9uMPYkm3XOSG9Yb08mgJPzCAYUVhwpNMpwKkJSUuPsTElIZWixmhOV3J6ikEqUJ06y8uO+Xlz2L3HxLeQlxpcwS9m8IioB6+TN1WxzQfIwzPgVc55junRHhKZAhoNKHkIHCAFGIIlakCVyAp172IgInG+vvuK/mpxpbui4TnkRcO2+RziXNi1qH2m/rOOYEp18EzXBwGwbgMqZoLhOPtyCs/9R9xh4vEKOaO0r6poc3oqGSferF0r1me8FwxNu4pqr96jhN1E5BXz7pnHn8DgiZva4RZcmCO+AzNA2FrIiXjFlbBihkWSdKaVTuFOARWLEBU6flCxPdFl8WggY/Z6P3nEic1mvXzDHAPfOlPyC6ATiwB39wuGdpyWBa1ZTctTP5ngRAU6HWJqBO9EpLETj4ZpIpit5fqSaYLXD4cpbFnrlIYTncCUVGISX6ozY5P1dzXhyYEErVA/8f82ESx9wWzN0mL7eZ1QU0hvqymfx8BQNaVAa2nU2vZGt0ZFF41Jfn5HGYrwzANuCOvmECMKxXCvf4cs7q36WrlShf8JG5e4P6crCWIOIUX7ex6ZHEbl1rzeYjlf7lwg3m4XcZybyuc9g+zjFYVocz6DyiIJ2GBy6sQFZKDFlkzERi0dKgMTLZwbxsiYPZ1mPGEbVAzyRKpHgLMwiwiwLC2ixMM/3BXnrME60IxuqcNra66Qaq4cEFeiezSP+FwlYdyUlQCGYmxOP6fhdSrNOXKZirGueIRiWzvW1gmqBj908gDcIcQjihwGxM9R7wvQNPZH/bzTKUTHsCivMI7luUuOUHO/bAOTFjbxLDV+6ARoOi09rjRoa74WZsAcCmikym1WN9HxlCyWGra5gwSiRE2LzDbS3FmnedrIznPu2WuErnOUhiXT42IafXFjeMgranQIQkHZYaWJ4d9pggwpRUTUAFBllBqiP6vP7plLVNA9kAkDyX8AGY3sMBo1ygVxvmpqaLf029maG7bNouuqg4MqCswT7zDy2THbU3y77CPNAwpCaZtrmimyOTT30BbSFsFyPmG7rFEuhmeK1O387C4M6dvjI1qz6O0xtuiXhjvvBaoCaYvrKd2JBL6/jExGygZJDHwOzhPF3HKlnHba+yx1U39rxHtKPGPzNBzpaSc9cjXwaQM4AYVAh7iRneOB1Xpu3eCNdE8YCZvOJH1Z3MgnwU9yrFM9q4AOzIEwmquH2zIZd1nMwwoAUItkjjULhONPsZxFQyI2slKkq0h45mJVo8uc6g4AdDpC0IjhjkGsxdtbw2npGJtiwxq1BOc2vJ2GrgA8wpTnX7rXTRcAyKjgiQlQXpn2XefAnHQydcxBmjgAppxvYnA5NbPQEP8aXLSSwhhuiPazQ4dl4dkxOQDebmbV8mWik5Sq8TSOvxhJDwjWdbOzfVmhU3FZV6yb4RaOT8R4C9VHS23/tbvDip8aI8sYLscpTPmnnqlHdUQE49DcM2izuuS9Z+kUnhNMjM0y9/Tl5MZs4xi6mNzaHJa7lxk7n09YlpO1t/SozauSuMwczuz78JT7w50vyDs0eC3wyBnl/J50jDnR/KzZeZ47nEncb0YkOC9l862ZOgAxp7HZsY3VZEZ1Bap0p69bZlQQy842NjVnJoE5PgcR1cBHRibtmeF8IM8HzxP5vzRcCuY2SbggaFF/OfUu6cARsgr7dP4qJAyxGufAdFxeM0t136fFU7fbs4azyM8CurmT6TYxtoHtsmHbBrbN8LcOc9xAHIt0eCCmpoGwn+4AAbbLI/3R7Jz7noW6VGwBxbOjpQu9tW/OMeJny+7aMXfeQeFyEIIZD7qFkHZ8K9wZs8SJUoXuwBq0JHkigQw43eJeJX/F29YE9VL2PyUtgOMJ4jb2Mw3vEaaogwqcHP+cd6UjjO9BIzzMwAx2koOGeDp+mAxXoyIVVoqAm1elqIBxqUpmBBxKPMnVlfiGWPfYaAiYKpzOL252DL7F2tWvjzELBXVVJuPugAx+pt3hhk7bGgPw3SG/RpnZ+2qgj6RTYlVgOC+tADPJXTua+VmDmFOPTHMMUg9uCMcg5fKlR4avew+e1+R5hdp+DsVGptbXpgnCAcacr5hpw2TL2RqaTq/Jq551bSAyLAQt9fEc+MdNFTIDuH2Jk+axoIQdLYcTLz9EmYX72DzlcdPSTuEzQxenfvYJ915PW/bbW7mb2EsaZDrhS1OXRl1Ea46nvL2O52BJCOrzoL40sp/3nMPvmx6XFDcShszCf35wjl6sRjbPRfC0dez7pSD52M2Xz+0nX9ZPTDK60xq64/94XP1++wWhI7C+nId0+XO803xeA8XY+mlJbT0VU+hsQcP7S4iabm917LBC4xy3dx/Qf3kNgWVOO+4jL0HWMufFCPBnKjipUYJ7VXwWgO4Qz2e43pT1M2zzOdq7gp7rb3r9C3VVXFP2YVTDnh0A5rv3GNFfgd/gCUgd9v3WvTpe4ZBdRtnKb7emo4eMlImZj+EaB8ByOFapv+WIzXmw8bFd4sukEhzD4ffynbfbE+/i+L2ml5BAS0aDg1aYfYql4KDw8iYIGYj6jihZ6Q62A8YXrcMy/GzenpWt7Fi3FafecdlWH7CSDcBpMR6xScO3i514kK6QxopTsvRf9mZun4JYH+H35H3qQ9XHjGgdYueT34+wZsc94QHQ3BcnCwbTGei1J/XOIxBX4ggElU/lVeGq3PX5m/iZPE787nNhvwEC9RnOac74LOWHOdKLYqhrCb3fR3UbBnlTCF4D+Jgd7ZJVvD94JS0QnP/xJk2xDhcDH9EBbL626/++w+m/fkFvZit7/N93EAFWZzHSeF7PqfESx5UcHFDBodxjaTwcGnx18F+lpdDTNux5GfFF93nvIEdRZIxYHv9tZ5lGzYbzfYx7xDJ2LVeYAIk8bvx03WI5WGRSdt7Esn8m75NLTUwVAiSePrByWJgbT+AKoV419RRJBPrLF9CHz5hQfPvwCc9/eYP7F8/x8PlLvGnw7gxzXf6ySUVvAx5+egtR2cN02BLv837deAKN/ywmVCfClhDoqmhwZJwDgDwdGhX9E8CKCxYxzyVpApnACIWJGdDFJd3uho1FFpyXM+6WE+7uzlik49Q6XrRnWMYC3AnulyUYWEuDP7C+37BtK8Yc0DmwdgPB8/mMdn+P890J59bQYZ6t2g3Al9Nihvt7MyrPMbB5RCYRkEjDepqYfWD7tmGe7Pfz2xPG/67YMGweVI6KreOg4r/sVaRaZIRgbG05HM5NGP2ZDtYWYWDnoCGySYu6gskilhjtMubA6XwOY1x3Rl7oMKx62Etx/aFa2nut0SPi69BR8LYLajae1sxTOBhWN6zRiUODkQSAe1MQTaa0cgLbxD33+fxnqL7y1VMXXFwJ1C0Mzo57qS83EQyFHJA9hVqFor/uGB83U5IroPIV6wOwvHwJBdBecH9oeNpfyaBihxrUCUKcZyRRBoDxRdFeCGgcQjNFSHdjgO26ORywnyPqMfSogSsyXOiIo66Gl6iztl1+IyOye/mnrxv4j3u+B5zSPOsyLqBgLhBPUShxz541GO5NMAYjFB0Heppl9jmnOWaoKHoTnJaO8/kO5/MdRJorUtTSFek3a12snt7pdMLdyRjM8+lk0cBeJ3FhNgJnWBh5RaUIhde5AViA7pGrNCKoaKQxH84sKVgP0/Anjb22ohq6B9KHSTxQ1ks8Aj3TB6fwYqTS+l1ah4oZSrW5MtZx8rIsuDxe0NYL1m0DtmFG3jkhY/O6oz6/aYZaGvq7q0YttXiDzgGqS2ebNj+lQVnR0ez+tOgxU92NcIDLvd3Tmz3XPCHuXAApCp+CcQWmhJFu8NFbs6wjbgCcQ4E23AwJLA4DVKT3xcqKRMrX0FcxIsP6DGPPUK85i1ByIeaCgDNRhKBDcZeG8G2YoKOeWtvSUPMc0LGkHjHH/2LKXDo7qWcXANIzFUCkwq7RA1PdKadZ2nhTPspOiTlKHBYAmO6OEzWYG5tim5sb9Kmw97hG9drkXjewCWO6stKhgtEE7jRFxbzfW3o3w3zvQD9BuuPBaYYkHQNj29yADsd34woFQREGGQpEoVRx+jw9qj1qUAnXzeZkmVFyDRl9GHVT3fqa6UDzbItHBlqkfc+zLIClUk4hiPOfhCcqgBLIEOKlI/ewT5OGc94uX4S6XHxHqVj1B+iYEkr9AnvoNvc2gdksypApMM3gYvQ40sQH3DsO98wcnJRiBHw2JhRwQQyqobQyBahFp/Zuz1tErxT8kBfV+akMdAMn53o4E+FkwL5B1JI4SAQ43Z1w+cbaoprnHAjDfmvdFLhjwbZtaXQrfdKwr85jVsxlbV5HqvuL+c2EowNwF0rsKKoaQikeSSi1CDd+jhuCJtDQvXOW5ZjV8BhT5Y655Xi77ZFFj6XDW+ADd5jty2LRDZ3pvsUVwuYMs40R0cRzznBkaN1gSPazLbN3hehmjl/1p4BJn1PCG5ONAlHGqGksmBmOBTUFvymXE8bpELP7vaS9NUe8Bc2zLQ0RyFixdWu3t1S+d5Z7CAtb7B4EzJxkRnKdNJKzXjiCjzYjEjGr4xEB2mwYurkBXtxJyvoykqPeEzIrlWtLRyhrJDIlWLYezxQWGRG8LrM7YW3DaKTx6d2dbw37b9uGbdtAdMTU5jo0cC0NA2MMXNZ0FBao48y9EcZwbS8yrkfzgzKtO9h2GvOJrwknNv6xbYbzupV5WpYTaGZq0nA6dZxO97i7O1va9ruTp4kl70rw8yjhsYVxY5asQITNMEU2AQaNywK4AUOhvifEHQodzfhieFRmWBMkMrRZzW7HK0L8bqNrTdFmgxJXTc1a99qBuRUU5M6TwnJITq8xgen00WX71owvUNdMJE7TPLpBqwMjhljDtYvgknIv9j8VEbavQUutbJY58DvPKt1LNzU3oJ+x9BP64tE60lyXYmfL4NVk/jGGGc7Xze9b9hCRBa0D87K6JrBjYgBjA+AOdw7jNCKj9YKDG5bTYufGldgGntSpOE3wBRuFMAznZSYJgphUZaxyZnsrq777m18moO7iQPkiwEMKO+48L3FRadCGQPrmO1IUTyHTAaYD0eDwk6/3/Y9yQAqEnCU8te7cMwtcBB63cVlmIM37IJ2ahS8PForTQs3CpQnwyXeFQO1SH5cmSKmYw07wXYVvRz5I2mXwSqfFdDQAHDZUMZeZuN7HS35oJ2cIz4JG3zsenaJT3fvdONWCClw/wUCF+gajFYWp0+tvrQe8qCbPWseZDo3pGEuHMfJzpKtTLaPTpOdH9GPO5ks3I/o2JtCps2mQZrDcwDn4XroDhajrJGMjnP8rvNksPFNZKsNpqHtoK0BDRcCEOB+lltUKqAbs4qDLphtZDUn8D0R2nh1TaoME+dXYX79MBrU5TA+OGngOxZcY9MQXCF5ZlhVo7KtyTwjj5FOLHBuFzSgXOD+CDzGCMOhvKMMrY1Te9x8qJFWjTaUTe354f+4eBe6sv78aBO0tj/DrfA8uv6m6PKfJG3k/NUGQgI4G7sDsZ5HvKj7BpBnjrS2Nf74teJX6mXLV9OhfBSWi3D5XY7oA2HxrPout2osAC+4NOT0thnPOOtexZtzat5B9KYAXmqe8wvuRBitoBHui1ePm3Xjue08cx/bdp67gJIkU+YP9c3Vm9b5eP9Zm0Kpb462vPgHGcT3l+is3vqsWEulXK3BL+iJwuwgSs2dJHbvfwwHa23d+afpZpKxO0TIyDBYZtsr2gKJJmkDNmb86gfl89LCeV4sWAzo+sYeOA0gFfJazsMc3e/wS6xv89nV7hlttLNJ3WhSn1U7PrkZ6nErqJ67PF3ksyZt1zi4jVCzyVLAAH5J8EszoByBSrleYIwV/8P3+SFpY5+jPbkdSqF7/vAQyTFVc/vn7Hm6h+CYTbWxo/YTn//0rvvzPO9y9fY2vHz5GH3VtqBPpnbJ0gR3Kt/sXgLLOxlOU8pdXS2aLwapG8PmT4aVGv8w2edjDfQl+MF432aAM8Bonfv/78t1ff3SV1eSAhPcPk/ijTX+/00LAZzLRhhw8qsSf8oACN3xpEV7s/bvlBAD4tpmibXv4jPPrVxjjEy6fFF8/fkKkCodGjeSYc4xKdve/iXnatYItBC9xfmNpxNYPI2ai+IyGl5juo1bb5TWguHx6gMFbiaKXyuLySEmOR1Jw4GWKb7tXU76MLwOn192NpW4gg6QiHwbwViPQDQDoaJqpH7UBj24AWXkoYEA6x8S4X7G+Wy3CWyew2bOX94+Qe0G7c+b8mSl6lsVAtC2uxPlke91eNiwQqxUFYPtgtaBOvWGKoL9smP8c2JYN/atYOwoMXcMbb1HFNxe+Bd2UjGNLIkJgVre/hEeNYnll4xvYMEWhnwVy0p0RtgEY62Y1S+7v8O3zt2B4H79+wfl0h+V0Ar2KKCzw4i4ApmSqxIpRJsfLnCMcEnbp+mDKs9bcwOJw9eBGC0OF0a/9/QboCaHgA5UeFlk258Dp9UtTBjl2GlMxPj6gv3oeyhrx+kNhMIeEEMBk8sSysypH/Ts/bx9T8Nl83PpZIS8lRqjYO7oEnihrWv/CmQ6mO8nnv2J8Ng/nSgCWl89d/lUoHneetPaejaOXc3XsuZ5HEwqyheM5TQg4jlvKKh1+i/uVo0/TcX06CehtDB2MS4yR4tbhkvoMGQIqBZw5adjDrLgxS8Qjz7uVflhOePbszvDJ9FrJHilrtUrNYLAs3XInuwH1tCxeQqKDtTGtH7f2CDz17jWBMkeOjAUPmdwJfp6pegYlvcDj9p4OVOM598ACPXL3qkxtyiTbGVW1WtMNpthrHXLOcYkbAVbZMJsAY0OTJSFpA1RcEQFz0FGY0B5KRk/zBFh0Xe67MxizMp6kNM2Ujr429BJNH0TDERTa7bGEt06A2jHpqTxmJLIF9vmaeZpWirVWE9OihntveHZ/j/v7+zCuULFM5b7VIx9u6FljXvW/IajWTfEaojxOFFZU1I3WrkRS21M6YUBg68JlCFiwuYeBqXXMyQwBCT/J1Gm8mzBlhr/uKeShpjM3BayWOQnocVmdWAz/AksTjNmwKUV5wfQ0peJSoEUoOHaQseNziOnCIxeuMJOOLgsWP4ud+VUpZEzbC3ofl2kG7CW0FZ5Srx5Feq34HjXivYz2nUDQJ4MrNzqiGf7g68Gv2Bgm4LWPmzkhRK3xpFB57BOvmlBBfLvHswygzUnMeP0g51oEumuu9ujFsjwRn7GtI5/HSLVUsEsYwayPck41YWyHpJ3RZCSnRmRjc+WwGzR9nLPArTmKmOFt27bAkzQq2fTVR2oGfRoFrlOrchzVvRSxV3befMVVsV1qUs4atW5trJcVuiiWxWiQNHXeGnEue9+MjrkgOMbAuq7mTFAA95rG3/rGZ2/TWTsfSUdUk6PPJyQy4MAN3gI64rBOsNFAKq7NuObOma2742qOISJ5fVw0gPNqXmNY1XCpqGLSiUHNyDGnhsOSjbjg9gnbzybHXUulwcwzYIPwdlxBjzibCmpyyY8Gu0w6rdk+FfuxvBGG5ZjggGP3n228VobA02wLIDLQRDzri0bZJspltjcJa9K6OyZYRPUYGzAtJTwzj0QqeeUuo/DLE/Q4VDeCj2ER4NIbdBtgOnOjBe70M5vTzRbTosyQGchkxyQn5fD/VOWj87yzPG9jKhDtjgRNDR7CkH6LRyU9EoFMp70yAz8afRj5DA1ydHIK47nvlTQsS6YNVh1OWyfaHBhDIG3zc2HnuLWGx6/TIppPC3ZOEMzF05tFgswOzIGmDWM0yBwYmxmdtwFgzJBVGuAZu3ytfU8JfxGppUqdUKxJY8kt4lR/b280yvWf07POIA1/zbOuCBTimZ14uGikjX4Ad67ZOEpXVok7BeyTewYvC6c9c5q87Q6rMtSMYuRvydsWAia1rSDXzje0pE90VjaHcHNcvYLfaNNqNgeUeehgOB9OX8euV8deCg9bNbM3MbXTXxVBP99huzxCVNBPJ+iY6G2BZcezUh9wB/IxMssElYzDFeWTLLNIjLc6+wIFZqjgJV+pBl1HJ/QcPGlKnlNyMJkNy+fk+8W6n+S+xO0QZTSlHwWYBRASzlXmoFQjpPPIz+AXOBZJPq7gk5qqPg0BSt8c+6c5HpJGqALLGTouZRbmfMQ3GfnXvIOgtiQzUJcH/JwQKc8B0GGzn4HHr/GeAu4sZo4dqu7A1HrhHxEZnDgJyYH7WTlCXpHOue8OB00Em0cnUuYx3sv4s1b0SRUw6Lh+/I2GGFvzAmsxFDq85H5wYwPPOc6PgA+dGNotq0JfcHe3YAyuJUl3Q18asN44dcqVKXASM8EON8Z3JzuRMc3/y5UMTJHHndBu+LuZ4wfL+BisPcW7/cSl2BmNG16gvbKMHfPTQ2jkbFxfYm6derEPE/rKeD3qbw+L4PMpeCz4p8SVfNwhJs710H1zx887RuFPXIZb/LRLgSdwXQTyVtHa6x19U1VsXutcOG65IaKgtKnA9ttH9F9fYf7+CfLLa8vUBGD59Q22dwOqn2LPqQ/m3/5rC/pcZ/7lMG4azmlIf1ZoRtBuT8v+WWgktxZeaBrFbqWGj7X5zm9Pzv87z/3ssz/q62d//3mIeWpE17hwf//2ewy4+tMT/ZPXtUHY+VbXgdDR/+5kWVT1crFIXR/nqfeQoevQJ8xh6u50wlTFWRbonPi2WQGA4bqf3gVjTCyteQktw8/kF7ZhdqdnpxMUzIqUGl0LqMjekxMg/pjxSx1jmEZurHdSt8N26PVzx9sFqx++Jx7Ptu0ABgosv/0UHOpPPPfkA6SDf/xKPsauBwFeF/wAeNaIwxDeKPAhjoPiwX98KA+91FwDcyoynnr95+/Y4JlLYSWUV1+Ay7sPkP96CwC4/8dbp6P7vhWKrwUf1mAGjqc+v1NuSf3daHcErv3sopVx/NsPeblu1kA/Duenh3fAaSTbf4HtuHH9qEU5fP5jvSuAMT5BFTi9EKxf94c4We0f9X19RYSUA0+L9l74dzOi32pFFMXsiWB+6+x2Hlt8JjnfHYK6hdRCMC7pn8jckHvpaOjolhJPKLR75GdvWMTSoK6hLLVouzEV25y4fNywnS/YPpqCRNaGx49f8eK/X2CsA3OZkV609W5p92AGdOkdMt3LvzfMVnZmIQvvLNEXYOkd51PHZek4n05mgJsDDRMdgk3pJZ27p6IJNVy+7uedkWqg0tU2xlTsZoTo0lx2F2Q0jEaKi2rAPN3dYVsvMGHEI941DaZRr/KwUbHzEQYGi87vdSYFOEjRGa0jibSL2Hbz5Ex6s3lD9Nc2gb27sGUNUSGopX142jUqsBmdFBERh34tNbH3LoL5qZJMLYjcBNf28hUEwPrANPSHU8i9KNRR919jPcigV5mTcFAv/aJQebzGLHV/nkAFdUukbJMc7kVD5fs89lHai++Hsf9p0kKh/ieZ++OwDW7SYYLOFMf3mmfEWE5W2/C0LDifT3j+7DmWZTGl87bh8XJx5T+V7c2jU/y9kxkOzIje3KutjCgMkBp4UQjPdjRi0UIpI7kFOwNb4D3/S6VrMAaBSU3pt+sfqfwCdvY/AFEH1AwLFhU+RqZdFS2Rk2uJCmMX4pUWGX03h9frlog2YxSqRWIPKGgE4Zwtct4ykntteDG8q+LpIyeTJ5Ul3sFBrpV12hLRQgJn8DLP8OFvSSjeWkucxuwfIqwNmyn/nz1/jtevXoEmgDkt1e66rmb42qxGKy4Xj0RSULubxqo9ICuO93PMYaQWj3+aM6L8WfdVCiLIyGUJA0DUcG1i0etsOYzdfA/xmUbz7lHUFkGskTFhuEFzd3QJ3EqYdQeooUGjTKEKAAPTDa1SlLnWjKvIgiABigFMlnew7CvMAEHjOR+PSL7hKdznqEt686q/VT6s0q3cJWYAsFTrAGt7lfV047k0M56Hwt5fT6ORURPVqrx0CuQOg0QMaQQoZ18SZGIeDWAmBEuEQ4JEhWN9h4K474umglJ2HUjA8RGGBdNKgngqeouCLOshNt/Ebf43lPecMwJGDHdZuZ5t0JEuI32zVqkmHkO2D8m04AKxshe7DaCRQcOg8P3L1lyDb+CwC9+g2T+zQKRjmDuIihmY58ysFtu2mIEK5iBzuaweTVvGJPuvV9cfJMAKpOGg3KvCNICAv6wDbTR0iRTHHUtfoBMRPdy6WPBimbvhkRb0gtHF8UzP1MRjWCYR0SwBZcZfi1ndGf248BOYfVoKzZBZPI9I0MsC07EAZQEdPqXsNWF4TmfLF6agtbNg0WwTCcaEX3PQogFJC5xXpJn025xvG9QzW3SMtobCuffMVhFRwKWd5iWsxhjoY2AVhW6eBQB0Yht+zsq8nRkcWCxixBUf5ohsMGnpcwCRia4Nig7tQPcqIbZmLfETSzsJDSVkfDT4kHBfDcZXgl85RsgCKcsSntifAphzC9yxu8qe8PxIM76FGcvmHIk7mpeFcziEWAYs8gY2lxY4oDXFthmtsbI2CmkWgbxJg8gK8bPDmpGtL+hdAXSv1axW/sLlBOmKLpYwX7FBYLwZK0MwilAcS4fYB0bCceIGo7XuLFMLB96lMkqTxiWDD+QZACqutbYaWlOAZ9TPVfQVRtNCNwQeee1OUkGs7LmMRIXLcmxLI+24zVUM7rT70aYzyLUkUp0JeX56ocekQ4aXM8sG8R1lT+L/6ZHoXKyEO3MmUAX6cooSDRUkJzPZAZnpw8+wZhcODEHsoQCW053TKWvfWCi1Ug4+96E0bsLKRAw6dqrDF53IEe9U/M8RMeaZTteVNztgTOzePix/8k0Jg0FHvWFG2fI3CQt60RYEOKsZy52ONs8kYKBHhllDmZ9lJbwveGYNkH9yOd9/j7TkyEjpPb70/ebZcYZTZIHqBoifzRwyAGbTCo7N+b08S7YNM5Yv2DUF9NsFm1yy1AnpFDknP19NuskbXoXdBwAAIABJREFUrQNj2LLxTCm8LAIcRhMf1v13RBB7O7UmBqIj2jUEXBszKrOyV3gnLCUvFU7PN/mbHUKKz9QH7n83YGruGD7GrOAYGa4ge4cvW5bk1Z5itG7xfnTaYEcO3UnWbjQlYrivQYBwSnK5F2Ucf5Cnu+oHgLwy4jIfHnaRhk+zkyFxBrTmL+VyRpH8uDB4oBnul7cvMd8/RD9xlnfch+y+7UeR+1qfr0/cmktxm9o90xTobwQiL2PMuWmK8dvHSMOd89/rsq8uf368+4T2yys79zxa6utQ3ufnKx+k20uwu44p3A8t3OjF/n4WM26l8fx2Q1VX9P1L8OBt7u8K5Jc3wO8fdvd/Ymoxqp999v/e9RReePq3f90oNMSI4B1BPtnKX9BJ7rJtodOdN4Ct3qHubsKcsvi5iZU0mqrYxvCSXtS72nXcQ9Ll6xCsn5/nT79Tzu7PNPxndqsad1vZ88RvP9mus8R/7tKfQxg/ef1ofY/n/OfasW/bP1esULCYJCDov7zG+P1DZKb4+u49JoCTemp497D4IpaJ4/t4769fx4wPV5fzolcr9aNxHX7/qzt204D+//ZFpn8/dWOOBevYpwFNwpmHql6Xse1ubqr4+AC8AHD34hmaWJ1jpkU4HrA7AI83RimwVDWLc2wCYOABC96gLx0bBpbXHdvHTwA8HTUEghfOIHzetQXZMzVEvA2peJV4OOW8lePk+MUZZc1nFKZAsLTWjlQZLuoMf5OGttgLFu1iBu2+dPTFBKalNTx2eCRAi4iXqMtrYXKYnyyyErBa4/3VEsSmvQTauQETWBogv7gQ/W1Be91weW/Ki7a0YKjmVLRfzSBw+bia0utNw7ycsP624Xw6Q4dazfHtGyb/ZyHnAO5CeBFljV4/ozQACNy4nQphsp2MJiQ5cpEBTJsIAOu3rxCIp7I3YfPLw0dvX0zRIxvOcofHbcX96WxKnN4xx/Qovtxkoo6+ZD3wnVFqR4ycmM5pGRqeCfSLr50TWp6RhnvbF4/kHp82yAtXbHtNHzLxClMKmPeQzQFzoL2wKO0QEj0CXefE+mGgvzQlT2vdFK8RYeHpgimIqqVw7xCrDaPJ2qcH8cT2kAnoycD4ErhiZc++kkhU9FsjyY/3ee/84jkun7/ume/65QYDQOYd5bH6tz5osd2SbZcnc3x7CpDqjEzFWfs6epkr2xAQGdh92a9TfTo+lUHP1XpeHLGQ0RfnQlx3HjipGmlU4YqWbvXKz2c8f/4cfbG0z6xtSZzAdWYaRlOsqRkdI2OB7hRyOZH9vNJjjUo2E5Tn0FR2skUPDVE5KJp28pC1FcqHlrgNMOVcr6H3RzpE4S4lzd0ehzeqeNYPFTeISfzOlE0j6sI2bE6wqKgMo+FUVG8BGs85J1E3VCvi/RhTg0VfwrOgzL0YnQGU5bSJwKT3WQRBwR6OxWt8m4ekRdZL0CA6KnCdLQPKEtHnfamKV/5b0Foao7exN2iXroMexsZIuY+yMb5ioYCkwG+hymbMaU5Pi1KHkVMxfpFIp8to3jQcenSY1qR03AuE4n/pZiBrzRy2xtBILWupeDNzR6ajE0+16Aamko7WzpoZWC3SkTAvmUyAqPXAaJijg82ndzOuLl5KgZHGZrgcGGPDGANjWrrnIz7bbcyTl0bf6a0tEWXbIuLuuH5uXGfEZmulLm/iaZPBrJZ8jTxnGtfd0ccex8avjjA1BFW/XxRcdVz5jje8z41Y2nfHlUBHpN7JlyRNsDXBNNrc2rQ0kIFXb61PzqUasQNXhgHFDFVjlLGgOrxUJKlFoUf63q77t9AfQCeaBe6V8ThcfkebZO2nYjjPHwB3CrLU8l5L2lMys/6cObJUGMlzDgFaY330GNFujnUc+bmu7/63H10StMdxjfSIkhmY6Oi2/R4typID3Q3phhcXVEcGbeqZjhAGqd4axgQXPGiuqpdvosFCBOpRqXtyZnPqvZlhmWm/aDiKMhfitjTroWY82YGCn5lQFtMgwjUvNNLWZmJu+/Wv/8w5y4ydjbiY94BdOFrsbUtjEs9b0I/W0Rilr3avdSllWXykauvUlx7jCv5iwuo0ezaYej44MYFibqs5NPWTtbk9AhrUAsF7qMMLBHPJlMs1kQPJuqrTCwGa43/Lxp+ZaZhukvjFxOpy9o7o9RZc75hfrsnxTPs8xkzDUjR3cDojDXaavl4u4XAIwNMK+364w64AkfKdJclIQ0XEHbMXADbfNjYMSacBwp30Zmm2p0UCbU67aNCz9MUKwUQWkLTyP71J4E4RczQ2oxsCt1pWOT9n0OII6x8YtQprq3VzXLLsET2ySkT2iFZ4J55JCPrJeGsaklmLcPEsE3Os1qPOXaaKis/pIFjvkm+M2sBNiuOX7EFHUBzZyBMZT8OzAocTKznQLYrXeVjpLT2KWp5RVTvR03HOVHGcBaCbfmDQUOlZguY2IGWG8P0gX9bcEM7IailG/G29WAYt9dJoboivPAWjrdNplZ8BM+ySN5qxXz6bnUwAkE9NmhQ6ChT+FQjYYUuA1O3bX7v72eH0sgDprFRwm9R2DWZZ77x1K73EcjfMKBdzJPNBGNcjjBWcVhw8IgvkTEco0iSe0zRAK7CtmNIDp+/WM/YmcWbh3KLeaQyV/BZpybdLnNnpjokGMw1Y3PiM1A9JE7DGfdAXjsnXMB03XMOy4xsE0heoiEe025hbM7y8MQvQLgyQ++SEq6QC3hmkQ+6XgPtrHhAF/8QPO4ixPfOsHb6PxNncS4ViaZYhrS8dOgRTPZuKn0ehI7E79kqXyB7B8VTicxCri4zHhU4e8DbntedCG2XjLoGLxdPJV16HdHQf/e7wuxMk7EFGeC4vX6CBDqgDq4+2cvH8zNcbXhiklL1qy8n7Ue8y3U8gMPpUZBWmhm6tA2+B7b2VsMw1zbHe+Bgn889eB1QWh0sm0MSN3L5JqsD624cQbRgtz3ZaaU3LvuZ5Mj9lj3cCFHj8n9/8jVcY+ORrnWW/FrzGwKcY75fffg9R7DYV/P5Fw7hKOgUeV3FvJLpaofxFk5X6jvize5utbVBsv78HIFf79zPzeOqdvwILf+261fORGSUZ+Nnd+utXZHbTAo8St2JU5G82z6qpCpxPC9b14Gxa8IoIcH9/B4FYVDlgpRutScuGRT64CWSafKfDA9YoTanpXUlzbLATQ3kOJIIm4gqg41iYDaumfkeWldCfgw3bmafcdH7mug2J84k9/6kxKQMM/tz1B0T7m32zgZeKcEGrdondrLyvVwp8+g6I13bGb79j+a9fseFDwWNum/z9IxgD7juNRWEO307/JwA0wRcAz1TwNVhvDWDnPCb5MR88cS3PZPBaHIdW7u8w2aLPv7J/BErVnaz777r+Aw3of/QKsvrUz7uLiR/vXj7H+PQZ2hk5fGS1SMy/fx0jRx4/fMD96zcAgPkxSaiZZhUTn0EwqSiiqiXrJTcAi97bx0vKf3fP+u3KbxOQacgQEY86t8i31iwKndF0i9fVWzx6JzzF3X1wqiuLPEJpQs1wSubAhSR6xYTSw9vpywJ8haeKg6VvdgbKIlM3rDpiTpbScESU6jxNrNsKWQVtsu4ba3N/A/DcJ63RroCp7gAazvurhvkwgqiYQuwrgBcQ97SVujEA1u1igrwYoRmfJjZMnF51QxwCNO9wHSuaNKzbhvvznc+9g8VTql1gzkSD+z0m1CfEhOemmsFfXyi2B3UZuJ6QPRaa+IamzwI29n6nsj9d3vaEYv04IJg4v1lCEAlDnT3qhhRjIsxrPXBhtG8Kd2MK9MByRjqsF4LxWQGPSv8e3ySgAvrpq56xegYvn7+EoBnPFqb2ZpdPIPTj+QaS2B1f+7tpQsLGrd/s2gk6UiEpUyx+b2CRSq4q8qqhSSyy5HQ+4Xx3xunuhKUtHh1s/U61SNWxDYzVos/HmCZce+3aGq0LV7hJyxIB16eDiM7PuSs+m9ltzHjsCn6Do70ERR1NdOmwlkaww8IoMDH9fMuhISmy97UAVZNnRvpKb2MM24epE5gTc25ufBKoR6HvIJWKkQ7L4gFk2t16YMSE2pi6cqUMX5K5sr2VTIu7W+Mji9RiraTV9SFMNExsmDMjU4nrmkf2cd7myOXKVhrQ/R/gzkytFYbOjMm9N2y3aKL381R0wV4hU4QEL8pjigtTnjaPdrO0v7f6Yn80ekgqkJulUaYBvBoZjM6o092c77IsViplnZjOuTBV/SgMuSmqrTUrrTrceKihVOZ+hUPVUD9HzUG67ujtdeytZU165wFsBqUvT2M8tuEKMs/QsAfBch3PhQaN4L7RAS2N5wil5k45JKyda8+bEt/apvJ1h3enRm1LyzTjRoECR01yVZ68JOFHfK2GR51GO4D1FbB4C8GS52gu6MnhN3Ynu9vmlNagzbP20Jij5HO0RNTvWw3nCo9yUp2e3txqz+9huohlkpzv9OjLMBK2a9E5nJ6E3C6N6HQu+R7BMYMJ+zC8ku2GscENuXNaBOtsG7TZuqBb9h+mprdoVIQRAMDNuojs//ZdX9Oo1bqPlLrdTsKKUqoM5YQ5dagzjTS0MQoUfl5b62hLx+l0NnyxLNjW1ZTvPtQmlkWJBnSMYRhESHc0/0e2zQVlZtrwlS/0g+lPYfyaw/fUiTkZoa3+/z1tqpfEvzTmG2DaGZVizL0VfWYGTSNi0z+rGxCNFrthxfumAdm+uvFU7ayb06zmFP0dwkLwNWQbYDSOqVQpDxl9cGONpuObulMR97Q5v9t8HMy4Y6naEXAcxqgi6w3H80zMVXlp34iQtcQNIsPxGw3oY4zgiaD7s2t4cg+xO963yic0njRGzs8dbxR42TZh57wdbbtxNPFL4rbJuYzM9jLGcCN65Zsk/vbuxs/Ci5I/sEwGHVMm6KQUQqDTCKNxim2wHIW4vOPwPGcomcSZK0HztJhuoHd82jyziYoav8XlkHIyHDdfnRfvL+V8gdX7dEO89uSXuti+N/JUuR4afBWdoMg1HiOTuae7AYB8b6WANB0abgqpc/euOM4xfkbCmL54CSbCRxjQXd9gTvsNoDMo8QtpC+zWdCf4dloAL1nBLBlRosLPbGsdY6qVYxsHkwYbfAJnn853lgq70HVhCbVJxyGNlN1R7oSfJ3A8UFo+7KlBgYEiOwTvGvuQcJucUwBXbpQ3qkDyNDFN+9EcQng/3KELLBD3G81mZqzel0jJCTVHIeMhyHvksTL+aoKOb3Q4pAxia+k8OssuWb2kw1rt4dRwyUAYPV3nZNOhS2Ma0HIuuW5a22bz31gWhM52WujhtLJAHDd3RPZR6bO0jagTShjejwHgXDTr0CsAd/AaNO7yjNHqSD4q+KriCIkKdrrDCYkjSHX9PRGjGTfWKOam5PsQ7Sllcu54pPczfLxNYgz/TWmgsf1QOgzE9ux2BzUiOhe+Iqt6/7A1V7TM597ckKSKNufOueEKHfxBqwnl25kT2p1zft+xG69cB1uDaArfEyYP6hNmOr5auUZJvkYAkVcQfPTsB9fj38MHp/kEnvrOdXzmuCvVjV+EwRD2RP/lFcb7T7D8eNjhs6zEY/Ql3c+dFhBNiVgU+ttX0ed0I/kxwlF+Ecjvt6Dl77hur9bt1O1HQut3/xiY3byOIP83NPn//PVHHJb/Yk/x3z2GynEoMgCIvABgxvDpOhgR1+uX893QsG0eKKSJg6XsKG2Y1Lue+wmn+wXb5y8Z3S7ivtZuNJ215FpeV6jxCR7olmXtr6z237VXt9r5+Zb/3Mn/y2P/Cfxa79GG8SCF9/le875b2z83bLjGfysUZ8eqs/A79fosibNvRaA/ue7BmlWm84dD9qvQ7SMMlv70D7f791z/kQb0NAAVE0FQviMJpBJX4r/2q+zf9+vifz8/WASuOJJh3XHqAOo+nct7IW/DotPPb99g+/AhALbhRUReOVsc7DxTSikMX3W8xJSMRD8eoHovamN5//R43HvDApCGUOw1AXpPoVdMSdrU6olNKLoKTieLEGctdNbSbp6m9dQapJ3R28lrJkr2Kzy8dnzauePUztguj2FsuLu7w9IXPPv1PnZrfvaVdMIw2oAo0F+bUDAfrMX2SqGYWLcN69iw3a0YHyf62rBuw4UOgbYvkPbNFKQCY4ypFZMJfbDdmDAmrL+2+ala3VcVYDmdIGPDyt2UhuXVgvVTEfZk9wHr6nW4XJA2z3fbte3hE1SeA9LQMV2Z0NHEjOvbtqIvSyiXd7jBlTPqNVpDQHV4CuO2M9JQN7ZJ1gnsDn9Dk41uL1wIeniGTe0MbJ8+Y3n5zBh/KmMAryNsdfyG11KeoGBgYzAlmEK1XUU7AsD6cTPYfzndWcXPZDOFmO0dp1zgCADwDPPTdKeTsjQ7DsDWIRnsHzOR1enliE2eImzskunInnpfyrP79nxNr3q4TRHk6nMlJk/qfG40VEeWlxZlWyVM5uLipn6BKYqPsAn+nHgCmtExzY1Xy7Lg/v4Z7u/v0JtHenSrC/b5q9eyZx3rbWCqeW1SYa1LZq4AcY3XpxMaLXYjo/HN4dMN8eJ1gSxqhlkW/L02vA+DuN4sCgBC2Dbcako576ZEAjAKzb4WRQqF5ytJ1dMuu+JPUQTMA/CkYtkUkto71NMETjfERi1GAXR6Wm5lm/6TKzDnnNhYd5Tr6Qx5nFnudWR2KEK8KliyNcWJOl8pa18VHfMwn1vA6/35mmsCJKDAum4QuaB1T0sste4xUkGl+1TDgEVPR2pI3j2Mg8r7St9NrtBQMNWDEm+WF4ijoxZRnwwMccV39sWJKXPEEsoj9XuzjARoaB1oalGRAiuXwjq5pljNaHRLG+zR4B6FvosuoWEgFNtp4G/hnNLK+ojRL57pSC2fUXfTM0eMsVmUI+ujAtjVk1ZbpCscSyU/11YkdcFuzCKesVIFzs8cjDQ5NzOcC5mL0n1y+3ukRqOLxNyPgzxg+uADDrOhslIJP3sjRjWO7t+L4XsEseFAUcI229i/SyOEaEPThqUDY0pGK6nzjqGdzf6yLKlHa4cCvHmWA4050GmCEaH8xzrXdJ7MlOipkBenFVDEWoDR5mK4WBmxfgM11L3IKPQ0nO93yfgwG9PAKhcoJtrm0aQ+VmZKsHmb8mJd17ImDi2SSWCvIs9l/2xVTD95OUhGXVRBZg2RhCgadXVMTFgq/CkDo1nK2NYEoxtdI31j1gkFsCxLRKVBLf3f8H+1BjqANIYQTlAcFGDOGYsrP3Va1Lo2O9dzzKgHy7TqUvCmBE3gRpaMSNG3R97F2dJddOx+3dPob+nlR6aBVUB6oRuH9+nU1FrzrLN0VvD1dpxRErTEsBkJpaoYm+X9amIRIwNMjb9ijBVzbhjbGmnK8/wCU9RwU5xLkhAJQG8wOYI0zbfQ96PQujlt3fw9ZsJpUx2cKu4zfmGqQodaxEFmTi7GC55POI6wJ5LCHK90NKA8Ek7JxFVBm7kXTreMtLgjFvGJO0iM5O+ajHDYmjLD4U5EcD6fPDV4x/l8xrKcsCwnnPx+rIJqGLpF1BzyCm4OfszXdI4Z2dXmnJgbndbMoTH4VLijlJrT91TKYbbmy2nxxWOELsmV7+u0lP3Suu8BZU8DjMj4IRbZuW1M6++ZFppAt+H8agMzQbQmEO3Zl6+rtJYqFMWeN6B8WXid1C5wTCQc5YQQjkWiZBP3hKV44n6rBnR7t7eePEnwpYm78qxPK2HTbN5jNf5qbl42xrOOKIDt8THk1yqPtt5z3L7vcOPT0k8hXzQxvUnvS5wFaQ0yGXFta1T5Tyij49nndNqCcnqeog/kVUINid3jhW+S2qJgd19B0EqmSxkIsZNF8nyxrJxlV3LOm0K5OC8lYjjFI42ZzWTPThkdb9BwVFZax0DemtH5OTcjgV4mxGmIOq8IAVTKuFv3zBleFoOOlGyywHPel+gjlpX7xnTzAPTbo59Pb4H8YPOSIL1Dt20vOwOe6Umh2wyHZ66tkT9rkZBwFAkD3p3fphwyxoCOEYYYR6q+Zlz74vhQ5lxhLnnbIn8VWIv558wDn19ftS/ZOSxJb8EXrdtqmcRa6q4o7yJ42v3ZCViq3YUxaf/bnufK70y5z3s8/2bkRzghWsmyWqKITlu3aNyPL/I0Us5EZU65J+S8Fk24nZ8U/Y29307nOBoTyZvNdUQfaJJOglGmDO70WuC/8Mf7KPT8+KPU0nV+Fa543mhoec6xaX3K4qvk3ScLaFFF+/UVxm9Wn3wKMK74d4RoZjyS6agJq7P8Fufp3Yeb0Yni2IbRt8uvb3F59x6qwP0/fsHX336/Odcd/v2XXNc9VLB5ikIAgLn/FTyGAns33v0JieRqZH/XtZ/hU6t6PNm33r4Bozfg9l9z7ccX4qvrwMKpFqZBfFxNNjgvi911Pl2n4u684LJtaLBMyKJqNcrVnDaP+imdGfzQvZSs3TdZbHH8Wt/h+LZhvNLQ4kCFpD17nsR/KPJrZCAqtix77I+t+9+5S3/Hnv/74OZG39BIzU78zoxzdBKqo/te5DmvD2JR6idYNgrgQ9a7B9AgsGJiwAWK+1/e4PI7nasQ6rGHJntcUekpNB29g0gb3ckyTzzhTseZyQCHU6+6c7Ij4rpFd8kCkmn4/yPQn7qumPs/8CoK8/wH3uOzVzEnetz0ij721yOAVwK0Vy8xPj0UMcGuWfxATNS2O4+ieAbBwMPu+VRC5AB2Pd9S+rMFRgLAgdHz28juPUekHkHRVEwgGSbon+Cp28lowwy+4hFJESHXTLg0wG84vTxBJtAvHdvjI7aPgM4FMoD7u2cAldLN0vHqA/belsjIuPDwbWKCSBPM1Q3o24pt23B53NDveqY3BrL93oEJDChksi6oUIcRe8taTFzfLgfPeF87q9GdZiSrHRunHqfTOYzo84vCDJAKyDewEpR56BOKrI35GRgvJ759+4rz6S5StJBB3vl+aRrKa+SicAJEcrGgRkg3NSP66eWC8TCib9WJ9qLhjJfYHh7iPSq37CgmMTb5xpTN4+GLP3PveC0VY603bDrC247jnADGpwl9aem7VQQ6Zgg2Ff6BZxB8BfDM31YAz6D4mky8lsx+N64f4YHvMch/lXn+GTbx1uc/08/f0caffZf4hHjiKGw3sdqid3d3uLu7hzSJCKht29xYQWUTjY6ZPrKV1I1R1zGwXclVEBxh6V9c+HQmFc1TNU9TBllUnz8/YBFhLuBPGZ6uUEO5osDOoylOmqbwOmCK2QrNWsaWhi9xKuBzj7VMfL43kDWvPdjR2syoEQCqpuQ1QVHcY0ZzLUgfPPW1Al6nL4mL7V96h5MU29+Cb6jAUw39Kc9uYDaPMmlBaxI/E2bSMOMD4MR368D5uW3J4WNdVyxeG1Nc8KhgEDUnixAfXvu7NU1D+dMGfaSh4spp7+mzs4/oFTSZEYXOcT595ZjTSNDQJtAip4atqSn4TZkbaQkBQN0A4AbEOmf4WW0CgMbz3tAls8tALP0ghFke3AjBlKxSnQEU25hulNzMgO5OVAhov570VSSiDXB/T7hPXsO6ewR86/v9olKOe+qG/hAAqaTjfwvDGPC4+2vrI40RPYoanX9bqejt1Z98vVVk7/PpSuFb65ERQqn04UqKDOSLNgkRgSgVghY5rmoGuBmeoIxMkTy/AqQC1YSjjJhlxg7djYs4WVrHsiSPqDrdMMt6zzDcXvgo1TSuRXvOzxgspbGw7tb+XJY9CMVgRt3weZ0C6MQcm6VWFOctHS9Mdz7h+Uiji3rKPSogK245KKmJ1uc+z80Rz9y+DJ7CWIvcl53ClXTREJuNd070acai0Zufb8EQi7gfkfbPvkvvZlgSCeM5ccNuff2sm+PKHk9yYirmnIWuFuGvAxhS+DfF2AaKTHxNQ8peBv8K3x/Jcg07Ghu0LscVRiq4QdK/V1kq2lAr5xSKeMd7ZCClRG2KZ5Gp5zhg9cY+qiLqvdr6W0adbUSlcUM1Hk2rYHRI88wcCMUEHXfg9zKGMmGR8CAe7W1OdAaDxtc0P1cNMqRE1llL4SQTjnvkUer+lP5K9pkK20zvmPB63GPSroLyPJtNVhyG43Yaz8sIiIvUzHlRfkhom8qa2b0vOC0nnE7Gay7LGcuyYDm5Y7IWjF3qEGsTADOMNwp1I62VHticTyVuo3PRHNNxquGEWBcF1k3D8Ynwnb97v84zUjPE81HhawdrFSeg0gjnhRWW/pn7GOCc8lzck6vWDf/vFLfcv9xLCAIeOdd8XoKPolMes8It/teiy7ln1nA42YnTbLSIoi+AsCtHM4Y5VkznccZmGc4iC4VqzKc610UmJb/B9VafC/mPMTc0L6NhbrbMwGJjrwY5CKBD3Z/CI7BdUb6Xo3fTMZzoaxklY4wkIIzX+UTAa8VtcRRFE38Bu5SycvUBDrd6+zdIGBArnDQBerNMUE26H0Lr28B45jqK7MZvTnLqIEN80BJ/KJ0wvbuZmQu51saDtgA7Zd/ky/1o7fYGXEuGrCRvRn6OD+pFAVwCHlNRDI9UhskfYsrogeRr+JyqAg6XqsVQXv6StgVMaO7JVIpupkMRMbrCTDH7TS1HhAi2wgX2rETSeAbGZAkFaJHPytlxcLi+DnS8NfLcAur4mBnGnKypf6RjCfcJ3LQdNrJzaTiN+sCYG2Grwm+Zc65B6q2imxwJ6HDaHCbJp9+a7o8udrMbpyOHdoCR3fPJckAAtDde0g7cr4KXyvOTa1T2l+tJONynws+/Ob4Cszeu41i/d12v/f7e8I2i5CIA8O4ThuO6Wd6rbUTfTko38VJDpQ/Ov2s+t99D7rmg4RXW399jwVvj1X6fWP7Rcf/LW3x5//6H8/wja/DvuHZrdLjkB7//Z13Xu8orYeHfPEsnH8duBXRGoVxgDpbMpDRV8fXx4s5oxvsv3TPU+juBv5lhIuhH7QWAuGMSYA5+MDmgOX0fw9K2B58CFyKSAAAgAElEQVQAD9DBNVwEGghG/Vre+rev8Q+v47r858P6EXf+lUvA4Elkhg9+//0jOtJ4z/s/Ht+Rrly/ezypciTEdtNhTG6+k32kbGlrcxPJ/3jc31e4/vD6zzCgP3E9jTqBs9eauKxUGmkhHhJ1HIdHDjKVE5lbRpQv7unfp0VxdJcPapq8YGSQ9wCrZSDScFokapGf3nZcfl/R0DDxJcBkw0Mwd/chZuwFI0Gmnq6pp3bsnZDRtM+nncHb2mxNIn2b6YokasQZ8ra04W0gUuU2schyKtMBF2ybWJ2iNoG2WYpETAjOOL04Q4ZFBzZ0bLqm4lqA05s7M3osDb3du3K9Q5jmS+hN5QKGAPrRFU2vLVL18mXDZbvg67dvWNcV6+WC9esG/eYpjkUtZe1wA3xvpb0UQRRfALkPA31rnqJULaIPMi2FVQhS9re/7hgfDwoJ7otafRJVxXxwgulpxm0B3QkByRxXd4z52WBzvFnR2128AwVEXJFNBFIVLTclc4RCes6J8XmAadPG5+rbpD5/Z8RxD6ZdC0/g4oluuGz6eL+4wPUMHR3Lmw54tgOdG6CK+1/P+PZuRX9NWbuhvzTBTVr3lHjm2GC1jr3OJxT9pWJ7+Axx4znwFRqf7dpwuGT355rZOFwK82Kd8ZSf0OOSFqEFMLxQ2z+2Xl/fqdt9P68Uwlcjk93vdUJVYKg/f4+WJG65PWK+f1UbXYHIWw7Z3aMiFI7Hau1vBSKaJQwuEYniaWYxsK5blnqAoi/NzuRmHtQRtbIsphQ9n3E+nxxPNSynBaqCue3r1XISnAf3wJTXNiVtZlhi1gQAlt53ahi1LdqWKWIbMAegYvVo+T9Pzcg9ac2iLqDXUQ5x6hyxF5sFRCSjxloaleo/e9bT8Hr0/ubvtdbRLN+tGzTszI45vO7qHiZoN5hhPEv4EPFUaTNrzu/IjjToZvhf1HI4UMFe52Rrvzc4RW9eM9qEZ7Va8jKBgaBVUy2Crmmzer7NUinulbJWg7F3EyLGmBG1TZiI9btFwJH9CZXxshfQ+SIVmN+7NASP6SmpR+6/l0WJ58p5VJXEu9Hn8MhFj1hrw1Mke03zYThadSbtxIzFt9ShA9ucYeATKiFhZ0xaQxePKvY1ZSrozmjvWE/CZc5VS7mWQYPe2IyOOp2Ceq5hLesY67WHl3qJKwUVmZqeTnvMjsOlUhT8Rf4G3uduXRERpFDuvdNinsGWCn6OoSJpdSXO1XivJkK+ayT6FL8PuMKb9Dr/1flbrdkWgnUs1g1hwCKkppWtac0y77TmtSYVaBrptmNKqkFzdVKB7YZkRpErU5s7JWkWvVfT91NBYCmnN4iYz7Mqo3k0nuOZ2juAOpyoRkpNGiNuGV3rnX10Dc8pPf6tlMDUFUOHGelcKW+R9YTf4Ypzz0ykBfdFR1wCwvE1DNTrj8hrivTLItxa2nxDqsr0our75GdtLotFpneFlAqMbekO3wd+5gZNaR7ZZFFiEpkFroev5oCmjJ4VNExgNsxmmaUNjkY8rofXbd99HA7fNMBONwZHFPzU3ftV+a3+PQ5y3rQ1FIcSZ11E3eAav2cdweaGK1nMIVatSDyWLhjNnSgcpgRmCCI/HbRfYBHnm9HNbWxYB41oTmfF1w52Fjj8NFYl/totGQkX/6jVeLfKEM1hxZxBBIIplmmltQb1dPLCcC22SRnZDR8NYsipjOPISTNqcMyJqJutdmIoI4XhIz6TRuW+0MBVnTIos4jAHF/CaUd347FsLLZ3i/OT0k7m9H1asPQF5/MJ5/MJp9PJ5FnPqMKu5twwR6YvnBszCqXhi+ntx7Zh3dwhIvCh4TkFExAR93lGBdJI31cqOLfLFufM6JVP3wFT6Mg98lxWvpFrEefWM8oxMp2Op8zrkM5r6vstySs8iZwEUYbCWoFOgbEt3gbPb6TX1vK2O541q3Hee8fpdDJ+zdO2LyXy2xK1VWNdSMgG145Thk7Dc/53W4dnetgw1DNXuROUjlLKQQR9OUGVWUUm6Ox1hZsqOBYCYyUJqIacGIOOoXbLMhV4/zrS+Bt98ExJ1tze0XM3kmsa0YvQaH04EpfIWMMzluMPuVLI4PhPdOYtBnbwXBLnaLkvCMU+lPojS4G/LFmux4ITKMyg4FY/vxOANnfi84xkImDdb/FDkJmXbA5T6cQXUtYVb2RncNsFpkARZzppAzAfH13PwD3ItSJLP+1l6ysy9vgzIRe7YzEEmFtkPHTGL+ldLTfGppx+75TOcbatjeCP1JMXAl4O0fLypBPnzDn6eqeT1X6NeNE5mmXPqhLB5Cpm3fD1d/4PyMwXiv0e7PQSwetr6KvSAGNwz3IO67fNdFFjOK7KqHpDpzm2qcPPkWSfqrt1D6jWNLRTziTM7+Wt25cEPU+Hrx+Ie6WvmILvxPNkFQ/Psc2lPA8A/ZXVBye9GNsGGvkVAmzDzmLziHPiaXf2Svyl2eMtuQqZOO97c+Gr8/DM8VU+94znP3drty51SIxWFN3TwmN/isoX+z2itzIJP9kAgPM/3mL75/uyFzSfv4pvGz445fqEBW+N93X42w5rtkPHT1z6M4Dy9Nu7GbK/70PrflymydfQtpx/EWy/WyTqrYjWf+d1e2lurer3Rvj9Bf47DLs/vYVX8GE3FjdgmzO7BRSIuE0B6hkf7XxDLVCxtWZlFsX0MWNOPK4bmojrtDT0GeSaxtRSnktwuVzQe8fdacHj5YLLGOhzekk+QThnS+HJYTrbTWfCWtA50ih1fuwwcfaN3derS5/4/MN1ffLh21jlKXz0o77/ikH1qUCbP3vx3D77x6/4+tu7fV8A3ur/x92bbceRI9mi2wD3IEWNmVXrnLXuw/3/T7vdpzpTA0WR4QDsPphtg7lHUKIys6q7DjIpMjzc4RgMNg/Ax++88q1GrtjdfDM9zPmPFMAG4NWvH7D99hHAj/eIPNlUtszrxivOM53xoaSbs64m4wDK0FcVgXz6J7fr0mHsz+GIf2sDOvAyovJXgLVgplE49net/1cgAcNU3Pt3psZV3Lx/j/OnT1B8DZbx5Qza4S4qOWQCn0BSbUtePyrBBGB9XU/rx5p9Ug1hL9VrzpYahva6LJZePGqJyhwDgPX1CYCiFq89qxY1ISJY3y6QBrS+efRkEjwVKG8K9IGMpDHebZhBrIqBbG/DheUzns4bHh8fsW1nbNuG8+MGpcd6AQTfQK8VE9TV+51OBIZAHiG4Q31bkCMjAYSxhWMKpZ0TQMUDLJm/MWMU4rif5c2Cdp+jxCaDZzq7jF3SXoo5eXTtXn9eTAh1/bfVDpqM8hTAuKSWEpKcY2sW/TVUIa9MgBoPzWWQkHZdX6I74Ygy+GB6QpnCE/tUNYN2fV+hjpQj3Z5hVNz+suC8bYAI6hub41C1KN/eIcWijOlJDpjRn+nhBx5md0Ewg1MPoS4Epr+QsP3o7L8EH7EFAXhGoPmjY3ppy3B8+d0z/cpc9/ns8fdM017SNUVWihlzaQo0U6J1ZZRiB1ypNYZiSTWfl3XBUlesy4K6VpzWExZXxrFWYvPo25jIYfw0PkAsstzqgsNTy7ri2Kk3oyFMj+8RlYO4bmDYA+EVSkMMQBiUUJzZtTQgKoPi/qk0p8MSnGnOsRuqsx9TYgmwVpvAcKeDaoqJXgqGKyUiAqL3UDrud9yXSOb4ySyrXzCawqyjU5E9IwfgaY3ZPOKA60FF8lGLcBB3dCh6MeM5ysA0VIiVGtGZrrULcDqdogZjKTXV2OxXo9he0sKQ6vRhRtBw+5JQAY1njo37ZRkIFOb/aaUQBkaURMn3X+sj0sUOq3nfuxkje7OUsd2vD6aeHt30CTLnwxS09tv3s2DWKRRxQa1G9F5dakSLMYKsCDxaZda4ZZQxU8RbhN5wo2Tfp0AUOov1dDYmLPlNnL39ldaW9Kf6Xs9UsJZ5YJfdR8zAi0LqjKCTuT7YHBv7FzAVbvEoM/jZzEpcjvTavkkAPmFDLmCEZT/CIKdTAL/Wop/4vMcJx3US9XloN5w86EhnHK2dKTj/pfwDNDbn+uc0MpvBJ2X3EYkSP9XT+Fvrft0cXeau0rA+UAt5CRtE9kyerKGEEiLDx87gjv2ZnNHN6hkp6DRkc4AAQv6t27wj4pxOKeRvJK8Nx3RNGDs6g/wRAS0JnQ4TeuxLnR4No0EsOzPU09OroozplVXIo7OVJAfoNMBnIA78l0o5hIEv1plMoPj/5kwr6nuOgtG2i8MRxgwFyDXF/mJGutvXCR517i3HmI1H0bvOfdq1YKs9cjmyBDgMyj6DHIAwYsowh9w6BlQ8pbbSQJlgzRljVZNRDN/OSNlZ4cX2zYoYEf/OYc/o0jSza7Dl69FB/mDC+nA+qnh9WXXHP4uu2/N/lEXI+xiNl+QUOY1+XGeL+LVPI0Wk03HGh2fvIqgk3gW4AA0uzt7YA9LRsdvbMJ57SaClLljWinW9xc3tTThdkkdc3WBrhinrmQ5BpYr5QyrcccPOEVPtjyhzMNCaGUfJw2HMs1cFkbWCWQvIHKnDRpfhPCMSSjEDo8FnCfwKwOhXgpsJBHD+KvPeEjDOVIk0JA2Q/5JwaKVjdPTAs0YY41n3fRhQ5p1BKGEdcC299iwbQJ5CioTD7LqunhVgb0RXx79FEc5/2dFxjmlMJ6juEebdPvOn9RHR6EPVMgoMAUrF9vQUBtHltBjeHA3wtMcZOK1UgNEPkQoa4FQs0wP3U4oy8DrgINc+Jz6YGxpE5Ar2SjTSuSSNfeMdwKxjwy8y384+9jzVdFCZuDXfNzvQHQ8i5NkT75EdI0otkaEh5Aol78U3FIg7TQ5XmlI3xljwMIvKxPN07sh8dtABiAU2uJChaUGZScXAhxN2GOK/Y67b/DYeSjRnxF7EHgUJSwb23Pzci+u/KEtxC82BNm2Y96uqYYnYO+BIyqbAPAiTLqYXp61M/NCBINp+lEnw4h7b50EaophnyXEWsyxqwEss4I7/jHWn8bzMW6wvc7brjmf6MB3ZDocQSToSJJ9DniHzY5RWj/yzabo4wEw7D3t2bRvjhDzPk7+kKR4AfY0BL7EpkwcbsG3I9bwBYHwZkPfVnGx8GSyAizzGkff3d/n52TnXxBHw51J5g6DhF8R43rNfi6tLdWXOmVvY/83GvojOil5Gn2u69/j8994NAOXX98AAyq/vvM65GcnrL+9RakX7xxZuMADdvzRkzHjxT2y/pp+/pB2JxHfankOzNgD03w2+FkyD6b9/e34eL4XRv6rtYJWk8jCC4rruoFXeqttphiqEZZdUPdBFsbh+JnTpIUTwpY4HquGUdVkgRdC3bvzxOdEqEGVnHoQZk3RX/oC4XPMBVE3XM1+huzW4BrIvQLd/AZ79g8/9IVl9//wfNaJnepTxxg3eh5E6O7z0K+TruXcf90EgOP36AaVWfP0//9jdOwR4/O2j0aGfwXe6/0N2a/kc8rqGhy7ptv1xBZIUic5PvvD74/xrMcK/vQG9sIbOwSfunNIV5g2kIBoR6BeUmQyCfdGded+cp6XsHsQ+Hk6MNYy5Xt6/9Wtz09pHS6nbcY+nT4nIy0w7rXge+YchJY83MWL5TriSRDUZATJAinjNbQJiCWVJgRnOS6XX+IIqFYvXOT2tZsRaIzq9hFKuu/c10zJTwVSWE0b7hnOzGoDaG85fFa9+udnx3aUUbIycxFc07ej95EKXGQXG/+lo24Z2u+G8bXh6OqNtG87bGXgFnD9uVou9FJSyQvAt5isuFUyv0uSRhQdIeQuUMutlqaU4GWOg3TcT9qiQuHdiIq+MuFVbcwljgQmZ25cvYB1lyKvwVA4hMow1slN0GiNXZwSPCAod3wGM1rGss7bUjjCyB4H10S1aX6GQOyfQD83h2ebZvoygkfb0Nyg6xngdgrB6ZD4JPgBsn79G/aGCEgYhcUOgRUb6eUq1rkSB7YtrrdCwvlsggoj2KNUiVnvrHil/RMffAtp3oI95hgRZKNkj3A2X7ZT+JiOx+J7MDBCzl3xWv0dzFEB1IZquFLFdzzxIJcWpWoptegfulSf7N3P/eKZ+gve+GO/FeNQyWpSFCvlsmFSwQJUph2emD+0UjNWZSzubrFMq6riiFtRRgKWawVFZA9EMeKsb3UuKjA2Dlg40Rnz1fpU4mzKiRJ3ZAXHh1DAvUx7S0Yi6qZ3OUt2wVMgs2CKPwbOzZyqhScUfQ5rKy70CxJ+tkiJecwpujmGeUWHNswpgUaxjxel0gqqp1NsmrgjpNk5/X0RUDisfMpVAl9k0KHTH2QrFMNnyNLx5G7LnOWTizbw1s5613W9R7EaDunR0y003hXc3CNGgLWIG9PP5jKEdQytqWVBKs9Ie22a0orWpDGdtw4MyOpeMmLsETNUZlyMbBIYbLYzWGjhp3MMNUyU9VoxRPBW2RUFGpKtHns3112TQE7TWZvSHWi31bbP0yOZ80jzSqqfBTrw9xoi929EZ1Rl1WQrE6X5kifBodAE8XeeM3tEhoaQc3bNItIY+mkXpUaEMOqc4XZAJw6RbofBL494bbSZvVquVfKlLdSNftf0bjjd9b0SsHE1xXErnjxHnFIEkRRhZT8fAEtG3kOvC3QVTnm4ZmsZCxtC3BUM9koSwb8YIRnFaX3tVIA0SgSfSGu7HkvqAGzDC664YvgC8VKnGs7H6Y+5DGFH4S3N95OF1ImlA60AHihsLektRgR6RZ8/RgGX7UNJcCAtJN3qlTbqTMyAQ/3LcxOfLsto6iuD8ePb9nCnWI9IejhsjdbZ3Sr77GQHs2uU/Jaw5QzcEKMN4uFgnwAyyMqzuKmaEnp21Dh0Fo/t59oW1qLKMyyfwRDpq3yvxLBPMblFylGGaX/CbyohdGmmNZwsHK59TponkyYofANUZ+Q44rMc4ZwRibkzvPt+i8SyNKswmIV7f1BxhPFUw36eAerp1DNIBw2dWTtcdDDwbTcAXKEfMLE2qY2fM686L0Bkl2bAiAiTG6+tEUlydD+FqKUHD4RRZGTcGugp6G3tZwgVLVUVRdyYiwgs8M3EtZUDfneBB8w/HWqSgh0OOOG4YkCFmZHaDyDyg/k7l+XI5Ib2TBkMadCYPm8YYhjs3yPrPUq000N3dHW5ubx0GTf4pDv9W6kZ8WUbwykONr2D2FNLR1m0eW/PSDh59rlCoZ/Uhtmy9zzqsgllbNwtoIvvyP35G1b3d1PkQycZvpz/kRqb8scdLRz6VNH7ws8u1NMKRbgfe5M9Qr1Pt/UfmB439D9k4QgX25zMMrMkJf3Fegobzdd070NI4rUg0Riesm1Og8aqtN5cTjaY3/66reskY44lCFuDxSrRtO5tmuayeKY1w72vOUm7EB0clJbfVSic4nnYZlzKsepZD1QnDtu7zPJHe2Pa6zoajVOc+E53jObG+BEdnmMk+7a8bzpJ5vJ+5j+OwVoL/FrjDJST4I2bOgNp5GHTEEnE+XiYPlWQIOh2bUUHAElfM3ACHQzrOh6yR+JrJL4LMVuBaqCuBna/RRwVwnu9Peeb2G4qdjiL9SvwIsxi6c3XC3TtHxrQOImPKLEhOi5g4grxLmHsdOdXF6PzWuyunfa7uwCT5nd4DKSGAKJ9FGkWdk8KMsafTij6alfJSk6d0DHz+em/0TJmtRX1KSbaZCDDWwE+LOelEtgP/KWIZagCs6+qDGmjNzi6clgXMeaoYkbzGGVAv25FLV6Hh2XVWsdZp30VQVcM4FTguepQ5hh+0a3d5/iUs7tA9VLG+eYN+f4/69k2U8hpjoH/+MucQuIip3D37EMtSKDyLxny70R8JGZRGMbv/fjfOa2wqoeja9TmXy3mSo2bt89t0fsS/fxTgLl3X1JcAnsJ9vie34zkMjnTs5aSLkTvuvf1/TE+7bQvaf3Wc/ncF/q44/8NuogND/+0T6q8fnoGu/Zx21/4Mz/+9lvD1FRH04ja2FU4bYft/87dfAAG2f3xM0af/k9pzY5L99zu+9a+bB3v7zhLvRhNOPhzWgYTu/nD9l6rjcREsrsyn2mkMRceIcngcDx2GaggPhv97lGSwd5+bOSDeLAo0L+tVq5c+GYF7TP6aeG7qGE1nWwXYnH/JgZlz/TVdm6syucTj1NO4r6zjxZod2w9vfHFPu7v/p52ADHsKoOETTvpr4MncLspLX2lHeHbtIrbfPiJryPO+kXYbC5j5imfGrAnvSVzYjULzKOQAH6oTzjSPFlOQwuSdkZ/FfNX3Mn78s/Dyv7UBPbM2/+yDcAZwC1uw/oN7AQPu4sxQ+zwTS1ss4Nf4rJjMCBvnU36IxrFTfORLU1BL/pPiEeksI44ZmVKQDGIwJcqyrKakriuWxYzna7E0rutqRppCxboLd107Kk5Wc2MA5/uGeucC9mhomxkxem94+vgE1DOWLwtub12MF/dMhXN9TnRMWB5AsXqNbWs4P53RR8PWztjOZixh/crHp2ZRiItHy9eBKgvqIlAUjCHorL3OdwGouHODnDPLTph679i+NEh5guBu7kz88Qgpt6A4NGwpvbbwQMUb9CNpPiil3vztjafMNKcGRjvYIyakMgpOu8OUaqSM7tq95gkFQEO7Fj3EMxKiTSA1ppUjo407gX5VyB2gXzWBmca9VLJs9wP1bcX6/gOePv1uY3wrkb4ZZPTdgCJa0LUlfZKi3AH93ljl0QVgPTml4Wig33cMPFwRZA94wHFwEJxrDM0PWpRbeOH9+f0/vPcAAhSqjk+HgHAQUqcDDOYX/zIugIKwhLKpPDNpGjmJn4qUaXAuplRR9XqFzSOkGQUHAGo1e2m8EwhuTic/y55GupoClXSXSqju0bVzMHP8RajgxyTOlCLV0htTYWTpzGEpj44MJGD9iEDHrKX3YyBIwnnAOCYXsHsXPLXefO00Zs1x0Kgm4qlB64LT6QTiIhGxNW4pBXEwLI4HBkK5dhScBQIUWNr0pFw43LGrt2j0xl+FyX/NdJVpLQPYSyhn1HHNkXGbSnQ66FgHlpq1YtkqlnWJCPTWzSB0Pm/YtuZG9BnRYs8f3iHJ4Szh59hBHVBPUz+Nfnr4gafK3au6CaeMyOpdUWs3ZTHXJimIaEgnbOffY3SIFGxnRn0rVO1vf3juZ8DZhL3Yf51RP77VlsLd0ytS6V3LjMDm2bbspIo+FL0NbK2hNVvr0bspxX29pQiGFBRl5AwOP5okUU3RrlRc7c+IRR8uUeuWUfRDqMBNTnLFE9oJhccEwwNuVKIjWwljG5VaASfi6+eArewnjqTTPT+0xaVggcSaa5qbvzUUXgOGbzAz/afzL0GjJ0rYK0anoUDTWYHXUXWcPIDqaaglzoA9H2nZIyvACIV2hs+MAYanhO69QVEj6hUARlc3nptBgwbPWi8jtdlvOC9NNcUFjVNfr10tST9zvIH7QaOequL8+BjX2H2uC3kUtEJ5IDBlMB1v8ljUychhPuEdw536aTrtvCQ8a5Wf3ay8NFzkCtXRoUPQe4GIO6yV4PIMv0Yt1jR4WGpQZn9pTBMqYnz/sqCuZuTa48o9zgMQBkPypzSsIcHO3FW/ltfOUYBlNKRhyQBYxxHG83AOtMTfrZhGr3CwEYQhMasQIprNS7gYj9vdidp52MHsUgZPwf84b2PZP5jS3Hn4SJHtzmsB3WJ4SxTqZ4M8L2lxpPAOWHb+PfAR+XnHqTyr3erlLsviziyeqcrhKPh57pFi4jqTDA12Bo3VLisxEiZwsaXb7sPwpup0mgB6Uq5w/5nK3+FFbH9F5zt0DhDEb1TCcIzMkHI6nezn5gbLYqV81nXB7e0tShEsN4vzmX52y0DriqUCw514jsdSQUffZufBjbF0BNKu6KNBlPWaMddXzfmBcCGSVFOKmN8w181JKgAvJzRp3DwQWXUk6d/Jvu78aHcMVyD3pKA6ItN07cBbqsJ5w9m3rePkISTxbPZKGr4MXmopKNUM5TSc559aF6vtPKzghA7mj7HSazaOmbK9a0dvw5301M8nwtGBe0VHh+HlDSBzajHa4N2cQ5O09H4fTZ553ShjJipsfw1x43kLQ3IYdOm44OdX4BkBHPcwNT03lGueHUrgehbKurblCqjs1j+GJpzDhJq4D5f3zfnO6Ur2IiZ+YCkbOgD6utC5wRxl1WU9z/qndGib4ylifLAo0DrHhTCcE+8OfsakFXF2/fOgM4yPe5eC/QlQPNl1102YToo8B3ZtTEC5ih8mDOikFaSlWTbTydvZ8kno9RQJz6kGbeBsfIUsgGB0Evx5R3aG04nL6ZihCTHYoxn31F22FWZyEIfPp6dHm1+3c8fsZaTfelyYI0qJxfO5Sk98FFAWy8zWm5UY6WNAYRkl4PvP9QoHQO7rSCUiLrTm15ksnt5ImT8ZoLiDzi4ief81zmuU/HjmHS9pxUtqGi0DIAXrh3dxfia9BNUs0XprKGXxynHdeAN3QtFU44EcJ+egjp/HUIzf76HQMFLTV/fI9871td90xOI6Pme8Yd6p1wd2LM8jG9WPu4DDtR+tdMY91z7bRQVS1jCQLv29OqksF+/sAPDbNDF/vej0+fH8U9rViT3XiAX4abYxRjiF/Xe156exp7H/NzWTwacOgHxH8O67aVv2D8N3Ro0ZuZ64yV3ZEeoX6BwEl3lLnZkns+NrZPWKd/K6/a0Allqs5JROGWrHnu74xJF7eXYXv2fI/KPR2/+3tEyWiIfWX3+d+h0kfKrA7+m4XFs6wWVGEzajtvt7iWLGM/39cPD54wXml3iJAF4m9diF7pBD2OZ2/RxfN8/DNV5t1/c/of0bG9BtaUPBctGykODMEUwxnAWpaV62JxZnkl6PgZv37/Cfnz6BDPYTJvEPBZY/e4IZ3pLYG4ye4iEBQlI8whiOitdgGvfc525We1kn+qCx70YmAhJ4LWgRnMQYBNYHZeQXYCnral1MvPGO6Z1cSgU8JWcpcG/xExYRnKi4WFeIG8BuGiwAACAASURBVLkWVEsfCwVujTF//PRkiHVYarTTacXjN2P+bl7d4fHTGafyGre/vvLUbosZbFeFLBsARdHXKHJG09/Q+gY0YGsNT08Fj09PgA5T3HoKFFXF1ja08QUDC5b+xuqpVXcKKAtUFF16MIVcy4o7LO8XJ2kSZx4A2qcO1G9gREb7PELo3G2Tw1fp/E6x1hX11xVPW/MICDMGUskwDQJImMt+r6sd0SqC3jfUtXodE6/nmhEOBE9P3yACLPVkhK9YFBgqIAW4Od1ga09ovWOpFU2sRmYWOisE8loCKAKpDxphFOf7r1C9w+2HO/B8nd6+Q3OCa8p5McNbKa5ENPVv+2RrV97Yfun9RObDlZZkMJrXIjXB/hUGvu0cTo6MNzOFZaxANsXOi8YZ+x5KPRrPJ4wcGf9JKPLOHRnyMJLwXt9rZrDY+8/m5gZQV/LXMlPeAUkhm3AagKjZnLrZ/xH44seUkncULKg3S8CopJmOJzcmnro5eVDvLbb/rKpTYDWfFTAj27A9RntEc69Mq+OoWKqlV4y00dVKSNi5KcF4jqEoXl/XIk6AV7cr2tbQO5VjTl1dwjOmsIJHjsS6iKT6mAIwHbkwmr6kczoJ/FQskOKYYhFeuyyMQjzfPRc9nwoyGgZtb4ch+DKzQtDpwJji7sq6AdUG9bMHMXzNSAWBYBOjFNu2IWqmO8wwdW+Gn6mD81lRQUcmKCu4fV77KDICGZBPmh7qNbIPG4splQczXFyBxBmMn3JKiOLh4St671iWirqYQbWWEhGZT08bWrMSH733Q6/HP/hhqk7z+bZ5aJwfqzXr6Vx14oNSkjHRJZ6ICgDvtai4PKZ9FLqEUoV92d/2jEjxdLKH9XID8OiuBAglH6ayTxDXinjyzHopBPH+4Q4BzCICAVrTnXFh8ywwg3jbaUYYXqgcl7ngMSaeUSrq/JxlePHjAsU+XXgps8zBJYIXR4j+MKOLaBzFPMmlSNRVF5njtgeGp/wEdtGwcnzfbKRDkTVgl8Y+P+JjGeRbLxvtH3L1fTMqlsduGuzJy7hytQiKFitfUayUTQA6jZQ5/akc3+XLrBozNDxrxoxMVwSWllPTvIrXu907nFBBu59cWqodHZzKVcvSkZWOvrkAZkr2/u0b5pniBBzH5jnFe3NJBY214HPTueNiVeLcAnAjesoG8QJ6u+st9tvWegjrx1pP3Z1mLPtw89IN80wyrT5kKoiZgSToDeiQ46UgumUuEWBmn3ADenYmOjoNmZw0zxFpKc/QZG81Fo7K7OlwwZrtJWAC1Z3a0BDGKCAU6wrLxGFkZBqkdkojp0+lmMONchMTrONgxGVZCit75NHnVFJh8gWC6vxHLpPijqYeVUzF1nBDgR1TtZThY3hGHPOasSeIZ+ZZzgChKrCAtBIgxb1X7YELjGaYo5YWGyMjsG38hDSuj83HHBYsCnh4vXSR4qU7pmNknA13GDAeqkBFUess70GaBedhiOqZwQKjzJrOLgvVZQnjmXiZnFosQ4jJo+bEfXNzwur1zdflNI2yReL8s065jBJOHqW44TLhIEbNt85SKB2N2V2aOTSP7uNXc44w5/PpLJCVjTQkFsx94nkDTEmpEIxm9K8UeI1KwT41d+arMn7whSzu0AcBS5XkFpHoGY7S+RvEvUeExlTR4XQqu+eiRURqCbLKrDCkzzXK61hmG6u97Py0p4SW4qnrw0kXkba6u9Ng7w3bZnvRB51wmxvQR5Sw6Z7dipkRuPr15sYzI9i+t20DjY6xbNwrybjLMnIUoZnIkXOM38sjwRx4ddhZHn3vCCos4ifmPK0w53fMXv0safA65qAgwdMbO+l7IX4v0t6A+DH1maPUKRMFiz7nTgk5STLhhE/+qIpFw4qIGz1nqnoHQR8DAyJ4Dig1aoIRS+FdBOiR2Qag48twxzXSavJBgEYa9TlJa6FPeBoYOO/WBXCcGzsLL+GCCd/7f+LfvIv71ULQ2IOkELSRPB5rgbOmvOb/SgkcIpilbxoz4uz4l0R/2b+j5uEsb3EHB+1GJwdGZK8pfuba6O58oDiPbe6QWjQkx1urmJOD7FflsBy7/QjH8sQzAWL6ICloY1iWFd9jZss0+QixdhI81ZhGomwQgtN+P5LTAOy4LzNvGBc1tLmuw5iqeT6UPTPb6djzkD/ZasafgJUv2jXPEhIj/Qp8ARRvoG8AoE+ZRbvVWA564V2QD4gu/W+9N8OJmIH42jRshS+/yHTtZ9pRVIkh7ma8gyTknTrq2eM36Ve679jINTK7i6rpP2wchrse/+MRii/Rb4fBQFVKVJfjO85jx5/9E5vmF19pd4chKID6918BANs/fvM07p+BX96h/mIp3d/4M/c/v7V/qF1/zTMC5l/0vp/p+eX3Xs5kx6H5rwpx0mqmzKVUP0e6oxUKhP4LQJJfEtuloR7AuW8e5FD9fnvl4vXTH58ss86rVzc2jmK4ca0VT62HHYx4jiVBSiEOlcDfNrYp212sWOIzDuzTpJgvWNj8jh/enujNta/0ezc800047/7B9lc4AAg8gAWMn5h47kvq/vfDqz4YWcZHAd7rxEsVLO+mgScFgnZlXTKuLmrZOHou9faClvEy+wxYHyUt+N7iMYK+JL4qkP0lRGS8PNK1f3X7NzagT4Hhn9E6FA+fPl19a8qgHe05n67+5StOH97i/PHLjjEAeFjMeI507cezkimQHQaSz7AJfTIVwa5s5I0RXecdCSQMdLmXAlNaFJhyZGH9snU1o3StWJcFj08NpS6mbBDB1s44vTkBKBijoXWLCtcnQF5ZBKksS0S56INgXaoZzhbWuiuQJqGcHW3gaXvC4+MjHp9M2LaMjMUVFiYkGAPZIaVjURIZVxLF3LmWAAX4WqsZRNSiVXugsWko2h1yeXQx7FUSpoGol+avqLWijgFB98dlt1lEvsuyePqqeY3vNGFVUavvWTK20UGEipki9GC28bS2RXQ6oFiXxeb7WjHuzetWhpHL9rWj3iU48CnPSC1Bff0akOpChRtJZEEpG8bnbhgdgKXenMz66D2INVQw7hXyGhHp7lZHhL+5AuMrUeS37yLJOF+6Pwd/ZcuMPFuDGdyvYaTnhuE7iv4DtP+yeYSb0E8ziz/qnt8XLDFmUxQ857hEZyUjmsQdddGpQ1CBYqD1ZvUI1+HMYbfoS5jyVEqBqEVxVkacU+nGiKgdB0RAszHUpWLrLc5AjJBCrESCUk9dDYC12104j2wUnL0oBJ5eXooJ/GUOwQQ2lmqY+2fRGCUZegSy2wBXkCXlq0UL9H3KE19bUwpbZEL3utfae3jplyoo7gZCRRuVkJXspUf8Dzje8HCJUMyBvHEByNxPjYOfaabAtX0aoYRMuC2tvRZABpUpEoiBBgUFFSfX/CZlShA71lc9LVtDXQqWxRS1S632yLAU5xZJZk4Ve9o38Xa8aUcjrowDHLrG2ga6F6PsIodEd3qA1zCGAL2n1L66F8hpfGAUrRlEuhmnxFNIKjzKujoZYiSKQmj42UWxSwhPUPU0+WUqQdMwbQxWd169/jUVMNvWPOrcfyJVvu6NxUAyIunMghPK6HjRPCM6nVKY7t7mSbpYPEtFOXi0UqkIo5GlROp4+NqqKkplBIIf1FTrt5Bn2gm48LIPVFfSEMmhTyCakKUhgCILoAdBjWyFBH6Uw/dToL5E8knZyD0lDOQBcq4uKBe11Kkh49LAd1QSalrPw/Cz8XQk1+UsbOe+LHNIibOTa47bHPruXM0xA0cBledz8iCGgRvrmlP5fpjP7m9kg5em90w6wuHQaBSfr/S3b9eu/6yYZ0plCoo0nhePksawGugKhHG8926Zoco0FgIebeRGKM6teJYJrl9PBnTAcEotBWUrET113YjuSKgIqpd/svIKQNXi0VZBPMDDyEi5WEKnC+QhLG39XPecAUBTl0FOMOF+Oi7Zl+aIZ2uianMe3c74wEx3HfvsRjBz9GvAGJBSw4hO+arIAOsqmQzixms1XNtjjaaTCWzrDJcwvW6M3iLKgv4oJzcXqbLES60+H0VUEWY0iBtKABuj4Sd3Akp1b9nEnS0E6sZCd1bokvgtl59KMkFEF9mpzWSpIuag04eNbfhc6Ahhtg3iNTLuEo4bXc02LMykUCqKMA04Dei3OJ1WnG5eWcS9z210d65mGn1VQAaqFhDCxQ1aLO3Supd56d3LF3QoP/NsaKJtvm+7qFMANCSb4crBI050+lv9JIg71fl60njKHuO8Rf9OE9yCuDuP/l/wNvEunhuHbx+7aoY/XNw/9GhS0aCFoEM+cTScznnkuRTHA9XLwXhZGJZSoDzhE0IRhWqBlO5JUFieAm48H2hNw9GnuWODOTpsyVki07O9nB0OM77+pS4c+VzgxEsYLWV2pMTAeXY/nj/jr814D6aaV/IxjA7jftNgP9L+6Q44phw7B0X4sF+OL2wowI5rmJkckojhcJboaDy759MhkR8EypJXvleCak6GLufE2UprHIiLjhDDHAYUppyV1L8UykLkmZ1mD0z+AHnPJv4HHVM8wx3pJKDQRzOeZ34yNzq3KAyWJXjiWII5n7w0XJ/Eq+7mzplxQIm/orOySQjJSY8/ylkZHmwp+0/iqGZ/Ss0UAFGfhxmNVa00C8di9XTNUQ61RGZHHQNozu8wE2OpGENRS4VUd4BSjcwDCqT67VeazjnvL5EfNlpUloohnn0u783swH4NLmSKiMzvFmLPHM0p5qBy4Pc0y7G7MatbHiY/PbLD5q7vn2vHx8L5Tyf/acfLdRHv32J8/hKGkIZ74ItC3ry1oTNjlgtFmkCD2bVUv0DwBv3TPcr7xK9iitEXZyLBlg/pol0VQb7Tch/H5x78yzvl7u5p3LV29d1pUAoazzNNlPiS8hEAlF8K2u/7fokHk3YAdzrHynt/eox/qP3oTc+341PEMcBniLxDwWf8lSP9+fa9ef2xOe97mPv3s7P80dtn38d3CP93kwKd7yT46+pn1hzCU6Y3BcRL/InbI5RyiSJKELF1VUxXPr8+7CmvgIHWjDYvpeJ0WvF0PgcnUXxMAlikuQ1kzl1Sv5Sp+L4jE/s/ph253pe3rAv4429/2fOXZ3MvPxAPUhdybYV/0UtDOgB8EuBdgIPi9Itg+/26dYDYhfBb9RLjPPxgSjse5Nk3XG+c6yWHNZ0I7VKSzaNfxJP/XRD4b2dA50KVEHiMLEwBc0/4yWfpYcHnX/vr9ND+cuWdAPAI4Jc3d3h8+OYGmNluxKLUDSCpoLeaK8u719g+f4XiwfoUqta/7oBHfF4KYMErQB6vrgMBay0IZeX8YfRUqnPkdcpLKejOVItUZ74EkIIqJuCKe6JXMWVnWaiUVxeCC043N1hPN8DoWE8nYAycbm7Q+8B5O+P+0yNevX+Fx8+PePXLnfXbBb0U1HVBEcHNeoO//79/x+LvqWWxFM1LhcjJDURfMMRWdQxFGw1b2/C4bXhqjxi/rajvLG2vAvj2+Yt563oIrtXwHoCc4DPw+UoY6/L6l1JduLHUVaIDFYJHfEVxf3EAnsbxWzx9RLylFLR2RtOBZVlRpOC0nnDGGTqsVvNpOQEiWFarI0/FzbquECk4rTcpraI5F5zPnnNAkyCgwHl7OtS0nUqbnUGzCk6n27g+RsUmHfVVwbg3b+CuA+PBMGkHUPTWhXFgYQoqVQBmgOgeMdl7M6PEm5liq0jZKSx61MQyhN5wD3x9hRxXbdMQv39vSNuLkFcEk/Rzrb2E6TWBxVq98p3uPktEq+e+R/re8NO8KRtVr799/mbtm6Us1+92gZ31UY/zefPqBlDg2/latffnW15De0ODYjVD4ZAk9Amy0gBng8teLZKMSvecaj2Ud2Pg8ekRS29Y1xO1K2YQaR3LnUWKTIUbS04w8rSEgj9wYLWI3G+PG4fn+A+4ub3F09MZYVRLqaglKfUs64akfVZXeDH6ylYlK/8Iskz/zLWrHm2ZFYyqFp01hnvWu+A8jV3TsARXzM3sIg4XrqhjOYveTMkvasqTSiWm15vsvdvfdUQ/kmpJSvM3jwS5YSSfwMBIdM43w6Qpwkq+3WZcpsKjqF7CsfpZ0AnvOvJdgBmD0/kPA7uaxNttLZZhUd9L7dBhrgJmKKFC3PsPvm5mBtgrE7gXaSZZeRo5JZKipShYG1DEDCSlWrTgRM2TXSWdto/qY3Hx5mB0YXThGAoRSxPMCDozmpsy2sA5O1UVIEUk9sjuMfawG2nVhxl2PMpc3cmiowBqqZ0ZUKsAzk9nnM8zxW3vzQ1EOvunEtfXRHVgOIIVzwzD9f4ZD2ARRY0U6xz/AT/H2s7tpFE0hAffMNYdMzrvhiJ/cNJQ9rGHnwTITiudD3UHG/W0mQEc5BJl4plZJ30/z92aHAggUYama8fUbsGjAA5fbhAbZnRLs4y1yULxxfvJduj8fiq1J/4osTe2rouvMUcyxvDMxz2uqcLP6DHBGJduRgnbO9ynOq2ZoRp3BGD6UwAe5ovrjes060qasZGpVS+Gs2sJ3HkFeDY71k82Kkh1CvnjyBcxqrZJgufEm/p66UjOBGLOr1oZTUi8ms6hmsF36w00uHMP7OuJn0TUaXOBqjuQigBVvAYsuDn+N6PtCEvOx8g0RA9VoAnt01GXHQnuxaOSHYKgAEZBpEwcrk2ykgwl4EjHzMIyUbvz98zyAs5LPDrQ1ufm5sZT3Zdw8LPnAFHLDFKloI9vGK2HXDmcdmSjpEX+eirwtLa+Sbb3HjE5z5UbkdcaZ7xJs8w2OqDFYdczQ1jpDDNOFvItqhjpnM2SFV5CytNR83xlI3qMA4Q3glQwt5YBxv+2zRmQZfW65GMqC4U8smcREIOzZVlRXWmoUOcjCmrwNXWWGKgs7WPrt20beute1mvbpwQmnQQisnWMga1t2M7nUFJSqamZUxdJn1IEEY0h7sg9GUL7QOPprry8w9mMynW+zLOGkSOACOpCGOddXObpwBnwErh4/ktjTe90TN7jwQuDFA+XWZLA0l1FDXa0aJxZvoN1lQWz7nV1h/VaJo8SMAM7D5LoZQAP8nCsRIzxJRp8XHPeN0q3tRaOguagAUAKpNCwZnSFuGd0Ghd18vKkbbv95XeSYMh/+5kY2gzGSkXBsNI1qZHvZNxz9B+8QI43SrugPKpuHmSq/Fwj3YUcyjog3ARG5DUJGhJ7Hi+d/Ry2YcKacF9thyFGT1ojbRDHhzPLIZ2ajVwxa5/EkhZw7G481wA5d8L0VdMEb+wDCuRsFolOjycFPPKck9S09uYk5TChsNTeIL+YV23fQ0J05vxEOYUynyJ40SIe0ZzGF7ujRldIgMi3kv+EiJ3V0X0ZJeBgZkhJYyx5LxGG4Bhv0HXHZ0Oxjc15FK6n8RGjd2g1Wr71zXnMmXGFczAeUNJL5wDUJ73nDe3fIYB2Mftvh2WydJ6mVs/YNuZ5MMcD9fEPFDG9TJTxAtCCiNsuT/2wLQ1HWKGgSzyf5ekTAKJW770TBvmk4305npErLaP4WB0lnpPYluF4J+uuiVtqKcDbtxhfvuyMyuPLFxR5DXlX3MnX9YZ6yWnqJ0DeW7/9k/NDchjXxc79cHp/qB3Hdh1qrhlT/Hvdnb54JlgLXiP+9vVY/vYBgKDpmGVoEv7pfj9JaBOwGg/KL4Lxcf/9lYF9d73+mrU8zPw7ncrhh/ipwpIZDijG74KGT8H5FVgk+p+JQn/JPPM+EeIvd/T4xF/x5r+yOd4Qubgs8+vQSQ5VrEtFY/ADEk4MvDgdMElOrDyfObmXUtAS/woAa11CB1ZkUvuhA9vWQ3fBwAw6SdvYETIc5Za20zWWCBTwXDlpnj7/JEPC52RzObbn9+e1n9FrcPfBgXOk7zJH9a/KmPAz7aXG86vPOk1n1gzu59PvvycOe7a/KfBf6XUfJZFmWLT6e/WMGr9zfNYP07cTp+2ygTh5E51rz8wWBT+77on5ycrbK/cFLv+J/v/VJ/9a+8sM6BfA8xxhCQKeBL2DMHeMfrnWfmrxrnEL0Y/uxiN853cUub/fP+D2kHqnSAnhaHf9zb7CcSb6O0J3GK7d+23X3zUifhmd44CaUvuZkF2CoFqqZPt7Ye3YZTVm3d9MJoMCgUV+VjcumRf5ui4YXSK6q7eObdswesdTe8D2Xxte//raPF+dIKynE/SkWG9OGL8M1PVkaUcegfVm9ShTV2zBU4YBEW153jacz5Ym9rw19P6I03iHSv5ZKMDMFpFIISYoqUgoF0UV9e1cawrAl0RfIG8EuN+T/4EHqK7BuAGKdTmZEb1tJvDWBUtZ0NFw++put3e9txTVgR1jDViqPwBeDxrByEsaoKq905SDc3SlFogsrmjRJJTbz+27O7T2ZMznK0F5MM84Ex5usK+WYUpMi+I0B4xaCrbtjHVdTTDoEx+Y8tJSUwLAuB9QPED19RVdthsqQ9Ti2irMWSHfef1IxylQoOAOHY97pMz1uuDbsmLMbloOzMNVxh4zPvnqd98RuDiMF+GydOOFMHKh/MJu1FTWPifETMzh8BIXpqKoYL1C3K71ur9C3b0pLd1bWpkK1VJmAnDcIqhikedVLJe01U1csRQqSss0nNcaSl9GQxiugisn5ngEQHs6W3RSoRLVBalDVorilLzAGIqhmLV2mWKOjAYNZUVCepv1wiTSuOeVYV3MmZYRgbcI2Izq631GlFHJJ8LoquGpsg03ave6mgWhqS21QLoZNWqp6KVjgSsMtFhtOixo6s4iXhuWwj2yER1IKY8N5oJWUfkoSTVh0kIoOlhUXupM54rAQ7PfXaRUgjTyYulK/I665vA6k6Oge+pME1aYCWMkg0lWZF0RioCdcYUKPCqy8jqYkrC4YWAadZn2PJ+KKQi5ATUiyzXGm+tO74+2K8FUoGpR6EzVyP5osFSHo+F/d3fQMt2hLWZhPUvAHCrUs3945C6dpIgrQuEIS1N8Pp/x9LSFQwd/Q5xfkWTc1BydOWDxIYarY4PB+e6NonPt0sWge3uIiHt9vHLg1TLtiL0CGXhJ++DbG+PyuSt7Ty96Bhcem3LAkuHhx8/NCT03E7+SgCXoT6KndIQjrNDIfejkOk8eOEqjrwyfY/TduqpOZyT7PdPsqy+uMhtEuk7j9+X6XF8nG9IlYd+Pz/oNp5WLvrlC85ybE4nDus+fdObHhJt97VWCP+3hnmB8JguYiDAU1b5c/QCWsSJSJl/sBmVGQti4StTZY6YIBSCjQyDYvKZvdmAQnhFMBbfQCReAoKAUK69itUer04N5DlQnnhfijKAB4jMcbsyFZTBx2sJU7CKeyjBwKWBRGB3iMKjibCjPriG8mAccBuOsU5Pl+CuyeYg54ZZScXNjRkHySdqHK+BDfQ+FQKv4HilUvYZ65Cad/eNwNmkoQ5xj52/cSaGQF/LvKsV5Nzg0tchcGenMDbUsMX7fjNuE0w1xGlZmySZS9IQrSNPo1Bi0P/2Y0VSnhqZaVKOsC4Y7ZARPy/4iSsdLeg0rD2FGAg2ej/Wz13WmbDeY81IE7Yzz+Tyj0B3Oa10A6aha4KynGc+3Da1t2DYzGJkTyABLG4QCX20PaaZRtfOhyjXZN78L07iuEwZ95en8ajK5p+chb0VQveDSAzwDLmKPdwNw/ijzEVnvsqMXKQJxBxfO95JlE0M4Rfe5+ILzExpZJWWLSmN0Hk1UvO65uyP6IjALCWmMjZ0ZABq2bk7029a8JE9D25pHntv6dV8/KWreNOW4PsP48pH5g0k/pmF7Kr2zwdkcQ8whFDFWAO50A7HI9tFm+qijdmjyyRq/GOmd99HkD185Jd5NmivnJxLK8pl4JJsTAtZJjtn6cyXhg1iBrCCXaejb//hesjyCLLMEjjvDmB7FI5gxTOZQDUP85A/5Pnv1zBwz3GGKtCDBN+k05h4AgJ4VwHneKVmmyDBAHtcWbK5rotd8xvcltATXmdP93urci3nmJixNXix14Rf6rs53ovPp7BLO/ODadU/vFWMMfhvzRPv1MUYwDrFW5CNaxyjTSTlBDcL54NoaqO1I0LvdHAwGWc8e7mxt8Twy14rQG2V9Jk9ioStlt6c+qlj3vcqF+DqG4eiVMM0vJsYb0JnojPsSMlVai9AxzLFknivvOxL8gfyk798eJu1e6keQYURS/+LZAsSRg3sAhAOh6oUxWh1vMfvK7kwg/53mndbtygl8cZtOSrpbkzsfa+7TpM59u8Y1H69FWSX/rkGxqtEqKPk820uoZSYZxOXGOUBhPHRVoP/+EXBdDRS4w2Ut9Jesxh9Zr2c7eoH4oFc+8STb/u+dEfjdzxjRfyj+/FUt4errb33ZKP5l4/VGo3Z13QpPV5b/NHBpkLK4FkZ2KV6KRkP2yhnVVNTK1wIh08kCK+cId9CUgj4UxT1DssxjtGhmSRSRsDVoT3pH/GD9Mv56gYz7Wu0svVHgrc//Xuz6tbNv+nxzcHkhiP5btoxvc/t8gXeAXxX47ZnFYGmGBYLy63v03z6F0Tz3fe10UWdCWpBxwrPxB8/O5Oeb6jjwR7KDr0mDMtX/72l/zoAuuFqr9MhMHB9inNWAej2xMZ/Lwh2fSMoD9nvsu7iBuHUyJp75X/NbZ+TrRFb5eUvhdny3RT0oIIIbAc5CVnpv1C4CvIHg9OY12v3XiBQYo0cU9zg8A5ihb+AbwjM3+n4NlYe4Lx+A5szS6YjcdgK1xLXF68lto1n/w9IDj6VgeNrXobYfRQTaOpoO1Bszxpay4HRasXpq5ZKOYpGBh29PGDrw+OUBT09nY8D7hrYo1psVdzc3uLk5WSrWV4rH+zPQBO38iLFtePv3v6O2BQOP6Gq71LVj6wNPbcPj0xO+PnzD47dvHl3QInpTu+0bFFhfv8b28RMYrwFVPI0N7WyC8rIspswTU9rUdTEDQ2sY98BWztAi1GFE1N9a30DLE1Z5jZvTivNbcFTaAQAAIABJREFUwfhyh64PYBTNt4+/Q9+9x1LXqUyR6gb0DTJMMSM6hVAa5nQoHn97RH1b8LSd8f7tO+SNZdZbgXm5m5FRwoB4WmfVblM5Dmh3BVd1hwQ3cAAWVVTLEkwxAODWGd1XEinVBUC58wwEUkKZVMppnpEiON2c4tyUUrDenKwedbPzzSgPO4N3wcJVvIYCKG+yYO8vHpYFoWsPpo9LcsHkh9Ig4wdFJHMi5g/clKWSqShc4DoDfu/KMiqWJjNxFN6yz/9UBHsX7t2fDI7zYXsm0OhBCM/zdAEOaXyZPbsQmKA4n88ABHc3K2qp+Pr0ZM/4fItHb+m4NCQKgCIGV6c7wzSsc02YFx/Y+qrG+ETEENQhAwJ0KqxZm6ou7rzjuKfWClFgvV1xc7pBLRWnmxXrss60tFxjT+su8Q64ByV25yEU5FR0JyUQgMjUQb5vDEXJsVmh+IPjSUCGAsUUQlyTSB06khG1lt27VEukeISSTgFhJC+2jlULShkoHklmiirSSYBKt1ILFiyOV9yA7nCmY6B5SidTtqRxgLTWcMSyWs3wTYqlLB3TMA/Wn+xWU5LwMyNw4BWevGJSUubuvOsjElsi0mD0DpZtsG+GCwSCSAtMmu2UUV35cI2XM6cDixljAGg4Jvi7Q184hqWwxtivjTIFljl9jWHGE0bYiADF68nacZw1IgHxZ22vKpxulxoK4qyADKGqOAwPS006hjlIsDb6ulRLoX5QkJuS2iodTblFo3+Nur6cL8+hpzNmVJi40k4HRKzUSh1WX2+pS6RhZYpn1jjfmkWATYWeoNTEe2CeTXWeC2I1uOO8+bNRBzH4igKI7mooc87wyMSn89m+bx69WIyW7vg9pcFeAE97DOICCqpw3DFsj0ofnka5TILyDEcLTH5LbOAx/2mgT+sB0nEJHgVAKBdzlLA4jh5ZoQrDQUwPbMshGLV4iP88HWMwoSOjuxzPu6JbtDhsLSBK6C0byJ3u8Mwoxzdro03he6Z/tnR11Q1iNUWjc9MTnHJpkej3zlAtzn9IGDssos/4gowXZ/reNF7yHgosC88w96fs7tspL2AZJCCWlhyg8Mb5cv6yW6vY5wvlz59p3kdS8Ns6yXzpFR6ipEthIk40aQzFuW1zb8ZMoa/eP2GQcJjpG2AOEnVx+BemAS+gcRkAehvQOiMzRKrvS4/1ng4diLTIQMG5NS9BZO9a1hXrukQJC7ahA1om5zVGDZxgAnlSPHWjR8uyeKS4R5wzRbw61SE8QIGhVjJisXSIpVSwbrx6CtoBAKXg/PiA1gbO7Tyj2ACUskCS7NS2ZnIwHZZ0xHc2Ec+wwL32E6KwM7BtHXSS0eERLCKo6wpAIpPSXKMZT52kXPvMfVej5Anx2ffDcaoAfXg2Eh9XpMn2LARW2msBBBiN+EKdDlagBnNoKaBt2GY89+jym9MN+hiQ1jCGlS1ZqpUPu7m5we3tLdbV7hWxTDqt2X5sZ5YS6bs0vEbbzRhLhxIzuM9a56WI129H4EzSkOH4Tzx19BjDI24lYHinBB2KLmoKQMcRDImM/XR8pQVOm4M9jzTPgY9eoJzMba+gpbAxDZSRHlsVvSu0W7Q3nyWMMCMTXaCKn8XMN2djGXFBfKN2Plu3370PzzpXQp/A9O6z3rn9trTtDee2YdvMSX/bntA2+2xp0y29O8Zww54plsVxZnGnPtZyt/VIdLaUoC07JbdOJyH0BpWC4Rkp7KwPlFGCH6JuKfRMTmuL88ZCjEwHd/dKMMeO4SU6LGNS5jZUgewImHlVNUAMWqnOD0Rt9J1lSd1JfU8zQmGpJveEgdEfD/hx+B/uGEMHXhErnVTL4jCaHLGGGdJ7s3JaBYKqFctpcX4doY+ZZQYtW1IbzXQITvuNrjDl90D/pmFcsD0HVDa3tyfVf+ypR6APX6t0DVBQuqT+aFITRqgLj6x1WcrEow4nI/0N8r4Rjk6ayn1N8IfphGN6E40zWNT61Qky9k/84W3YDQMKGTSkI8bBSPnBEgMTBGKNuGbZwBrvCMsy+Q7qr3Kc9KShZigfczngPJTPs6tCu9fkLWLZ0ABzsErrKj6+Anf0c/ncp2Y75O8TXwaQdxE7wxWeWdJ55AJg823hjhQBmgiqy0Qqmcea+zccp5E3MNmKeFXRyGs7f7zgdfDOgzw1jboTSgMex2D/vuxpnxRfUfSd4ZjYj6nLpq6aPINA0GVYPXs7trG2zIxzgKL5/dzt3b0/ahOFSryHsgitMFM3f3g2/X18p165x+jS/FLS9affPqJCUH/9xfiiuuzWdVkWyK8f8PDbb9jxfc4BLWoG5474+mIs/9x24O33yGb3hQCe50wDlsZvA4rPOMqux/xef0Q6kUM/f6ztMNDu+qWG59qK/9wu/OhujoRwd1x2OlAf4TJWl7p9R3itD9ysKx4enyadUkUb++Kdz8G5OZBRZ2rBjxkfW6QwZQB3TktjZ2Yu46kmLlzcpjUA6GihmxEIMICbmxVrVTxtJkGQHzvu95SzDwt4vO/weVHgLcfoPMZbNYNkhqujwXbxz3/T6Qj0cffOHbW68ubn2xGn/EwLGfEn2+QD7Dclww7gFQTnZ3r9TcyAfq290yn3T9vE/uxPbsg+s776+9RPVcvEe6fTceh4Lubgj4O5DgjUA9N50xUTmbzOLqGeRepyoqFTzBP5b2h/MgJd+P+Px++cnCnY/FmdAs30hPw+EH7vPT8Fvs5gHy9eeHDHV4bEKoDb2HSZCip/f4WgLguGvDaGr7jBRQSnt2/w7ct9eNgZynu9W79A1Lg7kLz90F80v9296jVgO6JumXpKt2KC5LKssU+2PS5EFfNKKrVabWKd66FQPJ098nx0fNsegUXw8PUJ6AM4mxJ8nG48jbOivHuFtpmAML4q1ltTmkjnnkzmtCsV9R3n8xnn85PVP0tK5u3+C+TdO2NYC7Dc3eLx64NH1AxoB0bfsC4L2uiWLkXgKY6LRYyoAH3iAjPs+A4kBhuRQg0obyvaZ43xQoHHTx9R8Rq3v7yKGm+1VjOiuNdjESrwBV/+44vDyawlV6Tg/v4+YItRPUupuL25NUVTKPZtr5g2tx6UinWZiiqFukK4YJwVrW9Y1hXoiiILmnSMr8NERT/Xy131mXsd+TKV8oCgLNMIo2op9Yj4SlkwmEZN8czZsmvjHljeJQORHu8gPN9Z//i2Ox+TgeGFVw78vjHBXDtsjxF4ORK7PXuwnjuJ12by/S/3c3nhs/kZ4s4rTxKPXDBm/jMNUZmgZqE5RU8nGJq4yfZ878/NyO/0DJXrVPLY5oeCkUo3pmXn80Usoqu4sW6pFet6snIRnv1Cqsy+/Bpg+wkXTks4+GAq+rNSjPNz5RNZjIn3Js62s62zdqCaEsf0Veb2XQoVnbY2g1EtYjBfS3WFFHYrl/8SzHXhe+NcFRM+BY7P3LBQigJanak3o79F85qg3gBLhcfU9CKuoNzXVRevh9wFqGW4A9M1qq6mKPd5FSCiX6Yg5HseymSiKN+HHCkaIEgYZB++Ju7YMc+vw5/QcM3X7ZGFQiN11UyhzvelPdV4tZe7SDCSvqdjSe++10U82jzDfZ73VH6Ygj2vz/w1HQyc6ff7aTwnDFRPp6hxXzbyTaXisRnsF0D2DoqERaM1ec6AoqM3YCyJF2Nt3KR4VTXh0Mbb0x4mxxTnMSLIJ+H/EsrgKYG5rn9CQazPblbBe5ki3iIsRUyBbFFxE0+GMnh4NhsFq7v4ud7vudF+i06zDBR2LQ8jobkYUsKEGTAn/gkeN4Am0qAFTugahqbvUQTTc+8FcBParV/Dt3RAsTfQQSGtov8WDBQUqeawI8VSVaeoVe4Ld2cXFZTGSnjjmRDB5Gt+0PIZ4vnmOOVofI910DDmzs9uiEw8JOdwXNP5zv16h1I70Q7WWe+7zBmXe/Ss/JDP/x9sqmqpyR0v7GhIKEz5LgC4XDMQsztuVgzIkKmO3kX+zzNotNnPnSuJDRciDNnkrZjlheeAeE1VIaudBSfjsWcWpQioVstLIQiFb9saztuG9XTCupjjZvEa2YEXrYtdSt21Ot11vifqu1Pp7YZNiBtnuivNw5id4YL8i0WVMAsXDaojHMyGOeSViqenr2jdym3UU7W1iXW2PoM/c4MGxzb3z+7PGXYAV9QLaUtGTgAN9KVWlHBOT3zcjvXL8KF+7uk8kb5WWDSvIs7SmJYiPg2Rgq7DDK7+lWUCsA5LFcuYsnjd6WE8FPFLrQWLl51ZlgUyOqzEg+H19bRgqebMzZ9lqeY35IbwzSPJW3eXPuJZTTCn8zyq05GhHUxcGYbJxLtiJKOSajh7GS8kEeVcnLckJhfSleH00S0oYaTkUQm8kvCtcByX2GPSH9lfIw/o14bTncmH214xHTqzNrDWeDack/apCop6MiVJ/OqBZ4qBhqLNgIjGo+48ZO9meO5uMBUpWHHC6o5xQ4dHgk4jeu+2t61tlrp9s4h0GuTpjBN0JIBejedNvGXeR4B6qRJn2fAjabemw6CApJrghPx0bknvzeFricNXAu6Mpwzs4ni1FDHeYy79rqkinO5U+c90LuUDNCQWiBsHdy5X0TfpQGbFyT+rOxzQOVhEkiEdkXIWauu2LNXKKFBhD0C1mwOJDqhnywIUXdmvwWApOsUCzDOlbu3rOrxfx89+13jExJkK5+W2OAiZu1Je4xoJlbgl+rMhcI/nHsx9NQOVsVc+ZnA/5pmxd2Tey86PxGEKqEnnfp6dEXgm96k73EBeNYF03kBrTLUf4OsZWhwZqWeiCd7d+eF9d6SnxfEm+Y/5XQIFZyFGQOWkFzHRwMOUlTU5NIY6OE3DIXDSpHS9eLYJYOJb+Hqj2MSHyzvl9Wtz/OkD+PoN0FsUfAt6pjC4vH3zBtv9gzkMiuNzodw5E98ONf7BkobITs8/5TPnlaHh+BDzKhJwanNz5yvnnfldZPpPz6rYGYuMXgQFx7NBUwUoH96iffpkZe515pPM+/ySv1/EvV7wm6QDcRImnjr0n9/xRwyzO05GiAetkSU9sDvENnbudD+m+ssHjN8/BtY8jvUl7Y8882xHL9iAOc5ElwFUvIXii+HNw/2JxfsXt+Oq/tFV/uvbUYzTw+/cguUCojyS0SMzgTw8nefZdR5gpHf8yObF7/vxYMp8v5VG7aiOKCavbxk7TF/TvQQr6dD+vQqgipX1spJcEpH0ORj0r2jZp48LWPL1NLdM0ngtzjWAD2rqzM+5z/+G9qzo/xONsPQSw+wx+vytmiFc/HkLuJ38Hn8HvcF+rXZ8PzxIQ+z6nZoE9jnR/f24M7750UK8DJmRR7AXUFabfQcf9CLC9M9p/1Y10Om1cKCB8zsglN0razuopwgGmTANRi931BkR6BdfQfENCO/ySF0rHlUm9DTSHXB2mLLo9H514TR7+0oYzvmm5V1B+3yPgjt7Xr8ZMffIc5roKZ6Z4kwugJREk1OqU9JFkak86mOgFMy0H2r1DW/kBNVhBlgAdV0xWgO59q7D6mi0hps3b62mbFeMZkLr07Zhe3pEO284bwNbe8DoHXVb0b59Q20V2IDbNzfW/11B+6xoeMAirwApGPIYyHKoEQwqH1zawxBXistMITUUOH/asLyv5u18r67Am8KAyS3qaRY14KEWUxxXqWjyiPblxhQbbz0tYQHKEOBdRb9/Baigt45ltXSUDbeePWC2IQ/QcYIsplhcsBiBgykEaqloW4P2FkIUlSl6r55qDdA3Fgle36gpb8S8suug0nAKY+u6QpmeV6chffRuCib16I6F+67QYbD92Dasy2ow8wrojyM86CyyckEfXtO6wCJB1pMZd9bFhGSPQhxjYFlOaJsJsrvIOQVO71ecPzWU12m9MLC8rlHfkuksFUD/0mONhGu7g3n7fXrzFk/3X7jbEAiW1xULXqM9KhRPxgi4h/5wgacGYs4CymQpRYxI9/1xQ8Ml8hRcZpfI2TY4WAEiHWvGBZcR5FOuPnsqwJMrHilw8n1rrc6YJQMZBDfLgnPreDw3lOb7CZuUUPGtZqRlNhEBsNycAMx6nH1Y2Qdx4xK96AOvOk9m+JIpsqgIsT02DcTw1Kt8l81lqUvU5FmXBeu6RqTZUhcTgKr3m/ZHGXkBpwFjmLe/4704/77JpBMzurxEXUeOpxR4PW9EXUBTOJoDDNN0m6q/A60CS0eVxforNOrIjnYoMFNoa6i9HM8kJUIoSzTeb2loFRhiNWKhGCrQausr6BBUs5WqORNIuYRHpvLUrmjoQNgJTAF53rZptIZFzEgxj3wAEPF0jGXiM3QgDMFB6ng/wgiVIy+Ymt5KnySRTkmnfyDmyeHz4W7+e90Iu7vxB+3H4qXGv5cdXnt3OGS40B6oQTXGywi4xSM7c3YD4llG1e6HJrs15wilSJQZ4JnNSimWVA7j6OjQ3p3Od2wQLEWDh7Ao+T5LIwZ8cPUNoYay7LAMVut4ni3DtepM8+RvFB5VolRtGt3TYXQ0JDAqndJzOj9OfJXWJpaN5wx25mlwm3u4W97LdnXr08W8R3HfngEN1nOkz99rXjNUkwQaDirO6xheTh35EVXANnxMYUcEEWWsakZ0MyRM4zMN0+ysyGWqS37HrWAJA4OBmYGESqu5DLb/pRZPLTo5WjlsQP40HcQ4Ro0zwjUxGnaMqKWzntfaVI01D+U6m+PrMSwyUIMjQTwbo0sweNkuAeVH+xwnWN0owgNLGi8TxhQHWH0GJyFQgyvUf4DipiKYtddtrQadUmAGsH3pF1ciDUWHzsjQZkocs+kZT6CiGI3ndjOZyiNjzZAm00jvP2N4rfTC59zhrNqczXhFOEwRcg4fXef5OCq7mQFEu0e1xqI5HKji/PQAiGA7N5zPGxjNu55WjN7RNivd1J1nGI+ezQSPQQtp0OQ2LqVga915jAwf0zg3eoMWc3iBKrrMLFTcQ8NzkniXZ0hdZjCvAMmkLX6PE4l5Pub5DxzvBKF3wdAt1hSaaOGyeD+WHWpmLwBKXbAu5lDNMRYpkEUxOjy1+6x/XlnyCzPNOve/CECHv3nQnMYcFC8iXgYApD+IcgaTG0r9OL7UpaIonaEkoXyNMyp57tc2IWiYf2RteNDIbtmZpEg4RGdeatebMotJ321MwDhly0NGk/2INCYccuaOgFEnMZf2wrkJ+Xn17CpO4qjA7QCKQj17Tg0DvuO7zlI/RnvoAMjoWf7QeH5lZYMXpGPj9TYCR4TDmCEvKMzZI2SbUlwmLp7BZcIV8SDgmUsAzGEZ3inkhxY7m22MubRxlqbzaXZ23K/xZCrIFwkBKGBQdoc/OB63LikORj/++H6GI4CmTdkxMzaudVlQPTsYIOijo7cWtdE5p2nR0sCX1YpZg1nqmOmqR9YYDRiLiPaz7Vn0HYMxZ/0dTx0pmPlbEiiTH56849Q0zGPpjzs8jzin6ZjMfwNf89nsbj4lk9gWz7jGzGrmlKogI8inoxbsDlZ0txWI3vmXZd4bntkpjSz2NGZLHk0zVnDthW8AHch2iDMTlwQfeYnj1uBN07kRj6JeBUspMxvJ/i3M9h60kVoAuXsFPDzgyMQsjh8p2ptugy8XlLdvzOH+XszQrmS/Bfj6NeBBplusD5d76KeOE+UaJz4yPzfwFRDghA8klAe+MckKx00VuHv+a3vvOwl637pFiBYpnoXjE6S8M/kfwPnjZxCa9LLntGLfb8dnL4uVXO8zOwlfe88PWM+L7480j/Q1f+FJGOK5AUX/x+9oAG7+19+gCtRlDT5v/K6hlye3t0Fxd1qBXz9AVXH+/SMUFo358Bwp/2e2TIKvcnTMEMMz7Q5U+Ozz+gLKLUZxrfXU2x+Z1m5YP7gvt7mf8swdP2pHiHjJKNJbjqhTnrmP+rdn+Ld52Way1OpoxrRa1OPQVkSnl4tsDofxxKxkfiZtmW8zTEufbjo3WebWmQjdss0y+lxxe3PCeWshy9ysJ4hYNsHVeXNGns85mlPuXO3DutOeFHRr9220987uDEe74n+TTWdRoNMhuLVBLampzmfZbn/9gP/v948ALPr6019wPn8Oqv54uwbFdo7n9Zc6E30Rm78AOP3yAeP3T7v35L6oEWHE+1vFdbSiinso3pJ1o476MO7nZja7dBp7BYHv+KF/s/Y/x4DuSqGXfH+VCUgE889vhM4AvYP2d7K214n57oPfOO4V9YP9fXr7BuPzwMAD1ndvUUrF+u4N+ue9+cxSWysUj7t3HI1sz7wdJKj0FGc6NAqhhuQNqNWjyNZ6miJEEZxublzxboat4mmoRusWVe3pC1vr2LaGb+cNvW142p4wWkFvT2jnDaNv+Hb+DNQNra041dcYq6LcFWCbmQdu3r7Fw6fPoFegesq8rLblvdwLE1QEHQ9Y8A5SnOhIFlzoKWopiWlEXGqBiqBoR+kF4nX2TA6gQEoUY0bl9ZfVBG2msZxiaxqfeU0XHVikhuGvu3utKaDGTD2KrJIw0lsg0Hvb1vFVUd4CVCRMYLfPFqVY0X0voWbYMsOjpXsvqiEQK5l3sfvXdXWF1QodT9BbQf8296VAPE2iKQhenW7Q29jVbAfMsK4KbNsWCh4aDwXG9BcI1rcVfQwj1q8HTuuNC8dAZCBwriAb135EzHIE4FRAch9t2VSm4Lg7MoJ0Td2jeDIpuf3Yw+pyvBlGkun0p4SSfc+XWIDREhRy7ZfgtFQ0j+rgwixSPL0aBUJn8kCD4zTaxVv9teL1BAZgRpGYI6XVORmeVPUOVKZRZdAQ7Yab6lEMS11ws55wWi1d57JYnedaKnqOMotFvVyPGf18nIMmRSs85Z+iKDM3aJxrCt8RbeROLBHlMhRlVV+TBSoD4tklOHsdA+KRcDlq6TjWwnS3CTfniH54BEOp80wUpvRWQFCTomsAQyFdwpFGYH0zU8VwnNBpQMI0HoQzGlypDUBdEOgAXe4BMH0iPG22zrXnuXNcfFT4Ejan4i/Bi+MBnhMl3Cqm0oGZQEKg+F7769ngnWH+wCN87xnADFHZWM4hzhrStl5Msc66sIBFp3RmkgGjVdK7D0xIRAUDnvowGS/jXDquJj/g33QvX2LvKmg6TMHX+i4LzNHIKS+Uqs2Inhg33SuSrp1dU4QOQIvTPsNBRN7hhJIGkPsJOYEKtsin6KjruW00RiMi0o9Ef/cGBZBwZz5PfuGia8HEDd9jg6lIdkzl8+NJOUQPyTyLxxcOdsaxicT9pXgUunrfpM1eu5LR5dnQdxyjvXNAh9UJZs1k9smBzIhBNyoqItr7EraSc8jswd/neC1SE+8dcI71iWeNdb1cH8x3hIfzQBhsMv2+NveJtq/Rnj0H/729ttHFzKG8X43+KoAJ+pf8hHNSx4khV+jOjgAzFmp+YmMJBO6tzbPEXMg/BK53eKIz6Ogj0vh3mQqpMLApMEYzZdDowPCUo10tzfrpBKkzWtD2WGZmmMTvcK9JUwWWhtMyTHlE5HDqkQxgYL9qdbNHs/TfeWVNYWXlkRSK1lpk3+q94enxwaLm22b4M9QUCIVVjjaM85c2j3gozpGa0ZGwXzyVItP+Bn6JaNEAWZ/j5EeQ/ty1ue1wBmQOgpCUxheyY+ZlVdKn4VVquNZi9SBlpum3ShoFuZxIqTWiWY0Xc3wAy3TAyPRltbIis7TAcULPE6HhZyh4XpllMmhEH12hsP3PDjmhxFSga7c/C6Dds3sF7rtKHL7T1HgqL/MSOBekbxI0/GrtYdsAW4fBTAbE/35moYbDaUwLJxWN7+kjFYZAn8uF4ewlM/J+WRJJzfI1+dFiTqAmmw70saCO4edz/jS1rHGU382RaXhJMosut4ipuQ4KQHbyS1DZ3ZUR9dYFVYDedeIm5890dIgUaFEsrg8JFzvfm+KlxgANJ2Ia2klni5hjQ3faMwLnaIyHq3yZLpl4go5f4ix42suEC+Fv2GcqgcO9ggrvoepO5DSyauLfnawkmnscVREzRtVSUGqx2quRdr9Hf+MYkQ2PLMeCWiq23tEba9xvUcM1sKPzH7rNMczvz/Oz7nVkdFwPPJ/XVTJvcYkryGvheEe6db+2wN7xN6aMOFS+H8ROGUtNh525RpkK7/kU3c8lN9JhmMPfVX7z5gb4Rm/Ns5XKIA8Nqi59FMONHAybdJwsgKsPJj0j3uL1vHrZd2EvDOrUTU5Wb7c2cVkV9e4VxsM3+1wKCgQdI/jrayenASgPX7HBjS93r6D339AFFz5k8V4ayxNfs78hZuawciwBpPF8ge1vV02OhnN8l6s17zE4eI3yvvp5LLE+gDj+7i6LvzWc++k++hrYG2GegZpnr19rz8WhPorVMX5pXy+97zlqHvyvzntoXOP5ys4DkdDOcbKUgpv/taD95x4kFcDH//hPvPrlQ+g5FZc10H88wT1u/1PtGgJK7SuA12rG8bw/e+mXa3EF1p7p+Xnnv5fN62eX7PLpn1+9azLd/obdrz/deBYn3YmBBD+n/vm5tf9eu8oPaJL5k2phaEoAhv36F5kZxEzmsqC8pVbUyhJdkyfJ9PF7cLCb7ndmpU4bKkkP7Lx2QWQ/0XDMn7pBgdLPKdF9YIFlHn6nik+OK98NTUb0P7fDP/v0D+HuO+1Nmp/AyoT8OB+hNRHBm5H12oLyt18s+OW/fg+YIy7kqbpGKzNrMTJNTjLJhQ77T57yf9f2P8CA7hzMdyBkRlR+/x5gKq8A67LKrLWT7wOmcQ+CSAXFlHhdLFqcwg/FEgGJtu4QVPbnjqhxNYNKeWteljRm6IeBIh9MwWMaQ3S4tdRfMhJDyIlRhq2IRFX565jzVKRKRHUOn28goJCUEZE1XS399loqpJqizTz8mVpMsKxmDGruwdTahq1tOJ+fcD4/4vz4ZHVRPZJxOZ8x2oZv/z9539nmNq6k+xZAqoOzz+7+/993dscetztJBKruhwooUOq2PTMn7F3M42nPvjgFAAAgAElEQVSJIkGEQuVgdUdxDQjuUcqKLoIKweHNrTHfNgNhDZBi1pTrPAzpXTyNlM+7xsq37w3XHw+4/XSF+2+nydGBoZ5YrTUsdUW1ustSGIUFC2mUXZcHiAhWeqfraYI53+lbaqkQImxtQ6WC9cOK9u1NeJgOha+K2MXqTZZa8PTbhqtPS9QMYxEs76rux4Pr02QiWsu7RWHmSSBvoQqF3rUWXXh9efSGpsDuvVkAvkYsDO99RqmL7eMBvTXUtYbSV0Sjx3k7otwM41xZC8qisNo7ozcVXEQE0gehpWLe599OWD+sEIzIIa0Dr8RzRDU3jWDHQMBsew0A/T5XPr+xfdRo/9UzNkAzNZws+nx98waAgJ8E/aGDbioEJ90LCBa6TN5nI/vYB6cfBDf2OURJPJdxwxCGRs/jXmUUCKkKJmGa/9nYdohvHlcS141Jq0Toohk4CoDnk2IKj3D2OtRbV+P14eDGVU1L6B16BFAo0Hx8FjnGz6Z4vB5KmGDPBVgOVT1gvbSAVHTpaqguALEKL8vVAXVZsFZVjK6HFUupuLq5wtXVDQppnSp1eikWjarpHWFnU8F0Zq0I0BR2kWljMIUM2LiAqL9NBJISEUdjF4cyjSGm1FN4ZxKsBGV1ykj9GRIddE+4ew1Qg/F0xsMJp+i56J2N3tjvk93H9hgVc7MIXeOe/azXWi1zAIUQyKyKx27OQj2l8gulpUBr0EaKW52OK1gGDaU5kosxzSvuITeOJZpZjPa5EXZn5PTkQxwGJ5cI/Jxc9suk9H/dN7v+C/xd7mMY+BBzUHxJ8RtFWY9sUMz7O8bi6UGZ9xhjzBwWzan1YBd1IEkG9NYKiCw7DIbTF5mRMmo8J32PG9JLsbrvgxGAG9TDQOZpTAuhtabvJk1bv20nxfG9o7UGVNK06ZKo7TkSHI4jriCMe/aM+MzHEcyRSewMdrGywJrW1512Zr5n3ww7EFlWx1B/OzOX9i2JFTNThTAanQmXL7eItM9AoAti43KcMI/X8ag7tuzf7cMjN1r5+VLrluHFMc68zGLjyDW/fa3VeG18a3HnDDOEiGXQ0bCxHazPK68oRUDUQYbXwgBYavQ55jIixcUII+1CSyjd58Zo9UkceEvMmDLNK/DWvC7BbyL/nfd1OFyZg4PRwzMBMiHqvNaXQWSe1880MRrMRhsozY0C8sccdUey/JB4rDRbcoNdZw8OTJzIwITcbd7iaXcdPyo+KTYYpWVuWKdwdvNSSrqexaI5da07SyhuPDMJLBLNa+MWAgoUz7ClgAaASktk8wAsiphG5jAiczJyWccNukmRNXg/3WO2dNHKs4rCGytt7cKhRxBhrcfcTmao4FRuwHCZCLokaS2M0vAjDnf2G/vp1yjqUesEdRxS68ikRYDXYQYsew6Zd4V6ByL7/CSA2gNY+uC8nh+YxAeSnu2Bz4CJSTCAUR5DjYaeDpK5WHkSTFlt3Age9c/rovxHeqfTVo08VyfLpa7hNKD752NSw/CYku+3uTLYFuzxtxv3u0Vw95zifKdYdKOql6ioh1Vlr7ZNZ22MKW2wL9IZpzmUmlQ8gl4sUlcN570NnYWPefDdCrvcezhwRQS3AYGnR4fRCu4JrxmOlyA/4gtlcoNJQpPh0UFA0ty0acYMgRDDS94EjXI4MppDhVBqs5JqXv/cs91wZNBjy3zThNGlKR/bdU4lycPz2mj97fVwpTKTO1uBw5lCuIfRwZ0TBcBSLVtCKZb+lFDLcO7wWsUqnVDw2o7bFtcFsaiDEFWUPpxgNfKYwaKG1S6Drw0jNhyX7+jsYBPi3lEhafABcQ+NcADPMAcaynmB8/t25ggpZ79d8NzItoFUC1Yrp0FEWgaOzQGJ24R4gmaK7r3XpadCkKb6AE3N39C4x7O0Uchf0Qs5Tk1K47Q6cX9aiwnlGT4dHGfqZIAQxpCdZ4jTNvORUD4k9+9p8MdEBt8tXoLPvnd2I7I5v9h7J0PMxHXsORDEO5wXaTnYInfjd1/bntIV8HREDtI2FmzwaH2sskex7rWyLkcAGCpdwnSnL8eABcUFxF3LJhGpYzqubYwAPz0r9N9cQx4BfnhCJYBubmFMn/ec+HoMPheKDhkU0Zrt4VF1ZtCzFfGThrvdyO086zgQNJ3CcBKSrjTCaI//1q0Tghqv2u8N9UONIJ4473bPuRwMEN7YLRpsoHPTUbiBo3cG/84oHwvatzuN0sR8JrD7fOn7j5pAjeQiwI0AT3s2VuZsjflsZrbhR9zv/vd90BphGMqd2xQAV3aej5DAhWMd36G3hv5FIPjNcOY7nHCHm//8T9z//e8RAevPtK/fsHz6iIoPINzhvcHT9x9NILVfXePXO3l9Bx9Io0l1vQULCOXTB/Svd8HXC4AFhPrpPZ5TlOqvtJcD+X62XQCci+0Hq7fD13t26+ytux+CXL7Y/54gvNAvNCDP8Z0KTc7Hka1Xytj2k9PK47z0+5kMYzeylT0BkTnyIfiubiVxAY2Q9/rmhQoejkeTnbSfq2VV2f18wmcDnfDi7vY3orCZU7dPnwE8QKwuOqH5GoqeY49W33fecIfyVT+/E8Gdn3trb+3e+z8IrBemebEpGfrjJ33/ZMUH0CdC//r1RWclb+8EuJc5Ah2A2a4obJN7ycP/7XHy+E2dcT5YvJTzmYKhrz1jl2TsK8X9eNHpN2eJ1Yf+HFb5Z7d/rQHd+RJjcn0zXwPEMCBh3vzX2h8C6588DDHmaSwKRcrXeQoqBkKpM9csvaSIZavxPFdZ1/ZapOrw2DHGNJSnEoMUU7zIuIDeO2pdIV1AtYBErL619VtUoekp3rVPVSAdjyccT0dsxw1UCtq2qeKdBae2gbcj6GhGXlPutMdHXL97h0Vu0R8E8gY43W2mMFDPcFXUa+S8TSrWXJlz4+T8uszMTz7cDDUatab1HBfyOa1YesdWK6ht83OkZhwh9wcyxUSqqSvCqO8KmmcP93ffC+jT2I+6rrj6ZJ7n0rWmc5ZujbmfnOZNKV6KpRR8YMg7NRqwMJYyombZoxphDL0RvWYrcri6it9AO6HDBOJSK8gNJqzGdlVmlaQ8hqUCRsw/ZBaLdBSYgZIA6grrrkh1JYcqYKsfFROOtV/+ziEsA08AbnDpoGeCPZZMT42gAySQZwmDOOBK+SwAIWAojA9wYpHwU4apSy9+ZUz73/8M51kKGWGUsxe6oaZiRCkCNKX3lEjJq78VU4Z1d4QA4GRhENRMLJMxZxIyBx4raS3jCTFjDLOmH7WzVYjMSLjgcDjo36srrMsB67qoE8+yGMiyeZtLbM4wxiWaYPRkVm8oEY8MDd181snWpAMQQkFFbx2lsDGfo/Y0xOt+mpEZBZ0BMBmcd6B45DUBZqwkytGO43MYP1zpDoe3S8BO+c/EZxAwos8LWzS44tmFh7DueN6Nn600ozFmwKOh/A/sQBhGNAggnBwtJG5SfZTCRUT/JyAaRiuDpoRkh0HM+/J7LeqRxvMOTwH28T8KASG/j6j8JHP7s5zEiKIddhA3Yr7ypNNcGTxMvNmZUeuwFAEsGq8uNSLtIDCjpkZfpunGDCaY31ny9IyWML6xjPrRJIgsIMxKS7bTBqkjEwkRoW0dzA29dVVyYtG0222ULchzPmsJX2Veb6+UjztibWDpJWXATprXOB8j+8GkYrRz5XUH9SshR+f7+/wMTC3Ry8vzUw4hUr25FcIc5SoyrtLfZepHz68fY7Hr8z/fUh8LBb7QVJsy7afWauVpvfRN9n/v0/mCWFKyGsbOq/L0tN7jScDSdKe3KN7Qd/S0rtof+UOSoyqLlhcSHw9N8AG4853D+BiDGH3waNF85odTz1hvX0dJBovs9DPPg2Mu/vuP6filHzPtHbjkZ9pEgQmIpBwKYmZMLQmvphQwhORoYRdl/AzJ5kaXCig2VTBkjrwG8DMmXsqD1PGWGVwIxEnRJqZWttTRRIwqOTLbI2E1e4rWRRWLbKxqGC8MkmIRcVq7HWgarUw5zaIZUAWWOcAM44kGcdp3EOx3Dueg3vSfcz9Rv5Q1a4tnOmithVEPAKoQqBYsy4pa1QG42rudJw4j5W7FXZRxescRJQ+U7usGuF2qiEb1s1jqels3QNeMhLSuu/F/dak4Pdy/zqQOoqojy4WP4UZPhBNz8McyK1Ucx7jzQoZfgCHcNSX7slg/FHhH+xzGXOcvizuB0piTiO+1pfTmbv9StrUEsdNUL9JhfWdrbJHNPZVLEXM2NIeKwrY+ngnBHab258QXKg3iJT5vrDxybgWBlgwC4AGIKvPxMI7D6YQttZ87P6OB94yPFUnlhNzJGojsXxcZmheZnESXKcGyQM98ghO727pyvo1ARZ31u6Xy7k0z7bStqaN+N4N5cmiIrCA2P0qpS1WcZBua4HTSbH7r4QodLcbtqcFLyK+DHjKrXoQKFLfVimUp0aeoV5Cm2A4eS1AwsiMQCMwdxAsKs8rkHRD0mUXD5c+Oo3VpTR4hh4vxmzpeYCw8lcgc4vJYGNZCPpxfNmH3oNmEkI8h0z4C6jBQPFVtt3XxLAFAcrZCGO7J51Dc4UqUp2y6354dASe9R8yxyukUOZxhwNMYWrpmn/ZnPS80JT7jTOAHxjtyv37OguTM9yThYPo6LXfm9TwboR2c4AmBVFIr4xUkmj1wiyrMe/LIvIzo+YkhVwQqgwckgRqpn57HU4mPknSo9yucJygYRoycLS6WxH8LYQ2O0FDqgnKY+b56exN9l3cFkDfTmIzSYCf9RLf7FvxvDEZMx4fpWa9nbALGrOfIy5p5dCQ86rwX/KwK6vuC7dsdlvfv0O8Y5b3iPIiYbKJdMw24o3clQkozl+a4u6tHGoB7tG/GEdu9xYwf2Wkyt0DLF377UTsznr9y3cdwc+FF+3V/ja3234sMw/nQeQP06T1gxuLsOKi/Kd9QPhPky3vN9Pm5gL/onr77r//C09//G915PugZ275+neDqVbZ/N87Yrz+ywH+wdRn8eofh3ISOBLC8SDSRbWD+/CNb1o+m9DPr9Ne0v35x93N/aS38eiU/nyMTjhsNHZZg9M+//wjWp/f8xO+U75Ok9yZM8NtTpDJb8MxCnuWpoBrfoN2o/aHxBSP6C+0SrN8DE72Dffc+qwAfCGCX//1+++v3epGlNqhH0JPvCZntz92fhZCffv7PHHTZfTE+66V195rn36H7+5b13Be4vYVw+vI1uvZyDf7vjoAPmYTnv8EP6ZXgUzJXtdOv/Er75+GGf2z7lxrQB3r5MdAFw0/ujbpDatGNXtxcoWHMe0nGFoFGIx9QwCH0z14azpx6GkDh6SVjXMj1CtTcXWpRT/AHQXk7lLm9azRgrSqAl6WiW6S27DBgN4bON8iNEqOaI8X7M3oUHTRgygiPxDhup2nQbGuqASgmUBuS7NzRa8GhaASpniEaDCFV9dhu3SIfO/ppU8WTMEqtwOkE4Yrj9xNk6ahbw1Y3bMtJFX+94eHud9TbvwE3hOdv37Cua0Q5tW7pYs3g1TW8EUTAQsBmey2e1wMFgiOoXAEC82A9otMQdDTisoPRTYCrONSKYy2gqkIgFVLPaIHtiyKj8k5rfLF5p7vwOlKD5lTEhE736FyxyIK6LCi14urqBqfjEQLCqZ2w1BWFtI6RR6rJDmHyg2B5T7j6sEbEyaltWJekTDJNKltUBESN9KfGqL3pnCyKUDMUDkXMUFC5IFyxiGC5PkAAtG3D9nzUeyKV8BBBlD5rJyp0F8gt4XS3gUBY3tUQQoopvlRY87RI5lTAHN7BmN5wE+cnn7nNIs+VqN6C8QgGcLy3WlNvbiEiaM9HADWUNJAVyMrTTMVBoKJOFO7dGnIoIVK6A8BK5Nn7Zq9G2mMJP6EDVxASk5CQ2GQYzMJl+toM/twRIftDuzchkTI8AGGtFvlhSgJhQq1j309bj2hX7Wax9zSNqMipbxNjUw76G58YUoDlVteYj6o8L6tANkK91vvV0dy5GYvGJmDbGmqpqFdXmqp1WTQqQzCceaARG1H/+STh3R9M6rqTBNKYx96P9IQCApqmVJNDvn2sJbkBKhnnSgGEadoejbZqQBPNuACNLAEbDrZrijvnBLppmHF13nR/9zytMArZ/lOBLnIzPAk1REspWGQBr4LaO2otgQvcyUrPo+KfUs0HW1KGFjbltCnx3XgehnKCUT5T9bqCYeLo0xrv5j4xYNPhKWGU9ycV34z8L+fdz2JJONwl3iDsvM4jvsbN2b3eqyQYcgOWIYcxKxpwFI47MtZFMH7X9+94CjeeZKW37xXzdD1Se+W1ptGPkEQaZSrFaonvjbEOxwhFKIvzKwCa8gSEYvVHldZ0ZvW6loQjiAK/el0rHYv+bwhHoR4a6++Kqrx/Fw614y5/JEfG6bW9Ed2gsyBFiFI4EngEHJwOvsDex7hNM3NJcIixJTAkW8+Senb+a+5c/0StT0n7xL5m9m5Hqr5sVm/C07g6rMK3Y4I7if0ZdRuzocsGXQrIS9UEDqU4P75b2teIGB06ZLa9MBwFhfW8an6G3BNZYClnPfW3DME9w4tTSvP1S2fxR230lo1GYzz7VO++B+bil9KW53P2Upu2WPZjvPTcS7CXuIJQ5KuR2WlHlEPAvBhzRH160x5PJYF4ws+ggEn/nVKUgmd2FVG+Whwei46peIYXDHpJECuDlMdFFoWGkJPI6mGXsgzcajRIIFYPz8+6ngvp6hDghjWI41Q2PpPHPHmkhvao8+6GOuFkDFXnjkizK8OI7hGbJBRZQ2jVvdFSFxol27hrJi8mjcq9AAuD1CX6ZtvpeDvqWAvQO1CK0uVaAfSq9IT4wnkgHN68QzullMftON8S/eu5FRkGSCS6LpxH7A6AA4kR3KFzyI0O2pGFpRQUyyhAXfvQ7AaD9mVnvOD/mNG2BsKo/c7mFOh7J8whq8XrDa6zU7rjKP1sZ4k5HLglGdCZTSvAgw+SovDdt6aGK4OX11iKQB+5bn3wI7aGbhhPvKs6vKns5Ldmg53jcGYJfsSfHfxCMj7zgOH43Q/ztHKOX/TTRB99uMj4Z+AUj6anyNwgCdfY/V56oBqPI4zmBnRmO5M9MkP4XmR8dGmBHc70ngKQyg2n4zPWwxUAoPej4SBdJ0/Prin8oTmvWjPcU1AXw2NWzLygoKMn/l4j0YuVK6Oi5aeoFFDvaLIpLgye1DVPhvOMR9OMf87bufFu8Dkzj2B4CIPv0Z458KLjX2cbxlmleHYQbqXnJfhWhKyLPG5zaFaHmAHLzqeM9OmW2Uhc30SAReYVKqqjE1XsN1ZnCQDANuu1WDaIWI3sCB4YUDpcPQe9zMz7/uzrRroseg7T4zZ1jgw50N85yS2E5CXyIkNCVYMGvOZ512gRG8c+tQcm43luWZ6J95Pj6/TMC6xJl2fgCSi3N4Z7BOX2Rs8ADfQx+AODLxeHPTuJPRtInsb0vbxXHscOQ2AJMCQUrFgPwwFmRH6PcZDNVYIOy7QXDv85yxsA1Jtblecf7vdi0sVlepmjc/5H31NsKZy/Rshr4x0l/hLku/Kz251F3Ny9Ad5p+Tofv/fD3+9TJ0YHSzEcbzTp6x0Ygvrx/bS2sew0ItEDcH9ynhd/F+A6XXzJiP5Sy/ff7Nbppfcn1gHVnqnwHHVzH/3r3TT/As1TxvB8ZarD4c+EIgX8hbH+7ROe//7fcV49M47DqPe3fPoIfP0dDIl0y6+ldI/9+NEiX2y/uLBn7zUaCEH/+g3ZhTEP5/rzRzx9+f0iHGQ5e+775fbzozYecxrtr7fx9A9GtsM/8T6arw/qkBDZhXYpexGFbOrBQeaA0XtEgSMFXvzEqMe4d8PYjyoc/qCryqI8l/IEgJh+g1lM/nIcDUAEz5LLriZnY2hdd8+EJRfeDYxleqns6VvRKHDCnL3hjWDQABuL2+QeBjnBG2Tb19jMFR9QPhKOv/8++Pf03j8aef6rbe+s+6vNI8f9fJbPqjcudkbe2foJ1HDu97oR/S1rFtgCxVP9C2ODZpcI/J/6v7N12WcFcdoDIPR3Ev+S04Ktdcjv0f+4fplzGff/k7bmH9r+5Sncs/DijNGrLbDPL2L2846wAjj+8L6XmzNHo0fB4d37+F7fafQfq+QKj3yo0LTafVMvaGH+EwC1x6zutQ645/FcD9Ja8kICqWDdhVGZQKsyGW3bsNTFaqYN40UhjQIVCE6d8fx8AhXC1lS44ROjyEGV8HgGcVHlVO/YWjNDAqOg4sgPqI+Cm8MVqni9OatDGGnceiB1gqavF+wUvnDPSzXsdTwjoVq4AqKxYF3For0JUooiKjMsFSpoltYyIurIHDEcWUjerRnwMrPXvzP4k4B6R1m1Hjk2AgmhcYO0kwqQtaC8B7bvmppdEmYqb9Wwv7WGtZRQ8O4zExRLud1a07XrGvUFqxHFzJqOTVQcZDdACk8wQppLOgioCiMd0jtqPQAkqGQIlFMaWkvZKCLgBw4hurNHlewEQxeuiJAVVy56D1E1MxpP6aqfv5v02T13zcMaVrPVcYtCrKbP84gyEYBWeMTuxNWQExQX3GYGzIWTS5zQJeZof77ne36MwFxWpd04ElULAgYMA5LPjcKiRekZjLQH1nFJzKDrAcb7BNgAui6oRKrAtjPnkUFEwyClPOjOe9vuhyld1ciseGVdVtSlquF8d+ZExFL7yZlArX/ShiXBOkcfhJDbBWKKWod9EUDI8GCvZkSvKJXMsGip90uqKyiAgDUqrAqqMa3cveyBZ1ywdNMJFv27kzR1EshwMvDMXpiZ6aSthTO+Mhh8FRjVqzQbD/eAJSKq1DLvCmFGwfBEBWzPPIU2e3ooCTqjjLnvhf1vSu+qf0P5EwqWpCjbKUXzPpurTcz1YkspJmPfZdC6obic5/8zTdKZyoZEoZkSZfqg6VddOc2jduB078xF6H0IJYmnFNX+ehh3tH6nQGScJx9n1Pg1gWmOsBnzcZquS0eaWrPoGDYr6cKWLpmK19tDpCssZTHHL+2vmKY1nyl/1yWSGQ4GtphlZ8C8xBgFzFitUXcEiQwE6RmHTcIw6Dge8gwwWTEd0ee7MyLxv9EiPfuYocKHn1V7SIgsGmJW9mVAHMZnw11JD+rQy6EYFchOfUROkMjhcx59GOxFgkkhHjCg9NzSiHqfaU1AI1PEeJ8aCd3INSIZx2IFnRfnxZxDeiEiLFZb11HhIT1pexccc8JnPtZJsNsddklrmK/R1M9ue2x9QJ5Cc5wzvW/GVefv+pU2Ufbp8tQTQY1SMEeQksuH5PsG7O2vBzgQTCE+8Ga8I/CdGL5OfDEQeI1ErMZxt4iqam+soPqj6AUKOCpQpUEthLIsqLWEgU2AMGRkGB2RgYLmtZG7lX7qfZq7cM4S4dHgGrks3INerlULpYRRy+4nFjs4BaCu5QwEGupFhFrXyBhSa0FtWsOZe0exaFr0NjLZ+LicrxOEcVr5vR0+cpwSNIY0hb5Y+ZfSNCqd13DCcvzetw11XTMI7dHE+EvAFJVsfIVjuQnU3SlG0r6QZUtyulCyY5KeCzXgqhmikPNiHa2lOQYLqOvZWoPj6qDvVrbKs+t4hp0woCY5boYXmMJvzNHhma0fQGXQwJHBDA9n57Oz9dL67toYf3pgetr2vjgvJxgOPs5cA84PK7pJcrHDSmQykOA3xWmMrbPSG9tjBsgdFxNuFYwsD5dQ9xmpFrGMV7ZO5qwyxjLSFwsRcFK+msVS0bPqDFrb1BGlq8G/i8l2F3jAqMnMYmd04LJIZw9ECvWYiJV06twgpQLcjK+oRnfInL/tswACQi+iGagSv6F8sTnlk9Iw5RErCndUrugFKExgIpPLnA/SlO6KY4ez+h6xD9hSo6mdSkC03rhJcJEVx8s0Bf9LY7+I5SytYchpRBGQMTbd6YGuads6sBhdDn5O563OloO3ERprohH6en7F8U1n9KduTr4Cz9oItKDDDHI3O4f0RIsvw+XFxv78C3fQ4I3HXyBkN38y0/mZuUcCjETaxeCRk26OxzPx+MBT0/XdIKPchf/7Ec/hsnG6VDzKuxTQ9TUoR6HbveEQAQ1XcTAYYxzZjnxakgYcTxvO85E6pNN15q3OhhzPAIMPJCEQbiAWUDGgYnLzsQhz/ZWBqU62z8/H6moS1R0hypTJ3oqVntUxysvwZ/Pq8jBxn4IH9HugfPwQPYmdq3kCCJrMUNhRwyhGbXkaa8S+pk5e7Ih3nK/tv6q5Mf1GgEdSY9qlJru/HmVZAJRPH7B9HYYi+gT0rwjDU0nntH/9Bnz+AGFB+3oHdzjrv8XSAXBYeA9NCD0cc/grn43lpbXMcHXpvtf54T/ebuWlvmWCO78GItx8/ojnL7//g0Z0qf2IM/rV9tdCdNDFRPNot6qXDOhZLkmMq/alkTcm46ie+pcavfp1XAtdl+qFpiAG/z14+vTw9Fmm6xftR3+w3e0G/kBqHK+Gd+/zQUzDyo4q7xKpbfiG5et73JMa6XeJgMNw/7+tua1QC4Mi0ri7wXzffNlWfIB8FRzxzdZH7/8kl0/JPY31PLO9TjzHzJf8wEX4/0z7ywzov4rCBju6Q6am7LxkSM+GEJPyLt6TXjCYHo/CMiPL4cKoCSOiyxV3HtHprcO92s6J6DOAGxcUrI5krQsWImzbyZQjgo4W7xJmbPf38ygcyV5Ys+wxAgxGycQWTYlcqqXGojiIyoC65yRQcvSSLhRgqX8LEYYyZKTSi/R4Nhjpgt429M54fD5aZwysZoQXQT/q4AQSUQIE81YnAXdLgSheX5C1HlRntN7U6G5e5106NmN6nGn0VKJizEBnxvO3byOi3351UdSVB50ZRfT6WghcF9S6oC4NwgDfC8r7gnVZwkAirIKdGg508drxaALFDAu6Eg/YWgVLRWl61Gpd0HvHYVl1rq1DhHF9dQW8J/D3sevlrdavF1PUqyMGY1mWIe3ZM64AACAASURBVDiKK7B1woUqTv05iLlGjgJyfMLh+hbc2RRbKv1oNMKshK6lxjzYaiiHty+L2gRDgefXeRjALeSNQOB7Br2tKIv1b7WP66EOpTQKtk1rz/cHUwonlC0QrG8KTg8D1jn+PsW6u6BABDR5BtGV/sMCJjfoHMOGMBwVOgQNBSsgi8KUaJROtUOyTVHrhEqeRkojGZiep3H43dn7azxtqZWAkWYqmK0fEyYCRVmD25srtMZ4bk3TiZMqLtWORZHVQAXtfS9lGEDNs5mKKWM2VWrQYdjXBQTZtJ+ihxilMCwju6GugkIMbJY6vCk+o2s3tJtynIZBC5561sZeSzVlsqbIzBFF/ahGQyaNVSTPENIQqScVhyvcwmrzRZTNxnGfRgAZXLBmz+gEEHe0UrD0imU5gGiBlJFtYjgpGAyKQmLppqgSoFBFkQKpFQsRKKd293135Z4IICNVfMAyYdJQhJDsN2HXBxholuq12CbJLl3tIIxwQ1smmbVolDFqVcVBB1AJZAbTke3CzrmnsXDYtSmGLceAbjIQ+tvivuQQcaaZNRyDfduLqJNKK+j9uaNB8jG+oAW+dPomvsP2PjJpwKcvFplsivXidTmrRdXp067UPxNkEy4lUGSrYdaa09UcpJjZIu1GeZNRTXYQPQGMls61WyEY2NXwQqjTyA3xHjHNaG0o49WAPguGfWuQRb+JRZsBmpoXAjUYZYHI6O+4NMac4cfvnfaJEHyN158tls/WDRHnhkL/W4I/0ojzYu7XNm/rg1wDlQEhFJmmghgDO9vB/AjRpV9SlwJEvUR41+K7N82Fne+xnymnRnmxiSqJw/AznzMx4PX60yP9OU/3ERXUog5ytfh8KFIJj7PhfIT2R5E7cKzvuCdT8lfGD49g1+9uwI3IH/9eijme1Hi/44IAfRm4Sb/nOe744Wlt1RGvwqKLyXcorW3wlnucM75fUq6+Pvf8LdOGhOkkRYbaegxDuk620x5K0iIwQ8rMbcXMJV03g0nxs1fHngMwQ7WNRQo6AWBCJceXJcrFuFI3G+J1b/W+CnO6LFrehQPulV+H8TZOv9woKiyW8llLSLXetJSR8SW1mqOsZRHg1hT+O2vUuimty1KBWrFAsFZLxQzlL07bpmmYqYO68TseQUsAlQXVouZrXVDWjtrVCFtb1/e3MlJT927zyeUW/KwOJ6GAn3SmAp7ZaFE4XRGWqqS31Ip+UhllWVe0bbOz4dtnBvXpmjub+hpblCYMlu29hUgz+AhDmUBJYOsRc4TqdW7hsr0r5RxWzRjqEeNJ3vSm57vEs8wdy7JESQePpu7cVHbcNqW1ZRjqiL1mOQXfwU67ZfzTKPbkWAFERLA4DgKFYwdAqOuqNW5bCzojEBAHtrRVmd0I4nuiqRRzVr5R166M98LHjMDhApicajgs4SGBRe8rc6zwbk7qKgPqvWowsn32SFMaY3eZMjuezWcQhtYFAlaYNngRSJRJ0CoNTmPEjN7aVzOHF8+AI8yxH17SjT1DnOkpnM8FxHQeCN5sSnnu5a8MX2VHtqC4Asjm9bXzkdBVINNRIJV+kWKOpu7Q52VizJCOQqpvKQxaDhBs6Kce6yk2zkDmTFgWlY+bBxwEdAyaEzwckRmD095Hpheas9slA+X0KaXadp6dAKDQxFVO9BMC6YxGG1i6ltJwWZMqqDCoa4YOd9YIqC+KZ8kyjkAE/MzoR5XDPBuSTqcZpyBgDOdlmyqCOsq4OpxCYweDR/RpO44LXOU/ZWJpnwsy36vvUMfUdNMAFtvL4cBRIvK82vlTfook8X/er0gKcMn/Hy2+FwSOvnzDy00A8NOTHlmTxZc3tzEH33ddexqGZAQFmhYqvu35n2lpFIAqlP+s11f2Lprujb1NvLfT+YF7lS7UdwDxLfjxwfSCQ3/ke3V6vFe8bP13cR7E5C3k8yCq2zFYdjpyQVyMtfC5DTjUDqvNTXb35r8EoP3eQO8rlqr4qt/dKc7yGwJVSVrit4qD3o+SoI65Zr2w/ks5LS7uzattd+OvRp6/1ryvB1JjuvMI++aR/BWE5fNHgIDtNzX8VgDl03v0r3cAgKv/+AgBYfsfTWHsjgPbF3U66Eh8h/WZEIq+5/Mn8JevcPzCAJbPH7F9+T2g/dZYnkffn92YwzcKo9+XWxrAq/dcbu6AoOs09+OYdLM3nCDgL99wZev4V5hIfx4k9qdgPvc/8+RrVwAk2n65Yzr7ML4qOzL4tUvP7cfZWRP/L3W5fIPsJazxOe/6S/PPPOO+j4uvg+lw7AXKO2GUX013+hzVrkETnjwZ/0GFzsag73WsmQ5OHo3snznfrwcC3mJEqP+oMTRqnY0XYdzhnQwY/iB63u8JuKdLo/71dml9/8qW+X4AaF+/xZpmW+Al43nuo1nU+e923zvRf0572PpwmHsr6ozoklbd7ZfzXUjfBYCXvnPalu1Hr68OJX7WeFl9cND7S4T237T920SgvxR5/mJE2j7VYkIEduFVbOQO1isG0/HSvT/6WZAi2Q3CWIDFOBgX4nufPdiYPQXW5X7X9PnStPwvE2CV5CZAduYxK073LfoLgcKMn3YxHjNGvXfWeoTWOgtQBEtd0NvRBFBBORQ8Pz2FwkyHoQKhABrFTFAjgKXdK92iH72eXVcDc/doEj6fx54pPd1twfyfMayCMM5z7+BaIKyRobVoGqW1LRABmqVlrIuyI507OlwhIHClOwC0u459c8Sz3d2h01vUv61Y12o1rAuWwwreGq6vbvD09IinL+qAcPVx1fWxGumu3F3KmoyLKnx4BK0q/XWmLIyr61s8PT2YXEym8BUcnx9xuLoCBZyoAsyFQ1dORUo3KOFd1lXTbRaC1xlVIBN4Qc7WukUNtASbpvRXNl/HxzIxNxpNhqTk1x+8BrqQGcgf3qJieGKdwW/a6/HbEYTbuIPlGBG6rlSR9GRHQzGYj2hme8HwXzaH/B3DncfzEnPzM+zxzxDmiOqznpelAp5mEOa9nN6a7w1blONTF5QJyjZFzTzDISVFAG6k9ZlLQekVdSXN5FDIUhUSpDRVKmMYrNTAUcN4VauWCii1WHSXTIZgj4RURU4HsWZB6MeRvhoR9euMrs0VejaYu0VMz7TDCTYRgTtAdbi+ENRzvkvXiLIqphADSFbD5cpeUjElIItm4xCgdTfGM2rtqGIVewqpsr1S4CbfbFdAskG2r7sYcOb03hPqM3zqnSm65qilx9AIcr83UndGKnyOiCBbkGGoojgYZtAAUGvgXnfkUccGr+/ah2FkgnSHxQSPMYkhXc42yaT+KDQClXZ1iLOxcUQC+1o5nyAvXD/nFVxJ+pLzno+X4t06zxyBGymVQyGvOwFLABIzn8abaCQU5wJAax2lcBjNfRyexrSbIi53Rb6WRj+9Pu+laC3rcDDAzswqcwImNZiTs+8dCK26etBgIQaaK6M1dZjCraUkDAlqB6v5E41/w9CaNgZ+vcRfL7fitQG9haNZXt2CtL8U+4ziY6XxuyHDKWNFkNcRXT1+F99B2B1xBsaU3Sks8bCJJ3NYj+u2XMOYzek53zMKeEmbOf0ZV13Zq+P3dKwZTnN65KkDsnroKKhGl33UCjMl9swNX2rUspS99q5i2XPmbDTOF4xsBcOmIdHngG83KJKdawaz101HnL25ZZwhyNHiOYo1G3P9+llPNDKRKL3ws+73m5HNcTMk1iT270+2wPmpKzF8zSQj4PIFQTYi7iZakg0QPtlx92BqHHdOjyKdcmckgv9jYZBUkGBkeSrOFyCtu25+8drnRsd1KBT82j6XYZyRRmo83TqOxyO2drJ6yaK89KJeflqqabFDsIBb0zTd4rWUzYlvUX5lKXXwKF2NfaVpZo6Gqo5x4lKcpZ0vVcvR1IqCgrqIORIVSDo/Iotm/TDng8hqAhgdHw4HvkbZmSTvqgiFc5Y7XmV4m1ftZ5rui4Ix7d8WNHA+W/lNYqVudN+cF3GuTc+IO+443Rxz2GdecfwhjPittaZZMRxCRGLPPQK9Bt9SDU8oMBPB5En/O3jL3huY1bEb5Hth+CwVf89YbPDV5pTqZ36/8IFmzg3nfnCK/05urB7md993EYJA0z97yvbsBJDtadnYysZz5nvVOUv7ElY+cJzx+cxnY/qY08CjgV/JSb7hQ5gTWJeQ7YE5Erwzg4rzKuZQz6JGdBFwU+OqZraDMwWBmwYO8vdrrDJAJl84fXc+yShvkglnGE5tf5asj0IFUgGIZhUky/bkKdzH/YSCAqmMKgVcqs6tDqInwtDyDhRy8cSHpL30/XS+050S1XlTHZI9+lzxsPNGoyZ6Ormxs7pMwzHZnZ73zhv+/y4d3BiL1LH/ti0Q5b24j90ROL2tqLToGp0IcnL8Zh3TBpE6IvThOCNtQIzGXhb2aopsAX7nRHvz9jov5a8N8M430dk1IoClO1Ye98S7HPeN8yKiQSASk8mHVNddMI91/pyGlLHPL/AVDosTnaY9T0YgXENwNDwn8MJjMx0YY4z9dfnqbLxjErEvQuFwS8V583yrhNO2GNwqfSjmlGVRxkSQQii3t+iPjxiuzfNgFcsNx4BBnoYSHyKayQ2GF8wULe747FsdLEuSGeDrONZgj0n29GAs0QMI7wxXynSfqlg1tbFmkxgHgT7A1lAi+6LDcebpdsP+t21P9HJqd8IwogOYAIzh6du9VJY7W7xD+VQgX76FEYqhe5/VZE4T3ZmHcAd8+RD9KyTcoeIj1s8f0ay28H6M+zZY559d9V/dHb3fDfm+v4RxkqHUPWRTf2oDQL99xfr5Y5JFR7sUYPC/qe2N3/Nv82fZXf9ju5Cev3DQBq91eRz7sfzZ5vxMDkA475yme71skwcmOK/8s5Aw6zTG+5wHfGl2Xsc7bn6lPQB4D1XR8oWx+RrPvfy1WO+l3uQPvsef6vE36ZEGh/NK70Mnudko3otG/H+U8Wzuw+mDU+8zvErzfCTBrqTtJcjPA8j/Z+1fZkAfG6mgMSlw/Z4dI0lnPeyveI8GbukWr+FQzZPGddmL/fMY8EjzE8ytmEBQYowvzeMKQLvvOLwvkAcBv2U1OEHM89QEVXEetkTd8X1zg102DJwfnvFbKdUiQ93zmSJdbJ/MjnosJ0bODwMzhApOx4a1LgPfEsJ90ffBlRgEjTLrWwNvDXRYIEXQnrulLhvjFFEPc4ZoTY5CEU23tYZabiB0GsK9pc9rvZlSow8CNK0LGXMMnHZJ+T0oggEszjFZjTViT9OnqWiXKuADwFTAOILvK+i2jN0wAZm3FsITiFDeAM1yjIT3nwyBg+Uex1MBs2Bdr1BKwfH5Cbe3bwACrm9usNVnCAiHwzVKLejbSSPBRXA4XGM7nZThY6AuFYfDFU6nE3rfcHvzBtzVgNo9wsR4bLJaiEIFIBUCem9wpUcAgIavmBJdcHp+wHp1g8Ui5amYAtKECRaNhGfu6K1hOx0tKlqVYfWNKhTkUWFyWVZQAbbjCQCBu0csqKlc0066kMMGe09xhukNcL1+wP23b2dZGMa5IISDHV3bbwKgQ+Q01gFJgURA9n82sQSQ1QSjTV/WZXqhgx/jOZ2r8xPqV8J25gKmC7Hx5iTETwB8jh3yPR5p9+bqgFIK7p+P1tsQMAFgoWToIIscwogCVyXmwDuCBqGCShWQAmwMVLJ6ftDImA6s9UrT8WlmTY0AJFWYFhBQVCgprAYvjxqqS0WVitILqFnt9FWzToAI1ApI1DBHVQ3K2cHCVxyuiI90RTqXfhIQGGVNVkumiQkgSPIsN0ZFBPA0sCD0wihdwEVQTQlXPPpYCpg0vafWBzeDeutgrrHPhYrZHpPiKgxOBnFmGJGgNWm/nSkN8FIcBiAZGfTAixlfGRUCjYZyhWXrHX3roWQW8YwRNg43Roi9TBGInt9aIUSatl+sbmxr2FoDzKDr9wMu1Gtk2HCjR9B430rXN5TkqAECuNv7nTcI2Hdakk/DKy3vdyg3zs/UPsrnB51OeyFp3OFkkFKY14pkRE/8DoYCJiJogcj2odlZZrhx/DyihIcEoT27EUAd0zyVsdc9dcmaxDMnjPl6JC8EmkWCJCLwwkDeBUABMYGKun24sEjk9I+01MJYrmltAsfaoEMB5Yo8V2QlZdSol6klFajWyFQxSXgOgjte0pWGHlEdfRtODLUaAZcVB9kwCrhgmeE6G1XiKZctdqUMBAhDv+9biJj+njgCKtT6GEguzA8yre9kTBFAzPAANt5LzJDBDk/DeO5srtMLRlEFnhnGIcPQUOqAGRe4ma32qqeWTTBeSok06OOdGjWuvIqWhXA49q0YZ1gdsNzJj4itDrQa4DwVuM4h02T/O8dalPBqyQZd7J5xw67xCuROfw6ql3BQXnufy5+TMgcdSDzEDhfpdUS5I786nwXvw+DKrV3+syuKd/MhIOaESDFqJ8eiLmshVFJjZfH61KIcXRVBrRXLUrHUJRwfxnuhmXCYlRdlQRu5eoL2hwMTA0zqIOTOudu24dRO2I5aN7mUgl46FlltFso/E8jqKvcoL9W5WepgLd+yLisWUkc/ReQC2SyikxmkIehaWzOMEKT8keGZJcq9GN3iqs7ApaJUlT07oNG2RhPZ6svmLRi4xuF83hvnj6JmsfUHCOqqYn4/PeMSpJ5BpW2tqOULzhUGuRAxp42h5Nk3dVRt8Ah6prnWuGdUmWQQjLPiMmGctzCyMzpr2S0tsVOmM6iORcOAzgIsC6z8BKPzAiIBUqmJbhHZzvuIdCCyGeXMWrbSYSQsAZoeCV2XRfFXc0ckiWxQuo/D4BLf0xqSlwvI4oF9ULzudFOJw+AF9HUanY9wpHToiHvjmjsL2tqLXsu0fmyLUWy3ysR2p32nYobfsf+mwTA5S5Q3FoH0EdkfDgleHibkD49Wl8jUF05eob2TNAwdm2fBKcuiNK83iLjzIun6Gv1hZk0dWqo5D5iRbMrGkP7phiEcrGxvllLNidZ4k8AHRR3wbc+YoFmq6oJSG6oUgDU7WpTGgVLDbmerVptHOK07WDnvJ8bzOP8sgzDZeSK7T7MKlVzl6CI3POi1AqE7Q7shc/Aq5pARWTS03rt41gWjI2SO9izuRer6KQAbIIv1RwSiBsEGyzUCgkWeT3vtaGnv6EbmLEnBiw220GUcTDJgrJN9HPBP3mOsSbpdszGx4pF9RJXzsCIS/MVSKzpcf8XO5Dl6Tc8nvSPydZw3eu3H3S2767WkLANx7p0GE+RNgTy5jEqmPxLl1M54zzH3y02wYMBaub2Nl9Wax4FYN5dhWtPwJmmqb9Oo8CvgTY007ICgUgEqQW40FX1/ekIXRDk61+wUkZEoReLEpDUkLV+WaI7jDseVlGBDCBAi3L5/DxDw/PUEwX2K2htyh4ig+RogHWWbV/t2B/r0MfCA70n5JsAndcjphgP7N420lm+KXphGlHU+zwQ96/l9wDk8nO/Yv65dim5/y4jU7cDghwqAhhFB6bLU6X++onz+gPo3Dco6/NffAACPf/8NwHA2yPphAlI/AsbvhvmSJGA0//rTR2xfNfpd8KP1khfPIe3uu8CNnfV16cl9D+dSjMpUI2BPy3tsAPoL6dv/CpnlV5tMq/1LD2rLC531AtF2O/HC756x9rwpbVzK4F+v1gNObdQQBymt873w3EUQkz4lWILQD/isL2UCcD7Np/Tq9F0mhJ6VLlqD/VA8imDMiUCjPBE8Yw9MvlCceb2uKKXgedsuLdYLbcc/AXhMc3zxKXE+czf3C/d+L6SR1aI8SCXNIvJWGHdF8cVbGanfzxyq/iSGOzvPIi/Ay8813a8RTuBaET+zDIn07ZfeUoznazbT93bTZ8P9J3vHiGBXqvidJGqqE1wTA+Nn8z4m98l02fUMXlJTDKn+b3e++dn2r41AJzdM0k8B32RQx8vHOfsfXup1MaLYoTUC1gv3vN7/y/eUN8Ng0+8Z9aNMjD55FDPcq3LMvOHyhlwUcvyK0Qgq/sUIANVg2s6iz4bcdfYiJo6EsNwENVKymbCUlCaOZKlY3a2lgJsrTWQQC3iaUGNOWZldkBrQW2t4c3UDaaw1xaDvLHxjRu57SOORRk+GCBex8DSiEAwNT/PL93uEAhXgJISyqGJ3WQoEq3q4c4N0UtgU3TcypUWpmk0gWPPHWNbpfYFUqaB9vwe9W1Gooy7K1B2fnnH95gYg3S8B4/HpCXUpOBS9Z7HUX8uyYl0P6K1hWVf1iyWtoba1FoxeqRWtH1VYPVKkctvQsd6WKaqCbC1QSyBgj4bxvXYlNpVRn1YjHATttNne6ozlsYNuCeVW03UKFfAb3Q/mDk8Mw6a0JUCNmrZgI/JL2VddO13V7eEB9O7dRQHgkmAgeLZ+io4jKUWUIKX6jnDmpCSoMS7HGBLXKU1n5oLA+Cvs3zmTO54/P+8vv8kV5tJ7MhxkFUDmSFwR5s+SRZkDeZLDkEWgDqBaRoRqxqzqEeWmbIEbs9gMrVrLlIoqEUpdUIqo0VwKqliK01pD+d6PjF41CqV6RHMpmgrd4DMYPHhUks2wkKU1pkj3zjKEXekKDURFI+gtBbTWWPX5I1Jdskik6Wbp6KzrsAAjMiQkXYUg9tqrvYUiRPFkA2gBoQPJkcFxGcjsEb7uhSEyZ1ghzAxaNqrH7ppyi/x3G173utlWFqM3NRiw1cfOcOzRXNm4V2tVh4e6oC5Vp82M03YCnQq2kzk9EVuN2Dxwmj5K/r77sDemcPqRgkEdigynoS4c5mwJl/qbBMKfkFWnCL6EmxwfzLq7YSxzpZnXMu+aEd+cdzD1uf8HDGO6O8fkGlSZnpP3geRoZ8pm4WEcUucOCZpkMzB8PNLYuqhHtUBMG8My4EPxzKCzBRbtTT3WR3jgm0yBLzLUNF/Xc2EGJ/KxOp+jUV2RvWJRw5ZHj8dmkvF/Mtca81vI8RWpU07ApEmnoSA9U86ONtaRADPkuuHGU576WSVQnFHBUI5O3rww+A7l6uAKw8ElEZ8s8J6NTXKvjgeMdzOjJAnQQcpTcQdLn2BscmSAKPIsRZ+NdZkpcLWU3kMIVmO4pP6WOqLQlSdQ5aSYoWsIaOfrrvsF1FrMcY9RihrPXcnrCvsw8sZ8nCYOoTA7zDg+zga+qRHMaEaxD86BDieF4Xw4Oy5IrNcreu6fbHMH3p/4+ojEGsxz33MX+77mlP17wdmf1HeK4VxzlbHoxLpo+tFaq8keeh93i2wlhlgpinXRbExuGB3vMgc8YfTjCSw91m449hlOJEEx3pwVUVkd7IZ+0oxWW9uUblFFa1vo046PzyAiNDZa2Jryw5YyfakrallwWFd1nACsdBFbeSuxdOGW8tCiTpX/cfnLnA0tkpMLo5fhvBP/1YLIho+WMqnL7HeWjJ+uPL7EaDoqHzLmOKti+7fnUS+RwougGqiWfIRA4tGn53mUjlmq4fWJbrtBy8+On0/ADeitNePTCEAxJxl3xGH0TlNK9lgcGVlaJK1XrRIRj2KKQ0/9PtNZRu8O56Nm93wsHG+YQbCMiJ1YK0fZidEZvHjmzmla23AAyv0l5K/0wAzOPBwvHB+x8HQ/kPgGQtwz7wGiX4GEXD3TAsebRjttvF4ubYgPOn4maEYvknC6FtGMTSObnK0razR6Z8+BZzDMPKhmGrenuB4w5bDPgFidbS+3VmmYY9OxKVYejUSAWsx5R8a7TTYiz3Zj8xSCReSS24Ox0Kp9ebkAFHM2NgcPFhDMyaAzZFn13t7QOqMIo7ElxTEe0sv4wHQPsT+23+5QkHVIyoKI8Scj44VnmdN07kPe8PXI59qSRkywiSQPSsDZ4E3ckYMtG0tP2QI1PTibU3XZOS07rtogUOdplMFPzZUlxumZA0uMPtizwRcbbLosRKDASSqvUGSTS5wqQllMtDvDgqiDJu4ogTQOJH6V4iwzlNdRHszgDWK86TDohuNG4O+xp1NTwRgDki9xgq+34HMxeCEiCsO60qwyxuFZCcUd2HjmYV8c70xp6PY2yotlQ7x/DgdiZvDppM6e9qyAzEh8BNoVxNL/Dx7Hsy8Ilttb9MenmcdO/UzQc4HYaeS79iedQ1aJf4n2FdKAgN47ankCi/IwL6XFjjlfuOa0eT8k5/kxQepb/Y1GCdA9KSYg/CMvcX4vje2ZLl+/ee3hf2Az1DvhOcJYw+xXFkMXmG7a7jUYyy4qcuFzft8ssSN4bCJCxQd0qzX8atud5z/XziADgBooX6shv3z+iIUIzVLed+ejX3vVJZn9n9L2HOof6WHIc5f6zvaTzP9mzEAXhjBpN5iDTrt8GkJGxjZOM4GLY9pfuTT7GN8PtoQSTs3PduNxtUSE8gP7vpwWR2CC8bWdX4WSs/aaKflHdj7Xl+zHdandQTMvVFuwBUpn32be+5VR/iPaHz3njp/9X8ZRw/X7Mm2IX9MPd4QwjOOFZ4aMMF9V3jaVlhHXvM60/VyX8n+v/UsN6IEoEsZ4TXH5K20QWvYPAIADFq2XQgUnEBZh3AO4EuA4OOWo+8u7oVA6nC5k+BuPAN7kPK1ikYlkdZ1M2BARrMuK9v0e6ztlgtzjBCAz8GkruAKnqOpKM7wTKOpWePP0G1Pqz3Q/CUb6Up/UtGZuQFIS25mxmGc8i5o2tY42WRk4JRq9MZbDAgG0tjdIIzShKfOZPfKKAVpAloaWW8Xj3TOurgS1WC05FtAtUKTggBs83t8H8w7QIBQmhNhRBsgcEdiFN01Vc4Aq+4orV6AySJWCtWo0Q8UCohts/A2lL+iA1jwEYb06QLpg27RuYrGadNzaSI0jLhIClW4APANyC1id7n7fwB8K1npAKRWtbwBusaxrABpxx/XVNYpFrwDKBC5VU0jXRQV6re1IVlPdWUQJBQmR1mVz2wBEo/8Xi7gni4xxhWhvpgDums6yVI8EUgpFIH1nGYpaiFiKPT0NAmCtVeuNBVwIDwAAIABJREFUmxKgQNAa43Q6WSpsHU+ztL9LXaZxKMwTGp7w5uMHHH/fUN5V9AfG9v17Ivo3ttJPKHiDnhC+3qJnJjxNTfAt3FHlCoSKQoxuPlvix0BmUcuZoQoCm5Eseyf6I54qOnvC5r8Rj2nMtzs8nCf/jxunbwPfZFIKPB03A3s3MOgZKCYMZyVIfm61FKWuMPBoMYirmkhn3cUMzqxRn1VTmg4jtCscFCbKetCRd1VWLnSwdMuIqCE1wGs6eCoMkEeWMPqxgQjYBOClgg5XCoNsC0/m7GFr6YoUn6fjl+5G9E0Aw1lk0XG1VtCyoNQVxRTsYoY180wBd/fItD47o5nYsRDS2klY6VyQ1zqNAFHHlpSPek9PSl+fh22Lp09gAoFHWnuktNTkMDdwuu8ruXCH9Eo7o2o014jk1hta2/S718Yc4BnCujKz/l5Nm70uw93M0+75033bMPxuldUbCmtXfpMPazBnlzh+QeCYGBjsHBMM5whANY2ApufzpfGO2TvSjWfzWp63YZwa84vh0ZgTgEhD62VbaoXBgzmcYUTOOSzoWEzhFql4h2I713TO81QHmB2uEKB7mtveTSkspjC2B5Ugg0NVbtlJouZVtTlaxGRvwRMpAqw6k4OqGXrXkgm0bRHhFf/ZURkgPOYb8w6xdI/3hsKCihrP67KoMwdVzXJzSSwLvGBKkHQoKClaA9u7Jm43rjCE2mji7BFNNd/9ZZKKx84z2Uurc7xIKLTF+bZBD3VPUwphQI2HEzxILHAoNu0cs9XaVDSqkyGLanMnmnCUM3w1FNQEVPc09n2yd1uqVy/hAcBwkEVB2vBKoYg+93rRupaagp0nj2XBzP9nvlZp2rosVtJnpInXKFJfq/ysC3lIvwtGKnias1/4/u6ar4dmaUoCr/Etw3DOA2ZkGIl8bmdw8Kea9kdAwOLEmxnz58qQ/JiI8r/SMweSnk9rkSNSRUidR4uuYS1KT6+vDljWFeuipYbYapFvvKE3dShbVzMyVXXA0zd2MwLp+V4tcrSwKE+32R7DwxoLWLrRdGhGqM4QM7Z3VtrvjrnRCtRQLsNQylaGxGvSFjKexpw0tN69ZlEZEbSOVzUjFlDVF7gARDVotp8lNeyM9QV2Bkm7uS7qSNiaRnO68VcjpSOv1USvzo03A9K4nRL8nUPNz1xTpz8E6BAk9q0a367OwNrD8+ODjcmNaoxC6mA76L7/9TMCg0eJKHzAosKZzdjqxs4SqZndWJnpsa4JRV8sABXf72bPGxynkhVsToThtBSySKIsaYFCRwpSRy6M/SDjR1igdbYDYw5e2/lKh4VBmswoH7Wfx1pCZFoz5jaP2353PmEYviT+UMwbwXfNySd8QwqYitWFLfAaKFEZ08lNohfZcEhO7AkQqzsudjac5wvHPAtXFijMN47iXTGHcLKRYdzOupQYuvN2QUOVR63LYnywnymkvUbaAzN20zhrXjINpEZdYdFSDsuc3tzhplCxut4U8kBBcbFqnFNaUbqmcqfa0a3uemOM0mylAF2t6gXqDOC4KjtuaWYZxHx16SV4eE8N7hwPu6E+0YcszwbD5hcCXQkSYMbZdR7Pz66YU16XPvq0LDWD1/N9OkFQdXzq9YBalsHDmNNeSCnk/KQdQr/P5qckooRTuOMvNgeOLHfpbwrfiduZESnFEkz3RcuyBACxbCXuRAEAsBIEEy9gNHXwfRx4NLcZfSvfWoqWski1rfajOms+ysi3QwNuwwlVCP35qHolXKHQNeTGYPvpMfZjZOqA8bwvvX9cJ9wAJoM4f8kiePr+fcjSUH1nx1HlcRjWWVbQeoCIYHt6AkRwelad2tXtTQR2ABpZ7zii3t6iPWmGQFWLyMhemBI2jLX2C2Z0FaB4FjyiKK1QPGreYLkUwvP3e9PJqZLr9uNn3H/5GhH7bX7ViBZPsOhg505ufl+BgH9n0MeCDICN7nH48B6F3qN9u7uoS8rZGnfTfbG58fxazg3pf2Xt8x+1Gxnv87EXAMvfPqL99rvSDMxGYI9SXz5/tPI4jP71GzYByqcPQdHzej+kd7yR/T4JNPRBdUinL1+C3vt4Epf5F7SXZIT9ziUEZd8fSKNu89wczPmLBnwtf/uoWPK3r+hQA1AB8PUH+/ojuPnrwOJnIPTnHt/rdtIv03iVruhn57xGWS5/QlulYjjGBCggaD7LyJAb654eDkqV6Qv2Mz6ff759j2rP5me4VITDecxpmusyvdNSitlDOPDx1aLhpV766LgpdG+Jl700ytlJ26UVPcML1Nit1/3sXN7nM/nzpbXw/7l+NvGCiwCd9Fy/SJpenMmvNe8lv/+PtryC36zjj6J93/7nf+D+v/8nfve65vua6A5772Xgwg7BrOEY7Z1g+m35/BEg4Pjbl3jXBHs/OOjGUsZa7LGUnq2XzuX/vvaXGNBfA5v9MsWCnp37v9Zw/tL2VPutpXtu8fNEcM+rBpLctfJmCFXAYFj7945yq0zw+v69Khwxe7pJ+ltvKirdYnt6zKOwPj3SYbD/LswQFOkNJYojVok0cWdrJIBHQEEANAFXMSaFXQZCvNyU2jBlJEPQN0Y5uFLbDWMAk6BbqjIiE2ylRAQAM2N98xZ8esZ6+x44HHD393scH484PmwofIXCGula6TFFzSVZytZgFUmp4xmr7ZszvAwBcwM1wuoKPGOMS1mwtIqtFDQ+AVLhISJka+0k0teVEgwIblDwbIO5BuMRJDcgOoHwiOMdAfSIw9U15Cg4nU5YDyvqukA6o65aO3Gpi47H3zkdHIl3EhVAGo5tw1pXUzAx+qPsNljAT8CpnNSAyFov0Im/e/SzCLo5BUCApWoK974pc6DpU3UYbnzrvE1Kp2pea068h3w0hHKHy2bG9i6Mfq9ssq7uDR5+P6HgCUXe2mM3AIZXsV/Lvr6ZeUxv1BUQQcVBU4rSBsKCitXOcAtqa6oZxClJzFWk5sqMGs6bn7h8lvO9BCDl354f9Gty/uCLRIwQBhjs8EGMPww7dLZOMu4e20QMoYqCDioVlUjr+9UScBNGCOcNN3vXkowmtWr0uaVd9utUKBkQVeG5dYI8Q9PFv1FlxFA22t7EshEijaa4QsAiyC361tNXdwhqIXXuIHXAqQAqVSzrog4BruxrQC9DmSsioQxyzUH1qBS7h0wTmc8Bs0YSC3cwE1pDvCMUj0RzdmfHmxMsJCAQZzJnUcv3mXafnZlhSNSWZ0tXmaOSvJ8S6VZtLKYwgRk5atp7BxyCuqt4ulM4CE60Ukc7mCubyw6MxS5mRn9gPAzYLqK61yQU7OF5YrR3sB03xFl64VDtJZ0L94vk2QG5JrIaYAZ/I2IcayhfB/uaI9C99T5Hn/t9RMP4rvMqxr12uGK5sypcfY/BXgEwra0gaKUI4kyPd46UnaN+YDGBzI+D1ekWQFgVPsUitvJex4oawZ6Xk4KQ+5gyDPh6eRT6stQ0Vo8MltHXhKcHzgvDlSvJk7IqiFXG7eL7K3H2AqYIWue3WBSYhPid+NuMuPOEEfjFB+q8kv8osf7nHOZsOEq0XuZ7VBE9zrpYmnYhy5hh6a+HYwciO4d3qBmlCzQVib+OQDIcJbwUiBpHLFuNzTkylljEkMJaN6V6n7JSIM3fNirvnqUAX0Bdnd86edKzNF83DqXz4n/zeXLjucMQbL399Zc8rLsbYeKsKx7yqM8cwThHZf3ZtGYzXszwFSQ/QF45qAES470zP4TdIUxj3TElWXWicyZTtOuerOsVrq6vcHU4gAhom/KEp+MpDGARySBk9gJBbxJZkhbDa+qIt6JyR7F0z92zaFBXxbYbUo2mrcsKloZlvdIoSKqgsuJ00pI2UtzgxmZY92wFbljxzAhq+NBSEZoFipnRNzXSb63huHnKdx2TK+3Ja95GyltzumQrmSOshqVuUbbkEfjDcKrZvxigHqWYYg9o8G00EbOBCfx3L8/huHvAxb7tCXVCJDutC1U1RLrSym8DgOPz4zAkAnFuHW/bpUCdPi4xJ7Fu2SjYsmR0c+6DR/NavyWeh8osZQZgx2UuH3KUSFOcQwaLjvei3FXC2WI8no1Q3yt5b3UZPD1wPtb53AzehNIvNNJM+6LYFoRjl2czkJkPdJwUteNlpIKOjGFOByfcY1SCRh+xeQlX6j0D10YCrqDNNOAucKbPw9Y4eJn9WjqdtmwDNMbhw+l21jg2WMbYHe/EhQTZjqehjigw3rUWzVTClmLcS4oE/k7L4Lw4yHkg47OgSg/uDEIHk2aTICagIurtgtxJ2PfPjITAKM/kmwBgJUIzHk4zejN4Ew2QCKcPTMeT0lwjnb1Fxzo8JnCx91LAt4hnRzLTutPKhHdl6mEELKQNHVyH7VElnbPvfTec7On5I+OG4wKLpudTBy3OXzg91nuEESn1J+dhg7McjR4A5/MwB4ZgvaCBGEwe7W2OrIn+X8KMvk6OWQfs2DdC1GfPd4NISzbaGXVnkcF/JudHP+A01vOFwQCkBuJu8DzEhJ/nK8YjBrO+vdD1Z3I3i5NePErgfMdRVERh9my1zkcTlCedUTbZxJ1BRw4nAuM4sSRlWQeKcZ4dg5Y5qsvvHEcmcS1jCtOZmueghrPQAxXLuCUCGI9S6gKvgUCAlY4z+C4E4hK83pvPn3D6soFI0PBwtk77FrjMAY2cBN/rK39/h/LRskBmljnvhX3wlO3DqJ50V6+0bDB/JjWiAx4CNCLQf9WQLru/wDnncekZ/53tZoHykZ5m2LOVeE4kxHfdn/71W9zrn1229H+3Ajy+MB+BR2ufz2EOPfj3avt1dr23s0sZs5XpRP1jxvDPbnOmiAu/7z7PuMv4kwvymgcHiNN0AE0Yy5SA+/wlQWfx43X5GbwaVybeExMyzFHMAObsDEZDTfyYshRrqRdMfL7LkJfO8Wut/sK9v9a010fS87vPFFEEeINRmvmf1f7oXB0XqcPU6McLmLEIbv/2N/Bvv+FOWc8zpyzvQ3lSwRU+YsPvYdsUnI+P9teJ0H9rE8aT3b3GTZ69N3/ffx5c1PzbHqYv3fPv3P6hEeiXNmu6bgKpX/UIrZ/t2xebcPk5Qk4Hoe+pzAF4rjAEFCCvfBxQxmnLY/Uckxfwca663ZmxWFpiT9e+9Rb1yOtbq0vOGomIruDtB4dgXpikvZ7McO5OlqECt3EstcZn5YkpUpdp2jQTQr1+bxbsKg2GzVdQCESK9pgFRbPY4bg1LLXh5mrRlS0E4goqNdIYUgHWawWpzQ5Z8+g31oh2T6FVmNClopGgo6Pe2JrwDU4PR7StQ6hjwzMKGI0b6i1BesVS3uH4/XsQCN8WR0DKIGnNRU3RLwNOqKBLh3SNft2kqwmV1DgoqKhlCGguBPbe0fsGYUatC7amNUGy8kGjop8M6T1CIeANOh5QUCFFI8FOdycsnxcs62LpphsKaVpagu4hrRXF1hY9s8FmsCeEcqJ1rXsuRb+rwYxN7WQrRMpqbo8CeqvP9i6oVYBewL2h1iXSZiosqHDOraH1bgouV1iqlzgtFWLpMdd3utKBZIksdYzCmQAWBUDgB4U4RgO9VWW7K9OciVEifovtgQF6tjN7k5DxBZZC9H8+8yIHdFKHgIoFdCiQ49H62OJ818MKPgk0jVzy1BaL0LT1o/weEay3b0BEOD1eJtXdZ+Nn1J7tZhR1haDfkNFVhmtK//yGAq05Cow0ioelhlLfJPwQ7gCLtisUih9PTVhI05Aysyoaitd9LVrPlCy9mxu9LQLdB0VCppzouLo+oG+arYCq/i110WgdqylaQGFEd+cbEgGLRjFLKUBb1fC9IJRbui5uhC5TJKmuYYGI1gprzNiszimEwaWgFkFZFixijjywqPp10UgRm3uz1Iq99cCjLEAVNnu2qAEpzqNY5LjjAzHnIEJvRucWAdjwQBgEzQEpMdjwKEfrmxIAUAamASoBOZr1wZq40UBxPItGZvXWIkLZ8b+4Asp6Evufpx5kwwVk0aaLeaj6AASwVO5pwDTGFSYY3SgztpshJOGyM57BaFUoSVPUmaaitJSetUTkkL/mouBh45vGEzf4SlLscV5lZU61fm4RE9EpPSq2NTYPjZxDUnzPs3MYiLqmMra2VEsRas+C1MijDnCu+Cvxd+Y6TTklbM5ilmK91JGBkl1x3vOAktCpOLt3cyyyurGwPrx0A7fNhLACck9maHqzXPaDTYPlqUQDpF1xbfjIwCNhWluU4DEqiHbp2w0nqGFOdz72338PZwUMg2rMedxIMJZUmaYAmfif74ftjR5+R+E21sycYndcA0CN9zpjimfj1ziL4x6RoQAHaBhPnY/zMwHds3CUSWk3lUZYGYfsgFZGaQuBGUrBsUcB8zaWAq1HTMVzqkDfQ3o+iDCcpurgtzUAn814uhO50jkhXz+CGSU0OljFx4raOzzObTpnymzEc773zKN+ur8hIoxEAKwg6rb6J4zoa49s5Wn7fMz7DAFZQT5uI4zNyjPcY6rL3wMOY78p5ue7MT3qIOy4078TRukOL4gbeZj3Ywvg1m8eaQ9CrRrJWJeKw2HFzfU1rq4OABGOKGhbs1Re5mRgxrHOjGoZEFpXYV0dYxYQVbOFMBZeteSIOcOBABSP9hDcvHkLAbBa2RRAnUIHbhvgxCKgLpbyejhcBC6wMHKF1cWUZ4StdTw/bWhtg/CG4+mE4/PRsrh0rOuqZa4YgT/FDcFrDV6EO2NrHVvTNZDe0S2ts/LKuvSlVtQKbMcTAAZ3ChSoQzU5yyLy3BlOJUPfarEyIHayPSkGXpev6+EmapO7kUvf7YjMzjjBSjIBx8eHCZ8H3FhWCY/Shf8VGG9kA7PMJYUJwhQOBiBB64xq81Xai3SeEe+NQ0aEXNsckMB3TgMBd24Ugw8royY746GjcT/kSU8xikgn3BK1kBOinox8ZGXSS9AjP2HuUObfnS8g8bSzw8kpsl34+XY4d+OvW4qclgUZ4DTeeJNGUxLH+NRQXKIE3Mw8+XvSYKd99whwijm5wdIZWXcI+3/kvVljJLmtJvqBZKSkKqm6bc88z///bcfudlVpzSCB+4CFYGSqlnYfn/HcsKslZcbCIEHs+JBdcC6BGByJSJzmnO3dLUsAjg3gwtElfiC2OTJWIvUh7E0nVGeEmEM56Z9Jzvk7sWLLQ4RRWzM7QCYKFhyFpVgruBqtG2QMRWQTwPuYi+lALF2DvJZ8oy0eGF5VnAPwQnlEvi/Nzhf1CIU+lOgNsPcimnDtslalC2BofprMU8vhHonO7G2nnLOgMNUaKDPaEoYN3UNbMEhVnVlziqxi7MzgkwZ0nBaIiurXVOChv+lb8Vei5T0XaWXzvsh0vwdN/6KRIoCpRy97XR+MKWgpfWa/hmIyzydMfXfyGsBr5HT+aUVfj/ebe/pqmIU0CXH06b2MNZ4jvFi6Y2CB5MbkVAHRGzgSXSmNe7kAIoQq6nNSv2JeH3+P9COptU5OWjRU493enp4yp7TQk5h1Ne2zQNMZgrJp9adqlsV4i+8BLJXoqrVyBMHys2zp40yXFxIvpGOMlnCWMCzhV6J5DqmXrxVNmJeidu3T718gYHjrhTlj64Y6TB/G7wzBRFp0Nc//4n9O/dP5O3/+ApSVWkv6XTAr3n/28CD6/wR0e6bEJwLuoUlW/ffPAGaAsEADZv6uDKD/9tm1VwwIdpp8BgAe6fp8PB0+f0h07fff/voXvPz2GwgzQeGTiaNjRegfO67t6PduLBd/zT2llfhEhP0f/9RdVf4KQPvG+30Zgg/259MfGP+3LvkfIJs4VM59/4XWMR50uMPx4eYGgxlv+xkj0I0n73E57RXJbld6HITyxr4yiiucPz6P/5Ilb5ImIzHz9fdM8koTTCTuM4RRTOAQCC3J8PM+MPZucZA5qu+t5TxrPZPx7SSVnz2SJq76riAQQ5xXDqx06cgMf87+/PbxR2je+ZYP795u4qbl+e9aEV4xeQ3ZeQ1YCk4EjozxORKM3qPqOU96xss/fsOy1uSIRlkOXd7HkyDd9ZLJnNLYDhrVcp98XZx8jQ3+TzKVw9F+ZDDfPOUbBLn0IUjnueBfP8h/58xBWT5flFhmiFdThwPs8j7ZacgAhq2SB6yPw8if5+B4PlkRhSe7cJLrj49ov/wSw3VIrVYruvf/NkZWifD6+BxUE1XqloUJvD/3FOfbX4vzG4hs6+QkckNsfmYBrHDEKsV6lqg6aDr2sWMbDee+o7UNTQaqK6taDqIO7lrwtp9B0L/BZpSzaCBRZFbMk47Re929fXlF2xq4P6lDZTSriha84RWjvIGfCzo/A3KDIjcoeEWAMhVVGE6k8M9DtNcakpADqTKl9ifjjRmbBccIHhSoaNsJN936L3o/kMEYXRVfpgH+IqgPBHnSha5yD5AzwTnfQ57s8RZUwxMgtxijo9ZNe463asK1TGcTaUJBbRt4d9aq76mMzKpfWsGpnnB+PWsiAirY6C7olXwP6P/OHZAXNUO6DNBd1/k5v6mBImxwagbfC8Ldx3uFzTJ6GUOzQPv5LYg07x9YprtWYCpUJpmhFgFG2zlFCOPJWf1k9HP4FIpqzmQmzExTP8RKBjWDnzSogWZOCwberCJJ5r0BAZ93FGhv+ZldeKzEmiQPEyr8bO6fKwq5iAooW124byv7nxZlIP0+pd41RknpPrR8G38RJUhvN+4dVM6C6ou04gh+kjloLG6lP22elSeMGSM1p0iJoB4BzLi9PaG2hlbNqVSrtoEoLZS/qF63RJHoq27oC1IEoAHZNfiuVhKFtkSAOlut8nmw0mW3AHEfs78p88DWGkAWQCGbo+KVqLpfdJ4qqkXH1ME2MGwdigUQyfqww2i6UQFXQFgh7n1OfL5EAGZCKd32uf6rpWgFh6NAZKdrxEMoiMILjWFwsyLz/R1dRE/lcLb23hVOt+/oezcod6sYNlp3KDn/2wOhRDa3fWA/7/ZeXYNYxjdbbcANsO83updcqRVO/benYzCeA/eJJgaSVS2vwCJoLzzfdwKAC6QKFMBC6SJ6Wfvk2fhnINQDaTSREcjbkJQ5LsHcg3k/Qc1NQgO82lgkZdtgeTcPQGpAVAMThVbIaJfhPu/xONvj6uAGiGcF+ww6+8mGCmBzUAQodQDdAJzsZbQC0oIgi7MQScN2R54H/JXL6jnaHcmToOZtKK2BRFcDMtp0HajA10iZStxDKQFDCgoPQzfQRA2thm5oW8XWmkIrtxLXu46jr+i0TLO/JWnij/ZMVx4Er1BK6xr5+GK6nEFkuqOeiCCsEMDViRIe8jfOK1MfI+iauaPadbRM3w6b5kP3QB/EDRG9r/+cWqbY+hAc5l/1Op57hh2inaP/LJuuExtJCCD2mBK4CDD8ew8yso0L+n7i0L5i/apLWH7zzUy3JA+gOZKOIyYIuOrciwBSBIVVmx6u04o3g0iJFf6EtAd8/5DtLSbf4xNmVCvvLjXpuNad7Uf7IR7pdIY5f74+iX+58Ziv9d7OAHLczZbzUrd4/0gTPKMZc9/694ZARNB94NVdwEwmFl9e258AIqBgFyptxW0l9rfPW8xfUfm+bSfc3N7g9vbW0FiAvnecTm/aD9vk8/mtQ8SgyiERGFeIYl8DHWg/7zjvKsN5mPxthHrSNjHntzMgqus/f/2C3jv2vmPftXp5WHIyCUBVg+cxT8HfABChFtYAe9008DwEfWjymOsRfXSc+8Bu1eeDRJN0mcFd0LmbfqGVgvvo2ksbErDyYwwdnye5hNzB1G1A1vvVKq89aYGBUhhABcidXmatEkOGJhCwVWjJ2CF9zqeSjGCxcO1HPansHjw0GBe8ZqHAWJ8ITCPLV+UpgRBkdqHTle9Ftv3LopW8Y0wUCrXRNUCynbaQr5SUW6XHyftifCyh/2chLjwgDr9s+4VBIOa0d2XKYbh9LAvL9t067WxnMIZ6xG72WIA+9O55XaDPgCLKQctsG12yvycD7Ggh3rbCW2RYSMB0dpdjsUYAIDNgrONC6IXzMwmIfUttVVQF41feqsfNEa2+NbQmcMh8kOrHqjKocUDi81BU10OqGlSlWAPn8KSG7FMBPI1s8mYKZ6FTXawOaQ9zTcJINBszqza137fdnDB2TSIVqG+g2Pu5XkNClgRp82MyrbpMs7ZU2vLBW/OYftYqhAUbCAOkVdAs2jqMGjDMj2TJF1QKiFfflwCh2/s4s5xa0YImP6PDmx8wRBCdZkCxppHMC0sIgMp2JgEscCsCSOj0sGS7GshammBg/e6hvFk6Q2gAorZV6YRyKug8AAY2R7IhslZarheuPKgYIyBz7As04Ujlu8l9t0GDn2Dq9DY2YbYAQqoWDOG9zrNfP3X6lIiSFfZlrhU5agirPuX6qTGTGJPL26DU/DOWUnlErZHE7HqmJwgUosNVxs/sveZ3BKKz3VdbAeYLRTBnPOyg5D9L5wRkLR2+S2Jl7lGHPZfpX1kHC7cF6u0txutr7H9+ZQidIbVCdkWVKbLDuxbK2w66OSG4htMRLNEYiGe6qcZ0OcJlwl33yfvG15/FAvP57Ww+HV3DeN4QTxDRdysE8ChmE/D6XJtE+qWAP5uODNjzF6UxziYbbvnlAf3L1+VtQsXDUhO75IEdqfe9v19Ig+hkv3/r3Mu/U0HNxRtnHrW+37W/HwE8rDdAIbMr/X18S4lVqJPyWKsDS+Ny2Z2eF7+vI5UYix7n337Djx7f78W8nH3x7OvHFbq9cgYg6L/9jva3v8T+SBYk8goILoPnqkoZz7o22it850eOa7P7/kHf+Ct/cBw8UsX90W5J+2RZfqcHJabFx5Joo5WCN3E0k8n8VO0xpDeiyTNiSN+ZrUVOXB7LcIBAqdGCSf30fTSVVaeCAD21fvV7d7aiOWHw0OT3fP17+/xbqyj4seD5z1BTfp5Xobtpd+14pBmU/m87/shm+MEjSwB/zFoGYCo/rBLPAAAgAElEQVT3cu4nMD4vc3KPa7Dvk5Y5f+Yn5IfCuEb2V9K0X5zLLONOg3d56n6vkoj6HbI/PPvHueS/4/jvrUC/WCg9fD3I/+MMB7CFuWQCeupkSnqqGTpVFWYP/DhUlTsXeIyA8uKqAUbv5No+3IMIeH38qvasEBqp8NjhfdHn8QLgFhlKbhLd9Mmq4aWvQlbNo0ZXVCp6r6xaMESDbAREQMd98sdNEgzWjDhVoPWjWirIAlaSjLIpKNUZq8USSupkxrNnMGuwcmBwBVXGGNo78Px2BkENxnZqoHKCVFjwXPSnVRip00BAvcErAsTWq7SKVos5+rTC7WX/ivaxgl5egH5GqQ2DX9BxVgdCEVArGLJrBWd/g3ADrOdIcaOPNBOsQJ1bLIIuwC6C24JwpIhov/oKjt70DEGrBbVtuKGbmLvRdC73faARoT8CZ3zFIMb4eofbX2/w8s+B27/cgmXg9fNHAM/BflwIFyD6kAKCnbU6p/OO8bajfxFUKvjb//krSilazTnUWbJ5n0GHWR9d55sERAaZLoxCBVsh1FbAxajSlfVwTgj6C4cjVwDI88xMw51Bxg4LijaFuaat4rTd4/XpyRwNhCEDp9MNzq+vgDkSqVBk3IcRJILz4zQHJj8w5woV1Ac1hD3ou38dc18BENzFPDotZbdAOI1IALxB6CZoGWLB2ALIKADOCrEZM+B2aUfZNvB5nwazZa4TbwDOGgajedUQRYjwlhAaMJ+ZqbH7TN6IGNpEKHH5v5M3LoInPpfgl1pdSmim4AgYlciqmqBVooDNJ9K/qTAVMwIVDcPBdpxLQB06VXmpw/UK1DlF6BgoqNbPVOqGslWcWsO2Ndx9vMepNDDp/qwBbehViO4E0GrHEtDuimrRLMBMtYILo9BAgVZ3cBFQqVYhrr1O+7kHZHsfXXt+965QoNZPEwRsxneEAFQCNUtWEY5sRoFEZUIrAmmb0TOZgUaxKBMCUNCkGi8yJUIk+o8LRijlBEW7oFbQSsGoTeeneKWGQRlyCRr0AEZhg9C3QKBXso0xNLGhKq8Yo4P7wBDGfj7j7e2Mt5dXvL6+4u31zRA07F0EBjU7oSOJCFWJBABFT9nnp2dQrWitYtsatrahtYbbm1uQAOfThn3XQP2+7wqZ7+mJRv8C7UU/ikRwD/DqLKvIO9iyBCNg5yqNQANa3WInayWCOv9RmlVjaXVYbFpDLSi1obaKVjSI3tmTEGy8HsyxBBEiQ3xwx5l58BzYnOYrAjCoZ4nCRBS7v+ox6qAmC+BHda8FOfX9JWCxa7EKCAuicKocFiGVW7XFHAgq6lDHLo+CQtNBTTyi+g02tvhbplEWupVxg3DgmjOZiCFS5n4o0Qk27i2i+0p5n0EdeqINCqj6/d141XEWQJNvjJe0pmgtlWpAw7uB7GMNlALxCn1NZCm1WM90T5Zw1IzsUDYDZLiuYsklOqG6z+HIHYjEFhFMdIjFyhBDp5jkihTsIaNnogrBMDnvEOsmF92WhzkEqSBq74xPuaPf+Y2Y3PW+vjy6/mOGGH8Qkw+lVjAxilQMaNUYuiHXdEIv7rizcbNJb1KHeaQdCCKYEzKmkGa3kyWq2HXucnZ5UsA6lyLak7UAxANcCjKU5lwMpe+hDwwePQPhmsxTi+qVul9sT9n+JHj2/tzXvv9KabPCHF33L89F04CPJEexBvIu3EuuW4UB5Psr2TV/xAK8MKg04GJe2qALkMoMLaBK7ldRSHFAq6TCuWe0RIYIoHvaaxaUBnyvba0qUhHP+SQAbWu4ubnF7e2H4FtiiZMA4fXtDX0MvLy84vV8BkTRKkprZtcB5XzGowWRJ3KHjnWwrdfesZ+76rHeN7j7WhlfHNCCP7adRkWb4sW0e0Dag7WkugAE59ezXufIK8zoIthF8NYH+mAwkSVuFzAR3qzH+5ARe1aDa4bA5I4x4aieZYbaQBFIsV7uHuAjTdYphSBDtAJeGKMTyqmikOB003C6+YDWVB/Ye9ekg/MZ534GM8GDuxbuSsTDmNgPShO+42tAHU/dmErB25P2nxUChHugtAgl+jMdSW2HGvaPwxgbR9G8a2gC79inflprNZtOAvEoKQE2au3HyBFstLELIcIGvtdEMAa52Lf7FBSIyiwbV6FpQ/gRzki7rhjYaYHppihK485DBBhd9czerXdutP/S/+TKWIqEK8y5FAQ0u673gFgLA+ZhspiD34dJ4ON1Xcj4GGPOOxvfjAr2eE/dOwBwarcgKuDeZ6Ir/KfRrjvVTfiIwCpjdf0igBk+GID7HvSv9OCQ7bNiWWL1pjtuSY+OhIO0KFTn3EHQE55xjJnmFRMOXHlD3Zo9CdjfXuF9jkks8UGdCpYskGgD3g9Vdcitbjj5vVzvJIClQ0hQLekFwuidAXQIV7B0MNRuVv/QpAc2lCiVScazTAb5+/n8zqIIT3RI6BqgqajIfAFm9R+QT65oUYcm9VrhgFg7LNMdYHzBURKKtVSBCDpGIFaJ3VOE0VkR8vAmqK1qT/pCoNJR6k20RQm7pxAwkjyz7xzl0GW+r4O9tqEbuW7uQXDV5wcrigkPRrckI4EirlHI8hQwdyQjcRQu22yuF5MnD1hLO0PuYFZ5wqLPAnsmh6+BvZAlKnoLp1lx7aekhSoFtzc3eH15AdWpt7rvyxNFNSlp8rEIGptupnoBUG/uNNGaB4olsOR3Y+M9M9CdJQEsmcf9SUh70lXhOcaCW5QPxfwLGtQkBioodH3CnbZrS/codu8h1g6R1KeldjSp7igWGH19Q8UJcqc+tFIqZHQ0Iuw3J8jLc+iSbPqA52OPOfOTr+R9s76ZJaRC18HtwrApJv0Q36IJodMjPOtdX4PhPm6bWniwHQD4i55/+uVeK8thejcEjK9Jt9Rfz79/0fegPMppdoz09ztq6vK3vPP9EbL92rVJUl/9W3uaU/oW6azLvzXo5rJGv/1Meh+CBi9cPfcw35B5BwGgOD4IWn6yvW4GY9CFDtInVwNyMZcENPIqXgvYB4fT8z4f5v9bc+XHtXPXFaT1z+9c+SG/iv08C0P+/ht8Vvp/7WDrSO0aIOOdftFkDAO0PJ6uPz520NHsWV9rzvHxuHj81T9o+WLhN4eBaSBbfdXudwx9xp/pAW8VFpYYhEiQmwFy5XtPL69adGbyxtEv2DLSLnimCYvQ0XDcZ9ep4wIJBJi6lLd3sRlQ35TLSlrWMe4S8lCSHoqQc/68vXd7D5tXWfmjF6wd9/l7b+LBWjrYrtfe71vH8exjIc7xmZ+S+PTBPf7cI3/q0EQtkxu0Ji39yJGHWzCh7yc3nHvQk8L8d7p6H4oK9Ax4U6GoGp5QQHav27/+glIqHv/+92Vcfm8Pw8e6RVsu1zcteQxOZ0ZfEZcpcBJ1iHndE+v+WMSA/cv0BiDQ/97jq//Oo/1LNEV/4CUOm/tbmw+YCzb5pysel1eEE1K9KeaF4cj2F7gBNd+anxjlflXeVCG8Q8ULbqBC+AbAeb30Yty36WsyJsTMoTzCmJJXrLpC69dsNgDB3CDX1odgwQYk5596o6ca6PMWgnFy8AxlGrCjpjgaK54CyRRlh1FTh5YaVZHpSdpZnkrVkRMgPI07fwkhZcBDGCe5AVis8lINmZenL2itosJ69Y4+KyoM2o305XW44sZfZhP2TywQSKT5FUBUwp3TmctKEoHKWY3CWrGVD5DnM/h2KtdpXwN4AfOm0O88FP4RHn60KY/pjXCxXdfA3AzWUNQJCtFAfQP6+RyB9EInQGDwigxqmxpnhfD88gyvcuuPHTd/3UCDnNQSsxGwvJoAvEnbR9JciMJY28VDBioKUCpeHp9we/8B7kYQUxa096EbMoC4E9H+1YeiVUP3BePRuwZRzBLjBSL38IpddsOV5ugIQcSx/334LBMYC3hFu7tHAGsQgGd1gPqW08ef4GHOrBgAgJwFxa6XTLwAgBPEMSlUaiyCz39PoMjv7l8v3HFDLsuNbymSlD5Y+adWM9ZFuXTD2ZKL/G/nEiLad5NTRWz8xoAM8PCMMQ3MebBTnecMomqVFxrI08DqhpvbDTflRvtpgyKAPl9AB1po9lT3PrkebNFkGMRYGQMkJSpghYcFibTSeXgA+KA8HeFtYm0FoTx7cks4h8iVAeWInPiLBsdpdSBjGg6l2BhJEw7g93XHJRFGEZQOjAZAOqQodKv6WVSFqtWQAqyS0PeqB3KKBRcixVqgf4uAuwfSzEE5RsBPuvPVDYpchSWuMNOUIVG5Kjq/mg6mAd7miRfkDq7Z397T/WPufQsD5tR0ruPrdagCTcHvONtkFKDBXAIUXlAABO9yZc9VTfe8XtPOXO6RPeeQvOdjFoSTPCt1noBg0wNgOp40wKlnqaOuYAxGa7xUlCnN+/ybHpMSGXzMGkg1mSmz8m9OH4FEKyG8zQKZQ5J4rrevea4k9fX3dQonv70jL6Wz9q6Hql6vRFv2mwVX3ODUKdWqLkrzHuOHJgLWapVdJotradHuwZcl+aCiBQKAgA32ZEJ1Mnq7BF/jOfZYS1OWPLAYNGf/WRzSicn4OxPEyltsndJ8zdOnBLQJ0vNtT0cgfBmdcR5KaxTfTsNY2AMvnpgy6Wl503QfsvlyB192GMQZ/v4AHMbZ9U5lSLzE5nyvkKFrBEICHAVF+SLDHZDWikQKhkjIKkkDcX063sOQcJym45tE0ytdTynrzwRo2V8SjuMr1UF2i1ibmJ+FUtJBh5/H7+Tn/ja6nN9TFv72Luvfc+308GBavNJxyHGt0Wc4/NexRHIuee9vir+LV6vauisSUoHP7xAGjz3OkfMZIO0ZC4OtDhQUq4RkszkgogFmloBPJGh7pWrB2kIVrRKYho7PHFvLnrVnCPJiWkDdq+UHA12TTgYrBGPngc6MbjoqiNBFEw/0vBF04cGtWYnsNE0TmnsIvKWF7yfvFBYQwYJA+dEXtvM9SagVDUpVC6QNrSAvCcPQ35OKKhg5aOhyuNj1BLIyagSSgJ6cwppjz6Qy6cjl49wucC3qgsD8UyGgWBqDkFWFJh5vo/IWPzPkT1FV7s65/J1fHSFY1/NKcgfGIFOSuZQ5WgY0STlpDK4vOLylfeeyDWET04Rpd56Zkr8c8SgKB8jnGBMe3OD53f5lq7D39ihOu2sMQKYMkMnrw64K5cX1lMSfTI5p9XmSy+ks5X88f7e/xaDEo98z0QLfHrDtMvkQY1Yru2UYVJZanAQHSu9JMWc2n6XA0VLie1HHXd81uK9oWPom7XTC8aink9Ja73q/khIIatVkH0PTcn5bYFXpTmdGSVOsELbtBO4cSU2K+kcolVCkopShiabiNEsG0kOxuTTYbWvhiTmHw5PY8pquOp7pfYAlFHuRx6TtybvhYmfRS/1e6lexhGHzq8iwtXK6iGQ+hrwZ0p8QKs62ppvyo2rJjqUa+lfFoDHHARh6DeBwFJOLTLoYrnPFvnDfVUKaCAFHgHgbq+wcsPd1hAfXRVyHcLSN+HzuOb+t21kXXDCWzHETafVuI53u66fCAW/ncxIMCB6TXj+tky0CzyBzsX+ggkrQdoRU5vwZz56JuXMvzeFJkp3r3IcIiLfVsRMI8vICfHpQ3ga1JcrtLeTlGdVa4LlOrnN5QrtTeb4/PcXnkgNHWUUyuSOxNryMqcgtenTxFpsT21dezW+8KsYvVtF34DkCgRCjirfO1PXRJNEHcNlR+CsEBYyvcc9YVJMPy4S5LFieVQxJSzmCNWgJ0kgkclyka39eHlnsXPn8VtZ+6D9yHJ+Z/76De/wygRPuRCyofmUQcZ9Vi/Bg/h2AzUVlutJliVfgP5MG3aMK9ruTs46kwmW8HjmAdW09Psqs5v6JR/3LR1Ti2tFtHs5QFJRryzm5088fWR5cP9bAmAdvXa77ABZefrzD4dZL4h8QiI05SW4d45UPv/Eu+e8V3cXH6HxDEkXSOgdZfgLqe0HSY947Di+bpLi1pHH/nA4oJAE7t03jv7jH/HzSrPGU1PpCeTTcLXGVwK/t8/zZMVg+Xy/N55+8M55I912ViVJBP7D2f5T2r94p7/mf5J056C8AFGPtE4aFrs/waufrCAN5DfznsH8u//N5vkSeR0RuZ+MwJxc6wPVnX/Ls9ec12syfCyb5H5ctz2fWSf6dvPW947+1Av294wd52o9dQ3NmI3Auoj10eQbOvSIW0H4+TiWDnlFwb9/Mmov2UFH4A+jrE+5IM8ycL56hwXIAeLWfN1Aivf311xR4GOhfB+pftFoSAnMulmlswgicCD2/FiYz80+caBiW4Z+Nb5qGTQ6KLFOF+RLubCoFFn3wXlA0HcgCq3QuVsleYgyDhzlkJqyWKofK6Ls5y0CYsFwFADO2uzstXK8N1CrKVvH2ckbb1MACD+w8gFGjZ2H0LrQK59NDBb7egvEKd/YJORPQ4BITYaslDIlhAp1IFa8tzakf7r7xbGgURRDoHeiPRkECFFGnjjCjfqw43dyCmfHwvx/w5b+eJ93SJcMg3GH/OrD9BShU0XlHeyg41RuwDOz7QB9nVBTcnj5AWLDvZ3x8eICwVvbo0qsQjyopMzQoQUSpQfUKkTENAn6NfePV90Q3MVh5FZQPumdGF5zuFFK7926GCoNq0z7yJny3U0WpA/u+G6SYQznqDNdWgQfC+DpinnU+PmA8CXBv1WyiSS3XaDeYPwSC5/QdQLhFwQd9jsCcHMD5ww5iYLw6xLXeq97WuNaVOipWBSQCPusY6kaQDoW3ZYBwguC8LKgr6kDKhI0VyWO8IITL7w6KIGH9xR0k3nfPnWQ1AgL+TGNy2bmdHX+AOZitMtrNPEI4TgcPFKpaIQFCdHR3R0vRIHetDae2obUTtpsTTqcbbGXD6XaDO5PUcVnCeJQUiKnmdPdAujqOtMLHadodgBjmRIRWDfcxYcI1B9BQGSppNnIpKAJ0YsxdonM4YRFlxiNFadodnADC2Z5hFP0ns1c9w+IEMrMRXQm3LFgm5W+uVKMoVCxVQeGBLhpkreYwDwdeIXjiOkQhKsX4Wzir1IqIIFBU9ZgzCD7mJQKkQUYSsUrBbEg4szgYQOk+Km5FYfQxojJU2JT65IRaFDLC4T6rsaIkZvzJKpuF5/pNI2yGRcg/hjo2pHvlx1GFm7stHDM5AAeyoG9SI53xkACSJTKCx61ZwXH3g+Inca6AJ9QlTxgugSc5UFxH5HNl970w9ub9PRFJ+0laWwTR9Yl5pdXYIg+Y2Hj9/p7VLIQI0Mx3MdozDbzVAoU2XGcg1uvIyGyuySBfCzyYqgk1CtVetbInJQI4TwMw9R8RiGjlpljJP9m7esBET9P5kfRevsp5Tr2nrT3EXwbh0PctZAEW1XkQzi4/3x0/lN89vpbk8MPVn/5Y69LrFDVrgzM9+L5z+op959zOdbAkdMSXhgy1SOaHdpJnqLvM8X0GMh5m8xUQ4P6OsaaGtmCyYq6+/l6JAfLekRStGnwv5JmYFT+mC+TI1nJe/nv+ITL/9mQNinxoD5yv+8uvnjJ+5VNzlY7H8bw/+W/TA/Snox2Yjo1yOHvZlPq3VbkeHVTX3WxOLq5jlCs8aOqTACJwopVqqfJV3Mqx2STC6B2jijlukoAQg2BlrVSF90C2gHogD1TC6DmR0r8TzPYWagbA9o0Xqir/V9ZOtmc6D1DXoP+QgT4G9tHRGegRvJ+OLMQYp1wsxqsi0IIZIIjdJYrQIbCKOxtYzDOge4OHIkYMrb6rNQW5YoF07cm9vWnV5mzb+/tvRLik3RmknveAVkJb4Px4vLPdAByBao1PuY2KVBVu104dzewSQQQSPRnR9VU1PSZiW2YHHDC8iec5kzY+rvwwtWIBQRpF8EzbBFlw3ZEuygzC0tT8bPwKR0+AtiCCJydNfcbfWyBLBbqwoa/Yvg7kDDvXH8GskONRcphnd+FfurZiSDhq20vsodCv2APtZIFQd8jm+9pnlGgmDI2U6OeBTfJktYRA4+dbFfowWrB8z6CTUJPix9SFnJwFWPiWOBUceRIoKuPjvCMrjEMRcsCCYog10nvww3md8rKyVRyPCFwCoVx4m6VcDb8kvUEMVWjKd59z9w+5/ZTXrVCBw2jPQO905K/UYTsk2y8+YLKxAoHkBKdQl+9QmeutD0OWV7NNUMxGxFxjVqSY8TqMX+9KMgQINq3qrwojXqomJWjSJAUiYmXXSQCHWZyJRDZSs/3IJop9vyHRBSZfKM4P7N1G70BqO7EQICa3dLvbv3G6kPhSCbOUqtD0ADz51210oMBb9ATnXYhwGcS6fpzHZPwvz4N9reqvQIagtRPu7tQv5QmkLy8v4MGopw17Z6uglKA314OO+RmLJib5Ba4MP/1a7itKeUDYHM4LCKgfPmjyvZ2riC8Clhf0p+As+r0h2RSzidkeEvyez6CXE863HLK3mu+OPgKsnRQxZO7z8E/J9Psh72F7yQJCwwdLZNcbKVCP66MAlXvs9BU7dwwiCD2DZQZfQ+uZxtqVyUt7kwDCPYBHuAaeJ93fu/3yCfvnL6GfSjrr2lP88O+OgRU/Xg909f07rcexZzq/87l/FuMw/v5C64nHyz6qeEYnpCrZaR8BCDQP4Mf7L3+w5fHCjeAZyxg+4favFa8G5U6YvdK/0h/rI454wtQlvn/u5fFMOjc5L4eA8OG1vxIoEOgPNPfN5/zES6XXmBr5yr+uPeG7pHYYxXvnvzfS8KVcucc1zhs+v3RU0wMVbUrCxxI8mcgKZ9QOaLUoMsvA4bgc/fuJCI5BsV7lZ6/xHt0Ynoi78mSayLOWyM8C3DQtgvHi0+H+Xcx1e49KXPa+J7ke5E/qO57iFYfXir8FqhbnMThs+0VCy48Q2x84vkVP3zu+kAbRFcFWQPgccytQD97J/trt/L8K0EDYFwkhETxvuKSZCqSIp3779vffYy3z9hU77b09O9913d+yaF9Q3TXO4mjTeLjJvAdd/fjy+DNo6184/kcC6H/WcWQ4bpSwCIr9zEwm+v0BaPiAbuFvfnRvisHKmSlDpaA9fIQ8vVxUoC8ywo5yGJMznfM/d2y/tumYNuOSeaCZsDvy1+O9/XnTLZD/8nc8Coj5zhfzRkCpaqj/7X/9DeM8MPqO0Yc5SM1hzdNpSQ7DDIOoZYeV03sWKLybCg91DG204ea2GMyRYKtqyJ+fO6S+Yts2YAycTic1rETXsAxW2MYEFUWmzhQIKhE61YAKhVWrCnkCAIGcFtJ8AQeH9mGOfX4KEbb7ir11jKFB4fIR4AMOyHhitIcWN+A+UHGPgcd4gs/PJJoX1Pt7RDUaWdayA9gxrJq9aKV/q7i7vw/68dtoxW7DySqAe+vJmIbR/9kMhBkw1KFM0aj/fwPkpI7QGw/MCehU1ZFDujduP35QKEcA23aTAlta9ehww2rMA6ASVauoBLL0sMEMeUri2V5Kni5FjiTWzvKcvpi7UECgD2rYS1rj4r3q7kj7Ib0yys1ER9ChTgXE+/3hRq+vpWh/57cRMTUPol8VNnZkGPesYFy+2+X3U9Csn139+1sChBBBh2sBysQSk/VIMQAZAimskI0Eq4yWCO4WKQrpzAEuHPuXreen0kFR566G2PQzeIkUYViQqw6rYKaCQhsIjEFAYYXijyoKIGAVY35L0TkndeiAGVVmr8iAoLf94b2BpQOjKFqJsCuqqZrEeIieb6pBdkKBAgq/eBMap31YQpD1R5vpWTpXui9s73uwnBgQdfgXIkilJRDG7pAUo9NYt0nz2akWlXs+4rDPaNIA3CF/4IfuNIVYNZSEUcFRdVdQ2CqomSMBJZ5oazQDB/pfraoCQAr37LI7nn383cnS554oUBych3pgXfyDH9BeBSvkldPkusY2BkmVxdlRKbaPMkRjfCvBjyT9bwxN9CAS62uLCDg5jc1nTyMpV8U4LycgKro1eKPQknVrtidFHYs+KrtX7tMKIKIQJBIVSnneowqY5jrmtaqlRE/jZeyQuBcIAcPuSUCuDxUqKK2gFXVg16bVSAGRCASdEq0ylb0nPaVgh50fgXcfEHyZKCpRMhFkmXDkxUqnltPrRqoPQpI8SPzU54ymmy6+nz3Q08/4fT5b4m9Jz5nB8wm7aegGMvdhWnh4/cR06noiwroPYg+7J4Yt+Yecf5PydJ8+mltOb+3Q6gUO5RskKABIJhwrABJW3hePk8XhMYPnljhmc6fBXKxCVDATLtyTkL9b6NPXxPhkWoesbwHAzYcPUWX39vx8oIzMO78nvf/4kTX++XuWBcez5oiyTFvI4nD25dX6tzuvgbkeONJMSuLwRI7oi5tkgV9YW8N2czP7/B5K8rzFkj5q1qnORECy9i9zXIDJIoPbz9oueKKw5OCeVkcKugWpCaTV8mItYRxCO6oZZQmYrbwbCp9Onsiy6ohRIRe8SILX+A4gVrr0RkhsTZ1LJAS5Pm96RQRPEfNyPEQM8v68VpC3mw84Pz9dXLPd3CGCa4QZZDoc1yjfq+ynY3whlKgcmte7y45MJp5mVb3wEuzQ1l0A8VCE7RqYOAiXTZARWbADiL7prvNIqAwx8EigA2Iuc/A8/nadyRLZPZFYXA7ZaGKfmB3iMilePAZA2kIBidcH2hNZwEdADHPQ+gDtRuJvn/hX/l26kapq4d43FsAiH6c8m/91pCX9Ux3E5PtcACJrSUBiEMUe4Mr6j+kcFoBmD9KJBTo8Yhc8V+ckgshp+WOd7AtKV/gJuyUy+FS3lmz0wTj3V5zubuKN4xkup0ir1AsoWr/0/Yy63QBF+dFgRiFG33ecTqfoA+7yByKg6igdSAk2U4ZrW5XJJ5C+/9bx/teZ0+cz1ysiafXK6UkFQeadji5Sagl0kEoOTW9nilaa8xvPpABPfMJMfMs2B135F2tCNEdOa/WuiFirJNeDyWiwLG+dr9FTKMrswqZ7b2IPPO8Y4wi/gfGWwUPllDZhS4UAACAASURBVCfh+KOXhOysxyWKNt7kDClarLDygqyLXkt0y7y/tm3RYQDCy/NroFIVKuDxBoCtTbvTprUxWo2i6/Pzrlrju9cvkKArACEnlR8emDCpHL7/298AAF9++wdmGpOg4IRIFDSUpSlb30BnAHICblQGO2/zLeX2qw9NNY7J70SwyCzrbA7GI4AP+trpvZ2fS3lBZfVdSBHTVXIi4+U+POrbefac6/n7CWAJfkmdlXv033kp0ln0DBw+fOfIS3prfxyrz4/0cP3qfP5hPLKO8MB1L4aocO/vP4OBQFscpAmICQQr5uSZrl7+QwdBWw1katb/fgHwKxoI58w7/uXjqIfr8bP392rczNr99/Hb5ys0ef1QnVQWWgofAK7wwkSFWYP4FgFel07rGPzIgeKQEaZL5kGtfDJuhPDzLvafYLKDdW8edVZ91hpTKqVauxeKhG6HfieZ58XYk84fPiS63APL/oVXvEOLvHiVBaDL/XY83D5cEm9FA/znvuPUUihQRNHAXF/9xvp9i7VMW/EbJx2O9/nM9e+PNrrTuet+q43xzjh/fHiX40m/5ZElEfNz9xPgDcCtzTof9l/566+oRPj7b79BBKgeb8MBMcHPx2wvmz+n9M9n8IiqcXn8+Ey9nwzyA7f9kUv/lUX7E4//6AA6MMWaOzYcPokOG8vPFaijtt4XNHrA09cv6HhahC8BePnyCAJw83AP+niH8vRyoTgJNM72lj5j0V7EDsG1fWroX7WycH88o340WEsA4+uTBkoArSZMYxgIBNwLyJimnNDa0/oM5C2BxDlMoBhnmRnV04BhFtzc3qKUW3z5/TNqKbi9+4jzyyPa1tSBXWZ1qJAaHiyCbjCHKjgKaiO8nodbDdhuNwxj/qe2aS+qpw7UjoY6nehUwhmqNigBUrDd3eFD3dDfdgxSOHYut+ZMZQjVpS+ts51RVFgV0eBZcfh2wyYZJAqZDxOiSVSoYNT+hrc3N3h+GQqfXgrGLwPy+SOKCAZNGN3zqyZjDKsa0I31AUwFjCcUfEBUAeBlqZ6rteH82IFPwNPTE07bpv3sySC4xo4xFMo2DF9ooGQ7ndSh3DtqsUw4KqCbAbwplbphC2FFZhBJ2eU3ELyq/4JfMZ5uNdgsCqvJPIABhX2059580H7kL0/PcFcGWT/B7XQK548IcLo7Yd93jMGgMR2HFYB4MP3rgDwx6L6g3BfwowZXPdiquoZAAoYLsb8pGifomrVTUxoaHDQJAFK0srfcJSuWCG3bJg0IMFir7BUuXx30pSptMjP6q2W8y4099XVRZnKlWoVcILTZllsOF5BHZVeQPpx30LUPR4P+XWuZSpY9yKvrkD4DJmIBEdm7EXhwKFl+gc6Hoh1ohSJPxxATuEjwXbgD2Bznu/XsLFXhIIsFVKKS3NbFnYzK5xTWsJaKWryqPmnr5MGeAtIaFriTqrHEc9Rpw+oAZ80WJU4rJGL8CxgygHMBtql0xZpoSjyibQWPoJNwKqFY8Hs6beZcFxSrrMzO+nBWQMcxABBP+FumofzW5Vg4YtTxCIttTudTUnInA4UHMsbw3qx6nkJ65wCIBlGvKssHTV5Es5kxCING9ICPfo2i/dy8F59gBsOcvHJFDgBrB2HIIZbYMsaaUha0Gf1WEQaBz6nSqa3/0HGzWOWNpbM4p18cljgc2YnrsVJx44vWzWom5uxdezDw4nf9JzIrKpkJ+pp1CZwvbQiAiWQfdHX43RPbynTYlGLywh2MZSJuuPOXDNfdoRFzP2eaTYhVZzK0C604Ss7rQuABjL6HPpFn9BjYK5EoQiFnSy0G41mtZ3nVHpx1BkzjXqBJ+0Z7YE7Qzybr4b3W01SRr4FNJkeIIc2p04AllyQHlvjeimtcNq338Ip0AqbB7T15yZJ02OhLclhwGtcimJDtib+K7dej4cZeOWQVv/5TbAxeZavrU8whK1HZVUChyzBYkw9VKdB38y4I4ud5EkMek82ZK9NEinBRqqFzWHqSbV6SorysqP6AUgCmkKHDnGITbn3SCkOAhUf4Ofai7KClRXUH5zkOhx00OYMa6luZc62a5M+awN87spT/I8fCfOJPm337+x2nnu+RH3j2xR2IopKbjF9HlXfiW141q/xttg9RGZSDvBT8GuKyNR6lPwWaCAdoghswK2odlQJAaQoBHHxWRHVdqOzR3rcDPj1C2iszqgEFKGCIFJNjmkJNQ9d/t88c3t0DDXlOla/PCuBSAB6UbC6ePCTLF59vS0SdtA5XQtRG8DZgzsfse0WAUT7Ow6UbQO2EwgDeXvG9o789Y2qcB9rKZJC9dFPRvEJNrofO747nTMfsuh8CqrpI2BGxR51bR5IDFLFiWEUuDbAn5NhwizEobz3UD6WVtdRF5/EqbEXlmsowGdKat0YphqhUYIF4hwZvDZR0bNDkk94qI6u1TkeKSqMzMowufSZ9y5I5f/3ddKvbegcMJ811gtOmxHNHN6SW4rTo7ych78KV5rYm5XuKF9ZagmVqmyeAWzyByGO06jxXrBWCB9MVxc3mK3jLHDtCttLUDy8VNpPTq+6RbeV5mHObCOfXNzi9n27NZXnQp4M6WdBqQ23F2h0Itm0Dyez7TkQg6wcOmg51OMSq647OM9haK3kxgstFb30XdO9bTe0nAkLHyQH5i/2b3yCVWBNhOS+3BnEVO3iU057LX28dUeZ+CP5/FshZwDtDcFYebC34nBb8UT7HtNR6Evwt4m0mq8MSZAx0rZkMGPoHLo/Qa913ImpzQg7nH6fvwJ+81/mq3wNbaypnmMHD5I/kKxF6nBHAXC6a753UkqB610fy4eHZqI5N619KRQFCZoStaTyIQHh7fQkfjTvgvY/pGng/zKPreofvF+ATABW3oI8ldHDTEqwSHjj/8xG3v3xCH44cxUHCDMHryzP683NQhFg5MdMOlBX9QYiApmuqiC5vaLgBv7xA+Ab1Y8V2fw+Cew0mUkY3P++wv+lgDxomp1WQP6GhWEKWTNQTaxUmpeBUCrowuihigxzWLtOEr3eey/AXmew74R6dHheEDgKwyQMGfV3QD+lwjn/ma5zHcdRCf0QjBK5XkB/vSbjcRlntXMZxuF9uaboG0dfDP/dK9J1M27f7/WzVq1eeO2Ud9X+/nXsR6DdG/cuvaL//jo4fmb8fOy7EFSb/+5njiXyt9GoBof2FwL8L2v/6K/rf/2Hvd4XlfePIMpWufHY5cvyB0eu1aad++znTCI+nZbrS68o3xuk8cn2n4zMEosi4gLUd0wQyKqQ6GwTdoCxPbbOWdsrIKywRhxN/SeNWMTB9WTnhZBmySLSIjO9jlt7j226H2Eoo6Jsh2Mx+7zubTWe2lrYENX/a1VlDJDi+dxBmW4E1meU9qlvvR4efwa/E9yXFCc8k+GDT8tXe9x6z/eXyVFeL/qyN64846B8/uwP8vAFBjbWdcYS33353lf2b974APDgc3v4487VrvOBz8fdwPePPmTC3///Tj//4ALof2SELZpRaw8HqzFESwxqPgvagBOPMDVBYIX5WmB4B8PrlEXefFPDgBAR4cyjkB5KzcKIRpzKjci/gwSgfyRw9QO/dYBpUOSv48UPi/Pn0nLnriQRy2MpuxJL9XkvV/tDmGAcB9/cPaK2hEHCmhtNpA8R7VM1KIjZjWCtNR8wxGFaFgoj69zODmCGvAmBglB2n0lBrQ6sNW9vQ2oZWW1TS7azOzv52xn4+46Z9xHm8QMBoaKBqCAHUAp7Ks5UdjpgHJ7hzxLu7AU1EcwZNESMTjFQKuFQIEVqtOA9VVUshbL9sGiz6yqj3M4DUHzsGngHcoeAjtgftiX5+TKtABLJgunPB080tSu34+PCA8/Mz7n55wMvnrxDRDNStbosSNXqPtWinTYVqu4EMxr7v6NzVWJXkNHQHsSAy/40lz7WDYMgLIB8gg2PvAMD56QXZuOcx5u/7zHGaGWHiVr8GbwYrXJs5aNig9QmEYvPp8xNODkwjcshLrGE2Sjz0Vz+WeE8eZq6FIkKqAPGlAJiOH/GJ0mC/KzYkkKLvUgoFPPfcXZpCM8ca5BRHToA5HmFEOX2kf+5puyqyaPmhz/GenzYn7k/2e7mxNvsrI3pf+mcFZXX0JeULfmeyIAubw5kVup+IDL6bsZ/PBqMv4XhR6DTEs/2uhYoa96WgEFBrw9Y6Wml2vV6gCTpFW09U3fcKQU7BvxQS0oLkBAjOYDTN2iSJPTWsf/oYFagN2EnhTwsAS77wajUeHoznCaFpC8dUUKHj5tT/lUxZH0JAERSpBg1u0OsRaIA5fRTmKd5p33UIzOBak2Jv5pAQqAiQ+AgIWiFp1gOHAeXwT7NSYwZb3K8jKYCRjBEx56ZDfYruzCFdezuNEtfoXFlFTXJw5Z3hgZ73VPK5P2egBZgQZDHgeUHQU/B1UDJMRAN6eQO6Q8kc6+UAeexzFY5JBmAO/SIS1XM+TWu11/w8V2vmnep8iVlQigZ4Zoay0u8ShOakHYRj0/ibMQ/niQSVhbUVsLQwGqdD334MDTbkVgClUAQaYk2ZQ9nO3kw3Up3Egn/ioBMliyWvDXkFU1Pozmawqc2gPKmWhQ59PFG1ZC1WCATUAhHjfQJLJNC9oYEPh7jWwEjw+2VKbf6SQXtZf27nx0WE/CstZ3iVoP3l0NQCC6onC06MLyzOcP1uJuzMvR/TmtYe4hDSswI9Xx/zh5nNjqJ8pVqCmB9FyGToALgg18LGg8WTICayhDsHYv+VErzfqzcB5Qk+HbqcSW/1vr/GO9jXuVAkVCh/xUyguDgKiDgCV/7u/tMTMmw0Noe27yTrDj7FOoF9P1sF+rVn/uxxnbZ+7nrMF/yZI3S/n3ha0geIZlqg7se0vxJKie+QWptVgKbkPSijFNPVa9BH0iMFcIjtasmj0ZaLELRQWp0JhS7LYMhHzBAyaF9MO3DKJgCsKDjgAZDuIfBE0hiQVClq10c1vc7lElSH6SAogeJyuQaJv7+3hj7fADyAC5p8uY8OdEJDMzQYD8hN3feanG2nu7AL6rbh7fHL+thiPdJ5AELo533Ra8M5ufyRBEOMXfJrHt4fFnReLgj9XviMgQpvS2MX6D1JXUvMXdMlnfygaEBT5LjOMWV0toP8gaFzEyxQQ3PuqUDzx63y1tAOvPezy7RpWwOetDMrzaesykF5gQWGRIBqSE9AVMiKFBQLapEhq3hNSuhw8zVtEijleLnsEGA47ep+G4OCAxWaiba+Hjm4HjoH/FeGDIJEUogBfYhMm1MmrfrPWeAwZV3Qqo9FJsWy6bn6Wvb+V3iX64wjUKKMGmkGt5H4/1ZO2PezrYWef359gRDh5u429tnYu6IoUMHNzclsJXdyT/05aCDJoykHjT5FtCKWC+pWsHOPdXT9SWTEvHhCgK/jfE+fLwp6zvp0npn3JcNR9pCbCdHOaFGxjVdXh1b3pPJRgGH20fAkgDNY9lhPJaHDSNxmAcJ27L2j9469D0t4Mh1YaM5TekcNvE760URsmI21Jr8wXJCnAANZsK1o0caKrnE5i7JOSPA3/VtbN/RhCWSW5Bw+kKTb6388QdY1J91LocslHe9bUlqg++7Tp1/w5ctnABrIVxo1xKDDuAVilduMEQhUEwmJw177tn6wVIPiQGsioI8lGIbr0bHPLXn9yz+/4Pb+IwiE89MLBgQNmthQvZ2grQ3NW/uLxB4A1G5mAmQXDZK/vJqe+wJ5Auj2TpeNCOPRKOqezP7zYF3me7ZuCE3ellp9CFNmuB6sQa1SFJFNbY/5zpC5Q1cVP907SWtmRvnVbOt/Tl3D79fxZdoFx/k/rB7F/K1res0n9UqzCv14uKly7UjpW/O518aCKXtL+p5w+R6EQ+/yK4e2LJjn3L9/6jcPSj8XcXrlMwa0N/HvtFz7s8e1dfszD++J7nO7/27U8vff4vk/dEwD0v50RJn5cQ5OS+h9/3qQ7KAdpmcb75lOGB9IXBdtxUy+kkx/W+atWTcE1qSX1U8wd5sX+82WU8aHzKj1hMqgK0L40EyKL3r/4tsAUoB88hlO7z7ff/IFwJP1D5NIiYbtu1aryllH04PLoePFP0eldGXNj3Jsxhsuj/e/+db3oW1dfOrP/+8+fE1DJXhnLN+9j52oJYRZNsx/DIXGJ/u9H2gpH+8F0v1sD5rzcZH+xcO34//rx/8zAfQ4SHtS1FLQ6szAHKLZQMW4SBA8EmMRoLWK8nCPt8+PsCI2vH190sx059XpcQWB9pyGQNYjnExhe8Ioxlw+fQIA7E/PABGsSGFRJmJM8BqavHmsete8e+G+pJlAoNUSjPAAIhOzGbTQ6tutNasuVidBuzspLJcwPnz4iK0VtEogqeo8sMQEWPCcTfn29+1WeUoMhXgGwJajx7KDqsKGVK86a5v9a/PeAKqWmqPVO9QHg3j8vOOt7wBppn/5hfD81EGl4GR9SBhQ495efZAZUC7gw4hJ1REiIDkBcIWsaKbxCzRLvQGlNoA7xoBCNlegPUwDeAamAOAFd7/+DaUV9DFw+8uvOH/9DIcCrB8fQqEtVNBOJ7TTBuaB7fYWY+9RkVeb/iMzAL3HHg8N5BWosKWq1Xs4I6pkYN85nbOIQUPC+n0PEG7A8hoKh4hgPA/QRw1+Oiwz1TqVk3RvAKBaVQEZa3W80kPXZAPvRWdrsLUN5/M5aLbYnmFm0EcCnpKiAYr9ERn4+KgffJz0X6yH+VxjF95ixpBrfPoqhYC+W19H670KIvS3gXqyOU+pjFQKyq1AXjUQGajNuI29OqIi3Z5mgskRB44KwOxjPo04V5jm9/O6WrzCxmhtcXhIKGAePSjXgkciqOYM9MQFGbphGAMoFae24dx3tGZ5cK7gxdh07QczqHcL3sMcuxtEtKKs1hLjmAgMsTx2vzIre0jQ2oabE6PVZnOgFFBrReOKttl71oqbojCLwxTW6uvsvRZFYf4UnUFhBIcH/cdAG0PvfTODSN6ygFkdIYOH8tQxoZEnzVlvczIFHYheqnmd2OCOB0jhL4kiGOBOMyKClIIygG6Q9ez7z4NISE7YSBmcQSxb/Jhbh3X2IGh2IMWekBlwu6aIaSLACPh45wM8GIN6XOeGE0eygWcHrDS6GA8yHWBrcstUxAnqMNOYXFsNpbiGrHosGXPuXBQGqBrNObS18UanyZDtc4/4/M5ghCdfHSZIVoUxV1jnd1kTE3RtmCkSVuZzjo6KHNS+XBvk84k0wYQVGr7aHqLi7+UV6dq5crA6g1nGss890FWM77PwEjAnmYZVxI0m0vpqzoQz3ecGkQBWU7/z1ho2R18p6d4y4brJ6Dagv4thTohAg+imT9k9PLFmnU17kVxFGla1V935n8bA7Ttdm9AcLvZLmpW8Sro+HjgXgGmiDGjASNdG+TTmXk107rTJALxucnVOWlBCOIJ9/vw8HgJFJZIHhXKPe2btoCWG9EHskKuIvUyFTPZN7ZTCSk9rZMFzh9gGyNCAHHp18i6vfmLWRBwWzcIGXLetKWglC706LxahRGd5H877HAlCR8/x7GuH60ffP96xGqlg2dQxlz9rtdLVX5cji9iFkRgtveuE+IGn2zN9LTzpDU6f0EDy1GUIrVWIaJJkKZqcWEj1K5dp4ld4Uk+gpigVegDdE9hEBLWpLFCdaAoLT74AeTBxza2PQLz9Xuwni0D60GC7Bb2EACklkM3yPIU8Sw6t5Rnx3Tp3fvF7To+wTExvysnS3teTmdF3DcIxq90KiEHNM0Y/Y4xujj4+PmA5bu4/qd4MTVhGrKQNNejGR5feVS5+ifeT9F2WhXG26D4VllRxrqr44Amt6wLWdRkY74LJTwIbLLEj0VBcF5XdgcohaT7MTo9RUVTWRsJPK6FDk1AEzxXGOoTaohsrYswMgJLtEQ+06PRopVJ3xyfZOT4WkUBiU75WDeJdIvnIn5ePaJNwCI+Eg9hplXzFPPFcNJHQRGNZ7D0GykzCDDkYOp/up2H6n6p8ZGKT5joTQjaxJXs4dXn1tRTXA2l5Nw92B0Vc3W8I286TrPw7Tx7zY9tOcd99P8fn59dXnO7u1AYnR7Gh6Nm4UjHQ2oZqtnegyhFNe8+uc3lcq2DvOyIBIr+jkNlN2aHvKrcEz1D/kuoPjuAhzjWiZckVJdVGfpg603XIHzT1jsS4Ql/QdGGllUoQ6ehD7aPB+2If+bWTVoFpyasEZx4474LzfsZ5P1sg3ZKB3Iby/9C0LwAENLzSbA4/Yhm7600ubUMbUEUUmaeJpMsJQYvVfIksnPREoNVmvcSTXIk9OJtKLCkOMQgxHcDtqssVe1fEh82o9svDL+pXPL9qQYTL1/VuSS6ZvinOZ4IvOI9YrwOm7p4DTEjzCQDt48fF1vF398S64TY0tNr37fEJAsIJtwBeMOxGr0+P8xmm07XbO5zfXq2dZML2E0WPydpUT3uHAdDzs/7Os5UAPQK3D/daZfn5a6x3NpGNO6vPVSdwriHUgV4J1uauQIrKoiqKMtWJ0O7vwV++Ltf5WhzXt8QzdG8zsyZ6ZHMKgQsVc++/H6sIKW6Xg4LvF3Qcg+decZ7ZQT4I6/pfaNe2XWqi72vv7OMvmeeZGvZBlK29HOYAmD2//fAOmx/k5/qeO1fKY8nPCfpO19W//Irx++/LGvyrx1Vd0Qcgxw+ujfDaKJT7eKFe5pTfmyL3v16O84rte/HZtzjY9473Z/Pas+2LSABzPUYRz2zyaH4eT7hG1Eg67zVhCRi6n6JTuU2jtqcirnkyeUlt/Y4sPva/26mhY1zuzkhwOvCn4xhZjpqfnlVNT62kiXAAouUqEWGrDWOcQ/ar79XRra5O0fXjsPwXxWOuC1yRdZLoxW2g4ztebAuaZ+t8K7W6u6HIyhP/jD36reOKGP+pw8epSToqIzl9R/bZDbQJ6m6afkvn+PsWXMoDn+E8RlVFZrmIp1QItIc84Y/0sZdla7nemvfeH+UM/zcd/1EB9OOkHx0Xs3KS0FqLvlceUHR4bRFBuSf0L9o/ZgGCJAoobP8XBBwDWLN+M7GK3gQ8Bkpt6L2DcAf6UCDPqX/zlXfLv2/599tb8OvbgRElwwuXhrQ74tez3IhRo/x0Oi2ZTuqYMGjlUlFOZL24GbV5ZbY7AcyR5f2tWDC69gpUp3gx47Sb8ayjUX6nTonqmfxW9erOCw+wUCFstUJaBcvQSvCuwfhCBXWrOLUzqFXc1A0gTZQonbBb9ahW+dvKeNVUTmmFK5mvAO7MuadmTysasJQiKNzNGbcaFIazqsLpvmBYtXmpBft+xvnrwOmXDcdDncoVd/cfk1GjAQ8i7WG1nRpglTQKTauBj4Dc9SBVKQYFbcEoKugvwypwVWOITuXBKPWes5LGAlsAqgjG40B9KAZlqE4rh+wDC0qbDmEWAXfltEfnGpkjMj6ydaHBWh3gRCkGUykwaL9MtUcH5QcTDAJ5NoH/YCzfHKfhhKlNnbxQZ1nvGjDfXzrqjTvYARrT4BPs6K9AvSvoLNh8vmEOizsGP2ejOF53EU5hTHxDUkgSXEdDxH8juq7E6tSt5lLy4cQ1R4cMLYNKXELcUFJqaR6sz4EIUwiLaLSMADUUezdjfKjSZTjj+27BsjqrxJaiLNKqIREgwus0QPsZo3vQVJEcpGmiD5UaSSxTAZ1qaq1apT6YsXkwd2jQXGy/BtT8GAAVVC5agS4UgWI26HatVtfrvbcnQAo9bH30GNCKTne6B71mbBHdm1xY+7qTT7h9a9VyAgGPjrMwKlWMNgIVo9pc6q2N9ySlU2URoftiJjpTNmPmE5FmxJIF6fnSQs4OPB3f+j0LAx2QmhJETCa8Y5dg8SHIZSgnnHfhgEnGAZu/y6493jgbFi4/2JKLHK7bA2zi68QKvfdNZY7WP2R5vMnZvO9S0G5+fvkEsvdgMb4extFqvOWEDZ+anOyhSTC6GQupo5Z5QAaHk2w6Ru3Jec0t+SPzcx0LzYH6pfZ8ocN8LtNEyw8dF0XwsxjsGVVCLQ21VDRDo/HEsci0LursK+l2Xm0UFeZwRA3PHjc9EM6zKOZVk+VmoDSgqEW1OlMGlnUSWBLGtSOLuzxP/uqUTpo46rZHPGg0g+M+zuCRvkfsHPZ1MvryAM7cL3NYl+NwnQWA1AnH6sl36VoSAkm3MQzk1Y2QngeRAIhMqNYyTz0YTnlypqRcgzvWOxtI9Kr38f7Pa1CSEjJSWd7zuOd835QI0iR5Z/sQpBV1SwA0zezYOzw1aj3eY3j+rlDmJTJp7GjJ/sRB6b8xgm8w3clX6I8902We03PsvfkMbd2iQTFNziTUpigYc871PhrwtQQ0480K+y7QXEu9zxgDjImQg7QPuyF3gLVFlvN0T75gZsgwaOTgaYmn+raEyoFlh7N944k8aUd5QOf6fPs86eJ6sFKfOfUs18GUZznikc2nt8kBobXNgmSOEARL5hsYMjB4oDJjDK08dOj8MQYgjLqdZorLe/RhH+8vj6CmPWYJQD+/zmJJffPr179z6OMmb75+jgSfgzkhBUDdTqgmv10fHd0sdTknfdT7nyMcqwy/pzNkMWQigUP7+/7zBArlpd7TW9uCaWsUQQQQi93TkU9MpgGul7h8K0AzOvB3N97kAdmALA69PMlbYeupbLQMu2cRQwQxeplMcK5QdlJJ5quTzx4dW2yVkyIAk4SsDWc0VWS3rMATOUzXsMC+B4k1AcXtGgrDxlsmqByzYChyYorL6dUKouyEPui0+Xf/a+ZqzXnRJA0KeToTDzVhl4iwm214fn3F1i5t9jRrUP2/hPzxn/5c1//ERQURAEfkMsvMZLmidhl0P5Aq1VzZWtc5kg2QEuXl/YSci9GnW4Y8CL11pSE/URigRhG8dF1U/T4Do6uN5LJToPSjdOvoUfPevlrK3zkS7SMAXwiF1d9Uy0y+Fqvu1lYPOnYx9eeowfOi9gAAIABJREFU8+TxI33HQPhGKLXxydcqj/DFc88IYt+5LjFYO2Tz8ITrxPOJLKnU9TzzQ4VXm2Juf04oq8wYDIAYX/75T3z69ZdFD2TWNdmtQICgwRPVwafO462ELhK+DsNxm2n9bOpjgNOgv1dOjJTQr/rj40w2wPSt7taeL1rmHG1DAc7Pz4YmM1CLJVGaP4Gjnc/K35YkFKw0wgKMLwPl09wQM6g9eYUAKA/3eq/n50Wnr/f3ivb19QkU/D7bKsD+9QuQnitypLWVj/k9whb+xnFBs4jtvHz23t/He/zsQelf/juP4b0j5vbKuAgzF8hZVIaPz8HxpysP+tHgeT6Oc5QDUQRC+8uvGL8zBF9Uhv0uV6//9x7ffqr3Q8+NMvLxI+s0T55yyPe9ywH7OHTwHxnbzxwXdBzPdp08lOyLZ2cJIMBMrMPce74nPWkz68t5lX1vDgkPNFi8nS5SojhCx4TMxMb5rCvyWkxHOezOnGbjMnqivV2+5fePmYAHQ1U9jz71j8PxHRZ07fbxI7RGSSN0tXxZmfXnxRi+88h8/TU9IIoSfvK+/+7jCwGfFvqcR37H8re/oALo//jt6jvkhKBr753v6QF4xhVa//lX+P/V8R8VQD8ei4JhTJ2smrW1Fv2NhzlUqHcjEMvqRso4IyWgp39+Xp6RoWmIHMZ9hczyKvHoAySi1dQE69fIqKWAP3wMh70AePj0gK9fv0bfFaRncbr3/vrqd0ZFrlSl5RqfE89WogtVxq4yxl1qUfhTFlA13VsQwe62bbg5ndBf31BrsyBYWRREFwbq+NJKVIhguzkBIOz7jq1V7LsFyUgV+WJOhVI0I4oCbtWGDIJgB1HBdtJEhK1V1LOdKzq3p+2EsjXctk2ZQTijCH0nVOxgLuqYEWArBC5alaEBfFt74xbNIUJrA38i1L2DSWFuSykBD6/0kLKbSaEknQF9/cd/4fTwAAJh/9xTHO0ujK+6NYxuCQbsziFd5ba15Gix4PgYZpwRSARv5x2nmxMKM97edhTreUso09hxYyWMFgo/virrb/EOfohXUUuLIVG6X6nF7jdpgAwfR4rvQx376ByVSl51S2zQWaWgthYmKkDA+QwwoYMXGi/4CMZTfOZqBbMns7iy7dJb6UuD9Ern5H20mLF90KcyC/ozY7sDxotX6zcIgPHMKB8L+hNje2jwCpJGwFnOUFT5LJ4EwK2N7i3mJg9rXkFG4/qB611RzGlVK2MYLJg76lKgZKlotWc4rKlvUFXwOBAL2qklviBW7VkUgr3NwE7vu2bdi96FipZQk1WsUIzXYM0hs6VD6dFWwd+limh/SgIIBZ01gaIUGCzaALhCivZj77yjU7dqn6HJFQWgUVDLgJiDa3j1d+KFpej+2ewteTB4G0DHkkTljuZaKnjX+xSrHhqjT+egBdH153QkFikYlicoUOeP9tR06FZ1cpEuHByCsqJCKkPMGSo895+IIwXofu/oKL2gbRpclFrRiKzdxaxN8yWPfermQfBnjkQyd9hBZkVLUMQ1B2UySmZPbV0n76XJKWAVMIDXtK9wHs57F6K1l5I5dWHGmO+7JTDnPCD2g+7l1mo41nQ/EBQeW9dBvBeWAN7zmy1YMXliPCR+HAuZJ890Ndedj5hzGg7oKX9dKQ1eZQaozL4aySFlRpo9JxuqClGtq9Z7N4c0w1FOvP/wYIPX9Anx3sB2/2PFrY/C7xe8Pkavhpc6ow8Vf/lHmsRJY+Z8rQYzX2r0QNdq9BZ90AlFEzQGR0uCrMZ4cLwQwJF649V5lPjPHJT7L2dCkX+htJqD6AsNSH74FVNE8nmHr2Tl/fqoSfti8xxfhmFJM9nNe1Uu+q6PTwcr9vtVA1IFcuh3vt9jDQwNKIZgOqT2KHe68XmUgE9vlvAI2NzC0R5gwXmn/ZUveBugcN667IBVcpnMio1SCAoHn3t6zpdbg+j2LJHZJ9v6tjsdllI1wSQ5jdn2n1es+v3rtul4AIzzGWtC1HGSr31MMUdZP5nF5++Ztt8+9FLX87ES2dUL/Dkuv6b98p0rl4dOeqZ1bUVMV/HWI7qnalXdu9FmPJyWhA2nNW0F1bGfz/B2AYM1QEwMDOk2hMmfPZAzSuqz6tWtrLxPRDQx1+bgmHQdW1EHHR/FviyEstXJE1SYA+QtYeaNVOy4Gz09ghkuH4x5gkUr15bgw4G0tJ1NtV62OrYxGEM0mMwikCEo+669t925JmrzDkeO+sbhlefnF838DefiOF+cO7WAbx2m3TqdG+8kKC8Yks86sE2TX7qOgiEuA2cCyDGoQGlNVQdA6EXOR50uQvdBpgGZzWGIMMAmUwhFAKKKsPZFUCqhtaKITYVQm9rEfe9mchBKK6GveEJXQPALx3kiALxntlhX40KQPqZOSAANgtabeJJwRs25XI2pSyjnyvIj5AicNytMP3ufbufHruO3BofaUnY5dVXtX67rJiY7WbTL8KxKMMGa7BaHcRealamhF17QUX6xVT9SeSP5q4WicqsOEAyO/X3q3bYT9q50X8irrvV3HtbegVznwdzPoUfPAHoxmSsuOoVQicFiiV6FzCZwHVCCRkO/Odi1EZgWR4zS313uRYUw5lx/j7ervkPxPKKqugImrZCNx+UVFZebBgU+Brr9G5Gw6ayStH2Vj8nGWGlDoaYJTsyK8Dd2kxs2FmvZUmuJRJVh6IK1aDUzFfcF6Jo7aqS/3XXVzANAHgjJE+V6jl4VOmRS/4QIW2tmH+qzHcHLGIk6rguBDENnYEcBpUQwxNaYo53/fX+99P6tbRBro3d3c2vJ5sVscZUToZuLAFC5Adb1HsLegCH44XTxxC/W55usJdkcR6E7naYP+mEtyefkayGO2WWfiqAbTZ0+fsQQRn1+gQA43X/E/vj/sfdeDZLjSJrgZwbQPURmZGbN7sv9/3933ZUqlDsB2D2YgJHukaK6ZnZ6blEVGeF0EoQwmBZPl3uV+Dn4WJIgwLWCxtDACBFIlgXmMkfmljljvXDGC/ANWD5oVsj29TscDwKEmw8PcO6NIOCHB1BhzdxpQVpcGfzxg5Yf+KIRyQPqSNQzr+rnN08PCbSM328A6Ms3lA/vN/d5u2bsuHZfbm9B1VvXZyT69Tso/c5ziNJMyRtx30OGEjF+Jd/lfYVuXjSCXfxLAebKaOv4a0bz97J9155LduP58scnAMDxfy94+X+VpvMnAn+e0d3/ettDxq450poffvsNwSenzz/mEH/crjpu/ZZQ8Te/e38PEDhIDJgcXh0XANhcAxCyw4aHSH1qLXTLekSAiDsnuc5TsyiFo3zQ0+SIKJlPlplBSbb7euG4BMS9sw/jl3DlTELPGEPpXR8eVU6RDZNDlzLHI5BJH/9KM7LJArQ9iFAC5d3cthfo+vU3nnNX/1y6YJs76BonkGjef4P2jYAPgZemQ7BScf3d/vkZ9Y+P+GLT+oR5f4Pg7n/9B17+8c94JmfWyLgN0DXzIsH73c7OTdfaXr/1q+2/AD38l7R/WwN6FiYCidA0onu0nnqzMhq5tz8CQdWHgtdvbjK7LtQHapq88dXmKg7moopn85hlZiwf1dgjjwN4r+RqwTTmXCOF+dpANtwrM8i0u5tcwGhmKEFiE+0uCryJw6KJ5z0yVAeo36m3tjKrhRh3nz7i/PyikZ2gIAStN1PQd8joxpiOUKYOix5xQ5y48gCkdcGMuR/DjW9TiaQypyrb1udVo575BsyvIOj+LnXB8eMRbT3hsBx0bSyV3DDOTKNhu+qB2QVTmIf/XB1HoAXAcn+nBsPXEw7vK87PZ1UWBDNs3mrGIPt49fcdgGdbbwLfA+vT9xmphReIvA8PYQYBRZ0OzuczlsNBlUhF7J0aRQMRTe/MDIyh6c+hnsawVO8eodFHB90Q+uvzjxGV+Jhpok4TcJZ39+pdTqsanoMx2Ebe5HSIYVQiCgMiBBuhkWimLA6zHWm6K3ZHCk7ppkyoUGHvFmqs1P6m0U0s8tyFOAJVtg23EywIg32BRZkNgbBgeW/C8ntB6w3jucGnMp4F9d0UDl2wUuHY/aX3mGO76m+db/9NtgeUDInZJuVzyv1mIzZAca4uEJQrjOV63Jyv8f6zGxiWZQFY8YriVImxqqA0DRNuqCUxmLaQ4Uhp7tGX9h6tAW1RCoRgQMOzVIBBPc4mD0bpA6NarU9mdO6amQEMV39Xq4la2NJCH9QIAmZwd0UkQmnVx0AbDbRW4MDhcDXMS3Maz7tLe9YfwJ3RpWt6T7B5UZmhiEpwGAVkUcYO0zMtKMxoL5BwUBrGfLuCamMysj0u4ml0FSfPSDNd21mPNu2tAVco+ykJtBcKSptnUprqeU39dU95O6M/3ZEiK2uvcsupZW/ieC+2Hs56jmX+mb163+gTomvqdSiDxpkUqc5EEvTympEyosl5rr2PURWe88z/SKBz2htGT8l7c2XtzcqWjT7ZaEUgU0o1cB+Qqs42MIWvG1Fan/V89TXmUOGLsG8+/YyE4juLqjJcQxYcOeVM2t5Phqss2jkbbSnqymo2lux0sBForjFkCZlRvpG349705/DpIJk7lfz9PrdIemh3LSsbL9rGiKQ3eQTWCMOQ4TlJhlsxUcZB0Q61wyjsTBt0WP8T/siy+yj/Z9ddWZ+EdnLltJXQ0LEKRBhlCIQE3Rw1IueSaF9eAkT53AEUNSKJTNoUCn3JRurpLCDmPDTMSSIbRuYe0ub+PjQq2c8QkfKXmh7c5zDXI2/FjBJ0WSCfrWSI803YwItc3+MftimT7OdyjSf4reaSq0iqEZoO+VWwvHzjD/nDzesMNgnIkf6OS1pbsa7n4Adba+itYYyecKKAUnkG58vg5aYkOXSlgXlt74wbCQTmHrJerKeIRWdLivJN9OXKOd5EqSV6pTWYMUuoBD6RCz4r4/2tKfAa3jC+ondjqw3eba30jBXDr+ZgZCVygIau9cAs0n6gW9wMW7kE6d3q2w5QUo+6OenanscOmeHc13KapuZcrnO46a+LtdneucXz+75UBdbWZ0zEb3jTDMOT556dK75UmTsMpaJrTaKKJWGLjhbaGK6IpsEUoHAoYp7ZUJSuuCNGng8FOISDjhlIPX2z+DuYADEnIOMRi7D1Z9wbKf0ZZoGmMZWCLCrXOh/tDla5bfkHbOhGdjRw3mELt1fwwcjrbVHPPs5BEOkaRW7yn7ih3bYu4MjoQBjoLdOAn8fgjWIwEmPfzo1m/8EzxR2734mVMxz5VuSaP7EsB7jx1GsdDwiod4At8mt0yLA0rQy4niWW0j54ADNhyzNFlBohnGWV/s/a8BEhvNtPCsA1mZ12zqfG01+gHSJsFjNdzgyVUnl3pIDObACDBR4e4CnUR+9orWO1+uXNMnW5cX/yGRPrsJdgIcvEAARM8lGd3LkyWGaWwmLOQYBmHWkWdKBy0rBIVZ/fFfw+V2bCGBPE6rcHD5d4a5eREOP2y3bemdWJyTLq+dqaZkizAmJs3O1oMzYBZKtBoHg+3XK5Y8jyxvFwjPGez6egrRkPxzkTIJxAJre5Xass+yQ4ylkdRAR0O/nN7Jij+zn1mtlhyktoAFYgiFgNj3REe+rBDvy8pXNuyJWI0E2f4A7iftf2fOi6B66FpcrtzucqnhXDL+oQOsugOK2YbPkABpmeUwN7CKoGaA4XCSy3srhT5C3eLkneFhAg7yB4hMh0D7iyErHO+5XaX/PPb5nGXtMD3u9NjD/zYLP/zTiusVlXcA9D1SlCamSLNb0yXvLxXqJ47Ys00vpaNPqPmp3WTYsEEVCcUT993Izm5n/9L6z/mCbz/Rr8Z7Tr/f+Ez7T2RGpQ9DIEF1vzk3dnTDHxLCZ+kZ2ehnxNrkHfr7W9TlJfRxdwfo2eOyam+BcIuVd2OHb3vhx89Evj9LH4a5xuGj6EZaeUIVfn5DKJOB2XLT354Tt9LiYLboI/Lp7Z7sVeCmAi9M2JhpUuequK9huNJt23CW4QxeUavDXPv3aaXmwzbmW/jX8dFn+l/WxWvzsbx0HKFV46+BCA9c8vKdvD5B8cBx//+ISXPz9f4GeOvrfvmVzfvPc/b8X+Z7R/PwN6EgTElBwsM/LIDXRMWgvdmTomwi0xyDxF+xgoxNBKD0CRO0AGznhG3TGuGZDePbzH7bdHnDCjYP0eAXA6v0Y0ADANTwqczyA8hBJ8fXzaKBcyA9EMj0cddrvHr7vAtkcSbrjwUzN9Kd3DWJUsh+MxCCABlnIRmpaTCJ7MREz4OR6OFoVKkD7Q+jDFVtOoD/dCJ6BLx/n1pFHGlq6dD6yCp6gX/7EuZujWyKOOAUgHj2LMOgHMGNI0JfxdwenrC8BqlCq1YFkWHO9uQHIPMQ/UBoJQAeQFMG8r6oTOM5rUDfiDvGZy0CCACYfjAQsvkCFaB5oZjRmjtRDCvJaK1goh8/wl1HvG+gTcPHwwIW1GtYQQ+PQdQ+5BHywax+45HA5GCEekChVoanwMweF4wBiC0+kV528a5SsfBMebW3i04DBBICKx4EwEhxREdibCGCNeq8vQLwH9Sesmr9LBnypKVUXPGCP6dg90J8ZDKNWTnALJPExi40tG9U4hnI7eZx30NJ55Fk1Zj2eQ3MKhtz5UMwKUiG70+ZFFoA+LApoehQThgdHUG0+GHpjj4QgmwvqoqeUEwHgawL3CSjelBRGhvqs4P7bob4spbvQK+clFui9cB2J9qOi1xaPs7E72NPd+1esx2hlxo7mnR48TTc7sbhXPDuft1MEYWO4P+qKq/ZOlZpcx0KVhQFDM0CLdIGnxlIUFtWgUuhsZJnPn50TTYnpJRTakpZHCBaS6BotG9ZzsPJWlAsPZ0HTmbEqaqmebDd9NhY8yqsxsJTxM8DVFe1tXi4DRNe5jgHvHIEaH4goRNdKEYt3qtsGVJf6e3iE0dM26euGvXZVEtSxwRw82R45pGDCGn1QZSl0VVH4mtExDM8N9wue234PmGSwo5rgFTHOZS6MSStQJfdPZIivagsFKSjuBGSGGnSUGQJqmvq0K92zOP2LpdNmc1jZKJRcmgIQ7dgLPjrEmI3Bktfw8MtTLb3jk9N5g7fjJ65bCFO9Mjgc9SnYKWAKFYc8UOg3jmLh0Fx4YY04KpxxpvpnL5ineTzWtPgKNuFHPswbkfVLbCsU4W1PcVkcJ/DZE0HpXI4sZqLIA6ntEsCwsYXxU/MxZrWDr4vQRoDAAe0YKgdckp4BVRVeOm5LBvHCkbPc65fta5S4gRr3yzUrS/JsAD1YGfI8v4SLoSSj58jN6wML7m5Jzlz9PaatdYFcEv9/MtG55oykESD93M32mfc6wJ7LZK8du3q8gpSX2+Tr/y3MdgIx/nG80XjBS6s9IcoJoGt8iYMvSA5mKbkXiWkailIJCmnvJFf696VHhWEPHzQMy2sTSYjTGMiUE3wqDmeF0bkYPD3MoapayuxSfr9dxn0YHDhynoicXT7XLljZ8+lY7fppjENTloGdrPU+jhkFL7Gf+HQCykxxckevf59+5IN8vNyMGtIVQj3K+HN/1F2RO5deaR0kinJGchvUhWNcVzEV5VRhvaI4OTF6GSHvqrW+yBfiAhjm89u5Oo3q996apaDMdI+XriIel9ie4m+Xoff4WsSxHfv6nAXCzHha5568IXmIARCOMok4Puivcg++Z/JfvzKWjKWFr3SLr33AAT6Om4iGNYi5WgkhY30U8efHWG+zUqsxbK2BOgQA0WnRHl3Kd84uw9zngH4Kmw49hznTdz8Gcp4ig2zyvOUo53qNYf3fSTHRws/e6mxyGIEAGYbDymxgDYk4ek3QojJQwks2ISjXmIXgGLpodjDEdOyPDBdShopRiZbgUp3QrHcWlqJOI4UkyPqMQpwxFasgf3RzVYY7jYueGBCikxnNiFIvgHsRgNo7WHVWvHGKnIdMYK8ELTgyVsjY5PSCH3qT6Hl2ZS2Jz9LSz7HxA+JTKxA+2m2502vKWxql7+SKkKWTe0AOD3UAXtM/6HNuJS+ITiBMfvOO+vA/aw73R88hnpsyuZRYg8LLY/vRYA82wtqrB7biPhvP13TmgkO8NIiPOEJmRalaCQYAka6RZbtkAfQ9NGdAYZ+RIt9kS7rFMD8EIkQR/p7DIOlcYz0pqWBcI0GfGETWga/T5GInXDDnjAAJQb1SuLbViWRYsNxXLoWI9C6Splwgz4/Z4iybdnCwJ3CtKLRhkpdfWZk7XgkZa7iOyUMCcTK7M3Pmv6aBFELK1HmYwNT6fCEGf+rDyWVSM1zDYEnPsN32inzHfg8KshFLUYbsuBx3Gi0ZcD4PDiZvZnHk9EOEN7Gtjw9A9eHp6DF1nYQZbhDk8It5pXjbgkEVkB2s1ZefEVut+4QbllsGFzJlIr88SSCb/G45uT8/azxCQHAMWm/PXdzf6/NOzpo69v8eAoD9rCvd6p5HtzWqWuxxQXZ8avLKuf++rnqemLjyRyj3OyHYdY54mnwgEHYTT45MGz7y7VwzwrYM/FLx8/Y4FUQQStx8+WMaEYvovzdLkelJ+eA9aVxQZWHqH/Pk5TFCUB2bNefgJBTZOAs5fvuH46SPwsaB8VV2w9+WajT3633N/89rPGU1/5lYm5sxFR6+NM79npOt+j59F1ZIa3cV0HHEnRafKMxxnjj1z1Zfzsuu/wNBeq4vufe8553ltGyXcTE9e/lDez3PavpWX6vdafvMcH1xcAJxLwvUVudaXNq8Vn4599E+Ykfj7Wsd7JzvJfMMP7sMv7Mfvtot3/OD61b28glN/uIp0/Qs2vv/KUCafYkEkA4hMgG8Z0MlkTzIl6bi8Ld0P02UlvgpuYKVwxM9T8OdW6SgmUzhvUcyRzZ0xizvuBn78vebOcaFDtLG+JFl36rOmfLDvYy9fTwemXwOqF4P3faaOyRlOWhgD3bTfnfl86q89ef3tgm0ddL/un9+L773JCHb95Z//DLgowCZDRkn9FOQo8609M+Zz5SxnnJh1af9/a/9+BvTcRMKz2WsiDSKQRVeJ/XZBkhOju37/hkF1Q44y0siMFgE4PtxHmsv68A6v376DEilZoYDYHp9QP37Auq5Rr7ZbjbFyfw8XGQWTGfrZgXMl/2Ra/M32s6NbU/mRhDfjq8Pw5kJEH5Di9SOnQA1jCF3ZWg9HEx41uqStK9bz2byPu0X0qh8Lm5+kQFCXqjXGZECGogIiqPG7FLThyicVUlilFxSPGOQBkorRNMp8qWeAOg6HG9RlwbKogNZFwFggsqIUZXCZKwprDbkF5r0s7WLBMwI/3t0BAxooYPW3Si3ASWGh9dVSKl7ZNVIlDOMO67eO5YNHf9wCeN3skUBCCEekWdQNEpme0efzSRm3F3VWKLXi9P0MGNETEby+PGsq+xRF1p5bIFXv2uUjYgKNg43iNRhbhxfduRcQ3aG+I3UCcSGdja0M5YfB8ugQExYvlIQbDCwb2XBGI11jcJzYvYBwu7nPn1oeFizLYikRxRQjyooPANRGKNJy70yEAQZbnu/uyi1mHA5H0Psz1u8qnHnavmbMvhuEQC4kzLlmH64t4d7ylPm7fD1Ha21XYk+iaPtXVpLSXDnv8wJaN0TxilQBUjwyBlCmQi2EcUvjB2IwNBU5xFK0k66/WAiGGiw6mFUhEREIpjBoaTwy1Kjs4xJTxqADjZrVxCvgUlUxbxkF8ty9Lp8rNKtAUwkSYeWi0XFmcHClVW8Mqqq0jHR8Nq79jo5QDBosW6Rbhyq5iytapViJCFJlp2Nug1UWjfC0iYMSK8NQw0NPisYxOlqDKaRVsSNlAVdLk+vGa8sKErXbzYiaz6wbTMMQL4Lm+33REiU0Zb8rt0MBnh1rAIRS6VpPiZGO6MFQFoYJdAOjGVRzt65EfBOWMWne3MPtqRVB6HPFYN95eKd/mkV6Ghr9ZjfYe7IBbQ5b+tZu0j2byz3RwBh+NjIj71FrsUC2NlsYFMnpEneCY16z0Jj7O+a9TKRKeJpRuQJBgKPkcSGcKJSAEGi4QYpC4PK0tLHcoZg3Jzq2qCIqm88zG4OeXVWoSIKvCXPetcIRpbWRCQYWrZlsJdH/BB37QNNVKyG57R6kdYu/xQwHsunxB4LEfJ/qNd0QkOfo45h9brzRJeEc6bG3Uecek2fzVKleczeM5Yk+ZwMSaNaF148U5UDcScuHxmYUZct8A6ixkseAVB/vxAUC5WeaZfZwmBc3nhu/6g4WRYqV2Zlr32WoA6MrqEsBSw341VThJfBcRL/ZWY7oUI/E9/HZ+u2N57FrMmHrh83vu6D0V9q/LG1KGlIe256r+GkvvzgUe1N6lUeQqiF5GrjPrkAZDSCgFuXNmmVHImrBP3kkZvfayWnv2HhijTx2p2cCRrNzQsE7irhCSGcUMyczq3eP4U3ODJQcEMQNfpOORL4espIq5rQxtY+W4cVgxw+TR6g7Hb7Yhys00fuT0IhnZ58gRLZeFbWoHMB2HjYKN5nGuQtdkyNFR4RvGM99JYHrULTnUOXiO5rnBhNnXlN+EbDRXQ2J2fvmbPqJs5uzvghmhhm7Wx3rgxDCI17diVEdIpSHL86PAlYWAMYfTTl5OqgaLiRnARw/DIBStL8pRoOrMVwsMkyeCDCczmqkvAmzKVUBgDSjGg2AWSATSJBeNv+8smNX6csPFJGCqaSdYgU5SQ8YnwhkG0k8lZMWDWqygJKFERud8QkISj/iXCacY+cygRQmXMyxqOMsdgM3nLBjgfaRa4EMBKDiPBihHpZI5Q6GZdCYzobOi6kzi+K46bypzgca8Kr1wUcbaE1l+cmjd5NDxM6vxJByI3L4Sesgc8d9NVze3TzvN/k6Bt8Dn/TEi67/IXXycJ7fzxVMP9Es8nyYo69G5xvOE5OvacB1Gh684dkZItuYl1cQUT9/MSfLqjJeWQChxeSeYc51wbz8AKfShhedTlDQrH1EqGMHA8mJhqCG2yzwj3OBAAAgAElEQVQvOW6TvO6S13ryw14KEdIh5wI6YFOuatIeQKPVk6MiZJMlIxqXkMN8hs7jzb2W0H+6HJbxse//j+i/f1fuFB8Wx4suJ6j4EEEp43lgyItGzImYhHWa8/M5Pw94GUPdvuv7tx9bx5yvAqKEcWb0EVQ/5MH0Tu9xfprZPuZh0iIZeHyCi2TyTUeQQyTat+8KG/U9+NMB/UuDsIA/FHSMgIvptCRpj/0n4eudMOvzjvrfdj9ZRihJsJNQ1sWabWjylU2+LuXP5zOK2d4kSKdv82y8D5pynUBgCOofD1v4JIL88yucy7oGh5yuDMhPdeUE/NSI/laKd9n9HXgUQMHH+BC6zj8HBF/jvfmZv7vt+aN09Td6yXzR7MGbc6lv4gKHy9DvOF4zXY1fD5oaX/9ra5LPxv4du3ns6bmPa88P7dQaW1YhtzeWWLmZ2YM/6wZozaSgMkMzRnxcwW/bMZkzUGtBz67pzrzls+vPOi25No/tVDSLka9LTt+/h4HfgbDc9s/JlWs//O4aPfjJGnp7y5Fifvr7T2nG7VkGeXscv9CnPTDzpW7XqkGQikttgDjTg4PNt6aT4Lgt44Lcd/7u/7Yft39vAzpciCFE+mbzEPPUvHaTAshITA3Uo/bw8IDTt68QPKG8fwf6psCZfZgB4PTtCUSEm4d3ylCLIp9OiBroGVG1x2d0ADefPsThH08D9b0aXxnKiHilOT/aZ2cURZPvubfToES4oL+C0AdxmcQuhAf7fioPCO/fvYvofCZbl/0ptSgiAFrTTdQ03qEptNZ1xbqq8VxTuauQ1ftMK1aWRSPNrM4biaZKZmgqx1rUy/iwHFBZa/yCOaX4hhUSEZAcUIaYE8MBt3d3WKzO/cIVJ91aHEbVKKW2qCFtDJDmQwaRpc33Ws5wJu8YDPj5+RljWbF8/AiIMrLrd0vfJiMUsJ5e16NG1eim0etcC05fXrF+AwYN3DwccHqcBnQAEHpGH+8iYgcE9LUBGDje3SoDPQSv309m/GOcnhsYHUIColcQ3eLl6xdFng8fcFyOxhAU8A2jvybBxQRijxC/eadlBV4fTyYQkdW5Utj2WqTgChkD63pCKQuISjAr7XxGPRz0ecyo8UDQIUSk70wBJtJBYIzW4+C4YRIiKO/1PeO7RQbhBcAdopYxgPK+mvF8W5d7c0B8vWWbztMVCGSZFuoyD4AAYCo4PgDrNxXd+qsZz291/CpgE+ROIM/NCF1yqUnS754XC6bYf/y0piGLzPO3mdX+WsIDgDoyAECpapgqdQENrdQtIpAmQAX4oAqMbhFMi9UUlyKxXgwzNhOhVvVwb1eUwkSsxJx0/TzqT/9Xhd8QaCS5ZRFQQ52EEr2J97pVCISBifQZampAL6WhlYJFVLBUJYc+L3CPTjZHGkaVirM5NNGZgLWr4r6LCecdfCK0g9gcEjNOCCOPQCK1OoYrSSQYnsoMqhUNHaUIiGtwqRpppPusmS80koCgAvLIQtogU5oyhvRIja9CegN1oJeCIYIFFbwo3lODuZbxGJ4lJCnlHIbY59N7ZK1gENY2qwgKJIzGHrm/1EXPBxcIRA0jnm1CfLeNjLjCNsGt7MYRUfdAZK1wmIqz4ZpmTIFH73PfSxfafC/IRBjeKI88Oir6FIQiZozERibJj8zgSNl4rhMxBZJ57qJiRt/p+SGL0jLOGmMwiFyZ7GMVi5jKBHjL1Do879dtZtMQbMpV6MGZCm2ZBkVXTAyM4B0mniFIsQj5mIeNh52H0A0Y3BV+O5y4KFxbVLCiiaSMdQOuK1CLp22fEcZxwlwoHK6MikWHR95TpLdPezKl6bQWhI3lXBIM0nyQILu6XElpIHPrHWxCcZsk8YznfyamZYElK9um4QgbxUmM2cbfLSNGdBZTSYbzTYp2z8rgdFJS33aKyBJ5kUVE8gBRAXggh9G4QlmzCWgOJ1WomrLAvTDIlc3KdzVz5PH614g09UONE2L1UquAwuHHlPdDADTLVqBzkiJxNj0NvUYH57ThTkcvywT4uvoY93Rtsz5vKFS2jXa/r3yUBIibDgU/h5rNqH7r+7fuvvbWa/fO5XHeSQ+CDI1CPJ1e0VoNY5PSioJSKmQIWltBXCBD5TMuJfGC5kxia1PiO+UZpB5AVDWN8qjovYURYIS2bsJS4F7rQw30ycht/7lz3sYgEgdYAnVLF0iB4XfEuH3MDjszM4U7t1pXF3zctc8Tc4iIZk4qJc5iXaryApYieW0NrVatOTy60kC4Q5GORy41r4DItDlFXfm5ycmkNjeesAEUSfdOHsnPld447SI6jvxZl8MNpYZ7fdyJZ/Dzz0ZztGcJHKSdEoS1Xnken/JTEhw5WxQ5ieJGttryni2DaWaNo0LBxzi98fHCeA/lmQSrjMgwB8Cc9ptm7DKYYGZIN36UTX4yXjWVB5+QUYqidobR16EZ0yxIYOMQ6wv3E9Sh8D1+jDZSHwPZiE4R7e8Gu96bwhKTRg+TzDrDkrQnkistz/E6f+hzN3bacEdeE5U3pFuPwZdlnC1Gf2ffQD53sp33Thnvw4oz7KjCN0ck9ljSuZ70TaOx3cFr0AgHDLHyOVpSyY3mDb2p8bw1rx3eJ0UQCWezDbnIOMYuhjP5DseUovxgLnM0+0Hg3MjOMTpESoikjurZHORkuLOxblDvHd3KdEhXRwKMBl4WlV3ZnewmH6+6HY1yc9msFMZqa27ApuW3TG5bsKBUhZ0hA1IKpDXw/b2WDPl+1uJdR318fXmO/Yw5JN6gcLGwLHPeFA5XWhEBSjHcqEuqtGjieYIGa7jDHQGoBHT1kEHlGgpBhReVDnzd+eZGdYUvyYEXQMNrOjcTZLe7qjszrKyfOiQgeL6YQ3Rg+Hk4fUXgMMe8m95JdY4KA5pBT/fB8DtYZUl3ihkaKe51vvPP3shTcATfKe7qTwPCWnKtG72s93cAgP7yYqCyc+4ih42jjVWNTdLGZha6DgyRNWTpSa+MvpFrqQyPYNaZHaArJXG0DSg6Vi3GE+hbAcoJVRjtizrE4/19wEvvHaudv0IhjfjubGRh/6sjsYgA+M8GPBD4wwPKt69wsmBJSjaRhW+RANkBkveR33utEWYt4QHN7rCPPM+sgaPMCgJ/eq/6pT+/AvIdxB8AIrz+48/t2Oz3aTd4j+z22ucezT4oWLOr7Z3ofdcizTcp3o3PoLQWed7+c/jf1fSXAIhw/uc/N/Dtv72PBxvvPpL7lxvtTyUu4HvDp17sIO2uz++fSddn/8TlnT9vzgtcXHfZ+xd4kr/aMt1+67rT0c1nTP42ngFioPlcaJanSf8vnjEA8W+K8YXqyC1Y2woMLSV1oX+7Mu4Yu/xsF4wOJTghdzYHZtAE5nnM83Qe2mUgJg9wknDuyrrot2Dlp1tr6+52hHsBnnJ/3n/WoaR30O5Fga+v7Pv+vdl2F/hpEsjNRN6az2Us9vW2WSO5vmb/SnNck/GswDNTywXuys8RgPrHJ6x/fgbjA8onvbt9/gLAoQH2955uG6zI2zv+IDA3ot+Ai/9h7d/agJ4VIHAvVmO81t7BpkjzSF9HqgKA5Q5EFSLA8eEDTl+/XCAv2v0tAE7fHlFxBxeZ/bob0RUpbMfpQo9G9aqhKnuWvNX8nhk/set3N0g39ABTUT6jyvWGUgrqUg3pbv1MxDBXZiDC4xOKaFf3nLZaVFFz3dK4e/p1YkItBbUuqIdFFaJDzHtYsNSqdTRFjUmagrNGWjwVfAhgNbwP0fRMSykAFjWi1YqFiynjbPW5oIDgkbGRdk/z3ukaMYH6XE32iES7dHz3DjBmkZnA9ww+eVpp30sTutLaeW26woxyX7A+P4Jxf53YA+jPj+jvShgVhnQQAafXVyy84PXbK4QFhDO09iyhG5HV+usvJgsJTt9O4AdGPSwAiRo7jQGYDLRCEeGA82ODGqUB4AiPkJ8MhaDjBf3biy7ruAN9LOChnshtPWN4knNJZ9FdZ0ORal7QBsCqFNCzyjzFmCFdhV6ZbiL7dXPSKLgF2RpQODRIjCEzNuFYP2hGLNmaeSrM7clScaEeKs6nAb5jyKtELRJ5EZS7Ga1EBJTbAnnp8Gol186q9/xmy0p9m7uaAHcH3HvfcAfzFl+DYVHius5F09VHmtefD8gVDmLrVMtifdncBWbEAzz/ZCg1kZSkCf3kFys8yNxzGRhdzzuGnkkRmdHgpH1rusy+SZ0XUbReSx2qNC+hxCkxADbj3pAV0lpkzlAcS6hdow9ggloo7Fxp6YyXAEM0f+VITCvMqMNEimcgYez0rfJamwRTiMIM1Za2nkSVTMICGT2i8QQqlA+ja2SlDpgU1woRpA+MJmp0N0ULkuNYOI945Df58qriT98yoXek+W7BMEWZZaWebPFibte8SDdnnBx+ZgeO39wY7QzdZLzJ9mmOw2vCB84zWNM9nREgDqPi8Cp+m72LZpRMRJ8BmM44tq7kOGsa44jFYGPOrxSlQ2rs03vHGFH33mccf2/O9X4dnb5D6SYxqjmgAdAAZdvvjq1RVfkEQDDLb8y3y1SU+jbEGaaAH6+BMFzmS3Dk9yoes8w2ThP8xxWrO9wFT41MConD9y0viDNckXN/S41nCtc5q6x1cWeuqY3QR8Of1/4JPL7Zf5nzSe98s2XBLcG69iSXzGK+wdfENmEa2AWju2PavF23xnAhc2RAKinV8Mao4PXZ3BifzkkM3Tu2scTZsewBjssGi/FurjROmysSDq2jNwxxeN8KcCWUForL3PA5yxiIpezuKKbo9vlyUYek3rYlbLzNlO5+tvcLPo2B63lfduUvtl9SiGzH8BMu4T+lZVYCb43A4SKBvh5XAUkDkRp34wwSAVhQjVaV5ajfMVtt9Cl7BH00XsCNE+4czaWiVEJZW5RW8ZSIHrURkYxjaN31nJ52OL9pRiUb/IwWm2kPA4eJshNK5wcwGCyepNTx/ORffB5bR7Ef7H3m9/K2JzKqa2E4wnCAG4JLUbmHe5nyJ1kKcc9s9QNYIkbgeD/2bxrPgU1XjpM2zj5GB5WWuZJPH/S56LJ69LXeoGjAI+6xWVtfoiGIGrxi9N5TiBMhym74itOQqOk3I9bVAFSKysClzhrnXAiF1HREVRemdXe64JkiUZHlBm+LObrD9ttxdO8CIlfgakY25yfVKVJsD2TiwrTWDIKIOtwFzUz80XRW2PFVMS7MNd3wZsbTK3HewkTe+3RVEFPfnhv7j5z/saWeAQpmkMocZZw53+sMWEh3brMYxDeSj8rE2QzffH+NPnsRkWSwyAzsz4dDP8WYp/NEnFHBNEqLgEsFcYFHmOvQCUNWgEgztBBpeTJzbu2ta0aVtaO3Vcu/mWE60wtfo+1u7BBFzBUhr/nfP2zpPnanZseNMDnJ6RdN52SYTOblV7qV5Yt07wLTtTEGD5XlmLUkQfDTsLPHaCDD6VpPHIRwxGYm8IFRRkXDKfoeJq91c94NHklks1pkexHOo1YqyEu9oRCWeoS5lugeerkRy/RQCyenYkHr9v7RQSAU41ODLr6l1HMkaz2p/kYAnEA4umTx4z2zfdPzK1qOwtKqZ7ojvgdOS+16lLkEIDvYj61Ow6UbCuN5PiuOn9vLS0Sv7qndcLoobph+BZ5vQLeikenZhCtvzPxH7FBSLGjAhxOcPcHa9iy735RG4vjPfzs07Xlsf37gCSIFBRZxKoIl6LX+7A3V1+d5fd9FBB3fUfCgDjEfHtC/eOTzOww8Xn3ud9rPuM0r5H+Ob/c3ASgg8KeHoFf8CSB6UPrsjhy4pDXXac9sFerUtkKwIxm6L/YwJV7hrbnsr711ferQvfJ8wrk/GOu/wsH/Pdz/26P74ZH6Wa9XaIsA08j2M5rzr7Q33pHP8Y8fv8Ij7fq44IcCx7wtx8014Q2EyJAwnv9q22eeCWdJ2TvOYdJl+tnJwcXhijNj/Dltbp28z+/JrtfbC82SEG+1/Wv+M8Ho360NaPxVsZ1xqfkrqTPMPhtIpmEMzZah0u1XyGe9sxv119Iks0/CFlToJ3D17RdA7396q3/3/P+rYV+VeggjK7tA1TXC0BHPcUBT1MoEj4Yn9O8SAUrjUYGmQIFMAfcWHa84PLzH+fujBeK84P7DewiA56/ftTcCNM30iwoICJ5evXtmoJX+xiXwC5RRcO+7O9La53smxiPGlBGfKcM23siJf8zK/9vbux1BMKE8CWsS3Eh6p9csFDVO9Wb1VbsKjq7MFdFoicKMpVard2oRJeyKeWVHugCHuqBwBUe69Ip3t0e8rE3fXZQpktHRRleBFWqJWEoFzBjGxQhYa2pEZ0IvjNoYUggrkSrnwSCMjQDd8QqWgzlB3MSaENs6PQsGDfTnDhxhXmZDBSCBKZPNuNdXCNQANnAHAeH0dX1TsGqPHfTQUFE1RfOzRmM1eL3QFYBH91IIJEFUofs78IrX7yfcvP+g9TshIBwhkiBI1MGEqAMo6INwuLlVj2A4nCSmIAFRR0eF7rWmjDYDUOsgZgxTJM1oHkkApHATz/QRxuxhwiCgkW+xJ98H6B4Y0JphN+/eQQQ4PSrWzml0vHn9ZQCb1PD+2etUEbBhwjfMCQEkGiWyHBbNCnA/cH6eabv7s4DuLRUjMsHPxjT39nOilNI0bo/nBQ7wNM5xlmOqzkjZGfU64z5+UmVEKQUyBGvroMOifVn9xIjyslSEHknvdedDEO8CrozlsBh8DYDUsB1OS0DUH3YPbu/DDbRZ+TfHOddHbcZDDX5sc2fSqPAhEVHvi0BEqGMxJbsrrCy60Iz5RMDoLRTmZOkAvQ56HxYt2boyF6K4YdBAF4DFDXxGGJIiSSBRGgQy0K3WkaekBBUUKVh7R/W9KS6AIYxYuspW964AMIP/8BSNrngSoFvZCYGth4XoUDc/UiZUGWYc1gio0bQuXNQXTpEoqnDx1M4VpWg6Rq/BOkSwWCSJZiiAOuaIoK0rXFE2bO4kAq4V7nVPQGSFCLje0N7Yzc05var0MybNI5Uj/WEoVyduy+/y9NNijhbqhKCKTAbtPAOmotmVlkEzLf1rCkuI51xBrfSpxWF3mUaAzZzHQIxJRBV1ZCkZN3ZWYOL7zVzn/IjNEZAYTHqWPWoHsHICAsX1NpdSpgHd3+XOTNOgZThlgz8dthOfQDZm82/BALgSepdZS9ayLThOiLTtGTfMHYwMBGS5GWP9/BiyRp6L5dufHtvpnqxYuwCkBE9QP+zsoh1K/TltxVIuxIbRxkWLS+7ZZYrgrlyxt4PtkbIhbCVIsvXeKoNDgWN4wGt3AgCROZNp2iB4NDaboahQmXs/LVHhACQ9USoDPtVFkiqazYPT3WvAZrAzwzUAoPvekqba9nELJWce48llqm9D+Ws8a6kFRbQP6kBvqpwUi7wlLihlmx6bDP+PAXC5rCE36Q82RgJf77f0BNccfvKOXFLviw4mL54dFHziV7tPfPnV67/XfvWpH90XPAeS3GDnZnjt8OGGZd2XWjSit7WmeKkWiGekQDY869lqzaLKE2ekPISVCiBCY8K6Gh9nWbA8fTrXAhRWx87ep7wFJNo3ZhmOK0qxsYdLm68MUWfRQShFHUTcuc9/JiazM2rnexofMseH7bs3sODrOtTsKova1tqquZJI5b9C6jTXrBZr8DpBgC43eBuNqjxOLu0i8U8acjhSpWcFGwcInQLFfTG1hE/J6ZFjMvOo3a0KwqBKstkPEZN7lehtzrOvoR6zNM4BLcVl2Y6ownCilhWrteJ4XGa9ZYPzPgR0PkcGO8EsqaW0aUyW0I0ltmDqSDAihNuHx+HorfeyOwuxy14xDai4xGD27Hrzx/3AJrg4/5L2PPNCccn5Jo9G3SlOE7+Rn93AEyHokpA6dDvNmLy4GlsFc1lC5xEyg8SrcqDpjBLK497OAyEZzXMkBhP5XdqmEwml9PpzLDbDuegxR+f91HHd4Db2GuF8MvvTkbV1jaxXEGC0YXKOGZybBSCcG1pfNXLdgz+gtCuyMtHcJ5f3wihpfJxYLJLzx1PO0ue58Pbcb7ZYMymABDfHGy2HZ44tXBg8JMbHQkARiJSYz+iEshzAi4BaSkcP08WNgsEql4SjA5GtD9nYrNxUH4B044eBftLMgccDg4+MOo44vzyDDgfQGDh/fcF6PgNH4xVf9XyWo2fhI0MVdtZWq+HNHVTYZN+KUrQ6s5SCbnqsbrRIHaIGighE2DKfKO9RLJsE89StXYN110mozmPKRHJnTk5yA3mdCHOGFLzBYypBQ8644/sOeKY0CdnM6de+ZRxCUAU9APDtDcjwUyYjU14XyAnow4znezZmx76Iz0qAIS+gFwBWhxcAxsuropBSFV73BqEgnTe2vifFMUOdRFUmJ8BkZ3b6uVu3cQUn+t/TLW5eo/Q7Y0rVc0yjA0Oj6AlKC16+fMXx4b0OnRn14T3G1+/oNN+zQx2btucqG4D27RuOD+/Rv36z1Ojv4r63+LYshwjejjh/i3vd0+VchzffUzZbRah/fNjo05g/KF78x+dY69xv2w3gZff5Fho1/tCV7iyiuiFPGOfwl4pgXszT/35Mfb+Tq1xZjPGADyh/MHofaJ8/4/AfnwAAhz8+of35Be5yyekZ2vXjv9/ao9zI6WiMaU+Lt/zXFkKvzfZ6e6JZ7xyYMJnX4n90y7zupu35ofnJdas/asUDAtyhy2S9kfX03t9+SPk9+vLNWCIgZP9M6EAQMnXcRjPbbP5GTI9VzWaheo0CsUyk5+4OyR3XWozrB7Lx3tj/QhSBdv78cH7qrbbT31/Lxnp9ZEkOw8xEEU8nOnn18V85rP8FLc9iYOrXc3sk4MOOP85wBgAv+IJvdl9PWKRAcVmFwsj5n39CIPhKwB/Bf9PmmWttR+5/Gd/F8w7yv/HMf6f23yYCfSIZl0xnpID+SgKTR5ObUtYXP5hlKPO7ns/x7KkPHIEQXE/0CEadhNcOOZsnkS/M4cMRgiOYCMeHB7x8+wqBRrGdvz0G08d8B63VrOSoPrzD+k09BOVpgN57WkKdJZPW/p2Ea/7rTNuLAIU4mELCrEupKTeAMVxgHVcQEtn/JhARoS46M1cGi2gtBU4pDwsYhVW4IEtJ0nrHaA2n11eczyeNPLd0ifFaYtQyjbC9d1BjjGXgwBV1qRh9BYagFEYhTSFWuaowYkad15PVOSSkqEwBQ+tToxNubm9UKQ8CcUELw03FzaIC0lJPOHHB6+sr2vlktRChRndTvM1oNGPE7rSOZlsHzuczTl9XyM3AeBno8gI8HUDvACa17K+tYayrMpO1htKAGCjvCtanAcEz3OiYjYgQqGFadE/6o2DwMwhFowZBIHHDEQB0QCSM9eQpjyWmhddvX3H/6T9iL12AycI3ABzvKkpX6G/yrMZvWL1HI/7zT4HgBb1XoLBFcxfI6uhVBaQ2VJgP5Rqpgcf3UgCtm/bYUO4Laq0h7LoC0uFYU+/vDWY2LnufvytSPIrM1F+W2izSCM8jFmcJvjbYMkwgmAGzgA8FvTcc3nX1Pn8ZaBiQp4F6v0WfErO4eN2bbX8P2T9qu6UN3+aRlRIGMUsHiUCZcx2jrpydz1iPfQQlYv7OxBMRmtXPhiDSXMZ9njJfbKCpzfIL2SioK9OHpY026Wfv5KDKVx/jnOfMYmBpyVuP+nvndVVv92LYlDTqo9SKIR0sNZQ0XnqitYbeFEbZUxyDIvuFiCq+PPkkRA37RAVUNQsEC9BHA1rX1OrUN5EZ6nujOL+QR4xxpJZVGiYRUeHnkm19MUTTv5mxUMHd8BU7w0yWqr1jXVft01I/gqFRmW06NJRSsBwWlMaqqOu6Dq13rG01wwOntD2YNdEvGE7WaFCQ1a3XvcxOLJMeSQgF+TuBGCwgFH9+CKTn6KErKbuuHS6D/00UYAibM3OCYZlZ15RYnSYcVu28MHtKS4Indd3HuHgKxTysGLUrd9NnTy/d3YnIS9D8YFr5ecBwop1NCDSbC5dpHLIhuYEhziJZDeiktZZBFvlDgVuHrZnSjRSmCMOX4SzikUQ02Xv/Ze92ZWwpVctAFMX7pVQ7e5cz3giULrvucDeRG39yGCUwDC8JWSrVwRd9R632PM8QWpMYajlsQ5AZI33raW3JVkXH6jT2QojgqeAGYEk7GKL5b9WbUCcdc7T/Qxno6TOHpbZXPoPApGk2FQZKUu6yKottHyYvoO8ZQ9C8fqk7UvjsWNeRhuMs2Bgmv9fHsCzQCidCYoYihcPCBRBBa4JIyihihpe80zHjuZcE9w4FCWtGhz6BYAzBuq4RjevOI+sqAc/EsPR0HHxBaw2Alp4Iw4Xt26yDvms2fSVN7hwI7FQWuyZx5nw+svv+R6LmzA7lB+9n6Ze358jP/D5ydV/aamaICGK9MY6y02GeuNJpIjDPvxokixnUjZYxox5uLPV4D0XUXOM5ZudfnF9R/lzXSUaHMGuZKH/MYJ+YN8uiynRGs1TxgMouhRkYjIGe7rX9HM60I86wstsy5SpBRL+7gaqYzCI8R+DwRASrkS7xMpf/Js7L58CdD+wciEYgx0q5syMzBKQ10LumjPZ0+ER6zxCCnFcQ2VkwiHX5h7zEQpyPS6cTVf7BUnd5VK6PFeiv04WVjoTxKqAbgxEbrwtCDAIXc/AJPKJ40uWieL34Ynnvk1/oXrZE9HmG0s/ItuGABOUfpEtkYRoDm9IOJjmiVXM8GJraWR29lDYrpKucNUhzwU38afA6Bjopf8BIzna+ZoMxClALMITUEMk6diqMmVVdjfIqr4xI3y2u70g8Yqbl6rgyEg5To6fD7TRkkJWQUWjw0jSx1xjGz09cH2JqH1qD1zZoGI4Yxs+AxJzJBR4dGxHrSKwF5gUx59RslGGHfhdo0smeJMPoWPBMmvEg8FJqFDCEgF7/Ym94FPME1qh/p71ZJnKnNC2LUoo6LhaLpIaoXMJc0dshVR0AACAASURBVNsKWpagdx0ut6x4PZ9xPp/wejprGTxL5x6R1Yb3mchKOGhtcdapK99IXiIi3NSj+Z57RivPzDSj4+NGA2IOnZKeeXUG6nbGnAxFrWsegChtX5YFYEtXa7BBzOBBwYuqobxEQEVZCorxbufTdFIhAG0IagGoMArKDLywrSu4gZQz6rKg8AkrABl9RjvT3E/vUzMXNqBZ2aMyQMJWZ73i9vYWtS4oh0Pse1u7BjO0hvV8wsvrK87nFb1TZBvbZKaimWVjs7aY8ghVzwQ0ZZG1qZ4L9wQ6NXjaFIGiNXWW7ukcEXhZULmEDggQyHqO8xi16P0skuNex8t6xgdbdLmtVbW/yvEIInXO8vFPg3zHeBEIXoN7ucouJTonyXkChnucF/W5Kr0bAJdtf4khJDrF0rrzmuuA9J0I/DN7vjI2+0+DH8RZjLibTP7xWsaFKEXo0eb4zLFss2y8fvkCvr83h9KB5hlZgHjnj1i5a218/Q7CO/BHRvuqqdx/Zoifc/5x24/nrfszrmFRnUj5aOP78g78aWYtzJ3JEDQI2j7j6ZU5XHy2vXG+wh09mvPXqS+fhOCKgUzyDuld16QQQHne+oc5ov/ZwfiQu0H54yP6n58jnb9N87f31N9NVz/4JaPtuXe5+OOX2/1fGOQ+A8Xmu/whnT2dCocs4eR646y5eTTjzr+vZVi8wDmp0e7eq329cb9Add/KO9JGn/fW87/TvHTPtf6cVbq6O4n/eatd6L2BDR6V3XuvjWN/Dj3rSfDuENwI8AJ1iHnx2kB+amje6zzhXkL6lRbsrH0eeBtHXr+eZfs8o5+3KWX9PU12f3dcN9ZmWJYxYs6Oj76ETAv03XOv//gHjn/8EdcYhAcR/EkIjPc3H8er44dYYAy2/OwmA0S6lvmJ34OQv7/97Qb0/Xr/2vQm+ZleyInR2ijd01MupBuzluumdlMU+ftvhymDTEgsLui7ogn3EHpCwXtNzePvIK1fNgws2RK7vH57RIegEquCidiE8ltTPhoB7g31HaM/6ViiLtS7e5yenjUNU2qeStjbslSc1mbKMMbNQWs+n9aGAWV8iVSRpTWkuyklVGfLxKimrAbc+AV4lFHW5UTaZgBUEFFLEI18PJvQ19emBjY7qSHQE+F4vIWQoK0tDFejddDNgmUpENYIPCZVUFQ25X81xa+xqa7YgWjEUocKlctSITyAYeOvBYfDgrZ29fwnrWddlwVnXsAgrOezRlmNEfW1zqIezmIgpFG/xpytDVzI6pOd7R4C4QYrHjG+36LcWxo+E9r66JDeQlz3SDuxNEtBvBOjIPD3GpG8o+mCGfsiumYpNZR6jU3PQQ+U9+fO6zm81ibjYubAoVka1rWDmXB6fDQFiCtVp8DqbJMjtfatgT8WVQQRofCiZzQ85hl9mFCsXC8Ga4pizVIgaN87Bl7QnwC8U09d5iTED00/L/dqYGS5BYhwelS4ZjxjyA2GcNR0dYWIK4K3imuakl4s7VSaXI16BcJVmJlRl6qpQs8n9DtCe1ZFmiNzVWo+W683G+LLOJry47yBg+3hQ8CSR2/CFHhZ0UNqEZiZK8QZK1UgiUCVGpb8neHKal3XqTOb0UCtNRAIh+UALgXn9eR6FRWcu+K4bsZVZ6jW3sD2nGoqfErTKFa4Wq1jxrquKJEKS89arr28YVlkzi9f8ygOrSWotVeLRQtI49jzRbxEhQu4ApgBva0rWjtH7feoD1yKrlhX2sHLjlCboxaLPiNDDa1UVZjrK4ChKf5AHQsYUsbcS2JNyw43PlIyNiRFZ7E6skXHAjEm1pQyM9LL18UdlSicjfSVBHCB6oX97gomRmdbCxH0foZ4VDuA5XDQ9FNDYVxx2NyHWa9bzxVbLWIR2cCqmIPSzxjQDUU3YRsyj0Y4Pfm9viXkpRLE9lEjheqi6cxhGRWE1BFCI1xGnJnpMGJKPi/K4t9DI3N0WBLzzU2PEk8QeWuOiX/Rs2f7tFH42CkIbvh6bwKAjHZohIynxKT4W1mniQ/Z64+TOVLwVHQMqMKeTOYTeMSNGH3nzbpvo+HJlIJKE0SUT5oGe/XMZmJULtPQWax+dnJ+3K3q/BTrEQse94QxMBTefh+rUYMITD32WY/d5Bcn2iHba4NfSXAZ97irGBRGoPyn+rcQQBaTYM4FGz6VEPwsYgwUNBI7GIDvodCMpNnVtIfxHe70U82QTBsD+qSNvoiu+ANmbTZ3UPKoCr1djdZUhoaJEAJ3+fz6GMkz2p5lTZOscOfpUCn2yFc5ph6ALWmsbhQxw60Yn+5Rk2LnGUCtzrdqhpUxqhkZbD2NjjqO6FaHfYyO3mck+zSkX4mslQkr06P/AlS3G5g/k8HXEFAtRjsyftw62uQ2x7MDqmuvBcLpDGTwaTjB8UEDLP3BxD35noi6tTNAmM+y14P1G6AyRikFNzdHLLUqjAxB7w3L7b06q0Ci334+BS5SOJ9y38yGYWsyAEE3GaybYTA2RuGlFHMkVt6/1KJGsE4pS8HAedUsVegWNeTnPp/zNK9MX6NMEQjDjEMeHe+R0L5Xe+cxN/SRGTSDZ8y0UZJckPBMVpw6b0iloMJr05oBnxyWHF7NAVEE0luguDGa0US7fRC4aoaw82nHnyqBsdTGRqtOAj4C3e6NW08AcAi8KQDY5RuiSP+cbZxuACRkB+zJm0Oc7m5b0FAz5jEUP3j65zCkkgDV1noIqNaIjIbTKhlYz11lyQp1DqYCd7r1/RUhhTExY7UyZQEz0q1+9RBwgfG2CmuDB7ir7w9ZKSF3AtDzJsqXW2ecU9vD1wphEAt4MGcESWVMfH0cDue6mvGhUKwf0joH3JE6g2auzBX4jrvFnIyGjFlOQTw3iT07SWm0DW8Di4y2G+nKDY53yc924ilcbmh9gEmi7qgIpqEYigvibELgxkx/XW6aVt/xRTCZILIgBuefyA3DrGUAimb2GSKQPsBFwrE51kxGyB7recX5fEZbG9beMFq377tluZg4juw9oVoUk42d7wl8AmB0lLqgdU2a30UU3wUyGTuCa/OGvuN8OqHXhuVgKc3batnl7BwUAhWg1mK6mYE6Ctb1jPPqJTI0+IDKdBZUuYdQa9FnraaaimR9lr1wHklMZ3VbNQsWGX9yUl6yrwWlEcpdQeWCtRnOPZqhmNzBArFm/bmD77QkFpWqa1oZh9sb3L17j+ONFlAvVcsI9t7QWsfr6yteibA2DabQqHrF+xMvK731smIl6dcck2t5JXO4qFud5TCnqePxI5gI59eXcJKkVdBInWeICLSo/ObObAXqd+ky7jSem+M7pk6PYMZH56noViue3Wp/XAqqO5OzZZmDOeSMhrF2jFdg0AmqZbw0UjpmMuSm8JXY23TaE/xN+JSk4Z8kQcc8ZF4V8sAfLQUJqDOCOybn873hF/RhdUxxPi7OvH0twarF2PcqIgo8J+m3zuVA79Cg2dwwLFvMw3vI168p0n2zUpt35/lvviNA8IhKH8DyDoMeN1HzjtFzTfS8Djt3zITft++ZbNB1ZnMazh8ig4Rip+/onwH+j4+ADLQ/v4E/AfJ5W6/XV7vvEfCu+ds9gvQrA/dCKILQe4sIGuk979NDMgQPhuq+G17xNffI831r0LO8QOc3Pts+OT+NqQ8af861yevr+7l12f5xy2PJ6HnylEh/KD2SAJw9BP28PZEa0UN3bNcv3c98HHP+b41730L+FRdv964LV+DrLQHozXdM/PvW9as97g9zjOk337/B/4jMnwBQmNC60T843vPnLjBTGtrl2AJ37tZnf04d/iLTRHS1ZcZcl+OQU+0MN5mZYJXr2w3g6jpP2SfrJXP2D1+nmVnCHJfI+cxph9NAO5c5L5ZiN//deNIO5mdvALxe6WvyhbN5ucD8xY/2azeAn4z3t25XvIVthLmTxz2+zhx9gxp1/fNHu9mf9X4fBPgnAf+P7x8eAHxDse8GbfvftylH/F4L2f9Kf0FXab+7c78n7Mxv8MYY/yvaf5sIdGAivZ8R8bj/X3wfJ/BY3les3/36fRjRc2rT8WgMXFyZIxhRT/oFFe838qmIYHlYgFETQd4C/1vzO9QCguDUPHrgGjnLFxypkf8fXq9bzJSOHbkXrWzTTNm/A4C0ntIWq8FFETYDVedUCqNUNyybl3TvWFtHXTWlcgFCGNXUs+6hPL1qdY7aRycVIBkCMKNWrfG9Pp+xPLyLCKQF1RhXhABwWAR9PWA5HHA4LlhXFbqFBLUWgCp4DPMiN4WzzdkDfgZOgKg3d7llnB6BjmfQuEd7bqjvasBC+66fXdnVf+gjGm/Sf2VgWPr2DVPryMTpGBAIxpkUZcxNgQA7Nx6tGg+aNJCYSb5ARJOA7uFLIz40alU3vsy0+eKRFyoE9a99zoGA+p7Rvndbz+foc31sqPcaseFpeeNsmaJgjorh6ZgBAt/vGCTy+yy6wi5K+l4XfOeJ6oTgGpG19GyuPF6WA6oIaum6DqlbwhEDp8SIurj4FwiNK1fj2G5PvB7j+eb5lUzmVGDKB4QhxaPVE6pQo4QZYvZMrKOL1jtqmQKEvUQVgnHBLys0lmLKdJGIPlPjmr3XcYwAlKLYnYlyJYArQfw7iKAPNRqvrYHWFbUPDMdbtnaDaKbZMu//0ccU+pPC2aM1I/U0iQWfOh70yDBTZZHORaOtORRdruxpfkZWdw5xxY6E0TCEIGccCgVsDmBmEEBiYggekB7RJYMGmqcyKcBSVAmEooqF4ZEto2vZDVO+aRT/ikM/ols0/7qqcq+jg8FqWDcHqmCpKVMvBsgVCLSBH49y/tUaUJPmTOp6cU9AmsHK/i9xnmGrRCEQVKfHcZ7HkBmZQRSKeEE+W9t3+8YJwYynnmL1+hz3UU7uVKVR2LpPHjkbYyUYTLmAkhyDIGnSWSjavxdxplkEYnUS9X0zGlfHhKRwT0p6mZGoEuuKMG55hBnt1AWh0AXCKcoN+K74u9hbchqScJl4Zo2tQLxxPkAGOUmwObNyxLkBdvs7CSrJlTXEdqk39zguFX+HzDVKqPuHkO+4jaDOluYQN0QAU0oN6ebzMdKamgIQqohmdmc2hy0GBS8z19sx9J5mOqwMLwnig491S/BXOEokOS72qEWKe3V9SjLeEzxtq6ZfV/iTK+fGz4s6hPpCicwEjQJgbSuIOnpn9K4G82KR9p5hJMMNWXpmh/vpGPUbYtdfldAk/gH9FCjskbzG0XyN327Tmcaiau0ZSWP4FUVVOJmAZtYUmEMahhmRdL2XWnE8HnF7e4Pj8ahZBwC03lAORwyjLSeLkgMpFu6Sx6bji2jwwEMAPINRwlG+HspnYHdN+Ta0AWbNNJDpg/OJb3Fl++tv3mv8Vb4w/5vZ1PwOV8RndPUzYBAA6/mMSoRDuQVgstNywOE4cF7PqJUgTWm1rk+57CjBnSqyOb0hwVt+txtlbAEIAjpOeUK7PGC/Aoh9nX07/OWkCr7Xzvf74uwdBLNUAjh9kclu7ORZd4oVQCOB4ed+ACga8U1aQiXkITGDFQnYI9ZT3+L4j2xvfbhXlLg61YlDxeBEhspOXItmxPB1pzlPCsbwx232OcceZ+QKTL0F6/ux53XfXBF1tHNWfGA6X2m6bl/zZLSPvowfT31HZjn62eiuzyKcikTMIHm99da3iljDV9tur1JGawMQM/THWZ/352eCvhhNFmM6xHmE0SNF+BCXbyS9aShPjysrEjKgzkFcniAyR1G9qbWGPGF5I3INqX/nocLxxt7hdF/LvriDFV+ebaQzQCmlrPO8zgN4n3BarOvVnCj6pO1ZtmwaxcvO3Gp/VSoEB9wfNEr6dD5jbW3uJU3Dr4iWWeP3uofOhw4oj3U6nfDt+1fU14PCUnEDujo1nM9nvL6+4vn5Ba+ns6Z2N010ISvj13Tg3bIheUBEzIE9Y0GJbC1keq/j8Qh1VHTZj1BJ0IbK3CsG0ESNogZIQwZ4EJp0nLvyh+q9jdBTkCmREhun677ZfwHdMJbjguPhBjc3B43Etyjw1laczeGjj47x+gohjZInlosQvrco2ZaD+cE9Md5tppOrzZ1mZWZM2PT/i3zWz5qfxavjvbjmOPgRAx2Md8Fr5PYrmO6tsQDGG38qYHxA/6z10IXUQFLwHoAqsX2v94bzf7URgGo1zgGgf/6m5fbsO83kwap7sZq7OR71r27Lnaih/CjO+U3n4reiqt/au70EmlBPzGN+JvAfhP5nR8dXLJ8+gT8R6PP2mcRhbCI9f6cFS0iTJXp7Jn+97dO4p9f+3/abbWoc1FZUzKEn7+EvqsDeaNcfzvt17Y5f2Utlv2QTaPp7sPb3wuW/cxPn9f7GPrPs8yOZNcYANZB/EDXsChQnHfERHV/w3c69l+N4EGD952esEBzwAcADCjS7CcnPnJz+PmzxBov6b9H+0w3omSj9qy2MvMiAuhfhL70XADUwFiGscMPv9tn+raO+f0B7/AbgLozocO1rMgAJgPtPD5Ax8Gpp2r0tQCiDy/v7MMyqIAIsrN7svU/vna1otm0vZ62BzZa+OaJEwohqNeDTvKdNcBrHnIEHkIOtQvGpK8eh6PYBqayqaX617rdHisAMjCUiZY+Hg9Y6NGUJEaGLRjuerc+bWjX9oNc855l+k+EprgBPXz1EIOTODsBCAHWBDMZSCmpdwFRwuFuAs+0/uVFkoB+POJ5vsCyadqrLGTSgkSvMQB8znWxKgdueOrqlT0NVj/vz0yMgpgB8fgRwYwomFSQ7nkGP9yjviyG8BKWuifIWS/wE4Ki1mfEEsog/8c0Rg+oQWkON4JunxDplaBO1mmK5r+hPMKXP9JjtIpCXJ/D9OxBu0PGiDgq21wGLYTC9AeEZ9J5D+RVe9hYx2ntDtzR2A4KOp5jo+D7he9hZ0nk8oz3egR+KGqNAYcT0SEYfhzO1UfYgMSbThiWxftPF4CeYZ3MIr5xAe7FGUh9iL1+eHi3yXgfCtwx5PfoOYLJW+rlCn+04bwiiNzZDRwgmQzSSbzf+UIjsFV9JESRu5BpqIOsdloFCowSIZzQqW3TFumpUUaS6PWu0EoqnR5z4VyBaU9zFtFCSTPVSb5o1Y3iNODcEKmCHASoUKjl9nUjUl1cQs6wVoga80dX46/OQUtBYI4z01APVc5ISoYwCqdWiqg23JAOTRpRNBY+QRDYLhT0K+HAlJ7EaZrASaDAKC7AMjAaroafPFWYUKiA667kxRyEHYt9FBsFTRmuUvWd1mDDk++znWG9pEDCw6hmpZkArbri32nB97eiLGtH76Bh1oI+DnltLif/6+orWG1w5yMLo1OHGSl2xncJSJv0IGPVx7uHTIiRiXqQ1ybdKP523p2GuVWuEexTSXAeLdHajmF33iJbi2WhoejwSEXpbAbHoJKS0oVZnnhwIne7niRpNiugzc+4KIyryIzTvt/l61FI2nher/adHJCvnEcZNzSaibmQKgzucJvP8T6M9g2nALEwg0neXiJ7MIpMgjFbxM2YmAkHsW1G7rdFlwuiW5denbGPwCD6dOOWt276XHFMSIGRKX+yaG+WneWqqbjONdRCZMCbukeY0YQOXsvuVBigXVzbPBszTXPuY5MU1TPxnl3RNzaBIUGrHpJkAyHisgXBWHFZ31+tHTucE3+uZ9YaTkj0MTnNZJpD62js+QtoLXy8ixavuYMQ6vyYD1aNrCZjOhz422NwonDJL9QhM51xtjTPsiqQxa5+lAtQJajQfkT3HowZFKlrTc6L1VN1YMSfLlq1q47gFutynt9oF/O7v9zWUdG+GL6f4W2XF3kn4uvHc3hC0YP4OBzOjvw4DvvfZCWZ/AK8ZV5iLwp89p04PahDSbAK6jsyEUiqWwwHH4w1ub29xe3uHw2EBAVjXBiHdj9PphCdy3Awts2C4ztcq4x5whWcLcXlP7epmfDK45KJpqT39TZRDITs3MH7B1tLpv+8JpU11mSe4t2BVnI/QL4aVPNB0zmXux+bMe0Tudn/VDuf9/Xwv9KEZlR9e+kSotWKpC9rSATS0FRgphM8jhTXSd4vJBGLlJyavEmNNx4FAGK8KrwPnqC/MxwPkNCExZn0C6Oj7OZQXO2vqNyIATBCsICzhiIVF101LBaRxUuo7+I8Mz0q/NRJdQKumUudK6OuAaG0JLHXRcyAAGb9EVNAHWSkqwhDPDGR4SQBN5Zuy6oDMiGzuEcQhR2ejvp9FrcfLVi5k0tfeBZAOYQIPSyud5M6ot42Er20dhl3U/tzBckye2bOUBUzZQu7o4gXMJfy/h5T5Ydby1h+n3yqzt9423VMpcJwXFDu6c/1FgiCP2L3AsRJjG2MGEQAO45zuRTpXBKTlcDtta/OM1FrmGth8lASZKUSQynYgzsfescl5zHA4Mho9AFAqh4HLLdBhDu1zpOwnlJwqnSHU9U940u5zWqkp/adzgdMkIkA860FeYHNOGpYREMRWVo0gOIOgcjkwwFSn/shxN5T30OxnaW8cbzOZ473RJ0+Bb/ofKlZiBgxQm9tIQFk0At1lpHAErEC5v0FZq8qg/AKcXo1GjKD7oaOKMkHTQZOMn9SyV88AXsC1hCO1SEc7d6xdnfHWtqKfG6xjlNvp0NdHR9opRBmOxH8xKZ0gJpR60Llb2ZODpfoXANIHjocF63PD0+sjpC7GJwLDHNirvWP0jnZejb8qiuurGehtGdn5G9GMIIq7bgAI5L6gLAU3x1vc39/i7u4eN8cbEGuQyevLK8brM07nJ/TTSXkCYoCdB4hjc5VXwZXrU3eVrqU/3nL+CbCQFPlOAkFBa07TBZULOns4yc7CH6hmS7Vk80nZ2/0wEptyeU3mAwSgif4sgbC16SmaumuyBaH0ffSdeQb7dyP9huJLsKaBnfEtIoujvx2R3q/wwHZPYr138runUgfUaF4+PQAiYTz3iMXxzy8guBFZMKmA/Rg58ojU2ytrfa09G4lqds/tpw9Y//yCYkDlfZt4ggY1FO/bE80odMGlsVuzKwgO+IrySRMZ9z+/xLhOnz9jwUc1pH8e6Pgaz7H1x5iRo1/emM++ufPhFKO2zmhvyyd7Luzn7X4HC4IZkX4h5vxLbUvPr/b7hvyzb5NOZ4J+2XesRtx3dVT/cnPn5KwTHWIl0QwmVU+C6wfsp/tG9pbd+uz+9j3zJ8RpnONao58jLUfuNcpiBUxMXPaj0e3X+63v99ckBprGnPujPJu3e5zjpCu/9e+XLE/sm/P1togXdsWLie0u/BSIfnzDr5zaBwG+2Y3Z4YWgOOzxypAexB15yIvm4dWwkBvPF6gdFADqp48Ynz8jb8qCDxB8j7WLoMzNeP/6Kdofibeh6L9/+z8bgR4MrexxrX5t92yZFYRA8Va73KC37/M2MLB+/45C9xjyDKJ7EO7n99/F5RH97DX9oIs4U+d4ij5OKZgplPpE4+oA3yAbAGb6OEWElr4yERCCGTD7jmm09zBpSvPleNT7ST1V1XsTU0iBCnNuyNE+LIqxey1AVawjUm2oc0Axyl9KwdoaloMqLtC1Xp+Y4WtEbaUSaY0LF3hES6yNp22DGg8qAd1SUgoN1OWAejio8d3GIP6EY2mqKGVgqQuWumiaFRCEoQoME/44PIQnkXYv8T4GpDu8GRJxhc7kYzGe3PD8/3H35k1u3Mq+4C+BKpLdLbUle96LeN//s03ExJ1rWeqVZAGZ80cuyCqy1ZLtc3zulENms1gLkEjkviSRV4wwu8KPTXiHCAQ38Oya/Yd7nF6ejKAPkubOJjUu2zu81LcMVHIjxfLUUH8p6R1bYUyfe3p6giQh1ziwPmklxGt1BX5sqPcz3LjpOMLMWvobguXxMVBHCa+VH8PIC3VWpQaqF7B8RGSuJEJAxtiKWz/g5TcF8iSQTwK3dAoNBfm9I1e6WDHMVJYx5nfleUSEad6hLedEl4ZB6FIIXTsYV69cnVmvEzOPXmTZAXNx6PvZjHvez7aCUhaCIFd4CPphBj9/hw9MBUQtBQ9oO4dLWJihhMe6ec97GI4aNume6p4d5/B1w5qaAauVBhSoEWNlcLZbvHQkkYoAWjZzQq1aYh6FtBRir6bnC2Se9f3Aqt0AGW31DGAyXuR79iKzOoypmsUlRSKrVkudV20LYe0iuHe03lB6ARYbf2Urw6fPG73soCWbWR25o4f9OiukW0lq1jQec15aL2hRBVKYMc8Vtc6YhGysBtcyCsnpQvju1/KCtU5DmBaoAc3CK6/yKEPicPoGhEIiDzyxv+yW9EyfZ2Y7GGsv6b7xWspfVmPWe3S+flUp5lSvEyqgBl4ikPFA6WU1znyIw8K3Bw1BnUj3Ka9yrNLQaOzdkgLG3Hleq2f4m0KQ9vjIFNe16r3jPQLngSGaA1DDgEtFS/W6g201P4ez8T3l8YQOz6hhxVfmkA1I1BVoZt1BM2DZPpY5pAE6qUWHj/9N2jrAmHtpEZH1NvdswVHSfM0vaCUfetagXmaZck4T/WXxsaXTWwo9vkvCawFCQ1W28R3lgsZ7hGWUNyYLImLWADejdWKZVBHgU8x56YGZtraa8O3OUx+rj4Wu4DUFDDw7zAWafO2Q7wqkjppNqwAZHUTwea14YrJOYaXrUwXLBBQttQ5ItOhx+YSMB+vwNRsU3ao2UQcxofNi98J4hGilGoPPcKB7Rq71jOXhUPas2OH0wmq+1zJL3z2GEOYQSicS4QhJ6AqdkUv4b1/ihpu4witiINEYC8pRmEo4niTjwZbnY5wmVNDktIK0LLX1Mq0VmKYpqmgc9nscbg64ubnF3d0t9tZL9rwsaF2z+M6ns7VzWgIWZIEeQ+a0oyg/WjnUXV40bA5ZlSxoAgA1HkF3Ro9FgC5DT9tCNYfglO15GZ9RkjD2ql3HSQ+zkhzCCaf8z4QCY92+j2PSG4QKaNrrPHrH0juotVGdqWg7KtUJm+KCMatCqf1D5sUhn4NSDQAAIABJREFU9m2oVDIEkl0rINDewgxOdpmv3x6Qk+RH6pRPLgRoqHo9HCyAilCmCcCEfmzb4egzZTgZHP5h6vN92dgcgipfSiWgl3hWb6mIraheX2DZ5p21HRYkOYLtHxeQ5fGtAx8G7EIPQ6axY6FD7jUdiolBzau6qRxFzGACCruTJ5ksbeIrF7bRqdU/G5/L+azp7UYTv8N7fuiQi28+IqenOi5GVEYRSVF0hjfbx0YJFxnt5Aaorr363WO3n012ptAXShkmLW+fkHEi6+MtZajXaQo+qDyAw/jt+43LkENjflm+M1tEseBNEkAKo/QyHOIUpCvsHeJVnBweAQyKMSOtP/P7gBIM0rRyJuRbvYKSXrSirQQNzoNYVr31Iw/5mtfVDnxvZPgO+VhW9M4d6dNU0OuM5m3HWKIaYTVHe56QQDDdagB4LRV9KhEwJVaVjKw9FUNbN3hZXRuNVQmTyPY/9xMEBaUN3VjLoWvlRGb9p2IuoRxqZJWHTQwEb+7gc0yDhgQN0qoYTNrmhkuNqgFegr23hl5aBFE7fRLeVHqCwkADchV3d7sdpnnCZO8vGPJOYX1+wR50INBeefjh5gaHmwMO+wPKNOn1jdFeOhq/oPWOs1WRCVg7DXgT866clfWvK3HJz4lcKd9qm4JgrczsNAPdkyxsPC3fszmS5H5x/u1RX0px8QzxpBQCkYc2p30sibZneRojW3n1njcGsOYFuo8cv+qnX4Cv3yCUEkswZJkO46m03vormG/OXYPHW3/3Px703IbYr665Pq2/fLjo6NI0cEnefug5do87273ksWbQW4Y/RjiGAGj4iumPT6ifS2TZEwSunbuF5c8cWVb8Ce3jLx1bvHhvT/zVcf1owM32t2uy8lvngff39F86kjyf4adV5Abv/fcc1zF/pcu63J5wS++SN+//O49tcbskdqQB+//+7FiUKOwBnP7kE/6Tjoc3cGirN21/00CeIc89EvDZxO8JQ05Rdda1HmD6teL8BZh+ndC/fATJw78YK/7nH/82B/qWOGP1/a9v4Bx5cvlbqCKDXEhSzgEwvUCjzF9U6MczCm6TYsEQvMTOVweGKhcuvEwAyh2itFmpFV7SGAJ0aaFcEggd2sfoGlxWZ4hQTeHqlrGXVJQw4m8Z0DD4Uygjg91jlG22iOvhgAwtCaBqwivgvv/YgGawLZP2TxrGWIBqsZ5QFbv9DueXo47Re3eBUIv1q6WCqUzDFsWMbiXiqzncbm5v8PryCneg7ybtb+6lSwkNJGZIsYz/AtEe6/OMed5pyedateyZGfCmUlCnObLP+6sa3GgvoDNAskPjM3a3d/i03+PL//MFHUeoQ+4V8nBrmPUSRgaI4PT1rBUMTDkCPLrQRPBQKI44PxRMv87WS3soEqqsqzPDYRY9LmUoamJaL4mYkv+CzjV6j/dgTGk/mELqinlIiCYB6NUHG+4rCDrPUrT/8/n4imbl789tQXt8BOEmIlp3H++xPDQs9JKwzvOvVAEhaAQcvj1g/vhRGT55FoB+TncF/DKYAeEGGmGMgLcbs8b3sbMjyCFtCldqGEnZlbQumVjJyqoRxzRrgEg7n3RPHCMswMZpVCf6KOt7K/ZGZzTjm1dUyN5nhnD38XjWUfILJQEtGVbMkOXZ2oBE30nuykGLZQixdEA0kwmA9c8taC9nYEcoswaX9Ka9fVrroEqoVAOe3Bk06f7srUX5VjdC1TqBuQ+nGCWcs1KaxWiQEKN1iiAW7WXoRl1bX50eGjF4aagslqnPmKylQCnWL7VWy3wKIhhr7nihRh/LJMrZ/iKAJRzQtiKq7yXf06WgzhWt+x4fe5KtVPqCJQydtRcr5adGJKGijiLLItX+dz0MKmJSp69voaLOWgLASiNa17J+QmcrK66GznkWoFqfVMAchwUpdcqEWut3TM4DzCAIddQLabaWUHL0bnkNCCiEvjSAZGSS24YijOwxgMyoSbBWnrrevt8AeFABez/jkBr1D39WrZqJxqL7rsQ6k2ZdEKwfKUMmr3pi2YNGqyGaFbkKnLgQSRL9dP5rp0olSN/GCmN9PakDe2Sfq/N8qtV6QUoYYvM7htPZMyov+bzjSCjeRIC1S/F812LOFjKnmG1Du16fQSYLCBfbm57BQnqeyHgRAHfUFg44Oc3zlhHas5fCeX5hGku02mldiB4ud8nAfzAiGKRwMVoHDOO84U8O0rGKBGw0KdP5MZotk0jwlfX3yMwI+MkKloPP5MdS3OcBRiJi5YtLmvswwwrLykhNQqCquFur0u0S/ViVu0T7Gxq8UAc28kwuZcThELysaG6SKnlVC0EPARpmWJIxjjp6QnvQlni1HxFMmEDe8xSCwh0sNPa4D4L8w5C6AMQF4IbSO7AoVD0rN3qeEynt7BxZ6DpHCQeWO6Tymq4dZkkmuHYE/fcTnvHn90j6TOc8SMpkOFuMMYbAy+tUJMBDJoNhzCP2cSrjD/KMbAS+ZYOKj+XaUSqhlAm1EOpsPMGM1MV0iXmeMU0Tdvs99vudOdEP2O8PICJMveP0egznVWt95bAiJjCNHsVkvXFpxQNc1+qW/VYhywIpo0qTBvYQpJhjqZS8tOakJ23dlOYoIkYTreJON/raWSslXKyDwdnl+cBj5VWOQ4M2bIKxNnQkG64yzd8eLBrA3HpDaSqTTZPTEqUDIkArTYN9Xb9wGbpo4BEhleTLOODBVKaXlZLmbnuKIOoIh0CO9tN+C50MWwA0A0Zzxz9/dNoXi8mDenmEvPEioMmczxD0ZTG8t2Bpfx6A4UoZGD3VabB3W4te+pifWFYdi5WSZwiZH7jaeYyxUlF5SHwS4pR6BCorbjCqaMZ7Aay8CAfsaSomVzHAsgreBJEFEcD2t/NB/284rP2TOytvFqdjvmZrWuLYtnZujop+8HUh1dL8lFGYCBBR3B7Ba6rTy7gOZD2wBz3T3t46fioEsc5AHiIvMaKLbYIRQIOAtTuQXc7Q64zfJJnGZx22D7tc6dCaH6ojU0cxz7PxN8OJJJOyz3sr89RR3adg4GZfCkoVlFa1BUpL+8HHZLKIx2+LzZGcNhgiOw0PMw2G8xDOw1wm9YpeyfZAphvB8RLq/AN3oE6YasX5fFY9RDRQt1RCJbdWqSyjaDB4aSEL0BUPLxi0j1CCBlMhCyZR53jdTZg6Yy8M5gYRjsqAk43HaWkHq3xi8qs6jyftgU7a+5paA7czSAQzkQXZREjQ2E/M6AIwmvIh6VhzB5cPWfkGC2imSLIopVpQaI+KALWYXcnWxqtOBk2BQNDVmUkFggJabM4mT3RhzXh/XlCnCn6Zce4nuFGCiNQuZm0vqGgZ+/1uj8Nhj8PhAELBPE8wideSXzom3msFmBtbh1krQR4Oe8y7vVbkooLz6aR64KHg/KRBW83+RZCzmF6Y5Kj4v8vqsoZl3mu+k9dSWFwNWJMRiv1sBMNhC6RKhiMtg7sMfmYbUK684aqQvv0pjTP/dk1iyrowielRtm+d5rpsPUIZx1z8dk72Cb1q0NCQFmw/k82xfv6k6/JHB9MTpl/u1Y7z5avazz7/omz227cIMBgUPs1hM38fU8F6zv7369dvazF487t/sn0ZvESPW8cJ/NzhGez9i/aU582CdFUXUHCZpflBkpyNAX9gZHi6E3yxq9ZNCo02A+j4Cv6DUHAPwUNIAl4euaUxPHxvPvZJ+VtK5Mmye1zxs0B75/0F1511jqP5+08924Cc110GMdhcK+vft2NJ9pnV/Zvz27u3j/uroHMJ00ncVF1/Xp9/K2g3bDSbE1nk9k/aXJlnQGuMsQo442ZP3iSX7+zHGklNdrfJTd0ryNgjtvQhv327x/M4VjR9Q15v7Fy+Nj9EZFRivTy+j31uJ69WfW1nCazH5jv5+sqHdGBy2A/jx5Zg/vwFP3HVOPy6xyvgICj9ybz1kTQr/ebX39C/dJxTTQxfy68E/J/PxWjBJ2tX8YAKwRnAtzdAfw0P3hx33rtvPeh/4PGf1QMdUIKILCxsrkmCSf71LeEm//7WO+PeRPABgPECPN5pD6X0kGuETYs03aI/v6DcvaDLDTw6sppCKb0D0yhf970otUBO2iq+63H7N1dqV9TS556R1ybKvaPUir40kAB1V4cyGv8h01jLcFVCRWYwnWrFNM9BuFi0vDNIMx/rYQKBIkqWRXtudNEskUp1lREXvdW65/QVVLISts4MWNSgVDWrXBX5YVSAZWQ1pqT80hBqS3K0u0PBBH+NOBagqqLdezPKyqE0r5jInWU0POvYpwT7t3AuBOL8IBm9ogWjlM/a4Ll++XBAJMrv4W9WacuNKmG8cuPKUCvTyG4g8oqKW81fvCsmuHxIDMhIMxH6Y8ciDSzPivt4VvyQG7SHy6h/H7/Daa1A6VrVYKAS+LASvnw973T03DuIhoEkQRlebvpN5iRIBgiH8DDCKO4bztiQQuA1Q3I7n3TOBzNIvY7I4y09WtGazfmYcaF0XRKjwsiahcKUkeBGNaS/iaDlxpNhafXe4dyK+QKgswC7Yejh3oFKkFERWgW0VasH0d7ZhUDwLNchRHqwjUjE6cNxSdRKtaKxPSpQIBZW6akaDbWFpWKxsABVS47re5WWde5a9WKa1vCJsY8dUOx3hu9DDHqDoQRfZIwWgVRBhWeweIYsIhNFLGteRMClolBHKyNjhaysu95teM9O/ciczFbWFhR96zu60TynAYLzsoB7w3KuWCarrFG9VKXNkTuWpWm2Q+voooFN3Fv0J4Q7KkvR4AsH1IZHBm6K0ypZ7RMfV2Asr+O5xemVC7Bp860DhBDKyYa7bfb3GKu5GaIUqwai+HvVYcBWKcQN2v6yVX/boJtuopfVfhyWz61UknCHfA9f7unhCGM1XllZVNQCEUIpDb2rMaw1baXC5jweFRX8HSWUCSbLIvJ32atjmTaOZy/bzpZdNrJ1h8F4tB+1e8NQ6sBQMNRw5g6nboBzZRS47ljPop9njGufUHOig8N46QsxnAFWNaEkYkkJfwjh0B5rIokIj3W8vqJj/mHkWq94PG8tko3xSuC+GnPF1kDLTDuNKlqiEIjgIA+8KXWKcp3O08NJhcAwg0muCGHlc6kEvro852Pw65XGeVZzTe8ijNokerjBuAQe2qTdQjhVrfYRGYyixq9ucooH1zgtiP3aQVw1m5NmcO3gaV7tAUCsdKvicLeKSTnYREt9S2SNjX9bbnz9WMsqVzHijXNDpnYUi/UwfvGGzWi1Z7LcPfghYn19z1PwWd+eYrwUqwCJuCe/g0irlsyWfU4FdVY8i9LwYEy7OTLdp2nSvqmsa9BNRtP+sSccj0ccT0e0tqgs7ZCR3E5Gg98gVjljI984GMf2JA2eUSIWGYLhcHfaKKNH6lRLrJBmKl6uu+NKzw42eKUkgKqvF41MaQDwSggyxuzrkjHBJyLiWbg2F1/XC8kQ4NawRK9rpf/TbIHHUlALgBnofYLrbO5ScL7srGlU3shYFZNX4SYMblbZgDajOui1fLqkeGOe43Cn0+ADgOw1c7TAxnxclN4kwzG5ZUKtamP/BZiGfHoNbpdbSleMRTNTrR8QuHi2MQEdmHaksQS2L5VsDzlXYalw0spw+Z0SNAhUwGzlqwsAYa2CwR2dxv6D0VdnV4DtU5OTXH4KeSVlnatTOvV75k3QxnVA6DsSHVmv4Po2p1sc7RMk+K5sro07mLVkuMm+XgLSq4T4c7dG4BhF4pGrMReT9fPbWBMVvGS86gee0uBPH3IkkZZuDxgAaMtwLRFpL3ECtF+6qLRamMHSIN667AKwiuPes9udxiyAdGCeBSwzemMsZcHInEf6l6kENGCxa5FktovEJjFiYIvJbIk7iQUX2LXrIIQVpHUMdo/SRWtlpw9X/cP2WKbLqz1osHT5K5znic6IWLlYl2eKJi/IPGvg/3I2GjuNAK1qGdEQSNdgafJsbHLdX43mgAalTFB7E3OzamViCQkyZC6xqkrwljeqb47y+Bx7n0AaBGoBo97yrBChJ54D0mQPL8PP7ugGQ6hby0Z9YjHd81jOphcTXGdi6Vh6gzRGnzr6aZQErtZmkASYdhXzNGE373A4HHA47DFNE6ZpVry1gAPuHZ0ZE++AHVAnC66jYsHhhPNyRj8qPTmfF5zPZ3z98t84nU44nY5YWrPAxCHTDlxwGXJLBQYuXjveOD2w0/HWmL6AjT/Q8BCs8Nj3R+JZce/7b39PChRcc6aP/dic90NQ+XYlY7pdIL87Rn11fGva53IPiaB/URdv+WwtnGAB7p+Bil8CH738uP4O1PuP4IdHLYG/mXemZtuxjC0v5pgmAB/gvda3113IAVvV6m86dMzX1/FH3rOliHTlnF+XP/1vXQUB8ID6+Re0P74OemFXO5w/CLBu9Pr+eK4O5l90vPeav2sYbznH3zr/1rU/mon+d+Lbm+NBlvMF69305w7Kny56/uAjx72UvidCSBm11vZV4K+N/N8B77eOYXsguD3kP/H4K3TQedD37q8A9r/+itcvXwCo87wCeP3yO3b4dHH965cvAI1ql2d8iSDm72Hyz8P3rTv+jYTuX3D82x3oby5ICPpvn8tRSNeJ7tuL8UzAzRUDN+EDurG3OvRkzV4DwPQMebqF4BlChI+/qmDy9Lv2RXFDiAq/hIkI/CygDxZNboJVZ8b5+RUfPmkPpOPjo/Uq0OMcgtV6/LupahSsCCZzhJzOTTO+88zFFXgCSFaboCXDlQESfWmqzC1noHfM884eQpGwpDBmEGoIpQSLIrbo13masd/tMO33EGa0tmiZCC+pBY1I3807jfKGGbi6luHcHw6odUJrZ1PYKro0zPOM4/kE1VIqem843N4CUKXyvCzhcHBnk0ZMF8CypPWcjtujmff7SXs+s57zjIYCU0Q7o3EHdY1K7/wK5hmL9Qf+8NsHPP63gKF9t0rRnvRhyLxT8al5D3BTXjkkeTfM6HUMYH+nWYjLcwunhpbL8lKBArFUTTZFITPKYWsa7JKFUW1OoFHOsRpMLCja+gJCjVTyisP9vTrWnhj8JJjvqzmTxBw2urbtoaHLcyiMgmcUgRpQ8QLCAULHoczDAzAEM27A8rISTpm7KqDcQ9FkFi2NbwYndZzoWDxzw41Go9ybK+muJFdkB8KIgPS1MapB9p0wjPkGl7XxwK+zFShFDXKvi8V8G9Yl44GvUzkQ2rGZ0OUZOj2cF2uD+TBOhFfEHkeGI2oQMIc9wzKUYRkNnq1QNXqeKL1H/1fIDFIFGkFfCGWvkO6taaYIkSZGhhI0cMFn27lr1gY0k6t6OX1fi0Lo0rQNRTh5bDxmYCMrhUbWe1CrRY9Je6aYPreoU6AQ0FoQ0ao1J9SRbk5hNdy4sdGVa8UNl1AVjiWMk73zcOgb6SwzNNiGi8K/uHNSgUOkiRwQ0XLygO5fwx3u5qQuHEYfYi/nziH8hWHV1p3MeeF8gW1eYeC3Mn8QM6T2HlHfdbFsdyvz5yVze+tYlrNmOywtysWzlYUtQuDuK607hM2xJ84bNr0ddWxeXlJGtrnxkQh+cQ8sO/zX9NCaOuuYbP5qdPKymGTbzuih97Q0dtiWkaldQJh3O+UBEaRl6y1tGC2ZIbY+fsjl9FKv0jLaoMO5zEoPuTiyw50uU32HoYUU1x3f1YGu82/Wr7Z7QIMZbNyxH0a+1BczghIsm5xYRmuD3NjOvosb5btWgXEDJgTGSzzjLpMky/hOxsScZXVNJBMRlKvOy6GMrh2dSvMZDGE1ZHqVBgWqOHCDjuuGz06hPG697rvZxlePIUO6kyW+p2UNBzKZki0DW+IRMTeYg2s4QdROmKqQWGYxmRO9ulMKwymWlWYBAFrLyhLy8YCx0/RwoMdE1g6emBxBW1SkecN5FVnQUPFlUDlUakEljS4vMmgNpJhjHCOzEwN3CgHoFVw6ChdwYXPaSsgJnmnOPP55r+zsdBjVL4YcICaPiAMtT2l1+HwTrqTlvLyRArLDaiEjM9HbRqR7LjIssJUHskxgtJ/8Goly65TO+VIGXTM+cs284MEuda6YvTUSipXSVUfDNFl0/2EP7j1aUQDaX/y8LKCq8vjpdMLz8xOen5/w+vKEZmVgA1oiTuqhfiotFa+l9gNk5qgTCCu9LvM8AidMDuPezDnT0ZYF4rxqtYKyQlmBYKolHE/rPQKAnXS4vCPwfsssoi0NRKwNA6VnZMP5CsLr9+QM9qIyAm0s9PY0sKhexazliQ90h91+BiphP004n46YZy3767ILOcYE33S5L8muwHD4wIMwSgyADMeMiBkGalZuOTitKeBjR7lJ8jcQ72eW0RprjXHjr/0UMFSn2NgPzRxrsOzzkJMsmjHCZO1xdWhD+v/e0R0OIG1xIwrTLoQiBcIdbHIY81gnEYptb1KIyhyjoIcFcjgvkFXslj1Iq7YUhT2zynqlamW0UkZ57EJapc5DcIXF5BIZe8FlLOcdSXbTTPoBXueRo4IMVm3HLteC1iTLvrCsHbjuPA+5LqDtz+42Ft3E7DyvC6jSkLs3/F9sYN/lyI7LtYwgFChsRwLB2Gf+5AimdjZG45pq1ap6Wwt9bWko06SOK98HvTvBQvZ+OcX3qlcCdcxO0wRUpbka9F+iYgsBYGjZ7sGPko5iCkvAWIZzVytn2WKZzJ6gaDgukR3LMJtWlJIfuqX6ebVKQoVmdXpGfbEKgRQiAJkM2pEdiKrzWmUFQyBHpQgC6Rr8qbhZUcqEedY5t/0BnTvqPOl+sB7phVTu1AojDO6A0CgMLTaHWgSwIL9CQOuALA1EPej+CMAX1NTyT2zvqT0J6DaFDqRAq2FbA0QTQMR5MuAKAyXc830AN+zb2jKb7ceraHklBc8G5G72MUbhHVRbbSHjlUqYdjMOO80e3+922O32mGoxJ/qkc2FBoRtNlvngOoKOoxPQLOO99Y7z0nA+L1iWM87LgtfjK5ZlwdK70koLrF0LuYFugRcyNoSLkWMvpo29pj/5kRZ4k+Dh9BcioP0OhBP4pM/zsDhB0XZjNKotwPac23+Cn8W4B63JZcDz4aR+OEVplTUOqInSK8V0Fsz3ADdGh+nl3XDFiG+OAWoJXwI2aQ8PbmzZ64ZHbp9e/lCZqv7qfM9+t/3dIdbupUTp+K2ou52zYAQLuMjg9sKFBCSPeOvwjPDiSx5Lf2/ZsA9KX0SvfQMNcCfrHua3Msayep995vH6HFeXiqiVn9Sh7YdnnL+Vaf/W+CTeI8Af3+L66dfPAAT05Q8QtNcwQx1ZDleni/n5l/3a5YI/+rjeiNP/qSO//y8+6v13iVysRf4tf37vGcAVPSkx9NUzflqv99t+7D4NnhQsVtFlP00hs68HjpB39P/X5zlMJ3bdGzRhG3Q4ROsst+p5ldbz1RhOZrtFhEbL28213ztG4OpaZlo9avPEl83ey7+7bjsyB39oGAG3qSbdNj2iUAV7otGVG7e4ub3sZ/bGj177Z7dvvif3RweUjjkHOH35EtdOGHv8jK/ouAwEA4D/+/f/jsH9LwHmz59w+uOPd8vIB3r/wOhF6M9uy//Y45/PQCcznYtvShfIMZSp/D0Z2n7mcEF+u37OPD0yzxlcwUc1XuAZiPLcGqV7/LoVIOgCkQiE5fEB04c7/Z3VsVGs1NMCoCF3aX1j3DZVFhW4c0mcfLArcxv6kwV6f6AbjZbljN1uBjfr51Qut1YQ6lLB1MNxPk0T5t0Ou/2Mw+6A3X5vGRKLZZkLlvMZx9MJc60qLDFHv56JOqR2NYZPxSQvAktDwYTj8RW73YTTuQFFy3IuywIQsJwadvu94gLDDMmaDT92dUEBq/HEHIEELRcq5gQJJ6LDSAStW9Z5ISyPZ3XUaUpCONlvP93g8Y+jMUyFUMEturxEOba8GCGspGVgQ6hdvVXFs3c0eY5Ss36n2L4QqPO7J0ECAKoIFgFmXWiQlYg9PS04fCwgOQA4BsPYCqAxSmZMdIfWu8Gzo340x8gms6E9DAOlM+iSRANlSq9gJ5gyWK0qAq8r4rtSvOCM+YpQlYwB/NhB99pTWJVj628rthuT0DJuzxKOREUFf7TEwozL2Mqhr4zOAWtgmmYs51MIK+VQQMdkVIPeWw+UhLr8rPUYQ5Dwq2jEtOaxgkYJ25xhsBXQaOf9cd0p4QYewyMvcx4Pp6T1jPPDOTPWJuBN6TsLGqlxPdaV4RfBs6J00fT5alQwHGLRuUlXozq0BKI70JDgKiLDMGSCo3hhSHO+qkx2BQ8CC4bTUFhG1noqN0EESC2qFE5KB4pNXJO1LTDAKltMrGU1YfAIOAhMiSTN7q4VQgySGq0ZtOR1Db4Q5a9tLQob3YLOq7NYdkzXQBcCuGtPVO8JOIlmx6NaoJAp9c2MJmIl48P5kjKulAaNOcTSpXV3ojtwcetYtO+cDTDXRFXj7XmfSsbNjNjbv98WztS4zWApEG5WRruZA9YMl2olXo3G741KDJZVUgoiC8arfAzGM/YjXaFBCg99MrOXWZTYP0TrPsYApewVhJNwOEZJqxtaaUx38isV9WABsWw7rQBBDmKLhqiW2aVOx+GAjJ0mMgIKfOG3S+DbmgBaieiXa7EVltYZ6rK6znsKi8OLCKjqRF+vVuIZidaMLJa0n+Fodbk215SbHICVvw8ycv2u9bxjVhj9Ey0gBgLpQFQRAqLFTMEIovGStQPP3cXhDrMsc4zfxOabSC5GwEH6dBDla6N0cUXt3nNaDbxwOJDloxOpWJUy40XUWCZESic9cxxQmY8KtHug7SIa/0A0LPo6GXPkVrS2oeMygnf01RrgpO2/JZyuEbwiCSXeM95899cfuWMtU7ixx1fLVZpVVQv7IwdFhIkg8+qijhQtsz+qyej+lrH/cblf8+EBGvM0R2b5NFVUskpT1hOdyLOKteaWCGuG2ssLltbwejxq1vSy4Pn5GS8vz3h8BWCvAAAgAElEQVR9PWowah+GDKWnDbUWLK1jnqvKWi7/GTqKB1pRgl8KkCCo0dp7nWvZ5cvqNRn+URY8yYK1eIDeEE886M7H3LvKJkQaNBvLMOo5D3jCskvhMo9nDuu1xZxO1fpBl+JOXsdHB4DRZBZ0Uvo3zQ3TPGPezdgfDrpOFhxxPJ8hsmDsgxXpW1e9WuGDm58G/gT72hgmdW6JHh7WfW7ey5LwwwM+L3ZL3hh5jPA9MuQhp3YrI6CLL11W4sP6He6UBrS6GUPEW64BuTe0viEB0eUhXyd/nj877bkYjtF6Le/OIGF01tLEJFVjQIli7orfsJY+KeNcLC/dZVYZY+PgAwC5x3NL2waxUbhhvT/yt3i+y9cBN4kWAX7fdhXZIwmMcJdSrJKA0apB0mNYjmpB/q4iKtbtlmKxLy/NR+gFKxly/fw6T6P6hMmgy9Kwm6e0ebb8QuJawOhVqdC2IRrsRQxw6VYNiqIfuq+pZz67vDccaKZHRon+9E4o79RMY5MAYq+bbGLrPHS1VDkJGC38VAGDsPF2IFpFqa9/RXwjEF5BaGXeUdCbDpJIC4hH0LZoYAwXQu9W4QtiPdYrpkntSx4oHPZ9grYCJI6qW8rLJXQWNqd8Ic/QBsjkCohoP++eA6gVd0q1rPjm9iAGkcu5FmCNgY/uAO1dKxOK8T4KfEiVewB477Qs7xLRCGow+q/PNqevyWCFCjqNVo0axE6Rre5tAoqV42UWnI6v4N0O3ZJL0LtWZ+hnYA/UV2svYDh27GcczwuW1vTfcsbx6Rn7Dx/Qe8fh7iN2FozYO+Pb168gtoQbSUFRLkxnvFzJxj97uOApIzkBACLg/QQ5Drd2tmuJt0cisuSkjeMuHXnnvzfUoFEYchXRRsfloSu9fnvEfHcbasG1UVzjSfq09wFHAPo3BuMp9krhe8WXUbpyUHfbh/PnT8CXr1horFReue3YCEAVlTsXSbayzeBXz7IHlXQeAObfZpWZ6FcQCKfffw8nOtL9HyTAFset7593ITPceW9B8S790DEc117C/Ufe4QdhONGL730CRuXLNcX2zzy/J7LS8j/x7i18fvb4mXf9K4/39K737v3Z4Pe/ArPtUUgr4y48grkcR6+9h2Jb/tjqZZrjnz88froiPieZutCozJvf9fPH9++UK58M4CDA6xW5/0eP67AYlGwEH/ovPw7zC13kT47x2rHF1u2ovofN2z3rtDL/3tPf23vdt/lAwKekynwlpX1e6l0A/L8k+D8Jef4qvfn/8/GPOdAdWYc4f2VL0FpRz8rfZRb6GsU26hUA3bTbCJiOp0AuFkQG5xmPJhAQSiIB569PmIhwXo1LCXqFoOEWd7/NOJ4WaL9mVaqWlxdUFBz/+ILd/f13y7fnY7EyVSyMxiVFHA0Y+WcujuylN9VIayXboQ4aADifT9YnTrAsZ8zTjDU6JG5QVOGgRXtPTfOMeZ5we3ODw36Pw+0N5nlnSjHh9fUVrS1KqL2PlDCoFrQmqNTRiNEa4/XlBdy6jrUAvIhGDDGwnDvAogpGmTDVGc8vL9jtD1qmigmoms3Z2B1smkkj0gGZNIvVlQ8inM4dh9sDbm9u8Hp81fKTArDhVuMXVT7aDo1b9JyHwXc5LWiPLZyvzIz+xGGH7s88Iu6t/5abSjPTIncnd8WP15dHdZ5bpoKum2E1aTbuGYkZmbG4mXK7AJhNqVNMfUFrFWHMMWe2Z8IXV7AFILnBdK/l0trTE0gOGIY0UwyILNtV0PG8Lp9reycyBWGRr9DIf1clAXV2etSnvUDR7FHA91ploZSK83KGQDRTXYCSep/r/BiFKvY3h1AixTPuABRzxHq/UUnvA8WHqz/wk26sbN7T24IySqlxvfsaCIhyuou69e1pkmeMsid0c6qvnUXaU5x8025/tx90qbx2sqkmZhl0x1dELCaljoggZzMd7aGG9loMV/UdnT0DPgcXEarV0BT0KK3plSccjCuNCUqP53kGCDGmyzlLaGACNaCGs4s0gEVgEcEE7HcTgFHlwY9KGrnfE95lEyaVqopMeGT0PfoIpfgeuKXOOM9gtDH0pIoRYeqTVobvgFTPuIBmnHhWOnP0tWah5JgfARWjP6L1ki8VExhsMKpiJSKjXyBWhiWJBGDLOuyMLh2FrdQ+TRCxEoDeEoLZWiPMQFGH7dKbZQUuVtaYof1VvUSlYrtE1oEbmWO5h5PGs9hkZFUMJ4B/Oq68pUrmcxRfg/6G0VeP/B4CjHH7HhZ1+HhmtABSjH71DibWjEZo3zyxIJn1UMYeFPM61DLwnEm8CqxfBtmMUcc38HN7ZAP8ynnu2cYpeMLlnWplLdnT4Gxfal9ID74assBwFIiWR7Z3sdHySgQULaWLtIfM54NwHhtshS7N2heVMy7meQ0GEtenm8cN6VzwMEcXSfMLejKCLTN8afsdOcjqmgzpr8/0dFDz1XcCsjVp5azazAGCmIM7oMSy5pzuaFaql4DVDLtqpbNzmxvfTyIwRr7VlNdj2BrlxPu7bA+j26t7lAChmkFOpFi1kxZb1Y37OZBrGLwIoBRex4ZPAgvjB8Icbwr+MAQq9mlkuoDYHcgFXrnF5zn20ghA1KXp4K6OhtGuZfCiy325zRH5e4+3dJoV2bA9XJJTFyAL5EPIOBGYZHRD24EM451XaNiSpYt3GU56RYOpTthNM+adNiSqlVDNgS6CyKoT6Sb3NZwXxuvxqHoUa7Dr8fiK4/GI8+mM3keWZWRJFC0KWonQWketAooSyc4yxLKoLRBwmjQQqL9G2X4WBrfFHIx9zNHlJ7m+Fyh9H5+Izy0GBP3AqC+wWlcPvhSJoL3A0c31Ako9nI2/mkwf+MzQ0tQCzPMc95+XMw43Wrlrf9gBvWIqhN4bGjOOr69wZ70sDWWeYlICMfFnzICtogcAUDG5pPdosUUEc3qt57uCl8kGhZAqI/h2dl427h0isOlRx8V+M7o0+YpMAFqQhplm5V+kwWfV3lWrVkBCM37n1c6wyS7LcqKow0yKlRsoglJMfm0d4YSgTM8pcE4DoWAwFM38r2vjeW998EQi9NoxTVoVikEWACzWvJAw0YTOAKOZnOj6m45bM829dU/6LfEdcuLrdFQEhdZyZV/Og/dmgiDuKA+UgUMsWrrQ0DNZxlzXnwQ4lw7SrG0b9PkU73O45vdvZYhrssG2ClLACginr58bVTlSJroIVm2oSKwXNMBLjyC71rv21E4bgK06j2dce/BhtfZR7izXMt/aRqlYkONGQhwQ7hLVgfpKjl7LcV4tRGkFVjjq1YcIAIsmRmQ5xyu3OZ8oUa0P0CAfAljbYhSalHeIVz0a+prC2DK82HCclKYJawsfb0sFwwRmrShxLoTDYYfOcwR0a2DBBNXDRuCxysPV+pkrDsVe6N1a+CFk50JFg0UFoK7whnR0bqYn6DUCdYQTirULNEc/d6htIcuNhl2sfcoddxwILk+qTFmMP7i+GoROt/k0g0gDM5yHF4hWqaAhDxcqEOqgW3OiL3ttXCSCwoJ5t8O00z7xGuhQcT6dxnYxHZZ2O8iLZuhVqiiT8vCn4zNejmcsbUHrDa11HJ+f0ZwPWJ96l8JMVEM1m2GtxdagrWijo4frQxJzl9DsBlS0RuDYB0OGpE7JSQ3LSAfoaJn+K70y8RpG0OEuMvgZe4/fFCZG8CYZW3F/wHHz3Ztwu/pVYw9yyPjVAeD72v6O4WJknvv3HT5CQ6OeABk2sm5zFSgnJAjonsBfBSCBh8q1r99ivARg/uV+yIWloIddUAfhIW+ekejfF5+3CfWLz4Pyuq3/JgCVBfXzJ2vhN+QWNl5FBWaD0GMriU8CEO7R6CHGdy/rjPatxuJjIKgD6DZd486kO9b1+EbqPF9j2zi3LTjnWoD3UN9mxN8nfOnwyp6E9jtD8G2wvPS+Al/DKGwIQJ87Hp2gakoMXSDhXzuy7PpM66CCv/cY+1e/Jt6d+Nr6juvHYP+Dv6/0+0SPt08SvP3ceL7rVO9eqceZm41L39eYQfBA3PGMQutge9fltvPeVhtzsib+Dhq4DmR8Wd1h/JmwWBmVyRShapWo/HKC+iNabyG1bZ94eTa91+X7N67D5vzAN4XzjQiOSHvkwrG1udFFVfvugWCReW78gUV5ulYIMB4CisqVWc/bbqs/tQ22YuyfPN7b4h5o49cOSVZ7lBONICC//hdZw99pYk4U9ns+pms/C9C/8MXabY/8+4+RqMT5xXXDv5m4/ZuPfzQD3YUY34rXjMwRDXxh7Px7Dl/SrdnMy91so+kXXCk9KrDMasHNvQoOVArqhxrOKYYCewFQWr9g2O8N0A0LnJlGZrurIV0iJTPDknVVYJomzPs9Xp6f1DgTQh+CUkciqkCjQa1s6K7A+i4dcHd3i7uP99hNE8qk5Rt3+x1OxxOInjTKHmdIKWi8YGmvqLP382UrFcumG6kTzYld703nTcDz0xNqrbg53IBqUWMzXAHUbE6YARoAhCqIGMwVtWiPRaoVVEqUl7+7ucWyLAY7E4Q7o7eCLiec24s67l4Y5cZLNRNYRga1iOTkLVuyLD7pZ3aujIhlvVbLCY7qCuIGLlHgD8e7U2vLNkh7Ijt1AUr+H6OuwcF9kEOAKfCyVwSWGzBeALlZoSD3juXhUZUOU2C3Rkf/23GsA5FVVOkOHeuy7a5UFdyifPTsKRpKTXr2Shg1XO19gfBu9HdMEfWygr9voqwsSYBDxPvguaDjwRFqGBBh0Kxn1dHrtw+nV7kh9FeHPq0gs+0X6UcWZIMWJsMrJRwZMHCjOSKgYZxIQNq+y56tzojNoqURrRhaARyRAjfVoqIjMZRWkKUsB9vHq8y30KodN/UZrQu0JWHaJ4AZ2PTdnmktZRiALo1+ZnhOWYguuLrj1Ich1puODGZuhNQSgRw90O3hFlylWRBuxHKBz+HpNDIyScSHZsZHV2DJnUAERM/E4TTLgmmhogEPZA56F6RNAIYobCqKGpNKUcO3CDz9UnvTNrRuAnTV79wZrbfokcedUYpYdGpPTj3P3jQDgeOfOC7aP6gzegBO0r/x3Z0P+dza5bqldQn3Ew3LsoDvC/3DFHgXL42GgrXnco+5qPGTLYCpEFbVYPz+yL65KN0ho+w0+XtHFPrKqETbf+M8ADU6ooSB1Y0eWh55CP6FK+rU0blYJQKVC2pVI6NnLaszZ/CaMHbzKAgoEA0Smbx8LGlgSBd4qaVS2PiRUyIKB7oUw0UUy0bO62HGTxTbNyVwZOBLonP2rOFMJONnK6aWQC+bc98hfG6koiuO/+t3rOjye2ffO5zHDWdnQD/GZ8Rc30KaoVeqrn8t1kPYS8OKZd+LSZUSIQ6rOUp6P+L97kxA0PIt7873+KyNeWhSFzMKE4Aa84KI4oDNjZD5iO/vYQhi9lzqEDUT3Rs9QovJas5zpQBMqQ+wO3ScLwHBjz1DlbmgF8twF8Dr4GS4/MjKyg9c896xVRYHvXA6MniDO1ejAgmQqht5Rlzi63nvi1g7AMcpxB5/S2EtRbOh53mH3W7GbrfXIFUSROlRK1HqjjHP6l9OJ+38FKWIVXY6n084n7T3+Vgz4wPi95upeBKjOebuJECkgyHakoUEXQgVqVy1Z+X2fnVObhQDoNVhrjjc4m9J9xhsJ/NtOobUqeJ8XgDZ6mFYVTPSZ/saXxmTjLnqvxprNNinOzIFTgb9gc6TaqnYT3vQrJnpu9MJT09PADxASuM/+3mBrDBYEAGYgDn1TC4rZDKEykCn5zMOH3bwXvLfIbMAgH7UP6bb69cBGnTKfH3NLiEYgEt/Fly0QbFNLGib07SWFdN4g7O6TJd+jLWwDFwWgdexZaPBWhZdW5Hluu4ykCl0PS3CpHyNuYYM43IldcKgZaoP9i4jA90CrEKmDQfdoO2BuMgckVbwIZQ3Cdnq+syfEo1V/1Siu5uHuUTn86/Ws9n746lDM/Eju49bU5yuqZrBhYynRyHCm4iY4K7wJhSTcfzgltw38WBJ24JQZ+Nvi64riwZ/t84ovWM3G1zYWx9160pEKNS1aIoFbeo1WtkKMlqNdAvWZkE4jCEDH2NNM0yRZKaUzSYy9C+Ha/B6m+RV+YcodAsRzZbv1IGuv7PxedexcpUDl2Fr3UHkbBmmRkf8mQ5gsVLWE4euQGmJtZ2QB1wYnps9xwNyaq1BxVQu8DYYYq1tdF9RsZLjtaIzo3StdJLbSmklG2A5W/WukPcBoKzwRR25xqtNNna+rU7+GvRoOM0HDVE51nJVvdKT8ywic96LVZIZDpcIyioAyQmakKOpCdrWo2NZ2or3L8ejjqlpcEE57CEi2E2z4vWkSRVPxyOOyxmdO5anpoku3PHw7avhTcGHDx9jm919uA/a9PDgztrhiE7LjLw3XUak1bnMHdPNmT85DBz3TbfzDE7KtwWt2mA40QjiT0/XOxw/x0iwueatw3ckiwd46rzdLqa64WY67xyMBxi7WY/XNogneEEeUeX+ynzW82jfHlDvPwLkYdN61Pt70DcBfTJd6+ERRT6gfFZhh789jHddeb7/nSkwAZh+/RSyt54bskLINmk+tHnO7rdfFQ6/2zjxCxjfsqiyui/PdXu8BW53FhOulUxfH54Vnu/dviPjjPdEL/galTbzP6Wll4767x0+1/wuf9/fddz+nQ/7weMtP873hrKFQX7W95xwWer97ph+4Jp3nyEZN13ekcEDrvDgfFyjhJdjWxG+K88gDFtVskO7rhhXxS//wHEpM76zHa8eHqDntlDAApfVgRKyqfvy3ju2cP93HD/7zu3qZy0qO9kBdax/St8f7SbPQpd0LjvfCUDH138pLL6zZf9HHf94CfehtP3kcmWn4JUj/5LXyov7bdev4ANAT9pLgO5MeHuCq4iOtJ5NSyAU3ALygkJ3ELxC8IL2cIt213F6esb84TYpOir6Egj88vJdop8HvTPl79R6GoUK2Z41oOBIzj2DQBBtSkxLBFSA3W4PEcY87QDu60hSF3jJMy0JUylgc0QDEw6HG9ze3eLDh4+4//gRu90O034H5o79ywuen19AZA4LiJa9Yu35CxllhJlZ62yWSRUbsrLGBIhoD7cJApBGzp6XMyapqtBIh/d7JyqQoo6kUqs6glidC9NcUZcJlQi1TihU0JaGXz59QlsWnE4nzPOE1jv4DPS24PTyqL3AewfzGfIwY7qrIRwPrBDQHdCehoMJAPYf79GeGAs9I9xGolHKIbYLoX4oaE86DwhjKd5jyaO9HZdTGTMxB3oYXRVhzjSifKsA/OJsg4cjiEfEqZdlavIEfLsDBCgfCvrjDdxGIVDjzenBBXwdlOfwNmgAgWd5eCuEGLcL0aIsLcqMSP5DlWMiQpduXMFLHN/aI15AuBv7mlVYP72e1NkwVVWWKFMTca3jTadxay1F4AOewRSvkY6KCcfjEYDuG3d2+lqTGYoYAj6ZQgUXU84QzPDM0GFcQsomRmSQ+TEc1f4OH59nnOveCiCPKQAApv2MqV52dlIHzDDMZ8cDJcjRXCBtOBc8AEQN32L9OhWvc2fV8AeJ4/lacXLXmTviiAidfc3GAqnBknE+nwEizHUKQ6bvpUKE290OtRa8njuItI8fs0bGMxf0vlhVhwQHsch0Mu3MjFiR5W7CmBsSRAjSoHiyj+ULmutwKWzlY93JaBYAd/QQCFZ7HQTNLnVcyuV3CQAsg6OYQ9UVcz8XOF2sLCAIRM1gw2hLsb6exnO6aHlG0cAkl/Y9aKCLVvvorBnq3bJrtpUmvKe2GIy0JYZglKaKjb35PuA21sE/tkqQbC4QeIx8cECHlQLLjHcS2dhRiSPKuBp95sVKoLIZgr1SABBVBaAVP9zY64E9jg+X48yzW6u9eq85x0vR8vxUUAqSo1ANf7VWLcdrvYX9vaUUVKngwuhW3l3XrqOUiqlM5kQvl3DUzWu9aBGBWQQZFWssSI0AMLGG+2sDSKMLlpkkAfBwoGt/Sv1NshGRAAZr72rqWkVGSlrSQddUsSsBwuGAWEPXn+uBLD8uhNP6T6OZEgQrwSvAJttTmy/bl1PwTKfT7jwRy7pWo/D2GXaD08PocV4i8G9K0eMC7QUuSIF7G0BssVK3qgaOiP4ZMqEbe5RnJ8eyz5BGQUINFqoAC5qWzhk8yZwChcs6uMjKaiqqj9YT2aFLNPhisSDNUsbeUVlAf2fRyhrtou857P5iJcb1Gc0rODGDercuEhtH6oVc4PDc0KHVb3/tyLzX17BgOM89kCaqEfg6KBsIGbKYTOtGSraAqRxUUGpVfSVVMYhgCuOnZHCbpgn73Q6zVZnS/ah9eltnCDrO57MZjBXup9cXdQj1PoIaAPRlSaWnPaPSHenquCmlR9aiEEXQIkoBdy+kq5nuIGBZOKqSaPAQ0Bd3muZMU4q5e7YoJAdLSIwnH54ZuwrQMqFGxDLBLQA3G5lXGuzqy6WBLwd5ROlio8GeXax7UiJozPei308AatFqN8WcQ9M02RoP/mzEXp+wKhGv50LPE5NBa8VpWZTGQjDdVJWRj2yVjByPkqwCIIx2e9N1O6+doe8csvqLIFYOus6EUnYgmyt3pbPzpDI1rD2XNEBL16/3M4FCzLtw9tq6UnXHo9FIwQgog8pChSZw0Z7B8BYUIhaoNpiROyGbBQhocJyerzSrs60QltMZvWqAJEQgpYKKKG1dGrg1MDdrJ2SBjp1j/7gesJ0TXI53HmZOWA/C5r4EXAaMDB4UYuGgfCFCuANdxh4OHFt/hF7k48iKQYJ9BIbLcJb13rWtwRUmFkGo6w2WLkmBVL4WRFZWfQRElnkEJvKijvtBXH28+nudq9Jie6jzLQ865cLWD5zQTQMm41XuvOu9o7cGbnoPHIasdhHuiUbmajrAaNlmODZZf3Ddz8Mhiz7qDzq/C6AadKbZA2Fc7iq2RlrRAfCAdw1wEcdNMGCJDS4rh8woSqlqqeilR8uUlVboy0w6v2K2O+nmkk/VvlTmtnmxoFMPXC1UMNUh+7NX8BEO2bkLUIRws9OKUcwMmWaASOGvvXJiXKr3qNzrsoi39WNrH1SpwgPvalEHNDPCqR94Ezr7qEyFvBeg+88DUAz1A1/JZUgMciqkNIawA7qgogFEOD0+gW9uwqGv0yGcjRfXPmkGelcH+xlnzdYrWvvw5XTGwk2rDraj6s2GL2Jr2lqDqzsj4Inwyy+f8PjwTfXOolnq0hvAvvMlxFuX2f28g6XE5Nd0YSNpD1kn9qTLhDwup8u73VnkATF+mcvhIFrduqUmhPWoIG4L1bu0UKRm0HtlAA86p1hbxc/+B4eth/18niME86dPOP+xoONJcW8lf4wxMQR4+Ibp0z36N6/2uHakhAT0jYFPFgkT9hagfnZdi0D39/ZghWcx25JTk3ZJZgGoNk4Adp8/xVz1kfrs3jva7x27/zXb+q9/r7hHxwNIgLv//b/x/F//hYJ77H/7jPZ7V+e5z2ew19XqZ0d1zqDMQLvmKH9jSqvj6cp922cQLh1zObM//07pvF83gfCLjfMb+TUJU+3PbYLW9dH82OG95NnG8DMO/Z89XAaV1TlZfcb5ze/bg7b7Ndkt1070QVeDBn1njNtlfg+SF/IWvCIMACJ04dUz8zgBrcIgkipvpA+CV2kw3waSnObzs0mFc9j2dYFWeApbI23mZjpAtaqWjYeMcV2aWg3v7fNJJwFwEaR8cR8BNyki5qofLJ+j7U8GR2+bmW2mgrCbtaVFkDNd2ajvbO+fP95BpC2feYvvvHVsW1t8I80wz3TKS7Fvh3HtHW+995E0A/2tYJ8fHfd2ni6Xvv3E/5nHP+5Az0cAOJw1cvG7+O8/ccjm76249krARwgIdyh4drE/CThr5J0AeEG77fIzCPQ8yCxt5uGEcvvs98Zei2ZhJsrloiAARM+q1b1JUfCniZgx0cox1lq1B+GuqnG3+pXqPJlMYCQizIc9qHdM84T9fof9/mCZ6Dc4HPaoOy2HXqdJFS1mnNuCLoJ5J6ggtGkBn85rhmeCtGcfsRlFSgFKnVBrBfeOaZrA3NEbcD6dUOoEYqDOMwp1dO5ojTELR0m/Ys7NUoBpmrDbzVGO8vnxCXcfbtEWU65FBT9VaGcwnyLLV5hVaYoIy7QOzwzBqwZU2C+nx4dgWkMlWAv+tH7QSqCWiKKyZ7gwEhm2nr1UklMk7ZENY8vv6FBBebK/BUDDMyru0B8tY/yDGzEE/Djwap0dbj0M0wbT6NU1c2YRMLHB52VtnARAH4ANmoZRnOVZFVXLUpcHH7FefW5nFCbcTLdhEAuw5kHEHSpZubO+1IrGDSINhCkcC4AKA0IFgiUe03tHlQKZRhiOOtAntANDTrZfMIQtvX+XVmEtslDckaHiZDDDyvshpsyCCwJCCQJuNBJc60scxmbyRwnEa3gVjfAfdMznk7SZ7auRfhKLwmZzKFtJr3GDJMFXhsC7eaoIQNY7MZbdHLZcdJ/0rkayjgKSjlZb9IobPGU9wALLduMxd0dkKmR6sq5M2RVQ1+xw9QmR/e1BEYbv5g0sZJm6RIFrY1WGg6iEk0yNYpVGxoI75h0IFNC3cJySHCLsqqS2riilYDdrecTWhjOlW7a5O8rc2SQi4GbOKcvWd7rnDvR1pmdWggxucT5zthXg8ecOQxrHJ1FO4cbBcBTIBi/NIbV9lkAgPWVyhWPH30RBi4rhggctOH+KTPI8PjgODeUmxhFrbdni5iCPkpP2Tneel7J2hAfcSfmZlq2qYDYHTB0O+oGP6f4YDGy7q/M4Z6SSw5JoBB05z1mvhD0q01mdt+9pv0FEwIXVoFx8mQz3zACrU/dAFLuGJPbOegJvHVe0hrfQTX7koh943WZMQ5EbeOqXMrzkr6z3N4xeQB19gGZnFqohZwCI1kL+noKiJU3ZYUghV/pCupy82rtwwxyNeLL02xhiUNQAACAASURBVLXd68/MymqZimYCN5cTdY1ZWIMmNrzGaVkhAIWs3YAGPPpnVDsqBdV63Jbk8CvFnKBsMhp3C/CxKiwuKZFm9GrPbjeEjz3uz4tji1tX1jYuexcPf+xYBa4lHPQe415Vonj1AdKA0MnkvM5sAYsU9MSr77TeNUAKThIpGRs8FGJURRjTJoPbhGmatUTspM4BkY62LGBmnJczzudTZJKDCMvSwNy1JYi1Dam1Kk9mjncPWmvyqxC813OJtQEsTVcdDdAqAsrzCkA9sjWJoFWlqIAi6JbSO3Dxt525tigXauVwBCqe9zayjIvTKxc0jf9wv25AUmgNWqtBVTUCFwInrHSvS47FA0u9GhIEfFww1YLdfsbSPqKKaB94tpUVK68rAmI25/FYf3fG+boLMEpZJ73By+QSCehQgkbxO0ay2UvGY916wp0C5MzGeFp/7ZclHJN+65R6W30teAYAzzwXXzAMvuJL5MECBKVFhSqo+rQJMN04+Dl55SENBvMscC/fTjB9jAaNCxg6PticqwWjweSwmtohMAmIrelVEwh3LKwO85yBDrFMdOezY8artbt6vMHuAp7OfkOmcpxd8w/E9827t8/Nf5DrQ2SwWzuILoZ4fXtCJMtcvj8HXxLewOJSLLx4m7c3UIdtql5AziVHoK87jfMTYH5q5h7eJpV7dH93MHrrSjeXM87LgmVROsndeViHBySQBbuHc0g8KxnhkM8Z+FERiMbCXdA74wPLsqDUEm3Ntllovq4MRhEtbS6FADanvAVDadICdA84XArH/oLJOKBRrUDVPOUBPfV9h9lWTLEaOpvAWkuNrGxyemJz7v4pEsFDlbScrpjuupubAQBo0NZWIETgHYEgxTPLC6rRITaZw+GjpfFDYEX1cYnqoigEkh5QjaotLvPCaa3tYXOiRJUYJJ6GEVzo/FC6r5MmofCuorc4qcGrImjLojpeB2QnIC4o3IBSsLDqpR54o+2CAKrFysj7fnf4+PMpZJNSKnpn3NyuS4ywAK/Pz1b6e8gXvl26762MmmTBTbktnAy8XO0z/5/T2kzP7G9JJ9f7/q8LblvymeVjX2OGxCf/3lA+6UzK5wL+Ci1HLtu56ff+tQN4imciP9//FtFELwD8lYNm59yQ/NnpCfwNKPf3KHVtF4znB6saUPeYsO9BzSmQt4BwndP5PfeO8tmp/qXtSfAQfz//13+l8RRMvwEimtF+/v2PGIeH7SmafIQkJ7vCB6siBNec539XyXLafG7hn3/fOtFdpukuh//14fz08R1J4V92/JnM82vXXht72BI3OCBv3fC3HaPqSzhrnfaIX5HxYnDdLO843c92jyzrvDWJrIL43xkXt7SECNEe5m89fhKJ31ySN2RYnVv6P61pistF1YJ7Sy2onSMA8T/lGPRrTSP+zCi/2QM+irrt3gpXFlx3rL917PEJL/iKh38HkfgnCNHfePzjDnQtbWbbYovsmQptBa/89crf28+3Dn9DxzMmfDDnn4BNmCn4CMIj2AQMFuAE4JffPuH196+o9/fgxzG4boSxAzg/PuPDr59NMdMIxiOA+/sPOD8+j0Fcw2Y7t7QeClMxh+ogukO5g0AdTbJ5hlHNKzqVgrcMI5wuQYfIlIRZl7AqalVBad4d1Hm+32umym5CqRU3h1scra/44eYGrTXc399DBGjLAnQGnxdMtzeobMqCGR6EOfoZs7D1ERbtrV4IxcrM98ZYWtPy7gAaSWS+tdbVSEdTZP5Hpiu0v/Y8TShTwW7eg0WwtIZSipbDagu6nLAwwokEK4UpAM7PrI7n2zucX55Q5Ab8bJGbuMH0QZ1R8pyEpJWhlNdLLUB79Kh6wUKEwmIZEWNvuDA7HKeOTR5QMvCcRbNUjwx8/kUziNrDRogT76cuw24lmolecIt6r6X4i2WPsTyjgrD7dIfnb48xFoGEsbyb4uMKAZtwWAzROl6hJcgcAgcIXjHRnWZvdy//plmt50fWtoC4hVZ3gPbd+qgOfYHg9Y9jzH2/55SBaYbEAOBQRDM5KcX7tylDJniJUrLWA1iJ/gKPxFbF1DObNevVDLgBARtFEKJh/CCXZIgiqNqNQIv1bqy2L3OWmpiDUwAro6u/kAwMC8HM+06adDbVCW7fCHgAmKZdlF91gyQBoJlArUJoRJ6vaGpW8H0RHA/tQkl4OQRZie8ivHKSDIN1MSdeQe8MYgZblq5pgYq3XPDMYr1fqxowulYVUHuMGXdEM9x0vSzzngEpwFw0lnqYrCV6jgsEZIEStFOhjMrIFKT0KYZbhc05lPcHy1hnc5p6+VYy56dnaBIEEMs4LCXe5cYNx+5i/0GnBJIa8Jugc69tQmnNKmk07YNmRkgqBWWaMNtaMqwiSNProjSuZ7LAKgoEPXIKh+RY3/LbS8Z2IdwTYk5rLFvfpZlTFEaZeJt/Md5H5oTQ8sPjCf28jOw+W5uRDayj8SAN50ljjb0aQNq7/nDaGgdkNTk3MJYygcoUznPPGq2WfUjJyb7OFEXSknTdSARVdJ9ome8SOOuGZvdPBB/3bHff4wJIahnQvX+v9YR3/Pft/dY6wq90K44MfNC9Nwxy20BCp3ve630s6ToIIV5I6YvxFQ94uFC8Qu/0dbw+ibXyslZ1Lye+wrw1sQtIpJebUZzNys5G80QiIS76VhNo8JP4Z7AksSodGlRIBM0GC/85xfsH7XWcHuAYaynr7/EvjX5Dr0Gj15iUGmVau5WT78QoLKm8/IB/QMfGTY53pPIZ3AgP5XsaQADjLyWc525I90yfkcml9NWzsWotVoXI+fLgjOwG7yw05eX147s4L9+/cPtQx/tErpLYNfgpgGjhEEFW6kQvpM5tiGbSu7N1mibMU6rOsnIyKgxL8QoT5qQdYpDxFAm4TVPBPGsAwjzNYGmRidd7w+l0wul8it7q3pO2Wz/a1g3XGSDwmChB+TBg9GAB0QwiKxEMBkuxIDI13ovAnL9dne29aaWhQpBueHBeAFiwhAiAvjbU2Qtjqxpu5kAwYCzRRWaMjKpOebXZSmgHDzZZq07e5VLCOcLpPqPCEYilgU8aqODZsupAWQcYhWHanLiLVc56eXnENO9ApUKomBMdGxwf1TayExmBF7AgRYL0jloremsxU78o2kLVEZo22gRsN8+l0TzD1KHPr+ak8bjiLOZhgTTSUthlD1Rlt4VI+0Vzv6ja67QrHFA6OAynlF9pcmdXmjDtXM5KOpZVoPFqPNEyiVPQESH6XAIInanWKVrfaMA6IL1hKtWckrre5/MRlQrORCbHwaonqXO1X2ScYyBrYJSMzxA0JdbN26Fc2BK3PDPbCYyeIDs6Q6jA+BsI5624HJxG5osyrknjSAPSfWO4GKQ5c6883DWu5cDpOCtDlhMBoueFDt4C1NJ9BSBSp2QRc/qQ2yhURnPckvQOpQOM7m1u2OmfgEhp0dIbzuczTssZ5/OCU2tmw+AIzuywFmI+diQ+Kqk1nYhmWUMAZqtg4LgqY58bsNg8iQSXw3xONg8a6+DyCdl6VTCIK6jquy5sS47zhcBcdSzdHipAkgJs3D0CCZ026R4SlOoyO0XwIAtrawNoQBaKWMUloFsQ3kJWbc/XlLQyXofqYtM8RwCRiPIMDfJqWNirS3j7pAEzCdlCcWbp6hzf1RpjFEH01tZry+AVuhwgElQv+QOBdIKcAZEzpE3gPaxfq0GTdb2nWsJ2UojANwas04xGJ8yvO3TqEDkD8wxeThZYNgNSojpdgeKLWPCh8iIG5hkFQHs9wWWzQoAWSND1eXx8wG6/TzoM4XBwk/GgeWK07HB7C2HB6+sL5nnWygClQoSxP9wDAL788SXwxvn7zf4Gx+PR9piX73eZSekGxeYzvTobxhx2BIBU0e+9R3s0DeLzzCBPKlK+7uELMaaE3oRhIPcrRu0V3wKStxCc1BQ8gPk+Wi9Nn37B8vXbShyKt4ngbA7lbt9L+rnGeD4YTXgC5IPpgB+w0BMqBWmOOUSqycNDcOP9L/fxdiKg/fFN7T/2+6jlM47XDZu4WfERk+uhe6KZ3DBNc7TbAUZARrGe9Lv/6zeICM6/f0nwWFe3AQgTKKymBYT5t09gYRy//AFAUIxXjICjSxlue2Qn+nul3N863CHlb8o90cV+/5jWI+OMYFQNmKE45aWXX7LOBQIk681DvxtHliy/P2/vER+yF/78/P/KsU2g2p773j3vZaIPxmbHe2ChzUJevea7QwNAWCzCae92VmgginU2w5SC7zINcL3EfTzaS/1ySJNVnXQ7ZREau4Ks7SKcAw37+8A/HVRjMb7kFGhtabkGBsoD3sDFx+9r4nrLWM61s/5g+ofbMq8dIzllHJWq8agS7wRgNk1RuVo0+efMgmo8mpv53nyZNxNUGK2DdfPxfaz8zpEW8a15Xkqtbx9enp0waPQHa2kGWELYG+94aw75eh/HZwEWfP2uM3475reebztT8fwv0pnvv+OfO/5RB7pQwmoai+2McLVTXJm4QhBz9Ny779zc7n+P0kIf4ntm5f7qHdSB3nvH7W+fcPyjodwXtOchBDCeV4LYPE042f0fiXB+fL4y3u3E7Dutv1NcpgRXYWUKu5iTI0qcDqBKEE67vXM4aquVuIre20iG6SQgubF3njVLZZom6xWmJSLbeTEnATDv9tjtTgBphko7nzFPE/rphOV0jv6eY7pmuCd1GomYIwiCdjrhcHOH0+kVnRmnlxd18syMCdrnCqYwNMt6UUeBkpXOsPJqpJHKVXuMzpZR0a2wTusthHfZATjPqqCIgHECsAPjiF25CyVj9B4v1rOTVUHJcs0bB0k2vpjTwxcooUN2yYZe4YRpI/j7Xrgh7dtWaQhdZwC7DUFfCTAiYHqByB34UVB+GdcIgPb1SaNTE/PT7IwxXC8LlEtKFdyCUNDBKLiL+ZQPH4Yx3fY3pywCVZRKjLFZ+Tv2Hmmx44DeGsiUQogqrj6q7IS2yeocqFi1gQ6i8TwRRn9SgaQWsVLLNr/b7PBNzIG89JsqgRT/pYNkJeTA7/V1swwtTXCmMIYHTpozatx+XQjJAkhAgTBGU0yyC5gMmPs60lkiMnysho6ps6D+f+S9aZcbN5I2+kQASVZJVZLVPTP3/v9fd+f02JZKtZEJRNwPsQCZZGlxu9vznhc+cpHJzMQWiH2hMNQbvtkNABadoPmdEGnbKAfEPK+DopA5sghMgKR5Eh6lIAhPUxObVGClJaSl0rg1j+SL1Ki+X+xKMmY33CDq69meKHnMiSsMVDUF4IgQD8PWcF7aMmVEVnMxYv0MwfImUonmvYgpZnRNvD8UOgP2oFu6pGkYLACJRbQpA1ywkMGxKdpXnM8noDVfP0uHWrqg12rKdxAaVrS2+rDj3EwUk2jSy8bvsr1ngpfvtZjTdRz5Fqu2EZ8mBIYEmBHxGobkYcgZyskhRMyviiUnwJWqlBkH3KqXCsjYr+siyHAQi2wqpZhBzAzoBpuFI4U7Z2Ru7rkvUNSiD7pv5SIIXOBRjKbUi/NEiUN3ks+0LqYs94iZSTluinsXJ9TxjphLYcCmjSoMDeRwscW36vScxdKDKniCqZk8utd1Ih5y/D0Myd8TrkejgV/meW94ydmI8j0ovcJsbppbPHR7nh0z+ftjbZFKWRWFUkQbe/aJyQEixqrOCIt231+PgiIzqG6KYm8wvmWYsR3TXHd1ONqsdzKImEF3JpaGizDBsmtbB//uEZqeAtlw86UIZuA79hXOU0ooSZ2/5DKcKoLmzUr/oP6CHd9PGPjakLpN0xXnXfo3chbu3TauOHG8jax+rIUxI84XAiLt3YbPPTp2Tt3uCv7CBZFXo6vxRrUW1KWCYNGznUv69CRfMislxVUwsa6+2eFsxlxRakUtFgUPsaxJtkUdrXec19WNiOLp4eGGvgHvhWYVjtHX2Lcx+wZV48/NAc7qsJKnL7SUqeyRjzZuygDhGc+ao0VhgQihZzYMfDeloK/Ujk/LV+Nt/B7n3Jr5604Ob/Cz7fyBSsv9Dzxfpywksb61sJVBogKmDm0CWsKAZ2vb1xUnAKUWyxSwNLTecF7byHaRg3QOIRwQJ57VpUV3TrEa8VGbN5yoQOF8erk83247Og2D183YrCN7p+qQffInnZjAfd8NlnFn0OJAZ7MyKXDdbJCItJczPYg9m3l9c+IY/IICQKTMVls/h7R0gppnD7aMBBndr6P8kn01p5GwbJGnhZYoESAChDNjLJXCQwT9rBnGAJFMPGTs7XCudSKVvPp2SymfibfOSkUguLxpHPM8db5r5jWQ0YlJwz1Txh9pXDxavJtS9Lvo+MpvY6iB9wadUpgDDBMNwyiC2bPMP9atIv4vquie9pxUIa27U5jAylBYRpC2drS1obUG8XTXkX0j6e0M/v7bngYlrIfBOPd2UgITMg1zV5NI1Zna4bA2jpZy0F/nNckirFXNiM1CSahCRjI2xBw/iS20I8qCBd3ZHMzkNcJADdipbJ5FyeiYRqanYrx2b+GoZFneTAYr0EJIt2c1sys7X2zh11YDvVbTiy1V0FpQW7asc+5gP7OMPaLDZTiuhG6CiCDMXkJILENElwzSSPxKcEdpwIhxZBgBCgn42CH9iJWbOcPJAeWWBn/Gw9FJXY9DpAAV4EbAegOBoL8CtjIrBOzsqEJXgd4EPjJg6EmbzSmHGkEIWCM7D0Z69eIlxoCtYwsAvJ5e8hAth0OWAKul5jrd3L5LzszAepTf+vTpb/k+BfD777/i5eUZtSzoakEQ40j42IjCuwPbRtN5DOfqcZg6BEVNz3gtM8zgIC45vf090/Ze/J4zdeSoOSIM+kRmRNfPVls2wxJ0Hsf2e1wcXT5ixgiEO/BHRnkwJ5K4nmUUY7iaaB/rlweDCgXKp49Q2urq9nPbG8/3S5B6DU8hDQCtd9RiPKl6QBAAtF876t+N/zn/z6/TPKyVT3SlB5uLve3efnUcdI2zeyK8uZfX5vFe/xwj8ryHkVb5K41a6vNcabrvo16A1L+s7Q1m/65+/6o2pI+/pvc8e8CFdfNybPSNAU+6wR2uCtVUXJxhbf85aNB1aeb695md29x3/aju3jRD2RXcfbXn6y+cda6bp0Qw8l0hs7vEfH8KBv5agPlueyTg7zpAKfAHcH3YH9Vw5D76/Fttxk/XluOtV70NU2FXCZk4ft86wsy/O6M5HLbz+WsM/1+Lxf46A7pzF7MJaD7wV+8HhnQwC3HfEKT27zsTcOMPCJBpsZ4JKF7zPEwCAgW7tMtQMN7j5DVqXj5/BQNYPn5A4YKGYVCz+43xO59P6M/PAIWviOKkFgHMAFYHCtogG58yWY1fEOP1tEJBWJgtqklyEU1YEDc26qiFNbfe+4QEnc1sMnnecgKvwqI4uQv0zjxaiWD1w4spb4unHixkqbOW49EEW7/v5khg/ojf/vErDssRh7qgnc9od2c8rJ/dGA/Aa4EpD0ygqtDWodUMT7VUtPMZRMB6OqH1BpCiNUBWAZUVpZrAdTqvYCluXKggKhA18zkvBQsquBafC7vRvlrdSADi9cDkuU+K77GnRLdQBZZ3d2hPDeU9oz0K6r0JCe2xQ/AMwjsInnMfNd9DWAHcEtCIcHPHWB87Tg6TSkOolkiVtgNms1kGvLnag81j2WRWxZMq3tcDzj0cANSN2+RM+VB4Au7lSgCrYH34isPHDzC5xTi8roo2CUUbwgzT6fitKHgHwDIs1Ps7yKOifChglFTMqbrwG8K2SwphKD7cF1PIPymAW3Qo5KudskjhXe4Y+miJkIiLcxMjZdQwIbgyMJhZzyrQ3dvPPNe8Pqwq+rMJsbHYIWATzDBBIpYBgSqQ0YOEWhY0nHyMbiinBSCrz5ynjzWjDXmqGUUELLUMg8dkbJrTZqqSpdmbuJr5ExX26BWMetmTxiTGC+ZUFMnJIvX4xiIa0EwEHW+m7M8EVQJU3HiHoRSErc9AygRSi+jXSCULT0cLSmWkqNXohlLCcEY8w0pNdBEUr/tnxNVdEVTybFkGg4ZOPk+FpSKspqQpLCBeoLXDFBuaVD2chszbkcJG7+uFjB4fiJTyDKXa0fe0FM3xhTE+jLaUqXrt0BjO9jHQNvV4KGPIQvrMIcaj5j1ZkRvFC4oSUMgNtQxFR1kWgE6IiODujlOFi5XIkOZ1FG0Nu9OP6G/TNP4XFMa9w30OG8eD7xg+CQP3RAbH7GIA+htPX7tuaxkp13trQNJDU0SnQmb/fFg5QHlOMjNKKIKJctaY6GSuRVyLmoSIdO8j2jhSM5dSTcHgcJBR6L7XY+6uyHMllU7nKlPJY0TOBI0Zu4PcE0CN11H4ObTxBO8QMBDKeig8dey0DcGzkWeIYLaU3OKZVgJv0TDOqQ8sr8d/aty9RfRNUcJhZMitMfwRCDg4rD3zDcR6jHnH9Y1ZNLlydQXqPLdpe/PigJcNOOr22TlqbPN4oDAfe0Q4Bq0kjtRvlGswOrAHcy2dXzbYDL5x3J7wKGE8dCW8R4Yjo4uQRpjdgdtciB4UXr+eom6z4Rk0d2py50V1PACqCXd7wTvfS5FhxVNDT05Yht+tdvmcxjhgW4NnCHwaODWdUcLpLKJHI65pbFmCQez73Mj70QEWuZ+bm/f7RdO2KeZc/uZaN29WZHlw+kKEQuY8YFF2nOn8udhaHZZiyvpOnkKWUUvNlNnSCb0Xy95UJZW3HuAMEUCYUSAQD3eNWvGlMEoN2kGGO32vVSMi0MZtdehXqKiPA1laRpOOKOI05nn3ARETCtygy05bSf3f5I6p3Wuvd7RuOKElitbNWbPXz+n8g38LGjsONzl9kv2+z7s5aZqST8WMA6Z5+c+DjLDTGx3nnBjKgohmDdw5zsiAzkxFCYDYzgBgpaXO5xM0ok1eV5T6gtv3itPrirWvWFsHSkFZDgDMIKiElPMsYkPS2bd5/fi+Gm8tfR1zoMCmxp/MdHoH9fY5ti1pIHztndrntkyZmW4K5MUkC/LfFafEZaRwr8EG82puUNTEifNaAcO5cDneGBy2qEnk4KZRSsBlkcKgylY2xPGz+ouMRo3yG+JObDONiswtNWov9oaQNeClw3xTnU4IIAwt8LJggg4Kv3UQsdc/tzIVgf+Stju8CSjP1Gxbiv1INJ80IgxMsRKRMnwy1gF5JsIR3LZkUNDNkUmAn1Y4I70pnzR4GvR5oEW9ClBhhE1nap1+RNDjnOC1kY3GE07WfX80HGy83Ae8bFcYgw38rKyZrZedgy5q2eJIgAbUxXgiCSAmAoRNFpGO1bNzdLFz3NMp0nHIRI5HliXNIQdPEzsYOJoLA0KWqbCQw4I7Y0+Ii8lodtDO2LZQMovDQ6Becwwweawp3GGPsjRWTDGzwkAykryLZPkUwFK/+yjsHYUgpF4v1rO9EYFqRQ2nI5rwDtQk0S5grmAYjTQ+yCPvHfILLLW7qoKFUWpFEeOjS13AXcHaQWJmxuIRcyGHF4KtMdv+dC/pwKQu25BHRwuaG9CXw+IZEdn5eht74ZpMhEIhZ4Cog+piOia4Ybuc0V8VfLixkh5ka1Img0HgVAs4MGcZ3Dp/1qdshKSgJTL8hCwRvCChexQ62mp0xZ085tOTPCaAdj7jcLjJFPFpnFDgfDrj9XTC/f09vnz9skEF93cffF/8Zm+R2SQM86UsOBwPaK2ZEZjgQeQG6+LOKeK13xUKUqfdpLi5uQWB8Pry4vrcZCtSh0JkjhWR4YM9Q1yML1k28lUcIkKeZ/bflDxLTtzjK9aTPzcn0lUV+PwZRe9RPkUWIaDIHTp9HSyOjyGjrCeeMzKHRCQ52QlCIUvPDgCVPuLw4R79QaF4vMh2E2dafW2DHDHuIL/3lE1iHebnrxnPB4wErpLEF8Hh9t8+4xkA4SMUivo3O6uCB7z+Oq/b+Hz8+9/BpWRWqeLOUvU//4YK07sZD+JBJr5KsymAALwTNYP4zBteoQ1hNP+gZkTPNZ/uCUP4t/QY8cvDlYt3atcVmplZ7qdXvVdzA4x9jWc0+55ntqeF+y9vjxGw6POZR5pF339dU+hu2G+t5c85ym9nS/7ei3cQuWP/9NDm3CK5o7CblHDwo3Hjt4YVsMX5nuCn7Nlbl81OrUHUMl4SyOnMsBipM7HVHfrEgxsKF+fxPCOq4/SWpZkCtwe1BWbX8ghSFCiWUrG25s/NvNQW0qb/zR8TT8zX31waCuN18IJ2bk9+7VYVRwVOV3QeWxUK5bXgHcPBDWqlkWI8XArWdUURgZRi+Np1q4kDkh6PLpW3chxg6pE5PiG+TwPbTF7nazRffPs7vfG77vqav3dgoyeS6dG9Q5ECb6ZhfyDDfVE3Pe77L/0FKz5vhrt/549cS50jAEqpDIiDMZyPMf1mn/P8+PcMbJzumO//K9tfZkBPgq229RlLMgkSAxgJuab+oDKBpvQmubiO/GZEmtGC9sU/kykw/EARgEcobmGA+AL1VDUK4B1UnxzJOdPlLyQ2A4YJQYru0efBYLWXFxcG7MLh/j0OCrw8PGZ6j/y3wVY+RlciBqCpmoFGyddMi2vojbEuXNLDV4Uyrbt2RW+KUskJC6AwY/zidQRDKR/pERsDbRUUEiy6oJSKwpzj4VJRuKDUgnY+AwDq8QBVoC4H3L57h3ZquCfC8/Mznh4fcHNzg5dDgXbB6+kFh+XGx1hQKrvSoIOg6GegFI++ghEV6R1muCO00wrFyb36bRWbK17PcsZSKoitFnpXQamMWo62uO7pKiJYzw3ruqK1Zoqkboo4uiHo1xFHI3pC0WPS1+V9QRPFcl83+NR0Os+o9B4rvYzfXCGwwBDyQndACAcToQgzD7lATjoECrP3xXynGtVdIEQexQC8U8Xn//kHbj7e4dzDk3eckT1OD4bK0N47T1FmEy0fP6D/PpBqzEfnEei4BgKKvkO5d6H7Yyi5w2BKIK9r8b9eGAAAIABJREFUCSJL/9v9VBJZZgQo+sNAnYoXwKPXIz0jFcbygQBicLV6koqhMzHmQjx9N2faPhXB2taxr6LoLy6ER7RHnsEteeivFgNc71wB4lSWXDFQbgj9dXeGp7VORdkGoSEVETHbNKInZMDT77lJY6IbqSIjZAQenEliYnRtqfAjZyrJXmh7zCNNlooAK8BsCoCws0Qa61CqZvrRiDrYjBQjEssF/0oWbSVqz2edXJ8je7rMiNbJ532ZmNRwPmBnd1Y6qYtuHhUfkVRNAWkdzWtLL0vFoS6gQ0WZzBmhnSSQGcxLGPGdmC+2twRXdHrHgjDcD+ZMAY9WZxSu0BrOTrigSfB97j2UyxGFWTKyoywFtVSoGxYyLT3caAQFq3ptQ48WLRaNwKio1HG8NYV9W1e03k3RB0B7N8pLAFDAVbEA6FjR1JViHrSZNW+TXkZUMrZzCqXPhGC2JwoO1zpLVTvoGZD9VtsaG512Onz03kACqLu1zecpvZNoy/3Pde1B5AZzBVTQ1FQ4mR6zA/CUvYAJXcUjgi0yRzMFv9G2SElstKnWguPxAN9yLLXkfCzLg6SQYKmRLSJtOMdhg0OM1qtFekf6dviZ5RAOJdddu6JE4g8aApjpQiLyGYj0YKZQi5TNicAAjKiZEZUXxrLBBI9t9n0Qg60VDXISN3qOPZ09jckjcQeZcWhygxhx8SF56m+aAA8wRaOGEn/8RBgK+njeZrSHufF8HPU03nCMRdJojexC830Z5aahiNfEo/Y+zVrRvuq+HnsA9/dOvi1DsWn8kaGy2ejc3UFic9wmBhtGjw0LgzxXj2DU4axcPHMCe4YEmENHNzwr6Na3FIc7Qikl04+LRytL1A/2e6zmttEyqxZh8N5a9/H3ATNxfmFKgY4OhjnN1RpOkQwvsIHeO9ZumY/WZs6npVbnH+fYaGx5l2n/rhuOtvzAuDY4hv33cAYjAgoDrasbbmz/uRbUYunYS6m+dmRZQrhYPbdacDweQV52Jt7NbqRTATqL8yM3qEv1aEdJpSS6uqJn0O0o33Q4HFA9E1Vra/JrTGqODu78UmrFYTngrIJzX7GuJ2i+F0mXw9kDEg6hnq64FpTDkin5EJH2EWFf3OFPhkylouituXzidXIdngLWw3lDgz8OeQaU98X48txv9smNVbta3OF4MSIuZrpREIc+IoHh+DaV/QgDUhxoNwyImgFGWhpxiNzAEWdXTCFPIJi9x3g1iL3z9fUV5/WMx+cDuhpMNY94LsfqTnIlnf9UFdQbRAwGFOEM0ZLXDBBWT7eqbnAfhqOZz+T8nivCNemiIhwD7d/gQQGcPUuTp9QJnGRzZhBZSSHLjWMpYWspIK5e2uBgYNJXzI7rhAquhrMMFzktghvA+oApje0TMT6IuzmHgbxs1+DLUvZ3Q/uI7I6IfSDqewdvY/oJHvg8+Ek4TLM/OK2YgtBag3q2IHXY7SquZ0Bmk+sYdCeMN6bXiCjO+d2U7482nwJSeES00aJ0dst3T2BPsChcbPkwijWKz2mbdtif6Fum1JzOWmRk25DgCe/nWQt6vntBRj/PLYT1kGN2fcYPKlO0vrpzgfN46k4BxAqhUSrJDJIFdSmQRmb06TPVANRLIq3pCCSQPjkt9j6yasV8gwI7qlGXdZkKqEylnXhkcKmqaEIopEAbju/mLMRTFqUhGwY/GBm9lMVSwzpAmDOlpbQ3nzkrEwEOpx9G047eTMFvhiJCOVSvKS9Q6Z5yHhbkUEw+UWKHtYa2NhSygIdwMBWHQSJYeTGYLCnNHXWZwbSgFndumRwKSfqQTFbCUoHeBMwddQEEK6h3EAMF5ihGyWOqy5OcDgGpo6SS+CI2x9EjpBs/KBAUFOeHzTAtrwoqK8DFysxYL2jdMq6EMbe/vIAPR8tYpkiHjaynDs0sFQN2BSjshsWhbE7eMs5LwBITFAXaOoQIy3KYWBbF6+vQV5H3+Xp+ARS4vX1n4/V3nk4ngICHh4cNn0QAHh/NdPj+7gMeHr9mhPTdhw++zkF9CefWzCgduRLSwsee1Y8ALVDnb3PtHcXQhKMiKMoyEEXGsPGvVMLheIS0Zpl0gOTFjFfnNLCrDDks4GkpDNQBK5GpoPdRriOegyrog5/pbrMVFcubMDHjs9wQa5jYe0OXCaCh44IC8uUrelp6aFP+YuNbNG1q4kACSO9Q8LhJ3f4tw/mcvl0BrL9/BsGcBEQE7ffPpsoDwGo1yvtvH1H/7jLQDgF7fgbb0qlsYnBP8dDg7wYNCJqVMA6PQJ9pxtT2OoNokYNk5uBnzcY7gYfNXbbrV6092EAT18a1u9wja5nFaHrfNRr14z2/3Vx63/T1r2qhG9vwDt9o+/25toezoTjvi/froKMmWgTS0ziuCf/GJ7m4ZGKKnXWo4XfmzLRydW676+M4q9NXu6Fw0I/QHfpc/eUpxzuuz4y0ipHhjQauKw6c4p2mQ+XEEEUmjqAz0UmTlrzJdPfme3Q49At+ZPdsGV2HSnvX/IvvAc1Uxea4NZ5fYQinxuDNfKGON9T5PscRTQTV95EVyTMLwtkm1hab7zKNOnnTuOeN79h/nyPttss5pv7md/2pvq/EEe9X8uLzW/fF3//Q7bVvPQts+97o18zF0e4gpJw4fncd5SxLU/D+rpjkyPaE5GM2i+Z87LR0f0n79xvQE9iwObpJ0KFj4eK+6ZlgFGLVwkt43MBb4PTNmhHrKwHvk2HyKERV3ILwjIFsX8ii0hl3ea3gDoB5EEoqNYHbj/d4/fIVKykO/m4L+gmkbgf04eEpygZepO/ZpJ3za60LWvMaWI4gCGpRax7hpuG2CVMmikfXiodYqQKrdBzEmPs8+WlMG1En5mWLFNQRCMiJU+Hq9cEBaCiDTB3TpYOXBQChn8843t/j03/+B06nM3pveHk2A3mtBUKM3s7o/QxphF4VLIsZdTztWWFLK1hKwevqVbulo5SR1rGpoGs34QwOK8Q4vZ7Qlw4u3Q0r6qkTiwsXjPP5DBB5bS6vAQxXsB2G0j0ZWRXQe0qGzaKGDKZKqU7InWkkQsezC0yUTP4KM6AveoflY8Xpa0PHSyLfGXTTyBSYk2aEnzgEwUKoAjcwwqJ6AwBYH0atytMOQY7TN77fEIHwAhFzPFAF5MEMP6KKmw8f8frlc9btMo9vGxf5d74zL10JgxpFtM50TnlyZFGYIcAHMdc7DcHGWAIB8ArFjY34EVhBuPl08Ihu3ZwdFU/tTgxpCmYzQPW2Gp5R5BlKNmyD60MFuvqvCyImoXmqyxpR6D5PObnTA8wovTCDUDHq6VGm7JxT9BXLAerMv0dsJ9dneHGbBcjxmSPHgAX2v9It0kUOFiWu0gFiM0ITQVZTUC7LYrgMDaRAP9sMFxTzunNmijg+8QQ8hsQMlUQkACaGySRhVTMoEyijbSOVJbGdjVAyrtIRBvqRAd5SYcKV+uQM2KEyTuucWQNgJT+rCu3dk/yZMMxEaCjgukKUwVrcuWLAAAVcetQdH8iV/ARM8LxtboAKBZ46sxfMou9zKCOhOlLyBy3zfQdjU1fUUs4XoHqtWHVFvTMc8W5Rcfd1nsZo7+OiWBbHLGwRMIhoPWUQFVBxGJMOYQIoijGsfg4UqfIgh1MaezGdbOv/LU444TmYo/h+jV3bEHLbjxQqdveTK6a6qQIyujCFbhpGlPj/7h2DZSBE1kogHJmQDhzBsMcsFJTvIsCNWsXONE28RzB9HNG3pnQnsgwLsxLesswIepNUTkoaiAwG7Jj5e65GYk34NzVoZgRY20j5LkRQZVdQEUKpo8rTDoTDwJinvy6jL9LQ4OOIGNTNdvoZULgCGQqRluvEqex1Jn5mvuP58cF3YdTn5lRwb5UoY+QBC1sek3zf97BgtpdJqNWgQ37WJejxtr/ccx4vYmIIyYTXYl5m/NBIr+u4jzj4Rsp5D5l6KGID76rzfOLS9absh+oONvw7uaCtoai0f6RGW5jI/7JFSHNk/VA3aG7fa7ykw391XgsdXWjTLxE8VXtEjCMjmNe1ZU3tsZ4YdaNLZHPyLCKwiCZLOW58a3fDYBdPhez9WTmCsQaq2Bjw/Cr2q3W9BSYZNNqha4K18T33LjoL3ptszaIGeWHybCnVjOjFy4J4tHj1OtujPIm4gsDeE79HlLEZSIFSJvgJhXIY66vzJNKwrq6M6M34CSZLP+zR/FxMVoDCS+BEFC3l3tr0JOFPIZ6q12rdllozrTgRg5XBSzhcuBIabjxx50diArRDXYkvPZSTkg5e6VgTe0sD3oxnR9KvgNhtkKpOSrABB/Fv3kdrLuiruGMfkMgqFPdak6YHZIiqGdtYBvz4uETNeWQoVRTkxphSCpoaDyoiaM14HAk8AYBoQRgDLDOXD1rJnE6IIH2LEY2GRW1ZM6aRODpw/Jdu3GopYy2DQUm7XODVxKe2oLkWs2xebgrkVVysCYDBdC6WjC7hpXrtQ0uLbOmyHR9qBaGjLscp2htJJyt7eTKP6IkhqABajQftavIswbMEYMgrhuKdH8Pgy0spbgA1+r22PvjCYLWUob0DLB75bk5DrIB6yny3HKSOQKSjt9Wj3QXhFKI6DE6Aeh11SgXhvP6mnJr4nORPHL9nC3yFpIemcJXpe7qQbP/RJccW9CvoA9R4oTB4RZuzccX1xJnzfcD2sDkuMTuLJn2cQe0tI0me94S37QCCBgYtt75dDlVzTmKvBy6iaKQg6eBS0DxDgfZw+JLkC1SNjnWvAZx74TXFzWlBMmU5usWbBi4IumdnWD2rHlIOykQy7FbH2G4m97dx/OY4IDlz8kPi/ZuzQEmHPNAUpejdC8FgVcyxV+H0VJuBhEdPW53xZllIyPiSyODURbCKoErD2lcHJaN3tZgTVSmLwT4R6OBp8FvL86LqRQMp3LA1jROnLujNeSKxtVYicGXbPzUHcaXI/jbcWnxhzVk7YEHMQVmj1AIs+wA5X7gcDlDt5jyhwLmt4N7BbFnl9BUAr9bPdD7C6Ssc9sPwi1cFvVMs1bJsdJeHQ88UgTsBu3HmuEylCJKPQdbUDbIkag7GNr2Aq7HPykEbZx7I/v/88oyb21s8v7yAxN08djz29i/h8fGrra6P+fHrI97f3aM1o2c3N7eIbC+s6qn11WRZGE72UHCEwYkwgiT684vhxuRjA24p+StxXjVkY2aGFAb1gVOTrqe+Crkv4fAKTApzpqgaOWXm8fMENwLr4DsicrrpVygog2SC7EWMXvMNjKT3mREEE+9BrmcDsJI5u8aKz8bYOYIy8LxFuN85rqXNb/H3nebQrhrTZ14oGgHov4vrAsec4rfgpap+dF7iIbmP5IBMGWPr1btlifytg//m/B8N+hW0ufs6214NY/qPttirGOc8nzu13/qF7PTjbTaeb69biyj3SOUePb3zG7Y10fer/uPNua/MZsDfvv3f1t6ajb7x+VvXgLH35PQtbCwmBkzrR34+eDuGyPTHML3IhleY2Lu3tiL2O8pvdZW0AQAwGRVIXVQ4pEekfC1sZVdCN+MdSY8uXcr0YCGJAK48F4YHmSNSPd5L6KI4Hg44nc/uzDoTk1hRu0bMw/F3Xu8rOrPkDRD8KSUNGjycIYabxDmU/79Y4PkKIfXl9qDpX8qUIUhFcaiWBcZsQ0jnfwt0gVV1wSVczexw0Mi5XThKfOv7fvgTvMzLlnR8d7PSFqqVLEocsAjxO8TZVdzrGH9k0wgaEnjkK10F0c04CIZ7bvAR5W8F7behc/mo1yPYZ4jZrOkcNOO67Jy36z73PPoMdUNfuGFykgdJaEnZYw+7//7219ZA97/7PbpkxK7cF1zUt/LwfaPPa32F8fw9KKuYj017lzcT3UMRnpq27V06bn75gPPDV6/OdunlFZ9DHD/CUlqMmW0BByCczgbQE3+MYG5n6h/BCQpTJmprkDaUAKqK8+nk6dYrwuBJmJUerixlgvaOejyOkz4bkDyFl0U8dJzbClLzwlyOxuqVUtDXM2pdLN1ZsajzUqyO41IBXY7JuHOm/o3uTHlfAFcMm/BJZAqN9dzQ1QTTroJ+EjcWMVAsRZ950neQsqVK1bLBZGVZoH0dqZkRhDa2QTceoLan5J5h4eVKKdDm7gSFvUAU49gvHxacv6xo/IxzMElvunVtL86Ia0fi8QrCexDE4bPpOxBuIZ5UaSsSId+SVx3bn7801A+GkvkDg/Qe+LLi9eELDh8+4vzwBQWEencHfXycQPGdr8UQRHKTXbigHIZ9YGZIN4G/q6I/CuqHgi3xvtkwmEaPBTcfF68nPO4VGLxH/T3ywyKCVMrHFo8TN5RJ82fFimEOXGExuor+IijvLJKohKRChHpbgBeADoR+6okf2Otgx5yiznBGNzjDp2BPtxtxCEl7HBSumxpHG6yx20KSYAeY2drF+3VEkwCJUwOER2rLAOfhlAMCSNyQGje4ApojRavjlDkNzSZ2WSbwyNfH6MYuaDDEnhqGQVg9/ejGHY8UU3y7bYvCLZKuBhYFuhuci7N8oX2dXI/5YPjOjPuURodhQJ1HaN9mA1c6jUTEt6pFK/g+2nzs3ZHa2dIQc3rCRw3cwH2BRyygZBivRXy/igJikYPQiGYTdI2aio7HNbxdoyYref1YTXowGxkyi8sMjNP4Kd67a3r127+K4fnZ985S0HY/DVe517DDnYLG/k40wPbBHNtM4WnGsGT8p2dGyRTvTScG0ZXlkb7VjFPdowT7EEpovIt5v+zXeAny/dzO2/UVCKFPlQFP25lG7oiY0RnO453DcD5OKyV+mZf5WiSxLbNutqKTO9AgDOLbe8VTIwtCx3bJcF/scXQxIf2ZbsYeBWgPLK25b2N+Rqf3ApG9YJpLrMXY3TfGFp0Oip6pa/vVI5Vjn6i2e6XrtCe+rzFxnbmP7d5sVtCdfzzvwHAAjJ7VHFHCOB/rw/CU44XT0BvOLukM5f8iLbiqQtgUp3kiAl/1npHWBu/GAFu68ZkZ3mEYCqWDpoHClvYN3ECXP/0cFtHdp+3TW0eiMKQHTYHRF6bMYlE8wpppnO1Ms+vZl5hqOhPkJDAioAA4TwSIcCptrhuXBiyLdJzOK9bWwHzyn2385/NqGUyaZzGBmmOZO9nEMeN5SPl+QiGL0Kx1QV0WHJYKLjYPqGUHYI4xW+rqMJyHI0/sY29tMnQb5M6VL1RhCnrf2Hhv7kLwKDR/xw436SayIE8NbRVgTiWSLw1eIc+7n29iggrnQhktFpQOz/kAhDMUnC80viiQk581Jtzc3tgkuXoWHDFc6MarOVJ/RouB57tHPTaPjhWNLCABUwqXvDJCHBH5GISA8o0IGZLimvfJ4FyneRQTA4HhdDLjSAIvxjNHanTLgsG5DqIK6oqyEIDFU0tjrN/EQUaJH/PXIIAYVNXlZfVMbWpGzXAQpRxUQHHSjYhgF8+EBleYzi0No44BhAUsDI8/zLqwcIN88v8TTVWdV2jqO7S+ESHt/LJ6hqoNjd58Tm+uaYJbjBXnzGjlNYz2A81h0bIoUX5PPmi+bzfKN8l4/qjgWiCtpYP/RiGneonnJgPYxfX9uAezFmxT/hhuKnEkFIBAQFKsBB3F8wyQO/lkRrNhlBtG0HEWJGDAWxqvJx5us08Kd6wh5/0H3iLvY4ilPHgeDuc8O9+GBwlRy9iGxAPmKNYi8Jr1q+L4GQSudXIIVoPtLp6BwVdOAUhHk47WGs5rA5eGpVbUGo5ilrWr1mqlFYgsU5gK2moZnFob2VdExEtaMVb1zIGtm/G+d0tXC89q0z3lemu2Rg4TIVsBs1MVkofC2DUv+RNG0cD/it4kcY/NVdCeBaBm/ShAKCBtw7itfdCvMGYQIDiD5AjlaRywIAUrZWRAOeSQwA1xdsOI6P8m/aiEYTJAPaAleCQMnUO0cKM2RyrFy8uLPbfjm/Y44hrOmLFNYnqXHbu6kyMxlMcZzvJAKRXMJ3KENozMetM501Bn+F477e1el2pj2Jz1R4GH47csPefrmP1v79vPuXz8iHDAAQHy+0i7HA8MindlDfX6dUzX41+IEPNY9u9OsqYA/cLQLwN2rjWCRZzPRvQXGlHo8f76qfj9tImSnNMen379DQxg+Y/q/M8n4/9//91fJui/dvDfBi9HTCh/3yi+MbMgc6kv4I/VMn+Ltim21PJf1e7UjOj7/fp2+7kRvZtuH5zXv3Zef1b7I2NM0upvGCqEQVEHbzg62nNLP9sucaAdhiCfQWuJgC7suiLHK1MGu5LlK6axT4hgv3d7HLGRdfx7RMGv3ZQKmcnhytiN5BvPHdmGv7cP29/pytWx9vLN+7ZtXwYu5A0QjfT0bLSDmFFR0cQlqrdk/v3A/8hm/5PtosuriH7bru373O51C9s/U/u8fLLSsR1f/uCSDHni8u/0mYI+EC57mfj4+duG16DL3//C9pca0AFcAM7+QG+EBuAHDkX8/raPlQIm4DmmnRmpd3DjuVNq4z+/mgctA0XvkkUL5RYAnB8Viq+oO+S1b+HFfwBNnoP7FtFAmgK6Gf7IlQiDeWBlnwNc+a6IGnfstR3iHdI7np+ecOcCS8/aVIMjD4Rbb47+3V5siN9T0ooZsbsLTVY/D4AKHp+ecXd3h9t37/D09IwFjN5W1FKgzFiW6jWjzjjcHMywfm7g4gqSbpG2y/EAqGI9W5qlwubB32ACkqqlLO/Na/eRQjuB3EBabmBMclcX9AwZSzfkWpeC0/lsAoikqhkAg4+ANPfw3sFNerPqYEtFFL2fLMU23kG99rnt91b0NcaMzBMbTzibNc31ckMZNekG03gZKeau6Qdc/oJvFz7813/h//vHf+NOFaAXH8VbpFCxuFQv/kLBE/BgPk/lYyjVDWZfH75gwTvwnQkWh/t7tAerKcb34Rk/rama91t7VDfIMkg7yn1JoU9U0b82NH0BEdC+3qDch7JSIY+uJAKgePU664y6LKB6RVEIi6BCV4/QmdZqvlNtL2YDR4hl1jyJZNJ6yyGgpGiiYBWIUCohjjdHqL5ulLsAXOEQilhTXk6JI+x3qibkiQnc1laoRqQBocY5fQMPUkFwTH6sJzyYwyFbNxB662NubM4h4QmXkbth/dBIi+RSUmqSFJFWPWugwmoExtKJqAdrCUQJh6Wi9XG6Whc36FpXQoHfprPg6wgAh8MBrXeoR/6kElLGXOzM2wtCAYBuaQUtmrdBpbiAHPXNkWnZ7KyRe9KFQS+MojYgjnXNv244Uk5Fk7CthXpJBvNu7dYv2NaSkc4Kls7WDVHF0toG/sqt9L7I8T155IApUdWjL9xLFZEmt5g3NZHXHVZoEbAWUHelgjPyQpNng+OcNJKbJcOUE4Cn3BsHMAWYH5F+Yl9TszSt5080O1e7B6/VcYfPA9jhQ5qALOCeoBQZW9zjlZD1IOeUoZE2K/obRsSxZ2E8T6eJEGLE0rEaaIvTE80o3IiiHTBgRIEiFfO0ZDv0hjCGB/4Xif63D4TyReEG0slFNnDZhYDvjgP7muXBRAwjvNdXn1Lw5XtzGIGvKCOfQ9GczlEa7/KohcixNm3bwF0BpsMZaPDwDi0b2Ngz9PMCzZ91c/73ax6K1xGNGOfQlW0eWWuG6MFGxFGzSHS4gnZIDnt0T8CkGNj1f3lxM9L5/4PRjj0cJi0/+bky8dn09Y5ow1CihEIFlYvhLirpFBnrF6Vn4krgDU3DHZIfsKgdTTw38DGjFNsHuzandUTW7g3HoYRBf7kC2MP+ZlHj+lv3XLTdjbT9ZQNR8y1BT+AON7ValFwt5jRVwnkKmao3BsYcEesm9LYWaURbpr23LqymuZVRoYl+XJ7BiJISbSDE2o200eLG+dZbpnqGp0ovBVsDjPcxOxkBnFGGQdeWWjJtL7uhlAjonYFMKoqM9FIA68m8fkQaVLcYP7JwpOORyye1Fk9HPvM1Q2EVho9ZFZ64g+K3gM+A3zgtM+1yR0Gyz4Z7vIar49BUwzsgRgQVCFbLnqzurOGCyUnCeaDIVgAAVIqfJ04mqbcBOwZwESFve9R6R2+Ctp5NjoKac2IgoKm+ca66KsBuEPM1MnZO0+ifeH8DXzJ9DsK4xaXR6rFgfWmZ+eJQD15H2YzT5uipnmvEdoGXiCAdPOZMW7sO/tPmH6Spg4rR9da7pdmEGdEpUs941rLYWnF6G8YmRU8lo3RxOdt5BBEz5jgeGXRIR5CwRG12ypWKNZudk0YjENidYhUUsjux8dQysHrAp52++VwGsbkCu1OLWzXWDXv6E/T42pPk7NLI2mRrvmXEYmw/Ewk383hmRO8X94QOJEi0Tv4Q8ZbQaWAa1zyXwJWBcoNew+WMSBsMBMw53xzGTAKUimUfQNQlR6aJVefLouyFOT0kB+XjCRP6OD+ZwWjCCcHDhnQ8j216HQjOj9a6fd77oRpw6rDsNJdKQZYB9DrikUEMzcoKJS5kk1pFItKuoLXICKVZ8mVdV9Ra0dcVC7O9ky0TFnvZiVpqOohCgFIErTVwETeiR5kkx+urGdfbuqK3hk4WSdgB9G6BHmFI7yKWRUWNLuUhJct0Fis48yIEk4MNr3hZDVX006s9H+wQLCuE4DQc4QPva/CHnvJeZ4rjmIwAOZ3Qq+GnqBVuJX6cVnjpLuyeD55XYLheXuba5mcIgJv7OwDAy+k1UT4cT55eTzjc3OD15QXjtFUwGvrUE8V+6haH4+Kbrwltr7+eTl6axmh+WWoGykRbz2cogOpZjEQ81MhLwrQsk+L4AIR393d4+vqQeC1k4q7A4hkq43zkOTGiamNnW1+dZDMAEx9m8hbIa3EHDsHW6cCg6s5/N/3s6+cviVMDH81r0qdnFcMYHPdEne7Al81/c+kUZ1W8khm3Vb0OOAFH56Grjn4Ddma5IH4Lg0Dz3xhmgH2e0bduP4Zuiz8B9Ju9K8b/jgDWz97fBxQ2fZqsZzAVrPl92XITAAAgAElEQVQuAn0KB8PhwJP40B2RBu66h+LLhvt+r9bvLC9+r+2nFeuvAI5/+4TTb7+DYMYpwR8z0l9rEXl+rxjRpBiOWTO9GqP7Yy3mNBw/frz98V7/2pbO5RPcJy1MXQY5LrbVn/klpQgcMLhj+vbGB6gF19VdNqlEmbVLlcy4O70rIsRjOBmx7vzT6kxr9QyFXXrqWxTmDAsMWK9eMz2CC5Q8U2qtabwvWZZk7nrwIkw0ykrtnK+NJ0dmZQoZK2a0jWe9tDmoLxYBOAI401g7XwIbQ9SKn/Pe+14WHo61zK6fdrZ2qQdoW6FqpXGaZ+7Cte2bEape0ql/a3uj4+FIub31qzOnd9NzX2nUNP+ReWRWEwDn338D4xfPmr3Fg28N95J6IP8qhfxDSWPtPNGeIc/3fR+1/knI909sf6kBPRUNAH4adL+1uz/xin179qvvMKVzx3brtn6Q27aPOp/7+t727/saBJ0QKpz0wJmEp2DMRdwj3ev1lsJZm0dh6Zy4MM6vr6h37y19SHhITQJ/qiQoZrsdZKQOtii5BpWKqIEK8jrlUHz69BHPLy9YasULAYdlQa8VNzc3OJ8J0rzO3oFz3gp4VLd7YDFjPa2oi3sit4Z2apbRyfLcoomlDiKXiQgKeQWoFtQKEHerayQEYXvu/uYGt+9vcHp9xbJU9N5Qa0E/dEgTG8MknxOA+u79Dk84sZSG/ujpaPGcBHpEiFE+cgvgcH+H9etspB3Q4XLcgIbJUH8NiPYe94f4rsD/+5//Dx7/8TWN4lc17lNb8A6Hjwtev3zxUQkUL6D+3pV2hGBty70RuBhd/VCM8VWfMUVmA+tTHjuWjweIKs5fVzAsrSGI0L+sbhR52TCSub5PAsUrCLc+0hursvFhDr/ULWMvA0HYkATtGaBbX+dXO1X0jlLANTXEiu83M6LLSSBVXOkWnoYWIXR+PaHHzgeToPNwdaye7/EQqK+QzDDERKrS/bmMpbbkC4ArO9+402Ep1mgIKVHaYRYic21oipRQzbRzm5SoOxAjHYau8OAHD4VAeEZi8x5KQVYgbmwKuA4ByspYdPT8bUReXse15vQj4C7g3ryur0VAWv/OXIeCcfobjGVEiMe65H4mygyDkinPhTgVzwJzVhBxRZOnTpzPNpFFI1oKX06FOWPuKBY6WX7D/8HEB4PiH6JOItP0FiIIRU4N8vXZGjovo8fyYWeGkLjmf03bCQZzROHb7Q3uWv115GaTSMWVPOG01xLOQcN4XkpJA7rBKF/0ZYbVDpHqfyUNYWFAj5IsRFZD2a34AIVhbUghRPDyKoEnMFDjjB9zXezZOYY8ai/muhF5FGI4pVA6pGhohqdpjUhFyr7CuSMiyPPMusE4xiYwZYy4ECeeUtcUlsO4kJkkrrT9nifuTQS8R1L7M/WNRnQBY0mqQ1KjMT+7sutz6ibSwSsGzYrMKUPZPuYRO0VvHs3AWdO17TCdnAw+8nvznTNuIHbDYd9S0BVAMWp4e730VPiHA6C/a6YVF0quBIZQ0G4dBi261tKbMkc9a/s318Qeda+vGaO+M2V8f1n+2eeCnlgd+JoGcZ4zj3BxRQoDpYBh2aWWZUEpFUSM7iUrejfeuPetAX3+N/c9txH1CnRpXjqiefYLTWWLxhr7M+bsBYgWgIdDgx22CAcmEJXcf0XUXa8odfG5l5FiFQRFQxFyZx9FXQAuxqNLY4jAy/zYvJlps8dxbrpYxB9NafuDH4p7CO6MTDEnJB92dS/zLE58U77b3+dRHsHjKWSC4cDXUStVECm8u1jq/VKXTA3eWwPcyDAcJ2oaihmzshlQ7eAwM6tmunuAMhVyay0dIcyoqxktPOAlZqQesUeeXn+CYTUZsPCkRgj+6woandceRKADAacx9upp3emm5PM8SwJuEONGoGMY7t10qNGDjyF4KzGaYojI4ilVFEU9KpwYkRigCKOTwVPIJjMUxCeLGrJzKvC095EGm9wJec4sBXdCwWRs3MNQ8G5X8FW+A250ZautTqJWVqZbXHTWzLxCx5JsOU6OTgMfUwoqb75i4Ilc77dbOKN+q40jMd2YC3H94QmLZZrTLlF6YDtoE3k1leF2LdLlf2dwCOeJLe5E8EbqaZndgQhkdb0BWLkslykigfag55p0b2fq3uw7TXCxXWt1JeQs17lTR+7P4AUNR3MqpSN7S+x7kuLsw0oaBu8ftD/gJzKcqDtwqLqxXEPWHRlVzLnALODqniO9ewT6+QwCUJcFR8JwQGAkHrKIdAZXRvfAh9YahCXnagp9hqxmJF8dvwkZLpToszd0N57nubNlzHUP43bui07r7zxdpL5VX5vbd3dYz2bcPb9YuSubaoXg7DK5mKFTxQwmzgMHDoe9fuAbMicwAO7oM8HDJHtdQqz/E0F/EShOmF3MIosbiHB7Yxn9Sq05/8PxBg9fPnt/o0m8PN6jA0fNUqlOf+dHJlFgeqem7gA+5rkdbqwEYTuvSU8m7mIrz5C97+vjIw5+j+wIkfGLBvPS+8aAlPKKzw0JI2E8N3mrssvL+7WfDtE44+pZHv61jbzf12l94/PsWAqKtO7mQCEPLq/qI8qHD8DDQ+7l3nXnWpv3ev3yBYdfPl6FSatDHNHoD3j67wfc/td/ov0m6Ph9zAGDX52b9C1cCOzMR6TkdwnRd9ojjcjN/Zuef/s9w1guJfd/rs+5zVTrCtn9U5u+8fl/Zbsma3/vEUxrOWX8BE2yseP+a2++BoM/2//odbynEKPUgnNbcwxb+m/3SjpKuX7J7xv0/fLZkMW2a7CzUQUOIBoZxK5A2gjwiLloPh5vn1YRNJUr/VbbOzvnWm14ntE2DgsTnq/sDubu1NezNJb6/OCp8+GBcX9cnv/f0uZI8v0aPtL2Wtz7I/Od71kBHKZrOv373rP/N7e/PAI9zgl5nbWNgu2iDcZ2j34u3psH/xJJ3KSwrenJt29hSH8hxb0SCu5zDBsgSyblGSCaROTrB1dh3oMHfI9Q+tHXjUiIUF4mAptvhwk+lpqVU3gS6eaN6UKcKccU7EpOQ1ZT6udUuTgiC2UYuRK7dxRPsyhdMgIJQEYehTf+UheIKpa64HBY0A8H9PMZkIY1a7wplqPVtW4iOBwPeHl6BJfiyiibX5OOfra654flgOenJ6gyuALt9Wxek9Wi5Fkb4OkNh0CmkGLC/ePjVwBWs6uLTAZiW4HeekaLxVoQh+cpLOUhCOfzCevjE3qKyvE/wsnXMviAI4Dl/T3ODw8AAefcxQFHRlQoU8LrxJyHfCWKKTXe2H+F4gRCgeLrP74CRFA8Z1oll903UJmwqkDHE86f78B4j/qhYH0wJlW/PnpXigXvk1gqFBTKM1fkpqKgW7q79rXBojcZpy9fskOB4vy4hfa5BXG1FGWnaaS3BiesqKIoteT65LmUoUyGWDSB7dcKeRnCM3CCyK0rCRiEvhlHzHkzLpq9jW1BwzOdmMd+udFJPeVbRC4nVqKCKS7e59f8hC+5IHm+ad7stJ9d8EHaASpAPR43uDSVRn6/RD25sxnG5xIEZlcXyGS2TYzrzF3Mce/tG4Jp7x3sdcwghEOJ2sTYjCP2rrB7avqcDh4pcTqvAMQiowipgHp5Obl92JnMHc3YO5ZEOkNzNCJXvDf0vub+RHT4eGg4RRjeHcaNNCz5GAJJ2b6YI5N4igHqBOEOBXsNMoUSu3LYo9B9qMzh/FQtK4fXvp1pxaz0CoNRW00hbpk+HF+peWsSPG1aARZazGtUBKUo1rOlOIw0dVZ/Nmo5AoBOsKPbASCnvV37WBJc/vbmQxjKvB+TImfMvP2kuxddi5TYjgUbWImzPP06KZkB0KjVXYgQdS5BjgNEhiHC8XTqrX0o4bkr4bSC1RWU3Q2AmrQx6uGqmkOJKUQ14c8cX8r4PHNHcS775KATG0RO6wdb5TidcgPJ30fAiO72/xHgBm2PYuIyJqlAKE3BgHZNT2H1bBTppRppTl15GbWcOwuqRyxvcNwMK7u2USJrlC244kR01aC4x/45lek+SrydjgHADv/42kbEtdoKiqepDBo5MwxDsW5nWnP8l4Z0xGedxwWMdJ6Uxsrt79PsZPAmY+3263F1hQ322FKodS6AEojNcQQ84MrIiEUxxz5YGlFz0oHDdkQ3hxLVjFPm/BhneD+HSfc8RapPRvQ0pE9n/7s4ZSxvPrBLy/9jz337d8uyAJA7GlhktjlMZeYRtprz9nvNdNzF742ap62FUWLFuprROyIoeaLpcSbSsdHnlzCshsekGz1Y1zUN6F1HtJWdReeDoYDXdO49MsFQslfBdwPkeG3iX9ho3LIc0zAc69FaR1s6am94/voEIkK9PaL1FefTi/PTmmn+yflLcs2TmWsM/tIBYHIGmxXL4+zatdanLBkUWTBmCSxWbv7mz64n494OBxC8Bi6FjFXsGaflorDsP1HHHcGzbMlrRHha1V+kTGfzVXeCG06zvTfDAy4Hio60sb11rOvZsh9BM9tM8jjuYMcuOyoJlNQcVWDGaJq8ii/hXfNf1k1XdS5Sk78I+J/xl+EiRr01hwCdxmTwZEq6hQro6HOe+hXtSTtEBdoig0GFoINBKLSAFoJ2BRbP3lYAEs+YRR2FYY7o7DTD+7Yz0sG1jnJfBEhvnpHMS0wQQdlLWvDIwBF7KonjHAAx0WWDDH/PcNIEYJ5zDrCs7OnhC0g7umeViSwQM/uUymLf6A2lS4PaxUYmjTcnDCT7l3QotLxz+SQg9yDGUKpFTl1kqCDjCRxTvAlRmzHpPLNo9tJhEFN3lvevXqYmfg8jWhzpQbc5BITNu2dHQxWBsqWbZiWolzlIZ6253N3EF4gSpK0Gkw5HSfMxPeJrOs8wnIvMAM6ukzCmKuSr2XFsHv5w3gS4mAI/nd8cTpS2Rj57VzjMbdebCAPvY+yWqrh8SyMyTQe9NlHY5DtzEBW0cwOUcDicsdYFtRofwaLgLqgHdn7SXsAeqR6yVusNwRcokHPXzDpFk9HBUsC3dh7r5PXrkyqopoNnV/HyE4pSF7R1dd4kHAkGv/b68jyeZwFWQHAO0DNYU0C7Zdszm2pBO72C61b9GnhalSDns0WbH49eMnHw4SZ/IOdn6z2iwi2TzKutC7bt+fkJt+/u8ntbG8riMCCKDx8+IpL2Pn75go62oZOzbGUZQabxT58Nx2saY8MIH3yaiuK0vmJZDttU3A527Gt6Xs/OJ7ostEERfqb9GYKivnuP5+fnNHz26F8FDMvwolygnjUzxpl8wA4FpRO7Z3VRdcf34M0xqN48hTg/6++fY0FyxH8kEjgiyu9311ffj1uFhZ8ocAP/PPUyRPevAN05fjK9nn75AsId4N8BCyp4a3wv3l8kIAyRL2gaK/Aheg+U6LB6+Nsn9N5RPhHkt4lPE7X6z7tskE+//YYCoIRMq0aXPefpRmP3R6PDI+YkVuv9f/wdL//za8Lu8ukXnH773X7z7vZG8O+1iAyd252DW7yLYDWPCfNc9pD18+2JbNyMH0/rvOVzv3/vTMGvws3PvHBqf9iYHboEe0nq8FKvMdF/44WMp9zjs02mim93CMBKkAKGi6Jvw28KbcELO1+pQ0+zuv78UIwmWLZKM7wrZCpxYc8Un4+4o2amLYfxzIGnj8sCVaD1jkoFrOpOZE5aXT8V+GEp1eU2Z/NUUQrjeLSMxOu64ty7RajDZHWTB5t/R8ozYys0cQNhZCaKaPtZrXHwSPlr63usy1iv1lFLwWFZ8HI+4bgseD69guqCrhZU+QZr+50d/PPbt8bwvT7j2ftpjRSGOwgj2vyPnJKvZPjmCwG/KGHFZ4RzxvfGPP8+s/UX9002gryq47f/09tfbkAHdsLeW1uRXFxe+VP7/lYzRsGN1zCElggY1yI8vw3Uh+/0N56dBCxQIiZVM9TUEAAmZsfqZoznmAmu27f7XMG0nk443BwBYjO4FBp1gOEIlYcgHIxmKM96pPyFCaNLsdQ8lXkEifr6tPUMUUFdFtS6WO1x6Wjdor0J1nep1WpFd0Epns5QTDHSZKrZB8Xr+Qw+hPFWUQ4V8rKitQYqjFUVRd27loHCFZFqzYiDKX0FptBtrZlguyGsOoPcRtY3IiWblGnjrzOFoc1AeJAR+qNsYOM6/GgqIgfjYU8NoXVrIJy/G7y+gPB+ghkanO6VNo+pfrD0KMePv+D1y+c0mBM88lyGm4hKz8gHVUF/sP05/HLwvgXmjrKH6O+3IOLhY7YdLVxBPBByRjmKuBAJyIug3sKE9fcVp6enzVv0FaBbgG4I9PojYzyAcIa53iypENQ4d8mghYfemMuYmKVdfKsfxQoig+3ZOHwxumtIZv9SRcJOck06fryAp1AuC3n+9H1nzthNo6Hpt2uzicY8+hbPQJAjIHIllCsBgun0d2dqtVAShkKBLs+QJkzso0Dj9waR6oaHDnj69mCkZ+I+K5zCeB7OQez9mxQ5GOMwd7Oa0lnZamuyKoQigiAY7EgdTwkzIEpjSnGjfeKLSck+DAGuFPL5FrNmmWECit7nvSIQuqWM687uElkKd99JnfDW5Xbq1O8Yw9y+gWZyB/7s9pbT3dvOeKNd4t8pm4FnZAj6CQqninBiiZRWHVCkYmt/TMdYhrGwi6canm5UxYUi9JJdJUA924wfPUoHG9tTE85k7JHqiB6kEW/uA9vOfm8wCnDYMbyhTDfHF/d5ns4BKVv0n5cuSEOpw5AZleeoz2FYniO19tGzpJTG4jebOs2dccFun/8oA79dn724+NZwxnzj+5YRUFfOadKSpGm5FmM+ENnWRwMyFbqt4XC2DOOJ/aHR//Twm0uhmnszz79wQS/dHXTmddFUlAM2n96sfmnvdn1tzZ10JGl1j/rdRCiVzagljp90M5z8GwbyWakfjifi7/+B4z+1t2jYP/NU/Eqbf1zI6zaPlOZcLELQDK7mRBDe9lYX3R2inE+3Ug8WzXc+n9HaarIB88gA4M3W2fmI5EmGAV2ixIjvR8Kjr20PBweCGfwPSz5nMDuphRUwkmZpeUEE9aivOasJM6Eu1Z0GCtiVR6ACYjOMHw5ntG7rg7aCSzibeQpdURCJ/+OEQcPRDOZwQtpi0WG0tDEHnkzaNu3p9miM1IUXOz0RvmvwQMyjHIsypAmECZjqIQJhyPba2Mw7/Gfzihr3jMHXB5c4zp7JWEZ2FKuaU2nXDu0KOSn4yOk8Sc6winYsZYGCsbZTwgQN9tZ7om8gjnmtne10Z4fkYQCUI4+yQMHXu/GZAt+JojcC8QrpR4BXdwifBDIoQNXhaxhHosK8GfMFtJLjwqA3BuPFDd8i4jScRkruCQI4jdDq+0RZWivmmlzxjHwoZBUCPCNc8tqJ45z7urKm0SuxOcOlAdT3wHC9XsoD2T3lW645agw9whjLPH47tjuePxmbsc8pozpuSAfn7WRGrs83xhvQ8CMUujBnJBJg+8lcMkONeoaFMUbrYU/HkfA807qJz0YYcQQi7LBi+g4RgWz0J3EehxSc8ovTZTgPKakwiTWdMZOvQ44jjP+C3uNgDR5vNJdBmMGFra44MUqdSy4M3mvMd2T72tPOgBtxa6g636fMuefh7Gc2X4ao0StpEgKD634Mj5/XFbWc0LqVFVQBtArY4abScKIJJsicy2ryi8MZNdLPw1O/8iZi3uil619K8cOEIFkIA+183i1AxCLgB74wSOhdBq51ZzNG2fD7gcMaToAwuBXQjUfsB1+Wxh0FXL8IlwHa6ysICtZb8PsRFhTvn+E36Fd//UbdWrWocyOhFkyTMOCg7xQUdx8/4uvnL/tjPvYRAOFgfC1Om5rRs84ijnus6np+xc3tPUopELFyIqVEqSxKOArHqsgcNzvBzfNRmwqYzKEhjLqkLuL6d3NMJUhvCSubV8XcvW8O5X8pyfdI68N4Pv2T6fxF3zO+nIb7x1sQ0vw65Di9uG+at1/OdMD6OJw14AkLYdEsrPdQ+vrDQ4rR9N/sIBUMpwXF1she8DH3yuS+j2B8Tvm39TlTz2gdQFHdlBGw/2/x5B9tT2SGpGj//euvwwEAQP/9MxTDEA0Mg9aPGqQZ1sfD7v5rhvgrnOXVqz/a5hroF+n4/4m2H9GfBuf/xPMzR5gkHYNXnZ3Htg/uI7b/2AhCRq9vrHHyNPFBaSMTjeFs+cewjW3WeE+f/T6GOfxUZrOf+I1RrqgyY+1XcGn0IEivpKjR3rrJEkspOMCy/mx7fms9djgWU5kC4sTpYRMbs7Tn2MsWLWEPWo2fDzmQmXFzOGBtzYIues+SSv9b2o/ysW89+9a1r/TP4YV9I2zPzx5X/XntX/bif3v76wzoNG/WJEC80WYgTOPD1N4fDnj2tFCXTwJRcUph6W7ee3fPwTHGe+A10AGACLcKPDHwC8hrUW/Zlf7QoXhOwh/MwvB/j4TP9ndG7usPnCyiQFbOjImnBS6OBMNQFytJxiRGCrskGC54xBq/vL4aEhKAb47o2kClotY6OFJ4Cp3J4h8pHLs0NOlWS0qA5VhR68EVfFb/6+HlGctywOFwxHpa8fH+HufnJyy14vRs9ao2NZphKboqM3ipOL08GcNKphKRc/cUk57+qbILtS4s3jDwKuja0dDdjbVAO9DJImsqF6sr1dQjX8xrulRG6z4/URwPB5zXM8rNDeT11ddUkzftYkqa/uQRA7hFz7wFVvN7IbgvMmHBIAwK4DmYbRcSQg09DJkISQSgYEYH0ZvTWqvXogzFOSvj+PEXnB8sXYwAWOnyzDgYAgBOpHivdzh+OkBV8Pz5M473H3z0Vtc9DHQWWWGscamLzefzM1Qfk8S/fvG1oJhjGJqmCIzNp3GmCm5Q7kyAliePeKEZRzjEp5DvClBXAHfp6KroLx3AGf2FoLgBeXTLUIEBglfg5Qi+ZfBNgb4e0XEa/A2C+T+Cbxirw0LsSShexb3WY1wMRlkY8Nre+TYddWRICzQwhcafIYTZu0zYFa/LPsosTIzYtIx8Yx8iMsv2Cmi9WRROrZvVt/7dGKya+xTDFY8S5YgeTZwyY24ae+CnMRRWXq0NrXewMg6LKdRFDZ5D8dOaG3BdSfPqdUBZfe+VLNqGzTg48Kg683vdQBaMc0RVgQDVYor/LujUrdYQTEhTV+anMXu8LP/meyNSlweDSz5n2WyO/U7MKKJeei8ilspkkGdfE2RK1YCNLB2TCi6Pcg98SOZ0kwKrnztixkIG9wUVzILeAVltnetygKri1VP2LsU8VkUFJGxKJheJTX/nWUNM0+Dp3ie8NZ2Zn+fttgqCn356Uzfye++hC3iJ66mniJ898mj0E+jZVKMKgXZAyEqJVDcGUh/ewBFV3EX8d8twIt3fNCk9oqyBKkMRNa4GLMxjjanqrKHCUOrk37cX7aqwkVc253z8NhyifDEwjOJXugCx5nqNEgE69TWNIfGIGcmK6mYAYUS/gJWYpw5cFMbnbZQ5bd5lj+j4S5OikjCU/bkcw/DoenA/G9McIvrrIoLZeLNQhttiDmONes2z6DJvmxScUVIgXmk/XeEfpsjAmXfeLNkY8JXf3QkjYFE6hEY5iahL2H3M1JsxuVD0zliWitPJI5k9Sq71hraulkYu01iPfbNMQRWlKFQroqZ3PJ/0NqPuPNOMzyYU6qbc1rHWib9j0pd8B3DtnHxbSP0+itu9f2esYHiJDrLVDsUtexQAF85U7iDD76FM7tJxOp3cgO7Oo0SeSp+z1EjWhg6oTtiKNbToyd4jcl8sEjvWHk4rs/ZrS6NPOsSEY5tYJiYzUMQ8COV4RKkFh0PFcjigLgtKXTIleTgOmFOtRdO31tIZ4/XrA9b1bP2oR+i76lejSDosehI006NIq3xF3TqhjzS2xXcd0CDJ1ewfvS5ttvN54BtjYFAPx3SECzmMuqJ18vT34lmSgsaTG6viLA/HvTCih5NC9Gz16iXRiohgfWopv4lYzUR9GQ4udr8ZMojDgQ84P5099yqAhTIqxHA5Ev+a4TZWCZsx8JTCdhjNDa9HZL1CR71FjfxfcBxOgAqknT3ClSHUEE5rQYECslXWLZ3AwPaGRjugJfduiBRqkfZqb1MeDhW5H2LydFAxFY1kG36P/3WHCKEtdJDTdAqZ1N8tE+6y9wSfupWLi8tcCk9bnc5FM80ZHzMrzOx8ETwq7fL3Of2WyBiD+T061kpnZ+bBD+/1NtHnclxGz8E/BZ0jys9JP3+kbWj+wGmWaW82otu6RhrlIAGz41jSYBqyJG36iD3xubuTagEbjMQqUjgeTETbcWKslBnMjc6PEZD/3+HNbgxpKu+ATuOgKM8gY48dVmdabiKGZbey0iDFnbZ4mvtwBNpmK/N3TOs1/02eSQQdntlPLHtacZ1KF0vBrlqgJKCKNPirZ4noYjAe9cmlVgB2rtbTyRx2as2jIH2UD4FnlmnN0rO3tkK059jZjZ6GZXhE1TlyLGwGdCFJp0YiMzy0tZnUSrB55dqag400y+jYV3H20HCeyc/Or2/OBY09Q4e+HMB0A0aBpQQXp+1ne1qDNo8dLfQC1ne+Z25Yjr1zSFVVyItAcXZ8d9kIwNPDF9x9sJTb7EZsbAw2BntPX76M9Q4KGLyx39pcwxXo4Pb2Hc4vz2AcIDin3Gt8+AgaeHl5MicXX/coxQIaZamIbJ9Wp6fXccTQyakSqpNL3wWYtsMOl4iCyjhdgHEH7HPvjrPJrxGzZ74zmGYiNABdp8jUkAOmFWfcgz5a/7Mx+VttTsGuAI7+uvk6MCJcn32g97ZBOMB0zFG7/MZxT1ARIjeUE3Kkc3aAgjvA9SqMbZT8tbG/0DAm27u+5OdYw6QSzo80fEHVX3D+7VeUT7+g/I1x/m2eta1e7pAqDn5u1h1vHuOK+U3VNrP9rIN0jPm9YtK0AsvfPkF//S0jxgnAgo8AgHv9ctWIfqfDUKhqUfnK7oEAACAASURBVJ77NhvPo5Zx6G92Jxt7eeVnZjY/+T3j+dtwOnDZtft+lHz/aPu5nXvjDbusnUSj7Mv2NqfNDnPAwKc/2qKnrgGJJXsOR5y5bIQ4TgrHrGjnbg5NS62OXwwSa2GsYjYNSqP7iOZeHFRCd1eXCoFmRi2rGW5zaiL2vt6xsGUIQuA+Quo0AAwZUoGwbtVaIWtL3ZIv4/Z86g5Og9/wz1y87JtnRuaQ2yjOrc2tljKclTVGEI4QhNeT6epHVi3xkpkD1/3Qxv2L2vbU/nxXgSMCx3zUwNnXZ/ZHzmE4A0Wxnbntx7/vZ7/vISdeuGdM/K2JN7y/4//I9hdHoO+2ZyM87FrgtkRwl/dULhshavRxDayMMN0AeJ3fgXcAnvKOjbjmm694uQCsIOZBAAEzor+/v8P7WrH2hqW/4PlZ/9CZjfnas5MwYwNDqHiibqCoGb2YTIBae3MCQelV+/j0ZJ49/z97b7oYua1kDZ4IkJmSarN9u/v9n296XOUqbZkkEDE/YgHITC1lu697vhncK5eUSWJHINYTqpa30g2MQTRVBOV4QERlKgCIYlkWzJghrYFAmA4TpjKBhbBohdRqF4kCRCukSnpBg10J4QJCaxXz7BoeVWirOJ0b1lZxXpaEXjalXktPT4uStFmxKL5mkIjFvKLl3NDAkDJGoTKWtpoxm014YDBqE4RpVR0qJffZSXNPrk/PKJ6bidCF1kG9tl0rHXaeM6eCpxfXl3a1vLUfNlG1g2AbTwge0FUlb++4R3qAfnvE4bMxh+f7H2AAN78ecfoGKB5deaupmCiloPo+eK3HIyPOiDMSc0nZR/4Aiy7ZVUY4bv4ud8X3aT8L0hwuVhTteQs113Ay7Clczp3gDNLb/JvS3WWkUIp66j6w9kwvEaWT8DPkghkNgrvX1FoDTQRaXzZsmWB57UNg6ET/138fbQV71nusaO9I0P/tTLtu9levtzNXQ8NDSQMOkN71odiQIRpkMy50pssE4r52fZLcyD/MQUbNXxGWTHi3aEku7CkrzCCsakoeNFO6SBjduGCeeTdYuhDGuj09jPR9LGlU1OwkIleQhWYgc9vuDejV87Yybx0VoiQTrgpEpEJG9QqkEYTJGFK4OMrkuWbFFfVskMr5TjFv1cJo5G171KM2duN8AzwlhjGq6Ckuxj79BQP4Xymau/3yRFEekA2Lj+s0cftcRFcDMIUoxx41VAEg8sZXY/AJGZlCREANA7hF4spkRnQWS3/SpGXua2BUNCNzsYbyKe76sd92Dw5RihQj6IaK2IsbMVx1+P3afL61lMNLbuwggklaOxy0cDyDIiHfzUHj2rm6JF7R7w71SyA1o+Nlt7bG8zCgI+fubZlpq0h8vfStr7vP1WnNtToIcPQauFC7lfUHlJyQaEMgZSQEPsnl2C76l8T18vN0IUnjWDwbZhK7v0QUTGJOQeIGJnc0DOW3OppCbRVTtQjZ5yfxqHNznIDa3bfWBbXV3AuETu/KHFHY1pXWyibP9yZqvcXPACutwVuOaAf/GFnalnENnLZ3oyV7lDnldwHVHRHoYUyuqzlNrXXB6XTC6XTGui4QkU0+9cnzmxKZ0xSz9rOIHm2u6k5Vnhfb6JetT3N6L+7sAHZHYq9LmqELmNxlTl3k6VgKm6A8zxNujjeY5oJpKpjngznWzjMmh6cXtT21rmY8X9fFctquK+q6YllODtluBsRpKp772WDMRSTHNUwxgO7ssv18OHCq23MSZ+7N87+lJN0A178KWmTten5gd0LU2eQiS6k1sHPUjQ5p5IvvfG3NOIWE9gcUaJrKFUkHEncknU2x1k4d5YePoxHZnQ88f/plIYx5l5UCgWeI6NH4ngHyu007/ydnkzv5aKmzAsEFbqAOPisQ1NpZgLLaPRZG8ysHWa/90VnQi3/He28rMY0jt3u23zvGk0awEHGPJh65e6jzko7oPdb/EgkKhWD+fYXv67IuMgWGOD1EwN7qBYm5IhfuJiP/7DxcKJJtf5V+p/r6plOYP39ZqaXmaNV50HJFzbQ7XnFWhw15+c7V0ivqDkP7aHS7h20vSn8vLLNxztKISN6n7dpu9sa+e06/xr/9MKYcFeRpHCuhD/mSPdW+FxSp/1JH0ot+BCRr0K4w/gb8u6GbOHoWFYx8sjnhaqYaGx0KbUo6WkPINpGuL56rrbnTLgGYNufKUnUwSMaxx5w3LMsKaWIQzQdFoQKZpEeR+X1uZ9Ad9YrRFPFUbWtb0WroJSgRXYgJyg20DE4D6nPvKfh0UPWG7mtyo/KG9ioSmQUEaw/NnAeH2dzQQuoOSew7j4nNcZ7OaNR8UTtPbygFPWpw3A7r8xMYNyh34x4nT89nxnNx5/8XuM4sD/c/8OHTp8sHfH4e7++hXIB2zTSJjQw+vr4+m0N+w2JiwDz5mBV19Rzx3pNwcrH+UqIBxJ7noKXvoAXqfYrsvuOqmmzt1D3qG1JpKDqySJ72OHfUjVTRCwkDTeoikfUSgPKZhnV9jxTx/vJSXQXduP7S94SPiEjz0I4pQm/9MKQp/QjC/Zv9HijpRu89lgAxDElIvvVa16/f8vf6+zeU337p5yf7p904rrr7LkiezfMH/fMw7jEORY80Jxh8u4j1f/71FywejQ6Y08BLEeiRW/3P9OGyyj8/qDv99+y/v/rs3/HephDcMN55zK6z4y4bIO7+OLKX8sLP9PslqUE3T7xdz34wRIzCCm3igXSdR2Fm1KZ5zxAcVclRLAOdh8lS5AJIWmV1XBuI9ZXQ+Q5TZzUU9DuyucM0Xhn7WBY/wx+8ISJLThVYpEFLS7GRzFNJx+4mru9kQB39JxH7yBAsig71/IVz87+9/F1nOmkZAaFOCnr+t5b/Q5fin4dwD6IWDO6VcslMDqYdVy7eHmccpwnfn55faWxQGlvFKINyEgDKJ4bzGCCYx9ZdMN3xHnX5SPEIAnD49BnMjPW+QmCwSzOA5/uHZL4Y3S/pWSOy8xr16u21hMt2YdQVMMFKWD4uRin2/eTQjaZANCjgiGoxKLNow5g/kYZlXTFzQ50nm8+pYGKDZLdIuQalOY3X63J2ot2wLg1aBTgC03ECzsACU6jNns+wFEYBYTlbJIGKookLfqI4Pz/heDya13E4KbiyDAAoBLwZkJPPT0EqXiLvu8l13Qmg1mpRKs4Mn9ez5w4BTq1hPhxwPE5mcNWWSjhSxXQ44OnHPSL34JDh3D1pYo3CmcI4v1UVK4ADkfsB2145A7gd93jqCdxA78L6eA4yUmAvqFwoV4ARz1WgWL/XFCTOpDYKHV+4Xp6gKN8bjp8+gZlx+v4Hnr9+xd1v/wLRHda64Pz9Owo+QrRhweoxagTgFuoOAs0vMnaF2IDejfmT5WAqrjiNOQJMOdTuG/hj+s4COKbwrs4kTIXNizxG5Er61gT1yXIWKM6+H4IVGOY9z/MRwDmZCFNFrakjEd876gZ1uJIgma9YJ3VFvmIDu0nDOufUK4EmcgIyAajZ3pjtelRWUP9ks16j0DIqY9ppBYhQ7m6MsaKCgp6DMgS+cpghK1JMGQ3Xpsjknru4Tx/CS1ChqZiJSDQNejUoAg+TeUTG3wF13ZymWG6fnkMvISI1zjW6sRzBBOcXCCO2/Ta5Asn2SHGlc0ClxwjDkNeEATZayErQCaB5u18o9pD2iRgVJH1mIlebjSuirEyID4GP00jNA4R7KQVaLSqpR3O7QUi258Sq9/ymZJ6m4kpoMONQFHDAES7AxJMr1BuIjM5ZXlCksV2g5u0vimmaQapoEKDaXRJicLQtfof0DXhd9f7+ckkfrzzyQtHM1Rl/W5fChaj3s/dSB+mBhvYd1cNpvqjNkYbxkiThOIUJUENUIFU0aihSUWvPP2lFoGrKaGkKLW7AapJCXAnnitzXfi4ozgAlnbCzwpg4zKC+hmkgG/eKblK9hG6Hh+dHfipqe2sJLriyUNYLkr4MX6dS1pwvFEKG2vHanumG8GjRBOHw6u4K380bXQgeFVl6Oaaxj1ejVIfrdw+rlrQA24/s2V63KYViD4aRixL2P6huTxOA7PP+3ur1daSQlyIt+pyN/w5/eQ5bo1F5UfV+A1A1HqvFPIu9JypY1hW1LqhrRZOWeVDDryrpRCp7LcqxrqsZ3V1BTWSe5pPnBGVPP2Hjaps6Ykl7RHpE4kX3O6TryEtvDEmEi3VzJuzKF9fL+5668k70NdZ6IHe062fMJTtsO2nf102qG5st8jxzK2/OhD/bPFWEO+pEBL9ECgkxRwcVcQN67cb1XEc3QCkZDDkRWq1Qrf0uUrE7LMdnvxAx5sOEeZ5NFnD4cetbA5qhn7SmeH5+xrKYY0B1VJRaV895GxwH0smCufgzLcdzcVfKuBeGMwq93AYU56srFN5a8KQw+Z9kMjHNN2AidwJRtKWhlSkRBsid21Q5HR4ABQq7swBn2qnI9Q6H91eoR1Y6IlTkJ1cg8qDzQbE+nyEnN0SpQ5ljBsV2d/oqTcFFAGK/L8QoA41jtT3K8flAi2L/Br3mPjP+rvVJldDOChwAXe2Ml0OBLCumoyERyFkgtHq6jpjPQIehzedh4NtEx2rww86jR/bJWOChhPMOCCCG546291qtBi8cfD0sHVhtFTooMovn2Zbg1YJ3HXkMZ9DzKt+d1ZjQ3IPBC+hg1JbuJKwO83+xN1WHNQHgTqub2y37N96xHa2GYOfcnhsMetT54D306L4bda2Y5r9HxXQ5TzCUCwDaavI2Nn+DnAPn63NN3ZlDFdDOZxPpwHfTcNcP9yL6fZyK93H8Iy8R72h3WPEFTVkljKqU//bTwgGLHmNPNtUV5NrzmPrH+TZlSqhuRCeKh7ZpTUa5dB9BD6f53iCihZBnrJ8+TjLetTnyGVL+U5e5rB7L2doANWS18/MzFgDH4407BVnQx+F4xPHm6GmsCup6hkURrw7Dbqhla12wrCu4FDPQsjkiU9ybcW84nQSaO4GZzmiEe1URqEe5Jxys9Ah1SxdjELLSFj/vMVTqPA+6Xo9yzoyuzDc31vdT8G9m2pWgEy0cmTTz0zNZjlmjBSfoIwA9gm4IIIU+SaLmAdeV30nq3XjEcclRnIrhwfS5VfcIHmQK+J5SRZV6Uf8aEekAZg82iVM0lwPCwWp53qL8JTECEE6/DYB6BPiG0DkN0qF2G1sf/zgXEdgU2Hspm/uaMRFq09zXSZcjZZvrDGqciZib4SDlGsff4QCHPm/Xyomuf7ePPI/y7J/fxb0dX+gHAA8oPr7qdYQhOKavDrx5lL5f7kH4CNGH5H3SQHylk0+wXOiBuroBQYtCfS9ZlP8fKAqI5xQnKBhfwL8Vg3WXgSaj06TDr7/i9PvXi/kUH1zM/4fgD/zv9+Yqv/uv/0KtFc9fv24+P3/7wx18gPrtD9+9wPqK8TzKPQH/9dt/QETw49vvrz47TvMWo/P6Ary0n17qUvT7rfdfKzr89+WWrr+XN+kLr/+Z/rxWCPC7IN3E/fNwXAaAbkcBNIPDEHf/Rjcgzh++HjkbbxhPOY47dvuAEAcgEviF+j546LVWEMjRSgWT6wmLKki6M8/sSCuklu7L8oqbMfk4W4pRODrPPM24KROICM/nsyNhIXmKkAsBWECk8w9rrZBmASKTp1YRURzmKYPngMGBZ6QD4xyq5zFXIBAVHUczEZssFbDft6pYasW6NpdFCEXEHFoOcwasCZk/FFPQfsJa1808v1WC4lxKhH+tvFTbn2/Fevqwyd/XT+bAsV58f60EDfsE4CsRfvE7JeDb3+rnW9Rgu//R5Z//Q8o/akCnEMYAvGtLhSDpv49FBJiv5duyloZ/t+/x7m8iwp0LDQHI/URA0XtM9Okq4SdYNLNKAEbdokep38LE9+fNOz9TFGYYZ6IhasmZEgIMvK/ks0w9D56iKw1EGhjGqLC60aWJGYy04Hw+Q6pgIcLHj3dGvINhFIN0lLWi1YZaa8JGWirdLskVJUhrWFqDMoF4xrIsGX1qkTQtYSKZGM9Pjzgejm5UsNyGTQSFOmEIzcJUGGByz2tX/uiQjxEAXCBWKOCRPOR1KAi1rmjSIHLAYZ6cwRS/IBVNFdPtDepTQxPkvtNnBX1gN6AIyocPWB4fPKr6FhOesAKdeQ4t1XBpwL/vRrKRTboOg/vi3hgVw/433Gg0wnGEl9Z7dt+Ce/xy/C8oOjrD49ffUfARjQymvaHDtSsMYn/C3aZ2gvk5zJ8+wvEmzUDqU1Jby6iBKPJ4rX9nAMfsDeGuz5czJgnpmjTi/OL4+mwdd/8COgiANPwAwPHOzvLyXHONTBgt5jCgBpEZThqlTAa9nlCyAIbIST4wcG4QTIhcjfYFAWpwk9euxJdKCO8XVE5hgvZYT+6T4REg89nnDOyatiPYPwyjSSogE2nBRWVyI3EhRxSmbJ6ZEJh1o/Ec0I1yaF9eOh/BHDMJmAIetqBMZpyJSKbwIIfCo4oFiEjfvrEQC/Uic+D0Fx6RFyOBxB60WSUa4l7IFDkBKW9pJEqy+ZFTMCRPFXjEZ4dLz/Y9ZYEpbM0ZYK21I04TABQozMHKEAMmWx0ypW/tKWUtqvFwTuVRqnZEweztu8C6iezFdk9s1+T9991fYV41FxSbjfPaPrr2fqxi+MTSaFQbhBELBa4wpV4LFQ5UgFobiCxKtJTJhSm788JAMhqxAPhyb6MeVBkogOWS1HjIGdIuGPouS8Vb9ybrd6NFCNs4LPeU9jQDGm0DqZTxTbGfulAmdYWWj1wUxKaU9JaTNo9R5TrQScD2dkQxdjHGx+UaGYEAzeFHo1+D8eH6enZDTopFZHNRaPvcbhP0vdQnF/2T3R6lXseGJQ2Fe1iZdichnP5GsUeHJy/o7vgBwQSRnSy/Y4nHTl+erGtTF3MWI1WDmUbpkUgEjzSXhuW8YFkt93arW+OdwnOhRw5meBSZ39EWfeQe6G4sCF4gaGLyn1o8ypyyX3GG9tECyRcP//7zpZ/TQY5EGDlGZYNd1ZrPEMcdYfesqHpe620EuT3fz4Q5ERi8vRmi+02/NaqH4Tlg8cP5tnOPeczUFdKiWNsCuAFvO/+BnuD5ZEMhMxXPc2pkVKWiVTPYSquWY682PNw/4LwsWM7Pbsh3eF83zpdSMJXJDXMmvtZaUUr1yHXjTtOJYjzL7yz9Dhhe/0mp/9or6sTbeEaDYGdlkDtTzfPsezbu+WaGclKHYaaM6CzFcuWSG9LbYmfSUvaYM4JoQPLrJm8rAcBxJ4vEuiuD3aECekaZj0nPKc+a82sgkNh5N2OgAs4vBBVpp0Dc6g4DdL4xWWBx0yERQAKmirb0/OWEy3j4d93l6PyI0X/nTdM40vlWdifGQH8gDpSiTrGNV+XsQKAyJM+sakAzgzzaaWiP08u0RjmIjlBldkaj/uRzpTQYrvw8ZeR5OMRowIHGs+Eg0eXdnIfdRBqKTo/0HWGJ4WmMRijp5JF2yuVhI/UF8FUzXUEzZAxP03D1nc3qvVKubAByFD0Eyh6QkO4RPLCRsK923e9g/1JiW4b87rxX70bQ2jDNbXs/RqcqtKdgGt4HGSpWGNn3LEc43wIYzmD6JyadYJcpQJr+WeaE1h3RriI35ET0+zL5v0EyVKFhH+31Dbb/2NPIIfUMvYZI5cAENNrywM2gsDDPhi5IBEMrnCfM02yQ8MSQViCtooliXc15pa4rzmczoJepuBeLQNURxvyeS4eW2Aca/Knk/tbhch7PXLxn+q8twkDQGR33VNQxKorzd8Vyesbh7i4h3tX5/my/GV8kbjwnANLWbLb5eitOpoui4CA7j/FyUZjTSBnkmoHXQ3fK7HeR4txO21qcR+wBDLrhFwDgy5dfcD7be+fTCcebY59TKA43NwAIy7ognOV7VGRKELknR+75gCMaLTZdrC6L9f26vXiHvQpg0gNIBYya3zZfo3ze74AIPrJJ7mmn+r2gcRD7WdIPA4nan6T/mRJtj3hXBIeBR9CTj8Pz2MyR3dpWQuP03vJMZkQPmWUT0KG9rb7TLC89aX9W8B316xfwr10fxZGSErYTlt+/gtXCPJhoiEq3+jdX2/Dznqj0j372woEX2EahRzMVZpD//BMTNMpTrz6H4W7A8Mv/1KZ5Zxn3099R199Rz2uly8+ud/SGx2CbQPRCBh90RI/QlVw4y/902Y5Wh1/edqsJ5EMgTvXq+csj4lwV6dwVSFBxxiziXPF8XnCYigew+R2807d3R/ORTwxenQdH984LQ802UwdwEuKw+1yPXd7PZYW6Y1PYqZyGDXYrBbDWBhBQRTGFXJxcFWEuxaHqQ89Azmv9xE77h8/Yz5T/qTN0P9Cav3M6/qfP+z9d/hdAuLuXavwdDLpur51UPCEuJStBDu6fTxZN/kbR4Sc+CEiyD8oQFXz6j9+wLAuOCnx9uHcm1b2HlDDRR9z9a0atf+D0w4mLu6LOX2aoAOt9j0yueMY8MIUTgMx1lkO3uQgzVxyUKmKeNUJoClT3xElYEniUrOewM4Ln+dqS4bPLRMk8OyWNMZbDihyCq7k3USHGcjqj3DKkmaDCACZii3ppDVRX1HXBeT3jdDqZgmyaIGzKnno2Q04B4/y8RMoqBLxYU0GrzSDcpxJfWvulG0QplauEuqBDhZFHYJB5ykPMWC7afE8R+DBlVI15MCvmacYEhzF2iEgRQSmurF0BTGTezAuh0gLx/UgA6K57lqn0HZpskpo5VoA0NsW+PSlwB+D4+TOe7r9vhNGoKyIFxmgOe79zifHe3tg+1tfwgFMI38HEjpt+KB/0EwQPePZzUPQOa11x/rbg7rd/4fxtgaKh4gGnfLurkOI83eExf09m0KHRiUz5Q0MSb4Kv86OCPec5fxzVDDF/nZMl3Nr+d89kdQjrWte8/LfGcz9X1P+ysoWEl2dBuWXMd3dYnix3ur0wo+eZJGgTXyOLGYg5LWVCrSbotlYxlckMt8xY1zPEobClKYQVWBh8JEw30wYafqsgMrcEc8qZXRBpQM68R6wPy9lO1of5zlIvrM8mxB4+3Jiw6MzhxOa5qGcZBPzcYPYZh0DDFmngz8X8d2hEdSVJGATIvZJt3o6HCac1IPH7+FokfHNFncup8E9367WdnzS6USgcu3KUmFGmMJyb0r3EeAFA2Qw4NLkgZ/QxoN43vu0CSEiCJCgaSsVi1DrOVoSQqL/ncxiq5ICB89lzmjyKZ5SK137HKaANrXEayoPmxb5LpyFFwhsZtFJFW8kFw+L5ATvzzFyAYjB6ZZ4wq2CuBcfDAYUZa6u+lp53WEzMtkg3SgV3v752aBnDVnpf8ftR89fN3GD/8b4oBlq5rTZ5h5DyxxtWgz5sxdeuLPMoQA0apFB49Er8rZ72xAWXjKy0GxwipsjskbExLvuJvRvOJgOxszVVHZ4nf6dDbqq48UKNTxFiz7VpRpauyPWWnYcIDUco10MA6VOnfvf2fROKv0RfGNZI/YzoOOlBS4a9HvDtDQ3s+Ywt95Vu9qiqQpvvd99fdo639fVe2O9hCNB0fHODBMTy7OZ9OPQR6lEXmnPUN1Cc2riL6KLN4Gvy/KOXboCwOe/3+qisjt+oR6L3hdieqzjrwXCM5XJaNkWjP+qKWFI33nSaE8r0MB6oNggz2HnJ1iwi2KKf3YmytmzTs2ZDWqD6aIwMoMjd6dGzbOMtwU84KoO1WxyKuhuIzahuBoNwRtpC5W8juJMHHtf7hYl5j6Lr+oy+55lQUGiQkc25VBG0iDLf10oGwxuIPQqAq0UkMFvkchiLiNiN4RWqDnG7dgV8dy4Iw3kY4WPPh0En2o4uGEoLubFR25qyhd3fccaGH20QAWpd8PT4DKIzxoojSkMEEDGH3GU5u2PuijBu1GqOADp7PyZ4NLB1rhiwR+ZR1UbZi73BZ1yP7RGj/g2NNBDb9bjYQzr8154uh2PO2/n0lLz7VCZMhRGgh4WL59E2/qquK8KwM00HTFNJxxQzoHM6EVikv68FFMJi53NQFBpVMlosUPDxAJFTnkdRdaNuGHDYIjCJIHK29O3Dna5ebT0tYNxgvqUkhXGm20khcoZqB0eO3X/BywEoN0bP9XxGyG3R/dxbfjf2yLRrNfXlUYU7F/U1NaepKe9Mcv6W2VLoFPK0NcUMzyKK1rqclRWp0bdxb6krXWMLNDdw5wc2Q0Cz+RI3bBYo5sn6ZAlhwhBqOYEhAmZFq9aW1JZ1NzfojfQ8+mR0vKO7RHSwdcfPbNIfdefMrugfkZo0Fn3LJAzOrn2U+uoHfQrfRTJf0uVEP67UH4Z0aTUVzb0u3TyvoHRktiEF7YtXthdpPN95tZAXislGKTXEesRGtAZiL/fhkTvQFHc6bN2BwfdB3FvJ5w1UJtbaeFd1GcgcLonH8xL/ciLDAG5o972S9H8wEIfOq9PR4Puw2ffeW6Q0QMWdAggqzVGVBFQKhNgcfqLNcCAU0zHVaTKnqSZoa0UtK3iekFaQ2KvS7Pm6oq0VLe4HUqC5fNLMoaiuFeuyJB9iMqZASU2n1gbDb1/AvHsUhggmVfr8M6McjlBHarG57NYEcr1ErHc3DNv8n5+ehpnt6yy1Ji+qsmI+mu6kLrVvVA32r+effakMN9qmby7V4eHxAR8+frh47/Q8ongqDocjzssCVcHxcMTqeo4+X5QGGmvDvjseLAL9eLjB+XxKWuMuPwh5Mc6W3TseP66C480dzssCwJBTKOoGgXHwLpxcr+RpJlPRuB2z+nxVXgaUOwzP5cE3uZwZVErXBYSeyfWJ4eSofST2uiuaTn/8kfVlT4b1einy/M3idfCwV3MvDfX3NIndtULpIb8vvo9i1/ao/Xv/wJw7PsR+Q49+35cnrx/oxvSUpr1zZujThHTvt2PM4B+Qb0D57VeACIIuN1hUvY3vQL+CfyG0b3+gQU0u1M6bbOQun4O3jOgK4Pm//xuErQPAI5lxDqyHcwAAIABJREFUnby/Ec3+45W69uX/+vY7Pl4NzY/xv/DJwMbZnfnChbor+yfirYdhLf9MuXzvpZreOTnBUr3x+GtO8q+1zi4rhqxFm2eM9yuRWoYArfYgtfaiDPaeoV3i6ZlGr0lD4e5AWN1RamQt4+loXVymAYApUu+S8aYhm9faPCVjV5wSCMWZm7W1dCBUBUrhjNxuYimkxoGSKgobIlx1HZaop/JSYHKEscmdITvSigU30MSQZgb/nAENe4YFmylZkGSFJBJpMeYKaxMQI6HmC7NrwLsDLmD04FAYS6vJ8xZiaGse1f9OaX5D/v+cBuC95ed28ktl30cd/mutbD+J+//1kX1SuxPiHvi75mHHfVz57P/d5R+HcKf8b2dgQvDYKgiDkd9RHC+igoleikB/re2xWKV1XTfEDgCeSPFJH0D45FDEwDz/ghO+debJiVrP8XuL6UNBoU+Qxwf3ptc3N8+45YM5COOKfR9z0L1+LRKSoKwQMaVSPKPUvfYolObQVLqpEMAWOVfY4PuWZTUYjwPhVCvUL5a1NrS6QCeLWD+fz3h+fsZhnjCVYhET4WmuYlHm5PHxrtk4HGbM84zpMEGeGtbacFRFbRVMBvseea/AZtDiMoELQOuKMEwRDL6j55vrFwVCGUmGMjBN7AKiQYDELAf85SrmqUVkuTXaekbjisQW8ZJCtxu826MZ7oOhLvgACUPyBRVSHD9/QfvRss4Lj+7ht9cVRTvF4ECVtuRSYxu4rLDt1J1HMjI+4KiPzkROePj21RnX2Y1vW2iwHg/eyxO2ZmkCQB+7EOkSi/UhBJBHTbj2ONvtQcAfBgWA50rfjEg7mR9hi+VZARwQBvCXiPV+bssdD98B6gJaSAOkwPrcUAiYDox11fzahK4wNJmBtbaKSSdME2PGAUQWZcWqGB0vmIByZLRlsr4qQbVDo/mo9qP/UyXpxqLQG8Umlx3tZyToyta4Ho4/PWrUv/Pn+pq5gQOK53VNxnKPlpBRFoNy7loZ29squLfGcwAepVU2EWtcHGKe4AYCz5VHjFImTNOEw3ywKLm9gcyVYaYUJltDqBEdCSjTfs724+huB8Mn1BVuoh7PldKS1SFhJPP84zLsmx7VG/3ze8IVt00IVRtIgFrVjRVuZGGDgSVnlKOeQzuiHSu4rOA6GbQd1A0cplQSag6bFLuCOlO7i0Kw79+/Y9/QB71eoqFRsTcqfi+oAO3+9fYJfq/a+RhTnhh6tVnOhXUwdLpXMBHUHdhUzdAITGBWAGXXDiGU1LEmPWKIh7ORvH3vrgsSXEyZpwNm4chIDwfmYhG0ewD43+pnOOhanx9Ni0Sn2yBzCAqF1qYePxvbUxR73jaqqICFISR5l3NAO+ed5Ry9j7moITXwrs3eytCH/WbKxd2/1M+tYmvcjroCXQOR531X994wSxe/bNvZv7cXgcal3n2VzODLUYBjR17jIEY+M+jHMO86GGOYDalJzbCy1mqG2bqg1oZW2+B5HpGv/rlDaseWZ+5HkmBwyKMzhkGIN+eSe57fWAczoBeU0tBaAbNkPmibT0H6sozs0Ru05SfQ2/9C0TyLOqxhRBKQeGqIUi6MKUwG9W0cLFAcWtoixYAxUjSiyms1+PN1XTdGj/4jw+/WP2LOyYitrnBHRVVHshBAxZ3CbJqZu3BsfQiDVMXpJFiX1T8P2gwQWS5veDvNnTKi/2E4AkyRVMoQLYjOE6iOUfoO2Jp7eHOde3ntVGzviv3Z/NNFDS64EUDUYAYtP4FkfFVEjxtijPEr82yw7qVMKMWcJaZpMmfl2sCTeQ+0Ys5IF7KEKsqN8bJmML+BNjOQ6HlJCGm6vUF37jDkCIBQtCNZBX9X6AbTLafxGVBLsyWKcgew3KI+jmp1ePsAOZoNYE6ty+kEEFlOdH9+lOX2ZXSOuTrNV5Yqnc29XqYhfU7kpC+c0eggg0wGkMrGgG/fr2ncGUb37N4TbekENGjAfdMrWAsIBVLsDILIeQ3rZ9BIOyp2I4sYastoPBfnMyhlK++PG+/UUadI1Qiv32EW8dr8WadFzmmo74cwOIV8E3KAwpyIr0zFlQ+iNqQjCAGgqc/lBSrWC9f0xSG+dvUF34fu3LkxIkdEf9DJPm0bXZNqV1ITb+XwkDeC1tgZKPn5mH99dIAf2Q8KftFpsjSA6uWcBt+x3+ud3pvhUIQwTWT56l0OVQ1np04nR/5LU75QT4MXSAY+b6qpHO80kJKeBjpQrhcFH9vn25C1jHcUjwwnIkcfIhhqFhIdo7bmKCIL1jpjlhnaPFBCKZG2AnmregCGuBK9AcZ/k0LOFmzSPEiitWrdjXPkaxz3kTnv0WabhZF6TLM0OvjA67u2DwketR7nv2/4VClF2r6R/1Kf2/lwk/s0Im+DnxsDiDb75YXPGIfehbw8LQIw0WuUMpBoKpP1SxUAo7aKm8Mh9/LHjx8BBR4ezNi64Z3I0Dj35Xg0Hc7T02PnU5LuAMQFrVaMebjMeK6gcPgFUHCDclOwPj94cwPPeq3s+P4R3h3D79l9Z1ILMyY2Z8LYB4aE03njnEvtRmz+cv3e+p8oW4fxBwAfPYL8YTPG0Gzp8NPf6yXHMLwzBJniVl82okfZRKTDaSz1392HuI8Bu9+v3OusX1D+ZecpaNv026+YCFh//2akZDeeNvz91mr0FfsC4Ds+aP/c4NrxJlz731l0+KWr6N7Hg45PxXruo+l/to6/s7x0vV8rP2s837/LjjqbOryok4L3G9AzAaC6LPanW+3FzlHYKYzKra1iLtOGn3hXXU6Hra6e/gp+Z1uKmriEEQfJ37U7aHIZea3VeVxs9Y1R/PN0qoPLjRKsrK2gpVwrWNfQVfeV3et4L0sEoPnvKmiu6zTkCWDW7jfHMPvRjt1IB7I28FwCoOrPS2w/sy//yULAC/tz7P1+9O+bDYZib3n4/8vr5R83oMepGPjLi3KpC+2MQwhgTRWnVhPyrb8ysgu6qcMOLDZPrt/vLV80E46//YKPoIRyj8u94BFNpg0ju3z/DhBh+vQR+hjk4Rn6CI+esh5UADMIBxiBSMDoZGz3/Q5BGilIh+Iq3yM3GpML1NTHWh0inV1RldAgDp314fYWEeklsJwThRmtCSZmQAw+fp4K1ubw7atADoK6Lnh+OmGen3BzPOIwH1EmEw4nj5hQAlpVzAfzoDoeD1jOBsFIRCiHCW3xHJpiedWbK+nCIElEIHHGPHILkf1IaxDP0TbCgYRCV0ZBDxhg341Jbi7kWHSVCTBtbZn7ujCB9IjFIfiTIXTFUnMzcsOz7SfcvkCILdv28uNHoFbneveIcqt3jDDd1DAyAbvPLwyTRJjR87Dv+/TbL7/h9O0bjl9+MUHmh8FMf/jtP3D/9f824zmAeTpAvyjWHxULdcP5SwDp+0suPOHbvYA+RiR4N7yUTyWF0/YgELXTpo8Exg0abVMfRExvEwFLP8CcnmkKxRkjDCMAsBvh32Je1mfFfFdc+QK0RfH5109ZE8Fy+x1vCcv5DCbGNLuysxzMU13ZlGgikIpUzBUS1AOgq3u2nxV0Y/MzHQva+ZoSZZhZBZhmG6dfdS8JQzFj5WYGQFieT5Y7/uYIOg4vHZxe1L52Sn0VU7gwuRJwhoopzo+JWMuyWl7SATrSGK69Ad57pkM0A5z8XdvzlDVeFhqM56H5YVNqWbTXhFKmDteUURQEpoNFnvMACzsZbGAVgS4KOpIzlAOD5fs3HEJUh7apqwNDLbONZMlMnBtlXyhRTSaPlkJID2NsM8Hdxx0epuLPpc+sKwojysjIn0dEk0c5qxmI4+4IT9KpFEwHQzowhbFFQbUmrqgqnosXBlmvXSkddOwlB7e3y/7+2/7xoiwV+ylyGQ60MJSIdocE3UbuTygbXH4YZQJK09d4WPDsn/h6s4T3u5rynwsgFc2NInZ/lXRS6+OwvjAVm1+1+WMqqZjdzIkLSqHgDZrKnh89z1PsQe0CY6DijOd49FQG+tr55XMBPQnAP7uCduLPMFPmWM+DomE0NaVqmOYJo/Bn42d1g4ajO6Tw50g5iD2W9XF2+WKbxRx49Hmc09ed0fqzff92ypoGdaLc85tHsunOyI7nPhThmvPu5zvWbHx/+OyKbNvbjXxt+zIYmPaK1s4X6tD/oNPDZzrSFGtLwAAHgpEhXOgGHhXJw7A4XdzMk4n/rVn7HLlKFT0HMWCQrq2CpRt7ZbgciBilKFrjNJqqFgScrYgZUEflQBqCXilb6eDnvv2Zsr+vg+cLZXtjtrRG3IkVDXMbFyUxGcJKMxEuIux6RLkm/HlrHea9G3Skr8uw77Wd7a53uikhXxCBFGht2aZtyQ2v44gADSMsQKQQboba4WksFBiUWPC1M8eMOHNE5PnSCdPkeeB9XVU8bx7F2ANWu59324PjjL/MLfWziX4Eye7OrVvYS6cSmA8Gd74uA3csHh3KBCEBN0KDgMidRHgyGshGA1ULFAZXb8hYZoww2PbJI9GLI8gYIoeq/duo2ToQPJ9vG9a5d53YeeEjoGckP00hEKudmel405VUz+IRrLZmsgDTh+KpRgBlSehwoIFvjtCTYkyJlJCtegbTcfjE1mu6OaIti99y7nCVdxylHN2Re7arEDxX1jg+p353aNBwyv0U8O0B5d7dyACtFcIMtAYBYZoPiPNn6E/m6FGbeuSSQpugRgS6hqzjBk0iCDegKlSL8aDgwVipJjP4utdae27mQI4L47k7NY77MOw6gY6kljfJHBw4DHDS6epA6xUjPxCbhTL601ik4Y56jagO9Nce7atDb727+/4tRfoYDQ0AVOw+6HdtfgNLL9LJlWLLs1MQ3Iu+6AXNI6eTiYoD2Bka+Qivi9kCFYjJZJFm+27kD9PhE3AnMuQ9EHcAgE3dwX+TO0hEjlajJ53zC47jcqo78hXUjeqwMybYRppHXnb7rJmfUvLW7OhdkSqKe79VoaskjTdkB5fVPbdqaYxWK5bljOdnk8cMLZABTD0/Pan5glDIcdafpuKIghW1rhA2pyszfo6OV3ZuVm9XQTaOs89N+M0ToT03c/DkkFU7D7Wua455zJPuu2xzzyaU9bCllABK5Bh7K3ivqCX4zq0z7bAmu2Oh2EbQWi2Wd7zcGhqVnJ26urNqvjjsqzIgnwB2t9TWcMyc5vbcx4+fPLLc6ugIfA3n0wnzPLtDnvEla11tX3tqKwovR7aUihhQvwAAUi/oesMZcgJIj7bvVYGyOl/Rn0sSFg4dw+cgQ+lKgRDINYi1Jw6knc43qRhNUdcVxtrE9wVA/fEjI1itv5dr9FrRdzwDmB5Z4QnZVLECYDecK6KPgyGcHhy70H5Gs1eMfGQTYiqZ3tefsYQRfRxUkOLY+1H8egLD4eMHHScx4fDbb8afOJSzuDPF+rvlKp9++xXyx3eUX39xaG5C/f0bwkT32lXzUfv83PznfwIAnv7bnh8N5m2cnJ8oEb0OWIQnhnr3fYpbxfDbCJ/8KNz/fLPZdpRP+j4HgD8xxDdqubab6afa+WkjelbuzpDBEAU99S7RzoBO4uedrvcv9S9v9CfPkAiEfT+7fi3QohTYyRQvtQfA06FFpLWD0hsfMdwXm+DNoY+iwOyBQk3d6UwGh2r4vhOxRMAhh3sKqOxGyPJidpe1VqytohSDeQ99u7q8U5wPkUABdCfn5kjBMUhm4+vPfneEU+utWMBnheITgCcIbmDykQCZsLgjw1id0hqErnM6wE7uHkryYEHP99+/8N4/UfYnDPBTNdxhvbyv56SW0lHxcwgbUfVYe+c4/Tsa//7fMIN/X/lfAeH+d2/Ln6ltfPaJFB8Vmb/3/PUPTHz9WSg23qfBBDATKp6uvkMAZgDTxzssP0aYpPf0c8hFhu2xCA90VcqIjnwohCMYkTADo6B5XeIRlNNUIM2IY5MGIsW6LiaU0RFLreBpAghoaoqZtgqWdcHp9Izz6QbHw4zb6aMpc6R5fgp4lJAbHkrBPB0wlYIyF7RmlrsqCq6mKGjS0KqAiwnzzIzCE6AWWt/OFThERPmV9abw2Lc5Yx4UIurevC4wFjbPRhCgAfNMBm3CQiC5RbsTlB83kARFtzbag4DpBi2MvsM672mQDj8/S59eKx5j0P9WBdMHiD5hoesn4U4/gKng5pdfHf4KqJ6Du7bV9umnz2j3gnU5YyoznvAdwGuZxaM/O5VFQvKqC/yuMJVRoato9wrByVIKwIz3LXOeX465iWBSh+SNtgDQHQWmFAihpDMBsj1bm/MdY31yBwtvQxFQ8w3LyaLMwYzpUPD89ITbuw/ZD54Y59MJ69JwOPp1Qf27tpoSWFwhYYpgcxSYWSFswrKs9r0pBBjlaIq0dmKDsHpjrl8rzrf5emyvXI2EfFGsu4OiVbdKJPTHmUJBA38mFEQGBUSe69wJRyqqevRgh+Mdo+KynbEfr5Q03O4+NGMkJeQpsyk5mIsZ4xSgiDQgY/TMm3LCfDhgKhN0WdDm/YRiMCrFODzvYBrRjQ4bnFFXsu1ORJdOU0ligx7if/pnaURqPSoGhCahAOn5OMd5NkYabvwizy9IUCaIMkrxXo13CjPm+WBt1AqIRZGWUlF4QuPVPEQZIIfLjTaN5u79+/+NpWu4Xt9EyW7EGQhmXtzDffMQ9tTHINHDmOXjLR41BrbwElfWRZSPRdzF3PCQ7oDcIFjcUNSjMbvxURHRRjbMrsQNx4dG4m6plJojGfZOKA+7QnQ7H6mLuz7kGDhGspHC10gnKKKEnNYPdWUUN2BjEfa2FcqKiSY0FUxactyR73WsQ0jeZRC9NoCLuzfWCYMRcb9v9gIVYaMBivOru0kNI8ZIR69T1N4OoXtVX+zejQbW+yqDEBxzdCkZ7msaaO7L3IjNifMTjG5EB9ygM9Jsdt7XlObi14I5kilIzFgYxzLpXNBpp9VmQLD8y017dJhdJd1ZShUOXR4ZGw2O1cbU0BrFSwB6VO0LM/unyp+TWmyuNc+BOw6qugMnDOFCI6Le3okVivx8CUcLm78eMaCO3rQO9fe2AmbbP7mgDzaP6mvu+cqhMEtMlysEmg5cFEa54DKSXvX9Q6RgtWiuQJfqpLrzbyLmqBX3SnEoYNsbUxpoVC23rRnHrb3IB81udEUhwOHsr63BiysU9zZeOx0/s/o+O8QW/cgNaHDDjEBJcPvhgxvFDT5XhBNGVtiglwuXzAccOdChwYtRKtT2Cj6RAY4/4Ty8Z3wDOopFop99BY+2njzPGJ2Z+IYBd/AstwQ9B0y002Uh2yYt5q2fPR1b96MpWMDaoe7L0SxXfDhgZoaclhdneC9Tx2cvrgp1/jwc2LASUIxf73nQ6QLSslc+pFbZ9SQgfcPRp4khb9gjHWWJ2J3flCHF34koVRaoMMrEKIcpjTRx+iNPtpH9bkzfDHOTBddprSfzTseTvF/CaXDgHmMS9/xTsPka5+1yKrZzP/7VH7YUcabkDNQQnjrP81IxerRN7bL/fm9cToej8bkc3uCsjrhB4l13utzLP13U6bwMWf+pEBzayixOAodV1TQKhiK9v+hGdCKXYfd85tD2bhzpHCeAsm75cFWHnrYz2NEQ+wR03lQAN5h3PnNon7oRXNWh8ZmhGOiqGqJfiReD6Us+qTty5hnk7ITRLBidquuKpUxgOuFwOGI6n1AclQlkedYLF+isjkjSwG6I1daw1orz6YTzajDdabwkApWewitRbipAUhBOPqoKOnukNQHCq/NW3HV9Pr64t8zRYFs25yn5ju33mvl5w4VDc09CFfX0hOn2Lvs1uJW+SP9sFx06vfH/ZR1nAR9tT8zzEZFOiNP40bd9mcwxq1UztR6P25R3UY7HmzSiT1MXmud5BhVOtIB1XXBeVnA48kWaHijQhnMb4/HjEmCROn4JAHTusO7S4cr3d03MWShDXiIzed+ToaGMcg6c72oSfMuW309nYv0I0h//Ngn4RN1QquiRiSPljc9HN6tr/QvaGM+lG5l2oDLF+6LQgW5E39/Lo9QxkNT8rn79A/O/fs3PRr5GVVC//oHp119ypYkJ5bdfO2lVYP7Xb9Dfv8buuqCfYdgmAAVfct3jDB1++w33376+Pcg3Cnl9Mvw7jvWKZHallpe50GtPjuWBzHj+nrf/XXv231XinrdNTRip5ojIEo6rLAyS983ze3sQeorkOULm+VO1bal/6FiTDL1Q6eQpiarnMh+jta1C3TgNEIX+/RV5WYHqqXIPg94q+rdJLUI9eEL3lVz9PYbT+eZ7H9wJFoSo8OARf24sy9+5hH9zef9J/qut/Lnyt/dtQ+D/PaP/d5d/2IBu0XXBSEdJBpDIFShA182/vkFeoidJeK688wGERxeebn75BefvP9y7VjF9+gy9v3fBQ0EQgBSnr3/4CMJLzzbI8uM+o7gOHz8ismIsT+YdOINwenjESc24dOFNHwxRyCDe57UFC+0GFfG4TJf32SFTLQe45Z0yr59ROCaD+OXJmE/PdTuBcHt3xHQ74/n5GXCGvYqgiBm0pbEZU8ii7aQ2tJlxOj2DmXBzczQD1DRjKgXzYcY0TZnLQrSlUg5sOR3ZL7DpYJBRqzTAFQ80RUSmoIBR5oL13DBPE57rinq2SBkhtTypzJC1w3OFgFjXhjI51KAilT5mDBNImXsUjEi2P98cQdNksE0NKB8K2qO6EOZ76QOBHpxKEJLhJNwBeMIMZAQ4lMz8rsARd/jlk+WM//2Pb7m3+jqNm7h/vr9Es9D2e9FHey4jhkNwBG4UqHjE/e8G1z59+ox231DAloePSipV+SPh6Y9vmOkzzuEqCuAW5ll7YUwnjz9R9ciKGwCmlC2fTSm0/lgheAbRbSr7RZ9TuM1Iw/FIqIJwM8CAM9qTQL90pUecP4Y9CzVYdov0tAu+3BWcn56guMOUkO0mpNaTQCDutQ9IUxTGRSFdcT6ZB998KDgct/DyRITpMGM5W84whQmRPBUcyiGFrfNyRlsEspjP6XRrCmMCg24V63OwHB4ajtmVLTbPEQkc6SQsfyKBj54r3eEKg76U44ziIjYIaIt59PNcPFjAIJmDSqobW7sAnqtha6rInJtGn7w+FI8aN8XuWluqB0QoPfx6bbG/O30mgtPQnSA77AdT4omtLzsUMBMKFU8RMTlEu9chisxuzgTmKSPVwQUC86qU1rAsqyFwOAQ8mFACClHJYcg8+odMuZMGw93+DcNEKvhyhrd/p0+7diE9DkUYUuIPVfX1Vc/V2SCtpjOUCEBNUDKyk/KOMsODoLWgV14f1J2c5lSitDW8SC2qo1WDZsagsLTvxaGkIrpZe3cxKGqHtnywOa63DHpXy9AHJrJo8qhlNCyGAmBkDjxnHuW+U4cwJF+NIL8NQAFUEu7Wzobtp7gPopYSCCkbXiUch0q/e9Ig3tNXhFDX19WMibYfev5b9vQyrVlaCGmAins367Av1gpzvHOjmxsyR41G6AVDiRajJ/Q1A9AjSXxEKu7h70ZcjnXmrYE+ltXyjxdTRHJfjO4QYHU1d+hS/zu9xskMBwz2HOo9p1hMdfCNsTUu+9HviqSjrjWK9iJaaVw7dqevnr7C+YtB4RyOLRdFHSo0FNQ+RnEF+Hi/d1oQ8z6qnjpdiU9ScT60e91Dvs/hnnXYRqhuDarhUNAGY7lCPe1NNWFc1e/MoLVDJBUZikUgBkTXFFsIPc45DshZa7u4gXQMWRQZeKXsduz5lqkmck3Mxyn39HguuxNXkCLaOfYN65PvjIacN8D+aFwb32hCfv90p4F+PzZQ3BUDPUD8RC8i6h89et+gfBuYbf8a7TCI29Zqjruv77Du6PX1/SN9TlpDxlKVrmQBIY3yA6VDCC8xh6LmcHFhpFEgIsRHw1f0yWhfy8+kKaDVDe3NefbI3yyZHzqgefc8y/4uHu+aQPVKBXmuAwa6EW8NqtlhD6znk8l9x2M3xDuMZGsrmArmwxGTo97M82TRq/A7VBRlnsGquY+1NQhTGmSJxCCLPYKwOMpJ4eLODHGfyIY+RemqLPtNzkufBUfcEYVDJrqikRkFDPowmSxFDD64ASj2at5xABWFPD3bXMOQfpSWPVOPinMi8jQRRFoZAJhub7AuS8+xOBhIxV3cc44HePU4neO9QjCjCEjzrAS9DvjhHp1tdFlag642VzT5CSU3vKmhozU1lyIVMZouDVCnKTnvA9FVQ10xPjIcZXSTHkObOUsaLVIzZAE9J7pNMKQ4LQkuOciEeTfm2QjKabSFNs47iDtMDGVB8mkeoHfHexppyE7aN15PcV87vdZorId75xnb3DGxJRCIQfHwSPcl294bsGKKRyc9OPpE8g/xmI+L7BHnG6IedwJ2J0eVlghOBX6+GIl8whQ6BUbQB3b5YKRnErIMOR9e2HQWFLRSAFYPdXQnuuDPxGgbgzK6HFAQFzCl21LeD0mb40lV+K5DyBOxjtPkjhqtYq2ac5PIBG3kbL0ZUcCyD2f0vKx250x6wDwVCMV9bmrwnqZDAMxgbair0TN2Y3/cY9KaRaKfz+YwJYC2hmmahkAIl3/LBItR84UNHkqRSAmW4sjPp98BcWqUGoRa5/8AEM7G47LL4u6TElFURm8bko0ONIsd72f1yfb4a3fYoNIdRYOH3cz1ePbQf+9reskdqirKDQzt5Cl6YCsvjwq6sZGrIoNGAEC583yIsxn1lhEGGVfLcacDkdZ83o1XbK1hWVerxQfXumCQn1kbfR/qvsldnp1x7HEXGZ9Jnr4x1obdeV/NcO/ySt4aRFAuPu+uV1G7Z1sgYmqktLjkr9nbm74w6vdPgN7nOu25yLEkHzI8F5/rOAlXysn346M/Eob0nlvc18LbDjV7QY8qT1Lp7cePAAnnX3b1MYA7BZ6uiRlXyhMZfPgT9fqjfNDe325gHs5x9M3vsfb1O4QIyx/ft2udOt14jzD/61fo719TXv0PPnHmAAAgAElEQVToe+nR+8E+V+G6tFaL8F1VUX///c3c3O8pCuD2P/8TqorH//5vANejwQMyXqGYnYOrtK/p7bb25bNaNOnfMJS/sex66hN9bb5/qt9XJiBpFsGQh8idTSm4ps4j7gszb86fiQK7Z/dtDjTb+DFz+lDYvRm5xI0Gvyw7jo7P+8byXGvcp/b56kgZMyzIMVFEBxpqxm248+2oi0vMJ0ANJU5d/ltaHWRUZ/Maua2APRhMMJUJz8sCppLoNapqKMbRuiLbLeyCuSvoJjY+96AKVkqnnRs2HkI9PNr0Ay4zNdOdB+0QAmYxnug5fEnfOjo5Obr5828r++3+0mMv0Pl3Vut10JVv36rXVtZsCcB3escrlw13PZgqRrbftrt6xF04RQznKmSXzmEmL3vZTA+4u5AB/qHyzxnQNaAVdWdU6YIHQaEOc8XUmS97bHjnFUbjPWVcrtP3H36pKhoU9ccP3GJkhsQVuYNnXxivg4CSYqYPqA8PmD5+yg2jTliOd4Snd2CzBMHqzM6WiVaY3AXEXBoEJrMADgVo09IjEIOo393dgYlwXs4QF3RabSkgEJDef601rEQovJoxySQw1LoagyyC443lWZqnGdM8m6BZLLoThSBVISSYppKwhAyy3BdinsQCtYgadYN4tZxvFYT29AwlM1DcHI/4vq5YlwVULEcT3OO7eR5eVaAwY9GzCaviAuw8I+BOVI3Zt4ctmgfuRWvRUey5WsmVUzdQhxAK5lzwbMycLxJ/IrQHRcZG9fsUqooTAMIjCj5BWsNH/YAFjwPQYWce+y4YNgI6sdk8Nwpq6Mog2xswJY1foABwJsURDPnx3V+9A9EHNGmWx/2+C19n/fGqB6sdS3LvMBdQXdjYRAcAUDw7k34CyHJaEd32aPNUem2nQLULqVvT6vbyYWZv29dAkQocBeFwd4eXi3nV2aXMqGtND8X77z8AAF8+3+LmMGGpmvvYctENFwBMqdJIIWgWbSmWWywMSIULphtFPSuoAPUsmI8FxGqwOMGEIGhhv1gSPpJ3yh8AWGHQnOoiKV3ul7i0QOiRhNvglc0CJGuhTncYppSIteB+nsIgYUpsODQokkbHNI2MK+3aMi/wLvRunnGmrwkwOSNVuPTcoFxwc7zBza05UWT+OoSSlzDxBPDBIrl4AojQak3YuuW8QCbFYZ5xOBwwFwYmhyUaaEcw6GH0yeimjXi6GdnAqF2qXAgeidFkUAAP+54i8sQj0ptmuouExq1q0eXs8MoToRRTZhrUYEOtAqnN29Q00kyl4HAMI69gZQLQUB1a0ZQhNZVjoYBttTlqSRjQLg3l42emYw3lptq0/AXWNU/ejnZcZ8MGxW4w9f45+zxYNd0HV6T6IVAozNGkoECYjIFSOHQVMkebDsoeuy5LKoDDOD4a73qkur3XoZgllYuHw4xpMoQAkYbTeYE0QeEZhNlQK1TtbPqaCHo0ehOjvH2qrT1mMv29p1yxdd2ey+bnKL5rTaBDygJKS2WHm4wZUGeqUwlu3jcgUKJERAmUCFOa9D1BIWhLT88ylR1tABDwvPsIEYWCJXXUQCmWZoYIFR4V6jkzDXraJoCpAAUoytkWuUenpnMDfN9c3kmS5zOcGMTPjAwRhIOU+67SIdL+jLwzdLLnOtvxz+P5lmbRN+LKRKhs1oaZ3IA3CE1gSOtOLUQRRWiK0kIEnhhlmsyZ0teDSkDA2pyImGkn87Vq0LoBWtN5VEnjaeSHNWNZKc5n+mc67P8LI/pGuaHZBpyPyVzfand8OnlcXSWn3xT1Wt8mh+Iuk485jFJxp0qf3zTWxDzutopBEQLMiloBopaR3LX2H6uLEc41Y8706GvQb+KI8geUGIKWRrYCdke/mIcOBW8fDU5bbNGJmvdT9Bn5zLjfiBQgT40lDYCgVkXALdpd1OXDaHvv7LAZ19Xnov3Le3ofga5XDpjuftvfM12p22nCBHPoO8wHTJM5QU1TST49IjB5sjWK0Lu11uDmTa6Dgoudm+g+FwYrOx90wOl08vMQNDsXedtPANPt0edseIzMobR8KChlBhMwsed8LiXPQExBTKvCeVMp4HIDqZLKSqYDxN2J48zaLXFAoxXL6dmj6ycIEW4+3OHu7g7n03lHy70lr1f9TBZnwmJv9b1mfS2xv8kUjAbZ7or3YWpUnL9yWsIT2b3qJCFwoWJuQykpTTbR/mYg0+6hBjgPOoyDhv3GjhwUvHk8Swyi5jSWN8rfjpbTeU9VWCSVmtO68Vs6zFvco+5g0ezfUO4ye0ot6nfuxjANo6m54uOeYuSdOOyIzflMXYgGL9vrfkmZfa10I9P2s91TGMwy2YP4IxS69q45KJrTwmQfc4E0h+cK6HenxcV/UiJlMu8udkefoU1A/VwQUCYAzdHJ/HwoMNEELZ6mKdqMtQuFtVBC+zMFj2U8a6R70JzlMBgORnCXqUJeijv+dA7IeHKZXz1ird99wMDf0Pi5fWDQ3ABhNucbP5fGU5tbe1H1+4ky/QAZR+2Q2eYQWVvDaTkb31ob1PVL8zzb/e4pSTKfeW2Z2oDgepyC9NsIJMJwYiQyGdvutC3ItrMAKMQ5l7bNx7tfPTKeUWv1fXNpECH0dIOxGQSaKQOjT4EgaSmfau6beno2XSQRbu8+AgBOTw9Z/4jEJKpuRDY9mB6H/W4CFhSOSEJAk+J7x88o+p4NUgEYnUi5M8/K9m67GLejeNS64nQ+dzQOm7z+M7Slw9fRrZE7GVYH25Pl1QXt98946CMBYHciZiKwJ9Esd8UQDBRoTw8Q7vzc3AQnd6gPvr33dyQgTuWoG3STxuWY+u/dCWg3Z7jCt/iDbxkKKPSPXs/IWTnrmfWzahqnKMYQl+BQXmpzH0n9Wnke1iPaG2t9JDPGb6+QrjOsvzcIvve9WDrGSo6T9vJfb8i1EbYfnNv4uGlPofhu4/n6BU3/gAL4EfX0yXjniC9L6GfiXBW8DKk+xutccqY/V7bc9f/3StKwIOiEdNJmLl2H5c+N9A1ABt+o3x12RvbO1dfbjbO2N1CbnuftOkaeOss7F1NUUFD6wU+GFA7ga3eSfU1ABN0AhsbrcyEavK1uUlKYzSNSe0mePSZBcT6Ey2QAYGTw7sYDmuNOphIONA8M98lwEaT8pUjnn6RpsWyuawo3ArsDDWE453fDi26mOOvwX648dVl+mhL8BdrxU83kf8f2rgivL7x9ebO+r1gL/Y7K+Yw7RpH3Yba26xZ72oHR+fMlUeBShv9r5a8a4f/5HOjv7v+eiaKLbwkuWASjd7U5u0ifiHA3shlkJ7WpYv78CfM84fHrH1ACZu05Z8pnRv0BPAfDBMAgXbdwdRVPdrgfHjZR5hUAPSmOZGzcU+/BC2Vg0rz/9nxsWGe2mnhOLSMqFW0QqtUjCszjV0VR19WEHLKLoraKwzQ7gTQF58QFh3lCq+7FKg1aPGrC55gLQ1rD048nsDB+3NwDTLhtdwAXHA5AgeVhZppsrkTAUwEKY55nrK7APMwHQ0CrAq4VQoraFNJWlGmGwXgxqgimeUKVmhdVWxe0Jgmdll4wRBat6cyzSrH8RwHUrw0Gac3ummle4gYBb7maqogFAt8Gswys31f32u/kRwGsj4+5crxj9Mcd/Hz/AzefPuP4ywH6h+KMx+xvvmMS/kZZsDFKh2w0EC0C4RGC3z7/gvXHDywcF7Y9YjAohDulVAY9MXCnTwAIz9+72qHgIxrM23UcRzKwrgRVNQB0xZa5Lp8Y9f4BRB8wfeFYEJ8bK9OnGXIv0BdOgMbzzhCoG/UPnzijhlrtUUpEjHInkGdgfRRMH2znF4/6WWvsexPW17pgeX7GYAUFYD77iHEOY358XjzyMaJdTSAdmTEAmRtNpaFB0BagkjmmTJNFSU864wkni3b3NQ5F/3Rb0M4Gtw3Eftae606ddFPra09kCoEFHgnuk0gCpeYOKLNRfbVRKm8vrs3cj3+QnY1+0cV827/zNHXFmvYzMXmEVRPJKNauvL5+URrjZAb4VNbuLjoK6I1gwtyztLjBwRAVei5cRT8/mzGwzUOezjDUnD1i4TCcYeejR6YsZ2KU5IJxHrUAwdET97mPcYxjH3NMAlZHjrUboiPvnngUaAjbhhBiyj2OvIRB78gQGcCM7l2iiRZQ2JSIwsUhY4t7lHrU80VGt926jUxUrusbTNx+/d8tOdLwX7zMcV28Q/1Xh+DHDtrYb0r/K1RQQdlkqKfH83U9RCjv+3NEsQbdW753e0vvwwA4GtDjfYoIPb/zY+8Z8oBAlROZIMZIMAW8RRFGjsshEgZdkFTfsvauO5hJPOtIMmK/2/4Lj27bX7pbgw2nphgqH7+9skQXsMvbV9KxQfVC2NwaDHYM/W5vqfYoevGI3epKM1VXeruzhNVBADPYz96bvPdOOOtKtWEPqHduZxntTk/bwfc24/s3OjEswoVQOfIPOwn1wgFhUAYkv+P0Q5SABrDa3aQiQ3ojTQEpDMGhXCeHYZ+myZwZEq61d77f65TtjZ8PEzYoQS7nhDIq8uX5IlwKd9sJG5YSY3vX6hojHNwoLWbotnx4foYjzYjzMpFSxPJdG689GtAFCqymKKmtujGhG8XXdU049+ATRweVvDQVwxph4GFMDiKE0003tCfijUpGX1LwJWSOSZGz3M5HgerqBrhAcdjSwFhXo0umDlG/K9PQOtC0cVzjWu/XIY5VrJlu1rCf3ZiaJBNxHmiLpNGJD22eh7PhiX1CZtzOqI3I80qGjhMoDf385yTa+lYzrk2lDO1b5HNExYQTXRhuyP/V9F4ZnNOSrGhGcm3OCNOGN4p55BuPzVI3EJdAgjNA0jwmCmS0e5No0u8kje0EPjAmukF1uN/wkQERZr6B0tppQymo5xVamt93fX5yDyX/iYvv7HfKOdjcsaj+5pCjxx2/VAii5ngGKKjYPvGA8Nw3rVl6sVDNIwx5+/1I8HMU+2+QESj2UDh2dqVmOPIJCCLmQFHc2aKJgEncWS6a6/sptoxIc5QqxZj+rSsK+71oxmzJ9Y9HxeexHx2K/1+ct/G+2nNiyR8jrmFKutJEzJibThn7e1X9M0KkMMp6x3uKXroLdwR9uGaN3ne51OgxudMt0J2wwphl74eTQ+YbVbH0d8kX2O8Kd/bLBimDA0iMhoZpRYPv8fqV4uwZ31V4CiF4uMttXvraj1G1l2sUczY6D/X1phxfvxZ0s2+6AXVrvFV41Jg0qMulYayMncFMwFRADSAOCHZPTaRhfHSS5ahajStEJjNSrxYRrtocgl3cMcx4Mln9nWbnt6kiUxbB+ivNEF4knEfSucLngmCR/U6vVVquXSA/BT/uU5Iy2DjT5gC1O2cYzpKfcTMuXG5RhF4FFuufSB9A/DW84PQaAOOISLvRHcG43zFBH8mcgo/H23xftG3WN8Y30lPAeTu8XFLeVsWyLI7KkTPjNDnODbpMMBzKPbeyObQvFPX+hq41jMQRyLKI4PPHz3h+uAdNhHJT7E523qt8/oL6ULHiCUrA2SvsMZ4xJxbBvqdxAst/HrnF2ziJQznHRh++6+SVrtPWd8i2jy88ElLorcse97xFO+iNbLu7R7P+5O+z9qUDzACugIfFXC9PziO+VMadrFCs374hTN8WDd/vDepd3a2Bo3s4fRMRML6A8UePyh/mV2AQ5180AuG+52dv7bWfKafff89UA4CF6DzStu+2dvbJF41j0e+1t8q17l4z0L92O/7Nw7a6qa/Zph+b/b0//+8Y8KayK+0O7Yy1jfyhP7DRE7x0X/aX2Z20Xpmr5H+Nd+BAOsRWD79/f3ROsu/975FnHN+j7fddJwIA0nUWMIc0gJyvtc8MKdF0nKyDQ757yIypr9TbCZTJcCYLfrEQWwANYA7heX8p5nlGrRWBTsVEJk8EnfHNx268Pzut+OAy6LN6dLSfmUkUpA0TW6APWvWId3teaC/jv29Xb67fd7/182XkPV975rXvr3+37/FIJd83mvc6Rr3W6kaQzvYpB6X4+SP+v7n88wb0v7v8xZ3/RIo7N0QHCZo+f4T8sJDx8w/ZmTyul8h7kn3qcg0AvKuOfXnp8IUnzqUBgzbPhIGloWFtzZU0Bgc2TQWn0wnHeUYo/koxRdDhaJ81VUwKizCHKXvCaH1aziinCcfnZ9wcD5inGWiCZamYVBEY/OqCiwazw4TpMKEQ4zDPJsChYllMJIBWJ44maC11McFJgYknVF0tpxwEKmTCuDRn9AlEBRBNg6iIw6WJRXKQG8yhHlEEU+QpIxV7FpmnTvzdsACLolZ0xg8wBwmPS4YCDuO+XbOT/033PyD4hNtfb/Dw7RHvKaN3+WhE33/PpaBAcSOEU0YKXh4OAXB0BVUgKhQYoyd4uEqs1VYGBx/b+PnmuRQQngB8vs6gvD3ki33Pd5TpAFpAzFAX+Eoh4M7+vr27g8GbmiIjI84C0ksV841BkK3L2pUj2F0AYz/ckGW5xA7Zz1bbcG+ZJ7xB7ZhwaukVgCLGVJmhk6ANfR8tCp0Jh4mAoynndOnezyEW29L3yyqVPDFnblhnCtcZH4NzI+TvjbfZW6Tz4sm8DUd0i4jm630idIjU6Pu24u0HPLak+6+30ge5QBqG8ddu56Br1u1dJXt5krdrvheEbdjeFzIP8P+HvDddjltX1kS/BMgqSZbHfbp/9Ps/270RJ872IMtSFQkg+0cOSLBYsry21x5WwyFLxSJBDImchyH7pHHSl8i6zwOXjDIRJE283pV+kkssCpYgQspijMopj3vr8pg6GmTBi4n63okyQUpLTLVIVOg0eT35nJPWF0ZX0Pt6jFEKe8pMMW4CXRn3Z7Kq27YVu8d17c5KI2XuPuxR1KTN8xJ1EGs/mbI3maBDUJyR5EfPQseJrBHalr2hG8bEccxGo0reZspBOS3N0nkp7PTMEzJOiZYiAMXTrrOWbTCcAh5n6uMCe2QGq2LSMjuAMhKpA5RH4WzW1q5GIdB5lE3j10GEwZJF1JhhCdq3GdKvPh9gtbbqxvNuQIesTRqjrcEMKN/k1zlACe3B1VZpIO0C+n96HAjm6PlzMWvT7861YUzxHj2b0ZgynHWfrRhUUwVaai6BNe61tA0HSbmeLDV+k0SxpqyRfNMk8GnngsxwClw4FrgSRH5idKSglm54/Ue9i/ea8119MV6JwtjPrtEpUue1RKGkkZZpsExNWSPzc1KeQT33a21YFymtYem/AamBXjQdpeF1iTyXMby0JFGBblEIfp1sDkmRS8eFth8593kQQ6N4k6SVV7ojY7K08/AznFJTXgl+tvzvDQ8wGs7ogjbvzenn3xtOHJ8x3p6dnFP4BjvHcMsnqBKtwXlOMGvmEI1y5LgOVu4ggahnQjCjYx7GxkpLhR5wlXO3lIby3FAqo1Yg30TecLMeW+bajAPm6KfgKsaxJJGZLPvpOFQj/JtmKWBm5COhPFlqyN4y3ejrGA1Ldx5JAuMp58HRRofke+WOY4HX23P/vHAA0nNq/JLhP9vvhqa8FqNV+TFe1haCwailgbmC0uRXzfhkaZG3OJO3axzHSeFcpP63zZsowyqf0UygqllMYE5KZOha+ACIjC0x900zQImBPiqLbVwGQwDplnf+yPfOeQ/j7YCUJ3AtAZpoy5oPzflD6yHwtaUUTJMYiKNzDbdLHmGLfweF88VR34P1jrA3J1V5U3gte7+XIWNj2qwOPJOS8GpqDvdMM+xynS0+Ebn2uBuzbWX7Ob1wCFKlgybC8dIHdl7J+D3afx7hHhkrILoVwDJ0mP6DlFY15YG49XPiuNdkVlaudBKa0GpDS1X6CnjbHbn0nOQpAZg02l6m0kJ2P+h61iYlBEupSKl6FpxWJTuhrbXJFLU11FJ6YAOJ6cIi/ywVd9ueTR2EjdHGQjk57yLzT0iZfXyRR+rn6roq2vQGBrcppws4BDrGAV6v2KYADy5ejYwdOuwTzueT1jbX0n0kuEPKo2jK1UBrmRlrWb10EplMQZCAHHX+A+RzDRk5Bh6anGW/OLKv4mgjzafxusGOzJ88RTcYePj+gImA0lbU0xlECYe3GjTUGG4G3mGLr3IRCnevYQOvGcK3O/RntOedtf4jbUvPf9Z+9Z0VhnU3+O9K3+vnL0ggTJ8+Oi0FJNsV/Q2gv38A8LVni9X2SBKNbg4Sj79pfWKzdxgMEiSl+kutn9A/3rYR7i/1x6+451/RBD/8CqRdPj983uUZEJk1/bX5vdPPa+RKiYam31IK4NfahUAiTWmBR9Zb5jDmwVYldp59imN62egMyiwPO64ntaeEEzxPk5TyJHOc7N8S+sELHJd/jr8xfO7MhWkj/gRx/z+obSnVC0LHlfYz3PS72hUI/Y9sfzkDes5JPW6uEYUOWHEjo0LGkDcRML17h/O3b7h9R1ge5KB++D//C//z//+PMmZdGAqq6OFNDcDx/i2Wx0eAhEk4YR+IzLPXvHc7oonjjwhMRbkkSEkMxEkiEVX4Ea/qKlGxLNG4ayuoTRBYaw1PT0/KSE4+r7KecZzvYf7+XCtqFqV703qhjYFSC9YqtZrnxxk30w2Ox1uUVpFQUSAp8WotOC9nLOcF5+cT6rKiFknHmefsqa4qN3BiQJX7tTW0BUiZAG5ewyfPGXWVaABU8YB6fn4GiJGnGQygWR1NrRcHbuAmyplSGfOcPeK+WroqYq3F1aT2b6uu0OLGqD8qGp4HxlkYNE3DHPZrgnhQLWwwJ59nJQAP+I72peINCD8iJQmbHgVXgbNLI7rDiX7//PkzCMBTMsHRmBLGCYwbNbR45DMRThrdfcPiaHGNmTsDOOrwDvp5S/wSbsGPQH533xVCKfYpMLV8f7yYshH0cRnOuq43/ZwQNC0x0B6113eyV2LUYZxPJ6l3TQm1dcVy05TTd3dv8PT0pONLyFOvSSm/LTWzKbVEAM6ahjMOMk/Z04C7UooIpHV7bdyWhq/X9WuqfGBQVuUzazkDaqg3hHZW5RypIkQVF21QwBjeYN8QRvBytxq+zKAp+dkiIk27p1HbafT03TbR5ciZGfCpKp5YBXlvapyVtD9hwcLzUQnK6CkKTRjuWUP7urohQv8laIomsnUnxxWizNEoA2PyXIIPlMAmzgDmzjBS+O23DkKKbY4Z1nwDfNTyzPak2PddZSJ8KA3Pbf/OKcMUXaxOPlLrTVIhNmZQa6iaQhe2JklrlyJGEEq2DNJa741IjOh5kt/zJMbz0hU/w84rDBKwI1zEU0y2UronpjALQsuwNGGAF4joV9gwFWHd8IZu7KWw7zoGRp/n+O4Ib0A/JaJcNltfV6o1MIkjQ0z7afWfa60X61WrpDtubCm+OywTdU9dfy8pqtF7W6NBQAEDWqEcIMY8zZ69IJmyKSzudkVNMc1hT3rdeHu59YPOE9k+prFXd/YD1BCTBjr2UmOzYtnUNEp/O3CLAmvcPP0YIQ0QQ65oEx6paOr20YAO5AxUdBwjz7VLWN0IjeCeOt+Uz1HRyuG37dPwx2YtgipeuAjuBo3Njb1tGdF4z8hG6h6P2MayGbAQm6CUhRuduDEaMVJLYkQXJOBrTNyjzbOW9JlnKZ8BghvNnOdOGNZwO+hugG0D3rnGrEg0tOGolw3I4SHs3WiG3YAq9l+6c4oktbnsHZGUYDF4IlVqiPE8pLVP3eGLIfxCLVIjtqwr1nXB+bx4umkgROFVqwd/AUjDkOO5tvXaRmN0XjMhIXtaeVtTmYNdt0hZed7SuEvt4OQZK2IqfJENyNOkJiLU7bCDEt/Hu6NgY758xiIcBYZ7P8Mc3ZDZzx9jx3ixt7WIMAucT8+waKebm9seRb1hqrb4iEhoecqaThoJKa2ARvwndzywPRKLWi2rwENZsNRF4OqYxNj6ZJmU9P3KYZfTGfkICCcvE2Uoo6XRIswNtfQzlxOjJqAxuRLO4IlZ6zvqmjZm0BGSBnwF2pkdno3vS8gAViDdIKXmyj2DLZc7w9rvGsuNdwrncQv2DVB+FX18pA4pmommaYQ9c5MazRyjbCVKk2iCJoQPe5dAqQKUJApfz+KWQ5HlD3IE9WtG3905V40/kg48oWWVPXP19NdS477TXgCg1kCTyBKVZBRessboENQxPBoSsVlbcpYCzioz+5GTLG8JYNO1sOOIwTnyktW9yrmx6i5sfUAUajVb/x0/MVtZkFc0hQ2KDDwijkCg08bwsNc973yblBkhMuOh4egaeL+RD4hztTW0c0wEwf9c0RK5YdoySSTqvKuxr9GMD3venTJH3JbInNK6sZ5Io+xVP2SyaeQD20l1Rybo67jbGstLqQgGQj01pLuMUquWI0iaDVBwV18DSaY8T5PwZETgWoXmJQIg8ok5JIgepqJmoXtNDeprsZyQDWBL0a7G9nNDywwkLT0BaJaIomem82UOnAoXko1RsX6SgIzkMC33Ny3zUKvMjamqOGHyDQ1rGR0bdMNG+WJoHP4yfg94fvoRxtlv62dJznUyPprUrTpkfWIOZ9otJuHUM4EoI01ZdCUggQ2t37uuq2S9SWZklwACM6wDwM3hiNoa1rLCovW5beO4O1pwadDwDPc04YQezDEiDB6ckCMvYMbw6Dzoc2MG63NV6en3h294//ETyo8HWQsNnHmpNA9vzrSNQqD3gq1+Ya8v2w66/ENtlys1vlbXLTq4dp4driuRy0rPobor5Yuspng/FVdGTfsft3cHjDasgYR/EFZ0Z7z08QPKl6+63oT88UOnTZYhyPr7lHDgj+AvjIIHzyR7z/tR2r+7fScxaJtO8w1vswWMg/ASMTCj5ssQsbeOvwN+/sy2ex66cKz3qCDoGSivdXb5scPYGP8u+KDTUXmdOet2ui0clz908XrTse+L33KxsvCLGZZhaPz+WnMdx6a/Ld/Lm7+iHCE6/fFt9n1WHfxaTYch36ytihO78kBtY0T3vMyWiIkAACAASURBVCPc8Rwg961aSlLeL85YA1mFsRDsTrYe4Z6EHhdPbS/9Vs3qbPYt2xdbn9oq0pQ1Exo7PTtpcOa1ZX7N2fgzzs+v9LnLG/s3lz1x+H9fQL2GdeXaWxYay1fu+FmLUto+bx/ozFXu/z+z/eUM6JeM5fX2DMYb3fw7Jjwps3n69g23Hz/i+PEDTp8XJLzBPM3gd99wfviBz/+fcHsZ9+LxjTF6mAHcvrlDeXp25o+IcHj7Fsvj918A0isM3GZuF0fEmBsWhGYK9WbMU1DCAGoMY8I0mQcyaRSRKLdKa5KK2YXprGnkVOncKjIyzumM87LgaXnG4WnG8XiDTBn5BpLKuggDXlpBWRdJwe5CrWFcE/CbIlvxWCp1RW4JacrImEA3oizM3CTFXs6YiLC2rjAiiFLG0t4ZAm5a602i72R9amuoYMxZagtyZSyPZ6z1BLQJ870Iz1wqihrPZd0vBQMTFzqhCTulhusF0NpXhEc84R4JdwCezJiw3fOgPNg1om/ua2BMeAPmGEXOTjNPxDiy1TKR+mRHEBat9bYyuxH9wMCyGdIZwA3gWRps7raTjGek+7sw7Zeh3lBwwi2m+4T18Yf3FYkwGKg/GvJbAmm0EwBUzVOgYhSmPGl0unq9GwkaUvbJ33d3d3h4kBrnVl93RB5B/FejeVkrcmakw0HgcMpoRY3kVXM+bkZPmsVAP0kKN4bWGpSzmQhed4YsDRAAOmbUpXVGiqCKtlFh5fBgjiMXjFfPRjD6TZtCbysCdto3GhU70ylCuJ4GRUA2S7tXGLuuWB9X9zqm7nAfxoG+hmaESKn/UFhjps5Em+KqKyxpuzw+aqbRiYAvl7IvzqDceg0TMuQnibMFAj6ki944/FBP87XtTZVDBRVYK6oqbCzKU5RbgJWrcEOICS9JDDxi9BVHEavhvWtgITOeb2bDCBE6V1ZCnaReMmz9cXaLrvwdmhsiutLsQii7MKgRYEpBBxBj+C31egcYM0DIuucAo6OSwulxa25c70oiUwbFPu07M9LCaxXHyE076SmFtIWm5Gce6plvBTPw5fjs/ex3BvwDPZ9C6obMDMMRUp7EBFhf52HNLwVOd9JpAJOskyi+RhpoxnOr5c6uOIp9wZWu3BqKKWtr6WvnZ0LwNKlmz+L5mXReVi9W+65BEc8mdRLGtNnYqlqHr64LgcbkvXQyXjo0P0FSNl5WJpJ53HunHBoyzCwR6EkdExmOFrvxXMtDTNOEw+Hgqb4tvXsfG4O4XaTOBDp8SM3vjZNLHP/FgwDYjO7jXF7XFJB13fvjP+nH8LhGc8mYOx5N8SdbxLmsU9aa07aPhhNKKVhLwbquWJYF53Ovdy1zj9krxgi517TuSGzTI99LuAKqG8IBLf+RxehvqQBTNQfEAsCc2jJy3jOgEwCRBVpVo/W1MRMJrt7wvJtB7+xx/A6BhvVnxdBotFwQ16uWbnMUR3lMehADUfIMJHH8hgUIBErGAyQQmjoeqsFuA/O1McBFshGUglKb4HK2+oKEfGOOQ2boU8SMA+pZRphu+toSdYMTs6YQ1jrc4OTlXmoTBGGyIjNr/Wtb4xB9SIDUt7eInMUNbylJVHtOt0ipeAT6YKCGHz0d5uW5787MnefsCyzXpPxA3CpVFLIkJbMUnc0NcgBB61LrOxKZsVEQvzvWcsDkppQ1eti1p4DTCTOg6r4QAUyQCjvZeY4UNDSNG3KbNLuaOi+pnG60XJxRGB4tzgYnHR6NLjWFE2Z22OpyrckQtgMYsnb1tc3gVvz9mkJnd5+G6C3d1AtSFBl9QMrSBZnMonuNv+pOyOhrbTxCBJrIz2B4hRHw7ozHUfHcHTkokUbJq4OJ7ymDG0nKbwBoXdew7Y+JNKWv8Jmdj9vyOp3PCx8duTi+MLlD+7H3ctjva+WDWg00ArzZCG0Lgw4BSwaYNfpg46vnCrqhbvgG5N2K+xii6E5ao/WQGOUsMOwOWcZP6F6stSCtVuYE6hQmcyxVoucqq/6mNbTFTp30W1kCI9a6wvRKcV/i4ibSeuk624TkGY7Mcd5IRq1VSwixr23f58Fscyk/p+QpfmNr5nzvG73963qLM3Fjh65Xn6c6TCwN0+0MJMbz0xPu7m7BAJblhFYbjre3eHp6BnMd8G5rYkyvWuJA5IxlgM3Tch5wL/OGkyPyrGrb3F5RhjWZ356NBl0zjJsuxXWbgJYdMyecyzViQDPkmDM84fvDN0wYWeZLjmKnbXgMwj2Ax/FaxHmvbHvj+KPtglJGVvvK2C7EXX3QHPa3ddRfzJCw4Y1e2zKA+eMHAIT2pSHhm+ZUYbQvX8fp+Fg6PBiSN31P+sSoX/qQXtvuGfj+68Mf2gNJP0A0nl+RXdD1x+xXft6stzf8h5b7X972eIWLA/yrLcCedJec7xJ+nz1oLzrlvWq8iIEf11/fHch+HQ/8kXaxZIrAppzASoN70EHXWaSAX338Lw1X19Zp4E+mZrIHb/q9fMfP6J68uIJBpQIpgQnIDC+f8Z/e9lHmy0qbfwSyJvQS1b/azx64/b/U/nIG9P/98T3++8tXFOaf0G77Vu7IKuBHZHL+/AXz+/dYvxU8fv6KAuDD3z6AGTh/kRrP54cudImAJ4zGNE2Y3r3Fj28PACecHx7AJDXPxctyC6rGxO8rBkdWPx4yMca0psY5qxfI5PX9hHFGF4iZta6EKkGUVs35gFKL1j4/IBFhWVfMecKqNfjEqC7eS5QIGRmlFtBMYE2BupaC81rwfD5hmidMywwuBQ2MslYszwW1SQ1H0hpyRA2UClAZrUqksCi2JS2lKaSzeimbguB4c4tcK5ayoLaGwzyjoeG8rFhKkTHmhAJNMcq6XiyaulMVAWCaK3LKqEmeKT8KCp+l1mQ7Y/26gvncUwEFBX9TYT2o6FQm7zB4hEWh930/214Q4RENn96/B397kLofLqD2jX/RiG5KOP2+gjANIwqQxJK2ncGa3p1wq55eRwZO1DxCHdC6JDwyOYfQ5y16+ndrDcBkQpA+X74/Xj2Q7M89oz2G8SqBTnQryiI8AwCW73c4vAOmaRK4eG+pys17ThS6LN4Vcq6TRNMSJF17Y0mDWusa1lkVSeo1nTQCASDkKWFZFoAIh/mg6RzPouRZgqBIowLKUgI2Y2TAWNeKhjakC/SlYYArgZPggyllOQuKrsTAoUbRnHq5ApA45Bv8EGkdQ3ZHThM4uLEog1L2rMCtdcU0U8+CYXU7EZisypJKT1LAwZUwXYHVmTMAOB6E1DyfVhBxZ7xsPmEFCJrOL+BCBz2a5U7q37sRhghE88BFxnNi75C1qaLU1VqYDqamIPI17Ofa1ky1v2Gv9YcEvfgx33MacYubnZaXImj6OrpBFFmfZcXfqlBsECNoq6ihnl3JJArqaUJrDdOUdc0mEYZ1/GVdPUjOIpRjdE6klReNMCiQeYDnrry5QGjD98q8b4n2RqE6PM18UXd7d3CArBmHzzCnj67Ikfc1WGTMRqTToZDCrPVFKkj06bhSWs+NGMiSR+FeGs9N4dmvESRTTOOmRrUe8QlYpLoa/5EV9qoqH3sknY9d0yt65gWtwdyalp1wATLIQ8O1sKfUPZkHxasOz5xW5FX93PX97OsZ2yC8uQPQDhfHZixgxwNdF0pOM6oNrJEb8YduEI3cAc+QKossEtINS+Tnlw3NWU9hesM4h7/D+1z5unFc2P7RScrmOgERbi8n93JT3sX1mwPx0chHNgfGeIYFre06QpEFEBJYYRKAGtBJDcQ9o0U/ReT8DcPW1oxPhgIiDHQjbFJDc9S3xGfE6EUXHvUvrcu4dhcX/LMbYG2PqJtbDE+4MledX0gn5Y5cRsNgeTLIo9tWrODWsK4FIEIpBUspWM5nTdMO5ckt+0TV8g/VcUNzYxZ2ozWjct8cdDqtFTzFkMElSshzEtpBGpGuDlliQCfh5wEAEu1XSgaRJOYUu7HgMsvCw8xAAXLWM50ymAuYLNOVnalOLz3bC7qhuOPRyHPpE8arR0PW5v7uiNq9fSzzwj4dv7xkqHVcX+oG4SuynaylRKyACfOcFd8ntPkAEA9RnYa3LRVxLeJA0UrxiF3J8MBDNAaDhU5TQlajeTsx6qkh3/SoSOeFuGfeUSKvNZ0pGC05zENWgZmBxWAdAK2CGNwJQIz0GUdZn6M6jKxHJP0nkEdovPgbMiYUrL5nVurGDNBypKLpHYNhy5ae2SoJi9NEa4xGFVQa6tmyN5SOj8J5n7R0elFj15wmyZgQVoqBDX8LiAwTI3GBgC00E4c6LObkdZhJF3aahF9b18XPdeOmDidiTOfWUJusQyWJKWFuUj9ScWA3rrIxvP4Oc5x0kNHzL+u25d36mjiLtuG7JVuOpTWX9+3CP+BOa9M0OV/njrMpDfWoIz1iiDHTaPXWOMoMqVuqTkwKxs5jGe0Z+bE+zi5bJOeZYm1vUlolGYNkDy7GYL27zoCc5+rkhcRBLxEykgcOxDOpA4M5VjIL/U5gcNrgtkD/GJpO1nVUbfPT97Ixo525iyUM8KLjpIqcZtBMaEvgB+N7IVn7GOJElRKJriALhYvynOwtIacJ5ggux0Zqymdm1FJQKaHVjFoJRMJXCP+QsS4NvDSUc0VZVjBVsHo5cm0ojVFCRqcubgfMRcCUpSSD1Ym1v1Me4TVnkaNSTmhrQanVHbd90Yi7eOfycIBYw5MYSQvrdZNtbBy3d/d+z/PTj10pLAHId1n4DM3A2VpDfRIHoHQr8N9ODUiS0S4lQjomnE4nzPOMeToAM/D09RGN1w13aefC8BnpOwTP5DyLjsLv0xs3fJfJXIlHfVH3W+6MHCVCsSACP99tOINrKchJyj+21rCuK+7uboVnAmsmF0ZqbeAJ3NGKzDlG987KK8BwG484wfl260gjo1UHxd8AJglIYZKyl0OACy6kmReb3fszdv71/blrlXw2nNmJo14f+W5zri96bsyV2/6+Y6t1vtNemPQT9TrqFH4Of/vk9+RPGfyZkD++946WL2INX8HIn79i/tvHAV7Xz19AAKa/fRS89lmM/s7bvGax8Ptqol/vxoUHAEA83fcsteeB6zXNCWI0B8Tp4J+Vhvl1rTt1XR3WC/ob4yflw+s2weDHCKucbdXBJHQn1HCwLFgvnvdmeIEhZzwJr7gdrtPU8H7vGNB63xXX2jWj+pYPubxhfGFcY3EUVX1D66Vnp5wlw57xKPoQA1I+FxL8xdTLEV5bdV2WQN46T9a4R6SLytT6Mge2MC/jOcI63Ni42HwxOw4t6hzawMiN0DJA8wTmtcuCv3Bg/2ynhm3v293cOxv7uEIixcecWJunaLz/+iikvVU2j0nwxi+vhLOvnWZuR0ARyGjvrv/s9pczoDMY97c3+PZ0+oWDxCC8ATSSvEAMnsdPH3H+vGJ6l1Ee7F7qAkIScI4pu61ZVKr0Pqak/l2tHz4xCnfmQFMn2dyYRKioCZZdI+cUPKUlQsJOLkOICqlyLqvnLTOpgNikFp4ytNZaS4Dq42spWFcxTotxjpEJOK8rlrairGKA41JQa8VtukWqAK+M2hitMLgwSmG1ezNKkqiyBHYGHkDAOKJ4rF5nXSYjun/xXkwNsDxEpgQnEMrpjEoEwozpbkJpJ+mHZX0Lr8P+WcYudkGgExwGUJgxQTyjGECGRHif9/ZRmezP377h49v3aN8fcN4w3o6HeN+Ivu2LmNGoZzuIYriNcdEo9DPEuGtM8c1GiDuALiLQh/FjRPp2a/1ekd5mv6vt3L/X7fac2HhlXnKt4QnrwxtMH+WN5iHeWkMCoXGVes55ApC89mjWTAop1413trTu1QzMh4MovRJhXarUcM0T1rKitYKURKhPHFKKqbGFW89/2I1I6gHeelo7ywqRrD4mqeIz7okqB/Mxoamt3yIuWxUjeIIqshIPi7hlQtkAn+AOHoAfiS4U6SMeUWbGAf3Nfs2EMH0Xj/Doe6jfC8PVlUD9wU6It4qZqNAne6+uqym4LMVporYPVGTrGBSt1Ds3gVlek0DR+Mh9bL5FF4xtPKthD3YY7sv1GW+8+NaUnorjTHEGbpqKUyK7qtWkJE3ND0aqhJoIuTXM0wTW+s32XuOjK7N75Vt5DumLBybdxjOc0mAYGNbpYh7y34tRkZuHXpCvfoEXk/Wli2vy2yNwAJCr1hGURdA5xtfquXXYbBq1t5OuUHGCR5UO8+JhP4Cw31DF+lATlrTmanNDWUpyhpihEWlFoou0Vm3SsgayKT26lciiPxEESBMm+ziMxtv7kx5kBlxxTLbCLsFGeKbwvG8H3JisdHp7phzvh/PBrPCue2ZOP4YPTXBsGwC7Kn+H+ywyVGpGq8FjEy3aH+OXP1utL4f33+WBPgDlH+rBlLhbm/LoACPGc6GRwk91sN7Mw7ZdU3jLEWKkpgZsN7JKiZScxUhkzFk0fLAzbOMLeumLiL9HZxRgpEUmqHeeaWfsv7p2e3u4I/H2MdqYyc+IOaOZ0ccjk+1+FudRcENdi3jZw1Ko9hTt8h47yxaZ2TxaPUbbvRSxHxXU7pDgGm09V5q1JOVZjQpm0CXni/KUdEsFfsy4IE7F3elB6sgSoM6zyMa3ilJf6qazXuu0hrnBMwFQP1/D/siNL56MaDAadeEMM/bbAWHNoOAsVHzP9sX+JXcHLFY6nLKWxqFdfOK41XCPZio5HLRzq4+t/IgEA8asGWr4ZYUxpU3NDqdjUsPVAlP5htxYG+ck/tYcPiWcHx8BSji+eSO05dRxe75NslZal9t4ArEr3QrPZjCmBvJ0UFpiMHcMKTZd4BAVReMFBAaxfsYKM4IRNKpR5SEoX2iOFQb3UrYEfj0dqC8NY0hpXdWwaCxqhxE57M7ibXghspTqRpfQOzAHqrjOlpGANEW4KXvld3ZaO2m6SsmaLjXQJbW1GLHEgF4hdnMZX0sccGSE1Q7/HWjD74SuOHY8egX3AaCU4YxkmJ1F7+pLXe4YhoIOnkRSDx1Qx+iI11MajdPbuWj69+hkGL8f39m5io68L/s1mpGTORckh3fjiz3FaGuSvp87FbVfnY9UpTbCK40xUZRD7WIk+rXBXXeGjjys/ZJtMxoaeBeCwxc3MxpYpqO+Kny+fLusadG+GFiBHu81qxwrfYhTI8BrEZl1mgCsmJo67mZxwLJ+KSWQ6qFEn1GFjwaLDqVmVKooWdK8U9IzTAm0MmhltFSBJFkFzXGrVVY9UD93HUZt/TuNk3WJ5wL9b7KxSbPyS41Z5GPFKaLkU2e+ZFkGVEcWeEE3zuzssw1th6W4+D626e6NcRbhRkbTAnv8fPAnyfGR8WySGau16iUDJpL7CxZ0hyMAOKB60b4+IONXhnXbOXs2vui36fYsUxDYnV5uTPQQBIApK4/Q5azG7PADMJ6enjDPBzFetabdGlILY9F3JY1i1ItdLhlnebEnRh/AjPn9O3WUQx9L0G1cLMCf3C75lH6FwmfGyH/7eE0/Y08T+fGJU4hrcstSa/0fHfeFAxwB06cP4/hCM4xb/v4F06ePLo80MOrfKxoeFN5szmoY/yc2q4d+te1+x9e/gszxDfcsoK8sZvLv0Uzvdk0m+Q2vMMcQ4z3H7H+A0dOto4w+HBGT8nLCwxDZs+P4/7h8/xK2f33zHoJOBZCSuFQlGNJLA5tcCMGtUxLHtFOpne+9MtLhnS+zWuinczNG/RSSI41v4P0nhiukva+rHoKRo/urte8EvP9NE3srbA0SgOvuHT9pW0Lwwtf94j8Z8f7J7a9jQFeG5fPX7+oNyhf7Gw8WBYZChKmn8X7lf0BA1Sjz958+SBTIgygnlm8V3+gH3nBX8TKEOTw//sDNu/stS+vN5G7a4AuK3+MS3rZ4hWFKfFV2N7lw1LRZpRaI9zmLd24ToWrOEzIBBQ3MFcuyoq4Fd7e34slZFjAltMp4d/8O63pGq+b13jAfJo0ILoDKyZQZDRXn8xlznrGcFzAIB/TUylQl+n2tFet51Tkzai3OnTER0pyBmgGumDAhzWIAF8UMq+Fgwul8wqqGIyLCupxRuEl6b5Ck3kdDKRq1qes2U5YINV3f0lg8peiE9kM9x5pEdCZugmSC4MGAG5nMWBQZbgY8C8KEWzSckCHeVSd0suKGJxXYn75/w6TuFqacoQ2QbB1DjkQ48j0e8QjWd2TcoeBHf48/Lv+fYFHrcuWkisoj9xiibkK8BMR4nrZChrV0n7B+f0SmO4CSO5pE4THhFhXPFwy/3HODpt+Z4VEYgCMY5JkGpilhzocwSflDInom5Ewe8bSui7w3S+rByhXLUpBnq0suwtN8mIf5zocJ0QPaPOxEGdCFPouuoZRwPj1pPTf0FHaQSJCcstQTnRJqknpi66qKuSBEmkFL+mVwZk2dq+eEVelCCYkqQvLGoHQ1r+HkZ8wFPVMUQSM+ArxZPXE4jDaQJjubpqTlMglg88AHzE2iVQZzdeHsvMj7btTT8el87vKlS2Yjxpb9FhLFVD0uyQTtrhuaIfkWJodHM7DJGZIkNQY/jFBjk6h7/rNmLyAg3U5a95BGoN628B03U5IAV0+GMYyexs4cLXTXtgyl9aeRr5QBLmroVHxUNWqaQCi16GukNrHobhJABVQkowIYWCBw3krxaCmyNImaKrisxZXzFsHRmlJWEyQsfYFNDux00xUMCPguwGc0tvtDLy2wN62Sd+2R3T4sAskiDPcjUt2JAmZqCLwAIAYdPRdJoyEdLlMDtT6gXvOXgtLT3gP0dO+A4XkzvAm6IoAkpXNK2Q1GraqjmNY5zppNoCl+qlWV62rMl0h2dGW6KqHIot5y1oj2pilgG1CreOxz3CejGeRypU0mRjpuo4XlnBufZf3IfCVzToMVvx5ondE7O4IOV/D6rUbBWutrNwjDDDeuR7o5KIxUsZtbBubZjd+mXLSU2rHO6NDHdmOBUP+cvSauMX22j7Y+Hd522hVpcOuJ/CtyVXx1j8RV/qjJDYbHicfInSHa36/Byz3kLDVixftdMxURgXKMIpI1IWUcmzlyouPPblAnf+dWcdHPi8F2rI3e742r9rN16Ynmtl9ee0pljWSm8e5gEmtWE3UFPek6eoCz9tSYxaEUECOFEGgxhrEYpG0PUko4HjMOB4m8KqVgWRZP7R5hrzVViNCl45I5HhIR8pRdmZ6z5i8ScoGUNVIwJ1CalP4nTaEMT9MPmHLbMtd0IJG4gdQdV2M+bTJHgqzGc+OvqMMHJz9Dglc6XrLfqh8azv9gN3G0v7+hbkwyY1Fw1I22uRwjEynsqeJ6j+rivl9EBNTqc0M++B4AW4cEdTSYVURPPVIGralzizghS2r/1UtRyLolN5IB3UnMzhiYkXIe0v0OcMGyVpSB8qOAbjPyzS2mrBl7zuaUoeumUaoSMc5I+Sjy143hTcnSlCgh34S6tLak2o/IdZAoV2jEJADmjIoGhvDvnXoLnNXIDxKBkD1zVNgmJBzEcK5ns9d/BtAYpRVxIKyKF0fAQFUDrzmC1GoGGokc5lnK0mDtWYAisWTtiwecqj/BiJ5T1s/RaZWQ8wxGBbgCEwFWKoHF0Ya8vIH8xG3lQHsGHKfKYWZ1nFFIMXnA6EJSR/qUjL9XWGSok4nIKa2sMH7LYJtVMmGNKIqE1Nk4RQfm11zWZZTDHI+qIT0KoYBm4gq9Bjphn33evDF060Y5TQGU90ogysLlRfpvmWi4yX6zvdPghgDu2XGMyqeUUFQuMoMnJSCxZhOD1hlmo3O961FZr2ulzth+v9VwZqGvXr+bofWsyZYC3aFDfz93hwehz/ISBoMpg9FArSAfD8h0AM4MHDXLwFn0OuUJSEdCW4q8+451vyTKPLeE+UAg7gEfUBlQnD9H55NWG1oKGbFKA2dNA38sElBRM6Z5QikF05SxrCTlAVlLnhHBUu14CR2Vxw2ITEZvFoHuDIfSRuULJfti4JuUzrt+y5yBDMeTBKq0Jk45Hdn9hBcJfz8/PQ5R6P2OkS/LKYNyBmqVyHMAEv9/RoM6IAEAjsi32fFOVmdayypy9/4uvOcNHr886huXyPKPQ+mpYtBPdBgfRhITRUZmiLE8pQ6nSluy6U2UZ2Du9XOdxLM4FxIIh4PUG7BsGmylSDYZLIS3UemBCLOPkXuiThiu3OxLmDxD63Sr7JXfv8Py7aGzNbjcaYf7f6M2GNF32iMBLV3ec6sfJwbatUkFkW7bLHra4OPwt7/BVijKWp4hQDvydO6QfKTnv38Goxs0pr99xPr3L1jxDcZ12/v/2cZzQOb5SFYD/eUBvNlZqMva6WNjvJxK/+cY55/YXL848mbjLRdXXt99+Judt6bOW6ek62UcgOJSpUEc3m/0MQ04gQaExht88JpRR9w14kkaOtk6tvxsFciy87LNqs8xkQU+AYcpD3Laqll/19ozsMRmNMJwb1E6Oem5XJUPndKI+Qxnm95xcF7ezI8g5WLtaXMENp5QxiVjPoLCPllfwJSzB5HIA6OexNe1vXRa/pz2Ggi+PKN74+fd7/bP9/787ZsCwgPxlWdf1y7nJcSayTlcONP5H+Xl8/P21zGga2MTXl59/yDaAtB01LXh/O0bju/F8235Bjx9/orDu3u95x4Jj8OToygG1O8/hj5/V+sCmfbNGBT03FhqRzVlPk2oZkFAzCpUpQQukui01IIKwq2Kda01tCTr+fXbF9zfvcE0ZQhSFMFkyhmlEuqcUNeGPIvB/ryccTwcUItE6ebboxgBiJBmefc8H5CnGTlPWM4n1CpKqZwnHG5nnM8LapV33RxvwVajrIki8aAG/FQyuKyoLKi1saSzW5soWpZVIhUklVMXRrWEn66ffFMZopgHXImeuKlA35EUs6TN883oYnlXTmk/4iLwjKw7liHZDa5Fop9JzICf3r3Hj4dvft+gcHGIlWsnNByJ8ZbvMb+fkPOEp89/x4/gcUxNdwAAIABJREFUhSZwHqiT9hkN6QTgHCJ+TMg/7o0V15kyy7ZQH7tyauugYs1Ssm/7kv5Pw7sIZm48I+FWSgL8KEj3k3Dw3GvOsPbeWhWBNo+RvxadtT6LMiOrQu1cVi0T0Ne6G/1s3SwKemNUUSHUiPPN3Z2UNVhXNYB1WBGZUQT2nBKmeUbKQvTL0hXd3LqCW55hoJKfZwJJ6j9JagMkMTSzch7BlhCUAjrcaBnUeVFggCxiAKq0MqUjG2MTFL8jhiNYXg6LcjHnAYA1+jC8cwcwPEJcPlxcd8UIKRtAB0ha9n2S5oo0ArIpJZOmFAVgprgESXXNnuppK/pv+g0Miht+nCneOR0Xl0bIj7TLumHFSww4LjKjljGZXo8JpvQkKYeRmuwGSZrRshY0BmqTPa3LKop4bpjyhHmScgG1FJQiEY8SqdI0qpn7qFn/2sBQ/GM0Zu4ocIf16NT45WbKqVfc6odgkEq2L/Zx/0S2BRwbCBEeSiMMBw7BcBKiS+Vt+s5ev9Su94gxwSs5T2KUNAGGNUKuFq13q++hDCKrfSxOD8XqIifGNBOYM8Bq7ifq5VDyhJzFGFMKgVHGdKStMxxW1xyqGOam0Ba3Tv+2hLV27i6awUIjSYFB8Tz11QZ3+I5iYVZGqOPVLvQOr+Hxuy3/lJLUhJ8mScfbghHKvdd3ahBj8x675AppZl2f0WDyC+zpeP8WhON7N7e/RiC6XKd+vQFgdZyxFwj8KQ6KMIvcHQ2m3PG7pRA3VO11r5vvKbfufCFr1kLfdpyiUK6xJNS/c+W104zLFfjj0QFje3ltFT4sWjEaTkEA1a7AVxjcRjCI8N/QLC23OtAJX9tA04Tj4YB5OuBwmJWvkNSlWetH9+jC5mvamqTQj5PoxvOeGcB/0gTLhoNEmLIY1kkNStM8iwFSHXQtchYAShmdhwj9nLfUxNDIyo8qLhEFvuxlI4uIa/A07uaEstnLrgix77riRgWebuTV52J6wk410dfHLgCC4BMJrMat/gk4WdC6oT6DBStNo9DidINIo4xTcG5KCZnEcbNBcD5QUYsYlEqpkp64SjmspmvkELWle3F8OldXFG6+Z8060QqAmxTGJEpIMhvLYsth0XiSGz5BlG7TPGuUJgGzmoFNWd9iphBWnCDOqUSspSI0HbHhbMVHFjVhDpAmqwAQZ46BIIV2AMwQa9kM5NxB+BM9ayIHdpoTuDyhOSBIdgFZx0Sy4Q0d3pwQboYy4moecJfQGknhnyj7mpOnv2ZUYlAjKUtGVYTMJOWq2lUrxthEGYowts7vkgKuO8xF2VPpvk9ykCHkWp5mNFXEXoJfP5vcODi3jVi+qiPouqyidwh0gFJSXjLygXv8pF7ayBgx8p5cRta5+0TNoEcANRBlzS6g8hZDDfYMS1UvjxFYnSq60nvk7zMlVJQh/Kc7Ldt4g0PI/rRgTvcM9Mhvp6O21t1IDh8zhiwl1pcZD7qBMeLaLsu3ZUU+Hsb1nG2WFY0JrQK4YZSqGRJYIsQ5Z2BNyFNX6DsZ0M1qjWEZ93umpeZrYmXb0GZMU8U0VazLIvqAWrz0HzNUGTFq39iBIo0EYFhn8qxMe2jEnLoIEoVOKSFP4kQo/HDyzWTFUbkCFU14zJ2wL3FkNYBIw7ifn6y2NuHu7g3AjKcf2+rMcp7maQbdEdYnc6bezk1GbvDV0MQh4Up78+ENzucz6lNwhLkgGNs/xoVlxcdKnTEsauoZAkn1GkMdc4rOOOw8tvE3gCyV6W1Kq5goOz2wkpNxPNK3/B0d/a5GxPpZvuS14xP120O3EVA3H4hf6u/hQf+xNgoTUZd4LRJ9eHqzPn3dhFW6wxiFzjt/XRuVc2UMcChhcbEnBBDegfAAvVPkQdAwPQZ7ackdEepf0l4ygm+bwY09smdET8Aeevr3a1u4Cedp+PxzBczrXhc3WnUwZjwXZwz2LDtCZwLGinyAj1Ig1HEQKQ/wL4eobeP9v5XHMXomZQXF2Gxrvs3aJ0+4iKafr7r6+2t6WF6/GFVuv7Ji16DB4cZISej0d8HQv2O7XP2XVvP6Ohhu+fNKPvx19yC2v5wBfakVmc2Q1YXg/RbIKhHuADxBjIqnh28i+z58w4Q3EB9kxuPDIzLgVbi33mLOUClCbtQ9jUdhc9s4/N9vY4tU3MCjKTYtJYepgxqL0vdcqkR2Ad0bE8Kkc2vg1ECsyfSE4weD8Xx6wkQZN0eJIChBqEopY8qS6r00MTzeHG+QacEJC87rCjw9ozXGlDKONzegKWNZVuRcMeWEdV1xXheAK+bDAWUtIK25fjweRWhNhDRl3NzdIKekqfA1GpcBahodVytSzpjyjEQrOCWJwgv2vCknVGapvZkzTs9nF2gjU+XrHgRKBqPY92xIR2BKE2P5c0d/psNBhqRGfgLwBsDMEm2dwk0e8WiKLGb8ULg7qpPGs47lHd7iOx5dcDY55IaB+eOEp69fwV/fgPEVK/V9jfCkqh9vRyacbUBbINP5nAi40WgRy6xIGNN/REGi9/Ksb3z2M7Cld1HAiK1t7jm8lVRxzG9QHivyfUJ7LGA64/zjLLCtyuAwfJgRnRdx+rBIMVNOk6ZxLKXicJhxc3NEZJ8s9eZ0mFHWFWIPqBhSI5ryCyQ1IjFqbObpoAqMBMoJpa4+80mVqsebIw444vnHE6YDsJwbuLBkYoAIlClL+QgcCLVsBEKNUE/IKgy1sIbkiqKILUauMRgDg8HP4D6nDIuC6dPWtJLUvcKJdLyTROS8eXODL18f/frzugJrXJ4N46zr2BVQYgDuAnUQtEMPclIlas4jyQceLgM0gagKfjHjOVmZDcVziZAagwsk3aDCh1evFCBURSk5YjCDwBCBHhxY+h+mtIn4ngLD3wLuB3rNZY3clJJzWlOSgtFensmJ0CzFtaWa13taq1ghsfqrGlnrekYpko5wnifgeAOgodSG2tij0D0bhkHPBlf0MWxF1c19UaRmg8uIo17JXpOuzdX7A91UhamUza3hmUvu2xSN4/RiOQ0OOEafJ4lDl0sZFlmZ/EAJdLVQc9LqRMUalBbhZWcv5yx7rPNgwKNg+lr1syB9iUGltoJabRUSqDZMU0HlhKxR3w2k9dVN2VTAKUnmGTR1xFEeyo+TAafRSVxqkcKqmoL30tFEjExuXHbhqiHi8LAFo0KfO42Ow/LXxBrdPxGoCJZBQ9zcPJ211dZOacA3rpQe8AsP34G7om/vmq/dOMUAii+ofEhxTXC+iHfZllz0vW2sSneFb4LCFzO41T5H3uuDXdHuw6JeLkAMNAlpMp63Z1hgw8/ggMf6mnQXs7HvPQWkR/0mq7krqcblXnuHTZc9e8vlWrywTpe3DVcEx3ZjscGTwE+P9GpMXlc7Khn8XKvxvNaKpj/ceipakERKpZQwTRMOh4On/CYif3aaJtTSwJkBS0Ud+Ms4C5dNWIx0Vs88J816oYxezhaZnsd08ylr323o3yLFYhp5YzBqbZJDhOHn2eGIRzzY4SKmhwW6caGfO1FYc8BJqd+PTq8Tj6menQf/6V6H5grmiy+GnphFZphIHfZql8UMXroTpjkmBucL7Yub1B+vtWoJoebR5wIvQheIuwM41244MHaKLSI1jNayrkcERJTQ1tZpYWUgATU1cFIHCYxOK9FQKfMitJUBEqOR8XDCdycwGtqpOj+lK+B7Y7DB6PV4B8pt/AYBnIQPJUE8Uqom7ErGLNHvyse2JvHsfBbjuWU0acrLWnYx4x+sr7qKxCNR9IG2GZpTWmnXBkAwg1pYf3ZFcqfjbli0vUgJc5rESN6Ef7Uav9wqJCLdzps6vulPr3veaZDvvYmI+oEAIBPAQv/t/Il7rsT6dTxOnlZdbH2tl6xjaErskU/pyRyEX2pobiEgIifZpI8YP72uAh3zYR7pBPf+dskk0WBYluc6dYyGQIJljqAO82rIJct8QYBkTem0HGTnx4zUOkkr4RU4XiJZJ8SMYgYy6kwy6BCusC2iE+rR7TJgpZp1VLDavpsBukX4Y1Waax+sC9va2R1KzExMLQFUnR+t5zMyDqinE0qpYFimAJlz8oUBkDVTAwgNhIoFrYlehyCZSzqsyPOtiONdzYTKveyU0UFxeifc3tyIrHIoSKeTGksbyGgmSA1sPV1sn79kPjJ4KxqFt2UzzInTCTmR1Exn+DnJOXnWCDCLs4XtQaTzHHhCh8QrbWNEl7GMuBuAVcwBM6MsC463t/L9PeH8vadbN2454YzyNGG+y0AiTeOvGf6yneEN/5UI6S6hPFUc39xjeVzBOF9wahdca7xAO8fUeQkJepimjIzs57bUaosGwLLwRAcRecmUCXe3tzhpZrvaGnJKaLUYQnIdDYhArYksaLoO5UGKDrmyzM5g50b3f3AI9ynew+A2v38HYkZ5+D7osACMPEe4/lM4+M2t0+tLpPlSJPqe8cyM5W/1c8KYyv0lCd3uB4Djp09on9XBlID6uaFq9HgGYf700YgxAGD6rwmtfQQ+fwEjlhiQW5bPn1HR9ZOPkS17kbH789oYfX59EGYkv+efw4XzJTvX9u6z9rN9+TNbNJ5fGM4j0bsChz/tX/8jwGuf5yyBMSmLM7xkA1E63rYntX8ysLEslWYfMLrpDlZXEOG1GfAGr1+8OQ4g3L/VjWxuw6r47phn9X0e1zPpb26MeZrE2Yy1/8buuAjfI+GLqu8FD++zTKzWGoteqS+JBGhmpkH3EaQ5HZr8PkEy6iYWV626WUDTDbBmym1N9MM1R176svnoFb/8KmT9o2fltef4pW/eOn80fnNJUX7eKwH4Ri/f86vtYmT/bML2L2h/OQO6NKlfWX8BOISx3G8NP3Dz4a0gnm/CGM3+zD1u3h9w/vblApkZTvXPfxrFGiHVhAQ2wb42cE5uBGLAxWFTaLIK/bVWSVuWMrJo/VA1kogIqDWhNcZSCu6OR0zHG6RpxunbglYKntYV56cFRIRpFmN7zgnzNKFNGeuyoixnSJbYhtYK1mXF3d0tpsOkEQBCnBIRDseDK8o9RbKOGcwS8dQyUp5Ry4Lj4Yi1rBJ9R1p/Exx4L/OhDXvizDgDJnixOQ7A328pg6yXLeJq3mHfkQzgFsaYP7mh7ABgCdsWDenMjCcC3uAR95/+hpuy4vPDVxw+zOCvXbFkxrGZ7v29Z/wAQDir4RFsM7ZbRiA8oQt7F+AZCNJC4iRwRGAq9HdDr8NDuAXAyG8JlBNOXx8GuNy2CLk/ZeqUiZnfTpq+t+/j8uMHMm5xeCdXrf6jRWABEiHCTaODVGljylomxlpKTxkG8hIFh9sblHWVubaKrX+iLFU3qg0KYVeKJTCR9EPUI73FUoyv376DKzAftAYmkjNNoqhRITCRZzewZ9n/t2Uiddzp18zwzZdD38xDdqEb0ZOndjMB1P+RpuaBPSPCqaiGRHGXEuG//vYWXx800wDHeYe9D5pX0jlE72PqjwzzjIpHn6sqm/ucQlp66zf1ualsrGe9AiE6K9ZANjxgxtKBedZVdqb8KjC/TAQM39gHqZ1MhtR9XQF4DWzXL0ByrqZEqM3SRNqwWM6DpnvlxhJlvp57HdXDQWtlA60WLMuKZV0Fn5biHv8eUWkbY/Ml6tKL1QI13H1dkoi/0NVKv4tYbvuJkk74bQNIgbuOaRi12dnvpjJNz65wT6kLBCllj0qxaxKNQxpZKlGi3ndQXpgR19KGymU1nqvhXZ7pM2ucFF6AWqHRoQBDYaJmpFThkWrUkCACJRKDOSMRI2VG0vrFtZEqjppHC0dnCYGxUCOYqK+RAp9nrhiEsK78ZVU42unq9a63O6fRgeqEMpCzIQXPxaOXfW0AUvBAQzYHIC/fMAqgLZxNG1Psb9d4bvXQ7Z/dMwz0mhh0eaXLPR1u/4huaLsGZthmLdfADZ5O1a0tLsBeGaMa15CAnDSa2nF6f0fMvDAqmy+bG3JcgdmvG42yn6TaZAk6EjziO3XROe/89fpGAdfJWZWLkq0gydny6HiEup0cOwAzSwalGlNyF8kAYPxwIk+Xl3LCNGVM0yxpf3VNpqlgmiYxoE/iOCgG8RFGd+eS5Mdq1buzbII6nEmWizyLYZ2oG+4pkaa8FnAUmtR8XHHvWmOAKhpXceBN5PvC0HPoUdodX4y4I+zbhn4YoA1z5fFz5ysCHw2Dz+YKln4i47q9dNLo8m/jmYwWG48kxbj1GoMoe7aSIaMC1HFYaUUpBaWUbkAvDY01kpQMP+mckuEvw6d7OHXz2QwE56Y8lxkepLxLPmpa6zVmVxjXhQGlK4oLjDYaHSNZ53Zu8CrFbLV2JbJ1OgofXs9ajmBYZk25TAxjaqmxRnqyR/9nEBIdYAY3cZYlR2W8mNFTjGuVVZmokcXm/9hBT2RAg+VsfDGUR0OT7FBQus0B3+vzBg/XTqJMhzRLkkWx6qpqdo4urfVz7WfN4CJkr5D66H0eDhEW5mvcjMJb0wwaxnMwpAwMKz8q/HSXoWxetVQxitqlmFo8gKGsqalZ5bpkZkgOPxGijI9czj2le3d070sbwZsImjWLRLdhcKp8huk9zMHPZENbcmdnNWItJVJ9iTqBQIzELlOznlXIZPuJC7TNade+AdXxBMt4u9J6nKNBnTkDiK2+w4KTJc/GwZ6uFWy4mcL9uuYHRjudVP8yqROJOowcCXzOYC2kcDgeZbGeZwDF3xswNtozgDsCavNyH6QR2mCIrgkNVVchOhAwhM+tdUJLiiM8Y4E5F8n75injSeE3xQ1UfVFcZHfw0jEQ0NPe21nVjm9vblCbOBdTq86LR758ooyUs5+dREnXTSPsA+7quoiR7sTWs6DIU7VcGlrOy6L8o8HYzYBPzs/PSFlUu+kmoT6PeF60ISc0vkPWsXjkuzoRzPMR5pQBiAO9bEzF+lhUxpdsIxWnC3xGgKdP7m8f5TqjUSmckmG9fM3kfNVWxwPj/Ygh58fTD+Q86XwE92VW13rNkGN60QRxiq/UabONzn+i819oW/zEeATwwefUseo43D/CY/72NuDILpO5o16gb3qTfq94fG8DtFur5hbxGmsXzWWHvg53cUGYwXjA8oWR8R7sdct1VJ8/Y/74EfVLw/RJgkRS6gZ9w7317w0FX/94Xd8/sdmavGF+RST666Al2ix+Jbr9nwGLZEQ0vG9rPN8azgdH9X/k3eEdiTSzU+510LlqqR1cygYXgqLpNHQ+ph+23zLWPzLaER/+7sbDH5FRQi/VE2S0oZzRH32b63H6Veaw1rtjG9ev8wA78onzvPDlY7KsSBec42X7hTPy79ouaMq/3ZzoxY9/pfaXNKDX1qQWwh4yHFpEgcAeQhOliqT3Xr99xwQxfla8AeOH1I94KADuAfzwpxqAqr0rqtol6teOfLAn9Rt3ALGxMOr2G8roiLzUuqGOmxpxk9T01rRGSdMTkiLZUiqO00HSqlPClCdMlNA0sqXUimUtOMyEpRTkSQyCWSNhmIDCK05PT/gxTWhNGP5DnkEZ+P79Ac+nM56en7AuK2otOEwS3Qu+VcGHfc0oEYh7WlWwCu+KORiMKWccjwchkHlFfW6YmqY3bA1MIohodUlP3SI1kJoLI0OqHw7MG+D7+LxDXlj3uoEdXuxJI+RS16wzPJOS4POVfWVjsj7/DzLu8b8//RdKLfj47gOeHr5h0XtuKeHwfoYb1UF4pqafocYI03Gww8c2oo6IcGzAOeHi+l4z4pagNaAAHN69DXtkDMYdEshTtdszvNPXJbGEGyKX79+RcIfjh4PMrUjNq4nugFtCeX5CwwngN5KaplURZkFd/88M5iqrr4afeUqiXMqmWBADDbcqYhZJ1oTDLFWyWCWC3ShJ6LqaQEZATnPfXhW8E5HXmCMIfM9TBmeLQvAHdB00ggD23obpkNSg2WBFgjP1NPGSQo41ckSyZ3ifQcjxtMSbfU7JImChygBVdqsyStLHquhLhNkV4fKeiTOYCd8fF5giiQhA7t6JpmnbYuDulbpZVwCAOTBYBBA73NsZMGXIuIq2NzMSMiTtcHYPTRP8GhIoyVrb/KzWZ69zGxlAw1Rm/mNNV3eN7owYnzZXY5RQZG5zmoIjkxj7TDHmBnUCkmIhZ0EDxyrkgQFNKw1iUEqYoBkGCOBaUVWhYpEJ7mRKoY5xHC8RSMFQIuzjKVdNlv6W1YoevyFjxICBrzS6+CN8jmsrP+zrbGsxiPYYFgiQkgkEdCPO5i2D0CfPuXFBP5GulUelmADGlhayalribggHhGZ3I6HiAVMg6X67TZ8SpqmvX1WjVa1mBA2GRui2Q1LirmVFyxKJ6UZ8ZtS2oloBUoJnagAzGhFaqoEP4Z7+y5TkJmRC/2b0uqEc+g3rzxrlFde706pNc5Bm77/vgwm/O4/pey+UYXa+oIY9Dv3sNDuL0SAer2/7HPYxzGHfgEL2ZZ9rnFy4aHh2D4NcOz3b657GOgiwsVa7Gc+bKeQVf5hSJJFGdjVdP021yi2hkp5+2/L4cu+sY0Dn9Xz/aDNHHSNf4lVTaCeroQmGRKGLkUDAuUdh7rUXRQS7Z/PZDUIIxk6y1O06K3MmgBqd0N1uzMjCgBuDKktWCks5Knx1pz+WIp9InKdKWbCWhFoL1rXgfD5jXdfOFwzjtUOi6Zn2Js3jB1M1+1kTxKbfV7XtSWkPbuwOAt2xy6J4zREN4NpC+m0xyOmn4byYsSGmad1yidF4zgBIga2fReg61w5fEUdFXK77ILQ1GJXGVdxbqHDtGq/c70+692bsEWOZrE3OesCo04G1FNnrWry+vRvQq8yL9TE5vk3PcXM5Cg5v3A+l7wFtnP0UDx8J7STRfIkIVU0OWBu4Shp3gQ7J2JTNWArj4eCGCXn/0g8NA7yaO/ImShoL5uMB83zAuiwgntC0EJYbPNuOXEIASPlUcZlWfk4dVukg6eZv9OYFSAd1nm1APTeXC4mBfDzIkjQtC7aKMXGaJSuM1UKeDpPOVemZ/i1ng0K5k87bGK/YDYaRN+k0UHAvo1FDKdJ/4+qZKsxRlJvhDXPAEfiQ70L9aN0X6SkNIO3nFIJz2M+jyEddOWlGdJVFeJWz3QQftNpUUZ0GA5TPMdBsk4+NRrBGndr3FylFmdHKGBbhPI7zDiON3Da7zFFZbGuThEczx2pL456zyhsG2JD10K2VeQecwqHfjjHsHejlorUDCmtv1NDKPYATpnnCuiwCz1X0Gebcx3rmy1pVRkmDbCq6oG48d/6y1e4kR6ozOknWKYDF2aR102Y5LQ4uxEA9NeQbSDQ5AEDGl7XgG90IXkuOY1nPDUsZMrW2NbCnYZVarJI5Q0o3kGRiyRW1Ci04TpJJ0DKvYJVFJeVJpJSISIlMMVQiwgYHMDQ5IQKmrH+pxflfMNQRRc4caT/zfEDOqdc4bxI1Tc1KJLA7xUlpFdFpMXe93a+0eHeaDuCyoOGExLdgZORplvFPGVXH33RfGCcPAKnMSM8NdEcO0rY+h8Oxw6vCEKWEw5SxPq6hTjCQbzPwfIOi5fa8KTwLbVGO1/lw83clHUtDYnOw69l25FwktFYC/TYeFMrfWW1z0kxZwoOY0z8oY6auJzDaa06NN0Qo9i4AJQFFDe8H7kkUnK5t9kOu3Tu+lwPZjeh7GRpf2teX7vkdbSD16HzGxX0716/JRQC03CeMS7jg+cl0FHrpjYACJsgZTDmhAJg/fUL93DwtO3S8BUD58gUTgPUzYfr0AeXvX/x70r4Lvird7/P9d2hWd/2et8bz/RHa+sQd2BrI3+o9GRZN+u/dovF888X+d1dg88V3+A85PRzqn2ehaS0BFHU8xhdH2WF/EgDg2fmgZT4sU4Xftu1GGY+x23D/xZX9C7wxEm/X0vgso/nzJGnrn89nmB53ytn5z3mSIMen0xm1Ndd5VuVLZW6X45k00GxLv+yTmZ2c3mznZbOgzpPZrxMBd0hYqGeWMH/77PuldAQig1YiTJR03JfrNgxw56z8GpT9vvYrx/Y7Ae9Z1uQd//Ez/5av78c/0kyG2J/UfwCC+gPtL2NA354LUz7VV0DKSwduun+D9fujC38VyrMDAN2hoSFfqR8UFaUM4MyvACPqQzECuvdMZPhNkd3dAVSYxyVi5sbgTJriSmurwhjbBjTCj+dnHKaMRBlvbglz1jp8qhib5gqwXmPG6fSMwIWLQF8rns8nIGdUruIhDKnbtKxnrMuCUqtE0swiFAGQ+mKqoHB9O+u8rCaVMeJgUBNymXJC5oTGGYf5iLWuHnFfawNlSJRMUOqYcMAIJh1dKCMMiYzw84t1jHaV89pdTBJtVfNMSecbHoUYHyPwCMYdHsF/b7j5rzsQgPf/9b/w3//z33iDhLsPH3D+ekalJ7AJZFvlhE5qgCvXPCicMuN8AXCjB3VM394roAkRO7y917R9ajDYRBG6vmBn7baM4sV12XownsA8gdTr+/A+YS0N/NznVxuDLA0NGIReC4tUmONWQZSVenflNpBhJLslca4w2f90Oruiw86bGNqDN6LkJA4KkS7s2QQtlSWrVz2YtaxCUWGNkIjBEwNrrysKwOu7I2UNDCM1YIgipFnWAVsM+6TKnhikmTYbsZF3TA6ERUUkUqYxm0OCpag1g6MpZ7QHClEsQajsL+mYaYu3gQ6fxgwP0wp/x2e7sg6eqkc+9ywLZO/WcUvkKek4tMecPQrEosEuWjjvDMPHjH7q+7cjDjZlQhg/IWR753EeLHNpqbrSvNe6tjRUTRlV0ghqg63tuiogBqXdlNTRDOoEBTkfTQ3opVStqW1GGYZHCjFcCeRRpUFJ1VfN9hQdLwaGeZ8mXhUpwnUK9w6sdjh4P29msLHHOh2N47gyRrJfprwjxzMpj/WZAdaI856quWq9TDs73YikBqihpmmHDTfMIeuzpqwWBXdUP3h/rWkKTalJSZSxshgYfN+SnnOWqDPK6vhHohw+zICNAAAgAElEQVQUhbzRxygQWtaOHsUdDeJyRxcs5bqo9sxpaaCDuEIXjGRaelVj2F251iOzMIzOBqGGQe60/6pxdSSY4d7e3/BY+M7poBlIws1OUy9eaZRk7zsfCOxsM8czfuWc/OwYDY0dd5rxg8GS2CJJZ4LeFZ59WuzpgiXzBaOhZ/boVo6+DFY1xhQC8YxEfEHEQxbTfkbgY5H6zDGFO6NWGuF6WK8IhK9alqH5MJ2+mtAodMVqelr2kqiwjdQh8mENEoHezOAFSL0+Io2CJC1XJOe+NcayLGgMrGtBKWpcXVc3oF3AdFwP+9GzIjijj8doiPGRAx6keM7gxvNYe314vxo2ACs91c9bazZHiRSp5ijk+9y8trefukh7GZtx2/V4j55FmIGu70ek7ZKxCANu6H2O8pS/KMgTW7rfy7V0cKGkJTNCzVejEQ2RVsj6SnaYFUtZJXtXWVFqlewE3JSRG5nMwenN3m5ZmHxdjFbo381OHsXZXWl6D0WHgE7DZFmCswgAwgGEdcPthR55Rp71+KgTAwPAgYAFIJ7AWGHOknGERgM6zx3OIwiEWR1bbG7BAJ+Udt8SmLNkLrJqLK2BE4Eq0GZCW8exx33yw03d6dtgIEbmAYEe2E4Ynt3wlKT7xo3M9dtpS2sNJeBc9vTtWpqn9Ej07lDaeRx/BxtOV6NqTkF0U14mqdFc7xO4ESclmg+oZUWeDyirGFlbbZ01MjwR+rTIcB+D75W0ypIZx9ci4JpqKdn14Qvy5vxlMMbH/WLlO1ROJn+GnYaYc4A5FzMSpqwOAyScDpgU/h1VdsLgAQAIONfwv9J4UtrHBFBCItbUp3r+icRptjaUtYR1gsNbx909wjyhgbIZ4uF8gtcUBnqaf4NFRU6VxQjaWCLR8+FwwUvJqwncvVGG5vtwguRy9m2Rd1KWDIZkjjqUZMwqS/excpArmsC1ZtqwTHFWTk9KM1DPGuTnfg+LdfmDIgBtZmAGF5AZXqH6DZlL1fVe1xWsBR7RGEtdZX6KEqxUnJ3ZlBKKFkCvtfYAlysrmaeMWsrwTS1n5Hzw2dB0QHl+Qnpzr/ApdPZwPOL0/AyiG0Px6LvJqPyM9uMIApBvkztinZcTDofjhpYKnN19vMPjZwkUuvt0j+V8Rr4jTHSP56cf9gDi4VOsA6Qe5MEDfAZ5QgfYnaSqv99oZVI6UzUbYDf2m6FcujYHtY4LwpiMJ4MY0c296ZYJ28ryQORPtzsEpHdpdP3ekyX+cPs5A//at0WR2Hu188x9DaXP0UnN6dELfROAzOJMNCyV0uZobLOvLdocgBjFPzfkTwntc39vfGsBkMDgz1/U/U6aGdy399u77rkbsf+VbWsE36trHpu6u+IHXd77ncSQdpmjQto/CoW/JDr+5P1bA7mfp3AO433SAW8A6fWt96flLzUzo2V4SmiguHDc+RX5uGUeeq/2ZySNg8MJx2fC501ayq3E8PuaBTdIlqQWhAGbXyJyGY0ZmDSLSrW6f2EqF+Mk5WKv4blNtHkQmO3xviThv3G5Ng7g/t+1KdNFyYx/Rdu+/7Xjec19hB6KFO//l82ZN7//H2z/IgP6S6g5gscGS/H2+71npe+1VjWgbk9dfPf1E2lvyXnCChE6jh8/4OHrV6k5DUZqGS19B+EdEoBi+J4ZVZm8iTo6iDHqcQQ+rWE45Mxw/Mrqs20ZFHuHiHtWswxgZFGIi0yLgoKEhIkkjh5aM70znqJoqbUBiXE6nYDDEdONEKDWJEp9yStmnlFqEUaGgTRlEUZFxwduBefzM2opYJKUwetyQikLWhWD4c39PdZlweHmiDRlcGWkanMgj4oyGbyuEnWRJ1EG1VJVEDWinDAdJqQlS51Z7csNapqG1tdMNHWdKALuLcnoqYca7XjEh3F5RDhGvOKytfWn3024BfAstdNJnr/WCqSMQF4y5sMRAOPj+w/IJLXwzviBpN7cZ1MK+P/R1aKPK4IPA7jzFHTxPsIp3Hjg0YhOsAj0N8JAGHYnS6Fafd5WSz6H9YlrFFv0Hl1Y3mtd//j2gPsPH7F8k6iU6W1GoYbURJhfnyrarZbyg6ZCVgOzGYUyZTkfLEoai7gAwdMupiYp1xM6429rI4K6Gto1VbbVtYOtvwHGRkBOSersktZIlZTO5oRT0dShOiegHTrMmRtAbRU3h6NmVhBckNOEpUlkRvfSFji3YGhTcJrSz5RJUc1pahcyAcieYzlX7MreHnluB4co6VjlWtaUukWVadlqmNu+63GEprcmY/I0ihCa2noUfDsky6v7vki0W4L/z1LfnldCw4qEG8Fxnn6yK9FFCS5GyMySehNH8nVw/3QdtAmd/d3CrI7G8wDVewdu94PRO7nuioBEXuMUlpaTewSTd86MWqReqNGUrClYrfZnyoClEKc8AVwFdyumaLWgNhNqdK9tv1XJBVMuwSKgpM/OdSvOdmndFy1MVa6RZk2grHWP3Chj4vFLXLN9l0LfRnzQz+LQAlZ+UTa71gEDWrqgR5XK/ouwRm70is4X3UjL6pDQaUtfu2g8N7giSNYMXXug74m+XxwXFD7Eyg2EMfkxdYOUnRxRsJdS3BAiqc5s/8XYkzUdbV1LLw3xf7n70i03jhzdD4ggWSrJdnfPmfd/vztn3F6kUpGZAdwfWAKRZEmy2572TPrILCYzY0VgXyRoc/BmlArh6iU9lS62DlK+2pkr20ihYPO/EWswj8XEW/Wa60z+jPqYqmC2EGRvO6IfodGH7a+6cpf8lhkuZGZvOPICCpt7GgDtmXwq6EGczS8IHV/icLOvOzyTHKI3MHFC/f1ovJl5iuez8YSoQjObjdM2twQF/IgKaBihYTFjE+iEDrF1jGNkRM+6LPxXZpkOnAzbFwvpc2eQ6V2U41v5BqdcxCAu2Vdyao4rEca3aLu2o4c2w2FiXeEFhQGzxUJPKHgJFBpSlUWEpBdJNVQgnrYWcOcQN7a2Zg6D6osnKlkHe9u2/BdlNgDniz3izVLnkju2+JwoQJYcXRrlVJgBi8jrICswxDNRQGC5D20vc9xpPDcH2yEDQwVDJ94LHCQBV6LozWoRWlTBCUMVUe7B2lHjH5KerKQ0+ERjswK+VxqTpSdUnbcI2m0thaLeeCfP7II18qUaleuxp0AOBaqOV8JUKKiDJJZWZTjfSZYp6Hx6clZAsW833G43bMNLqWzuSLfvRvaUPSuMwr0pfY/F6caEatKRozpiDZDx5uGIl04EamewUXxHtgclDNoe4isOBgSX5CHhRvRYs5DxDN/vgNcpB8xZ23hyw8eRP20SAiAiT8HTmRNEUJ48HtMJfGEvO1DO5RPcUciMUyJzfyLrhjnhnyAgiNxAnTA2AYjQzpM+yQZwd5mcQ4ay1TQSlJWkQeDMljGhxqPlVcGiQJu8bCu4F25ctMwfA6p7ZrERKFRnCQg7Y16uRYfDhmSdSA5cm7jVIUF2AC3lFgK8lIvBDOnkiVQZRGLpojUcgZEOQIfYpYVuaSAhWjFvGOrFYZlssL5GToMDnxbcrKpLZjMV00OEM4DVOOZJu4nszAU4VUdHNVIVJTiay3thvOPcNYB7h+xh4PY1Y6RjwlA51CINmkiJd5QI3DqaDD8nA2PfPQrb1idZaPaAh4Jtgl9kdwaxVPSJaHw9kNkIoIo9slQYNBjsim1JPLNdr2nwbDj5GDZ7iwBcr+iXC1gE49VgXLy9ll4YlIRTKahqgLP6XrLDqgVCKDXo7rqDoCfDeC9m8mALmzOpGM33bAExb6LIBlYyAhQQVNiCpayLQC10eHrCO8H5+tZwvV0Tbow8iZVhcR57arojqlozgj1h8ItM3huXvyP7FWgnUPfa8/1sjmuv1+TfBQa7G14hBXXG+ht0vQJQ7J8BxhMIQHtu2G83k/FcPofCdBMqePfDs4/BjPSffvyE84cznp8/QGTgev1chuqwS4UXD0aKjK8YrgMxcLB1YdcnhL5B1fgFqBl7okY6wfQzw99nkDuQBE/jfIfLAua0YOmcTwYoiMyR8DU5K2GH6bq61pMWcDAvAbD98gtOP/zgzviOW7BKr28ZOd9qN+78HhB56/qX2/qCMfPF/Z3eq8312fv7TFbCMjIrxn40BS7/+JvjzH8YHfW65/uPXx5/1DZXzIj3y3/+B67/9d9rzXO/PqgZnv/dRvRj1+8rL7X8ave43H2v62cY0gfusNUdP/a79/0PWKtHszt2kf+SOV4Q8m+6aj+MyJ/lAUDuaEVkwT0rBxbvU+G1ijyx7BVStkyZ+TDW48hXeaJy5Y+vN38LBUqhSQBS3E885vrUX92p6eQlPVQGdhGcT90yLyHorL3bmS1AIrD3od05uJi3/b06F1Utw3q/ci/BPz+aNyUOfbwSNzY8faJn7HhJWjAOEbNaxpnnYunzeFq+9v23XV86Qnr3u/U17z/+LofnH/f4eMzfqcl5P/3LZ/tbGwikXxit/0PXv8GA/miDAxAeL3A1Ak7rpwlgyaTBN6gqDNOYFN1R6f4RuzKvyfwZI75//BX9+x8AKF4JOGmdieZBT0SsD7tY2o95VWMMlr8OI9JVAIlHAj7jraMHoGRv7lyv6nd9YchqrjG0pO6AR5qJExMzgCuAMXYMadhkA4alomIm9M4QCWWE11XigX0b2Pabp2n3mlI6EN7P7999QKPmyhPB7mPdblsqRkIoyXrdw/5uveO23UDQFFSZGY0YAw1M7ptItudCcy3uPEoVCT+pnCuGn5UpKdJIuagoze+IKNnv1RM4DFcXANfYclrfvTmE0c8/A3/7AcSM288/mYMBkEbuCY/TcDFhZVWaLaePJjNamYkB8zG/+vdrWS52gsX0Du27eSankq0yvC/TU1QfnbP1e8JxnVS5Pv70TzcoP1m5hmeHuxd7c3weGD5qpg8wyBZvU0Hv1QVDTx+nJnQBfm5hDihpwIwJB8PlxkWrx4v0rI+VD2IX65o4gef6psImDBNQiCukAGTNvX1YPfeIuGywOurcCI26oznC6cRmzMxFpQUW7xnFuu/TcO5vpsI7DISWNnDOHWkIoOyPiVypC09V3xK+2ZnYiuMSZxdcDTblbQQz55h8XwL7VaPEEUbMYCIgdFhc2dkWpSwCuaK2kgRQjJXzMMx1mK3b2saJ8h2uDPaSv2k9DLGmK/ULY7PhQ8MRmgqBMHxCo1CEOF72vfHGTLHqisYgh6RQMscmm0tz2HJloDYznTBjiOAWHhzRpqcINYWs5E/BCEfN7TRSFE41ItY1EN7hd2hkTfA27rDBsdjDoysilQ5A4F9X/vzQ1sIq0MI6zAb8f/XeXSNuaCUzqmf98lDqOaxZpNBwBWoYOdboiGncsUhvCi/hElgf0eetGXyPsbnBwaN1ii+uktdoh0cpOYtELnlv+4bP15vhcuasodyapS4dIl7PlcC9A8MyEjRukMiEEMsTyC6U7NU6nksXhswACXU4UDRRaBogJk8Y0SlwWAthKXAxqGLdulXBhFUTWIwhzpXzVW7UA2wMpIBQREnZXEL5Ge9MqlfBoZyDpc/1Gy3fC46gA29xRyx1rvWCTfXuuWWuqOOZjcY2+cwNJkln1O9hDycu1Pk+LEoyDKk0dozAOZi0Dgh8XnH4JAHRia25u4O+IWDPuxSHAuQpby3jylSc5zu6tiKHtvJzouJ77HNYZlr+VQP5NJTPuZez4OtgZ0Cmodd7ZbISEHEeySMJVM1pacjIlN7X69WN5+ZEx0GTdeIYKE+juc5phBQQ0XxDxZzZaIAHrJwJ+ZoOm8PAHP8o6aNlRN3l6eS17GnZh8bTSCZK6DrjiYLGqUrW5SskY+67f4RMk2epGC8Sx8S5rUo6Yuc35ikkkGe6mptMTVO5H2dJvc+aVSeOigSOdu/FKI+l6inGiUGN5z6FYbccNYUpnW/bhtt2w23fsI89HYiH7GB0tDWtT/ZTz83+qgBuaJeaN8rBUNd0frEWONDjQCmB2rL0RkEtlIfYebtI9e37b/LdBUphBBY0EgiZM3XgWtUB1Y79KuYYgBNAOzLkF4B7mID5DKIt99KJAiLlNj1x1mE3PFGAnwhyA1RuEGlmnK2CPQgqN99b27vRLEtbwrOPm3xsNk8zFkpwSa0Bnj2KGqNzn44xXiYtHHIVCkhkFgCGAoxRZCr1TDKWgWBG6Ibj1vB/ZmoPg55AbbMTt0WNe+NZxI2nlgI/ZC9CROBGzKgEavbTYvyFAmTZpiwltzruoaQBj+yFazTqSq9CZlchwOdGMANpGiCdhgceTzh2ek7DDKiRU5hEXC9jfcWKx1nIXef5GQ4Dlc8IGpZRm555bcFRGobS2Udk+Yg11ezY6UOmC2cQN3diOcRVFZmu8rjmOGX8MnNdaeMdZcwSGzPS2zHeTSG4QkGeASSXMf9lSRbvlvVs6duvhkAUm4/rXPCkOb8xrJyX6X1i3wLhwekSIRxNIgodSuZgJVZ5/bbvOIuCthvAzflZAlOfPHfsn0ZWlTsObf1GALkjO7xvc+CysZxOHac+8aaUEgkUaeTV9GaZPSYN6BN2Eyd7do1H18Seev/DcsvXbb8B/eSp6oF934CdcXrvztLuEMbP76AvA0rXifqWHXZ642nY9eUCfdfRIEsGPNtPA4R6//0/3idd4gac6J1lC8AtHaTsNT+7Xn83A3f8nsmXhkvVaWi63Xt3kYIZgb/uFkcdl4b8DA+CcFrlDYXi25yU/E2dhvSNgC5zbd4y5ikc7/z8M/T77x3++O65eyh8+7f4/qV3vnw9eose3PuGlg7zPupMH/XCcDJLZkgHTG8liix10d4Yj+3skdcr4zn8Ha2IKC7/+R/49F//fffORzLD0cf7bfkLXjarT44bv9cv71wVnSb+mN/f0qF+60iOf911Xri+b72mszGlI1/SwN/Y2ltPBxwaHrS+WjhZJk6ifCb7JwSiwD0mDohb9et3j/yO8S7AnGya3v2ej9XnH/V7gJt6jJkY+264fQyzj8TaGA11GnYc2oEvAErex4UvockrFkFqMc8dBhzrWVf2RJa1eX2+yhjA0M+1kQdXPRVHzFpPzpe+P2pr/V65SC1z+dL3+vzsLXY+KNsMTIlZ078wVjqM9dFcvv796zTgW+hWzRT2NbryV73+jSncV2EkgccPWXo6ZzoIcmHaBIWqJKiGH2OIgUs/YYhMRQ388PrOmnFhItOIxInND4Hh048/mRnGazw+D8UnBlQ/gr//G+QjsOHXCVKpjDEk9Ml7eF8EZHVNViClSgRL4rIihNAdOC9ATDXOK5RGlGk6AimCyFM9K3a9GQIlMzZr8RAhj+ZUVYwBXMcGfQWYFY1POF0IcK92VTFhzxlecY/3275j3wm4buaZOQZELNXkGILL6YR+OoMGwN2j2XZTIrIS5LYbDHjE+Nh3gBinblHv3BjscbumxB9QDJDa+0wW35CktEiFxICMYbWrXAlhMjZZ1AwUe1W+qacTg04B1l3QNIxdTlYiw4Cb7JYDFoZBArDh5UDkgScoXh8hEkcyQoTrL78g1BlXcjk04CP2D/N7qJFXx7UVCT4p8JkUH0ApZBCAV1I8K+MZAI8BIUtL3NDQnNj273oKLESUnm8GboT2A2P/FWgHRrxGmd9NFTYv9/HGzg2RsIxjv0EgfYV+BhRPOH93hn4Q7J9MWdSfn0FMuH38bAZRungLgtsnxem9wXIycK5cDeMUFOZyHXsbxhUCGp9TGUHOFRAIrFWcm0SRNO310DCQU0udnp0zgYwd53YxHMYmEF9OzeufW4QB+1kjEFojWD1vhXr67ds+MvrBGNTm8GL3M0LWcR9XxskjmdiNf6IKJoGl2TNFSOdu5RJSYUEAm3ILFBH/gKq/kZEdYWa0SU/bN0/8FJCpMKWf2H6FclBUwb7W5AYGzgg9NicIttqVlhTQaAaxOUhwszS4nJEHrqiBAidGCOUFmSMowmRXBqYrUmBoPzNRDgPBZOrkNmO+vmaZ+jToBQVKUcerxnymQULVjCSyp1JNlWdEbJ50NzLC6BuxKTVICCBLyR3RSEOsFh6IoE0h+47ttmHcNmy3G7brDfttYLvt0OFGEcCVQn6OZSRNW9P/ktNuV2ZkSl/1tOShVPLjprPuPABoK5hB615kjBwSmQMI5aYW+psvV8If11EioAmnqfz0MxQvmL3D5jJgdFIUEB5Q7jhrA586rD559zqaDdy6O9gQLLoLIBEwNUhEri/G6+Z1weFRpJQCjSpBZAcz/L6achQ7dGwQuUFlM1gmhaKZwUJNWCJxw74rlgcs5SfUDMbunoHOzeq7sin49zGguxnpd88uMoaa452Fazn/5fsnvgdx7l1571yfK2PNAEdidV6lNTQF0Bpa5WjceE1s47daZh29davFlcrt6GbS44ANAOlzbgZBw3ddnQfwVPrRlzpuV6pwqPOfw2Cedr/HCL7V6EJGoVDgEc/0kEAYxjiHuzhjxagXT+ZIklWzdVV/19SPUod4aMEXSEzhG46P8fw+rK620SJxw7cZfRrzzKYyTBEe0UF1ynDlt0XBwWCtubOOH4GImNV4JyfmVpxydqkw5IHXAFOykpIbIoEeoEe7re5uOCXoYOvNnIU83XEKkbPRZP4JlDgqZIOkSSM8WTxaGgQo5/w5/iXQeFYFsrMTRj7jJQfGHk41jh89elBhxgN1w6kCaZRWjcwRA/u+e5mNqB2KIKwJ653NSSqUJfNcxCpbpPfQDdu+Z8r4lM+IcTp1tN7NKa6xG/9c2TmmEW/XqIluOYe4dwgGtpvVTo3a6CA/1yDo2LHBo2Udv+4eRTtH6EOmg1OVrph9SaNIcaycJrpjjDoJNIOnZZeCB29HVheBlyRhhY7J+9XLMgA5D0QBJ5zGIhCwj82i/6UDpGDqADVLOdy6nYtuRpWxsTs0fUbvDfs+8Hp7xe22mcFUkIaeyLagFE5tlPvJ3KD7Ff1yBolC22cAjNbcyJkLEKAcRslyCDR4M78ngJDCop4Nd1q6aMMN3Nhlgln3uLM768UzPNXmNAx+b/uGfQMIO0AnbJtF3hIPDN2SJzLszmA/n9wUltT9BgZlxikC3PnkCe252zpT1L4EtherVdwuloVKBRDPfKbdz9irgE7Wj1DI4RZNDCLwyWheaw2n8wkAWRYOnkiAzxNYqhMBERlv0IzWny8Xo8ViZcaIzFhI+zH7jp9bIsdD6mmtd4gODBluJJ1Ry1A1PkEJTdWTOoXDHhJXWKS9IdDe24yktBNs54XsjLMQlCduDV7bhZvMoJHOaKCJ02ODQFniZBqhJ6ts57jOnJKfjUMoCDmhZn1BGqYpHHnFDMi5B35OZiYu49lbwii7o7DBsckvfq7I5PTOBouGTwaIgd4o+6dmNUTNkyb4dxu7OUpP/EvMaCoYUKNnYlHDqWwlgiXhcFOjMwtVzo6zq4o0KutuGWCCw1DPIhayxBiKTE8mbI62se5kc2nnC7bbFVDF5uUTGi5QvYHoFQqgOeLkp0vuHoGhV6dVwx0R2YqpMRPAhovIaUhs/BCTgccQMHeMMTxbg7epgn27QXEB6557xCSmD2rTSSxkCSWjoyG7UGtoPNdPFMAYaMzYZct1JhA4yrOpgpgxxo59u2Hbd5/bAMQyXigU27anDEGeFUvjjCm53CRxVAxXiJ3RlIUCLij4aULrJ+z75jocmZneAGBsTmMDYl4heIcGxulywfX1BdwI+twwXuYBy/MdsO33BwGKK0gamC1YhsgcgFTVHFx9Dswta9Jy63aWG4HJnHuunxiKV+cJZ7aF4NDJ5T5zvhkz2pEnHenNnZ+cRoUz5ok7hioGBrAPC6jw8mU6Bm5jHAx0vt7Bh/vfEaEKNTlEvTxKH4JdFawWRf00Vzy2KI5fGo/Gzz+jATj9/W/YdK1xH1vLNSMhBf95zClhPVSDfuxZZEpZuR5Usn132T2xYI3jb3fy8no/gfKRXvLBFZHRH/y1Fs04Hxmt2L6UciFKOP1Hx/jvOmb7fKkiGNb2PS8NfvrRw9bfGOZfIX17TNVSsduGfQr+auViERMRAB2awU3hXPBBjd34hR69hXz3uB7Hnr521ewMx5Zy6NEyRfu09JvsRsoklL58KYq4kZDKzmuWDYxGaPa8NErlGWvTEjIJCALqiqaG40gc5xgzDVKvq80MoCV9DP4gM5ikPcBkKPHDFvqSWrINKI4+qRdY+Zslxib+qjxPynPkvHiiCv+0/sTLhgZa0Wz73kwLYJZHCl6l6M2ILNOl6hwvF12HDYdSF2vzsr1QL2kShjPhyb9Ydi3nQ+BR6Akf6sEK9u1dOCIy5bsAUi/YwtYgtsmqmryTZEbECgxzbY3mTOeq+dzxvbfaefR9vWd7vD7z9vfQVK19H7/PHWQ0SGqga0DZ/HfMdXI/fvnK74+/f2ldKuCqBzNgOZsT1gB4ZqfIwlsDLPJ50aTVb+GrN0sI/A9e/z4D+oIQ44CG4UdTKDCE4WpHImcCIlIhDsY0COXGKsBo6WWcaLkIL8E8TVw8kVVcLwT85w8/4PM/f1raVgDyq6YSCYl0DchybwVQUjMgUnk5nnHMGA65UtfFMWak9/O3HxKNwofktyQE3j47IzvUvegbmZGwCCiWqk9NOaOKQcA2LIn4uZ+gNNBDIBEFvJQ0NwIQ9TYsSmbXgajRGlqrbdsh+7C0O6ezETERd7UXU+YMWLpJsrkaITQY6KezRxS4hxMU5/MF19sVpna0HefWwZ5eeATCJE1lrsKMRyHkhcZzKg7WKxQSCCJZotGWNwrV8uE7GJCPbzLLgWMMFt+B8Ll2GWCSDb7m9zAiBizED2un9f+ZUtYf4QO79aSEj6x47wi2AXivs24gNCJ9AKJ36B/MkJp9hUIiXdLcg/zjW6zht1/kiosw0pncOQ+qeU6fwI3R3xuhCWaFnVmbpk17bX8ZoGcCt9Psp4wyTSOel755KrMxdqBNv/ah9mxTASnV9dIAACAASURBVKghdzbWmbBOWEMQGmhuJGS2Nb+0hnaysXMz4VEFEDYluZnLAfJoj8YnKEzgI5gg39mUa1CrfxM41RwOYEyq4xp2ZX7z6J0WivNYV6e0YVBvzYheKJoSNJQ9bZwrTMmUyEasDUYiM8RUJAJgTgaMfb0lzxhm/bhhqSlJzMDH0YYb0Kk1I9o0x2QeFwqgmzKtudLXXNKNYUcYXGeUWD1v8NVLyAmlGEni2VTIlc9IAYpQihSFx4SJoFkKLXOOVNzJ5JaasuZ8ZKk7rXmazDKlK46tsSKZY6tfLYb7hDOafLhCx3A/W43VSAc8LMJx1tB02BXBGDClUTDcpd5tkldWU7QHjdYwavqcswYjJiLMNUGmK1+vIyaZexVw5auBQNfkOL4+n/RoQUQB96GujS2vdN1bV9iZ89vqis/BjK6mJGyN0xmHmXHqfTrnwASC1lsyiXYcGno/mfDFjDE2V3pLlooI+jFGoTeqgJjjWtSiNljWhPOZUYPM8O9KvckPheHIUmmSz6H1jubFaQUKElNSmqJNoH7mpyU0eB/r3/p25XAlaMH3eKreMNQYv6BAm/gaag6MTRq0wY0X3Qwy7Dxe0iEgHFDy/XLeYmfDYc6GWk75/N8kVrH9wS/gXqkQ35MDIac/WrnPSfsTBsseTiV5HXwuVhkHrEZJadUEWkn8WY0TOTL34BP10guBDG3JIGPHvu9miFFBJ3PkYDZcG6dL/D8KpwlMljQVxGo8ZWRdydqyXvog6ONcyOOc1XkNe1YdnwXxCvqR+NQHYak9LdPCNFS4sKaWNUapwmjswwqXKNGHE/n5Pvkm2D7OQlEcfBmCbvge5PhigsYbpbFW9qxhSwk/Zmjek9cWN5DZ4g61KPRMn172WioOY5+bO73cC53q52vMNZm/+JIQzuczTqeTp8lldHdEi82JtOwj2nEB2OqVCjan4dawZqrg5Eslsq4ET14USHNjbO0rOo4/aKLCBxMon8Ej+zvOC1mwrCulNNL/h1WdfJplXQNOyvmm5u+Ucy6jYfCO1+sLem+QbunZiY0eUzu5wsEj+MjS2l83q3e+bTds+5j4OYaf9NKHGDtFDGa1vrYdKsMMS2p400LO3aChgogSXiDC4YAooLEq3BymRdFgDo1ojgcakrdjNhzd3LDVuXvq5Vi/4bzSJ2AIRmvYtx1DBNvnV8P/rZnCmCYfVk7qGjmPqfQECHgy3jAj/h0RtWcvz+TniN+xBbd3RTjx6TsGnI7aNg9kBHTwsc4D995AyhgerUlEOL07A+Blj9KAyyZLGH01B3Bmd/5M+B8T5SQen3AOADrsrElxXhmyJ+1PfAwrUSVyzABlvzMR4HwzNzvXVB60TFCm9rQcEdMYGUrk6vgUDlz2EyVvl0E0eV4qBXX48vOZymrM46+YcJqlYtTpDdz5VDCfgckvgTUaN3c2d14EmJGirkA3WAmn9iCxBaergKj5OQWmM7KNKfZK4Y4LmN8DzxpqFK+v7UEOSiAZSU9MT6EATuYYqcAuwdvZOQh6EXTIjHAKwGRGJUnjVLITCsOzvn8qgF4VTAplTSW2rQljeE37fnnCfrXo5KHu1u77GEUYws6hDjUaG6puQA9nHJ8zueMzYEZKUcEgzkhhAjkfTFCyNN8Dim0XMBRyAnqDw2qUHmpTX+FR6MQAyeRzzSkSIOWMFlfwzLwIhw8yR5fJMRqNqyUS4HvZgv45PjWYEHSYYTtplhsfwmhszgM0y8Ad+B9zYrM9bP0EGcPXWbINgkL3DegnN5gpts+fgHfvcX19CYpp+Ob5CduL6ZgIF1huwwRNw7BkQSQnz0hmA49E0WSORk6z4fBK4ZDOnO2MsaM9MfT1CcPTxJthzdc/dDRkwSyV11Cy8QaejVPYW4NGJg8CVMRwWmtp6BlR4kEjO4wRzEkaVqP6zJgxMwWYo1/ItWY8j8xYdxHZy46ZQRf//Mm+B79TrielLIPoC/iwLfhe1BZEzYk49yJ1j5j8T9nPOar5d8z8mw3n84dlrF+7DF+WeZE50AbNJv0eMwIR2H/8p/PWk7mLETzrakS/n9XXa4k/nFPefnz/z7rmOL++ngq4wWw1qx3ffsDVT17h0W/feFUYy0xa3kpCU/A5ZVxKh9nRg8Goc8o09Vgho6feLAEGBaAm/6BG8hb8aXGWxqMSLNsBw4rqQNSaNP8yozOZMUItOMA7rXNQ72wajzNPVsoxSWP8X7SaVPpNOFsO7Cr/6/Jxv3lHFLOyiXk9gpn6XTGXV3Hffz6DwzQIWcov2+Y1oDMVZdH68j34vuDt5gh36PIbYDwqAA8SAQYpbiCcmO7mts6y8pz1+7ICbzxf21m/V0ylD77jje9a2ljx3ey7fo9QreAn9PD7l3d2/f4rffn3x98f9XXEQCZ/AsUO9GBIoQcKOWjR+9bnD/Ttrxil/m+MQK/Xo4Wph4wO38sztB4E+4vw7nKGCPB6A7ahSExDtBDMTPEz2Y/SuvX5Xz/9hGeafcBb88Ro6a0TSbRqCxP0gcsP73H7+WOmxAbsRS3wuIBvvZ/KQPsYLrFwpo/FMgMKpv04Fl8yhSu8htc07E68TDNZIpMU0IEhwC47To1nCjlMwtGogTtBhqI3wSDAw7lNMeHKehFN7zAIzENZ3PPf5XBLSX02AzgsUiHyxFp0H+O234wAE4HE1iE4coLV/Pg8rnnoQtiN9eHDYdxdYbfjK9cdmBS0WO7fnG5s/vm0PDn3POIF4MbzJyg+fwNjtTAw2QYw2Zs3Bzx/95c/kxnOLyjrg2f0HzoAT80d8EReS5NWpk6doZ9KDtuygRdDrbSO9NXffFpGjfQgB8wGurmC4ubvnTC9MIG55q+/Whri3O93Zlg5PT+DlDA+u+LBFZzt0pYzVZn5wCLTK9y9DNXr/KVCK5wiYFEOChf8Yr3CywqZBSMWwJTNllWBQOjniIafhjxmr+kthFNv2DdxozPAvYPiGedqRIHegZtuhhcCPcacwpqv0/OQcoz+3WfP5NkGIs1kt0jaYDYb84Q/NuUst1AwEoAOEKMXJW/Ujrc+K8ZGEsue9b0lz7QQgccOYULzjBpwmCI3NpKnuc0lvhlw0ZlAnTzCrBiCk9ktTE3+CDc8BlMkqewwg0ibhp2ITkR4UmoqmKfyzAFVySJ5cmM8VaAKIFNwN4MI0oCjnv0EcIOjTDiOg0ywVLsWkRn1t22tM/JsKBSbKXk0akb6mnkGhLFL1tYdY2DfN2OQxZXpDvtjDF/HuZbqY1lrFrv4wBGJHmfusUAhMum0gXWlaD7nOwbQqPCSVnVpdcWBqjIFroUOTMY1+q4/P9YhKFTJDMppLAtDRqRvtzImcOOw0VlTxPbeky61bmdGYZkFZMCdJ1x5CirZEyj7c9BM/ENM7qE7HVaSf4oJ+BmEmmExjYKuEDPHFDdC9IbuHsGqpnTinSHqUTYOhwQqa+Sc2IG3T3czDYVzcFnwo2dcVMDSfPcRR47CZMe87rYbsS2puI/wtfIAQVMZ/0iGyHHPW+VfOMzkw3Ew8o35p67j0zlkAFMgfjCGvCaYexReaTBJcME7CdE5YYTyW2R+j5TaMVsF3ACqsF2/U7dluwvpBKYSQO+frecoj8zSpubCaMXbh6eWyxXpCB6PFBGdH0rxmFVFTXGGqpEBy+92M+SKqJuahhYOXOt92kraGdZhtKLKJnzYi+IgkPNWjxIIFO+R7xZpXvcVdn6JERHsZhyZDk2kavQGSDr86Jpbdc97KqwOLe1TqS1DZs3ZBHmdzlQ6FSUi4lGABl/ESEeAUD4Nr3VucGhzyEEFjruD43r+6pqu+5h8nKobc8iz2cAjxn2NixHluAy5PQVvzD2jgqoOJ0RdEU/A2AHG7jKGz2bb0c7dar5vlp2LYNmH9mGOk1kfNuDVD8ZQgrIppuUK2Bm9Fnoc8tl5ubc4JRwAYq7z47uqGhKnlcNSj9xjgUg4t9vnwA5C97Xbnfw4DRlWcmAMc+Szmu4Mve0e5Ui5tAhaAHgk24Q346nU/K9VwXSGKGO8DOyNIEzoz6bmMD/RBmXxNdiBoRDWDIFhducr54fHtpuzEJlxufWG3jtO5/NkYQg4nXsakVrJcGJzmEZ0iz5nuMeGGQ53wdP5DGLCPvYErjzLmbHH4Us1MzWImCON8YWGA4nYI6MJTXkaRoM38YW1MXGJBGHPMMYQj4ptZPXPkemyg79zmklI/sFwqJnGiDCNh7GeC62e8pAZMScfUBXRE06DF/M9T95aE3nPcxt8x1Rqy8LLhTHMsufZcVLL5qAEIaC1SRuhAu4EaHOjIkNooKnxfq0xRCKFt8w5xzwinVBkXQE5TMw5hJMmgx0e1WGRMjKdYg3VIuMNhZojTLheHZWMk/yWWtyBF+x2lvwL4yUQvCUbnrm9IiHHNyk4iB2byRib5YhrFzdbXmwvREPHZi1IGvAND0TGMnBH6woRc0gRGYBmcm2T+UWhO8DPhK4ndD5Zqb4meG1XyxbADcgsJXr3f8Scg//0PeCQU3XS6qBvxv5YTXgrkzIJE9F01k8Y9N5Mzog075MmT3xgMAoxx77GwffGOA1mwuGjN8bukcSz3Is/u5sxPNK5Xz9ZLkSGAvqE9r6BiNFc48LPDH15AvR14tnTCU8n28fr66sFt4SPCc52Posag94RRDdzhGjdzqjLH+rMBmnQjpxwylYKgFtD54arO2uYjsAyxe1jt0xJAMiDc0xPM9IhuRGht57O4PB9Pbmz/iDDLN15Qy59gAjdscyQwGnTgQaYWKqKFVru1d/qPU84iL68Y7D0hFl28fh+2f3Ddwpmf33x0fVIZvgfuqLL3cdw9huxjumc9I8ozanY//uf+V7V7RGmsfk4la8ay/9iVx1u1D5/NIf3jn/mbzbzaowFbJ0e6aqPMProt99yvfV8OAfWvUp2rdDZlDkS+QIhs9tvk3PnxA9GGwP3TCq5GlQT0x6OhCo8e4UH+5Cnb3f6xc7XKDFqUgajR1rKPTxaD13lxTdWqDoe3Mu4d40u6/gYH+Sj+Zy1HcGkHjh4eC6+78Nrnbv8EnrcdPijyD7K0CGWlRhGeYNnCZmeMO0p4jJc6LAMv1KKSVl+D5MfSv1bTETnnG+uF25Jj4fTYsvade5mdH3drGSMMuFElLzdCKH5IRL0jaW6gnF96fvXn9Wv/H78vo7uW8cSEEduBK+/HyHjcVu/3Ckwf//3Y68UY1y8Z+bYCevO/F+4/gIG9ONyJhp+8Nwd+njw/nzesk6acJg+jlo91b99Q5+++4Drzz8lA/BKQMdHq+2CaUR/q00FcP3502o8p/tnACzOWo+UXpOBj79XoI4/jk9YZHFhugGYNyuBqCfDzy5QwD1/g2gMEZzU0qWLmPC/y8DJlYiNGkbboWjAcIO1KPbN0mqqR9IQAET6WZU0qpjRyA4gE0HYsgiYd3QI+rEuRgB675YGloYbLUyRYAo+R/oRYe7OAVMbNRfd6Prv4ziDaN/BkXcDTYfowjD47hzwOYOMwY5ntDQSrxEddv3xSfjSbN46OQHL/B3nGofgb2Dgyk0CVC1Vx/j04o+9A32wdSQA28dPUFDOcSVJ8/wtn2RjuMEM6Ee/shvMiH6cg8JrFXqyd7wS8BSeaQR6B4zPpV8qEfUIw7FnOwgjVfTikw8mIqI62ZWBTIx+6ukdZwqS2a71x6lwo2VWJly2TH1u56E1M6w1UiidIGNH7yGDumG0m8d9qBlk313xaClQOeO6URQrxZOVpsF8MrG+G8TojTP9JVNDd2N1KOlC6RCKNYsIhZd0cL/P1rLWGXsaTy4MT6xt1HcNdpmE0khM4jkRxkAt+hkG+XmAfD8uYaQnVIVSXfPJ1NVxIMeQ9CGYw1AEEBCWjVg9hU50InDlhpS25xmOaFxTsFBGgsNLSVgKJTUc6kpLGRFpONLpqSpPyPcLjh9T8ND42/shQXOjZww4ouqGDuz7sIi3bce2bdi2HfuwaPQhw6ICnTMWT1mVZqlgjv28rHTJ9zWEp1R+VpquczOo7tTqYqsgc05wxYh3DnRvNwty172e64HYq+ADyt7U7u+MMovhIe6FolEzOkj8uYhU41K7WHW38qbMIBqpPGQ6gdgicnrvThdhdYWl1BMmFyg808UcjkdJsSm1o+/YZ/LsGWl8AZY1SsVhOfvmkNAMppg9+sEMAJI0mmcmGi3KanEhKtoPR5CylJpzSnW+/R7G7UDOPtiVWkQ7kz6aAbwIrb6fSwYBUSDWaIHN0rIeosvveALNYcVZoPJYwHi0rOXeGt1Rv/uaVBpfuruTecojVY2qXlbmMJj5pM4xzalMo2dGM/oZmaCi2Vb4Py/wcxxbNXaEIds7zFUPX5h6BN+8Jq4OWMuOHWaNDDndjZB0Ikwj+rpu+bf3r3UT117t/94XsUUzsEc9hCJ28uyaUQ5Ww7PAiI8HRFNBE0oJx0kLzECLoTnqjGuebfZoYwCgoCMyzBlUwiHC0gdzM/ocMzpC9YKKY13yT/KMUp6iNqI1PXI2OVoFIgMBaNIEESmwBbDYb1GzHYqJIyO7mONxdVyixXA9j8mE/qqcye9U4KDArKqaM5AouDyvFVaO63E835Vh9QlP3y9NnKAkXp/Yrn1sUIShze43nCCi2K9Xe5YJYxsQGZkBJuDUQmecz6RwkuNsK/idoVGc5gw++Y7HoX6g1DpYbrDQCcU9vMT6R/kNsZTuSs62KGOoOdk1NRlu+kCRw/JwA7BgiEK3MAIRwiEu9yJftTlY0ItFwIua0dYSq1mU3hAB0wAuDUN2DChYGSrDnRsnzlN3NpsTc5lBGafzGbftZmdQRhqzIsm2ZUIxGsuRxSnykbsMAF75Ac46vvDgbXOMNcc3i+adxnPrV5KGxJ5JZnxInlE9UpQM90As20aL+XjK3OBtiDwrAU9+ufm5DhgYNHFXFkUjc9wgIU+xOXEcBUfIbHvjdD3SeDrggNgMbirD8ScXGAzJy2Ut9X1PnDKNwPG8RkgZYM75tAZKmJ7D+S3H0UKwElXexhBJgyl59HLARegqTAY0Bb9l3fCsJhqqZl2c2mKdJ8frq0SYynsLHba2na+dTqhhUAhZZhp6p9E75FL/vfL/PpZwbspIa1XIqzrvVJc9ZJrYBVsxeKmI+cNBMk/6FyhxbrbCFOnz+E8HiJyH0xUii14O2cLOuiIywZECclPQ2WXO3gAtKeHdgX1IQVz+YWPQMipyx4mYAjmc+GtiWXqIFPs+M6gs7AfDPBCS/sxdFhU016st+JWCTnomCkaWaWIuzqPBz5bxhW4B4chfSinE/tR3LFHVK+TTU/LYwSvx+wb69GxdsdG/oJnpDJyM4F74vjMUr9heLyAw8Exo3TslAnXCCV4yj66WA93hN7ILgIDT6TR5AHfWCHCLTEGAOeJEZkxxj4wmxmO21gwmvHQF53jtHGWWCJ3jYyKciSz9Nx1T2s6rRoK2QgNjDetnvQgfoPiY9OtLzxaQ+MrlOHbBa4GcC0D6H9aX4q2Wo52pjdTjA97tWyP+tmvFwPY9sn8Bxud5cSNoft6/+0dei+OJ1r/x8P4f0+fciXAz/FC6iBTzATEfEt5SMs4r3v8SPD3q//eMedXFrBcd7s/x0MRZNCEROtc1z4S3H7TLZKsUtlIPoGpZtyyri+QeWrsr9CZ+45algyoODV6YmN0eYriU2YKViIrjn49+5Tdi4prtrr/Qgo8rYNU9e9jeg/V96zr+/uj7fRuRUSf2xRxiw64Vzm5WvxyRXyZbDHkdmLxFtX2JKtRlmChtEXO+wzFlTLp8q3fKTpPxNtsYmTEsZG9F6FVp2Yy51ocedX3ia+fjzd+p0N4/4npLEVJw+69fA4w3ru8dnn/v+29d39rc29Tof+/1FzCg//4rhLVqkowN+vj6iqeTpUPdRRLCj0j/rYPt7HV+772j/f1v+K9//nNKCQoQvQfj00SMroBVMiNoIMmfSQrienAdD3jO0b8H4QmsXGrpBPKoL4RAtbajptwuHiKW8ogz3VAw0Qo3krGlGwsBbtsHWmtW42izNBot6gozg3tHB0DEGIMgZCmvQqFnhFBB+47P1884X86uzCie275+RAQdtp6nk0XEhSHy0kypL1C0UwNGCBiWAi10lTYPE05UdHoVYyWIWUPybl/eRvu/5YpMNIvM7PsyfciofH7blQLbBJSFMfnW61OkRfUxnX5V8A9VtLBV2H59yQhXIXJjTgjvL+CPT6D3hNuvnzLxVyheAKSxN05CelYWRqQhIvbtOgNuHp/XcXZzj8KQ/gR5BcaTZppEfRLgatFd8qrgd7FuKVaCm41Q9qi/Qy53lfOm7rEHZ8JaNdTG2Sqf9hJAyPRjNufyTJxvX1urJ2pp2KkxWDtEbG6tW+piagzxumvt1EHorkQ7gXb2qC47B5GCPtPf5jiKETwNzpQpOJkYjZulqqQZYS4qOLUTRMTqTLoC0SLyOsDNGVfN6PTGLRXvdjJt2qIC9mgasLpSwwx2LKaEIyIMj6oGYBH5+3BlfktGxup9A6RWWzRSbUZavrzOLtRj3dcJTwdmVuM+WQeaCeLmfd/nzDZQlCrleCbuEVUMr18rkY4z0gAiItEivS8y2kiKEYkIHi0FNAE23a0uNTcQC1Q8Dapaam4lcTxKaQwYKhj7wO16xcvLJ6u1vg/sw8ptiFgJD7BmFFE4RYShJ1fBYUrEIlxj5hqLFTVP3GBhSmHfhQhXJmTU3nw5+hpOY6vgT8CQxf22MuAhgOXOalEgOB1fzurhCseyEAWM5zCjRdAZgUXwy2hQ6QAERD2FwTGsHUvBb/VTLTtAM8GN55giA8HR8BT1OOPfrDsfvIgvX+KfMLDYPAS8rsMDESsFWscFjS1VevdnVYEm4sbz3Wo4D/GUy5IRsqEEpLKHM/XqdKLw3vKdVWwyYwLSuDb38k0FRwisqQVNAPpm7j2V3Vrwvhb8sMC87QNCoIszX0q82DPxbsUxmPe+MJ/w2Las2Aa/rIVX0vt+pmd6VdxPnjl4QSJ4BKPO6DnMoxpnMoybc5jeXqHbR24z7q+KKSww8Vuu2M7IVmT9zwFE+RBy3rU62GR2gdJv0J8c2GE8lDhn9tXI0tJnzc0CU7EXlhUpFMCaxgGOfaZJixaQeqSsUksbK1CAGnq3qK3Wmn8a0hsi2MeObd9xu948unfHEHIj+8TDj/nceKScX4pVgEcODudhAq9Q8tOR0UZ8jsnLq2aq+eEpV3c35sTv4bSBOLYVnqGAsJeIWulyKLhnqm0sz1SbexjgyHktU+KXesTQjPRNklD5BdXSoMYD+dvd836JLZ4/JhCxrDOxPwSAtg1DFOK0XmRAwW5A98htXuEl9iloge1V5ZLtxA+9WTScKqDn6eCnE7aPuNS+3hAENcXFgm/iB3V+bZBJOA1m9FQSK2tCApaBzg3CI51ORaw0zx7Ogc4PCSlIq1PkHBtF34R0QhSIpWRny9BCzj8xrEwYPMMZbp991U5mPBWxNOh9B0StXFJZ184ngI2mnU4n6JDM7qMwmOu9o586ejuhu3crk+FVMwbZ5tgZpXS+UQX6yZ4njdS8pohs3Dyl8SylYTyAAlpK+0A8e9vILEaRzSGjgVrLM8ZtRvVPA7oiss0ZL8zgZvIat+Ic5xlthAmgZg6txfBodTglfIMQZQGSS6MD3AZ/BwU3y8QzS/tOuM4Xtfyps400JioAsPOm4fB6wBNO+eK3oIoilsJ8V7IyCp7qfhDAYoZZkEXIttY8Stgy6kWJLHKHg3Cr1TAE+phNvOI8x+a8I6aoTkYj5iC5P4lTCq0gCucKlxFMAJjOwgcUtESb+whFBPo5Nyujliv8I2lf6EXMiM7uoC64zUcJGLAMcHy7ABdg3AQ8q6NlNgb2EgFJhwIvkyZswuXroAnsztqAlVxoT+YIcv5wQts7BIpTbzg1d9BmtqwYOWtNXRGF46ZOWg3AeNiEClv3fupGX5z/ZCaMfb5PLsuk7orIIhvV+BNqbgCKtOcB14XmBB0hZoSBWKGZ4c32QXOdem+Z7aDiRj18VhbL7r3mfQKAT08gKPjZ4RKEse+4vn62yPMYrI/PMsJE66/e7hWMJ3PM2He01he+TKHpJJyyhusAiQn7HjG0RZPr55qIEi8T6nk2R6ht7GCY0wtc75BnRifflQFDviDuGmw+umrQ3WHRvMG/39FDALuEc4M6/D/OiSUABB/B+A78PQG//JLGzmX9D/v0bdecVzo42GJXBDufLngw5LFje5PPur/3Tdcbj0bK9ff+vR+eUwX2H38C//37hcorLPr6Udr2f2E4j599Y55/tPE824UZsQir4UUB/OBdmnH8XudM/tssprD+9ujc/xlX4MZ546BXq89S6N7vRxS3gl6bswtPGY5mqYUI1iMR7J41TRP/TeP8cVyRVWey6U4PjAGdfEHSXyCN5etI77591Spw2KS38PN8YJ7Dqi/81ithNvQ3b/QXEeHkjmuR9aQ1dprjMOhG6uZ0eBvB33OOMbC6ADi1hj0yjQElkIUW+KzTbRHgWPDUO7WSBTcMRJBGTEBUcdt3y9LV27RZqU5zmB4W/l+8vnqO/tju/tDrOzVj+d8U+MlZw1/+wLHOqR93WFNfujh7/R+8/vca0Ck+DhtzEJ6IYHVv33Iz/Mbr//3zn/jPv/19uWdMlDPG+GAMHT7m8C4ItvWPv44IM4WucrsKCBW+w/Mw0mwzPCUvgE7d7sO8dYOxD89OJfMA6jLAY8PIiDQXOhpj0waG1YQbY8dgwibhi24Cyc4Ah8JIZ6SNEcMyCTahRDDcqGf1jrd9t2hhMSLQuIHI0knJsFplIWSnzJKapiBWIV78WezGvK5AxEYjIn+Bo6AzzU3vALzE70eGrhCdNTV6MSxpSVn3O6bH38125RcBf0/Yf/lkShSE4A8wWSrMgMcdn6Efp0IkUuXH/GP1q+nSmLL5deqvbwAAIABJREFUt5bPSxnT2e9dYVHoVF84XFYZ5QJ9FeCpTcNv7n0I8DmCMgZCOzXopsWzuSXTpECmPQ/h7WC9wkwBDo9qz87mHAuDEW0wbC3b6WRRrfuwTBonN8apEafeeypjbtcXnPEO56cLZCdXDrhiLiP9fDwUtRmnsTOUNPW7pazsjj/NcaW1kj4aPl4ORxtG6xa1ame0gXm+z54W2jxMpwHdSjowlCzlJIZ6JJilM4woG4t2KSkKidBPDLgnenVOou4GSmb3QJ3v8pmBMevWHpVtb10TB6734qJyz2TbVRA/9jFEIJ7C1IzkpkxGKrbZFTaRtldnuk5XeAQgWfYNVxywIqLRIR4xpKasBhGULVKs9VMqXccYuN2uuN6uuHqaQvHxSZ4YRGf5t3Vf8HZC86wPnsYUzO+L4ifXKrxbNcImDI5rOnh/NwSfZL4haJnuMYQgn/eiEFn3I4S7Jcpp2VFThq7OM1M5tDhfjAH18ibWZ+CBEOAGwlhERI5XetZKj+ibXLOxW4qx2EtVKDXLMBBn2FUzqkWZRlPvlbVfI4EmzfTKdT4ZuIyyV0AKsVlbkuacVAZkNOy6Y8ewLRu+t648B2FxBot03BTKRNhAl3pJbkhJR8HkGuql+Wx8Luz7ctbuJRzVqfyfT32JG6gUaV07+5QC20gF/fx9He8ioBfngLthx1khyhS0sSIqNJWxB/CuHvqi5ZwCtti5Tc57DXfM8WjMpaQHTW98ib31f7XdNAjnasZ7cWbDYDPP0HFP7lY9lOC5fvebQx5dqR7lHlGgTDNiMrIaqP9dcXW0+yDAOZ9N3OYKoUZm0E3WwSdVa+FxKSdijiiRyhUZtW6/wR0RKZ8NpVQ4zoSxubkT2ql39NMJ/Xz2VKamSL7tG66vVrZou7kxlTx6FUfF0OGiWGYt3+fsw4hAoOkMylEipKURLtoII22kNY6sKeH7JQXuJ9zqdMCp9zHxae6R6jKm2IdwXptwycfjn/NZYdD2j4tjchqYAl/olKsUcAddj6rnGRVeUIEZI1wOEj+zYxgPtJNjx+bGkzE8I03gG/FMWg06Cu7wcVLSAoBoyzMXaZMVZ5C+zD1JWuhG2EIbK2SIw86S3nIuPCZqVkvbzmIOzKpQYRBJKj+JGTwYg4c5nxSZZIzhNYWLAzWcHhClY2AIcJkqso6BzXmNhB2ni8mLOrDrFbq/g16vaM/vfPgDunnq83EFcYeOqHdOCD/Tbb8Z/fMMC+wOK9ysnFFvzeq6c0fvxvMS1CPRFVauxdqKCCiLajaHk34y59QxhmWxG3s6jYJgxnFP755lfUZkLXD+wc9ROJBEXew8D84Xq06FViVllItrnybOTPzDPOXxcKynyK6hwGgCGjYvJYDYDMsZwA5AS5/mP2cMR7QrYwc3K0clZTjBj8yjPWE2qeBC+6bzgBwRd7nU4TZStjNb/WtWtVqzhCwj1hpSb0T+HJ06oO5Q4HieFTO7XjGyVedFmtANqO2zDp+fWpRzPBNOFXFm47XgVyOrkWXf4nkmC+pSnXyJeM1uc9r1UlCOX/OM6QWE20PjTVxmoNzqjbyfnZI5lz5SmytNfcU8wwmISHfKMo9JU22q4bTVtIFuhHbuYLgzS+/u8EAZppm0L+ZbaPSsV15gwwfAHArgUhtbFLuM+WA5XzGnScfdyXjM85nLdjD0zOwCsx8RBbeIRtfl3d4Z26YP4fueS/W5Hf5WvKLh2Z73ebTeQa8F6ZM5Shh8nKF6fQAdrxivT6Bno++NXS9haajM+f7pPbbbZ6Di7lV6yrEv+lw/h4nr1Aw1JieFU6FDW2bwY4e/RAyJJyIoh8iCP04wg+ReRlGN6ClhOf1PfixpppOgAy9reuGPYP4eSt8B+JhG9H9FDW3o+rHeD0Q4SkpHPpuiDRQQjvYmll11Ioe5fel6k7eEOxY4DSAA8qPv34+K0z/+DvnxnwD++OjIObbj2mj5+/H9VSD7Yy6CGV2OdosINYha3XvQgvIeMKPPH7X7x4/2vo/8+wAX9OB+zZgCYNJ9IEus5Eo4r9UosnJYym6CyTbhdKrOXGuB0Tpvx752zl0HCMAzHYzkKxZH37hUM/sPEHzAlGMf8cq138iYQaW9ek1W5TGM/VmOG4+uCVuLdgCdjbcl2P7tXqpxjvHQTqV55V4+SxNej3a5GQAyfxswPJF6Czq063qQxoxT77jerp652PfqQC9TZ3/cizf25tE6ffGiw5oU/vVbWsjz8EhIfeMKw/i3XOGY850+dvj6U6+KlPjb5/e/6frLGNC/FXUszOGBaiRDDuA2BnpvuPQTuiq2fTxEfLW9rzGd/++nfy5g/sLAd/7bwEeEwpEKaopvk3n5bUjyqKCcP9h9yTSi7vG51B9ACijiEY0cNUd94iKCQR7pemCm7IPRGpIg6RCMsWPfBa1jRkyoRaUzz9RaoZRs3RW1EPQu2MSQ4xhqXqiqkGGp3pt1BtmH1YRtJgiS5VvyOrE+x32HyG6Kpxy3eu11UxqMfZ9CuAsp4YEmJf3Vm1cImGFl+BeuK+699aLJd1gZow7CExSv0MfI1ff14hB2VX2D1317hhclXEnxpLTUZAIA+VVBP0zP9O2XTxAoXgC8g6KDzBCSkVarAFKZdQB4LqOh8nf0+1yeXRk1+x6GdPG/F0asvFOFeYFmyn/ADblPCngkpqop8XqPJDQ2aoULqqeOsSFTs8uwiIlcFIcNDY0l9KA0MQagpkScjGb0OBVDmZq1GNTI65uyn7+xubjHBJWBsW/o/YJ920DEJgR7jVIoQK4Eiog8cSUGg01xw57xoAjyofAngqdcjzqvlEa1qK/Mnmre8B5nCj0weU06N1x7Knem4mwAgMgihYQZTWARTcn0wCKZlHB+13HdNsiYcH7qDbfN10YJdHZlMhNa5xL53kGdDSft7Gnmp8EyDaJkKf1qJAeXzVRXtiwwnMoymt8Ls71cB7wsatF5Q6y+7b7vXuPQYdSlfuuzKAJ0Og0AkX1EMbADw7OHuPBhcBFrTUDvUCUwD4t6k4Hb7YbXqxnQt23Lsho2CjO6W//skeUAiGHpxG2v2Y38FumOXNtpgympckNwKXiDUsOxMr8qU7RPmNAwduqiKLEOgVmLOHbqS4h7nvu5NbHmA5HcKr2Cs75ifR8ZIRh7OcYGkYYwbhMFHtbSZ4KC/8/iF8QFC9lnlTN2Z5Dmyma37Xh6YI8SLfChyq70BiJqOWl+fCGLSku3rbI3q7Bj+IFDedlgtXe9ZihAILXI0gm/tp+OJifvVXJ3T0HT9iwVlWoK7Ye7lfOIGJB1LR+/UxS3OdvaXjEUZL+hdHUjco3+K2f+kXH82Hf9XZbnHvCjUuA4YL7834Y0nSXrfmVa4sQVy5t+udGR2LNeDDdkDTd6Os9KqyJVoa6QFheu31pjg6lK49fnQng+OLAsD5X1KT/VU5qnOvCgR66yl/rJ6PBc/jsV2t3aHwd690T0xZZ/AoVnTkyjc58IHlVBFhnXglehqFuuUNYZmW4/pmE64C5gvLWGUz/hdD7jcj7j8nTB6XxGaw1jDIuSZJ4phT0KgAQQHV9U0ISyIya6fq/rKLktop6JwnmX6RigM5uKqJco0eX8VOO5otxLQ6rTD+d/2a25Mbe4gj6HoeXBzGAKtbmHYVQJfBl7gty/CTiBmjNvg0hpudB+nTR6Rk0YDIqnDGci9E6AEsQdBQEFU8e+eR1rjXT9hifD8WIfexpZyOWyegarO8uEyduCB0Yagw5OcXOZHqwdCnzr+p7jYQEDNIAwBBKlshwUkUUM4ZK6XGdpknA684Ve+MO7EQVOiy0S/5sGmC4gmDwyyGjg+PjJDDr7bvzQ1WvED1uH8fKKfjmbHAPNMgcprYtln2mnk9XrjWxrjcHdIrXNOZTANI071kQ4VSAjJKGWsS0UunCjTDpeQJyXaEA47zn+FZ1nKhx7g3eokmzg7+QRfU3L8Z70JYAoeB6qijbn4cn4MGaBDLVgZCLQIOwkIBqYPoiT1xSPUrd5+99hbFd1uZE84r7AYln/nOMBLJdSDXEz+HhvKUD6aLQlAAPGO8oetUHtnHUKZwDCGApyFRmrgrs558caM1sWouF4ZIh4yaeAfVjq+6RzMW7H7W5Et/NejMWxtxKc3eRZIsV3Y3Y2ynm4cqbV12fiMnNPyEwfAOiJIK/u6C6vQHtX1r/ghK/wVnVPCAQ6u2PPOXaxOoeF3O18+xAom5ObiCT+A8iyX42B8+mcmQOZ3eG0N/RzB6Ph1BsGyGpwh6M20wzV1Mn7hswfOB1Oj6AmL24j8LE7qIfMt/DVkcpeH5SLcgxMQG9Wo1ugwF7OWek7oqytfIOvVvLr5ljUWjhkKMKaMLM13JvSjmflwdHJ8zHwCnmx7+f3H+xMP1M+qKpgr5m+3V7n/dKGjeUV4wXoeII8T9mkoaFxg17D8UeRPLsIdiCjHkN/GfS+ubyzb+F4bDrKIcMTmEUWQCB0F+wpmRfnjVgQTxUezxGAEThRq0ENmXoYQMoz6jKLqqQRs6bRPvKlgYlPf+vYf/oA4CPI33mbC1svmqu1YsYCS6RTCg6Ubh+FUn+lw0dBBN8aWPC1K1KTf/CxnVKa1wxA2378yXGyGXqkvPdnXG/N6880YEbkOWDzDKm7+d2Am833Ldzew11JYZk5K6z9SrZeVdb6SN8OX//ydRACH0WiG8s6eVNgrjO53sDUhcY/cYugl2lATz4aAhp+Dp3upXTkeiiTuZDyiMlkRpuNXXR+E+VcOb6S5L1H8qDpjvv1Q5QHrVLRmbnyt12Jf37jG8dMxMf24idxOht8FInZZYSdn4HxLVG2pHsAWSwDE3u9cbuGB0Le9/cIO8ZPevfElexsRIgTh+yWNJPxfDnh44tnlHJdQ2RHezTfdR10HcKbz33b9UhOPgZnfFM7Sbe+fn1r83W1j1rLLz372y5ndu9eXhHR2xLd/+7rL2NA/z0X5f/8cqGMXBB/3Tac3cCTSbFCmKL7tn4fAL2A8AzxNO4o7bzieLr+mGv1nnPEWRXEOs0KFBSkvu+fAku5J6EaUcUYM7JEoejMgDbj8yO1EwhDdujoLsyrM/tGJIPpJ2roBKvTJg0EMiUKUcgNqURVsvSGluZupkdWNaeAnQhdXWglgNDAPKNIbM81ayKL7IhUaincJ3bTnO+jTf9zGBBa+I0jr1EZ8fjsIFwAXB+MKJQS9nEvyAGHbX/8CC5q9aXu3kX6gyezF4+Fgj4ElWV0bzAaj+Zb/3g0tiqMHKbyuC0AkfDd1vAKBUNfCfzB8sk19vRnISe6Qmoq80PpwpYesnHpwRXzoDTCqtTRrMwwgOkLXZBVjeqL72FUyNbUPVKJsA8Fmu1EO4WBfGB//Yx+8rh+ImzbDafzGcxnUwztmwt9U7Ea2Q+qsdyyNbgYSyHEI40od4wxraS+Ks1CYRfGawKlF6hN63F6IiKYImEuiuFzNwi01vGuMW63HaoWNb3twzNPEEIBSLAIQUs/74pEduWmr9OXGJXF2JwDA46vaFQHSjk9mMFIr3cP07E21aimEqm/zZgFmGKGm0WKDtnjzVSum5EsHLPYz2pJiQsGtt2ia0SSBnBroDHAnV1ZNzD2Hfu2Yd9u2LctI5oAuILI+/ZPZs16nIElLEJSnGfKgxUIHHfKjFzEKmr4p9Ja7xYFdy/3Ig7ySHUrXv+NmLzQ0jDwFZuQ/1ZHNXG12c99P8WcIXrfM8VyPW/LLMSczkgAIlPLmEFh2D+ZxT8ippbb2QOPFCKvHjlclbAA1JzapoKlGKgDZ5FgxojTimwdlnKLyAx45uW72z6B5/aGIUTEFFNEbhilorT0NavrUAw8Ua+ZvK3VqPVwqxDOJMetDoVpIPUwNIS0HBGtemjvEcx8SeGi/jKV546G9hQU83ePWJdH7c71iIjLZWTRV4G/GQFfj9QD3oac3sWzbtyM6MZ8yJmFlU7NWq9zTFOxYMpxKravmPujdSt8KZXvZV3nssUaz7YMHyHrERuOMjxodcf5oEgINci6LlTvLQM8DLue/YIPeYHj2Xb1yA8azmRRT2loxmwnaq1GH4FLgheJDoiQWVV67zidL3h6uqD37uVMrFZ5v16TLlpXxqsFXXoIzXQ4A3S/LPmrzj0ZJJlRQgEbg3p6bAlDfnW6uI8cuTsndU/KGILnTNhXzfTJ9ew9GDEyHXk5OZU0xRrcSYKOXAx1hIOPFFwe/NU0nN872Nh7QxUkk8chTw8kFr49FYDKELlNflvGHANm5iDm1YgeMoaqoj+dgX0HGrC9mNGYL+FkE7hd101OuA88Oddr0oIH6ysCYTcuENYzQeZoxWKOeNOAHjWkNXctfpt8/+z7SM8XdK0Koos7jBlvBHFjKu+WEn4fGNfb5L8iPbk2z0ZgeHXfvSwLFKdTT57RShlZZqPuWR+ivFFrzSKnWqQftcTBU+60dZiyuGdIQ0Se0eR3FQinrUn/gAjPzpIu5SwbHrF3c/0dlgKkI0JzgRYtZylwDijPATeT/DrMUV89upyEzFmT4BGFapkWwGASCBHgfI2U/b3H30FaXGeDSm8UD7XPQSySNiwIAuHstzq6FDzq/QiG6Rm8nQHxDIJkSZxcFhrOZyqThaq6xiyjYLU4UXk2LHhWLoKVDwvWys5w0Fde9DSKyXPnefP/QjFtkefTEYqUQO0gg/rZrmdL1DJdWVSX8yav3g+9Atqh+orKZSdOpok360a8JUMFbpo6N99foiXLSz3j4lkoIgPHPox/HtsGpo52MjwZSvWTn8F+aeAzQz8jnTsDJ8eOB1kOGlGw/1JObRszOXLoPobzRIth4ECP4jPgjdnq6Z76CUMF2+22ZKO5192FfoUyDb+qWumV8mvCugNz6wzwCfse8oHikUE91uDR90rpxstAe25zX4P/8/GeL++wvw4IXo8UMq8dr9AXC/vo797nU+1dw/bZmyW4090AJz6osEXL5y5jSnh+vrVCo5/32PtwYiKnuUGzwUAL/rRghOA1bM3NeJT3ymiqbmZBR+Uzng1jhfwsoB8Y/e8d8pPTNrXn3inuglYWyZAe3E8cWdftvpHFGBOEKJ6MNS/il31/HIn+rdcjeHjrEih2/DKHBwLhewA/Lenu/+jr3rn5jd/eYnz/hWtiJCTsxkob3Vl/ewRjdW0YZjw/PvdHjvzRPtxFnh/0ZevvlPx65TVq+/ZvBt6k8bwxWvJIwWNYGZGppJ1jiMCecE4mdv0jU/I24s43M0sVQqjDQhkq8wYsWUvveI4H6/Uwmxnu4e+oF/gzrkctK+AZd4BWeUxSDCULrFEBxijvTP5/6pLgvLEHfGR/BdIV6fB/vCxzWmUKHkAcVV6DsItAXm/380q6/+et5ZtXQcN6+P7vur4ry9AwSwj/z11/gUX4H7j+cgb03wT+5bwszAfgKbYEL69X/P37D3h9vb2Z+qQ2VolcfAZDBeA+TQeek7WPdrS0lfPxSK2ljt7dyN++jox37c/6caMNhUHFFSCHCQmpe2YVNiyUXMRgWLQDUzMBzYXJ5kaqrHUeU/IImTF2bDcjTqd+AkyGRyPGqZ2gJ8XggbFtblRQXM4Xi6TlMKIrZBdwd+Z5N2NZa5GeaWRqKGOYGxRXXC4X1y8QNtnR+gnn8wWv22ZerPtUGoeyXVyYorolqGv8lf047ODX4DYEy7eedPnCDebWAwFoCrwD4fOdUcn2+DWiFNTbJ83Ijxzlgy4vSriy4p0DyEUJN5q/1Z7oOwL9+gzGC56dKRp5Vuiri/Ub+PD7d7OXqWRbV7GS7HN+2i83KHaIMm77Zl6djQvhViC84qHrSXRDayhkGjPQuytPPUKMfVRUT+O84sgDmMqt+M1T5eazujKfVZhhZoxtN+O4SbaADvTzxdOsT0G39WaKr3FKhfrQkTVvzP5PPnVyxtU84Bm8pNkLIigqgFh00TrBWb+0e0rwIQodXjbDW1Axc6+kQj8MlGtzqXyKdY91UM6ItlA/98sFTIQtUm8ypaKinTpOsS4usJPXqeeeyQJcAT+ji0NInoqY+yuV7lSZSqRxAuGJWZToObc8jtOYmcouT56oEqnarwlREvVioZahA+Rw68wpzfSdZpMS7GNDU4pFtTIAhKKkibRYO/axYR+7e5tGtHQAi83l6PQBiEXthKNSKLlpntVQTEgw0rnGIThgokTVTMFqN1oy6NPoNcXLaUg5Uuq6QXS4BwTETSPX0ag9DVmxx9CiTHLnm0C5ocQg3w+LQN9dCNyz/IGhEa9NnzjB64cLLP0piiONHzWrBUlobUa7WZrKSEPsc29nUAfgGSrU6b+IuFFLMz1w1B+NiEYwT4W8zLTLyQPn+fAViufJoumgBAyBNLmLHI/tm3DjjhiAOQKpeF1eKYpoM8hENYLj/sb5sTSXtl6c9BUJX3mF0r3CXMIo3AFkKkGnUqk0ETCLlReLfbSRzTNYjVOL4RzGMunxN53trPc1YSz3Y5mjG8QimhOKNKjXsRaiGZFUorM2dXiTN3JHDcY8BD5xL2FfwQKz8bhCzcN36/Tosq3RpH9hDNDcKHcqWTUmZi53/DAjgEOvQvk0lfWdOKRgA12/z2ivuFFmqDY/AWfZmsl7xdCK8YvIFTlerxwAdvOiz+acMSimxXQ4Y4m8UdbXGANMG0ZvSw1Ui8yTjJ41x4jhuH14iaSIil2Gu2xEvR9ON8l/Edx9R8uhDrAqRnJ1Azpxpp5WaNYLDn4pjeGRTUEkDxxVQc038hh5DvUUuVHT9siHHun3BOP1bNRXXBZaS0qszeyfvZast9/eXbJxq6fsc6LCABXVUkQwzt1WWNLOlVcIGBruQCXD1oduABqB3rtTkJciDtzJenL+w3CajMprlKjvBSmva5V48bB8JaN/XnkyBWiugIuHsiY2E4TM0Mc04Rk5DiSvNs94/Hk4iE4XLUuJwV4o8PhCSZfls9NpdLAybi8vBncOu006VF4huuHSPiTtHTqS91eFRVvD7p/b2TIyNYus5NYz2wW5Y4w5mSGd+IPdhu958BPhGJdn1mkUqym7zOHGFcZKGa1deUbjn5MDye/LjgYsgR6kGpZ8fp4tN8SHM4cxjVlaSlVBg8xBSXcIA5mFgIdltVL1dTb6rZ41SmNNZ09HCFtSrtYrIqUC99SU/4/oTDgKB95LIyiZnMMHw7BFlRJYNbMnsL+nMtDQgKYY+47RFL01KBj7J8sMwWej7+TOW0TmrL27Qt/QW2ToYWC38zl202lEaQtVwa6We1zcoDfLWhyOn5fwQskwNM+2AZ9llyk8U+K+aO8CxQaoZ0nz86MJK+WF0v+ddJT0Y+L4WarHcVsrmTkw5ed9N+dhy4a1ZUkrHQP75w29MUR22yc3sBAxuHXI66TZX+I35k/OxNDUgHFjL2FI+fu272mUD1l9ZoWZcJf/ClZvreF0OgH7jhEOtLEuwylm8IheCibPrtpnIzs8Qyxzic8w5eGQPXs3/HHbdzts5Lj/OP/DvlVYUljpvf0TLIsHuUaTZlbEdmH0JzOEBzutDwBheNFKeR3Q9w372KAqIJfHY93CgUjDcaHwcr0Zf7N72RcVRecIhLJnrVa8ZUAjEYvqJdcDxIpTrLXJWdOlgyZ8z4PjPK2VE3FfLDRYFPAdvGOm0z4aNgE7Pzs+gn75Dqe/sdOU0o6WZx+sYyWDWn8uuCDuBg+WxsqDHLQar94+I7836vxb3mBf5uCElEy3SSC0f/wd+48DjB8g+BkA8MGf/fRo4f/g6880YAKrMaueOUIkylgpYYWnSNX8wY9IwwprWtr6s5dqMZKHjFP6vTOuwwb3KEA15TQKo3cz3oobWm9oUXpJYXrS/8/dd245jiPpfhEglZllumfnnPv+D3jv7k53mZREAnF/hAUlZVW1G4OZ6pQoEoQJhDeDkn9D8siOp8hlLZMzWmMrPccT3onsbN5JGXvwOlbq0/cl9kwkgjuqrO7zUb7v+/ZBpJ7gN++sq1mev5lC6Vflj3tQ7bdnOTbFGbysSov7bhlfcq/F+OxRoG0gJ9p9MCbLzuNG9OPOe86beXT7k8HIGco3CoCFVGcZb3S+r3tWRuclkN8Pdotcj1yoGN1h/f9cDDCP6i9AafhEmfXC8cl997rf1nIOh1MQOiMTfu4Jjf9B7V/OgP69LY5DnggAFrUTii3B+5fnTPstmJD+vW19Blnk+G8dE3AUDf+MVon+xPg4X4iMqvXLAk2Zo/XNudQ6N2HCFF+OLknYvJdTIeipZYhZmTmCCoAANlGFXR8Dz6enUN431tTSAMIIMMSMQVJWSwCyiN/eN7S2YD2tGGNYbSVg3zvaAoAbiATrcsKAYFkY+87gQRj7lqmG4Ugrmcl5bwRJKv/c9l2oRLJWumYIACCCFxC++hzuEM0bg983mMLLwSusAXgRNdTr1a8AfspBlX7Fx+Aper9nXsfxVQnh8UP6/8LFHPeJapX0HBhcbNBHN4xXAr14ZoRQBZu8LBMc1shrjzgPjEM0c6s0T+FIIH1v/DlPBTZbZyQszjWjQjAOBcfxqimcZbSouZfLmO9qy4Leh8nUqoSjuJFSSQut+5jOAqW3qmQlm4vQBG/iDLJYPgtT0sSJkvzr8n0oqimjqKqCz5WRvt+aHtyNbaawWJR5bqKMdmRRII1Ap9LvkdH31KkQhEA6JTUVudnDwKumeVJykgb0YHMFUafchhNzq2fU03FG6ripZqwL9KTYOhQ2JZK2MK0iFsVI6vCk5VIHCIulFkUIPBEMIRr53i36XXoHxq6pfm2tIpqDFX/2sMvZvG9qjM/7XddFb69r7D8erh1FTBEUsdvWlPIWOMgmFiJDGnkWaeq7CoKzApm0bhaRMuo1nfyEY91RwXCGnyWTGHvv2PcN26bCWGtNU6+bkFYFut41+g0ddk9h7k2YYBcOXciTDm5PIBrA6R16f4X0DW6Q8Eh0thAPT5E7xGjkK5MbAAAgAElEQVR1CH8CthIJEnOpcDiizrAvcfxjNzCoc8pYtC6lO8bM++wwjuiHmxmNJDCx4RfFHMPKYnAFh+z1Zl8SV5X9tPUIw7zMPEHue/2LqVV6I3fuz3skYGwyDhW6kke2/I7M6HK8ng8ZbBcc5E4w1QgYuEJyfF7bdybhqVAPfHpw6JrwpuQz07DszrnRzRoi5pdkL+6xIx5wT7gxnuQ7R4xL4A5dbjSjwFkzxcYBCRU6UCTK5BqQZ/vOMMTXw0mlJD6R+u6i0AmjOhALEM/UNaUskyAAxLMC2PqP3tGJzdhQolClw0uq1GjI2/rS/s47zWvEx/mZrdiqzyJLwSxBw4fRqSE93u+lkdyAHnviPGM5k2FYMHmNDgxVyjHzmYeRwDBIuuaqHJdpc8vE3ZgcCvmJBgA0jFcrQHAgVXFvf01XA35G8mzwc6oDGEMwzgPykozB0lQmku0KQMvcEEjTgzNH9K76z6XDKr8UJ41yThN+s45uNZZXg09Q8srjlb5yzpXI3nycIGrcLpLeYZFDg6ikH5ZJo8NhW8tzkagtENwMB0PXUaVVww0gkPFVIhsanjAYYXD2PVWHjBWQa2RiAxjLshr975a5yB3XtEwCQXW569MyRdsrXWSTHay0STirK9EUUcWk8sw6uZo6GAIvtAaYE4ZmUBLl4RkgV5sbXDm8sckp7DW4bZM4nH2rnGC/IZ3tw+na4KEqttF8DjBjONl+q8PckAaWHX147riBYfoBFrcZJg8Bp0dxXsmsAYKaPrkCWcjtDsMOzxXWqkL80EXwO9CSWNs2sK5LnH/HJYPSMAGbC4vJHt2ipnoHETDY+TcP1hLdq67144e5RXHhQ0x1DFgp7SE9cJlHYzGpg/rEb5R5iOlhHK9K/ScZsT72rhG1oxrOD/yLAMKiGRngMDevWexXWdibXbI9dr2RXqPYd72FY36uj/N3DPHI84Gx75p5SwDBFWMsZjBN2GMmc0ZQ5z9Pf9/HjN8ScZcJkLP2qSc8zrhrKkaEkykIo/aLwhM5irS0+uuyRCnC3rMM0xhDDQzD6NmNTqTINvDyapLjiz9zun4idZzve7e/wD0jeowb5eiVfgBgsJaC0yJ9/s7KUz/gHw7N0/IzM8Z2P5o59mlI8i/2Wx891tbpNFM6DjgutUWLtauO0Tp8xW+Od7WkjqVmNphxB0Pnpyr78NZc5c5nAcLhAURa2vMXTY/vBndjg2KuB3E2rtUjF7/R8U7fx8I/1TbJYgeYK7JakPnCl2nf37PbP9b8SAqAjn9A/udnAL/CcsfkuvxR7zsw8rN4deRXfIzzMzfr+p3tg9yfh1EBALBU9vk5x5B/3ZDuRrHfuiu/5dl6du8ayW8fyM8p9BZyX2Q1c0Dk5v8000840ok57FH+A5kDn58hQgTVgTwC3dLBe8lIUT46eC3tPfgaMl7Os1a6A6piqNyJkDnq3B6sxcSbTD8caDBuYRS4XetvtQmfPxjTtzrwDDjHH77lZJIGaeM/6Djtot8oV0/iz2aGAoWTNO4DSDlSHHcKtJqQbt6w7FcHUnkrwzs7I9PXmzl/9xk54M+b78etf/CeH9zq726121//pHe83f54+vGv1P5tDehvNpqVNJfz2X+4udUPEEGJ1xL3yfSEPIBwMbNmKsleAJw9Hhwej+5vukVs30J1RwCcmUYXOm8NqMk8AoiwywEVHgYNNT4BEBrYjNFfaTEBMqMevR6YM4eNOZSqow/s2I3R1VpwoxO+fP2Kp9MTltY0usl+Bze0ZUT0ABhGMJVwbduGbqny3JDpAldrTSMeTKmhxtMdW79a2mZG76RpifctmO+st4YgsLsZ2T0C7ve0b5CW8jcVho+ecUj11O3PzoCJ4B3RBK8u+NdUUE/DDTla3/yt9mQG82domj4G8F48ddh7W/+DQGqNfR52+Rjd8KjdG5HP5x7hflhQ5IZbmVkHHc4TPLpHIOivA3hhEA20ltFLmk6M5zSC8RqrRe3g49yWCxzTmMiEeDP4EdQo4Ur0GJ7Ma0szex74ghRiGjdcth3cu0a9NK3Z1q86iGVdsV0vGPuO1hbIICzriuvlamkU7RwT55kIQx6pwsM2QWvOqOJuDI2icGMNyKKCJaO0XEEXii0yBeYY4G4+i85cWfiiG+rdOQTOGFtmC0/BpM+IZqZwxUzTyDYsymCtttep0DdjAaWihIqCjIYLKZ6xQ+cRaRIJAGvZOilnLwxw5HWU8jrKHAGJaDEAYchnZIQ8gEibLCONlBoZ7IJ8KlkUZNjkAE/XbLPYx6QwhUWPurHdh9V4iagiN2a5gXSMgYFUQh1hemr2HIYYXn+MY1LRiRDWk9EkoG8GU44bkWcrXnsw5ERYWwoYs4NC5Ywlfr+dUqWL/pioIZoIoAZIn1Ob2o0ZiZtrFdEOY1gU3jWM5euaziIcgqEaVZgtghgEUEfzEhGkzmYYLnBWIRKQfgW1VedRomPauqJD7DlEZOhwJ4ugPmSr6xgSAeOuKFOlUqFWEv9RBzW2dMPSNfKuC7BAS7F4/2KGv540pDrL+Ehilz2dtej5vlOt1z7nuFwA086l/HYw+tr/VPHfpuu1uWKeQBP4HwXCfHcRyKpkJihjPPzuby5rWp+r18J5w/sjZIpa8X2bjeejjGOiZ8X40UdXhxmjg1xg7GY9bs75TLEdB1H8VqYjdwTEB2Q9I9CP6+IENx0+pRr8HbcYKPiZqcvpke4S/R1g6y1cVvrRTox/cCcVG4QrhjxVu8Ob1u6cYdYN3TP4pQOCj0kM73eQRltZzfoetMP2HLrvPWolGz0RkwRqZPX0RjNs0nxtmr14ilQ1QN2k5ZM8bTIEXVIBLiIYbPvm6y71GTF2JwDIV+kGd6Ns26yAKmM/bqMAsKwPNXK/3hDlSozn8nTMiQ+HOVqeAMoUgoQrgBPac/QEV2ZXoG+tYccZDXHj1JyHcXmlGWzvm69hypjMFJHoo23Bx0EGerdsAOE0JZGykuycb5dLRLUSgPWJAFpz1R3QK0w4Dcf9Vg1J07p7KB9hMhrEOfKvw3hlyd8j2scGJaMoYe1xpR0UezUgGGfAne76uCheM5nVAaiL8+iUa2+6VmYCLycsrHUeW1sybfS6oFnUuPOGrsyt+C/OORIMlPTbWMO5oYP4BBLjcamBm0QdTuXFtTa7QOtwyz70PJqk7rx8Y3VI9xrlIlLksuK04rix0BV3nvK9F3HHPahc78arRSBdwMLgweBuqdqF0TDQh60lAGFYwVeDNdIEPt7CKF/4tiMLlzfrufDMcU4HfU8dJhQuDA8V3jz2RZwXQ5byCgdqMniS4JmIBINEU9QzrBY8Yd8BpmHe7oTrF40lZDD4WQ2aNBqAYeWsGiAlG5PjPhFLmWoyFFIm1GlrZgYZwxzJzZAYizPN3FdVnawMr02GSgByLjQIgjFWEF1N1nAvWQo66nyu4jU8boI85A5bgbPcAZSNZc1zsPehxv69Q8bVygPqi0YTjPMF8v49gHQw6+bgufcLtqHPdotiH+pBOssfBY78j/M5x/qtuvfqtNLQAr/eGOKcblhznO3Lx6z12t05gaHR7MMzOMZuOX6XwPN1oftQeTt5lKKjoOQXHMba2tCvB6WWAnxFr6hiUFAD32/aDb8NkJysTMx24BGgATeOjMtZZIPVxg2b9RV8mJN/E1AD7VsWOd8LL61H9lnIdCszabWxCDzC3Dk/IoIM43cNFisdU9qIMBq5/DvPL1yWco1Ql+EOIUfqw4QIA1+w0kfrT2uh96kPFNpx2B//LjoHUS6wvLkyPmR61cKHxI4kTZjGeofnvbnvd7R3pZug2+Wvru0v8Xs1JBOA93JfVLhXI/29/Fjt9EdzfKydfbt9uPN+Kv+07/m3cKgo14DHxi6HQwKmGul+2j2t+1vP/9YWcuHh8L1l6E2clWP2u91gzaZvZPvnZarG8LyMiPNBUB2dRBCU83BlbG6U5xbZcoeoM9IYMvEbPi4lCBZ401gz6slBfxD8Y8LIcT0PXd9ZkNsf3zprR7j4VnPeRUzvE4FZb/TnvODEfMP108mrAMDSVlz3LbmOA0sQTvDTRYtSvzOJCzRo1fkBhjnw0fQ4XNdKzm8Py7TYGmgAvO+ggK58OPQdhfE8yofy4PN3NcFN4PtbNdAr/vvR5pksvmeMHyVx6T9ozoLxR7QJjm4OgdGfenD/Q9u/sQE9GfXaQs8GPcyfvn7FTy8viHxyb4Cf7vN7AF9+y2j0/XgtCd0Tyf5WD7aH7Wbec6RG9eSvgk8qwwmDPOVYyj0e+eqIkIfV6AMBpNHozIzFutm2K2RofWmvVUzYQqjvo0EdnC3lKjPQVBlATMG8RvSrLdPoA1gYsnecTisgBF4WjOsF0tgkcVVy7dcdaCbYXjft0wVOwFJkSkkvAlS25bcyTD/enPmu7PeDd4vghGSYXN2vRkfnYRSyXlxkEBQSIngRQEA4PzCk+yj8mfXjB+yfPqPhPZafEzXUCKsQuBzeXGgRmU1dZgRJ/c0dRt3/8wctf7oX5OyOQkQokIgh5EqJWyZmOkv3zq7DqlHLyUuT0zgehuCDtBRKicL8hZHdHxBXDAKn0wljdE21bgqw9emkyupt08gTS0ffWDNuLOuidbXJ3DbI5hLv9IhWgJsxkKheyRp1TCWte9HH5ZeUS+GbOYag05i2liBRm7Z6jzduFu3DUZfOUyy6UolgRjWYEXJBUai6Y4qPyw1w9lXUmjiIslxE2UafK3w7LaWic49VEeOGKjdCe3RvNTJ6emsypjycjkp6eo+m7z3TKE8R9hPettlJOUYGs126jUMBmaiBhSE8QGRpIgkg0qILPn6v071dN1y3K/q2a/omN/5TMtG6BpTzDKOCK/uOh+PQJIXFlJ4F4HYbbRqbaDc6zS6wRs6528r4OQq4lrIXoTyoD+fO51c/7x5d3h9zu9N1eyaGLQCUTm7bFufGDefL0hD1t4XSsExsEeMmSDCn163DEgAXuQkEKzuv54ZjYaDOOR1as7RZLWLY/pl3NXlWiuSLaqS2Kla9rICdH/GoUgn+imHp16hr3bLFHSJstL1jJ12fSUl5R+h2YVgKfN0Yc2+eum1HUiOln9xjuX/z/R7nz4ZAHhrHyxo++h2OTwKvVFwzKz/T2GFDufH4C5PC/L5DPEM4zxgu8X95HwXeehSJQsFdFESEwiMITBFcFPc2dzGDRPZTxn93G5wXrTuQtKtevYmu8buD1tm+35EZpkV7o5Gd03vv8Xcp+eH47EZbIo1cDEcsSYWtZg+BGji5wCoskqsPSw+uMKLOV5qiXQ3oh/TmSDoPkPFio6LFeeqOoGdiPdFIN0qFs64gM/dMtMAddbI/v38UuA0l+Z0THQ57dYyHwcuD5+UsoOc8L45rp9rBNMNf8KHxrrJWAcfaFz0TxlmN6DmOIGqgKF2QnAkguHxRmXL7+mokndA+qFHIcd7oO9ZljXTOgNIBjXIl4EKgdxzPHJVXALA8A5cvsP1WGcnxC9tYh8zn7XoWMK5YXk4Jn84zlvuO7zqeggl8ynZVvnwi74eHFd/Y2Sg/KEtmMHYcQPAWV9D5lHyBAIIFTJYN6A4tcThTnzVzEGHlTRtpDc2F16x9vq7gtqARWamkxdK4sxkIHTdI8CiOL8mixwOfEjB4gDph9AuIVIYWo68ykhf0s0VQRfOyrGb8FciwaFyPQG+MZVkgog6auU/O71R6b3JKinUgFoho+kyvOeWyucdQMrGlQVdjfxOda9/VaaYPgDHK3ttOimM03zvvF3Ca4jSxPBR0qNLUGV3lt4Rf5DUHEiDkj7husJGSBIyIqcGOh2a6GyC04Iu0aq2QG/y0FJII0GhgfCXgvUahQ6BFP/wgVRlPnMcCNDegjwtRAiD8ZR3P+qFn0hTu/oTxvWLLKsZwB2cQ/QnwhKyBDgkn5VwH32sELpip/dxSTi542j4zc8IfGW2Ejp2JIgLfS3RodpUZQRCe4BR/DEvHTVoqads37L1j23etm25OZd1kKZRe9L/kGdzhfKAUHoisZkPluY9w/KiNIeaYb1l/TIxyHcCA0/lhhlUbGdV1TKNFjsPplePjcoYqXg3iCHWk3dy8htlzZV6SHASROcDnCfRjNGRgWZaSzpzMUJVwApFw0vBbRAS8EPqewxWQ6iVqmShy5zxgaQzXZ+mSjMhUp0Mtpz9uqq3qKyo8C2L1/KyM4kRuuONmpagY0ev7HvCBZaB2HgnAZ7SffkL/5OUoS9Y8YIauI10nXVY2uAlqGnyGH38pe+pAldhRcJSD4sECg375z4lEH4d+cga3nwWp95Ty71Fa97fSvd+TCe/9OBtMnV98o2NrH0S1JT8b7+IR49Vn9YiNaqr2713dz5RR6N6/93Nk4f+I9mju93gp+5AXXU72MyM+Tv2fR3uHcxVR8F6h9zB5z1CE8lGDAR6gkZkeFHcVWCfMNHJIGDa9jBIEIO7A4LtlF6XgQbkj8wLH/UtO5u5OhBxxC2O1129D2xst+JzjSN9ufh+3gs/L2ffft97BzNg9+5nenP0U2nX7Bgp9kZemejaHy5g7IUrgUOnaNL8g9XgCBLgS8NSzdJgEBrmz/t8h3/+eFr3b6+P74b11hNNzoIfk5FH7KIlnjs0v/5Fp2x82nxBNH8vvvwui/6Xbv6wB/VvI5Ju/m0zx/ukJXy9XvKwrztc9FDe3z70lIrw9ToIplgA8/fQBBMb26dPdMT4GpUfvPT4hqDUunYF1QdM9bRwR6mEWCwIo73DGF4iUGALgsm+AENbWtKapJbcTZCQNtoHWmgqXS4syB10EfbsCMkC0oA/BaV2hftgSqb3asmhtRgDLsujYhwCrIxFLxdU1sq33jvV0QniVdk0ZPwTYrxeMvgOlTnJEx1iWeTUL+nwlYEM9VH90P763/dbn9TkvI/AE94rX5tBQAjHVAB5Kr5lpAzSqvBvzUo3pZxK8E8Li/TBj/emjpu2bxi8YeIUU1K/CRAoz7//+NzAJfvnvX218ec4qOTtPveYPns7op58/AgA+//Lp/vIcGARAFZk66dPt/agEmjAuAnqWMCyHyiAp3uFF38HQuJSLynTb2tjhGEMVT64YcS6jeqslBhK48TyHoqyn9KH1agyIx9iwtMUiyIzxYFNie/plN/JDx9RW1igSMy5ETXewRa84h+5RBDlAboRtV2NsaxTGfI+2deUEAZkSjUjPuZ89ZjQmEDecFlNABkNtBo9QhDq8qdE8lIIMCLvBieAplxbWFJx93+0+zn0w5QBsfWO9nekT0bo7IpFOUQ2IqmRypUwaFstnA+aI5vT32p40biEouHOJiKX7dmNI10jwaitY26KCrNVqd3x+3TbAMmgQKP4SiQrsgy3FP2FBw+hDUT4RRhf0vmPbNuzbjm2/YrfIxm27ghrreFMGh2Ao3jWDfYdFnweM0o2AMGGQGPuwqAAnYDg8VwyFE+FUMTEyHhhmCbmtKFimuEWBRbKloiEFnVBL1ZECluaT8gG4svW+4ddhveA8o8X7voMsO4o+u8SZq+nRU+ozhThYPa1ZjEbpuo/hNSABGWcwncJre2kLxjLCyK3DJ81KAWj0lAyLxtB08UMI1AhkpQiPEcjVAOjK31hzYHpPpGUnrWMoItjtHHYTdG6o4vQu+2DRJqpozJrxTvD8rN1tkv8mBar3eVe4s1uMx/GuHcc6aM9GbofZcu80ifmr82WTg+LNuGfB72aGoqOs43fFswgsyjYdeo7Pi52MmmmiKokcLqf1Kfd6poNxUJLWvpOTLN3Q1J1to9Ol4mRXDn28IXLPIs+fOUjFPtnZnBC6f/XnfFzzEgc+PbbjTjjGcE/5EFBlNsxxVUCLZSMRnUf3NKFFWylA4IFmEWQiSUeiRv0QUANcKetG0KnEgimbFB/oXjYG0Bb07RKGerF7byZ82KfcW4crmm71OU5OZL4ttkce2erG85uVzkQKgf9v9uLmTN2eEbkkPIRhEDLhYiJCP+sLT+9KNcnKAFo3ma2gnHNzJORnoJ+dzzmhvTDGWcDPBEcwfg6JGwQElicb0dVeqYZsntZcIirW+QoAaI2xfdl1Ty8AnVxxiMBPFX+0J8Hly0Wd87rJvOJ7LhGldhR99tdroaE3x+Ruo+MXX0ZKflOZaDJemsLxAmPuV50EB2hwrH87nTAArLan+/m1yEKFdth8SAB+ZuB1JGtS/vn7yPgOZsbr11d8+PAx0qADFNGQWn6sqbzLDYulF1UaXJ3bDoICeTYnNWpnhgO/TyNniEUdZ8ZufJuEA8roexh4HE8uS9Nob/FoYTesK2++LCcQEfa+wyO0zDZqa2o4mgTEioMJznqIKqc9fbwvlB34qlDW1KuaWQEAqJNmRBCtCS5gkGiJKRqiWbjMsOh4Iwhr0AMUGmi7RQBZ4bkAsQD+hJ7qJOXd17rnR1h1PjBNxjARwujRQgFfSvc7umh2J2PfASItkXERfxjywlr/eNs1k4Gtz9j2gJUa7S/ieMAi/G1OQzKLjBTcGbKG8Tca/a8XtBRMOlRNGRwAyOuAPBnH+4wwog9RGAy4oFxvAaWsbXt149RY6G03nY0a66xUHzlMpXzH0LUZVsIoDJ1yAuQ1+mYIlnct1nHb1eF3Ec0I0LctSib1rpHokdGrwAb5GJjRiDAwsG07ZIqJBNwpxTNBDRm6HuJrGwBY4A7x+9JOuG4bxpcvOk/P9EaCxqxyWTN9gD3jZkUtueHAKROfNTyDjcGMO2Mnb+J7YLieLXPBAXHHqSFbXYbpJCgAO05fRHtfIWPBIGB5eY/+qrXH+UTo+xb6P4GAlsWCKa5Y6F3qAnoPeqrnyXUDlna5NRAQ8LwuC07riq+vZzRuWGz/NQKdtD/y0hXGM9l6ul6vyjLNVsrfH7xL8OMjMquFA5fJO9N+Y2aVMuY9z4AUuGCXmfAxdBFqPJxEn5tWWEQIdGu63AZJhaNg/X7bm/IbhTe/edkRUEp/2UO5p3y8K9eV3wBff2AnXVs3dn+846futNyjuT16kuyap0V/ZDz6VruRveK9j2bxuLnhHJijq/9mXblWYOZzbvW5v9g5+SA6r7oW8xjna83e2++8oz7zZ7Sb5a8APek15hG48dwd/z2riDshElkZhFo8PfQPrOktLGNRZLOA8jJCloXL5S2Yk8HQoJE+OvbhjswwY63iDc9I6zL13GZn9Dr7t+A/ie/tHffP6rH3uZvvBfm439Yg7ER37gy9a1CSdCI68lqL2ZW6Z+85vFPql7uD1eDLZnwFG493NpuNq349g0e11w0S7DJwsvOvtdPnyPJnCF7vINaHsOp6kAer860W4F0O7Lci0H9vq3jvJ3k7Nbv/9i1c+dtxxIHvPnZGf8yc/1Xbv6wB/XvatzYmlJdm+FCPV2NujHG6h1aecMfQ952ttSUe0DTcf3J7xAwUxucbKL6wfnlFoERqsKeLU1FTZKAPRt93jGUBD0InNex1i4zR+qtubBnqzU/KNpBFYjbjIi77hrY3rMsJZCK/C+5jdIvYc0FS9akEUzAWDYzb/Bo3MCwSQLTHPMSHVCV3AOjPYjaiVc74+G7nOepvosSsFZgNj7z6oDPseG/4TCNeCO9Bb2RU8D5OP3204d0XjoEjg0nz75SiXP6eDFDwEQ/GEamMQsiyXn4A+wquIJxwu7H59kfvD8HO1vaRMvfbgygDp9lAL1ZnlKWeSYNMNw5V2HRiLOkc0fcdsq665c0iTPcdZAo9bmp4O19Ugep9JXMEyG6HpVjCHIT0H0/rHl6gFr29tKa4dAwsVtt5WklR4Zsam4LAo/DVOOPR2EtTozK1hiaY6pbHukXfWmuZhTQ1ZAjixvCJn3dnvOyxMUJZRrHmCNBMhZVeYzOK71k0cEqxPpzRHv3GmF7PSjoCwOpoLmjMWZcJKAaSjmH48whzYdAbBj/OsXn6XtRovqxnTegaeQ5G74xl2cP4Nboadj2Cw+sL9q7CBY2BwcPqUSX+HaYk9L9xzOLM5HreGBRlXp+pEU3OFqHE9POYYBqwCFdaZxcJN4aLEj8CNW+T/+IKcIch97olT0vxLQ4j0JumX20+SGsaOdjBvKN3VcI7jplLXpDpr1zhZnX6hEB9hCIsDNl2xoiA0S9oa0MbDYOtDrGnL6N85hY2AV5XtAEQNQh76QmezvNkLJVbs6wb+wCEc0jjhmU1xbrVZL1uHrsisdYT3nAYtijcVCQ+XPppHezbbX8zJHyjv/rhpquH19150umz8yYisxIqfi9jS6nzsK7TZ4lzXQWS6nxxNCrme/IeolkJdjyPRLMTk0gdK8pvvj/H9SiK8ONgDltNThSn7283EVUkqjBNyTA4XD3YqFRw3ioQ8+l6f/0u8w/sddeAMIihGgDyeuDN3jX7iRRnFKAofe0+rxlqiuu5xIfhXKdDoysPPnqc0ePctH6ywY+t12McfIDz4/dag5Yym0iFZTE4FlFjnmHTuHZcdM+a4pd+lOc6PT3jfHmFXAMRw51cfA9jjaElfBzM1GhVpfuyJz4jOY7Gz6uAcYp59FePCAyCeKCDOQbHoCTA9dOO9sKaYQuApsZHnD3HK86/TDBHVW1fRljfJ7nufr1Gn3vWqJnPSnQUcyi//QA7rnQOlHwd1XSSov1WPC2EJifwc1O5zeCtIXElyRMIl+Dd2j3EcXkMQ4mdikEPhNevX/Hhp4/Kr5ky15010QnrslqkN5uDm416iEaSD4P05lM3ftP+0tLU2GMlG4QFELYscCb3DjOlefRsgUUImwOTKM1mgLBArFYLkZbpWdYVnn1gIHFrOE0Z26QJ17XEA+AKS9HMRaKK6kCxNk/HH34u1MlPbFwDQuoMGriPCo077IFhPMRZIUoeLULJCGmCQFyLVNc358whyWClyKAZIecyDuW8zYmAGKAO0JKOSDoEiWh8CAI/+zwFANaUe0C6r6MjAheIWdNaM4Nc/hKBXK8/5vcAACAASURBVNWwRc+SrEDMIvmtqtR3Pl/nkMZufy7S3Hv5HRHIOU3iajg/8CAOZ34NJfr0wDs/dGiytfU1iexGB7rjhmXNzEXoUEeVnQgis8asPb9M0ccA1DmECNt108xZY8G+K+x5CvdKW3Jsc2YYG7wPqvAklT5T8NGeBWNaCyrwJYLz5QImRpeOhcxJizKjGnmVBaPzwzMMhIyJOLsQmcquMIDhYCze9R2jKCFk/8rL0PEmv8Ct3Ggn3lMAx5kXXyYs75aQ19q6YuwDgztkFKdxZIkkcryHw5oDEcUePG3gGeWfGzOWxhj9juzhZwhJ9yXmUGZaBciR8Bkp2w88gz9D1m/l5fJ83q6pw9bNe+0+N7W709w7ZPnFI3tUjTCxTaRUMd5zkKFc1gndydTvDCk3kehx3Z6Tt+/70eZPDwBfy0JP62Xf6zU3KH+Qee092vuXsk4/msL9kWD3I3N1KGe4AZ1w+q+/of/vP8D4CWf8I/vFLf903Pejoesom3hzjO9Gezei32uP+vjeNsnp9OBs3bnmDjj6xfCHwf8xeEcL0mRATuhoYHiZzHhOI3nfeLXxVKR1zokGBqkui2VoAJ2VHFRnK3UqFS9DR2zOSZkRstIIiX93GJm32mHujx03/oR2xB9vjHVGmcYXj8L/lxFya9j7noYz4/Pmzh4P6WezM5x/+fVwO01/Z5iV0EUkjsvXHW14z5jtd39lE//PDwlKP94c9/0k943of/Lrv9H+ggX4F2n/1gZ0IIUYTMJ4tn98/YpTWzS9aGN8Ove4x7e53j/wtbB+b7wXfnjNu88Yx9d//COIgQvZ+l8jIPXFPzhPYBYUp++TcgLm4Cnw2uf1hc4YqoFcJmW+j3rrHUxAH2rwEUBTmJHGpO9LB29usLQ6Ut1SS5oi0Os7SvMaasC6LiA64dQYO2sK+Wvf8Sw7iJ/QWkPjRQ1L2xV772hE2K5XMLeYy3a5aH26dcHSGvZdU4twYyzmzQpYxJlFn6VYJ7EOBWymdQ0hCuOGPvw2gmeC5M1VH899IhuR6KJMhzNJmf5HkLsGkHyGG2OZ3mHgSzBYAPBiXMeZBE8e8Yj3EWHRRwdE0H9RRcjyXwv2f+zT/Osnf/O+7fh/v37G+xiVxDgBIH3K7zeLI8f/tcjzZ3+LRCYeCAArCRmOKYxkYglAwwZgvSGxR4W9SzGurAwvdcHEJMbK3pdCczWGRvWG0jrgsVlGBH0xmZdkqvTvtHtKQbMeiAj2bcP69AQRQVtapHldTwuo1MdjImy9w7VoKtxqGjBCw3pi9M1+s7UIwbwwuKrA4Ey5RAjhHSA7l2mohpjaawy0xlm/kRgvp5PVw1GvU3WmcYVKGu+iVimpcN+aCYarCtteEsK9URta1IqtkadeIgJIYweAiDCflJRQOX/0jj0i+yRSanoE4bD0mN081j3926RcYfOmFPOubV0jmXrDzhRlPrxGtP/16BTTImik9wR8xvg70z+6RZq7Z6ga9t1DtNGC1gm9K2x3i4rufcO29ayPShRR8CqwdMiuqeB1u1xBmGscRiP3BNa8xAG/zu5idEzqCfuYjlE1uihT7zoeU1hTGHQNMAX8ZZe2y7eCDhAaidClhKGv0FUBPNI9nzOWPRQLEs9X44SIGvWmKiFQgYyZse8dy9JL1KHP05U1qkZnXnVuGnIQSll9bwOTQGhAiMOQR5ZulnZV7mv0hSmZmQFiywKjGNIJnzvEtKZp3l35WQXYbzVXrjn+WCzVbWst5tf7bk4zzpeooSCSewbTomutv+kaVQXn9N6hWSm53RrIf1TZE/T3jlL1cKPr2kLAThi+T7+j9lb9PaSsIzU9XJX8pToCxBVJodJn4c4w03xKnwSoEtFwVqbVl8T7x/X03/QG6+gRJ+RGkTInOS6l4MZNW2J004Cjn0AdpnTxZJBEh5SjHnUcU0Io8sW5v4Kn72CL2td00QxLyoyMWF+KvjFNtDqXCJCp2iXlh8mIbuyt14kNY4jz1iTmlDPQ94G+79i3jn3RUhEeYeFOXiIDasUpY3EaXaYV6zWjvbxXgC4a40JD6ZkgZa8wqtmiEzKNLXMag2cns0p1kwbcbILvBSXsPz292GeBXH0++cC6PgEArtvZskp0jFcJ/tshXKCOqTkGiXXXqdgaOl9U3kLPtlgHY63ud0aM7q8ubwqAK/j5eZ6PZNawMQauF+WUHZ8OUIwx4EsyQiOyxNge9K4wwidg7MDYFA8oz3TFPZH/yGEEOrZ/dHuAp/uO1/2Dj3d596waLdqCFxNY5KnxOcvzk+Iez1APreca2Fmg0YErgK3ALWYjQnwkjcz2a4QTCAx+Uh6zn1+d+kS5sdcvX0z+ZLz/+BGgoWnKLZLYo6PIJ+d8cEGL1+sFRIR1PQWNdeMcgQArPxbKW2GL+u3GV3X0sVsNdMDz+ScvTlq+qKtxbT09weosoTWVBWCpTTP6faCJ8lRia5MOi643EIPzBrBEvXaIyc6iZz/ojRtvmKy0BIH9WiUpcsSwSfNv6LT42rohTBBlhCDZ7+G8e381WinwbDWeAXAnW+WNPPpNl7mBQKf63nxNZPDzElCCyI4VhlURDNEo3khm0HcMQKONoZGztLFmq7iQ/r0q394vAn7OLCSn9YTX13Mkw1ea73zEAMlSvvtYE69I/GBw/gyM1wOetSqkQ1bjna+gYjB3ftAV5QKVYSuPX/dvPw8sL3P2EQBgy8BFzmOEMdvOyJ1sFIRnq2Orjr/bvoO3TXUVfgb7YvRx1zroXgLB14qCA4gzSAStoUvzSyuaq9RJZM70EmMk59qroQiKlC3dtnu/+nwDL/rzJnf53vYoyaJbSd1SGjO0+rWMcHZxZyjiFn067hwWrDKkT+uq/bKBN6Hizgnxa9wMRLT0x/b6BcATlmeL5TYnoiECaoQmzZNaQiDgnn03bmg4oeMyvcJ1ElLWZ4hgibJ3WvpMxCIekfvX6z45D+KfSX858rGmKrA6uhLnF/XZO3scjqGSmrrac50TE8W86u8eLc+EyenriJ68H7nzOeWyA8/hv0uli//c9qHgzeN61eYG4/eiBuC1/FYN4tUwfi9Vu+AHjee/sX2UifQHdXr6+38BMHgZgg7BwC9390LwdtSo3/NoH38lNZrV5uOIyOE7fR2v/3BzncmRF7ynr4yXz/mCgueihGdyPBS6HZPijG8Ck9Ic+6u35XnUeSXGJhHsg5RekNJ4D3bZ9w3bvodOjzj1IBCjw+L1z99qlWP+7e0ePvmRt35zFKFP1Tu9dKY/x/AyNHpQtfqoYGmMvVsGI1RHRdUrRkEMunWoux0D4E6Kn798BqDlK66QyH7sDmZMKv/OQYRqeyIAq+kNnj9+wPj8BddDCcjXw0Ikyzj/EDorG+C3dvv3tB/ZX29/M3zo+LHWMPcSDn+TrG/+c2GPf6XfC5U/0gql8lQ0da3vyI7/Se1fzoCeaWgyKY4zLwCsRg8mCAnmph668swQwXnb8G5VY++9A++H6UeB3Q2TVcFzQzDlvsD46D13EVIwjM6Z3D59www/yCWhcWYSgx1CN148lXgLEHVUl0amrBvYe4dgwzK6pjIbgEjPGm5Wz3GYcl4VJAziXQ3xZhAhYuyjW43nZgpAq1nYO8RT0LoXNmnkOhPhqS0YiwnPQtYnsDT1ShaYMZ8swvN3HOZQEpb9mSIm77Q5ImsC2uj0ntFnJiDmBes9BHF3hiaxp6dqJyJ0+RqO84R3AL6i2Zve2443AtpPDWQp5KomlT6SEtWPjP4px1Rhg2wuIoL/8/NP+PLLrwAOaabeWNNHTcqnLvYmEVzggizFwerIFFHaNmj+h9veAEAuAnp3vErT3Y++xfErjAjbfEfvEKgibF1XU452VWJJpoF1Ic/30q/5WqL+tXvU6C1lDGT7TpH6qFl6yfjdFXTWHRmDChP8+67REmSz0NemeOAKO48cl2BeOdNd2h9PxzSEsta3RaNSIzRqVuucsbIyyC3SNlGku3S8nYo4ve612uN9hgcgw7JkUNaVRaZijujxWLrhSwq3JzjT7T/s+45tuIFELIMJwnjuzHhXzYpFh/helu0jZRqZWFNnj4HO3ZSxKkC44T0Vkwca6DivAKsa2we6qLcsxlDlgL3DxwkAAwO9E3jPLjQCfdNU/Ia7GlEx1ApkkBpqh63ZACINvq2jmFE7at4e65kbrHoUsqbYAnC8LZBJOnLEdxKQcCi5Q6g6tDmaWWFETJV072U1siDwiQt2RSN+711y3Oc6Byk02toYWiNz3xva3sEsUSZjjD0cVETIolBbKuwKjPq7K09KRFrCpKtTBBNjWRh7F0tJBsCNQC4owvZkDE2NWdJ7MaBKYlsHNmFWLHK2LWv2AWD0K9I1rdJIvYOZ0ZpGxq3GMzjN8/G7AF1diuLMhpIQ9py6JrpgnPp639fb/TpupCqBnTe0s1tS0Sc4zjBVo1mH4YebaKwyjsorHJ1FjvekIRwPy8pEtJPhiYhqFXPyKd/h/J2vpc2VMGeSMBcXjZDzenTm2OTROrWPOJ8y89xEMN7Oy1WoQSfO7XEuExvrZSvKHknOo54nEdG0bRbRRPCxCobh1Ihwa4Q2NOfusHPpwVDFZQe3SkkCDpmLYPOuTlhHJelRwRTnoChj3DYxgBsY8hrpblBVh6Y+0bSo1zm6gewxU4u/TxK2v9HqLTWaUMR/tTnbGg7jo+UAt3MfAjWEHZQh02k9vDPuuE9H2rLaedffuS1499M7HW7N6tL79Bxu9tfxf0w1RkW29dHo1pXIS7AAsJro7rSRsCQAcNa1Szh5QFMC7RXaFLV4nebZs0/6uzs8RZS07Yvj+Dg7vhfwIV8rqSowXq7Zp2CJgkkKaLtpdPPB9sTGTs+AXE4gXM3FpvCzzyeTDWlaB1DJriPAuHrk+YMBUBmAAEJXiyLOzBrMBLkgoh6dP/OzLTaOfhl4erdqRifmcADzcimqAGYICNvlit4cb6pq8Xq54vn5OYYnorwYCUXWCK937s4lzltKNwdIUZk15MMxAF6MP9id/cWyrLFWY+8Y0jW6d11Nma8DoKBhSLgWM/Q5bPJsMFV/kBHj991xpyoWdfIgFhCrkwGTlnsgUKYEF3NMLLKqn9nYcUJGoJpsYzemg+Zh85VeS9BMMhBioTk06T7YWrY8T1evMnAYOsU7POLWxFlDzGntPNTI/gzIRdCeff7QtbCziQtANEBftV8+65mSs9LUlFcGLpeLroxFg3lGCgFuorKPE514ooIz8y4/fSon61xnGSR6qwjj2Jc4LtU1a8+hWscYAm45kirH+Hc/dxMtM56ovdjSS757jIFt2yAiaL2jnwe2fcfr+YzL9YK+q6PXMJgVM54EAJDRCMlxHeXq5Dtdj9FxuW53qEhZSyfsrnc0+jhkqAwuGe3I5lTTuznJEEN2sfJMQFVTZTaqAYNOXQ7LQgEAYnqzcMwv9FTT5PdkBxXhQZ0QKYhfiDG+R2Wy7lLMuGCcn7VERlkL5SkTNmQMYGTaeyLG88cnbPuC6+uXqfvKezn9GqL8uZa9c0Yk+Uz9m7Ki4nVOvo+AyCph8OSO9GNopgIRQRexsmRiTk0ZefoAXcR8b645jXZ6h6TdIEJDoSPIsbHTrAnFVMMgggMmJvBI+cQzwwgOzkPZ0aHfmZeZnM8qz+pfJzmXMMb87Hc3Ur3kKNOMbZ3u04vOG/zAG36o3Qu602FSrMkjo6BHmntb8DMGfj28ICSImdcqf7+nfeveW676Zhh/2hp+q7lM4vaaNJUjs+yxZiCZM0G545Pcwkd0jCKfzPDvNKQXA7rz5jI0Ar13y9AjmvXHPIXi7B+DYY5Nbj74WkviWcdXPsbvEcQOU/ytrVC7H3/I6LDT4MC9sdga3DDqfHztHnQddAaJY1wKqeNMHXWQ0Ggb5gKt49MnED6A8PlHZ/pv0QZwN5BX6XDiIC8V4Yb0hnTyeaBG+ktbmByQNFKPu8tpkjf8G7Z/qgGdyr/puiPUoUIqLE2Zc5eupuCJ6JMXu9Bz76yHqPH3fO3Ytj1T4NiB7ihG8MO4gATCYDD9rzP+9msyhH6fuJPnhH/M1IB2D8tNDI9+UE90KrdI1vWtYy6IJ65XChoR2Hq5QwUHVvkAgzKNmysbXLQYUEZTyHyhF2DvA31sYFKlfaRWc0XEAIQGsO963feLFS1wY6AtOC0rlmVBH9Boc2ZcL5cgPKd1VeZYBLys2Lcrhhl+hgDb5Yr1aYVgRR/dUj4tWNqOdWmqwOsCFT/Uu6wSRyZNC9O/g2C6QHBskZ6r3Fv3NpXyScxve3/0cv39bED0XAVkEZyN4XuhZAKgSexBRPhCgvdCAH0FAWh4D9BXdaIgQA3rgn23KKZfLaXfRxXXet/jDHVkxMvZ4O3FBFKvWX42GArGXCQiN24Wpnw9HgWPSBcB2ujqWTYxu3PzLHu7MVDNU8HR+xBidHU2CE5x/gGkor96voVlpkjvto9MFsEAjzjVe9anE8YY6iHfNIUzAPR9U4GVnaxRMJg2yxCMA4+4UqKsJVuE/IBoIEsHeGFIB5ZTK0KOjqc1MxyEQOcETXNkeH02JjPoEkXGCuZmUaQ5RjWKKPO7NDX6tdYijTuxKZNYU162tioe5IbnddWZW4RPRH8cMmdMZ5MzMRacCfdIdKhHuQwypeSAkIBhqfH6nBpdPMrb00oV+EzWW2nHvm0ayS1upzGW2BjKGyMZ5ntUCLPxkjrvjF00XScz2Bn7e0qwAL9U0g8Rrflm/bvydY8apwNEGrniMKPjUBGudwGRK2M1DDjSsBt4d1KBwrP5qdauGPihz5L7ntp5FMkyAU50jvhtVspImSNFNL3CV65HFfVTvkqDaQTJxDYW47eOQv/ntXhtX5QuCUQslyLUoCsWse8ZJCoNBDDVpFUllZ8lXZXm646B0SX2kJnMgC64ble9n9kM6Lo+GvVmez0ErbnTjR5YIjZVvYOthCAqyDP0JJrCrMuIdJZha2yp9Cenp80i+i1DBoMiVWjvHdu2RfqPZV3By6JrQBRjzXSZxifsO0QGeuvhZNO44eXlBcuyYN/2TLXZB8KpTgTsR9PWvIuAetchDgIvHGUrlmVRRxSYos5qVypMzka9YNwL7RzTmS4wR5V2+Z56tM+YMkZ4FN8DTfY0lin6tihv0+htY4n7cvyCwhN7HXdrXk6i7oM/Vd/tkcnVKD6gwEELm+NFw7quETU50NHr/WNE1oDGhH3XfvW7RiAtbcFiWYEoD27MJ1GDz9ONyIXc+tyDR/YPZCn4uvp8kGZkIKMTCzrEztbSFpyWBbu/r3c1shsGgwCZwFr7j/NNLncglD9CxseEQsGoduXNp72P26K545QaXczByc4aDkpbwQHnmKNSx9ASG3YMW9M9A+v4teQGImpdICBeAZTU8XDQvieE2PtlBOdznJzY7xWXeyNqGNKBoblTBjnOtJkUunv/xbdrqc54DZHWdUlH6OjmjnFNRNeHB4M+umFH8cD18wXtXTESHx4UIzKKcwnhtX1UrhHAz2bUeJVIneT1hZuXqXkGXCWShhkdTQ/NNFldY8u2AqNDYLQXpbn9awcWAXHXftKKonzBBnNmFjOuS3kXEBmSC62coMDlVftFymd1R0tnXmcD4PzlzZ4RmE5BK+kZIJwS1g8wIHEObS2uVwBpAFaclHNxnnAeespnJAuEzJjcGO1lgVyv4AVgy7XuT7sRnaG8VFsJ62lN4wxTOAZ5KnenKZ3TeQNdSxcRCK+vryAiPD+/FLmRsgSDGW1693JnHiXVw2kTMJ3B8HcaP2N1mS+vr7iC8PzuPZhZS/KI9vv88gHn11d9Now7kihWVC4mz1pCGoUNUvwgXVO8K9lQ4nzUMyCyCCj/xUtTQ19HSUZUzmnwabpmjge17rDEEZuNG7Nh9xgRSlC5RYYZX4zuhDHRyVABUE+HzFan243dmdXH+AZu0/v7uWOHgFfdEyHBWJImD+mQFRi7Qua42Puf7Pt+tTE+gQA0YgyCyWgM7GQZH4q51FRgGinmBnZCh8pkGpkngffD6Q2G588AvZh82bisG+DGA3q2PTmfLNpvT36pMhzOp/hfSmfGqGUbDtf6b4yh2QvFS1YN8OiQyC6mMmFrDTueAPkSmTq2vofReb0uhmcI+xdNw/v1/IrL9Vec+47rtmHfLZp7iDkYUzgKDmEQPCNL1/3wtTBaGI61Bi+qA1E+5Z5cI3CDXxwHMz4iZM1u72STucPRhgjUgcEKZ21ppjMo/Kvxg2R8vfrVeEav2VAb/iaCwA+A7WsM0ORqp3u2j1TmFmdFpMCSFdXgK+QKnF7eoZuuAxDIrnzgvu/63HiFfHkG3jW0pmM4nfTe89cvxms7L7kELLle5XLdYp2bkOrtbC6NGItlJmgwGtvSOM3ENvwssYauzgy7pXAOY/lww5kj23SGA4Am77H8TWnFGILzL79MfIwbyyfHqnIewsBP6vj01Bo8N4oAWIKvd7zqcKVQMEZgOFUdLXEM4353OAjDu38niuxMrpOoIOxy49QO/Hp8E4HmdTZ4GDT/bufhvfHFJs5ixU/Y5FdsBHytOmsjQu7wF+AZgyR8RfLEv9ecfiuiJe8zXZXpZwAaTe+1xuvTihV+1VTt//O/AIBni0R347n/8/vTveiPaaP8fczN/4VNMrKXVUAJPs1xFXNDC35K+WNWZJtn1ujZwAjZ2a/VdQ3ZvPAYKgrs6lgkeQYqP1udT/QhxAI6TzB5jLw1ZZt3vSJ1oN9o9ODznbfc3vGNy0mz7sP7gOoPlraAiaw+PFSXC7ULieh6DYFlSwFQS8cQofIcb7VenJsJFDoiDyhi0wX6fjpfBiSPJfAMDp/x3vf8wfuq7HPzm1/3vf+T2m85k4pbtH0UjUT/WWb84edMAPyX5Hd//k+cUrzf3+Z0MH90+mi6frj8gTAiud2WjhHR/0btnx+BTtOf+FCJql53wUJBxpHx93j2GK1Gx6zwAtQw+e6weZXovdU+FpLq97pK7u1nfwS07/fk4EqH74+fkumTK7QC7QlMoLyNGHYhVKObFW26gN8I6LLbAXJFA0NIo+io9CFMEOkALSrgUEeXBQuMUEIivXMfWs+1i4DMePvpf/8f3r/7ELRqiEb2jYugrYs9gyDANDG5Ls3p4kTdUl+B74Cje62ue2Ws39rj74Xb720iFg/q8xXJOUPwlYB3Qlhg0dJ4jwUKI+0nTgUDdE3Zo9GhS7Z/+nrjaOLrO0STwD1RGr19TD7X39uuwCTgPWoDU8K/mSmfEAwVAc4MVI2Teb+nWCxP3zRSpVgzpdqyLiaoAmpQI2zbFRCNyEbdJ+aEGSkpdcmMY3ZS2SyHNbCCLU2y21o1elAwugRRSq+vEvXp0TeuVGNn7XN2Luir4p1D6SuiKQ/VeK5Kj7awXSd4jaJmRi6P8FjWRVPKDTXcEYog78qwg0K+RonVxqCsB456P0Ipsu97GtDN63T0vTjKOP50ZbmOYYyudZCcgZdpQJNw7TBSPdbdYKUcoSRjbaksVbBVCqaMPcUcqexXCAhRC1MV4gNuEMtyGeLpt4O+hbiANFD1SC8rplQg31O/u0h6rjB04UBNwx0sYs4WLuzY5xCR6ruRHQLT3tZzprdY2i7b86OxOvZKPeCChgHOEiQ+yj26LwB5VAk8KsrxJbnSn4tzgxvLKdYllLmwLjxNa1U4iZ5BjSpX5UvvCpeqZJQ8l4aeqkFj0QumaqE4Ly6AeqSwCi8NDYLWFoC6nsmm9Hf4JvoasgstDITxsYFYI3caNRNYB/a+Y8GTQtEYoN5jV+xwRDQmE6lBnEnLI1AHJBWFqmgzAboz+s7o1FUxv+v+dQAeCR61ol3CKRE+ivNunU8Et5EjR77IecGagvweLb7hP63/NHjPBvHHdO4gytgzGQF1NJ6n0VSO3ZgQWRMLHTNU5FxynJ6Voo8O6aVXhztoql92Jy9ynqngo1HhehqAgYP6TJNlQnFYBWTGoZjPCMp4p/GXyxpZpTTKlSmEBmaxM5LYHERh5Gq8QFgwuOJhVWizaJRkrL89X3dRwS857NhLueUNHE8qvrjdb0B567Y0YN/T0dTWIGoUT2uQ1/UdNMGdki0KPED04EyIOarQNBxH3GXt85mDL0bMP9+cMHfc34LxEc4gweP4q+/zwAJYWnbbkSd3ztUxrGvGIcSOiCRclz5baxARKzHjT0zDQPdsWQSsLTncyFzi547syy1SyJ4trbsbz2vTtb+PI9wIczTewOeGjPpniGaUQYcIww2i7twrQ6N9IwKzrMdwn9IioDoc30gtdYuDLxC4sqw6I/n127MD0JPibu/Hx9rPl2mNfOXby/OB76twK9MJvYV1JxeE9kKaIruJ0csG3hlwxx6Zn9JUlirPLq1p6SFakj5PvEq+zDOlXS/q6LWsDStp9h51PrTsM303DknXb+9bZJNwp77RNTI9lJiAwr6fO8dHhrDIDE5P714ULxou0AwMhC+fPgcedlwea0sWISyidc+NxgY2pa71lgWRzagqY4mAITStodflZiJ0Iit1gTi7TleS0UTgII9Qd12DITcg6OO8/P4sHcYUsC12ro7yOFGwEs2zWvl1ILMgENSQDIkMDINgZXAkShmNIRjX5DP5xBibRbbBaLWQBkyAbJ8EEDWqenp2EZW12AxT7GtOM02foH2SG/19EjIDRBIXXZBJ2SohsP5Vmc3gd5ouHVfJPTu8WV+Z9FqIgmbIUEfhuocCqKzi/LU0jKEp1EkAWNBD7x3EjKd37yLVtmf7Gl0jzR3mx0Udz17P/4vL9YrrGJHFsHsK92F6KgwtsSiZpaOyxTpUSv1JHHWF5963NKzifkunS8fFJo9QwkYa2tVRp5FmiRgysEAiMnIyIrkzuAILtL4v37xXoPDqDk7cLNfgiJxrAIDWlqALQR8KjXb+g0VupCc/7oMsStx4iuGOq/6aePaMTvsZdgAAIABJREFUhvcYImjGF6xtwZU0Hb1mp+LMljYUV/c+YqXc0VsdbDzFLwFiRhdzRmjGT3G4eOo43v/8N3z+3/8Jh3jpPZ3R7R7Ge4h8imsNH9B+Vl6qsfK0EMFoAx0fsXnEseMM16P4Zy76DRsX8BlEPwNmLPTj946As0daBb71KHy9rOMyx7qR312EJtuPgJeQjw/7d0dOeSi2HH8YCr+JLueTkDLy7FAy8Cl46+gaiZudHgV7Yb8zoPGl/sPvaHXOHwT4hHQmmBxgfUELf/NRMuLT/JgSdqA2hY5fpvf1/3nb8Ppoyf/I9le847ua5H56mYbGKSMyp6MJYE7aViJKjh0dvs/yeAYnEqxcg+Eiz9iWT1kL8i/FyP5b5niEcEz88+MjdvvLP2vfahlfKf+OZz45kczhBiDo69SOBJM0BfuGWjaYsEQpQdUH98mJSU/iyYJIjoGOrvP3s/nj7V/mpEztrVERcq4OX9Xu4WvxrTIRf1Qj571jdM5HpYNE6O0ov/8ntH++Af2HWhobXEACUriuB7gesyFidXbvIWZt7hfz1X79AMYXpLfMXUQo6glOeAfBVwCAmx4DjIqAZzP47tnenUz0luB6/2Z6cHn+XZmWghhNKFU7hSl2oPXoNMLV6jHCmW3FkuptPkBd71kWAKQGM1c+ySDs+46lrWZkZDxBCZzqjwULK1MsXVNhX89n7MwgSzXXe8d6WtE6q/LdBHaNpFdlRka1mqOFzRGufCxLM0Wx/FB7sM737pTZUPZ72vku9AIXn6shsvd2/WVQ6EkFwH6oib5bkY32QSO120+Z3UAE2D99CaTs9LASKg9oqcbzudENozr/+nYLAe8bN4bw5kKefWxlvZIZEPQhSNu1JD4hQuZHq2bAIwYo+y/uSauOHKpcMibclebwlO4jmIfeh2JgSkWoKwjIutaayRQ6JxGgLQsgMCMBg9zL04VIJvR+gowd60Lm1e4p2jERMhf+9LMZ1ShhdYiAnZUisprmbF6kZsRDGgIbaS1yTX2pNbiZGVsfWq/ez2Zl2ErqtMqMqlLADGmW/psXW/mROMPPF0O99D161iPPuxmaXYhWuJrhi8mNyZI19BIIk1E8dOD3hKHS+iST9olhTkWk0ecwL8tQbM6NTPEY6TbtXan0UCM/LCpI14ng0XJSKJw+21OIYbJoJ53dwlQMD7CeDga8ktZR8fyusBTR0f6TZ4ZJaiLiY58FnargmNZyZL2+yC5jN7sQRK5o8Le5sqAJMNju7HFWvG8XpjINaIoCfigySrni6lQ4e6eKJyT0TsPWVm8xfJAP2RQtGrybFz8JiBpcS0KU2XUaDfSuBiCEAt9SnrUVy8Jh5AcEIowh+vu2m8NKW/RdXpceMDwzOw/5WksY33Lv9J9lcBgC6UMjXcXSTXdPf2qOMKIOA405FcX+KlHHF6+NztzQRkffOxiMzc5NJylwn6AZdQPnZc1me1FhLfbMaT9w44hV8UDCrcP/DMeHB+L3NH4VsKrjyuHdb3d+vOlGLP2vnXOnU8eEOAp+9fzrPNRQiIgYV0NHpi5mqo5cyHM/jUngxWXd/yC42jhD+j3HLdNaKbzeTvjIg9U9kPDSycWMKB2pPaWhqPnc3GFEFO52UQwxRtYu1ROY4/M+bveC8kv5WA2Kt+6npZEZubmBpBc6m0ZxjyaippyLWLra40L53qbhPYHvhtWiVNiqt92og891jvk+nkOKXwoHFY3Gu+oD31RMic0fxkRKjICfqlOf15XWKzWS4fFYU0a6HYPTnFHA1R0qHJn4rWVB6dDDWdRwfp7fQCCNOr8C9OT0u0aeZ1ubVv7U6ElM8L1wU97lbPN9bliaAHTS9LzbOVZMs2K8ovcljLN3FuVuK0druuVwnMtufKPZHMb5An551rUahovOl5s98d3cX3U+Ty8vcf1N3FnGQwCWF62P3LiBVwKuK4g72tLMsfvZaspvZQ4UGbu4nbC0Yfd0EDRKdt93dciAYJcdcdJ3yQNH6ix7kQ3L0mL9v3z5giEDT+spMpfsfbco2ZHp20WKgxCiXwKHTKvwOQJvn56eUtgBFLeMjpDSDtEd1ZmYm2U8AFuUsfLxIWwwaaShn2lCyPvOI4n/kMTAUuZrKvddMOH2Oq+I+nSmsAg5BZtBeTCKaFGydwTm9vIrSY2SN3UiYfMmgWUCkxiQKwA1I48tmZcbsnGNi5T66IBsKSd44AEAjC37RRnVOF9sTWcWRmTY/gI4Ff6EnI+m4P1rj2Syl05Pgs46HEVkdc4UUnCUmOQuIiA5wR0f1BAokOcnyGW7pQWHw0jWR3t6NllASr+2JsjINW6MsXf1mUTDYmVjdmjGtKePJwyT31w3NXrHzgz21O2jYzu/YoyB896xDTWme1YHzcrjcFf4NYI54yHOHRGBJNJu3egX1QE7A0HodkVyXXx5DvSjSSu36V611nA6nfD08gyPbtc675tlGOvY+9BoaeyagWo47Ahe3r/H9etX3WeClY/T/j0DhsqSKjuMXgxOTl8EKl87CrM5u/5PgOSDCq8HWNkoIfR9t3XO2vOTvDyGyp3S0dDAbcHp3XucX79GdhaxTDnMFFmdCpaBBztH6mBizRRi5d/CIUpsf8XhT7Asa2QCEBlgeo/1g/GT7I5TjN5XALoH66KZ8wiw0kiqn2BuWP++gvefcfk103ZnkIIb8R3P5vdBhP7pM1b6yTQxaljuRHgW4OJReZS6OYHhKzg2t41KFBEw7hk1QKTOD45jfcdk5uu+RU8ftjsP1kten9xr9jI+AuZw8E6ArwfGwZ/9bNP6ezyn3z+Kiq9/VH3zz/eZwZv2MeBd2374/ROpMf4YlX6xSHQ/P37d9+Eff9A8fiWNSPW+pVx/xC9VTuA37/+jdhTgAN24CCbRN3OUsWAzpNcsl96V0TMvLTcxoYnPIRo4JoKitbJX2z1VikvcPI+7GiNRPt/7frN9riipc5BZNPqRdnzmFlxkui8cWQtO+NYLpNzn/fTAu8oD9ghCLPc6L4XynQo/Q0W+qfoa/yOCBnWuVB4mS5q4HO+lOp+WEwSCbVdeGzaeFYQdgmcBzqQ1z9/7s8j9vZGzDutC06T+oEP5B7Zq/P5Eio8ElhUAwC+k6dsL6x8w+tudCb6vVV3D8Zf66e6q/ust9e9q/1QDeuVvvd1FAJSexnE7HQ50HJyZUXDhSMgFq8P7rbmJ6dmF6UfjPXxnvEM1zBGAlw8fcP38+Y8nUn9RS3ObNnJ20ghbH8OUr2J744KB1ZgT1vROtu5i9YlBHWM07PsGbmR4kbFCsMOYVTblGJHWJ4IZxVmZdTzBmNyGyzainpHYmCIdoiAVVq7APRAAd9T2pvBY2Z4ZlvTqNzBAPP89gP0DrRLpIxMQCon0MFXDZxqCGJ62H2DJaE1Aoy689V8H+KMpaz4rY+LR58lE3L4vhneg5BFV8xcdBufXgNzPo3KYMIANoFUNmWPoyngaGZFhnlPZKvapMCB1X+w3gRmbiEDNBSmGSE8Y830aIyK65/cpTKexS9+1NDWOuXCmKeM94j3XubUFXQaINHVd6pDSyJG1h1L4cwcbT4mtirvqU6yRfa3UMfJIdVArxj4Gs47Thbu6oqn0cdxhyiNBKhABkHvwu7Ghc+xFRIGY4tEFYE/zqwb0PQzoNSWuvxfO48deHgBKbpnuo4EtrwP3DCi6Jpmy3usCVwP6rCCraERCseop6CN1duAzpUSqdC8GAWfuTcmSa62db/tshHDlB8r7p7naWXInAq/NR+T4ps2ZASZceBBBfP8dtuveEACZHS3EPosrEcyCpyRIwIPVfi7mcVyYefdkDRpw0ySEuod4mpzKU8CE4s+hUQHscKmRbLmdyvbWbN8iVpeVu53ZMae2MnjxcXvNMM344PX+9LuIWITMBpENkB19tygUtvr0hhciRb7DDCmbS4afmNwRrsxx2zHA8EmJR9Pv6piyLiuWtkAoa2er0bKZU4Hir75rdNECsrUSjM7YuYH2PeCKibRES4gAdPh72Dmn7cftgiuaBDjg1judzP0VEjbxBzL/7vurNIXyKB5/dRxS4LHiofnuvOTKMd+qAUncMG7F/hrV6+c1HB4lS1oACgtCSiy5WQaWQvOqIExC4XjitWkrHon3w+FpXkuf1RxJ95ghmB2HDKcNdyxT5bCEo0X2a2/Xs9y0zAhES1sMYoyhGZBU0TiADnS28xt9+HnIkVYlTBVXp+kkwbo7J7I11zOrjg99WoOkh5FJJ2ik7WkW1DNc7HhIwG9obMLxSpDnqigOROzqRHhsTGX8PtXCTM0zEAHMQWNyCJjWxJX4usbDmdDrDP18MicteJr6E0A01zf/RuO2hGzgI9i7poblZ8b+taM9P8D3dWJVZjzfWeTjtefCIT7pXL2TOKPGd1X+YlQEIqVMVwiwdo4A4DowniiHFwZF4JE761tKlSpaxGxql5RqkxgXAOfUJviIz9aZJA50RZocx3PQyVzOr5keeAK6B+PHSaPd7ZsqaAn0wsC+gmmP6D+mJ4TLiynz2Iwp1DrATWWlyxX8/AwZHklKGN2yfRltExJIB0DqEIOhuS9dpiBC8KZf9zMANXJ6GZ7k7UbgPV9R5xM9rTicz42a4lBnc4I6lLKuKqkwYDIBG/2gKOWkc9ZyFNL0hew8VR8Q7PAa5gxEGZzc+3m3q3Tl/ASKrBGOjgFLEnAmRlMczWWGpoSTfA5hLNe3+VlKoHVY4eBtcpQzwMzJdJMHgoavOdo1GkMnu/tkEfavA0Jbvj927WRYrJxBX7N74jvpueCT9pFTte/G7wdpDkMdB2+hJZ4004EMhc8hEriqrmX8Pa6I46GK62TFW67x5UatAe+1sStdNnlQO+5ofaBT0ghqC5Rn1yjaZuV8Omv2QYHOr1uZmt53DHiGsYG+7/pv7Ni9/MHo5mxRAIdm55BJCWwiNvmi2LlhYpyvl4T97K30fNATOLyUxfVsSpodwkrhMWNZFpxOJ8O9RgPGM8bouFwuYHeoGgMgywzIyhucTk9ozHh9VSM6i5h+R3EUF6UOEYEaNIUkVF4S0WCfKu85SZrm45e8XBRT4gDTDxARrldzdYpUCFouZz+fwe+0TKDX8CYiPD2/YPT9hn/3s8+gEutTtA+kTrst+LTMHOBIZZgMKOMZfXSwvGCTzxARvPvbszr/UupsAcJiKe8Xw4cykmbF+IaWyBm0BxxMa+RrHbqU2bCuRu3PIHyEc7KRja7Ak5YL8q2h0OWNWp4EppU1GRwuO9lacPCMmc2OrS+hwzbf5VlnfKnkgQJfPdJFThk/CBD5DCLCVxK8u0PCq8zi8hYTYf3733H97/9WmJ54m7+mEb6dbv0z3Rrana+RwzXgj5+BG9EecLBvtr9iRf18Odx46brW1HC+eEmc4rwdsjIlDaw9iqjMMOyc+3mfcIj/lfJ9kr21+RqEc0pZkMkJ/bhScvMhv5dLv2Vffm/71p7Kg3sio4h9X9qCwQO7OTfdwrCmcE+ZnlJvRTLNvcqAykUbPMACi6C85xDB1geWxsaPMrbiuuKZNhjqqPMkGsBX7RP/9k0ezMIud5hxXYB/lJ//Jnecc350QR7pPh8/EC+ZnVfvd30MKvpPaP9mEejanOhWAwyAcpjvPGMMh3pbJyIlzAbj9P7TetNfH0ChI6IGqw1k9+0APn3+jCcc4bei7eO3ey+YiceNseaA2vmQHvBh/xOjrO+oHtSuDHaDl9ZeNWRpqzik47JruvQPz89qrDKeagyNPLXSsmhN0DThIAgMNo/O3jUa9AsRnveGpa2qdBCNFPBoDGIGt4a+b5qK0RZ+WU/oAlz3Ddu2YSzNdAyqZGAiLI1wve4ABvpuCmRRGGDyNFSaJPtWLTf7tM3K32+3G6X+QTj9o1s1VBMBrxa5WB1CPIZBU/Bn1O0AsH/6DEDhoH8yyCBPnJpDf7U+7jkSVL76r2sHSD8MYNAVoAbGqdy2Q+SEfRMsJxdcO7ABvHidSsnbb4TKojwnAFH3vBlO8rS6ZhheVKEPF/yla21fZjVOoDoYmFA03AjmcySspwXrukZt8khn171msium1btTuAEYWBqw92EGcSN0kWLX69aRZVx0xZMLp24Mt6jz1iwCtoEbYVlOaNy0fILL1WQp3EsKM1ek6doCaajX/4inm7ZrNCJHAlCeH+yWSBdyLVXm8DMnFmmu/9xw3l2pUhQGMCXPGIJOKvu3klKKUCPc5/3PPg6QUe+fcLIZz5vX+XHP+fv4RA2A+ns3BYwrmSK6zJ8lsvrmPj+/DouyUEWH00tmwm6GiKQfGfUTgkfgrIK7FKyxNJ3Lvmd0qEfhU1lbkEUIsa+H0y3rs8xBBGEY7E1AYwdo8Z9tGFTGo1Hcjvd5KKyoYuGwM6E4wy0epqxz+gh9UVV0iFMHAcbAYIPFEPpsB43P0NSESj81GwQBvAPCEeHlsXZEC8ZwYcTSWiGdezQNGicOgKa1Svq0QnDFtqvwo+UaCjwAQfvitNuSis/Nag2jQzNHNEuxKOqcIlBntt47MjpO1EAxtKZnMzjRKqvmDBHKN+PHFgHvuxkZ9PTv1ysGE3hwQemHuB+Jzr9JcNIIdftbCOuwfSrfq8I/znQohjPVJsRhw7mjwzswcwyhkIu+7S4ZkyJA7SNFcC3HhSjPeVVUI3gA79wycsjQKJ8+ojSOWHYhJgbDIgF8weu6mOJM+x0RDa5m7Vsv9SokVUX6PeN5CF2HdPqhuBSJdc4oQwGT0dkhEAc0eyuzRla2wZGuFPj/3L3pgiO3jib6gWRIynLZnp65fd//BbtP21WulBQkMD+wEAwpa/N6hnaWpFi5gNgXc/pgSydLZHAMkEVmOXg4rYojvuEPeHqBDcy5h8zo0dhb3vyAK1djpuZDxe4dfZ+8hM9TgkP4+h9g84E/FZhRe87RRMN5XfzyuQ42IfGY5dnitEIeXpnnynGzfqfUQ6vvuR9utX8oPaBZ5PkX20FmOnasj+49AgCUC1kWD/PaZ0mz9KQRUN7p9W7452uCnWSM56tAcEN79y7JWghloe97hkYZttaM16N5nfEyRITtB4V5uQOoBrEe/UzKvLizkpBG7eWyS8s0zeGk2bBjywFT8NOEG01OewKdAdx8Dz8xshk/RSSTr4MbzuWhFMVEdH475Uel/Tj3wrySUC9lOr06/vC65peCsg+bnzOICO3yDpUI+/VV6Sm541dBqcb7QXC7dgA7Kp3gzpxaUtj2sDmDgTS9dLeU7j6C2jbll5o6s/Xe1eDBk84q72u41Gg8AICNb6tVIy5RMLrVU65aNqm5dBbrphmvmHPmKj2vRn+PhhXjDdzYoztzgEGskedazq3EuME0aXKsSeLngOBTVZE68WmQFsFiBCfSaGEvmQSnX+S4YK5zHA+c6/3wTDxGSwhWiqzOiNaIghOU1iLNPRwOBajNaaDSHYhg3AS0EeQujnIDnmO8AlS62Bz5PFyQG9MNbAZpsv0jdwFOBLkD48YQErRLnXjVxk9QY6QbsahQOEV6uQYtCSBB1zg79YikZ96W40oEb+ivAnr3Tuf2FajvKuiskfeCyUclwucTAADY5Qa6Ekprs/4yqXOe8ECrJxQq6Pcd3DtOl0vQXaGCMXqMU+UZp2uKJUUK+m8d0uqUiYXVkdPKdXlZq3CqdkAlVdSLzNrYMJo5Fb4GcDSdaXerlW3QZ3Duczd/ZAexN8mUw31BzGdrDZUKTpdTPMN1Y7U1vH56VfmeB4YIStXybKof2zHGQEGDUFejK6ZTUh8Drar2jmycxTNWwTJlyqRdSs9T5Pja9fV+Eez7joKK02VTnGap8ckyngEIh8z++op6uajDe1UjdK0VoxRcr1doFgZFEkc4I3NEcnArlaxcVX063+LZdfgcfNEP/+cdWDQLClu5FschPGwhJcmMgoALKgWjd7S2pX4Rzj/9hPuHDylrA4wvRtAFss9CMyp9gFDlN5zpZwg+hHPUvSzDTg7XZhgXQOPu2UDVYFcAsnJc8PTXiSd0eBcisJnhA7d+Z1tkDCIrrbqyyJ6R0Z0+fwQF3nwnqveVQL7A+7RfRYD7f//308jgP7v9KJb+G8o/faDH87kd0yRng7ajCB/H8Vm/p+V9mrODHq85sFXxPcsev2t+5e27Qxdvonwh1We0qsbzqcOYjwpuwicvnO3MeA7F7flvLVIx5QwWzqx3XDNx+Mq7+LFnI5J5+nnL2Z4e5JDvb5lX/7OuV7nZbSLKk76cz2BhvN5uGOb0pdebzqjAHM/nk5T/cuc07cHRgbobG+bBRKdtA0Hp1b7vqjMG0C1ziTN6QkX5cRo4C/Aic6xXgpXIwaQb3zJffyWC+UwLnA7NLsGYOOMDAT/JI775P6J46o/KbPEMjxzP5x7H8aQv8zP+rGOGCX/KDFT4AxHjX9z+PgN63nj27bORqsYIL6lo/HsokA5LQcZguABJlqIriPfz1ziSrY+nH5qyd6tv/w2ikVZfcf9f3x6B9UhIlejodhYATBwoMVJT2/UimpZ58GTsnHFS4wFCOBcSjNGxj6KMZFWjXi3VCKagiBoxybx1975D9ju22mY9t6LEudaCOgidCPvece/DdyxqIQxWw4NmcOIgDsxTBM4K9NweFIlwuDnM32cYiD+8PekjOcf51JDgY6Bg5IjSevt9EtOGIYLXAryY8Y4OT3OEGAYDJ1ghALqeYvZ1pk3+jiF/x42ZqWS4N+6BlSStgTrugroVhSkglERiKVaFygwwkOUJxt9pjXBP/ycQjT6fUqTioEqooqnqXBzX/mkEXElGccDRna8fsJ03TUtJNaLsRcQMowyIG9eMMDWrZWwefIEbjcHRwBRP4+vrp1klMmFTJrdYWmg1opN5kXr9Y8Gw1O7OO5bwVBf78/lwb/xsWBFBpOjR4xXSp1J2nZcUOyButJWoIwnRdIHx3C/uT41MyLRjNXDJAwzGI4/70QVWZybz+MTT9xdwUWWo3/Nsc0j+Ju70YvXbRGLswlm5czCIOPMpdm+ilyE8hBCR37tGsgY9sLFUM6ZF6kNTPggPQKbzlUBUsV8o8AvJdAjIwop4dEgQYIFQBXltzKA5bLDp/R96dlBEXfm6HtOXBsb0w7Se85n0bsAvC4ZP/xESgAnMA0wl8KBgKovn/WZ4FKVnEsZC5S5KqVZHdTrANOPKiCqI2BRXKyOalSOakUBC6TjXXcLQ4Hjfo8tLcV7InTkYURbBIi1EdE07MyowlTOYIDTGwE001XAtGvlSSQAaKDzTjFKB1kivbqzQSKNam2aU2baZ3nR0nSuWRVk9V3biA99rX90C5lJ2GknG87wvaGqFMp+JwFMp8pye0ypJzw38FuyipPmUZSyeNjKPWQ1ZnBQKj7hjcQjw1PuWsWKkyCyHKTUYqUNGOFEmnBfRhM5DsISRYpl4okQ3fHQwvGcGCTsa5ICWKU5jmPWbBwvg5Q9Y6xPrHFokKHlGDKe3nuWjoprjB5EK5DT0ZSMbhX1Nee5xSfDla/iAow/HZF64RHrm5vvPHRPz37J+NnZ3ioxIrHQ86icH/M79O/skSBg8YG0Gsi9vnrAX9GSeo2NHD31djqX3u9stsEZYH6+T+SNSt4sILpd3jn0fos8X3nxRCR5agjd90XcI7E9u0QjPO2DOmXIVlAsta+pOhz65VKYRZ+Jqc+gwnEMUlEoNOGZYV/5cU+6WE0HcHyANK3aZdcBn7Jme4i20SUAqnTKJmc6xGc9R7FOA+8medUd2kiCDqe5ZLzLc0eQ1nvUm81H6OXNgOTyVgIzEIxqAK45gi8BjMGsUOuEGljPwOkCXYnssGII0nwbbUCl4iBoeiU6abMl4gSKcJlczp6mcaXyq4U1hhecxhkUMOv/j+zfRHqiRp5Sa8Lw7kQnAM/vNII0WcgNxtQxHzh8yS8wPQIH3Y55pnnNDltJrrSesOB/Gxyl8hswnkn0iAZnPy3zTsrJOLAMPrPfq6fRQwoxqjTmgpcTR5NdVNzCduOZ9RMX4ixp4JF/hGQhKUWMVQWszl9MM1uC0XoIdRO4kMp02nX6sQxYAm71P00ODCHIGYLCiGf7UcUGW3k06ADOeO24UZsu21dHdmRgJtyzv989MIOYaEBH66ytAZ91XAqufPhfGV+6tNuUSrKm1A/+zJQNyntdLUJljnvG0lrBB94voefxGKOc602ODgOC9VW8BWyOvgQ6X34tdG/yGjSXgxEFQUkrvMUtqrLMWbTGcHxmfhMOn3sozYxTLqrLhdNrw8vJO4c5oere0tXzWiPoCoJoj0kZAuVwAEPbrFe18xrjqvAoRyNIqmhuLwqutXwREiKKfwraXcIbgZnv2rGsVjhaGa71OPQ/Aso4RdG7b1lBqxf1+X/kmqB6CBJBdMLZhGTS0zFNrDefzGddPr9P5OO63PZ30Id6P0ipqbQorzKrfCR4bADO29xWn09kcKvS0ysvJUTw/eFnYueAETQMfhwQRUFD/439h/M8A49OkQYDpOzDX3QBPS02aU5p8RMVPYHxY+WaCOZdNfE+GW1igjsVOlQz/KronSHH9rN3vso44TLi89xblf7tltKy4jpZzPld5CgHChp8B/OJIBiBL4+6yU36W9zfRAQHwG8Tkj2/v97e2jBG+g0t8aH9Wj4/PpSfHPsfffeneP6LFPJpM1mrF1pplratW/s1lk4M8A9PbkjuKTYftfC3LGiE98cXUU2iTGGToo21DBwvyBUWCsa14mK2Fvj6O/29pb738CXDrnptyIoHQRw8npWMTAM0yIN77ngIy5nxP/cHc+munMq+tcv0FKitUL/lJNXgORxFeCx2yBj2+5Sz8Ve3P2gDf0CTos3bkmfPQLzQzXvya5s677849+fzXtmfBH9/Spo7EYIjcOX3tSIDBU3vVv1/7m1O4r5GsISjoD7smL4u2YAztuqyMOBJZf5ymERY0Kg/ela8QvGAST4ECZgDdAAAgAElEQVQC8CnVb/HjuR/KijC8/jmgavEL6KFmyvrGt35hSf2ElTSs1wUqn/P07D2TuTmcdSnliHXYBSBFnm7/ViIIwIQ0V2J/vN5QncmGppgFTEghBot6PRKRGskIKhSwAFKx23M2ZnQWfBwDL2etU+cSj3sB1zZTVxNR1FAiS2dMplg0a5qmy2KeBs1gKBEeks/aKio+J45/d5vrPo3oLhQKLMIDhCupgshZFY9I99FcbW1eUjjIS8q3HcwFHmHsuH/juBwEyiftj0Ofq4D1sG7wtDEuLGptlSzkap91hGOMEHZNexN3HjvtSpzSLD0bNIJyO22hEBBxobzqbJkCFaHMsIimwYClnaxbtXRhGt1ZWg1vdb12B7iiWNTSYBeQgfvtjpd3P4AxUJvoXivARhXDlWlFlTElRVur8XwKcmo018/wZC/VUs+Z0a3k9NL6GQowKiFI+rqUAvQhc+yiNeYEYsr/+adGcL2MCKCTrfN+4PwM7tk8z9WQq+sbY4UKruwu+m7gCHxAs34bphCqr5D5LoeTyRFmDl1pRKJbM5Uco5NF5bKgSJnKAjrC7xycp0hS4xdHdAlccHCDiTGpYYTOgqwJqzwczjWl84zu0Mbp+mw8D4SZ9hkzo20NfXRspw3+oP2ukQgTiIC6zSiIEIzcgJUVpSHtkL9kTio0MwnylIc049haUj1bVx/Z45YU3gK4U8zDxEtMXzh6WFrP2Ceh5eW4nWIGyXiQElPgz2ce8DSMpkfQU6WGUKi4oGMM54U02pwtPauIgErTvQXdX5qRwNNWMgYTWIamuhwDfe8QiwTx0g9edoEIlhGBwFKUPsMjeAAZGpXlhgiYwKtp4W2eBMAY01BTjM4KhXMQrJ9USKOgS0G1DUoEzZZRNZ1bKxX3vYLbsOiiEXt7NvKpXqLZ8l48trxlfd9LCOES+zrovOMSU5qrMXoapAHl9Xoot1eZIB6TnqtGHePq5gVrP5Nz3zyofCYBZtia/Z0wJulysbVhSxfsGSvsnG27Eji8PpQs8VbgdddJcTQEOYW7OxHoYyfT4HM0lfmTk8g/NWOKJHQ6r+OhytohEiUsiAmo6nzBovDFxQzNIQQqr1qqpblFQ0WHKx2BDq6ieZVE04pycR7KHNGCMdZsA3N9aVkzx/P+nYCIwAMRqB5Ks2QYS7PCCxzYKNxYRbTIBYp93HFG17agxjzNTCtufOFlDWSZ53XdH+SNpBjJV/IBbuF09wkYTdXMnINnV/mr+cYoZ1Wwf3Nb2b+3zy8S3XoxrUusfXp1ZsTn8G53n5BnUo1O/pqzwqEZLeVqcHpx46qXJuAgf07CxTLtVHPAzJUaRQS4C8pLBe+JXiec82AsO/DzT6cET5YvSLnR//NyMM3efXl2nlm53UCn85wXw90VJwzcl7dORzn9zn7DcY3sUyMAT4ECA5cZrmYaEBTUDZCyQfod9WS0XYB6Olsq0YJxF4jsxs5s9sar9ZsAbEoUsesRIohsyXBikobhLILWlhQojXOjAWAOjZhKMzJi6Bk3ppuo8xQyfwqDuvK2fd9BrI5omumq6btgeEAtjjanR1pJU1Zz8UZstRXNIxwOU3moYvROUfxxXQJSDBcmQ2ps8QPNk+UBmVRECmIdghn4nZbaA31cXieeSKP9WUSz1sH3Wnq3QPll40FdNtMhMZy/k90N5x0xCAja6QS5q2wXNBWIsbo0MeRmztwnY2v1/fvrMGO7QZeos4TDzZwL7aPAMgrAQUKCH2FRWsmvORLvZhN7NlxwCxgQyfLN5EUJFzCuGAD4lWIuQ07SAw/3CmKBkhyRXJrSPa672+87XJcDcmdsLE5SzLpmcgPqpjqNgZuWK/F7ChlPZI67ZNG4pE7xhbT8kKqztBeDnS/VDHCzZsBsCgdPsOWTQ0dDutPtYri7WMaoVhtqtRTGVR2r3r3/0b4r37H3uzqnE7ROOIkGqAihCaH88B4iohHmF81ysL28oF8/Gd6a8tBgMYcFmetuxM11QAUX6/dlwkfMIwI/CAMdw/Y0UHFGe9GMDQyB3AZOcjK8plNKtZhcShDZQTuAbdN95nI4ETY6YRelHzJUc1rEDM6YvBSIzJmA1ImbWfWEtlTKiw1c3r+HsGWi4yf0kGyLE54T+7gm8U1UgnbVWkG1oghw+k/gt//6NCPRacKAj49LwWZ9d6cvIUL7qUJ+VZzzo8HvJ9L65cUyDylfoLuskvp5TkOXyxUwHl2xkQYVeKCCZlyCCIjZ2JdHejrB+y3GKU9NptdTZx932mIsb6Gks8/PsuNVHB5tHck17wicf2w/2KFcH/29fF+99B+N93or8tzbl6LIj5GgBy7sD2+/0ox6J0wj2i9v9DPzqt/VHvj+zz9J1QaaiaSWhq02bK2htTZlNmZoxUuVDdmdxw2OpqMcFnnds8TEOUJIgKoDP3KkTv8w4fPAO781tKQW0HNx/C0a4bjmu2f6q5rvqHjL9Hx91inI4YT/GqrIUbwKDXK53ve4M1R6Niw2BNqsfGh2SsyvqFQimHIa0R1PTj4BAM6nE8b1ChEtVVprUT7XMI6WqEhsURrHq8s3Me3HCdBFn2Ivraf+AS3rqNwA/qOsOMcj0b39l537+Qv7/ovvPnx+tj0hH0pikmVJVricQXB/7n74q9vfnsLdmXndpI+TO71YZe7ORcD8yvfonSqgxELO+5O4erjr7cZQJeoDU2B/r/+UnXloD+Nc5Adnvx+ZoAGNLnOB35H3EA3+Y2FUT6eGyfgJpoCuyugRQrCzY3utKPUKLqqwfzlfQKRpF2vRCPcmM7JXhAM2PHpDDXHGcLmia+QNbT0IhoOmwS1G789/vnYz0voJgZQMTwdI+gMI6VvMbShgrF9zH/nYJ1H1VXul9R6AsAwpIUDv+5Fp+FIkuj9LjtTuW8b8GaPIZ++zz8f97OR4srZjZ7RThSXKA0AotYF7n3gpGRhiHphRWgnFCwHBGLrA4O8giHkLUxJkEUZsjewGtpMKmFRhNVNrMBrMonXDIBZiXwGqKMRmbGhmdLP6x4VQ6gbhboZumSl1KKUqD8XTXD81nlu6PLJUv8YMA9O4Hvs6LZM+QqwO5JwxYYRhnJAiJLPxSgqY95kWDgQ6AbhNxxkDjLlXQYvBddj3tU+GsYhw3IpqNJnCqB5TPLHaqFI/EzwtNCzdr3KsYBCrUaXM2pmeypXit97JRJplICvHTFiICA9Pa2z9UF+oKSAo4jaJ1Dyg3K4t7Mzy23hujsaeGF/nHPW+6xp3NfSWUrCdNlxfvWagKQ/YFh5271Kb0F/jfaaJTznjMPKBHDsahyKajwjwjALk6xZqPVNu6WSQandMOay0I5w4oF7vxRV0qo2zunW+ZzViSPmRFOmVhye5sw5XrtCa86uOEhrBraUEKsjqqpZCEFSIw4UARGosFwGonjSdL0zlEtNJIaSSRxlbpHFtDbByAjz8PquXbX+FCnrt6jjT2qQJRGYQAMZtj9qLGrlkKadZDfy7eJ13i6LomlZ+WBpcT4FLhVBJI1k0Aoix065jGW6IkJCcwonSU2zSmjXBVnvZm+6i4AvDvhZpXx9hcwrcUwmpKYitL3LkIhM8LntG3jSeS3q2rECTHh4mdOuY9qvYoekBzhFxHsbUpYeu3HOcOGstx/vS9s/wnHHjAuRY+R03+roRA5LL4WRjeeIPUgcCT9i+EFt7NYiJlgEqAmIBY6BI1bAqVxSafFBIHWDYldDkZUaKZkmAQKhACoPYBX1fRe+k4WPpwRsYUjnM+0oAKQbnYotFUvia+PjcCSrP90NLcwvlO2QweGgZBbb5cUeacK5ieXyUCNbZnkaXN/nLAFc5HJ/A75Gu8OcYU7BKWYJ0y8NeoxNZquRJc3gM1Pb5XGBHnKsHE0xa1Fer2+yNZ8n29bM0918jVT5C/zzubhyhny8VtWt2IWzW1wHQ2Qw56OoACTE8uT485sFoxRgMXAV0aeo84XIQJg0RYVXA+1rT7N/n2vOxp52tBG4+EAK+AaA7wtBq14lYVKg9s2F+d4gT3FGgqXEH9jiqY6HgE499mpLj7EmWeUQIYIBpKA/ritk7r93HZDkIwOmlopQN/f5qZ83oGB3Yoy8FgnLawoBDRbNeiAj2+y3oQkGB+++5kVDf6450jm3mGrp8UGrTzE5UgFLhEf0auau8S2lqMC/Vyys1NMtmxQKTtRG8f+YbnUfyrAZ+TDePmJFpypP6mWisCodYoSZ/pxWo4vsqn07abS5QRdcfJPGKWPGVdC60Pvrm6aRRJj8ph76lLkiad8WIoniInUfoMA42aN+4CwQ7yOBXvHsnQG56LRv/0AlaKkwAukpcO9GzBMbIMoiPqMCyN2Re19K199EjGg9nRN3zoKO+22Tyz89WSz+v2sdk7CoT+KGRyikzGNK+S3Qr5E+xTDdUIlLWN6BnOyCoc4nTZQBg6YZDBPKJAz68FrSQBlOQCNq2YYOgiEZrEzOIR6yX4yyFoxkpFzrAQ+lDn4tnVPhZW2TSJ+eCzzp8L6VgO18sc6NApGDbdPx7H7i9vgZ9FRE0XMDvOWWAFMirgF4oHCe8G4UmvSAU9DGmAcR1Gcwq/08MGqMnmg8TAPBsRbYOasS2KHAi0BjAOwAiKPgB/PpqKcPn3JA0iAjGnVFOSDySZZy5+utlfTf5T/3i0awasKDyhl47cVstGxjD1pZ1D9DB6e8rFtgz7GXckeWOUtWB4P1//ifu/3UH45PNqfPWc3/Evy6PAdg/fACoROp9j9crADgcria/wQLL8icG32n1BLMsEwCGyVW2XhyyYMa563jdcestPjDDRb7+OKdOV/QpHxLN16d7Cnd7SMBzOKLZ+LKc8Ky57v29nf9IX7WsT1vOWPnv1hyzF3ghuC+3b8Fx39vcOaqUglYqWnP+RP/8/QMARQr0SeBV9lPa5Q7skQUGsGwrtvcNR/heMQy59ieot/OY+ZWPAkQiz8cvdr8sn/+k9q09OqZad51EScdcdxC02PHyk3c7Xa9Fsw58ul7nMzDvC+cIUVtPSXhplSmNF0r85LfB7z9vjb6n/Wzk6Fkk+t81Qnf+DdHqsDB0IBHhAPZnI6C/oP29BvRvkOgjDRFgM//HgsuReL5CUPARP+EH/IqPT+9RA/qMbSUAw5D59YtI9fn5o4eQ9+3x6gMyfyAWx6sFmeXKtCMcsYEwlnK6nlSaAUS9I6lY1A8mUvOodBZNw16t5jMHU9tMQUTh7VRMcCcAH/gTatfayWooHHh3fsHWNjXQJM2He3HXosZzHx8BKNXTHNEUjmHKADlgXnKBQjTIEZKYte+ArycYQd4+9ac1yespqjzxQb+6UHlonywS/Qw1MNY4juX6Z8MQHBjpJx3KSgG95xsGk9q3TqM4WqcOwBWoLs0Dbmh0Ic0NPcLDUpBYGkQ2CDchwve8dlFMaVMwtWVmnBKAihoS3bDhfSBLj76dNpRaprHL77dUYRCNUJcxQFRwOV9MuNM100j0AmbG5eUCiNaPYao4nzfcrmriapWwjwkb7qHsCsR5vIBIGd7qkaF1U4Vv0Tkopc6IjxxkZ0qKwnp899R8pPM0WKNbiYcpgGWJPofVedz7PpXJd4BO07vbXhPns1JQiXnoaRZAIxBKcYeP+RAxpUEh0ig+rKhCgDDUPRi/0gue4dwenpmuOFGjebEICk9zrQIuQGIZNRJc6Z8JluwR5JPJXd4uKlrU2jC61gRnJogMTc1NAMBpvmZfdfYRSiWFUlf4ueCi+yWEl/S+sEqIGkTBDB6ign0oRXz+7OWEyNlISSECOggm5DcdJ5nS0MVgjay/JRE4W0tx5UHOdmPpJYXWVKoELdHgNbx9z8Y8saWtF4Cdlrkwl9fFHFeEIIXV6F5rwJ+mXncnDou6a0Ap3by3q9Uz1/2PJXmVpOgHLYtSK2HblI5qRhiFuVoqatH3UikWnUVoTa8RgRnePC0ag/vAoB27CMQywOi1rOki4VGwQ2vBo4VQS9B901lMoYpYhPttB5mDkOI5w3cwxyEeEELgCBkKv5yMsRP+/DPTttW5y/exK2Z0T0vATNR9X4ErcIsKjY5rYIaq4x56q0nQwGfGc/8tCfFEhqD07LkrnU/hUMJPB8IZlZwdbQSwtMDFyJ86hCz2hTSW3LJzQjQnYwKN4soddRzBqrx0HnAqyPy5ErzKozLCsI2tjytTUDQifLAApNk8pHgCt3kvQftFYlH0sBS9mBl4qAgKa9pjra2XuRhLs0ymjqwNRZIXvSR1jMg0Vi/GppjAqXjwtfGsEZImUmyNfM5j7hOatDkaRks11exAqepkOtzpCqKRX0NW+vxmk+XDZaFCqvRyo+CzWzw1+2JE9V26yGqG43ZMOEkvk/sKhb13nE514WffbF84P3ux7tag7/ZLEv1xx0IRQXtXARLsnw5p5MOgJFAD07pn5X7XGtxuJDJ8Le0MYla6b2uoGWTGRFCIXQB3oGPWbCx00/q/hTa0UrDjFopGlZ9sHKUkvPGWLJnnIP32bqS5Hfd7PEe3wsRMeY2yXbXghPv9hgaALN39Mzl06Y/TYa/KIhkHrv0k2tGv6uAi5xOAAdyszmJlULlD6jtQ7WHAcnWPZ5lx3rIQcH55Z7LsBYBgXBmMO9RApD24vH8fPCOgUYkwHu7UGn77eNUSE015vtE5Jo2gtBjmRKaRxdOpVrMczyjVZnUi3eGMB4cxqLXkFGcOclp+RQ2UlSpkqFNbsTIe6tiqWHCWDpi8EVGJdNt1FIwyI7/9M2Q++hpoemOR8650XjwiPbXci7DXdlam89mTFf0wqFJElpaokTyjtuH40DtDkx8VsexjDHjhiQFG2wpYTpZBicG34SY5wIznANBxAxhoN8UBkfIfJxUxb/oeq8pqEVyTFrqBu6Ya9ctAnQ4UsgxbEincR6TtNh5H1lnKDhNOGzMvYrvX9heB5Gx33sBpfQlXuGxwenkBX82JgJQv9odFqUQTxIr1mQnY6qzR7LxkbV6+DJBdM8W4cDcgILnizgNgxhkXuDNrhdUPP21GCzv23tF7x32/ww33PnaXXQIgJI084VyCoG4b9t6R6u08tGwYfzjnyDPLrC6EGPYR7okaMe77Db0PjPtNdVxD5YsqJ7SfGz7dXnHaNINebRV16/jw3/+t6/HuB9xfP8G5kgJzYBzsO8CYCOeETpgdt88SPUPszUQuXdYjAtr7piXlSsEoFGnUeTB6eQGTlvMg9kh2gcgOAmHcAWbdO+2drb1nf+jrfIudI9chGX6w7fywTSCCPu4gKuj7rqX15DFjTsij/ISqZCY1frsAaQ5rRDqXJk+d/veG2y9pumga4Igogq2cB9WZBKrxeyVdGxUPHYQsHUiWXykgOhkuBAcj+lxJCv6b0nPnOBe5OKDosa16RZtDCcwBMT1iNdLAplz+DYJ3trS/PdsvZvAf0NTMz67J7X3qnmPMH4+w8KX7ZRrOHS18bZ3yr33PX9UchmaI2ZfbV133KBR/dSMLDvKSFa1UrX9uWTiCp3PjuRIvuCzskeieSW1EEIlfbHJOjMfh0OXj1PeFn7b+YdLAh75/AQ54oZ3/pJZH921XiwhQi+puqWCzbML7GJOXN7w2TAatpg/brNyQOgXDDOcVex8YtysQ/OJ8M1kN9FIK/vXLr2ARtFYxBlsAiSx9lEIou/bF4XxmoTiM29c/FnKV+9bx/9N282zHVXwrwvxbU7b/riYL1NihFEC08DtTHxKG9iBYAN7gn/5d2t9oQBdkHBdLEb8fFR2+/1yhFKzeQsgPbxGaOpxloZ5tpNlegomgp+cBTRux4a2tubZ3IHz6p23UhGvoMIi3GCh3ZBC7iezaSJMrvmmcmBnRYlM3eqpMEggTCCZE1KaeaKRM/2gNRQg/vHsHIgkvZTElulrtCXvvGEZGSyHQcEOU9t9Kwxn8aN3aIm5gl8lAJkSwjPeNJXueLeHJfB0m+3v5kUUx9+wZJMF4R2S4TGYZUOOMbyC/Rns298/dBMkXpKDrI7OQ9ls2jLlyBch7cmXU/8omUDhgiAkoXq+SQ3gGVMGcFfcRzGzpbWudkRxuBNIIbDIZU4xWkz2vGPwJKtxIoUjrfD6DeaBWjbYUUWHY03xynwraCoIUwtg7hLUu8XY+WbQLoZCib3JpUqDlCsxIS4XMOP8j7rcrCEBrsPTUOpBi/ZsKxakYyJEnAo2uD2OGsGWeIIxhwpkxMQyCjD2ERN/vBGAMcyJgTWEpIxmpIIBojcLe+yLcUpl9iTHbYjjxnicwa8qZomkxkNGB6Q4DmdcjXGEotyXS9S7A6QkeMNoxQWqy7SykNe/NgF6N8XQDu3rOTyOd99sjSyUUbx6VqVOk2QI96Zu2UrXWoNafVnh0ZVuMPc8DEPtiKlUnXgwFlF3nqUIBRG08rY1uWUjE1kgQKcjj2S50u1Lm2WzTIZ1lXpcni7SQeN38zrY/XgyaXrSitEgIpmyexj5NE00WAiQgEkvD7hxIUaFPw73gij+W6SwzjQESOMT3EPNMnqBjYhDpfVFrL6XD9qwOc88QTlvDtp1goIzWrA9syvjSUIumY2/tpMr+4qmF1Vmm1N0iTaweL7vgKtNJTUSjLihHZmg0CnjCbCHGbsIV25z03tVRxAw7bI4H2+mEYlF2xUpWkKXkrmVEyvs5fi1HMPf1gV6zrOnIc2idESNPaeiT7kbxhfYbfxMGdkwclfFVGBbyM9MzpgE5w33aV3B4Oe41XrviyqkHPiD1yeugDk4lHsQE2mLZgWD4YtbLXQzAdh7A5On89xNJ58gHOQyQ4Vh3NAgD0UPz7BgS90Mk1lWMbqZsuwF7TGyZhgpIPMWG9yOtq0UXqwPXxEPqUFVCAegbMTtkpeGDSgPN2LYEQhKwlXmiHIXk74lSAAdYyc5sjsciBWGCrYg+GiOM5713FCkWjT7UwSpS9h/6GbOe4ciV01hQsBqCOkZS9B+fM/ffQen6QDh9bARprBkz5PA+mRKX80VaLsLw7Bt9+HI7DOzQuWVsiT74fdnRSo/MKMx6UWOTXNe7AYBxQynvLYr4Ys4rZlhrFWPoYmvmEQHGACdvB3e2A7T+OzNQK6FG2YWq0celonj9bcAyZHj5gkf9xHE2cjOy/zgzae/Or4k/O1xPMqPwB91tPsiMCBsE++c7cjil+yG9wunvEf/ses75c6UrLyi1h3G51YpKamYo1WgsTYdVN2JoHwSlCArOYLkBmI6QzIx62tQxzQzowgMdA+9+fNH6u1Cl46kVDDYHOJqOlDVw7OTDFd40Hfu2ab1Ql7VBxer6iqYBrvq8SsVos/OoWjpHxOrAC1lUqMtCpMpOmuV8AI9EmhQH5IYR61usB81aokDwuLGlFfF+2z4txcwoKpkAABfFY8Qlso5MXJVkAef0Ds5CoVQvWgLIU0Q7yo9xM6uTg/g9ZiiXXGJHwOKOvXXSDUx6zYk/jx6Io3BJODnROwAiRuFTRh3YXGr5m2I+DzqvqwHeeYBMu3zerxCra52P+xrJnMDlGsYt5Ns4l+cZjgeDOTBY91JgCu8t1YGudWa7mQZMTo6eANUCHt32kkBT0Wt+J5d762Z7uFRQqziJKvP76Oj7jvu+A0VLBVJR2O0yIN3Teiee3KA64z3/fto23O9eC/yxRVT5g4QhaVrW8QKuk7IsVlqvSeUFUn3W7XZHv98w+o5yvmDbBm77Dftvv+FVgPf/62cAwP12w/mHH3D/9Mn6YXubzBHY8CsZ10LiSu6stTQe5eLZXxweEm4PS7XuP6oXS0uv8kItVefV3k2RrUufP/ktK/dFAyJ3g5mXKNH0zGxrGeiTPmKVFJ9hFx4CzSw8xxiYgD5zo1+KdGHwYH64qIwbj5EoU7H99BPGxw/zvvQMgTpGV3s0BYg43vfXiDlRKkxagjPQIWNkgZc3Ub1eHpcb0Z1erjxpdjSd39zomI3oPj69L0fkzixSeXLyfQ0/Y9D/YGokJi/r/F3Mc+LHQ/amdM2T5mfK4ffXNo9ed86S8e8ZfQ5MTvX4/Vuf8a1z+KXnOS+jwTbOX5nDDKz0g8nwLBZcwxyyNg/lMfx40LeMJ+jtnq/845TZnksCh2dIxtnruUdn70dYPfLDf3Z7c+2eMf/PjmNlpQczmjllFyoQ8rT665yIsPJtiT8FgK1VC3ScVob1XQYhtv+H8TNjsDlLjiR3KS4VAUj+WDj9p7UMRu4Q9KO8bSA/pnj/nvZULfPsus+ccBpG88sf9+J/cPubI9CzuuLtyczpZoI5jcgzQ1XGMIp45FE8+BHpPmkFwG8QvPeuHftw+Jzf9UpLXDoF/UP7euP5ShDoybFn/Tu2Oa/r3TELzhAGMbADvDKaThiKeX6KqCcxueHGNosrkztrHQ225xWrm8oYaqTYBKCiGTehkbW7dHAfqsgoBTcTKm6lgK6E8+mCerJaZhq+ChHCIEt7aH3pQw04rjyM9YDVfPU6wFBjM5wgk2jtD5kJLSciWxnJY/N5WlM1ISBwjXL83Ip9XfsafURmmA9npnQY17iCxODYPGxf3XDx7IUiQSjXpz+PRM+yxO9vbz3I5//5PnGzdKPHzqypTi1NmUV+6l4g1NJMyTJAMKNxIas7OA3gwRBY2rS2bTHfEL2n1Q3ujZfrfPa9g/uMkrmLYMMGHmpIqpYePrwwbf201rG+r1QCoUIYOJ1O4M5g7rhcXkClYL++YmdP+7lGJ+m37NGsDG4XQTGDW6sqQO5dFYtTQI6NYMqc7NuLMOgMTynpBg6Pdg3uVlPQhgE95CzDJ1natPUimlkpNFW94p8wKNnc53mLkgoesSmiaT+FZ+q2N1oImScC30zsOhMWxBmwNY33BMB9f9yALoVRpAaOgkg4VrAwxDJjDI9atGeKzFTsBLinQpDF0fvK6IsPd8Vkk72luCankwxhNw1LjJMVhmVXmIopiEa7Y0y8ov1bHgAPJ1ro1Hcm7pIAACAASURBVEGRRzjegyfbP7QEpjxIl/gpJJq8nEw42WDE6biIRl+66MWD5x43OqVOLPZspz1Do7xkqJPKNJQLSIZGfZMYvGriPhUWR+wjT+VbKqM0XbM+2Iiu9tzTdhIRsDWtMbY1U7aaQh+77ucCcwQ6aRo1q5faalW7vzmxMDNGLdjahvv9DjfYe3RWaQ2lD2yb1vMs5KUIoHDPAhkDXQTCA2PXuRtu0HNYKAVjdJRSISRo0lCK4rbTSQXsYhk9yPgH2Dx6RgYeI4zox8Zj4ngKY7rBeYBRgjVkhapdK1PYDgND/gy1kG8se64rhr2ucQiaKw6S/N50fmYoyb3WPbnaK6a5wg3gw4ynHuXse6+YoTwUvl42opboK/MwA5/zLbPm47JJP9Mc1tV4g1ijiViOeMRfJ4G/XZnsuF9xiOL4Yk4sYOfnTdHGrM48gT8IMxq3B/zqnhkxx1OxX4HAeWYgZ1tU8Wg6L43STAHKGjkxBjQTQHcAWMeIaXbSWrXdFMbZkG/zTRkf26yl6/I8D2aMXY3nve9mQGd0N6JbFid/WgbvtCIT/vLzkeD6+dIt90ZngwWoEO4+AB1D8JoSGatyR3KfWAQVxht4ZOMDPabl49iWfeWAHM/QNXqW4t732IRN7fMwfK13nIAwott+uQjGdRpbBECxGujVjN1MOyopfpM7oQyCbIQiyouJCE6lRNaaUkgdLUsBV438u/JHFLpgax5t3EBlR8N77OMVmq2rYCd1hIJns0m9fZuzmX2Pv8M0h7zzsBxHzt/Nrutzj9+JOmCx6UsrshhDF9bKaa6stxGd4Ji9FI2+bi8NhQtaO2v60FJQpaFubsTW+apEoGp723AqsaCVqjAoAmBDv47Ao601XC6XBb8WuuD19RO25MRVjbb1XaN1xZS+ZH10BxtXOFMpuo61YmsnVEvlHuvojqEyHf3gzyg0syU5d8+OFyyVsZX3gAikFIUR8UxRxrW54ZxgjtjJOA7CY+p22FZ3hynHIW589jVas5nE++CGJHO+tMfTQWEb92GFaRdaauCLfLHoGElpku/rwIkiqHUzh2njr6SgyoyCcztPPZ9jjIBgvJpkaXqTXV4nvOrkg2CORkQRSeu43nFNuWifosQgS5ASUeKn8xFiBlmmAgrew2mFzs3ZpuAGkVv0yGnKQ7N1VleAKyTx/75Ozl8DwLjegq8OPQFRRBY6fzgXx/kQhFXQ+ct+34HThPFCxRyDCpjOxrPoe2rb0FrDqTXUtuHsDkYQzVrGgvu+o75u2Psd+96xjw4wTEZhVdIzo0Czq2VgGra3Xl7eYdtOuN/v8J30DG9Oh5fUJNFPnzv79PjpAqCVgkZnlZ9Gx+v+AX2/4367436/4X7fgX0AF+D6y0fNLgPBr//6F7bLxXAu4fz+PQDC+//4/3DfbxBmXH/7eCB7FHAJ7CgGH3RJDvRnwri9Bs8ihVCSw7UHBQDKM7kctO9ds+2Zg6dUlTt4MArvdv/Uc5A0oHTQyZx+79qzlR5b1jqQlS+webOp1oxeiW+XKV/0jwP4EQALWj3Beb3sKPTVLRtxbBqVFwzKrxyqlQryOXYztZYd0GsHgGb7t/icE0B4D1iW08jEYU/OaxiZEvwd4ltp7tMF7fna2xfdp4YoMcfj9x2N6EsLXnz2wecl60B/YARuZKiR/2MY/+c+Or7j17CE6zt+8mWFGoiOy1Yxo67F5pbs+JfqAb+XIBdhOPfn/2jv/Z466n9X+4W0DrrD2Xc1eQPH/Q7FbYE59hWKTJYeoSqB/1WWH2Pop4zpcA6xbC9imbVG8D3eN+cdMr6V9O967Imc87gVPtseZDGs++/Paguv8zva55YzxkEIfu98OqHWgd53DBZ1K5TZj1YrqBD2feqtRYBaGwQd3KdDoOMzzybMzPj0eo1ADbfFAECpDS5vMQTFHAwh7+w56qjUafYdC52TeRwzGDBW7y9Ys29tR7vNB/qygfz3Gs/1vV+3zQ/iFpbdNIlA2AT9+1NbVBbm/o3b314DfWkyCfixUfonFM0mRCxE/Q0OSdLyR8RFakdPNoKmu/7xqzr+nL2+gHC142cQbpD4/J7n/WEtT2+atxCx0qvTrKmKkRlsdeUgaoAIppbMw97SVym/JiiYUT5taJp1IcIQqLGdlVSquYKAwrjv3Z6j3patqIIDTVPBDmfSzHNckFK82LjInleI0F0I41WIjFrpSSGd29Hb7HnkefLNN4SRLyMbo1pxv39dQwF6gPFwMFm8VO2335OYce+oI+ykjo7nO/P9VNZOAvNxXvw5RyXJNwsuz975HU0wGfGQH5LiGoBlQwCyVrDvA2RGs7o19cIrAKLiL+y4PmX0AbJoFiB54sOUJyaAjH3X+sMuQNkrPWqsbVtEepdaIV1Tyde2mbHSjAXiUpWAqKI2NaTv9x3bSd975zu204ZKddYhrk1ryFoqNsRoHG4nDDC7cKT7QqMkmu1XvX648tANH/YfpCLdGcJrGApjX3EosTTmfqQ05RMXTUXaKk3NzBeSP3ROXeBfmG7g4cKAlQyz6bg8HggjuitHDkz8fKadpSm8u3AAZrUrDzf6uxCjcw1IGP+nswvbvmOY7hPCmkXBCyWq6Dr7G4L08v0NOmkw5fjDr/VbXDgmaETPGG6MAtzb3I2Wk4m176GAecSzabIOhw57lZ9dPMUjOjr22MYPOuZjCMZuxe9+S3Ea7Iw9rEa5z2MpqEUVhgWEspEZdjWFJLAnxbHvVR0Fs8AVqwNd11oEIm5EL9DI5RN4v2MU0ghznznfS8wW1T1gZkZLpd8BVLTGlp62WqSdGnKoqrJ+mNF/34cq2EcyvBZS4ccc1kCEKmIReiXqS3vUuCE0dfYBzEipEXlskfYFgm61FwVGe4UsOl0BRZhRWzND+Zj4xOiUeqpriYegM5nWOi7ztRx23hXAQNC8I8u4RG6lj4m/8l96J026xwscpetC2TfNcHGdZByV8ER6UijOJ0MW93pWHl+/cGaxiShFIy095aZHnTvtYpFIoxcRmIXMmLgacL1G2RJ9mOZIHZHY8IzCuc614vdjc/ziyrtpnPDJNdwqNHl0i1gCzMADiu3lqx9zYk5vzIzOrqhx2jdliFKU9gxOOMZxn0iUc4HXljRaeeT1YPsX6Xwxo1istQ/NjF6amX7S1KkU9kwWqiw2BkSfYw5Vw/BNkRop3TkcDGTtlq9Tgp11MdaLBXONF+cNu2b+XgAB2QErYV44f01E6hh0dwNS7ud8t7BYyYv6PA39gSd8i65lR4Xl7GQI41xplpY5MhrowAsB/dNY997hPe3dOwCC8ek1TeUJkA0iQKFN6SZuU8FgUgrgDmea2UXrtqasHE275FHnRI7PtfZ2pQLCBSyfIChgUUdHzxz+pfa2xEmTfsaDnM+w3qc9QHmtE+ORJKT5QucXAFQ0DPSHt+e1yyPJ/SHaQBjQdNKnuJYM97VTRWN1HIt0olsxha5Hz2hkPyWDGjkPmw3AmxpPWmuQHTidzhi943y+6PNQcD6fcbvewkHJjbq71SZ3WlYKWY30GTmuRkaN2EKpOG1n1ELwOsQAwnFsym/Q6FLPcmGX+rjY3snMKKRGQmHjKQcsW0CxcjQK44vDIZHRHV/3zL+ta7LQSIeDN5vtPXIjVN4PqkylYroE0ylIgaVZx0RqX9EyLQ07HSvP5vS7Wwp3feF6p2enQpSbMuWu4W3mZrj1rtcUG4k8UPsVj/p3kblzAle7cVOMztm7zBlZI+RT1hQ87mGB842vcAboiHOZwm0heJMjP0yY5Qqi78FAASGPimUu6hzu2USYKboXvgrY992CIgQiTU97pGKtoDIMd0566g5JkfUBAhKrSW0OEOdxtgjpmxlg1EFwCAdemNm21hljEfzy6y/4+aef8bUtZOdgPBXneVaLrTW01rBtFbU1XM5ntG3TLGF9x+v4Dft+x/12w+16w77fMXpHORXNuGR8OYxHun78DUMYG11Q36kj6uv/fEJ5p06njV4wcNXBkYqG7hQDOgeIG2rQP0njMPlGLGMUMYNwQnmnvAyDgWEUgBIfyjNbk3UWclQzE6DOTtq9IXu8J+vv8vW5TJWWiOOA+SMeeChrT1iM86HpPDrQfY5QLkK0Dc3mzWEw867B08NdMxFzlV+lx3+DG5hzV76MOXPX5l5TMFl5HoKVMnqS6tj52cDuMvnQhZ4Di/5TkkxrB4Kv7vgAEE1DtAg+pYRW+R1HQUypqFjGFDydCeUZCISfMfA/Uf8bcLf0t41PlP6+noL8+7Svqth0aJNL/2MbkfOE7rCmjr0oGt3MVnJj+J/MCHTfO6pX5Nhj6elBH/3fPKBHDgWHjZMGLk9g4UE+ekIbH4X19V1/dfvd79SBtGLyJA+0WtC7njvKWESu69FWLMOFGtwd89m8kdMcd3xXGrFmpZnXH11yjwMsUPXUA77/N24Pth0BfpK3nYH+iPY82PJ3PfGNtYvTz77+W7Z/lgH9i20KXGKur14fRp2kjSuM+oSAY0YTyfQpYeybC8jQNOuqCNVzL1AB962eTCYoeepCCfkFhAbgJ5DWdIHgvSH5BtLa0k9bwujxxIlMPi+QLvx7fMqT8/Nt63sWxiY9IwS1UlR5R0m4g0ZTlFKAwhg0N9DoHSRAMy/8HVBFPBUV5qEKI9aL0Uo1Rky9k+93NaC/Xl/xcr7gh/MFl8sLAMG+7xijY/DQVPoi2EGRHimQNSxVNQpqNdgRNbqTJEOY08JVsn1z7kLwsJMR4RWCCqVrBZou7+21+1z76vuOTC2CfD25eDUCaj/1O1uUcjaoPjBZT96lb1qjR4/v+JY2b6M3jvuBY+8o/ZubKiZ9j2kdYITx0lNcsQwQF7StgUAROa0psQXbttm9ytQVS2c2hSiahhpgGkIL4Xa9qpF8FKCy1TVU9v90shTt1pd60hqGbvSYRj+be9HhtNbQTYARZtStgqApk0u1dJ6iqXxLa7iP/TCftExWMLsGeGxpygbvqqwlZ4o55sxGanqUvs6H4RSNiptRviJmHEAFrJyDvtc8HZM+G0AIgA5fpbAp+2zvyeyJ9+Vz7ZgCGrIanwUC3KAR5vD3EKIW2ildR8DcbbpfwlgoQHbQcGUIDza7CAUuqVLMSAVIGDXXlgVc1S0KwFClEc0opOV678ciqGe6kiLOXZBervbjmpHAU3sDCodijhnCBNdk+TjdQDpDx5beRR/eonOxTEfjDs3xLXQ9EMSUjBRMKC+TPVIS7NucJjrMEDVwkUaYm++AGTMqWi04lYbBA6MrHmCLdIF0hLFJdG5YBKgMGWaQl4lzHceUorDBzdItOv6w/gqrx7YwQ7YGZoLXtG6bOrm0bcP9NjR9aaEwvABmxBVECujetX6kp7dkZvSxQw2GsJqiApEK4K6GiNLQtqYRdgZcAs++4TtQjZ8iA7vt/1qUYxKokxBYwLVb5GxDc5yTItcVf1FE09Fu/Ibjeffiyynb55Ie9Dx20qK63NDr/TfsHXAmygDpdZH+c77GyeDEOyv8xvUCVTxOMJ6RgKE4wKFJXB8sSr5IHB58zXoYjwtInSVIIwCaKXFhwqsr4iGCzgOtIqLTfTyTJxIg9piuRdYpxtyxgIs67rmh4WEB0vqE2t8VJs5n5nUwdOJjZfZllsAxxWmM8f/MGq3AXfdJ96wFfViaYooooFIIxKLOYF5OIhSg4loCw8/F1lGCnrHVFQWpsay2hmFpaD1VcygMRN/JxqE6jxqhNMY7TFzg2St8J+o5MgWUp3Gv8Cwlamx5lplhweQJhpcrRJ4dDiVw3PvssYGSKehomNHYcCyVKM1STuY0JmZMXxRTihZZGEUY2fnC+SukPh3H91ajN69yfCJBJ+CfBxnAf20vL+ivKsm1dy/Lk0M+FM0UU8BopDiU6IxZooEChnX/jOAnayXLwgH033QeazmDqKC9aI1B9AJQAdEAycCpvqDKwCgfVTbGWMb71gzJ05Pk/8dEP+CnRfk9eUg3CByVW4w9lKrOCSyXBJ74vLww5S6CjtGMa2c1iOOmK8B3Vl5+O6kxvVm2lqbR5poNiABMg7o/e3IT1XhaArFmkSEhtHNV5+7zGZfT2SKYzaGhKby2WlGq4l11rNN2vb6aAd1rAJuB0Azq7sjUrN+ZtxFm1FoCNwhEHXgNVmWIOvM6tJIaGmshjFK0FnrfdX3QQIBGftk6Br8OQA3btk6OMsKwsmY3QLo/+H6H7Ukowsiil2svi6W0owxPMp3N5nGY0zsFrReZWVbC2UFUfmIZwDAlLxkPYfweAdi2FkrgAbEIaqMxZgQHKa/nNLhzB7Ma4OisOINYU4/LTQUW7kZjYnZUVxUG6gzLopF6QdvJPwybuvNVAv6c2UUg4KsA59WIILgCOEMijMPZkHUT5zUMp8R0TrslZoCdOJAASKvhNAeC1ZEn1NOE4WJ81ugDpZWg6RDB6Gps59HRWtNyZm4opwJ6t4E7g1pDO59xPl3Uccj2MYTQuaNQxeaJIoiwcQc6sIk6zpVRQTRQqaATzz4sg/Q50PF++KhGQBKn22/jz3CmMximauUjqhrPT23D1mZJhsvlhK02SOnY5YrSG+RWcXu94vV6Q993gBn7603X1+iy8+aayYVQXrxclgAvhPHJ6MdLgbyqK60AiPrmIiEv04uvZ6J1RZmtUghgiax3i5GDyJxYBJ3VkVVlVHOW9GxcIEgp6lzs/O/tjrKdo6TN/eZZW5KTkgKcAZnRIJoOW6I1f6ZOJc2NPuATCn4KJxbHD7H3WJ7K1I/ECHlj5I+pL7E+MneMXzngWvGlzJKXsVfLdCx58k6naQ881ve0DM9B045AP/mP6IPjny/0I6L6ocZqgDRrBxRv/0oa7S0gfHhj9zy8w+BsGO4vSLjf2g+Jda3/QZB//QzGL4GbPCX7UXP/o7OgaQYIGfK+HNH5B6zKH95+tE4JsDgSfFV7guv/sOa4Ir1LmMGlRAmqMbo5Ae8qyzjvENhE++XYxfvrFobc+/z7yJesPOZ3DPbJPsjG8zfpwje+5ovd+IOfS+kLoYBFsy6x6WDH0CCZHmXH1pHufaz70/DBiIyKxkU6P1Mm7nPncED3uBvtYTzIYF4GTCDUnwr415WHys7dUy/9+QV+HMk/s/2ZhvPvaUf4m04PdlSM1hxwdtjD/mHj+b3tbzOgS/5CTiyfzO4R2eXfi0IPQflXIWIKwoqII1BvedtxM10heIEu/AsIr29sN8YnFLwDkkncCTgA7PYsQJnZFoP4XPu9W/stCvHkuDMVoSh60reEoFSHzIvAUAiQYkZXzGgEv5cFqKQIucIU6mANbrP3lVKgkRNqkFNiOTS63LgcghqWmAinyxnX3uF11phshcmUxt1qwjFrOslCFsUqMY5FOIQL+vPY0xZMemKC4QIUjGGY3tIBZ6JMoTP0lB7l8/T0dV/xPbfnkLUK1tMJ1XfGVM7o1a7cmA/NkPGMiE8j1JGxmQLpdzUjnF+++4iwU9/Sp5Fz/W3jUgFINNIjDPGq/B+9o2yqVCEqlo4RYXiPdyQLRzZChMBpqWNHH2inUygVeu8o1aM6SxKevI8FMKWOzoX2j9J4vJbzdjqh991kOjOwigqcZMqMUM5KwWCPDNTZWbzGiMFcMJVUZAohQodHL7qif489PxU7BaAaYxET3kcyoPu85bX6Emb8/Hk1oHiqKGLFxIeR6fyFQGz16o2xr/4Sj0642bz7HjjQl6zwmwJZgjh69Mabu83m1plGEoy8y6yudOA1UwAGQglQTc+SGV1Eae3EItet04b3V0bUGU9XegtWVxjF/Xq0yFxFH/OiKOVkXAfMAcL6+bCI+iw3Xyy8gf1yg5xfDZ8XaxrJldI4H+j7U3yQYC9Se1OZ99K8jmU6W8HuK1CjdG0b2nZCHR07aYRX6RWgPnGMrcMA6zitBIQuYbXx6DqJG+nCqGswQplWKVAKNL17YUHdtoQ/bBCFQnnmhuJI42/453a/4b7f0Ttj77sZ1ffwLI4SCLWiGS4rBlNEGtEntodkzMwVPm+Q8B9HKRVDBDz2SM9OtQBDa83zYNx711IRPBWHvq4s6hVNQ5XTjarNz8zSACAyy2TYXSGAUMIQMOk/B6GT5WrB5BlyvXLEK+eTVjptcxfvSHDri0Dzq6/x7OYDJU3jckUDRxkKEasnxhqJWKAwoCVA1Lir86MRRN3onDrFmMOo4SyhA66zddB9Y/guz5XjIXNonc5TR4FLYi7ju+/ticrsLMV7QQD6rP+a8cMAWS1KAEImnOu1Q9QZUz3q1SmjNM13BKPVKO7IlfkFw39OD3TT65KkLBKZI/KxqE3ceQCDjuTcMSO9CIVdXvC5sD3DA56KnoyvgDkJMOk6D2YMGZaiVt0zyPcEJrez/GXwe9rkyU+HBQowjCwEieFznnfyeys36IpZwOUIvaacAL5Nk5zcBDhDo0QPWZnl4amfGY/39dCXADM/VMpy/8LrUjpquL++vGQSvnbK55e8DItxBC8WIXmfRMFTO883GJ/liuTeMQTYezd4vms2oY8vGE0sNWbBwB2DGb0X9H3H3rs6uC3O5I/zsnR5mQCj7Wlc2fDp38KWiUc+Zx73kU0ccryQCEZT5vXL/C6TPNEB+eME8Bq7md4qPtGSSV6nsYJQzMDl+5fMiC4CzVRWqj0/FlP336laTUhC5Yq2bai1Yjuf9HnVImSrpeTftEY6SkWtbrTWbFFaKtjqmxfHX7OGNKAOOUc+RpzPIZOMDMcqj2JZRIqX4Cqo8LIJBTTcwd2jDjtADTJ0Dplp8gr+ZnKnQjMmkoWBp7VauHhJpGBZ5/lriWT0+U1jCt5StP7mw4ak6ZTtBsYMizAHgJmufvIxut6r/DagvAtge1QAcInnBTYjdUJ259FIPQqVD9knUia/cJiaNAc2d0YzHvBZ0DOnKQqR4XDBBHeMdQffOSNIs+jPy1hwJQK5nyFz5L5Oip/e4/TE0tyLytGFE+2397rBWh2iCLBrijn4FdOfKP4rmimtad1yslIWRAV77+YQusc7WBjX+x3vXl4AK41VSwNXYGuMvQzspc/0/jYCYYkouMc503Irx1Vb+MXgbfQOzzSjEfKE2hpOtWHbGi6nE06nH1Ebo7WK82nDy/mMbntWGBj7wL5rHfd9dNA4ocs1ZE+FZ1lgZX/VzAL18oJ+fYU7vADvUPAOpbzqHjBHACKEcnKWN3IGjSz6X3lvgoQz/yo7CvrYF5hwZ3tmBlOJLD9CM1uPQECXc+A2vt8S0Bl2N/7AXWOL8XVwh02jC16mMfjrwAs2WVSh6TX0XiEGRAMhXG4SH5Z9WZwKnefxcj+W7SDooBgkhMEGGPgYNEn1zALwiqdWaJrd9Xbk1d5qR9bjeG7Fl/OAvs/2cci/FJfosB/ffKTtPpZ3jhuNF3QV669pq/3mE5L18wnXLPxV6nToIY1R8W59JI3K7BDIvxiCXzCA+Gv4/BwWe5YlFJnOoRMU32yfO/dHXP897YPNx/dEnv/pjRC6eYZljjXaOYxH3XtHH0k+A2J/+o5h+HPmc523nAZUJ2YZfmTir+B3V3zu+rVJ5HFYOKdjTwb3hMN52Hp/Qju++fjOI4f9NS32jIhFntegsc46Pd1TNDdn54FqhvBCGrgVvuGOHUnxJcdxieOeYcRxtOU/ifeOX6cuJca7TMZbWPF4Pjr/mWu/pk0nrXjc13Tj217x5yOS3/EOlcEmL5HFO8/SsqD5fOcbOPdLv5/14e9o/4gIdCeizyfZrjkecMEiCfpH5eW81wwPjggnv7A8f15BuBhqrT8WbL/+iFf8ise7FAk01KjB4ldcn/TkCsGPIIuz/Jb29ZD9yKIdz/tE6zVW1RVRQxdArpNzrHUXGV0LW1a5qtE0nkaYLf0tcTyPQLh2NQ29tAKUYhHOmqqwsAoVVIHBltZSMbkq3u97bNKyFXy8veJFGHvyfj0VQrlcQK9XVBHslTT4zwTOIgXqtavGeSHF4I6OI5W0z9Nh3JMIO4RM5pNMMaPRphaFQI5UnHHlQLTL5xfWUp58f3bd2+0R1kKsDqAXhALsyNAnodsJ3/Onvt2+FnrP0GDf3IiK1eCLDr1x95fZFh9fvtwFBhE2oWtlS1RRsqugX4B22syAXsITXA1rHGnWSQi971rvXDRctbYGHmo8r00Vb/22K4NBFe20pRq0c5JVoJ+Y0X89jNgMmrVWq6PmqXsrCmuECZELx5r6eVh92JxlQOfchEKwOa4gUt+JaITPwFT8qFHOU6o5vFREvuu0bqP3A5PpeMhSCJORJDos1PMFNQYqiXeKKHTfF7KMlNMorEw0xZhLgSm9CjAGuETcjirx7R6+Ggt4LhkN6PvvEvPkhiM62Zw6o++gZ4yoC7Lix+A1KBmFowfGtLri0mDtQLnUMcKNnT4HNhkeMRsSKEU/5wDWSPYQau2cR3Vm4xZH/XVTVGKm3nLE4hGTmLc9qUU+x7LKLGLz4nMksz/PbiAHGVne85D54oA/JJ0v5SChxeLoO9nq/MU0EJlivOF02sBDz5feFbAss4CYEAmBpUvViEpiAXPXNS+b0TwV5wsh0jTrMXUEk3pSXqYQWAgYbCnQVbm4nU5zfVI5FU+XHjXNbS5u9yuur6/oDPShAi33gdHHjHKHALWgmDGSRDCaTrjWmC4R1eH134cpVWukrnawmHAN8UNsae0J3dZB2qbXsYQiWUjHRYOxS0dDTbVhtU6WWS5xVCdkZbLYuhYjwiqorZyT4IC+7I8lXEUWyJa56RIO1LnnyDmbOpCYUMY8r8K8BJy6sZi8DI7dtjqbmBFd3EAsEB4mwGqiQ0/h75GRPKBpns1TXJ0V0j61CZ/zEhtq4r+QHH1mnYcymBPRTNgFE1/mcUJBW+LT99rkPx2ZOf70KjiOp6YTjIQBRuFrzsdgc16zP4iAWMwwq1HiYhGHGV7cqK3oLxn3SIwJh5GGqgAAIABJREFUVoU0uUYOQO93MAou5xe02uCpuGMApq1z/ztmc/qy93mJGc3kMdPxi2h9Xqdl7jDhRnQxhcPggX2/Q6gGoREHubS+vkwr0o0zCbYem8yZWPkpo02tVgw33I5u4yPjHw2ixDL2YN5fzvpFhCE3Ad8E9KJ4BbUuMPEcra90cf6b6ECSA/Pw3+bFHXEDdAG2TfHvYDWUEc5QGGrxhPLDe+ieHKATwCcBdkb/tKsDZtUxDrlhXDt6n5E4RBcQgPpe+aDbhx0sjC5qCIEoT7zXgToaXtp71BeNvmUUMHYMdIy7gKRiOs4lnLSs7XEW5vGY7QCaiX8o/U0yL8sz0hMwzx4WjlzyUFjN8qaxPE9XJOQrA2rCpjhxv8ONIQUXQCrKNpn9cq5Ar5CrZf45qfOq2ED1gyxtunM3hKh7ayn1S6tomrIDqA2CAiGtGdnqhtMZ8Lq87XQBi6BWowcAttOG6+s1HFERBnSbg6ipbnyqGeTdWW30AQJpJqnkaFYtJX3Un3benopmehAdw/ApEQDUIaOAqgDidIYjk5vuXqOAoQ0zA71rPpyeuwwgUD5lWb/H/UnOL2ePCMB4WkWzIhS6BSFJe59miRYfi5ev8AweycCd+0gDynfRJbJ/CAu6dM0wEMy6vtMzjHWvF298vesNnCcoZ1Ie4Wr6gAtAVz9/B3Be+y8zWpLh8G54xB2BiRbapucKaNvUcMnGUxIAq2ktrwr/TLcwuL6B6hcMIJivCZYtnQuuighSlcf3WuxB+puAXxn4gYBPDHpH4JvxTGc3utp+Jwq5V/ehPk+zJRCYKgQdfXS8Xo1vIkCwgZu63Q7RMmf3vlsgBlAqoVHFGBVta2ijWuaZglIaRAS99zCQxghlnSenUHkOlgnU1JcBs7UoXtCMPxsu24bL6YTz5SecTkA7ndAMd9TWgN5RidD5E/bxEf2+Y993YDScfjqhDMLtt49hdG644Ma/6bpsJ5B0CAh8vSLnPyIilB8a5BMg9Gr8NgFGr6Yx2PYdpjEKg1C5gE51hT9/uijlc4M5wcpCiGjJKZsW92jp9x11U70JSkF/vaGUE4amygne0yXbIuqgT+JOVxMLAeasHQ7Zx0WZeO/1X3e8///P2g8uGNKVT2KDvXRL8NYHxsizPyzPB4GK8anGz4QuBIRnOYUFJgMi7amJNuONL6Lj+5S6sbA2coTB503S39J1HOmy2PjfuPELL3ON2aQVytr9AAqd/NLSHCwDt3N+/FfDyT8K8E6AD3bZD6IGeYEb4H4J3OkR755bMe9sYNYKZwCn//0fGP/NAP2y4LrYJm+M+2vm/u9ov5LWfs/4GlDDus/N0t7Uo/4xTZbvVsdc3J6g8eRdtHSc/nWtc86mm6ep+xJyGC2LviZ4UIIFtqiebPKNfsXam7clALzx+5FvyceOMH6845/cvOcnk186D+zMaIWioFIuCeZBFconGP02gVYg2AyPVtFAqwr9DBnY7r4b3XBZUg3nrHy31QXuY+ZpEyJ0ERTLr+D9fqXD6kjOlYagm+KZ5ZaRH9f1czDwud+PUPb/WiP7N+vRAIeBVFrOkCmlzSlBk/24//jr+v9ntb/NgK4MRFaEUBw7MgzBbaR7g0ex/UIQCKuRS70TE0i7V4u4F6YJYYk34lRjkaCMAUPQPwzUxGyRixGiaZ5/A6FFfNXKGPmPF0sEL9Ao9Ihm/47iDUp/OOqcfU+rro2ORukP8TmZIp/L6c1FwDQEGZEmS8ehkWkS43clpyJgATDsXo1kF1JvagAatcFaz6oWj3BVw/cOhtwK2mlg56GRtKSGCi4FchOMogxcZ82QzUXAXMDEGLD0r1YLC0EQJuqLGQiF2xz9jK7RE+4tW4msJpfV7jLBN7ywXYfaGnioklNruc60sfHOeIe/yNJor1jrYU1D0HhyzqFWjLmfYzw8gQ6fsfTGWh4YNLH+0oEZE3vjaqT7crs+OSauHBiOiGWB1MAbxy7nftpVCYIPfVVDxf0GnM7N+q5PYQFk7ChoqETYzEjuij9Yjd8xrAY6mqZuJo+WpIhYEIIaMIjAMrCdN4x9dpplRsGVojWHXYCLJSFXP3h6dfXo32mgkgqjg4E+7pqy0qJkuLOlvFNGZgxbTxE9JAQiT5+jin2dIN/TKpTXWhMTm6InHNZtsVmGKbPWNRqWytVsi0GQj4YVAAtt8I+ZikwvUKMH2f8Ua+Nd99q1KdA+EXG9iLigFPOUF4GMAb654cqVBwopXuNHzCjEt1mrXRYIS44PGS7J8GqgVIljZqa1dPmBChZDNJOEYVXc8AhlFIkMnwgCfnWNPQ7fDOwekZ7XlxDpu0PZCMS4xLWvts5saRBF1KOfzfoTUe+JHga7GWscD47fRBNKFvqf92u6xpX5voxUZmo8p08EgphRzMllQJekX2TpzaER4hp9AcXjZSqxSQSjd+y4oRKBa4t3UylQZUoxY5ZCwLA593J7Cq5uULP9QjSNlxaBJrWBi4oLnRk7E8AE7uoIAykoJEAjUGnh6TnCYULHV7aCse8O9AobbJ7g0qcySTh4FIUVcw4yw3ssmWi6TRaAx8DdHHIiZb9MYUsg/5e9L1tz3DjS/SMTIKuqW9J4PGfe/+nOxYyPbXV3dRWJzIhzEStAVi+SvMif024VCQKJXCJjX7ANjiifGuEhthbbGJqq2ICdiDRieLtamkeFJcVdulcCi7abwBZ43RX+pMYHq/Ou/IEtjp83g88xUxis9MIZOAb2tbQtXfeUGXyB4iR3QLO5OY5iUoeLSpZ94iWIOpSYbONzZyRbT52SOhxqmmCDbSH14meJNPzTcIsaeBacTmecTiuWZUVfehiJSZpPU+vOMUMmRZokan7cPWOBnVpxY43xTWQQI0ZTDJ4jOqDZOXJBVsSc0mwX3Phj5R8ULeRiZdSd1XAsZ1gqn2Lf3QjPkzHYShOYY4jWP5+BiB3vs8EYG88iTh8o4clTBMedYnhYZoydmkoNymMpn+v8ndJUNkWPr6dFqjvtD0i06C/yKgPqUMqmrWSYcaYpnmeiyDCDdgUWUn6pL0onZtYLvWHFKGmvriFl1odyj8Nq4O3dNZ0v2XhmoftBxMTOLRFQ+F6nNeG71Aw2HwRyddzqq1LPhY3BZTOn+QC8HMNyOmNsV6BZtKECYNAkMXgku+54odKskrcafVl3jiB9Wc3QXaK8KakYiWCMCcgFnRe0dgJaw9JWTACNCSQbhDeINEB6jIvNqMCL4Z6r8x/qcDEVoHAZV9AnW7zF+b9DFE81fMt+zx29i/ja5NlrlCU/6m4XkIhvyqdQ/kKeQQX71srz5M/q8wsWTJq2/no1kkLVLhzNwAbPWlKGON/RqYH6QOtnYJCWAhJAXgV4gmrZBYCVEvPI79YoaXTFRQZrIgLqTTNDUUdbNAMNWsOyrhqJ3hbjpaxOuWVCQ+8ROfny8lnpfl1PAzyPIM+903PULNvLZAbI6JFlN4iVFzcwscFiWTyCOsKxQMwQvwDqZLoAkzXae9is1TGcEfksAk4sVbPtEqTAExVju41HjKELntZTRNv8mqQDGxrBy5w01s13vsEdoAOuSB0LOBx9DT97HWYERw1Hx2poFgMTiSwaOiYbv6e7hhrICdCyRMjrJF5LHvt00AJomQ8O2R9nQF6vcYNuKeV6+nr7HgLQcjU2h2aLaKhIWTZJ8mtn1/EwRLTMtTn9BmranSJKHC4FTxhyIIO7zPqUWxq4miXPs+vYDJA93a7MCX5OpTatri8xh5SuxmYSJQJpiDQc0Dpo0cxt1DquPMBX4DonWieMMXE6nbGNKzoR+rqgLWs4kJA7lLSORrZPTfdg7cA21YndMxXM6YEhVhbAXNucTrkc5fhAl0v5L6cttGi2n4fzCY+nEx5OP2I5TXRzntcsQIKX11dcrxe8vLxgeyVct4HBKvMvj2fVU31UXYTvzcQrWtfscbxtqagGQIsZqccG+Qz09xQAUzWYmWrenMELc9pIy1PgJEETYFPNvVFHAcB4Y4muA5/1ltkbWARjG1hOC66fX/RNfFWZTZUPkEbm9MKKuwF1RmjdouB78FEZMuwoU9fn/P4HMAQvf/krrn9+xrv/8x4bz4B1X8fp4/VyQaErFrh+rNIn1/fC+EvPsOVlarQsAVsWhW64muKvrrXEWXOMrQE9pN0XOugmH4KfceMvnEcuuslAPEHIfW6S98VUqIoegTdY0vtfs065k3dh9JAfRdSonU0iY4Bz9t79x+DrPCOK0wWO/fTT7riwwl38t5GLGgAJ/grgRztv18P73kuQUns+56Cu63q9/7FB/uxzNk7E1mE3uxJcdWRnvq3V0/d97Xsyd/5MwB8Ot/+y8eazNeMegKKjpkQKfr38BYAhjDm0mOMQwTIZ3WVuEpPJ1ElYa5/DMsclj7+TRDwDY4zOaTIsS4WBvT23y3oodRew00Xd7M5u0XYc1A0HfLu+lV6mDjze92u+U86a6/d6b8HF9wb4FjzV0jd6LnN+XGWuQ2tFPvDSYnlmVYmwgLKUiP1dWsdmdpDmpQeXRZ1XO/By3dTp1LOyGpGZos5jYdyv6wHnoe7t2HHwx3vu7/LXvt9Ao2XfA5I3u7enVLr54ncK0rND8TUQ6Uvfvwm+nE+F7BFUOcvNeW/77L80Ii1XE1RL6U7VeanOSimb832Aq7tyLW9W+YAsxeZ3vHgP7P9e7R8XgU57D+vjCki9D2UvDbq0vsxUpRZDCTQYYFV6i0U0yeFgKGLTVOJ1hz7bfU8R26M/MyYefjoDP/vgFEJricGBT9k3lIg8EFlV3/S8oXgP4VEITFpCVxBO0Ph4c+D9aJZ5CL1R4/AbW3hYl2bMYnhuScw25w1Ns68MtzKVSS4oGCAftzP3GpmtTNbrdo0ayg0arSKkCHFaCvhGQJ+Z0ppZMOfAOhZVDBNj9IkFWltuRcPnBqg6vWFDx5gDTAA3MzqZEn3jYYjIObfKGaV3+9HgQkDUynOBnKDpALtF9q7LaikVNbxIeJoibIKgQtUgBgYUPu03gcJMnIcwSmCfCflwVm6QBbmRmdIgVQwnsY/+G1AUNBUUrA8XPCDG8O6ZhlAy0JFo1aMlu2fKS77YMhqswlg1DplhOdLMulLFrrd8exhWkF7MgHtWJ5Mtrqxpft4yeoun1ggkamhCWh6AVAgVUSP6dt1wOqnya7sOnB/PFkEKEBPW8ykUXjwFTJa1Ae7gY6URAAgTpHffLl0woqjLxyIgr4Uq7jBkym+xKInJuE7dN6/1N+Ys6ect9SFLMEce+RGp1wuBixTwplhVXbhHPnPU++ap5zgUKuR/MmKBURjXwi1kKnwb09UM2yeDZfGlsO/+z/fwSHXNOSAnkR8FYgbS4kHHjI0ZONnrXmHRQMoi0NUYmrMZocUNDslhVqWGp7r0N3o2haRvCmWuuEf5nCUgKLxAAWV2vVaqK7jd0LIzcDlzIZVFJAhxRDtXg0DgpFiMdHxKodZ+N7hGqD4p8LW9ZY9ayz5zvNDnmzBOXgsS1bkOwQfU1lCW2dfL7m1GR9zI5spVX22iGCVAgqUrTZTBmNQhPEDS0KlHZDqLYG5TDSPUsS7qbENUlMu2VmxsCYum5VccLxoJZgYvwJ7THYZ/UoVKGheHEGhoJOeCxdLPKi6irkp1CCDT6iWbEcsBIPdelXNzDqWpXm+XGsSUiqH4lAk3qLjio/c0ghIrDG3bZkveTYlaaKeIvYfDUc3VRGQ1XF0N35Zu6RoBT0MezkSApedHKGqZ2YSogSgbkQwYGhv/0DsgFJFJDm8sgmEOIUEvTdkacGtRzO4g5em/3fkuqCE7DCaEulE9kZ8b+hxOA+HaMbAzr2RAffTDUE8QMyQ2cw7oRJhOSzg9+QUSdbiX0wmn81kjsPqCvphhRtIxSx0i7FkCsOk6kjkKeS00zzih6cUZmvM3ccqODjQ1kLTWzSjhZ1mVGmxraSultDBq3Xszet0ozqrjjYoxHL4JZjgy46lHN2xzYNsG5tzinSQEboJJavhvakoJHkl5KOVv1QHAok7DcUHXgHnaP4MjOyNe31PHrzR8bBsi+trW3VPhw3jkKX4akpVpTJZJ2Ogyabmi1pvyiU0N6egEQUNbVlBfILQBvUHmUIePWNY9DxlsobXMQpD4styet9rPYnzUztACYDmvaK3j8+dno1O1B4sqCaYDdoYBgjm8CGtktdF3x1VKhmR3Tl2W9HPkfyck4awRZBaZKfqyUcf4c/YOK62pUdDfTyD0vh6YWjccEkLbBY0UnoPxQA3tx471tGA9LeAPDMI0HHnR7CKyqrPcmeJMuEEcWJV7InOGIpWXxvwMiKBh1Qwcvp5t7vi6cOCChCKmikDOqsWURM9t94w8vJvsTQuHmXy8/qesOwWfCGf1aMJTarvftdJvSmfDfc9O2AvOvGpqc1GWi3rD0joaDXv+ZPN7BV4b8Pgu0hMTNdAVmjHqqaPKBekYkW+PzCVN4WBZVvR10cxqojWPAdI6xuDAtQ0LhqjB7vz4hBdLvwyYEydEU1WvC5amGasCuvqCZemBhxkqEwsUDrqlnNczrwZHQB12yRSQSsZZeRAAMKfLpTXMZQHNCeYFbaojYINlbBMOOsWYYHLOyWRhP9NQHKSZOTiPlRndiGD13WlXAout5Ehspq27KFJH44ZJOp/GzZR+HArj5mnecygw9iWjs4GD45plznHjAKkC16l4gymOnZtx/NSanU11TILxK35+nA72h8VwngLO5HM61gUS3fMsLgbtwd1xSsooJJ5lRuy6BM3hek6FQHIG8GqwXxB9ejDrHnAwMQee0S9LZXXCiD7NmNi6ZbO5Gn9IWo+bHhUv8qugPzY0qL4nHFNNDvBa25ryulu0cPPDrCUCO+E6JgYLns5nvL68AARsnz9j44mH0wkLTZzQIYuu15wuaVI44IUy2HhnHpbJZTqf09C602Zn7J2uKOppZoyEwJzo1PEEAE7nFWtvOC0LTqcTltNAP52w9I6lWTCNCF5fX/Hy8oKXz5/xcnnFxbOzUQcuBCyiDnGTNKOTCE70YPLoK4adGzH4wTYCVwq9Ys5Hk32dM00s3R47vLQTbDwCQjutyt8wh+NpGFTIemiEMbcCqOaIAqAtK3hOzepjmT2IdG2vL69mVNDMW713w43NbC2ielW2rHzdDOikmT6mOeXHGTI62PEOT398wsvrMz795S/gyVh/WPC6bQpb66LYqmtqecUrHMevOpNXKpNOBsnHzzE1GME8u9a2qPGgNXQvf+S0jBDX/PRpuT2GagTNiQTvgfY5RQUkv0fiQRWiuHGWk2lEylkph1elhxSyjbfelLdy+IOYkZGa8gpweVTfn+7FgQQMPgEPp3eOiEX1rM3W9GO533lZdTLX+bC0yP4QwRc7C51+ZmjK9tRJCt4J8JEkcsIeORN/53MwcfnbzwT8KAT+61+xgNAo66c7L3zUjUtkBPwFzZG+5N5+VyN8lxHdM+H+h+3DPjwMhzX+enM7g+MYp410uHbzHNTJU5jRoLJ2a4IWegmFvZSpje6XA3gz0uAnq05YmxvQg/9n51n3lOw41qoX2vOYtwORXQ9Hjfd+oEHWd8/i0Nd3frdhxRbeu/fAJnurAYG76367vaDvoomdLuQZdedtGI1Xki1YrMwYi+kiu5bDHIRSXhcWld4BYfTWQmY/nVYwCy5ji/lptmAdSBsDDQhDfIOdb5fjgn8SO8NkW7fftR0/Xxdy9/2w+N/wncp/6yt+9Xfb04hHPdxbVOx3v3/ruwLHGF09rqV+V54n5DcoH9dbR6eG6TaYcjai3NCB7xejA/U01xZXypLePW/2+71MZX+P9g+tgf6txKSuzRE/vLludOc8oCD+N3vXkWX/zwCdrQ464FqHt0gquRETCOIZnr2EXT31CuiMv/Fm+PnYLeDR94oOk7olN/trX2Is8j5XqjMB3ZBa7I1lZlShy+4HASa0q2LAIpwAbDw1Wt0IsGwCbh2LcptgUCjtB09MFquBqZFjWg9KFQ51HE5rY9+PAOYnmCSU/PV6Mr515mRe7mTpZc3blij+qRJCwiAZO+HwW+CYstsbBuPNs3TERDY3Vz5IYYD0dQQ3xla7Y1Hr7ro+nsfvZhC/0r613+N99XvAeEHGmbqs9iG4XgdOJxPm6TBfYTAPoC2qLhXBnBt4WgJrSQ/XZV3Nm92NZ8Dr82c8PD2accuPIIXHZIzdjyHtYcoZGoszCL8H30v3bE6i1MzYmorjRprGmVoDSYvot9jhSIEjwTxVQBO21JfBxjguSw/i1jwi2dcvRq9jQKYGzlZOjRPdKsk0Omzk7WkLQnwwou+wVCBc24NCyHV+kq+4pOEnlkF8XjmUMNBbzmd3NTmuXT1FR+IU5z1mQvDXGcYsDKEEMLuSLrxPS11PsTRYagtyI4fkZ9kPY8/M2NrK4botQnrtu9nABP5QgNZeadfzfkXKuw+S6/H+I75TZZg2rz9o/B/CUOuLax3EiSaKaNDwXi7z88XRSNM8D4h1YzM+mgFweD1iMcExbrVXt+g3cW5ZOyqGjQLbde0JDGqCvi5KF90RziITREYIpNTPMWEp9IplGN07RgcmXKlys4MtGhCxNx5x5u+DZUMQUGN4FXtGdeASc+4gixJDnEHHYW4AK/4x6YxhF6q9bB/lDkAsRsj2J7K/NA6+wmEjsVCBA/92w+6UiASrD84QdEtZbwS0cO9FHD/SFvGzkoC2g7cyJ90GihpiuQnm8DQ164Ma1jyqirROozthOT9RJAtjkWLykUGGGoiq8lDKGgOhlIjxsSnexPZFT6JlXjNlvPfWQLCsCWQ01JV3ZnjI8h/1uRwzQFBHOcqxh0OfO48ZPNrZZHPamObwoOkBzYDeLAX3dIVms7Gwpei12tUAWBqa01aGpu7cufr7Xh8UScZztiCRTrdTWVufV8cGq1VKTldyr8iUF/6Y4hk14s850doC6oiMTTZRcwbM4R6VcfszdR9bH+9J2M4zs7vb8M2Yqu6I80g2ASKAOeAsL1ccYCY6ezbrI9va2jj9vB/XdDmf0xHM73UHoGpIf6M5xj22zFN2eGW9tSxxKN8fClMnAD0Q6NnxHiGw/oP2v71Mm8eChRYY1saAOdXICuASPBd5mnKnw743Uney4L9CC93mFrQx5iZaq3s30VyJgHuqq5IOV7c9Bga5vR7yVOED777XoCOyfpgzmWWQAanDw9K7KnaaOhs1o2tq7Ws7WhMGUIsoFrs3cgg15S08eqL1jtYXyzbWYp2nwfz2PHE6LRjbgJDget3Q1zPEnHrcMWIzgxeRjpGbRudmNqeyDtDsNzw1i9rYNoyhzmMyGWOq45JmEmJLrUzqYEPukG3nTqbml5nDHKRsVwwWW19MbrCdMt7UI86V13NFdQEeydHGwJ0hO/622/ekyk51eEcn/TeE482eNknwWi2JqsljZpSzd7TyNiZ9T6DIyjvYdyXzEgpZiNE32yPnc3w8e4hv8YUeCHRBjNXHGMsnOUdHsioHuZ6iHNgkdLa8yXfk0hPoAZivAi1IqI2juODtXuz2BfcNBJWH8jETyJzIcoj0YFD76rt3AcsD4KX7nKYK1DgugsV1IqYX0XHY3B3BdC1LNsbQzGmewNnoIQahtwEe6jA5ptbXVZzhfI7BuhBoUSW/8t0Tk2cqjIngWb7EndAk8XUnHcucABOh94a+NDws77AuHaeTlnbqpxXruqL3BWvvVm5Jz+/r5YLLdcN12zC2zZxmBHgkXD59ssw0ufKDLvByKA4qzdatyssMAK9Z2sF3FZS+ExAcRWXb+f11EaAt3crGTHTJMmbOa4V8sW3q2CcxCiMFNo4dIw8Qe5CTranFtxFcj9osaAcpZ7sTshIIPPzHGSDgdH7E+z90DM8KRAIsPV7Hku6J1V09FsP21elnrJsg9oCMvomo00qpaQCn7Ykvcp/S+GjvwG4ZDjvw9ud73+WN77HH8bvJun6x8il3xuHjvqXB+7G12p133/avObJHxzEf5/qlewUaZf7R/grUyO7No9D9uSOIfyA3MAsYH2Aa5rtz/JYxfql9Gcv+9u0Dadp7J72GHX99Owq0X2h7GHXHO+um/Oq0j8tzb8G+E8ZaFlWvG3QVeuiASG9CwPd8v8fYv3X/90LHP19zPKAlSo3XsrUPPszwW7IiggsQOvWT9yWqCzf3YwzbqskzDPVTlCdTZ2BOR+oSAefR8T62V7q/0kc8823t1+7ZnuvK/x6v/orv8vbvv9W7dmtn7wvSdXz28DvEglSNLfWSfdXecuQZw7aw7/Km/VK8+/dq/xQ10AHc7tJhxWKD7/x+0GeFEFQZiHzsjiK/PC9xjzM8P0BYLI277O4zNQWeIXivL47+XiD4EYRXU2g+OfMlgkdj/l7sPSuAFfBsX7jcOZR1HW6vfkcr3FUlRc5YfQ1QHcHl6Sg5+QRx2p0BJkO+TNgJr77K2xwgJvQu6nEsJhC0BpZpHk8NvXVN4z6GMvRd08Esy4LeGCekADuHpuo8nzquJmhhDDQWNZxTsxTIqUABpBi+6jrlivj+e1q3CrIU/00kSqTpNT3dpjLnHa1r2romEpkS7IGicIgFRbD7VVF4AIDd+dj9dhyp/rXMvRGR7QjPPY3jbgd5ol0PXyRWtL9Rjr99obkQ+AB1mJiH39tXGTkXiep4CYsrT+2iR3KTpQ4jSxElc+J61XEsJ1WaRc8iGsEtgLAKUGMMhQcT/Jd1hcgMYU9hiTEZQG+p2EKBMwLcWB8g0PZrjSKLVbks1i3u0+jCVBJrhOHnZ41UOp1PWJYVXge9tYbr9ZoKMVhErbjclNFlugYIhWPrUsaRiqfKxKZBC5G2sYEimnUUZbbuvVrZWj+Z8tx+bPsJq6OSnoPKeLtQXRV97EMxYCw7Y+e5MvWu1KeA+5pyPejKa55BT6sqKELBRUdF5z1x8miYnbnFbnGDl+v1Z+C1AAAgAElEQVSQgnkw444OQP96xIkzlz4GMv/g4YZUsjGHAq7BnSQErryIpcBeXSMWWa37Esa8umZFkZPZIHJeLAU2/T7/foPDZL8uX2kGLUqnW4t6247TjvXP490Fhqm+0QGJR3nIjcVGXywAV0twaJQw88SUaZHWB+NjEkZoLW8zlMX4Er+H8Zx8vdVxTKOtpjrutI5OwLKsljqQMC4vSs88Gml5hNfOnmPAjapq5BSLXkrv/1xQCtjXWqsce6SR9rZLot/HuGjarTnQsYYDCTXty/ErWFM4ef143QOLWEbTKIuK4PQHOw8mqJkiR2HZDASUeFSjrzyjgkbAkWi6WjdQHlvv3dIu+hyTcMWqWGajBuVHVLCcVhqgQKDj5lzMPeDBOYzycxUmPDo5jBnGApTzxcKmrLKsF1bbGwZLnnqYLNKkrmfkiYg9NSHYopiPWhY3ILsxJ51vfD4CV4rq1qiSmn2vJyWvZGl9Q+lqqdvUhyP73iMEgw+2KB1SoxkMFmqGFD/LjiM9u8K08ioiE4IinLtDDHQ9mdz4Pq3cAgOBy6zvoDOGgyVZNd/DPOsMgUamO81bukZRjbGF8lUgYaRSp7OG1tjwBIVCAuKwoDwyi2gmF+qYRJhikcVsWXJaRz+tkM2i+HLT9vgZRXlFARaBt8RhpBh3jqxls4whRIYvxPC4ZcfxCK45hhlPikG80gbb48msfdp3hmjUnr0nxiYJsCKwrB0w4+mqzhNjOwzYvjovONJBSNMH+0LfPAHFDukwGIqAcv6mSKRNXt8t4M+vaI8PQWHUkWNqFO0rx9o0nMDoYJmYLxkJqiluF73vpM4gbaqnP7MawjpOaoy6VgoL61MgURjpPl01rhP7p7WxGbvyh+R5nEsoIKqmj8BXsutQt1vfM4GAqcxe4PyF8ny9vCPejewrIytFHclgmQLMCB21wL28ShvqZNQ6BCfI9QIQgXGOcbTHhunO2RYVGXtPBLSmZcP6orSjNx9MnJ/JrKUsjJ+f21D81Hpkq9BsFF6+RPtcLMLc1zBlCp06D81WMC1byLTMUmOo0W3pGmW5XTRFEln2qu26WVY0xQPqcgXw0LIWioOyNIKmMBetPd7UkcjHo7i68OSikBb41wZbIS1ODx0hLP/qvqch3PcYpApWdv6r/gOSVgaYeFYZK3FgYTsEihIOHOl69f7tuqER4XReLaJb+xuFt6480rDI/jR4m+Pm1PVpVjomp6e4rrUGPALDHGPcaXp5Wvw2uHsVgdAt65U7EpPjPEFmIRDBtl1DZgEyOihKjjzoZPnF5Co86Hc2LVMVKpH4rPIximfOpgjf9Jq9b2mLZrQyukiW8H++voJw1vOMVxAeFDc+Cog1+0sjwrJ2TQFKzRw3oH4HU+efcd2EMRjLqnRyjBHyqzBhWRSOuQPbJMu+4Y4kCBzSDLDI0sW31aOGlQa3oby9662UoOm5JYMzlxlaI/SufDWJ8pNr76Bloi9ndXQ9LVjXFefTuivzxzwwtg3X1wvG5YJx3YCxoj+dNJr90xawCmjZxXAw1jqVqBS5G35yvMoQtAfCeM7CeOpIYfNXIIHLyK5T8iwGp3VROFxXiAgul1c9V5cBelz1HSyYF615Pt3IIeaQ7ovlZ8XOM7OUsgPphAXR6OWaldT99LVuueL8W+pMWE8ncyYlLd00ASwInlqMV3U3r8hYtQP04oBASRf1iDj+Jy03wazR83YuXW4KfaexEZ7qNnJR2Vw9C92NLRBKG1+ojIvKj/5d9s/4X9n/tJ9efPF5l/nvHrQvZV/2yibnL7TtxAaxCFH/8T7LsXvlcfzHRtC6516lxq+xXf9I958TmJH9jTEU7hEd9Ob64Y1r/8ztA2ntc8VMfo5+4SzK3h/1Kfda8Pb7Tm6pvtE/4/p2RnSXPd6Cn9uXBtkOnU5klvnmTnKsd1/wxfuPvx8O7fcO4Wvt1/R3wCv+tZnNYacPNFogkMgQ4K8+9w6I4OoOZ6Q03PLp4oXUluVZsUQIgwSZMZNCV8YCbDJD9wTAnN7S3tRRnKYBPNgwnbqFM1/R54C+slRviXq/pP2NtvrY/tb9F5Yiv8eLJWhbNHdUc0p3tLofuvL9dM79xuL4xnP/rO2fx4D+K9sRjaURnXbE42ubUeHFRfTtwwThCaDn7xrT0fPLvYidN3m0egkTqjDY7J1n0MGI/hs3Z2jlHsP1re8tIpYzuFR/I1QFK2DRPkFM1aju9etUcRY9apQXSp1n864HCyYNTCZLqzrVKM4T7voyzZPpsmmNuLlNqAVT07ESyMaCEMjZ0hnfzj6v1LojxzucSdfR2/KaJSxSMUuDkFj6LwpHgRAw7Mld/8FofxvqjIge8ujGI+d928+RR45j801v/Nu0+yP99kZ3PlVYdGHGibjeYNBPygZs1wXns2+AraawRVczmKw+mqjRujdlKkQ0SqX3huv1AkAV5YulEjvOrspRR9r15jqICYhel9UV+LZxrTXIVFiYvOH88FTScFp0XLdaY71hDDU2kFAQxEjrF3O3A0JaRYo4D/29yDZXwPtv0wwKLsdRcwUs7cGbEA4JvvJuiPAb3bGBDg86AxX0QPIxqReMgVd7fcIAeWoyYcg002admuwdj2wj4E5X6vGb7MENhd0x+nd+yCnerGsyH/ofFoF7wjjmUZVy1mSTA1JzZUnUHj4wzMd36uNcOyjGIhye98iNvbx2fEecw3rTUfH+Pc33uKkiKyIsblrZtWK0EyBg3aOLAHV2UAEgjV0iiOhW5ok5JsY20HqPVNgeYQZxON6XCEBrcDcasrmrwnw/Rk0dPjCGRBrpUKjSBRBVkqensM5pmpFOyvw8tbWOf5b5MNI5A1lCBGxG9Fxg4ZGKaNF+t3Exp4ChEXldabd7gTRqkE5Kf8PpI5Xsfs4dpjL6p0ZxSBjLYywBx5ZmnTlSu8dumzFuRz8rbC+LluIQKuuaOEffZgp7c46o8JEvuss4HK7dh+tqEHBDxpv3AZHW13GWRxhpLSpNj+XOJCHGC8PT1QqQ87Q0qr01TRFvtEP3N2HKy4vsvIYPOMWdrojUeN4sohpMiossg0gYWzjhNRxOok9FIHp03GjihiXJOQX8SqHjYvs0o+75nJ6e1SLh4c4WDA58n5PaRQPajNnSXXid5VAQG1wF/ETa0zJGJ12iTpsgGC2mNFCSljGQoXNu4rU2LfGsG65sDZkZPK4YW8PWR4x58zkPz0SgfYOxOxs7kobbzCipZM5Up7k1PnYgT3LuCzmx9X/W7y6yNngtJxZS+iojY3UawKqxaCICbmog2Z1DTqfWXXmrIv+9TRKO0uOxJVUSSQfI3R1lfkTA9jxADw/gFzPanGHp2Cc6d7iDX4PyjWNminrQFY0e0HvH+XTSkkA8NcX2iTE/a9VPx8XtDMwrANrQcHoTh3yp3ayA6Jwm5p4/NdyRJSp2j9zuoDgPWH5xtI5ynp1XhGdi2eP7m/EaXKtxkixFYFMDFVmU+OKGbuXFldacAxf5ezV3ioBfGf1d07EKIn3kYu9Zlq5G7ragdy2lArJsS+buO+B0X8etqdQF4+UZfVkxxsR23TCnKh5fXl/R+wo+Aevs6I2AjbCYPBEpDyGGxzbMqXhvjA1zaITtNlRmAU+AOtaFFZ9M5etb7yYLqAeg40PHx840N8u0MskyVVld9MQGpQRP8B2uBt/vmBuIdgENBS4S0BD4wJXqfk/0fXvgboFCEJx3nFl/1NHOHSQg9i4tP1K7NnlPFEKUZWXs6cOhIzpcOCgUjzy2OzpLs9JYgGaOcqduH5tFJmcpFasha38ji5aPwZWadrCXp47teeT4RA7jT3x678QRLlBrvHbB4llBoKeHj67uAOOyk2trvwRY1hVEtLAoA6oyaBjAjQeB7Q8rPezOD1ODkMGxybdDRswjHSs55UyDSXddVWV+Bjp4CuydswZgtTy1ZvvSF6yLphm/0gQmWYpSimRpYnANK5PDkzGG3nO5vOL1coGcFlB7UD3g6xXjwyc1FBDBy2lJ+adb63tleiQU/pgo6F+UJgu6cpDa7EyG47ONV2UoDyFmZwgN9geun0cGMliffr+zDT53V53s+IvCi/t5dde0MMbA3RTIMjQanwXjsUBY6AlP//0+AcsXqfni79/Hcod3L+3G+FeB16dLVqs39AxGK5z/TNISD5iIkwbzO/fU9iDAZ9uQhMHEr7+03aPP99uep7vXT/1rPmd/s3bEG98yj6/9Ho73SO7urSlUueO729dYy79Rcw5YI4B/u3ZvXY/n5ggfgROCfmlHLlvvZPLd5/LebwPcmz7+3X5Z48rT1X0wCBgiVnLX71fZZlk6pl18heAB6Uh0EmA74lhU6arA0GEP72GkV/y7/aOb8+zJYN/y2M6H1WyN/ypH9HdvQFc5+j6BC92Jcy4iSUxsk4/phIORs+9sLGyDS1ZUHwdAGlGOJ4hVOG8Ansp9zrQ68mnxizLILxD84Y//if/7//4MABq5Hv1/mYn5Drqyfz7pmPX3ve9JMVUkI4NDUbKr/ZsMVrzHlM5MDGEVmiYx3APVlbGDNerrtKxYmir0s06qFTrrgldLYefpOOecGGNgjIHJAxsPJQpWd9Vhg0wI2bymZ+KBO+OmXbrnWJh7igF7gUe+RW35RiDRqAhqWnuoIQUcduVrjIFCUfStTfx9lvb0S0/yDUHTeYa+45cC2LF9Yz+hCP7KfHNWx/N402My3eRpGM3TTnKV2TMBoK77xOSG7imIDWZF1FmDZUZdKRXOzehsBh/1VF4wxzWV14FDJGAkUNSNaHB7Jj3ysreMKkHgOckuJGHcmdZm9Y/RSCNMzCDk71fFpSr9KZwG9vsywcD0FD8II0xEuEhGgUYssK2FG8uCmZ5uIFAji/+me+vGDhOqp0ZW08m+2z7G/9xqbvfXOrQOH6EsRMFDnEy8O0IQNY0U6dCIzar4p6Q5+jX81CFgyAmFntwanEJYC6V+KiL0ek2tbeyJrZcr7kmMLplygFSjpZ9d6WYRT/l+W1WvbU2ETh3b3O5wM/7OxCM+mlsx6faXQ0/7ecYPcvNdceDXzvP+7XGfK13a7btyDLn/rj6L819gwKsY5P0eoerKDFLHLKMvvXe00cFj6L9qCBWbq/cT+Y0YkQ5yp1w2HEMCYQKTYEyAhoBo0wi4SB3rtNIVjWblqxTE/mhKWjdUljTaKOmRw7CqdapqRJbjLX9eRLOYCBPmmJDF9iBqlHqEMwFCaB3wAsuTEwYDd/i7zTCvZQV7Kq8pFZr6XgE3c4Jz4/mcu2gsjWDduzG60O6Kr+4Bn4Sss76DcoN9TkWsO5SEQraA8j0+9C3eSu/PvagGTl+f6DPmZVAbUYM212Iw93IGNXuKwoLDX7Itnp7Y4UmVHOrM6GDrKYHhin1YGgbvF+Wr4XGWCVeABq1wumvrCRSnoFi3jC6HEJpFzBtJgx8Uh/c5dSzh3ADLDMETY6gxOR1egNYEfp4B2u+NXSPyv0oU9RhY5FR33sFppqWKscwhWteyBa7e5ggFExFpjePWMMd153TqxuPWjX8lAXWAWEDckjeZGanLLOCp9d176xARbJcLxrgq9e0NMIMq83U3zaBQxWjiWJxzMy1abh4UpMknubMSc6GtzBjs51sj5ocZOJzXTfppPXpkQtQcRayhw7KSO80qIa0BcQYcYROoO7+dfNZ6PmmEX2k8DgYfuUMGAT3rYjjNYfdwnpXd0bSE8gjIq117dZqckW/quMagR0KTBloa+INAcAHLZmSc0PqG1gnrWQ0uMgSMCbpaWk5ZjeO4gC8IXmhiCzyvlaxtvofx+n7e0+9SnWOQkJQkbmQRyvffLgz2Clbj8RT9HjgKkcT/kHQ8Qe5NGCGgp7e1M1rraJ3RWsfSzyoHdsayKJ1svaG1J/Te0c8KS3y17ASi52IKATgpbBHALxP01NGn8hX9rEbzZT1FFKk7W7F4rWVbd07cyvZFBNheXjC2gW1sRq9UHuUJgBm8rGpAF8LsC9ZVsKzK67PRzW0q37dtG7Ztg5DWR3ajvGZg0BTsq8srwQeSRcEr3qxZHMDuUNWApaENjwCays+6jOGla9xx7cYotccnCSNkO+bbn/elkTANe+EcZkQoeC+2muaSr0sDe14MDkgATCnv9YwZPifFHeOipRHW0wKB6P4alDWjmTtjVgHOlJUSnt3AJjZ3d9Zfn5boQ0Qw2CPSm/pDhnxUVlOyRI3LMHNsmmXF4GFycVwCqQHY3DRBkjToDPCrgHBGwwXhGhF0YH+Gk4M4Q0TQ+qp0DBbhblmHelshVwHLFcAp+IuGB9ADYb6+oj08aKR5a7lOxreJOWsSqWzpzjUiguvLBjoprzjnBAjo0tHh68AYYyT+EXUU0exyaaQN3o48Up9AJOhCWuqAvWwOQ5qgVvpQmVLLQqzLitO64t1PP2I8MyY+wfmcjkec3r3D+vCA09Ojnus5I44eAJZ37/D68wWvl1d8+vgJ5x9/hIjgMj8mD6gLsduLQH3GH9kMsLx70uyML1ocUogAZlw/PScTh0fTBzjvwLZvXoICAFufBFw+XtAfCN2eJ7Hoc4MndbJVPo5ErIZ2jk8mw1JRATBcJ8Z7McX14DGBHY0go+dOExQWKRyvVNfX8eF//zfwkZZtPIMn4/wfJ+UDwWhrVxD3DZU8YJSjtp+SV3P8no6IOrbWc3yYjDE3XP76V81QYmPOQmo6bk8IRbZrQkB3PlM5aghKeuJ7/Mgd/uTr7YibW3xO55DAlnF3wJrLIIUfADIi/L1ftu+r/IAhH2NJPXr8lzZBqWWONHx/rX2kL9/3kTRKWyO0CfMG8x3a91hw/RE4H/r3b59sA31/3tn17wsBvMPrvdHCKZ4S7o88gJbLkrjfZfm4v6zVP2jZ/nVaPchfaJ6pybN1tMhYpm3KfhcdH07Dpa3KW6Qov+o4X6AOQY51TqKupsMysTZq6J2wDd7xQ3XcD6IJ9Z4JeDLWq+ZVARBOa0FZ9ujql6HOf7doNzIiFWnPGG3n31KHUn63TakO9/8Ke/L7NqCTqcElv+9Oj12KjbWN/FZSqKjjExp+AOCR4cd+QwV0VxkBIJTugj1j5Y8+QBna//7pR/zPzx9u0lb/1s2jJH4LIuURPamQzG0IUbm8hyGWElki7Z0F0cKNGpHcVdzYqUL7FALY4vZsL4XFak23MJyB1VA0h6Xx5BmCKASWStY9bWNR9jJ4WSu9nAe+MgtVqN15LLvSSEzYsKgBzRF66wkru0/p3epC/F0G7kAlwhji3yTNRHukJvF4NZTu4fl2ZL+XtlfkKUmtkcneBBKpjDV9TYletBt5CNqJ4h7HH6FODJSTEXqNtH6MK67m5GA0Ag4BeD24fOd9zCQGmPqehKsxzavejIbiITP2uzJGCgHXy0VTtwtwfb3kWQkhsamiVsTS5okZ0MqC2LinR9guXevxtm51KMlen7hwZwR3mG5kQbmOL9zUos+74cfPmSviqTetv3bWGpfUGpbWgdbQS3TujSf5HcbcFVgQiVAjVypsY2BihsMNczFWGc6gSEdfwAyG58/+DoveCxwhVsPRxyLYQStphKmn1iwAY/1YJCLEDOWeOs7XSgJWqkHKX+hGd4686ooDWYph+cj4xLrdSvRHFoghkbLp+PvOsCgJVzsnB2Pky4J+tZGP0xWb91qZn0ca+bU0tiY8uNJbDX8csBSKT6uJOKdGgVFE11pk15yI2BGVopNx9LkXnsSjNjXYXdPCN14xZIK8jvO4YGwLrtuGy3rBuq5avqS3qKun3alA5EooRVkWlSta43VOU4qzoPcOdFsHF34mwE3Lozhs8RwALCpqOjwAw5yDVjojM62YgrXQIh2LrzXlX8cJZjzXNXFDveRvhaMQmBGKCYyhaV5r5DntIxtj7yzFO1tkMDOjt5FAVBRnO/DhPGOROpMs8nFXAz3f7/NWtug+LBNR4hdgFznreLHCpB7tjLZ3xtYdEdIBIh2XUlEhJUpNIv2pRp9rJpNYM2bjQZMv8OcECEcIhWpLKyuJeyjgm0DULEtQC1Tm0VJ51o/4ueCsWhOZCJoaHeHMUA3oEY0umSWiRgzu9jRwMocTodMZEbIoVYmxCJRMzN2C2LjsP0HbHJ4EATfujKLooNs7Cj13a8vU/etw/qSBia0Ugo3E8JZG2Tds1w0y9bexXbWUxFSjAgTo6wre/Ozs1+Cw8DvjuUfvRfra3AjnUvWZXRafmy7jS5YDyfuVPS40w2QTx/+uEGnUNDUoa+YqN67Hc0CU8PC2ntc4P8u66vJue0N6ff6t5nBrk/ZTARLKsgDIqH06E+RVKcDSsgSBiEWgzwW953lTcDnBjbkOdYoKaWf89owTQff93kqjRFMukiQMvimbHr7T4e/xrurcsPvZzsr+rFXZYr+vuZa+BlQ6M0nZUFztMnAdKHFY7+j9FFHhjTr6Mi19e4/a5U7z3dji/YAaukWXtmVROjy1jAkBoN7RLZo9jOc23lkjZa00RSPCVRindTW+QGnP2AYul4s5dbM590w13PWOxfqGCNZlwel0xvl0wrquwYvMMbCNsauBvm0Dl+srtm1Do4bT6YRl6bhuWqJE0w27E8cMXKn0zx1RmwYJWCkrApU01gUX2FwmT0zJrC8iinME1ShGkYVtx41KOpkqSZ32DBuedQmdb5DWEX+FnOK/yf5G5wp3Z+UNM4zzGo0a2mLr4XMXNfS68jjkhzebYUhy+kFlaGI00x36oanAmbWWdVOD/VRmBUTpfCNWmsLL1QTPUOUAEc1MRnkCGxH6U9fSXQ/K216fT4BrtOrxQ9IGf1awj2QM/wGTC2UI6ESQV4Bwjbm2R8dkhse7OU0uPfCb0zPFg2p4nVMdUefLBEQzrfRl0VKKAsyZUdDuzCEs6NINz7Kl/Kay1cFwJ1/LrHqi4ZmjstSLT8JLiqzrinVZcD6d8Xj6AU/vn8CPE/3DxDY06n3BErgCEMjphAFg+8wY/Iz+9A748BEfP3ywUg4SuLHKzQDMKJF4nco+6+lS3n4+f4bQExrOGHhRo5RodKBq5x6gdnKT9x+ovLOsi4KgZvB40D2flhmFL8mrOSxXh8hY2gIjBBu/l9sgwI3qbSZcOYRo5Lkadby8ya6RRtSiNS2HJy9wzQHIcc0LhE74/OcXPPzhHPgUQKbmN71x0kY3/lO8x/86nSHS8jJkZZ+8MQu2P48bHp9FDeRU/rXQc+S/jvfoPzXIB9xt6bDzZR7lm5okvf1iMxksHsqL3/QaghrOn+mrt353X5+oGO1/Zd8fCPjP32Jdv9R+K0X7L2y+Xt9rOL/X/Ix+1ageOo7EXSqjNUixbii7LEFL/fvtiz2gDjc097aPf9xa/x5bnHIxB4eedpC7a2nIrDXa6VxCjmXLUlR+u0BwEi3uIrTXzreWe3vjgHsY46Pc49rynt8A3fzNm9O7332rMh8kznroQij5aSBhKeHNdWN24Ws45Z+0/X4N6Df0PI2FlWkOwd0g93hIi2o7uq1/AYDxEQt+hCdT0+YMngDUQOgA3kHwufRdh+jqxpBQoq5nA+Hnv/wMAvBo4t1///QDXn9+xoebRPD7Vtmb72rfyYQc35OR2K5QbjZDY7yLI60/r6uVnLby1qYQI3Vm9kg5BmuaQCE0JszBmMSYXYXYhRbdT4u41P4sGk5UQaIGa6iXLIApwOChkQFzooGwmUDFUncKMdLdGoiUX2GRoCqwNifgKMQERcAkmBHDFLxS7vceA6O48K3oqZnXfIyOjoqq283K9S57YJQxcVXOsMhq+3UoWonvw3FFsPqO9u23e/9HIesgBOVxAyCg3syQwvt0vEImYE5QqbjSFoWvh3c/ggiqpGoZkTDnCGEv9lrcWUIV3+vppMYj+90NCLsBlgHT7jvgqWBbt3p5bKk1Y2P3+E7n5IZ1rZc2xjCDjRnNSLCczximUCarq+Y1a5nV0z+NvJa61IVRCDA1/bsIg9HQDIg0unlBB+n6wAV2ywDgmhjz2Pb6piBYrtyyKhbNh9YsAqCh84LT4wrqakBXxacK3UvvyYwf1zi58GS2g1vUWyYz1ssVc5kYL6psnMyQOQJHNAczU8BSrBCDzjAmUZl6vhxqOFpEBJ1ulc0EYGMBNVFlmmMGSUMPW11f4rbLFJCOOxNhgDRMKl6ewsdgmmmPhpMqWPuQytCEC5YS2d3vyst0iDgKOJVxSmGS5Ra/7pHQEb/dYgZCkbck5ba6n+LkJvCt4Xsu3+HGxaz5JCIaJG5Mf0WiIpkmeoyhDlL+Mwum5H47z+EprnUwE5oP2qdlBk4QwAtAIwxZAoDmBYMa+rahbxu2ZcFi//qy4LSs6F2Nlb2tEFP66DqXfAgWJdp6AyabQatEXDSNitTC0E1roMKcLDRAS2HQxsUQEDMEA9vmEGx1n4OhtsghsGX7sWOOKpD7GMreOuONjBYPyHCHFhatE+k4zxRkjrE8ciUcYUwJPsvzW9vgUV/3jEMJXtXYqzTZS2A4MCY/mArGI+RW5YMgo+x8fFVJkUZGg9KIpPZI+EzdrlGrffd8riGyn0J/BJSZcHYRvZrBpzYJhqKecElFvsgeTzj/YpHZ7ohCdv0GT9TEG+WTRyw46sj07GzjdFouSr/KPN34m04ye4EuDezWvxLMSJvskYfaOBU8zvyBLKLd52trWTZcuDgtAdgw0QVWl5i05jKAUCV3LXIUtUIbgTid9WIzjIcccwJE5rQDpQ9zqI+mvXsOsfT+ouf+ZmMTPmC0el1XW++MCBBoBH2FJZBHBu6dQslgy53PWm+a7cVgHheF9XbWPXV8pbwVwUU4amR1pzWSfTrPP6fVRhVbtoa+9N1ex2iOpOR7lWxBl3Tdx6cr+ruOZGQ8uoZi/fScXcHoJhuejN9cAvaO59PcfM0h6gzQKYdgaz5wxSab9QkQTmjQ5OF+n6fYDp7g3pRwS1GrSGhPQIAAACAASURBVE27G93Jcs9b1yi9I+2/NaTfeaddIDvcRfJR+CZkvVzKLVCYO6G1jvXxpCl1J6EvatxovaN1GD30mrpO1ysvBJjNWOHODO7UCO0dqbH83M1RraMvK2oNRyXvblwdlhadzdC+6JlwBTpFnjFcrgNjXJS3tAwVImbodgP6uuCdR7Ub/Lm8sW0DY9PMamNMXK8brtcLLpcL1vUEEGGYnNJ7j5TDIIBndSAUiNGOvjhdpsgq4dGeAJJ2SimZop5MwRekMTtxdsBHsJfJZ1aezMseTfFPEvc4PLHzxOW6d+dOj9H3DQw6fFv2mMNvLkIRkTrqksKBZ/aYzJhEmGMk/brDorqY54rmNPBp32x7GgbxSuOND2FmSGtolqIdMJ5NJCYXeDTmqc9G9DZSF+P3O9zziwS+8Frs9dzXaUlfMCBYMMAAOq0qAHUfC9kDBL46T78C2EAA5ove1x8eFB6poy2GuygdW+yC0pzpNJkw5ZLZkuYEejcHbsbpdMaYm8EhmfMxW1R1Otm4IjfXmoxHE/A2wDzUiWMWfsHOttIgdc5elwWn9YTH8wnv//ge67ri+ukZ5/NZ3ymC9riGMyNA6NTw+S8vYGaMAaz9AuaJz5+fsV2vkDmDr2nAzsAQPHJshuRfx1l2acpnyyBnl0SwPj1hvnw2w3RXkHzQsbHhcq8dzi/G1TfRaNxC7wCAm8XQW7Q+TXd3mWmYNh6ocncyh38KOqHGZJ+fwmkDgn4StcjYkNE1OjFpWt5CdCi5LA6OAoi8AMQQecCH//kfuDz3/o//pXRZEPtTj7FQzjsy4xV+0WGpGT8rLBhjw8DHvcxQ+XhUeaLspuObGypc2w3j8sY99d/x2uHpyu/5Gpd2hL2KVO+9/YP9/N7W8UofIVD08F72mW++pd0zvNev1Xj+pcj293f6udfk8Pet9q2R2LtngO/nNf8GrY78B9jafedzx3bLUktC9w51GO8lgFpX906uR+P5EcqcN6xG9H+372g3DP2+uQZTcbKdeJPn3CHY+fbV6phDgKV3MFLP2FtmG6spvF1cvpDgSdT+FbnpqJD+4JH2w36wlzs+eiY1pL/em8+doxb47B98Dr+yDb+7FjyutV0gAHw/KeSOep//jTX5HR/q368BHUBl95W/qorqfXMkcO96w63i35sfXIGg4wcAH/LV1uMrBCcki/hms4HthNQyC4J6WDKA55+/hcT945qrO2paTb2eqf5qSxWG34fwdHckLWRG9HLNkezidSBZU7CPrkqkDqvTagYHtigADbaUG6LMEEtDKmFAULFaYlx1hpHBNrQA5Y6iANNXau1KEQZTV4NidmdKgFJ3Dk5g8t1JrnzhMtZGbG3EBQq/WPdFMtJD7L9aPzT7PTIi+r2+1z6L5AL8HduveeNdyKuEWWTnvODrV58LY4kJSr2pUCwErKdVDb5miN6GGmBUaLaabJYW0I3GQUhiH1OIEtmPzY0vrpiS5hwGYYwRBmjPwpAMRypIfD4sQF8WgAjb2HDdNF03WZ3Dy8sLQG5sIxuzR4dUVUpwOSG1OtFjFlC3CFo/+S6giip+yLRTWiPOjQyabrpVj24iCKUizA0urTe0vmJZeigET+cTlt7NENHR1gWNgKVpCsaotbSDBFdSpdHNFWl+jCYz5rJo+l+oUnQwg3kDT5PQYc4JLiDHWWbIEthMFZVdLFKW0ytTHCxvHWF8zr6/B3PV7j4X+F1/5n0LUqGJgmvKB0TGBEkh5h4jU80tEQVRvu9++xojJCmWl2X4xa0+H5FQFYXt7nVBzRSXJS07ADQrbsyta1pm3lR5GbizdCu6t3NqXVrZtkKrRNMsC/SccbN98ucbwunMiJ4mJjEc0gSCBZp2U+tehuKTOEqTqEJfzwKvZ6x2NmRpWBc/o4WRtSh3LnUlPeW7R/I5eRMIOmkq7GZwpOVGbC12uEwwRVOhb2MD2orGbJVzEaUW6ngatXjemW5CZqpxBw+PDBaSXZYaX0yBpuWWst/O2O9SQbMqDKWmbRYtAUN8kNgO8LWDIMet5thH01O+Ax5dnEJDNS5hZ7xNY5wkPTJD4/HZG+N5eSb7QkSdR9r2g3ADKbivCMqdGoS0BvosdPH2PBvuc4m4XuYjPgEANhsCIxzMYh3SmBR93C5/0LD4AgT8Z1p247cOhnKPbtcxHJFCxVuOA9yR42b54r4Q+EP4y7WE8V2VQzwahwDR2t0ErXDUFlMSN9sXe9aF09Y0PSo0bbkr9JOPU7jhMSODAFv0eaTek4SzL2Hb+w6ZEkM5rtvtrRW353sqF0FQnEjSwOf0mHDHQ/IUqDtYSR7bPx1HcYT7t+S8oMzfwWDaru044+X9iskDEAaR1TN3RYHP6QEgOgObZ/MBqFv089QSQBrBnllqfJYxVtFU3WT82xgDcwxzjMjMPoEP/fwaXMT6VFyAL0HBfud0Xd0ZB8GzEFFZ7zsLhvvw5BGHu5cd+G86rLWOH8pkmYMKmjpott7Q1mYGueIM1BsarYi8udBMTMwCfp2gE4WRskPhTVpT/nJZ7HnlO4la8J0hV4lGnkfmC84SEsxaR5stFTy5syI8ynWCMLFdJyZvhssBmYwrEAaoOc9Qp0yNMHfYcvw3vUSFCMa44rpt2IYaORlsqbLV4WWZE21pamSUEU6PgDqXtdZ1rRd9hzqmWJT5nFa/eVqmFwn84pk+dvOXko1kRy+CuYCIO3AlvQmzedCg5C+c/t3AGN8q3B3P+meZkq+HwZEzaztQVDhpVnu+947WLR0+gDZm1CgHlKeYxo+7I2vlTTLyXHYOQlwdOOq4gy9VQsMy1WmYYbXCC2VphDYzmu8u7SQvnVLzkCua5uMaHfpI5wSFcTVeiMmmurfd17DKUwAIJ5NfTjs9UDiXebkz3znWrHz5To3CV5ruZQQ85tmwscnbl8sLWu+ZNaUp3KpM6w5tyd+F06UoFz7NmZJBkaEp16uO3SCEdC8efvpJ8URrWM/qsPL4w4+4jg3z00B/r9nRBMCHP/8JmGeMYaUbrooHtrZEJorKz1V65xHLNSMbjnADwJ2CuOxdowa8Akt/B0GzbUo83kUdlDyvQHtskItAmvJtWgMesBCThJEdu+w6OqPZLkuXsTmrGxnbyBwCA16S1lc9BGB4CKJVAiQ1Y9m/4wukY49wlDv49Of/F2AMETz/6X91DHhnegodx9N/PSWMQAIH1+yAe1gAYMbzy4cPO57db3J2wA1DFaL8t2qwqrxj8Jg2nuAPvoNv+bWtrvMveXanTvyO9kxmRLfvjL2h3I3inmzxrfbJ1vhrhnSnQ7+X9qMN9cN3rO09fvmXtG82dAlujKiJMW5dKo68ohxwYXRCeyN6ymLJN9Tr/27f0HZbqjiPg69Ku9gqhI0kbGUsEuV1PUOZ0N5QfZQ5h0lSC3CTZVmgtq8HIbyavu1BTAcA4EJqOAfMeP6N2/sL0dC/2y9srn9zu0LITOWe+7qG32f75zOgf8fa6t4YM17TVYema38vlS/1UFXv1M8QPIJ2teOc1Tv/xwr89UcwfcQzaDfW8OQpU6hKEeODcMITRD5jNkI/3M9QJNIBfLRrDwK80NtI4EbZ8OZq7dsvZRrk8MntezvDb1G+WqkxG5sLCilQ+i++d55dWL1Sc5SvQyNl175oxAsTiDgEO7N/REQUIOW9zvybIh4AWYj81fR4q917gTpDXIuS0mdIVAR7+91NAQyPLldv6E5abzR1j6p48PSjxxWV+jX4cIqUUxGZK/7b20clGG8bpzqVUKyFHw93NsnjUhmX2Ni/CwXKs/lln9w3nzs0T7+39qYGMWtpGKAgzjrb6Qgl+xZgWZruNZnxSMww3rzGuRqBddEzSsQN1/bSBEKV3Mr4KzfoQicZs0hFcURWl1ZrLHr6V0GL8fgezsk4tYYmhDlVMd1bx2SNWr9crzifThjbQGuEdT2ZsgEgUaXixlsItq608LXRlKtU9Cf6bk3rIzo2Y8Y6NJJjaZpGsjUztLcexNYN+n3pGJMBSi/xZoqXbhG353dnLMuCddWalBgaJaLx7g391GwsprDyCGkqOK/SBmfWDVWzMMa6YHwaGI8zFZazW5So1xXM8ymwCOaSXnmyRpm3pgkpSVLAFhHIRQkCnSnoRCgcwjAuNiaPmPa7DIdSj+haV9ioYZhUUAllpF0zGIUgol9c+PBx3T1Q5bqPYadk8wXe0br7QtE9I3o8fjgHwHE4byMjzzryFj5QRcStwTJ+b6osB29Go7QnjYLb95o1fRkyRvTtihOHjebKeSJVVpkSqC2nyE6B3qGp+TN6Vm+1iMLYJ6jnLhFoakrsNhp6XzR6lxcs6wKAIurOjaoyM9qRXAln59bxkcKyOoY0WHaDxpZG152DLIW7GdLJywkwa5pptj5Eo4h0DThrOZqSWYKuqUBV6Y2mlt/DIlkN4kKi4FF7NYWypdyIcg76Ssr91yQbIQDSLAZQIARBVzDfY/Tv8RSBxw6GP1//MAQelOu6vyWFu0gq3szxyiZbFO6ygzcfy/EdAdcBTwn/uzk0snAgN2x7dD5nXzeKE3u/VIOJG5PyHlcMUtMz79kGPGpbbzsY1e62vEMjMLd4X5bX0DnWdODe9oqfI8ec18PZxLw1ghY78+4wSMj9KPsQmEs3M3GNSEZyF2FymYRlXazOuEVyzgnA8qiCQNNTvSu/C+fX7FUaea+OIBEp6fVGHZeyZZIggjR1WOORqcw1m4HOc121ZnrrPYy9AqD3VXlYr9lrThFzDnuPOwy6gbUDDVhWrZ37enkFWvK9y7IEvRWQpV9X9VoD5T7aOdrvU9lXAk4P593uij13eX3VNNq2rnVNavM0yjfXo8c8P3Hm7IH5Yql7n3rS61eBWGrktXesj+8QBrJmNNcdKcRhScpbBYwrmBeMoWsyzIDu6cdFLoDRmJQ8bQ1kr6asMuY389ake9xskBTnl8IIVvtTnHTfIRDGL8nuATG66ueuLnoZsV/3qNKm8MB9U4exTeFV+fAGakNTrLfFHLVyRWMRLkA/nzW7w7KgrysaT/SFwzFNeWYCSLMfeLaBnJ/jn4k5NTW/0iwBC6mDBZQOazanBmmE6zaxDeUjr9cJkWnyoPL1rvyN7FgEbFON3l7XmSfj9eVFaWzvmHNgsJZl4e2KMYdFnzecTu7YrdlJxraBZcZ+dma0PrFi0fdZBP4cZjTnieElXyTTuJu1TstaGPx6zhzFJ17SCvHP991zK+lcM+I8eEsYDRZf73I+jDeIqGS5pdP1m/O/cZolcTWVfyDNJMabGuxobeac25KOkUO6AEPxuMvykTXG7thenkFQJ4j+4AbMpFeenpweFMbI6UIK5zpIL0vlOEoAY9Ki3jK8TEnhu53mp1xv9OEqVgqDIHgteMH43eDnPUOSjoewgjpBmqempuBZkKyaHtVHApFFmYcTi3UXNbeNxtrzvnM+3qCbEHNEyXIMXkYBQAQk9NbA08qWKVeqRvQijwgsmxhPWDJwpZc8IHA+LPFywJJt/kJPePpJqwlfPn3C+fygcujjI+YYOBFh/qQOPATVD4w5McYHbNuG63XDw/qDnieekPMZsjAu1wu2Tx/1/BRepQGWea3t0GOlY+60QtBz6E5KvTkufIwsCiKwElHKCzcQpig979QgD4IxRI3nJBCMcGBUh27j4yBorZsTmWvujLdsdtqnVpUWUhjooUOBOuVS6j4JeRIXi/JmBxG/h/VMsAAdjxh4UflDxJzTpeClxDkVF7jjhNCzrec7CATPf/qMd//1pOMXKH5cSqYdB17AnFzUsWn8zKa7yIxTRHou2+5EIOmffyGg4T0mfYL8TH7p0O7hteOsvq997cngQhQp5pgKbrnX2P65PpTs88dvZjj27QdJ4/l7+eV11D/dXddsAjXm+Zj/2dv3GM4BxFn4ERr69/Ert99rSde+4XUutwtQregun72toLk1hOvL/U/SxTss/O49/26lfcHpoUEdQYkEq9Fr57ncKc2fvnr5MctUx6I2HHEHYLgDmhhpvw0n3Qh4sM8nw5nXqTq7zoxu73sXGTQVB1wDBr6OI2+mf/j7jwCPvy9uqdLe36Z34O05Scj/XrrskHHioN/9vbd/PgP697QqZxNMyWSKHJhy17/T4YHy+S1Fab068QGQ/8TDH87guQAfPuBEP+EiH/DZ7lzed1zvBo6LJUAGWJ5VcC0v2TF5cNY+x/FbNieEv1W/t5FK969XAdqwdKTX1WY7Vq5xiJWyE8Lqfs05TdmsbxE3ohDVrv1nf7Ui48JoezsjqoKh0nsX7ndTdaE1FMga6UZEcP2zIxSl/enF3IShiWAZ9v8Q3moL5VKBY5ED4B+ByAXmWC8goyjv7dWezube/b7Q3N7j3a+9RVLK+bevVH8yxd82GMtiBgX3cFfxXJkHwysuxFeDl/dNuw93fhB7XwE25T9T0apimxvx1Z9ClXOcKeXBYcAQaGSoCIOE0ZumatT036yR89B+rtcreu9mSFelQ3NjIBzeYIQxPwOpVNX7OPCsX++maI9IJlOguDEdlNECzRSWjRCR6QQjxssJvXecTif0roZDrVFJVsdRnycTwLutp8N9GkIKsBc84sdDnSIWLMMieubE1lqJFjh40IpHu5vCgD2yQTQSebrjjEb0JL6wcc29hCfQ6AGmA/4suAZwA6UBkc2NQBolr1qAYEJdKRvKtDeYmCMeiD09gO3dFoqGOw4wN/TV8NNhK77A65c37w+SAFErlee0o3uPzS5KWje6QWJoXdzR4KC08EiyA25xIyPzxNh0AF4fz1NTEmkUGwvQeEDWE3gbkHnRe1SFpYbLlsZ2PT9qFHLSxuN1l6nB14yZNV2rUbKGjrlYpgqLrnbjRpIMM2A3i1Rxpe1uyyzFshmv5mjQWu7djEDq3hb4RtKBbMwZqyVLw85eWoxFis8OeyRuvAUwCWgC6ZS8HdKY48/QzhFAjeeZutPmOxFzJLJyC47nRaPpNGc/W+r++81p6bSyGnCa7cYlX9/WQMaLVOP2ka4GLErCN6mWEdUsJsizr79nxHnbLeLdQ2zKwVRQ1L4aeZp9ifu9Zvre0dHX6zimNGCjXjM1YpM8M0DyRqXTm3WuJ1wKfzOn1w5Oo9O+FpvTJx8uxfjKguymg4DD+3ysz61F4K8Z132drEelxXk2g477mnun5lwyMTWa1o2pcP6i4hpdb2qW9cBlmzKhakziOW+cgwgKZ5FlaafY2tOzoC/unFDuy4gCpyGUfx1ucZDBrCSMnkVLI++vp/zqBndijjMrsX+5Y+rD6PQOOD2cgiKo8x4lvLDg8nrB5fKKx8fHpAtlbb5sPM/PvsfbxwsabWiPZ/vtYnLdQ5xWrR97Br9eINB1bD0jUB12ARRYPjRelWe4atagYYZMT18cesqCu49n25f43udvac0cG30/HEYrTkj8VAwNAR66DyoH7Rd0b/T3+yq22+8BQQ0+mlZbnSbJyvq0ptHCSnsf9K/xvkdcKJGJRfOXRf/mSNS6lxmyrCw2ZzI84E7bGtG+x91O1dSJVvd0GJ0Qo4vD95u07vUYWtiELdONWOpMmYzrVWtJL61pJqQ5oizC9XIBGOjnNSLAQWpc56m10LmrM2nv3fh/dcQQu1cd0RkLd6V5XcA0o8SZR51PnhYlPzPDhRscjSeenKndPcrXZWbWOmqWFWlPJ4Lm+/r5tTTHw3+svzu+2yF2/yzxnzuQtAPDXQsHEXLobMFPdCC0ZcqDTGAYz228RPLXBMJD4Iz5wljeqXqYXwzfnFKGgq3Bnne2kQfe9t5UXhJq8T6aGrGuvJONsJT1KhNEPxPmZZ9ZylvW/nYcLXlwI7MjBczrOVItBgRKnx7TyQZAOBH6+jrucH6gEQGdgs5BgAnLavAqYVRWx5l9hgAQMDbNJNR6w4JVnUUOPCBDZTAxmjYnA9McXy0jCkSdkDFvmT+FV0Z7auqAwkC31OtjLGiTtWa7GZjHdYCb8gL9/IBPn/6EbduwbQN0Puv5ccdJUSccenyEPKth12FBbL16yBUU44kSCgYVDYKFrUZ3a+pkviyg9hTnnOcEt4lgwAgwk3Jk1WtQHl6jyjVblgT7RZZaHZCmRnSVuRxGAHUGEQilo7nvR3e5CIgyV8YxKG4v8JE0TWfIwec3XE2H6jyJO/VEhqYjLSr7yESRA4zwrOcH7/D8p2cAhKc/PgYc8k72tcxZhXZH1glfAd+jlngkgQheCh5EVgYOB94aFjC1A76k62/hsW9tjkXiez3v9ls45ZRnfklzbPVOvs34/U4yrfgzqQH9144BUOM74dvG8NZ76Au/fa25HeL32o66lJplwVtQJ6MJlWwAhS4Cu7U4aoqSf715xf12o1fK67/nNf97NCr/BZx/t2xIX3jOHaqbSOFfVAcdJWXqe46qCBC6i2F27bS/xXrUwNHvafRrDuq/269u7rAYOilKp9Lga/7F2u/WgF4RQPV42R9elWpCCWX3gQjn3nCdE7dHft9COQPg8vMVT//5hLY0PP30XyoE8x+wfLji9OMCah0bXLVTmBAxL3AAgxCpd7toRLQqB/SJtRijAEUi74Xw/EYq7RumaLc+NwsWDNlv1ozhalUJXxh9EJU1lpTL5lRG0moetjC0sSmFnLm056eu1UU0cubUF4t+cq9YpABKpAi+AXMMMKlX+ZwTcw40Um9dArDY6F5t6A9QI/qrw5Nz4kWRd0P4IWZokagpRbDoRU+/5eNqHR65pU92CDGaK/FR9zSF4PDYlTSim+h9syVi12u2Ok/fdQsfuxMTTFA6nfza9iZEfvWuI2zv2nFwh+9LpD3TXlP9kOvjCu6777Af3LPuermgWcpkgHS/PXKQr2rIAmFZVr02OSLZ9v0Whjr2xwxDUnZUxFJLcmyi/kwVLGyOqshppOmipzCGGJMDSyfZgUbdIoqanhtKGJ9zovesq641UMUcVFy5ZGM1WGpNjWguFItYWjIB+qJGbogZuK1GjhvNPU1mpN20PTx3VY4yENEfaWDvOJ1PSZw7oYvVrSSdF666sPTYbZ1u8YM7CCjcBEDo2vuazY42BsbYghFo02vm6lmXgsfcyLIxYwytUy4vqbSJ2sVVoicAVxvPOVOi6lzCpSbuj7HBjBMsqIdclZEmwIhPKyPRAU+HSGXi2bf+LWptM46IahNSEVEPyPHYiKv7aH93EdLrdzcXHY1Ct632J7urLKQlD1z5+UY/VfHqwkI1Phyx+n5eVZjUfpgZGAB3AYaeN/QFSzd01Bs6d81vLozJG5pVgNKSqyleO55W8LC1MloHgdZG9XuCKKjybdugEe0AWhvoY0FvYqtrgmlxDnDjbvMalPCzbQZPEo3WrutMegZBnOfBaqQrKhFzJphgFixLh4yBJhoxlKncKxEiNQQTRdpFN57PMQEQOvXkI4ymE6tSzs9SOAgYHgoFuCmyWsC8zRVkpSIocC2xGs5ZgOap4Q/GKB+yiJ4HFSYlzyyQik72mt+H9NIFyKoBwM8NHM6Io68bJQYOBvkbKbVwtbZuEnAgWu+zoL/wGLaHVNk8AYtcIqCkQr3lmMWdCcQyZdj1Rq4Q2afEdAOUDq/yGXuupMamO35VBfgIA5bjbMBp032Hzuy7Gr0M8+giJI/HAvG06p5eliw62g4piWYZCb7WzkfwGw7mbmRLIhF7MYUh2wC7sp8000onAm0dc25aZqAxWo10hEWaFV7ejeZRnqbwNrE+ge98DB55DpzO50hFzKJZdOYcsZZZs7vgfVe0iyrTNSJdz3/vRo+brsnj0yNAhMvLa/YgUqKEGZB05lAnUwmc5DXeHV5FdJ/m64bT41n7ahRnKPdZ142nGrFvSEOVW+5Aiyv//Hy2BwJwShgr5NxXXIQhr/p9sgBjs1JTgpVWiy7W5z2Frw4l8YTA8ItcMcUcpbjwH1IGaHP4Fup573rli/e/EVo3vCoU/JjiWSrPu7NE4phG/5+9L+2S47i1vEBEVnU3SUmemXPezP//dW/m2ZZI9laZAcwHLIHMqiapxbLk59Chursql1ix44IMPjsCGEs64fEZ+b6dUdbGlHQO7NmYzYMnGa3fmZOKGf28GJ8hhl5Gzk+VO6xnFxBOoAuAe4JeTO7m0xntfMapL+DePChSYbXL556TMR24cN4XWTh71mz8UBxqHepBKV7znIjQuIO6QITBnfD6+mpOfPXaxGPDeI6SX5qO6SHhBGOwuHze3InZyGCiYQHd67qZLE4WoBKITOawUrS2QJpAujnSe+vQDeksV1hQzgAs8yic4+G0cjpoY7V+jsw+nwZxg3+3lc097Pshg+ooZKF5Lw7rGOc5uZCXubgKfIzlu7GvAYcgB8BoiOBXO0eEdjJkp6HDgizUZW5iNLeYRdkbyzLe8n3bsyGILA9WnmN7tizegM3nB4aKYHt+AXB2mqTQJwG92we9B02EWvBiBoMhzoTaCBpB1jF199i7Muc4JiMDP/UlTl09ccanUqEL+wowsIGUsdDJ19DpHdnenefU5Yn8vTgJb7LlGUoj6RB1nakLsClOywkCRaMIkmFwN+f4kIGuLWUsBzIBt+aobAqPJM+SBOpl/qxEg/EaFdr1L3MUyFERnSc+ft7QT4/obcE2BnojsN5DxuZ8b3EUGRvT0IGNGl6eP4Hvznh6fPSMelcSVLBuA9vj426fx3SZWmsody0QpdTsTJuXjmJVq0vOjKV3cO9YTiecTycw7gEQtrFh8IrLenE52uHSm9csV7V+iQWwqxhqxcDqWde2KUfSN57021kQyIOOoFDxVSULSupkej0DgACdHvCKR0cYsHNHzLMGvM9N7GH1tY2zTmK0zALV3RYjE90itv1OTvUx1Ox3+/zRJcF3uKwX9NYA9El7yGQnEUtGUN+rA5/nHPieR5Qo2Av6cYnxSVdU+DtG5+/tCZ8+QnENbbzr/Rf146+1oJ/Hj6s85Qk6jAAAIABJREFU77Jt0pkqNX858/eRTNusNcrj829pj74g9f6499YzJtWa7YNeZ7x/vqEe3Wpfy+z+xmFc30N4mwn9ghaBBd+a2f8O5lv4yX9//PLlVy1kn93rKHS3o77m9CtF6tC797LAfMy1bqupo4Roe1u3ne/9jSb2v1m7KXvfmMqTGnx6tFjnpXWs25ZyXA3mMlHDdWndn53V/2YYLzmNeZ91QdM2cQfgOSgT0ReRmOMhb+2Gf9YuuSK3/vOX0JNf9sZvaz+PRE2+P9mfEdoWNvsseYUMypg6tRba+I+bid+j/Wkd6F9q1SaycwaWVRQ1I2xAGL35LCDjBAWfAXrYodASN5x/uDeDbhoxrrfiKxR3hWy9QPEuVaDZVIHlPQGfgXsQnn8Gi/jWQ/BbEJOjAHMdQX37cz1QuVibyOQx4uvKtNYzRhhA1hWXHSf2hdU05aTjeoRB3h2LgjCS7wXs2Bo7GKJdPysku109HVbq0LMBVSrYBOhp7DdBofeeWXriGeuQAYyohSi7OlY35z32M759HcPGdvz7+vNbxuegfr8/oTu+8Us9uNFr/7yuWL2gnKvCD3LtU9lBGrAygzvtEx49Xhwjtk9MwQrjSz3B4fyMBcxvNMRMM8CmIoop2MSum2sxg4MQwgfcUaED6nHOBM9MI8uubhwjI9RQ0W1bU1EHZjR4RD/XDDND1HTDJsUej/MazyS0zmCyrAFq5hAjBsAts9IzK4Etc7x1rzsYzNiZM3PLbHNzvHDOgypAIgZJTNP1cjVnFRo5+qxpPvIMP4DeMfqjGfsGD4PlUzMMzHfauR/i2ToeoLNuK9JpmZl86jrwFAgBlMAhTzUesKAJKRkHmHsoDYk0jda7be1w7eLvR9Rc3G91VOoRNKV+Q7tr3qA0Vy+/RWi+fpu9IfbkW+04gqqpT4fRVR/mwUQ5SuXsHzr4hkMlDQrke8WvGSKmDLiyp2wYMnE2lAkQD8KYQkMal8yAJ+AxDImEFkBWBCeD2rmwn57JGVF33kQEg8gMelLQDvL7DWOIOeH9nY2m0VFGNTtdt3UzmOLT6YTxOsDKoCyiaGOPOR4yncqNG3RsALplIXNYE+DwuKFkuZHM4YmZ3FgFNmj4CsvtAgFhKunxf1LM+vZ9GrIIBLS41WiRhMMaMIOqsDntxQPfMIOJZoahJu8V3c9YzciiMGQD+VlsratdVZ5tw5t7K4OISrZ5Gur82Xycx8LDU0aI803TmR715YNeR4BD8BAbh4CEQZ1dFiq01bxl2BEX1F/35zUcUPM4vuXoPsyP0/YdfTr8XVvssBoIOK/XdPLUvWPjLgo/KcQhmPN+EXSe/DLhliMzT+w+W4+g9TBdIWlUvADurJ7rIH5xleyIOkDDcIqIQGRoFRQPx6R54TyP31Nu2U3mPCv7zHPN70Q9U03cCelyUGi8O11qN/FzLWPP2p3kPMnen5JBnImgQf6ZZb55bpbz/RgbqQLcMigBUJzuTzkPEcSrAC4vl90YE3reS53M1b/mf8dWZ7H1pfCHinyQM7szTokY4g8LOyyuuuxoYxgjnDo7amIOAZc3bfxIxAONvqtmNmGUopi1ZX9e+xLnTTpKU17b0RgNAylyfEbHDXI3aHCd7/mzSBvBHnMc8zt2yGrLNidwO6N7NmrQQY79CcIo94dDP22Ele6Vc68enANml/Npp4umNlEIWVLtLLszA7dEzOEeCEQKz+DxzEYrbdQhsoG7jePl+cWD0GaGKoBEHQAVfq0D2oyns05IzTGMIKkPWJQx2NbD9hUcWYAgsMzZMQY2ZpwWo0NjiJ0zd0JasDB5RrSXKRomZ1hfkaU8kgYFjYrfU/d1+hj7vMypxX/OwL/8GfpSpaW5ujNrdrent+udfGyKbXdeVQWX59X21T1hpTVldMARezrM0egO9CYN62oZzY09i+uCrAuXzoPUAQDSc54tEIHeIeUFBI1NeWJYuaYC3RL/j2AU5gaDZVcLWok9GkeonDU6E+jly2c+6GjOTJztKm8h1Kkiy9KkF/t5NnmuLgWBZsChiz2bZ3Ib3ROcz3cIFBNujMYdbWkWfEKEPgakMxqznS0fZtCo4Zn5FvRh+zP0MRXnB6VutrjsanAomnPR7+7xsq7Q7RUDDVsT0HrB8u4B9PiIMTYspzMum5UCMCcsPPP8gpfXFyy95dwxmay7joHx/JQzrSEb+O9QZOZylEIiOC90WVDZdGwGcD6fsZzPOJ/PuLu7A+s9FMDr6wteYAEH22aBcdQaSCwwTYRArIYulRDuhtRh8nicRcw+uC4UQX1OKgHM0iIgyzxvbP/MTioQfUUXxqaavD54i5GNQgN00tY862r2VhExu14E9uyKl+TWLTy7fDa3ou/sR6w/AfT990lzKPe+X+eJMq9//xF2/kynyP4DKUvvVOHowhTXoZ8U+J4mWoNfe6fAU9KLST+/eF6/pf2KBxztpd/avjUD/de2979ibP+I7k1N91dN+1X7uZD4jwA+/Ir3fYuOdmyxz/efxR6uX4Sec61n2y8loesgV998dh6yf7evtd18Hg72XAdznh/VPSLCto2dziRTJPbym/b7tND6d3CUZQLOSHxhl/ntvlCZLzRZ8O9AQv7dfnbbH/RIyEkETmd2Xhhwyg6pb//5V/Vf0oEOwAQaV7aqk4ldKt1E8O604OnihhW/rRpXqPyLQ/341yfLNtee8EpBSKQYrUPoqu0FVl+dAAf4smtWBKQPsEHBjmXzDMWdEp6KJ7dG1Nsw98JXef3Nz3+rlj2KsYdR2z8LA0VQ5xAGLbFSMzNBtMEyatQdj2F2CwD3MITbo2KGh0NQR73TNJCI3bfBofBdEL6QYINYRggpTtCds1zhUCJqOavhzJ5GlKJk13lQy/Q2B7rCQmNNsYAKGgNKjM6M3rrXayJsQqkkKYxrGCK4R2fckANuGvq0/AOuuV25MKDfj8bsnKaj0FMe+bVPf6umk8ruPqfyUzEzzMkzEUMgWLy25lSa1HcRz2ktSsmVok/xFouiij5NQ5amwiPb6hDLTiXIYPoiOwFU4EQPixKOMDosmPrYX18vgOo03lDU1rLvGzNOzaLN45xEBhlBsQkShaG+2TLNm9eIJ5dwaJ7jYTDwp2UBSA0qDzPCMJVlIgS8YdLYnAerwcbwrPOAlWtm9OBGXs+OLKsoDDBshj3LHoArpATiBcBwxZTNjkAW4eb6tUXNnwBcFHTPhjChSMd0HhuK6LdmRs9cB6P4CkIDQ17m+6gxaAtDD6VxKbIlhkNzjrF5vfTNIuMRNaS1GPOrcWkao2kj8MlqGw6v5Re07pjNowAosnXc3qPqUeLi6BYu+IrXpzdaU7lb7EKjzszTGR+GT5SzEo499azSMNRreWTs0/rFzcwgVCUpxmOO/2+jQfvvYwwGJzmVruQ/R1ktZAPS0p/998fnX703aEIY2wCrAS5W8zSz4XTzbC/4PwJ78AcRMtMSrRnvihrsYUCBMUX2gxxTXPmvimBAIdIwNsHoA22s8KrpGcTRPCPUIBWB3paEXFXvo9b3ejstC7Sr7yMGN0pHt5KY4c0FpLGtQOu5KedTur0/lGVfm+rYjcy2DeaAIS9F0ISsNitKYIwrVxHLaOfLoDiFCBjiNeiRDmduLWF64QY3kXBaDmjzcyZOUMbcFdUZl85ugu3ZuZtzz+S+L/d9C8c8sm5RNaQilzPTkcVesqK+M/tqvzHgjhyTr0TEnLFsDpep5TaHzt472Fs57wYZr3i7ZrkjAhwMmNM4Qil35FhTiSpO/4MxZTc3hQ9fvd35z3EeVONZM7st913tJ+b6pIPHnUHwORjaPHPRT6BvQKd0JlHK5Nc2PAKiImYGhRIm+r9ABrnxwJ3gwSMI6ItVjVMiyGWFrpvt8THSi1+Dh67lwwkz7xO8/zoyBxQZeCNjwHXfXBMioxtDNqf9nnGMkBssC7Mv3ZTmWkNUge1yARHhdDbH0bZeAJDVLyfCy/OTZ6NPmYf8/EZGpRKHguBngBypwmCq49wpFMtpwcuLfZeZtO7UPc7T/L3SvTD2HfmX0WaTh1wmwhn6rLsDLngF4QzBC0it3nF73yCwzNagP2MbGPIM1VPWUlUohrzMuQUy8CO6Q7NDOzk26IP6WWbME1lH883Su5+r2I/pRCfandV09iRfdD4cgQE0aVXKPztUtXC4VHqOqXuROckbuYyIAaJlOqsvgYxS1vJEwEVhsES275jPYDS0u2boPw8E7QpabD8/Pb5iaQP9YbFxqsnJSUNzLLZSwdMB46kmg1uQRjjB13VFBBhs25jIKCHDefA91JCbRBRj3aCgtCkYAoSvnMYeMaXRUBsMxn6MgW1bc44DqcVofwghmk70sa4YZI78QR4Q7M5DFadvQacjmCPpp+aaS6IjOC+KbPPQ9xUTzUMdfQOamzPg9sP5G5XRUzF1oZbKTiaaZ/v2fk5OPfeE/z5DleyZzcm58f9XbCDg+Q6DBK03LPc9oSlJzdnYhLFuK6AEboLxJABfLNB2dOir8UvoM0QezDH8JL4ugShkctd4FOAeU6CPsVLIb9NgbeUufCZcbrdM9iiX4fMSLF5j7Db8RIOoLRCOfM6tG5rBm+y8f3r/Yk/Yk0PW6JGiH89B8DR7xnq5gLmh96iRzpZZbl5aD+Byh6goGhOYO4gJy2nBsiw4LVbGy2RjO2N2rjjF8WqXS0erDAwvkVB1BoUnVyS6hKFDQc3QH/Ve18+foTDZtzXjvdKbBY0Oweb6d2uM5+eJHnVZL1aO4XwCEbD0BavriOvjZ5O/QnUqPFV1BvBX+SSIZOijTCbTNuev9/f3uL//C+7v7m2KhoLuCfIkWC8XwHk5gaAcZSwGxlA0MAaFnPeSyQIUS15Okm1Pzb+JFCqbi0zWx+Y2Cwuqa2i9WemaYXPaokRBeTaRSUySspvtBVaAukHNZwkJ1xki6OLYv/p3JC8cgdMrT1QAl59+wuWnjyAifP8f/zFlKwKWU4cORcd3EPo0Uc/KWoBo0up4tmoRvcj78wmd/wJAHQfDbJYC4F7hAPNVov09G+1+4LBGX7nLftckU+bgdnJ+qw73B/8uaMnP7OXPdtK/1znXX33H0Sjxc1rRcX7X5q97Xz6qzvSfVQv9l4y/itLxkQKaMnMELV/rK/ZDC6v5uhP9n93+mL36cr8UilPryQuBCIK8DkPqzQP4NK4zg09eR0iZob6ZMJMSQ6YpGjGAydsUwObfhX0xEMpu9f44wlshRrENqwT4z2i3+NEfqX1rf4Lbh3McsFWNZDgkP+T8O7MNXAdMfZWQz/ijzce3tn8dB/ovoGBRIwm4Pnz14MXhNmPEZ6h8j/VxBYNx/oFAaFAd2D5ehTzvhM7dw298RDAm93MEiD9V88kMHXE6akxxDjRiYC+0VAPRdaakZUmFMYYV5qRmE0g77H2iiq6KAYvwjETSV4RpZf/71RKpKxW0J8bhxHPV2yP0jW0wN1O+PLSKl25Q7Q7BJ0SGUpV3h+Hhhlg3X/Qz2lGKuSHV3Lor5juV+T9OqzMQke5mkPaaW9NO4ATbNx3VZ+jVeffLEcbC3hcsfUnjtEVGT0ejrit6Y1yGgFmt5rYijYv2otmZcEKSM439/rZeyTAFt7UFIVjkgNLoYZmkRpMGtm1GbZv9eWY8aiieNOcpFPLmcKYWPa3Vz+P2qs2NPA6/m7XsIvO7Zhy0nN8ZhTaz1JkiU9Izidgc6lkzmjmDEsxQapTW+txzra93QlVW4cZSAl4VuEeWfeYwOMRuoPgXTqg9rbFu0P5VZbHCSDzEM3fcgLNtG0Q2N3YHvPCeZoXhn90x3xxqkB2WULcwzh+HO5WNoz4Txtk0VGpkyVbahNzLcW4YM2BJb4HHHWjtL2qF5LCBY//SJ10/8PBJGEkYh7VL69ThTv1luuH+EerG7VmTcp4NAoozCHmCoi/2NzsMacCkQqMUiDFEJsZobFnqjf2sVuOMGdtsvTeodMiY9EhUDFpS4ZkrsEweh1kag3YLfMtJSTBDYDhBmQjDAwGYBCODERTbWNGd5vXWzRAoYo7bMun1jNWAjCEjyxMoWTBMQK7WTMidwAAkDwin4GBCU7Id4QJ+1r0VxTbcOaFjPtPXNM+5BGRjOKrmCtYsk72CdnBkJj1+o6Uicn0Nu5wQGUfRz+YO9F1w12HdNOb1KEvtXu0OgcM1t5r69bvnef8LhYPxCMT2TeUq3lGDsX5Jq8ZJ24v2d31HHYt6hlL8Xod3Reb9mklv1WGaFUROXZLO+j8/80bdLFiPMjTT57O+R+HGZkNHEgyQWoBIONKDXvtsphHf2ChnCQLazf2k8bts9CuedtvUYFD8s+Kuq8Y5t8h5v70/9kEQlJdTI8g2D0oo3ymjJX2Me6cT0gJAIuPWZTyH18+fsMC/gOxV2B5jZjw+Ps4AmoDlr3zNHShH+nxU669Hvf9L8Fqujbtf7QyIgu4I8iJoi9GfoYLxOLCOJwucolekNqRnKF5cd5gyS+k0DKlI55n0a+PvlN9Fyk6cY/nmdmC3R0f6pJnIvWaOUcnrdvfmH7d6FMY0QuqJtNge9P2OrIVMiMy/qTBrCahSV6MUTHcmAmRmIAGNE55eyTOjZRjfxAY8m3zY77vTWfLgszn/IVEzU7ERGdIYkdUR31aDudy2bcoKSl7WpFl2p59zzlIOJkMO3QAvqRNBubughW2FyMAYBGGAdaQcHzRHVMDicn+W6SAQBMqacyYeeC4C65sv6qQU5CpIGFjLv3BCOsH3PF6DbQcy+0QyUzScXZNXz5XD1M80dOJZPsK2Y6G/QaPj1GnpcSfQdovW7VvsPkMDUWwywEpY5QmN7wEATaZBMBzpSkbvmRTjRSCsIL2D4hnk0q7eEzDus4f8wPNMEUJpAz94cLxqokmkozd4lp9pm7OiM/nDuPWZ0T9F3t0vBAAM9Lt7bC/Pc65i5kNfoeyg6XcwGTGdGc6PKOhTCeYLXhIO0Dqu1huOtHPSLQ9WcRuJDsXrtqI1xsP9Pc7L2ZzopwW9lJeJsiEAwG0G0YV5KQM8JGi96wrOa2UT6FBHAdTca3B0H4bg9dGyWvZZd4L1xx8zUOaH//gPlx0Yy3LCx//3/7C8f4ft82MKC8SMl4+fAOZEhaLGRYExhAgbm3jgRMMmAtCYfQiezhYK3z2Z53Q64Xw+4/7uDvcPD6bZiULWDetrz1I9USM+S265TDlomPOaIvB6Hx56ECdv7DHfpphyQNCu1uznIMlydHzg/ZkkQjWge5711HMBwFEK5j4D8nB9gcnt9/z15/W7j//5n/jhf/9vK2fDDBXT2/l7wvi4f8p0IMS8lQc736iN6n31b/8ZTvR/pUYw5/XHN75nANCbFtCvtvf67Y70adn6d/vdWsjatHeGT56C/PtXvebfq/rN7fq4vD13RFO/yKDtuCUExtKu/VhFsyp6hZRr39Yu/93+0E1jdQs6LYV+ZTamDGcNHv/zNNE/ZPvTOtDdNPXmElC5Lo2GCmjUSAJwPi14XVdsGsqjuT5foLhzECKFHfDuQqEAWD8Pj+wWvPz4irsfzrj8tGFg1sMlvC0ExNYJBSlUR4Y5cFcoHhDy9DBI0TeMjV/bht8iLP6atoc513yRVqNv6aRCU74NZTjvLYZczRQzN5DNl+zevwFmXEFZc6L4yCI7SdFc0f+gQPtwj79+trpHJ4QDm3FGrEkweEDcsc9w6McYk/c+UNVsN1gGEsiMJOIQqAqBsDtECCBu6DAH/1C13C1SSBlHGqToW9aqsJ24+EqL3rfK/HZG5KIgT2fBFHTizn1Ag/1LweiWJvLmTty3MHZ+7WpbJ8USsW1ZZ3Yqz+GwJsws3DSUqU5FDzNiODKlT6ezK0yeMdAaRAZWh64Z2wYQ43SyTJVNBJ1N2Y2+zRFEFH7UXasjjGwBMWg1mMHEJnEPgKNQDDcKDi8TQOlopsxot0yAcJBPR/dx3SKbm4jd+BXrqG4QtCxQMwjae8WxegI5WOF1MmO0OY8N3Bb0bop9b4tlfsId6N2c6NzY66cWZZ2BxlbrPLLhlod7NG4YssHyKF3pPAO00o0N4/vUz0CYO+OaCSFNuf4ZVqEEnF25X22sihKdqebgDNh22Ry+fQvo2wkxG/2KiDzLULCAg9ab1YXzLHluzWtaWt+CPkasrtVhrEM1GjmNFUCew3QU7A0glgUM+LRi5rzZPq3OOAJ2f9fvC5Wqk74jQ4T9V55rcPtMfxt5OFw8r6/OpgHPVoAtsfEfX2OfwOhbGGR27ZZVKD+a+yhmzRxf6s7v5oYeLTbI6+e86TyMfaia2ZZCChoWFAbnN7OeNDy7QcA6jaegmUnLvAQbdQHX4TB9HxKtk+dVI1btlI+jd4em1QZz+Q+oMhpbP2V4ZLKqOX9htdZj3ieTjrM2d2fKD2HU2+3d2Fj2HCbGcKkgy7mEgi4WIEfiEJfN1iyybgBAm1rtyMAeu2KVCpBadr1ft3dGenR0pTdh8I8zc7gHx+ejKhp+5otxFADE69UrURrWY66ypmy88/AedecjtxBKqdxrBloQpQMkZLP9XBx4Ptn8qk+CybtBc6jQJ8d9Oe7zI8k4kg+d6703hNB+vnB9bHF1NabxVZFG1uhvTPu8QYsDamZmw7MlVSPr2mddw2EIhAPI8z39+6Azmp/CZTqTKSOS298XWfoISHdNY7KogeBaFldH05Mhnby8JDGP+TrS2OwviqToc5dlHApc9L7F5Pmcu8AbTo9JcDSfg3BYqKJ3wzHui/3cLmvOjRLj8vximcWtFZlpPjMcsukYcuwcVQU8UxE+xyFfAe6UaQ0fvvsOjRnr6ytSOYv76zpDUen0biZ2xqJYE8Z4jgJbL95j2q1DvEdfFDoUWAB5FEOZEUn4fiUqAYqAyGXWMaa572e/i7zlfUqnVjkfIUPUVnn6boj1mnCKBVlC+SO+Z56BgAe6ZMGF5tTy6tk3+jHl9WP/MpiBAKUBagrmyABu/m4GscElgxiCU6G/r4As0BejfQJHXwmuciLoi0DPXnZtKLbLBmmC1hoEwDgJmMmyud0BpKrmhCaClUii2KWgCNICMju2MZI+GjKRyXZcSpKczyeM8QwmmDxPUUrDUYxUwWCclmWWcCFDJIDrJwIBiULByUNNXvSfqfxI3m/oLjHb6jWuvb+wAN1j8FXsJ3OgF2c4JkQ2qvNcKw+MmumS86D1fKMa0Scdyz2b5/9qIyFpFCidpEE/7VubjXDoAYq+LJBthWoYcBVQwfDa4CPkoGb6Ho8pI1BjLNQgDWBhCE8drHEDxp3JQgDomUBnQ+6w42wP2Z4t05/JILTp/iBzSdH9i4Mtgu13jA1hjyjO6hFIaTr1QGiSQCuHd2czTxe00wl4EQxeobBAI6MBHtjlx9UCITn3VXO60Mgdwd6bdGqKYDwL6M73nTB6IBgxQYeVxpMxEXBEhiEpienYiHf1hod373BaTojs+NeXV4xtoPcFr+tr6l5mOnKEMPHAsFL6A8FtPAN6ZjMPMDfoEHDvWSorApJszwqG68fw4K7Tu3e4vLzgdDqls57v7/Hy6TMSIj70TQ8mJy/TFjqz0t7eI34GIwBAKg9wWq8KQw9oHb3Pf613tG41x/kELJ8se/98OmNsK1rvBuHuurc4gtrrumIbAyqGnDUQ+8D61Jy7xUlKal32qPUxzgQAJUN08L0ixIa4hQFZvbQEaE9nHVlD/N0rAXc+XnEYdSjAYkhJo573giyWx4fI0SS9f7kLrljQ3Bt+78f//E/c/fCD0U+1fdf7gkvcnzYW2j2P8t+1rE9k+yFYQf/uO6wfP1oCkGraB9/5sKKObDRFxodloLwq8HQ9mJ/Rjm8oH31B1q4t7LSZiKRWe/uze8bfOY9+5wgTR4e3gx98Ubav7V2Zl8eit7zT/TrEe77XmXmu+Hrt8z9bq/sbAD7j9tJ9rR565b3X9pEqixbZ9HD/jG/f3x/6l9HTqUMer7ndr2/bGL/WCf+nb0d7y6FVHgNY0onU1Trcu5PFtOjmWr4pxkmGH2KaT1Y1RJejllcd7S/xmLfsY7cG8ZVdMYdCU/d849pvee2vacfH/9l26QySr7+TBZWl7sleBtZaokkdn0N/vvEf25/WgQ6dgiSAhAx783I3npEoKOpZszmaDLrJ1RA3qCTEVxGKFOHge3Ql8x0Ejxhbx8DHvCej9FP/rAYP+30X/aaawnIdhcAVx4BH+A3aLYb28xrtiMCUrw7PDMKqcchsbhowYaOrocSfFTXO0/kTxk6vG3dT3D3MWzV4bdkFO8T8/j4j521NCQ62hVcAJwrHVXlXKDipoB4EYxBUzRkp4fSnAQxAWNA0smnaXEedtfHyHcU5E3Owr/V+Y+w0o/mofBaugjAaaGYwVwK4n82wl1QneswclZWec1ykVF/B3PvHfr7FyX9Rs8PlJgNfF/8qp9PXizkjuu3ramauuaomyLXesJxOBg/qhh57lq+VDjR3CKXAoYq7uzsQEcYmvv6uDNM0bogbwpv3dwzb00PMqW8Zkuzzdzxnk+tTzDMwjZkAKty7ktUTB8yQ1RIqPZwHM6NCtRj1PKobbjSwpC2xvcuMFplAGrBslNdOp4RB+S19ATVCbw29Na83Z9nviJporRvjdQO6iGX0WHY2pwNm6d0MNJvv22DQlzJHrnwyZEJvkinZGrDZvjciYMAE+XKaFb7WYzJ+Is9GsHUQzzxftw3bumG9XLBtK7bNnAOWHRXnyfrfmkFs9oduUPYbXTkvtucV6HZtZNDJgfbvHeMB2WjrGdndRqLiXPi5zOOhCXkXpyAdRLXmpk8GxRlzg5pL0PZ+rQCx1+33FI5EBTpmFlMIcxz1AWPPgwBymHsBVEfy/tro6hcUPrVXAewMGr28XC4I5/nSDVoxMoWmvBLShP0d8P9h2yOYcQwtzngY2lw+UTL+gqDRAsKC1npm6CzdAnvMwWQNNImfAAAgAElEQVRmrwjeYLbzyF7rFUyZhcyDAXaKr5FlZNnnlk1uYyM3kFsmC6y+OizgRUEWDFT2oWWgdBAzRKzkgapCuGV2uKqiMUNbc/i/CLCxrA8E7yUz6OoGbF6fnSngOwvzCf65DRM8SGet7zBKqsHgRgBSc2hRUQKLQMcwuFlx6GU1emjMwpewnrU0eN7e/UEjv/S9et9jz4yE2bY+b5zEBc2dSY0nPY+xh3M3jLDApJvDs+xSUSWj570bpNvmO1RgMpmqmIGTyAM67SYuipJBkLeUkaKZs/4a4SJzEEZkXs6bgtbctt34+VEFPAOJMkqTr5z26muWWWqZER8BZB5EEGsZc1doYMx/7LeUOYr9YCJ+wEobANMgCMuS1mEOsXBu2GK4NNJ8TkKxVEBFsemGMYB1GE+irYEc9nmMzUsW7B2VNVugFYPHcdel2CTB94uYeRDZZhBVyITXzwttaYqFKbQAiHm2/dE70HvHsixoPWTjKRdfLhes6+oOCXE5R0C0OJow7eYx6WfIP71Dts3ntuc4Y/1CT5g6hpbB1zHFesy9MUQmSoj/P2QgLmeqtYZGVtJibAPK7tii1eQBPmUAHbwczLpt6fQZAW1d9mHK7Tt9QWegUuk3FSjjShN2BsaQJes/Mrlt6YvTSQ8CCKQvYnS2tes90Ewmn9u2Dc8vz4bK4/DIJj/P+QYA5Smr50QCYLKSHxFg2VvD0gz6mdsdmIbxCopAsXDQAoi61prHAlHzG0Tg1Rz/vTWwNrShVlddGV0UzAMbbWiN0Xr3oNqWDiwRhY41NB70Zg6rpS9oS597HQyiZs9pxsNF5jng1EuMn3VqwAYPKGUwO7LN8P22bVOGIIvXC35oSsMkmLEP5r7xgDsq+7nId1WnEhmBO1UkFVv/QFca7kBXACB1/cGyajeLsHMnu5WEqvDKzDz1GZ8r8n0z0cXFHfLx/ojamg68qRL5KHSWZInACBeocESr0VVA6BBYSYqh8PIUBOAEpdVkOlkxmKEviq1tWbZv8/1u+7uiRnm5HfIa9O8aoAPy5LLWvUKfYlzeV8ADDWIZgre409XlsOF6mdmKBK1AsdfgsNQRgomg8FGatIrvnDeud0az7hvGZZhTz3WBkIvgtLmiIEQmfgRkhlEh3h10chsDNExWWVzPMMWSQH3Wkh8e4MHcsJwXbK8vUBJsykk7TssJd+ez0QVip/GC18srhg68Xl6hQzCGo4NtmwU2ZxCc87hQXRiIsj5RfiHGMGSggUB0BrVXWwe9nk8oYTwJ+IPg6fkp5ezL4+e55UJWI8uY952CQQCNsZP5yNHIOO/xoGcPTgs2ZeULDbo9HOJj2/D8/IwxPuJyecWynLDogtY7vv/wHR7u77GuP5hjnBl35xN67xjbwGXb8PG/PuHp6RFPj094vjyb3ARGN6ZgJ1Mi2F/dCU+pYwFqfMz3NEggNKABzukT0lrDZTNe17mlXN6XbutQbBDJ4YjNsTw2LzUXck3MW0FxiLUJ6sIe3OLnakcL/GcG5YcNi2bQ7frpExq9h/7g5e/U+A9oWsbSJhbZdm6DYWZ/vzneOQInELTf3ts/fIfx00/zObG95lCu5C1g2pJvaxS5Aa9EmwjOBJzmlM/zd/8pHpiSokTcX+SIkPzSLqg2p42Ad6p49FGlDAivkV76JE6fHsm+a96/j18ZXTzrcYpeU17ChGxnIJ2FvxYL78/S3mMP2R776WtOdACFryHp/lFCritD5TwEz87d5HbpYwteZ/fMs7y/Rnc/d/f6L0cfxO/mRN8pTH4Sf693f7FVyvG1K6dulytabt+Vhyljq2wQ5fdbumGYZgwoVbOkX0yfABmQd3v2tMh89f+Yn39pc37lq2+bqX/RdkPvffMycl4aaxeB1MHHOqMvS/LjcbmY7uv7q4U9D0i5/8/a/rwOdCCFSf8DwNuCRhhXkj4Q8OOnRzycTxZJDc/yCXXTr22uxDDeW5Q4HkFuDmx4AgBcPv9k5IdqfR0XnvbsJWHCyTvVYO54qOIhah75e58IeCDCe5C/6Y05wDXDubrsjd9/dkvB1v++Ili3KVgac491n2lPhC0OwhUVrSwxjL32+c6pVN528p/hV5txFcZgHz8/QaA4k1oEqQInEF4wcMKcx5Oz+peo1R4KvAKEMNS4kO0CoyiDo3a6MAYLmsBh3sijrJGKsorVQjTnFXJfVriLFECKceTYMqsAs0/GqIpJjGKGr++N2bGpLxGBPt3z1VNMV4zifCxG5oPCnuv9m3EnP58O9zZ01gYklMz5ovAB8OzlUfpZWXxI3dMZOTbLJB4BHxiKnBokmhLh7nQH0QEQYVu3dL4YFKrNn5J6nXRzEKgoRC0Dfh1u6HNGFMb2ebQ0nWeAo2K6dT2WxznQngHW5RbyAnUAsvbydHbDjXf2iFDO7QbmuX/m9ZwOrHTEp5N3OtK5mVGltzAg9nTSt9aBcLqpAq15DT0GNSS8HBHQ7+4capPdqRbz5fOAzQWnDoVadlEkN6k5ioTYosdpGAynktWrdoE+jfG0h5Gq2V7hkFUmyy5xhXIbmzlA3dhtBsvmwqbanIPA3eaiS8fCC2ixmpmWseswhOHIC6NUlBih2ScgyIT9v7WOdN5FuL5aPfEqmITCq2NLQca+mM65NMIduEVVXsJPFUgdVy0P/o7K/2p94tbt9e1zvawFHyFuVjs3aCuHgy9du1CNmr97nhJ/TiqxH9O+I6aUW+aPoA+FNAGj5SUGex70cGZbyZDcB7nfODLMp0VA3egOhFnc1y6Chgho1LC0nrSoNctUDcQNIrJglKwt5QZfVugoGRJeFYU8eztqtoNgAYdipc5VmiNGWO3j0YbXrxSMbbjzNQxa81lhIBcSsLDLAQqUPU/lXIZiboEARisU6ggVlr3TmJ0mhEHezxfb+Qcz2H9qwj86wgjBrgNA3S4fIIgSdGwgNsenyChC5PxXnefVAFV5Y9LQdG7cEJ/qmdXJpSTgvr0urYxhMkWzjGRg0igAO1oS2evV2FgzyZxym0GaG5QVzJoOvISvVzFautv2AQWqUDU4/yolTPnvIK8pANJEMhHnszWbIWjNVdbtQRaKYCNA88zOHgZ9c4dA9r/AQAOOMjJjpdXlvGSkas8QyT/LeFKr9/XS7F/sQyhmjVWolxryv4Ivq9EQVgI1z7YC3Pmos35rA5aTBcIscrK5bx0K4PL67H0tMkFMV9GX+rLkBlRRrOMC1YA5B4LahdHEggk9CIbIEHh2KzrXjuCZ50S4vLzmPjenxJbrQEpY2ALjzAnToBdgrBcoz6xBGXZOG4x+yxhgd2CFjKROMywIzPsUAWHbyPfbHIQjYu9QtvrGczw2bzPwIg0CHnQFdCguOT6C13v1/CujVQPKNrf2fpM9eu+2991BDDhCiziaQOyxSg+CHqJSlbnX02mqs79xRr9kpKj0yX8xWtk6uDdgEKgE+gZ6yXKyesThRI8mYnD622YQ5CKCTS0DVypiEk3nXAa4ekZn42ZzxJQO9N4auJ3TsRzn0Pw0ry5X25wxNZBeIKETILa18baF7iEy0B4WaHMEhKbYsFm/BkO15ZmwbE87/wabHnDKgCyKM1MGDwXtiNrEQR+HiJdO4QyavFw2Q0Mqy6PqgV5OVpSANdGNZjBzZm3C5WO2jRMZQqqwdfR+KiY8u7jDliOw3bPm42yGmzrIiDjtMWQBO49uCvDt0qAk0GHEJgI1Y98TBQy/bSKygvEQMXm1yo3qKGGxN+1Zc6/GeZ0bODKNB3Tb8157lwciOEpFA6Dq0W/BrwYsoBIK4MX2gBJATxgCyOf7GdBHjNP7xeS5cMierTyMCLn+B/BQjMeR2eAkBDxbf9udB/g+WTACP9keoQc1XulbQh0VcV03O3u8DxDTyihRZMgr0XxSqdhspmcYQg9eLdiw3xlfGM9GM9sSyhQlIhsBnrnsGCrJvxnkaDfx3/Zs+3ahxa5TSnUUavqwNq9B/iLAMrt4eniHy/MF3DnlDNvqVgKh9w5RwUXM2tOYceoLNt28xvisk208kdy2YrTaZCIvccFkJctGTmqeZeE1eozlnUH6D3k2GfEp6NAr1sdXEO4geE77U9DfECME8ECBeyi/IpytQ+uamI5tZXqaJ+EHjZyB3gIPBuTpbDc6oZDxjHXb8PBBgIugtwV9WdB7w92d9UGJcH9/h+V0goridV1tP24bXl9fwRdKcx4VZ3EEEWT8AUz2tCRj8s8pdbDgtfB3Agwhxgaj3YPMEG1IdR0WJsjY1EJ/CTNLcRXFKoIWiBRqc1d3dpx/o10hk0x9Z5eUAsr/q8//tAewZ4kbrxJ6xvbxBaAPuPs/76FgjI8fbUy7Mzllr3hO6J7swa6BWDQ+CkiB9gNnslb0MWw85nCyHoY9M0772J3okrHutPuxZONXkpBjvWEjuPV3yMRlkLhuoWOYHNvoAxSf0HyNH4I3wzK/HxSIEBNWQIjwKfabjzH+xuF1Mc5Hp5M/+PfvdX/5oy/NdzrNYALFdbHVP3fLtX1bzMM7zGCLmWrw7e0oQ9ZkMP9gr3c473d1InXfW/toZ+k/nqXry6/239F5/ns0usVm8cbR+L3bVzqRx6oIVtPmT9jDyJqOeD43vF7WIoPVPYAUOzJBQS0HhD3YO+V+NoSazqZnKGaAcNik770rV4gaqVDT/veq+4etKBRvxX5Pfusc/gbtSL708PkfqdHXOuV8joln0DeMt+79j+T6BNLus0PUc7vTH+GY/Nr253ag/4IWIkqcvcaMpTesm3o9Mszvy30Dn1Hj/QE3buG6fsOX8/KAVyjeuSAsCrwDZXRetM+FLv0rbLRoRQWwvyfvdSIaB29q52kQQqp+X5yUnRANIOAdj+0MN0JgQg7VZ+z7fPu7W9/nZ6q7eIJJTNUi9D2aP5xxaeW4OSjdzcXXmiLm81eQ6lsD+0fe943t+tHlZIamWhxVtm+mInB8Uhjue2+ZoTcN7kVIdOWPHFb3dX3NTE5ubIZWV+aGWDmHgBSdO83W/XVsOQ6TWSJjbL4ukBOi0yFkxF+Fg+3XWf1abmasiUyBMIKEYIEweiuIAj3AjWiHzHLE2SQKPxOm83zvlI+s+Mgkj6h+CkMhG5U0h30YXMrgAXewx/OwO0dfavXcz2AOuXF+p2CVBvfdj3AmAlHHmpnBasZjHWL14jIrk7yshxkLd9n+bJl2nS37nN0Y8dYAdlkkdVC3Lo9akjfmYD7Q5uKKdqjevOPrrXLCnycS/lZk4VquTg3N/o79iJgdN03IdqVsfS34bLbbhM34uLoh2ZEV3BFco/ZBlEgEjds0RB+khfkWuvpk/1s+1j5ROESqgBxWFDoQ1mfaUY8ZMOFqzU4orhnLFe1CoWBGZgu9e//BjG0eKigZCYbslAUNuUG9ebRqa1BqUEgGWdVsZlO86eosZNAO5Gol8hy7MqhefqV86fa8abDPrG01ONKoO6xk9W6VLSCmw2BdmWBQ+odWjVGph15fduivpvxIZc7reIMHSTOeE3MU14sqKJw5NPeLU/c0fJIHD1Qn27GuelyTwUI+mOHQlSpGk3mHXnHr/OvXfv3mdivzgCK6Y/fGgn5T6EBdiT3fC7STCR1b+cBbhpEh4QRyKpL/uyUBHsahlGg4AtubMz5umCPjhlUmpVeKsgFzDWdt10kHfDsf+rGn1zmvMunAzimbz7qWIDX31+HTQueuvy3P4uaZi3bNGBaUQkMgr5bdhuYBZS5TQAOWWcBQjGEBG1OG8fdIgQK2gWY5+8iyD5j55IkUmTFzXEEjsg6xI+PMc0XAHSAvZx/pq/OaqUkQLu4gnBSbaSJZyTBTbpRu0nAoOU1OeqhqaNtXs3pYriujInJT1NWvtdLhP6ujIGhBa1ZiprFDerNlW/fFsq3Dcc5t8jqrRyyJIhCQ3epw39lfms7lef6M9o4xwEzoCdVOrh9O+q0ZbO7Op1hbv2bBgDjSzP4EEFgII+b8eUAYWO4GRmvpiGq9YUChq6CdOy4Xe8oQhTo8/W5vikB0YEiDqDmmcy7UdT1RKA1Y7Eme6jRiyvCAzMs6s7vhSEPQcu59LZ0OCXnpCEWiYs1NoOlkccZoukbqk/Zx1P8Wq32C1AlADtWuWXZAMqgKSfqYZNKSGB3H++z8JGIXmZ406TFyLbU8dy/TllWMs4s4q17iQhVRLsPqvM/nA9YHsGIoAVjdoavXZUb8fbGnc3/SlKVTH5zLYvPQCBALpJCXcmgVWfYPStAXBd0T2juCPjHonpKXRECW7fUyGQoYurpa0I3rZcG34tySBiXX+fKUgjWhsQF1NAAAdwR9DthsD/q9m/oPO+0WhG7HHtyCOU9Hnuf74fRuSYQK5ukgjtGKKLQgiYlHqRGA88Mpg7rCGT5kgIbJAcODWeKcde4QFnRq2HRznU0scJXhMN4ux/lBmtgBIeOaeEFqiBGsw3XXIofibGfcy3fMPfxy2LdAw/1uHwJxdqfsyYcrlLxfrlNk8HjIxDDbIbscJ6oY2/DnLVDdACG8nl9BsMDWjR2APc47E7a1eYAP4HXbUiYO1AMK2R3Icxa0Ouwd9QSRKUIWqEJkpclaM37SmgUeeKAUyJztWSed2ejZGHmugv6IB7PdKudwLXFYa2Udcn/5ufmSQHrMtk15hwDhR/z0f59wR99N/SiuD+Gfpk6qFJnUe/ncaN0nLPiQumPMZ9iQo4t1fxwDSJFPnaf9mYD7vP5w0T+wxfvt36eES4+Salqm/dEvfhf8rDzn3S/oZz3H+XyYUz0CPaRc99+tPQL44Z/diX+3P3R7i44yEy6O5pXXTpFl6ov+b9SLkiL4RYoSznTdg6oCV9tWUJdb9rqwTf2Dydu/G4A3mUjRqUeU5AEQSY1hU/92e+sfv/25HejTNpYfzAO3X+Sq5ESGkwnvgvPS0VvDp6fnfORAMN0HKJ4BAB0fsOHTQS1xvUZdULi2QX2xfSbFWcyJXklNNIY5d58P913JT96ZnaERt7d6JTQ/dyuHEPk2obol2pb+qGcMkClzIUSTYfmBCwwxIPa5311rBs0F3b/v9UaPGoAnFShFhroZ11YAJ5QMMSBror6Q4EEJdyA8U5mv8trdfWECUIAoYHZN41Xs9G0ApgyONOZNg8TN9ZqWgjI3uyvyc6ovqQyuPGfncEFEbs11iueTG2j2xtgCv6g6r3Gle5dCXcd9Q+C/1XTPMbPN7Bj70cLAf1DbM7Ml0qqzH9NgI8dnA+70ZK9hZgaKyAQJ6MQhG5a+gKlhOZ3RSPC6maggw2F9s37vPiMwxqAKh/rGbjP5NF4xF/FamOelW53tkoW+Ixg3DrJBeo6c+8jaCkYXwk3WIAMBrGZkYFfcY1/D+h7w5GEknxHz0ff5GXPL9VAotk3Qm2WeDTKCaRDXYS7BvJcM4o8dwm4bW76jboXj8PVi0pnex36EQzG6UUaLkEUwAwEI7Oc1BEDjEQy6Y9BG05ArZjwnh/3LrBSxqHpiTSMREBkCbnh253nUysyV1/zDjQTTGCn1y8NCq4pnArqirhPmMvic5oOB9CSU58XlM9L8cGZyb+aTPJvfa2CXo1S3rpY61nVvRumM+o64uZC4n98KXyAgszJmusuMgox+VANuyAPxR9J0AhJ4jAh7EZ3mc6EJOduaQxT5gFRmvdvmATfEZBlP7jAJo1gYyqdR1J9RDN41epyjGzqzvjd3QESNRVUA7vxpbFCirDxRVWDfkwAU5Rw8ky0MrGb8Bc7nO6gq2kmdll1wOp2sXyLgQQY17RDtQxWCFbwRNiZ0sme11qGsiMR7o01zHqJuJEWtVw2HhZ89NChm5jKY02Gu8J/lWerZ4xb8FARkBr2E7NSIIQx0BgYDus49BQpkgz1UZBjXZ7aOrWvd57Q/HHafZ8MbJOs01MN35Qzg8nrtROUzf5SIJ02ZI6UqtZRGTECFvOTtDH4RiaBRyczEoO8EtXnLjF4DMzGo4RlEBdD+HKWwEUM90pUDP9x94mP2yxT1GTYPtgfCYTwdQLt59jGGkdfmksqzpnwpwin/VLjC7MShRYZrpZ23pLZbeohGkBo8SxHktYspjdHdr4mo/JhZs8uSnVNumdmt7jgM+tC6pfA5Fk5myjZiqIwy/lB0N3cyuoNESiR/0Msqp7gzo3eDqt7WFcc2gwZh2W1qcOzkxnRVpEFd1ZySIhv01R10QTvEzzF5dqBPtdHSYTC0RLHB8/vouugMEpnOOd/PsWe9JIY4nyIKeV0hzw5rr9YPc0QS6H4a/WVXmuAMxSv2Mmk44WdAV3RQVSxjNrJgQy4DnAazn2uUp5WmLnWrXu3AK5FwL9RPQ4b3KZzV8Z1BVbOjlUSA6ayxuyxLOkQATCeWFOjkMQw+2T8nLFCsTv+b1ejlmaEN1UR8soxwD8x0iUyh4BMBdMJ4fc1xhcwU2evmBOoALX7OVgALiDYQLU4Hh+nr2wrmgfFEXl/dHOinZYF4sNsYgn7XoKtCO829A0YioahAxsDm4xsYuKwrLpdXXC4X799wXmooVASg9QWyWfrzEMV6Wb1esMne4ueXWjNasW1TjItMZTXaPGWbuVH2vqJZGzyC1lLv9HJS4UQ3x6NROXU5OWGwZco8ERRr+qydtdAxspsh15YAiqF2xtWDjmPvJ/dj16U09nLwrBq8FXKcAJtf6Inl8Lm2PR28o8wLOkQurhtoiMPl1HgANbcyz545TpHB73PyArQHNmhnmnSeHwjy2fZVe2f3r4+ac6hPT1CcbR2e7H38EHwr3iN5Jn0CoBnB7Auc/Z4oQ8wWnJh8I9di8k4i53nuDG8PJoORKnBna8ktga2hKoZslNCrdi5FxYJsmNIJCzX98f67O8xyYcavtjGwtJb7WFXR7xgihlqhrvNaWSaFNsWynMxxzmS/b6ufOcH9wzuADAVhiAXRrI4IFzDfMgZk8LTc+9TlPiYPLNIZOJj0xSePQBjjBUSK9WkGLpTjtvst9zqesDw8ZCme9nCP7fkFRC3vUCIM9e2raogfveUzkg7mug3IunmZOJtf8QwgkYEuwCZAuzAu+ppBu7HuQweoMXo/gbsAvi54INDnGWxPMo3gA4A6nQ9EJ1IEBMiUk31yCeasVvJsenekiw6nDyVw03Wmh7/8BTIGnv7+IwiEVycgWdLEz3WUL0g+52rmu+9/gJLbb/z7z3/9r53tLZy62dUyx/Ez5cs4YyG3MUOJ0QgY/Jhl84JGRWBvOtU9wUDDboKQ5ayZHfIj9G/vgQ815Eezb83pu8mJSFmPinybYyny2lMZ23zk9f78LVskfn2nVgaqA+j4DpIg7N9h1R/xvQZfcHLh43rw7n3GXs9JJ7uarf0nX8/qaA/yL7DMdQLwQS0L1gFGrvr5R2/f3M0by/rB7yf//RNwo5DWn6O9ZRc6Sr7famf+te1Psn2uWszOpHlFtwzR1mUAk3CRfD549ZfIiJUyROrx596hEFxWyfdBzYYzFNBmdHqTgTtHvyUivHoHDdXEdSDXU+tojvbymWhhf0uM51ZfD3Pye7ff9r1FuP3Nnni0d8YXb+/+CIg0u9z+WcekB+D3O6//qPbndqDDjWlFgchv6G2iW1f2dd2w9DMIivvTCZ9fXkCwLPF7EAKEveE92gfG9inevD+Ax+i3r7UQ/N4rYXOycAtW5QSgf0e7QjHprPwFbQpo/5w2HSaT+RkC2TSWzTYPMPl1EZVbnvjF973YS1M5r3HSvdxdUQRCwn0iQwp4UMLTjcMf4wkYM4SRG+4ockjOOlYA6VAJaMqIxt2pYt9ID2uWKvnfYRDeXxfPnrB8hyfVGfjqO29FEd3el4qAhf8t2teZXqXaMyglCHq1kdvVdpLNB8Op3NTnTyOhQ5g1M7oLom7rjO7fKXQUypimAUbG8EyJQ5+/sNYqBmm59I7H50sZ5dvRXAbhLXh4eIe+dLy+GCxh1MyF2jgyg1lt/QLuMR2RITxRzR6Aw8rNTASAprMtHMgBz4np6BOFO44o1wVQtO5GAMzJj/mLMVb49iMdO05fPUsqc2xVLLB+GeUVuDEAM2QgGQhHnb+GpubUbs0hOXvDkAYWtcxMV957L1nrzF4nsyX8TWbC3Vo7uEPOJMargI+raw8zkI7zoKka62gOzXRSYe71W2cjrjhm8NvbBo7b+E268JbyU79QzXqov7hlbeNiAArDR7wDmnvdxkHl/3N0k5JVQ43mnok9bazLjKlRi7r1njWpI2tGoV4nKOqxEwYGhgzvF/I9CIXmuMudv+zmsMilqmYE27YNzLD6rp49OERwWk45siwx4WtGSgDDMskFaYQCgNfnFxAT7u7uPDPOM7uJsCwLluWEbQjGunkWnxnELNvK9ts2BmgzeNx2ak5S/L0+yzUTEb5GoYwF0yKnMyh7Lb43h3Bk6JDPFzIzjZ325B4NZatoWNTgwQX+7O5BMwSQEIQMMUCG+NrBDGQeMJIyXBi6Du0qyzzqgRLtvou+KRRR7/rWyYhnSPIZQricHCjfIdPMKFvPgxlIB6Y3vO41pMIs4eiAG5qX7gFH12fbnCKHsd7o8wwWcPi2N/nY7mQAAJiaw2xqBqJkcAVVGHLsnlsz0MNxziywTOYC9SpH/hw9iNr2s09VrqptbjE9fFgN9L5PSTE8+MqCM6p2EfRH5/uHJN/MzF6XobNnHggaDmOCzD0X/dZSiijnys9E0pQYm/XtMCE3W5RmmKWIyp4jAncLrLNHqpUVUUBYMZ7WiQJR+ZR3wXdLIi+E7C2i+/1Wz5L/Pb+d6xW8QF8EfD8DjuTFa7bh4qOPuxejDyp51uxpdzCt0Z9bBVVVQ9RByDHulEoaN4M6U9Zxx9XYth1P3NMUynEd6UN81gqqx7zNeSSQCBXBr+C8M2WWkjlYHeg1c3yI8Zz4N7aBdV1xWS8Ym2DuyhWtWbB68+e0bk5qUmTGugzLuM5x09Qfst65TAeszd9IBN9ABCYAACAASURBVCijJ4HKAeNDsBI+TGPSe4cQD4QkphUzyGOgtcXngSHcLeuVw6k/12IMAWB1eYlHzuW6XswhHsEEQ8G6AczJ9wHCum6W1a6CbR0e0OJOZdJZe14VCoMHj9ITqjPYb1KMSZuT5OX+neeCdJ6xSdFcPvZsfjCVtVHTXRFBO5PXxd3qH5r9hZxGx0JQXqOHUxXdjH6QlO80dNvKP03eAZHXOrd7I5t8J8spcr9LjP0E8OVkTvQwFmnw23reHP49ZkY9K1+Nvo1nQXvgIHF+hsI5yEZTtO5LWx9iguIBwLM/886zgjnL18U4JilxGhzPE905hKvmekuqjTmM2gBadKt6e+U8hJkZq+TlJsjocJT14dyLZW8RZT3TODOB1DUdjlzWWPO+pS/YxublZKwPLYO/Dd3t7uEdXp6fTNZtHdu6YV3XRD7rSwPxGdu2gkDYeLPAruHoLyF/yEFGKeUUduNxfhrBUOqTmfsV+5Z6FQDGvctggvWzVR1OOZ5gPB9TvzDdgGbQJJAIctwMeWDbYGUxQCBqM8PZz4WCoYs6/1DQxhiNs273EDF5n3vy/Tjf5O9rvl4RuBklVVRSwLsac/xTH6PZATy7PJ85A801EUamLK8KbJ5UgpA/dWagT2NSyFDWlnfv0U/LFdrJ+//5v/D4t/+ap4Fg8itmZlwMIJz6/oc7yEuCQKDu+Z5uFJDsIYJN3XA60Q3NagbOT54NOIKKfkLDd7v5bOo0Dd9B9COyElk5s1R0wviU9UjD3hDUfkXbU5brFnrpgKLhI4APYBDofxD0r99j4Ce0v3yP9W8Dio/YvI+PdWm9vdeyp7B3Asfny1/+Avz97zn373Q6N6o0fXj0f5vGMCf6v0R7Yz/vgpX/AXv+X7Vdqd5av4uEBcYm44tnJ3QaFF1k2zYPzqfDOQw5Coja2QJyk7HzsexMWjRvvXHHg6tUWfXZ43j/2dvjj747b5g/dq3KpZN32/9UPVgx5MvgR7lQNB/yJ29/XAf6W5Ipyud+Dd1guvHFrKN46wJTDk6nBU9PL3tjAxGeAbAadLvgM14/TUElnhQQnEfbEsFrm7/RnqC4874zgM8ujD/4gO8UeCF7/uWj4gdiDACfHcLrKvJqUpzy2dfb16b5zeu/9YbsVxjenRQWy50JPXtHUMY9UxBX8c+bE+mo3fEW9S9qpxeXPsPmNIRjaAZaF0MCpZINIjxGaIQUBRR1vopBNJQqtU9zbwAZyZowd2NAxoahgvVQ/3NPdCTnbXIoH1kaB69nIPq6y4XReO5eEM8xUb07l628QPO6vRFcC02UdETOKVLo8YC80Wq9ydmnN66jW1ne5bXZ2Tmn8XmdMiKrkR5KoimomwkOHrERNdc2r/25rZuP3wESiZKDR332ULoyYlwFmwwgDCHel85A6wwUCESDknSFrndsKsAq6I2mwpSJCGXf0BwTAFzWi9Wg6x2i5shqgEHPk9W5tHqVK6yccDgiLPsimWRCunu9RFfoQXsnenzeHf6TaXaGiM1XQ3XDmQMjICTDwNOaPXPbBrgNtFhnV25TUHJFTRFZ/Ys9W3VmhCJEMIOjpBDUoBjPZoTgO+tTY68pqQVi7kxQIZCaE70roIuioUOG12NTgXrenxmILTu9da8X6sbYmIvI4tnt3RMZrGtgt+k841LOukGBxtgUSGOm7TuVWDvPXyctzvF4cMi60zkejohdKw4UrecnuzNpgxkY42Fxu1P1wzmujg0ACd1y5GtvtSu+VWhnrQsIxPlTp0Pu7O4Otbut863ViUGYcNe2EGlYCSepzm9nPwJ5gGbd0+ngip07gzR0eHYFxdw6vxNBBOfsxqnBsODX2S+DFOs2wG1L2tUbIGIKTGRKAJYNNllJ0FGvY93UgltSbtKZIeiODFKf0zFwvn/AaTkDF6vzS2OgLQ1NLFNJxjCjuxg0swXxNPBCuWaqFrHavK4mM9uchPEMwWMiUK0GR/i0eN1dBaBDIA1oYtnkLGryA0dd2bnH/HFTlvSxswDgZvCdnllm7zdnOdMANkU6ztWhU8MZppoRKdNxWfZu1eD0sOvL9TuZIPcmFd6LnCcjp5oO+XpfzLFi8kvL1jCqsUU/Ay4TDnfoGU3mnBKAFb0RwC3nbHeWk67o/rv96F1+YJQVLDRlrs3+Hv8018IWL3/3sQU0eFmCcn/saYeBLsF9M1DDNn9dA5ta4/fViTP7t+/1fOZ8uYkFBic7++TZiiQ41gZQjb3j6zdGZrHN4JI4J9g9M7siEZxrAZvZW9Vdr2PhKAXHmEPPjPTstbGJ24QZx5WNuco5I8JYDb0nDPe1PIACud+Gy8Pb6ubRzZ6x3IVzBn7uZgma4F/xM+c++CbFms5VCptKGNhjbenO19uhvemOEOi81tsFiguAC+R5AVLeqOvu1Dt58wwOaTAndToVQgaPvlYhnL1fqpZtWrJu1eXY43rHfFL5O4M3y9oQkFnDxCWgqzi5Mivwxr/kIQVOeds2bKs70Ic50CP7XH0eAnmlefZ6X6YjvjFn9jjJAukD29OLO8lPgF4AXZK2A2aYy7MRTl3RzJy5YAWwJs8ymbwlUojSMNoBgBwBIOlis7rNnYehJNwv0M0Cq3gNZCd77iYDRAPD0V5AEXzQcLlcDJJ9GxiyGV3dBK11AOaMe329YGwXz9wPp5Fpw0Oj1jthvazG4wLd4UBXVZF9yrMMZGS/qvH1MaT6CJG6EWDZi3GfZ04Gst6OWiicL1s2oB80k4sImAFAQUc8QAPAeoQBxR5S2aunJ+0fDp0fetkMkknCOuUDBshKhbuTRaf9ZxhCS5RzWy8vKa8W9u/6eoQRIHkxl7cSHKmDFXQX4zBDMykhzMxBJ6NYvA6gv+sYTwK6t3tE30OhWD9te3nG/1kgkexoetIMzAz1HIQTuRElyIBSWxmTrgejRlAun2+xABOyQ5PrB0xdm/w5KWuDdzapCFKMmunwsieyc0TG/FgPqgOdPSuNmbFe1uTvp7sz1nVF7x2veEHvC+i+YXVEN5GB3hqIW9pZzuc7bGwoKc94hnLDkJHzJpRiS6yaDTkMN05oo+SKvNhfOd1pN5r0t+4nQIGHOe8zGDrDqQCS3FkW8KPJI5tvUGICc89AbihhdEE7dZxOi+nyxFDqGLKBYbq2qJWMaM2DXzwAfh2OhtH6zmaioqAHAj8xmO/ReGATSWCHUXhVOChCPwJdIwoJmdM8PiOEbYOxsWdmw9AgzyL49Le/pa4gY+AvH77DX3/60ffd1BkuUCzYk8HYj8oEWfcw73c//IBtE6yffpqoXb4Go9yf4adpB9nbcSw5oE2ELyIIMxZMeSniLxuRj89oQ86PVvpV29T1mgLAd1B8THl3YMZ37CROn3uB1wRXpGO9rsWVnvErWzw75Y7D90rzjCg+mpz61xkQcfnxR+PHKuhOA97BssM/2I2zvBWAju+x4sd8fkCzVwkMMH41sRvs748hj/9GY/9Htzq3t9oH/+LTF56h/r0C+B42J7HXP7910x+paZUE5mfA9fl5W9/8b9606D37jwEYHwCAU+sI0p4OaMxkqNA7d2c+9KuwahHN5DAN9VMRMIMpb5HJjUKEMwNEZi9VhZeHI0cTzHBOT1rRXd+j2etC6ZqBtzsfRR2/Rt/n/d/SbtG4r7Vbfb31+a9tdTy/Rbs90+VL3yd85DEAxlDAy5uGDl79W/9K7Y/rQP8ljZCOxitCmod6fwxOvZvzvHEamG48FlSg3OMJXztQd6BDRaR9e4ZOhzkIz0VBA4AHNQE/hNf2xnP+se2XkI23m+5+mYL49XpNIpjdwDyMv+Slt+Dd7Zl7IkoA7lz6e2X7/QW6uy66v8+Rt/x2Vcp6aXFFGkE9snaIZZ6P4TVwXWHVorAeh0D4diK5NwLEfXv1Zs7lUe3xv9OY/Na8vZWJfniaXjPwb21v3ktIRScyC/b3mbOAMRlqwLXp4TlAKF92wgw20QUD4jS2VsO5mLcZiRAY1xcKY06LgahxyGSBIRmxrIqleY0wd0Jb9g2hsdcKNskEDQTuPSEut4BiKP2fQ3IFEOZM3XTDkGGZ0V7ncSphAmjD+XSPbVzcMApkffN8qGfeuKO81rSLTPRQNBX2efN3Wf80+zSNM9ZXdsGLocUpYn1gLgaiGGcIhVsesd2mSxHbpbwQwKoCGWdW4wxr2TfE85wF43elH2pOxoZmBone0b0MQzyrdc/aYkZf2szkclg522MomZ1139oOzczl8g9OQ3IuEMqpDT4cXxp2hpSc3UhzZXS1+6ZgejjrbxCbmgRQz/rxrB7p6rz/RjZtMfr/0pYGDw/cCKQFP0KZYaGx+b/WNPbs8fKYt3zzjVtjza5fFPRERGctwP1IYPv3DV5XJ5rimbZn1jHQ3IEONPQmEOVSWsYdM2Xhgv9mlGgYmuOHv4tBEJpzaHWBGb03bIMxxBwHIh3LoqBtgzInvG/ASdu+FbTek44KBNgC2tnE0jG2VLpyTst+fWvOiZtBWXKg2mhm0dU24Q9pv1mndugwzQIeZuyDw94LKZo2c6rCINYjS4+jXmQYkDH5Qazf1xT9XPfysyJwWDDAfEbOCc0M0syUyYsoHREA3NBvvIi8zyriQTwB3257xSCYNbwpc56CdsT9h/UoHSzHRPN7CzJ02anu0cON9VnN53UaOOs/yxiyNmtoHw0sNg3Xzybgam3SSK6xB+soarstC2WLjMHiLIhXiRspmhsNERmfhAlRHbzAnxzBM7O7hZ9MIcSeIfXUzN/DIZIk5WcIa7eusqy+OWfzRfO8WXmWyPiP0hOrQbkHjZjeFfubCYSGSrx1Nx/maAp+D+CKtxoDjUz4GP+cv53M+hKzHP+7lN+vYeuznyHv+NOylIsHMcF/RkBg0izTEsrOp10AYB1JuG/248dNfpNju7WmrmqkyuH/wiEZsNukBHJ4ZRHBuq5JzwOuPbKsq7zC7qDvzTPXl47el8w8T2ec909EoAzwNkucAJcciDnsnR45etcMMDG0E8l5eXFeYPPcYPIvWNxGEPNbhZQVoAVDCbytGF7vHVDgBCynJR2DbBWGALV6f2Ns2EZkuhv0/bYNd6CvPnfqELxbLkHMXyCaEAhgcypYdry7YxOeHnlG987kOZe7YK1CGyATzaR+PNESkhuClUAqkJIdCvi1dGABdb/NBU3904475fUHajvvrb+Q7qoy5Fr5+k57QLlThp+hXk7RnvaHLBjzFrcrIri/Ih/Y/6pzWCJQhyiRT2JdQreZgczudIPLEMxQJdC76XB2bQk5O0RuLA5IfBv81CF57lcRC2SrjcjLwfhsWTZAZnnNGd/Tgxp0Y13n/Jt9PDEz+SzeabsIOSpKhWWglKrrjz4nHrTDjuxm8P8DXh4e4nQGUJzv7xAB6K/PLybPieB8PuN8PtsMOgQ/EeHx8TPevXtvMqUGlKgFMd+f7nBZLyACXmVkoPK01ZTN4WsaCf+xX0xGDh4T+uqOzZW1sP/J8zMumNfsAnDJ6blOrizQWT4BLg8QWTZ+0NTFAsVP5xPu7u7QwGh0thJO27Ca04v1esrQmvLotm0QKLqXViF/RziuAeD80CCfGZ0teafBnB7sMuU+KFdTtoyxDSBRj5gs23yIAFHCw53om1/3MgzVDEPAIjiL4vWnCz7QO6z0hGeYwTqCQy6qZsAOHgDg9fWym0ffcY78prj74QcQFK8/Tkfs93/5X/j497/aPOi0T8T4IvCdQFZWpJmMGYFnGaiNVJtyrVuWO5i7YwYjBa8K3j2dVJF80/4/e2+65raRtIm+EQmQVZK8qL855/6vb85zLNmyVEUiM2J+xJIBkKXFcnfbPZ3dcpEEkMglMvbl7U8Y72ZZwOoQW8WVey3GsTMivXTzd7Ta7fEVw39k3d8P+I1Oz0l/wAqF6G/4qfBjkZLdcrz8mgbzN4cz198JCB7ZjsMZ+w9sASOfa9VIXteDgMx18NufP7R/XntBZv6v0fzPagEds2X5FZctdnJIsGEUuGn+Vvmvnc4Wtl+dGVNKN+hkAsYUZvzPl/e23nHvzE8bx/H3F0Hqv+2LrSL0Iy9pskvKKc7X3rn1b9/++gb0u5zpfeXNTjygW8UYdgfJerhsG4YIHtYFjYxZ7ENSAOkwIs5eUUaxT/d9NGonkrgZI/nzt+KL3vmchieNlEqlp8PcvqW9JPh++Ql/9zc/f3xoMo8h0oWgYPe4Z7/WGgpkDBgRMqoyuizM1udGqBnN58yoR5Q/x744EXglik+Rgg0AxBwdgkG+xyjWzyb8aOohRcX2UmZKqojIG8MEx+FCp0W9FYWCSwUaAnHWfTpCVxAbTGIXyosb8lLWLAgeuZ9X/l5mdHhVOAMEYZxj0+yzviNqzNLOV/T2vhDK87XZ350UlIAJsQSL+Csd2v0BT1qMJhEZWCKVqnHCvaXCyD7GwHk9eeq0xQRxNcXW8DRwDItK40Igwihgkb0TjtTf09zj+3Q6mdKsX7OWFYOsbpvfH0pIkEUUQDlTsBMJpi7HgZeRKZE55xXCnSG0MQba6QQmxvl8AhTowyJkGq9gVkt7x2GMmIQvnAw4jeic94TxAlAz/rcGbsWjGwFnsfyuNnLhc1lNsSzDgGtpq6W9CwUQlTUGINs2hcrsE4h6l+Ni+KW9cvOMRxutHsEzhhnC9OwPP9mqdyIwKdpjgwOEreNDgz6bgByV63QI1tUcEBRLwuzi2Qosa0HztKUWPZBKX5l1AXfKbffIVt0b0ScM4ZBeN+YddTinncYUPJxrLzKf2fOpoeja/Tj7LunwtL67HNnE5QcCoznYeI/uO/rT2nTO2MU72Oa7YceV7yqg/gzQYvT1wExEhCMRJxOYDAEKUzjfshuFKqbHrp+N5qkXlczIJZtAanrbXJ+KxyRrfOeyJnnb8zFGYgTqynweDGG1CGxM5T8Q0WMKHZrpuXL8idMzoWSdXBrUCch6sarICBjL0GAOK0yc1Hp4JDqg2HwpeYyMarSIVks52ZYFvJygz6Fgpmk3o4Bld3KiWIupZBY3+EwFr29joZOAWkRUqCF8fyOybirlgg4ZLWa2qGUWW99IBSkiniJ0eC1KAWV0rFMjmWc75h3OOVUxViW7iT+pfCsSqwNPKP7SwEMwI7t/V8Wsk+uLyerZKqhGVInTg1lXeF9CwuYvaRChYpy9E3F/ZG6pOIaoRYFLZP1Adegrj5UyIwGjcT4IHgVH7N7ydS0nvTgaEENxeTz7VP5rH2si3DgPx0ndtp3hyrvUekGTE3W21LKYyBAIDY8Sjggcj3xSz1CS3QSX46tfDca7EOW4d1LMZKsOfFucgzAWGE6d6b3bYjR+9LFfpzLXCfOE08MZUODp6QkKweJ4KNOyemYDZqvRPlbfq23ymAzsaCECfsrcfZPdqWRGfu+MZ0Tg5vCqlf9To+3nyavxA0GeqyHj/laHkRCY/U0DHGXt2YDRJSLxo8QHfD5hUBONU2T0KrazACpBIwtz/qtndE+bw0Ei9jnGNv8YbbQMHUHpaQx07gaaQzC4RBSIR56XqHMZUTOaEp9HeY9lXbAuK06nk5U3aS33UtwIPx2srlBZ0hgf540fzOh4+bjZOQED2lFxTRqGlaxWrgZeZEspIgQFg5vJI3xi6MVpBjYn7QrLVzLxQyerB99kMX6GFJ6X3EtwdZMJxPCmRdQPN6wP9G1DH+5I6/t2Pp+NTxjdI8/NKVdhzrImqoglpRCL/FQoWsSDq8s5hc+o7hfzTOzh1RNY5zUN+AsZcEJMRjAG3wkgnQ+i3NVkwDHPR/wWZ6zwS8YTTGfOrINdoBsexQkA1Bw+uyZeAZDOMcH7WyYw68iyCwRFmvjXYAQpCyVe9GinGHgak2H8GiswYBHrTRqEyKLIibC8blb2hlzGJRQ+VM0JSASs7GWZkCmxoYr+SUs5CKeCZPwfjwFlxvXjFSQEfh3G+smjTb77cP4dM6UzrQEJUHBH3lt53LhPXQcV5ThK1gwowI3cEcrXzSPtiVuWnyAi0LJkzeyAhergB6+XGTRHhkJGzzqaJxgOPZ8fsK5rwt22bVjW1Z1OzDh/Op/sHSJorRnvEo4pPreHV494//69ZwOBl0egWQs9od/SjI8+YM7HE9fv+C81fECuB9iTCIKkvOb8ZNAthjlkFhmqNsNChXdkN96yZXCilXA6r3g4P+DVw4NHnD9gbBuu2wZazAFmDEncLMOyrYGQ67ttm83IeeXha88PwOWDOYCtrWWJJ0u/prnvCYMK08U4jAvc2O5/BxHQO7Q1AzV2eSiPoelcngEsMizTiAKMJ9NV0BsAv+OTKmi4A+9h4eSDoP3k5yH2ouC4TEcBwsNPbwEAz+/fY+jYZSsDlWwLHjluZ9r5Eec1w3jeuKXhnJXN8cWwbDq95rHytUvOTbE7u8vPP7p+wHCHqoLfEto7pOI5+g1fVvL1m/zHvs9/dSPMiO9oUaTylWrKsJE1S1Qx8CsK54Tz27fo795h+cdbXH95B4ZNPxw5MkGE/7XnZ7CZQzo+VvyHW1L1R+b2Pc9/d/MXf6vh25Lo2/o0AL8AePNnjuuL7SgrfGU76qIOK390jP5vszbloy/ch4mbGshLKdgqM4DzyRy1+hiBWJLnqrIyexap6DNwJQjzszchxUkBMKHDaFFz/f/qTnXwrKSRebg7jzTfb/fPDDya7wamTSBxLjBhqRzio/z/z2r/bLzxLwX/smb3X+u666CfKKwlXg6A+Tu2v74B/bON8lDPTaVMkWNyAE0mv26cCxNWk8dSWbSV0cgVz7qXDYEic82330S/Hu//UpvmvM/O8p4s/Ddtmv+9N6fwAUf+td8kj97+ie85isf3K4CPdyKu6c79iik/qQulQESem7ETMMcHUWMgQyE9XCmdNZ1UoWTptXK3da5TffeNASoZiMk4VyX0jVLlzqqHEfz+Cn25vfz8fuRf7uirXnfo9/b56MaIKxWkXUxC98YroYgBlrZARTLlUdTCAwE6pPRRYxas9zAUVdRTDUDwZ7kxdJjyIxTKXBZSCRhia2sODsYYLDCGJWDLYHE+tzfKFMMKmWKm9wHmgTMe8PT8BGbC+XSGQtGIQeviKQojasDYqYg4D2NF/D1GoFPWejZ4nlHoSGXNPmLQPLVNBTHsPleysBtcIrXqS3aZPeiYEV2I0sHp9hzF3sXfYMAiKtJxjROBmFtjV8JqQ1vMICbLgkU1jRatMVozAzo397b3+uekXi9ZvCb2HRjOMg/1f2lQO8694IFQthTDERy2RGV3bxiQEmaATA972xzzfCffExGCt93/Mcr2NU9RznWuaawT7hjPj70flRMv3+1r7pG7MqbSjokhPKO2+xiejnnc9DLbvKZ6UI7ceb/NTSxlozRQH+B2hWqUPJnCyKwba4pdasHdzr8xtu1ymWvhxp+1WV6PbetoS8N6WrG5001EFurS0HrLqPO+dXSVNKTLEDO2L1YTVzBLQ8T5h+pM7e9zMOWfJNOVzgWTZLrTGk9lla9fGJnSCMcGkxXnhtEqMUMx0CRZJTsrrS3IEisRFQ2ARNI4qpgpmIGAQftMHKU+ChY4CL7k6x5K54jq3DlwkMmP4WwVEWNhPLcBhyAZC6UYoeTPqRvvMhx+RaazopWECImTEJgynBbmX9wF0DqfWNcQsNNpIPbm+KzWa7YJMzJIoYOLMxcXMKZcj6nH3Bsbak3zecan4xG00I7vxX/RRyyhBl2PaC3LXkCeijoylEjCYHV02jt43JTeuGnVeW3+pvGbTm67ylJR87M8Upj3+7SCnOGp1BWK5I0Flkpaa/YN53OSVwBAa/DXdRGDH5jjNyeQgHGASHcwMPfb+Bhmmsoefw7nGSEfz7ZHwvi4ArjchenCyu3wc/19Xcx4nIYjB8TWGsAFttygoWOYs22cPd3LPFMBfzsk+gyA1nHFd1PUSxpKaUyaQ0S4qmJQ99IalNH0Yezeti2N32E8j1Tt67p6lOgDTqdT/iPvY+sbtuuGrW+4PF88gn0aVpkwDfYwnKqqGPrkSUAKj3SYtkLdSdkN+myOCcQCXi0S0vrVGVHtGx8KNxUFQcwg1BSD1Bw8xuTZ7FyOdAIwQ/hA3+YxGWPD6LJLgUlERgehbsiyCdjyD6hHuIp99XcNi5DmoGeTNwSmg3JSkjviUQGivCdpW6SzjxUUBRoV/sgihJRhGW1i3cv14dlZbpuvqzsBqRiOyBXZOVnux6kAtBjPJ4bOrm/fVuhWbG6VkcxhpLCdOv8p9o43BMu6E37tEw8HT8mJj0RGGpoDryQvU4ZD0W86r7nTSeUzAxGpYnnVMD5OPua4trlccGM0wWVeclx464SefKTTXkPnhc/07GM1krwFP8uz1ANirVTBy5IbE9cAk+2kAWHoNj4vHJuLozBmFh9Vc9LZrlesp1Pe191xS4Qgv/8OIsLpfJ612U8mp4bRfIyBcXFem8z4+dOPP+H9+/fmcM7sDvAF+NSinEGEtgA6sM9OWe4Nx5VY1b1ymBJ/2YrLDl4z+CA4zqlldnFu4n6GpfU2PlBxOj3i1eMDHh8e8Pj4CAaDZDG8etmgzWTTft3s3+jYxuSl45ybc1T30D9z0JM+/B7fZ25AM/wvbE6Xgb+Sr0CM1/rfHJYiOwBUocxgVXO+QDhf+JlzvmyMgS6KxfmBCxFeEwH0bI5oIhhlna9Qs+lD0fEBjJ/wklY1HKLrlVf/+B8sxDj9z/8z5TVmfPzlFygTlowg9zNa5JNa+iTRGDkuLSUmKWHAndsrb6QTtwXSNnmihgoRCD+A8OE+esVEYX/1FmsfpylksnAaTMP4O8Xy9i1UgQU/27NvCfSLoL0lbL/8YveVWVcu7yXS95/SXgP4+I3PfIAZzf9T1ua/RvM/oVV5rsiTQLAgZA5Zh9srDEU5r91u7PDlLf/jtxhODvmBTA4CkQdgGG29y/fontLuYOEFAJ/Bhf+J7d8/2BduewAAIABJREFUr7pFpg9iRF2n2wCGf+nQ/mnt72NAf0GBYQqgzx8MKtxNmrv84S5utFLF2hoeziuW3vDxaqnjgqA3vMagpyT46fHtDNmNYIfjOZ4C2fHOYPfOsFThr1K4BFYFlID3xcNmF+HzrY1uPuxGM9VA9/vf3/cH3q21lyoUB0t/6JsCtzuT/cK7b9moeDwU7BqfAAo//MmIPw7zSH4G8BqET77ej7C6qc+kd3ovrwzZR03gzshoIAW64Z614kaWNGS5woLIoiTC8/S4x3vjeYH5NAwghf+EcdzcBiI9fMeOSO0MBtAy6XgAed98phzDQiTlTr+7d8d3VyLxjbD/AsRRhRdXSfDczxDECerCNHbKWL4BIvJ0ix3Lstjyjg7mlhHZ8DR8GZdR9j0IBiMMZ5MzCUWGT9TgYbuCqaE1Yz5kiKXuywJdvgfFgKShEIyrTFmDMFe2IKMd30KhDJmfn54+ZZrfrW94cEXEGBbhbhogQDWiivbG8zCAtxaGIP8NigZXpIfAiYiYsHNmfVg0fiiQAGBZrXby6N3TI3t0hguyweQ1Kt7ruWITqKKWXNiu0sDj9zYXesPA1161vB4p5aF7skJnhj77u5sZw1lMqG9DzTufYBH4bNFuCy+e7t4MX231MY1Ym3JOoTuF0p4rjeiTI16gBEV1+AIEKr4+TvdmZHaFTUB3Yno9o3r3vMY4AexquSmAVurBToeE+jzNyMiCQ6Bq0bK793++HSmUMepzTvCa1EOK0bwKCKpWMiPyRh4aW6FJqxEdSkI3NNxE8+HIPKqXJIgzR2Cy2osqrtx3w6v4PjHFygZV2idoE6kRR2UBfTvV7+ldQGS1W2UodIn3zEwhooX2NOtEaWYIkaRN8KwFgsfXr2ztCDDxxlMc5vwZjScOV3jt9A1gx6mGhyMDRM97BkUd7oFlsUwOrIzHV6/x/PwJuTLqdZyLom7Slls3xh38JjxrKvVUBkx+03sgcNPySCrSSJ2uNmKGQeQ6Gl5nVxymR24hktPoNsdpcF2uhfKuROpP+oKdMi8MTqhwomXusedxJnLHfR4K6NhcgR2KbBsV8Qomq4XNi6WxhA7oqDXBNdcoU2XvkViuYwxuzxvMTZjfaO6b5lM5dwLDkjsEXaKdAaSyL9OxsPLQBRcmP+R7Wuh4ODrGLtnHOuYjfxIv3iGG5M1Cia004TQdp3xcM2OBeDroSG/ujnMUcKy7d8yPuuMFKkaONT3CY92H+C6iaMtifEvvyMgsAJnrpGT2AcH4WwZGNwNrW82BbHh5nPPZ0s1eLs/JH6taen7A5qZXhbSJqwCLxKVAeA4JySPlHte9xMSb5fyGE4pN154R24TkR1QBfgDGJ+zKjlTaE9EWjIkTKMZBhLUtOJ1OObZQGllK95JZJIzSqpY622mXRfCV/Yz7gzeLeefv1hpOEJjia2ZMo4Q9peloHsz7kfKO3k2RxeYEGFGKYUCvadtBQDNikmdwWRasq9XoPZ1OWE9r8roQYNs6Ls9XPD09Z+30aMu64Lyufk5WPH/yJMi6QrBhOT9AIOhPlzRC5MpopH1VsCwgNCgrcCLoxdLEoxFkdViFArTMdfU58ELQoRhXwbJYZg7djG4s3NDVDOiZyt5p0/A636oDo4uVcTJG2vaejP4FgBLZmhJbuUgdHXActJxWm1/vULLMNUZmwlhdeMiCC6LO/bHt+KvJ6iEoAhE8fTHyzMyz7gZZASLbFBTOzzNUZnrlWMN99hJkPyDyOr3IebgHM+Y3wwExxh3v5T2JXOfYUCJPMZ/LOerRwF/krEzLvXewip4zzbfjHX6glFVTpwRklK+oYOEFQ00elBERVO5wRwwiRfthAclA04Yh4k7R6o7ThPH7AD0C7U0Y6o0mCWbWin1zHqw1y8ITuE1GuVrm5nBSS7vA+bE4x6HQRv0tZpwp5RX9urkDJU/dQDHoM8MdAFvqfSLNetC9WZbB8Zsqtu2K0/mUehMZA22xCPPGDVe9WNYiZpwfLePJtl2hqljagtE7rq53+fj7R2x9Q9eBsQ3He4plXSafRAAGsLSGMQBtSBkg6s8H7Zh0oNDXJP1OqJkBGUiPKYI7OynE5eFYd9sk9ex6/rO/U6BovvKn04KffvgRb17/jMeHBsEKiOJ6ueCyXqFkdPcaZVCugLAkno8yclAzWhu9i+xDBiuWYYBsLI2dPr82RwZ0XOXjjvdDjFMtC+MoinNVK6nEImgKaKOZtaQIT7H3Vz9TD2RnTxx/rvBiKvFe/x6O8pf3G04/LZn5LPlXAj69+wUEwpt//E8GQXh+NkRwREA20YxCR/0b0o/rOq6Ryt2n8CjIqPugQ57LzoKyfH0c08y1gybfHs6/BlOehfAtIO/3vICq4nd42ZLgIwuv9K9ucQZ2+PfQfnf89ho23t+Dh/Hxv/bHNn0H/ILU8xAAvHM69c7eErjv/PYt1tXo98f//f9B/T1fIdL94Xbkt/5pbS7orn2r8TxazQN6rw76nz+fP2cXjnRuh3fytztv/2cCwd+h6f403hqi58desBK5bPj8fE0cZJmf4HzH5AV2jlLBiup0CMs9IpPYmAhoU++1Nos2X5cF29YBGRAvTROObJPX8r5dR5Uya7y74IvKy0+7yH48xzW41/Z47f/yFvyP7zOT8QeWlHby4H7jDk7mmUXKnHsH979f+/sY0O812gs+FcRrNMlxf+rX8HwhslRR3CmVOLV1fNqlzat3LHiDq5OjqXJ7ecz3Lla0Vi+3n3/E9bcPL/X2Te37wPSzs/rT2pci/b6naf1Auw/2bv9adbnPUGPigRtWoOgnd0ggkIitmAvNgzHYBUBXSmohbhRSlysfg6G8FZCPYwgFwPx+bw2rwjfl8Dt9fdX631sM4MV+U6D8yla7f3FMu99DIVFviI30FSwWEir/BabRPhScqQcmS8UYXZn+PfaszEht/1rzkYszD0FHMJ+xeqQDy/LgNX7ne4M5iLGEMidMn8GQjCFZC81SCmvWjplMzf77buam+dgxQATFdduwLMC6rBjSAbjhgHBjNDdDzvxb+8q8gUTpqJAGXPLoeW6ghYAB8DL71hhfWWtfpN26V3jaKS9SEH0Zjne49hnAuf4wBdnjm8gXj4jQwObowg2tKXQJIdiEvtb2Bp30UqcwqHKmO93Nw8/8PmXt/XnEkU4leL2WE5hOY5ZmqeCUI10MIE8EOBmeu8f6cMHKGtzDPQeEQfX3vMmv/VH8H+N14xaZo0IYi3EPl2qPJbqBF1uKw68vIjgkvN+97uexaaQ0n2mvp/I1FgVQ7MuXhDCgWqKJ4lwhTO4CEQaxRcFlRKN0rKc3M5JbpgFVXVE2qCGcDyIyU9WUcerzDgM1edaEiDYkEPq2OSPNliLZhyiejiucQsboplRyA5GlO7e6r80V8jHvMcwJIPZtnouBwItwYSzS+NV92gvWMyuL0V8kvFHo1OP4Flyz76+cs+AZQTPNbdRCHANo7fC4j0Usyww5HB35yGNL2hB/S0r2aBGpGVHqQUdy3TWM5jPKa2dMz/vcaU/6QaChhN80ACIWLF7k6xnCVcEfN4qPrNudzI4r3Msby7nbK0pofw8zGhTh4DUzosQ2BbeOvD6TPs779hOpkeeTf8i1ur9Vd9otvxzngD2N6f6anYsxzAEmmsiwKFUfqBxQ0EvCZ8g1L943F/gOf1AjMOvNX2oua4lC4VGq4Yinlt5V3Ig1hpgDUwIr8t3eU45vBwM0FTw7eIDzPJ8hIzQtybudqXCilytwOqUxPJTeMcTIEfXllbD7lmYZOuZvVNKcz+wZA5oBirbfhoupwF/0URVBO56xzvVE4O0ES2YKEE5OSfpeIZRwdQtH2s3ZYWF3aoq08yq7qNGQw6OMR2bc8YwZ2Z8YPPc+cLlecHl+xvPzM56enty5LJwlbY1kWXx4V8dZDVaipzn9KubS5JsNdtIQ57xUe2jJS0VdZN7CaGh0NXqb5UjYLRZmZIICfXQsjdHdyDFgtFHc2SVkBjOmewrlNCLC6CzPUkW2p/ZZyaNZ2eichmLS2QP1cRsd2isEKU/q5CNu9lP3a3W8T2FpPEXNUK6qyTeEU1zwVskjBx/i0eW9sI/xGo2NqbREg0clH3WhFAmgM9J7DjQRl/NOcba22wnvZ//CesSa1BffPhJG9GrcHTos8lcJg8fuISJK4zmg4OYpTjUMz1atTYkAbtAxTO9EsOjVMGgTQZ4U/Mr3YIo4ybfa0NXOYKTW3+GGHWaYY4x9iT5jf5KXCDzVEI7fwQfEmpm4ILmWow/zReFmTtRElnkACvbyZXV5pUYz66SR4lm6tBlefPr0CW9++AHXyxXMjEUWc7Zc3cAYvKGYSjPSy1+3zQ2wii7dDMReWkF8HxWKrXfDx1EixSfYmNHAloWid6gAVEoQJB9JxVWQ6gzhGYgK3Ko7yiczRXvoDtnfZTE9P0BHN/5F7fp5XfHmhx/w06s3OD0sUF0ssxwRSABpCgyxczaM/o4RDgPAopE9KfZQc80TUngaLsy3RdGwuFyhOOE1Nv1UeD4UvtJ4ligpp3CHDyFEMu5w1A2gCHgTCJiMh75S5NYQrB6AMtGXJpxfIVgVaBBc3m/o+LirX2843j6ZIR149fM/ClOApG1Pv/z/OfcsNwB3JPAzSX5ekjdPeazwLhMCAsv4WhkdmOfT3KX7uw76KZzQ7Np4J2hvbYwNP6Lrb9nfl/jRfPcOEf812tcaTe7p/6akb228E6z/7y2F+G+7bUdq8FduUzdy+P0er/oXgu2/Z5u4tDYv+ANVd26WqFhubecE7H+TfVNN/chRIOtqukIdAx1BBkaW8gM0s94ds92oqjkouTPdSxxO1eLW9nc32v5722G1U6/vOm2K4LOMXDs8HXD2lbamv3j72xrQQ1xMJFsLO93cHBqT2PyJKDYdWJQxRNB7x7V3jKg7qiY/E5mCg0F4wGt8wEe8FkMtpx9/gn7Q21roB2quuwtTGfLsguCjC/chaH/y259++80ZtsmoWzd/AAEkZnkZcG0It4j03m/Hrr91ILQ/h3c6qgSU7u/vF15cVCwFwxcG15UPn7wO6KML7Q+ut3gm9RroRTlhD0avOZA6lFQ2wIBokMEXYLXuTMGze8CUvq4wkfJ73rjXiL7IGE/GOZbnSNqCYE1BOLqvDOtLKmOKLmnCYQwt3qlh58kLsrtvipO0+w7dp9iayvT9RofykWjWW4v7Z10UE9C5QO8eaavXs/K02hEd4P2mcllnKpoU9Ou6kOmZTN8UghZDteeEQ90D96gb26VEiZjxiQDzzvcanVF2zJgJToYkBO+FKWvYA9NIG2Oi0Pbuzlk16s51jd+GDMg2vG5nA/MUsqsCZf61F2St9RcMw+BmdfBgUfO8Wm15sM2tb3b+zq9Otl+2CUmcg7mjFIqdoSpnc78nXr/zsmet+DHGbiu7vrE9GH422SOhubErE+xvfy7ptskUQsIeSaaMBUsGn1rU1lx/RRjcAFwBWgl8JvBWDVKAXmD1IaUa0R0v3KNv8axi1jcmWBYMccZSIp7Zz58GEwpEPeLaoYbBOca0QzFHvIldRLkC7uQReMPTVAKYGG1PvyI9c4LLN9M1749CCY4Dbpx4eM61LLqPQaninTnGiDxJhq/Qz5yDf7cazAz2dP21NWIMBpbm0eToiS8AT/8JTYX0VE4GfNuroyZ6Uhs/w5mG3O1VprSPFLFi5izVrHE4lV4C8vSW+0hWF5N8/Ub39zZTbhERlnUBL6vPGwC25B8Ah711tYiqPrCOYU46bUF344Up2UxhSkoevQIQE/rYMEQBmGLQ6rkzIjo/qZlO+FRX/s+99WWJNGH+Y6RbNYPlxIGm4J5AfwONTt+Gw0bsMgccuJCJ6oS5LKBh7+PiGBM4fk+RqL7qhs+rDlEETeN5KN8D/iXr6nr1Qa8JnP+ib1dYKyjLDyTR8LFR80hkBciNoDQA6EBZql3Z7clnHAQoDR7Dr3mR0CinSnneCl50I8AuRtbxHEAWBHdQ7tcxxAN2bVZPnChi8gaTnmDSef8bifnnDZV3uoO3aD//6sDAzRz+VMj5joEhZGex+3tp0rXYt6wpBszzSr74NN85+bGJo0JZS/4/7HhAv5a4jD1jQuyJG3/ievN03sOMg5rkMWiLxV7FdV5WIE4uE7bLBXOXNXmXMBLymfOMJF0CgItCTzMSK5ZdLsG3xV7bF4FnEiNLA8ynsnHJ2JQ9O5k33fb0bM+dViidwHKZ+4iAlcle8YMbxC8xlzAEM9ZlQVSMr+fX8FGUdlKMIegi6GGgdqEgDaUTrCYuK2MKgwuRZTgiilwhJ3uOKGnV7K8owOpZdYNZOPqB55zinFY6xI2tvvmyoLXFDSAEL3+M69bRS+r35+dnPF2ecblesPUNoVRp1LJP0bnB9t8OVYsU7dcO0Q4NhY2fEYp9DRyHDsWK/tydTjXj5QcAIbRHq6gq3Qin7WkDn91hSaeRT8yrAdeyh7lcLkdSUy+B0f0c2FqF7LcstvJjdIDgmR3ceYy93rYkEcf1+mw8G4VkYkRD0xXP1yb0VZyuKxMwYmaBzw4tx4mI2gcUbFH7fq06KgT81xeE0XOeJx9ZgZlsITukod57CTxW3pPjT34x3notr99nXMuXlOd2ne1nj1g+rmloYs7BBlGJdgocC9vX1hq6TPkBlrcIrbHV865kiyP7iJ0pUivZAS8BY5HnDGaF9AGOaO3k9Z0u5LpELr14gbtT+vUxOpZlTbmSUz6eepGQ4UDOv8JLTCCM6YWPUgX5/FCcLg3XNZsPPII9nS8I3NqMrCXM+t4ywLASilrpbchAY1jtbyF8+hgRzwRcLjidTnj7j7fulG68kEWeA8uy4On6jCGCrc/oezPsDqed6lmoAB2C0WdUG4hMvmP2sl023YEBEULUTotVbA9nXJ1mzM12vBlwNDEtZuYWv2+nJ9kbDMbTJ/CyWl3w2EdueDifsJwZp4cHjM0eZTD43EBq6yE42ZxUgaHGy8Gyo23DdB4CRd/6zHKlSGW4kjseNTgP+IyhA8IdCgHJ3GMrFWb71gM+KfCy4ayhAOtSGSeEjH/k+aYeym7vIvgkI58tnBWgwAWKRT85hzfLcOZdGnwaYcEPvtfRl/XBIDz+zz+StrXGuL7/DT/8r/8FIsLzu3cILpJhSefY18zYUYOIZx/fo3oSgl3JDbtYXC7QAQx8AFspbyw//ugwoZB3go7fbP29h4+On468fOXvg6b+a41Fe15ld6WMLbjw4/g/ln6KUgA/YPItQLhgWBP8ig//2z5/2JPlF9ueev0F2mEgPwAJHfHvj0ad1xbS3Q/+/c8JzastOOI/px35lXtOgDvwLnjl/4b2ubMGTBpc768tnM849BH2dPYReDgzg8HsFwubE2vQi5HSBIrOPl5KGTTgo8uMiMHYNA8EYyaAGxbvR9ti2UJ50sN0sovuZZZIqjMM22DIUTGumFPC0L8AGfxl8MxXtpeWJLMoHm4mzAy1BMGQWULxCHRVv/Nd9sy/QPvbGtDvNorjQgesWm5BAQpnUCx1FuH9x084tekBCAAXBR7nMQSB8PbNj7h8sIjz/qFD0twNMF6DwbjcTZDycguAOu/VhPfv/aPAVjnUf1crSp7YiTyQh4N563lIf4gu0gEcbpBCItp4z55xiXYQVQ9LqQeQc6NMMoiCoR3hVY9QchaP9BhcqGlD4Nu/5uv2fqpbqExiDwB62Ieb378ELy9c/8NgtiOyn2t1r24VWal41eNTByacLBIaMKWVeop2U9i6oUDnjEIB/vLwBeJp2mL5xD3aQQQyyxByd0pXhNha046kHhDTm56TiVE0nukykxnB7Zn5XLO+pyG9RkmLKuBGplpbsxqbquE+jBP2WaeQG1vqH0hNQRre3Zb+pRqiXMnrRLm4v8QqpfL62ApGKfdMpsml1tvnisLvdv3KXMrnWAMmM17ZSvgb1f6TDIIi0+/j5MMgAj8w0Mv7TrByq775VbDczy8GfWdcx4VJxQwM5+RKH5OE4wa3qO7eWH6fe/JZ9PDCfUfl/3z193slTqNLrMcdSJlaGr/LoqDVHVri7ObjiQojYvD+OIksbW1bWsKuDkkjVGMGU7NU683ytQ5Vf/+9dZ7jrdMQ1axHiTI+QGd2E5hxxozow5WGlmJUvMauvaPZGU/8Zm27bglXy+kMEVPmBg1WUY8ytPT02gQ0yPGlww0zGjesywpZhwtIjN47TuezG8ssNTCI9rXZxVM8yoBQGNbVI1rdBOgOC6KRgjJWgXw+/s2zkxhshDFuLuoxyqFmM81FTuX6pAFTSVfgmWat4IKUU8EYkeC996xzzGXsu42mqWKrCrLEM65k3Q81DDgDw41y9uxIATTuS2HUxzXLgWviXyAih8wQKh5djFYccV5oL/GpO4N1HLBYUd3TsNmHHr5HVhTCnoGKfvYOMxnxq4bXbI9l19807JcxqO94VfQBO0eX49tfWgMpkGPde9YcBjAMLsfw94hFaEdEYTrx2MbsnV3KACZupZtrN7xrKq+xQ9LTAJxLMPFM4Q2dpNyfu5phJXmWMAr6e80qQwjViwJmPFKAdGaZiCwUd6Y6x3aNNbX1NJ4uFCaZpNXgvwOwkuSJ82xu5kR5QKv27BmgJ+eXHk4OG1fLXlOaPO95EwLcAOO8mqfGtv01PCd9pFF56xu2MTD6dHbxzU9aXVfibqVXmrsf/xRRw/Dst1DemvNU7PEDEdZ1wcLNnT2mQ9BChIEOkoBPnbWf3aHHUuSTpfTuG8hTlvfesW0bLpcLrtcrereMF0yrRXs2M8Zzaz4B2u2H0gDUo2xzvOo0cNKQxIsEgDqEfNN1QJTR/H4S40Et8tTXhc35o5aoEXfkklInfr/stpgLmjuozbMyWbOoUU1WIoYAdge3wH2T/8bE/TNc2x1hxI3qQY0KnxYlxCpOBXZnKL6rA5FCM/6AiSAknqYdtlbQ3Rwqzp58khbgvMMbBZ6xTfQDSBmhaniXyvMG97QSdDvQCCjgkefzbZunhP/j/GPi15hY6WqvuPe5u7FsqKCJYtCAjHA8gfFbQbfLezKaP3AUEcweTSjxV0bfXjlcQwEpjkZwnbLjtTS8gvKdcGY2jP0A0tmuu9NKTpU5ZRlubWa7wYRjAlmKeiXwYufbzu5M2W4lXtxJxcfNS0MjM8bPsiQAVLH1ARJzkOzp5Ic81wpA+oBQlOBSpwuemv1yxbqu0CZYaDGDLk3HecsExhjbcL4vjIrTGS4M9aqW8YPJsouRCpgXw0WqQHPHBJnrVtvp8SEdr45nbndE639cBo7VAgW9cz0BEU6vX2NdFqynM+TpCcqFbyGCOaptXvZsQKRbZgRmLK2B1pPBjprDDojAG4N6txroanDblL30FEM+KQxJvgbVKHPHTxEpyODEaYauKeVfBETe6PUiCx2DhVM+ivMVMMKezyzg7KKKVYGL80K38qq51azJub7Q6niIc62AKbMbDNiuPL792csjEQi2HnEGGzyThE/5KDI/QfGoQHLyGhCneWOMpuZGkveK9j8N/LNC3jsNCt6h8KLJkxZ+Pq/FOv0HtAM6zrVqh3v+U1oYtieUvNy+pR56xNREn3+klvq/q92TJ1+UP50H/G/7clvUSk4cIa2w3xhD0BrjtC5YFrZSgS9KvfP50O1Wmcj+Gh/LxWE2eI1lWcxJrJnz1sKOi8mzDbr+ahCBxsCgqbu6Bw4vjXNnRP9vu2nfsjLGx5rT6BAC87DyjzjI67r/8Hffg7+9Af2bNoCCHds3E5xMgDitxn7pZcPFU9g9QfEII9a/4gPod8IbXkB4RNePO/3T8oMnsf1tj2CCpTuONASpiyteHvOevdA4BdZAFPfn/DJK+3picq/n+RtNhcvxesXBx05SM2XeqKCXjSX3DOe10/31z8/r0YWxJ4pIHuvlURXPyezPvpUoI84flfDo/TzRERXcQQ6HEanCjejmk46oAavqyo+AR1eYxO/ecXxPwSsVvPs3H987NTEvjTJe4rBPk/hMpZsz/TfT1vK+MgY97E3df48Otev5I4Cawpa+iuHhqIUdT5VHxC0AtY4a7VDcXJcZsWZXRu8p+IcLw4xId7UGhTIKM90kPMXMeQU8it2uu9ATQqcCIgReFxujdFe2+joweZSojT2MVSF6UYaT21qpKMCeCtXXdiot5j7slpvmBxPR7633/E0UWOBpmVVyPNNwXvZAKSPPLfLJ4/7Vozu8bz55akxXrgyxmpR0srF3GYjoFERUe8Kg+x37mmrZf1M4hjKOUqAPZ6pQAKWg7pHR7A5T6zIFeCIyw1NEGSjAjwyIYjyPQm98zsoWveLpBjP9ZRGYh4olH4iI+Fb2iNjqc0ZQjSOp3LKAufre3KNqxNqfY0AhGKhimKQSCXnnLf2cSKf+d48GDlTqgCeOjFIqwv370V80DTFfQabu3TKVBjZrRJS13z+zIkxaksoHv25aTIK6bzuBMNXqyDNgTiuScKaOc0CEtpjSKur9bjrS+BuGVCJCW5oZzDZLPdp4vz5TEeww5ZaXMHwPv4+ZoAIsrcxLp7EqlZFqadFD+Eill0d/R81quNKFG2HbLFKHZQDc0uhkUYkNrTUsbUFbT1jETnkoc3q/gpUgzXDB4vVv2RW0UPXI9J6kgpfFPotguMJKFNAxdrW/Y6aWLYIB8oxBYf30dbglJxPObf8A5B4W+KLbZ4JPK6Qzy1sQLBsIVDOlPEckemugqH+uaul7w2Pa0wJH9ohQdMfpNA/s5sbUiMgNI7PjKqf1k/ZZtL+lKRXHOwpoOHIgz4Cq4w9PGR10J+BQHb8pKCOcRQQ48Y5/2POihKDBiHEetyFWVacDX0Y/FX6+4jFgBlmrIqPOocVhAXuDhYQBI9YyI6iNZlr00fFdcxrTaJRoPHHKzXzu/YiKsydWtUilgGeABkMRdKUBMuFdPRrrpcE8AAAgAElEQVS5LQzScL4rHXpkGx3eUkiF/3HX4jCEOtyk4nih+nOu2YQVNzi44jzwEDXnOUrWn7pAQ43/hWwAEdbz2eY17P7r5eI1f4dNxxd6Km7MwJ41W89Bv8XvI+gJoCuMj2DOeZpSKJwODaeLKnSbuJ/UU3zjZJFiq60wnyxifVwuZnx4cH7i+Qo8AHoJ2m2TlmeAs67f3hkRMPwca6+wSEaoRV5u2wbpG5QXjMvFzoKa2SzwfJhta16T5Abv8M3B/U1sCBA2tPPZ6Nq27QHeD1byjyCcz2ecTmfDGw77Ywx01XT5klqSQR1OPFsAc8CGZW8IR4HrtuF6vdi8PSsRNbUayY3NAY2b1wHWHM/k6cR5bc1aiAItKd3dkJpFhAFCx7Ke0PsA6bBE9togz07HFz8hA2acFoU0gWgHKwAxz0fLZGK8nM7u3WkAkE0wPJXy5C88GnQibpclyNMqe5ZnDX5ZDO8OnWfJ4WzHM2ZNSsNnzs3Ze8PBRvM/CDNqNQaHQZKczzbaZSmgSRRMAqHIMFMEJp28hfolhWYmKpNdJxINXimAKfmogsxSQQqNzO7QS8jEMYdrzidTvCeA31GV+sW6jLFOc2XqNR9vST0NRcJi/+R09JGhTx5t/YqSn1CXXagxhgwwNQwM1Gwh4eTEbBk6otyXOSsbnzA+KVQJ/Irz3IFnLfJKcEjDiaLsteNU9gjiOJOjz+w9cKUncZRbIFCzcjrk5XnsPQIZFllvpQ2WyRWlI6aNY7ibWGMGlgVLa1iI3CDPUBaMYYRrjIFMEivW9ybdZLPAqxq8HbLEib1vA4Hwy7tf8HA+43x+wGldsZ5OyUsBgIkCMmEk/8U+OyxDZ7kONuOt0WjPqKaADOMZrBIMJW5yRhLXp6cCX7Ede6eO+BzuDq0VR4UMmXZZVQnnV68m3t02PLx+jaU1tNMJ0hnb1sHtiiEd137FVTdsW8fallIqLWCOsawLqBHkmaCXCwZ30CDI4g6uauXghIbPgaH0CqofK3iZM5hngyJPo6QMsBwcNih0ArZOtuw84Y3joDuMapSeUsumQZ5C3VCm1T8n40dfYLlwdaxwyuHujfgmNTD6bwL6aWBox6uH1+iXDby0xFXMll2ucWR0I5zeriD6OR1Rxm8fkmJKsJaOL0KWctSetDv0IZnrSQve8X/81jJSXH/91XGr9RGl+oLHTTVDyr7xm9PBgv+T9b+3cOX3l9bVrlWOYv6iu3vuPTf/qs/9d3/ncSd358fbR/8haqQzTB8fkq6Wz7fc0MttjzW/vX3r8zf3vfDgD/A1+sq+v2X8CjPQ/4g/w3h+ZCLvve2lUXz97ymL3RW09I9v4N+8JV9z0K9lyT6//qjAs2/Pg//4TMCiig2KU4HkeoYam67GghUMfzdeoNxTVo8sh/HcdAiD8+aYfGP2bXg8z76ajLNSw0INy2K463Q6gxtjccF0AyAk2KgnTYBq6kmk6vxgQTHqsgGc7woZRzHpVM58x2//89r34p1/enPbWNKl0LXdw9VU6Dw3MAZUGDcBCi40zGCA+7Lr97SvWc+XSOAfaX9vA7qvxPTyLkKFSc0AAql8ftmIYGkpVD2yBViZsclIYO/lfgOGp+xxHtp430tcyrHtWY+JhuLa8ft3tm/lMA7tDz/qJ22P1r/x3fTHDtxerDYkyQiiUtd2GusedXoG6y49542IhB3WrbScItmZ3TugIJG5m7TvwWjBgUV9ab9SCXLn0m5EegD94zk4MsRxbo4dfw/sHSeQJ+Uz33H/uksB4XxgazQjxkNosHWZ/cSnMKRy1PAlyjrngM76uP6ARQ4WZ5hIOxgKIx/NjLCiiZNgityZeMujR1zZFdGL9rsJ+kxsNQjd2JIDScF6zsuUq7M+VwjyU3jnrEFTn5s9ESItKykH57Pbp6gXud+H+Oz1kIlmf8cTnmnMnaeLaFMUJisYrrTwhDEvGDKvp0YM+kowDFcCxQbQWpinO9AYxsPDtR1EOkwcDSJR+1lZALG/rISIlwDgion5veIwOjm8bJN2BB4I4TIUbp+jKHNY/s7J+tzQRov0OaTBvqkkPfGCMTvJ8uCIYb6m7dDYC5P5GtL0pevBLEcUQ8Aa68u0IxTB83rDNFnsB71Do4fBM7EZlNuC5grzGREKj7BrViYBi9cEv+dIVpj6A3q+wcoKWFptP+EsVrMR6mmDJednxlQ3PkAMPzicEU3jvPsfmFBE872qhKxZSgyiBdRMESZeN1aiPiQZ3WRP9anL4uNDlh3M+rB+0HPvVEHuXBBGY1EBa8kOlIq5MEzd5FPAvHlC1lT6uzExjF0o+Khu6q6bwOlusHZCYwp+3+/YS7K0pSRmgFA12g+YcX3zCHQqRoZp0ECS4TC+1+gSRNpWf1Y944fCUreP0dG7YMhAdzdgS8upII/szIoQigPuGHDiBjPQ+HvEAIMBqDDUU7gdW3XymeflHv8Un19ouWVzbSYui+uU9VpjyBhTWA6lYo4j95mdhrvBHr6OZUQ3fFVsd/IcLw/9/nrM7zWLSywDAZ49QnYZWHJQ9fzrbqSl9wNipf1vlY7vcE4Ow89qIAQf434OmmtBMcbPIeVgicgd9igc7fwsdwYixe4Q45HhnAUz9KrAab6AgofCVL6Yba9wIM43BV8Se5+RlGr8mpbfUuE8Fxm51KpgsjToeLhCnu36jo4fcPhuJ3ydOPkbeErwaVQe1w2jP6E7HquG8lAK5XJ+QQaqXOAe+9l8gq0M3DmNhj5nsYjyh8dHvHr1CmHUGFvHddsyXWKmWVbbO+YBjtR9ZGmUW1swRDCGRdhft2tGng9xR7XFDD2tNSxLRJ/PfSP/i8QBexiXKLWj285hJozucd923YCoIy0CIsXQJeHHNsYcIbqIKejTSWrieukw3KjqNZEBWsyobkZOH7fCOCfPKDX5u4iYUQgxor4wgClzAoh0BWF8pRgPjOY7cCDQROzvDjxKv8A0sgS9mMb0EpErThc5HKFmGvHqMLGjSfNVLzbj8X0d/LBOyrujtslv0omAq+yu+duQuAjRV+VPkZ/vP7tvuS6Y49vf7bBXEHJgDP0kwBsv+aUAs9Fkc/YGGhZ03aZsCSvpo/Ee95JPOIeivWaDP3Unn8DDyV5MHL4nEbbGRhPNMK6iicd3lNfpZ4uI8XBKC9wQuFsZxEZXqc0MVpU+57rFGhChEaF5FhUiSwU/1N2gAwer4rpdsfLi8Giy8vAsDuYkqWAl9NGtlJAr/bdtc346srUQZFNAPIpNgUvfvNJMIaCao93BAMX25CJZZDJ7anpmRVO1FO7JUxx5zzy9Bd7qG4Ku+ntEbE3FzweTO3fbfddPH9GYsS5vsL4RK80DwrZteLr+Dlp+BPSCrXdcL8+4bFf06xVYzfjBxPB8uGBesJ4sor6rerkAG0ZjhnBLZwNmh25xo62fDynyArt+i4jMyQaEQcZnhMMwuS6VPTudkGJZGOu6wJwDHQ+JBwOooA8xetIYaKaXYCJzOgcdjOfzHM4NtnaB7qLRE3IV6PS7cbu/2v3yu+L045qlriJrTG5hLFTAuL+V8AMUHycPV8YQ+PUTgFcoDqAIPa+9QHMO1mPLBNvGpwuVWSnw9HnyP1dG939jjPcSy30Odd+7pl+4/lI/x3u/9P2mj2CJdWos4vSFkb3yO3+l9jIduv2uAH5PuDhu2P77hy9cP44h3vbbN47/z2sBCQdavrsO3K7LsQ/6zPf/trqKR+N5A/DKcQsA9MRCdRXtk6gCw+xiLUrNDMGyNN+6PV9hSbz9F6LPnumQzxtF5lb1EpiMBs9o05oZ1wGQAMIC7Qqw61Scz+oEz1728mmoEPW5qs//bcCXsPONzMvkTuRsDmJF/zrlzwlnX9s+hwX+3e3va0DX/bIS5oZOfYgxs9ScWRfbXI8HzucUwI+vX2G7Wgq91hiPpxVDgHF5gqql4gn290cQLqnEsecvUDyC8PzhVx9DCDeVsasA54a45OunIrRMcjI9/lkjL4JGn9FvFRaPhuoDQVVyftDXKwSluPvO92rsDQHEA8nzt9131O96eBZ3jBb+Y1VqIfhWj4w49oV73/ctk+sXDpRI8cnXjeoS+X2PuS6EJwIeIn1eruORAagvobkY/n1A01vKdio89OdTyVIHVg84iOgq9yCfQjjdKkui1SVNqfAOe0EhMBfW7jOZAY5trsB8Pg1GTJ4eEGnw2D+1Pwv5b/dq712nEOTV1RDeUESM4cowqAth4KJoqHNFKn3ZDdwiZmYynGHG4tQLxFqUbbWoaju7obBJI2fUuSKAnXikc493ul0HwANglJmQKQa45btEFEw603QO98pnsmhnJaiQRbsy0MXGhdhPn+w0UrvCpdSyjKwbBLigyyluhvLRbwdjQSqpy/NRU0zJvLp3KaKIpqIPAsXq8QaC0/qAxoxtdI/612SEqnJoRpM7bvR06bE3YfTz+DSP5ohzPZUZgRGNUSN4oUeMzWsX+vssIC+UoIrrR1N8hWHPUJDvc4wp4Ys9CwAcwRU8fI55eeShGw0iBCKMhEMsTWikVbY5qUeJasJ11LFOw5lGtOXOteT2fEKRIqfGHRMJ2truPQergFP7rj2SbbGn2N4/iViP+Hg392zc9rVs0oH+i0A86lfLnsDPu007EPBUzkcfds8AwrADrwG5M6RPA2sq59WebYsZABo399QNQ5TNfSqbfX+GQIYbi8KIh8lgcjFsqGIamssoTCGplo5aBQzCQksQTVO+8oLL9QKoQiIzgjhsue5vDJlpd12p1nvHLDcRNMvPF0VtyGZjc0OlwP5afVc7w0wCwmIHyyNOmBt6HwBGRsCCCEMsUmuopX7u22Y4hl1xvxhNRmteU17QmrGw5uQERDFmi4TkzNSx4xMIWePRGJ16Pu63uRd+FjQcthxKxFKc9UiZXnpi57W0WephUovQastkv+OsS3k2vLtBALopl0UF4gbIxtZnKCsjUmmMgd43+xv1SZWgC6PBsw3o5MGUk73AjFbzdZGKSczoPGQ4+jRcEorQqDOvDpM7vEHkx23Pk+ZRpeCMyF898eK8R+c5ga0jk5ZT4c/CzkuXARSv9DgXqbBU8pMfBvjcZVSlQNT19EHsMOZXWI1ydKpmmISfZxWxiDAujgD+3uERecm7xZkOhXNafI4G7ulkoHUQSTo40V7GG0c/mAZDJwQQtQwmZpChxGlGqsnhC0mvxSwBaTykBjv3QycP4t0LPLKhMVgXDGx+nw0+sn+EinkX/e9nOHG3K3fYnSItgvIKotWy3Ii9X3RGRBgPbg6OHR0CxXJtycMG26oAxsXSw5DLThldHTAiAgiwtEeQWlTnugx7XsTx9FSvj94zepqJIUuDwkpXDJF0ueR1tbrvuBZ6FaCnk1+aUIZKp4Jl4MZWS1gHVBvW9eT7MY0iQafghrR1XXE6nbzchGe3GOIZA7ScKxiO5YABhxWyPezScb12bP6vbx1dxnRCIgJzZDAx4IrMCxlZHU5Cqp6JwY1agqyDns4cmqc4ay9Saxh9IEpZgJor28wgha5p+B59oFEDRN3QSdiu3TDFQl6+AoAyqO15rOC1A864/BZrNc/fPDcp3bi8MCRwOqCwtSBF1rQco7wLhKg7EnxYGELTF8rXRyaiz78VX7BNK/HoAGydtOXZV7WMAjcO4BR0VxM2Q2aftMG+Z0SQzvImBVkiZAu5RGYLx+969pNxnXtd5FfNwexp8O46ZvRnnYRAE28BMwoaUI82VgwMkJKlu85SObBSAE43zQHD5BNmnvyf46rGDSMytDjMcnPHk9+NB1peeaYytVSlS/CaqR/xuXh2GsBgPedFruyOyPOsEWpzWpbFZDaurkgTN2s4T6pTBiLHH0F7JMtSEYyBMDTgkc8UkdUmU1q6eXVGwx3PaUaCCXnWN2KIdNTdUwKGz0ykA+JRvTJsTYnw/PQMEcXpdMKyNPTrBb0PaO8gHY6ezNnT5rznRCj0gpG+nVvy9DEfcbl70IBxUsYfNTygfxKoR2TPlTwAXegM3LAcNAsKd7igdNQW8bJSLgcMfcLzxyv4DQM68OnX9/hwPmFswPV0Qu8C0YGtX7FdnVbBnGDY38GL16JvxrsvjdFHyDAMouFyMEM9k0vwiGACiUXjCwkwDHOyZyhiJQxiEAYGE6zS0qRKNXsUE1umLlmsvFTsp/NgBLiewhZPVdFFXFejOKnik1PIHGNwb4lHDII2UpxgZ3BqCsTpOOV5Uf0A+Y3x6u1bNG7Y3m1ovAAYEP4IIsKbf/wD2/sOoY94ePsPmCZjYJHXaZBPB3gYr3wOttH3v0c2KAcJo2SKTeFOOwrBb5B3Nq9OSSKhMH3kpG7zPE+IM84KseZGBFFN+5NdjJ6qAX9+RpkLdnfM52PPoLM32XXvT1c+3Pt57XvyIRhGxLnc4+1w/oK6UZmA14WGfkw8dQfj0/yNjtcOKzhXZN++RifxuTvuPv+ZByL63FaJysADtunm+w/+/cPh+vE1ceUHWBT6G//+tQVnP6sbTkDVue50vMV3KZVA86x+boeyW5rrOdc1YHvOlnbr8O3tq9VQf5E2M/RYO8Lzo5/PRKv+Xy92he5/dxMn4LQs+Pj0jMfHszlZeVm4MQbWpZk8cHD6FTFdFLfK283xBI9GQVc8XykxYSVzHDy1E4gsiLVRc3oEtEUxhoIGcPFAAlbT1oEIPfRm/s7ARbvSgs7TaPwt9/zhbb+LfF5un4f2f+KLgRs50lrw5lRui2yToVuhtJ9Exi2E/Gkshjs+Fn6S5lmdYDCxvOz40tupHDGd0gvXy41H2K/31D2u9sqXzs1nv9Pf2YB+aGH4mvJoUbqos2VkykGFecOSCyQkMhVHCOFT01OfGfhRCb86AmfA694YEEQ1rqnwKYzgC4wOpfBXrqriOY3ok7AYYmNnjQTTzq6Y1m26//2G6FZlSxnefij2vZxNqkOqtwXjoofvh+vRaTJjhQhSXfdKHIsRrRoT/nij4ETtIwivlDI9eyLZfDXhAYRnZ0iDUY/ZheKVav/w6SGMMnGvgjH3Zc+G3g6zLIo9LR2pM8W8dIMLae7zvr+5QeT3EQAPjZ397Z/8Qru/GapA5q2CM03Hce0GTkAxxlalUsCWFPiqoxRX8MsII0pg9foupJKxcTMhmdyIFKnl08hS5qSu4C3MvY1PE2GTijsKyBTkxL2ndSoRAujStzzmkQpC8lRoMX/zdGffn0HkETEANWB45Iu44J3e4L42BHYP9AYimyeBLT0faabUi/rHpuTgpFJREw+efr9xMwbMLeqRSp9o1jSfaRo9hTEUWlO7598GXjxFnr+rgkIowA0nkdVKLrckcY5HUoFcWujdAAAboIalyQ07qvte6PiwVFgInCXA2ZmBZ1dxF0eZcD5pZDHAlufTFSrNGI5wBgmjrorB8BAzfI0+si4oFJbaVs1oBfV0Sa58E89moakcqCmJwvBZxp+f9DDfOLCVZujhOl74zd+gsa6HfSjn/JZpPIziO3C7GYansdvAkG/RTBqk5o33ogft73jh9/3YeWGczmcsp9VSGhOZUBE8iKjXFSVo14y+i7rSYEubqaoQTwWe0Rk6/2W0LHlGA0d1MgxPWQFZypriooKtbyDtpvgKwXYMQ3hDoNpAtJliDQvUPY2XtqLrgNXdtLOeqafbgrYuWJbFVmmICzdmUF/W5uk5yUpjNAWrlDqbA9wszXjvNsYuijE6pHdL34uOsXUs3LDymvSSmqW9bG3B4ueYuvEHXTbbMY2U4KaGaFhSuiMyBZ4Wxj5hCPvfbhQfOs+B+P6EMQ0wJyZxRVHcyxmB5RAlRicWN55Pg/NM656qLvWa9qoYRODeHX8y1rZgWRqamkNC8DV9DPQ+sG3d8InXh2dikCyeCl68NjoMv2Oe33tzLT/OsQ7nNf3MiwTMItMcxzNEQd/D+MiuNI1IHoJqm8ptNpgabmBMx7ZgUODYSgOBWpkRYrJa4jBBrnvJglD0A5T7ZgpOOLs3+bZMARe8nsb7NOnabkUq43uAlRdyItieei1ldWebvDdqhqti6EjDV5x9PWzRfflTUesJzzWehoPJO1bejJMP2pWMCbwx2dlp/NiTgd33aYAC1KPbrZyFlWox+iapGLNIA0qaBgA4+RmJlPHxEq8nHs48BC+d4f8ac/IVW+9WVxyAAyjEjRVVpZv9F36C9Qyh5zkeN0w1ZggB5LRbhoDOK3rvWGnFsjQ8PLxGo5OfQ0knvDBiKsxwduYzFlmwjjVroY/IUKGwCPwo77Jf7rk9hb8OZ8AajY1mqZcXT6tsfHDIQxOfhVNeGJ1BjDEE123D5XLFtl2xdTOAa55tuKGH3PhkcNrHgPaB7XrFdduweeR5dxwpzjsDZiRkFjOKq5X2uV6vkz+nOscB0nkOQ8msTGBFRuvmUVEzgFJjjA5Ah6f69zJDjgHcldZ+9QwVhhYlzyiJjYdBTn8pRaswcsSLnZWGp18wfjYMZiEHxoH0ORiqbGDIrixH8H1m+GGnY4bA0pFSo/6211FWzNIKcBwTDlExzERfjgXdYGjraZe7O+flqchzrQk/gSoVE4fGuLI8mRvBdAdnxkNbNza3NJgQdrhpNqMniajLGSZxR0FoOqzPqEW/jwK/HznQ2hP2C5S/zewLMib+kA1ZJxnD6T5R0gsPkkZbGkRH4nTySHUmS4iNRgALyEvyNDQ0F4DNkdB2UoefV0aWE1NHyGbYdZrJzWkgPJraZLnWGBoOLzLMCV1hZ5cZrEaKRKxOKS+2cObYbXulYo6Ay7IiSjxMBet0mGNVl7u8/NYwfAmnzQKPSHceU4nQn57QHh9sLml0Md6ZQuYnO6tWP31BGx0iPMUAPxOqZkRe2mIyswou1yu87pefZXZabP211nBqJzA3LNywMIO0o4Mw+oZe6e4ORBy4XMpLKCN1PYDzMX7GloieG91hiyd/T3DcA4gODBJ8ev8ORIzx+hX4lwWfThesy4pGDXRiqAyMbrzf0/MzuFm099oWrOvJ8LyHlBNgzgieCcV0oLaHy6sF+iQQtkPU5A2En0zekIGrbBYj4eulZFkKWJq5FvBcktRKkC156CvawjjpYtmS0GFBARwJ4xAYRTDSANtVcNWBRRQXDrN56AelvNGeVwWuOpK/IneSYCKcxWC0EUMUGKS4/jpw/pkxYIZs14zM7WVzsLj89h6vfn4LiILfEuS9vUOC9jooPDfyGuiEoZLOfOEyrW7EF0QWMZcuHT9N7O1/45xnDyiwhYmSnSiRZ5tT0HRiQvC4xdi/w+HTKQHlemDa+SvS0S+/azgi+a8avxe+h5BjiCNzi4nrvDWd/GIdfqf7jxTV4Z/avtTdvesGwnd0Il/RF8GyFliK9TrR48SdB0BQyP31owmdDn+/1L4546vee2P9RQ2nHegq5WdnguKxQoqnEV0LaQ6Irb2h9Pkd7ZsVUmXA/6Zmp32O5LGsX8kdk6Mc8Ojzw7ATTojw5tXjNEdAU8+pIpnhpnlgkyavbLRAXH8d8mLARwWr4JPYmTVzKgJenc6gIWggCLm8AsLWBhorgA7pV+eTp36+ZgGxMYVM6fg0eN0bWI1sZi/AEX1ud0OW+m6o+8bm77sHq3fO7s7WhnhUM7OU8QW0e3byc7f95SoT73RfeSpDTxD/cznOdBfy1fjla+46rkDl7yvM053vuHP9S30D/wEG9JeU3wqafKxfqMfsuCRbH3g4LegejfV8veDNq9fA8zMA86p/RXYA1x/fYPv1AwZMr/EIq5JsMVUWrf4Ayqj1eFukJctBJX/tCIzmvS4NlREqflbgHZtwT359r/gMDmMyNZMwzRWaDttfAEsFflCfE80zquV6ZWpehroQgELovo+G0qi1O9z737+Vnh8bAXgA49mZuacYkl998rE93lhejr3MA3pvNoawde6pT39G5AZyOT6dGA7AdC4IaLhhR/TOugSxOo6+jGde0N2zM8qe4v8vzPDzLfYsoqz32GoeSrr5bueD/fdQIHOml4ud2s/RPOwppu8KYM1gbOYGJleAu7HCFBeh7JnrAXXlgQpEPSo71o7i7dbX2ghjzJRcUStrGwKCoPE511Mx94kiSp7cfB39UvH2iu8EIAzWsYjMrgQmK7W7mDFavK+9UZnzHervpjRohFE72Kv5fNwtol6rrWwhQizW/JwRnbndBS6pAYtHJaWBa2A9nUDE6V0+xoASoanVhY4a6arkHpBi0WUBX7R/X+CoY313q54DqCzJTBGmErKxhRKJp9UWN26e35whqnj+8OxTI1j6Tl+Jk0IvcC8qgm6eHhuasBvCKSUjZ8xERJyHAj5qU1vaxnmGxPOEJi70v9XbvWDMCc+A0RYH6x2dcIezyTjFs2GsqAfW8ZTGu/bPpA5VC+5OxKXlzO53JMcyoXrH9Hxvo3sdxhmeKG7PQ2QEs+91+L5U3OkGQWi3NQlnIY8qVzJFcR8D0osySQGSMKJG9I4Bb0RuhuYlshDYc34Og3YroOz6P4dDG5EbD5UAESzO1BIIrCFeUxrEw/jErYFas5qc8JqT7qThulsQ1L2VneHGbWqmyI4SkYpjbHmHFGcSdYJLTGgrY3gksIjhPat7LJZatDXLUrFyRkFaNhf3euaJxyYecHyrAqjXRJ6sEaZrSRUcA4PYHCYP9plWYFt3MDSf04QXZP8x/6iLG4osdiUy5VrWLtXtMF6n0hX1CjYHBbL0m2Z43kzharlL/f2GG1uzVKnhXNB7ny/Kccf6JMErgwlDOUeCAp+Yn4lDpEsa2FQzejf7C/glndJ9MO2JPsoiOE20RwI3+gFkAmQkDh0lEtLmy+V8Be53Y9tuljtAQVX0TboX+4qMGo/1y9H6Pu6QTyDKoJkEkzdiQJ7mFoijYnxPGEYmTM+tijHt7ehz/SqtrvOYac59rmGo1OLsp3GflDFYG+LZMzykwbJgGN9VjZeqChaDO/7GGEIAACAASURBVLArcQPnaRihjCcJLqnMInelqMTNSJtn3pUvZwaJ4zPnZ+6Vnsm9gyugo6yF798go/+Lu0W3Bwaez47nFaDNYEJX23u+YqUFyiukC9Z1RVsEbRVPRQ6ormbYE4GqG+PJ8HDzuTSY01HgY2kb+hjpOLdGtgqiWTe2tGlEnQprAEamSrS8RKYWqJtzrE/LnFL22K0d/XrFtm3o24Yhw5wRIvzZ0w2rWuzlNEarwYwMM0zIgI5h/HTwGH6A1LPdkFrpCSIGC0PG5jhEJg8VsEwEK4gF4290HojA20GnAD+jPSDJSrKpeA1HB4iJqyz1M0ShrNisWrpDC0O7P+/ZRDK9evLWNrfgS+O8E4qzdW5d4IM9jghDJqNl+m1QGCH9PDCXU5Erk7zhjgbVz4UtO8KPwhSXgPGFBAWaO/DIdDiaZwg3fGiMZFfP2NNCH40wiXrKmbdIbIGo1xT2SFiPs5/86gxMxzRHBXTZROfnOubA6/t5vNz2d9CjG8QB6CNBn+y61UZ3eHtlJ0vZ5MF8HzVzIPIzrAUvh+y0vDbHaTtT063VUmMqloU8k2LDYJM1iGB8Zj0H7kBIrVk0tTvZUeLHgEWGkiQ9HWP4uR0zkxJb1BdzODi4vMeRAQRojbycgdNlqEudOmkWFOjDs68MdxruyS+u6+L2yQXKjyAQhhvs46y089mjvS+Aw+UQRfOMLsasOryJlaMJ+dZKKFmMb++rpYRH8F6cMjyIvHY8ci1RePX18RGDgP5kukGlqyeAmPCf8ILgSxUhhwPhe9PSiVa6ZcZYmknn3XEhCO7oYBk0O1lWp23reP74EaMzTqeOlVcsbTHcR4pNNkAJC5aUg5SA4U421351B0PD0cSMBZa1KXhz+tHggQBcP1zBeAPBEzYQGnWbBYs7LZq7cQ9+tsguSoC25vO2fdRhNKEadJHPGb5DyMlOY4YKZHRzjoTiLPDAAc8QSnHWb50Xp/vNNO5e/dwRKR5cUzXwO7bffgT4EwjNcZ4hkI/vfsHKP+Z5fvplw+kny0Rw+vlnKARP736FEHbvFyUQWRaaMC5lKEVB/1LG2X7+Gf39rwgNYbBfiXcP9H/fjrzOHiYDDwbOVr39fsTo2PU1cfiO3pb1Pf6uhz4EZgTfpZMvosa99ypmDfSPe0J6ZIcQSwvgJXXz3XaUdo6fv7UF9c9ebgxst99/A/ATQvVAh/vu/aWMJr+Fi/tQoIc7PtfuG7m+8FQl8MA847t3F+DfMzI3d+Hm+dve4lG98/s3ty/J/n+xdjxCDzgag+1Kjxua0SJztqs9WOPWQAA+Pj2bs5MLpo0bZFjJj20bGZiRMOJ8V+plVRFZQ+8cc0zzKixLnghoYZyXE9a2ovcNTRlNHA4XBnXBUGAho5XNGKhpJwLQphSS44rTQbCyJIQdBPrgJu6MD7uxvwT2Wm7+hvaNt98+T7dO9Pfu2X+n3d+ZvUBTb34cV9yzlLKyxxOoed/tCTwGoxzf/SVD+ou4nPbXj99v/h6vv3B/fS995vvf3oD+vS304kvztE3hIa6exhQAMBVUr1+/LukpzUsMMHG+wQTQ5xe3I34r0R3Rdunb720j8G7HNCimQu7lZ/bf90T3a45vK59fKfDpu078v58oPSAcK/bKhyOGfIYRodm+JG7PtT2yKwTMpAAHRuElOv1l9vjz90xi9dKYPwej/4r2EiNJh18j9eF+AZ3nN2PU59hBsj4iIlo8NSRxFWwLaU+FltU+q+dM/g97b7ocx62si34JVDUnDfaOE3Hjvv/T3Yh91iCJIrurgLw/ckRVNUnJkr1sLzhkdncNmBI5D8yoKnARBOl3hqStZgY3iugJQBQNBIAqoh6z1QUGyHISDMZyGf/79x9gntJfHz8LvBLF/RSGsA5C6QW1AqJ1IvU8jmemKpH3p3nGZV28T0tPN9Uailkz7hFhbRotYXtgjELaLx3VbkeLCUgk0eumQNRMeLCoOpIMgIPQA4hixD47q8UbIuqE941wrEaqAUDSn6O2nxmBbjgivGZTWDOokyitVXmYsYLot1QZ0E2RxG48X9sadlplPvcONt/WgpWx1NJJxHDlbvQideyO6YoZ6mM3tneMxqjvGev1Z+3cv6w6uPLYN7eB1B6+b4VQR4mkWZcVS11Ql0kjbEU52JqkkWaNXKhq1GaLfqnF0/MzBxwZM+pR5xx4L4xJcMOxKUU9sg2MdV2AUjCVWSOSAJSCMlWvS1mLpvMtUoCBNSJU0jOK8rp3RkFHY8JUGDwxLHiwap8RKa8OIIVQMIPAOJ/PXpKgq/OJO6mAMM83WNdVDPiFUUgimd3rVZGGOZ2grWCuKbpOt8aFuHHvBPdaZG8WxfXatv1uwrPu79ZITMlI6z9nLKQOSKV5NBZrdG9vUifTSv1IOjVoNKE4b7hgO0gGvOnRvuebxErKKdrF/hjKMOcrGW3E/TiWTl1shwBohBJCAWveynBDt9Ei9iF3YjFsEalDUjae6+CUDxDSzsrj2+95TIScbikrLfPKxAd+M7wcc5B5jfcYMCs3pa/tS+WtY/q5zEvZO/U+Jy65q9QnGa4ZN0eOII2bltkANqwzDtC7I7s9cEUeY0/r6Kt/heV2PsjLuSgf04Pflr8zOl8E12QD89C/Dt+ux3Sc15puJ42cBQCphd4vHZUqpvtbTLWiP0ON3w2kkd5ECxgN4NtQLHB4+BeNCLXoi1KKlAGZJnCbsK4rLuuqJYrCmdKzMaSxW1aD1pNDAAGlTqGs6F2irNVwAXWaIo2WJdW4WbRIbw3PrUn0eGuR0UGNIs6Q2arZmPRvTtnawZ4NIm1kgFkXVVcvDa2dPeJMYIbHdOEKg4PBMBts0ndpWYrdtAP4Ev6sgzQrnay7GEgLTU53KfejaCNzWHvwjbXN3QfFJj8vdiH2m/3YBmbOawm47MJxR1cHhGvz3SqwGJEGnDXiXe7Q6PeSeuVI4+/R5n1z1jb95GbUoRseHSeTKAjvUN8RHmXYGrytfQ+VH6gkAXRX0J86yj2Bn3Qfv3bggVDFf88SKivzYYKO8t3m3AagEqnMaLygZjUTjwqRG8XaCRQp92BpxTMvZODTwV7exbPgmEzq8wgHB1IaKUbdJk5y6oFuGcfkEeNLGWByh4BMhypBN7ZLNgfWc2VG26bZCKARuZWwtBWnWn0WTIRaA5fYxKa7guVJZkBGNxTvDeefAZDI25GRRBwJOjPOywW8LHLWNZU9uEhtV7JtUgMwC+9pFM6yDZA6GoWrQ6Zr8Sc8ce1syZiFgY4gBnJAj7lxlwjvrhiCQVj7iuflAuCMwgXlvTge+Slm2dvWG9DEcN64oVZxEF4XKaXRu8CIlG2oIBR1iisufxB3cK0KiwUVjKLlm3TJgN4SlxFTN/pssIUiOGldW+LVJP188GzhhGmlgUJ+4FgbMieZAxrEETx0wJEM/A+BcCbR3zYABV9Q3KEvGgNY+bOUaAEwfyRxLmGt4QvNIsZAS5kdG5OOHxptLgYee6dBhbgJmWTJqL9+RPvXvxwPZt5Epzj+cHg90UXevIPinkxXrhvPX9ZGZNwYRpkf0+w9jxRG9Dc/ayz9H9iOtRbb3+K7wCGlKPSX7wesFvpRO+JEIn37z1+aHeQeXLPDOI6GN5Dn3xI92LZrq/B3aJvV9CUqm/sI4rK88jGGtDrmLt4pze/Mmj3MHM+275XmCV3p9f0QB1p5fyHhPyoKJioir3R10CXGsohDYiFgEo4IhWOsua/gItlxOaUrwH5sey70b97eeJgG3P+zxvLGtu3/Z37/mxvQ44j8++kJv9Ad7u/vUIpEQZ0vF1QiNGZlagj9yxfUD+9UjSI1tr+CcYIQvRnAexWI7kBaa3t7GN8AYjvANYFAEQLpb68AuCNUzr+FF+ZrQygM3PzyAe1fn7yrjwz8OynOrvU5fk9jdc7UIjS1P+d91aNpc8GYwHzvtzQi4Dmfclc6DJ0LY87Jq/Xa5NIQgy83IUfnp9tWfA7dJFW9e7+ADitJqfcScvptDMORmBAanC1BfmvbxkYMgsvwwpffPNUJlhouIi5C+OgWHWXnbLNhppi0lDNRY5ZcISVbMcKBpGDWeZC8d1IF59IWvLt/h6enrxKJyRBv8srqDhZj6M1qLtrINd2SKqOKG0xkbu/ef/D7VN+B9x9+gaXh9XQ3peDx0ydXrD58/Iivnz+FsGp9Mms0lio8iDBPE8y7vWgUal4LU0yfTjPmPgNqmDhNs9ZGvrK3AMz4UAgo8yRpNa1+Tcl1nTXNDxhJ3+uKCYt6tcgMSeMebKB/trqirA4BqVTB0DTiej2LoF9vRFFjiqfmikS5PdJTLwidL2nqQ4AXoBCjPUnEGs8KVyz1KeVsd9BsCiBTRrKnf2xdIkalrlADt6Q82I5/lHDdAJsv2xoOoobXPtDnLKV8Ia9ZmZXQPRkUDZIJKaJts7ZHCtjd+rNyvAfNsNtgFD68c3ziVXzEdi6dZApuHpwDDCdbz9Fy2RAzeBhG9DUkAFTRUbC2FetaJRsFs6ZSbH5emp7bTkVS+qZ6uB0SCRzkPaKSWG6QzI6G/ZLTSAJNWUmN3pJ0m93pDpFk4ZD05xWlTJ6qvUwzCios8pwBlHoaopPDbjaukytgFLZaZ1GMqkEHzFjaCtb6lKUznptGDxF57c8KqbHKXKycK0qpuFwuqBrJ2bljbYSJxNAvkS6iWipWB9QMFElhZGSeFQYkDSmLsTTxFPvZYXNhQ4XtnTn6SM+Z1QWrqMNZ7oizZLBotQ+JIira4u6OyCXrm3qT/Spd0kmLTrZJHSoiwFKtsZpnmLAsZ6+zK+vCun8HvM7VFVE3FtN5ONKh4G0sHW/CJ9mgAjCsZEvm79DVB8xwXCYtFpOh9IGNJ2aIkYGB1sXgmGtr7RzUup0v7Z5lT+wewxV5rJtdSPPZ4zs++ExGXylcC5jhnv2+fsOz3a9xOvu8g1kydgYW7Sd8dddoQeNnYvytRSo+74QSXbX3J6cc2Vb9XJTPdfo7lrswxEuEwRFmWSUXeSGJ4CX1QRJDRWTyMVoqPEoAmvFFFmleahXjTiHQTRHtM4y/AJgncD/D03Bn457jiKCannoUFwAzQOJ8eHns4Ba1nOf7Sepfnwn1/YT5pkrUOc3O7zAkgm9ZPgM8a98ScSlOTB1UCyrX4Du1bIGlg61a0x1qAKo6Z4uqtAwIloZ3bVoKpjWUWqNURDIu9Y2hSZwva3ByCjOXdZV0yuuKdVnQ19UdH0kzBtl+MbLB3LaLAvEicHWWPUkzQjEVqaGrab6JJ91pyRxEitO8B4WZ062kl3z+etYj1MAp5UuhAlRCW8NIGDQhxmvryFiAPgPrWbMDTCDqboAM/sz+F3hL8L7x9Mr21OJ0xvny1GQvzHkhznU4eZjBM/j5QNTp7Op34TMzGgkuRrfWjvqOj2IIzmXNWkREUpqgiDGTJS1X8HrMEqlvFCkZugBdT3Wa8Bq49q9HCRSG/a5GUB1u9zUYxxgT2TifgT118Zb/v2762fy+XZgN6u9Pyh/dJ27oDmhfOxjPeust+AsD76o41AJeaouVL3O8RubIrHjN0vMXkYtMzyOGTDWwF4C4gtEE33He4aA5UZwLTpcDlypf36N0g8h9IS/KI5rJI/H3A8mopPfHWbYsSU5z2DJVWIYcMZ5eLovgtIl8z5vXkS9eVpHZOCFyR0HPz++YllNqaNu0yO5SJk3h7vhT1mRdmvKEgR8qFVzWFf/zP++xXM5y3TLV9Q6aKlZ1jKVSMdRwOIAqSv9jlkwSVKpkjFIYLxQZQkxOZ4izKSnvW4iA3gVPLhcsDBS6Qa0zZpayDUK/xfGBAXW+irO6riuIgXUVI7ZlupIatFUi0avmE2EGnhhrA6hOAD+iqDNSNSeDrlF+dh7T3A2HFAptkMxFgpMsS5A4GXPMHYb/hJ/tSt+cp5ODYlVNIjMXMKYuZ533gHKNFyx5Y0AAzsS4hZbyYIX2NCEyxg0dwAMu/1y0/y+4+5//Qe8dS2/gQprBw/BkwKWlN+d0noR/JZUtCf8m4P2//o0ZH1DxHh2fVW6I+Tl64/hu/YzXdxhu0/jFmwZedvM9P8R5LJv3H/1aWOqYfwH2uPZa0/seD+WUF9pr773e1fc8un+Tw83L7R1kPbJh+/H67ft+vG2IVpqFOG9Is4xyn97cx+/TQsY50o8f0+vMVgmL9K1A8udoL82KobIWs4doVgD/IuBB77Eip1X5YFNbnvO6EmGeJVNdW0WX01SXRL4v9j6E3KBjqAAmKytXhD/opq8Z5qI6bg7ZtpYiemYWx93gNcUR9PZ0wtIallU3fpOq756BR7IABJU1OAf+iAxxjf/N8/jtZ//ntyPH1N/UiFK2Rlk7Bo80fD+KgAl6eUzbyPM3D2vX439G+1sb0EdhDPjn41f8vzc3AERx0ZmBRe46Q6LN64f3aJ8+O/N21r8XF1PJEcrThsGQWjv9uzf/PQOfv/PZsb0dPRADj//6t3sw3bOoNO5Y059/b7/K2JrBeXcn808ngoMu4pULOdrhDS/A9sh3JWpXtNSvPP3fdg1ad1uCvHYqKEHgrLvBRSHOYUyFrGRssg+WdrtoCremKZGfvj6GNsrO/nZvN1K068FginoRpAoB7z58SApM+VfUO90vbP69//hxMIA/fPwoY1xXPD8/S/8FuH+4F+Zkkproy3JRgZlcqbBPsSJ/qyqDqVo6SX0tuRyrNc3g60pEKPOkNffIifI2dYwZKb3eW1hids2VAK8cjKtnZ/PqLZwcPUCb74G7EIzCDPA5hEtiVu9yUwoaoyfPdIvC7R19bWJ4bVKjtWl9SB8jcygB9LspG1+av/31+w6UkMzhsXllxf3Ktf6uKTd9ba+/fNPTyzvxPW1HV/TjMV0hgCo8z+vV+7JwxgA6UGZ0kKQWVMMFcVdloRg0rAtRjsqZ7molJiKPsgAAJkncSdCkpd3OojreUDL+6UxhpMkUTVrfvNcOYhGTqVTMNzOmaRYjeqmodZK6uGUCqGBZLpjnk6cN7qWieIpa6dCUWWz/DNbVGaS1NdJoN5nTchFFU63VjT3FFMda87R39ghMOetqYNdoS1G6s0R8rA2gLtlA0sbkDB5sY2aIw0oN5T1Y6w1SR3/hLMmqH7Hu8S7yUMzoN+Mpp/vb96ryXEHDDWLELMYUtSITMiymM9kbGkHLdogil1kctnoXw6mlVyb9vGKVtMCUnPxcSfEGrkNpl04y1RbXa2ogoGS430bK+hq+hMOy1tLXC7vf7JdIa87qkBQRTXm97V8ptPVzQ5Gqwwl++Kg73dstnX8FP/rtyRiW9jTXix/fmRGoqL7C4cghcdOrEmbuCU/tm4OTfznefx8GkSoxFLaTMf6oB0onhzvQqSnui87N6cTWIT9zPGZZt6LG5EjXnpwjKOgwA264MwNJNiSDR5xw1HpnrJcnEM1eoUB4SXGIm+9n1FYx39zg5iZG3zSjzLoWLMsTOj+B+ATms4yvSYYjqdkudEFogRgRWhNDeiFCmSaJFlcFU63VI9VzvfN1XbE2cdpa1xV1mnBzOomjnv7W1GDSLX2uriVrFGbhpOtVxVnUyE3ZnsyYa5BjyhYe+ROHgcSL2FV3EEPGEVpeCWZUMt50BnhRcmcKG3I66nh8m7ZAAVh+aU6/HayR+KGkrOu6/oIvGGzOO0VKP8n4Rweh6834KAxGjlgXhnom+L3ufGB8NUEUka0P7/UYofTefgzKSkuuj9J2oWspAWZx4iA1qpe8xDaCZEDfni92mIgU7tGZORkYrt/ztb4a/nPGyTOYL+nul/nib2pHSOjQOCRb1r8yxHhutEMM6euXO5T7An4SOtnfEdCV8hZRZHdNOd7VQZhU6Sy3aBSw1c1WPNy6lRlSKDbZiQN2XMY0eW03nVG2IC3fYFnP7FlTbjsfwTIXd8ojo2m2i0BOCStGYNJoekZrK9Ym0dClSHCK84B5DwnCW6icAj2z2DjVuVxt/Stf4jul9L6WimmWzCBT62KgZ8b5+TnKvUAy+Jz5DKoV//zHP/D+3YNEW3d5r0VsGxmEliYyg+gh6MRQ04/Kp9sFR4/JgZnVsN3NOUD3AR1tBc58QSkNU11x6jcbem5YTw3U6J5ZjJnR1nBwlX0UOjQpPWLWPa4y0bUBzA8gPAGAO2Z125ODmRt+F1Y3ar9z71h6KuexMZ77XoLdYONOX4oTM58PADOJXnIIFHK2JiMsWZlYKqMC8u+i6/agY4OepeBcle9FB+PRV/n5f89o+IJWCM+t+3LcgiRdsCJfMrlbdT8+RDtfYLxjiUS/4BMmABUfwMnMuZXrd3L4cP34Hv9t+P0FHMrbr8FDDbe8FQfT8Vn5u7Z36fMXAO9/Uj+fAXxAQDwg6eL//ZP6+6aWznUOYHjLc/nWv6jt/Jtazrn0XtlLw9LOCzBcTjqB3IYFyI2VCpqVSgJGPvtKKzB9cAEXCTiC6ZeHZ814LryH5mJFLQWlSlbUUgsaN6zqgHpSiAhn17GZFHnHrFRq27by8HX5+PWrf+WWZY9vafxm9P9XaX9+A/ohd/qGx4QbdYOQSZ3rsqJOVTw1ATzc3uLTs9SteySgfPqML+lYGbtrCZrMaH53qIzigRn7lkZE+PJGynB08Hnz5Vp6xG37CkFy2dPIRnHPQuw/MvDptaG5W3wSkHw4b4xEz1PY3PuWpryzdm+CocmeSXGRLlxjTq/dlyPg8l6XNKdQnuJwbrTpZ+u5Jfd4TNL3MaJ5I39C47RBMfYsKaafNsOKz+HRXPw9IdAPUWa6wFmAEnmtejoZuz8FMrsKSrYxC4Kk95ITc/t9WRu67p8Yf2sIFJs5aPk0Af8iTEnRaOj3Hz+4YKl6MlUGa0S4MiKHzc4wQZRbGiVgysW7u3us5/MhDN/c3MR6EFCnSQ04hOWyuPLlfF5xd3sKxZtGbZrxZ/vXo+nn6oaKYrUaSfdQUxGy1pevZJWb9V0aaWtj7heWfkkjGmgD9bYPpWgkocnMGzjzM7Tq81qTTce+PMvv062kmzdDXtcI7Ydf7sEs6ahBwPq8gHtDORXQjaT2743QK6MRgIsK/JZ+Vfelq3LW0nv3Vf6Jwr15BFooVEzBfwwGI8SFKWwHLhvmtbcmq6h7Fn1E9gxgjDy3yLGMn8wQz7qHHv3lhFVbj7dmnB3P2jjTdMaP2xldvRJKPRvTOCSL+Agm0arPjUTF6ZJMINEMHtbMsJrgpEXhW1M+prTlgHjmOk3QtO6kQoOQBnkng8FNo21BIC2A2tkMyr54YDWWtS64pmEFyiTZQouc72maxPjitSAnUZgVMeQQFfRS0ajjZrqR1Iq0oNSKdY30jKactfWRGpaCS5oZWlpXhamMeZ4lKnNdNKKdJeOD1IEUh4JSihvIDb4uir9qra5Q653BJLALKh7BG7iXDuCJJFLOFfqApA7tvtax9ccEKaDXRuLQtSHh7HOMMfDus8mTfkXhkUqRFMtqTM9K8dyH8a/Ga6DIPc0cNDVC1PfMlN69o0wTLPOE8aT5vWNflM6rRkUBIJbSHnDvcTiO7yy1u3svsMhk35/t+XYFpvXvCDv+bMYzRiYantKU9eqcBE7847AHQl9LsTVEpBf3IsXj54iGyMK7I+jYlaufkd4li1CnGvcReQ1Ug/3tuKVWeAuir/jN+ObBkOcd0jDvLRcpTjoSJSg4M93hS25rPc7HsygYBufYw7zBbuIjHWPJPA2pkw0rABVwW20D0hDIkbfxOVHn3JwitKb7SU/gxfAlh1OJ7yOBNUsGgVF2K6N7jgtwuRHjEi0AxHEHXNHPDNSOxmfgTpyR5vkOi/bRWNKlX9avOC8XrYF+DlyzCu4jdWayGrt2vWumqvl0iuwatmpEoFpRpxmTGtHl3HV34lrXVaI7q8iya6kCA5ohxJycSpE41QZ4lAEzo5PwqkLHzJgAT+lNUJnQ8JadK6qgMrmhn91ZSgGH+3A2iBDCEQEwPpYvIKoOmx0NzIJ/ZB8lQub89KjvmxI8AuVU0Bcx0tBiCXB17/XcgNIZN8hlw3IMbh1UV3QmzCypeUsXo5IZjo3fljUoqGIVBRc5371z4jPiAKVjGeSCAvdaZgc3ZFJaIx+x1ZYMucp5COQORnbMJSnHq4EnzMFYIoZUcCECFxJcvuXrjH6meXXdZ8BwJ5D5TILRNaXHlGghxTM+If+T58kAZjmjOhAC77KW4FUHB8NF2/usr5EfoFuJQhfHRJl7uSP0p1tZNzwHzsNX8Fep5c0dWL80SCmAgvkd0IqU3eqcDHqFQFwcV8m6JSdCYlCL0lq1ktZYHvl2L2+BBBMMcNG08L72qTxEJc+KZnytnRFLX+4ZSsicGxON6gxPdKLp5+VgtSEC3TMUcVdabClYNXK3hKzh+07yW6kV62PDdHePdn6ObU4MVaiMBKMShFZMZcJUJxQS3k+cx1Uep47VHFkZ4KLlzpYF0zyJw2Jb0Lnh+csz+gIUOkGcOMIQyqDIsEEBr0Gz9W9nCD1RUwdbxft9E0O6On0Cqg9igG/AcwfdQpx2KUEsCeh7ZH2SXZg7lvOCtvbIgjcl2S3DeyGAC2oVGs8sOJlrdzpnzvPMllHDIsVDvhT4Ekex1hu4ackOh9rM78Wesu0txXkUltH4Rnlu8WVOO7HjZZVHNXhK+D+3E4AnALdJtiXjE8mkxS+yN9r/ik84u8OHnNVbKCC6rMgDT59Xu6ueL/hRxmcCPjKB+JNGCye+189HwvuH19PaguO+HceD/S+Zhz28IV8L7JN1A1ce8RroV294QT/6V2xf9O/3GM7fYx9Y94Dr0euf9LrBX0EY8F8P0Ds4MFeaw4FB2wCLL/RgfMKB7jLfM/S1e+/bx/lnaiNXt2/vlO5NHz6A/93R6RET4KUjylwDx6YzW1icfToATFrKGJIJZj1LFsACQkPIZfmvfS5UcKpCO5t2dLo94fPj1+AnPKDkCgAAIABJREFUOJziitJfFICJcXt7L9lOT5PTLJM1V2b0yxmr0jCG6X07blXesjxoygU57AVPoGMmx+x/Gxzzlua8A0YYsz3uHIFXWeI/pii4en7/Ku3Pb0D/jU3SCAfAfP76Fb98EDJmKcbe3dzg0/MzCMDlhXdlfuDpAJzsIP+x9VhCcJX2OqFhSO3zdxwHx55+YEuy98obmNPEj9bmPzwSnRm3/UrU/V7O1p/HNE4u3X3nGP/87fVJBFSSy5qHiHmLsA9uiihveJ3p4tbz2AsTADxaOO2RCVm9mzKDUUtBbw03d/d+37KcvU5MHktEDsSc6lTx7v17Jy5EGm2u1x1uNoAZRkr2KEK/5soWwnwjStd2uYAAPH796krWm9tb3N3dqXJD5ny5LLi5OaVB6x9LRWbfSSPN1YhWSKq4m1BaqIJmuFIEZJFV+ko1chOFQs2ZKsRv+yiiY2XWbtO3XNKVloW8tz5z1J0oC9VI6sarHqn5kBy0TK61mm4WKWkRXt2UTPbPBqr7zt/KjOxPTjY6MVRJlRw07ES5CuJKf4fe7EAyohy3t47+R2L7LV1xpm+gK1VhYMaWmo1HMNZ0SzOukQ8x6GlEIRG4dfHgIcZUJo+iJh7PuWVEHnETYPmVTE9khtHWGKSKewKJoj/jF02lJUaVGXUKw3kphGW56DkuqPMEXhbM04R1beDCMONerJkoq1vv6E2UoRGtqMbZpBDkBlWYSgkJQKI00VY99xWgjlLEyWa5LJjmGYOB1/C5nq9Sjs/Fjl/g7oJSKJSyoonj69E+pv8HO/D2szG27dh80K4EL57WmI6e0CnZabU03zq/FH5oXvxKNeJNfl+IPiZPD2tHhO1SelRzNjY7/gYsbbx85wOcwMMzQNRnHYzO/v9w0JJf+vEaM1z53d1IF4aYMHoHrfHrSps96iGzxjx8SMpcXKUbe3iUd2wx8u4+KGxSmn+G1w2OsCdkKjb23eD9bhuyD9/mehXhJtiw75v7h/XaNJu3fJY9pAEeYo9ozDu9E95zf5aVwozoJQHpoHTnqJ/qEejMgg/MwINY3zy1WK8zgCoJIYikhmu/gFDQuQC49flJBDe5o6bR9XVdJSMId6f/VkuaLNqiFGdzTBFeSpEoc3Wm6QCoR2R6JZKIynnCZLWDmT3i3NLVX4gkbW9bsRjc63p0zahEhFTuRYzm8yRZhIyHVtBUIwId8k5WYsj2padawXlfEoBAYFizb2iWgn32BIVAi8ZUY4Q702xrZ3LArZSliewSxpAF6g3syBBHTat/3nvDhIoVCyqqeqiJI0jGWcoJC/3aVEHIM7C9Dbqezn0vYrC6JvQAAy7cHd58yPMLSLNHDOdEH6Ajl36lkyZTFAJZ2QsTyjZ9+rwSbfHvNmQ9/5xlO7UbxtaQwpmuzQ0B5w0W4gO4MDjI6/CGFm/dYpxjxMhP1/QUANFzgqoYCoMVL6hxGB3MVfm2JmXKoDIVAJj8ZKPQPWc9tyt158VGZ5QM35vppHGGcZ4DLxMSLiWXWww2lfvzzOlhe9Rzban67Xwbr2WZilTpbSnj+1DVWV/4grODyNYSNT49TAIvl7RGm7kSkdaOJ6cVUIduEDz7UnHHpc1ud8ZlXXA6zeDWsDJj7SzlcQDQSfs+25KnQ5vx4nA8aTNOu4/zTfpHjQz6Hi9plgi4yBes66nPFjYo8teHYZXV2bXhsq5oyyoBBupEW1h58gH3suA0hVfmKPXUmEGtwaPLc9vI9KTrLLgIUkc33ecLc8CLOBvB+8t08IibeDwX7f4h51GPnlf9ylmJXiHGjb2OgQsRbiAp34fX2lZSnHsdEIyXqvFrBMYQOX13EALjHlHbd+iJRzy4Y0PTdRtSfN4vSMhE/kvQqPHX3bNxbfvOb0DC/2279gILsGvXjN6WEv6oPW7uO6Z2v7EZ7sHLL89Ogt8VgQ7s8Y/2/3dt7dMnVLxT3RKE5gG6J3D63CAuiDcEzY6h/C2AZV1wvixBPxmYp8n1PGZMtVYAnCYxtF+WVfgey26FCMIEEDwHEUoV3XEhwtpW3M4nTLWigiSFvP9HA64zRy0pbTKC2L3O81EZzeDTx+//bdFeP/9Jlh9a6FlGXvOvv8Y/wYB+sJK/RzNe5Y3dupc2m1eFMA1rI3Dv+Hq+oPeOm3keGJJzegchvLiugUqKaxMUwEEkvg28hKRG9Nc3tu+E5UcSZPRhw+NvEecdi5H9tea3JKYt1uN6JHq+L7fvPaJhLAphZFCIbJWkLITI0is9Dukn2STd3fO8OQ8x/+ORHzHzx+MfPx0J9X/GFudFlO9UQvFsSm4gn98QKIU2HghyrjAQpqwzJM02ww1QNzc3eHp6UsGb0NuCMk1Sz5pIIkeZJe0WFZxOYXhclgtOpxs8P1nimMG0DWat1wl4HTJAouOBLinioCc8wSERST1IVWjUOilTYsxHGLd1UUTcUknv3ccP+Pr5s4/FfMdaEwMuKVM11YplWbBaXwDmk6R2XnvDPE3utS1pmC1qIS0zCspMWqsZqKWCakEzA7wqhQjyt/Wmw1S2Ss+R1QknkNf/C+TOrrmxCB2dGMygbzXcLqtZII+VMuslXKFkGkIKl2epab48iSF1upFSHm1dNZpcar/RiUBNvB8lAkTG4Apdm7dKxab0tbrnOeLcDD/WeqI3Bk1sCqe3ILyRyxyUiyZMC6wUcIsUTYPnuDPH+2cp/fXuEjDITkaGjKFtvh4Jbrz5cby+XYADmmCKaYOVRFfIhqq/gwGiFcCkF05QRALwxecvUZNpP0zB0M7aj9QelOjGgIHtxLoKKuZwUuukZ30SRZjWEaeeDEGAKplV1a3hEOJ0E9wFQJhq9X/MEm14fj5jqlUyH1BTOCVQaSioqEXqIQLA6eYWvYVxCYPCXmGYu0RJQ2r8rhpl1xKsMRjrsmKep53QwlY/2WHLzotF01rXOYPLnsIxN7ReYr0x6i7TsiMbCQoVuHFfU5eaQcFw7fYMMiL6eFjzg/OYlU9miHEi5gaG/AAUDpVWkWBhUny+pfXDvfqrZ4fwvVKlsNIIT8XaO1ZmjSyydYZHgAGmsBxXm5SusNHgpHgf7nN+iH2cIw8Tc/QU3GlvWYUxW0Hb98A1un5J6WL9hlKUEAlBpcawZXPI4zhyvPDI8924U3MYUEyX7ts6AQzOBf4sOc1yJUC1dL1yo0fC+SYZfUn7AV9m2QvHw6JUD+AkA5I0zuQQo/SUgci0k2Ddn6IYLyk+HFNKDzO3Qfs4KW3kkGYXLA5kg0Imw2K8majAFPExF0v3Hfint0jZbnVesxwndjsOM46eJ4soi3hOwsqWLYPEkF4ji8gKxrk3YF2BZfX+pTRLQ2OII0wtHh1ra2fsDaOj9Xx22YBHjPDrCig/uJCMpyl5IeUFJ4ra6KUUzPUGl/MZX8/PWC4LLpeG9bJgXRatk271gcNY5op8Zgg/NIH7GnwvqzG0aNQIM1gN92WaMZ9OOJ1ucHNzwjTPKHUGrxeBGyROLp+rdP4lI4vxtiFZh8HZeCByXhks/Fg5acT3Re5hAKhAV147jIDWLfnh8Xq0BmxGLxigLgYnSScpzg+1FHCX8ka9dDWdV9S5aFApIx+LONeWOh+x5obvGGBqajg1/gOaJSUbJnUuQ2aq8SxJdqfIPgKGl/gQ2obEw1EYuCF4Ib+tAAlucdj8/JFtUdAllNgrMu/ZIhHZxn/5DWz0ZOMkNRPoYvyQz3IziDTodIzShqffyC8ybDPyjCFOjhxrap2vmhx0fZRrpwepLlofCET3WL+EOUPueNRzdg/ignqr2YYgGbgKEzpFFo4OoCptLVqTmgBdW0ajjsILmsJPN5hQGDEDMds5qRG9TjBdV9eMbfLPSssZ72NR77a3gPKjIZy6zGr0JrYrnCiYBBahfKiBsPR6BEzkqeTztpl8IdH50HFaWnulY8pL2D972NLCMzNY+d/eO9a+ovdVSt0Qo5FkeuIiuG4q5ngDrE0dAJrUDC+tAjNjeX72cWdgcxDLAEjb2+KM+1IYX+OPh/GJmGGistACySJHN1B6p2U7iqbd7VAY63HOdR/WxliWBcuyYKqzZHFixto75mlCrStY5XTji32viYAuGSnkKBfXDSwkLshnwzlKKwyWhlPHiR+jgAdCBDWBSDL9lSKOY5aZD5k+O9QBsJwc9juBStoDKOyI/7LSHXK5w9Z8cd7asiJ0PCuc3+kzZwCDVxkwrLOtFwehMlEDVdFJuJCwT6QToSidBTMagMrvUfEFnRl3ctilDjin9TR40UPG/lozYQadScx0LAz7/4bfePOFY8RxP6e/NoZhb/bt6LfDdo3o7F745je+7XXfeP8Ryfnefu1d14zfL7UPkAhze8cD4txdi0i3lPFXcl1qe+M+IK8Fj9vih2x/L6V/NmIioPDI5/AADyOcDY33boF/hzYrX7VWAtMXAOQ2MVnfW13dJ6fD92A8gT2NewHhBCnTwWfJQjidZvTesaxtOOPWCiRd+zTPklWzrapH7+hPUuPSjPCGw13210yCBHEYrrVgbaKnGEio6rs0bgIFQOtS+tIMmc8E3DDhC4V89cDAIxUUAu676LY+5cFThrpoL+Gv720/Ck/8jJbZZ8NDBXldWGn9qJMx3vhb5vSzg2J/r/a3jkAf5Hj9W4jwz0+fYV6p52VBJatFTCPj9z19CmuKA7/CV9s9aEcEX0pz8iObHRjn4dPvPj5+mxFd2vGYt4qO37O5km/THjQ3Vgdj0mE/Hg1x84Isl48Mwsgo/bcFTNm/7dpsv4eQEjcUVa4SkDxbwqATBjPzbiR/19PXr6ros5phEKMpqaJgUqMw1IjcF7QlqsacNZ3cMHZVHJrgZMb6j798VDwAgEqCeRUNTfjcECVR5E2uHCdN+0wHDIARvHcfPmC9LKBCeH5+xvnyrIYLrX3JwPPljEKE+TSLIc0FStIoJGFuCBzXtM9I227KL/K65/KZRfBVhQ1RKEBkiZQgk6hyJKUsfK8O2xGXk9ra+iEMXWvDvcoMXOuSwX7dPjN3cJe09KJkKsCJwZeYQ1bsd1XqR73IJKaa4G416FxBlsbwAr7PXufbeWyfcmMIyOmRGTavvfvoPbv70t/fiuN+3POv0ZU1EbWb3VveQvez8Y8tVMfekJSYchyk3uA0ay1BkmhF6kJle+mDYdjwCCCCBF0Vd8n7i38AawQUmhhESDMl12lGLaJQk0iR6vjRadfGWNVbwwox8q2akhMgjzcPZRhhvTTUqSJHDhON6UV7b4hjRbDIKKtve6xEMYWQmEqzE4oZ7HcrQ8ewGzCvQvfmJvvamePbcG7p8P6Xfjwy3nJnD5ohUmeco3flPq2sBja8E+mp1hRpZiD1hZb8yzGWF0A7r2fY+PK+jCddYF328RhVqfHc6JDxsLq+vjZpTLmHGK+Mywzf4TCzEdA4lOEeCeVjhfMRrkyFGoQ4+s2KG94OLo1riGw/bNv3pDkdXZCLB0/nT5kmyS9ejsYnELDkdhB7/tpYd/v7CuHdjM3oGEhpTS8e0Wz7rJ/G2nraFW26tLf6CFgdnxGOa/bXaGu33/po6M9ny+GPzNiXopcBr1ta6AZUziK96Xit1jktF81uJL8vbcXaNAqjVin3QlXHoVJUOne7k64R6lantqvDEgOSFaQJ3ita/32qVZ0Hq5b+mXE5n3F+fsTlcpF/ajRp3MGtidHJ93k8v2BoFoxRWWaYWyJHqq/bPM+YpwnTSQzps9ZsZ6JQwtjecOa+g1bBDGC1AjzSPzeeDzDA/sfppNKM2MPilCk7Nw/03OeXeZ8clc6e0pz0LEH32qPX1ShcSkFfG1gdSQ257DkxchpipVbAMe7t3UZ6xpXLp8Gkc5tOGFHCMSt9h9HpiFjN59HwofHhjEjdmLOPWH9GDbv1A+E5dpBdCOgkKTvNd1bvJYJWqDAFnfZNAE4EPr9RayIEAMcRqDT+9UkpPTM04Ujy6B1HfTJyxp2Ms2NNg3cAS6YDy9AiWXtWVCLwNKHW6qW1ZJyEruVybI0EvcteyVKbg6V0ysVKVBnJV6cZS+9uS6E4hFRuK2b0ZHUwygpzhpebIK3jDmaHf24c5Q2anuHW1JBruyeQVYmk3FVar6OTkr8U9dCuBWC6Q6eL4w/jKWqtER2neLK3jl471nX1UkOtp/T1w6mTLEiliINxhzikibK+o87i7Dbd3GA5p5yUrv95AUpp8y/fF3X+EvzoGVDPOfGdJYepxmLUX9YVhRY0z7An+IDD4w5g1hT64pS1rqvIBWoo78xofUUtAnd1qkAjd+qxFTKpkRO/xSzOZ6vyPobPJf182suD82R8l+EpS2bveErLgKR8VsCwXxi+0/A932c4zPQPG1xqNMHwmWX7gvEHwDNdl7zyO24PRmcR7ObcSUqZ7Hc3tlMY4ScAjT5LqUCjF5xwiq0pMn212RrHYLKSERH7Hf57SDPxju3ZG3/ZnNMruobXUKcYt1656Q9o71hTzP9B7S0k51rLKd0f9F2PeDmtu9VG/2ntYEKZC6H0H/x32ggntHmP8S87LuM3rd+fuTF4SGMeJ12CpazEzMTir1UFreFOKe8NSHMwqgVM6dS6Nky1okBKhUzqRNwUNxd11CuQUoK+/hTl+kQutWuic6wa8FSo4jRNqIVQS3VetWv/nRlLb6hFtMQTAeuBDA4QnguDXBlFUoYYgaPcefZt3OTfso009PWWg0aG9/xFDOXX2vSCLn5o374O2xf/py5kYjA6Y9UYhFMlFFYvwQMNkxmS3zKrfEyN8fnWo3uLYPeOVva70MGOKdq3B02NcfPrrwCAp3/+czdvhqYHeamZUDd8D2YRUEUKbH2uR6Lv57Dp5+UhxHcKhUmO6BH8GmN6JMY7Fsb5H6m28va+/IIYKw3D3EYovTadn9/Gcf741zOy8naLUPerodEomvq7aarNQsYsaa1HTQE2eDETuRGdKTzuwaxGnm3khg2RY/oq4Nh37pJWuK0raBKlQWuMeb5BvzyDyOrzkiuDtpIHQ2VjzmJojLu3Ju9OZCsMyyHgm2c9qzKi945aS+rJzpCuuQmCLIaZu9s7nM/POJ/PmKcZlQumaXZxTiLjo+awlMEJL23SepkoghvJ1hzVD6kwveRCtUVAuLe3XifWiHH7rgxbLRGFymBgJvAFYFoBVHU+CjjZ4mY37Ov3UidQgaebfsGyoS9YIZo9TTP93IE51nFti3pVSg3z+X5GAXCxFP4AmMTzX7hUuEBuqdtFeaP/WlOBVSOnGFJH0MRZm5/D4378qjvLSCZgYouHdowjq7JJ1NzbWro+js077Q2MfHQY6egM485nIj9z9H376NhMzDd44+H+0O2Sn4GjSHTD3z7u9Bbic+CVcjJA1/q85tG7CgRmGsod6E3qhXYjBQVU+iAaitAgdcmnOgMMLLxGiq0KSeFeOiokbaURXbKokKwcpoJCrApEU4CSP3Nzc4JFnwj4iLMAM6NOK6bacLksUoKBsnNNMuDroWwkCtLOZuRmXJZV15IG/C4KYFw9c0SEaZpxPq/qFDQqs3wPR9LqUXldjexmMOuG864AlC8jMQgVKOyRsFJj1wxyCVwPxx6GoG54Lyuxdv1m4H/JKK7roqMwQ0+MRbkjt84ITi6OP9L4bAk6oxmsbnu2dxvNwOGyRd9K3AJnA3Z6syOnK+r0usGGdKX42ZTdJfCO2Razsp4ru4HcejM6F+VYAHj9bqUkHGddYF8jvTFYtpApcuDGTMsC3+lS+aNRDyz3N5q48t6Ho4DQCABuJCRVnq+rqAWoFJ+rRP3rSzsN7w1dQDokjJi7rePGEKo/yro5K3IclZ++iYEQHP2QsXjZfUYN4l0iFUstaE3q/871BAZwfj772bLU5nZAs53JeQT4cG27PSoT0HPovJ7AktU59wj0vC8+2ryxGWrjH3rHSoRCEk2NApg9voAlHW1bgEvsvNUiF5w7GvPlOaQzBOXvSuL9dLuZPfKxs0SeV32vOCV09HUFN8I8d6y1gmoFqOH5fMb5vOKyXKQO+rrKOTA+iFmMIDyeUWDSdUzqOC3J05lR1enFomMt689pqriZTzjNJ888crlI+SNzDgLnxCwskdFEIDatm+E4RDaftFNOT2iVwo1dyq/0i0Za6v3t0uIxYoiE2pyOGQ5xXsHfG+s/wANb9jiWXecLJlRUEgdTOc8EoKIzgZcGTMF3SNaTeKHhJUWlDoNb9szGa+Cds7LYiwTdBowx+gDgbEyl4j4x8pR4j+E35+FlEOG8Z4ctav4O9J5FSerr7R85ngUAkoxNwv/LmnSSsZaiNbQTHeMBHtJYMk/KFgOy6Hnxp7cbmJ5P5z7R0nxfbFb+TnFd2/mLmCRu3j3I/gy0Pt8pcxO5VZwUIxVAx7Iu4Folo0NrKLWiQEvvwBx+Yu+zA5DBMqoNW/avajS6Mz4dLo8Z3ba5O+UrBVbWiRXPi/MdO46qRChTVRu+4SolBnktKegOjwKKyOGpBI9JGuI4jHQf/J1C8632Orkjaq0VtVRMpUqtVi15YeNGF2f4hcQJvveOy7JgbeJFms+7jf40z3IvM9bWAW5oq5yx5fyMOp/S2AD/4plVDK7GTGkDmHGmP4gLGQmM4Ob8Q6cziAra2rAsS6SxLZmjgWQlUf6KmdHWpqVFOrgxGi9AKaJL6BW0FtS6Cl/5VEVGKVVKOBAgmshHcSpgzaiGjo6OiVlPoa49FU3kEAEC4ldsOMT43FSGxRyTdP/MeY0hJIgPziDZ8tsaI2cGHSVEq7lLbtLRbSkjb0e2F3kbWJxQIkN+drgNhyxmljwVzLhj+HlzODdcRIFhTJbUO6M2vCJ+gZdwRnjQd3xJuHBvPI+x7Vq696UW9Dc5V/kv+Tqc/mzesHmPNDOa/zDj+WsGii1duNIe+AcbzhMJeUv7EV0TgI+p20+IGucvtU8Q4zshR+hmJPdtjY9gL8PB1T2T3wf5DgHj43dKT2y6+rbh/qnbAweoeRI1qL8iAFuh+e5OHvjaUfEEur9H/ypZch6JcatOnMuyoE4VaynCOS8LzpdLOL4rTRFaOeH25ha1ViyXC6a5YL2YzroMEfBCGeNarQW1TpjMaY+kznpVfNpZgiuMRi/cMYFV5iDcg9CYsKpz4B2AryC8F1M/HhUKug7gS1GbVuaBtL0UmPQj2o9EK5Y15UdBeebOtAOVXYy+WnDBfh5Gm7YjOQru/asZ1P/WEehHbWkt6smReAYfGd1+SxPl8x+H3jkxsa8d6+3Vo7t3h2/fo3bKm+82mP1bTWD7me1aVOHRkJppI+nl++yCKUT9J1Uk/MXwxxva901YeCfaMflbJmrX21DT2dJj93R9IJnY1nywOwsHE0KswlsTI25HwXK5AFTR2hr1HmWAmwEjlNwF+PDLLzARl8EimLryaWRW98RKfpHU7/K1tSYGlEIoKH7ECrHoDAmSTtO8yLUGResrmKs8P1VNmyZG7a6p3Mo0qUKANNJJ0uAQJKVamasa7CyCyFJw0kB04YphaEo38sj1yJiblAYqJG/1T2BzBkgicRJaj6CC06bWUjy7wNsbiwHfK3mMvUhNU41wYKmXhq4pohOsdqv/1yQKYllFgWPKdRd8md0wYwpWh/nNBH3utnKEeA42XjOKbxBXaGw2cxoZSwIOhOI9vt8phH7ndkRBoMrd8dcNXRkejPUE8yHDeEgzNjd1hVUA6mBSLPsgmKR0g0QYVZzmCdybpJDUM8yN0UtB6QAXKRuwpxvhHFCLKKpIcRBD9uymVpxONwIPRVOsN1Oedc1oMWOeughMJhzVgqnO+r5Q3oihWlWdGnlp68Y6x6L5EYnInXsMdqdZv3eWCDT93ZwM+tpC3UjkkekSvw6UwiO6Zqmv2S3iaXD+MOeczbKpEq4YvtHr9chhYNj3vNnhWPKaFuoqrXKFFw+KqIiGlQgwMlWaj83OZTiJ2ZwyvrHDGFk/owbuHn7NoLRZKpJ+tkZUd9KirLjc4yeDT3vO30liOC+1oio9aI3A3HyuaWKbMZGnkC7JecwM5KLs1D3cKRdl30rOfoLtGDnBjeJCJ+CGk0elzZFTU1qAZJzcc8oeGW9v40i5BwK4k6+HL8umjXwyq2HZxmhrMQwsjSXWmGnLo/KwFwb5eRaHMze+fjPH7fTN4cpvPTiumVQFqCmxkaB2BT3po6txWGrnITnWZB4rDTU7Huj1NBw/n2TvUL6FKrlTXl8WKWWxrk4D7UyLAT3gz+nCZgzOE+kYTH5gNXaIMZ6xcscKgJYFbZGU7JKOl3GaZ8y3s9RN74Tnpyecn59xWRb0LiV6ehMDHjQyW3qZMBYjM56FY++YUEpSaqrziznBzPMJp9OM+eYG8zyhlCpRjq2hdUvhzLF3tuS6JuIckfaJeZc1IDscuPAlllcU5lAUpnMiXWi0IaWzYH3TcLz1Og3Hw5aEwep0BYAK2NMDyw05m9KrbY8K4CZS6yvjLVb6xohI1eHZeN2Ar+lIihYaY9HJcbbz4OC8py1Yt44olj87U8ZI4rrhE/nO2petkdIky6JiDJL+sff7iE4EXMw5dwMbiYc+bNtzvpkqDmTBb2mGpwj3atx+8lcT7mQd7jUdu5VsgDgiNxHk3LGlzobU2COOe49yT4bjDCayA4bVyM7ZWABoZgZ2MkS6D9l5yjZqNEaGwxwAsQsrfipUxZ2ZyN8v9wr/0teuuJmQ0/K7gxCJO3Qmn+5gpve1JhnRhE8ApjrpfeI8TnSPMonOrtYqWTBqxSq118AML4PGYLTS0NaG87q4w/jOqZ/UCa93rOb00DuYzQF15MWAfJwT7hiYqiBu/rOdc6WX5GuuJ/KKTAswuDesWLGswgt1Frkyy9aFKsrUxYiRDOjmwN25g5pEiVNrWNemJUHEiX7qEwAW2YKLOB9C5V11ijLnN1GzqOFbdzzzVwFS4bwEgozRyhQgnEa355RMN8JbDuTbW0kUdlbFAAAgAElEQVR7PuIvcof1wZkwnSPLDLf93YEWG34siM2gPzCewuh9kihgGaUM/9pjRWOLB9kj4cjoMtYv88DDPf4KHp+8Kq8c//zKpT9le8/A5+8nBX9oM8P3O2iKa4gx/a1ar58ZiW76rJeb4QyMulzTxyT86w7mHIb0vx40vq3Z7Cd8BPG/h9/ERf0ewCOW5ycUJkz3tyhf7gRP396hPz/hQZ84AeiXBVCdpUWQm0yTO51K1ewz3WFMMtOQljtVyqsIjSDlU0nlhmmaMVeJPD+VyTNc+QSI0NElA4e+r3PBioZO0GwsIbNNUGcRReoPLPq4rxs+ONP8n204/3nt9x/3sQE88ynjuv7VDObb9mYD+k7u+OZ12W72H7uwwqMps6TCtzFxrXcxSJUCtB5OpUoALPpKUf3AxFyb1Xb2VZnetx6Bayzj0G8SoMAvs5mj//L1ZowE/fP/bsbzHqyJYkwsZrxUCz0EcajQsFWGuLLKDUMRRfRmaHlRiE7CoSmojBA7C22/6zKqdPeVnA0+vi8Jh/4cxQ6Eou71Yb7UrrMJPN7x22SMH9ZCYNIzt1m//f3Suua2Mi9wU3ozOCKUELUvCRKZjt4SPImBJdJUSr+msJynWep+E6mNXUandmep60IAoaKeSkSRKAPXEw7pvUvKN6Q0vIj9IhBKmdDXhjqnK6pv4N7ANcYoMB/nwtfG9BiaYo42DM2+ZziDSSXMh0mM2zyv7y8FlQrKLE4CoTgW43k9TeFd6EY8iUSnQp4OkEiiUK0+28orKlUJcrDxdkhNNfihcyGQU4a80ErE2O38kQrXzoCnOVmEnzBv9TClK8OMgRPE7GS1MzVV0cWMdT1qRDOwrlJTdJ5P6L3hcrmAIRG1rN6T5nW+tuYG9KY167qmOTRDuu2XCOecC6W90GLex44E2Qs/C9QEq3kZ6xnVg+W+pA/i7VvgSh7bg1eZ0fS+4xm8tY1viPjHjGvZlRMCWuQ4yIUxjucCV8Nr1lM7x7kjAmgC8wLkM1oK6iQpN6HCg+jY9RwwARZpCoBom41AU8QSgSBR4HVaQQ1gLno27Byzw5RMUbNRcKpXpPgyR+9RmqErRKnIuJIG07NFkETbRRaewE1pwUBQz+FCqHVCqeRhYA4PjieD+BFLFH5DE2UdJqzUcD6fQUUihWqpuCwLWm9ybqEKY+M2OkcZBDalcozrCKBkXiX4AI981zUmWz9S1JScWxz/jIqmbFQ9ahlSd89t781IntJnf1PZjARGWDWauae5aPSaAAXIsf9G5FHlJPv7BTZGvgbpHuFxCtn9MT6Bx+68ra2lKESkn1IKqFSBlxIic+9aPoQ8tme3hsQk3upVFMTGx7MqcHvv/vdojbmzRD06jxzwnhsB6hSnmagSj5jhzBXgA2ej+MbqzJpRgtmjAi0qzAySRo/MacftQ9ZXUzkjNs1xqckkcPpp+5WSCqv9JBjITAfS+lBy3gJA02ZdqvA4pmi2Gujxlq5ot/j7rF42se4xkKKRu1+7RuiYLfpMeT4GVs2MRUxeBxjQKO+zweHGcE00yG55z/c0Q39Hoqm2F3avK+FlHdbWh3cRSQ3A1oWI53VtMJIi8F+9/IspnWSMTU9tJ0IvQFGHCovQEyPQBOZnMVj3Rc9XweW8+PljmjBRQasSsS3ZciZwJ3RiEJv6a1V6FzQTuu6k/HbRVPEWjUKlAHUClwncVrRW0JcFF+64LBdc2iq14MUCH0YIZnCTtelE4Kkq3SIx9qcsU7musXwWj8beO7oa0UnHOSgrWOZEmJW3if1mm2bimWStOnY51fzcCO2sRKiY1aGMQGUGujpW8P5Ro3/2/0oVvYgDbHDk5LWjTXHpTmsGx0g0OE2Sssxv6YntXBiSUBxkzc5CMEGkcnEJ/iL/n3nAaS47U8CJObNB+R4yPlaXTl+kStfgQ8ThNEox5P2TOeXf5HPB3rkzO2DA+JztNduVHc7ZRAvnuW+cpHbUXpe73An/tzwapbyX++8J7bGDHwgVJIZoLaHVOwG8AqWiVCkhtrYOLk0zsAkT1jRSfV2bO7f4etu4kl6DO1AUHmWvjUPM+I1FCc2cym0w4PIIOejIAwRUOcNUGFQm1GJzgDtgt9bBtWgZHlZno6Znt0RGGQ6YYaVZLspl8IWsFzm/UFDuGXxZMNcJk5aQsEj03m3fLNJaHXiKyGGtrWB10CR1tiRj/KFl3EhqrHLvnsa9aw1VunTUG3Fs7ToP57AZyi8PnF/MhGx/uuuhSOULy9AgGVk2wGg/pf1gBtbewcsCbl0yF2gaXEnVr+tp/JE6BNicCAB1Dt6alHYTUGYp0WFp2Jvy3K3fgPtZ1rR3/dvA6GjKf97Ugk6mB4CnnTcqrmAYdLeQ04XerRRL4Ot8do1PH5Y2XzyQMEc0QY7dG1GgCaXtrtnNPJ9e7txReuiigh9jf8bhluCymc0+HL2g3DY5DyngH7wvIzDSjA+gXwumf7zDSmFEj8JMe4xtcu9+DTdrc22tdvL++D2/18oNBiXb4tvj9nuncI9cUvsr+09vb5by3c/ld7zjR7aM3/+t3z5CjIsv1Vb/eGV93uvfz4dXXxrIlhfbNAUY1+HBUIPKifk0OD8PeK64hCP/6DX/o9pDPuP0GbaSmtBNlni+wHlmZsyFcMET5qd3aPw1zisDzwDuqaAvDTeByHB2EYlx93ALMOF8uaA3RkMHdQkMNdm12Dvd4ZP0I6njbZXyyJCgEqpV+OrEp5jOYO0dhcRuxsJCSAr3acbaOx6FRcIDzHHE5IR+9cT/3i3zMsARlTpqx3f9aKO/ycSmH82/a4dCrzZZIfRSRvrDs4PT5F+w/TcCnTMTRIpgOhha77iQC2ms9++Upa/A8rXLfxzCz6zO9WY1ze8Pbjv9OoHoVzz/4x8hOGyeO+43n7Z86WBdIYf5mrH1R7VrnjIhFO0Ry+6+0O94M9Ou9WGKU7mmz/6A8dPBJ//6J+cqRrZWPcN9kU0pFMowaN1VS4kdTx63nJrE7rN/FRX1JOn2SopQNL0Uq+CJtTnxKLVELavUB1RA7RotY0Y8n0at3u8g+GxgM4zpSphciRmp7UTJqDNngKq+OSnNy2ZFTGy0rqrW1KRaQOzWbrlmTI+mYPR0ntq3GVvssygn9CxrzXdJpUuutJF5W/Rl2t+dcBf+hhuZWOEgp9tNZhg2oVsYq5aVZd/U1FucjeHszpS6AYdTxFWPGs0WSZYN6JbqVQYaHrUy5EgL/PI5fht+jKgJBkGjEtJ6HXqyH73nyo9v5emuncft7y+d222jzd94yUhXAu++ha7QAW1Qx4r0uxi8Z0nLXsThAr2jM6kyis0vJAx8RSIj5XtTQ5KoU0phkKZTR2ewCiCmvDNjmygnN3PWRRv2LhkInVGGCTdx2939gyjgTAFvijTFHV1TjjKAdZG04KWqUlMjgkspbnTzM5KHt1VEm8KKSAxNRG440R3wWpUFAJplsWZbUImkwevwZ9E1pcRa9LSX4vxkyGiEfnOCCf5lWO74/sZDkI024WQQswbBlVICh2aYzGo7Uyogxqa0b5MxVY6AhBL53Aa4HpiYdJ5GhsYvFneQUorV2ceIjB8H4Mx1SgumqYCo+hqIgr9fPfgmwFWlS6UUV2rbO3J5ly2iGoxQRivL9r6Djmmkn3Yb9zy/TKNtKelg/eyerQOX/K+nbXBcbfDuvGMai22Z0w8jhcYvpfFmIDsY9zAWYDwPSM+/ma8M3vc4+kTWVcSu69g+K8sZ6qwIaHpTPZua/llSnnc/1yHdY0cLgA18eydxnyxrinTR69npglmdrs0JAvCsRM3Tx+9VtxYZKEZILaKifRcQuIQhcztmAtB6kYozvKD3jvVUcelVI4tNNS80qBDAJwJ1kWf7RdaLdI26198N9b4Z9x2SjM/zTCWRQaLo+LkWSSnfO87LRbLsaKkaq+dOtjeAp9mHPr+AMFVo3eQwDG8dC4BYM/TuKfxttca1Vv6JZliFx8D5e/xdjMhtNsydbTzj0h5+wil/t20v8DNyc+9NFVQ5sio7geQXbN6WjrU7ByZ8DTrgdgbdh7zD1negciQOzaNpZzsK5VGcYjlLC3d4c2MZYk+LGM+JyQOkA2/08UVgYAZwke85/OCI18gTk+7SCvRjSFHEnmdw8LbjbsxxWmSUO3R8BfAIxh34q6xUexSD9fSOvCa54NgCQkPrFYUY1KSYIBVy8G0qL6ythTMvoE4ceYRwvt6zX8jxjYjzDY0BGJ3Jeb3jpuecxJG61Ipai8qSxlNBnL3A6F2gqUMj1NkMkvJZF8t2KK7bXrHhHem9UMFU1KGIO/i8YJomzPOMeZ4xTRPqNGG6v8f6SWIxmRN/oDxcaw1Ny1lcc7Rs3WAv9AlNHRYAYKUV/dIkKweA5kuW4YqOEYFeZgCj56teyjQ6DpGtUrqmvHFb0btkxKhgMfBOBaWy0y8bmWVLs5ILXfmtrlFCrOtMK6GUhl4mzYgWOMqyovTWsXaJ6O8qH1RE4E5FwiNJXroGXYbniIyfhMvTtkVb/HP8suvMiTtKHCFiZ/OSbMjDqiv09mG/fH5BccGQZPeS2S/eUfAehYCmZsyW7re3qZZLjevQ+z6h0K+gXwrKv96j0SeYJLAdH/uVdM3P9PHa7I3oe87j6MmX9vLv0t5x/P0j66bn9oh9JLk5bb7UGKNL9G9uCQwIEt0PpMA8/0eb76J3cAdjDicr16kZ88Ej/P+d2sNGHJP9IzTIftt+7ng6Zty9f8Dlc3anIHwhKTvh8pqhSiLcMoKPZACqi3D8lXh6AnBzmrFolhejQ6S66Uop26GWNKylqHpCgkKAYNOqlQJVB7re5fsCRivFUyxstbqWGfZ9ZywAvoDwVUvH+KyTHPef137vMV2XUr710Wt2tb9S+24DuvN4370+1wSYP64NSk1IHaTzqsptU6Jtn0kC41HL3ob5vrZNQbZpD5CD/6RP2t93XPAZgji/lusRf791VT8kpkDeN65N+4eMv+IjAKBT0++f/fmOFxgKDibvWAkxKh9fQyPfPN9+DMCxn4nCH7TdffZafa+lzH6tjYLB679vxLMt2zv2ydfu++Na4I2X12aqxZUR9hylECpTrA2KWZKotG41qJGUlsyIOqkaaWLv13+mmCwA6knSns9VoqqlVrUJ4ZLqKwQVEf41aF6GghD2mDtKnUTJeVnE0DQFm0qlxjlWZW2GK5sjNwYX9Sok8vqxL651UpgQEe7v7vD8/CwXC232QVlZIomo1Vro4ztFsK1qtJ80krB1cSIoteoeq5LEhHJNAe8p3IsVHcuaA11KU/pckkJUl9myOrHtoSkCeg/hWF/mzB05vxcpcy29tIUP7GY62e4NV/y7vnN96hLNMC3orYHRgGa1wHoyqndXfrW1RSo9VRRzt6jNJJUT4LXRwfshXmtZoEi1aTEox3Q/WEV4VbjvInrAhzQmoqFUQeoK3hEj+vHcgOkRm0bbG4BU09ylpeHuLV01RarB+3bMpkh9CS+yw1oYSnjoLJxNmOUcnuYTpnmWM9M7QA2lS0YM7pI+3QwInRnQWscMjtq0xJr9UqO/QaApaiGDCOiMVTRLOn+p0Uhdao5LWtQpFoXkrBYVPmop6IXRumSMkFS7HVOdZfylanYLSudT4KZrytplWTDNYvgspapgM7lhweunKy30qDJff9mLUiTNe2uG02PvWXkuwbusAlMyYOkBbD2dmQ1kuHOO/0uOBEj0w4GRJPbOcDlCAGjKG26PwrH9bRzRcB4wRs11znBNWoMUkjKUCEQVpXdwqUpmRJkpaVxzXzIPwyGB1wxeGaWz4t84s9kJpCTjkESyxTrbvMiy+Ozohhmxt2skCm9LKxr7oE4X5hxCGXfD4cQXTfFAKaSOGlXhrPlNvpdpvHmIkv5N1w1dnLg6uRF9axTNmyesh2V1GK8NnOB2sw0PDZMJVOIlEfSHqnVsWRFONmAHN0f+rac9HprhZzMyU4owPMS+43PhTJEN3NE9t/TdkCMZrJA7tRRMDmeFasxzrsLPNMUJ6cSM9Fb+Z+VxrFwMd3VKgqUJZndoNIMHAPSUwmYbcU5pjsPc07TEyaKoow7rvAz/p/cxI0fPFmagqvMl5Hz5m3cyh3Ersb4NkKjqYs6KGlGhzxZMKLPwUEU08oITVonmJhDg8qH866tG+neGqJMqQOswFusPzFI/l8z4WfT8Rep2L8PDwuOiENqyCG/TO85PK5a2YFmfJUJVHV8YAJ3NMPzsjlPZQcH40OyYaVkx3EkUQFu07BARCIvyMHXAQUSzQDurgZcIhFl3cXGUYRhPzl/CfYovPeKe4bjHYhlZ59A4R6ky6CaM9OTnA46riBD2WuNn2QxI7IbSLZ/zYnMau8ehfgv7QPwyoEYvcmwGM2yq22ji58w5dstnJa4q4UcqkS0q2Cg+oKfJSE8UKaH1tcLL26LxMK9hJkkOsL4AAEXNeuYw0tNYmSWDWX7Pjh8+bucvn0FEuHl4L+Vp7oFK77B+kXGWBzlX/atmNNQV7h2YrOw4aW1Rgu85cfA5ZvTtyvM4vtBhktFACriVUj1dK8KwO32ZQ4xTLyrGnEj2RbJ03UlPZXTf5GTFM8Wyj4HRVgJYnGXk/CqKIQIlBzvbTOPXZS7KPOifKAkEzHPFVMU8uz42MJ09bXtVR56iEWz8zJjv77CWgsvTk5/JgoJee6IZR03oZJAyyUjRV1a8mR2AJFtGOilwg7/DjcFdZPYZ1fzKj3Tlodgy1MTT3t+g67gBUQFfJKPOfF+cdhAVzPOEeT4pj63x1g3AinCmgGRIsXea7qqXyIYm2V1IylWwOYI39H4C81mHr7gKFEEMhtPzKih97DqVkrw8c2r0rrjPSxX4Xexwa5kHfbkt65XRR+14de5MUgcXsqMvfVeYYXGU8dyRQ2mA9W+GPH9pHhsRbqUWiegaYHlMYh1WSlk7aSz7Z4b9CnWkZI1W19+X/7ui/k9B/bVg/Qd7tix74TA25GtXeKuM23h71W8anxweCX7HaOb2DWMM/+/fvG/a/iAt9Ntjzqt3etQ+v6HU6qGO+xsn/X7z/bevmcDODX7BF/zTjemf3sBB5L6tJvo3R55faW9NjW86wsyPkvFWpn8xWpf0gEL02ElMvPAHTeA/tDEIVXU0hd+D1UGHIWv+yypG7VakNvj65SuIbzXb6h0WfAUIuHMZEc4zAwja4v1B2SjCVIU2ExGWywXEhPfv3oGKZRSCl6WssL0lz3IqWWMkwysp8TeZjgDNXqIH0mQA7q5DyOznY7GtZ7xTPc4EwfGWWTZcvBKv+ju3/0RwzKuSf9uu1n7smQ//T5zZz2v/jUC/0pbWcHealUkJgfL3bBViSH8E4x0IX5Qo3v2GWl3X2haVVKNBFLQoHx4zTtkvJjw4o4jXgOuPZKt+v2aKjB/6TnsxrickihsxLPVfAb2JoTQTwmhmPCso6NwOnzfBOCsHDJqtGmStxemCGd7aqinXkjLnEIyNkOhfk3ulNtuKuZ+0zxDSuHXRngODok3SgDaEMSvNo3XwZB0e7+ygRDM1mCpCRhXT+NmmUIhQTies65LWKsGdG6T84vim12DfBLArgLld4pDnOKV1pM0KkA6L/GoId9uO+E2H1COwTDm9G5MKtA1iSFfFdWfx1O9d6s61tWvqdq1pqFENZtjxd5oEjhB0cwTla83g1j5nCiYlEUxhEFFdBzGReJ3JjLW4xmQdM13HY74mi157/qfhs9eYwXRQqBZMpxmneUapRZRSq6R/xCqKSFOCuVJIQ00lmqZpIIpG1bEYKqjWSMlJAFap+2QGAzBDMqaL0q+1hgJGK6sazUWpKSlmJe0ubBzn7saoadbUl7Wg1kmNXeIgs66BQy3Ccp7NQE9qBK0qyOa0t+r4YcKQOa4o3jXP8tbEKLYsK8RgbfgZaE0irooqHXtXmkcknFDfK422UYWUPlA6v6a896iRLIVxjkiPNGgEw9nH5+FbyHxnDuM5R/SKkA3a07atEq8zWB10toYIZnhqe1sTkChGS4dHorvjC1SpOCzBBsdvnNciMiwr7EZclR8XnExJeCZ3qgLgcH7cEo9JCqP6rJU+sD69RqzN28abI6l1vTu6OKkMRurj3nmgEXsaMvziBowtf8YHQHKFgcgGa/8Qm+S23+0rnOwmTCwT0L8J1nazPGgjA7Ef8k5DGfxApkEyJUkaWzRFHxWAesJv+r5jihNrbw62ObK9tYRvjJ4CPs/B2D1Mm4bPPowE/6T4lrtkvGAQuG5SfCPOHJvx3DJnaN3eA85jHBPBlYMRySzrb5EXBOXJpjnZyQhc1ejQ4qyUWsOhUw3OrJ+JZuc/Y/qjkX6qNRnh9exq6naLQjfeqUwTlnURg+eyYukNy6VjrZLrp7Uu9nrIGcYJgBnR1Vjo/BxzOA4AQC0Ak7PeZliH8jHmfEOkRh0YrzrH5E4EugQHGHth9yT+NtGUoBcZf5VIW57Z3AH3Cd29ShO26F3ppAGCOSW8xO9x+jvy8DL6o3SLR+fcdBwweEpjMweJ7dNblHDUh3PfpDyIPuNJP0pBUerau2ZHoa5G84MOFNboRMA5+IQXmx8sn9DwnTDByzcNMtYRftye2L3s6TIdiSGwPmRaLjtj2b9YaUQnKQlAkEhmsowKXdPtaDp/M6Db+LLB6tp+uCLaHMW2s7LzbqSCNiuQcGKeudBfeLpwI49clZ9oFYWUcyLAxJvMH5hzhEcX5mXXJSNNdU9QRxlmoatyQYzn04Raq+C7WlGwoFv2DIbvde8dlao7p8ghGeeso/QhWGYxG1/mqbKbe0ADY1AMHB1SKrBMH6wGaipK+IyXo3FE0ae9h8Lh8UTDjeYAKY4NYkAnBlaG8/wyxu7PWaQ3g1FZ5YQ0B6OzEsEuTDG3W8G3G940eENjORgzRCd4nYMK+PBU+dl5iOSkMsl7Xjv248rtCnL4KPLeDyfalrRn2YAGnZKXIbD/EzQLBeORpJyl847arBQhIKv/lLbObrs3UEj3SfsE/OMDyq8Kd6ZY2qCqQU9whXyEbiDx70gs7ivtR5nFf2i083c0M35b9Pi7HzOt39we9e9D+vyt7QuACf/CrzBU9yuAf734zJaXeCnd+89oxt+ZYdxK9zDkHBRzZrX7mL3WtvNfiPPzH7KdP63ZPCeONQJ9dsrUAdwmEU7K3gD13T0AQv8MMD3BeCJz77J1S+pukT0w6gktMytB5R/D3crnGA0d+Ge9Yk64hYr+kzG4s7RNjmxfhYfpgxxMx6wahJey0rvvVa/2oOc8SNT1INS/W3ttFX5kNPl/dtT/29tvNqAPcsn3vUH//qDNeeN+mFJvw697+qRKhNubGzxfFiyAC8POD2+MGX1rSEJieFMf/ukKdrd3GuH6fz6+B/37s3xXZFFIUm1sp01bYHyDYSieD+IDSBYuRnjuDK+FRJzPv8yYpxmf/vf/w4yPuP0/t/j6v5I6qwqPfZDWhg5gRX7IKYsAJOUPjzIw8tKNL7s22x939N/akpBs3zgZL5VjNmWHMw7WNvs2KMjthySkbLrdyW/52d9nLeJkMbPWgcyIUyK6PZW4z13ue7osIADzNKlgX4b3RprhLJj3EHBML6C1v6iwKyN7ZzSW9Fkl1UsDA9PtCbVKlA0zew06Mzx77WwqbjAgywJHo2BCKMi6+VIr5mnC4+MjPs6zbwY3UbSufRVh19aICtqy+PqIUkX6qLVi7Q2TTrcwg4vVmyV0VU5RqQ5bVAjzzQ0u54sLzaUQxOudnXF9eLhL+yjP1TIFE1bJPQ5JmaFpmrVGvExqmmZngiVqsoYipKSoHIsok57keVMY3wJ8sfUUZYwxylT+f/bedMuV20gX/SKQJKv2ILvV667z/o9317lWW9pDFckE4v6IEclkDZJsy1bD3ioymYnEEIh58Jr0BlelNh4VeBmjRHADm1qKcAk/I/kkDTJw4x9UmelpWmX7PxnoTwOjr8BRwkgolk64rz2ijCPq3D35LULEFaZqfC/RpVYT02to+3h8/F7zOMZiCodIYRvzKM8AWEe38yGxujCFnCtQE+e8IorYz9V0ubU17eGcPVx0Hz/R7u973ENuX86//hjK6umZqYd4LuDN2W2eFYruuiEi6JY6ePSuNSCH1YxdGsYYWNopotGbpebsY6CxprMedrb7GJqmU64Ymd1/GgcvDQyGByyb2QXELYSaPjroSiBcFMZ7jzPoazG6po3tlmZXBrD2tUShc5wlgWjkaddIPoGgtRO4DYAYzD2Nq0DiFh6QwVAlus6hjw7mBWN0DIsmJW44HhgrM/q64nw9m8e5ngNuGUHNpCkrF1L6UCPsQVYDsgCLRz9XBW7vHWSZMxJUdF7dhMGoQSo7Kn3S+oZi0VbaQRU/TajtHuVJYdjbQGz+iTOo8xljAMxaS9qsHEquxHSwqUjPOtqw+pcxzKALiHVA4EmFUVZcbvwJhmCQnmmNwiFTNlO8cztXjzjT5AEUxm0ihe9lsTSrTcsTkN3sNVP3sl/EKSMGMbLGqe+VSL4nlMYc+BVlXyfD+sRqSRiKImMHExgN7hTqaThv8Kunmyv9OSwGBDidHxL8yaT88RdAIxJdziAHoLoiVeAilUsq37Hl/1xRH5y101q5g9Ep/jPhUV+z4IXKOYroOCAiz7VUC+ycM9CMSAzBIMGyLAG3w3CiMYRKSwo+btA0f9P89OWQodkhyPrZOqKF4sbPQ3yf8bjzkAFTZU4gi8Qj1nI4tnZDMpJRgNjz4DNhpWoKn7pPvSwKruxjyKfDa3tnFPqgA0SM1zPY8XMWr7iK1bn1t6yxTwJVTmnUeInwBkIZSQabbINxJyItQ0TAuqpTgQA0Gro8AQCOhyMuo2NcrhgLhQGiHQqM2nrgSODnB4CfJzouMiCrGZiYwCsgvKBbumhNI19W0vAbtwZuB60N3xUH8FFx2sKMKzqI3PUIvaYAACAASURBVHl13gkOhwhPpW84DBLRMuxRMsRaqxgDo0Od5uRqtGfBsiwGj+pwK93KwnVRY6Mgyi6JNKOrVmfZzxMRWAiDG1pNeU7lbJBFjZoc6XJMKJODmaszLmfXfymlKMboenaNxgTnpzUTkFhZH/Dz5qcpINppkki5KtFH1L2WEeU/IOk04G+J/DLGp7qOI/BkwNQwp9DkbXwcaEtJBaj3L8dT7P04M4acFQ5Ya3tGNCy+63WcIHi2tPHqwDc72ejf89dfICI4fPwc9LWujIig0wD1q9Fek1NEQE1LP12lg8US7oa87MpxH7XjU89CIsmmEwUaH1asyli5BAOyzBVMQBeVAMworfuC0ihqWTeLNlfjoXYq5LBnOFNSlmRiDG7g1iESyF2dLpviBytaoDW2CUGzfBye3eO6XnUdVgHRFUOGOqVzrqGsq8rSvYOPRxwPH0H0Haob0NkwMQ6LZk1bDe7ibLGmeFuvmrlE2HCYy8Fwxx5d7BLAjTgbBS68/BLJUF0E9SAYQxyalIdw1kvvr6RcIjMBlgVkuYvHGJBVIG1YnXLC0Vju8b3jslwsQn+Js3VdOwQCambIYKXTzfZAoFmlmjSwaH76LqvlA9Y7hgw8PT9jXa9YxxVrXwGx89da4CiBgEy30Unr0vpZoaZ4tBUnnwBfny8IUhyplOdX3SLgjoBKWIfxzo5qhsn5nsEg2B9n9v2MuNykjK+yKTpVfaTsB8QCK5CgDttv/ePaCMGDbfPKhGcZeBRKJ1Hb5O+kRvYnyucBROyo1zb29ywCQH4C/V9gtWxc3ZhEx9fOm/h/9LrrQPz6SD43xm64ttDoil9N9JivbflA/63oG8LxpGzyxAYM4CNk0hGHrmYrpL+hvfcJN5jvRZHP/NqdMdn32o8UOITLTrfSI4A58tzvqgbKX2s89/Z3VF7676A74/D2FZr6/S/2/ReUFShzv7c39ao7nE4Kf7eTOJ9Zxhd3Oe9deXC/bgEI0z+/Vp4VmXr8j21fydPiS/KtJhN6BgxFEQLCB7SPDPmmPA1EcDVeH0A4+iT+lYkOecYMArCuK669RxYa6ReTcZWPOF+ueHw44bp2478XcFtwWBacrNRKaw0MChpwWa9YLMvbKh0kgmtfceCm/BELZHVec4CY0NEhjXCgBesYpq9ROPxOmYmyGV/EYrKP63GLzPfHbYWAvfmRtLNtDd+z7A4klp7f6PJysox5Xl0+jf7d22Fz5O4Z3X+v9d4GbPyzd/FPHIHuQoaDh/3XPNtdId2MabuU1H0CTBE+AFLJBBShJ5Whu++fmJ9skkPC+vMXPH7+hG9flZRuPYB+ffOX3gFw+3vPQ1DwBcCPGDJwkv/Clf4H5/87HyBfq0+SDFIoaMur82DyRDAnBGBrlYxwyoL/Ti3G7AKbw1QIvUXwL39fRzi/Asn+01o9J/Y3KPM834BKSocVndk2pSKb4OlPmXGR/L450opdABhq8B6k57lb/eFIJ2aKdPd8HiW9ZKYiLu+B8m9MKujLGGCLXvfZBYyaUAlB1gJmG7+oIk75PyX8EX1pCpIhUE912G8gXIfggAVoAA+Y4RymxPW1KbAW3JDOQUQFcVXsCT5+fFRjOHutcn2OWxpkWnMFtNe/hL3D7rAIHdOvQB0JdL2Yc081FWbuN0ka38JoRy6A2XfLP5ep8n1UFulLeWVKiU4UHpL2VfsbKei5tJpRGXn2RndjjdzgfTV0a4Q5DYrab71nzXOvd+4RkhGZLiUlo3lvdjPIhSA5UigNOTkYP0/vmQLsJMzGX04B2uboisshCctOD38NJqkRGb+l/Va8/iJlu8No3XufR9+JO5iIK1zsZJjipfcBoq7e0UMdIbqnfDSFYbO6zX0oE997Rz9f1OjdNNFU7wPStSzA2jU9u0ANBK0x2GpFAYRmKdCZtW7mOjq4NSy8BK7rvYNwhQw1Wvk4HJ8KFOYeP3zAunb09QIiWHp3MgecEuWLVNp3EYBWDFi0kbQwYgJIo+bQtPEECtiGAJfL1aLnYco0iYN5OT9PypsuXWuHWvQRNzYcIGDiKDnhCl6eLCxJSzM9pKYZDbRvVGb42fKa3sNpTKhQUFkYcZAqtYO38NNlC5HVY16dCvTmWxru9zE5j6B0L5nAHccaGx8hvb5BeS3wis0FJgS7sBl1J4VKzVS/J9cycQ/i2XCFojoWjYLSWqXHqa5d7x795Ka+7frZmjtMNjb6KliLMxNgtTuDV0REmqXTgo+HS/9ufB2x1tEH5byjT3dqEDUwipClpk064zR/4vsJGBZxrbRGpt/Kbt5i0RA65q+oe15gXUl/NXQ50yQG6wpqu0b0l5CvAKFJBuBGr/yuHwek8B+6xlFXuk6rpCfvlOvl+MFv58a5t6UTxUNueCv0EXaeiUB0BLljD1mGj40hMg3LOU1IqZ0b/I3zH/b+IKi6Zsq/Gb3wvzf7eZ+y3u5FKp/Jxil0QFu0ZIdQ1h8fyIhE5VfNkSuUi3kGwpHGjCcVTpmSvlUeJHBJWRvFEQec169oY0G/Dnznb1gOi/Y9bN+JrW5s8vruLKO44REDl/jNLV26L2QpdtXZSZjBcgKH8YmSB2WVjslorM9KLgI8EpbHBdfndVceF3hKdo1c6TLSuGPHVUQNM2x8vsKvTGeGvbYjEdZVHac6oEZ0kyU8l4AbVFgYwzAziUQmmcGsvKSII9hSGsyNXQO9O/4vFIZTliZ41I6LXGkgvlGKD0AoaV7wwRPRq3h65qdCbiu0LFJm+3M21ozslVjfxFPpWk6QII1i16uRvbYq38Rf6ZvvAnke4Eflow6PDdcnzUTAR4u+fR6gB4J8f0Su7AlEamgPp+u6dnUcdU2mz5k5QwMDRGuhC5Tejm7yjembmO+8w3ADyQ3bwCm62BuH0SoBN5gDiuNHBrhrCnGnJ0FzKegZyGHbogIjBf7A2Em/7bwFWaYZ8Ug1w01kFv3GOv4OrZ8t5iWgjlgSRn8ZAytppjb1QVuwyBXr0sGrOgdJ7xDLkAHDi8fPR9DXK8aw2vF2lFpjDBKMywrx00EUcx/mv+DyvkfOSVP8RA4Dhcbp3o6iUvSzmuyhyPCs7aFcS25MzRYaaZ/6RkDxDoFAYwDUIOOCIeaENgg01CmXO4OG1p/vlumJ+WrlzvT9rl+A6SmcHgIZFUhDHW2HDHgSKpfR195xuZxxXVcMrCVLCrAQz/pJMccFMjxOpGl7w4lyhl1szpHDXwOini2Z3sJXmFmy8kJpDRrYlCnbESua/AlhMfqp8J7Rkg7PvktK+tlQovEM82TRAZwdX9l8CITvhuEbMx7JIs9F8ERuRM+pe9+r82rGB2gwk2iqZjg9qku3g9Mr4xi0VW7uTTycvJxs+kL2NF+v+obCi/n9wcP4HGnqqMhSt+P/w7btujj+m4VF+7Cf/6C2OOf4faK+PXI9jV3bN91vX5Cp238o17y9CSb0Qv6lPK/VeA7/XH6PZzYwtoUzbD7PcsDr8/xPaD8M5+82LA4S6txvzlXN+lcwvj1B8Voa0V04lNITIQPWBhEupPXQDwJcPZugBWEQMxZi9L7ico6DbRkQGcfDgtPxpI70FrxGHjA0BgYhHH9dzugwvD/EUrIzIqNhYy2752KZOYjpjylPDgYO8gkiP+MjgC9bHtjlvx3Z4F/f3okPN/LtXrS3suKJ+/eOy9aeef91qt909v2f3f5VxnPg39iAXoWT3d+Dav+6/i+joy0LTqcDWh+4nM/2QprovzcTieMXma7fClOENJzv9ecX/kYCfPkCJsKjUESGvwYtsvm7/XbjMb5pHnnO05iV/9JsU3/B9acV+DE9abv8HU3+ipX+ju3yf5aX68nonF6YlHXofK9MP5Tvdw77a/Dy+7cZ+OL9wUzY/hPtPvEeZJDP/RGR/9yCid60u/vj/BGX9L7GDTAYXVYzilP07XVis8MK92qwQR/g5WhGTwWu5kKTCfpWWnIeJDPQ01jisOjKnjQm5xthxEzGwLenJzAzvvzyM374r78WiSKbKvNLCsYwCmzSzfh4u0Vnsx0S8+wXiDoqMOCRygDh81//gq+/JEvsKv/Hx4dpHBmxuJfmRt+9riukEYgaIIJ2WNSA7oKR1XSDpxy2CAdyS7oglPmjiN4Reb4FDBmAsHrcM0LR6woAi5kyo4kUxpw0msB21PFft4gAJrYU7B2CAYh57W9OIpPLoIbxfY0eCK0z+qrpFlVRkSld3ZDjxnNMBjpVMA7X2oBSwezTli2mk83nl1pSptYauiucXPEhKPO8c0DvNFe4JZNmvaRUHN1unwTmdNsVk21PRXbzBhwn5Y/zgJtb6OaDffFhy/TV0l6Tnn2iLLIHYF2veD6fwRcq+5VGAm4Uwt1yOGpNpt4hQnh89OhuBK4b8CisKhbNwnBlkIcIDocDSJrxFbonwwzfVn7W9CdqfPFUvSRK4c/nM46nYwqfMkDSIH1o3/4uqCtGN6FnWP11NI9kafFeX8eqGImMCvbdhWi4chXapwZHpkORK5y5MZZlwdIWNfDDUoBZ1pAWmTFS0a7A5J+7CfEcuM2FJ98vr9fV75wDqdApgvDmeRP9LcKMQJXo5WyTRShulUmh/MxFBSCuD7vBU3W0+2Nzp8X5pxo9Ecp0ArxQb/wctHiPLkwdAqLjzBrRkn0Zjo2av7Ufo/MUxlNKGBm2fvYOx6uvK+Ho5vOEa+qCbPnVohgMmjgx954CGxGpPtEfrz+7Y71OeLDvHtm25Q+dFzDUMNm07Ln8nohQwdyevdFibps718zjE0pHjaqkIOO59D3p8OdaDXXSkah3T0To65q8BRDlJmICBfeGGTdgR/8MMUeYDS1zwCCCpRrPlOBk76+GKXfVJNhZ9r6C75lp200rIEWUhiKf6zvQwg14uhHF5TCiDmrHcHBiiyBvAIhVZaYGLoOpfo5ztVWIuKNCvNatGbl1VtsYADOORGiPD1i4QURwfvqOdZxBY2B9HsABWNpi2YGU33LcG3xZ7xbZLgAGcFJeh54PAM5Tultdc1tL91KVBUEZCWoQvCLhmhx/XwF0yFUjzi9P10lJyyed17gazpBueErnz0Z/w4HVzzMYoAFaLNMLAGqLwn1jQFaIEAYfIL4HyDMjMjBAuF4vYGIsh0Py6TAOlglDWBlNRwTizg2+hU63zEBaQEcgVsc58VsyNMnfKarL7DJ+NgLMb2AyD4DUs2h95QwCoMJ5KV+7j3fUucXP9ku4aTu4eVw5MWx+J2Pe9bvgjP6UtKzhBIAgz4lfAOD4cYEAuHy9QvB8gwMm2gGA8KFQlfLX/iyftG520kDDm1YqoToAg5I/9kxa0y4LMIyXp5YxxO4UrGWiJAx+AwDXki+mON/ieZ1HMYqLnt/BA6MTBjQ6jMSdotNgoetZeA7J8cyGPY9xizuVDqgnDFo7YL1cALhTHKMRcDWZCQSsY2DpHZ3dOVjAcsTywxFEhOcvv4D6CWMsWMc5UoOHy3FxgnBeKCGv0BPKAQZsiwRMiwjQGjxzGADwg0VHPzs98/M6IVz9xw6yyQOT8T+Oo3V12bLYXCE4gkBYHtSg21eVIXvvYBYwLxPv6BkAoyzEyBTvjhuYGbgCKqdD5eW167g88vqqjkGrBR4QPti8B0i+azkNe2niER39gUiLJTgvh0KT7DMzK86wAIuEdqP3VHhQSK5/uQ/QeueAR6tnC4dI65xs4ym+p+OYwrb1m2gYFA+OCAzwIZzr/kpgQ5M39Cc3nnu7MZ6X5jKSQCMqP1tmqDn30xubwPbFYaHSpuzQ11ekXACm8jJiz8U+v6IzKEdoaisB397CH73S3r0W1jxt+6eybYDqvv9uv/3yxn4A3I1ue8sU9+qM/4C3vT+b4BNkZz3ev8gNwP8A+AQ1qMvOGN9CqV9rVaYqF+FyXdwjxTnjBXirOOM/tX0UM4QnC29lALURPkPwBRDVYR9IQD80yNNA+/gB4+kZ0shTdyAwlfHQzpcIIcrLDKgD8kkA9G5BacontN7RRNBIcOWBx9ODZjqF3uN5D2WofqejA63wBqbD7qPj0JbI2OkynmfbYhC6O03Djftexinxu6A45ojSiQu+oBPje5G9w7Eavw8sv9R+BzT3uzd3aATmgEO4fhDzeeI/5Cz+de3f1oD+z2hfv33TyMxQY/z6FrIoeTTrrztQBOC7jPBajOtFMH5xANM9FWXI7u17YxwEfPix4fI3rVs68Hd8ISWyTQQsn9HpFyzyAzo5+Rf8MIAv7U6nv7H9o5HfvfYoFCmY3tRuhPv3t9pFRXBpaLW2HRaV+3eG8Vth/K3tPUtQmfguXhPHhFHTfrjwaeJ+Cp5ARLPstTFWeFRSCAkipsDKOtEx3NFBfAgDMYCINiYgda/w92+V0MDp4YTr+YqHx0dczxccT8foIf47vbQ8/OLiFSHSHApeuv/x8RHPz092D/D4+GApMNNbtuiOQ7fKHnWzadu3kD+U25WdemdlfYYrJFCEM+SzYRjRCQLkhmxRJbLBgadWdMOMet4Pe22OsiqKQECvcGLzlrzZpkJq2IOqLF0NkEybP561eOu/jGqVuV6QSKSf9bmGjF0RcRGyq5f3y41Qegwl3XCl+raLsNz8vu12qGUvsP/K3WNw597f0rZHRMraCAglYDUYS/+sskTH89OTphAnnuDbSxRAJCJ/2GBGjR+CsXZcLRekwhnDDdlsUdliEbJutFOlmML4YnkHCciagVAtSxiWhkaCN24ZPRfCqL77/PQMXhowCMuyAAzNwKOLYsKSnx1XXg1VyCKFt4ZmdVU73HASMi9x4l07u5Oh2/pXI9cCGitgEVTq1KRzWA4HLGYwZ4tk4cZoXoedzFgD2JlD4gNSo4MLCBOODioirm/abWn8l9KBbHp7qalImt7eaZbXs13xGGK9iaScf2wUYgGW0zj9bQLaOfDbOZUI9RlVT4ev2k9ccL2ZIdHmuhnLXME/amRi9lfPeJAxx++CqP8+4dYCP9stmPma/Lw35r25AjL3WY1QADTNSuJjqd1slbv32O83tIlvo+lq7lqVdoN4VxiY36uGmwLPgMJk7Wfqc0Mn3zAZ7z/9w6QgBBQjcwKXYc94jQQwatPatJqeWALnZWNiTcNvxnIuOBsbuEz+Tabtr9Pa7OI0bTHE7fu9hasXt/gFYua8OlvfTAQ6HDTLBpUagtzM4J0OfRBoLeXN2myjEngaq82+wj1pfWavfX44aIkjGYI+HjC+XdAXAYbFUPs4nC8nILIJOe/Ru/E+CNxV1zxpnASdiLNPVyhxaQAacCF12PI9KOctDMihCLo5PPaNIGgQudpziPudt2M6TMYXNUgKuJYQsXeqo1gp/VSJyBCrn87mUFmyTFE6gqoDghosIWlY2zOib6d0G321mW89bzE2mv8Qbs5CmnLms77pobR9eliXI2jsRFDyxztT3GlHgNZbHFtbWJ2q6RZ2vu1cPFCMUZ2GkrcSPECsVEGdiFiP3lldjyS3iUTIHOFENF2+5qe2IYoZpokgNEDu2Gvrk049Sv/5cMR6OUdmgkyEk3yDJQzSiFy43OLraRkyjIbndedDrJcxQELoDeaA6bhbXSqZc/6wTGIe5V555nCGZIYMN1Rm9jA9dSrPHY4njN7LfCjP1AAIi2bZMHlcWgNLR//5Fxw/fVQ8078CclSlfRZi113yTDIOFhNIiPHcOhZ/byWFAqc9Alw9it2HewLw7H6HiLIA/jslPnK8EZlXbM21JqzLHyrHDhF1WmWTB2DPPA+MRy+bgyytMAhMNl/vWxwHOKJj4AyMJhGtKDK0VJOVLYOj3YuUsmNPEHks+/NosCIAngq9Lo6/BqcT3QmcMzusVTjeGm9jsyTP271smTd4Y2Yl/OXTjUFLg8e1CMwXEIxThy3vQGUdgOQztngtjOWVv7cBl9PlCTri+4yLZfNEdK5XRfbvC1pV78+/Evfk56n73RV5vTHUGEgAvryM4P8h7ZNsaVy2vwjw83229ndpr0Wbr7c7+Uoz3FGvWAcfIa+mhPd3/QJN467k8uWNubtEm+feZEdxeDMdFbsBHXYuPBsjEk/ejKWc2//UVll0QPHBLwz8iPmH5EU+Kh/5aDionYzfNTroOgTPSgJAerciZknvXN/tDtwPxvmw81VDcBDg+9MTjm1BN/zXWjo3iwikdw1lGpZ1CVAZovA3w/6Rpl4FiDBGV3kEVFCQ8Q0m892UMoY6uHzc+iAa5+8lD6eyXb9z+xegtne0W4f5bXNH7f9tc/vdDOh7yrt39mB/39fBa0/ti3A791WFjvdpgu3i3pebl8ys3pZYaHP+2Qkak6YwWm1QQ27HR4TC6GR7guARhAeoB/9nKd5pzki+cQOy9/ntBOCDwFKKAYTPGPhi0QQSgXfPf/v/AADnn7wOjzJA/+dHhoBx/ZuSX4qIEo2E+yQ65/d6HdbbNyz2fI/Mvwd80Ezofy9UcM94Ls5oh8IqfnnTCLZpN6oiIe4Bpkia+TcTiqUK97kCoQqhm5XyAbw4vje3Tbc39GkTvbfdW49gaCbaeUmdOm4XONiUwSjKnyNrmtVNri04oBARusxJltiI+Or1J0Uwzlcbf+IJAXA8HXAEcL2sKhSzrmzvA61l3XDtR6Onj6cjnp6+48PHD+hrx3I8GhNj42b1fOYId8abAHZSgr+l2c3Hg0bpjD5Q7Ocxdq+TrPWLkUIlSFMnW9RA1OwFrEYzXDtgzyMMWZA0zOXRSGMjTop7x2X2cI7ICHYvwwQsqYJ6KCM8RTkc4G/WSITAbBG15iku42JKtA3ut36XRwJWwvpVxy0XirQdo6eH5JCR/8aIKAhn2CTgN5U7k0CyRdHT+ck0l9s9ne+nqA9Z8YkegfA/f4FOvk5ByTpMHZGN6y5A7uHBF+bxCt68RxP8x0hFPY9af/ahUl7zj6HXDTi1HphNqaNr2terGnIPRy3n4AdpaD1tAmEM4Pnp2QwRi8JbV5VmY4agZbpp3x97b2vmyEeaKouHaE0oEB4eTgE/NVtE7x1taRHJJhiQQRjE4GLo0Sgly2IxxAwkunDCEkJpPfsqsLjjR8nEYYofZhV2mB2+KZShEYlLTqOK0VZlISxLA3UAg7B27d2VfswNh4NGoR9aCwOZp213A8Yw/Cmi2R1mymepowE4YtJam8NwhkbVzHxtPZnVMDJfv20zjSUnzPDzR/AMHg5rGT2UyjY/V1Wx5utXFXtmi0FV+Nbmv1caH8bziIjXvqykGdiFrCm9W/2b6+RrlbpzUhxpylilqrbOw2BDIrtkrJRHnrEp4iONnD034M8jo8s2pZX292G7JzShl1i3Le9SFxBWPnYkf+XnRL9ovzkWnZw744wNO0IgrTe6SoGNG7KTzYd9b64TEdnweHWutW7yDhaVnEp0qrBosDLq/HKevv96KftVI43VsCZCN2caqqtImJQgii/8TKRyuZf9HoavGjPogTGullGI1UAZfHKh/+mQRJuz7GPVtN7zDO/wy/aZKqzUzy+hhfL7Ro8PdRoiEBbQgYGeOFINfMZzESClBNZYr5rlZNNXprB3JwIq9NGyM9maNG5WOqRheTjheDhgORxBBKzXq5ZSACAXQJrifD2yhGYZQtjqHDqs9TFwvVwA6magcT7onEwJxOoOI2maffaSHzw6QANXMIgWkEQYuvFeB4sOzKNgmBaAYJw76MjxIw0CyQKB9qPloQ+a3cSzHEVvpHJtl9yLRf+qYTCdn0Du+JRckdJB3YfeOwYPRDmkphbKvq76JmalTc5LCdKrSCzzlljZOYPjeuxcl1D5ZIPU+bpjfDvnfmIjdfqE7yVRBWVMysRF+oYZjHnUcERHxxg3/G55y14LLHUi4CwGvgTgOslm0xMh/CdN9ehp8FGzX8kzgAMWLMmbFPw98Ky9OSxuELgvx/KxOIs43Evy2BX36HN6X1977H9VZ5IdeI8USmdg3RsZHbQsjnFBUYLJne/0mgiiLrQmrNa6oq0tlkKVppTiJI7DCVGfHmJG74FBCqdDOggUASGOUjxbEpHiBelOz0nTvo+uMhw1Q/kEWES0rAOjewRZrlNfr4brdQ0YhLXri5kb2hhgPoBbw/PPZwALxnjCGN9A44gxvqO6E83plpP5mJyr7adJjkcBJ6KpXInf0b8/5zcByDPoCQIviQxQa1oPnJvxfV3dgcaAsBoeuFlWIiFgXTWafAygNazPK2B7Ik8EPGqEfQewcENnxxEw1Ki4qbUDGgZw1gFSUyfbrCWuOLjDnIGGGtPHdZjz2oDIyaLFYWclI/DHZq0c5hfLJBDZtAo68QVznnHmd9SZhcVwh3XK5NDhe2rZWsp+Vd6DUbGb9aGH1KIY3fmLKisQp5EHALEMccQgHkarKg+RLQIZvCu55cqljN8/12v+y0f1acCg1J/Od70syU/gXu/e/BBOCqHn8r+Wq0fyys0e3eW977cwyv2K9u7nNuzbXu1zwOtKZ/sk9+/1/j7i1iD+EcD2sTqE1wzob6+BrgP+wfofMIN54T3eU0/d+wEq/7T/1onHnEZzez0+BxItbJ9fJCi+G0P1caEn03uqg0kNsKov3eMp/pNasF9Q0j2gMNobGW/1deJ9q9aTiCBdAC+BajJZ/m59Lw18XcFQw3QThK582O2LiAWOEPoQdAw8mdfY8XjA9Txw4AYWk8GGqGMbs2WxMSxiTI3id4lBOI+6mn6GNaoDxviBqWHQUH05gDY6Okk4KQIIWAGAr5w4iox3dIdFTxv/z2t/FCj1rC45lkmOjbtuHtu7+qdq/xuBvteM0/37t+/48eOHm5/vEZPXWjNvViaa0kfNr549VW/eLYJnlN8lHvzNh59gxnMjYAAg/OVuWhrPROmMxSejYRqlqr5zQuqdVFnWe56ir40N2Fn3uk5ye4n27vs17988PyvWf32fvm1v6efmnrQWTvOLKBPl8c1AgRv4qOlF9/qd0mvdG9PryPTs+QAAIABJREFUo37TXbVVWIm1KQrO8FImqEHWzkvUcnZeiu6c09BADKzdjJdBQO0tdKvkFgAyVmU2bG36GGb8AkTzZpqi30drCoCi3DmfLyAiPD094bAc0JYllJEpxKhxrfb1prULg4sKwNI7QAKBRjJwWdjwCCWgLc3Sdc57Rb4YDqf2fRIy/V5nSEI4zr13ptkNvqnM3Iw9mGT/KzewKwA8rEJMse4RvXNktlgNM8ktt3s9KkoVP1JwLiVzvgc9ZAopIosoZpiOE8NgYgytmT66ecwOyRTFIQzYO8Ui5Ou1mzVxM/d9Bwnf860iZ7cvcWeNKkBX5PlrkNq8Pzd7+wrFrGf+fqOpJ9r8NPXxIueXfaGMNda+LF2AsdOwCvMCPVuWVQA8tB6TuLHZ1tuUfLSSKRTNm9P2Imo7m6KcSXMckAwsywIiwmXteq/hPlWzCR4ODxjd0yNL4I1Me22pD03pNcDgpmNEEVzSEYsizXrsYVH+bxdIjaA61yFAs0ib3hMX6wkb4RwQAhMa2KNdfT3MaYmbGjf60Dk7LiaySPPWcDgecFzcyOFTIfS+okPT8HZ0wJxoYLjEjUeEwm/5rIqwtddk+ynSscrNHbeNUGPfpMAdxZrM5zLOdaxbHYvcHe89nqLeO/0sCINofed0p9SPHoE/8wmAG3Jcme/vVVzcu6f393r0aQSN9KL+LgBuPGDP5ACKbB0eCdV7NyelGce+t6VgvVWGpjC/be60R+V5KbDmOLniwxfZ9BeRIN18DPoMJEj6f+8xzeRwmDfo8bvtPyl24pddbL47J4q/7vTmb3YnGiPucJ2J14Ke30LhmOdXh2VxiT0v0Qtxvv1fiUDfKuZv93o7r6Q59ZQH5+x4BOU/lFOLGqrvIKmVjjkfRYs7knia4wJzZAbKMrNu9c+jL9oYz1lNCawsCMKoUOgo0xGHxwXNIs+1dIalwj8cMcZAe9SSGYpmbR8F9szBHCwtXboI1m6pGaG43dcPOEGsDnrgPVgkjMQgjUYA5OnRCWCsQW99DZg6CG0XLIdcASygcw+GmA4EvjI0NfIVwCFofcJSKRdEC1yWJ4+4FcUFw/hugSoX3YgOII3rYxi/SGBhczSDKgmZMZhB3RxuhkHYhGfNQDmKAdppqK8FAZAN4FWZbpLvlJceJLH/L1K0Lb8V997e7ftU7Gt5HQh8PWVuJ5rGoFMheMaX+B4jlKnPaaDB5/h3BH9P4wzBwXjiM/oTgx4oRGrHkskzY0Lg9XWy+Z5zqxeSAyBkWRPhDhnAwhxnsdZpZjuvMY6ClxxOhWDGVP1dYSKIE9RNQ5/pImj+zGYjqaxPXVcChQMc88AYjEFauQA+GsleiBitLcAQ8OmEy/Oz7SEhfa/sLcxBJ1WvpDxs0jaT2WQAR4I8Gz+xNkCuaE20D/4KloZGDyAQunRNDysdkBOGfJ94mGkjZQM/wfcWvGq03RX/s8lS+bhJDPMFNccav1lEr8XvRgAFMNyh2RyV37XwgUEYXaCZFs6I6G+nibDySlA8ssrQPiLnd/IkhG7Gc4MfqUZ2RJa0ATV49D60JMCaayEQhOfENN9KY1NPUJ3Y8lfLPmDXFSYKr2RzQdGLMvb89gzvlwepXLjJOOPwnCyKGXKr8bzICHbb2CiFZpR1h8iXyyq+VZjZw1kz/+N00GmcvPTsRoaIDow2yrbvIEwbvn8ri5R76hjf0grafbF9lN8nnfvv0d4+u/vtU/n8W+uav+6YoL8rDtB9+2pg/FHE3v/6rOodRDTN4dc25V6SZzVUd/u9Mh5ktFM8A4n9KTJe/GAHooLO77F/f+TmNpcfoIGLH0X3Pvc/S/AGxiLC+PoV/PGjfoXzN0nECQjFt+M+IDOTLMZ3Rkkp40sFatcWAR6hOqQv359wWBpAGiASPJ3xwP588ENE6ExqJHd4FqXhAJS/poGxkjqF2Y5rVkGthU6NQ19ERQ/wuMecIfXURAT2qPg/XTN+E+87N5OM+idtfxoDujMd797rCdPfApi88A1IRNOoYWFV/p2OC9axpgesj60ogPywb8f7XN7xQQhfdxiht0H0PFZ/YoExpyGQ2e/uOW43NvmMJs3qFmsc/FcC2t8uOP14wPJjw+UnS4mHHwD5skk79L4mgKUy21yXefzbFkjB5lRF7peeu3m/7I873k+azv2ZZyh7r2E85MUx7//NeEPxtO2rSAQROpQEKmtE3mP2/0HYMCYwz6Su317Tmr0C1iqPVufbU35bVBono2/0UIk58lxFeJsJ8BA1gmqkJMW95+czrgQcH0+hnAREMzDEWuYe92uHQNPItSKYt9YKzKnHcoPg6flZmQkb7RDB9XLB6fFhZgA9zfK71tglc3IpERUWtwB8ejihXzuu1ysO/aBjLs2ZG00xWZhgttRuJFiWRSNpLBqMzeCnSXZUJI1hQbKuu41HdaOuLEER0iTqoGs7ALjmJFwRJQDMy34r/HkaO63VpjNy/BpRDCX9O4EwuIfySPtb4ewoufRuTGOtRBbi6VkglwFZZP7NmX5jHMcOMwfvo+4aFfxVtjEVXHMTQ1RMjBFKtjRMTXXm4x2pmLvFKvvYuqKRvIMS/4QCd5reNN/JcG/j2OKBZO22T+/3G2t3B5/c4puM9aEy3mDvpZvCPhWYBMMnJABbxNLCmlIXBG4MGpoy0jMuqGJdMzbQesFqtSsXZpweWNOV81Bl2RDQSqlggwsDrnDVa2pA/I5jX9DagtNxAYixLIcw0qug0UDE6B0Qq08unumcyOoPI/DNXvmHcDJw0BdyNKrnrKvCd6wCbguAgdYa+rA07gJNy9Yv8NSTZEIyM6uhyfrmxmCwZfEYlpbS3j+gRteb40NhRE9IMOXfEKuxZT+WEhwe+exOBhBPDz0i28kMXUCkOxNAC8DrCu03mv+6IU8YREVQtd8cL8j23MRx8jOTxsyXW/RuZ9L22IRG705IwtFuNsprtF7wXsPmsCFNc3JT50NSzBbDQ0M0o4Bneck5jKAHilcI3NxwrsZDcgldRG8fVgN7dD0LfcTPt/uxXacNH1L4hzkyE0mTwlDp22hCp5U1kbJ/jiAnIxySr7tpsXwbmm0YTedVs2BQwb2GuIqoEqi1dmXjEOhyF1boVrcg2xVzyrS50TvwIRDNfVGMNvBydSbUOtCLZm0hVZ4ojhtFjaKRBmIlK8Z6tVqwYsqYpOUALIOP4mE23mAiMyg0GbCz7vX2Rrxf61X7fbOy3Rc2ILz6PxJNt00w8Rqa2FwKrnMVjEX/ysGd9vxAOj+gfBkBWNdrGvdJaYmnfXeHAjUgJHUl3xcR0GFBO3DUWtd3DPROZctJ5dpliTMT+HtpOJ1OWI4HLM3UDKL8b1dCBIyBDgJkQD4MiDxgPHWkueJipTv8OCmcNbHMD0xoY4AaQbjhcDjgcj7rq5gxRgeJVcPlYvgQ5zUJdPC9IuAEyLOAcFAYInO+4HR8rw50ycUTqCutbccFQoROq+LTs2bdEE3yFDUdI7ud8Q8K7xz7pyncGTQ65hjtymP5JV3DMPi5rDOlfy54OTYwlWa6Ro7kN7zbLtDuA3I63fl8x/SrD1zGhg91AM7NxmYQUy836Grr7RwtrfYiFLzN5FcgF4V5PMAjeQkEfMh3LR/UlLB++5K0QF88ve3ybTaVHD98siwCOrX16wB90GAKQKzkD9ThkGweZX/cgdp5Zc2KkXg4ZDLbe7dnesYdF2Gd9gwSkJ8ZaJYgjIrDyN5jn8VoIxVHR8se0ixiXM+9AOakrZFiAi64f12vOByPWNehThqe6cZBrndQO5hjlMlKXorMz1tbIOMK6QQ6CXD1GrnddlqjuDVVfcZbqmPPEyACxgldnqcSJcaNBuH0bAlb4lkdLQFk9R7Hs0VJFOfK4m/6BQCrXBBy6xgagW8bN8ZqzoFW85UY3BqOh0V56JHOh713iFyUNxsngJ4hcoIIg4ZG8TUSrMMd5XVdx9PQdzUBcde5iKWLZwIWO3/u8D0sle61Gx18sjU65dIIMoVfmX9iF1Ge29dug0dD8CIrj0aJpzwTTay9JPsZnLDMOxXNMhf52WCi0Gf6WNSQruMjZrA5bHYfA6AOUo5yjccL3pnYnEkCGAqfPoGPwrrDRmWSJj2wfj4Zn/id1PgjoqUxf+Yv03ps+9i+N/hro+t+19SHX4+vc1/BJ1XUjMShlZ97rZVjByDTtn+Wf57x/JO8btDeRpu/GH0OLV8KYNfg/Hsaz//Pj/+N//env02/fwTwLSQD5Ra+6IPGf79vYX9AOi42o3OVF69tu5/b6/XtcZ6KbBXwGrLDBjb9vp0zsoXXP2Pz8+NyiBvRU1QRLPgE+qxX1jFwJGDFJWQb4nSMc/hxutCYQXiE0BlCwOHTJ8hXAX8iyFfBoO9qsGbCIh+w0FesAC7EODZ1oDss+s8du5z2RRlJ1/sxZ111kGX2MAd7In2GgANrangmwtJU5/bUO4QFC5o55przstHbJ9Lg0KoLJpvoXcenWMN92H9PS+597+r73/6q4/e7WlIszRZ2e3pjjWyvInvZn7z9aQzov7adr6umCXUG+h7MBMMtN5cJsJRwKtCuHoUj6SETRnP7OxEZN75s2vep/uZ72/6DweRu58IAjc8gfEElZQTgs0gg8p/5F/z1px/Q6edguBg/Y1CNdvh9D95eb/TC59eWjN6IMd963xt6uv1cLxV4mBgWV4bEeII0IHfRYcqeKut/sw87DE685g0j/0e1Cm91vUNpJ2kA9FGpE8htlLNDeKTou3mH91BjBfWKdhW+wH5VI7tNWGuxJ5TK6hhv/iWbi0fgIc7G3mheaEXpGQq0+N9m1mTKBBpoizIaQEbEBgrbtN67RhFR9KRzd8anEldQguUEsz6+8HksLSSxSai7uWW7LLbHYWCbHAZEFQVIwdHrw/UuqkwjMobK97qko67CpV0jgkZ42DzI4Wh7QEzB5UaPW2H3do2nado09uiNIPv0VIDbKCOxMThJ2X+P74qmqt5vLwx0by8SBEMPK5E20t53R/AH+wYn6w/sguOLbSvQ3Ty/Rxg2Y94OT9FnMREOqNMGZqVaRPeZMOjkeXQ1HKqCbIDQ892t4ShHFVSJ0V1xxIQDt9ngJoIxKGBSMNBZBQW2dO4Lq0EjHFWIUiEZ/smADDXWC0MjVIAJnikM8A1UFspPSj2OrtBdL5aG1NZsjKHGeYMBZrYUi6agHR1olQXVB5mb4c4VrS3ofY33ZNrvkfPaBRJbJ08ZZjiA7SB7BAqBYuPdaSai6pHC+hZjzTqjG0yL2wOyQ1OKskBKP6nAKl2KTN/fIjuJ4Ucnm4rj09A1jV5mNJK1iRNn+xmIkUQ/RcFokec6Pirv8mwgWbtT3GAZ8On9YtpThUkOoTGfGxZp283w6TWf7/HFlfa/tnalA2fNy/c4Jz4mvy6y/2p7/2Qf+lXNaW9+Vzy/A3MVvxkD4Ap4r0yiLGGNAngHbFV8OZHt4jjgfJP9qxjE+dS+rvkwOZ8SpyFgRY0A6mzX5Zp0UGaOgkDgUwN30tS5dZjlbEVWClcQe71wM6LsUkXKkUfd67CkFoN18JYjz8wO2O1jilxS3wsttS0WJqelOLypUdb5F722risaa6YOx+VsxmDl93TQEZlf1oNEwuDenKe0iGnCSGdSIvDSsPSGwUOdFlidtRozDscDDgczoJM6LR76irUftCZxZ53fEAxY+Y3TgDxZ5DwfQXQtawmrl+jMshaWcP5vdTgCIq2kGO3Q2NtYVQAEWsKtI/7LJzWU80X3kw9sDhkMXAE6GjxfRHFS5WsEQUNiwAdoiQ3HpyYTjN4BIvTR0cLwaHxl4JaEkFBYheHGOFDXF4Be4OPmVp2saeoyeZn4UIHzDrDeXpL4s8cmujybTpsIntrnlr7f5IMuiElvyOEQCCcIznfnHLhkq5ivfB2eoRkIzKT6nSCPZT1EoFU/n6P03quUZCNTCwB8h1la/GwZ/yFAHyuYmslPjC7DxItCFGMpjK+CR4+ZU16hgUGX64xF4XWIGtMBDr4IDnNewifmIFEKg8Dp2EYw64qW6DKsAmLFFzWn2QpVOK7XpmkJx1B+18ZDSAcgFH4j8aoq6mnouR123sY4AGA0rJFaNmFczIdCo8bZ+rHLgQ1iOauhpnhQOg+j9MJ5No3Mcz1egc7cfu/bznvgToE5B0nQbhFgSMdYB9AY0tS40ZZF8bA0k1kFuAJ97eZUFjsb8D2gJSbUeYoiorwPnVeTFaGngDpm6Dabc1NkOjgYjX2azrIbP2KtRQA8By4i8K7VzR0mIqPBJB8mT7VhAeP7Pm93i4F8uxwM2NY8DN932jYrRzzzOsuYo3HmaJfPrM6p2OitCvjZhweDWbaopnv6kTR23xmLw67djW0/lXb5hXh+uhTvyy5e4nnf1n7r8+9pX19iun5lq7TgKxS9/1bD+V5bf+o3RnRGGvA9C4VPUFPIv22yH62vGkaT3NJ+yzfdNtcFbq9NDyM7Twfh/Gn3vBfaJ5vvf8b2Ufb3QXHmJ7S/KFFcf/kFCzT63LWwXGQggvpPAcpnu+NfdTq6fPuGIz5gfB1gejKaTgA3jOMZ1BlyWcHLQcuqcMPSlsgOSgJ0L4/n9eyZQk90WbvqiFhz5fTesY6BhY0XMr6gD83OJGAI1yh0c44dBKBjgEFD8CiyI89RYXl+b6vUW9pbENH+72+R0d83ilmCBpIWtshOkNfDtvEGXcp/cvsDGtD32NDf2N3MQ7wIsv67B8om3yz7eNoFI1f+3Lxe0VgXaFoqEK6947Qs+H7pE9BG1YZdLdZMWrZEzZFAKEFuAFvyPtxneMRuoiGxBoPcgV9M8QwIfkYHcPrvH3GQ/wL9z08g85D8O/+MzyLptUelpoyN61el69kZ9GSwQTILCUX/mAP+aN4Bz6X7p3BoyPV3A8z9Rpu/3iYWotxuSGwDH3tK4Zh7YUzuDoVm+Pqt588CLnB5kcWaBrD5Pj+zWv1cr3PbXGtJZgA2yYxc80oGv5RGIwDmoj9CeKXhKcHcG45DqeTEeqy6iWo3089MKsBfIFaaQcesz7NFRNsQDX94DWAVZIw4ufGmRJyLMQd+7+1SudJex1JRXF3JG/xQV1e0rvJ6uWI5pMEtnvX5W/3m3lcQE5ZFlaEa+ZXYpDGXyFWbA6zO3abjUFsamiOkoOcshVy2B8dq0OcMgogTxIx15J3pVkOKAdKN47p2bCykRrLbW12JAMq98LrNPgVSh41+UUUHnyw9rAfHh4JeDZxe/9wV2Ksp6dmykUgsjkXG22gj9asTJP+60dxVRVr9OyzyJpedbK0J5lYAr+/6ltNZ74l3XgB+4Limx27GvzHusi9bQuqM9VuYsVdvKQaBMtidDiqxLuoaznPv9wtKJIQLhZaSCmNYNKSq44gP2htzwLWQRscSM0i6CQcjYL17SmrR6BBVXlnKxGFGEUNKD4djrNllvWBpOp5mzkLcKNKbq8IFGH0Ng/AYHYMQqeEhAC8NvXtaLcEcXmx8Q1UAE/mGxhoPoBhxVhsuwWurt8bo68UccQhMEsabYelu9Vxy4PRFFnReLaW9ntu+dqzXK66XhkaMpbHtTTPFm68HolaiGu6HnS+ytPE85WLQGtpao9cjXcv0C8yowlOdnvyAyQYub0+Ur4cfXk/d6mOu0R57fST3pnSrjikN1jvvhBuxKYREBVsrF+Bw6lhQ5iOj+0JmGLZxsk2dgQzDqjBTDeeIeYlFU2qq4MT5EYlOiRoclXs/NnO7R40vw3Cp1ueUdKjYWYt7XE1SkMpLVu664AHn8YnCwOi8Oomge0YBSierrbtYtQHVcfq49UiKBZQmXtr3+HZYqI4MOR/H084n+Pwo0mEjIgFd5LgnmFcyFOhbUuE6858pcNcI/FpLephhSPsmLActIn29KMeo34H1ulq6316ZhYCBGB8UhzbSiGNagfbQgLUZb3cte2vwaP8i44T/HRl5HrSB3B6gu9liXg4emdnBl4egDjtdCi++PdcJXmVXsw2rP8wX0jTjpTSHkPIQSo5Y12PVOTU6gFkCd7LxpZYjJc5WlSfYeUpI/C4Wvd/HQBdBJ00pHMoVIoyloV2UZ232m/NPYwCDlaZFnWT4uSZdIM9qYXiUHxhyOUMoI+RPxwdcLyuGqEH8QIvyYaS1ERdb29aagabx823J0k4Q+7/iCmoUyqExjP86A3TUtRUIpBtt70DjlhHMvkZHBQxmst/shFC8EQRoZAz1oHE6hgFcBWgN7bCo4lAGhkX2wvAzxJ1EsWnbw5o3ZIkixdpEiZ+93EE+4mMlQN0Tsnejb7D09IGGgvf3f06h9jCsxF8irTUMEcWRMj+ZktH2xOwgpiMBz4lQd43oOyWwnM55787TEAQiz7AkpMbPOt30NTNDYpGpa6uUAwAu3zRi1BXX7aOevevXFQCBP9jKG1xlZq/D3K84j8HTnjhf6HgVNhcbYoGZdMLIrVciTlJYmbJI3uMQk3FNhlmYwbygLZqholGDVzVzdoCkWbS1GtoV5whGayBece0dAJnjm465X9cYAzmdh+geMAGieGzQCD7GcTNEMOQIHgzQumv4S6fjR4Ce88fCywaP4bQl+mk3/enieOYcufk5bvpuvK6U1ONG512voDyoOhOuECySsMTMWubNs/AwcGZgHbqGnhIXQujnbhlGnFZR8hTBb6kRQ3ntYhgnBsSMJh7HOK7zbOjRToa7H1gdXQ9iILIyFAKRUeiVZ4dJR0ja4Eh2fB9g7XqWjIr0+x8/fcK3r1nn96b5mTBHebuUsGC3caXh5fBS6Wd60L6GfF5ukw0clKeCaapZOIOnD91y8vHf7NePzmcBWOXvuAXrAnd1bvHF9mr6noxeXk7an99rn/XX+d1B9e4xjy+0z7KL2V9tv+aZ3/bgy62WMf2MjAz+vd/7N/wd+Cm/e411hubh+ArCZ6gBX6+Hi59Fqt9vTilrTjWCRrN/3n3ibW2PbfmL/tF1muhUPpOynNw8P30oPztJ+Adt8x+mfRKFuU++BOR6TV2DdFz7ivVnhDMbf9Y76NrRISDjl/05N3S3riUC28ePIAHWZwoZ8EzfteY5TK8CjRRnIZyHygfLoobz07Lg4XjE6XgACeHb03f3nUuH5Q6gDTRo1tbr2rEsLosheK1GhLUPXMZF6VpbQIvxNKxuhAzCGJoVRFeh4yQNX3mFJ+x6L2z8HrA087KIM/n2J7btPaOaKFFeDbpYMj+4bo4bbvUPWzn1ra45/7ntD2hA/4M044i+na/4/PjOVMr3ugyGVgWAhVkFiVAeuOAjyZGVVr/eCtNvHsTb7rH7Dj/+iOtPP4HoDgk1SWbBXwEyzzu6ZSCMx56G8GuM6Pdu30cR+8++5d67fdRtuZfX5m09veud2wtVUJ8jz7dtZuh376IZSe6+81/cbl0+XMJMYcwVYyDAM+lXr8bbZufOvrker8KpACClw1jsu1hKmbYsakhxxQQEXdSrfyFnYSgUHlYKOfdOtF7ZsS23woeY0FL3BCkcvSWKbtMdaAdWT6fTTup2Ww+PZDBGp3EqxjGNaxYw85p9JqhNcJp8Hb8LjpIP2DznGeD2vMU+j0j9JkU4nLyqBSGMm2oHMlTAVgWlDpIJqIr2OpTZSxuTIj7+AXcZNYdTuIGEShYF2r7To8hNfK3CLm2+Y++M2DuDCYJLuhv0s/fcHcTm+3TZ//le0ykVQ/QNvEuc5Rz3PIodkohXGU2Ht+lBXXf4mAphcGNmGBRxmy8hlLxmcVLnGBU72zDG04ysbtQT0dS0w5SAjmxcUFxXi6SNmtA5ZI3UIJwOR1Wo20Ye6KB2fFYBojXGsixohwZmFWJUIQd0WS0FZEkLT8CyHDG6YFlYU52XWVLNc/kKverXNc+GpCHRHZ7GKlhaw6ABlhYwLabM8XILwlqpk4nVf7jUwZQhuKKDryuoXbC0BX1dIE1wILI0jPq3CdAt2lIdkrQftjSu7rAx1ek2RaQbt30OARwTUNknV0i90BTdWZrvguecbjmgR11oe4rs/imaqiicpt3ZnI007KXxvF6vU8nywpL7EuOkxD2k1DL4Ux+naSGj7ExVOJb3DJOW3Vmr4sz6/XbxdOBMHPXQotshUUN9DAkYfA91vIn4jyHb3vq2kDsgkDl/pIF4iHrzqyKjqqBegI39ZZrwehgJts+9PCMbW4WfamCR3HcBhP2sz44YdXj3ce/O/Mo6qVaGgmd11FvnQA47Vp6HfA72fDiNlbXZbUTACsiC+f0ic8roQqdHPfMllXsa9iTq7RF5BKP263uz5cPrytB2HXdWMMZVetPnjPdaDurEDOdncz85HL4AQlNHLevPM545zXCHj1wbKhu7wWNGi6VbeQTjc7kx2sag1lrD4QMwzme040FLmMAz/nT0NUv3iJ1jZgZZuRIhPTvDZ315DiWuKvZUTXE4NJyva8GVbpTNFc7vNofh64bgqQGDQZGkDWXu4ypgWotksEANy4V2Hil5cceJZ8KgAekCLHa+DO4D/jYAMRkuRDRtu91IgMkieTYDH8Tzt+fSjU/ztRk255NbDuTOOfdzCx+PoNoc874bvrK8UAB3PhMveyKW9YBgdY7lps/sIEYys2/BpUn5Ow0KjkvqL1IXEDa2+PUJIifdgScGHpMXnAxYdwxGe9ySB0dUuVT3lP315br/peTZo0Nd/HC6M/zuZ9r32Q3NU6PajW1iofNwnbP15fvcAm94FosWxnNmBjeaXsKBuxlCmpnCDaOrZxMCsNq4VUt+CziBX7nMixuIOzA0W4Sc7dwQhwPQGAcQX/JcSt2rJzR8ANEDGM9mBq7yVRprK58TWQKGr51+d0Nqk4cY94qn+Cx4AB6fIU9Jz+D92ztYzFWANLuGiFiae1b530qSuJwu0IACgmIlicKOBk/i8kt1zHS651kf1OFKvHQOCELdHHg7zDsSNHo4uiq//GwrtljkddVCAAAgAElEQVSE/rOtT8EpTlMq72y8EfkEjAarc8X23DK8roCyDxUpmTOnCD58/IjvZkQPjotmSCrs4wxb2IO4bM3WNmAo1rHwqyj8a2HcpNzrjuuBsu3W4ZuCXAugGuYFH5xe+TMEbE70LU+2la+dF7aXV11IvS/wZ9F3SO0n5lZedXPlTnuVX31TL/827R8ylx1a4+niHf7JrrnB28+Cu7q8NSJekKrtGt3+3nnp+xXw9/je6QzuzG+33NXmvuQMKmEuv7wB9v4j2g7P5nim/uSaXudHGkF11vaUYX0wf8wHGVhFjfBXox8PYlmVvf9B4PEBjK8AKa1qTR2/WrOgMgALN00eb/I6CFF+03nkLiuot8g06I7YTMDzZdUMUcToLGhDgJbyHvOChTq6RaCLMNicH29Bwfg5Sr3kf2Lbk91d5p5JK21opwcWJP2fO/Hf/iyH7Lb9gQ3oW4B+eZPkTXeV+w3DyOb7zBYIunT03kFUatnddOTqjB2pstw3BvD//PgZT89nEB3AvOL6fA4BMsbiB3qC7nmGD2IRz29o92Ta2qs396T7DESpOMJfQACO/73g+W8+RoDls0W2CQ7/rZFl17/dEyrFxDRVXnuN6tfGffceF+gLcd6bZwrKppbYvHcPyu7pAfx9QEabV+PUPRw8yRLTm1+C1pd+KxHldwypVNM7V2PRdsY7z1Ny3G8cz23b2tduz6cz6o6c8xz5r/5JMLC4AQAdLASzls4GN2JgcaG8A5CMtqqSVTFITEKfK2wBXJ51BsvpYEJMsYgWpMHGGHBV4olkevRmSs3yu3u5e1dtaWA3Yr9AyF+DGGx+DwEogNoVBRTC6aRwjE4cpknTa4rVZo4IbV1rIjJBXjSSRzytKZVM94r32JWUlMpKf3eksENRXGzmJFEDPecWwqIL6GWNQqZ1zCObpSV9T4PjdbEopJquprLlq/Xt9Tz1z3ju6JcRilCtpewRAWkk9JTDIWzfQW60/WlzcHI/YXOyGyotEJu1iEaHoBgMqtA+vWB6fPevHoz5qf5shuMT7/eWEhJck7B1SohbxeFjR+C64d02mhLQ/tHhjK6acXTBRCJz5DkB5MpyIqv9yHadrJ6f9epw3UeMwWFT972boknnTxFZpimrxhBcr1e0ZYGAcb1qjVjxwpQWZaR2YTM8WEpZXhqaAfvhwDgcDjhww+FwMhwIVZKJYCFCJ55qao4BtFaIU4zP1hPIf75nFunrhv4xNM0WNcuoYO+0FQeagEQj7rsQ2PyN+pXQG0C0mnLPMl2IoLHWkNUMCXlw/VxdV4AuhGu7Yl0WLFiwomMxBXIjRhdzc2ACNdYwUCDWTkSitu8EGJJKMXfGiShtuz489ZgU40fAEmLfko4mfnLYdWU0UB6nhOsw4G/hmSwq1OYqUoSeggOSL/F7va+ZZlYN/e35IUCs/phYpJrhkvJSaF3W20drFh4IrF7p7EiQyy45HKMTIfQWHMJRT7ZE4hqPIBhRx91mup3QzXpGlNvmDt9X8kGR9kdsKbEtkkqFTgFp3jl10OoGF9VYaSxEvHerHLK1NWYk3+3jccCydQ04285nZw91DB65qLBIBmNSwg9dMQ2ZU7Te9JtAPhsfBTd75sYPthIw3TK6LO0QZwiARRhm5HlblpTRaJjBE1HOgQF0k5NibgbnWAX8ONORqtQWX+t6juM813Vzx0yLZiOHz3S6eokfI1jCo4lzyxHl15kZUArRgAUY5w4agqXl/gtQ6pkXGANgy4d+vfgGqGMRuTJEIGGQEogZ3Idk+noq6+FZOfqwUi+dcVgEaM1qzDe0toCJIVYLvbE6SF2vV/Q+1PHSpr12jWQHke2h8V4yNBPL5RxR1yJAO2pK7fPlua4arnIBDzL406gToYFqfiaoEWQA6iDWO9AbRK5p8BHR2oqjA9fEhdSaORwwQBJOHP3aLduVjoaPDJw1+wRxceT1QOiHcpqJIiJSt4vjvDk+9L1kInRmSO9RtkCVjIJaq3wyvBRdhJ/xzHCCxEf2eQvBRIgawzM0zs2oBbYG5fmeuYeqOwn21eCgKi8jNWR9vpDnypffnhoB5ARMUejbSOI9jvf2YvK8A/gOiOiMlw9qTrh8+2V33vV5urlSn3tU+PxucuKnNI6SQHlGNjxAAEVad+fVnP4P5bdIz5yyHpoSVajgV2szy+wGZtLI5gD/gtwqb2JwSU3PHFPyMhNbrQyzwlNjkDC68Wcgwlg7lmWB9FVrmcLrXgtqHRk9fjw53IEo8IufGX+viM8JwDgCOActi10gQseTjfkEkgGW5ynjiGDA640H3UXyY2K4UiC7ivd6Zf32BIDQGMZH6Qab2kyz56BP+NlSrlhWFOWb1qHX9Z7bM0l4iJNRf9XKtpbNA8Nq0AqIF8uSpXXjh/OFYuWO1ksoxzvNNEbn/qS8Q5EdYLoQAsH94cT4DAcLEeXUyM59ZMNIccv2ndBAGqlI5IH+YFhGrmQ5yhogDl7iuUJ5jZYLrBJKPpU6usL3AwmOUl448xI6SZERRql0fKysUuVVEfehfJbS96MUw7f8gGf6ZUIqN2An+e7b75ldau/eGFN5VDZ9CSyjX31lWdt77TV968A/r/b529oedZivfRarMV6aRwL7VP5i33++JbPTM35529/8+n0iWzlJBw2G1jD3H/6OtwXbeCR7QzppuFGeAPyCO3RzO9TN2OLL5uFf/kF7XlDDP7TtzvOf3D6JBip+FuAriWarKGPq9s+bALh8+QKGpl0XUtrLROkayprRjx8Z41kgzwIR5UUHUp9+huKND4DizDEA+YJzU/3LAeZc6/x578mbE0IvpSoLLQs1OlSmEI0050bqywXg2lcMy5I4YPajwF+ZZrwRrCShZQ41fRINZW63AVa+k/8suHkrvEz04ze2e46eqctHslEuM1DZKyD2Tq+5dPW/Eeh/YAP6H6c9rytWeX/UZ21igvx6XXE8HnC9pmIWcOdfRVLuwRsesJKCqnuWvtV4frdtiNqtwKft+tMVjIblv9vNYRF8wfo/P0DwCzr+guN/L7t1Az/G2JOXvPe+N4/9td/k9nLlZf61B7+O5j2P5eSqILX1rZrAlGDRrbjFxtVQuvPsHLWwP963zOLXEoGJ8S4IXs+IXYxoqjR2aFoZ/X2IisqWAe524ycBsOxLSl2qHDzohXHW1HsCaHrvlikx3ZDrKS59zK1VgT9k6BAo+6q1foEUQkXGu/BNBft4ahKYaOa0UQnr/ns0MkvFpojmgqVaQxLXUC6DJuLqD5Brvyu8Sb4DKIZHG842KjC+SU6jjrM8GCqEMG4JynjF6jDD3qvCbtThZaCHgvTWqLSNmBxmTJQxMFY1mA7THlgmbmAozKpThQvd1bCfn/f2oN63u09VsH3XWbu92Xbjzfff6WDT/HTsGM896h5A5Ibef7x8QZz77W33hui/3ZwNYD73Mbbc420UsoiUmpHGmEeUYt7jCpFUwpmziCkkSCyCZF1xuV4NnkasEREgJGASHJbHiPRtbcGyNHw8HvWa4YplUaMGIOCmESIkjGVhhcmrRcYIKUySoI8GEcbSmkUqApfzFXRgEJsRRVJR6KnOxxhY+1VhnxDR9uE8Ak0D1YeASdN8eQRMX6HKu5FCjtebVOO2lcjsQ1PLl70YQ3C1WrfLsuBwbvrs8ajpg22fGIzGDY3UeWFwiIiYnC9o3ncRKueTMmXvBi79XMoG4O6eEEoaGnzQDTne4sxdrA4yoXds4Laerxp5TuXdYczdjNQzc/g6TAYHATwa3s9iHF83BhEQweGkOxBzwYiofofvmbYlTghlq7/M6cq8ULe00VF9nQc2S1hWco8V2KgHK9FApV8ehUzMaFaqRUwpTq4QLrSOAMt6QDdwNK/ApgVC28DBzc33uGkCUdLum2wKBMuEsqGnmJXwmaGgDIz0B99hXWuZhuHOQgDCsEjxfIEvW2syejsL9hXY4rWKK0CQYlwhe4imM21nufAT7pTjuNnvCTpl/I0qlwApEZYzrzyvucOPb5v3OF6gqGVFb1lTgWmE5h+ZCNxalM1hcmOajWMV8OGAIclz+POjC1iA1Xkym3ucuaBNAzR03GvvWqdeJBzSAFcekCMIaIp4RMRJXzsGDawGB4lyFTtwa6DR0Z+B0Z81EsaM++TjPgvo5DgYAV+69AZfxbmNiRPuJNMET20sYOsTIpblyeVtQPNCeaxOLvyQi2ZPsQSZRMC4DAvWJLAwSFbzEV10TS+AHMu5IDsXXnKK0rmg8njiE95BVu5sFnjc9mx2QvKTRqkgK4drOu/GA7+Pd3yhSfal6ouk3/6KyXjkcFjIsj396qAqZhRPI/3KM6/9qmD2DFhUcWRdAYDvAjzmyLZ0dPseH5+a156mX2+wth9JusXBE+7fAHSIZl42TMwxihJna/kx5flYJOqbuj7pXa3g6FnZIPZ/U8gHHyBoSwN1zdrW16tGnTFhYIV00kg4IHA1uaF+I28BXi6JABbNBHFx3JC4DCAMOdq6nQMFqjGdjfx4BDpAcgThCeHgbGOJjGEVh5M5LhgvwwAOn5QOffv61d5eN0eAE4POEjoI3zM/t2TvAwAyB12BllxSfjcz2wzXJUg+ow575c0BA1eY0sT4XrFsABrVrryLwZVk5iv9qqMgoogerycy1iPwipRYjYz+d32Nl7KLvSQz1lgJvoq/lL9leL7foLWKGNF7yWKxAcMbHEKY6ICAcPr4CZfv33IOMLxKLXARi4Ted8JhNq/6N/BwmWMMJlkLuMRQ8fW0f44K7SsPhwSxNS1rPo1dpr8TXPhClbN083vwQ5v+88ItvpPpz/S5OlvQ9rnS/ljG87e1L/UQbJqUf69N7Wu94V5/230trXIp9d3++Stm2H2J8vmzHQmy7TfYO7RRsPpb0ePuOF4mzrf338wpIPB9Hf2bNHfU+EpZFpcB/FAygPg++ufnFMPwSTJqXGUpq4NOwCoCHhosJVe9caU1yniSSDhVAFBZy/AjG/5iIjRm1UO5gy+rPsbrnovpkNwRjQaBwOg8sK5a9nOIgEbTIAfRmueeHSw0OaGDcd4fEZiSOqOGhQncBqQr/wOYMz8VfI79M/anbsYjvCTz/meesre3fyMD+ha4/zFbt+V99t5858lXrish+/L9CcSMhbXm2aeHE76eL9PzEQl309PrI9mj7bL5/d7SCYrwbQrcQV9UsPnbXyEQHH/8EZeffjJFrEDwS4y5tQWM9KzzNO5cPrt33L3d+8vQ4GJnLooucndS2z2KGlx3H6D5gb01eGmALzSitzAAvxVuXchIQQkTgptvreyEev06s347jpf5pXsTe8t8EirnuKr7/T64AGnfBwRXSSGOR1eibHcok2ZKKfVT1jTr1r3XAjSuIZQ1kfK9RumIYDkeIvXlMKHNa0YnA6HPDxb1ZGeNxgNUGGNO9NrHwOdPn3B+fnL1gikCgMv5guPpIdfJjdBv4cLLKlL9Ui9IrnvcK4J1XXE4HCaFW9xvEXIy1GNceSwyhWxGT7YSmU5M6FbrmVmFabYaO5q6z2pOliiDRDUmcIlYrl8TyOEy8zXGNp35RFWToBCfKI9IVcCqAkI9H021UJgDQdRDF/NVD+WyM1satcQPWgv3fB7oWG2thkam9xVj0drW0kekKKoRb8oUaoTdGANdxj4jJ5t/Ny3FVJ1Rng24EnVa1fwWawmA9oDO4f+C6d5YqhM52O4MzZ0UyrtC8JbARx5hdaPwpvkD7f+YV7ZDd3pwg9yM7a541CLfYLhECBZpWpTcQ0uuiMGxKntY66A2OweiEWwkoq41pJHVrigbY0TkpjrPNFyfn8Po6WdLmXxVal3XM1gajocHuKGgcQMvasQjIvR+BsBaU3zMRkoioHk9WD9rQzBWjX5ZZbUar4CMgX69qt5tCFoJlJY+sK6rZloYA91qWWkAXJ4/skwTXgPRDfHSTSlXlUemuAMJqKcRZAw1oIeyzPZJhuKT9XLBmRnu4NMaY3UDjJ3pZsIUW62u6wCEsz/H+0EQKHILwGJPbf0cP9WhSDwz6ZtsLpFq1SOKICXqPA+yv0nXDYZ+PKp7lLNFgEVZqwEXyDSsc9saz9OjOOeRZ/IWH8T87BmnGRBEqYnp/EAFZY1o3bzLcJG+s3Ik87uctldEEgpdAUTUIOz1hreCXay1PTjjOruWFQFu6FD97J72scegOJ+69ma4ZD3nWlNe8WcagH1PKXgxp0Nu1J7T3utqbXFe7EHN1iObAe+2xO1c9ikiaoEw5gX1oMTJAndsyQw7rvSAQMulTrSKElb+f/bedEmOY1cT/OAembWQks7SMzbT7/9sbW09I+lKJItVGeHA/MDqkZHFIkWde3SnXUZVxuYrHIBjhcOdpXDwenoHgbCtq9Zj/fB96NEMLs8vsV9SCShYTuq5rpErVEkLqGCnDVIlEoDtMtA6sEw5kI/mSSyEoMJ3Y6VDC9kUN2jEkaBLMldXeK2JjxKOtyd+5aAv5HMHgx9obj+yw0yLKCQUc6TbO+Gx0ngsyi75/FbRtxBh8LjuxU5BQNsGPDyAWgNvWxi+NDTF92NgI4TwrVODNA3RmOHazWt60/Z835B5xbe1oa0dRBdIaxAeaHJWj1Q8AwKsbVUFWeFfdK57wXG2qXgoTLKeRQXAeVkweGAdw8bQdSYsks4GAORGLx7hSI2y2Ca0cYu1lTHsfGFI2XAEmYcys50DmhkcyAnyzJqvGzC6aDiSktdvoEz/IAp84vhBcr8m1CJ4FfdCrvg6/tLMb7XdHnC85Sw3i3mItvm9qeEC1Fce40UJpuAn5UNYf48IVmngmETMr1PKSAIfiQB0wTToo29LtbK7HyV4/WL4AQI90mvdull4Up4DFNePU22u0I6WRe/wGBaVY9jeN890o7sgCo9gIgBjpjfN7yeVjTE7bgWg0Q2s9dmgxmIOsMDP1nqcGaDC4wGKR7mcYR1/K54lnO/usQ09K3XpmofVBPljjIy+6DyPwbYM0TOVp0aydaKz4f2XCEyHoKMMQM4BKTIuoM6QeNHGRZdE3RXA/acUoPQ9IBWW9P3H9z/g6eMHvedzTqSh5uEKa6CfFN347mGDN11PKJ4lweCBl8sFYxvhZcci2IZGRENrFgLfY/7dqUGrPFuOc6cNzmMTqEkm/7ZoArSthjfc6jtxrrJCDKFmaTYq35pAJrZeDl0MNf4FAdzM8DDwFEEaAGoTjQyFoCEQNv4enAZyIsDL8xNuFQEiH27heuBEmgjYnobCSlliaxEeQQFQAfnGudBudOd1+rqJCE4ieIHgTggvR3xC9K7in2tMQgSNaARgIwD4HU/ByV7jtkkBVM9Vu7qjZZmfu2FKovDcW/7e3Otrnkamp28vP8hBvvBXyre0cVRSEfl9aozIrVbdlzysr8b9yvt5BpnLJ2QOeedyGTvF/L7uG8P13Oh/s1dGqfMrlmdqcqY031DHTmZTHQqPSjVO+X6Q8gdL5WX+hKr/ZimK2Pg1YsEg4KNdPwrwUFgqz5veoLz7EOAed1jl2ZTbGlF0a4LeF3VgKHPeCt9FUNlXg2AQmdK+AdTQqWGxM10n0nOaaP3qZMSW9tDlGJyyOqPNmwzcnc+4bKvJgCgGEnjXJnYdm54tG2nkE+nK90DwJAwalAA54bmCL/9EBXqlcUfXV+//C5T5Lm/1feW8Su6xuZdXItT/Xf5KCnQte3x069p/1384+L3/Zq5Td9uIPMev9+WtJQRooiFQH04Lni4XE7472OrFkefTJKg5KN8PziWUU9wYnlKL8CMEHyaHweUffRLMNNEw8B9sTJ4b/RbiIKSnen/LAA4WfGKWjwBi9/nRo9eafoV24x6EZwge5Dg6gNP+by4hKMs+uJIAFQHCD96AKwMmx6AyObOHeX08dzTaOerWF6DtaI/VQ8tRjc7a2xDA4sG7BSJk8CFgMLqYAsQPOd3eq0JrJ5jk43Nv2AUClTT6ocFDe8XejoMTILvw1ak0EYwhgDETLoAewmp5D+D+7g7bNjSHGzRHjEAFAdvY8Nuvv+Jvf//7NCsKb+VI6svqfaLydp3ogH3PuZzM57weUs9NUSJEDovlKKybbLbEdxGAHdPnNXXFFMphu/a3zO2+XJ0Z9oh9X6pp5MHed+VNYZfsu/noJ6ZI9WN97vn0HhCHF4EpD1XRIEMgm4CH5sRWJaOEsjHyPPu8S1qzu+euwnt6Puz3iPY2v69DyXBzRWCAL+OdGarb0cOwXzj+3kQ/r/F8ezrmY6h538uerWWGnT1uwg6Z0+76CPMAk0Q+mEa7T5Jel1dAtWvbPkfPnJDHkSNmhZ+2ZXBjnt9SBN/eUz1bcOZqdJxmyoildxA2C625gHkDU4d7pZOHbZdNPWYlcSuPDWMIOi2gfsImG5YGnJeGTQTrZcVyOqkniMHqYIXtYYo0Nh5GcbMq2HKAng/ejJcKPuJRvM+9R8YXDQy4EaEqPTKnun7D4EFY1zXmu7WGti0R5r6RRvMZNl+DBQQNE+y53fe8lXvXi+3RSZB9AE0qmK7KjWQQrsXskh8VeJhpoXmYUPJ/ekHX31Fi24isUnmMCmtVweYwJnsYvQ6dOw2UXMl4/RhoSasqo0HOIKaxkI/RFem39rVP5bR7CfBcalWBePWhf7Vbggkv7hS/Vy/CcZJ/p//3sM7aByrRWChgrxqp5HTMvNu+BGUymEBzfOrK46myq69nkjc34ugtIJlIw41OdebzpJLmeUZi+oyk55U2Vd429rvD6D6Cgzgec34k+ZsQ5MLTqfi9IggPHKmhtakDYEbbjs9oOBHwou/fUty5gYnADCxEPKI8pAPmXzGDTWW8yOnZDEeORwr7Fri3lliGgxcmWNeB5+9oR5Ke2j2GAOyK1VxTf16HIajrk4Ys2+fPio/HgCxmaGlGfmDlCbhbNJYOdGgaL+rdvFxI+SAYbwOgSUPbCJ030Imx8mbesBIET/dTgx84m+dILDDs8BWmUG4ZU1I7hIIdxfgEq83OyZpcDdf6nJp/Th4WCi+lACC4FKglVYdzC8UXoHhAIrczQZ4BOsPCZmY6BTeuoZbh3AHM6R6CPBbexbxtZ49IDfXuxldqoOjvGh/le3UHE85beAcSkqsRa8JMvrOLVlGBywEy9jV8u8zQuEdFTvreUPy7N75+jfK+8KyiDImOHjs4fEuZaiEzpTDjMKHEdyBg8NC9UHnJQBCYJ6Ok5vBJZ5g/OLlPa/iKX3Xo6oyhsdbBYAwiYPhMqYFpawY/klG9Qv5g7uitNWyXzfal8mhLA5gohPQt2nYapTyj+PkJju9sLxowNwjoXvkQfjEg13xCBSgbQHcAK10SPEPc4B3ltdhvdW1EB+LpWTC/9/ThAx7fa3j/x3c/4POnj6UCirWoJILuULKSSdAhsvHLAIYMiLxgM5xCOsVqJEswXXfWXwE4abLVbp77KRvx3WvzFQYYjgMNFyQDMYMJFdod2KDgD0mjaBGAm3sPKqA6vVcc5vStzH3wEhoNSz/l5Idydq8KYZ6Oyh8RgA3PV98ErNc+wMLtGz72M7y/L9H/sMnCsxm5AgVnV35h96uixwkZjnIODRye713h2vlJuZ1nrMTxMo85UHUqz6XUdsU73UKiX1MkTfyz0n3fv1+Rg9+3mtjTFLnxYP/9W6el4euNB46Kg4onx/p4AGcBKG9oq57e92VPYvb3r66Nt5ZiYP6W4q/u2XmXCQTnIfV9OV6vP1S+tZbvDLilVOOIDqBP3JSm4hg73CgwQ6BSxyPn0xUXiAAbCATGEA3x7ukt9cwtAWe+DgQPkOW4TteslahY6hik+GYbA4M1eojLdUQZE+VZzXmS7L9GhHVsGJznBz8LxfoLw82uFF70XNiaAEZ/2HhiEoZmRE+so3X4+akQfce75ToGeVi+ZiN/Dcf6n1lyXf1vypfy39G++6uM8I+Wv5QCfYblPWRfv1v/3arrLYvsKHv/7fzcoGl38pss5wETDIkqAYlw4S2YR/HQVDdJgUAP/730x3pXD1TBUFeSZ8Xfu0nRrllOEoDxOwjA+ssP07vuSXb5ecXdP09TTU0yFwxgnunm4eL1/2jvPf7zJzRq+PDzf+CHf/wNv/3yHwCAdww8+RnvlcW6ib7sQehX3bP2hlYpZsuJc5mOV2GFYVmogHdCeNpV/2ieYp/bDLfe3r43r+HrKk/f7wJyCbwRuL3/zdX7B23uf79eXt+H/sYVn7/bF06/qCsj5NbDmxNqA+dG/o3+X63c7HuIhn4kmLV7x/ncwC+b5TjTWemwimQFjMCKK3n0Y9tpwIm65hEjQM4n0MXCqZGJHqzf6BYGXLkBy1GpB48hAhqWIzGUERpGry0AsQo5n58+Y+kaHnI59UKtEhiN3h8rRQkAaYhyElFvHCAEEQ0S+GfjVb3HlzlUpfLaykSNy6bW8kszBa+F/duHaq14z1CRe/w7lGsY+8Ls2aEZVGDR+ZeCt/Lg5uH41tKqhMIJpLhIdlNWu+peNr6/BbB8nIgDbyN9UVwohVSSeL/9Y4FgPA/wy0A7qaKD1wHWwNyqNKeh3udSlAKuVBcJ78U4jE8Mos3B9QrFoCQmAJGqoSo6EIoDP3p4ACdlgac64zubHCE9xE9RMcvaAGj3lOsZq1Lf9Ods8GseH7E+Vh/hCh6CNY8mD7AkpWeC9ilD+wEmaLxCfA6vZZ7My8/vuwCbDL+wJS1sy0nndFie72b7hxmMhogUPiSF/qTMO5qGRGpN97iIpnvQfxrytTXf4zqfA3oQ0CSAAuYXCAvWwZAXQaMz7u/v0HrHul4AahiXF7X4JaD3eywLofez1iYAjYHBjG1oePV+7hkNgwHigfAcXYGz75ViNezK9MEZnjs4IXLvXFNekIDEPF2oKN0DLiXWZy+YvgqxZcRP29+wXjJk2LJ1DdW+AALG4E2tncemFspgNW6ZEIL/tL6YN1/EbvDD1Y4tc4EUD/Z1nVAAACAASURBVMc5ST/23pIu4HYFhlWcYAqHVcA9+kRm0ZIreFx4TpT7PQXl0ap9kvsp9kGMw0KsB4K0ecVcT4hYJfsW/Sbdz22iU/67Zb/F9ybA0YliyW57l30WmdEbZdhZUc/JEPg3QA/NeuS3bMoxVvG9fMhH+7h9q9P8zAabslRyohh4hpopyy1PsgBqBGOGtipwSKTpAujGE8hFsyw5380ViHBYt+uG+WOiMoP5rlEOuGJ6MrYw2gOBeeiqMYznhlPlx4gxCyxiggnKVaVByYAUgYN7RYfC0uarkXnSreqfQIYgW7OcvjbgCMtrcN8XDd/HHrXF8MXgDa5EBoDTouMY3aIDXTj2GyAYKydNoey758Amyx3c7L4LcGzxY95g89rIPTMR7+jDmTYdvlKvA8Co3MNcxObJ36NU9LOFRKThzXfjMYbybxeOd73vhlh0HxpMx+2g1NnHDqV/LIJxebFdS5oeRAZagyYds/3bm65ZJ7J0GoStGe/zzGit4bQsOJ1PYDlpPnQ+Yb0AwisICza8ZEh66sZja2hdATDM81LgipUGEbZw+y3wsphhLYvy8WdacLH8vjr9K4BTrIOiQVIeHYSMQMQQWiDULA2U4UBWfr9Z3vOTnNGFMOSixi+9AXKCwL3bBfxCoHuEQtHxqkCNsEQ0fCbQLBqRGC1t4HApdvhKBUoqrxLWyHC6SIVhHzuFQsbRW3CI4lFyvB4zhdjDpm/XHT4LWA/+zl7n+QGVb/xOwt9OGL5vu5TkMV95aVd8nup8HSvEn+3uPTwlCT+5CPkRgqepvltt4eB55T7dgAMw4XNr6P0Ua0NQfAgYPiQBy0i6RJLomDmUzWFEMfXAVjsipdkbE4iQGX8EUwYhlW6rZ6J5m4lgWQyFs0VPCINYoDt/AjdiAfqygEQNGzugeU5tnxI2rdcMGRsE0hips5SkB56mjWB0C4AZSLe75LcgAD8L6NzQuonm3WMf78AvxldjAPgMNx8KWZxPbGs74o1Cc/XU8enjB3Sjfg/v3wMAXp6eYp0BoJ8IchHwBUAj9Lt55/Kl7FdRw3z1yjdYce8SMUW3K1adB/M+uqGF8xUggLryuaIei9QaMFStIlwiHUnhRYsGIe/5/CRIuUGksQABz7oEtkOZ0mC6ROGaYVTH3iDYIOjUTAbkEGAKORp5hMN+P9U1csySxkpSzoyeKknpSa6FREZz21c7gZvF5ZvxlFYOAuFkcqhLjEt82Q5wmy7uvQDPol6jgKC197jIx6BpmOq6dV0Gnr2KtZzrKrwBKk0JKrp7Q2ut4oBbeO+t5dPEf5fa5OoH6jxeXx9xWdc43ZXWb/U8/0F0Szl8fTjqItIT3O3V3peHVx7hKLnRv0PxpvjGw0lsckCIfgLwm13+bn9/wMFeOrh+a9+SMXmdnl83VvYO8lrc0UH20Fxapj2s1F596Xo/iuP3Eysdz8whGGO3Jm8oEa698Fjqea7w+ZvNlUv3DtsvbX42HNi3gUGEk8vRSc+0m0VscoMuI6+qVCen6G6IR7gsDes2cKaEGpV9M4g1KuLggSFqgMvCqhi39ynoCYVs9PHhHi/rqo5oZkTb0EImF7ISINKEhKyW3PjbI5v5WRRg9wTVDxXPifN106kar+Mcv/5ymd+q9f9nlKTrU9QqIs9PB4EaBEeUFroeuVWVNPg74rS3luO9/68rfykFei3XBx4T6BeGSoCiYDFGiPKe8y7BKhTGoQpR/GRRdBXIN497l7BEE4vIgCk5DXBFhUcudI48uajM69FI38JIvQJW9vp+UzyK4Klg92LArtbz8qFUkOX8z1NYHFUBsvdoamcnPBICnn/+DarcRBySHu27dyL4iH0lX1/8QAnvUxWo1YM9pWfMrqs3y2eavc/DP8GaeCLBfVilTr3St3f9aHaAivmbhNs6yVIsgINXEIMPmvmHot+ciE+M2X8XAjjPVn33LeSA5p8GBHTrHW08DzZ5K/QD3f7ZOcjWEFjOJ6zPKzx3HKBhXNRofA5aSAJsQqHoIqjlmzQVyImthR89I9RptEu2h52oqHCfLaSckOV6IQKoQVgt7ltrFp5YSTQzq2coNNzktq1Y1xVjbDif77C+rBgLYVnO5kEqAKkPgTONDFPASv3rLIAJG4qw2efh5eUzzuc7DQlosBKMiHlCj5dVPbGpp0c6EB4M0xI60i2goyhTcvHCSMhxcMFiB/uazs1Mum1/YO+F7GMyZjoQs8x1BSjnBnHnDHjtbmLugGXr6gYLEdKOWfWYY5igypSkzBBS5SIPVQ7KIuqNLpqzLxV0yrRw0A/fPab6lVwLgffDn8vU79y/YnAhoSwJoyyWwGeIqXE8UxipOlXWEbHT/n5nBx6t0gC7l2Gb52nP4KE2Yp9r3Q2JxwoD67BWGXj3OIFdI4TmYbcaOH1af28zWmiYYIZm+MorD6VNCAV0oWhJovXac0mTiAn+DBE7XvV8rYzIjeu9UqZfhf/6jcIdixmksGAQYxumjO+igmlq6MsZmwBi4R491QK5AmOsJpxXysbiSitTHheaxzwUy7UO0AZmFbxtPMxwgExx7qHbEXPkfLhTpsHD0EPCmue/4gNvkllhnkBU4V2gcD2GKvvWsaGtmsf9dFoikdu2DWzbhnXTw9vGqigTqFETbA42HmAZ8Pyp1dsfzOBmq6QN67h9dwbNyR3UTDgdSkv/1nBtxckJcvaNHfbEDnYWwT0MFYkapJFaWJMqJYUpkKhY1KJZHVGY4oDVxOP+bp1f395OtMk8PFXp2U34qc9cZitiNMn2+sy+FmVuc+WW7yEDAvFZLEpuyp3tOy8PvdaGzG1Noekn/EXlHzALYCiIemAcnx9XgFPDsiyaf7prtIlOeuCHRZJQbzpAPB/trWKMDdUNIOUZkjrUuYzfDlfIw3/QxLLOYgsTOUzd6s+uPSSfwx2zef4Kaehw7wNZWFlbYVfwuzA60gn4usFhZgcDhgdov/FjAkxhT83C/AkcySQPptSEKvwaPIoJAHTNRijIc9qNobTULZ7qggzvZPQrKf/P/ZdcuAReSj4h12ga1RUgJJ/hKEH7Zp4US4G7UqOvpYfdFu83dNoGD8CM9bZ1WEQE4zTUClq/93FIjsjpax2DACALAS8GBASydCMKD0SE5eEe1DwSj0SeQmodfTVu9KTGE31Z0E8LmgCtaSj4y3ICWJVFkQJATiCscO6GYOfj6KEF6SXYN2mumXNHqMYhjUj58zjQDk3BQFC+2fAdkRpkKTfByRf5/zRGMpQ8iIWwfAHGHaQ7r3LNr9K9zby4Moej3skoA1QZp/gbPFdZoPA+53ynGlUayCQ/NPEtDOGWpM3HD4nzjUcSqJAfe1xmA22dFslWSt8rhak4rVKpuDY4CuYChcdIUnFV6pn2LWXCQLs9yqVvfr7K/k8WpVf7/ZuKoz7KlEE+FzBITEpeW6T5mCVQeiBGF0LyaTjP9cJXPG+dA9s7E1IgnwwMErQhQBsYG6GTRVGKBSRHrxNtjjUXYKGu0SbM+HEbbOd1pzAaLQhCEc3BcYCgoy+EbWxBEyKqnCu1nWcRQXtIWu5jdqO/5dF429+3PDZwoggYj+fW10K+9/OahNFIPeUZKsMCOU9me//Brx3+xfbFWbkNuQRtokbm6awma8LDQphTaMla65YOLeHH++9zrH8FcBmI9dW8dwBB0pKK+3cAvd9XQYcraPh5khxkJAMQ1dfiw+tdQ9ZWg/JUvTXl8afGYkZ3jJHVd5PpurMvX+zVhFW90v1NonOvS6Vr0IWwChfcmryZowUWRs0QzKSM+wAyCoiPH0CmGkosRAWfZ48En53XoNJg0DB704cfX0nUTdZvkwoh3vQuSPmutJ0mBLtFKuXWbFeeR+rS+HAl6cq+Yu/1fGN/Pf247os/J5meMFS5/dHmLFq3vkn5/srYobZf7lVDjko3AKWP7yRzvd/SGPzR4qG5dWylBCOH2BvTTIsqzWl+gI/QcO4BX15u7S9xQ+u6Hgn3U4eOjBcc7Hf0JmFBYiwuA3JZ4p4fqJR6hleann75Gm98/0b5LozB3JOOjDbAUPzykQ6asm59gsIfAVgELmaYXnSUQ1BDK+chVBbegK7y9MXIjybJ8UbVsHQzPO0G/gLlm9bBGOMlZClDXIkuZhhl50+nGSZvBhEu2wYhwd3phG31NFBJJ4DEXWJy1jgPCfDADR/FTw9pTHZl7DBtbJr4rqRpeZ0f2fNa13de8zeXosuaO3MDPqk+J19844/sLFTkEOw8nX9GeV4KHgmY9IXI2qO8dr2nBG+9/nMw6tvKX1KBnkTOmQkH4grMzljZJmvOvOmN6lXHzhg5k0JZg4fScgtxKVVHMYYswg0SkCHjqmUjsLJay59PJ3x8+ox1DAszquLrpREuY0zjoAKsIrM7dqjm3aUiSQfSPmePMqj8MRRWEO57Fnyw5//H3/4OAvD8y686V/apWzoRBBsB9PMKwW84//2feP6PnzFIvYbv//kPrfeXX2zJJNYDBFNaAoMIH0kt3y6//o53BDwBeAfdkI82qE+3dhN29/dLVBgc70fk08TMF8TP3QHgqFlHAA+G2R/N6toDRIkAD0J4IgmrLzh7KmReZBKGFQ5+4gLBsNiV0hk7TBkTGoKf2qtgIA2h2UGptUpISpWkNTTqwQgxzEMJJYeaCy1bCYkpqRCsRMg9EBsAkRZneV2PcqiLr/JgK+Zq3rjhYozSokuCfn8HmFJ6fblgvaz6YFG2QkBAgyp/OXMD1h5yGbgzYczqYbSJgMYAmNC7GoVQt7rPpDkZQ6DbVcRmzITvSAH04Cs2G6ICxKV1SGvh8Uzmlbosi4X+HrhcLoBofjiAsCwnA0c7rLdm4fjqvKvVNkx4ycyQTujMYUwgHfj8/KLK/N4Cb7q3OAOgwdi2VYNcUoda9ZOFQx5odEohJ3X1tiGgtUUj3G0MIsGyLABpTnSBoJvXbd1E5HiPoZ5uidgVhs4UueMK5CCFE34nhafkKyCF7WcgEf6k/tzBhWjwaPMs6oujVM0bKswQGRDRUEQiDAwBnYDtw1A4XBTfj43Bp1SiCiGEB8pkGIwQVOkFsxAXAcwDVsSV6n4Azsljw6MN7hdY63XmsnLWhcNxHByMzs46fVOACcVM4B4ThovhI2yQJ/Wcxr3u9U3cgyuXMmfe9ohJdzJMvQtxVbHrXvRsOC69Ag3nGY5Qb8AcXYYalHzfx2T41OepTc+BUHDHHBudZbdt1XbHtlmObvMUG7rerjT1XE2ughfDw6q8RoQDbNYei2Aw0NjnHCDRfFGDGdumSqTBmsdbQGjEoLaBBmHdNmzcwCtjWwXbxhhCEFZ8u24DLIS7hcBoIVxVeWALuHNBlfaqWT9VqPk8njGEFZ8O9eIbpjxvbQn+JGSUNnYVzun4lC+qxNryvpqxhnumxisGj46/Bw+MLXO9igi49dgndfkGDxv7ipeXZ/Xkk6R9MoaGE7useL5czBpaAB6a0914ueEKjuGj8i0kQUsBNTjw8RE1tKUb3SMwGBtLGGJ5TnhqDemnLJkvbOm6f0UgzBb2TN9qIPOeAnpvxftfXZuZ1ZNKjL9VeTbbPBraNEGww58R4dgLHFKjcrCijt40v1hfCKdlQQ9jDDGPNxM8soAsBD/M8KBBheSnflbB76LRRGhsGhKWdf6HKDboREBvWJaG3he0vmiuTurYeNNcqBubVbvuj+TTimc9AI94JGgg8ugJucth0V9iGmD4Rzc1GnqQnPN5wbvHdxYxwvgcUXgbxVp/s300RMBjC6EoB6NDqIfdgCxHGJJnkojUYjDOYsFzfH2dX3KDGSKodx6p16Cjt6bmqUTGDCgiBfUWPDmg6wvblyLAYFdSOPYunovEgdco+CijIswAGIMVrvqyxHdEGtpbkHSgUUbCibQxZB6X7MI5tvzaur7ugdygzCERQe6Mx18HVNy0QkjQ5GRc9xp4DrBziEIjnCj6sVIMwtkmw1dLhTX2UkVphvdd0eyV5BFCEEvipIcAoKNhizFQXVcxobdozuHgcjznoUANnXyO2KLfQMDygmYHNu/D0k9oJNjs/eZ0ykHT6PwYus/gHtSGCwSW+5gA9vPM8wtwIeDdgLAaVy2dsfSBu7t79I3QTgO9LzgtD1haTw8UKC/zsiwAPWPjhm3bjC6c1KOblBYmTTd+kSgjm+xibZndoPLCREBnNFpAzXKgc2ygaX4Eqpw6n+/MGMD8H7cR6QjCmEc0HGUjTSclndFaB2+MzUScynYaH/NZQPdisoSYUoWa1kA9o1oBDWQe82GU6Xg5YK7wcfFPozT4WU3PWQ3SdC0hBGJgQGlpnB3dK747RPi5Mo1EstWc5zrr2scx8WShmCoIliChaJDyfdItXR/eRbeZvGZcGXBPkOdiSO6TQ7W/5bsbhbz/5Rut4d6uR3kzW7pd49tKA4EelXYSE053S9SeU1ZaYsXlAQaGa0If50y9oyenZbXnMUhC6015gk3ApBGRnJdTPnfPF+sf5qEpq7qOobeObpEXuvGEzXGG500vuJUALK2bkaZuVBoC6gs2GcGSMKmcpLdFZ0Uy4o2emQfWbQuF/dLM8MU8rCVDH+j35oU22AT+Ysag0H3hpMc94wLWyLgd6shbOlFuyNRI+blBwMvHJwCEu/c/YOMnEN3BZR3tnjFeXrRbny+AMPqDhpZvJ71PF4vUAgBtCTrlAizd1xTHWqWngMiz7l/pGgHAlB++qLSclSccHHyC1psplZL/s+tWoadMZx5wdK7gcyfwQIse+SjlqroG3dIUNKKQLaW8qAG9Kc4FQCYPdXwwDO7FxuXpVvQc4QqQO+C+QWyehZ7NucC+tSHpcJUou3e+1yVFRqeNMbZgnaROE04ltzsJ4dmi0CEixPg07faSzduDYZwH0TsCwcBveCaXT7oRj3/uynrvkHgXy+Jow25UO2SUdFOGF2X3ty5xuUdOD6h4ubp8YgcW+X1F8snjCkzRGyBFV39p/2x3nXYHLe8fCXFlvvxwpN2pIL+73ucyd0/gD+Xeu/L7g03OD5xdvtJZevNXwuVravIazQLmXflxB1pU65z4VbrazjNVy34LZLeoufblFpzvn+63Ythbm9xb6MQBrNSPVK5O7XifotOlrqu5Opo7wdWAjq4DvnaAdOOvOH2J69dL8Ej0+nteeoFjV55vZIYg0P30KfCZyQcBvINGw31vsF2bc85X32csNJ8FdUiaurcNVlk1mspWzSGQSbAK4JGSFsPlbHwrmkDsvKfOCqovGh0mN9fzKoxPaYbDAahsWVo4jHQiKGtAFlpesIHB64rhmMjkcGcW0NAzBnPhuQ2fayh3i3Jj5xp36vK5CbmyOP6uvFB968vr7eWt731NcaOCtI4g7A2Hrt6nFhFZ/ZPyBxIQnXy8pwByQBLjEwtqn+bva6697Hfi/lmd6z9jLr+2/Psq0G8hlgMa6cjWlT3+eVgnGbMlVEBCqcs1Uq5N0fyeMxSCtGo56stkLWfLnl/p38u2whxQ4Xnq1Iq2YWkNaw2hVUzciMiYoNdB7Xr66jt7RJDFrZW8bL9s4Tu4Lz7Hi3ibPwJQZD9IBYbbzwPLP/sE+PvShfB7g+s+DBmrN3wXnffediFqblX4RoIEVN6iYhJ7QHR9/5XmPts6P/r9glSeWzIhE2ggFeZsyFsPTNqHqnCotNwFG8lFUs5HQYQEzJ7nQEJtKJ8k+AUXOAVjIjNxcEFaNehw5Fr5rImvaQCk5YQYg1mV+IHDDSEvAYOEAYEe+QqrbLlGw/vCaD1vDiEMWRoaDTQZ6A9n0OeXKbwNxZtzEZ8bC5HpHrwA7CCVbB0H026HrIlTJuMLrY9DD4MbC5bQzGqd3Br60lVHgAXbtgWT8HK5aNi7YBp0xoNREwtxRwRh9awf1NChTAOT4HJ5QjevucfHRws/27BnjoVV8HrZNlOQJMdViVYQ626KQ43lGe9POpj4bjZUCdml/a1C6zkKwp5hOQEY9k2+47OicypRv4es1fvJGEzV2qBEoPMmMGV5y+cApHiYsynUEUoO9/g3Zg1AVXpPRJ+SUdN3qbxjXus+SfbX66vXzk5TQTYREsk3danGWRYXtGadVtugEq+sUEZfG4k7EMuo5H8bMn2He+e6rsYtkcOAzeYgFqJYJAfcuGAKghoCGrHSe6+IGRaCs5PyG4BQCohR6ptYRcn59PH6m2CggoWfxz3U0ewH518lzyG2vukRoIeNMdjQpMEwCzZTnPtaKdlXBTkxYZGOVRpeLita27BdXlTItKkwWO0SBCDGukG9e6wiAZvw37Jj2aGlwTyK0GzNGRq6U8C0AQbn4RVPFubZZmS/LmzSRvUGyiWPWSUg2PJKgg1+YCDJ1RMSmBSLLIx1MM6sY3JDFWZVlNfKRYBtMLZt4PlyUWMhF9ILIOD5OvZH6RxJHkLYUzOY18yibZF7R6KDMIJv64sqopuFBPb9QQ0qhLaUGqo4gRpM+ZyawJugnpjdo52wc5VsW4mV15WCd8p+b05oKfdUUpWZQoYA3hQ86iHXVRBtQkM2fOlGPcGfcG49svH2pSPDSep6+Hf5rbbjnu7epm86ZhcAIzz0tb8NfqpzfOCU2gmTtAC/xE3+ntMJqmuowngQsCwnnM9n9FPP+llATMC2qQe68Sbh1WzvuHKZWiv7Y2/MJSEAmf4Z0LuqemL/Q/gkcZnjNn6PtA5ySzqfSPuupvWInpkCmwx/Rq7mgJaEkfhG6njyDXH+qDwIKlXJge+3Agtii1yVyr4fBUATE5q7J7HNwWg+H6a0OOm8yzaLM4N0SgZlVcNErTsN2Ix0uRG1Y+9AaGK4LIlukLhsLdfFx+3puJZFlWlGJ+aQq9ae+HpRWGMQAIyB1i36Qby+GuTnmRh2PeHSUCBLkkoIhBSv6LrC0hEVWAJhiOY/HxCAXoDPA9I7xoUgpwf0xwcAhLv7O2Aj9IXR+8kM3y7oOKH3BefTGWNjLCcGrwyhzQwAMipPrvqeH6SgK1Ve7/0cjlhsYho1M9DwTw3uxfZA0BcCxCIOmRFXF8NLtW0k3HKDuRwOiGxwN24X3glryg+nKxk+OOmFRrByGEpeh6Yx+tplvQKJqCUMGN6ysZHoWpqmSWEAmI8stk+EMjpDhZyZ/M1LYMUdnH2urYsTDap1CEGD7MScA5oIM981cnCgW0isaV9r+htxAx8ub9pY4kwfHQp4cdlOLbo6z1Al+me7+2B/P+OqS99SHhMBTsJ0zw8Kw3TT2W82eqkpplDosKdBmwYEwM+sE3ZyhGuGnMmyOi3N96XWIQgjSDSDY5AZCiIm140jvHjKD2oEac3wkUCYIyoKxPExzFBbDSbd0B0iYCJLR6JGe9RN1mSCecdz5P2LPZ9zCCG0u4ZtPUOkA/QMyD3U187nqsxTTH4anvierdgBANanT6CHElEgnuZawva/82y1ht0K2h6WWJUw/IKN19fP5pwYajxDnhJOQn6YR79iKBB7kW2dHL/O8qiKU+uo4jHSqzDhSD/x44Km3bAZoNlghIyud+MpRqnfFUiVvlJ+bDdeADxo351mBW8ZH8Te90VNZymnkRL99rObjz9GL+6QITFXnjYvaZMTp916QsxER/Fyqzx7dW12j1A7e7BbsflsR7d2WCnOmZK8dox8N44czvV940kKw5RM20HZh7yf6iaD29L/hHTC5NJdntexJjbac5s47tMtZP2VSNxff2e/3dvbZV7vBBkt1d8/6s7BOh3ef6XUMPE/yqzsn6EsNvokD84O5v6prQ8Jc+Spqupw518FX7IfEnkjVNrBTTjKnsapbRpFUulC+QvTd3v25PZf3+CH10d1fOF6v8W/Q+FdnYL0PBcUx8JS/Naj5DLsnf8dh4ooH9+gZzKnrz6kToqLBwH3pIbNi+1jKvg9OlecAgc8CidjE1aJIQEW/EiN10hN/f3s3pqm5tt4FBqpA2iUEV/ZwsCzMIYp+wGgbS7DkTAGT2F/0d7tcHLilPxLxuekbCufH6DzefL/ZSUNC4Nr3/XB5eoS8wxn4aZ68qhufEWpypXm8Y7ziZU1qLjvDX9x4/qo7CnD1+Lv713+fRXoXyg1vIovJO2eO/N0a5Ll9qOb779arinN4dcDA08vGrJp41EObx1L7xjbdtDaMUKvngozs21MSSVUpTyy4BPlpvIcRpFjwz5b6UPc19vGGFtIQE2R+CPYsqdsv/4YbTCADb9h+1kJ8e9NGQzvSTOiSwB+ZEWoTIQLpbcxG4ZvUIunKXfNVyEpA4T4owDjQodAPrsppIM2gl4ftCJEeIbgASr0eAqmXZmMnwbh0ii80Z14RR7RPdKLev1HQr1Wncdbf9/JTa2qEcWBOrwfnbv3jSKl5gb1XrGcvP6Nen443DgjVTdZ2ZUzHco5Le+5DfQ7vUjEbgfBTQgnJJwQgO3TM87vHzTU8ImBZwFbP6mp9yRtdhi/W9Coob9/AAF4+fic5DiYxxxjA+F8f1IvbymKe07GLRXZydSRtBQKVVZSuYiCkARjaGhKbupR5TlV3bvwdDIvb1GF0DY29QAM4qbMDZN5IBdiFs0BEBK8PD+hU8fd3Z3mIQfQ+i2bWGBsQ5XIjh0pxTBi+ETnRsPKScRpq/ChloMqXRjBhlzhMEHgvkaV+a4AM8+ziWtvPEf0mwALz6qvzAx/4v79too9UbiEquvNPutHciJgJfS7ho6u3lPxrkKCCwkqDycXU75byFNaDKW60HhfygFDO8oB7/OgXEO023S836vmMVpnZexpFkCd7CDftI5wxJm5JHkW4A5wLBOi/3itzd0q01zXUH9VDbXjxdreHvNW7ABMcarqoT/eqIjJxnaAzaX2xUtf5vpIcb57oIdShRQKhTUig0uNZLiiggFh9WQX6EHBmRiVkETOKBZoKN0GkCwQACsPyOWCE6sndWuao9wjlXhamH5SRZA0Ux6weVQyMGRgWQC0IL2ejgAAIABJREFUhsYNRGpl6lERAEoBEg9Qa5G/ygX+sTMDPtOYEYAJ9ApDLvFGCmQk69G6PFQZhwd6s3lxz1w9tKnSWAZjvVxwWTruzif1ojMhrOfIZcsXrIYumipDx5EKM8ft+o719SrcnN4ngc2lRg1RPOO0UZXNomFQsBgSIcAMmRZjblLZ31ozTxylA+6931j7T46IPIKDzVNVUPimimvDQZV3cG4h99qMP/1ZPlH4dnzp/EpEEuK89q0sxl8RQb1+imAj2RfDr6U/wb2Ep2cD0PSAbIJ1V3SJ73lTWDPbnclbqtAUUuVKcyWg730TSE5CVCOkrVPAaG8NrS/oy4KTGZdpKH89tBMd01Sny9mH4BhsPux6zytVeuV0x3+DkEYBNqlOY0IqbnNYjHI8uoneL+aEE6lwYwalDX1RYz8ew/YTpSEh1/bm/pFFlHFUOSzXqkceOp3PgNh9p6m2DzR0e+arVl5NRejMUGMO81bbWNAhWLrDnOEeIgBbDG4Y4er9bFO2lSG7N3bCeOT6c0+igGF7w/FizN2O47Z+kCktY0UCtgGY8pwWM9Io314JUp20GR7w857zO9vGmjP+MvMJnqqkn9Rzcovk1vrH03gEB+epJPoJvRHGuk2Kk9zH+osjug9BoKFvOzpaX8HjrPSOBMvS0RYCNfMVGXfQvMO6l1sYFemcMA14Hmdtz/udihgyOuVKpFT3yg6OJQRuBK2zpeWN8XM+D6RehpcX489snzke6MrXEgAaZc2NB264gwzBum3wPRpLeQcgomVIKI2IlCa3ocYxvSXP0qhpWHiBRqAhhDKGB1tkKOfvEt8lnqCKyOEGYrp/LL0BmQmbt2kUsag0kMK0HVzK/Dvo0V6B4jxAxWtyUF/5aP9k0tfQ9QtqyHaGyPN0P05utXE5A3iJ/b4fTkXDqkR/V+YB0Jh4T4ddITxAQuF+XO9RqaGq121Fo274N/GBe4znfmjYZMP5rAasW8A+Twovj/yhkK6KukZNowzB6IGRE03BYPlCLVKFRnKhUELDFNW6Z2MzBheekGPRUHyWjF5kqqlC/amo68W4MiZAOPZKV4GT8pXN+IsmAFvoe4jhZNsjZgADiF7Y3lJvt2rUaQJo52noBZEGq6yy7wNMFAN7RizXXQTymaEKXSQQG/HoD3c6nuCf7iHyAjoDcknYmWCMCBYqCSETIMffBcrE96wrRZB01V2pR3qe18gOCS9Ot4oTxK1SOunnMeqWs9Zps88czQYjFdd46UQa3bIpbDkfWoW61SnCv9epbeDLRQfdgC53IBDYspKXFXJOzP6/W09vyv6eyjcCidr873kPB1dTdgQkwJPRf5ePpjfxzC8CThOpKCip3L+Gw5Qvz5DkcF/fw/x0+hXNfXPJr9uN+7eu5fDZLaxK0/MI2W5l9n5/W3HPc5fN0O6+lw7NKV55yd9JFdz+PSFzjf+R8pGAnyTb8fzut0riZaSNwjxV0578COBHG8vfAPwWtH0346+wBEfX+y5W+NrT47fUd1TP6298bc1vL3+8hrn8JGo8xDiG2S/N7TM5pRLcy/UbwdWJ8pG9eYSV5LcBAOczMAaWwWj0gJU+KxxQcLlwgArde5GdMGbjnQGEykHI+UCVt3cAD/f3aADWF4viajQSMOV9V4OwdV2VvjTnL7w9wkeYoahHgXL+IwlpzMDM2wEzzgF2p7ur57fK/pvvDyHXLU588lWZH8z6QaevmPRg9SgBYFKe30I3X7PTvnZX/tkz+DXlr6dA3yF8/xlbgY5u7u7559cnn/n37voKMG9BT0DczIQUVgXMjN5aMq4AxhjYYOJ8OT5aHtX2pXLdE8HTFfDrWwSUPHOYPH/jc3+76RdtaoBA+BFdfsdGGmZksWeP9VvMS8QE3Anhlwa8L9XFc1yrzvKN0rFXi9VG+7tfx01NLdUDC4Bne/oM4J4Qh1ZHbINUITwfr9/W8/z1JbJJB6CsC+5CepAaMNQ5DZC3fkfOQCvqWeVjcgByhQgZ/Zr7lgzRvk9GMiem3eE+3zzbg72Ki1nAny8mgpvbA5QooxG2y4Z+N0A4hwEBEbDc6cF1fV5tKPrfcqeE2fvNbFbuzSy8L7UjhW04E2h1MRzvlsQQx5gHox7frB7nRJFXlTy8WVvQuipdNN9vQ6duIdfTb8yJP4vnKYmg3mABHh/utNneJuW54ks7PgpBmgryNgBLoaBX+XqBVKCIhMe3e8Rcv7vf8zuGxan2AXN3xBRf8T/xRxDQU9vk62xeV/0MawoTIJnwtOr3fIzuEaJ5RSUs1qeeSKiQr6wUwzLScbx4rvS8PpqH/VxkSMs5VNYtTBiKrzp9AkX4I8fvPzICR/0LuNe59yGeiNFIFDgo6FkIcxg63O5r4pfr2/M1lXYVtmYafWtCKP46OtMO3WJyr/tNwC7nGe3wmSQ/wpIRbXztDQ6GLRoBpmjXsMWqEDdvA1FPV2p6Xw1nBtaVsY4LejeDKCAEsa13YGOgA8INhGF1DtsXAoh6Pg/Zwtu3kYa30mrMGEI0zLvnua36wltW8+4ZV5UMuoUOmDcUsBcgFBqS8FRhLbarKarG2DAsnGfHCUtXY57eCDwIm3nnDBnY1k2NFM3goHqb6D7UPSUTEJfOGToXHhFCXXEag6Ub3hXXp5tCv6F7DmAP51/CZrqHdjPcj0aIXLkheDRDx6BPji/yt9PaPKqS4aqZAs/bk3bDNGCcNkZdMlGvdzPuCCMg54+vUfm03uHFQzv+wATojfw3riqq/HIo6amBGqOhWx8cL5bPE2kmf9Fsv4aQ0miVCUH1t4UZ7Q29dyw914/YLOeZNQXDQT/dG3De9zb2gmudGu7ZhrlSE4SjjCEkYeVrV0RMdNs4AnEsOZfwNHNwcw9nhz2i9E6wHojHTnWcGUYRknTZ4Ol6KSiZvwJ3Hv2DxaIMFJwWioCAe0njDGcyprF1o1Wz70AjMm/tQCL6OZc6Sb1xxfLBH9Id3AjPGcqHnLtR2td/veQ6tyqLct2jphFKP3F7a1XvAqJ1eh+Yo54AiNzvU7eBgCcCzNYi6aQObe6Leo02gFTJxUOVtKcaatiMghqdFEsK61l32zAWRhMB0NAuACylURMy7/Gc0+yjzZM4lSCLFmB4WEhDOhYei8d8egzxlxRPVPvLPLJtw2stePIexsTBx9Z5FT0zDPaTSRo74Amge8S3vphEbYIXT6nkz91w1RWUw/hOFs5oApz4PzFnQlsdeRhgxbpqxBndPi37Z/tpZn2MxyzKtoCHWQMDxKxgCh2MMre2oPY79yMqX3lUbjyItSgf773OYSNkuYPgZXpnxpgVs87n0ld6hr3y/EulnqGq4pKF0Qst8ihfPnXNjaCEkq74X8x1zXUb/DQLyunyAKenAt38bJjWFNUOElToSzPPcI9q489dSa0RAbjAE2LNa98is4jLJ3xnN1iaBkG36BGNBdId92so+WYpyWZjPd8jI9oPkuPzIIXLuG+gjwTBHYxzMsrx7G8ozimMaoIWxTVhfy7wQVI8n59hBif/9gRw0fdO+2HizSjntLQncR63c4jAomkAfsbwEPd7aD6mM7eoj/cHMcHkPFzhHwCTP1l/vTbn2fapBqK1Ak90xcte44nDnek4i6YTSTyrH2lgJ+O1S6VulGtbIls20L46LkQXdz0q1/eFT3qUfCb27Jn2Y9rR7IpzK86boroZbgHB0yqZJVZUd22wd03v/3jJvt8az9vKa32aF/O905fy3cfb/iPHXTpA+7J7tid97tRSu/qBtD8fXiVsby/VA/1LVe6wxc13DE1F+YBUov8E4Lcb7VyB/Ct9OXpPyr/9u8BtOJz4UYPn+U2a/twsh0z1F775FxTPcQ58neHH0VoTZpxy9L7/JqCcwwlihlb63rMa19r5zCMUpwGcGcyJRU1sujZuLivlrxqwm2E0GEQLiDSn+ql5zYYTU8indYwi15Xkce4Nt6XsqMjbyvt7vtbN/LB/9Ibytu++Jy690Y8r+P+aj5HbherM5+M9B/AKR/D/i/LXU6DfLJV7mRHzH6312zaVHF7533VjsIcZjHbMmpzqvbfVf/VetSzEfnbmD94J8IkEj5wWbCKCv7OGYgcQkiI/B3czUOIGCP0eFrD3/zgDRHj+f4AnUju7H4xPq1Z5TaCCfUqvWfPdxCeyXOIAFrvH0DR7t8b/dtLtP+23McXhgf6lRfbP/H92QHkQ9Sq/t78A4TN8GVII9tHW/FGaeqHvGFXPcxoH0ZS+TmONg6BkG0dslN4VhFC1lZDPlAeBXe36VRyUEYflOPiGkEMg4Ot585PRTgg/OfQx8FDW1EMUXyB4Rw0DfuDSPnUAy+M9GIzx+XliuohMrGzTRTYuEGE8C4CXmKH+cMZ4flHBmDUs1k5rmtuVWcAbgy0n4LDw8KoE1AMKiUZIIBD4wsF0eES7CLkXzLUrd0nDn9thbPAAVgFzx2k5mfeWrlkj9Qqn1jSEOABCs5CaLYX0LGgWv8Zz647LCx7uNUBY5BgviCXEyiZM1ryynHRUVFgOuKdB0/zCQ/PREDSUDiDoi3mkmsfbkKGwMTSMPNkBmaJd86AqB+eEA5unvbH4QZkjM0j+RL3v8CAx5hmVzIyVer/6BstQ940aBjznuDbO2wir/iqEi90oKVQhImiu0rrfZPrn9fgRfy+UTFGtzZUp8VSpoznbxMYk9hwiJces1gFCCjV9r0L2U5GhksGzZZVk3wRAu9M+z97zSshm2uPMNmIkyZjlG64sLaYB+eaRYs8FM/sijvtw/U12EeSpGrxdqe9PAKXvm0CxKpMJxuQDanyBnB9h885rmlNZc6XbYUK15LHvU7ifkHFazgCAbdOINb05XDX14lwNt7VmeaabHTA2CJbIeQpIKBOY9QDU+6pCfGubiSGuyEUZj+XIYh4Yw/J+N8FiFnK9LzlXEetJbBw6PuIZGmKQlQ6K9pqZI/LNlDM1AIYwhMDrhtYaxjZwWQfuWkc/LxBZsC1DcfVF876q4sY9XM0zyRQSvvYNjM33896goqliTUOSeSoHCaMnMVwcIfGpqUKoLehLx+mkClidx5bvUx5ADZBgN3Xei/dUhcRZyT8rCivkhgB1N/t7vsGrTzxwhS0hwmpvI/o7vFhDaVb3KWJspYIYt+tN4mxchaXOh4hEmFoxOI61MzrbWwfD1trnruQ5Jl9PF9KGEG2HZ6F8A5Wp9pQxfelYzicsXffpYAINwmib8gG+dLzD487GJcuZELWjfdmrA+9MG1soueFeSGQ8DCyMcRCc4N3I1q0Z/rlu0DGk/e0FkkiNcQRm/CDm/cZNFd0kqkRBGtt0W7dQJNpWcj6bx1YgdYZKQXyCMQY6KZ5TYUtLgbull0BrWNeB1gjnk/K3y0kNDXkbhT82XEuUobwVAev4mwTtUWMF25eNdvsMpc9WlPzqG0uBe6OZYexI+rKmQyhLUfhcW1kd/8FSZdO+NxO49OsTiAaoNwz3OBeDKco9o83O8O+haHlsIN4FgY6NKnGtcKo8AnMDdcHJhVcEbHzRNBS8aJ9OJ90f3YzChu43iGDIqgYLvQOiESc23s2A97M13aeuFGFAyLxqzbt8mBHUjCfnwjZ/mc1bOz5YYn0aNTQzXlU+2JVD2h8WsUgFJ6gaf+fVaaW1lsY3hYZNe04A3jbLRQ4QupKSpUOYsI1NdV9h/GVpNKw9jSxhffM+EoLXdhhxw4JG7lmaZ06NhNViDICUNCLJt+2XJec5+RcKmLous+qr8nSFIFRO+aiaZ+ex0mQslvFAceW8nc9E5TVra/u/yctV5TiBIqT70wGlnMvRsyn8OrLPy3LGtl1mftwjagHhMd77AiFgvay2PVXx598xc8CqSMLA4IHGhNZtfU0ZT90jKTlmKfyZ8TJEmUpGo7YZjYychDlzScVoInXi8Fh4BFT2pkFTo5CdKizSWQvewj4TQUePfeT4jWVYuq3EAUZFgrY6nVfT0oLpCGoDH/viHm5osWOXYjQSA5hhx7Zh3HF5xjC5ToRcL99UfN7OBHnJSsKxxj3CfU+TaMRAb4sAULPzSAMGY/WoShBgG7lVnAkrZTJM879HUXaC6fEt2+J7cnmRU7ZK8FjpMJYFnnZMix+mzAAKCX7SNJ877yJX7Clz3Dc+qAmB6QLau6vvxyF+hp1lEiqj0N8XEzi44PwBKiuoMS8uUd0VoByWZwIeh8xyB6gTzv7zq9qkQJsgeJYqN0heE9NkTSktSsXT7E7M6vcrf0KVN8vHty3DF8vR1pdyn6D8WgNw9/d/YPt14PzPE37/+dd4/zUP8a8tH0ll65UL/DPK71AlOkE90Qe+jwf9l8qRbNAeHL4bj77jHP9Z5caxL4qH5N8rzN1o4pYinUXUSMPkD2msTvhEQN99V6fLT18EfY8haE3PfRgqC9+Y0U4npam9YRXlAc59ibQaGZ0QdjR1agujdSnb03OY8iiNGsZg9NOCy7piRcr/A8KNIFzGBa2ZM5kwmqV3EQg+k+DOZQxO7/zTI76wzMVrRd7wzpfKjdNjPid3APq6lr4N5AtvF9eFmP/v8sXyX0iB/mcWP2R/JyIlsNCPJfeT1b2NEZ7p+F7tWaHp18yAPgrwZCHWP9n9XxvwkzlgHAxhynVwKPCzMgiefi0xdlE6eG/8a8/Z8ckYhKqUeRQPi/6tJU5e5c7tCl9t6oBYf74K+Wr17CTTQsCDEF7o+r3KkCVZq306VANispjdIUXy0ymZh1cRCnq4zsjdSdmyH3rqM6+aoxd0pTjOw6f3Ig/K7l1Bdi1G2RrUM/8OwGbX/tKpEZbHBwwZ4KcXMIWNeqnXYNDm0IO9sgnQYx4/X1A/BSEMEcRyTfHzBQKAkQoPDK4LMx+URcJCrsp+JrVeLNnOBtoI/dhGKBDaclIQbblDqKu3G4bmp2TqWE4nzY3aJLyWVKBywdI1HCr6EvsrDqSic9NsAZjVE14oc6mg52F4AinM8BhjwC4EjAhqHi8/iIqLL0zREQdUF74Voe4sFhNb0YN+iD8rQvAJqySDLWXtI0+twYdGXYAJhDkE3+rJ4GHXFX+LaFhbsTzIItk/FyjGOKowtTJ3kvjfBQY5JL0Kg4JprNdF282ASr6vEfezsCsyNZl1me9dnabB7r1jk4vFbMU0FgDgZ0G7Q4y/epeAUPrs+Eymeq7a3f2NTXqTubxBfVJSfeM7r52ij65/kiLOmIQ/U7NxNEgYlawkcaz2IT2bs78yLMS4IEJRuT2siCnPSz3CquSmIQCGKtWhsNspv/ewwMOMLAAC85YCM4PxbdvQmuamhkiETGwufIPKziK5QOBKiYgWIqqYb01zOeaxx5UcFQdcHyOqJ4yAJyUkey7LMmvuea6RQXQcg9WrcVmWODi2RrAo0eChOWhZhhoCmRefKrN9LaXszwlA9I8r1sp+DpodFtN52FN61CNNR1WiePs8ZkUPwTxwTeBZceIEd+L92D+abxx5/Ly9XL/MLGjwPrOBugSMAxIHwVB2lvV3w4294PaWAYwgFQHu7V6VYqksasYDGZQcDFQcvn1kZLtlEiaKSwJi3dT7vGNZFg0jK7r3IK6E8iydFPhu3uc6LzO+o4MUAfPcB2bxzu7foFkRoT+r6U5VhFHS3T3f6XMh9Y5c/VY+0pSUzWGLTHGPm2GZZx6CrtEylVmR5CHVG9w3X+F7g3fTO70VumIHk3YE6OTvHFOEwExv3SM9DzLUZzqtQ1VFh5uvDWHzlvTne6ingPmjvh3dv0XbOPCH708gEIF/WfZlwiiCX767f8DlpSgNJ3qG3CsxYK/X6JGnJ8IZ7dTAg7FuK7ZtYBsbeDDGWLGtmyq9JA0upnaseG7G2FsCEDiVMHafaBQ8o/zPpBSJPgfwlbksY4Di7LZ0i2jSTFlIquBbABoMMe/6UME0jRgz9d/g2RXwzB6pSiJNC0AYwugDQC8GDARNVzFaKOj1y1xXnQE3mmlIoxMKvBBvqsWBeXP6mlLMO7mlcOASBB2fvb5ynaQYLCQbVMYfkZJ8mQzOOSNN1FWQ/F+pY3rtmm8Mvn/XwX1fc/ZwtNv2HIrg+ZD9sx0zfXOr7CHt6IWgTAT0xQNGF9wrGXUj+MBGZkTNpgjfVbvb2wpvqpRuAjP+i5fhERGUrDbNVd0d9gmd3ACI0KHvNpCFdy+5z73XBuNS6A7Z2ureFLV5sX1tR2BNSQFVkDssiQjakjStMUMspUrQDxKMNcfjOMoCiWu/zaDcU9AEZbHDu6O19kgYTzMj6GsuXHAKze9M0kLZf5sLLvwCameElKukH0hzyIKzJ/7Z59L7XvrQukYxsnUcZki9N/KOMUf1N/iRWBs6fqfwJ2mEQ0Eb0jDSG5Xr753eF/rv96YXKY3vb9G+qev+luO2Wlulf0ZbwlgIahxW23fZDiErbCDcGY9OAO7EYhZQ8mM5jXNfn40f0WRF7zHwIfq8HwMOpq2cIg/xMqS8RYU3LGeXPX9eYfzorPZXKl8bqv1WqbzXR1I5+RHX0AE0/ITxK4PxG5j/gf/7H/8NTz//nN7n37F4fd8Slv5ryu/Qsbs3+r+qHBnB7e/v36ks6V+1HKZxtPLaOv94fEB4tUyoAi5Fp3AKgADSm3qhk/MROslnCDoRVma0rjIkZ0FEEJGvTEhj9FZCrOEOPtSKYSkUL517w7ZlNFetQtP5aWYl9p6anEijM95bc0NmOVJVqMs08uu5uDlPN+b+e2BHuqJ1/4qyb++/wOb5F5b/ggr0fw9CHwJcCpHPwXN2/iaVknYQ+pqiZ5FbO9sZJXtTpSNTj55IPb4fRQ/J76xPAg3BDmjuHwHhk3Fw7+FMuF57j19+XnH3384gtCDqVeH9LuQBfshw5a5yJO8EWGwsP0iGGP9EwN+Z8OvOc+h6vW/dl+P7wZEez9/+aa29fuGKc81hRHbvsEoAUMU5JTPCN95NxXvpgB82dsy5Pp4V4PMzpLV4S8EIix/AEAdwh0s/sIXXRcuZaKSKBxWaJtOdPbE2iTAkGVAAeJgOle7RC5ztboMip/54j07d8ndLuOTkAdVPRX6tnpRsms/IB16OoyhtlKMNIMD4fIGH6hIiE44RLJEKhE2IFw4rqkRg80wBAe0E8OZtmLHCsB2yENSrGbHvXXHFZN7mUGu89MJT4UNrZvlvSvUGwthWoInma2XLWxd+42Vs5YAVihpfS9J6BnN4FoShxA6WGnX01jAuDGIGTmKHaz06hHIiYNOV5p5zsjAJhBJ6Uj0n2LTX/HJkfVquDw7xCc8z7FfhnNQfNue15ipcG1Po9/TWV88orXcMVYApCnNFuoXWjP1T+vLiHpSmaD4paPGLSXKMIodxkgBYBXJypThMwJNrmYf5HYQL0KlN7bmAMS0dDzBjbZuB0/0J67oiTFJ2ynhteQO/NM1bEZVVQxGFYSIXsE47L4sLKAz2y9e2X4rlVfkhVuURGp3vJeusjLfdpRR4OC6snfM+R9Ri649AND+5GEZin18PNFwFG6aoRa6F4xq2dAEexrIbHl6WxQ4gVoOFUW+tYZjA2w8z1BuG4ZPWGvIkY2OzwwsBxWNaveFTiMho0iCiyvjmJsvF2KUZLo6wm9aGwHK5uquHuG2GeldAEErmwwOwaE5X8gPXMO9+pphvxxkAYWkLTqcl54SAbbuAuWPbuoZsH6qcYAY2D3drBzgPgQtfO4uUwaxKRhKNngHAFApmAOGcCxGI/OBnOLu1Kee1Igajg43Cm1lz2wJjW5UXHOWAZ6E13fDB8/DOgjggFBCeEzRwFxlOnmnenoeh8m//FllucOc14k3bZ8Pyx7uAWpBmfXVDhzFFEVBOhhE+95K8AgXY2r4SS08g6tHMY0R6gOh1sz3gClyZn0/D8/3iYyLZKeByCA26F7uHcG9d89DKgAiBmQIn7Tkx3S/zmlX6Izs+/Ap3pTQBnqu2fA7Hr5MS3RCh0+EQiDo9hw8zveP3dc5FDn9WwTgZ3yKCNA5xQhVjl5gDImDbNoA0IofjQoEqwmk54fL8Et83RRxwSNW9StF/arpGZGsrkOBjl+VsXojmFexpJagZyXSkovhsMiJzPqIoHfazc33sqlwlQUOb+33NKU/+oczrXxsJA1Rrm0UCr8wKqrJqdalkTNeWgl7nrdJOW48wjKt7ytq+u38AEeHl+bMF6yg01M8FfVG81juW+3ssd3caDcWUCnTW7zbesK4r1m3Fy+UCGZp+4+VywbZuun5XUUrKlbdtUVRUEW2GM0QRMY3cOMn5HaShJpEqHF3h4SjO+V2Cei166obWFywWgcKV561bOqumqVSW+wdABOvThm3pINYw8h6Tp9/3MMQJJYyY934YbwGwc4QYPAIOC+V3dNZPAYzWF0MTqaSGJP8VOKJuy93e38dFMggMfOEwu98HHNFAnCfy5mX3JoK+fV0p+/7gqcQru6cTj1H7FF8FvM93r/e6j2THFoK/OhnbXKphUciKKJ9VBVYxp4p762XVZTHekVnCcFLpj8PDfi5sXSEB937Gbx7WvJHSO+qgpme/1pulGevKIyCPwr63xOrJsRQTU7vpXWBYtDeLauLnJo2yZhypKF8mxbHE6+gwHk6JQuz33gFX2AvrGSiM08MoPSOmRCQHcbNZ5dUbgOVdx/h0h4FnR0J2yLwinnlBNv/IvaUgKqjqEX4W0P1nizp4BnAPWMh4foHh/GJkFfIg42/4bC3s4JCgvCgLWLayFXQOqDn/nnixzq29mbgmaCuCh4u5kIQljZIES1dFaEg+w6sJelj5WRulABZsoBA7pzGA1s+GhwynuWyn7lGPeOdzpUGhsgOvcDnT7zmIsOY4r4HbTu9+AH9iNHya0rTc2/vPTuZvlHufRmvFI4kc9S8NoKTc1Pd/sDNNVdDeMobY4zYixxMH7xXe548Ub0+jnb69vrdQiqo8fi9IO3t8P6Xyvr7C4U3Plcv8Le6//PoLLtJwd+9zAAAgAElEQVQhoO+q4N4rzP3311LWKI4Sv1CBK9J/sNe/xhP9HwB+/eJbr5Qjmd8NGHd25d+l/NG+HHmev5d0MiQR/EYaEZVp3mdHfMt1d4xKGR+9NE+HBpyWjufLikciPBNhiSilAuoqwCSj1cui/IGSZHdxE4AahAdQ5Ce5iUyuZHTZnUhXOM0ww3kIiFQuOyCa2sXDtZNo3SzoAvxuv90Rgd3g3/iDPWda5+j7l9xY37w/31jkjYA/8cHOqBkt+TfaNv/25b+gAv37lz8K9IcAKQBTtXYsj4I5/YbypQ30hkc11Hp9Spg9wK+Rjp7iXv7fy3x/Isx0VXd9t2MuhGuLvz/uhV5b3Y/yNSKz++xGHxqumcSj1vafX1Un89P9su7DMFL55yPJa4RipROBPJQg7BgZWkebARd0w0XjfpgvbbpACgihUPXBsxev5ueYU8t7DcCJCMu7B/N8t0gNzBhPLzoq72s59KU82kYV5765LRcpFFFTzJOnE5g8qDeVPrpS2JuJ2fFDORFooRCULwvB00VTI/TFjAAmr4rpxAPP50tk+cotlBzBhSNNlTsNIGrK6IDQLc8uSOevm6Lbc8MFgz8GejtNYxZBCfUpuaDDTiNmHVjXkhbEOCdvpKLFDBJtL4YAKASwruTQ++4wdRt9fR0mrmwSYRcGuvRZ4Ta3dCi3KY2ZhC3sMzOGWOhm8e+14+xT4EyaP+dZ8DAps8thuVpJHo087ttAYh6psGeS49PxEKh18FhV4ePCEvemP2hvvtywunOllPXysM2lfxR9S+HZniHz8PcprHkDqQvB7Q63xPPDj248mu/XnVhDXCJg1Q4BIfXOPZOVp0DJxW9keR89xYFVliHebd4jhKfADgGEpZ/Sk4iAMTarJ70h2A5Nur6qxFOPv/SSU+WCwSJLCBcFlIZSrLnNhS1MJqkoqqGDzdQ3FG3lwEN+2PKx+CPxNSffDIkPTKjlAsoye6oAhwtQ/YClkTZCYOfwZ5tZQ1I37b/k/lzXFb139a4fjHXdsFmOdCmhb115nkJU27Oxm8q4YEKmAjBkcKGGZe5dvqgM0b3Rfeo89GkRSOq86vg8L3CEHGXGYPNOh0xpQ7xvMX9T36/p3XcthDBwOFKQvLqXRZWAYoZJiSv945mxFIGGZR+JQ9RjdcTBeBIm1qbqjW+cDrJ9osqCbuGRj7mXpGYy7YeJBgIRal1vFuQX+FCVgWL7W1yKYR5zHr0HSF7E+6p7I/mTSXBNySf65M+5RG+Na5qQr5vL3btEZkSCNBh1Bcs0B4YftM+Kjdw8I4Ts9rHTkiH2lgli2ELEBv02xsKVv1zgRlNoZJ5wGFyy4/Wc3eshFsHzHG4wJ80DB6NRTOHhVIpMN4XT8O21jTXToteXKabbBSbBj+4r1deen590BI7HJKPVh0KK1Hio9UXTh/SeynN73qlFTl7HVcLqjT7WTaMfDUa7O2ExHH40Tp9tkjRMzNznAFkaIyb3frHIFdhFfapzQjSnzQLUs7bZuJwf9vc9GldTQ1VpDctJeWpsDW1sGINBY0uFfiO03iOSFwBskmsMMeV30/VIukJBb8ED6KbgbA3Sm3r1WIQTXdJWxuVrnt61M16UmL1muCMWPhllwyF7z9Ok/c7/6PpUfnLe1xMPi6PQ7jM9of2VA2/p301Y/wINPNrR16M7qPbVWr+u1LoqPqtnWlVwEyKlBBBKT8fjLGoMrSFRZ8NnMZwoU4PpmQwAqKHhDUe31u3MuqDbubIbDfQw7oDBqFReaIeMHGc7T1i0W9p9PU/FecXInUcYIlhao1CWzuAplq7CYasJQ6ihiQDmHS+NoQbeCuMR2STmvUHIPLQtqQMbb86fGP19R3/s4Cc/0/nQBBUvxD0f/xR9za/3MCfAMyBN0O5eoPH37gFcQHeAeLC8c/72jlfYr7wAqPD/ZjiGul6wdBLU0kMPZqRQnHeuPZrL2e1LQnoqvHFVgO/wiFPXKstSrJQYe6amZbzWj4kn2nUjeaHsN+3a3w2yzJfXWHGm/tkAjfZFhP6+AR/egfAJGxRunqCwfQfCS5yTSt12QVCZWRga3OhOYNBylqr9ucn7O8/tm2s/Pu+HGdqTWYh/L8X5rfI98ehRjuj337OBUmobe0yHg+s/s/zZXuevlQ/f8M0v+Ib5uZJNyfHvb+jPv3N5bV1/EjXUIKjyHAC6aHSAD7TjoozkfqlI+X/Qcqhjlgjw4DzyED2HOU9KhHY6o7GgNaDTgqUv2MzAFTxCztXQsJlhr+N9wFGR8hGbGYAube7bAJTXGc4vi51fGCLKI+iZTdPLMXNEDfVzXXifF/z2rTB0890/uB/d6eyrKpo68wc6EGznfxJS+QuW765AL7z/f3KZD3GprJG4mv++Xg5439ffLxNwuB3i8D8fbma+5sgL87Ca2vAX3tyzpIrNGihyqgA63kbAAsLwvBVCOJFZn1k7Q9wbS+ti/GYH+b/jhL8D9OvUvIeH95wqwVPaC1W47qviXt3PVkdHWljdRhh+X3bXuHnfzwVHh/I9XNdpfhBE3z7ZPNTwkf/9//y/8D/+1//cta7zdhYd+XOsu4VThx9XtKT/jV8b8WnNQv/qWOyurbL/dSaZwkukWw4tJhU28pVaQ4taf8+zRfvDhSmXUihRempC4kfyEO+SY7G58mVkEFaRQEouPHClzOBnu6/zMWwhSASyDRUKdGvZ95fnpYTEXLhAySsiAaQRGC6QqjMZnZnyU5Gop6ELrjTMtoC2XDl+MavnhWx8EtOVM2oht6klkEEwthUXEfN6IVszVcBLm+fYhR0RKQCqUOvd9rogGIylmxcxA+u2xjwDhMW8z+uhPL3I1Wt+8oaxcQFUQuxarl4TWPiQGrUCH+r1GoYHxaAgIOuOjnOgy439uft78Fn+ldxZ9YAdwiCpuY11vipDJoNB1NFcodaA8czgzf4Jw4e1mYBLc1Yy6AwQ1ELTLSZlLX1bYeEMdyHXL0OZ4Q4VRA9jIE1IM0yhT9SCQYVoLkD1rAAAC/FovzPsvE96mRBrv5/vLPJBx+cnx94zvUxo3ICXE3DnHg1VUKDeVgrrZUUijKjVKlWQrQ+qpy9zhkqOEH+1OoejCOnrrZeyIwWVUjteckVYAor+Hpv+dWWaK2pg4a18Cp3JV+Fhbc3uW9/9LMBQ4VUvueoJ/x97b7reOI6sCb8BkJKdW2VXn/n13f/FzTfd05WLbUkkIuZHLAhQlO1cajmnG/VkWaJIEEsg9oXAbdUz7fVR2b1/rSsmjQyaCFPVLBAiZFHg6DCm1mkTpgRtZdTa58Cm/AyVFQnIs2aQKu3j6NcKd6rK5wcxb3UOJFs3gSlQS4p2ScvqrXmqdnHBSGtxUdUISjGHQ7YSCvm503nF2oB5LlguhteaoAljbSvWtaGtrPXbLYoZVjc3G6A9g0AhzX5TLDtLIQZQInIRCc40te8EqjSk+IXR2zpNqFVLgWS6oijAUo81TT8v3Ot2NuHIXELFHMQwhcCp65QwG2GE2QG6N+c8/0M+IcZ7eRSa04B0r4JQeskeCxbHtytMVTnaFaQhBO8oLsVpFgiISFJ1AAtHA0gogL0JUoRsMG0KpTl1e4fzPn+vLw5Y3WPSLA6FEEYDd/aAuCOoGulgPEpkHolJdBh3549Mv8ZVJz96KCjgIsrAlNIZGX/I3ic+9lwbXBfVzovXRC5Bq/uYlK4Pa7VtRku2LJ+wGZ1tXFrmpq9lrVprfbVI8mIR4m1T09rtQN637ykl3Ahb/xgLHM8af0hKF/SEAq2Z0d0MoOCGtgoELdabB5g0eitihvTbtbN7FNjYsqrfl5kIlgWElM1rAqkUdXrdqOJ4MvcrluFGOmT0fSPbEHHeTJ8rhTQgcREUHMDIjszu8FYT8XCnC6BgBh0I7XIeNn86HHVuizJjdHfUtT9ftNyPOWl6wpNSCLyu4FLBh4NR/IPKVWSZHKaK1lrQxsYMXhbdg6Y4ektX+tqk/zvfaDhZSJ3PlE7uVo8f9pFInWNqUdqpZ1vfyU0wk2ULKT2rgkCM59J5H+7fhDMaEXA4HnA5X3D5qpms0IxSGn2uVipFRNNPs3j0TUWTBjJj5lRqnJmAdiLLXKJQUbioU4aIlXoCykyR0SSi1eH81zXzvPXhEYYa8ftCDQ8MBkTHgHZQb6GQ4dlAgLciygcmFO6ojc5KDnd9TyMAzSJ2X8r1t53TltTJzrXXjeEeGGijO1Z0utuVQR3v+G8exV9q0UxZbBxR8+OgZ8udWBS1bRzOisJmKYQyVUwWsVws20J3CFTY9ehyHb85bBi9ojQ23SvLmOK6AS8ZF1lx7D4rqeNDij4AQBS+c06PEfz0xc3fR1UzgommkxVhnRNGw3B3QvXINIyKdhagKP6tb0zueDI+3wnWVs82AIrA+bPgL5znDZzvdEQXUIjAF4BE8e/h7h7LuZcNkLPvm+bok3ZW/sDlRCc6qTxQ4xXB98gYCFFL0bUpPfIeouXudDqWjQnjOZOYDMcexgDsUOasCUBR3UasPTSbUzHaXfSfL2lAaDoL3r/TaILhLSLNNAKKgAd/SnwO1pc774oATBxZFvbaBuNd4Rl37ToC4AcG3QPlfQHJO8jXr4Oe6Lx5Ohv+79hTt+tbV3xF3ax3HpMfmz2H9y92PZe/TIxn//sMsoqsaXlPA2jzSL4X87p+9Ptw5mvaO0MQ0f/3DzX6I+j6vhPVPee64962dOSVS/7Nzfv92ango+UD9Ir2DmpEYvv3PYb172k3I8//oPe/tn2rHewXBj7t5MjPjiECYEoTLdBMwRkGRxycMiJf/T42bgIphLkCsCxdIowTBG8tE+BFLHMGqe5lacA0me4JquepYjrO1lCoYFnXXqrOcTGAwzSBiLC2FQLBXCcrByZhj9H/6eyay9ppTjpN03EyozGhJYdoRutG88SnvjbQ4I+EqR8PfrjFh3f9ncv+fj1It/Fy/2mvb/+JQH9to29nHG7hzkEAkA2DKp1Pf+59P+Il8txMnOB770xu6hVl/IUw4QMafd5hDlw02u+9G73H5pHAmXY/kEaa+xtyxPkX0r5+TiR6Gn3q63u7fSOExw0W2hrPe//qnXon21W8HoOuzeY+M9hssxqHvrtLpFrLzxQwNdVhzZPmRJxCeyldQdKlHInnsuAc0TpkY3XEHIonhQ1J+5rhuAA4gsx5oKCgagR2USWbPEnS23cR1NNSquGLBnhypsKvpQT1tkY0wB6INLrD1oA6tVVBbOhXhVJPIaeVQT21rSkZHMMSutA5iKXjngozyIzc67pgZTWcFio4Ho8otWDGDCrJdGLMQ4WuQSEZcAiLGsNKVQZnXdZQGBzmA2qpVlfR9sR17dJBxOT++D46CElaVXQBxrRtrnRzhXAoocVjXyTWcsSFsulbQijcvjNfpS6Gx9Ztv+QIaP/uuIfFnZpGwwi7sUtcySsjjGtYcDzjaeslnyN04T5+m8TC7wE5C2QSyMVglMzxJARiSmUM0jqJQNzIKT3SV7jf7AySpPUb1meDtgUShpCICFNrxbBH+VFK1/tnWCrnPm839twSMcdI8O1Ye0QKpR76Pkv6sqF2w9f+xZWXAaO7Y/JzYPsJhWFBjb2XQVMG00H0FSf28WY4FNQyq0NJMmgtvGq2EKjzwUjzBTKUXS5ha4OYYcv+NgGoqaFP2J27fPwGt5YbgEpRBbo5BAjMKGI0hIaFdgxs3yIdcpo3pZU0+HVyEjoyW68ABz/3tr8s4rng+35BDQXruqKtWhbBM3do5I1GbzdWY+uyuMGVLaKfA5Z6tMVoNHMnLcXYFIouBzY3wqgDQ4lSIyH0kUZeFlMUduOwKyY1JXlb1XgeBnQRQHR8nhmkeFSi166VtH8bnPj7tp3z1P/o5w1vOhjRgZ6mMiv0gcCHYai2GsHiMCHmaNBawLYE3PT+umGdO6zSOA4xgpbPuXvdk52DqHVs0VwCQVubKq7B+rl1x6qM68dm35Pwri/s390hJw3G7P7m8GZYQGsbI+DUHTX1TzfyI/DGFYcRV2i4Nu5YvrbPCxsxsVt9Jwe8GXh+7PnqjUG/RBEkRrri/FSkTjUfsIKRbsP4P3+pMCAlObBRwruBR2DZLPxfx5uO7/v6Xq/UraXJX4gKUB220w2D8Xx0tLo6G2kcmc8PRxeMsKWo7QDZ9ULs90R0q/Me6BAyHQ795sMBhAXtdO7PGd/tzia1qBFuqjUyDejoLiC6t7TnB2THTJ03g9cFq2UU8fMMfw8yP5DHb0yNfQs+LHj2ztff2reScbLjVKv5sUAwWX9kDsfgBmqewr1gnub47GWxqkXhLw8LllXPdZkLpnnCVCY99wDKUiODSikVlSuEG0pRB5Raa68NaTQBxUrylAJMtTt8xFqJOQI5n637JNLPJsU1oyVkzmooKgMymUzp+OU6atRZHIdR5u0edTyoa5p+kfyb80YbvouA7li7izW03RHoxJtfjgCdB8TTxdZxLtmp93vbNY79lid9HIlUOQ4XSXuV5CaIOnGwhAOZig8MeRR14ntPkAcxw56Vo7L9IhPuSACqSnuqyb2FWCNiTUdQU+YEBA/UJ0zY0HtfaOZkbAfcMdZxqsKP6xbSMbYH3NBLxY16ybE70wYmMzoWc7wy+BZCKZNllqDg/bqR3A3PFQLNYBRR/ehnRUTAj2y8wR0gTwBpAAMnXHNt1HQGN+20SASle73yrbgQPLVgLHUgMsKZy09ZeHPi0Dh91ye8vFChikKqK9DyXsYjeBkke5fzaHtzy+NMG2bzofGOBAPZGTPghvrf/nyHCUGmheM7Cab7MdpHmzvS4sFxWMdb/ZfduYnjpfGmJc3R+Y8IYDAnFjaKs6VdWxxEaW3c8fElXPSSgSXWYO8+GvdngNFEbwdc88L7/irNDYs/OwLdV+u9jNcyn5RbvvaVNFr4f3L7Cg2o++nT3MOne5/zPT97DH9C2zOe5+aw5xm8GBp9/uzct0LYCy3j7aGJlaMSAk0VRTQTR8gAxiNnh/laSsjGbAEStRQ0bmG/iPIpDNTJnLolhw+6XOZfJT0rkbkRwmAmNKFI2c6SMm1mbnOPn31xUX5fGPtum95zAs5rnv1P++72uxnQt+f1B+y9f1B7CQLtmBlj9dKEMhvZ4yXS9UGx9z3jeWm4r5lP//Pxv37F13/+M5DJwQQE90ilwF8upFhtUSIzHHpqP4szJBXO3Wj+Rjw9uzGz6MzeKB5rVTdnWCJCf3PX89HnaWK7LA7SbzfuC4benpLbbzvZHt4JQcqe6QW4NwmRs0ABrXZ1omuDTfYWJqIhomKPwI0RVX1e7imuShlVbk21ok6T3rGuQCkRVWWULmqqagpx+5wU9y5obZsKRib0Rm2sNCfxjAU2YtF/bMx9IbXfFAJwOmH68F4J7NdT9B/CKLqQ1XeHoh4LSzLAWOPEbBCpMF5cWR1Cj0Kn1yKMo0IE9jScohE0zA0evcZEWov1ajd3GL7V3jX56NMYWVBEhcNqRneRhvP5hKkU4CCY6ACaSOue16Q0E0JrDEzFojUFpTBAFZfLBYWK1vh15YRZ3YpMytzUCVVNZcoMsW0IhTgJCDQioVSwaFTXsq4AEaZpsnXUdahUoRl2Os4U9NTVcT0LtVYrG0cCIiDqWlzxK9u/N1Gn9D7iFvF0fb1PTl79XoOYG5vxrVmUaBtIAlVAC6MLsqDunv3ubb+eNCL8eNAzciYKT/9Yn6VPlf2w+YA3tX/dgESp7rQAEckKQo/SJKB5LSBPLe4IPyNkr1dPsDqlVofAIhnsVG2MHPocYwVhCoTZux2dI/xsjmeFArflncrYsWwMTRLv8ahf5ImMbStHuFEfjiNsPiyRLnMkk/YuoQGKgiGXHuVAVq8xFHOEUEz4+uv6qYBRHQAVuWBhr/2gyeDDsF5Fo3aa4yjnRww/M6MRYVkWTQ9LJYzpntWATUHflYhW95vU6ITW1InHcRoXjcghgWcCGE9Sx70dR3Dsl6bc1pSH4jhWOp5kOJ3S91MhcBMQC5ZkZFRhCYE3eG1Yyoq1NbR1hdQCEVWkrqumbV+XVe9tupYELZGha+apvxS0S61ovAxsgZPZiIKKqVIoHMtUMJUJ0zRHKmA4PZsnjUAvNaLSCVozugljXRb9ZwZ0jz53qHP6w4VAmnJFh8eclL46hzAeycZQ+w0tUIGN3y/0lG0+ORlOWFeMbhgnyuejnwGbnaIaHvsSQ56e2pXNmcDxb9uUn3CY0yPcr3Uc4ySGrD91sxN0960wBkqBZ3KJeq+uiLZyB2A14Hs0fFvZotkQczYmxxbT5+4rHAvT+Uz7v9PDIsprOA9WihnoU4acwDU+dzOaFSp9nZ1PMmOZRntJZKxBWrvOUo70RUe2z/3myPO0CVhX5VcPhyMEgnW5hPIY0Kw5odSQHsnOpvx3tssNzrmWtdMgjqVllGo8hDJ8Ha83U6IY/oW4McRwiGde8nIOwpEpyRelz93WMy3FrXWJ3yk5NcRmS9qXbPhNyzhwNejPZlhH37N2FpO5sBmfRSyaIT0c2ArZeip8t42h/XC8Q8gUYntwFjOKSZwXzwAQ6dqtlMVcCubjPabDAWWaQHXGbNmUjnLEclxwOMyY55PuHRHocgEEmA4T2qOuS51my/qzxnqP/I+uTC2T8jdt7Xgr4/G0iv28IHiCxZxyALL3NVQqaFVQWeGLWwWXAjqoU8RMM+pUMU0TpnkGAZinGetxwcOnR0xvJ8xtBlhp9/HNAWUllDvl1Za14XI+Y11XzTxDwLouATPOo0NS5hlmqNOWpaounuVGzwfrAYBHC6vhP98zrksuUeM4E9xQNB94rxWfQdEX3lnIlAZaDFcPqG+DH4IWRKymjH0HgL9MxIYTYoMMNLtRHBsKv76Olw1Xedr7Yxh5wpfGPL9V1Vt3GDN53zMnxRomWBfpmYWsMdiyTBlNeEs9K84Hk1+M7rYHRnlLIMukI7DsRVZ7tIjKf6W4Q4xlYPAsJhkHeeYEy1rmmdvCqJsMcGIyjm67OaWT87/UDydg2R6kd0El+ciYYTfkcs++Ya7rlrmilKJ6GOp13TVqn9GkYV004x6IQO78Zhk/fDju6y5PovQFE+obAj/YDrt+5NYeZwOkw5u4kwh6KScko3p6/nJ6wuHuHpenx4AZuFyJMwh3BrUnmIJH+QYAqEUzLAHq8EMF5aCpdSEqe1c4n0ChA0BrYNMJDOVjbAQSI3FajIguj7HHWMzhqIx7ACKUCitD13nKao6v/RR1+dAzWHn9XG9bk7OPV6HZnL9kzKgCq5sbWYow0ssOus5r9N/WzR43APe/6HseP/2GJt1dbYsu8/IAwD16ZgWSt1joa5TkGjK0vbrp+j44F7rz+JZT2ToTddY9X7ddD7zzbeO6dffzXNO3z97bByMbDDOmf29H6EZ5oBvmP1rfvhrNPm9rkL+TbsR33fgH0fu/J+36D0zj+9rIbj7bvqDXRP9ojzR0Fix383D19Le1Ww4df/j6/OR2Kx2/X/e/nnkg3/8eCoOfNjAIAG9VmAFBbSadBxxf5ns1T5qd1ukNTP66L1XpL7OSCiJIJRzLbFlSYaXOjNZSD8ZrrHJyIc2W08yRrVblQ9bWME0axBVymfEI7jUd/E2MVf9rwlauBXpvETyIaDk/l+dchwA3oF+zsrkpB/0z2yt4QvoOpDD2YGzGrXc5T0UhU+vlER5+fBz/Xu0/EeivbD8DQXfQfFlce+737wXxl/iJ/+/XX/HbP/6v3ktARY/mBT5A8BkAwPQpGM+hdjAywYwYYosk1z6eS/KSx+e1PN49k2ppfONeby+1Lhy81F7zFgLw9MLORlR4evVzb79icvVi/DY0Y/6JTEAxRtxTsE3ThDqp8byYoMQuJKXaqzn6M0douDLXlSOOlF04HJQZ8ZdCcM4C5wAzRJjI1XVqRK8WaRXp6mhrtOpinBM8GcaLQbl+qwnMeObCg10vfh3UlQH2P466ij4HJ+kIY8x2nqZziOaMQle/2OZ56k6rcz48bMopXi9optzQDUEiiqrU0Bd3Y8X5ctbPRSNJa/XU5H19CkofsMOW2C4G4b2xjiLAIkBliFCyOA03xaZ3g7p0JfIWerLXoX9Igt3+cCT6HLCdC8ybs7SN3hTxaAUApUckszSsFvHIVke510z1f5bS2wV769sV8g6TrkSMKLc0tivv2i1TtF0ih6FQShqTGPPXG91JIM6F1zBPB9ENvfklYjWMCABWDuG+jxkxx1B9nOzisTPgnuJ/UF72YT+PA9OIrn4wJQclQ+urO5E07h3gzvvRDVYS5VxcsUMk3enClSCNbUwGQV4b3vbfo93urHbqsq4aLS0qaIjhg+bpjC2dlhrOEXP2rCEaGsFdWeV7VK3OIVooa8HQjBOWaWPYS+rw6Q5ETIIp1UeH7OMCP9LuQQzAHIxsA0yRClvvrVe5fx0/+1pLwAtiDTU9u9Ym7ziKhSFNM21cLr0+QinmCGD9lQSKLtxdA43RWXOOAwilqHqvsmCqE+Y6YZ49TbvRO1ufavCp0f+a0YeZwK1hbWvUZ1/XNYQ+n4uvhf9VZx5z3ErYMujrzfY8DfyWFqShxLe0VDtnKOvzNk4pBnzDU6NBUc+NZ0th1jr3wz75fb5Oud5kgiO4U5YrY41YMzqfBBBKVcG81KlHndrMGjMulyXuZ3NSYnewcuOv4yQ4uqP0JS+AfUzZCTrMaZSbEAFFIFKURyg0PE5p+QO/IjkaJTpO5FyKwctOP68CFbr68MqHKZ17sawk7kiHRJM6TVYTr/fte9EdDaIvRyvxbJ+n4j8bYfBTiNqgmSbnGURPREC1lWtpllfgTpuLZORJOp3dLpeXAnC4jzPi+9OVRsObqK/Gdgjd4LR0uhSvFNTjrPNdm3MLPaU9Ok9bSg0CKQJMd29wPj11mcQdaqXTtXiPCNrpEbReML3/AAfAWifUqaBa9CmOrU8AACAASURBVDVEs9tclkVroNeCdV0xlQPETBaFShjur2m8cd+U6tubcyDJhqskqIFZxkwt7mgjdjaFGWiMpokD0CCA2Beowq+YYxqz1o3V0h0VtRYQzZiNrmvWEEK9q5iPB0xNU2JDBNP9iqlWLMuCqRofsFyUdisw6HyEzXlK36/ZUHqWrIiy6YycZs3w0x6ySudhNkuof0gAYXAjcAEKKy0nAhJJ77xyf7R3tMG7QxAtc4w5ncgeaUtj33uDfAlNUcKj2WkX9l5nP7eRmN9iRN8bGaW/r7k/7h6Gp7KTO4AoXKMvPKU5DTRfHbmrlxUSGVJBj6ute1kszZgYTfESJQqviN/c2QxMvW66GZ4jCwX62dMx9jmR8ZTsdM/Rmvg+mNwZjAWFzOPjaZJWTJJ8k3GO9PVkiDpRVSt9RupIonRa1MmdSWn2sCcAHRSB8lNDvTdj/omCEhHuAEv/72ubn9/fa/8kwUNTWggBQOxaBJ0LAThbySyd9zEpyA9+NXCfnW5QpN1t6Nl0yJwhqpWjKSrLpfULeup6oFjTNI8NcA/nP4FyzCPd3zOWUGx1SUbzbEzHgLfTPie8QkEUO78UcuoLTThLqyM+0P67A73Pb01zddSxCPD0+TMm3EMAXILXMqckSQ7DqXn6Y4JgxjvbX1zJRFlUHtbR5+E0219r87jCewFr17zEcH/CNdtI9F0m5C/WCJY8DT9eG/xWBHuGeX8FY98A6iVRa7r3B4e1297L75jS/ZXtCzSde3bv2tLq7xniVkcQn/M922e+811/ZrsFr359D7a8fSFN/f4OHT6LXX+gnvn3rTyfsdfp6rC2knA5awlQMaP8XGbMBwvEI4pMe1purkCkAeAwXq/rauOzUYpgWdXhta1Ny4tu9jv4KudLQBBw1EhXWZvNkavzkt14rvKAy2BbOSVawrWZ1r2E8l6LEl8Dky85Y/9Y6wh8K4sOc3hOyf+fdtWmP4oqPscI/HdojiTuGXgg6YrgbdvMyw2HL803alS4wu4nrM8tnkfiV8CjY/71j38C6NHiC3WGXgBwUeP5CmAG4Hr8kqL4Kj6A8UXvx2c0UkTuwlyVir/JR5zpt5vYhKAMyQfRdxA8cv2ltiXT25nTjc+vfPrGeO+EcCLBfZIg7kA429+T3fdkirGj3eSMxr15dp524Cl4VyLIxpGgmDjnSkgXunpKct0VF1amOmGe9B+Zh3nzWbry0NJ45QF4pJITJApvdMGeb8Mbi9g6Wc1rX0uyNOdiypwzFHbeioml796Bvz5CCJgJmN6/xVSn8FbzdDHFBLCGbnRlAKvVkzLNmL1Xoqbblaety7PB8UlENKk06J7MTu5NMSA9tbHLG65QV6GTRmOiF8yaddyHoiq5dVZBXaymMhdGnUqkgBaoJKBpbTL86V6dTycQyKJ9ZjSrb81mTFIHAAJTw7qo0aHUgmmaIiJcWRFd38k8D7UWXrW9pqSohSlK1GBXSVMVK7zZfQdCawKQoJau2HSFiE7MlBxbw0nAubFYu+j1+uKrqNfe2QIGpbGtLCKyDRoBG0pW1ohXhwhnVCNKyCBCU+wKGisTSdJMcav7VmdlBEshNCYcisLWqXWV/5V4kBX81FULum8TAItQFjXyEAzxcof74gavhK/9+8DdGXzrnpkioFBXcooM9QTHPfCVWUAy22q6EmGzF9Sf0CF0AxeQ6N8e4k3Xkn3oVbxfMI9pifXIe8RmuiidqZUMKxtr0xZm1ThbN8IAVJtsRnUyL9/T5QnHwz0AU/xTA3vab8MltVaN6LRxu1LGFf6NWTN42LpNU8X5smA+HNQBgtcYsxsPxWBlRPfdCYjNm9eFf52ixH0+z3jWrniEuivLPFOD+9MMp35HmS+G3wpIy8dw2gxbyIi242ZhIRKRj9VqX7amqdrXpUfyV6Ne4djCfU8XNybZa9iIm6flJZMiQ9EMQZknTIcD5nnGNKvRhAgaUV1LRNX6DJouLASw1PMrLuuCZsbzxqxK8Eh/rAb/SIHGHGnktQb1WEqhGwKxaXsHg3avX12hzT/oHnoZAGCft40x0PDHzp+tPzIs+St0Hgx1OGjcII21bEZrVkqjje/JSmC/njg63TqlPWFMcJ48DE/UlbqlaOpaUwoonKqR/GIVMMOFQawuu3Ay3suwXoTtetiPwz395r1dIWM0SnCOYqu14RPRPwNkONw7lav3cdO0fBFhtMHTtB3QBrZ6NKnCXVvbsA/rqudvmg/pusTaCUYnPo8i7IpySsMWM5RyZPgo1YxBfqYTno63bQwtgU0EQ5rccHYSMUONBC3N/VG5Pju0+Ry9pn0PWgjnpxFKanbMKNIH52Mkj94bcZbOV3FDOZrx7HIxeOt8q/+fAJTjHDJmmdV/flnW6JMA1OMRXXvv2aR0E4539zifTjCEBCblcVgs44rVYwZmiByAWelTbQwcgGnWmocTCup9xfL4iCKCeZ7RlmYlMCZ8/PsB//z//zeCA6cCCKtRP7JfdLhehYOPEEhk6nED5GhYIAiq8rMu82TDAQvIcS6MlaoAsfJLra1gOkC4gM+M+qainVkdZ98WlDrh8PYALACtNtIL4TgfcHh/0FIfU8X5fMapnDFPk82RcHd/B4hmcGBWJytqsAwxxttTAReJbF6xc5JNpYlHec4J3fC4ykowPKOOX+q8w4AUlcVjDdN5CiDfwcH5IOe7HbQGzhFWESKdkS2y8WlFavd82fkbgJDKDMRYJGA6k6vB6ITx+mvbbUzgM7tu/CCgN4h9Z2F1FGEGqFjd6szXZgKc8KVFUPtcyWQB5b0Y/FVQ3xEKE+hdRfvaIO+l0zZQ4BgBIBw5pCz7mDuYjHy5G0TF9szxU1vXyHAGqHGcyWXwRI+AUJCXmp29xggpIaBaOnjPzhMR0jYucgM9wSKvFV8QCFOddOWqytbUGoBFz3CD8tgsWKM+KyAnjrVsJ4sYIGgddG+ppjs2sHzVOjGDnxVLitLp2vDAEcLGi0fR2g4r+oRA5AQqd/DYaBHR7HPOTVnJBzWcW2kNALUWtCaxnhGNneRM70UAc9717CabEbtAlcblGHY8p5KM56rzKaT8bbG9IgpqgwmTpeF1owuhGb8TvKeXwkB31ClWdkQu/maHV/185egc6FJS+S3DQZkm7GzrAaqHesJjopcjOGQ85mfoTKpjLQQ0PEAgeIzME53fEZHc7ZV8u8Vbeu/WSUqCh7tlC+8Zcvb6t8nEIErwbd/T3Jj3fU/fbl+tzw9QOvLe/Mq/x5Ce6557JtSeEbWfiy/UU7Sv6PXXAX3+g2To79ffCywU7eX2mnX6XY3nryNnOg70dO4OY1/SI+/R1+Q1+3LLeP7K4fwl2q2z6+2lyHNvH9WHDZ83936w/mcizAIsxvdz6WftgV5f0mBpGih0tIxKgGAqFYfjHZbzGTMRylSVX6lVM5xWdTQn01t52nYPSlAnVf+n0KHlRLv8o1kH2dLAI8rN6ggEd4cDwIKn05M5t5vDVeulYnStLaOYG88lZTQL3dF+257Vn92e6/eH7X0k2NqIxv6RfvcTuhlTyEf/aa9t/4lA/8a2rW/9qvZHAuX3HIIklBLUS+m9jIers/gCtwluX7PiMyp+QbHP+tQHwK4DhPo3wuG3X8DPsBC59uj3r1xGFr9v20N+d+ie3Pna2S4e7doFwBFaB/28lzZ4YJB7Zy+uy7CnBVOpmOqkwpQpAN3wHjUiJXlBw7ILkBM6qJd0cWGLgJKMfmnMZ3SBG0Q4RIo/VW3cgXBH6hhRQJigEfLy4R3k4QHzu3cok6a8bU3ADz2un+L/B6T83ps90LcXeB1oHoE1gcT2uPhP6rzRjfQqqO2lj77SxoRiwD32N2Cwnx4mBBXq301oZhkN2UICNOC0nFGpRorbxdJJSmuY5xlzqVgXS7VnShlVYBS4Q4AIIE0gJChzATfGKlBvwCFZ1bjOoWR2+RnKtHRBGl2glC4MbtdP5drfDz8OIrztD0l/t8cgUL47AN6uuuHLlD+DV6NtFNvWafkChiZXNGOARat7LWePTNZjGOqGYO6+DWOZoiSrYzLXPkrzkd42L0wXhrthKjdhzouY/4z3DZ8ZOAFyh9jjvMvXz4e5Yju7zQXa+TGfshdWjzafMy64Mqa4KgUbpYEg0gqiR7whdefpSSldt+yqAHok9mE6quKLG6Q1K2ilmUHirFm6djKcLq5hgXUq6kZEBDARzotASlKKUFdK9hW+1mK4MCPSQOVgqTIBV8z3msxXBzn61BS0wDTNG+WOY1NL7SWj0jDwhe2JR+65w4EOQ2F9q+4pVFCqGs+nqWqabQjW1RxITLArZhRF3ex1nktSRPtvqoDqqby9vm+ZKg7ThGk+4HDQNL5wJawpnRQyJN7nUeaedl5TgI9R1apg1LEUVgW0G9bcKJ+zBnyvMutbW+IaOhTtGc/RcX03oiTD/g18P9IMpVXCopk/WrOMA2qgC/APnLlZA2c/0JX7V+9zBWkoGPVer3se6dut/8YNzUq3kKdlh6WHYy2rIFfTo5iyCrGO5Zxg5Fs7zxjKTsfRbkjuCx8L3BWdNJQiiTMfCtXrRcjGimFtvI+rRd3Cmp7RHm3V0UGOkGLh9LSkffZzYmefrmmAzxOUFMPOT8Qa6t8hKisTGR0m3DQXYwlDCMZ1Gph3iih2KvvK5utG+XFkRfo1Xuy4Yt9yJ7tKfOlkZ+BXJP7pLOvhYNHet8dNm7+B821sbVnUeWRQasLqvhKkaGrGKubQxQI5CKjM4MZoZUVrkyrJqhqv2/kczrx8uaDUgmVZcDzeWyp2f1GP5FNfRQq8mufPw9p2/OgOC2F3MdhgWcH9Vp2/4StnzRznQYCD14QXQeMz1nZA44bHL484Ho5aZmPRl2hJjoZ1Vbpc5xpzQKpxXksB294IoOnsGZgPFesqAFWsAGqzlO0kGm0jq9HIztsFHLtDp/SzlHdenVD2oMCdiAUsKu2oAzJA6M6YblRxp+p0JDfdGc2LG/x/tnseLRT/7yd/PGNXHd/8Rc/wEZRkw+5wmBEoOg7RJ59Vrr6mvUaKGaDzUbnEcq817dkdRNDx0fCkydC616l8S/zWQw06vmcwm8MyAfSWIA+AfHBnoVEaZT/vDMiyqqLbshDoGVJjp9JGgKpESRF2Od/HZK3Y2vr2D3SikjnFZJxrfzPtQ4ccuL4iFl55C1fUQ4BSOz1xp0p3DvH16ObXvIMS9GR9asilasjepehDndnYMsClweAaKq/bFlY69KtmiAxZXdNfv18AHHQdaQJESxWpYxkHX0Bu2KgVZapa+7wUNFotOEHXxTNx5Ohz551fOaU0wi7L+RhGpsiulc6fFcO1FQR49o5GoFUDb1YxR1iX4bNT99UIdvBDQlKBhgYRyAGy4wHnoS438MLiz1/9bJPJ/CWAoxDOBbg3NFTEDLIE5Q42/fQo8D582sDAVSYN8iXqOzEuRF+l/aFnxn2fv/8rtx/D4KOhcc/oKJu/jOff+brgr+9rf4XI821zg/kHKIz9Apg2TOul//KD/f/o/v7V2msdPJiu557hs5HS7lsszEPIw8+3K37KnigAjscjGjdUFHPMUrxORiNUv6IlX6ZSsfIKU3ka++J6HAZJvVIDMCR0K+KDTQcusKl3WrptQuld4jHE+WGxdZGE129wl+l9t+DsJvz94DkM1vR78O0N2f7mrbs/vLqL/7TU/jQDejBq/40I9KuQ9wZC/dsfwYjE+U8M4HP3plvxEBya/q2GOj+TpPrlPZrchZovJHgvLqqZIIVP6S3dUC7UsPymrPXhl1+BQmif/jWMNavnjZ3F8eNHfPr0G1yd8fyMnruesUQW1vp912u2wSxBiPTDyeQLr4P+Rggn0jRNgNY6AjS1+ymogOBEWhddhHGCGtfdiK6jGpnvUfxApKLswl2Jo3QHQjWb14kI76mApoJaJ7wtBWfTrzT01KhRMxkAKEVeQc+q10xzhc1dIWgtKY3We7IRu/H8Pq3eCjPNiUbqnwm4g6CKCtfzh7dat00I5cMHTLViXVYsj49ophhzI6EqsxhUzqj378BPX33IGyWgRQPb/uQUc1uBcKtXyde7EQppVySkqw5NguIOC0nZGQrwRQ/JZbYajaugTABNNp7m70zzDDG0C/phjCEAraHZuGqpaEyA1fwVuYBLxTzN5gjhChM/82K9ad3qUmcIi0bDsJ5mCZ0GGQwwJpoitbOIhFHK8VszxYafGk+/R0Mhb/WCF9HoPRe0EXfY+l76lT11Qt/r69OMdD3f5/oRH2PZ3E96khQgpCKSXxJQiIea5hCgsa1LndT7n9dIr+yM3cCssaChR+aBNJq0inpdnibde1n20tnqumh2eZ0FWz3eYin5Y27SmWm1O2q0lTKXDITi0/balEt6xTAvy7hwr2h5Hyhf2LnRFW9bnEo2/iH6cSPYu3NAXx1cKRSG120BYXtbMM7pfIm/txuQc+087yfTXB8nm4IzR+xkvO2o9sJnM66Rpv8GzEGjxR5LI5RZDQ3TpArNtijCkJRRgKCRYofjrDXMAYilyCKH6Zj3NV2JeREGpCijpunqgX7uJN7RvGYtjSDkBqw9sipAJETwHfXI28hgQWnkZlCppYBIcd18mLAsCwjAUlYzupAaHYrWmZVVLCVtEjjFeZeOb0CaPlTxm+5d1DEvRd83zzgeDzgcDpinGU203pen9YZ5QntqTGY1lnPTmp1tbbpWScGv81FFdcOKiqIOFoFUkrD1SqX/7bue56loe4e+2PbVsWgsmBm3N0ZGyXgMfggiiiweR8Lx0tOji9VNa9zs8w4lyOuQzi6RGJxYXfBCkJYzL1AYtz0FndaAdaeT3r3XUzMbXowhxhnwRMGPUUC8OGXRt1qKZc2p6uez47AtGvOIazhu6rUnYlscJhx/CqymrJ/nHVghS/vrOE+NjRuHw7RO3kPxdHu2LkllHvgseBn7LEbrID1yuq9vC8WvO9f4+/y8E2z6lPMgeXSu7vlktdUDDIyuuW2mONQm0kYELc/ArKmxyX93AkMRhb5dw7xKFPSsRD1TFOVDBZZVwxF/pKnVM1CL80/6c7MattOkxqXBYARgvbA5GHllVltnzCCsqDSDsUAEOM4z1qY5myaLOl9X5RM9q46vb+JwbU7a72onk4UxH+4AAMtyhgbMuhOJZokgEDBpBIpGkTQ0JizrirmtmAsBB4I8JT6sFCwPjxBmPJwYl/UBlcy5DAvcMXGqFSLAZV0yeR6yUsD33T9DDX9qD7J1MgdI3Y9Opztc6P+L4RDPSAAA0lZImSFywdruUNaCtawACqSeIU3xRFsWnD6fUErF9KZimitqnTBNVkOSGdOkdSMff3sE3Rd1KD4erOa5jYkFrZKmcad++DtdlcBPFCDrTJUhhhT567MT3+gNnlOlo57XGtm7PPuY3u/oJP9LC54gCfFjuCTmw+cPCCyF/HBppCPR9z7Zy2mHx9+7A8ZAhwb6OdLBb3CT2Rte4okcmjZ44w0gDyOPm1THkG2ZHN8nk8P7fO3nBJ9EgvZF93vFI+Qro9y/iaxf5V13DPMMWrlUm46C0UQgqxr3ycGnNIsYnqyciD63rs2SRPSyQuqooXgnop8C7/n7S2SVAHXnATdwUy2gJqEMd12EG3vJykCI8QZi0eoFnbbZi/T1keFE+Xx9vqEUgFeBnLnfTtC+iFCOBXxigBaIn4MNjA0XtwCa5JcMC+KwYfBehk3fdyYTKE/KBFDx2rIaac/tHE9KrK/ud/V/dQJwgrCmuGPYejN3YwNbWYiyfff2W9kcgk5L9mUxNXR41LmPqdCMWtUowxC0phmh5vmIlVYcygFLa2is85swo9FZeeudEfZq5DDc4h/y1jhGcp7Dzl/wHYSL7LBCOyvRr16HRxwtSyVB8M74QkZ3V6d4R0CD4XFJOO3Wer7UaPjzw+2KX9/8fON6Hs3bqz27fn7b3FgYdZ932FmR0aD82qjb7fi2nwP1br67AfsXAX6zm98aaSsAjr/+HVMtKDKhNcHTP/8Rz/+M9qcYz28RvBu3MtQC8MH++XWPnP609+APtJ+1tj+7bWH1PXqK/719dDj3ddpGngMGZ4n+NwK+FE3nfiTCPwh4yxLG82E89m/r4OHOeBB1jJtqxVwnnC8LSIwXqARugmOdTBwlkzsVtx0OBzydnvDuzVucL2cwFTTnQ80RmVkwTwX3d3dgZlyWRekAyIKMug5cQDgtZxAnmVsEpfksOu/uf11sC/4U4/kduD7qQW35t5/RNuz1Tbx5fee3t9epgzZ8aNarfhd9+fduf2oEuisPvuvZzXNdcJKb92jzwy4hgIfiBuOzWQGeo/rI7h+o6g3Yc0QQkTAANAJ0P9rv92y7K03bH+yC9DKXuc45byb6JiGnAphSpz+T0YIa1glKPjIysbv8TzI63X38mMb1o+0bqP9LPXXtBVQpoN9YgAMsJaMgcksdoUZ0f4yKGp3vmwogJ+KugIuuBfAU7dY8hbnq25IoZsI1UcGZBG9KxQJgLoTLPOHdfMThMGEphMIW8RiKSlXyRelsJOGTCEgRX5lKic0plL5wA4M95zWuuGlaVPv9rd8iwPROXQwqqSf6PFmdLjqBL7MZ7KmnfxFCE0bFXaRU873wUqIiiPq21ZWXSSDp+5aW2v5PTnU3d5EATKbUMsTR4VSvMZlobUy067rJBucGUCzmKb4CNKMrDBZdn1DUSR9TKDY8BfraILWiEJvCV9fbU3y7SnttKyoVrWGcJ0MVpVja9mJ10yBAI3U68CjLuXuQlwSHfi3T3O5t/m2ntSvfHfsYDjoAcu4IStKG8I39U0OnXKV+vqIXHet02ycQaTFFqgnbvdZtawJG00hDVziszVILmy8y9ddq1M4aZ8UVQK7sYjPOqbLVolCHYO/EEb622fsVjlLKOu/VjOeABHzl95HDUnqv+NysmxhW3pf4wOHwIgBIJghIGX1TAsR0/Npm/N/NSu5qVfPY9p7x+yi+9/Tx/mdPfFaGc1iBDd6INJa0UZltUpA6TpHerd65ajpP/ay1yFnDwgZFcHwuwOFwVLhixrIsqpRCwah8GWmMCxheXplIjRRgRjN6wbB0kMyaPjb+G5ufJ6OKpqQkTc3oNY5jqfpkQ8gxicejer12eDxrsKjjtdSU04Q6zZimCVOtapS2gdWqxU6klgFXwXCESE9/KrHXBI98h+FjQemRyaQZUw6HA+b5gFqVZjG0xqYaxdUwrlUgzAjc1AjcFq11H7hFjFew9WIWEKxUCF/zyO4IpdPgAU+8ClUQ9RrZQOAIX/t8n/KtJXgEH0E+pB5VCedxHR4dzxkPw9KNw1vFv8/TFeTwtG9mPGcvNxBE4BpDhGHGz3DmJ3dw6UB3CJa6vfbo0Emz9qhRXZ3BeFksq01SOAc/xTEPKgTiYilJFYb1HKSKiARLBw50B8G+vDKMN83BaZtQzyZEjm86r+Dv8C3ryJYQxekxrk8oUPw3Fwds8XOWuG57KmqYEMFQtsDpgaf5Y1H6FhqO4J4Q0bJiq+A8oo+KOZyCnD+lFFXdo2N7an0fg647Em+iAMh2A9s+Ok/nC1cANazHQuRma5zkQl0Kc8Iww0XHVim9vHQD0tCj+FqPa0i+9z5Hon5OTPVTqIClgCYBLwU4CIAJcj4P72BuFuUa08hSRAcXUR6yUnKT2dDKyNaQKIHzkcxqpJ8mc4kuYvyQ8xmKK2opds4q3n/8iNPpBAIwLQWn6QyI4PFh0TXk7niWx3qzDWfdaamoA47jdStVFEYKgcIzPJoTmOcDiMjSIwPzfESZNApHSoOUgrU1KHiq85Ma5Urg2caM5bJA5AnTVMHtoDx/k+Bl5SSo9xMO8xHMaxi+yM83CNRWnfgKrLLVIZCdVzurYLC4y3uHT2ldQSlwuHTc0mvCa0ko0izupIYvvQf2HIfBNOAz8SWEvtfdYabLM3re0oYGqouDEJc7z+m39TM+rMAG8TkOvXLq2sDHDzfj8bc9ys4nAOCvKeMMQzXhRYLfcwOuryFAkUFjO24yWdsRpkii6cYryANQ3nanLqe5zUqTMHHI8MGE2/PuzFOgGXEwdYcwEUETpX8wuHKdhxhNop29IpNTnbfws+gE3PkC8pvdoMvJ6R8AmUHcxxiOZtDyJCutalSHZoVopnQvRBCTces8aWYZYtDRnr/omOvBzu/JeDmbS/AtQXf29zl/c3oxXhN4KvLoJ8lEt+BHCGq7JivbJsqze3ktMd6RSgG1gsoVjcX4BS0LNR8O4HVVRwkrZSGiGUSiTNfgRO3b0/coaPiWJqQMPlmHKjCjjzkyTeWA6VB7dj/Sd7rDoxSNnq8wnM0t4EoXgCNIwVdpYGM7E7Gj40Xwh/03UR2m7fXVmU7z0eV5Bof4mkAzTk6FMBFQ6D0W+WL4z3BlGsutNo7zxdfaQ2SBENfPDHC4o+dODPdVx7T5OzgtvjA2AXaNes+1baSuQA2POU06YKmvv63r3dYpJq5we6y/CN6JFVCwvavQvaz4JfhatnoNd3//FY///GeXU3ba1obxo82kg6CG1A/D1Xt/pv1M10/l2rdQ2ekrUY9Adxzt7PWOfLbXtvC1xZM/bQovAfIPNofnl5wgbg3jXQIhpm5I9+8rgI92Nt6Jnrft/gZPuXkf0OlcoYKVGSQMYi2V0qinVweAJowiWpKSqKC1FYf5gK+PX+HErBBQS1VmRwSHSeVgMl2E60IhotkXgeAplfd3OaXDaddNIAI6h5mQTTLRKOelALcF5LN4jVtvggDt/763nd8ERj/h7IeI/9zvGHFcD8rymwiu3880fPzsWRl/YLA/ON+fiSu/p/15BnTpQhiAgSn57i5fQr7OzENriLnbSfYC7sqd/T4DYAKIbr/XhdRiCkYHPm58fS9+DF9nBuk1fcXhEbJ6G5J+AVaLbHvj0ULxq/4edc3TL/6p4EOkcO/v+qy9w4kMvQAAIABJREFUEEHwFcsn6AHFB4C+oAvW/T1MwP/+pD5qlPdnd6Zb+Nlev3Xfree8bWNU957udaQIqtR7Ik0y7t2dILgXwqmICgsWRXVCw1vRWlBHISyR4p2wGONLUMGQuoYnjJndJIFAeJUq2jThQAW1au29+7s7zNMEloYmaxBIgNTIXLVGWVdyU/TMpYCaVUw3weKJGVKAd5bOxZUUmlbFCB1s30oFWFBLwdsP77F++WqRuKpUaZ8Z+LtG2xzmST2k6Q58bDh//op5mrBa5N66MqTdQYgwvSm4PKgn7xTbzMq02pqUaitlaXsZHgElVwdFQd3P5ggXkv4Xyhg3cCQC3YruWSE1GkUciXGKhY2T0YI1ECmQxTzt05sJmvKRLR1boQYWQpUplBaFGVIEzASqArRmHuMCiEYNTRBNs2f7rX6CRaMci9aioVpUwVlIIwyqRg71XXTCqcrOkoygXm/PlfDTNGHU8XRDlJ5vhoTifyTIHbvkKBKP2ILVmB0FdxWYZXzacLhXcvNk9MEsZGZzs9u9xriOtVVNxc7CQBHI2g063JopZTy9e39/h54CcANb6mH3SpJV93VZGWEEI58jBrj0ddqdq74w3U5w0T/uEFfA+ziBsR5OOgu25hKGDsm2lug71tkxoKiOa8uC0vUxi2E6o+ejUHxROj12GMg8WhhBEO/t897wY4TrDb4mvfqcOQlReOH4eqSzQz27hK97XxV0ngDZoGVz8z5BIPcmkP6Mn9kY64oeHQrff8F6sZrCh4q2cqQxJABznSMCZz0vYdhUnKcK2FL62uoUVGGmw1FjuzCjQRXo1fA8s2IzEUHhoiifCKVMiN2VPvyAVdtAppRiC76uLigxQukv0PMEjtrXuj/S77F3VVM4l0mjwEupqJVQVgJWish0qurAQabE9+BZQM8yFS1pAdJoGBaPVDWlrQl2RBohWGrF4XjE3d0dpnnWqFdoeva1rbhcLmh+5g1fsddkX/WfDkWjUsT4UrJIc150PyiitTIMG91f1x3Zw/mDtAtpT3I31ZV3niI/07GAX6WftRSjCWSGYT8T7jBVuoHSvTDQDSywWZDtIdk4xXgJXZtmEeYSf8No27ED3HXDn++Guz5vikPj4KcwntfAZ+pKeufTa61a036aME2TKm/N+WJ1fG/1iZtlEADU6cENTzBaWYoZBVijcCMa3MbbT66dlzDs6XkNraqHWdkRCLk/NAnU8RZUmeL43VeleOStONSRLZDTA8MRZVzPfpZtF9mHkvigTo5Rao19g1jJAQFYWgfCjazh45O4lDJ3AJEaH/BsExSLMFfnkwDxMxf8B6GS1dObaudpSPfbnVdaayBmrK6gdlqcKZeYc5kBl6cltp+ghpBiRoGCOs0oU8W6LljXlqbqvOMw/QEyxZVJRFF+yGufiwBYGRyFtLQQUmuEciC0U4PIAmkzyoFwBfXSHSwYgjJXe9+EUJqn9Ts9PfUxQ2Ho7du3IAK+fFpQnCe06EEAFr3IVqJCy0ap5ZtQaMJhvsPSLgARDm/f4k4E0+GIh8dHzPOMdVmQWyklol/YZtSd0iQygzg+uXY4snNhFE7Ayo+z0Rkiw7WmnBMGVzPgkMJHnSqksclh2muThnVVJzXIijIV8MnxKYMbYTpo2vp2YjydngCcUIiw/PLGnC0KCgHH93cotWBdV8yHhsPxHkcI1sMR67ri8ekRtU4aqbMsuJBlEOB+fnM6dfjpTPWxg6+xX434Go8n/XlxnlkgWDWFNxSnuSnByxEx1PgWdpd8jp1fErZyWv6D/iGDMX1Q9unZeAqvfsMp08fOj2b+cNcokc4uACvJ9O2tv0diCAkd5hduvmUcWIzY2nzduc378gUl40/h+MCdPgrK3DN8qXOX0k2Xgxs9gp9GProAmOk96q9VHT0egPmXSR0uS18XGK/EhufEhlys/IXTQ1IvM+Oj0+LY+zpdLkrrIEZ/3IEbRvsAl2k8S42vKYsMZXCiZqrRneJ4mgVNFjRerc55M0cPhcI6acY1XsXqtk5YaIE7ETAEOEAdAwBgAvjMIZ8lTnTY/w6s/b58mXag2dcTcoTAM4sY7xe3irNAnYaRGi2U4F1MsD0oLNOiYzpfII1RIagglMOEKkWdP6tma1pWdTJYoY4I3Jp2RYRqjpyoNQ02NhVOU5g1OwjMsa3WGk5uIurU3swQM80F9/OdZreIaPQu4yjfsCrfxDCcXVEPM6Z5xsqM5bzYapLJ9obH9o65y4u+cFluk/5B3+/OHHZuNv11ua7vbw6qAOyMSnzFBcAbFEwgCBEYjyhUARF8LVouweqP2DNjFPown2/EUpRgBv6ab3rYP3bIFXTek1zGcxybeGBgcy5sIIRu1LvVfuWPuNBv6YqEsfG/+Bf8o3zCLz4Z6uP6CuAdq4Hye+qf+zs88nd7zovNie2vv+K9D8BwVcNvWP+hcy1S0ND1Bi+Ny3UMgJPo/n7P9roXkXyjM0cb/f8bW0tnD647/SEDldGLCQp3HxynQ3W23xtBv/cYpQ8/MOKXX/TathmEw5PbTRyynzN7vTOauKeychj6X/IBEOD/FM30+547jH4m4ANpNtyJtB8/c6F/DQm6D5tEsDY9XGe5gEA4ug6lAhDlKxoziIrSVibV7zBZ9iQEv+glRECCuUxoLDjME1AKTqeTkUudbGMt8QRRGjxPE2YQTuez8fkqfRXSOdTVHDQNv4SDbVG65EIblRBtOi12HEXX5+xntpuiXmqKU3j3DL7uHYYzMs72vxs8HvhSEh7PIzTZ0+Vk19G7Q7B/d170+zjn3v5sI/iPtH+bGugjYGYiT34pfZR9iHc+6YqpGpmFHLm+6fpm+5kg9C19vbm6ubP6wP64CcAkfwPTvwYxEEA3ANmd+Xi5nIBhbT7H4fe3mmiIxw1hvzae/0jbPv+aXfq+t5+c2baHGBwGcAHwQJr++2K1JEHAglAVd0QIxNVO/rTdS9E0UdQRXCi1CiDCYLa6V61p5IOnPPN1dQbQlKzBjCRGMYkeVvcSYVgqAqv63AkVzDjgAjvzA6Z3b7F8/hoR6dMvE4QFl09fMP/9Y3hxErrCVD2bVdIgVKx4xPokoDKhQiJbgqCg58TS1fL0mEICYlt/jywKhku+FQR2G/MYtRMso+MEW0A+syr9SEAzQZpHBSkRZawg9BTifdVTqrHMtLMAhTX9OimEVbHUeZIVSKLMBNKeo3d11ZyIvmbyG+I/jjz95tqSTa+uvAtBlAARMyjABcoJMOVxN0Ig/e5C9Cgkb+dGskP2BeHoBAAyIZR8lM6DR4SFmdqFSEk0AK6+8gVWpbJHj4XiMo30OUaC0/7FWvk8yJ7dzNOdGlyhq2vqzg59lBlBD9GaPrf41kd7paR2uM5rDEBOAN2P47qGpWD/0LUdN26m7YcbazYizZebiDoC2VkVMXiK9ejrElGZBg09cgcBF9sTo8K2e89SLFinbbAUmDonmlVpLeugdo7GAnW6WdsV2louF1Q3wMT53vAkG3xkbzV4KCZQmOOJCApJVw4XUbxia5KP/aBUhC6ij2V3I9LlwTFG+qwCL4hFwdn+CBdLhd5hXEqxetRWkkQkHDuIuxMPfE+RM+xYbVhRo7Yefa/3WVBII5NLLZinCYfDEXWyOrYefWxGYrGU4z7Wxq3XmeRxnfJ65Sy2vgnbO/8ogWNPmNulA4TAI9cGbdj39NlwdOaXHSd5pLmfowwzyq5TwF6y93XlazoNZC8WVqcVAWG7dKODmDsE2L9CXWAsQBF1ytBQU3UEk9Jrv+bl6kK6Gs+1j57uNGa3gxgDRuOC9UbqvOCjDlxCfSZ6bCgdt3HCkSFgz6hkt9+CrrwbW7WLK53D6UrcINfpUni453GNgJGuI60VhmvOOXcj4CitZAnG171Qj3RwxUApqvxxg2goEq33zdvRMUZqxt96Le9u3N80pxk3FjdgIR/+zhj0P+s4Aj939dB3xBWwU6FIZDsYEZ3vkAVEh1gbh4nO2+y1PreCAyhSyPczq+dYDc/ruqIUhnBBPZ8wTVWdLCGYjke0y0Vr8toe1arOAMuyaBQiM453d2BuuGyi6YlGZ8i875JvgsNep+0iDRMmeKpfd5zyzaAmkElwmI9Dto688hCY/MSamjLmz2A+A6KyijbGygxpdn7PBfN8QCmMWgvu7uYow6MOPARusHcLaq3g1lBrwbp2PBUR5wY77qwKSStxBbKvjHIzBkCK9+nRrYhUnA6b7njt+wDqPKvzmhRnQK73KmWg8GPgsC2+3ru7kDbthpTykvHcx/yzqGru6+V+FXkpuXEYBdwZIBvrIuIHaYu9j4w3kc4ibuiiTMYXCPirAL8S6jvovpZOY9T4aRJQQRqPyzGIv24EDPZWgFIpkBv7tMKVgkKW2l8a7cSXxf6kLAqdJ9D+Ot8dMCMq70v/ak59rHcTRfkJd8zzl8nF+jyMfLLjfPUJ0sm+Bn52RRkCgDsAZzsftr93dveTQXjwAIm8CLpznRPBDAZ2ZNXRRh0Tayvgamn4a1UHWRHINIUDYDNcKH1pR5rjTNewJOMKdPjvp5dIHVOn6ZAMOJY9oKkzvtASRl7BCioMYgZVgBrUGdZ5NZA5nzq6O6oRZ2cjgh94Bu8Ncq/3eXWP/56wkvETHfbHM0dEkWFqD0i+Bfds+x762TOA7nx6rj3fh91z/dBtxob6h+BQaPvbdRNSmtwAfN3wIv8oGlT1iTSXqdvKctOgsNv9f28L58M0X4Ur+z1d88/uDviswfiW4WxnXX8anbrxyo5Dv+9N79G3NuUss761VahR+bWOAK81LAZ928Fb39J+JKBzj54JesaE18zZyw8wnofjBZ/HY2QZAz+ZqPkFmgGg5z3bIu7NB9N9UHEHe5dH9R4BLJugy3rmgEqq82AquKvVsjV5MF5/DXOXFSkEnjHgJNbM5Me1tQ6rZmfQ0Tj+T25pN5iv+A3dGVhp0g2ecXvhB+DpZ53Xl9rI+6AfBBpu6h/pWhbo+g/D2Jv9G9ptlvvfpv3bGNB/ansFcg2PZBcaLQ1aKWX3RH0rHAaOcAHW+hiiH/fGmZCWAHgkNaL/F2vE8ydKaVbRcVCBRpbDEDZTJJ7bjF+/Z5WDqgB8XNsxydBD75XwRoDHIaIq/90u4ots3nDtmofz0TkS0r89qsL3c8djC1p3/EzqsXqC4N4ijj1q1vt3XJWREm3+5d9nu1ag0XE+xktc1yuXYojOa2qSK1mpCymiKWbduNCjDrogHMIwBEchPBGbwKjvu7f0VkRQI4OH90K9CvN2MRFg9Ua9rjTRPYQfcfzwHhBNawtLozi/I4AfwO29KcceFfZqBdE7VAIIv2HFAohGtRQSvH/zAZ8evqBCsIjXpK4miKnnfLEUd37+osYk+fBVyGlbONoQ4yFwd6eNu33dGJpOng7F3Ok0rU052IOrK+Nn7WTSRdWaeAKRVbPZWXJY3RfLaiBFIz1FIKRRIjUZIvwTs8D0cjqeGHwWCio8RR+DMdGMUjSNpRBhnjW1rZ8LXV+LyCdgmmYdjzsEmKK6lKqwYwK/p6AN4xn5UufFjivop+IyCvXD+ktXW1LItfH0YJRyZZo9R20CNR03CKgWseRphQpZMgHy/iytuyko9Iqd0xQFWKigQSKauxiDOpEqYjy1oNfoXA0+MxLOigsispBvX3M3PDm27YqTiI4Pw6Od96QIyKvn976GKl0LWfmZ+WoOfosbPzL+pc3jTs+GG+3r1kgtVssvlN0vkYfN2CM7jKerd8bbcGFf+43x2PrpGRN23jsQDAkmlcPI1N81VY3GaZctJuqLJwDYaqA7nVBjEENktYjLpGyFpm6MYZiSPdKHW6pa73+7RuFIAI9q01TyJD2KuXd9/Zmsnobk7l0gYR5SY8b48qL0w5ZS+Frpg7ZAeNJ/BWir4igWRltZz3EENWlEaq9Pr/seXYoMffs+EUgN5bWiTBOmWlDrhMM8YZoVxrmtWMQj+WFGpJRqPxkcbiomKLbGQe1qR/o2pQMxdEfj5623p79n6GN7zvNhTZcGJqUbcUkMb6G7wfQo4Dx4x0FkMAVH+fpPrMMwAl0PvQ+njOsYQ3aXs5HRkg3hHri9HTTneHjgo0gj1DNOEOM3aqlKc22f3UhLgCkYnP/ZvMcu9EjSrjAXALkenNj9biQj46mA7pjThWLPYoB4Lr9zcJrcW1+//wYJyKnaHabFoiKz41ZbNfK8VIJIuYYJJNyAfvR7lgjdy+BhzEkGIEsdvBh9pY5bvaMCzYhkuJktO4evZeMu6/R5+0DyX+cRZFgO9+YHCIWqZfSZYIyqrVM3EInAIirNaOP9xnqlz56aHTSwQeLq2HTsQ4VEhHrQWMN2PgE44nh/h8u6YKpTPwtOzy4CHJ2/ppjTurpRPPODfkVwenqCG+krDgDa1WFnMNCAtq7gUsBUUOqCw+WCUyHM04yJplj0WEtfg/AkGnYn8Sxpn5MBi8ZfQaVgqhMu66LnuBZQ6wa8KgDhAKHVDJid7nDwYOqEI2cB7g2HeUYUQjhEiTRANNLVco9AcIHF66C1BdwqmBnlTODWcLy7x/E4o/GKOh/x5v4NDocjRBi1iKXcLyrPTBVrW5WHxtqV+cqhdvjORESAVGQ32nZnnX+5rcdneBhP8OqCSPsceyWwdJoZv0gvbeF8ktP87XuC9+zP9jEkvmx4Nu/46GQx9DvMZ3+eHc63iODWfXvv2vs8PlEtnfr6la3cg8lbdiuL2DdfN6V30jhwvv6GODNEhOXhq53LN2musru/YnDT8BUiR51zymCW2K60vXbWWGubh+LbyiMoGpbAyV3f0R0klK/vY/HvmVehUlACJ6LLC4VUriqEImoEBgiyLlAHSE70LqgmqBBaW42uWqei+yy8t4sEHARy9uNDakhvM4g4MjAE6BWfhzM0dq58Q9PEdUx3Oi5nhOgI8gwwAsjJtBL3pFkWnK77IroTpq8/jjpstmwnrRpvv0KkaKp+k1FbqyEf1FKAaepYlQhUq+qIxOFP59Adr21ONhaiNM9E+4vhTQMANZALcGorjrZOvLAZzTUrYzV+nB32qViKYo12RIVlklpAcKccQTGc6fuRsAY04YgMPHX+2c9CJu4LbjVdg9FR3CIu/cXpkG1f1yCRjSPoMHAbIW1aP/l/XNsjCbL5+y19TaI6FI+wfdhh9RdSI/m2RvO2fSHg7/ILLvIJJF4cVNt7Ge/7lrbF4QWvmzOneyXd+6P1yr858vyPajuEMF/yc/IbgP+Fj2j4bVi/52p8/3dsH519kW6T8am9l9fP8yXnD4eHw9/+huVf/wqD+yQyyN5U9Hz5728FEZgIZBlCW4Hi6anUjpugadU1aZPygVT0c5TasB4qAOaGWiY8Xc4qhpEGILimhQAsrYEXld2al1ECogyrjkVLI5HLdSKRkbDCs8cFgxH4Pc5eFyCHiQYb6SIE9v/+Hu2PxNv+RonJZj45y7oyZMe7btRlNIzr+j/k2H53m35GNMuPeOv8ac09LQywOvOjPw8K3RfaXy0FwRYpPtc8An0lq+UCRbLbvgCApKDSBzR8huDT7jsEmrIm/0BCm8j0zf0YmQ1vLzFPf0a7xUwSNAW7t6ed+Z6NefZ+TLQLIkuBqPq7LNYW9xBcnMjA9SMdgxUQ7kjrvU5UsJKmXq0pxTa3bjwQY/QLFTWCiwDU0xZCgCdL2UtAYNuAraA2LglLn5Q3dpNLXyg1JAKNvwJ8BH99BL+fwKVC8AEsKwo/gsovkIc3qOWkSusyo7whyOcZUeCcBZM0PJweMJWqtVhIoBNSdUQITbZU7lEXa4KU3tv/t3ees+D4wsmSIDT+aIrOOPT7yARtQgXJaDALZmAFVM/YkdOVDCibAxtRmhIGezdS5ai/rIBBui5271Dz3JikMeK5p1zzUUn0Ka75gJkUou9MuGOFxA0FPiCVyrOSOc/9luA5zCu4qet7MoNFQLynYFFF/0wRZeNRdQHLAhQRrAKEC4PVNAZUyRVGOjtn4uvGY7rqrjDvG9iHm9ctYcg0Hzcws++HpAhOgSp1c++5nvlmbbtydLPGaX2218e17fC5Rxe22RT8me4/mk3imYBcvWK481vboExNZzQyciBMxQ7CelvUA+QuNJBofWOSmEHQtICvLH53lNkN9mlNB4cSHphWNfaO1D1WoWipgITIhsZWMsQNbe7JQZZrM5W0ikGKqQMEBDCr0dxKlPhWarTdjXW2dzRmq3+1c4/9n2x5c01UnyuJl/uQ9IReZyGrwyqWoh5hcETptA8iYZMVEbQmqFXpbYbKgA2HM6tlXItGTnp97GmeME0zqkVTsoiW0BA1qHrEuSSP6yHbi71NQUqjoXqE7ogPtut1rciU7W2vaGOqyhu3XJE7X6sBXLJxdjNqj4QbJxHm0CsUvcX312OiiMrstM6uOx7cnJFMdLZCoKc+z9HnZH0VuFOiGjs0XbUa/ZplPtBz1cvW+Mz8TIi9s9dqc86EQ/LI48rrk7/rXOwMSIfbkvbHj7bzaw77g1HZ5r5l1eJVHSFGpxnerg1XiZ7Gfkq609aFBY32EogmGAC6o6o5ajIBAytNPgqdU+ZRAEQK+kJaoqZaZLVmMOqOA5Ha2iPwDEcMDsibdclz95qtPZ1diXe68cZpfeyBcD8r4wbHAvhbIqKJrrOZjI93/uGKskYJEMFqqYhPj082fhid2tB4AZbzCQBQzYly76367YImBUXM0VIExKwG88YQYjSeoSVsLNK7God3FEzzrA4WIoErgY4L1rZCGuN4vAdzw3K+XI0gg6vjxq491GscNEWvu5MdcwM1ghq5i+G1GQWE+b6GcQYJZ/SU0k4A7bdZIJNAplkzbZ0Zau8RVBKshcH8BcwLBEXnJoJpngA5gkizbc3TjForIITzsvRawrZhpUwoVpKJYr5pa5xPDzpGuIKVDYwTFYhwcqyh9ATsN02Pk/vq9LrjGIF02JW+5lsZxWnPNitOpwcde9wibrtXB/51+9P1E0P0ze5bfr+mvOUGf2VcbnTEo3vZSwj4ujquNZAXSVH/JACeDEpzlFHnd5SiPALyN2Q87bXBQ47zUSrC0HPqNdOooFYLqGBP++/ryoHH/YUhH1KPbIoxQ2nbdp8Gp7FSNQJNgLXayIxGi6dbt8VV2u7l5YA6H5RH86AGIvP6d7rdeX2yjB5yoBhrgaYcBxWQtOAns1f9SFcpgIow/s07H89kWn5Md96ROjtZd1kO8IyFPbo3OdMBIBxVnmVBa6ul1l8A0dTp0lpPR231xmNU9hskkqQjgC3e1R0MHdc4PVIDizvNGxCUVOpDOj4SC9xpqe9YU6evrlc0XkpLCCGsLgRzfHdeX9JeZB5jF0ds8F7CRWMzPmEYo153PU84h9p6HBNdd1jL65R1Mi67Y49v/pOar8yPjSbTLIRP180+E11/CTH/s3zC+8Rv+yM/Mub83HOvD3xh37+QGiuz7vqvsYt/bPsEnfdH9Pn/H/yGvyEkmV2e9X9KY/wxTgGXf/0LvxWFOefUB3VMkv3c6RW0kTfTLiiuJgvwocBDIQeI2geIOu6G8xcEk4kBplVpDDSQrhBpQJ12Es82bloKMDLnlmC5xeUlAojTUMXHr0Z5d769lTXsqt3Yl85njNev+ri1rz9w0H9/G+oNHjozgz4O5x9CJ/K7TPl/RPvLRKCHQusPMsbHW1zZsc8t3XiYrqWzncMLOIAKwLCITVeCjYwi7fZ5u2XjT1wbhngLC/TTQugR6L+Z1PtGnMBpFGcndB8gEBz/fsTafsXlt/+7P198xkrjmyTVJhtRG8U/L5nlNfseyJcms0LPkdyX4Gb8XXavXrfBiyk13u6VEE7EGqGdNH73UvBk0icBeCvqUXuG9J3YnZb++h7vAAAVE+5B+IwvOBJhIVfgqbqkUsEK0pLLReswllq1VohSNl3bpGDWOq9Fmb0CuH8sc4jBV+eSoM4BbyOPsf51wUG/GetvP4toRW8Cg9sj5EGVbfcfJzwBaA+C6YMLPPcmIK0gOln0xQTQGXwRzPMEFFIPeGZMQlj9TLF6s00QTZfIjGlyZVk2GMEiyQRan28UtK4aJTUHbQTe/NwO7grhw+Hlop7sKgCWZPDRfOEyNxTMEIsCqtMMXhbQnFh1AVSZRVo/qwCNL6BScDzcgy8EFEZh5+S3sKqeeyRqCCb7F0KbMUmoXVHtAiUVaM3HTHWhKYoFhGmuAFkkgACedlCoIaAjGCQbmwvhwz7o9XLv7y6Qk0peyuTMIOkKVQJ6DVpJ650xThJU/TcX6CTdw2AtXDYJWuOIVCOzgIiNufg7BZHymduKlVet1Sec6gC7obifJVUmpZkTIoV0ePQbs9qGyEZ/GnDjc0T/2fnFVYQbvPN9MuNoYU/JGD+Ot4dBJj7qiJxuqPvPIfYnBh+bRFFHhwYLbmfiVCErSRDIY0IHwXxGd6aGG/Q9FMpJmHdjSafoLkjAwdVfmfrx/dReWiiXyHtQpZf4G/4fe2+2JjeOJGr+BtA9Qlsqq/qc93+6mZvpriyt4QsBmwtbANI9QlIqs5buhr5QhNNJEIvB9qVPYQ6dejygKOva0FWRY0VXQRbf3zWiprcG3+Jr1X1/D4cylDASRFSgqdndCtM5k5EBYlrPUGSGqsccqmwNumgqMDf7cLe580fvUKrr4QbfkuupJB5uuY5xpm1xR5SQPRn1pYepQBNsRAp1KZSrsJTKpTWjk+L11VWtTjwy7fFQWAV4SnH6WQrLcnQDutV3PCwHlsNCqWYsygj/mG83o1BPI9oWPgIeX+Q/jHlidirA33Gf23yuk13T230LhWQ6Ogbc7H9UJhwUuCw/5QsCr95oySZjVGAsBavFns/dn99AAXM2BYwm+J9z1NtmDTZ8XAiH+3XyHwlyLqlMoJgC3aJmbazV97iIsLoD3OCXxthNAZwLz6gNHOOfJhdr6saATbk5gQxGAAAgAElEQVSI7hEuEjzDPHbrvzgeLVLny36OJddWw7nRHRCCPyol8Efm5cmli/1K+qOD38vtcD7CYN8mp5uJ7tugR/O+Rc16VYyP0WAJgg+N/TQuNvUezm8cYi6Tkn/Pn6XRl3Decfwg5CzjrKkqVMUsSDYVg43iEaRiDjuIRwd2N0y4EqKPPdexcPFf8ktJS2XLmwRuyZrmblTDHaP6pVOOZTJoHMd+EPt7ydcOp1GD90iL/HIzbHs5fUWcdojgvCPmjIAQSi1V5er1zNvakiYdDw9ot1IjQ7G3RYZ7uevp6atFO2f6Z3tvOFwG/zGcpQJf2Z7WyHzkdKSWilTjU1GoHGzkcgUOAx0EfyZqRi2HE8siMHC8tOZROiPzS63FDZ5KaZ2+LtTjI2tbnQ7B6XTi+HDk1etXPDw8WkRwb3bGEU+vL77eBbhafeDAUzpwac8ls3VWDfiVzdru97MzRSiTyzb62p1ynQHVj3boT9JZ3nFIBiZEH8GLxvHqg24zv2WiUTNemL+f55EQLQ/AZXLG2MH0MzqWrG19j3bcvvDFNviredzxnfXXvoxorGFE1EFfk652XwvnJf0Madc0FiJYmRJRKq9RlKZfEZweEk4V87mSLHnV9Svt0wMqyuFdoes4w+HUX5JuFisNVxcy3bhYdrwVl1scT1vNa+PHSmRa0pl2DZ4/DcIBgImDNdfJzoNaBrAilDZtWK5RrI/xYGVZct1UzKheqHSP1C4ewd7c+Wm2PgSfoxPeXRZbg/N1MtbPuPxGB6A5drv30a7FR3eGC/YgyVoYO2J+ETSgEAnFMHDxiPx4nZ234sbkOH+9H+j9QFsviMJ1Nb4lDnzg5iKCloK4Q004gHcvU7Fh/lQh69xO+ANGOSXC4GJG8Colh2rR7kJblaoHlKvtXdCUWFrnj8rBzJJlvSLyQD2oq3067XKGeqCI7e0Nf5s8xvb65j41p/jYiv0+xvPBswbdSx+RoMlGLnI7AzxE3oJahoivEijUCMqPGsvvovNppD+Otfad6Ob5uc+f6TdIQazNvg76nHpdMCPki2vjX33yPsOQGN0ujMCwH2kxhoiST3Zgukem3y2e8fHHPN7pH5NK/mcj2P+R7SMjjbtg0efvuU3n/u80p2+1vzruW7H5/dnG808z8DFgLXDRpqnypchN9Lk9vr0gRXiQkqUE4xWKq5LdwG4BO+ZYqbis53zC2oSrZ2+KYD8QDnUBgb6eST2z/5Slpuya3Ioric1hrDv9r2RFJf8ueQbnW4y3mYM2xbsa85k5st2C3PJv37mXcvPgfTx8jz/8s9qNg+r4Ipibl5+deMCb9izP8z+n/VQE+r9l5Lm3YOgMU7jnYqSjDuHuBTC3ZzUPceqI8gZS4R1iqHalFvmHHZ5vtRjHk883otGFrQfdjKu1K0utXNimtZlE2O9EELews1/Cb93/r9IefWyPTOkWvT2J8krF6pMjfPXPU4Y03lA4PUPYxHODGbNtaTkvGM4qmTbNPLiKXaTWhbpYrdZKoVb38AJMieEppHs3wbYrRRu9FUpvHj2nSBdLwyXzuCyNuwkQE0M84ZFUigNfgYcJguK7Dnz+26es8t0+dVg+U5YDUhfqr285vC1wrtSlImJ1ZvFzK71AaxxUkdZoPSJ+BcuGvRNKZIxOkEGUw+ONmMPLBGFPdtOAOTkYjHe6MtMVXHJ0ZZiCsBCG2NS2O9Oick1lsSDUwwP9erEUcru5EMrHKW9POVRYhVIWIkW/ukK7+7oMQ+34sXuL/wxle/AnwaiEMUhSGRYKTHs+xzYrzhNG9gYOGUognXZMYg9DyMSy1J2iTw30u9ud8d34O4RBV7GkVDgJxb6mXaGrReToSelVM6oxDNOmt+rZd7PUDqiXJIhI5kir2dtKixrJ01js3Z1RRmEozcNBZzIPbqa4PXc2s03d3LGIds8uTeFsXN9c3yHgG+PI7sbt8/buOd7rftT5rUAOA75+GNXr3T+3N+j85xxhPhj5OEvx+o4rsiZjEjqMLjc4T+OsSPYpUXd3xjmI11dsieczCidq3F4N1/VrpKQk70uDQ8zXo2+EiGiOB8ZC2nVNIt0xY5tl7UiV1mY+YUSPVF2bVO464clneMioN5z9MUXE5vkcbx4ezZqKqrG2ukXLqubIMxlCRUwALMVwX62mOjkWaM2FqI6V0rEdoeXYZn6NyXhaWJbFavfWhVotnTvFFMRdFW2dta2s68rqtGi9E4EeM45x7JZ8eyY09mDMd3Pjc+0HpLN7zoHiwmYKTtsnjB6kQdKfkFkQ3++p8TA6GdXCcGlnybM+BGxtpjn1Nb0jQVudP8H7SZ5pvyZbBkamvrOurIgZQAsuqE9OYjHf4hWNa/UyBs2V0PYzojsVy+k6RHUzZMS59U3a8VU6/xbZwGMK/xrvY/swkzOSR2SVUG47behR8gOmsgojgmxe/6TcSVLiiw1FGNgy6VLg1HhEp/fsAVO3sDrhhpl765g8Eilat/Gzfe6NKmIpyWHUq9fpWETEueDZRgbeUa/np7371m8GN/Jz+npJcb67hhHd4rl7GNBV6drorRmfOdHggefY4AaUVMQHTxmAsUWZwfwcNmNUhaVAfXS+tgjrk7IveQMTzu02ztz7xAszjR8EdIZJ1QW00HWFXggn3OY8UBiz6nLgel2p5wufPn/ifDlzPFrdou610rWrG7aUx+Mj67pyupz4+uXTGIM6DU0Bajsro4EBR4rVaDT6VybnByRq7i4W/ejd1ONxE0FtzhmdyDIhiKWR7IBWx2Wd0kvyd7Wakq9Wk12UlUUF5QHqgfPlwuVyzTG2deV8OlOK0ZnDoVFL4doabV1Zr1ejLetKa6tF90f5K59QOi/f4AWmdPg7WANC2RhOPYM/ut/y+Q1dc97HYVSmzFSjhNlzRCnuG/LLHt4GrI8rd3oBvSJ3Mr/t9Tg3cP4HtMJrzBXh9EPPBe0S7bkPnhIufzQHbbi69WZ77U61/XNneVs2uKQ4/pj52gH6dr0DRUM31eil2jlpnRbZhrDyYIrhU3FHlHCgCZpiaV01jaxdexrvRXFnKmvBnwafwTS/lAENkMb3zo+J2rntYvxrR8czYOXrILMPWa1v66NoZI3ptG4OQ6qmTyhLRZoMuhsjneAyhxlUc+JjU3KQraNC6AesHcd0sn/G9zvebfNRGYfb6WvgJ1ynmFlWyoTvgnB0K6ehekB7Ye1qhKpekv4Hru46yvyFvuDuUXFeomYwx6ALlmZdTFYWRTxlfDgDzc7kS31wuWeS9yc+XLHMINkya5DBSNFi0Y3Jj8Y+aOIz9nhvu6GAG1qfmWe0gLfcIHRTqi127cFx8inmhMlDQ88wiEzg0Ty/s+yTOHHLxn5v+wFxYLQ/Di3u+rSOZ/3AjOXBxhvppl+iGs+1NCQy1Pl/VJTgPJaQDuLa3kgenz/Jjo38H9DeMtZnFnPn9fqwW68fqYf+r9gEc6L4cMOn/2PaO4WDwiXWcJYtN4hjSOrz9biqXWnV9EhLCfovLHmv4ymM4RzOm8145F5oTKXrQo/iz1uA1QNfzk+JL0VgWSzELh28Z1lQSZphqN2i4xUPfHGFwMaZ/xnEN1PlsT7x3Xg+H/8RmPxOHP2vBuYZlJO6tNAxxHrHd9uRJ0c56Sn+p7Wfoi36b71wE7AwHSmZmN/vOg1zhMXUErY6cbhDcNlqCTX7GX19+92BkOboyB9jloZAln1aT5trQ5gWulhEJW0wJ5mSXIfRPfl8yKc/OhfxLhC1f1OIGIIwyCtf7s79WzML8XDPku393vZI4N7V55FcRI8UGemqTk5Mor1WmWq3K0+Twl7x9O7O5L2WW6O7xKqKRZwLZpy/huAhZgCvYo4fpRQOZbFohVo95Z9QS6WGcg8HMUJAN0NhCJWlF7p0pBekCY1mBp/eOXY4SedRDTaeRDNdvQB0ePJlfj0J/Ao8DmrNgkWb+0LmbimRatxTORZl/fyVpS4sB3MIMOHZI2y6EWpFuGo35SpK66QHfBg9r6t5wh0Oi+/GeG8Q3CHDuyCsk5C0A7uQ6UM4DaX1OMfT2dWIGPMzdVF4rJ7mE5TG5WsDEQ4PxeXCBdXVBHugXaLGJ/SLMQzliAttSumKlA66AML59JUiQuVAk7OlTo6am9qR3tHWETFlcTkeOBwOvH73ls+fPrPIUN5kNFkC/4DQta2UXliWipTCtV8xBYjdYSmbJ5W5SqZ/FwnakaCQMJLGyhBKdTrXIVzGJWIdZ2MbybUPb/FJCN0o6cbLUwWjgvYrSkVrp50bjWY1bhFj1kRYr8raolIbU8RdKKSHYbxp36R1TyNoGBr8TIejg4iYo5VGTd1t+tlZSZPOWznHEaGVBjj/fmsAZ/uZ7ed8ns0juw3bXd+1ZymYHb6cs+A0QyVTiWeMSrqb3unkRQ739vzO87PIs4GrAiZhNlxMyng01zm3zdf04fgIwOV6nvpXuDT0YdkaZf255ShmfBDuKNzw6CJyr6NVV4hlxL6TngITXJDRRT5KBLF0oEUzqqT1hpRKl27Gppyjt9iTwImB56YteUnZHmMZuDaO8DRXDQOoukCkXjrBzkIo6qOVWTAs5jQWzL3VIBbqslja+LrQWkOkUooNRIph7jVI9h4fMDgJkUiZWzZ9Lwejsa1ZVo3eGtfVjByZirjPeGD0LbjznIy9QWaVIpt7h3PSzbHLNU78EYP/jjbvSTyTxodYTzwV9mZ0/ilSZcfV5Ie2bwn8bOdLoE3G8zBgxv9RegS94Ymcc5nSf+LE3sepBS1BGyZBOj5Of6fR2AVFIdLH4R7uNeEp1wrnueuCqlKKRbWukWKZIdwn2t1rPWdl/IRLRrTZvIeBGGbZZPCU8ZzfGeg0px3SQC2D14ssMykVA9om+JwAqLXm622GwzAOB6wEXJdSfNzbcxopqoeN4R5gxvkfcBw+YHNZiIHLhoFln1h8CPiTwiZq+fle9O6RhN1oce+dFs6XbdBvYryeMSOwVYwyyZcbBCIC3SIYA6KTSOS4RUxeC4V+D+Q4G41mPkYVvVw2K7ZfRUEoD2Peda+tnY1LU1seHrLDBFGHt8fXbzh9/TLxFQNekm8QKDxQfA5VjwbH/Ypopce6imTpiut1NXmlCr03Syns/a7rmg6yUVdRBB6OD5zWDtpQqVQV1rUnnMAlFXrBK27FR8PFxnt2pCwGk15LuiwCstDWFVRY5DAtBhk9ubZmUfoY3hIhYai3nvJSOFxJrUYr6uIGPJNXLifjL6TAel3ppxW9KtcvK6fHE68eX/H4/pFSqxk1W2Ndnb60lbY2Xzt3/dIgZOL1oSf+ZQaawAtO03WyuAvmlBCIRLzP0I+EYnOGqRSi9jCkDIN98Oo7WSqMqoORn+UtHXhw/+j0vn270X4EbtTJKOd3zJ9v+tnLJNMb5pfH15VH6utK/xwA+QrlKe/Zk7G41vyew5s3CLB+bPCLRXCpRCaRcTCNz9KUC9fWCIei8kY4f/406HkOVXM/D/Ia5SkdBjfchiq8Mb7IoneL8Zmi4ye1Q4b3usszImLZheLsleI0xWYbcmoEnETZ8OJ708NRuwyl+Gax0Al2g7aq+xmIlSfzm4XhYGq0vKSTU9B9sLNba6WVznptiXNKqe7MMLKZDbBUaIocrbhL6vES7GQ37uAvgmM6sulQxM6eKBwFVpADg99PtOvr42hJPXpCjoxztyq04ZxnDoCeDeSVjaufGqKVppbCvl2u9N6pxeYuVRC5pNNFX9uNc4JkEIatI0wlVCacU8QcJop0kOp7bbLLIoWFg+938GOd7g5ew7Dsu+r9ds5wfqAcBD0DXJAV5HCk0anHR8PHp5Nl15EChw6nQW9jWTWZktHmKOV7mCF4jJlRS9wWfB+gXXlwB4/kfTFHT3Pu6gEcCesDh29fPhvP4/dzauHcI7ao+ZttfjA/D7z8M+2N3om+7piTqmKZJG6/TiP43QjliUV7bniRRj1YyMaoh77vM4z1z0WJz5JErMh86zyc/23WCvD6P/4Px8cHPvy//w9/gSyVif+ea5//8m+8gAFXjTGvmTR8r1PAs/D+nfdWhatf+zx8txH1uudVNtHnArxSeNohlJmGhnMSDEOh6U46qwoinSrucNVNd2POW15GY1LWhC3h8+lEWxtLLVBgUeOLazX9amttGovbRlQz4DBYy2tf03l9ztZi51GnbGuDJ7KtmjL/zPN22Tzx+G5N9k33X+okg39H+977Ns/Ijg//jjbrhvfvD5qmOx2jsf2uz+DWcL7VG71AlP4HtH+ZFO7/6BZAEqAUKY9UNL3bXwLWe8LRczfdRvr8PMX4rvd/Zy+vdHiMzXxUEDxDoZaYRRAuf79gSVo+DVbLH+wYMr9VgN6O+zlG9T4x+XmG7g9pOyK0H1FEZ99r4ZUaz6bSzw00kkgrxKCxXpfYI/8+/l6kusHNa7V6jdbuQmLxOpBVh/FmpNG1KHOZ0i4UjyJWQFujlMJFOo+9DKIscN7D8iREzvAQc+gYkzEvYcwjYrY6xlQ3lMXfU6RQTeJFPDKoInRRGpXSIt1nyWGEIaz37Zqm7DPVlcyxiNU3S6OraKYXnKE2BCIpkVJRkrCFQFSKUWvz8Pcya5iDQEXsXTuFTjsb0S+APB7oenXj+wFYTelgf6YRakPYZAU9gFaUhtWzX6FXIufyiLRyg5WqZSLAFB7v37/n66ennIdNXdOxJQTCEB5TaamYYkduFcdM923P/TD8pl1B9SayNRRgCW06i+/V1ibXfoyH6VoOyRV6Y+2nsU5SauseZb6Ykbx7AZ6+tlQcRWSZarOoNjegtylVa+vd7sla6iS8pPIcOyvSx56kYZxb5eU85phFGB/xuc1M01yHNaY5lM3TvOc1Zr/mk5iY/fwILg7jq8NUpjNOZLdpt6bEOz3uSer0rj0CzvXQGAtDAcaYXyhr1NMHBxyGwnzM2QD2eHjId8zGc1TR85rKsFCQ9Ki7m3s2RQBNw99MzM/DnodII/RSLPWuI7iIdo++MmsHoM3xfXHF3ZQya7tek4OHbA3kKRSlkfX+XuUa+7pp7xRP4z747xkvBVyCRfx5kB+e+SHgebMFhqd7624oN2No91rkNkynrWyzCyiBl6O/kLDEjfJlOKBFfWOphOm1eUSg4QszaFw9UrBP5RPurUwILba3ZQgqTArk3yGUSP43Jqn773Qr6G0dOvdi1Pg8PMJNGR7RaRtZKl+rG/wQjoMzDsnoJg0BPKLQAy4Gb34zzzSO4KnfizuRMWgUA48MOjnOUHibp6F8WrxQGk+kZJNeN9TGmgiNjfE0jTdyywtOK7o989/Cp5t9lYTDhGmJSC3x/Zn4Sxhptjcd6gZmco9iPDKubsesjst3MDrPQ6dr+7O7eUbv3r6FnwmOU0liz0aWEES8hmuxSEmxEkbLUt1oDapWb6/Hsz1qb/fhzLEZ/zgXcyaVwTu6pkqG85FiZE0bWb5FIx07I+vJhgfZrABmJIGofnK32WiOnpVIpr0e/aytcVjq4K9+d7ulqeB9hsHF0zVTFjrK2gw3apM8D4rSWuN0OllU9eFgBjfF6xcb3l2WuimRVZeCNqi9+Ro3+7k7JmU5PtCul/0XwEB8mZmdPay546p7cNTivJoMPKBqfF5fzXCuavXcja/uSBGOxwd67fSl0ddOkYrqApyRc7eo0bP1ta4rcLZ+18Z6XSlvKvROU+MhW1u5ro11vXK9rub4Ec4v6o5n4Z06w1Kc4zv8UjhJdQTRYg4GYkbaZ8Pmkl4MHNfRrMutvoY3ILNjcOIMb0ymEx+QY5/nwjj7CujpNpZxhokbHnX3+Xka/a02cGd9bY7C5Y3Qv4Tz8SPK6Vkudqze+NxR2qcGb93YW3rile1KafJT7Uujvin0L/ps33HNRv0K3HA/f6ueBaYBokItSuuWLl3EZO1SYgy4XGxjEbEU6CJ46aZt5NhWRvRxJG/JBpZg3vP5Woxzh5ats4mGDLgRNwovHjVv2dltvL2vtra60qQ7HhBzlGzjsIQTfo63Dq2M5aJp42j5kZnnyDwLGVAjEy9h+Fu3iUQ2D8Z6xQfNr3MZDjKy08VtfTyjKOW1WPWRr+ZI1LuirbFqoXSldAFZHL+dzKEs11QsZT7DEeKe5DUPXcD1Lx1Rr0OvSl2O+WTqTdx6PetQUN3OkSN67PTu+oqgyTLtSaTDL6AL9KgPP9GpoJOD6grrBD8b0EJSzhl7KDvwm5gngSPDcHOme3bKDvo69ctx+1YmJ3H5zD//HN2+S7afuevH5Y1vtX16duAuS3/P0D7f8iPGxWhhhH/mlTfDeXtnDM/dH60zjesn9+m/W7v+14r+xy1UjZw5o21KaP4bN+XWsfd72/fC91u9f1JXGaUDvt3k2U/mzGT2gqojg0PIR+YoMLi2pNeBtzAc7VKJX7eemzH6FBGOdUHFyitJNQf23qZMjzL6Dt4iv5vldpcZckRTtqWhlx+lGD5+z/Lcaf++8Hl/5DdXJfRCQ16DSYdwRx8VvNj/YPv5v54Bfav4/BObhBrMUmT33i1VVXpmMx3iFzqZBEIYDE+ZCeu+n02Xrlzw77dG6+fZmpkJvdutDsi+y0AMqeruF52hkLPbfqHzASn/FzO5fqTyC1dHSaEiEYRVlKMWri5k6XTHF+euf1FTwV79m+pvjujztxr1Op4b6PdyLvsVvd/2vT0LfRq92h+RCWBW+KiYIf3JmeXXKjyJKf8icvCMZsp8sDTuohbdLTlv4TUWj/4EuR9GmOy61cgbUfa1mOJfCq5MrCzF7w1D0aRsEPfIDiJYpJoQJQq10lqjUNikxht6KB5VeMoKYZayPUb/QERG2rxbfMYi8oNzKj4WQuFYTfgxxXjJSMNeC+Juq03Ns7n2nnVnFLKWqnoEIMWMVperSWlLtYjsEEStBpoTarBxamMpFcoweqVix/cwDCoBEEZjwjAuiV+KC/hhjIrVv5wunoouYEaQo1p+foX6sNAvbcChMwCS+ASLcgyBrAyDel2OLEu1OIKGGa06nnJ9+kG5tiu6dp7KZ0tRfChoE/N4z3TIvmsh1GrPzAa4smypXlzZR9y6xTqUag4exYsvD4ZrCKPChPe9v8QaqYwZbLeiqaxQMSN6jC+wsfhehbIcxKO5p8iCSUG3iU5ulka0d0WqQlOulyutNau3drV9kQLnkxnS7AiNCHPcIB5GoubGFVsHobjCuAWeDkbFI/3U19lAaRam7X7FI7vi7m4KJsugKLs5Tc9rYACH5Wcw3UxVZqXGvt3DvnsBae5zZrpmZwAh9tVTpT4bee73z3Ax4dUxVB0D0ZgHyegnjN18Z617CsIYR4uINREOy5Hr9cr5ekW1+fb5eFpHWqdiikXO3uODoZ0qhteYcGbMXxB0cbjvZTPGItXvc3p8KONBd9iJzwrDI1gko6HBPouK48BGwVLOtqxXOtYgDTJRKqTMuC5MvhNzPT0bsCJqirpeq6Xf9LI5GwegSTNqaXxHbdqNsUkZ9a+8moIU49la6wgNodKmqHVbVx2Cu+Ooxb+3mocyUJcf7Lp4auYS0UkWNRgGitY6l+vVFM8eKdia/a09jP63LXBhK3a+i69fZDYx4zqbgyWwTef8TZ5nPHhzDnPJn+kjHCNEclvT4O64SkSonhY10lLfcmMuvGqkvfRrGK/UfQxddfShQWP2J2P8Fsefw+3E4TrrsW6F7DEnCAONzNDhG19kucl2kc5IRmjcEOqOhKlYDQiLV5Xt2s5yzCRXOIIfeMtHHXAj07WZgU8a3DvqEXZh0MjzqriTjGzOctZ41TBwkvebs2UYZ4xuBy3FaU0q1PMgxR0Dn4YxNY09hJF/0G6fyDhvydAM+Nkalidq5Pvcg2ZO38XZKrVyWBbKYlmZpHfW1SOIr82Nj/azhoObSDqbAY5oxFLRRv9VxljS+ShG6evtBnlLhdtyF21tPK15PDjRZ72A6jXnrWC84DNtf67X01fgyMOrurmhtYbqCx1N/E9Xk2dOX78MZmFjSN2utT9ovx/NkNhPRg+1F8fXw6Gwa0dWuHJhLYXL9epRooWlWiajUgqlHqhtW4PX1lC4XC+DXmyY4+FsuZ7PHB4faZfzdj1VzQEVoCrF8kHb3svzbnsKHtUYcNcRVVop0J02N0mIX1ujRlruBr1Z3fLuUe6lFLhcDYS60NaOtittbVxLo62N+qXkWVQvCdLayto6zWuody8TEqclcdydCQTtisxO+4CBoh4BLCDF3zuB+7zXGhmtAhckG7flGm+HMRzYwugVcpWwzaS0pXG6+1PRk85ow8d1QOTifzveyg20t86yz3NtR353X6bAhqIcDgdUO0+fPo6HYVMDee5zppMCXL98QYAqb5A3QvvckTegbqDVlD81O4lnhcL1y5d8w0tcgX23N57DwhuWV0fTfyVv49ntqqWVj4wQ5i+UzICPx8qgJS1U9Qh6c6wIvrOtzelmcfpiTk6R4nXeD4OJSZke4594wcBP4UwgsTCGxBAiC4mnDZdCFSgVtIvxahJ42YZea4XjEc6GY1I2gxzjOi7NQIHq7MwxeGJJLyj/XMgzmMZzX1PZ9TnvXMLVwf/2hBH61Wn/m0o4OAKWwt5lWANEkwN45fxYae54a/vVTjOPuZiDI6BijiCFBa2a/EfOex6tvz4cUwUQVZblwLIcqMtiOrDgs0TpF0XlisnqfbBGDhHd17As4bzRaXomHMyL702/XKAry+Mry9BxPlkJQhHPejDkDXHxBwwWAp5uzo8IRwER5UzA/s5peOZXdezak3ZezUEdCPJW0M/2lkcjWTwJO5jedP3dbc9/3/LjLz24QfL+/x6jJ9j9VHM0zONf/sLpt9+AraFdMN3vMvHJn8awfqhFJPrc3m6P0817ZyN6GCvv4e59CvL/bdu28nf4r1832WijLYxgqr/qewThyt//wSP8Y9oBC+i6omkE/x2g+t3ts9yP2BeXG2YAACAASURBVL8Hv/aF2PkKspB8rtkUEsmEzpCBElbg0Fry1UYPlCvCoxvAU74XU0O11qhSWZYF0KwcqZie/1AXC0iS5AAt+1OWozX9n6l/glczfF3x2uqluIFNzDYBPAKffV7J6/u732H5n45/+ZWPf/9t0jWPeX93+6ed+5978Uv21LvfhH5vMp7f9hHywMv9/3duy48Q6X37t16zZIQU8waVZLIyQtWxyfPKRm6w5RxZOm4L5OQHd/PMRhPwp7TnhUGre75nDuZR3Shq/strXQigQpVBDCMdexjRX70Xnj7cF1Uj5ck0lDts3Pe0F8Xdf3hT4Salu0zfbdYzhUcovKHLF15r4UnMk9WcC0wQfUA4e2+G2MbzMtdhrNWFU1h2Kdwt8NMVeYQw6sqSSDXb+4Zxj3NxKTNzPojtSYZAGMKEzVM5I7zOhXGCKGb8LKkwIYEtInDDSIxHhknx6CJVtChVhNqhqVLqQm2NVto4s9zCkmw+MYziUWLBa4IipJEz7gsFgurADeJp8odSyWHY07nGIKyG6DY6SD313VAu29qsZ6HISsXSTJYjcAU5PtAvZ1OoClnvcNsOvnaCXju6WG3jSJe7ifKMfwoFr+N4utBfhXFXt+uoEDXRU+GlZKrGYcwY804FbCgoIJVXoYSZZKSwzST3NkeCqTNoADyCPmneE44JMEfB6DCgJpyTcw4Gy5QBYy2AUee5d7RZNHoLI1kax5opNFcznHWPfm2tp+NGx82kDiKpeIi10bEGUTszViwBKjQSvkqmH5Hd+gRMRa32nQFnR7v6TgSOtQoF5qxwvhd5Tl4fl5Rx20a3ECM/gbwiYX2TnsLHMKI7p4fn/uIl6RzA3ZZKWF/PdEiNuYXyNGEFx1sT7cu9UIobPGwPr0g9cLmecCww3hkvWc21ytLq+mWRac3iDEyDTh7DIyoDN47pbhSom2UJ42MC1+jY7GqaGRCIKDUNfBfwPmoYzpHuM2MspUA4DkVEdhEi80cMYuyLEM4FoJ4uMowpBaXFoua69xwnAynkYCbDk//uasaEsgqqZ1pbLGNEt0wRq0eGp1HP18NHNPA0g6Yh4mktLZV3LV4SJegFnd4s/f3lfPbo6eZZKybcc6/NKFKEcE8UxLOEBM0Za6CBGHXK1PGTPM+kF9623cUNNOUH4xV6F5hrne1wfBgpNPZRJ4ciNNM6B26M33NfMaQwlxeZ92sar6G9wYfASDGftNeear3fwJbt7+hKMV6kCuYIVcTStxbo4jDVJ1yfzh6jj9gh2SO1SVExlAgxxz7drzs5ARJK4780LAb4THHSeXa3WQ0CtmTKo5kp+/qWPjKNZZ7TYAq+HwrDSLa7uP/j2T6TZsfrwxCdxhuAkpmBpFbPyiSJ1ywy0RiowAlxxvL7He1U1J2hKxMYkU4mGB4qlFGmJeq+qhuRAif0HZDEH5frd67idj2EC6Y6gghXl1KGkX6ax20HtzxCzP3x1WtOXz77O+ZnNSZvpZ1ejejTqHceZ6E/885ShetqDo/V0yYfDkd6UXc580jQEjy4OS+W4g5kcjsd3b7CIF7vqfoV9ApyAG1mTWOgNkHoa0c6ltqdOe/AeEH3bzLdpJLUZNXCerX65uu6mnPwdQXEecWS9d4HKHipj1UtZX/vKVsYrvQa9V1ZezhpeRRp8MAxPD/Hg7ca/ESeX9V0vI39s9/FSzNIrn0uavT/kgUlkcTt3t9qAQaPxea3fwp+ii1tyDaVs9j0Oo91V233PkhuL97LGnK3CYQGueycaWT3+waGdtdzJl+cN/1iJdTA+HXlieKSdDjjCIK8Ab5s6cyWr4xrwmw83zuotS9Keed8q9cQV1GqO7D31iniJdBCgR2ZiSZZTjEgS/2ETzD4LnPeNFlu7LZMCzTBwkyHspyV8+Jh3J1h31+oYSiuW8gQx9ldSUPx+D8ikwu1gjw8cL1c6esFgrbLZJS/s6NjH8fBm/ci/4zhPgx+82WI8/HFo3dI6GDNQh4OXkjynGwy0QBLPaCemU5E0DfWW/86epR5RtF30GDZvn+cr+0Aix4B5zHWFS3FswsW+tlStzcddFHVg1NcJjPRvqFFaa6DMCfxiVeJlXInQqMdsbZRFoEUpYsUwsVPRFl0m8Idhv4t1i5WxOY9K8Oe37ugw8Jr5K3SPraNQTEd/hMHfUN++Ddu8zwDn9f+Di3meBRR6LGnLW6fluLPMNIoI3I3ep+N7nuc3uHF0/q/zdYqCmaO/63N0eYFqH8p9N/037b+uVMd2jfv/GPacxHm3xPBPtN9S98+0Y68SRI3td45+BmM7LCTmuKOFkJ4OBxY6sLlum51VqrUMrJ9dPWMhAhRyG2UuTW97IJF1psrs/2vIi6PDfkLMWcA+zt0jDkkahcOf/11zD+EiD2BluC5760dz2ZVnhfjOV7vZ9ufYmtVRqSv822Ek5jzS0xrvHlUx9n+t7YD/2Rb7oPL97XnfbZ/vj3HRPxRRFSyr2Cjx+/0iE3e/PvfKeIC8fSe7CdZzfHdnsRU2d6zJ+DZJoX89v2S12WPJPYDxZDTJzEGxj7LZBD3Mel7BCjyniYryicKv/D4fx84/ecvwMdkLFwEpAKnD3AvxlHYeR1OCDlmXbAx3a+HPu67/fycqHpvJYcIO5Is3gpGmzdthK9bRdHpznma3yyqPInvswIdTqJcymeKwIMKRycXjwhPN2PSrJE2p223Gq3V9gmBWih18Qg6YcFrYGIKvrZJi+uwrn2M3pdMRDJaYb8Wb/UtH+XzzYwDEYcA5PTOjImbgwF4avmiasbmYt7k4Vmc0d7uVd4ViyhioSq00j1C0A3XikdkyQb2Y6dXTxNTetT8q/7ZybQrBGIex0W4tCHjBMYIA8Bm3kIqEiWJcVYJQ6TQurIU4fjqQFsberXRNRekRZV+ulIeJedUa0HlMEHBSjkeELE69+vlQhimVa9wfICutKL0fqFKpbeOlk6vrhNw7/P1dOH4+hUsFUKAUaVpo3arK4t2Kh4Z3TtaBXQhDHEiXl85ZHYRxEsLmNIjHD38rIWyWoZhpFZP5ZlCu+PgDDWPNRTk0Y3EoRPSinJNATkjdyZhNNLUz8acpH06jBVdO715LcBCGs5N6en1Lt1A11vUOYd1vVidTH+/GSj6OEMhwA9EYnAnxfpwJVyeM4HeLA149BcGANWgEzaHbbRrLkK+cBgIYrr3cNQw4N98f4fWzMrfeT67UQBXlAObFLjzrc64JVbdpBWXad8BnQ202zFlrezZCKyhOJnW4s58lGk+s4ZYhNZWH4mAVA71gfPVUhyCecWq1wuOVliSPy/OjMYQIqOFUDy9eggHSjtrGt4XjzBvlz7mXyWjN6IEwKD3bCQadTxPnKlNnjT1TB6WlrEXizTqnimEMPYEc+2DN8chGbUlo/YzZXOWQnAqUswY4HhR8X4nTkjxSwSvEmfd+tDWJwI6Gx3sOxEzyNRWaLUhq5dUoLtDixm1cON8S7ztuGvmGSQybpjhvC7VHNI8ewa90y2EiXVdOV8sA4GljN+ATf4WZBt16vRFdNAIw5sl929E/kPvox4wakZcA+Vt1NZL7R5HNPOGc83ciNYyeI/JTHRULFJxU4Iiz1M45tlYe9aAj4fNcE5nKL/TRV2mOckQ6PxzGs8lsuEMPkwSR8pmsmZEL6bvdxg1GtwH/Dmsde3GA2SUsaAdelFK6/Si4Omo19a9LvE6DIYRCRpnJQyAE2BsxufnADdY9N5dQJ+4LN/zWE+jUZL7FGtvNrNOCZiK5VQ13CTimRLGvAevZy6a69WZHJkcWSb8WEvQ6oFIBp7dweKGxg36EIoRU9IEfzSe0dsOxnrEOwQ3KNq8DwfDRbUUDkvNWra1CEu1z10sA4wUV8rvT4SfNzuPPr8e6zGU5jIpG/DoSVuynoZHVaXRc98yjXsaf0geBUBXL7fjKzQvot2yzeOum7D0I/1ie1ofjC5critLOEcJpqS6gyaupwvLg/WdvK1sHaDm7+JKlQdQaHJJPK8aDrGaaRibl39a15XDMd5jSrnI2NNFKDUiWEfJqeJILmBbRFivF3d+Ud69fw/Ax7//LceVzre2e6yXi+/nxA+AO31eoLtThcjOyYact8zgO/GSIsVkKAnabLUbFUWvDb02C3vx0bXL2RxbUVQPLjuMbAfGFxgNkU8rFy7II1t6nviFLXwRpS+G8nGzpzkf44+ijjtzqbFgfp1XiHMWjFHfwc9dnYNaPzovGdHH5uYbJ5UxUs05bv6eaX4gikjTskeXieH8vPkXEqVyXvQA2AwzhxfTu70Jvn78YPBHUA0QT+HOdO25Fv12vmIp1u3vwmuG9Ph684z4/PSLvTezBMqWlsOIOCvZx1OWvSix39q5flKWt4X2QSlvBKHBslC60hfPQNKbyeNeMkhFkNLpatKhnT+Te4rjyyyNgSbMFqwWNyLUI1ha9XAWGXC+ccIjzskoW0APeLasYX2CQcsoCSyLObVLOMn5c8JU65XE88b/CnXpLB6JrfHcoJ54EN0A3yLhx+0bdBg8XtB1h2v19R+9wctQMu/7nWvTGQk+KRLbiO4zedl4qvPusZbBp3WGI4UqdHkArghHSwtfLPVTKXWUvNJMqE5xmF04cnhYUsa/nL7aWhRLq38sZmLrE+UT5ysF0ql8BVTPHPoDCpzPT3kgbT3O0/IJ/XLy7Fsuf7tDWay1BUj5GqmmvmcBrjoy6QvwIMLFAyYenU407XSFSyQ883V/YNCZs1rqdluL15S35li28oXIoPN1QmqBs0eww3bHBt35fhjZY9UNomT6cxAIf2CszR/ZfulDVxq6vfqXwtvf7NpHgbcmpo0o2okv+T3tnd7Oen+G4l1hRL+XInvu4x+Vsl2w8X/k96Ww/5H3wLencw/3PNc+AL8Cygfjxdjmf+3Yfv9VYf3ttxvnlbn9quP+f6X2F30GLv7k9j1lBmB7ZuwcGI5dVPgg8LRLcRz3d83cN8BAC8EDdhEedvzbiIdRrmujqQ49l8t4Ugq9m07G8HBl9fJtKsIixr8OFZBYGdqQ1iLINRkqSR2FyJRWPnhhJ7dvHL+Gc2jwn0kDnD6xo/HIFg/oeO3m2vzoXPnoR8HhW7qc1G/ctOdO5jMne+7jmUFmdsngiQaQ5Fh2g3tx7P+d20+lcJ90cP9+LQ1sLnbpiEAPxjLTst4BUHkOQO+08Bie+/xXaYVRH2LfAmkIQvlVuH5Y+SCf+EWhqvD0nycM1Q0juseyDaaQH0cm8fxXGZ9/rn3r+fG98tzdz3/zXHutwldRvopS0oPqztsl/Ktwhh1qPjHd50S7OKEp/iPiqWZFvPaX1f2qrlhcauEgVgcsBGF6Q1dDhpa6s7mQqa6crRQx5UnXZikKtTuRUF6rkeSCCdJbPckQqCQ/zWnOIiWdE0AdiobwLAefm03QDI2EftsyH3Qqi1ZarZTWkCpIi3s1f9/bQZe177ck4kophcciPF2e8zGc+p/7S+OImwFMc2ApGz0Kv9ZqdbXzffZcV6VkugK5FaguC4giD3ZOKkdcFWKpJU+d+hiKSLaHW+2eGJMclhkNWvTlwxCi9jg+jE9jwlN0bZ8iayPalfn2EATHOkeE8HRpKFzmZ2IaMR4FHgVO7vySygmfsJDRuaGESQ/6jWLGPg9lkjGRrXd07V4n1QzyLVKzNq/bq1Y7tWWka6Pr2O8wfPivoXCOUcUXjGtxvxBMp39KJljyvlif2GIZWzI1yXdtjRzb9d3uLzf3feMSaRy5ub7lTZ8Thkd2jv0pjXfu2dnb9+s0OB2Lnt8PGCHXeTuvSXnr8KNgNfoWU/wB6DpSUNFAqNlXjvyicJSRcnz3nkgzORRphfIwjSjOfnxcBF3VctsFI7uqRTreMMUzTO3PTfAghout/qmfOLW6l3Z7lPyIbt1wLuIGq5oGSnNcilnE2fI+ZfAA2sMZbK8kCsY89nHAa+5j2eLxGbFpV640v6VvMlGAw5xHKBeJ9OHzCjmNqUItC7UW+wnHLEPl5tzSzHi3tqn+JeNszca5VAJPG5F4bvdHCCuafTjl3AtsqkOhv8/1vlnN72+ykQxl/0W+PNa907Hs1MMp6TbqvE+ZNWI/7d7mxqJAY+rziKxGG3CehLkxv2FMJeA3jGC5ngx4nTLKNNrgTFLzPPpPh7/ePb1sMfiN+YrS2+qOVVGfuJlwTuD4aazT3/NO3UQ6xlzi/OnYi9yefV7gzZdg9eQr9EbRQi9bbtyy3pVtWuDd3qQXupd0CAX3eNeMX7e0eoz73ozvEI35qw0o7+E6KEMoTXSQQMfxEXkW5X6KG89LrSaXTIYSG6fBZvd1G06kEcEwHVaCVZWkYWGM6YOldf5WCUcvTQDfzfO5dv84oy/lcp+6HsCxfcnj69ecvn69fegb/d0frp8XVa7np9zwh9dvCMfzrme6Lq6osnX+9PE3Ht68SUeOpURpH6EulbqMEgqz0SwN098An4CDqFc+42HZ35yMkoNSpKaeWsCAym4VZPC716cn+lJpbaFK5eHVYzpbXtyALwhtXdOYFue7SKEXL+HRu6WGZ+BRmey8YfA2POsGPfX0zMl5pWfGmOZ+A2V7ViWvOeCFrDLfsFv35wIb7ioAdYbL8bzefD/x/RNdjlcN3i4fu9NecCibZIh5rH9EpOe+B/t8QtyE1hnn7par3bcTkVGi8dXXZG88v306cLs+Q3cGP4HxOTEGv6Rerqg1k3P0k1DfFqNrRalqyueuheqQFrJl60qR4UCqYs4g84jRNvJeKZZ+vFTbMS1ob0lHBr+gg+dy4aAr7hCp+Tt5AxPcMsOWNleqd3fqqX5L0Ove0mCZOD9kdncOrbVaBjgCjfvZFIGjwGUB1rtoe+Okpdu932aQ+x5u7Rk+z9nuiaxxs+uxx9lF4J8BE4YynSt6JfBV2TgqSqFopNatdr0cKax5hnrvSXsFqMch+CR/pJjYUWrELQx+jZHFw34eHNIuFD3k0GfdUE5sg+NM5uodKIXSzYEwWb6ElykDZmYc1dGV0/gH5yvDEVooVNE0CKp0jol3ZWskBsqbSX/TlfBn2OOqf0rU+Y8KCj/Rkh75e0MXWJQsY/hcDefnjUffbs+wVHevzXXT98933Ej6D9qmd/oP3Z4/re31/8owpi9//SvXv/3tm8bnl4v5/XPaPOSfLWvwR7dbXvY5GfSFZxOPSeLdL6K8oXAC3mD6IsrIxZjOizpkhOQL1DMnuRRXy0ItQmtmQyJsCGoG/IGbt7xLoHIrDRuymKR47BNGMeP5IeSIv3XqX18GtNQry51j/q3D6GKpCM/bFX6q/Rg2ELmlMdlCLrgDACPbCi4PyLP3DunjvwOm+n1t+SmC8JJE8J3E5kdf/yPeePfaTp50oSOYsDHoTTrT3Vg3bw7m/e5gxwMbI3p+LZvbYGKkdvMLhYaqMW8jIke2z02zmOVn4f6WXHf3zK0DFUWls36AbtVozBtMPvBOofDOBCxXTHeGMVhRviRTdIvEXwKRz7IR+55p93r4Vu/3dnGradh8SoJy++Y7lzd3CPBLf89H+QhC1lF65d+ei6VSeaXCebIkCsJFzKv1AXBbjHvqSf4DMUO5kLXQSygQRbweutVBPxyO5lW8rrQmvLoWPhUTVrsq0juvRPhShEetPEkY8iylofZ1ktK8Jrt+3QgePWFxrMCTE6PXOuC/q6dr8RTtc1B6Uc30WiCDQJaIsMDT0SsVpbVK9bTCghs8vC7oPiXqvHPxhoMeUaBxBTzaQjUjPZ8ufTqKOs1NR3dBOGd4UI8a9vqktYo7KBQiOlR9LSX2QIbTQTsrXDulKP20+hhGqs9yPNr7VC0j5epjkgXorCeF2hGZjMrqWSn8p6iOdJm+NwpQJLMaLMvi+nR1xYcpjUuxNWpeO694Wmd1piYigkstoa7y/XfcnSkAceYpUhQH/h2M2MYCBSMtN0OxkSfSFdb2qLhRwa5HlFIa+Hw9FKWFEkE7vV/Rbuk8dVFT8GhHPfq8qaVvb173uDczM1hZcwMGq//XTVHULMoKNAVsG9tWKaOq1OIp9R1Asv4gA//jY04FqqeGDe/9QSx4sY3I0YTu/Q0bpcW4vr33PpXcX4t39cQjW72Hx9Go3udAb2jsjlvO+QxPVFMrD2C5UZwmeGUHo2cfsgAsoE05vjrw9emrOb8EfLmzSSpUzkpndWP7lJkhsIOnRw0P3Yi+HvTGfjXf23IoY/XciK709MSdHfN0ElcTF+VaD0VORjTj59qCbrDSEjXH0gNfhPJITKAqZp2klPAPllT8K2HQjLUMdW0o/4N6aUostahFiKZAZHthGRd82Xzc00ql4rRjZ8WC1Xv2n3QjjKtN6WL5VK5qTkwH18RZcHGhVDe+1YVaFlemmoNE70BvHvWnwUAOiLxjvImzHJFI4/jLzTkI4+BYf8ZzSSTHhwFXv6PJ7YchjA4j9g2frRZVa4lBLNJfHb/GXOfPEZVOwp8QxX7CCC6OT7as9J5Tn9ZsLJ3dX0JZPGA9I+m9zEAp4eSnuU/aSaNdKEmtT/U0s+rRTApeH7w3WNdOWxtrW1lXowXwPE7cTCn3v1AEx+F+/QbvzZ9jb6Z3BNmTgUHCu75r8G1WXiQig1UMdsO5UNWis0o4w/j5a82N7uZ54rSTjMKe66kHzg24CZ32wNCSuDbxqngk2I3cYp/Hvrgz6RT5joKjV8KxJ/rpraGHg+EpjzyEZg6mDjhBgxSle2YZeqQldpeBBLAFoSCH4ngPEIdfdQpjlp7EQ2GYMT6oex3aQXs2ZyoyFUSmHs8McDw+AHA6X8j0IRvwUKymj/GvYckvIqx9OAFUf1WR6lsQiqpGP12oDw+01nO9r9eVdjnbuDL5x+BNVy7Ot0nykQGMqop2y8F1+vyZw+MrHh6OfP7wwWixR4lq72gJC4oZ40qev0HPRKxURtByRyz+Sv8ss2P6EZEzqsry+GjPn9oEidexdA5v6YzRPDG7p1aXGo6Qdo+e/QFRZJFET0EjuzbOpxNVCk1G7erT6WQ0RK3MVpWT46RHqoob/Nwxsqk5hbqDZoxVgMPhgJTC6XJyfjToLemkoLEPY3YkxQzNXh5Kv28qAZPgpfn44IVmPim62NGexH87fmuMxrNbeKdzxoBJ1eq/tn3t2crwDd5aZud+ZPNYOlxNPNDmPX4mbxKkTbdsno97ZPBV87OPvxzMePv5FfCU47inbDcMZW1RQXid/GTPeT35va/8HeJo8BVmeJcsoWcPiFNap7gS5Qrs+eZjkoT5jn4UyluD7eRPP3fae5MVe1ekmrtGc4OpKLQ2ouARk3tUwqHBHTwynbVhWOkrUqplKCqB2/0ZL0GQOjPIUindeYoojRGRssk3OjyH4X1tK3GQTc6zAILrdfVSLIN3jRI8BirGOy61Wh8oulrWibLY++qh0i7rBs4t+TdOO0liGOS9PI5yMQEr8x83Ys49nsJ5HnvIU/27rFZLGeQi+F6/3dBnT+AV4r7AC85jvHG+XkCehsOO4OdOjqDXKRW/za26LJHCAtDPjc6FVY1fBKD6WhSx8yCwIEgGPAjLq0rRCqtnGHBn5ofH17m47dRZL+eJgXamTiY2uUgkgku+I0EV4apKF6GqckgLClwFHiSCVSQWyvkk4THRh3B2p6Y5q13AZvukHH6tnuHnNXRzqNG7Mu52/3+vUX3Gyrf4RrZfZPaRmOMWH46h3R/LzOfda+/m5FsMzv/0n7+NPhTevtDHBhnfa3euz/XL5/f/THurXo/9G+29vueDfHh5gN94D4zxf5bbsf8+yLjt49667PvWO9fu9TX/XtmufzrRY6z7O0c5y1//yru//e3ZCPO/Fxn83g+0P2J97rV3mqIHimHfv/8sYP0JbfBmgf8D1wpvwfXAcIoIDz/3r53/PvnjTSMjppeb6+biF3E9a1eWKi5+dKPYGi7umrJSW3s+00Vp/UpvmjJKkIaOO9hWLwLQLTvn2lZ3gg45jmHwLq5zQrJUx1uVDBRbBa58pPwtkMJwFHWyN9YrdAgz/8udM7K7kM6qyStvuvtmCx3I803v8Ab7O76/zfMfPIiML6eBx9q8PLo/78z9K7clQP33tlvvgz1J/dbnf0bz0zcB/LgOkd5M0UzTZ20/j73ANv09I30/pTc1sH/fyLerd4cC/ujqBrMfXe3f8RwS+STwTj9R5D2F98AHN6KP/qK2zT+n7fbk2ZX54wb4Tt9xlc+cUL6I8Eo/8k7f8kW+3LztIamAGdFPMyJHuLj4GEkcNb535WMoVMWJitU6nyIFXSixOoMHqgjdjc1XVvMm76AFXomlQ3+rAsUMRCcXYtf1SpO2k+BiJoNyJAy5ci2JjKinb9fI1OrOGQxB289Lnd7gorEbaE3JVJw61VJRLFpeSqGGEo4w5KobrMOwdNsUuOo5CeoMB3Nawrg7FXvx8B2QSoZdLXJfVMymWkBoZuwPIwBCpCifadaGFj8AZ1cQC8ABdbcXBfTsNTono/SmLvFzTRWONd8XCt8k1MFZMAS5W2eEISxuFvWGnY618Y7V/57624trKBkBP66pfxWC3vhJhi1gSXXa9yHWzozIUPDEenv6QL8nFEtheDfmrlltdCxNkRmMujN6EQUk6VAEIHVB10u+aTvXWOPdZwIO4v+tOjJnG4ynklm3N7vkBq3cEVd6/x4aMUb30j3jzkGarigP4/k9zbWB3T8Ad98yGVITHuL+safDIO6/Jw40I73GbROcT0MQYDUnha+fP2fKSNXqUc3+bCJ1oeiU2EemfQxC6+/qOqVinnHPtJL9GkpmndasMcVAME6WsD+h4/Mt7G1gwr/orWUpkPiu9Y70jmjzCJOZvjhCD/yjZlgSqmUuCVgTaGp1NU3x5km148j6eesBqxJ7RBoxYpBJVsSN213prkhUNduPaqTPHwpLWQTp3ZxjGE4oloqUnE8pQi0gVdyw5A5iuGHDQJ6vHgAAIABJREFUo1pqRqcXSg9TiO9nKmN1qwgLIy3hBKlE7e4hsxiNM6XnJNTkXk0S2p/cgk2WiTGMFMThDKebn31tc82xWvQPRJkAq0eK09+NaTjfF69NJwhXlIdSJc4Pm/vccJ6ZeYpFI4mn1HZjeGQlMJZqSg/nSGo+F+opKA3nt5xj6+ak0z0394sC8zhwSWPGyPe0MlLLad6x6UbH+mzwGs7QKUjp232InhRXmofhzfBb72ZITSOXzOR8QtoT/Yx/+cWktN9N6M78dPtdIly/lMqMHX829bWh4LEmYjwhpUQao/G3v9sZNN/YkTtLuRlqorfufdcJ/pzVcIe3nllv8pwnXXqmKcOwkLDnX/3IGb/4ax7iWW72QfI/fy+G06oaH9h7RyeDRETuJS8K7kAxshdEu341I1PTQWna5cIZSda1u8PFUpcp1X5lWRZK9VTLmAPh09evln73LBNtvwNXOn4ply1NA9AL9dEXJRYn56Po2Z4ZrIc70vaD0QMTUuhllDjQVczwJ2IylZfgEe10MaWjRrSheK13qSy1UmtxfLegvbN20FUtPXJoBENJ6CNScYdeVVtEJdc/4C8ATefJTHyERiTvZhll9ysP0GZvgxa/1PYYbC8TbBWOOv1/5/reeH6vz2fbETxjQzrgxtMvzWHmP5+9596HaQ03SyaOUp6wYmyC1TKfwNnbwD5zi7FYavcJw94MSW5w7qRF8EMvb6F/0d04By/SAVGjHUP0DXpumba6dKQoYS7X5tHXLneGk9NwoJplKwb7GziiN+iFkgbz9NghMoIMOcdLHoT8Ek5JUyragLFwelN3YNfWaU4Lm5ffua4r2iMz4OBRclXFeJBlWeja3L8pnF3G/SIHVK92VQaHKp6BTXabJvuzFQj2btPbv3Z7514Do28Z0sPNMRcILc3aAo80i9yf1l0EqMV0F8VnLCFz+velQBhXiH11npyjwwJ0rkZmnd8zB1ShidDcwF1KSSP9OE5W0qivahkVxehk9ZIkLWimOjwKPjZJxy9xfmJmLzqhN8OohZh+xsIaxlYc4+9wzEAGrwg5XkV4oLjRqRG0sQDL27esn3rCqmof49rv9A+Q+u9tz3X5PJa75UO3327pyqDJfp719vvk3HRg/Y45LCumZ5zLXzwbzbtnzPaobDd6mT7PxttvYPhNP4GvGj+Wun1rPJ8nEL1/+/0VqLwH/r7rQ37g83hvfiPPsFLPDGtDq+ZF1O31Z0h2Ph/dv/7rf0ylkITz/3f5jvTs33c4/sxU99FmrYvnm/qXbnNJgs8Cv0zffZHhDBAtz41OcKOmcXrEjPCL37hiOA11jyh/TvHAh24Z/1ofKd1Dm7X2bvaKMgKJqtsMaqkEOehdofQcyy7z/PgjdCkIv6gmvlkFfnP4fCZh32byP4KHb47QS6T8T2vfHvBeuw47rCGzA6Rsb9oogDT3yvp1/cH3egn8N2yLOEWPRRneBt/+bMyhOFKeot8SUIXBVao/vaVEKdP9ICb6kUj0rRglm+v5t4CqCbGRts2M51vDhej+lAgWwqUjSijfItM4pxdK/kes6K1wqMx3mUI4lnN0limc/HNG90o8F+ka55ENQ2CkSX9zhyGJ+5WPHN7/leuHd6huffA+Ar+68jDoYmNEoleUX1W2Xlo6ecVv3rWFsXH7N7De3XaPYbk/w3ufh1JuEIa5l767P1D7J/nE4wbGhc7nDfN9Al77manuGZY2CP93RDPe2KLRbS/CwTgckItVG8OULuS+luzJDNBLXVhKoZUFKZVXvXLtwlXhugrXavVGHt8biX36+JkD8BR7ujZM9PHV0TG/YUWaIwpiBTTPlIoFWaTxPOt0kd7MfULSG2ZaXankEYUFpahF11ePNKpS6BFxWL12uxsQB/MY6bqs205EWbqhJPa7j/MUcwMXztXSvBFncuJIu9qe5nl2/NF6pBbzaPLZaBBG/g6rKAtCeYC6HGwlj2f0vIAuWB6DI+10QuRIfRTXF4kJjgIqFi1bS6FfLoPQ4YZeCyH3eXZ0XZHjXGtT6X2lCKxXF3TKYnBVDLaaC97mNV7yHfh8QtE6in46qLiAL1GbcnMkZZJeBgQlvCk2BwcWPSuZ6zLRsgv6eX0+qZqe31kjPSQBtZMaMNjAlAuJV02RJFgNSm12Hoxr0oyQMKCopnDqLlA3dWC3MgmZMjbHK3Q8kkEb05B8+IPmFKlk3Uvmn23GlKg9OPra4rm9klJv75g35k67R7Um2jidCVD01JFXXo9VPHVpYKjg2gVas/NRpgi1GN8Gl7ty1JRuYaT185QMdCiYdfsYas8oyfBnRhcshpmz52ZZKkKhlnjGDWXHJLw53ezBUeJslgnFtqJTOtd5H8ZZMCWPotfBqs57EStvdEgyO4dM32ctwzyTUwQnsjWQgSuddBKw1carnj3BcVYp1dNvCtSCdhn1FhGKVfsY537aQT+9FE9x3GLKAaOuuVXElW6GP8LYGGxkKPGsZEml6+pGQqdOofgr1TJ/IKkgLDZVFiwydMVw+ELQ5+I2t5KOaSqjZIN62m4RK5VSuhlIGiBtolg7I/eIPJUNsERC1TTye6mSYDJCCRh4y6Ja+UZ76dxuwJasve59byLQp4M509BOZL9wwdYV7OoG5oFbSUV4jKqWOozjifvNwU58g0TH+wNLpCDnjwy+38dbQEQRqYDVPS9VEHFjnS97KQUtPeFh9jwvDmCGdzu9jOIMoTS3Mh3NItmSWnSvge5wc2fBo7S2D36Tbg5I427ig3TOiUnvMcFY14Q1kaz9uq4WeV7dkBx0N/YpjSKqaDPOTlVp6zp1K9RahiLDGTVlct8Juhx8ztXqwhfPpBIZVFqPSoceJeBa7uT501getwWFcCvkvD4akYl2kETcISbLM0zZJ5wfVN871Jw+eltzz2JdN+/H1pMC6mWE0nhMOFHZWDpmhO9ukE8jyShE+6xipnstYJtHSXn46lkNqjszNTcaxRlcuteQLSZ3yjFWRDgU4aqdQxmxMrJUIi5IV02a2c9XyoNYyXeULp7r2MseqEhGxyNC0cOAQ70QENo5+1pAGC1U1SO3M7yEcPKqYjSkLgczpEs1x1c1mqOtc/76lYgMtUNkRPXzh998rzxiMcJOwI1+ip7U8fnDBF+2uEUGvAbfWh8f0fPVjpLAw+MDULhen3K/QS2yXB9wDpHWDN/V5UATeHx8oNbFM0oV3r5/z2E5siwL58+fqEvNFettdYcyGdm7Too8Or71aQtwuZyzPvQGv+sgJ4ajxel2APPgcSNDAgme4ZRku3ij2pjeMZ/V+20g+TAUwS2faSR+5lV3nOcdTfzIBuj7PFc0mNCj9XOdZFPYE8tQ4T5XkEv2c5z52eSZdDPUma+Kb88fryhPCI8sbxeunz8/88bo0/q5esr3JI0obNLAP22+r0CVd3SPKC/IpCOyGwugX4werJwSH6Wh3B1bVJXrp5UVWN5Z/Wr0ifXzQi/Qf1GO5Yh4SK+Klb5qElkRnfZJsQxlTr835Yr6mFXTTu3NnEewyDS60ptledg44gVvOiy9fnbdqK2OHprR5eIyqZXZIvFK68q6Ntb16ga/nrCjUQe8G00XLIPakaNlG5NGu3b61cYQKeSLVOfPDs4Sdeqx0C+Gl0Hpp9m9NcBKh/5zDxLi/G/QR7/en/yzZ/YvbwRYDFdsWAJzBF2dJ12WZNKh29r31oYjguMNYTpvItTXxo+28+zA4E7CzpdKv3B4fEyDSCmF6+WcuDT5ey/fgYfZlDLcJlcp6cRagPXJtIjKBb08WKa7BxCplFpo1wtyALlOjtoKQ/NqF8QZKad2ztMXrpiTRRHb81WEhXn9rPJ71D4/9S0NUVUe3HmhIJlB8JXzbId3b+33L8b4tc+Nzheaeu15/tz2XP9Dz75nQB2A9jrZSX99Y0D3PwXoOjvMq6VCV6Gp4YikIWJj+CxW8zz0fhFl/VaHIVTYjjI+3xnFxngaJUn77jnF75Fx/1sdAV5vpz5+8c43xvM/oum9GWw/f0L4iyqdv8NujLECGYzizw8sMQ9Wp//JvR3OyIMP2o5jenbeBMhsFSNrxe468I6xT7EHTSxdf3M957JU1nW9z29sluv7Tkrs1y9q9O432c39jzpw3n/o5j/6+vyq3w8r/whD/74N05SOjAYKb7Ays9G+YPJhDK96ANiXorxi2BgsWEdMohA4Lgeua6NUC2BbVyuRsqjJLvh91YPbrNa6Bw9o5yzCBWVxybJH+TcldWmV4LnUZDKMbxbB7SvKe7XSg+bOCx928HvTgn8Mrm53BMIxbr42I6Y8uT7OPbi+zDO/0GKezw5ZuDk8aYeZ0Ixv9Kj5fovjs5/QzQevFt9Nuhamc74d759N0f412wJhFPYFnjmIu59D+hLfKJ0YFFfj7oBsUL15I2DehpmUzFvxEvx/6967Q/AWKQkJBbzzh91Pkf0KdevoSLlF6jPLZkxbeAS7mntD63ydpoM7nBKmwTK+z3c7Iik+MedRUokVrwrGPpiT2TMmHR1+oI29SbZ/mrvwd/nEe1UK7zF1zwdjuoEHFbTMBv15cgZHOsFfjjG47z+8fQujzu32PpnHPyOWqZ1Q3qjwVWAR4UumZR2GAJuyXQ3HiKPDRfE0WEfgqgZRay0c3VhcPdJ8m47bDODmuehetU3RvtIUzuVMOxwoUhFZOB4rtS7UdqRcz5TzBeUKYhFIR4/aWT09qh7niFtToHc/NCMawiP0PKqnI8YwLQutCt2DKBRMYRRKIydUokrrwrU3yrpS1iuXa6UulQOKlIqKcJVqBvMKi1qE5NKVZTXlbW2WQrGzVZ6MXVWWjVNJHss8jyNt1/7hLSYpYkLCRIO2bRdaoCXi6MVl1lCWeQQcppo7yAFtisU6N1gEziAslKKgB9fvFoaCD9tDBYtUl/T2VFdM9KJZ47s/XWA5EBkDwkCoDaiVMBoU9zZnMpSn4C2KSENY3LnBaUQHSt8sn+ow3AVnPUf5zcs9G7iHEcYVJqGYZTJEa5+IVbzXFY5Bu6b9D25nTsE6fEode6XRo7uiJmBK88cyQNg+Sy8WndjD4CZT7dXIOWlGHW1XY/5ydQYNMMUPiSsEW/9wABD3lx97LoRKsPn5S09Qp9GbzwxGdFoRJ9ETAM8S0IawDuKz+WpH06NpQOiUvn3+1n4pseBBl3UGjM3tMfcgfr4TE25WxyexW+LvCPqI4xzTHV6xmANlLIufzziXkeYy9r13n1X3iGU3OMyMzDSLUFbaq7s595x7OsCVQ0n9lLiC097Ucvxdg14MBXukmkXMyaOG0Sb2fd6z4FRmsuVnMEit3WVOKkoHKYgqa2/UvhjeL2NnSi2e4lxDtwbNDXm60nAnEqBrYSkFPH01GkahBloRLMLJHJQsPWgXiCwKOWTpXj5C6Zcr4ZAyRx+XYjWQA8+CeOT0ACdxo6l4lHKtkqE0XTvSVkLdp+4QY8Y3V/5187wOJe+ERgkDJZjReKy788p9Mp6pDieIxIH+f5zdjdPNnWO0aYHvtrRq9/Wmk+ccUff4meSbPetFN3zXWst1yEVO3tRxm7gCJRwC4lbfn854V0aDz0P2tVJfr6h1XcVqapZAxP581Bse8N6TZpWwqAcsgkfFuvMKGPcy0SnVzqWt7jzlhlgc/5aS+CH5bQmMJmOu9/DjZl8HHUiqLo7fWktaKPs92+1flvPoDXE4VBHU69MOQ7rmuMIxZfhDBrbzV0ygIGOLc9y9RwYcG08Jo/MEA8n8Ihm5mPub8xgC/BYud8g1BuvGAvtdKEv1qLWKVDOcrOuV67rS1pXWVqMBnt7feDB3toy5iFg5B6/VrUqm+e4TD5Ty2YRTDAzdhVWM79nLP/26Tuvhe9z7foaETGfRgCVuTGcjCOcRv1mKpXCPckHTuOBAv848sa11SKA95xHXfcy1jGH6H43LrqySGaqL582yPSx0WTMyLfjRWheWw8GyYi1RKsMM6skLY2khQ07PdZGSfESiJYkIWkG1+YiuKEfKY5wVm5GVNzAcICrUxwfk4k7Jrx/tPdcLZfFMDIKlTHcdhxmxnxCEh1dvkCI8Pr7m8+dPti69IaVSUicSfKKtQMQ5mq2w///svXt3Gzmy4PkLIElKsmxXuerO7jn7/T/a7pyZLleVbVkSmQnE/hERADJJynI97r3T3egui0xmIvEIxPvhc6we5WoGLX0S5KZnRAhaXrW6gbA2B0nx0klWuipDVY/OtPc3x6Y4rEp3Lumn1aHBs2m0Gta9lNCZIntwkOv6h0Ac9lPK1n9ZuhO/0ftzxWCPFo9B0jb9tUr0lop8JPJtB9zBafvQBr+sxPuxlxiSNi7Rv+vq+fNPieVh7ahz6YlgnbfOniscGQpO6XJFFgEeCRmw+jVxoO+5hMZsYz4Orxk+YnmLRnpCuaeoUsse3hRSqpx+X1jeLqgIU+o9i8MUEtkWUnPcSklISsuuEA5OiMG+BO9ZMXh0Pqo5hA586XbRtBpfGni71lEm8u/LQonIeDod786CnlS61MbnmUxo8J2zzyEnOPkZnDsv1rV3pits9Pu0FZzi/kFa38xNWH+/CCNn3wMm/Fpi9b1D69Cf614k92qzEnJDMnoVD1WNyHMBMWdiRKlVHIfC7nBjtDYMcxqwas9FBHqc76rKUiw7X1ZBVUjZfu0jOtm3tHffc6UsSk6FLJmcM+VkpWhqwE0sjhr8qClIUMw4DtrS8p/C6bNWK8NWi5XNCkWwJHYCJSV2CDsvwddeoZW5KjsNmuCyjAqJN8bzO02vGg7OLzLtf1sLrFrPAcF+WaVR23wPvD7qYsXlFB3dGP0Rf2M4f6boz3mlyPJ/rwPPIX2McfbfY0bjN/Rynp3m27kyfsEQ81fntd9Y3avVIWlOAJvpR73zMWV6W5pvrup3tC0hgUaj1qTNFkPEApu+DKUVOuUYV/oSpgjezX/XwAeOpdzwKM4vd+ZqkAOUQddx4RWb65fWSuggE3+zvG/fl1KYf/uN34WVaMAAatvsfi99V7ys3vD9r91En4Mafvo8boP//TLu87eOumz+ju2lcV+4/yzTVBcIcKrauqycO2TcKisjepyzOxLZ9f85wVHhTi1oI0ojVoVjWbifdtwesjtImXyUU/KgIpxHV6jFeG210hkpAt4wW0nQ5JHhql5Cc8Gl+5yZSLxLma85uYwpvCkV8sJJgrceOM1gJkadR6Ph9jfJ4Cg7LEf7HPe3Y9ixkfFu9mG9G68HwnGnzuF3A1iy5ty3d0UpQ93c0+5sNjmn2Z5NMbL24vihj2Zw2ZGOf7sM8Dcctv8D2hSL3A2DvtBXv9u1FfAF4vJ/L+riIpXO9rcNXFxjHi+1NaP47WfH75Y1SgdGOO4ZxbsOIMMbL4zEAMoUeJkR4Jqvc6yRCppgStt+zwd8gfX1FHlC9kiB8MjtNfs2B1CjH3lxBjuFw4/vePj982ZW1srvBUF4h/JJxv7sjog43/2QOeSfOX48UeQLvyXlbetsJPr94KVLRvRBcfvHGM9r4gjD9W9RPFkzX9qjorMzH5FcJHtEb23rb31n3nKvX/jaLLTKDaBJmIGTIzowZwN38fK4G0sFDaaEn3aT76dzCKY1cig1ZnWSxCT+dOx/qSynBdSMBDlnjrvMbcoWRahmbK9v71lOJ8t4+e4d+vWR+5R4mAzOrP6z14KWSqrSU1grfsadsIIbLBSdjMGt9LpSBTNMZYCEeZ2rpXtZinmmT8vCPC1kj4qaMohmaqoNwRvuT1YHflAKNSNu29k1PNzcvkFVeXw27/6U0zrNVCiRNsx3yql5HKPKvBjclkjpmOy3cIKIZ20rBnE7JTcC2bnCI1yT7+3x6ejBzRPpxurFpf0MRzzq041DZNKNwNGUjgnLaDA/PcE0kVNCC9TsqZhL8VT+AvtO+FRjzoomO3upJqpU8yBOUzPcWV1KF4Y8cqgm8ywNY5pgKSNLNUY80QX0QNwampOG/vx726YAYPU/3RAc62nvKlE2z/bOD0cYnFeUSwPDh2E++gxnEFx5Yu9cTgtlqUSdyTBOV6/9voRBx39PkljUFDsolr5dIAyhtVbQ6inXe3o3+szt/EQNeU9l19UuBk2qCYuQlwZZcea6wVHj/4Rlr9O5/nv7LutTIuOFhr9HiO6fskRcQVvoDVvnxn/xvY/fxSOlow6i47uqjhelv2s9eqexMS6VBlwxl5HaBHy02omROkoBps7oe63TSCMVgZdmBMh9fxzSQMxRwhlRPfm67FmNtjPnFtFRVSnNUCdujPE22zpVuoG9tnXoDjsVrzuYZRX1ifeZktU+ljhDwTDHxrmSy9bazmfwERZJaClpVYVJhVM5IUtnpFM2A5VF4AQMhWJjpkoiai57wnbElf2IwWoVUBIqxRWpiSRKdWOARRmKGc3roKyU6n5axfk4LB2khNELMzgFDlbLDLKgDc4joiSJA3CKKGQzNBbHER7jRKmFWkwBa44Fsb9rHiPwU+PJ4k8zjoayTwbc4TCr2vcgYDLO6RiRJHCZ0R7b6/imHv3rar5N32FYDTwS+29OQuqOBYNRZzVp2pijT5Xqjim97nipBdvXMgxbWhCvPdfpgTk8JHLOZoTLfv7i4Wo4XV3uaP2Iz3cwuoZBYozM6Oguom8tYquW2mmPACkb1qm1pXl3va3jiX7uRl604YY4l4org7WNf0TI4kawgS1ewQrDymu1M6814mS1RQfGPoUxptHTyLjjPFu8RBd752439fEGr66GTcSvJxF2O3eycTw0z7NxKVN/PhwvraVGxc0ZLfcUjwM/FvSvlctVDNc0YT8hWZgmS5NtWYgANSfOWhbqsrCUxWmuTyElwzNBwBzfoEJK+5ZhyFmWFrXXzkLjb+jG8/FcxrXhe0qZosuwbWv8YVAXeNx4+ZbWMGoWztUjQNOYtdoZbNubeekZo0yWgbSzeqwyGNREEsvzk8Vceq1k22Jp/FOWHaIwc2xKbkU6/LkSzBw604Bf98ZzHQzXmfFjYjft2e8PZsjN2eEzGS4MHKwM6W8Hft7xugxwmFNErAaOwNfNvHbttiD4PSuVJGG6DUcAg790c8tSZ5bnZyzTsXqGIXeY9AS/XfatvH3/DhFhSuLlsgwOT6ejnYdaHX3vgJPLSx79WovXNS8+Lvc0JmixuiHGzm+JMwpIslIfKVs6/CJKWqDQ66QvtesgWlYGQvHYti9Qa1ekN25u4KTa7/QxiMu9Nc6ArrNnOH/jH0dWJDLS03m3wcEjxsRg4hWFPdRT8JTDmVFFNdPjw2Iew1jWfzpGHuja6vowFo35v3BPcCjTfaZ8vaNqjx5P3KE8nj9H1xtEx20sbsCM9bK/dsaVnrlgfD6M6OYcZqHKlSdQJesdha+E3HPiARQmuWsKVeWO+auyu68s+sjyWTi8vacWZf701aKy37xpPG+sZ5Q3ysn21XQkjoF8fSMmpbR9Ncxf0TYm9ew2gXOD/wmZYVy/Ulwn0Rw6nGJoZSmRgcmdxujPK915sukuVHuEfGRewh3zcmLa7YzOyIn5eLKJMNkcNCDN3nD39obHL7PJA1rJt2kY34Dj+hFZwV+Dt5jn40qZMfCS/j3oQnLzQ2MZz+Fj5ayS7fflycoSTTfZ13mkHELam2W+LiZzVqf9eWfvCOen0+nJdJMp6IutSkValHJRc/LJJGZfwZ04HpHQaoDqCeYJptqM28/PR6ZJ0Tq7O3vw9+v1C/pjMBqOtB4MMCXeKFALT7WSpVAWEKlQ7LztwyHP1zY7rB9EqALPlnKqz1G70UXkiSTvjV8VK/kSjgWXzv64j2N70an1O/rpP8jAakjnU9qiDd8buh6cwuO8RxY2eup/75F7d34LCJr8vQvFs6Pi62qQ9ehgKMA75/EekvBO4b0In6RBavs3mLc1/4vT+eALoMkC0tcsUlpvI82jlzAuCna6H7YIpy1Vx2vfuh64u+vaupPXtut79QxtMZYm/2ypzua94/WB1+kYKWiztOxq3YCujR9pJbnqQPu/KWeOE7WstPc4RXc8lgSKfiLLj6ub/++ff+Z/fvwFMIeGMZ37Nn7u2vf2nPy90d1Rt/1SWNala2PGirGPWHq7afUH6PTuvMNznNDp71rmCHXrg8P7O7Uo+UU8lbv3/9l54TzQk+ADsiSKmPNRivgfhFxh2u85LQv3Czxjjss5J5ZaOJWF7Dy9umN9w5T+OZxHJ00tQxyRfY9gEE1WNPnNerhJmUWVdwr7ZBlov+Zh7imRFY4jQZD1ue9n1HnZpsOVdiSC71DnC85OqoYE4PoF7fsWZ+67m7R/unRxhuttcAFbujqf9uaKzaW5jAqE07HJbMO7zIDSslE1HQj0vQgMMsJzW6g/Md9/grYu1rlq3/+9H+Jv3bu9fp0h+Lta3/SBQjYAlkGgCoBRWv6ZFXd7Nc6n/b5+q78xNOOsBbfzZ3U1xD/TXupCgPrrl1XEbLw2tS9C4h1wXuPli8APGIN6+mVBRZl4x71+4ks6u/2/SfvWov5x1PAk2lK5C28QHlYRPMuFZ45iqqcQtQ6YUf0opqQpS7E9EKgpWeq1bJEbKSVStjp7u2wCzGhQVrW0nk2gpVIsJMwEIxH0iyC3kxODSuUe9BGBFokjtaCSSLWYgSQM6KgZHYp4Olul67xCsT0Icf43Us7VUGQGD+/K+VIKZVnsPoWUlJIzqBmNlsV+b/+VYoruWl48WfXpPEI9CIb6+V9HeI2MPCuBqT+9JmSW6kZbv6UKOfcz1bBlI0wD9R0+1mdlugPE6p+Pb9GnCncZqbY20V8IdSa0DIpFet3aUi3+oFQzXk0kouSMaGURJeseza6olQW0ewwiUD0/V4qaj6rdzqN4ql83ZgikIoThzoj/YGjVvgdxoUefO8MTgkHt84nr2r43zsiuaL+uEfUTdXwjja0L6Io2Q0kpVvO8lIomtcg1N6AVN5Ab/BdXrlbU688uyIlNAAAgAElEQVTGXFrGQRfJwvGixoRWsBdwZYgiyj6M7Ft7Qtdr1KKNQybiejvr6zvu0+G/8UgrY/TAtgf//FzhdrBknZ3P8Xv3om6v6ZP3j3W4Nji+qa579QWJyEGgRaGDUo+FdAN6bOiR4nXMxVPry1DXXKEZG3uWB2lwKEA9Cey3HI7fs0Qeg76zZQHyBCXSR3YmdpzLlmOydJXrFYybFNpZPOdC+g70WDJMWKgKEnUH7eFSjQGv7QxV5mUm5alF8DbDZIakE5M4nWuwOcC9dlivHhluEb1diA88YWM2Rj80QGZoC3dF9TlaenkiWlOlGeMkJWotlm69RrR4XSn6V0oN/8dwsPZSClxxEB3beDYv3tA7CGH1kiQdHskK5jFc3ZD0F7dRaJQY0yAnMUKjy1wtQnz739mEpfczKP6RwTvaGSPDYcP92L476+mPm0I0JUvlmXIiT+ZQmlJyfI87fnWnIyufIqRUWmaQUYnRzSyDKkKCfnQveotgDQclG1SNFEJJkNrXp/1tQuxmWVbftye7fw1RoXmoa7xa2maFASx+G/GyOu5LAtVTuppRzunk4MQVdLO99BqR2A5XYnQCSYkSLeK/2d5Yv6k2ytw6s+VMTYBvBhc67uiv064IBFcIYmcjMu60eRfqHJmTRqw7nPMBz0W0WD4zanclecNJlxQr29ZSyfRz23nTAVGPTNC4wLq+qou29WaA7xVWGJa2nWtx47SO/Y9ObjJetmcju4bo4IBmf0dzUH9EsJTps7/TT9NtnE+LPN/v9+wPBw67PYg5XTSWrVSeHx5oBcTXCNEJlpjh5wIq7GPZI8OhSMkMXcb3anPEMIchW5vk9KYcK+kmk29v4euTKfyERsd2h2wK4VrIvZhBUAe/z8x1kZHr+PiFaZoo5YmA6lIqtdAiIS2CuoNKc6BSOk1EWlkEMIeFKGsVuFkSiKZWUkQcZ4WTQAMTd8BegfBVcF4jA42ByWhgGbdL0MWMoNPOkiMvp14eohmd6MrLdp6G/jTocLvceYcVfdUOy8qOtRH9Fe0lXHd266UY+nVX5Wuleur1OCOVx4uK9u3rtz0H/bMvsjqH1/oam3rad+v3kcQdC18H+rt57xtBv3o2Av95fny0iHIJx1NleVLSnTl75NQd0DUYiCBXQuN3k1+XRl9M3iq1NHg0B7DcjKO1FssoUrt8MSp7Ow/XZ27dn+/SCoYilWNgLxEvy1MRyQN2NJ2LJiFnYVnGnVKQgoZz7fDGu7c7jqcT5Xn99jWul3bpMkRdg7ORT+0fWvReu7yhJ5ueo4+6ut2V8F7OKK7JSvdpRtDIiqJaqPPiThStMJG92ffZaHRqsx6Nr1HaKbpPvkeFI/pc0GnfVmp+mqkyD87x0rJyxvkIK1WiR9RVMcnKMjWqB/040sw5vIapmE+adWPzOWCoMuIixNfthHrJypEu3jWeurNsF2T4/+w2slyvuXdsYajbkIvGeTTQHpyl2z2GEyx/wXsfxufGIyNiUeAiPTLW3/deeUWNbGtvz8b27Sm/putv4fuXnz2/0OjUpsu3es5W368P+ebX1323pfUMJZhTkTZ+vd+z+q8B8Pe3++HzuAeZ96j+zpu7/4fHRytp8vWXX0DMuPtH2tZg/hrj+bvhXZ/93b+/EsauwdNrYXSDnf/TWtKBh/D2rXFI2MAcdm6qBakFz2aIWrhHOC0zN+lgulJgl00eX+pCDb1w4wkCa5+P6dIIjUc3/vBZLHtsUg/Ac7KvakF6t1jJW2cyrJct2f3WvKUHTm6fC5QetOi1ff6VrXMN59fj0zYO/vwea5fwU/u75Qu3fX0Hz/zP2ib4u8BAXvg2XvlzO9C9oP/MHLaQEAqdYBgHTugaqyuDP4p6Ct4R1OOPR+GpdGYRuodoS/lrk6OJAY4UUijuN+lwGyu5raUYh2BY7nH08TkhzGklgjQkkfUH9j/vqKUy/2p1M75eEAIKX5g/ZopYVO3+w5766zve6ANfxeqsbyuB/f0I6FycfN09aXOlsR/AWNfD9isiRsben1CO8nnARWZUnxSO/vwU3rExjqDQIpwQqlRusLSMULiVxIQwV+0BkWKRFrs0WT3BaTIPsJSAhFY4lcW8uETQYgToAThUZQJmEiU9wsOM3L+1yOL3Ap8NpnMWau1GlSpixlM3qFgdUCEs8kWVVK1WLE1Z3Zmy4iu1cwG4lcwmCHRXLC2LuRtMqpRJTRDy6PcwnC/zwhIGdK9HORoWU9ooem6ESSaeHo8IcNIFwdJ7tZMrHbpLidRyPn5XSDVjMnHmTCowB84eQRrbW1TI3cbKlM0wtxQb6xT1AxsDuyDsKU9WayvLniaqqYDMoGpR6DG+k1LIPXwWi+6nKJLUokJrBc2UeWnZFOaUyGmCBItHPtc0k4uQ9xkKRD3kUm3+GU/N79HqVFrUdFIl6ogv4UCfJ7qWMNYrFLQDcnJlmhDCvZ0/UaUeq19XtM5tvSyNrMFiqXFqOwyYIZQGrxENpxEh5PeWsnhty0qpC0tdmE8FLdVrLsdvxe0NguqCUpmXMkRXwFJOHS4GeDTjPU1paErRkQ74+kcWhwCi2tP4NmO81iFtZ2DuDaJnFJB0BZNrpfp4f+8gxjUByyXm0knUzr/2JKBxj6VJ16qoaEtxFw4ZpSxrPsQNGhGBsxrX6iCPxvS0+Y2eZpdY66CPFX1ekBublZUEWEiybwpC29xs0XMnbTQeAXX9bDpEnWxfg/22dnufTtDzWkGlenJzj6xEYVkGOr3mazr57kJF3FZqZZomPwf9vbW2lWk0aMXFDDyCqHbjk9pTkXpYJBTcwlIWR3HZ0pmViiaI9OkhIeYJsEQVDQ/HnAzOhxTSju9L9f3S4vwTLYJG2lhy6MaszjWB17XRGjxaUzyFqMGB4S5LzlK95q85HYnvTewFqp0eaaxmN270axsudsD/Y9r5i21k80ZLbuP1XJCrw34LhMORbjuJNr5UXsvZD/R5JUGNf9efZfifYe7O5yobuHUB3JeFFgYj0G04PcquKWyJPe8p3ZJEuv3MNJkhPafcHPzAytmI44JW+9x5EEsp6+uShnX1AY0GHYZ9RnHHEm3b3DJeMsCpe8OPkbmGkVPHYyPpG9Z0JS8M917cQzdktDWLiJF4zCfesqngEcBTdsNdgYHm2RFw7stSy9j6RZaNUm39h+iVFQ7pk7Ct8nt2e1NFm++x0XpJ0stq+5kL/KnNAB7RAAYXRQuxknG2u9HQUvlPk6loK56lw/nHWitarOyQTJMB4WhQV7F0f1rcl0Mg7Q04vYZtcwYY5wkeEm9GntQQ8LDP8bXxPNZL3u8oxxMhw/WIH+edJDvI57Z3KsEb+roICJPVebrp0WWjc1g5HQHY3Rws7W2xzFGdpp6GUgRY6Kg4D9G7ocrcpuScmMeZx5afcHOF3xd4YUHYISkx7TLTtONwc8N+d2B3OCDAlC31YymV49NDx6UqkKzWrud7bniE4JNpAxrgQ0AWn6PBXyjFattzGhwFTMaGyUEoz8bBTG/uSFqoXx/7uvjZF8yw/vz8ZKkuJfF4rOyniTQpeb+zup85s8sTVhkpN3hSrRQ9UnSh6oRqdQkzo8+OZw5r7ifQUgpnk9yjRxCx1PEpkUp1ZyXLQNX4PvVsN8n4pUAwQZ+j7EVb2oFur5vj9EbyZH2e9bqjWfASUNypwPl581BqxvG2t0HtgpeYjSdRMKeyuNEQ8YWRDnxY7LJ0Wn9xjMP9r/thfcuCOUp0N1C73t0t1l3Usd9OSluPMtKKYYpbg7wfhdbNiSefr8MNt3bP0IftxKPj8wRfIcnB+hHPEqMHP48LVZTl8RHhxvcE5q8PTOmOKQFTQvITehJEbox3w+AvvZlsPtkIvfGpnuVLiw1MQIs7XE+5p3Mh4HHQtjiuE6Q5qwUvoZLaO2KinV4pWsWOAI5Lk0RFECRHRiavAb6YE1ZEvNtY8Mw2GaIMkSq728kzQlnGv5I271d6lhUfXZRnijPTHH0f13xmzLxW0Ccl36Wxm1Y2KJxv4q84oMyPxbOB2DvrMRhhQSZYjp7efrK3edUScqzHTtDZnPLzITs/JhZpCHg+vcFI5zyVWERcw8O4sdm3sKrpKCKzaTjaFjVaI7Oa/uJgD57mkPuNt6vi9CglsojBrRvPaxL27hAswE6FJ+20JEniVhRNmajPa5jxlqpPnc9CeXI+JqjFgUSxg2N2eO5IbzJl8Rxl7lxfeUTE6vyOPN25Q41svjVIbzD3UvvGz2tEOMgaF58eeNTGvhA8s9P3IRodaHrhNxGok5zHLxGZ/tn2DAi94JvAb01PaPN8EOH/+vFH0q+/Uehpp2OUY7T3W8WLKPRsb01W1v5Mj+i29mlDLt5pN8Q/DL81vDLq3LU7fp2x7bIZLB32r7WeXKm/50Gu3v5iE3vhakeDDTU+oPP8MZctTbpKwK++0Dr4ArzH1Am/YQZ1BfY/Z0qFr0//L+V3pYgZnt+q3bv76QM/fPz11cZseMFg/sJBSMDuxx9ZfvuNd3o5enzbora68Hpj+aW2hbe/rV2YvzlP2OfPmHPGXcBrsVrogSPf0LOjhOPwE8obMiLKXBYkJR6rZVPOWjktC2pcAUutSK0WmOcyVpdxPFNVyN84TNKDUCLzrtgAuEF4FlNp3yEsCfYKSYV3Rfg9rae8U1g0cIC2qPt77Tiq6+T6WX6Nc6T9jXF3wB/UGt/Gw1daw22ba3G9Bd6NOGe4R9DumBS/bNH6oJtZ33v5/Wdty6v+0cn+E7Tp27f8c7drRG3lgHXJG2sEHBdOJJiSQZRvxu+rQPYHoe9POQxcfvPFNCRA/tEEkeW3QpVKvnAfGLG/53cU+CrKj7++R/nChFjKpL+o/f1n9q+jcjfaBfajI1kP+n7FW/os9wqzKM9qhtQp0hiKRVe1iKxpYpomUyrnDCIWNbsslupsWVD1YD7MmJ+q+U8vCEUS6eEL09v34IbWG4EnSaSsTcFh6bFwATXSWo/xWyY0aa0mYDBEJPnfhDDdC/WLKUTqoLSutbCURF4WfxaLUFdl8frqYUA/nU7My8w8LyxLYSnFxtTzejeld7T6XFl4bqscAn6XFEJRPhrIQxHR92UrEI+0pbMAHVFIPLNi5H0fRbA4cKi6bJ6dfR0OxuQcFD3OFjH+VKl30jy42UM6aYvS1mTpj83JoZhQ6Y4GyzJ7LdkEKVHFvMqjJIGIoDmjZQEmEDUFrEekIoJoZE7o87KoF9oYIoCzRqq9qEMXa6V4il4YV1gbjA3rLXiK86V7sbshvPi+afxPL/9Xa+01JS33blOwnpaFshQvW2COJ2Wx9RJVd84ImC4tZW3ZKP7G94cxwK6N9YyDgQtI6LCTxBUi0pVNvXvtzN8AbU2Y0zXsXRPcXhLort2TMBwm2l2K8mbs523fmM2LeM/3f4h1HT51OFg/Eovhd29/1w4D/fFKfZ7baPVZgNmUPSJU5qErV7K0yPQwwnl8hQiy5JUg2hjsvZ3FcPaQfeppR92GMwyqGbnD9pE2i3SWru7SEjqclTJS8stG1FEhYjOlbdw58234dz9NrSZq9SwMZravQNRABJHJUse7NKbu0FTCgWs4g/1NvjYurG0dI9NQoyl5/aYkQia1/pzQsk1F1fZEzKCQFDQpYp4/piQKI6/TM6vxKAQw6DCWrj6L5RE3Rn5nu8DInKdoSy3JNYA0A8EVA8W3+MKNoqc9cwkPyNCfbK/3//orV66ABF1Dttfsr9LxonVk43KyMmCLDqySLDXy5A6COWevg27R6KqGM3MXJwkjudZqSnLT5LqSaRy1tmVYOaD6x6Ib+FSGCHN7n2zWdYSZqAN7jYM1eeG6Oifwg4xLYgxV6zO2MpQDo0Er5ppSoixLc8CKSGNUz8AgVvHaiGQwapqTiimuV3Ys/1w1cIIgfu6uT7BfslSQnTeMvTPe19Kb52zOo+K4WVWNZi+VWk6WMSZBXbpDmlRtmSWsEm70uzPcsveoHa2eFtfXmKBza6Zyw2Ketw3Nz4c95XRCN08ZHqI7FaIgnm0l8GFbo/HsmkJ7wz31fqtFWdeDosdrULi5du2mVzU7d3FOd9Oe/W7P4XDLfjdx2B8w56yElMXXd4hEjl7WqNhBZDOw1VfLaT+iulaawOmZoC0tfsMt7W5hus3Mj4W5LFYHmT3KkTF3QOdJ8XJGFrW7qJJVzSNMzFAVGVzGp8cxmZFJzfEn8EbVwZDuUZ2SW/C9pOR1xs0xLImYESjSXy8+HzGFZV2ZVlnh/GaYXKGfES7XQBC4szF8cvm+9RXXiIzvHfsUNwwOFxs+9n9UgQlaBYR2b8edNqzrUej9tFz+/GeacQ9rnHCtje+M81w3a5NE1s+MPMgrdUDnO7fJE+UyXMPjfr0+WpmIAqRboT4/o5pJXhYjUaPymL/nGVe9NzwPR+DQHeWCjxUzXGpVk9ldvgrcPsIMIj2jSyNuAx8U0xJojngxh3EVWhYh/Mz1Ug5Ij6g2nWDQq5ifydMpJ6aamc0dZniT45KhLEL17GZt2b+7XT4nAPo04nhZwfHqAV+q1Zk6KrqzccZ5F8W9nvXsfY0/UsMp00Ha1a2d8FuOMxf5THvwzKDR+BMU6jPKHilKmZVFS9cfJGmlTfJG0VNQJnPpH7h2c/Q+4fqqBHu5h4NljkAU7sKB8N54iYevhj3X7ImnZ7cztHv7tjm8li+Vog+Gk/T2bE2/p/0VeKn3tGLG/2Af11vovNsxcJKbRbASMW7odnnr7Yr2Wur2L2LH6C22tnc//cjXj7+1aGNBeONwsjIwu2z5SXqUcXfEtJe01NXfMf+wEWyNa+36aEPYEpLg1b+xcvfDjw8+97+rjXpYNvTmr2qxvJGv9i3mFDrt/gfH+X+3+96qYdH04w9M065VIvq72ofOAgLbMLnrLeZTMBj6M0b0/4x2aXjb6PcoVXA/pLMRzEC9MtQCN0V4EjW5jcEhXcQdOBO3u8yslUW7I0zj2TD8HlmetrJTZEpd07LutHJsukFpsnRktvnUNlEaks/qOsrhbIazxra9Rgf6zTZO+I91sPoWbPU2ynuUqy/t8V95hv/dvt3+aQzo3zoE54pJP6CDYnqMPLnohTJSYvqfUYFh1DJSCmlTuqy7kIacoovsh3/71jEyPYQDGeazVdxvBnw+xivc7fOAhASaojZhhvP0IVGl8DtfXjykI0Pzu3zmXoW3P/8Pvv7yv/g8uAKeMfzf0boK4o88uW2vHIFjM7lEcS/AS/T63LbAU2j69xtMtAxifoO03U2Ip3jvAoeIcEBYXPhsSuZkNWgthXtilyemPCHZ6oOIJIqLka1+py7+nLAoeChsS7sleMo/VaZ3b0layV+f8ATXPCYsUrkZ8Cyax+whPUWX1bUVEFNsi2uahB5xvnyJ7x49oZjiSBQthQVpEYLUSq6V09SzAMyzGdBPp5l5mV0QL203VPFUXxYtnBBuuKV4Or2ksJMbZvVInf0Ny9NCSbPtWTLP6Yg4jxqnBDMdx8qZhuJGoRQCnQhIbjXVrf4oFqLpSotRGWo1gyvCRA0ocFyye3PL8mhCuTxnRHaoCpUTPFVThNwY/KQDTMmE5bTfWaTKMTHt9yynhelGLPJDMktZPAuAUtIeVJh2OwQ3rKPU2ZQd4mn8oqZqWQopJWZdyDVZTTRVz6TR8Y84k1ZrKM6NPTKPf1mh0AY/GjW2wnis6OzpLKUQ8enNIOdsR/Ua47aOUV+3K1+ihmQtXifSU9mbwdxSti/L4rUrS49Id/iNfa8t7abXx/VI9lIHJtHxdqTObcphpUVjhwFpFamOshSvkamF3TRZyn13QOg1s00RXH0cDSYbOuoM5IijtjXxpN8eV4fx9v2Yh58VvDZvf3Rr/hH2BkcuqrT3er9Vi5Mp2/ja0pd3B5a10mWYxQgbYcoPXDzgZGVwqniex4fpGG9NUwxEPV0zQMTWhSY/BXyXlbJnOhwMTxwrshfSvjPWaS9t3WqF5DHoOoyo1ywcFIY4/R95lVAWq+HWiODf2OV9uJ3f6FVotnTPJR3H1Q2vJRrcH+cjOVud9YB9eyyiuCFlKx2SkpCqKSNLKYjUppytnkJ9rEW1bS2VcwXJOI0D9aiSnCBLIkv2+rF9nxGPNG7OPEAyI5lF/ycrOUFBNQ2aNcfvaukex7OwqmfW8loOnIjEGRnn0Pf1Iuvhjwcv2oz4DHvcwCdwqfrrhvE0wB3GrKsfzvdbVr92pwOkKQSjh0tNhv9Bj4DU4X1huJa+RL3Dxn/XPrwVax3OgdLGnpLVOp6y8TU5m6NXTlH32lNHemdVw6vc5ldxR0NZY6nVmkcErvazZ/fYiYsSBt3I508nIZM7rm3vHibc9qVPdO0ERIOBLcA0PCwb5cQwX9RqwoaxvJMT77FivKDXQE8pOS2kR6OHR5Q/k7M7xgw10kbIkWyZbko4omBG9XAmE69B3c8QbXyjcqM502ifY5iq6/DGKU0EZKaUeumiyQ3oDo+1VMuQVIqfeWk8QchdikBaLNobJaV9h+NjX3dUPUKwNloZGWtGGS5a0MoBO/QdjUMQx4S9GepPHc5ExZ0JF89mE/zW2hlKkkCdDTaPOx+nj3EXZ2qHcmJ5ema6uWGpR/QUY9sj7FBV8uFAOZ5aZKop/rsDyBoaY1bjgR3hm5adIYzn2fdo5yncb/YHDjcH1B06TyfhND8bTAhYiY7MlO1zeX5evyeWsXaZGNkz3YTj5+T75yVRhvFpxZxt2sl3qPGSV7Uaj5huhJx3PD58JsuO3e0d+nUxPkVBF0UkpCKH52y1zGtxdWVKLdLStj0xcQPg9bGDAMxI2hElumwNDcaJjBDQ6umKw74AkVdY8MwL6hlUsmWIUk0UPLuCE8XuAOTnzzNF9YwV45kd8VW0CwQteEJZ/1pPS+PJ4lRXx59JhJwz8+nYzoyOVvyg6/E5cLKXwmqlVVSMF0oRcSuY06ZyyZDeIsFF2nsvzUm2Vy/R8bNlOD8t4+NnfQ7fz50kfd0FFgkHxYGq+Ph39mXFQyjOpg79K0/mSLHiNdSitYGkB5IIhWcUcZiB+ljAZXJ7zx3cCseHryY75uyl2I7UVJjIjn+EyrPv3Z75q71z/3Zy+lO6zB50JAbrtL/BrM8xZAJ1a2ZLLb5ZOiczjU53VZzL3QyRtY22WeaSnBNVk/EQns0hZXM8y5JZdhldBjiV/s4WTQ2oCvnQ93U5Ou07cLH1yPO6goszfaQGj2L9tmxTGnmtrJVn62fR0uAFQI/hoGXv2N1MIMLyvJgYFeRYTwZvZce0E5hcdhGjiap22JfT0QI4XNJTXwwd4VG6ETXkQCv7ZTJYDf4DN7KGvF2rRaLrM3sOXqdeGz2t2s+z+0Y2R8abJCQOTLcZtBq+SYnpsXJgcDa7w/VOVoJwefxKVWV394b6tZLevKF8+cIP796jX5UTDywBQ3LPzBfmhwey3lHVfmuyGI8sIjxr3YLo2fezBBqhK76KoazdOnp93p6B4UNUIb18w4V2CXGNyH18VvoBCHpqhnK1TGWhMxIQ3gOfW5a68XEznkuLlH367Xfry39/Z6/gi8sabwMIxJwnRIT3oVugi2oPTj/vO+O1amHA/pzgJ33PiU/c02ugj0b0viTdeL6KTEdbLfW31dbhy/CeMQtrPDVmJnmLpbJ/0eHkqmT2jeb85+i8DgNdvfqeVxA+vz2iuuPJcAZ4/OUf3P78M1P6icIvjW/bffjReBfPYhGp7JW/tp75B4Xdhw8svxamnJn+4z/4n7/848VnYiyJNY7579wuLdnEO1A48RkYdM5V+SqmtY/nJvXU6GrOcyFH3jgBTVMCySzO32ZJ3B4OxihMWJlXtzVIhNv4s3MpTQRCIWUaH5hIHOsyyJl0OdG//qCwV+WLwEHMVfaDA9uioB9+ZP7HRxbUM+Ta82+qDg4D2uCqcX4b8O7nWZ2PWK/qqK++vPpXb3hdG7vZsjbCN7uNPWuZ9AJ3/7v9pe2fxoD+lzZn/FdEI4jZFaImYvjjUmCFQXIXQv/4sK6nlxgFs9VbmoTwcts+p2fXX0vI1z09CMgv/5uEMQ9f+Nduz9jq3MSFhsh7mzlfVRGM8RdhEbiVTE2J5BF5aVBwNgI0CNwpiaf1VCoFihkLHrAo+VAGhuAT0eXmGZZa6kOAu2qKl6cmyKemWJ2mqAilVt/PiV9SF7ycITEBU/FM1SQ1BWcTcGtPcZyS4GHspkRCecYigecyMy8Lc7GoYTOedi/31uVqD5645ZbKEyLwrM/hP44I7O4mludTI5rb437pSKmn7E05N/qmmGBbKc2hZruxI2FuXvsqaBMvJqrlLOT49cnT6ZlSDE7IrfsKulJUnxRuk6c2rE3ARkH3yrws5ClRS6KkmSQw10rKglCshjA0A8pUM1o9vlyrGyBCGDKYUs2u9JpgKWhS1JWR6mtqOi4xQxoQ6ZY11mVArWEIDJHR9O+VOmtT+FmK0S4o1bjHowqakN4U4G5kbynbSzOYq0eQh6G7lNIM41ESoBllxQ1seomN9rEOY4hc1LYEXTJoJGbTwuhkCh+v3avCUgs5ZYvihZURAgaydAarrxN8VrLw8OzFpy9cvHTOZPh3UHmszoFyThqVQVDdjF9XH9bjW0eaK1sDWDeer1vU36uXDvaotFzhVfvbI8ddMXwczD0nkMOG8W5/y0oQi/Rzq3sv4pkrkegOm33OoSincQ0vRbDHmm/hoLE8qDvcJGqtpNTTPw9L5WtkdAmKGdxd0ZAkait6WkYJ55Nk/ak5QETShZQEEp4Rw1O3x1/xWoZiRvFa/Py6cbDJXxJrPvJzsYcJCc+eUCwGLWyrMTqXxL53/BPPnG3GN1o7568UapI4fZSh//FR6ReGj230195yTRY74z82n/XKg3JhDDDsB+vI81BaqzsIhI9ly2bQ9srgxTIRRBaC1NP0p/5mSVHz14DXxiINBiNKGYeLedMAACAASURBVEIpFvvobk9VV+nrAiJaBhPMsStSZb+EY9eZEIZIlQu8wMU24EaJBRJ3OAuv/IFvWj3XaCduOLafqkfij0Zr0OFdw8DGd687bz+rWPabiuGgMAIG7EWUfhrwk276aaShnVZZiVqqpqwWxOQsMIOnG9AleSrrJE7LCyygy8JSZqf34fDmvG44QWhpBld/M/lGWr3fZcEz21w+7zriiFe36OREOYGwH1ZDUbF60eqpXnqqVOP3egrg2IVTh1WtiB4aHrO2Z9uUE2AlS5JYRLweT0aHAl3qhb0af7/SwgFmdLoI43lKiTxlppwt6xSQszZiE7Q1ZWkOAUmEIo49LjJO+8EZc02TCJxdDTZFTHaYptQIRPChxrKZ8q8qlnXLHSdKKP/O1jEMQCdEk5cnUHBerZVdK4UdoFTHVwnEUj3b+ArogZQsn4/U6rZzgdnenO7Maag5tAzZcDSIp+MW9SjNQNhnvASd73UkseGoxs22J/q292ur2xo+DMMC7f1hwen74wbfIdI38P1qDwemuY9AWrrnxmOucNf42w5xI7oOv8adHWYuA/U3QP1qk+HJb0W6bbFrw7cDf78P/gphHpXM276G6yOZ1vH3FRLb4nsfgd9WFODYSq0ZLazwJGe4sEeeR2cjVjsi3Dq71Q3WZjg3mT/kM5IgKla6oxl7BMmpl76Kl/u94vDhJ5amLasxZm1r2eHNhilYRDzJaWpO5FrtTEpfoZQyZVnOmPXk/YyoSVGC1WirkEbI6/siq3Va/73U+qnVCzfrWW/xbwTGtHrzdPZB4tnRY80/JszwPGaGEvGSacfasti0cQ1yyoiTJXDRBZrZonmJjHUdH4V+CiAfMjK7niUy5jkuTCSPjrQTNN3cGn/Y0u4bvHEYHPqqol8regOLRqS566AeFuQ2+rsDlHSfyZ9h/+4d86eCvlXKZ5dD5NEzUMR62H/HP4RBXt+UF4znf9U7Bn79Klb0gyXgNePDkceo5MT7FjmaXX6eeMfihr2OOvpklPDp7O97532XYQwBthYY5EEc9KA4ETNe3yvNwH2pfZRPqzrZjfw0GbHzqO338boYl/Y26N9wjkRk9e6zzHXDmYm/f0WEbOgnwumI4Xx2x7XOF/+pdzHM59INfjaFbjxffi1UfmX/4QPHX3/9y2H3BwVz3ID8IQ3I/+U20k7Ls/f6qPX/Lu2tQuEzmXevklMCdzbjOd2JmVYuyO7LCvcedLE77CjHQikdP6iXMomyJ10eHz5ffL+/J/QCCHfqBa3E5J/PAjvpToLhxHr70w/8f7/+auVHBkC6145LoE1ukOu60/uKDz7jl4br/Q+jTui/vF0WVM5TW/67/an2L2NAH4nbtbb2MnMk4IQ/CE4nQLAW0uy72Sjj2YhS7cTc3gMra8dWfhnGM6bw6kJebxHp2lIqx8gHhfDQ4dk74vtXN0zdq7PyPsWigspncv4f7H+A+9++5RU2kk77/EXgB33v6V4/re68wKes2vZ79P5HvcBk2Kv139chlqC728iM7+pV4Nn7CeblKH3FRmHqxhUP6lKfJOFGTIFy8O+hbE7SO5kcdtSNBMmN7dWJmrb0gcoDyi3r1IkSAotaHZPp7TtSXZg/W033mpxARg13MWFRNSGSyckjtjAFyT1Wz2quweTS6lGnSLhaI7UQaPHzIZGK3eB7EfH68WYot/RvC4vXJgvDpl7YgR3GWCvw5K4MN3JAeW408unxoaWvsbeYQXlyD/3FUxNXehSlOneegoAOeKJG9L/2GlwinnZYoFRTlOaUvR/1NYu1sJrDqUUDTbSIfpT6VEm3ydzxjorc2BiKp/xMtUdYiFhNrvJ04nB/56meFzNGVIskl3pCq1D8/OtkyojMjJZESguIeMrUBFWYkqLZ6sAty+xRqN25IyBaXOFvkQczQkS4MeBU6Ib3jq/K0Wotq1ZXdpryJiInRMJ4nlCK19TTpixtxo9I3b7525QyVdFSWWoBDSNhjMk4sFDqRi10M9plP88Wub5E5LLSzpUqTCl5elY3HhKMW2mKFlVtURc+OVsDV8iiylIXDvsdy1IYDZmiPRoh2lYpOjKM2+vBOo4/re7T9bVtWqg25E0KzcpamVz8HGWPMgmHgNj/bVvNQTczauvmd47CIZvJXBiv4ukauwoJc/BQsnv4NENeCrNq77eGAArA7L0YaxUKq3qqfskwS6QDRDbCZuzNQL87v4DhFO3KJxElkyziM5ZQoEX2trPE+JbWd+dJ3LDZXhj36LCOEEqtyLbQQa3zJiGAJVe4TUxUKV6nUNGU7VmveyuUIZolaJrhyai5nHNuOLIZDop6NG0m5eqR7TrMzcYVkcmqZpS3CHpzzKp15IniHJlxY8VuiSnsLd0pTQndYekSV6X9F9nKYTIIYH6v08Tek407sg9Ebb+xo3OOcD2exkvI9rfhyXFgEkMbxwar3OQDo7Z1LGn8g9D2qq+BtLIqLROLuEHQLedKxxHh9CcNxytIsmwqw1g0hie2gIIp16r/2HCBw01OAQ+2BiqW2jv209ie2lMsiwnH5mDTFddn7qwOs7ZcHonzgrzRD1UHjjPlVSx/8vNBT6EXjwvasqwMHWOj7jJIGMy1astgMuKAEc85MfOo7vitQ5VPsilTWlYJLHtDM2g0WmOPpJydxi6N1gWtD9mrzQ3LPJEHhXhbLnX84PCDGJxoFG1NNu8SNUjnZWV0qTVocm68x5buxD4HfImvXWQiCAcGkw97lPO4gxf1KZujZO3Udsw+BC9pn7VUr9ftg1EZ+lFkv0eq8SQpeJ3nkzkgiRl3T89rWmPzOyFygDhvuwmZnd9EWBoNl/aus0m2ia7XL/BCEjtzkTFg2k3kaSJPO5LDbSnGS1npoESeErnsoBZqXRwmA0/1MQSoojOw6/z/wOModZCNBsPNOGT/PMKkAqevzyQOxiMgkGCZn9qadHh1SlujfqOVRAJzIi4IkrPJH+lIcqOeiEW2Jk2oR6BH3fvqcN5xbeL29kCeJk7LTE6ZJhs2I2OhpmrlnLJH0GplShYhXE5LX5/A9T4XHeHvYosBDWNKgxE1cGWUOljpG3TVv3gJseVkcJ/ShGrpGX/EzlTEMazoSvB5AroDT9TlayUEdrbhaptbHwttfwfy7obi83bl8qtaq8sdR3nDMYyrLU6LfPV8XPZ3dpocdHRsIuYesBdzrhe/thdpaCJ7nwsM/PEgZwKIUjjSlda0Axa4WfSAAIs8Ec5b5iC/4YTiOVdiB71VeQZuWB6q6QsOJl8i4UxhMFa1kEqmUi0Lmi9WXUqLXq5Cq6sqYdyNdXLGtGXz6Oxz349YTzvF9ltkhivVeWqXn9VTsi+lyWGpwb4GA9J4w1jf0FeXYuNOO9cnJIOE2YEuyruoAk8dSro+Jr6vW3nscc62Z5F2qTsPxAxxXsDVPqhCvrXxLI+uZ7jJMA/ypENiOqzhsTwXVE8+Zu9dK4skklaTcwcSFevuwozzRlxvTsO25Q6X5ydSztzsb+zcixv208yUhvIXMWMRpmnPPJ+Ml8bg4fT4wKR3zPpg8gAKX/Esb33+yiPy9ZZ8D+leDN6SO+1/eaAkpX51vlRqg4cCFuThHESciUt4aGzXluRbOOhbxnMRqJc6uTaQS/dtN0y2HBPchZev0HymJt6TPwjHX39j9x87QKgfUzPKHX46kD7+yMzv7RUP2N69U8M9nxyW3jrNzzj8jljV13flmOtT+8HP/CeBr3FEhnFnv+9dXJc+ZVVdGZ56Ga1Yu0AuwyI6c/0lLl9kBIel1NCpDnrcv6Ct6Iv0//ogz7f1UrvotHilfZGemt05obYPT7989D3/idPHj5RflYrVuL/98BPzrx+5+ekn/tevH4G/Nl369CE3OePpl48OMy8/E++OGugbm+zVNq5pRLH/V6R9f1t7JpSFz0gS3gL75Z5f05fOg/jY3jTn53GujmOJIAjhuCzcTJmaJjQlqgjPpznIUNPf6OAwGY4lCOySyW1zLeBZBgtdBxcZXKDzyU8CBwRNwg/FdIefdvbb+wq/J+H422+mu9200VnmzZDkZuXQHvTJeZ0YgMkDsj7DTT8SFwIH9DX7ntZFOW3f9dLvm7ZF32snn0Bi6z0+l9T+3f5o+5cxoF9rTXEj/aAPlHN1H9v72o+slSLDo3LxxrXi7bXA/KIybtNeOiSvOUBC9+gLRGrpnP9Ym/nMnnetFvrXf7ETfDsQlmNcvLIGI2w8iXIjwqkxjZaE7d4FpQMDNygmlNyRmJ1TCmNDzhOTWjrrpbjxrtaWsrQAj1Tu1FIYpk+F2CyLyLI0uXJn9ZzqwwP7lHiWiCLvhivz+E2NgaqLpXEKZiqUkVlxRatFgFpdSlqa+xW3Jy5ol0JNFg0ddXhLpFR1oqttLQahFJgvqIcSqaVwLxhCdFG4RUte25uwNfXzdGFDB8F9xDM9FfymX8WUAbW64sHrzKUeuVe9etfoVaoIcoD6VC2NezLRt+53TXFuxgOhVouqLi5wZJ+tCViLKbOWpYkmUzJFXEmZ7A4bVdWjQQVNlaSFqhOqSm6R6m6saEKzGdXqqMxvNL57NuIGFIt0DY9Ag0PJZlCrpXo0upsIBEQySQtlwde4NMelMNgpXvc8/tYwomsTemwbgw1KSHjXi3uvu/YhsLkkE6xX6LnxZa6CD/jUqGg8ev2ew0EwcL6zzaDjXQFwPM1NEZFSajWmY7yrNjJWMdALQt012qArID0f73mb0Ut3DC/Qvkir32LO/ZELC+Sf4x1tGTddxj3Xos/tXru5qqdqdOO5pUgNPOq8gisNrkUjNi941myBTK68Wio6JK+T4b7Ae2e8QVuX4dqwHKMXvp2T6NTZcBG0ekpzUYTU+xwWbRu5dK3VWmyN2mvXs20Kboc1S7c9ovIO+/M8U0oi1YpIoUrT+LW03CmZw052nOb6MapUdBGP3GOYgzYjCAS/ForDcCw4h921EFMb3kFC4frCopz3crFtuziLOGC9B82xIfjUNp+4Pz4P0NFlv4EPPXvz+lMzUl5wX5HzcTWF96iVEbpyaVBOt+9CpwUr48owbgnFJy26PJTbQCsdMkqDI+2QMKBo3KMdtzv9JMV9QlSsFcIoavfV2mF05Per04FY24bfXwEcK7mhiwIwKPhfao0navMeftvKJRIOH0EhhzEIF+gDbmz49jhelCBGparT50YHwgnQs/q13pR+RmHYu+iDpsBLYZzM7kSTzHFRqr9JAK2W/UgLtRRKLdSk7pQ54m4fn3Z4XE9Th7GNZ0kb3zfOTdFGH17brm57WDha8KVsfr4yZu+0HvUiSG5pyHQ4+HXHLafGgl1pl3+QC7+ICNPNjeHxIXLl/FlPxy9CnjK7nXHhtVbSDIv01PTV9zf4tOhO1GK7A0/X54ocHPKVHrHfjCva+MyGShxHLEcrPSX7yDBjcJJkBbYDT4Xz9457qB4Ibqu9lIIglGVBpp3d4SW0TKnoa6NmQNdw6nInClUl306owH63RxPsZWcOav5GsqUorkDybFg270qqznPWcOpcR58REPANJf+4X91YMDjKNB1JP9PmRIfdX+1s1Iaf+7oHfxWnZ+yv4abGp7TL1qbGwcDRcZOMkK7ADmR+Ec9uVD7DfF+FntfrQyjcw3Q5zHfob4tJFecF1NfD1+WAu2Y2MD4/SJG5Lt4/A5cyhTenqnZB1nNsJEZWk7dMTUYxq2qzKTWjbcwteJZ4j8Nwk9HlSCX1zFNJLNuCOzc2nt1htqi2TES1VoehoL2A8+uC0RYljPHu1NXC5+K8WwkgCLtY502Sn/Mqff07MlSWYtXPY8paegYbW8r1OTotlkfPSg4JS20Uw5b25CvtCUKitvlaQ9hMsJxDoq6udmq7/nsOLU773FgfsrSegrYpcOp7/1xJt92ZTjk1OFZcf6PaIts9icCq2f4kqNWrTkgrCdf1NcHP0ZxVNZ4NHg9hmjLsPBNeEpLszDnvBLvbxPH5GQHyFBodW4PysDDzTKUy89nStqvRFxRKlGij80rCV+pnIckdVZ6bHrSzKWbUqeClI4RjZK2LuX8vEvmD7cVX/JkxDHznSy8bnQhzoGLMQerw0weE1PVzPqSnXz9y+PCBnfxM/vgLn8SiRS29//kr4/xHy1gkug6/b4cWBvir07vynKUjFx5G/npzFNeBd8OZa3Mc+Ez7Yd2NqpeP6b/9bU314jpEMNVf0aLO9JbXHJft6eNHJt7zq/zeH/z1Ixk4ffzIT7zno1iw3Z8xov/oLPT+w4+ICKePH5kxPe/vr+wzjOfRvmeV3uk5vP5ntoDpVroP+1vkCz/WXj/8nZrjQ2agFcP9oubEd4PJiLdY+bzU8HZkq7UWTtDtTAXst1My8EUxNunnMDQRcRyqO6YXYMeQjcz7+RQypdBo9sVo8qF1PL9dtDUj2L42xlPa9f/qdh0W/xsM7l+g/Qsb0Ecm+4IRnS7IbBVccvGTNoIZkY+qwVBEBBE0Zaz6AR7OaiCcFw3lV5igUTBeIeyxryta4GssdrwqA/N8IufMXn8A+e3i0F4idF8Fsn4i0++5LAq8rl0TJ65dj19DrJDN9XNyf31UsdYArZi3Pxbq3S1SFno99FWUmWy2aLh/3zh0YVfVjAsi1KQ81speLDbi4L290XsmNxPfkjglaULhNGVTXCyQqlIoPWWaaqvL84CiotzXL/D5lvxWWiRWj1BVS5culSWZY0Vyj7ImtIoZcTOJnCpPVVkQbjC433m1rGeEN1gqXnVjehZBPS1X8v9GoXqqhadIr10WdCnNEz2E/uSGm6LFjbVrojdR2d/de70loTwpi3Yv3cnPb5HKgQMqS9vmSA1uxo2uQCpU9jnqcNIUB1XVBHYRK/EgoMmU9DjjXTEdWKmCloUcpnzJpkirSrrJyCyo7CxyUpTEAk+VcktfpydF7kC1IpbzhlqrrauAHHaUsnj/ExSTa9UjOlNaSEyIO02QM6UqUyrUvLO1VSUlj8ZPCSnCNFU3PlqEV07JsliK7avFnw7wnhK6VAQTgkM4Tp7eXURZjtqfkdTOR8rZhNVaqVpMme6eh5Iy2ZXPZngOmLRbFEv5XF3gt//C6OZZDDx0I6LmLS1qP591FJDV1roZxkORQD/oYcQ5LjM9CkD92agZD81ZwAgJ4nVBVgopTDEZ+FzVAFdkjCLqigADuPCOHwVBaQAfNrkRE16KPJft9Y0Cx9hbiGrpHR/bGaxYdGLDF/5kRJWkAZeO67tVKaHjOzVuGYxlpiweDefX6IswRO2r4b/GnDfFf2f7IyIF9cgFxnWL07+gZDjVZjhQFE0Gj+rMeNR6KyvC1U1e25roMu5dPDKQ9bY1dbVhzmco1EQVi/SzcSVqjTgPQLRF865YhVEacpg945XihjDcic1DsiBMrSZ5CFe9/rXhaKli5R+cl5omr3UdaZqbpGV9L3VhIbyFu1WuKdfV4E6c59JWg7Dv2dm66erPau6jW8dlY8P5ueiLJu2rYmxDSgNM+V+L6h162fCdrdd2RkZxdGgbJc35l/N7+9/hXtncEzjNDdBxNJqiWeIWWb2vZayITCttLrGqsQLdaCAOo1EGvaeN96jN1P+uhG2lhQs0Jbuf6zapsDBVtcwlgVmbo5XRBH/U6Dh+hn0MbWte4NevG6VifbSt4/r+cbf9Shj+/XwFnAdej6F4noeGY4I2yADs/QTYQ0F/miLNnYfE59rOygDKINRiPELKFslWlqXt6yXYrSV4yTVGV62t65FHcDKO6kJOieq8onjmo9xgxiIkRNWMl8lLsywLunR81U/FgtXmU5AdUe5mjF5rMBD4XqThrGZ8d0IUMLttZ/u5hYfx5waXa9gIfNHWckXPvZvjyec4tTqy4xhkb8aR7auX4wnZQZJdAHqjVZ5TicSOEmG+r2m+DrvDLTkldrs90zSd4xTfk5QSx6dnpmnHUgvTbqKUQk4TOlVkMVxZw5lSjZ6IQr4xJ8758YTqicTBHIBvUjsLEA6bY+aW0WDDmp/YdZ6+qrk75xt3NJDjcAS0HYqmP5Dsjo6FlDMTxWWRPSlN1DojAhnzKAu6FurB6faO+UHdIVORg2fAcXy4aGEisd/vySmxhPMnitbENJmhXpMhzKqCJCiLOYzCJjsPSjP86yAnDTASMGRgGXgmMdYqN1ZSGSxe9v7gS91TNuQ0w0GRwcKdii/Qz1EBOnBFA8rdEPCDwKy4p8VALwVlP/Q7BysDhEJ2+/aX4/FfapkbH69lKyisz15wpTGiEbUKBu852f4BnJrStuP5GGnomUYcFN/nyIhCnGmXZVa0J/gxvMxb9Ks95beY4XORo2dDw43oqe1hkydKhZxXTmhOOYlSZ8oTNSWWh4kyV/KdyTkJ8chyr4mt5hScSIaja0VFWEox3JEjtt549aijKzmRqkWwi4hnW8NKlcmYuRFzCg89TixWyFcDQxh+O3GGquPTqoNDbJrIWZnnEV+u8Xg5atv/6UZYnkGfL/GOdI/ccWiYXqKVkOkbzOLhGUlunL15bM/BbR+nZFTHDHmPCMJcpMMSgyHkIB2G/J0hx4JJO8lr9SnSl84ZB0vlbTRWPVtAc9gUGT47GcLxguNY9cx8Brf7FYyLCMwgWci3CZ3h9u4e8Mx+DU/ZGGotTivdkd6zaSnGbAxV76wUnhvH4dHTjqvJaxJla+C5YJGYGisam3aN/+v7OTbdXt986Gz46/pdyzHyIq/6Yguc4AzntV6++n68cRSswMIXll9pbE3H5hGlHI5WFtTxA+9AoOonEu+oLb27tMCr+9ppwKLw5uefOf0yM/OJLMInMX20tgOyWRhvYez9FP1uljWzxqvrJem4YfW79te8JdLGdyy/3TkRaXlZWzdngulf0xp//51w0EXEQf9xpbUMtRKp0/t6FEL/L+D7Oj73g/c788n374/XQY+9nXhPzhOP//hH2+fXtvdq+DaCwRb4rj7+K6LOx1ax6OsfXZb91GQLQHr687sffuQWOP7+O6rwxY0UNwjPoryZMncKswiZTJbChHAU013t88RehON8aqX+wLMzDmUsJ6e9kanZ6JlFoluwU7Loc6cJkRUoMPC+JnZJqMkySWSGQCZG+e4ygN7rGgX0TCOOlWR95MbjEjIgjOeh3/dn2hZfX/uOdMcDufS76mp/Vysh8g1q9O/2ve1f2IBu7WJEOecH6fwGVmc0ItTHB0NxO96rakirahdoxi5fHuwrJsQ11PHHWw+CsAFcqx/zGmIhLzz/R9q3WdS/+g1dfbJqVy5He5TrtVOu8XcnMSP6M8ptMQb/OVt6xYTVBFyWyj6bwe6BL7znBkmQ5R7k2VKuuJE712Tp/caoXqcQq5qmqiyqCA+IvrEo78Wid1tKsmVhETEDuoql+pQO8+JCrwULJarn8ZkEEGXy+qV3YUTw+yWEeI+at+iVjITXr4+31MJSq6XcIryohe7KtqUe67a/u6c+VtKbTHmsFMGTtVur/l940QYjXumpfNr+bfhRHf9Kd6qIeVraQ48WwRRcKQstXiHme9Kg2shtpOCvqJoR1qL23QfPFcd9Cw9NCVDKYgqvsjCJRflYdHeilsWF3slQF67kqpVlgZwFVEi5opqZJFE09jw1RicEoJwm7xs0TUbwJeRo7TgvCdSCpMkjAkNvkVmk2FmZsYVNFXVFaIBpZB8QN3S3SAcMBiLdUKku6LeUvEMd1IordKoL971GupU/cKUJof6xzW7KfzV4bLVkQzfo/3YlwyUgXF+rrpgIb04HlqaoF4boQDVmsaWrC1oSteUkViqEx0HgGTk+feGAXBmqXvuhNWm/9OEqyoywRy2Do5+ZkQIOTyjd2BXjvzqkMGZvrn17Vv3u4JKH8bfZNEW7XW/p/RxWmuE/FIgEvECPV8t+vQ4e9fbvJc/kpljejEWHJbpEaroR+MLsN0iq1MqUc5MQWmR3GwNtXh0C+5owCECMSjBfB/EolJ5+23GddJzRUmRjGRZKTS0jioiQcyJny2QRhgY7pzGOMR5QNnC6nozNLYFGyYOY+stnYGuYvq57uH4WvnlVOv5D1uNJbnxQT8kpGu8Sf67jikvv0OF6FzQvj8cgrplI/N+1wEjAiUSk4SjODcDp8xhcDvqwZXhDy1krjWwn03BbNFg2Z6rgO9JIT2CAO+tRR4Fa8CimiFztc9LkxgG/LsPTsaRBUzo+dmOTo86IHLkGP9+HhYJfkPU7WxuM2CvGRoe19Ct+T8BKGNK3SoAGDAqapKWdHwFlhZsHOrNKVzmOyH8yvkSbPH9ON4J+4vgnVmyEvri2WYlW/1mQafJyJ9KiD6PWuZVocTwTA1vhBTM4WzTymMnJR6jhYMpZm8TScqOgs1qB4sDbAx3o4uC3YaGbCnW82J3KBE+XLI3u9KmMDnOxPcPZY4fsQT1ldp+qtn8bJIVSydOd1xbb+sqm2mrSJ89SJHhJnzC4MdI5l090MkM75lxaSkWZzAFVFU3aeINM2mRx8j4HY0nDYUGTnCe0KNaBQmy2Ro9+ZvYDjdPgY745+c5WaY/WjUxHWfYkmUhpAk7m4NyUYoKkTLqraAF9VmRyuQrx0kiQ8gSI01d3EXDkMImwZE8BrwsyGsSarDCO9wX6J921a4Vn2s8dJxhd0GYob/jG10SkOymuHWdY9T2qQwE36GrDxet7hqGNfO1OeiT6sC+BWS7tYtzdxtxueWF9Nm3MjdLVnC8/PczUvjceyq/5vA7+d37NMfyGceQkwn7gG+L2yFpmOMD5sDb/kfFZ84vNyT1+VW1lhjQcPCQMr+rOEpXIz63uXC0Js7rVcFWLJehraUZ5w8lVLV1doO5R7yZuzBVLKuWlIUyuEy8vJuAKCcdDAburvuIftWhlnH9Y3CGvLggTGg5GCnUOORfSNETnKyzPdQA2VsC2Ph0dvrNrjqb71OilaCbVwvHxgVCqj7R9q1u03p4wI/oT8MZRvaI8zeseEAAAIABJREFUj28cPg/wLDEcdyJz430wxCETS8hHQfs7kCB1yMmwkhUGZ6aB/23BCUjDc+LIuFYlUa00xmyl4FI2PcTuTVdrJzEDq7iuo/DM4rXto4xaONdFYISClwTwKhwbfe6YxS3GbZn9aLhfWr7nAXd20nq1fQeV/e72mvf/+XdsYW7AqUPLvHPfkM8odpYDhyQS+UNG9QPLr+fpmNt7VFfvOPzHnvIPEN4Bn/kk8NaDcgJ9bcdxbTka1huAf5u1ZeRjxs4CVqsqD8G6NV1O32PTgwtvqv5l+vBXt78bELzF7gUW/JaN4HehGc4FuPnxB6bffl9l/nmtUToDuw8fyDmDQuY9YwnZb7W32nPrVWwurzWe/wEfhb+lPci5U8i6DfzNSD8Fbqt9foMwOQ7FM4BOZI8dtJ2NslHhfL7ivNxhT0itxNLIvgXKj8DTke+JM/YDdqYsqO4HPqdHJudnmzVD+qPB7wbf/2J2pc15Plsh6YGB17oJuvW3H6vt4p6PBAZ89B2VF/7d/kD7lzWgj2dlJIyXDOoyPNRTi43yxMhg6bq/FPdKQziimAAR9Znae+SMOG8PS9TDjKd6PdTNjapNefp6EXCQHzbXl08LC4X840T6ffvUtbY2j3yWXg/kte897/HP/X5+R6yOnF09v2foo63thrnyO5pAORKlsd/NMAaVAmYm6MqLA+YpLGoRyiKJCSwtpXbDYNGo+QiLPnBTJ56T9WH1qDMpWQh0eJ6tRjAIYI9YXfTy5QunUpmXGWpFyi3pXaIse4o8MYuSa0JSbSl3m8JHzMCbk0K1lLyTw/s0CLJKKMYrGVOa5zyRd5P9nrCaZCF818KuFqiVkxvQa9u0lcjfFC9NKHOKsnw5oTxzehAWTHlsVbzhRm5RfSYDU52QW+H4NIMIBw4scmqKqOrC9z5bevMQJFfpnqSroUotZLLzHUKacoMLU5IJWhM5JzjA8rwYvniu1APITpB5osriXuEeWeRGAPaKB82YkgFF9ISkPYJQtCLFapuGMFhVkOrpv5Mb+8piKdlZLNJALQ1zG2lxOMq5CcA5JYtCT8KUd2gqg3HDpEohasfZ2GddkJMwHSZzWtDF5lQ8LZ8KQiUyRv//7L15d9s40vD7K4CUZDvpdM/M+97v/+nuuWdmekliy5II1P2jqgCQkhyne7bzPIM+HVkUCWIp1L40g5zDdGNcqimfNMoSxPInSFVYHAzE2WFxBUzg0uDrLF1wV5qrWpSa1USO+9UZPo8mdkNqUXPoKKXDXjPUtWhI3fTR/0ajfma82xTRNKOtn89k48QNBeGljyo5Z8pSiTABm1tHulqr3+Miia8Z2jMh3EJMQhcciXMFiM5EOr/16bMogcJrg33lhDCjRyE/uYeqp2QsUWYgD24sOginq2s+Al+zEEtXdbpUqZvo8y2N2WD0Ps/N/+Md4VEbkQvN2JDX3HUZ+kqUVpMR3Gg+ruswtsbw44pJxBxFIgqibXWfRTcb0sezWTfjLfqLIyon59xKRoxCXwggyiCIDAJJSCoiPRWt/Z9adoQkDQP7WcWdbuJ/S8glYuUHxI0Mcd+UM8nLRiTHS0s4wawk1B6pgtr5jdCdrpAzgqfEPmlTnNmjulJAdlixZyUOsq9JKJ7vC0wjJH1biul4kiaU2rlf32NGpzTQl7f4lnvf73CETj9XjMqgNB97C7E1Hrv7ngZP4vjOTkYz5gy525phVNzg5gpRIQxAbGCtG85bH8E1aSj5u9LbEE3MxZ5LAfu9C8y5o3Tcqj3tsKRhHQwp+rIN5s/vkqLXfOObd7b59QwZOmLsZLg+cLUZGBjGNeLnYXsEd1wxgA7jtJ2L9Z5HW8ElGD3xrrsKJV7gdUXpWVRifGEcSQ7TrXxNvAdWEQlxbcqZLIkpmyOmaNBLrKZ9ZJTJQNFWi9fWUbBMKR03dJNHzM/TcA+0lWEcCkyYwXA5AOcLKp6NZ7JR1vPZU3b7MqgO79y0jl76xFVaSYLxlFWzHrVxGLzNCGdULoAi+5nIBgO0ulHCDuVC2gkiM1UtrXU9nZkeDrC3t5VzmNJmPzZmIJKB3vqFAQr62OfDAQGmaSLlTJ5yq4GehpIMviHmTImy3+2Z0gQVlvNixprJeKwUfLwq024i3M9UIR8Ste4ppyMwkx7ysHf9NU0+F+M5sqdBr7W0lOi7x4nX54s5+7Fr+19eT0ZVVmOH5LyO4YcBG2oi72d7x9loW8pC3SksFZFKqhVN2bfXc4kpxuc+gpy8lMxDQs5Acp2BgBycfxSDlZwSl3Ixh2OFVDKYdEOSDMn4/lqLp572syoQ2Rca3xv4zumnSILVtOMsRhYZAVLD7yP5W/EiAqLiWZ60wW/wwQ0fpKicajjcyhN1kFuZw+N1MV4Fz3nu53YIZNjUcB9AttEJW5fIaHYPM/eDuqaDD6TH7jJdXqyP4ETnzWe8O2hI+wjey1P7ttUYgK/riu6MUKRlpzvjeLHxh7RnewS5z6EqKh5zF2n/Y4KRSl8xG3senIZcN1VV0VKGOSnU0FWJ4y7FRJgXoHJ+3lt2klrRQ8fJYbCtgBQfYNWWHabWYqnRLxcvVWf0oNG+pVCcZzR5dTL8k0ygjEh00ObooqqeKaWixf4PAiIIdXH5MBjypl8wedmWeLJ1K+b6fT5b2vK0N9gor3a+LqcNz7Chq/MHc2zPKTu99NsWXWVHaU4Xzu+k8mrjveJFFDj4Hgb/dEB5XfMGOrr9x2gMlsvxtTl0OvJ4g9PtfJomLGucywniZ1tcT9SeCD5EzfEh1WrZ6lQRra2cgyoslzPTlFGZyKeF6fEj2g67cinmBLc8Xyh6pKha9oK6QMBqyOV09BCwenSZwJa3ywLhMB3z1uBFB/ktlseyyA06ofXqtHXt63yfG+x64QCE9s+wS9tdo+/VjR16XxtkkY2uczUu//llHB7Co2+JUdgfEITDn2dK/VOb+/L3wo4fu1yGRSJ/DTrehqJ8EfiA4Zsk8PK3v/vLhMpnPhmKaungRRJPqnxNaw1HRLSnzfeIXk4iLssP77+zhIryw7CNQy5Kvvp5+bBeND44LF3xQ76m6vP9VttCzdam0SPH39HX8OzVHO/QnO2tsX5fpG3Lu9tnMSN6Bi6//Mr8p5+Qn39pQU3vaT+p1VkXEf7fv/2VT/p9kePQ05kr8MvvODbfk3r+Bhf9h9qH2oMUDS0JWpWPLlt98Q18qsqk8P/98jMAnySRgA9ezqtK8qA3k8dJEztAJpPZJtfrLB50FHJX12OqO0955LmPqLjdIrcgjuBvnMTjWbdUeVR4+PFHlp9/o2Y4p8+ITJ1PMkbDsVv/91b7Kg6bm7Mwng1jIcUDmtbn4B6v1W/4xu+bpje+KLc/rfu1nDqw2f1uVVq6x7i0euq/7R/V/tca0L/dNiTJv47eKNufoTN/265ySo7ITOjMWIrqy/ekxrvT7pLE2xztmzd11nP76BfgB+B76nnIVT/vGtK/rb1nZG8zuG+1W0Ryp1bffDuEUPsqXXg+iraUR03g8//Fo2VeqrKvhSLKUUC0p1bvCgkXlpOQNKG9SJi924Xqo8ChCqGutawJX9Ffn1j0CxWrT6ia3GM3k7O6osz6y2DRZNmUGHvn4ZPAOWV2LoBJkpbaeZoy0zSxm/ctLdtFFzOueIQwRaFUZq1c6nr8bf02BggIgmh/V2inL8x2k0DhyMQDi3tmj61yZtYDZzmtrncD1TCGDbUNY23RyuQpHE3mDYFrFHDE7SjahLJyihR3l85cuyDMSWFv+yZ79bRyZoDO065HNqAoVpe8DsofEOdazFhsuoECxQSB2oTk4tGABksp9g6hZhOPsogpWrzusUVQKYilay8qTQBNC0jKnlLeBB1JQvKc1SrFFC6KZyZwoQDp6ycmiHf2yd5bg3NvB6/DfxhpbP2rR9p6ekOEKp7yUt3QXrvB3fayG89bFLqaZ3ysssaev0No6QqUMfp4jMdZR86EAVEjRH7AG0nsrNrR6h6fip3NspRGxyCcxm4N6uafXdnQIGeHcl7dq5w2jN264/H5bd/S9mx7oK5Hc+OSz/Wart57p02iKyZG9ruGsi/m1ZQ3jl/iFLZ9u+43sNM2c8XNcQy/qFYrR5AzPf04a0PLH2ylLL0+LNfzCENnKFolhVOUXbPoo8QYYdjKOAzJDOOaxxr5OU0kyeRk62oxnckVhomcMmnKPRJZ1ZS7Qc/ifLvSXFrYRx62U2I1aVp0DcNTbXC2cr7oWGQ4j72ZIVK/m7ca23Z891rYA1LwUrKm5VcQ9A7A6JhlPYbBNaJRBpdN+5mI5Xb83VBVKNE341hFMMr2Lf69KX/FjKGIp7j3v5MxDEFLLGuLR2SK8xo+xshSWeqaD9/iT6vFqG3/rxDIsFh9Tb6zrQT01t232y0ZYni6zWUYVHMUkfFdZmwT7TxdKM47DY9j0TMHtb2IfQ/aojfWyJdQhJYIv+PY4GGFlsql1TQP/InrT/x6jfR//V1VcaV1L80jEll7/HyL9a9FiVS/1R0gIp7RpmWOOx1UvZ6v9kwb4VRYtNwQdmJd7IwoyiyJ4h1WLch5SBm7BZw7W3tlmI3bPUtLrJ26MQFC8d+6BfU6z+3C5t3tulgpp531u03tTuBXsSrK47DedQYCVWwyFCWPSreate5EhcnSH3/8ia+//Yb6PdNi2aeqZos4rwmtyUqQeN3cRgdW7+1pumOvVsfZN+8WDY3bTs+XbeZk3+vN+fUvtfE+ZkjP7T0Gf0WV3dPElM3AN02JvE+8vlTEHQg1PSBEBqRie/4K6SHBIsgpcKPhKlVleXE4PBjSq+FMHJldpDsYBI88slWdC7uHa/TqSiNIw/lZJ6PoHGuUwulOa/e7l+E5EYZU4gNeIvheVuWUZNNnCySesTLOMr5ufNNb8Pw+jD9SM+GhkUJUKC/bxO3f7jnmeUHYNflmoL+be7/PWWvd2jY6DQ3aoCmcZ9wpta110JyBdyD4AGl9Ri1U41vw5zvet7OlaBki1TmisrNMMUdFHqX3jbhC3emI1Ruz61qpxdO/Ok2xYXaYs8B2U95bNiN38s/GfypqfSSxGthFV87VnXrYuUuTUC/2Sx32bI0d/Ayo9kwleARdEhYKPSPKdg8Nb2TMOT3KLWWJdOSJi16or9qjduVA0Ve6JiSgneGbrTNA1YitlM3v+Dr1X4VDn+Mb8GbLr9fs1KbFHjQqupG5AFQswtzwPYhnkZFk+yY4Pmw8JZTmWCpEqYBSC5evC4u+GH4si5eZMf3Itd+CWPkLEc+iczVLYl9bUIwzwetgqM3OBt58V7uNe+/hgXc36fv9ve228f8GexG0f3hPQLlFnf/G9NPEbp6ZdjPLeaFoIefM5S8XlqUQTjM5JTOe32lfpRvRae8A+ETlN0BattPQYr4Xr6/Hvl6zK1nC8fAnpDkYjhk9P1RL4970rmE01xtGrZCbfoeA/wcg4x/e/uhYVihEIf/pJ/TnX95tsJp++hGAr3/7G8j3G88j9XyM5Xvbxytm8V/YdJPh13mie9HIy3B9yxtdksncuwR4IRVJmYyiIuzmzJwnjqdTc0aSzbtFMZwKRLEitNvENlpoml7XryXg9MtnSvKysCvaZE+189g6uqYp0d5vv3q7defSkYb+Tn4seKyBVY7vY5fbPVzFDHEP5O67gf63/bH2XwP60LYCSRfaYM1ibVBrY47G74MhxAWKJELOwulSyEmYcmI5L658Wo9hS0Cvvg9MQ7wyRiDDhRUD1yZzQ3vg7etmaoh5zQVyWH693HxubE/aPfm2rfKvAbr7xG9LItZiuGy+3+19pYRgs77D9xBQnLFq6focNE7u5tQV8rIa4qunUXxCeABmTRxFOKFMWHr3gyp7T1X5Q31i9+EBvkDRZ6I2ZFWaxzKKp1hMpHapG4MsT2RCtPIqQkmuRhMxVZF+JtcDlReKq01TeGi7Z5jqqOy0NPKqll3Pu0Kz1bScMccAUVeeTTO7ecduNzM9wekCy28F15FStEItFrWiyqEqJUTcZAnK4syG4bfBg0/xxY3jLbIwCQswO6wvcjQbPScOR7tFVLmIcpGjjVW6UL24AC5WqLShg37+1Kq+p07Y7a+EZGFZFkBIouhiKWfrokz7CRHz2NOzMh8mVDPldCLJTKRzpyq8Kvog1KOSH85oPticq0dpeGr8qDduux6CrPsGuqd+DYEfy2iQyF4rGTNmUKkqpuxLiXkyj/taCyRLLxfCpYp4us2EiCJF0JwJo3eqhVo9CudsyhDNyVPFVk/R6hGyhaaYRS1NtClhTGWT80QS4VwvtKrIErCYqcXqtKuoK43waHT1KNyI3NOW9h2FqIF+Wax2vKWjtMiY6qUESrWohzrAX8Mwbmwdo17HiPTAEUYuelr4ya83oc3HYpFEPhfUI3fF98iVpdU9qEcjuli6u5jvaNnRAQWN7ZbwnP1cVc4btVElItLvM3TBJXaldCgjGq3dPqjjOhKr2tZ4xLPAqqbgOPoVdh/pvdCU/f1eNz5tznGk9Y296w4Pwch32ht02tbqDfbaF0yT/RHGrlLreilk00ds2u9QpDa1oPaMFGsb6KDElDCkhwEp+ZDFonJFULFyGxYtvpYIGs+kEMa6NiFJJFFqyiSvWRkG0pwsQt4xACIeWVTN6N1YL0lIMuWnXfGSH4FrmzFBYtYrYUU8jWjjm0LrPtDxbrgOPg3u7+it67L6OwyFa3ExoFkaLgiF/Kq+7FrkvPmGu03G+6TPMeBYBn5Trh7YzC/Grr2L4RNkOB84X5zaqY0yII03cuNoCMApIoyH91nWg9Si0UluVHdc55Dq69fnEWd+FcEPPZV7fHf4i6hme1Zafdbe3xrntOWCFkWtwz1rHj54rTv847a1nw0Oos45KXk9qDi8HT7jU1HqUpztt3sC9lr5EULx4XvlcLaUhZE4JAnjrT1VytIgFtFW4/5yWez+5JEvnuGhunFihc+100AbhBnRo3BL4ChnXFt2AcswAHjt5sgMoqW28UiNfTL81JxoRBwPdSNj/GF2GvXIw+162j+NbmH9573VyD6fTogIu73xXktdnH579yclHTK1HreQcN3akgh5v/P1Mx5MIyLY969yGsiAIMvoZNThJzpWtewvYTyXnXg5JN8TLo7bC0geBFQ2f9zGOAEHMf4womePjhZ3stUaUaDSHMWS435xvlKKUkq2sSR37xQBj2RWhfL6an87Vaqn5PsUhHUHD33MLePI0Ix3UnaPE8fnszmqsve0xH26ho6lyTnGpvp7itp6BcZy2K+1UlLyLF62hzLv0CW7O73CYzI+8qWiokwPU5BH85lI8TJaBG5B4VUQN6KHEbFhXPFqST4ei6zVda3r4C433h7t3A08TCsnEO9peoYtFAd/109KT/Fujr3aARYSnto+dVzm627pfS0DVNPRNHI4wl+9wpOs5ubjEkBm4HIVkB6fyWlWqy8/LopvhbBHPbWDYOc9P1kJAhUlPSaWF109d9m8L9rD5vueoVyJCIlH4Dg4K7iz0kZn1ZoDwHlzOdxL2nwdbCIrGAK1Bk+gkB1mY9QDD4RgsqDVFbB+HZeHYbmo9vI0Me4GUhrH2FP0vhL55PRZgQO7D1auwMq6gGgm0oUZf204vNRKBqoIopaxSWtkGvM655LN4bsqeTc32Ukwo2mU9gp5qsG9491FjZ6ov9NQraAUHh6fOB6PiM5O22zltZq2Kzu+vrwUp4v4edxCXgDIkfTh4wq6I2NGqYXLyxcqynx4YsqJy9GcwmKtiw/8FnYOthxwfkZM7scMkMm/G0/1QH5YFaFrYxyxRUYYoMTOeLIzP/KEVQwvR6a7oLfQaaw6UlURpgS1Jqpg0edyQKZwyxF34IWpcWPm9ByOFcuxUMoLpVoAxlKK01BtZysQpbh+S5qxB5PfBt6s607iQxwXJVObSV2dr1W7TSq97xu84c0+Np0Ekn9TFvFbN3xuPP72U37fNjPQhm8duYGV4UrMiJ3lE/NfJlL6f5ygGeznaSK52XuehXlWlsuFZVk4/vWvzfFzPZhhPxjwmeORqp+d3ukqolyBTy7/betqy2YVonQZuAF+hM1hjkEZPqrRBJODe6aPZkjV3tcIH/8oY952D1fcmWobTziI3jKpvRV5/q22FV8+Nwbkm0/65/qdX6RHoS+//EIBnv7yf6ha+fT3v79pEP+kcPrlV6uw/q4x9BYZBGLbvidt+3b8IlxFvn+rrvs93HFvCFHTe1sCoH3ViLpew+0ntblFRPYn/yVqvccYHrJnSA05vSrTLnlZ1tQiyI3uh57RaakoU0qoZ0cCiIy5Mb5zWVZ6lRh7fPtBzdHk1+x4RoQpWamiVaDHwKB9y9nw6/CC0OPduu+tNsrXq4G/E+ACvtZX7CPY+LYQ2y6l4zsbg49D6fLqerBDKcb/tn9k+68B/V57L2dxo3VAHQ64wJST12NyhLI17jlTuFZe/r6xrfv9Yy3QW0LInzKX95cRuWrPTlT+57V7k7qNKuPuLW849rJHPI4TRBKzM/uPJJa0JhSRulo/wLIU0pOw+7LwkgQ84tiUEe3NVlM7KWgo8u23qBnZDSZWjzYidQswfXxh+a2aCkEKuHHYPH9DaepK8NT8zpg9VSAC+2xjqx51lDBj6TRPzNPEvNshkyKltvpyYehf1OtgPbmQ+7Wv2w440dNzfbMNhE8w4X8ZHnvVkxn+MfJ8K5VQKJ9bpFOspjQVTju30vZuKwholJ6zlpRRcWvqwUiV2rQQ7Z0W3m9hF+opSptR1TRwfcCq9OJx/rqcB05EcQdwUqnUDEmzGZWlGzRKBdFC8ZphZK8dJt1AlNSUM5oqSQXJvufJBM/qCjUWideSqqJpsetVwRWvpjTBU8j5vAd9zm1BQny5ukFbB5mzGW/b2tCieMyYXbwmp6UUra4UCkWLqhk6a1NAB6yGMoBvtntwGjWD2jy3dVzHe2ukrQYhgZd42Co5kyRKueEI1c7B2wPe/qqbb7eEgFuj1uH+8Z6re4cl1PHfuwN5R1aXDeKNaNf4LQwMPdOD71EYTgfDyjXDvp7BRoZ+u8VcG77RTW8bb92bXXz7TWHQM+cTqxEm3FBWxLvc4BQ0IUo3pJQpFebcU85bdonkwnrAdqzXel3j7CU3LtSU2vcWZRLvH4xtOqyoGV3dPSGM0i3bREygK+2bnbHldd7Q53H5VuFrgaUdJQ1S6u0Vf1tcsd6CWvj30dgc41e6fk1GYfFOrx1ZjBO5GtMWjkKXOA5hZTgc7kO64NYcT+7Azvi8+pemmLwhiDZYG/v3tUhgxrecu5OFZy0RSZ4qNuBrMFq/dQBv/ha7s/5RnF0arzahe+OBEkLwbdw+jusdAjsDT7H9rdEyGS4E3hhGGqDcjH/ea6tP28cdQnwok3WgeeCfOt7fr49GN6O92voYI8/R4OdoY9QOeJ3jGyYdKatHWFU/y4oZvbtutysNQoGgbTX7/sS9I/6r0pM438LwgY+SO+6lFDW5r8+AKlxOJ6b9jnToJUrKifXZvtHCUUcVdNE279oWsLb16su0hhIZ8kXrBYQZ0Qt6vqywRPAr9XwZygHrjQjjuPsOrfBIbLAIwJkdzYCeLaNKTtnLM/WauGFIV19PSeaMmsir+unjeLriaI4ZQKtYCeuI9Bi6rvGbemaecBAFlHObotEpSIc9IlBeT+4YF8g5bnWjGQeSKHJIFK2k6k6/xeolR0aF8lIQ9xut4EZDzOi4i3MznGnvvTr/YYZKP+XVnH6Cx62eIQnnkpuCM+o4GyJotOKW4nA8l/1an68StGikxvR18T9H3DL+Ltsntf8udAO77VF3fLs2oo/90rCkIrDzNTxrc8DucGtG9G+3awKR3ORthnPnYZ6G/HAK+qK8t8VOjzTZIn9PDYe/v7fva43nkDBKmuxuY9KWPhtdgWEbk8gaP147lHU8bDqI0jGqmPEetUwNI7K32twfB3wfz0S9dDe2O2xboICaa1lJbSzx3iSenYiexcZvwpz6ajtX4ZRVa6UsxUoIADKZYX5VlBc4Ho88PDzw+hLwFNjTxm1x4zRQGlwAYjGHb8dGqyNCPzI9WRR1ZX78yPn5M+V0JD08bja097qF3Pi+vSY+vv75SH7s/H60eqw34VDoxhdf0rvNouoHetUQUu+r817GW5hTY2LaDY6+ImjJ5HRg9zi3Mk+lFpaXBZ2Vy/LMZSmUemEpBbxMgDgw5+QGfZdZknQgFxGPfN+srQz86hu0e/w5zsl7eL17zOrWwfu9z0UzfL1+/hvDH959u9/+xts9fVDY//Rn0w06v97WYugkZD1qZZpnSrET8lHtDD/n+yNVuiEwRjnC4q0x37/6+7BsKwQhXTf4VeBjXNzw+R+13/csf/TtbzVx1N7psX1cr8IfzWjyz2qKre/Xv/0VAR7+/Ge4Y0QPg3Wwx7+3jbR42z7qfQP4to1D+GHYgu/p462Wvn3L1XgE45smsTEJkINmSOeg4wxFkVFFmeed9eCKiVIG+huMD2s6EFlSVnsi4iX+7jehO6UY37f9lZV+7rbp/P3t92R9+N3v+he8I87Nf96J/p/T/nkG9K0wttKgbbZUuELc/2xgHmXTfu3boNY80K5u1XUfbb72vVZTymimpbdG3KN7ECMVbcbCUUcxpvgdW1P41EhR+I0JrBS0jC9Yj9vnEzVbQhDIKV8h7XtoK5T0T1U9jU5n3p80vAMH5DqM7I8e+m+h5mD6+sjXiP9bkegKdCXf+GDMpztDGO/k14PJC6bJ93gkbBr1DbXX5nwRRRI81sSrVD7UiUUqT0WRVIyQLYW//vJ3fph37NLELv3AvjxzlIJK9i12gQzxVLxWW6uGR/UAZ5aiGiQJxylTRDlghunXZ6WmxFQKU4VjsvsXr62c/F/Jat7Xjsknf69F/yZOqlZThe4BLUWRHwR2yuVZeT0WzqIsEjVwzcO4APrgDpF4AAAgAElEQVQ8pL9UO2cJZS/aDN2nFTyM5LZP90Jlh3AaGEwBZrqJQ4B0gHKK+C9L9QlmSE5Jm6c5DttN2PL3RMRXytlYEo1oKm3K4DSZonCeZ6LWZSaTdkKpC0mE6WHnTMhM1ZON8lXRh4tFo+gZ1QR5ojxfmB73Leq4YIJUlUSe1NOwD4Y6Txta1YNewmDgc6SWrtBQj+SWqNOWejo97zEhXi8vU6hIlZaejl1GFpc6fM1SqqDJvLqTnUWpzizVxerzRffq0eNam7G4LNXrnEXy1q5RiOhuLdVqQbbnXSFZKqWUIbK8UIsbxz1CQYCLe06WqENeQ3Fp5yA8oCMqquPvGIePbKznrF3hE/eWiC7MedVPLWFYFz+r/j114+9V83NzQdt/0cQZ1VDY2NkInNjvC/X/Fr/27z39aVyX1X0XVwwd2lNCRKH1cecc1ZLGSKX+lq4cxnP8GqTxeunM+2aMY6qlLX8x1rSzezs9Jl4f7xquV400incozkBet4rG8YauLNo8OOoZxkuD80sf4+0xjBHy47UrZz3dPkN7LrCUZWewWlc5ez1VVWoxJUv1lF8WqSq0qDD19OoqXRnjcD9NiWWxrApR7zglrG7uOEYF8UhzavEsKgIeoWbBPFF9vte2FFGqjzn6MXDy8QGqqdE/xY3jiqf5Hr13nbJL39Nx+aTly6Yb9+h73+i8Pxe8ni2XdN5vZMvEFCBR+zGcBMbsCTd2ffPtNp8VNXvX+90m0+Y42ob7qg1zi/OjKyBq+E78fGdnUkWGCnPO5KSglSLkSPMZfUjHE7ml+LYFVtXwuvL1FoJBH6Mqgoft8NQntdHdt4VaGacbYtws74A0Vljq3TLMt+8LXLSK5q/q0bG6noAOuFuDh4vITluaRi+C03Ujem2GA3vHbt47fbLMAGFIiOfjLIRTWeNvvJ50rPfaTcrhriaohc55DE6c6qVi/LwnJs+SMeAOrUMEn12z+Xg2JGe2zTGxRxeGYdIcPnMbT+O523J2WlzdeTTW3gwwqdNuvF6r9IQAVZVyOhmu9JnX12ODxY6HhpUZQSFwSxJ0uQAb2j4eNZ2JzC/26GIbrbdF/JFGA3CusLO67Y0qC1ZHW/ogNTJEEOc9vmuwb1j0pWc/CnlZpBvAxY1XYtmmaqmO8zutyVNmt5tRzZzPyjRNTU5BlewOC8tLOAkmsio82N7qyfY1HdyQ9toSR7vcZdkNavHcVamCR7Iux6i3vScOe0RtX/MUCfTaqKQArxV9tMjEUpQkyqKV7HB7qVav3mo815ZRQ0VITA1emcTLIQn1bPxklEtAjdeUKqQq1BIwbmdwlw/ItHA5X8gyQcZ5Ws9kUEPu8D0ezkxTckjnUtp37eelrQXS+Ljen+PqEW/qlluSNvdWk1qVoesVD+oL7/1152MHQ8Miqz1RmEFPOuDG4H/HfyGeSu2cWyv+lsQB55xIj+EkTJMPQllcnguVV4toXZ3pEUBiKtI+RXqWuoA7O1OWMW3ne3ImcPfaaUf6Zjn81Nb3yrCdUnNia1G4Toq1LaQ5lqjSa9BHBoSUoFiK+hr1xQM/Dry00HHAWH891lvUZOcSSyI0Z//Yj5AExvWaUqImoSVFS1YSInuq2SjFhfa9xPciCWgpjd9QEkks9l1SsmwSwV+rj2JYn1YqSCLdtPX38vkLInsPm8ystXqDzV3si6oOmSSOjdOO7Wzp7av2LGJEdg6lHp7Qs1JeKwuvKx41XtO54P65wvs6OKK3e4xnLscjogc0vbB//MDmsYEd6thB1I0ecY/LGa2kXwreIGRuYrLWx6Bc7AaR4A1xvCax6ewOB/I0tYjHqpXl+MpFK/Voju+XWlqACS5vRxfV6VIRKzGSBMaSVuJ8TBtn6nMyB+S+ZlpjPsK4OmMbZYLV9dX6/452A69s+wsngfWP73tbUizwYQCkkRVdSbaOmx8Vnv7yF6Z5h2R3UBODl8jwMM2ZqMCYsUySQX/m9CMLn1c8hA1ZLfLW6UgS8eKiymfpUbkx1I8+VqHLLR9YR+3GKR0jkM3pRfmowvPgSNqfWa+dClbKR7X1/QVWg/nB6VNx3PNFb+hpNu8Z8ftdGf+eDBGXt7JIF0zXt8t6UbZz3OpNru026+7B5vzlm5beWN94vnrmS2tjDfLpbxfS1cjGMf/+FjXLf7zRSRi932P4lqDd2gMGlU00+xVL80bHcv27iPDZ3/VpmPd1doWeEViw8xGZ1LwqJpmPLPJ14OHscFtQBFAqeTL62kvqWVYUXcJ2UJnEsrRJzhwvJ9OHeLa4qAuSU+64uHSHTqPFgVOVSAJjZ9Mc5EzdY3rsWowON72a9Al3p1yhljVP9FHtXBq/pYRxwngZx+FXcH17b8LG5dzuH2ttDwfY3pKQkJF8jUB6hqyBBgx+YM62xRdpuvuWyZVYiwGh3xzfNf/2v739UwzoN5H8SrGmDfBCCGgM9T0kcuv6O4n/7TFWyoZ23Udg/VD1CIqN120Q/u3B00ACNsOMK4yLeZqPJ2Rkt1cGl/XAWz3R9pB/BiJ6q4VQ8T2tj9IezHzCUPc7nm0C+RtM/L+93RrRNfMbguH7ex32UB1Rb/kYX5wQcJsyUT3SWeyEHJJwEeFZCwcVFl1IJE4s9mzOHEqm1MJLrUxSXehyb3INlZkRyEcVviYxRYqPr3r01gjrisFbmsUyL6nVPT94SqeakitdK6UslAKqE6gic2Iie+1Kiw6LetrUIIqWzmVUntRaOX0+szxVTs9nvr4cKR75W8pCUU9JFDQh6hLjAmibqbW9f66rlvddNwP+9b5OtmPmkX2w35PsSA/CcjwbQWcd77qFpJFA9ajPamOukXJOXPnia2pshDECjlNSSkhOLC8FdiB5dzViBfRVkYOgJ9BHACE/7G2GEkYkS7+edDHbYxIXbIvXzk4+MxdhU2lzCMExicGDEd5E1kqS4kKoUHNlWRZXBgmopao34bVHDqaLRRZljziy6FZTNia0KeqMxzkjJE8riu2MMw/dgA5lqVwuF4N5T2Wutba0blXVPy0ddKnFo8yrOaIM0eehKG9rrD0qvOE27fTLjOruXEG/d6QNocBfpcfcfMrm2krwHja++vkJNSA1rRQAa8nacVpDa8FlxcmxM4bqFWzdk8918/dbpGVN7frVpoCRMLzSlO1xzNVT+CO0dQtHGoCkQj0P0USyjii0OfSo5+G2pgjoOLjPuaHugXlsIx82pKWeble6I43x6DHH7arIKvr96vfN98Es3FbPsiAwAEjvKEB3NbY4kyLNaKaayNnrztbeT1PSF6GKlepIYllGcq6cphMiGTNAi9U0z+rvFsLlwsZnmVAi7XAYqRTLcDLK9JKk4RIcDlLq9WVTmjhXpQSeEiVKRHQ1eMefoTSvkSlCIw1wphvRzSEGVUs16bQThowa7tCjzmyF6NQjsfs6j+d8u61tbqnD/vhpWy9uwHeYFGk19rYHadX/9pCt+rzmdboTgGwe6fhBpHdqSn3DSZaKVOz8eQRJX4A4WzbPONvqeL29W/Bo0x4ZJim1+xs+8z1OOTX6Hg5RksW38Zq/bUaIkDlSp7mhxNVwdHLYCNjsmNXvC2w7GCRuCpPSHfTWBvvrW9uNbzXFlO2D524YhSsdHxoaCIUGMJSbaGsR9CpIwXBNFdS8YQDp6U6dswr8GQaLWIOsuoparnhEn0DWxFL96UjpKpZ5pgT/5wvhOVS6MQmvdx6RYkaAqUUpoqTkY1Wn81bfoaVejoi94vTenAhdFsuTv4sGg6HY7YZB7RkNKkiWftaTkMihL268TdCl6tFrKSczVJ63pU121Cuu9AYvqnEGuhNOvG993w5a6uCAtTUyaNHo5xndRN+W85jw2dfTU9IWDR6QnpJZWvy9M9zhMCyecrvLEMRQpPW+OjehvMnsKHJmnmceHg5ord2ZLpkCbZFEmjKlJHTCnWk9sjBZv4VK3kk7c+kw8OE+t1DCqjuBHZ+P5P0OmROy7EIwgFOsefBJAx4Nfq2tNShnqu4MV7Xn3Bio5pSpKbEsRzQdjH8uS+OL5zy3VMFalYVizgEi1CWMlqGLcNvT4s4Crlyk0SgGO7i0PRCk87GEUi2Zk3/g55giA8w2WhGrMNKWDruBNesKRkPb0+mCGSvFnRNWTAphIdEoiSWBqgbjeKTOZ4A/bcNsBkpRhR1W2sfxofEAdV3HWtbnr9VB9sUcjee9KfXFU+M/9VTmN3F9m96azrd6zn4ODC93HHSbboiVVmNI1T7wxtomNOAAVyp3mhr8ldOHlrlc25wt60f/HvyAJis5cLks5GzpWiWlVrO7RdwGn95oKg03Fe21xmPEK1uLqsvInc+PqSSkGeek4Uh7pmC8SDhCGq7yQl/aDdPzbkIRlirkDCLuWOJ8BSLNeM6ZQLyO43ZERjgrFRd0olFbLBfefiOLuHN1GHVxutXm6/NbKnnyiOuUqKW4w6jRwd08U7IZiTn5ksbB0NtZJa5AKKY0XpMH0iGhrwfkIcHrYfPUwEN21sxBaU29RIU0Zatdm81psqrNu4QjO2rlUpyvSNmcJFMSslpqeNUCdUbPiu4MViLTldZq/EQpLK+v7sCmLqvHWL18nNAy+1lUdDLH3dTlZhFWBoeG8ySc4mk8edViDg51mFM42w88V6xvd9QefttskZ+wlbpxhZPGB654gOG7BC5mkE+2iESa7LgyDm/6tXN9OwPSPRDb1Y/kaW4oqCylZdtZloUpT9RaG1xEZ6oWiDL9eYJfwhFzMx5WULhqkf5bceM5zrdL19qHEX6b+nr9Asejsl6PFS/trfj3Z+lBZ35z6+7JZRtV5RjyyDCe7WJ2eWWTOfLG398dPX6tiLhxD1cZC/6V7V6A8qK/cfjTn/jx55/5dRjeJ8W+f8cy3Gvhoj2aiN4dde70swZvtu0Yg88309yvWKFrXZbd0vFSRIyPBvpgSbtTvsnXLziMOs5Oje4KkjLTZGVDLQOpQFVmEdflZyaBLNmCQS+wpEoq4jKe8WeJxNNuz+l8ppQFmTKiiSll4+eXC+dLp4HTbFmp4kxXVdfTmrG/igVfaMUza9r5mHRy+pI806k2dsnUDqY0Cmc1Db0ygFomFNstOk1enbH7+9xuGfD7Wzzfm30QWqvtC2XTp7T5BV6sDGflFg5oWVbc+cFpnen2N3Th1vjH+cUI/31o4T+q/ctTuIdCdiVI3xA2tl5n/3ltJN83vFZUaXU0MQPYPGU+PB2QJPz9ly9A5YfDjuNy4VzKqufvGsatJ1aH+jvWMAQp9drnjQmrKL+B/IUkwgfu1znfXt8SnlCS/R5K11f8/fd/+95OybYkqv21QjByvaR3uLkmLzoCC+GtuhAUEl4oJLo3eOUlCCdwVCV7xNGrsdc8FdBUKDUjpaC1sC8Tu0l5QcnylQ9MnZAgzaAw88CPtfJr/mze0AJUq2epYhGu5gFdPcLBlDMvnnY7qV0/pmxG2DKKwL2Z0OoKteQG0eGsHLwmVihqcMG1XC5cfrtQsDqbl4tFa1T3Xm5KgWoEuxszjBDlJ7Gon99oWa8f6BHpARUPWEr6U2Ngfb88aH56FEQOlBd7qh7ObaOng7IcYUqJKZuUUNw43g3MQyo5CTCRpggqCiTIyZwOkphn31IqyaPPkyTKyWudS0IXNcXmQPjkAPqKp3HvoGq6g+QRVE6kKxapIoqI1eyrruyKsYXQoyjiNfHEFyZhxpLkSgsR0AWyVDRZbRwUNNIv45HNS2I37dBkAlR4f+eUwWvbJakUZ7QiGi6lZBFCAkJqWRlQj26ntvUUsWiJUCYsy9IUuaWaAT2UI2FI0zooM5ryu7RnVLVFobdU7c3QMkSZO/yaUcNBqXa4Dlq3dY7qXoza+lwZs1S4LDaeKeeGT4KWNmHf8UdEdI3nsQ5nzhSkK5WJp27auoN03JlZN/ESATpUWRzZv0CH9yhPPb6CzKS9Kd+DBWiRutV9Tl0JF8xlRJ4HPCZcUX8Og+34xkHpIGH8oa3fOL/AP1e04ooz3tDVlWAdd0akm4+nyy99ZOOe0RWaaWNQHafTjX2s9m/kPcwUn8zgMbwwxnOLn7qKYAp+ZphVK8GtbgioBVK2fSqVKguapp7JBKUlAYsl8D2rTaHrazQCiw9lZbBukdeGT42eOQyEEU8qPW17d1bqs0qoFiJtNWrvqLhQJrXBoLa11laDL4SGZP84XvbpyW3+oV13i9MomKWoHUrQCB3Wf9gTDRwuV3gjrQFqs6lX2/zmD8F2jIagW/f3KYgRSe2OC2ITG5meZlCbcmq0UOguDjHfFAKdhDHH+aKhRnqHj1j4fq2WbuRfOTT5fTpoMgYzzup8X/GKN5nH7XObhRkVr9qjyQK4tudqxMl32032fnMuY17q50KdHwu+KO5p93a6FO9veMTHrmpOkah6xhw3BIspI6xusd+eMoiYMdKpsqo0Ooo7s4XAb5HnfmYlItjjTPl4FQqFLJ5xRC3bTcAIWArBUIZHXevgBZoRWQYDkPdjOMSAPqXU+u9re4Ma+GYmyaQsa0dmZ5qm/R5ZyuDCA4EDDM1YSvHKGZXT8Ir12W78Vvt3RvF69ALidQTDkSPocHtmPCeAOpmWXQw46LYO/163qhfQuaX9p5SIBbExZk+ZjBlAd/sHyunU1kWINMhLoz8a+yBKlcrlcma325khwtckAXPKXFRJObHf7YzPKwtopRRBF0gPGao7xGiivizAmflxj2qlnjwCV4X0MOKRoM+Kej3w7NG2KUHaG22oJx1qACvzfKBOO5avZ8cjp44hVTl8tLrFr1/OiFbKs+9RWtDHTEpmMNCiqJoBIWHLUZOw32dkCpkBarUo1zztSEl40Uv7zYIAtG1eXQpUtZIq04QmOJ1OFE+ZLUjjh80RxI1yjS9wfBW4KrBzqyVucKnBcw747ToSzRyyNyxSAIXTY20GFXtlpwmNfwqa604oqpZhZp2SVhy/DTyTdnlQ2zv9HqleKmsdQSoyZIAZmjJb1hONVRCW49LgCmB6mlDg/PUMnN6sbdsdQ/u7LtJp/r5dfbVU8fpqcwke1vcBrmuc9zEP9DVwur9nJ8FzRD/OGwKWc+2MTJZ7zTI0KLt5R1XlslxImtBaPII9WaSmKgXIo9Eu+o/yOQw8WZt6NyaG8wPQ+OF6NvieHm1nlmN3vkwipA9Gd8wIp72/y+L8fmy8x7IHjq8VIlsXRuvUlfYopCnDUikXh0NHveafFXI5aHEDtzo2GUiHrey+8S/DlN1RQVGODfcqkOTRd+9IfansPs1mcBDLWhdyZLQpTxQK8/6B8loo+ko7CYMOcHRKGCnbeL36d9Uj9fURwQ3aTzFyIT9meHlAPeK9NYffBa+jPqyBfSaoQpqT4z7MEQ5tBmdxGplELHEF5jxRRJEKRc+oFvJpR9o7j+K8OF7DPsmuETvxMTUdpmAZVIz5p4rY95TcIVAaI9xwx8DPxbmNiYXzQ5NNCf7jmnHsK9j/6nB/zQasWHv6GG4aSd+QA0Y5qDlOb8bVHJSCyq1kJ/qzEUlKzyax4nHpeOdDhcNf9sy7HYq2rH55mihUO1/A6WS0f5rNs88cxIwIX375tWVO+rHCQo/sjrMtDLzwsAQmUcmKdo13tZrAYs9/HB+ONfDz81VGx3W78alunKL93g+u74n+vvjPH6XHTL80RNE5tK0B/Iqe9o3ov8d+Dv29p32XTeU7bl2/oz97z/DcjMjb5+LFAovecD4Hlp8L808/wq+/fte4Pjpvea+ueThcgDlFjGP/UVkZ7N9Kwx70f3zPJ4UfPI5tdd6v1uD+ol+dX7/3q/QU8a3f6Hoguc25w8EmSSIrKC9EGIcAspsptSKeoShnK6EptbYMIrXZt3rgSfBlxcv05WS6F5HENE1M2f4/V7XstNn5B8mtDJaN3/kdf8WHCl9d51OrIqlaVsFUSZEidbU2jq/F+clRrrWFs0UK3AjNIf172pYGvvn7cNv1tjuuGvbnZoeDXrf9qs6/bkTIuB7uSY3Pd7zR/h51Fndee3NivxM3/E9q/62B/q7WVW7vf0RWpydgsyyFeTdZagnHsnPOXDwd1nvaLQbn7QdowB5K4ve0r85PPmlH0MvPhfxTJn8f3Vq1Z+kMxv+GNgrw7XvblPgmXdjQ9bNKj5YY9+4oyqMrOl8wg94nVxzu8OhmEX5ImZdAlqocKiQmTvxGqhZWXlXNGFrpKUE8jQ4eKV7qQnEDZBCkJGLZzLIpTM1zNq2UEV1Jnqx/QgA2Y/aMJ95Vj2RC3fDoqY5CwIUmQA5yalcS0xnc8sUYr+mDncPy3NfvAJ4QD4QD0r71FsEnImvva32NAySUI40I9X3t+2a3BbEK46kZcUIhMj4hA5DYu+3/qqUpgJOnDV1OF/I+oSf3tH7tlFcVZO8CiStAEsL58zO7j4+Wfg9FNaHh2achdJgxGMXT0zuS8prG4r8nJ8ueocdm7GNLtVIn2ytLwWypyC16qFi0IpUsyeZVQbNFqlUpiJpnenjHJRk09b724gLzStnmdfA0HEG8DmT1Wnm1uIG6qEUBqQ7wXDsDpTRlytbovWWw4p516ydV2xW9vmXo7y3q0o2xV2RldWFLE1ZD3YzbZPw1w5mSUOrAZL7Z1vOrw9X3oHZboQuwb0QpogZX/ayiOeyXEHyJNJSALgvmDNLH1ZS77ep6jVbjvDFnvckkrmcYCjo7E9eJxdoyv2NRepRAasqf0XAaEbMWJUl3tghkgePaVtv4Fkx0yapl7tCNJ/w95ti3p0cs2/dSq+HtAcas/IM7cqg7E6q2SGPunKf1yvXX+gKxXvtwz4pEn9FnonlNoViary5AqA6G9yZ0dAo7KqtbPffYD48qtGeuhfvtHIaV2sh3YVwearyP05M1/IVCp/fr0elvrN5t8H1rxHL/60iXkjitd4OmScDuYDEoBgMGvWZ5RBMb7o6MOOrrO9LJNV0deScIXKld4wuuuOxRVzoIoxrRQDo+v23jVRtXnN0obxHGeL/9/Yz0FvduSf/d51bDuX5fuy4DntmoWJSx1DHrSQ3ZUXyvFIYsB9KM0MYOenS2ebUQ8eJd6RypAZvXGM2i0Cz3xoOq459gBvvfDIsj7WyYkdxhqe2B9nMe9FqVSm0OWC2f+kYR17GlDt9xXNUAZYB78Uw9ZjzPHrnW6J8WKENk2yr0JJRLUDyMMSjdBqX9w9vKLSSYWkB2s+2XR8Vv16aD3tzp74qQ6RqmgP3jA1qV6XAYsqpoi4iO8jYqEWFSsXIglfPp5Eq3zvdO0+RGD4VamepEmUyxl9TwMgn0pMguQ1mosjQHViSTHzP1tVpqYed7q+OHlsa6Vi66kPc7aqMbhotWqNsHliVTDq68Pu06thj4DfsMZ56gc9rwFAxRv2I10rMmUxhrpZalKzQleeYtM3gH5rSMXD17irwIsuvG8FKM742hN2dPVZJkzEWgj8No9Q1MqxhebkRJh0n22Y7Qs+ZR/fgHuvdrDR21m9XBrPMosUDSvkuby+omjy7t8gCrf/Hr7MHqdG34zLvNHEVj/8OApqvMEfu2TsqJiuV22Cq732oyjOVMLx4Ar44ODz6318FhdtPeIUsALCLsfD7x9kZ3PSvFOktTH11/oo86eClVHTezc1OSiEhtf5vzPz5m7Y4tceQCVhLZSYxl+jCfQ0E5IhzgJMijrUxzilVBshlq45wY/q8sxWiIIJY7XhaqgBbPDOHDTyQ0ZdKkJF08Ok6REgbZwOGx2uHKMLOGqOBngj8JI34dVvDQzwIv7fr8wehLreqpaE2WzykDqeGU5mTPC1tovg0J66vjGWhcmb4Ya/X8iD5lsnRoTg+JeuyIf7vjq9mPeMI2g0b8lJsDbA6QKhSHq5a2F1A9k193pMc13ZYkyF7QE0gNmFobDVT6uMO4bvKWGdHNmBzIKsbi69Rwec9QF/+38m6qwzMjs7g+U23tJZx9+1o1PuwbzEE3gKz77rqK8d5+7jaL3fFUkyfej7duNTNCfmo16Ue0UGpp5f5SMom5j10bn7n8stzkS7Z/31sdafeM8kgHuf57v78O12S4D0wHDmYQ/6AtcVhUj0PxTJWso5bHsYoIX6NXHeY96h6k/9aMfnfGtOr839Q6zl3T//e0rfF82774Ofhh050Chd/I8tP3DBXYZDe50wI7j+P7USHzI9ANH99bw/yzWD8T9x3f3tNuZU74qH28W/tBlGrpfGePsA8VyMwHqkOnjj8g7gxVPUDCDrN65qASWdw8JTvq7288nCAJ5mm2/3cz0zRRBPJi1dWXZfGsclversN7Cn6BjjNXs9Rv8z1bOfwf1YJ3eU+Tzec/t2n7d8RB/23/uPYfY0AfmUxYI2bZchf/qhZMYyh8BoZxLeOtDWJtDk2na8by81LZzcpyPJEkUamclrI6TSORvHXc1RnB/qP9kdZfB3lW2ndjjC3d0ZUWL8YeKc86Z8qzC1AVWORX+PXbJLJ54L25XW/8uH2B3L78rfbt+9csybdZyGEgNzk666ElTJfNDaPxYWDtuiqPJmzICuaVqAMyvvaMGf9wD8+XWqha2DNZTe+cuGRLhxpvSRVe6gulJJJYv6nY+6sMURqKpzSxNFVVvXaeCDsVN9DjqZ2yp62y+sUiPW0I0CPPsYgCTTQj5dEN9YrygMkukgRNSr0UdFe96JtaelFsbcTZ4ZXQkmgcbFVFv/Y0z7HwCYtGV+CrC6wgzfM/PKjTo+2k6skY5EPfpzjv9VVJc0GrR2f5O0pxJZ+nvsx5ckWwCV9LLWTJTMmYg+LfG9ErxqW3gD6xPay1YGxHop7qYMBz5v21kg6JejzDgzDNj5aSXBJ62LGUhaxWf1w9lbtgdWJSKm7I0JYGrQN2deW1q6eKw21KzchZtZLFcZSC5qhLbArNmpSlwKSmjCjZItZIvlcpgUSaOrox0Y3nJuCuEYEJm7JOlemp2VUsrbsBst1flsAOz7QAACAASURBVMVTuWuLRg/FogCXYjXPl+pVDxWvaR6KdTtvrVZOrI7DbwiLtdVf7+PqSqbAxcHg9N+7hNcZ2LhHGVNi1iZkawihwUSKNIVLuaqXGt6ifkG1C44lbFKd+ryFvqPm6ohjE73W3xaXrgRAh9l68sXYlXbXVvBtTzsCSa7oNbK0GBDkiQlp8fNvmTa7Z2oIEc6Ar4jF5vmRN9nQi06v+36usbT/OsLsSrvh07MCfM1QE8ZGfIxJTFBZ1NM8Bj5Na7FQtTqO8NEGz7Cd0PBhJGeYl9pMtvSrGbPCUEnIWkP/cQg2huxQwBseC/geGCkNsJchHaf4HEYW0I3ghKFEWNypoG9q4EWHZi00QzimbCvLAKF+/pGW4MvLTUmbs+1JGIV9eBFF6y/fsqcrFmtYo5xyi4Dd3NTWsOnPmkZt03c7KetzxXD9Vrt28pAte3LFZweGxRXtydM22/AqybMPjJkRQlGdUqQN8zSqeRSAO3yPjhkRIXKFYHxtQHsade1wqp7itdW8HnBdOErFWdTgs95cLfr5RFYgux5XIJQBkWwE9rvnf3VPv25kQPuXERauxmiGafH97xEq1urN962j/9qn82Wi2msl60AXRFflW2xMptzOTo+KVjtnIwwzOEeo7Z9UbTS90TJPUxsjhNTSDq8iRH0PlWL0vPqztRtNrDzLgHudtwgYGpc24MWm0w1ysbVJEjnn9n84M5pCKVEpzhfadCdR8n4H54WCZ97Q0XAC2f0zlyMdB7bdwddGoF5cQ5tdkR/ZHC7DLKLNwOKK/RNy8jSqp575YcwcIwC7HXqKMPXuGqSc+xgEw6HE+ZfGm4nC+eXI4emRYLmQvswmP/SMP6/HI4+PT4hYNh/CqbM66hZaWsZcBc0TOS9MOaM5w36iLonTcUFmoS6voNVSOu8G/oCKPMZa2TyS0y0RRd0hKqvVVF7hFRJyMJjJeUYksZQLKMzzDoCzr9nuaR4MJ8rDD4+8fH6mcsSMXQeSWsp/M4gp+w87zl+tnicefSOvC2US8n4GEkUrKSnPr2bQqmfncWvwusG/CbJXspoh6HI5sxSjeeF0p15qCzXH2lrDuN7XqhmPpCvxnQI7rhBWvFkjzB2PN7jyn0ZDwagjGQ0n8RGlxoJnMefXjt9TlFlofY6um0MMe/IzHPyTO9tKUtgLluhAQOfhDAWY78h7U43VV18jLwFQj4WxGJiN9sTp+YSqccQRGblto/KyZY9x3Kixh5ifS6SOj3GZbNioMDvgMuqbfN3n1cle86JdpwaHp0eQxOn44imw2yBBhLoYnKvvdfEAj3nekXC4lxHz9LFUNezUFN2qPQ1xwFNLXVIhUr8CQ5A4JCie4aGehuFpDHPkW5wWOQKdVFjcQUZqMTnU5bykynK5sKTMfOj4vxZt5WNweEmSLDoOJVV3+FaBWh1Hngbeo5+Dps2p4Zz/YOuaXmw/rK6YH53Xvn6A8EBEpp9+O3P4tGs4OHvt2dBplNozV1Zw/BzRs/2chj9XFYd7f9NoNIzRtyhwoOgLvAjy8NQMoiLC/PCB8lIoLRI9+B8aXxjwN8rYlF72BREzdLd0bTitwNZZYqmr6x2c1gKVM+VVyB+m9pyJhdLOTg7liQjFa9svyZ3rREy/ItJ4GQKmEMJIHsAYe9yyzTkjGCl/J5Sz64kJsQecDoWjnS/OKMwMdDvILNAcSR5IZJ4QSaQPidevnzn5ZGWA/Scnms4Z8yq2hiu2r81vuNT4bKf47sR2U0bYPjfqkP1FjwqHP/2ZaZrJU25wmnNinmenV9pS9e+ylToZ6cZSFfUSoQpM/MAiv4EKH1T5OsgJY2RpEuEv/EDlMxVlxjN7rM7WIKmq6anj1QlpepxEpLQWfhx26kcMB3TDefASQSvbD3wRN7arvbe2pdrYNAYAGOfTHeqlyQFX+8ftdovb/2e29bjs7ydwk+z9NkZ8x5NKZEwkVOGARXA//d//CwRdW7f3zPle5Hm0oK9lc90iz78janAYzPjK3xL85LDRhACu9/WtdqvsQNhZbvnUKzj8CEG1On9v/GPhq313/Bly0KRqpTclU0TYp4TkB7SeqZjT2WUxXlLU9KdZpGVkiSxd0zQx72b2+z27eYcmYbqYlup8Pls5Y+1BAsELjfs8nluJid3U3cWP1+2Dr/0tJ6M/0q6x+dv3Reu0t9O28fr6Tm0dtN+DB3IC38rg+l2R0fIuovhv+0Pt32pADwVWA76BHm/vu0Iw/yjIf09zAhaEcjsG8XuuxuTjDqYmDN8mt1oqjKWWZvwe+M83WzA87e8bz91S0BkiHe5dLfhbb7Z6MSFopDfuHNtbacz+c9ofwCzf2KzxZ2P619/Hm0YYb/s7COJGK7rB/SBi6dKqUpPXXyoLS7G0gHtVSMJDTpSc+cBHntMLospFugcl/i5VZV8nLlQWhGc63NaqbngsXmcwUbFaZ2ZkSCa4ef28lEzhSfMW73MI+3ZEbMworxqEvJrHcfVzUhQ5aIsgU41niR6Qj09IrSxfnkc60s+iXjNaY9tj6pADnZ+x8xx0ySR3OWzOsTfBZGSZIxq6b+xSlSnl9r0MBnYTgm0/y6LknKlaWqr9rpzoDHkYSjUpHpqzOsctAi+YJI31SPYpNoYqwpwzqEWGiyj2VZrSSV0h3iKpkpBqsdmLohlq8bSGSUlqioeGI9WyJgTSMHk1kRNotv1MqiTFUvtLMoeM5Moxj1RqEeg5akyPwpD0Wi5AGOtUewRcVYtIipTrkX69lNJTtw+cupUuqK3UwVhrMowxq0+NOQZ0jGbULohu8fFN4/nqPrl9v+9jYzDHbqULHDr+tynENL7T5X13mIiUdB0/bVO3r/u5Zgjj2TT8FnhQr6flDLD0G3HhVPpKCiGgenrVSO0dqaOTYBUmWuXxRnveQ09jGFtc0XYiFJwiV/O13/v+bCPc2/ncvGvFRhD7KW44yM0JKWWHd1eCl8WMFaLLYPRaG9BDSRDOFFfzbIeyr83aKUD7vqTBKOzCvKVLTp5yy3e8bW4iMpFo63cQE1qErFGCBs9D5Fs80wz/vvcSuMeN3aPSy+7z1NEDZHZ8Hmslvo/JlexeGmJIMWpj6hHo5tDg42k1owbE1jZ6WFD692ulhynuIo3hrRa1mE25FGlb1qC0mtfdntbDwddxNEpED7Ide0xhDaxGC9TXTJI7c6ildvUlieiYFCn3s/EI2RVnW8RVa+nvbLyQ0sC1M0quvDKOKhTz2pfCuxiM59q/NyQZ2Lndo61EQZyNm4d9WMer7/fux4+T/34lytx6MGjKeK+Mn/bSHtgtV58oFmnr8KaNPvjJFFde+5kZVRZ9imug8231cxFOmcGOBD+SQOowZGkG/MCgzUDkiuDknYcS3I62K2IixWrghLgv1qnxhxUtXmO1VIo7fupmc3pEpc+9wYbzmGGUU7ozn8NtmjJTnslZkJxb5GJbxWb4D/SZYD+jr15AV2xptL8eBKYHoRzfACBsnrcI8lugaq+4+D3znd+B07ndo3oOwtXx+ACHzalgBZv9S0rC8XTk4fBgw8YcDsuyUC4LdZqptXA8PvPw8ISlIh9oqL8wpUxWqxeukzDViToV0Ap5oohQF+NDS/K691pJcza+zXGKeC16wXnkZIYjKxlk5Ygy2dNSd9ylqJe2sZWp9PqIpRSGcsxNNjt/vaBaOHycePjhEZEnjp9/tRTXqqgUXj5Xr+eemqEq1dpqPS+lkEvQR/XIfIfNZEb04OkMC/rsip2zrNpSu0f2Javxq1ACWjwVptBhdjAeddowOFwK7dlb6o5brfU/RDdKvIOuHm0o1A91c+py2ty+ylBygT52mhwQ1/FMEMGajLDVZuZfZkQWTBr1FPmv68npMbB0LwA2on0l3Emv53917RvU+uwP7aWPcBzxrTbSkB1vR7gJpiQfdQArxbv2j5bNpY3a6U7jx6UZg0auK/6O364i2gdWqYnqjT4Nk+7D6ffH/ukroo/Iq1AflJyNX4oyIFnBsugFrTP8ULEyV4rCxUuPOB8raTKZ1OmCJCFNifyUqV87TSuEk9a9VfaVaPgDoJL1kfQhcXn+ajhOH5me0lU35fmR89fP7D78gAJLKV6+S4C6otSKUl5LW8yGk4ZeR3norWMbIy0bPlNelfpQCeeQquqR6BG8Y7SvGW2rGQzFGR+7VqmWI37z0oGCObxpOMmIvUuK1xWva54vi9HlWpV6cgO2WD37WqTh96RKTRY8olLpsowHl3hJljCCFuk8Y9HREcfgJvQCppPy2ufaadgKiNt0pc9VxHm3+7vxxBOPPx1IeWrIJqcfmT9fUF54wUv++VxiKTWcx4LPbbLpdR1z20vnG13AtjW4xlE3je+bvcwDjwa0zCOShGmemsNXStf9gzlZLD//7LRQO1/oeGF07l+NwfHM9KcM/MTys2dr0M+NjgNWJxk3ZretWAkOK9qzxXy07zaG54Q5Lww4Lnk/H/0Z8+mUlrp9HHPHgbFHXY93pdx5m2z8x7VnCf4B7mGdLe8qw//bJ0xPVcx5s/Ej//imfH90+bbdGv8PWAaDZXvvLSbhRvug98vmvjWO/ojy4jD9cbiaoTkxN9oZz6dMFnh1+WsWsfJGR8MrtVSklFD1g0JB2eFBDl4aY54n9rs9D4cD87xDpsT5cnFdFpyLZbeNgxoU8VksA8GzjOcPxwcm/6Jdrox5Bu/yVnsP//p72re6vYaNThO+Z1Ar3nAkofEdxyf34OudcPffdr/9+yPQRygAOi3sBMWu3/Ha+gPvvaX0bt+dk2/KJA3lbdw/kNZbxG/sz4lIccFUtXJeCn/56RM///obh3mHOhK5syxDX6wYgtHgEoKcQFfQhEBZg3C7B/5AvF0kWi9P8IHiKdz9xicVMh/8qS/cQxf3CND4zieN6Pbxxbef+yZWutOaou1mhx3tptXVa6Fttadv4Z3GEXXmFH+ToGjUAW0LnPylvk8rds1VDKrsJZPdAp8EXp3InUWZSmUnhUWEPC0spfBclQdVkMQhZZ49EiKJCRLZXb33VSmS+ZoKp2Se7udULdW6CxgtUjeUXKr8nJRJlI+SeUmujBeLKE4hnLjSFhcyugDhdWzUCGVVmLB6K2dX+Hz49InX068cP1s96vzhAZHE6bevNAKJrcHixFXVmaymGOqG5Njb2Nj8wff+WXlcbxsA09MjpbxQX2y+6TGHPNd3SbWlBNSlWELEKXeBEUU9Yr+C1elqzLYJ+kpFsKgKEVPMmdHMIiG1Fhf+i3nEaqCmfq4RIdWKPHRDWj049ESqclX0dEElsXvYUySTkqJazBBSBUkWsZKqRcJrm4cBcsXrkSNoqahUhExSM37nQRgRCtkVDCFQFSq1XhCtloZOLNq7pkoikVIXbFt0jFlMSSU1ZiDOdBjXkgttAV7ahFmDxaLF0lmqspTFam0uUcvT7o8I1lIj28LaAFNrcQN8r5O3MqTX2qLUta6N5w0HD88JQzSYrj/XtCkA2HDBUo1GTFkG+O4RHq2vQh/L0H+k9IyxVWjZHMYMrVs9fShgWuonzitD+7bdvD7KgIohMq/pWY8z7C01rgz3aiBkCThKjgMTpAU5u+E50RxvOg4fIltibeS24iv2smHfMZ1dMCV0nnNLH6IP6eokNxxOLMulGbQ6Bhk6GEnLYDxKrmSP+x73e768HMkooj09Xigx23ltyourSbbfRliL/pNHvasWmo1JDduFR3IzYuUEnoavGbWSeKUF5yhiI4fXRwRz4JerVVw90xen8VwSc/VfxYx13XHId166Ql0DP3ifoUyV6Ff9HAT/ZuFTrvwwmJNkxt+gc7FO1p+2cXc2QQY4Ht9tt6Yp98wBcdZjO9TWsqob0elnPQ7Gt2SfEU7lxg+qcvP+LZy3dRvmZ2clHBxANA39dbwloZz0vy2KP5GnmRaJ67UBa81NeRn9G74cq0kHPnPMIyClMtZWjz8Mb/cIrNGgbs4o7jwVmRBk81xk7uivvsP3jbhEV7evGI64rp0f8Rk5iunnsfEYMvLhIwwQXrgtdX7Qv3BQiTSzAXuW+tRTNjPQl4Cnds4y6o5mvYlxI27Itn793Cs9c0acaVVynowPQo12lu4IEtxNi5jz2qdmJ/M6m+rlXxLk7IruGL007qc5mqB4Zpnazk1LE97o7rgPI80NRw31udFpuCOanDN58ujzksj7yfg1nH5KaXsdNEukVxXM+x1SzWnQ3nk2GHc6U0fj+YgOB5wNMxRH4w11zLBKJw1wQXRG9ULIFeF0EgbCKwIoYOVjLfm0Oq1KMvutC4L1qQ4nxH5onMEVYPP6+sqHpw/tzJZlocyFy+Xi/E/i+PKMiDBNPQqtO507BItlJppSpk4zglDKGZg47DO1ForOlHq2OsGiXC4XSrG3VMzB085U0AI32ocDlcsrBpPm0GNyttHZKAegVMs69TiDKvuPe6tpvljK2Xqolo0qgEAVlR2t1q+nXk6aqMkUgGnfnUKSmPPxpZQB59i6JMxBSbNSL7W9o0HwYnRDH6f2aMqJhDnqx/akZGc8BY1BG6wGfSOctpJYlOhweJSOG66UlGuGyPFZpxfBj8ZaC4O+pIbjGNRkRDlkzzD8Bz6POUieHLcHbun0SqFHokcNWjXeriXh8yw55lySEN0jCPNHg/ulLKBQjnG+9yinpi+Y/HUXNdl6dba2NJQwAAUr2HmbLjf1U3QG9o2OvwAPJPkIKEWOV4Zy1TGxvD24F+PZ43q85+VomddmEUbX7/h3cV5ymiwleayfYTOj42A1uNM0kdXOyG6eG/7GM4kYCNc+rNhugbJULqH3GnlhXYE+w3J1pXkC1WeqJnh5gieYJjevpIRXBzO62Qyf1XAoAlVZlqUrf0TgfEGSME87pjmxnC9kSeRdYvqUKWVpAQVLqSi5O7MoXJ6/2vlQy1AxPX1o6WdV/TymiemHH5pM2vCdKtNkJSHqrFS1nHgpZ6obGMLwWKoVZVevSTs9ZLJ+4PKyUPVIcApRmCicfc4asqmwG/a88XJEFrGemcwiEo/Ul4c2j/yYHYfbssVZtv4CLxnRrVWNR8f0FGMb2PrWVvwfhqPPjjeaXCpQ5cJ5mSyjnkeFVLkgnrlDRSAlkkLNFWpyGT0cO11miUxJjpM6LxaZ5yp10cbq2f/dkB54LvidUXoxpM4qmkhHIPe1323w6JQSj396ZMrZAhP8550Iu7/8/+y955IkyZEm+KmaB0lW1QB2Tu79X+5EdhYokiyIm+r9UGLqHhFVWY3uwcgsDOjKiHB3cyNqyskWXfbAl38U0B19kssHwyHKh0ENkUEmxyLijjTBVxEWQ1mh97pH8d4aia5qpUOmzcDDo1xp6AXH+lhGGuMJVBXnv88WnaqAMLnB/RkTefSsAk/qxmjAdZxDwjp+sSjhKOEkbtljHTiXoRAKXGbz6HFeiuxcp/7wt7/h8I9/mJ4InkUTik86+Ov4q6p4KQoUjpIyoa+p6xb3lO9rg1eQ5A+1Qkdqu7GNv+fCLzci4NFH9Oz9RobaxVnRQQJIPaiDbO+efO1O//l3dJh+qv1lmcL9ZynhPzRW/PPG89pXfiazlgDAM/v8FXgpjiTV1nWtRRndXxrfqqtHf0cY4j/5im/xCZ2egc0ENLaMqc43MzMmtqA9Yra65brBLG+uD7VsH106dl473UKtFALG1BibaYPddgtqjGk7gSbL5qW9Q6RjPnTMIgvMGKe66Q34L+xWyJ0py9XbQi8GePYpxY0l/oU2aOetrujGtcvfNG++6UyRuNxXxmXvwe5Swfnl9yv4IO67jin+3X6l/csN6FcB7MaBuRqJ/qe1JfinAjwVwKvr5b6lsElFGc/JzAKE19c3TG1CRP5N1DDrx2uh/3K7gTV+9r5XStyEVwIe9AU7/YxP+HWiVc48xhr+eXv6q2v5oZF8cMi33h1IN0Rpyk/B0NHF/e4m6sYuSoEoIoV7dwP6bIKWqCkeDlDsXNgEgHtlNDziK33FHTNeWbAx8yXumTGz4EEbntmEu8YKcWG5KnSvwVI1LtRoeksLbS1KUganZNm2BRlhqRbRc5pnUHvAWb6Yh9r3N898MEyA0ZgsVbgx5C6eJLOqV6FMXhX0MCJW+YFC3wV5VfT+Nu6/gnPCWLPu2+p7xpvjgglhYfQyhv86LotVU4+CpjCUsq0VE6NNbHVjggndqmlIHHHKu1jEvCo6eo5HRKEsOByOuG8RKaouNExgmWBqkBnhbAN4NIrQqA+Wy++RgwyL8nZlMxFB0IaSKucMN/SKeaMLAWpCNaNdNaCDOaPMFyncyZkGJli2e896QKGEM0Wc+StYKlcovA76SN1ua23/hWJmYWyJutPRXzHCVIN4jWAbEII0eqyZ4mrY8Q9+3wrO0tCx/r2qLK41HdktL6+MLcT1TCE1hdXamB4wrxiRCh4ofXs8FxwcSroIP0NHhd7BhW6YooMp4QeEEbVF5zSeL+e2mqOOfbDvqzH67xF1qCjpNcfIctj1HYtoc13uZ6So7H1eCsqxZ/HbDxjmwQzb38P57IpjBU2Ah0kUoVkT3hPzXcHTNUIhhXkDZFTFlXdqwaS+/iZANTeGRgrE5hFgSMWUlawojNxCKeXvLq9Z7sliGUyxk+eAfG3UcANRrhVprFkYc+raGt4xY4yCGTDfJqNQ5OvCpBlxxa6As2h7G0ekkjZ8avXXqxqg8jahyLKvjp8UqbTLupq50AWXOK6XqPcb0fLXGmH0MaCz/Lu6vdym8OzJpa9xH61+pvK7AmTGqsBdcS1OJbnAndHKZKkcp6kB2obyWIFO3WFipIC18hMlU0Hg3e40KTKOoC/OUaG+OebqDBXCNoHcvGaweI2v/1i7cv+1nyLv4/oWHV+oXvnJUPJSkkRa7NlQxIWJZADkNZ4o8AZgUZ5J/6DuXBMKUM4a5imMu/IVUKB52KfvLVxpquDEswmzJOnsm845VOHMDKhZA69m3Qkc4vR5lBnyXY2ItZsyY6GDQfPVnpOT973jnCOfzSFk2kzpOASoR0slQ142RRd7mGtOVUltvxIli39tYwDa4gIYfgqqy2qLw3h+YzX81mIeze7bZod+DqcXJJ8HKNar6xwSoMD74R377Q4zN8yTpdPv0tHf3yHT5LVQ79AeFdNuj/l4KB0VuskMbQ1tMlzNTaFdITpBdfJsAwyazFFDRdx5dDiXxTijbrg5ZAYrYgZlkqWj7wJREtAPy/kqFDL3IgnYn7dvr/aONhyNDK8raEeQs6KJQnYAaUSUWhmAcAQs1U98XyLVNlm0jq/+2CUFwfQJUWuZiXGWOZ0YbF9GJH3IdHZO9QIuAa1pw5aXYGc2+YU121S64nhP/maKccll1tWyj7GE7qW6Q4YzZb3HxlJfq07fyEtSkM/RKRThIlX6otHyr63G8eJ4AhFVNg5v6HyWy3ALD412fRzx3AHAI9YZh35Xn7Xbxc3LuzNDQhrBLnFQgzlUNgyaDyk0m3jhzGlwYN+7dpxnW72kAwQkqCP+7hwODjkpZqRw0tAhbwR9VGiU6UDQFHgYKCWPC/VoaOnQPPLunCtmDJicV1GX21vrkL6xsiBtg2k+Y+4dtOE0cHfcgUhB95aJz3hlzlJDMRY9kxkQQm7wc8STBVS0Bs+K4Y6owqgCYi1a1t2IDig2dw2ntx+ThW3d7vKX/EOyQbGfAAh34Dv/8V0XNEovDoQu5F5zonMn13CE+8lRWMhvReYO3lBhsCmnI6jdgfnswSmO0D1LWWa4E/ZMeZYxiRkj+pxoOAL7Xoyc95LvDWcrjXUKfjXo3XoZfCx2Jgr+S90UYe9Yishw1IQHTE8TdpttloyyffAuSyasp//1H1AVHP9xguAt+SVgqVtKozAHzizQUSPOC02oe7DYlyuAVXXeBC9PheHkHE6IOaICW/0w43Q+4/T1i+8pluVRKTSirqujMUbrdjh+DHhUfOeB1TN7KhOE3Oiho//FxBb0BJZ9wPVRk362EqZ+SEwPu3xuPDuIJZX55rmI7xhrdOEky7+G5/87t7WjxwvZnBf1vMkMy+HscMlXAl/IUqB/IeDzly8AAf/xl7/gP798+UPG+fXnJPqX2zVcRxVgL65dZnaI9kN2f9U+6QhxrG/K5XZ8wSCABMM12nQVTU3XTLDyRhMAIcb72xuYBG23h76+WdYjWIm7NjE2mHCaTdZIXUdrmKYJbZqw2WzAHtB5Op6SRhZV1kW7VvcdqLzE0Mde3JB96MLo/Ge1n4plNx+k6wj2ZiuTCTRWv3pG2ECOV+XgP3kt/qe3f7kBPdpgQGxH4zBVTzf7ffn9j240KDOiFlgVmckFTdSzSoWrQiGUwbhoEdKJPBXTGa/HE/7ycI9ZBH/9vMeX769DuPeu17JpKsiT8Y5rSwYuWEGRMXoFsjbVrfX7mRcUYEb0hm/5Jvv3Grtl7UEvU4+McRfp9ANtjZzq3K7eH/zNxXSDhS0e/Ise42td3Svv1cVtOZigj0OftoyoivfGugUDO8ZpQl686Z1MvcJEeKhzVkBV0MlSbPfeMfeOPnfM/v2ldZCal+2zAoSvC8XD0QWOIzEmthqLDQ0gQDrQmmLabNBnrzdchJsuQwE6FNCUhqs7BUg0tYOmRDWBY1bFK0z5+SqCrQq+y4xtF3z5+99xVq9gS7Y/M5BG4+aGGP3+nOlBk5gKwKRoT2YEDlmovxQYVUBftICfQl4U7ZHRHglEd1B9B98B+qbQdwHdubd+eYaJwDt/PxF0toEQWYr9UCIYXhGrI0bNI1xC1iM0N5YIqa8XQZjAQlYPvRnEqArms/jbjSHQA0B7DObblU+Gyg5QJfSDwWDbbnE+nnF+O4B3E0gnUFOo15KOmr6m8Gip7KVgtBLxKaQzaCJY9AdZJEDgOlMJ5AEQj6pUdEv1ywAr5ykU6pYG3hUN6lBG0kEyjOo1Ap3B3qfvgzRQg0UWiEWMRCr2fB4KnRSv7wAAIABJREFUqEcYKdxhaRjKVS1TyIgqGMbzSAOvrgROZXtEn8euUBgekOcgAK8a5uM7yvX8LYWu2OnECogISqiUWtGjk6wflfihqlgH7VrgeP8Y5TlqmqmO24xCIzOiXzOkF7koBcbhQQNTJGUksN9JJvCPNO2j3nYqoI6DS4yZSaaALZ7cWtbDfkBoieKn67WBbc61tEpVfppScflcROCGMgRa7xiKXW1h9PErOuBOnV4zKYRMQb5rG5gbzOijMbvZlhDKqQs+IV+9ZsrHPHJPKs1fKDpXn9UNPaJuUAYQxi2MDBFMUdqBxrqo0zsZ0DxwsS7Wd2hDYuV97qGpI1OGhQMNlEEsnu7ZkYPWfVNEphdmQXe8Y2dLADLlr51nvxDK1EzZzp4RgAasMlYzqYoT5NnM50GGn8jrqTODFwb4YrxypySQmgJQPfsGXKGaSnRdPH9NIroqN/GSX7R1Ld9ojH3cNPbJFMJL5mfhzACvvxUGdL82tQnTZsosIVaqAcDsZ0B6OmuxErojKwNjgmofUcU1tWwIiYtJVW5RBy5Ux9EhcDsP9WMmVK8wkZf3J5g67VvsTsFXef9gEAFoUaTlRni/a8Od/81UzquxUDE0+zmxFPvhOGD9ZRkBH6v07uNEIIjc8ziRRm8jIw/lOQ/YVGX0WN94MsuODC9644siWZ9mDUoAmZ0h8QIN9B3pm6FWax1Bh6NES9BvV25DNUtELPWlg0iqK5YVxsdZHW3kHHECaOeRa42BmcA7hiiDMCMU/Bqd+5kfiB52piOal3ZYuK7tTsMJMnf4ysFlB/thebTuNbfafqUZgKJNe/RzB+hcb1/1vXF+ComNxA3vokdXdNu6GNpLKf1C6SXq0cVHBe8GzyTScXx+caegDu6CDnED8wHHtzP294/LOcTciMC9Q1StjiozVK2+qs5kKc4F0IksClFmM+IRA7o0bkswR6WperyM1yQOQ3XjhgZzrzq9G0e0f9yDiDCHgjB7c2OWG6mjZrYZEyzLgmaWBju3nRTt1CAbO3eMDt1usCGn5yc1OKxjfVfQnq2ONwhyWDrcZxSoH5bj6ZBOC5GtQWCG9eHMYrhUNfCRppiX7IPjAvUI8XS6w6BzYz0NmNK0oRH5P2Al+O84AkFnxO83JwBKPDDk5yFTqfMYFL8VWEw8QzJguwArbe1MK9uDm/3G3uH82+n5bDJVpHJfHcXuSHLyNdj5ME81Ewsl9lrxNytex89UyD2xHrZehYume4DeMur35I8PufuynW5cUQHAhF6NPYMcopE5Kx9PRyjUMoYBaOuyM0mvzAnkPEcsZxi87FOuyqq2dO+CLrOXGCtLowGWsSLnwZP4dZEgVMBJXyFokJcG5obt/T3CwEUYvFS6zBOQpT+SJnTLjuNw3v0+bvZMQ0ObCK1PmM9WksNAUtGmjfF4n1vSIahimkxyiqwbls1oDCEzI/ic5lM4PNGSf/B1aJ7GXdUyXnCz/ehzjw7Beg/BK9ZgcfavZ9ix22GJvwAYPFCSK3DqWx02DgDfNQR9atij45B16WMiJuMKhBvgaddtP7s5pfr8qtP9j1o618XnEECYATpD3NjcvJ8NAyKMU1N0x3UCc4S11OCcztiDP0Vh4AgBppH6P+SDgW+LLLOSI9fzcXEC4pkdN5E5UEdON6Z7PPz1weQMP2+ZKZQK3x39EwA0TP8x4XhsOD0/O9/NuFd79kAVl/BibKrls+tWEk8icNZytsnOVJnRv6uaMyG3BnbnEHEdZnUEELXUz1063v/3f0IJaCve2sYRvIiiJ2K3vw8jtSeiWmQUoXnJkRsSqXW4n3xv9/iEE30HAZhVE26qbKoA3uK9X7+WwzLWpZb+AkaEdWFiFvMPp9ZaEjboU35XLY/++Fx8tNHq75oNvNQfXNz5u9qnoCmOP6ohlIjMLlD1DOXeSQcMMDNmKJ7UMo4qFF/J+u//+DJKLKzO4Wd//meG8Sf9AyPPr/TzpBZ5Pu6hDD78iC3rUT3qXoEn/HysFPfokv6/+cVHBd7JnN8menS88gSdzti0hsl1FM0DCKQZvp2k40xscvjhmC8z/G4lS4UIG9g5b23Ctk1Jt8wRm8Fk2UHZs5rFGc7skKk/MzxXjedBA7KpA0qyFbqEKVU8imZmlSFi/Qps//xeLXet/65bnq4VHtWK3+sYK+8Tn6h8Lk6DUL3IMD1uHfL8DZbx3+0X2n8LA3o1GCx//8Poxx/XiLyuS2Emrt4W3mQBrJrIbPZ0b3FoTM/I+NtvT/j//v5lxbb8vCWTfTmKi57y2+9eXHtbxAb9pk/4Ss833mbtWt0OwfX6urfnMq7/yv0fab/r+Vsv1lufdXVpGO+NhxhMmLPvAKw29wHB2FEyGMY/u9JTARJBB2F2A3oa0acZrTdPCM7YFwH/NbUXxpjvW0vD2QOANwI2CvRmKfyJ4CnMJOFXKYRxpGCcoFUUimEAUf+9K9BhSrRZBE0EZ+nYeBp3i0p3w2xZp8HAey1URRqgYp1BQHsc7+0vxg62R1oa0WGR5/Kq0NcRAVxlKXnzM3p3HUqCebazrrmvPDG0q+9V88EP5U9utDMogy9XSFdwA0BqUTVs9corzkhZz5kFKvuqqgY0ewCeqE09vEhhadC6KCBnE+jd8J0R5uRKNlaEAYwd7mIjCHAjTGEAKBL1m5MEl0gXKHnqPIZwN4NJg6c/ZZAK1KM7h1NLCH8G8CHE5/VSO1kU4CZocAXG7E4GUc+RbAwjojxWLxgvzXksaqP7PlXF/MIjPo3y3psUY3zd6hSKwmBaYKBc/1mrEesVBRWRbnQa8yvfPvSOD901WhjRf9hfYYrzJJU6noRiOCeAmkcHeA3uJLcHNYUJKNcxFB2RJq4uLZV1BzCMJP57yuGEBf4FBo2qJ//aNBeerykAD2PeArcHfoxzE+fVYYkZ6CX6RtCgRJBSU1hhwo2yZqYGg0NaedgWvBhPl7Gs8VHgLhsnXHmu43ujxA9hCGjUQOTRqV4WJNJ120bqiF7TkHNcCxXhfz6Oha44xaTK8IdR0O6x7ARuPJdIr36Z8WHsqxm14j3p4F+0B+LGi4Q7MkMME9lcWxjQxZyb0qIVa+aRRAHHvi4cQqbjt0gJX82iql7zD+zjMJqtIovavHVOayaELn+6uO8qrilS1iLynJY3Eco4ImUHYp6+Zr7/MedM405W97019rSgNntRhXIzpTUR0qgecOACu5M6QKNER4lmpjEBo01XuFEt5y1/0sv1uLJ+hIo/r3O6o5tBD+wbXd+S1eAWJReKAHzxph8haP3ZDbCzU/AnoKP+J/OYqw5aRkRuSBhrnPU3Qe7ZSBY9S+oSgr8u0soDqTCMxRorOqKBB8xdrpoGvwdNJwzRyGjjkeg6/sZLEtVUPgmDz9ak41I30lg0d54hElDrIJo9242le5akQZXeLhAxApepn5nA46EhlOONY3uzKWjXoMd+63JZwp/1fEYY0S/6KEzx2Hk4P8YLmp40SxXb+wmnlxl858ry1kGi6O/vmPvsKSJtr3mzw2baJU9m73ZaFdNgxgRAW4N46keNwlDu9CEygwmY3SjC5A443mfILUGMmCwiTdRdB9ScMh3l5JNS9jVgd9B0CrKKgCY5Fp5zG3w1vGyBWoSVL5pOQ46xcgBWoxknp1lnNSfVRU3uJZ3ObTFkii6aJX5EFF3nkWo4xg/JvUsexfte0M4FPKzWIByYbpCTa3BHFGc4ugvauaJjhfAYv1Tizy8YsnrWlnQ/HHsUJYo6Ihq2BD5ZaarBWMQ8FXr4Ced3nQxcua3MZXUtooEXAf4XepnhbA+Yvqhj1Do3h03KffyVps6eTdj4+M55YQlxsU+KASkwJqqRZckJ+Z/I8DFZNFvAVP4nUSJEce7dU6EHH7FaKNVFRCp5yRLoWCeF4YXgGAGY/Ee2sKF7IBmOY2G4VjIDWvRDahl/ugub5FnNQva0dN8Kleb8ukf0MgBq4E7owiD0xV6wIwQrzzYkXHc78z4oHb7ipaFDjDjnsRADjCvbQQzwPYHe7B7FdRCtUejjhIzugeFAzHQHvnOn07uIfXf8gpIxpLSkh6qQDtMFhCyPKGW5pLPr9+d3UyZB4HjdS1sxBx9qtLWl3AHP9mPryCDTLQhB1o6xrRjPF+MfMrzxEz4n2KJXx8VbJy5ofJUtic0IPwK1HM5AuP/LPVob7ml5GOKeQmQXw2XCbr9DY8b83VLlz/RqMktz/ixwRHnSutXFu4yvWxlx66b+oD2AsMGT9+n/qWXHFCimzYQA3qvRoquWPtp4QqfngftVPXDCYVStZv1brHcd8qLHuKqY/tLQ9Dccvn31QJfAP0FXy1mrHV2SmTw/V6dDwzmq9k9AwlfC8Hp9fxGXr157ddg/u//PaILr0cP5bl+TB7XAKMDGffZjmfj/Csh8J4tIv9Vu4b//6lYN3n8B4QbXfrPVXAS3jOefFfiOcW5qo/L3k2fg2avxv+yMuGUW62CyUlUTmY4CzJjYggyM7tjJY0wgek8+/jjP2G432LbJHfMIXdUcaqJkhu81Y5TRCEIVGfZMRjS8/ehovLJEgcXI6XrgkoW8h4KvMc7b9x/wbL/KO108f7vrG40uv364gysnO2SKy57tzoVeh27c9e/2K+1fZkBfwKoTRVDxai4CYmW2/ksi0SvDYlw1KrDZT4qq5LJoy2Doy9iSIJhi8HA+o4u6wwjh/XxyIVc9+nx1ivwFsV5/EeAfuHp8Vm0gDpRxWF9LD5UfteQjfFgh9FbF74+8t55cQFsb0V8J+KxPgD4vfv89u3kN59xmopZ3ra9doJXAySvGVVcd536s9itaKIdSDRWwXjwYFR5xXRiFd+9zD8LJn35XQYOns9bRv3jqwt5nzPMZ5/MZE0+ekqWBqeU+xDwDskMBfgfCiQjCDJIJ4gy41XrzOdBIIfgegnWJ7BAFIGRRSNzN61ZdUaGSCsdZFTMEswoO0jGrRaGLCsgl325deQ03xV0eCPvDjwAJYX4JSZkAGQIPEdk9/lB7tEf7s+ZffqTRpYobed6WGxmKwjxKlAYYhYJpB8XZIizZo8aJwDw5rhL3Qo5aWzxSRauia8/xm/7Bk+kQRh1edTGSCNqHooMA9INkemi6G/OphnMCMB/PNi4ocGYwd2DjShlnrERgigcORThZsT8BiHS8xwVJdSYsvAebK8/FazaG0U4A6MmjURpSaUfoYy1kGMxTRHXGy1fHBCey9LtRE85ujfSdQ1nTPMo5zl/vHWFkE6+5WA3aVfCvRvU0ngMjPWwoVoNRy0M/aNgwkGJEphdGL/qHi2CJlXWp1ED0QyF4OSMatbChSSvr/dVwX65kevesZ+mXOwIXWLvm5ETYZoRaNZw3Wt5XaVRl4K81U9wx9OiKjXuk1z4OAO5c9KWxR+R004wlhN12j+PhtBBmDfyGUFbXQeryxii5OOsACNElzNccvEo8lUo83z9Pa6yiaM0NTCQpBWYEQyEkyeiL7YcCmNWUTsKSqffq+y7enwRqCVvrVQ5lVHrDUI3oSmYrf4+IbgKG84lYlgqmqDdsnsUiw5DEzEkTJCJ9wglFbSHMkNwcPyyFJNcnLraHipLdjoJ5MIu/D05jgp7ajhb1hk/ZcIYbSsT3jgIfmbE38JGS4Xn2OuhVGaasWNjgyxxCWIz7udUas4wWhvQCPxl9oJ5qEpL3kOWivMr3Dj51vd83BDRCKgBHB9ZC0XsBZ/mwbUzg3WWkegjFSMN5KDnjfwx4elby4RlujEwCwKgLKhpRobIq9RKRLQPWFxFEtnGJS2tJhuA9Kj6NFudwKEdvtcpLr+9zXK+FHhCKTGEvlEgVXTvKs0gp8MdILMpSL4LgV9JC4jcagOgT99qNofD38xEOOF1HqvM4N4gayVqi4t2p0SJ8aXHO8owBIzLHOwxWda30X4tva5RsYKWmyFHCeT4jnNw0eMliOM/IcwmD26Dh5AQknDsMtTWHsY5wggycTGWMVtZmGj1u76Bq9AcJy4T5/Q2YJscVbkhdSg0Ycoein05ou61Fax/H6l+e54hM3Iy1umY8d9iOBY+U6D9XDrmRcQvIuaR9d0Zvu7/DrAKcLRKUpDut4XH2AJzf3jDt72A+mQo9KfokaF0hs2CeZnDbY3d3h/n1DbTbYRJzKm9QYGro57Mj5pb0kIjMWCeCSRXCzfaokZWGf+0lfbutIxFG6uZC+4y2DB7ZDxtkIefHdTun23uLMD175Lke7NxsPm3NUN+jfiOBtryo8xrrb45VzfDk1owbcYZA7qSqVlc5khcoAD1bdhULGTXeTUmTJ4AOQ1tnAXr3Wq1kkefBfxZeVLIQluNfDGMR1CN3CUOpyQTpY07Rj4FZ4Dkav4U86PA/nKsjS5bd16bJa0GHw0s8484ZWVonssaM/TFWZaQKT0NRWfNwDFLqiX8N/1lWAOwYOCm6ZxgIPmq6nwACzq/nfB8QDhiDdI1dH7je3hGucChwVmm2fT77zxZEMZw/49YTbNtBBMEhY7ljLQb3gOQVrppyNPYXjl504HPV5OfDDRzOU5Of/+Goacaqic1gbVG8jI1HWh8P7+4UnafB+texelbX2Gl57wNHY+Ddup5RLkTzplgAP1e9Q+DR017N+Pj2Ys/LFiKKtrOOw+ebmO05ZjRVy0QWtIQBOc8QNqOsimCz3YKJ0c9z7nGcW4Kiz+L0QJDRylBzDtCQ67xsGQU+roY3+3e73TpNi20LHofTYQwqjkdi1600jsb+vMpwdi+wEJRDAY90o8zopyvjatxHBPB+ZINJXlMV/f1tcR5ITaE8+5qE4ZmIAYksHPYuDgeG5OFivzlh1L4H86BgNX6buXkppXBMJbioBcCy2HR/VzrmpUOrFL7c0hMbLxPvi7Ub8vPSoYiSlwjcmXCOggvL8Bffy9yIKIVQwl2mMo71qA4ayW8H4BcmKuaz3TVs/8N+fP/6bnSmyCwiJbORvyP4NuLBc1Y8eaFvLwhNCz+rqngj4BHP6PNvkI3To3nGuc84/v2Mu/9nD94Y/bO67h2EJ5A+o/uaRFmPZbGql3QgNhgww1/gCUnd0JIvN3owFlxhOKiBcPz2zQ2NfjIHC7OA6cfRmfdrNO61RDx/chh/JUXmU6pyGvGAm+byrveb9BVxJjEM6SvY+2ijn95waaxXuv7ccGz78TieymUtfzt+bDyP9qjO/7jj8/cC258U2P72Cacv37LfgLtHUXy5MfYn37aPJMJfG8I+K/DtA+P+UCv9EBG+5s9j4Esnu8u1Zp/L1x9M5lt2F8AKgMwBjYnMFhN8Fx4h9AZphAPe8cBPhuuZQa2hbTaYREHcIK6rmGD7uQGhM6OLZadqzOhdIAIczx13HrkOIg9sasZb83B4URp63MwAcqW9EPCZaHG214EulbfUYBBW8E1YZtWM6zfcXuqNP7l+vd2YzuomBBItuLxcqz9UXcKqi/rFAt0olWe86qfqrxL8Vuv57/bx9i+PQE/DQwWm9T3Xf/7TGsU/wSA4Iqrgqs7U5f2Vo6l9uUAT3lMCr+XbxVJoiTEEgYRKt1fbEcCdEt6uuX3faosO6fL337G4r2REb1JO5ufDw8m/zz+8749o/xKkcPOlV2AbyIwGQSYGOlsJNAmYg0AOBaEpQ7t0zPOM83lGayfsiXFUS8E+8djvSEWrqtiD8B6CiDImBc4QbInNC5AIG5fIQtGxZKw1+1IFmE3txMJpbBQ3PpIA4pHOsypOKtiq4l271fISxSs6duLMMYCTYghDK5jtzxa5FeeLYIJTf4alcMf11Kf8SJAXBflffqzOMGXH7gn6tpA6Uplc8VK8hzYA+nhrCNrSBUoKkdnSQ3Mz7z8shRoNCxsBRCPFKceUPV1hZfIXAh1M6SFHtZTzB08nqUjvdgFg9VFc6uyShiJxYc3qegoIjLaxvZcTwHuPolIqTiXqUbOUSn9m49ZEBBQp6AUQV4STiqfpNiOREIM8aICIoCM8NBnmpRjrwo8z3KY8JNBMgyHQDmjLFOvmHOCe/G5UX0SaxznyFHwLA7nfK4TbddHHoVwydzmLS0BcX18Y0evt14hCgcFEDVeYx0smMc6y4sqrLtriPGBT1R7Z1sbz1TAvXpPnsHyP+zKaFc5Yeyp3PQSfYOsxxz6Jrdr7+zuWYnRd3zGZen7yZ6IFjEV0XT47DnquiWLgvLF/prjebLe5j9wYc58XuGghYFfmX8ijJ8RT+Q1DFXvqQ/JU4sj3jz2P1NQxrlCcDjHYccRYIP/dlO1Elm7R6v1x5vQNCI86mEQCmgi9Kzp39D6DJ0YXMScVDXpVxhFrJaMERRM7yYFTLhROUW8ZIWiQpYSEmmKCyegMydgj59kqvgAInMoxS0HJbPMOw6SNr9v6ONsX0S5IpZtFEipRGpsN/2rWbov9Mt1JG0Ji1FNHGNLLPDEcFtSIue11IzRpECWwRGGMYZjM+d0q7kXLj6GMRoHv5GCLYHVNsI97xpoEjSpCsMNoGM5r9PlYl4Bd+yeV7HAnC0g6i1m5DFdK++eFsUUvINrGGUpRWjrKKEZksrqi+qaSKmH4Q2gSA/cPxVfQqXUL5UmsQbkwxla6DWi+JmVclzwu24UHuvNx+buGESd4HMl1rAbHNBxQ4OqBV2w8y9Fc7M0HxxtNgSxZohlp3ld02HFLKlF8TLm2imGEKx1j8LTRx8WaEUBg0HYCbSaPInZ8qJZN6fg243Tq7iR4MsXSbgccYdnaC9G5iG6qE/1J+9Hara/9XDl0rZ2XBoxF/xE3GTwHDXitY1AzfpN65h6XS6b9HrTdgmApjfvpjM29QrzUVJPJDSMEPc9DO0GasGYGO1PkqUTmEgXvCDqbwk7UGUlu0Ld3QDp005yulv2Hywv+iQ2zZzZEZTOw9D7f1EGEkQgIZ5SBoS+219dVYfxS0kUfkwDGI58EbRsh8K4SlHCiAcJJjqElyxWAOwAHlwOd3g6T7zCQB5s4spxQGo0IJp+R4zGK4uUIuB2z0jg/AQZ5X8EzKDJbOVxDz+H4RyM7ww0IV19Tn+vCyclp2tp4nMZyxE2231Y4RXycirYlyLGclwV+GGu3xmSeFfwH5/GioxzXtbZBRJQv7zvBIob5ynNbmE6IuDjXxXJfGVnumePGyA4So0xylDQnHA5qJ3kp50lkpRQkXuLPD9qiLnOZE2Xv8RnZ0foV9ftw1Cp7DmRtbSIz1pHjjEx1HeW33lwOBhkP1kYk8qyCJg0dXs7Lx0bKZhBPHkFLrmXj6/nssjKbUUqFXMdn52DoSsqM1PnaCqtZ6sjhhgdgaT7jlFZjHQjpuBb9wGIDxXmXkSD8EnbiKSnP2loPg03DffJ2tQd5l3yu7hXB0gyL8/MQATh9mAa/x4rrzXmSVcmVsAQ0INO3x7gswpcdPxAawYzF5NHyzF46ysfp0efcCOtlSR7CkeRtA+b6bA+8lfJrCOb13FqkAQpaBQDc/fUedTC9d/QunuLYjN8j5TEhkL7BfvBx7NHjQPtf/4H3b1/RCOn4Cyh69XgPHnANQz62ij8TR1+5r7YXAj5/E8jOzt3h/xxwwncoCd7/N3D3/975/gEiLmvV9aclBRgnxwOMqARv6DCevxHwSdxgCy1LXig8mRHQOEGUM4VRZjU42Yq3iJal3sqAH3Scn0clPK/18kXQG85btOC9STUD2tbXEb99oF2jKhe/VRm5zO8i+r08/5G313symI5sfX7WHgp5CVwV+wtYlPnfYCijr47sdUq6HMePItSjxR5GMCDhj03rDgCfQfh+5fdr8uG6zWT8wa1a4Iv+yPp8VOAVwGcMngCJmxiNLECPGbjnN2w+f0Y/KrZTwwQLirBKEiY3nQErdcDsWZ/sVFJjHM+z66Uc5fkZn1rDbrvFtN1i2mzydxuK47PIHlPw5KPamQ7725KXK03V+LiiBxvsR9GDwdetdPH75KNfb9fPEK3+Xrv2gZ5p4C6zfRRequDAy0cd6m7wov9uH2v/cgP6BafsCH0tsgy6shSQ/rkXxyt11ddg3vKaC66DeQ1EVboqDIn9POZAzsKezvNCGdBV8Phwh3nuOEnHtk04SUfUyr42alej/3B2odaSSijh0az4+eFZE+/U+fjkHxyRP+HbD4nNOvp8zXYG8Yx76pw/SryvtV9/LhDP9TUZBOjyPVS+rG9TLD/E9xoFFH2MvnTRtyqsllHpKu4YwzGBRcVSJs7zGadTwzMI2zg8zQS3e2IcA+vCiCgAHKB4I6vNJ0xm9HZjOGl4sw4l+A8ZOwWUzEgu2kG9KJpUoRDMUMxQHF3h0yF4hQnVb55GnMhkjp3HPXeK9GM6gFLHOqTwryZczy/A9GTvjHMc68oPfr7j73rPYi/vKo4gqG4RisZUrNEJii1AYtHVsyeLc0FRYB+zthXUlUAu9LEZdUTmMS0Aoh3mFd3QguGAp5ibzbCAyphDIZ5VrdbrGsvicEcDP4XCq3vUiPZg7AnQjn7sIJrQtqak6QLgdIRiA943hLs7EWFqxmzNfYa6sUhIoWc1aX7uiHrCHQLuXh+Nrc5e1NLrUpMaFmHfEa/tBKXnNOCpx8gMT61NEJlxwsnW1pcnFC7i4TTkm9Pd5V+S6VoZz9PAo2lcX9wfe2or4UbdEuUDZNRc4oLArbkPIxNFnnCN3zkZxPpM1GKf2oSA7IX61plpKEbUpgYcFMDIxVi2qAVe2F6MaLghRLuPRLaPMBa2h2Zo7rBaiyJWtXF+JzAr2n0DbZBOLKond3CojjOKkf3lBy+L6wshLAx/AVExL1OwVTxNAEgZig6yQggLRn3dzJBm8Bi03n6ra6fuWGO4rodgrQCUHW/ZeNTdh0lWUbV9lNQg/xvKecT4Ehw8MsrxO2BwwSD0GdhsNghjZ8BHCCQiwGYiP0NiCh6aQVuLwAGszuOZCTpZddBheHOI1TAyVGVMpaKx0j6HrBe5UjgilHphKB0RahYdwC9lAAAgAElEQVR5tmAqfQ853+8UAGgWQU8whQ5Rw1C1DZwfzhUMGgYL1/bYPpokQ2qwaI+5oo5okcqceTmXGCKHTZtgChWFp1UzGILXGbMtXR/WK0xWfqTF91Gqo/weghct7x3nIZ+29GtuWPVpppIula3h7JHXxvlUjbOhmR0kcGNgLvNoN6e6vCei5SK6UUu0UO6qz6NrjmMxkdhrj14Ohn7g5sJAoPz5Ibs97o051VWv+PjCeKrjBeM0SPLoCk3nEvZzOXR0lVKMbu2s9hwPgKwlHPQPMJzXtCiWg7mnYdRqUFg4sS7wQkgR9f0V5SxGU34rlC3XQ8v6LiSbQidP/Zx4VkUg3ZziIJ4xKGpPx/6T02FHYAFzrcK5asFHg4bHOBbnaDs5Xj1DpLkBH1lf2jKonPP+dCbdFXxEjNP7u5VkAIDt5PjanuO9T/mIZdMtQKexIJQsF5IWk3/NzQinE/OAGiR+Ay3jHA9ETV9PDD1IKgDC+fBumSdcSX9T/gwWJekyIAeBTsYPiQjmuaOfO3i7sWjBLmjThMPxgP12j8PzM6apQfqcKIonM643tgi2BgWYMN1POM/Gz5F2zJbbycQdJvRGuPvtb+hzx/l0LJG0Z4MHbpY2/WCR6/NO0GiJM/QA0IPto0UJEsizWnXprow3CJpag4KTv8wVpKAJ9r07rWZ2yAsN7tH4ZT4VPg0A9sb76sGcA2jP6NQdrg1v8jujSwdefA/ubEPCOQxOmxa8H5B4kFIJGa7Lit4tunUA1wAMR70r8p0ncJwlGhHMwaeEHBNyGU+TKWW5L+SfiMhUz3qjOoxTI7LX5wmP1Cw8S/BY4RyhcJnSjejwEiy0szPfT/by+X0u9KQsVkl+bW8ekdtEdrpmWA1x+Fyv0dm908YDBl6NaPRATcj3j0j0zGxQFKVEhJ3j7YNPWp033vnIGXuQWhQ7gdD6HkTAjDfM8DJxSpgyE0fhaaBW5oBiV+BZ4gjH0wGqgvN5gkp33sacrwDgOJ/ynGUbbCmEjaNIpbdfr1wYAZn9Kxz/R1+Otz1lvGVxrJkB3gBVsO5Bb0C7W/L12gPOZ0CB0+kw5s8N03YDZeDozrm7/Q4KRT/PdsZZXU7285m8jI5NXAJMwoUMpSaCIz6fjuM3HfvfxSLruU1QmE7FugxHRjeVk6I9MfT53rUp49V1NCm/Vj7ceYvgLxj35oS/fl4V4lojKSekTrOiBJvLwIdKVHikQa+rkd4ixevc7N6RVl6N5yeGMGNyniWCecyhwbIMLLYgzg3HqCnPZzpJIPDHkgeIyREG7kn1ql8cjs1jLahc36xwLwBMj48eYW6w03vH+9cvjkvvTT/0yOivHbunLUCM3W4LJqC1yTKZgNFaRPbbeejtCWd+yzUWSI53J4oDAXc+jvcip11bL9HBGS1m7Liq6ou/0Xfgfyv4M0PoGQ2EroxO36GyharxbnOfAS9vci3TXV2/MLWL8zmC4FPtvgdVD/oohueCwR8UYFVM+AQFMOOb84ixHQ7nuuTbh27N5MtXGqvwIMCLA+R90HN3jLkmR+W7Yi0Dz1Q9cNXlXdEp3FqfsSOrzwmgq74qXbrynsL6gQCI0/xHH3Ncb84OBJ75ToturpZvvdYubAcFpmIg018+Q79+uz7PH7QfpUv/7KxXRJsTvK76tTH9Sls9SzSM50vYsM9PCrwEcXe+70nhWiY36tNlNP1VuwsRGjHeoPhNCU0tgv/4/bvBORG2vzWcnwmfM5tHA14Umz15unb2gCrHSwAmVTQFZlGcUbJ8FWS/nRq4MU5zR2uM3WaD3W6PzXaD/XabpevCIaW1hqk1tGkCt+bO8ooXGrD9nWxPvtPlhgy9/cDd19o393Q01UFqo/6UtqZ/urqWv+rlR1qfyfWcV98p/zHElQFJCc9089l/t3++/UsN6JVhWV24utk3fv5T2mDklobCUMxccEGDAt5gnK0CmkAxOUMoLqy+vB2w326xaYzeTckz3zjfmojlZwsRd12OpchBv29Rfa7hfXeL+bnWFoz1/5AWjNevP6gZWR0KCmO+wm+4MngrEMPlOio8PZp0nOcZhJMr9I3RftAGIoWwQDyqM71kSyMfkxkNKBUOoPIMijBSRYTkAUyIFAhepWPfQ2BDpl2eVTBTpGE2NVB4gFYSF8xmfD4D2IbiNxn7ogjGHfAYgoNgfgb40R7uLyNluw9+CPTlp9stFCjLHUieF+EXjpxHvkYANF0Y5RbrmOdwRXJFgRbp0MZ1JTIF7TGEvuHtriCvFz26qeskACJdpKWFZ4y3u1DjSgCF1zM/mpGH98YAKVnabSAisgB1Q4Ap6gGzh/pKiM2RGZg7ZU1IcuHGJT8A5AbtsQ7BcIUDdWC3VEzChWYyJaf0ELMU6tGpzFZ6IKLr4OOEhHE5zs8qSjEVi+V75XoCAGLdtewRRj9Y3H79+tqZ61bk+SWQ+o+EdHZRVVBInF4vfigRrzjA/AQ518uV+v0o+rw+G8/FX8IGfOfU493nSvB0zR2Agrrf3BWgeRioVDKiZUQdXg5kEVV77Xc/rbqmgeX7drOxDlQxzzNIogogu3A/L9ZD1RRyqeT1NJcNjK594IbAGeoGHEfuqcAraUeJvOIrWYRFpNqPOcQzSwFh8CKtueNOQQnMrnDXsXrq82o8+fvGMwQ7G9vdDkTNo6WBw/GEiQUb2SaBUmdUombhAr4RdGMpDsYYKOc2aEoqE0tBLDOQkmlhExe448+aN3O+rSrciULZ6zjO0zknTksss4zCjZUynOmOUh49l1DoY2F7MPGUpZ80JUsYFQBkpJ9N22lsI5CnFGVxRylfQ0Q6zzGc3NgL3vDK+QwlYK7j4tZK11d9EI1a7uRbQcvU7ek0QGMdqBhdImIYgVclUnFbdLl0+2zGc/HsNZIlAAag2981f0AUGQ2Q9CRgLVL+VtQXuH3xX/Y2PqptTV7R1T3r7+t2KbQHbzCyuawNLnF9iX0Hd3S9x+vD0Nyw0Wc1xKQLYSjJPNKpGtzyPu8rT9oawef7HavokpYlHNcf6hogzr3TrIxAD+eHUqoFipHq2R0nEnoZor3wTn5XKl7KEBbjczzlMBy/mSMHg8QjG9NIfdnkdASogbYTzucZ02ab66IA9Ghz1pOCsHXW8rTqZVv+HpdrSwB0/L7CenVmY3Ev7lx/Lrfn32swuQWor5Sc9Y2VP3J+ows6dUSZDFXgdDpi5oY2zzidTjgfT+jnI6bWME0NzA3ULHLMvpvRJOgDtQaBYts3OBHAEDDPHtVC6Hxvjpls0dQceABDxmIF2p2pKnkOSmdzP76cnQauaBFFJFzQWM2zQVeFwdWiBk1ynB8GtKAByW+G074YzyoRRS+S5VViHgIZzoWAG0wV6W2RTIfvUEGEIa8t8FmdBhFasyx5Szw2zveCWYg1jHuv6EV0/fOCvvodIeyW8WQkPNFIgVzhcHUQmNnkEVDuEmDGDovC9+xbq7IPlRYOzLc8R7G0VsLrBAawAy1cVMYSLs/KbUpx8SAAwwx7IKMwo21L39VVRgEcfdH2OOT2H1VxzzbLiHjPslxrGhOOqZ6VIOZcaW4XAemc5VGk9wTxWbw8V1Qs0dJ7/d38GMq8wlHMf2HjheoKxr2iioY7QBqEjsA8aEDSsnBmdgcMO8OLt5mjP1DokBjOUl9NAro04++lIyEleJJKwyrQVp4OYYxU9LeeD1h0PDwyWRGWPEMD5SSRjTWMylUvYxG5hgOnpwkiTzi/Pv/E+W/Jf9hW3IFAmB5NZqjGUXkXqLwnDFRyf0FPl/+UC5q4M8qzJdwZ05i8fRipybNANfJgCIx66Bl5zbwYwwUazjmOsiOLet9FxqexM87n2AxjJ6oDT3UUGq+5/vI1jSYibDYbgMjKGajiNJvzTsMDFK8AgPnF7j19f8fut7/gfDpjs52w201ojdO5jNh1fKI4TzMaDbkPNPiUQyH1H27XdNs3fv5Gz3j4hrGOfs/7f/4nFCNNO5MnW6DlftXsHms6oTCDv0LxkP0vg0jslQObk691xzNYH60EYB30FeYp9paI8AqLiq2tipl05bn1lUQRZazBP6TMv7p+bb2XY/zRRbr6/V6Btxt82809xjjj9cwLfTxN+632kRTrjS51NI/6cyP3b/pjA7pi2ccvnYcPtls8cuUlIup9eR03E8vV52697xMMX070lLoIIsJEn2C8FWNHT1bi1ZQTI0guXquaPGd1DtPI3EkEqOQQj+czZlE05903mw122y02u63pjXx83WWm1hqmaUKbJtPbxlkg+jFsL5riMqBgtE8KfMPg4f8r2j9xHD7cS+VMF3g2rxWaupD7/93+qOYG9D8TsK5QpvWvziQOJup2T5UuDcPj72trBhC4pDmLC5UZXHOO5e8oG7IURoKcn6XjfrvBeVZ0mK93awxuG5zPM/Y84fvhcHW8B+hC0liPf9wbTF2MbckxXRgMrr7twvyetPW59P+opp68V/M4q3v7QtfTjqgCTX6D0je81Fd6G3Lz5Rh+pf1slrT6O4Zyi+h9rH9dfVBgmSZnwWwjF9aEuipthlg73hSGpuXauOFSLc0pd0Gn2QVkxn4reJs6IoXdQtQoQloZympC7mEJJ8R1HkHsyBTgoXBTBQ5kyvHZn5/VDOavsNp80hVRBW0HS9sCAHdgvPEQIlGEa1WrZ0JQRDy36VHuc8kYhP5dwE+2lPpicwzjuby4kfhp6UUcuvQLvODrrnpMY0g0eVcTgOmEqOOKqRikNSLPFV3mrA88TVaVTETAEUGca2n/RApgU/1YhPpmaugdgBLEjeekCrpj6EHdo9VHvh/1vUzfpG6kCEMIo8+zpyUuEKWAiXGewo7sm8oW8q5gmixFZ3r8+1p0V+bOZEoPl7QzZR3Bo0nIYIIULGpGsEaAR9V0Ikst7xsqGnXtB3BmPcBEzRaJrRPBApVMGSnikT7iwrN6ijdXrEctLHtHGN2BMERW+0o9i5r7ZN8IlNGSKbqFkQhLAV3jOrC4XiNnF0b8rMI9ADOilw2GLCV1nJOIqDevbf9MlJkBO4bCFz6WFYnIFlHodu2EcG2I89KBzBU41TEiPMfhuGML2jP0IKC9KT7EaWrb79Hf3iFkSqAmR0C2wKsz6VFvFUDXI+72e7y+vhcMucRhqfIgmyNT7BBQ/smQnqQDxItoGfaaZVDzmBdSoCnIo753d3uwNhzeLCKj1hIbeFrQ2sbGOHvkpMaqL8eeNCKUpBroVGJiCJNg/MDc8gw0tnTxgThVFW2aUukfWordZg8AOPWTRXO6EjAcTASWxSEUhfC9nqaNnV9mN2yeoUoQMjFVWcEdIAamNtmZRUSQYLFG7Aqy4DQ0rxVmP/bKS0KUDTbFLwGzpzCMyHBCYb2qVAHne+KGVAo7DDGVdJ21A831tCKAFcIrt0O5D9U5LRWEFMYfjP2ozS/YvNgFV4faCE+PodAw1FA8u243mBNTIvu5qpAUa1N/pSvdUERDY8yPxpzDsQn5PcYXSnlNJXLWsa5/PQtN3BfRnImL0+jjayHVoSmUn6NGqM86YW2Yn5EOOBIY1rczbUnFMWK8tC5mno7xXKzlNT5qbEIs5uK2VLKj7G15deXNMopucY8k+6iBAGER6ZpOcl4bOJTAdc91RKtXDab5IQx4VN+riLysC0ekIMh4Ng9fMQUkbctlKPs3CJH6y4fyxp3bavr26LvMN9aS3HmPMOYeSnlTDg24AgZuShjWcRZUFaeTYpoE2rvhvd4h58IjrPZcAc+64xgucQwAeNYiwILMARC2wC74S4Ie6tpsoXKGYoJ69R2dT37DBrwlqzlejfC5vjH78+rCuJEASz+Pwc/FncuTBAhOYLQVbohFNCckhaVWp8kyf4gbnpQUE01QUpzOZzSe8f5ufJ+cDmBizI3BbcLUGG1qHrW/tdqKrYFpZ9GkAb9eWkRFoRvj4TpmcPMyH2xSj7DNhsUjUYMGnzvQz4B00H5ve/1yNmfEvUXIssMUZ53aWFbG6XwCBZoWRfNavvNbx+aBYQ5nY/Woup0rJcGiPQNHO/9ReokCV8KVlwpwZIW4s77lvSe9V/XMOO9ksITBzyLAKeicwlO2jx1Xd5xbnEV/cPA0Y8uj14TZxAHjugat8DNKmW6l9ktu1A6mhwdvlM4CBXILUA5Hfl9HCofCpQOQGU4IROGANiajBNAW0NN4S6YULvx08id7gh7uslQWY++7dMQYSvAy1UACHFfnby1TrhXIFmW+5EqW/3oqd9/nPVxGdsc80z/tQThgB8Ksr7Y3Tq83vrzHpNFBA7tjTz8njQEdZVlSNjfAxyzdy22YEZ1dujrrnJlrjB9vEHS01gw+RNCdtlDhD6CethuxDwFTgdfNOa7Lu9UzF6f7LoMNnlHQqEEOCrofe9HDUS/piiRcWQZyi9HeTmbkPL4fbT3doRFkj8yvM1QOps9zQ6hCQU5fWPdIICTbqMiUoYCVXFPgRAdsdnuEdS4dW/zczeczAJdzldC1+1wNChpPBt/q2RgePmF++w7CnUPcW+a3IdyZngRvdjYAEB7Q7hn9rUOEIG8K0BuSCjqwdV+myTfmqIQWed+hnqmr0vjBJ8exJQDMCnVexOJGnJeHOVCQ5WwHeemOBjjVUU8aZkYi9vMyO1So/0tYZMMHUNIMAylzLzIGBHzRwPnR50hbTymT1f5Dokv+19+5OLfOCxMBu4dPmKYJUJPZ+yyYX14cYl+X8gQIYML8+gwGY7P9K+bzCdANtnd7sEejpzPFX+/Qvk04y3e8+Mj3vkVvPp4DAU/6ANaXkTLZ1yUXo/wNqKTV1Vxdv3Avy+8TDNfMg6VEGJqVrmX0v9TAxl5GlT4C4a0QBXV6Xh1xYr0jdEAAEJn2OpyGgCEHBk5LuuOfgsV4UNNxq1rNdwJwr7YvoYsExo4/KPCevnolOGIch3EgCvP45HhQQTjrMvK9/l00Lw+gdeFz8cb3N7r+e/1tr8Y+xJge8hW04A8jcnu9fY+iaHjCVyplWi/22NozLJofuIxYfxCb++HvX7KsREzefOkdXmXVud/z9epCjbbBst75H5myvQZE/dWVE7N9zfc8+RyuGsIxxvRZLRJbV9eutU8eQNNYsfv0GfOXbwB9xva330BQyHegP79gogahVzB9Mmd9vIPmCdOGoEyYTeGKd+1osICcsyogHZ3MoYGZcHaRInJ5BYZgJkzThN12g7bdYrvdJp4ld3Zqbjzf+N95Nkc8hDMUBZ6ISReecTFrrccn5bFHHQ46a/C7ZlDXiw8/bisW8of7smipbLUXpd73ll0u7EWpF/RJcdVNRFDHcvhUPgT/uR7oB6f777ZqJQJ9fTT/iO91l9bfBw3Ra9uthe3IP44sk2jS8lB9aGxL8Lo+qh+1obhcTIL8LNTuV58HYQb22y3O81vw0ng9HPG432Hugt1mc9H9uu2J3Kf4J804hYF39Nqc4YP7derx4MzmpL9B6OsvPXumryi+Tt7+QAr2363panZULqz5VXxwPwhYFuqMuowd6FYTkLmNes1ZIzceLWdhQYCG4FYjbivBSA9i/5zG4zinrjANAzrUo82hxkireXcrTImjGuNZFim401opOXnRoX9RQCxfoTHZK2JKIOBxCJm3Tk2MPtcAt8/f1eMSv+niJyTGUoQ9Gkzmhde4ZXRoWVj/U0esKbRqn+1Ie5kHUgX2BHn39KxlcMmEBAPh11PRDqSC0rmVsc9KaeBUEa9LbnXRI/UiHQTkaUoNDC0lsuV5Z4uABgCyiBlWtnporgw3z0egawfD07nDUkdGTUmDmzCwDAElxVNHIaZXN8Bu1PJ3cloirkyHImufi4gJ8B7xHmfjQiEe30N81FDhxD9LhuiacXwJKj++vm634HDRY6SOxmA6LfqzGuxLT7HXVSr53e8ncFGaxp81bSUi0F3NWeJCpQhUJ4iaQUBJwHQA6S6FtpgXaAMQ8PB4h5eXtxzgmvRW/kHDWEjjXoDSM8AUNhzAAgBZVmEEcMUBHpEjoGU69WhmxI53EaBmmOBGUAtpcVAxeBqivI6RVyNb1p/z+x1Gh8cwlfdS4u02DRZPVbHdbIcBIN4ROJ6WqTYJhIknLxMA7PY7iAqa11hsqpj7GZ2s346OjTbM8xmRcr61ZiUAmICImknjqi/jWvKJ3xfs2gr61ixeZSOIln1ea4SFMoNAcGIJyprIpb/yMqpGBFfOkLKnyg2fjIC3gaMiShtEgw9bD9VBMGhJ7DVoKAXzvbe8rq/8TIt/FZovKuf0g6xXzCHoysJgnmeMFnBZR5G4VcyAKWHILJHokWJdPdI+DO+DH7GRX8OfRhM7mBrMa4pz1qmQztOsY68pjLCoJ83eGfQz5zP6COJQKMJiyhUn/lPNz0q+JWAnh6S5makLDnq5UtypK6vXGx9RXwCWbCVreZeCYxAVN2oY4wsBRXwf08jommVx+jGN4tiCUAaXtLjai/E89nK97I5fBh1fJ5u1gdfzN+jjZTufzpAmFiXhqdsFgn6UMTYf7yI0qUDFAjpW575CVSrNxzCNxzqq1xAvyK/tFh3RlqAnM8rPuHTC/lEL+KbyLZqoOle+hZkpLp91rGIGyDtg82DudEqePcnrCQs091hUMLPVLz6/vZuB2uu8MpkCbtpsQCpoXhoEMBqybVNGkU2iUGlmvBOFehm0ad9wOhwsbfw823th0dTJz4nxLo33UPUxACCcoNhBDgq+i4w+gEbkvZKjJI/AEQUiOt7xyYIwLTY18Po4n+kwtndspV6nOyKAoMC+OLAIwNxzfww9CMy2Z9iNtA1+1fkz9Wh21SUva4A2ZBXy9TnPMza+7tOm4Xyec05XT0s9ZmsYXzNpdjjLTYNfvXa/pni5hM+Uu+qA1jg3zpKfPaKxRUMeBnhbHJPz0et4ISKHywxB2GPCEQpyJ+Rfa8P5yvrbIgx5l1P0B0B+30mBra/PWe23gYmOuQjnhEkt/E3cGO9PxHjx0go3swgAgUq3FNRqBmn2rrJ8CDuvAKetxC536qDDPh9F8GCEDkvp3qHg8JfycjnkDhfhvCcxJac55PAlUIAt41o72Jx1P6aY97sWIBIRqUe9y9zN6UOsDEUXK0XW2gS8hZPjHVjfAc94YMS/yEQE50U0aY27xRdeY4fToWOzC/yiWYKBlEE0dCplM/xse6YkkBWXUsY0AdPTb0m7u2y8T3c9YMIGn3B+7pgeTGZmJuCeoW8CdVNrypPJ8wT4DKX9gCfb0UtKMmi1GaAVpFWfOpzbqgNqlA1h9gj0LubYFDQeQxtQUY/7VNkqE+xdQeUKPC94xzGURSN/qCHRMazw1cg+UDFG8h9DyMme0nlVFZvNxnQQYmWwzi/PWLdrEazMBHl9Bv/1b5mZZbOZrIQIASqC+3vGZrvB+TTh9cv/8bcXXO+tp3m9Nr3x+VqrCP3y/jBcX/BA3iLnV223MnpGkMdwTbjk/WIklUUtKvB0torIZM39XM4iP3sn74W1iz2513FfjXR+0vH+ND6D0EF4i/EZwU58r+TR4XAdpuP1IsGXFV4RRsqB5R3L2fzad4L6WMo6+xwEFoBhDgRxxi+fHyeybtCaARjvfl2PXYdBvWhcymr88+0qPf0TWqSJf/KXfnKYI7pMe794zq99o4+N8zcxp6YGoOkn9G8Coif0b27eJsL0mUH0Cf3lFXB8y46nlgE8NtgNszuaqdFDdR6bvNQajSCbNPBCQWzp2TfbLTbbLbaB63Rk35s8An3yCHRiBrzsRgZTxNzHP8t9K0jFfLwVjwo0MblDfnGDfwmugo1a/LaG+T+jLSdVcd3FePz2snz+238F5P/PbtMlSVsv/e/87sRhec/Sc62mILV/lxu6iA5aXIgu1f+vy59/8D0oYnhE2wU/lIVarpmMMswYvDG4MVAd76oM42KGYWyE4jSfLTKsz+4VBxznjt12i+M84gMDiSispNk7ER4kPDGHZ1olSbr6Hh8IgLArv+JKYf6WqTNWkd+6yLaVMpbCPNoazHgeHnpjJS36PMfjzLPCCMdnJTwo4YUsHU8Q7LHnSwK9Jtg/+z4wnEcmXXBqtPibT61gM31PEybt96Vp97IFDLe65nVuDksJeiLm2UUeYeAbp6KAdKvz4wzTMF4DCs56NKbIUkTUB3fG6XQ0D/AWBtsGNPZxeVp16ejSMXdB793rPIaiBZh7xywd3euZM0XqVhd21Ixgce6JpxR8wGKpNLtgFsWkgrdIr0oERsPEhNbce00AgqUwZhoAxLD6KA9K2Cgi0TOglIZzkXfIszMozzDD0Cdb8f6siz1eCydMzgQoUtFbmXl5V7T7qvulokRxVQcJLNcoA3oGTWyKMEWmuK3eieqGG8CiPgFLJ2eCpgzcQi5skp/VDSM8/VUFugfkMOC+EQHvnoY5EEAYHNiM7+fT0dIKB56RYagDDO5ULKLEmJ5TMlsm307uzmz9zw5/zQaFkE7ymCVNEGfCIpqBbc9TyWd76Un1MqV7MHVxlDKXgtq+nfoMkHmWpuwKspTaHPh3pBDSUORn0gfyqIGeinvoiNxX3y/DlzIcU9QUw6Zc91TEASKBMz5gXM96lBhe2YSiMKFI74Vcg1gfVcHEk9kmXAEVqe+gCmL4/voeO5IlLcJj0IMAel+X2cEnFI4Ci+4J49JWY1vUBSwUI8gGtLeUqtJ1RAor0B0+eU/AHUHeC61WApPAk77a834e3l7U4cHet4HXPHXaYvczOtts2fkEq5vrpkhFemyb4qahNYL2Ga1NHvk66Os0WZYI6WGQA87nU443eAF1vD5Qi48VjqB97SMetlLayVX3PcVxymdD9cZqbixx7nsX8Kah9573T1PE7SzbeT6PCFPf8O1uDyIrbxD4ZhCkSz67i3kkW+YQAqFj7mfQGTjCjEyqgru7OxxPJ7TJUnltmoVZMrnhH1gYwYyW+Swj7XKHp1cN2k5p5GNlqP1qBNgAACAASURBVKcfY+nGj3GDUofK2IPk6xxGI61txMVL7IWSC1uD9odheDAPBXghC8Pxwhrn/TAHfpvsMzMae/rAzAzhw/NulWJN3NBOCPfu5HKY2tXUnAs+MPpwuAl2Y7AiVJ5AQiPBnQBca59Gcdj4rG4Z51KEsTzqnyP+K3QzcZ4byS1KyyKjRYL3UEg3eLb07V4DXR1jqRdBUsNvQEljv5oLyJQ8DPJ0x+bY1atB3hdUgLKWfn594VUpHSMsKs6gPum/qvM9473BOwS5pegP8XshiKGNDUAYlu9Bt1Wtlidr8p2JvwNwkpaUvpymJz8WK8SOR0FJy+OwGJxYn4Zv41wO2hzAEvWbzdDRcywRwcpkinwzYsiAAqe58eqaqnNsS9kf50F0dbYIkYaTLlBd8E8JDr4Z5tvnY8kafrSgwctm9Fi6lbnZ7Ddo3MypSIAuR+NrKegaWdYgPzO9dysns5kwH4/QiSGnON4MbC9V16bo9zluCVGule4CZ3ExDtAIgVM1tt7r1k59j/42Q3AynIJBvzVwmwR/GCAaMicW+CXJAZ3diAwoW5RinH97htBxxESecalLgdgJrA2sDcrG2UkXkBCOxxNkPiJkIfayJxsxGaQRofEZZ+dVt5/2LqNEyQeAqWHyhDF9nqHa0XgDNOfDYQao7jXoSYHzQSDSvXbpBOZ7XwtBC/neUL0dT7ETEc6dwU8SGMRAn209p9ZAopgejPfPbCHKAEYdZgpmKBbZcVy8WCP1uAIa9MbPhwVlR9ohhZLVCa/kHccOeDQo3SVhL8bYJCq2H6uzZNe5MAFlvPkLJQwFYpR4Nk5ReYfCjKyJahDTVctahZaG1VDUqp8JYsfXUTYhnzc+kDsHpVn9LTgycLzjPHK8EOdJI6NNrCsUoTjISMW9RZ3HZ0EH0QzSbfaelhkAeXJHqONi/dTl/nCAjgwvWz+nG7oHEaOnhsR7pTsA7wgnzK3Ph/QOO7yZY4Uqwgn+lHS80n1KJXPQeqM74Vysds4hZrgLmThpB5njpmo6Wwaf1TiiuG1cPSFjyOGqsGwWJOabClO+AxhFdp1+SBAxDR7ezpA0gONck80v6C8AnOkdDYyNPKETgVWANzIOQQnTnsAHQN1RZn4+WP93NsO5n50v8PP3RqDGEDadyoYnx4ENoh2QDXr3rFW9Q+jNgXzvdGI4vtoYjH9lFYgQ+qvtWfeVYi2TCQgmKvjF4OU8Www2t43fZ46SIs4LMqUcYWjN9mbzZHxqFwE6ML96Xkh3ehA1+GzBlziROJHBdPJ9QPLVgVjCKJP3KIbfRtAOBiI0XDEcRgxbasJPyMbjXMWZGnJcYEUA2BDQybISELujvDtZRcm31DuHrioynYmtVU89gA6+DgW/qc/NfyGOcxxytWa+kcw+p4oJ96Yr6B0igvPL91wYopGePnRFjS0bS6Ss5zZhfnkBbTbY3915PXQPHGjAzGIZWAB8ooZTU3x3GJp8rKrAuw7hgpy2EKntsWPXMFTHfMg34VESTBZNKNQq9vxrI8OhqnhwGhq4+4UUn9Wy4wkNfF0xFPv930hwt+DVgielHCdyf4Df5DOEv0F8f8JYH/tnumx7pvl4XllxLwYFL+TOg6p40kcIXvBMA5++IkFnsO5QkD5B8R0gRsMTOr1YlLHGvA2fwnWND4P64pPGepqjk2KUSz1EnWzXM9jQgw+vq+K3Jff14+93/ukte7D1fEjKpe7ExOgAXoOfXKx+fAKUGGd6HasdfHrMu9wLhM2g8hXx2XoNGLGfFI/+7k8OY8/rZ3TVzao9+XXGZ1iC7yvtxrMfbdV5+ZtnHyIlz6hiuPBrOThPwS44fDCALyOBqNPm1aD8a5yfDRFYn8CdoPgOak+OhwyfTyDMz4Td588QZuzaJ3Br4N2MifcgMPpmYzJzs1iRabPB8f0VRA2krmFjww/HfoaqYtsmgEJ/CWjvOJ6OeD28o71M+ESE3bSxSPPG6HPHCWeciEBi53DiEWAw4NnWcCa24AZ3rA2HqUcBWBVfxLLWiZjxfPfbJ7z//QtUFV9IXCeL5OeGE35sVqxlyDGLq3lL/htnPf5S6WLBWy22abyz6HPH96FnWf5exuDjrhkAoYP+pgzqfYwADhrfKXDAao5r2FqP+cMX/u9p09By39rqf+J7aAbzemX9x6dAGvmrLvsKZn8An/0RLMe+Bttr38lfRkygK8VbF0+uYDyJw//P3ptuO3Iji3pfAElyT1XV3ddn+f2fzz6nVbVHkgmEf8QAJMktlaTu9l22INXmlInEEIh5iLdONWe2dn4NPD6fiVACdxWWAmhl7T2Z2f1SeX9fJ/2jAfy9GIJ8FFKKu6I5c7vcls02TIjYiwPq1WqRjN58rmyc2y8eMINJlWFYDKL/mvAVayf5fiAsSQqcSQXm+U9N/8DnefuucMSMYOavN2MEdLtGv6dJ9CcXswmA1O24wotKNkh07JOKM78OT1IKVTpNClXEI7yVIh3pUPrK6WyGk0XNCFRKPNcERtUwnq+s68raXHkdNaNFaKqW1iWgWgaDXzMl6EirWMriEX1QdGVdzRjWe2ftnSbdhQHzoC1STNelsBPlUY2ISmqEOqtbGVRHHIwN6d3Tb4/9DmGKMWJf8msCAxE5aPeFUv0SnkSgvUO5v/x+77TM5qR0i1SJ9dDJB9aJZU5LZIx13vIyjb0D0hwGAG2orCCLdxHn65wddPFIGmdETDbz+10D28UVWbUCPQ21qahTMxyHFadjypaRrnd4mkuJQ4yXplgT36mopZ30dGxdLTVepEYklTIR6WQtkvcGXpkpiv+SkZihzzm25vsdhp1Cc+VjrbborQ/PcWEoRMMwYXZzM4jb5ylKovtvuGDtU+iYIbv3Icxc0YQYdxo8Lr73ic4e05dz/vUWvv8SNpQ8EyJCd0NSCMqQW5v4NusHx3MdP4l6lgb/rfnYzStfCQXDTPMKB0+B6sqgRGU2slCkDo8sTdxvyxopZ4XCns4ZYYfcgX6AsCCcPQXgKE0REFT9DNs8FKJ+bkR3OEO92+1BOq0HEzwIqEQEaxqBTAm4rmfqzhwDwojxGZVYu2GrXYlSDbG69i+UWoNO3uKbYr8mmgagnfU8MNyyVHQ+E7mCsFssOrH1NVepuJOFSKdIZfX67cGvlLpLRj3g4XQ+stsf/Gx0hE7vK+dz53yG1naUCrvdwnpuLLWCWMaNUkZd9DndHn7+FYuiM2/32CvxtF4+LokoQsO14oqioppGDsk1HiQ0jJ/h6DHDPZiAq67osQeVyG1p6yXiSn6DSHHloTklhFFZE6ZF7GtThlVKweoU0ilt7LQ9Ms5ewLDR+oGH41sfb1jWBkJnazDVpGNCYjeS50qvoQCQwBMM/tY/lDLgqXh65eBnYj8GPZ0c/zY0z/cjHJEiCtJ5j966G9Q7Ixp9nNHorWUWnQkzyphojD/WL/Y+ViDSfgfu7Q4nmrCoeX6SDRSgqdcAjnmQOCSu3TjbDUZk87zRBr2Ptc8rklkZPEC8zrzM3E/oqEzBEXyYAaDVkB+9hAI8zBnie5VpeZlQIJsjQBAEe6sIHZXZMSGu7RR157dMgTwtiGPrgM9wkgjFSRjHN2vs4zeny6FdSloWOH1KST3Tr5EGvk90KJZc8m/0JYhHXzRKF/raaYs4b2COpq01NFIWS6HuF2oxRdHH8cT6+g6nFRUzRPRprLeIRdBt1G2/sc6BgxCq6Aa5D1336FAKLA+FtR/ox2MsRUyWcJie+YCkNnK5V9Z3750iinaha/F9MKe84E0F0slp7WenEULrq3OQjeJpoKvD7tpPrG5AB6gUKhV6R7qa8aAUU/aVwvm80nuFxA1uxnYj+tl56qX4AlYo0tyBr7tOQSkeoqutILUhH9A/zDnCeHarPC2xV37meVfkjrEnzr9mqRhlnJGAqfk7HQaMOAAaMEFPPgiGA7E9ShPP2Kw7hGyhcf1my8jatx+KeB7wNPJeAd+05Tpg7Lw29jtz7t3trNQcYWjWiU4lvmfgrhhakColmchEzf5p4DU/82KoQwNO03n14uAkbe/zV5veM8NILqAkjRA/X/ZI8XBuPNJZfL3GivUPd/4GN6SfN7xtXj+tYRxXyXMy74AaLIcx1G8Yqd0HDz/fZ3T2AXin6FA8q777nDTxzInJyDIti2rnVCp7GbygYXXfvMEkTXDpvJHAukYa8RiRra/d6fyM3yfx8JBDpTj9MCO6FitvkLKkP7J51oQlMqeoGUMjQ5p0k3etJBhOIB0b+d5236BFZfhCUsy4ea7UBWRnjrOyvNHajv6m9HulvRpPWb1cUpGaTr1LrZRq0eilmPNo7zvWtXE+r6xyorUHwucDcdlcqjv9T/SgObxjWfrGcZqwsYSzYkVfnZ96HPxnQIZijvgIk8wg6fiW+lkd6xwuc0H71M/xcHsgnbBWCSOv6X+S354cwJJXiDEX2ZQ5Sz1C8NSSdvT851xAEqeQS4zlnOgdeODI+Kyh5yqF5vxkizQWSuItO1dWeiMN4GLOIrQG4lkdCZwV+6b59MiyJUUcfqE008FZebgZd/m+eQmBtTVCezVk97G+gmVj2e33vm06Ba/A8fuR/X/t/OwYjC4itAbLotz9/R+c/+f/5slN+W8aeMLPkstcZvwNUjV4MVV3ds7FnfS20yqUsRwkUOHBNrWk02Ls5XBIMOeYkfh/0IbYf/X9NhI4NCvxrFsBdwWl6jfO8sPgFHhBLXNq0KPASjLuKcWMugWgNZ74AgIvDLwtmLw206MY1coPij+r8Oo6hMu2dRKYKcyWisk0py3NCIiZZ62bK+brL4Lipt/jqrt5MXX0Z7p9C1B4lflZMy0atoGxrvNufPbK9efLgcr0u4R+zM/YrfuvOrjuLq64dmHF8cxNDuk32zZ73dylpWoXEb6qZdP4gqWw/6Js7FxVhSbbGX1lpHr/5v0/izkRVNzRVoWu392sIyy8UOUrY5UcXp5JnnpZjtTdnWUfVDgfT7AsZKYwPJK7ndn5nJSC6krzM7RiettSIEqF9d45fRx5rwv3hwN6f8+uVu4OB05yRlt3xxh1XGf8vXgAUnNZThCeiznjlVpNDpDCl244ubTOg18vTs5O//1P9t++8frL/9w0nudeXewPl3s+7cmM7a/YqBv7/fua/PS9l5fp/INFANouB+2QQVM2981H5HeM+w9P8f+D7UYN9GsU+8c/B/LUi89c7Ppl+xXE+i/5PL6f1d1J8z/5fNk2dzpR2Qh2l4eTIHlwOjdqUfZL5dwa+/2O03nloO7xJpIGCoB37+8r0GVEhsQzriKhP5my1R6bCOnEQN6Y2GSY07w8BE0Ytc0F9+oK2iFRK8Z+/6JzHfQBA12Fu7//g4fv/zNFrl+zCn9mzzf7GS7MZXvVJgUjE6uhF9dd9Dp86W6hNbmCpct2zVIMAfnX7pGLD1kTESMKZqwyAtV6Z9WVtS1GsIopv0y5SRq9YFJYW3hNplEFj6bpDW1KdcWZRdq4wOHRWrhCYjNiqURZUlHlQxqidUOwVpSH1QQZVC0FC0NIepHtngB0fXAZ8MUMhw5/I/7SFqV/Vzf8Op354nDtSsT27LWXn+wsywAMFOivUJ7EDeczUxiXnSYg2edegkIrULs7nBbCeNC6MT0ltLuQgqWlftMc45y6ShSkVFTPqJ78PApg0Q8K1Ls7SjnBB8i9MWT9nfx9hvtI659p2QOPJQMTgpVOAbQ2FjNQuodyx9LkhfAttn6BHi0+VhPraiKSwC0VTz431mGscEZdzW2ooiTXq0qhdVMBFSle38cVfR6lkOAp3qmMaDYBFjdOnSOVsNecT3gIRb/OzNVwD0rh7AJkfytVe7R28Tk9Cf3+5t2UVETNV4diKdYk4MijmVyZ0SP6WpXMorJdGA6yXfIZdnbiCgv/JWCrAPV+lFQIZZlyyZ8K9aHkGhoeuUPlRCiaZxOfohTZ27WluLS+Uqmelnxg4VlFqQmhk7CU8wr6N+haGAHBsm7sd6asMx5ccxIqynpefR9K8gDEOdlMdjhElVLc2YcEkhjXKnPk+XQv03j9c611qlFuBG1EnseeWz/73T57W9s5V2Z3OBCCw67sOZ/tt1pGlD0M0f54/KCIUJeF8/nEbnfwJw8FjMFWs77EUgt2bfS+er3BMnBscwPcBohnvjFgR7EwQ9/djVHNcYpoKjQ2+xtbUdRoDkMwK9VoZTyuxFFYNJ0xKJ4RxnmGgoAbYSTmIbPrxoXCfRx+i4yfmSQc7v2j4Y6gEUpXoXRFas8oImA40U3cwpb3m872FUcVK1Py2s3BDthNwUsmpmPQzbj2mveZFTXheOLzVzLldRjGk9ZwYSyfjBohyGcU2Fg9N9D0HMuMawTN9VWM/dPsy76M30ZWpVAeT9fF/Gc8ecHcDZ5sGt/F0mwcV+cWOCM/j3+zjGK0VNMoFftQJoND4E6LwJ/6S3zk2HFYrrc0xAeeuFPGfoxsQDG4NqObGPDUpsjzyNaC4W9fZcPz3p1Dl/0m7ti2UVRDRDJZP1MU4rRSCZMOx+H85DHxhPK3+xmelneiHO74UoT9w4NFT5RKWSzbRz9NONwBVXY7FCtpIUU4qOHp4+nI+diSH2KxW24r7+zpUfZZIdPVDkfeCVgmR5LBNcY+mxLenM9OuUURUXbFjYhMazjOU/48K590GOBTvlVl9/iQO9E+PqiHAxnrqCtVF3PYVMsUUIoJBslHJn7vyZd2T50czjXr+YToLg24JP8a06jUUlGUBRBRLDmRRbwHL1iL2Jp6JHu9U/TNnAML9+bAJYoelSgUrQLlPmoNhlHBHlylgsD51fiC/ePi++b8gSot+I1p1/TNzpncOxxFj+KnYeIlYgvUs2FBZ3k0A9a6GkT1j5GNxvbN4f1j8N9ycBjZjMXe94CFNK4JH6czh73xEbvdwmk9Dz5dzfg7R10Np9foY3zKaNKyNSzkGAIOnd+KerCXCtCEy3iSTAsUa5u/M+A1ndUGR2XrrWl3lb24Ed3GKwdT2/fjcNqN/m10e8q9Zxd4P/gzp3roM4q+opnzPMb7MxGN++ZG18s7J95QQPQOlTeKPFEeOuvrmc47CuyUwAAXD7UevUq5fVVw5+9ujs9VUS2e7aGh1ZwVcfo8O2dBRHb6ugquzIV0mnJCEIbcdNjsDKcBDdwd8C+sntlr54fjhGWfCmO20XgxJbwRahuWB4qc5QXLj/bgskt3o8+HrevLI6pQ5QEpngnnteMJ6U1JT+DP6rNJTQjm2duNLqq6fF9onqEi5mxgqjTsrFV1V3QRilg0+iLhOB6EseR6wcB7KPDSKY9QFzOsN3cibxpR+ePcNVUz8Lpjm4KlDldleXxifX1OvNTVqthnZj6Uk/cn4SAqkhF7gRO1T7JYcYob/FnyewOGiXJuIslTm0jn0dbJpwSHYM+qHaR01sCpyTMBGjyzYY7ia62eWcECOwQtmFNVYhGjCcO4Xyh0VKo/eNCocaDdgaCAiKU8Vqex/s4c7n2RDCzfOMgBRGmva4C7y47FHHl9PFLmLCDzmgd9fON0ukNVqa2yLDt/ju31fr/n4evf+PjlxJlXg32ZsJfv5YMbpV668Vj3PgcYLrrgoreEs5ZwiZJDLxD8zaOak8urugHccW84ZnZ1ZzrvO8oyRCDB6udAEN6FLRQoPDg8RXp0sDrsJ75TESqmN+vAE6abvlfTq8+8b2Q6eZPRjyCsahG8TzL02A861ey+mP+sF5/fPSkeLW3j/dLxwIQvXrbqheXrV/qPRv1aaN9/8fEJYzW2jxsQnsQsn3dJLR6ST/PfZ5DC9KZ5kiXG5sEhwFuJPmXg72l+Qc1fgsHJhZ1HcUn7rj8/OV57kZhFUGkbe/d9+KoDJ9h8Yn7BJN1+RJDjle+3efB/c/vhjpB/D6dvxll5TuZv22ZOKWq2/72PuXTs3Bi/UNyhzlqAxSrCvXyBKuzLF9ifzViO0zQRWBYO+z0q8PH2zul4SjLTfV9VzZn8rhROkLy2YLh67UrvK8uy0Jtp8SKrVPDsbV05n86cTydO5xPr6iFxRdzfOg6RzeNJ7XwrypeulMgOWoRdMwg5ietzFM6//GLrdM0ujqbbt5fLrteXjeOl5sgQeyE37vtdbb7p6khcAvCFM0wZGHHu4ienfvORf7Xfbssf3Orf0S77327xZ4LEv79NWGoTBnVxyY22pQWTkPnpo4KY2d+hJMRqi3nN0KVWnt+O3O/3vJ3O861X40rl7sXvOl1zc9wuiKKTUJ5EyglPMnjjt5lDUggdVrZHX8Ia93jX/3CqsOZ4ttShA+s/m6Vhkuk3nSf/Z2FknsyW47mFNP8T7XJm8+tn4zGh0kX9GXznuyUYKid4GANvUTSr1SvpgnRLP5bRsxk5q55S1etOt5aCQGsrbW3+pJJptmI8QsnUacP0ohYN5QK3loKWgmj4mgqIcMAyLAhR77In0RYXfu+18E7nYTJkKm8IDwAeCTMZMdl6KqbhFpc7XzQN6fj364sxIOVJ0iEBgfIo9BelPAkZMfLJgTcRc7Gx2AQwL19fl8lAF8bxvDcEy3i2Kqwd2flsFPAoXKsFfZqA+ES5g/4R53NPuTvT36Hc2Vpc1RIKQ3AaziMyO1K2D8O6bpQZcXsfyi7EDNQ3kFYwh5EOKhyA1AXbeK+MvWPzauqR28xuGIskFXci7jMvbPo0JwCHBB1nJ9Idp4F8gppZTIjf5s86jT1TrU+G1n91azAUx3OTS7w8q7Zl0CFfJ0v56eOfc65P3YYBe5aFpsclU9/jrArAbkLjgwm+ZvFGp3IEubMSDv0iIZwqRO3ScldMmX2E+lDQjwPIiuTZGFPYnPd8N1YmrtpEIYr9WdvKbtmz33nGgtY8qsCuPa8nahnVyZgViH6+BxwPGOu9U9zzN43oN9Z1XqVaKkKkHvbv6mWOAksbm4hJPMKlzvXmYV3PG7g8n04c9of8bDX5qgs/O8AUgBHZFXfWunjKeDz6vnud22Ekrmt1+5VSilJroZTqeMbIQrowunFh5J/wXfMoMavBW4iUw7aePR0fIjVCKBGuM3DZhRp+F9PprgHhyga/DbqGKdFCsWu7gfQ2945kFI7dm0HMIgnDQQfSKDzVj4ysM4qixQzNFaVXS+uZ2RRyfjL6muB7pG6fcbWmESILicYv2nPBZp4wI4PSmG7rvDH0Bn79hHHZ4FWdRqkwskAwDOo+oYFGx7na8GqyddAKmAuMd3mGAtEpMf6Zh7gxbpkMjBOdiHWNFcf5H4mxzjzrrTRwOs9hvL9C5TrmEy2V6dPf+P0qQ4uPK5Y/DLwXD8l13KyXTMZzDaWVQ5srWjsgmfpzUNhcG4l18zmG4tRpuC3VwJFC0BrJJbRr5IqU9tmoprEjE/7VGEmMvSNnX4NFN3O9JNHb829jWIrV6Su1Tkp1oR4KB723bE3tbEYkMeeiTZ+YEf1Moy47upwTTY+9HJA16K1ciaZJ0TeLMsOjbg+ojO2/aje/G6O5PEtT4NHYMw2nCtuBIsLx9ZXDY6pq0eMH7f6O0sVKpLhUEtESJiMIyg4z8fnZ65jzrhvN41/vFm1S4tkiRKqgPF+KReJpd9u1IJwtvb5aImlKQVqnYHWUS7EIuXIH9b248SnwhlqBaQU5DFwSuxUGpoCh6TCNtw7PsXgOLl62xu95G7hZ7qezkE8zA1NurG+M+tm84iVk6gtB30J+A/1Qi6JPWjSGEec/I8wJw/WAxv1+x+m0DpjcNJ3euSw1Abz64OQKL13jTHG6F7XRB7FRLnGawOSYGys2ZjS+2Tr5xi0yOtkaBUXQ4zZtLYx9sWEV9CO+DTn9kr8cht4NohvDzfvi2VfLOm3zBSkmDMEly4xtaeGtIw9CZFmar7C1KEjpiBZ6OovYXoYxWSfP5pyScLHqMIzMwZtMu50pTsbTrWTBoAGRfQDsKEZZvDNWvmnArw6foqnPcJRsAo134J7KB6rFDcqxFoCsoCtF9jRx3cXMk0jxAHwZ/IGCtAke/D/LrFdNryGBN0dpvHwu6jxmcWcjyyK42W3nxyITedA6odNfO+Wb17Bw2C3IcPZwAE89kth4tI2MF+3thUAHuZ8TWETGkbFOkqgjp6IwS9BBSwJLbM4agVMk6YfRWOcXCp4iPrKdxJwHz2B4pZEZifpw5kmjImPeRqft+y7mUCWlpIwZa2S41iIjFajBG4S+Q8aEE1NI8KkzT0IOIMoMKuYcY/qSkAk8yGM+g8F7+zmY6ficrUR75/T9F/puR5Un+jd3CHNepBRhfzjQviovz2RGqdwFhSKdWpS3Dk80h7HBW8zHM5xQ5QJPKYF6nUeDUaVIlcc++K+OySRfVTcBA3PNYvX7LkY7vR98Hmr1xt8kUp7rFEizzer3qPA6j1vn/j9vihvO/Tk3yNXV9XNLu+AEQOH72ni19fuhLN8Wr1sdAquX2djQu8uDN76Ol0FitjMbmV7tMF7Gx8d+xxkDM55vWhLLy3H9XJvLvV63G46ibskXDPd/u83yzIPjsw2at+7XapD/q1oEEG4DCc1e8r86/Hf5TVC6an9Tz/6InZmJc7RAhctzJMIiAsUcPaW8oeWe5vS1qNCLlbuMbB1Vd0hfyVIXxXS8el6Tf9p5aToLtAv8aDXTe7esQCKms6pFUo+zrivn85nT6cR6XmnrmrXRcyZOXCzMAr50tXKRnuriR7GsB08q/FA4OS5pAhdd/Vy7ABvl9mtce8t4/vsf9idbIscZO17zX5ftBsr4q/3Otvz2JX+1my0Z+9+H9jQFB+WsUHeV/XnhdDqlIercGoel0rpwnJW0YpGHzfg0CpZy5YMpxfEFPRsMjnFtkdY52TSfw2AkNO/TJPJTvyEoyMQI+3jswH7hiz67l91sOL/dXgX2asj5UWVDUOfD/+vk8OfaME4akx2RhpfCrMhUI/KCzf+07804B+GfZI8b1/1WP1OTi6umB5qrMgAAIABJREFUFKOpDGB4ksZ1xZVwvTVaOVtqw1aorULpZkTPPu2fOENONyG5t5Z1S1trLmRYGvhO9Zq2MtWUHCqEUPEeRThXYaeFXovVr9WhlPlAeVBxwt1N0PBo4eoTasBB4U1M4X/owjudr0+F9vxoAoh710YqoeWLRZfLl6gZCP3ZHQIAfbbnL18K7cXGX78I64uyfBl7qJgRPc9KAsP1Tpo+2dMgL5W+9gwZ1qj7Xu0A1WoRHZFeLs5r9xq+tnkeuXVaqQcFsXssmnO/8T5TPSF30PvRvbbvKXdH1ndPQY5szrD25sw7jgs8ZX8bkWOB56x+e2GSSbFa4QPP+CwSpEJwogzhN8ae9XIIOOhYFHq3wU3ClmLKgJ2PSZWcTzxMUUoXS9vWR0oGgws/1y5kR0SOhnQndkZK4nTDxZaS3YVU9TRsfk7S+BP4dxY2LzwC535tf3uO+xKxzIJ3EOjm6xhlCzL98LgJFE6eKlyi9jLhEBAnQhLeJOBOB4ybUmp8d4l35eLV4j/AEkTiEWonVJfNnaGQGEqUiDDCZMQHU5L0AlZH8sxVS+MFKGfkdEepgsjiaQFPGweRUESE0CpaqWL1u89e7kELHHZ7Wu8stXBuVucxaskDafSOZjWg7zmd5zH6Bvi+LJhC5pKHj3IIUiuLVHprOa+IuIuVijmbUadwtz9YrcnNBgi1VtIQ4bR0qTvr25tFg89LaR92HlE2MQw+x8WOrcPxup7tOZB4e78fUe24Mfx0PFuN71695qDB327pXrJi4P1Siqft7g6PpjgrXu+qdzO8h0AYuCTxjYhnTxCqVLQo6vk7Jz0mc/q8+VTOUW6hJAtlzZUCXCLbSvSiRLhLKZGBoOS+hWl2Zg9tHzu9l80e5L6EgsydBqT63qt4nUfJbKh0j7aanjU/b04LGtH2sUc4hZxWaLyLVO05Hkmlvy+H8ZERkxXOOKlc3M43GILElX2krVS12tLd8Wek9gycakY54zUyCtoZ3ZkuDAPIlmOUzRhsvcWjTbcLH/zUBSI2BDnmk9yM5loMRfD1rXrxjWQfsfdXiD/PezArYx9BZmvqhKcvefQZ/6UCItbSWziyhVGc3Dpb99YsOjci/9zDagy1T2l9/WxGVhNkytDiAypFRpS508reHd5kdFUxGhfTyud7nbyGDhiU4E3csNWBqNm7xnlwHrisDideG9ZR9aDYMZXtbkopWYsUEavNK5bKd+0r6vyBIFM0LlmKIfovpVD3xUvH3Ob+gzuQy28VLyvhMDAP+aIrde3zDPcA9a7QP8Yz4tYLCMwvJKFlPChSz5viTFPmU/foGalfB9xSd3Z+06gz+B8RgVI4HY+210uHNVDG4LeCPjRVerFSUX1dLRqmu/IuR233LTuLajdca3tPrajT2+A/SxpUBl8iBeSuIB9qUbjSSF8RFP3olIOdoOLwWbxm89pWw4V3W7yoznNqlI/pCkc2v4cwbTAk6JvCQ8jpQccG/uPO6VPUhZTiNW8FFoPztVmGmvWtuyIz+FB7lh632y93EytAGJElefKP45m7w87pZGG/XzidJj5IhsE68J3B4wAwyblsbotf87oSkUiO65TI3uNne0YcE6zaes05+WR6fjyQ5HHD4G7iwjDUC8Be0NNAXKkTyWE6HHBnjhh0lGOsWJ7nfLzDy6Ys4WSE2hjP4n3wIDmbGVeENucO+GD39MXKoz2vXi7ifTPl4NaDU1FM4Xzwz+eJjgfdL4F7VPws9kSegjtAqyJ64CR2lncSFCb4F3fk9PI9USqp1sEjIlC8xJYRh8XSZk+EZEZ3s9Hto9v+HQjegSSPycsQPEZjlYLKG6LCkjyXgLwa2Qfz8Fwq0gT6ivb3SS90547MAEdat6wbmnDn57EY7JlcFVHJ5iZq2f1snbv4GLtCsTS2UZ4h5UEvi1EoNLFyNwmGrg86/TLkyhnk65PDWIH2rMn/WYU5Bc/k1+XV8ALBP2junYhQqlBFDE5iji5n203q/IaNYaQZH8xjRFonb+I6SfFyGyrurO9Oq5EWHSTZtDgNPZ03Arfi2S0m52QdJ6X5LqDNVtL1BaXP48mNzXNXSxnnWWRkWoxz6TAcZyOcsSL6PNk1RwiC4eH3H98pdw+svCfvgA9ZIh1vtV2f2YYZn/Z+R5OjOQK0Qpdf0H9+pXwpLN5hKea8XKvwVIa3yrv3edfhrQJNKRWOqnQahzgXTCUBJ7kl4c/f9258wg+EB+eH3ooZtlHlrcC9Kq++JipmkH7z1+hvIzc7fn4LdMi1c8JbsKlq/ShzNLU1q93tUeBiEepvuaa3ebLA3+8TuQow/7V2+XPs15twkZ0zcO4LDeHrP/5hY+2N3T8q5/+xe5cLUnc9Wrn90ffqIebia1NQdjyialXcV4WFB5A3GkYnAr8qv2bonp4zzauwNZBf6kEe1YPtPmkvN56nWIrwoqQedlXDZF99nLfuu9UCXX3/yev/bHuezsoXhz/wyP6fHMM81m/OTndhk+o9MsLOOnP4QVgyiutK2u4D2R08k6yX1ayVXTVHL7Rzev+g6A4RWBporVCEBix3Bz7ePyydeqkuA8W6htzFVHqpeKYpo2fn3jiez5zOJ06nM+f1zNqbGdyD+sQh80P4LPB/dKUXQdQKhAZdf6mVoh1d27VM879Nk80LcEOOu5Dvpp+NhsSaDJ5Rb8iTn4iYf7V/cfvLgP7vaBNw3/gxOHo6FtVWiqDrYCrPzZT5IxpoEhxEONK5d4bwyIRk5tcbWEQIR9+hHjGBVlxguRDUZpo4JNxbU82mPG/m/Sxe3+PmWsQ9PzZDH99v3//LcIJ3dhlNmz/f+P7Km/RX278Yezlc3BorhLJJIrstqbCWEaHWWrMa6XS6RE3HkgpzIuo7vcZM0OxeC721loZ085gshD1QXHmjpbtDrCayj1qbIfyJCEdxRcjkIjZHn5lQ4HUqCeVTMMTKnTKpBcx4seoaYtSUKpzcCn0G+bplfGM1TbicFBr+qq7rnM/CvAPR/zBazJtif/o6KcgQtF7QT9+r6ilNRz8udjXN9ZX9OTuP2vVxg16dQ5fWNFX2Y15MUWUiWPpl25vuk57iZlKYjmj5jTDMvEaSn3PdU9COi6br5k1IxbIJwWVZ0Kro+ZzMbkcnPOQG4Gmcw4kkRWoiwmV+vilWxk53V2hEbXYYSlUzFIz01LeM5/Pmh9f7FS6bgWQjCd/Yt8t7r765/v2SJxMGHhvGqAmOJyVJ7kkoVn3torOZSbvlMGaKA50OwG77+4ciD6bkLhfCt36A3AE4k/1YUK2094Jy3j5PcGUm5iDg6fJsTsfNOgStS7hUpUtjqHfLZEiDpVrqzf1SLcXqjXWuF9Hc+8UEgrn13jmfjpR9Rc+mhBjYxVrrjb6aYae4966l4pc0IpboV2yOS6nDeA7saqyxRYAVJPFTPKvUmmmx8ryXwUu0bsrJj9ORu7sH35dw875CKJxOR79m/CbTYT9mnd1K1855PeWZiUgLj7sgDOhhTI3NK2K10s3WXsZxUTI9e+Ai8WuqgniKUS0moBVXbMeaDKUwQ9vDOAtzCFSsoeEnN6zEusn4Tlt33EYaMQijicqmZmDMw8atFv2Y7N3s9CYTiguF/aBN6uPXFtEq40yOKG6nGUznMoxYE/zHeZVkHGZ8EHTH6bYbOnO3HZ+Yf8OvcGfqGWX8PzOEdTc8Kp1Ob/7ZMX0PmCHo2G0MeHmuZENQxtqOoQRutjs3WdQnYj6z0BaZZiPJuc806AaPHGu4HQeDUGbn4+aZvZ77lNwXMh3IjBOTqs8hf4x749wXRrRlPC+MQWnMn+4vYris1ho68Ridw3cQ83mNB50d3IFDnIy55HKhzJExIp5qk86ZeUE0M6sIYw3Nx8CdR6fayNp1lDbJdXDnE+b91VzL+fxtNw6YjQBs4S5SeCd59+dp10kB5Gsi5qB4Dbk3nzz2BEhmNHY1ceHmanu9wZCKmNKr6fHKaPrZGC77/+SEJ15BBl+J4g5UWBmKaVzBN6UvgKo5JETd2LsD+nq069143rvjidZYe6eqDqdTlyNm/lzE6KpoNwWfKlKV0ju9GDAVoJdCUc2sPnGONqhEt8bgWI1ya0F0i4/D6G396Wbbg4ZFGYGk25drLUGX4cqILm4cDn48g4BGlHOui8sM47gGXXHOWbAcmFhNatnFkBU9C7KzvtOInsObDUnen4P4FtJl0MAZx4nk55QM4qzKiDAUMQedcH4wUngJoTq9v2zj92ADwlnNvMu6J3AQjzh2mD4IevKIWlHQFeNxNftU8HT/p4z4jShN34ZP5feJauRaXDrXnf2K7VNnfPaRvZmhcKIbUxuk6oB5cFif4qEYOaaJ9ud3znDoGr0YDa/F07JGNrQYmxRqzEXGGgiG540NK0QkNIKn3GabRSDO5eX2Tuc9drWrud6qn8N9/uYOuua1RS+Whl8pdPYUtawgBG4Qg+NCNfoZJRBCDvTgUFSg74037T0Nq+prWARw55oiVk6vi3p0b/CHY52DJxaxbH5tAKrtbRiTm8trM3/DFsZm426PcFntTDkoJhzg3+iD05d3RHAD+AwP4ThUMn03Pk+jwVu4nVvCAbiDt5+8fI6k7mDoGPxzCUcRsg9VMktE0P0kPrkok3zm3QWMSTEHBekkPMxZxopYDXRxfFN9YnlGM626uLOKQgvn+FjXQfOiT7ASIYgHjLyvxKhLnJPAoV7PPA/QRTMS+UKk7TeYE05y5q7vx/MxJ8a7wz3LP3a8ff8nYLWtAU5FeWwL1MZTg5dijl7G/joOLpJGaRU3pF1ydZ7e/mE6uk/+65tc0lBrETEevcj0atQI3mZiqyNgyJ4x4FzE0jw/BL919TQ3nutPGIX/Hc0B4V5nhwBL6/40XRY8ueg2iv52Ew4EBbg149GBqq3nO/DAq2XbJGNwWL48Ic+dxpvRNMHf/USb5CKAmhW+rT06vn6RbTryn21xqqqT4ZjWlsewNhup/3dr87iawPffef83dScCjDQ8y6iJDjDT7Cjwt6DUdAJ+oy4HK0flwReWzcv0wAVorUOtSBV2HOBcaP1sfIWYrvTb4yMndxjt6o5iEhlXTDdSigznnTICEtvaOZ9PHE/nTN/eW+T23MqL2RT+WZRv2nlV4xtCb5uTlb6Re/63a5+xpX+wbSUSkh6NL+V6HcdPf7U/2f4yoP/JlgyrkszD5QEOUcYYJGPyQm/0/eWNEOEUS0V1Xs1z/NvjAx+v66avBfiiwrMoX1ywd549+xAygCWF9IzcKWW4g+n4PaLFLomgXE/nQviNruzJzYmjETC7qGNR5k/ITQ+xJlD1C4UX81RkZm7+LDLcPjAUXsn2RST6xYRCCd2nNG63RvPZ90zfX8p98/WXSpiB/iZEqNMdM7yRYjeoR4XpUJRqt0j6XqCr1YXu2mha6LrQtLPoyEcwPN5JBWkoItfWXP7qZqS4pG2uqM9ahc2ESS1Cj/RwXVPgmdu9Wl2jN9EsBRCMc0QtN7lH9Q2PJ+Hgip17hdP3k6+CQWH18RTg/D0ULYr+gPLF+uvO15UvJqisz+ERK+izcvhm7Gxvr/QXJ+iPQn+18ZfHCU4gBcfrJjag1RVXq5+UnQnV7Wz1ntWL2C9lRHmCrbcsSns/U+8A9qBWp8qYDGdJNpYmgAPImd6NrU7dXdRyLsHKuPdhW11oLaOLifRaxKGE3zolaoTFyU9h2M5S7rKnrUN1E20WaaFTiY8JwAFXqxvrFhaa+Rr6etg1s/Ej37qAVqhWQwtTWBTEmEHMaGgGOFNSFHfs6MlAdgRNe34VoVNQsYjJNilrFR3C+GYcW+OMTuuhcXMsso5r4t45Uv18sRPXBmw7v/0C/LpnLkl/TEdxqaiZGK2ENZQaCtkY7wgzGwq76feVU8J/9FjvF5uYP6O48TyVIzEKEeTBYedDkaV4Bldl93gA9uh7I2q3Cg2kp3Klc0bUUkk1HVH1wkK9L8lY70vh421SDmJCWC0LsrsW5YY90QXByXBucx2G94TLSXu/2x8MDvcFObVPhDyHkW61tAlDuhtq1eEsDOVrX1N7tKvGtp0ng3oYW6UUlsXyNES5DYjFH2iiebqt4/HI3f1Dzg0s7V8ozXprnNbjBl4eHh/zmVYrczy793Bp6bQmCJ5eH0HEjCKtWTrkpVavaeuGTRGqFEpd3LO5IDuh96FcE0a03Vh/NxKU7il6bRMNjgNjKVlDLjYtjGI6DM528qLmouQ+4IJjCnYinpXAUtObsFjy/q7NoiPRySmJhN08rhI8ZIxhG52uPt7hsIMrNjzbhsT5nZ17BjyWcEILZxHr1Pu9hsoJYMY/2SovieDjYJvUFX8T4gg8pxF2nFk8LCVz1DLWyXGPPl7HZH1ukb5VgpZtx57pdifGJAwycV98aWOTsWaxzg4TNkdXoifiwve8jgg8V7YP449s8MAYh5+PEGbl4nl6/T4dmny8kQGje+R+wGDSETfApYKdCdcTRjpyzPGMWJp0dMQVt1XSL8LmZDVD17ZiZocSNyb934x7no+fs8yu4QYEu2ziH1Q5ScQ0xtTU+SMbOuocvHgUryt3SxEv9bMkLHRt6DlWYseQsuKs+d7rGLtIRGrYEIpEyYluCpplnIVw1kucIhZxEePt9NxagN2y43wKldZosnk/UYtPjmY4DSTfF1B+cb05DcT3zsvrwaPiblZD/vxZqhQ5uAOl8/ZBy2uhSlQUNhm3tRW0sj9Uzu8mO2R5mZSBbc/W11fWUhDZj1TKtdKzDqw5l3XMEbiuK+vRowYPhzyDVpFKzBk1+T6Ta2spaOv0Ws2I3vsGTqsUWtEsoxHZKsKgm+vo6Ww22RlkrFatxXljd/f1MywloE1SVgcdGUWCcjhuC3pk5OJm7tQN4AQsDoNzIjwAlsclHRH0ow86lrTC7mhe1kFU0XPg8fHYwAkfxxP3d1b6JRyTfAreJ1t4jEj2Sb7e0Fc/M0HLRsafMKKTsA6aKUPDwWmoLgafMw8gaOw4j5PTwJx9JOnLWOKr0yq7fK/hIKnrBqer6mSolPyb14RBUIfkOAyIAx8lj+LtDOzj2eo8jcDhy1dU7Xx0VcpDRI1/AVXaq5Vii1Xt+o7FnVu0fNN3RCzDl0WpmSL8VMbzpQtVC82NdWtTFpENbO8kdq24LGFrXLASP8XPsrjlbm1nm3epG3oXu1ekOD4v46w4b6Cl01pPsENxx6uB54/e2QFzvogsLqtalDMClXeqVpZyR+k16XR1R5JaOugO1ScKqwcZdMt4JEqX4fRaxMtKRAYyeYei1HIHWqndM+707hlZzNBQn6y+dn8zSbs8dNqzUB6E9txTLlZVizRmOI4Fco3IaHEaGjiGSU6POMGJtWKGdilR1f3BdT8fbpQN44vxxl2i1NIUlFMM32WpGQWdHU9xx//pKJWpbzv3NY3ruZOqFm0vQmRYtPTfOK7y/ovT8uAdAw4mPgM/Y4Eru5rhvFCwzMI6pfMP3DaaeuaykqYgXxMtrutorp/Q4eTj62P/B78z+NPGh9eVt3JS+8DhweJRLAp94qP65CyQjrME7qxIeebcvoL7tJRi4xQtLDKZvV0uuOsGi6HPOqgtaGCxcOjueJTvhJMAHrpN6LXY/j81wwkvojzoCH65DwcZti16exGPSC9uhBfTDW4YqQGt6FVPgy1uGK5cZUSeXze59eX252si8Jttw9MpyZPfafjdCE96j/ICIvzXt79x+qfxZCELg1C/fEGelZU3AB6955D8M2uCqvc96M1ogZ2hFTO0J/ersHz5wvrjGXjn9GzXRRaoj9+Y+JbLyEE5Hn/mi1pfr9i8w3j8W8btb3ptWH4Vks/4G1D4CvxAZKRh/+b49bO07F98oJH6/D/dXqZSI/zBMSR9lOv1V0hHnw1f6Xyn0euCSk18Zwk7BVozOlKKRYSvzQKYWqM83lnZ1+M7inLqlqI9gvQwTsRwnnaWZcduWdgf7tjfHSilsHZF1zOyrhyPHxyPJ86nk2dJsjMit/Sp08y7xl6rO+GNwIXLzA5/rv2Rvm7jo/htIgabr7eXJaG/Hs2Nrn8NNW2d6bbf3QqE+qv9/vaXAf0/0SZF1VbgdoZYhKWa8llKsTpxCqfzeVKkkq9VhHsR7r4JLz969j2pevM1zmseIPVfdCDWMUwXaCehbeOx/hMt6nws+g3kF8AIX6T5+uyerzyz8HdWfvn5h/2JttXxTRHn0w+bSJ9PFuFn0NAlzvx3tIw2VfOc91hcFBkRHGJEb9E+UqUmYOn2vb+Kkp692geznoa+iXmP2uVr72i3OoPagbpY2kXTKpIMnUtWHzeogLoCK+bW9RV4QHhjwVL3ABR9cjgfhs3sw/+FEV5Fac8O9aqUryYUrD/6lMI8hEtbz/XFOuxAeZ06nziXeehXYDRh2KFA9vdNLSXoNOg+vY+3mkKS9d/05PLinlCc55lWzXs6zii+Q7lXePe+Np33Tc15KTPWCJiyjxapHftjlxXZEaJu0UJnBRfsI3ol5jvNzOs/a2qrRqRkamB83dcUONDBQE8y/6jhmPd0c0T0rpqIRSLJFLmiIB5GYOPrCc8tzoJC1GmNzi/3ZKx3/BvwM7crhkVvf/9HGJuJT950Ph3nzdXq6zWMaqkKsHMH4yx4v8kmaxgyF1RHdoChCNwxK3ADbxYX9EwXNinlXKHRBeQkGQ0bCjZdhKILneuwuVDGayhMci/OwJ33b84/M4oJpZ7SWCI94bx8m5Udzhb2jdNbKQ4zxvwbilRqWTKlL8B+v09h9byuOcaNiBu0tnePTBbqsrtJM24Zz2ccNEcgbxTpqlazvAh9UpQN4q5j79XuBFNcGe4kFWGDRI4RztHPATelNFozcXyOOqvVUuKf06LiIxVLjbx0RWu16NeymALTfI0npbILXAGZi6IsCQemGJtxs2xfZdoFN8ZD8EfjEvU12uxFXFtKpjQ0T+vqijJFOpTiNe972QCXTG/mc2LKcBm1Nac1Vh3j7WqOMT1x/7TuXZFiPIDhkuLwOw8g4HrmAWdeh6x9noo/ESjDGW1kkg56NvO4LkoGLe09o9B7s4wDvVnpj65e19jxb9YGDVy/acE3mEFLAOnbKJOA+Q1Px8CrqlscK0Rq6gt654aZzbJRoDfDBZmWeopYU/Lc3WqbvmZBNg5GrJ+PweY5m1SHwd8P6vR+esZER9MQh44oLh/z4OXccBOZJ2ZhQh33B62b6O5PMb8irvCXMX8VkO6wPBmDZ3nEyXk45EWhSBEhituJWUzBaZJOcw4ng+A/tm3A/5VDSyyizI61Nm8tY30vyXQY/Ab+nBfp88WSzTsd14diSrdbbU5LM4zppjeRMbYNrGiMU5A7aB+/vn2DKhjcFeeZlTQBjAu70ovm6LUrZTFFWnVYq14/Hv+9i6vn+6CJqifohXY6myJYLviq3jKde+9Bm/owRopFyHV3RpNSKL2bE28X8GjzXkqW/ghF9cicEPMaRuyASw3nPcfFucuaTCiBtYyNsVjgzZFJfmo6SkFYZfAhRUDuZXOON1t5cb7jyG+wcNCMwOfdM3+VccCHst7Oj0gzRagIYdzrYHt/AnYD17+/f3B/f8f+sON0PDm8DieirUw9zsKlcxjzGCYGY+MEkDhxyjbgZ9cYyFvnfLPK3mNKQON3wRhQLU7fQLxuZ0Shz/LFtrVN/+E+OPZWNuMSrvd0y7uP6z7Tu8z0S3FBx+laf3Ocerd56K+0gzmhysGXOZxVBYpwV2ryAsdwenPaXNQzPATfIhNsxvsbJDwwxcyzSjhTJ37d3mioPhwgfUJdKGXgu6zXHLJAyHrJ69jMulh0rWihF8No5gR6ROVh7Fkxp7GuBXF6NWtWuhovI1Guww3qlIpgTiDGNxWEJZhfOlYiZV1972TiHZ8avDS6FOqjOULLo9DfdEPXc45AZkgphahVa7PaLLtduuGrlM0GyXg1HYnBQIlsHoFHkIxMj01PvSKdIhaRGDhgE00O6bSeuBey9vmlAkVDDm3qxvg5M+fEMTjshAvrWB7NY646nMMNvdlvGrycR2yYU0Kss16tY6RWzzXL8xwX6eiTwTPFbG2VDOed1HBGmdZylShb6DQo6t7HvKbRKArd9VeeC7ooVC2cvq/oV2G/LAk6xeHa84zlUmv3gnhKyvLqQ+oy9miULdhs6XBmQHjSjpSOdpl3g6fu7Jov76w/iRZGc4D3KbroyjHTBz4b0T/TWe+UjIiP9iaXKdz/XLvXkQ7/sqnjlzCeg4OkvA3YEOHw90POZXbwK1/KHMjt90/wd/HL5kXHB0WnHCP26FXg9eWZvz2ZU/z68sLbrxOMn27PMqLOn3QM9Wejw7/p5ynWtYD2H5E4ZrMOscZf9T9T3/zPtt8TLf/VYag5fb3lGJLlJabT18Sc4lQsq0YVpSi0angl1NS1Vvq6Jj+h7lDUXt5YcZ2DB+esHShKQ9lJJbVNAstu4bA/cDgc2O/2iBRab7Te0K4cT0erfb6u9h0wZ1eybgJu58kxgveCxwwceRnV959uM7v5a9f8G/pPOhtyRMoLMuHrLT79q/359pcB/c80V7AMD2lMgcHwhhkKrBu3I7SuSHWPQhF2y57SV87rynEd9abjeWHDe1Lhv3/MnuZBOELJOhlB/fvoYxME7AepqwsIIjfP6KXC6ILP5dW/eHQGffe/Fr79N3x3avYD9/765NwW/cbuvxaO/51PvH3hzfYrHV8KCZ9ddaFw3dzOhLR/Z/u9tw0ZacssDgFoFv6DOWMoGIIBc6bN7glBwAU/JD83V66LbhULJhQ3V6q4wCAWeVymWYUSnC40tRrprXVaG2mpUNBi9R9fuinODwrvF5TxXo1BrxjTrmKE3aLJH32X71F9pQL12984fx9pzWNpVuIsBIMNuy+ClHuUd1ChPyv9R6d8K6kXNqbWXk/fX/LslidBXy3Ve+hUw8QUQk8oFVN56akEI6+sAAAgAElEQVSp9cMNXcuekRpZPQ2eIlQ3ms1RJuqpw13VcFJLI4gJ+SisH1DvTxSxCJySRNM+83EyJYqYwvQ8Gc9XMO96PKX/JLRIKoSMmWkqLCJEhFpPhb9F+DTOkdQNcvcadFfklIBLE0xr9SSt2lLINe9y+1AcPsQrJK2lu2AceqKIMp5OhYyUhSHMd5METaAWpelqNdX8otZWKGJGxYB68Qh7ZxzNWD+dCtE8V6pDVaakTv+qXWIec0YhYefK2KIXbxLP3sZhYxwxxuEpfqvfUDKtrdm58rrNYVwpauGlzc98lYjON7gVgcJi8Kh7+kfH0oiDsEfuZUsrJLzXO0JBj45KHqB/+ApKKCWceonAkVQKAezud64gXD0FtM/pAPqhdD0iLKjYeesf3bUFFglXDzsKynp0p7QbBG2c6fxq2pCRZnxa/HxbBI7n1UpJqHrkSmG3jFSnu2WxiBrve3Yi6JF7NfG0n12/d6nbtPi7upgRfZrGfrfPj5G6PQyKM5zPbX84jI2arr8xRa/nqNNvQsFgw5RqQt0NZU0KQNrpKqyrRe+s1aPypXq6Snt+KUKplV4X6rJj8Sh5XSrLUkErIpNiUsZzwxM5Ui7WLCkywWPyZGXa55hrbO6suNbcg9kxwYx/JslKtawBVQpSIy17yWh8KSV5K7t/4HmbgscMeJ3ljH68GN+QnZze+BjSrulvMgqoDwOAOUg5PAeR0wF/qeibYHIe5JDLpnEFSxD4aTYgzbhGzWu8O02zup991Ib07+w6n4PT01sKtmlgEOc110b9CA0jekDhZ0ZtlzdjEqOfm5dahFnSevfQSD57+IPcaJPkf4spzGj26eylUGz3m25+ONxtHQEUUx9HxDC5RwhUavIu8wBCZ6H+IdOgBl8Tz+oNoTMcyqYFtEfbKLpHt+o4N6Fo36hHNGjfQKppxJTRdeCGGGNE+jVVK6EQz23WT+/Nyid0d9oh6rcGPiw2aQ28oZmi3uA5PsS5jDMRsBjKecNDET2hk1E/6MhnkDutnNOdsSb5w7zHCpoOHZLbM5+A5Dv9t8iMY90NuA6HmHI40E6neNjmnF1iRAVYdqg2RCtgZTaY5AiapmK8AOvbOzzcIwL1vnr0+2S6caV/7w1lj7RwxotMCYuNowqUcObzOuhrMyeiIpzbyiI7M8DE/AOP41GmiPHYXqfRlt3PsghahKaGfxHD2dLNyQuFRrMIQ4EmMx0d0S+OBAA3NHSDt6iNHtlJAvufXxvyIOhxctq5gaXk4tUHv7nG+AlJGSAdR4hMQ5oOCR2l3An6MUU5koH1PkLPNiWC6smntzOcsjqsLLIZRymF5jzltBSJX8XXfMNCaeBqvC7xdCbyPEU2ihGVF3Jupm+fDCZbcrGBYF/fXz+VictFBu5S0F2BtUfyBO9rTZwV5QvCaS/HnVsmtz8HfQ09zQbnTzziBdYt3GEx0l7Dtj+hb4FPlf7mfECm+oh1EL//3vstlIc79N3uq/KAqHDUIxV4cL7kLJZ1oQFSOnsVz7xzoJSKOa0GChM3LI/xRqA0mHGxq+1fdcNsc6f+dJqPfdLAWZYOfnwPWhTWSu9tZPyaEWGsIWp5snSOrlWadEoXKPbaAKpFJNcnc8ZsL6YfqU8VmtJ/iX5N7uo9HEM7vSi1BPy/Uygs5cnxyjslaloDRe5Yl0a9M4TdX22/6kNFHpX1x0pfOzzYjtUHw2Uq0F57IvqoeZtG1gl+4m86JKpA4K/gA0Kum8HVeUSVj3QQFXEjtxuwD0U4SxjCHUJ7t2xRBdDbAnHAOH5fKv4DNB1MO14eyY2uXey90IjsBiCjTrhaXHhkwyIcS3o4ZDq/Ie5E5Bxo8LQafGv38WXJlIugBkBagwrmOx36gOFQETWEQZP3jnsHWgw4d7rjsB/R92cpdCkswQSpOH8ZCEgHj+z4I1IwC91t6ebAvApUNT1T4Df0gaavGcjw4nz5nTvIFNdTFJFIupOw+yHTHJz+f1THlzrorojyd+dJmzuax1p89QP7nYn+ENkMDC4edNQe/1QMuOC1Hn15ApxWhNcy6OLcom464+UPt8+M5yEkpQHfCUo4FFcRij74kbOLWm+cv6803ozf1XuqPNAZ2Wqrz7A5bi+y1SUFGxu6hJAFH4B3v+6IORY8AKe3V1DsCTLWW5JjCYe7LUXN5118jt/nNPkPCn/Xr3Qv2fpr7TPDefA23wW+inN5RfniI1jk76g0/tG/o5gRXjFD+lxKNo76f6x9Mp/fk2b+b+p+fgxU+XXCLYCn5BfXKdn+13kXxXR679rZaeFOKkuyIpJlVRXY1cpaQLrSK/R1pYudKQEWUc7d9Hurl60oUqAUllK42+/Z73fsdju6do7Ho2XBbSuv7x8cT0fO63lkq40nb5jE2+soFx9une/f135LWvu5Lj4dwW8N7XMEx+ZA/mR3eV++/bMY7q92q/1lQP8DbUbCnwL3pPy+hva5B3t/f9jx+nFGtbPUBe3KubVBGGetEsbYPCK8XaXE3qCWG0+Ui2/i0xBcZm+/n0/5oNmLCRadyt951H8mEX2W63E9aZjq+k8848+1MIjZIELJar/ZNt6ORLeP2/X4+Wf+PuZs0/1PPkuIFJ1jrKH0U1xwIoQEr29OCKyTciGMBFgaxoijrDIMFaY2G8/pXq9LuxnO12711ddbBnRf/+5pi+8wQh7tXdRSrakx30RZAR/zMJ4+orwwfHJjH19ZgQ8xb0+FTGG7PivCm8mMKPWLoM9AV5avQvuhqfxJj1u16zZVD6yEGv1Z4VFCtpk8u/383UEYA+zGNvbHBpHGmCJ1wL4LoykouWKh+D1NYw2E9g48HBH2dD3at7oHzma8x40XH2baDuP3YLa617ULJ4kZqkZmi2BsbO6B79Sj44bDkKXE8/3w6jtd3TPQLeABX5mKvdkeRiTaUMAzeXGLpShXTQN3wGwqZWJVfD/CsNy6enmKTtFQKPr3PjNhxm9C1OeNnuNZlo3BU+D79aG4iesus2z8TOT5pVLvd+PB2DrNP2zfbed4K+pdLqLRc5ySIOk6m4osDr8E02rR0lfG83guw4giEhEIpsBGlM4JkYPB0mREzBp7WGkTRdFSKR30QO6T7jr6sfhovErkATiZ+FDvixmuVSkaoqfhk56K8msHqjBGjAUZtD4iz0WE83lNmJiZ+N6V4+mEINzdHSxdVhV6Mw/cXCMZjgKhPOhiaWdrqdPzp/25/FZ1pB+MweN1zpmcnpRxzTTRyCgReOCSi0hlk8jlwphho63ujDHRSO/L6E5jXZUuHWmWpULE1kIcZ5RSWJaKLo1FG6r7pGMllHV1RBsGNs1yNWJKXVV3/mmaRv85qsQXYbsGMWNPE40MHBx0TPAUmKrUKpRqaearv5ZiRpaAtaCPEVVtTxljUI29lwnmSzqTjHnOynwXhru4om7sQcCzRZxXF4Y7xbMbBVgUMQXiduqSzxtbt1Vyus7SFZmEbmgDIzqPZzaYRx107Wb89Gw23a+NqSRPHYOdQfXqCAzqZDzQ9sI0ojtRsDMaddZutCu4356TjHbLfKp+SZLEMOQM/nk24iPz/g9eO2BtRE7n0aFtniOGpy+OYPAtEX2WcxEyYiyXdToCqauYELwyb4TxHzPsDlAJuBzpoHPvlGCICGVqBItL4BrBS8I4wR6LT0oRDnub/jpo8QgtiTOgOSG7PLKEzAr+0fdW0Rg/9sTDgqSxo5RwjNk6FvfeCMeTWitttWwkSpTCYuIJP2vyqx9jn2wrBk6ajejxk73q5nN2cTUEW19hB9L89+txxumaMNYWelUnBkHZMUrXqEJ7a5RHczDqzl9EaajeuxlcP475sHhWbGc4gqg79XXF07A7Xl0b7aiU4s4rjjtT/rFcw6SBRSBqKwc/ohPtH7hnMkI5TjaZxTKkBE0dKYSDEsWC+Znf7Kfj7TCCBGznXlib8hgQhzjP3DisV7yKoAMvJc7G7VhebkQ79JLp951i2Bw5+e0LzWFYdCX1G5KcPtCtDHiFt/cP7u8POY4BL3HOJMeTjk1Tahjb79kIEvNNpDqynYitohLRwHbJtl52djSt43albsH6uFrIklPTHEY0V+CYNnCHjEjngb2GDL4xggdyHy+bZw+cNYjrwN/O3YbswZrjM+M5lIdCf+3E7k7I3Ns1g65vw1gYPMkOvPbuHVUqazHH7YLxpNXHZP5LlvoVPAJfxSIEkzlh8ENZtguiHrcp+0MGDFq2pZNWlmdkIUrHC5kDAOKGG/s74c+jX3lP8VI40Io5R4g7bZaXjjw6rDodpUtmxgreortjrXoq8FhhqWb57WI1jIM/zNrfdcfaVtZjc7pjjuyGEkZ6dGCcF7XIeXukJqyUKkCh1OKwKNPOq/ntT7ToQrVF4qDg81BE3pGof574cPCpqxSPGvcelJGuvRf3B7QJXeMqGWVm/PfUcSrbfdSRKcP6cgxZogZ7siPZHxrMRs+I56g3bxlcStYQjv1Sh735+XHtrROk6zrKTBTjQbJ8oQ6aqtnfHMg0PdlhN3G9QJaWEzgJ3MXayHj+ZQvjeWTEKICWV3h+ZPlbAUZpgnU988wLh97NGT1lFOit59o7JGQZxz7hLTNum77mScXceJwPeK+F+6aGA5yOlyasU5ZIxfRr0VfoiL84jD0qvF2IaPG9qtr1EwMUuDq+f9D4/ufa4HH+PS31Q/MDFTd0D3rfXY961te8d6RlvwePD9e84/Js+auMZJ+KvT+J6VzvCcP7GMebv79cr0Fat3zKb7ZZTxB8KXDmB8tFbfTf254wePtR1Gt/b2nFynOG80QE+pdpY+M8/yej0/+ccdccASrBt93mbF7EDOrJS8qEdTbC32Zg/mqbf+6Nw24PIvTWWdeVM8316CNzRuI1lxlbBGA6ZJZS2R8O7PcHdrsd2pXT8cR5XTmfz3y8v3P0CPQedE0u8axeDDI+SY53OIz9Bzfzs/Y5a/kn+vx8XgkHec2vr8G1fvPfhe3+/9P+MqD/4WZGvpswKGyjvG80Qz7GoJ+b8nhnTOdpNa/mXTVFvxkZKkdXOodw0R2hPrhi8F3iVxfmJBSGca5DmDFvzGHMYyNwzIqDTYTLxdm8ffaGIev4yz8pfNkwqrfa0//xX7z99//F4X/tMyXqZ55hn/fzM8gzyGZQoPTN2151w5Dyc+2aTf61kV4ybDcZuGmRM+ruYhEy04ALoUikywcZeVYTFiISrHWleLr+IqYMatqnfz6XYobTWgu9gcpI9dTVGG+ardnaIgJ9tfooKUA0S/M4CfVv2FrfdTOcA9whxlSnED1SI3deTMDk0YT2r19pv1h1nYCXjhnPwbxk7zSi0TVrgEYKap7NKN2elfrV1j/TS2GMSgP28uBfvHF61jTAVt+z9uIQ/3gBSf6h3h9QjkCzc9fqxSUdS8O3uFF5cQHWGYRwGNcKx5EyO2SL9gYiJ+qdKyk+Rm3Lud4ZLlcG4zzqfu4pWtClQevs7++N0f1YPQrFFAq7w4KIcH7/oJQdKlaDHRlnZtRfc/yjIOGh7yKOwYwzQfFbdyFLLP2mCfNm+NHVcFVr6gy+MU9LqSDCeT2nRBb7mwydp33VNnBiFwH3kgyBurtyp/hcwhBVq7jhzb5vOmqEr66QCPw5HbWJ8btomn82zOefbsqkO73NdIYX/SVeilrpdIOopcj1iGaagNLWlbqzVO3lbki5qWycGMnAFXxgKaDdyNqP3YwUFBY50DjZWdU9QqGKG7pdYdI+XPlxV8wjtnVaG0Y6USzjwgkfQ4E7TQE1ainuHnZpUO29sZ5XpEaFtms6uF2HLTETEU7nc36uxT1xL24V4MMNBefVcHgYlCrFlY4OF0F3taG9U/c1FnJ0hu1nLdWM5lRKraztDG2s2dw0jGtiypY4vNo7vRSr3etzSnFExCLUBxNB88h28T+K0NrZ6+4B4ql6HSdsjfVhdLExhAEmU9UVye/N4OrK6MAzPiaKok4Pi5RU/gQeSmN0qRZZqJoM2Yh4iWun9OoXmkWdFLP56teap3coRd34X5dNJoXeu0W6tAm2ggWZ6r4XiYj6ic7PY73cS++jF18/V5FYNJSg6lHvnro4UrgLjt+0hzVz2pk6IoR9/KUGLAiUYUCPLB42yIEfY3AR8RTp2VOBOeHaYVDXxLlo8AuaytfNeXP4CP4tkX78HoxOYMFUPOckfx++vVx6B4AZx14LobMUPRucb3UvGXUy9BiSa5i95WEzBxkLjtJ8/jD+2Z9ai2d/GdEIqaCeUqWkUlzJPUMjCsEWrmi7EGZCbvDxle3nfrUe40yJajrCpX6N4Lu6R2DZmqQBUG03xWuUam8WVYbRDpGeZFXVIvR7ZO/pCuLZbZgeqMYC+GCAwFWGB005b8aDUqrzfDbP8/mUJTp6a67fV0tDqB2hucOe5iNvteJ7H7u8kdFmiBBSwX4tm8yw6Ks9wU2fAD/WMo0oZ3UezuGjjciTWekZ3wl9lPhA8/qlWpR2rGTy2T6y1r18ilj2kLFX4/wTvKL4yb27Y1f37OqOQqG9f9DFol9aKZaOcrfzrCor5SAg1c+FjaQHnphJdvCdCZJi/Cnh5DEymBQK8iic31fjj4t31o3OpwEr6HEzur8sC6pKrbELQfMcaTuSXZ5qrq3ta+AyN6DezXjE5/GJXCr5O7nG7teS8srazFBnDmbQH7C00EWAYxpXOmeKqqW91zI60hUr2xN4RC3/6yK8vx/Z76o5SrTOML0EPDpNDBpHoV1GqDqu754lQEoZz8mVGDR87Ong7QMOmeBsRv6DpMg1753GmOk0XmzB9WIPemPneeKzxY3dEpH8M02Q7CqdUoJvUdnA1dzmHETRg3CX45WHQn9tNwY9Wnk003d7c8fKh8BtBX1XOg1UWXigakWaGRAPak4Sr/qKopzVsn4tfm4Khtuj/nWNLCEeGBF7H7w6voeilgmttW740Pc7Mzs47rK06GOdiJJjfmaCzVx7u410pwVVH+NRlUVsn7W5XOp0aNWGfPf0yS/uhPmi1Cfzpo/01P15wuCKRdpWkH6H1DpqbMudlSOSxSKgpVu6XDeG16cKvdPWRm8NeQBpQnu2lLflqThsKTyCvhivSDGgLtXpltP7cBM0/t6yFYmq6RN0Xo/h9BcQaSUpHggjuh9fQPjA5ORd8PYhL2icdQXprn8cDvHRIhtT1a1jcDpG9KH/GSfGxwmglhWx957ZRQR3eIu9TRlekwcFMZ2WI4EidQOflhWJoff09emON5nxhoB4tp6qK2sfeH5tXmakK1veUBLu5vNpwy5ZHibLOMlw2juJcFBDxeaYMlZtxmGjLKPNvzgP0tUiwK3aifEm911ZJ+P5gy1Owk1Ch3hWPvEMJ1j9aRUzHnQpvAo89FkHoqhH1TexFM/hgIIqO/1C4wdnzLDZ/dXZT8AM6kKcb+9V5++2Z/xB4U3GeryJRaOD1Q1/G9sAWOBWh/H9J02mf7F78zNfr2+5GpdrtMbj1ZxqqjyyfNu5I6nB4cf37z4ue9K9CitvPPztbwB8/PLuLhIGBUvIdTgfPY0zeDkBKncsKGv/yO/PwRwJHBArkndBd3Rm7ibt/K31uFw3JrqnIhbxr8rfdIz5j7RwtkhudAocWOUHoKwivPjzYuTzXv7PbVYqo9T/tHH9in27tjX82vVz+5uaLvos15fE51gTFaHJiDg3yi4JMx90Fu3se4Vq/NYqwt558N1iurBdLby3xr4KVcXERlFUDVpXf/ZZBzTOa1yWhbrbUZeKeHai1htrb6ytsWqjuQNPcztEyAVx1m0CMnoPXYnrXERK+O0Zvr9Yk59rfxQKR8td1Wvtgmyv+OnRyPSq87sbjOGt3n/GhnVp4/ur/f72lwH9X9ySNMjnxyYPRRACf60irH0oSUqxVFgP+x3HNiLeYAjT75Ni2EMvCbYyiKq4rId/vsoUOClMhnCjmwMWz51TA95uyquI1zwRCl/hN1K2PP3X/+kRbH+Wav12s/kOT7ogbLPu/Nci0f/fbD87hIhIyllGyjRMQG2q1N7oLVLOjr29ygSQzLwRK/l/2HvT7ciNJF3wM3PEQjIXSVXd8/6PN32rJCWTjBVuNj9scQMiyEyl1HP7nJbrKBmBABy+mNu+ZA00u7+HQpYsTfA8z5DePTWUwZHMMOG4KuyDsVILFj1BM7XQk499EA9NRYrgxe74omifGPo8iJaT3hh4bl13zttNppYKtTDb8hxTCCHMiHHUbQZS75VjmgHw64jSp4OCHyl1/snUHs+gfSgFRqYAWmNeUlfqSgpqAECiwMYN43tAT8D09GAC5PFife0G4Q0BiBExtpEe0VP6FM43McUDWUSJR2oDhLZzHHTh3CdTBE5eq3kofkJ4tPFKCn4WxTIUVSlgoySE0tgrT9pGkfJLoLMpeEMpazBn/XcyxYRqiNChIFMTNEVx6Vevo8yO/ySjRM3gT8gIO1UotxSmrV4P0st8CKbw+S4j0bH4c8dME78vFNP3zoPi9uFvNCpLGd/rq2vfyx9yHHkW4PAX+5qQXIhGEdyXcyhdn50G7imDfRXwtKlsdZrpAsYOIPboDYtGZyWI7s1ZAbXuqEJPtrc6C3SjkJOgd8HEDD3BzlHeX7xTCQvPLIIbR95Y7LWxghYfKOcDuNK0IqFoNT1yPB7kBCFwrI0gY60VivP1jN3GlJenyxlEwGbaoktH4wZuE1SA63zJ+daxh9ImziQvXhOK5vH+CjqEGP8Q/ja73eIuiVrsfqYoolBcIZ9pW5P/sGgiU2yZQi9UNlbX1uhKmzyyR3RkSlG189om2zs2BY795GnAPIzHjGDi1SRM6EtlX9Ay5gXPUYX9wFtp4FUCOY7KHfXI8eaGN57Yx1XWRxTaZPRFMENiN+UeR1QVc6aLjnVL+rMSrk3RG3vjyt10PJCsn6dqZ8N+G3RdlEDDjwsRzeXb5nBkX3hdCx2CAf2aND5waBrGXYmYhvMwhEQd1ViP4Cd0rXBctjjGkaZ8jeQG3hwHLunoQhq95Wlv3/WGNoM06ZN1V5B+0H0dvySWLDxk5TF8pe3eer3w4ylHVNqdrKnjWOfvqyKZEcoGH7eEM8pIo2zjdZgsI6aRpzjPzHo9HDzyHrtjOMTVlvFBoezzLZHMMKNj22L6AAgeiaWWGlAF6CSpnGWGOYjQiILP40KETDcf66nRfzghjBfGOY7zG3+JOWu2RpQkEBFt9nzywBj4bWz7LSzR/cuJY+2sDYIy4HgF89Fb9d4bL/4uBUmepBQV7F117EE3kiMgmPMjFJo5JYPHGEOd9mMGluklcIW4wdkUexw8sQLYbzH5PoRRBbqxNM0ikN7RmTFnGY8OeiXgCaA2KGlgJw3YKstAYRSwL4gI1nCosug9w12NG0Q7WMzIkaWxeEgECqsNaXBX92I4dIVpYmrNy2YBUMs04wjAzmCct7NaFqt4i+/9XZ4krhPl+UtHOKchZhSjwQsrASwWwYsdFBcIE0jYHViCBTTDnuG3YUQnl2Vwtfle0bGZmqWwVl8XXY4x5jEizlc4Div3c18X02kMLBQOxiPrWmGqgu9DGMBjBGEoLGtW+NjE5okYuUSG+nnYkBf+DK5NFmfPyJMiylcIuf4Fcabv05vkS1CM54VWAEvjeaxD5b2rWb7SRy13quP16ogxINjgTU6afJRCoU92TuVo9zcVXN2BKGQojTJQgf9hy+Jcl79BkkYnvwIA7liT2+j8Zuy7uPMfFz/Hsmx2Xtmz2mGps1rcuLgUvJhFvomOTHcqM6QBTSwDlLzA4C/wBDu/ybjjBGJz672bfKPmImtjOgP4ZOV+GoOVMU2TZYjrPfmh+cUiUM056zaUJOdGhu8yWpktAj2cMSOteIeCeuDR22UJXs/WPOD9BNBTwpCd/aVTh629G68DWSjALB5oMZxzK6xBFRDFsJ87nmDN8jHhjGAvChkUiaM5nleFiPE8KsWtU8XlCIF0hzWx/RrOuGGwH2ML3UI1oAftS9zg9MTN7ZhThhbf++C9XQ8BYDgsLzeg0t7gMUDuxEfGv8U4LjA9meiSp1nwsC6nqAoOYhmTNnne7N7r5eJpwR9xxFenzQ77DoMg5/IpyoKYbjqymIWhVnxtmNT+avCtkrgPYymTCCspui/FwI9Y4KWAr9pCHNLg4VY86pOa7jnw4isTnhwXP6pH8GKoAaJ3M74vXnWDa+p1xW1N9W+2sgYKoMFSsvf+AZevHe1Ty0j/2josBXeFnvF5XCfswRDMuJRfy+v3ZPqRcn2z6MngK/LiVREknyr01Sez+vwd0wfwOz2nc4MFIn3E7/TjEeko+qWggS+rCEYqt74VoFe6+mvaW0D0B9pPEo4qb9/zQutXSfI9cYZOFHr1cLRxPQGpOeW4o5CKgqcGUsV2o7hcr87rOD6AsYOqyOAoocF/cGO01tCmCZvNBm2a0KbmgXZLvkXj/3CGirMbLJUf9sH7woMVDE9G5j5g8PoLHu5/SvsL4GB51u5PL2hJIFxymp2BGGv+U9/gl/5u393+NqD/yUbBjPn3GgGQ9yz+vWWiBIrD6WJpnhy9X+YrdpuNGXK64EkJryVaJerQPCqZEb0qBV0IoXhfeeWbBMIpZjK5wTvnAaNym+bnMRH78loIl+CLe2tWYhxo0+4//J8TNtTMcPMLsP3pF5x+/3XBLPw17e2edLGDfu0Oc/qmAHy3z/tvjZnrGzemgeU9Dq58IISxNHBngUWk6ApRwSzdiI4wemcwWR1qTpipCvcinK+EeUVEkgHaB8z18L5NgR0Jixb5rgv4iXnUCEEA6A7TD4qRmljNa3MG0PFiQs0zgfEEwmtW7h5NcArFhzMPsSYKoKuV8Yu3bj8SLl89wjh6UMX1yyuIyGqo0yPm59dckw5g92QGwvmrQl81X9SP9vzmcYfr4Qzeu1JqCkcYQ71jKVwAbSam9BJJqheAizKtH07YfHjE/MQmYNoAACAASURBVHBBa3vvRyGn04qdLUb0cobzjAMQEsjRFHq8n3A9eK1QusLIg2W+kKM9n/jOXaZJIxrMfpcQBH2hxWuej8zSsSc6hCuyGq05LtWIy8e2MS5XASDYbLYI7XSm0Sx4Cm4MANRSPasLeakIo3R4iJRttgyO97q553cZYnMK1RTK34CuwQQCWvR0943nunI8unPX/fat2+KMlfW178GF1r6K8mxFp8IgIBIZAHTBjMXLSAGaTJ2u6qk8Y44K0KbCF1mdczZYtuioizG/RGBsEWkCgR0k6skSoNJxRUejncPcxbrUybAJwbQKZJGywZiHKlJOpvRtD6ap6V1yb8JDnxRo25a4bL1gGdEMct80g/RIyW2gGvRVV0ttwFdUAiDAanMD6E7n2eE8lAjRF2g4oZwup+xDFbhcrS6piICpw7xxlidfNbILrOiar9F2swFA2EybG2VFKHNMGClIssIYCCpGP7L+ol1FGFuZw2vY1c3intFEYG0QWHSiRWsYHhGxiFHqwDXTyppiZ9PNsaW1DuaG1giEhtQzRYkIskwhHWQ1ylVBWpzF3CjW2pQGx0hxqRKck1Exy4LeU+FDakYjauGIAzOku6NOa81SafqORxQ6AlZ8F6S5AT08q1sYqksd9HvMmgJNObPNhMEqUrcHbPbeAfUI3WJAVyhYGaJjv1VH7EJE21rgES3Sy9vyeV5GAcz5yNdGlxE/kbpddUSdI/c6zk1izzsTDZhbMJlv37e6JXA8aES3xg0rlLb4ONDAHSmcwhEjcMOqAwRuWfX91rCpGHzXN5m33QK3EAac5hDrCHzIBLhy3QAkYF/Le8RLkcQspZdU7eGdYRMCoDlOZ+igKUkMOhPGmvKYixLRr9NehtUs1+Wg1zx4lUMiotj4V/ge9DGBMLh0o8XMbLSurzlDS7OeQgmNDBBhhGjcTFETymymERnrCmpihnTjdXvXcYYUMKev5eFVj7RYK0lv2fwlXR4YI/Cq4ziuq0V5tsuKLto6MwBtyFi7uJPd0NN7Hm+GZgpbC0BRqM6ABk+FYFQXytYgYXI8gx8fzNHWnT2nx8lo1+kMEKHtd/beE0APhj8Bj1wnAk2E6cMG/chuRO+Yhaz0kMDGCwaC1pHxhOHs0BPvAQFyjq4QVT2kRn9TZAdwePLvCCONG+tw9u22UtKY2HmiiDx0Gnl9MQapfRh4HYlLCfzkOPyoIIzwwpEdXJG1a99pQXtFjH4bC0EJN9M0QWEGHn91yo42mD3II9E13gtbqHGGNWOPzGAUJglArooLFPvdDufL2QyeGnAxamty5C9J4wcGr+EX0lCSA6Vcz+GdE2UhbLGWsZjZ9c214PfXJ4xp1Az1UaQC926n+bhjRZdnNiAID9gKEweR3boLmc5l07l0S84racGFBMIuxjJWCBZLFpIXgfEBclDQI4FeCZtPXnf0S5xeX6cVXmI/M/3VJKPthw2ICfPr1aLRZ8vYdL0e7C+ASc2VAgpwU4A0M5ul47bWtR+00s6iBYYY76gJqwAyRXrII40s05iIQmkGc0Pk/wHUs6xw0gfmBgEN43Oco9BjBZ5Ug52TAntYea+uBKHuDjQNCsLmk50fUYA+jlhSeVY4chhQpANUe38GmCEzQzGB+GcwK6ZGQGugFtlNTBLoL92yO+0V6AJ9sbHykzly9Ndh6RUVNGqWAcl5RuZiTPczLWoZ/cAwPY0K+EODvsR5ZoDjPB0GfSEC6JDRxwwXtfycVGeewGeR0l9hvIbMHcIM7tWFI/h0K/mkAMAO83Mcdc6eUrZPKPJ9JB87eckAGSmEVYt85k6qEMv+l0e5uTwSQCqafYfzaWTAiLGrZy7kxojMoZXH1YDZwP0Ffxo8u95HkdlOgn3MzBPhrOe8vxLQAj2r5TF8KLQ2sm7kGhHh6JzZgwINhK4vaPwPEBGu1yue//0vkCpeIdiJ4ujzfnEvgY9qEtyrHTt8cEy0/+kntGmD47//nYZxte3DBxAaGY7Z/eMXqChe//UvO48AIumBaXEU6um7g6f8SqOUZyZIyH0fQKCqeMkp6yALWNbarvQkr/s6jpKh9v+TLg2q32LZ4561HuWDI+iXig9ynQpP58+1J8b89RHz16+WiU4/okvHK0JWsvvOMJXi+csF9Eip57RMBeNdSpc8C2OMQNsbg9JPpkNoCPpiekMhuy6O25dnrUwkQ5qLQ0xkd/vGekWLLAEA8ALFR7X9/hEj1JPaczHbeP/aOE5kwXxhgJ70EwhfMqo7/Hh+p/H8H6lL/lYbDn/LlbmxNcQa31nATzqW/ZmSRc32k95Gyr9C0JS9PrzZiUL/eiTj29OhR4En2mP3YYNfX75i2ybLiqKK3WYCmHG5nNHJeFCCmAOhCij4XKYsp2V85gbb7Ra77QbTNJkBPbIpc8O0mbwmuuIyzzhdLu6MeqcFDxEOOgh6Y3iSg5dCzW77f7et2UPg3oX623LMtPqWv/q5WQR8+HVdXa/3f9eYgzf6u/3h9rcB/UfbPens3ZvLv7Wol31AlJIL4T/qahIRZjGm/rOSMxiUBvRTRFno4lU3wxsCab7Srlc+oHAklQAsjKepZHt/xi+k+AiA9RNAb0egP/NX/KyfF9f+Ui+we60yNauJaFmXGyP6/9BW9zmUxWbsIWdcTcBlVyqJK/NIBA3I2kZQj6ZJIusdaghLcclrfxXdJHnqz0ynG+NhcoXcEOJvRw3shXBw9kf8ta+qWfOIEi4L4dChHEge5E1CZXd1wI3kim5sqBNgZ+B1RGvGWBoAogfAnycMRq2/6uKsydEGHwy2QtEe3KDuoyQiKJsSlrdIwTtqxI+oPE+x6Qqi+bj0GJumx2S2QwFEj3vgeMpVGRVfbZRV+Bo+e1eQ7iDHSNcaUSLXYZCO50EjqlwAYcNnBDLBPxh7VWN0XKAOjly1EuwhmKYyKGDMLVbSBduJcb7MuFwvmFpDeK0vcF1lAKj+rjnXiEKPejuMSLVKaeQKJtUUhEjFV/wYivS1Qjq/rvBwfH+LQbmNCr9727tN458iUJnSx5Ri70Wer9siqrIu8D3WkAhRxkQB0MZ7PakLrHGqLEow8JEt8QZhSLeuBV3PIJ0AYkuliuaZK1wpAhcAYuxkhgQoW23cEK11lFqo0aZ1iwY8v0/KU+HqNypC0RJZPez6beriO33lGi/fWQX6e+hrXF/fEfjaFIvkcN/neVFjsK7DdrsrfEjtaeB5dfwV72RPwVW9fYGIxlQQhSLdDQhEZgghU+ZnDTd2POFjE2mQ2fuS4dwQ6ZDt+8UUXKr+W8PUZnBraG1Cax0kDG5Rq8/mRayeeozGgsOVjAQQsUXMubE7FDTixCdqGUsXaCOQWI1BFQGm4AvIhD/T4prxfGJwi5gBgNFg3t7utOHbGA5lANJI3dwToHpWrxu5gssDcHJvJTzK3RnB6rCLGdAhpWYzEPUSTTG4PAHDaB40n8vnGLzRXYFZClg06XsYz5FpLItSMWF40PNxeSVIvsV3OX2KUh3vtaQLbwqIhVGxlw60XYlR/lyUukHLCmIwXnnR+9tj4yA09+cdmRTMWmydZYBYGTpjybMabKvDElIhbboOAjTdG4Hgb9VwdZ7uYtyy33woWNLd5Uq+gUsp35bK41H3cWDAsa42q3wnFVkkUrt7h+LySpjPUnzJMfr5fIvGOmMSMM9kEXzc2NaPLdVr4DFLNSir+Yfy3F/nUXe8WEOHWSolJ26XcAHPb3ALma5yESX3B5QfOZyrv4UGTa4RXes1WzgABv8XPZZ7M8KH6p4MuhxOQ7TfYuLJDBWAlUBiY7aSpgY9hwI7hfIWMjXQ3DBjdlRiXPzsmveoMVxLRPTSk0TKZp+0KOydTBZN72V/LO0yg1gA8TNEPVNsB7QHBK3PxIgUrCtvSsbNZLT6OgdNtXMe9y98F6Pmbxqt4HgHi+u+LY6XhpNoGlmCR8+RIA5XwhHTFmI1cJynXPJOuY8IPmiGoLk8QNBZIBvB1CLVu/FhqkgHxBwrkaXLLhZIyxoRkkDQnCXuHlzJ7fyXuOc9rm5gn5QAtfRVHw2+Ae5w66WA7PeGhcre986u1pHYqRh75ribKfe6aj0IwDb3qsLbaBUNE4D2ZPsOmFw7zvOavtS3BGiUsfoNAqPr82x11i+XS3Y1E9AdLpsHPzQE32hj7ojU2DdLb5HpK11TnPl0tsLYC9IwTvoXjfhf55PYHGq04q2caMjMGLCkGPoRtepSO/UIeu2ozrHct541y6Lw+cnKO0iD3z/eoz5GVUuPTWJjJSawdDT1kj6kLhdz4j9RxZwOQj0dTvDqe8JjzMZDO/xwQ/OIvBYOq5aaxXaXeSGbaBjiqTpTRLbAghsKwJwxStYl6BQ+iJlzHSjORiOgdwgH/+c8gv/1rOqw5P8DL4GMT2EtEeUFLo33CeO3jTocX8jXPozg8TflBzKZn91RKZw7rcvBuyrcQSxhqPLDNt/u+i97j3o2g4CtnLKd20Ivkw9azKkaz9mdeocMEE+mI0dZl/cUsUcVPIJxuc7YbBqu1+5rJ9ipl/1UKiySnTqmYdNipyXczFSw//knXL58wVUNY7WYCxjQyDIDl2fgawt8IWAPmOGNzJD6qEOFKLBI2qe61g6TtUZ6nfJSl7T84cnhcR1ZHhjxSMDuPbapvuROOyWeGrh4HfVcX5r4u+xX90TtcWWk/Q9cbm0GQHTEhMcxrHim/q1nJB+/pRsAwA8RFDNu3cAr4CFwch3dbfvGEt20tV4/DNUf9E9En5e+34ssr/ukAHY//4z+m0DxBQozVj/TdxjP32Mrvqt96wXWPqmdLcYt7Y/2O923lSistMCHO9cNz3mmOiJgB3Qvwdqa6URGZh8AYjjA3X88uMXg4+I0CO60xSBsNhvsdjtsvPb5NE3gacK2jQApEcGsgtP1gmlzBJ1N1xI6qDpW+0JOK1xG8wxhY2KDXv/Pa7eywV/R7s2UgpevPDG9rUv6wwf473bT/jag/2ALUvUWcnvrzOj6Js8pJAIQK3abDV5PF+w2mzQEzF3wQKOuxbBIjfc8KuOwqKcYzJcuxhJERFZMBy25knfnHreVx29m/qTsxkfzAPt689wgzp2+gPXjWJLVeO36mpgvJNzvaME6/RXY7Hv6GWwvcDvyKvzWv2toWuyLcaZ33qSjHJua0ZTIauu2XFEjUF0E1AXMHdRNkg+cqwozEKTQYQNbwLh/l67mvexjelCDqVfCiJ4IhF7GvsbVRzfA7dVSCB1VcIDV/qnrEbPYfCIQHk0B9fwK4JCR6Qpgr2O9A87XMBURnzXdOQBMHwnyNQQoeyYyVM7Ph3y27td1JfCT7gEcEYrJ6+vZxkLhzDCeJ1WIl1DmJq7MM8E3mZh47rRMd3V5eY3Nt6WNEO9jsPZj10SHqieZ9VhTvRizTCGcW0xsnhaHj+4CHLlSLmNivCOrs8Yg7RC0lMAyJaavUUQBRHRq7Gx4cTdmzL2DW4OK4DJ3WB1TM151FOByoRdEwwPP4WxhyCjIKqI80nDAkWLaZszUIDSnwrg1S57YZU6FlBkjDGrmmgOutPwahpD/n1tVWms9A8aZ+hjVIqsKw7yola5q9cEDEKCgyWt3ekomtAH7cjXlk0XHubMFE6z2uXnVR6QboyHq6yldXeEGH6tYuj71CAkyVxCC1V0f4+VF3fpIDe0iP3hHkLNnfoBiemwZgSXnMIS4ci05IRp/VntaPYfrmmpoiFFPnd+3+hQ1o0K50FMVuKJQgXwrWJdPVYluht7bHByrGWG72ea1aTOBABwPr2Bm7B8els9QLIE93aYJGdFK4xznWYvhUuA6S7sc1xWaxg0OBTs6qNneMcIIZRHkCkWfO6hZllhxwWuzmSAygbtgmgTA5IpAhrrxC3B8qAMWVNW9lilrHZuHtDl4hKFHne6Jdovmo44uYRhVn0sYKgetiXSLFFGrsRhQqDKYRwYEEEBdkY6UJRV8ptrSgtMx3qVKC7gM+LMUwxZ5rsoAdXcecIMKxbFXDFtYdYwqQrP/WaZvJ0S5eEsMCrBYlBE8E0FiDhVXaoYznibdXxhRAoh18Kg3/E/5fI9vuvfM+vlqbPxeYZHWL0GAOznNrTzRGNXNPO69r8BNpcn5nK76VlfOk/evyFqi6vekMcEAByNjgP0V6dCyer2HK24M0/F7gdscauxd9Eeh2IlZDIcbcyy6wx1rofPBDy7mHnQIjgNa0nxEtDUD1E0x29UjBcnwBgdOosCHjlfZDCvkkdKG6BVp2bkCurXMIEzwcgzNz2NDMNa9S655jDrrbJeJGG/c8/ymg1jdI105auTiDngNWh2GhDzANGC5ngd7lpCOr7l/RcEcDxCyXFPgM8DXKR2vItW/4WYSp/t0HYP1+VLQqcJbeNxl0gKr6W2ZD8CEqU1obSo0JP63fqbJ6gXL7BlJYKkbp2lC21lKyD53kJf+om4ZR1jhKX0XwykOvOVirLf3n8Yfn4+ejIYJd7AQhC4Gm9j4yij0CGC/3IVhaLYIUiayeuMAsB24PFkNNhplBjmAkhQXXqzQ/W839awJyPTKMcLJ67crCPSgwDlwhu+D6sLRJRBOstCQMj8A6nyxn6vj6Zw8AEd6bYXT6MFrZu3fxEG02peAKeczdPwCYMA5lU2EBukc54li5cKIGis0+qxLOgwH474kU+WuYQXDopOIoGRnfSy1McwRByOTB/vfCV7GwAlOGi0cx6ZxebG7ioYHDNekC+ZXS7Xa3UGqi2WT48cGguL6Yobw+bWDHwjTYxvzA2F6ipIJtpTTQ3O819FfO2axWPmrT79xs2h7ABtMlsUBALo5qUjCSaXYmu9obPoJZnNWmj0iPaLKyHmMSCXPxIbrJfbU8LuVwInsDgyi4eiZAGAAg7db0CSF4gDwE5rnfL4+X03Wc4a9v9j9m08N168wuuK7oNLQMS/4HqEn9D5lSvYuL2i6BePTko9zncv81WqgJ/vvtKPBUt13EUDIS/6wZwAw40dcs2eOtlj6kOcRIHTno602rS8LHcc+ESVXCFgEbMjvcDhdngXHUYVXZXeEAg0npsFrWIY38ShIkpij7T1D3Spkju6tRZklTvkDgPOcNAwnKQO64dw/m1+84woBlBUQTvgMo7mE46e3KBuVPD6bw0MYjCz7gFomFJijiG/holV9TzpAxAIGvSNK4zk88pydMAfOigwwETi1d7wQ2p4Hp7WWtZFwIjX8oYLL1y9oP/2M/mVG8OYnDPmVQHggBomVxbFxLSdy+e03EH2A4BUCwoGt7rlP33S9RDj/nyvwCXj85y94/a9/J456EsU1hVbCPz5/xvH3L2ngJnhadFrCGxG5od8yUg6D+A2HuWhHsij8R7XP9Xr0fSJbN2tv4Ie3dDflOgF4YRv8g/Nux+zVgt0eKkpSO+cM01s2PKD3GfPhgEc2vVK4ll1zWAp1g3fDAzodYZqSBRIBs5V7U5rHrM7DYdnO1g79dHI+fudzOKNQdT9mTufeaYMviFGulqlcr5xp6OtEFQ1/vL2SRWDX95kzseGB/8BP+Bd/wYfQ4+knCD3jQlZjfvpt8FaEz5jwJY3od1vCqfOG95iH0pK/WMPrgibef89nNZ6hAbiWcrPf1XJdO16IMEVmz3g3k1NOQy5fXr9it9nicbvFbrfD+WyZDK6Xq2UJidJJYshNupVa3boeJZjE0KluNhMeHh6w3W49fbtFoLfWTL/RGqCKuXccTyfXwViZIMsWQgveLEJwFMg075ExzKbkGKboGL6rrQH3D7bYxW9gjx/uf/3supsUt/5E93+3P9/+1xrQwzMQVAwMKXR9C+qXLOT93986O0vEGmjc6tIA26kZwdcQpUxI2AIZ5vAS6Y/9dwBQpqy9txB4yzAt5Vl4CMZQl8rwqP/5Z40+sUJCz9+MKI8hqirm32YQKT7A0rykUvCOGPn9zZ//A4/EEiy93wvhfPddoy1UqvWn1fqm0tGJM60UCrZP99/43lbVdHAWPcvo7BHoZAYvjjuCMdACN2/RGXUvYjava1FC92ijnXqGhDBULuau624G8VPFnoCjKg5QPCh5NLqmn3J/BoBXtI+E6SPQnxX4SMDLEFJsvLbnFfb0zueYVxrOUYzL8VtRGMX/lXjWfggHhCKqLmF1flH/i1U/w0hDWcOMYIxD1YHWOaxBoq9uUAukSkZjYQREgW8K39M9wht9/R6FKUWhI2I/IlxM/zbSUYNcOPb5pNHTQSHSpw39xnhj44Z5nn20Fk0UCpK4NrRhlMJoXSC9x/ir/TNqyTJUZHHOI9VxplsNRUim5qx9LTdgAVP5ZalQXQznjQP9Q56UFV3cwweuRL1rz1m8+954Ak55/F4PQ3TiE1ffEwLAW0ZrDLmGobghXMHCYCJ+9gUK1WvCRcMG2tmV+ZuSpsjUihFBQaToenJDoSuIVRH14AAG7QjX1xnYFTghFIPD/XVfG82v85zfo/bt+lwBcAPu7fXRb1lfjPNZhgaUOa6vB4aLe6o8kPr5ojjfbnZw2Q/TZoMKjYtZOyHovTvvYaksK42JM6F+5gd9dazLEd2jI0W604I2TUglNVkkBxcnliw1oQBIYLYoAuZIHQs0Fo8cN6U9twmKDuZNrgeFV3Stye5GuahD2aYJm2lKIXDMS6DKXs6EQN1giV0hmAfC38WuvORI4c7NswfFeVKoWiR6wIqQa9w4nHoiYrjATFXSpGUAPtYRFWhOK+F05co/AUQi7bEp/nIswpjJ1nMYDHS8J8Fg1EAf18whQFTNSiDFcSOUmBqp3MMxSgtB1fJfgUL/PXjaVLxm7Y8V/EGH8rT+uDYYjhUrX1e/F2F8GdG4OrtFcZKKlERgyPTcYQgb27Xi5WItF98Hn2jkzI3HYRha8GjIs5Y7Q+Spp2tfVOr4UjBbFsVsEx6K7zq+u3TkVuZJ42zhd0LJvdhbza0HEDmDYl08c0EUJy1rkXsmej+S/M44oAHTY92GXBfvBDLqnQDyPJLEEXUON0bEDQCzeJ1VjwB3nkRi+THWYLvduhFdscgy5lth2YK0zN86CWdPorG3YysKsxQ9lvUYnwlhMFg+/8a25kX18fP4QYfSs2Uft3uwvFZ6UOcGtNC3M6APAlCDGcZoMS/1qOR4tkOttirUovulmzENXqYC3Wjk1elNlIRx61BXgXbDRWZPWY2fynqQO1zIkn8kYos+pz0QeDuODQF0AnQ/ZFWKg+rLWOlw74ppspduNxOuc54GAAR6xCIieL3SEdG9butI9F4FgcJbJA84Qp/Hu/0GS9Y5nGIG706LjFYhp1p61FD5Vy5FMffY3jAeUemhrJOvP3Rk0Qg5JPFKTO52WersCqyP79G9pIXLR/EGz1fx/IJGsYMACFkbPceujodt7JbMYACY8XLL0+L+pSU+vY5j57tyRqVg4ZgYNIh07xlnnLdw42AumQCRtpUebG0Ewbvamm84aO5YZstcI8BO0V87LhpyGFnGOY/87tSdTq9knaDPsSE6HLSI7FwzvHwNUBIzBg+oYyykmXWmnqe6Z2v6tG735aqQ76JExx4KwfW5Y9MAbmwZiJKMuis6MxqP6Gf716OSUfljK2nTXaYU6ZAu6Dz7PklGU0epG9Fwaxgy74JVYZ8xM0AH//2jL5TkPqh/jzTjvglDzwAC6HC7ardsT/7/xi0+NsdNXuqGbnD7MHb0Lj4Xj8ZXgrDTIHVsEfI3aJBtR2C2ZBH17esnZf3CmVqRZzCoW+RLkpQ5C5+qBYOp2H7H5FnNSZfZjevWdaQP7lU/QEtoVJizzBXIZytOTOc6MjxRo9PvwfUJahHUgVvihVQGAOT8eu/AB4C/fMALfbWzmPo5fz7gHIHOlu9VvKT++EHG2SRVtFhLfAX/9gT8k/Dwz1/w/F//WsDLq6PDRwAPP33G4cuXfOGBbqNmAeAR7sZHWsSBgOfae+Abwx1hRH9Qj7a/03e2WOZ7ylRmUJ4hdx2l5bsCVglWfpJA2ElkiC3cvS4dxghW3uX68oLusyIlNNpB9YSrAlsCmu4hOLh+cji8DN7Fx54O1kXfo5XM7fKBSonOlZfMf+zPMm30Lf9UDubiJ1ULaGpaz155B4CPAkw//Qz98tvtun+j/U4Wqb0eTozzH/IJZ/wOABA8Q2EG8p88W2FEnzO+fPNda8e672rvAhywAOHVY2112zdtUuvlf3eogec08WdrzR0e2fGrOQFbEpWRoeRISZkGn5uGbcK02WC/32O73WKz3WJyHctms8Fms8mMK8fTEbvdFtN2Y8FSGHrAu2sSfAcF/+C3ieH97tlbxIG96tO+vxV+7mYJ/3hvP9IW2TT883rvYyQc8uePv+zPPP13w/9iAzoQwKqJGN9SdgN3gPiO4u4ug7kgTOVzZWhhnssiFm2+mRquc0djxmazRZMO7oK+Y9B5Bolip2zEmWzcF7KUOEcV7AU4hKogFFw+B9KhaMuB8ki5VceX0Udljq0xas3MaNKNqRjdUgoHDZ/wMwi/v5XKXYHdLztwm3DVOY2mH8jS4gw+MfapruW3qFTc5obiKk2/2wKZFsF9oXSgVTcrRUCdHFxxo0hDcKiZpMCeYsBgKHBiTzhifsseLdNzFGY4agy7ESH6VgCCDnRjmLrDmKWu9PuZbZrN+1QCOjCLRJ4gEBjEQ1gBFK8+7kd/1x7OjKuiyVBcHFbeFCG8HGDruxfCXg1+X1TNsxZWc83MJb6eX9OvGI/tI7oO2LoRrqkobVFh1DIkEAD+SGmk2E4fcPr9xda+23vivAiAC1Gmf4pIUqY9FOc0tl+ce9352UtC599Zux+95uts8LHdbyzFTaYxJSizGZJcMGRnRwM8QygNJuTp4xOuL68QspRf60rIC49yr4XUHhgvhyMeok619x1MfdTM9YB5bOGCqnfc1NLyWfTjjMmjuLqaUMzMRRGnHuEdwnHUBCOrYRppZr3/UCiHssPgRobQVxfdEwAAIABJREFU6d9j0AzCmjkIxV2kXmMuHKda+jwC0AlDOS6C69Vqd3Y3FKlLF1Hzbyhkl+e14o1UZnxne5P1u2OIKVNYvnbx3H18SX6+jUTY+sQqRoYBdacbau7t36UoMxNbeSpuoE3N+hNC206uDAXaxurKysUjZOC1U0XQMQNiorm6EgEKiFeIJB+foZBNjh0DKqA6ATRo2IwZfDJcpRBoJ+N2+tinoewTT1U3lMJjXY0/kD522lKM22dRN0I5nMazI6XhChv518ykAFqmxy3wXmle/RYp0bN/Kt+zn/ju53a+4unxMa+fz+cBA5V0rbCnSM/0fRX2Ij0ia0CKGxZAqccjYvSoZdlM8dD7bHvZFSrdz5FnLVDLTACCZR8gYERPC3onEM1QYYiYwalLB1NHa4TW+vB41oY2NadrUcu4eWIMRmOrA9+mNjQGpB656FE6LZSrTj01puhKKfH3upA4bfz/afJI9wYKWI4U647nmRnU3HUt8Kgm0N0IzZR7auvbRb2e2YjCYQh48vTFrQ3FoBuzvXP03tH6deBYqGfyCBhGCqlLT29dwEAquJ1XEtFF/fOsfb6AG6QxK7vIdaVFf7Y0mrxX0DkJoys0+aTqL2WRSWO+1fEpFPjjTiSPXBvV8zU6XrW11mII9sxhiPLnXcEmNW1x7GvpPjFq8O0EM9ySl3OBX2dFRHlR6aERW6YABVz3bgpbcWV974k1QYbPF3y1er/jVBufwku8JCKJ44ImxlYxvJ6wVEONneF0RHN4Vx3Oowpxe7JFHfeS5l49qtvwsCI5urXCxQcRpFI8ewS1CSAz1uBKaFs3tG5tbzI1YOJNa1NraNOEvplwvc7GI/SO69UiNRo3QG1tGya0xuhezxQeaadAllZY7JnaJhm+qfkBgC5nEBgb2hU6O+DozUbGAQ2cFvjTz5ACBMW0b+inHVTPKRvY+q1UMn5QhQSELZotGITOy/uSTPn6qQLYoH+doQ/BWyuwM0OfOSfZ/NnLfSjUI0rNgUsgkK5oRJg2E0DA8fnF69Sb45LIFXMXNL6OjBk0olQSPEgTNhJ6QsmW4O7jPHsZETjuVIHIyWAcG18vx4cUXOwyVbK8WvS5Hu0EtCdXTvozAHC5duih4q/kPm6WlhP3v7X3d/g7CgfCgcvytAcCTmeB4P0YRMXZ1XkvWzfHnY5T0r9EY16BR/0+LRHwyZcOp60sE5M6iuLQUxnZhTJUFz+vW65e8rwrhriWz0vSNOjYAu87rW9E6dhHpMAUcLXuw9aJMEpDkaexJ1+eQQ6Go0o1vohadBfIUn3beY5xFV6NCYoz2CPRiRt4p9BXU7731w5RxeaDOapc/cXz8RXAzvgskNEVZVz3xpNY5KLNYz6YzCOikNYw+fCJyCLQnLmxNO82pzgL6v5OEgje6UfQJW4TWjhOAp52PHBkRUNkvjDiRuvWzFmRLDuI8ZEG1QTTk4DE+M6kZQ7diQeRn6/zDIJ6lgDyIBNznp5hsvIEgHRTar024NX7awd0UWif0XvHxSPNGfDsW2doM0efuV9Al0/onQA6QHtHl47e50U5KFvWoK0lU1YCm8JKZ4nLZ0CXa0IxYDxDV0BxNl7MMytllg8coEpZG1hVcfa9Y99jxsiUgDReDB7KjiZn9sw8WoWEJP8kzrs5jAevU/Gorb31Y/TG+FtzMAhHzULzNegZEocnnvDyCAaXfs7gDgkUZza6c0eroncAsUWXExAlwhxD2XmAZJb8ZN01JwpRYEOECxQbX7uLABq10APPwEtPuf4tDFGRt08dn4YGpKoATqTYe4a7IxufMzJh2byO8PPx66/Yfv6M7U8N+E1yz5PnTr2K7c0eQeOA/c8/m9PHF0DpKxTACwR7UYtaV4XqE2b9ajKZ/obT/6vYfP5oMh5Mv9VcFgOA07P189FxABPhI4AjlTUwZIMzHO6IMOmgl2EADPknZRmnVTb/iES3544FfkGKk5ojAvk7Em5zsc25qTqDBM4Kw7zASkCcfK8eYHtxaG40VsLB3xOlLtgpcaMHzK+Wt6Kr4e7t4yPmg+HvR1gdczkFJx2gbtnkInum0BWEKREWXTZQzJDTJdfFHja5j9UStnecATWzugLmJDWWIfHFW2xHZljyeY6a6IpHEKiU3lsb+x4UaPiE+ffIH/rH2gcdEcrBI8TenMLWkOyCffjsg5jxJecp/v+b0ecx17oy3ztcX5/MIOY0MsdVUvUnfhVAnD14dtbqo1p6+fgb96v/rbpQHywUpqN1t18HX+eNnYdu3ECtWZAWWabBp90WL19f0EmgTBBlvFzOUJg+XkF4DVmNAIgYLSd4nfMNdjuLaN9tt9judlbWjk3fd51ncyaDlyqemtHrHusVDLnhgJDNjJ7aOwWA9I557pj7jOv1ilnUAy4c2lNngQTgtGjRKnsDAp8MKJXxWNLmb253/fTO/fftiUgc8637F5mlFjgtrtNbXcULl+/9u/1Q+19tQAeQirr32tIbEKUG1tv3Zuf3qE8Q+qL8CnGqi2LihtlrjhJZbc25mwduRJ+fIHhUxjnqAhLhzIpHYRyoR8ZdLE2oXis5BL9vTb0qFqkeyGKCC8TkQgmVZweD/IzdP/6Jz//6iC/8cn/dXLkgxcjuGZhuh/XemO9PxMbJdQ7fgQ3XvSxevBzFot87Ctl4Jp4ajEY8PxjZUPwsQAlDQFkzvQtFeyGuQ+h2Ig43ZHO3GtMuhDFZGjUNsbpE+jKG0jQQdWWq1GsamVLQlGOeOTbpVsxa3xjzYh1hQvcO5mV7JE/tFM9j7FyQ2cPvzxk5vrTP291Snqm7NpRrWIBDn18cfgcxDiO0eiehPnz0RRc9JUMzvM9Hx/X9wQfEheFZZ5e4mccrAHdoUIg2z1+3hBvFEDqDF3v9+oqtfy5iZ44jUh0NxwCFHAQPGArVIM6KMFyuCH705/1kPIMCkeA9xA2tf13iHUqnEIJXu7pGsavzYr8PJyHmKX+LqLDlgAdTFu/M3Q0BDAHTXkMthDIdNbVFi/BZzvNifBVR/EEG5UcYmvUTubRvobgFoz3w+3qsJugN4zlmdeWhWs1BjzqSbmsRih8CwJtIETmMGBA3UO68dIEIumc+iMiD5fvr3IIBtvt5YUhHovjauiqyetMxMj+U/hz2LY13gYE7FIYbo889DcJ5nSxijRothCFb0tUG0O21oTyt89YhHK3GEZS8eoXTzb/LTyBgM21u5gQADw8P6RUMGO7l1RhVBZpOJ4tf8neLOjGFV5zNyDkAEES6pftXi56WbgbliMoKBR07HrSIKs8+AXL6EnjVYUUFKgTlGXM3nJPRJ5PhysnTBFuEODw63CLr29QwTfaenKf3HYqeqEW5iBwguy7oXjPZDDybaeMpySY3ZI60k10VzdOUiSimqRme9/4WSqDc/wGHAz9aDVaaI021rYeN0VIbc0kfE4o9LS5k3AnUwwnCU1muUnAuDM3qu6mDhvtQEUZ6ceXj2oiuq3MtOko1RN9vt8BJYbCQpUC7ujVxwOocV4WFg5J/DgVE6cOV/PYzxW051HTmUiA0tJZsIoxblP2oKqgwJKrxzpWh5t5UNO7RfA9cKA4zhTpTRm6UTeWpuoEd8N8GLxarN/iRuE8Lg3M7npvP6s/6FkmsSSiyyvpopvQvMF6ZKTgPg0FbLEODKU1E84VjLwv9TaPIetzkkejO+zM8HWwzPEC02mNawj0RrH5tcyVvE1PuR9kYbhDtIHFe2Z0hmUa0s4oUY+2YNxmSAwCLxGyBayrvEEo3uju/u+0OfclIPldmRvR7e2joxz2gp5ttD3YgU7pjgAfdMGf1QR86wlHiApFdOixGdjMioPcZICv3wxgOv+P56AsDt8Pm0RXQDih1QDpkbmO+8JTGlOafYjjyPgveif4BWEFk/z0cdeLHKruQAr0sgp4U2Ptfv0cPGaszeMySkeWWu4Hh7rtrS4v7bijxW3KVnx0luplzyFqxAqZk3QB0xSovCYy/c9zilmASRdvtMF/M9DaUn/a/ukHddiHSfcLJPS/xZY7L+y7rbs6T4XQSjyylC/hTqXwt+oe6YMGjZakiAqJ2ePAqKM9U47axt8X5yfEL0ZBtqI4n5k4ZNFzkwkrTk5PCMJLux/wi4yAN2LFI6EcwmaMcP1q2GaKRicZwf1lfApBR7QR+tNICCoWcBHgwXCQq0JNdJyI7osqjC4xsKxG9bXwj3BlDkDF0bmxcO5QyyHhmibXzPY81ArL6FcGcyMOIZY5ObohAOLqgtLquupIjYrE9wEOiFIrNR+joDmAE6JPRWlU36HqZBYdxAzUvYePrEMZqAGilBI6Sres8m8E8xhhrF/LkMITogvFYwDkdAXwsOF0BdSO8Ow4IIjr+aHCpj/GwRVIn7bV3n0v/JWlCPkPxaNFpAMGnYPDp5Vp8HvfC0y0M2p2p3tWc9IN2hi9OlNWIUxmO9xVp53Kt9j7GXWHCMuYFrC1xpZa/VD5rvSqSe5n8c3kWqul4IDqM50owJwMZnQ4sELxAKS+3nguWuD34qCNZavOUWajADzyCVBVfVfD5txmP//mI/+cf/4mXf/0fCIDjnXUgAM3hgvHRnR6C//eU9wBeRfAkxttxFwAPmD4TtsTmACcAe5p3gtVa/+A4URwnhn5RyVO1x/l2XK6Iayuc73NWGTKbZo0Huyv0qCcCHl1sf4CndHcavtcSnR5AXk9b0JpeKYN9OkWZMDK2Ya/u1JAYJZkhGweAJz8PgoPdpQp6ILTDg0WWh2wFxfbpKeVPwTnfLKhjAWgP8NXl+43/xgB0MkikS+K8mLeNbQfgkp2tqdENUNzlS8otA12Z8RywOts+5tcCaw+i2OIT+BPj9Pz793R/0+o5fXNMtV9d8rHf8/yPtKU+finHG5c1WgYV+WA/w4OyyPXWVKCRRincBS+AgTPMmWD0O2Sjihf9PBJlmSkLjLSfT5eL7Ztq9jV0Y8Ax6ptW9o1M/mmtYZosiGDyz5tpgrKd5bkLrvMV1z57Waw6NB0DhKZ8FuUzqiULqhlAMXf7v4s43b6FpYV6M/mvZVNd6hdu4LGM9Y/CzT29X/0r4Tz4ThvDd9wY9C3YvMJ/V9n2tiPfy3d1L3+372n/6w3o/13t5gCvvgzWThd3qKhFJpEpYKIm1IUUMs+JrJ6U0IhxYYusZpiQfIQifI6YLX3KYAyMUdE5TU/JYEWzVJ+EVOSu5pHGkBh9ZWIBfIpAZRjheGXCJ1eEP/7nA/p/veArYdHHpD8BZAoV1k+Y6RmE4Wl1v/13kL57bbmTH5w/++pydMVBRON+LcaUxXrFtfGrX7/9BdD0MFwotEsbUKR+P1zIAyLqInyzjf01AtN8rDuxaLyLR5Sn9BL9Dh4Qg/3AQoYJmYCgTnhd2MIjBAc0EK4+ikd///GN7Ys3s3p9IkV6SSNnsWSC6lpEre/95w9ojfHyq8HSwUMAHrTGf43n5dlXyeug35xOny+TsZ0pcIbxhcYKaXlQC5zYLljNn1DJ5FxcmdQjyj/OaxjSyV/uKzC7IJnvcwYh1idE9EbLMVVGwvbulKvH2N0w57Vebt5HFoke3vnmvGDjN0/jMuEUvm2+XWaE0Lzkl4p4pGNuo4b98hwms6FwBZtgGByG4nRiRmsTLvM1nwsGjBDKcGStPWCk5rYxGC6+9qhuWMaAm0t5YezbH8NT92C6TPr7O3mrrQEbPsbVi8d7PY0dAGwIcoUp1ScCihEvtzI44mnFxHunvCX0s0uj1F2hCE8NZwp20pqxwf/k2DY+qqEgzXO0qEMen/3fRUYPAnskXLtRWC/xb0aVqRn/2aF9Vs39Xyg27vTyPe3NLXuzwzhv779ws7lvOH+vmQKW3wJwdE9jb1klBMCUxgGCmpKLCYAZ1i3trMOBxhm0/xoTQFMq5sLQQWoCQnMNtCmIYIKUR5S3NrkRGmnoURXMHV7XUNGbYJosRdg0Tf6Olu8Rt/xVHqgqAhq3xAuqg/chamgu3DVmN8ZPmKaNp3H3eTuEchdICLs+pzSuxDuL8uwG38XY4M4sTcp3dUWLOcNlpDuGYDX80GH7BU8HjLifFrB2j8cL5X4o78JACB3Xw3A2/r+dy4+3SpmW5/Tm5/Vz9wxTOpRs5JJoKBzWzjD1XYMe3fLH4y6nJ05wjXzTuyh88AH1Wkk1TuTGemRGAVtzT3sdabhJIR4NIuRGL8DOkZc0GHz7wJPk7EXCGCJPkgI6riW35/My1squh02sRypZFBhQv+I8SGQiUDVZJZxLhBhtsj1TNcfhcFyDRyIaKA6jS3A+04YxX2dMm62NNGslU2YfITYZSDGjbbe+jmnbdIUtpxONOk1qoOFA5XNSH38LvMU04F7EzTtFKb4WmHL8vt7NaK2TVVzlhC1nUewbeLl3rWCyGzkj3+Tj4D1BjsbRLp7X1WkjAHoBsIXgkhQ2nFYTftbj2W3BJwU/xmgG87nZbNBnwx/czLHper26gtdyQ6X8+/IVRIzN0xOIGXo5u9OG4WQ5dPCDl28hBmvQ/Hgfl3NecJKOPQRgdsuDD9D/V9Roe/tseE+g5AZJVeCIhRxAjwQ9YOABmBx8vszY7zaL3dJ813KvhsS1/OUW1VXGbjgLBP8STnFdxDT5DwQcl5wm5dOy4gdXo3Ocxvs9rufToIvDO8TZ8DxQSHkgAEfr3vgaFODTFU+15INX011+WK7G4n1DmU3u0KEyHAIMTzk/mzW5CQWNl9gBKi+idIjfbreQiznv2TqFzmbAfd3D+LtPGhZw34wHI8Oj7M7/hA/gJ8ZkjBHmlxmLrDFgTI8Nqh0kisvzZewZYq4AIJAjJQVTKMSzJajDvE03ZFRbL0oaRnn+AXNTlaAXRCOtCCH5nBhn0DOrdxpnr8iyDr9MA46Zmqd6N0V6yHsRMTvS41s0I1NkPHMDZzhO5LY5nWeq6o5EEBYBewL0KewISQdUCcSGt5o+ApgB2oFpRsNsRmB5BRRgfQTrBSxPpsvhAbyi3eROUYi+ANpB2Ob5srlFivaBjQBA5AUgLpl8vhof6HR2GOWjKYCDwaEo1CyS2Xb+5RK3rg7ciOpFnuNw7rDtG1xRyACWpWbsazXsrg3rNuXhCGHih5/P2LHgMUpo4AKl+FhTnkVexGRYDV0VTJL3CiKNuySOSEeakCnyTTFGHcZzzzJjyYM1z8/GAN/m5YObQLhqGMzN2A3/nTxLw8CF41zGIun42b/bOh/9+aiCo0R4YqN3p5wp0OkFonvnIz9B8TX5yrOPdat2HqaffgbBIlJBQCfGAUeTexX46BlautPOmZ6x+fQRly/PJjcpQPoBAGFSQJjRaKDPBkWDZXk4hCOhj4W8DAuR6QtPLkc9qOJIhAcxEn3XAES0zPQBG++BzMBNcEM31HiH6th1j6G6fcHqe2IsnMkM9L49eED640FhrEUPPEcx1hP4aCb3LR7Qnkw72B4Y/dCx/bg1KDiZQ9Vw2nNZm87QM4F328X4yKqZgWZAdTPk1vjdS9lN2AIXYMYFgGLrsH9RLf1pkDlgJRfd6uXse3OacIBFLR+yAx+X64Wuz79nVgDC4Fe+1Z7UM62ojoAZDRwzUqCPoCrCwz9+weHXXzPbT/yruBOo52fpk9LCDvG9RscaEJf92QU4UVyzLPikRh4Yn9D9bEZ73xZyp4V+itaXI8vXcFRSEZxOZ0zTZA7DRGhEuBKg84xDd90pLDNs8DAWEW4ZpDatZar2aZoQGXZmEWCe0+Hocr3gcr7geD7jdD3jdL3gcjVjehddOBEvHNVi/H5uFYZ3g84tcHTeG/9+357dXcYffvLPvanStXv8Yv37d/u/1/42oP9oKwgwhau1kmRxc7QhjsRPzj7ABEdj3huPiLnhtb+KXGFyxY1XH3MmKpQ5DZxjCsWmiWMDSS1lh+g7Rkqo2KvYEm6UJQTCkzPVkWqkRiqff/8Vs37CBj/jo37BC436JdM/mgtFA9n99Ygr+v7zaOetsd1bl7z+Q29aPvU9xjh7VwhPIem4B+zgX5wAEQ7Uzair7JFNrvgVWmRIiEiWqLtBKEfAAWNPXNwjn9A+NejzE8yg/4ow5QfzeE+bTKvPCmN2HzDqfSwr7blwAGOaWrne3eip6tEQOqKcAFiUoHfAn1yohYA/ctZEFyCjp+KsRhLRtXoyhMzkE1VTjwC1c8kAaLeHns4hP6FNgMyakUpDyCwMWPKznqI33qo61hW1Bnp4yI8BJntRGOFgMG1OJyzdC24Z5BhKXfM6PMCiDBtMuHcn3SH8ViSCoXBvRKlYjwGHUBvwOp5bMrIW6UdY5B8oSrmoNXczDwqGDEjFWSoeYuPC2Ld8/v6qjH/XjPYiRc83mPA/7BlYzvXiwp9swcDqDPCGXEDxN/VAKIN1NRnJT4UsEyRV3MhbNiUjGhTXhMUwsIIWYDuUKlgag7P/HSzt1cENOjta7Y8roC4Fa+g4s3WuA7PY9axXC2Ck3m2w1JerPV7hhXtRYetrb+31HfnqTnOHKIzIp3sUrnt5gtOpuNFTMaSp3qUtYWSFWgT3mv6rmgE8DGBp1ONuteunoCkC0oj0HlHKKgrlVZ10LikMQ/sUximvN948GslStEdKRlPi966ACmbplj6wM0Q2UMdFYRRLOC5RzXX1TUAc326jQhTUpoxmt1TPlu558prolgbScQ9HNCyBMlrHkHJ6DhMtlMYxQiPhmufEYJehZGMPp0ZRi/RnDqO4jz11pVTepVkn0tIp9wKLBbfmQbGNF8eZWb+z8gwhzPq9qoPvHB3GKfkzbX06KjMe67Oeic25zoncqSMNEIt7B8M0hq/5U+aozRJD/m9RPFF5eKD/+7h5sedaeHEgz0A4ZIQZIeeRN1b85Y+VPSVyA4cO/BiK2pGAoBg5QMg8fUETdazhcJDAyESUF2KX/d+wOztPBOcJkrrr+F3JSmrYOtg6R8pOUQBdEncHr5tvm+HpvuOEGR5Jx4iqXMfAv5m6vchAI4JoqaQR0XRSGcafiHj2uYilEX4/enxFpZhHqnffS70oLjhi92Cq2cvxgN3jYz59r+vcOs1vjq+X9Fo8Wpr3BDmvaO76s9b3bYEo83NnOvmavfexL2Pzc0UWrmp0A2GUQMKF4WUvFeU0g9vY6y4KZnMaIi/zIQcB7wnEHeJG9MQD6UAXF8IgkdjL1vtY9xqoxvM1zc5IkPisI1KZHp13ChOj80qRst1KkVZcWHDuwRabHpG8kEYpgsQ09/iXWwf3+I18X9SN5nT0fm8AiBAuwssFW/cZdxf4psJHOOqwkpoBGBjylxbaEmdV1SNEB57JgVPg6jIILVF+9wZY+JqY54iEtlNrBsDbM1KNfZSOgmW+qo5fa4SZOTi1/YT5PIM2bD4n3hMTAUE26jS833rudAjSq3sVclDgYy6d8TaeAh1PhkNAxnsZTrFMPxFJv4C5jP49u9HYohJjXQWWeGqBE+qAFmyR8aOUMqn1wggd1dBHBf+VEcU+N/stnsaYf76z0Jzv4iNuOYH6WwYbIM4rPFrOHDgHdhCYVDto1hjREVlbuMh3dtcBSs1HO/g3QC063x1xCIELz6DePYJ06SRg8nHpO8qhIGhj0GRN3BCjZHq1+/wMKaJQWwDj2NT1/gZ/Y30TKHmemE4QdPsu5hU3MriVlarvSdk7CYbRAK5sB3T4Qen4Hj0p4A5XWLylbneconD1HtlwCu+ffIH3GqkjHA9klj+H13DQVRU0VTw9fYKq4revv6NCb8wznUdcjtqTYib28l+ENR5b8+LBX8f5HXw2YI7K5PoWu+dQ9ST++ZWBvXRMzUpZdaUxRcDPKGH/j3/keqgqtJvD9O7nLeZ/a/KU4o4MUabm/OV54CRSKL4iKhBMxFAizIgAEhv8MdYl8QIPZyFinMlw6n4WvHq0PRHhURWHoL1BS3LDl/r1gWHjq+Z9IMIDPMDmh5vRkbJdaTivwzhjpEonUOrPBEcQHqwbBhpNOF/P61Gj4wTNGubRa9DfN+jgjkDnFc1549bBXcRNdz7fHLTbtgcttGVH6KK3+EIgvKx5lfe7zrbFJ3QsS8LeZM5YDff071/HUunb961bTZv+39E+qyfmWKpev4u6vdnu6nPgwSlOdwkpy8T/kUXLYI+XD1dOx3lRYsbUJmy9xvlmM6WOpYtA5yu6dFy7pVq/XK44n094PRxwOp1wvV4wd69f7gLAiMqntDsM3juwMVYy2L31Kpx9/bF8+fO6iDfaXwYvlS4HR1T4/7/qNX+3H2p/G9B/sK2Bd20XIb+YKTTWkE5L4VNhnnNnT0Wx30w4z1YjSbpiM03ofcaeGi5zx4EFH8gM7TXlauNAbBY9NQZnBsXzdTbhwAVApqr0wwrxhmd54E+9uYXSQmbfn8lqkxiDpnjCSMuk+ILpl/+E/voZ//xpAybg8u8r+r879BfF/KvFzSpwQ1grKf+xNhiRZY/3ei1otfBaKOPKwJYV0bv75hAIdPQz1HELCfRmeMGIuOy9VKwCCGVD1lRzQyQ8zaT9L25oGRE73ZW/0AYSxV6AiRUbdudYN4qEgujgNayFSr9q6dWTWZJQKhgDTUxon5vV/fn1AwQvaYx6lMFEKsxTEQBeSSGk7oxh7UEJRxI86BhPLHvcE4bci3++fnlZEMcHCcOEpqBAAJpHnPdnTV60Q7P/7sKoCbIjcn6Xe+ACShjjnbyFqe/qSt6Nn7kOhh5PLlApaGsHjKfwrFdsJvPqI1jtYlXFPLsgSRYd1b1mdNMQDleKBvWNcc34vFBi2Y3BKlUVTezlvOA4xloTzEj/RCYQxP2RKr65s8YQEyijsgAMOEUw9ZqjCKYaFFHgBtdEwNznJYLN82FMVEODkiustWNqVqtylg7tVx8OlfNMOaGqaBAXxjiZlbUCqwz+7vV4RxFgFzfeZ3luyMOaAX7juXg4FaF36My9NyXejhuCIY59gvvCiLlYUCqKA4uYAGzRkcRuAAAgAElEQVSpn9SNHUHqCOh2R9dutUq7gDYNqpIphxVjfULZEitOwZpIKOIIgyF2CN7FOjms7UuEUc50UI7wug6hHyiGo8TNS2Ltgb0IBYbJHR0bG5pXaY+o7QEz45Stlv47Cdh98efOL7T8uN7+LjPuv/T9wWT2AN+NgD9zShrgONZFc+9FCOypGtVLgxB1j0oyI5MZ9QnzPIM16g8zCBO4AXD6QcQZ6T1NliKMm0Wsc7Mo71BkiRteRCyyZ+4d6GEYNnrGjWF1G8XrnPPSOK7q6a+9lnTsI1XDu8FdawTyyMm2mbKemI3X8LcwoEqWAp8MnloozqLDRe1ecuN7UagXZVjUN1ZGRvmYEEyARM1SyZRsgU8jyg6wLEOslFE0RH1kItJAJq4YS2/1MGS5sN29zqiYIlE0FLiCpVldUXHXH3YO+u5WDzLyICzPRDF2AUjmFoUWpfLN6VHwU9kb1578U+RfcWqhSdGy7+zhjSO34K8ReDD2BJ7SMgzgCp4IIIZ0Ky4T/ESSHhU3uBOIBK6PMBBJeEDSq0zBHjwSwjHFYaGbor9rH/YtZwUz8i2j4t1ZJN/hcBE5eV0RD6KSwcBubR4Z13v3xXLjQq6KNYtA9PUmpIGLt5FlYrXnClBj6KyWOhiAhelU/jtwdlEjEmfNU/Xb0kjh/2/YHHkkItLCCpChMbUFzL1xDshxjSj0PAj75XDMrs6HbxvR65QSytNQSZCz5IN6VpDX1NQ7hvFBYZffo93MpMJ7MzpO6k6OAnMumC3TgIknikvvxuupQs9A2wEEtlJmsDqgxIT5MIMfGrYPe4gC/Xz0GtN7G5mSOfexQEMjSQCpwVNwn1GHV/0fhUBOdjiG8fKdlj+ffcL7xCcKQI8mO7enyIZkG8FPvp/Xvugu4frVo/XDqOSyRRqb/N02wvtjVJcHCcD8YqXg+OMEAmHzwbKP9C4IB3coWQpv26jF3IfDyXKXhQi4XpGQEXyhH7bExuWxOCM5iRxr4dX09rnkQoquws7ve7oL/73XeUXWHDt/0Uc9I5wwowUO/By6cUqMPbBfVkqf+XK19d5MCY4Dqw8eOqaaUqPjXRPZFKAzQJaHIWV62gN0BEAQ+QCQQugIxQ69m+woBxlKZrFIRsmMgkA/+hyitBEYShcAhCsAKuc/KVyQy4Ijr4E7dIiZXSxjnsB5YfegjowetHJ9F2im9A7eMblnhydRc6rIc5se6T5PGe7sACzdqyhELBJdwtCYk9I8Vrb9fh6VUqZXBSQy8tHJd8nSuXdECRUnZSCAniD0DGWrg2411B8BHH19osY2oYWghIP3ZmvAqT8wWjeL1dgO46SVxFkaMMyBUsu0NHm4yAhAGOtINIIfLmp7tSNa5New804DBYjTWN86MzqP7FSq3elrwRO+xln+KDIiDUBatPFbGIgjEpXyndCADKTBfGRPwEhnqxhOg4WHjmcl8b0mDQDBdBRVDihrmnMIXkfCyco+b/TB+BUm7PGA9jj0rvPp1emTjXdLplsgEPYEj0gfr9WQs1GNP2OPoWOPffVs3AQ0CNRLaa1xIcFKCnz5+oyfPnzG4z8f8Pyvr3iEHcGnf/6HvVVt7TmcfkVxnudR8urjR8hvMzq+uj4r1sLfI2PtgeGYaJGqZJlh/D6F4oNjlVd/htmeeSLGqdmpA4DXCXicxWqkI9BxrJRlhpNgSDGWJ3QNkWtxrwbje1WcyIy7O5jR97aQzXoF73wLmu8weVr9rov7Ap/a7loq+3CssKw+3Le4Hmf7fU/o6jIdXyBghON+OMnwZmdOWb7uKVfmCSFgC+g8W/+T8WN6VSjmHGDaL3xsWwBKjFl1cdZ2DpXX3IM4g7UjS9e+Xs3KNzZ6wvS5AV/WNxXC8k77jZ7xWYEtCHNBVyED1UyaPNjozECiZJkRGLUEZWn++ueVY8Q6Q1xKi2+Md53C/V77QsDPalkbtr/8hPnX32PnvrvVNxCKQ7D/ZvqZIdkcLhdMreNpb8eDhdC73zExZhFcescZJuOrKvYqeC2yMwGJF9pmg+1269HnliHmcr0CV1ury/WK63zF6XLB6XTGy8sLDocjzucL5nlGlJKrqCvKORCGPBeZQi19u6ReAu+AzVugtN6X93fprT7+oraGe2bbF6blOwJfxP7SXziGv9sfbn8b0H+4USGSjkwLEbIfIp1Q8cBKTO9kqTCVFAwjAdPUcOkmJISSt3EDA9i0hnkWnBmYiPDIDRdyRsGVsBYVFQm9BxPK3KvecIl4F4rFeq0IIa4ICZ4355uC7VBAMpFFxBJh0s8Q/h39tys2v2yx2Rjo8X9Qpkw2YvMFTMBH3DGi/7dginfI1D1k/P4T/20tU9vel0GyqQiosQsJ+TRG9gGMlGWqeIQZKEzcahCP1D6zCcUfQAATWCzaUJTBYgKfUHfhxPoKuUvxCP5oRl7zRmNnGD8A+JrPqI/lrW2tDBcAHEnxiGWMdDJJqzVRwIVIFyyhC+VZOI5oPQe5uUUgwGCOIn3dDrEPIbo7/CfzXpTn/j3SU8V9IajHmFJhIILrVbGP9KHOMESKrpqOFS5QW5q0W3Y1frsRWP3fGZZqKY1kZeY5L9zfH95vsTld0oC46Duix6AecaErePQ3aVW06W1H9bDJ+veBbyLNYkgxyiNqWAN36RBy6irUOucGS5LPoXyq64LVp/hWlzn0kH8UZ4USJKNtVvj1m+0tC813tvo4YQmfedFXJPAREWXdv+o8AQVUXFHmygebl1pEWEScQUM7cGeanMqHHNeuDqZAqaGxsfjQHMpCjKn0T4tQVJQSgCvrQK74N6Mo+kiixjSBojhaeX5heF5dz6X5xn7+0V20tOjjvFanut47lumwPNLAjTB3+4txEC0gfyHWuYEO0JJK3u7voiASNCiE1QQCkrH06oYm6kZTPGVyU4XwBhEta4Zyr621sRRhjcPBiJIXURX0Lmg8Y+5mmJeIFhEzqneZ0XsDtxlNCUDLeyz63WfIEQluVMXs2ZSe1QCZMqjZmKnZeCZuVmudhse04fSx11G78ya1m681ueNUROPn+QCgSgPilTJatXdP2d0JvXcvw4NCk9ZRiRYNFsZwgmcucYWtRUUlYKWhPWp8ahd0j/CPWufw+u6Bh0P5SDrSir4L8mti/8PNOyr9DT592fKMvscC6uDRR5aKipbVyzoYTmOxc3iTijB5N7o/12SoUQz2/qiH8WR2gsFqWB3uwYWZ0E3jBqaAbzf8B18RKqMlynMaaSZrjQhqEJQFWmx+6kaP3v3tpQQKQK6oYoNTRKSdG84RimwkXR/Ya6w7Cg6V5Le0KNTHtdiX6uhihgMraxByjISTXXk65132JM8fXNHe1Q0BBvuWrpjAUwN8reKsiISD1o/T4t3mETQBp6/HypZ+f5cLGHMcEF2QOZPpecmT1UfeOo51CPn5jZv1dIE+stFNxPkvEYXw0hGkXrJDzGkAhK6KRqGcJ5AKmjJ0axlVrq41VT9vZtxU9BfH409kGkkMvh1M7kgcA3R4EoGco7RPqUlc5qTlfzvLvACakH1u1J6xcQscYm27mXDCdbGamRK/rqdK0tXB05DhmxWPsf5bP9s2LfkSgtXB/v/Ye9MtN44lTfAz8wAymQsp6lbN+7/dnOkuUWTuAMLd5oetHkBykW5V/2iFDpUAYnM3N7d9AadzMhu8IWAQMHTFJWARIWb6bB9n8C0nWGyVs5Q3eCsKd4qnrOvvC+ClzLiBX9W5AtxbWS7sL0V+dP5obwiaCtEsMONVXgY83hsl6ilFTKMz3j7DpztOWX1iejcQTubQF+NRGQR1aZsLDmAPZn0TF/RAOEDeWCs9lPl61Tl9Xw+5Qgo8tMKCB2BVQM708ExesY1Qs78iwEFgFR9IHSzssmee93JjiStIVBEKPsXWPooCziN0NTrTKX1c+ayzY6NLuTXBx+vjSMx1fSxLwQ/SAES91miA4avzDZJXgAjDgkmGBQ5r3S1bZZM5I3DIqmb03oExsPYOWaGl3sUyB6udbXBMMRwJZT1sBRJ/yQIfAifdeZ50clrjAKnzbeO7gwNeeoHAdejI6pb8XS9RyhOyTd3f9ZWUHH0igqX1GiSvD7y1lk8KVv9Ngj71wNt0nE8SgN9jeFMphvhVovLOIgMHARYRdQh/EHM6E3Y3CwYGTi/Phgts+8iqhaKF3swWSEuBOzPMA26CsKEEz5K8KuQ1+92rLW4PJReEw8NX4NNvuP/Xf+J4OmFZmjmgLWhWgP5tBe4Jpz9OWH4D+toxmLBbdngbRwyyXuiSz44lJLMCFz2omX4XNoBmTrCy98PGyYw3q+zVXI4dwHFH6gx1MmvwGDJwPUjLupPvkUJzk2Uab3VY64PeDI5nTvTK535w0Obve/dM1ejsr/N8Z63aPmMfPPf08mKVv2qlqHJ0nO1ZH41X8ygMV08xQLKDhAXPYC95L5A2Hkcnlze8JWcmbqSM+S7tLYe2pvj0/Yu+c3iClfLTPIy8RY3dgKud9M8N83ERfP+24zJAPoomHPqx4NNM8v4d793IS4lzA2MQehcwiemMA0wDNLScuowe4/FEOaeDkSlHGpTYGkeLvDEGjseTlmXvK/oYOByPeDsdcTgc8HY84OXlFW9vrzhYBrrP2Gml2xW1IkXR34x+dBnqQB8jTcO2p9+1M1SZGBc+/32A/1uPanegC7+HTvE/PK5/jjz+caD/1eMdJkGXfncjZhHQndNkmWzb+ESRz+JOvsYLZHQsvOBwOqrxSgR3YByp4UiMezBemwqMrbGWEuWmQms3AzKPYIiNVVMcrkGacXaIGF2kELpHEdxqqduJ2BPhyRjuM4D7gSwbLoL2uYH+/B2dv6H/+Rn0L2XcS9uBWLNMTvgCwkcQHi6WTLkI2799yOZzUQr8pVUeNTnk3q8Wc/TLfFuVqCY4lcfqG1MhmsdTASChWPo9WyJaDQZjuIKJwDU1MxUnuoryqljTQOcGHoQnVqKwYMGttBCY7nnBKoQjAysL1s5YMaKnzwrFk/2njxo11tQ5ceod/esJV7/tbYyfw+F2eviqvboFuIkyzlaKNuCiEPng503C6wYxxkzEHGouFmp58vlgkPXCSgWurk8kD9nJetWNUFT3YiDMXyR5syveBMLeNDWNoq+KHUDXBJhC5S/zxOC3wxHSPUsgZAONCjYFQJgtQ1hCofd4fH+HV7ZolFniflQhMqLAXWkozPnStnt89d56Nn9TmlyAVtST0i+5JYDNeKDOJL1uEoLis2X3DRTDj19mvbnEsyhdZxcVAKnH+qWA5Flk5FsqepX7sW+aJX002Pdy/kfqVDzPt+LfoFVTpOtk8PnOy39BksqymjK9z3G0Glp1N1kfLe9LC1VE1zUdBeGMarMxABDI0LVSpcsNSAChOTpgZP+BaToCgPYJF4KVrCSCZx66UyVK5sqs4FXFdcZnM9cQRdbXiLKcAkvLCViQ9Y9WxXPFDgsYsB54qbCd/LmRsTqBo/ywYQh2+F79YYETweTk2x69F0cZWWapP5s4T/3gNT1oUVmVoTSIQeEwdZOeZ7wQNfAQ3cdEURJf/3VgQM830Sj6BlWadoCMViI4bKAmIxEheo37aS2ruMO6ruZAH5Zpp0GINahAokS0K2pGv1jhokqb0i3tc+7G0WZKI7T/OlFcQwQsrQUOpqF6gEivGZYRr5ksI94tsICu6PGsTrsoX2ayVHARInN4syq+QnAnv4wR65ElzgoNsX2c4GiQLuiFQ6jTU8KhPnpmn6+jY3RzNI1uiqw7y5E0HpgcUUp2z2mZxP+2P/7Vw5ClymXvXKn0NWHsIzxzhMWTjQ5QcRjZHLVYBwNjREaMZ8q4bO8BFCFmbgLDcq2Mx3slIX1pAsvS/oSGymiivJ7NaZjBHnq5P4fZeG4p5+0QA1K+ivvsLxMwGoO7Gl+INCs9glQknW5EBE0gd2MvAZaVPixjTUbm8IuU97sTLxxZZsRz2FjlHTeKxmi39FTYxKVm+5jRRwcvzt828kQYe9VokyXZoRmSlglxOnY1+LhxvsoXyPKwPpItFjkXueD6uXjsP3wAgbC+dgiOQf+OLyvalfZK1uodk5gwI3xZajfKEhO0WrNxOjmCsAdjD8HxPCPHH0F6XcPe0PA4v2sjTI+XV6VLH66Dz+uhWa/2UPWnvUnRcW4gfbUWHVphg2gYnWULvgKw2+tjDs8g+qDwHSoXuCgW2TiZDlyGaLwIBNAALba3hrKefprxpOKc4rHLTzMAhrzo15dbAAS+dX3D6aKe5ltgPPu9Q1vRPAn4ljCegWYZ6+NZM+iD/tySwX8OPHEB3B2/mvFOmslvtoE6Un+uRLWELfbmjJUeSUlSN+O8n4c7pl22c+f41tGadDd2j0UgnMnMXhbe6OgWfknfM1kh8crlQQoi4wZgH1tRKHSdQs8o2e6S9N7jM0Ou9CA3g/dup4JqPx0hEOyurtGYcXh5tfF4/rKvuI6lWVQJG6DdwdlN1vGgPMK1OcRfNLA9niOa/kgC4ixA5/Nz17zLid1qy8d7At7lQyxt4RMOV86HE3tlAbXjuNO4ViKISj/S4IYcr1oUcrwYYH29bQyVtmlVlZKhTHWtrC91kTkCN+pCkzqWAEB6Xnu0S/YiJRvZ4DtejbebbMcqh5HTDRCYbtHaI6hntRQSDUxhfoFyarb2ErcgetVgn/IubVXRQKY3u4OQyv7xv9t97zIGAOtobFn1lDC9hug8t/zywiEiELY5WCUYsuoeo7E6MyFhjwwn+kjbIJVnxZqWdYCPz3/ajgHwDajZzRF44fu84CbVe0xPFNFqGQ5f8YBOgye57pIvDN27DMbPL/CscwFwo2MZAjStqtVF0J+tdSDDgh/dIQQw3yoW0AFEhFsCXr3NDFQymOA/DHZiPdalONTt0KI9Keu7XlMPLUGv97+QgL8egU+eMQoc1iP6wwOuPv+ulaVEZVj+OHD83x343NBPKxovWP7jGuPIGF//nGQ+QOU2TWjQ7NHuehMYjdQaN4hw/dtvWMfA//rzD9wErQY+CeOJgE9g7D99wrfHR3wAoTWoHGk85s6Chx9IgEE48gAPD3jyYBfFHYUrFTwUwDL1g9ZD8AbBNQivW+FJ5AwvJ4Hg4pE4DQuQcYJKQATyOQfFEDCuMI4HMF9p1rgIXl9f5n1hsqn/EK1FeLYUZNUH/8HnYGNY/NuiLfpWzYAnq5h2qhWqkHbJdHVi3jR23EBttx8Mkx2WWzA9QcAPKz7iHg94vAi970nIz6QO6EFmcyk82e9jAN/MyfvJCHLQAuPXPp9vvlxFr5sq3mw3VJE7vneEw/kMgdR5/tsQLAQsnz8DBPQ/vyp/s+vvDV2/Xbj/3YNQbHQuw9h8ibRqKek+PK0nOAH0hJEBYF2PWr0TAiHghTHZxW6G4JWA5m1EbJrr2nF4O8D9R2tfsfaO18MBh9MBr8cjDscDDgf91/uKDNSeJI2Ae6XrMmbneY8KNBch/50z3z/eu7eKR/UCorMrfumouJZPKYiz5ZXnD/hL7/3n+HvHPw70v3BseScVZugXeLllPZFMOvddXJTPJISDAKKZ5t0Ug8a6VM0MQT4AMqP0woyFARBHttZCzZieEkI2Ax5br70Ro/IRuQOsbsYi3cg5SSlTDMUoYOJCM6kwdfX/7HE8/Qunr1/Qv3zG8q+GMayMFTGYPmHQgxHfc7j/95X/BC6Ty/d/PruGtHT9Nmv+33PQ5lsaUnII31GEkApMKKJ2/QDwAsJOCAsTdibM35IKvNzUhZ4RYA1P3LHzMrA0C1O0+a4ZqKq4nL5pWTVnrg2f0PEV5fIfHi70uPN3K2jR5q/O1RNTbc4Ec/oIxmPZx87Epe5thfcwGLqBA0VJSXXOlbt4YNxfhZnoK4x8n5fYjQyOHvVR9RkLaZ90f68bnJhUaxmpFNbDdeUx7fIZokGPRM6E0MrKLx6mFHu0oGmvJlBRllOTqqzYWhhOiQPB4XT2ks0vVD8SBNERVt8rUt7rOCI5BipqqhnoyzCV5orvm4sjOPtBNn99Hr9KDv57aVw53tFQcv+4EYFQM2pdIRSIlV5kTAYqc57P0yCgOFhgr56DBGgGthIdbNqez2MVx27M/Ck3IOqKTFUayqnqpFTc9Ed5ga+EjNPCFLBXow1U6EcGm1XYTI5umR77l495GZOGzNcYFSpwFbPoTMoJEIp+dVptnxc8G4B0QJjMweRVOyV72xoExIyjg9UoNKz0N0Q0Gn7Ayquro3Z1Im+OOKySfCgURNJ+6I3BxGgmX63LgiEdvXf0NavbtGVRZzeMdhr9jMxeonCUM5M56AnMC7gpfWO3hDV1yrkh2cvME6dxw52lLs+QWIlTkeyPHKumV/YxtHcvJS8go7Fa5tPXTd+j1WBgDiZARmb6eY8wQNKwDMCdEiKsvnoMNYw6MhkNFbFS7RZJrln83Zzpdt4Np6h73vfKLPHOZ8+/R/uXitjv0KkfH04XZLq/8mHgkkJK0x+HxaXrJwcRieXwWPa1SBr0jKC4MzcM/ja/iU+c0YNClOAsUzcMEcDCbtNPJ4sA7vwNfxIj9rSLD5OFuMokjjMW4Kb9LJtmAQMa2BF0xoMsZio0l4xVJ7qUC0ImvXBEj3QkMpAZkAvhLXIbXIiKdXF24PvaA12CdklBLSo8YHN4EAqBjC71KNXOkOSFKEGAZyv48w7zdw8CSNQ5N3AEcITIFSYdkjDB+PuP08oaYw/gTWyEXr55D6JSynkjyAwcwdiHuvcjOadXeUwnktmjRe7yVilGXgGwlerXQMoxGCRD24PAcIuUzmrv7x542c34R2AN8qWURX2do7xzMTYSDW0/1i+U9ZwBaHvF6cURWuAU0ztCLnoB5KbQj1cBXVlAzc2APAPt1h5sL263mz0i6dibq92UYRmtcGl62F52Ax2bnDWeSwn/amjH91Fna+gLYNj4Qm6z3TXLgsbpbL/q5eQJyojMQTLIFZ0A0RpqS4/zOUkukhZE8IPTt9jjErTh4hxHqSBh4wGpnOJDFJ8z+++zPLWlKYEL5kiqMqCSYwYCV43/F9rkcouU+c3BCUXmJMXNcbBgn1I536RBuNPfVqGs0VaEzjmk4zLXMy9zvia2nhkk5TaLKKW7ldGLbBrzJc94TCEgrVXbRfP/XZI36MK1Oi9/T8WpI4Aryco5IN037vB3XsAcIfEKb3617HlKz0yhNSQmN2EA9KwOSiKtzmQ8S+PvvE2SOjy97Lt3BgGAA8kcXSuEHWU5dp/iEYXvO0yprONPHM53nQ8SoFU7bE95L/Zw2gVdzfcmQ0assQ8srgEF7cj9VaiwB9X1GJWNT7VQCKb9JtDQb297479FoGqhBfnuQtILKgV6DAGNK/CNBsp6EKyTrvVpBejV0DEXSO20tyBqUY3wjQCyihIhg0wzixHbGFJnqteINMu89oFORDeu1aVR2eWbPOL2i2D36TcwM94evuo8vvwBQMDjDtJX1dU+sVZNGILj6RW0LFga4yie6uWJYWWnlbZUIY8h6RWRthu9EQ1ycNh36G8goD88AMw4MKHBq9jo/QsJuui6Ew3IIAAd+0F4DX5WAzlSRiKoDdBbQr64Jdx5xS8e5xRnPktGC6u8VG88grAnoOMQCUsAIMf5OYCPr1pAfyxX+lbzzxM9Xe03b0li9GEOZEteThfG7x+uMYnnADSrn6CO9F+VgL8PV8yWmcqq3zl+5v1qw/8rWPDXD39b//MbqPR2dwr9a3CjCR7nh7b3gABk+gwAbTnnAf6w/uUilYzEWJ2GaouRbo5stbecjkeQVyUTUQf62vF2OuBwOuFwOuB4OuJ4OmHta/qNJlps76L5Q1Y4yRZyQ2Yp3cWP7Zzz0/z5V3Hy+8ffw5tL+meV70On2F73P4uu/xzl+MeB/t9wbHjU9LtsLyo9NkKIBLTvDDFOXTWffbOeCMRYpWPPC14g+DiAT79/wrenZ808b9aLkxmNMutTOlspUnWgDwJYtPwFjcKMLJMqFIqS/XnpcNnHN/WtehMigsqP9UvH7j93kQ1woj9Bf/yOjhVCj7j6/V8ANBJ6kXvc4QFPpAwN+Hc6pp3FnxPs6Zo4XbRcAB9HCmD1INKouLPHSZ6vcq3U38tt7uz47vCBzNAmmvFqHm7eVjmLCUEDhBMGrrjhBDMIMuEWDW9M+MiMhRlChEYAW6nKT6Illrqoou+MlqE9O8ANp3UFATg9aCT107dnHCjN6XcgNLpDkzszdD1OQ3d8HEAY1oHUGbWEZkZyupPcn7EAYOtvPoCp1LiDpiENvVvw4ex6PdND9dT2BF4Z6SLgwxEyu+IAgK/duSIQ6SAvVYcGpjlK2gXntgBYNfBFy2H5/hPt/23jElP+HR7NnqCfaar45OWjKuy26ts5FOaZiinFYagmhDLChvjeD803gjperCiQR9ESZyaE0cPGDCFgXbWPuWeADNHS2SzuEPPI3g6I9felzLJ1Z5KXGfZMhjAk2VoeV/3sQUpV3DoDQKyMGhRC3pug89eOv+RIr6Tj0mLi/DxZvdBlc4KIsz8XEeQYmqjCzI2FNs620/sDx0OhMYNe8xJzSfDC0TztGbtvr19c+fbP4qVxzeLerLLBSdbZEGMHw6sc6GjWsdr8dOOGo7dkGXppVAGAfQPW4rwJCr1AsBodRThvGQsGVliBcaMXgm0u+Tl2XCbc8evm9Fa58u8hZJtx1HuhuoEjjLwEnI4HXF1fn49rI6DXjJ73VQ7/3Yobh5FHjWuDCKTpOGYE0v3IhW44yRtjqI3A6FjvDcvCVoJ94LSe0LhBrjX7cEEDL0v0R7cub9Gr28tvMjHa0qK9DZfMcpD16AODF3PIN9YygvaX41qDD1PCqzEQDnPYxlJnJisBVgPzDpq5s65Wfjih6tm3ww27AKgRWLR1T1T08TWGO9kJSwOkcfZntJL2Xnpd7YVVZZQIeqDhcgRZJrH3Vbdy1VtSVV0AACAASURBVMOU5K4OdJGuBlT4u+TMyextF0K+kYqlFWeS7tD2F+f7Gxnp/MsPDrJHJAnLx7ixzfe2fdavm4AXQrWJwlYg5ifW47cZ/xk8LBjH8IJgAW/mkLXnTs5EgspU+nqjs7oxxNq4cIIMACyzR8cWDjQ39tv4vZdu3qp70x0n3hM3w5zsmebAJMtcHyA13VnCILMAg9GpR1l3MUatPiVzLBNPdMVlg+F03cHsGb02Us1mtFGZbrHNCE7qLjit2TNd4a0tEdzQ4u0NNOgEoIJxgqxqEe0ZAKwNEUhCUF6vcgShsdSkSXhQge79urvLxMvaTYdsgvu2x2brjKOAr8RvnRnCfCncgbGV54gEuCLgcAXAspDoOA0zjN/TM49QR/ve5K6jjcPxTq8bQde3cvauZJv74h/je39+AaTFvhlWhn93c4suAEEdWGMIxnFAqIPpDYRr3UMvA8KGsWRBUtculBgDlAEcLbjU9pjaE08AEaSvqAsmDmebsZg3iuB05Oi7WoPKAvj253U22b1+PYJvUl4RAAsTjg8Dyx3gjtD+LIhqCJbRuN/vcPh60kz0iwuu948X/bLc6f3HB+vRfauVVMbzKDd5VvYh97EddecKaSBDPSEe0BvPMIzx4AQon3La504U1VXYzpZnIIMFYnyC0BWmEVHKy+kwcXBZFRCjP1Mmb5FfnYKM+p1MfxCE/Oel+n1umtmZo+xjQLpXeiO8HdSluZB7/3LMIOBoTKDbXK/JHeVBUCbnInlv9OLsEyZQz/EBpWKvUU8qTv4MvkjZeObCAaEAZnKO+W/yZ3OjFTwAIUq7On1qUcYZiPBKcb7qFX1UbgfNwQAwe5XzAOU/dTFdjsm6c+9JG/HJA9PKGQ8luoYFe1olmTYYnU0nCeFEok87iEFWAUC82pajCpR/D9JM2W4lLkhUVq5BvO4uFDOuERHQBw7ItVvKCom9X204CDrvtLvKrGwftSz8OdOYAqWRMmlihZb+Hb2k31gGusua03oA0/yyhLvNNeRcdyQ7nXP0b7rP2NZzqG3R2xn5+EWBicWWZQChvzocDek0i7ESZt9qMWCHq1+gn68AjPEBuJaopMUm84mvg0UOEHvoxw2iog103wq/KA75XEnCTuG46I7uCEhAOsi3Oljsp0IDayWh+H0Ms9npM54IuP72Jw5E2oucgBX6zp109D865E5w+vNPvPUB9BuseARwj+v/uMKHf/0n/t8//j8QEe6lVAKD9lvXChmGcFaabRV97+OfXzBkoJNbpnRNX1hxlKG2uRuzMe6aVhx8IVi1q4E3YSyjKz6i49paC5BVgZrlLsIHAV7Jql1S0vQbC7J7tX/18K2zbauUazXLoK5fewBWEQcBqLP8qgoGxFrTzvBFesfuw6Kth24Y8nbCCsrWS67XY1WOGRXmtA4eWY/zqTJKN/63CZICUAKr9rDO5gCA5vgNjwWaZ3oFd4wnP36DlBBCPWpJ/BsQXiDx9wFPuANwC1LbeeGPoePKFtvzeKLYnfgolerrGB8I+NT1mggydn3PpuMQ+Wyv/hbkx3kkBcScV/lxLzirlDsnhSDRwl9aIhB+Ey3bvvxrQf9joNMA8C1snD6Ps3Zg8wsv/2zvLFMFfPwiGKx8p4tY25CT6WodDYtV6kh8U0sthbz0DAGGoJ8GVjrhaPRtUMfJcEfGwDoG1rHitK449RWH9YTTqlnp6QMplNzpujEwgi+yvs+r4A3RQGYPEFW5Bqi4vYXa99zlUv69C+p6/fnDYxzfuz9u8wdEq9ZM9ND9OEsq72ae/3P8Hz3+caD/jWMyCEh1BDjx9X1SJFDImdMUdkn9rQ8BtRSsXNiNzUTAwoyd3GH9OoCd9YzhhrYwGFZKtBibYEbhhgUQQR+qlIjWAr04t1QYLwjZSOFt2t8mNYRxMci3lSyVjxB6wIm+BEs+/PFfYHy2O85Luvx7j18nRtvscoF+ryv+90jce084//1MgP6JJwuKkTuMBMpetwbwRoQ9cVYrsGw3EgE3AY0B5g6yMpzhTDNNWAAcv52w3GtkbMcr3jYquApMT7ih7ElF0F5VzyT4IFkOuU5QyjPqvAXn5Y7HY5kX62eGKhBk4+Z7vZuIII+Gp5PQlEJEGHWS86fh0s/H6HxgpvDe3gIEnJ5f4JHlXi6wXJYCD7lxQUALom8fLQLqqTCGAcBK93ofvnSS65h6+SYwg3qBXUQwn+327wsd5iaK9fPWkC689xI04Xe5yptQgxkc1FCoQRmWu1Yy10KJBIxmZTlcN8gB5qQVdWWN8lathLCdVcI/kvjLfjiDwwYcVSBKCm1n5HvQe+c5F97xU8d7tb7/AlFKB3m2K0georBkIsgCyGmA2rzCAQP72Z3S5FlEtc6tycckAtoXodGFaqct5bnKAznfYeOxT0kcyNWI5EWNODLXYM9RR5UU+Zd0v5nDaiwMWCZz9HYkAkF7iDmNcINqu9phHFdcykQ/KwlWCdovHoGhOZmAU65XzWK2gBafIxFOxxOurq6modSj7lVX4jVrwimiG3grkbaQAadZFqThdML3bDoOzckOAQ0r8QzNKiB00Gjoo2FpA2vrWNpiJdbdsLTT5zFjYYqeXK7TqMNL6S25Y4wYzbLKPVCHTD4iYrSFVZayfutMZBnmbuDWqY5iCNRMOlsDvw5VFlKKKQKLnnZiCTOADaMZiotsZTK1j3MzuNGMKpSZx2qA9shx/dxLf7HhHttcWPuauOhZLmHAs0oBvVsP9N6t3/Um22iLNzTzBafLM+2veBObNsa73RKTAjt9OX//fFdykOnaC0rpLMsWZ2Y1crpDIx6Thloa7kACaHhpW4mKK+4c0Z2TPILKGuh2ElAjULdzwmASNdDbpiIbC4HAzWjKxKaqrjHPVceRRnAyQT/8EQG5pC0qO3UArC0XJPGZaYSRKmVJq5hj+yXWvZC+oOm2TOIfXMwSlADKXLzJPBrimGXZFoPM9kgekvRIxznA0gwBEPtqXTWzwmXk7u0RDO+HDHiwTFH4yrN/7ZAKfFjpYxCWG8bbyymvM1j3wwBdk7XkKs/5iXcFlEizoXHU8u0/NU4Aljs1/1b2ToQU2p/17Q3LtUv1+5RdHWcrIZGskuU0UeXmrjxevG2K7TkWKzNsZaQFoKHONO0gIKDXIlNY3Jga+gTw4kmi4XDMA7QsWI8zPCKY3NeaoPKmWvwnHpx0v8JsPsZzOubNv4P9R47KKWBYOffcO+0mn7SVJ/zMeBFzzktcF9cUup1zsYX4CTmEoPvUnacEj21RmMyZlL6xk7oHvGNMFsbr5bgrHyCkbaVsjun5pPs5dQDEuqScZXAIkBCi/UKQTcl3+Pzss6+117pysMXrbH7SBRF4FUtm46VKXVFk21zDlBMS1n6Fw92DkmMtIAAdEG6NoLUzLXK+4rQjl36SGAPeYbeRGY8dYJQDMDJC5rkfMRcP9J7vJhCN5HVEIGEgqqSQ8jcPNiOfZTquvZJPIOCGt2/3w2QHQ1lvuGPy/N4DgD0EPAAhc3j3XDdyHUhyr1NjUFcH4rDWYn4M0Wd16ipLeKUJAMOc6SCyoN4GXtQWI0Q4Liv2ru8CUb4Wvv42gtSPZxnA1886X2GMwqu2clDdMpM8oScF6rSkuMad586wjWk7rA1nBWI0cn6PeykzgACbtSqyNGnGcSCdABScouA5Cm3zybgzSDJwFQU28T6JIQU8rwAsuEW/G+inHsGvtXpH5V9axNqtIz43+yuMhe5w/+kaRGor84cInky2IOw+/ZbBxhB8+fonfnQIkrbX+QDWQo1m2L6iyGzWOlFE0HvXVk1fOk5DbcSCB2AIBN/w+r/ucfUfV4CVdbaw6XfGpP88+cT14noePg7bj6+kctyd0R62nuiecc6DcGvBUStWdCEMdz5t5EHH7zcloBikjt0rUszpuUoh1/1Igqp0uf6Sqvg7fP8CiAq3wwBwel2xfGj2vdJ5fUHaEZKWf3esDVa1oQ6i8iEY+dyBzIlOyNY3le+eINgBISWaJBf0f2ubvsa2tgnwYp8+gPBEgjuBBTeUcdXN9725xWjPj1sBGj7jhNw3FdYuUmgr0++5V/X4KLNn4pG0NDxB7a2X2s7OR/Koe6P9y+/a6tQrsdZEJj/eM+1dPGj7YYOp/vBgFC5Xi7VFIrD9FhVqqnHa2+7YPumjAytFxYmBFUeBBuuMzBJfR8faB9Z+UrpivEsDnT1YW2UnwHls4p8gxzQsCUOCjuvENmx8+jbRmwmvfoxjE1h1cD+Fm7/41PlMoR/vZp7/c/wfP/5xoP/lY8uE5iztKhvO/Ph8E8h0xgwzJOhDsF+a9fG0bOBB2O+Aw/GI3z58wHp8xCstWGSHezQcmdBcE3HCY29oxNgtCwarExR9AGO1iKfLBevIiKb/3Rodz+Zt8/US2Y9wRiZY1xE9wjxK1JWfbwx8lD/RhJQeF8i4s+97mfBbKJ5/R/kum/PnBHX7K0EZ6IM97r6esNu2I7sTdRTfCfBUh1TfVuSFSuZnod7FfQnlIm2UsxKkgo99cqHdz1AyDxcknjCwgLC3nrACXZdrukXjg5YYZAI31nJYIqDWgW6OCGbwGAANCG4hIjh8WSHyjLcHfckbEWaLd8L3mRDO4lBmifBCAzcmnCy4hUAbBVYs1bF65idN5wXzSu8HQB8J66NgubdsqiegP+a+IyK0j4RRpKQs2+b7OB1i4utUpLKMmDRBw9alP68QHFV5BbSE440bUIqISas6Y4Qg69DybuG0syz/RXsbCwBu2pta1lW1Y3PCNCM6IoRu605Uet3F/DD1mIvKc5im9cNDHUwUOO74GA4Ew0mnD55J4j0utZe2aLZCgWu3Hu9EDM3Uz7mo8UUdOSTNfneW5ilyTjsaLIE/YW1/pXzX8qwjf3mH3sRdJfDIFUAyQ8avijt/STxyGdNLS3L5fUvELrwk6I0ZGDIa3LDYHIHqwLN3iED2pMizU/oyTNGtxhqn7fOLRYOlIVn+AFK0hKq0pXbozquFd+UywrpqL7nWNKNNS+rZOhSFeh2aoc7s2R0jcCnGJUkvhgE0ynvvGHLyKFEb054wTs5nfTor1kMqnwsIHbrvHDe2Tqp3VuTszPZ87tHkyw577/Xl5QIDhmbM2u2uDIS2b/3pBV+GO19FwNwuqpitXeDJRREO0yxR7jOBKWdm4OgjjOpgNVyPrmXgAYB5aBa0NLSxQLr2iYRoZYr16gpXVjGiNQa3PVpbNGO88EFfE25kwRxljMxatt2c5tr3vKnz3DNSibLXnNExL6Sn+82c7Ia3lLOP74Dyu0UWeLbmEFFYR3aWFF5dyoRewAnl9+Qv0MABQe6DsIIqho7BxqsllGc3aElZm2FZtqq4Ki2NqHQPgPGxAmkgFHgd0qmySZVt3z/owufLN0zS0SU6997VF0q6O92GFCXV9nQqrQ7jVOzT+RuzC8cyDcIg7WmspNV7wKYs142fAVSqERi8rK4xkRoNhYbRXpev9T62gBHFYR03Cj/3v1lxpcBNSJ8rErx7cpyUa9liPYhbtsQx+q77olkJ+wEaxWA+rVEGElkvHJusjkwg6jAARWWgLKV8vsBBd2LJCISOQYL9siuCsr4194nAdRrPIOtDa3YfV6DJwB57zVQbtoDWFsFlAwBYR8fOMtyVBzWIrBBvaxIwz/F/X77f0OEqQ1QUjruKA/sCu6iy64Rc9bB1cersPdCLzXQaLxGh7XcYhyNoDzAz1re3GIc74IO1w4IYD7UkvNOjEJrLpP18y31NsMBVWC/vgaU1De45vJkOQuYof9W90L29xlUY4whsGeNi/aLttQTg5NqEjq334wS0SrcUL10mlYAhKOVbgthefbF7PiQ6lrl++Kye/Ocvr2jMWNcBeVIZfrkT9EfLoL9Tur5brIJcX7HcM06PI16/PcZLuqLH8wDfMvhGV6U/99kgZ4givnCb5xEwIaOyJgI7fWHnGwYv37bhWa5OZT2vQcG2T+IGpPwGl6Nd3yr0xDN2PLG70FXXHc7N+XVJQ+Oc9kRqbyl7CqSUwudS5aNQJre3zLVvQWHJ2PxusG/2mYi0TDKUJonhvFZ+cyfctGuQGb0EwT7OpRMd8cyODpCgyyGCRR1aw8tIY14n2kBQ14qDT6repXMnIIJOYaXJqSANN4pWC4DLotAAEWQ7BgLNZesne5M55AcF70w6qnSdrBJbyMMxT4dZqeTg99kVcVUhTwcS7InAFgwXVXtg1aUKP9D9wEADhAU8KErhsr9hmAOMBoRUHhsWpCkiIG44sOCa1GFIRDg2wl4aemnD03sH+gp3ljqOuoyRsynyChGIFWmpOONnxPTFLt/FMrZNx9Pg6hE4AcOD7D9v/NXB6LK/GTDE95YLMpRtwgq22fMNtCUDV4MvKPF/GO6EHIYzOwcAazGwsXOWeYrhin7WZw0RXIGw0C2W2wZ0guYEl8ERY/SB0/ODzffOWmXkHiAhC755xkIfbS2K3EwEwVPyWaMtWqVHs0U/f/oNf3z9MwN/6jSKLJ6/5TmnwV7xx9/p6sxqur90AWTg0L9CRsc6BN8wcN8lApGVRj1gPX0OeiEiWoWNckcCWd2wG2yfNuOMNldGL+5FeYoItGIGaxb0M1mRL4Ort7F4ZaCLVsMcUL0xFhRBlkNn/2Bj/WD8odq7rqFZ1FTuPwNmwbHpPRsv8byNKN5PohLS4sHoJqMd+8COAG4NAx2no4Cb4itBTfUCC6iJYRBoqD2EdgRggZiBSzxhyHRKapdLvnvSgliFR9uocG3/aNdbNzUQ1Inuz9nDyujbpIfLBnb+qlQBFWgWej1uhuDRWa0zMDmH9/cUR7/FJYgHUlt9A/AHmfN8sz4fJVYOK5KPfDY4eyzYF+Pnn+36zwWCIVvbt3uYnd+ed1fe94SZn7qJZP3yZcIpf6Zs/r17XLS91NNSrivSg1jYi2Ql026XeByUJ7qIJD2KcHyxqp4DkE7ASSG4qisAo3ftU27VVEU02/20rqpTOW9n14s3MHWYeCKVz8XnIRnoMsPqXBB+LzRCNme+C+f5xnfQ8oIQ/u7z6eybV5KJ70ie9u7xg9P/HP+9xz8O9L96FOG9GhGzLBKQ7LPgOVWi6ATBhDV4dqZFwpFg1xh9VfP7OjoYhIUbFmY8H064ghOZgWcSfBTGEbDyP8NKiun9rTXAynxq/cIV6IDICmIxw2hSh+qwdqehf465DJk3eWGGnq37TIRP8gDCv7CuK5haRNY9sTqYiTSC67fxEUwPCjPScpEUY7ns5P97xznZvERIt1FgP0NsPUP931F+XpWTlt/LuVnHpPjrwvm27BxEQOMS6xBbL8EVnrFgAeMOzK8hgAkGdqNhZcbKbBHSgOAeAhewtSTdC2WU2aXDmURIuZvjJYwRT7g3haauA5ljfSManDFFEdFSoOYYXx8H2NQZ7Y/I6tSyvUh32RudoEKuK/j+PN8bzuSqkE7Icu1iY17loLDyewGMlwG6zWfFM02olmahI9LKE3OLSpfIzqIGVdg6qyGb1HnuPQJR3gFoqa4FHuiSwDtTwgpct0fM22ctHrGoYzEXmcLfxzwZSRGZ7+HEEc141HLJJZ3dCEtELwvMEOTUdcQYprG4oc3xIi2Y9n9BDjrPR9mkdwT3cDIUwc8/eaDLTwtk5dpLivAPb6zM5UfHDwemNMPpR1W2/bRAjX2DJEqfUhCZpD/1hfp/Ke+udMl+YcCt5mmwRzGk0TRXd4DYNxs65WWuzBOZAlAdmllyzpBp2r/+PjcyiADYE+ToBgSCnADCAphK6dNzPPd93kRUSSOP1p/p3d+JLKWzTwItJQkbe4GPzYdKz/K9lXD3LCPiKs/4EylgGIfhnYgZQVzLgvKqDHBxBJV8FvK6PrLErgi0JQOpSisBTNc2CbSYCsfAaR04raqY1awnn/dCOyxLm/qZe8Y5E2H0bkZHKA/guXzz4tno9pdd2aPEdbPnOHQDbs7XFKZOIcseKvRliJZU8/JkWTbT1mnzTl/Lad9P+0INJ72Lrb8ZUxoAGpE9ZIOM9b90VMdEXfy0b9jaiBpWzXc+OdEFVOiEBob+/FH3xoxL0xWXRYjLz6sOu6Kw+r96VJ5ZR+N4pjhOKSubYj9oWJAGT7zNBAh9ApM6kqpGDsT43GlCgDkakHhh+5gdn71kNM/rqa802CcGmtzgxi6Dqf+hPD/DWA3n8W4hAAs6dSxDA/Ug6lhA3G/81Olp7JH00mXwAttWt76iJjRcoo6x1C6Dxa9ka6Cf2SuL+HusnCq8iKtYNp/JGTLUsbiuHdwELuCMMXBcT+o0EQ86KXva58UEGu5c87f+Cr6/f1zf7gxOOxzXFevhGO/dwkbHqK0bmDno63z4WhhuXDlcrzDeBIOOZU3sjpDBADkCfA0s19fob0U+LX9Jyo2YeUvKvHbJ9V4d2zikfOUP9fYWrwBdC7qVcNcqMVoFgOUKgqPKXyTWmsLWIqo3sCL3Js4y1ylpw5YtU8HX2fkroZgkiFPu1pvfDCeuAURTAvTe0UzOXx892mbGGqcbZHiYsk2B0Xu6sckgAqA/z2Uig7Y57vv1P0DXoEmF75BvsgqEgKu903UCl7WcTxQIV6CrQ9H5C0IfcEOjnrGgYZTgnDKIwC/n1wUfSaSsKXLNffy0/b3SSZfvZgoQ5L183yKS80wiRNsNKue+B/6Ug90piWz5kQJb4IgYZEjc8WkwMN61bljPlr2GU1Kq87zwFyr8S8xhAwt+LD1YVAccAXtvfeCB1ym+UDrlU0ixPazuOGFoT/IZMjFnhPzucgrlvAoDrPvGOS5EW9MEfghwJEBIK19cd4XhkYFlED64bkIe4GC6xoCWswVhNzyQPOlhyHQ2uSGALMDJaNQrwWgMoYkWbKdwUOtt3ctUW5U3OD8nmujBNggh9wbmg8qfggcTnGwzjT7vU0bq7j4nKu8e1sCdBmFwoY0E1YiMTyXObgZRVpmINRDA5+GCEQAho61lrSdyVJ9ovN2DeUM+KftbM2gJu9sl3jueBlY84vr+k8l1A8cnzSCt9GzOQlaaxbD2C4TQV65/0yCvLksM6/jnIelEkCzG759+x5dvX1KEvUQtRG0/sV6GMxHMwdqqKnQLG+voQ/G/D8jo2h5FBj6EXOvBGvre9ZsG5bis4/JURStfJYKWX/cvnq3semrCK3nKGwO38MqAc//3F2hrBW9Z5XL3pcPf4cFuZBIgBNYOQKHo5cavQEUCyXlc2i4/luxo5invHO4Y1/fM9PCHes0lAbme/hn7Au0K2bBKR7aHhRB9s/2Fe3stkWC5vYFD77rd4eWbGk9vPn/E4YuWJK+BCv4PUBHg1sSnv2snd5HiN7nHwCO2ElF1YPuR1a30/oaPNq5vEGiZdcYcUxixgQCATxB8U15Wnnsn5/gxvVn8GZ/Q8TDtk+2cHv4mXH71qAFPLidCcDFIU4YG5xFpm1TqiN7qo3cMS4rw+YlY0JmXQql7Ew6TWecLfctKtqe8XkJe5fIA63pXG0cNvp721y/Beiss/fVbgY1M4N8v/F4u+PX3/nP8W49/HOh/8XgPZ2uWSb3YyYOJ9Zu7tqqfXuFlLwTA2lfrB6zG3HXZgQRgAe7HLcY4QobgtQ0rXUeQvmqkqr2OzRCsvUF7KDUuYEQZE1OENMIznXqp1Lx3CK6E8IWBWzcwWXqrMHD69gVXn/8TA18h2JREF+0pMsx5nk/cQn2OHL40hvPvWzYmZ1dQ+VxPOyPsm/E+bW+cHvDrR7Hl2mP8QUZEZcMA/APl+ZotFU4nF1DZexBLZNMgmM7M4D5k0g32vy8YDx+xEIPoAcQfQb919P96g9ARRzpCuKP3b+gQvH0baFBh2aPBatWuGHb568w6ADFdqPjzSNoPqQFg3DvbDIFHi+vcAJbxkRGT+vxzU+MoxhMJoQjfbkH0pMxZtD8M4D3HvGdnwrsqZa8CZEvCNLCKCN5IcCsZRZ0lI48gqyc5CVBEWBpjRCi1z4RjbRVkdoGVdO3SEXmuNLQfFdXIwTlKmAzExy3+FceBlP+HAXyCpZVANTGTCw2MqpYjcToVa++NLmhNYTOiNJpF3wZaiBkobPW6Z+d76jVs3g1gNahWWuyRfRqRO8KYF3KUOdqHpEKWs54/ATizV+ZudWX81+WaLe35lWf4aM+UJdp88JfYe5ZLQjGg7RoMfIyd9g89GLz2qfwagYlrw7kHp9bdDKEZRjNq1oYhvYBAA4EHnqUWwrsZTNbe7Q0qgC+WaahBYeLDiXE53jSrTLDsZpFnXVdUT/7aTxARLEuz3WZDNAPwZtgAAN7vMN6OZa0WENZQ2AXAziDjmeh+90zlt6uA716n4/JfDeamxXnpx8gItmu5WWZ1ZLjSrFha+dHRR+CSZ4JHdK+E9leEfF0ztgzoNAUgNNSYA+k6H09H3YtmSGcmC56xQqkCABxl8ydNF24QGuDTEW9SpCrLcvGezLRbQOTZ5ZpVDiJ0XkHhwLdS7o1ApG1wppLuzTPB3akNzUYnl0iq4jOvZAYv2DkiDY4ipX8L1Kk8umV9ywi65D3imdnKnRngYwmcL2wocjXUQu8fopUEANESnj9xxPrGf44H/s40Vmvo1jhzojtlVv6ZZcN//djO9QKx/OFjZf7jcmp1FOCynOuG1uCdtpZM5qAkv0Yi83xQZmWNoX2TZVi7ErECkkXmIUJpEyPqYAEBI8fEBgJ3PiiOcKF9MNlOEtLkvFgR1p0Zvha+ZYOmwWR/7+kcK68v50YAGrgNUNcMGQydG0iiMou3RG324JMP0kvGWyUJgWi/WTPQu3zn8okXTyZzfirdjkXUPWV8jUSf05BBWtrP0c28Q7P7zCjbTyvasoCgvTYbNy0VbmkzAzK/b8Img7HxtGYVg04yLhqcfv3IXZ4LRNgvC9bDEYIThuxtAfKePjrkeIQwQ7CH7CVoSd0j5sYCqMOzBkFA+0AgPZml5QAAIABJREFUucI4nbQnInXj5wJ4tSMIToeaqb3lTykLAUYnDyZPf7BrwokLyAGF7tl2tj2d9OIN8gbQzQeABPzhA4gJ4+1NZXMLqhQZxv8MZ5nNWGoy5ckh6n3XPUeqclOfx/y3ztR1lyrbhpehPMT1Oxmv09MOD69Y7u7Ad4z+1EEQ8K2gPwvWJ2C5M9hYUEkfqhf4s3d3guNTQnkrJ4TMZSHrtF0h12OmyV1BcChPzMkQIYLOnFZ6wC+wAHKMyepvO5jyqvdH/XCAmsvjOg6XSXTcAnhgns+FFJ/0OusZK/qgqf1JAFzHP83Pf3cRWObVDQdaoaMh/0HXIW6bSs7Xx0iUevcx+hVeBUcytAwgzTJ1RwURsJDSdbZ3O18oKn7IfoqDR0C0egTRHiK2fpYBBtrpehMgFsBQxDjsiXCUwt3sz4is5yrnFbmTCpq7Xupzs/WMoGhqdr064wlZQcVppesV4pUMDNjeDgguZVg5Zwybn/FdJi/nbdq/yYzRCnFIjm0gAlkSJ1I+EGiQMAWchjq2yRzBY+DN5DI0CvlMhLGjgWMXgAUHw7W98RLyoDlmHNoAC+FGCG9d0EgrZIFb2OXIeTc46JQQTF5OXK66cizU5hDfztuDNp/F1z/3rsvTIgB4BG47f91spfJOccIBsXiXDtGgwNHATWHpeqL2F9cHOTWIZSFB3QTN9k+Dk92ynnV8KPOJMVUQ+f4X0CDc0g1EtCN2w51W2LGe3u0jY0ef8frtT1x9/FTgRmDcwAMc60Cs45W2+PrYsLTF1jZ1swUNvaszav/bHqevJxAI3ZzEy0fF5ynIpui82+CbDNjU+Un0BW+xV93t9wLNxr4ZHnhn0roIGtSxKPJnQGp0AZPgtg1L2lCcwLJgMKwMtP7lpo1VBMhAPoJWSg16o+N5Id2rt8Ra1tsCqJbuOpHi45As4zzcnllWERs8gMHnTUSDXgrfcieqZ6BP97kcTTnO6bF1z5Xfd3biKHVMwI7n55xkgE2eJp8ezI63AmQVjobJMR4Q7+0bqG3wzA06LnjbMSLD3OjhXisGjeMBAMV3OQpgRdqJyCpZ2sAIkTEfusgHxhhvGC86no5HXN3f6NxPj1jL6Cpu+n58MXh8lDvc4EnrjFZaBOB7fdDjmvK349Fc0uWYZEjgMd6r6z+gVTtXPFjSnlJ8hrXYQKYwzZXVvoV0VIf9GC0B9dd7kan8u9gzOr7Bue4A8I2A3wX4k3Rsv3r8DHk//7VAhpJ2fQThTYAHo1tOX8X5qun9AuUNQxVL0BD08D1pwOowEj6kVqfSMYg9RWSgUVbw06HJPMaJgbnz3Lj4sADZM2l4A6MLfPG94zLc0omfF06C0a8/vNgfAGSlw782wH+O/6HjHwc6cK51/vBwJjgTyfON+d5GNg3hnfdNP4tgvzBOpwGGmOGKsFsYfVWhaIwnvI6G/xiCo2h5IwFhXVf0Pky4aWBqoIUxOqGLQJgwiNGJ0oGIZAbTdyLLWi+j28ydyLJQ/CaxD8agvNwb4SOABwClt7hoBjpdYBz2BlOgHZ6p1F2G8fZQN6lsgL5l7JdoqzPOW5md6C7wxB/6PgrpiKV8djxyBuLw3M7NWEUZXKAsYbrW7ethrIcJ6WZkVWW+lNosd98MwpUYQxqiTisifPiPK1Bj4I/fQPcdx/96gfAThI4A7dHlCU8MdFEhfFDOLmdSAatnrr0ck7jyY1nn7yzliykP1/KIBXcgEFZowMUCgpdLnAU1gYvXHhxNZZ10DW1NAvb3GIaffK9l3vWyNHhMa2P337hxkqqQlYLGM4Z1xkpm218E8uEN3BZAlqL4Dayr9r491259HplxHRhFBnlzZJGtd3qK9Z7mRhkHPOic/39PIDAlxEuvEXLuIQSIQsAjh4HMDHcBRKpARGT9dR1uiD1Rnd3wO8ZIy7z/XjKOIlCkwk+KICiSStRGSK+Uhsr36f1lOWj6oe70Hx9nNOgn7zu7YUsOf5afFaN6payKS3t41m48j8kiyEfcoKe4OHB8QLT5jmIggdFME8uJw9BlYRSuFoJIK2B4q5Hsga7vIPTs0e1rEvsDCIfNRjDV0uRQfiwl6MjXLwzBtq+u2Mq9Jo0bxzmaQmS19y8YsqbyXQzLf0E3mo76DF8rn3vwazuZvyEUYAhhZ0qzGvMcBySeCbISx5ApkVzi0S7H6InWmir6lhl4fti+IOB4OBjasfr+wiltY3eDnIwMmSNCxxp8VumIWJ9vAp9KVoU5UdTgpCXzhJviLjseNKXFRBZcqHgVTnPOrHQCzGGu42Qru+n4G9O7eCQdJdJU4gXQrHMZlukkEB7a19f6LOu+oljDurmC3hZsCLVSxAz9tofstmZOdHGB7H3SjgjS8v/IgmTCmF/e7fTe8WVsnOhhhK3u53/HMREbhcIPNxcFz6skrT5x+5vziAwmyKo6jdyB7e9X4Ay2ALChBn0xC+qwUjYiqC6UfKcUmmfvpBAuBdH/3PDB/2p1ha2MZWRv6Bu4BKAk5NIJNoHT6NSU6SQS5f3UWSAYYKgPXGcyPAMbKgc2KvzWZ+Xygo/f14XSTY/h2UkGCzMOtx1jPXrQIIqfTCDgmJsG4AwQTOal5CYQZIuCAWjPa6cbKZNExqRJzA4Hn4tAq2AsiwYytNjjuYcmo/4vHO6cPEfm/M77HcbxhPV4ALsqH2R8Be0JWsxD0E8C7LgYrmR6mtOZoCGwQMvdDuNU6x/ZmKah0fQ8p0acouUkfyoq1e924ShPca+VOzrKw4MUivV1fTk4cwPBAy0dObxobTo1634LabPi/3T+O4fz8mpg34jMXkYf5Ht9fqL2nuxo3IA7wenxCeN5QDuEJtj84b4fxhjB65YbQn/ZyCCbv3W53Pmbv5eXDFJLsqBsrpkiasntvCfCqrxMsS+QuMyGgghQOWuB8ZVSZpYySGyI4YDTsUA522McEchGe3R1XW4s4sq05g6/wOhYNsfrws8AW2PTKQJSNNki3uVpVe5DyjW0wTOiEmT+zqMc2gxPbLC3U1lZOhrOHEP2dQc/0cl4x7ziHiAqpMG03uIq5F/fc2Wvl5Ar44M66OSDnO8g3+sePOcF6U3uo2Y9v/0lqb8JNADGY/0olohBTfVKoV7RxNaJYpSxfoV+67AcKTc0lmjTfkBCpphrmWVARQ1U9YC302CQDLA0CHWIYHL0Kz9OuvtmsJFhULLy7hWFQmcdI4xSle74h7rn4+YzbJKcfvyhzTXlczie7R0lCHp2Ql8WwOoQMkhd8Xh0tYU2a0Enwmdjq1T7LKNeHxUregYP+xwy6yUjn9FEEQ10AJG1GiO0+wYmk/mHtngSAT58+owhgreHP4tseJkaqB3qCTu01F2NqMUOIrXViQj6wwoQqQwScps2ZPjXp8/445s5s+kSTAp/dXyTlFwk3kVRHctxXuBBEyNUhB0+atvPfg+YvU3ZtbURRIG96xflNxEtwe4jnJ3RVWaynWs6+lupTNHHCN0/AlK3TnQLwrjkIHMqcEMcVSC8LcxRXX8QaLn+2EG/4GgDznePy8g1QD9kQkoRZ1Cp0jmzDEyyleSz5zddZhqRRFU+R+uTqo+W7+7fF3A4JpM2aFIFXxPGm0Kpv16SMAinx2f08XOVWz/I92bxc2vwHuX62UMAfGXzPUhmnDM+QvAwZbOnZp3/2vaBm+OB5jE65g94clbC6gtpb/W/OpfLxxkVzUGkomU2mAbIwANpnGnOU8rTqGzf3Mcubem+d76RGJQwqM+yBBipdCCfBnuWqwmVzovppM5PGOd49D2H+Xe3+GVW9hce9N49mOjCpdN84ffzJKl3hMZ/jv/24x8H+ub4ZVT82U0W1xUFpghQl95P0ExLz+gcMrD2Fbtlhx0vGDiiN8aJGbfWo0Y640bUsHDoHePUIU2NwUvT3p4CM5iNjg6LsDLBI8w2ptGxwLLQfwwhEeCbCXvPRLgrcHkmwkcB1j88UzWvS3ELuLdMG5KPAGl0lsT5/ESbT5V561j03M/QFnrny509/mlz/b2os/9OgGeee6NfOirotnSWyKP5tyzDB6Pz9rK/DMcZZUeZmbtVgaqRUrPvQMqoVCFNePo9LzRUeRCNJusysJ5WEBh3+xvQv4C3o0ZvP7OWWDrQI05aEVON7OGI3AhW5euNsEX5SWDCCi3F6yWbus3wxbmqGTVvBGi4xyM94U4EzwTciPf2TmPGituYY/vIkMcV3cq9V+jWQyMCBxZwCAzHx7yjYtvtp3s8PDzG9/fK1NtGxy6+mnBBs6IloysQ+ao4MOZ10kG7puMatDnYDbF4WTTCu69hdNYFnxEvHv2TR4y1jDv1II6LJse0+Ht8L6ZDUzaOUM8g0Z5flm0jllEgZbC+CNG32Y2Yjibe31cdN+vwLPYNnbA/bAqFd+jMKG3XJEY6ZQrY49gIuht3yE8fVD7QL6zLpbFM37dDMVg04zurSPRhnO/fQR3KKpLKm+NtGSdm4VThb84myxBvrJkvrjV20fLc7LhgzhZqmonipXTJ/u8C5LDSumRNL/uwMt+r0zA34yrlWLtmlmtGu2B/da3zMVQ9Ho6AEHbXOwgE47hCINjvrwAI1q6OzeOqhoyrtkANLALZM3AUaGF2gRo2Fnv/WsC4omEBQBj2+84w5PTe2v0k6kx0jEyxtdt5EfQuQUM8my91pqHXm97EZV19q2U2mFXhMCOhWEZOefs0HiaysuzJrakYEHS8WlK9947dQpp9Dl1bYs8OUFpiXE778a1aqUJLnq9a1YAY6j9nnE5r8Ndu5dDdIdnaAm5uYNHBMBOEFoMfRx90L9fuTjWlx2wlJpXHcGMsSzPSmw41l9NSXcyFTSObAE0zjbg60JuAx8BAz9LCUiSCrbGUoPf5NZK0N++TcLKKeFJ4kRLckRJOTZsradsT0IjsLxHvbX2uwMXeFwTfCSc6JSn6y7Ttu0fC2fH8PX1WXAb3wcR1xqymsuUywZxg5fwMuSnWWAMHUlqL3WDlSt2Im6XDPeuBAQzi4IcCLU+bzohkPgTWeLHAyQxuIL/WAE0kaiAcEoZCf4GEPGZ/y56Oy0YWXRRItHfK9RWgMbgPDGI0VnyRIWA2p6UI0DRo4NS7ZQgbnrE5Ubz8sDkqNLvPs9oAbkrDxxhZ/WdHaKPpPt7UF9fltQCexrE3XUbwD97Ls5OYFqzr2IslmS1geIjS13PPl623mPHL4NI9K4wJ3kew3lbhrD82QM67tmqlotzLhmk6ztFVn7u9wfHlhA5zIjtWEgA00I7BLBA5YT3twIvjTezICWMRv9gVBMgCYC1XVdyZNpqovGTfvAIUBFgLJgPA+nZAu7oKwe34doinECxTDxJ7dMse15dnhBOOvSrTAYIrax1A0HLuWgqXpEECzprJOa2FE/ColjLTuFpNoE55c1vCsjw8ny/Tff53aQv66EjHn+aaCoD12Xc+QPdKh4+rSg/SgfEiIWvNUNoKqjm6cxGj3muTNXriJDLXPnmYf1Ksv4JggGlfnBhOJ80pKgLZuexnFW68lLY9i3kPYmjgjb9JBKPr/vAS4VlhpbpvPDhwADSMZyXOiiMj0qkWCOrDFac9Y6J1VPgwkbWkmrd2wHEDTZWxNgjM5aRW/0PKTKTBOJW2R/n1HMXkHMndvLfVMXogexAJVnmFwAKnmbGOSm9ycETzT8Qccp/+Hm9P3LcxkFWlULlEccgDKTWIidCE1EAPSnmLW3mnMVp3acX77P9cLmHVESkpTcBHYRoAzTPhuxSdk5f/lgoDiaDRCBi0pBRyGJguMIYmdoRWbIuowYbqPK9JJu5UOJFAeEHbZKR6VUhYlVvfZcNKa3f7O872d0ofgAXayUzXHcYTbrq84H/9ms11YvSr+GUDtJecZHU0CnYpgTVAH6LtonoPuRqifeOFhslTjuP23mgNRRbEk7jwnpNky55IHKcdggWLRct3NwArnnGA9mxmb98EtfMs1HAyfs2G00McKWkCQAahmvwod5rJ7wo4kLYeIrRFgwfavxgv//tN52kyy/Hr0db0IRgOs+/Zc6ruug+g/Y0F5qwNRdHswSbAyNB39XL/h99/w64teFtPkLVhJ7+BQXj9+jWmCQg66bN3QyDs2eKMbnrkjWiFxhq45baFund8Pgdb49wXPdoDBF23vSKCTLzY0FmCluFf4DKBJXpB0EWbxVwZtxUAr2ShVZJ0RHXfDaUv+7VCf0+EE5QudQJ2xOhwpz1hhOyu9zX2ihlO73WhxFpm+vzY2jn4jma7z4M9XY4+3/A23uGunlnO9MzzuM57oh/1QYtoNrpzPzLneZcNxpm8sNwCvb+ETNwNTm4X3t3f4fD4BAbwDNGEIqM/+4+/gR6/2rw3EyHCZ/mkaPuJ8fb1SySz3QtAuMfu04LXb1/wHTCcrdu3mITRWSgeL/AqppphXszzebX9byDp4Uf7+0i5vy9QYezxCas9u33+jNOff4KgjnN/NgH4uhUmfnQ43CbHR6SoGK1WXub+HkNI+8dWNdhtMWXeNjAy+ZKVmKp86vcjcdvnrtUsjX+aDul02/cFRCxBk81GV57hfGeDEzN/Smr0U2DCT4D10gVOV4LO/OQ7N3QpPm9+rwk+Pz+bf47/U8f/3Q70DbHy4yyRY7s3q2C6+aBCZVLbyB5xAdIeSlYYZFJejBCRfWMTlltbsDeGqaZ6VciakTIWoI0P6P2EwcBKC3YA7sB43ln5z6WBidGIIaRRs4MYC5nj0A2xBotU2JDcwYhYNRzmrHWO6Q7XT3dCeDJR1fJR4WaCs8WAOqY1+uqrOrBDUN8YJiYxnS48qVxDl85thPzNU25lpm/+Fg8KqJnz3+yCaqcMDNjgjcrXEhBgkoiejb5A8GfVEZqhok6HyouMKxG0DykTtJcrkWXRmUBGA4PcfOQOClcMEaV/xMptgQj9W8e40XJO64M6otmCMlprGF2s/6UJC4Ynabp0ocWH7f1BNWNd1V81mIlpOS4Y3oiWdXI4CAgrngAInkzrU0P0vJJi1wgE8ngLddnfomuRoIsHmWI8JI21ftQsSJ2L4BYULnmK9c1gk4prbh68tvVvyBJSAfpXAd8cwbLL9b14+KaYcT8N4y4y2aWk6+kZEDv7mxN3vKNz+WurOECKkysNVuEIH5hwVBxnfXk4TsQcq+Avlt08xNfbSv56ikbZlNPIxCL8/byVgicZQBeQKSRSXwyUNcin5Suk7C9896jrSNN7sF0meFByPV+/b33ZWxn6gtyVfKfC+CfGOz2MCcDOeJCVUnJHg0cOXBPQZaNQCEQsg9ceGqWmJ+iaKZiN1ll2WJYCTQMebQwoyqe9jDbi+RRZ7/YuJ/ledQOeKeLv97WhDaAp9wGVcUbZCi0Z6SWZzS0LdaKvcAoU5dsDPCtahM9clsmzCgQyI2DiPA6Tuk8dJrpGjJFKUE/nuDtLUsExrjJOOL2tuP5wq8ELMBw0r54MpPOJkluTlD1h4/Vycs6lKk9xeSZgLCoDSPRyzQy9WEVHmwGoQ8aspqIBYGwUFCAdK6CBM9ZT/XQy+FsWuvrRWZ3qMrBbBrDbGQ8jgLSculZkr9UWzHg/CMxmLJ1qC0+bQNfFghkqTUuZyEBAsWzwoCIGh4OPQJq8N5yGq1NPfYWpgELgtlw4rwuaJYKw8kPgGemKa7Pxtej64bgVUsNGYwKGtg5S66MAzZzyIrqHg+/rGjUpTmOrZa7ZYoqnbM/UJZJ0WljFkIxcRxg6BOXcxWOzFnVrz6yufMmACACYen5v6L2TSQp4u/xNWqmAkg7pOB0nExYq64j1bQZItMQdYUSQqsTY1Ynme4NYndRaRhQWgOfBHmQZcEbfzCEeQaQBgnS/VL4+vBiWFIlT8p643hQEKdWziAk8zDhDgLBgjFLS3rKCtYR6On/gmZRQmjJgwZfkRgQB9xaBGZ69N4yOefZTiimefWzGUCJoCdJYXXWYWJURsnsqPvmnMToi0srP2Z4YBnux/Wg2J3uvl3qcM9ZJvCpTQa7yXpKedPbM8bGRIwwn2GiT9I7ddcO67rTMvM9dBHxaQfud8lU08DLQT77WQNuZ805UzlLSTtavPriu2bbO8eZskzld8iUGwNdXFnx3gIQh2S63z4eN8xxQeeNtrGj2i7u73dHDkl8k6BkbjgiAY4xPMUGd5yQ9x+CAqG8Wl21MKCMUTEs6r1c4rTk/lwCwgIxNNSQqr137GvBc7u+wPj4B0mK/uBwkzwDfKu6NFyVEGbxaHuiIWaAqdg2ZI9B10e3SRVYsCCGoJigM3j4/t2/s4z1+DepcQeArC6pxcJDRLHce2d5lqyhFZRyCbpmWFEZd1zMACvqRjo5m1FOzJJUHKX5oD/mUV9IP6bRhTLzb13hM4HL+VGEs5a+v2gyDXA37TvnLQgSx1jUATe05yOdGLnaYfAoPOO4gCxguqxdDFGcqTrMtYLAbP/DqPxHe5bgjmGwSOcsQXtJByJxB4ZVUpEAPD/EUl1eGPcv3j60RUwlvIbY2amUEdn3DgLRmbc5GyFeAbwECeuKuz8T3AnqlssUixQQMx7lp0ez5bNtM+RrJgAwCSCvOTLcV5yiBcECWolbZ1He5yY0WsJDt43SuY6hs23tHH+m8Dawzeqot0DI4CHCHiDsYRWVv41kRBvGOI8CDRFy2ias2Ytj01dan2hJCtim/bQ/l8xpAODhCuBKXJSlL90CeQIt5LwYfDX6V52WU+hmRSS+4NllqoVsN7rCKhuvDCvrUlO6OHgGUkRUpJl8LNGCCW8hSEFjQCIHpHkyayNRCySljE9U9xYD+4T+uISI4/PGG5fMehz/fMLoA9BHkrS4J8ACqsE0FfULocAKxqlmaTOPtpyJzP9nytNXGEJyo4/hfJ/BvOg+XVUBP8W6/VzyfA05TCGIeUpe7nPaFA51yLV1nrWupy1TWFDLBvuJ2gNM+XhtquzRXs4f9UoI6TY82NgIgQXd8rluErTw/ud1KhEUEaxBC0zHhNqzKITebyIEA00mCjkrIZvX922+T1Fhs9lV/vxQ+9/3jGJ8IgLzl53xX/nZ61LdAPFQ4j9393XTvB5uD1yv53sg+i7bq5I8Kn+vffkf7qoGEyyfN4X6zqgzPZf1/ebp2DDK4W0CFi3Guszs6bAu5eSn4+b1U6JT2Vfe+6QLg5csXLJRVGYVKVQcDrift/ehIvVvyvcazSFxvzz2Q/8j0GoTpACDcgXAC4xHZiiwkGLfRaV0cpdtO9wkaoOOvF5U73PNFQhYoLSAMa5elunSjBvHasZIZ5sOSo4bLQRXIJk+GTB5zvLDH/tYxS0K/dpwhxo/vELlYzr1WmKy06dIuigpZVdd9147yz/Erx/+1DvRL7PDidSmvTxf9LAKG88iEBv2oEcYiKpA522ZmLOydhAnoA2N0nNaO328/4OVwws3VNWgAh7c37JamCiEBMp6wrg17Ad52wFVbcH11hfvWIER4ySre2s9HBHJa0UV77CxeZtkE/YgWJWg2GwQdlk0muYEdNCGA2d9PYg5/SaFBAAx0sLoPUR2sYfwF4SsRPrkRyWB2PwQPLPhkgvJDRClVbom0Czh9maWM6ai9OPLt+rdGt0m5pl4bKEHpUPfvFV30XDHMIB3hWfLejaXm1BaFCtVwrTIHt9+7IBZmUrKyokvDsizW95W1B7BllK8y0MUcVgDCLWUKx/D+OQScvn0DLw3H9QpEhNN4xCsTGhYsi0VEA2hDcVW64FpUsXwxJl7cXuYEUMbuDk8XGd1BoI60DULZuRezwHwQjRYlAG8EfBBXuOYVHQQ0PIFwF1ni3penriltfrj6+BH9oaPT8+SP9OsfHx5DIdBn5roh1k8Npy6gABpZKwLc2HXtxh0IDLqC9hL6cIQaGwGiLM0JABF2HXvGDTW1yCb5VlahKOJ0wu0Uj3QBcFKcAEyZXeXJgISCr5dRCm0QNC/BPYYlT+kG8hK25IoQYNmkXo61CkMWX26Ck0Ai4XyVzJYbQyJiG5jkg+zxSgS0NLLGHh4rGrRHFaYzfn4k3d9A4EfH1nlOPrbyPBFEFjiTjSOkzTSWxfaf1gaTQK7zLIOrxCfkrCJwxVhEI7PLNdqrvNRTuFbBfrxqxjd1imzB3LkMNXG36Nml78hSfK6EMpl3lswJKuqEGyM5gKLMKOPW8uBhJCmyoCsZu712ajudDqaoqsJw6vqu/vYGArAsauzlZZlKyfNuZ++1BetHQIBlt4Nn1aVDSiB7hhwA7b95QgW/ilXpRB+F4qy5ZMk7kXvCnXhkjh4vLRslOakaNB0QyUsZDAGjkfVLI4Qx1g+SEQoa87A9a4YRNqcx5Z52g0w1iEqla+KomwpxfJY0kPjEexiXRrFDE4gF6lDMOGmd+4CIORTFKZ/RPPFI/P+fvTdvjiNJ9sR+7pFVAA+Q3W9mJTPJdr//59LKds2k1908AAKoynDXH35mVgFk98y8XtPrpIF15RHh4eH3UYbZuQpUJ3Q+4byecDqteD6fcHu6xZs3b3BzvMHxuOL29g2ON0dznpMphPASnFAfJ/k4xMbHAsDLc09Zu615R0O1IwS6cxII+kTtPNvU1lIgHOdxDW/ph8LpqJhjJnhfZru6wcUzgqOv+tQJmWr9naFlsELRIZs6pTHXepfafjKvlfcjhXrJRAusi/KJbbo5T50CGgqdgknAgPWfjqxmES0+4BdXyTbnMwXh7xwF5aS7+VPDxTzbd1J3GlD9Gv8TOXw8KCFKtzMRFrJy/r1kItwYnHBRxUqESQyV6XOGOV7XFcIeNOZZz/FkUnLHuOKwLJY9FHyfYY4TAMRFGxJHAgaRpamwfdEZRPBT8suk4B44BMCML8mXqDILxa5P1w8N6FDnuYBOKUanZcBkWCWJ2cpELos5gZWAoQxlm5c4jqSDQBTE8XliGYtVbfCFUrhTWICQp0PfYi+5y81BbtUABGHeNWeZQMDmS3Ejxvm1PTuVAAAgAElEQVT87LC2ewHqgcjk/MxlQCboio1cVLTTaR8XbmU8QtJcW5dYDzvd6W4oOKQuQ1sGGQ/Gcdzg+fEEkK2xZZedQVjSCUwesKJQiJdBiX0IBejIzf/q1cpIW0WCtjWM8G62JeHG5Ep9Aogwn57iySiu7sEkT9YP/FquNE8LsDvDuBqILGAl5RrDONYIsTTMIvrm5HTYZ2asBNA8Of4G3W0BfxRc3RbDHlFZaYil8ymXLYqSjnbZBAA0nXOU12HPu20ZId+eNjKjBZCcQIFPIPC7d9AHgT66zB7ZvrXL63M6K/e/G/aFsT1kLd4+3c7QN04DCKRPyJLaOZmbJK75ZC+9zArgFmhX2LvMbDfebc5yfx7HnzuCw3FLAMj6JEMJczZs8aAl9X0aREyhEF1NfsNifJLKHadKjd80Wugfk+MoMnBXy2Nf8gosYyrBGwFr3VjZ7B+Ja5l175hGDGVztCzOQ4bjJ3u6KEdEJIxXSYMtAHD09sbqQWnkNOQEhWDBDQSClZ4h4ZhXYHWnzmSToQa58dwHa21IgKwUEHF00SmWYm+HK5Y8QEwbr6U6x79ap4JkghaGBTiEM96eRRFMENMOcDZMFjCWObGS0VAR95bPmXSfltKlVAd0eoa3mnyT6xwMM+ggj6TpyIow5DJEJ38eoJ2j82o0QabJPg8wVpfHInDrvM4qmUwWJkqeFUxKlo0Nw0FpznPrk21VkEYEommVtJ46PWuaMtHB5DXFqitErcoeE6dejjb+qGpYRIEqCKHJN0CTlUr0zGt2pAcgD8QKvO6yWMocfl/xZ0VAsTreiyfgkOOIOE3hCD4jr8RZOlusQyfiFkgw85y3bGXa39x9xLIccHr4jDMx5px4s67AabojR5wmKqZMnD6foHoL4N7oDn0B6UdEdRQe5C2jDIcOY8FhOSR8Liq/OW8OvCcQ3vyXN5hTcPz5Bo+/GM/8qB+hdI/7aH21k2vDgRo97JUJy/FgzvNmj1WnG29E8JWcFyg8E11w/8svmNOCSQ6fvWoWfcAhMqBbQFNfdgwCDWt/BWbcw2VIty/HmImpZMcYewTGxf5qIkbgeMCpnOaEohWGC7cgl1urDYQAWX2IiXDjfPLZ8YvIk1sChgB0Tkg4sZo9Muyn9vgI9LAadBTGdpheyTQgQwFvj0niiUNNrydUoOJw3Z2mApiINnpznU6DrBpDxo0wAWJQE2jq+3J6RpSNB2BVfzqenH2/HQh6UtCRA9CAKsYblwMen3xtDATemt5bOhmM1e2+sR4RPN/R+3z/gEGR9FRrwko4f5klFzsPVVW3wRuenr98weHDzzi1TPP1s2eS77aSwWlgwzW6PRnY7AWgnNQfJcBgX3zyMz4m4OIZPlefz0rdN+GnaDnAP+wuj2IQU0sri1pmEV8WFW4vdNcd/YyXKRbUNQZBMZJWIveO7RNRiyGjXEPH39WqhYkq7okwfc9iBvqXnmN61AA3sSeq22R1C8AIhFpwQdiISTQDmKwKJnDggbEMTLF5CCZUJIP94lWT3luZOzITpFfuK7k05fEGtz2LwpXf9t+j0ZWrv3/voPzvyn1rLUuuaCNOXnu5/pXsUePf7IG8xbVv/zr+0eM/nQOdrr0PytWE3teufREVL3Yj9ZftqRRGGPsLwhnOxvgf7QxTLowBQ8SMullCCjixQlhxBxPCl0E4DEb0VFI1orUsw0o9LxNzDMgYbkRpRn8nlGE8jz9yQhCtT7sjpY8XQEYB3SnhnoAHUtzRF7D8BMZHfMQnKNSZ1laIr4j6gvZ7Ab4O+24nLu4Bv1mTjbraCapeGm9euRPea5ulL89d/64JeoVDdYdNlinCiU7t962RvaKDbSUykpCAbdmw/qwyWxDg2ehkUZDTMsksm6yUfyZzvFiZqkaUQ2kEsE43+ubz4SXY2LMd7ZlvTLIEq1UfECI8trJNb8SUtjWGuxF6ylyONpO36r3R28YkKN4o8OT3fkx8Edwq44m2K3un6lno73HAg5drv+xds9wtmF/tl3Ak9nLr8dqq4G4wd3/e/lBVHFGOu/WbuvOmoDC/KfgNb2+yQ8wOqXBh7p8sTVExZ2FlDuZ4Q+oh2jJZFxg6LUyKFAJX9CHshLEBII3wHaPj2SpZZhrYPmcjAPVbE2VmOUepnx3tDkdTGe6uihMA9sWsttDjlxbwDxy6e6NwvAsl5IVB0O7zxSCv/QaUknd9FDvAtt3nSn7/PaI/K6LfDKFpZIHCyjl5RkwSB1uDzBJyqT2c2/bokN7DiBZ73KsO+P6vQJGadDpZE3FaaU+NMmxAeodipG44JaWEOzmuJgK17OIw3jONPF99nnJkaPY/X32U3xepOo1/7cjI0YvrtxuO3agXPY6tX5/xiOFGqHQQB275vlufH3F8d5f3s6A+7xc7whDrT2VtzyfP9KM0TpXCbDgQ39sU4tkKrOG0M9NJGlMoSvj5qkso/lLygAd+RW1wc7q70UcNjcAmH61oJZl9DQdXJYrD4cZx0PCUfQwF85BFOr21IMJpyLRxrKRAFALCbp9St6pKzGsr53UIR8Bdp+4ph4G8HqO60ujvFR58YfADa8phOVJVKHq/QH9qW0dlBiuwsGAdpiRfwISm9enUCcl9ijRamnOWzcE4J2QweKrdWwTKbhAldaPxTEcj5X3K6fQjeyYH52PdkLMc+nZP7bfYhmwU69ow+hKRKGFWZWz9HBVoK7U4zCMDxXD5C1jWickDmNPGESUdHQ6x8pYxFrjp6xXz2cgJ2/UOh0bOnMKBlg/ZwEEYhteJvzEfd1D6ZQaj7mzXoufb2ybMzYbT5RZkpryqYkY7DvH95gJzZH/u2VawrjkFGLvH0lYSTniEYc63XSXu0h4avm6U8zseDlaKXibUI6GUjPIPlcwIjFDOhi47YFDKUBdwCnryIrJv72rZ687fmiETVHJU3lsVb99Za6P7r1+hmCZ/qPNeKHCyADO6IauOtZtLDawTvvqdHYpXUADAZVZS3EkvPlcwgZKYc7YtblFjBZSL7Dr6MUXlEh+yB1OEoMgoh6gG7XLRJZyPoJInMwuMqv83uaySaXybGbx8dNjE+wqZya3vD3ZUeejz7s+49tp4kAFww5NMxKE8XYJf7EZU43G+5oPZcUegOxJiJhQVNDwgJXifAqFXuSvFsv045uuLQO64zRHs+KlPJOivLRf5FAlWESnWMZzyhZvbm8U3+x0bCKjONoOfkLe26/B66ShdPCGa5X7aWZ2PoMlOgZRhYE1Da+Cu7X6mhFIZeQN/r84ZXu0jKk5ooFttpM0TdnwmHeT+10G1w93gN+SyfufmQXYKlLXeuQc4JwJfiISBVduwUBOGO3qZM6DA5ulPJKQ8FPFAMd/kidqXpvZIbKGNWKBtJiIZWCYsGYIcOE5eWW3RgakTGYAV1RDUSZQHbtMky9wFMghS3PaX+rFYRSze1XYh9E7zhSuxZj3AtWiEOk1oyRix6Lm3ekBMA1HwsSJchQx+nVKRyc1z89z+NmT2Ha30pU9pWIPDb20XtnWarQHBG3FxXjz3CcA7IsyHicNPhyY5EB7oHnfzDlnlAOUIFr1PpyHnTeGfqSoWBWwSLRXd5lJFoSoQsokmlmwwW/tLIhB9wEcAX2nbZFIbvTIYNeemqsltqCWDKr6qYkq1vVCYfWQFsiKNqDmuiL5iEWTGai1g2CeNXmUwyBheTTVk0zhXXX2pdQoYlZ3If/HrjF7UnG49+PBxZ8h7A/JKknaPxfdvOngbyiqshspzWz5bLso9HsR0k/npn0XJ2+SY3hzBRj1QAEzggBmpZed68HGCDO0vkDzzS+K5zuOibU3y5KAndX4E/Od4rxyKFYQlS7bn4eNOx/7ePtjv2ZJtNOac4yg4z4eHtKuF4zjwzJb9a86zP2rA7BMrvlpi29ff8gEfdkPaH0XKrwNg70Cvs65YDhtZvPYTgTDUnOyfafvjvZ/T5x1/n8n8CPnkwCO/x7X2sC/JAV3S2Mh9bXa1+3Oqm1loW0vA7UYadogGl+DdEfgbakTMMB7f5hZwytE0XhvtG+rXtu+dK3S41XoQQpErm2Eb4w5+3aa2LVzyCjJduc9/yHGhl7Z92WlC//0/bHB/Hf/pHOgvHn/CBgkFwQhriLRbKh3C3+l0xoEJ62kFRHCgAV0VRyj4QOCjZRrf8cDtYHxjwg0xbj4S9JPg3o0kNBYcx4IVAhkTx8MBMi0zCcN6BqfCSJH9sS07BV2wkSNypDkz70S7EX8BmLI+MXHztyNAf8fzLye80y94cF/cewUWVXwiK+U+g8o6gXwv7nAnY55faUv0whFZ+pY2JemV45KDAqgy7b2fu/r377UEhNT1G89S+LBJy5Ad8lsKFtuMBG3vNhAl51DN4F7nEHAF1sFqTH6zBzIskwPEUI5oXot+JyI8MmFlYGXgSMCNX7N+WnHGPR6oCWwhHBLhnTLOYKzusAgWdgLwTk2xfYS2skjNpgUTotm16ZgJwfOAUtp3gEO9rHutSP+4d57b/b/h8PEnHHgB9IjHT79ljkZBHyAmjA8D5y9rz8NtIghtPofw75WNWjFDO9y/UTKNzyUUJIOWltBNhQ+lkniwQ5Wz8PMpb6hZjq3Nyg3FWzyye4fg3rPxrx20/xDMe/DGMG/Pg/embqfnWPI//41cUQIs86oyxrfKk+OKK35LlEpVzxhzw2ZkaEUW5fPqkY1eEjKyDsLcfKEM6BZOr8lSrx/7C69TnRmnvvacPzCGchpcfz4DTUhVEBnGip6MjukJAwfnOwQ8zVoHIA3JIRlHyeu+RfPcRpstAwnVW5u2a8A6UGWatgcpW9nC5EElM07PGJtiKystUy4jxJunaU7LVIwyiJF9HWDiXTb2ea4gKI6LOdL3SqkpFQdYrpyCXSGlloXe59M7kV3LvNvMu2ui/nlLf9yQQ8BCDImsmyZXRyV7y4CAVZ9xWh97eSycjizx/nxpYKTauhvFw8djCvPin3mjFCXfgfMvO8lL2jWjn/O0MSwrJm5iQRDNaGLecTcAuSFUBawVkBE4Kp6dzTow2bJ31vWM5xNlO4spK6YcKuOANenSRXS3s1hT4hQ8V+tt1yJtIhuD3AmQxu9aQSQ2ULt5npPMYXdNe0vkZXC1DOQhEoQhg3wMDKhQ4kjsP1GL7o6+gheONiIM9YxzHVi09TNu4xYCwO7ooNSeN/RbVKyX9DAnsZUoLT5OTg9IABrmWM9iSHthqd37x47OSbegvHZewq4tU842+ANtVjFBb+9b7Q4yapDOZXIDNY9WfQC2RqogDC+/6sErZK/i5ViZrAVTtQdotFWD9kr7zXiqamQr9rlSZrIHX4zfhnrGcZMhbetaBoNGydPYl6igJah6ByDvA65m9hAizzj31XBrS8oPTiSnCm6OBxCA07NfOy3LfPVMfstoguskWwq6lcxKhuyImw43H/fCwXdsIEl/iDEWqwaByAQEPFvdMkXPDupwNIuIZV049IJ2xt9V9NuI7ZeIl1VHwvgd7DPlFYXOifPzCqvCcXLeNRwpyrlMzrMVVrFlCmE9n/M7gEC0+ngODq+A3RGqUWr9COgph9+hbqXaLbaHNt9f7tvYBX0VAwL7PRbnj04349yNnOHo78Y4Qznbf7U1K7CzyjS34K9wJoXx3LNajEdE4F585728fRInFJ+OOW+7jNY4+7yMI16XHg1/voHwBgrLQLS992ZzHkAt8rPzjR1Eaf+7z7t/n9v/2aCSBVNu2iAr85a8EgLdhsvQYUoWiJF6ChtvMvko9mTxMYrJtYxrwJ03iuz9GkRPgh71oMy8xh2ORr3MljGzHFfRLex1LiA1Oy0sjP0TYOqlcTfABJIP+K6CspbDiSLWrXCEnabEMX36tmqaPHNpVE60BczEkyncptroo0L5hHBYoT03gB895xWRgR40HYk/xRFCritodThk9iAU2WLAq+gY/dS0R9jFofv6mexzCAJCQaEsbVPjnKwW4ffyILzIbA3Du/E5p6HB21wgsnZhMV8g2qCkDcwHEHSiZh1zRKua4DQ68J8Cb1zOJjb9nt2Rl/jTqaNlUDPzhjD2zMmuBygqEDhwa4Dd0Un9F9iuI8gYCewNt4w9qom1OQfO76/T8n4UHu4ObWscTlmviHIxUh+OSBvL5hlNt9MevIk8P5ISE2+175Xuailn+cQ3nL4+YxDhLQhf/drzlzOWDwORzcs8MESw4ANWy9UG4S5hHlmkZdMFWBm3f79FZNJ7ZFE+24LBQgeO9YtKRYQxBm7+dovTb8Z7iSzb+IPe4QvFSAMNHR+j4ozCMjmbyNUveOd6wIRiMkFXgZCVw5bBeCOKM4BvTi9/cjlJPXCECDiot+JxOdUCudlk/7Vobmfh0j/v+FKtachAsvntVmHyMwg3SiUboyQaUaM1j37tDeqk7kx/ZsJRJVstEpD7IPnULpAn9F9mySDPrJogmhgAIHXWuF847iLxQDwxZPQAWsAqW7W9HKFnEbBbHKJgpVDM89n5qFfvWcxJblnmBPX1MDvaCawmpehT2OEsU12eHo0OUtFo1YId+WBjZVI+CzBFvId/DDFivLdvTveKJyg+0MCKqCwaN1DcgTzh6gHfqC2w0+twLr9EkSJAfBP4gNjxdexpVXeA39WS4/NWLMFPqi0g6SOUPuMLedY49jLCPpi9nhOZ7z8pLpr7/rEjGCc5H4sbOr4krS82r3DejC72UEv0K9oZ8FCRFtHkpzivVSgu6baz6rQLlaATkqPWjXJcyE/Xp7qRH3fD+V3HHn/ze0qZMz9vnrJDxAvmtx+Yw5L54lwC0NvHfO9Wfx1/3vGf1oF+DSn/6Yj63U1UwlP/v1QgcqO0KYLLMvB8XrE4gwnhfZ2C28M73PDE8yC8ZSvf9I0Iy2fF7U8E/KYpoBEsv3aMUX/MmG5sjbI+RlgFiAyFnYDz2qQfyDKQCeVkrGl/xfMv73H79xtwc1OGk3r1L8IV8kBWxqVIuB3BPEupeZ1gNjLXh3pt+C8e/Rnx/gsBkcNnwgZAfSClW+3G00X4F8Zw7f0PIeoVhYOtTYBmSa8wcJiCxMxVSo8o76IA+OMAfQ4p0Rgfg/AOjFsaeOZpSiqZgXEa1pYwoMA7tKjTxrQDJ6Vx+jQa+HzfKfBAlxMvgev144EU+vkT3v70M0AA4y0U3y6dWKkkPkDwNse3X6M9U9/zzT0eHoAS4jSCOpphdncHOSt4AVr0gF239ZigjOWhjOlmvCRW1ybuL1ryjqKUk/J8boFZOOvUyWlAdw6pC2IxpISBFBRC9k3FP2/cSiN2eDoe0AZGteeaC2IDb1G0KP0SuLVJYrqZ136e1z//S479M/7RZ6rDmV6+kW5e08WDxCUiiJ4BOjRHmCY85BHgN3uKG8YMRjitNf+z53TxG5vf4oxYL0JoXRkrEnSyEd8waGc0PSGVqpibro5bBzRKCx+FjUM2BlS+KI1pJ5MZ5zLF2YbKqpAbAM9dveh8xpzoLx1h4LFH/E7pI3gfIZ24C7EZAL3qiP2xOSaJvZyjldUj/02hOD094ni4gcIyHWwNLeOFNBwRvs5tmEqATM1Mmcz0yvGRB7RQrh8TgZYFmGvSnuiFN9gCcwKGTAJZzShTFT+i3KfJJiTwMuMzHWtEZIZR7703J7Cu0V9VvQQ08HxzBA/GMgZ4DOiiWDDAi4UzctLrnHHilwCgWWMpxk/uMDRc3vQGbQsXdFTrQ8uGrXP7TssPoeF6j7Eo+w3ZXm63ZecbhAHLfmKhxhEaSgVOsJqhV+CBkATiafNSSrnQyoxOCDGI5oZOhIOSxLIXSDbWYA8gUnOYM1tGqDCEYd8BwODM8t+IU7+bOLfdSdvrCWUYDoOlk8EmC3jWFm1pQxhxS1Iq4GeAoZrhT4XNMqIADcpgAlWr3iEsZvh2uBhtIwwvQdh74ZojdW54lDqvyzh9XwtJxtcNbqj3EtlUQFl3yiBNzkenrlnOOOS1kB+sHKo9x8rQ23fmQ7eSk8qcMCVEhSsUvQ5YeysPgTiO6qWMFvJOP1YFlr4evhgEXNBzdZ5CMc+gd2i4oJjrBC9bOZjg7bfGwFS1coVie0Y1cp5fouU/jrfd9/HaVZdPOgI4ebb8angWgbdEmKs50ojJggfOZ0zAqlL1G24ASbus2fPuydcH2Xnia99f0KH941FyYWRLVzyWu0J0y0sjCz+CU1Pm3sgtDeX9+9x/6Zys5yuKRqvD4gSjT0dp3UI9Ji9w6Rm2KlXO8vq8O2x2pzaZol/3CHOi77jLBinqDrr/6aVjIyTeIMODtcq/bu9TNCVpYtKpJhsArfLMdt/3XVpVbzYErs0CqOokIbkFLrTzfZ/DaVHxPEr62FQyu5sv8jX8jAx0SjnIZpFzofjcXi9EyeLoCSdyx0MqSQULk4a96oF2p/iW77y019qJfpgTd69n2fgbrdWOLZeYh3ZeOlf6uckrKecVgXzl/DGYWuCRyWzR9x1E2YJIvXqiKHs1isanyGQVy8ydUF4wvOe9ta7RxgPtOve5Jj3bwq5p4okbgRcliGjqGgqIVx9RtYA3oQymjAcYj/cqeH5uOHdUG31xuUo8MOelClSbYNbmJKrvtzC2+Zh8HcFspJLlsjfLS41a/IislXs9Qbj5vuMPOSuZ0bKrBTbFpVtNLfaX5t6pPR6aa+3l3JdePpjVM6vRgu73Y0TIvq2SEN6C8Lhlhz6VkJ0mCMvHgflJiu45DvcJiQqGDvBHk7eEIzDAH081q5SbYesWgSqGs4rBhNu/3SDW+/lXC1i70/f44u7+rMKW5c/t7us6QSQpy9QYK+BRYDpUOvCIQKp4ZMJbidoA7szu9JYIZzKN15w/Xu1yDJwGW0WFHS7lPBFoUjvxMqjXVkG9D/KNUHO+h4MdeELtK/E/Uutv39fdgmhg65H0z9YncCrHQdRaLVDKxHaJwqLCsi6N4Y+XIyiJlAqP9/B/4djY5eIOLUv3GozUW9epR7ztg/DLZjd/TBZATjX3H3m5+JKxfJxbZnpV2IivmN9i/fKAJ4fEuGPQ14844zMAs/cuegfFPQi0S5gCoFXa/F99fP3OgjWyic8E/ORM9CdUdvlXsoTA/TVx3KmphxFEOQFEO/kkWU2eyqCSwjo/9VLK2wco7WVJ9XPMptZkSSeoIccwWxWMPN/vQ1OiW4GjaxBi57dtLL3KX+id6URvOqJfinDEB8tXapQy9vJeWP4PP34nEl4u0cXP/6pH/3X8c4//dA70YK5NCkMw4D9jHBsW68zI+mmo2z4ts/S0TgCKAzNkToAZg4DpBtqVV2BZcGDG0yC8p4EnstLpyydkz5IpUgrLKCP7GAye9iyBegS+ZK9GwMdGl8Q5aKZ9ES/qWdpd0K9TGIRVBMvfFpx+se/j/AcnovdkjunOoAJYdx749DmrSNP2IegXtXHt5IkLarX/3E6+b0zww45m3/ebdgJJ3hv9heFdO5ocuZFLXjteva0L/QS4E50ADUO5OTAGAURRxr1KuT+S4h0U50+f04kRGMt+vhJh8MAiguXnj5hT8O3TJ+xzosNxK435xefgm2G8KoNXGbXMiR7I+Pv36zdSyKdfseAdCIzD3Uc8f/20ccY+f/ncYPnNSnARNWdXIVIyfwB/v3uH9evDpsdxnB2Cs6riHIYkKG58r4tGCb66eIzuXrPnBb0IB0Y9AYgSu6ZoqmdC+cMnTMD3yOYYE+MV956ihG8t/AnhKP1k/r3ITAOa0dcGBQKWYRv1ebUnZg/SnSEgDBWRWZIVJfycjHx1kBR87fU8J5gIR3fErW70lwgK2kzxctf8sPCyd1K/eOGGev3Lj9Bdrj6OkP2/iuuccn+RNkMATlBdYJkjlvkbjuye/R/GAgVAMrtFYAujoB2b2vg7XgLr5Rol6GzdDF+IhmfhmBAtXiklhGwKPE/cM6wQrNCTgrE47p8ALMkvoucXc+1nJgWPBcyMda6AWna0DmCuAKXxIBSObXYOYYVmrtB2trO9fwll9g6fjWHsCjNkUEay2gulkzz6VI1hvaUGMXgZSbtFBOd5xnk9YRkHzHXFWBbvrzhSOdkr65FBJBT0yAKn0Iw2XUkCU/ZD5xFyjX+OrD4OA7zDlgg01AySOj2DGp6h22EkUEyIEJgtV1pAILH+XVgJhGc3dihUBATB080RzMBcFhwOBxAUfICXgY9ia7SNsPbHSu6XRqXZAhWIFOJZGNcU2v45ehKDKB3tiRuO7xFMiZAFsnyNlQgP/iKeIUFAVhRgFsB7005MDB3unNyuaWVTIDRV7+1s+DPF2gCJkgcosbk4iTBZzCkv3TBvsBZikFiJ96D14oZNBZXD/CUnuvc6SzEuCRxe3kB5dO5QMO37q0wG2/21l7tKRrjy0I1I4jI9hVHDbkRM0LNijMo0V1XAWwqQmNEcotnP08rBG+1FlkBWZMm8hHX+h8o46gZ6BdNoTp+6dllKbtilKhcg1HBLBVbZAIo1DS6hA4TcJtZdyh3SUTwHUCcNlM4qd3lYKUt/1vl8RmDRprRnH04Ti2x/XfbnLmllT0vt97hH6oOIPuniTlXTj+Y6sySxwuhelDQ9LAv0XM58BbC6fGPw7E++RgeuHVfOcSdV/tLQOp+swM2bBc/fzlAAz6eT8VIANBU6rA9n3sJbYCy3txgiOD15D3mvmlLDDT4J6DOBDmYy0PXcxkGFm7j1Jzz53tqVfcQOLFeOAwhnRGYPkpPOHFbt2jDYqTvVIxgr+bKot/lYzTHlcMy+q1S0qLqVKDB9zBE0guBxM/HLss0Nh57apFg4eUbsjyf/EC5o8u/3yTuvH+Ewf9x9B2g40ne0aH/P156RwQgh2yGCnz2Hvhk2Ka+pvHm+DV3NaH2dA3iqYElMTCYe8iXN6f2zxStPBH5xtGBx2ZL9J+v7WbNM/QQtqNYpSvDLXu1qs13be233QkHHzmnyLVG0yNrRHar5h/+VnJ4TvNQplE0AACAASURBVJM4We9x1uIbCY2Y53VKZ0tCMHml8XN1fk6uU2naYbQPKp8zcSnjqZbc0Ved+8Jqnuh7p+Yfl8V6B5w6XYlqLEOHo69C4RXx2Pe1Z6OzTHeMBmi8dRSXTkNTEK0Rp0zDH1Hr7S6xI6y9gMkXBUTNdXd5DHBnVIHOnFTO2VV9ze2ZSmTVSoYHBWSLIgK8J7nQ9DZZgjlDJ3e5VAv3SSh7lJPDOR3njWj0ym32uquKpMH/DauYF5N5V/H+t+4qjQCp5hzs+BBcspZ+5xDdOfv6dYBVM1SYPi4AiLxymNOFCFw2WPUx2F0y8MSItlXKIgumUmrBBk1wM/nC96ZnfIuK27iQawwA79we8UjAewDAAx5hjryTFh8zXPTqWYR0vBPep+zepHsbsipEPuPm+H8a1ontc5nipJIbvfMd7jrRdJgGmQQHbTH43/zbDZ5/ewaUcKfvoXoPEcWDV/rQ3JsKxSxHVAHXnquO62rr8zXw339/60GR7+BOcmyWCQSTnwZZJQ0eVr79iQmLt3o0WHWJnFKPR0efHd4ZbIK+2UyS62UbFsVzF1sDVxwfntXLtFPh9Y0qMMzhfAPBswK3xBBVPFHI4PCEn6DDtv/7eJUUA4vpQ9HWK5yPPajZ11h9PzNVwOyIwPEoCOXjtMAcThk7e6Nv5MHWe9xXN1pEWHA1oENNhlsVugI63Q4X1936unisnCegQ58JfEuQiKHz9QqotxyZmmcuXF+P7TnnLw+bwNhf7z/hv/4f/xVf/ofg5/eM+UUw8RkCa6Gwl1ze755boFBc2OY2z76Ur/vZdz6hz02AuHZNn0vKSfiM//2nn/H8628QInyhwsM7uFjp133d3fLub3/H0y//vrEPAe5871/s5nrht9Lte21B31udkFJ2tarC1sbXaJIlWQic17NgSrTi2e5Tdd0kS9S18fSEseJPBrGw+5DT4rBVARXcX67y0AVdFttVnLqY9z9yhKh55YeiRa8c3/k5zomAn3wmbX7+HdP5kQf+dfyrjv90DvT/ZY6m4IVjOg1vLoiQ18EjsYi2QYzbwwFPz1ZoZiyLleMehMGMhdlKf6GVkgTwKY0LRjDDKDTXtfVgoYwCbkksG2EmxvePHA9kQqlCIb8J+G8DR/wM6G/eJ/0KnFLxvAJCH957KO5/cHD9uj96KIwJfveRWi9X9Ivrl+h2rntj7h85qL2S948OfscIR0dJw2EQVVEvP6cpMBvzM3wZzMBYTFATrkhrYkwNdbWMMchXA0YIYBlNqpqAijUPgZLUehs9ouOkHbcKPFFlpN86DOP9k59o5zxgwTvIV9slPSM7PvexhpC5yRhFjyWlHPe1Jd4rnakshUPbmSmFwAVgQF1RK1jVDfUKLm0lp1BQSG2tpmmtaUDI650mpICvYeBqJfTi/qmYK6o0X2WIF7JrZglENYYom0xA9mMP2HTcMPlIEeVoOx3L3+NJGlGYdojDFEqmmAOlQKbytYXQHnw/JJARsAHgxcV/3pHwuDYWvfxa2m/pfIGC05gSkPJs7jAmqONDc0CUHT2xD3tIp9GF2nPj+9g/CU7fY+0ZdXHhWh7eWF7PPhhQG/25PW7Nu9DzAXQkiJgxJhPtdLfE+TYcnW4EZYEeATz9flH22vnp+HmF4JeR1ohcKPRGmzkVk8g4H2wO9MhCD3oPtP0BxZzmPFmfVzAPLIclDZ6k8QqvUNIyytSDokQrA4NMSeMwsBNAg61cuhLEg7cieC8Akg50VXfzDkAFQ6X2HcGdHm4UFzJHLaZl+jbnBQFQWTFlAU9TT9WNCsu3bxBZcViOOBwPuLlZMecNlmXBMhYM9uz9cOw344WKlNE+YD8FEhVcIBAwSAQ8mjG78djcq7THhp4V3HCFXP5So4zwcYDN6DOo1jMcKBJRb8FnfTyDGVMBxoRiQDFByluZTyxQRtwKJIEHrFmdQMl+UDLnu5Rn0g1QCvIArjAmRRlwlZ3D3J3o1rvd+6RrwEkBWOCnVkTnd2guXf0URo1eZafoVmUOmsLs6yG195OHqI01stHsGfXPlqyNYQDnec7z2CsB0Wznugyw33d+AlpZjhx3yg1h0AhjPNrnXfZ8zLuqLOyEzvZYwzsGheE49IBWOjXgGpRa87MmjYDDuMsgETyCwAm9NJ7sZZv9HL4rgoejA1ERI1B8F4jgsAw4M2ABODFmv0+N0eC3elAyOk3dyAj/+HGRbRSv1PiBE4xxvIGsRhvr2gqCy7k2JjeOPvZ1qZ7ze+ASoKcT6HhEIAhB0+9ybR10I+1fP0L+O94S8FTw685cNIeN0UzNrPOS39XL6WsGCxj+U6tiHk4CSiOW6TOa+kr+J/6acoDN8OS/7x2wNWdNwWov+2wx+bq+8Prx0lWOkR6k1qtN/O4ndJnOGVRlPlNrweHfEIFuHQf9p6Idfg2oBa9T0reY0avj2Q4uCF7+qLGuzvjUne7hfFeprMtiGVsHYJDWok8+maB1RW3bqEpvNpyjzf3itc9vzxcGHfw+kjJBh1vBwK6UFj2UezkdGi8dNmsjZYTYWYHDopY24d+UYwg9c40SdkkWLggE0sCeYWk+p/pDwTRoa+x3Ugwa4GGy1uDhCGV02gL6VoiYJk4ChJzPpCAaVq1I/bpp5ys0Wz1pCLEJFaTjNXTVwvQOPU20S3YvZigTseeRKMhlFNBA6Kfh/4MCQ4fLC4QpXsEI7vBSSZBan+Qd/294o9qwWUtmMJtMBb4KJG0ORCb3jcVdyysSD5SdF0jw5h2fDXm72wupnDC1+HA8RtLWjkHq5wcNCbtPjF+dT3dNPe6r8IJ8aHRaCULq/mZzc6fz0vd+isCqbawlSllQQiSP2Ly+AXinion3IHzK9lcbxEHJeykXBW0LARKK5eOC4/g7zqcT6OaYWeU87Pw5J9awMXUZ/4oOyC16Qh1+x5+OWFcBq0D1I54//YJbITx4oGYEzesUr8TR1sxhsjY2NgHcAhdZv+znG/pS8lPWCPa08Uw12emRohFMowP5lDq0rU+ANw5C0LeSCmOv3KJkhKfOp9sSJZ2iViEmkBNWS2dSBH/b/Z8vwd507npMBBuLGnBYrC1myUaAlvrriUOxf+r7okG2XwunfKg7XnshTXV8JN/TmZHj4RbnoMdh+6AdnPef+/cEwgGKk+0rlwdiPTOBATmZLZvcHeM9Yb2/5Pr//X/+d3zEHc5fP2PFvk1n3fA9spjX9Uf8DqGqRmH3/3Ix7tc560tHXJXZ57mi7QT/+LPT75u//Ru+/fKrBbA4Pn+Br2DwhUZ/ASRt31qjt7aDDd2Dpqy+0Q/Vba5KDSJGi5gZk8STJtiC1DouNzgSDW8T59Zyu6TwiNzXxWzJm+FE9wFPNV2qV48JPVF9w4Rum8LIP/G4utp0yQ//0SPJe5ehNvtpL1fR1de/jj/3+MuB7seeMP3Ln4dwame+b5YQGszmQCcnnjIwdCKiiI9jARg4smXJHQ4Lpk68vb3F4+lspVUJeCeEb2xRekMHJhRfIVjX1Rzos/U0RBNwnElvI0x3Qkm7BsAFgflv/+Xv+L/+n3/P8987I3kX8jB9gdJPSRi74/yjWA90oMqnvP+Z8PgrsGZEth0ftHi2OnNdFHn9FcDnfDaf8cL3/nrvgtDnfxA9gqH+8WM/gd97uEDll7NHv24clQ5TUcFUwQPIKgkEgadwzDJ4AKsIBjPOPHC+f8C6WpR1lGmN7K3KVUDLIgqh2PdfM07GLPtMB4C3MAUHKCE/BOhHn1g4zG9f4HsTD6AqvJ/491Yjd6UicE343R6uZloAC4BvXx8ahHHxPpzvIXgwGCeYg/gIUwJJy6C9Pj3bs9/dokwXdcfSAYKEh/Jd+2MqrDSxwJRMUqhYSc/IAL/x+z4DqfADZMYBVyo3xjIOY3qDRWqz1Hqk1h5lAKc1ct0JU82gAQBLZMr7cZ6thzW2GefxHdB9+Q6vRn8E5gy8drzmOKf+gCtXxvivfUyN/J8s0OXx2nZv6NGzd2i/e4KfoM6fZQkAFFhCEMbBoz6l7h2Z6CKZsW18LIh6e1wK7y4QDtrAZu8EIzLjSvaODEOKmnbK3tN1ztWUds/OEDGaEQJ4Zq8fFXoCyPeH4twflyBQnEEnwri9AcEqtAAMEVMWw6hyPp1879pNDmMYhBPWCxSRPUmJ+/b8wumI3g+a+CoVp608Qu157ZSgCJtverl2HgPU5pJbJ4xi7qgUEkRPe8CyQZMWqmXG3twaPTqfT26kBm5v3lgmC7uRI3r7kTlVSZ1eEGN4UFCs7/Dx5XxRBhIfJEBqxtNY28jaBgEYhqLWVNQMcqJOo2wckwmY01rDaPGax0GYc8VyOOO4HjHnxJyC4/EIPUzosljlAjUnP6EMXMrs1Xx8vwxyEiCw7HrDsAgACQNSDy4JnN0faaxuxvTNGjNVexPPPMsS6c6jKwPdz4vkUwLGHLBAC4XCjL9hVFNtgTI8zHk+7XoSQHTG6MFCmAzLnhb2fvQ1R2njIrJqAKow5VkVytbghQSY7kSfLgOLzy0z9L21Q/VFvwDbDx+dBhTMtWDc6Wk7P4zoGRzWFXvNk6oFzm5pM4M79nXiczy/GY7ze9/RYbBG6NxFT0Uq4jVplOpmnuFU3zvRa/4Fm+QTBK8OoeBzZSkq3KjilUiqty8DOs1oKIHDNlb1TMPY+2FMJP+8kGXZzBesIotn7q8i2BiifgQPGiDmnDnJbqOOTMjYuUwjM+CjDGhm24Sh32nBcFgA0eeWoV6NJXs0N8prMGsDr627OfY2m6CZEZwU92Jm3Lw9YE7B4ZagxF55whzHY2mG/3bzMsyqV6VS6MFe57OCb+v0yJZSd86M4xHz6anAT+QG/Senyt5DE6fE6f2+i6cvt4TMzfY+60fH8RxyWZxyp/jQ089NRJZVCYbO6RmhE5jOb3dOH3adRgGI3FgwBJ5rXyaE7QERBBoPDp64P3IPvnLICzDp33X9oz5H7t3+mshKf3v1dzt65nr0T/fUsqgc4A+V5K9aeHeN9CpAb6jomYvBwb8KWo6PkXHkBv5OX4HizYgSuGRBLzL7yQWNWI7h1RbWdUU4z0XCKBzyYXcJBz+uiRQNdDps0WF9qpX8dIWMbgKkFYjqWUQRdBmyQOjgCtUzLBhxpE6WbJ/yP4RbP+o5ZGY4hWO8XQOqSl5ZucyDCJLXUxrebXJOm2vBEEbv5AeAOU6uTL4HbFCIb9T3XKyVy5fdvmU3NjhEZr5nbJsF3++nHuynM2mxutOZvW1h0LqoBOJddnIeMUEOnsUurzJZSyYhV+O01jxm5jAN2VNglc0GxCtbKJi8XQtLlqAPnAq5Wk3YxuTp/CHoWtAOzTLuzJy0DXD5oeGfzpBLAvaUlZygagF+iRywgNCxgETBQxEtX268fdUjaQZ65h7QKAfedk/Y/RqMSnZSLC4fZelrx8CFzFm5Or4NZCiH/e+0p/aCY4jLgNGjN9oxiQhY2do4Ob6Y/Khpp7LLt/bMHkACZjyTVSF7RwTGO7zDg+8zm10G+vm9ch8TsHwcWD8320nwZgXO9BlD/4ZVVhzG4g6qSlgIuWNpdhYiAg+ybHQnexEASC6PhexEBK+8RVhXo3Xj7ifI5xNu9SseHKemhCNdU4ZTWGY51CsKwRyIfc86Sccjm6P4zteN9b3RDL7PJJNJCojgmwo+iEB0G3AYdDFo4484pZIvxH5UxY2oV+Swbx8hycvj2NvrtjdVMDPOzbZkb72qTHwZB5U+HzQYwe6YYLEnHuDt1nzmfJTvQX8uRTuOCp6OgGyFZfFngEMMhDQrP9n+uGQ/wXvEZZfQSyPoYeXVEckgk3ZGn+o4naA4AmN12m+hD3xzaziozw1vbf+YHXMn0zVetBlfe7/eG9Vp0iPu9B3u6QErvuKBIqDhyn2IDKc55AFKm3H8buu0dUK+5N8J/iO7QXe/hm4vSBkHAD47zfmbAIyPeP71NyiAT75x74nwUYHPpFvbv8a87e3//PWXrGr7on+gCO32a9XaqwWIdlmbgeNhwsf3Z1QQ5agWlvDyCo0p3ztOa6KS21lyMOYbyKdS21BOV3bO88FcFTdWcfFb26v6mB1sm6qk12nI9ynLDx57pSwfoK///qO3bdcHT9gE5l69tgmIf+zxfx3/pOMvB/p/5PHCnqD8i/+tZOyA9SsiKFgFJIoDD4AGJsxpyTQs4lQE61zxFsCjAk8y8Z4G3irhiRTviHEgYKhlo6qEEGg9QKcsGIjIrumlnZwROVHcDn9HzXcfRQT/7e9/w2//76+ZJWAluM2ZfvPz3xGGRwLhvVYZdCHCe9VtWXT6CYzfXgQrKfChwbLf73+14x93ov/+Y7M8TbEIgk2bc92pQmxlXUggnrmYRi1msAtUYzLmGFhkYk4z3lkJXb+flsEoFAL7Xl0QfZ3d5dhdcOPfwR5jXm+uXNKj9rqj/ZqzvN+L2ne6O+slA3UIsnbSNhP9pJolzkJuLr7aV65f97KUqgCgZVziMcz44IqHr7ApyZFuG9e6cYq6AtuMI1l6PZXlNtayauTvqXg0eSOdnC+TjxdXOGZe97s8U3/4bn/guLq8DTNahuA/5Tk/cp/dOZdR/NgibbtmL1wrheD6DIJlmvW+i7hxJ2LeNmgCNZzZzqHozm5+KRHXvcIA6BNBBrKE4gLalVSMXUzpUyLPpsMR0JOd2Kd/uX8V+izQmwE9CeaRvFQ4cNHzY7P+7khk2nQUe03/2S+B4pJmvBR9unnARst3Y6Qbz8YY6Twf7jwn7wmYxpOWpWW98WLbdgXbNvBhHPJ5p9NzBl2F0vb0/ARVxeFwBIgtK99HxmDvj2W5E1mufRzMQEjskfzFWxRqTiB38hBFeWULBLKx2vhKwSrapd4nN8qUJa+DK8QqmCI4n818IFqGdlWFzIm5HnA4LOCxYFkWh+kED4uwjuyWcISpVM9OEgWG70D1rG8viRaAZs5FzP1SPgttdDWQOs/elE4MPNpmA1DCKLMJ1SnxhPd9X7wst3pJe9vnEgZX15BzT2o8KbCeMMmcUJMM3gz27Cr7YwDCjIH0wUOHgidZ6XlVAAwhgGcEebG9IgshOT+0fb4vGfiHjyZ3XM1E1/g+iFjhmAKVge8CjaJ6uVp2xojHJK+9SoDjvcLprK2XqG/FDMpyBzjZd7Zu6rIEas0o6P8VvpgIVk8PQ5s5IVC/q7bz7P8RdM6z7stB5HteCcqKIYrorRpGARMxtsZbK5lt+sV0g7D034M7aZxrA70qL26MZQajzgNLbtnDJOBAmyrIYYwKfI7gxwSHhvPfcUJcFhl1U72yBjnctoFfOq+LeWoXufE15J4tg+WFU68L2j0anelPCljmg5zWqqpVcKEzEJmccEfmzRFyOm9Hu0Pr/Uxeg0HPHs/jFuXTRexJ20FDNcu425j83WYraasIoUDPPI37BTA9aDVXS72yBjyQL3iiwzxIcc45wX+9EsO14xFVxj3G01/334d77Xvn9yNozuWT+/Gtnb27YwoqpSckHiYNcWvFmxbYkwoBmijcRk9luKdc1dfmsvvlimAVw4mAzMw6D54elS2wdRhrLZ69aw6NWmyvwNL5XvDW1IuQvwHFS5J3U/8uHOdxUZSFpt11/niQZ5yWrhjwD3lPGl+uiwtuIdd1574FasOrkrx+mJF9O09qcxcHGrc5akyNIuAw5PPtX8wjKiINtkDZMbx60lg8KJMAVsxJgK4ZjS4MsJrFaoxoWcQ+X3EYWQd5AjCJwTQ9qKDgFLBJjuFIWbwvaGjxYKMV9jpV3W4mEB0gFQwA4gFMkYGHjiM8QfD2ONqCxpMmI0twd4P6hgftFi/ksmtBt6GnMIXzwvk42AKXtfCwggJdfnXnefC6vb2oy56O8M6j7E+SfIZUcuneTDT+HkIGFJI+7Y4rxFKBDUxyzD7AwJuQVRTfQHgH4B6pXwBGD0KOYAZm3KdKsFP7mzpDQICqV93zIHS47LMXZXKfSwVSEGpfiYq7aP16KWmJiC1AUAXjbmB+eudZ9Pfe19xsqumgVc2exiHjTCr9nlLHQgaKCVnbCaUHsN4lfMXv8UiKIYJ7nThMxkTo0ai2Hb7BxugZpg7bkKte4AphH1O0suVXcCbI77bV15Ye15nfoYNNQTNHou+DuDrL5SPta1fH3oYaME/ZgVynVGpjj/1b97BKY1z21D6HtM1iY4ZSx1HTG5oc1OcGAnB2wt2/D3kSsPDS7BiPcMASEcY7wnofwdLVZmaP3/GxVxF941B5r+8geMDLh436nSPcffLq+PX7/OwfPYLGbrmDgvARgO2f3jP9vRoLu7OL+40A3foBvpC1iL1LHLffN3pqiCZ73VVbAHg7LlSlXMv8AkFPrd2JVItGOBqwV0tT4P2cECJ83uFlTosiyAegXS2XLjsQkyUCBJPw0wSa2edho6p/Ptous18O4f8Xx4XND41nxef64bpO/NfxLz/+cqD/CQdtkN2FOBiBYZjRg9mM4AdePCLUsnmsv4zi8dli5ZZhovstDZzXiQ8fPgCPz3iWFQe8w6RveEeEJwbeg7GAoDotc88JGasZ2heU0VInkD2mnGluBAAXYLtyCBQ7+7///VdAgbtGPMOJbter989WjH8b0F9/AugT3qsxpOrWZ8e3X37bKDbRciOe94WcWRGZEKiKD2olUALM1xdj91nb922Z3ss/xyH/z3Gcx+CuaAvXjuA67fxgXFGets7VFMyFBVMmwMA3CN6C8FYZjxxlYyyL+sADzBPEAzwmVrUs1YgyjfJLPRM9ejvtGX/MIta/Rm3/swv62Q89jH8NMmVptjJS/QhH+SMBd6oY+ACGYrWiOXmfiKzsAm9XjgpcdkVGtO/Oz3H5mzeuwJz82nDAnN2UuDQYAYDIyT6zm90uGKsLrQ1+BDKhPgX/El4iepVxhHpRq6tbwCeqGkYQG1E45Nbzycdis6wS/ACaQbzDKwIz+oMi4/x77F937+Lzy3LDa2bMusEfFjso/9sOpAmDF3ff6zw//JwfO7YR9iEoFw7s6YXWhYms4utnav4zCDdl+GjOc3J1ClQ9jJyVoUeuw/dFVDIIZ3w6qTITqZQ0+90iUSOjZE5LI1sOC1Rh+IeWie6KuDnYU8KuseMA601+ueKmj52gzww+HpPeDB6mlJG3W1DgeLxxOE0AbqRr90rFA2UgHjcHzOdtRQTevZ7jc+LP1lCZhrGGXnvUsAo2XlGEGWOJTGNOdAwD84w+zKJG42MNARCxleQmAglhxWoZPgQr813Ateww2BoyMVQFPMYmojsqVjCPjDxeYfdmBgYYyiUHhWO/DM6OZyQg5SwZbg5L5xRuNF/Pq/Xf81JiZSRwPqECVQs4nOtqfM5LMJt9S8yBPifWdcFyOGDOiWUZGGPBIoIxwpiljvPmzBERDxiwLCRlAolAB6cT3diwR+/vvUe0fd06cPvPpUgnr3PvH6fx0ja0vXAxNLZ1WBaFqmXRq3gARThsxfpYa1jffU02BlQ3yprhJ5RgRZQQDsdjlmZXtVdRi0AXQMl6tKv3hCRmkE5TwEU2TnSbd2QSNlj9EAHfCnMJuiu0NY0wiTIaYLP9ogJ4hrG6cyFLuQ/LJBEOx0dkLvnTNeiaO8BRwR/J1zTNBBt6pmryuCCM6rZWkeEDrWsuZk/hOLK2A0A5lPv52SdXaznDMBq9N6OEP01bL6s6gAyIEGHvSWp6CSEyz72Yd8dZNxJnieV4nq+QwnrGk0R57auTq7MnoDRBY9i69Hq8XI8OOFPj4dVX3p4/5wpznknLREdmdobMGfQq3S9y6Ryop1z/fFhMDQ+HDFSwns8WjOE6VuBL7usmtSuQulHqkmRnqW3J5EpZCYAirRNbJCACHwl6AuR8Ah1vc7Ds8uMWadpE0skDqNU0Amcm+vMrW/XmhfenvJ+0OdsQqug0k0KJky5GcFPAokHJ2qGRcWchY2AERTb5DDjtRxtABXBDwCkMf4GXXRQELq9vRzzpBsAKutB1jN68hbiTu+shAYcXj2QNueL+w9vdqKj93wbQz9IO8cq8TdH2bTnPgaIZwReAkoPYe4bNaZlOY+w1/LgHFU3U4Dsln26POMkqE0nQQdW8LrPnnTYWzd/xA5cZj8uAyMTq+FPXvwRu+21wD+5SFKOys5jaV0RgDFjZdkJkZYd9PJzzRn8qmNmu3TqZQtauIVJbc+M3xGQZpkxeZjzgEPJFpJLhYq4mCyIDFGKPhdMnAgEzeHYDVfj3Nh/2rPIIZiCK7E2XV7z8uAUpevUzd8TLnEajKeQGAELgw8F4izVxTp7KPKBqtJWYsJ7P9mzi9OiKGjhFYeXa+gRS6GjQ1MIjIGRJDwBz+clKuMPbLpr9zALtKHUjACDxXuVivHjSTIflBtE1ZBJHoH3AuDvvugM36x+FbAryrPQKfB3EUPa8cHXnmgpuyWTrh6TltkChL8T+7s8McHU0PJPR4aNjVHelcJvlLKzKM+q26iyKan/Eg67RZwSv8DGSZ0X7L02czbFHOeHQmUJXWXSB4gNO+NX3pIBoMXyILF5mwx2xQFyNYK1Gr1jvcP5txfLzAl4OCMV4XafhY8jTHQIuqw9eqie6L73CAxq8+lrJlEH6XHZXxXI3cPpywri7w0KEp0+/ZS/zw4ePEFX88vk3QBUf/Ps3AL6FY0ujKiqg0+D0zeH2RgGmr1lK+96XINoYyBRM8kqUHojLFEEKgVumFyB0C5+oi5vNNoh0qgV8gyQ+51ru6Baa478hTlY2MAkgbSals1yiVe7Ixuvis48YZgdxe4TThs0dnLaKWp/01I9bhS6AsmRDzpXcse70OjLvc//MmfJQjIuA5K86p099YirghRsMTwyJfZj+/J0CMZ+eAFWMW6tYI4+PAGpdiN+kXDDeKebDN2SwXhNoAhrfoLhta/Wu7oSvdI/9Sm7haDe9337Mozu2I/Ag9/te2W56LVB2lxcdJpDDJAAAIABJREFUkYkIhS/9uRNfoETm8PYx3Pn8hbyP+Qvj7ofgB3wEG37/0lB3J7wwL/XfgpeJkullI5zoxbeYLQHTqj7GttJ+p6SfIdfUmMqWQ43m5v4M2cf/iWh6nTJYDchA6j0LeFna/rHjYlmIrv7+4hFC2Esn9gGG7PXdm14/LgOA/jr+rOMvB/qfdFB/dYNSGNZgugAGmYOcoZZ1K2aAZFYclgWDCQsPgBVHFaxqpczevzni6esJn8dnfID12LIkMMZgY3/EzsRFoGTMVKkMllGWx4xGBJL5IhG24zpVjysiEjEZ/6eJ8TfG4MV/n/hZfobgEwg/Qa9km/enR0n193uBx4fxHR7TFKTXTtoe8aw/I7N9qyT/cXYRQhnQlCvPDqzIY3h5ZFMAPQAZ30g9y9+dsaHfhuLLMyOco6wnEWWJRdN5Hb/DUHIxQMoZ5h7RrYM8MtqsH3pd8zp+2hF90gHAitN/wPgwIF/2xvowVpXwV7+9czx+6PbZzTn7V+R5Gy0uFaiAxSQzqK1q81wfHcZvAdUTFIdioF3edwXLVXzb46HoR1Yg4IZHE6StTPfJlIka0uYIZ9Y+O60LTlvHraSSG4p/GKB/pNLA948fPes752m9dOHp5SFe+6FLcKU0f/eBrx0b7QHfueeV41p9r4sbXhmIa7DSHABesL2GFmXEuJVhhAnNXR7sro5wugVd6T9ou2dYNjVxJcbYcasZr/znjE1Nul/noD8b6rNZN7PP17D+JtaWkrvfE5bFU6X0Os3Y0K2A43Ofw/a3fs/6gO8fFNfFH2ekcP5RtGCwB0+xKhRzTqxzXuxHhQe1qUDZqlOQ06MsLsGKYbnktrfTq1SKGyGcLWE4UESli27YJwdIGGPjpYMgHPSWpO7OhnD+xXmEXIdu3NJw1OX674Kc3HgTDvR1Xf356k7zBWNdrSd6/A3v2c4twMGVS44y1MoYw6oH82DvpYEMCgB4Q2x0t+bb5S+gpCNMo/waQotFGHrVYWYKrjk4yZ2b0XN78AAWeNk2ywAnuIym4v3kW+laH2safzgy1pujQjRllGu0NzLfzE7OwFDIRAZqKFtvNfLXcN4TSrn+R+SemsgOvlRZ5Ncy0Y2sF1KqqJUPdEOqpEHAAkKMtw7MObPawmvC6Ibca1KzzXhz9llRIAJg8YLdq9HsJmPsgLF9nzIIxeQ3PwduaaIdeSCwI5v2dS8jOBNXlhGwMfYa/RSn09s1DsOZ9cOLvXodhnFV3+k57mmlNTk5WbuJwCsG+N4QSfkle7SilZvvhtpusGQGmiGzBz1dO8KQ1KmmrUEMz/HQebmNQZJe1o26c8/pqxPEpHYbsaT4pAVmXCCOnUXktMPL6QI5d8ICeMbkuL3F+vS0uTYcpsFbBE8g3FylCYC1Tul8qNaQ/Lrniz2yF4kkeAppOUgTyfxMKjiHU9TopAK3nHeZTyHL74zlmxHWt3rtJL0MZLnYfgCeqSCz1yOWDwPAHZ6+fLm4bg/LgsebLW8AoBvoXQ7iYlU0zipZf38nehtG9/YdhebRr26/bRj7ywLOtfFcw5wcVc6zeHnqJ7lH9bKXNFLk8BsQBrlUw8Mchrrbz+FAcWdeyjJUe0833+HC30m8OLm1jRjjyEFpDdN+4804bcu2IIY4cQeYvIYJkMp0pOC3vjdyFL53Apdqbi4bUN0+6FfOUylbPAQH1ZwbITJ043WE/uCMazgPHTwskYOtRSEPd+yCYP4gwoAaUD3oDu6wih7yACAsTtuN7rOXpwXYs+/dGUzwDF+j9cHPuuxfAN2Beo+UCmSYmjvSB8jGohb8eYH3RO6ElXx9iWeUDgO8pEeX/NJ+JwtQ7cG40ZoPIW9oSR3SaNdr6vre6Ru4FXJhzC/G0Fnb9r49AOcFvrkjngqU7LH5MvhVyTPpIIXz6SYcJF56SWFrLYQMQp2t9RbBHMHlaPOA2GnzXj4OrL/BAyEYQwci2GT8ZMHHIoJ1TvC0bGvxliDjYOcSCHMKsmk7LBAkAiACzufzOdLIDSskAqMtrcja9JlsNd5bwPnzbyeA3mGBVcJaP0/wB8ZP+hG/6W9pF7oPnpjQVUyv5DVCZydLyHqjVV3AYFI0eKoAMkFOOJYxrA2b0+LE1aCZ0UKi/rO5OD6yEg6qeNTiOeE839JhHwtRVlHtBztBI8CCPSFuNwuJqSTJoPeJMklUg56iZKk9gu6PoLcajkH4iicDK52Hgm466nfedeXetPlvG3BV8glhkGbiUtkrPVD1ypBzpjv+TeCkHQaWxh+7XfcFNr+VSN5C8Q1f6f6l6XkJ9BcG2I5e2bWkkFeIWDuKY718UOLHS/eoM4FdeftOAF+5BwF4r7pxose4Nnqco2nRt8Ak3eHKJc8IGUaDZ7mco2qBurZ3US3/fPmJGSTw9ipqM2z2a2KTVwZRC9Dr8g3l/QByf5MHWXt7DolWE6oXLSDCttc44QYP/9BBlzLay4i7/55eeO+HXvn6B/D49xzkAuRfGeh/zvGXA/1PPFyFsMMFh1AEASNYh8XN1UTQdYLIMqfubm9xnhNjEA6HI87rGTRXfP36gMEunLlx6ADCeww8jYGPRPi6mLNdoOApmCwQKmFGYcZUgUJXQOeaSmIOfLdfy+FBm98fmvIXDmi7/yc8//tHvPnfLLJt/NvA+utq0cVKUHwE6DOgdl3c/isZo7zHlmG+d74hrnAt/vceYg7va8rma8c/TI9+7wN/4I66p+GdQhs2FXN54QhZjCya0frjesSnkGUoKbKXrLCAmyCqAN4q4ZHJHCkM8FhwgOIsVnqNhbCSOWDCOZKjVLQy0W2wXrY1nQUp0qL2A7CZ36aU7Y9ofX5EVroAOH4w5en44Secv6wQ3JsSnOB6B3hZIQIwcAfPpcJy9xHnr59rLECV+2vG+LjWzrMO7keq/Bpjfu4Uom1UtgkPBNYT5qOChoCPDDkL+EA50lArpvdbUhUIKZbD0QIOaPVycgQSRWafhyF3J/OKuCLKbhRQ79+UEdGu8Ol0pVk8mNZ62sbSRI/tF+V/vXhz+dPvOS6aFO4J1c7IkArg9adtvqUdzm1+2yv9V2700rX9mj78H5f//Rnt5BCwsYUEvXLDAWB1ZcrAeMTEEwhHZG/sDcMqDrbJSCVC7/8IIEvNpVOJzJgVhrwAn2TZaPuil5iDWiaKwrJoTVlfEcpuKNyp4JICR4BOL4Oxg1gBzJMFlNDNTRq0ugNnXW3fHJYjLIPXIrzpSJBTQGW5uDth+Ce5eD4B3nEM1qe7wc3Ooav0hPw3ZvsLw2Q6z1tpwYjgX2VizhVzNSd6ZIPFeXO6A1oJcIerKVMApoKVMQfMIZtZtltFwqpxmEJlrcqqdCTB7mOUq1pKpOFAC5+sX5z3QKXIrPGKBk63zI4kVqpYFWOx7CVzVgOqbjSj4ifRloTUexBOgtC00Aq1Eu48VvB5YPFM/sNyMAf6Ycky7ssyNpHUTIxxGBmMNjzSawy1vpjDxsguo1woPde8LDnjEqRyH3cj5t5J6rSKwVkq33g5gxaA2fqWzymYExl8ZTCwLGpqtDKUbFEBi2elqWTWn22Pmk/P7DCebzQhDUNsI4Owl+Uvp0Q6J0LmjMyvLjH/EF3sO/sFfiAXQlXOOfYd5SqUbMROX0TVAk1n0a0pE8OdMOVI0cw2yfXpzEALZknHibw/q5QhDXC5SizjjQM2dn1WsMhR72jJjr5YHm/QqdqLCTkfV5QUze8JgJd0JN9vES7XRVICgaZDVCVxiSPjW3uAonNiVWsrBct8k8hQfyG72x7lDx2Or3OWwQbwLKiad+TxqAjG4KzCMZixzunVJQji/XaDtkbGfGS0qN9zxGcPEEgQxPeRadRGvBm/G0/RUR5Gq0bPSqLCw8x26jitHdspKxyR3zN4KY+Buc7N85McnZ6huAEpMM8n0M2x5MMjQc8D8+TyY+tlDcIFTaNNvlHoHlbx7LIEx5Udq+HYM8AwKJ1bwVnJJyggYBVfEw/yief6Nle3BgYcSCfOD+LtqJynOC3veyj2p8L2tAAm4+z4st/2ikEr+Nr2xGci3O6uByzYTe63etdVsTPfvalzr5K01wTPurCMiRvogt42WOR6NNnPf4ig43ps0ZQ8d/vIxJ38Ag4/80Q6/KmzwEDkXMfQeSIQRoBNid+k5/4VM2GE4us3JK+KAhgdnaiMxc0RdC14FaEFCwLkgXTkX1D7HgiaXfy1WZhhIYJGRxOuAbPmoKBwVsEN3wENQgWzgTBogZJAMbHQwCrnjZpAgCe1Nx0dlojRz6qt2scKMFvNtCBdQW+14Q+RG+OTTnaHru3paDfEg61PtwflT7XqOOy/LTJsb8iEqLUfUiiW47C9K9YPeaq1oBOaHuDviQDsshjM6S4dLwnYBM2G3LjhzR1wJXMF/C0eTCA0vIqOyV2knP3A4edussOny5DCqcNcbFkt/hJ4FDrZxnnYHJ2hb0VLCqgiOsVIVAMjs/VMsbohCuDGHZVexDzpQLxXwKsPIHE9ORERDjA8nf5M633uDlciRPu/6bAsKYsL9jAh1mRddbnf5iMeXMbMFYSNoF+aMMzKCcygjQzgFIzN4UPDqmM9MeFWgYkvAGSTOS8h0wOQ6cGVZG00BYLxMyCf7PspYoGq0oLJVCDqlQcQ7auiuozxEx5kfJmCB9WehosIzAPr+ZyfrdSxeLa+gKxjn4ubBoebn494/u0ZgompXwG9w/p5QlXwRroMUbwRqlYZDOYsu3X548mx4HGHz74wVmlqWsjfqiuiFdTgUfve6SL7o2IuYQO3akaatHsVxTMBN1r7NOSDXF+nlTYOILLCDcdLV+oOuWUsFpzoe0uk3NtxSD0mcVVJs7x+jhcF70iUMbu6VgUhIP8swLuKvht+I3VfhA5MyKAG0ZnORaDZSRwewV+TLnllstDrk0yMajEF1ye6IzHOO7y5tfs/PhYMUg+gCpB9bMEqVLbL5Z2V+X/8aoGAlvRUDxJ8w8OF9NPHYW0AYjyXOnN9/6Wx80gOtIon2IzNp7yl5dpwOPZb3p9cDtXCXz8+KtwW0kPOgQ/Oyc8I2S0qHFwZ//Up5dF56e6HF8S6OjMrE7TnFmsrmh7228kEnSbFKZm8C+fPEMEDA+sgYAb/d4iz7ellcFYWjkHsA1xK3OlrUw5zUWSQiW72lZOlXPNKetOUXa8C5BqItu/3KLjRMUIeuLJBgnhde2y/JoTAOJ/bKUCVvY816etFBb/L9/X5Lyf6f/zxlwP9TzxoQxLVMyCs1KUOjZp+xZD8leF9jMj7r84VTIyFF5znxIEH3ipw0sgifAeiZxNYiPCGGPcQwKN9pswqWzpXc1JMSabvD0dEG1+jNz9yfKVyogtKAAe8jOG/KdZff0IQhfc7PULhZVH8ldvn7XjUStX/yKCCCb3IjOy4p+qr/r9Wf/U+gReOEMrc4a2hSDCnYZAUaWDfRxYmg4LzAcc7USvB9jQmbiSU43CghfIcilFzSqsrCy509IjlXIYr121mGILNH8LEOtYvZ1PaQFg+LDh/2T1T6ykKYKKixF3eBxBlw67w4f5KlvUeJcY2hvIwjmqJ7ycEgVas3xpjlemlw4CIbM9nSwgfZlgJhSQVxp1A1YUoxj4T3WmSl+A1KTOlTX/d3i+VQS2YvLpV9OLNlU+/53hpBV5/3oVguz/64v6RwenuPe1eXzv/dzxTc22u3/L6T/btimYogDtp8io3HiNcD6GIhHAPM3aQ7e3MZnQCTjvgxflNbbHvHe/Cn5B9Sv0e6WiAo+IGfoGjAQl3+gSuFoQullI3GUpawHoxYsJm0Q3ChAWKFYoVhIM/aYWVj4/ljvoZmxH/qNjvMOockUDkZS9HlMnkzb7OZ7m1OqJ8RQWDxsbQVvNCCvtiRCV75JJ4BgWJlSJFlIDU7M/XpZty8voYwqDgvZKtIo6XTAXXCvl4SYNCa/KIyDyCZz7ZkolXSwlnn1YJvKmwnr5wR95AGKTdsupluSMIymgfhmUpmJFeMluIB0Mmm+ITvSUHY9EDxggHm0JpAGCwO8+D1qPR2u06pdaZWTaO7ZcKdMdT3Vya7JEA76VNLfODQeyOTFYrP+6Oh1z7eGpZTXL9xOEhbrgT1XJu7nX84D+5D9GchUEfwhnReOK/5NDt7cvK0NZlyxM38jmK7YlHzRu9rNuRwoJMNIJQrNZCGKeicrYZTuGyGUBsAYRzFnWidPA03p9rE3A1mcsCj8IQ69dQ6fmBXpw/xT17eeDtud1hbn1QqzwoBElfJZzrYZhszpjqmBhOrrgfaosnva59MP3eWWb8O0dxm9gE5ViNbAh7TEMAckPRnO1OhDEWnNc1qReHo9TRM/SwjZGjvdf+W3kDrh9tjTIo6DIlIs9dVTCI3GCqFzLEHlobO2A7tfPAMEgrAJxOjTeejM6fFHxsdHw/pRdlmC2nNf1hm30qpxV82JkhbgB9rlFvIWv/29bZTb4jGEo2AZBZZtZn1ea8OsdW/y3hIjB+1J+vFaoqakZtKOXaXcAyaUkNzcgbbb5/kxhvXwisx63cC/gdMB/2s792vOkj8DHWPb93dcFou6j8tvZSv4s9oZXDdXqiTWa4kGp2tGV7XEpAG2OgBq25NqPCL1v+2dihOzriMyGdE+G43EyPamcwWwWZi+FSm2L/mpxD5xYp2PTpV6lzanRYARqbkynoggeoVKZl6NflkMEUXBhP6RL2q/ZwZoXX/w5I1Sp04aFGewkIAN2Im3eOvs0RKICQSW1c7Fn1lb0eFewqU53ZHcpe/tzkrf+PvTfdjiTH1QQ/kOaSYsusrNvT8/4PN+fMmenKNRbJ3QjMD+ADQXOXQpFZdat6TjBT4ZsZjQuIfRme+Yd8i3lkusKdNemgRmfdFZw9w8CA10FnJGbFhxOyy6EFf/Tvp+wzaQL/iPcV5mMJo4NEWR8o5+3IhGvk6d7DeN40ge4qyps0ViePwleWSDC4Mx+tk7Ksd9DxAey76/nIR3gKesUdgC9MRc6d596ZJR67DRHP6NyCr6MjrKhfndcaopQG58meyoEP4FwMX4Cnxy+ZMBwHEFMX6YcyTuE1cv2K0fEhhjsAmL2F2MwA0ius8znRr3iKKfQfAYNCf1PggxvLdx3o2oJuDU9z3r12gEFLxhNxx9Lutcx1WJ5j7i/McNnPMDWI9DDKK2yoO/uF/gfmjncOj0Frs176Oyh+B+wDEp8c8AfXY342fDINp1zKYrediwDCqUtSA8AWxulW4Jays2es9A0mP+kORNwui3IHkk4o5wDELKlT9xMIz21ZYCXlvXBsNYS+Ai0cOlvi0Ss4Jm8hMml5of3M+pVrF8bADkmdHK+lbbHyal6qQ+YYQRohgdduMFk2IXw6LnGudBJ63rA2r/UPM8PZzcvnxUnn49Ilq+ja/9OnP5bujl2/ZDzPwLmvtRcuevanyi59pd1Y+Wev42uzW11/vSf++oNaRt0fnaOW74gXEXoyOCAua24LJpwUzCwc4UnznEYN08g6LFEK1HEPs/o1NaDNbFf811mY4hyX4+c/60ypm5uZ12b9c83fix6v8CPHRXvFNn57q/qIF7ftBkN4/LWO/ZlL5WqNvrf/9PbdgP5vaUcEMJX8XuNQXSFpszZgTSfjjDBw6punihTBdgomdzfc3W3YtreQxx2PMLxDQ8d7/GCPGOJCnqf9CSZnKMbwujU6RqQv8+fXITuzSmPfYR7P0AaqJT6Y4Pe4p8GN6T/iV6j+H1BzT8Demnt9/ySQXzaY/QjgN/xW0rUL77UUAQEEwwuPTAeAD3//EZ9//s0/f4362eG1tB9tZXS+3Xhu5e9f2cjck7GpRDMIIVypa70F4xoR49zHgSmMPDNch78QjAUh7HagG9oeUXZ7iVaNPWN6IsOsb8517UJDenGqiBct9Cv7QVwMw1sIPtdIkCIYf619EeCHUCC3H5w56Pghnvd7EZY9zZDgHTztu0eij99HRKQbRkCeOwXMxTuKGPxFGatRckB61GJNBj+jLNE8U4CYwc7OsHOpHHVE5ggd7pwSUaWXqFUuUeteJXz2Dvt7Fz3tYcAij+yBnR4rCtiS4ps4obBkfqfOevfHeR+/sVft1I0V5H6r3fw5pZlrSQgofNGrWsVtOdzbTNMtw+V6H65x5YtL8Fr2/fBMOX4ry9eLmMgXi7NpTNl4CawiCchGubkKwggPaIPXNDauQ3L3qaSgcoPCloSXOM9ti5rWTmMCw9NzV8RroaewZkFN5onjc9UI4+v6pV0DOazDGnob50eonLA9bOHw4xf2FnXwzJUfQ1mbTZY+pvFc4OagDnFVAnyV6zmS5KvJkGnOZaWxRy9ejyD3tOJpPG+hyC3Gfxq3VEcKJpzsLYP7tG96H+6l73jaFdA6o69jbxF1q1rbYj6rCZ10xVOme+S+BwpIKhc9WiowX0RQiIQxkjyHSChPZ/8WBm7pxFMDAot0pb5gqgMt8pVbGM2pGNH9Amleu92aG8dbE+hosDagbUBPA22PevBbx+jdFX9tph81VejW0bfNx7Yhoya7Ezifg5VYPSlR/CWqaWqQVhiWAtqLYwrXqAjXjPp2ZZHkvkAk6g+2TNnexOtXj1TiEBYORlClkOv106eTygTXSqZvKXDSEec59GaHv+P3X212+HRN85ZHV4N+ud3KGXK9t4UzGQA0WGQxEEOmVTe1SJcYTouSlzscUylAh6MGRPbNpNMWGRQqojLYtDzHGGcEOZBlErjPQkUn0lh0zMDSMqp9roNRUcjHxx7qiLTGsZZU5iNwocEwnrF3FyidBsvAq9NRhK+KK7B4LcHm88NToNI7Kf3UcgiOD/xKLUZfj36UhUeRdm089/7Na0zm7/78W1Hzle7cMkQ0Edzd3eN8fppjSuWkYVd1Z9UCH/Oo2PIMr7NaeIN40eATWU5CBLDh9eO3uxMuX55ir2wpk5mzpoOQWsniMLnA+f4Jta55igU6nLdUhT0+QR5q7XPA7AmJ3QxgKuccbE7l4KaZcL6mQ04DbMiu7rwl2AXosKx8sxs8OtLaNW9AApbXC5g+ngsjMaekuwUCk3fyKwFktdDE43cxVsVn4JO/vwUjs83I8zSDJoAVmnHjXVmcJCjyjo4ntdfSZH6W9Z/4mc5CJVOMzDVIMAw8Qz6QsO1lRqLcTMhDargyiipLP3hnwUtY4lYhbY81aUHT+Lr1U8DELGXDUlWtdTd8yMC+V2nOW2vVGW1ufJMolQePXhceGPJtIQMn13LgoSX68Q9bvNekCZX3S4OJAQMSxtDoozU083UbuCQ+rRBBGsEyPWn0rny6zTEmTBW8NU9d9AFMeSz2tfeazUFSGW9xX+8Nm/SA8xbZlAA6p219i4x1lmvs+79BdMC6R0Du+yX5EKXBIBglwuAIQmsQjJ1u5uQnVyODiOtMEptmFpxJc6WtZ8EQ2EgN1objxdYgaqAck7JE4A8auNHCeUadB8tCEgXe0+CQTssFLoTX+Qhb4HXqeEjrnGZ7FqppQHcYMhi+xFp/McMdgDfCUkgIZ1dvoygfatRc8nWxhrvMc851EgEu0dFD4MOzcEbeKR1MECsxcQhSdvGvmOVH5n4WuKy0COJOPhbZZtKAW0qSPXz4EfsfAwO/QSPzoPfkei5p7mibmcdEYn0Fp83luj0y7oxfB/A3L+kDSDqtDlOnfcyCFfXFPcjF5z5GyUABN7yDY0XHsAt0nNGkR9rl4fdwUxIvBZ02w8Pf73HeL9h/2QF565xWOhv4WryL2x6b4A0AkRYR5w4/GWFeaDGNd/lowmEtB6c8b7FmElkRKEMm/BikKXQIskSNUdYvONLm2ci9lOJw0iSi2CddrHJVwrHpdPKs+K421cyOyWjZzXx8ZnBen3AafMR2OuHxfA7nII/qBTBFcusQ2aESOMPKzcSTXM9E3FEqQ4jvkPSM5cHcmX3KxVyb6SCfFMA/FX63/mpPjwDuIQ+S4xJhNH7gYTOYfcnePEvlW1/XiDPPzEsCfHkFD39c/c9CmSFwnlUsPQfMGbPUEc8zHYYzeCvW0o73H/a98ssL7MQtH5jZAsBJfsIFv+F3AX7UklkDzMCH3JOrFTh88YcAP9i1IyzHdJMXnEPF4lSLaoAulwcd4jmynK+4TWgwe4tCLPTOIQcxA4cMcfrLfaHDWzjNOWLFeibLPCiTOF2LMl3qzvg8j166CkintORrby7OtzVb3171WngzoMDf8abnxlP6Wfnn67He6uEIj4nfyvfJw708gu/tX9i+G9D/DU3KHwBHYpF2rEGgQzG6YgybUVqKqaywqEvcyW45hejitZZ++eMzfnr3BncPJ+yXC57wEe/wIwTvcMEnjMuOy9hxGQOXffdrLhdc9h2XfWCPGjZZ+w9BhAFoqVWznPFXnmJGcANOZM7/2HH3Xw6GrXUYdoxfFNtPHe2Xhl+WQiIzit0A/B7E5hYC+vLzb/j9cO+faUwR8k/oCsBfr6N+te7+LW6vQhCrZABC6Is9bb3NGkthPdOofwLMLp9D8DahzwlFMMWezaWYT4KeUqWVDGOKO0FvhQYazkggYthTyTqvtcMrV+Fb28AfPqbf5/0N78v6uQd5w7t41tsyDgpoa5uJo+a4XEDw94/Hdb29qQAM4wbLRJZXzKA7INv8nuanuTBFqZbC+6TiVRFcGb1ksJd/ngPalSsI3vo/s33ruRP+c5zQNYOz/sr1+2cshAtrr+lqGkLmraWXPHE2oXLplymZ6z0eMRFGPoEbTfoNeJDjGzngkHpS/Wz7EOR6ieN7j2afigRGO0/G1oV8jwZgHyGsUFC4A+zM2XuU+EuNjv+CHc4i2Y25EMfF+zxr/H1H3YqWxQxI+z0S/Rb++hZPVBduGoAp6GSrW1wU1iLIyBemzszsF/yTiZYsCy5zfYJ+mHmqbxpprKTVOwoOmOOAGmxYRNsxBZjCrC0eR8SiVVULKuhTqKs4auL0SJSJAAAgAElEQVQzM0//LBTgByDd0382CMTcUAzxeaA3NPXU5U3VI4fNcSzXQ829rw0GGwO7DiBqz1tT2DbF3ozQHw3a3KCajFObEDT3aT2wnPHM8sprbb1veXN9JuM4ZLmEpNs2+zwKZlNWjTNzVC4Y66FrKquTjiw0Bpm2zo7XYe7fS/BOQdtyNn8dny70+AbpzbSf+YNhAbQiVCvTBBo/G1pTaETLULGVvg3Bg0G9jhzIRWn8WhBKxSlUhiAVXrdw7zUdPkaq8VrBVAaWDpJXnE6yhB0g65cDS6YHrgXXwBDZJIx0xqYyhP8xEjf+WYzy3mEuef17sU0iccU13aLeBWSzcb+aeIYApcHVFKay4J91P9jnDcJ7GMdrsfvd3T2enrzG+HhyA0q787uHKs7nAdgFb968wRhuGJr8RsSUmDsnH5WAMAN2wLobeqxFNg3pGJfd8SLuIPfcpzpqOoatc+He1k9MdN/y+um09ByTaI9PqQBdr7nmWVOpXYlA3VxeFs/XmHut+ZnKb1BxB4gqVGS5zqh95TVSnllQsCU8lPF/A0238m/lI182pNf77UpeeqkJAHlX8bUU44QBsjoTTDZvyn5OJzhs4hxeM8dyjCC1G++WuVTSZmXvy/vEFLH2OgxuEiQ+m0YyV/AGvxiz6b1HSnBm4Qr+RjpalOl4CffUKXGPZqmiAxzS+JPR+6QnsvC5XL8wKyc9oIEkVfSCmQr+5qgK7wQB0xrfnE/As2clqXgsGIhlbOtAj47MWeNdfA2mAtizQJAP9drTknSRkfutCQnYQoeIFhoE2ohVNKObAZuZEw80hBmyOK0FRZSzfQBRRK/xZsLcNd9iaVRl+brMGmOeucIj5/2MNYTjAdNBc65W9+z6sFSDNAe8KPrNswl262nASDqrHiCjw+txc2EHZCnxAbhR+57nOno5l+Uy89JTl8Ma3GoVmvKK+EDnPrruzy2iUZw9HI2AtaPypANuSGcPcUfWhzwHXuaxx1+DYPyhUHy8wnftQxghAx+ItDDESzJEJszuFRkhhM4pvuc6DK2Fk4HGMsee99j3YVGOK4zypG8j9mqMC1rgL1XDGE+g44CfbC18ScBGrJiq86sPf7/DRXeMX6ejV/LiMee3oEwgeAMP6vpozht1ANoaevRbneVv8fKZpUgN2gCBwqzPNMY838FzBUAHjzr7eUBEqicwzbH734zS54hY5qbSTu7J3N+JEenQdQVjwe85TwWI3MU1F/dpzTPizQNNDLvukNGWLJo+toGGzR0jjGOV5RxLcVKpGHtyBqv+FJh7Xdf1ZqvkwabTy9rJE/D4sBpfr3jmSd9Flh+WFfxyXM/DuO3w+s7Wudzq86U29VuHm+X1fXytOScBKH5Fh+CDASf8Df3vDV9+/vn5m74ygN/EM+uyRO0x6vyDAX9g/e74jCOMv9zmWpFmzXvLThPGSacKvDJjTPKDZBvq9SisP0J3YIqh8broCXCDfmN2soz929pXt6A+52p9SbS++bG4BZL/jPacHeJ7+9e37wb0f1Ojp7I3J69KAVA9EtxsTAVcMyCYJrKVwyzSZlvoZBuwnfDQFF+eLhnN+iiGB3zEZh19GD6OHXeXgUe9YD+fcd53PD2dse9uVDdzD2oTZPpDEfPUhUq8Mgn9ZKKQ+qQFYWLWKn8XCPK9yxDY5Vfg57/h4X+4qmL7e8f55/+F8ctPAID3Jvgk7vFVmXAyJIoZ0Vxxk8AyvXszX+9f/gTy4jOPEbV/tn0Uw3v7a5j0Jl5/tpEZ9QhFi9RGAmQNJtaWxQB661CMSBF1y3vM9/qtCT5RnhGva9Mg2ESgJKop1AazIciIjeqYwX5zfy1sDMHc3RAlF8bhjUUUOpzxN9TIjpfbJwHeBIw+5sUf8daAjnfY8RkGhzEa0YFIxYW20MRbYm9OA0hB58VWDA+1rxHpr7bwuBcA4xJ9XwyjjWT8PYUcR+aM1GnzKsv7oHK0u6BNkTiUYR02vSczxWFh7HMGRfAyDWVIg+r+jF7Uyr/z/qnIim+zlug1A7d+fFlQf045+818hgGLEqxu7K1WEJ9H41QlQOmkCp03hnfru5vP/Np8EkCrGHl7bc0s1I7z3BO3moTHfag5LDywXeItio2qyAHTfEoK8iLFQsoJhdBrcZ8IihHL/5gmeDu5QVs9V10qciQjO30cXN51hmUBE39MuKRwDBT6ok4HqSxX8ZqM2+keXl5suBf5rpA7QT9vOBrPK71qYKSQR6JHRb/iIe34a5MJFzXCJPcqdgmhgLzvIai0tkJU1sMs8y7Gc/45qi3KHlVUvewiVFG4FUOXDuoI5xskFOUK2xTOUolsnhGjaaxCvL8y2AbPM6fgadW9PnrzXB4d4WSoiQcF/nnEGja48d+j3j1Cx8zrpgMGdPH0im1dboUb2Rmx0SEYg1HugLQOnDRxmcAV6CoCbYJufQrBKH2XbY0jkB+WLeOaL8viEJC2I/ZUeQsn1lNX4gfJz8oELlw1CaEs+bz1FKm5AtaFYKa3L9e0uYCZqt+o1OCYQtkMmUziIi0f27ci7nXcwcZmUMx1b2Xxl02pvxYTpSENHt5n1EbWaYDWWApGavfeIOIuI0M0cFucFBGYUhllOCpBmGGh0kWnL8hIdpsDnWfI1mdwenkOZSotnHeg8XzWYmVdYANSycGzw789shLMrJlT+aEkEwc6yF4z6sAMW+uL0WHC99WWXm83kMYYtuQ/bd1WteIoUDqZGXZIjzxTBMvbZARMNRjZ7DdRYJKXIxxe89QvtTcPb/D4+OjnsU0HmAmugi9fHh1nHPK1921Lo0Er55w8nPXAiQJg7Lh/98GjEvsG0R1mU/FLfOM8fJk0EIz9kXO5TXkz+i97BOQBADza3h7nGrodSbAT3rCiK4f3akwKJHkEMpQUqXH9Hvh8h+AO0zDU4LLDHSzrmrKMErM8QSQN8TOycvLHfgm5/Qp1ZVmu0vQL7gF43Ffl0BbsfqNR0nk7WT3MPZa3TBB8OD6yvrFyzfJZZMpiZaz5VTFi1PE2ZtLyZUOq+62WSyg9LvA5BzqixnXrDWJe4qLyImqj1Pw2WPhGehQv0rAi4obybTtN/iaepzGm07bBI9I1T2nrAhvrutYFzUi3kJW1woTUC0nrEIYR8qjz97w0I2InP9glDOdiEDHAthiGhgGuQU0wwimzyZjp6xNGXd0PYHGQoJI7Sa8Y5GDdmp8nXCS+s6IdYXR07mfJrgMAIH9nQHGmabWcHKIeemsYusOa4a6foKIYJXq4ieASUXBt29B2RGQ5stSIZ40J2DRmI3J4Is5SQ9DRcG6rdcZRzgyQTBrXqkUJoYyeTZriJ9DTWHsKd8cZlKAASETyNuepnJ932jsPQXV0m7BvZZ2Pzo9qXoqPre6VmvOte5Rs5H4OEY8Cp7HDDGgNTwEbwUHgnY8Ce5QBhAB3xghyrtnEBZvFFotFMSvCl8ObtqnDEwA7wQjEYRL02nskzzOMzrdCqEoaUflRgeFeBPfyA1rruOhv2OPMbDLn5tkj3uGjfMT//Pv/id//n98B/IaO9wAGtt6x9Q1P5yfo2F1HaxoZMoozqSn0V/U5/ug7fXe6S7htaM6TqMY59vOuZ8sITo++lnBsDlgPvmbf1eUk6UBznSxTs4+xF96MkJuUAIbh+r3gB4ZxLyaMdJk0zkE09DHDMiU7Yr9UBBIhqbUcZwFFJMYUl502ltEipJQ9AABr4s9qLeYF3EmUhzT1UlzEkZgOjr15CQyOQ9X34BJR+ZnYUmTyFwGFXtDLjfMWOpu0XQcsjaETxUnDkIuvY/C8qs49t4C/XUfyiaPwvUo6AM8aMM/MXDRmurHEFZbjTVwQPLtv/dQwnbpnLlGbDvsAwk7ADBVIeGQbZpl9EEDK/orHGJw7bTTQSejB91GeAHP9pMHQgh95jK7uMDmUa9i48Tk25xiEVLOuXd181ddB02Wk04m+S8eyvFWmInqm/RA0JahX8kkNP+LeBNt/dVz+secwMw37caK3FVTZfn9hDH+88Nv6tFcsFoeVdC2cnW/QEIABNnA6kec3gvGk6DrLeZMFN9h8MYt4UDeeq0384uOIdwuvHDSRXbxqds+3gxrwmR8LP5M83QvNnrmkbMvrd+Zr7avA8L39C9t3A/qfbN8SJXbdqDyk8NIQ/FAKpWaGy2XHIx5x6g1oW9Y8F3jKq9Y6Pjzc49PTE1rv0DFm+iqsOp5hhqYPGPYRb4biSQ1v0DB6x2bA1l0BNszTMDZxZsZHGyjrRj3CqRil1xCZN6TSprkkCIGgiYYx2g3jgODHEB72saNLQ8ff4eyCV1glsvlDplGcEdw1kvt9mW8i4kKjPqgmQfNlvr2Hq4IrOSnuHN4Z8CkVBhTOKNAc1qf8KwK8M8HHZuX3+T5x+aFO3uJdHGOpe+NpakIMMYPawD687xFZC6zfoW1beDr7nqSgbkjFVq6ZuoliYCRh6zB8FOBHaZDe0+Os9+51U6RDIelssJtNhTLnZ2T+sFIRY7oWRnckpwFGPvHy46sBuI/f+WyS4tec0kzUVeDnI4B39qkoyJYrJx+Ed0Ckda9sS6W3k8mSm6l5OH8ApZYsfSgl10qBNOYNtZmeKLXWvlZqALY+I6UQggZhVQSqF4jRh3jOxx1nyGzOWamucBq6yCulPkIoS5mf85f5nGcVyKGMuuZyb1w6n3jVKMjeuudrPWeEbh3jN3A6eVcBAEnBZ14l69UFzVjC+nz0CwM4/LR6jx4HRnWErf0ah/zcaTEYdthZYPdUxhTgCkBrC3NJr9OpwL06jQtf3cB0034vz0HFhfV3PjdmI9zz+M7m2l0pt7HBMK6Utrn2gkzp6vA9YUKbZpTSGEwI47hLDZCTQM89cB0A0RTygTDGAlAqLuD0XLAaFvL2Z3Ykx23wjDVN0SNqh2ncW3FWoCOHHs4FFcuNxrpioFmMd4JQVPtvUiAoo09j0cY+PDtOOfO9tXByiM2k9En+IRbGU8WjGA8l6kYH3Jp5mvEoP4MWEWKhXG7EWTbH1uIVTPsqE9YEFkb2UH6Nhr039H2kUredukf0WSheAw6bCCBMmd+i1qSv36h1lQ1ofYOpZvr33jfn92LPZn9ytelcMoikQgthWEAoFKXVM6kJG46HJ5fBiIw1EhyROlWg1jy5hCFqnrlg3GQ6xrkiVvO8qa7GIik4iLBBQ7uqpwJXnZ+f85SvUevTyHvAU4nC1j5yjjmO21j0eTZ+nj6LOV3/Xv/8u8mzYWbiKQqEMXYvXwCWQ7GIYI/0jDYPxmT3DAJNRWmwbItzUiqNI0qoKsKpxJhpIR1fuqMu8lkeDTCfs0aYK5bMNTEe7r0rb5H8sJ8zwkrcUSIDeT75nWc1MOzmfYt62Yis50rMaHNvnU62OT5B8JsTTmo6aRC3x97SETGNJVL3knxOyyWmPGMJOIGTNHKHZcpRK/TfcMxfVR0QOM4jdKUThvpZGZEC9LLv6PeC/WwzpbgIxDx715Ftcfw3UyHmGnD9Yz9UFZ//+A13D2+TD3PHjwnb3KNMpw1MjxQ9cirErwBjFCsdtvI52Yi4n2CqMFyc2MRe0wBW1+mwY6WjFSfIfCphDQao4ItMLmFm5pDsrvbicBQ9lX1LHDaPY1kHgCnlqyNVTiCuG9HfZzPcV3wjc+XmmkmBqjezz+C50rc5B1Th9jZfITEnCKbDiRR8K/VKvi38VZy1ahRx82ELJx/JSFtDcaRjFpfAXUzZzIxHibxNINAYHHkOwjGgO9WujCAvkduV1wvaU7B7vmvSMaXHiEJvFlFS01X0llMjv68yoy3yhECaJdDSWBxYJPdVgr9tbfMsJbI6FRLPO852+VxaQ7OQBSXWSsjv8WwWfEeEiKD9aCl/E+8LGFnuADEjPWdpEsd3MqPgA2iCXfEMd1IcNYNPQrA6thv2sWPDlnxr7+7Y78Y+56MseaOGtrUw9BnG0xOGjDyoFf94amsrMqrlKrhTxcCILCOUrdfse/Ns8qWed5Mpm/tatDD8+I4S55oOr3MODb7cvMQAFX6xxA0tqgpZ4l43zsYcYIkH0+mBCpPSWMrJ8aavr1jwbGOkTsaNjj6GvbkUkgYPM2S5obIkAncmfYRgy7EZBuWKoH1naTjNlXNdkBkuZs5HFlpKvMv7reIHXpNyoHg5QvUxjqgBLuq/UbdIXHYngi3KDPb3Dfq5o5+25QwCwHkMNPyGbobz+Qnny6+xbne+D2qevao3iLojyul0N/mj+HcMd/IQ8ej2O15DnQqsZPSBZ+/ScJ6wBtXwPzVgDDrotqDZ/pR933NhNTKS0hcFAKR1jMs512vmDXdHDmZA2H7acPn1UiG84EXwAQCAL2JoYSyXgGslnpBZGgMA3kDwKCyf5b+dn84Y+45tO2FrHaeT4x3uTYt0zzosHNL3ec6CRxZ0dOlQGLYYJw3B5CsDtXsAGiwDT6Tg0EkP1shrP0rhms2zFfMcQWharGc6KJD/aK7f6+KOOWmAFg1Y9c/9FuE9Mn+xyLy0BZ4RyrlGvDHpzCx1OeHLf5OJp/mww/M4zx2OSk7l/hEyMsnPpGdPMLvP76rebsIG8CVK5XCcOb2ch6TO02IP3umRdyufbq3VP7ORfrXD12UOiV8OQzIA+z8GDL/9xSHMs3T12/MCaw7CndtXPrOycBPefW8EzNADP5vblhl7VA277V76Lp7vZV8b0I/Oq/GSDwWo26BOKQ3m6k5YQ3cvH8wI9OjLHZSQOIY8Hnlv0l2yMSwD9h/RKntc6Fb97spxqMjaz1574AGPQS7f239/+25A/xPtrxnPsQgv7K+Bgkx4X6lijIGznYFtQ9uArW3oW49rwjOnNdzfnaD7WAzm57Hj/d0b3I2GJxg+iuEH/QjoO2zvL/jy6+/BnHX0DvSte82/qD0zlbpB2EqGXAlGkO8BKUq3KTw5KTBI4cM/NffYfGfNTY8C7PiIL//vhv5Tg/4yYAIM+c3naT/C8FtBNgcKKvOrjlknncRY4MnO3v79bziZ4deff5nbYHYTwVVlMIdeKvgA8Ej6j+RNkRNeFCfla7xX4FPz+Qok75/COwneCltUhpaOAQlFYcCMcd1jr5wfGc78iXqqJSvCcuvp7Q24QkG1Pjfqm46ZjkoixeNDM1gHNnmPJp8grWGYpwv7sgHtIjAR/CGu/HqwuWpWxuH7JRhUhJTfBYioQ6RQXxnKhVRaWecp5+JtXPGlcpN1Q17R/DkWhu+5Myvz9BncNfr3G+Y+1jF3vIHhC+4BnDlWWfedBq5GL3ShgOnfh1yB+/sTVBV7KqWRDIXBmShAcDrdOXO8X1wQcdcJMP7GAhcR/pSdNGDErBskUtUyIeeEx32MGcGK8EQ04LxPwYYMfjLhMcpkFGUqFtOBoO7ZYU9e+Hled+OC1/DeZpbM5KualDeCVORnUtAcx8pu27GPIvBU5v2qxvuzz5/C5sLAXd1QGetVcZ9yfpm8ikCx487uAAj0UYGHHjA5N9Xvays+rXhL2roCgaAz1WVf8WdrzpqwZrcb86aA1lrL2ohNAyaD4a9RzkYB8k6AM0KR6ye1Rt2ULZjCIwxy9lqs/e4+6YKg43x2H+u7u3uMi2DYI2DhHHaSSRvPEqpJSWbXn+d10WlQZ7JYCmcVQji+5tVafblyD93NSdWVkydDpiPszaMdzACon/0WqQtToBI3oCeeqYBfgENVoTKNXUKkHfhCBNh1x7ZtqfSjkqJBorb5rOHG/eHCGxSR3y/sdHQwCEwhkvUdLZRGLph7lAbdwrMue5sKRqm0w9wYCRoqzYCgf977gDSBRgSUbRt6ZgNxLA5xgXNrXgO9Zc352D0DbDgs7PAzvG3+nLZ1NPOMQdI2x8jBZ12F+pm5stDm3qQneGshNE5sivzk+3JlRObZHoGn2OKsijT0FrWcDbDmay1tADJA5yJQqE3h1vLZR2chs9V4noJivffryDx4BPIwLXM2kLxfOymV+yiYG+Yccj8xmVp+qJ85X1RsuWBN0PvDIhKvKofoZCgiGMMzSrmTmyvFqUnNsjUSJ0YONCLu4ZBcyT37p0GZ1+IwR0a/I2BmDK/364pGwKKGpivuNcfJ9VsqAcdeKhg5EJEE0FD6u+HEImvUVA7MSBrvRufvDAMUgyk8god4pE+DYF4fC0F+KVAN0ulGprE1eUNGfkICPx3AoG5vMnuuCHbfIAt65E6jnkWhRCtKm91dyRVrNoFqqLHl90TEEHg5kb5tkLe+VkMVlyct921wSrXHIz0DisiGsQOtIxwZqqLYIH3DeHxE20443d9jvzzBdsPQPRXiUwnr/yqilvTdKc+jPp1BBys5XA/UsybBd9ao7FjqJ5n3huy5x/mgQWTuLXnlkHcSuQdN0T3R+kSFNWq/Rh5Hn8GLsKtmDeeWC4yzuIl6OuUWvqk6lsa5X3k7rmPAP9FKTY0Q93J+d2ZZ8IUOGVwxOsUdXDIK/pLCy0ye46izKEtTeA72AJbOTR6J8vyRf4QhlfqLsi/Wj8r/TOEvzNolyauu/cc8uxtTx+4Z8SYen2codQ4wyE7Jy3JsYjTGztUaey3fI8tbshHkVVVHGn0FI/FvXXMrPTUiIcKiTOP5dEKgo5Tl2sDceCpC/qWhda+dK63Pey1yFQW+dbpKp0C/YINn8BjijgbNwvGNMEQcVFchHArJhxkEw8z75hqFYZ7yoEfLNsAEo/q6Jo3lX8yH65jndeJnHcMz48HXoW8dIs5nnU53MCj23elB22bEq5mibx168aCBK74DQcvS+GzpIOaRw80dvzBppxvRLeCUhmsitzhnFZcGPpMohbfIe5ExkqhIxHm2Li0yUflzWgKf56QKjt6fH4bbSY+QujDaRZVeJOL4gc6zdBBFGCucHjtdFwGks4wA8NAE5yZ4iPue4nH3ADYIPsX6PXGNzHAJmqAxznqqDIZznIkevImaYUBxoqMAgN2QqcB3rmWlvzHAIIlkl3ztI/NPBo2a7wZ1XH4mfT0u8gfGZ0HrHdu2BX0wdyiIV9Kcn//v/yt4nDdQ20EHEdFpmDptJ+zjEo6xDhdjjIj89ejid3fvZm3qwrsn3lODO44fjSm+uRI01sakEUP9TI5RDcwKvXiWwTFGCcKQzGxQ+bfVQHOI9hVmI5vL/zlww5LFJnnqgG+OvzV8gvPoA4KunlmlD0XfG57UgL658bx39CY4tQjIEWCE3vKNNOxQfIbhSRVvWuTC68AFEflthiab04IIHBF1vXjKGuqlutz2H7Qz8BLhiohLY22pdEw+TjWcHCLLogD9LjI67u6A0APeLB4j4inuCbTJO+ReH+kxDd8W/PZKkekERL6G8MJ9IN65jDFpK5ILQ3CvUSZz6l10aPTnGV5OpuHgP/lXMySOojOI//qUY2Lk/mc6KwVf9YYwIoJH0kWui0TGJ5GSOQ4Z4V3ndWy39OWBltbfeeae6WfV+5fPAkhyLbNVOUQRlQwBnP7L4eHxH/9rjv3Q/4vjmQRlXideovalaPRl8NFUB8A69VF+56iPXh8dfAodjbYtMto4rRhKPtt1Sq310F+4PEnZzubgg5+bPBKv0JBjhyl283Iiu3nG5VF4k9A0uR2CtLzwf76G6+K9Zpkgy8tXVQ/f2p7b7+e+r43Zz0Qkz+ct4zlblfmFBPJ7+29t3w3o/6ZGpPLcb/5q+VrfVR9Br7ko6akfVA53IvhyueBt3/BgMhnfQKYmjvz/8pk7MrvLT0nN6tCubvwkwAf5BR3/FeuiaPYDTH6HyrU3F+ugH+uIz+SLqyNxB/D086+4fAO2zGj2eEZDVh37U+2jrMv08Zk5vKaZ3V7yjMrJH91kSsFxjOH6f4uk7YWZkdayXuyxpdd5K9kEZHr4t4y+6/jc3QuztYYP0jHaZLSPbfrGr2fh1nftmWuAST6tMmh4/ny9tn0W4N3hmc9t13PfVzAyfKGc/LomU7gkc14VkOnZB8LE9YzdoEuh3/fOmWBPibVw/bOjhCMJpjkV0gBkkXBdSMnIyH8yQ3JsBz7z39eugMFwsJCiLG4ql67GLWVGNwDDb5v9/FPbN3RpOEPgdb/sUWFvi3I2r7GrJWGbLK4VWnDrNNiBJq3GXr4uDGVGJIQiUNbnJczfIXMNvvYMHre5MvctDopk/Scqf2xGUd914OJRTUmVUvFKYZdUaj5LIm6QcWZO00ae/Wtc5EKrMiLDJDxUI5IxBZ3JoM9zvRo1nmup5A5Qzww68fVU2nGvYk3aTCPsim8XnFDH1DiHEPbkcIwQ+wuNMiSIqHpOvwht+XlShhhURj/VSqCMRGUNTajXLxeEAmq4QmFw7c1gvcXe+3tB8AiMNu6em1LEYM0Nkqw7bxCo0gkuMob07unjA7emwYc6bOYJDIE445RlOgosCKYIzUeAyfNEHB83LMKaTPzf4PTcVNFbx972MAAFV2QyMxuQdiScWu7z8r4If3ndX22hME6DFRXIkK87Is2BlDcTn3Ml1ZjxB1PhBuQemHmEPRhRowM0oOQexRnx8gPzTKeBkfxW5ZdNwmFpXklFHQBIMeRGgs3D0hQsHXvBCHhGkeX4GfEW72nspxEi61kG7HpqTy14xvkOGiinAmVdZg2imPy6yVTMgpmLCr04ENCqPLjt6X9r/usgijrmNg60SFufo4p12n29W4sUvgLIEY9+Td44PK4a27kuDQC2EzbiKjWMvqOJ4PFy8bGMiD7nnVGeImxQN57rcHn/cI8xFOfLOWD6oKxJnsXn1enZJ6TjAtzdYTw9can+VFPSUhDlFZgo/V7PhWf0ihIu3zS4IxOCl93r+G+0YvLyzwZ8ERrR+fs13aSz1trZIpDlR8OtewvOLGO5dd28PqLPD88hBl4UzDJ/q4Y+Q6EDRdgQUndZesl1WeC1nMH6/lpxLUhviaRtz8COrevAq4x4hfhmn7huYlKBdMlIKn63jPfqLnhaZDiu7a2DRlQ3dEexcpIAACAASURBVJYUo8bnBP9S0knTScvKU6ngdCcLN47n/YJJ15OHamSKcpEoQ+Soo6/5gIITc93yYghaGD+rO7gV/ElYI+6ta+TG3oSHsn6tLCYdF9e14GKscqPzHO5s1Xv8bQ1Nejp8SQuHrM0AdcMoaStM0C57GaGVvteWkWxBg0cYxVDuEDve+xWuxAJWAq8cD/8V6KdsbRmVeYWsBLMeeqwrnU7954KbjyO1+arm5ZC0OKta8kZlOJnJQfwZJaCBw7vk6eP5u17nZWevUJHDeYObpJq4+zBPzwBm+uhAQjXCV+p4yh6RV7jC4oEfToG3TC0N9u685lmumr2LlPa/RWaV6jj4FlCgv/fzeLfdwWBeQiLGfnd3n9GTl8sZwwb0Nx/bm//xkBtKR5K6x0fAssjgWBePRlXyjHWB+9Y9Eh0AMwOdLxfP2qDxPbM85aNlefZzut86NJZGfFUrdImvD4lRvL2xoMW+GS4HdUMLWTX1VJDAiYaH0DNe2O/xnFaglhwKBOIR1DxLZZxXNyyfJtA5apV0Hkg5XyJjCnAVBVrAOO9ppZalHNbEv5YlY1stsWHHOeZIr/fGAsfc/pU4fo6T7TSPW7bEjqQFiUfWuebZJJ6/eqzgS+GNbp5ZkC+SWSbpn9hYT/yf1a7ZPF3O+D9z/P/KsQuQ5yHl/uMNBc+aWgRDtMw0Z/FjdaqJGws9mlnrpkxpU0YkHyj5yMK74C8taL39+rTbC5//te3WObgpp35v/7HtuwH939FkIgge2eAnohERIRFUrRPoBM0Zu2GKLoLTacPj+clTmAog2waYQrvg1DxF7EcxvFeB/uFpWs4i+KCCJ7T0OM0hUnv6NYTymms4p3LZp8oQwvCHAD/+suP09w1Pv/wSkedT5koEG3ek4bn0ScN6bZTRz/H7a/HjhtVoPkVC35uP34DoOKZPNzG5hSH99f1x6Z69wwxmLbwCQ7G5D4w2MhowI/eiQ263f0cG1lyYg0Qa0obPXXDXgTfyBe+k4UsYj1r+NXzZABmCLx2416oUnTBfl4Kvn2UqKt8eeGLqjjNDXf0xp3EQzmF4G0aWL7yjal1f2RreYeAjKMIC18q9fvhMAxsVDrPNCIn1IfNbnvcqTOlhvENLWvuEKck0ylwD97AXj5SMLrZTx+W8IyNxAVzCi531+aLDVKTsOiAy0BkZzMivRgMfx+PX323uWf90uYDhLOvSOxTMCMlV6jZMgf12e/6357xNv6X9ORa+3BMGGzoWzNqqVQFy4BITRItYcpWj5/lx3RIFn2vuZXyLgTseDX9exFj69fdTKSGiMGMaXcPYByCS6cRJR5jSOiPOo9GDm633qDjKTAzdNR9aah+6cN5C+ROMuDim7+GRToMPccI4G6qDyZFtZgr2YxsWR/PsFPLp7BEF/b5DxaCXJ9iY0dKKKXgbovbYPTCeQnAWQhapST4p7tlyT7LuZBmzY+Ge13cAm/m1VCx71EOYiEMSb2HkEiCyhhgs03Tp1b6sbRX+OTlZPhcngjS0VFQ0DdZjH4jK5EGgnSEysTJjWZQTIoJm8QWf3fJjMgitUhfTqCMYBkmQzjEl3jSCGhUmAhg0hD5BGz7EPeDXtEWWjQ5Vw9YNsJ511rHvkG4w68AG0MmgncLoSMP82P38WUfrVgzsMb5E7IuqG6BDVLR0LCNPSOgKvnFeKQlAVKrSOClxPaM/XZlTGIJQAGkTj+prHdqi/rkeI84txrp+V40etdXvXou387qbKK7gztIWo+D6SyGisl5r816HYwveyh3PpLWkaYw08ogKv2eootGRI3igxijwgN+G7WoN4nIAmNkNOO9cI6YnDvw8qlEj4E8mH+TPdJyYmRwC/plST6nc0BFKDk14mpHzjIT29TDVjEBjf8PgUXzB+1SMxyOcuDYO+WlrEclOR6NI7ShIpWDMDIYJc4RfGoDJs9Q07nXbkz87foGi0Mj1huOySHNQa/RpXDei9jvTm1a6zv1ajPuGxEf1jCyOn1b2rYlHuQTd612AKL0jcZ9tgF7CxE7Yie3XMCTocmZ8XzQUVwKD7twv5wmZSYzKU96zjNciwr3fY+gZdByrbWZNEBArTHiYvCZv22Ggp7dnv588ogV/yn2yWBcBPEosonNzL+fBwSaCvTwPMQ7yrNzveGQ8YwKpmhdwevBH4t4MTyh7GLSQcPkQY/wiWNdEZuRt5f+mg41Xgzfz6E9f5gInqEaKh4QDVOU2adm7Ob4aPejpuLkIVkiDgDIf14fdKabBa95KemFZpqJGGHOVifsA5HV5plM5e0DMwrWKE2/cL5uZLWCwC8dfz5LT6N4bpFXHRJnjzOe5S4RGbV0m4SZ+8GjxMDiH06EFGSY+b61hjGKIjsVt5IsKH9zKGvhlLqd3aWEvb5km2FHPdK+a43ZZTs2gdKDiHjY/P80aRnOe3VmhqJcrmACee74ag+hYh/JkZnIibcvT4cuC4tbtvcrEcyKcbJrGln2m3kBapIcNxwcvDTcAaa6obIYW8kFrgFpDa5eC4wPHJD2duMB0BI12kN/3PfYwcEDosRgJSecyLfyEd1kl/3hi6uTWLB/1lcQ5z37ShnmuJvyKBzQYwKJvCa/kHcKoWJsFDw2NTAUBP/V5K3s0DSNPMIjGOZdJHx/npYXmEj8IZhhEnYEhhEMAngaakDEC3jdp6Sg1LPRsidTZW/RP3Ea8ZICNuQ/z2joSw5ONwBsSMhMgZrh790OU1RI0VYxf3kH0Nw8E0LcOJxD0D7Pk3mW/JEyZKqwBY48sofuOyy97PptZ/vbLGX07geeB4+OuiQiYs306o89MNJJn1XseY4AKsIXfBCDwsgeM6NVI/06lD3k+iONAHYb91wHFxzkWWXextup8/bVm8MhZqM2SFZDQRwIPZrPmsYVDpmjwug3SBp5g2IhKpUUKd2TpmcmLz+f62sW5DViv+Mcdxw9nptBgzi9r0yPwGnGzAM2ALhHpbwZL/EucH3AYerjMkFXOgOPNdFXCJNzTXa4cUY4y5SiXKed3AOWESVcIQyPgo4eeLuEloof75o7bXgbEZV5nwSQjgmGIfHmeKFAkMgTB9eoc611Z1wcUHizpycS3ZdNyrADwIejoH1jbj7FEvx9gdOFHardCuuZw/0d1IgGwDmJiwnk2w1nscB2jwT+sG5SwNcp4lv4r//3coMt7Rp6/Kvr8Fe3WuV0M5gsNvTGkGL+KQVTdKWd65kyaG3xDyrFBU9x2NeVMlxsDHuI5i6pTVnL1zDK9qvH6Ql7ie5sKFDluzDN9fQMe/Fo79vDdeP6/X/tuQP8PaBNJTBa8fsdfFOGNK5ap6xgRc7dt+PL0FDV1/N6tb2DarDfW8CUEZz6jwZnbbZFqguo/0ybRR757/upASC/gpVpPXOU39PY/cbK/Y5ef0/gNRMS2fh15MrL7VntvkzB/Lfr7GPF8q6/XRo9zTMd7btVxf22zwpS8fJErJvd9R289osk8jYrzhJKLbJgEJolqw+J1SW9OFxSCcRBP7846Z006euuRRs6VsF/TjZsAb81Thb21FaoIPobboHS9FrK8/hWyNAwlhe91+xJn5R1LF2A6XpCBvMm8HHo8KnqBKrBWJoAe71M5WW4oCg6/yRW9odgMJmHfZ105Y45nKrmCB2IqZDNnznUUr/A6SitpKWXiHr+SfepNYL02UlOYsBu//Ye1F4Cq6Pu/uZPnjUi3OO4/3xpKZNYrmkPMGQJBe7qD3lsijMb0j2G4dXmwQDhxiiyEpnwHJGWR+Z7vCNPXzOsUGKtSj8JlKiMEkDvAzq+c7KFR8TgT9B7OqgBUlDZMQ5lwrAK0h5Z1G1jv/JZg0CJ5a7sypJfoJxlXkKOhjKNBWsRTXpL+W0gjFuNtzZWSEiVAqJDJKS3ndY1iYXpWAdLBqp22iMSPEhFlcSwuvuwKREpN4oNUTke0ttdULan2uMACSDfAmBI+8FE4CjD9OemZ66IlBX5XHCFSj00VIJFeRgAQT5oAOqAy4XCY128UbZAxsPUOVUXXAbMt8ZYBaJFeFtsGyA4MCVYo+htej5CR8H4eWzqIzc12wbRFhJoJDaLlbNiEnwmQsZ6+kvXrqSAVxkK48G/qEf6uW5FJz1uD9Z7CwugD3XooXAFgeARTGBOP0YeZ/YAKr3i9heO/1Zh+q82IN66JlfWc63C4aY6hXHIdK3KdN4fnzCOxAfRQ5GnAC+GY6fTEI4m50VSwUeEAWXHapLrO7M+jxf2jEhXJwLmRGQDC0UiZPt7HNoaGoZx1zyOFe2QqonKTZ97Tz48ZYY44IjQqW6X3U2phpKCZLYabus6yfF0ukAaYx6rlvIqWRTCj9fkN6rvXKCTK9spcvmwsP+AGEqTiPeGzwnRyxSEX2TXfuNx7NerjxTSqAWBBeSj6naegbeOC8DHA3X3H01Oh5oR/A877jt5rytJyjYH6ecgGmI2kWUTirfU0sOVtuR9Av2+wx1C+voo/keNOHVoxuF4pOsvkUnA58BR5sa2GgYpbJouc/VUMUJW6wvTNk2ocR1lGFzgvvrfljtUEvdL+IksfzggO100O57AO2cfafzpk1VmW+fNud5Jc9570YTHjSlkr4a80VDw3ckyaf/w+YbWsVhpB56xr1LnCoGdfA2aQ8bPVIH2mbq+QMem+YJkAEIbMOX7Ku8wykDxPi9Tezc/71j11q+kAjVNFDZ8OyRL8YKcjM88YHD9KZyrnSB+/7K33sRhjEc7thab7SjmMJe4R59Es6EaWDoDzUgbLyjEjeDkTnXiZtKns8TSMCwQtDWOkczPiVuacgr55H561o8V3m3ha7W3b0Pvmkehti/J0AjFfWzVLh2SP6hy5FjVNe8LMgccwwGky4ShPkSSMKYhq15M7obDAU34nETUpV9fxXepbRFD1fEt/Mu+n4btJgzadGXTK+vPaNF7YNKw29VTwqa8pPBiAEPkr4Ys3Zni8xSTpvO/mWjyD+ieND1oSgCVwXKOwKDrC+/MBs7uyp1Iu0eVz7ARhlsZNNVjUGUfruHv3IxhR7I4ygtPfTsD5x6i7q2h06uVZgpcIgLkM0FrDCN7p8vPI+u9csfajYN8HTlufY1V35s25Fd2OBo6ZTkW8jbjDeTYzYIxL0GMfXd/C4VwtaqO7cbV18TI9cQa31rGPC7LUoxkMRzmycLsGfJKaqeI1zefBcidZrsMMXUgdHQbvDdgUuFNFV8VZALOGB55zcSn5QRpsM+zS0MygQhOlZJAJz1PSUJHMEsVZ+Z5PXEYYrCeV5uv6PWGXhvepn5BwcJpOKM9xdVMziCQ9U0ZCuXv2Qr8J8pwOBxzqpAm3+MnrEUwKrjd+602wj8k5kLPoIokPYcEfxLqNpI1f4fiOvIzNuefYyKPd4JfrvaNinckgHmaTnb40qhee8mfuA87/2Aul/kpLGHr+ytdw0X+lVV1+fb2aPtFxbB7pnOPX6jYniTNnHzb/o5wZTtrDNPCtgdnOoqPg9a6GkCLQkete2M7/H7RvMaS/Ct6+t39Z+25A/09oBWnQ08uZedYXJJIJD+hAVoaG3RQ2BFsXnLYNj+czOgTb1nF/f4ddFegN9+MtxD5hx0eY3KHLBxg+4qMoHsyQoVwCiDVcMchYyTy/JQOfxpFQQpMp/NoBn31ZRnq1vwvsF4/YNgnDM4CPDXinLxuvP9j6PK6lmyBmjfS3EDSzZ1OjMC7SALz/SfD4s+F3mZ5weoXGv96WMVukZmlzPu8NmQjuOK5Uwsa9KTDne7I9mMrqkGpMDfsY6Pvunt3aItVvZ+nhq5lUgso0eMsYyh2VALfwoGdU+pcueLtLCju3Vk3LD28XBel1pHcKF2X+nHMqYgsvSrh8Y9PYvdz4FWL1KJ6toeEDFH9E6rE5gHsTPIplfPrs35ngCMTFW8xaUwbgHoJb9rxUpBtmCrLarSl2w5IynYKjj8oV50zV5zWifLisGej4xkLYkkP/NADphB/z5GsGj7iicXDBWzqwscadReQuJ0tmexEabBmzp3Bd086+ZEM5wtG3n8aXm111SID72oj82ozQ1wktIjMSjLUsV6VhwOs81NdOEscZXkkUL7v+EL/sz67U8+zogHsgK85o5zvoXRhn4KmlFYYehhIdOyCSEcATP8ly5CQMEy0tBf7jMSKakUhMN7ydIjJ9hOf/cZ1o2ADCf0MgdwI9j/KUKjK+3NSIi3YIBNvTBSIRQaoKOTmFudtOYBpEQXikE3TuBXY2eJVy8RU94J8UFjJ9O1clKNgk05xmKJUVTQWjaSBUhPHTcNo2QDpOcsL5fIZcgNEUTdwo2sw9i0mzATfm5rOPOFIKfTABIhtObydXNMgK0x41BgzbYTog4lTZ0/Fp1nvLJ5OHkKgML8gzIdLQDFEzUyIarCiqOa4YtzsCudNhKnL5G7vmWIBUBJqOrOuXNbxF0LoAwyPcTBVNFRr8EiHcFGi9pyLWbAMV5pujXVfCicBaiV4FDT4luigQbcUPjlIPTg0ovxFCSChLyvtcF4gbhkwgPfbQgNYMw5orcMRr5nn69gZ0QzePDEtaAoNS8V7gccLzVNwyqnk5qzeQ/Et4v/Zbz/iz18UayOIUyhOUTEIs9ZG7qeYuyT2chzSeL46X0KnMjnqMNhUVMMG2CZiBorVJEyXg2wC0HvW2CZ90DInIdRqLEDyfw3rUwS70k85voU1OuFTbfR/GyJrs/l6jdp7jHh3M4BF7Co0yQDrXNQ6MwSCbeCaO4P1E594nTJYt4Or3EsU/NGSPMFi6481MR5/Gc7OISCqGu9wiGnkijXnB9JZPJgzk8cq+aeDgWKeBoqZvtgOQWoFHXXgjf78yqwt+WsZTx4Cyz9EHFadRwxbiSlyzSIN+8hqFl4tCbaBLT544KO900DnSvM1/y7rMcQ3hroUyfJ5dgUZNTRFAekdTBVhWgxl34nLH8rJMinO0sjZzjfgUAZXktT+jEzlC2TxuKF95XANHspwJRKZBypB8bs7aptMXANwH8n0U5kaQQ8Y24//ZzxfOoYD9VL7PL6uzK9G11Z4O1/EXH/5niLyty5bnqr2fq1H3bHpbBeTZdHbxDfFYzSbMeTyHTGRAmF72CIlqrllIIhHOLLSgE//NczGGTnklogkpL/DY5SNOAlxcXzJswPkQOn2RD5AcL8u3wEoGraDRrUX65PBIaZHpoLU5GcKPhCMUYBmtum0daC7hTb7NYUhaB+uGn7aTr10s0hiXOHcteCf/a+FYSJgAJp3IxW2CnusDMLMAHVnJ24iYp5+PM6NBs7h7FvvdJCKvo1Y314cOeHSQnHh2yvx100VoHKch3fmuGv3JSM2tb9haMaA3d753+7s7QKrNMiVNJIObM1+RGY4ZR0aUCVoxDbBHyu0KgwY6+XGxp0Euz2KEvuYWAEGnKqKfWrPCDeYIaHhYcLkETiafwF0Rp3Ea9bevkRsRBg/FPNdmBgs5QLH2SzmKxsfEfPHmMX1bKz70vchHJD2eMHLNh/kXJxRZUyTLOCV7CsFecrQrCJpehsoUxXml0EqZtIEBGomuBL5m5s4ADyHX3L//weXRxFgCNHd2bT2+1YYhcB5ORzqaZr8Q7PuO8esOM0P/24bx65jjgmD//Vfc/e3vAIrTd3nv/H8iTzfyA7hc9mD9fSxuHE/kCxrRlc4MwEJnTTUzjsHmGTR4BkHSS1XF02+/5BpIeUo6vR7g7TVGHTPgffTGdN6TfYnPgZMbDM3Ua7kLcBKXVSOxUfA2kpEoE1/H+Qw86TzXhOecOz1NEw/NdRW4HotrQ3hUs9SHjjDukWS32L/e7vLcmwGtb8Fb+D7OTIOkdSg8j+ULMQXx4AAy2QIAbFvH+RLlnxD8Su5BkfcKvqtyFee69T7v03CG5Mkj/o4zRPkiLg2Re55dyHT83eLZe8xsV8VTef7nSpfimoW3XJkimCneVyedQisMht+yl9IhEGaLIrkd4LQ6Gs3O17bg9LI2L7Xf47ofQBvD7xnwJ5iZa1+OWKZj48R/bE0iiwOf9/Xj96q20hgkHzfPyI2b6tjMIngBQXfJB4rzPcSXRc5nlgmNCPRh4cydWc0mteTj8n3QlqPxnNfNwjlfm/iNuSyfr+HiZjevwIMvtXbr/tsE9NlnHp1m/uKQvre/0L4b0P9dLZDOESEASETMlEwKT3kjqmii6IGoTDxqasA9I3vvGYkFEeyqOAHM+Oep2AQQfAboZWxuqF48knDbQzbHfSv/4Y02VVZVyDheE1Ho8HH0X/+Bu5/+C91+wnv8gj9k1g/n016K2D6uZ9JpTCM6ALSfgHcQ/HFdYn3ppwMYvwC/HhnK54dws30UN5gfx16dATjPDzeW9XhvymHmm2r0hjSJNG4GRgwrzAXKMTyVew/ipQPaOmy4YnQUBpC1zFzwbcnEavEkgwnejIbfTHOvixxd5m54gxUE6hSblZSemN3w+pqJQA73VtpTlbp8Sr32jclqRH9lM3yC4MPVuNgeGKmD52tGHeHlmDD5OK9b32WtMNxeRyoKOX8B3IDbKGu7sbNJX044je7LIA0wXT3+6yZdHWcDdig2dP/tmidMhdmxHZ117MB8/3e363FWBv25uwrMPTP4agxf1ztwbuXkv7nJjfe3hYW/0jhsgwHnAb13Jb4w7a7Ikj7aDnMWuYIcSOmZCv/5SxFAyq1JhqQYmoxJBRuWzBcS8Lg89rpO8J9ZhxypAExlT6OOGc+PC6giArsLo+xZIWUMt3bdjeg9PwvjlSlQwPdhqMIw0Jugw2unK/dBgf2s2O67C+GDSk3NfXRjcZvGI3n+rC5KXfHP23aHLVJrhuUVQJSwEDewMoIDQue8EMipnAJcgA9hMhXUPHshwDfCQcuVdtpXQw5i9VpRaFPIdiGxCn58QsGGUvqGRwOZjTCs+NqpNXgZdHcwsuH1/IYqtj7QWkfbO7atY6v5qpth2zYMHZDBRRxuCFMJxbGt4+FyH3DSBOz5DWKtQi2ea+3LFooX/icCa4Km5nxhWRerfYmnbYcZsHV09YioPcsDWJSFqas/DedMPUjFdRq0ikKR1/y5ZvMv5y4FjqqcfGQ0eB1pZrzyM/GNkWV3pyHuh6ef7Zl+Mo0gV8wOi2DM9ZlDYKSdD7hJcQQJxfV0NEIqLubkKqdbcC7X2jwt+8go9BmBPsbAPgbGrlkmwxBp3InDYVnrU6thJ+CK8NSiNASQiwUaIepS+P5PrO8rU3kr8RTkg1cEDs0Lgjct+3urFaodn5+XWOSZC5gGvUYlHtd5pgx++RlLvxXXYrLN+/Ao8ta3gLE21zKesV8sDXnkjlXV/bEWxjLwV+GHkehiElKyHckHgnR6TU+6zE8iWnlh5NusK0zlNn8q5+oYBZXcalUKFQW3l5egUpejZ7QZEsb8e8kxbm/eFAXmGXj0dbvA08h+iev5XItxK1fO6n4aHlAcesu8n1OqVXi5gztlH+nqLTp7O/r19rNu8ZqTjaw7PU+XfyyGc0z4A5BK+eVZeYEDzKSR6yVLR94JDgsZ8yEgVneBSSucL6nBA3O+9mTAvcEu05lZ0EGASGf+HFNARQE4yrRlxdBMoK1BRDNavfLpDUhFbppieH5bSyfQSTuC+opkBhmeYwEgTcIZTdG7QKTnOs3UwGXNAvfRWZw8Z/KaXM2Q1ci/1A10PA2oNqfZttgq5p4XBy+/u6VOwLPMTScAYOoKFsN6rglr0Ts/MpXIbuA5RdT5Fq+tsTzJ3CKvT23QpmloUhsYY8dQC8dap215Ys0mHGV969BxEJ7A9SYI3sDezzAmzt94Cm5cg/g1ITDy1jyDzi84bEznDoPBmjl/yCU2nvWVb5jjmHjK1yv6ERTd3jooH07FfXwOFiU9eUjilORNEPBpIVNIHZvDL43n9XpeNWCLHoT7xcFZPIsCjylLNAXuKnwOWew7mOtHAXRmtTLD6cOPMytYlpHw+bfW0IYbzkVGoiyOhWnRxSTr+LYfPZgp0Wnh0xp+BB3hJ+W1OXEljjWcz0/OX0tH1qQKYBr7jt47LMpIuLOjRnSyheOrt8vlAgKyO/caDNOoaqaRPQPYfx4LVqj8B7//vHIJX23pDFX6FZtZF/i9mkexjqFQ2bFJZFFtDVufOd7Qpjx6bhKp0DmXSjVuyA2B/2upjOk0vNKF483X8w1ul2e8NbTNYDv5irgr+Saem8Ili4+Fjnn+3kdPvUaDwUJ2ZuaIu1PH5aL5XOJ9V+jxgfO5N2dxpOFGqu2OZ75SHYI910Nu3Fr7KCQxebTaCuux9HMbi87WpdIr3jM/M635y+2VEPtawP5KM7helrzBt6iXr7m82SgTfUN3swWuoh7qWqYl5ZYI8CDNnubo6hy1wBhpf2voDKyrmX7ieo0aV15KYlIeM0167GUcigMbCjxJIcdXhPUbl+NVt//Fh3xDq+cnny6T31r26XAI62+V/nxv/5723YD+72pSlFCHc0vB1oIx1KidqXFoquLFgjH4fLngh4d77GPD02XPtOy7NOCsuGxPEOu4f/8B7bJj/+U3GAxv1fCHKN63hg0d5z4QWqOrk57jLdhyjSyNG1IY4X3TG+9IlD/F53fq738Xwd9+9jQ9yUADeGfmUehfQRiV6DxD/wEA51+cGf9RnAB+OlxM5sIAXGAl8ny29wZ8kpeetrbj2DPKfOE4ZOXpZF778hOmkOPboKCXs8FgwzBEoT0ijlQhOj1a06COaexpUUsOZGxs1i/5qAMihg8RgbkowG/JoIdVqpfemG6+PxIbO7xhKYObQu6iYPbGmuh+b6nx9UJz5wfNKHSOp5drFMxw4F6Zj6znHuPjme5x94Ar5J6SO1lJeJQoQvDp2ILBYD2x8+6Rt55yUbD1ltNVnkMTVzjYVHZ4BAKNdhRGS1QZ1waaeElk88gmvRQuscCphfNOcDyEQQFw2nqkiLWFSeDzlswBN5rdeHf79/n5n8IGVdh5CZEcRDmIhgAAIABJREFUnx/KdEahVPVg7dt0LJ+PAhG5yN7a7KHI4FfXPzv+5SU9Y//qIikrij4ZFA2nNxtaxplZKEAEujsDvZ1Oy76n4HkQgHmcIRTz/JXp71hLfb9ckuEGgG07uWFov6QQaClAVOcFMvN7CpJAmFjFMye8pg3z895lh4hFZLvhfGHNTWd+x33UIOsdYp4uTQ3o9+7EYmcBU+lV2OV7CSP6jEifVb4FUyEosIjUiXOmGsqzEwyKy9lXsp0kUp+WvQwFNb363bBqQa/XM8u58XU7nSLtZqldH0KbIHBN83qBxg3mc7UYWSO1qZSZTnwYUCCSThAthb34rtYwD+OSUQJrhCtmxQmBzwHooFQ5CC4G97hWV3K4kdGFRg/KbmhDYJtBoVDdMFpH3zr6aDCLGoisZb2dIKaQMcqa9ojwVFhzOGHZixR2b2gzZtqzuVKSuCROgK1zq/tHmjMF6Hg/JebkA5SOmw3obUB788+mUXtRchy3jOfkH1Kpbevn55TUZbbP/M02hcppRKeCNiNqtNAu7jtT+xLeuVYy19Dhp0EaYdEVPtNo7um2Wfok94xzJw+g83ygov1EfPC6vaEArx7rLfVmxekEBGMBM1EEcCwKRzWBKqDD07BrROjtg8b0HftQIKIEUPcJgn3sXk8xlVxh0CerEfvsUSYS5RDYhzvK1J3M+uwy9ygjzMwiK0bMtUbWxzVdHNflOtziIeT6w0wJLsslWSoWyEhV1o8EkBHLVaHndN5hgBBnXPs5YGTPIpk+eGseCWfmGSgEgv1yyfHk6ySIpZtJt3rrThODsJ/PHht9d3cfEZiO78UMeOjZTSG/yxJNmWs+r6ZX1IQpy3FYRj0ym4At/GziWgBQy/IaBSGl41Tn3AzpwMHnJW3MfS14wyz3UAGc3r4JzvYRzK7B2tn3CINbPOsOXstTRHAX/F4PQ8as8TllWDqvlVEUUFuZGX5/jjFeteMe5FwNjxDcx3dU0g4MdLTpVFyekesQiCWpQME3GclH+qzMMuF4rnf2ocGnMeJ4GmrnpOMJhebWOcwBXE1wrmhcttKLajj36KXxOPllY3RqwQuGAbEN7a4odtNoMo2/ueYUOigLRehrD0Mv16n1hjHUSyAkPE5l7+xOMmsS18koQwfv0lrwAZEx53R3wtPjo9f9bm44VjPUMjZTrp5rmPxJwe9pwAsOqnfH97CWezmKNlwE7jBwQ+Nf+SAkDExeQCAZFb3w64Ue0qnM16Qt6zMjEd2A3lvP1O1XPAqd7uDrQiO4iBvQ96EZHMCMKkNn+REGD3iggea8LHaRdIYZUwazHnC905AQZ+p48AtIH40/PIOJt4hdA8e0WK8KnzwHTbunyE2ZqRj9g6e1cNBI/i/GkHo4+B5DMPuaCHXCMWbN4jOxXZloOgoAMKOhvOCBzF4pyEwA9V8RnDhMeLr2c2R0GUCw7itOmF5W1GO5vi75G55E9Ww/uU8AAEWz9wCArd/j7Q/3Ln/1yKJSIriNadv5W85TU4ZKOiiCLg3SWVM61uanO4/0RdDHOJqXfc9MaRBk9jQA0F3T2azxfMECDwnosenrMZASkUS2DQOazbJBjaUlaiRK0irKhK7pGRjYUpf1DoZPEVjlz/4sdFSYbdXxru3BBA8/vAfMMD5+hgDoH947HY0xt9aBj0CzJzRzHeQGQGw4f9i7O18G7sY+Ek0nL1t40nuutQGZR0EEnwMOfcndgZ34F1h5Opj5vpmx8lnOrzfmYJPMgOE8hmaGsbmxhmEei+1luCITjxmssWOmkA+4yXPoZ7OFszMzde6XcbXerTkt4rwAgekeo1z3izSDTl1aaCVALYLF3F0WHarQVumORcYIPw8pHwrds6/bfazKZ+SSx3yn41gdL528foCgm+HSqmOK1UQpt3XglRdESvZF9glcRVot8+q8/djpDTYtf6rwL9Mx9FcYPtgMy2CXPwQ6e9ZucXxWbMsft8b1La2w18A8v+QX615S9q/O81I64m8QSeN5lm1N+bfsd9AZ1eE8zbBkzA2WqdtVNbMsF4qbT6+08680nw/3f+1xkSX+hY3r/8EcPj6XteJ6P+eIe+yjfnb6/08e7Pf26vbdgP7vaIEkyRABZMDZgpCaed0X04jiitoR5Xa/2pHPPz5+wo8P9ziHV26DJXIbTRAlRDH+IIHyCCTyw+0WgSpjQgpyr/eNqkbwKwGjtDYXBbv8BkAzIru2mu78FlF6refWDk8vJVgNocfGUd1C5v9JeMuCEQt+MxjPuRoqzhAxCmmM3YVQuNBuY/e0nVqEu/CONoS3twowBEOc4RJr2BtwpwNPcCWspjGdhlS7ue9zt2/MBd+2tktfy823e/rKzzfbH/IJH+zdMsZx47rnGMtnx/BCu2DCKMBErTf6MMuaSQBCuTCjMww7RE/LfXkuy33Xc6F3oKKjY+vdS0KwH957mEzyv0Ay4WP5/XZ0639WqxN7GVCOwovfsgqyyyXPKBRnh88896VDcz2AfwlPeI0Hw9kplJ7SLCPGJIXZqTioyn82OTLfZT3k6g3IbSKjus2W2/w7imb1pirAzfnU77+1DbvOCiEQyJ1ALmTai6cvPC0llZ16p8CZPcza6Gy+3nR4oTIJoDEdiAgJE6D5egxRVwRD0E8hwIARg7YYQdSQddClrF8+/5mzKgB639DEFaVZjzCVyhTQSQMwI6M4/8QfkoIEISNhhhe10udRuZMrVkUlAzkOL63e4CVwZsrDmtKd807fbAnhnnW+wkBDhQcMnn6e0SR7pMPuhtYHxugeXcZjSKV3PLNJgzV3jEREtvj+FGFUDoIVhd+r3cDVt9wL474EvLkyDa6oCsXIIiTXtigLwvWAAnRrUGsQ5lMtgjhsPXncy8oTVOW/vx4M6XntjCh7qc25ScE1c13I41qZI3+XnH9+OWGBuCw62fJ3CwU4o89jfUrq4AmqoUi3adxCrrdfREUPnV8Siqk8DNhYFNuQaWQaWngvX7NM9WkIA8M+a9FF2nb/2934MGZNumXJZfaTa0oekXIEgMgRiaaARkaFmvXpuGNcoyRrXH9BScMFZMYMmfsyXSRmo7PBrfOx4vtrunLEfYyCHENzAmp6rUg+nJuqJKzN8h5Xcl9KEZXW+23ZQuobPszQtg1mijsg9gw4PTScHy+4u3sAAJwvZ1fymkBxQcMpcTn5vpttYd6O+KCMr+D5PLdDJ26v88hbLfhjmT8KYcCBazGUm8JT+EeN3ENfgNOdjjk0g+HuzWSUzo8GbmBb6ANwwkxhzHNJx2ku0QM8B8wea2Mx1g2Cc04u+iWixa3vOeUDfqpsWumP1CvPhVmWOslE8gLAlJz8xGfvMHFh/JqpfctY2HdG38o8B2k4yjqXdttIWHqrsv76EL5aeRu8gSAcG8znYkgcNMI4NB4VrhG5QHCCYQfOq+qqyQaB4NSLUjgIqfs3FRpK2G0ChBOYNQNGGO1ReVVPp8v1MbMl4mpGg68Qf6TTNBrP9OqTb41dy/sWDBJ0yUpO5YSzAKAkI2W5FwuNlMtrE4QjQh1HfE/6w/dyXFcsazzpnxvLeq/p9Of7uq6AFOMhkgcdOsA8FWqaKV9VR/Bb87d9eFkgz57n/OwkkVPuqI4IpJGWu/QcVH+d73DHE1tSCf9/7L1texw3rjZ4g1Xdkmw5TjIz55zd///fnn32OUlsS7ak7iKxH4AbAKtbjpN5O9e15oyj7uoqFgmCAIjXjNzOnkn36FgBwMvcpTzI/eqzywVz2SUc31XRRksD+ivjsl7cyUvlQjFB2Vhh6/xiD17rbOJfE01zGaD5Yy2ia4G6A6jLOKOkN3YCwBrPFW5B6TT1kpl2XmIvEjaAGVVv3vyEw7K6bgs4Hg4QT2NtBmR7O2UFcoTkOQgHDEYOowksPbFnL6hGahEcD2vSdHDP2Ls5T3NWGlEzW9WiyekYru4wa/00l7XUnG1EMHQz2uhBL1w88wmpa6ZlaNWhyZ0lH8aEl/WxPbv/1lYoU4ht28Ojwe/dPRph806Az7fQ0SB4xhDjq4vve2kKWTxCewBPu/EM7ll12bacJ4iPRwHO1A34GVj9/L1TLYScMi6hMc1MKq6InwkF0Km0gu1dK33icJcBSEPD4hk9EljO0uHJ8hKfgaCjo+g1eE5t7kUb16f9Vkb+mlLPHzTOJyFjfJ3SXf81q9Ffe08+FgZ3z1C0lxFsd2ncZ/D+89kBr7f9aaF+LwLQN9D8eKS0d2oG/p/0sheB2SuA3w8A/NbX/5E26Q+KvJGG81Z0IQmLPZ8XQeHlEsbz1qxUVFaeSz2D4W45z/q/cFNTCzzIqZO2o+hbJvHxj8//m+74JwD+lfY1+8DXos+/t/957bsB/V/Z4kwj066u0Q+qZvg2QZs1I9MIEUoyJDESKA6L1TPdxsC7uzt8/PwM6R3reoAsngoHwOHhE1RuYzgvjCYVwWcB3gzBR+NiPsY8TE5pI7QS2lTKl5NmTFrrb68QBYUGE3qUS3ImAO5HRm0vSKZV26PMtUP2oAfSwL5B8VEEf1PBX/wZ1nTZCxULquBvfXyUmlr92oj/eLtXdceBcnjy7vYCYG08SwhMaKPQRd8uVY00aFYPPdMNUwHL0+d0KHbLrA4AY8wGXG04O45uGJEmzaLUMXncMlL/DYWqPcRCMWk/ekDAJNpenbpOIAqmwzgLBfDUgDvNw2IVm964rvgpNagFpvMbP+ERbxVoeIuOL5OnIZuXbMKN0i5mQv4XCP7y7h2eHh6m+RyBy3qKsIgxOyi5ki9qQvOQGcQECqC7kew8Ot7c3WI7+QwVgB7MUIPhab8I6xFpMVnhswo6UIRThdKL0IV2iAngIxagOEoIsLZmKZk86mfz/qqRIzzoQEFrhsIM/8sD32ttUmL/SRkkDBpqndS55ftT8ZMwlTjc5jA19u2FULQbqPiaxWt0xD72CwBQapKOS1jIJQHdg2E6LP8B2dEUzCt6RE2bYN3HiPWm1CtNzWNfrGZya4RrOXK7sYlpOkV7XOehayYWfpBclySG/kpCELCalmZYHiA7AwAcG3BOqrJfwdVp7/k1QnulcWsIBAssPV47+2HwtAICbHICsCDTP3upg+Mu9WF8yn1OOjOvYTpH6Rgerdkg0r12omW76GeLED7cHqxUxxhoR0F/MVo/UKJUoMEPmmeaCONxeXPdAm3x1IPlR8J0uPbr/PKCxrrZbqlUzqrmYQ6FoSkZbRtp4KoAofSgMjTWdZIxNOkLx67Jx2Rh5GhG+FIpLsKU+waPVuavodPkCQ/ucKYmN6igjQHp4vPNenN22Eyxqi0NjVHbwrRmdthk1Oo1UlEz1U/U8Zr44TJAILd6FI+kWTOMLJXvIfnu7ACXRuLWgObOA1Y/1SIvtNL2nbZqb4CZotHrXFDWkm/mwVwLX7iATzGiT7NBKANIn2PdA07eofO1wAOHT/N5L0AoCqwPW9cWa7ZbN2WN+KT9VZEfkW0xx1w/gUWMI+Zes0Ek3IYboJgdiOk+DVamquhb95TtmcLdjOpnjD6wbT3OFozsaVEmwVEogAVERGodMFNLiinsWVahUX7EjLMQMwoqLPJ4qNfppbKf+74DlqKZUTyk+5fMnXBOOWaOeokgd84J8/d1WfKc5T+YYtTmXJX8BghqjTTxqc7UtzizbQyltjSnyL2yHMwIaNlVnAYNdUNfrAIoyFKZepDFZPrj4kpm4HA8Wg3XBVhvj+jPL1C5QRiqo6/cTzwzQMSdL6rDVkKqQr2PgXE+G941q51s5X7S2CPlHWFwN+tGRIViUG5T3w8ZRZYWA3g6W6dQqtCm2NxZjkacrsD25Ysru+tazLwszgPC1L8p97IvxUCn8vr+TTimPX163IlNQWSB3fUZYklrRSv27XHR9zbqJlOPQqei3u5QpzvwTBn6OIB7T2RMWuiZN8T5czWjWGactUqgYZyiA5ll6aCzRE6VRk/ugUsDugZNIN8UwLPdaJwRFV5z2HUdw+mQPtfnAdEGwcGVrpvrTlaIAu1GfB654zmjMFD7OPq24XA8OlNvYaVT7VBYSQuTYZulTV4k9tzMl22/UCEdP3pWk3w3o8ol5rudKdtnhzSUUG6R8hrOhW4oKPxjBJLQkbEilMtbV2Ta4h4Ro9zDjvNj9LldigGBM4UgaqkLBEuTomD3CPRSPz6hQ77ogSNDAve6Zz4Zwz4rNLJQKTrO5zO2rVv2PI9AH5FVxQ3lnjnFDiqOW93Pvg7/gLcDL3msDXWMPmeKHC4tk7ZxP5C/+N6oma9UEIExZoTTgCWjwwmPJlnqwhHD+vQAh1luqvyB708+JT4vGZn4Y/97rV+ceJP3UL8UPMH3RoygylOkLX7W47tOjiMmC6YhuUYXi8tnhFvoCooDjI7EUtKxgyoW3FvmJ48OXttiMppH1soYkGUJIzZL1iCy2Ri+BCUToLUV0hq2saGh4fzbC/roWN+vWNoakf1V5jR2NrzMgYNyqOGoqp3D/FxvBnLXxTXCzXJwKQQS52n4Hk5YsxRBlR1FjF5FRgPPNnn60I1uFLoEj0KnbDdgBoG7YTqzGf1arFFt9x5Veir8sAFY3r3D+fERR6cdIce89bF/uQXwPOu41M7HzcsAqkiWhIGzMC8jhKIHp5xE/LhRxXkhraIDgsGqCfkL8h3Ol1Kn7fzJdaEKO8uaI1ammR9qkeNAyo3UPQ24HOvnV7I/RoTzejjU+PgbU72rBslaJPdZc3px8lI/8U6nDy1Kj1C/S9JHGgun5z6G8wYm9G+G8GDQCwC8nLfoBwA2f9fi8Omaui2o4kWk0Dx7V/jCqgauz8q+PMd/priTBOfrLcRYuf77JGLtsFc0sldMDnAOdydVIb/X9sOcCKPYIZInSJmnQx8/KD/ZvzkL7T+xScp+Et8FQHOeIObkIRnIYLel3MSsByZqOoBac31wnnvpSNJVA5b7dSBvHUheEEPFtBWjXbv2+/Pmc+Qn01vKwL7e+V5HEb3MwuC110+9c72vLfvVQJUK/6vv2lPk7+1f2b4b0P8dLQgN4kPdvknUTdiOGuhq6VxZL8JFTk+DNNAAnLeObevuwYbwjOV/ByxllQqPc4I3aFYPTlzA/uqOdPFLNJXZX7vdhei4+eJuF7ITLF8D2VWj+b59krmOeO27miGH9/cMxa2n0KlkNdbDnzPlRbZ3+vUx/9lmqeEvr+9pOL8zUk9dKCPMVTSN0GpR6GN0jN4stT94QBnQTiahkCmmA6FQpAoFIsC2Adpw8oP5EYonP8BquIF/G2mvjJE84guAEkjyuz1Vxehn0Qu8fPJNVlO4V+b2rfXRzevycwgi157g9VsVnIpw9svDA97s7hNY2qOXi16s0XO7+edr+FavNQAvT89Ylts4kFJQ3yt37RA5vo7DfmgyNV2mJRcI9mmx7Xb3bq2CWErYu65fidbS1wWWf0Wbom53Qss1xfx+VfYq0z/0bszp0wJ+MZwUwPPdfyesvqELPy85LcxIaTOidOAkGEeUfa9mSFyN0upw4Vx3IA2FYR70pqUvijqgeLUi+Rp/J6tJWmIHhAhnJC18peXjfx6eVEZUpYa1JShG7b2JYBwb1Guih6I3XIDmvufPnipu8JA+Io177HFVixIOjYFGPTkti1Fp4fzOnVLcD06tLXhzd4tOo/IOZOauM7DIkkqKcFKiYoKpBwsPMOLhfWjQWSrKUn3hwg3HuDuRZGpaAG24cRtxoIenUuWBkJF8TUYoMy19HY0TagZiJQ8cYKTBUEGDGY+HABjF0CumeN6WFlFZQNYR5Rx665DRIh16a9aPtASsGYxmWlsbv14Ts/LceLlY055TDaXm0GLgoJIzUnS6kleoJLdUhzZcixTzYqtXBZd9NLpWnKwL+QdbGBiCUAhCQaMwhVcl7aqGC67o8/97xgNPOauGC0sDFoHZW8BDbcsIdGoKgpAYvFqZV9CFIpTWcwDpF5XyhEmLqEcqHHJ/DzcwqGcWsugcS8We0eiM4mP6PK+J3ge23jEb3TPCxspyCgQNTUYqWihH5TbcLQTpCuWtme4RiwgDO9Nw7ewGccWiNPH6iCQ/Tknl0vkCOoG20NPEkPqJyq59C0eC3bVpijlN54syz9LpLfvhuY2DNJ/Ugf78DIEpYYmDhkY0+Od57+npC25ubl12EizLim07G61aGkYHQiEoEg5I7eaYY51kQb+22bV2aFBPqyraitIm92VKff5bE7TDDfr5bHe4gcMUzIRU8hGuj/QNGt4ozqOQRoF8n8ubyHPFcA4Z5znCVgTjSedrgCvR7Vujgtqv1zOG4Zgyg26sqJT3QOw8IReIn3y3NgEiTXyF5IWQWPhZ0IvdPaLNI+bYyxeInyqkdJMyuzmzcF6cUSGNjms258H04THpKot+jSZXKF37RSc477uKaFJ4JDEU+szIJIXqyefFjCR2GhKsaMcFTdyhpEowTitCG75rbWluKHeDgcCIuyrWRSJjTlta/DR3kLgDyq6ocp/Tnh0cZUcbw0FWd/cVMLEP7vuEo582dmexjBaem9Rb6yMTHS9nWym8scwz55GwDWeAgCX5InmlpAxYkIAlChuNPgJ3BBN0PTvvUmx9QMfmzhUdUDOmM6uKRaF3MGU9d0mdLh0NZl7ETaC5F1DWNnj3jh840ChHaDnLzDfSWOZz4/9eCfm95qQwDXrASywVDOH9Va7guItgWI6SU9evXQi5LL6zg8Th6jTITHjD9ULpOFflPEZREw6+SpQ9Cg+fzuL8zs9+pjkCENxhfbuCxtLQa4kZNjG6rep2xnBjUBNB/ziwvHcM8L3URCBej9uyIViq7zEU609H9F+eMD4o8JNljepj4LCu+PLfTwCAm7/cJN3hklGedgfG8Zs5Cy5/WdDdGEqPCWOHdh7kGSNkvooTpYxFlQcFgKhnbukd59+6C6yKgUd//F3sD47yWRTvMgn2BVpc02ooTCdWdWd3Cnx4+GiG1o+fsL67t1J0DoPxWQF5hic8R1fFIiZnCxTnxUnIKI6wSocYdZmKDvexqQARnHwPLg7/wE06AlL41mt6r6/xN8+GEATeZSjXNcLPiZRJRdXXB2lgjPcjyKZPBx10pqhyor2qlj+K9SjMiORWJfWgl7PKMYevga/dBsF6Ze7fqoO7pKjXW7KXvVBDt6F7WPJy/Zbudp3uL/5OB9dJb7bXxZmrt37tex0Ru/xHx9dfb+nYV89NIjNfrjy+8hDex1JllY+nQ4Y7lzRmSLK1G+7IXc/5k/PxTggkn14ws7V/Xvunv+D325V9Pf/8LQj4LwHW9/ZK+25A/ze3EBTjbEHx2omO1Hpg4l6MIwgOCfF5DEg3I/rSGtZF0EVxOp9wXA8pWDaB4gtWeYvDjys+/fYrnkQtEl2AVRr+U4H/JR4JWDm9t1CuCfI3JcO9cgAsUrvJO5cs57MTi7eqk/GYosSDCNAQEa/Xj4eXjfC5dn/9/gy9qGm9IjNJMl2NYu5LYRHvn76R2V5r78qBgd3cu/LpBoITrhvULyYTJwtXRpZz4WCEeG/oMtBkmx/y9aWiqVF5LqmwzcPQBh0NGA1nZ8odGgrZUZilIJXzb14h9jwwcRgC4C0uYe0d5nzLJR5GP7evi3NfRPGmeAHy+RBw4rA5H9rYngDcKnDAWwCC9V1Df6BB8XOod0y2Fty5zpkHDAqvz949a48d1BVsV9b5BDskzincOU97wBT8gmVpUDRs45R3utCvCqBTkWHKpvubBfp8wkP0qqV7HrDoRT6wtNUFpsyxWpXUFH7O3SKUaWi4WRach5WgCEcNV7gUtJ0VG9eUQH9EVnhVuL7W0XVlxVWlCQBBqU1e7iFpG9x4u4GUO6cLqaDS+Z0yjzQMRPlgwWP28fvE6FJxYsAXef1xytYdmuZgVYisdqh9GZAjoKccn8iKZidjoyOLrXvUQ2RiVRfKLQoJJbVd0iVAPFLYM2YgI9R5n6UTh3ukEz+tDmTM4SjA6eD7fkPGGye9P4gZL06/c4iUXDYAtu4VfM35qFViE/+vHxZuLLpBeo80VVQBV/4iSD5Wf68ztJQfhnM6XLnf1JRti2LbOihbMMLUomEcdn6ASrrNnY+ATZk11mW19MayhPFLkDplKt3O5xOWZbUeGMWgDrBmyn3iEU//NJnYqo2A7yCERNxQmwoViw4duY3rPLRFBIICkGGZeTIjggKjoS22r20flJUiwD0tSpAlUWpUMIZHLDfboQMdhMomYhHnPkbLKsGasraIrDM+QqhqWNrA6L5XFkB0TKlcL3DxyrUQvZwHzPeL0w+nZM631Y2xo5uRlSl2BTrvR/Ga4M3qoS11r4hFginxSszpcoRB3t/Ld07cvlBJoaH2dwi/JO6GGEoAV6VV1R4pIs0jSPfE1Hqh7Pe+qHhY1iVSiprh3FPfeYmBiFwbNsehtntD+cCXN7hhy8osTUp74tjId+vwneCToxEs16x71J0ZG2gs1zg7YLpuEX1WQ9Yi09WdTgRVwRKgbAKrp1sAUoW2QLgCa42kRtdluFBuulOvctdrrl0DFjC94FwTHkqTO/e6lP1fxhGvIx+oiufaFzJ7UuGvIhbVXIcOIJwa6LiqSGW/FvkJHs1ujhBW59eiKTHtSTrqSCyzZ/EQoG8nnL2W78vLMwDgeDgC8FIai0K3k0cQjVAwB4coEXwxNQexOVp3qDaMrdsa9g1tvfFq20nPudQ6OmRZoGeFNsHYtuTxgBkuAKsNqoqFkcUOxSWAP6CwyFQsir65YhwK6EBXOmKm6cvGYfS8N4+0VuODTMdaFZSRiUStxu+RisFJRkOWd1CAmWsSgln3FiK4VQ0ZPh56NQeuTg6yr0mgfFGVe5+BqIMuALqnw5y2nEswAsV6vwJ+hsvkLnQgSgcVOk2xn+4pgldZoeIRjJpO2aOPpJNOv3ZTRIa4AmUKF3oBEEciQ5lGF/FXALkVjOdc9cALnN05IJ/YK3aJzDD0AAAgAElEQVS58UUaZJmvR6S4CJ5fniAAbm/fmOFKBZAFWIu86lGQ575haaYyay0drrxX+0sLBaOLo3axTiBAgWXQcsf07AsxVnVa19wgGAnIfR23oIGOJwSijuBF6pHoWhc+/taRkcZL9DcZ0X1wVaSIse6aZm/+3vmeMXociqlxqns8HL28bvLW3UhuKe6wqdVR1b55LfT8nXzPeJ9FqHOfFM4W+9tkjdQYaYyZOAzH3VynuMfpfwujn17AWcseNGPigI6G0fwsMxUy1ImfmIxbyVWRGYTLJUVOLWMu6zwKKgoERwDnqo8LvrnHCw2eBrgxEZhK/UX2BAzIgJ/1s6TfAZYFMzLmBCQ1nM9Yek4UEQ1rYrefGyXhF6ukivV2jYwsJDfaXG4q5YrOvUO+mIMqjejHdsC5n7E9KORt8xTilt3g5bczVIC3//HWHNykYflbc1wbOP9qxumuJ+vr52PgUtkEEBj/eNk6xm890u8//2K8/Pbnm9hMYxDWWzGU7hwJSuYOVUSk9rquAEy2O/+S0cO2rIIF7x1qI4zpXNY7NQcqBbAuNA3YO7d+Rm33ftTq3vcYI+jvkzugAcCDDLz99IADa5ujljNTrFjQ2sB5U5yWgdbzrISQr+EONURlRffz/eJ780uRAVtr0D7MKa8lDQ0nOgUO6wqePaYzQpwbffaub1gYlFOzxQW/UY9YT2qyxDnOoN5cnzFFMqvzCahnnKCh0zl67NNIfRY4sLK2uRev3zbn320Fd1edB18X5ds8AwfpMvnQ5hmvmpjkJ3u4OJ3pJQMAkyTU+0weQ8jZUbYk5pG3v3VepfIYQuk3GQ+TWAav2ssS/CAhl8x0TXbjqY+RExl6zM+HDOff3wmwcs7l/ZE7QFNe2I3wd9u3BA1+c9tP1OnCdD4tIhTPuCzdBiB5iSraGBaYp+K6H+dtY1jZV+oQdMR+I82vrcp+/6ipztN+Ver+artwmv4dvAw9ZBWMrg/I/lz9Sab3XMq2/q5C8/6dAWf/f27fDej/AxqN57khKAfb8SNqoIMpAJ0EOTHiKYGK2W10LM2EEOkDbVWsAjwNpuA1orh9IBcBz3Pocnk23reqWDPDZeVkfx8J/CzGUFkrpPacA7hyHt21B5mj0GublCvIEXdc1kMXMFHufK0++48gXY8yG9IfBfjBx/q1Gu3ZFEz9w7VMJR7xZ5gCZoxIHxueZ3NPllJWBtDr/BQYxiwt0HGgx6GPXqHl0IjsHzAht0ZgZ7PfOYY2fduz2ryf7bP8sRWoRnSfFQQWnb6PQr/GmJ4FEP1s++ThHsu7FeNhoOEdFA/zsyEwWItA0PLuyxlFB/FxK/dda4mT3OHlPVQYuQCTQpJinAbabYM+9VeFg+oFrpiV2FT0hqqFwhV8HXlJzcu4X1mqPYjnSMQ/0eTal2/v71uoF2F4bZhV0fDN76rnFHl9DFd3g+SvcuXhbwallH/Z5dU2XOlhB4LN91AHTjf+kGHs0MUNRTRcUBGkqfBxOFKkZKTUPID5IHd1+OxHMKVtqr+xp9d6GWpRpjQZ/r1NATDCiAo3CLAcVyzSXPHAcXXgYM5uOCeXmpak8F5+Nxq7gFqLoWqp2seADMF2srWSVeKQ1JgK94qwftGkwEztcNDWJYxGgbOyU5bCMNKUDqaICDokEoYPVNhUg4Z/Z59WLtyUCSqyq/PmBzQ/uSuGGwAAEUXTlqXpAPRtgy6LZRBuwNJgH6Rj8XR8hHSNwEngl6wsDZPSo6a5UVUzRG8dm1gKUksHaLWzXWPiKcIbepy7FH1Y3VDVbg5rkut3uU65XyrqywXCfL2pj7lHpHIqQG398n0+dAhcsdk8Ap31bppCRxpJp3egKEGJWF/Z23t+uf/72o0Xh0viu6bRJeXf4oXvEegBb2imrm+Ou67cY3pvwoQ4p/txSYGFv9fkS5loDTmoiiKjUiv8inIfGkZzjSid4anamZadiQBoVB/oHegd/jkdG4pwEPATnxe4R31AfgqZlPpQBQNYdzt5blcYX8XZUaR0aWIOVZqyRzoF+DqFYWPXvxZwC7IMQ1VgiJ2tumfjqfjKEi7hUETeBcu6AJjRPU1N/pwUhw6/p+7BvUIOsGgxXjt4fWaD78Cpn6FulFhbOpcRf2ex1cZbxzCDRabvAgBLg27dMpiIZ0Z5GZCbJeBokcGxXMBpA0aHaEvjM2DOa63eSCjUMewuFy/aKruqlwEhr6o4RWOltjy/MOva9Aqls2YOyd6x4/BFkR646MRUAbz89hE3P72PHytsRS5ls1Dp1r7KePY/7I100z1AppWlEQm5frxtDN3xozp3x2GF8+QyPkm6TCEj5qM5lyAPhadMtCn+lnHvcFAnnNCJhiQvAPSZhp6XHQs7wNzKDw4+ciGZ7hORYjyXq3suYdDDccqhlHKPG/IO6yGcjACJLDcTH0FxVgnZhzDUkN9ssYTZo01e8WxJ2hrMZiJg2HvKkAV/1a7U2tiCdNIORzX3ZJrwS8taxXlLpkxAxK36D6jrQFzG1UZFunVmcu4oIoQqzPBXx1YI93BHIHPis7TXkabd9V2UI7rSMXTE3PIcpgUvZdJZUc7n/tjj8rXrAM+3dL31vaE66ZYqHIyNSJybjLZ1y+CjzTIXLbm12EI7I7AsSq3wFef/4cTHhfCkW3v6X8/xbOfcLFdGfnUyPpd8rEmzLA00wKgHnIwcpw7Fi9Jozv9xnRS90uJKqFHwzhkzVaApoyvOXz4Bb37ALTP1CBClLz2FvziutnvBuq5YWsP5YcPp4wlQ4PjTwTLC9I5TlAmwvdLca7KfzVFsac0clX82R7Htwxnv/usdHv73I44/H8MRgBOiAy8mOUDR8QDBOzfaa9Iczt3X1dK1m/wx+kAfW5HZFP3DwOGn1Zwif8likwMKSPM04G7wxMCGxxjGF8FFZsQk8DueJhJ4RLx+QlnnKlfHGgoeMCDa8Mbxv6vgBYJ3Yhm3Tk3QOtD9uSFWRowZuLQbJ+CYXxz3bpU6j3T6FIjJBPzuAmCVYWkwziXS/VQTGf03BcLRfZK3mDadPcfcHZrxbky6DXVeHJPy9K+V75NuVJjOjkyGM62ZLsHw3M/3SH2fln/Bwz1T0BEamS7jpTORT9AoAnKVPtZHdbpC4yxegW/lLwKGIFzTc329UcOSMPxDOsT9rd9ADuuUFn/AEz1M5V55PS5cCFFfH+c3Uubp/mt6wOir6P3jPFz/Og7XeufhAOH7gXs9MtknS7Xr2p13D2zubNR1FN59DVfmpru/f7a9Dr8/Ctn/ee33sed7+2e27wb0XXuN6H5bOoU/3uKQLSlw1QMlYz6GehogMeG9h9hvNw6YkmZtzVI3joG74wFP5w3oA2NZcVhMLy+t4aANKsBdb3gIxmPKvOpZz0PYDhgAD05+2LfUox4xURhYGOz256PdharMmHi3/30/rOY4L/D6D06I9x5a7zST99a+OtI4D5iRuh4QydLY3z2AOwjORVSoRJ9d3evc75UJX7Y8z+Ies2B07wPZCnn8cQg+tBDTLt4wCUgUKHzx+lA02IFtdEu9GsyxXY6SHoZj0RRKKdaoQnsHRPDYFHf0PlP6FDs85XK501kE5c4ZYg+BV8C9C5+scRSCqktkn/cCfnnP19rnV4zotyr4Ivq1VQOQEeV3+gg83IMKkOMPPwJQvHz6mOuhijufM/cWx/ns47+BWKSJejp3mfFshCcnhei52f5XaH8xIYYK/La48G/f6SUIWGTFCxTnJ0++46nPCI9ITwdMSptMzUmPZ/PY5uJyz9Pj15S5nBTXziNg6F3rh5xXhYE/LSVc7kMXsadOr653vWV3Aw11cWvArTo1ledik9bdetmYSvJSoXQ5tHk8vCYXv8rVV867b5SBzti/h1Q+PaBYVQCs5d3sw/t9GZBb1k9kRx4BqIJNjY60JlBp5vku5lENwAyfqlh2XkSmmEsCOsbAwLAIP4xyyEsFLc+zgECOiFrodZ81MSeP1afyWk30OBRy3pKwmkARzXyRVzmi3UgccEWA8eKKTwD97BHrsc9n9606CnL+Js3jnBqYdnroQD91tKNHMLc5cqOtFpXRw6OlYBD3IzCn03JavCy+5zVr+grrtDHKqQCgxb4Wp02CxlTgUuKBNA9nKOsn/gzpF1MtTnYa7rsBwwdVlGzd6H2gqWJpFkVitHKDwIxzmyqW0YDDCvRhmTw0FTKDHtSJAUYvVQBPlyhNnf75W4dCZaB3gWybrbFHVa3rimVdUhnfGvrYPIhPMLqR7t4Z1Y444JrzwWt0pO5rCRybd/GlLKNwkqVM3c5o5hG0TFtGlpDBi2BO394UGM2M52iQMDjsRsk1Lsp/+Bgu7vX/xN/9Jtg9EzI1YVHeHxSqZZpi/t5ccaAeTc7vBr1mclJrUVu4NU/3KV4HjgOER54Xw4WqYlHL2GBw4zpl2lpDcFiYGGegRYKtigd1Cuzw4HqpatQ5N0Wrq6xjHCOi+MZQT/MuEMmI7ICRz41KFZURkB3D60h6dPUEcUbhXUux7pNdRAo22n6mcUA1nbMAsSggaWiSxhrVxfYfPDPXNVwQYNvOWNYVUDEasPhae4Q0R9BEoWK1kR3UwTsipabzZToUMPpzactOYe5KWtaIVYW+wHgOLGKS56Pm0XuTwtxTUasOnLYNo1t2JwCQdc294utKOauhmYORwmBysowws3NSynRsrQnOJ6uEubgSd6BBbhzPXGY0h450fFM4bZIFWATjfLY1awLtZzixB2DudDwTBKb0jtEWtEV8HrluYApIAcKFWN0tM/ZkiJxBm09+uDg4FfApQ1XzLOWwH5J5hEJ+KdndJGTUeAwvv30MOdWquLK/xKWKf1OLNLKY1ntP9ALmRYnO+2hEZ3p2g8UX0ATSH3sYsuStMUBmebG11xhDvB9uVIdMqbTLy5PbGKPm5XmqNO5RdtgZ0EC830EqzxYI5ep49lq3OLlswGfO8cJwDlNLxy6NRjwvkbK0GOQcvWkGqC+fH+OMOroCTS1SsvHMKaVOssF9WVqiNetgQ9DV4E65zh4hQU8jAo2dsca0KCszjLjOxwCafN8WMiJNMzJ9XgP1vRDlDkKmKrhVnlBN+h00tOLtLOiCxwt9hZbEerssIQKXzac7cjxdnYeUjQYgjePO12AyXPeazkAPA57yfs9wNgrPpGNTGCK7PQdGQbc05hrsJd5v40sjPdc0nIDhexKeEYlRHSlMFXir0RbJlNwW7OkRn4uTt6iRnDgrLmsMYPJAUB3GK4hbzjMNvzIXVnUAFW42rp0T5SMEp7rJaSmc1oXIMS868Z4R4kMNHkMyT8RQM4BW3IAgy8vFfaOU/SAMJgyFCBwH4M8Ai74xIyLXaMCyI9U+xKSt04cTlr82iCw4/HBAf+x495/3OJ83bOOMDuBwPKL3DhbeePxfjxZp7nqx+/98a+VTekcTwQ//1w/49P9YPfGXX19w/PlYJHTHwmZz3PABgndY368YHwHFAx7/+wFv//q3AL8vEUY3zqlqRtLuMvm2dejHEfxfRLD9uoHnRRWEE+jhp4PXuR44fxjoHnnO9maiIabbOW4dn8XKyuybrTPQfrjH9ukRt0gjOh2JAu9F8NmdmZsH8pygWNYFbxT4rFZbHF2hzWsnE1Zdgu5vvZuOyWF5KwJpnt0Lpj8ToTOrBs8ycUSwLS2Ayv0PIDJGhhOR5J4xPedAV3U9ANC7fVi4Hx21QmYgX+Ve5CjGrL8jSpNeNy93pV6+hPRlH0tA3jQ2jt/kvbUt0GXB+XTCUMXRZdK+P7e63AZVLJpZJIYCL5pnNTpOj9GniVFcYRYJo6M5Lw0mgqAHhgseFlXgJY5vosBZUlcdL/qWFjKjRH82EB+PpAxywdeA4NUhvVM/4rx1clZAXb9CU2HH3gU/OB58KvTW7qec2Y3i74LEvt7+cHbbV+4PMWJ/q6T9Z+IjIbdkljbiD0uGkbcENDU0bmZEd57cKc877lVNSqXt1ybzmjuFlP++1lKm2fdwXddcr11zOPvdloL19X5Ffm/Il7/vxxDgKoThe/u3tO8G9H9bC8pvn2YOh/2l+nHwX9RfsX9DBSdP474uLWp4bsNSbYgbF1QU8s7e235L4sk37LcjhYPyH8/GWgnh/u+VRsH8FQJSZYW9QbqXz/c6v+1aepMHMeP6vj2+8u7XSPgC4AW6qwr+97V7Ej+t0JYQtDmeyr4Vgt8a79Py6/xtaKHh5bspTmG1SvyA3S5mVIUKRVeBdK+/uWT6lslIOAzHaGgRJePNGqnZbza98p13JrMBHuM1KZRlCvbXPRW/Za2YzmzfrB76t/X1RRTAA27Vjy6f7rH+sHD4oHKY8wuPvf1YyucDsl7it7YLuyzX3QXeFCR2z6niALha6luEkfmgYZdq2s2Cl6oZie61TPdi09Q3LnHi72t5+L7+rq8IblJEN/nKfbtWlS3Xx+Of4jA335GJ8fdP7N/zWt/1r1695QqrKT/LBJdQ3L4yDssgZunDzOihsNpt+ZIxPDW1IOqP2gO+L5RGHO6WNFx9CxBiPZUK2FSsTZvO7/kWmZjqmUphv7mFDD2/6Hhz66ikqCnl7X29ProbydcGLOEBH1juG76PgXYa0KM5y0hEZ+TByJTyJAx7AlG/J4VuHqE9Kfi509XHrJiMIhGhRUNTMSYIhyyVjmn8jcjufCwO6nXkdjaza0MV0n2xGRGrAHSg+fXYgzBHDTRAerdIoOHwgUakPVA8rpmSeHiafgE82XQY1xKMns5sCHQzXO9bx9g6uo9j6w2tN6+jLjsc8vlHLT3BWDi+wIJp1crMLva4Th8IT52USVazEUWxRNquk5GEnUa0R2sQd4rhAZzzmHeR4oL4lbHELf53Lxnt5/01zN3fH30Jci9oeuC7ySMNUb4ePqN8hhKLUNHnMKQwxFScnsdcpqgY8ahd4zJVr2YGKoG4hi6VDnQ2UadrkmsJl8OCBpZ0jS5nDmUkuo1RYeUyRozCOyMswvjDSK6co01puBEd5jzCJWXuaOW7K7K5cfhinTQiJ/drK2LlaYIvuGF1dAGK8dlg0Cd6wLXehl2nvxDTn8c4xLILjGLcInAj8o0XBW4AMYUuy5HUUQsI/xkLFVqUc+Wp4LMeoeifRx/YtLuBXiIV+gy76QUxDDlyVb2WekkHu2dpy8FSf4rjBnnIHGXNlQIgVs6A9EJ394bj9JWhceQK57Nbh7ayM3V+RhRTSn6d+tu9ZWIIu8/T7VqYzfVGWSTn5GitsyH4NaFir4Bjf/X2i3s0jYu1y2dV3IoZpuqwKYvvubcCwOcBeSuRvlfKjCqKi5eMUAAL5YFKc1X92F6IlFBmy0uqIyOnOTbQyQ6xtiFP8SzJ8iqqGF/MEdIcgF9wBcO9Hcwoc9vc6cPubADQJCJiKyAL9ppjml8UKGQFFncWmjanCLT3oE3LIuFgRhhZST2b4xDF0vLdOqyMCdzQZfYoN7KTvpC20yAaMOYQJLes84+gARfK6NdbPkPwZ7py/iE/sVeTXsi0DDSex29lLFJkSTO0MLOZ8yZ3fA16QUNMxQsfpF33TDguhwymBY/ScrZeWeawjpFzdaJhyD4DF8TrCsMqm2hkN6GuoOZzSEq2lz6yBATXKGR/cd45OgasdAXGwfppO+pWZQ9HcJZd0nJf3OuMTyljlFEmPBBGRoowpwnhSrfZpT0vO5LK8blBU5pAejqMMEW1yQ+5juyD/KOe9y74WiU7KM4nfo4cUNzer1iW1YyLYCUJykwWzYwG6FAcflwxugeHAHj3H/fT2onj6ef//cUB5s5WQzgd6ACGsiQA8PLygvf/9Q4KO3eN4ngxxoZt62jLgu1jt7TneED/KBC8M1kBDyYvODy5Tl3NWCtiJSSshCcwPtKZ8RJ3CVcMj5x32r99ADo+4YsgAjoqv5h4B/+jc+/8SQXo+AzAaqdP/BaZgTB6Vgv+enL8uVPFczNK2JVoYk6aTQFhhkwHBEtJwZ0ow2FXzF3epzmzfV4TJA8UvkfDYWnerZzkDkC8FLySugsU8lgMkXHd98dIx1w4j+fuJP3hf4XJCvxa0KcQCDINPlNa8izPs4gAWEQiS4GAOg1/v49RkPJGxYOgGjrrlKFVnaIJaxR5b+x6EpOFG/Fa8qe3hQwVNnSVok74uft+SYP/QPsTj+5vN/h+wvrTjxi/vcfAhwmjFvzoePZxZ0vY766/vxnLS/nm2mBDLV9Ye0GvPKdW3gPTW41h9LGPzWi6r7dI4dN+r7oeYehAx0CP82ddxyjcFTuILlUkQ6S7ddVzajx/zxMNH7DX2lfW/O9dlQmlrrznVZST3d8/+M7v7V/bvhvQv7FNHuN/uhP/G3JqSoYy5c4yZhikwpmY1X3xtBi9A1jByBH4PS99g1WFa2jLwJubFecOLAO4vRF8PA+8f3uHp4+fgHEHqOJGrX7HEQ1nsSiNFc3TGrpI5kJrEjgkIXYmLC7cULkt8KkMIC2VCi0agMqYKQBdM34/lOiHz0Ix0WrxXGv3ap5bP2h6Gb62cnvGrAB+4OEMTD5s15mdlMT7lddHu6YMUaQHmjG5S2WTRYgLHuVyfPmZnadUwgOE4ZRiaUD3CPEBYBsDIh1tNLThB14NThmCcyjKB9BUcVhaHASD+QknaAtnEf8y/Y+VZGPcjk8pn6YDgAKejpFGegFTslXPvy9QN3LXrA0U4wpIgNd1ZKp4guIumG/eKxDcqaW2CgZ+AfupM4tIV+BOH6Af32LBPdb3K14ePsX6KhD9Hv1JGsqfoy97042/87Qb/+W7XXGjxFJG9JlQ3YZCsGLzWswaHu6KbXTAo85XH+Ep8DVpU/3AA6xni0LfRg7bLCgQ0EkjUarrALpHO2gxcvohaZTDku05TeBX0FwRlOTKl28WJqpSeNfCUBE7NXfdhYBf+IP4gaHeEJG/LY+VQEYaDz+oM/JVyzomnd0NvQ66zlviGDfPR2NWoORMFVlNxbSPEeJheKJ1fkvXFGRZ912wYcEKOTboaUBPiu3YsahCFouuXdbmCsUl4NZKBFMYDv1dNbMJL2qBa5QKsLvMg9on3ZEK7/7SjS4dOUuj6BWUDCblvAXqEekSY+2BnzmWa3gIaVggaLJCTxvkxmPFfR797IeN6lgmxDHBUg87hcJSMSQco6eTnuAGowt6boBYtObhuF7g8jXOWKNCbM4IAOsYVtNtog2uxMDwIBkpCLrblGQ5SDpj6y55oIt869a3gE5as9MU1ceh93a6YqpJj9RWZJYVV+TYZzOaKexaE5OxVAwfLOKVN/tCMKpOhss1FrMhIf+kYZ5GsTEUsg10bFC1/X3eTljODWbEXBNKqk4HFdAlaq1qA2T4JBrXgrR3rz54nVtVZQnxDFQmwfeRpNMAU26iKNtpzDL5rrlRZwDLYnnBGbWiVu6lEo6I6J7GzOhZtZrLo1lkRdP52asS3KV0NImUE2+nAVtBAy+N2Wg0bO/e4x20WNcr7x9wAyC8fjyNBwlwGsYEcMU2eWnu2aS28Cj0lJPM+D0yYlHK+8W06uqZFcbwbFC6YIzNaaFENPyAp+YfBhhbEtbzjoUFo89VxevQUkFCI31G4ZBup7ykQbhSjU/HA8KA8iRlSEp9BZPVKF1k5FANg1ROXyyS0bPZhCFlAOthxWmzOtyyLA5TxcvZJK+DG9KNtFjUah/D0/FqAGRpzaKgiDPEX3cuaDvkIHVV8y6A3BgklmUJ5ScjL7MWdNYeZe3Ys8NdHUOkn8xJpWUJDoVCmkfRissUrjUWH39VjpmdU0OQaUWbxtrpigHdBtqy2v7w5+lUQlyw7CI2FywtIq0CUPNOSRwpkBok3n1EJD+dxEXSOTcgG6KV0aV6gjgCOKniBMXNRTGydEaBmvJ+gyKpr8aLhjJzSqUr6fBoz1p98mcA80z5gMS6zkAA6sFkf08YFJ02sA760DRuc2yUx1U+Q3CHIa0EwgrkUc2Ijoz+ClQQymvumwXj7c7WYsDkoXmKqU4ldboCLJyPBi6NUgeMTmmAy3S8RwfGZ3LzNFjSKLvIDaAnkE6Kbmi3t55mlFoJphxdsLSMnOQ+hZ87RAR3N7dWxsXlqdvbW482NnoymIGl2z7ceo85p1AEh2sSZGYAORzWSM8eacy51lWWdDwBDcPd6LgsRstZ45fP8v5wnBCYcUaS/gZvEYmxiajTXPvMWrxhnHcSnDbVvQwROw6UxyrWpwHFz3bKNTa5iCg+PI2rnREBatOVn6m1ZwQ66ePwlO4mMWFsGWlO+aT7GYE1pI2Guyp/2P06nOc2NzQ5w4rjLiMv1R1aQ9aZ5WH7zddAaU5rwcO4EDxzGVy4Zwzrxhh+8mgQbABWNDB1eOJYa8DQxZxbPH/5UDUnz0a/SrEo9hhvwxAr4dQHcS9Gghs0bNy/Ctw6/33mu5WODtVQz3OKjWOQUIhAxEp5hGPdMMOo2fdmOsE105C1sgxB4J6ks6Hxp3S8i7OemgK74Q7rzU3wpWZMsFBzl+/VeHzvHceD0Yf1cMDT8zNubm4MZ9viOlXB3V9vTbZQxeLy0PPLMxg1i+GlsVRx8Od7J93r2PqG51/OUFWsPy44b2csPy4Q/ITzx9/QoVh9bw0Ap77hcPBE2qpgpiz4HthGjxkdfqbGxr73XzuCvwFeRkJiT5pWpoc8+uQ93QddDgZv9F9z1QMRvfc79RTVD6l/m4Mj3MknyEOe23ntyaPShxv57zwyPcq9qffjcvDB9z8dXUezaPY2Glqzk3qDyQoNyb9OXr/5xmHB7I5ZSpFlJvKzKp1m4PsZOLlYc/QsB72brLn6vIen/M+sEQ1Tuk3Yfh1+TmiLZ6Abag6oQR81z8YJvjiHmhMlPMcet6lCZTNHBIf9KegYgnwbLXVnNafXbSQO3TgtJg0gr2LGlKRevCERJBy5PCLdkm0pmB3KzpNlYsZ2An4PCqif97gujgEXtONaexjwZywAACAASURBVP0eKYBMvCiaYkftuQcajulYIWWeQOIxZa3OOf72G27/+lfof79HxyeseI+bvx2C3o3/tsFuVwXGP9H08mtATHbwZgav2OuTKIKymEFgA+8k0BgKiyrfWE6lOyJI6n25iiO6c06sM6jDMZacQGFOmDEciWFdSCT8fSd9M9hufoYL7zLGVZ40/907ttZr176TX8WwriBeYvXFAEG6GTzVFyi0i9OZyujK7/gAf2//5PbdgP7vaCqzElIrMYBtkpaEsAPmBd2BTQSWLlVwPAAiB1C87EB46WkTS9W+HnHWM87bwPmjscZfTw84dkXfPuJ07tjUakwty4Iugg0dhzGw9c0EfI8kawsV9yMl2JxUDN1YpW3+Bou8qbWfv4UhAsB79bTtpQnkokb6NRqy+PMRAes3v9NdFLqPayCN4wCN7ka6+DyNwdfet7+215vMP6ZwT+WV3d7CE+uRBwgS+gx9m9/nhLqIA8F8BC7IUCoRhLenjAYMMY95tQN7+H6pAEW5t2CB9L0yCq6saHgR4C0aFgXCshrzmpnQcOBU8NgUZgHbIttfB+K+VrkNXVCxi2surnDV8gOFtM9QvAmGVtitM7LoNidROi+X/e9nGbjTR6x4i/5RASkpRl24f6OCrV3tZs9PceMC5plTK/yT7Vp2BFv7AVluZsEg/uNroxQG1AXxAoB2ueas4TYwAlsJq+FKj0iDV+fkQjiTO8exnArTSv8m4WYWOfbwiQ91Y1JTcPlEkaC/skFFro4E3B+vP2nPzGh4ZRxlIeuYQTjsSiFAJmFuBiyHTPjs/grBUdWf12mwr8juNyMkIQjvp1OEW8a6Gr3cgNMKSAd0gZ6BcVRP0UdFdHmT5siui7Y7VyUqFuB4VRQ9GZVjtRGZcnHq7ZwTqeCcQKsZsRgZ4OLdhI3EJQVMUQnx1Gi+fpJoZ4oGQT/5GougY3M+JQ6/svdkt1YK92QH0irsjkoNls7dlcqsYWVnoIZWIhBptKLCSYNhpJLZFEq1LiiBI+bo0SwFNO2RDbBITio2STxjy6Ui1Z6RNPbA1IrqdICpKeMg4escynkXKIZ3JlSaliUKBx4fwiI2Pg7W48vtfapej96MviKWxt3GQlnGw3/oBCMj+h7S0QYwGg2AaWBvnlmhqUXLjaXh5fkJfduwrgvWw4qbm1uMrWPcHDAOK9ZxwGE9AEtDW1c0MQ/+qJuOsmUm2lL4LWbcmbYshZrhtlrzuYw05WYMs3d1NUPCwADGwGExA0VTU1oNLwUzBjDc0MjxyeixztrEMtosLfZQjRRTKEbvlnpzOEHXHg6QZuxpWKSaWXwFQ+FV551Yy31oWX2XmQRz3qBR1K430Rm0oKMT0Ia4Y84IJwcAntqONcldce/KrNYGRl8MXyWjkGu0jjJDB9S9/DX67SyRRDyA7XdOnLuow1N9bpby9jx6UQDRiGEbpKvRALjMx1AeGhrUcXfbgE1Zy7PQPcDl1Gb1hn2fMlW0lpERC8OYAjfkjrKO5S98LUbvOA8vL5MMDXXWEKbRFXMk6GZUhgiON0dsXrt0cyMty0o0NYcqEnxtCEMTVFzpM6B0MOieVYd1jnf7ryobBeZ40LVbVrB1dUeMNL5z7dQnS/yijDy6RaxZGQ4vI+BwUCBwC6poa8O2mTZ2bQd3ptACU99DHgpEpZ6l13bZJoyECqBhnBXtgBCCaTCkgl4VEQGcxhbjg1XuvCa+cjyBmL6uce6i4WR31qz9Rer8SeGf+HlNlCAt2Xz+5lCVoxWg8Mr6aBmD2p7dYHh8o3PWKBFcjDt/uC5/XWthcPDnbpxvjoJj6RD3GU3egCl9A9qP7tb81p0UKWfkYpnDAOUluIHI3zkcx0lfmNKTex0wuUaG6wYEQfsIK0JQ3PFM4h57X/9SjBhQqNKlmG86myzAbGfS0F4aljuTd1ozg0U17RJPqJOwbW442xaB6JIOoN4HU80Pp598f0vNfq6fIugc7STE723b7L3NYUXlqlj5iuoQDhHP3GKCNp2KFWYkkl7wLviZ05HFpRw1ecx86xQYA6KL4bbTefvgMormuixtKXhZ6PS0dgSqRCaVcL6KJ9P4ZQ4oNt5yvASj3iNT1BjFWZovEccCT2lsIW/YRrfIYTW+VlO1m3F8BE20F6ZBMUqORAFtX784K6Bcp0GcWJQlyy5aoT/JlhQIh3Ziixu/VVzBLxjNDIAdlA/snzkN5f5tzRw9MSikBWbH2cLwyTNMQqGL6W766GgFbqwTPwQWHON06jMUBwXOiuAnARfibgqc6DB+LH2zM4cYb2qFF5gMZGvUxMoUNZiDyegDZLuZ6ae5vOzXorY7UGvwRjQygAVvcPPDMcoccXzMLkhY06mf8xlO65oOtKVhO1uRRtaxF1/zvTPf6ucpK7viewENY+sx5207Y2OtXy8Bcf4wsPx4MCNWa4C8h5m0i8OYAC/DSj2tbQ2jvcKjz9VSn6+yeGp1z4KjgPzc0H+le4nXD4fv58gUlI6ye7mWWMpGx8i4z8VDxcAGCcOBJoHN7/t+NdczCLIImBFHRfDcfMGgbkStMl46r4Rc2EmHbK4Nhv2tNcsg1gStWWXqG5dpnn2Sg/itjkuUAwoNqbCIciCqWFubyrkJuB1tneKc71HuDCGi2EpZU8Tv4TnczwStwWVNnzH5K2YYB09Q7jEp8ELItxylOj0Ud46m04+IZZ0RWL6XWxXcieIL5+YZnlTmfTBiaDx3JdSklp2KtS4A9c8/+BMdqd3R6JEaq6si3PT5qiwlKbGAMu0Exd1g9k1f/6k+yVs8sz8W/AQAOPxlxQE/4/TLr3j6P8Dh558Mj/AeHR+jj3cqFhz4D2jpYOcZcISyG/mX7TEBzGGcCirjmnb8gxhtRwOauSfJUiCngIpl1NvGFmVVJseCInqbjG7fmDGGkmtD+IlDXItN1GFgX2T8mOSDWRaP+e/+5d21yfzAKz9dvWf3e+rY6NCIIADiMhzg5/vYApJ9kcc7v6t680t1b9lnuw3wj8Ge7+3PtO8G9H9Ho/AOwRUdnRNB+2zegMUjXxVbH1h6t6iIZcEqLZSM3flVMFAB7o5HnJ9eMMbA0gTLesDQM4YqOga+jI5bF01eFkFzY2h3phzGnCYhuMa2ZWQ4fCINrszOo94UYV02PIXyetYn40qlYn2d4C2Axwbcq0VnQ4B3uEzjzroh//fPP+PLLx0DH6HqNW3FDOl+HgRQjeQ18rDAHcCHQiDfXSFc7/RaOnknf3SYEDPgv+PiRLP5vA+Dgx08792L8bHch6KclHqdb+TSuGC4iIRXWHPhp48BcWO3LsAyTDESHWhRUmtPxCJsRNBU8DaMBI7PoC4+lcqpoEQyWh+xwgRoBgw0KlND4jThk56ArRnJood4LoJWGTJxzF+koRhERNeF7m5aBYRRxBw1qhCXo74Q6tRfpjTu24rdo6HhHh2PoJ4acG9oSIl69378wwtqNCNwVPOezTRIOXgBrCY9AFlWAIqzR1MsejKBRSlCaQi+0PQQ3K4CTpkLLWHjirHFD3B7BSbUDq0tVjeftkNDVSzkK18XiwgXv0sSzuwzBI4Q3AKzysj9Ez+Wg/7ulmlEKfDw/uvjo0JseC2+6SApKbgHHhch0zaNK8QjqmI3mqih1erVUJ7w+sURgXgfY4qN6OOxnhakQniaZ+x5nfYGWxNTuhwkA2MFxO8NTVeoR6KPl4F+A+iieQAu71BY+ksUI4Q6bGsUDjgNhSk6FWjLAlFTKAzUZ+0/FOLlaP330ykUN/Gu4HUyr74g0pgR+mvclSslUmq9Tv/1KCwA5xev+S75BiV+CDwNYgtU51aVWC2ii/h4GtbDAmzl0ApFO7TwlhI0LAdXRjXWs3JDfzc60JzebkUhzHTJDXkgg8D2vssvzWkpDYANFsUdkcbMrQfuSM2ztrrB0A9XUEwRtmYsNesmlfUWidSNp4lHXdBwI2qKQsfTJjT4NTRXXKah0teymUKSahMeY1Rh0dStQYYrwNsIpd5wxS/pnKi48U0jzR+zCqkAOliF0A5WZ5yhfWCMFVavkjg0YnwYCl3XkEUgZth03XXSRE+ZbtFllV/NzfamK0aFRrz0Mg+vj6WhjRZOdqb0hUfKDigWxAFQ6U9A98OGRc1IMsTwqol4khsz4ICR9IEPHvGhAJYFMrIkiLQG6dWhyAykoR4K5wuZJmq0ivIHISJ5UBXSsoyOgUjINnDYBDXgRnSls7YWSjErF0D6MTzLjivtPdLbjJlAlxEGLpZht26dHkcEu2d/GoDqMMMo4ApVSqo0DCiGZI4QHbYPtu1shvRuaYTDQKY2jwGPxBmSSjiPauN4mBmD0WSZAt7T9Lvsh0LLm48lHPMANxDZnh4ww4kRRs39q7kmRgAycj78Rz1VfJUpAYHoCBwgDRBY7Ux067H37oa+NA6ct82V0UZ01GkjYLWQm68pa67K6m43yrmm0Y44BCAitLvXCpR19UjexGPInCkF0MAVW3+Tz0UVzO5FhWRr8PTQs9REVFap393VUQ3Xo342yYfQicoVaNuLpXQfgHaxwN/FDHp2LlhApTBlc0agpaHlSiNoHSuUZ9Qx4no6TjDmszwckFOoNKPx/VJeWmHxnCcoDiG/5U1nWNmicJjWHQWRPGvXN8/tDsATGt7gDorlfoU8PuAJ5JuTBBEtQfOapDu3VKTZ/S8iOAZfRcg6jMIe+sW+q9VETwdthT7CaOdb27dRFkvFo/ckjF7GDprjh+FtOLxhj3MSuChqcgfpeldNWcLHO8aAusG8vWnoXwYGnkyOkLvonUaRPaiYutec2WhISeBWB4MEYKVPZrZalgU36w2+fHnE9myZHZYmEeGavL5jWZaQQ7ViJg2NjvzmYICAW6yN5O+UWRJNPJJVmjvg1bO48xR/X/AMap7BTejEk5RSbJ+Itog8C0N+hFsY/2h0fHI4Bc12GlHBT57HO+M6scwN9SarJWV0u629RXepXZm1IkRM0zNZuljnb2NDH8PTY/egkeEH6Dxk9O5OZjXQw2GodELzLBteVqyamih3MHSTJwmGPGTEnO4yIimALeSRWDzU311mo9wrw0wVQ93Q4QNYBKLNDRy+ZgrzAKVDrCpMaZL8FbFe9r7hkeLwo4A6sVOo8UuupY/nSe2mufSIO1tEjuzCr8QcWoZnfomI8Tjc+kjI3Mu+qXKP0RrKXKQVnLvvw7LfKNsdATQsrhOSwB8aGbTgVPIkj9QX4l5HGJxcljNnUHPUPJ/N0/rmaDHMh5tbPPy/n3H3lxVtPRhOasfp+WzZlqDYPmw44SMa3nmwge3n/rHjpB3rjytO+AgVRPaThvfYPinWnwRNliibqAr0bcP5wxnrjyvWZTHjumeyORwFT09POB6P6H/rOP/qdOJ9yr4Gu4GBh6k0IZDBRO947zD4fl5sMba++brYfhJpeAHwjIE3via3sGyQhPfUFEnnivzC84cPMAyQt26ZHb4Ph58jw8BK3HRxd2kDWmTfZwgWtfKUiyrupMXZ/ahmRDeZ3DKM0PkeipDFUh5Dyrhm2cbiuHl2nG9FT8GVBNKBVJyXDpfbW7dyd7quiZNBx4wHqMtQdOLUOIcgnJO3vsU1iGD1DEwn749nn+ZnOzOCkwbM+6+J4A39wwT+3jlggfsq93PhFJTz/QxHHRAkeXPwVEeQdz7nD2RdIVuS7k4iW475yvc9xY0xi8swVVqJZd3JZxdCnvcaLNbgeD9mWNz89BPOv33AAqvEsf5lcRgotl8HBD8E361yMfHsQebXXUx6P9ddP/F78DnXERe9bcj74gbs5lsQ/Es8pNNHvpXbljg4wCjzYVHouqHrKGPKTCF1nlWOSDkjtn+O1fHHhxvjynv8nEE+V4hOjrG0eDD389faVTS4dl/wu/w3zRdIvR5yaa++kGdImZ8po76KGq+gyvf2L2zfDej/pibAVeP5fltUJsHvFP67KkYf6A1Ympk4pC1hIAWA8zawHhb0ZkLAsiwYraHLAm0NJ1d4iVJ48KgZHoKocAslI4JD1ki/MrrdyJPhzjPBK7/bo2lk/jp8eN++Zjpg18+//Ab6PJG4st8Jpv49otWvvJHPXau5/sdbml/kynW2B4FXSZrvuU5Q50hB/lZr2FDh5v7dnv1ATfWtI/qONEo6MIZAsQXLEzEvelXFJsDTArzXBXeqtgauEBdUAY5RjhLCB5vHMbuYn+txTXi6Jijhyn1f+23f/2dRvC2C1Bf/LgDeOI/+ck3QQcHdK9dFgEdRvNHHEFYopNZH2Pa8fT//o//dyoPE17mvPJxcmKu1CFtaxv8NrDjeozSkNDMyeCSC+NwmgVZz3ilY6avrePW6XOI0r+/HNt9zTcSYgVwNM/N3jrcIXlpH/kpTpDLk+s8AUsgTFwKv4brdML9vMtq69EnDWVXkh1zpyhdtGcmlV97XkcbfOoZKNw0/cw3564F4Xfus++E8oNItIkZhBgymlAylZ/Z9mT7uStNrX4shhpxJ4Io7BJyvCqhX+ru2jOZcVTc6JqXRWh7i4aDTOEhFapwQ/D7fPM0jecUjWnPvasKkLBD3XD8NSzfuEFBF1CNUrzei3Z5dF0E/G0Ca243a0qDdx/TaxAtctA+ghUuFRcjYRFyRbqVDTAnSguZzyrE26g4jijAUhiFPYEYb9eGIw6nJlNYU2qFtMQcFehsq6ZS9jSaj4QpmM8YDg2k8ATd6+wHSr1nax5RwZACyaMhK4hEozuiC+0Y2IY8mEjTH76J6H92y+3i9yKU1bO2cnspBnPNAK7A109aAZvPRKSNNHuSmjBXlM4cWOlLCwNNCMxKvuRG96YIGU0iZIrD2vaOvIsg09u6swb+qHh8lBsjKg+Dz6MPXgnOoeJ5Gh8jT44ZFo0/NkHzafxyfxjdR8UxKM5pXuIWshMl/DBEVNUHTcUkBSi80DoRe6Solc9x2ur13EGKUDKPFY187nrLu3PC9oB6hbiWXxHDZ/1Gqq2Maing28EIJBzocEUgSa0DrUJ1T8HatsEsohSlU8pdwkCyd5KqI7/dWepJXogDzjKJqClf1UgJ06FIw/fww4YnT8LaN7sayVvAJIbzIskC3zZwLMjO0j1Tiy1CP3EU6QXCuoYQFADHDORWGCnXLGKPJXTm7CI5YPKYM7rTTsDTDBYv6I43jaDwKbnjE7kmAAxDltcY1XHRcd7ivR0sj2xXQI6CnE4AFgsUV4a6Si3rNCpYdSy5UccOnXcQWYp0nTENiEe9JThFLlSzzlR2V/b/6o7cTsozSxa2Bi19rX0rH9m95+xY3j48IxzzMUel/ptWjt31XnEQs3WpR2iWjzPEJ7uLsxz2kOqCf7VtzYzqgEbGpQ0O+iVrolJsk1y3rK1u/NFhbxKXE2Clzkd4BwPhMg6lifEn6kzLcy6siiF23dM3tjiVO4mHnrQpZZmSZ0vELa8nnW0Yf5oR8WNG3DRDLstOWBTpazs9hZNHhI/o3eaAOYl4z7k06G4RQE/RwnmU1+BniV3459V7oSLyw/pnGwbNbvKnKAgHGwjcL7+VPxX8Z7jWR1/ymVsfjg3FMc97j9NprqXIwUgbFjGU6ehrPRzeFPY1dkrjGPu37fPLVOJDUSSelyp203/f/yO8JJAWpm2dEUTEZtsGy77RUqlN+ZJBKwH4Sv16jiDrjgS+UAjioOeVH1pudXmbqmZu5QApXcCIMaJKyReBn+Q7s6FqZTkTzjWGyLk1AQsdq10HhDof7g0Ua1/d5j82jglOqoG6rYV0Wd1YclhnJjbqtNciwLEnKMikADusheNKyuB7V8RdqRm9goP+maFjw/q//ZfR/O6N/GubMAODmxwO+fPgFtz/9jOcPv6LhPQDB8r5FZg1ZGkTscEYDr7hRfWwdfTG8GBCs64o3d3eADrTWsP6teeS7ZxTtA00a+q/nwlNnmF9iTF14LpmGbodUizvsIhvklf6SoqRRLngSjH7c+BP7+1H+SvSRTkl2gwCOx1F6Rwa+qOIWLWQPOm92L4c0iJca7qfB6yj3TsE8PoiQuIpBs87JnveU83DeMJ2DJSLBSUcZ4FDvVUvrFjy5SZHNyxLJ1XWtn/LdJCAvYrN9M4DhzgB+rEBKMGWOPibh2HzcIvCSIP5M0O/CgncoUvXs6v+p/OM6Pft62+PzNfz+w03q39nZqv7cFDj+5WeompPJ9uvAwEfj+XjvT+7k2X9CC2d4FLpnCAhm+OC1dOxDuVYDF4k73B8so2I8OMs9aegh2PTir0zf2X8YwuO77/dxDQdkusRSaNfem6P/57fX6Gj9u/8MXOLq3ytpfG//+vbdgP4/qv0e+c9tOYYZz7fGqDRn3a7EPKtCTx1vbxru2hFvfnyH//PrR/zw7h6PT08QAQ63N2ijQzDw5IdgMjOM4cxAkf59RV4JmkcuaUqj/Yit3mQLIWWaTSWGlVh7e3BB414RaU4evZ+WD0Jh3l/7lO8CYMN7AB8AZIQlb5lj9mZBT2CRDAKLZKj33Wve03Z9seb63pjPyTMS/UG8/lDyDryjEKfuEOCdP/gt9+pxzQbSWCtG+xlzZiJlLQcGxCHZFFbqKWsV0ixCb4GiQ/ycxLGyH0U/e+1gVwaO1rCo4tMCLL2hi3g0c2GH1TsrJE8KXjO8m8Jq24fExaiznAOQEbpUpw5xpbvmrAlve3pWvAbD9+GwfYYZzYcAd344WCgPwqLRFYLPorEJMjV0Cti8TrwUAF+a4o0KVtxjwIzpzHJw6+9n3eWXCW9S3Do5/h80iXaFHw8zHsDrnpd1X2H6OwK+hMn1RoVrDMvH0TdgeMq5Jq4855jEUpBpEbKo6Dr3Xf/xyd7AyLdJUALxgmPJk5xON8/OJ3l/3b/d73H4lL0z9bBLCSdO5wjXVKjNkM3IrxyJ4Vq+daIzTGNWlVr5WjugwCRbwxGmxNunDuLD/p6CiyqWhiyUJG7gqe9jlCsNLT0XHDUWTMpV6z8dXzokaKaf+yLyunlN9GXxyE2wtIFM9KY6a1UROiKYwvDg4PHU3QMbdjozkE+qwj3HgXE65UG4rg8HULU6+5OI3zh8jouUDtrsejUcETZGejvBE2R0eeLW4mmkLfsLnY6EY0Ie7mX6X52E5NxXwfayYW1LZDZQuAGl4Hp3XXffkhaQsYTyvNI6H9SmVu+w8TDGTe/RsxhqafToWCNOlxURiSzq0eL+DDM3RIxWa1jcGCgCi/iFK8JplPZ5D7WUY10s0paKYgEiy4FGhGoLg82QTAcOpcEc6fyhszxCgzphYpFbto7pCGIwMsOr4UQjvzMLBaz+pUA82l5EcT63pEWqodxjJADRcgGwYEHn3iGfYcHVaggmFpMH11aItRC2dLAcA81rblqaS/WoDnjNwiz3ApFE/9EsqtH7bEOtHq3THRrPaT8Pc5tHhPXWLNOGSqxzE+vTMrpJ4I46P2ZEVxsWGc8UwpeTRUTDI4zg9i6CRmLfSYByJgeOz+q4DiK/45eSHkW8TMpeJSJVVWqXmJTLQNDm4c8xf5AZXhWQVIpHmvjuqeKHh8I3AZYF2jej4D5eUaQBw2mj+l5UKNbV0/bBFNA9FOdGt9Zm9/exuDxJoqvBuEwh6jBvDTT+87cwGLvDBOuMzgun05ql8ZWLoiHThpMvkJlaQBnLzzXMiiPc2ja/oMM+F6EjD1KOa9JwOBywbZZGtRU8oTKXcFSQl2vApIllXojU62qZUpLM2H/FYU26r1AsnoGiLQuenp89u9eAYMGQgQWWocPt71jXFU/PTwi+bQmJ0L10SjCzyv+lMDcVLOsSdYf76Qw5HiEuEMgCQBvTTvjzDd0j1ao1rtJOljZhpiN1cjVl3yjj0bKOWn+svRZRseblmaS9JlhcxlC1yPOz33VSM6J3zGWQBCxtkn0mZlrkeTZ3TxkD49Erk6ri+YIG/V7Tr/w004uDJu5Trum+D4zXEP5PnrHqTb6jGAOGdj9QegQ6BMubEDnKmX/GcSAdpXL/ebdIHhZ7CEB/nCPaeA+gUBloeoMhz1B9ns9rpM0gLniEtssf+zTL5sAngHraeknnNZuLRGR9g0UsH483obsYWwdE04msCdAWrCKRkh4AzqeTGTO60z+ea5PAWLaMHR6oWhaSRVuuuAko09mZjZkhyJNCjmMefO8z14b8yP8ysm9vwdivg8pu79Q73OkQiAwl4ooKlsSxCFKn+03yicDFNHCrl4ezQA+roxrR0L5GMf4wdlmq2BqBDpRzDtTPm/nZ+kG8nzyIcilLEAHKbNIxCC5l4HNBX8qL89K+ZnzW/YXdZ3fupFwkgkVJjUyf0yK1l8x9TFGi3B0avGOiv4E3tneDdkZEeY61yvxAwtB+IzVM3CMwIrsI8Vi00Ib40XGYdKTsXTXhZFDOEriztRS8t3HeNUHzVNdtkWn8MQYdqAalod3kSbXIcnN6XstcnVcvK7SZTLWuK+5ubm3GIjhvZ9z/5z1Gt7KX67JijDPw0fq4+9sRzNgEALfHI57kKWSWl4+/ockPEAFuf/rZ9rYj/9rMYWcRy3YxWDrp04jsNR0AxgbZTCZ4eXnGKg3H4w2kCc5DTUZzhF48S0HINJjbnV/ornkxNwBM+8bW3c6FoZ8RxZMA0hbcKoBhDouPuN4o44Yh0c9RzFR5q4XX836XiSIa2xbIZUCN/f3SzKm9MZOOy7ZedApfZOCNCp4B3CqwDcU5UuxnCRyF4xznaxjq2R6Yuww4q+JImdHvAhRdLLW9mEU5HKkZVdpUgXV1fUXKh6RgPOOkHGILYezBblzaggZg3Qwftt7xIhZ5D1h2GgXwHMJxOnnFH1E7+sD25mdxPBDBC6MNitClLjdUIzp8bMmTHO5FvgDyLFOJ5Q9azjjiNCXoOOcsF899rZHHB6bs6XPhLfvLzn53v6vLMwgZB4mFgMsebV1w9x9/zXOYKsavZ2z4AECw4j2Wn5bQQ3R8imkJrmStIi5oQwAAIABJREFU/Qq7AAodvZj/JaAys5qNlzQsdAPlc5bKsDP3QtnH36mSehrqJuiUHHrkAtE9rZlHncioVy5fZaSUsS5umK/o7hGU9fwWZHpNStrD90KnUl+zG0Id236pv/b9e/uf374b0P9NLfjThSD++224cDjGsFpby5LmMmlextA6Hwo8vZxwOK64uzni5ckErnOzA+HaljCc61BP640kbqPQoF0TYPI8rnqYEHaVQvefb4wyJ6O5V+ChVdIEHCCuGMn2SYCfVCD4EYoPr8JZkYYt2ve4MRj9wca3fm3NGq5HxE/vvFAYWr+Prqy4vwKy2l89T+37vRQSTKwYSkOtCQddXcgbCrX8s4VJ2eGKgpaFPJkisIlA2oKDp/LFouhiY+fY4KKyRbXJ/8fem67LkdvYogtk5J6lkt3Dj/v+T3eO21XS1h4zSNwfwAIQkZka3O5jtz/R3qXMyAgGCZKYB0+DCxe0LpFBnAWu7O6Vsz+cYSBOwfPd1lzgf/FIo7syOAFwr25EP3lZYSzjUo7gWRTAI+6VSp9ybn5yvFTi1r1oDEt6927ur2Pidzd4nd7xg2NwBKE6PaXufs9ljDWZ0b+VO7i01y//kG/+sSabNdC4cm6d8TfhbDblf76FG878nOOzT4xcBA1WSGVhRlPasbXfrN+wMVNRtJvmhBvPN3j8FBbs5xJ7quXPvq+QYw9GvTWFpWjkeBPyxGEXd6XsOgfpUEZGFSyGkIzPwDW7I+5KwRwouHTP6YtgqIYR3V7BL8W5IgBTDHWg+VdMEGO9tgYzPPo9A65ocMPyhBkz0+wjIfBvxrZqGo45N2GvJiBpCbM+r/q70BRJ2AHQqEheY85hkYmaQhkC/JKykwAAjX5mfJyuWDWlBSPRZ/TFWosKMOARwPT/Kzo8UswNjFOnR/bYzaz/pn5eQtxW7nNTAEjdOkxpphKlGahwbp7WkrvXlJT228ZpjArA4JWMnqoIxrGCNh0j52FgzkMoiit+tWytXuqgwSAmqcrh2aHBzvg0LWPimrhQ6kZK7Ub0tsbc/KwiaIO7iPROYllFNAznaArtVvfdYs8BaWq1w4uCHFOhzc+Su9swyNdu8SuuYOZ1KuFoHJixLtvx8wSE4TUUAwrLZYcwYm9wayhtyz7nvOvJmvvxzHCumjscleNy56ENiqKymby9Kyk8ha16FPrENlrdasR6hPU6PKLPoimpHGQ0O9czlIYBzFQ8ET9MbD3daDQJLB1wk8ABFX51XtwjELE19K/amxvut4aAivnP0ReJveFp8Rk1KzyFZf96hB/TwAvHAT+jreV4xRVEo5ZnSFprEV1rjKeOL0q3gAZhprY3vLu0HjxTrAX3XKERpDlGB5wyiWV8ur+5xcvLs/F/3T1oh6J1z8ogtuF6a5jDUtMSTnpcocuSwDujSOQ6A2J7SIHu0eiRWkU1HBO2T+5aa8AcCe/CQ3s3xci3XWM6P32rXeDOoi1aMzXZHj98p082ykfn3nnCeODZ+KrHO8iDYH41GVqLgwFg0XWKb0WkZ5+MjD+GUjlpwIaP5loU2YN7nE6Pxrs9Q3HrvN5z4W9uEfhbbee2KVETvmmLexWsr51bR8lWlOsBbo5bAP2aZ4KzsdG+QnELq3eefN/ldg3BGwQN/a5t9kjV7au6IVdgGRrIyxVYN08lYRlnDLnR2RSwedNRLPFJ7rqq4CfNn86ngbyrwohA+FZmb1MmGnroASpPXt812V/1eM3CocZK1MwVqCzaxEm3Z5p6yZV4Nj75K8RleSiABqqIRJzvJt9E3n46XCWglMZzdzSrEeib1Ml1XCg00KPQdW/46t33edLI6rzB3zilMC2fAcrJNQX2GcC2GOu/0zgO8iK292QYHJuSrua/dXxm3EneZGOgDrqLInts6SpnoewseBvkQZJLe6cioe2MrDv/NyyxZV02pOdCPz4e2xUzTo13hRsI7j7+GTncjExna008+4bjUN/gUxlw0aHqKcpnw7IsNvpmdP/o5V4e7h/QxJzo1jGwLIuVqFLF2x9HrOMPDJ0YzYIFnv7L9uX9f/xnwPL2P+7x8l8vMHeI36AYePvjd1x/+hPGH4rlt6T33Q3Vw2uhzz8UXRagTehnQf/kRlR3ej10+9yaoC1L0G9xvDCOA+9zQOURT2dPWW0FgobSTtaWa+YikAWASMnQeKmphlM21DI7UnfRHV+GA1Jpc/LEVbxrY3iFsRkM6slXmfFcIhWg4Nl3/1QAxSmH8g1pD+UnZtephjIRGPWRrFdsNNj2zADKvRL8aNmoznumTJnsn0TWztJ1kU3qyqV+RERwDbVo8s3SavQR41F3Qgmf16T9z2JrEmdJqB4sGK/Ii3TgopNUNaKnLnS7lgLBByeHo/b890GnCbeTN2c7X2b1G40LQschyuNJ/s3hPOSIiekBe7GurWGMERmo/h7TvTxWbM4C9YH8a4xCp64Q+ZnXbS4pF1EuHeGo7bRYKfM6qyNbeW0713N0tOKVvH4OPufu2/KS/4Nw/dV+tQvtlwH9H9XINxdZaN8uEQIiM4zVhUW7+bD0QHzqyiAjhBM6Jh7u7rC+vOJ9tVro76tFLExR3I+Gz23FHJayU9pEc+991Uia6ekkT+SKwm0VVseVNbphZH36zlck378Dgpbe/Ppv0wivGZKToXry93z89z9j/uWvQSAtovv3gHfTP0Hw14io57+FxQkkTAap6LfjnpP0M+VzZZlIrPkvlVmcvxlCUwOhAD4io1o+TD1L7B8g+OqwlJYCS41gY63MPaPGv+mKvjkF2iYENZVuEYRYo9I9+jGsBm4ryi+F4tgEoyW/4drDYgjJxdby3IvviwdlqqpMmwW/x6JBrPNIm+cdEX5bJSwFw4Szb5HwpDt3sJ5FcYeMWK9MJ5+3sYo5OjjDrXVTf0cJ9CTAA3IPxT6SvXjLH+rawmsvWSR6bcZQC169ZtfS6cVMAxQjf30+Kltv0XOS8mYdqvqo/C7dcn224h2oguE1UiurI6WTcnd5ww4/gGsnO8VdgUn5YatEcEEPZanj3Rk9HLUkvWZ866G2BpARDiG2ldSVAkmBHOUlkt8rbuF+BJlajnm3XerX1qzW2Zi1eJXVc4UIDn0BwqklKmnZWRWgd3uAaYDNADmTmadQFV3XjA0KC6LR3J/KOF7A0roCwAinkEhBzR600rGB8W6Rd3JzA4XRJWPaO9BNGNkKADshzAE41qONvZuHPY1EdVfReCMCjFemBV1c1N2Ac5teVnP1UplfPMMl122ozbmBUeYGTNFk+VuBi2W28CgoT7PePfKAkY1R4Vkdg7fp0cjwVO3iSh0Ebop96kIQDKNjuTI8wOL245g1mA1rKvrSMFcar32/oAhP2OK0MPSJJB7ziEWRFlEAEsRgi15CMapu/BvqKdQVmBNTBF0sJ8pUQBbnP3zuIihRq90UM7NjygjFQt2AFPYJ09bcWKBGa9iXiCnBrQS9n2Ovk0n2Zuo0hVsXtN6Rh8f4nDGMbxrTcElzZFCdK6qC1+Aww3CuY2CsHXNeecrSLUK0GQNoi83JGRkzovscKTCTFklGQXBFuF/ANXTj+TkP/fgsElH6ogqGkdoZF8wGiwTvjh2o4BbBFIvqnMMcLJS1i8Wi3Pt0jsTHasoZi9Sfk7XsXeke+B1WW17dgDgnVBtqNg9D+I7Lm5crYjkLcb5BM6OHwYewyV6EeFEKdlRmuJi+p3Ntg9dxRuQkssH3+2DpBKSC2XCgGRnWcbT+VcIgr1BLr63GsDHyQcfEOgbGumIMq+/JFNnqz8W9ns+dcOw9+aihqfiBes4mx+Mj6Agc7m5WcecW7r3pcGWEemuL7c9uZzx4YRGr98rz7zijCYJGydzhHyRfuLJmJui0UCixmEKakYlUJtFXFDwTfG/Aw/o8jhVLN6W04bVm5SJ8TnGkfU15XVUjeqO3bri9ZQTv4H7RpMnkCbivxOlKXw6OnybaBB5u72CpSifWsWJi4tAOMd85FQfpeIfTjJH8yDwqFAPtsGDPbebutM+HxVLHR2Sqki6QVvp3Og54LVltCUcVcwwDgKFGgOic13RANA3KClNG8P11PNsmJ58q/yVI5fIB5GuLQVyZptQuvPnl2/1rtDgbbt7xvL/NcPKDYD7autZa9yf9fqNdcfzl+1u9IUhImhFeVHEt+UyiJ1v3FeRPnyIrBNde8ATAcOecd6bYfppoCrSHHqlwBb63uB+Usk/uDwBheA9FOwD96vxDcNXZn+IWipfg1s6KTUH+rn1ON2g3qRCOWuFJzhwOzaMvCYqaT4AOdeYEF4ZMOTiuGGhLD9pJI6w0N5ILrKzDHOjd6i9fXV1BVfH6+mLvYOT1Nrd5TktSxogoXftisHTdzZ5+aCKdLYBUw+AxGU1faIqC/HE5C/m6DYNW1dI08DKLFbO2VMcpA7HvBQFYqJ10tMVYMoOUpYM1h8vpNHyTxr7S+kmHshE8I8m6pcOXuGfo2M6l6lcIZIU7JOS5YXaBlC0TvDwtlZcg5JPLr1go74irevozObowRACQ3tCmOAw5lhqR77yQ853pyFiiQAM4ftoEUW6oTXNAfQX3S2VyijEFhO/AxEzjptD5DN9sk/xF2YMBv5bRjdjAz2lLKcswVHEN6rQEr1B8/M//D++vb5ZmXXXD5/o0AKXDz3R+K2lrZpLw0kQiOI4jMAWrGm/z9vl3S4n+7/+JQztgnas53TTj916/DGh7AtDwPC2ryc0Kqz08gce//B+oAItYivbRHjGgELUshB0foSo4/KlFEk860+mc4Xx38+/ddQDYGHwNVuSfgONxhYhgWRoijaUqjr8f8aa/4xHbfct/n/yz1aROCXBf6cUMvBk5TTn82R0Km/A554E2m53OGeVZP/AisKxV8DXaBOEg1iw3lo2xxk/dTnPIN+fMiTeVqAEdbiOOB74WB5wqR5TuUw4XiZrn1wDeFF6yS7D6629gqc+h5txO3aJtx+YRDAJl5jl3Xm8+yZCdHN8L7KxOIGgT5oS4viNg43To2fHEdckkAVgWTQB4dYeKSR6XHnYlS1boM+Dr699DfSe5IcwnhvinYr+tEX0b/WwfHtTo1wDwyPtIm/5OrfKmiqRBIoI/KXZuwQX7ncFn1CECio8On+E4vU1718v/fcPyp473vx59rVzWFUTGq/WPFat+gaviMCT1v6Hf34PgHDk5O+HyscivdJYPwzngJdWA3tKYLiwb6M8259nrNZNZBobLl6s7ajPgQbmCWvgdqSwK12M7ocr/5LVTYKRWr9ynp8DR3IxFgFAC5yIIz7V9/xUW9fuPtJ9786/2v6n9MqD/Ezai7Yu/OxOoqtBGrzWxtJtFCT/VItSvlgVjKA7d0vNhDCxoOLaBRTuuoPgiA312TMCFm4E2u0e90RCnQTTl740WvjlhgwnrtJ2L7v4qAP7yV3SkwfpRLF2MAGj6G2hk3SeTA0wpvUBCnD/C0/TsWhXDz7WS0BIN9n6UfylHPYWQcmpwpaqhXQDKz0Sih+DixFzhCdk0vTEtZaqPbVLQVIe7K4bnLGuuUE0FgwJGYJ0o2ySMaTaC3MwblIJMEQhvVPEqgq9niOSl9m3ewn6lvGfCpHz3SUYZvYqlW7+H4NmvV0aR7U7Fo8pPOtpy/2caUyZlojZPDcznL7RzxlbAlRM5gJij3b4TSs48f46HO7evLuKlS2NO7cz2yR9lDs90d17Jdv6H7+HR/Y8bZlrzS95GZwo3ZvAMf3/oSOnm23gz7jj9sHkRr9p58lrDQCgUE6ekMTOinkGHKM15E68HE+7nRky5yFdXhyOBKRqxdpyKJhxfjrvOnlTEvLddWebGxzR8p6GLT55uHc1DVIFUzkplhiv0q3zIz+fWUgmP/dqVbScgeUzcCeTvRg/MoNPcy5c1bLsLLGiZ0i7eORVzNjf6WL9NxIyoLhg1F4waXLEVgpNHayuFXjpNeG02H9xYLeWwuKB9akT1yP5I5UqFmBtXmFbTaweCApxuk+DS0BhOWdjSmIpnqejlb1PUIxU0nF6kdRPbZwfacMOCBM6OleGaCIO3yjXADf+pAJhTgTbRpjttzemga0YL28RUwaIcKcfriuvZrL78BLS5MU2pfBKbvzjcWgPGCDjqVPTFImBpPG+9mZOFZxcKw4H0mIrw/SKbvSxAKBgjHa5Hr9RoCQHM2D0nsCyxahtjtXgy8TlDMWQLqMCcZohpZmA3h6qe8isEotOcgYapIdRh0tWMbYxQn9IgbWLKxFQaxp138fStNHTq9H50Al6mQhmRF7MosOheIgEUiOEG0nqQ60knjFD2tVJn7dF/Xk/RNM55bkp6eL4r/4pSGVWJTqO8R935uRKRYjRXN2T7HqITxvA0t2vWiWVEfNZ7ZLQitq0cF9sjkmMq+4QKWztGW2NMzjP7jz0phUSz3ADPct2sRUGxX4M9p1IdF6UMRMWdklzL2oJ++YuUa4k4934FgOHTOQZUFetYsciCLgaTRXruSWOp3RCUTgGhjOrdnE0dD8P3Csduxrdt28zUeWcrvyJQmPPOBLMbGC59e33F9c119tEsWn6OCe00WgHqXlSVliW1Lwvpe92DyE9bMNe6y2YwC82dm2WNVfNxVzregc1+1AqIC/Cpp3tzq1QInue3rqAnkeA180Wl3+d7OG3zcaA9NOjXG6g0XOkr3rA1wtdxM8r8vXwnzT/Hg9Rn3Ucvrr2pIFaf5yd+L/1J6aDMzei7K0LFOAFG8wKuyC8Gj4SsmDPMvv9nQO4F80k348hPPGlpqmV0++V1d87oJnGJBH9cHaLsemtt21fgdSnX3S1KAOniZ/IAkQOwW4VqILC/uemarffFjSgzxmNTNTxKWg0VSEuHnw3/iKQPiePSCWEzIW+T9FBzzUkr9g7pyWcFkoYvb1xN/YHLDmq0xrwLT/G7AdEMInPM4DeI6cPB1R2+mpLGzWK8TjgGvXf8MpxuDeKywDmEVRqOq+Hjglv6xRZQLef//A1/hya57vYujfI0LD0VNNivj2lpvSHJvyfKS7639gunvw0N0t3JcKhJX5od0MGwWtAHFG2akdPODnmgMg/u2aDLF+b7TbiVwz/zLC9QdDyg3dmF69bw/PxsKYa93BD5kublA6AVs5S9X+jvnOZYNNAw5Wi8+iNw9duCl8+/g9zA81//YoZ06Ti0T5hj4F3/gIriuQsGi1+o4LkJbjz7At98xGeflxuY8cUxWUOXhg4JeaZJZpoQ/617hDmdxVliBlDMP8z5HM3xFwTzt1y71/96xRs+49F5SdJVLt+5rUzZm+wFYlW2d9bo5Pxe+vEXBP5XDdnydpiTNJwSUBalfiu37XliwOt3ThX2EejXqnhRymMShkyOY2M8r5uVuN2zAQgkUrdDM9Ld7rGz1hwVqvOg5ENjPCWSXY0ARXaU3PElotxXJWKVVbykQTpFG8W9g+6c+bhWSXPISynuRPDs5RCghZYwehxiuXREzDiPbeaODTfFfSrhnuB0LecYhLg0BqyRB7iIS39Ah/rtdtoxy65++QFmznh63XzP/0pcFFEsv3Wsv0/M9oiGB8gndyr+Yvf23xreP/9xMqK/ZXYbPdbeZrA7Axyx8H+tRZCNiOGe1ho69xVyX1tGRKMDZgsyR+8xR/mrNdDP4JFAMOdnetEAvrt+jhs+++x+4r/ar/b/oP0yoP+Tto0sSaaCtInMiCvsqFCdvafg44Lw6zAf9MPxiH7okKsrHN/ecXNzhfXNjLSLdry8v0FaM2UQFFMXLFT0so6i9x3CLrY4ksI4CbLCA5HlZEbRglevGZ95e/0+gceGky4+qOKLGIG8haVxF6SR3V7/GwBg4LMLg79h4HMY0hUWoDegG6Pmcfe9DmuboM8Yg6+ShLpGGEu5n+/8OJO5UdVIYzRU8bTxzqX3ZmmqluJdBCyz9uUkEp3CrQFRkVH3ZkT39OxOQCfnFozljHXVqdAxYp8NF3BsDw5gAqN5XcxQRtsejIgfKl9nMq3Porh1gSM5XPuPlSIwwdngZgDrbgTi9WAaYv/shTjdKpzI6e/3V21eN5hG8lsl45j7vcHSuQOK5wJvH9SZTrftVTxlErhP7NlbX6vXGD5ZTr7DLjMzwsKJkF932E+lsXd7aCSENBdW/OOeJRF/2WnkF3/3NaPiwp+hMBiOC/Qu9nfcHBZMVbwdPbJt92Zu/WrIo6EtDItFGOKcUojn+HZrwAVEua8Iga3TWGbv6qzzW7qRYkiOURdlw4VX5RzKZXbbWxrp6pz4kulK6aUvJle4MWWdPI8S541CWPeINipfwltUJ5pH0FVjAde5rgQhP5kalko3SeFaAatjK8CiHrFWnlcAN9c3eHt7LU5LC/qhAWNi9BIJ6xAaVL5ZMnkcDofNOjH6pC8djPaUppApSYc4VnV9SnNDMjqWu46GBe8vA1BBC6MCNv9yh+ebZbPc+2eifq0mbCSf8hTtZkDvrZshj0YeegGDCizrt006yE3obJ5uNI2kDaaEXVpzgTSju9iPvruyIs6I426PUjB52WsRd4kMJA0SeLkau8Nm6mm6Lb2mRW1RYFMSG1FY1b6Cu6jsLMoLCvMTachWnZiWkgCC4QLrsMBrN8wHTvYP5lE9XLAXx9fifM0MxVHdT5VOWDOlFI3ooi2yvISyYDqfsxRFg2qmxoO60V3AFPmpUPKdPaZHkNh3i8AGjnPNaAGYMHtsZkBnWsGFewg0ivtcadwt+w7Q2BvkH2VOoHdwUKHrgZ0VqEJbR28K7cVxUtxNZqUfvvMJEGi3KDDMVixRgHanQ81SAs/VI5NdyShMM+7Kob0h3RwoEjeOZqk07d0KbZa2v03fpx6hEpHgu1McxUbEIJOR+LttAPIW9UK9pTgWTOLvck3zyFUaOqvBKZT9PBPOa+nAOi07x/ToaXMcgOFf9fMxNCLy6IA0xmrP+h9cST5B2NCYypkkniObLmWcvK91QRPLPDR1Bv/VxTIGRGagYlVOHmCPXWkomEFTg8stAaVhnKnGI/Wzx73LAYNGAoTS2d7E2PTtqajjoUFgYFrdd4cn/NzOwXrKZSuw6DjE/3VDU+voroAy5bYEz0jnnNYtU9i+RcR94WsaQSICNKs7P9YjluWAZVlwfHuzMbhHn9VwPUSGhymATEYPK5oykbnD1MGnNPI7jCdouKp0TmLuVLhNNCsXoNUhpNCb9Qi0a+cNkl9kZPWVyx55PhGyCPkNS8+f6S/NwDs2a8mEv2EFpOAZjMoJ53bSKB8BiDIMbEHPH+6hXyesDvpdoRqK+Tgw8QzRhgUPuPH07pXfu7WiUKDy+7r0j9296jg3B5FGzRcR3AQ8zAkZgJfKsthuiAScrx00irAxJYuqAPDktOHeDHVPWZve8y0AAvT7ZtF96jBXYD6VjAxOc/EV7mDzglZSxduJffYBCJrcYOLN1l0TBpV/Etyg3XlpG3H8Ivmrghkf3ODUkwAFHphbpw3AcGdnpjQB0JpvM0VK8AZ31t4lTurX1xhj4Pj+DhHBu5/Dq+srPwueDUdNphgjI6PFaTX5oHTeA9Yx4x51XAdo6EckYIjgyTZNUGTc4owVmSK00Elj1Cy7SeF3I+sNu7dyQg0wvCJ0pCgOleQ/YPuvqXhpAUAOzbJLqEBfB5pOrGpnbFY9gyA/72gpaaTBpeDmwseNySw1samTZ+OfMeubfVDpNrdX+sEVLkK3T6F+263DZSyDfA8ZEVBrRp2KYaLp9BEzaf7wFLp5nhBMOemY8YWFoRHEoRcY3yc6TRcjSWebNEhnEITtyYcVGBA8bvYuU7j4G5iVwvfrxv5VhqEx1vxhi2PT3YjrKvPGz3eP4IzeFzvjaplzTB8jHtnuvfreOq5A6wIdFnE/VpMvW0tYP/31/0Za9PV3cQOTwWVMxXMzPaPic8hEz4241haS83jyMxP6NGeqeO0OzFZmtL2H06eNp4mdm6U1z64GvP/lHczMKA6pBoG2r+bo2HzMEMwvAtV74xvlqfAtyYcYcjX43ueBMzoswKPUM5QLWPc0M0okT1wYBe5FdgwFM1k8DMQcIPBSYnQsKrxi0Wdyv1SHEfFzbLwLz3ruu+vVeUWdeG2CzntVw9monmcag0XSuZilyADkOruR8RbNs20gHIqbZG47cfm7+WpFmUP3PjUdhUfKTzW5FR5ZD7HMShDoXCEqaO3GoLa+mNFeAOhd8BjEw03v0PDk2hNseLw7MSO5ljmRR1co7iH4WgSXqler6FB8Yqnv5DrDy2xRd5BU/N5vDZ08xYXgKvd7LTbWz7Wyt4GkFV9F8DHoqc+LvIpPguteJoUHMPOYX+UZVAX0A46//xFZhAceIZ8NVleffkNHw//58hkQwZ+nlxnz/pvqD02Nezb5w6S5Gwd46jyAzb88/xGJLi2C2qrOKcRgZmgLPZ/Lmjowhzl0Dy+BUMsfnOq8tzRxQ3Hrc2faHjIbB8DN5zPAKq8PBvIn2t6Gsm/fizxPx+8yi+8886v9722/DOj/JK2Sjx+5u3rdNjFl4/RoE6ZVpCJxQiNNDmBec+sYuLm6wtv7EauIRTnNib4s0GHHfwLQ1ZjWOdYQQvYDl931qnfczuvnZlnbV/bpjzPKnMbzr849eeBXRGkbnf4cZkSbw+fNSCqe5TwmqsF5M914BuWeBhtH7evcTC/h+Bo99jN1WkIwPEfDTt7l4rhSaTUjrR+ZJhJNKnfFGS5VdeZO439Dp2no2sQc5ilpgXotJFElkyIwg8KwgT4hFcmVGaiGikvz2F44d2+u9M80MhrPUNy7Ku32G1242Io71e/XgDrTXiSqEMZe2EesfKv9GAt2pqV2Jtb8/H1lcJfGUPfdfnOf+XzGHeQbfV9gsL6z1/nK7S2XHji9iwLJ9lfZ3nohNePf1L7TTyjadjfXfSN1eP5DRjX65RKd3kSQEZJblq8yfgKYow0FJFf8VXxpn2ckdN/P7frqBi8/ExLxAAAgAElEQVTvrz60FVMPwKrWcW/oxCiOd6aObSTEGXjweIecH+fdDTLqxrj4zaLkG3oItvXRhgPkGhhvx41Ix73AzGeEFsEWIywFj7c0gB7yTOfr0cSusGm9GFJ8XfgibWY8FGmYzepUNklBr7kiaOndU+xvx7ChvPUsKaqdK+Y6hz8v+XTU6eVzqpv3WApOGkEBGdNSdCsgwnT8qZDR0kdGWxihiPrm/nYz9rVQdE0V6GiYfaJNgfS2FR4FlrpV4cZ9FBoUi+nGkeIYAMcpKh5qNVxhBUDU0rGLhCkOCgwxA6aldMxzNqens4ZFl4siU+e4cXdCLXJPEtxTHXaiwEpBjWvc0foxDeRuTOudG9n3jFkY0gAX/1XoKIJnbxlBILkZiJstgldM6dosbSW6BhwVwFwToIzq0Ga1yms45wJgcExTMRbPOjGDAzGlwM6QzmjyTZpF8gnO61HxKGr15I0dMceY4GNQ/hQlxbHPmwxsPRzEIdg1dTzo7x6+f2ZNya2kT+Xc+MN1TEl+3Yuf6fAG670Od+YyY7UZQtzR0eEx6BgVUejpLEWjuuEpdWO8xji2o0LiesHGoTFLFxi+DsVp0ArZ9MXzoWWOBi87A7GUkgY6plP33EjRm4ClLhQYlHfo8EM86E5YjXgARfGpu3XUUCBHVC1I68VLpczACzSAKSbMbkSHNX9KJNcdhof7rn5g8BHi4w44b5VgiHHb3g/DuSsazSjf0QU4qqIvB3NaWNN5ycZi/S3SoHRpK+s1cQR0iagsEXO25Gpyb/hxhR6P0EUgTjdjrLFZ/PxFWtx8l9+ReKjg29pq1DXXS3d3nP/8c+0I/Hgd9As8mT5WDt1Gayf3JTCNZdSYAG4w8QIA6IXT38L6FvB7sPk16XPFI6pW7xSaRnNeT+tf4j/yLebPpngXwZVaBP61Pz8KjZ/uEGVosmG/IuvTQDp/aPnvk6PSajiwv4Hnwk8bjaejhOjrpnxV8JlxKq/jc+VLGK1I/iqmv6s9zybndpXTWLM7uhN7KFA5VuIQ8s45vrlOCNqmHEQsiRv8VNWyqewcPjA160j5L4YPaPTewiOVznUegWCRRijEb0aLtvnJNgpodqEFV9tN+TtylU/1Ic7XADtxiLhe0Q49aPh4O4Llalan7XP3lmykkzn+sOfYguXIFFHTmDDLaRbHJ5+rPVbx1T+qFYFCndvW4kAa6Z/dwDon5ljNwQtJr8Nw7pmFzJekbd/j9zlV96w0XD9z1JTWcNs61m7nwpy9DJCtBizQ4LKRBSh3IWmnvytGUc7v99oVgK53uP54BaiVmiQzIp6NawJoSsc7i6ZEa15eRgFtOIhgeKkTdSdyRcMcE+tf36D9q9O2iWc1GaCJWnTmVGN/B/DobDBkt1Ml58MI4c3vCncMId7IJWecM5EXDVvdeX5RxfGvK7Q9xovYzwrBs/MiTDXOz6pP0KlYe8NQy6SlkkEol1o4rm1whAa+jg13qfGxckt2pXgw5rXcZriMwRKMt4gMBzwegadp7Mt/9wEe8PHTQegZdMZNKvZNHSP79LMS0f9I/s8c15s7s7t8I5m9jTxPyKVqDg5qjKf1F8jaiKU4Xu9ycEeKYefIPD3Q5Bi4bwZMNEsKxnQyKj2oN+nxLDz+Zqk0z5ZsYYnNfeWXksUGMN13B/BZyu8O8Hs4/OBOCruMoGWpN9fPjeObbc9Elkbd/JkJnfsa7YSbqLQEj5vgrKYfADw672B74s8fBPjy4PvtsfDDP98q53hJi1pxLMcQZ8XrtGeK9ha6KZ6vOFPOfJpjtnr69pQ3t1neEDjsu3O4xFifmwu26/+zz1769j/VTjnMX+1fvf0yoP8zNBKtPZLH9kDygE64kG4SgXk4T/MQmstA1IyGYqhgUatb8fT6hofba1wfFrw+vWAIMHrD3dU13sew6G0BpDd07Vi6M+460KbVKaw5/epYU1m5m5Oj8kB+zACmRSD6BkyC5XfC/GG6cVktLfpjsxrov1EZjy0iY8qWTwp8Fqs/7bwHDsjEwxSnFmxFq4yf2863Rq+T8ey76yjXyYSRqRlSPEJBWKTX30fnfL6InmUxvorgQc0rfDrh+jhPI9G5pz6S2RLFk9fg2VRvLkpqFAbUlrWKxrGiEUVkpRYF6zQmuHmAG9S9NKEuUwuem+JmWPQ2PdhuVfBSvd41PdNbM/MaqKDTLYS3qjek93wRTk/2Zt101QBTrj1BcS8NbSq+NvOgFK7j7rwqBLfG3eKlCDn2ejKae0UB97Wg4xaCF0yYgstgYszLG2t0l31S+zv69YOzaGMc0T3CKT1IkznOvdEQhZEvNReGN/x54Y8tamRYTSelQJPnUAusOYrX4zGMaHVNvsV4RLSGD8SMXwUWZb8TNqpk2C/NTUKQcF7RnYMbNmBTm031TBVxOxuNT5wwEIbUEjO3YZrD0Bbfx9n5y+7DGANTsrb9YTmgu9CWEeUuqDF60M+y6RVKKrGo4aqbo1DxdHMjaJxdGhQ348q9wYITaYSz296PR6jXSKdXdFsZ0RcScuARi/xPhn+sq62TKxX7koZ1hUUbWv3fiHED1DJ5NLWUh1bD2owM78+MUB4lpT2gWKFveV4FValbdJ1yuqfC03e3kk3EU0Y3iHSPLrDUg0vPiHToxAomKU3wqgDarFxA14YpRvftbJuaW5qaMTUMQn7eVDdjosGYI6wqcNImKr6YJi5GU/GGmrF0zAkZA+rRVeIDHjJcwcCz4emHnVaQ6HGspMWm9SJN5DyqtKrABKaYQmgIPGVeWS8XBlXU6w5rRNJKY8R1UaQg5wXOXz3lH5TWC9ufoSH2iLdp6bJFabg15RSNFZgNMmyvzaYRIcqIBWk8r/5uT7FvvbuiFOLOjUe0d6e608yMaN2G1+xsttY8UqHlHi0MxkaJzkhkV4YykiMX2/ezGAy7EfNw7poTkMX71jR8RwR6020kuoilk26IqBvyXU00U9mrwVVBeKund04jugnuzflSj+KfzSLgPcW1ZnhDaUKCtING2WpB57bnpd7IVMeeYGGT6s+HajTQaadlnsj9pUDBz1wPGr1TcT49+nwwEl3coKkOAx9fZBeh4Ve58P5GNxhEtbp4aZ26E7zW7AwVHE5liilS0gif8x5eX9U550KTc44SZ4v8JRwnMOJGmkDOiKNqyN+qQUxEpLvC9uWhpGqu5zlWmErNZqILDW8qrnAXKRGrDSJm7AqFJ2FW5rU05qXa8iVEU1KEkDSS27/L4QAoM1S0kz0WjlHS3IBu0U0iDb0Z3b++uoECeHx8xLJ0rKvRAkaZQ83A/vryAlkWiK5BzQQCfT9Cr68gsxiwOEeR5P2PR8MPwza7NnckUsOvx3W132jwi7WB4yBx48EbYjOEwLPZhmZWLedwApEmVUF+FTifU55dVsDv3gc147njgCsA77vjHTTxhP7kWKUYu1GM5kl5jfdQfY5pNtyC6ny7dgurniqQhwbgAfOrzWt6VVrKnVcA3vcMh+b53s7frlxLcvbq90ctdTUD/NXJcz5fpZOKgHnJxBhAp2/kH+tQ6KAvsY7D8a2AWaX8vDgVUbFoOwG8zqzjDLIIzH4jb4DF0+ceVY/shuL95YibDwvOqLohEEsXDuKIrIQ+fS5ubUNEgUM2RniBoNrkU14XXN9c4/j+bobOYeOdHj0c6X4h8a45NTMC+9yZAYq4RgjPzd5FoU2Eva9ajIe6mjpW4nyn0TPfM3U6vrD9CtXyDsevYSSh1G98jqUgbgEPO5/wGsT2/OpOh3hbnS5ZgMfR6dVQRRXVN/Qw6JY5QW6OcpG3jBcxynbwnfVeFPsZ5c/3JD5XRcK8wjfgp/nfDY+4uWm7RpvmJ+rSz+We+mk6j4GpGCwDoM35Ag2eIFtxHAMjck2mEJ6xYAbLM6RtdTYCrN0MLH568DQFa3lUWt8Y2dLXbi9L+v2xXvljGEh3784R2V66+nBAb4v3nYPQqTjOI0SMj+y9WSbG3tEBl1WnR5GboXpVd/QVh/KcOOILmja8NaM/TS3jFDNCabOgIunizgxb6EF8fkKc4fhjNtCtKlea+9jWpGtGgw5pWLzsiuFLG7gZz7/E2vE8PzkuZXYCt9gF7xAW01gf49GOJpjs1icHKIKsla4a2a3MWdTpMX8Pfuh0zaHYzP1eEWV/+PZG3qngXg5I0OKcR7kugZc8y6x1Vy6pjcI5fnHHnSkFh4AcKMenGxwBYSr44pC9M6R3BW6k4egE7d15pZup6AqszuMxiMAcAkwfkz7K4plQBOoZwIQZR5x7WQ6Lwfvl1c60z6HhGgrF0BcnZa/YYObQS9jLhg68iEVQk+8WWNZL+P79CsWdwjNoKl6Iw+tS7oyiAiB0oNShqWdNVWY10g26EVh5VId4+C0H/AM+TvPLptqzPt9spd/9vnyE4oMmnPQHeqYMg+w2+BthTXgxLmmJDDcPaPiK3hqW3jH+6wMGvmBpH9BgbEID8Ee8vpynOuaYR44gYc8ZWCeNMhvxQMAWsTeY2YKlrVqpfV61V0TNdlY1MqLptD86atu2LAMmM7eB1hYPpAy/XZxLJLTK1hs9zQZOudfO75qf2kFFz/tjLXhGORlEvFnxs6P41f63tF8G9H+yVg8bP1d8QSZEXBAQnRhzANOiJ+Y6zDNzSUFjONPd5sC6Try8v2MITAkMQ04DVotywBhOXRoWWaAQTLWaiusYm7H9LXO72C5imC360W9cVWRd6X37wwH5VSzCu8Pqz5VsowHrPbwvDbeOgf3W+2s6wj1Kl9C0bVsylN9GugpLS/NJM6rCHTxPulUoBjL1/v2c+NpINAvhowReGeCi8AqnQrHfTQA3QXydgmsoXuCGCwDS1dKPwYQalIjECuWXTQr3M6t3UUj9XnOhrgLkB/oiMXyG4lYE92oR5neaQnncC55JE5lu1WsJ/WRruAfwFdcA3vDts3LWAzG1BBhjRgShEfc6Wiq2f9wDfz9nNvPlFlOgNjJ46dF4qa+fXc8qaG2vnz1C+fvFUZw+JycfUGDsAmtoxq01aRg7gTQUAJeH9d9qVHQSf4R3Nn8PAwI/515Jj+0WCGzrLJAUh0oZBTxlJ00wyHvCeKnAbllz/pkKuMH17aZeRdOD+8UMG+MczoeLRxdoCmUxq/IxBOE0FG2ZdwoRiU/36xL0VSoUt3PIyA1/bSisrFm0YDG8CkomDq815VHnvXWPMHDhulk9QivFobmWDWja/KybBqIBpkCAoHMArbvDjCm21fejuIEKG1yVoqMq53V6Fk+ubNDz9iwyYpOwFze2wp21mMo5ojpd8GJq0ZriOfwpYhAtFoc4S9WV4q2kuCwyKBXgzKwnnkJZFB7fyrPs4yrKSBFP9dgEgma1k0XT0YQGLwEwLZW4qLghNbXHvcMMCoJwSAihd26F3xNQqw18igBjhUQ0OkyBenXAomoGQIdDa22TttrSR+capyEQ3o/XToQp1zOqNtc4YWJGRVOqIhTlrayHwiLIjXecYLYHGtEjrR+VVo01UB1kraF5Cnt4ZIcZSGIQye96KvswnItatP+wc9maYESkhePCDYrW8k/Z6b58yZ3o6f0iEcWTxgkuGv8h7nT627gHgKS/tjjqStmpNE6P4gw7oWrOsMPP3JwA65lH5HCpDcuxKNyY7l5hjCLYzLjSTvEzqZbN6hx1Vl8HGh62e4T8REorCmSaYPuSeyXwRZ77TCns59U1/6rqdT8L9ZGGQ+/oSw+jkALhZMn71NPfw3ulc19Eq19gHpblAKyrKY1sRUudzR10diTJ8Dqv2zxrzDKVsox23ZpCEOd5EdvjY5hhdUHDAnMok94BEdzd3GCq4r29mxPrHB7hOS0N8HSHaNDpNd9DB6uAl+Q8Bybm2xsmShYY5+k4Rzhfyf0YxvN6vJxu1X1xse2OG1+63Y1/O1e1jT5POl27N/xVh6Qb3uFS28Zj270vDohrABNpTBevXSpuFDY8qn5un2PvvsOM3GchF8zIflQa92/AeXKbGdQFGu/gPCYs7a8Znu6geAklt+AW0KQVdu5fNu/heWNt92sALxDcJNOx2Yvq4zgZ825eyXO48Vyy/MY6JpZ+bhW0GM/r+3zspMNO/4j7Thxylfdnv9tWs+e0qDfK26UZ7jHWW06Vz1UmKkDIW7Tg9jKXb8pRiRdJC6ZOw8ORUUo3ZFDLk+FoAONNOXN+OIERPcrUeTxf5ajxflDoq0WyTdWgXYy4PWq+O85D8PaGy5QOjTH25OF092zMRzKrSRjO9XQFv4mdfgB9XWqXHlM1fo64GNAo3TOnwhy5+GLTIo1hkX/2b+5GizxXKzfkdK51c1yFSCQEPIfFuBcVpIkmqwAetTubZwdyUIgG70h6UGUMvTDj7xomyrG9wz2uP1zFGe1eWpI8wgScd5qeSUU3DuKtCZZ+wJgDHR3TeWg6HCqA9XGFYVzjWaeSHx5WS53ZI8T0qhReW2uZnlrs3YY8GogBVIatRdnDhL4ZsoAFC5ZufHrrZthi6TVBw/t/vbvx3B7/2mzuY8yAd0SQ+to19K3xF56qeUyMtmK8K8IjZQ96cUeaoNyUF1JuUC04Ettuzq3unZokINi6/bD/in/E1zHuEMS8TKYjjm7+uWGKYBEBfXkfG894/jEjwkRmLcpB27qR7wq8LXIyH4HgFRqZ43rvUAU6XO7RiSnppA0/S03MkE4cn7q0xg0BUUWTK0y8h6zD85I65CojJ1ckkABbNba+8jphSV6aciEEDzAW4s4FsSdsf69nOca9gY2iGtHrHOE4BbAsETH4vxGP/j3ao/wcB3l/hvHjPu3tN8z5GUDaENonwfiDTqlG55dPDesf1IKlDuxnWsoz+W9Emtd/Ba6DyrE2IFO2SzGed6MVTN+etN0+1dIvY2r80YmrOhf8CEwv8Sqby0XG+5Fnq9wdd/ztIsLfpT1oBm0CSPnpV/uXbL8M6P8E7dzhl80Pp79XYVNhDOUYA8feTcj1+jxMb/Z6fMc6J8Y6oKsr6pqgz4nX4xtkDGO05oCXGDVk2ywKWGSYcsUZkhrdDCQin4HMNBmuQjc1FOZkKosS5yJsTn/72lhv3H6bTvhXnPNFz/ZhJlOy4DdMGBHkM/TcJ1E8Z2Zs5TpTrdN4XomKojJAFNgpeiSzQd2CgqBJBemDnqZzr5G2q/fzoBaN/0GBR+/nYao9K4LHknrO+P4iFfvHh6n4WmC9IZBCRsk9w3RCh+JBGibMI7NhYlUT3qa6USgEkdwrT6K4heBJJu5nriFlvEowjVhTaEjmLYXiEvVSGq8TnpsztiHadZLYELwP2jC8XtodrGb7HRdJMxIdautMw98dGl4kjUZ1vAIyp9ZeVfGgNPo8APqMOwCrR2Re6QY6ePedt7C2H4Ubf1Ol1+KMExTbccwNa3wGer5fiVzOpSv37wOZ2p/1PuFMJhVx9QGmrN0rg/btRNBxoXAPU/Lt1rfGHnUW9kRw4zimSW3JcLIP9u2Gp+ERT6qGGQ4Hi91ZDgugwNv6HvcXsEQmhMai7ntGiuu2ff3FRqNY3fdDLS24tIZ1PTqehqcSK6/S8kHM0Nqlp1e0aNQPtMhziZrsVExALKWcKXkosVGpwTSgDctuPyknSRoQeFKh6xH96hqOoqL+LETQ0SOqEgAOV1cAFMf3IxSKw+EAgWA9rkk7NMXyTL1mtaKXw5X9dnzfCNLWvRm//aONRzVTi0oVWO2/4p8Zq9G59x2ft+bzad2EfKbPkqx/x2OjCihTn7eJhg7mnAvjvcuq9CQ2QQju5U7kKpnSrcD/RBngypXqGFPnt8FVfv4TZhr8hkXB8nzM3CuKiBxwtF0hHutNZWaXAmtCVhR0xqnne05gWTxKUgQqEzRzERZWFMDSoS+tl/0/I0WgRYJIKGWjjqOn03MzpCkLCVMa2wUZ4eBzY3RGpPID4HmfI02aRSU4xmnIeo3cdGVP6lTMrmYwI+Q9NfcY5rq0jGFOGb1jWRYsh6WsXfcsAGXfKp2egDlGKEwhGhl+eFAjdbqSZ2gWLd5g6dyhDjPDG8zaTiO6mS4mMCxbQBNPgN/cSOtG8On0P4wKmpFy6dygWxwWiklkXVfweuLwUKZvFLxAqDPyP0E0LlBCEDkwd49GZJzmZhZGAAHm6cJsEeKGk934oBiDBgDDretYLf3mXH3owwzncLhMj9zTjB6eWoz6mvtyglGeApE1cEG+PTdd5Skrf6Ix0TSWJnxRnmGBg9yrSriJG/Aj04HXLFaj0FO5xur4U8ISZ2cm4b/0hmVZDL9PRsIYbOqg0kHQ6rePASvv0FraHQuuJ47n3jwcDujLgre3t6KURtRh5ataEyvb0DKiozCTToNMBmgCN044Dz09B1ThbYUG9N4NVw1FF2BpC64OB4t+F2Cdo74Fx9W+r1DoNLp4dXUd6bnrvXxb5QHDIcTvblfXhgePAxPi6VU9tW1fsK5rGPelCWQ4z8OIsc0e0eCH+F8uV0SkFTqk3I+qUY8RnmHmcsvyH7G/a31lWNryg39/59vi99P2PZ7sUtue8S1tPTw0vH9VNHezXb/kc28ArhzDMEL89cw4YqwnP9js35C11Tf3I/laALgqaVjJwxkXx7E/+c7hnnlCSsrbl79XXApLTA8B3iqO2Tzt50Jks25VpgKsLEx1coffQ/nn+gM5zglow1yHpypVoDX0fkYbIECtdWt0m7wu+QGNdwGO3stv5I9NxjJ0xQxC7Jc0XyawiplamH1vYqJpcwN/kVRkv4e3tC9oToBpT9sS1qHk1kJxfG/yf1xHd1+LPgbXM/gy+y9LCPFnZiRp0oLvmT6JleOcivl6NCcv4nnn7YeX5hkoYy10shrT69xDhpzufAaAzmSmb2hl/Bowyd1eT2bBV2ehiTO/nmUWAqonv50YAcwgIfxN8zpAejadBy7OcnQ8BUHrWXucn2rkq8d051HBGFJ4E4PCmPAsAKZfacwSBWyiTtXfEY5o6oUNPB0O1+hk7ZwvPGtmyQ1+gsNuILh6OBSnYDtr61iTllQAtw4MgfaUlajz4L+zTQxTeuH984ohj2gieHHHgwlxp76C7ZgBQ/f7QOOUx/luzXCUAGgDOpsbqhXTlZ+MWBUouv6G5d968GZmxDL5vrcWeJBgeiL/E2XCCAPKYGLp+CNFs0mXvfs0OqCwjGfi8vpDobfkT57quijAkjuqCHvv3PwOIkZ89LIh2/wY6TzY8MGvPQYcTo5PJQDqfEXosR1XNkS2rcuEkV/yHeSx6CgCN5Y3X799xPkd143r744jzWWhO3iGoqWjDQBT0MYwx+fCSxofI8G/RlYnd2SwKV/hcNuhuuD16WvZYym3Aa923fki6tlF3QnPadN0XvjO592bR8JrMd6LV9KE4In6Teel3dc59CJJjuvzcQPiLtLMIguJAPeQLONVeqw0brP8pVec2yPfauVmitbkfbf7IOUdto8V3rCQDicxEKQjSMcHKBTtA6CPHyB4QoPi6s9/xpwDh08LVP6E4x+WQa59tH4Onxasf/2Id/kC9fcRZz7WAV6aWtC900AiNjqcABr7AkJdU9E9ldrn5gtbnCKKjlUneejyd7JqiKxlXIT9PeUUbp/dfSjYrfZ+ATS66d+eKzihGhz+B1stNbmx1ch2J/9q/5rtlwH9X6Ax/e2cA+scaMNTdUjyXaZQmpCpOIjVQG/a0MeKIyy6/LiuOM6RtUV7pvrooHcrwrMteKgL4yLvsJGJf4BYfLNdwEbs8rNYuvaPuvMEKo9PH9vQzyfdfm94uruPtV/2hnb+zvtpSD/pn0wHdnDSjAaKGu9n2qMoPqhsxv/Bmd5H2jM0WTIT/ChKbhPZPJaRkaSJbPlatrtpjP1RZzDeDxN4bxNdG1qbUbeRTOO2j1Moc97lnxh/Cr+yf+Kkpw35/QbDsW+yIXoG+2eoKYNg9dAZiR5GdGz3BJPw3qjglUzlbmz70Uw8YXn4DfgqENwDABpe3CO47qXTvnySwQRt7hD/DwUdf+hCL5fbd5k7pMFVssZhOKrv7tXdvH60fcuL8QeX+Hz7zrP1HMcjP8ughSBG4WP7cN1D5x/fZqag8FQGVOBDAZuK/y0zZ97WUmpRUQhKQ4FFPzCyJsdOr/pgk0kPyjarzHSdG4WROuw5abQEpKtHXwDaLBUmT0zIZbvnd7IcYrU4pt3CkdWv8UocLdMJs1+re40dlsw++BcevhwP6Hxmwnb3KBsqSRoQEecKRmNPLyNgKahFTalyf38fQQ6qgueXJ3THp3TO2JQUw1bpw70b46VBT3IuWvBYNQpfbK54s6zljinL3qEiwqLVNOmHb5gpHBlciSpmb2y5MpbSnGvBwUrSI392HepR4oh7CSuryU2B0iN0VCInwpy5V6IO3wRUZiob57CUmGgb727DdxZB3KRFCQtIrelnc1CPcpDW0Pr2PJ5v4tFJ9m7Vo0UiT+PTlmFK52Ws6H3BsixQnUF/xBXyTEWbsFcwLb02T9IfxrstBqJBmitsURHhWendmSF5qqbxXBWztfgX07NL0GCuiZNOqLcWD/dZanYTXzKleVGwIxS2Ggr5jdJ9zu07JOFRDRPnBfV6E+9Ig8b09a9QYsS5QtHE95+fN6b7B8zozTS9A+6E4NeGR6LX2upQjwrw9Lecf5D2UH4j4GMgs+ibgbxWQBE8IVFf4LpC3ogXbB3cmVERsKHiIuzcnGSAT5GRXXl2GRlZncj4V/EJJs8ScFiWC3WOy/qVaGjivO7RSYzWO8eBBF0FYn9eXx2wrrV+sSRQYA4Q4tFj6Sy36dbTtRP/m8IWY5hS3/dzpe2McOoQtKlYVLD0jkWs9IfqxKTjC4DrfkCTZinVVSEdEO04DuYqy6ixgNM7ILTSVgJKQ7e6xNClWLkFmbmCzkLvEBwArXE1grKTNmv0vZZHkhHGsSM27RzvGDRAt+kfz7UruBH9G0wo+VjdXbuEvWtXhYaFKX4AACAASURBVN0+6fPw8AHHx8f4/lZ+p/E7npMt3xsZnAq/V51faETXcr3ynlUeevO3XMP4nCO4WwQ3Md79jFOSfC/XkwWx+1kCJpWpRChJZ5jJ7NL65htfMJ/voBAsD+56eIZHEfan7hir3McovMS+9/IeVUiT4EFjtGF8qHhQwynEDF8dY672hGjwWCpiZXxaQ6czknesnr0tE8s7bykCCfpQ5oDk5+xzntUcrP9SHthEXpM28BF+R2ydgL8CYUBi1qVkvrBZz6kTZ/kaGs39a5sKTHO0V6dJzErE7+wvaDhpPRSNvKr/Fkb64AUIE8LanRu10MYCu9q+zZXp9tM3cMb3L9rb5xzOQpYz0Cz9d/Ph08CRa6jOlyZ/bMH/fu4coAKBDPFSCWUv+l5jyZg5h8nvmFZqaK+vUJdNJvljy44kmmX2MoLe7jNeZFsjd7M39ggVNv1b3OHq/iq40TkHoJblajwmH1edFyYU/SPQ54o2Bb03zDmx9MX2kLDmr2X/ak0wIHhyw1LsYRWcs8luWsUdPAOtoYc+Q7C6BdKMpMazmnONn2NlunCYTlU8+rxbWSJzIp9Q+ULuLvitkH9ZDopnRjKjHJuVWjF5Q6c5tbYLkxvANnCmyPfb46WBP7kGDzy/8gDE7qrc1ddvQXTbyrvo/JGRtS2yErknOUQEh0+/4fjHZzySTu73lv+x1IixFC1kdmYr6yxfJILbchxVFa/N0rdTbmkhyzsmocwZzoOIe6VxHyRETAngGQomoDji7e0d19e3Lpu4czepqKhnLkPs0ciKFnrIXJN943gq33CiNxHBnSqeLvzO/k8j0RNnb35T3VA2ygYVDWy2I9dJnQaexdA/2c6zFhfbhucoNLfKNmY8F8xHheIJDfdxn+Ec9Wx3E+1jR+8N93/+M+ZU9D816B85tH1g3Henc4GnpQODbAaMDbBFyFvk3g/n6sJJcY4mf5NGeJlgUPfHV2TQyUYsQj1658e8v5qYvT5x+myhAJtrGp9+Eqh/x/b1G7LEr/av2X4Z0H+yXURiP2PBIV9UeDHr/Mz78vbN48TqWhD7mBN9DEyPADaGxiNVvJbeUMFoDQdX6r6tA8exQo+rKWbFhI++dHQPRafXkmWFNgZ/nGDKwq2cWi1CaTkzRD0UfxV+Ad8L4KyGZIEZix/Foq4hZjhXmFLgk2qpNbIFcff7qBvap1LcG8Qrav4swG+a12rqv/q6+nmnxiXpARnhjcQu23v36sKqOKmR7x+m+bEvroz7k2ZE/dNmLhsOEefap2l1a96gwUA8wWvIT8XXBsAj3JkS7jMEH+fEizZos+j0p4NnMODcmqUEe8LEvUewuR/tXh0So91Cf0tCT0f/NzJf+9cAePYIvmcf261IRKLfFrjXoYmP4EXMiP6CbTPRkuYYF4AFGE+rna2HDn2abvDRkr3BIlOWcnaibpAgaoOKRzTUSKiIcHLFvgCBH85YIM8AxtsGEUm5wwZjqc48hkWo6MrzHgqun2A0wkgSHXhUkiarZUZA2TCQEc8ayva812DiGorO1MTGRhKOx/Xo102FypSM7+9v5V85xVswIaIx8uWcEkE2p3/Xtvt8A4vSV/PU4GxLN1LOqDB7jaYRglTD9wUVH+KCJyN1hntGs78Tj13KgI6k0sBj+4kJnDlSOistvXla4u1K6Dqhi0XxqHpkIveJxVCitYbX1xdTMDSrb7cej9HPhEZkYJ6DzdZD+HT3BVB1Y7WnUAawCEckZXRlRWT7vXpS91ZSYTXDv9OVI0vL+lNZFxNRL9KM5TSeGxxFvdZbvMsFnSa4vbmGSMc4vrkywM4EI3go4HC0W77EzrtKGloz8ih35FSNKDTue4EJhktrOKpaXeZOw6obVgRo0jNteoOdS+UbvC/1cyUTg+uldm9zY7iKnekqkTEYURRW156ZSQSuUMnbRYqhbIMb1B0+0gBhjg9GAEap+5k71R0dvAQJnQ7mnBZ51Qz6rbUURpXf3YAGr1Kc+TR96NXYoeW9Cp0CEeMcdAV0DqytRwT6mBP9MKI+Y6Rmm+5cUX1QHIbiZx+z4uMzQmt5Jn513NE8e4U68NqcHmFA5T9CYcMMSORp6LGdChmgpvmfOiOduWWgYHSerTcN64yA2hvcsxa4lTNQrZM5w0WQb9UKA97EazPmbqUsvIWx0fFB427Z4Wfy+xyX71lpEpk/Buuez1mivHN8FoE+MSx0JObFCP5orexfsUgzRniLAKNGditw6H7SW098yRruklyZcWlGe+cYWaOXdN4/CsSdPhiR7vepmqOLulMS7fBOEIQH3M+mKbsRkebNQszC0Mz5UImYpNF2C+UMxYy1oAHdbjM6t4mY2tHqpsriIlEP1GhHNahNiCvmA1uX5VC/P9IgV2caI2iRaaEqaHvrWFrDwfKRYHE6KGqi3M3VNVQV78e3KL+lrZtg4/iYjhlNrqB49x1l89Irh5VSWWZbfDgeMrgbmBojtBzvMYWwjlFC0uLIFIhyL53yMjyHwa0UPlQdPihyQ6Vp9Xka/ZS0sA7E+zzC6p+/w4zEQEnn7kNrAF4A3DinkOKYbhyn6rvPNfFXH6DBB9XZvz5ayPn7mWf5xum/y24vkVeTAqtKx3IAgjcOJJ6VgMl+n9OQLkp6r57inUCw368oxANmPC+84S1v8wVr/vs1+R3/oxP5EME7zFAfy+ZdGv5kV5SBXiG4BZMc6FTnFVp5LyB09O/psHIKYc2MQzSy+b2GIwBmTuNfc+ZO4HgM8MwWq71VYJnXvCZujsfm1Nvi9UNnOg1NxeKGIBooCc9qCCaLo6rBrSXnQBy6O2PluypKqQs/8/wf0TMNMiT/BWwNwJVnfHpf14hSPPceXj9o5WQQeOYV1IV4VLNoZLGayDl3VRwLX8AXsOTgIciKO50hs7io7xHyVDGnmKwm3grLTvIE58F4xuGv3kc+DuTjzt+V/To9n8zb4g63DkR1vDkh4fRowCTCcudIIPCcxuccEWVjhBxoGHfqAA3jUMUQQVOXImLvFX6FZ6EBUIlI12tVj42duJrAsw6/N+dptENzvPWD/3sLwfX9Fa4OV6ABFxC8f16xyiMTcpXn1eWle5vHGJitYzQrT7RizWwxqqAjL1rDkzpcHKYbDEE6LxJyhX2WE8c9y3ZlWTQsC4VldvOLhrcGIDqhntmqTVtrqkiX3tCXg/M/EvtTm+BJ1TM05jhFGmYHo6LsoE5YVijyU5stN3M9C8xZk5xdnDTNe4PAav3uwUMNAD4gDeUPWxhtvn/NGttbtcx2XAV3isPZlsRw++2fP1mGHhEcx4rl02/A5wyGOiG69RV+DsjOC3lav3bv56+HTCC404YnUSzxvERqdtXpfDKzWjmN9T1EXoL8ujjOCjzkjzQA76/PTqcpnDW8uWR/7fg0HC19763uIMzzyKnTsMN7p48ryok5z/nBMwcM2O/3ujWiB0gVRWbb8xAAs7TxN+Wa+eY6F8zGAdIAzAt7duZvbnL6sergToeSWp/Q53Novv2HfkWXj4HhxYPXxhgYAN6/fMHNp084fLJscK9//BH2AYGeBsLFOPTkLFS6tQmKCD65jtgeqrwh6QrdprJMeWqvLKvCFgrVWWs6naKcdkLZJGGjm172TU8+7fu6dGz31y49X3muHQK72NTh/lP2u2804qwL6OdX+xdrvwzo/6B2lnnjb/5v5f/roQyEXlLjkukcqjgEA4rCXAuOY+AggvcBHHrH6/s70ATj9Q2vc+JmHVgb0HSBom08MkUQqWcHtszs3wf1/Hx7FDOg10ZiMKG4uYDKziHk76FbXicB5DO8/kUyjfsJjfS/qqyr7z53P//9EUS83xurj/PTN575oIqDCv5aqOd+HH9xhXCdE+vIiAtX0z2ooy6nfMS1PuG1K35vHW0FloO44hxbhZueEtBv8Fk/2P77pKsq0Gp7gaWev1OLRL/Vy2t5q4JnmT80nDcADc8Q3EOfFHLf0J5uoXgOBeO3YPOtX77ltfjTbgY7xvZk9dQUQa1pMF9Sbr4wlH9IIzzzrCVrKSIYBfKXYX/uFwoePz9ZV538wI2mxFMXyEJ5Uloo42Je2AgN/G4CgsRvTTRSmvHGfaS6hoHF3zo5+pSv8y05sr50rMcRPxlPPiArMNGBqxRuBaxrN+B2bhd4BTTaMPK57QQGPbtRfQ5UggxLOm10WJ2+cY9K6Y8CcYJvK7I4HLsp+5tHoHYpKbOkpPHmkBSgMY6KQNUe6dgaGu5v7wP29HhXmLFGpcEz9WGMrVIU5xQpOSFP3UXF7cR+95zsdclToDqxuFsexcLWaDwXi7AGlXsEKkKpSWcedYBGCmddPAVlCrgNGRVCAwmN81QU1uirqoBuvk8FFjVD+mvRAup6JTdeAoj00s5v2R535qopBBOqSSznNKWdtokm3dJolv0lAOaYvp/F63b3TAkYe40KRpTrGkBTAaYK+rTa7GhmLFZpGFNxKKUWlr6Yk0pLxX9lA7F7RxpjTrdKjmO3J4oyUT0DAZVPIjQ08zwKtLkTZ5QkQCixKk0IYX1YmvpqGNciuIcyd6rrwbfGc3uOSly1M0b84AfUwY7g4mILVd6EC5TR1EDy7SfEzOelSOeUdFiT6F2xmws4l1RW12i8dAigswCV4ierFUqu3VUbg+PoDa/IL7458lcy/nW0nCYxmOdUImzDcO+LqgIrmWC/m1NOUrea0luAiNJcpJsTCM86Bxl8Y5lBoTOkuavX2B3Da142RD90eCFsYz5ULobiMPHIXrESr3Sa2xzvKzyDxm5dbKtMQHuc8+YOgLFHK3xFvCxDw9I6lrZggcT6KSxN71gtpW3TBsUKlYbeFKrmvDj6RJ/DMkC44wIHpwDw9h5lGpj9pF0fcj1lorcD2qFZGlp/crojtkYt1ivgSqEvdR4a+PmkfZuRJRDy7xtMY5L25F/qS1VpPCf23774CuJuBWY8v41e/3vNqPR2nHSgvmw4z8Z79gpSJVjLHo2LcU86d2wV4MXwfub+PJhwen8KCY7rHIT4+FTgXdIRISN+iRf5vG7SzBOznPCxgBtVbjbXaSjtkjAKxyQyi2cGybJFcYc7Psbb4llGkUsYG9ilZYdndpeMWFdFlHEIvFbGFktmF7Z9xnid0xLxOs8CwQyak6x46ngSwmeao051mHEjniEfsU9zkEAPnO1ZLCjTldWKqcT8cveQ8h11eyYCE2kazwkX8i0dZkSveDK2qcKeKrTyOKvhFsnTIUn2HktI7XBzYM5+/BaYz9+gl64r1mF8ThNzqNfi9Mn5heXYD+U5A9CeJuV0SM9OeYZw1qMRXegUqpFNIIwo5KkAT6md/LNlzFHcwIznrJ274XPh48fJ0AG1jBvdQjNyfHPi+GVglUe8sgc/VzcieFFyJ19x/wig/QntT6tHoAtEuuFPAcYcOP4xsI4vQFuBIYHjimAZfzFe8uXk3wvOTUMmOSFxJz/qfMw1uZUFUSggdKZz41Xv7qBlNw5VrJ9/x7OIB624o5/OdJBVd/QX3UX6+LqIQptBZ2r+bfm4LcqPMQb/ueEWUCnCvdaz9GHfy9mmeNxSs1nkOo5J3ElPSvpz/3z3b38OR77Fgx7WYeFB//X58wm232RlwenxDsOiOzRX53aOc8J03W/uqOUdF90KImqdtKKy1O9Q3Ips8GPw6NxnWhyN/Iak3z4SkZNnkzUiwrsA+MLLRvaKeIeW2/L3akSv3fD9YSgnDMgz1t92+LqO5Z+znR+bU18oLEvDgwjWx4n+QYDHe0x5RNcP0EfFiq+YArz/8Qdu/u3fcPw8NoFz3z4hu/ZTN1NWyanQQSb/qFsrDo1+3vYvrjIosWwY0APvls5Rrv0D2uX3/sB++0cN+lf7l2i/DOh/p3YSqXeuncr426+S/5A2Fn3k7hkqy+1vAGhjosnAOhtkdUXhVKgOzFUxxxGrdNwuwPEISBO8vb9j9gXXMtDV9L+9WwQcQELIuRkDN1cTeYKBACJli5wMmJ/bj+hESJFLmvjzwHpA1viojWoSgTE/v7lXnhm4FV/E1uqT856qug/Sin9JbL4I8ImrouZ5SY86Gs0/Fj5GsaEtm6ltp3JKvoAKn2RCHhT4usvBpKp4dHh/cMJ2wEcM/YKP2lJlJIIH92LuCnxuwGcR/Hkq/jSBvxYiyHTxR3FGGWYsBrzmLjSY5w3MBEADPstXdAg+TuBJJnR1pV+z+sYD8AimdK0lUWY3tpN87jPTOhNmexj4FM/CkIzoGeCX99kHVZd/WgoL1neu05tzr3cA0F1A8jMytJxJAW4UeN0dekZI+MxBjdLTnLjHQBMFHoH+0NH0HvP5qzusSNS2VniksIinhhb03iPlGcAobYuKoHHCEIrjqPBqV47kfDtX/3zzxOkOnnMGHkiFnhmYugtBx/W4WfeTPkJJmEx/vHvO7c1SRkSD4250FIDmZDrW9OQFELXO24mXuddJK4Yq5RwBnFRZp+AWEQ5F2EJOOAU8/rd+30KVilRVhFPCIvaOIWppEfk8lW6qno5ypiBa+5aMdqAAqQC6R54T3jQ4pDMElQrwpRFLt67NM+cyghlg1DIAvHuN1qU3HEemKMxVHRjvNCYKsNjZak1CeWNwXzf4sTXLttI9pcgiPaI34pzAHQNUAK99qYvtqe6GBZkjhFmIOZFBphtiKbSacZhKYP4tveGqd4ejH2lpG7gmbXchk8YywBVOLvS4DfLjx48Q6WgiWBarezvWCZ1HHN/fQnDlGYr9xbY7M9wD3E9MK2gzathjACrBBuvQAYCoZ56ZaOaPX86GAssCuNFYRYGZkfmxj8WkO094j+6RE0zZt8cHTOPbWtbBk6CDHHcaAQ6dhjCDtuq0NMS+2WgM6gsgA2FEErjx3vfAnDPSX9o6NWBMrwFaDAPTjOvDJo2mXss+BFofv5hiyJSVA60vIcTCh0cDo02l4D54dNY05dsKQN+PllZtGi1Vr6U9xoqrwxUOV1bDeek9UhXuuQ1DmwWvcpUKXQ6lWjmt3KvbvlKRZEtGfol7VIMOcd9ym9o5aXbgfV2kqdVVlrZJ5xr4tXE9M4JbdUKGGQM1DPASZw1AREEXCOS8cOpUlmfMsw9oy/Nc5hHzaYUvchxsb+B6qrORCYcoKcDFF8e7Or2mItxrVXdj4vvtzE1YNoCIECw0SAMfFIMTBEc1w7Z4FoOol8jJ+N29d3TxzCzhzCOeHlcBpUKN9NCjQ/2qqNV8rXOweVqGIjoc2TAJVFPWA+mMsIloji2Wa9Zaw/p+jM8Q57has2wRNBrEuqnNc1rkGnkL5bn3CCPygMGXOHx7XwLHi+8voNB/b3NOrOuAeK1g7tlaSzlw+hxYjw2tG780PYuHTvJq4qmRE87i2TF67wafMXFzOOB9FehyhOgCy8jQLV1vZCQDMH3nvx8h11cgT5DOTjPmgHWF9O4OaIbL9D2VpnQZIf3lDhqEUKxnwiaqlzcvkyHw6PaS7WHXgk+iYy7KvkLS5rhbBVfICPQjyH+XW3AaGOdbbMePneN6t8+x8fkfMZx/rxFmGx1D+Vyv3/hgXnejM9S+HSVpJznV2IvBsyCWjvO59Xfz+wqPmvdn+N4KJ/Kb12IOPc1SySCNyxq4h0es48HePQF5SJrVmanIz2MTc1ChkSXljpSZiFdjTSXL4BA+lvrYQwQ45yoTFBjzHXOsWNeBu7u7hLLrHQaGOTwi06ECzv+oQtByrGUPW4YVlzGGL6ZmJotaMIH8w3YzF9qrGnQyItEp95EnUsAMziUJs4hnpADejnZihNtHx6ZWdsgzzte/wiI2iesOqnghPg1HMXt2qiISvfu1t+pMpoorp3fU2bz6PuC8jzBeoUka2wEJ/Bpw9X5O5V4N3g/IaPj4LXZN/sO13pymPQLQ7YfNV6FDiRFC9fcyy4ihYYcJWR/6cjjeyzICZLLzO9mJkD3Kl9Zzr7Xm+J3Oi6NZBsrWcHW4QpOGdR0uS/ke9vV5VXvnC/kzkvhE0LG37Ps5/Clo9w19aXg/HqFQHB+PAJ4hMAP7a4Hzi27x2JMAwGe0z4L/+PTvWIfR2d4s+v7t9zes+hmPqp6RsTjDOl/uQ9vQcZ9anB8puoWzBkL/1Xjg9v+z96brceQ42ugLRqYsW7JrmT7nx7n/m/tmpsuLJGsLEucH8AJgZKQsu6qnu+cz6ykrMyOCQYIk9gWLqGW4C1lbcRzAYRxwXBaXJWzVe/cynF86VBVXqrhBpsgPHtxha5naGuQALLKg+XtUjK/ovbuT78Cq3coD9Y73I/e2qGIVL904vQcTfMl3Xw+gsTwPBIL3eQbl/QyG4SVKmFQIciIzaPxNZytHu/m/ku6kkfr//PFHBXfg+TyliTcCXiAnK2RBILBSlG0Rf4/zws53fxZAoFj4zFCMdcWqihs/M28dbogxAlR0vyNOFONjpYyZnuHhcEJIOF/JzCpvmJEqULqdO2YKXJyvv22AasN71dB/WI/kK+c9zr33ue5hjpf3et9Vx6o+zziNzgOQb6eeijzxzVTfry5+WX3uvdjfMzX7vsbDrGV/7WkWrF1VwCApgtU8v8IQyyF6pwNv/aaBW+Am97WKYsUdPvuzHwS4/fgHrn/7Dfcfu9FBjmUzqRilnloDztmUwoGjFeeNzXXmwotgifgvXmc8imzpI3mCOX37wIiSYiOYRe5a/k+InCGDQd6LbmF7p578ks/HBBH0M3iSuJC/vGb/fG/k+Ylz9Ux2Y0zzj/Ua0UN1upnloZ/t36f9NKD/k9sWWbzmHAUyciLKqJwxOvoQrKsjerU6e+qMcX/uOLgACbXUs2tXHBbBh1/e4/HuAW9gxjfDrxoGTChm5XGlOy6IMk3MNClnUAPxqJ5Mcotncp4Fwe4yX9bRe2Q9EUali5rSxgihnkSqD1C4A1ZNJBwKFEeETQS/aDoCX1UGczMsRqGfa/vm8vOtwkVkvxY6iSz1dcvvDfjjPZ5xAwE8hb3gQ6nheqXG2DyJGdR/VeAP10PdiNUyv/H3Aa6YFXOZsOWrA/OZFYKgAI4ffsH15xUDt7jpPeuPCUJJeaNWT1xbzuNKBV+LWy0J86W/8kHqlbIOyc/57/sLoScLl2vPmEqMAW0zY1I9+CCCBYJ7WIotMhiNBiYqKgSQZYtiZ89OOMOsY2DVG4tmxFtgJS1+A3EfbCmP8G8Sca83vzlMVQmxgUSsWXgXnmNdgjnAyTksd4HKU8vuP6xuk1IJ4KKNf9fy/bvazgM6IyNIW+Ks8W+DKxx8b+V1RozqdF+d2cT3l/fVNZmBdG7sL/04P7/tbaPqARPkYpApd2WemhJ7SPPIHYe9KkZLoQiakebx/zRESd0HBEukMa5jVGhTMyp1L8Sg6s5UDtPKNAMYazeIE63HS+nrawp+eQb6QTFGmxnOeu4dEVPwRSs12yXnWAVC8fUNGigLFEB/+mrpFEU8tbuiYYHKiHpRaM0VtR5t7aA4SMPhcHBDDRnkFoJMUAwqRodCB0ypgRhcCKvv338wo8bieKdJ7MvlzRs8Pz/muZadbVUEjElo5/7RuqPEnRCKkdEXzVItG71eIIAoBiy3PDOQUOCHCLBaJKQwO4KIC2iekt4VS0ZX6YjAcjNld/v+5N6TZsowGsFCSYHcayE3O32Z0YSNLwTLQttp0GWqw3m9BrpHSkizczRQhK5Ka9QNoIOZe1rUHBSwpvlAx8DQhqNHn5wsnVBBkbSGSl9T5JmjRx/PWMZAW1eszyuej894ejri4sGM5xdvLnA8HnFxcYHj4YDD4RiRrWcb95Qr2YfXOLcopRFwOfg6hABMBVFbLD201/ebaLFHh+tgxHgaDulU1YbVfB7NUuGOZYl7yePmIs9jZqo5+381Z73njiHdFJNVKVNRtAKhUeP2I95SS7EaJ2UoZEkcONMdowtNuf/dmVMR+41Rk6oecacaJQzMMOuObsGMusMO/L6eQ6bRnVxynQ4InsXOmlCpJjJlAOKT6tFNlo7Q3j/4ueARU4w1SLNyBrb0JivoGO4bQD6J5MI0qGtPHEhKIwrDm57WPKxmpB6jnL/gUwQoEXLMvAGH5+PTc66LA3tdFTJK9ghoOsBNcCdMC41XDeeeunU4PxrpBYbX95wwLJpUMXrHGkpK9bPtClTveKhFJooqsJpS/OCpSwM3kW/z8ZhydxgOGwPau9GsZTE5ZmkYT4+g62DvK/RwQB8d0rs5FT4MQJ4Nx7ohW0emljZZsENGhy6HE4V+AMV/SNY5+VM7v0GcMLeCwOM8xY4+38Ihhc/Uc26rtiJTtp++fcv1zP38SPvxJ8+3IDki0w8ZDfcC38lxVTjVUaoW47id35JDJvYbeK4V4ThPQ+4jEi1XiAasg57DjG5+06W446ogJFT+DwDLtX0bqhi3Cnlf1q7sOzsfrjbmHvJJpWN/hRf/l7kzZdmRxH37wOSrFxwWxbp23H29w9W7K6f3hIxYVozeg2fNoyFlJZyOBY1cQ8mcLyy4m3TF+QXOKrEh0d/GeB78jtMovye7Nvxijgicwcz310FozAPBO/DaI8yIbqj1gKM+4sHfJXCdAm/fOzUhuzqtYjYWIEoIBh5GRsrHC6bnyd+K06A0FibUyvmfdnAd0/w1+Pe9Q19h6l8iqEGddrTTR8hP7vfp4/Q1iiMQ+DP3Q2RwkmZ8t5dYEREr8+PeulEHXQfWdYWIGdAPhwMOxyPG6Hh+XvH89GQBN35/pbMBv81542+GO07PEvf+wWuXDx1Yb1corCzVYwVCkbv34DIG8J9//KcFLojgP375HevnZ6z4gq/coy570ZprrF/SEHE5x/aNlbgK/NXcybY61PiWSu444WClCxW6LHHGjqo4jiMObTH5QMWM3V3x9McTxvIlkqHPhnPj4UYfJg82y9TDqPRmwqKdjbGir93+7248VyuX1dXpM2wvfmHfvp4Krmv9DFyryWxNTRfKGBO7egPBkuitpgAAIABJREFULwWT3YB6QII3Dein/FHM1fHhgTvY93KThovjEV/dcL5r9JKZZhPeQ4fL5e5gVfSU/piXA3EjllowGktFGF42x/gRDiQepNAaDo5qTEY1t3BtEk6XUDuHo3G/EfdqlCKDwuQmBRRW/lI5zz6bfic5iON3WiACLEQofk9QIe+/qadr3+CXK1+ju3JOKXNOYHY2juvDH+kEBk2HNaM9EnrrOL3+7spjE8fn2PU87X1VI+8CJKe8z9eJ752a/aMpMHAHRUOHhvHcu4y93XANQKNUKgB84Rz++IhbKD6QHEkNDPKpQvfx4gncC5V3ut8oh8eaJUcjTbBQx0KlVIzbZQ5VhkHGOxWUj9QzwdERx8urbc8uefX4J3+bUDdny3X2M5AkpOzp16y7zB/qK8nHar3tB9qWZ6y/b/nugnkcFmf4GdJnx0GCrRPnz/bv1H4a0P8F297BT8Qw/0bEw5KXwwUmU3pKpKhVGFIdUDw/r2hOwC6OR7w5HHBz+xXv3l6iPT+7MdxeMMSFW+cb2zDvR9a9TgRG9Y4rt4gyi0IkPgS22zA8L+ERv/ZhmKH61n96DyPO7weJjI3ruUTOKuDxcsDvCqwb2YTEjUz0l2D4gQ/YpQfbYU2ZlBjRvovAq2DxwnTZDyMmOP5z7VbM4H3/x8eJgHDktwpcQ/EsOTam4ocCV4OevFZP3gOhbZwKDJEpLVcVq70LXA/F3QKoCu4/fTSGbnzAaFafSNUMzreyoS+quFJ/vyreQfB1465Kw/mktK5U2+GainIKMvJtQM9DeRXfdu/9D+4VdUPHKNGkAN5A8eyMza6SwIM3RRoeoLiEZ0S4M+MUUxaPFO8AWAQygExJ6NyiSBplZAuPsu8pnLE2KDbXEyBnPu/8yOUYAo84G1EXmEwenXEWV9A8rX23tzDuTxd3BzBztEQx/vd4PBQ+P6OZqSAyb3VETS0aY46Hoxt5TCVOBln7HP0er6zv1RzAyYiD4SzICbmvJQc7vSAVPCkI5BGgMRwlAqdGxmsIslT4U+ARFwS3EQwc50JBeO7OGH8KujDhPurECpn0Ahd3ve2Y++e5sHPKAiHus7sCsoygIYqskX4Qc5IYSCeyoDueWjCwgOMbIwkjop9FEM+34yUgeVIbTIo6yGKGLMK1ePQ2wA3DXC5Gt844hwyzzVOhzeDQ1LMbKHB1dYVFFsiSUdsNgsNxgUhDX0ecIYl5VQE0JliX6WQc3FTMyKCh+uH5iIrTAOB1BGfMxR1FvEEUyx2pY6AtLfYJIvrf3lddNaQJmm6diuy7vZvGNX+Hr6uVGVRcHhY8FiNrWw5Ytcc2towSVERteZHtWbZxWVBtOpAEzsRMG6pDR1VguobBBPHiiKVq0Q6xZv4jAwZGg6VqFskoex+AOBBUB8RTZyujjR07qaYzlynj/WwMUy4eFotAFWm7Qlt1jMx3FyWKI3gdNKBmRNJeHfKMNk8DJc8p61NSQdkAjNbQYPXdG4Y5Iyym7K1OYLanEPSKzwvXGmKprRcCjwoqBWSEwimRa5v3nyLKVFBhhLx7t6UyaIARzepKbu6H2B9eD9OuS/ifaNlPVNYl7UfiVaCcIPj93KlUoNkfcygatkMUgGR1ROIwj/l0RYufT/FzLRLGfvX1b7DU5aqWMh3ARD+SUyENtHrFPG+WVaJFqvZWjHNpWHbFNXn6mCzho+FcMTQjroT7YBMBPtE1nddxbPrmGPgAM1NwHeh4Q1pa4R3nmp8dL9X1CkW1Z4eZHTXh9Axel9jdyiRpHDFXojKHHwTtcMDxcMBQS3HaRHBcFvQ3l2hPT8CbIw7jAuuwCPL1673B+uIAffbN7oqenItFXkUk1GPJqxSw0hw/HDUkW7pp8w+cHwCPbM/10N0n6sM+VioJnVHhLjyKyVBPpY/8K8Gzht+k47xvtXO4oL6j0o1vt/mu1xjE56fnCKZNjqZTxefm1cl322fur2meaopkFcVXtRTsTQSPcWbzeZTnaiQV9/BF4EuEoQEyYhbL1XvoneL5tkMgWK4b5Lr5ORT0L0bz3vxy9CkY3ciXStKHcnaYkYmZpuhwSieXUsdnnkTgIfXsIPl3ORzwtgn6c7fsF+S/fV6qkX8B0gS6KgY68CQ4XLbgu1yAjMAFg8+YcErgmewx1slwpvPrWoxi3q9qZmwx/FJxEoKnNKdGL4Eh897aMyyLSsgHWu45kK/RgbfXlwAW3H+5ifdVfVX0rcb9ryG3Wir3R+LMWJ7cPwBCH0U+nIamxO3ku4bx3JEaPXpCcr3z/OrXsf3hZLOff7xekumhF/DbtgUvqSW7WPLPlLUVmEowkj6EXC3W19Y4QJpFnm6qkCt0jpsxgwLpg6g68Ux1/rL5Xn9//Gyaro5b3EPxBjIbzzfPhV7Dx99INGHlOKDAf3/6exiW6AisZOqCPXG8RbZJsn8RDUd1IQ8LWLYePy9Xvttvg+1KI1x8TvD5CxJuzAtljrH23isR3AkdmcTpMeV7LwXTEPNQNQ6PpbXH6BjrMCdST6t/5bz5AR+gAFZ8TsdlxbkNGj8e9AOW3xb0T19Md4z3MPN7ca8Zgi5fYq1uJcdoRkQJPRZ5DFsBib0ocONzM8G6qeD4H78ByCAp1LfWLaLIOuA+H+Xd3v87BR6q7KMazvAKYBXqQWtUvNG8SOPuz+kY6UzhPP6d60nfxRwlsgKG8bscjkojdSSPqcXBM2ump+Ps4nttKKAiuPY+h9Myq9MNLLgpclP+z/d+UJvpTQFJoARmlSo4p7ZKE8LBdYNP3quW2tukMTsIYuq44sXv44MAP+dCDGu65dvIgDH3l46o9u8FrjHkBqu4JCqWRfSt4zZmYrx4/x7rTWjIce9ntQYDHAD8opZF51luT4S2CQKSeOEEHJVOBK/vfeicaYf3c/Z0DGEmP8Nl9s82Mn9yLpRq2C/IwWmv8Q6Jx8pgT2hoShGk8eeN52cAsPvDvKfmcXzvronndvZHdKgFRtv76ljOdx402J6R7Xb82f7N2k8D+r9Y2zuA5FeDR/U7Z97BrhghhkcOREytHdrWIrXlOjpY0/zh+RlvL99EJAjTrzTAU4A0FzIbII3VD7GHNqSMjJGRVTDZEvCTyQdftI+Kts/JuQubkQ2YaWZBwjAEz/L5y6afG2f+aKDee43gtDY64fejrT57LGP8oKdjZLsVRCr32j54RPmt6DSHW3gFI80xxyQ2LSL9tr8XCnAjiBR8d86sHiD4dXzAx8WM6AIbI9lsgUWdG6NjdcPfqeCdc9dbQzpg6QPvFVGL3PmB84P/BzYzets8tkqrH6GNVg/9Hg1vQTNdsj7zXs0IMWDLuxoTJJPytqojyTqJK/F7n7HLn2mT0kZgys0N4+j86D+gzVAn47jr6UlmUGl4LYLvZj+dZZDOIrO/cCfuvoNjTIZ6hmf1WE0DkUZfycwZTy7zO8LgYDSiF+Z6uk/gKQdLFhI/CBGB6Qw39BSOp1NrEBoE4aLiUBdgxVOPS6TKFR9jRtGL1xJ0UV1tgCZQEwZUPLWA39IWLG3B6CsanDa6IN/cSm7R7OIR4UzX7unqKcAKyzr4+Alb+Hn09OW6uDFxAFfXVwabRXBx8cZoLqNy4/1lT4pMcEwhewbmvEznGP/i7Ia629X4Bc01r8aeJg1V4ALBW/AQjd1Mwxy4KNBMUb4UgxWV0zU7Qii9/B2h2GrAEYLHnu9s7YB1XeO7xlhy31GGT+EtlcVDTUFFRa343tnFHxxT1TPyLO3ghTAyKPGxfZnOr2u2T4SrOHxpVMwa2faDboza9k46mZixcVkWAIeT/s/h40pH2E/SEy21x4dHDY/ZiO7R61QKmeHRke1onu5/RGRjE0ljupphXbiWo0/jrJG4ANwhw6I4FnWl4xCPoA+UnwBVBagsKEgp6IX6GdHJZDkBq45nqKJFCRPrbGisWDEWYbO3JdfY136oIN1Ztvz+a5ufQYincS9zFxg+Eynn2Q3pSkN6Q1MFq/kJBB3DMlLstaAn6VgDcSO149vm+MsUwTPdMZydimdxJSSjW2zQCAMCDejVuDzxsptNvrWr860VN4Xjno/D3Lo08JJd0kzBqsxmVfeERr8czMlx/qb2RDwLAWm8E1tmEUNi0NYsdbv7Y6K5I/PSWixCu7yENEFHB2TB6B3L5QUwhjlC6AE6Vgz1tPSu7B9Pz35W6SwBPxdvYMmUc445SSXxm2j9X9XyzPsKVVgG0cr2IqSDXr3mfedb39wjAL5+45m/sm2N6N/9vJyfZzoozksdSnMaGvbo1jfHnXg5eIe74fPJwkMCYNwxUoyQ/cVxpXr6busojFVlP9rYNs56xKvljGoFQrLBuX+JzzXPsD1TeCyXeYauoXTnC+TYoM/VFGu4w4w/ybeH4eQMzMRfHBJeGKU0ATqt2OY7+dQh82vYj+Sc0llzZzDFcTMy4ZGnVKtjbnW18/mueT0Hw0wRPhfnazqHWl+uCQPlf0EfNgp6748/GD1mB1v4ACcnYG/OuQD5zC6i090uXoNPJmbx7C0aMtC5ltkjqvJ+Z0xKNK+Ryp3ZAasTDMuaqSTMCUo6XmFn2DvHCm/9wzNu8FCuv2Q8Pzf+l1osjUiiBf888QvRvxvPnY4PBRbVdCyK/W5n5W0H7lrtq7gmb/ZFoiTydO64L8MjgG1srRhsw/F0adh2GWUKNDMxWfYk8uV+lnxMK76EXFTP2UlzIF+rZ7YEpY8PGPgS8xgAbvBlIwMhgmKud/oewe6mQ0eTGiHuume8x/G47BzJ2annnBEuZbGkjNQbXjkeoNHzhjxWOdsRKSrk3zP1v4hMyav2DnU6VBAZ5V/SKsseNI8/Kx7omb2uez9uttrN2evbduUX7uTMDT/QPuisEyVNjl2/ocVVF/HDTdjT6xrPK7fuihsMWL1zAFaqk/cK8FWtfKzJTNdY3jc83XyZ+vwAwRckrngFpp/ae8Xk0PCqSSQL5m+kcTaN6MFZaOGdi96F/6Z+Tcr/8+v2cOYJD47griYa8o9ouvn8F27jf0wrsIrsDT/bv137aUD/V2pb7nJLmANLEBnNCImEenjqUQWwtFQsWc0MoPeB9anj4nDEcXQsywEK4HkMXMmCe0nhmEaJRQTamqVaWhcsbWTtqsIYZpRXFRwybaOSyy5KC8WMeznViZj6x88yfWWCJdxA8QuAGwv+wa9+wxGC499+w91//4EGS2muyJrltf9zKOyLzAZtQTKF52SrP9vIeCyb/vjubSp3NqZep8vCtUewfFCFDonrXIIbduoD/6Bp3AbSaeCOLhOhMFBXmGghvaloULExXuETBIqrbt/Z95UyukpSYFfz3Lxz7vFKBW8HhfIZqm/9l3e+f76ylstmf/Cn714TTUEQPh9afiroVU2VcxkCps2DQsE3yWKVxkIsuHSmjpB9B9Ga2F4iYoeKXdkor6g0mJQx4FljhKv1Zanf4YLXd0Fpp1kHjGBAB4YMLG0BtHjcvfY9P6CRUyrdATx6PdQtY25GnRzM0g4QEdw/WrW1Q6Ted7zlj9eIVgAhUDXWsNvUZxc+uxvxWe47ub4lAvNXCl+Wvq16oNoNy2Jp+4ZHmjHifwyLhrGI+3wVawOnxyWdLNyIUM89XNgRg5MosA5XoPQ+Hbia2YPP1Vkp7OwPDIsi4Ov9Y6S+JPsvgB4WqGcSWJrXmPOU9UTkC8sZiNWWsxTsgAecg9qiFul5TcF3uDhCVqul2JplczAjNo09TBNPYcOFXEYMYbNfq0ADQKLMgnmcX364CiPL8eKN3bdIpuAdwGinCg6C2FLCeZ00mZnxfW9aSX4A8Fqb2af4fekEZ9cbPJra7xwCHEViH4oI1t7t3EhGxFIhMaBYYNGwEmqBknI1BkGHP4eapOJGB/GHnd0+BsYj19xgtK7dFUbDz6Pvs2FGcahGiRoqXmd8zv9TyKewqaqRESTG6IqUKhwqFM3XofduxtyFKRY1lAjqUcqisNIAOsM8CEjAgmvDfjISZvRhtZP7gt47jp6amamjex84eHTq4XAEjhu0WhS1OX91QyXxXU0FS1NdRrWlEb0Yzl1RFPCRPAvEWbxOmhWgdNgzKFBEPPJ9Yjg38HenFwXGYhmTFLA1H14ffYqvNEprNEMDx4jCd2qN7uI8ikOoVqrMnZJnUwfSMCUtNWN9YJTUoYwIo9XZ+OidGphxVHx9BBEZjHi7VyIfBZ/SIEo+xvE76+jZ3C2a0m4yBwvtvkdJCZQR2AMTzfEom4BFa1hEcGgLFIpVepb2KIp8piCM4+9dLCJ4XleQdLZKrYNXUTtfEyU33L9qf0EpUV2GeLwcs9nCoY9Mbvi89qAT6vSziWDtayh7QxmqsTKeAUIDR1SF+J4hb6L19DmUQACZjrcCCuRJ/Z6+mgOLKtqyYEBw8B0/HHijNSxqdM1qphv91eOKvgJYFCuYoWZBOx4xHh/87CKz0ehTGhbJx050qiiGCi+sKEdYTMYJPOYRXTLmzESRAKfiWdIxHUAfyWfxXb7fjoUBeS57rbZwhOAakn/htRc4eXZXM4/91Y1scND3In/FHMRcGgCPwpyef8Wo7HDGx9yTiqtySBXmnvjVx3Tptz0r8KYYKuj+Y58FT2DME13HeOaIF97BCmMJnvQu+mkiWO9cD6GXPsbLNGYQNpWmCrPm2XNjqJVh8V55vsfwDFSHA6BeM1s4NtsL5Hl0OL2aMv0I+ui4f7CcZO8uL+0YjORBIIrH+2enNCyzRP4aM80jiu/dS9BdAHgq+4pOcRJGaAgiiwfxsqWqTv1MRKd6R2FAk7LnOSNRNJWgf5xnOuHO57xGQQvMeP6ktq5voLjQC3z9cmv4uuzDoYqj75EnBS7Ea11v9iqdsQEN3EPnQBq/1PlM1uYmDhYi56rAd3wHUOaZ3oZpcuVXVDozMYHlEZ2fOJv5Qabb8E4BwRVu5a7cI/PfaUA8Q8lfCQBZFueuJdazjpU403Cw3yHz2uqwmtwiPWpe05nDshcpLofgqw68FZbcSyM6Ak/NAFRN+g+YcYpb6WFnihM4vUXpn+AhmfGSDxTAiqQ8XoTd+qomCKNtGE+R60063tDQdUDEAj3YSecrxYzoQKar3u4k8XEvvy+QyJhJGUeg+AIwSMllzSk7DWUNW5DQ9Qa/rcMCIcKx0OBT+ddn/YIbUbyD1z4/gTT3sy3MFfGRAvopkCEEH9DlBssAejDp81pVYyzZTmaMCbzieCtg4WXYIGJ8QbvB038t+K/DpxNYnBjn9o6a5tLTSNxU8X5YCVM+fyMw1NqSD6ROJuXpZg4fIuG+ZXyD4N59+Gqq73LQCu6xzw9qu+sNBc5BWqNlPjzbuZcWXAFQjPEl+BVVPdFPb43nQUsTLFCcD8bKB4O5DTwhZYtY33OACufKyH6CNfFVOq6Quw2eoBQJfxUfJXtf5ifvnG/m2K6QutXkLA0vfPY5HkpmAd65wINEoHi8vYUI8Hhr875Wc7S/EcEtgA8qOOAaq9yg4+ZEf6Pl3227EZzAcvtwgikzJYhfywAPd4yG6QKzFvpmIJXMuC5GBh1Z0mnSKTDonBYZJ7fzCprM8znPtOLFE7L5Ay0DMpAbam+Cf6Z9a4Cyv/fq9XRq+Nn+t7SfBvR/w6aFqiZvbIRuFOWPtQXLAmPKxITA1etoPvcVa19wPAqe1o63l28ANYH4HsXwjlQANRKRHtUZU6D/5rg52L2Lee17kekvIw3jALLmCIDjb79MJOO9ng6VUebfajRa79Y59xfyva/BkxXvn7tuf38x5trbgpeN6LvvcSZLYbXHBfvR7KpzTXn1z60IJsFQazJNUp4HFO+lmSef5XvCNYriH8a8m4eq2jVnAG5LR3fwVEjYj0QHGL3+ne1PUOtQlHrbI5s0ZtPo+AYWWf5Ch1O7w71HtV/RxBSMbzIxFCJf9toMb083IMzGqnnMlpKw/xnw7LwfITzDGa4povGvavLi1/0HCijSUEGFgSZcTxTdOPmuJ5dcXDgDzNfoM18Y+c5w8hxK/F7GT+ZYci9NBo/SseSHrFuWPyWqVgr1ZPgFQkeWzRDNb0rjhz3cN52hnXnTUDLWDhyWUJqK0yTViovS+CUUjrdvVIX2DlkaWjtiERM69OKANro5qfhvUetWxGXsWdFAvFgmm/ovIKIuoVQaKC6vPAHgANoFa6g7nV0Wrze8MTDHGqRnOxUpMUNq2x0K23POvza9zCeT/ZuizQzBKV1ZilN7+zax+2E54Lmbs4YOS1VuylqNMXcMSAzNMuQIFkpuUWu4iUyjqVOa4+V5TtMgSpj0QcePutwWQToineP+PjNwVyeC3OuIfTzTvfoO4n/uDa5RCMUwJeUQV3OKYEg3IRdljgx22HAV3NfVOK1Q9JXZRA7o62q1jvvA6CtGH+iHA/rhiIsLprr2PSkzDU1lasGDfJ/XGbe0hE7RNedUo873o3LLqkrOI9ZSKaDPZ5Up54fWBT1duwbBEIvUkeH0MnhjuA8ADRaC0PyJoCkj5eYzx/1AmDD93XwCbEACCaV5KJa4gjTQN+tPhngJGBuHSkbJh2OqphH9BH0RZjvg0HDkSi7S6DvmdJRUmPCzG9dt4+KEr43+Y2m5O4n/eU49+tmHEMb6eCeNPgVJxuztXyuvkmemUJ6Jp48a6lwfwCOva9877RSk8TvxFGHfu0ZpCgFThaob4LwWbZCEqtClcv4V4wkIVP4scVXMcqusKf211tDUcMsYVv80nglFqD3UmmAZdl5Eum88q7OKwzPQ3gRDIWUHnEYO+VYpfB1Xq5AiVOwd4/0WQEr/J4CCRqpOTPjV8fAOjr7wZXlGbYoLh4voy/z0t8a3WRk3f/41TWNPJk3NQUgaqHBmX7/uLdGzlu9Mrq6osozhqPugjz6UnfV8nEaWZ5p7OjKny1sA9/GuBqZT5rpIZCrhJElrB0agc8tC0jD6cNqhmBz3x/A5mUJ/DLVsvOrnpCHeBYGffcvasJfFx+juKLRrNooHra6r84bnhXQvM7sc3l5C71fMrdDSusLe78wTlrs5HpZ+0cQzOrKsVvZnNXtFt87rYg4skoZrAJ7lifRRQ0YdykjzR3RVd5TIXcWd0AAcCh8RvMbed825hx4MCLlt+HUhHCSfTyRd6cxr5VAt/754y0s/vNCuzvRJHH/Cadq8gKAPnNt0/shf+P/bbmIdSB6cBxqjo3eTqarzRGsCqBnR3+kC9TTvKlYmSIHJiP5S40rcv24BzrazEXyUeyuDFOxQGqfDeLu9VUnjFZARJRtuYKUIeZ8CqGzpWxFPX17e5/ct+qs5IHLfCZ0BS7yqiJUMc7wSawjqTtw43rNWce8sZUMefJbp+K376WGE7ez4e7pmAsuoJgDkN4F++mD9yA2u//Y33P/3I4Cbb271uNySD+ELIgMSZV8a0Zfm9cNvZkBux/3CPqNe4lrTeCzwtVXFEMEt1OZYdJnbbA2UB9QdGGvmkZTR+QOdHECENQOCvzvOE90B33cqiHTz97X3f287dfz033d4O38g9nmuoNFiilU8lg7haZAvjlPmD5W7eOm5PXRj9CIvso8HmP5WhI5vltK9jvMtLNNqSYOKyw+/oC2C9eP3w/q9ph78HLxrI6+rmxUwXQodGSRgbA/xJuOyRJgZznkJhenyaEQX0F+/UE/Efsfm92o83461jnNvZt8Fr13aoecu/M+3qof72f7XtZ8G9L+4nUN2uwzeNxQpJ7dueA8IwqM0nlHzmFxVI41WkwW6OFOwCJaxGGJdGkZreNaB43IAFBhN8LBa7Rz1vjga82pa0NrAAhOiejcF/JZoTZFSKJFqROOBbWfBZDOb+E03BlQSg1uxajwf1KLPf3VO8d3ffsciC778n//E5e+/Ts9VL7y1XlDWhDlNoaLlNl6j0V0BXBd+9XtSt58j9nz98ptg/fg5CCDf9xI6JvFllDxNJEM108Mo8Bmn6WK+kA/wZ2/9haytY585xjRQpbHRxnlDT/nwGFe8k62B3Pq+haWWt/pPpoy8EzOO30HxdmeOhNnt1rB+Rt6cxOaZ13l1ozK8nsFLuAf2RpEtzpGJNiwQPEq9+tIK2n0PEFzhK4YnEZJQLNVeFDp6ng8RwCNzyfDxPRbRWn8zlsuUU75DJNnYGM034BRyw/Z3/5f4cAxLHZyRiLMRfRbj5hd8iyGub2TL2u+ERz31gHoo8ps3l6FsGWNE1DFvHSPhWYWmi+PRFOsekTZ6UVSXDqisjuPx4qj5y+zNu8eChVDiSzb6cCZ4SeURLIraHJ1MaKRhgTK5GTbaiYwXylBPJW5wEPfKFozeYw0JH0BwWBZP46zIcG+ARmWFTnSsKrktcsJrU8oWYFQO2n3jGThc5FrdPzxCRLAsZiS6OBwRijcfH89JZGsAIOLR4zKAxaPZVSGHBUOt1pi05kYGy8SStLyoQ7cw9Vsayv0kfY4jH+6/4vLqGu2QdZIHbDxlF2Jd1xAub29u7N4xMDDQ1dLv0u2FOmBo8hzNNwqdHbgeM+XN9SCe88nEhhjRv0TUmCdzxNP6jMOyuPOeODpxHmBopLtHVR6p17iWXJ8Yo0isU8how96oYFSFBiLnbEZfPULaht1B/GbrPrwuttXtHIm/dhBMFcuzDIUGjYOwVE7uf9bitOhhn48ijMuN5wcCiJ8pKpDQoa15tK1ankNfA2JsrphtAXP4SYOwBwKP4VkaPDpldPQxLPp8eUZfL7xedFUinvKoWwN9RHf5XHwRE6erhmGRhnamdafiO5+3aKLRPdVkz3uZcvJkPcSMFH2do1OhVWAf07PVqEZFr7rCADp8eSUU7LH/fd3Q/Fq1QzptnyLykJQlDeaAKBUvZoBhaQBGErc2aqB4nRIS52lJNZo3s05u3s89oe5Q5Lyo11kPI3eQ4GSEmixRdzIcRXzCTQTjmQ46pKuElX1hatHmZ3fheVnEamYyoopABDDhI+/VDNL5Iw0yUpQrHy6xAAAgAElEQVTkhgrMWLUsS+E9ayYeX/eCwrYQtv2IiY6xj6GGI1oTaBOs62q00/ca+SZZlqjHXmm2+jkI1fzMFoTCva7gGMMyw8CclbRpRFQDxIWefaN3LMdjnKF0RFFXvgNY/ZrUfctp2vlvbcHSgN4u0PUZDc/o+gQ8KfTNCugCMzcXxlqAhjd+Zh5BPmdsjFQb1qdM+NTxFg7TJg2LNMe3pe5sbJH5uTjqfiZjj/kKg1HAxREMUBxPNsRsfNxypMV8u3nqtIW8hR83nu8po6vs8QYAVPFUAHGhlpp2emZP75AXT9+r888WJWqGhgclBrERBs1Tr4cO4qi5//hNFUd/nuaiDjeiy7vgC/OpMlR3CFrlzkvmvMPxfWbz4Twtw5IC7WD4z43ji5ejWaRhXZ+xNM+UU1KL17kHbnVcKM34Bcp5abQznvjieDTeQtPBnNHBUODy7Rv0buncFZbJzwxydp6TThq+OywL+puBft+NlzhdqYnOhaOM4w7iR0ai12hV0m7nmABlDXYBxB3IBs95PaE+dyrSVSPyPWqgB34xXMCRPzos3qgGvRsAvpadHsZKIHiAGpGpmhGXMSZNGE+G9eY90mEu3sFSJMQr/FT/neE8TQzz1zSc8Uo6su7hhtouvXSd8Qqe42+L2DaZySYHJW5caKRPp4MDRxAZnMjLx5yTdofTn8sfOhTSrVTO5Ijm/UhreBjDU7iLOVAMi87+lr4g5iCCOwCX22tnPk/ks+Jnv2B8uO0q4/W4LpJ4iJ1QhiNMJK+F7stJmcmhAxhmuOabP8MimnXq1/RW71QsKtt5IdIkjklhy7q0FkY5vVW0o5fLXGhQ9k7jrPo59vPd3dFhDCvJOejcqrODC5DlRZoq3mka0Lkee1C/UuCIXwAB+sfPEPkFy+8N4yNw8euvePIyWS+l/RYRS+POTExq+/bO4SMiFkAjmb6dcxcRoAnumsub2zJKmyGfON/6QYkjWnRJxkOqVXGX5rxHUnfujwgQ8Ct09uB9XwWAjojYVVU8LIJLJYdMPiTPLgC88fP3FeY88bZkJfPJ+HvM8UiI//SGXk0AMkMpJaKW057GWfGR72iDA2Gj5/jkzU0OmwhMyJ8n2QkAjvoeXW4BAL85HD43cSGVi1b3d0E1G3i91Hbvkf2r77HhH/3TItfocof3S7PsPSPx7ANSr0L6xDlequlq3v32OwYU4+NHrADWmxWqd4CelvbZh/HmQoHDizzcblfiTigS+rupPAKZHb5I5qen93MQpK+hd/HbJI3ufhQQchUQ76kyct2H3sl3ze/bTc58/hM9nhnjfL40ftNyf+g4Hd9973r+bP+67acB/V+xbYlaZe7IMyMVFHENACOAKrM8PO0SmRQq8g5tAZpF1705HrA68W7QZMZGSUUIQwCtNQwomg6rL0lOnMSTBDEGnEzEq1FHwe+nyoSZ2pBP/aB5icT8UwOu//g4eR8agz3Tq0x9/vr2RYBfijC4JQx8D9+7N8Vz7+M4x0ci5Q8QT7ok3u9LUejvfVxffF5UDArc2cCfW+ogviH86Mga6rcuf1yrTGNorE1M4cL7vBHgagBXss9wV8FQYMZzYIbROxV89RRaCkSq99e019955nkqZ4NVyD19CcxpZJDMOn++xGlaxW+1rwDe4h4N76ClmqIg35VMbFFYTpMtRH3DxlUDgKWl9ig9/fPwynfnOvbRzcsxmMK89s9tPMHWQuCZ2L3ZEzRSJWJmDmUrifwQrySbT3LytyL/U6Uuz2A9UbkWKRBKCPiI/VPePTF7m7+ymWRlqJvVYB0j+7K3K2pkL3t7CQ9uIZIrMtCfBLgQRLatGHcyvKyGHrutyAcBhyw4ZudA1MqajNUE0iKIVBjRZ8Xq9C5oR2A8pyFF6rvKRAx0DSKKh/uvuLp+73QbU01gFaD3NZDL7e0Xk316ByOWhnY3GpoxcCA9ie11O3tkY2TQyi9sFHY0/qjDYQe1RO8pNKGcFcOY6jwCx2mLk8iKsG0CyNKChrv+2l5FPx++AxplZKgLo/GcOgaFO0TwncVamWN8iQpz3HOGAeXnDf1UsVfkMqYRGgVGw3LzIyLQGyBD7Nw0m3tVhpwYt6lsH1QuFw8+j2hJxbMZqddlwWE5YO22ZyblKhBpI/MlqbiOqDqE9hwTQ1fvRTWUa6R4DyX46KEEnAzo5fdpFURi/45ukfV13NyHiYd9rJo8p4inL3WHs7q+w8tXGO3UZF785FI5XcCSL91pNUJ0lL1hD8o3o1wrXeZejmg70ucNjPgO1YrvfRQ0MlR8R8WgUEFO5aWfOUlDO3tMA/FgZ0hDBIhQc+8y4tydQuD37NEZtnXrHAFYOkUFluUQqdsjIgiBfQBIyD5DhxnxKywcSSUZF0tdPpKWQz3ts2QmDHMAMuX2cDw9hlpmL66LDmgxNylpDunrzlzDEYnnRoDeO9rBDWvqeLMZzHsYlTLapLucxv0CAN3xU4c5QpOfY+kewBTpTQSDc20SaZ4Fzg09DcilmYCbZCrHk3ls0ubanqt7MMB99tjUn4dqOmphNspUh8IYbO1ANeBdUNOmybRv67y+xYu+hldhv6+573talT3iN50/n47/9JcfUeDdU/7ZsZBVx5E27QszVz5vaVfhNYNG4g5DG8JpzkfOUlVhaAJTwn7F880VLj4YPjPaLFhH9whPM+gBC0TMAYA0YTkcLZJ8wuNln0ndO0SChWb4mScfavttMR0LtOCYVvp1POAGXbQWfJHScSwcTxXrGOgPmSjY/k1o7bbN2pBmpANcfo47N7wanyNeZeBCgME/0JDQJR3rZ3jZW1aHG/FyN2IWkbA0GodxPh43ZOS3x7yn/Vf4je27OS/dPB+83z4Ev7/tdKT7P5/vIlHWKbLaOW+6vUb8Xr7XPTz9LYbjFA/duVgJ34HeCb8l6CH/aw3oKqX+szquTn79tVHo51K3c7zfB0fFLmojgAmXSpOLgXt6hGNQ6kSMuofMD+CzWBbF2PsQ9GZpnGMG/m6DfWoDl4MY/y8DsixoOEClWYYbN6IXCSL2MmDBCB10UFWs7iBL51M6n7AGOQCQ6xXV0Ncpcn324HwnwC/6Bctvv2J8/ID2m8sJvxXYvbLdCfABMxqlfoG8NzwKHSK494CP5plTu57yhft8P4fmtEriZXBWKh7twfPZGk3BAL6faXSkQeylGasqHmigJJ+9xZvK7LAbmojEgbK9UL/s0vjXt+2zlYXaaxPNLxZzmeBV+8renuU25GDLJEPH4uo4q9irdWlo6QWHHG7BM6PfsoVApvCXelO5IfjenWaZhARXAO42UExJJB1T6CCxNZ6/pk382fciQX8+nFG4h2u/lYQiZbvqbF7vCBRX+DKQ7hLRS96t9JTZtG/Rgu9ufzWD/Re0ZCHnwU3G86LP+Nn+vdtPA/r/UKvE+Rs04bubCToUmNwAroDIwFCBqZjNQKbScDgejai1hoaG4+GI5664f34yoWUo+lgtDSqxpbfWgEVNQb+uRuSapgdcnQwVaYOpKynIAaBn8S6cClOXXpv13iSsImac/f9++w33f3wKQ/bjf/+B/4QJ1l+cX77W5GkYISCwlOW3Puabfdx/tpFA8v/vJREkYPU52VxvAA6/L2jtdzz//Y/4vUYpbluNKs/U88mgMQ29AHjv2Rtv9zqqtFztHpeZAk405FP5YY/lCzi3WxgT884Z++oAkFHz7sTh5+SKnpm+t99BcCuKa335tJysw4/S7nE6j2AWVD1C3vdo7MmiUIApAxsEF8JqdnVAVZpBgbfiEpbbYevsUW9jHbk1hLs0ZinM+WWKZi61gBSZZj6jVs1K9Vpm59t3BSCgEE/vbNFFAngNTg3nnW0LYWOjyDld/Y3oseUVua+WxS/bDU/PT6ZUa4fyqEV42fNau4uItyk98UZxsWVQ6/OpKNmbZ2Fo48KcBhcxHgqFoXoKYVCRCkczpjKiuIxLmVIRFj3gBuJ6PQ1BnsIc8NTNguPxCADo6wpArYYkGlZdIaOFpFqNQGS6xQER1EA5b4FV8BtZmYqC0kZwNBzeoU+KdlxcWFCvM6t4fn4C1GrBo8CDcBMeEgFUGi6Oi0UEwKInW2sYo0E9kJLKqdVhfEAqNjjAsdL4An9HFSwOUF1z9CGMqKfdszWA2vkgHRwKXBwXfP74sdSYduc2dDxHxO0mmpY6Ce4bMvCbXZbKpPn8UKgKc4VvSsKCfSOecriyFjzPhysUtPA9olRmDAwZWGBnKujHcKwnxEezAinPdH5YR0+FaZmL7beWSkoNDHmifM0zkueMZ4rnyhSNRQFQEZEgn9sQi4i68lIC4hl+WhOINjQMjxRuEE87O1pzW6fVLRYM54fUle4VBhU32Mfhzo/rutpeagt6s3SP2hl9n+dBkAa2gKwSitzratF5fLnM9yrSmF8jzUN5X76PYTWs7e+aqd9LhEXqOW2cva8RgX4OlwbOloKjfQ4jeNBCh2Pc+fs5upY4tuxzYI5YBEDusp44YI5gHig1zit8NWLCAv7VeBKjdF410+tp7PEwcJTaG4qKm+xvk4VIwnB2y3Oqo7jcmdbcx5JZTLbc6vF4NFztjjKht5bcZ4ExCq+95TeqkWc4zJsr7hhFUVfRT0Xhxdv8Al+E2M+Fj+iKWAfKZ0wvv4hg9bH2YVlXWMLgeQwcDguenh6xtJbOT1w4enb5/E8dkPxMMMuXWeQxxupK24ahHc99eGQc6bWN8/npYaL5ynk5zEfveH5egxY1T8tMZbIdX49WGQPavPwBmmecUeiD08gKRxFYResRu9KipEjvjZapynwuSDQc3gtyrAIPtiSibF5ybLV99OTdLMhsOva3bIA4EOq0VAF3GohxbAwGkqxlxQjJb5X7tzwaNr9hc/0l+Wy++9uNqeB5Kh421y/1hPW03v2HtxA8gEdC8c7PBsffYRcPPu6sDFo/28wCv3ITAVghOEhGVDbEUuPAsQnw6G98A1vDGlMYuSQ031mL0cFxm73xHeysDLQGo4zaozwLtIO1haUJtHe0Jnh6foKI4Hhx4RHlPi93aIvIZc55DCzHQ2Rg4gXxz+ohq5aBQ9HXNelIKK7pEGN9cw0I1a4dfbVyC+PrAOTR7ilKbWagu58wo6+v1u/VYL6DX4OfVn93CWgUwYVH7B7xFqoPgJrjd9I5etm4M/nAVEaB0FM/O49O194qIPoGd7g3HiB2jo1pVJiT35r4uTIHze8pp3CydgpG93tbHZuSgNe3cxkm/u20yebbhC3i8zkDzLZd+jiO7z9ARPD5y6eptzOszfTWLU6aMkAUo1/QCK0GZglZSAk7rquSVzLGQtTjXIkT/ynNcc7216KfQUxBXG4sEHKZqDYjGWncTmmn8D2az7I0QZ4FRMkAALhtkkpFkcjWBtjaXOnA4W8u4Q5AZFh2UCjG4Qu+tsXqclPYggYPP2CZikDHU3Uesptj3aDcX4Z9m6/3jDjAomlY356CPZ3PKgA+fsLxP363e8QyOfE9n5vV2iarRb1djbYHyArZnvsqSRsVwNdmJZeaCJbFHDSY6W0yJmrtERPfc7ozEM+K7wU6iQR82ukz9Vxtt9B0X+EVORYgl/9eqT+yALNL2Bo8OJzeuI7tknNwOf7eN/GVv4M8LfdY1bNzvfcwVuAFScdH2z6Go74yQ1WhD6/jRMo7qnF9p92IO03sPReyGWWWSnW/9WL7ZxcTbQVY7/Pa35vBhdwbSRe6Kp4w81HUmTwW+lkdaQCg4R3uPn2yTKr+/MCt+wX4eIbnYtkb9Gba2+y3J4ydpDwRpeWEp4vGcwZ8SOxjHWccjICgD4b/RzjmS6wLeRp7z9bnIWg0ZptRbo96x5l5fW+rZ/NkXmcO7otXdu71CfyZqPGfxvP/ve2nAf2f0fZx/Pd3Ql6r9qFpLh9DTPk6NBiuJsByOGARr7ED4HEMHJrg4nDA89MKjI51zVSoAqAtYkYWbWgLoCtMITNOPQMnQ0wV9k7um2S/H2rXzgw+/f0T3v3td9y6gfkpvNIzGvtcE53rfr/2vcT/RMhnEgzBh3FiCK3XdscF4OJv/zH9tvz+K8Yfn14/0NJukLCoY64p6b/MVDHguz/Q/IFKzVlhPN9JWYTfo/TaDiGlKZivvtZZ+Xjrkeh3Ujxtg8n5BxGojfKN7V4H3obkXFLA8jH/276HciPr7zD6/By/UYWmNDSmUt4U4S0ECaB6gOaARMwAOLqEsuqvahwbJA0s3wWMl2AX114BYL/FeUUfRZjUTm4/QdVFSQSg1Jr9wbZZ1OAHN3s4zxUHbb80RtmRgZa5Q42TxD1AxQlSACyCajVwbMdhjPPL8LW0a0AbYlE2Y3gKXjjTbQai6M/HSoGVpvO9vX5C6gB74hkWtddMUdmkAVIMWJJRe9A8m+I17TjutXfLzuKdt2bpwrctohAoAEKK4XySz3yEC8RdrSg4Urms01/FYTk4/TbhbvFU8r13SxHWB3R0j9btZtzx8VMYFlRY6byXzi1frL9kuuQinEg8PBvOKi2ZYERByhG8lMjz5oAaAxCP2pIBaPMk8Zv68dMwyztno6Puoiuea1OeGEypZx06wggQ58BHv9/MoaGGJFevbuvjzLORftCZNoUZgYa685LV7BbtZvwZpqZSN2jRgWPE5Mk8+X6q0OLPY2Csng66K6R1NGlY1xV9XfPMOz3YOtEABd+Vd41w2jhlrKYINN03oAOevt2N5aP3iEKvCsraiLcsav00hbvdw5uRYws8r2Ek5TwCVEP3uot5nLtYFaknnIFuvvv9NHhowATFYOD3iO8LLXSmzIc8k2q+oZpV1JkArTCJa2XPisCL5EHUaEkqxTSjhci4+ftZkxiQsl90+m79Ge411TSrXSedOTGMlNbH6W9+85nf/S/LNcRLZoXN7IhVEKa/r7nhNgzeYk5zQwfG2j1FtAT+f3h4iGExWjq34QZHADup3pO+cF+LmgG4y0AnTkSmQ2b6daatHaWPinfXMcwRUOx8azea3FoaTxoWKAZEjlgwMNCg0gNHZyt8APflZDg7zapwIpvO3aDreQVEVcLtXt/peu/+ihL2e8tNEXum3nt+CGe5zfrbO6Dkjvrx9nhu33MsRLtnrt87f0i+t+scLR5N0rncv0JRZdtNBi5/6SPgyuga5Zf3kctjLfVIIYuEVyvnR8oZUzguKQBXVeAqHb6Yih3KDHwCaYo20gFVNQdnDj4Cpf5C7LfG5BqxdxXr0zOkmREx3+f8NIFUIEKeLggxb9LkW5jFRo1AWimeuxWQx6mmOAdHHo+kbU9WOdkiW1mF9EXr+ytY646+D/k8xumdTEZEx3vbMaiXTpC4z2fOMRSIcQwsjcL7Sf+2hvN5iqTlpcd6X7k0c3czxRboPP28kL9P3eaXPTT3qkZaRHlivnTukfi7vZ9nVKe/VQKc8WHyRzxrpT9RM/ps01sXo81fHlH4ne2ErJAnKvzJ3r15f9LBMDY5AtJYHGcP/K9qOicqrB46A0JSrSEWQT6S3x9iOI8ypqoZieG0+P6weJplpkSG88cd6/BScaruOK3OVzPafKQDipzuDY6V5+xcBsi9JrCI89ZY5sH40yYt+BF7fh/Otd23lFIKynQQVR3EZoDnZIwzEcqnxi4JnoVreeu45pxh7OxYNuM4idr1s1wzlEOBe58nx/sA4I3aXxrY+Xyd44TZ/sRxewmfnJ+htcqv+g8xoHOR6Px+69c/6Cves8NDlosvfX3hx7wkMUYpt9v7Om5PgwB32j1MJ/sgucYD91NJhIYr9Kk4yf6Z/Fab4C7z74GvfGLNS4IFXy/BnRSCcLraWy6/OuBp4JfCB8Q8KuXkyeLr9JufpwH8mVaJr+xd+Oe2c8bzf5SJ4mf7n20/Dej/4m3L01OQAoATZa0mcqPQw/Rg+b+6px8N6M4Qu8Dz9mLB/b0pNMlAp7KsWYpubdA2rJ8u6Gigb1xEckGK0JGjSvW7M/RVIN6d/z6Jf6/GBN36a/5LFP/v3z9iAdDxCz7hM65H6EYypbg/vzV2j9dwEjuNSSJrfxtZa2ovXdu7d4wS7SeuSPj9VzT9jOePemr0Pmk6vbASuhsxOLIO+pe60bzdAl4jeG98mWY2iPMcEjILxGJGfAD4oJIOC8FwCW7UotTv4oLiilof7/VK588m/NZJljnTy/SHpVwK6TmtLShUFfdiY/Gqtkh2gWNVT2P6fQN5UotEb3LlvX6Ns90APItVqDwMh5HoNL6leRQGktm1aGKvXlyEREvD5hHLepaV3Uw+4VK/6wbsJqmXC/lWY/hehIiCxq00KGz7L/eqQrVNv1IN3cPhx3p4++YtAODx2VKVaijSybzObwhl9cR1lo8xzY0EBYTy4eT5zefgdYFJQBOUjAF+AzMMEK+uYwUN5Aqrn93QcDjOpJ4MnUXOzbCq77UhuWAjNNgjasMvy8GOZrfsBoOR0L6mPYzVdRYaZIHQ4frwe3hG+xhGWfGKQw1DDItUwwGPzxazdHxj4+pjmI1o8ZSZHm4YY/L0hE+Pq5U1OQwMXSwK2gVe87rPAamq1zZVNG1oMsBydYR7uM/oAYCgO1zEtatUsl5fv49omcWN9zTccKd//PgRCo2ad6vX3O2qFtIcdYsFaPsUM3yRN6jcjGHcb8XwFOdXdzAXhazsXUHjvlHCtjA9Mhc6JhRVIhd4iZg2MDogo2FZgDYaRjM+pY9e9opGtEUNHuB+CC4jlMR+PeZSHjIkGoY6o68KZbrKAEEq8jn3Sq8CGxV8d1axqBqlPdAyTXNrw/aACJZm8X+jwYzoDW5QhSnlaKxiqRRsojQIE24/KDCAoR0YgiFMlz5mYa4YDdnv1sBJx6fe1zT87TgMVOW6Gc/nOu3cb4w4Z/rJztrqXL+Yi/ggNeq7zi8ssAfT+dsC2mcNNsj20ijjUNR06IP3hlJep9fM1AduPGedZZpWjZa6nSLGNkQhkrBQPReFnjAMx0RusSgkmQMazneJw9QHEEaMhCFwPC6GozoiYlogWXMy1qgxZ5Xd0wToAmjzygumSCVPQWXOGAOiJisAXqXBIXBqaKmYfIZwhcGhHaAySvrL07U3Mk0FuNM/BWRpkaKdSGzaPg5bJW1zHE5CPIbVGm1xzkw51btlj1hac0M219nhQbmpwMfebSlb+7oWXiT5tLrrFEqpKjabJX9QWCkFDQe1JIgaTm52rnr0OzyV/lDDKwYPqyNtaa+PkNat/nGhvxXmGdBp9B1vLzG+fp3OqwKBSzodRaKmpBBKUJjU2Mr4u5//pXkUmxjtOTjVWKf1PtkGBAEufH/R2NHKtdq66s4uLDTEW6I5nXbyGUz/ouL9pXaOdlzAZIFz93+FKeS3cLlyGnUPFAIueHQm800Zq5S9w9tr2SktMDgdn1p0ZFuINSB5mACYkf0CyQo4JcMCmYz2bfNZADR9i+RiBIfr5s4jjlP9KtNNw8/r0AFdFcvhYP0Mg9H6nHxyTEkstTi08tl+fcP3B/4jTyUZlSYiiXOAUp/Zy995pLyIYl1N17LedqjlCPC18DOkkgbOujKbtSANsV+4f9PIhqoMV4TTF8kco8/EnfbutvuXD5bX5l7Neyk/kY6ztvadAsDDdK4UyIwwkt0bqp77yf6Ls5D6bDf8wISzNGl/Xi3z2KSgnbd24VkCH857X7ePfKO9LQ8IFM9fPkOQBrT7M2jj3Dv4uwUuk+GR6ZqhQnd+Jix4v88ppKpYBD7M32rmD6M7dZ+RZwv+DTP+/D4oZdsuC3EL5QqNs+f3O6JPJ7/co8qOyO+CdMqd5iCGIJjMC3ZG47xN4gPnp7jlmYoBK9AdDy0N4jrXGxG8Gx1DWMYO0L6iq+K9Yjp3VuMcWNWM510Hei9Opj4KRsDnyTf8Vl3qoLOO0IY4O23MWD/bxa8fcDwc3Pk9sxM2L7/1wTsYYnXNt2iD360mczs5P1anObMeRNma2k/ghXqK9cTxddvmQK5sdN6qjpKxF7bPkQ93De+ZofkLnf9W0j4gFAjlMHLvPBD3KdzcWnCeP8rV3upDtmiC36mHJv3q/syd9/PO6ZAWmey1J/Oc00z9/Rw+/CKm133P9/mNXc+XIT2ZnH+Rk99O3+lUFO/jZJBnSy0A71n0Gs9yhwdRHBxub/2my+v3EBH8/cvnqf8Gk8Ef1Z0HvTc7d3eWnQIIfFqzQfyZNhvPJQy0DZS37JxlKT7agDCVFT3d486zwHSknaXVQHm6ynIGT0jJgDDxGKfn5x/Wzh2IF9r3LMNZBxt8+9xwbV5jPP8rIt1/tv/59tOA/i/UTnCBJLGR8p1C1UyuyBDZ9wGN+npdFTIG4N6PAFLBM2AKWhp6POWvdhcAZQCLp8htrkjXAdUFfVSmw4fiBJqTCDQ+c5g/CJm5vdc57fhDkMjPkaIcSIGcf1+KFH9NCyag9FNr6+zKYjvf6/NbUaOyfvyuzpgt0jDwCxosZT3n+q0IesGcOv1as/Z7Hct2bOf6AjLj4nbkRRcbimIocAWJ9FFXhXkyJUEyGzXKgczHlR+GOi5+ZjT6SdtyvN/Z9iIbzzEFt6L49cMHrJ9vQiQNwc3bpX5fLfQLWIqgvYmcjILK47h7n8xXz9k0nmWzKPTvGOQrG/FTvr+8WExJ8cNnM8DjzKDqST8Zy8X7kPd9jySxbWUqf47/Sa9S1ZDzywuKsSxu4LMaz5NYVEY50jyFkiUZvNNh2AC2RnTO1YwE8WXeZb6OVNY0ES8n4uvC2xQeKSkQqcI8nT08mhxVGXCecTVZevV04Gb4WJqlYmfUpcBrYUoqXsKwDIUOwdoHlrYkXWstjFKkYRqfvU7t5IAwKyaAJ0BSeFMtabJDeadozVIphzHTc6B++vQptuYYbkAeK7oOqBUqtFq/yrrnNhfOqv7PvZ6RYRnNsAfVZPipfNKC1+2wKksoO/8Q9ZFxcOkq1ekBId+6vQEYPc6uNIV0AAuwqCGHUowAACAASURBVABjeApXh/uMLs7SWd4Qe0VRBEqb1VCE4ZbCjUXNJipRkI8ieuAq+jWlIV9mI1pBqnyutUwQCQGaKJrnQaMyXdDMSFhqoTMSfbRmPBz7TlRf5nx6lunwk45dNr621n14ajw3sJV9D4BR06sb/87huvqcjh4wIN5fGp1wfAf2kbXPQxFrz8xCp/Gpo9ZD3C6+G5KtdAVRXdl/EuHi5Vedugov/A1hDIX9yXwR4643C+jo4GkttWMw7aea00QqsjIinRbegAdSkbY31vhbFYyqiOSPkimAHQhmMIdE1LnBeF5QktPhOEJHriHpUryXxIqGGBEwIpX3b53RCCMAeHx6BJWJ28a16L27g8lp26rF+N7MICLxb5JQGgzLPtPca4wgY3TH0po7cBg+ObQF2sypOPaSzCOpdJGtr+uJEwgdfiqESGeYdcK2xvAMEICObga/KLWFaQ+wDBf3bBjPxdJVqwgIztOjLPNHnfmFUtzD13tOkYrNejDzRxgdd5tggYbSdxRen3/NQfrbbYWdMYXiAMm+Cvs0t/lczZeS7vuJemEO+LNM4Om7AXfYA/ZxksHqHkg+1Md3khqb2lDP8vJYOhERXDqNf4CnnfVn38DvxR7sMGMmTXPDCXrGFsZlfEjHiqGKJxG85TMlz/5ynWWogMQ5igFVlmvhjnf8qxyReY5YNQbxlMMBtEB6fbMfWMJIRtLw4G1EwqkolcgII5/xLorRLV9QlqVxB53bDjrEEHfafDySTJyVKmfP5s3pO72q9Np/q+VSwuinGimdg6NJ5uV0cTerpTrvw93P9bfB3+e9qNHfzDNv+zi350+/7J/f0yltcBvh8kI73ck/3ohD7sTK2f2ZfgDKMTzzeZq4x2beH16CqSj2ZR9ue3uBNEmhkeaX5+AbICzd/jn8mLpEnu0SCcyj7OdiypCj9QwhaPXM+zZzQh6RZ6bQIIk9i5j35vyJZI1nTw+ttOqrp2OXAYGlyG+wUiMqLINYhquZObQzS9PYcoJxu//1nboRjgKbFaPzi8vlsBmfbjD+41eINCwCrC7niVgE/TPMOPr+pb4IvZ2NtrcXKv+tmKOcY46V396wHKd9+nrBAlzudlK351mQ+tQGB+XeUTAryjlqVjmXF7iFM4uQKPAFvuQH2/ecvjryk7Uouqi9SHRe84cdEvPeFbge+lUDfZHr2jxSx3361DZkpGO7jixD09D7Ol0jL2byHfBGNUrqUNNzLi9l7iLd/nB6b+HL2EJn5Y6CbfO5wcohSKTaoSF/pO6vtcB7qS9WRw+Wtar3gTFWz4IxTvCNPSPxHK8P1/n8M9tfyH2fbdMMz9Czl4znJ1kdfrZ/y/bTgP7v2ELRsqcNIHtevNF0hMDY1xXravXBlmY1Z8msLSJ4c3GArkfc3Td0Tye6LAsOy2KpDGFIUlStbh6cYdQ0RITBQbxWhsnU8TnF5BeoB+apbRHOjbiy269/UEdORFDksZ1na07Ao+6ef6/qtevxujTu1ei8bTPb9O1GCGwVCxUyzkbGynLOh99/xfMfn06MTHvtV2W6dhPc+E4B/PvMekyp2zejq3Nr5bfaS+E3cz/AjMzQhPPVMIZ2FnZKc1gvXS0Aqr7jzFwnY7r6xLdM8xbgr23bZzbdfvryBX/7/TczMny5RaixXeBrMIbrkRHO+91supc4N03eQnEfnn8XfseTGxUuHKVn74WRHIA0QR+rK6KrI848OReTdiZ8pp1yV/P8HAgKQXfjJmLf5Z6eRZQtHLKvXdlJywc//1m7uwpCCIMaDc7H5QAFsK7Pplh2ZyHtL7DCE9olfprv2goTilMBj4J53OPzULghsYjMrGlr8NuuEoFCz1SLam5ersPmmp6re7uOCpG2iUrfjrm1xdZhEM4CoOHi4g2aAA8PD5AGjO5jgQTOtZGO3d3FJRwY0zqfaASQe4V4XAEMNSVlf4JF2x4VGAJ54+Pw2qimwzRDfXPlq4hg9O5CiM1DPRITgKVOnzZ20s4+FgztkKjT4GIb65r77URD1x9+QX96jpqZy+Hg0VP0HvYFFBLQDRhG4tgw+PhO4nrnAxJwEiDqgIXwoxnRreXuKmDZduH+aZHuW8Tr3vkweW6G17/OM47Y/9FoDBJLWdy0obcVYIV5WdxIXWsJm+LkmfXgVRFGsoBHbhzDmQUH1terRcBLU8eNDejNa6rG8fK9RWWkG9DEhWUWA9ucc2wUDXQ0o7PItpl+efi6CGRsItEx0L0munXZdvuZO+VYMKMrUfRi3ORfOu/EeEBOEqhG3rX3kvp27qc6nO0bxAFdSp8j65KzZvqk6K/zEYH29QT31wnTPjS8lIMInT7cUSfSb+bweX6CClIZakOIK1TKBmj9KdGsQTkPSmMvAED3KIDhzqkDA727UtWVq6osuWQwHW54YFc16CbeGfQu1yDWRBL/ttbMeCOeqjxwYXODimJxB9veu59jjXT7GSVUzqTjQeILc9CVchZ93YZOe8QPwzyhnSYARu/Qk+jz+Tl1eBEL5gpFL6DCq4EV5r1MAp8HKS0NV24mVje/ihnTe189knQgy6IknlPMdH9SQiqNWnnGJME1zc7o2YAMW6dcix64a3SP8oz9lwedESX13UDHcEed5XDwMzeg3deWjtOefQzEcTEZwaQwfajVuB0KrAUv+RuQKbbDZCmwuvb+bPPze4BHWysixa20o+3jdTV5R03puSWLcYbLzFf/fJhWKJ+cYEQ4Bf0AAqnUF+DM9+1lmY3Pp/ef8mDbFvXPnaBWHjNwE2w9GMlKev61ZOtiFHTMuZRK4Vge/Cxf+p2XMOXwI06bquJSLZ3pPexcvdOSlU2BRw+du4ThskffPxflvQrFUlXaanL6WzWHR2fVcPHhgPXGHLLEUwqPbnzbYfG5xUFyg/dkFEmFLxeiu2J5OF5LOBlvGCOk89qG1hPXrD0N4FCNSGkawWiwjh3oYxAA7Z2g397Huzg2ngcVMbgBkChlpjFfowtJUylDDLX00hiXkHeCcTdwo7fx7tyMXLHkBdje+N96ymOZnDbNhrE8O7NRtRq8dFoL1TEFac5Gq/q+zft3Dt+5Y8pfUt6l89fOxOKOer7O9ft97X7Da7BvRp6/1fNR6LVtjSocG+WsWF4hP+POvqHBd3op57VHEe1Y+GkazrtnwSKvZduOdKg6JPw5iNX9Y3+4UQan4f84TdpyCaRV0YPrLJEG8ro3kr9OeEJnPrnV/so8Y7+rWiYriFcSGxgiuILpPoZ0m4cMPI8V+Kz4fFA0Gaw85k44uT8pv88j5lvrb/XfnMt7TSPlltc4167UnZz//gnHv/3m9bQVwBeo/g5pguNvv+GXTysgd3iHF4JDHL0k/pv3hZXOqeENLjfMNXdOz/yWeHN7h9zquNz52xv3kGb0Oci7TXTidNdWziHu2SKkaSh5jXupyi28+lbrWuu0n4DY2tMz2+krMhDpym/iib73d7MEpoDqUM9K9Iq5bNteJLrGRMu8/YLA9fNQdKc9TZ31J78gBrNItT9NuHDQ54yV/ve9alY38/uDwxPziW2km4AHI/q+9XW4BHDvHdx92S+XWmWsJxG8VcUCWHYJANAfj0A6pwufI8/p/JxnRwAsRXZB2VPDYbEUnD7RNJ/7GAN97RaFTtmgZtNx+ELkdD9qBhTQKS7G7v98xzb7dtvZCq/Ba3/2la/Fn/lM8tk/I8z/d7X/ew3o33sK/pEtMNlLBDlvFUlBIPVreyKDgoLLUAXWFQJgdQWQaoNKw+L3dh0YfcHxcACkoTUzpCz+/2FZ3FPLjOdULogLetUYpxulwym5fT0mPcMjhYIeyOjyG0HUWyGzANSlFjTNKAeOWGGelOe2RB1DNZ5/axav2WIcR42uIHPToOh/fIKKYPm9AfIhGE1VxeG3X/D88fOJR912cJ+bpU2v+Pu2rM/WgH43wWI+LNs53QgZ/M3VIvwEW7gRiIRUdaNkTYEpxF0sCnx2hcy1zt6Ip2LD3LZXvuf4686nvcYR/f3TR/w/v/2G8duvePr4KfYakOu87a6CRf1GgfM/uIPganf823nM8obk37rWIYQSxiVSS+ERAzh/TOXM79vXvnTtZODf6LO272HCigFj/7IB7CQKgte+NYYfoCFnnUXY34n0JrtzPlXqpJCfEed73+3e+Cx0YNl/w+5QBYh4ZgFSye5VLqmAaJ6OfQjQWD/OT6tJMCFkGdKm0m32pOd2rXRO443lrIjhCqvmuljtZxEsDbD0wwKmhW2Oc+CZVEzrCOhiRrFlOYC5bgWCZ1Wv0znQYRHEDQ0yxJQiyGhim7zgYjlARPD8/JxwFMFYO2Qxoed4cfTjUISb1vD58yebJYUVV2AQH9Y9wLWszhjTHgsFGNwwN6CePpqw22YcaNIm24n6gpjg1ia7Ap9Kc4h4lCU3QsH9ftaaKHobaNosq03zqGx0CBqGeAq6LGMKCLA0oKugDRrCcj+EwsThIFSY4GSwJljqsHcqLJJzKUqwEilm+2/s2vvSUB4ARkT7Eb62yQw+boHX1jwlpsT42zDnjoGBNswArKKWqd/Tq5rTR65X6qU3nJIiFJu2vd08qClABxUOxhJEftF3KkQpZHeLbJe8bzKOahrNt0Z0EcUwt017zZjvn4znusEFgBkmyl62d6YCWACgef0395rk1Kb+pTgLYH5HAlUDjvV90y1I552t0oC7MQyGCmjvkfbdDOk9UtczMp2wtuwBBQbTuvDvNp09sYOdbaY0rv6EgFraTGQKzRitr+lMFxUWk5mKFC0wFdPiRB8VPwUkJgZVHB9odlKn4GvEHnVzbV6NDQaKr9xhpbxU6YWySpMFGG6KFfKjiAwgwReoBo5dlgVj9JAxSDuMnLlRDAgDnELR154y2zSWs1MJXD9ABw13tFDbO91LcrEOavSlikKCcp86jmvLgA6xGtGSkYTKaPWRDiQnTGZVkIrAXDgfjJY6/VWFp9LPLBBVn2hUYZfR2axSvq+uO2WNBRLG8W1LVCxTP/MdM4DqHSzRcjHfPY1tS/vmhUz6/DoW8eW78rzz/TMeKDfG+BRI+s3IQSRcePspf6cxvwY1JT92jKiOI2hEV1E8QCNqHJiN/Zditdxlc+YVVu7FaL5MsqzteqN9Ywy068UisnVEmuZx2zE++FqrcyEiwNbY7DTYfko+dYIvDDfbEHvOxPFmo+OqM07qRDYzZ/kZ8oXXrlHuaD7/hku7DvSvfdo5bDUqcpJ2g6XyeVXae6aNOwXeAXpTcXptSSgf7eUAbL2+1fYM0Xt8ut8c87f9MdP56Zny4CmFqKctIT+hKzmDWqXwiDq/s9737Zn/QNvwCIXLmL6fPLb5HnQHOD3AkyGQGdb83dwy8AxEhY+snVPpTz7fhu5nZONMRx4T9bfNWMs/3wXXb95baqJpQWYTJq6/+/ynfmmY4pwhUBlhxKNak4FCW9KVPAKCj4jsXCh7SoHR3XnV0+09/71jLF8wtEHHgtbsXGRNc8c/4plBUfeK8wd6epq3lGiiy7y+YwTjWK/U67oLcA3gyGcUULwPFLgsDfLbEevn95CTOOIJmzktJl3cp3cTLuG+IvwLzav37UXqbt8x1HW+Ot83R4kmzt3CcRrfmWvTfZy9EOZSrrz8XP2W9H7vyS3m8Bd+J+YiNThxEtgMuX6dI9HzwrQGVVj2e794Z9eOL6J7ZaBR5M2CYanva2dUZYHTaplAwOqVl1EAQBRSUZxC8xx0DwCWd1d4/noX15nlle11O6fcIglawyPUDWWadqZsb0vLCHTibC3OGbC1GcuC5mfHHF0lcHgfij48An10rCF/5lrVEQVuAVJ+8Fvp0Bd8ICZU/e25/0grNOZ/rO3g0O31/JhOOj8jz/93tP9LDeh7h2xP1JUzn3+8nSrZpovYxR46f1BJxBe/OrPjN8R93d95oIJnWApOi0Bvpo2WZsrorngYT+hrx4c3R9w/N2gDDs0i0A/LAh2KFcOQr0ca5KjVDRTiKccQ9QaFHGYR/ZLaudEBrSCW6i2OiVirPxoERoDVP1+riUYX+BX/P3tfuh3HraT5BZBFSiJFLXbP+z/enNOWRHGRRFYCMT9iBTKLpGzfO93Xgo/FqqxMJJZA7AsArPwF0rN8ryDgA+Hblz9UQYDBwJkSE2IkAWObCfvL2KNty0Robgygfb42fhz9C6PgK+rvHwG2KNlwBniqHjqBdqPrL5U/9ShLJYz53r2xve9vAbpDxRUucRPG+GEfgFtTrDEnY0ywtneWxngrcun4ZEeuzerM8dzFZEQ3pv/e+0xth8+c6fnOU5vHN78bfGp/BhffPl/j1cf3WN5foV/f6K3x0u7QtYdjTFDAKOwDsGRBtmLHiYk9NlH6VLEYaiRxRGEKgyq4o5Tq58d4JDeyAFGv18byLDv5PPPO3AN3efrudM5jpdL39Ab9wUuT8XhfbL18sPp/2Xs7M+qPx0ddJ6kFutRIAf6S5nW4aPizvU//zrUVBQVKtIuNy+e604OlsDUh0lIVS/1Wc0IRZq1Q1IhE1VS9LO+rtWrUOLlw4eOZ6Y0JRjTDK3xDzNhTIOfdSoWs66pGBTOOqvG2m9kpYUClG7lZqdYM5t0h1PBWrJ98TqJXJU2fLdfbcdXoc0JXx7BidErrABMDKzcUVFSyKRKWZUFrzcqOg6kp/m1gVoMKF1eeViIclgVEBW/eXKhxX5hoiZySvovW0a21iPHPjOcs+9q5waK9TdHTiSKpBo3nJEdc29oatjGFL8OiIL2KleCvXAfYBTjyORm+8PpxJSmdeErhq2n4rXM7c3ahcUftJLWhUVB6wUpdPLlTdKfhqjy3QuFN3hWf2bB9ncFgpmF9BBuaIofATbziixmUO9CJUYrVlZRUx+u6Oqx2BirF6o44MuY374IjWeN/WFm1WcHHDKix3NLAWp3AMWNI2n/jrQyV6jk3hZ7XjEzwjPQnjXL4llV2EXGmGSe0n3Gett6sxu7iAjg5slZ3LfZ/nm+Jb56jwN0BjHXPJEM1zMAzGJDdCCxAIY4iBjPTu4wm+rkhWEcD7+0t4L/ofR5lofvMWpvcUnN2XxI9l7FE2l9a1521IuPcfFw6KqPdOlVL85fhMuOJZZHI8d5bKLGUjvAOLbSItqUu7pwBZjA1oFaADL+pETkPXz+v6xFLXeKiwtf52Rl+/JCY1/PzM7S1g1sH0b46jbHFeVYT3dLODxyF/iZ1vwW3LLrHZkw2ummlFyzletCh5IDmfeYRqHGOzbg97106V8MlTv/LuprtWSLHV6x2XaMAcwQgudJSMgtUqgDxAK+NAcvk0ZRHYu7oD9Jn4zAIJhLjz7uSlBnAw3YmHKm0JeMXeb4Zc2RynsLPqDx6NFxOhssU52oGASoCL53bbg3Uc6VVjzYWIjXmiyy8AONht3VhlijvSQn/CIkAdzyffs64f9xe9n4yrzIs5O5z++3x+VvwGgi8CpmPRXtHhoSXN4s4f6206scu/IrhPL4bxQg889oi4DW0UqLxWdc1nG2E4qnTI+C/hNhHaPcdr94fcFyPOh+t+/lW8kgUxeUgkux54t6ovQkEUi/qzMMwaU1gGnFOFU/LwG1+opxeW8NyqG7AsXNXkjJa+CWZv5RQCNrOvkb2byibYzDx4m8AXg2Rw2EE9Wb8jeGb1H8Do9N3qbf7rePt5SWYGTd3k7FL120v0twGFv8lvmACi5kusl3L9HtY2NngKpObqd0e7FrJr/y+oFQ8/Z1dK7dHjxB7MreTxzQLcs+1Sff32snGJawY4beXHlI/0ITNYk3DY9bSVT0iBN3VVeVvyxDppEzhORG52EtgoDuOQxN8bMaKcQ+fQ3uzXJ/7Elyxozk5tXbOCG2G5LjRJSs/ZkWM6OmBWLWgH10XzLIB2XKQlhJiAt4w4QDG4d1HrNcN9F4zyDFw5E+444qyQsup1GEeJh8C4uhrJdHG8xJ842amNC6LlU00kNkjR7YGbwDc6z2Pf3zG+X/9rhncOprqHizT2PKugr9K9sf8/h++9xE9uxtZziGrzI1Z9cqQCP75t3HWYweXINyBcWQ5WwMdNJnaeGMaFyvPw42QpkefzztPY08PE8WXbk7rdi4HodF4Efk8yF56xfADQzK0WDlMf9ewAiyR5wqHAHDr5zPeFSuY83tOnU643uVKjivTA3Evs2YNYlwxpz0zksW40r83JH17Wnca+xxYz9SuYPzWNAINgDB5X/QKoS9odC/yfLHStvqeEhH7DHga89EwjHAWJEL/3gf4lLN2CpGdbo6bdABqGkm8ePxXIEEhYTwXfZfpOGx/mbWgTWdwIdVXT0FvJHvQVLYwmcfwDUPkfk5GYwENNtENLcnc0N+sDaByClf/xDrt9/NU539Do90Tkl7PQHI600e2+OJX+49o/0ADejCDG+bBDDoc97m+krZI+68PZepwEEY3fxyZC7Nr6QVVWcQitJkC0zwlDZ03G3xvOKoymGsFUN1KURQJLqWgc8H5QnjkLlHoakB3RYb/p2NkSw2bhHUOA7WnRnImiYeJWarEaQX8G4+oPn4Z+mDcQ5gm82oXkZjQ8VUIAD6iX6+6r4SCd+h0DTDjLauRWYUJn4nXOJS33xLjHSPP3qMqCKNx1JiV2NotEDmRlt1AVre5IsuNX5BIuTSeV7//hrU1PH6+3jWiZ4Zxbmb4jrru5MJIJngbsYgIBVcAFSy4wgVucG+HhWQdg/1LHW1HBSDqso8nM61baNz993t0NaJngTuzPfCzgfgz82Sbz+MI9ke/1/IzKwHcRchYrgjHm9Gg8oaBb35S9tbFkA7SXpz6nuEh9+eArFEc+nvJ6VDDK9hSOmb85xycWdCQGW1b0PH32IkTK8askZShjDnJvJ9oOu0nfhw+DD/4sxRjzJEQ7Ab+50aAQRjI7WcYJlu5bLyeQdP2N3swzkbtvahzSte3up6RySXvt2DjKUnp/p0WpTp0R+3WQq7wI2WsqSuD6XUZ9TcYGNnaG2zGjyM7rsZ6G6fCbydJ1woCeD2ilwW8SEYVozBlMYcFS81Jugk2pi6Ga5Zat2SOCoXQ1o5eGOsqKUTFmBTR3CCNjEpST10qqBDWY0MhQj07oK8rXr1+hda7yHnqWXx9fe375lTPhqe7bQZkgQ1LR5j2R4WcMlzjwOWMMJTpOheDLwcLFQa0vyoeBqgW1VoynIfyKY6fnRG7Gr9Dje2d1DBWujvcdZLoaxQxwJLWmgdZKnQK4x4L3oi0iqrmKgxwCZpp54TLUE/VlRm0pQ/hbBQpl3tnhZGiThfdceyeTiXNWJTgbBkbTJFAvlbGc0i/AoMMi1LXQfYOUJEsCTAayz4+MyTDf+tKOwM3G58RbhXyr+8T6/4g6i1anxb1Z4aKzYR1bmCJsC9eP43QU/1x42GGpmecCOm3juHGpKztvrl6jgGHD+qEpqAsBnLS3/tAPArkPkPApDSVY0Fl/IlocF7gGDiCOCe6ZjiJWTL0kxlorfY5JKKrTzDm8yXlYhW3EhB8sq2VDNJwgg3Va3GOmwSn4waLG7wujjF9lffUUtGajaml222WiVdgAL2rkSpwCRk+jmUEQYzokv5Y7js/OwMDOD8/9xW1ydk5tPW2iKa4Tzpdm8Ql9yaOYl3qM8j+9+7lR3xc0Pt6B1OPVUpOQjO85nWduYzNiqaz81xzPkS+yHmDKrG6yHFdjdzMHU1TuYejUuB4GX+B1O+CRKsDrgSG4rem+KUpjBoMFiNfM158avzzXFxu0XPh59Vu0rMzHSlO1+3UkfImjquINkZ0+7ZA6qDLwEc+Z5iI8kXZSD3v5yMklfXePnszFODjDxz1sLkhDYB3Hs5jfUE7m+4n7Kfczn1nmqhiu+MDX3uIg4WPbxj+dnzMjPMOlGL8SPpNv/8wJAB24PoBSQUPgmetKRQvM57KznopYkghdHX4U0rXAa6Uoiw7JDk8Q0zxRXEnef03kzvkib4ZdcZVDYy+dpRD8flEddCSzPGGprvfQf6bnW8Zb7vrAL7rfsiLOil9VjD5kdjTweBB213IGYPAcbx8Cwlo93BeJPZzs5mbvWOYPokdT4GDBwzjOacuOH3Pv5PqjBKOH94YRo7N0Gw6zB6YMYDmLqJi5WV1zM45YzyG/6qWxmhD+0ZiZNl77Ru9fn9yTHouE+n1vokHR6ANjKT7yRjXwXiYrpUEb/ppRUeDEIqglvH7PMw9TPYcduPp7/Ab7fxm83HcRMO9w21sfCH5tWzk8COTHCbtZWrHDcMUQl8nkqC9h/C2MxZ+h1oW1A9V3vde9qdxw4///oGb0lEJnhYZ1L08lr2MrGYxhzNUpo2xMKOTyqyDuGB2/jDzS1u6BNyVSPt9Q4zfP7z3noMyqMN+KSiVcPb+o6R+vrlBctGYd2rajG1jiKGvF8vCNWWKMB7nJxXyb3hyUImN948Zt+wN37ld4x30s/HgsTsc4hCJM3jmVK2376S0L50h/+T0Ke7PNOSexr7yxOw5d+hKPcceTs8PzJ5CiOlchrVI85jxTJqLPXbFcP3OqWZ7eWG1zphxCdrBfy/hQnfmgzjbzZzp9DZfo4GHehkxIAAVr4WeK9f1DWJYP4m7t8dt/55Eu03fWhAFV6rK4ZLCXXRHco0GeGOjkW7MAswib9+MUzH5why8GcmAnunDQNftR7txODCIvcjXaNzKv4P2bhT8/+JGI5c746NfRvP//PYPNKBrm5gPw7V7NFmYKfxtB5PoFPI/zWgYw0aA1ktcE40I8SyUfNFnB2NlqTfXOoPxiNY7zpYF3BdQlWc6A31lFGZ8eHuBx8dHfPnxQwTSDlEAckchYOVAoMOyCOfmkbitszCIoEy20liTlxQIphzcRGIOyFujKDj25aYAbztwAYkge+AvHimmWXpBAB7wGQ0hNJ9/PKDiN3z79CnG4PPKTGC8e2BA9XNON0kYKjQNi1Omqz19ZwD1A6HiHY5fE9HIgwAAIABJREFUrsd3hQ5Q3qfEsJDVlK44fCCsX/jJSPRTLeq6c1oHfd/UFwM44gYdwL2O6WN/h7fMaHSLW2cBtVHU3LHNHLeTASZcMasfdqQtuBMONEPNMJJvCgCS0p21dvvEGu54zDlDZRJRdlCYBJG9N2+aPtsVfL4T47w3nC0HLMsV8O4W642ztVoT2b5bnC1pel0WIZiBb8y44Nd4pBtUJlS8BaOjl29gFkULsXiYH8FeYkGOT5HU1QRQKV5X1fEDQw2IPPA+h8MZjo+PKAw0rZMaBlITTGn4DrIoP0pMacZCek9R1QVHjjOCMIHEWyVznI3tWTqxDfFh4NG2uIoZYpACgYvAXGt97Ccx3nLdTnbURwRCzrZDOiuVBmZKkPhwnZRJrhbaqmfE6jzbCTAPWp9Dql1bQGJUJTF6mFI0T5rVWtg1/WupBYMBUImdReD7+dBm13ONdAbbBNBbi7WFGiBIxikRyWLcLJ3AlYDePV2dQWaY7swoamtlHbNHJnWy+k4WRawGK6z6fqDTEcfHgiOaBUei9QaigqUSuEvku6RkF1hgFver0lYclopDPQMRofUGJtbIywOO9Ci4uS+wWMHOXc4xN9zd3eGwHECVcDicYTlUT791OLxy2t2ZUTrj0/UnPw+2IcwAtx7ezyR4olKVd3YGk6QkLVrzvlRxehtS0jESXSXfz967w7Mbi4kE7xbZN6kLLwaZakqHZJhgUxRTcaUKkdAl9tTn7DyLOYCYswIaozWJDmOuqjyR9zFIsnGrwNj9tSHIZblNhqdp5iH0kaFOhF2yBTTlZ8oi50T2KxxHpBURKNUgDNYa74raem9eQ83Ow8A/+JkiP8/ZpaGxpIl0hZmvi+4PMxq0Trtf17ZKX7YPnuaVoDiWXFB1YzDCgNx7GELNBY3BGjlHqjhhxxdWm44FScO0Q46ZktHYoisYmQ4kpU2PyGuDy/QnwJOAwmbq13NABHCDK5ZE8lceRe/hDreTp7m7c6nNmsj5KFNgWgRvphdd50eFUGpJqyX0QE0+bn6JeQtttol16vEkA5ZTUvqT5yWmgNHRxgVhXxIde0Ca2aoZBRLQHZlnDA5lzxnGX/em2S3AKJXQj9qvovW2Gh0U4z6RBJYDEnEuERkRQWpnk7FCnC80plv5ViqR+wHMWI+rRFMR3KBb7eXZuAOrFa9UwmFWzr+kR5ZNFaMaSXQXRFHWm+5SW0EaZVKL1fbWtdM9FeIgMsuxrT4MAqHURctMAGgNvQk8dTVeO51Uow/XgqpOQga7w2Zi4glgNKBjFQu2rGkxg3F2uGChQ2rw7obXR5ZL1jlH1ULZHQFMYD2GclqNIb0QwAW1kKS3pzA1sZ/rbKyPTAqc56VOFOZuzS5Aa7kCg2nlzatF0ZMZzkKRbGSfIcZZAO7sZdOxs/egfxcWk+mRJ0ks1bWG4WalF9KRyR4YmwIDzz8FY+ifx5SXe38HLnT8nh/V/nne19RemfJfDcKPjk2kWf11SufGxph5K9sLarbGtp7y42v9PtS4ndboNRiFO7gpHUi8I0NklOZOPYxvTDgHYYHwcaHUNexudPM1GHcouMD99XeUiwK+F0lnuVz8DWDxZwMSXw3J2FAonGSIoUxE0aw/ypdQOGiYjsZ3TT+UpWgAQjRG4ssdv7I72zkApzPUuKPfdaehbOtpZBsdvQOrMCdprVlhhP1zh5S/MZ6bAXW2KnKuINGkjSsev38DCuMVimcV6A3K91ESZPLr4pxzs2wX3Z17zMDHiH/ss43TqKnTPphjUHeZYT4Vfut8Hfn6zsFgWb/NZU/JL/R+NOifOGDPtaeU5LNhf2pvjA2gOynQxkDFFTqJHgUs95iOJZy+EeN19JGDCCYyQPG3K59TcykCZnjxbYU1cyhV6Rju9Nc7zteO2hnfEgaxEgdpONvlOL1SeclOPGUdmnNeyJ803Hfi5emnShGxWWGfi2ehgpAv4S+4i0FJHR69NrA5semZ7gmGmAjv8BalLFh+Owg/rrStqtPXj0//ja8AqMt3qRZGANVI0cwMYpE5hymkBbaUzT2dswwfvios+JWpK89FO7BLCb7EcG41tb9/+YqFCctv7+UdDHDTsjTcsTbhF2pdUN5/lEyld3cg5WoFBXJ+k48vpzZ2TR93oJHShdCDjM45th7knWVeRfgDcbY+Vx7vjEgi8BUnd2OgqACNlARl/aT0GE5W03sUSVk6bEvMRSjSFwO9ddHXx+bFWjDj3uRY031TSBdvuvDtd9T9Xczp3bpqniq8EL4R4ULhobPImawOL0xmEJX1fK3yzh35LrmTCEFyY8jvCGesRBRdLjQhbEZLDFS27wQU8jJHzAx09uyxkmkACGNv8GXm7PLa5Kp06ge8p0O41/257CGV+SfuqlcAShWd1NpE3jo/HHx/hD7JMyL3h4OM6cGYgRXf8K1Idp17/d2N57tIT0escJSd9Ixmdgtc1HJkDpO6/oVEXjosi+p8BMdovlHlAQlcFi8hQAVYakWtB5FjFWZ7b+De0Rr7+nUiaMFC5W+UBijsxL/5LEbtddfF2DJ0ntgLBnM6ZwP6fgJ//4vbpgyEfjf9zlYsSDIwzAlDr5iOy/id1LcHf/wysv+vbv9cAzowHNpTjJ/ZH3j70196rSnAnmx7wjmyoOL0PQ0+PcRmhBAFbGdJ40Eru1tRYaiAWWFCkhimJZUiff/hTLYrBZHeRdggPDLkqMwqmNSwR0FjnRkKpm9kCti7F8VnLEDcEYZAGB8E2zOZe2eLxJM2sqKAGXVs5JcsaceDbYoZz+xf/s4Alg8f0L58gbJPidcIU3xE4ksbzXAA8B7M11jeizE8v9J2l/s1qH5Q4td9NIflI+hjw1HTvv9ss2j0S4TQZS3zTQBwTRje0cI3HRcszLfN0wwJA2M6te/KrL9TYeQuc0UbLmT/u62PRLMnYSIdYjYmDkYc00S0Xi7nd/B2359qecgPN3c4fPwIqgcs9B6dvmoEkNx3wYT7EhDGgMN51ClmHPFNx/E6TgvHKO3ULBAjelzRfBE8jEx+Z5WfwciCDYNxXI+wNDSFuzoF8OSBiOTRaN/jV6ttm5fNGEBSAyKAZDD6V7WXYG4GJ4Dn4dNPDs4W9ifHwcZEp9v2zotjpGR4B7IRLQTS+A0jadB9BwUtEobPzkI+fDS8dyMP2P0Gj46mOf1lMTwwu1CZmWlS/G19m0HcBWFg7MvHMSqo3DkDHMPyNWLFypqKq3dQYTSWnB+S9rmAC4HUtwMrg6vFFUi9XIle7J6iXuqhH9FMAQmZHANYuXvaLPESrii16vhskwU5Mhif//gkMFAKuLdh9z1doj5TVTkAEsGnsBBzM+ZW9UqmPUeHWJSI3k+NKcCYQJC6ueGlH5HnNNbh9QBRcr2cbIKaDW0vSRxpuho6ARUYiYFe0EtD6VIPlcSLByirrAsIljTAjgrDvKUp+ueiJU6gwrLwPK1H7WmiooozaLRuHBJfewe2zIyFgMhgFFbjp2YeEMcDc0iwqD7po4gngBvLQCSRagoHIZDBFdSe8jDtlejD5BmBreLGXR8/hYJHtlGVUJ75IbgT8gxGHVZNjTVa2n6XY84aMc0jj5DWw8cskDusnMGJnd25ixHfBT7y2pOlWUCt40xjtmQ6AoQWoWt8rmcFUuWk7XAnB1GdZ6b++gIGmBilV4nKdb6BwSyOIgwMdLZbOgUbJ1SYJjlPZkjx3x3P6cHrto+j0d3gvrD0NarNZY3C8BotlEcGDw296P5ychS1vWHdIdGUCmzaaWO4w4bYd7p/Z7BGj4YTJFCG8fQuhqOuaQJrKW7QMEOgpfi0s92QUu8niGl6voynYnU40dUIOqSKXioVx3XVLBol5qXIjUBYFo3m79Z/kgPsTOrGWf1RYo75QxwxOo282gTZuy3XLJQbQ0Lwy/ZeTvvkUEC+10U6RHZI6N5F4AXAcALAVrccluEmsvHYXiC9e6THNmY9W5otA5ZSkoIGZ94wnH10Bq5Mt/kh9jidgR1uZNMOAI7DnTZpo78cPzIDNCnL4aAxrGNipYZ+mKDe3Uj7HpRqbNvxD3TziRbuWPGdfN+E5oEZx3TP7svSOISmFPUhyNkpCN/AeB2THcdCwLl2ZWk/AdUjeJEd2TgpP2fvVHdJChi2MhONJZ276EnuFQ7uQHQBvu/oqqomvnI5htDROlnWVhARKp2h9xWNVzw2QilVf48sSK4knUBjnGQ6P/l46vmQY8ZO98QobByJzCmMNYT1roMp3BE6ZT2FDIS4Y9XnPRA2Z5pIu9cp4CuyPuiqFCODjAct2xTZdQTXiu5kH1dFthR2h0sGnG8ppiiexhXjszOmuCLpW6Tcg5lpY+kjknenr7/UfCH9yt7J/Kttw1NPf/06pTkSQFdi+Gg3cP7KImczv8XpDCXmw/GCaf6yNcxKPxLgONm/m5LGPttYFZ5Z9723pk6lfeT/HFcEvk4j/Btb4m+f+H3bYn3MuFQYMGcj+T+etex4naWcV2+Ssn7tzdOWm3zqe6tL/ZaB+n7xrGXIe8eE4x8Pwp9S6GEKl+DxIPxbZwZ1K9+V9oZtu3S9TcYwXhXC75kj2rg8ZRzPvGbT8t2RZEkQHE6SErubEz95SndAcX835/1MIZVXyNFCPh3TW8SLDddY1k0AUYpHecSZFRzWIp2BzgzU4g7pFcC7QrjNWcigJWJUbnQttJ6xjB9GXj3QyDAcx8Wi7BAnjJbGGYa2EU3saziSqTKPJM09gPB70rvankgwgPbEur4JJ/sDA99nl8knPM/P5LjQ/aTFACuskaMnggS0mRuTdbUo39Sc9yVfq7f6+ZvzhOPCb0+78Cr2Q/CoxuOMFMSznLyEABCJZ03GwxDcYY6KL2+Jy5wmEdkw2QmE4ybOa1nEIF5U19FlwsTGL+g7yDIHyn1UizgTa3aRziJlSjkn8c3vaZ0M6iKVe8g98nvSnezQ/2Gxhs+8+clkrcQhjL+f/L5jjP9JwjPg2XRtbgwNCMz0FBh5MiO9z7wv7v+7OZBf7d/R/tkGdG9Japo52v/hLRu1OWMe/W7COBM8qUfniFroncGF1YMaIGYsqLj/9gAQcFYWId+qXGVA65/L34IClALqG9M0jO6b4jzMGzbgLd2KVOXjL/8FUUw9KIL3Gt02ZwZuALxHMDOZ3dj6IwtxOX5awWAc8B6Eggdc51tOtswwJejB2e+/4fjHCsZXUxUNbywfJRWSxQex92Z3AETv0fl6GEIFazp8Nax/+IKlfoiatdqWUrFCDNFf/wL4vlMCWvEOzIwV11NU+8iafy5jTbUr/fE2Lc5Tw2EIs37JElX9s1H09xQ10QlinPb6M9ObhOBD6b3spDlgD8cf2zP1bDMekjQNX1fvSSo4+/BOjA8MtH6H9YbxGhLVEeyxGutQYBGWD5DajpLq7xJQAdBOnCkgCawKQ9IsC3LNIjiZNQOCMsAR7S0RTkTKGKhCnYgFvroY0V9C5IMnmFmdaZk4hLhCEnNHRDhw1YjR+bk/x2DE+RqwD/IuExCKKZrHPatynmLpchoo3ZMk2AEhFIYDQX4tw5T4jm01hbYZxD29L4UwBh1/R4HLPvKQf7c+zHgGNoGH1Ogq0XdWS91T3jb1NnUBUPBNW1eAgKo1bKN2lNaq1jH01gAqaK15/wwCmhpEmAXePBuJ0rNMx/JuUYIdjrlFvGQ08+PugukFArpAwqIR+q1LktJqamYTEjQLhCgVO9YuxvAK1rq9orSoi0bI8oremtO2xBqDAbTW8PjwAygSwU2t4Pz8TIU3EaQ7JHJdiqwXh5fIYmB7SuBSQegSoUtizNwoWvTzXGfN1tPXjQhUq06cQ6mRlG9gyc5AvQve0ehuVyCw9ONKDgisdbIMCraRI33PO2bCLpjQuQlMdqCXDnSJ0UVSAIMKGOIAVwoCb3RKPM0YBWrjFSOBGNRYcWcm5GuLZWSG144Uxmesox31/AIo3S95VnSrcEtqSGfAvfgJ0VdXOLVaqt5H+kLKWJkxvLXm0efdU1GbIB74m1OGCTP4hfJN0+r7WTDldvyeo99GrKxRyayf07xs/qx9puUbUOloPEwyqRq3uhn/85r4N11z28uEONxI6rDHnkXF4VKZgEGhZxsEO06Bt2dyaNdYv2Qhms1zjuK3iKgZYSWUSOzrY5kBxkYjPOggS1rHGLMYmDwynTQV8pHRS/aEH89lVsxm/OxKM4X0at98PBnLwJW8vXe0tUsE9TD3jqXUpOBi9NaGyK5xO2Rxmyq0nDqneQToMEBSW7konW+dQAUSJU6a9lCYIxBJJo9aGKRGg8IpvWGPM1WqZNgYANLW3ASfofF8IX7xM5lANztCGO4yGmWwzoaX3Azpe4OEm+LEA67GbFWcxSQdAjLYu/JRL5dXr9C/f499EIQ1nMaclYSYlQ+VyF6CwYGmUoZlX4CfMcPZwdvoWVVAt6wGrLRx0eibB40KtrGs+vdcVgYPBrb23l3t1uiK4CtBBT+YcZ5GhM1nA8I443Pf+5+n7wY7GYYAvNHxNkDlgYkn0leeQwxCD7kvRdRniFT1e7OPsdD0XdoPSP8P6fo5kmMd4A5I8XS2mjBe6Sfrw5TOr6C0J533cOayPi+UZ2EQ3sjn+wa60Mw1il/MgbEwQ6qtU2KHutBgMkcrQtG0TYLHOAG3wesTq+XGHsP9NvZwMLEiHNy6ZjoyvD6njLemblPG+zEi05fjXcTfySgg9EX75tcA3wPMbqCwZzIdsmkj95vmIU4ClhkKrkC3U0kYx2XPYrhu7xFZ/Rt6UsQz5rM1fuLp+k82nj/Osz2Nl3eGEdd8wKcdCE61bySZAQreolwJfjzefAUAFK2LXq+uwDcMrQj8bBPjV04lrrgS5PtFyh9YpGtP/ytKlzHoPVC4aSz93sEMtlLH/Ttt962nCzNG2WvM210Ze9xCxv71/e/jU7rfDMk4RKwZHLqfe8laaWclBf7Y085wpLewBJ8cPnxUkqsZi0gcQAnAqjjgFhBZz+cPlwELa23xtBrFeJQBF6U7jL4l/skc0Kzd7uyTt2c26FshqTNNpI7MAlOFChoDtYScdbxfcXZ5QKlvsPB30S3ByKLRR+VB45cd/jbmNEzz5UcMgDoAkPABnRJEPGfh0ncl7saQvGZ8s6vGbym/w+KcWRCm73nf8ufdb/rnGzEazYb2naY6vddq1G7Ki7A7KEXv/g5K2S2AdPbZHZZvKWlUGP78kL3D8eAeTiV8JeCj/lRYHdX0FjOmr6ROZEa7SWDL9Pxv9RkJAtyCgN0nfIh8eY3Y4tCzSdYJqgp5/Ryc8urkGuc+zCSXWSbVRfV3XTNW/kj3EOWSpLEawzrbYlJcT9sC5ehDgkoTNmef4Xd/i8onHa5rdt0CjMqS67lj/+Rc96ZZYXzu6X/rI+2fB8yY3gin2/wb7Xye/558lvJvf5orONlmvm/Dm5zCHSq3vAS1/Gr/+9svA/ru4TsF/X/1VPwk5X/Ba12fNd0r10flhhnUQyCSOq+tidd2BQEdWNFwztXri1Xlgp0IlSJ1bwqJwtaJVwidJrxbCktj4INN1v9pR+aYCA8p8/OgFGd5Zh+yd35mn7MyVwes473G8vGjjP+zEOu7bDyYBnXJI6Kn1B9r+OTy8Te0zw0F1+gAlg/mQ0awSBh5tygYqqaGdUNUf4/lo3R7/PwFgCiFcmS7sUO9c6QYIeD89w/48cdnT78EkDJKL4O/WxIDPANYcS3rz8A7vNwob2qTS2hamx2mYq+Zx+vCb/EWt2h4qg7Y/GwY0aHvBAecbcQo3mHaKR5Jd75sAFO7IVFa+b6jaLo7BtElcHWHfmcKSmVnNoKkPP0AYQgDlke2Kf89QJxMTD0pp0ZHoRkXJrMMDJIFBjVtOyYGarMMaZS2bjT2eKoZ3jCGObdKBes2V8Sm/UlsuunEcIxd2Oi9n5hIZqxecn9+73jf/oo52Bo+TbAcyucweBJsbZMhyLrNE6PhjwseRCbb7rG3T2RNcS6f051m2B2nZmMU1CeOGu4XYEZYo10qGA4CBClsE08poTgJq5zmnk015jzDw7mQapmapcVg2J5VD3IqFZ0bjp1xAKOUigWLppMtaLSitdUzoeS1W9sRWAnt/g61Vrx5c+GC6OdPnyT9MIWwBlYDfp9WnDS61AU2gLqHXA23svWjz4kizP5GhBktMofixmlLe6tGl57Tn6nidEi3HNEslmrYIpLck3oYVWDEuUlaN1FkdRYFugBRB3N8BgBiWYumUboSNappUZl9H0av+9GQPm64cUyzuGR4UfCVzDXNiwxYInpxsjPqbTp3MviGZpxg/zVLp7yBIme0hvPJzF5fnFp6JvNjww6Me5KTcfvvSOlOJ9wUht+0Z7aAue+JN/U0cJYmeUacM4GZvR6dZ038I+x0jxkaSCP9GBiMzP5aZoC7Ru5B4QygKvvtURhsaDPP3/rJMLJPjWyoHADkzxq9ZD9ztnbWX8CXpdQnJVa+I2w3+NTDCTDxPAM+V8c4gkTPk+Jgh3P93/C3a0+Q8bMN3srRjG+htDbkeBQI406sV61FU//FDrV1dYNvXDXY078pGoTzTWQj4Ng/2zRLUd87KiAppRE4rFYa4UhpaqRw1CwfGlmdz2I+JV6iZtjJpzmWlng/i7Sq6XdPcAJb8NxfEHTHFWQZOBJu0f00J1JmgFeFe09/w/GeBOt7+FpkA9ocVSf6uk+WLjLoruFSw5k2avZ9A2bcEvO2PZU5FEQUa6zJEr05f/HIwMGWLo6jP+fOQf6uoIdiQM6/ZM4o78iIH8+QopOeBoHU48gwsW7sI5sKdOYL5I+dxTNmN1KfA14m4YwoRUrJb+ZcIEeQg+UyZTLJvKuu5yuW+x5Idy7NKcuwdrn4qsTeGVwmgNb0/QmSCOgsmXiExN6D+fXg4MRg0L06XVwWtPsGvtDyRUSa5SUiuJjUOKB0GL1oJh8to6L0mBJcUJrTuMvxLWCBNFqXfcYd6jjUO/gbY8W3YesyxKWtFLidLQC+znzyesaRnb/BjJ8P9p7Ek2VjythPHlvwz4YD83npvqaxZjFG3nRqBvtXDNwnbLaHX15wYP5U++le9x7g6eNWQD7d0rYybgG6clJufxiXAqbvaNd+rqzA8J3NCdfO8mCkZTUEm6NrV6eIjGchGXKqHQXl2aYpZwxpRvT/OW07mKDNIgMFbLLvXVwX+m1R3JxkBsmYQf5c3vGrfqVZyorLV613L+/48McKpmvcVbi/mvEYAMS5vTOa6T4MHZG8kzSrWDZuATG+ge5k/DAsx89v1D2NnB0U7xeVASXbmRpAW5Qeqm8WnN8DD4pXzQnBe/JDv39uBsP5z5ytnZaz8t3SuApDz5wMZzOCT+PgecycMtfonLo+3JEyjW5kMfs7IpPtfOO7iSaJdNpDm5ExOGRiwLMk7La0LuYgMY5gPP2j8Tz6mAaGy/RVXn+FhhtwhSgqi2bUSnR1nPH4bU5kkO+nab9S6ofdKTO+7y6H370Dd3b/2RNn6Tk9d3RkG8LD5a3x3Hgx4X3M8cR/F+IsMlEHtMJv2sfgu2a5NeOx/LkbXlF5z583nVLmkciy2jx/TmeQ2bS/eNb/Duv1n0mtTvM+/rKi/8e3Xwb0/5C2IcxPISFjnltBA6OgSy0gjT7sAB5aQ+WOi/NzNGb8YE3dRaJor6WglRrGGk3tk42SboMmklSIyKqmZ9pE974rVfyqlz3CeurK4sffpcezgMsYU9odcQ0G0L989teeTHmnLf8efb5D/9zRdIREv2H5uIDxAfz5C/jLFepHjXMsLs4PdR8JcOODMeGti/Hc6rabIeP4BTjiM84+fgAgkalUhHy13geF1h0xLjs8XfhLWkQ3CyG91WGaYf2GMhGO9paFQb0jiSLPzCoDeNffoqLiU7nePAOI8fyWgEuVGA98hTe4+VNG9Asm3M0ChXkYdxFwPBIYqjSZufw/S8wV8NbrFfQhUnJZLR8qFQveovUbSdFWJqOGCrclEWFhHBuA76Au6kIqVQVgYdePk6erZfA07thSLMoUQ8mclfJWs5iQjB3PTdeWOXO3p9aF7DyKeikL+ZYiNPqYBRX5c0Kv9OSL93ycef5g80iKDBH+bMWit+DYoxOroWgCLZnkYndYetl8Fu0Wzl6cFoHSkzzCjidKrTGXJOCWUi1Lm/yf3mNGRq9HS3oOAByPEqF9/upc8LVGdFmEuTHdPjotNjlEpqeDE8rXdPoZOJydgZnx+PgAIhG+O7ooL7LgRQk+kRn7YQdC4bQDJsr7uwNWfm61Gu96dSkVDE2pTYKn4+yF8F20yFmD1g4nyTNSiIBF6KHUPAsHEDNUdCk2CeaOu/tblO8VpQg9bZ0d6BjsRuScmnHr4FAg9bwlOp5A0BzTYhdmKK0x47gsSpwxGhwn5OwHpRSByeBPFTXdjJiSGLeWg6ZgrnF2mAIu3AQksN05olQF5vMec/zADHBBL2Lo6igo5g1vZS+qLK7UANQoL5mEzKAzeqfkOMhef02yMUgaf3SNHCDJqEOOMxM8kT6vkCQKcqX+LACYsYOfVSoaNO+HHMyUFPoGYfaoPCd/eNQWpGZ8lwu0L0CE2aDOXu8Gjn9sJyxo9ZQwbKng0+qMfyYlE0+/eRaM+XlsL42/RAp6WV/GmCbdnjWB3uY84pW8Xl1rTffSfU+En1UcTrouM31IMHtq/YV3Cpyf7JfTXNMFRRbZqAhYJWmLhGI9AzGvQLMy6K7aDg9g9n1WPpKb4LhFHGF7N2W7woBlhVEc0pNi1F5TwIETR8TtgzJaBoijp9QyL0BvWJZFcX5S6QxKwGS42SxZrGm6mhdChyB0SaK7Ga3nZ7srgakUlG7ZLIo/R7a4vWsEmM6r6BoxD9GhvTNqie9PuJztNpuP09/zZcSOjGG9QP7PeND8Qpzi+OUIPDD41bl4Wz4eMS9jeiNMMbt+j0gdrxerdwYnwh1bAAAgAElEQVSljIE160wN7DlySIyVJqfwVNF2PE95Fa2shQ1zbQ2EjkM9OD8DAMe+isPxhEKT+V6Xh4LeJBjOc8sjeVDj1Gtkl6OdxUvfHvKNtHtbzD7x6hQX8ENxwit1njulX7dXUSG8mu6xrl/lwTDjnIAHp29K/5XffQXNIAAaYL2C8FrXz7CGr2CWc/SaGH7CyPAaeg5tfnrv62TACIdInRMDoO+OR4negF0z8AaVGeUiZWGy9WAIf6UlVqw8g5el6ZQCAQReqVBaU71mv09b6QyeKpHNeA7Fs2IUA/q9rdIrgH6Me6M82arr+WCygOEWe4fN6wQAeCkG648ZP3i8tqFXCX2P2GM2IMZf5D6SvLaXYj6P1y7fKu3gl4mXf75tztmJg/dXu/9JPYHdfU+i88CN0Pjl6kqydGl/jxqRfqHPfHuGnITz7nyO9Ox19uxaxivPEb5EhDed8b3Yfhpc9w3s2HhG/Loz0VPGhGeXbaZne7/TC+7T1oWv5k6e2YrRUWuCbwid6b0nXlcjebnv9n/FwkPU9xIIc3Y4A6OjtY7HLyuYbkBEuAc8dTxo4sm5D/XOichlnVKKlEooBcX2YZh2pFXe4AbOI058WvrzXLtgoL6/ikdU9qjKYB7Xo3wmoFwE7jxcXoG/3+PYmkfvAsChSsa7VVPU2/Wm/HjI3uNcLAq/v/C83esSHggShc5JJjjR5ujTkGdStrSeV1R5Z4bqYM393+h0iuid3uN4OzpTOhz3PCXbWZCUncPXLmvISbRyA9+UrAMY5hacQMBZnrO1q8b4WrCFL97em9slC99X8Q5n/3XAj//+A41u8IWADwBe/Z/fcfPHJ8mOWwilLnL2WgcR4x2PTtDFaDDFOQWAS82KcO/rHnjL7u8IvtX4mOX1G/Tv3xyOm8oJtUjGKhCBlJ9hhdMDgLo2VAi9FieFTJtPLkda99nc6j8AhVA40X6FI/9eKAIY3fmme3kVtFFeZdVrKKMrfXGCT+5CB1J2rdZa4tkzzuD4ZDye8Y47OH7WA7rxHVusbb//rOH5OZXzXsuZsrAzjvk+Hi/Kn3Qp5kSeDdK+E+Gn5/Sr/e9ovwzo/7gmRjXJdNbQu6QFb8rQLVSlHgk6Ci2ACpy8qhKqFtSyoLCkg5SaYuq9rUKeMQDG2gIAMtOyg632kOleGu9Ln4Ua0e1e/XvzghUwhJtZtBB55a9Eoe8/P8xLPy8fNXUx/a73sGZVLDh8/AgXaEgYeFFITJ0AbuhgUEhD+lvfWbeHT198LIePH1AKYf3UfYxfkzLhovPLPOPwPBPwVpnyvf7MIH6T3m3R5xZVnu/Nv9tnEywJYoJ5SfS6tXtivMmR6DYfM3LsCPcDQZ2I3UYofGEjEK5xh4/tyvej9S6MDwAQYXl3gX59h/MO/MhDwDh+AHgA4RW+q7LxQlIag4SRU0WS1XwcJq5nz5RjDEvbG/OH3abCiTGFLqjwC3UEWqjy5FalfpSF21u4v6/Nh/UFt58ewtQZjb9sn0tC6inZX/+aIXM7XlPckStVHTZcIIo07/6D4WO9bvBGiemNyMPdKQ1j30LjPClj8vnEHYQwBtu4g7m0+uXd64du+8j4Oo9UlowHeHaP2OEsZ1V8GDxDeJd3V+qSAq2rIE9C+zoBaFDhRRWcpsiA1khfCho1qZ/uSkMGqGjddTFWgRtQ2FMkunE8JoTBAEN2j3ogJ5pQSwO0BILNDCxKYktxa7M347tFnIIQ9eVsWQmeJjfXnuu9yzqwrAeDgVrAnUEp/bVPgcxhx9XysR4OAwkfJLwg93dQSymiqyqRNB+fGe9k2wqILYX4FDHP4TSwjZ6GLzrbvwRkZ4YB9lNKu946yOq0FCmhAEgGDUWmqvDReqsllCNM0ChgfZUbIqCp2UcDTeZN7KwTkY/aNAp7ERJDtB6lCGIeO8/nZ4c18U8CE1vNN6c1BzDQDr9HHTB2DfA7XwfxNivurSAyJrrE7OeomBE94wp9loFB4Vgagasqrg0NU1rPhFOQrs9jno0OmzUyWDMY1XzcsW9QfKPfBwRI4dxBRgkSokxtT2AvWvfb18NwL8QtJGqqA4xUe137M2WU20to/z17NJI5r5n8PR6PWA7LAHe29o/HIxiMw+GwmVdrwkE2czJKfeZ3jMqPESbNCNT1vsIMVIC6Ge1YlGqK63rvWDtr6RKjCxRGIMV12bnW3+F7+DQDZU4PhvsBcjjiRFeHs2mIlYGZ69rX2Rw3V+hwAD9Kcm8le545zBVgziDCcVV+kZDAzcHVzxoVU0o4uhGc9vntzmvYcgWlj102E3gcDDlzDUgRhBk3rMNs0xrnsc6HlXxR5RTMcyNMq51pCsc597mM3e+CghIDX+bh/BVNeCBwZ+n+M3PEUIWnIa/M7ej59VqaE8xYZiM/MT45O8DzHHUs05k2xGk0xEpGORcw0H7Cd5YoeNtvJtruhc8hpX8FwCmSm3EPvnsjQeUKj3RZQjEOBt92lAvRdZRCQBM+iKigUlGfRZl7OA7bDmzVtGnpXZncW4sSD7D6t2bA1iwj+G4rLuPkRDN0rbrjF3J6Pxs6czM6IO8JOmn7sHftZGd22Z9Rpznj+Sb6ZuP39drI1+NK2rXxuX92Y9wBuES/4VBmzfh877kN3oIc34nPs9JAglO6w5k5lRqMZDr/qhc3ortjRg/ebTAynhjfv6e97O3Gs7gRUMs4AXLuJZNJnKGO7rXPJYuVdxD9Abjid2B0lPfF+anWVjRmHK8/4VbLKlUk8cHPdYyvM4PWDqgxv9QC6kVKZVL8H1kp5B/jrST7l/7Eif+hlxYAON3c/Na71j2PBXh8fEyO+gKAXZ0TqRDOXr/B2W3Dg7tJJVqR2oCV/kUANWej2vyOSXfACV50XPnz/JzUnyb0VK4JCVcC8PM14+CZd/F7N/h0/3vG7Vn+zU2cE4p/nmt6DwJnev66MN514Jr2+x0bDTJ0AVB/K+L8SxKcdckQHQsRLn/7gO9/POLVO8Lx5gYFhE7ioFtwCcad2Cd8WDSsX/57DuAHEWbYAhAJlvRPAbB+/7Z1bvAOp7WDZBOq+vnv8P2izRcN1Eg8tvGSpt8rRKPxHKGfaa1LBhHbVhYeh6u6dLDg897JZZbWWYLuevPsOc6/QPeaNLugDsj52sSuCS3562vyUp4gpF9DyP//KJC9XthfCnvY8Pt2fL/4n//d7ZcB/T+8jUJXKMQ7S4QAKVO9AkC11CESz1YJePPqDP/3640oqht5Kr5K4tNUahFDujF3Kb2svDPMdib47yGNPTRyQ8AHeQxfALyFGAgBIcINUvO8QwibIXSZt3yvCEJ3Q2GwtXdm5Yxde4p3c8Khzb202KJPgcdPR5z9fhiYWDNyIUX0lVLQenhmCoEzhYYg3Fo+oOHzMN68YjlpyuPnLygAlo/v0T/LHW91wEz8UxHoVo/cnnjLJuzLIG7097e6l7c6zzPW6PXE4xPC+H07DaHyW58v6HYwkt8RcKkuEgtf4T0TjnSD+xdQ6XtivGXCBdMQvT4bRMSgMQ0qLfRs4LVvL1lJ6Yaxfu04+1CcyfbodxBKqahvGfV2fk8o9wFNGQrGd5Y6goQ7vVGZVHLoGozoBn9myCoWIZ3mZUbMWhas61HrQjOAMnjanpojAByqwP6qta735Hr5wOL9nmBrFCQm6XTTg8J9x4n7dgb3grYx5M+hoQoTARo0/azMrCsXYtzKfw5v8H3NNU59JAGR4pykETP2RlPuQuMSSY1xs9It9Up7nsUMd36qmsbbNPK1Vp/fntAZab6zUBN/mdvwvlolrebxUQpxWHkQZkkjLDiQUMpo5GSQ13oG4kzZpb00vyI4jIvezQC9WW1pqxplainolUCNUaijo26YJMPW+XkTWwuKzpXQUiQ6EUMU/IDUKFQhR4VIqppCepoPXHiR54SM6u46DpGqWKDwkiY1lolS2kYtxmePXkD058YbX1v28WSYaZqYzgCjdwYojPdLPQBgjdRXQVeV0Y158HC3Xgsis0o2qLCuW2WpIkpMakjS9IGWRrnHmploLZkVTOln/AC7ECiRAskQkWlERk4zoKRtsTTuzGI0Z2gWmCIe39U9xUsITywOjLUWeC1gMxq4AdP2nAORJOGa8llHCJID5rDlTHQkK+FH5w5s7QO7uFMubg3gad3gWyjgNd3XWZSSSQQfntmlCdKRX3X4RFLiz8Y42HUM9FxuK+iF1VOf9YyUnTmRv0NgCigV6T1pomn+fm521kcyH2R8NeMSTg+qgw4IFj3JCJBgVjjONDrBUoyNMKSGUUZOjHIWgT0aaKIkgQ2Moy8ddS4/QPpuuZTfH631BnPWm9fF8FDmeRjAw/GI3hhrC2N5LUUjRWwRAMsM4QZHFN2miBrbwL7vL3uUPXMRIx1pxiCQ1C1lxtpWoXts5xrgbPAkAtW0jroXe7Awt2FdTMHKgV98a3xZxwvCW4635Gc27ycAj8fUk/WjWQc4w3d+Xo2PfIaOR2SRwpW9HLtg0klvHctywLoenRcBUmpTl5MU3p2PSpNiMaBuTzlS1K84ihy0RNaxjaWACIQjgLO8fgQcQDgiGZjzOiE7K8n3H7C63TrHqRRRuDAPw0988PQO9qEg9sL4JFk/SQUuj1ja9TOM370PxQlndr4xOhNaellb/zM2umrIRX5/MJ6XZK6vE2gD4WBb9eyL4vc1JDKcvc4yeHy/ycwmt78iwiOLafn1jDsMFhC7Lnks5t26d1aA8Aa4EyMYXZDUESNg1XTvuBR8X0sBEaP1FaVUG9lGfpnT0m3oJwQPtzZFqCoNbHdWZfr7hlYxgEe10D06uLPTeCZKOD9Bv9FEU9ja75xwBybnQVN+J1plvGFebtkzM/7LZzPSOW5yujfuwihi5H45jdsngX9J23T7977nz/a299y9svMXLDI931wqZDMWvB3uveRbMF5Q1k730EsWMAPFYjIIpUuJHksbPsuL98ojKLCEI23vIw9yYm4bPu6EoeDn1vG5ST/xpL7IM/OQYBAxJgFAAZHnTHHDUU/nJuhatAtd58P7gxuRiYCHPx7Ryg3uLBtckCf/a3oXuSbyIJcObvGWUgFCtZvDMDPwMuyRxkPuST9mhLdgy405/vjMmrpcd3WlWe8EUkSWlPcuyyIygc5D/twB5QprW6WP+gOvanW607gP2RVlHoSqc6wkBtcckQ9EBhozJr7EACV6TEZlNdrOTffwYyd8Th5as2Ha6TKneVpQTpMsEfdVDekFnllRUGYAwDxi59+nucy42iP1KeTWe6PPBqt6PylttshzzxSL0OFbNhZxyJexWtkCc/Z2PMKM64kGveTw3un7P35uAL7gi5oHrlQc+fHpQWCf7vF401F68zrpBQCXOxAuQbgHM3vw0VFL2wkvabXmxSEP6Hhte5V5c5Jgwao8UsE5Vvru9cudvzC52h1QIuPBgnOAgZXFee9G9WAZlueW+b69JZuftH0aOtDrpufLjtBiPDcc0MQDlo2nlrcbyHaTX7iBWZyQW+9Y2yr6KoXTUWah4AOg8GC/c6wXQJ7hNOweiS/5mxunlTXc8+JI7x1dAZD2wsY/P/dU/zTsGkw3O2QS+tX+o9ovA/o/rBniM2a4A2hoqESS7lQVQA0dP1rHj8cjLs/PcHc8onNDZUs5HoiBSonP2EGW9BT5eLqZ4Vxf6b0QRuN4wza2wu4v6b55LTbEK43yrRLxOQreaoQPl5VAd2ac/XYY1qDWKsQN7IJRUSWgpesy5TeZMJ6IwfLxA9rna9dx35Iwhbk+os2nAeifr1FwhUfc+BjvaIcYPNMsDXvm/QEMnnyMcRwd23E91TrdovBbNLqNtPz5Xfp3+SC9tmvgkgl3LzCi36oR/U0H7osahsiYf2ETKDPhykyaUvavy9zSwdnHA7g37TOUIV3Trtd6hYqveN3nFG3mBTsOxPx4o776M3u7KyvFBJnFoNO5oemYhBn/WR9LgRSez4a/Md7pBl+2PfjJV/2ptnfif/ZxVfC+sL/n52V9TDtJ41VLA03+gxktbF3lcyE76CEkZQbO8Ir1kw1xgwbex73x89wd/alveSFCTRPnyxjMoimTudBYNiAZYwiqmGZy5Y50I/9yGichokUdxvzc2/qEIJjZZe4dKGIAr1XSq5dKoN7FuM4AekfXyGJSIbaooGmZWYhW9EauBLAx2FqQGoWL1QC2WViHbIYqVmVBjFnmqKn4axVlcBUjeilVouFNyQCWNOXMIDOkUeBDqUEf3sMSfRFCpRjiuzrJVVXSuGSa9jwEqKK3jIZS8lIj0D2iUmS9E7D43bpOvXPAB2Q/M46h9J/oueSdEWEc2VuyUZqIwjlkOsZDxEFyvohU7hJlYeePO4Mqq56SUKo4oVARhwqnPSwGqkKqyDDNfMrO4OeEbKjBWwViiDVkmLKBhnHb/3YudstxzMRdj3DmXzIs2Npkgx+n68PazWsJpAj0MYJyH03OP/qbBK9mHsA2WM/OzJvZc5Z2mzRFnuuI9VxCFVFSk6/HeHsHSlGaGAaHbORMkxzhzfpHGLv7NOM8RbYxWxQ6AI8kCGzvT43GvQy7o0LBM30YPRiyLCgP0CAw+gxNNhAMA2caV0YJaUw2LoPDw+GQ1rH73gApGjvNset7mp5h1jkaHdmuJ5+ExdiVkFnkfMoESM+1pUU0g72AgZai6MnIBej41ZnoJ/iZfUgImmYZRfZZjfFsAsBWWRMPj3CizlCGg3ytEueXYUj32912ShgwZf663ssCPDyCqcMdMQhox6OvtRmGR6MExdrRONZYFgq6mGdoCm6y8kzP8HlTB9u4/G0LTiiuxMLEN4NvRqp9jv3tI9r+GKluFc6cECTHFZwGsTy1XpRLYBt/9pQynMJaOkEeFnlZXbONFyQa07BnXE8RcR7nijEjkdjC7III78dqxW/mlYxM0ZcaxxPnNpKxe/3tNfgOAFnU5HcwXgN3QL20dPjqBs+M3rTmujsA6sh78ZTXYcAw5xZDQCMelnOkRmwwrBAd85grggHhJ5ndkUTSrvribBBcrL/imxJneGMoP3Et+qnIr2KwBzrMn/O78zPD9xP35XdSem7eu39qs6x7HWY0ItAVgW8YdFXAN30Xh+QWMk/IQL5zgd4FCySa7PQvY4/0G6fvL2n/qv284Bc4D5xqui4M4S8q1CmydHdMsnNmMtBgRD/RpckdNqzHz0es9BX3jrfgC2KByVsKrefUgpS0c8MCWYafjei5j+HMpZc8EwfxZLtgBuMWzO/RuaPWita+otBb9C7fHUeZiEoXaO0G/f416qWVo2RwET7Bh8aZC7N1gPCTM5H4E+3SUGewB96yYRoMfLLgpolvtpJTzsMn/HmpB0v84wkXjXBfAEZzXsnk0fm96cLu9cwz+++UaK9dm+/J8rvBjf+1oA397hVElRPUkmrmiNGtbNYWye/PBcCWuAGNboat7GRURzbH3M4akKLOZW0It6hqBRD6dJ+63+Ko1/MY8tD0upjdH9TgLg58P3bmwhAjGelfxkO80/v8swhJmmRXHThpL+E6r6/ZW0riT8R43kRWaew4KXqT1vVsib6FAGhWrdbk/97RuY1OQ85vB2e3XSQ7wf9uKr7P+/3dLa/hixrF3uz+BvwULf3V/ue2Xwb0f2AzdGhMdOOOVeu5Hi2lC1U07vj67YdzfARyDyVncuQnTStSwOsahJ0CkUusFQHUdrDdFkVlhuoOUtO8AEP67/xU08/vOT4TgFe//Y5ChIc//sA7DkM6p3tmA/tQqw9mLJeq6h1ffe1q6ssYSLcnMDSKU3oqViMeYe4pFOtkKbXZJB2C18CupYA+fkD7cu3G/Eh3Ht5iZViPr2r8J1xypEX/mXaZ1sved5V+vyNxMsh78iV56r/vwPUzBeVvSNK6nyInFgn/41pqwS/8FgUVF7h+0XwUTPFGcgKhNGGObT4eBWr3m8LqGfp26ufNkBi4//QFl799QKGCta2eWlngiFFKxfn7d+AvX/GKCT9yuk5XbI0h1wxRNpni61WRjBCVA3ILgKMa7xY1ssEjUtL5KYR1XQGkiEzQbnGZfC4y57I2S0/4xHqQGM5LqS4okdZstgdnw8Lcz18RBG38+2CTGdgQ6jav0xAXqyO+L1bv9DffVkxxr/1lQ4f9awIpNArFf4/P4ZGajOIIgclHoUKhR5ZnRMWciuVODKlutAttKdILgNaK4s38LNK4awSYG+90fMuyAAwc10fBv82kW1GuM40M/DA2VypzwpfkgrKdq+wMY+fcQTr+kfHJLNGSYa+wpeIuYDSgFFQArUjsExX2VL5VI95EeO0oZcGCBSs1SV/b4zAZDJpQXqig1BpGIxe4k3CstVctRTlI8sSACIflXAzMALz2l82pG0xwGAPBIBLaxL17hLR798MMhZyyD8gvy2JpjTmcGaAwCqt1S5EG2JTlOqfsEOTvKgDWnndNjdPmbqYwOMC49GllJliNsi7qmdKjt3i+c/AsrCNI9YrnlhXdtiO0mgMKi9MhEDRfDZS1CM1elgVUKypVBzWL4Mm8kSVz5XG2QFKeef+A43BbCP8ZkHNsuJS1Jpo5Mxh82eKnKQ+/YVRM5L+xGIEn88pFve9pPQ2Mba/6/L7tp30+US9aCneDJzNissGi0XUeuipU5NyUrmnuttF3At+qQFLjeetdHDY1I0jMkTfryMi/p7V0mjKtbbduxrUUg665nXFcM4SGOEsBYDw8b4siyrJM+cJ5MEiPwjYB7PXQ2Y14w5uS8ZTyr45Xt1S2UpEITbZ1EoOVKX6/P3z38hB762ln3iIruLOfLXNAarZ/zi/tQpYrvIlizrpoIJA7H7nCCizwspjaL37PMGhpxGkno8Gwt9NnN5wNlty4i9MHmpmvTe8ZDELiAFhqn7NSIIclhtbsGNvwXfaUPKTnUWu5nqO8IhQGWl99zh008XJpjRARPUVhNMM3kRrBDarsd7bfw2DrfKHOLwVNooBwIMm01tJeeFEA9n82C2cZWmYotu8HkJHkYbk81TFJRPv+SZDngWy4DxzROBwPZEgxxsc03HMAj9O4HM/qV4vAP9cLD8Ov00NQusNA0Ug8N2Lomh+NyXJFfqKQvp73eE0ESvRTHMURLGfab0D2Cgy8Agd/YI4EfublYed10/5l+T078jO+JTwofwliGFigaWUBFI4azwTJION0V26IQ5UUzD1HnJvBRGGRmbGuHev9LQhvtnQGBquM7ymjho3fOEaby7xznDozOXA2lP9IY7VrNn6537IHmYNiGMyzIt1BcODFCYnjGtroyLeF451H9i69+Nd/V/t3jUKM6MChvAe917P2roL4CnzDuODbk/qPbEQHA0yM3oRtNJlB6HuSR2iiWyY3pf33FL4/0S6nB2zMb3j8/rK+Mr6xdrqDmUJm3Og8FWsWa+rDA4b2WDMv0M75e8P5O4OZ8Hj9CMatmPicx9gf3Gx4E8Mlg3qicen/n23MjCsQbgHcm0H6ifXaa28YqCAAo7G83QArbkFnBxyZ8ertBQQ3ayYuBhhvUN9WSLWMgk6EdW0gYiyasbCgSKp8Tfl+KAuWWvH98fFJw+SpGujzE3ckOstwAia8YR7hbkKqnqlL7xmMyAxcKqtUAOWh2Mk1oaAzgZr9pnzP5Lw84Mf0fTMrLZtmEqGz+fbMBBvf/HcZlxvLpZYKLIrZ6jQfSExArzUDyp1F1KOgpSyCLvMM03gZTF7yNjDqtlhmgFvcWEktaEYHvpPSozpGyfJwN7zW4MwyCvxw9kNy34BIDemG45RfLKQy4jkaHvBa5Rg6NryBZCj4DjGMHXW5G4BzIhSc47F/BwGDxppZ9LlA6Ltye/mJE1ghHScYQzYKc4AuFGn4u5ZTswj0zg0FFaSZRkEYsgA1biB10hGnlo7WGtZ1RVN9QWTlk/E4P/PEftscx1ryIZftPfmnaGliNyOY5OdwWn43Td9Pv/fpdwwON8oHGvz+ij7/z22/DOj/0MZQAy1UCV26pm7W9KKqUOF+xFIWlCKReLlel1N0VWCZEbj/NMJ44n6SuufzHQXvwGrMth4ciedeWao5MgTYZ4UDp7+zUuvUdYIwBBaFzgDalw76KFTfnAkAMZyUIvVvTe1txvemkXUi5Aif9fjHEee/i4rHotPJ+txhGu8Q9cHt7zu97YaAtx24LYS3+Lka6EDUTbpk4KJHZMTMe56ykWfj+Uyw5rYX6Z+fde9sunXB5CXeyLfEMnYIoe0ADgxcgHCvjJa/h7MXNobrf6Zlwnn/+QvefHiPpVZQqWhtRXiIA6CCw7srHK9vnmRUTrUHMM6c9ZV2KusC0huyOsSUzqzCILCdO8ftVo1g/P2E4tEeGoy90yn8l7IZCXD3xPC50bN3PLdH/KL3nOo5niMdzRgJFsY0/ceuDcZ0uX+OQs9R5zNoU/p3vs7pQ9LPPDmRvAqzMsMMSjZ2O6NcVKAyXy5TpEIUOb3Y81DFhsGq/pMcB1zRm2mSnXNT1ArVA6srELEK6NRRmNAYqArrK4DKksuZugjIYgAPTxwCRJChgloXweOVtXbvKPCyjRETE+4GmVB8utmUCBLlSqhLBSgb9WKfuXePZpfa5RaxFUpeS6ltK1ZLSduvZ5SAHDXAKrxUHZegDcU9HggVhi5zvAulkMGgvaVIBvqOlKO3OFwg3dthPEiBRWaGgpjj3TDlwgjRTofIYJiQQGhc/7QK5lzg10wZAXg986KG81Iq6rJIWYRSsNTFz4EZ0EVRb1AtyoDCdiI0S4qf17RGPo8JF5DtLIlDAjOg2YK6RlJnmM+HcTb02pqCoE4H2/tnIzCAMZX4Tv9yuXs60J1b4Qd708K4EU+FYnNST7ki2IzEslYh1PZO7qhjfYqeqktkUglFclOlQmegLuN7ZC4jzA13sJ2zkbeIfbC1H9uAb31ZApaZNtuS+qVx/Xs2Eht+EM6Nyoh3LLW7vNJwQPYAACAASURBVNAcaWy1g2ug6UQ9S+vS0sTeK4w14PEojrfZstR5y4sM96T18T47p3rhpxXPmT7Y/5LSPi2swkrAD7CuGj2v6UxLDTjhRFelaxt316k+w9klw0VeUSPxT3McsR8Djn3yiTGK38ewezO5IZIM5xyWwJ35MZvHTPD1D/WOBnEcNceBvfeOBlqdm3U18BZbXMKQutfhmDzfk3GeKsFt6REGQzlniRYkmmw0L74FjD5uxjSel0eoIZ8Ctv1X3nFYwXjGzjerJW1j4tKvD0hlzk622LOuC200ZQBJy6JFNKw3fOxKL0l4qTDOWaSmyTxjNF3O3OC8oe0QD2yAP2PPhesd0v6ozMrjDpC+u+s5KQxwEZ5Kzk0BNylP5/OeaKQ5gHGyKMRoDcd3tLs1jXRLKy1VtMHo7GCY55jXeXCsLuGss2coP3XN++N8BtQxwO7T1ND229y2DmiZ8AQ8xfjysxjm9DS2+vva02fg/2/bYDRmdfII+KYrAm7EuHk/zWb4RpB6zKqDMnmdncZP+2X8ug7AeL8Nzf23NHnfheLkgiusuMG3TebBn4CatLDiB5/mOsmI2WyU8Ul++zdivOGAf3n6Rl0fxpE5XXlizBddskua87inzZ95Rb8W3081xx/Pc2jb8TBQTcyg4BUyNvNS3wk+CwU97bcN9LamKP7AO+KE3dWBIXjzjMueOq17/O9eMyO6w/PES2VZy96b9T8XXbINQemFzaGl95M6uhJpXhRKdDM7CzusIZPb7R6mPd+7x3V1BgsDn2pjITe6mpOUyd2jHg74bgRW6T6Q9iKAaJSLXwBODIHpza2cynmmqd/u8Ln3ShJz1tU9+TPDgw3b2Uu7x5f+wWXGBedpe74BYBwR9DifnL+bRl2yOBMM1N10c/CvAktqOJfsTfpE72MEemd3lrDGFMGS6IoLGJ5Za+0Na2uiC3LcMs40gcVmIZwu/VVD8c/QmGCMkNftp9sT8oe95uVdPQElv4zo/5HtlwH9n9ZMGwMT4ESR23p3JH3szSOZGAWFG87rGR5bQ2HWWhld62l0j4IsRFhLAVkKO/7zeMMI5FsG7grwcRK8CirKx9+xfv5jL1BW+1BFQGL6LO37zBDbirwCoXwAflyP/WCoIPTOv1tr+IqKj17bDcpAliJRN8abuFK3R725zozHPz45QV/bB4kY9nxP4kH46vffcPnHp40RfK5Xnr39bi1SCwV3z0SDP9f2hAgbyzsGKgNrerfVnCdC9h/cNEtJbw4A8zvtmhvZSVLLv3Q6t8R4C11KaPogZrxjQivqjcqjoscF/78gbgv8M74T8AaEWhcQAcfjA2o9gC0FIQOAGl9OvC/D6d51dDGiEwEXuNBUzcCyrINSzQw4Q80enbNFcz41c+NXailYWx8YPR8QhSJgsyC+C3ozA66mK4Tai6dezs3G9Qy/s+V4pgEGO7x34053rswiv43yAKwbr39Gg2Jx03zqqhicFKh+WzYCwwwgCp+5M1NUutCuHrUaVWzwnJ+PYVCkizPhKr0/5p1U1R5BqxFGBDVwjCYsiSzM41dlm3Z0PB4B8FgfWt/RW0eTLOoJjhgW7WzXBZBhiDU6sPMMETTHlZQeWaT2pJhsvq8MUTpZ7avSC1A0TTozWq1A66iF3FmsdxLjMcUYxegn1woKaLF7I1p6BpQsUzqU2vlENmJLpDMQ+2z9dgQOs1Rga2+q7Myps7MJQj713gFiUKmjMjfDHwGGfbmrgTYpRvSBtOY2Zh6vMftmEgFcLLKMQSQZcbLW3CLIAcbapOwMaWSY6IZ5iHoznMGQKKvWeNijUUAVI3bnkZswOKt2HopeKCLIVikip8qfgsOyYFkqaq1YqhrSS3GDBGvKehNUZzOJv5mTF7OtC5FnruhNYQuhCIkzK81T+JNkOWjcElCdboODpP4/GNkp7SWPn+d+/JmsFNu9fXsW4pf8jH7QTBheOznDHwHMAu/Zpl+K8V/J0YgQUbU6PjkCo4KKO4On2jQv5QwMZ5tiblaIbholvM6EKFlhG6I0k3RF9Fx45EBSqMXd5F0DLP16LZ5kNAdJNuM1KVJIcIvxSNK3OQzlfE2y+HG6Mq23ZxUnEWv0hDgWmXEnR15lHsRojhmeBA2wO3VaJLvdbOu9VfrFOnj0eHQIQJ1eF8F/a1sF1yidrDVqxpdS1JBmTE8PRTNsr22bN9A+chwsa24XuxBbp3m+3XNL3aaj5e/cyl8Jn6Z8XK7Utdf5AMnpJCXDKapkIpHEWh19bQITSvc7m0o9ZEEAKArHolNuWKhIGY+hjrLicKLR0KOlRmCgO0BaULGYKYFLwUKE3tZhHM6KJjoo18NhxFcz4dXZQNj9GGofhTTbzcjXZWP5Cjk/x9zfDh9gK3JAREMdMN1ne5nYn1Pt8ZnfbSAEO2dKn5XeApCMNvnFetiISoIrKTM13IZE6wyPGMz5LYwLKrGfA68rzxa8AYHQ8G3glWzyxiOZaaAl/s/kRakLzcK7dMZKhAOqZHpzoJDockuVyjZ/o6mKa4OnpvidNYMOM86vFrT+FutNA/M5pMp7jDv4uUQfM981zdHnmugTekdPGaReYjzPPJl86+l3vZ6M51ZH3cewWfx5oFva9gqkSexthV8iw7+Uyv65dqr3f+1bTzeLIL1koOCtwIhsIDoY/SZ4gJc0d5yE0GvV8qnjIJAIFMzBRRGdRClOmYKiY/37BEJ5k56TEI7b4dqpJoayd6hXItu0rx3Lu4Kbm3zXSzDZ9Hl6t2TLMj4j8WX+TASvtB14Dg6FcPwq9OX2uaFxnPtsuGUeg1vsXA7n1uQGzRBh160JaR7pTgHwljmliE43p/vn9oZdpRH90b1EV+NSZOOloBRlTTsr7WsaPUvo334AxHi4E+m6agY0AvCwtsSTavYyBn6sEXm+F8Sw2dMTv1vmAwuwKT3RaQq2ytZi5hE5bVTv7Ph+kGkQJIwVTtCBdx1Yq8gk94RR4WzjnOqe7zlB2LWuZ1GGuoPXUz82fptX6Fdo5O8QMLjn9DSvfZRU+ptaEL5Ed+Yo/YBBMUcQLLK+q36M+jj21wC+EXlkuelTWSPPhad4hVsWOvzGhlOAju+4V/pnZ+mgei7ZwgfcGx/g81B5fMrgFHqlff7O2gK1cRiwxcak8yGOvaUWlFqGrHmSZa6p7tbodV5fHYXy4/a9s/LtCHuO2ICkAwuEyprYkJDSPDEF5hjemfDKKT3nn24Jjo0iPk8RxmfyeDzAaNKhvLTP6Dvkq7nPX+0/r/0yoP9TG4XCwYjoyl3SByUxsmgOt3JcsVDByhKpHkYAw/kEFEJRAbvTqCjkp4xKTzSrNw6MSLJ8jPSuloKdsEWkpu/Jze6fmTH7vn7BoLAaEfQ7f+YrjYbc4+fPOP/tNxdCaarnywT8+OOTKxJe//67jzILyD++SLryi//6XZgI3adCwJII2rxOlyd5HBn5Rd8aqF/annus8GhCs2jyeT9OwcDtC8bVoR57FMZ5+/5cuyWp5bSooMQkaScvf//4/9h70zW5bWRN+A2AtUm1qGTZ883c/7XNPHPaVu0llZJEfD9iBcisRZK7p08LdikzSRDEGvsC+vMzHp7h5L8X6VMOMQ3g8R+PTuee/FYAqsCgSCsATliU7t9bHvCAIwAVJ2lfZV8BFoGlMsrSxefYkXSF495UJU80jc/wuOpaqGfY/LwOQsRChGXvTvnnlGxRvb63/zyEjfl3LGBicPIlVyI6TCKHa0QUeaz0GigaWhGGGRjmr5S+ZAqTckXu771UssANADzfZnfVCX5nGGoBVAFmWMo8yaJTzQU+uSUTudqbRVhkjKcYIgmDkH0os29nBaGAeaf1GCBVNXBDgYSe50KYJZC7tKlKUlLYIkrNCKMFaLh9iBWxMz5s+SXhzKQrfu2TstBFBBZlqp4OARAGd9Fw5WKcJXUXbmCeZV3TxjUFCatAQdlAMGtqAm4+/51KTPcHQQzsFmoRzrnjZdnXbrjV7w0mZ7ZCgNdAqPLmtH+ZQ8DHJKFuS2QGCOFv2iY2t9nLfqMb6PJpDzuNjHm1PUOyR2udUAt8DxAI08GEqU6oBwc4mA5QpqoK9BCANRBoWRsJ5U7JuE2xqV4EKB56zZZzbyGCaHJUgKpK9Gzs8OI55rQHkfZkuj5O2ZYQMl/nESb4i/Z1YX1PFMYZlgAhEWspr30P81oTepYyrk+KU1FGMJoZLOSxDbhrFPZ4vayA4ExVDs/5fOSHtxqE7uM9U5Tnvfse+8v+rdlQAHA4bCfViin5PY2GnWWyM6pnitnDWBptEQZq21SfCfSLRrr49jRjSYJgCSHYP9XBvmQwwUMdH3t+pnHWQcunwpNspBZwxoQ/5HSMo0Q2uEk+R45qeegjFYfnQm/ZXG8u38aZMm9Y7bnR0+P5WjUYZ5u1711JSy1hVmOPrSqpINxwgNMbk3jfh0GP4g73yt3Y+xvkkJzjCAI9wudRrgtkJQelCkYbZIyudIMJPzna0aVIh4C6dejXSQS7JuRPV/UL5QfRWKOccR+xpMPvKarDCIppWLMDvXaIOKkvle/jV2RCTHmQDZV06rsyQBLYjORqWYicDYeI+j6GMr33SDfhtL+Bo2fjSbJ6dj/C68q16ufVIm0VLPcLDi8OMC+LwwlRrtuOYHAr6GSgdg6RYW5EOrHUF0uTVHWNGbtb8UJvWXnOeYchNiiNZ6D3Sh+f3zTGcoUE4xjAY1JSHOt5+JJgk+xxo51CWZd/Y1yv1PvXbLcTpk1led4z37Nrf0p5zaH6J5Z3bF1KsJn7bjrPsGfyuvORQbG2lemJ0VBWzsFbGL2Xi1AIokQfexodi7ETgOW24fDDhHo54eHqzzev04sjSDT0ZkhweuGVTRxyQp54t/3Mqmnj9zLtiX49YcdT+cFlwcKS8qbLUZzbJgp6OPN5MDjx+gks9ndBIDpXDA+0G0a5EIPiScAodgDKl6+o706cz2yPX2ROSPNaJ0KNdTN3MpZ0/WeXDL9M7tstiYNeivpa3iOlwtKSeWd7nAhYSEY0QeTgRITTBYDyqTcKAC8acG3hpzf5oY2+pzVnmBH+AJMzTVt63rkbq+Oqfv8wmwF5j98M667PUx995DmZ11shSeB8G1+P3zv8meaQ0zOZpjNftILj7j1Vf2vg9x6NAiBmTBru3W/9RNDIEAevVWANexWRG9CLwX4VOQSR7kt2D3TD19Yu4Bkn4TgeEIM7RJSZxiJLCdoqt7AxVDIYHXtOO6sP/Njk7JWLvPQcj7TJj5W3QcxEu2e5A/WyhI6zGGk4/Nz+/yp/f/mlQP9PLBuHVKKnNswNItiYJNcNa86bp2VBrRXMEAW6Am9whNEkhMdb4Qjl1rZf+XwXFTnLZzDowhxfOEg6/Pg7AGD3eQfgGgUfIIj9Ggzg6eovB2Bs40TPdyQZGL46A05eF9gPSE1R/EFpEcvlQ0Ro6vFG+WUIRP/lzz9x/OkTGIzPJMr4CZcyHlzh8R9/4ui331yQ0ADUjx/x7vNnV4SfcSjP94VAJ7DkbPkO4GxKeSJhFm7Se4+Z8I+yRthZSX+v9NvPQAtZUf6eQ2H/mlDuYOABwCnYvQkZwDzPOPhwjotrxlzuQSC3AgfQh6XN5RUDEoTOeMciLJ75HhWn+ryFmC1oLQeD+j7abOR3vwE4whfwrLt/qrqOQonWWny/wvMEpw2aBEVbRXKex7ud0B1+e50ShJaLSwtZArKOQN56P30vcTZWp2GAXlqu4P2kDlJsMAmE7n4wY6W/PvZnY/8Y3AkhplQsuYISZCZYJ1XKOqNE5PAsQnCxeKRLx1bvJSIs8w6EgnJ4sL23s+AaytABzlgG85k0mrD5UoMiY8gI0R+kegbkWCIcOEOnodeMIWzMsv+YUesETtkiybUc7J6l0jZHPk8bD2WhrtRtmH2sBBFINCJ8gyjAd7xDKYTSijMytUyG/AT2M2uOdGuD3JOLdQ1KrSCWVCmisBdBfWwj7vaArW0pFaUQiKpY/PseZfk9q1Le8odrLnAJLT4YsQkAQIOlEhHDFVknMTBqJDCsorjyCKDw1KYk8E+hlt0i28bDKpJWTpEUudYF4tmb96Xl8SaoIKDoptH+6RYrmnoG9jgPbL7DJEKp1Kf51bU3gQEhGBk5O3LqquYck71X3PCi1iIKcnOS1/WZJlWg1wl1qpI/uU7AMmOhbOon/W1pvb3naZHy3FIlPycOrxmm59tQrjFce6SCeMs5+BYly8jQ7lOebz/H3X1eVefN5zf7lybHx7x6noOR9jbY56wVAnFdMa3NPC5lIgNXwrZ8n/ucAaC9MC+52+nLa2c+IC5JHkmjqX31E5TgrHyyOYpPLqbcsTEDjMj17U81geFUAVrUg59IvY/JBXe1iIGL5NyLebR+hyeDAnxVylBaM4k0onn3CFCnzWfnzkrFJNyrLr+nTFpsb1tWbGszhelUHGq4NsMesnVWwVIlwlQn4Xn0PaV7RBRyi3rol4SDUQpm81zaWPUBo6LxDoUOdM1kPndPXwU/EOHg+MgnaIQTGNceQasY1AEAOiwAN/BTMuxd9Uz6zhC0RWp4Rnlsum+YGTwv4LYAZlTNgjMKATOHgt3exQCmdJawqEeRGvkQZN8xSyoUIDxa3FQjEZxu8JFGcig7EAubMiAiuMwAplEjaj1zjUPubf4t9YW+7mePIFGgeLje39+e9DLUi+tpbyJwbdOcm4c6/qfZPOxfD9dXL4PioayIgeHG/r7hEwOsCdJGWyx0ha8ZRVtUjI5EpyR+1BbeKX/U4WvoPHEyAiNyDzFZP+reb+MzXl7e9QWME0xnE+Z5kWhvVl9fwm1RGkDwdSkVIDXEc0QA2JuFhwv+qmlqj/luho2KgWQsHHuxX4CgEWOOhxXaELzas3Y9GzkdM+OLXnvU+0fM+JqjrKQ52+d57iULiNsG0E79B0x5fgIC4ZQfsEBDBj9bXreP37jbf/rzP61oR0yB7JBGt+RyYztcfRX1+jsWr/WtHN0AEnhLdDHpb4r7llM3lI1dTJ9Vc+8Vrt6nPlj/cz1764JbxRt5uOvZfyTggs9x+PFQDOlTpKW3lE0WNt3M922v+7kDNF0i9ZHvdMyW5ZiIQO1Mni93QnEYLNT6lJ7N/QjjtXVPnZ+H0S96nk153szoOs4tUbdrcNZijrlvXMb3jCzwneHMi3Ohq5hBtWCiD1gubtFu7lEuCtpdw6LW3YvKfANBybu/LGI8VGB5mxUSMnrYZnxhh4+j9/vEcFvFI1lSDvudYBy2dt4anr6HHoXWElmwVuD6eInQiDGTDMejoTVGvfiAjwR8ubrCDsCJPn7v9MXzA2T1Mva6w3lnZH5FeeaNNQ7jRqzxyEDudMazWM/Z9zoWrdrZuDZeZxQI1pa9aXTUCQMzs0eIeKoFFYyickWDcZVOAADlWObkA96DmbHcNyx4xLuLD/ivm2ucIkyAD46OwV+l3bslYWpO50c/52UBkaUvCHpuCUFYT0hBo7PugQFWzCCilCLRBJJxN7MqzjV0ey4Gi9wwyOBFutZU/tH03JLX21gLpY3IRTNkgo9uHvYV2ys56u5mvecw8uoVCUZu3d7XF2CDrnrmdW/Rm3T80WCIv9WX7zxDv8r/G+WXAv0/qATgG66rgEt8tBoWiPCMqoTkEUGJCF8ZhDabtVJzBaMLmWFMJHdM1Jsg3FDuSRTUUQKBlBRniHCJeimCvfnqA6BKdHuCEMKkMfDkWJ4HazerK9bmt89XOPp4CaKKWinlnZUOFFyg4dqfefjzT2csbklC1X+mK1zyB8y4xu6vGUe/R+A+IkKOJPoa8PsjINrCwzPCAxwwZfY2c9Vd+841f22x3OgX7QwL3W2GgHdZG8l4zgAJJ1UA5ltM9RL19wrQoQiH/7xGo+/31s9vZ5ZcWe9BOPv9d7cUbE1CFJtASnLsMqbzU8y3o5X295UnmAeL9SYxtqpgy/0JYnW/9/XmKH0bmDD/mboIA5aVXObVb/ybygaMSirMrsoPgLO9JbdLwxsNRgRzncKzKpdO/pVSaPa4t/nOJAzMAhXvzKq8ApqYIJIR+WgTAb+v+CvTRIjyud8vxheZh12l2u1fEaoKAxVKUTXSIAqmJTcI3b2pg4wmAmyGeqYqLG+asNuIZFrQuEoOa7a84wRqIjhA4Yi6BVaGaJKzoEwMiICmCgMOwppUW1Pr5Gvfh7jTkGbKGM2tSRtqlEOaM8vqZMWPCKVlHlYeUeqRRZprnAqDqUkoetYdSrrX9DcIHj6eXMBjTHryUTXBNivebAyqQCgpE+NBYTDCsD1lzzaUVpBxjO0L26cuvNdlFluMoB82PbhMiEYUodMg7+Ein1OdcHB4IEYJLIZyBQV1ktDtpVbJhV6lfqMCogWmGWpswmkbD3fjE4GoGVklWEDF88oazpBIz8PB8mGFMtjaKkjh3G2OXmBo9zJ6ey+3Z++70UcXS9HWeAP/cPRGGH4OOCMNpt5Kf0k3ilchCUnaKMLV6uu8o+apY7umgGTOAZAqaTOOY877KLH/2qYLClxBn0HrHlzp/aFUtwfJ2Vegf3RDwdJ1ivra6mFs5LqnT+GgA9wrhduAF9jhisPJPYimqZDLbrfWPHR7B9uLHNLWbITRaMaIZdIcxtIxqbfAYYukohA6xzzFHcURoTBJ5IyEGw33yHhshSI6CSnOdWWD4rOmntdV98eolN+H8noUyzpPOxDCiO3w+ASggt3XJ5jQqnGEukceP2LNGQZD1ufLQmFuLlUQGk6HkKb0gBtBUry/iQGmhA1gV0Z0fVrNQILPFGcIea8h9qFtLRsBgTzEZN5zhGSelCbXhXegdY5wLYcMfHuGoLOR2KwdbtTw6De63w5h3ui5jX4/vIaG3CLFSN8j492GBa8v/fMuLKV8N0fpSfWA4PfHUvIiBK3p7bL80+3lrfYS7pJd8SWM23UOPIrOQNM1hS9E5HtDYPIjdrcnomh4LwLqb7cz6mlBYdvfokQXeroAjTUdG6X9rX9s68HgJoL5hgfpQ5ov8oHD4Zf9/ZD3UYL5Gf4Tp3zmsLXlVF9wtcmARk/0jCfHSFZyDpOBRBoDK0J51wKOMISmzPaSL+rRf5W9ZQsueDE4nCraGgT81NuOHBNO0H3gtPzGGbdfjxvbNsDyGWjldZ6fXpcbusUf+KRRtRpqKTjAOS6YcUMvy0Yyi7PvNeNIOM+X3VeYk4e3ijvEhOmy4OlG52EPPUfDbwOwHV1tjO1QVxRlzT3Qe6/lHAYecMsKItyDN9MivlQqgPpBIm22dgPzQJfyHsA92p2edxRMhftQ2iT7a0njdthD3A3RcPzo/W2Uu+zXl6S1+8sDSf7zluZsC1uulOeMsDnhuJ+NV61BwS/WqNAY1uMCgBrj29UVwGcAsRtgQGnVLW9qK9lxxGg6l3UY/Ut93CeTEVi0MuNvGPCIdzamFX+XPtxIY5AP/AwvWcd5e66v6zsxZ53wflcQjhS3ftt42OZlwVcsXxiH796niALxwO8XF5h3M9oDoxwR+EnuLZ6Qpu+ntZ0/u5e+sGXttoRwzzfi4LjMR2lvMzC1aha6Pc9LA6ssKuPywP2L7ztzcGTnLZRA2ugtpT7Je0j3XdAE22Tgf0oJeeyPn49f5d+j/FKg/4cVMzw1ZI/0wcxYmFCoieUUAwdcUZSYmNFA2ZPM8iMZw93YkVUzgtQYWwSx9GIfkZkuQTA9Yg309X//+gcA4BIfkIOEEQjT5Sfsrv4EAByAsIMJRSOUjz0x6dPfwKjQsEN6L4d7Z1Wen3Pv8Z090Z8+X6EAmD5eilAtvejwtwkPf4kC+iOLt/mMK2+n4Qrnyuwc4BILrsD8KZaKem8FI45/XNm7v7gXOfW51rNH+EIihFopsIVPcE/5t5TniP/7tHUfCHivTNp7Xai9Huna5ikBEwPLFaN+kt1lxOe7Pz7iabfDu+tbFYFst9OVZ8b2//3+BwBgyVaM0PzKiRAkSE7outHGSyUrCq17BGAG4wApRYClXSB0ocDacDb3WQi+qi/Ymo7MiAYQkvyXYWSShezrVvtpd6XaG/uGrf69ktg1h7pVX5x+DSFTLtmIZuNm9yYXXGC0YEwzSCl3OEMVdXFQO8WbMl0AUGrdaA2oBwcCbxeNCFCKrxEY8puBZdn5ONdzaKF+EyWtzJsLcRRBeGjdbt4pCXPYBQEWRhYEj9Yg0VDCiMAinzha80Tp5ByUeUGb0DkrEWzf2W/P+UXyDtL0JoUkHDajopEacJWi58fqMpZmYbgBMKnBjHcWS1t8jUsSpBSqMLE4UQFpyK46TcG4JIYeYFd6sXkAituong/WeWPUnEtbJ75UoHGFwD92PZ+ln2CIEHluolBu1HwvaHT7fiM5w07dNf+qzFmzsLikgt0GEDXfnybkI6VDssDCvyQBdDElp7/ZhOAthAgM926Xrd2cWezUA8TgqhFf9Gqdiq8JCKi14mia1FPTPGtJlOelgiZRopu7KnkOvYC7JgihZvszjVE2ksxLyWOP72R7mQUomfKwEwQOAjpKzybVMt5enkOA41r1tBsRNiO7yPCG63amR/ifHPntDKzaYzFSy/1p3FzRKmcmKMtOKGZCKJArDosqY7fL9nWyMaxgXX5yvMHdUtvXVS3W6eI+5LrT2fpAaw1UqgvSsjFFGAxofxVO2h6f285pfoHN4i2+tEXpJSA8NRU5Kszz1O3IAjiZiGVZMC8NB3XC07LTvJkQ/ANohBIW3kNhDKdJMRjDi8C8BsujbnMj391YQmkN0rzlVGtgAAKAEpG0Am3q+Mz4Ki8qiZGRCq+yUFHgUUft7D0t4z3Cga89A9g9PSlnEvDDcN1YbC3NC5zLBiW2s/6mzo5FF9bPDhVwKRFpgBGbL0Ua4RbKOrSgp50H1O0BFuE6ILyWLwHEoANQ+oADQ3fwIsepNTqSqBMUf9P5ObSjoNFhdstO5lWbMNPklJZrBwAAIABJREFUndMzZgSxBRv7ueT0uUtPH6Sb9sS3PLXjfHdF7k6l5wKWtF4MDo9nnS/Df1Udz3bL4nuo7+0ry0DGGiVqqGlsdnM7ceIjnPwVyqtSSXx13yAzu1LuvR18pSkbfQkaLZ7AV8Vpx6Y4H1oecd30/j2WhwcAhOXhBAvuQeUUnECYbNkGcMG823VKnjCYYp9nAkJgrZxjXNd0F3wM4AucVs5KEBtnV15etx6W9+WLtnB+eoblfsFd6lc8L/9kgbt5nm+16byJnmtFC6tyDELFO5TzglokysvuBiBVwv1IeeNu/peV7+knI3kw3kgqq4b77pQcfPiA5XrBrHKPcfq3YIzvRdg6K55ieGQlg7jiULth2ALgpGWztu0S9+783fmLGRSbbM/O66O+4/HzP4SNwwWaJh5qm4r47XH2X6JDKX2wjkm/t3XKjaAB4fOVG33PjIVucHsDR+TO3xrtsHWkrf3hvJMCne69YGeFPQd6R9Oje95opYmH9IavJPFPWcK2L9c3PtLpA2OZbwVG3ZHkkyYCV00u2SB0IR4Bfif92AlGbLqRn8mQGBOS+hkwLd98Xbkn2Vf25KJ0JCCw/X6ryfTboitk/OWqZuXTHjK/Bnmf2YvJeQ3HmIozUDPsGXjJDaj8HRvF5gGBd4znaxa9EZDPIFjF8LsUzMuSG5M2PF82uyxhTZ8qvv2bNaKvbZ2Z8Y7CeeDY8KfCsqnq9aFVizb6lb/iGxjHrWF3f4e5FByfvIeFs/tyewOAQXwCIsLuq6RbYeXRs2EHELBQPM+DWDIP9NfM2z2JHsFo4Nz1nm1XOZF6ofc8DrsSPUcRaQpRmzZme8d3M4sDAiudTz46BmhBMFxCscm41mOyuQnZUn8u/FgbXeY8VtBS31MSNfpdz7u8rZTuN6xFg8tvVYa/8Fw2NvxV/v3LLwV6Kq50GA41Z4nKK8qzFlrp1vcQB/vesY/YTW+DA0VjlGxYrokSBL8wJHYrCKWw+p0DJkXqFeFBYBALI2VCSQvNGACJOomRA8FEcGq03hgHDCEMFBaAr6ocB4ArXOMDgHb1AUDBgissV8GMNIgi8RssPJkytYpUvoFxAAmpdkXAB53LWd9XyW2s/Z1bSuFrRYqAeKMfXF5gmqaA9YUs8iT+olCc2zNXSvzlPHlLa6i1+Lo1CJH3WqX596GYvrhwSudufP8txHjgA8scUFpTWzpRiL9+v79ufNuVLKx7EDz2KV8eCkkIHSWSJwqmiSECLAZhYuDmhT4/BxZOc2jVTPgg9qBPVpHcz/WMcHL3mjB3zxf2z9yOsMeMIB66mn8bbg9b4u6qTwo2YeNIbHB0NX8AeAVRZsBg68Zbxj1O51CMsH9Vo+l8eNsED5FdSFNpQGCQiXkJtlcNmMqhyx7K8Q59ZhDqvw4y5A7mTxruZqFKXreecAegYYLXc+7d80ZVpENxues/mfeLVTf8Brj2xlaDOSl0yCKCe1uk0o8Oh5b+bJvHk8y9IFBm9ZJYFnARj2+PEkIBgLqhsjFl/U1jxAoIXAoqFYBKH01AQ65n5dfSFvHmNGYPEvK5E0bkefJ+AGwKA/2HBDwY4oXlOjcDm1pVkayCHnnAPDLjff5yyi8LBivjUk5tudIy0w3jVjG8osilqOc6Wc90H0i4ckZpwLKYBT/ApB7grQc6oSyjEELUqmGbJYSrGDSogoPiNIYhge79pWHBrJoPoYXmZUGbG1qbscy6Zj4D6CIEEBWU1iSFjsQcBloBUVibZ9AZeyqEJNYb7aHvMZ//WDCdSvUS0zM0wtHu9wCzMrxzpcIgmGElXtqGtH00rgzDifE9NlEMWOSGoU5+KucqZzAKF10hW//1GEUoqMHuqYjwbfWehCufE4AhZiX/3oejTPjm9PIWokt9GN+y2abzL/CxZyW6KbttzVrLCtacSkmNu/Rt5mkDXlx4szn+1rC0xfdDa809y5gZVHqBk/fNhA0GnEzo0Smr7SykT4OnOkfubULsEQgEFhQ0EMALgAZCzdAARKYY36ZRsqZ9aWJYNOJeMToqoZAdBHG5SXl2trd7+zY1uy9fQIcHsoc1zDJ0v3bjjx53Qle7zhxfnO+iwBEucCMNZUsAcVP4lI0x5brAm4ZxSzsKtzkpQZ/RErxErGKaak7tjfOu/TeFAxJso1EYnFFnwjr7Tosr1PvueDPj/a0yE+FgQyj9umI8nu517UMbJijf7+5kBlpx+EvlrcLMXtjY00w+Xz7JMYMOd2xvc1KSjIR9+pVlMpz+xKs8YR6d830e7BKJR+ruHh5ctkB41L2jfu3Wb4tg4mc3wR2OM9caS/qce6N7H904IN5hY0x50Ic5Hb0NbY5ceJ/W6QgpHQDgMC6f+yw4b/dqnKK/v2YcLFX1PPLwbL8aNh6XGXGvZLG+HrPADjo3RbuRw+9RzslTYY9H+z+59OHPT5E5ybEs1+GJbGUl/+P09MBTbeIxaaTDJZmGY2actH6tx75t4oD0ucbc2/Xu/NuNhjqW8o4ZD29VauT3JJbLpmQf1GPA9zkjFOxEhPeNUegDbjSapNyA8GuKnAwzdfh9A8a6oXXigeT9cg4XDmUst56e7UnyoFMas8vPct+fK+91ntuN0AtuQGzN3sGV59ZXgLEDcEAF/Eigd48gnHah7n1qgqj07xtm+Ov5Qb9GBitPLQic0ir3FHQtM3nea+MhbUy5Hf+ub7DUkDzUsd8PuqAr+YXDbDg8Nfy7tBtUvvD3CD43Jfy6L7lkHMJuhJ2NEynxoakvSvcyx1udr0PwiINkZnNuVn0a8FH01egr2795FOljgEVej6zN4E8z3CgMcJLJjGeXGX0kNsdf7BnMF2ZNO8GYH2c0PKa1AiwXOiFohddRRa8o3m8e0uGlQaYScKP0it5m69k673Pn09hoItaAd4HTQZGWghmW18bP8ja2kXu+rhRyEjL+AOtzun8eePv7m8se2KHwYOzMqyIncEoImXnkZ3rAlNq2udTP9ZkI2upX+fcvvxToQ9nc2AMSBRLyytf2tBkHkGCJWA2wfw943negt65nosWoiNYWP+Ai4KEYigLntijyboRSlVFXQXXhsGzyjyaK3qXNmOdFgXcwtGUqoOQlxjoX1LvEi+NgoqYvEkFjzxZUfP38Zyivtf41gHNco+ISdypZOGtA0bziM/+FuTVvp0GIPAZwiAvscIMK4FLfObPm9YEQ0hMRZn1nJozHYt7o5wzsrq5BHy8lZyTLXBz+9gkf/voTLdW9JeA3lrDzdwSc843fO/v8GaefPkGQ7YLp8gPaVRDuZsX7vV7opwxMOMeMW1Sc44Zu+wpsCFsU5WfKhbwHEqMgoYnuEBa7+ihO2XKn/xxyJCsRnbBNkqT36fMBBNMTd0S7KxUB4BZEv3kdAoCpYvrtA779OeOC73H0+yX+8deVjmnPGBJD6VvTQibpd3ifWfLp1dqF5EUa2+YrBoS8VaPvQfxymk09KtjbMaZ6m8H73pJ7IEKXmAdTNLJ65i7cYLxhG4j9sERO4zZ6cENuLzTmhktE17cBeCB+yh540Wa6G2M2snIlTPee1v0mFyYHG0GkqTBKSR6Wzb1mbf18LQFXsvIixkrTQaR7AMTjnADPXRtrYg2xt9VJurpBBtCbJvFkXNSy2T0HuReIWx/9xCehTP7M3eHEVFE6n8xWXzzPAcmBnt9hAttOQEKmgtEZ9rFyRFJh/U3yCVjYZlmrQkDhCHlrOaDKoShSaxFPxvnb7N7opRRwqZigHtuUvPcS/jBiWnIBM6gQKhVwFeV5KGQolLu6giYwtVDITZWxzBT0O0v48VqLh5XPeDuUtQA4lNdUI8+s4fBCkvtX2pH872UqaEsWsCENjp3cYbIgfKKEkTUKBtXhMSksrKS0RuASz8Wpyi+VWev+Jl9/aHtUJKx/oSI67KKel2CAG+ZZBm554S3nebG5rhWFZO6mWjSMO4FVgd6I8G2eXY5EAEoh7FoDSgPzN5jghgmev9DOytPuG5Z59tQ3xkT7OuufKdELN9RaQVx83WWNSsj8weCFsbAo6pm4i3xQkjGG0a8cAEgXkHsCzHG/H24vnQCKAzcFw97VdoFN5KkO2ED9weiQhwlVCFDviUX2SRjjKxYzWjIbAiQa1b7Y+TBlToJJbCH2NWd4KQyGRIVphUFcejS5wRvkH7xxbSwjLCxpP9jYzLMhN0Wan1IiIJDCNMWznNqVSY41Ifi6Z96EKJ5xT2D0ynO5EmfeYscUg7OGwwiwfOINAC/NBTfLsqAUQmsLlta68QeNZnNRHK7VSpJr3HsGMC8wQZn1OE+54TxxkmJJQ6H5yomqjEBhCWjx81XLpOsg/Z5KwULiRckKqy3CBYgwlVAEGr4FAKoFB7V0ofzZ9yAHvUCE6fgYrDEoZ+yEVWyMclixfJtl3r/OODg+URuSXuBlONLmorXmdExTTodnC7We8DAfAtiBda0sDEnVQ7Zwc8mzkPHpbFv/u76wALIWe8zSH6A1yW2r80W6/oXFK52N0Oko3LgWdJXu0WRU6EpSjj2603FWpQer0kNGP8x6f60Yt33Yn02LIZUjR2kPAUjY9gbxaI9W1vR8STB5rMANWOad3pdrywb8YPTC/gxHp2napJsX7s8bkMg9SqFneemMBCbl3ecVXT0iBe8KgDDEsXNoPEDT/e9PDwScXb9nO6ty/Ui/125lGIdQuKNnsIHxjUjy1DsPH0g2QT0/5wRguVuA09qF+heanGKf6z5d7kN9L7jnK/oTKW8AxAvScRiAL96B4hNmuFCeSvT0sJcA4CuAd9pWY8ZXHs40Av6BGTd8o/dkZO8h43nQ97ig3fqScbvjdXQKPOS6wzYoDBSJHwAw8Hgt6fSOLy7A3HDKInv5spqvofln7v3dZcztvRWqfF95db8TAfNIoUQXP9lT9zy3ywWncg7Ns5ubwoD+jRJRiwLfk4UjlxQ+AAIm61o3o3+8b7Ku75rgksaagZ0Z74wP0aqn+rviHAAw47b7Tfrb4NWEcwC3SbZnHFGaEC23pJ7RONNzP8inXlEMDmU6u5uxUZCg/B9DQBKz5Ft+cp5J+lHUytqV3hm2KH3pfJXhN23bFOdhNCx/Z4eHuNtJzJKW6KNlWYZUe/EvhtlbmGNfOL0LlFLDqcme0/Yt7zlwh3bdJJT7RQHjXuanEMrB5DCJIAr2ZWmARlcsdC7juSDQTU/XlZKVdzpnDpNj4g3O2qXxLJ0yUJm79A9MLCYnZPA2SgGwlAIm4GaAVRnOvQ8yx7tk/bxf+5p0pQEeNttuE5F7vnuU0fT6nJ8692VlGKNtCX0TBhamVKU0blOcN6VRpyIhaZruB5PA275s3LAJgQ0/88a9N5bVlCldaPuVjV7kqtHWhA5pLWi7d3buWOTMJpdvRWvYAZ9jPGJYUUE4wmkDFjziTp+bCCjHhPZo45Wz94XFka5qf7+OdJzOeRnWwOm0wXC9A97wpfYfNy4/t26QrzWpLKkUoT9aa5jnWYxVm0QhstznJify+eSmclQ4HPd0P057yfWgzeD1XVab+pUnwn7X7Nxhtwf54dZZjnMyUkt7kCztr2NT7PSO94H9waKyNOfLBvo999Wet7M/KtE7J6UMv8c2OhrqV/nvWH4p0P+Gss9Cax9s+JHyKquarlgIGAWYWMF4AKLEkjyd0DCrikyLhBJBY3AxwbgAmJIBiQJmkAg93FsFiHngAKuZ2R8DUrXEeFYFufvUW7cAzpJV6C0BF3yFig9gfETBn4kZifE33PhvHu5NIDwxY3njXJsC/PLzFervn5R4krC/J3/I7xMleP5xfYXDTxP+J33C//lTPOvPIB7uxlqYsmq5urYAAYDWOQ1cEUUHesrAY9nefmcMTLgAg3Ggnx/4HNejEh3RFoFxS6FIf65EGHaZ2U74/J0lhLorXI1TBMEJmKe8EUGO/QGI0v2MAb4G6A9KYWrEsq5SxeFvjN3nM/z5WfbUO8b+sO4+5i0Vv/2GX5vqlO5zCE/oFOUHQ9w9V4R5TNaDhcRT8gWl81vL5pbU/eMcXVd/LX6SZzgpPHggVtZ7YG/5G+Dvmt2P3z+yzV3waG0TRAFQCFQy0ZZnQ3ddUozZs/596GBmbsiJx62VG8swck7XODFGzH49GDIOGJAQEBfIHuz61jOVFlo8Jrcn9EfYIoxi7BO5r/toA35RPKWMKUJBSrkSA1R8P7Y2o6GK1yokDQozoXEBqdKAmTzOm/E1QAprBYk84l6yuu9Bcs3whz3DTUJ1tRbCVtsX7MIZgFB8NfOqxVwJg1bSgCW02yLGA2xMAwBWQQgR0Ew4pG0lHisvr0w5ybPMKT+6MqBJWS4h0QsyS0KkCkSGbRIXyBREH8STNQ/SBAWiSG8aaj1vlDxnMgeaZ6wW1FJRC6GW6nnQmShk3r6Ppcdt0VBnKvRqTmipAFJpIGaIJ/rSwngxMW5k81KCJrL1La0BVNDaopbPLNoIUqUds4Z6XMALx7oUoeMoSc+ygtWVTiZEb+l3Ejrt95QYz3i+OVxzoIRVGEu0xFR3xCnr9zWOehFS6fiMxhxFkN5/HyuDF6W3QChuiFBEUdw9viECSB6LRP2ctQwnEYZea7y3DYNfjVOS/CB7o3XfQSIwJ+vBoLTUZprlm9d1c88V37JZUbfusHktx/5K3s5jt0fcpfAaJO/1+1Zfvdgrs6aFKJ2SJ9c3/MZEaPMMKg2FJDpUM7inBk9+DrLgRJCwejc0hf/Sva0RyRIEHpF3d9u/Q1gEAIcKb3fC85TDQ+XTGNPxCXaPj6t39eetpzziXLbh066nR5n9fDEDXBisqr+MsFzg5sdUge4e2EAKUwF2jz7LFz8rgJK9CfcmQzLgyN/7kTJGbYDBcwMX0YeAA7mu/XrOo7wfTP9zSs8e2PvX1V5oZvusdzW7ZeV8J57UcyZrYzA3Pa/fCxU9K+u3GVacxx5RgOF9hYfb1g+5p/SSKQGAAR5zgJittgfBpi2ozbWgwHj6SR5KpEAIQinv09Re4wcQ3oHv0pl8r7RUS+NjxvKgIYu78T636ryan71jHMpIu1l5JMKxXt/0QNe+ZpwcW+hE+q80ZuC0Pfh9aO+lIr15AG5OQeexL0n3YT0/B25vXz4o/6Jy8mpE+/PKuze+k/FMqrrnnttYvxEuyjIR3jVVvGXBzQZ8DSXDGv8810Va/dqeBAnLfYeDi0t8uBFnF+Dt499sXfmErj+O0/venfIZCMCCOzwYLMkKlWFMlP8Ikf5KeRpTnJMymQyAVXkehmnyfQz5HWMKGJvPv9MmbHwggq7qhi9X7gk4vblFuTjH9MF4Prm33NwBxvdBYZ02NE0VrClFWAdayjkK3W7OeC+zJpgm3OjEsdi4CIRzBgqL8YU8fQ7GrSvTm9fNf6aUB96De0cjB2vsErczjncyxJSlkxVsdzJwr32yKXtlnzI0t3rPQCRarD+Dfi3xSOaoMRqaWl3HuQRwo0jFIA+DdYbeIofdfyq3SzaCCfrTO+l1XL4xvMj3lvEderObW184fdBkVgOyZDWMq+8LlkFwy1/j5U27dtA/vjm66OxPKA43U0k/R0dNhwnZ8FjlNSBylYrxuB1M8N4nPp8zzJB/2gv06NadkK33A3C8sIVz9s3yFmE6EqObfbB27fsrPMjfqNMZFek/Wn5GG7/Kv678UqD/M8tzHOI/sRhx7D8yhqToprK1WBpjKg0m+qqlohBjbs3zNbfKaFxQW0GjgpnnHqJxD8zHwpwRU3ToWgmP8+HB7ueA4e/skl67IeCShRyeLj9huVrQcIWCD2iqbB+RjPimSDs7RzvP9OGZskCsR2utPg+AAM8CIar/16fffR7+16dP+N9//ul5fG4JOOKGCeJtVy8vcXV9tXrP6dAhC2FE1C3vqszKjADP5CnXBsxwwd51T32uJZt3216ZWP1n4ArPjU6WD51wyhSMlhOgcCapseT0LJpvGFAkTHDlzB+/fcTdP/56VR9eGuaiuT8BhNDXCEGw74sTpr1h3DfXcyUwk7JDIgxZdHiWN5lMQQaAmZ45oT9WHBQwew5PSv2tpYIIWHY7mMfbP62MRPyrKm9wouiZqFzGa6EQlrtjUzY1pmw0z1ghoMmtUs1jwDyOrBelZIsZQimWzTm/IAg4bkFyoxWY6XR3Ztks4uFr1AlI88HnINfBQfgHwe4DTGPWWUoT1VpP6HNzf/LVeOzMWjGDGPc0BdQ7MzGhbO/rlRICHgTfiQBJ5r0eHWh+MVEKlCLMi3lGNlRRnjdRyhBmoFTMvIjQhIuuRwgiqMi7TdFADriDAQQH9rQuMzHa3NKc5rEHEyHW8dKew7fkiuHWy6ReykQOl1zhZutOMi/iyWLLa0pgeJv2gzrhiEQOaGyebqr8LuaNYYp/UoFRYjA0F314dIjHtylihCmEKvfE5C72pvSvUtEcgvB31BIMaikF1ay+a8FUpvBAL4Raq1qYy3qF4D/CmLoXJeCKRtv3DeIZAp3f3G+nV1iVTK2Jwr5EZA4wwJVAaOIV2q0fVBnR4szYQ7LjQgSR0orIc+yfpiy305tOsQtoXirumRuvz3dRy+TzpjOgQgFO4XLjL0cu6Uf1+pLnKNy7+RnGnoJmbQ1czWi0g+LP9uX7MJjBu+12eKgrhTCSCQzu8ENXCCIQ5MBX8lBSGrtwpsdO4nBtAhtOZye6xI2BqlA6oUsxQEl1OK9LzGVA9n6P2rOmeBPatoDVu7oQafh58r1q46FhvzciFG6QAKQEsLLCC6EclIBH2odZc7N/230DmHF0eOj0oc2geOk1HNj+1h4sGafZOAclvwnSmMW4hoAOFtrzB+/eKW1AXXtbhQ3vAgBX8G6n1XnY+k/dPnDhMWt8AYdPsTfZ63G8LBXn4phxeHio6SrIUK0KpFnD+Ot8aLuFEB6/UK9/Drjr4xveZ3iHgYQ3pOJOYQcN+Xur71+bz+xqb2/pTonuO4tgw8gxfwxCdoKVxFAHxLNbLepAIjoYfgIAVs/vCQBIdjpRibQE3I/H+rYMnjYEoStqKXpOjL+x9CsMcPPnJLKRtRnekkY/CB0QOVYNH+VtaSvm06m4j5n9OQM1Em0nJn4fr2hhy20fWNIFWwtblyOtV5yXCHrLxptf4fQOgAZRpAMAP+SaCV8NodgHMjmZLMq9L9hXNhQJaSzd90xf6/WvlOmcuK5fbGZge+4EhEduGrqWfZ1OmPA4IBHmvFPlwn7l+XidMJ2fe5qOg48fIIamEi3l5vZ6L//0ryzv2FL+vYIV/JGSBpoV54FN4jeARGvf+7ef0T/Dk770CfcTEb7UonhN3niu8JNJvFrP+QwA0HCnZ0dkSYcXHwAA326uFX6da5/vUiy2c7A/t+LoVqUB+HLzGVDeg7CdRjEXBynpkMoQ+zNN3QOIe0YGFeALA8z37lxjcyQ1B2JK6QL/T++ZB7HhK0rw1N7vObpZZVjMEtL+GVw/ludqrvBmKg0Abm69TjkSSNoOD+Us63+NxQP8UFuwCCnt+g64OEMtBfUCeHfdcE/htLXqS+IBXtrPntecQmFu0QgWfdjkf6dGHyrBwix1KLfDUp+ZXZ7JkGghtmVEbpjptz2dS8+PFEMD+Rm383ZvuIT7TyvjXPj2SDjUcJ3RWUSEiSy6BDpkXKmAFf+3Bkg0uoavXY704Z1JFvo9xfCuD03poIxTnO/1L7oXfCLtABIOT0/xdK/wYjAgWNRyvqhsYa5FohTgCEfnx2A0LPQO5+UrilIHC7548401S5r296vx862fH6s/63UPrZ7C6wPo0+5hXN/YHaecIpso8et0MoIfzwSeONIVFBXshAhLaDRj+WwK43uYCRFZ+3H/Z5axPTeBGfi9sZjBwGuM9FYvTFO+/fx+ZfpzsGd8ZvRA/1X+c8svBfqPlHxIKVh7h4ccwhytgn85iyAcNgjqYZMAgTGhVswLnZvkRS/L4mFAiYEDqhrSnNFqQeOC1gqWRupFJ4T3iDT30iCvnJqGzyi4AJLi96Wy4AYVF2hXjHpZwVfAgmtXlFvJDExBZlzifv7+EgEPiAK8fr4CffyIUsmBvXvavIBUAGD+fIXp90/y/epqBbhNkd19ah8b5No+a13r/9kr5p+x3/s/l043tbqpbX3nUXB+iAZmIBEZ752o0H+or2MWvw8Azomw++saR58uAYqQwMvSUErB4Sd56OJ//IHb//tfz/btjAln/+N32E5algXLEv4cX/96wvQhwK7AiLz2YR34Zty8hzg4GH43dHzyStj4swqnL678NaLQ4CJFyK51TvZ///KaKRXClpxP65RbRCL0VYbImCU/Q/YsUdow1H2+dlldCJBI+Jz3UStpTR6u6ZnkLFQ3uB9/HR5Ie17KWmxlobtjL3GfPkT/7FrPvMp4mGxMOheSjwTFvNc4zxQcXFD3r06xMTCUDQgIODoAsIDnBl4CpxAY1BioRRX6pPOQNU7aOFiAq65l9j5gD5YsQ1+WWb0vW6QPsFGqdKGoQjo/7bSJjdvoAYeTBKKCUhHyVwpGK9M5tlpss2TTyUjhtWVfUyW0WeCpzLdUMuW57O1+p9qOAQBqsS4iiCrIMgJxvmadAVLlkayVedEDEfoNJrQm8YZkKqi1arj2ilIqplLleQ3f7l74Ol4JJykRB4xOYjT9FKZa+tWHLCdC5KtnOzO2W+TfBQRemtMnzNAkcDJXy9Lgccx1Yc1gv6G3TpdtbhNCvucc/hq7znE9K7Xtnp3e5z3tYn7YDpbvbxkrldgXcXjhocd9orqdkC/ZGGKMfe01tItl55XXu1v1K7xy+KpzYbCl6Dnse7Xq5nYPnA/Icz3U8rnPFxC04jhKTj5SiZ7MfQnewyAiD62geweRKd3ZX5/bsfpxtjOP09A0bYTTtqlOAAc5R5TjT5N6USYizs+/tUMEsyaxcYthUIRcJtN+QKfC9/iwHDqOpvuo0A7EB6BDiSDRAIn2YnVJgqoMAAAgAElEQVQJaIsaK7HkPK8EUI1YVaUUScfBCypVmHLUZ57X69h5Eqminw8KsBPDTiri/SqK8/W+fqnEnga4Arzo4uW9mP7kGROSF4+6EkK5pE5MuJ6GvuWfbU+/rRuZ7hCDFflugirqjOxiDzo/bWAxYThGrLHARoFHk+6rxcdu53GgkvxgrAGSt40NxefmSPONjZ1I3a/Nc2eb0HBJ0O8jNOaonq8qsmvKkxuOtChUY798jmFwmbv06o5wgDTrsdaZXshjkxDia4OfDjfZu5V+yRMyylQ6vKJKPZCEOD9CP49+Xx9jxL41w4CmXuWMx7TO6xK7wvZ/D3qp2yXbOGmrPStO5wO9DGnjuYwzeuV5wm3+AOMIYWBkb37Mm+4VZdz3Y7+qXixl626U49Ybib8dwv1IyWdb98EAAvKxfUvfnq1L/fzJPuxnKaATg3AKThHp1hDpe4qcace2m8YaAIMk3D+Ah6oOBq1h5uRBjYBCuU/tJkvWeHU/33nNWLbkV6ecoxzuH+rel++pmutS/uL4J86Uj5zRwbtiPJb9BqmThj6X6poC91bbYma8Z1OgsUcLHXvb42ysaUUDQ4Yj+06vyqN27p32e8essFHhCFn8G+7mKmPPdnOH8uEcpVzg4MMVzq8Zk07PY+n759FiaH09/z4FoSbP8zy8Ruv1X50l0kidiTYkAKdK2Bj9eE8iO7xLeOi5+col88P+KKMzuADgtPGoPM91aKy/cc+vJkW57YOi8x14bVF+zhvd5CuCHn3ZieUlepS5XwVOn4aXzLM/G1J0bfiYGfO9JULhJCmKuctzb3Ko6V3F0maUUnB0foCnu69oeEr8ic2T4dKtczbQhn9LCTow6Cm7JqOzlFiOMEpBUaNz1vNte87O5wj6ePg3yN50Da/a7oE7XlNXow/pD8U9TkW/ogV71563jTS0vce/rk5NFB1wPi+vL2+t/6v8dyq/FOjfWbKFsF7oDuz+ev9sJmFdTAFugiwHrqR/CtyIJSzizAtoEa+5yi0scBpjooKFGI0KWqlYSkOtk3haLazCDwI3gEvbO3gXhO8hFgKdW3jXgg8sHupeMc9tD6txSwDjChc4w3zVHAEXSIj2HVgV5mI52yA5u0zGdwjCDmtE/dpyRcDF5884/HgZeUMcGUqHrc0v//gT5xDP+XMG3n36JPcZnoNlHyPyniOkuzXPEOZjC9QXBANyR8AHPseS8leNodzvYDnT4bq1bPVpQcnv8vxb/wbG8YfKOJi0Dyj9tJxUp/r7cTiLRIQ7ABcgLMsNCB+AIv4DtRb3TCgaGrTyKUB33av/5x9/aHsciigttU7qfRMkzHw9Y8aMk9+O0BrQNI+n3c/KiteWlUAphij9mNVTZLJxm0eiT9sb39iXDcg3MAEk3j46P6FIkz1tub4mqqq0UA+VRFX2grPv7uq654Tv25gblOZanMn9nbHfiXjbgivMHLHDGR6+fZkbuDIOpgO4pzABbVkAIkyTLvSIb7SttghkKxoJwcJYl1oSHgsmklcNeQe7aQgvNUZmDFcM5J52fCf6MgfjtY/2zUJDY7Cyr1rnXeFj7ZnF7ElIBEw6HzL/mmuYZN8Wiv3bwMkRcwIfiIB4mRfxqpgAKoxSGNgRUI1xlfeZUlY8wUTAa3jJ8hbaLDAsr614QzMIjRaZK0rW6HJYUCphNgRmKWhdEGu4Pzy0qJg3vBICBPee5EIO35z1YVYv+wzjNSe3efrp+yTyuPljRB+plC5dCrMJIhLC0qW3dxeFLaLclsgVsDzyCKWve8uBkx1I5I2zKBzQXOe1FkzThFonlFrFC0+NJcx4ohbzHif9Loe3qTawLZqT3oQZgwLdFNbFGswKB1LPDtUjLqWAF7WqL2Z0IfNnlvFcFt9HebLyEZOc8umPGYtGNugs5znmZFSme510bjbLhhAsnH3Y4XiAFjsPqcOJiLNnBbxlJfQaGHAMP7oyzEUA3DTvQ/8NfoF0fqqsQysNaFX733xPegdT2Yblqy7HHIxD9weoX0sgctsZvJCLKvxp6ZkgAhkpfLvxJJTPqb0yUR5pHeIM6h5acuh5NdAxYavuo9JIowfIqQWFl/XS1ABE14KUJjDd/dHRMZY242m30+mV+TVjIc4RGBiodAgAWPBNpWHa+THH+nrypRqzpN8QF180S7thuIQE3kx1EvqkMeoBCUJmlv6wwXH2OV6awOdsLLZ5fgzfQNENDnFwVBTnBC4zQw+Dv9ulN4phq8oVdLB46EoGA8cyV/w1GYZkYfxx6a7ja+BpU8L5O6yeDa8IfG/L0hkKGGwE1Ei7NTEy8yGl/nGCN04ToFMosOJgvzlSYRz0zThv9k08rxm9ZncNZ8KIrW1et3RjYxmhA2UeMHWpmAeSnn2nVTSHI7Wme8p4jR6OiXdSgj5Kt7jhg14+YIlwMr1/B/6y4KnzkSaYoVCAER237qyqgEUCHZFHSTEFJPu4Mt7r6cRxAkjPmMxD3ndwIwoz7Xwici9zQD2+OeDLCZnhoO9WP5PkbRIaWMbCjHHl7ZM2vsdMSbEcuEZFKnZ+xvO8Lx2MTwY/dr5GI/s4E2kvDwhvpLOZNeh8ut8Svsz1OnTMKyS67niamGMQCKdJGE1+/hbdVx8/XKK1hs83NxuY/O8uca4pX4J40lK6/l6vP2wh9FWbL1SxmrqR3nHsKWONCWfajsgY6oXklJ6vx7V8TZ9e6C5HlCfbT85qMnn/uBRUPsMBM1BY0gfOJtOQDhxcXAIArm4lMuK5Ks+PLi4BMOabSKsor1fPYf39qHD75dLXeVZxDnTnyP5h/4490BoZLIHyBUSklPwCNyTIRtnKu8n6SnqoWggW9QMIGvkhMDYAkaWxI27gvAnN8U3pNeOZGpKyd2vwRv9Rv6/3TZvjscMDN6RcmFFRgaJRhBARRJ6Yu3QHlmKz8Q1quUQpFyiXLClcrm4DD1kXE8zONxr3dJIM4xYEoF5eYHd9g4b960/dc2EAaB7nQDgMNbCEWFeex2M8rGDr/rL4PuiLQRmbVwnlHhtoVJ6v6dP1e0djKqUU5FM1wdN04LQ8EbCbNUJeEwPP2S0i4/1ZHrLP6PFtxVa7oyb8OkGMH2yDOgZWBG21T4ynUOqjQSITVgSd4etcCRMgcgcGvj3IahpdEfYDjGyvbb170isRIUfhYlW5uw9Bvnikn3HknOb3mam0fptUwuhTpohwZIYvdhxI5SatNZdNRUQ8OD/d2SeTnQPW+mk1nEcEnu1s7reeV/vMhol5fgpZNEGjv7SDSfYxzttekM76Ys4v2upcfLXc51vnd/Qip24AwMinPSf3eLPe/Vf5b1F+KdB/oGwyMwPzY/W2iIR/TTECTihDg0UG54MkjlA2hcXjYlkWtFLdeyrLGowIL0UE90UV7sKgKSIdmNR9ZSSy+nuAhH5qKPiIc/7sucZfU67oBhcsiLQCmuuNnRilPWjk6PePqH9dO0NsCOgty3lNwNnVZxziHNPHiqrKKhFYR72T3z/JvP35J05++y0I+BcYJskTFd+tn2No91xGn88Ftx7CjLGdBx3ajTK0e0/AOSJve1f2EbrbePTZkviCDnHl644UjUH0+gNS1IoLgN01gMsbFJyj1sk9Ay03MLMQVe84hd1ZjwjzMvuaffnzm7xlTRnjy19fUc8rlhtGOdc6zFju7rtz+Jry3Nb4BuDk2aczxPoZhLO2akQWYp2rE6LhKarcZi+8/8GyLaRGIpY6Ni7fePu7XlPjuanV11svWpPoINUek3SrSjySN9dz8VvQqH+pCJq3DufQmdwUG8NncJHH2grXKfZsEpDDnlWhXDAWmWDPSpyUgzXe4PskPd7hk1AUKF7LoaATUd+tuyrCjb01K1mCKZJNIJI8GM3jVze398v62USZyryAFgYWaYMbo1UCNd33JYSKFSX2gCpnGxNALTEcAeuYNXe2/mcWyOOe37Xk+ekzGSsX8FKhlQntC8At0TTDU8bkyJ9gYhhLrP21x0doyzrvpPMYgrvBy2pjjyp5pbiaUahqCHfWvPOA5Jkf6QfqvtuUmLK4FvM6FwV6qVXD84cxibyXnWmkQiKkQMOyEECz5PNddI5aEyacRQBFzN5/gICawuM7/IMo/Gw2l0UME1mV6EtzYMpNIg+4gG81aQw3ktK84lyif62FMaMrwtJ1O5WjlwSAzgslvQ7rHaZrzbavkcYc7ftfjj0H7qIk2H5b7H7G+05fJ5iTKhBluMHInhGOc5g1d3wP6xoKSmtoBJRW0EpTvBUxHUSBbYs70I+DgGyEfwE3Boyv9bLAJ69HV1pP+3R5rrsmWcFxWkszoBgMMDbH4QQXRXuK1xduGp5U97n8A/gcxeEtRGgWOpqXMLRILzTIyPwNhaqPzdfZCApV0Bfevi/h5tnDoZOOpfPK9JHvgN2EMsnZsTFlrwQGUGr19QEyTJT2C4LGsblBhs8D35gFlwAL7HeA3+Pw15Indp7R7TfdY8cAfw0jmR5fx1Iz2D3+/Z7/Dlie4b3hZe8njVABSaAmhnxZaGY8GRC0ypaH1lisv8QDZEq0f1yyTiVv+mFix3kOyLLdC7tKw+e+FmNEBKONADiNVL1/ugcM3oMx1Qm7edc1G7y4IKhkXxIRN9K+24FwoPuDjiv4izVF6b3bJfZWzEmGXt3ZUpjhMBrxDMHWNsFqBfqlaAQHk6nYfFC844kINe1b8TBvYuxs8FKvO3zcOPczjJ5J/UjfB3SzMRfy1yhCS2dM9FLp4LTjMfbfWunZ5zuBvbWJGO+++9jAhy/3d/+9E5Y5mD5MEPFGcVqhqSGhwdNiSoJXzdLfUdarRHvuvraHr1pvAO8SziajKXHm+863A2ufhoYJoty/x/cW9rPnMKuTXSr+VAJMcKfS+ZrKpqXwxgYTtuDfvvmzayFLGaGoXXst1ttfPIT42FQie15TbJx2TsIcN9cxHkPwVyESvEQFpVQPhW7lfRO/6tPGuCXxkpYznek49s9+dtidQ+5ypDBDLfam7OlL6zNMHY0j75ogkb52UMOwxiiV+nzgAL7ozxOO1WpXDPqo6ceIvP/2/q4kmi9PdFZ0k7rz148fwMy42ZPacGjS995tumhzf0uBE8AbsM9B5utg4khnWBMmVyagp5NWbeyhLV54f7dyi6qZW8G8NDHII3IPaxCrsS33nRjpnz1Kx7f0iznmuufNtK/+b+abpF+UajgNgVAKlwQrWjDWzgcAmn8+vdWuE4TONGOp3N/nB/TC/bcUHfLeJv2cD7Al8QyFoY5G2XmCkZc22fPE9YHV62j/V3S7qzxsetJ/TMXkfTZeLO8ru/5K+P6aWmFo3f/eVy/3be/9jevPtf2r/OeUXwr0n10SMO8vc8jX/pXnLgMWpcwNuRix1UhAsuQPa2iN0Igwz4RaFuzmRSwpN4gOooKCRXKtsDJNGTm+0LGebZVnfmfgKUH9hhtUXIJAmHAJ4CqaGGmgjVea8rziI2Z87pZk0bDw41Ld/eMvCecN8UTP5ZzxaiW+hEu/wdln4OTjR1TL/ZYIKyPG3n/6tNnG9PEjcPX5mfajmCf6vhDuY33zXj/AhV7ZDpO/oB8zkSnveyaok7umz4Gf/+GS3wGksPQgPBLhPfeh50ek/UAa8v6KMV3eohTJ2VZMSUGisDn+4wh1V3CkiP/o6AiL5RFyhrTfiBvQAAChXlQ83dzg8PwCUMKn3cUp+fqKPbVv+kwuFU0cgQAUzKqEUA9ESA7KBu5D6P5o2eBFCGo5WiQPLgFY2qzzS5L/xzjdPamZDGz9rH2jra47/IYiY9N/O+H4yJWkB8xLjnIbY8X4LkLmMl4GINaoIuQAaq0AEZZ5TsI44ODwQIUiw1C3JrJjsDn+TfDew/wBrnwxfNCxSGyKc7vS77EsHGfHOQYc7L2DEBAhKGjcvc0tzUOhIu/2nJSqND86OECliqUtci7Mi1/rudOuHiLLrbu0BUxmcS45uBs4EeLWgQJQkzQQXACqABNobhISnHXNqgpTLAc92VkQpXpRz3QJx64wrpAolSgifuxmzQNc+oBx5uE+wtvMcImCSfITN2pAS4ZVHGto609YYN7QJqSx8GJF2VvS51z94gg15jd2V9oPuTqzK9rzXmMArS2oVT2oJHm7GyokXZ2/zz0QkzDdoosWkjNUaxW4RGJAIXuGvC8AgxcRAh1UwsHBAQDGUnbgmdXLfgEWVc6rQrYtBluDcZwQVu0yry29R3PQa/dJo/c0Ck+hzCCbkijDBCmLGCzJwuo+tZyWYTnPLEp+IJ1hQgi8jCjxNTKLnnHVhis83LMzayHm9V0WfUTO+0hPmvBWPRR9/XqYbefTX5VyzOuUp3sb/c1wK8E+RgOWglIaWgE8iJKBCoaca9qeh30l1DtbN3vaIdfsnzCouRZ2McfTK/RGklcaMKWW7NWol+GH/Da9qe0+F4Qa7kbQ1aL4Kponc0WIiNGSKgQjtB8DybjrafckNInNdylgXmDC/OaSocV7KzzLBC6MhecMBLBlTyUXmrFB2o8Fy3IAoIEmFjhcoQJw0vMEzJrLt7Wd4ohYA8NxrjRamnYlcNAWaedCeQLqSQXDHf0dDr+25GUcdxoze3zr9iVC4o9eR8wMfOFnX2vbLEYu60JHojirc1Rsg9e2wDxTXsY5PQCwY8NNimM4Vhlav+uWjZWG6xp33KjyXWoj7WZM+t3C7n5DL9izc7gua1rNukNjtX4RuuNmc3PERYzwVI5g+GDWfZ+jIviEAagHFQAwW7oo2/B6/wCCO+e0xxYAX748QPhoMXKZ7bE0jq3x9vJ3Vs9EoPHsoLGUovwt4es8w+CNtNKfgIC9rOPYCf2jaWpIc8KsvQJ13QA3FGgaHeTJxt/R5LL1CX1bWZjbY1gpto2rfpq3V9GdOwrqH1fz9kwxPIv987KSKa2E3gEftozejkB4Sgo5Tp8bu1WvjoY1z8MCADi8uPD5E3u/xfu/tCb7AcCXq+tNGPjPKbZKUSxHsUEoW8/Xeji/5c1WnAZlgOgM5SL8ECtdKr0jdPWCM+313Y/NG4vi/YlY6Bl5efRJv5+wRIwpMOMwq1bQCmO6BFoj7K5F9tZuz9D4NvGzJje6RLsJyFnpDMBdkh2NMzhCnp+3S8a53/pcPaN4uzMaTjR4Nv4yXstMskmJctJUVaUI/VCqwPj3jXFfgAc0UAMeCuOsscpN9YwqbWzOHPauw4+XWLihXV17/09Z5V68lVZS4INFgRxSNOOECV8IOKyT0C1GT8+z4A4UVGK0ZcFXxcenTP6eUwUMdyT7iwgofAMGo9CF/L4kvL9mPJQeHmd+3+lJvXQK44Gk0aer6xdTZlpTgOQ9vx1o81Fh6Gs4bMVMz72kLO7TmwREZZDOdTgY5D2Ty/awZNdtKetynw5KdTqMAdx9EYu444NDMDfsOHisAlJDSKUlnmn7NYr0btAblzq6WBpP1cMYOd9fuG9jxw2ER9VN9KG2S7GTCUhksOb8inEHltPc5Lb66uhyExr9kIVuWM2JVjSjLxNPThoppw2GpvuKUT95rp7dzqu9InQaAZIWUGULZg/vcgpr2Ok0dg/+bkg/KEi1p2M9EtxONG8twufl6FNSTekugwW8QWV3QJpeRglWhWjzrI0Or/73XJMDjvylPP9VgF8K9J9SeqUJ/GCOJODPJwm/s6QOOOOKwYpc/xoL4F2WBhRgagXzbodWSqeQNMG1v8CADAERz+3lrtl7rYsXLEgw22NJnQZTKF2whDvfHCqtccQdidK7gLv8NFvrQxCmakl1DhEMtT3zmlzouf4tAbdXn/HH5UcV4Afr3EXgM2FJmsKR/TMP8xxK3X7bWO36vjzoY/8bbjTP/Lpefm+EO5LPt+5tW5+tdXpN2Xem7Po9SbhBI7G6ORi0+fdg2W+fGdMn8QIuRJonE8oMiJciN8nna1bYz51t2c8BBRgPILcbltLujPB5u/f5W4ox7eOeN8vFv6Nwmp3wOGyqzEm5z4UC/GEASRnm7KvzN0PhgGEJmlH/sxNcrPoHF1KqDlUUExoyFoAoDbUiA6psfP4g+nrvW2xefbEHVr95uBfW7qEoF7m/ebXaNR6aSgoiSgQ2J1g3CgeDM1jt5fzdLZItX6eGlTWhhnBkei09LUIToKjFdtdP7ZSEBW2iwEXT9QpYQUwgbpJ3lIAKSU+ABaKUgbyfKYW4VUWv7ROJyGrmbHqZAS4LiKoIRBqQWLP0ryqUS2Yk8ihlXhsEF7ZKoIXRSgq9nQQ6eYbJVezBpbGe46ILL2upYabZ6KPELOX1dF6mZ1Tcm2xjv7YmitO810vRcLKJibJP67mz2wTPwR4GFGsGPb6GEUOpBQcHSj4XYILM0TzL3hK/NtszTQ2DtBUWxRqarpHz/mlvg8UwxXLGNvbz7X0zQRNbXZtIo0cLliVS7pRGAAkb3czSxJbPcgHa+WuMHFYv8jmTeDCkPbtal067wv6cCCPTb903sR/UciPtMxcbJppINkpSIxkc4A0hxgZh0SmggA3CQ0Pps3pUF9nHaKJEd4V52JBAAbQvgeG4wHfSv9GYdO31wvljfYsDtYUXidEOQ5uc/kiuh+ETe5UMm6m/A/CQVomH9tGrMv111rdSPF2Uez91VjW29uSzYn1aB8muaG3R4USe9dSZZ4tXNXcczbneQvqkbX8DALTdAfhAwiQWhYU2Tws3YJGIOkbL2Pz6KjNLiHxXjuEZQQ3p/k1GDXlIA626VXjz27jPBjzKfb1RMffcrFLRfqqREwcySkJKXd9VyHNoyH5dQw8tsSZdKgu/JWvDSCcuRmRwzMBaboTT6aC84wJPdmCCzOCiWwBQdzoCju2fIP2HjSYw2AMQU4TchPCUpHDej6fLFVJIW/3r4UYYP+TrAhtt3NKPHPXEDAYZABOvPLK6eUxHfpha9MA5rjvs0364QDMbOiHWI69uROqkiOiQxu3dsnGbEY/Snl/12XE/A+vw73me1iOJZ58AvNPfbaPW93IUmb7ZkiWtvLYQc+PPbLTBqf2n4X53tjNM3+5g/7Mbe5yjY8XqZGeF4lnroxjLvWpa/ill3M927e8spqwPilSU53Y2QxYUa22/xu/veb9MZ195IDN0Y99PFp0lGxJ4/yiMT0GE0oBFacrYp3AFsvyWhtrNOJv7Ao7biBwC4O9ciZV4IMG59XQ+E1bYHtf5KzpPJYVqNx5DeE5Lt2bpbhpOWcjt1lhT2Og8GO3gdGV/fgFSh+JQ7ls6xtV5pjVdpx334Z+wQOAZwkfNIBwSoZwR+FZ5uD3rMhqaMID5WhT/9FF4zErnOLi4xtlNGDnfFFO4Ex6SlaO9oeh+Y2LMpPLGV2yLgWRN14eHeft6R9Pu4T9zadw76FjTQi+S76AXxFKr8hpYyYrzuAGliDG09VfSiamC144qrcwPny0dnsEwV/nrag6N7nJMFPSm45yMidJ9hOFOQXBsZaAYrC1lpv2sjGtxrOf6gYETCL/cELJQHsayr2Sc+qPldGPPvFiMrDZ+s6NxuDs7jOwIkaGryrdgUHa9bsPr3tTBvDq9SizRoEhz+BoF9pt6Q2mehjsJ33lRnPtiq/v6+L2E36/yb19+KdD/rpKI07iG/zcO2x7GcmSsGELQNag3VAN2uxkFRTy4S+RRNkIvSSHkfyUWrV5rvSBjjYac7JD6DjoDicq9GzR8QEHFhN8A/LU51OfwHIGwIXJN706EHELOsyBI/FxGJfR5Qmb7lOv/dfUZH1m8yqta0qlcQ7dLVr0ajbAWRjHC2zyPgfXdZ5uMQd+GGSLcE3DJF5g3vM/D4jSsp62BWwSy7hreet94NLi//hJ9Mh6lIAa2X1kAFD7DYvnL9/Rrke2KebnGVC6VoQphPwioVMCaH13eLV6GpRDmZcHuSvxcbukBFziD7F4xNTj+eAngEMySZ+cA52i3C5juYUp1I3y+p4QARhuyc0dfhQBt4lm5GCOnuR8LCpiae/D+jCLzFoRtk4C4YJYcWkQLeqb5NeAxmOvvNbqQ8hIwThv7ua50749DtjKfIvlnRYMxkhAjHuF4REcs/xlaMeHFt903EAhHx8cKb8VHhtXj5+BIRIVtCRMgZg1Diwxpqf+tSp+R2PUzNjJVTqF37JJPkDFE3ZwgCViRhNiMdH2rTaicnlN+5XGlImSawCkC1QlTrailuiDPBRoeEUAmX/pCfsbRWEOhGYzOKh8J2Z49e5yRoQJqBNoxuDTUWtGSMj8LlAmk0QQAYlF87tCkHhVR8hbZKIQJaKroLXKCwRpaO63J0aH4Dzw9zbDIwCMji8bg2lAbYcaCytVWORgvZlcC204R+Y9dJMkhTARU83QixfexdyoIpYn3C5WwhLdJ9z1PGfMFg+VMN4lCNkJuD6uf8Em+a5+F0Au2/Jzp+WLzeJZxMCT/uRg+ACgV5WACQ1ItTNzEw6oWzLMZZCzd3s3gghloC4MqlPfn6LfjwLTrmUC0SO4z2PzY/iONYJD2LwDGAmqm9C+OU0QhE6GY/V0EUaQzNDd26+5ZXwqKeDGk63FWu19+jRNh0HmejDC0QOMcBvFkdGjQXJYOyYxXAOxTnufPrfKcQtIWw3GX7FcRBJAreQwS9Eq7JPzkNc2mHesHv9GXUVEjcDbWxvoZcDHWz15heCPG5ABO0zFlON39o1+N9skhdwPwmjDH6nPCaes5ReddEotaJEqD58LWma0F79+/x+Pjk1av2jMN0KieH6aIbWPoGkYXurWHFARwAXFF42/5Ea23A88EbgXtQGG/WrdWkmyf3NR7plnqDVHKi9dYHnfAwH1zI4oyw5WGC1+miLrBbl3t9tWh7JevT+vttiVEZkie9K/rtmWdC1AKjo+PAQBfvjzKudix49VCRSINAe5R57AeegqU9+EmRs0TREljKU2OdM6+cdAAq9IB2O0qsOczPAIw6/WJw2sJMM9tYJfmxugxm6MV5Zpoksj+GcKhlVAAACAASURBVM/HaZNc5K6cAjQ6CFB03b8QfF2IyVMRmNdVx38DqHUKgTLg8GpWhuCQD/GNvuEQBKIjfNN9v0Dy81p6gnnZ5WGgVI0Opd7deVc6TE6jdAjVJCrPpHTWbo+nFoE8Iow8pqe8LXKGS3Gj5bxPHx1J9O2eKHz7qr+PjbgcmIaS8xGndTGqZMxh/jD8zrRN2lJvKpteV1k+09GI/XMOx5PShPN9bSsbM4z3eYAxAYPY++FGYHsGeMIkYXE19/X0oYIY+HYtMoST3z4CdZJdwSZDeY/L84r5ZsYtCX98xgTCe//92vId09496HQhAkcwgItz4d+vb/els3vbm98zuvMjT9+BIBHvms6PGfQ29Yw8/l2SsD19K2g3DeaJTog87dbes7nR9cXvGqMS46vmCXsH4SUe/f6AN+jOYQ+ooV0fi7GK7r/7cg+AcOaRtMwI96abz/2RGu1dI2R5C/57ueR5X68D1vTovnbIA9qDoPJB5Vks7UtRXg7Q1JZm8A7xrAYBZwvSOZMzJ9GrwluTAVScg8A4/n2Sey3gTh9ZUWR9tlu7cSa6bpxXD4ldJHrYAQtEr+dnQpdcNBDuwbdBed5thlFnPCideMqCO5fP16gfNaJjOUf5GBN9yQzgDssVKw0QMOaDusvT5QWubm+BxBO8VGz8lw04J4E3I0TJfPIKro6/X3jvg40X/XowgIUZj8k44DXeq+R4adtD3OtZz0nXuVTU1jAdTtgti+fyttSJs9Ffe85V45eNRbw4etmgG6XnzlswjF6Ev9/mymp0PIrOZci0VdJiKZtQ1MBf+61o3dKPFtiZBDJt8i66raymzqDlMv//2fvS9bZynM0X5JHsLF6S6u/+b2+eZ7rjLYlj65CYH1hJHTl2KjXdM12sciSdhSsIgFiJcA7gUefcPM7Nw5y0n1WdBSwH+msNEvJaftNNWV6Bc2xdgusTvG1nUSDos+35zkg023BJnN7sV+YvvBuJl8hnFlvrssGPbM1H8Box/sHIM9V7Es5PgOtrnBbztB7V7/Rs+93BqWXju1x4uf2/y//f5W8F+i+ULeujjBhe9kTnhEz+6p6eKhN6YwvvMSKcfNASK0fJ93mgg/xS4YiFMTM8F5aopIISD9AHSmGiX6YZUtvxQd3Klf9mMK6YfpoXJ5d7Aj5xwy2Jsti82Rk3g+IcAApEmZwFPrlPeX1NaT4v7ccZ2ev3SxalLd98AX3+ww+YHtrdx6ifzFhvb91/+VSIMUKyRtXnLl+YHrt14WvDWHCFUyHcbdzWxjzotxwrX1KEvqRQn+c5H9Ts+gcGfpRYuSCYPFRqO+KBgAsAfMOo/+ii0JpaNcgsGlawK8T01rGrC1asCpPRlzJ5nD/fHFAuC7IgPM/aa8K3v6Vw/kLB4HrOUiIVpLxl5X7eppzZwquqgSVcEvQQShBhf0n40A6UP0OQb+3q0cY8fZD4nUVAjk4czu3kc3SU32A+7bde6JGjLq6rNxyC3ry+pLd4epdjj/gdVxAZPAU9sf3F+W+uxxn81JaetDLsRJuZcIxHls1RUohgqFY3PHChhh4qRahfxFubRo+fUPwHkmI99OQ5kKPV+B4RgZ/ZQUy2noap5w7u6mFtvSeAVXEuQhgLi67h1Qujco0+6d7l7iq8oLOGpcygAge1JmAdpz7bWcOLq7KCCZ0aXD3rikD4OO3gZh5sgCmk1VMzeWNaLiyzJpfzXkHRGO61VJ3PgH/zEXc/HAK6eeUknFCmPmRhQoaBreI0eyCyLCnutUrLVVgoxi0eJhY2zkEp1Rt7YNwPcEG1RCVmR8UjfxidG9GfKNHN1aGodj/SJmgbOae1ogZ5pjnlmmZg3ObMGjkgKc+nZ3pRr/h8PRGY7JXENrCUA72geDe4snrpdnAXvMUleakZIrDDv6550E1O8xt9FH1R4Matw7nhZFb8a+/MqC/jI+cvVNkp62/7P72i/epdeWvd19FlHhvx+U7zbHglR+UYp3ooW+cS1v1tEQCSlCrBTQDhi4IgF+KkM41bqExQ7JtdxZNhhyStqLJcUMvsUcvgxtqbFd8fvwNs/LliJv0NWoLenOo2EtRPfEUhQi+M0jPuHt9jrMC6oFe9qrwMegdqTXRdACLCY8JTWHmLG3A4etXanLytHNHCIyDeLtH1+dkgznOqLsPDXAoYhHM10iskaS2YWb36ZT66GhdJOosGN0hF4FEzFDC/bGLNb528+AAoz3Pcn4DHjQnZKgk3ZfiQWxLS3SkLj4KSw1S5QY3THx6vb/dlQLqYz7rbb6iwEwVomo4jnR+ISCLFKQ52LmBgIBl7BkB7dH5yFGl8iClzivFJ3k0CFYYncfWrMRZi4VkkD7mbhIGZfP1mPDzOO4Bk2JVD+RrMEaCpno4xFSPCs8u0s3j2m0GL4iPnLqaD50yHf45V8vQQfmnjWjvz/pvxxIkDsu2F1yjPT90H6FT1p/s84CxzMIgz7qyIyWvJ/lXOf+WCgK+qKLy8EHrw8LYOvXXaHW455v8IhwJot/dy/+Tm/HnL7znyfM+6K/l64TTiOIqA9tGsV+3MhXH+rRdv9UZ/xxLhw85GHzDBU5JpGj40HoxgrA8F2c8pWd5c3tj531G2thlhNH7Lj2ac4Up0BE4pxb3PS9F4DESoVZ5gltDtYVwpKV46d1Wad1/jvCnpmlBcLgLb+BBp1f0gI+gsedG/GiIEwCx8pKTrsj7rWIjwoDTjghlneszQIwaMtvU7FgPpnxZp8yuJ/K0RcPjXrZg8fiIUugTjDoWuhO7QJZZPwNXNHVZ97wqE+vkKzIz15laU678AUhZc6Gs9DkXuZ6b5+owMeePaVD7w6FxEEJb3u6+V3HNalN7dntHj9s75tFxQdhx7hKbeGpZCWJnQkpEeKY/6u8qR7AcZl8a/M91x+M94ca6PWQzuETyXgX0HhugLADzNwQK4PsMiCRGZYl3nYCb2p8aHOMpYPzMKn9D5bytb59XRoMn2bvCFnbsa3WzzLvM1X518Lsz1/5n+x2lm6K58D35sVqi/tlyceuVEv+fIhlvft37/vNDw8Xf57yp/K9B/UzlpQTMJbP4yjPuW4phUGPGOxEwoQs05AzsYxB1NpQ383NCoYCHJG7qUoiHUEmJCWICJ5bzWls7lw/nc3xsn54GiuxccnuBAhBkP4h0KwdeU1fOdl9TuJxRVoktb1wAYO3wG49YZoyDU4rWdlaU2b1buSZTX2SPdnrsjGRcDePzyL7z7/FnfD0UHJgHjnB46K+bN05wRlpAf0wHO2vpZbq9bOmVxHSHizdpvUKK7vpl1zWRm7xODD5yUBxxdf81aRtiqY/pp4co6gE4PuXupl9aWfL8HcEHAoa3Yl50Kbgo6tyPGABD4qZWcWXv3jzM8/vMHgI8Qz3PC2efPaI3x7csN9pdXciC53z5ofv/J2rymDOFxADwDOMcQKdMP5TZnFaLwEkb8d/RBd4qvjTTUARTPa0hI+hTp8osIMhiy9DO/fPz4FqKZy6/M+VadNu3mUWXnYFVSmuXqzDQKUx+CCH9FM8sKkyzv1Soewh4SrlRPJSBMKWO33wMA1sMBAOk7EkEks9LmqViXZZiEwSI1KVpK1VxG3SxXZb3MU0gHEzKANEKjN66Q8rOcKtGIEn7IB6lxv+Ua532cBR8EgBbx1rZ8nJaXd7dbxDjGp11g3/IxV/UO766cloq7hsRusENBDyX3KpXZUS8LERmipGno6MQoXDQ8ez5qAlRN9V1ApWNnfSyMioqGJh59aChFYEDWUJTtnotLTyzPz09prqV/pvwDxMOrd/Fybyr0KVx8LTwjgI+FVHGtmf5EqgQqhEohQGJ1FOPeJIqM1selolYNoU8iCBd4sSD1ZRDIhYC/hgBA18oOw96HF5WlUG/bqRgQak56WXMLBc/upc6myCGZRwktD4Cb5DrvLPWroog7j/BvwvvBIMue0fDsSPTR/lGlhxk8iGcreT0cbtCe+5VsXABgYZI5Xctt6O98hmbNjx0PKIw6ziIgG374nMdzrlz3k3PcJ/V6KqYULQz0Kop5NSwxgcCw/zm8vLMSLg93WFZ79khpY31TIQuZRb/McyFG0+6aAQFBhD2ekxlTGPih7VCGSx7v5jSApnkDEF7XQx0j/ptaSDTcEaD3l5HmXT+7zl1WohtO/5kAw2Yg+pgIqgtx1KBF57Mzg3pXD0/jyQPe/ZCxNTYI3uaVQNhBUp+HyiArf6gKXBQ1vhCl/OpKQ1mnaMdXjBlEC5aloPWO9qxwsuxAB8aq2bKte4wVpNlAYXRLXUeYAxLCU7PrfASc2rxUAFQq5sG7hyibwXLQkp8zwrb3crWhxBye/AEAZwoaT47Xbb7SFAmtfsxnW/0sJHBbCeu6Yr/foTNjWRYQFazrAZ0Y/dCdjoLFMKaoq7EpYZBqZvVUNiGzGUmZYuZ9IRzWhsPhYNxEvHs81KP5MZ4sIJmGuyaofda9YavnIb9ZlbL6zhOlOdnqT+7Bxho+6ee5rr2db53jykhaP1ijHBD3sT2Osy8R4dBWLHURXpQNnsSz/Lk/acQzKZ3FqNUUOAuAut/j6el5wO0lGSMzLPe5GEZYX8IoUOAYBOyooKh3I3fGqu1lAKB0wfbBMHrdP7C0T4Z7GGCSsOyWo9w8099nYpdkNF2sQmL+9RH7/dYDgchN6PRrL2zf7Ok9XEt0y+jUe7YTgRQJxMT4npoYleNOGjbvx14Y9/9gsJXgai7nGgVJ7Cq+4t3na7TGaM6LiFKdNApF64IX3/0hco5Dayil4KMmt12Wis7AOxAeX5i0n2HDl4spMGO5DMJJz+xZGfZne/CdIjS6vRqgIuHb+20HrorsV4oIDHZe/PG/nwAwls870HVB4Ss09UR/a7Gw7xUs8fE4/mxCOoweCUSIQpVc5tPoa0RbgXhUd2Y8qEb5vZ6DvtFbZip14JcO5C+XrRr56O6J3qZzqZ15zci4kEoQ1enFlOfyCT/rAKQRRhgPYHzoAJrxvOyfgoMFP777n/8BM6P1hmYRvYzHG7e5HnjTSIhxwSJjJJghTaIjxsOy8KWVCp50X5wXMZBrd1+HBmbZlK2YwWvwCfLbDDo+kqYNuGE0aN52usX+H5+ELjGDroFyw7gwrokZhy+3eLDocG8pBsck8PqhH3vMz0Yiw6A2njtVDEeYB/rEgtlmssrkI/FThtuBfGaJ+t9D8tM/+Tktzh7Z0M2i4xlMiuFGReEiKYcsop6t1XSGymN9iyJxphmmUwDGM5Lz/SqDsd9C/qKOjyAUFnlkR0R8ZbijuJ4HVKZw1Lbw2IK3lK9S3GU8hoVwN6W7nad773hM9S0qN7OID8VS/dn8KN8zg4gZEP4camXNSK1VMg+kE6LzkyL12YFLBqz7WnFHb5pSicY1Geg5vGfH5+bt9e/JQz/eTvVP8Ovih2yYmUe9oTjf3GdkPDoP5GH2PH/JK3wei+vqXgHjs7J9c1/8flL1d/l/pPytQP8TZUY2tjGPkJAehuxQ+XNb87++uPAMwYwNxHQ+zAKKzEWRXqoIRWodWVALL1e6CtPNw83a/RMnnwcCPun7HfcouBz66P145fQaEj7gBuef/oF+Y2FaPqPgCySsVgi8Kz6DcYMCIeorZAP9waHUzk1zauPUkmevcAbw/csXVIjX+/4PUWqJgJ3w45//RIMo5M0Cy5XXU7v2mQ+A5oW+1RW79po87rmN/G4u5nGfdIL/5sLeaTtAnhIWADLH1zd32P/PP2QFqCPCKqUMYf4hjOHT4Rlnu/0g2Mplf3mFfh8envDnPlgvf0sZa8fpugmqFGAABUW93WavtzcXQxoDL2iepnLD7bedr/6TbaZyhAOmfTiJpsau/4YuDKIAZwLndYmn9Cih7bOjX2aK0PfpEC8H6YYqgRMhtrpQPeCIb+WwEVjh9H5k5JjohvP9d0YsQz3sjLwsL8Ml+Zyoip402LYii1KKOc0ED1TJmf10dNic5wIAy8jOiOKVBsbXDlw226GgUmMyDmvl6HsYLzA3kOcjl8NfAXk4ddY186OsKolEeQyA2HNBi+44xgYCmuf0ZtROaAxwDQVRRQEXRukIpZhYpGg7E2SrkqKp8NnCpAaIkAvBBuXtPN960wRDoigvqsQuKLWglkVDzBdA00Fwq6IIZVF6U6kolVBKdeGCGIuZh00CQT3iU5GQyTDBFAilisK+QGFOhVQRWsz2lcFhOmgqfNoeE2WWev3X4uEX5wOTedZ0ZqA1HJ6f0bljbSsOz884PK9Y1xWtrWhs+T6TpzSZkZV6gyC2F7v0khJMpD3GGb44BOw6rg7xYiEz4CBdM5M4sKFkDo9SivYnuVfwg9Yt+61rBkoWVkM90xqq94N3oMAjjtjzBAIqNDJDceG2W9Q3FhMi7gjRjM7US8h6QhiUcJtFoqB0j7Uv0WNbHJsrcn4m029fJcMjzMmQonkag6L0buCz1VjBcSLgRk0zrdhStCD3M4870dKMw3wdUyGO0R7VbhecDaawidD5tSgoTtrLKGzghNNN+OvhSW1fOr+R1miR9sxAyOGeoy5TJLHmySQmgCsY6zBfw7g4wqu3FBnB+JOcU9TxSakx7rGqqD2sOxR+42Ga8JLDINJ+tu8aVr+DUKjGXt5c+6BnKAVQQ7o8YLIwIFr/eF7ValP/WPdsmCz4QIc1hdM23RHEIF2RQmLU56kiDG9AhJADT6Bf8ur7vFPsNpBESSqliFK4j7C8xfNuldedD507ePkp409ojkBh91/To41+K3E6A/DkPAp8z4WB7Nwe1NBHDS2ZPfUKM6PyAqYVgISWRYpWZHSYdD/2H0+6N8nHmAkFKe9QQOhkEQcynMs+tbkx40UqBGpwHDzO5zQutr0ZXnS+Krpn81ybcbu1ezSlCv+eMx5Sf8V7rPztVfAz9DfV/eK7L908ce4Zeq9jbUT4AeCdXv7BI94+Up4zH81Rvi904VUbInV33HMAgo9nNT7U9eVLuKF4oSJ8KkY8FP2Iuk15e7IPb+rxxtsc5w35nTdY1O7s+C/0IHueD49nfkkxvSYAEd6DNxRb+rurUfpxbvHXFQv3/oFzmGNCRHNKNJbZjYAZkDRBilPsnWwkTBDF+fc04PccStQBbii/NU/QX1Mcz9G8yhtrfKJb3msyY8EiIK38j3v6uhI96FXvjA8skQrfGw8jCarB3DUHekcH63GOMaf+6b42YpzZOTu6xBmdweoJnTFUAneMdHALV1JL8U2cvvEgc3wt5vimZ86POvNFN0HXc18hQqVPKH9E9KnebyXk/wn8uFU85DeJ/LGxtFuI8IFGWelQJ5+4/sqSeZetu8cOE/lHeORmLASI8pxcsZrfnxZAP5daHVcIqHQ9s2g0OyakdOhvUpRPQxrGNCtqg6fQP4r7A9af5v0KAHFXCct7sCZNYXt2wCWhb/FbBjsII7ONrg+8eVzFG4y2XoaRP4PNhM0aaePA6B3xTMr72JkTHAYaFPOWz5hDPxPf9jIcv1AymknnDblkOozor4xTLsiZy+6lHpL/k36fLpmf5Hxt+p6NE38Z/qd3/3rq9Xf5Tyx/K9B/sZwisscHA78xIP8/s3H/bImDSlar6HfHuyMmMsInsk8GNwJVqOBKBevQY7UxkGRh0+QA3AdmcBAPe5kPotavOfy4PHcPwicVTFq4cdqo5eXyQABu/qm59z7r1U9gF6XGRPT8DkShn5Xndt88CS5YlLGm9J4ZpNzTUXl9h4t/xQZt03sPFB7tmeiN7LIKAbUf32hsw3KeA9u5qa75ctMT/SuFYn5Q3utgLhhiiQwAzO6BX/gCvTyockoZHBKYOrYo89d/WqwPVxzjsOrmXO2FL8D0kJjM+dP6LfkWd4cv2O8/BwdHOQaCCZPVQvhwAMB4Ojzh/A/zUzlDpvx8bwxmd+YQAJbLCwBAP+34P5WNgxGO4cCYd9Jwm0X3cdPcSFxN4BmecSawYqLwaLUyNXAKi5F5KCGYJEpKKRO+mRC3tQ7jf0ohVBbBnvnYxK4e97fJ9E7CyavP5288yHuIjgngEvyYEM9yXQPBuHMGNITA2AUSpLhUn2rcUXrBYmHHlRs+9IMq+xpAktu8UAE1sdvV8ycO65P8VgFkW0WIWlXpbBaubV2lnkVC45rXrngch1CLIErArjHSBmXAPFd+LSvTVfBnoTh5gNgEX5kRl+kyIT1qHCwJJMo5rVe8oZNAAwJcy24HUq8pPwQqbTYLXpm0MJzKQovcF0YBmj5fCFzMPzrWp6swrCKBDDNYFZDEJtQhpGELbWVGKQA3UZqb1TZxARfN30mieKzqwWNGPqLsJBzW7vDDCIVRHDTZPfAZkRPM/kKAAs3ProKhWsFFwnEXqqi1gkrBmYbzbauEDO+lo7F54BaUUsVbXUMfm7cza0763puf+OQVQi3VFfaVRAFfq0QUKAT9U0GVCgoMKRAlZV3vIDB6Yxx609/ybFXcVGtV2Fb8BBVWcdc+yqzwYdX1FYX54dBwODyLAn1taOsqSlRdVPNwZoiHMyykosH8mOQbRltoQHAZPys+0XyIDAa6ehKSCEx8vzlCkTq6tpdxtynms2CTDUBBUYfhgJFJc8V5p8DX9tBQbwdaaSgcUX/MMEBwDBwvVJv3akJdMVawaBuvKhz98Jk1QnPEZGROanjBcYSvCafvU3sieNa+Kx3g3iUM5TDpGefpp9PMkTcfnzumUaOyfIuvmQm24qd5LbeKjtPwaFaKMgR32WqaELCmtQTgoSVlL8VYTRC8RcO9q9V4ieCdrLL1sAb96IwKC+kun1ZHUUaaV3gdzEB/PkA09TvhQ56fte2gnTYOUQDCEzcabYn5NS9fm1MVgLvARo2LFcdmwRWY3Wirc5iJvNoA1XNDG0EMvDMomYmAcwb/AMq7gv4IEJ0lwfsPhfc96CgD9BnMR9vZHuURW+uavkPXiQUGeiliaF0kV3rxhli9dJziRR8xwrEZXZayOL9Ra8XKLeb5pxN0ahZHROYcDo/3f4wvhUd66ufPiijDt69beYTsp33armeg8b1uStMEP7m3LKmSiM1P0vYm8Ixn9ZY0uO1KGpQfIoHxJ+V3SoEvdjHwMn4hhQQuRYQBnuMeyfsI4pFcWDxqSylYdJJl70tsh6esYMsUhCUqDBGwLAuAitaa95kA7PWLVXFu/LTWp4F88KjtzsLPr5FNXS/+fD3nMqD2Uw9t3GBmj0DwA5hwitEbWetHvfYdgWtzPbnvJz28Ns8gG/uDR8WPGS3NwyFoGHAA32/Eu/TsSpwbaiGUa22LNFJTavvpyy24d7z/nz8AAAc9fzyemP+3r8rpwiwKXgHpjyj4ioavYAAfdD1+JRqceZsTjvOTM4KlAoCOB9DtBUAPaHcXKJ/Fd1IicqlxLgH1U3UWUGhmB7SvVvdrwrcbi2nKcyb569D9paSr6N4EMxqze16S8sz3+l7ec2x8KQPfy+hZ+rqe/TXF6Inz2shwNLebn9qoS/ka0mcp4VLjj0qhdFYqGrVDDMx6X0X2YmdKaK7zJsahTeds//kTGGpQDXgKFOtZqWXgb/wGGRXTUOgduIRc+7YxWiumeNtXibLz2JvSb+n7vnc8ksB2h8D1CIHahVPrrZP+AAk639Fx9vmzn1ebwhXjDkRXWG9uVTZJ/v5LsJSjk9paXwK4U2PO68RrHdXjaHHGbcf0aC4fAHwrsQfCUDJVnvEoBeTk55Uh1IhNUX4QIn2N8ndmvCG8kaZMgazH8yr8cLZP8ehlYInkVlh4pxhcdgka5mLLS/1UMdlL4CSTZQW9MUcjO1cDZuDFuGbg7PIaIODp7gbgry6P8OnrMY+M8Iz2FHDjNIdntPYpy+e9rwSxtEilqEf6wXPIayo8bc880u31eYaODCZOwd5cOB21Ux/tHHn8uBo6WWSK1sDLZIhBx++7Yd0Gr0A4jiiRPw32GEAtDsmyHpwhII3/BTjavOrbQgmStn8q7znP/QUw88b2XHa0eE3Z8jwf9+3f5b+1/Aco0H8nS/ya8vshft68L1//d+24YAzjP8DwEw+PTX3kQOL2ENuJnAjm/UVEIO4QN8hMCSh+4njFZwJ0/JudQZiPem+azTzQqZEHjCHWhfin2o1wTG0yIsRMZn0iBLwodo3ePqSHzIvcCMJF1+/WEEvd98mga8j9sbF1vmI77NgDBdNg/b97YfI+MtBwPzRzxCTML7EcqjKB2woVb3NFfIFODy/kFztVjl/Ia3cMv6EElnUVS2Bj/kOukCuRA0e9AfD5C/a7z6m+xIj4e9LG4e4BuytRhrfWUTXktTNqnjDha+rtB6x3qjmnLXbsLeV4bl4y1vHWTMmhCr9SijCLycLzte2bPajBmnu7MqGo4iy8ASOcdOAZxRnarw10FCNNAB3oafIg1NqYjuvaqFH78bY1eCmqCCdmOzodzNzQd/1OHMyxKbc6A1wiJG7RsLZej+IM93q2eglpRVIbuU0jBnYnK2T8O/vcsB4Mx7mK69nzxerIeMSP/r5WHWacEiSIkwYXMPdpu28HQ4Ip4Agq9lGjAqc+08GWpTKbLw6v3DRSSLjzCEbmU8GMRgXMXSPzE1g9FAGIgJuEBhLMK5I1bKg0a4FbuHShbrrvj/eCznYn1NLRujoadrWyLgwuyxFRVB2tHI5NuWPXbE3yK0bL7XuqK9ZJhEWlVPE4J0nfUsqCqtf2uz2oAGttIuSuDGqErqHjS61iIGMe6BzKacuba2soMCyDqFRQ64KlLqI8Xyp2S8WiXh5VFVOgOgispP6G1lk8KliVPb25IIvUEAC1YK/96greHV0OpZbHt3V0bihEaG0Fc8PaGtZ1Hf56b8lYQeCtoEgeWbL49oBJU4fzGMWhNG4IDGX2ABo6HrAQkFn5IytsgoDE8bmxwsBj+b5OFxxSMpLVOmYDIjYQlnnPtDQ8/hRPNRF8VKoelYBKEcOfEh7p1p7tOUYDRh3WtAAAIABJREFUnoHn520FelYQEFlekBnTjVcch7hU2zwtpzHT9L7nPQ/jnByKXWayKx5U4Sd3jRhiT01zLj0CEIZjubdW59hGrFCmKxHZI9FASmvOw8fpQkkYQZ6hOuaCI5KCCeOLUho3zOEw2pCIKtFntne1DaEfI/XOgvjADWnszJHneVL6aA/i10LglVF2BH5mFdA1gFiVCJTeTGM8rGCqwEIRfCGdCRx3+2Twkacbw9JUTFDJUYf8TwB3h1+vY2ANOcEIIk0AUqWnWElFIvyDQXQOnGnrP55iz76r4O/nYH7UV87zsWRop7MY0lEtqGS00ipSnDdFVchGQCMeEkRioTVtpKVqZksPWy5GVFj7sBe8kbnin5Y43ZHN3UZJqPVNZVC4U/ye+cYMfQcwdkYBMw++ZW2Seih9FJE467M1Qmd4GPSMD1zYbXtV629q7UxkkRnIo6gUIo18k4xnaByRcKsK84YzbY1BIKgCH4Q9R0j1ESumVAQJFxOygZ8NxvaNGfDI833YeTbRhmu28PAby4RYk2mcj0F+shpS0PS8GE8I+gjsELpzG5/eI9oWqrtA3H7aGeHUfevFTEX02wBqGaeM7X4lxjsmPBLjHIT1TlamXqlCWNfcZ8f3f+qIAPqvb7I3l5EGZ4r7jURZOPfiFEp9uQX5zKHcTT4EGAheOG834x6aPl9TPuh0ftMOf2CYDdfAaw5/aWtkL3TDC/PetjXMuHwu2QP931XyGvgcI8BsGFN+4WSh9JJOqPHxhWDptCR0u/4VxvsD8NjV6JwEB3dAlOdqbOke/zrfgqJShzibsedxJXkuiTzTmTAbkvEmCmSCZrKckxAnjwQkEHb8g+6HguHWq0rQaPZ1EMcTNfD+cpsqNc/zaMSMoGe0emF9MdilKxCAle9c3mnzUDpwSSxyz2kCMx0MXK108QX52fefIQQlWaGgztHFaPhMqwgC4T2rAn0wlAo6kiPDENRk2vhYf9wU7ib55OQNPq4hYwRrv7gxxEwthmghAz2RfTHQqQlPGN64YqAwy9ld1QdbWSRnQ4R8/dQqOR9u66y/jdQ8QVK4ZPnIPO5jA2X9kuq23/KxwYTapAV4KdtCIX/hDAFS8nqKdISU91Hluf61zmIHwPZk6uxPcFq0mgbxUklwz9MNyvzphuFAZmUIcCOHbRoybrDXRciNSHHSHh0Pn2bOe6uaeILHn2kZM5/2J3nIv8v/c+U/TIF+4tDx23//J5bX9P3PjoOUiI5MZaDOU9uflAmwkIl6gCOozkN+UylyfrX8ZvYsw8NXtp+NYeqCobkbvfHJrzIagBQMEJcM3JsHlAvjXpyQoYin9BcwgAXXME9HYQ8aCnbY4RMabtwS6nYaxieOOR0OSRhDrwPhRZ5/5/Kgz19wMIhzf63kWTUPcTM6mBmRzCidgra53vndrBifV9Ke8Xzr6hna1JudQOhEAD0ER0PAdf+I2/IAZ+7fsI8ZMl/hPynlK2muL7bcXffSA2Z8AFyN7Z6o3or8+0AA3TJw/S8s9XoiymH915nR7kQ0fLh70AyawO7qk4ZHkyrpksD38pyEbScA3wCwzCnlsb4WJ9izG/NiY9Lk56wWgwe9XpoInMg9mNTCmgq4QpSBSYF60oIyn7fMY0VxBOvBUvI1W6/Z7xvTxcpAM0no0lKAtvatZgIu6RhGAQlxmK//OIkyJ0Z889fGvM/wOXViPlDYIaz3vrFKY2/cGIlIvS2rzA0xnp+fASLsdzuB59ZEkIxF5k6Vwb1baGtyEMmGKvbVIhGIck6s50EE1OrKH3D03yOX6H4xJbV7wcY28nrtUCDXi273TIEE3ghlyOMFQEODQkkO+feiNMfyzDbuQCHsd+98XEQx37XupNYe0VLkcMkAEbqY/itMko5bPwlgJjCvEnkFLN7vHegUYc1hc1El37kr0SB7QHIGBlx0MNAJGlQADHI3L9a5+9GFYhcNT/xOT+NNQ/UzKnZF9xOAVb1zq87i6ms1TPfwKYpxg4vxMOPethayvVSUpYo6uBTQskOpC/ZlEc/wRUOplwLuC1qTSBbmvWa5ApfkgU6Q+XWdeiOsfYV5ChNBvBdLxbKIEn3ZVex3O+x3Ek6+koVdFyVsUa/VAvG6P6wN3BrW1rH0jh03rM8HCbOeQtLbnjHvZ6zCZ4iXZRPv8rbKmtSCjri+que55foUD3fdaVlv6vswiU/0hGY2PmH1bMIJmwitgk0lzmp8EHuKAc/drosq/WA75CU8Tv5P0oVnYcSMrUhguo+3bQxEJDg+KReZu8ORhJlrImgsjIIKUMcCWTeJMFD8/WhdFIatdzw/H/txDkZKPoroYFajxt7Xe9oQ9aDTUU2a06g66JrlROfRi9rwHeu89M6YnEtSO7NAlNP3tBIqjOrpGedxte2uA+x9rImJXbF91AYhhEe2hgg4FNBJxj3Ocxh5obRXSVC8RuOwvooS3TCi4Zi0II6ilCfIkqxu4S2V3rCIkSS/PJR2yRqsLJzXmFKJsLQFDKBUAKpEB9bgz9k88sjfC/hlb8NhMrajKu+VHxw8U9R44MAoZxoxhGNOgbQf0zxlI4DAEGMxxeDAZlD0lUOiHLSfQ1g+iOl0QANM/HgEYQdWxTnoCaxRjOysJziqAr5X5Xo7HMBFaDB32fvPq6zIrlTfB+u6eo7fUhdg1THzKnVqfsleCrg199w3/MSK81viqWzctkYDyKYvxzxjvjIjAa8xXd/6Hd/P9Z5Bk5m9nBEhEAFrrvUJ2zLjoHzDM8viJa7A1wCezzTwvCYrVvxk9IfcyNsMV0fheRLcK5zMw3d4tKhyBrOWjxzCw5VSRRnkkYvIhYswHghiAEcAKhvvRGKwe3ieZjjvFeVXCah1QdP82QCjsnjKCi0HgILOkvHdldA+wBTpyadAdlmfl9cn4BgqXvrNG/et/ADwAe+xXFTcP9wP0z1Cg/abxPBo0BnMD9o1JBp0jDSm+2OPj5Ug+pXz3UybGI/EA8/uigh8BeEDmBuICh7/+QTGV9SrCwCk/B/j3T8+gTvQNPJT7x39jn/BqP7t5T0Du6uP4LsHLJ8qwFdiYHl3P4Zff0N9BKEjJssxhXmuK691bF1CuSoOp3KmszUnN5a2EO71qqDfXaDgYVPRZMWa/a4o4yLdcxqPZNCLY5hlZnwv0heTt71nxneE8tyVJup5bkD2nbYA9aXy1y/83CWXrQ0bdsbv6VdCt34ARtFQWJJqys6WTgGoAmVVBSeDWyi/gC6e5sxYPl0BAJ6/3KrBwiWYHvx6+9KEMmhQxPLpCv3mLui/UolLRSorZCm+VemTeZZGqqthZOi9i9zF8KneXRGwfQqvbRbO0C5/FpFSxihXvxEN3qXGT3B+05ARgIsuCuNCFwDuYYaZ+z/koHX4J9xoE0UMqIrORxqu8wjDmNJekHNIOXrJaKD8DK4qcGE8z0SoPtHpXKOyB4A90kTuQoNxEHpGtHZYQKwwYTGDb/OM5uh3jAFYe5wXXUk7bDWj/9q7bOxmdzO/OfGe+TiYTh0R2QzksGBniTD4FgPYs0+fUXfLQNuOYM2I4ABXMVZFPjEqEp7nTp0dLqigg/Goc/muM/YE2buMULZOfMAcweukIn94jQLBml2f4wvrcxgyks1XCYMK5axcjl+iOpH/gf17V1n0oCtw5iIMnfP5Yi527t4yULD70jMKRTgmUErzkJmQjHatHkvrc4JVUf0IIQdmHTnt8Z1jJXfq98j0ni66PsN6pTU7quP/Aq/yd/nPLP8+BbpRAsdI/k8qf/XvX4f8t4Rgz+FQhp4MWMDQQvI+SvdcHKkfp/RYP+0LlJM223DKCEmUBkHiFY0PORLl/dZZBMUMLAU4X86w3++wqIDg6ekJ9PwE5gO4WY4nCQxFFsbLLeHI+2J0dvCucFbKpoTTpyiYgI57MDw+uMGXCRKVeozZOWLsBomm1O64RcEnX4/OdwD/wwkHEIw359/GE0F0IQ0SgZKgnuj6PEHasfay8tzwPGFUhlu/L1iuk7edbUjln6qEx+T2F/qMK755OiwpQHrIMQYIV3iPO/HUTkxXJoTWZljvBZNnc/KxAb1g6OMDRZ50Kwd6iC3h/Fby8Eo1+Bro9bDjMIYzzSdGAs3MqHwBxh1ASVnv1u8xAO4Nd0S4+Bfj/PMzKu2ELyIJXckgtNax3jaUq4KFLmOStG3h4cMLb8ZDDawHTUz3/yx+y3M2RkiYXwsr2Gz2oYowNk+6U21stEXFPdAKRCEeQnDDJ8ZEksIXac4qWQduKZSQ7tRFmfvDFgulG8fxGVkrJN5vRe+bENGErYbfDHBLhucT+3z+PXNyW5OcGf1Td51h0xEPCnDFkWBVSgkebZ1RqhyeCnd022xHG9yYwjRvdqgRSR3co7Crn6B5Vaoi3UPSZqZXfyPBSCgGOJrXxakgnzvPv5iQw4Dru0QOKKRBgvXQabu8FBlr7Sa0kIok5FYBqSqlmtDaD0pGV05Yd3dpK0BeFeuQ90pjaNR0rIo6bHU51RlW3xJHhZXG2qGHSJU9Nm+Gd/KUKL4hEBpU6c+GWzp6b1gtB7q+I7kUjX6zk8XYSbF/Mr5OzIAoQhWxqrgChcyTuqJQxVJ32O92OFt2qLVit1v8cN1ax27H2POZKtLhfTTBOqooFzs19KacQWEsvEi7RfAGmfJ8WcTzfLdg2e1EEF8kNOyuLqjLDpYJdV0bepOc9bXIopcCrG0FOrDs4PC/2n7jjtYbemN0VZavbcXaV9FXgBWGGIf1IJ7m6pne2qqexor/qvFS8l7TQ7zFoyVIqoGyLGJYoPuyqwGiRJLQQ7EuSlcFibgGikKZ5Ya0rcotbjKPEq5AFa+W/13n33EMREAP3bPmNUADYEzwMXjF6F5ymh3Ynfw+D3VYfvBFIdBxc5Xp3S0Ldvsddhp1QFSmDcsiEQaen57w9PwE7iwGDYnus+4Zwwekc2qDIhCoke4rRZPd5gFO6yxUvAyXQNzVAEeMJyKEqa2TRFFovUnIcn3ePMLBHa1nBkxgxcPeq/a7z3Oufejc0TAqVx3nar9zmE9daPlgeEhW1s0defLIPcezP6/jILaUGArLOsFmlEGQaCjifEU6hhhin2i9GT+haCoNjaZhxnoGj/Y989wGQKWShqiWcXBnV8xnhbq0F+GnnSwSoezP0A85OtFhmPmZhJadKntVcWtPsUYayCk6nCbavLnAlVLYfEaz0JEatcG8dG1/er5vhAFDKNn1t0Y6gfEsZgxl+9H5lOBL/dq5jZ2V7zmHqPjOAWZU1axwXXQ4ReDGUzvI/caCM9feknCO3KDLJvN5FeOi8/O98C6qJKeyiGHDMwOQMCvBk9pa6nw7LMsYaymwbK3U450Bd5Htl7h0LLbLZTqHj7dgDMyZXngaoCXe9G/Gc2UBO5tQPIS2hoMsbcz4rMe7MFIeY2Q48jUvfgy3M14g2f9avxjPqopf8eZLJSJ9AFxk81qKH1MgdIuUZB1QYDQeO1JDaZQekEYgESO2BUnZASQjPPKJpUI+EYJOxMxd+C3lMSahqeGFPCdwPEaRj9OE/tNzRpfJo2SFsUrm+4yLHd/M4PeIw4O8AwJ+uEZioJw6yXneUwuU+zbeHyImecOKU5NxUszEuBcYwX8E7pp/67Mko/1eYrSiOL4H3QOFP6LxNwAd7fZO3rm+FCWQpnbwHt0zmL79DAT/dHnP0Og3JEblRSLFURcj3m4w5jg2tpsrDuycSpFT3FADT+/a728EvE/PQb/TVURtOS4hexHWX+jDcgWsd3Aly0dm9/YuiilsOwu/XTzViqU98vN5railgInRSkib3MOxdzlPWKqjUnAB4JvxCp1zT72QRlsSgwTFhq5wnEY5KVtO3nul8HMOO2z1Go7VpwJlO6pI+FtlpbGbR5zQdT9ZfA5mQlflZkdBQUNDQWVg6eFs0cG+luB0HkZBv+mpj/cAGOs/Dx65B3gA85V2pYBxqc8FDpJgbTLuB1v/zVn3SQUDWFtD5eLnGAPiOYJoh8Dylmx7WoXpq0z0PR0r4B6ykouPTOwVkOWXh2Cmr5BzdfCXhy8roKH2jU+5J8JHnZdLhssVDM+HM1LQakLIqgZP/nlcqY8zaApvQ/ODiX6nG6bUZYNbiEGK3jcewUiCnAfKUJlRD3EE4DCkVvrrhq7zejlNzOsiaxGGVuT98CbzeBB7y+R8rifh6b4qcZkldPv5J3WNY4pzV677xT3Pvt4OK7BIOjpl+tlS/xiAJfP8wOQy2uy9PLNh1oYbDAR5Hvrsi2ViJ8cgYVRpD9qRHumzFMEfliaHiESP4im+xLmj9xW9ibFLh9AyACAzmBg3UQxoukHWdzX6MdlRsTO00UOfh3k/RP29B70ynMobz8q6BJ3x8ywM2ghNz3J9mLOESvQX+78lBmO8qMI7Tc+nLjq8C403PBMyWMeexn+mvsxT/Hf57yn/OR7oA1Bm8P7dvxNX+4vlLcrzXIYwFgimyb6EonBuywTYDJBaSb+SiTwqJEwtqbZ3PmA588CKtjiQmXYITAWtN6zrAa0zznaMPZ2j7PcaYnUBSJiwvnY0VWI0SCjWTl0twGOwRuxsiSzjrnUuCHEwiOIgK9aXFde44I4HrXPO7cjqoZUhwvixIElS7gn4gz+j4QsW/OGeM4wvIqRTungNDOGALll+f2Rgr2Na9LNCBAJFx3lfok3zNM99s8PYHYnS25TsHzn1lWj81HIB4HuRNbNw7tXINvlip8kZt8PCV2i4xYpbLHyFC9ziPjNwG7zXvCMYhDtIHqIQlSCyfjPjIVX2oTMeiPGxE75SgHcpsQei3+VIge5zqHD8tWgvEhM2CEwAVL7EBe6VeQ6mIq+DhV69A2NZb8Hl2veQh9VmBnNDu20Qy/vLqIUalqsl8n66KR1DwrgTvpkAFAR37ftlfJjXNlbl3K8Eow3ABY98lICgel3uhepsyvGCO1NI5IdzQPBA1VxgnLjRkKHLJlxXFaSaoDQJnMHQAyfhmcSr5p3iqscEQxmdPuoYz3SDn+nh7AkZ1hUqaJpHP2ToNcOJ1q18OYYtl7c4Rb804rzNou9TgSo1CmohrK0PTFzT/Mqm+D6sK0oh7EhymFmuJssxZnxfB9w4gBAhnkk/e+tCG5JnOgARkNihR6/HJyfPuzw+0nfI8a3dL2Sh/KUv1l+jkdIvwrKTz9bWof5FLeolFDiBduJz7Zb1JDiiNQthrbvDBLeswiQS4bsbCCT6QTAlTnPYpwox7ADksKdj6MSa31GV1qZI6g0mJHXswoRWkvCVAfPVDAdGcgU9MbCAUVGxchfvdmIUBoS6Espw8IgIEwFWRreMfgZEMpEDhhzmAr+yxQ+zfqo0sFB4hO92O/dERyka+aSD1Au8FmC/0zD1Har0FXXXbhEv9efDMxoTKqmpXa3Ji1rXukqu9WWp2C0LllpRyqJOHwV1v8fZ7gytN7S+gtaG57XpXhJYKSX4HlYUZ/QWLMrwta1oh4a1HbAeRIHuijwU1EroDRGqXb3NW+9q3xHKcNvvTb3yGsteKSReeKVWLFWiR5RSJLw8m8e7hevQPIkMgVNdua7P5etkeYYXkvAIGvK4K07oanhTqpnWxY51AZ0gYt36SWEDOD0dpF8GFpj4C+Mp/d+RyemtSxShQkCvquVUeF8WvD9/h/OzM5ydnYOhfWdypfTT85Pwoa1pbt2qfTA6JMJe1jlvvfk1Uv7IOs5pfriz7FvDST4U9XZEdSbMZrEzY20dbV2xtiZe9onfpFJ0izUf/zhPuhedBmEsJiBhE66Oyn7awMv+qr3PLZTSFAsW/CQc51mb/l1TLwzeZjC6IjXYd4KcH7phQ1eGQ73TzRjK5lVq6CQwbykGmirUaw2BqYlTWAmYKNFkXXa61s+HVTwcoTkMCWjUsFRtVw0VeAWWvURa6c8jYxtgKuMt2KM0gHYmkMzPKM0g3Y9guKFZqWJvczig7cT4UmhsGK90PWeRbaCkRKdFFR+q8HQ+0iDF0LJx2U7/4MTA17fH7/KeHLAZAH4ABef6oHKLlcD8BK5FDcoUz7AZBQBUi8PX89OTfF9XN560/nSlrx0ioHz8EcG6l1qw/ngEsdD9DgA6R/Jyd+/3UoDDelCQrIMyN5cFLFGgmLEAHhHKVtmU1qEAGKuZzxyxk2Wen3T/nOvbZxnPUYFxHY+6GAG9hM5yPnzS6mKrsnts6SE/9VjGkpVug7LKrgdDJe9OCns4PQ1GlXvLI9fHN5jYYaaktM5q4KhGRbovJb89xvUh9YxnSFqUVGetxXEDADTjDXOrBFie5T2rIaZGE+os8egIiadhdn7XouK4wZk+BzUUteg1gHp9Ke0Sg1KODtgcd/K2iBhnujBPE7y8j52JH2n6vvKo1Hup8NFTeoUnGLC7jhjyvVl5nmvjozZGnDK2awL4mJIwjLDnGokRP3egSUBpOIfK4nFeifD4zzsUfATja4ApCMe9/D3lkgHCR5TrqpGjCPSPzxI96PYeZ398wuH6CnR3jw8cnuMZn9pvm7f3CUjZ2xFf7/tiY8cQVGW2GxaPfDEEE7Sp+9YZCKWyRZjWovIHmyk5eYS85xsJHF+CLKacGrLbb2m9UEEtFUu5kjM6HoT3q7JPvkEMP9/JZgZ1ifrwuN9pXco3ySaEBQyTLgdf8APJLJ/GHLSDEsXwMc8QmZ7NcH3iOaM7FrXEjAgas0bnSe3DSa7jSzGmMV5STjREUN7Q6IcqmaAplJlRi0xArWKkWUsHNYlKtusdKxMa1OCLgNIvwMTY/yF04fmfN+hgLJ8ugRsG84O2w6BPalR2c4H1y40O4QrAg8y/r7MNn7Aw4QLAVx1fGP7F2BnqAc2MQ1txsHAlAN4rhJlbhVGNxoxDqu/IcCKAIH0GPXXrU5c/JeOjhPfjS+yFC8XnjPDENXj68eXG22OI0xIz4Vshd0YC5MzBIFSFnwuQOvMY7xUOZgN3MLAbiT4rzj0Wy5MbQMorPI4P43cC8GggR+a5znBDfKVHFWLw8rg+Od9oc1KIsOrBvbQi7DEAUAkDzamXY2KpNGJmj7Dksp5xKtwwPrA/+xo4V6R8DYPDOIODq/pfdzf4g4Un2l1fq+uD8tEvUIM9PuKAb+EsoEthDgR23frmiTMn+PzmfCAPeN7wl1PIPr5+ypjH+LiiiN4jAMH44ZhpOaNKV3pnWS+qqV0W3AqWiIKGv7jrmU7BiuQ9huCpBJ2OJ40Pla0YehVnDX2p2fcQAE+tZr9932u9FtGnQ2VIbjTCNqs+36wNGu6x6JX5Ohi4YMZ9SfwrYgx5NEh3m8oIDF2IIaXKnkGoenYzPhQwA2+MPA1L1Jccxc+F1kNvMMzD3+W/q/wHKNBzOWKX/oLftPH931mmPgzMdXDkprQyb8nf2qY1fHTdCJ/cV5s8lTmSEmRRjLfesa5NWE9XuAkjUqmAuYnw02yJ0ji9+VSUZbWRJ5Y/7jvP60w3nIJmW/CJHjr9ODUb8khDwTXKJwLfMBZc4xb3uEIotwF42KFLzn678idjiKGZSpIwep3b81mRbvVLWPro20uh0+c5OvXcS9BTceWE19SoA8Rtgc4xCB/NL0MOdade/KqU6yvNb+bZOG7cBAJE4ZV/oczZVjdHxheofIGPuMdXD3mJNNhgNADgcMugT3cgXCJSrAo8lyvCencPsXOV2VO/CrS7lukuOMwI3OPL2/MObO3zt+C34zvz3T1CsDi3KnmWzYtEGaimVq2JWZZlUyRBacWooGBB5D00Ji0UuoPFzMSEB3OXGJbU+fJe7zxiuL/XN56HcY1M9LHFx5+nK9vQtvHKEC9ue8UG8AsS4EwtWD19jNdXplNSSKuHM9vhb4y17EwlBIdbzzd21kB7XH8qHfFPe86YXvek0/6a8lhClGWDHwMWOfC7F6b1RD3OTaBKbeyhCTvDuhrwQ/pwGND3LScoi8DToh7kgfvY3KNI6IAP1ZpBzAWzCFq6jx1wD3FSFVry1jMBs9VfoYo1MCyigI0l29V2EiWQ+dRXo8uqDMx4yslgAkpbd4swEPNIHi3Cfp9CwaJ4FEF0ofRXRJm9LKLgJoqoFVZV1YMQmweG5jsXHkHGXheAFed4yHgTYKkCvdhfqShVPNKLehDVumhYdQaxejalsOxmJ2DjIhWMGX8jwhiFX4o9PRpMGkyTjpVA1MQ4juHjnguBgFJEUFF0vKWqUUAJ44DawVzRekdtFpZPDA65sSrMrf4u3lLMHjYdgHoUAqTtQPev7LWicKyCCVPEDvAzIviAqpi/wiOHRfqIvTuEENSqDS6zSr53RlsbiA8a8h5Yyg6VCPv9GfZnEtnosB6wPoty+nB4RltbCkdpIfiNzrB4NVNz/AHvTVrDmQz4Y3z0hjKa7nloLMZgOGSK+0IScgcM8/Smub6RInkdPtepb0xjRCZ51AimfJoA29uweU7RKljrEgGDCm7000VdlNcriA+DkvJWngm5oNHXeZ/IbdlT0S8L42wUiUngt6c6zMsuvDFJUWhwTAZL/p2Enu2WRZdR3j7fLaqU54GW5VWQM8SCrhyR02VDyMzAXgXrSfvBYFcWk+5BtjDaLnAUGlJUoddZvPVjfQi6gY2hSms8E6jhS9qbmSrlEuqxeDq4DvsuPXvCmK07eYENAMwq0Nujs3jtrxx1+tuEqeWt3gHcIgqA5UQtZErexBhOoX5aC4MQrzvJW7umX3n2S8YNksIvDXORe+hLkZhO9jryDAWec+VLWkea5oW1B0+2GY4mhI+v5QvKs/Cp+8ZX+feZmEcv/G1jDhC8y1uKhSFGE3ozpHMwGEp8ryikM4Nis+KizIR3Mqyq4Z961gndUhoGU5SFYhvo7r1V1GjHveKMR1VBr8BbcV4g4/0jcs7TV1bl+MYjDdO9Y0IwlZkivfb3tvImrvPw/NaJ5fT1U09blXz01COAd6a81Lv5JFKrKVHf69k54K41dbzVAAAgAElEQVT/vMVfLnR1GdCUQE3wyAcAjForDtqDd3wiz7G+bg4NQxtDoPSxfFBwFljeKpzo6AmcyuRwrqo/ucexsz9Y/UGq0lpstZraSD/esyiHJwzj77xncYoQFCK8fMju8tNR3yOyAknrmoGXaLxmvK3t3Z8pLJQXy0/JbBrcjf0a6b392MKdgiMDstk9FP1cW8TJiEhCRBed0NXS4TGcb9NYOehsEQ1lHvvNg65lcMt80xV7Phz1/6Xfp9Z8HL9Rt/HpYrJVIpSrK/Q7iSDxdarUluNIxLd5I9HMX8B3eTsanPm5ZKK1FVfoRwGg887K/77QvtHrmfK+xhGPAePXM+eWQY0pxuXijKGfsQ7M8OgrJkcZPxMfqV+Dw3pjGWQ9W2SLYWdIf9Zf5TiPHQHGcfkXAdcMrLe3AF0Aitem1gBkHPRtWJU4Z7yWgsw1Rj1/pmzhp+zdb3xNFl3Zfrf7p/YUJ5BMqCR9iUKpH2H8DD8rzSXOVFv9TzTT4GHrrDy8s/194P/SVxtCTm17xeqouFGPw4Gi42GqmI/O3i+wcv472Gd3mzm+93f5u+A/ToH+f6NsI8x/TznRh1NMnGPaX9nKp8b9EqVQbEbBKHD6gwq4TCC+rl2YReoqJAsvIJhHO4zRZ7j3D4eYLIR0gcYjd6MJ+swaL3racZPuxDgz8+GjSnQmQvSMI78lYRSvboD9p39gvZG+PxDwiT+hgtFwiwJB8NaK5UA3izNToBNEGf0vnf7P+uzNCyBgXcpK+vuN5+dLpkjOdVk/Pmr/spe384gs4zZjDQC44rsjyrFpHz5Tef15ny4Q4CHiv82PJ0u4XCws3azEOB2QnMZw+Ppn1y5YBJ4H3IEIWPgSlS8Aus9VxMtpLhqAww1j/0f30JvMjMPtAwp9RKGP+tp9qkhMEPio8lPFORR9/Ff3+djWEyR0nAniLVAnMbADwK3hAMKZem55bmJ9vpCFE7KAi9sHIwJUiCah2wpZLm1T6LIr4nryBjZ7YvMYq6Wgs3wSgENv2h/Z5YekOAdkDNkzzsTA5vVxhuwxMZUTe2oTM9J4L5ithASOdl/MU+IZ/b6fr+aOmCBSv49GGMHs5sPZ8+EAIsmRTkQukK4mTEi0gwwHk+VCT8ymwb7vAcOT7OspZ6Y4QI0yUalb4EEtuin/jkMeAZL3OHHAniteKz47F18v8UQn95oi9WQvatYUjD2G9kBVn1crfqVPvTX37gWz0y2pZ4WwSC0Y/GdhytmtqFitb3lae6FEdZH9vzbxkJJbQaPcmFh9wkuRfdM4KB8TOf42g6YDA2ekIcmQ7fht/vVArhdKj+dYD1BGnyJiROBhSuMgkHpxiZd9oSrKbVX8yveKuiz+2w/Oun6LwmspxZXArTcJNd6A2jvWlT0ahOUyr2WBCcNMgV41ys1SF1RVoNeibS9VjAsgSngzoGC2kLCclki5DjbLeFVUw3Ytq/N7UXgzeiI4bKkVrRCwQjwZmNGY1PrbN4LNoChWAZRSQVUMC8WjfnFlOhaBxaU356uYGa11CXPPxesvXIBiFv0a6t2V6NGe9UF6rv1KIcvNsMMxA8c4T0kSTgpk0vRafT3Dpd1A0PbV80F2lCK57UtdcHZ2hv1uh7rb4dAbOjRdwbqiNVO4k8Kh0pzkkd+7Gi2ShnA3oQHTUdoNTjhg6mZ6SNIY2IwirbLTvkK+3qz44MgoxXBqen8UCzqHC+uS/yJp28PCk9bU2b9bfc4Hkymwgxt2fGy4GJkHU1qdlJMSnSLDtPKVzBo9IepywzfFAV1xpCi7Okg9+J1+IBkkEIBCzmdUQqIVUWotEWUFAJOmh1KewXq61DBr9RkukZOyPzNQAdoBfAAoGyEAangVYyYWnFA0ZKQ7a5EYtbnDTIfA20GeZzDWw0Fo3U7CoTcywzKGhxydecVBiWCDTZBiYZZlAeEbMMOMj4DhJpO00/2pKSPOAeAc/GiU5IdjLok+I/2q+728rhaKbW3AIjwjtYOlMY+sofq7av/9fKf80sIxLORlpi7UT+GkqA9c6w27pYBbF6W9Tp9vZyGfeNpQXMckWvvk8x7t5igL0aEclj7X9qg/z/MAiNAtZYxFnADQbTAT7gGAvcLXI+KRk8XGnSo5g3q0z28O+Js3Kp7gK8cvPdW2PZtKZ8EFtQA7IlVsFKBYHs+SUpOcHqCd3wPTBC4kEBbdj81Czlt9CivLIlEeKhGenw/qjSke7g7LAA5mtKHjkUhCwZNWooj0lzSKgroVp/o4EuL1XSzlaVilvFUpfpuS6sWJf02ZAct+n4Ym3vpOAe+baoipmyOOiSYfITnRzbvRzLELfcDauwrxv+JwF/KJ73S6r7+jtLuG5VqiG0lfZd/VpaB8LnhaV/S7DjPdmhWFuXxgOF2vV1dihAG5dri5SbA5lrxKgnuU92L2lFTu2deFoAT8yrmnaYSw/ecdWrtGu1vBSeGUnTzY28HA9xAR6qcr0EMF8ADPn8O6F6DnDSI1kIr6rMLv1v+kaJX26QhyCMCPI3yKicYFD5KZJh/LK5Vx0U+LuGWouSBj/DDY4aN3jT5GD4SwD3mCVWlOyqew8XosaQzkPKFRw7oZfAG7T59AYBz+dSO8wRfh8ytdgvge9dM11ptbrevC17YbP+T9H5XpsvWCzwMsupZ874r/zEPUpnJaXQDksjrW+VlvbwObbK3jMI+n1oim2z9by/H+R11+A2PnM/S3UVu7LjFJNTIDkyb7jGotglxhidz5MHQvYkglX9yhxRHKtxWPgMmte5CLDP6YV1CM8uWzDOcHgsz5YW1eswzNjNHHqXO5wDTtr8GyTqv8THy81jOt3hj6MM6tHtwRcNXZ05hJBE9gf3mF57tbuLJ5ow2LS2hcusmV33UMymOD988fr9C+NtypL3o4YKWNkMi575c3ymFNnhJG3lJvM97SF0QNhbk7XHewyBNUvyJfWfsV/ZB7gcfG+R0p/6DwTjokx262HzbkzswWtcMcIeDAkcc5wMJ0bvGIZ1Gp9ntinZJg4UEjnt1S9DQbVHqikU0aK+dN4eNiZvJeO4JbH3PaR2+Wv/9d/pvKf6EC/T+oTIzjEYnOBCAzln+myfnCy+erzfd5QrIiDO84qIDIGAQqJgSX0LOulLN//iRustclC/o1VtyeeI5cYDO8zEdfN969QruRvO2f+Bq3fIuVv2DBJxAu0XE3PJ+trINRE7Q/iOBZ7pty3DpQePRaz+X+NyDzzHS+psxH8rGy7TunmA1mYXA+vBWEeWTdLCxrbsv5giM2YrtMfCY+cgrvc6J8I2Gyn748DDmhCgCmrxDvc/sE6KoAd99PDwvAt79YYHCqbClAdhtQl60RqVCWGMdDOvlyQM0HToSyhxLfZk+o62wI6UfmLOyzj8vW+h7A2KXffOL7UfnZmW+z9Zdq/LV9urXXXKnAOhuONvXpNGWmbDUlNwBRMplQGJADvt1ThZLnRjXpCmv9+umsLk+jduW5MefkuJ/NyxHkB4YhJ9agVEqiQ2WWhzx5WZCiwgO2y6ZcmZeDgSMIMG7d91z2zuE0UgbjILDPq7eHwwxRoXTkzpDU8+y0jV2pyQH4G4KaPG6fG597coOzmBNBPhIEVTwdxCOLQkMxAZJPoU5c3qWzAm18Ua5TLer9LaHHd5qPfLFc1bs9drvFlcHGJ4i3WUHVg6Mf1DRf9NoaymF1j/Om8Fr0d9XQqlTV270WTRNj4eMX93pfLI9j757fkdQgIeY/Jn08YHZwl5zpvVkeX3m/dJYw8A4vss4STlPDYtaC0hqWJqHcxRM9ptFyiUEVjQUFZSnY7XbYLTs1ChAvajHkgObRZgl13jtaa+J12TUXGsHDXXfuqCyhrSktOA97mhwXtC6InNlBArbXPcyuegZnWAoYneDY6bEpjlh5WvMRiQO0Kx4M7cCMcoBSCXW3YL/f4fz8DMuyk0N773h6esbhcNAxZ5glMUogwtq7pGTQ+UHTEPG+/OzdPzp8Z1w27wMbvwtI1SDFFQHylglSa6lgbqI0m+cpgeJIfLLZBad//W2MUPszGmfPT/hUxwHKOe6ClrjwmzHMR9CduJJzqQYujUgA83hFH9UcrwRaDFxMahwguKl43QxEKhiktWczCyxgNd4tVIb5GASQTfFpIaCKR3p/7ulsk8fMYN6B9haa0OiTPECKq6V/JlyX80Z/ZomCoN71Nqn9+Rn17Cy1YWbB3tujlfxZOcWRjPBs872D7eQcrt/qkQQbZiwJGxzq+RlCkkYhrV5bMjRIbb+if/MYxpd1YjWiBrohI7m+sIRpzzzfM+AKDKPoW7MZsHrcT1+NZAUQ5DPxDE5E8/434+4maSOshbxtNor5/ucwxi8W4wkgUZe887mt10z6XC2nM/obiynSDh0gTUs18H6K+O25rHgzXOOGmeNQfS0zP2z3SOHTPbM6oy4F+90OT8/PqZ5oK4eINvqn6k8ws9Nh4eMimkSGgyEO6KvnmUdmLLQU2NhCr6nt6FtmPAYPsYkGDl1mu7P97lh99PuIZ5yfQ+yNevUR/Y5Rr+v0jODH778Q/eCtpVyO5yPbIt6sw6DMhHmgv0/9ovxHBOBCIxyM5XVb6MJxrJ/veKT0KQ6I8iwUOEl5z651wZMYni7+HgDcQmyLU399bKyG10Tuiewl040TCopT/TB48Bq3HjwlW4KNXffkGBrlRFuIiOHAqMyZY+mnlqIrxsESYPwHaSh8woDj7M33bIaj7BFWOn8A1CGFDLdMO5g5u5yE4jx3dR5pRvdHQ8m8dsbtPPJfoT9kn2NDjJlPYKgTj78/4oFjOZxV/Bs2NpGnszy6lb5/JY1CCTUQd1ItFy0yaC71+hq4uf2pcHTGj5S+x/XxDeEJE2//qrkIuORE0x2Mjdb74wqDdsYbGcrfhlYHr/LtB7S9KR7ViedtVjTRHYoqz+tVxdPtzRFs5yK8aqLhUztbvF//2rHi28aEpKdPMY0nyhsff0WF4ZQRdCAB5sCwBg+S5at/Sk+0gXuzjI8Bj6pBv9reLAwe7m3FHjh65HXFENJru7WB9/8uf5dT5W8F+r+puJV7XHjTRv+3FU7MkVkfqfd5LYd0qGDUQmi1gmpD6cJE9KmuUz+zMCkzLeaB/Q++AsBYcacE5tbzfL/QxMb9lw9t5on+ia9RUHHNV2iqNCfUwQLS+s0Qy92mNxYAq3btmoVH+6K/L3j0LL9L1y2ku30C47XXlNmC+uKNdM76tWUd/5GBb2W8HsqY6eH0O3ufz89NOtSjQnYQ8PeigtdsocLi+cPaj4+R3R0f+Ngzfi4PxPjAZiEaB02B66/K4Ioqvt8RGFW8VNIhnCCWr4+vYWtf4iDfWJL40UOcmyi1QZRWnf20ARPsliTwKiSeJCFwkCdtH5RiPrLwwxeZVAAkykRouGplFGsVS8sCAi8LkPZk7x21iHKMSHOaQvZWzqL4DGnCwnXu9drZNN4Xy8RDH98EfroQutZ+mD2xD2YLRz/g6cE8e+/21JmqHo6td4D7oPjIYzisKyw8NwDPH1xK8bBGBISBg+VAVwG5fVoOOe6cDsfHRWRlsm6uPPcDXfF81nH4GxXozoB3UZ5ITsqkcNcDu8AXsCzqCZcO7tZf+z0epZAWZVwfF5Dm8yh2AFYdF4BnHmCDTUjs7XWgqwcCwuuYLUS4tukKRhMjWb+n3HRmgW7vdp2jCjkcu9JIvQPBcI89q5cQwgPTJ7roMs+PnIg2D4KmLCoUec+rKtNFgb7DUnfY7Rbsd3tRoJvXZyy25LyHKse4q2WweBMfakFZG2qtqnyWntVaQaU6LFjIdAsXf3a2x36/A2AeyIRSCZSU8Fm5IUCU1t9hWQwdWkse6JZTXBAgwMUNGcQgiEBFIx8wo3ZGrw29M3prnvM8wyXpOMRbVwwEdnWH/W6HZWc53SWPbGdR5ANAa4zWVk2Ts4r3kQp6xauPNI+YKo5ZUyJ0UfqxesyR4mrZy+aBF0r1I1lX/kyCkS0iG7xszDaMx037ShSo+YLJ6UL4s9QF+/0Zzs7OJAIBRHd2eH7G8/NBcowrNbM9mA11uBu+YgH4Pud9FMHrKV6Bj37YBmbFf4FjBo9JNYygSpork93rzudu2HQJQ6X5zzz2uBRCvY2G57oidHGa1DwIxUuhmYbPGRVS7w/ytbA+mRFQTnVAUMEkTEEWIGG8v+RqN0W6jTbDRhOhEPsINEhVBzQMrIVGNViyGfBibU0zJDBu+5f8OWupQWghPUc+RlGaHIbQsgTxGFn2hhvN818F99qZWivWtgpv1DsKNNfkINGKtWFIaFQ3qlE+qKhAu7VnUF3A3SKzYFpPgKZLY68Rki1zybZnaO/1Ze87ftJVOAfoR/Q3QJIHpryjAVVyYKflib4Z/dHfj8Poo4jRI6HwOcr7gvb4PQ1IcCyZcikBvcGopeyxcqZrKZGHNk4tR8wLJ34gFKXQM0bQ7BAIO8/gA2c8J88c91zO7c185UY/fmxyVtvlo35+BcOyyR+9/srqNl+bmIGT80hxgcHonOFVZACF5GQu+6SBuSuss9MehoBsmw5+bhxgK6Sedv1gkRRkHfYaoeiwHlCI8HyQdVmWCjDw/emHrJvB67RNGAAKoTcZx1KK01Ox0yHHE9IbivcA93Djed3TfeHD9LmMn/CC8nwkq28qzIwL/ogHCtPwgRYZVmbgXPv9neLdU3XOvynxnX69j88tVxfCv32WMf/45xPKVcF9lgj9whjfUi4YaLcNDcDu827AoT/+dQDwFWd/fEL5VND5GuvNCsIDPjj9ymn6LlCvK/r9PYAH1PIZBBLP0BQ+eHYWmIdYrorybxIhp3BETAJJNBVAUlsUxO9uERiUx6zXi8LUNfpdV8/bo22MprR/Icghg+5BtCh/rjhbSDDcQI2KGJCyJ/7B+9bxPeG8oyPowA9GT94z8DDwTON8bMmZMNRn9MVgN+23F+Cnaz+rGsBZH8mMKSYAFraBnAeJhs3gMN3XcO2AKmcNgbKeo1nWi/kO4I+oV4Er6udrN3Jf/7XKMPgO7eYuaCV9dVqW0a7x841ELgWMymWjwwx1ENGXfGWY03k0iqntRFk9UuwcAXOQYU8K5HRs3ywnWO+fFougaUrwufcFss+t3Qel4VeKpwx+CRHVszKw3ty63GGrn3N/mRkfGPi+eRYyOQRjXyPaEkEiij231Z8z2Noti6ZcEHgrpUBPdL6FKMGiGdQDHMbiqjjnJBOa+cRT+2u7jEr/mXf7+Vu5cdmgNvczHXkgwiUDxA+ofInD7cHzameKZb03I1+r5dvUN29n6setqWZnNpnHnntGz0E+d5x6It/LxZ6aPdGPnku8OfkfuSOBoByR0IqzxExocXqTTX0c4ECPJoE+g6/eUhzPDpx+BiYe7s+C+6Poa2ncx9Erpg7q+9cQL/J7Oobfoue7eX5NwpnXgeygemILuGE08roHrv+7/F3m8rcC/d9YZus94zwyk/RnPc5/uW/T72CBMxkLpNJaw/PBhiAhpwpRYiYUaRriNrI4IXBjIEJbwwimIfeHNCBOWPcVXOKSH3D32pPYG3GiWVQDQIMKyvRedtTi9LurwhAs1x6IcZUI9T0Jw/eRj5XiHzl/xs3XKs+tZIX7byEDup5fp/r+SiJDetBHgqWXLWCB4+Oj1SWhI69YD5RvLN8oYPKjnr1MDGDW6iaIyKHU5Nq/Zz+PmS03Sl47n7Z5r7PnQnfFAcHDJNrLpdRBgOJrY0wa9PBYiz+XD7WB81gPH9tztoBweGE+9zqCVynPf1t52xFF3hi/83ydeVgSTmvjFuOI1RqNs+yJ414NdMZY4rzkqS0/xNhBIwkw7Jo8b2EMVbAACuX5wJxS6DX8gGlhFY9xyeAlzbmT84ho/K7C98jtKYOy8cow4l54mPmQfKKsu8OZS7+JvjKEic54K9Pue2XqXtR8YiQ2Xg3z21XoI5MkBxg2xR6PVZJ3WlefGZ1MWQaHK7mVUxxkuCIQCqhIiHZTmu935nW+x9mZft/vPKd3WjkAokCnIp4s0lYH9wpAlfKLKIfXtcHQPJEo6k3ZbErxWshzhpciYdBjwHY4685cmDGKLHXkQmbu6E284M27u3OP/OwEkOYMByTMWmdWowWjO9JPyXyxOGx1DcFu3uKuLNOXLL+7GBxYLveqIe7V4LBK+PpaGWsrqK2hFEJbi3qnp/ViBrhL13pH4y4K+N7BnXz8ndOedeBmjwqUcUkSJ8Q8+j6w/ZjhhxIc5XcyVosamC19gHri7/c4f/cO796d4/zsDLvdDmCIwrw3yZVeCLvdDq03rMs6CurTxqUAZr2SvM5MeeP7m9O7J0ray15nZ7Cnag4Gi8woocjce8qioTcxbz7hcTtwKpmweZxDM0zIJqk8VWRGaoZoyYLeFYHrIhYgDuOlVOnZQGgE/toh4iINNMrWH+F9C1IPbMs77nx/zDN7SqeAMVsL2ycW9tCMIaSNwC2zkiaJ5X1ey0Qvsse1bOP8/ALmg/82urj+eEQ9P4dJ1Ry+fSLEAE2UbQXEDYUKlj2wtgXt6dlzzXMhh7vBaEKFQLYDuTfQUjII/0Ih55vPzoIDjG3CePrxQ+FIL/4A6JxAj8e1jYLR7f1yiiq/VA5gVDD6d872HQM/YtHLBvKeIDG3y0ghzX/WuD6T986MK4hafnTkiBP+62lerZwxQsGNk9OGc/388Zr+pr78JYWNHrzu8Qgfb+xKvCi2N13sOFKu++AfofguKQtyVzBy1IGvYcyu7J3Wle528ZhVnjLrQ3pnDPiWYj1K72CK/pkMo1kbxivpXsmKjLG/L00aOQ7J8g5FBi+/tzE3Y5n6ker70Alf6ScKEEP307vjlud0OdEZY+A3nrMbEoI88DddEtbbMXrfX13MiNTJGxLeMJysqW16E8XnfDazv0W96IvmOx+UrIbDccz5HPXpTgwg6Uroguy9OJFlZSRSncZnCOuhV3Vuy1UB69RamFue3idQMh7hgHEVXJnxNZOo8QhiyG19+QaALFVRpmcOp7nFoed4xyI74gQ2yk0m/E/Hk59/soUv1jYJ+NB5M4pgphuB59PmxzjH2aPc+fbEv+fztZ+lbJQMP2OIASuDzCiYP0IcbAXvdYSxcO8duCbg5hha8jzlGTV0UgdAPi6M5EgzPRtytHEeHMelOTLP8/zgz+Vwv4dKXXBQgZf21AhP873xrfcKOsaF9o1nNtvQsX6faN0ge7S9pfTIYYQIu1KxqmGFddbmsStsSBQmdkcGTy/ioffjM4yHjV/JyuXfM/+ZJ5rngpV+H9EwvW74hZXIhBJWP3l8yc40pzFIyFvt2oWeH77q01/BbmT48rj+JIv9FxTHqf+HvTfdjiNX0gQ/AzxIaiEpqar6nD7z/k82P3pmulISSS1khMNsftgCA8KDi6Rcbl8hTyoYHu5wLAbbF6MF3ebCOEotMDVKR9YdE5/TXKMbjhjTXm7tveMNIh/1Ke7/8RU+Ps/9/vcMyEtS5upgB4R+AvWdHk/C+fP141f9mvP1u/1rtt8G9H9AG5iPdPjzgT8ytv/sO595R2bYdRwYmC3/e22rRkORe/EtgEWMudDkcq94pOJM4kWNvcpce1RUQoTS773HZxAECzoxZdygDOgyDfzUAjyHKwNQeuweAK09dfi4gvAOgIAsKj0TdiBl1LX3XBnDdoXuzZkN4m7svqVeW91/3qp/fqrl6eWo9Vt6zt5P7QTMDV7BwdBN99jo1dPzGp/KTXpmhKW30sc79xNMQVrQHIne+6GBIZv74STnJrakC9YvbC6YvLbvr6fFfQIK/7L2AOAVTHAm4Fw0coWgdaEgWj8UtdqYXYjXM0jQNT7fXWClA9Z2GDhfV74TqWK+kSkgXFsR7FUXvFqzmtNRmBnxm9cpW2qJfS5Fa0kTgPUEuxbjsVfd/5LV22gu38+HiWBGCZ8tDff31MN+LQEk+jI481vsnqVWFPJa2sBut4BIa4K6JzKAWKswILhxESlaEP33alaKTl/S3GzTxQfmGNtxdwB3+lscXka3pzDGZmICisidOnnCx5xMIh3ooMNjopD+bzC05GfbDGWS7o5IeX+bL3peR0vdLgAOrjD1eKi9bfMrsNzre5p5uJeEW2z4xdc1QQVrEeowDGf8NayDPeXKTSagSgGTgAlYxFIcD/dnxr7066RKsGwKy/dKGmFk2DB49jrHdSEsixvTK3ZnFoW+LJFavddx7IqBavDr2AUMtNIAIjBX1MKacvVhH3tcSgFSBHp3zAMEWt/cM14onJvhnAWNvWZzh1tmjShrzdKeM8xg3tAspbynb9dzQBYBatAmBGoMLqyKRlGjZDFnwVK7h7hE7fKGLGS5gOoG9FIXLGcLdnUBEWmKcog6HJAZ5Ire3yyt/VoaDvs9BD0iyfcPZjyndcUKh3FJjJtYLfHMc3bgcTV7Ps4QxiwodkURpe/dsOAALX4Q0jkNsV4EIE3TvywLzs/O8Or8AhcXr7CYM0ZjBppGQa+shsmz3RkO7YC6ajaUXA93VuIcZXkSG3JRXJxTT/fsA7OyyPY0H01mS+fpP7tSlaA1xwWFrUa9RXR1o+w4vlkJh1gjCfwrvsi+lmyraPSh95FwPSQVioMjgYBBfdbLJFDg1ejD0hiLCKT0GsYQO0sQFNTAw+FIINDxmcHKnTYgPeI7ZmgwoKjenWenlfe1K5MBrG+p3UuxTpSMYRkufG9ZBKs0ra0tC5AM53kjNJvImUZov7J3sECKZeSxIHp1RlD8Qyggbvo7EZh2nRuINEASYKSRcADzqriZoKWv6tKZ1DSXfD5PtbOzc7jSM5HE/oddq4uqAA77Q5z9U3yVMEcqX17b+Fv6mwDs0aONdiCcW69zlPUZ1K2juQlW0pTz5to7imSMDhQzPXPm9Gx+jyu3nlpBu8vXj9LJoHGNhjNteDVHxp8BeHjidfcbu3oBhIu2r0mD8j2yQpQAACAASURBVPK++i53nC4U9cKWj99jDHZqg4OAGdv8Ya8BDEakuSbyiCF1bPQZihAWe7mjrc5D6jdJ8EGimQ0IwGH/YOdQ+ZQDrzqa5GRztAXpQmmCg7Sgh98fFJ6cftRSAdHI9Ca9BvU5XMbIxdsk4CV4q2bXBuEUYJNn/EnHy529lvxlo2Xa0f++EF+rr766R/cAiDrNX0nwSgSvjUbNhsjZ6JHfPkR/ib9fPwuA3burcCI8rIpnP93ePnpOn3c6X9buALyVO4WtP95CAJx/2AGkqd3bTV/rUgpwDbTPb6Fp0TXi3INBlM8l1P8y+SoZinTvL0EbiWhDNsjXrvs3zxTm9zBULi+laNQtKw2upaq8wTZmOxAuH5JcQuhueKeTnoKemYoEIAbWas4m6fC703OhglsjXOFgxzyUJRlnaNeG9Og6iq8AGnWeJtaCpuw3IX9knqQ3IecpKDr6Uk7jfO+XRUIuCzxC8bL0TsUjIK9DfSyb6UDSKRXdv9esPJ9Id6AVCEhugZu3ul1X5mj7SQdf3hfIJ4HgNvi6mSLk764z/M93VyAi/BeA9aNGrXOeGzBoLt+YF4lHrNeSnSxzzWftY7Xt/pLlBKBnkZp11un6Y3q4lzbXYhzpV9P1Odsm0r23lMAQqg8lQB0aAUiSoTf7GPhrgqcMeSUF9ySopUa2PhZGawyAcWAYDPlZAqiUMLy47MLcsDe5kAQ4sJ7jShqJXly2iPH0s5GN567AyXpRMb49w89T+NXh+bHI82c5GzhOPOqvXwNU91sAnH34ACLC/cc/Aq4ooZLcMwNG3YCrCT+8tRm/vrzE/3d3m+wCaYKYeOJ0fc6E86P06FTk+dzy67suTkCSS1E5pOaBndibU3jQ34GJiRUJ+SnjxFP9yIT3qGQDfJ+QzeRRXjz/ci3ADdRx4ANrUKTIHW7KdmBSOFUn+Q4md2EyhD8HBWXjeQTB+DW9wRfgGb39bv+nt98G9H9iSwzJX9YGLcDjbVCUAjFeZmUcVlrh0TrOPIorL8u2IObt6wvGAXRGMT/yToDPP7J8j7yb1TcQglsseA+AcPZhh28f/zcWXMfjM5M3K1pypracut1bNqbfkM7Fn926/yXth9flifYcpw5VDKrx3NNJvUmL8ZV+jEkZo22HX571/MiW/nj79hcf15e2C4wChK9ON7/0qNx+Gw1KAY8wW5ZFBTWL2NT+WCMoN1KCAX2fsg7JcUK/KSl6+lAT0/d8CAm5/k/Yl60xPtWO2D+aPtHXfNazASZ4JDjXLdlYDztHagB9QlwSx+Qy3DWUTfaXIY/JcHkyZoQhBC7AdabTacEpJ5uYO03viI++0qdQ9BgRkx4RnVA2rLsgtwUkKuC1DqN7xy87E7Lv437Gd7jxSoAUweN7o9YVhjmEiEAKxfoN0wyhiWw2icYaQLhjBBOhmLGfrX6EOqVxvB/DOiboIwJkhMaephSpfnAXhHwvNVVhjXPuEdP+P9L+HpsKVciK1GgVgKiDHbMZpW0duXGHl2RA10/fxo6PPFJEjeANjS2iPCI/VJEurPWRHV5FVLnFbuyLJVLHjlq09rorKrzeNTVNsd5aU4cJBriocYxKifGBrGYzW5SRZ2Lw9bK1csOicENrK0QIUiQcEQr0mWr7KSJotQLCkdZe+9Fx0dogxFriQlZ7xmobJwVZVnBOGKCfw5MCtN86Y8Ej7nB8LmAup8fV6PslMhwsVirEhOFSsdvt8OriFWqt2D/ssfIBbT3gICva2ixFph8BxTeldDjhZk4PCa+IdDgLRcfWfB9B8ps04AS6jRMxKCMFG9qhR15g+Jq6U5t2OUUBTYxxoEJkZUCvgS6R2nN0cnIFyDDmJJ5En2mcqkgepzAY0l2hEnRDEvfROQ+bDCJalcUcHzo+1/Pv7z3eQz//I5/Yn7XXHzW/s+AMTAcUuojf3HnM8Zygq18LwSJgNeKSi6Ce9UWTWM5OE/PeOBZazLCtBosKloZSKwoJyrKAhbE3Z6MMHmdnPel1WsJJma1runLDzg3o+IKCc4hPc4vQruZc9Azl0Q6E1f4+QB2dtzhDgRqDM9aYHatzdMz85rxmPmyXs3Jk9EvaprLP4c3wZj5eCdriLy8f5GN6aQt+PTXG6fn86Fz/ihbR5U4/TTkpwyoC80rmXciQQQEJHUcxS+CxMF7hGIRPtT0YxHTElwe/AnUiBAhVBGtSIGu5qMCUA/QOoGS4KE8yO65qJhDqxj3pDqs/2gxzPvq7t++k0cHz3T8aZVUBLO8uj67/mZnqnmoOE4wvILydyOtbuNLcS2rgXQXwTvFKMrB6yZMOKBNtBTAb0Ts+2xqV4biZHch0deMZ7zHKXMDlh/E9lB4TIDLHqQXS4JK7HuO1ndOFCtaiUc5SthwMJ9gI2cIzytAwcZ/bazFdX+I1QDTZ3HvplNR9pC4fBb30ZzqbmZfxxiKRGVDvUf46G0wGw3kpRzCbI26dt3ZjufI5sOxPiT4TqaxmC8I3mpmDm3YiuB3O2oA60vdsKOZPgvJBLywfrrF+/BxlCn3mc3UI2WBaT+nRvuT9yG3Ck6f1cD/fPLDmFBb6EezUea7e5uyRT/VApI5vIj3L6mKcSiOJaz4+L7cF532R+FIi5ZmSTsWN7uGk7PN9csLqjNbPx/EaPbaemz1ORvDZKN7PnPT7SY7h5kQLcDoFb/P9xn9fQh2j6JFn3gP4/Iw+/1ktyTfS8VRcyzgx803TfjzbjjTd5zLDVkDH5mjl+Dxt9fdUuzGwvbL+dv+x4Nunx8vWepaGn7WbBe7/3X63Z7bfBvS/oR1H89BwPUeiz0z3j0aiP4q7HqWmjshHIj7fERFXHllVCgp72lO2VFACYkT0hjKFPPSa/d2ycilGYl/ubG0+SFK2ASBcg1Dwjj+rsXhLOzZP5BncxCf6FA9dyUfIHx/wkT7ig7zH8qHi8PEags/DmpjzoV0QNLjSzeruPP1afLLPd/b5UiN6Xrv22I0vaA57uQb6DI6zCt0Zcff8vDYCWegKK27xlo3ZD4Y8zyHv73QD0cC8D5G0fl8a3C1ZSvw0PBcyCD2V/lNL7GM6bSo4eqC/7EfaTz7/AEsTOSlIurOHmJKoR9WJmIIymGU1mutv3AtRiRq9lGmuyjhb+thQlAfTp4eNcwor9HNBUIE1NPAujMYZ3V4Ak0Fm/RTO5E9O4T4Jkr4ep9BzKSO8jrgPofibW+NmGT5mRlc95Vsb4b6UmtUrCHViDp+yNZX0XFbgxaAwCUaQbWZYYEZCr4FNgHihDX2mDobWNPdR0xj9F9I6c8cSoEOTTcLuCWGVOeYSQzFDagjPXo/SBNlOizSVrxwEqh4tEOwBnKGevcZ6+J6iOXRlmm6eDUUVL4Usnaho1FIhQJqlKM+1DUtRAzv12oZnOzWErKtSCfLTkxWscJzJKFJAnPbZWrPZDnDjQjnBFG9dURuq6Yi+sGgMpHSGcENwd5TQ+SJ4Fo/kzkYigCKnKolgqcBh7XWsHBC5aP1kGGx7VLsLkR6FQ0A3fBsnO0SSmwLLUzV7SvVI727/kyQBvFpqTgLK0h0EiBTHecYHgUAOup9Egipm3vYaq0mxQnXBcnYGKoR20BqtftYBi+YUj4Y3Q7B5ni+2XrVo+n4WAVVg4QZh47NKNeU+wE0jZFELqKlpCsKqzPMDMtESJ5EdhPtBOqk8D8cpha+cWUNrYzsO6G5ZAYF2ThgGt4DWk68azU+W7QDcB7s72+HV61co96roPBz2eKgPOLQGOI1yOkPZe7zP1eGcbAxcLKn5pPzpjZDrmfpzMY08pzw3OB7veEwNoYkdDf6EjJ6OSm9J/xqygtbAs/UUV5eTRWNlfCrR0Sn+JJ/jzCOGypryteP5VzcA2zUqnd5LRGAh9sSN5+RrYWdS983Pe+dB+rrY6onCSLPIHKeh2YBMRm9AOZLK8JEpzX1SAo7YecGKQmZ4lodhfwSEQudwDwHdhVSn1vcV3ci71ILV9rrGmUspOidU7PMoVetgRtknUGT2qbV2eIqxScBObvv9g9GPvkaHw0Pg9lIWBGwlAinyANyfg14pbHRjhY1TjM71p9M69HrmYn9n2PNSO2d29cG+H5KxI59Ax8n+trP066g8pPR8GlPQ9FNNHv06TCw3yqPdeq5feEA3or+GsoaPZ0TqJ5H88KTXEjSLVAwjfVbSdzw3Ej1Sxue3S9psjNPfwIxHLSt45wcbmsamC0XGC7HzIZAQJWAZX6TNGQ4mGhJQYOfScUvbwuPH491Byz/5ceqr3Q9YAaGJw7TxHFWdC89qRRPA8lYMuAXofNycMeNoYWLJ9bz5vKloVNVTxut5rq9gaVXt/LT0e+7rlfPxNoRXPLIGDh/fj07m1NdsWExnlGCODYb/aynhhPAkf/Enta82XC2L9wUPH/X78u7a7lB+sVgNAI9cdB4pzl3KigRAHR/Rz8Du/aJ497Px6OhwBiDB3R34RhMQ03UJGky2RmUxdxFJ69oFGIg5DmqKfB2opoXv78g75NduSax8jqCSYIGgJJxdLPPRHQAG4Yr1LHwjQRPnJUfu4AgTu3yVjG1K4NHrp8fgaBhsOEslI3qcT+rw7SUhoy/dBBy3RDMk8aSZZSq6r7PhvGz0J6BIwT4az9l0IToYXdNL1CudHHODgLB+btCE87qO7bPE0P0cjhRgNJy7Hu1Ad5BPyTnN7jl/dw3+JNjj1rJOak93EwPazPh0ZYv3xfblmq/xmW4SHzjTy4lI0JQxdNJT+23Xokayl7QKDfzxlNwzPAOno8/9rkS2h/F4vhQmwYWxaq9EnYnG5jSh82WNGypVlVuM3/ju/ClUfKmFUKnomRF1vKJ4v58LQUVFI8vWRj3qOMv9ALBPGdLiehrrHCgQlk3kc+Sz7pnmtiKuuwyzjaPn66OOKHWUfnN5m/0+u3wL4D/4sj/El6hyCzb5y+G7nw/NVrNCjehsssM1tO9bv+tOzeszL3gUYf2LyNBTkduuQzmOTHf+RuLfvpc9i6LLZjK5xcQ0ZOJ75z16wm4UzvjAaFCe9jGwvZ/z/J70DkfpXU+w7VRxZY/fEHAlhNfv36N9ZDz88QdQCHcnxj2SoB7o4eMqeTKbbz5agJifzz9Hsf9uv1tuvw3o/4B20nsvMyS/8n3PuSlz+9OzmTn3e4MhMSayrc0Yf6sp6gWorJPZcP6jzZlMgtdE9yFdQcnyC9uJefe3EW4J+CCC/5AP+IM+4vqjEu0F12DcTF2IjYWwQNDkc8gKLyntoYYaJayPeWOdal9In/uVzY3nc3vMqHxHKrwuchVM7YJrMGnl+q9PzGv2vovrm2dogNJoXwi45m6snz1038rT4/iXa0nZPBuavRUArujdYu+MDw9BSVgGhKDCJHfmY3hYFeulKlPSNt6v22edBSMjnuHVLm3v6an2V9Y/P8KLRze40D4ymEMr497MsD4qRU4jK0rv85IZjngijseUMM6ww79GB7NAJMO/+bpGLHdmszs/UcyBHPhompdPIwmVw4x97JvNjb8dEHtXXYgPwSJZC7NBsQuKBJEVHJHnpStbAMhesJy/xmH/rS8TgCIyOKMAKb0cMQpyDUFXNvjzPoc+x8BnSRiitBdZsSEsWjIBgmpzr+RRxI4vc4ouM46Qv1MH5jCjSiOHIQTMiIhFVTQwV7SmdL4taxjkNNOpRl3DRN8tYZIqBa4BgKVaMZaD/sZ24KtFgHtddV3DAlg9cjIFkPCC1hrWtVkt9VVTtW+cD42EN0nccwM2svTAalSl2g33BRbZRgJiQqMWNVchDW1lNDRN15z2DYAZtytQi6bej9917UUUPnjViFBpakynUrFg0TrakdnBxi8AqKBUNVSXQj3dtq2RmCNBY9Z09oqgFeZIx5JhHv47uhAOzPgnn/8A1A476S5OSppTWDGMrY3D8aGtDevhoHvYGmotWOqC8/MLdcRkUaeSMp4VHQbFnNwBZOTEfJoMqiWezdHbcaPdvIGNbBNcsdXnJ2bwz4qnIRpATPkhczStWOiyjCg9M9vjn8ft0R/TbaH0p+O0hj6PtBZdyTUQJV8Ce68phETi05+N+fs1ACzGrYuMKyxmhm5WN9IQqESaS8GcdWWOOu/KdB1kKOos5b7Pk4jAwWPgKMqjr9dB8Q/O49wKZWcH0bq5wRfpc9XqxxbpcAaoQWbLGEUJngs67uYUtQsA+/vvOpfKAHaY237/YJ97fU/mORyOCGjrChZgXVOJCboAXWRAovQvQDjDbAL2Rw/PAT68lHvrLfNxZ3DcBNBrA8JkOX7eSJ5of4Jh78WlHHG8VlvH/EdHenIfZGBFnt2eikJ0xT+zRHYQZe36mXjuXGJtgod13uDlA894WKRjZhY1niM5tBCRZhGSghJ4ujvFFDeSZF7uGbNi9HT9v6qdXFPD6VtpccfbZBNIZvpwas1ZBHSTosPem/npTzhbL21fCHgzDaNc54AVVcSzcfEEPi04xzMhWvQ+4FxwYiuebDR8bLWZJEMkaMbUS5wVgs67UC+FgZCLAJehur1Ao7BR9dmHKijuIMpqQs7UYXybBE0cnPDtLnci9aQPnZdKfO4R/YmpIlYzpitHe9Of2wTi5CSsmaZK8NKedaobk6ZHLZNVd8ptzBBmvPK65/C550rMM38tsU75jvz/Y2nJ53nmxp8E5T3h7vPGjz4JOl6ZfJ6v5LSe8WV6uDQuqBH9RUFAiRDOcsbjhvPp5kd+mmntqUj0MxD2Piakkl3o59ydlgSi2dwGecr/7VThfGsM4nqMaT2Nhm5NZzQSu05hnL4aFK3cIhAw3uQ54VWqz8fMt09jsGEenZ05SCI3Dai6w7q+V6f5dwUi18Dnm83zwRj1tvlVmc/6UX7zn9NGWqttXJAc4GR/nDyfj7UsZ3Tc6/LDPJpxeE5LnmWveoSOaqlX4P/5/Anv7dop4/lRE7Ga8T/WHOf7EH8bz3+3p9pvA/rf2HI0+XYULQVSeophevY7/dMZkrnjDbyWIxGcMFPmaPwG0V/byigLa4pTYcjaNCLEhF2BCZgTI+CvJ6IwYvZ3dcKcm/lrp5RMN8bIvMeliNbuGab1hAjzpIQj9t6Pcat7VF7L5+kuJB5fYpIkCO93gUbRr3icqfxUtpn55zZ/19vEvOapvjP5Qz3AjmsKbUW+XorWnRquD9rV4QcAarhW28UdKt5DwGh0AxLCXd2gwZNiVJnHxBykH8YzNL73sTUBEPBDcgmAIHT7i9UZv6g9Y16bjyUG3s/yENUjKg4fVvWkv9jt9Fexpwxum0fQ0qgscGOkRl64B33yZoRH3K5wI52YK6qiOQ2BWCzS1LM3LFYD6tvh8AT8ZwH+T05neYIrd9wV0ZdIDKlnajixcRkOAYraWM3qV0WqXbtRI/EcuTB2i1oCySInuo+9vZMk7EnutUzwSD2JCNZ5QJJ32CUyybfJBi/cFyjXhdboYavtVZfhdgpj14w3jomEeuOONW5ngxRFTuEND2rp8OrPi+wHAaWcKYDL3hQpuAABaPgO7HWMLsSJSNSGJSEwWQQIafS8K10JarilohFmIlDjKFttNHLPckJrqwm3XdgQAZZasCw77A8Pg8JJzJjMUFhZw5sdgFb6jT0AWQ1EIot27IJ0FqJg8MbMFkGq9aZZLBJ7XXFYDygHTy4OLF5T2FqxPp0GLrZPskIVczaepWjEDvOqaxSgoN7+REno11zpICKszFhI8craWkSfq/G8uzSQQ4OtL4FAi8JS4YKyeC1kTZ1eqkXKmdFNmNGoAQ2qWG0NIEEtO3gq+NVSyPuaFSIsO03r1w4FqFWN95aFQXGxZkU4HA5obdV08sKoVc8kS43IoAzHjg80Or6YQpJBpUSqdi+pw80M6OjRNFL8DAhYKBSC2QisK5d40fTphtVw8igGixLbNvF5KZKAKOAcUIUjJ+eHw37Ffn8wA3pF3S3YoQF0gYf7ez/Aeiw4edz7+CXzmB0L6mPucGFUJuEXYUFHK8c4Q+cpw1qQzwdqBGKLNBFTrOb3eXpvml+RaKnzyV5PXGJBETh7HFmP/BpTvxrMUMeN+WdfFqXXHS/xqfl7ZpWYKQZ0TdAoFs+gEEtmsBQp3R1eJM/F1p0k/GyJbD5kTha62QP8Oc3IxmF/cx5DV0bq/4XIvEzG9af0e6fHdsagEXlkK16gKTo91i/KRRRdHyJCQUGhbhwXEYv0SZxnaKZ8JfQ+rYNeILIHN8LeYJoBnJ3tIk3sFm2LPY7dQucJSOttgkgNWUFDLlAuCOv9PYYIPQCEczAeIHg4aT/yKu/PMaQLgDMD1ocT9z9mdHTe7gzA/tuXo+sAcG5rHKnNN3mUx8Yo27edeGwe7xwpLtPnVrsQ4N7o8Wxw836O0vGeuP5Uu4cq7l9hilq3Y/FKTCaizus4DS14jVurPjpwa5ThcRx5rwxAsDR0AJmjHNw13J4nQa2L8ifrwTK16e+ewUB8TMda+s35yvTz/lRmuozb8tRMMPXa56WYw35jwx8aOa/lehi1quFkv67RLzb69dkXEZwJ8GDrxe3xHX3sfND0O4ngQkSjKvP+BGJwhbvuuZZX6wac4b32vEfQudPa0RhEUPAGTb7EeNaPb3FDX4Z+juf117Uupb3VWtAg4xs7Ws5OrJQseSLqgd8s40kx/rQav6sZwwS7d+917p9HS+ZAqnEHTfee5UODc+50ndK4stFEBDhYFiPv8biK/fhzOFcIQ1hL3HjKaCLCd3thLZrZ6oGAylqSBAAqGGJZl/pcqL/HeSDyd/XYSnVIpXGdZ7nP2utIK58hwx3z/Gv/+1QkZDYW63vdAVKN57UUK5FSuiwcvErmJ4yfaa07DXp5KBZ8geCV6PpoVo07rUevyBHr5wbGLW6MZXljHZdk/BToGSSYjo36u73NhuNL6c8BwBVuwZ+B93b941EfNjfH7yKWeVHljE9WbvHUgXy+Hm7swEOaTqLfqV0akFza0Xtp4JA3h0l3mmGYDFyslrb1+8bWq0DpcSkVeyJUg4kmgirKPiofySjVy02Z7Ajg0FYQAatlS0OCH5V5Nap48R1pKyoRViItb0ZkacqNTzoclF7amo860g3+QrYphPO5nip+VzVT4UHW4fmtZ5+bLaTbcVUP03VEKqMKNEODmEM0AHwmwjUA+fwp+lmur1HfXYNvbrBC9/6au3zg41ReyTPaarsGcAPgC8Tqob9sLpu2mGc899Tv7lyT36N6vZHem2SD7jBsm0zjOyLj3SSvz3+fwq+zXL/1+5bsz6I6rGoBP5xk8ByANcwVXb6Zm9sk3jOwmvKHIFg3xpWfHvhr6vqNHzF8j9H3o/E8Sdmbz85w8rv9e7TfBvS/qW0hkb86Eh1ABKB5e/5bujABmCBlEgmLoEmDNImoIRe4nkmDI2L67oh53m4NHUG7wPZSj/+XNDc0z9cAM0bbNcLVuFKCZLTQxtBAuA/SGd0/oznzeSqCndEN7G/F05wdM+vu4DDvykt8vwreBTEiADeuMcIxjGzBzNMesM5OHd/zVrRGVCbyRS4B8Xplgkv5ofwF/9JNhvXaQAphzOu1dNUIc2rfBSLOiOj9LnRu10rP6dI6g9zrqU7I6h/YZmWC/pmYsKQwGJVcm52kSzT9bgqWiUMl/13S39ZEoGXKh7Ozxerq9XzujgUrOfqBYlzUJbVTkxqRdXSU5PDeL45bhoT+u/RxCyDEwzt6BLq9SFzocmOE9bIJzuPFgnM07LGDG9L7ypTUb07/F/uda21CEGmiJW2cqLDp7xarn8YMrIfDIJA3bqrsjrUSiGj9bCaYYd73xMwqln69pPTPOta+f4FHBRBmrE3raxdyQ6+Es4jwGXYCABWoo3E3hJGMKkwRp8YqS39cgLpUtDWuhFATz0NiH3XsDVKKGYzVgO5G/hBDiRTu1Spl7y0gLLpG5vTjKuNiZWh8jUQE0vpeNKwgFEt/75HTrEb8tYUwTKR7IKzuWZqun8CtaZRLKYAp3jzi2kselKnWM1vqeTanRE1z3lP/6z2Cw7qirSvW9aD/tzVgXudkxvYCSBPLTqHp4Efd+rHwHTCUlZfezPKpCtPuANHptF5whQeTpeq26HpmxuGwx36/w25ZsD+cW3YDxpKM+62pcf2wJoeDGKevGXRdCzRFvIK17aVxh16bsmbFiK31cJrHJqY4ULgWUKmJbzHlKrsRnbtg7eCXlQvG12c7ZigmXRGJ46WOvUhznn4N+jKn4It5DHcD4QCb8ePme73/fiajv1A0dwNsj8a3F/EG7Dj+96ouDmJpTxyvz4omgZgzEEKpTjEn6nWEqa/ToMKy4+Pr5OnZsxNRqVXPu0XNGkrsSiPFAnrG+ooiDNaxdsUU5aZAtPXkYZ7OU+mZp3A4faJts7p99UwhG5MGopoLQYBXfsYTd/A3s1pPKSOzwVww1gGnhDu9BP34zD+Lj7x45Hzm9ivFQy/rdIGeV2DmvzrV6yDWTiWKPwGDwy0Sh9WU673/fm78DBwbcQkXdsevdZHt1EnHcJYmEs75STlMVEDCwVMVo/WKwzy7y+Pv9PT+Uy4S/CxsHhm97fMVS6Qmzvy8o1/HB295Oz/gc3VWntWGzcnin9++gPAeTgyCfiDR7VCUJYKXbuxw3NdizGyj1XpP0XMAkBsBXcdbsa3hiLuxsUPgm07vaLr76JsIhKvxgGI8nDoeZvpXiQGqkMLK+wDQMledt0HiM8R5abFSLtASjiSaPNodiwWGXyYnstwIPRpYP43/HwxHcpJWhCwDz/5iR9YcWUvpxvOl1iT3JH7OjeheXglegk5s2WbjV19fwhtnZrQv3MVZm3dkawbPjbA+9ayXSvTx2ADTgxLrPxjrT+mij977Y5HoL2nOk75Ev7jRyfC1B1xtO58RLDkZKcXZJ64x6KCoERzco8KLy4vosoLKuLYRRFYLvQ8gn+QeJGEUKdOcjV0e1nmglxuUlZJTnJc4I6EBLQAAIABJREFU6tbuE8sm8fMp/I/g8X+Obs0x8HJzg7N31yhyiYI7vFURQQ3pcF6kn50Z312DLJzu5e1Xwu+Pvmd0LpLhmfTFse2whb9k6OT6l6mMhctVIqk0nPz0ml3b+N2YfvbhA/74/AnX0u0VnT9KHOkvto8dBQuewDtHkf+/279d+21A/we0xyLR/zkeLV3kUrRFgbdUHqakHBSsjUHgSOXqMVBsCiRKtbCyGE2m7XTl4VPt1hgXZRQd1b0DoaDiAwQfEwHqd5zyJDpqj0g8pyLGCdcoUA/OhhuICCppFXMGBmp/KcoEvP8f/wkiQvt//zeAp+sEObObmd7H7gVOe29eGmNyawz3tXRm5lQU+hcaadaVkPY/E5/OBWhzPQPdoMo1Gt2iyjuQe7xOTXnJzDx4vxPznn7Qc9PnVqe5fzGYeat8udlyCMAVfHOqXAIpCv1nT+Gv6ue5Hfo5yqqAexG8Nsj3lJjn9vseXRguIE1LGgxK70YjnAnMh/mN+mwpIKpqIJJei9Q7L3PtLPS6xVevL/D9QSPNH9bD3D1GTHFqQX6yPWejtjQTXQIKo2JEjYoZWgDDh30mdVEP4KjZKiMjvFg6ORZGQcGy6PdmtX+XWjeNKYPhxKSnfDT98lHGhhNCWlYcZY/8o4UyIc4jj32uJQypGAwvmJjQI3pHRgezSisMzp1xZjeeFJ+Daw7Extzn2KMXnCZ1ZSw/SDdYkMdu9xTa+q/G2y04w8FPjnW+wiMiNapTSGOS0CSMsmF2kb5no9IGAEkYtLPhX4RN+aRzL4USzFhqYgACxmLjFsPLuexg/G+KX3fuoJQuXFMZiq0v0Jqg0IoDrJafZOuOWD9nKFRRa0XqqsMxeRSncRHmaMEi4FXM2O8+5cNAbey6t9waGkwJ7wWXRVMTr4emSo1I4219iNajB5HV49Rok1Dqk57NMKDboyysacMJAB1A8JrjZCnIGxo3rIfVIlHZ8IDgsAewWwDsUXhBKYSVCpalopaiKdbXhpUbePW094BUnuBVFXmeKrLUxepUloAhEQGvK3htOFgae17NGFygaelTVD0XczSQAiI2fMXD+e561M6vZa/Lo2xJsEhsu7cQ4rqfW7F+xQRzMoXk4XDAfr/XlO37Pdp6ALclMgo0m9d+/9DXelJsKSwxqJGm96/ZKIrAX86/9tJCx8aa3mmfetKDgQx+qRRVqMJRUsG6GoV1Rw7SuOWMlyVg2s74jPqIYn5eY74j8QCOfn8a7tzm30gkMsDAFNp+HwRDzfI+Dz+TidcXXe9ICduxG1zBHHDMFj2Thh7jEsCVQb6RiuMk9syzVx3PjfoyJ7TfqY+EUtOvAWSOqzameF+nQeR4pxQQGoisGrJ4hGhSVRo8MAmoUqyTt0LdtE6oRhcAT4mp62H9kWDdH1CooNbqG2CwIJqenRlognpxFjPa3PyM/uBcml4pAPjhATjfQe4fjG5Tn1dszqk48d7W5/Jfhgtm98nNp1+gmCKMad6dH8g9yLO6TOcps88n0MKp9t0+X6Er6Au0TjnQo75fpd8ArcO6xXrO6WQ9Us4NndWO8mvDU9+PehjbK3vu23Ci+gkh8f3vhICgEV153N4crlhGp8G8fAKFpHMBKp2DUFDPFRp473zxAYBl6wBQasWZMwICCD8M7yMoN5Yj32fJZBjn0eL2C463zhK21PvPlZ8jxZmlEJalojVoOncg6W6MR2PGmkpOdDGor7Y7LZjLouFGme6a2/YvF2nf/C6ZaAMAvE4OZxlPkx0WP8dsuP613fzV7+Zjc9NWxGlEqAMA3kDkCxhfNpXNf5eOK6dxd9nE6ayX72mt6d54TfTF5Tg9qPv1oJmGas9A04mCl84B6nVBu1EjOpBPGkDQ2r903XmDwNtJhjrGDFuw4DqL8V7CWJauO5OxOn1Q0QCYYT2cLymohcGsZUniOAbvN2Lz4FdZgKL8JbOWQCoQCBEY3bExWJmBSdE/vlGH08CB3I11ZLT9aCloknPijNmZDcNQN55rpiuduzpmOpL1ICAOIzrn8+C8hckY3wpwyWo8r5eaiaJ91pIpmccRmO6JFD88Ox35RvNnL9NSvGPgEyVwzMsbUNL5dkCdZ+4o47PtQT1fD/dzZ9tLkt0lUe5H2munq6S0thCB5BKML5up2lcYXbWXntk41rXh3nCmt9aUZwMQ15dSIUhZHYLjcfzKqCCsEFQRNCqmEzcuzdbvYBlPONbY35volsmGXa/QaYg7z+/q0vl2EeyMr2TL6jS7DEvq+xTPtHU9y6zH+yXDjTmgBBh1yg7H7dNNYD4r8oZrUf34W/vBHb8yhrxN7/uCExN4oj1Gq+bfnhuhnu8FkpxFhg+FQeQ8Y7ghj5PTF+nzcBmr730p5Uh+H557wUFy47mXtYg5tvboqh6xzTJKbld2hPz/G1Ie9qNl+boWwfdPH0FEg+6eht5HpEDz3/n/F8w3P/+U085v4/m/d/ttQP/dAIz854AyjDJJ/3O4X5kSUzaLJOWYKa64K4h6FBlS/d1j5d6PNO9DSc5nwCpoOLH9K9unZAx25lUTeY1GYkI37L4bBM6nm993R4/XKsp1zz3y/Kl7GzpD7kbm5zD3W5Ht8zUfTpUrAECRKzx/1r+mvTWiTXDT2NVPw98/sW0pNo7uycIPgM29GBg3Y6qS0WC+b1NoemSLq/V19/0eu2UJJU3HC78CQ/z9bWsWwQoOBsJxP8gZOZoYvHjWBOEwYiEUCL2rqV/pgkf/HZg3KhvPO6PemXU3PwR7TP7uND4k4/1Lj/oR3J6W5sa4+j5mJCWMCxAeY6Op2+H21+H/WSjTtotR9KUVNPEaltuKgwpP9z5u0zgzV5N1BUv2Lp91FDntcShBQSA2Q729h0Jm6jDUYcqdGlxA6sqwPEZNSb6CG2EFQcSENNnrO4umu1vqknCNGvgjzbgZe1VIVCVVPxQ9UnUrA4Ar5fpOsm2nKw/6GpEL1QMsEkpRYbVWTbe62y0WBW2OP7DxUIIj4YhsF2KtaVdUiU4gizx1g5kp30SdkIInEU3dLOtqRn+CyBmwWzTKmhukWVp8E1hBQ5lvRGSzpdPfESKa3JUnra1obcXKK9aD1YHn1YzsBUK9pIJAHSqkOWwk431Ws03ytsLuM3DxcO4MdOMxXZulWoaCoqslrI6XK69oraGxhGPC/uEB375/w/33ezw87LEeDmhrSwp97VPrv7ux0ZxLDNYlIaGMLTaN5tIHLKn/gQOm7rwQ/YiW1wg8OeACVxrlcdh1440HfC0I3EqBq2cqYt83iMuA+jF/ofgg6gYPb+EQAMUfxeCRCh3jLhF0c7LxFJIicWLkfe0kzsHYme5hxn9dWc7MoNnyiljVQbboETF6HkX6eXIjX+BEx4P+X+ZjqKduxwrNWOA12cVT0zveMbyqAzeckKI1qOMEM1/rXJ0exL0a9S6N425fuqx0epKUhlGozyec+uz3UGTiAqKq4clo83e1H4toCggT523H62fw2OVTfT8e9/kjzSAs3nr6zf0Yj+r27Xu975lze87on+Koe58UfMmp97+0EYByUeE8bSECzixjzt74RdkBOICw67BP3U0jo8qD4ccqeNR4/nTrvR7zfX6LGE0k1FoHGciV4Y6Od0Q4zCn+nnjvr2hbb3vuCGS69iPtVaojT3iD3fsF+4+/coa/vjnN6rzOBp3baAMPMRmbHEd3ELjb6OHn2yhPXII23vOVVE/kZRFt0BDqYx4zvnSZofO0rCVeSkFNvFy6OdZA6R2D2J2/1dmWjR9yI9FQrzg7ZmL4If1pxI/7WE+lAzdWPsk/TgPdebagePr2Yk6xIV87D+LlkLQMZRjRx9kPPF4vXdfTSjf5AuBNvuV4nr+ofbG95lMHbgPd5OyUzwnK+SvalTxOL3+kdZ9uebRvv96gTpaMY6e/xxpR32R3tAWcL7FscnAZlUxepHC2U3m7qHz5jJYjwEX6/DJWdyfrvP3BsU/I7uSau17/EeTY+Uu/8hwaOLbMMzGpo4nrq3xFvthNb2V0IPkzCM1TvOhLnEWeey89sW6hL5G0H2GQp6N7Z772qTE4nu7ORj2rGUsBcVOZOsm/J3nnSenlgY+Xon9/YKARxakkqPPPVm8d90r8+yvbY+sy6Dp/t3/79tuA/g9ppz39XLkm+eZf9t4jwdgZzZCokoIujcmZgCE2kDqD64ptTzEagiYZYTjSAGTir+2WNB365/TuUyRF4zElUqsXfMQnAO/5HYQ+IyLbj5Zu6vGUFPlyHmBoblQXjGmVPA38//3ff+D/+vAuIoLfGaPjxn8VxjIBMuUXkfocO89CPTOAQHBL3TC+Rdz8N+/5xgimE+Qv1FO5n4wSBXBLBgmzxl1EGRxLlepMaEFBo88guQLT56P+fra5MHhHCoOXlp7Mlb0kEkyZ0K3VPvdnGQvu4Fceq03f2dSfO5OzQPYrWlZQDwZXjOkuATcLYjAyDOML5pwA4bBljYZSNaIVKqkWqguTBaBj5s49XHeLkiK2jBVjKqs5SiYL2QQ3nmYccpIJclh2PLd910Y7IfHOHTgDm+qe9nkhamnNGisf72HVGso7qxEekaWsRkf3jC5RRzl5SQ7aG3/FiLvjei8yfTSfHM3j/0ooLNK+ECLdn0di+uu4rV1oJArv/r5Ms2A4IthByR/4TeI72W8aGSIGXlrLzxn5iNrO0QSARjCQj8H252E0cvhgBQ9oaZULzlV/Qw8avJomxUbrcoS9r5VHXntNQwsCDuj2qFiPyA4joI/R6ZcdPIevtbGlb5cQLokIhat6uXtNXnsbice6+f6V6BswA06IbglGmC0rSdOoAC49opTUUF7NgL7b7UKRDJAZrAUENscboFndQG+1Fqv57UjZUplTAVCQ06KXIqi1qmF6XaHG44a1rVrz28WwAddYmtWiYy5L1ewP5Onabd1q6ftvqeDXFShrQ3PlGoBlt8Nut8PD/gFeCoCKCpWlFPDBItYXAnNBQXqeCGQ18rhpnfLGK6QxpFaLyk7U3pWSUYtewniu4xEzODMaa7R88zrw5mThOwxBnFdGsVTxPNW+HnGDwieDqGKrkZ9R5A/nBwyeO6LTnj2FpkEai8ID+x5aJP96WEEC7A973N/f42F/j/1+r9H1ptScRpPGDc2kYryJps9PGSBsbccHjKZRMioHyk5RIJI+XDElAEuz7AyJDRIxepOV8j0axJYFBKsJTM5jJ9pqMCpAj7KG89zdgSMBDYhKnAGfaxhRJ74lhoo+HsWZBBSL2qmG30t6wmidWGp2Md7Ax9/HaTE0fYIJJ497GJco1ZN3erGR+5Spr5RGpNl19HMDEUg6M45vPVNKYUBoxWJuUGxTLIVQqcQ8O95d9T3MWpJJjCZzLwFQy2Ae0Iw8jnehmXqaRaBHtF/is8pugXlmxVr7/0SdhiualWkZjZaFEb3/WMwgwt8FRBfAA1BfE+SbUwmDN024C+AChe51vpMs6rC0M1jLbeSJe6YPkl7r/gyK8/c+vwEIfrzlM+64z1dr5n23nj3i5+evI7o7ah5pPnNZfv9cI537cQKhZwC7n957YeDgv8/cuu/Bub0rBZXiHpqu3Z933mOcn35vdqH6Olq/r+O5IO/BK6hpigZQ9P49Iv7cJsnfGeWigPdKF3fn6szG568ge8NBchbnnQ3+Sr2AYLXUocAOmib3AMEK0zdgLKkzNtr8ppnhOmbs9kAC6EFHbj8QOp8JSZBmiEdM3qHkVhT7kwyNecVnTpzSb0+1cwQW6Glwk0J97in8FpPl0XlHIMEE+r6b6Q8tjEIKR3c0wod2rNG3JATGFxzMeM4ieIMxEvqf0CpsmSijWos0ts8Q25rTR6UlO4tI9zTeWd4TIOjNetP1P34uc4slIZc0jJ7auaqzs17jrtOSLofo5xWIAaa7jh+I8BWdz4A4Tzg6jHV+gIwX8nUpWhLHyo9wIgODrO16KQHABVwYhYtlapAoeyCkMoE4U4oOoa43mB05ATH9Q1w4Zh9sft1oSUYrKYznoIIClTe09EI3FLn8LiIWea4yQDaiC3pJSuchfB3e2AYT3kAgWG9vIQLUq0sAgsNn6WPuYiK+hLdsR54/YqghdMPz3cAPImhv13383EGkU/38hH46skJCP13fAWDkD17URmItAkgBGLf4gjKskRedeCVQ/psKVq1DoBmLakXhhjaNpRswfWuVMCoPKFEm7NAaLgC0ugCJXkUfZLqiohi9udyLWOw0qw4hA/kWCRl4KQuWVKOdPddN5jeCmAeJw5B9al5Nl0fF6Z+M16zjCKKLZxy2E0862zasFQCLXGGl2wFXOi/nemurBIe3Nl5JuhcAeAOK7Cl/dntu9HnGl4VcDhz1YV5uQh9CMLAjnX18LF2H2uW5wO/TOOYj23FmdzYKGYXZnPwJJ+PQE1OT5Rq3d9xSx1PXduZvUvrNp1ayOJ1xPavB4EIlMi5uDMXGM863n61jiH/UKeB3+7dvvw3of1N7SWqbI8RMP3ekc4paRy6u9D8W5CTeR4DVymzBRJJseABl4ZA2dDv2Ptn6YWqfNyYayhDq0X6u+L9mWAWyPoxrAW7gKWWOBehHh2A3EJ433h9t7wX4+sdnvHpP4E/HrxGR0RfRlGiXrGNzI6/uayeSnp69lOOFJOpp4P1+t0cRURC7gtHjcDbKhpLOiU2i2m7A90h0gUad6+c7yDM8LF/Ej08KgyYMAWM1qcX3exFAcAmhu3guVCFkUUrW1TuxGu3/B7QMV65kmwW1o+V2JXnid4kwpVyzZ5NA7GmO/c2jElc/W/Dbo7FrUJSnPv3eGEPi/N2bvhCB6rax589uAmgaxijBnKQ2vwH9sGYjC4CopVirCTrCmiJ4Ynwj5VPC4X1zrE/Hdy6sy4QDRZLDhMeSIwYV/eqk4OkNu0HGx5GRj/4hKbw9sen5piMa2I9uBipnqA3nZAEiKRv0T+7CHABhMTiTEOiQDBUih3idp8L21pWJ4/gYghX7JHDqH2Es8ZSeLva5IIIuVBfSv5lUUFLhnEPxMy5apr/dKWCEL3+yC6uMhsIFTbQ8QK1dmZfTU4XC2Azgnl1ChdxBvNc0hmg6XmKLCK0ADhFpXqumHfYIrVg3M9LWqsoo4YbWRI2CnAQ+oJd9EV3fZunTfWxEhKXuwKJmAG4ND2vDuja0pkouXRoGrwCIQuCCpYiXtuKhNQhUCVqXit1u0bEbWOnzjMNeU4vvH/Y4rAccDnu0tWG/7tVIPaSyN/xkC8fccDgw6rJDrZq2vdYCbox922v9dLZIalE4GhyMmMFUkiLX9s7uYdY5Hw4HrIcDDnvtkyDmEEAG89CyDwIsuwXLbqdCehGArRY5iUbpN0EWO8Xhs1mqOasbGfTStc+SvifcUlyZmRWVDqfCAJuDSSngs11gidYYhBXcGg77gzpJeGS9mBMBWJ0xHD8QUOtyxDNwSpXtUcISZ8c+iUCWilVEUESzJKghluGlBSBmXE/R7yxW0sD6KYZnxcKfNJKa0dau+IbzTJl/KqTvhZV/kHhFnIeshOrOC4kO2qbNBnp42lTvJzXKjl2+RkbkCwHVmaFE04TV8EeGP7U0E0BN6To7HAjMwG7GbaTyBEgTpD5uKkpDchppn5f2wHAlvy0MKqmjTQtFHQx9JrynkwVBz9JiyqFFdgCdQ6wkh5eaqkXLUbgzDdECkMJTi1r3UKPfhTo5gJvWOm8t6IHYHlDME3EGxFLSOowKrHYsN5Tl3PAxIJ5Guqi8QxcVhApyypecSVjEcHLigxJ9FQhKsq6qA9QrtHJQ8mIlYkZ6nfiM3lXw/Iq/Zz5tYhBhPJ8kOQ4ETApEUNqvH2gTy4iSIuwBNST/2iraj4xjHEp8dwxLG/cDx8bz/OzW/XPfczuffh/uk/GZB0g4c/t7jrmyPA46WvOt9+t8X6OcG/+xjOWORASyk4SV9R+538WLqSxg6jxYVsL/uMJTsBM1xIvPI7oxPilQlOLyyH4TwojRaFHe4ZGlGJrzdj8C7hegcD4DEEYMQk8br3uX5Fv73fkhf0YgYVSfz+2WlO7l6I6iF7lf03e+geALgG3j+aBbeP7UN5s7+z+7drTpVbQusfPufcWctoCyK8o4WJm/++cNQ64r2k0b7hvP++Xx1YlvUiNtiVEB7hxmPF4BCiqkAGVRuCMGWKo65rj84KWJ4M6LQKWKUguWqs6vpRYrtzUOi8hK4dSiWY4Oa6c31Mc5t0JFPRR8/k6yXVbZwPPd2NbluOAlIGiJN3KHYqWv6uBGVIKP1u99EgQC1aVPzM7Cuq4hp4jTdeaIOg/5MY/PZtUcYpjB4rrIqRQSoJhpktEd4t4a0vmzIr+7XFmQbYzz2j/2+jIjqJ+gz7l5uu4vpKCiuXlGFMy8lRL8mU0ZuvizCCANaIm3PH7GGWXuPK+Y2L2VIs2ay/qlVHvO5BOHLQi+A1iEh/X00TW2wLSmkMXCif/rgQGBp/296H8QGVdofOp+bV0HQQ3FD+RWNqlTS5jOn/LzSdeSeP35mZxa3nUVea1ONS0JdYsiQMEV2EpTeA9afknbrKv5kpiVv8p4/nc0d95x52yg0/9MU0P+QdcdeER5thV4E2aUUlGXBbtliXImgOLJ1fbadR8eHFSobO5pHs+Nfb9i4LPtzXsR/OHqMiJ8YOBj6XyRX++wbufAaYfxX0rX+hzTAPQjcK7RV6cN/myQhImQb9Cn3+13A34b0P+W9jOKgV83CKcxSaEz80dICMz+F+qCmv8xE/HcjQtmbjD3zDaemqZHLdKREA8oc0XQCFkW4L9trCUh1B6l35UCBe/wAYLdhx2A/8R/ieC/b/5An3VWDtDgjb3VfiXSnBUgN6RGfgCQT8A9ZEg7/z/fEf7X5y1lFOEGAE1jz9ERt3bt3fBU7/xKOkPi4yEfD2nKwwOQlMUIgpKNnqFDyOtr4y0gFLnCOwFWugUnr8Iq70ByDWzUQO+yxnPOy5Z4ah6tJpzcmRL4rXjExy3IUsmr8uAuelmpryNTrxP/s97zJ2jyT3To/fVzmttglO63x/rfQ6OAvAb6mSl8G6vQH8w7Z4W8oJYFFGJOhwWNnOV+b9YuJAblfm2TUk6mz8w05Vi2fv+gJ/eDjwDEPO1f3x7pVwKZitUO8kcMoxIictJrXBUTcHa7HQoR9qtGqC5VU126P0CZDL1Axn/JGCN9x1Wp2I2ZQHJWmHGKIwCbg+Q1Te+DG4H8sdBR6HxbU8OY43dhVchTtfrWlBwEUgcDjutIJd7k8OC3eY1lN/YorfE1OU5NLMxJKbQD88EickZhdlaXuZom10vvS+bz8n772mjpRAr6aok4UHEBlntN6S3dk7YvfVdIiUdtkikRzF7LYhFiSpiH8bqh2Y0ea1sjTTlRRTHDXjOBq5jCoJYlFD2zECLQVPVi2RBYADoclB6XAtAedalYdvvBkA4IimdUYP3nsLZUR1ijtP2dIkDzPS4azesZGIoJc0upptBbLNq6Ke5hTc+8JqFNQcQjWKHKraYRJerkc4ZCAC8V3JqmZm1sxvimxvL9Xv8/7LGuBzzc3+P+YW+13Qua7LtyQcxIb1G5TABaU1g1p6J1XcFttbT+XRm6OPyktfDopkIE8fNP3Yi3rivWpmu6euQ5VEBcG0VKa2aAZYUUQl0WMwIH4vRtNmXL7DQHqLK9oaLDt5+Aji8sojbR/wEVs9gc9Bk2wyoJUC2S2AVbPW8MbtCa7q1pivemjhOFCppFl6szhZ6bErUEbb9d+WNwyoYDKMOITaeQOQbY+pJw3OeJHPXc6To17uobN0x4FomMZ3OEsa+e72OsYuBuPY8ihKjynonlhJxKddyHWPNjvRF12kE4MvC4c4BDQ+YnCiHKHrCE6dp4eMMbVZ1u1gZIFcjqPfsZ93XmzSESKW4xpI3Ad36fBFqMvuLDGIEDr3GdYJGWIoYL+zmrpcIRo5QKqhVVNBsFo2r/rAb8YvDEXABmHB7u9ewKaxSqyz8F4EPTFy87deaDgLj0UgtpXVVR35WPbEp7p7WlKK5bznagxmBRuJTCYKkAszkZ7I1enSWlqqeoL91x1j2ZAYiQZgIgp2oKY+U10O7TeSUAOA+FrHeT964YHxMOfr72E/5wMK/2+zoS9J9uuRs3FFfSSt/0miDfGIILCL53GP+ZFz4xfq9x7pHoNH1+G2+PiHTv7pTx/NT11+JKZcUZjiLm971C528I6kRwagse0i+vNvgj/xIsozXf/3z/RUr5xPgGfHuN8ro/04wPFsd/kb1BZ7FcLJ1vA0HudxBaFT8BmjmC3MhDODTFBafcaFeMyi/H4rtJ2iw4B5mxH6tgt2hMPofzjBid8HOtskrhBZAH7KAo2eWr6aMjtXjpCFgzmEWt83Q3AWGkwXC/xJiid4kYRJ3HYOQ4hoR4v4zf/e8rIZC8RcMdGoBvRo8bfXUSCI/rbPjzW8VbAMBb+fKkMfJtGIW0EQTNaE8tCmfugOT0kk2OEWnBnzmPKwIcbj4P50NuMKxsJt0DnF3bTjrdNT6R4Ep+HaeX9xFRz1P/nUpRHP2+gG8YLLfKL1v/l5bt5xtZ3W8QKun8qhnQ65TG3Hmm3OInluB9YgwJEbhBPV93vjYcUPK9k3wZuRtYwllXeTlGqYCwOY6IRsQ7z+LRkrV0ugvjnwRWwqioM05Oyd7Y6TlHdgnh0QgOH5Pvg58bEbzhEt9FgHpp84dGnoM6XhH/exM+Ey74QdpYBPi8EfDRHQme39ccLPNSxdWzonKNn3YdKEPxM5AcYeR5fc3N9cf2JuM/rsDlDt/o9FI4H++71sjoqwhqUT43BgbEffG5P0AdG7WvahD9zfZl5YZXQvhuPNnOItJ9/w+rrkBkTNrieUHdCD9PxM4UM2sJpkI4cMNSCSimoTLEJNRLK8SsEl7MLZzc0I3nLl8d34xUG96np3+4bo9Ei07cJA30ewHO/uOYcIqiAAAgAElEQVQDiID9f6/GnV5CcBd68QgMg/Mb2r4+ocf/u1uPDJ/GKf24687yo2dNEj812jIksiPItKcOEzNOju/eN6nT8FL7pysVqZA6Z7Ebz8WVBgMIOu+p+rY+32tB0FyB4B26TDE300IMus0+y76O7gxWCFr6Ci4zTjAcekukeats+JhN7jG884+w5f1uf1v7bUD/3YY2KxZORZArEw/Xcz3aBoLhytl4QaBaHHMBGrX8VpShKvBo8hhCMM4RmScY+tGIan3jO77G53psqH2yRb+/pt0SBr9jN2IDQP2Pd3gjgptPPa35//osuJKe0p6g9UG2mvd1Ku24R5t7zaNb6ozrVjugM7NzI1LPWTcqJ/o0tBuCEcrbWMqeWv70y3+hz0LM923qUyFOLzS6G2q1h2MBdQbt74lp/nNaPm2ZzfD9ccVrPpnihj6mQcnlxko1oPMmU+FyrB/Tfze2g7JgjMR4JQHVhTYEQ9s9+0mil9zJ5jqOKHAbrx5f7a4v8Xdidue7jjMEzILcCGEnRrndjjSBZkQanpOjr8GWh6GKBtjNXep3jTqQfXIEOjE6F4RPD7n3UUiNN8W2vAC9Jre1ck6ghyRXDu+0iEdI9xL2DbF1V3s3x/MCidq7eT3UGA5ThglADJICmd4IqFKMSdRZyo3tDrcheAxPAKZAbm1FbQXrYcVhv6KWFaC93kYCMgccWjT1OlvU5cN+DxHBblnUWLVUQAB2QxP7p89SX7sGbEov+1DFDON9VUjcECthRCdAo0cbR4SoZq1oxi9on8ysUe3risPhgIf9Aw4W5b3fr0BjiBseRXp2BACRApQlskr4d1DTKJ5VExQGdJsiw4VSx5WhJKlFFfWiUfcsiH5WM55zs5rtqR+ehGxujIf9Pva8WXRtjmLLHtlz49bAaINAO8BSRvb+i8Gf1vVrkTrTn6+1YFkW1GXRT0tlr4/qfrTW0h4mZc8wui1mNf2accvELyYIm5+KddGsEaZ4bS6IH9/uvfSe6WiZAtfMio7c7JmOYjNdHjscaDUlYivDUtv3AqK0P37W0xsUnThVIFOeUHIo6EZSx7lNLHraHCk8daQ7MZ5q+ZdTNC1Rps1FCoVKXjM49UjwYuu9ueJEVjNVTG7IcCZRT52b4g9PPOE8oghA6wEsFXVnRm9T8nejYJ9HZJQoZrg3ekte4qAUjZiTBztOZvy2lNKSasTnaH2b6GD4ooTDBYjoRDBD7gU4QyhD/ZwVc3aRDHcTYx5f83nHJPfl+4e/T0QM/yTvX3CBhu+KP791MzbhFTyh+FOp3P+sdgrD5FW4kNPG8q02RgjT0Tm5eOY4nmoCHBnn+1vz37lMRL5uTg32X7CN7rgkMCcMCiV+OM2Il3SBHbQKyCHxc11ec1nN0WCMw963SP8dAHZCw5zcpk0XjsEF5t3W4VzG6FRX9KoR/SF4lc1FGg9BzPMl7Zhv3P4d0yfhreGru7j2WB9b3zuteRN9n0xLDoXPby+c33PbmzTI5Z0ZvD/3rHdb9xuHAgFQr6+SYZvGgafVcZo7UMkwngvaDW/uySmK5VogOrr+RAvY1bGUEqfJYE8NtyS3mjkOzs+ZgZmKGs8tUlsN5+psRUmm90934PSmPGxy8A3+1xx2ja7kCHDngamQ8f6+znS05LGGzm9Rd6gUlO5QIAxmzTqjpNEc3vz/2GUEP0DsI3ac0ssHdfrbZUjHHY7LZmNhXicfs+6/Go74VoBLQnlCmbXFz/1II+ia5brQ41hHGj23Pt+N33TZf2Jwx9AdqbjxzpxFf0A/+1RLcyJcPeuREU2LOlRaD+2obNT2844PzVd9WNML2eY/le6MvGp2YpC0f86LUe48Hu3yI6CZOHe1GvnSAcm02d24O4gOSD0+Oe+jtsUobNzizfXb+48fo0Z8tVTuubld4CfZxL+lPWaQ/RXz6XLQ8wiuO2M47HlGktDvQlQ3xB5U4KXkTs8l3jyNwcsH3RhwVUFEnwNqi2i/iE84tZZdFv6TGJLf7d+m/Tag/4u2F3vjJcK62Z8LskmYE/9O/frwtMuS6feZ6M4KF00/k94bQyNsUdtCBd+KKbzhkdE92sbT/Xh68EuPZMEnfCLg6g9YlLZ27fGbJ5mBxyRGdObmZyPS76jXAAE0Vb2mcf8EAnAFPZwf7b1uED8DYX2EzN7O8p9fBzBHqud28eED9h8/Hu3dJ+fNThCbrxup4YG+vl3IuoEF5GEn15Byg1sA1/gMyBXesmwKu3N/L2tK5L+SprIvAIpcmvLwzupc3qljwmQhuzV4ec/ApwL8F9u6nxrjEQP75NA2739pN89tT/XnBlut8eVCq0ZIE5mHrEjKtKlMlXt8ezrTIV3QtGsu7Avn6zJ8ntzlowlMmqh40AXcI2z1S1rsj7/2SPg/oRC2+3ydS+lKjaxoXtc1rgGIlF4esQ0grbErTPy9dnVS1iue5sEo7x79ubRD4OqZMXalQnwlOCBodCShLrthJ8miGbg1NeZYhFGlXtudAEv9m9dQpq11POKr62PN8OUG0jQXJ2CpD52aM/4Hl1ZBZwQ5dIN7f6K3Ak092x0fFJ+6LO1JAQmAF5l0FVOcCL+3nKNSwetXb/D9u0bneG06aVU7LyrkshmE3FBTRY3LZEosnw8wpmPzDBKgZkaQYueiWCmS5JRgR0ZIDbMOVxpVLnBVAIVxKcE3N402pQJZG3hd0dYVDw8PoYQWZmBhUK1hUCtEWMG9lrBIGE1rLr+QFAi+7yJq2C6laAp4u4dbjwBW8CxoounMSykQIRwOB1snAUsDcUFrhMP+AF2iJerWtdZwaAc8rHushxX7wx6Hhz0e9g8gFNCyRORcJTJ64tFofuC7EaCnC1M49GeJCLBomdG7X6N9ixBKXTTlukUlr+sB66rC7Mqa5r6tK0Q0Hby0lgTcXn6GQGpgXz2y2tNVpxMezJ+veT8TOZ2m3+tzC5WqMVtx9BLfwcK65gaXnqZU0/9XLIuml1+WRb3JZRTexeDPa1RntN//fK7ygJBjJSn9m+EPabqe8pb8N+eB0/8j7jBjbWTHcEy2TZM7rOsadpoR3/JgN6ZEwyAo9j6Zgs1aQPaH7pnn0HPC5vdbrVIbW2Qn8ElA15slRWuFUtl+HXjlWULIl+xk0AAyiQIkI3mP8Rt4F8eDVgwi6LErjwOWTYno2sKGvdZFxTkED8r/FIRCkZJhWdJ/XmuyGH4VcqcZgWCX9i2Pp4w01qI6CFDHpaLw7Vlp9JZzg3cx476tq/GtPCl1RRiFKlLewmHB6QCUAojcQ+hMx34vKGc7CARFdiiiDjv8/TucBixQhxyPavXa3UEIbbeMinV4T1ZMgZE39Exic01xBZ1j/u0MwD7P8+gOzar0Gve4B3D55i1qLbi/vbV1fAXCK0B+jRE9sQObA8qR38D2sfXU5jk6VfAyI7rA17yfFn/U+56HJwBe211PpTr1X8MoEJ8K20WAijfxw0ErLtuzPqbXWN5oRqX2VcvARc1yz8gAATWAaulnDwi874Z0Dh5L4ZU8M1AzPOEpdLkNomvMcuLbC8ii3/v7gIsBBAmEw6EpP1ErxGLgNIuSOtyJ0fTISxKouHck49cYSOZfzx01ILGxOIZ3z2CTW+bVx+hzAVmE9u56weHmEqulxo1nT6Hmqfm1hq8AeiE2z1Sw4A2WdwsOn1a7/8tGL9vtjTyd6e1NWh8CcPb+nfoCifM5bwF8CR2Lj8/v9zk4fWXHy1DHw91ihlqr2e3y11KUljwcDprNxiLOl+trAHexXnnf8lT6Wl5a1DlwhBVIaTMR1ACN2UnPgJfV2JFxLBFBrowefbpSeK5fo6yZ1/0upaAmA3qtbuQuxuMIpPVzqejdeCWPPDf5RCBqYDS+r7rpmmDvIqVxUP63FLEzQ0dTd8Oeklvl3fV0edSk76JAuPQMPUbPvcSQOhWM6cpDtmXn+ZS3hGd/YY5SM0qfqUO2GzHdsJ72QkTx5yuhwMHt7itEXqFeKl+w3loKamM73hpfO2TSDPg4YiKfbF5u8dV//idaW/H906eOZzKffKLvMVL7uOnYJ8bsBY2CUe7N651rxPmneM+vbC4b678JLwaW3KrNSFi9ZNP+IcZ/KAIpi8qcLe9aep/BwYK3qFeKDdYbASxD1ltWp6U742V7ARNdh32Etnu/3RiqziwGh0YLtWxRhsYkX5Dz5gDMuaWIsfqszq6xIiLDW7vz2ggVmb9/ViP/5/gZv/qFEBlcmq2D61MYgNDtZinXzQwjMR3p46S+Ln9W67vV25YDaej2pvWO3/O1zjwMZ3nzwbkf1xE+Jgc7Mkpfizmyl+qOs8prtdY044iwOtBHxqz+cGTWSEP1e96nW/3EaUbacUhVNH37jI1mOhqZPQ0eKeHRky05fWVn4t/td/vR9tuA/q/YJsT3vGcQSlRXxm/IcD8/tBN9zR54xzdg+4bp+mcivJOxNrrfQgDuiDQ1FxC+hj+EJLelnl/a5rX6RMoIex2gw8YzBwgalOH1+uUuVwi6x/Up7+ut9pmA/wHg7MN74JMysoRfmHLNhRsb3yVuou5RCLGPPPtjxnNtX8gM597d9Ls7JjRb+zlynwB8MOXmr4pAfy3AdwJeSWfsvv1FqYe21vmAzJepwrkQoZaCQ1NDqyupXf7KKWndGPqcd2od5WeMMx9a6qP712qbmNDgXZUHEQmXGN48d1eejEaUY7nk0aOe9w9dkRB/o6+3Gz2mx5NgRcP1+GaytQtuSPJLfHHBYQMhe/TrKCDoG/zfY1HVvf5d4SHDnLyPLvOZYoZ67XMRRAT6Y9BFUCOp40VPxd79SfQ99aIA2IH3B2jELYHOBNjrAwVnOH99AZGGh2/7YeMcBZDPLi1ZGQxcakT1iGcZBDUzGPlylrTHLJa+TWK//I1i6Qx974oGglvEisPpCJtidc0B0rTaRCjrAWVfsVpUODcG73YAM4qlDScTaLkJmhXEZSAM6GpQrckW6BHsCCFIh6FGcx0/g5tY/W9TEoTRS3V+3NTw7jXLGzcQGqQxeGlgaWi7qsIZ1AnhcNDa5w/7B408P6jhmohRBmWC75qNcTrDOlrdC2ZnhrrxOdcPE9H0mIXZUmETFjTA6o4Li6Vtb5FqfrU09uuqgm4zBZ1GkpZwdvJz4gY3H9lWkYxB+eawSQRpLaKSCGr81gwLErU6494jBY0qbjQSnS39Wjeg7ywCfbF68W2otdedtFzh4hFgW8qKUDzF7uDod0EcqeN2QsmheITMkDnt73D31pO2NhuvepJPdQXAc8mhTdpWCEmtMZxnXSPv13BkykbgHJodP+tiUnCwYGUGC6IucK4nCvR1cuQzDj/HrM7TpsQkuhNC3m9K121hZFYe9fsF5lBjK8LS8bnTYncUIlsESQQtFPzBDI2GKkFP93m0qY7P7GyEQ6LRZ3IDB8GiB48h17MeqP2cNJ27AXFea5X3LBWkOH4i0N748QKAL/RZOQDJuQ0JNqwOSQyzbMz5seY48VQ0+jbYb/e937x63AivcIHv4K8N8kaN6gDwCt9AeP2P4iQJXuhgVOc/U3yLe+e1PIX35mde0jLqSRQPBa/BYBQUsKXs7s8Q1LRKQd+toE9XZILAxZxwBkFLAEkY1o+hDHdA5Gyiud5mFdfoLkGW8F9pXKJdCVsdIVxSerWjnabaJYKw4rRMh6ZhnuoN7ngzzvo0JZn3bWBD8j1HhnV/nZWLuVqwHwP7jsY4vy8HWszj8uu+o+6M4Cv5Wo6j0Odrbx4ByPwbTZ+e2txpebkmtBugXl+i3dwNjh+EtyjXBe2mobwr6BDocG27L/1MSnpZhlsfkkefb41tWB8f7/XGrzTec7qZk3bpGUzCwYS9fBpQ3hfwjfGXFlFYrcZ5LRVLUT7bo89zX0h0vEkDNy8lZB5bRo+zDgACLSvi57AQSiUQeWp4HQtzontbsyUoL1CK2h2JoxQYgCh3JSSKMzg5D1vEe5xfY16D8gtHIAdDos55fAbPQjZfRTj5PCXx2XvFuVCc2S5/fgVEHVY6rexwNbNyW6bclzR9txp+ayYGgaxtYwlH5zbjqi26oD6Y8iLbaW4eMJBbxbj7hGs03Pxy2tzdKPXbDHOvRPVxMQ77W5gHBwccPXncNLuFoF4T+KZBADTcoTt0ztlifIynx+7Ot8AGTp/1hgkvK0xlB2f7zXnX1Gc4uUm6KY8rn3N0WJgzMpyaxVZ7K7AcKL19Ib3eMDo7+f3ZaL6VZeHk61/CTP2i9pIgu6d4taObX9Bc37LZlYzO5kSkZSOLOmaQyXGrGc3BHLXPXzK/T6TBj5T+LiB8TPD7gV8Wfe78xeZv84XflvLf7U9ovw3o/6Lth5gMgSmuRqZgZpy2hPCjbuZrXf/WW2LUjI8NZdhAiOGR4cr25i6YR3bjGloP/b0An9AZBRcaALHobh3hnSvSfRxJOTQP15nLjR/i2s8Yc7ear6UbvN2A+86+vxOty7a3N7uR/c7W+46eTxseo3ff//gYqYYvpUe+QzAQyqciu/I73APyMmp5GtNEPXWT7u4NimwbsJ8z9hNPIARNACRWiwoafS4Yma9TzgbNYNij/j3927MYt4322ubh/fi8XqcT9e1Iufw0/9ejPB6/c462IVL48jT9bALAq0W1WBe7JRQ0w976w7Y+rTVANIp0VvK7AVgA7D3qMkRaDJ/z2KYXHs/bDYVe0OlXccoZKT7j1q4ocs3C/8/ee67HkSNrwm8AWfRkSeo+++z37P3f2f6aNqKRRLIqgfh+hEVWFo1a3Wf2jDDTYqWDDUQEwsq+KdXEM9A32OeNQNjPksdxM03RHkHytIIPmUQ73IERQnGrW18gzX1lc0b5uVbjivtxLL0nr1g/YHmLMIUkVFEWHkGamJtMrQ2x1odaWRcVULEaZGhuQVd4+ql1xLE2o4NO3PA0R/sHazJIORKsEYFwgsaHovhl3k7vA9Mg4KyQEOIVhBMCyukJ+vNO5+1E3jnZuKUxgVBOZR3E+Juxn2fwZocyw8eSxRjTtPF1ICK0/d77D7B7+FlnxUOjBw33SKekMi/xlqwoh3NGgLhfm0e75tCGKq07gFK9Tusrs3pgtoaCgsaa67M3nJ6cozHjuXUVRDAqJO84kShLwR2Vuh7a5F4phM1URYNPyXezN1XWR6gQEXTpwQ4Ce13zcknqLc2HrfDZFUeBgdbnlIO9o3FH44ayjxCRouAXz/N5P6PNlvOY0efu6+b561mUX5275Y4BaahyU5D7liwFdZK8k24YYAorZrS5gZkx1SrKyTKjarQPZkZrXd4Bu/K8WQ70OVuIB47oLly1MLMCKGwKSoRAZKn0NO95/53gx8NXYgxHb7CVnJoddnrpKF2jIRAUJibUOmGqokQvpWrd4wFf/jPEeFx5DlPgM6c+jmU0CnFs42C+5JMtn7xFjKAkOA0CufiSo3b2X7lSHPR/7KEJAEms/GNq4aOyexz0KCvNxZCC/H4Oqxp5FC0CQgdXFcIDgKZfKG6MEwI9i0bQGOgmdNb9RqxemZB5Wg47/0igcYALAagyORPDxJD07C2zJNyynzgvAqnAnMQbDtzRnE4aHhdYKNgAzNj3Jx2HGi5p97KRD2BwV1zASA57YqQ073dC/jcnOh551powMhOJ4ptQYNt3CH9vRhQggFRxXoq046F1bdwJZi0k/XNHrQWMHQgbAM8gOgHTKQgdVAnFbdkIBUXyxPNGlSnCQVacgvEY4byDfMeaEbmwuGnfsmA2cUs41wpmfX7MK3zpgb5WTgHUqwnUL2HRLc4gSvRHAGf45uDxfGzbfW9Z8osr9RPC8/0MwkeYB/gZYk6AOC8sy1o4bMahIj7vhlzVYLfxhvKkX1/pF9bOBpcoIOzUw3ipHKggSCZ4Qr0sjr9PtycANFKSGdyAsNuPhpRzawKHi1yVmws5lxi+IZBMKCVldEIRUU5Xx+cGWacEfmLQmXXDNzgYjJNpA+aOAkJjESgLHqjCWriBo5R97wd7InGjvseL40H54R7MiwGsrVdRPkyeX4LxFdP1Dfp9A11LuO7d3Q5CBxjTTZXIYmCcXImbwfO9elLTJQDCnDzGK8KYPvoZZQ1EO75I/m9FqxNfoaU6LzjgPCvRs+f5mjLdbCtsfk8/fQQBbjC4qcIZF5pQP31A74y6vUG7E0uBur329DH0kewoBjPKrBqhqaO7IjZwqkbQATAVU+/cKCl4gEHLcM46mBeAcJ14lsQTKo/lRoH2P4rawuBZqJPRA+fyjJQr31sJQCmYzEBRecjnUl1pXtz7XPlqmHpNcoM3TQvUzDsbhDoVh2O5LV8U1vtEEG9waWeIoObYP09U4vGgxl+QlHHEdYAxi5rWO4N6AyvPvQQX50UTTyve7Hpu4VCiN/NE9/F0VR7pTCSDzZw2BVq/C9L1PGtrZXyXsQyka3S2vRbP61vxTG/a40tW2dI76VJjSUux+23v3tVXXRSUnOobz9FRDuxoli9Yaq/vVERl7/UbDvp0+suvoEL48ttvINz66e6tzj+vFZGTEm46456A//3rJEbGd4wLlkgZBMI3DlUuMyeFuvT5nMXwY6Owc6mpAKy/AdEqz6aCZ751Ltam89H2mKb+AEnksbktPc+jZMOFHH3QnuWvLKAgc/Dyvm0BXJycigJUa9m10U3LUqCIkWdUzOAEO68AJ61crKznMTj/QqFsJY4oR+Ywlj+xCCOvw8sBQK++tdU3j9iVHS1vBdc4V69fLxmWMP15RyMIODm8/3K/AHgEj9bUKNr/E4N9S0+3VilHhWFIpeWOIlLGBGBeWOGxvmNXdnZZHRdHClE43UzvLfoVcozjc/Oz/CzvLT8V6P8xRcj4S6TPBCFOrPMzMkHMQkSl778FJRGtW9+l1iEHh3K0pwRhNk9A+BXA78Ykax/lHekUQRD2YVadbJEY9Q4trhH3dDBfff7OkhXJy2J9l/BGPBw5jimZswL6QI6zsDRblvtE3I6V9xIelWF775dTlhlPYZa2AI2rlRm37ylXejhfHvjfyqBneGXIAf8lK/ljJQvCXmv6IuU5foT4bjyBcQZyhuJRf5xZbboHn49UbmKjLJg80d4sD/1yOw6M4MzG2ZuxmoQUihOH+XcMDt6zkOvK8wHz4C9vwH+o2JGHhqv0zPYsiWdlCE1ih1Caa/cSGGoaD3GAzbudOGgl3DwG78tRWGdKoXEkfLCDj196TRzteHMOFCNUreF9w9aHVtisgs90uGM7cI6he3NnWN/DntPtMbzy2pDWoE72zlqsEAx9lroLpnKCUiTH1G6eADddORw1kDy0qnrKdALQh7QqyDTQx2uepazvyVG/c0dhEkMZTc5WIJV1jvDjXQltAYE3iVYuaEBvDCpA63tpg8y79VmEtboWpRA2LLmuS50Cr9h6VYN7EeRNGsrY1qoxMFWgdVGKy72G3tiV2qwzQRSeOWARiDJUsE7ipWOhyO3b1vdozTaIwhOrN/fc0HoTxRYVTGWSHOCdgYKw1iZo2HuFJ1U8ZuW4KXRONpPmGSOEtUMAVe/iKd9aQ6EZVGxOZH4sH3gXl1+0HnnMY5+M/BwvGbUkqH0JkxJRCiVK4PpyLJZB6HtQsc0twntCDR1q1dCiuvZEcZgv2QhBlZvZU+ywFQw56YeJsLmIHiVu0HDJ2oyIQJTUo1/22FJQwMtPAr/6/GDAfwMC9BcD31uaDIOjQRnMww/IVs54Wp6VYiHOEwUqGmKVPKa7Ct5E4W67yvKYCriIoY4soP7x/0SZJDEjTXmelNtrTLanFhh7vF4U12v45tXxa/Ox9oe1OUVQ5GI8phsWJRiD3ifeQMJ+L2nQYZG6xViooILA2PWmIdlVrL/bAdiANzryvfZ0E8YNokjXNC3l0DTS9pnROp2dMHIwOmjrBnIjJKIJ7H7Zyr+xGkmQhG4vqP5dFtzKXD2j4gyz5hM/GD+C42GFv9wv6HY8diY4hpDe6oHee0f/1rC5PtE0OKG0Xm63f6Is2yyAK/XP0mAtZLudF17fE+PzY1Bp7Y9Y4f0ltyMczch/Hr57AQKhXBWHI1NMmoLLI+j4mJMBF1HQiqwJ0vuU9j+fArRXqDsZ+Ww8hRGN76SzNBNMoF78vrVrtVhfjS83T62m0Vi4i9EcNTWA0eFsSNjMvCeUg4uJMhyTZjFw1Hj2R6onJix/81X4mns5R/MDsLPzm77X7wHCJTY3FfzQUW6KhsqV75nCYEKmI86fMSdIbY7nmTi1SBh1qekLCHJ25sW7FaMS/X3na+Fsc1huoysWll/mWzyBCylfyaJsEgW59YU0JP44qHwmCfwXTzjlkl8v1zBfy4Jrl1OVHH6ZcjBnZ0MPlAI+d8a3238pRY8DaiHUXwrobotSHlFqBWnY9g0RnnQujFe2+o2em2K8sxhsWt5bMq0Wc3hvc48858YvFvJQwMF/qeI65VVfi9ZU9JteVNm6VLCDAe5AKWrUQNFxAHlP9G40XqI3MiT0e0TKEZ5CouOJYlOiN8U+TadPrT7zUnG9jMbX7uUbhyCd5CxX+hG0yOqonyr4zzbiDL0YpuadjX6PDGf8Xs5Cpjy35nvvaH90v/5b6DILdr1UWjHVihnXIDygbiv4tuOSzWgpfMUfF505Y6DgDOBHX89lShMAqBBnndPtFk934VG/HJssQ6afL/CUWcGptCl/w3rf4VDpVN4SoEOHtFDMxw329gLj8HJf8REe+GAB14BtvLesxUL7V75Bo0WKEYSX+t9Trh2f/51lOSuHM/JjdgLRCGNgqMG/nu04YAeAnxl6h8gXNHS7KdFT6BA35rfvDhpeFNNPfNAqbhNB2/KPiXjLjqhSV4ymGm1yevdPnwJ+lv9p5acC/T+tHCE8+bZZnjH8nIrl+XVgChJztiYQsdK93jiFxfv56JAPjRSnFqiFEkkY9+tff8HNb3/gHiyWaQzcKwNkiuTtoMzLh1Y9sq4cku4FpA0AACAASURBVFY7b597v48FnHxfsVzohFEB/vk7cPs9iWd+QfIgf+f3ptA3j3gzQFiGeXlrYdYcN4tPcqh5ACAWS/iXvNDf2OJwZSHcOz24QPI91q3Ldwkv52c75qG+DM24ZKqZrZ96rX8tp9x5UqrnYoKOM+RcWkvzkPVtvwOAzthoyGKx7JYNv9dcyPZtWLp2FPUeNoaEAdRSYkwmfE7fNxV6W1jenMvpWIl6VKJBEdKULYTwwfeHDNRLRc9Ub0jtdeQYlHBCGIqY4mztRUWk6cRI0HDSpDmvQSBlMs2j3wQOIjjgxcFnDQHHQUfakHY7zEM0v0qB5xFC+UHJZHUmRaAoX8UzqDcGU5f+prEXg1u4qEfr0xzsKjha4tLxIDg+lzGzV2rzHsrzVIe/AxeiuBenCll5F4dDz12JgK0EgSL8IMaGklfKM6Oencr6dc2ZRidg7imfd8GmblQ4I4rPiJoClJMpAaMohwGAm8yPKb/qVEFN8m6G958JoJPwxugsh8cTA6rckgCqYZagCjM2CCgi5KiQoKwMMHWAiuY/TMoZa4sLWmdQ75iYsZ/33jcCsCPxwKwnJ5hAKjTvmNWpoQBo6OJhxJpvvrPkFtc56pznLPaThZ/nrsIvtvzthKY51mMlBYCoiACyzR29zTLnAKDzIB7cUmfjLqHoVfHOpJE2SiiWmBlcZPyFFRaph1Gf7ZsiSuAybTApL2OQZGPo3dq3lZPD6kyEOk2yRwvAEEX63Gf0Jv+ZwERwUJqnpWDEvIldsEmxP1SpaAqPUgqKhlS3/lMpHp478o5S7Mej+HTEi9njfQiRqQJNPcmrYl37AEQIeJhiFw6P3nSiAxFqMBsf2TeJD3yJDmgbGrsfbnjgH4VByMqnQHwRwkjDMYZgEq8qODn4Yv+aYpSZV/eGMt0xZN+zAMH2pcKv68/lmdjoOOIFEatxA2Hm2ZthrcdzKRJQNH0A2QsJp3l/hs6OhVaeUBqoTJnCmcJd8BLxm31eHXODPE2CMqT6LXVGIcWxaihiBkYS+6ljRkezqhiodIrODX0ZyUQH0JhRtG3irvRbvLtl7+ocqQSrnI3KRTFEMlhiyblZwtBBZ8Npqit1OJRlgkOMjjGIGOVMx/3M2sYpypl43aIWD4UMAP1pRmGg1FNwfwbQUfgUTEDjRzCehWfV+WY7U9kaZth2eLEtLeOYFTcblawKMqdaz/NxRDLAi7epf/ffJIx4fxAjgdPrG7TW8fztIebsxZp/UNEOmqlCNqTNSvRlWXqYn/PhdX7FHtt6GB/j7WJEDfb+987DKa4AsHsVGy8Snu2qOL8cAxO7R3kxYGjOq3TumOokiq5uHsACN0VptuHW7gCfaDsBdAKYMhAI2O/nFPzSwWhE0Sc4bwzB3t3DHCilojPrWUfeKUWMTTqEX+iu2Dd+nXCqJHafZr5AeH0zbJacr8G7huJO9wdfKOr5BuVkvfdix3eFzh1f6Ivzu/lMkI1WLphQ8BWlfkS/6djf70NZtHIQsjPmE9jPowY3A0/vvy+x+TChEOHpc8AXI7zZJXyzKNiBK1R8OVCuyzxJOf30Ue7rGDYaoWk3C/7dTFX5JDl/PO120jfl0eoH8Uyvaog6K5+1mUb4FNoo0XBsnhnsRmYKDm5wVD8QWrjNgXCtYxU8U7aWSHALAtDuANrq7BGCHsHok/ShmuIZwd8Tgp8mRkSEQvDhfj7T1DhQJXYpZpwYNOYSCc9QwLuEORdP7KZ0pAORB50JV5qi6Z7ZowsaqYd6nIvXeTBWHd3TCrkijyR6ihnzWkQW+66WGvs1AZqlgmLFHcFHjrDfITyk2JnK6df6K2Myo9M4A4VBbuxHKxqYQvZLOmt23fNEJfHgAOOL89IMQNkAsJ7/csQQBuFBmTnztH0t0qEpEiuzpGAEHDdY3Wk6BjzwnjIYbn5PYQYrPyjj3QIAHv/8E8CKzO8HE2eCGNQ8/7YHwODyoPuxAfQFp9st2m1Doy+ouEbDl8Go54mA82mD1r85S81MmHAJAJg+SLSs9llMNJ40FWbES7MhKf7Xzdv8XHJ8wAw7y+m1nbkg8jQgzhMZ18ahQjpcADzu915nLj3DBww+IrpXPtcsoy8sOjvy+gc35cE6HQ4aIUeQ+wOHu4LwOn8P78L+z3AndwkAcKe+5xZp5wveVpZ06/UPQsdBMHo/4r6VXr5pwKviT5NTaNvLd9wgSOVTTPAoeNw7uLWhcf8+ybAyLDDzgfOi7fECCu9z2D3gszmUI/oahoshawHgv4/N9/LpT+X5z/J3lJ8K9J/lhxVjoDNuPCCdS+aNaOXMFurpQ1Irv89A2P/+WQiqvj1RvJHOjgd1j0c6Wjx9gVFcMgZLacR3liXxXeZ4f0sxpsL+e08O9GVZztAW9O66Diwmj/Qpxq4kj9Ve+2+gbxYC6K8r6Y+XNVBY8z63v5nB/qJhac9fIO5PbwC2NeZgB/M4X7xLwsRPtQwSkSSfOii991C2Q/ZoiIvs0B+eUNEvoPUlS/xa+cEnqR/dxJGlyiMf0N3B5wenjcX6UdyjcV8NrS0Q6zDzDNXZ8/As3tHDrWHcpMzK/eeDvuU+9jV0OnSxs+VCi/eGHi2+Xz9XZsBUQaIe7vws6gKVaCgOUMkqez9WTicE7A4aBEMPupCQpEmkozKr49cAMNVTWCi/XXvG6XSGxs2NFoY+EETxYAfa1mDhD4kIaCLMMn8VG+uSitkkc4KNIZqE0mmGeOmMCsyuig5CYQ2VSBoWfXGIzgcbAqN1xvNurykJQkFHc5HFrxF2S0IniuFIaQ1zIRA1MMgZUxNINwWG3rorccWroYAKq8EJHRwMSbFTKUXCS7IaH1AFVfXK1TzB3MVzo7emIUGbCiuazrG2xTTkhvc90zs6FXm/dzBF6EmZJ1FAFyooU3Xhh04oWiM0SH9aV6U9i8CRUFAqoc4NdarYnJzo6uu+S0pcm18Ch8AOultMYcwjzNqm4JQ+xDyJJs1LbiHnd0SgeQ/uLOunuecBiIC0KA8Yp2z9/yFPAMDzZveuoenbLCHp1SAAgIe8N0Fw5+7KYG+DWfcOr0sRiNSA/hjCPyaWsdkDTClMJEIs92JzrvGQ+XWymudjTRg1djXetTYo7h9+pf1O3R/oz4DwBWbtf9Je+JKKwYx4aRWoErbk98n73vWvK4S1RVGqsuPjjNh5bYrHKVudjIOzA2LWgZxndK1idoX/8ntWJUDpti14EP5bmPqDbvnKr0MNIIqaQgS0JkpmAwgwGp5B6hlbTs+k3TRk39FqkGApGHydEfDj0Kd4vWlYe9b66SwbjrAqGjfgZ6H9jB1ABdN0rmMD9pVBzSwvANQNsA8jP1PjieEChnWyOjiNqrD0k3yAvLqmlD9+ZznFCvxA1r1O5UgA73+2GFtznMt//Ztj02PvLZXyds5Y40nfW6IfY+SSgguwx8wqKJehrAu7IKEppuRmTvOQBijbcMRnQ+Qh54cFDgut0H4K71rTEGSqZ8Z4hg19htIkOf+g+DGHEPX6TLlvHgID1KtRAWnaHf2+6XPj3brleef1tSlXYmKye+A0z6YIZHR8wbFVXdIYhpw15z//QCE+UFK8VL4R44Jjtjw/OGLayk2OSxBt2r3T7TUA4aF6vxE8cicqCzPIWMJ5ePym8wl3jQQDdE8RZeeBYHyyEZr1pTOj33VMv9S83BiOrI6czOM5jJPMAFTge/RalM+v0+jTKW9rkxQjzPgShPAKT7M40GoInq9lVFCbZz0IqBrJyaL51LJFqY8AaXQmpUEXTBLNLhloN1Vwd1ZlumP6MJBq6tXdOCIeySMzsNT9ieARhJ8VZUzvphjpodyARR7iuLZ6E+2WHLzsvLF7kucoBHoetHdgEadA6EToyoN1U0ZqWGJXxtucZuDW9h9hgBLlQZhCPx9dwAx2FD4H2AD4HsD2uEr6rbTBvHEZwPznZ0yfPtkMHITIHpSj7yE+/u07P0qFwLjpMRecwrVbf/+uQoYHCOi4Q8EWVR12hDe+wnwrqr6Ka8dV5ihzyZrKcd/AteARHScASi3o7QsKrgBm7G9vJS3QYkw/cmxmjOHXfq7HYnkO16u/syMhSzG8GoZbYZC8KC+CSOYc4k4u18pbFr5Go4eBNmWv82Uzr+ZDf+PYrQ3HO/9A+Tth/20dYMdtnRnzrA4Fmn5vOIeTnUUTH6RGwHkcN0fQxUfdS3cL3BTe5z9+0n8qz3+Wv6v8VKD/P1gOBeZvLKuSBav0lTaPfL5azwt1MtTTNScqo5QjKHvDqIDOD6sU5PdfJPPwAYQNSzDCy18/ov12i/t0OM6K6BDmGf6nVLcdro50ejmmH4iDcyj3G/4+gpoVwoT10PAvhZ20tgFp/56A666h3V1Y8fKwmfmAkZHDrhwxGWFZm5lLO2jY/4DDOXit78tyzZLDd2KASxgA/FXF/LHlt35/IwkVZfNvcyFnwMgDZ/VYKPZzJvEyXw6zjO8BEVIvFwv9eIbjYS7t/qn+3kC8IhiMuYtX6qZUFTBozlRldEJwpPvEmevYT4xgVHrPihi4gGvX7Cz68kKYd6S1k63tj0qZ3lMWC8n6+8CY58iCu2epC7DlRjFkoYf1wDPDH3T1erO6m+YenzYb9W4QHNaaePxJrkj4Ycby/1iI1vDMiTzYsh7SgIVq8uGZB7/XsxSjKUOtoYrD4l+8Psdc9zE5827WcVRVGCq8dMvBq3NicGUChs46i+HdQ6rMy3hHPmOY+J4s1xfbopjSJvC5GWFJC7vow2l4rdtcLumBLjI2UGGrw+F4ECTSUOw7aXNzOXmdBQQqG7Q+g4gBzCCS9S5nataiCh7AwktWET2p4CYElfK7aL8IpInLgicwhWtAm3qdMjwCgS0babhmG7OH2dWvuTWkNOoS3lfXhCEhSofVUWHWvsvhi3oDzTPMk7lOEwqpEI3NGEeiUpTWQdREQa4nKlbJh+UizGHDclh0qZ/QuUBE3rKWVIoaAcgYCxFQKvZ9BhiYakHngt3uGa3NKDXBOpF4pydZQanVhZCTe8dIi71LyHVqovhnV3iJF1ClImE1S8E0VVljDs8cww8iz2PNOynCwlqAzgVoiqenDjZlMh2I5+CgvKTF4iojNgMgcEkvgMGd3HFYBK9VFPabjSjRa/X5b9oX5gbSMZApCWloOvAOhfeFgj3AcVCf5xn7/Yz9bofdFHuIbS1LeGmFPprgIso1RafRJM4+OYe8XpIjjDd9Mxg8akIE5W1WSVnipcj7GLRB5i0Qmxi6yC/Jf82J30V6zyAuSSAIbgyjSBWmaMhjNeUrc+QRXUxUjLkApROAInnCu0TeYAieEk/XhDuMbyNSNGzYKvrs85HJd1qCgfYm2M3jcG/z/C6lipzIpbG7QFwjf4AkmIYTSUHsXDq4QY00xEyJmfPyowNoRGDaoaf8JwUmrIeO2Lxoi8xHl3lrxCgcIhzuDMIp+FGU3I264gUBcKIu3udOw0RpMkZr6L63bV3sX5wJvPXHb6jnZ2IEhYL2JPBQL4pH9rB0CWGwtde120N8wkUdUglokDDzveuaKKyWxb6X2TBFn/AhRaNfMJErwPK/ALAj4flMFfcqu8diICq08Rwzi6dYwQU215MIBfWZFAk9rw75Pz4X+vFuAggF9ykitPxL5Wllu67Wf4Q1PvRyF2/i94bNtPf3HppbinAb3zBd3SjLopFzHOcqH1Lsl5Sa+FhUUhoCsPGBCufzrPzxJP5pZtRSTImYkCVZfWCUMgn8saXKkfqMfz7ZbOSOJn81/GLpJ0Aa/UWVdicnG4AIs/Ll0zQBROitYWZGoyK0kDZgzBFBqQmerBZJCIZTdF8b7reJSdoOwoWSDfmi4xsqLlWx+RUd0BDrco60M0kD4TGpIAwNPhLjTMnNzMDTITLFGhRZurACEYITA3V7A2ZGu5PIAtNHORc0jSzgVI9iH+/vv2CjntmbqeLxj8+Ytjfy8u0VyrZg1pzlZ79+0vWqylvK+WO330k0gOSpLfyT/G+jvANY2m7O/8m6n59O4P+K84wZYVjEKFtfYwosO4mP4fNnEAiFbrRpUZiXbcmU+aCEYRTJ+S/RYQK54tt49kxfiFIkqkIgqmFQpQrtagaqIFRNi0O/VtAdobAahpFFGxIe5rwTvhX53iItiRK9ocGM4QDWIwUDeODuPHlsb2EMxFBMzxqmpE55dFn3UoF4en7Tb4mMuqmhaWnoKHBFus0/d8zmKW/Rmnof6C8rI90tzZH9BgF6tupal/QRoYzUMQUuNaNTVuU5EqO4ZsAs9zUGFzYIXtOClXc8gO8W05fgxjw3r/rLisEr5U9mCG+yU4/uYqhzeQY4XtWrJebn/eWaBaMbNjI6ch/TeKxV/ft97QLwc/U9GFsQevKLrXwNYkL9eIP59had7zBDFCOdgCtWXqgSnqjjbBblOUqRnNAANsz4/e4OIMJVN6xu0QVkfXZlNDYz/v79g7Hayes5+mrm/w+ZsqPf5H65fIQVs/oeWykGwAdni0OMuKQ4BhcTCJVvMNO9v1chIb45vZfjhjBej9TwamFRnl98+gXMjH/d/nmwd3B46XdoAadZRhG9TM/9rkUPyeeViECz7OOLxMVaIIBe2S/Ls673khm9NaEFaiBv+HNQQqePiYFZ+RO7e79EaBD9wgZb/Em3MR6oUj0NkhE8jB/xU3WveZ8fzMWK8ny59w7X62f5WV4vPxXo/zFFiV9iyt/21YpAZIEY/zrKSRWa1JcX94+UCaIMrAD2v9+CCLjqpEp0YUBNaeoGxd/TvdXbRgx/rPTlR9ZmXt9X3ax6I1R7DqNuIRSziPkgfPkbiHcuS+aO0n8rIn/wIt+N1PEyk3ismProtgDb117G20NmvbWEl6iUvI++0uiVfp4s+u3d5YjPEhDS2qbUUiCCRIII5czjhhDhHdc/XV9ck/EfXwM9ENrBQT3TDzyAX+jzS/XKz2XfXj11/beVYZj5AEuH76z2nsPK/9iU52lc4/fGg5rcYQohgFWiMoZDZtL6l9ZvvaxSB8SapwM3A0gK8aWVdogqFgctTnUyp7fSL2aAQyhkAhTHzhz1g+MwOfScl+0eMtR2LjQPcTkrpn1JtDiU6N7gDgnyKUK5XZ+l9QTGcTAIqlKI1GOJVtec9NhmhwToOCleGGCRVxFHurdcbxV+URdxQCdSsUDBmsjIvnFv7N7QO2FuEs6xlBm037vHCFRh33tH5e4SH7kn/ZIhqXeMKWqsu6ZYtdkg8dzpzMlTPq0GEahqjnWGeIo3AMQukIzJVSMWzR0th1w7iAG1TjjZSDh1U7L1NqMQYaYGaoSGOGgWKqBaUQt5mFGm8G7tOmfilT/L3Ok9WRoGdVGaq3kAiirNejdPmpQawwFFleku/FBhIWQuC5dx+Q0hmJdgIdQqHuimRG+tuYdrZ/Hc9dQHbGpcCvgjpLzcCwtwhhseiPJ8h+fnJw/xW0hDh2s0ABlWMaCXdfLOL0ExDCmXWtvlN4PwNPVtrFBhDqYEDZ6a8vuBatZ3yYIRZWShlSVV8MswSsALdIMwKtEBN4jx9bD5t+bJYOWQ0RPjiq4pONIAw2phrRepDTOUyrldzZ/zSIkuHoxTlAcpbYsK8mSMyxrT3B4hoq2zr3nrAJUGcAE702ZK9DQnFHN1iOtPQHg+WBzDDVBDITb8ZN1kUUrTmcJxhyjys4Ex4B5zBHOTD/wWdM9JwMG0TufnibYycCpr2R41mlC17aRKdF3DMGbbgekEtFGl9z5PjcyK5XhfPRcxo1Io0XswGD+s7CD8blflOAMoF6Ls5G8AXfwg5v4vlCVcv6Y4/zvLI1jNIr6v2HkiyqXDghXfMwuhpysBstGOvZD5EN0oOfUEWMiT9VtgL13oDxeeIv76N8YvEXkqBZa8JsMCBTtgPG3HblblsApmmSO9TKUiwmACCJNiu+QliDROGM5m/2tlNH76ivn+EtN1dfrD+IIGHgwjngKpKGpZX1mG5PcN06DXy3nSwJgxJYbhEOo2FJ3ZgCvPO2OZN5hw8esnzGpggC3Q7w4pBKvCFNCw4tzR7xj0gYIvZ81yAT2PknEb7DjXeMjsUdsX9COxCU7D7V7njnab8sBuB2jHARguSjYgjjDnqQwGTOn8YfPsk2fGTuF1Tsov+e9aUWrFVArwC6HQR/CtnZXuZP0V7hrDUyH13jQ1kChPmFNCgSIT7d7ebDxdDJoh9aATmGcxsDAFemtCP1h2xm3ap6CO0gmlCJ0rXMSIisJgHMyYO6Opwab0UYxx3ZAs00MLGW9niw5w0dDEIOeXTUlovBHHiOVfZX2WR6SD9SXglAlfPZKTKN3Ns1X2ehippqU9Ai9v8K5FeKLniBBejjKi/1wRs6ctxqDO/1BJKP0gEgs9wKJFEK4Fj+Ee0/YDPtx2PzMzf1UZXOKB9TxwRw9RIwHT9gOe7tQ6AoKXK4Q/imgOcdT6K+Ulhd/oBBC/s5J8SSLINzIH/Vgoz1fpyg+AL0tlmktNv9f2yTHQ3vL7Ic3ow/vY0h/Bw/5YPvigGO+1gBU7Aw4RDXrHrLjQlOjf67D5gYHP+nvLAv9Ptio65BtG4pfsnDrixvEk9D5Qe4vy/Gf5Wb63/FSg/z9avkep+CLmSQQ1M8N+iKBDND8IuN7RDavPuVHK41GLYkqxR2GHcCTBkiDH35Ud+T+/fsLTb5/FKhri3Xnd4akctyxhQw6V6HYwzug5czYr0qj8/g9CxtkL/e8oD3q4/sDAR77BjHvJUaLDPci5rn25dgp2SHzWQNAFhot790QHIdztUPGFgBvcDzKUax696l+D9yuFW6v/VoUDH7iCKQ4hxw4jNswcJuh7lelfCZ7PLYfWbwuvDUDy0QESGu+lQkcvVooKc86QDCMoxsgATjCmKhDBRsGsQuqN5iK0Z970AZyMx0AJySxMaG9dIjZrjkB0YFMr5pbtDddHa8IBUx+tb8MfzAlZMwQcLMeSe+P123JPwz0PFdDwa8nMei5wPeibZ04+4LtwZjgMjfcO8Lf9FLnJsIByYOiDojwLk/ToCBFGjlannVWIqOG0s0DQOkDaIaLinq69q39cUUWOpcJbLGV4EEUUguhXHOxCaAN/z/8iPDZAJvHfyKh4r+2e6LvqobKROA1tL/3vesotOq6iYxwU62cEfgboFKinliVPhD/ohGmzwTyL4rhU8Vo2AZStlXmTZDqkMyYCpipeMKTraF6eBBPK6Tox/JBOqtkjMEyYmMF6GcnA23XhMlSZnQJslQoJuyiCvqY0tdoqFNHE1CrCwbkxGA2lVOx7B6knYFZYitKmoFBHKR29aFj3kum+tL+fZ4AZJ6diGtRamHzJXOphSb1MuCku0lza8yyh86kQeAaaAuD5+SUYDfv9XkKpt+b71PKvSmhNEVxO04TTjea95442Nz0IyvyZEt310bWoR9BG8q2yGRqocKKFB3uz0O0WtYGgod/JN0rrHQ2aw5Eb5rmhzZpj0tYq7cMDJzMOD1t7OQu8Vcs+Fp/bMtySnWpGU32Rp4GSAAYSAl+1Hybs7Ky5cfcznp+fUUgiEsytoU5T4EL0pEQtPherVMDhVy8Un0jodWCxEVYQkPxjrzKysoi9fvscFAKHmJukdB2Z3lRTCG1HvH2Mti1p8rI+/ZesmyOfamokUlqgXR8Y/FA1FRQVBEsAFPFim0rFXBSnULRqYy7E4qFcksHeAaE3Pjs9ywzK4j0xEkFSROns+beRF1LwYqJVaU2K5lqtpar3szTaQWDqGkHG3455TTAjfQica3NmXbca2n4/4CSwGSRICgKrlPEI/iYGU5vLS937gqdMMZCBpDs+j7EN/LGtreIPVrhjAP2RQWdAf+oAPePk8kLozl72SG8NzAW12r61GdK4HnqvnJ1jfvoGVlxgfKbn8QUctx2cmXRms/dzLGniqN7D3um7ppC+PLtEKYTnhwdt7xz4Jjxux9cB5P5JJfZ7Exi9tZzGNKtH8tvKs8KFGei+liLqmz6/1Pdth3RcoIAkFRQI+3l2+iM4RrlJMqpQFB0afimAepYCFiHDjE1Yoz1E1BOjhb7Xek870IyECLu+8x0qaE7jndm+ad1xYDf4NgVhwslFaVZ4AIuX7DzPqkDvrrSNs0EYrVpqEfODLyVCYNieIs57JOFUnKPxF7R7gHAB4Btm7kcijR3ig4wasuFpYKvje+3syAO7O9/fA8yo2xuUUrD/PKNui0cKqjfXmO/H8OaCAY0+yn8nmxr9/i+gd+HTmyYdr+rBaRF5+h0D+IJ2CzRcoWxVmdyL0/PicCKRhgpZvwK+TCFk/OhuFpxd9FzTtX373W9lTet264J5ILEPTkvHfZSNWi2VSKHi96mEoYe9R0ZVtBmho7LjhJ9Ur3wQUHQMem4utaJSUd61okBoCH0E+BYDjLLCdWfxQG9N9qErvTNfiBSdKglsDOzF4LZjJuEVbE2tHuPD4RHJrOJQpJdegtfWc0TRcPlgYOYGbqKkb8qKNc3J7udX5X3Youaw0iMC0CkZkbJHvQBpFBkAbqQ27OfRUMDayYaXnVkiOrDRTHlyTyxOGiTzUVi87e+8Gvn+WrvvERNTO2ORG5aj+SqG7d276cA9rE1fqlcwfBTz+gVEFkdE705/eMO217eoHwra50P54FvKtQ7g7REk40VZSsIVSxSlLxBce80AFwLhAfjzRiOtiefz/vbW+VYGJOQGLFII3AjE1vq0W4oO4OnznaQeg0T3ICI0Xe/l6F8X42c6MKg6B1wxjJxo+Mq+zbcSdYjxeH8ywTjSQZcNxh4fnSWivS0z7ugwhecHjurnzqgMoBBY18CckO5IFbAIB697etmwpKzffrEQIJ7nwzhXXlorzrYqrnwFTk2eZ+dDm01LiLEq7zZk8krJdGm4l/4u7zscSOfCwBgIZwRIqpkCHmiCGGLJ9Y3i2ArNaa79rVrv/cLCp0J1D5ScyBLeQI32yAAAIABJREFUyXzeQB/HQRyZh/ixVJ6PMtTvwUg/y8/yU4H+H1TCW+bfoQSjl1m+/FRKMHxr7wUifP79Fme/fsT8++cUJklYXmO+jIDbwf57ivodfde3r5UfqUQnjHX52CFMotHim1fae6C3eXB/TxlCvevfvCpXLLml3kLgjh0MGKE4f60vNl8E9dp/gUF7rWQxCCOU6kB4n/8dW5Gxzjzm/uwBbBazZczLcpos1GssQV4p84aIsRCgnrPww/7SE2kqBfv+nuCRI5OX2/+3KQfoycVneskDozfgPw4GUf6uj4uHb49Bu/1LB7NGaR/xKtO5PFatjmTlE33blMJLw4shjGf8yoc1mR6DNd01nH+PeQjN+9M9XbQx+Zm+cSUyOQz/aKjhZ53tHUCndoBigCo20wabkw1am0NgKC+kPTeLAh0E1euDNgxQ88OQjSPy+LLr48LrS2aGOMNSOjgdOZNl5SqReR/qc5bc54B4bVQARFV0pGSCx8M6TWltYdV775j3exSK+6QCRMtrTVTEa6apIr1LMm0TQhN40a+elPuk3gIKMyQyOgtHxprawE6tNl/mibSk6VkGKgLJglqr5wPf1AmbadLxMOayxzwTaCbsmVE6g1N+x2Jj0xDurc0qpLfQliKwbCaw1H6Z442kAQglOjcJH9h7w9zM27+5gF/0Whmrq2GEhU9WD2pT+CPtPd+floe9NQ2xL0qR1puE9tfn3CUk/6CAz/BALCFGmUHJ491wBzOjaYheUm3WPO/R5oZps0GtKkgtMl5XTB/ZyIZ9Rp9DxDoPyE2UG0tcjAOI8NdV12yC1gST691Z6dn3lYEEr6FjyngVi3mGdRwGF6Y0ikDZhOyRUJLgwTkZxz3k+0hSjsBznhMVVIiXWCmZdxh/H3Z++dDSc+g+5WjfYM0UbPK2hulXGmDeJEXHLn2UPjc14jN6RV0FjzxyT6YQ9vlT2OM0N5zal/kfx2GCqA75h0oYguQ940YzpPszpatQJLwQXMm/lpYjt2dz5WZYj9LLeib7r9Pe50RwnSoOuaN0oPUxjGRnBvZ7cJWQ7wUF09kF9rOkRAERMO9RSaOAAG4kYEogABqYW9Y1ezCPvM0LwrJ3FLMBsvqgswWcQ/yv/2eUU/4+gfFfLcGzXgjsXymDAks/EdFZHG+ABvS1/G24xaiQbLkCMckhN2TJ0WYC1wOO27xS4//0qTEBiiM8mgWguDzxSz4+MTQkmKIekvqIjdM0XGNGkZRCLLEQY40sYUpyYqMgyTNaGSdrM8q3hDe/okEVgoh98xaBsNV5zuMadBCeiHHG5OHcjynOgfBydWfomyuPxFS2BaMh6OgVSwDKzVVKxZLwqPPwlq+aU/hYN9FJc3MVsHPHKqjgIT2J0Xt/z+lJhRjTmSIjEU/jhRK9Nu9mAkBbhbFhjhT3WzUHxBeOiOxr9yDX9ovxaDDYzHOECKJDcOW7GJUJjEl6DOWnlWcttSodn6RWBiLtSpypGsR4qjcxXDQFuo+byGmnwR3nPaI435TjOdJdt3s6t9w7LluX0O1eg047qQd6h6ZfknHWWn1uuvapKf/cNN2CGY8SxBjO9rntJwtB35Vmyj60/eIc4MGaDiH/ljRJcrfEpcF+Pj/ovw/EuGDgqynTsVKWLOtfKFbNTfcMFeFE9IbvbQ0rgG2ay7cWU55P+IjpY0H7/P3mY38p9aLhehC+khgbfCWVt+orne5BfI1C1/rJwzhHdiCkJX8YUZ6+EnAB5WnIKEOwtZYa7HvKUv7ykvJ8ed9lCHZteNZoLYcR71rJvLTzlj66KNcsBh/Z8KIieLy8hgYbDDGkHPhXGiOUbr2/8p/JsV+SzVa+wSfcYffKe1a2/GONG0eMQosnf285Kqv7AYVZY+rYOYRilPbXzzqQ8Oy2zh60Kk1Bg8BCho0MV8vZ+ysjM1r6s/wsP6pMwN+7pZf8wL8X+C5H/gO5l9Xy3zf6ELvAf3E8GO5j5f772onKxrCSi/kl/8cPCXYwDN46CaVYPIicNPkAGDswdr//iZv/+iQMwb8+uwXU/0LBIzoeYIrk4eiJscUjuTTJxjdwxcqsH+OGVyYmuJej7xGJJSphPZfIgfRh5dmaleg1h6f5derGMebUrE3vCYhsr4eMExAE1ZmVPH+JyC6tEK0s712z1vVGOFx+b8rvL8TuVWSrftWBh2UMaYq87wzgBmrtqM+v5JWwCF6ej9M1AfgGOOwuGYAMba95nh/UvyyL+0/ageVx0F47QeQ+B4BKItK0HGsR5llmK7wN0+EUjM1UsJ8jrB4Dki+3SHa/ubF6efVhvOZhMs5GZr/s/grTSccmfTElaxq99xR+qYUjT0g9fvUVO7CqDxh856jiyoQOJq/J1rsiaBcE4EKDg9ONeSxEl7Jxj4Sus8MT9PCXmGse51SqicoCTalCtRAkF7UIMkutw6GLFXGRCQ+aJLunUj1tiIzZJljbGrqT4MDqXR7Y7BCnONfvpSENq0QyGOaNHASfdwFHBOBkB/Oclfk61cc7f4XgEa1HCKVQ3VTNZV5q2CRy7zi52IBAuLy6wtO3r9i1HTqrZS0DjFmFYzIX5QTgmV1JYyBVNYNcncyDXsPC9xSphWLFbA0HYeYAsuwD8mkrJrDWJfD8kAqOpYN6Qa1dFE0skV6IYVoqQBWcDSbMmyTHoHpU7nasSmDxIC4Aaq1oc8PmZCMQ3LuEvSeS72CCRfIcj/O8F9yjQEjE4B5HR1H8zuKxbsMrxmtA8203hXPGvN+7oKAzi1KaG0wiutlscLI5wbSZcHpyiloLKjTXJxiSOlMUeKUVcGHJWa49EqFmkfDttaqxSR/abKrxkRyjpFNE7g1lnScSfNBax36eMe93mFtHY4aLvdhCeWIoZPhHwzSXUlzZLmEli4aDl7qod8zzHCE0ISGRO6u3fG/qBS8Cb9svwb8JQlM/QvVAMmF4Uo6igedgSvpJQwdjM8+oU5WIBqVILlxDHYOCVwVUamhje9XecQ4g44hB4S8b6CipyPhpIFliYPLSwVzwCvscw9MTyF8PL+v7OOpy7Oy4NuFzf2PsdYTLj9+B32UAA/rP+IGh6T7Mk5hAFIK2Dss1ulDaagVM0a+CEvyBK4x8y0aDPgSjmGOt9tsUvTJNHMo5XY/cr8hZm4SYRm8Xa+PKKwImilQVncxwJZA/mzBSiRnBFME7wd9sS3SKTh2Nn11ZDILnYM9Ku6wA33/5hnJ+hjIVV+pblIuepoR0kO6BrnOaOT7nDwgo58IF9ycG05OPqT3vwETYXJ4L3u6MTqIkFCMZgYdOSrIJOi+xyrY2hcLAhzhypYuy8BBaDOZGwzh5fkIFBQU7h6xDiDheGF8fv2LDjIIz1Ivqk9a/mvJIyls9tX9UOdyt6+WtLOu5vphzgxKEz8+e9RYX52mlD6egVz3PrVz6Co39tPnczbPySgmHEWF+aCiX5HTElIf5fO8Rr1yRna6NjqJ4AnHHQc7jGt8a0RcCxZDXZX0iBtpsBnbyrJQKZmDSCFxzmx1FlVKcD5+Vrzg7PdXIMR2dRPmYgbUU2XeNpfdE3ZCO9ocWnudGahKuxoiidXfGfcPhttntu5UlPe3AsBt1ikR53v3z0knOMONW9f4VMMrNlSiuEUrDTS3+DgAUqpg1Tzrfd0wfpiHtEStea03Wv1bxzLcUMe1WDJ1mHTVtBd+UD9XhZuggyelqTMMb/KZ5KHfuzh8bDQyyTti35v0M+CMJ2U6QczFFCqcYr7wZhk6WwsTGaxcUCmOYYS35i5PELhfvaMCfWYoMe1/sOMKUy3jFUiuq8pxydmMHEfpAoPsbMH0Ro4/OuOjAg9JQC7XeW/f5Iu5ixOD6w8RR2KGBNfpVF77R11jfFLFbx0VnfKV4NvJVoghHKUJDukYwg/FyVp/9q38T7ZMprs4HAgBVQmVCb9obQw3JymqQa1HgDI9a4ddheECy6GLIMMBQsHGxdwlf0XGpNFGZ2DwRIsd6K5FIxeRuppif+AZM9x4BUUyQou+kMDg0DsJHBmawKilJPezY6UqhLbbqN89Yl+VdM1yeVLAF0LH7/BkTPvoc2za4YaFdf0lBvlpiTFcMPBTh1SynvPXxQY0+b4gAuk901Hi7a3Q8oFkaAzXYLlTwSN15969qeCrGSMCZRRdRHmgqxaEVrLB2OP0H1773/XkyC07PwzGO/F/fM0Ru7OJIgA1vZ/4cq7DHUGNEA26OvULJWv8BwAetozCj8BZzkRgJNyzREMCMaxYZgJycRSFbCWF4mdo2OWVO+/GaY9MVA3u6R2GT9b9ebunYthsbMjqXUdbw1sENuWmXmS2R+vI5Jei6nVl52VCq/tjIbN2PPTsc1VgXQSK+dNYIMLDMHWbgO/J2IMK1pmC5K4RfIGv4/338JA4Bnztm3OK+iDEPs8jaP7LoIxYzPAzOHQbYDCvHdqvC0WEZa80y1tFR52f5Wb6//Id7oC/RRr5/7PoFavem6//eIsIbeHc47oLeNZZ84MvMtDD0/pwQiiVvODFRStDXEDotfo1P828hwoWCmWBF0J2BfxHjhi3X9xbA7Uq9f9+ax93XEXa2inzp7bdC01JhvabAPqbUfq23S6vFo5bvSQACvM2z+8cw1CncGIUHuLGgscJx/UASap75Cki5jXixphcsh8A1LyQvC5D6jnPRDyhrOI41kHVxRe+SiRHG2rx2exhZp0PsNFXsd92VA8G0SRhXOUAQPE53rAZiNjg9w+K975mxY4CzrCtff8++PvxehAQvAC5jyEPt+JY58ugeMOzH6jqEuDybUQzfi/J+aYSwhF9F4MMbwwDSNUf39QmHgkKnh/UzIl6s8LJ2PlhyRhglZOGqvWvPOT+3Pc+AuHNvkA0LhikEgJ0qXTbLh7x+ENED6UF1HiJ+St8obVNp3vnFFfYPn+MTsl4QxBZ3AmZ5wNT095LxD1pLqCipHTDrSYdAqviIg7q+4zO+HJf9R0O6aBMUiWduQSHJN1gHHNoldGaxkF+AaH+qCoo6WAWyvYmHpc1h545CBdNmg9N+ggLg5GRGa5PMWxccIh5gBNAkoey7GmikObR8o+AOtjzirYEhvEFnEawzSUY+ZvGs9rj4mi9xnmfMbUZrDaUAtUwotWBzusHZ6SnOzs5RQOitgVoRhROJN2+ZxVtaQlkmbwUSj1IJTWnMlwn+LLRlF+8YtoQCJiwNODCvPlFgz+jaT/cEN0MMkgO59aCoEFKUYxre1KIAqDItvFBlzbl1zDw7HDTLjbnfyxx1a7upd1H2NiVQCQRguzOHS2VoaF41HiBigXlmdBbl/FxnTNMGdSqYpuIH+iX4mhJ0fZ8ngM7vH764Tj4SiZLI9wrTXFZ51/HbzMVaAzJ2E6uw4udxYBR/dE8v1ZBR1uhk3DOYCWOq1AazGoAakCUvGSqKNgimtsmTkrirhH4InZJ3sQmbFznocz1j/xPRGN4x8WMyEluM2NbU8rnmtsj3z5L7CMUdQSN1moJL14UgkTBEea57k6AeeYrjdS+DoHjkWZQTzG4c5RBg7wLuCRdGTvp+Y3DtMEWAPtLvNA1BStfQtfFDcqUe57sGxjN6EYCSiNQEVrxgNHTmbAjouxYyBYxps0HvjNb2KBSKaSEdpHgOABNch0JGE8wrPNbExhNrGb8MXN9bbCp3AM7A4G8NdDGBv0a6Dx5+aSf/BxQDwQLzsx/vn+nfR4ji/PkoTnlLuXCe1SQIphSMclj7mnA3owb2KoLfER1ggm+n+yX9Tpz6gRHSSlEAk1Q3Yf5FmubBDfdI9pEbIy6U3aakKKWiqOErK94sFPypCKCTgpn3ikWz6erxwuk/yr+P0S0cQveYfzzmjCHpxIJCAZVTCo70LQCUm2t5b5shIHUiDaYWAncCPmhIcYqWDdV3TfdQFnS5bAv6Xfc+VgqPbcO1UJ6DQKjFcDw5vpcmtMVS1ECTlf9BrEGR8xtp6qDBO50NXIL/BhKc8gh/GJ7HfBh5KUWVdAvlsM2mGdh2bdMMPnx9eNxmZI0RubFmLWXwcu8wuii8QNVJdTNZpZus6VK6KtcB5cEzNLnCf+RphCZFx0yOYHTo3HheMh4ICRmLkrITAU2G00lkCcVDI2ued1Y6D+f6k002ScowgjEh+rOLbNDGlMA0zPvGNXTbAMc9SYGZoOs1HJr391ewy/h+VFlGWNz8ssEGn/D4R4Sk/pIMiBkmD5Vic1iwxQkYH/hOld8AcIuCG4j5knAkQB51zJx4FnOKaUTo+IyTj7+6B3qWvAFQuMoz+J7r5aqN717pvrxk8zqPvjv/h1DcGga08OF69A1YKUIvnoucvk/ajEfD8eh4pOK1AICJXHqgCMeTSwnO+jWl68AP+amPN4eosFEanvQpceIkNfqmsWt9xWrg2Ct59jNduFGS6EHPABR8GChC0+/Mmzx/TwAKb6UdevDnx6LqEF6WIX8hDQ+f+jvOyl+ENn4Z+uz6OGcpNWZanp/8HSXXm/u2HJtyQPKeGU4DEHmYGPuaMJghhpA15Yj4xKJ/ufjlF1ARg7WTXzf41x/ywb3C1gdOKZwSIVuOP/ePcDhfg7k1yz9L481XTug/y8/y3WUaLI8Ah2AX6L9ybQj9AJEQFoLYceNi8f4/XpanDs49tb/HUM2xa7xwvXbvnxw9eReIAXPeyk/XjLUOe6hW5IqsBLkm4bUy1/Img2G5Ko1cmGKuByHSuS9FvC60FTvWyCo4J6vMhApsjRf4oqEiN7//gT0DZ/rqbwCIWSyeGtBwiy0zCj7gM93CJ2VAzytHWqWctFhzF+Yx8NKaZwbd98qCWckgyUj7h2OOdLp971EZw7GNFYklqa05aGWf6t+13EbLsCofWEwPDkaYBYBHCjN7BADgMMf5jy+J7BIAZnzReblh4Eq9h+6JXAlnjOIDEa40u5SteHjWy4+woF4OYm2O5U6I7+RvRXiQfPvLc3GcXQNEWGYW053gsGBCz6KA2BcwCc0LaESCuctenCXw0jRprrtaodlxMM9NFakCfOLZ1JQ/lw2+SXMyr+0bsm/Zt+bLEGY7YvEW52d2Y3mNlee5umEjwGEqt5tRRcarmheRbZ/a/KrAOzw7FSYkNjbM+3c5noPemtU7y+JZ2L/iXnM6z4pDSsnGDCUf9QBYSEy4sMCecO8gaN49wD2DS7XrDib2/kclI0NrcGFW8APaIHIm2BXlHiGB4h4j8rqluZSnDFd+8CaNLCnRjWgwAycE7KBGXwCz+G254vFM8lzz0zO4E+r5yTCvhUxAFSHaYzgF++c9iAhn52fKzE8AzZ4jkncBa4WK5DrHDOIKVGjueMJkh3SysWj/SlGvRxVMNd1n+l3OV22AwCAHxKaKsWKq+MQPCg+nohAVfHYE88Cd1bulolIHsyhluwmfVRFKzRRFJJ7XrhEGmDtqqaACtJnw9PQNvZ2gnkwqABTB9X7fRRjdTxy+GB3TFLkzmcUDrHMDdwkL3lmwy343qyEDofTZaQJzl82hcLTb7TDv9x5CtGhuehcQs/S5MQDNk25KOPNmF0FuAdeqnjwN8ubs8ztbnskmodctZGbrXXOxInSaCvAMRpl0cWZRts+tqR+7eiHo3HYwqBN6ib0kIWZZ61T8QEIDcjjOWgjddgAzuDXRa3cJ89nsv97A3EIeY3ADUYwXBaROpO8J/Wncwkt6OH9oTssmXrCW95YLgXuFReUsU0FV0R9raHiw4DzRbyReyfAFMo+S+TY1Upj1+xRhXrplXkZIzBh5Pk1ToNqTw6+T8En5sFjbRGcGzVAYgRIAE3IxC54dFfHWh9QsGL0v+FSGez3JPlZlARsPwA67zj5a6E83TlAvHBPKqTDRBI3mIa36U8HZmju4ga0J33sWmcAnJ/2JASURiX5LTGgehjZWFISktLU+B48Dhir3aQgdzoB7gU9qZFNJ4JC4epho884Twy2NHmHronBsOQylD2eY7JqenU5FquRDpmY6P1dczqAGNKUreQ4Cjgn98RumiwtX7jHHjJRaQCzi6emyoD3OLlBliBGUZebcPQndc3qx2QAQb3xYCgaDcOXJOhhUhS6Y8TKpAp36Cbg+uesSUwdxQS1dUnqw0Au5tpDvUJOwMWrRmGs+rZvvxxj3qXLZJrBlesIMoH47h/hfd1/zJ/8eaR1SW8Oe+nGF3/jMltKjATk+kOsTjNueSSNfMXCq985TvcLxifL8PN19cgMPLUcGfpr4jigF5YqcRtreNgG5sCaCTPpXQr2xvM3yHgES/tmNv4qjh1CAmvKQVYWj+MT9InVkBqvMCVqMKxSka96krnhI+CZxbmhNDMc200ZpSsc8d0zT5DSnFPLUI/t5Bphxsjnx6WMAu+eIQCEwzgA3AFVoWZ8UT+20n7YEmT7B2CU3ZO5gnKS1LUx4ZnZ9CGLUXoJqREtfiOUMqsBVOd4D4OmA5PoC5YZ8PbSjQteK0n0F2sF7m8xDMvpTyyRnFFVoo0jKD9YQ+aUWJ7fTp+r4lRF4xmszXg5wQweBnZL0RAIvhUQp200ApqShdVY7yoAJUh5XjMoULvUDUr6pJxwSBk5IfSClk/KazT0p/ZW8v5aqCNCTuO4FwqZUeIoV5a1I55SKcu3OQ5F7wJunutB7nYeewnLfEPr9DZjv5F4HLjph7sC9ri8ZTymVy59uQDHiiOB9FN/bb+eNZH4LM75Q8C4Z4/k3aU+aQWmZu7G2qEoPOiwCi81q4DFawAtbn0hgVcQREf0lIqmQ81wRLU2/ZdmXtuSGwwzO8yiG1CSGDxJfeu+bNMHwOB3rhdbfMfnUlU7B1z//SPOqYdh7otvICkr2312di84+/QJQwfzHDMYWDbcAzNuTscEn7NwRSWZ5y8AGW9SPwP5zwF/BDWollF8q5j/GIViamGs2ljMG9yUTu2E0r5XAYF/I2Gtp4MrOICQ0pCmM3htdUNi61PNJIxk3dUIrhCcI3jivkjIBnXEG4JtO4Al3PBLhK8WCFkBlM8EnRlfthBF8CEf3oU3I3meD5th+tu9Mnc4qz5R3SKOS5YgYqWk2umh3zKAoXOLEkGYx99pd8+IHCS9ZAGw+fBQarrKc6fMWO7pTOSvcYafgWqt5kAgk5d73lFPsmJJB4c4YocBJUbr+TIwrHt8lvHy9rDthlYP6D+Zy5Xp4pnjTcMewfqyU0eVSQI7sCSDpCtakgqm8xLOmNsOwb9FnMphT3Kj4UKLSRT12JrlmQgVwW0iV4ozqcMUoVPB/f/8NzDzqGFQnQyNABjeX9k/v7PKypRe5DUto/wtj/1l+lr+hTEawDuj4YocevU7CozUEt4a0/n1KHlRGS/yO69fQ6zFU998zE87IL9b77aWIRTEDjC6MageYS2JHpWayf104a4cqsW41JUytGt60FgldCAQRUaJih/PelPArw1UoEVfB9JiI8S8AHxJBAqzNYBa3LDmBpCzXOGdhsXUu+L41T8xLaoYQzBItrr+wpPRy5yCduANo6uMYQQjPGEhIHYIcGtd6ZTlqGOtKdGmW0RrjD3w/1LIzcnJd8Pcq0Q+tEwMu7zMH6jOlpzOdSubxOk5mi/oW16MAA7jSAX8juF7Pri85Kc6PckR/pUSlHcAOhCswzi/O8OXbTrsse6zDLGd1z0FyEjPMe60oE08wbw1h/e3wb0Y0wDQV7PfzQDOIul53xL/icHhQfKPwcG9wYntToTf8pcX76frAm3zt+mUA5vQrKz7llgoa0/btiUkcFFNH2ObV+VDtCynDnd8cTYBMNa0M/AEOzO3qW94nY8ApBNwMsHmAUIRfEgGG1SaHVBe25lGYMALpUqVS/sRgYCG4MC9KgREa6okRpfWy756PcybLdkx4BWYQ7yT3+ekJqBCmejLMrJXeG6qGA3Wcn/oNwIVhlQq4AKVImEvzWFZRoChn5BQON1oSV0QwA/OscwAVuaknCqDKn2bGMCx1pyUwZSCTCkFZjQGK9VGmqKODW0ez0OoANtVoMKF1UmGjKE5FI9kgua8L0OegrFSwqfIu9Ybe5NlMHR0TGqmBidKuSkW8FYod0Dv2mMFQxVZn9D4rnmVfM1F4iyKfAQ+NjEoy5ywh5vfzHvN+j33bi6Be299sNthoLm4AGvqdRSDJHfvdM1oTZTgzMG1kvWku2HHHvJec4QAwbTaYesN+v5c8343Fq7vPaOZFDttdFOGTLSZ1F2+ted6jzx2z5V2tQGHzViVVUDU4OmczcTSBvOzJQur9nk6fwotB9538r7UZrc2wcNLmXWvAQciH2q4HcLkuutdLFUHP3Gd/X/7TEJnMYEhI+N4KOomCDpBw+VwqplpQSMKT7mcNozoV1Ll6yFHx9GPl93pSstu+gb9jxgUEQmNCZfVEM6SsCsHCBVy67g+AbN5KEa9DMxwaY8c6zc/GP77hCiSXLiGUYyZAga0Zm9uuRilgZUtY94UJfBeY2wUeBjReDTxnKli7LYoFk4aZMYgIuwJnAFDhPYuSlA0vVYA7igloMykh81yrMfeAhHgtPjmO3x0+B75brylgzCOTILxsOLutaPviUZgILBZKbqRxQwRAgKRHAAjFjJ10TlnntLBRT5mb5ostdRecCmxSAdOT8lfsQ3J6a2cBN6YwFQoGWLVnXsjwfEH79oRycab7yHK2i/AK+4JypsCl6T/EgNJ4uOI8H7OZ1LHkOy/kMBd0FgaoircFrZtHOxFA0yQGMk/KtKkyS8YkoXkLF4UFQlFDjc7ABKFhTaOBjFbdmWDBf3RNvwIGZk2psaOKU1cmAcCjr91YTESaK47+/ujCGEOrH33vCBvKEC9ym1rDGz6qACP4cDkeESRPq71/oiD46HjlkIs5XeVsJO95uUrGZUDay9Zm/pIXvyMiQ+bQ8itm7kJEKA58apBlV1KJ8DRKMwmOsuBKAmd4DJ9Fa0KH4l5OP0EUdQn7UYRWJ49456Hdkz0wWh4UFYalvzH/T4m/S+QPAAAgAElEQVRKtdGFflIUr98zAzgH4TGDvO1SX+MOiSpmN59VWH8KGmQ9GaMyJHS74CtOADNsLy0X6ZqHkMBFeYklkCzD8JvH98grQPg5MCqSQpoELpoJ1dVAKPMNEgbYFJZy1jCDXtI6zSDI9zip4VBTI2Pj85QOSV3B2zgclRGuO8J8A4qjzWO9lCLphCbxmI/IL4n2sVWs0YBM4Y/A+0QFEwrKNPnadc1LTgRMdkbI67oQ1BKEx+1gjUqknDoXFE3zVRpgqQTkP8IVijpQdI1kFZEUABrXz2aKY0/7PcXnBJF3mFNG4AWGHy5Mkuf7VtkdhQP7pCt89IGeRglllCmsSPhgUlkXsysUWbtZlKbJ2hkuTOtt+FGtBENvn/ap0XJEf5YY758oa+0YViK+AfhW5w9ImAtA0P/dHztsPm3Q+E9/bkYkComo6PiQcEbBFgRG/2z76A4Ao2IrqWtcDpzsUbXQ4u/y918qJKmHgDDNMyg1/Qf5bCzvx19mdT4BNAUE46tZ9WqRHRZcBzmsMCxi0MDC8JFrR8eGNOJFwjhfznvZnWS0YnV4aPqBh8x8Qz5HCPBz7/AISfGawoIa/wjxAPUt6scKMNBuO6ZPE+bPEkYi9kKKTMCE8oEw36axa7EZ7YjzAjCy9g/G/6TvlqzhktYN3so/+O+y3piw8WGYhhqcAc68Am7A5fSfApJy1X5F6ZkDxeJ6pRzDS8xyBnJ8Z/WUxOUx3CiumsOjGswzMzYfP4K5o3fg8ffffc/c6bcfWMYtuc/HcXHCy0OkxyQMXVWiUxq30wp1unElyqF3elbK/yw/y3vLQQ705e8lM0BYQRoUz4e/R+7bxb8V2NJroz12jXSNF67f9ujvKgNj4l1fW4EVxni4EvJNipQsrCFgXgAjQjRqTwh/cjlXyQM2SygY0pR3xSId7iETVqRKgvRA44cq6QF2elr8wMLy3zBLfhMGTojwSIw7ArZ8KzaVq6El1xYosyyvks+De8eYJlq5fmBRfOcDmjOxGOiD096BL0rE+1b/3uh3FdCsRFJM5rieRySKKdevWN5/VfF9hCi9Frr9r5aD0D5EuDJvN2c0FmtI+Vt6Uz/tawud5R7p+YDJzl/i0vhg/e5yDVReao9T19/QM3v/jAqeAex0xXcg7L4+av/sKBPfWfhNZ5kt/LoCnCk/uzI0TXNC9b5H7A3FEemUVCDh5Haz1HcM3iYkj3RlcNa2VeaVFk/S3yV7vcTZ6ZW/CJcu9nfmLuofKAcnq99C4qGu39mSiJKiDPVkgU4uZklKALiSewwzL99mP/3ErNgxxdqJ97v3S+6Lnqe44jYUX10VcQBQ/PRjHiLFwkIuwpvYHBCNFtjxr3mo23thkWwIMIeCjr7vF2O0uRDIQmol5gCgskl3CHQKUCG0p2cRsJ2eemWiWD5FObdvdV4JLnQV5r2joWPmPZ4fnmVMKOjaRwCgjR5E6iT97NJ+oY14pDPUu6eLUJdI8mvPmptTXGpUdhUwztDwoSTr5iFnGBCPGoW5pIiSH2ktWISaIFWkFKPj8HZ6n9UTUXwtK4sXL3fy6CgMUkOv5l6qMmGiJGEAjRhlz5i5gXkCtSbhzqGhxmtBKRN2YExTlfkCo8+SSxxQhShUyKiK1M4A9yYeZbExZJUdviQ8ee8tFKskipnSC3qzaBDRdfnT0eYZ+/2M/W6HuYuHmth8mPJeDBfcbKjpfDIr7+MmrLCc6GFEI4BsObapAPs2gzuw388e9QHMKJPkbp1n8XIvVTz95tkyzaX9QMpnGf+QXafSHgiY8C9VoWcqyIRJDO+ZS4LOq0fI0QOusIq6XwcmiBzfm7i2c0frjNrFYKM0zelZMz0k76/xjqa0oGQEUnpBL3BDhhhPzH5hyWdeuCT3HDL5AZhIctOnqWJm2TIWxYBMqTIqOKyuQdDlbynO1v4bnIrxGuI9JleucN679gmyAZy8Zx7ZgUfzGituIF04UyKR8fjOvCvO7epQbDyOKbfg8g3jd0JYxYDbZxjvPypgMuhZeHNLCcBdhHDu6a/bggJ4lR/J4rGgx9YF6RvnW9bg8F1bMBuVJW3AUuCbhZPDXwKIT3V5nz3SACkuIkQ/nFNKguX++CQwopFPTGjVXZAq7ZvHd7m4EO9JrYGfGA1PqOfnaI+PQK3gJ9vzocxxhYhCgYUpbRnPaZ20mUSJsZsDzswTXwWvRsM7izKqcwNvKsiCxHYGa95oUggxsOpUsFGdYpewBNhpG9mwILgodlAwRcip8iW2fqdIAnu2rxgV5wAY8xDcfO3vP1ve0ypDIlclFtP33SUoCV2hUbdc/ZnwiczH0xGr1DWleVxfHD6l+FEgHr0goH3ZH75WJLdmrsHhyPG6KDZtfc3T1M4bYsxmAzVckszelb513ZRGi42fcS5J0xC40apOhlxWtDbDDYghxm5A7MeNGsvVWsBcsJ9lj0ybDdj4ASLs93sQgM3mBL2LUR2YwRMQgrI9qJ3KaPgZEkfgCYwnbC5vsP+6B7PBrXxTmIfls/k79fAFgY9Hij0um2GkvrhP6U26IScgRTfgVApKqTIvBOxn4aEk/zZhzrmwGWrQCcktD8a0ORE8ojw0KS1iKK1RHk1uSy5h0roDrwMn00bpVxg1hPbFIn2FzMjxqHm623mHMw1GYlOsXr2ythZzafxEIaPqNPDazAyokr9qnvJaqyu2bA+ofR2oVkwpqlcHaVjzgmmSKE2wHOdmNKj8qkSrqeDCaiCn/Isf6QnggsIdMwNgwjel6Y/aXzewyqPkANm894Zi62P7eQA+CpA3LoSkL27OZHJBtvUP+WGnVFfiAcQMRHnm5aYg48X0jKD3ihtYxJxQUTxDgJKjqCpWSf5vvGyqJN15O15/4cUrlgibbylLuZVx6tfaCGkMyRjvyMmHAvkOT3/GfYsLYzLJ6VPBRL9i/8cOHRLu3cwzNr9M6H/sEWYXABFj/rOpEYftxGxGIdfZK/4GlOSMeVbzCI5dxzdB2TUiJ5Z+vGEYaddfFN9fshonlS067nAuIcDw2BvOe/coBefspoc4Y8bjYh0MpsEJhhxeEuCk/sa78ZwyqPk+NOqfOKS0v6TtPO8Lj/ToitfvOc8XM2tf3TCjYCt7qBPqJ2HgqBZMn4D5T8k/1yARLq61rYJr2Z90h3YHzESStrQzqva3wLPXBT3WcWS5c8DsYT+ha83penQeGdBR2CmkSXwJwmLPBFzy2sv6N+iq4vHceUJeMP2TcIyvsZ2fHFRWlb985D4wnjXWCi8G3ixSMIXxm/RfPMotIu22A5tPH7H/Q3j81jue/vjz/2fvTdfbyHV14RdkyXbSSRwna58/5/5v7Rv26sSZOrGlInF+YGRVSZYTp3vt8xj9dCypqlgcQADEiFt9IAfnETRw8QzDte2b4RyQv2+Nz88Kx+fBDq1jdsyzqfUzPAMAYHoIZR4iIo+5f+v7w1vo74TH9v4xGy7f+5816oBlv059D7YltGhrTEHIhBCaEFFQqINT+mJJl9U9ks0iiYiB0jXiJVuloMKfy0HC0r4UCHNn1nqGhLfM+EyEg0rzlkb8Wh/7MvR5wfk2r22MlELgeOj+c2aZsYiB5/X9m+0s5cwjPfpKwtQMLBL9HHhKNnNOPfRfbfMbrWtE2fflfT/Tt7+O3UOSUvEPzjthfOZ3U4JltMte/0r6v6Xp0qW1+J6iAwHWNLn6BPNCBuLxWf0q9YdP7asAglSt7g8h8n8orHr9wGbPYr0IxeorzpFGa3MW0sRnemBGpNXt+WBmv9ji+6nhVEcJ5tHvIrgaecy4bRE8buxf5hxdQYzVvskHzn/kih8wwmBhz7Bd50PozDZfOQHIjh5rWM7d+i7yu4L1sBu2xAgImNIp+IIqXnVH+prrc70z6MBiHPQ2LUpzeURkd7TIhq9Q8MVJJ8x1meCQH74I4372TkOjUNFcrRFKB4pZYE2xyD1SYHYGl0nTKHY9xJfkuGej6Jg7UA9i2kDpaFxRW0MpVcZVRPlZa0WvYkztvWG36xKdzOKowNQjalEN4txFmuhiRZcIfCRlieK0T61a9wnwyH8zZLNGMxM1MBV0dPTZIslnzK1hVuV6UacO9trgsp6NGcTdjQBSf1x+M6s2q0HDahqzhs4UQmLQpmREOE6Q/krpHmKY70Te7Mud3pO2MTyydQ9nOqOHaA4b7QIvHcEWH0clA5O1reo4s4WwRv1pevQOyRwwt+IHY8vWIAaMqPtujgfZ4Ups56JU7aWBWh55jC9S3Otag5PRN8bBaV/pZMl4OKirkTtePOvKXdCgfKbxJn+P8YIh/DQp7GncSMHDnYTGXPCwAqZszvwjpb11w4Cq/62GNqlziUX7+sMFVLobKT0PzZLdU8ix5kzBdnYwPE6ZNRiSbcpMXUtFiG2HTL82wfbFg3R9G+zJ5f0+PL2YMw8RAXRJ4LtLdNx7Xze6NnwmXIlTFodjnNACWnck8cbMYjv/AEBu4ONF3xxTKCuWgzd4pgSYo5jiR+mgywnsJSHkSXFSUn6h9E/Kh7DS+8S7JvV8mefESzJGsv9biLVeu81pfObFWLQnSca0NbdsYzz8mtX2/wRc4rwo9GPgjtUJ8hIfl24CjbbuudRdn2mL3PsSjO+gZDgvr1QCyI4wiAi3vF3zexyNFyxjfKM1GfRre/9yyJjZa2BjdIZvDGP5GduWs5mfXrerUqs7nWTIEX5Uinq/pTEo/aOCyBSnsgfTLs3bpdN+9rf+GDB3yWK2R/Iwlp/CF7n+UozngBszrdIDAypnjbzKyl30L5rJ47qsJA+Gyh6kjrAMeA5DzvOsOAeoIVxlAWTzio7Bzh5Emh4+6KPhjOMVJdnXri0nRq+doesPI4Py0KLZTwgih0CvmeL+olaUUqX8GUUbHjyihvJaqu+zTgTuxTMj1WrZmGS+29wwW41a9tNR9FHHToVQ3hDaJ93Hsgy6342pLSZioDBHZyH9NWFEvh3VkyBklPwWaF9EFuRNPF+fj22/jgxzSYOOj2OxG2xdYigb928++WTwFPqxtaFcYMkzLPp3KbPELMqT88eO6b3wCok8Bzo+oeBt0AjbvwDmD23YREGNsXrL+L7t6w/DsoWH2jr9XTJkwLMTgDu+kziyie6Uh2yeI2WijRaBNcZscfWtZ5Z7YOvzOH7z83jMqHnjuoFQ4UFzhf6JQTeaCeYtoX3+hFuVwK7tGQ3OUQnTM1IUYKVDX8rMD8k0GUJ3e4wr/jo8fr9v9OWfEUFPQjgHYzxbpY+vjW+SZPJ98e6dlBN8v8P+zz0O+OzG8wxe+3xgqOFETbQ+zzlHOWoMP/LzOUz7GZ7hF2D6pzvwDP8U/BxxiQPwMVHsxOvSIQFUUCTnBwA5cFU9PAAA9TAgiWJYDAW1qELUDhmpT/b5CwHXJN5RbyAR5wSJRH+nRHXWA0KuybE9L8txHZ+3bSP6uU+P8FX/vgU0EdLxZ/MB8RTPIJjnVzgRmNAslbairo2lts/3AU9v7Lb2jqWP/9n2MoixnAaDuEWav+ax1nu+Z7s7q+Pao6DiFaD11V9y4O2pw+XPgNU+vFsdBAQOiqhWi3yvtfx2mi5OQD3YbRcyYMm3rCYNCOLxXuywEBD4KHu4kqY0NSUG1tTD4lWq50Y4DWHkMG1HNuqfcyD5VVi36XvV06TaXLDTLNGnWPrZiLSXA1r3aETzu18f6OJdDGgKQDshjcIpQIm8xTXz7gdbOkP9npTeYhxSow+bF6q+a7DA63qaMU8VY15UONH53EOqdtBj04C5gTN3ZZDj9XfOY+NQEIw9Wozbh5YO8xcE8Gy9AAAUukQ+/roCq2cVAzDf3YMIuHj1B+yEKudr4WPzXjB6uroE4yD92zPKZQXvZZwEQi8HTOVKjNa9gQsDfQZTdUNg7n6tEyyNtEVxeH1P7Wt1BzUCSlY2s94PwVHL7QzDUZ1XH2lDKRMsOqOQeptD26NIX2msunMD9eKK4kKCo5GyTHCBO6MRgw8MLgXUGa10UGlqLCVUjXDaTR3gHViVkZOmLG/ctD56U+cFG4/UKLWUnFYbXdAlaFAtYcilKvW1LQNELRWlShR6bx2FClpp4Jkj+vxwwOGw17TPqb4YQr5RFJUoIWpwDfSAk3A+7mmzdQ09hl1DA2Q70kCDoXia5bNCBV1Djkz3YzA4TmQnFo9eo2iT7NksaZ0AouEuf29B5EEERMHsGRykxi0X9n50S7/fCdQIfZog5UCkHI/PaW9RR3fog+I6F5TKaB2hTaLAcp8LXR8qRdIMFh0vidMnQdNKJ/rBbO4y+jtRMD9X6FufbO/ZhKa/Scgzg4ITlMjenmdzXImE02aE9tT1ZPsd1tNBVlyazUivk/EFSNRoTyUjMuvN2UiyY+tKeiaAu/Ga6Ivd29UZyaIO5W8HUxlk4Gh3NBDY/l7eOBpKxk+nYCbJ/FHTzLvDhRNNoPKl8ux7MPbo9+NmW/bb1m168cK/W1YXcQqQyA/jbfZwG/Bb8G2aKloPh+P68gVm9XLx8gzORyXa0xOPUiRyBXIEL4HKBBQ1QrPtlzyiUIVC+RYAoMlsVX2glgIuBfPh4I+ytkmQSM1ZMx80pQMVDOrdFRQHnbkdaGX46hCDtGS7EDx9ATW44SVkd/7Qnv7wsR83ZJ+HG4+58wo+dNyduvGIyPpS98cPwiq67cEOEvB9QYgv2PpFKzzNUp3AdxT84d+k5nmKFeQwF3DCMwDoUpUd0x8SA2kR3NNUo3+QiCV0o4sUE6v7uVZ1rKh1iC7tgGY5CnygJO/KbipoUHkiNLUAOMmjTs1S/+OcI/3WSHQlnnZmBhXcH/b6s7YzawRea0ALp7pSCK0FT611Anepr07MoEt9/k73zotXAORcNtML3Ts/Ng165P8EJFa3uj/fbn8t00bIwbLu/es3GR8D5c0faI3c2BvvDdmzf25g/AXCH9EaCX0vBFxcXKIDaJpJqXOTLDNePzdcHjKfOcwziIAd7WCZAcwhK2ioLhFHZLuVxhnnhp0/eqQ1dZep8hwlEqrzIt8lMw1EtmaZQTsjOS9n45HmnCaOANNuh4kKSq0iZxBJeSTbgSTyZy1VxFMCuIvzZp0qLi8uJNJfcaj3hnve+1gZkl6/Jm+HQhLB7mNh6A4pKLBMS+E8SoZAiSJs0Tx3BInJTe0DL7voOGyX2traTS6rKPi+NBnKPMHCU0/fuxFD7c5jyXUuRDFZv5L4GQFVM1EkSU7nC/E9fcq8f7yy/ow8Nic/NP5+aoPy8OEngF23Zi281r9fKeqPE0IHd+30M3hsdty6+Nekf3cAAXf/3qvx+BP6R6DgBgUStc34BMJbTDcT2kcesMnas7xQ1j/Tyb1OVtSspzsb6PS65PsyLDN0HvBZcTRy17xkMaDIWAQjvi3m2VwJLBFHyNyPWMslTc9/W1fZPmXcoUAZw9MOYJltKTd2vDeMMQOF6Gplx3VM7ycV/xh0o4Evlo0kqfB2/RrlhtA+djB/lmeI8aYLbn6CBXQJfhSWMmBfFvN1JJxklTnl67AO69EN4hAvfj9zaaxHW4+4k/jQ32UQy/FWV79m/nPGPlg7p5wHRocdx7KOAEm+YbGngIEdX+s5mTG3Gf9Nn4c2/8Vv8SdJrHoB8KmkYfDY03DihjuRYXF9DUrLyRw602SR8bJjzz7DM/w8PBvQn+HRsBXxcW4qDDvklELofZHskQFLgctaq9wP6qawP9ruWgIdDdrZYzk6c77hNguwW8Lsrwi4fx+YwXgr4twE2p7u+ztHNdak/3V4xVD1zXEoGHEgR6sTZB6yYLwFSyN8hpdp8ujI779jfsdEfyeAR2HLUioXjQ4Mb/3hEVUcya6rtYrRb9h7mo6Xga7CpNfV4f8Ze+XXIE3aqUWgI58x6AlOglO+rPcZDt4IYniUjKW3LZaGIcZXJvtrj4/CtSvr7FBmp5GMP8lz1Qz+ZvBc/vU+pT66cV3/s5TQ7NUQN4fwAKTjPIWChPj4gWdLQUIlFLeu5B0cBxh9r9/vUwtKdFlTJBfWqG5IxJ6lqTeVoiu3iqTI74AbqWWdCaVKak0ro9DVaNXViir1KK1MQPcx5PHkDnJv6KWietS2qN2gRnAmK61SYCGlXfGFmiivOTFkT8vImnjaDUASeciqSK1E6DVSoYIIO5rQaPbxWk3D3iy6Ozh9RxfDX9Pa2l0jo3r3iHiqk6aIl/koasgCSapYAkkkN1jGpbXKZ61jftgfcJhnqYEONcibATk5JzgeNAbVlD5sebAzo6csmCuq4xJr1s6YQ5mHPijiuu+NQLMlzlqj7HtLcd+XOZxmDG+aoPJJOEHWgHQw9iwIitesJUKylog7o6OhAeBe0fuEiDoXA7vNiw8izS2R1IOWaDR9r45HUCCMtoKDJHWaa4HVubXI9zBsx+BcEU+WPnlMEXkyjdzm3C0k1dVcb3AGHqO3hdx0/03KPxRXGIuSLRQNrEYEoS0lFA5kEmHQXizGxlxQSgezyQFQPfeI+xjk8ZARjoGvx2KeOKVr74vnt+jy9vXzOcRooo/fgKV8fA/bGqdap42/nq7dHWDgdD/3OBTvyjbuOtpLfScBdHnlmRiELnaRt0rsN+4M1pAfq6ELo4eQtfMIIwIudpPiV9faz2kemL3mPTVzoGhAIfRSMBVzmATqJO2gVoQDjBjKSdO7m0FyUPxC8zdwRKeCCHstJdEhKaONRl4g744kkw7rd55s9dTAeFwE+uVCTPgVuExtSLMvYSek4BEvha/jL5AmfjejmkSdx/OUH8xKy0cArz7o10TGbX8YrnFePZbzhb26okQKZpjBNgzh7piTpEUrTUQ+IPK/QmtMoUv+WcqnCH0UZ1HKZWrdAJ95rzk6TtMOfNjr+HQPlrGW7u7lJI4uvWs0N0OcmRvI3aMBOemdpoHH4NhyGcW31hjfhzb7FzGMlzfGR4Ie2dg7/vK26A2taHluz+iD8WaTBZdyS3wPp9nVSExwUdlFfiKhKdwHnkMqJDHYDYXNe7GcJ/k34ujJfxGaJThQnG7b/mDtk2RSsvTztVTspp2kwLcU7izZPFymU1wtKoMVKp6OfZomXOx22E071KmqTNucTnNncO+aSr/4OpVeUPvGvOX5Tc4IAGkmqQXYuPTzcPb0c5sLlBogkOXNWKKVDMAis/l7FLoa+CnN/qpn6bxFyDiZ7x+59noGNiBIwvrWY82dhDMfeHS7jwMLkFkOYflaWvyfobXuqbqrP8/qkhFttY8PFYo8DY/NVukkItD0l3gUIUI6XnB8rvwGjb6cWKolsvw8GA3N289+z++wTGaht+NR+N7q2sa7tuRzc6SoN1F6ytppH00m+wxCwWuWNMf1XUH70NA03T/hMwii7zX9qzlzWLdOof42BXsYfvN2WsA/IWECW2emRzw8ZnJyXomBpH8C4003BxKRT1pr+P8+3a6aNOP5ewY+pLiBU9vR5T+M5+eHxjWc658N5s/wm+HZgP4MTwYnCRYnJQ/n+yOyjkBeJ8qMb1T1qMuhxrJDBesBl/XHAiG8DOCz1oX6qiejN8yYGJio4L+p4zUTvoLdE5Oo+KF36HZiJqcJsvYtC2tPAAypX/7poRvt/qR4yLB0Etg6RmRh1wzC9txbBt7zG3ykMeH9uXDKyLzVv6eAbyqclRNt50h7E+ByzThAvo8pgYBXKpkeF+hDxMueu4xvfuU7RU35U/CS5eDewLg78r6XC2PfsfuWYIfkSoxaKwasUEVA12ioHHnadT9WU3ZSSfVKo20iqctbi9Z9U8MUt6j+i2F+8i8WQXhc8A1Bi4fvQ0T174AHDmOx+uzKcCAUgl0ja0odowG6HnQkFSRrtACv3rXyCPXukLeV1Qs+DTl8Z3m4HI4tcVQeXk32XU5notRIArtqUkwhaUrtoI/SgNUDc8aQ/tKq32OpAU4DYhLj+RBRjvFQJzdK9Btd7ADMYDVk23dgQjZciQKvo15eelSM9T8iSQi4BIguwF0MtaY8k1b2UaeY98NCrOoKmiIWQKcC6h1cK0ondG4oVTND+DrJc1QAahplWDTeqgClTJimqgcK4ZPzLM7hzBIJVQo5buZoHFOGceK5woObetIXlAKslVcSSSb1H4tEoRfB5d5mADUMpsZrKS8TiQNBA0BdjDC1al3kZBzUJ1qXOuncOw5t1ghZi9zk8MRnMwhrRA0z0NlTQEMVmqUQaJpgBSh775KWTA2npMtHLBHPh3nGPM9ofUZvTSPJZmCqIM0cAIJEWada1B0dhRlQxb0XnMsHV8dz+FxFtXRIWvakLLT942vo32NPmFDgymlKk+8lAEw5Se7oSCAZAyHWT1fCqdcRWkirDyN0VWoPamulS3YYduMijBJEe8ysEejdcVdb9puMD5nHRNo9MtMqNHaN2mVAHEEagCpm5aKGeEl3rvNLGOipZ++g4k5jA50zhIgHYg0y2cZoTMlTuCXfESJ9PQPDPh72DCvOq4KFqEjN99KF5nBHR0HtXUPsEtXtQR/8vYnXsym9fTzsuGU8jTnKBeSST846lK6O87LkbyNZL5jAmKXmcqKNea5WD52A9W2sPGbjXg4qzmoS5XTNx7TxrKgeL1VBZCUKAHMOMKNPIhw+rng/QFfkTlGGR713wdfLK9zf3wkvNOeRorxLWUZEtqgTS5VKlH1uknvIDlRqkJjqhLkffLIKq6zMaki3XMCsNCwvAiN9192sxqXdxQUYGokMzaihg50mcZiZDwfMquBbmtcqd09PDBAKjXW6ia5kXHy3mse/E45Fnx8zqt+TGNG//2KHw3j+Umf+L0hkuUQ4l1eCke2bRlrjJeTsQiA3nIc8OH/VSPLXNc0zuexg8tLFq7cAUqS33nr/+ZBaBKZXE0CaYYEZRXmLGB3JyWzzdOHy/Y8/pP8/fnxXXOpABy52O3SGywO9z8r2pbzLrlaniwTGxcWV4Ni8B8AoVNH6nAy+kQvK5NqqGXIAACAASURBVHNmOdsAsp+j9qjSXjAmrXctTkzA3CXiereTIlp7NaSb817X8dc6Kc/t4CZR1/RS+I9B/4tBpNXtfV+FQd3IZxYZH0KjpVN9X7igR4aBv9C/BE5lV3VSHPNnvshMz2BcvhOV42GvEfs6nFImMHdxctSxSPD4SP8jyswGmOgLiSwIMvpBqDVO30RAa3OSm0w3wL6+7qQTUxbvRsgplPaCZ/8i8vUZ+LM7SRStGS9p2adasdM07jKnxv0ZPGv16tbBNItMUULGIwjOmSFeHJJ26E2MGfN8QAdjKlWcT3VE3Ltns+HVAGMcbsRmk/PG+TC5Wjs+XufYJy76LOY0zvWSbSDEOvI1zU4u5qBiPM7aMbmnqHNg42ZdGMDeZ84ZllmoKN9tmkkh5BPdCTXVKiD4BhkiyE/IFjnynPty0vON3tHt9p5Yj5F1cabzIkTkuU11zrdGAC7f/wsAsP9TSqF13GLWewuAy5sbgAj9Y0e5IdTbG3R0XPzXDod/H/xcY9P5iaIP+b2+vvj5rJfeziiCDH83NzvgmUr+0nV+wZL55RUDVyxyXYMcEQp9QcOxpVMc1nZaN9p2bFDb6zz0O9Eoiu2yQCEdvU4A57Ge+VZODrgGb52PXAMA9n/OmN5Jdqj9x4/elvGJiQm7mxscPn6UWvI3NwCA/lH69lrpTugZsmNbBvK2Mywjz48BpecH3rR4fvn95+FnWziCkMuOPwBLveegn1u37mC8d6U3TfTOHB6+EPBfLFkm/voz9vLRPsGyDGjq/g3bSt5Dg25T5aOlc8DyM+WNAeXZlNrf2He/TUf8DP/Xw7MB/Rl+HVy5bIfkJFw6BGGOGpijEg4syiSgi4LJqCkZ4WT/no9Vxn7tUKHxMgCE4d9CiP2NGjduUHBLHW809ds15DD1jU5HxDxuTnCcSz0CHsk3zwZr04zGJgCb0Lll8O748qAh/NT73nAIPMeE4p9t/9R781JsebG+0gPeK333tf59yLh9qpvHIs8NTCH2EJq8UIFD1uf03QzgnhhXfP4E5ki53jtqqem4rMK+RveYwcqVn3lkXhg3RyjL/7VWj9LwfVpEYd/+JwsvpzanH/SHJO5+6aw2znkNm6zIyxVBrO7PzPG6v66rcgVG+tf7EXTflIj2jLeWD7RWd9gF+7g+GkGjV/HvDOJp6GPuzzbM/ol2IxfJw+b9Xvja5eUws8MhlRn9HgD2qC8uQXRAuwMIO/AlodAFOlRButyTyRJmY2+YMfFODIKFpX5mUf7G7MYO+9+eJ3eyKLq3RGm221VR6BF5el1L++68lxCGNmavZxnKRApDeif0IhGN3AkgTSxu2QlAKFzARZWgLIkxUQqIJzStbV6KpHqTFNk290kxqshCgCpESfHLFF6ikAQBjUXp1TqjzU2U3lrTuauimwBJhW70iQODREkvitZaq0SqKT50VcZGDUoZZ2dVxLeO1pq8W9NbV+pojVCrSCPWb6RDnMxzAYqlIu++V5ZGyjDEqXE47S1XUNqe0WcHx6RjLCMrPQmKJ7EXhrkmO4TGWGIXWHvj1/X74mOOQiNAsy/kDR5ypEfllqL4Tb4WG0NyZwOTCwdN9hlgbRB3oIYDl0AB1Q7qBHipg6WTiX8CEJG0MqBEZ5Yv9TmJ1OUDLAWZ1cW0nraXk0GdARTiUFYzwxJU9g4ULRIgTjWC49X7EO3FlOo73esinHEylXbDvdc3X3adIhMEADca+5xsr3WMG47Lq+lS+vCrcjjzGo9ORs7nfiyes9kpV1eC8/m6pxkWvDud8FH5Zk97nCBKzzuAXkIYttETUrmsCynMqXFFSR5rLR0sTossS4jNc50m8OHgI6U0xx1Cs+UcxuBiDtKyNwaHZJkg1IsL39NVHR/n1sCt4TC3mH8S8xS7UCAlHia2RKkyQFv7LCvIp7vV+vynwLGI9Msn6mxwVuO2f8DcP+wa+/UkF1mt80V7g3FraOXI9wcOOqzygPHoDqAONG9ND4e9ReMbs59oyBeC58Hjg8wYSTOZp3MzDqJ7MXq6nDHfB4vBElKGDH2RGQit61buxXi57QnZLBGBTp2xm3aY28FpaPlDecZfy9Ug/ZdXvZXf/wBrGbEJb1DeEOYvM7r+hlVLy5FmeDn8blkL7D1WO31sTVqUcZusN8oszFtPbfGBJV2Otn0uFzQnOwlEAaRxrnLLtPw/KftDFCrqZBcyXoxHMLAk43mdqsqb1Wle70gOV+GEMbcuWRS4+MyJs63Qy6lUMApQxVG1twYCoxFht6uYpio0szOmrg6H5sCe9hER8LITvsLWw6iBSyVpon0Fl5O/4sdLnLHt7DjjuK9ylVHuLAfD9ubylfFOE4GHdbEfjtGnE+Lh6ASR+q5TcYyk/TLJfoBWngOm0/r8wH3HIn435Sn9//ChoeOTZIRK101XxnoGmW8/ehp3ov+F3X/tMP872jxniE9ZMtLZyBO0aWVUrLTKqSa3NDO/CszhxGWKmfEIFXp268PJ9o68I4MZzwuuMb2r6B87pncFnYHD7Uefh07iWFkAXLy7wXwrWakK3oozfWr3K4le2PS+OQr9n4QnQpP/6+BNWpsbBnbvK/6fjw8/d8OheTPj+UO0c0WDlmcpOkLDjQ8fu/8ZnuGJ4NmA/gy/BC7r0RkigiriJerIDhZ+vBV6VxjEBR3NBWaCRlXAjIikRFLSBxEZs7coIe2UGieu9WsnwsyEzyQRct8IeN07vlB4nq5Ob9H55YgfmpEnga+QekWvteWfi/9eg3mLvWX5/JblYPklCTBZkPlEY6pzwuPqlp9731MazwFZCfMO3YJsJLdIc4Z64rIIg1vPHquT7u3lA1f6a56+Vv/cDvMv1MD2Y1Gn6Aflp+PjUhb4np77QRsCe0bfBE2jxqXOJY+CtjmtAJqauYdRU08jTT21a6nopPWRofUwiSQ9HRiHQ0NnRvV9e0xEzTPGiFqLkcI4j8OVHEkJEPTgEXBkfh4LRodEF2ARVhgVBqa0oIh6KBSuGqLrkLtD1Tcaw31eKA6GWU+QnZkkgnQxTmwf7HjxzSi0DaOzpE23yFRTrQQ+cvo/6Gqt4UEKo/WAe/obPo3zmHWnYySlq8ep6bMaybAxCgDgw/hbNp4LWETUBGagaMgWacReKGruARA6LkAglKtLfV8B+BLMd2DsQfcXyoJ2IDqA9x3ZHMc2Z/5DR6c9+q6ids2s0gG2hesNnQiwaMW8vskgWbWm4jRpBDqJ8bc3oTyFNErb8Cg5xPQu6cl7b8qji/rFBF0gljrSbPUSS5WTe5NobakNQrioBaSRNUQAVUFUe7cYOIIGuBGnkLYNT2fZATQwqvYFDIn4V3zobUZrMxo39M5uDKxTTfRDcbmIkd8U9aUWFFJFZp1kDLqcpUv6SxlmpNnUmRjojKwDhxxkzgmlKB3QOu1u3OzgHt+tnrdHk+uaWA1qqKKEQRHJ0kMVLE91318rckZpb7DcK2MojkOUCEj+LRtG3YiaUzwQMLItpQpKAzOziqdUJdtkXKT3W/8LiVPDVCVSq9bqimdT7K71tym+pesaWJ/BTmO8Rv3CcA1O6etY2+sMz2kNQOo2JzqlBuBEnUwglnFlhfqS9rLsC9vPNqWdLU1jMjjbGlBOpz4qBbb95oI2GO9GD7mmsFhUBZW6v6d0oBGva+2mafff0ocx4irWRfA7RdazzJ0OAkTqwEkFqCVlAygacbwVWcbomIdsQRXDNDv+phXbmqQVTKmflF68VPtkjkMaUQ7ceyrgsiHmmHxY1MpL+rmrw5HPL7OMpxCsOoNlOPHMLmT1LWNo5crKDJAuwrj/0IVCEBFmG1c2fpQi+0ZqJmDG3vfbNKWMYXnvkJToKCCAiwTucZ43grNumwczitNgPgMRYVdJeZ/yB+UbvYnT0awMdAfB+93VSykfwADfRV4AMZqv1/xef73U7yfrkm/AeVgU8Fix8krxrtPDGaqWYGOy88XWu2V5iqdlb9+aSpmRpNpbIaB9HZN6u5lPJ6J/k/25u1aHRj9PQ1tNndqA9k3ST+9eXwz3eT4i3cNTKcP1/f7OjQmARHabnBpZSbr3G9C9ptlqLneXICLc7e9gRy3D58G5H7JnWOsV1EnGaRGtxkeC3si7qv7eOe0xEA6Hg88NQfacZzBixn4+uIxYSNJXowNWXoPTvqU/4mzA3yz6O1O874upZxT8gYKCq3cX6GCUtwWHT6/U+e6vNGoziH9P0lrwGs8mqPeVN2bkfeXyLgEiZ4FyC95n4qBnS5dfk5GN1uwuBD9YnUuNR/bWPeW9kBUxVrd5Fjm9VviEBpP23nT7aal0R2Q7DOe9PJnkGYq89I9PMzt9K6WgEqGWgqlUVKpSboAA240W8c0NauSWsXQNlY+zEmOmivmwx17PJ9YH061N06SZs5SGcshBMn8Mvu2B73quE/2ZyS2aiaZnWcslLF8l0qG6NwrGMjeU9q+XijeGxdHWYDBPfCOfDUPeGR3yrIAX6Vh1N+pJIPWFTIeozxneLfQMxqSXpbhc3jf51umg9Xfsf2YUwzkyJid9OIOrnHnbuZDlJU6fJ8iJuPp9b0EA9h8Onq6dEbyJIIbV+baDUHDAZ9X5iQm//fd/e9fHwp1reCyv/B2wNLYViM7u8uYdftyGxfA7RXT6Fiz57/HI89Owpc+Kc4J1OmS48e6FXm+r/e2X+se3Ko+QGs9rLTjgIyreo9+qc77eG8bzdxDJ/TMKgOldQfvYceBPuNVz7TVDS58wbuy8QMDtIBMGZHn7nO95BvJYySnEdvs/C0k78NMt/A44Ni/L30M/sd2Pz3rnWz2PfPvzw3Du3DJSW1aLL87++Sgds/eak+NyvxwzonsfTAFsek/CoCPze57hGZ4Ang3oz/DLEIeq9eEDGJk/d0lNVTQlqB0w4miVjlkqlA/RcaX6ddGRWuQLq7MpOW0mML4UwrVKwV8IeKuWoIimJLxhPjtF+u9icKfgK4A/fuObzXjOGI3mIhQHrIWS3wtPHY1+qr+F38iHnKL+J95th5Cy+J6v/yey76IK0IBQkC3lDTcSYzwUWhmEddRVAUwBjiSXJ0Pgf+7M/Bp4ZI1rGbIAzz7sY6MPNQINuLQ9U4/bkRHrEO2ZUXwcAZByvaYDNyuCRCNupFmMKMcwiFHLNWMrYT1HsOdUf/ajtNGyHmwx9NNaBjeeE5Aj0k89aaPhPUCXG9e5gfcx3o49Cl1A6mte6BrvESOKveWHBkxqbFLDJSnPq5lfyWeL+CYI32VVDBFJJLUYHyeQRk83ddaQdHuhuCpUpdZzZ5AarqE421oDlcFO62vSobo1boAZpFUJZ4ZeghgFOxOoSx10idQGqFRP0Wn4IsbIpDgj7RMTSu9SB5sLiBuoi3LMMmO03sFNjdGEwSGlKF3iItcrVXAROlWLjH8qE6ZaQVqzl4jQqcdBm8Q5qPWm+BupZEPJqkukijUii8AnFNZ3ar8ZXVOPqzF9OLTGO1dIaNtNo1VFDuq+nnnPbSsHBMO7R37BFbBF63PmtNMWfbpUDA6cwjdHXPBzstK9VdS5fXFctAGoMZU0zamuyzRNqHVK2QDWNIN1XTi9P4z/mqJ9CxYG/kiVz4t/LYJwfXfKWB6zZetlNM5ulE0LJkSabCoxDzYeZ5YMpPnZHkOakgeUE/JFVrUTUCSPO7gDvTCoNaBWlNbBJRZ2UNYtXjTibk80XB1z1ClHUsOGEVYRUPYIlK4xD6nBuZsz0fbQT00FsBAzfgIyHxpa9gGcVsSlTLj+uJWbGnmwKH7kWuAgq3MNbQzEnS+WQiYDKKz2c+Mveln35MA/EfNmfN3mvlMROsZAOxyswkXqg9Tm9X1USGg7JzzoTWW/7nPDRdT3zKwprE3hdXq9GFDDUmpLZVK6Z5QXE/i+PyAFCNyfcc9TwWPeYzTsnsSYfi7kOueEjIcvF9/lLf2b3Rt4TK8I/ZviTHqg6O/H5nWIXKd8D0eHHgCTE0MoXqv+M94WpR/CpwrSpegPEZhnLKGokTXmS7L1KIcczzKGX8Rr3HQkhN8TZbjj4iBb50UC+bvsr/XCHYMXBrrx5caTNVPZK0L/Zrzuu7eV54VQUC06nIGpVLTXFf3rep6Wwzwx+PSryTDj9yVW2Fqb8dfvTkLF4BydRrtsr+e0A+AFv8tOZ/K8s+RxZbx1Wnwf12y8x0qiZKeL/FstImtWmlTOiswcWfqQEobdnVmhMnAncf5kHQuBcH9vujISmX+qYKWJBQSoPGciR7PpWvAik1FMFpTzqj03EuQsGcXUssul48okOUi/D0ui//ns231pi3D6Ie8kWzk/O9kCLfppD+Uz5TGg1YfV1g7a5Ajx69xjdMlML95q+szXnduz2GXr56ZFG/VdxZyMpabV+UoSYWrtzbhdBcx8pdAzHuuHtfufDKUQLt/e4PsX0Rg/ti77U8GSX8hv6Xo+kODnDOiM2DcV15huatoDwOX791qKUM75ha/B+IyKa1SNUG/0BQXqgEGEhk9ghG7Xj0OcMqAGY3h4Hs677ex2/iPxb8mYfrvAevoF16xxEogSqKfg6uYGd7e3Y9dP0WHn9/F3aQQfvpPxYv3t2UD+DH8TPBvQn+GXYFDyZkO5XDQt0eLycEwOj2Go/zsR6rQDuqRI7b2Jap9ZU7un1GqqzOkcphZvWJ/5XAjvGXjLBCrAOwY+ar+/oYCJca2e5F+chS6rqzySa21JpL8AX3+9iQEserzp94KIPi8YGeNbDoHnWuUyq4FyLhy79ZSR/FeM55Yu/luRw9XrI4Ku/XaNLwC/8TGZI4Glcj8lJP/BwF/pekd4nlpVcQAgvAKnNHmMSOX+lqHJnrfhpR5m/6Knlp40ytM8rptESkr0qCpeWCIpONWCdkW/DtTSHVvkiZGFeRYMq1UMBK1ZxHpBIWBXJfLi0MZ0kgGjaBv6LDs40/bdK5rzc/CgYD1qZbBSFdk/Jgzqv51T9DcLLfPzvyt2JHKFADTSmDaSN7hnvR1AVPHeu0QyjDXgaT0RoYPQZpZ0ztbeOkReo5as3fR9VFRwos8m2i7mdGnMyuc9n9Ywu9shyxUqZL7xfb3GMwMTxefFuPnAYkRngEgjplTB6jUeUQDsYlbMcH95CTdyLNR5fLlHwQUAQt/fC2+72APYAYcCqXkbrjXy34yCHQhVrhwYbGnSWd/RO3qZlJ2KMq1qboJQLmW8Yz9IWBSxRceUMkaJQnkvSteIQDkkt7mjVvVyT5V+QeoZnBaKqXsdR4JkU9i3GbUXSU9JhH3ralC2yepoRFKsZZJ6pKWRK6qAMVIEAEizBvfW0acGMwBy16h5ya0OVFUgdMhnPeCbobhzR1X88QwDxJoqVQzbVAl97ugaaV96QysFpUhfmxqw61TAWsu8sEXCEdAbmKrOCIGo2zaSvaQKXYs8BxAGMkrbM9E3w0Ewe6R6d8Uw+XM+hQPNGYHS72RzQwQyI3oy6Ft0EHN3DccxehjsyeS+ka74T1vWUJb1sJT6E0n6UcmmMGlUlUXgp3dmuoSYw1DgcowBw6MIGhe9JJDzFWY4XojxV95BNlh1HuHOGm0/an88i5Luv4EnMEETtYDR1GkmraDNuUWmccybZYYJap3mc1k7W+dGjJTr/S9OXqxpXrs45PSOXopHhxiOrGbPskIgRVmy0eq4tzNHunEk/ORRGUIk/MvV6tpWRAhiBYXIS8EcF9NOCwIp/8tw90r6Z3snUuYBc+aNRNzVSkbYeHm9VqbwMfrc/KbAUp8vkt9dnIDMm9Qkb06P+o87EK5QXlBuxj90EIr1mxmF+nDd9iaxGnC03eAp4sBstFmixFWZa8bIQl6PPNi8OOJ046NmDYPWcAdr+QC9W+lP6y05YXRx2NK5r8wo9AK4DDmyXyldxJ3TOJuGjixjjyt7mX4nHE+pfhqLTsNx3Dx97x1JKncCcLeS/+POS05iKAAxmj+UPja3R6BX4shQX4/PlFeyQ+qb5PxijxNQ35gclfpl+J/2ra21vg3Ta3GiKFSEL8IMefB1zq+SqDtgqjVkUDUidHTMh4PIZxT4f+gHTBoxfjgctHviBjhrhDKD0dGwmy60s1VwjqVmtp8ntOfOD2HycKZj6ggCwVlGrEtVw6lHvkJw3SKr9/u980ECRaYJfXspxR2rrN0s/5ZXC0UzXgD4MaA7gbC7luhnKhUVwOFwj/61g4boc6AoHvSvua45oby2T0YvjSeGud7mBSQGeioFc4v5N1kg08NlBJ9lsqlUASI3kpdalH7JfM57WXcqJTlvxPlDDD3raGSbFLY+jdsh+qr6KdMyERV3aiD7z2QodYCgEvqsUsUhsBQxplMxfNEsBVzQS9cIdSlXg9L9/Jf/tyxE8/6AvQ5iqhPqLHXk0cVZUByvClqZQfrbfDigzQ39lgHVRfg6FDGev0QR45ZFo6dtbDg00A2VP4N1hdyV/gzPsModzltUf0cMnddAWAa7I4+Vfso9orQB2K8Y/mVNY+gL5tZ0XW0Pdsc1QPkXlKA6niw+a/sPE/aQY45cTd90XEsBxAb3CDiH33ymMS3zIg7f/874hP4RuPrXf2H+cIPyjtA/MjpuAQC3BNywxKduGdVeJeeWjtDtvdYXrHR9v8JoUxObTpe88Xlxn2WiepWwZ+I36HND/9TwiptkRiOlsEcne8TVYwM70o0Qy5z/JFxPCEWKt/nMNsh0Gac23rvZJ2a8Vjmr3mjOGjsXaRY0clnsDaZ3BYR3AGSf7dFx9f49fnz4AMYnzB/ljPGFGG8ZeGtnXQZe/utfAAF//fnhrHnKkGf3NZte2ijBKOcdl4WOrsCj4LSsld+25HNHiUN068yuuVMFh0DYnVct0V/mKTs8myyT4XUKQqwApnc3+P9vbx/sy1sG5ttbfFbC8qaPdoOtiPLBqfEsg7jQ5TijUvxsMtmzUf0ZfgM8G9Cf4dGQxVsDI1Q5FeAWS1j9psStgCL9bCKi8+GA3giNW6SFSx1wQpuOX3qERfZu9Wh1FFRiXDPwJTEPwto7knlrpOfAkk2dD2/wdGnaT8EXGlOw5zo0JlCbEfkTyWf7/pSsiBA12LeM1D/r4SnVPR/RD34Dpi+r+juvzlzGPxb3fSf5zQzpOSJ9KVLb7zsAP460/wTnieOwkB07s6fusn6GwVR/ta3ooRYY/2KkE36AtPMhaxJoEmWzGdD/58OCZrAc4hZ2FbmUDVE0RpgjfR6UAlZvehERbvSrrgnz2NhJ0nQcy7wPSSinZKga+qM3m0IlIs6XHYn+cLqW0+FFCmaLUmAwGggVmv95u8NzbjGDLAYfANoBEYG+RetnABdDvyNlHW3wjAsw9ih0GYZUAEQzGhgFlu5dI1OsxQs1bB3Y55K4ylg1IrNzR+nFI6fTMvg02tZcg+3dMNgQFI9IotWZCcwSUyCHrwbmAuLuhg2PjmJ5URneF5SNARRmdHQUVHkXS5JFM4QVMIgLUBl0EDzqFpWjytVmythD19TyopCutWKeCVQlYox7UxyS/2qvoqDzOtV5CV3d6e8CUgpRIvTWpZZ713IzhcBdDE+WZ9tqUBJJCvhaEcrTxYFNsmCSzJhoCGVtVwpGk1HkHX64dIOxpvFUfAjkplG3Jw0NtGXABkkdkLZg9Nkcb0jXyvZw77b3FnP6IKwVE1nJ4I5YLLKaGM8jXXudJux2O0zThN00Se1ObguFw0g5l4dyj2zjdd+X6LEVKc/c0RoknX6pEV2oe1CUwVLzOTc4sEPvovTFE9a6tp90m5qQpUUNTJGrf1axSkaL84BozCIAU6hQ4Hw2VMLkdjeEM9DVoUYFKVFsVKUTXVOb5vk0JwtOhvRwWoDWQBfyy2JkhRkSrLwE+Z6tUkFb0JTMzfMn4VcEVl+8xc+2TLntpTLI0k3nrAgAwlybfmWNAu2Bq9ZmpgNmyPZXEWMq1enXdPUC810H/wDoheLAwPvNAMH+Pb9PylAUMSh0lhT/7lXG6H3WrARK7d3SCcDqnZei9IXRW/N3Z9lBjOJdDYLZYcckncAn1nfnz2AGlwJuarozo2kBmI8ozebj0bX3i1V5arDdeAk+apwf7w98+Zk66JZSe0BPxNjKK8m0YpHmw7O09QTWPGb5go1Hjl1wKut4blf0DM9Lp0vDz9xPY2BmfONVHxs3fyYboyU7gl4HxlB7iBK5FEI78AqN5PkteXFr2GNGibNgOUajtYoVwnOSsXdk/LIVPYsAQdKwM0jTsAPwclq9zyHXrbmLN+/kJjlWLHFr/VdkbdfM9L6QWzfMDU72Fu95aKoJPoYlAlL6Z8uY65eXg9e+2vjlcwlFvWaKyjcRhROipW73vxZ5TkXKERLcwE6FQL2AqaCWgl4Ipcf8xNi0M12dRRjg1jFXcTD0vunZktUhlDukzNFhRmsN6AWsIZ8ifii9ZOBHIZVtyOWJwQNMJ4cHuQXJkH3s3vQdC6lNeVFo8EIWiW/k/M8OmZGZwfiYyXH2KrmySp1Nwx/AMWfYfE5PeOv63wU/yZC+HqXFa7DgmXOoWrkhpOkGEDrDY5LasTZ/B69dveCJlqzTFwBvMb2t6B9FLDpuOP8tXVAYF3aQm/S8sOnYscXHjrzhtbLmwqzR43b3Yn8wY3pfkbctQxwed//a4fBhRsU1ZvoMMHn96yj9AUw3Nyofnj8Dw/ls845/YJ+eAb8d39ObtvBuQ9o7u8UvJJkmKq5x//H2rEcrgA963/GSr9HTZZT58rfN78PnJAAudDEPOis8wzM8Ep4N6M/wy7BF9IB0aOTlvSUcO1mEexbtNCoBtVZMdRJlKhW0ueLAe/TWNIK1g1ijYSkEZmJgThEPgByCGcCnLqLvO5YojCsAXxCKra9mJGgqOfiBixd9fwjsoP9zxPrUhnyNp41EXzIz2vi94HG1zn+1D0v4lpgv4byUMfm5a5bocPNwNYP40ig/k+Qe+Jmod4s+f53Q/Y8kIP5FSeT/hgAAIABJREFU8l5Sj28zqtt9BODLA5HlVgv9JUfU+s/AUvEraZQZs9aP3FUzncvOCPwVCbc3xW+tnVwtIsKUYdmRRpXpxWrV6Yvt/Lv0dowD6nqAcR7m4XsWo3eQul2i0zDha3mftWP15DYvr+ftwdvGOwa9IEPTUdtBXI/hJJF+gBh5iCm1NKqCTPkcTiGhKSCYooE1ZXeiva5kXHRz+Rc8fsU4z6bQtnTYkTZM1SDaWXOw4EV7NEwI4rC1MDjFwTyi7ThfUOh8yqhCwzgIWJcnIIBnJIJrkUSqZKcJw6mOJfzZatsSXWjGFIB5rwYhAAcCYw+6gIS7HaQWetWBd9wr77NkqwTeG89gfb8lSScw7+STFcHV1MuGT+EoJAa80hmdGHObAQJqkci+5tlcrB4oUDQiBsh0QYwntVZPkcsaZSvPqrLP1pvh/JIgkaBFa5czS6QHQdqTWzWykBlEDdSkLjtKBVHTKNlYc9k/GlHbZjB3lNZQJkJtRYw1KbSVQGjUUCkiYkmd8aQmqqQ8N6MqKz0z5zwGo80NZSqOm7WokwFVNDTdCx2Wxp0qYaIqDgCOZiyJ2ltDb4y5zxIhqRFCjbWUDYlR3YKG/ZBneK+GLElTr84USqvdMKq0gBW1l9qIiPa0riUaS+bU0KWUffOHwE2iLHrrw3hio6r0RIbJI1Bc9u1rdC/IkvCGUgrI0pwWkf/qVDVTSVG8FEeM3rpESHMPBTFbayMwtK6sOiGQCoqWehCWZpqgSmzFg2S4FN7VQL2ilEzjYpxWMaAzpcXLMrApt5LsS1gwioXCWCMcWb1ORofAWFOfUx80y3xpSQZT6guvtn4Z/9N9o/NvGZ7G9HgEeO1d/d8M4jrGps4tYkAfDaCOJiQRbrIfizsZeRA0sc+LPEZqZVjwsHEWAIiiDxgdmrR16PScBPPNXTmgOZ4s8Fi9h4ov3yXAh+A7OgZJwFHApKl1r66ivUyz3IFH51ZmFuJopfKTrYXvKymzkSUPvmPUq+J0falprCS8mKHZBbQIane8ZxB1FJYzFjPA84wGdRCaqksm7jS9mHnBcpnTCRMYXR2gJXuK6Xt9jGr0Bisv4ILDYUbvHYfWnPcwAG7dcY9bB+MOfHeBO3wHAZhe/KELn11WFWoF5iNyA2nU+UJMMdio2uJ1068Wn/M1AzNdXun/1v4yz5l9/0FGX7eoWoCld8/LbBDyNFBfjdTDyE55tXiG4oN8TPOoPBXMzqe9PRfcYr9lg6zQDgL/JfhaX9X0wsSr8l83lEW/LOI4sl7I3wuN4J4PB3QwLi8vhZfvGwjFI8+FLknfiAATIy0jzf5wWBghi4pdkfFpkFm9fzKOMNLH/suSa1cCOpZ8IbS5AWCh0bld/ccj83W2nHbY3lm8i5i0vj3rqMnro3vkL7NnCNtNE/AW2H8ai8U5fTXDOcW7kJbOHUJXDFjmeVbBwhwCzNmRktOk8+HUiBiFyUs8zLo+vYkjocnJIokH9mTanwlgdJ/GhbHPHGczZYWOA+Yw57KOIEbMg47VDOaTZiySYBCNRI8HUYhQSUsHEQFV8FvurShlDgSlMvh4GArWqvjJ4mRaS0GZCIUmgCDR5r2DW0frLOdNBhhf0VF839oxTuSTngxcIcsMU2VnVZsvTphmZwKb/fxdt7SdQlzO4OCznOR50xtYcYbOAGm5ECuzAIjzGQCtFa/nH0BlnuCv2dBu9CzvCVvfjpLJj2Tgs/kA0DzT3sKVM9GDoBMjjVtPJhKKJgZ05JEtyHqtVwxUFmPXBzr9HBA6uJxhctlz/40Z821Dw+dBF1chUehLsJ++0gKN9PPXxfenBLYOpLaPlgE6Yr39qg+b/nH/6RMIQL15i/b504lum2xnUs7pAJE+8JGxzyb/STcZW5M16lG2tM6nJ5gh+kvCmF2u4C0YjP3Hj9i9ewdzsiGTBWz3GH8uQXnJcemz04Yb9cq+/Ne/AAD3f/4JEOHu33+CQfhU/NU+c5uC/+YYDZfX9y9lqIEO5N9plLlW21P7k0Tq4TrS77RxPe6z9tdviO+83fAJ8HcmfraEPKPLq1kXCwhemv7/mjVTAIB/f8CD8J5Dnn2zGMpoS4nPS0enUoqWCxx/3zSuZz3yEeP5EsZ9tezXMzzDaXg2oD/Dk8CS8KwifZSFegScMjpPq2mHJ5LarTtN1zlRwQEkHreAKunkIBIJ1AA7HFm7+TQZR094nVUi4B0XfCTxin7NEvk9Gql/Rqp7pOS7Ae8AfNz4/anTuGewiPQl2E85pfk/Acciyo8ZxA0I59VSJ/zc2MxQ/hd5xmAA4yHE+mjfvTodyfPLaX+p6cx+bBjVf8V4fgpESc5HsdeiQnsSOGyvhfKDVvteti6Lwd2ejUbd0L7uz+Ph8BPP/D5YCv4M5jA8ro4FDAtuVSXShn6H2SNPUsD3ph6Ihl+ykIlfJE/R3ubhgQGrW0mpz37vsBdSWxwN5L0zjm3BUzj0eQ7Hg8wehK1p2Z4qQuc9iC7FeG6/mpLFtWwHABfKf/ZhOAPQae8R6XHITsoTezlJ5LYELWsUUmepVaz3UAkjixgHG+aDIFkv7GnLPRpQ+2iH3azoIdJUz2qctfTkrjQnaHSY7GeJVuXB8KacXg/ZkpLZzSxqOJY2VVVFFYSGWqobEGVspHjeMXcxklFnlNJATZSrpaoFCKyGVkJBETmBgIIC6mb0VuWczqXXDu+MmWaZL+5iQK8y1kIFferovaCWhA0UqblduVZMCchaN57VGNZDzunRBypFontbAZWO3gmFWCO/5fRpigRRvPd1hOoGbq5oJy2/pGc5DJ2tp0A8wmgQ7V07n9qhaHGtIBi/Z8VBSQZ0UbhqJH8pHn1easFUxXGh1HjG0jo3j6wKQ64bPmJoMIcTUkcBO1STZydIaWNF++2zOBjQGShFay4vDu/2/qLKLc92pPvG5peMNrKtkrnSpeWw3gwKkGSUGVkKQIkOEzlOiuGX3HHIlPr2GKuh39+Vn3XjueKSzitRgaEfqdw8RLzAxhp4E81LR0spWiO7AKWAmg2LYngM9ezTM4F1kmk5XQL92F4IOFcxsrzNSkGQe0g0p02yiUNpMzxnl7RrhQFcqBnW5lvHxbCa6Owo4buY5SrhXspM/GDQ1aVft4wgHBYPf85iFkf+bC58Ch1yHtIo+ZDjqqSv1uetPqU5ghmt9/OW8QR9IpwEZa7c6J3PZqwGkd7FMY+EbnLfOw7Z/gm5M2TrMN4fNJW89stGZ8rmJ1CKWdT4FqbdHfm8BUvxa0kft8Qzx48H2o3Plm7b5mKFBfASENkAqE8MHMTR3GSbcS/R4sYkxul7YJiQf06DC7zNkiqnp2wsy2fpyGdpVo1wRuO09cw2GeLIJiZIq+1LLh/IiDQDg27mIWvUCrLgdgKyonfojfwytJJ4rJ8N2EnI6lV+vrBlZR8V8Argr+EUAAAXuwvsD3uUKjxXjOj3GFcDWM3wQqagjd/SUAfWxcMdue80jGeBicNgx3VY9vUYRA9W+GJ8Rumpzzcg2dR1D9m/Jv86q+RwZC1UMKkjYK3i/EfZoSmNt1RxQi9VKGuliF6vRGCWStRFPfdc5uhhPAYA6ixOHupsaLy8QzI39t7B8yyOg7ddo8956NJ3SnXScZpsOq+wZijPKy/uTfPNAC/u4WFdZQ5XRvuUBWWMriW9PSLTaeu5BHnbUPohqGTwkF/nHL8ID4s2AEL/dW7GxJ99/dLh6zWLzuuc156jh3tySKSBF99/tjkAR43ngjkjVRf8//mXnhOEtfXO8bHTbTBERi0ACt7CNmpHR8Nn3d48zB+tt6nvpbjNjOfyveItyrug39PNjV896txwdNG2pKWngIfX6hfR6ESry3783Ph+ZVbsHGk9IADXkKqIRIT7P/886zx18f49/t+PH8SuQOs+5UAce2/+C6je48i7cgai+A0Ajbvtob33uIx6z/AMAc8G9Gf4bSC6k5HLRgrZAGZVhCZ6WDRiBlSAqYNbRW+MSs0VmnbIYYJHvRSyg7EdenvcC1IjJ+HyXze4YMbHPz8ARPiqyvRCjDcgTe+uL/DRPAwR+WkCeAj4Zz1/xpueOhLd4AtJzZKun7eE3WWK879TIP5CwE1/CwA40CcAo+F8K937Fxqz89n1pTD/q+MwQ7qlvY3D2Aj5APKa1yr0l0yuLHvJ9MsG82Uk8rK5WaNKJ488D1UYc0PVmpcRjWne3FEHkABMu0lrEHc9qCTfyuHESqlfBC2hiYtpQiFgP8+rQxpwSiA8V/jZuC/TpjO3+dHb0oV8YGILw2RVARLG49TCCBOaxFS7TchYag+I04bSGbdI6fFp8GROaSgXw13Ccs5XB2hVGnUPEuC1ciwTMe8WD9/9fn9gVKnYHyIZakRyNlcebsnV63HRqvVhPBr9XS6XEv56B1s79v7OWvOc9hp5DtCF9nlvz+whXOACsrPv9XdC12tZYxV7J2r45XTwk8713KU6t6UNl8FYZEQHF+WRpWmUs0TtWDRPOJppb4ahxkHGjN3SF3j//JDVmkR6q9LPa61XzRADiVif5xlEwDyLMdvkADOMGq4Xkihk68ZK+aDG6VIw1BclAJ003TosjbtaoMn6PkbNSu30jq57ypwMJKqzg6hg2k3Y9Ql0eaWRm92VbTUhodSWlwh8X0MzJHaNlNZo8s4dtU6gSm6Y3R9MMUgwQzUDMp4m8lFvPWq7m6FLQ2g8dfwxdQ2nD2ZYsq+9a8QNg2FGMy19o/31SFyE48ApcCWnGQQXh1zDLYtILkXwppaCOpVQPFttXDdEazr/1iUlqabiHUDngQhS8oKL01OL7g2yQ5ohhdKBPggYs8XKMbiTJEMwfA0i7lNMCGOXFRFCwjnbO2ypsUePoiFTiSnox7bgxv9scCDd4zYume4CK4FBqqSXl4izhquadTxCazWWr1RfZ9I5MprRLXWtrzVcJh8N6vC94qlvdZ1NySEZorKDUGoUivd5PfRyqTsQpHYvCqFUMU7z/d1wHyk+GAWVUhoj/xlikvVBi0S31PxFncI80sb6oUm5O+6RDVP+7tys5Qkn8swThoyGZ34v6x75sdc8AtJiuYLwG74AI5XR8Lm/B98BHRcA7jEhyaRGLIGo3+vOH8rZmDWK7+DnKzOeFn9Wx+B8IvkwKI43fWeHlVtgcGtoJQwguyLMnSHZVXjuih+E/SwR660FDUeaI9J3FVxoJ2VV+70ZQnf61nuwRekXuTtc3s6Hc6XMY2CR6cdKNEXk+vpN98mR9pJPqwPd+Gd86ZVi/qnzJ8faLiOzihI7W4IsRyr5zG9PbGUppzpVk3VR+hUZZ8TByAyJTdN9F0Vwy4ZjZRGM9xvMhxkM4PLyBdrccJgPIMqRpyOVtumYqjjqd27ON4wsM8hxt2gGFPjcKh4aM9BNK0cKcyqGHzFMzo3INt8ww/w4fUvz4nelqSzDkxzHGJeJ0vt1sQjkKdiFpotj5W6aBnmovK6w7CV5fSkGGu8m4wUMrDBz5BPxq2FCjM9LUGjE+awZA5o6fXrmJ3XinKaqk1pFTpmbyhmBo0SLd3L+ZmD0hPzKss+Zh9hLxNkO8Gw+ZL/bR5GBq0aXk2buYilG7rhvxvOpVsHDqs7mhVCmCtZa3dkBLiGcGMQ9i060GVmXGnovItOS1GLn+lU2Fqc5SfuaDE9Vh0aFQC3jKwcCpDm0T8FbjcfIC4a7klwei2P6APY9E0vG6ea8LjoPbPKS8VS5z6hET/Po+1d5Xaw5RY101XFUGnGleVYubII5Ti71fUtnyxWsfnYiNMAbZtcZMdaGc9d/ZQHnEdzLosqvExuwdzUA+48RevqWMeyka5Ytcask8ZVeLwA+4Z8LvjkNp+fGHRJU1i79NQCgq2E4arpl+fThgZqOKzKNKL6mUmKnurllVB9QS+m+O4SdQlrY2l2j3hS021vn0YMujmgogzIYLvX7/t/Ch+u7orKzvHtiYHp74/vj8KGh3hDare7PoR4Jp/9PzWV2Bl0SsmEqBj3oVosPnme1nRyZvtU7Xkka8TyG78unRzzYXCnGWAt0C9JZ5xgQIhDK6N0qA4I3J2n333TG7kbW788z9vENA3cfPoisQul8kHmy8VE997n+Q8dxrD9nwTEF4TM8wxPCswH9GZ4O7LSIECQXNyhBVbZnSjJgUCABlgJLDnKYdmiHhloaOpFWR4QotJ1hjAdTP+zZu/SXr0R4o/U8v3+49X4a246jyRLOF0Lt/ed4Di7hFuLtdQp+ZyS61z09Acfn6PcBQSLkTZkNPK5m+vJ3a68j0l6dqrVuh4FzDgF/EfAKcEFm65Fy5Fo+Iv+d7H+Jr4WK76StaJCMAwwAzIMhwpQ4DnoWpIEmsL9XhHXSdz/9+P4+ECqyZcZi/UcMVUMcWL4DyIee+OC35KAh2nhUvi/aPlOYPGdfW/aBrPwwOuyZCQwHnA6n9jOhtUio/G86vOcPfLTC2uMh5u48ahZ7Qcdkij/sQQAqLsB0GA8IiBgaxgGM3bAODAypPGPPxDzIPMecdmaNAjSDDkVWAtgBvHv0sCnzLAKmgLCMythClShBEgtnPDqic8WASxQmHrMumuHNnjWji62/8Xy1j2otyByhmhBG6f7Aq7scuoumtjfFOqlCs2vt+NkUcxx0CgCYGK119N7QFK9aFwP6YZ5FyVm0xAIzSq3gqjKLyjCFkpHRDBazKB06oMpsjr+uzGKgMApVjRCSVJNN+2opu+MgHm1IVHpyYFjwtFVsFcWVjOoxvWK44N7U2XFEDOMJPfcd24rxzfceKU0ia0GwTAhWTqBUS3sa0Vv5qd5ZlcItolpNYbl16La9wRoVSxTrRcrzLDMIScYC+FpBlbjyXmPONP6DjKoEEocDYt1n3dtzWtA1rfxA24MCGgfJvw6/JT3DclJj38L1xETmmJLKI6jVc1CckPRfHGxsTmy+1AnB8tgmPMtG856U39F/OP2RTAPyfCkE6gSzWJGVp9AHnUZIA9pY03d2tLaNW0vI54OafjOYEEZ0Gp4JeZN5lHliEVJFa/1tS8lju9kU9dJY2h/5DzPaj3tdtyldJBSSFPAWAB+pcPW2F1eiIPvRIdb6e1QAjQMfgMAfj3zX/82QznqT2Qet3wQkI0RAgWUeUT60nIA+8u6lUZFZyggRWxkMm3ftsEew28NKdy90Uzb5HiU5AMa90y+5R/ogrgW/B46lcL9L17bgPCnkHHiJUUqPdcrkfZRC4gczwEdflKssUHqQWezzCQV9IYkw638YpozR4Plto8McNnnI8pfh7DJVQOtDT2WH1udhPHl8lrWGtRb6+LpEkxcvHGiwXzMaZzR1a3SPhdzbNNtE6tAHZe3kzrqejMLFVPI9tZw4xxTd0+JMMPaU0r9ptVUOXN/hiEbp64Lu+KhoXO/Qn5+YK+NzLHIc8el59Z7Teh3tjvVaLq4j5DyTfQE1+A5yE7m8bQ6Axk+lhFDoxQrk2qTZdqgUybKksnMrBVyrt1fSu403t9YxzwdwEzm4qjGe9J2NO0rr0nZv6J9E1gps116z5K34mnAeeU5UjnICv5ioTAceAsdmVraeZSOT761Bw0WOPcBAct4aHVUGXPcVySBz6/xt444F2VxcsL8rQhmDehLYbid3LXfxlO7qZ8GGFzLp+m/Btcu9jE+oeIsb/uQOdNlZ8X8ypB3/RHz694HLTZT4onnAHQECUG8K5ttbbWNc94K3mUoPbXUWJ393ygTQPjaUdxUX796hf0xOXQDmjw2ML2i31/qGL/7Oh6WgkdI8di2eTs56LDyGQh6Bf2gjvWbg6uYG/bajvRMZ+i0Dn070pwD4SMAbxMjX5Vd5SyRx2EzTvvU9/37CcB48/udsM8/wDEv4ZQP6sRS8D4ELLs9eIn87/OyaDWCEKrUzps8Mxu3RKehyQANAmp9UzgHFDw0qRkt9Oz3QUamgy0uJToLUC5u5SzQkN0iVs1DcMFgdbEW4lgOhGOioN3xmBv37AwqAd8rUP5aCwsBfqtisTKI0TUrk8LY+MS02fkBTk+qILGrsDNiqlnO25xXG95hIc+7jVg/JIrQtrTtDvv9TXqT23jfq+bl1YDh1iFhecwUKzkst9dABxeqgv2KN0k/Kg2RK8rYsYt3NAzS28ybVEszwgqUeuv9+pF+usNDvVsPRom+qHdLdiUUNchpavNPUyE3r31p06aEJdmbFOwO4P4yes0Ji1Iu7Vq9ZPZZdkHW4vLjA/f4eTECtk9Rs5nHsbjw4E5HXkR6L60SYsI5GilrIqYNjw8e/+rmCfV6yxtJ7lFK5h0FPW7Lvoh1SZfX68OMHWVMeICkeUsfyeshfHn4PAXb8/aSAac8QPMKU1eBYNKXAaFRa0C+PJgBywkpOk577Gz/rXHDgn/e+Se1Uf8XCVTemJR0DXRtBPh5SkajvBTPq1Qt4RBHC0Is9IiU0IAozXGDe710hJAfZ7vd07JUnAD3NBwEoLMZ1u5+4+QIz9JDKBHBDI8KOCpgaWhO3AoLuXZ07IkZrTd/dtYSC9pOkjnjOWmCKwVKK/29GWvMSlnksHsVLzGqUY1EUmpqBLPLD1rmAJkmtLqVX4gDeOkOKs1SpsQ2WNJaVQAhjGyiUXgx45ooOmyM1pPfua0zF0tQr/y3J+KNeKGag7V1q7TY1mJuBam4zsJdheAp7iPJzmiZMVdLnR3SvYLTM3w6lN9RSMHNHtWghw0dFOqn9TSCWiDAiguYy1nrfjDJNGu2vRialrctDZk6/5pCUJ0RGjyk0XPlsT0EDM0RJYTWmOp7ZK2LeIwKHUKeKaaqYph2mncwXqIZcxWnfk6YzLRKNJdH6B/Qe+3re77G/30vkuUbH92Yp8nlwGrF+ARZlbqgkdIqrzXMaL4mCu6jCu5DsO1ZFee8Sw2xZHExRDQDUWVMCFzSexZBiAbT5YE8pNZ3TCgSPyKSSJIJebu3onb2uthk8dAWUfyeF2QLMCcIzPplsDqjyS/Yxs2RiEh5F6qTDUVdb+1VKlWKb/vaGrgYCq/Ur8oNKQOqQYtlLeofUP9dSDQPTJTtiCL7a2jHt9PzSUFDRuAONMe/vBwPedHkJ7A+yr0qocc0RhxxP0zsRtdQlWpC0bIQ67pQichMFd4HOHVNyHFQ8sohBoe8XEj2+WBdmY6bs9zIDgvKa/QGEBsbVFXD4/l3JquBNeQHgjkAvriBZfgWJLt6+QOOOu897MPSgb7yfL0BXBL5j0E7movem6xQlNLwsR4EacSQ7hDmJWD3s3ruXeWB9D/WOOUcJO+8hqV8M9vWV/Bea0l+zUDRuQF+fhAoDbPWAuWLaTTJfvYEmArc7xU+XPGxngBCG81y3fL1XzpMxt+BUCvdT174HV9iEByPPNW17d+cCgF4pXQLcwcwzSZvRalFaqRZyGii/BV4CQCkSsd367HtcZnr5jD2n/NVeQNE/gDH3yHhC6r4EsDv72HiKRtTOrS1opMlW8r4f998BROSyjBWYv7V0ygHqC+HlM8/K24WveZYFIgyv0aXJNbsBMVgCJv+RvJcxROpl+TdHHDLMUZmHe63Pwt+lnE5x+tJC9k8GQCGfSTHs8nfQM+TrIJXjLaOU7kmPqo52lzwJWMzN6lISDBZf41xmgwCijjmhHVINJuUxZiwmmMxGaPNYq6nUGsTT53DEYaTLWT+FOASF8wQZTtv+oNhXpPKQGu8la07FbqqodYdpqqgaUS7ZARq4y7gLCJTK1BAIvTFmdFBnkwRQpwkVEwiSvp1KUV2YyBvzPOP+7i4GRAzuwAypeV6rRoC2GZ65hxlz/yT4vrsAFWm/qyxFPKM0oM8iT7XW0CFOpd2NDgQiRm9SAkmXRng4x/J32FZXedinWPFf+ZTNe8ZLBlAqVA4bEMvBMktMZQKRfTenxbzf1HhXijdhWfPA0POq0DMgKoAZngr/jQjK3hOdTvi2jOCMzArHafoAlCbDIMvlesmMUKdStT8UDHIOWPNfFu281vGYvuyaJRPkDjfoYOxxCwL8THqA9OWEXeu3wpmzfxQqZM5fM2s2n09BrSiLrCOfPMas2zLCfINGyc8/33Ojk+caCa8ZqLjGfHvr2Q2OZdI0hxWD+UNDB2O6qSmLjfG3DnAF3YTzzfxxBuMzwNeo7wjto/Dk26Ui1Pu+NYaNjaFg9brj1nEWVvNqZ4Ejb7dr4ylrwcfS9eNS2tbvfOL6ibXbuJSDC07Bkk71I3j2Wun1F4hTbb/t2L0XWvu/37/Hjz/HIug3LJknAOC6RxDBFyJcc9Ct0Y6htL5E5i6TU4fhMi+eiww9pqdCts0sz1guA41tPsMz/Cr8YxHomSg9w/8cMKWbe+KmeqlrwhX326E69IbsSCC6yaQMNEVzV6VNKdhdVkmn1BkHOoB6w9wb0HgQav2wmk6+7jHcJf0rMXBgYEeyAWYlvkTAq074AhlLrexew4Adss/D2mCsxmgb+MwAyq+QKHSCpD56+F1HmAGnfiQl+jly1Vd7Xh/7SsDr/gsG9H9Cet4AO1y4cKj4+BT1mf7QuSr8GkySJ4D8v1HYyoKpfX7JhB/EeMHkguyySwXAKyZ0knSPL7Re+t0iSuOKgB+L/Xif2uvD4TT6gRQhhnQUYoZ7FS9hPPrZIVsVOsyY2zwokZawb02Vp3ADgClXfx8Q5iMbwfQljwYjaYn25Ia2vomCYUk7TbHPHl2cuq2TzWoDzKkag+ZGF3jYezmFtTRn9IlXhzqksVjflYrDFErWVzYFl6bEM4eAHEkZvRi9uDkTKh+7XWkDHUNfpuzSO/tYJTQM14vx23yvWjCYYUbaQZnKSUAn0uyG5LyLsR/nSJXLsM92wClFDOGpX8MhnGadn9FIA+4aIUwgzGgAKk9SxxvJEUcbGxQ9gNYtB7iLAT07UABAraKslZST0mIY1Ul5gRjGqJhCiYFaYEE4ZpQOo1CMi6UTouhOyjPh84RGmvCtAVykkXHXAAAgAElEQVQZtVVMFWon1tnwJRZCK5dknFY73fRVhUja4urBq2LPNEO/KD87N9hSWSStKSAAkS0OLKnCLbV8sTnpDTzt1Pu+e5pNwQuRjSRNKqNwE1ut/jfPUse7oITfR+/SJ6hzIAL/itKCqilLbVDHvLHXYDgn01/MgL4gPZ56fbU5hB8QsaaN9gUcX8xJRlSD3lQnXF5c4vLqErvd5C+1aPLWLKeQ0CO3d7LhcRNFJjP293vs54Pvr2415ntyugEANMVjaSjzJyLB9941pakblmOozGLE6RaOR4TOojgu1MWonVLPA1JCoLSCRl3olDIDnxrFqaBlshdyivIgMbH2tl1UR+y0J2c+4HERR6XDcA/7dTP4RsYYgHtHIaARiXzQAS6Gy+zyoNEFkdGBwkXfaXvfMjyoAwMViRRkANTVMEYSGs0SlWpRhSaYcRFcKKVgNwnNdUM1T+itgVtBo4ZwWNJ6sXtCfXEF7GdNiRvG7Aw29sKSraIaHUglmNT3BtTEGSac44ITWVYBEIGmSfs8gSHOWHSVeKuRl3QA6k28CviOAdoPCruuffzxvYu/QlK60g/lS3d3KC9eiKGbJKMFacR6/z/sved2JDmSJvoZ4EEytao5K+a+/5PdPXt2u4upmIIMB2x/mATcg2RmMqt6ZojuSoYrSIOZwSR/H6LBMq5BfCH3jgE3BQcwJHRyoYMYHxALb1YgUSEsvUYngFsYZXSWiAC2dqqAQRaO6RmxFPVyzfRV4bxQQS0VXKZ4M5TooeJ6Lg2FzmS/Lmqw4CG+2/CtzfZQJfaLKWGGLXXi3R8upypy8ODd69vkfYmD87NGea4GNhu8kr8w7Bj/bjeI/pPojKVLC2H6yHclNKopKWhn3OzvDONIrOVuV3DimeE85S2NnpuxjPFJQkl74gNpqNnFEgm3yoc2jztQQ0EDDFm78nXocf4bGJ8YkeoJqsQv0dpAL5gBH4vWTrln5oluc+r+/iPfrEMvVNSwSfduqsevpiHTqV+09wRTveO1KViHj5xsGc9SsKGH6Z3BWJq2kQ83SvPhAdv/Bxzpyvro7haGjddUXH84HHB2OCgPKHIx7l3PtIL3hEesKFRUeQs3QDK+0pTltVYxZq2mPK9qPBdGahHNRnnLJpDeu/Tcwru7Ybi2VbXPFWKS0Zvw3oWDJ+mcjKN8jUg9/oP382c5T/kwzYxBjzxteppu2HyHMWiafIbT+VwyXsu/erpBMPKbz58zBrpbCXX3C79YZgT3g8TnobzRbyNVJi+zdxok7PdsjwuIzO0LAfNZ5a8pFunp577u0+/fNYJMKX66Dtt+XmfCiyeKKc85fZeV51ZffUuOo0ByLlvfNzA+omjM1OPlio6PKHiN8kbwcjf8pHxBfVPAeDMwNA/GWwGjzOSuco/F/NW+7fEqv6X8RoUwAVjeLUGPId7lubxP10/evsXXy0sAanBzYt+fMvrfjeCVzrP2Nzt6mDCbM02655z8PXjpsfxnKI8h3B/Lby12ED1l8eMo2QR6lpe0dXQSLwfJx0hYSKzcqh4mwEBTWydyPbeQLDv4NIgQiKUzTtA+6yHMlKdmJfVZhXj2zW04mE/ThnjHD8t6sL0nnft4v9cevBhjbDmQPpJY9b1mUaD++5vXWC8/4iv4b/FGny1if7TY4cL+vjLOkW633H0tDo7JUlKKvf6CJTN94Reb5yLAkWa+EPBUwWCBWDwTRCleADxJSvS98lVh/AlI3i0BUBdMrkifvV3mkJUMoDHjYhFB6Y2GgLODaFPGt9biXuim1BE5aHjLZiFa76z5j4sfduMpXLlkfFV40Imo73AouL65wbIcPP8hATg2y22ZRzDe2SunDyZyp5SChSDj3z7eltua3e2Kija4hCAmCepM8GGCTpNBWzFPFg+/i1CsgU1AmYS+iPDqs6B/v3ezsGkWMo1Ds7YtF5x5YkoIfs9suHv+51S/MeMBOllx3vzQy1MlQ39bvqMhgGn84D4HGGKAbYNoqIZyTg7b4s12prRqP4PqOo0vlIxI45V38kHcFYFaL+EAmWVTAIzHYfmuAjCP+Biv5+3Mh1O2Z0mChIAPE1QBWSFnbaVrMgWXHIorAcxVlFhqccLoaEfzZBKINoX88XiMldIk5qQTVQxgLaS3hvFllnCsothTuCkmQKWoK2bZvWRrkdyTXXOpusV1k/zwsjfU4xZd50cF4TSKEEyfFgpHaK51QmsrOhVU7mBVuKq9gdZtysoQ/NmedyUzi1LCpiEbXsg8Mnobw/1vygzkLvDPz2M8svCpNk57f68Rtv3I6KQeRczQePNSSnjTlVJUSGzh2QuWuqCWRTyerDskSuzcbcuXbR035XlvHS15nIcXk+zMUiRq0DZSUPaakHX29AG9KzxFztk4rBvvqLDAMXeCnzqYKySmAsUaYzuP3FkUFXm+DcG5MUJgThmHvEgKK+jdQ8ZaTmA3WIKtB2Be9zahtl/2FF7zEpPVQzIqs2VYivx3VFfSqtPOlPI5jv8MtDLjP785/XUjLp2H7A1YiirQoR7xbFN2BvQOLqsqv29k3+MI3BRU9dRP0z61qrNHEnsk8LfAlijxi2Dc5FEd4ZPPwBx51wsM9slxYLm4QL++BphRzs5gZx2Q7m1IiojeOzpdez0EiRAUYbXDcMvHkxWb37+jXFwAIHz7qN6J/B3GIgY+B3B9LfugAXSQsL/cGgjnQAEYR9RyBqALTlVFVYHiKmdg1KiCOwjd0UGce0Y+pEKW4xrAjXqRllo0/7V5K/eJT5jQG1csF4ssW77NQqel/W/+XYb2UyHWTyPW28upsOy31X+x8/yp8i5ffe+wjmRn/MP10+EOgVBeJBpexn3n9DKnS0idbC3RPJrnj9DaUX8KsXLSrWvWnR5EvxlwD8+tQjaNj5JnqcJCLXGOIBDqsmBtDbUsAHenJQYn69pivIYLyS6Aw4sKoOLm6gi6AM4WMejq+p4pNVeN0LOUqryIRmYos6GmEIWWDH9zf6zn9omdr1zQSwBx8cg4LqNOc1R0PSR8j0bjGMyujAxuTQKGhjlQoaXS6MxYqKATe7/d4SCtywyB2biPADdg5OHVfaV59GxLp8eWyHkv63zvXVO9iCHPyP+N9cw/h8LzK4JMSsKRYdhDjjvn/yQ1Snpf+QvnRQqJsdHO6NbW5Azt/FjkOqci0W4sIgfVikLN+3S8ufGIHyIzi3QsAGNt7OtiHKcPXfeD8aFOj/Q/D8WceSbYNzs8KN96OVahv4X/TXOt0Mzzu3pRVAYYhjJd61EDYvNcdPTZ82Xqm4z6sJzJPK1tgG83qNM+uAd5BlSG8IVG//K4N2ev8fPNUZzij++gYVPLzxc8ytvuVpL/JEHTckrOdkrmZ0aG7cR7d3b3wct9WwzYnssLHv92AAcNZS7Q9RHbXb3l/QHWSI/pznx9z97+jiJGouKq9YHEmzhj1eruXGKw3N53dHxIcP8R6/uQazA+oL1/DXrNWBY9A7fRbKXoWbGleqy2U73cfz7fZwkvvvk8bUAavwtONV/dD35Ok5c4afDOe7MTx7aemXP1ise39vjjndfteaF5Y+b5C76kOE2Sp1Uj7AgNPg2tLxk4Xl4O4dpHfija8iuVc9xWHpXcj+VfsTwq0B/Lg5S7QmII+cyHZ/Vu8O/hlrKmPGd08ELielOKhHjWvFBoIrApdmi0Q0E6bDmZEryP1nli2KWYwvglbxXXLyEZWu6Dv++jUP+V8sNhR+zcztY3PbTf1gZEkZwPBR0WxkiEW+XtS/DlzPjc1o2/j/hJKM5bnt9x/brDcw7f/v4nEF4o4/R5YKvtCGtqGfvGPLot3A38OeNrlh6f6PgXGhWV3zauyneXkfHXjUKQHJLMKFWU6L112cEl7x/aHgghh86lEkCR3zLek1QKZslqLVv7nRnn5+fiWajAK+fUu1ZqGpdvxNMHJCvrX3J6GVTft7zG7lES/9oshLcKbVdO50n+MaV2oNux5VlA7fXM79nniB/zKFzhpMB9v/2WkAxG+ODt46EQRNg/9SzN27wPThxG8itIZyu7vRkLDb98bVwpmt6c5jHoTj5ZxPoksdpU+/x8K1/JweqtL1kJG3/lCzeu4EQPJ8EgksCwaJQZwEI7i/FaZwnVa+9aGNDwdJV+dc0tDoIKvEk9XRCKbJDn0bX+sMZ9s/zLLmBW73hRYCpdMwMBaF5T5LHA82Qy2L2tXJhvqE+/sb2S11O8yPWORlDv1NSzX9onZhAaurlQU0CF4Xnpiz7StpPcM9YLSSDNOxDMulP85hbP+TfTx6FITdhlgpehEljnLay39Ysx6ksCLxXL26keVNXCmtYCNEAS74gnlCtudVIsDQQDkpoB0LQBqkRvaxqDLpeHdLN7ZZjLPPZheKWMeI9HmmqGGx2M0hmdQrQUsERAGefN4TevaTJQyD1L0aYjVQMCLgQWVKmownjJ/cqerzaEuTwsmwj/x30+KC6Uac2wJH3yTTHwylEv+7rNkWzGl2VgMsfzY9v7UfEYrk/gq1Trh9TlfFRhlF7AhbHwomHFk8IDopQsSSFkg8ye+9YP6zOBNGKT4IJSCgoWNVC6ThtWr200FN6DFjlLGwOdn+tckSs6XBndO9ZvHYSjK90J0LC6iQ4lImyKqzwqZkb79g3lgsD9DOBrxx2k/bBFEBwp4ESlotIS61+OYFQUqDe4Riwxlm3gGZjR1uZhgFkB2niPCOvJI02HCeR80v097uOeHWFGvNMJFGkl9kopHgJ+j/pLdvhThdO/2Pzevnn/+/Zsfh60m7V/0uvb+UVRngc/kPa1/p0NzTKfBSBo9e4sxc6X9UwIV79jDp7C8dyVvvd8FhPPxdqF4iC7p+nWohsDXJUiZifuecssodDVWE6+4VQ7If+xueLvAF4kvG/E1rsXcJzv3b666T1HKUkuMdQDECTqj0QKFwMUV6KD4vxq6LgAhesYtcX4NWaIcSULb5RogY9DNPGilAUpNoU02lk9Bq2/NM3ZOPKMe8ZtnP6l6To/d7ZS++8/B2SXGuIN3dr2TH9vl9zLMDQmOHubokwNhqSuLNc7lt/ch5dSEJbAzQUaXcbXz+oUj/+OFqn9UkqhQmJU2NWTvRUCNYsMJR1sGoWHoZ7izIMxQWczvIMrnWNvJPrqz9TT3HCQ83gJR0xnxeFid6L3sBy8bkcj+Xm6N2BATjRB54HSug98aR4jZ+gwJd5Id2J7zXB6olC0cw9MMH4a6Gan8PBn58m/bJETzyuccv3Z4L+/oty5kD9eOj6CACxv3oDf36MNW9K/cuiJlxr7Ml6b93l5Q+jv4+3V+PpUHTPjqPnRTfLyiYDXWm0nDJkG2XHwuGcN34DI99tDrpMfw+5b54++/7Cf/3hjJxr6dfAaKxYuQXQiVSMMtN5RSsH3f/4TLyGcxvupPwdAY1iFE95D9nQrp3osj+XvK48K9Mfya+UWrXGcG9IJ0Ml6HO5EWMXg1tHQJM85xAevAOgLaX4oYKmLH2xLJRQmlE5uAV6IwCWEbG6BrwdwP7gSDbjcDuJIDK73PR0+8lDvxN+J4J0SCN2nvIAo8X+4TAQ3yW9Plk07LPde6Nnsf11+HJ7dVf4uGmdWo3dZ6n5ULtGI/eyFvpL4w56yvL2iyEfF+OwKN2NAbQkyQ6oiDjSMCNiYFvNCP1WeMaHfbrDnxUMLnlism9aABs2ZFh0+LEWV2AH45gU3CiyyzWbKNZsPgwws6jFgSraVmwhnh96IJwczPPedhaBbNCe75UQ8ZQR50HEcqnig3qxi5d+GcIr75Qy3CVWnYsPLZ4AsSfK70R7BrO7jOuoJVnzAlio06hrKWkLhwj3Pra0QerDVPLZ+6gSXbhMxUGdGejoiTPVYCNeiY1NEOp6+UjteuwtoJjjyEKAJb+cKGpCDu+bZHed9aO10OWgdxyyEWVBBjvulJhO+iIc4nx2BY7QvXkJBW4x2RE/GvmxFUQdI+PZpKKDpW8EcRTHHOSrAhGusAoyifRjp1bDGIXQ2GmjDzK2YIDC+y9iMVZlSNPRww2q5pIsYeZhn+qp/i1kuq0C4q4jcRIqdOqiT4iH1ZyCAoUox7c8QbpulXzLGrvgnwn3aGFn3hR/qWddKYbQUHQcrvS9Fcl0nZR5DvYKt3gKsLB6uRKrI1HQvpajXm+VLBTz8tHtNq8DBeSIVXGYlCgPg1lJ46NjfAJKBR17gEVI2O0DnwmAqPAYDfuf3AfUOZZnnLK0cYEYf2b4pkKy2FYQK0muBvwoLt2z4Ku1kXefem3j6qsd5bx29N8+9W0DK3yVDCfdE0nrZ8KLlHlTBt6+rpQ7KXKl3BFSlbwWMtjKoJY8jrZdBnidbP4PjcYXTbjniZyF0FljroyHWioUSZ1HWWwj9Xop4DPdUX1Y+k/af2fN/hvBYI3Uk3Gt0mjF0MXLmNU0hQeqFprxB171kKIt9DlXIofSABmncBKQ7xWhbppEjsKm3qAQAQKsNtRcUfiIPbe8DsOg2qQMwMY/BWoGFiJfxLNrHrspwcANR8uzXedH4V8kwoXhoQYvCQCQh8ZmBSoTKscMLizFJLzdglHhmfJaufyUzQJ4OIInXsryz/WsH8zflOQnl4gn69TeY16mFiSYiLHKoAmUAKFXWWvOwF1WeF21Dk5+L8QgHH+M50FtHKJXkG4us45mLbShqaBOKBVX6TAxeZx7Cc64Wkcj28Y0in24sSHyf8aDdvYvPOwGWGw/22/Kanyr5Gw1448a054aZJ4I843HC0527ao5yxaDngttsnsYBbbhD/92uPoPwDIwvAID6PEfUIrSrFfV5hefZMKU5d/SrBnpODo0SLl0xoZNeVlwkTZaauVhy/F21fvMkzYpNU/iFZ7fiRhCWWtF6gxkJ2Qwdnh0AAEeNelCfiGHIuq4wPCPf9JFvM1yue2COoESpc3vkU76xXRDfi8ds8Rzq3IP/oGyRNOE+Ow8sy0FppNAET3CgPMXh/ALcO77ffNd+kvdb8EAFc3fPXUMlFkVq4P3yAmQltsNQ4KX87gCdaU7tofHIwwZNVjHOS6TmrQ/GtFIJY8mWDGZuK95UhhFVkIciO9SpYayUjLNIU/mgaNqJ4rlci1htKc4kh3mLTGS02IzUhR/tig+V++UKrqwGE5DoMzAYYz939dYl3LqFWu8pPQFJykKJDiZ5bJ2kaJtQvqJ39vDuzWi2TDacLjjV2sGtjlKM+uf1ShwewfemQ2WgEecjsOHTFKt04QXNOM33z8A1xx9buUIGrcqvK140mJHoTju8Bk2XI/k3u1IJvW894YwnsF+mPXSK3liH7h+W/XRNv7OIIi1kg/fu7r3Lj9dodin3mpJ5oVgcq55PcNkhLOfN+/doA5q+fQWNjjAzXrDwUh8ffpJSg7e/IorR12B8ANHb4dlnkoijMuZX6Oph/mGnzg8AXlOM0diW5W0FMbC2jvVSUiwt71QG+J5Bb4WOrJs6Z05ty/lsBxv3L5VnzbnQXzLwKRPngd7MtCqw3n4/bm8/ahnx1vw8S03H9uZ6d/o8tLP/aG71rms7570E4TMBH8Gud/ifbxd8+8c/cfFvf8i7GJXn7xj4U38XvMJHEv9/i177OfFhztba+/dQhA8RYR7LY/kXKo8K9MfyU2VWFuTT44DoknAy7vLANEMZzkYdRdKaq2BJBK+dCBJJjSQvZRHPiN67CqgKqIjwmhyRS57oyC029sU6ZOP46NfjOD8BeEX04wrsqZ5CmhvzB4t5wP+MCSPbZ5QUoduu3buyj/dlRociJ7ZZgfS7y3zePlU8J3p65xnHgeU+Rge7ghP/Kgnc9b9VGWhTpM/TetuR6qmGXvz620xaRREqh1RShXYcLA2eZgbRrO+9/zwy1a5UN6UdClpXJfrE3HKNnMZ26vYw0d6P/fGbQ6AJeuXznY29U/aDcz9UCbVVXvPTZ514YvIi2F4GhfJsYkhNkODZIuhU/dGKfU6gzbyOXi47ZYiCEOp7h5CdaXdBB+evxl827qG08fJndoAdhE99y8oSjc/z2I/gmzOLFBvf7cAXqeDmZOHIOUu0nn5t6gGD/RAja21KOPsv92vunwqvSCFSJYhjxAbDQKwZw+2QE0Jkm8NSCa2TRD1XoBRPUOlp91CKqhRl80y0DhrOIO8Tk3juFMuprjMw6AZhQUwDz1AeZ56wROczLotxQbylUcI7PcO7w6koEQtbqPCOljzhfI46VBBuDWmPSb3nSOfIFFFgnxuoAgmD8VLeCybsz+UO6jqDJt8u8Lmr5r39Y2ti3r4SGchyhMs9m3vxOre1S9Er0vG+t6YwA5mTLhFQwBKGnwjohUBcUHWtSqGog8g9UKVtU4TDaZB8A53fpPBFrH8pploUL/D1qELnpEC1CATDnCSFAUME3aVWx9VsxiTpk2nr+tfxn4bO75B/ajlJB4P/IIhyIAkq3OmQ4DmLeaJQGlI60/LcOydHOiDroUSspYCFHUPAYWtaHpthHpSopT7Ylw4mLP0vVAURNgbXFHI1rWOGV6dzuQ+qlKOBWLLaimheWkWtxGbkEvMrYBfGO56+oAj2LAZkOichTAoPwKVWMUKCwhcFz+MYMuOZLPiz/cxWZ09RDQj9+rtHhCCquietbwSUUOIRAagRTt+UPp6cwSaucxh1KN4yvGS8Hmn7poyJZ/BnrqhKipK+vxH0uZlV38bX3I7b7sfnnebMfkdRs5Rbu0Aerh3+IOCZUV6U8bkD/t58KP666jt3v8R+1uehGJdv6AXFF6mNbt7nSDgfSMYs+lWwfMMYHa+qYjiidgg89rRnLJ+55GZV2qDhrKkkypW6atdmUCV9g/Mhxm8Y/M90knd+5WkIdMxaV5A2M44jpUel5vqD1vc+ronjadPWIfpqezm4AvJ2BgbcDwxFoq5oyHomFllKExOOkvHKAP6EmKaJucp3JnxrCuTd84Ody4q9n+l4vGOXm+gxNsE2q1ofW91AXpCd9hVKmTb9L9OLts+MjhaE8D/WwDxxGZmvnemmAQVDFd5uNAU34OhGjznWhJUmGa6wKDtNjT17a6oQzlAadAGvAbx/CaJPWpfxnZIKofWOJ63j2oxh57MgC7yEsecwldOmHr6EUwAj7fqRk3oOGLKYMAnggjfhxGen9ZIzMgc6OlGGvZ77/itltwLnkPR6pien5ur+JTt7mKL3ofKf37f8SO9/m8jqVNk7qPxgGR1kpBh2/nrPuWbFBy/Tnqp4jZf8AQ0/t2aWanO3kNHRoClIlCaPJ73lv1/4Z6/A+IiOfeW51d1YUxdxRCCw128uL0EA6ps3YGasl5I3HZevsbwTLPuraTnHwps6P90JB0o38QC4YO7Jb2Yjf8eWEtiSM88b5ans3EGQ45Z5mb/kUJ7/jzdv8PXyvdfzcqdzM1b80fKoTH8s/0rlUYH+WH57mT1vDIWSa3kAE0qKt4KEU6sQz41CBYzixsmSs6uDSISntRR0javaod65iqXZDiqTYH0Tmg2Z/+ehu5+tovTObefB3I6Nb7Bu/YFSAfz729f4//+8PPmOK9lvKR6q8ifpzs8yOWNIzt9fnqcDWrZ8O1WMeTVrUCP6L3hkLG8rBHjuc6bPACJcOyBraDmSnyYwpPSeCxhhoXPImZQMSl93BNK3lVBw7xfLIVjY9ij5gb0zsCwLAMbNjXpqTO27eFf3puTGjjpsP0g+N/LemEhibc1z5NrpurUuOXcsl3oWwKiAvFZywTcgOXpCgMUuSBchhwTTs/7leXHRjTKHc66q+5YsN0P2CNm8qIf8Qg4Dc01htGFShWDuTelWSlEhuQm2VchvogoTOlle8AlvZRGLFQsHLC2Sf+998WdREcHCLbPJwpAFp7eVESdmz3OeDtv8w8rzGQ0bBJDNj71wnL45rgCReMwRoZ5pJtJieZkvQBdyjKALAn+XXKuB92MPmWJF+nDw/S4vH8G58QkQCIvuklX7lgVyITSXOhvc+xwAstGYSaqm4hAlUjGIIFpoaAGhN6mPquZb9tCUSenhwvECKtnzInJAFlNOsXrhaohK69vGQMOUO8UEx+Rhua3eYcEcObLTmixAdqWYjtOE4uI5j3hfPXU8xNxcbLo6oxegMKNzEoCzrbVtPBW2FlIPYNLplnu9mVeyfJq9h4awuqZ8P6GIiNmY+8zTXUr/bu+7onPeOEN17PAsOeMLuJjHnoRqL7pPioYfLaac8zExao389EMTxgN2iUTSWkPvDU1zhbaWcyOP3TRvaPE08tAC0mZnLGSRixRHUlRCGa5KAFWmLyb7okLuHesKETPcTIiX8/9c6Wr7QGmA9j2cbdm/zcuTPbyTD7R4+lq/OdabqICL9sUed+jein3SLVd652iTDe6iPyMOkXsri31CZ0aDGfAEX1MIHnGhKxwzDH9NlG8WcCnYk6ZtGOgh4tqVRiT42RQQboQCUlpr+CXNkefKvvG1huIpB3UIXkDvmpbBPMFN56+ebaYIJlIjCfIQ6UX3ftV9UNI0iu8gg9ZV3ymQQBhdPAZL0G5T+lv71kfLcWu01yDacqVXbZ8givPsGS8GDhK/mBaZ186qmLEg2gxYTJBQnDTZA72bk7oYdiDPMbmyjaCGK8zoBIUHwXcoDKIDsiaFdQ5g8weg9SbnQGY1nK5KVzIRSOtpfEQCLfsrkYbyk9PF3jiZO30q83vnO03sgPtuoeF35Dq37wOUZgNlmV8DklBqA+JZ/nR6P3bmMnicA/3K4mFIq/VFRebv+lVHeT7uZ1lxS0xF6F87ylOLgmFdI7Vx6kHeGKhprxouc4xIpB7jUPzVolXH/2JwH0YuSMwZNh7fVfdraw2H5YC1HdN+zjPB4J3DM2v9bqiT0SgMjyl4634oZUk5m21sQW8k5U0Ho+n4nXOEGDYfBj7I++uzQT5v5slPGtGn1goz1uPeUGvFelxhnukS92+PX4y1HQQdtIUke8/Gu1ubkRg1pohuvYIAACAASURBVCOri+KdyIAR8LXfGhyA6rKIUnltsQDTq3aDfDyAOV9kSB7aVV4uv2D5yQuRGAGQsZkM4jDvNONRAqMQ0JTHNh5J8G5zHCj8NCISQVH+iQGmrl7YQh/Fa1zuNZb0NjGfNmxyOOvMktakMzoxWtf6mv7tHRbOPZIAwPcT+1QnnKK0cm++jfdPkzrUKV1TOu08nRraKj8H5xUlwoTxlxlOS5Ex9iLfNbYDo7RWqAqr07rv11x6l/cjKt7MCI8AZDjYjDdtfmy/+0iUF9nKwOZ6J8Rxj5IVr/dRwr7gh1ZW/hXl5zs8sQY/Vv3+svu6WyStu6pnAM86sDCj4BWWt0J/ailY+A98//Ofm6iXc8le8Fmq9DqdIQZF/A7o2t56ySPfcP7uD+PeUSAKU9lZr1HeEI4nPM/zAD/rd+zK81dol0Jfu+Kgiyr7quMSFa/Q8AHrn8CnjZgsnTkY2Brg3jJIkMtvXR7uB0UePxsE+QknOcakE60Ef0v5vXQ+z+9hus7ym/3Ct17GsH5sX5zCPn3qN3pw8R8B/Lc3b/Dt/Xsc8Aq9dY9U+pGAf+NXWHXNXzGwXnZ8JOBVj25/MvL6k3LVrDA3A+VHJfpj+Vcpjwr0x/JLxb3RTACVhI4A/BlNhC4f2qECIIIcJFYmUBcP9E4NnYp6tdRAniBXjlXqWKlI9GEW4UEDp7pVKG2K8RO0FIB68yWC50j615H1z+L7L+8/3Pr8vt7xbP/8J6Y7FcIrbUMD3V6MiZ0/M9AwhXpmdJ9veILPw3FIGF52SDSL1Wc85jz30Jip2PW3v2qtNoJzCuOHLKfAKfCJfWnCp677bV8fJSEeiUIzWkzIrpvUIkwA8BDnOTyzM60YQ7pHHy0sGzvKuQ38f47FO1X2WkqizpMduf8G9fPFjoyI5nfuW2wirU6VCsxiq8FTBXDBiBkwIIHN/K13yvHw2EHOGn9gszl+dJ0yBr9n5oNfKlmYSXoNaolW8qgJu+eAtkdHuVOSTfDWZ0q+GPegCSpD6S37VPZKb6owLyRRImrVhbVwn3GAsYMNM4O60GupXM0V1Ltl8GAHqwJ2PAjlQ2zngoIOZkLvmtKWO4oKgrfQRWAKj3ersFBJ8zsa0hmu8vFPY8teqSbAJECU6ILg4ArvBOQ21k5A6SRK5CqC0a4pGBo3F64BAGvOUkubcdrgziQL+fqWMk0Tbx7E5TzWcVD2juabJZGOhEdrxbIU1GqHXImPUGtRA6lYJyqqYNRJZ4fDpuFEOxgqyG1NvQpVwItQfmcBt48hw6bSMJRYz9ab4kzdAxz0yoQpvneJQriksOW7WgX2svZKoxhp/pSPTIptUVyowMYUUN71BEteWQyMScLfE1mobo3k0O319H4x3lrHxphSGYW3orUz4ugk7GGpb3g+CM+3BicEQiVWY9aC6vyO0fd40+bGf1B+Ap9HlcK4Mt63RwIB0jnqHPxLNBAepQLKyXgJ8f1ooCFnCQY8mgHrQzcCMjxiqSMGHgbTeMfxyYmmAk8ugOsbHI83uiekXYmWUGARZ9Kkx7wkfB/tCgSLwry6oryWChTCQhHCnTQBMDcGSkXpXZX2xfmmrjwUMwPmMdlbQkUVRKvysjLArvPSHW/Iq50t6gP5fNmMmNLEQgvnYnzgXPrNhA8zOki3b/StMzx8pKEL3K1YzxzNHp+2974ousc7BEJ5QeifO8qLAv7MyRs8cQjaSFaeQ+sEvoL1r92z/vHV1rAceh8A8Fz57atI5dSvoneiTGf0q69oVwDRM+cFjVd1uLVuWraCYY6ER+DEKOX1HBTkSDhLYbtPzwckY2gNRY2fCId6iDQbzh/djw8f699cpJJoYToYmSdw66vu65k5HOtr/YjWCbUuznvJ2DPwd8VTS9pn7CGwoXiwNTFMseeFFjDvRENK86FkE8GBxso5JDqeMwOIGBP5Wo+4Mra4KrP9jFFG4BjGaUTjFj5oszbzfgnl+WbY2g+PSJPGnPuoBF7x5BgOPORPiheJ0SGGTKgE6h3ULNoKWaMRAQaGO0XBbVHhiNQ7sAtf0xtj7U3TGUB4ND+LJEW+eZHru8ajW91PuoTwHei81pDBcTh/w0y88lQnjHcX0nN4sdnVdaLgY2Q95rWLq+y5PhiT+H5OXdvpwun7fMuzHY58eHHb9t29GMtdCtb7lpMey/+ZS97uP1muKLyyrcr7OiK9YODAr1BAqG/H9BS5/lMl55Fe8Nohpr4VTNQum7oeRPh8niDS9u0rSIjtlrzEDf8WvEZ5U9DfizyuvCGs7/vst3CyKMsq/XwjZ7/j5QdA07h0Zhz/FLpyg49+jnnYwmEgMm+tO+Hgtr34r7hxHgCwdwphdCa7ef8eBcDyRs7269rc4/wfFDB3AHCkT3iVUP1J3vYORcie091d14/lsfwd5VGB/lgetOwiP9hxza5MgMSbbzsLIeaiXki9oTZVoDP8cIws1KGCWjsaV1QAHrKcpQ6kA4w1Ti5IL952FkoZAx4WWsLMfPC+Dmfge0zMPd/bKR8BuLfNLeUFgmh9tt/0S03/hysfBbB+7XsE45r5McKWkf5izAbC89xKh6i1KL1nHvK5TiCU6MbUXtHIhpwa0mBIeWuR03jSJfvfaoJUqKijM0qp6KrMsPrNozT3XpQh5IdzE+jYFu0c43AvL4jHh6RlEJGreaKYYNU8L2yvD/uR4DnQuoVpN+Gc4h/38LDvtP6DhtE9NvGoD0vRNFM/sq/3CtsB64QwEtBQsPCFG5XcDM9db8IKsBoiDbX42OfIAFlgOKSc1XCFewIFBqdssRlZxnshMMpCBfnXDCDy53uiLU7P80RvxBTdxpg7e9fCVG23+dsjvEt9C1UwrehsLNAKwgI6EKB5az3vN21EQ3A0c/FE6Ma3rw67AICzA6Cehb7GJcJY27RysqQhLIAblKzDuCkAQfaLr7eEti46XXZ0pvhwU+ajlyn2CAy0FgKxhuR5Lx5BRcfjeK6Q5H+GCOxMuaqp2F2QbaBuecSpjpDs+9SUNIDk4u0riCqYiuJIqdjCZpqyhbInLoV3M6M7bvO1IZKc3iWU5IPSsADEikNsTnsf30EKAmt7gcMQ0DYZ1yrKJhe4al85Kfs5vIMk93rX3NLiGTOhhvSDN/cHw7/9D8eyc/vU4ZTSRqpQ4S+AWguWZcFhOaAui+Yl1SmoBUutWJYFtVbUWlBJDCFFCS/eRiLAZfeCaseG1lbxkNLc582iinjEkoTHbPnjp8x3GRX1nXtS+obQN/twxvgzZIYglnSepT4GoYF6GbzBxUMXIqB2j3X9J7ZyrBfHVfZ6t/aJu/OqeXM7Gp3WypuZ6KKwudGBQdhmeMmUsAbMJNIxCxmbW9y0SxBjWpB64pHCC6UxjwZvURK1ULTZfRzyQ7Mbu0GdIh5d0z6EePboNFyH3L4M6cAI55FXNo/L6rX5WBUGqvIoooRWnOB8C8BtBZcziP99jXliqHEHYykV63pUrw+JgsAsc2WGAgsVMBU/x4DN2CR6abZoRBbuWPel7hMLJ298nkTGqMijt9lvRcbpfBuzEynqHc0UL2x7QJQvNnbDVuzKLwAk1Jh1H3aoKdbQAVszqdfxR0yb1ieRLnjtECfDER4JB/11M3xnJZTnc81z2ceBe57ou7+nahM3BSAM+SLJxIxzno18V3oDAMoLTa3yUu66dz538JWZ/QCWy3zGE9/0/gUIwFfvT8HTDdbL3/WrK70vHvENX9M6PUW/amB8BeEZyvOC/kXo9frls3jdPnvm+Lh/6aBnOjLFSxa6vdaaxs++DzNvLnYYpMYVEZmiFgIa0NDRv0p8jEVzoPfeXGkuxjbd62JiNJa0NUs9CJx11qhVU8j3gatMy62bMVBL8admbCYfJAAhw8mmaM78niFlazugoPcV4EV4GcRz82IHgFJTeHdW3gbGh2YOM9J3MI2wP18JDdRx8wjZNH3A1BU+CHNN0l/5zzkrymOkYbxUKO0jCt2534Hn8bblIWBUdrlWmryzQl+n0ZLh6VOYIOonYlBngLrIqXpwE6F0FgrkhgcFytNKP0h5zbQRodtCld3mac7o3CD2S7InhG9qwidptJ5SikfykGgNKjsDQPwSwDdwJzRW/so80LnhSuucSH3wwlmWBgFRy57DNpfTAXrGf3MJOwR5cylV6IbmKi8ZJp2fCflCX1vMNeJ+mSwjDJ6OWi9YjRNNnpCMAuR7hEEEcoyVcVxx9t2hJ/NH/t7Id50iRacUrNmB49Q7r1m8k3+X5/l/FaW8jfOV7vnD69d4/v49Pk+OHXkRX7LwUvUN4VAXlVULTmtq+DKXHEGTAPdaXzRyiqf9Uv7v8IdE1rr+M8Kn75XnDFR6jYYP+ERwRef6p8TGXN6JHKS8k8h33//8573g5gWLxCUo0CsQATeX79GJ8FHn7ObPPx3iC0X+7E05xY7dya+des/OEye+HwSomZ6PGCu+yhQzfy//bGT0m+dzLUNtd5YwKrv9i7u25fztS97eI8g6vWOhvZ2B//1eIuG+5ohM8Ify9B/AeKXfznATjgrGrybaflLeQLf+9d/OUt1vDh/LY3mo8qhAfyw/XfY9zeP+yFTsIEm73e2gwSATvKODqaGvBR0NDQSqDJAIwyxEM2kFRcMOqqhLD9rhYddaE4tz9QBz5tvprB1gpWNmOW0HoZcsR9vMptyJrx8Yn99mdfUCojR/CROm3X1o+a9Q7ktUmcUzHNDDSHICSEedzZwy5Lv83A9f4zEaL+zAndrNbBsBHkDvLmOJ+5Y9mMnnNRkqq9ox3acUOlkZn7GqEKBkgcvJEMj2DMpG7hrZwDdVKMTkaRb6kwq+TMBhdc+L40JmkXLAPYB97H8HwxUt0+Zu+suzgD+/ta1l/JUxFzA3xvGalPwsAbJ7hLDAY+6PCw6mA8Vej3MTe8KHsYxHg59fIVFDzO1Z4D/GioIliUWNFaLpr305jmzoocLXXOgMwPEg35LlOrf3DgDfZHkdJDDwAaJuGEO4e+2KKORZCMoJO5EsaLseUZdURIAIkbooQVCqHO4VuiKNdwHQgKR4MUEqLQWldTSdWfcutxiMtocp4bX5EOT2IuwqJwv5TtxBTJ79tgCenzhHpAEEF7Fr3aQdy2tuE+L7JHnvcprLLe6V70kFaa5QA4WyvydPTf0EKshnzdUt4YoJhYuEx0y40lpnDc/J3i/Zk5Txqg/nNGWnU4uPfZq4h2syTsr1mnc3QQ7Ch3rAcjjg7OwgivKk4Ibi6KoK9KXUAW93VzaHkqSpMHddu4RxX1cJE65WGaUWz3Frc7OLfFS5YnnMwYzmQo6kVCAe4GieH+MMRTFhaU9CwCzg0EG9aBhXhYNkPOLzzmO9g/EFAvaiCxkudVjpWcYfzOzGInkN43UVuHOifmyj1qnQfeLpJ8qI3kbl/gRHynQSIBEaSDz3hX4rbgA81L4HO6kAr96VGJCNQWGECc7f+xnDvFQJ7skp2zB7/TVYvmQo/GZhe1qNWKs0Jo4N6QaDROKRUaDGh86umEKQBTdQAfUpbKwbZtlogLIsWAjgdoNuRklEIA0xDZLws+Ily0P/ZR/qOqpSv5CErbW0CguqhJtXhVpWSBg/1bmjMEvIe8OSvkgC270d1bgn8JGsR6TEsFrdaCGDiH+xpad52/HIwUSx1ASdQWcEvhnXzujA2N6PF0r/7tXzRP/ex/P8NA0W4XPs+6dJkaQ71NYVcE9zN44aeDoWw7XPnGA4Ga95O8D3ND/2+wJ2kv469fcprAcjL/UV5Mr2oKmMr95ev+pq6PLN2+5f1ITxWbTSv3bQU2mdWdJJcQm8aMJXp4mGdw2PWISMlLLC2I8dSjf8NErGaphXSyjPAYAKoVIBd/kuItxsMEVcO04teo5R3Ge0QcfR2ir5x5NR1/7RiYex5bL2Iw7lTOao943y29oa6IT2rvWO84szEAjH9QjYmYojUoeNZJ46f2L3NvSXNv8OT9PGMKMjR4/GDNqQdwTndm3e1taFYfqMhskkyDu5ioQ/p2FtLzkMDJQZ9Dq4A0wd3Akd3fkj+SwBq3/bJTJdr+Ca+pX2PpidnwRYjdmbG7XLf4o5VL7Fmse8dwkRH3I4abcBKK8J+KAh/CGK89Y1VY7W+VQ90T8qTtnwLHswP1zlMe9MaWyRkzI0Y9ktbcLwPgsJnT8deN4T9Z64fbIM/dvBJzN/vPfC5p0HKpafe46KmK8Jf03UtbvK36Lbcp51vH6I0t73E9XJ3VcdKHiJ+qbGXnT8L/v6eNnwIe0vU84vb96gve84e5fUMzMeMcOR7odYvODkgZ1oDUjdCliUnq+6SBoqPoLwGgBp5DN5d71c0aHORBx4+VQR1PUKy9tFzhfQ0O0sMs+PFOHms1z695QNIfqB7353+dm+bevZd8359fKRRJlucOQwWSu+/9+QV30gCdvfABzevcXXPy93lfC5z8DP48LblOgC7D9R6WN5LL9YHhXoj+VByz6J0ON3PjX5KVvFmXtMjglUewetDQBjUcaZh1BkhkBFSGYHba+PQ5jg1Stj27uFC8wCgmRxqoj6s957waMSPQSLO5PxAJxzB/AGwOkM6ND+SbFw7i85rCaFcdGDyO+hu395eaiwVlasrucs/3US5dGHMlr6zk1mj/L8PGfoIkRudWAECd8GuB1UfvYMMIQktVPo5h21oPYOMNa2opTiOQdLqahVOKS1rcHAsAq5srCR8uE9Dg/ReuQENYZavDwYVS11Wx+DR3kYPxUYzKOgybMjG/dajtrzszN8v74GATjUBQXAdRsVlOTz8DAc2f66Bb4xL7+EyeJtTsIIfckdKDjhM5IxZmNae0q5ScARrbc1CRyYuitARUlpgh/z8ol8jz4GJPxiOHkQ0G/bsb5tRCy9Q457ti48gu2dy9L8oAaiTfj6MFAhyR1OnFoDJHol4ezsXGmG0qwUIQEA+Pq7/LYc6XQufy/UbIYZLIGt9BCaIIAh94lQLP9rhhDObNmiz5pfi6L8qKty0G0hluRdFVUm+BJQJvXYtv9iQkOpI386swiwbbwMcCdQ6ehNFCWioDEFD6Ey0EoR5YsqWsSLLPaeKb0MctbexGPdhLWqyDT4WRujFpacv0TiOUYFXKqGGBa4KElADSJwy5kbx2KKTXVzciHDrMhWSffw7eihwkAT3sS91MmE+LkteGi7Tl3WAQUNEv7Y8hfLZ91xgAjzYy5sHWf+xW+mMnsMRofSdzRghqmCzY4UIxnHLdZLvS5FYKBWHJYDDmdn4mleiofEtYggRXOfs3qTu1JE83f2tqKtDW1d0doq3vfmUQYR8EhK5yoGlhzrZ+vD5g2rqilXdCf8JDKn7veIs5FFrJ95ObsitluEgDBssLllQPAJKw/KiLymDndww88slQrY2ylp3TwWB5NEfiglHlMSLkilMM81S6+UtXPi/d/jfW+M3KqfSngEZvpi7w4hXl1BkMZmdK0DSyUABa01pbEz/o+OEMk3nSRnrMkYfR18TbVywJXinmMeYZABLiDcwL0W9X3bsKOZo7TTFByK77+YK6N3BAKKKMnckIxkebqmd+idRbmia7IQQcw48k4VvAUQ6vkZmBlLY3A7qkFEAbUm68EQvMuk+NPWXoyDSyFU46+IQFTV89zaU3F61SgRrTu9JC6K/wCLMXLx5Am+f7tCU4CvpQBdhMerRseQveJDCbSkPwiRu70TPFJDBdQwpmn0DdYIYx3l5EGFlBoegeOCelbRbmw+CZED3aBUyln6fXcId4p5At8rRLuVOef5qVHw9I4of+IMWgDQy+LP2+cG/iw5yAnYKAK75ch2uv/F1+HbPXjZ79M7T5w/M4X6UwgX/gwCHVdgfMWiCvbyXPAtseRQP159Huo7PHs+jpcI/Fzyo4MA/trBXEDU0S8Ix2a8uPTL+PsBa5AarWk6AaEPknpg7R39O+PsuXieH9sqcOjnDqnv7HCO65trVPViN7zAahjnreoeQgvcYXmZgXGdva/TOQgsz3qXXNWAhm0H0Noc0HYHcjjW3emvHaCUJkH7RGa4qKDMzfa1wpPi/vW4+oyeX1zgeHMNYvVap7btBY2cg+eFz7mkKPee8qfT8GK+BdJnxbk6MRi/xmaQFaXt8Go+LzZp2PH8S2DkPadBRR5jBGuY+6kS49860AsAtvDpCUoTjyA35YbBDvXY43H2tKKpbFS51VlylVuEAUv3Awiv4eBI4lkO9VYnqqhVDDqErWeHE4v8I/9J9J/eIwKJ8VgOX8b7TPPNMDrNjvPHh0HDfUp8oiPimkW/sYhxtVRnx50vSfXOuy8ULKmHHIYvbIxblg/CeMIMN7nz+e9+MQ7ubkzL3qy/e4pI3KPMMrD5+r3Ou8mfPpIoNe/yHP+FLj1QeYAeJHz5kNUXvHQ8+oLDONdCvRcA5+/eOV0vVNFWRm8NyyL0R84rIeN6w6/R8QGEV2LE9UemU+z4Og0N62V8v7xdcHM5vZBQoHgLS/zUjySK0YrXcCO7y46uzxl35D3fzMdr2FkLRFgvm9g5Ksy9ZKCRvXuibBD0fP/UzuKdy5m7Sp3JAvsfggEe/mxoweZhtDfzovL7Dkwx85ED3aX95n+gWASPdMMr/EThkV4BXPzbv+G4tiFk+3978wb/5/17/PfXb/D9z8th5Puh+dNZchzYht5uvnS5Vfxn9x/LY/k7y6MC/bH8cglPBOwixBDST084iNJwWDUCwXaQXTV8ZwVVbaNLjkwhVfE/q9DDXiE8UYT5JuyZpmfhmQ5jU16kfr7E/XOPb+bhB8oC4D2k0R/JZXylRPCTO4JNJ++/sJwU1v9SnXEQeJGWc0+p/iOhXZyPkHMxnvX9o9MeU0QTwy6wuR9mde/7n0iLfLL8Om8hh3RTgAB2iAVqrf7MjGLGc6mpHkcBEhHpd4l95LGzKp/VOrK4rA88rxzYx0Oy7e9QYNpkSESJ43F1odZwgP0d5S6uML+QBAnjd/fsYfpGxm5KS7+zU2bRQwg/OljV5TToXYAkoNA1d2Us3QK5PwyLWkeh3TBnd5WB9mBBPqjulVCqRwW8s4CnllTCUa96YDafMlGcs7l1ZlglgHAG4Cg5vY1eIVbLDuhjWfypCbEMx9iXe/LEcf8GHSg0t0L6PasnrQi1mTt6F+9G7t2FyQxCZVXUFPEcayDNo0voVFFYDGNckW45fT1rohzkwlMr8LVExdQQlEXeJg1vXgiirOfEVnAaL9mApwW0+gnisZd4gzk8tS/EcPK9RaBmG2Iw3hPVm3gpi1I2G+nYq64UNFhQ4axM37gJDVXERWp+06GpJDYgY9iQU5ikgzbzSRCeymCueF1iUFFKEeX5UlGpoPAYWhYQQebx5phSeyi89YbWxOO8tSa5z/V68PjuRVN/SJ+yx770nyUKgbiFpVFGqHjPdcsdKMWFqmxKEu0TVHDNLOYNrUWI8AF3AyKABsDUkzd9UjJTCNr2ViiWM+hTLGYWmCQhAkWECMFZsfpCH5USdxmntc3W32w04q0YHiFVyrIaLWwpJqd/oxDIPfrFGIRK5quDpm9Qu02pGjNQvq/LldfDmA73PNOQ+bN4SvaS8jIavjmfFYY9lPZ32ASwhh3naE8G4zgNMCNEy7XuFYbSgDu6Krbt3WZKCzAs5MtCECOb5YnDMTGLJzsVgMxTVLapGagQheK8kPytamhhAGU0wtmNRPRM6SChfnVMhXB+8QRfv33zNBbcwzCFEwjYb4cqtoQphHI4Q19X1GKhl8VIYYBFU8Sn0plHb3mKsNsA0G8sb/UMTAcA1/GdvmHK8/Ph6Vhm3vka92NhLpBp8ulvaPj7dGjYIKe8IKcVBJIDJ2L/7BX+nGBX+3Af5fluXZs7li/9GRJ0g/3+89GIZq7vS7r/LDMpBi3fAX4SYf5V0Sf8AY2HI6TPld46He1JUXYRbW65XX2/dTUKYZCmJDFPcHKcqv3oFLyh4REzvFJ8aeMxHODwoAp5XllCr+9O0t1rtQfpazuictX9KHF6Si+OQ8nypLPhXfa9z8yoSwU64+b6GqVmHJl450mAH7/Yac84u2Sf7QxCoxvR+K4hJlurEJQjGGImr3PPkHooif/bmzejUICuM09r53KtknAbq+2drH0nSTlAHeKBTnZmRjL8GjoldTY9Z7Xq/HQBaQSB4B1Emd0DR3aJ6tBbRGGE0jdbT1amWEK7M4gagIpaWKIgvSrgT/INtH7xQlevdsXzT5k9RPWA5w1XJ7mf8zbGJ0TXhrHLfkixwRwNTKvjPBanRwxw8TnyM+hm4XcWem9rbXga8i6NxwbefD/zbfb9HMT5JK6+88bDlsBMf2PY9d88xk25ixD/RDHHmPqGgPev1GXrEwiv8JYLOt6jaCDr1juWWsU40vgY5R977ygMvGDGZwLO/1hA+EPlY4j9oLxjb82NwxjAzeWltwNIKPaUKEjPtmPf8+Xh9Vus7xvqm4L1/Xt/TlDluW3lE8UMBeyEV9/WlF71o/Zh5PE/kXiiP3zu89vKXw102zYfpAd2Pn2IumBrO+K/HHbdfj559xYMxvXl5YwU8f/98Qe+/+OfHo7/1RZNTm3+eO+zwnzv+rE8lr+zPCrQH8vDllnjooVMcqP+c8aUMsZMrybccQEp20FBA8RSAUgPFtC8Tb2pB695DbGGhdcuSdWwP0RFPYlGIR27CW9wXcakMzM+QUKlfwTwGqpEnyiGH+5+bvY25X2q966wLabUt1zon0uEdHfF8n8S2pMPAZ9JjAU6Hs4zfdU67OBRWKwobV1nS0qDGJXjmj8ICGHMAMT05/4/ZeCrHlSfMd0KOy43uqP/J7bhydJV6WWeVCaIJvXYCGWAKs7qgny4FWVb7uOoMDDF26nxFM21bJaRXf9ymlkTZfme9N8RhULyrrIIjpHTNPQ0d3ZCAGImxwVy/7BTQq3b5jZXOeGDWQiVZQPSS4iw3AyRaNsPE0IA83YxgQAAIABJREFUNj9WpalAphb2GO/BGkcFVxyCjY3Mx3J9zf32dyYAh8s2R90xTa+bMsMB4SxV2kVRew8luuTUJvG0Gbq+DmKNfZFJWrJFwmHiJjxUcUYAqSfE9bXM1dl5KBaJUC6k3/36GDUSQAeBMz6qpzitPm7gXA6dvcW6ETyHsFEfoZoHEAhHNFzgEJDPkmfdBOvmsTlCO6HW4nPNINTB4CF5XrlQUhTdMm/i2VhMEGt7RKVqEmZdDngVjEYFdCCQCqc7T6H+mXFWDyAiXK83LmQ0ZRSBHW5WFRwUDsVcgRrZcAOpR3oBPNdvPmS5IhpwTx6BN4E5j8SZFJ0OjqqkklFyWjeAag3lpSAeNaQYDSEczmwfENQjNYyLzNuZGRGafABQxgi1e/vQ1s3+tcZyPWM1g1o2GVb4M0rjNZRZSImbCXnJFdOtN49YwqSeUko3LGpBZxHUd+4eCtvwRFNv8w5TdnNqR9eAOlr3KZfvk3RQUD2jEYOaKs5LEtlkpTaU59M+EFgjUMDXp6vWtjGjN1OOK50hBF4koDf2yEjRZ9thoXgkVfCHr9q4RgOZNGExxZqYFI8QkRFkaAbppOPs6FQA7qCOUKTIwEe8C7jCDgQNVQ7PZy9O7+Ehl6FxX/atqicmA5c073cwJrRPJwqJesg88ORVnQj3DNV9rXvR+QLjJ5z0R5SpuTAzPPAKC34rnTX1k8wrscwruKJw0FhZro5yfq51CTxUKkpDZGBHjXxjA2VVdtt1XaoalEQPGZbTlYBanIUhghisFMmXvlBxQxCQ8UmBu4kJFxeiuP3+TXyriRnUWsCgIrfjzREtRRySXLnmMd59BguzG5EA4pFpynbShOe9KG4vCe7sfDfwersgAQA41IpeCMfjATgQ+EY9Oc8KcGQUHJKu9QJsvuOK6427uJ5rphGwTcC4y2florfP9TJN+27/x+unfiV7TGgtAeAr8cA0z/LlZQUmPsbat9DtzmuyhFGfledPIB7kBMKVxiy7SFRDUMsz560ZX/ENjCfTO/L7mTYvudT7lcA5PZe3Ds/F43z9cqXvBf/IXxjNFe+6t58+BTqhX9s9m8/ieYxtz3JSolbNDbs2ifZhOI0KUFAUf4+e52LwVXA4O8PNzbXAr0Uw0X9cXsF6NmKJckIpks/xeMSyHHTO4bjdrg01GULrrQku9geCjGRbMkbEf7rsvRVGJVYnOx9TwChVcDdrlIfWZa/3zuBuuEOfq4G0m5bmcWw6k2CD9nn9xFRgvgUk4x7afjufGf2SthyQXAqjZQaesHdo51Udb8D0zthM6UWTupYInRjoLX0vxkpChtK7zA5X/oeUZy3Cw0qEHs9jJMpvViPCHhGJzHiDOXugS7o127duXAYzCiGsTSI+iaEFg9pzEBWs/YPwNOqBbspzK5ae7rPC93PF12sfIxyWYXFiKYZr/WucD0iMjki/vVa6HLLCSAPi9a1y3rHoQEup8ChhZNFnYr/3btGezONe5AOj3HGEM91BmwEoW4P5LrN9z8O7+cfMz4zA8BDl9oru61F8z9d+ovy+mk9Vz0BE7BiJ1w+XF2m5CoD+Ps5bBS893DrzW4idi+zLtXWgsaYPjc40buhqpviageM/xLTv7N8OegYOPM6miIfA9/HyUvvyEYe3b9GZsZSKld/h+eWfIv+cWKmMjp7r7+VtRbs0g2g51n2evtkjSS/Z8p6/AkBY3hbcXIb7u+E35pCfftR6HA7no8CpNflVsPF2NhsQu0Rh0/DU0cx47dW/uT9fR/2OZ+5TKHQjv1IS2w2Ah8iouXwkCdFe64K1tSFn/b+r4ry+eweTdlk9n2mc0YxXTQ6QHt7C8W/LrEh/LI/l7y6PCvS/tfwI93Qbsr/v9w9fZgXT9sCTGWJg9EKf3rV/E7djTIO1sywS0pYhBwgRumoIKzA6qc20vk8cfXLmHOmwZ8JMtps+stwjv/0ZjBcIg/j7eqL/jGJ9tme9awU/6ztX2h4hMUR2SP2B9v8jll9VnlteKVtzgwICsHAo0cUj6fSaBL/E6d8ozxj4QqI8p53v/nWK9Vx61l2Jbkpeub8nWAcQMoQk1uTB/MDumcd63A5/nHg+vOvtUexdhkoxE+OGLPyPxT2lG3/QkqeP9h48cKFx3KRzEwKDjIftOrHyjFFJmg4SnL9HKFusrfw0LdzUn/E+YwYchrhzyFGVp1D+D71BwgQjUxz7dwWwgI+QfOZTN0iFWSH0GQ+ccYZigG/AWkmhpDgjjhDLyLshVqakVSAARxxRsICxOmzH0xxiX+6NWD/2hnugk9FI9Rj1w5qNTZ9xHKpF2RvSIfNYBTHKwuI5rcLmqmEtLT80kXnDerZLnbeJl0gKZvMAFW9NFWIwgXqHyL7V40oV/YUkHDGrYqepgNnyjcLGgR8rlAm59tkF4klqPtdrqk3BUaHU92c99oEJQdk0j0MtAWQZXr3RGQBnFHMC5YQAUOu2MZhCUtdP5rmHsqw39F6wrg21riAqflBmzatpeFbyXjNurm9EIVEraiEUE3ayeOMiKcxdEZAEyFREieJ9H6RkUAFpOrA3G3jHagpuUt4QCOMFGyezGgBA+y9K02beYDsTaVijGy9pXrreNcWxvqbyX9f19ECuO4KBWBkzIgnPY9t7pkApyEpynTeZXRgAiifbhNEJAGlYb1cGk8P2jBudarD9M0yEzqtvkQE0mXe8z9XZkQfuQHtI5KHL5w99LwfBginNnSVgiQbiwnid0Gyke1ehhKM7QyJriAYG3fCY9rMcLkRJ3CWUrqcDYMNlno091pZEWcimgCmEslT0bze+TgUEVsUgOEIwFlO+Q/I1V4UJtsmm4jjT6Nb36+8gABfnFwAB379/UwNKgA6a/kCNRxgkCnbjnRD7sStOKhQ4bTTeURpJNChZOgUMGj8n62b4NJDovDpEJMrzYzod3fQYM+K7H8HvZ0je5oPE/eFK1Ph0Q5frcyS+rMrMfGbQi0zDR+LCYOCz4i0AwFd0AN/2YJqs+nj2HexKdKta1vSrz99XsId0zz1mHYd4oZPfGYXChjn28KXhxYu45yldkzIarCle8jf6jvEygHuvz+lUKFydhR+hBVWVlUtdYDIASedmXY55LqWgrQ29SUoZ6F49O5zLeYggHuzSqXHsFgWl8YQnHxC2dgyTPOUEFfTWQVSNOwSYUUuV8PEWnUKXry6WCkX5uTSW+8isx3cyTp7uIfCeReQJ2VHwIMC4ftoT+X63PwRs7tO0LnAm1g0uTg1GGd6ILMLOw4El57k1SUCCg7HOzqxhjY2mAY1ZDFMPjMpLeLZD5FltbRruvwWNEsIsaW9UOSzXsVesj54mhWRP9A5UgtCQ1wB/gEfkYe6RF11xxG7sPOcnRJlu8hae5njv13BNDo1eDmCs2GdbY02Enu3WvUF5Wzzk9U60YvNlGothtkxPTv3F9N6pHv0IXfqRElh4vHtvRd1vLvOK/PZe7QHTbY3udSotaAPQ8AkLJHR5fetEEwwJq97wyfcOAaD2Ch2M5d0CUNEtK28sb9+iUsH6p6oiqWjUHcOLDBRyY5n1srskbXnzVpp+z+B34jRSAbxkMTR1ubSNn8VLuOAVCsSYpL4m9Pc7iu3pOysvWJTnhzdvEo8Jj9g5Tde/CNT9Bym3Ij4MRhAPVQzcP071vmLg4u1b9N7xvy//9Pv/4+1bEBHO373Dlz//9JzpGVTy+tMpKwyEDmXD38/XFA4eswL+sTyWv7M8KtD/lnIbypix5ENf/71FQriKB4exAiI0UwEtFRNHgWHeK+r9weFZ11UwLmEQNfwnicCykwoBLF8nAxUimBLH2j4cDuQ8lDxavHU9iBJU6C/3ryBMSlbp6ejStyUxreMa5C9/6Jq0t0p1tgp2uX4JU+6GkvHjvxAM/I7ykIzanhLevPqtfKZQtNt/bec7QjAYEntBmV8WBXrV956rNODqR+L05xISqal1Y1Hy7/xcrotavTa9PhwO+H59g1LCwITUE9WbY7jix44LvgO4ozBjCFaoDzt4yFkeOqkIKUwo4YVuijSwC3U2B3SG7wVJg1tCkUjiscrormzMO3KelTMAN7sWq8APbaN88vbenvCcmKo3hffMNE9igKmoMHqw+hQM6/LAJIeJgStyddmGhkAGgTQwmNkkOJjNIRi0LgvbKspSi2gQCmHmPNuhQggDC3O5kwY9pHJn7MOvjrOxeqFPXSLbEnndyZWzftBVTyIcjwAdwGcFRGO+TACg87Mk2bO/+puAcrbIPBylnXY8yt4/MEBHEJ2BqIGPKwotYN1fXW15TUxdcJADuXrQn+FMDtzQyA+I3JVm6Q0CKkhCn6tbbvYKNOgLZTlcgOmGbqgAq/epP1Olf5EcxjaP4PStHMklp20XRbx0rMTBJwnf7NeyHAKHkOY+ZMZhEcG2eJAojabiIe7EU1tDxnUCSgcxYamLe4qZcq2hoTSSnL3M3kZJnprhnTlDlvU98EssvXo5cShv3PPIaLVuK88pSTJ+86BFKQ4+ZihoCljt2NQh36QJXjC9ow3dgqt65ncUx0bo+6jOlNMZb4U/N6Ozev/RKvldOfKRW/h1U0xIaGhGVy+i2itaXbDUGE9GykRAJ/U2MtjpGqY358TdmwLFRQZbpvhmjTwEFmPLyhHaXKo3GtLRu85TN9WrRD3itIcsFLd4lJtHrvzulPYYis+rvDUKgWesljlJJuDsUDX/KRI5d6Srcwvth9VjuEUSRRAnJXpqz2kGAUSCTIgMhMIgxwwO9v4TEqK4VOlETmnTlb7kUKKuk1b409TuamOr86Lj9agcO6EpnQ+m+E0QRXPDte9dM47wSeZEB3NhAwmlWxZ23HAAM5oa70iXKOYY5yhLAaOAC4NWDdmp+62lRlhxECsuQy0opNF4NFqA5MDtsnbWVdv7ui7G0xyMdpDRcDE0ke2jEYZ0H7X1CCLCt/ULnjx7hounT7De3KT9xEAvaNwAriCS3PXEovhpFs4d8GgR5tkHhgTM54AlaD+ZJJoTp3cBVZCCRcOzsySlLs4pMBhnhwU4FNysR+UrGDgK3MQ6MwrOwbh2mJvznxurIYasT3D2TPjG9u07OnaCwPN07WhLIM/g2/AFTd+Tep2TvlmfCx7oV4rvrsSLu39uIALqy+q4bJ4UvspmWF91HxG+pRD3c1nxZZPvnACcv3ot3m2fP8JQzLfU/29gnINA+ALCU9TnBe3KuKlnqC8q2mcGXzE6vqC7goxAeI6GKxCA6uN/KtD6VGC4f/0qSkB6Av7OKBfF4WMw9FMccKgLiCginkwjGs4NbJFrCpaifB4FzxlGONA51BoVkREBy2ERWsJQgzzlgwwXWycGGmz0X7yJvZc8U1FxDGBWj1lEKPof87QKWkLpqhbxMD/e3KA6X9VBlM5zXeQlzaIhZQOSTGKTYcs4aakbEynfVjLSOKvWflB+aX4vjdT6OZEDN4SzfPMEox+pMPvibZeNnV91JZbS18SeOI4Rj3CjK2qAqr3KHsstwQMTQUKrL55qRW1O5bl+11RRzoqoSpH90Jg1rdJIw4zE2/CKGpNILvGCBqAqXaY3AP3zOcANHR/csCsHWTYp1gs2wxozePLZGv4a6QgehB2fGGbM0q1vuoZnir7V8jYWMmqF8VvQswiBfL8Iz6mbFYS2iiq+sfTVo5zY5ECxU5ItGK+WR5bhLfZVjMbfVbo6pV6P79mux29Poo4Hvs4YAZtnv7NsW3rIsbmB6ol3H7LkeiXK5Adc4K2eIVnvf9J+yNsrMyo+4vD23QBDrkDXCG30pqKUMFjv3JDJOCnMMyLiBfRsvrwVJksivb3GJb3f4ETbwwWvUN/I/qql4Ps//4kTCUV2ixgOSJ52gHDzp+wz66op4i2H9ue8lZ22YrtIp+7PZR7YXcXr2/lwh6favmd8H8flrf0Io6XhxZ12AmNOSGPbuvzOcr30/FfKrDi3UiHGIP+giCzwP9++c1nId1WeW58+zhxY6mspZdtPO1Oe6FfeJ/I+4m0nevvfPZbH8leVRwX631E2xGM88gxHIEKiOvn6xPu718A+Yfj1cuqAJ2fQQPPD4ZRC1MAW0p2E6TC7V1GeC4NrHjMgxqoh0FpnNJjVLDS0aFPlgZInUqGNMtbB/HIckhmgLJTzadM5pMDX4uketRSIQOyVfvZBh0x2ivA3o76sQjBhX2Lnh2t7T85Oo+rttnP1JwBv0sGQYPnQ/zq2+a8uvzuvkzG/WW94lei4hY43pfpdpQB414EjbXemLrhe/OjARobD4Ho8Ohks2bumdCUQa3QHZhyWM/UAZjV8sQOiKLhlQ49GHHL47+Gdz/HUhBHinTiGOzQvBIbtWbgyycKgyl7krUAtjU8ET4zIwwrnZl0YYu8abgGGMdx4jT8JVLd+euphHK9v4+lvMejcvpwwHqW13nZFgXZ+Zn/MS9p7aFNKY0CR/ClBYSm1ywFzI14M5Gv5+xy+pCKERifRtckFJYdvN6XCJiIKKtzbDVkRrW0QAdRAHm73NEuevaTcO4WKKs9DcGQzpy+CsYDQ0LGCeEE8Jlci+T39r5OEgeOiq6mKa3RSj3ZprOachQjhop///BDLaX7C28iVHB6q1OJFxyHIQqi6kM7GX4oYSBQGVnKDovDyCcFiVBA0T3CCKlNOmFv7flXlJhGAIvm2szLZ5oeZUbhEeGpO9VA6Q99jq88Ga148r6/yMGwGJNh9n70bbNk1p5yQ6ZtYsOi/Hlx/BDvFcV1guphBoLGZibDlUIN27eMgDPuQAfFu4oa1kecsZogyoGnI57xXehfPq1YYiyoJLZQ7WATNDhPaZs4NaiFKw39XUUE3hU0ozKH0yOXlpuyDwKmEei8BA7pmXT+QUKoMUNd+QfKc570FwFTr9r+8ngygkynXtV5qCX+xKqttTTLnBp2zhqUUrK0nOI+97iiSdY+Z4YH2jbmgu0COHTaJ4HjOvhMDKM38Sg4GPlLzRmYLaw7l4inouKHr0gGJds7qjGl0W5S7MudaL4LfLZ08lD8VcnpiXvEDLc8kIdF3xtFhl/SZK1dLfDcYYbDVoQpu3xNqzJEwazMv9N5RioTJrdTBnTQ6R6IpUGOfzPOUQPZEEm6aQILcblZpX1NUhbkF+ZrITBQ3bqsgx98y1SQGEdzRCCBmlOUMRGbAI219+3KF5WyBGS5XraPBQpEafyB0oFJFKynnrqbNsbnvCh8S7jq8/s1IukM8pcyAWrov50GjN6ZUykiObSEAABJC38braSUUnuIUdT3gkbRthmsBhW/gr0B9/hzZ237gM1wSnK7dyEj3FCxdClxBg/SGjdX/owJ6LnNWngvPVF5W7ygTgT9b29af2E9MxmcxvmVE5vvCR5cGLs8vlCdjQMNeh7IcEM/zbwkXC3n6go7noOdA/5yM4J9ryPSrpyBRjekUXo2GM8+kB/0Lu4LRIluBr0E4H9CgbBv2ccscpH2ejDFmfse2oBkZxfQYrIaimhngJnBcqxjENKO9IDEm1k8t9Hf2kpd6zIObndbYmQQBKjEM74vu1Z8suVrjBZ11IPFYXg4H36OmYPYjkqwC7LyWBdc7XFj8mvgVSpdST/EHQpenWATaSTtfWF5d45F8zab2bctvxo2AU+oBX9Y365/PCwsPNuhHZqW5Mw/Rfh9sVEKpTGqwZNwieH4vTRxXCc/eBa9K3nIA6Ko4t1Q2McLeySPm2FwSQWgOJV46zxQBjZXU9C5GmySGWf0lA43Bfz4D8weJ5Gi8sc2Vjc+VxNlwZ7s2PpNk+9L2be7Z3pcGG2nj63pI6Xr2YMV7oxEKYIZYUfxEPdERQ4vG/zNiL+br/LyT8Tv5/RHN8nSd90K+3pT07Xx9uq/ba2yuJ4SzOdPeda1f/zxq8uYdAua+7rTM2O/JfbqRccHw3YwksHPtHxAceej2zxGV7Fsbi8Gf04cEyWImo1XpOUjk1h9x7O+wXv4pXuHvxLiJiNDXMLUkFgV17x0dYeDGl6uGjg9cfYMPJwf1mYDX/BEVb9QBTc4kt8pO05y9ZuDw5m2aXKm/ac7zZOIJBvAp72H7cxfaeMhy27juXXY6drKvMlk/NZSdj17ymJf8rywFr7DqugLAf3/9xrm5b//4By4p8tnvdpEC1oFpu5lCRZkxZWP9t/Me7sUB3xdeh+L0kR2nWwDssTyWhy+PCvS/rZxiWmbW4SGu5/LzWDm81e6uwxmGhNREPmKKvSqIsVIwKQBWZdpJFeekTG3nBtbk1N08tEpxLyC0BvQmQlEULIvkHWQTfqrSPQSkiMM3wvKVTBppVlJFyGIhcs+wKx3PS7PR5e5CHzmcGcMKR+qxIrFGwXj92rUJ959DrIazJaDQKrqVIP/7m9f4X+8/3Lmm/1WLKcdt5V6m34D8npXneQdaRrmSrgmyHn904KvyCU+ZNDug1TQv2P4Csq2ynxSgFugEU8+EEtX+MchgzbUpufIAEbaLINDYdQIzqSU3++HN9gg48g0yiSd71+eAKDGaSh1YXMQjLxSr4ED71Uk4I4NwT7HAAGNVwbCGaSYZAZF6mev4RdEQO6SWilIqGAXMTYVhFKGeuxFDY8VILOJd4O0s2rC29y7TAX4rFtLrlBvXvFUzw2g4a1zLYFYbqxGRr20wnfJLBXxqkBMKcFWmQJSNFpHAFY2FXTAUinbBQ2zTZGdOIg/PWlS4K0tbxJszMcuCWRMzXMjrFdRJcXJNh3/ahJjcm9P8rOo8NT2ALjo7CxgNhRkVAF1cpHmNWXPilPC5zXuvyrgfCXRWQOcMPkordTmAsEZu5XYELQAWgni4d6AAxVgxWrTFBrTqeaILVZQCNKoo1LDgHJ3Ei4VAKAxUVKx0FBzTNbyu7pum62shSMUDSeb3cEjJKKiigDTnOWlecfPELzBHD9vLUAFgXWQ+C4kXOlT419aOrrnKC0m4bsMb3DtujjdorUuOYLAbwK0rAyQ0nCw8O1SKoQqhYnyIj488DLTvUFNgaUjkZTWvZotkMRmYnIIf5TGGfUeJbyFOvAQkH3bGEuoBUyoJLNZoWzsSxfG2N55+35N727yUMBeVvRf0Kft45av8V+a1FFa8X1WnRkAp6JofuimO6l28z9lDn0vdhYoIgLtwY4XFu1VgQibUFeYkilayPQZGybmWlb/sBOfNSO/Hdg2FeFauYRCCW/06D/l7sjWG5CklzX8KEaR3NL2W+etkBhTaUlLGuyd7EiyZ8ifjY6riMWYYqCl9NG9oUV5bugUyaqu2DapkLtlwtbkH3AASLPtaBBQdIFHckea/FYUuQtGjgjfpf1ful1EpFKRutArDNWpUwN6kwxJ079i1dW9Vr/8OWd+SQs6XQiiayzX4Ak0rwEd/z6KhpN74GrujG4173/LeW3SrrnuhqCLZ5PMrJOJFa4zaC6g0FHqCjiugaY5xYpRSUQ4VYKF9qNKoK8utX4rfGJZ5WBX4LPNqeaCzd57dLyDQUsQHvjMWnKOVG5gxWmfG+cUFbm5uJJ85GL03VDUSEzV8GCcYHN+0I1bdo40ZrQBtARoR0ItaFEukIUD0QL61NDWDRQMpVNBIDBJKGoedxcIgQhgB7rKn7Zh3fnYO7h3fbr4BnXC4+H/svdl2HDmSNvgZ4BEktVFSZvf8Z+b9n2zOXHRXpaiVS4QDNhe2wt0jSCmVWapuIk+K4RtWg5nBVqE3qFXOia0BhdB4hpuvUAPhAswPA9Rlkg4CLolQrl6g34qquN3ewgxJ9gAedFMS2X62oOPGqcivortwqoRaqnqRseKZS1eqAgy8lMmS9XBA1H3ItpGVtypA4WhfoUaiCtwqPiDcBfKI/eV8jHbcGDV/Lutw+PwZDHZluSnbv6UW78G41Crpy2eQh6FnHD5rZBgUqZNM2WzxNsJkkb/B8WL71qW1Yga5APAAflBzjgvJLl9IVBBGzltvEP5STNDY0sTY6Nj42VCGikK0o8+B+KvyPvNh9jqUgIArodaiS2Y0T6dYab91uSj9YI22YvTPffNcMW0waDhP2pvnQ1oneBSXJ6WXAIFKMrFRNC/GbEaHBaZKJdRSQFXlFomdCSNl8rkDguZY/UZlGcL7DX0k0qgTUTGlHw6JduAzmlRs5UrgIZO/GCzB6I96QzO7bGicDR0LBy1y9t266udSHhWVXgsc/xciUG9wI1IiFFb6aLgEYbwnI+lw4r2xhMLTk57ZGH1umBt7fZZqiCG8VejwWRTeRfcaZ25XXyLI+nblS7U+mvXNPuPBYJqB1joO8xEzZoCVf2cAeC3RG98S2s1HUeZn3gUaiZGAbw4Zcra3vpL3LiaCQLjUcd4rf2dmTlQoeCI3gjf6zX4mBrqGB9Z9r0YqZojT9FpkDSn/tPbKarFumbFh0/3jkalsWmNhnRfkBEe5PnuOof50nUHCnqffjgZPXFtd/B3XidPwWQgA3brG4hmnTn9/4fQ/nvCXFu9j8fy7r5cNPKWC1AEj2yamKvr88A852Ifn+fi5nbTah4by26SRe8QBDLhG+9AwA6j4hH35HY07SjLIAwAQ4f6f//R7gVY+AfS705TWOy7ev8eXmw94ySFrzH1qAHBzYzv1Ccpz0rDtjIq3IJWXHf6YwfgMieVK+OS8h1T4Rb/31GSLyVmB0hYA/JmSQTdfZwMSPvfBmYpocT28+7QBZD579amWCslDfpPopuHeQT7wHWXJT1j9uVwzcPWfF/h//yHXv7FEyJnnGQ83N+gA3kINkzn138ZWRGblJuzG3xt/Czg/FgbRcs9lOnovwrfrJPhvxWjDPPCT+KXn8lx+VnlWoP8KxbUYmYqk6+Xzx95fXafyE/ALJQT2lDIwFcLPIvpnMf7kLckVJTlczLvF2TqGmNIqY0yW7w9FcjvVCb23QYkoXuKE4geDxMr5e+wNGEK3PGout7Lfek61HJxfwHjDIjy6VuY7Augo8+9m0NmDLYSpq2s2fjjTAAAgAElEQVQ5vZ2+3vg+K+XznH/SyTNF+kklOhH+n/dv8f99eFainypfKRTn7h+rE23eliUt/XKal1tvJlG635rAYOC9FicuL6f23db7Bu9yX/nhM3VmEQD0W40QwbYXxkO7Ca1YmZd8UHNGKbTjQ/F8yL7/pM+seyWjmGzNaNcNetigEh5u8cIQtk9yJ6sCz5UEPFhD20/JfP2Ti23P9cWZe4snZ3D38mgcvzifoAGEwMmU6MMEON6LY1qcixKupMT8p14sQyVyegaMa7T8uiueI99YBaPkoYLQgpFOU0Z8avasNETCBP3cznwsSmMqSRBJdtgYDzrkHy7KgQD3WgdoB/DcVfO1A9Psa8hHBu2AzjNECZkM0vKfXRfEQqRehiUdKAoqCkCiyCk0iaIJBYQJnQ6QNLyhIBaBUxnIn/SJvW5TpBQN7yme+OYdGPtdvmf0zqga2rRUOTTVMoErPM1KoYqpFngaFAWrbkCggjD7zeqVXgrH4QoYBMMEUa6Jt1IHekGnPsyfCWFNOEYglFpA6sXj+dBzeTJ/tEDwCWWaIn2oqkAiMphnA1EIc20+OfrpB0Sr1Jt9Ot+17JzX7lL85Vu8/GS8R4l/MvRgexESnYeUVshSWjBznQ83ekw4qDf5Tuvw87huQzHCSmPnwNn5gO5KDoSQwdcgPcvCdB8o2zg5g6F0VQ/+/n4hNRTQelzQzZCw7VpfYVd05/qjX6kHPqeW7sA7nfAzrVj68JSGKz18qVQBaOElY35sgjXUd5H3iitNRFEHUzxA4VYjQHk6F18o2btFyUzxucqdgdcNUGhFzeggGTXY3+SvD3Dy6M91IpQ3/t0ifPUpgYqHbT6zn4Y1Mto1bB1dSZYoBvWqoR8kPdWsBkpF0xN0V8boGnfyMM1Fw6F3IlARoxQzDKmK60uaU+erIEaIIKB0RpkEx+9fVDC9UJyi0Q+a9GfS1BbTbo/5eERnwuXLS9RScTwe4QIuVgMXzZE7a5sdJggT2iOdTfsWMqdmeCD6tFBsGodpAjOwKMrJ5psEr3ORFApEQK3VFtz/SnQbJWdsFdpei9VjDcK+hAL2OZTS7+6Dp/D1pvQt+9pn9sNNXFh2a9E9VyqJctHU6t3mwPZg7MXBZ4nj7Mkp0ofz7Rb9ggHWIOuWo/ySCXcE2b+OnHOh4fdl9B4dhHsLaR6T4H+MDmXDbcKt3r+S+3pYdmMoNZTN9Itxl9Zm3ElF97QsjYyxEBzPQnGa01CGz9WwsGTfsz+fNB1Pb4qv2faeLKaFLmfloRoDfT6ilIr9xX6tRE8wgN4lNDqA+TgrDkp4yMevdGMYdZyZbF/HOSrgNq4p/RvPvE95/QgotaK3lpaAEr9JitNthSuoqAzEcKMCu0UptghDorw22pj5lhi2R4FSo1xbV+M3DQdbXaTLmmGokO2tBIxGx0yrnCfASUuKFpLI3jCXvN4hNhO+g+ysq/22e2YcHkEh5CuPKGTPYppXpVvfOmRfJzhR4A4lusGN0UrWkdjYGXqAArLBsb0rMK/fdo5rTbHTrxl880J4dvqiDrhdcHsn55UjgRolHGr8i02GTWwedIJ6EsMOdryWnFdg3yZahzBscfyZrB7kTl+3Nxh6DzOLnEps4bSeIrjIK2YcCUNlG+8PKDM937zenJVU149c21ycfJ43SP4I6fdyN2DxfKvH5wsPfzPWWmKxU9Dyc65/Zsl1n1OceyFg99vkD2c1KmvJw5dwrcEhhB/y+hLvm9GYbO9r6QOzR4w7/PEHXkLlV/RWZ/gjOk6H6z5X3jKh0jUIjPpeU3N96GiqPI/ebP39K1fhR8vI2/wry6kuvOGQVOX98wPL92jZSvZjbVvI9lIK5nnG7c0NCAJH16cU1ZnuZDgeUA3F/07DjC+JtDIh+JH3Mm2WKrNMG2vk91yey19cnhXov0z52SzDKXbkX4xkaHmRj5BSnF1QLjax60Am2wSAiltrmzdTn2dRBIgEE+CuFqpxsE7Nj2yc5grM4XsDcfck6GX/+4kYr5nwmaD5xzVc4/LUtiI6P//6CyRf92s97H3Ww4i9WSChVyxAkFkgfv7jJvr5XM6WgmBG36YlqBxnWLP+tDV4w8GsEICbIjmJLN/6S7b3x0OFldcqvT2fI33jEESUdhiG5+N+M8v9UHa7uIxDqBrCGZccwHZHKcXzC5vXQmvbGZZMPN/UtS68XGM/ykEXKaTcAqexGdp0FwjlA0beb50Y6LMLZaQN9b0iCb97BLDT/4/WxomzwJOOCLkzvH7kKzE8T/jFuMMkjCCdJFeLakVenwr5BqyqIf9QIjD6UrSwPEo/Rk4stGtxiyLtlzKxxtRK/RWe0OuEwsKVaxQKWhtVzNUiC6GD3ulVGPOiW/BYSLh3aiHgoAuZp1lzkU87bT7vDluXZMxBAFBAl0UU2ZBIDKUU8A6qDO6otEuDZfTjEZiM/SIsjtwAqnhXTQ3cgCM1FHTssAdjkvDvJAHpCwqqegOLUrtLBAFi7FDQoOGGQREevkwAQT3CCyxAO+sYq/apdwnPPdXiXpn5OG/eyAau074KbOxkWOaJV92jijR0nAnQyJ+RedVAcj2S5jwvFqOYfMLFW8ymrBN6FVpvIViBSddohDsCacj1BuoRvYZsbe3vEt9wggGrjsJbkFXTa/ZAgp44kFilJISHCDGRcjfWEmGQB4VieO4Z7EANHJB4lNjVW5iJRlTG7PxQDG88og94wf7hxf7Lx3tn12SdeLlHrHpCGO4wR5qeYXnZLdJcuWy96mqYYck+XcmVGLmMY9KwXPBMCa0qpRZ8RoFWnEdMnpM2d7DoDuz1dnAylBzncNuAMqbR9p7LE9TTTZTRllM1QGdYt0CWIuwuaT7yasmgwEyaZ1uMhUzwBpjFf1oDiK6bwZI7mwxPi/FZIfNyJDRiDSMrnuaswndbQ0uXYvjDFM+uRBn0TQwL8B0TWvwnJ7zsg7TlStQ7fz28CyTPxW165N8rLM3axqRrYAaT1u395aXDd8EO7aGBLgrQOqh3sLoskRogND2jQA15YLxVV8/0LnMuHtsUgi5GUvqLwtbVoLMYEB1ub7F7+VLeUPi6Pxywq5Pgcw33u99foBbB8UwdxemRwHipRQwUmbCrBXd39wizFZ06VZLPun2OuicmQPA8VajpourNNOx9WhwN2m5oEwWEhsCtrTdwv1fjDc0RzROy8UOHRB4odKHAZCkVIov52XVO/2d+inWNr1g9HSlSrBRNO6G7x/FX8f1bwKUDeKWshIW9J/BtD/h7FVBos9u/JtzhezMiBHTcAngB8C1egHBLcbo4YxOCKxAIL9yooeMbAIjynGStz/FTNpsX6R4BqK8Epvib4Z0ryaOp8bTsvLl/fS0r8+Vz+hrKP6gSXS1PjIYQCLVO4N5RVBF+bAedc21PF8vZ0e6rKXOi54veJTZWqbJ2rWlkFFVqMDPmpvGzGJiIcX8/o9CEaaqaZib1G8Jbz/OM3udksENB6p2Wc/RZQNthx09oDI3UU5Cj95VS1LmAtG6Fn0DY9rnDbgES+2NG2spf6L5lfQYy/kuE2GqXk2i48kkMz1qgcQHdY9LrSQBoUaLcMAIxbqMDHtUQ5HQpG5XaWISG2DwqhbN3RtKrdDzBMq1JhsHdeQowltinUJqYDCowcETDF2HDHLBQsjKcxu/jbRLYJBs7wnhI1y/2bGZ2ZJ2X6XgEdpruB9Z9Ii3TOwJ9YDc8ma4r2semecRfoYCwez/hcHNE589am9Cml6ros0h6dr638bzg4LaAONP7aD2Cj3VfDVyc9wnek6jrvFBwCZ2jXm0/ZBNas/EvHOfjCIOfYHhYx9O48PvKmXro/OOnlTTOjbun34/f4Y26/Gq77qf15ycM7Xz1f0sxOenrxWBmJFyrRbBi4r2HL0T+9PDhn/4OQ5Tphz+ucfEfu0RjgLt//rEJHrv379XTlzxqQy0EwjUu31X0m47dbxWdgfnDW3yi73OMestAwVuAPmN6V3wQDx8sJzYtJBYjT3eyGDoyXv6p6xhk9fz1qfc3+5FmNusEtirOBGN4b9nQYwPaoBKLvpuMrgP4pDTZ+IpalnKip5Xl+f5cNNqCazAzplpx+98PqO8K/uvjDUDieX6dOr00ygjjSeVbFvTnsWVZo541f0OA8jBxbogxPpfn8veVZwX6/7oyItJ/TdmiesliGIAFZOP0OoPRORFuMiGg5u7jgqlUcFGLa7XgBZtQLg5kY27EOODl3hHi0OvC0IVi3C18IYprQJToDAz2hd895ad42O/43Pr0BYwvJKFZgG0e56/OIf4/pZzLSfOpjAy2QcrLxHOZrfVLXs/5IEhJdwGoCDKu14UWz3jxLF1xOk8vXx3qYdPXxHsLbj72x1hymLfHiyjppG+k+5lU8N6G/XeyhiS4euRFsClpfVzj3v/pbFjmlwfGe9lXDdO5darIr/NyAVPJ9wcBBZn05fS32lCEXN+qf+s6qetdEJFfSnl710P2+9lbMN7nYX02xxfa+o2KlyVi9xIqGC3VKSLfEHFFyO7BCCW0b3EghB1mCyaVPrIK/6P/nL4nCTsLyXuGpF8fhTiEsoNGXlGapcpTCWvaVchE4sWDglIkHL2FHC9E6C7kLD5eN1ZhUeIUiAd59hwCODuty//Jm0WUMUCpHYB4q7vDIBG4drRe3ZOo945OhN4bJH+7hlQ/sWZiA8ca/d/Edfqueuh1Fex2VT4N3qXaDyol1ggAUUVD14iTsetXSnSDySybROYX9FvK71B6ovvNq2Fv01J8SUO6ILq3c0jjTUimhcfx6i1vfegmSMLLWx5xn+fF/A+oke1Z/G/RBEzpsfg88mSa8dVCqd3NGNH4MsXLgSstJPlyXczLWHcHw5WcY5hOJOMirdSMHHJfCdHH1fzBeTvPkUuhDDa+UsbJvt967u+CV1wbLFEyxjC4ED828Q4PONvG2gvxgcJR8KvkuAhMImQrskdLKRqRZYQdlb3DPMQ0WK9HfzJYKwrb4lkNSZ3EyuV04R0k5GvgjOiuKdDHBcuh060v4nWaYNPAZigSN4ZIRJpLz/PBcHY5WNsYNv8gH0usFg+0S0X4ut6sxruGi1hTXSj/wiSGPQQwNW1WRf8x2XptCjbZO6z4wSKshB7EcAyFniChqsP9XR48qBQcjgdJLcEdl1dXuLv9hhdXLwUqj7OGrq2CG0jC6FtKGAaw3+3A2GHHwO3tt8WJaZipYa+Q7YoOmNJtCc+CR4pHnLA0Dy0Jk1fSVoLPnd+6IIkwcm/eoRc4p0Q3RbBBwbjGcnmlvw8QT2/Dz7JfxQirZoWfToDgt9cC1+joXKW/LxnMdool5OUjMPpX9WNNfIas8ZJnvE2hhQN3nmPvZC3uQHhl3ESiZ6YQ1L2SFJjOc+okPUDC2JsCVMKyyztmQ7YsDwD26Xo5mpj+kbmyMzYthMeZP8vjy6QUYFQLaa/XPq2OMMf2i+LLHLhpbkd0nlFpcuUuI9Eig8VhdGPthFgjQTfRd+NIY87FANLpBUmUPWujc8xRZkdXc+GpIoK+NBb+EMY3KgCK/URBMaNRCyeyQLhOb20F7D0N3Z7Tv2yGmrW+l6AlrrhPODjz3jaZmR+j5Tloid8VVjlZZ41GbuNp+2w0Et3PqxX2fRGU3tOSLQmVKwMYINYIG+z7eqnksLGHt/g4xti7PDYz9G8xNdrfzpbibGyS3hFw8wqlE0AMugb6TQfjM4ivAQL27ycc52vwR0ajLzAWNsLj5w4s7tnvxfXwqq2R4jxfJU9hYcYfaS03l26cK7eWUGSfx74+crOzpkMJtnBjkH9BCcLweFNn8P5TXlqGch7L2Yn+jnZo8fip9T2x+p9azuCDE7/zl/b/7t17f48IOPwxu6ONyQAl/eMnMP8+iDOI1vUT4CkGqEhKQugZdv+7qHTq75PSJkLHp7NjWZa3DFS8Q31PILyHGZi3DxYXag2WYx+V9n2XDPBfUX5m/7aQxek2M01bFpvTj0YqzjpNPbWMfTsnxz7iE6b2DpOm5fuvj+Jcd82KJ3VdfySiwWa3jGdYGXs9XjZYuOfyXP628qxAfy6/VrEzGwcDMXIrYT2N4S+BuIAqofKE4zyPghVKIUBYlAzMQG/6zAS20Q1loMkPT0MnV1g7mPsvJIrUawBLu7+n8MF/tnyBKPGXCtrM8FgfLST5swL9+8orVk/0IsrwijFHerGzWhJuFIiYt2HQlwEAvimT9ILJrbVV7KFpCERoe8XkVt5b5YUC110pzuiMQgIs7smvWiybqRTP4ac3ajVv0OLCJyZGLVW+SbmOmMJDYrfbYzoe8aChQ7MixIxYABMmBeNtTGOhugrLCpzeQ2tVnIzPBDKtN1QSQwXmrgIeUSxwZxxWJ/0kTLKOL944159zxXoqgvoQFw3MOI1w5E8MSSbpgwkzl614KEbAw15L1SGQdIcAsppsTUxRt2D8YXgzzzS7wmst7Nbvk6d5qnYD0UetW49WwyTxpGY0lDKht0O0xwDVeC/+EDBPAGaUqYFKjDpkbHovC5Oja/YSwEihpwK+p1Jx7Otxld0eNpulRGUEy9s4A9i5ctcte0sDiMWjvRCId6KoMI8p3gktq7N4ADKwQ1VPOPg4PHIAqRdpB7giKZgFZmoRBcFhjkgS5lFKYByPRzB31OlC9m0R5SqVHaCK+dpln/XOmOcZaDNYFf1zEux1jggv0pk0bj0psa6phakVYWVHn9ndAAoX9NYllG4p4hHIgqtQLVS9rHQjDeNuKTmT8G4pAOC0ScwbCxlWksA047qt4nij5+DU4/51nsUFr1HKcKg+LaxawqspMXvb4Hfy7yzFge5tw4VEAEvOYRJdqYQs1g1tioCVQQzZvGjVzCq0h8P5IJo0A4L0Pls+V+h0EwvfZ3CbPbCzAWVMqguEbHxslW0WdvwL8LBeHrqdw4vYc5f6+i8lYLbPVQlDXZXmoZQBqaIbi3XfACejB6bsIx+7PndliObSLgV1qii1YKrFozsYve+cuQBpocvAgDxvmc5a+F1ShZKucedsbGB9Uk86jr9eTwota0MYViV1K7wy7OaUp3ek06dIy6qBWB0L3Z/8en1edBgCrXo2aPd3oIsrPbcwGj+A+ALUJQKHGwQYHTkcpR6L2qNtNe3DnkVJVksNIVOeA8VD5tlbIV7yNVmz+BkGGlK4FFBhyZf9cAcm8eBjZg1tDWCe0ViU/Q0d1nM2nKd/ry6vRKnYgcOd5Azvmu4nG0d4yH8qwm/14ue6UhKGUgByGoqOjoJauuarF/xRSoUFn2AG+MCJz53AD03T9RzBaCBcppUThTkjPKkJKRs7BZja/Tzdg9c1yZhq0f/Jcr2T4FZmEF4IDlJP/PpCwyUz3LOYv5oii30v2ZQwfVOaRA6XZjp0p5udGbhyxnCJa6JcgbB79RqHr18AAF/V8/zK51980i1kNVFH3l7O6yWgMm6JcSt8DAiEV0hYyOfwXvvx5csnMBgX2u4dybwWBO8B7CRiFDH6zCil4tiFnyPnx+A42/rhimAovDlfVnW/Sqhbz2UNeBoF21+kv3MaEBlyFwO+OqtBDIT+eTQVrS/hyND1JrppU8pGR208ow9jb5KqaJomfV/2VCmyfwrJeWVpWGy8W6kTWjv6Ajr/WhRXs0axgawpVRNiA4SYHxkax1wTIiQ6pZVWGm7K75DNGOykPjpPkZCvvmfGoEt6nI2vRmOsrTMPAm6hmNDomp2F8kb3PmRay+PvDSW5fW7GJrHuHGu7rFPPnk4LgRTLHauxjIpzM1yNNpZKfR+6w+N4du69ARYhi2MtlZygoqC+Jzx8OIJQsKsT+DfGsb0FM6NO4iFbCwPvgPZJmrLjlTkQWJfFjoxcYTj2MnkPKg20pTGnmKDxNKQV6N0oH6X3YuCrOenB79rZTCd88eJyR+VaT9/ty3uLev10z4v34oXtqpd/Hy1B/39uOcUfP+3xD7/7CxbGWl56vTHdBODi99+d/SSIQWDDRzAi+qS9m6s8/HMG4yMagIt373C4ufH3Cq4x1Un7EmY3BtdEEiHwoN7i36PofMfi3V5JUs/IsYxw/NDQ8Smbr3933cOHp8oSfOmR+8vrZTvL9s7WT7FBT1kDnRqvE3V7abvheDIQKC/XesOMWYzvitzg31d8GhI9e8MRMWFrOQQWCQ//fcARn7yLTi6J8AmcxR2rvhHRo9v88Teey3P5tcuzAv25/JIlI/Y4zNnBzIT88QL5/0Usm+WUCFb3DDs0mlcN+4FbDy6Lw9yi4USAlgx73M13KlEK4xNM9fLM9tTyI9Z8rzkYvTfp83xUNwHHuZAuz2VdCJrvnIBvJMpzYDyTE96g4OuK6bSS1+clR/hrq9+EE58JeKVw/O2RNbolVaI/Ai+RigAhJEmF+2id3zWnp+tVOPbM0CUyP167JGDagXpbt+EKKb+hQkwGuijt5T7Wwo7vLPZ5rZMo/bmPex4k4R83lJ1/Xdk+7K+Vw4jcgHFL311OzEKglBRhoVyysMFWadwf5D3pehnaLryU7QX7Z4U8T5T1IGnZeMKqo2IxD0/7wQXTfsJ8JFFSlB0cCoduWX/F+5t2BPGLGvNhZ2OEJXwPP0j7MAO8F5GQyKwYoCIe6VwhweKXefrkBGICw+im0ayme86ONHYwUa8fahq8fQI0N3wBibIEAKigUhWhrgsmx7mWc5/sQ+4qzC9JIZnoLYiG0N8OeSrkI5jwSxU/MIWaUMJ5llDuzBXqayh50ztr6OLFsS6BNuc2MCqHrB1SKV3rTfpsOSQLo6KiQYxnPBq0zQngOcpRoOEyQzkKw0naJ1OyG6rwsPZLnsBxLK/uDe/5UBd7Cr5cG+WU5OAJhcULdVlTvs594OEZ6xwA1MObr9vvJS3x8ab5G6TpthjjPmd02x4hRE2KaRdgZxSWcQSTh1lnhhrScBgGnBj75nTZX7YlViE2Un9Y84Taf4a/FjDC3ENZonu7UBEFdykQZTRFKOIkZ0nQusBVWNNHAxyKtRSl+YQ6VdQqinSbDjeo6BkPyt/CBR2RRzeRlGGrLjvkeyIp5U1vYc9Ccaj/2Hrp++LZzatxRw/1TYknj2VZe54/suJk80yRakDbXZhWRY3MILoUeFM+CX0PZsZxPsK8YqV1wU0SfQTg3lQJzmiqACUAM6tXs6aZ8CgA2DqrEGbF0SU98kgI+k532iFmdMzCk7Xe0Xr3PWKc2rHNEnreNGGQqAOOr7RfKAVobYWJehc8U4iA0iNUvKb3QSdR6BveMwRShJ4X7kAvmKtER2nUQJzU2gzQjsAH69OMUOXAlXniN34f9xFbxcZS9P+Zxnceww+lyP4tVdTHxbxx+yWIJDUKlwK8NKWohvQ3hZgZpOr6hi7tDqCkLJUB4d72JMywG7h3fKgK8I0IRgzC529fNphLHWtsMBWMEgbPJ057SV9+AHBpCmB/7RtEiT6WC2CIA5Dn9gDg0vnMC+/Qig4O4wGy73waiY4WuocD10hqHWCl2Hy0BF02w6dOYi4CHnlF61v0MfXQeXjjWSMKnox9MT5adtPwuY6yLFCe7VNm9N4wTXtJoWWKcd0PRGLw5mSIiuANWkB8HpMZViR6bIZo7nVO0Fzm0Z5FDaDEQxFFhLKlYoCohPJ5wHNkjSvPaXjX3o23nVVL9wczxSDkvrJbJfpLKaWL9GXgQbRR58jS89FygAZ8PPCMfT3/YSMQRnnxyVM4lwWv5dekcKP0l8LwzWBo93YacrjPN+KQwv9H8EPrHKmXcBpX/gku9URdFuXmryjbyvNofcHLYvvyufzPLaccjTJ02N+Ca0W94+7Y2isFQMVbmN9LeU+YNVq6Kc8BoOIa02+htiEI/2GGYK2LsvXwRwPhGh/pE55a3rIoz2U8SmE74/ihoeGTsDXp/afwR4+W5bnlX1b+jk645MIuV+Wz4uP8zc8spgcQmrhtACHnVMY/FHbeQhwBnzxDiTZKY5m+G39gRtdxPfACC/niwBtx8FujA9ZzeS5/b3lWoD+Xf4ti8kjxKJOLfDA1LyZSr6hSyD3aJBTmDnNr7jlnyL0o8m5tHg/BfsATgU0WV/YNQd3n9PwNAyZOegvgowrGshfpX13MwxwIomm8Cqd3MkFdlmel+roQxON80sPtdZd8mAXjXL0EMOEzqiqFJn4Npi/OgC59qm1NNNigq9oqSD3b5Y2XXFCAlAt9sUBquHEqcKW9va9VGaVoXwQBpP2TQ3uBeHKYV4FZuVb1WGiN0yEBarkq3wGM2sTTqqknknnxPCAJlygiQOxZ+l0ImsvZ+rMO17hVtg4mJrjoBEwwIxoLYydhA81DvaMtDADGmTt1xD5xtH5SyXsyVlVXxKQoroyzxpISkUYGMnsnWJ2Uflj+SyAE4paRM/P2pWQBajCy2x4fSziMvsilfV8234tR5xnk8T0eFQRjPYz52LDbT5hbA8qMi90rPBzvADTJeQ6sPNHNy5lR4Z61ADQLKxh1FJ0o/Mu1eNWBGNgJbGQPpMKsyjFCZZ1jF7iaoA16mKCh/oKdCiEbiPagHaE0jZpQAEBDw1PzwweYMPcGLkDjEsYoBbAUqVmJbjMu0nERXE5TRS0Vx3kOZb3S0Jwn1CCr1gqqE9qh49hn7C8nANW96gkF3MOKmmtFNRrMJB5WXXKIEneNekFKY8VAgMi8+9mFh53FC9vyqRus5QNVaTTgWVGizyhcHA4LLASy9pFFoeuexLJg4KLCxm5iPPu9gNg4NQLghScNEAoKaLhqqc2jRCivYICejTiyQr67J/YPYBxaf+V4RWMCr577vxwIy3CPJVtl0uhAw2k3I60kbeVBEL3ZydzmgudS8U6qlwIfav9ZvT25txBAc34vNTMOdDlieV9hwtTkMjzW7gV8DMYWqSFmU5yFEt32VtFIDyjj/JniwaYNnDsZ0K7xsR18iEltE6R/tVbJLzuJsk+U6KFsHJQKhgaANdUAACAASURBVDcUa1OBGqfEvpfpGD3iBgOCPADAQ7rHvIxz3hWsIIEngAb3Xu/EKAMHbqC68PakDcBelAzZ5xR0ogwtaNrRyRXxwT8ILKjile9BD4QKgIzJaRrCXs2nAIAOD04/xOM8K86X/SFQLU6vbf0NTfgPRR05tRVD5q/1BkDCMjPgXtZVJbWSTqOj69nIvmPAv+2toe6K0sngKQCBDQ/ITrbcTvxljkoR+sNdlR92hpP9WHUc7h1MQEFHoT0O/CBnMEXk08WkNNSGSuBLQu8F/aEDFwKrFep1fK+GWkh7GWPodu0qiJT/TqxQ0baa3lDTA1jUhVxMACjRC8QznaiAXsqcNAD4JkJumbQCqiZS/QZiUYCrKQSoWBjxF7ijWx2H+8vLe8y4VIswZsY3NCxDOgNwxfsS0O+wVdLYDP/YdXIlZWbcE2ko96ia8M37YwZLy7PIvX5zpfBCIFQqaCQK32m3E3rCXXgso5PaN0tBUkpN7YrCtit9JJBERgGjmbFIkw1kuC8rWfMP24udOzp3TFMYBBYUNRAM/GcTnkOWG14ciuFvMuV5Gei6vUS6DwLdE0AsRhiQ/hMRuLU1/aToO9Xgc+wRkaTaYZePYIQLry/Rep0TU7gmJOxRTMxpIZTmoxGEzQ1D0wSxvFvymcAXk4LwEoNbV4/7cR8PgOdztbwl87lt2BffyO81AWHmiECG6NeQgzWxN1tnRNurPrOuLM8GQbqrKbphESHW3VvCzHZZPydtJ/iXbEw5zw3M3T1cQaJEq28rmBm3/30LO7+YCXpLo8hcm82OUa8jAg+9gJjLXmn/bq13SthMIZj5Z+ebxxkBsPa03+Lj7K/zc6v+rktwbyPde6104as/1/Gbkbq+uCuazqsr37jV0BKGf0p5bGR/vp5XDHz9sZTMJ1v5WeXPjvrPtml4gNUizmDu+GFeKS1fMbB/916jPAqEHj6ExzkQiecMEs0waqqT8t4CkPOHGRf/sUdfxT49X16zKPxzjm1mxsOHD2BIOPHX/BOgalFBYgPHik+eyx5570Q7fu9kx7foNAA6dX9rIHbJZwA606DxclvevuYzn1KCr92iRfL8XPSA+5sbH8NHqGc8Rf+2FNtjI+c77XIlU6Yvrh9rw2VQWZH+CC18Ls/lZ5dnBfpz+SVKOiOu+ckk0AhvOmVQABW+CKM6KcHrnVFZ8n3JedUsgu0YrkhX67LQN8uDiQvQ/cDxyEBIlOlv0sAGmRL9ILPIf44p/EwRrn1Zz2eS0D1LAv6sPD9dGIMsCcQSxumT8p/fdJ3f6WR3+gLiVwB99e+3pveUYt2EFwB72M5T5f4RGONFO8bzMYJZyYr1LBqzf5eKD4IpuVlzLsuXjYFj6kwWpLE3JCEd71ny6V4CuFfPpT/rEL6eZ7sz+POlf//+EpgmlCf5X/lJq0t/g9L7GwufBVku8GG4ks492xafm1DZ8KbVBdC6GbK7lN4b+zB0fKN4yGNYB8d6KMmalvVP0w597mitex8P8z1q3aH3AtBx0Y/U8adIMHxdbPftYIHACwjuOYqcH1cUv8Qi1C2QFALF1ikfRowOKRGko/Z1ryHHW7bc1Tcp2gRXRCDn8ZDGTlztT5oDHleTOZTH9s7geUZGT7XnZOodOcCIYrej94IyyEVFUEsOU/K8lKqGbjbNZRDoRb8WikkwQOxzLT3gyGqgBjNFFXsG5MQinKNSJB0FefZRnU/299wLvac6KA5rbetwanBi86P9GnKBUkDJalvEyRejgjk8aZnVu9PDz+K7kBczBhy9xhvn90KOHEKQUNOkQlVy5DIOyDzAvJtOUgwuF23SYlDpmnWdbN/oBvBKheXrqkhp6F2NHhmyt5bzte4uguOLW92UxJyUCDYf4KSkj/vnfJpkGmjAu0ulg3s3pn7lr+VW9/lzeMn4pYiSvk4TaiVVplcVTnf0gRkIDpFUqVm0/V4E/6VXfC/YuD1FB2wvPc5EZpBfypcMti0UvdXofDQt6jG0ZYLsRxgIWcswznNPXhKcXjQaBdL5gXJDSMJNZpTLK5kVFg/2psYb1lVSQbp912n0jrT3OhMOVEDUMRGrOZfBi/YNmr4Asp+PEIV80clpvePYGwrEkMsUVgzLjWkGCnJOYrsGHO+JoBagrnBajB6kswQVlCo5fS2Ke9Ad+A+2cxiLGrqk8BGiNC/Ck1Slp72hTuIJeeQ5CdigMAdXWPfeQHvS6sywDZvgt9rqCBQa+CmSARGc7Dks2p7vnTUdWBhbAZr6pBTUN1UmxY0J1IigxC4XapB2PanxmwsWxYjAeTfvp8zBAzMudVpKK+jczgg25c8VlsrzlC4kTYzthehbXku5+wAxfI3pHhHsYxjQeZLLAhxCTWCKOlOakddGCWcvcAxpFB7v+yKUR+5Uor2nzvWOjx1UE/QM82Q/nDlarYHtGQIpn2I7WvbVEIHM6zAmTfjMpkDo3s/JwD+ggzQ9gs4kBT+Sx1As57i9hy7ptxSnS58ZSLyQ43pDwtae8Sg+pzJvyxzoIvgWnpEpPOITJzJMqOEo5/nsme4/X5tUejpHBObFWEfM9LhOywOwXzrl8Q7SCAK+JmmwcT/Xx4nGxM0BYM7B5KL6x9/Z4FWs7x5ZQPtRCtC7GrQTASmtUvvUwPQVJaRbAMaIhkBey9HAbWCBx26dqIGRI/b4FD5hbp5aznMoW08DBgtGeU7+xNL5PcBRJujUiLc6sEWkfrHy9fTE/a8tq2UjCC+hivGGtUd4QURbFN6PUXGt9Xwa6qvvty0WCMDDhz8kb/Y/cQ6oN4twKeogkwaSIda873Oahp9WfmE4/9PlFJL5F4zZ8O7HM/DBEOX6WxZW/mfpAZbe53rTz8D5+tT3687+Twac5/Krl2cF+nP5NYodlEM+MnAjxlgQdbQeubLsHGq5Tqvmw+ydMbcZmI+QSIAVnBQDpOEyQWqpvvQUs6ZNAT9kxGPv7ylm3jzSr0lyoX86fVr4y4s1a0r0JUF8zfCcK8tyzT+Q5+Z/ePmmXMg79T5niOL8dVrfpbFCAwD66giXIevwgiXs+m2ydHzB5J7oWShiwtOZRAA2MfC1jEqWfCRfFrt3AfKDc8lvugSMJPdZBmwOYSWg3k0tDtcZtLOQ4sG9R9blBcTynPSbSwB3bH0EDinH35W+d3cGFi8RIS6H3rB6dCA8hOZ5RuGGXqrfBwO7acJEhHY86tfjkSgO82slH3BSZvudJYwlfEVd+jaIEf0ftt4mIVz2nAiPpdQMn8/dZijLZW+Dli8L+HSePLdkIDuXRyVRFi3aATYs8xeCXK9nMbl2Oc8P8rtPahiwd7qwqzs13BAVg5SaatEw0txS10UhTRAPb8wVNBGMZSJI/mBWCWRRuCqlijBf2z7OB9RSsauTeyCYYNgEoVlx64qaC+hhYifpX/eirC696vsdxWgmM8i8HHn0KGmc4J8CQ7jithCIqioG1ROcCPv93teXyNKRsFv+SuQGySlKROrlKx77nRlza+rpLZ1khEcpQKhTAWYCV6HJtVaJakw9efvAhb+cvoUKcsUoYUGzF/IFBosnaOnKP+jqUcE0TRBHm/CcLgGwYUxAHeikeeYZ1LuGa06epaBx75iChANnZKF4a+ZVu8AYFPskWzGZXy9BFN+s+art+fcI3CK6zjp/ZhacrKtT3A+jHayKn6BUoTRl67jWkwS1FPPFjsRoW1ZJwhSyuoIyCqiYUFXnnExhaa2K8m/ukg+5te55vJcK6ty/k+O2fQb19Ej4yg0DLCwzx/wuPaW2w+brrFg/VIK1JUQQlGjKy4gGYT1x5NiVMc37HZIfu5aKQlVTQABmCdC7RHWQOuULUaBrnvSkxDA8YF7rkoFh9F72eSZR5BpMGBe9YSIj9c1G+RR+TCG7pB9JOTGsU0m+cF2U4ybAXOnQmIfv8/40UmsReMjnWvagRBThxToCh/s7PZsA2F+I0rR1aHaIlLtVvjgO9DZ+H8GozJiFuMCg1kIkk4YOJzM0BGnPNPR8IbS549gk4kY1ZZmuGaigseQ47+h4mI9gMCajUxADoc6Slb04Yg3lT6kT5nZU8CUJ965h2aH9yPsr6dYlwgqT3FHeQoyaJukbDqBpwo7FE/5qd4U2S896675Rj01iBU1TRWuqNiVGv+/K35iv87rkHbaEx8G8khmVoMpLMcpiWCSyLoZaDWhFIi8VvJA5KwV0a/Xcgo5HEO1R30w4fvoo9J1egnELZqGx92BVnqsGlAhXFFmpR6NP9QhWxEcQnnpmxv1yRAvhIyF46jDOpTFELY/4w9Z98EiHnYPDfDKU3esJtz22ByBGh8WFqnwApv3kvFGsGwPHDuw0DgUjInYw1LhGWnY2igyvCZ608715tvYuCkK7TxqP3fjnUguYJb2B0BcZaNH+Gv5z5WIX2JtKdX4n+rG5BHmSxSOZ1ljfc7QPCl3S9uw6h4EP4zJXnNv+ojh9FsIinJNxGIHnjAdi5XvSqJzO2dlJSAarUWKcVbGEJ0r0Jc3Pku4avg2e0aZBaY8zEht0Uucrq4aHZ6mdkyXV6/OxVZ9f0kBf7PjidMOXT/EzxztghuYWWCmZGeRGodZzb2dL8GSsV/TeIt/74+FbpQdGqw2m5XZHrSI3m2pFQwfwGgzG7noSmoJ3uP/4YXMKDd8zRJ6xx0sA37zZprB/p/2UvUx2lfqZlegjHQ9e68ycPFJOfeGmualfb/g1pjcV958/gvjrgKUA+AR/s/QIbPjmXL+inacD6L9fecPA5e+/oTPjHzcCM5so8SeUv3saM94C4hh6/OcMekfoN5L7HFDPfZK/FcDFb79FRUQ4/nHjdVa8RcdHWJCQw4cP2L17h6lWgIDjfERnYP7QNnjqp5U3DFS8Q3lfNFUjYf6jARBnnY7wPnd2/K8uT1m4c8Cz9X2+t0VwHqtzeL5sQB8sPdZP1cnrV7JcPtPF74HhAQ8uaOOWLP//evsO//XxBm85lOrZ2Q5EuNZ6vzh9SPRk0UZZ4u+Nko2VtYlQrv+J8lg0lufyXH52eVagP5dfsySeMgpryGgRKhWLR0iEOlUNAQhQKWhNQr81O+y6sDsopZzvVEDmptP5EJEEQCY4hdKlxDmfI3KMFNaNTggWnjQfiWo95XUIk/aYV/n6SCjfPJWf+N9cbhZK8yx86hDkarCRYcSur1nUeTkXupVsrmEh0qyOqmDZ8HSmIVd/AGOndzm9QEn7RCsBgj8Y6yMg68hzv7dKzoVoYduYnwZnj410rTxfF/c4JQBlpwIOy78swpnHPPx/fvkBxo8h9j8MmJJJ5FqGY0aGdBDNJcXZyZDo+p6jLl93Wr1j/RGB2ImYbo5eR+Y5D2gEszjhDEKlxZhW55nSAVRwb0AhzDODK6Ookhir1bXdqFlQ2XYWQY63LfbukUB7a1dzj4Gxm/bST1Um76ZJDVQ6apkkFDA6Kk0opYMPDOxjsHaAcFyc5rrY4QLdhbd2HyZYT8I50IZnzIm1MBghgugxXIhr4UVDsJ7DZYvS3JT/akjQRQEvB/AZRDvxkNZQwYwkOPXvWHL8FqHPdog6bcSmoR1J4QKh0Hd+IYXWZV/eEIB7naWDOkB9ByIZbUEJeC4EYgnpLsOQ0PICjzLnkjLYPH7Zvcrca0zTQ4zeZIJ1awllgJWuIY5NlG26Lle8JsXsIJBbEpdHigm+l5/mso0WMiyw62uHEOOrGjl3Xd7YOijnNfMvdd0UPh1v2w7UPWPKbdhcMTCrQrs1CcFr4cZXB3WOtk7Oh+4nz6mut115bnwiZ4FuepbGvYJtfYcVRmnRn3F6TiBrl2bwAP/D9xTKKtNrsFiIRCSD1FrRsPJiVFI0ljWjcwF4oTq2MfcU5Sl1ohi0pcnNgjhqcL466W4U17EoZk17mVrO8znwIwaYBaBedN1ZG1imCVnPk9dt91TRa8opiWwgynX3kIwKBl7dw9wrviC2aQiDgzBCU8U05N0GoPQmSmlTSgGYCqF25VcKobWCqQCVCMxFlOzSOLg1zJ0F31F4QnFhtK5jQaQlODQx+GIwHg4PmHYTDocD6s4Mx3R9FFBrnVDKLN7n3BxOqZLPfXxnnrM72bNEKNhDqNgs3u2QyAhMFQWEY2sKQQVhZIb1uhv8QM5bbbhPnsPY7p9ke5IwL+gHVkr0qIOBLgZatRcwXwazDvIQ42L4UwC6A+OF01rQHYwPfzA8bzhKkeqDDQ4Bn2nLAyRpj670g21cMV5ncsHpymgXL0OlcfADy7NB4JP4ZJumDKuFCEezA8RUJGi3KU5tvL0DhwLa5zEoPTIe2FeEfe08uoMqp+OtsTjfrC+ZEjFQVtAO65vEUciEi5Lc2jiodUsSIUHhN/PPaQwxxad6nGpcoh/nschTghBI8IPPRYJxp2tKI9nmMPFNBGBhnAvANUUCzuFFuVm0Dj9TDG/bWkq9rjjX/nR7d3nedZwy0lr/RYv7SeF6iqZunak3JTd5DReLwKlfw/CNf6CkGLfvKaAtj8HW5UlnfY4/W7Dnu0M3bBJx+VwSwQ3OTKFWCuHy9z3muWH+1NA+ddS3EmXj6v1vuLsJJTqt2pa90PFtM9T7FcKQPh4u1yyCWP8dhVc/5KK+Lpg/zSCKNHubH57fso4ZbLj8hG/+Hct1B3bv36UUGHL2+T+//YZja/jw8ftCjf/KZSCXi+vyjtBu4j1Tnl/9/nt8w8IJ7N6/w8OHyHtuRoeEazA+Dfw9M9A+NHR8/FOewmawerxp2L0TnmXmjy4JWabAyeM8V1ZnvSegsF+uPE6C04s/8uz00x+ZLiGzY4ffbFRk9/7v97/h7o8/hvtLXmlpWPnDJfOxtDBmh/EuT6vqWWH+XP7V5VmB/lz+3vJkYrTFnIpFOIH8gF+4eHjKSUNUlnJEa7OETzzIIax3RlevDdG7m+eDHIFJ83j13haHLhO8qsc6up51NEfZyrR3LOa99wbAZ5wX3v3ssqWYXRZ7/k6J5ozn0O1PKRai69RqflWhkvm5mqL9qNc2xfb8lVcWB6v89wsxXlke6lTHC5B7ZV8y8HBi7faqsJH8dHZgDwGVKc8XhukoRB5eygsjCbbkRRNLNADEjKoCq+Uhcysvu3miX0DCtwOSI/EVzF5drNQX5+qYBP2WIB7oL0C49R5Zn1Uw05vgi7qTvJ8aYrVMGj60c3h2Im/rhWjQLOKRJuxcefKeCkEfkBWY4zhMWmyhhAns8MM6UQQKILVIlmkCC4VgiBbzNRjSbih+JhKv3Z66A1e4r99fChY4CYvHB6My5xQznQWP/jkDQMduusBxngFlxltveP3qNQDCl6+f5EU2UTq7tzDPBJpUke5iINmhZSJQI+AI0L6oZ2aV/K1Qb2jz5oQo7GuZ0LrlEpe+TbWiX0i+WVAIkW2Vh0N3IdmXBBBVUeBXUwCqIr0QCJMYDCRhcdU92VWQ6umyc+jYRL9coA9Acm2Kh1YtRT0JOcI5kyn2gYoi4Ud3Yi7EvauSoYFqdQ8MVkVdLRNY81GahytzRy9VhdEyrt5HJZ3TZEo3kCJpOKDopnA4Y+c5RMmqeEC936A5VwsIqOIrY4q7DGsM6WvvkHDFrF5ZC0G47SILo7xUnpswupAoVMKLl9XbtSu/Avcy7z08wPL295VMf86hoVOs19bZeKuaARcu5SImmN7oQDaGYa18UMIo7loZbS1wkDyIYMccX8M0r2Y4ycxoc5Mcti3y2VNfWrovOLIT88eUjBoA9XZnoKfQ+guOIOYi8X2GVrQtCS1PYI28QH3be49tHh2XLHHsilKkqVMlSoHicmmXSATkuZ6iMGmRJagU7wsVQunQaA2np8sUNgZvvSSvTco8AaE2oKvHsjuqwwxaWfujEQgAzZtjCmnGpEaz5tntxiyy+SScNQgs2nShdwaEW31HGliBK7u6EEsURdsS6laXU+mo7WXfZ4nGWP5eUvglxf8ViFQQiuPYlCtgUX67wgvYEQGNwGUvCvleQKWiX1mEHTECKqVIPu0qismunuJNI/FA8crhcADVyDBv8ypKFsbD8QAAuLu7BwBcXl74PE/TTum4fF1LBVHTEYvCWwLCV+UTgWm/A0jfLZpOoFbUskepVTTUtaHyHp06Slf4UIuLw+GI1ht2ZRp27vH2COw0CoUqfZgZRTlKxh1IsoWfLr51ip8LzVCg4Bbl1RXw9Zu/aGxV5w7qBa10CZfPLFFLNEKLBKx+jZkeAPoE/vbVm2QAD4JZsNd67wBc2p7Te/eQCEtb/LMY1DEeIIaxAwZYMFAvQauUAbkvL3WvMEmu728YFdlZWZiV6RIgJCiMsWOGxi69FYrc0Rz4jPY7FKreEQbAc0fZVelttYhA1fWN7MSENUJCKIKr4py5zaEchvAzEp2hAcyeI9yS3E91MsYIpcrKmxc4MyQKjc5rAXnuZZuHzh0EeF7vkA8I7yT9NqO7wOFlqTzNfHCyiFzxEwgcZffdUKoELSkOT6lOXwczcDTcGsp0n+IBSkYleFbY+/8KAStIS8Mc+BGOPcXpP6OdzD2OBmlfGJ43xTugyXEUJzugkNJgmz8WGhER2E7vidxPXrwpPNfIK/r+SKlVBoMc2ysDG6K0w/Ie5YN4asznYGUIMJaY19iHwR8kxbnOna21z2qR9ywl01R3IAKmCcBbNeAFYW4dpQBX737zMXPvuP/00dtjyJoUJlS8EEW6zkvTA6TbXft6xXxD55jSnK2N/n5GMTOaANBYN7l3/PwJHSqXSBNvPy2qk50fLCLPqfbiX6sl8YmnP/mOch6+H//u+x+/1aW5+s/fY784joFH72ofPuINZOs/Jqf8l5UnTt+Crde/n+X3DbD77f1QxYRrXP3HTngIqppSq2OeZ7QPSkNwjY6Pwr8BYHxCAXD8cAN+9y6ipoJPRgl9yqqLvPcjcAO8BsA38a3bAmL0Xt5SyP7U8lR4iCPW9vennm+0I85mIx32d5b1rOpdfHOu3TNztzTG+t5tYTKS5TE8wycAvFf8f7i5AQPYSZxcvDFWW/Fz3pc2DWeX/oTALhuuC+sTZxpJvxvXz+W5/LuUZwX6c/mlyoruLBhpV9zpAa/1YPIJQCkTptpR6+R56JhFqGGKCsDPa4rMiwup3YPGmNtBOJr6+YjCbGl5FwfOH6QQzCui+Fj5AgAsTNEWg5oV7GZhWIAhnMtz+Tllgy3zkpXM5/itfMR9CijsARyGOgaphzIxFl44vKEynLEqc8TLNPmq8OK4mQ1OyHKCrvuZPdABEazZUfhBn1v5hqcX+VZauz0xOwxRfFWW8FdUCqCer/qCC8/+NcUOzzmwvomoFiVJsEbmOO4zwkOGmdV4Ij43zEbL9pKg7ZTnOTsznMUu9v6SXc/dWt6P/uX28hDX93MduW35v7WO/W7vY2tt9m92dYfWxedOPqza/hHgCeAyNOwGViDQBDe0KsVMX9jDd7bWUKiKtb0KpQpVF5xZaPfs/WNGDj4KSmPRlt2DE6o0JxEOyn8i8KVSAm6JRIifhDdFlV4mXLVVcw/uYUnijikH4tCDpEjXw38FWmunt40eSs3ozNatlALqXe+nPOiqrAJv0VlWeSgDvatyjjXPvb8xwJl7l+kU57Gx5pZn0utikQQWL+silSLK/6KC+MKxMkxhWLA6T4fEXwyTJJ4zXClr68Ws+c3Zlees4fVz2FhfIxp6uDrgfw8mc5jYeDbsOOejRq4oGx0OXxqMKa4IYS5gHtPGz616pAI358nSOx7O03k08TYP44OePIDHHi9Fl4/Ni9EyMxhiNmUsY+QVx/5FHRve7/pOh/Cu1MijWIiSdUCAJ4UTWhFCIbMtiBDnfBHqe4rT1Gcy/KN7PdIZ5HVWCFElLXdISP0WRizGz5BPnvbfIzhotQ0a6UHNlIoovAOMVBFv/WSAeloH41lg6rFxz0s3yX+f5cIo0ToiD5vOfq2e7AxUJjR0WKjkQLvRfrm4EEXuGV6CmTEvvrP7Nn43sAFhZ4Th6gW6RcR46CgXjD4XpQ2ygK1UzK15mHmqkqqmH486nwWXFxeY5xl87Ci1iLLR5iop9tjazX30/0wxpeOuBcAOdUc4HJrg9pJSzJhGlRIeEaKi/BiDqIImBpqkayg9IifY/Jgic4kzcvQVpyMAiF5I/zBCwPK34f0wTjKVE4G/3XsUGKN/AKVc0i8Up6X+6HpIbbdDW4AYvJpBwwN37FiD03Bw1wb/HWUw7gy8E/NS9e4pJXlb4OxlibV0YhopVYwek+H0xX5Dor0+j3luDbmEPxul75mx6pvzML2FcnFF5Mhpi+FqndIBb0mXKI0jzR04GY2GsgeQ8au9feKXTjI7i/kcw5oypX7YnAxfb9Sb4WnZiuE3GH8ndRCJScHoiS7cpK2VLbOECbfd7Ggao2J6saY5LY3uZ//fKmcy7HByhgI3B313ms48Rn2xZV7Nz0jfabhvP9OHshCLdFALmLLXFne34NNrcPob1yNdjraI1VDbAMueJMW5/8esivPEByF2l9PaU8VZReNVNfmOwX+i8+NnZvSh+50kNWL/1DSSxwzgK8r1NSoxikYuEcONl2B89RmL1fmGgleeEqSJlCrm8wx2YnQQl7PvPFZGDm35JP0d/3j5PrX9KYeZU/3/8XH9CuVtBy7/I8KRs8K4RZNgZsw3n+Sspezgrzbit/0NOn3266c6E9HGb9uXhs4MPe7fv0etBY0ZU5nSdzREz5lVYW515npLkuXwRl71HykWpj3qjXbnn9LCd5REds4+/4nlPF3/4QpHQHgMnoy/+tEmnXdb4vLxjsXzMHw24xN+Z1nnrRl4ao844U1fwjMfryIUnLh3vs3FWJ+18M/lbyrPCvTn8ksWV3BngYgpAfROAwN9FkGRCqNLAagU9WwoGma3C8PBjFlz7hW1fs8e5C50W/YlHfLM0t0EGWtF+XhtrNhrAG+BH2d1Nvp1rti7rxnDQdE8ob/QmAV4OsrcgwAAIABJREFUxl+T2+ZXoWVbud//bMnCuJcsudEtv9Fr/QvIvcwAA8HQhI8ScMGvcaRvIKTwppD86C8hyqevxHipC3pr+ZIhiugdRRsPIBwg4T6BLKzMEg6z7odbtpu3RfaolFCvcq839TAyYxNX5MhfOyyRHgSK5mi/sC0U/wAA7vU7U6ybcv0ize+W140XVqU7PfKevZ4EF+a9IPflgG4W5FUPKG1l6U7p33z7fG70Rw8E9tg8n5B9OAaxkLyXBFsqD/IVlfZC+QCIRx93AcQt5eAgNlJpVSjPxxBeIHKvOQv5KQJldvjJBzyZlxCh5HkwTzvB7QwLv2vhWlfCN1P+MlCwR9eYDjEaAuOIi4uXOB6OsDx+0zTh5uYPTHWHy4tLtLbDYb5zZRWDQLtZG5wQO3MHyfY8a+2XKlTqkT8TYj1ORNhPezABtVY8HO6xn/auDO9MaNz9uhDFyqZtWUxSSKQW4EkhpqGsSzXvmRlEVYT4SVBxJNI5kvXM+a7zb1OKZ2U7OATwBbIuEvpY+ixeqUAhyQlaiuTlRteAb2QKe8V6LDSZoB7BXXPtSsMAswV/EAhJuarXns0mFGU0MKofe7uHUNcPRuKTjAtsojszqM2iuNP2WhODmlKL4wcbC9u4YOGtI6svk0UDgCg+Ha/Yfux+gGYwuIVnrwhIGQzxsuopHL4JgUPBLorbgvDWGw7nK8GfMgBZwZDeWO6v1X6z+4uDOXldWfAYGCuKKrog8AjuGhUhwgULbC14Jzbao5Boiuo8PhOc6zMJhqLe5r17iP3uXbc5OCEk2bzNPgpT2CeVufx7RnFudSzpf7wnilBFuSgwT2JD6OpBmMB3qN8MBAigzuMckvHM5LDTzMO9qBGHvUok0TEGftiaYCOQ/q5ZyRUUoAFcfcFQ2NbizBR3U/iww1IloX+lMZrvF0prLsZ80Qeg9SMC5wCViq+7DUT2bso9TgzqexAdMa4cVjyNgX3pFjVDaJznIldFovldA0DZ75Wviugbvo94FGaJX+26VAik2hIVw3sXLyR6AEjxBQPfgHJZFE+p0fA8o7Xm86jYFygFfT7i8uICTSNcmIFEYxYkXMT4RJE8aqnO993d3we6KQe8ePFyVMJojG0qBfu9jLcbfdf1GOa5GE3v4GMYAEA91nf7HWqtOBwOmFvDVAtA1cfEyt9OV5MYHul42aIQBKHT+d/Ce6xwAnTcKuf1UrsqGXqLKeDVg3//pqJ91ShmMMO2TFu+gbEHU3PejZUnnplxx8IzXYJwMC5P7zPr+BMcXoHQiV1g84DYYHvW3Om67zp4FcLTisOarUem+4ov7jvjUqfOvKbzc48Ew4bzgSOJwW6QuaAQRkOlzT0YHdBzATXBXXhQvKoWtFQqsC+acgCgi4sBh1IyxjJ4Cn7BItXB50hCUQOYR8ML44XNIHLEG8Dcx6D/Ma3yw/ZnT3MEghppKqxR8fMEWV/T+owrld2s4yRwWijMCPqifSzGPxb9bXKTbIip8EUE8qh6Vp1E6/CbeY7Jxk0YcGWeO4IawsSOd+6ADa0nPi1RZCOlvbNHPoLipXUEogRrJRtKwddd6OWIc4dJp/H9LWXywGKtKkorwSP9lWuseVGKPW50n3Rv9XR+DANB3RuJ1zGYWLBlw7cynBFuLMJRGIfZt/G+XbqZbYm1nz8JXSDHG68lHzNGI7YX768wtx3uPt74vmUA0+s3AMn5un0+JXHijTk2IIx8cSeWYfxqgfd9eb0laaua/CLflw99/QHg8votDp8i7Phbfe0jiQzIjPe77kszfm5P6m0qGZ8srzng+unlFP542uNTr7/pwO7dW0xT9TOLp1/AZ7QbHvibDngUolxMfvazy7LKU1MWXvN7HI5vsd9JGrbLzjj88UFWM/Xbcph/TeuTt6Hdnt6/A4EwTRPw/jeFfVJehdFYIuXZKele28pl9+4dAJGpzH801PeWFo3ifPPEcZ4qkgddcq7Pmqs909tl+duilC4H8r3tPgIAtn/9KORn0p/Ybv59YmGc9AJyhjpJ78dq1m9tf8cYIwh0RGoAQPCkK8+ZA67tfaNl6f1cnpL7/GRR3s1o4HN5Lv8u5VmB/lz+5WWTV16flURIod590BCqrXfMbcZxnjHNE6Zdh3n7FCqotURuU+5ojQe5XHidiDDcclGu+siW08rJ3HA/c9nZi9fqN0HZW/072t0+ZY42s3CdLMtDq5UvUGU+Sz/e6TNjwn7ZUEp/svwQYX+kvjxVFaI0LyzzO5HkOC8QVVzO4GXf5rPRLQGgL6gWSl2f+YFOZSKvmNAJuFuM6F7/vzrTXysLucfGaNITg/vlpthgmEI5Sg7vBDFgyUqLC5AIAM+Uh5M9Got5rBNEyLicl2UxRQK5r85iFDrP7oXxtxcGPJj1ssSu3hK/0erKqkth5TxU4ugRKWF7k4e6i9qy4A3J83zdc+ndUjKVur1ZxopGASVvMtTWs+4JEaKP1tNCBdO0Q5tnNJ5BILx/9zu+ff0GsCh+JtqjD7bVkvN8zJQqu9cU+u3QgD0BRwZdQPPFdg8/Orcjap3Q2oyL3UWMhLp6HxUfF2/MFuVfLuGyuSE1EBveUqH+pJM8yyGdxcrfDL4kjCwDVFQonmFehdmDsUimcaT2IRLFoJDk06QCDYkqBmmdi8oKyf+38FxdletEorgLHLQlHGb9N/pAwx2jwRoVgyBh5Mdui3KrpJkiGqIwuGeyJ5kTwQQRofTixgJcCFRqKAGIUGr1kO4uoCYMynNtRIWWJgs2AyNWQRglox7zOMJAtONgSeidBEepJ6RPzhKFn8FdplzeEvis3k0SR+d9fPFCyAgkjy7Ggl7EqhHsmfBj0caaxnAP5bl8z0m2EfNkRhmA5obvoZACBb7AEu6Hxk5MQHpkdbL1Jb9zTpqZJtl2boT+1TlVd5zO3UPvFvUWXEYPGUpmIs4QTGYJb2+w5NjSYVfuWChhn3eFTYnUnWGSjFQJbulqyGXZahVeDObJvrFqbLMGSVKen4AiXt6sYeZF5s/gOQY58iWaYsn7JhOz8g40a1wGRAVJqfG8zslT2vqt3szU4XPGsHzlBpEkIcqBpFHTorCc8X0+fxjlQXpeYSE0Q3nIpBELWNNcNAboAfOtrGm9tJDlaojz8CC85+5CVoeb5E1XfNw1ugX0zMIIPLS7vEBrpnCx+Zl8/sHAt2+3qBPpUhKmXfANZqFhRgZWgxn2hXGYwuJevNCpFvAsBlpEhE7dvzQOIxtnSX/ir539EjB4KS8I/XZrr5K3MeBEVxhafcWNBYumQzIliffJ5ge+RXBHhHvE+lt54FHRy6osFA89xV9M6As6eaHvdjDuwA5uvctvC5l+t2iPCbgH4YqD0yS2NAoy6qsim87gNesUQxdIwgbpg87Cs+8wnlOFz7G9ZJvvCDGC0B4kRTzuddyXA7rxuRxo1oLeMQDo+V3SB5B/l6Y46pIPoq/Lh4aPUh1nkWxqx/e2weXiS59bH0vAS7TCad5oCcrxIuf+WX36vvEldg8B4TZfYGgIYcGRQgIMxwWOciMRw4sWQniT9lnjerWk7RyrMxhvQukGseOYnJLHR5p5nvQxwQy+Nnq0fftsoY3fkTZruV4xFyuedqmgB8AsZwKj/SuPXE6mehzGscMclC2gAHxyFpvE+8xpbIWAXmCpTwhq1MJi2ATlo5kZ9a0w2sePcqaaricUItz/cUS91miPRKBaUeu02i21FHQwjp8b6uuyIQjLM0DLKdt8a1no3HMe/pytaOtRIcLu+i3w+aO/Q1DZj77zgkdl8ALyz/T8+8r3K9F/TrnW89Llb+/97PLwjz82R2YK8+CtpAwG+Vpepou/Qpm+Vd52gPAGV/+5977sporWOlpvmG8+BQ5DOB1d61H57WLQS9gTvKp8PVlaNtljbryOOK8Yv8AA9u/eLWQ0cn/+0DG9r5g/NDT8nBzyFcD07j3mmw+r8XT8G8iFl4j4icXGB2h2qJ/VlxP06dwnf2XZCvG/xY+cMi4nPA3XbMqKn1C+R3n+I/U/l+fyV5RnBfpz+aXKqaMYIAh22k0AM9o8o/eGPjcc64zD8YA6VezazvM6mqAbJLnPHuYZpYlgwEUyFK286cCNCeT08DcEmUsW0IHsWZVPcchzAfHGuIxYS070v758JrEutJw1nwmuajElpzFsP8Q/0PDnly0/i+S+TAelLxSWs8b8f9GHr2DMNkPss8nXfoLMexaYvmBVooPxJuWDIwAvUii8CS8xMUC4xS0xrjrjloBXCo+WS/yKVLiroUe7HqazD0KBeMMA5pWaBTVJsEQUh3cXptgzzT0IRu0R6qm3WcKT6tMHAGDGJUTRv9dnD9r+wxOYp2X4d+uHMHfSe1OoP6QX5Ls4Offe0UvzuQAkdCzYdGlxcN9VWcVdFaV2Y8bDcV4LThyfbAi6fuigu2Rlafjr7XP0ZIj4m78WKZhhtbiHJPAp5NdhKATJFQ143dHuWJHIuUxos2ByOeWETAIh+Ddr/OHzuWpvG1f5AUAlyV++3gAgvHzxBpUrvnz+rBbfsgsvpgv1Brecg8exQh+v0gPXkB7RLb/6wyUuXu2w31ccj0cQAfv9HiDC8XCUCCi1oqDgeHgAw0LJi7GWzOxxIePa5c2VZryB9nvfYKE83YFKlfVmllMgFZTOfkiPcC4lDvAkcD432weS59dzC5rsEhakl1zgLN8XVYRLyF2eGdwJZYIrqksRAzZZbwm1TlqDhScPOkoDTZW81UgyWBoWXUixCvrQRdhn93z6JMS6CJLNaxy+5nOTgLZij8dgbjAFOXWJRlFqReGCHUSJDqLIVW2/CRpue+yjwQ+rArBvhGwP5YTBOw3X49yQpIKlRc731K4LqBbXQ5+IAAtBjtPv+USnsXh+ae0rJ0ns1iE7Rw7I7RieIW9DaYtLd0kFyAlXmBKSaFCud+6qNGeHGa+TFWJ1vjr6CjcN/T0lQHApYAqOrNtz5Pe2v1/LdwwP2vehEC69AIUlgot6Op9aIBdCGo3ZjHELjxBBpUhkCmKAVRmIiLLgtNQ8/z0KgsybZct2z/bewVTB1YwXJDwsSEIi50hNmVaacRAzex5UU9DB+I8KCd3c4HDmShB91/WkWp+3h6h/XFUZrwktl0aNAZ8AuAtfz4FvDW92YlVsSr8iCYphSzXItfYsabq3R47fTShbAeeZCoCKS9Qr4yIZ7eEeFRcyTh1B53vlWxiEPbg1zA93MJxh0UYs5HlTz6e5dxTNnWwwJKkSunvTEye618XoEHwEcw1aUG0dFJaMRySjF6z4Xr1cbX1YDK9AYgiw3+/Vk1H391Q0fDNSRBLg2Cwnb419HOgCYswG4EJWpDMwFeDoZE1WenqZDFWZ0b6p4QeudC7unFbJWVDGV4pGiCiE8sboaMLbXzmljYDzTsanGgReQOZiR1WV4FD+mED8AjN/w53SLSbgm2PrhEFY6UtSvt8qTXyh77x0ftHgnfAiwblF5xhoLRGAiiM3XOo54s73ceD4zDFdkBj7PFDHDgSmS0W/dwAziCUyQbksYFyg39tmT3ThktDvxdiMFBmYR2y/vwdhh3aRdlrqCytv4QaiHKsdakhonYGP5lkiWEzVRGEcE5L2vdGSJXYlhCevK3xhcBOYRwymJJpDfGvj4KE+6abcc0MQxSqBqDi9jWF84akM2bfKi5VSNEd7cd6j1h06Meb5IHyRKq5N1Q6E8SURPMWI95UITc9OsHnN50ybTv3GPdUcZmMP2n0zlAvilicst23zl7zPDe8kA4rc3opBSfzn5v1B8b0BANtfp+vlE6vG1keQl1GtvJ55X8tWUR4H7GkjVs3oumeDsqHpPKdpLDkiAOe/kDVvvaF3UY53MOobi5QDHOcZDZ9x/BgRU6SulyB6qU1JQraHTx/liEKE9gW+v5kZVxDjnuW05Sl/yjk6w5OPLz3T04yOTYxmh7QzQ2W6Bjo///h0Mzz+ms7N1uJtYiSMWzzlYZ2WTa5tGTbeXX70U/RI59pZvPaagYt374Tv+NDx8M9QtnJ6jxcfnuqm0EYau5Dm0crg6X2imPytMvD5hK2ptQlIqPbyjrDficGjGTC33tE+fHTF/xZb/9iU5ee7aSepcbg7jWBmzH80AIymUuCKN6jvKy5/ey+YV+VIwq8BtRb0zqjvK+YPM44fGjo+umL0z4IC4Rr9JuIk7NXr/eHDB3REBM+c9vNfUh4baAbErbK4f0NiBPHhie8/en84pODR/i73y2Oe51Z4gTB4ef9EecNj1yvEIcvJwuLz5fltWX9EQRnp+qniZ3HKhtv/SoB6Ls/lx8uzAv25/Fj5Ue7tnIVSYgZCWGCCCEH0TSQqaOp1xJDcs4fjUb3CVLCnwq/dtAtmNCsJ9TpTus8qGHcZEAio48F4GabLKGD2dJN/s0eMHMiXfN01sgFuJiKZieRHeYJcVufNjXpuAPzGQDclq97/rMxEw7+BxeFTi8LaV+DHuMwFQxNihZGZXB6OvpIIq641PGu2uDX4NjUa9DcIeNEJn4nxgmMH5DCfxQQ2AF5q3S9Y9GYVoWS+hFmTL6dDBdtkFpchZJIDDRz+l9bvMh1JNEBqoS7ViOCVhKgUiBfMURX4ILhhCyC52fcb050V4BlNEAH3zLgkcqU7ICHgL8A4qNDrIn+Q6rJibXqEzCUHa8oMu9RXWmuYO2O/m3Cxm3B/3M4Ktcn/nkJ3J5nlrQ9ccoaTmIAxOmssOkSDcoVWuOzUOgMbB92NMUjPTmGgE/3OyM1w6QLGoqYx9PiqL0O/pHLmjt465qbiXpXoyXWLmmn40AWBcDgxxj/EXEySO1aEiyogVQ1n2QEoInAvVPH/s/em243kuLroBzIk2+kps7r3ue//ePeu0znaaVsKEvcHRkaEbOdQ3VW9zVpZlkLBGQRAjNjtMfEk4+EOQDzXQQXMEjyLCCiYABJL9ZgngfQ5EbmyRjy8pU/JCc5AFQ+RuZgyUdWcft8KAxkiiCIY5sXO7jVoQR7tgkO1oJYqOb6LKE5cuTJ3VZQ3lDKpkFWwh3k6AxYONitFk6JutZGkqVI5PYvCzBI2HRy5ogdyLr+HclOiz8g+JryWqpjiJ999O4siqYPBrQseZ8lFW2oNxarxLklQK8pzHs6VD9Nuq6ckZYPghuJ9sksobIdk3ygphJbVdTy6rDCjp5dKTCVWRHC5eTLpOiaJ3rCWy+nY/ifBcLxOrjSx33hoM/7PXfNk9z7kSGUFOBemD3PR+hZbfIn3B/y6qIv0WHkmz8utY4+5bLdhYzBoz3NfeUqzwIVEeTAckgTmWXOUBBuUYLBzB/Ui3rtK0G3NLK9pL4ypCg7qqmzNsCyKQk0pooLmkvdBz5h4qLMo/VkjTQw8bPDTppwJ+I/lEjZb2qoU+0i2x6yGIXpsGAwy11vScOYkeMMUWyOsSWUiDf2d4Ju7eHYzLWii5qXPpVABCtCJUc170La+Cr9TO6GjoGnoeLaQ0rp6DLnLZGE+GJjI0nacobyrvte9M86urtFmMd4TT+N0lpTezU/dz4NBotFlO/8MiAd6VS92wHO8Z5h0LMEAc9W6Yn4rURH0N4URMDTXuoVglj0N/3H2kNKlVB9fYzEu6l2iLxQi1Kmi1IrWZoDsfHc3gCu1eCh9Uy4JjJWE30/wY8Cw5vJdjKs6Oogedc/JDTOK0tpyRUOj/ZuwFOVKGuqt+7zmNuPxSc70EwjH4xFV0411ZhwA1CZ8ZGMLfQsccQcCcA7Cg4bSF958RQTVU3RQEQeaMEijEda37+6C19lTETEmEJqRKDOk5Jif96U8SmNGLVX+kj2X9gor5lB+ouhZwxmBHxPN1LNEnHgWAMQ7yK3h3PdvSVOtDehaOXV34kDD+0v8FIf4RNlC7YSwWUp0wLYqDG8WfLIq7Uj3z3E3grYGjTV6z5F3w9LFOL3ocOG0RShyHpjBTGg9TJrlF8I8P0XqEwstbutlcGcYhOERf+LgUITZh0UEUryd4G6T9Vc6J/xw5gsQ+/gaPkX/g9HkUyR4c9NPF3s9qin92Hjv5NgWtH3gkTjRwcXweFE3+gpe1+BoqMljtI/1gOxPrFM2RILyYWz8mOJwSQdle83wuwuA+UuDRRRoyGt2J3XScL7phxtkEw3gIh/PZxb01d6HDj/RpGXGsA6MLtoc8/uv7OW5AWA5kUtmlxOZwvff5Wn9s16b1yxKaQvZf/wYBgR5bVf3DcTDrd948dtWMaODl5TnNwwQ32D3R0XnjttPkShzpnGNb9Xj/Px/dnLGepd0G8xon774GLvi9RXKeGYc6x0Pz3M5SoKr53/N6Pg6tNvxFRN9GOmF8XQfG+gfhOO/Gho+OU/3u2S07/Vsd/Vmr7gFSHhDkwWbA9Z/jVw4lc8ZQE8YIL++/Fj9X8czP1ZW8Kn8h8k9COKt/owNyrPtDb9R4n/U8LQU8s8eWcEudNiOOPlW3spftbwp0N/KD5dfCqFhjPlLfTgzTR4OEhChBHdG7w3mFUOtAYeDCA7bjGmaMJUKooL9fucCGmBkmu0yZJcVCz/FVa+NDEwpZGHnUACGBXQIwJiDYCwvZ3d6mbxlUYZW/fk9Eb5iccHmEBjqEw8F9OLyIuaVny4ZwYYgkvm3zxR50l/RUYx5+/FforzmEn6qZEIPBDN+2+VieIXFJYjGukvm/5Zl7ScAX4lwlRTlVwpTlyB8F3k1rgxeABRcqajgXj1h4Pk1ZwD3EAX0mUwaHYwdxMK2lBmN0/CKSD97Fw+o2tmjEXQqfl7swl/IFIWkAtI+ypuUWRIhJFCp6gVEOp2Y8cQ8KLNNiX6AeLA8cVfluN3so33Wy/3Wbj4ijtsjkpBB18HGdwGxnn9ixsQdKBMKWX5P5RpVyWG5HyPcYUEthMMsoevOdxOYgUOz3NiLCzulhdFfRr3HNp7wQ37yII0/uIDNG1YBKC1qJIWL40AYLicJBQsMHibRPsKoljLuG4vIelm3TuvpeLIla/7rOXeNedZ2LWRq6KXinKSvvt7FFNJmEqQ/PDyJiVIpe0hOWhHxWPh3F7IXjcuhucxZrUHqpJ2p7LHuFMZnAtGM7/ffUYgwlYppV8Dq0V2nqvnBC+pUwdMEdFHkH9ss4ZlnGWfvBdhJOHjQjFLPUJOSM8iAHmAShbrsQ0etqrhnmDM2SIX0ozG0hnplsbS3NXcluQpfLZduJgzmoSoK++Kf5XfxUirne4cNC1UvHqqxZ6746d2Vy1D67F7JXEDUnJ6yvg9QeJzm/aeAnSXlizVgb9/gT4ztRHHiXoIk++4h0nWKc+uimFMFgtQvMC0RK79gwmyj38I3BMYiiHdxIZZw7L63Rrnhwkj5vuaXWCEepXjuxhBWjQd/6cnOLDmqlwc4lK/213iQ7vViAOwKTFcBJsEw6zsOWxQGi2ywZ+HbU3+GIBMFiKkxRCnSm3gs65r3lGw7C6O3lEQ+p/TauKaZl1viYVN1BuARyCNojIXg+a9zH6qktVYG+mnjQ5w1UzSWKvs87JiulXlwkaYfAOSMFUCU2UQJ5m1PCkqVnIqtSV3DrlPRKBWaoqCW6vl7Y+HEK703RitNjRY6uHU3hNAU1m6gaUI/mnWPTfmK+Gv7Q2BwBZgJvUk/6AYTrHAN53HAAPUJjIOuheEgQpl2ICK0+YBQLkBwTFr3jg5axHAUAwJa5aUXeK6YKGBFjBIZVCswA602cCNFesmLE4KTLPJPwB0UrzOqwWBnUBGYqEXyQddScZgPEsHj4dHbIAAdB4XJwCV+Vo9HDSO/A3aSQ6O1pgpLBvcGkOSYF31oAYMwafqXuTVlQu1eon0oHDbH3aF0k4gEXfjOkmFaeQJYiFPGsTUwEXZ1j0IFF2cXOLs4x9PhCeXpEeZlKjDbVNkuBgdyH1QY5EiPIKPkxPfK/8ulhnG36DdE2N0Q+gNAXAFcRbqOSzU4uxfluZ0VEfox8E72f25Ky+cuvHlhHI5HPB1nEDMelcbtIYagFunlCzPeAajMqCwczBMYZwox5yR7+Kgbeml8FcbSLBqCgBEeIfcAM7hlQHC0Rn1x/FSKGmxcgPkh4flQyjdoNC0iLOL0YAIBdAYCYSJg7g8a2vuoSl/zhX9CYQbVc/SHLsYhrCkqLhjtoatXekU5J7QE2wV70HlFKRfg3pQ2K9QbIuXADYpMfIxGW8gec9B7I3xdUxWsCENuY7XycUd3PjSSqcpzvbNseQSzyyUYmg1A71lwvqOr4Q0V+c2Mg3IkIWZ23OWGn1B8rzxi46PgSSogFL0/MjoKep/V+Ai+565IcAZZYYHZ75y2plA8acZPPn2OdQtluv0e6259a0vDEr8kUDfnhuWuDTxz5qfMMNWGGCz1UM9mvJnblfx/az7jmeFmL+VhnM76jL+umvK7m647Z2MGx0oI+dayI4TQx1AkxTrYGPMgB+/3RKcNToW//eo4xsZ9r9t9yZpPdzEeG7Hh5oX/yWbxoQ3LtDiAW5WAYXx2jyDOfFPA+6mmctnpQW8DHQfeGbwJwhW5H0Jxbut8txj+Yrh/Tnll4y6jzHCAcX/z3/yOl3SexudxvuOOk9qgePoa44IbBqYP70EYlftfFujWQq6f/88/lF43tI8dvFBkWynp4UvDWNYn7YeoOk9y2PDWz58HfEXm3FCcronB3SeXJ179Jjgxj+TyRwF/vAXhC+qHgv6x48if/isV5gC2N+25ub603nTinVPPl68t73cvlCVdWtIOixiQy+0JUsVJef6t0Kby/JQD1alCSlS3FecjnyLzUAPpF9p9K2/lr1TeFOhv5d9b/EL2XLHLJ+zmH3SI42ofF01hMDp3CUmrijxB10E1CpELA91zic27IS52pN/NYhh++QvkHiJQGp6vZpKEbHbRG2tKOPdvG3W8exC4MLIH6ZYRQ1hwj2P5RpI725/ScvQjjf+vZZp+sgxMQ3pm9+hBib6xdpS4M5WTgADZcSZ2AAAgAElEQVS8B9C0EdHdEu6Ue7lkwh1CJQgADXeouE7tvgNw7yl88xgJ0NDx7ksq3pr6zpaoqEJCqk/E6EnBa5f1YPIocrIO8iSDP0ZVZuhJJRQeGjprkbXsYbkUMeCGUGAp81ZEWHpOIiC0vkzJ9hLj9YDwUDevM4lQUdUjOV2x9eJrQ+3WPiWB5A8Iemx5RgUX5T+wJXimBauI9elNN1YFsiVMLFuKVnh44zVr+bqybGPjkHjXyznF3GhjnbY90AmG9U1CZIIpxkGbDLj9HTMUk5ACRkGfL9BqQy2TKHymCPkKsHhx84RSCube9fB3TNMONMHTjZQCFKpBvVi885So6TuqmPS91tmoPIhKQbE6bMYb0iJDPdwtvLkulCmTiyrjE9nTvkpSMJNvmZ8HM/VR6bQogKQRp3/2GcmojRkSOrT7b7a63pe+N1B0gxuGC6phXlTpQmrK82HfmNGZUBN+kefWr/wThZRaJXi4TdL8vAWmyPV5WWScQVmbJVHdx2xz8Wnofg08g+5NzBeOh4p5odmaLC6lIAKxKQYsDCuh941Qcc7XKA5XeOldaxLQWdWhBhgJPjoQiv4FOjIeKl+Xl8tiD7YEArITuU724krPk+Js2cbY848VXnwyvlPOSNCek4alG0zWqXH4GvHo5f+6UcY+29EXGdzCrIRYcpaTcQ5qnEIWypJQ2IwnkjjFULR2N4zsBA1b051xRoP3G8OV8ZKTdf2+o6si2x0zOwo+A7v3qqcdccm/tWGpB2JCK+WFKmzFw3lND7NRiO0TQSIFWHj3UgpqZ/Ak4caLhsM32rOE8eASGXROfr7sCnKcQ33Zn56Gtc5/m7dibaqiDQTCDGAHJOhiwHEVlUQ9OfGBFY5HlnDpxoZKa1wgV4pECelGi8lxlEcvse/FjBX0cxXaVkrBNE04HA7uzehrRGLs1UlSEpgyZuBxObhvMzaxB4Mx3wNg8TxAhHJVHD4KEaDKc/ieB12FLQ1iX83AlAGgSzoGZlGk+57rmt+r0sXxHBMedX3PQJp+SCItcZpc7MYCfkm81+29iOBg9Ate86jvnRHDlejIePR5/GPKdR4AmNF0YfbWAsV46Tzu2GMfyhc8evM6OvE87132QN42XoQ1hzP7+zx8wEB7snENRQfSVs/7GCaxhPQi4lwlqcSKN81r7MZ4CQmxIoEBrXBOEJLomtLbjo7KApfCRmzTN+vJDAcHOQYUp7JFPzKfYcFgfteKyeg4ln0ZX+cdrQeS/nJ8sEMyNLX5edXj+GMo+9dDGLd/3aiBzmY/lG/sWxWfGegGrT9d8ihfeHPJrm18MlrOeaWG5nn5YBwHQegdxV6RLq5z3kpXCRJeumyMhCHew5swviqccAPSh803f6kM8LHZ2Ou5rVPFeQIzPPhlj9Z/b3mvqL+mZ1tHe83XYQCAl2a9zIFuf7//wPm57cD0h4SUnz+K9/RJxfk//4HeGw6aq/137QoDiSeJ7c5Rvsxg8Lk+J9zg8K9P2P3xQXCPpQYA0PEFh4/jmr/klf/aUgAU3OL48SMq3qPgVvv8rLyZzgcvneO/eHkGr/y29n/k+aL87qEtlee5n8wj5Odf6cfGsfVulidl+WY4aWDk/3+ivCnY38pfpbwp0N/KX7rk8E/jFZT8YikE35To4uFETTwxCtlVl1TgUlRcqJd1cTUMQai2Lfdx7a0DIdDUcQ1X5HTxDrnF9nwgyvJb/XwqmOrSU9MFIMh3Yfbflr0s9ZQmQCJaWy+aUvc9p3A2b8VhZqt8KZoPXZmOG5xmWnKx9b3h2P/oL/I9fSfGO/UqyPm5utouFwZA3zHr5fMJkkPsQeHxHKKfq3wEA6jYAzwnAZzAdiGzOJSzc04EcBe1YIk8k3IcejJc3wJ0himU7ppl0pQXPN8785DL3D3Se0MpKhzjaCckXALnj9hm3M4gYjYr5vfyPf1OCMGkRLBgFRiLcpDVG2QHy1cvyszew2Oo1PCoZmZcnO3x8PSEqU4ikPR5pzVBYvqW3OtPnbf1bSDwUfdbHQMeztG7WwjtQ6CquM88YSnkoUNPKpQLhZv9P+Ak5GM84K+M8UK4lQRrW/NZKM8j7BNS/0C+kg+Y2vSVJmAtqrSd9fukogKW/F9EqsSeAFqFF7fVYJQdhZKFZME6deBA4N0RRIQK8eIUgad4Tk27SfqZj5j3HThKfrOyF2VDpZ0ot4k0gkNB60dZgCNJzlkwinmBk+bQTcsoe0CSs1u/MQRnmDd0VRFJ19yGVNTPkjREvC6n6wwQZjiAjA2ZRgLAkT2Fe2fBLa1311MJDHQ3XuncNbdiD7hj8yYclVYBRzIWU1hTZZe8mYJ9OB8binNrT+C0m9Rr8Z658utvJqF1tiPSV9hYuDXnQVahcnWtDL95NBlTXOmF0qukS+cAfhDjhzDMgITbzMrzVIVhkQQ4CXeQXeXGYnyQCv+KhXbuklu45yDeuh72+/KsuGI57UN4NMX8fVArtMbejeyv7kv6DudzeKyHFSYIg4ZFF+N6LZgmHr8MtonGgxEj/5DDyCYd7dD2KT5R1kzPLKtKgyXP+LOkYrGeFkaXezJ2UQEGOoOLKdFlLBOZt3j3KQHVUxgEHeAEvwukY6WPH9mr5fPAHt5ShwTaQSzp/NwxSKNBGQPBunaiPNeHeh5tjgxI7l9mtOOT8Dh5qAw37LFCtnYLfi+Mdtg7zwaLE4tJHhdG2UuuWJ46yixh8jkpiV15nroxXGmD6dpHqcXpaO8dKAXz4wPKfg8+HIYtf77EeO2I4cghIbdxsK1dMmLR+Xfuzjew0v9sQCB/pHELCSnRV+SZBG+R90opKFON74rnplIw1YqyKyiTeCY37nCjKqf/4n1cLJa/0l/L7a4vgUDYETB3xlQIs4aeNp6+U3OFOIFA7wrimOg5cR5HoT/VH5W/DL5jBdN7UUIBePANYpyx8F4PGQ/agg4lR0Yw/pgkOhUGzskCJg1w8ETAeYpqpSuEAwUNy+TunGzeEoHn6EZ1dmCCHyxUkhEu+R2zq3EiQ72k03lD0Ug/FtDq8TvAewkNzx31vICooJ1JOH4cANoD/UnPyfl5mh0rvSTnSww0bCy2nGZskaO5yNaueVVSXItuBhHkdG8ZOUmMaiTKgc136ySaIUauG6fAahDErJljZw3XOjDaDgq9772jEGuI7YLxfko2QsfRRY2ODdZZUwIwqivPHYbSOZOPzygUB1we52EZoW/47u+nxR/Wa5zJqsvNcdgfXr00km/di8xgwfaf0+/ayMIyJtoad3D5XlrCoSxqwZigZ2n6M+2s2l3AaTAgi47TsJfyISE9RXnfUcJFJDigNw13zR27usPjv55kHtpvNr3xNlP39t4dM65PzX4BG/54YBwX88qdbjw39kwiU1aJGAJJzTa+voaP/NS45lnrWaqtnfIF6Opxv2CvrywoGo0RC1fo/0T5aZ3RifVweqpfr3n0ul5VoXFb8jFaTWFEuPJ+ngCNcDL0yad+Gcsft++lHf4M4GalOL/Ra93ZP/9A6x1P//df2/jDjK/K9gI77C7Cf1okC4leBI8QRcw4++c/0PUuOH+MkOt8Yi++EPBBozjMHz8BuMHujwmdZ8yal5zx+x2bbhiqMP8iSnR8lq37dLti6e3918g4/63lFHznknFfRo9b7yzbfa7P5+rnd58Z279LGXyrpOAzAR8YnpLRTtvdSH6HqHmA4TnaoDN4Fjktjd5Wdd/KW/kblzcF+lv5y5fwJAFcYOE4WIUbDHDv6G2OzLbFBB9CHSSc7gSyXHoepTqIReetS836IpkJwyBQSReTpeey0e8bRF7rwjK/G2Z8NaZdL/FIcwzRFvvF1D3N9TZEfmFVa+HE9BKKCtplfjn3ObOKIl/i5v+mhG+LiL+uYjDJW+UOqkSHyHevFwxm9mJYFlcE6e/O2zHhgsUS97vmQi8A7lX7cQERTtnePWp/5wAehrGHL673mThIhoXyZXQQqv7aIYpogijX/H1VaItBCg1thtzZvDGfvwQ9bTzLeUaHEMbauJ2lWouE6OTxfB1egM3RXytG39qsQr8iXvUtK+7lcBIATw0IWddCAAqpEv0Mc2ubfHJW+C4F8ZvFJYF4non/gTJcfJ9r1gTHgAJo3Eodj1A8WYalHO/Np0Q9a7y49d6y+tKgKN7ObalyngHBsM3hiuqi3iRh67NiNvrV2ea5IvYRRO7BSyTh3i3ieQGwm3aopbhS07y3oeFSSykSzpQaWpcQ73VKymtVuoC7hHqnCeWpgUtY8EL/knpCu0WvKrwiZ30IuqkQ4N6AUn+ehW6IYYjOS/MdawQ5ed/OuNFiUs9DXxvFA0eAd6a4jLUlaJ5bpdMhDJPzZulRWPNhgiMU7+CBrgJwE0blo0JkIZ1lXdwDhuPdvNGCq/Rg22gTfDGxCJXUE9e/azGZCnPXOUHDkxsehLetWzEUTp6ZrPTady0ZLvhfq6/wZ1FAzDDOz0LqJ4Q2waOYd/Epumhjdy96VeB2VZ9brl7pWxY3ckrnszMQQ9i+Fn8/eauCADKGTPehJ19IhuPOpEIflfEU79mjrNaPVzckha/BtYvp6C6DQCuBw0anMcDcpMPlog+HrVH6k2E0exYyL9rm7NGqyq+aWDw2r2FToDAak+SzVsVR4Q5mobdmykEaktIVmwbrPuD19C28P8EiPwFmzcEMN9bA0QxPAJiix3iBtEfBalewZ11dlLwcHGcj+GHD5euqed2X0W04jYNAKOeqmDooHiXBE7OmhyhgoIshIhfhsIgV1AlD255S6exM+S2NJoCO+eEBIKAdnxIOTvPWZ41ijv5rEYNgKgTqibdaHFlFnclpjl257/jWX8pxa8zjPI4uE5SOwHPp5j7N8JRqkYq1gkpBrRW1TsKTsfcc/J4HMkrCvLTfVCgMPgphpzTzfKepuJQONVLjsnemhKQRbSX6OfICEGOhrABjSDoSOwcs3vCxjIxI872JgUaeiJNhXtregZRQop6K+wnARVqrwBhiZEdmTAUxEg3FIbsi2Nr1naWg5XJnSCQyttXhmEoR3tgNFuO8Gp5xDpuMxgCuGIecpSWuNLxH+fty3RY1yODV1yGf61jbzD+kwy1ryv5lsWlxe1uOY+wgn5JxrOPnyC1vhl+GtwpZLLGgO1aHOfbN6CujBQz4357GTL7vbnTAJlNZRFLJ+G+J2/N7G7IUw2+rCXsD9oc3fl8Qws1vJ19DIIRlw/Y8N7r1zu8pP9XSmk04WZaGC+mXZ7+Oj0YcT1TQmxgYdTQ/wAOdB3lElOeGSwDe8TrXtxkEbbCsMaT0MOsveWNbfVTbbMhQeSnNe+VSrwe1eDSa0siqWB5ve+13eA5vzf9Xyo3yIn2jzTWeep5vst9P/bwFpY+6Phccec+fK/94/x6dv6B/ZFWcR85zy9W9/+M95o+f8ZRCp79uROP4eeMtQvBq7hCjz3d/vNec6h3HlIudEwwIXozUjBYynxDPOjMOnz6648lv3G4vBcD0oeD4CWj44veqz/Tlr6ks3yovHd7XH+4f7/c16/Nn9f9MObV3DHGSy3zG6yEr8S6JDxvuAcFEwWVY+r7JFin//lbeyt+8vCnQ38q/tfws2nSmbcD55D+ax4JwHLP80kkEMyJZkRDutXqott6bXwwlRK4JHiznuF5InegsrwqRC8rowZbyXB+AiPEt3d2uId4ZJpS/AeOrzcsvFqbAG0UH2VeETRDtbWdPPP2mnqjvISEPNaWv5OQDhkxAW3bnW8L5v0X5swi1NnuvXy1vvHmQAybo2O7/qwo8rhWwi3xF5WsU+oZLFXCb4vyKCffEoiQnFZRJFZzrmTjX70+ACq0ZUNEZo4U3mP5uDHOBCbUl5LoI7wp2AGaYMLJgD8aB2YUwHRqGOQv5s9DElskFOGnhION9hMzlIeXBs3nlwuod0jeU81sWjd9XTxbtASLobA2dOmqp2O3OBC9onuNhIEQa7or8AgQGuDLmuaGWKkJhBubeV2fIc3ovnpvca/3wpRKCjKinY8tPVfLg+GPx++CRQQljMACWcIAWHjvXqxa+ehDAEkxx42HLXGCZlO3Mbrm/lPuYHcUq92DCf8PymGEF2xgbiCpkpyqYQ8gDhivSuYkUgtUTgWp4eEa4qYo+t7gAwAwM4mLAYNAEgPeyxxQeRIUkdy2V4grDot+JCmg+gvYNE00SmhNA2ZkHmuSnBAMTF3DVM0Tq9WQh3EmwhwxL+i8UO2WfapXxNwuprs+n3V6VYfC8mhIJItEDDuGaCbFttePk25MZhAlJM7aQSKjHYFNlOiMpao0usyvtOA3WBO52N/M32EJo2waKYpzUTb4nRSPS6nYuA3lgICl7lC/QM03am3zXEM3ajjjsmGK5+5xsvgan7umm883FvtreZa9H2dpRWV5qXSjNacCD7hHkSnr2yy4z6fpsIxoLQUwyIPQeiszOotJbCgrzWON5/GF7qySexpbGaBWnOtwjLD8nOItHY/f5d/P2MfgctuKERGPr8UKSZjQjpAXaPVvi6FSPUx0fpvFrGwNPdT2lgZq2+Xy1ivGivvc6JvM8HJTu+rGXjsIllOYo6Kx4kxizktUCzQdeSHLNq9FI1xMuTEQHKxPtsJ7O8WaZu/PTgO0jK71lyYme4vAy2A1M2NaMgYXNFlyJlRXcutKmWGR49gXfDDGuWRvLpu0eSle8Mxnxt/P19AQC0MDgg55TFqVXh3qLlg60rsp1oCGicthBIFg4zXM3jGgIXMLLMe11tI/xtNv2ABk6HHczA6gE4ob92TswGIenJzSl97IncY6Nf2WQhqVnGWWJlRLlFzu9zxFjShE8I0Y3iocKBRou4s9cSOh+KRIhrBZR9Fo0sdabgjKDSbCP5fYmsVpQgzVgnsUwWkLAx+6enYkn8+PjAwgV9SpRuLwXNnhtO0eTsEPtuMXwkp4T9ghNsp52t0JuYnlRTN3aN5mSPL1IdDz/jbGWVf38nvnYV3K1NY4AKgEHBnaGy+hR51wUv8feGx5hBorShcPi4FjkhAvt2RT4vckZL0o3NZgbLLIBq9Uv04yCIrwbM8rZGYgIU7UDb7gzn3NbXAPuwKmNVYmc4TQX3VfSUPClTJoWQnawt0UYe0Mz2kPRdeNhM2wLMm5f09jRMCLot/Af3fmqQhXVozVIZB4i4c+cRyNCb7PTFHmuXrXMvl6llmTIVNTgoyP4NptmGBIKvRfVTl4PJbFpeonQ+YpxrD+l9T+9LOlxWr+N8+J9JHpjcpzBqMiRXupOUxdxHjONVYb+3HBgKf3ZngAtP5wgh6sXcwz6U3VyFT1Da8Pi7QXmCBkl37u9q8iJxFiktxlARJ+z/et+RyhoTY09iAG6Q5ZyLFOsM0whauc3GIBK1zjiDoSQo4yD3ni0WKPnlirvl7EeR+64ZGhucqyPbsYrWK4mYQmHHQx0oOv+zSXWgJlEec6M+xQxAwiwvtJ377Bdtlj0LR3UKbbruXasfPW0gYmseMMAmWSSnl/v/JvJG8xAdlnPsDVBDCxsr5aesLneJQNn7+lkuPZrlrztHcBR33m50CIM5LbEzuQGMuZroAMH+oYbpAiOAOZPjEZf8Bns7d5wyFdzHuqIDzeMBgChKt27I5nXn+F9XnGL9kkjK2rfZhBgCliLlPm3UKbnsgS45fjzwc6bcAoH08ZvL+HpZ4o5Avzqsm7dt5Z7ZUrzrv22dHleGvSYA6Eb9fq9ioMv3hpI5mlUQKMsof4cziSnkNFPO7q9lbfyHypvCvS38rcqYVGOxOzoBb8zOjXM6qGKIsKFUqswCKUIwJNcIHqxMK0blzP7q5cn8UEzlk/KGMYkKm4Jspf3QSLCPYBru+CpcOEKwDe9GBFZiM2FVXj6vCKgaU3s07UKqUwtOAH4RIwbBhpLnj1AQmp9y5esxZj/ruVXQsacFAivXhSjhPt8918Is7bblzdCvdxdWTFcSABcM6GB8D3B68VCdpH5QPvcAZQ+CmEbswZtFDE9kQjU7IQRGMfMPEmgRmlDpdm9dxeUPbMsAI9h222cjwjP+dMeHIuvqoQ0RcrogfJj+2xrZAqjuR1RjdHLbxG5kYE6ValQMOX+JGWHScKRHjkLnAbucvVxnHsIvX6Gn3SByvJqRmOD+avVsP/SzAeBeO7DL8ALQcR6D7YFPCc9ypeK8w18W1JTEYSjg9gCjEZoVmAHNoMqayPhU4NPERwHziQSelGKpf+Qh1SSpzgmFBxR6AL7aYdSC9pRQred78QLvdSKWoo4fpvwkwiYCNM0oRwPMqZmynCA1Nir2Ek8dHDVfMSL5RWFw+Q0wlWb+idCkEo8CtF96HxN8UwTuEkKBZQSCk2kM2IeZQbnJbzkQjhKADP4MAP7yT1LV8p4Uzy44tz6yl581i47iTbKz3oWrU5uGwQJBUtJeepuKYmgMUTxuQhl7q+fOnuurFSlgVoB2LpLuoe4YfvoGKLEzvQknR3hLPIlU+GEFP4GBfq2BzqABL8Bx3b39XDUL9E0TgaEkHGLcohEwM/CQLHjqryPJy7HScGZUQab4RRBvPj1JaNJrhH3M09OI50TpAilj0QPbf9fS8KfLYtpBS2lkE5sVsjnaBQqjIqWVwyBIvIFmMGa8sTWjf3c9jhTzl/G+WAmCXGuxhHugas0HSjA3CVKBxoaipwpQCaqtK1b2OzFOXZ+nPM6YTUeaWQ8m44JmCWc+8SSuoLst1lXdxdtZlpiS2qurxzrDsQ5OQUTS+/LDkZRGF96o2faR0U8piUcKNTbm8TQhgowKX4+KiRYCCiGh8WmszNUjZrV1AivPzzoipATPsNRRIHfHU/nySx4s+FcUFQq2I6gYHg2FCnGKeTWcnfjukiTGoY92U9yB7jEHATvFVUMVjFyLmG0Q5D1rFVSCtSi9yNPcdTEoKwXEHVAFfF+VnRM9w8PNmGsDIgMvtzoq7txh2I4pUFBO9xYo7OmBHrwczicfl6vlvec1tS2hKn6eJYxgAZ1skVYW7bLQXeMV+rawxGMCYQKwh6MWd+c/H3hnxx/DMQwq1xTMbKqgLXksYb5MsD8pHhqZxTeBfhWip1lXxc7g1gUGv6GUZFVDL4qDTXVIsUR+l0NDMdQ2ONEyXAoxn3MGEwerffHUhY4zvLOq8Butx2umKaciZhQa9B/Sz3FnVHLhNabnBvl4bumzulNVrh39lUUO0sKPKDIesAPPmU7yyMExxXlBX5iCSyvInfppSzreKma8X4Y+cLYKcbw8cfI7+vLKd5x9RKN320v0p+X2l7i7VO3cV5swhAZYEOelI1aoa/k6A3swCNSo1OFsO1VLNB4Sm28Mf5XMnGvAbV7Gh0dfqnkTjbbG0ex7NfX5c+Awx8sNhZTpBPbEfn6Q+0scSxDvMzPeXxO6R9D85+fWIdLFlawfeKV4txKjsz40tiWT1+SHck4r1FuBfjnL9+wA1D4GtOHCmaRhR0+f1718fUE6sljijW5RcNnUPsDAPCebzEnD/vfVTQR229v929XNonev6lr5X+X8PCr5YaBb8l4VGIxpvO2oeC24lRpdceJ70uex8+w8jbZqdBSGG6J4N/g76383cubAv2t/G0K6z9XZpiAxYS4vaOBASroPKPXCd0E0po3lFUxUSCKuK7CR1eCKaNeTFPmlwWzChdy4SpPyhf8IEjikREXEB+zTUZf/Abp81r/dohn+leEVSDHjUXWYSEc3aL9Wcl1R4RbqCBPa9zonCyH9i0TvqiW4lcsHn/bxeQ3FVdI/ER5tfIc2xaa116fPOWkhWSyy4r6e2MH2eID7iQMNJtt8r1cLjRMwSUUVpldCPJEwJl3xThLohyBAR68z0Wg0nEgwo4ZT2CcVVHO7RlAB4rCd1eYfdDvhQrOSDwSiAiP6VIta7a8wojy/KACZvvdzsujvZUE01ZWzF1WwpTiZ9AE5Da/c6LNMPHPFUbHPB+Baeehqa0fUoUSKPKVRk5BGYEpL8zLLvyIbfD6J90ut5TH5mH747xl4BYT3G1d1kI7SMMPPlpLipvgMxRZiJDovheKL03MvBJgqSEQRkXgsudNDju9QSpcIg016h5vqKAC9PkIBqHUndboKDShc0OhHbg1x+XiZR34kZnB6nmBKvMnVUr7OrnisqTxNBAucL47x9l+j7nP2O32mKhK+yQeHbXuZaSqTPe86MzY7Xdoxxl9pzk1oZeNUlGODKYOmgos6YfRIqcHGvaWiMR7ygVisuaT74us1q5KkvLWJZRw1VzqvVb1vnaCBhO8duZhm8gvSNonK9yAYx+PDdiTCrAJHvJZhXfWxVJg52CIddhQob9Iijl2murnEuFdlOHOzIIEjIIorxSNTjezGCiiKZCAVsidta+hHV7kA2drIlotFEpBU06Zd5kpleRZ8WgNEWlAcyTbnqT6NgfjZQrUk4jZQ7TC1yPKYDhjMNY67EyzKq47E2rC8bavWdia19PbN/AoxlvpelGsG5eioGTpRSBpeXzfxEu1NVJjhCzIzRKqxXefVDbmyPiGNj5ZPRu/QkVWyum41DbG4dux7rIxxT0LsN7smDGKwgkGM4r3TEmnhg2M4kq93kU7O8KkKFNqYQ3TLrBvobQbx3kzwzjhjQmTBpgsNrfhzFpahnR2Oa+00sVu58eeErhrCkp9l5lBVWs8GfwC2BHoyWBgL/PfQz2+9w4bsuyWcZsU3rvDzdY6Gz1ex8dBzBNK/5mdH3L8lZstalCnSnOqBHXzhxk3cSOUXsAksy4NqBfnMl42QwjZu/74GHxNIdDe8EAoEsu58j5PrHcb+JiZMSiRbaSELQl0OjPWggxG9spIAOX3jR4s8CeHsYEYJ8YK85Bjm4c2RIFubQDdzJJMYVgIU60StL8LbewcBkuyTwVUGFMtmKYJu/0ed9+/4+Hp0XkGIPiYjKeE9RG/sNbge9G7GYoR2l2Ts3dpuJ/Rv3U0/g6GGoky48JWdIGGAmXIsfoAACAASURBVGmnvUTAISlvcIWCTpCoagiEQWQ57YMfawAmCn5vy9h6Vpx9oTeRI+l6qaFG07M8VVHePx4lt3FnlmAHyDyd2Y0Fd7nXKbH/lTWruz36PPtMCRNAB1CfAHT0/iRjFO0wyk74t/A8z+uXcG9KcWK0HQCaGvVQvOC8AhFQS9Xxq2e1YanZQlVv427nBQ3N6YZluikgVVZ420eqjCOTGsBBORZiHUkFqhj11zKpveQGX0ySu9kU6MIHSVQfo7Os9F74GYkYUktVQ48Bgpx9s1NkG2wzlMec1jJqr6KOOByP52tpaLtc26UsI59Vg+ElhsrtZt4x9zPesWhVL7edq6cL7ZpWb5XcwBYALNmRzCecbGijaBX/dRAwbbWXDElX7Ua0Ac5yMFjkItvbwNPL7uoNoX+5Vjr4bbXfxutfaj3zxHbnkI0Rb5WFCOzE6myfvO2ygJeT7RqvM/7u6VZsvfSFqnDbzBgUmd7J/PN6AKNxQQbL14ithv3I3zdn8bri40mNXPF67su2GUK/PK2g1nkkcfSwQhj3nVOfdu4tcpaVidce58vypQC3fRsK/JkZLg45z+nkYpeba40sl1pR3F34GtMf4oZicmFLKGR7bIbf90WiSGasau/l5T7/P2fo/Z9gAPv/8//g/v/7f3+7PPWWgYr3Mr8PhP5JzFK3ZJh/O8/zU2VFOE48X5bXvvfKMuDFZw74goytSl/SVUTo9m8lZAEfFMi+FcItB8yZfP8U9TGjfMFD8mFLlp6Xh1I99zQ3Xsfq0uik81beyt+5vCnQ38pfprz6opLCDAKQ3IKmIVTBS++ETvK3FJJwrYAjcvtPwir2RegvJXBFLqhyPz2F9ONat/IUH658yUuMojUmgkoXNSe6vH8NUa6TChG3wmOeXC8VoFP6zkwrXiCED6OV5O8OF/S/sVzzuPv291R+p8IwvdewP8vSEZa8uWwKFxbfGSI4qoDCRMcTM85AeFLlG/cMFfAQ32cQRT1zxyOL90o+h2vYj/IEeO7lny0hqIUL/kdJQpTHjbm/rugZMyVFknowTGhwmvEtFAK558qmAmU9lB+ehFQJ6BkutluNj3/Gd1eVQnk99vJcWTDbxlhb+9gWrC3bzPnG9cniLVMsdRWAG/PeUFhSeLjAM803QkQDnUTRWFRwK4J4AleRZJhi2xWcrkhRz7lacb7bgVuXXK4kfoW1FnCTEP8TFUy7/SDrIpJw+NwjVLwYcBCwY/CsgpldRT82VVgxGF2EnCRjJpBql1WYqMikA6NHNQF2haFiCluhQaXWJMhUHEBxMWLuGiJUIppQgeRNhvvWDsIAPjbUs522WUClg9guU9KLbykRQouAmAcgZ66YiQZkLx1ZsuePg55PG/SgnAcGJTJpu2P6Sx5SHsQFUhSKwg+MryONEQDQ+4gD2Lwb4oSZgttz1yMunrYfcRGN7wKXBu/kQp/8O6UNEAMH/WqWB0suYCGAc66AZSwiAJV16iiSF1uDTTO6KtdZj1F4ImfaRcqziRenKr8t4gOT741uum2ywHeRPNKiMKOIxU2k4GKKvqSYLrEfPmXCIsnjqc/bxQ0k0+sBVxaNwToKuMtl8Fhetp/epVPCcKKVQpTN05bFuKFzR1H+1+pnb1LR58rpLqzwofyzpesww1IiMehpIJU7EoLRhpwfRuR/ZsMaJ6ibE1FjUdOZZ8PN7K+ebsOXI95bLldqupCkXnjNBeMk2V38QKfeM6RuGmcisOKNAkI5O8Px8Wkl6CYFLPPq74+PuUXkZV2iLGBYxhhfgjMZjvJsSFJmjrksURkImnrEzvD2dNn3MjZGjCqaeGdz02MrcJp6dFok07Pg4arya12MOJKwsBQJP91LR+liVNYLUDRwAqfUH603HL4/uDGjHV6D1dHASgdBpvQXOO9dfHfs/d47yjvhk5k7+j2jsxi5ZqNNWypLU2Tr4njaH41cPhVCLRU1gq/HudLzY/x7U/qw04Ng7ZjdBhD3SQlprkYwzBF1wHG3JgCgadAt7BFnUmAjzudSoXWAGA6Y1z4AVcypER0VMM9iXNht9wFgB6Br+PQTp8rxXhrL8iUb1NraA7aH4zFOdMoP0Lr/4az7MBb0NtO7rfGvRqP0Xg+q4XyiCVX5sEyuff91zEX5gu40U2G2GCxH+G1iMegEk0Rp4uCH5SwkpsGmlw1iEv+8ecXjjc/GPL6EdJ8jva+Vd/xCOY3Hf7a1P2OUiy42y+l+f25UvPg7tmH3LQAo74H+hcF8BWgMwzzMrb7vSWRcrx7NixNYvpAp4XPv/9zun+ITXtvaS3m+f0R5/iPFvMstbWS5PAdNO/QvYxSBpryVjdOUuC8N6xJrT/ML3jpnV2AL309S5/GZxl9Snl8zhiwIVlZL9ANiqHpzk5yO1AjTeSQzGom7z/yprXh7WzczQLB/2yaM7z1VwsO//i9OU8NfK4IPGOVD8RDuX0nW0CQrDW9yYC+/G6X/zMF9oWzlPb9htRVBhOIHXjcdu49kPPQacPB7QFKWZ+X5W3kr/03lTYH+Vv5Sxe9di2K8il0KQyiKEJaCAQ0x2qmhFwJzkfBlvXv4XA+BVki8Rbh650wp7yBH+F6z+JJciCEsdS9YvQAvc/8WSt/JPAxDkMLM6OqRdQfgSi/DlRnXRPimQuy+oUDf8mCNzxvCNP25sYWfZvVrVGLLwDcVTLvn6Q+WU5Zt/9vKNwXT98q4fFMBxDWHt3QGY7uwfPf1u0MWtb1jEZw1zWVvig1CWPdOAOrVJQDG4939qh9reWbGOUQp0QE8koSnvOyj/CjDT4HkqvquudQIQAXjolQcQJJLsWuO9kW5AeGgrYVYePsCuwU3pYxwDYgHfC3uE+c/Xuj3LQ/0ZRj5XLJA28JxiRJNwxl3WZxCNQ2UPbd51+gXcUS3D0LkCrV+n7FEPXVLP/kykJXLWXDiq+0uc6PAsGsFy3492IkyXDBHZo3N4/6Zp1R4hmeIYxf4mRA4lEkceB3jXkfr8WmpKCTF+XXaS1MqhKWyg+uz1Btw8NBl9YpqKrBv4scpsa4IZS95yrGbgHb0MVvoTHlvh2kvAs9qOdRLwW6/R+/N2yu1SEb2IoooyWEuOLiUKkp6nVPv5qlPADF4B2AGiBi8Ew/d1hs6N3ARJZflWe8s+YrBmnOWRYDOOmf3eSKIpxng4W6rfmenc6pk4SZ57FjDvpsxgeYsFsV6eJPkPSsE8HEG7Segs4ZWV2MHatJeV89/pdtsIX+xQT91HgF6AYPuCW6CaB1Q9kB35Tkxlk3EvO0dCFyqsp5AQCcNre+HN84BZwUiRoSShP9ueEHFjTXs0ml8QRVNukexEXjIivURSWdvPAckHQORHnECkptZejeaMr0fQ89h6+j6THK+d3QqngZAwhmL56LwKBjOso2PwXFuABRPTmD7Azf6sDPMxJ5/XuaoewiSiO2sky4WHppVmR85ZA3uzRt3U2o1LkEe9vjbJk+qPBwWISAT4rWPCnrpLMq6WtbkgBBHkWObhpEVv7qfo8Gdnp3aBTUViBeUwHCCB2jUiEKYu9C2ktyoiVnSGxGrF6L026BGMwhJDDOH8rzHGRpo8gHBo5vCne2R4EfWsfVuwsi0Hgd5r+yVzh5UAnoMnLN1Z5DwoxM6HUe7CUtFUYx/lxF7uFJr0CfAADEq/CAIbmGHRnAhz8ltzFaB5hpUowcukHVFB00V1DGkyqBCOH6dQeeE/hhcCiP7ixtlRiySrcGZ4slD3BFMAVcYflZBwH5/joeHBxAY5+cXeDo86dnvAXwGEEjfKS+zrhyNQjZ2rb1FL+nuId7ZPLUMXnUNVPkXaYWgivPRnaxQQUMTw69O6IWxY0InwpPhqKm6QU9nibAiBjY9Rp0AzHhIF76zgWpD73DPbCICcUd5J+fh8O0IQLzOOwuYWyEADyC8gyizrwDcQ/D2O33nMfEiBKBojtV3yhMQFcmRqvT7oGdr53yQ5HuF0oXq905p/6h545vNk2VdKss+1N5waM3XvnPHBMZdfwQTNIoV4wnwZAlhkIacQAGPLCdhBxI6XwImeJ7FOKpIbnNqagTYjyDeYf/uQvdbeOmq/N/TN1XoKHErF+fDGPbTpL3L99lzdLM/p7zRhse68HnGD1n9qgPu3AHaNga2cQI5skMg+0wPMkKndHCsb8tfwGRpeBhEVfESizGjIUO9/+f59rkBxB6BoXOTkbQU6YklmgKBJJQ7GY/SHc+yz0Ew2DKHeDcLPMULHsjDPEVbR14qXwM9TDlq2FYxuhiGJYm3Sut7onq0k3CUVI+ZvVR3OR6jR9iou2QDePkLLce//b4ZVZ4eW+YItjrkobttLublsnLK2Owu0R09Nw4XqR3GNyNJA78OGK0TGQNI0tAFDwi8089budD7ixsYL1zpxzuH4+3KxCSh5UuGs9f0Qf6NATVmiohzbRWBT2tr9Ws9d/cLXvRnZG157229bwz18GJGfCODsLvCpTCjfC/7UHCD8qFg/vRZ+G6tdsXPK/uHOzWwkv+YMn3SbO+NANB3MD2AGqHpPi2V58sIEctynbTLI5aPZ9rQ8HdxddqeE65QbysIGqmO4XKa/f4MAFD/Z9bhieGXGO4L/w1c46p8AxNw0z35yPpOkUrBLXZ/VLTWMX8UXP5nRfIkAB1fQJ9u0fEFDGhEUigshNL1v8YDfVleSxSWm/YjxGSruQVeXGKpU3D8UvfLbfqDI9iCOFGIAbrt56ltHSK/eI+08fzEOEgN77UXMtru8qc1rvsT7Aneylv5t5Q3Bfpb+VsUZ5LI/QXkouihNe2iGmJHEw4QEairEix5NJg3AxdGYVEdbTrKLqiXCaZ8HK6p4UU1Sp9tvHK5NUW+hVf9DqD2jgkitLEQbx+I8LUUlN5xBQzZiE5f5uL3HM3U/pb0yPhQBly4BSLQfwlR+5Ew7M808pMVKUnstsJgnWaLxHIwvHO+E+OdCrq/a9VLXjJYhHb3HQzxEXyEKI0BuejZGao6J9JxXLII3e8JLuBbzGJlDes5rXrHDiRh4E9IK77qw/ONtnOxqA8KgtI3LS5ISSAj74vxCa9Ow1jOnv01Skl9+rgQQjAXeOc6RK8ybN66JG8ZwfwKzJLdngFEoOzX3YKIRRmwrDV6/8SG0KrdYP8Nn2zNJZSIKuIsGd+sx7ryrs3P9H3RhxSY+kgE0smzR0OXCqomgEXwzBXoc0dVL1IThJhSmucGqpPXK6qIJxBoAmqZUOsEKgVTKehzQ9d84h1itFXrhGlX3YDLDbkKYZpEFJ0NKcLzV5RifcfADBGSVqAcCRJxVBWspQBUUBC5kB1emYezZB7NjgtKyoaWFpiUSpRa0S38PWSfTEAuCvXZDSNExhq02ZRHmFkM2LgCFehkoeYBqhXUZlEYFADcxasWbUS7pt3V4kJOMuwE0w85ffZ3s8c6hceV0Edpdzx30YB3Yb9wEubaZbgv4k4MA9f1JV1/VRzVat7/YVCTFeVVQ/nKbyLIsf98TrY0DFes0nhIlL/IL54mZ67zt7UgUs/wMFAQ/oU1SoIpFGRcRQXwQyh+y+HuSFUVrkO/3ZVepsDPW8gUhooASThr15eQ4l8RFVDCT9CRjfua+TVfqJMYksb/jeuV+NDFD0PlUNOGoNXgAVxUQVewRVvyfjrM55cSv1u4+HpHS6PhpYlLLYoLc8qjqnitFPNgl9F3HXU3nnfZHlsUAPg+bq2jePCOc7StYvt90MaQ8ynR31F/22OzGB6NRv07n4yCM+IWf9TDMOJ5QzdLc0Eeirq3LvYqnCIy6PkXAZNGV9iKfHV+5rnPfS/tUCzWbXiAOD9LkBVsLmGzD08HTJP8eDiG6tcwaclMF1G672ysnOItieSV9jnhEg9ma4Ni8kuIrFFH4442N8xlRqWK1me01hQ+O/rc0FK6iK7/CoA5batso9J8Cv4/xpNwk51Lg13IeER5D6elqWGkWoL/EPyM9OxmajAsQxhD/vr7pjwvbn6h56/ouTNcDJyllAxKxqIt0psCs9YVvOwpDHQ8clYbDsqvFhIjDzNSOkA/E4HwDox79UAf15fSejymz4afejf8FjhEIrl1EM7AYFTdd0r0l/qGAaoT4MU5WR6GtC/eJzLM5jtC0FFgCdennm/Df27PWJSsmF+/au8afyTTK9MeUy1iGNnDSMaPvfId3CWlQFfLI0kN0eN3nWnpDDFSrB5NASBQLWpLknFhEb4ICu8Lfkc/jPM4Mb2fKdv3nZFmP9fdENXqBCn+2bKGvB8sL1TOdPCHmn1VhUSneXyecQnYvhuvlHCdK4RN4S1I20Kz52Zp8Clfe6LbiL5vHCRra6vO8+Xnd8fuCqeV169sm9fjPlWTIYrR187RxnfJ67hrVgjsx5lwo3+B8iHSWBz/9Umw0v4M08U5Wm9o3+4AEmePSwboM3C3VOy/cpynyoOyEhPuAVzige6dl5gK4fGVa3zFQvPMBtiMIn18fHqsvPicv1tqxfMPEtLc7jOeNosgxundE0lFGjuMfOHujwnMH4Rf+ZJkq6SBs7AYc/o8/VGdZnR8wZdfXfhnSsh8Jbe6wW4H3IDxN6L3/57yF16ULXghhIGEyXx+vJy+G49vIaWzisOZleen8exbeSt/z/KmQH8r//5imPyUPOpUPWc87YJpkp24+IuAJoQfrKEt0QnFFOhZWKFeYB1AmyXUrl9KoQSACTVfMNPQswA8LiCA+41wvFe0vUKEUiuqEjXxQhfh4l0TBcwNEb4BuC1S76YUcO/4I63Rl/XyrCyvydcCEu43jx0icmZi7CCeyWHJ/WuKvGsW68W/As38JSU6L8X9ry9XHDnP32kTO74GwJjpztc/LAVFgPSOyaIxr9ePNSwkReir/KPsu3qmQ6INMMQThgHsVWhm4zKx/QTJM9UomGjtzkUtHeLtbhfgB5XyvGPJc87MuFCvyUceV+0CcgG80PGExfECGXASvC05LhUmmveHKdFrqeJZQiLQW8iAADzjeZ5wASC5IgtX1KIhq00JpR6QHtJLh13SeTnVQ/551G+p8iSNtmMU1LMtzQs4M5eR5V2baphwblFJHqpw20SA5sFZXARsFdXK1ITBCiS9yfWr1OK5s10xwlBleY+w7DBAX+S8tLRjMIHzWoFhSloZFaOgodBeBJiaD5ImAFRRqaJjdoE/WEKp93kGlYqiij/vowPQkOUh9CaUApRyDoZ40k7TJApxXZlSCI0l2HEtBaWKF5wozUsIuyE0gpk9h7lENqnqDa6Cww4wOnjHaMeC1htKBXYFmNWDTKIlAGYtZUJp/02FMJL3nZwGkZ5VP1PahihCVOAKEcqbR7p7EhvppYJCkT/RFMy7Grm8CQDKhNYk5y9N+nQCam8AJjCOHgaBCqE3W48MsBYuXKQpohThkIT5HwplunqMmmKuKL8Q4VzJ/5/L2uNdcasqc80LFZxCyLuyj+JskMAMaah78TgTdXMhCf1v/ZhRgu+P8gdE5BECTEgfuec5cqoariKkfadQ4hkvUkJRsbSItzXcNOShEKPasovijEPAZA5rPObUBNspXdBjDu+6wEnsfEvMSfijQhoKOLsMM1A6gcVHXvdZDSK5pfU4QVdschvfaPzfdrEpGo5TRjUrXwE1KBoUpjofNi9ZaSpggbwtW3vHUXqoDc4ErBncRRliY9oV4THMG71Mdq7S/joos9A9FM+B2y2IOxUN+6kDTdPoeiRtfACLJ3Q076VUQm8LXtV4dzalpymjOHh6ZVhqPbOl8z95SckyNlMDqMOVVYAamRieWMKc8uKaysYGLoE2JPd5YYnoUTI82B3EyjzDUEPZ7dDaDLAaKeg5sfyehQpo8sVDuSgRVtvGg1Ht1w9CW8g0mwOgyoTsYxlWXmlhK0AFzi8ulEYAh+OT0Ktpkmj+rXmTrEq+FQtN8SGMPxKdJEKjGehGd/Q8qHuTR4boYtBUi3izHo4HUBE+Yp6PME7EPNJb71qnAx04sNBAB0JXNBcF1Y65Q3JqpzNm8N50LzwXNgyO4fyf7J/eG3UddtcTer/E4f47CIQLZ/DsuI6rnw1npstL0Pfv/r0AuLm5xfztiAd6wgTCu1JBzHiCzGuiauZxTmM6gGMHKnVFUQR0hQ81qKqKhXqXaCIzF1R0gMTczs4hQQy590yaAinRNYcs/eu0lnGe1o5szYTT1z1/tGUHs94/6VHvJQzcn6HjASBC74qjGQrgYtzBndG/dwAHTJfv4EYdCPQQuXMtjO4SYAEztgcwGOowNMPUgBOy2VP8Znyrzdk91402IYyJDJczgibnlCzCD+qQOgNV6WlF0GzFNcxAm2e0ftT2gq8vII0Uk0LnKy7uTaPiKR9JTQbGjST1nUKSGGzYmpDDhJ3rQhmeyaNKyJlPwGHHYEFjR+MlivccmmPc+fuz5dRL663f/m1DLhDkIM2Wh18WFYzWbpyUtC4nje0Qr24N8VTxdnwO8ZfT72vZh9HvhAi9enw2Oj6a/9nrW2dr7C/PJ4NH/uEOwHtcg/HNo+Zc6St3i1ltF5npDQNnt+/x9OWTQ+yLRVmLNSt4itAt11nn60Q4cMsarOLB3WLbaLmNiOfmFZwzW5XbW/iZA9A+fwb6DTq+6ii+upL52xfgRtmZrwW4encJ6h0fv36NToK9PDH/5bjGCHon30v0jgF8BwG4x65OAAGHNuNA8Ih4p3ZNFOc3AL6i0bbxhS/OxoMt43sgwsrfkcgqD59mXV9N+Tag/Ybdbg+LQAcIveltHu5XQsPEKMw4Tdb3q9FMGC8U8z374x8Ot7UUEG6xlu7+vkL+7z2Az0pDlAzpO4wfD+F+zX+DsO8DMvrPlZUnusOHlJCPYXi+RBRbUQLeM9ALAfiKr8oXWUpRjyCz6NfkeLygZ37ffOHAM4wXi7urIVhTnq94Al+DZ5t+K2/lL1veFOhv5d9bgs/8qULLb2ScMDuyNsYfEHrTzSS+9xCQKUIvKOqey+DKLtzKIf3y5Tyz0XZhzqOSy+R6guS/i4fBVFLYXADcC1pnVCLMpWBPhD8gF/R/qnCx9+5CDWLGP5nx2eqbMN0mncZpn5i3eQcb20SnrcR+VAn9lwn984PjXlX/SW7L8gkZdBiDatAJiEyYkby7GbhU1rqr8CSHz/quCqULFotheSZ/z3n7aJleDJCwi4wxAkEuzcendfVvhnmGhXLP40r9cce5MU9p7R8g+bFeBAvR5qUGbdB0kvHt3J9lwnLo9pc8vLMFvuVdhgnBvA2TP7zOqnLrHfOM3nq+Gh+f+AysFnRDFYjxuvYMCqYQhrHix218QUMjzjyfkjGl/lSFC/MCzUy1y6AT0Nq743Uiv5fqW/ueD51Q6g4AoVJFRUXHQelEB1DFAxqjgC9bzeYcldIeYSo70I5Qy4RdqSi1CvlhRsve0KRKU7ArON2DnaCe0bJA4jFfEKGySG0KxHu+tSMa1PuoN4FJzZcmHkimXIbmHU3nmFTBaoLQUlBIhQDMaNzUm0+9CDOdMLziggjdtxJCYbEAGgUWtmZZsVshIeBb66iTPCulqvC5SphjZrAKfc0rxpXjSZQXZ8S8pdmFYpz+ek0W2MgRWSiNjclyrMe73nc+wKNkRUIYu9JLm9bDQIRQnpN5nEv1ovS/qKd5eBNK0GYfG1TnlGBd5pHOpp0PF7j7Y4dDH5t/+BW6OGIQ7iwCelUyZeVEV4VOrsma53n0jI5wzYOXP+xd+wzNo64qHiqwvOhbcw0BndHC5xD2Kb5to47i/1EhHpXy3LwNGmFubI7Te4LDJNJD4EjuXfMeJ4Min6/xd7FeeR2ZoYYOrHSN44zYuut78FzEXT1yCYU6uvVrLyM1jiQE2iQaqshLAnYTrgpmYo8G4Wvm63QA6OxZkF2wG2siR+nZj4A+DX+kaV00p48ZJxTxwJ0Z4Kcn8UZqgZ9kT2LRjf6kxj2Eu+UvlC8Mfki80Ql+b/m8pOcFJJkPWubwxFhltzvD4aDe6ApT5qXMq4WNcyQ6SQZIIyap5RsxY6IJXDjC/SoOrKU6THeW8OGtz8DMKLBUIh3H4xz3OMsNrwpyU6JbCGvuLRSIyj70ZrgcvvaxnGogYqHd/UVbmvAhN1VyRPIwGlhRqxo8KRQfFKgllVBgj/jHaN+/h4CUAKhSdX+zx9O3g7Rk+8iC3pqeV5NwNzAmaJoAm7DOM85V7BSRGIAwFb1bqJddF4Okwqzh+AnnWqvgHSQ2Gnxtg4awYYhh/YwfkUjkozpL3n90voqVbxB1wz4GDsCV57ZGAID9ehwGH3n/hkqZT0jbOxyc13tn+bou4MUj7yiwWYqCdV0OnK5AISll1AitSNuGJ7gJvB+OB/E61wMeEVkCH0H3EICHzAYRuAdAsCL5xl2iuOg4FKIRfuxpTW1vU39rI7RxVzKGeXE9NxHZ+M7pyouXfoKtebb717Q3NMDj8z+pGN1ZjvuHutykh88sZP7JEO3iR8fXuNam7+KVjUXu/A2FREGam/ehPbv5oWQGgLPbD3j48vFFmPMWtO6vK/70vPgabJ2El8utHumCG/QSsSathQYAX76Mob0JuKSvPmfre8hZvt/h9mwP7h1fHx/xnynjGr223BEAkrV4t6j6jsXpw1o3setrQ59bc98IuGKBU/5yhem2+jsmO+5djApLDRpkxlESMafJ90KYP7aIxoM1BOS92n34w+F9/tjAfxDan6g8B4DPBNyy0KKC98KTqKcydCx/eUX4v7v8ibj8V8qmnJ3GW+71K8ZOw4eofTLq1rpLZbviTvpynV9z0nsrb+U/Xf7jCvT/5PFZErcfla38TH9v5eeLCdWMRZc/psQiF+QXF3aEUqG3Fp5aVdWZpOHzxAkO3KD5xHrIzTO3QzTmSoReGPJFGhWWGxaApd5zQhGC84rJQgMDYJZQazMVVG541EZvlSBx77hjxi3DhaRgxgf9+7mzh0+96l0DaNlFSwV3QyAHEQAAIABJREFUlHKixAr6fL6MUwkhl1mb/wqxeyVR/TPKzyrBUwM/XKYONPX4R1J2HOkbOozJZ81ZJb+Lx768ecUiVrqg8G590FiLD8S44Ut8o3tcmIKATDynQyYRaO5UKGIe5w7OLB7kZyze4BcImIiAf+uyzFW1LCIQ2V7x+zyAE0VFlRraUF8udvwWlV3gJh7P7gFIAaoeup3Vc/+FzbSoFcyizGxdhFaWS9POk4VUnlXxWlXht545xf8zzrC/ZCY/OvAUNjYvl9vkZKHHlgzL1uXFsvGOSrMsP6y9J7YLir8s97CNwRWJuRFoXjCIIshmq/tFRNBUk0kBxQCVlFvSngpOM89/EdLnWUj9WqdRKI09PDMtFXRShTpNsr6mbDTFeamjXCgrNRGK9FJ3mOqEqUyY9hO4m0EKa35NAFSAJorEqQKYRFA/1eJGGWYYME0S8re1hlol9kNTz3JAPekl+TB6b+hNPBgZjNYsfzL5/oRn9YjjO8QYq9TiHu+lFKCJV1/vXZLl0oILcvgM+ltsL8mwBVyA7MCh+dJdCajKpdYYU5Fcb6UW1EbgIh73zNA87izwgVAGFk3V0NEhedLtwpbBjmEacjv/tjb+Wk91FhI6AWczoFOsq8gk1tQgTvaEvKPAvQIqFqmCADNYcLgqqNOE3W7yOoWKr7WtrZkDUiEP7e7767AeivY4FxRneaFYNhiBTt2NLgw3Od/CAxg4biOIMk+F/qIwDy9Oby8pFTkNCQy0Nicle+rHP444NCvP5Tgbgi/icUmERmb8Q76vNm8ReCXcsBASxK5tl1jWxTtGu43uKEyIh2D28CZ/ZuPw3IqygumsqnLLUi04HRRlWenqUa94JOKC6FlpEeaaGZi5Ka6TNZibpAqqu0gtwL5WQGti9LHbSeSMuXVw8t5lsBvZ5P0xdNCeRgW+Loy/X4nAZ4T+pF7YcqxRdrpeT5IKwC1d6CirEzpYKUaGOoTIz/rc+O00QDm7ZrjQHT68QQNM3W3yhsQ3s5Dg/xwjhWGplgLXElRp2wOP8tzC8JYKSI2ExAgkxtht3zALrudE5m2o5+rNgaXZru1NLuTTkpOiiumZB/vew+MDzs4v4n5C5LyiedILnMT6MMcqeW8O25GDuZDwROa9TSSGbGTgpHS9c8NxntFKx053oPWG4/GYeCVdp85Oa2Fta3SF3hnV1hesdgK6m3ODGbLF+Qgjnn4vYyyXQreSOZWs+Hf55HiWHsAg1FJRiLC/ukL/DjQ84ozZPc66wpcJWiy1UrHkuSzPvt/fAyDUKjsVrG8BUcfcZnQG9opPq9ISeTEg03Bg3i9CRAphNIDtsyrPC6MxAVzwRHYHeACjS2Qp+7dgbRmS8sYNdZjBLDeJ1gRPVbpQiHXTbwAsNuvE6KUDfC4w0Y9gEArvsXt3heNdA2ueedATiArag8ypXkhb871DK4ieUN5d+NgyF21GmJ5LPHlwy0axRkvQ1vQHTucQyp8QBDf6PAHnqTz8v+I+TjBo9F/OI7kRg3l6k6aacXrCHYfjUfhBNJjBpAxkGP1iV3Kfk887DCM5DF2UbjZuUc/xoToYkJyt3FszfGEr7CGPjX+w1AEJz6bfHX/YOq9m8cKDLfJ9gn84XW/LkG2rxFODBX+yMtQ4Mb6FU0WMc1wAbyUY2O2BmdHECgSMt9O2lwZ+3U+zfofymvrUUqwk/mVxI9gs5YbGPfiScELqkQBcMuMewAWLGTOzKEiZRC5y2TWVHAF33qC27/MDbgHs338AGDh8Frq5v/mA9uUTrhTdmBra5WyKg4xNfMcid1ka+uRCXi/Zr9ny5S2gSBWyKhR8Uq6fwe+zo/GvIBInCXOguNR+7hb3syvld0zhecW6hvpKu7oEuKN/uwMx450tY+JyZB5hfJaL9bTMgfwSPFhbU6nQqOhyv1Ob10oVYGB2biPKBQPMFLhFBghCMpgoGnVDYSbOyxj55ZQopEBg78raU3zOeMB8dwFmSaHDBFR+h/lavM13kLNxmI9aTeQGu90eVAvm7/fo9M3XZ3l24jgbPpRvBubHjx+xTo7wfLnWuj+q9O74AmiY76b1b17f7ar8itL9FJr77eVP7+DXylL+ZWXpsW77VDCGb78B4WshfFBe9YYBJloblVg/JuP39svQ38sRNlOT9l6qQ3rHzIbgeU5vSvS38ncu/1EFemIf38pbeaHEBcx4Dr2qyW9FhKkoougiZaA9c6YK5qF/wzuuoBOjcoGI5wkVKqy0uqQXPtZIgcrfuOztFSPP/8yjjKioB4OGgCsyaOZgHXdKeHrv+IeGKXQFAjOoiwfHBzDmziD1FLrtcin4pC25AGRxYQ2RxmiJu2RCs2fuj5e/6Sn/BbpuYbSWOI5hl6DIa2XPbxiWxdXhpEM8z5eD6rjHNV+imYAp/Wbfc54o22MLSfp9cbG2nOY21uWYCad38ZyzYp3MZ+XE268rlts8BhC9r+3ugfWIF2OECC6zQiVfmiNgpCg7C2sWepLLXBL5rHu0C+KpuaQLEW2s5ELUtyEEovGmzYu/C6HQa8ppeRSt2o2v5j++1SCFkCg3kdoixAVAkWoSPuRVGi/5/olokAdReg7qgAoL/QpN7O+IwLCAWBTFZrxginmiHTofYJ5BrvhX5t8UWpVEgb7f7+XHEoKswmoYoCFqS1GPvBngiVw5nL1LWcfbOsB8RCkVrc1os3gktX50ZXdrHe04O/43RXqpAKG4tbyvo0psXGhZioekr5MaHDBjBtxz6SUjKccPrrTVsKv5HUrGB9qfCYaFTHfUWtCP5n3ddX+6h+gmtMFIbaQ+JwQMJhXLJ8qE0a5I5qjPJeBDWyQucKsIAO6JDvO9DfjPQmAz2APCCzyE1MY/FL9fCtxVF6B4tAup6PDpSvSkoLI+3Yhg2J/gilgVKZye2d+1TRz7C3GhHT2Z7bM5tDG6p2bolp+4myc5uTECp86ZuxiB2I4mFL/cU6tHw2cK/OL7amkM2Pk0UaqHgUms2/oi7wt6ojgu8iPC+YdYcxc4bzBR+jw85IPYUoJbB5hcT3/n3sUTFQWld5Qi+cmtJqf96nreiC1XtKQSOHY4j+tDNCEG2x7HXhvb10kFmqpVXZ4+eS23mX7z5SfQjh3olkJ68+jJ6/UsNjLYOUCjSNkPxwEXDBCga1s0r+XQnCnX0vAHg4s8J6jhFIexrK25eTe7UYO329EOs9AANZyyY9C6np9W0Ki7YQ6dB80ja/P0Umz+5nM/LnmQkZjS4v14K3GYnIxRQOhm6MMSEtropKSnUKM3Lt5GJcF5ncPgV4yWFV5J+mu94ziLB7qHzOfAKZ275sxOedHV6Mo3J2HDwHdiHupO8YpIQgksyvNSS+AkZjBVZCsOwqXqrh9RqaCWCdM14fj9gENnVWCEF7At6BMsAs9yk8JQ1tI5Sa5rUdt3BiaLQMYwuyzF5d3zqI80MtO7caONNhdmpRMVhTuaJUQHcJYgpdnpDnYn1o8p8Jkan1J5BPjclsv7DtMPg8Wj0qjAY76/lOiTK16PEExzrj/YCxK1gR/Mw/IsQy2my5peX5+SvEpr3GZ4Weef39bvgidoxJu6JjZyduUX+eFSjgEdM44HBtUYhxiLEBo3WOo5X44ggGl5RgjQbt3gpYMDeCBsDvKybKyKGZCceiew68YvlO5wG/V0eL+5PEsx4pUTLOS/v7xuJZaneBz88tfFd9PcOq811h3fTuMh5YUNSv08jvUJiPtDYE0wQpG4Pb089+WGbG1QMIOXDICuxbmDpS/CNeavn1DxHg2ft7vxOSsfoD9fd+CbfmFknLWBPxfjGs/kVp2fKzn64IIjXI1hq055dwGejyhPh+GdrGDP5XcdB2X1BAY4DKCJGAuWy2Hqksf+LWKjNHWNriHcSce/pJ8/ik9WO2SKQxCESkvpIIAe0O8Iu6t38k7CaeyMxITeOtonXg1iK+IjAai4Ffz+saPhM4zyvtaDHgBu+T04w/ori/Ov6u3+5nH+9ytfN87BN1rA2ysU36fKKWX+q8qv1H0rb+VvUv6zHuiEEJL+iczsKfbShQ6EIWzp72F/tseRy/96FLPmPLe+wldqEGT9/+y9eXskN44++AKMTEl12u75zc6z3/+z7e4zM3a5Lh2ZQWD/wEEwMqRS2X3YbbHbpYyLJwiAOMfpWl1IQNyc4VcLDzdODC70tdM/uXKcwZ4LtkG0g0FoROjEWMgZvxRiR6YwE/iQh5QewtiqCsUQ0GxGYV2nVGYwW75l8fCafGgeLsio462a18RbcuGG6gjZKwqhFdJhgizSDOkn3pW3UHwi4BOZt7PCzsx9068YAQH4QQm/VuY9JCf4bTBrZy7//p9MWEOo/D1lEg498uxb5aO//NYFTpFXXJBBUA0ugWScAWPIFeEJZPD2w5vX+PXLF1wr4cGVAh0M4Gv5Nv51r9u2eHuaingCMj/ztcxODK/ibOqCxHsiXG0s0BkjjFY9qN1580TkOc7V86PvzdwkZi8jH8UOKHGaNaXgpLi9kBFZOG0RgWg3q3Dve819fgXgYVeIMI5M4VFouawiBzZSuE/qniwu3GRirNJLTsC5f4k9UnHiijAdwrVUFPjJnYDM5WvzyogdG9+PsNUuvKZN+98E1PnIGZ8Mz9sQjTHqmqUQzz8IO/FJxKbjDmi8n86hCFV8eQ9IJQ6AzL1aFWZUJLfjcO1z2QFgTcVuawefNxPmKyIfrods7xbKvdEBBDaFxrpA0KG05ppFWNPmfSECehdoB4jDo40A7VAwuKl5l4opz02JDuAs0M6ghbAsDFEPoQqD76WxOUF1hXSg9461r+j9BFWCrLbTNQTcCouOQIQldmi6OOjF7DZu5vUUEVDguDgEsL6ekToi1sGEY8jFi/VAfB+FyLNOh+I8lJpA7Db1b8wYoAPUQWc3bEAHk9MtV6iH31oqoSp8qHvQOT4LRbGBiBaPCleepRuEMXvEFtKWmJz3s7rNUy8EIwH/Oa3zuXBI93Oc8Loy1H1+a3MdU07w9Sfku5G3O/bVCOnu/AS5xyYJdPX54BJGOvmj4I3UUwPr1F9xJd/w2ii8VPmbYWR9/sL/32r2tcqIPTq83MLIr9QX7ata+FjVErK9/Bs4sD7BhB/d+CCW03EyAxnWngIuYlgJxHMo/Ki7thVUpoahn14DJsXvhOvr/VLXRQk86EtGRJ4jm/I7TR4XhkMV6XXLrKY965T5pIGhrBUxQwbLt20GK8vCIDUhZhL03MuExu7FqxGW2fbS0my/rn3g7+Rjfakm/o7JcUgo8IcnUfftqwTwQhC25xJKPAX4iqAPgODBwBtXTg99ugNk67wfAT2ZB5rlnBzeUrn8xSgkOs7Noj7BhfBUEF/+0sACVz5fZzfwMVoYaZwiYEOiqBF6yuBeFHw8gOgAPJxA5Bp/skgiqmpe0nwJNekNe6fuhT6WT+58PFFdzAkfcqU0YOhglVXIvrq+KXgDqCGyW9lPOdc0QmErqXvnF4OptB5CGmsFHqkRXSCWjqRjzTYhrkynjvN5xbmf0UAQZsOHQjBDOcWBGMrA+WRzx2TY00iiADJCwSf/Ua/rtleAbxz3urEJqfEfxtYxWjG8sv3ptJ3fgOhk4ZzIcpcrKe5ELQu4I6BrcuV5WmRQ6Phz7kWBG2ZAGd3x7NrPUHWFcuxx7/e9WEQDm86iRA9a5QuR52PnZzyWOzKMuJ9lr0H46hj/GgVOtNAmvXa2U6fUJYTwcL43Oqc3iXfF9xsloALmg+q4DmQG73LE9c0B5y8dD1/t+Ur2BWnwPwxS4Hx7N/ZHwKYtuP++x4BaoHfzTM/94qGl+fVruwzPc/83lM5U7gFhwKHoYs+PhwMIwGldE6knjAE4tODOnA+kMIDnySO89w7RM5osaIcGOXcIBOu6onfJ1UhYjgbCGHSaiXG1rmdALW2CiIIXezfoYj9bv8PYZZpNCr5JBx31Z3EpDscURhQFvwJmGJjXgSCB0FeNvsZn2JTAfRv6XLtpvAlilvPdR4t3k2KT6KATNB6Xvgwls5QHsa7T+L7V9qYjY49tejAtaSLcAHLnd/Zqst7PvHmBF4LT3K3xmPNSVNUv89/pSjHSaYxeA6qQj8E3Gk+jGPxUKgeV8JXCiYAQfLkC+EpkHtcKDAu2scJvvANnfAY+vcP1Dwdc/5//C6usuP/5fco4BDWnevBSAbvDICg8eIPW2zCsLxFdLNqu87aljZe7b5TXqiYzeQzOt2UDRl8S7odRavCQ4bXPPr9Xx6Otw9fbTK93A5PZBI+sUNz6d+rfzTPtpIH5Yj8ojI9mJOs0+MI4f3v0mcPhkLyrEkBsNMxyfRMO5xUR2WW4Db2B0hd0AHdkq6c85Awb1GH3nylXzPX1s5i2Vp6VafeoaM1vdG64YsaX//cLIMDhpyUgHMSM8/lk/DZ/dkmN0440QBnzxADajz96v20tPl50fx+nh5PTGwWuf/ob1l8Ux7/9B/77l/991vhzeAAI79HxcWr7D5N689+8jEgs8/XEy6B6hs8Ls12m9zo80d+q0waiXM9tO1Euvb/tmpmmPb+liNu+TLWUc2zITqOtf7b8/6W8lH9k+cOEcN8ysFEuNucTz7bMb73ePv/e6z3m+qm+7fX1pTiTrnXe9BI3PzZZiklRNQ5dwRQpQlw3O8X5oQIj/GAjxtIaDstigpuDYj2vWHlFP6/ocoZqN4tJUQDiSlCCcBFwbsmMwg4Ck4DV2EPNQ2QIaBoaNyyNU18oKtDeTUGngOUGVRAajoQROtXbOa8mrIzDzABgV/wA+IEUvzLMAz96rHYdTGA9Tv268VogKFqEaCtrdgH723XdrMC/ahc8FSJmr0cxP/kGbR4+o656wAkFNjAU5mFxK+X92k3zfxaoKO4/foKQ4hZDGH2H8Pw2JuU6V6Z2cBz8kh0vyiiGheJTF3rHF3d2lnUjjOHNGbzPhCO3DFmZoy1uniq5eOIYtZwT5zzItT5/NzUQjMW9aO59hus8XIPwgFmZThsmLxRoxvB52ELtaHTI90Ah/Aum1tb2sDRXCmGD27z+updGrOQyYyGo09B7Td9AQ7CRPUH8k4o60kdA08eZe3q0S9OcRz/iXsUBVAYVz7CPA+pXAeCu5IkqCZgUILlR8pouKq+RR2LpoaHsUbeWdTyayktTUjZeQBxh6EwYr3w0YYgbaByXI+iK0fuK88PqeLeDGmNh9gP/FdpCWNpixk8+/3QgaDeP1zwwuGDTlCOmGOemoLMp3I/Ho0cfsSgkTIuFtnbFAnMDa8d5Jeg61JbhaQcNDyXPsatqYUTZPNnIc7OiHMxEFbR2rPAoKL6/mtNAW9rwoB5rEAqi0A4NbzP3kvNw/U7aks4Cir6OEKu2P1zAHHmwsYJWsZi0YsIIEvNGDyWgetuJzdSNE3zvJ5BlOwYg0YeKN1JJJm50NiHeiusp/1MAlPYsgwOccZ/G4B2+R5h8M9IjMJv3JTOB2wKmVvYZBdme6YiOG6qEHmiPGMLF/7gorubignuEIZLdS5jKdfWoNgUtqQFZCldjlkQEEt6jOrzQrY86QrkjaK/Nt9brPV5BB9005fcwPsqldkCbQ6QbzDE4VfwefNZRV+HHCt7fm7D0glYkP5VKK9rwEjvI7ylBhzjcD4V3pamDDow9a/PW1Y2nwvtWPJoFUeIv76gZ4LhBg9EsAnnO6TSEUTIDHoSHDdCCPyV1OGGoe6sDgi4M5sQKI3WBjyNy2HeJcKCaSj1RxboKtAUcuBEqDPTkpMDBJ/Qc6xk4n9Cn8MGVDy23fM5M4HtpNCm9O3Hfrpvv2ao3IBj8kAuPRdBZbGrcgMGUwRaFhGgdug1WCzeq9l3wUHw8oJ9OpuzVsZvEU33o6QQhowfEZuJKx40y6Gbg8tH9wk8QwHo0OE204ftwGTBfjaDsI1djupB6WRhrD/PNuQROFS00uXaj4EUR8dQUcGNhj4CiBGFJukGA02L3vO7dYYhnZbDn7E4kkYpdQYMph0UFpGz31Q0RVS0PNDRZBA+ibXRayfg3aNL0RhGdxE0W3zDk1hg8a3o8t7Dl90kZgrMSEB4gbgJCOKoZRquDeSfNVBkatJcXNHbDFyhWDWMnwRljLgiKAwTk+/JEbmDja57Gew7HV07O7ryPByhW390WC8Ww5lWhoxJ0PN33C9hkWIkR7N5Qc/CKmutpUWU08YahoDiPl51NZygdQE3RyjleVbHA5mxhtjpkmIBHT2o45bKVE3DD8NSeeXInnzKeXk5qjM1t6INf30Q76vzRMHDYlildh3dUtKML3ABHsK5niCrOWNHWSEdkiKme33LvFvIV+FTLvk4WPcBeMaJ6bUmYgVfWR3VSY7sFibkY3eANqrnBzku/rXzruxRcBHf4jIZ0+jPdznNv8FkxZhpsYqXbgA7vayefJRAX3Nchn02tXfASFXr9IzfYyHNZ8E/Zws4oFMgQjDkjmt8/toZPl2ir8HXJfg06JR90o9jfL4EnK3qJrrudIISKDELLPAIuP3uL5YcF4IYuAMoZWcvcqF9nVEA1v9t30ay39VqBL6STQXqN+JFcWlnj7XXgyOEYZvVkZMe6L595rUDKBwN/wueNFHiNsTqHthgNPZ1ybEqmPH8tpihXzI4bFaKw83t3n+TJY2OQ5s/XMGIQxer5waOPi4+LfbDk8zMiGX7BP7wUNsI67WajETUj1jeUfqq4//IVhNUztL0dhoMohtx4AwrjLMxzxwCWH39II0T5YLN3fmbO83cKMH7Ef/60QFTQf1G0H+nbH27KDwow3kM3yvOX8q8pExxuytYwNf4uMKcOwJXnKfoifAbwAyKS0WAXKixWbE6VtgGGgJP/cA6v0DSKf+Jc7s8VSMOYx/TkL+HaX8q/U/mXK9CzFIZkyx5uD0N7BH1bHnvn0b/09PNt3/b6iieua/lHetv/Gcous14PZ4+dwWjvyFAEzxHqsh5gskI7YEZ4RRChMWPhlnnPFgVWAVZRrCLoIEhfTSAZRIxNKZP1eMj4zJ0aB68YUCogtXhvqCt2TDlzaLENCdo7OiwconT1w4Tg1gU77/1QIapQARZWrAo0rADEFR00IloSXHiP9LwHFD1yXanNTDD44aWeDD9RHhjHwXqzCtOGnVfnW3v1n8W/vdMd68o4a5bri7I5+FbZxUXRAZ/x96s/ihxWUVgv61EgLYZfkylLok837jn0wHbjFTRzmJ8A995UtOMhlV0KgLlBxQ4HXTW9VVNYCIBFJ0W+5UXXPEfckjNJPrDKHA2rQuvXfVg4OxzcqDF2X0lxA5pCvc+FR72hHFET+kjkBb+Y+FCqEu57T2Upo+O8DpOQe1QR1Oi3VRGKjMIk+qEICttjzRVdYQ1RQd+B48ANaxezPtYCM6Uu5KdUFBAmNI88uGNolO+HODZxHExhnnX7m4oQRoyD6Zi08W4qSKnMYb7razkROk0vJoBd5zez/VuaHQLI8OO1OmkKGxnCgWn/uYf1dr3CcTKS0MU4I4xuBsCWGJoJWJkamAVtOYI54lW6gKQTwA3SO6g19+BiyEHxcHoAE2OBK+GJoXTGQjdYyLz7WmPw0swAiwlMAjlZ0NXwprCIJb46BKz3K9rrBhNtNyyL5VPnQ8N6ZpzPZyyLKydXn1HHt+E5bKF+TQhrs2yCeQEstHNraNJdGROKRFN2rqLgs6C1lvuU1ObVtkAYrbjRRuz5UHi7QYtqt/+kp3JKmXAgh8U8nWEoy1VGdIgYSwDNqqDO5rnurn+OxvLdgTo8BHVVCjoGUyWXwBXw9X8HmrK9MHw5Kn6x3+L0Udl5h43L1Ezq6n4DLMfsOOyaIr2hubdDeJ4rNFMI5Ek2/zilDjzo1jrioZ5B5HhjYAjEVFxwoaM+M2Qxw4tUEJf9PgwbkDTEV3TMp2qmD5iUzf5W0BtAU8A9DLRkjAcBF3Vm/b2qPM+5rHi0eHM6jE31Vhzi99PwCWNdRhl40t63+noJEU05zjHDU5g7QioWo/66OhnZpOBhiWhGhbeNJcx5jDF727aGERLYK9L8aJpT8T6YxyQSxkRM8L96Dnltxg0si8UQNsNMYGHLix7ksTtcxObsJzdwOThucGMeIfWIGmZgIaKQVcFHG4fbuFgJ5XkQXABER6hanslqgHjBBBCAs+NZuOcTFD3hyNfOjd9kXZFvB19jCw6Qq1UJSVuNzxZAH+wMgBuHTU8/EYZVAICT9bMF/hg0XM4n57mAamCrqsDpPMbVBWiMdlwgeoLe+biuN/zLQ6CMo5PtomS7ItBKwLKNpFB4KKf9D/f3uL65SXzCweY5v3MRVWHDMwy+aSs0U4ukxRYxgsm8YNkNu0gYJD15oy7dogGoZvosdS+2iGqiomac4H3sXdGIAFqw3j+AG6AroR0Nx633Ag64dFwmd3euIL8xOs2Oh6+trf61g6nh8M7G2NqSa7O8MbouXwd/EwoK4Nrh+aGApSmPT8FLgrCo4hT8AATXTki6k6wHrGAQVk/XBVUcou9+TbECBJy0W2QJtfm/8n1JLGho4GY46p5MZXwgy8++qhkwdKfL1ps4HzJ6qFhiWwZOFRsH1KJfMSV3OvhoAKoRSv21hX/3OuxcrAMOayFCv79zRZmlOLhqzdZSVlxxg3ju2QsJ7QYvK2ZWvZfQ7tkcCHK72u9XzXjMGrkOA+dG/XxjX+q9oL1qOK+nrE1VIHfi77nRkgpAzZRICvCyGB1wo6jVaWDQGQAQWdHagrSPAnb5jzGJkvxKncucCbXUdHGEqc+DD5zmsfAQabjrZx+SiAYzTAyIKGEk2mzFs3O/X1Ht3G/dAEaSOL0EmHnFn1keEeAn+YwbcglP+Usxot1sxxP/BEl2FgWOJ3LO/MdYJeefgsYXngGIeZj7Ppk36Vzh9vyUrYSicDOu6iU4N2KEei/izjyC7eXnQB3Tv68cD351+v+ZzGOSAIgS3kA9JznKeth57Y0Ci7xWZmmTAAAgAElEQVQHv2/F8Epx6h2NDc4PPx7Q2gG3/0sgfDR4IsIbn6JPpKk87jp4izo8jcWi0ofYF3k9xq2wXORffI3q84TnDX4az6eBluf255XPVQlIh0Chb9VufwLw7uoIdEE7r5bBBiVKoHc9coUTgFsMhXpdtgEPc0qN+B1ShOB7m/NVybs6rx4830Nf0ZhwOJhRkPYO0BH36x0YwKnsn/sNKNXyxKNnldgPN4fDPKLuchePwJGGgSkfNSO2pTkj7J6568dPWN69xfF4hPYOVfey91gBV+/fJ18ea7whJRAoPtDzlOf/9R//CcCj30HRf3Ga/UGBH/d88vfLu9hrrrSPXNp/FM/zbTe+E7v/aUrsl2HetENHAIQRvqqCmfEehM9MaAr8DcAHAo7qMoWC2bvj1iA/szxxdtyCjrPqQFfqvarOgpiV525EyjTqJ27el++Yi8e07S/lpfzByx9HgY5LZPlHuv571/2CMr6/jJBO++WpOTeiYWHnRATSOzoxxD1vWAF0a8PUKKbUUmKwShI7BQ+TWUKGc89zh58aspd+AJkOvPUkVXpoTy1coIXBFBeShx8E8AmKd7BwuSuZ8JPJFPHQ5oRRkjJGKMAflMx5IwQw5ETb6S5jhLJiZ4KrsGw+WMWxZjvPMxvwR2J+vodB3MgBpxtPVUPlbxw2Qtz1defDp3DCHXnebj9p33jo8OsMRWtK+Q7FtRLULc5NxmbfMGDCXy8tTQ1p7IfS3yj1IBOh2Os0XB2u8HA2QeFrHUr/vRJW5oBavcWj8hEp2iSASGtG3Xvf54JbhlZjZnBbcF5XPAcCLwXEw2DEeq1j7LSdqeiDKXCXxpBzz8NxCjFo7vm8e+qTastPm6eUc2DndBpPY5+SC1V0rvOJ0W9+b/u0/1ddGLete3ik+Xs07kXYT/YQnIMn36q1UIwEKOcucVEy6jbOCOzG7r3H+c446BMZPm80nnXSscZ+0GUldFU0WrDolbctYA+/zTi47kixuDLeEya416dBAhMyx3mEkYcfgJgabJ+6lygTeDHFlXmkIz3zAIBWExJ1CYG3mNJaABHD7q1ZGHT0nqHu1P1xWZvRN5TDmM9z5J9V6PC8KSviF4ALgkWGIE08DHfv4kpAhQihg0EkQ7kXdcCVaHEwU/dUJU+NQgBxt5itRKlMb41MgVcqs9CbPg7R0V9VqLpXWwmdZ0ohNhpPQ7HKAcMBU4W/SEiusDggHRPW1KClDutE5T92GHBPsoBBLTxD1Fn3VAkZnFRVNu+7UGYok1GDQ+wWU57b/IUiT8MgzhFfeP2lF0/U6V2clJ/eqK2ntxxKet30o3yk0y29eGWQiOjft3nmmK1vlVCub0PKDeW44kKQvOk3gCF0KO1HPZWuxPqojGsUPB3GIcOLKULR7jduCujilVbgP4Td3dd5RJxxQYXqFPZfSw2EMf+DnVUHgfBItWs5OaepmOpAUY6b95b3adF/qOHwvA5jTsbvylQMgNbiempKSU3cNbEpVPBE2d/bkhR8h1+OqB9YFptDVShORj9o0F+aK5wGN/bNIZ+Tb0wFzGtdYdbA014qtVLUFMTVbzMlTBiKmA1Asg+h1NEB64O1FKjS5LWCoIccdJoAFkAZ2hSsnPwbGQF0HDJWLuBXaOyMxoTzuc61gnoH6dH5jhXAIcN/E4oQmx5gsYnKmgKg14unXSHg7h7L27cJSUEnL7BM0pGhKLbXCAsBa9k/DxkSOwzEBp7MdBtKZd9GJDJ1vFBWRIErsj12YgsTX1c7eB1V4Bhj0NizI5Rv9VLKbwM/+j1GpVeFJmGLd/dxtea9gbf20EGud67LeCbSd9/fu0c7z6yqB39+VXqstYNzTdM+FoRdgAI4365ApZ1T8RhiqljXwPuxvyoddFyuhfNPXEBpJEnjA/tT9vCgs4O3if2omNe2zoVufm/nLFElec3FyyTfpbr2FjXi95UZjnK8j773+8s/kCw9ybTs8Q6X18/jfbaVUrms38rlq0/26wKu9wBn592n6v5qFrs7Lep0BtmO/NWP/4EugoXZHUAMV4KAtQvko329/HAG8AmE9wA+b1oYNX5x5BLOFW9+ByAo7Ps5f3Vtra7ItuxhKyu3Tkarz8prNR/t+OKNAvpwAhS7cqbHyve8uy2DD3HM4/hm8YhDEQ3FUgPeoKulV+sAVB6wpSH/rKIYfHCenTCic5px/dh1Cot+ohnpyWoxUjv4JTtTEY7v32P9KG5YCayFoZYP6vT2o/N8z+tzODUFne0/D6mUwpXoz6zLTqI/ZM71l/KvLo/v/b3yyWEz/FDeq0XmAYC3AnzmEeY/yrb2b14H8+BnngvWqJyF4khVR/NSXspfpfyhFOh/lbJ7Vnspz5sT44AereApxp3UvfhE0EXQ3dubwwVdJa3WmQB1JqgjwpZaKMgQJIsLhsJK3BgaGYw/wy0Zwws1/kO2B23lQBKepQwmhRBMOVIsgFUte9wbsbCbRM3aUZigmQgLOk5q1sbk3xCZECSV6E6IP7ry6H0JNfaZYJZuTic1THZ35tRHmteeyurZ5bFX/1X7YytseEz48NT3UWLl60HhtQILFKvfC+XzK91+q7jDZm4BnMgU5n2SL5iH1RnA0YWFlsvUBHgKuGLQBVcufDcRzywMDOU5gXBPius8kKvlIiTG1/MIhv7VQ1peq+Vi7gDuoLhxYctdMQBgEG43ocRfA+gg3OfsjVkwHs4iNXSplvPzO5LPCKt0SD/Nb24nEQA3Qggiq/e5tTlaioOTwvYNk4vGIieX87+hLD40Rs8JtfoXf9dyyYqFN6N5tWtItC16y8gVqZSh0ba3kiEyQUMRk99jU/aE/49dl4kBhkQt5qeM1BTjtW+XHblUcAU+NIa9fpZG/2xwRQTLSUZIpZqj2Y2yEuDuAr8lRMVnEL1KAb6h1VC4SuaIJPghc2GoCF5dv8OyHFy5PZRg7GsRIcqH4k88VLd7tLs1bir2SaEnRV8EJB24PwNX5CHcLaxnKN11td+qK6Sb8ryvK0S6K9LD69pzXLq3eSiulAirVYjFw+e21jL3b4Y7xvBUtBC4QzASXtomUBd3EPWUIa5QFw9ZbKlEzHPdvDVD+hP7dCj0TLnn8QmIzQBIGcQdtI48z9LhIW29HQcXlT6OnkUQMvsZ+47Q8GIGRk469yCFlrQKtpBDMTkWNj2GvAPpybO7j8nrJvcwZ6e37jksQDtQMdYZ+Gf2BCpRADCENPk8WYmYSwDVY2xnD3qtPtYCkyGPDO/9aizkCtu5Is3asm/Z5oRqfU69TvWwytuiYw8ZLoi1dZ4oyw719W81n3+bAalK9O39VGrJ9tl2vTd1Fobool5nogYfJ4hIJ9EPJVfoO24hndsT3zf1m6Fl1OxD7C8Jt3M1jwSyHAkgUTw4nB/YjXZc8Q33SGePSLEGMeMwRIm9a7+XozW/nnxsDFNKn8ZKpEe8KwMJCu0Dt0+zf6TMtUI4pqJxAqxyuV3qta/TWlgI+YIZolPxfUQAiDpDGew4oAEQJgBHC+lOJxsgX+c6jDU6ersWvJvIv/c1WW5uINIhKhA8QHGA3vsQiFzJ7B709yfQFUBX5u3a7zXbIAB0bf0dWyMJY46fg2/x0cP3PQ3E4XusTMhkBDToHHIdt0YX4xkRufEX2bkqPVTIaW5LwzLWhjBuEBKPoEQ4PazoPNIBhMHXSVY3bDahNLtn8rE13N7d+5gCP1rNx+sr3N/eOa4O2COQmZYBdLYwmETQhysADO13hkOXbmHaXZFfphb8mtBvC+AVELYw8opFzXNtDdqnigVqZ0n1/PKxL4sQnlx5fvD5ffDtzXrlOPYu5xtEaO01GA0sXyf+KhXgeg2SlnSTxPgOlRWQAwgCIhlnWN/XTG5wgNsJW4veOpq3QUe461gb8cgx/PpNdNXrhK+Nn2oS/oZiwsCQB3tZ+Kvg6yKdRc73Vmm3g8+B4Y0++M87b+YV+GYw8cPeeK4nPMuxpV07ntH2vgLUwddskcGYwI1wOp8HZ00AN8ulG+cb8+i3M3+XDtHAZzaJgasGqZ0V8hHNSjxdQPBgmbs58R6ynsonLG7ck8CQDJfmupDTN+f0QdCM3hTYQYrhNgGZHuLCk5mw/TFP7zNo+aPl4lN9/FF0YTDy03tU/wnwpcA3mzr2mk16NS6suVmNSHUv4LL6var3RvNUqNzHqoyuZdjw0csEg9DkUiIU3W45JNzs9I0AvE56nCQ36S0AvIHiM1mu8/j6B30HUcXNzSvja7qpjUQV558jKZXJ384fBUQ/ABgGzh9dTvHGw8OnopvM4/21K07fYKME38LnI5P39ULopdPfNHDNc37M29PwPUEsubKfbRwggA4LcF5zHrf9e63Rv/n6cacH7ydv79r9Q2uBKqf7Efnn3Hv2FTBPd5JbtM6QbrgpNpBigElEaft7e6NG/xbmYfSomoafApNbabPIINq7G/v7+YxcReLnaJXufSc0ItyfTmhkabqYCKcPHe39mCN2fmD90CH4lPOWDj3fQG9/++FvxoevHf2DnSHEld8N730MHy/Acq/a935T8Gu+80fxPH+sPGdcf6aS6Y204oVhoppYQ8PBw56Y05w5+sXW/IWAn9T0E+98Mw10NWjMXrnIrb4lOJt9ONiEnRqjrb/z3n0pL+WPXl4U6C/lL1NCkCGuPF9hhwVTLpjXVBAJ9hBkHWbplZ7dzvhm6NiJCZ5OHunRlgfNKmjR+E+HsZe/BwBgikjH+Z61EJ4JYkqZZkznSgQwg4RwJkITy6MXioaR2c4VFmphNqt92RdnwJnMwpWoEvbS+ekwWK7LkX6EsMafn+v5O5Z6LvlKY+qe8uIGhic6+28u63GEWSEeqB7MrKQ1YRRfj3rWqstzkyAch+BLO+HXIHz1t27UwkNGfQRTphMUt67sB0yRfrPDzoU66xpzjvLsv2+O7TC27yRjKrIJW1oGuWHwCEMRngImqHsJR91A793zVNtXs85MXUhvHq1KJigTVzyEAJo81QMzYRGOzGGJH3K70KzUoQ3SmBTUIYtyCW/svug3sHMQ3mVynwK+vUm/tB434aTd49K3CDdc+/tU0xk+P+bZBTUheI8Dr7sT26GCgcU9u83b3EPMESyfNgh8YBCdwXyVuagBck/KBjSCupU8MeHm6gaHwwHMjMNhycN3J5PAEDPg+cotXLsCZxq5XttihhNsIhw+OpydJENy9S6AnsGdwauJeC23p0LOpoiXgwKrh8TrrjwXcUVMnVAyK3pXckR/LQcpo48JNhjgNmhKKuJNEWvK7vAwjZUlD3WoTuYsw5YpxeN7QMjyl18ctJzejRDk6koemKGawp2iXTkCmIFBM42crCu4aSoWJ6VvKNkyGaEmjIZKoSpL83CqDsfFKz2g+wJYddSEfDquTajoinKfY4qw+H7NTIAO/JH6ns08pYDWhzQewObavbJFFSU5+/RBsCWPnWkpcsmGkZ1zAuHZFkYFsf5a63dJ6yS6V8dd9hUCG8zedptr76TmdMcYgxMKQdyEcP1ZMcahx9mMyjddPLu4Vz0/B68V188uj7wbKRi8Y1AMXCk5XxhC9aq83Iwl6YBSqU/zPe1D2anwkNhllmJabT/FXKqFClakED2MVuDpF6x9SUWTiBnNhEcY+Z5S8bozC4R7l60AFjNE2nr6AGQaw0fn8TE6tfnG6QZTGMfqyPF7UY2WvPQ0C5C8WjOC6QAxmv8XBjJp/FI3wqPrP6JiGN467WGaJN567/wbR9SrGU8F7ouN7j7SNpfqvFU5f9i/l3tp9K8KsANrEjZNTt/RlsHwfZP5QSkU6UHTq8EBXfZHFTgrdBm9NTpm9XYFVDruHk64ubkuI7PCh1x+kJqiWpQyElf0flXjEQ7+MtEJyVEQedQWSgXM+DpwhK1TeN4pzABGPTR67OdTbhoBqaJ7b8V5dQ76RUHHBCyeRkUVB4dPyxHvynxc2VQRQ5VArwC9VRBeAXQHTn78le/tiI5jofK7iKe8CAK6pX4K1VuHiTFn9b8LWISnd6h74QamL9+UQZnnkvcm+mdzQmQ829mfHDDzyXuldkWnu3Nv5E7BN1zw0RYH1VFftjFe3Dnf3Cn4xvQvEba9kDoQdcfZ/gE7j06zEnruj/0YPwclDsOsgfkxzfU4bQyTgtp1AgHNgHrwTCOiSuzdxgu6rFM/hhEdTXXuz8xmPBcKyMco+jOLPnrxzy2PNK3feEWfnrXNe9/Xl8enpkLJtuYnDuBA8jOX++3x8pUstPp2Nrbf/u3dj2h23ALgBm+uCD//3CH0yXHpOwh9QpMfIrzU1JuL8Ux9sb+/xwt9rnvb2hbfmWHoN1DYVEL5/U5LtLCzp6BQpFNFLVsv81syZ43fWobSP/geW69eIpQFDq+4sXdBh5ghus9E7ZqxUftRSf4eZUTUHNCgqlj8nBbvrDB5b3I1avxu7Vn0+/bXj7h5/z7rJCK094z+UcA/esogVZx//YBOuolO8Pxy/mVNWtvxKz6TwcDhbwecf16fncc88p4T3qPj4x9eef5XLntL85lMYR57/ycd7xHs/mUUjOe1FfC7u//yrPNEHS/K85fyFywvCvSX8pcpwTh1FWSyYlFoa1i0oYXgNvLGAgAROjMO0gGh9FK0ZxghsmlkXEslmAthhvLPj+euxBfpEGGImAekS9vBHCE9XZBCLnxTdUtNwtcFUFG8EsvP3BqZN425xQN9tUMFXCnibbMzvx3GJL5Xy6H0lTcMbfkXNAveylA2BLcImfxqN1r9M8q3vvkzkevK1IQz/zbQXXigx4Fn5D4bpg9W5pHfHA4ucA+P8lnRIw4/IapMz1IK4ZSVu50JfaWKWzKl+h0BCy/o2nG1XGGRDpGOu6J86gjB3WDy7jeCkRvPbVtDw0d2wr01DW86E+TqkwKJ7qGvRz3lIJtWkqPeUCaqFI9wZyLTEwCK3le0dkQoIGhsaPesIM/FLW7YQJ47ORS5hhvEhVVElttx7SFonS1QZ0bWn2+sPM2bruxJKgKvmIMcUpmRIryu5XkMcLLa2INHGjM03k44ji837chYnwhtDc4RujB8AAuxCQqOU8h2mIAVNORwzO7N4/9brW5qHYRDevoshwZVRmdT1loEEFcsNsbSLE85hVJ37Y63e4YxjzZAhHa9oEnD4dXBFelBS0yZTWHJfjYvbrpmM+bidSjOACzXC/pDB53dCINMkJxCClfcE5w2dBuzqiaODyUSWCBiv1UEyoxzX8FholUU7yKW/RRTznPMynqFp4xAKtxtXwCre7anl2MsXcmDHsoHqnuSvDcOu0Jk+TZ7h6rnbGf3eieFdoO0FNiEcFDH2AlAelmnttr3vO/DIGZVPOJyoRlMA8JdoMy+7xOqE8DJmy9pBTg80U2hF8Yke4r0kX7D2pLisVF1WxbadUdJ3cd+qvVttzflzYAW8TaKr55HQ1AVINLYuDdnIBiCzp7a2/WIxrTcSDR+ic+3RgVahATW5YH/AsvE+CtWqt+nUcGOtFLLdNk4B81R/31RaUXWWc9O3dDpvoR3f3mjp7ELAI+GEfh/awyXbVJpryjYAYvQIaLoYdQT4yGA3bORE1YVwgoVgwMQwOQUqRscbJyz0T0NQ3oji++tVSx8OHxFDgU2VeHprUENpvQ72LoFXsnxXHl9D47/r7yvGRpnO/lbekb5O/aqqOmgoQRuy1iHaaMXugrysN+UHuHA0Y2zFtCRLYe30ylT8J68loPXfZUKJ9tD95C7e9AVWZQPOkLvH6DstMPyJtl5ouSsMOHtwde8rru1lmeNwHuQwe9RoKPCJ8TOM3dsXF0d8fDw4EJkpw9QwA3WYp+Jz33OfhrWWMh24mawxZy0nImNP3I6bIZW7p0l4vMw+FJRRTsaTe9dwY2xruvgA1Sxntdc+rvb+4TP5OcAqJ5BsBQs7WjGWbiPHcVoMKM7IcIDDMelZy8pronRcIMGxvn2K6BHtFeLzf+tJt2PPofRkeoJqzoNdHzqpA6NZ55u7fZ996Tzh24KdpAZRauPKZX1/Tb5A8at72HCWRj9q0c6wFfLNw/2Pt1B8TrhRuH0vUvmnBfcGc6mVwBucxdIbVuNd71TxXXZaQGHUnC0Qw/6ly9Obt1owvdhwiwsCtfBFg8tOMdlQURlo2vC+eEeAKF7ZIkrp9UPYfSX8Gj/HMPU3TsU9jhXjjciY/mVr00ktDEP86Ag6l7pgNx7aqhrhmQUiMHY1CggxGOPBj/A15T8kWT9BKidVU6rFFoMsB6hBPT+MGhpjA/B448cxIhvnVAmzXE+yvpVjQfjmzihBRU1PLeuZ4AJh8PRzkVMOclEbrSnhK598G9wQysYHjBSNnugZ/qSSNXA2xPwtlzS0ycfb4h/5Ql2P9vQzcs3qPx7SW0ur57u76wWfvzd5NdyAR9vv/JZu10qz1XnHmQkpTS43OEnNnVTgbOB23z/fHKcRZ+zG/vK/WEg/VotVzQz4+7XD/4FYQHwxut9I8aDnH7+Be3Hn/Dl/7nFCPROULJw2KymyDz88BMAoH9cp1ZrrufZLCXOIPb31r27vzy6RvuQ8C1YCAP94FqvlwUgwv3ZMNJrN/xt/vyzb493IarEkCGpwg0PSg7zbXeeKLOzBk0hny/zF9v1obUxcqftq6cVq3hzGIj6u4XuMbHzHc5raJ4gAJBF99MZboLj+C5DkfJdRF3MfVzOKkT+nNijO1lZVV0G7Cp9dfhwHh1QrLAsNKI6HAbUHDLoB8pILKdfP+Az7UHEt8tbBc4ffnbF96+TolxhxiOPzcvOEQWCj272PpTnf7Qc6N8qe+P6M5XtGfXR8ZQN/VYtdSurGWB+Ils3xnv8zJ/yvSpn3i7nrlMRCt/MWznzwImPjuVPAjMv5aX8o8qLAv2l/OVKWPpLBzrTCHVIzQ+mBGpDoQ3VVDhuCSD82tIHlqchbKII66pT+yZUDKWFwDwfPJCVM2vsAi07obIfdhQQsQy3TXHLxlwKGG+6okt4TWgKeEKBE8LMPP772T8F+sAIwV7O+o8WKuPVzbzQxY+/ZHmzmZevNKyc3+hQmP8Wy+B83Q/DIYgE4CGlgAx0rIru9+zDoXjYU55HnyKEux2YuinJ+hkLNz/YueAnuuL/3ZOFcb8rCvRQpr8C4brAWziqXGMo06dxVuHRc1nnWVrw6Eu7Xh40h8IMG4aiNy/CWtt/scOTEe2xqWZRQvxtzRRr92FBPhpHGgzsDYG29+NU7e1PysJR8e9TnEfZjsJ+z12j8ndYru6t2tTN8m6VUdTvIgIAh3KcCM2VlETmL8ZeMXFRFhVBHwCQnk0IwDeOZxnKisYHgBpEVjResCwNS1ss5Lmad6UwUgjAYFNUqa/nTcPxsKC15jnN7b+YHBXFmc2Hio4MnNTRuWK9c4HPwT2PVvMMZTXhfmsNIjwMpUBGb6h4trryundXTJDljFW10F8hiBGxVCUoh6bqsRTK9F6E1JOCUGGebbSzd/LdGfFVZXyst/0tsVEam0JuAdDNC7ARQXr3fgPCpoljtnCroeAxQc3wYRhK6hAUls4rpn2UAmcnflpexcV3BQeUMabXOZmneYTvZw8dyB6eeSi2NgI3X0uN+Z22pTVi2WBCqWH3644cmObSl0O1VEhIQTzlhrPIAZECwKbI4YL8ZqH10PR1TYUIdKwHQti+mafs+vRvGeU035e4Y+Ca4oFY+ZV8q/JbpT3dzktpLoXHxXjE520YImxFHrMnZISoTMFy0hcNMjyMABKe7BtLf4DhEX3xfhlvGcAYgtMhNaOGMWz7LZAREQVD+UoUqRsIKgRihYSCJPoAAOQ8K4bRhBnGAHogFyaG8g3lw/2ScseKF6LLVwR60HJ3xuF1xi9K1Oe4PcJR2zgL7JS9G+8Tgv+l5MMbN6h2EI72STd8E+9bHYyRHmKfR1EAeh98+cOAW2P6vU0GLwv6ejajBBymmSEAnuzah6r5dExHgZfkZepcArf3D3h1fTUOAoE9dBiPdDKBemAUZ3ZAIMjZxkxHn2ce+C/mY+FmgugI3wxNPNK7KXKhCunqKTokUdFsfEIAOsRJpPgat+y5cUt9BQ7hgR4CdD7Y9StFE4HiBKIr4LRCPKw2M+OkFiHpljyaEx5g6mJvU9WU/r1bxAVHwmHkZLu8Y9VItTCisgSjG/tCYTQfeZ50QwTAjFqleBj6PoozY6ykwlGT4yglBSvBvNAZRHcAbqCqWF4DD18ko6+ZAcCt/U28+HXwtJjPufHOtYNKwsIloQIALHiNlW5nGKV5X5wx4M7+dwX1GFSmWhfI/bKPP1RzV5zq7UIPT7DIXNG9yBOa1WV3KiYJurk9Zagrz3f2deZ2iRv3/p6ZGnT3QAdoGNuncYUiDuAMRuPFQgcnXIw5C546flfqKSVMQBjSOvkEwfdVzH8q1y8F5uy8olsBDKXRROOsz4N/mOFklnTUFi4jmf2mMuGE0n/dXO99+qwGHsff/8xiuABP0s+nP3780fih87vbYV9MxcZUMUBq59Oxg/Y7Es2mQWmBj5qk4ebHn3D+ZbX0ib/+MqEbs3V+h+NPBxAZ/J57h35UmFuItb/htL9RCLesWy37xfe/F5Zt+kdvQg70bmcNmlrgnt/iXfqcbz5/T51+duhpRDboxdOfDSPRKkcxnHOJcf9eRaEbY6OZ3xRPMxPrkeITddwcKNM3o0UkNXMjbpx1h1G2eiqO/rFD8Pn75raUtxPrTBde5g2WoqDj47PrpPLfS/nXlD0ofwry36ob0/hLH50k262PiNX8rZEz9uR/0709eSMNl58Xz/OX8lcuLwr0l/KXKUTBTpuQzw6X3RSLIAsRS+wh8JwwMIFciU3awZ5PrrsFubowLgSlkxDJ29UQNChSQCWew7Z3zzdHAhZywVzY6JIpOQhoLqzpJBYWOIS9Lsj7wUNiflHCKwBfSXAFRYN5/4SXwALC6qdrVbM85MrAFsxo17sAACAASURBVIEPJjo6LOnnE1cIH+13Pdgbt/qPIbDfe5CpVrb/zPKFLhmkLwT8qG8g+IJXOiyCq2VwEZE+WjfBPMIUwyOBEEyNCezevrnB6csJJzqb0M8Pq+EJEI5dr/0gfLvTRgMwvF/Mg+rU49re+kqaB2GF4lpm5XmEeq/1bhX399N4y8MwCmjs+2bTQZrniYigHH0eQqdaQqgbB8KqMDcFbBk/m1LUlCodIuqhyEaztS1VtYgSQBqkhGV3KM/Wbu8fmpHgCJXbRTZ9nplZhaayeRovkQtmewq+cs9OwrctQ4zfXbKKVIJX/FdxgbrS9ZFjHMFCCPsFTY/GnDDgxiAMaqZEj/8RiuCJKPOCx/y4egBEJhxnXkG4MkU5ka/bEcxmcX91dQQz43w6QaFY2HNWdocDZpO1dAYrQQ+Ovzm8jxfA1wxMaG8MhkXVnfFc+OAemXR2WD82LKyQ3tFawxUfQQKc5AFAQw/xqgv2yQUDkTdWdBhjRcj46Jd5/rGvx1iLUIJCPWRs7IqibDKUT+Y9n0rFAke53HXdUYRxhMhpHXshFLCqlvvc4LtDYrEBiFqePxZAuZkyEAWWgmbr6HM4U6dwYweyLvaD1xUpAKS7YgNke9nJYhoJeG3hRWx9j5x4oTxvk4FIjXYx9krs7Riv+lh0khknhVUdChRC6FHGSkY0nRzeZj1KWy7Pn2XQPq0ZOSD+VwTpwdfE85jPce3/6QwG02LUrk2ov6xReagpiIs587ojie+wLsDwDiwK8Rx/aV41U2psjT+qUj3hJhpFUZA7TIuH2p6V3WXNSp01komUdQwlevCBMs3X3Pnq8aOqeCCU/LbVC5AwVgnZ1lCoW7trF1AnsDmBYnGvykhJIu5HGRqsMLAI5VBfYczm4nMe+cyPpeEyjdUALOsDoA/h0R05vzf04uEC4fiflvea589mZjdSBVQ7TIirYx3JPFGDv/HFMd4fHj2CAWD1PasAGEwNGio8PfjEn6HUASweejtg4QjFQ6GVhed2r/VZbrUApOkpTlewftf50yG4Du47cHgaXcgwpqrzSyDcPzxgCc+yMIzYwFmCXtIPa//4eintEpbWDF+Km9+w4ZODK9FDWSzu4d57R187unSs59UiaogporXHmcXhdxWctSO2c3Ty6uba0rWAcHt35yQmUvKspjwPtzbYnDS6xvpwwvKqgU+Ew80r6OkBB+c7Ghy01XBLu34FhSuev4qnK/A89orEdcKmok1TAZ/H5grxe48YcoApc5eY39hXQbeIQOGlpwrI0ZXnHdDrcTbVe6iQnR31GqA7X/1bKBiMNyAidP2C01cgPeZlde9zTZwZEAHHg5Pne103NR792tN+JIA45B/oDTq+YsXXnL8HVVyTfRfGWleqWBAGkAaTYrEAEBFODK+cERFRyNewO0ycfH4zFZLDb0ULU0qo4EfUFOuBzTW8x3WqzSMW5Mdlr0Y9l7HpNekCQfUhv1hvFYRr57fufd9eWS+uLZKFGd21AjuEvYhbx+UaIOB8DmMDwvD7R6bjqIaD5kWZ1NfJ2zhnWN9tf1n6HDJPdKLESUxtc8bZ5eA9rDulQc1sXIZHDxwXhkCBr/J+6StmPsjuFZq6U+9mGvd6UMn+qP9ClnPR8fl686KizHvB3VNjOyXJ4oa8XTRFVN6LyIWlo1rpzHZ+kpFy49HCrjgftN/FEjkm6hkf+r/RwlxHdC3iujx8+Ln0s8w7gIO+x/pLh9InsL7z+6YYt4g679F+GqmoVhHIR6M/y/sf7Zz96y9QYHgBbwfk+HQLR9WYKDsU87SZizGyywZi/d5un57PF+HVAbrIjb06Af6yuR/X31KQP/4szgfbc8JcDp7ujCkiBiFpoIHJvN61KFzZ7FG4bHXtsNGY0NqC0/mEiGwRc7V1HnjO7t2Mquw4+7VEjvNyblPY+V5EsK7daS9APOiNNgKI0aWDAVBr6CJoymks1H/1qCdOVfgd44zPuA0+/jeUzzSU6KvnLN8r3zKO2IPK+vvP4nm+LY/i4z9o2dKlatTx1BJ8JuMpf1LCx/KNwoxq4s5jcBDzw8n/x7/j+lElOG130/bxjEP+LsLEl/JS/kTlRYH+Uv46JaSEfkBQWE69puFJgOKZR5kXXVxBxb2Bm4eEJPfaSQGcC7RCIBmWWnlwrYdV9zoUAXsY9/AWJGGg1S7Xg7ARQvHDNcPHQ5FLU/GTAOdF0bDgTk0xusJCUqkKfpCGRQWdYrzVewzjhJOdBTLRX05iHJV2xXd5eP8jlWBI/xVK9N2iQPvhLT59+jwp0X9DNZu/HrZZh9Dk8OqA0+0ZbTrMD6/xpzzf70oe89pOEVlMXgc3SrjdWfw7UrxSxh2p5UMvdT6SKjFLKgkiRPtGMPNYoS0s5/2yR8tIth+aYPiQXsQjNOKG+UxpknthMU1yldn5c1bmxd0hANobxNz3+rfWm2OLduNJoqDCCldZDjbPfmNJJWH2ZR7D86xVK4TRkHuSGTeFsUAjC4/e2P/TCBvuURaSpy/KAxFTpJNC5B7cbkyx0k5Y9AbL1YKlLYiQrgRgORwQSkKRjkYLCMAZBG2K8/mMRozlull/GmNpi/WpmeJ0WSw/uwKAEHp4gOtQbtgSMXAF0Eks1PFZsCyLwf+q4EZoEh7tLQ23IoKKzc1WaBd0ydpTFagwtItFfY859akngolWY49pwfOuRFFoCtzGuoZCtiiJ/Trhw0OJhpJweG3HnhzGaOm5r4A2Uzisq8F5PO8AaCXQAl8jOF00EV30OfYilzEFWF4alBRYjfH4y5V9oJyO8FRVC2OcY+LidX451uwbhqCu4qQZK2m+L4XORkfyUKwom87v6mZfF0VC/JmU337XDAZoFi5qFY+6JwnCayPgovAsPk/yiIhNt1cTvtYN7qP8d+ZTnBPZ0oRNc6mUyKmcKdkUIUHz7tR2VaLX98MIJjwB95Tnl79MWVTxNRx+g3RfToe1HcYxiecdpiM9/RASzoV8IirNUl+vqnTJ7S7DSEP8vun2NNuxLgWvgaG8P112YYv+a7up+AVSafFUGVC+IfIJs5bugnkYuPRI1RLsrH8aFCsN0xIfF4PW2PzeeDV+mIhqKBx9buoUEMKKIBReWlKOjPckrF0drww8qqWt6O9mTmiMBdjC+RivOo4MpVgqEksI1/xUxz6nMApyGhl0p7mRkHCEaPboMGxzJ6KmLCaFdMF5PacX+tpXU1A/uCe3w1kohRS98DRBy4D7u3s0ADc3N35kcrq1+j48WgQCYsHVzRtAgU+//AwmRmvXOLw72qQtr9DvzHzzCNiZTY/wJCu2D0TQ1VK3dC2e3IklJGGxmJ7Z+RFIY5YzZpwbaxQ7VtUMqsOoWfQOkKtcDENjCuiNr7GrifVVXhtNt7cp20OecaUqygvwPICGz31hnkMJEPijwhONz3HGVwCuZMdlGfii3Cu/S4sJV8FTnKFoOjzJ/64ljL/n7bVTxjxcYtf6xiDFcWaAzJFJ8u+drQ6/FZCKG+XIdIaejLfs40CUtteTg9jpiQ4jM6orphje6nGDHE7DaCEHUmQdUXMFrDohCTfBa+nMNG0n6rEJ3z3fPabQvXjtot6ZK3qkECa7zy1L8qy2/1FlZ0yXL+zdfaLXugsxj9anm4lINqcY6tWvLudtHsQWdGo56o9QCLqHaG/1YbDmmzNO/xixk+CwvKF9e8X3wd4Dj9OTOHfQzeeV1/JtBecbh7FLuZS18wV4ct2j/td6me987973ln1W7BnziuBBBg6vbxNFWo7RwGOw8H37jrJ+2sBH/k/ncZkzRUfSnYoIiAfUip3BiRtYj+AbM1Tv+AItp5zbz/jGXn26VG/iPQX3e+cNuDKNL+Xfunzg6YiQeyVg5bly7S0Ptj1DlAfeDuVlNfbPo9D48bwOvJSX8m9UXhToL+UvVSpzFAIEUReUqKmU4/AbojVmZ/YbgZWGt3kK6V1IfKHUGj/iqKswgYS4IKlT93DElpOPLRa8C69HCSFtWO1n3jn3UL9FWIYCKxTNPQ6+AnhFwI/dfBaFTWh3I4TDf7wF/+8HfCRTmoTwT0ejKdAA6lG7cHh+kN8enMLD5y1GMK1/RPnWObyWf4Xy/K2aTHl7kPrAX/D6I/AK1vfnK9HnEcd6LcsCke4w6OFzifD1y9dJoE4u/Yg7r3XUyrB858DwDg/luUJT2WYWw5L3QeH7a7vntRI6TPFec6CHMv4h6zYP+KeU51FyaranqQ0AVEeLsJqe6nEBMfumDqVV7GVCCL0GtDM3D2kLZKhlCcWcgLmlR/vkIeb9Se/z6K6W3eR7v6Xge5nyDp7WdVLyDaX/EJyNZ4BG5i4d+Xarl98IR7+VMD1vczy1356jPA/l2m7F032HLzIhf9PwYnOFJRMac3r3ChGghANbuPIYKDteXlTR+BqCNZVfqg9ox1eW41wIrA0cYdtLeHMCcDgsgC6AIr2L154JEnC8ukKLaCGtobVDhu+2fOycSj7qa9YvXV1gyv4+Y20r5CxorUPVLedF0LhBmh/U1zniyeypsxFS0djvIuo0wKzsla3tEIpKyqAoBbRhbBbeTBZ11AWuucxD6Dp7NQyhhKqaQsVdZKqA3N63N5nZxtuaeUerQrVhWYB17ZlLr2kDWHypKdI4D8WAmhe6CEASdL8oCwe02v+LgkzVQHBZwrNSE/5COBe4xmpyr3Nmjz7gdwl5neOtyviinB5Cv6oM9v2eQnNbyfCu9im2dYNO+25g7lJibasQLH9u9q5WwdPAZ/Gwep6Xu+WvJt8SdY/w3rU/gzZVfmP+4/9SUZYHX6V1lJoC3T3F+DTn+Xzgyjqm9Fj3a2YadWeVNph95Xn9qZhHp+WqlHBon2YTCGOL2ZMAJbdsrM9TaRUMWC3UugF595Cay+LGHQwPI237xR1zig7EDT3gaRTq/Jb+ZB/1AXRFYL6CKiD3DwAUfH2dyvsccNBXVah7LQc/k+vjYd3pyr+Lazp4m4LwzA6PKTg+YOKMzMqtGR8vYnkwnY5AJfOBAwArofEBSh1hVGJ97RgU+ADg5AuwODyph9H3NSxGMwDS2GFa96DN5RldFW+qVIzGhJU/yccUfAFMCnHD2yW0DtSMkAAsHnIgfHDJkWkYecCV5ZGaIvDl8bDk+tjZpPmlppKd1IzIRBWyCkQ61nVF792jcHXIOegZAO5gJXRZzDOdUo0xhdbtMAPg+7s7tANjoQP6ecUCxnJl8GAGHw2n+3uAgNfv30OhWFqDeGoUIsvTLnf3WFTRCVhe2zpKV6h0MxoRyx3exQyQAUVf7xPT2bxdAXQKcoQOw3dV0JIoGADrMEMmAN3RxFBwK4B7f//esKk6PlT23OVR74B74Nb3rOFKyxysWH3Ne0ylo4UbmNI79jMlHDrug/H0rxz3ZsQOlD1cAPohF9Ocua9UcSJYPAkii9ugFiRfiTxnueLIBCjbWUYEp0hvkYYImEsam0QX9pjL+bt7AFeO1hX3IL2C0B0YN1CyEOyD/F4n3ajrd2HkE6QCAzeP6CAKpYf5oXdanYarABasSLDKOninQm8BoK8WaYGJi+IveJkNTSeUe9U4zr8Jull4kqCfEbWHE/EH31H4zXi26WPwYNm3if4GfpLyCV3M3cyhXHAxTluKidvWYCj4ivFC1jvVE3gy6eqgp1PrtWNTR2d6POwTt3A4f3gBpRp09qKHU68v+zu/s4X/MG7d3xbbWUZJM1Cf1T44x7PhcxSfkj+otcuAKsNv8ZHjmEbvseIjvji5f6sjIqLgI1jfO2QXxK8AwXKer7/+AsK7i5Gdf/0AABehrwPKR0ZyKouHjRGN5r5QhRlxJ4wHr8xpIJar4eMA7K8C+MKlzpydMZ9bZXeEcu86VmJPGR/17ynKv9IlvA8eP/66HObirfm9GFdjztRejxVC4Tsct8R+J68z5C5Ls9/rpkrZ8LGPGd/vnXIWsghlCsXiKWSivlrPoTWcTudxXkQY57nhaJ6rw9BRsegV6BXnMsonM/rbjx65g5eeUb6Qrb8C+K//+E/c/s9/5+gafsSv9AFv9eMFbH+rTKj6z1o2+HeLjv9oJZ0LsMXke++NEnLZL9v3APyowEem3egTW+wSv2sOdNXxJu/tq6dkgU+8XxXrL+Wl/BXKiwL9pfxlSirPdYgZBBaOqquCxUKpL6lQc+bHhWZMDOGGhdmEPk6E0pM7pV4lENWGoqh6GEwhCCwUcQrXnR00BQ2ZEDGKaIYIAiLELMEknkYOGeq5fBlScu/eE/AG5F4UagIKFtx9+IRGDUwWjnd4fXjfa78383ihRI8fKZy2y88EvO3A52eu0b9jecwK+SsZoxR5Z6sn+GN5yR8roqboTS8rL5eMuwKbw4lgWHg3jBxkWy8SUUGDKYhYacC/CpZ2sHZX8xGJHmzzoAOmlL+jkV/9OSUEJlGe8kKfFULzN1OJx4WzVdXM+6kAunTQegY3jxIhVfADgBhdBYzipR5iBI1+AkvjorgZJYxzoLGnCBCksm3rcb61F70cUlUQXr73WxXnzysbBnrb9yfa2ltLE2aE547A3atBrqgEsyvSG0IHxo4P46DeQpFe8KsZMAHogn6/gl8xDrSYVzubwZSF/zXBU++SQgEiwoEP7oF9drwLD1PnOa4Rnta2Duu5Y1nUlOSNcWxHnyuCLi7QJI94AgKvhJVWQBcoLLeuNEZfFoPH3hMWDV45ZchajFzmNRi/hwGBOj3CVmLo/XEPRXI5tYPnUNLW/HLWA8Ljm3p4dVdYmI96NDWibmigCO+5ZYF7xtoaEhFo8dGHgtzDzY7NrU6ajOKHcjv2af6rxQu3DqNc574GGellAtThkTwca9BztsDQZXVQpXQhylZfGlWkl342nbhahxBvUqIXEUKwNoApQX0dt7M81B9jQLMShBKP5bpAUXzfvbk5tC2N6gYDAOe0xmuYG6/1RaFpvifPuXgj13PA87ZUGA/4TkV3Pvd8tBreKaPOMkEAKI0UNq1ctq3Tn8tHZZ0miYdevpdtIIQdA8dOxheosDKXCe+6olYRysVtB4cabr/zo866g7dbZrRLwImAqxOIjlNfprbDUI+04C8CvtPLxnBg0Ak3onNcAsXktcPcxhgcNwX+TsEnKYDVdjGRp3Eo+FUJhPMwDKlwGWlteKxR9Swl5HYDivNcgDsdMUIyg7N/dX5HN2zAaWChtZHSNmYeIQyCloOHZPdzhkgY5wRutbot76cpxpktbzO5YQlh5DsXD/PNbgCnanVb+HDJEO6i3ZXUCoXRNfWzV4bKZ0B6TM2ANgbccI7BndDRAVdyrA+npPU4Kpiu0IjNULFZGhbWwS8wM+jmBuvtrdF2DZBR6IOgH8wfPZXaMabkT8ri0RFtys79/GJzXpRUF6jlyiOPPWSKgcAJW6PMi3qfKGmghQKXRUkmqh6NbUux4fBpdydFzESfgCsAgBnOHIkA3OfZo5dXh9LBWnhU+bC5v/fewJXz9eAXFEr3jjfuMahl1PUA0NWjXE3u37GtN3ht258N32PMn+0psFFmn4uKh1NxpxH1YdQxlIubVd7wA+N9DD6r9DGCClnd7nFb0EjskworW0XxEK/oZqwTQd+Uy5uPzffcGF3AwHfWsFOnffoIBfwd5du17U5N/fabVTzKcTxya7/CwXPZlYHODn/1SB2XHJLJOhSzjIMUEHyEqslBvpCfpfB+4ivHr+GKQSAc/tZw/hDK80+l74+PTrPG4P8LA7YDorr9+KK+2TjhEVZwB/88vpiv1diBz96t8FLfi6D4hYay7beUkMFsHSfmMpkvPFkMTwwsSn7+EVxGH/GqH8XvTDQp/p7bvqikYRKTMbuZaz34fAAk4yyocqmwT9M2gafynBhgrF8sLctWvvX3KOF5/vl//xv/9X9MiX748W8AgLcfvt8Z6N3fv4v/uvKnGss4F3zvd192Nsz776zrqVefksfN723OPLvtfPcAX8pL+dOXFwX6S/kLltkrqauCuoCow03hgWan2CqU4MaZD5pB6GoCIQufXgRFagqYYABDiUYuPFeQeWHoEGKF6oWJIJaIB1wYs6jbnCVCkMflxGsnV1IGNaDRCKWoTLhFKBZs7K+7gCBgUvzfwvj/SGChOQUht6l8Sh4oy+F6Oj7HC3moHYf1zzu53P6spRy3vuv9KHHYCYvhW7JD5VYo9Uptje8fOcqH4JOZzKu0d1OeuRLPTyYZmEpBOEChvQOqWHydXPaT+XTuirya1POfww5YDOCW1JSSTC7VtL5196r9SnYoHR71OinR72kcIu9/I8+VYpmqRN8eUENZp8A1UeZDrB66ISgnFxCLKyNBxTLTFWHsHraHtgzBKQ3rdHGlFhTQTp4bW12QZN7KgOUSjKobEc69AwS0xinBGkIrwnE5gGC5H6uFZ1iBK8qEQj23nI+RysQoXBcxS0B/L+M7we2QvpV7NP99TnspnB6iDk2RzggTPcKku5K1K1bV9AQGEborlE2c3XET3tYI5ZpgvVtx89M1jscF53tFv7YwqqqCVQTreka/6+BrUxAclyOON1fgM6eQ+3A8ZCh1jkVUzcNHzA+DPKKB9WJZFhBb6HcRgYpgWSyfrmoDCSDSwK1hEUHnBmmreVUToKKpvAURGgze0gMg94X3KXC8kOEGYnCftTeJuS15vHl7u+C0UKTpYBhYKoS+6UUZtGmnPHV+s70dRiSM1oLuEZTE8scLPAR/wLuL/jzPrm0/o2vSbf+YF1sYLez1Rcd8YQiByeci8qoPvENJ8tgpuSnQ2QU4wyhgCKS1NB2zbd5dCfveRgizgyibF4znfqchEIotv/WQDjiQbMmFhiEMoiIw1FhX3yGTIh9Qh4XSbQxjuhGePxkF/372INK8r6WfowwKq+XfCkNmPIJsc/RxzF2ivaKEuvQ8DxjRi3uXpRgP5K3Rr8oXzHfKqMgNTMpwdHphfx5iCtIESMNDFZd9wkYwMkhDkCdAHXfAtnijstZFMV62N8LBSh7cbOLajcxcwaqkFrbd942oKxCpGU06AzhaNBUS29Nj7DEnmuPlo+U+7w8nqAB0ZeHPMxe6a+po2ZrshFJ8wJt5IMV0ON/qTTJ5svdmvAC7VUHW2RYIEW6urm2MYmMR6jlfhlYZig7VB0Aj97n4ni4rGsKoK4Lc+V4tslu6ogvSTaDMIUrA8FQvQq0LujrYnIkGF0zkRgMEYuMz1Bda1Yx8TcHNBQcSDgfjf5gZbWlY2HK1E4UHv78buMyHoSIlWoJ5gDOAh5MJocXChADCEO0Wel0Ziyq0N0BH5BiRYXRKbhClfhZawVjIvBjhc0VngK8ZbVlyDy7N8qOvsqJHpABR4AjQvcKCADm9uCLIred8jehl64OnUrjyZoJeRCymK1/0iusfclOpKh7GW2OOteChAQLbJQXRDcyoo9zE+H3n+EJgKchIC68Li3zVAdz5XghFwz6ltvv3BFwHbJf7cR59gBndMoIfpvREZ9w47omUHwDRNc56j3PB4cEnxzi2RkJRpghYevl+9nugten6AZIJFUgBtRxsXtU1NBCMKi79MzHNeTaZbVAa5ORmzv76fMmD8/MKwo3xfyqOTxTndcxD5RW42VXX4LZo4PNLUrmhM1r6WLvnH5X1D7rOGY1Dne5I0iFNYht1m9IpdPNhsDg4j7JeOV8D7u3HM88jF5rK+TrgPPfrOFRN83JZb60DqVgb6KQwvBXHXtRXAU7LIsZ9mdoacDyPP+MFbPfDVNuAtcfg/6JrqlNqsbEulZI4taChJJaMvOYwQeTRT96B8Ami26+3JZkZCAHNWHmsZIriq5/+hvPPq/fiPTp9LLgefvZ7BwKw/tydFpr3u8BIiAL42C4anubrkm/aXm8QxiNlO99vFJnSbjv2t4UH+zqCVwIAvjoAxfcf99rC8DgHhmPGtp2nQrdvIy0QjFZ2Isfv9t6peMzHWYTT2j/Gfrldkz4h5JkDV4vT2SHz1Efw82yY/RRKqOOwayCiXzY/Z4fyfPrOOy91f+qIwLOAbX8wW070VUD0GiDFencPWo9Q3OIrbY2Xtvvvafj5Jj4C4ev//A8AoH8Q8z5/usbdEtX/YVJY/tbyjen8o5TheR4yjO+b+FCek9cVcPTJHXkI+xEmtuC0NUAJw7vn9Oapt/Ls8Z3jeikv5d+pvCjQX8pfpoTnQHJTeSgQrKSmRWwA1NSGlN589l4I8sVzQ6p0iHsIkjNkKZzfaz8OPyIQJgDi3o0WlpZJ0ElM+c12GIiSofW0paIqFVY0hM1EnpOaG6iZN4cSj9DzKhBVHCD4tQnedsEvLFjUwnKrRri8IfwSFQ+vOpjV7a+p5Gm+zr29/U738/r8u5at93l4nUd57QeieuDKnOL7J9CpBIMWx+o9b7zwCz0pcNA5nFDzZ32zjjcgV5IPP0N14eDaz7g6XEMhk0ff3CYyxNDIeT5YslCe3+j3e9vXafkmYxrMq+/PyQMuhRMu+CFcMLtMpqgdo7LZi7DsMbuiQ8mABP/KPBtuiINhi7DuvoeZXPUde1qr6Kn2dTu+eiNW+nISDPdtD6O/326UHvltXfsNtVfluW5DZmvKmOwc4AdxZqzS81DMHraNW8PkTaiKhiMElqDX1v0EoGEVQevmDcei6D6ah/s7a/M4vOAt96vjWhcwqgjQWubZJrL8aCyKdrAQ/yNqCBDGUmYAY/nIRbqvyPCKjdDubVkgYjnRe+8gVkAkx4oIG07k3vY5nRfCIlVXPMc1G4Tsgo4ORctUQVEe5nqjGJLMleStSTx3IYC57EDsn4g6oLHuBIgQ2HOLhh7M8JSvt3i4e5U0NMrc7cEHFNiY+pcS0Q0Szi66iIjZhOCEVJSrC46qJ93k8TWNv963/mnOYRjDeE7g4F8AKA1Dt5z8naKl+ugdZODtgMWk7Zs9S0QltHqteIghx/ezMGqsyPgm1m83Mkr9eQEXW7iJMLLYv5VomwAAIABJREFU7VwI/cY3SSHHfX8nDJ2GAr6EVU6BYwynNlZ+u8DkUe/tnaE+/ladi83uDQGIjt8h/N4qzifFqWjO13YE6u1U5flel/5/9t60zZEbVxN9QYaWrN3VPn3uzJ25//9/nZnpZ/rYZdeWKSmCwP2AhWBIyswql5c+lbQrJUUwGFxAAMQaMLIr3avInz+5sMde7wpysT3luBzQyCFdFYEAsPi0/kA9h5nu9+YNr8fc18hhqTfcAM73jEeILwCoaAoQpTUCj6wRfIFOpo6vEHgroBkWbb7Pq9IB84ASdB0JWbvs+MmwxA0Bt4l/yuAUX4LYxcUw/Ash1gpObXbJlON+fYgaYHTCFei1VONBtHBjLLRoxBOkelQj4od6pKsoPGDPlfutgN3IsADCBVIZLErzWrN1sFDUsiGAJuC0WCQWMRy8AeSYaEuMJsahNE/xfiQSoY7CC6mBcqVi1iLA8faTzuNNgRwsMhdP5jm/DR6MiEBHn2uFazU83gXft95rgAA3AN+Ni0q0T3N0wD6vc+LvLuNGGuHCQYOc7t8CVHAginRAcP4TMsALlQK0IVdEwqWdDq6VnTcWdWrdu4zxLvKDsT9WtQXY0PW85g97nve2Ls/bupzNtjZHDEm8seBuNZL0c/UKiXsUkbsAF6zR2XNkZ4lab1B3mipoqh1Xzm1OIdw7SlT80/Gjj7wL103R6YB/PkVnRZzfsLRuTsMGWgs7//l9YTsHpnOne8W7DATS6ZPjdVyII3N2AX1tr50dHlrib11sDFfp4u9eLu2sdOsrOybrHwMBkqHO5W0lcZM/CFyJfbnW+R2yy93b/AN2b35QOvRvJaJr8S9jWxVvsP1bxelndw3onufmKPwgiJyNPTr04OXLbaTi8p4XK5jJiu91ycpuR8Ev0ZWdD+VR/y1b4lZJ+YNgtOYv7n1nHg+N8COAGn0TwAnnrk4dA5WJyGCPKC5fKb5vy+oFgV4oDAFdwV8KBVkUIouOovxFfbYD3wILjsbD3eH0B+Eih4PXwnghX64Ef/EH9fOpjOWSgckXl29OeB7X4DV5o9P9p/JUnsqTAv2pfEfFBYVuOZ3kBYBIys+kv0sxRRmVEKgRVQCMJmq5WS034gLzNqsqwmFWS30yxUkLxX2c0k1428AEsFSocFcV3MSs4QmjexJ9FwAFpqzx/Oxx0AbIQsoKFRMusinQW3jn3RFjw4xbNLzlgiYNzIRfSfM3uuBW/6kwq5/LjbymnLJ2OZ08+jgzu/2BNAzNl+bv+a9U8oHJravX1136p44R5wcINiFF5KOiJKDo8trenH264novGgLzBP3MnuYuK2ERtM0GEMGxLbghYKrqcdR46V6MAADz9GoLgH7o8xzqroK+1fNIvMfLXhC50R9TfE7CMhoOcjkErHoanYTVI1wYMEFb9ZDrNm+TpTxgXqwNFxKpx/BUKljYxmfeooAKrUyAWkHgJQmLSK2gtS9dYSDSvXhqnUBEGnrfFsqiQmtaCFZ8oO0gFmeatH9zW+CeZSFIs/XQfoy5vJFqeLWsdn9IbnV1iQSWqzTjLDz64Nvrr68ZxnFrAkejgOs6YgzMAl1GDy9rimV0/HjAAhHCPgvgBVg+zagvC2TyPOANLILDp0PIf2upeP7DC/N6Vnip02awyQJ031R0uGxLQ9kAquVVT7cyKf5mFrS2gGf3zNKONhHwDNSNjq2WglbE8qtXTDxDCmGBGgo4fXLP+y67NJqRciUDlg7E8ocWm9ueHVMA91gLAfuFBR+uS4LBLD2V/nP1+AAbMnwMJQT/AMTWUwSaemSqKvx2BboAKARuDKkF3FRZ5vgS1JVo7r01SJC6BrDzB3QOxwQYbQdguEIFMjAF0Dn8Rx4+e18hn22nqp5GRWIstrMDN7gXxziRCOVc9jAhX6CB7VADOU/1ofno3YuTMACzpOehgvQusPd2nU+QUbEdzXQ1u06K8RdZFJeG48uRodGH4XNHIFPO6Q3fN/2/6DwACcVbv9OV6JFrOPrc29A1TWEe5YIXenQ3jWelyB4GAESo3GHUclbtvBAlo7bV1CU5ofc9hCAe2YT6vOdctsyKmsrQYcvhbIpvp3HlpofkBAiyaCc87QnYU7gY3o39ZkYmN6o2FA+hEX2JjsenCEBboGB7Ni/iGYr8erY2gxqaChZrpMA9QLMxHaAhwMkUrJ6OAdVjrrsSHTgejgABE00QahY+u9MndgMFbOBpNxSmNOKPh2j3yByskaHNoz7T7bTWw+/O22k0d+rfqdg+oB4FhdQoD6UbkHVhdVemFlOMk5DR77QHKfEx1aIOEVnUE+WL2tw0qo5JEnrkHn1P8VQoZJ7jJGAUU5xzhEUvxbzEZANigpRmHZ7BpaCYsdiR3YOtG9eBHCdQRP/waFuBP04z2rSg8g1AhO2zZxCcsBwc9wKME0R2AJGxtvauPUB3BvdCIO676+b1FoePs9a7IfCdxtpod9YurXaVwR/RjV1wT+e87r1PRfYJHwGCO5vb5/qY3EKkxFrdgFABHNKGuQHhNpTnFPiAiHAjHX/7YquxDXcaAoB4SPyh0w5PdKZ0dAKwJE7xYERg7zTA4cvjwBMA2WNLhCPuRnBPJCIfm9kM5uJ0GtflKu7sSpxcgXCy31vAUqNQ9HGonXBSVsj0VXI82VOrBZ0Qu1a7S+wGO2xuJtQyAUUj7QjPuP1wBONgivAtaE9oB6DsHcw1XRQJsN1sLe1BNtnqhhNhQNSXI02mtuXyBjCFYv+MX/e5N1qrP/VMEhPrryICuae98dUUbaRF9EU5n94onior52i9tLxxPnAcd6VuGLasawQNyr8l0VbquDeeMkPMS/1ZX6CzL6v6aYFylYSre//GOTtvMvEYa0OYXCfzW7Z+A2+6GgdRT32jNNEMhwYZUe+XoKeB+2wdfSGdp8qDmM3XeiNvsKkVh//UWHH1bUV7Z6mz8Ao3bzeYpslSCAAnfIbgw2CUBgI+PJDxRdLf6PCF8sLG+8mjtq122Fk7Mioq10pvvxcKdhPOfF71t9j15Uq/1t2+pBy979G1oeyNjJEAj6t9VKlEmkt9DnqWFJ+VBJM+TaLt12IUgljTX1oUPQCBu4qdnTaWC/3UshmSb88HJgP9nf4dpLz9xiKnsXhcPsPXjUFVU/Q5Kms2l3rGYuUlmFF2O+jphwEWLBhOL2ffvqo8OEQC4wM28hagX/ADv8H2xw0OPx3BtocuKdZ//OFHEBGOP58gF+MaPJXfq+QIUY8tHj0i9jdrdIo3xnF+wqN2w4CTvS9+/b4+0YXWH/I2v6ZsfypP5b96eVKgP5XvpgyCAsmCVhXH9Nyp6oquKu2KUhiMogyhKcPAgqUUFHHrdfc8VKaS7MDpb4hziwthQ4CrShRhDWPIZEqzUkFJyNiV5wL3/iPqIZU8pKcLQcJjAvZbBGUhSFHBkoqgGa8ANDCYVW74AUuaH/uvlRS2b33UHU7YuMxI0nD9e1Gev5SX+Eif762TA0B52PMe/lwV0AWE29W8ZnFAyI5DmXAeuicesnKgnveqYcw0eiDgmQlkmdTL0wXJzaIt7AHMdQK37j/iCpO81gcT5DwXZbPWinL3Pj/YuL/UG13f64Yu5+OstUZYN8/HeYmBJFIDk9yAQLCpnrc1NW55Nq+1o/gEwzO1qIlCl92Puer98EnDMW9kfFdvWglGEGt0vxbmzymXlONX6yIptbzEw9ZQZupXQjYVqBBgSnQqJYw92AyUIsyeIWfmhmWZwQdAnjFq0fcvyy1ENuGdx41VYb1WMhLQWtNQ60lYCsPDzAIihdOO0vUdrTUsjVXpKw21VCytQZqgbCwKSmHzQj+iThMaV1RmTCTdWIA0x28PH6r9FSJQyfNpYlfR0OYa77bTDKFsUnFNcJnoaZ77IQ+zDB+XymXPbDmDYYdt34m6zWrAlecO18gwGimmNVFnVzCYdd+qnLIrQ0MJM5w29XcoOi/0X/GJtqBCc6fHvv/dC72LDUO3RGS50is8qoG/qC/R+Rx0RkLC8GecYjmv7kOSdFUE8PDSjtsIukeSxyryM4ZvHK+5QmLcojavMv7W6QyAGTs3yiDPxqBTsbZ6f1hsJVi/7nrNngfd60k847CSo1jkt3a4TAIKv39B+Pe1gjcnrQ6v3jdXXmWFzTrKSg4BmEatX46A7CkFXNANRTa2Tof0s6zG4/1Z62uKu4I5TmEPN3wCaAuiGcA2eGYELPZ++PtZ7lu/6EieqWEsg1damkMIemjr2Aq53wXo0BvIh6QCxH2PiK55E43wpEnPY7N34p67l9gJkUtiq4SWHAk5X58UoCqiVkNasj77GlE1viPhHf8kUOT/puIppFSppmPUyCjV+l+nSZuxXKB1mkC1hGJniHYg0FQX3I04hFRYzkVTbmhgf1WkqxLdBr0D5HQCo+YpgiuC+jxZigxoXnNXyvvYBGoc4fqPsrcc08eTRg250boFahzCbugQMENGI4FSqir+SXm2QmZsRITTpwU3r7eYmwriS1HlPSGFGI8FtTlKoxDsbV1Nkc47e3ZM80ED4GR+1L/q2rtK2zfkjdgZI86EFDjBHx6VsOd44treSxQ0nvRUSbtUT0O7d+pN9OBuvqfQ8J0iRPeV2oGDr7/xtOrvwJHQ+CkXcHpccfyRzwvUjR+222caCaGQGs6a0loKcDgtYIMBV/WI21YcALpxz25KfaLOWIfC1Puf8NZZTyXesl5zY2Vtv1obSVlMSNskYEPr5UggQQ8c5q3aObd3ThOv3X+oXGr7civXvo+FHqzx9b35Pcqlfp5xhPLQeM5hRoYFcjmTcUofLvOcl3ZchzUKkubwsvlbHeot7zSpXMFrbP82maF56QBohanLUB7y1B57+HXlGubyaHtf4u37yXmQvn3hx5THlOcyzvPX5EL3sO3X0unJBXiJc+I5aRt+U+AP5UUmVLTGnTe/YJB6P6a+v6yNaYrx7h4RyPlar+P9d6PDcGwQqHF5KSDswCcBFu3rCZ0d+y1U7GvKRwJ+EI1msP1xAxBh83YDkR8x/zIDeI+XolEd3pMqy5d3zeb0PQpeIycHeCOv8Ss9KdX/yuUjddlsp7W/rfweVOlJef5UvsfypyrQ7wt3/X2U73v0f1pZnYw8FKUK6xiNCbDwg2CGoKAWhphQR5lDvcaYIFhQxZ9lFcjGQbILvkTY3uXhR5X7lyJo0lCaCnQamTDHvMxdOZCLeg5xeKB3RlFCsEdFc+ESCdDUxUjEDuJVPUA+ScGzwvgkjLdN8JYJv8I96LW/UgBiXglJ14IME3G5x9EoXexilj9BufeQFSBd+f5byt/evMU07XAjL/B/3/3zar378lgVAI169ljgXNhwMkv9TXhQd8Fznmlv35XIa8VXVh2Hd7gIpvkEAWEnDCoFO1aI/0QEipDT1rYJhJbGSWiv929NMXOzGumNhf87Fhp8UB6zDr4nSqkQqLA3hyYuVMJjpRAwTVucTmM4WBc2i7BFihjfsbRF92+1MOsV4CbBMMYITTDZLFJDD2vqXlEWLcAEsICG3nZPi0o1FKoeuly9vDTPZa2EeWlqLEGeW6lgX1VwPFtue0/10OHEAczZ8IgrO8J9Gk/+/fAi+AN+sL4kXOyN5/bXVQWOO/oi5PZcmMvcsOOC0giz5Q1floZlaSrwr7oGFkNA19hD5kvB3g1NmE0wPUOkYv60oDyraK2Zo6xAmmbK3L7aahQATRgMETUmYfeotbEvpxNkmlBrNeFD0/zhJBGWsFQBFhUQAYLTaQa3hibNBAwEmhm1Fpzu1N+TaEIhVa5Pk6DJBgxgMuOWUrrivMO0oNSiIbv1AgD0/OkAiBoERYXvxo+VUkyQY8IuSspT6ePo3rkIj6fBQ7kDwJl0NOBTMArB8/1QyuSDI6W/ErnJ+3tUqK9KV3uOCmpV+tTEQ67XgE0RhFeneyrEtoHNaVm5isDDQlv/qJhxhEJ7GDRQhQUFSKRPlUka/n+CgDGf5pgLH1vAvCvYyMZKgHCDhypGzJV7ccrwLle4RxOR8t5wBRGIjZHwnJ/k7+7pXPoUC9xFMHZnXgOHFnGeyngev5DmF95e/xUVHIxsKgEyTykqWPND6kGfPcM6DHZ+peNX55nGsvboS+tgHpmZbhbqRkzRa3E7BN9gV8Rszkutbq5xn6TvOqW8esDud4BdKcl0rehoitfYP7oiZa/0hS2B8eS5Oa37DuOSZrGYV49HuSECUBcFiWnSWq0pnEb/FT/JQfEt7QvUUNV4lTLpWgub+pDBJ0bZaB5LYelMSkIvMRuecx0bgBYTTHcFbg9PLtEvIv/e8YEYHudlAdBQkiK8FELDSb27ZQvBHLm9Iye9CESW4LMhCwbffoLm2Radf05bIvZ3+k0Y6SqBjKdXfqQY/UfptDIEyKVgmqbheT9zEwxflYKpVJSpR9EQCLjMEF4gYut/MhpXANpWyAIIWYh2ME63s87LfhPRUADBaVn60FjQlqaGZsaf7bc7tDrh9uPB1nMedpR7SPrY4etmxKLap6dDKdCIXwxECo9ChE1Vz3NMCMMIPh51fxosA4T6fMJUC/hoZ7CQkBCKwUgjQn1WwLcMuiEsi2gOdiieSN0f9qXitBXeim8W3h1mrOO0Otc1+qZ4TD3PqVRTmd+goEDkYGusROdQ9EFqmsaksEZWI8Phh4TTIgoHgBtDHU4q1LvYaXzCUeh18oiO8Ut/H1Zh0fd4Ft9FGFvs9d10Z5tzD+AAEf08Skyhtmv7a22stVbq+Dl0Z+MK3igq6XwWUUMM88tGs1cVo7fNX27teWdcCT7ZfHW+RutUbFRpvp1Q3aATRmm4YWkL5uOCuR1sk2yQu+Z0m+9Yo38USucah2WOtEL6nO+gZGCAsQRVCtlEii5DOr9s4+xUI62o0RnlJWRs00a4jvYxfIfxZq6xT+0LMOArjLf741g9msd57bnUv+FaZ2TGdi4Wm2vufO/AL+ZWZNXRs/3v/PO9L+zzceV+pKhZKRGvpTXoaWxGtUw+O0Y9WRvk29x99PoE0aDjg0MAALxMeKz4AGQkdZO8wvzzYk8UIHaf7lgWAS+a1oBF0N4149f1n6veHxXZ0HmHK4DzUlRp9SnB2QuD0UFBn+r7eF8lnsSvdzyjH5cU7Hlq2epeG4Zffy7AzQ9v8dOv7+I34T4jgvGGO08cSP+tTfg2dQNAsHCDepOXMOxW+uoG2457LWJJ8Ky6OkR+Dvf5kC6jSvzZcVkCL17v9WX4z1tMoDC5oQqGYG5LwK4a2Fnd+FQ8t5jn+41FRxFAaeYLAqgAO+D29pN5zut9Pddc5u/vxx9fXl7a+k5vKyb6Ecef1HHlV9IcBy+gsPXsx79DBHj9syrRf6FfAi73P+7wb/wj9JxrZ/dfLr/vr1J8PwLAGwF+fWh//0XKg928JCcjwsYiMzg9drnOx1Jiz2T6GEX6uQbAKjpox/drOcb5fnMee3WeiDNlOo+srj2Vp/K9lT/dA/3hvFX/9YqLQh7Gsk/lmxey5OJS3LUFQOermTzMoGjYdWJ10JOiHuF2AC6FNB85GiAV0lR53ripJyv18IUVqtj0MHNC0MM6FTg9E2YssiiDxoypTqgiqKWgWN7z4VBkeXNVwA1I4+6FTgAKoZggJQQPJmACLPe1ABswZmbsBfjIDc94xo8z4xdhy83LwAI0y7nLlns1cqY5I+wh4eBCanSPXlMgGkuNfnY73/vfGh84gb9yMyyH41I+Vys3/lXvncoGTRiFKv79b/+Ow09HvKdf733mhWAtHgcA3ELOPL+uFwOAUWNjhSzMuh5Q70iw98PstdZEVDhDJTRvevCVfli3vjVuETqUZe1h7UKUfu1AwPPEsI1dPTcCuFa2AE6rBpz5bLygUMFms9W9RDQIA5wZdKFv4zGEmMNzawtQLCZFnUJQmj11QdCcoLUmzzYXdFfwosrfJjYfDA3jCBO8ks4hxBXFQInczgXTVNHYBVMmpPJDKpF6XIvjBAkBaBdwjfO/nuuog8cdXMc2fI0vHQwuvO9CN1wo2KulQ7YJ97g1zCI4NgaVEw4wTzrD5dUO+1KdtTEmv/Y0HCDCTgQLM3hZIK2ZAACQ5rn0VEHMrIYVU51UGW3PaRZfNUISwJTutm7zrJ7dAEot4FJAjULx5LNJVMxDXHo494PSDyKgsY6l1Aoi824XAJjMq7ygtmaCi54DnWztBeihkltDS6FtFX4VKRMLiLoiXpgtosMKKkx5zkZ/xMRiHja+j8sFIwmZDgrWcc2vR3KIX1CBrLYTKVjsUBm5zrnvV3235oPV11sIaRJA3GTO6ZHRZWiqEz+8dg9cDVfcFeRJIZVEhqUQSi0aYr9W1KmawFvptwrNdQ5VCaZCKOHsNUjdKMOn3gXPZ5tQLggDHSPpHMXYyENK25ORE9vxSPMltqetlSRojTaT8N37EAIp0bQRYoTUcyhnwW5xz1VXZBNCsZ370Efi+1Zft5iwzeFddRylR1mgLuAypBdzw+Ftzv0NMQcUXivkguTUNxckRu9sDBkOXG7BjuPlXDiZ53eN83yORsWbTfMqfH/+PihYba4y/pQqwftBBNg5P2bh12l8VgUtFGNgaSa40b1eDN4jikEpAYrMHPRJ9yOHx66HgqelgHY+wYCgWmhQAQmDRQ3O2uJ7GrH/AGji5C3UfVQA4Qlu7EK0UXxYFpTqZlTdsKevuf1y2kUUa81NFeNSkhe3j5sIqvzXNWncVAg7N3iKCHDBhWXvMG5zlaLLY3hAoCkiSheaeY1SikUdURwT9dLzAsE0TdhutyE0E5FQ+IM0fcxUKzbbDbabrSnhADkJ2vakfM+t0jUWNfApTGhMKCY6YFEDNj4uhvuAzUaVho0b2qEBphPkxpiXGWp41Q0zFDcTWE5mYCwQpjDgStyLLpvZJ7NoONVqe62WikqKc3lpYBRMRjcmo1E+1WpwbOvhXsIGE9wA4ZOe607mUb8n0B1Qnlc9e4mgPi+aFgt6qGMRyM6NcAy+7hLSdpznG89vOS1O4xwBw+BWdL6qdHhwDrxUUw64kqBQoss6ccwMmgpoERQW1CIoknGmRaQRwR2pV7Z753FC8iqAt2YTLy3oZgCuQL+Pib90tArcLwQN/u6fh7O6+WwXPL0kOJH+8kxOh/fZ3PIwoxLsiiVWwuJ7Jl5ucyESOJKooMJzqhHqpmovDb8wayopgUa7mlsDnxoYS+KdOw8tUDAoOxraCdxu8+t7CZJoQub589+BHiLeNdAoR07BWxhEpypuWKVGx60/be3H1JPuY08PEc3Hn9Qduty3x5QrIHY+poeurco94Hu2ZR/VsQc7+kB5RJ/v68jF7si6VvpxdqE/0/mPD/b5Kr6P+Cl5UYp3/xVI1gJogidSJGSaR8HPtXd2Pmd7X/nw9VPyiOIKb4Ip81b387uDpuPyMn+m3t41MPhEo9LwWiGod7FP7Gf6Og/062W1+OJh/o1PNjlKLRapxZlu46FrcfxEytNRCZ47SJKPheir1y8dYYa1YDC6rNEMytaFEB7nnRZJH0uip8dPn6Jxsbnop4YrRrLfsHw02Dm9m7F5a7wX9bODww0bnXIPdDfkmPAWtz/9ExN+QMMvILzB9EM9e89freR9cEk2+q9UBpmG8w+rzw+kPJnLRR6jmM7GU5mPvff995RaO9/4GKV5tGt7/XvU6T2V77P86Qr0p/JU/sii1pKkh7dCZj5vBMhkgT3drh4c2QWq0gV5/UCrvFaRAkIFzQxCCWLmh0JKIabJBJR1qnAXFE1FxppnjwhcGEXOPa28KF/IxvwlxbWP0z1g2DwaVaoSeVch6rElKEowTQnxGYK2YbyZGe9rA0S9bkuz+bKZ6Tmzensu4+boobOYRojtOpHmdvmYCPrvRnTvYxpEGc9cg9Jvca78C8vf3/5dYYIIi3kK7n7cAT+vXq5vBKDhy4Gei9wZ4ttVvXWHeshky8lcVUAjbZ0BXVn9WisObYnWPHSXWyTTdqdM0LLgDqze6AZXdwQ8O+uBPRcCUQ2bftNwFnYeIExQpTnb3rlFlvEppNwAmGvFpjUcqIcBvrSSBJWlO3xtpo16XtWqQn/hWNPFDAc8vKwLpgUuUPWd35X3wgwptkdFsNlqsMdlOY37LhkT6BYTiBCmqkp3dkF7yvFFBHBt2Eyq3HfPXt0jGmTcFX3zYpbgVTXqYkm9BYImer0QoS1NvWJMUuERMEKxSF2Y3vvRZ3YNZevD7nVhUseJ1+/3EoJSuv/i2gBGlROMjyIgVr+rk3kyFlLv8WY5PFkYeypoJLghYDaF674UEDcUEJayR5NmbzKFprvoUsH0YoI0xjyfgFY0/2ut5qmoPRRRzzougsmifrCweqFbJA/18mVI4xBY+yF8s5lART0FNzcVjQl8YPMos3WWCRD1zhNawivYoc4lCSHQJYzSBa/jsBpwphb4VEoIw1XRT30dpMNhlOJTRD24AdZwRGP96Kv+1rzsvnf6YdEFKq7gFZGInBGxQMmNUwAOaa3Evq7o3lSoGjpQPZkbRKakuFTjBRWKFIi0yGOqc1F1jHCDN8NE5II9hYOpFpSi3uRTVZrqe7LUCm4mii+ugFOlRynqYePGFdwamnlNeISEc4Fl34VOo/p8u/LdqK3jKONzupee3TeDoa7EXq9kOqBjuAg3rsqVuwDfsBf5873v5KBoax2GhWGL4MYdEV4HYgKxZlF2iEiN3Ry0TaMjlg4njAUGOaBd97oukonxZXpPAHEo2QaMlGiS+6A4H9bHWNK8JYUaurAjf/bmfc/lS86NWg7JARaSIMP3ECEUqoEL3GNLJx1yEtCOUMna2gM1he9nj5YiXXgt0HQ/JZTDhLpTxSWjoM2LGuzYYor3mnXO5c5wlM/SEaCd4TFZIr2GKmUB1BJRlXACpBT13iZSJ7U7gPYYlZTWuHob7dSQrRCoLLEGoJ7TlVC1vWWBWG7fwYvPhUZ1vUc3AAAgAElEQVQrIW+ONiWN1ViU+/PF03gQQT3Si6MndZbfaLSYSmS2vCOhHXBhEMDVOEnvu1dqpuMCQZkJdV8NHgweixr/iQiqGfnUqiFyUQDMSsdENBy4OH2zOWEIChcwZvDBlOfcAAGqVNBhBjeAC6lRmTTI0Xgf1jQljRtO9un00bKhW99trkVWgdwx4EOndQSN+FGpYKolaJlGbrGoSKc57VcdSaeLanxDIuCjRjIg2RiOahAhyNHqHyjOjJ4LloWBG4LcGvymdYxli2EQyg2B77JyPJd0+jAcJ4l+F7qxfX2K/a3GB3c4kfJD0ayk9u1jL2r60WDZ1xNo3YDw2fDFXjp/4Xg6qKx0HN7S9aziHriFDL72/YBbXCo7uQFwwIE0HtUeN6tZig0CANjanQr1Eo9IWisc2Z8b3xddI53veH7Fr24syoPzF2G8l9rQUP96vbmhoYcPtpptacpnVmBejkEVOvHzDLvKlygc3yB2hdFuj4ZAhTpPRz5uoL8xlTWo5XmIimcnAGtHzzMatYNWz/m91bsyD+pKdOtnTImkhmS9PPd0eF3jivwg7ab00tR/Oas4/Lz+PdFz3wBAGJff09OLDffpd77MIwyMM7L+nXkMwOAh7vWG8/QE+5fmf83hXYqUkWPz8HtZ3QOAD6tp7HwTQUGc8AoAQehD9EMAFHkFpvco8hpC71UGJwDhh2Efb94qvV7eteH6o9MCrmHUyivR/OmuIH85gjlYrnt3+zTeF0L+JVzmdfn+K9FMWo3GOtea1He+xytRnPf5Cl4Luhn8hF49xN3xwZr4DZH+nEB5a81DX3GaTyiCkCd6upMuF1S+q9aquG5Wj2k3YHXe6tSWaH/s+UP7WUtZCyhSzVI0RVYTVahDgG3ZwCmbgNB4ibMIANwWpZHqcX+D5e620/Q0j8HLPQJHfavyiYAXeI/3vyLH9Y7ykYDy7oSG9zEfriJf8A4C4J15rL+UX8G/4DqA/cnFveY/WP/+Jj9g/qu7ywPJwPpKGfh5v0SR+/wlCz4YX/9Guoz8ufS0nrn0cyTHOc3PBH13C1gep4yPPiIZunifLzw/KM+fylP5zsqTAv2pfDdFCYGYUMvYfmMAXUngTJH/xyImpHfrLq3voZU9xCFBhXJSqh2B/SSm+fKETZDnQp+iArVXQsq0P4b+3KsMTqc4uNAjCwMLqFqI06Rod4FIP8eqIqlWDZnz3upMVUPbaxhQjtBlXTieFLbiU0uwTERnw3vIwvaPLmtP9K8tf3/7dwDjUu22mkf7x7f/huPP/3lx7LekTBKjM0ofCXiG8/zn95fR8lfLKEia6gbcloDRvfTc48+oAO2EUyEU6V4wY+Dz8xJKDVguaGcKV30XhBzqarkD8GJnvix3t8qk3WNgwax5NcnyjDM3TLsdTrN5AZMqs9AaFss57E0yBJWqCZ8oMAAspLUAWJYZNBGodua4MZsXBiUUkufbFeBq/eyeV5fmbV5mbCbzmjNlnivxskdgKNidGU4TaZcD8NbCPb+W33uxnDH3V6e9D/VbltT/x5T1AVaVkAtamzA1xqkIbqp6IlefH/LoIN3TUp9VAZRaceu6TmXC3E6K/5cFRxHUpYQXIEr36nbhIEA9JC6p4UYtGtJ9aQsaN9Sqyv7J6AAA0GwRtMUiGdi6g9RAgLmgtRm8NMzzYopWfWUh0ofdeAIdtwMIBSNMKJ8F+uuZFuiesuivA1UhIgO7HlLszyrxZjOE0z2i3vSVPIQ+q/SrFrSm+9qF0xzzpOutwiMP7V40WE0eZ7xQjeRKhQmOLacpCCgavr/UGgr3fPhUIyYXTqmyRyPFWGoVP4+yKpRUjirDGlwquqTX751f62ZuXdmcJKpZAWyXNHy6cUiCJH1erQi57Ny9JhFK5xHtSPBhGTfqM4LikYJEoH7s1PvaW4i5YzazEuljWnv8rr9fnjDpFTF+zXvq7LH0NzwzL+Dh82d6Oc9/KYm20vkDF0pESbAoEhqdJPNr9uIZwI58ZodOubFKy30UgEmU95sZqFuUnUOnKo3b0lRZntIJEUhzTAMg0fQQ7ttJDGhUCYMXw6XM7t1sb9/CeE4Ktt1poexdOY/gPcOwxHB9LXsI5i5YJDUGgAVtdi/SMuxzm8sUeQLI78YAc5SfsfrriDbjyhqnQJ6Dsz8f0LSyaBngIMG3F/cMxYyuxE/9AqBnDwY2k+aVLVTcoR4CQWPG0ppFUCI0UmGcmMGXC8nDOMzWQWOSuJFKP1dk716PfiLoXr8RJtxxYMzzpQ1oxpSkcOWh28nhHMYWkUWiSfMjAmz2G5wOJzCAutuiHU/WNgXeignEBpAZoA2AGUKT4mcilH2JSCwVmvqHbghFAL4b12S9+eWuK6A7XVg/YBi9iKXX8HD5nS/sXsjKK+xTC3soDjqIzkVE02E3tPbPjhXvHK8/ko6k7YaDvfPcT/xaydi45yBXTLRuibDD/V7tvLp0DU369c46m6A51n48nShoOJ9DAElE0dDlUz6vFP8MkfXZUMUTuImAl+61HXSR0tiyEusgkHIEtrvBk/vyVDg1xHmteOGFCbx2xuooF5R+CPV96hWzws3HNZxDQol+1vzwG6trl+qunxuh6b5yhRI/gq4+2Kxc/PGXKtd7lXiz1afEP6dJDuNyqTrWq0P5i3yAmjaVMTUdfcAHAl7jfVyv1PmhMFq0vVh+KGi/tsfN8jUgW5XXkjNEw/iI+1fy0TKjBzpaHvGuXDK8P6Cy+6LSFcS+n/09aoymvFnTc6lA+fbEo1Sqdk4wXiS1Yc0C37jPl0ohN/wbZS5O99bnEe/iztJlVbpxRg8nlkQftJWQdd0jl/o9ykPw9v5CTvM1XHk4+L8mhjovr/8gmPmziivPAY2m9Bo4W7TPdJVyXSmZDo90+d6naP255kz/PHnPU3kqf7XypEB/Kt9V6QSBBgvdOOSS/lMLWBXpqD+U5kJ3JYt7fQCRXhebaaMMIxcsrelBOwToWpFkDO34qbq3xf397ZZe/fB+Xjm1IwJhCkV3eKg4YW56/HkrwE9WX9soKIXxmQoEBZMIXgrw09TUPFYQoXJbCN5tADT2oSALj/vROCsKstDQGVu9/mXs3X0H7/vKKxvCJ1Il+tqS90vLP9/9Ez+8eotps7ElLzG23XaL/X//n/j4j/+4+Kzg3MqwK8/vFzX4tDfzcCZTDObDggswa6ngtkRLB+oe6FUEiwh2zMD+GQ6nA8jDSYqGdnwJnStBni8VfrsgrJkF/Q0VVOFg/D+r/E9zeBl8nGI0fXyf727HK0lZN4IGwQ//i3vWE/Dh80cAgo2FOJ3nGZPnZwVAVXOOaxpPHZ8ML7R3io9nAQjgk0QuLZGmbYrfN0/VgPuu0NtMG5yWnE1Yi3rCMiqpQnaz2Zr3gYes9lxbUCWsXRdoGga28N+q2CRMmwkE9VhnE1jpsFa7MHIjrkRtqzm+xnfLhQ3HuLBnH2Dcz9Yyvfchpl9EMBHhlPEG1OhJPdEZEwQzgCY6X3tSlUkTVQ6pAt0FQ9qFWiuAqjBBhM20xWlRE5IigvkgqDe6r2tRJcVpnrHf78EsmCogrWFuAs+xusyzhTzWjeP7tDGjHRi0NWOLAg0DCoFQA2EDoJlyacaRG2bWtW0skMYaJh6Wj04EHHjelIrNBeZtVCj48q2V6KJCYmFOnvb9HsFp0Gq9E4rqcJZ++P3fcHpf042QDduLqnnPu5C7oKIUDbsPwOZG0MCakiUL+ohCmV0sbHP3sMhDIKPDltPUFZWloJSKap7lYYxhysNmhhQIpTyCN3C4cKUXNR8YA427om41daFwkvBBMj24h+q3emF84/vUYV4C8P27ACBqFwSlSvxdWcX+DFJebBuL9oHSe/S6XyFyR3BJvel0n+DhCNXjlQjqJZgEXgGXJtSLcNqmLNLhWthI0GreRrC8/rkWP/V36pi6ojgjMzYhGyzlBq/C1Z4Jq72sNegrst+932k1c1bdBZezeUlCeVCUkc8UEWDnBpau9Mx5a7UxV5Z61IRKEwSC6WYTEXZKUu7xUiBySnAloN0e0prRMoOfnfLOzGRCWIbIRkOFN9FoEJZvsk+dmbgSIDtXOnPvP2ylWSM4VVGDOoIaNAE7aE5y6H4VgTSnk+j03vZlGCIk/FghoN0Wcvs5lMeN20r5DZtLKN/UGkApldKmr38z+h4ZM1Z8sI8bPJ4BMnwIC1Dt/mLnk6lY+HptU3GkP6vnAhZG5QKmGVwlFOLLsuBoaUgiuk5Sijt5iX3GXVGm3lqsEbAiXQIgQuplb2NkM2RmUnrthKKKD8rTK+iadt5C6xXSnNVqIFLQWFCKpeYQwdIY4KaGcwCwdP6YNgsq7bDcHXvUFYz8i071CQBh4VlzXOMEpgamLeSg/aatjq/djSkyruvpumdp58s73osVT3hO8eXRfu+V3ysEqulMuH6l4aR98JBqkDUnHL8z/OgGZCL9vHEwNHDTwezCWHq5sfe7Et/V33vrVIX3Q3HUcXW+c+X4znKg+zlCoJ7oR+ntOXo6648RlqwfPhP4rvgTnTyjvaXDpyEBdIdesnN/NUM93dPbabL10Wcbm4elRQCZJuXZm+2lpbVQxqhtnPP6PWJcnl8dygGuPtCoL8DSZsMHluMJkuojeLrWmvExBSPHtkYiPmGd6sWJwec1PyUy1slrgM7bjDTf+JSgMakPq0Xt2yjxZ+Orhprn8LnuGV24e17knnuX36yjc57w0j651MHIpDWitbQO6/6vm5Px5qr+yJtL8FqOWzob7lF4Uj8A5MtDBCHnF6LlHtQ8s/XObeXQ7Y7PHcI/EvBGXtkaC17jA4q8AuGDGdkB5S1hu9niNJ9AAE6WK13K+6G7Vybp/PuVCf2wasjhYL1MHoJ9I68heI/F9nK160znbQHnyj9vx+Uii30+VlH2iVSx6CtD6E4YAHC7khuuj9Lrd/j9ySLcLWb4p+cpXXG2iDsEjfCHovxbGJND8d68LHr+TtH2IG587fuEBrSTKj4wcrrY/1wqeeTHPq5KPc2YiGAjKq/apA4Ef2afumX2IIuGItLlWp4i72vLGq4eW3588zcs7xp+LZ4O8npLL9Kl7LTzkR6XJuDPKm9Eoyp8NBiveI2f6a/pfe70qZRr5utekc43IWyNCHjOEtECigC/Wnsv5XEy6e7gR+kMd36WuNb/S9fOdA9pKE/lqTyVJwX6U/meSpgRGtUqiBDqzvKH7BDqHcVgU4gVPesaJ6weaBVufQ6iSKku8wksZSWQMQYzlGxOmDIDdIEyEQ35aMmFUJfKcEjo4tUsOOvt9oPUS1HLW61GeEkVZHkB35My5hMmgBjEBNBiQuMx5KWkIYzH3pG1uGQj73PzpYrzb1nW4dy/tkxT7UJ1K37AgAj+x3/7H3j/f/7XGQN7KUTPWO6fm4GVlj7zQ4QBuLCngORcoSvLjGm7RzvcAqdDKAibVXtuayw4Z+wkw0KMWz1nxwxGBBdSQ8zfZMWVRdjcC9zaCCeX940fs6Zpg2VZVNDFSeiTNjvzYnu5C+EIrrjuggmx3JdL5HfXEMZTmdQowRUbYhOUXH0fOnC5t52aPZQ+7OK4wvvtXloCoaKyP5dtmDOz15+onFlIy/BtxfRfMFJ4UIGeW3NvtN+xZIWhC/WeEZmYFaoEaA1cGa01zem56c8fWLAjMaE/LJKIe6/63iC774YVgnY39/sAls9kIdZnlBvCMi8oRNjf7CHw/a+KfAjAB4ObPQFHoN4UyMkEE9sGbt1jlHCCRiMogIeQZQawgchs0qi0kixA7QoMh2+JkMgy7M175zcrMJHkCQk2AFhIaFfWyp96qipUTDGnCiMxAzf3UGQWCDEKMbh4CPAGZs3Lp10vgXOolIguYf/bdCdvYAJqVQOKUghkgnXNWV8C/7ChfTavXA+qpzwDrHE/9Np4DOeKxnZWX91Bsam4xBUfD4l9uwDUeALDNRRX+rq70tmFmiPMaEhzD9rgXfaoGYDjZYIrJRxPOuYdPMLP8Lh+Oq4k8wZp1BL8kUZ2T93y8eQw0SIpzYzzJDFX6Z0PwO9qq8UPvX5Jhd1HE4ruREfynF7ejyn1AGMIyRqGG96WdKVfgSnkjqQ0Y1IYptK9kgkA7Qh8NDxdxPJhu3BU24o88UyW+1xQoWkryqRrwY3BpWC5ZZQ9YSL1wpWNgHkDPhz6HHy+BbZbHdvxqLDwSXEhn6C5zAVgPgxKWRYNt0kEVXR62iHqCtsePSHBsq0rC4PE0ih4lBlUwOBJLMoDFk1ZDlMOkyllg0eB015B2e1jfpg5vvuaOw8dhrNrB3SBOjcrOvfegsW8qU05Grk53aghwIDMSMLwPSQJ53taCPeIvQRf0ZGZINMCyBQh6VtbMJ9mnOYTGi+KtyCRFiFgIz5tb6d9zJKM/+yeGEOq0c/NMEGttPqWjO1g+x92RrG1cZwDqHd5eJwToZKGnHfMW6DGUo26cgMiaLdHXadn5oF+dzw7s9SbvSopbw8gAJsUuluEIDhCsAlexGN5+BjPsXE+Ax2t9h5A8v+mXAfdaITIwsv72dGNr27gYdyj2IvFeE8P5x3pFwzePVpO7JbMG1zASecnuMvlUp0jgB1Go+mzxi9cu3hG7CTycn+cJ7/QJp19WT8HM3iP3DTnEZ2IQLUEn0H2p6BASGkmGe2LdaHscU2d5Oe1Tl05G5cDE/c7zNJDF3sD1xaIVj8urS9djgl2iatQUpn3en+SVk9mfOx0UOdDcmP9PbmhgP8r44oqNPy6jw96TPkjuVi5+uMRzz5Qf2WPEzTRX5VBZl03fx3O845P3iuyvrwX+/Uc/8QjRGTlOQA0+jDM+UIfMMlrEN4D8gqV1IjP3//o8oXzeal8oB5K2ovvlGtb7lqe5tFU99tEOwwxQ7r2sAzp8cVllYJkiGu0RdOPeSQUxLnIzxXOf7jhb4+W0o8s32CJLpZ1u4mDg8goi1lPF0H5BqYDIDssOMTRy58ZIpc9ojyWfj62bN5W4NeH693nsf1XVZ4DwK+pb1X9sf/y5bes72fqXvYZt7wQ4PNXuN3rPutQ9yXwt1aad6NduljvqTyV77k8KdCfyndTXDiGpIQOa+ioZN5DcEbLBdeMSk09ZuyQTSDUQhBRK/OpWpi8WkAuoPZDvzCIqh+xoQdMu+6MaGbnTIhXLMyrF7UERVi4u5BYW+yHVidwWaESpJQAsdxpP7FazYKVES7QvNQv7eT6AwFNKn6aNniDhp+LCgVFYJ6NJg4QBKM5pMQlDdbZZWNO1Fee6PZn7Ymuj/xerLYekr6GFbhPwXj8+YDN2715oU2avxeaJ9mf3b39ER9/+QmPPfhfq+XXT009oHd1EwIxMuMLXxNBEhqHAE1bvCPBXoBP0kDHO9xYiOupLTgVVTQ9N4buGu+0E/VQ34vlcnerSxLciIZE7we8vu+ICK9fvEbjBZ9uP49jE8EehONDxxXBkMd5S8AJgsNJBZZ80n2y3e5NyVXx+faT5n21QyCZIAzQOZssHDNDw7g3aZhqtdxaXbC8yGKKWNI9IYJqOa11pJ4PtI/AQz26UqSZxfS2FIgssS6V6mBVqs9pmFVh9bhF9KV7Pk4WQloWbyt7jADh0eIHS5hwKxhnm9Yrk34JBkoIk7/uQDEy5YqnA+5Tf0KJB+ATM0jUa9zxYWsajaC2gsYbLEvDNKliQpjxWQRbuJDdlSkbPezfArRTHKRCyqKh0l3wnQ46DQDJFvMnoxM7Uk84U+LptGsOYNkK5Kg5b7FPoahJFTGNGUUAqg1ChIkcn6ridRFBk1Mo9AhqaS/VQhAnBTJcYc5inseaq1bYlR0YJMpu3DVe9hy+ffLd+3CUdo608/LC5h8jJvvtYk990gXKVNw7WuFJ9zpQhMHsxgQMTBOWpWme8USDsuBbt0RPNsfC5skA8zR3pbl9unDdlWfQUK2wvkyT4hNNp2LjN8UUlQKQRO7Lw+EACGOaNqCiXth5DyexpsFDV3rrrOhaL0iSn7wKImkF+/0Izxya444fQmwk1PPehwDccbnTa+MzVkrmc6W5pLYxGuQ5TjKXQiJdX/cszoroxfMpm7c+J803Je+ArBBfC359JrqweVVDEGOhcXrsfXmgo4RuzcMM3qpekiDy0vZy4aMLNMOYCAAfoMryAoQ+pEDTjhT1/CHotqabnluei6U4KJonUnGR7hFm9SRuJ0bbAttpg9bUeOzu7qg0DoDMPXfwcjrqvDRX0ivdkrs7ow86iIUF+CyoewIY4NsG2SG8nJg38JDhqsjq0Q2CzxVHsSbQFQJuAFkMd5NAikDBRSJCRKHJ1uAErhNIGhYWy1bjETYkhMDisObsDIDpZo/2+TMAi3ZhPANBcRFhC8ac1voEyKav6dZxjfMB4x6h0CtL8MUgAs22vjubkxMgVSBVdG03jFo2KJ5upiAi1Pi+JBDaUYB6wnb3HESE5cho7YTTsuB0POF4OqpRijSjG2oswC3tzRVgKi9Tgo+w2AB9l/shgczYmCxKgijfIgQ0oeBMNBIsQ9jwu/QZa8bz1FIRB5dYH4rPGr21fpthMPjOtgD5NFkDtsfuTmakQOZRzwEbTAWLHAEI2h1jMUM1GD+oZz6nSzsbuyrqXQ9aV/hBcVw6wZXjsP+JnsEjf+hwVYle6BS0o1sK2WPUFZxi/Kd7okd/nVewldwDOEj/fo2PO9g99zhf82nuke53Kf1OLEUvdhxwT/Q9+rlV0D3Sh7Mlkl6Z0M/26f6awSAizIHfEQqgQgQuFCkjirVHZqjhkcSq8fmaAkjsHA64TGGaNJVLrc1oTTKj16TOGlkFysiy4bhY97oLOkIxoQTad9gGEP3q8+dxrzAw7TXxdoPSfuDvpcPMqgSJY98/+kefV3g1NrfzAeQ8SceJrkRDgrUc7WQICJ/o6nUITAO4h790vJrBwWkG0nxefvr+MnJbF/q7fjGwnvgzcL3nJatm/J0jM5PXE0iwZvjV95TLhbIcI7NlMoxIYt1cea7l4wU2RTvs+zTwj91ZK+4uKfJe471tFcLx5wWEBY3e6z4pr4YpHUBlPUlfWV7a8y9EFd+u7H5h06r0Sj3gPXKhl/sU4xf7Csu//hiAW5UPBDwXGh0ZEjzdiEYSwfnt+ObguK0bu0p9XwgiBLrAMmWJnjuZTW5ZFANsNhM2m03wuZ9vP8NTtdDQrn53Y67z8hUTkYvBaUaNAqAWjWIzQR0eCjNkWVDwMuoA0HMZ3RmtPIATPyEE8MJD/fPX6x2WvH+ulzV6eHh4guUXvqAdX89bj/whGMO2/5WV57m8FmDB+0fjYuDrt/7D77hcg0KO9+XluQAerc1Ts7hc4AF/9l4unCvFDV+k04nH6ruHyHj9ovXpXwRwnspT+YPKkwL9qXx3ZQhxckFTJHBLUrMbtVMOM6M1Rq3uuSt6cCWgSEWtDYULCleQCSZdoAKxnE7xEkkfgpd2KL212wUWJt4UAi4wzZ0My9BM66L/diRlBps1vXqVW8/tAAzSAwGKe7Zq+QQPb05AASYIPgPYeFhXFjtUa37SLNDstJdsLPBAgeM6dLHB2fr8GZ7o3yKEOwB8oI/4f6YXOLWeQVREIu8xQTDVzaPCKH3RXJiClVg9xj1cu5Aq8Uz2oQfoC/N+IFV+H0iAugEtC0gEN62psvCeV+8NDj0UfAgqWMO7qiBdQ2B3oarWFKopJOF5OUIe4ACTd6ye0Iac7WdCEhFspw12r3/Ax88fVXlthi+11BA6sDAKTahUwLQkgVi3yG5ttnDPhKlU9QQWD5mob1fvrp5zPudFrq6MXwk0YYoUFkaBecQacwsqahBhMMXcuseSqHC5lGxM0wVUZ6v+jfaZj1Xzj57f/9r9/CDjv27WDv3VQsi11gxvq4GCmJdqdSWrGz4sJzBvABCIiwYmqRQ5cX0fKrpOgme5BbADWHB3OpjxQjFl7QwRghzNKAPAcquC+FLNk8zmhpcFqBUAWxjvrcHbUe+nENzFQjPr2nO/B4rlFEmW8tZXTjcz2fCw74q7+15SoxA4AFnlS5P+x5QLciI4xct7XMmZ089qyhxTftje0j166mEGiVDI51BCMO9CahHzb0zwUApFCPc6FTOacVjxZpOgSooptrL0I9P0vl4eJaTWClXiLBDuB1nKcsxYno581wpaP6gDUL4k3cxwMfBBgZO8WYFH1RCdBKxhQdI/76u4/1FUF29teDryXXt/nadIFg7VjBWj744zmymHWCKMrhomkIXIvo5IvEuy6rzElCQ8mu4NUyapofuKXPn077EpL1yn80e8GDlB9wqigNFSSnjzqyBQAgdULuDCljLAhmFeQ8wCPjWgApNUtMZAJXDTKB+lKk1aGkPcOLCx7S+2uaKYQyE11iTDRQQo07G1VCYtRcvgIwRT2tm+oZzPpK4EgEB2Dl8E3rAaDRQyQ4ecIVlAVFWZX/cAHyBVUFHQwCji+zWbuuqezzSMAEw3N5g/33aDHVDf2QIUaO7s9dIDAJ0Isk1XEp5xiZfSBhfY9vCnsb4zjXBCQCkbxUe1AhMGnt47IbCw8xC0eVGl4twwLyccjzOOpyPmU88Xz2JnGekezN5nginpKoFqVzDC18VoFxse6XQz8To+ORTTEBf8fDPoh0PI15WblTwH+rjP/UrZbfVcJAI5HMG3MmiIBX0u+e4INwggElNuo28yOzs6T31fERyB1Hasc8/obWWX+DP3Uu+wV2AREYor0Z0nLNdxm8238wf+6cZ1nY/Ryp7HPCbuN5L5a6jtcrl8VwAc0609dYo/voUwgyJl2boPlJcwIdkwZC06x4yeskJDDqNHhnC4U05CYUv8j8FZQtJ5bjtvb3syoTN/hOK5S7NA1t9i7+k890Cwrsxh1LxnXa/dOl87M6Kz9AtueOQ8bu+X1RbfNueG8WEs9tBGujaqi8/d35g8XOXblKvv+IKNdRUWrtW53PYldmO4n0lfsIgAACAASURBVHnFgZvsfyU8zz/iUonzJoCCV3ZNPcw/UFdMP1QU0ntod4GGNSa8CQP3XDd14JuU3Mxaee5BKB2GXnzBmAQ9xHqWM/2Wbt/ncX5HjwdzVYgDbKmYvISjCzylElkaCr0zmTFia4uGRN9uLcWFGt115yBvzWjSZUT3zYrTTofJ4FtKwSJq5J7PHw7TTSpaPr/hm5DCb1baL5zCtz9c1mcswtcbbPzR5T2pEv39v0Bfv7bkqKeO2Rt6XvQvHXrmvR+jNT+Tubr8Z3U9dvB/4bV4Kk/lS8uTAv2pfEdlFICERwTSMUE6w6QCVBOmi+XMBYFbQSsVtXDkQ0Y6PADdCw4Q80olFHhGTi/uTQN8IPUm/QGE21JgJ/cgaIOwyYV5Qhb21wVlNIyjh6eFCQaK39LvxKBCeM1iHh2kwk2oYjdCWFFR5SARwOoRIjUJwBqB0JJwYFRoZmvMtQV2ZtBBnafuoaT/ONb1a0K4D91LPMs//vMf+OHN3/Du/c/4f//b/4f3//jfePPf/6feJBXsPv+3f8fHn/6vPdrnY2z//gPxur8eprzEvNtqFw27WqrmtNpggnvu5eIWyzyfUErB57H5q/PjguOKce/cQvCcYYYqhH1RL01pTfcgCCdh8O3nftBKRgMPhgoyhZawH+67V4h7rcyAJzPGaVbVemP1zBZh3asi4GXG85vngADHRfO4ttYw80lzfqELtF0gJLAQc8sMTEC1iAPQ7QlmVeL62OpmsvHpe2/2exSqOBw1a+TNfq8C7GXW8TBDipjXdQ//XC0qAMR+k65vF7XpIky1otQyKJX0VmK047NjEC+P2X1RxxjvfODsSvzREOQSXF/LtbQGAVXumHA7IWshE+aJgCtjaU090RfNWVm5hkLdIXljAn9uE5g1dDrmgum55a83Jan2GYHzjCSYEPqg9OGWwJtt9+AUNZqSPWG5466HNnilcAQ9YSkFhRiT9euOD/Eebk2VWW6QIxZeHupx2r3eOu1yDwL1cE79dpwgfWIjWkVSvKliOIUxjrakjzvWNkPBGn+lNcy31if7qxitX74kZ13TapgnvqbMcG/wgolgyvTeLyJCazNcJOb8gDCb52KfTR1DP0R2+FUFjs8hGSFTUsnWj+6xpgr0Ts+pjPHIHU9st1vdx4UwgdSTnCzVQyMgIs9ICseeyauve1KaiGNIU1jGxPYoNp1mJGOMlfhVEDqD/AXjgnrdJKiSfkdyNZOlxTp6LwNU03urr7GthUh4o+YIC6GMZ0Rqi2EP0JjTtRsuYbh/Vhx/+jv9Oe7tZKXAmo5dpefScZmg729vj0VQpIAPfRJlBTe5LVT00NeS1NAnAW0J6tFd0KTB+ciCYkJSgJuGUxcL886lQGXXprDbqDe6tKa8RutKauGOGwHz0DZ+OEKBk/KajRswd5wkbEpvCEQWQDTXZp8PM8gzTZCgR/NQ3Cog8XQ50NzeRT/LIqDJ9mglFMwQ7EFyB7IIOWKCZGF9Ls9pnm9XmG+fP8Pp82elOUaPVWl/gIgK/rVsrEvGo4CGNQu+jzQUftwSM5w76XpGaP5F8Vo2lgA1lO0WpRKoItLSeP+5mSKbGSwzIAWH2xNAalx2SrlLPXcy0lx4WHn3AxeHu6LnA4/EoSGtxTydATHPXgEsR7pYhAIGc4t9q/OWQ9ObkUfMEbA4fSKN+FFQzQsoVJcABEzARtRgEyLdAFEY9WaPZbm19+QziPRxIYV6tShhvs9JgFnUcNizw8wAJlHVt0CzEpwA7Pz8xh3bzEYjNgI12hLAzESHQjHTe4ssUboy18PgO2E12PQ03oF3hE3RyepJT4LCgkYZnnX/7QEIEfZkXugJpR9SvwSXvdN9/i/x7JETffVJ6VMgYDfQ9os0Vuz9GPFqPk+mnymHeX8sUiI4rTbawSQotZohHeCe5oUIm2kT+Fx5pSkaNL0MiAqWZTH8yUEjIBYxyjvGnaIpfwKlUwA8ykInIAdYuIm+roZLSaTDj49n0IQGJR2L86GGn4PHy9M0KNH6K3wfww1LEv0fOQBZdYWSEt1bdQyu8Nu9sekcuHJnvuBGh3BZ1aPh/rXnvGbmFe4vgXHHpzsivvqe8foKnjPzBEmOH/lyok/ueS69Uu5RjGXd3dyhgN8Lty6PEhWvML2esPxiucqt/VdyeayXnAj6XEt8r2/fKv7/VQC8P3v/S82UhU8PhDx+Ibii/u9l7UX+SoAqr8D0Adsf3gIA5nfvhvH8WoDXKX67K9bDEx+qEHtpPMErAT4UVZR9JK0vOHfguA5zescVbV6xEOFGVHk+1h4vOPgUqCyBudPlAkQaKo9g6C4UHoFrYZXfLHYmrVJB1HC6nQ3vpUhWEGdGNVKi3rg6MmCEqy8pnipx54MsNeF8QsUWpalUi6nglj6p04i9rYh6qQvU6HZpyg96Krxrve7nqa8rF8jUxVJ+KLDgBw+2qHJcbcmNV/4VFOde3sgYzv33KA83f7nGuec5YXXhce8P+b7+1qgSj3fkin1ypvC+/53XfudzyTWc8RS+/ak8FS1PCvSn8v0VSvxbogVdDI04e0j6wU3Q0LAsBaU0NFPUUbLaDHkGuezFPP/ME1wDrblgJL3V8lCWUvBCgDkfIkOyumLi/GyWlFbusQBxvy9BAUO4gIvEiUb7WfBKRL11BHHgpzTyDwS8AKHUCVNjEHEIu70aoaEtOgZJwlofoVv1jwfsvByXPdH/1cu79+8AFPyvf/wHngP45f/8BwjA8x//jlKn6wmzfkNR4TvFmT2870jzY3IIgBBe5ZdmvgIgy7V3OdTW9WLyoICCzwQ8K0UV+CI4lgIppeeodUGO98X6uPb8u+iNb8/uDOzV30dH5WPbQnCy9j0EpgCmhLZDnqghgYcCXyyvbq0VSyOI6IHRD2JT3Vje8mY5JgWynCw/q+9z8aSfMQ6fH0cU3BoWWSwksva8UAVh1t8U2wwMDSEtJhAupereEh1tLQULu4Jf/eHIvPAqKLJR6DwbLrEXuIfu1xZBx0O5LRU8I/q03ufXDCX8OUp9znM4vHjdnkgYLSyL5iYvFv2htWbCTMNNoUBnCN+Byg0KVRRW0Xgh0d+4gdBtwAs7AkzKyWLhOsW8wmHiS/ZQ6tb/CLkKAjADpGpzSgpcsblyD/Ocb1cPXZZLQVywz3kSkIV27n2u/fQc4JSqS7wbRJE2pFbPG2zedsU8F22OWTgEFn92YfcyDcWalmJCcCoF0zRZvvKew/Q0pwzCRGBulq/c4BK9PaKeG9lDhWtR/9CsRGebT7LnPFpADgl/JkOytQfcWIZDyV4x6aG9NfMIdU7CUrBIUnNfEPbkgJ8SGs6xVjxnsN3Fl/6s8yA0XPd7ZG1kRbR4u9LfEcpnE8ZnNmeN30VGjOGhuruiWlBEFVpsMLlWG/gK0tiwj+iyLE9yz+wSS/dwzILnNDb/vN+zTsYPe45d0AdEHulQ3B2gnuImuHmcYaEpOUSAXebLnFN0euZw7t5CClm+Vk0YlUWV6T4PhvOYjda7RyvcQCMGZzhrBLke8josD0CfBdgXw1W2xsGIa59jXRPMdy/mfi8bODRuKExGiwsq3Gt3D6mmqhWLPGP8LcS8slY8h4iogrgI2oEBIdRalHe3Pen9WphVyYXM6s1YH7uDX4m1QOAO32pxT9TT25WroAWqZJ/OaGOhgqnWPg/UgIVDMaxKvqMZaOjvxi28zYM3AtQowoTsBilmuKdRe2qtmKYaSv0O4mKpAIDIy+3hoAc8lfGJ7QedBjSoIRpsXgoMh1PBtpgBk8+R4wtR5TklOAgcBUCwRTucUG62mA8njQ4W7rmeACPtTfg5ZcRJ/rnBGPUIUCW6jlM/TzZMP+/MBGw7yF4uRk9UeV5QLCoOcTFyba1dEGpmPOv7Mfaur82qvvNwoSDPzd6DctZvz5gG6ArzwcsdHUU6GnWF29o//8E3x2aRi7cBP0aT8TkdH5KdrwvIbNZV2RPGCsmQMD/jp4ySUL3yEJxwUqd/BN1XGeIpJumcHke9m+7Fmf/duyAr+tdf4wA30oJe87zNsWe9vitXHW5yvUvwPPDzlMa+qnyVbN57M7iIa09+VaHV55eXx9Dpex67tExf9B65eHdoLhYu85D9ngAp7/nHCxCaPz+Af/0BwIezd17qPmFUor8UdJsMu1/f5mzqcvHr71W6h3nv/TBvaVDvV0ehPN7P1L3Y/d5rHp/5VpC7Vp7fVzwCh/NTgMbWiFOK71UzgLkki/Ezj/KDmarQwJOciW6+dGCPGY8LYI2iUPCOxXiRAxoRFvIw9OY0YuMsxlf0lFh/rUJEj/LKXkdG+AO2yjctrwQoeI1HWgv8y5VLSnJBj1Dx28tlAOlOALS+0T8GPufy80/lqTyVJwX6U/kOCwM9F55QylPuJ7xc2z0nAAKjMVCY0ZYFi97WnMhAeBm4YMNpmCo1tX22gzTswOm595g1Z+47EuwIqCyo7LlrOcKTejtB8KDCLbdkZxc0uoBRrO9VBc2QMYdkNUHpix/f4sN//oxfCHjDwBsAv1jfPxQNqPW+FlQGxLxxQzFo/4nl8vV+2fTYXQt8ZcLNoMypjZgnnDPbjy2/9RjtlpqfyA5236gDmVn69PM/1bP/Qr1ncjl0T48+UIbf3RBdWZ7ZcpRuXLFlioVSq+YDFsHSdI1qIUCqCcm7J/o+mDvBVCfNn/gACy7Wl2aHRA8x6NbQJyJg2qC1BUUENwYnbGO9W7Xnwqg4qLlCyvZnP9dqAyevbw/voDnc5zK2qsJUYEMebrSicVdM3B20Jx41YeE5FO0EoE4T5mU2i2x9/0Q1BM5NFlRMkROWSA+pdbONUJvMFuaWgLktcI9ZIsLd6agh2d0ox5Sl1QSoLKoYRumeWMyMyeZlIgGJ5dQuFO8sRUk9TXpaVMtx9YRnEVRzt1sLYh+7H+MxSsI1L75++oK+wMPznWm/1mbu2nAwh+4HPxAHzmbGPC+K56rOaVvUA30GsBVBK+alx5r3rNSGWp4BC2GyvUZUsXuxw7IU3H58b2ErXUjaR+p5kNmNKkTfyUDUBbkYXnvaSLCQYCpVjUpMSkFQYYTn7e4KcMeXYgd9CeFuLsk/2WcIWK8JYHCk+LeY4UcpGmq81hLrRAAad8W75jaUM2X8vUXWPy4A1RW82HHAPc07WaHklQkLtT7pHqqbqkpw6F7eFa2j0TkIwBbzPFtodwEsmgqVgpLyEzAxlraEqIZsH4ZhA/yjG914yGvv69B3D7NrIbDJkll7ZlOy1BxLW6wNsf/7PCocmxAslJkCWDSECHfu1/Pc+s45U2AnFYtJNgVjdJOzdbKi3q7WT9G2JLWZ1VAhmJOupMp4PvZYyr2o3ud98ckr5m6tpZ3rLruA7TEgPAgD034UgG9HazhG2hfkXFAas/R2xu7Yc8W7272VR2+w/twab4oxfWwROspGDWAiFzaSv64rk5z1PR01N2TdQqiCiVFwwHI4gEsF7zVHrzTzBJ8XTDc7sBDaaY45YTHvT0cztYKXpiH1IRoOHqrgdAM6tqkSAQpNpuh1QzLNlU2W+mIwzrAlDKXMOBkAC9otgybdo00YRQqITii0hWAHLnfqhS8lxpDxWjEQWe7u4LtAvawBQdUIP8KK8wE1wBNBwzrX56ZPyhGg3SjQKsZzLb7vit5TgzmFC4X/pV+vhIIFJDX2ZknzPhqpLWBpqDvNVyrHWQ1wDKdUAlqxnKHGz0fv3aABsPVQoyoqlpYmzj4aNUWWBjGFfBi3NAbcCAvdiMiNvACd0yoKoWzzMhNhT4QdCFMpaMa/Nce3dvbx/m10iUA7AmEb57Fl0Xnj4wllp+Haq9GJiETtK5zorVj/Gwla8CU+b7qv9glnLSTKY6ArFndwD/UwXwxF8c60sGTvO9h67Qggmo3+7EFlVlpd9gAdjR+meC5HQRERCCMMwpRH6jiTQDhYWq+d0ZKSaIH3Y9+nZLi+S99h9fzJO4yKci/PoGnK/F6M3+fJXr9b3b92/BjwYNK8XbLrI5CFhDAMSH0tqtPsSEFgG744fBly8bmFk44e9UlhSNubJo3wNS+L3TVY94gzi0Z9cBf53isL3y8OXjt0Yxn3hB8VU36mVv6jz+EwT2vFuSD6pZc7UIdCPBkB5DYEHGkNOo+R8GUk2/Ya1LdK71CaS/dC9y74qqb+DcQX58VvXzuoDHzAfYXS33N29KGnE4G++FDmZ0ajvvXZZ32OojRniHFm47GB7TGDbG59/jrW6efzvsT96bzsAljo9sul4hUANSorrwn8XlDeEOb3+vDHB5Yte8S+Et2eBa/BeA/CawBAe8dASXPFr0D4YIajY3trMF+XLzX39RznYjnY7355B0AF5wWv0PABQFdYupynQMfuijJXnjcg+JTc9Ul0zC8xesB3g9txXP7s3WpMe3vP4doEJDRGSAb3/bb2p04Dv6qRC/WXRjHpBvkEGD/nYy/xXC0qhzlY5L+HlejrHXd/KWSptQxN+9kOrYFKxURKlQQCbnfqYGF8U8TGElikEcXNjZt62qOnOrwm/1p7nj+MH35b+fnXnx+cmle2JoweAn2DH+zeL/h44Rj0VyouG21/YeX52RI8DlyH8txZDHQ8GYr1awtkGyin5yM/+Brv+Wh5TKo3GgaO/MWl9s6urenRU3kq30F5UqA/le+mZGboDM3bYY4SAfADBP3/7L3rYhw3zq77AKxuyXZ8iGe+te7/0va/vfdMEjuxLam7SKwfAEhWdcuHxJnMrBETWerqKhaPAIjDi/53RASuK6vhkJYNdGkgQ2iU/l88XIfHv4WiV20oM7MBDTeWZ/RkbYq0hqQhfVI4YaEwKEqPOpfNMZOEhvFoogFJ2PUD8f2KR3b98Lcf+fmfP/GLGK+qR5v8YMYHUT4U9Sh1Vf7e4KdlRNcpQkU8wiU14WHN8MOaYdQeVXk1kpjtIW/bh38dU865TkitP6s8BqX0R3Kwu0In1Tt+uLDJAG2hMFqKuhE9Dg7NGkxI7vdTG1qsxa+ZAzN/9pmNQ116Q6+18mwRDghE3uGMxbjf1TNHxc2Kn6OZG+K5XBeWDQhl4GnzRSoWt5olEeHmeMPpfOK01oiGE7QccGeZ6k4BrXVD9FIWlrJ0KHgx6VHnEoqsvsegR7965Kp5CgRsUtSNCGKfv6HkYPrezBX23eARhnUVKAG3hoGKYxaLmn+XsKqqbvCL/WnT2KqNg+C3og34IGwFd+2EL0jBDBeatGFnSP+S8TwfhQFpPJuiHWkh6S/udATUdQUz1hpGaaMbKwVQiYUf19xwXGm/vkR+OLC2xvFwoGgBZIoGt1Aa7gcjjOvNPAKRVGCHwSkgkrO7Z4MbLZRl6fTU+zrWQetwt7OylqE0n8YR9ns1udj4nAZzVyTEOgpFsRZvSzps5EZ2o4x1I0Pyst9zcOyN/q4ENvd37vXoX+w/kcJy8AjJUgpmruSGg09L5ofF9/K6nrtB3uvxo25GbKzr6tHQ8fbaaji4eC7nNGL0iHcZ6/dz6lgNxxnRKW41oz/Uoz3NWjeoN7t8vnZHuxhmUZ/GiM7eP5Nt+TyJH/PtNha7rqzu23wcqIfxfGuQyrKn85KyCVNaGrM+dIZBG8a1uYgEPf7cwtyygXFt/pHd9dHYzY2TOHYxCNtI9Emy2Y3R1SZujJ5e2uTolZXskSQcVdcdrbQJdoM7fZoiWjAdkc4uGRKLXF0xGmsMUUweMC1oLW6oBOx09qe6Jtc43d1joSh1kIxQvTYQcYe+do7nWvLIzCEc0njIosHdMQICdqh2Hqc1n1m3/asbw1Z36Mho6rSKJ50oWpw3TkgDZoHgE/tjM99d3k4445C5pvm/iESdFVOT0iq7WIpDkmuNMQ5eoWXQacm89mFUd8SQiW80jzZfrPTv0jk1nXRWWbfyU/BTVY9ax4xzOETkXMs8R+LKas0IdC0B++pGxO6sE2AXLRB98gzj8O7bibsAZJrOM0WEKsLRteQjIrun0II0Ipm5zHZjhkNHn7EwyRpnlCPLs1vWu3vG9rRwXvN9LccbuGs0zt14vqbjY2suvjRjFY/Ya5EqJaPOz+LG88HPh3yec/25coNwljDsysxHYh2YIpEXfci+Y13NxrLujGRbYnYfzRh8aaJZUW7ntu72WRrXbydens/ujedZxZQ4BGMYysGN5Uf5lujzyzIirKb3bgSkfLP07ZX3a8jK+X3Pgx77rMubowqs6ZY9JP9Rp3WZHipfHcuLzTKQMX17Uia303kFvF6jt6VTSBmywyQgwoSqMCjz5g1dae61jfP5fMYa8mgizfhZae+IN8uvXb/R5YZoQzcOD3a6s7lPfPYryzWe/gfKdxFNH6lkKzlcNv16Vz7fokdEuiQOFxVe3N9lku0Fez8oyV4UyvsE4fBjpBf7cUKfeaS8ND9WVLaR5wmQaAbKm77Wkp4ZMFvN86+vJKm9Vy9tq39J4/ceuj1LN6JPfy8/vgHg/Jl01D/YqHOe0/3vLMprsDB66p9tPJRBxy6+GX9YG3SgmaesnB/x4At3AIfpuG5TL/9E/Z0kmlDQizzX92AKhPK8cPr0ibMKJfptRFrDSJmhEaTg57idXPYfVvatfm2JAipX1/+/U0naMHBa/r2KfKflnHreWc/8LdDtvT39X/tqOpgO/X7vTl6SKQDwqTyVp/LZ8mRAfyr/VSWV5L10ITJPt5NUmaflPJTG5RZeil25Q0HUXLHDEMZWLRGl0bAWRwEJAc9CeRhSrEQbZsjeF2vloxkvm/GbXiqaDc/Zk1qQNIp4TcalFkFA6TndCdjNI8L/889/EnpNXjbjZ4z/ZfAg8GP1fE3dO60IP5pSFd4tuDNBvs4gFeUZZ+bt20rr/XA+KWK9lX9tJPqv00F+0iv9C0uuvXnuLr+foYC33zaqwZIRxaFUbK1Bk4DZdAeO2swVQ6a0VgYM8u5tXzOGd0MmA4ai7LlNhg7zdSn44fl+00V/r0pCbfnnpSye+1nEvYfNQDQUb34tlXACnBBOSEdkyNyXCV2tIRxmLuw1IsCLFBojcvOwFNq5+r4S6XTj4fSAEdF808jo4u1UVRaWbmBdyoHD4QDmkcnV6M/Oej2bplNmfYfkeHqE+6IFRT1383JAdfF9mTm1HciCIqUrX0spRKAtRX2eS7TPot61elRYjnu7VGd7867tB0kSGjMpQ3EroR3rEZQMspo0ayYDj5W9oWgY2LzCHJ8yKdSNVNwDmdJ1es89YJGT7TY71gTlSLUzD782youFh9ZYiueuL8db7MMKfCKNPt6+G/TZgjWjNqNFvbUZ9ZO/XMQ6skCz+5j0gO0O2PZZuZraIUGw7FfACs9QzyPC3R8yrMPIp79CNBJJRYeNz260cUNIV27mIWsmpHEpDfCwJ5ZZ8W6g5+/35TO3O+2R3df7ivIuN3wTxrDjsnjOc82uS9fStmkM3XZYIlIzUV4a5aDTq4YxvtWV1lxZXUoBS5cTCYWTj0GuaTPr+xByntJYHbJFGsw7D0xDX6AczLmOQzGfMMhiA+r42ui0TQ70LZpBDMxVGm/TT58gybZnBNrlph3926ImpEywNdp1vdcQHi74j3ewqwhM+vx5tmV/No0I0tLQYReDsZH7vsDX2104U9xun8uIO7sP3tryPVu5svOG/f7YjBMDEt52z+3HIWllho+GPHixb8zCEVMwE6xG/ubi7fMxE1Zh2gOCqedY15vFecC6QlXKojQ5IqXCvQTMfLS/NVhK+FKEnMHEv64IcZ4+oCGZr367wrxrQs+FfIyIyxldJPeir9uYJ5NNPfmTKVtUFb0VOBNISScKinHXea4byRaa5r4Dq17/cnvD+dOncBAYitrJNhbpboTKcF4cXTyRedBz7xggacW83a6LrDQNeOIvcP6m6qlFyjCoi9z06KtqDVkbqyrrenI6mPJ2yOeqbuw+LRXO4obiHEuNdDBJ65WOTKMxziUM81qEUoTIbIExpRxhSqmQdCD3S/wMo/rWdTb7veL0seBppkTdYbeIsIh0eQ5zlwuvPxyO+5njJmSbe1RvEFGkVfT2hqUU7j7ehdNfpEi5OXrU/JGA6Y89ZcaDuXPAAeEU9F7EU62qCc+fP3MnxE+ffC7C6e08rc9YBGBuZCfa7Swqxhl41uffpWaRkxvPRUBOmAmKy1jWoXgVVJFI9+Je3r7A9w4Lz0T4GLLUfTgAaJxhn8U9d7nGp0cz0rxfNpelngE3P7z03LEffiNjr+OWviefT59nAnYT6zMj9Xdff7EMR7cr34UAfPltGtJjb4WMUHoO4OLj3Z0zLL6PCE3d7VfAtHiqm0ne1dh/NXmT5m4JWWAWgqM9IkfanVGeuwzfkbA2olfS2IE8MCZsl/KCIa/2Cdxxf0eA2fHJq7xLNt9vDODTfSmn+7jNNFM6T5dpfEcfNlP0deWaIDN/91V1Xa/kC+LCuOPLN0Y7tvyq12JjzfT7bLpyIf6OcfO1IZt6JBxCNpHqUd/nZOp0tdDXzqfa+5RNX22eMX6jAZ9+yee8/JabPS683L3i/W6KnXO9olhheSucfw7HZhXKG6GUo9P41mg/tz4k+Yrr0ui2zLDWs9E80Qav5WPPkobwt82j4u/fvXP6EO/P7xOCOVPYvZzYXev93DoSuY7kvSOvxPy9ltf8Jo/jH87NvDV4iOceZHvDY3J9EeF4OHJ/evC2xfooeSbKm2FywBp6gXSmK+EcPPaXv7E2n7+H8znquGzH5RW5uGNs2wtBl0NxPUs1z1teQ5YQ4Hl5DoA+U9a7SsV6Oq+lLB5lHnQag2o1HAT8/PCwpgPn9Q2depL9fvuXl91xIdd1tial5t/kfb/+2v49odFf2R837D9y3Hr0vm++Q7bR2fv7rjk+f658CBn7a43nbVe/00GLM3Dol8jTxWf6MfcgaUXaDib90lN5Kk/l8fJkQH8q/z2lHx7Y8JWu2/DwHRfW0pMRermOYQAAIABJREFUnDlNBxuzRqtQQ7AEKIvhEQF+iFfTgEH0yAlJSfuxpsU/rTXW1aN+TwarKT81460qpqVnoJqNMd62AWUIeRBm5LZ1TVM/PHVlehOqVV6uXu/PYl20+v8FXuEw7z9WPOe7CKrwQYwXwKG50kEMqCFk14bJiGi9puj1Pnx9JPq/uvxgvwO+/d+oXFUDyFB+e7TR2AyLLqztfKFkc+X05iz8VSUPkCngyeHoV2zFRDZR7vs2zi/y1Aa+TlR15GaMcjP3U5SbUE41jUiuvvGUteZhznruZlXlfD67oT72iooblHPvb/plrR8e828x4Xw+9fzpJiMXlxY3UJ7PJ1Jx7a8JoXf6ARwWNgxE/vpUk6XntCtzvQ0emSxENLsQRsP0tNYedSsIZTlQQqG11rUbDAe0stGjeB8RvK+dE3sKjM3cTBEsaSR0EX9EpEtGujxS8VeUbsAwp8um6aLhpYZxOu1UWtwAQcCaZlR361qoGvD8oTBdo57F88+rKPJMsI9HLCFUSQXOOMB723xsGwOmGIbShc19MU4TZF+Pklf3jGiqo2d5UJ4NrewO8pNSww2ODOVs8IOlpAG9hDIkohsfHXCvT4Fq8ug6+VcX1WFUUy2uAJfxA4EkQUZvSjcsdbhLk26Y8ukYY5nGdrXFYYtjDdfqBkEgFMnpFGId+SFp4DAg+7p4/HAbh/SgXZ6beRiahp7cuiK9O7fpRCdaI1NL5HpO7/OMDtvrvq5vQ5s0E2OzWxichjI9TXBjTT9mPE+j+HjhFLHGiOjNMY1RGeOM9bEWQlEkRGR+KhcmatQVyNdHPGZlJ3tcctHtd19RNlXY7gui/5/fQ90QM6/HgNBUm5Q15vKWkuOPe6rFxMoS8pmKz6PS+ZvLaKuPXymUzGleFNYTrUNlD3rX109RZK2oJRxotNi8Nc6aFkRq78O+x3rT9UB9TPx1j4+NwNXczxdFZ0Nz7I1wAumoKSrQFCsj5j3XbrUK9w9DNuhoFWwM97uGhbx1RZbdbLrx0/emDQN80YKc3Wk17899ntHlGYntQx470Izz2dPPpAyCbR1qelR4M5p0d9fBH+InjbbWCQ9d1hhR4IFAEG3I1CPOW62vzZQFUik/r6Ml/q5zP3OMcq5FeiS2ikdpC+6aUAzOjllOcSJEu4PyzElp4aY7G4kqYg+ILBTAbg6oCPX+oZ/DjAfKzZHz/YM7TZmnfbnLw1qs5QMS0evbSW7kguaSsMbHEyNqva+Hvq4GrU60og6VvyEbY0FJ0EBaPJdTFo5FTca43zFo/hcVpvGKlL/zZy53uBE9ry8MYKu59pll5M0P+JnhyO+PQJ8jqS++s70cPc6ZLhMwzgSxtnJ/5TMp2zttSqetMRJm6URDQAS3ceYCuhN5v3CFi8xG9Jt0tB2pmPY8SUS7TDG+t/5Xv4/duD86iNcatS3egll6uFZp3GXTJr/ghYPOzkgNgnW6Luyf+1eU/cj9heUL56Lr0shOzrDLP689O8uJh7KAONKSWWN5s7C+qyHf/bap4xot2DdDALGAZJdfL24Vg+XHZX/c5vBjCfQvw1MaNXirtJ8vV991l+9RPogbqvZyb7YPtlHj17tkGL/2+5MOpwEsjWBfm8v4eWyPCnwSdy5agPZna58MTqfTRvYHOr3JUcqoc9c5xLjZqGTm0cNZY7zj68u377NzXWNtDCQuYfAyuXU5obW7qX7jvJ5JxEDfE8Nwbv96YvNdizBSCzxOmf/9jOd7B5v/tvJHkEd7mYjnteHcG8ZTrsnv9nU8lafyVD5fngzo/5Xlz+ZWj4mn/w5lKC7T1JEH441qcNJ79GjuOPi2VKA0AWlgFUwojEO85wb0yHTVNiLGGBGxIkLXQZPKcQWrvFyFdRFuraFq/LQs/E2EF8HgPoaCaH9IYVIhuI7UI5FkSgpnjLP8/8uKYbyJU9Br4F1Ek7xG+FWE/w2sgudZDqVMEeWjCgsV04ap4UHOPnaeYTmMBJOyUIY2YbsKd4qmEcH1r5Ws3nigtnsi/45Xf7/W5jodChWYPYW3SpIZ0A/gFDDpt8vSFZhmmf/cMJPwoh1rWyWj0C9b8rVODbfR5D0s++164gH1fXaFHPRDcBseznPJKJA5t9dN7FlB0GWBZYnhMl7ceJxLbWvU74azunpO1VTa1POK4pF1x8MNp/VErfX6gUpi1Rq+hxlKBzX8XWXx6JRUHLXG6XTP8XDDWs/dGDYUo6kk8vvFfM/m+pfp3QOWzJ9ZpHRnFVPtaSEk9nspihIGdSmefhFfB0cVam00DVjSmOg6srr6fBAKrc16nM1I8VkYivmp3T0aPer3fLvS75dcuf0wu1sXO22HcOUzdEOhKxuL5+DFDQbDICPcmFHMwlM/59BTcGR7G/dgtw6F+1tDnrkioWphOSyIFPRZpd7d9J6aCUs5eCRz5L3NlBk5WoJR+YS7JHlu2iZCtYata/g5SUx2dDPaqVIQax3BsJN+8TyHI6LY11LCOefg5zhrjIOUAQPs0ecC6kZlZgN6V2zGTgjocCJ9wETav1PZ1dQdC1JlOxQhvt68k2lUOZQSuduHcalktFdEJc7G8RlePSFQUyEtMg1gtq6EQlsPPk7nM63p5IwSN4aDAqqRRiOjIhMVoVKW4+D9QA8nx1NnJG02SYOOUcpCbatHw+9opYk77KgNQ5kbv2JPWmXRwkELHx9qvHlmvds1M3Z3Orr5jR7kmTJSru2tIjZ1+rb/PESrvi+2ZtchhY2PPkEW49P9TMzlDCUidwxOZ5AqcBxzMcPa2jTihkUkea4n4GZLcOxujiNkux+yfnZFnKa4I0WfxqmvTO0JLpNEcEYvoLOK0Y8oGrJdTtYY00hvkVDpYcGqp8rhBdjpznnBC6VYQcxpSz2FE05L54UwBLG6U9Jd0KXmBvpElWm1YWvzPrTmka/gTivmaA5mILeCnhZqe4gpdafUWdoYcy5w35Bno+/uEOPyTxrWRSL35rQ2LwyBMqVxUEWfCfIAtFvfE3rqxmfdOV8BNG3ICkZ1p4VY1GIDlcaXj8W8SDgbNKcnE5ytcAY7btaT5IZ7CH6rcL7xXOQ8AEV6nmQ3apfIh70gqiw3bnSwOIpkrnGacbYVRSmLYUvI4iFDnM+rQ7nXCpUwoIfMY+bQpuLINaJOJ+f1ZqF8M1GajJy6tYVh3trYMniqEklUBAYd7yljJjKreB72cV7waHidzl/PcGeGo3hE+inGfwHOSI+nX8QHUu3otBC4ffaCu7tP2Ek4yR1WsufCcnvL2tZAzzhSH+49mUCm6xCPGm/WWELukZCXmsDd/T2t1Yj8Ek7zIMTSdkbsF44IDxjHCfJW8By2IsKz4CGLaofIHwK0gQ35qTtUSSIp+Q42FKOG7AknHZlkXNwb8/ps1Izh8vxdzPjsvDrLbP05EdpHNxorz2Nn3HGtpIN3IkjdEChWBrdi0/lh5iyPlzyejwEeYxkCED5TUzoDYn3JDqkiKhRxJIZOW1RYJjQHnwbtrQRHmTKD++qRjaIuSdea2dHjJxBnrA4kO0iZ2O9q9/fo7bNOYwQivRscjzcuS7Q6xqgPk2zf1cdijOM8ohvF+sR8PhdV6SmUBt3dtH9zyabFktWHniMbMtF1X8iMOZpyrfvU5kbadSTY0ya0d//9/rN94fve4PE5zy6b8Z63Y+7B6Mdn695d/vIqn+Yk5ZBepa/j1oa8Mkkxm5kyXH6bu5H7wWLsW8gv7nhbePbiBZ/4yPndT8m5NsOX7/goYaTedcaXwHsMeD+1/cf2iia/UgXau59Re8XyduH4t0N3UG80VIqvgaJoM+AVFkbC/JmjV/fvzzX5QXyJvIxpzYjdedlk1HjeD1MOc/m1v+e1wc3bt5x/XvlNL50CtvNzuTw9N7qP450m3b9azdyT6V8vC5eIHUvm8L6iz3E3hHF9rlFFOlpHbe6cPx3BOkJfvxZyuAadPJ0Dec1GTsB5KvYUaJ6nPIdt+nexzrfXi+a693uOxVE/rUL99BEDzjjNAYl0aCCRum0+I4i4/OJJLa/vxpGewH9/IVvB7y57kvE1D7zstPRXTPaOIGOWf69u888s5eLKH2vgF7fRtz4h+7uu3/9nRW4/xos7EiH2u999EazThanPNuh3veupPJX/m8qTAf2/tmyOULtrf+Tz5jjI72Flf1bJqAfYH/LYwiYzfDBh5iWRc641ahckm2u9QsIsqnGAal1pJ6od2rKfTyVg+VQ2SvvVGtqElYqtwvsCasaxCM38cH8w+E17CkfSFSCVihY9cLVJCO8GFMVqcwU4kc89FF7Ucex6Y8Iv6gfFVwb/UHgbdR1Q3mscf9WVrKW48VybUajRnmxFHrdiDr7XZH5lXb9n9f37rNjvUzJiGvKgMITp7Q5+fERdGdy+ODaPfe9IpV87Y3addMybVuAhqnuGea7WsrgxZQljKGlAF46HGw7Fo6VqbdS6zqcxN0YVf0WAN5LWB2/RfMzM8cxPU7saNBzKXUxCZSe0daWI70iZ/staBiSTE4j5O4TuMT0UqMLaahiO4gTZnWSclmhE/5XI3Twgup1uFTXWVmmtsmRUXZ+inIBUrMfnXEfzBIUmZm0GNEq2IA3XDB1aKmjG9TGy1xw0UslzeYDZlhHxGhG/YYjKKNzuuNQhPoWMHmo0Gg737fSz0ew+jF9HqMq5wmFZXFFQ4KBHtKykIUERdBFMWldiJWxl5j8Pk5pHiRoB/2luxGjNo6iDJ2goXgnUDzc4gZh2Y7aFosBw49U8aHPEreD8JqP2RBUtGWGllMX3TedXm3HNevcaqYTKt8vvvql8zWledn9fWSfie8ijvkuHIdYifRHleqitsiyRd17G88hEK20YjdNQRu6PmI/lcADzdW+tAq0rrDKausX6boHy0FrtjkvSld/RvoCH9v+jnyJIT7sCmHG8uWFdmxspeyi3j00qwzUUc74WRxygiSvzE8HisVGNFl4da7P8Z8/Xc12ycwxkLJPp4J21y74mu1TNW7/f+j29T3lH0EnLNDnSxuse4p4m2NHi86Sxi3rtbjY+XJFz51Q0F0s/6WNv0W4vbTu+McD3V8m27kkw7UbJPX+YiyU9dTQZa5GyoQnrp0+oFprWYQC+d0QQmd+vFpDmYQg+RYRtNDRAueNdW5VS7+IQOMb3N4LcbZVByVu3sohM/PByDdo0xnNF++hTCeNq0eI5OiVpvu9Hbf7ZsJ5XfF9LbWDaKLfP4cNHV8ZaGqpt24x4UFGqJKx8/uSNEXMs03vi7x7t+gA8g3Ir6JroMkELJJyDCOenkAcW9cj4QDB3w1qtWIOlrtS6BO33VDOtNk9jszZYoUnFcJ5gkconnQ7dASE6GJvZANFCQ2mRFsB8YDmvxlqNtdLRENRcka3GBFudsoxHnCY7EdxJYxGoPrGUWH5FBNT5uGV6Hgia4f+pGGvsHXfgk0nOmKbr5kg9nZCbo/e7NWogxiQyjRwP2P2p054+3cFW0r83ssQ4n+/MBKRekWqmhpyyXZPyMuvtiDGZPqvvwamOWTaSpFyjca07IF/y6RvMjdbx/ZyPfOc21I3ngsvyNwLduGgT8oW4lNMCHWTkM401MxlEvQ3js8WbjLu8e2r76PQlPOmQJ6+XwSsm6S94hIbx3CF+S67DnAemKK3+s+V9fvtwyk0RwcydPJooIm0yED8u7+yphUTd267M7tLhMMUY0+vylD36zaMN2d3s+g6bPjPxm2lk94xv35Lka1FVos202PvJE8zc/SP7a2w/z29NlnB9xXyfzzJ9c3V17sSCa3N5MRb992dm5tp4PrKGLuox62Nz7W3WP3tL06Gp2kDNOr87c/sCnr94wbtuQL/sk+BGvGv5i9+L65KutVpw4/dLA5NfaT//SPm787EaaGwmNZC4tvJDlmvQzy8NCq+pvN8Ywn+VCV1QttDuc5kNkDmPM8T7e4H/AQ5/O/DiZ7/2tZGkX70Pv6LUL9/Sy55KpggzMoAM2auodoe8vb50I4PJoH8wgjymO77crq8ct8vnhrzezyX5E3IFuHoE0gln2pNDCEMF6hU++Z9SNOjEjAj4n1KEb1vHT2Vbvsl4HufH1JnMz39OinoqT+WpbMuTAf0vKsYj0uRXlt/t6ZRaiiSU15RRv/dzHqo39zwmMv++0iFMv+WZVCtMwtI4bMk4+QDYZCzKW0082HxSjNCMauKeszS0VdbqOcndU7NR8QhD08IFOJDpyF0auSqzTU3gF2kUOyNNeYVxboWfF1dOvBLhFcqHOd9bKsolj/10Y0zPHpneyR5ChCyF0jxf3i+l8cqghI72jQjvgVd5AKPwUYvD44bxRBVoCyoLKitFCmeUsq5UraytIuZGJgyquLoNm5ZJV1DkeFs3EHUl/Rw9/6jyIY6Cu6/rtF7yQHv9SXq7al77t/ay2x/ftyWPxPeRy+lYwsezhVFHZRjLxBUWil7A3865djQguvaDOGiRxOHEeDaTF2CJxz5KKkZScBttzWeHA6QbDVGPVuuaKQSJEJobVU4YSz1zsyyIKOv5jASygsVePdcHlsOBw+GGoo1TQnd7bdwejnEQnOCbJdXCnn8z+9iN36nUTqVRzkq4Q4sEhLuU7r29aAlHhKGgm5WnaZjIax26cXMqMk91GWOoKridUDrMOBVMI6czcHM4emRuwL03q1RrLIeFdT1zVI+I/nR/PyZOhCEitMn43W8Iwyxh9zmz1kmZNY1Zj6KLw23ur16b2Wf29leUMtZy01QHVR82EW6Ak2SE/YBNPSssvkhoofxxdjGQGvgEYgVeAitueEUQLRwPvq9KWZASCn3BDQ73Aj8oy1L6mjYpParCKpxl9ahh5hQCnm+dQkRHSrIcrIbBvyYEb/Oo9zAAOKy4OzG1dIoYrIzwwnAjixil5671+aDVmHrpmsAB+Wu02sIZbFKT2VZpOC4aFyrPrrmYDKsYpA9aKD26wYbc8jbtu6Q5GaUEtZojoawrxeD2eIhcwSUcAwZtkjB+J2QrkvoW6/LFnCd85Of1d6bs1sygFI/nEMJpxtdOdjOjxJNEpKNcRvq3VkcYg5kz1Vwr4SxBd3rydUNt6FLQ1cgQECeTgkQaCVGBE7RSvZ7V4bNP5zPWAiIaZUST2NS/MY8J7DwbihAbiDqS8z7xI5uikyziVt37A7XYUxj0KFVhEdzoFW1POpj0y6Naa0T0ucGD1ev1ITcsaBRqtAeb+jQVY4cRLL0NUy6f3TO5Q/IduTHyl22qmyWNbgAOetpNSo8II8YDYjdhWxSMU4ioxzCkPoSRTTsHAfF0CuIoSN1ZR+hGVM//uPg+E8HujSpOH5umzBWOOK0FqgXhpTYM3C2kSbUjdjTs4cREQcjI82CAAOjtLXZ/j9kxdw/D3On3tPvYJyU47q2vm1qdH5Vy60/muFhGkk7SeojmorizmEoYpXMtNton6w5JaESzRT75GdI956bnzDw5uszh9hn89jEQfuqGhmXfrOVacXqlWrDIBZ5rLVMriQwDtWjOKdjpTJOGlAPG2cl23KeiSLkNZxEnXqfV565Wc5qSNMOgVePUzlF37Yx5KQtaFbkx0MgnikCrnsJmUbRa5DcPB6TYlxUokabqIMo56GGN3wnhvrakL7A0dx9obaKpFntElKKMVW1Gq6tLpaLooiyiLEvAyRuc4sxUErkjYPlphrZE3TDk0DAN3i/uMFKtUc9+NmmnE/VwwKyx3p+omOew7jzAeVKmb8+ULN4Hn8NzrsJIzRHZwOLSyNk7DA8Sa9dlwVU1jNK+9J6pUG6VIgeKFkpZ0CXg8pO+06if7hAT938W8PRiK2aV1UJWELjHfJ+3kCMk1sjkf3WSNJRbp6snY7Mn7hlR6b5xhVtJ302hcUcTWDDkxQ+0D8N5wbntLXDPx04vIDEZbgRM77nv5HSmw8kjA0lnxrAPR5khh1qXE3KDOs00DrHnWtAFFQ2WqyxIyNKJyhOyS9B4R/RoQ9ZRCSc8n/dq5ggMrXl+Xg05QepwVmvm/vZ421RD+Eh5sw3HnHJ7S7WGNqVK83zQGvw9aJgWkFpZz3XQLZt+z3x5V5w8CHVtPYXD1vhlXf7ztTXpXizrkGld51PSL8w56QeXYNocsXUtFog5bUfc9TB1FzmVm8/9r8GDL3u5733cb9v7J1+Qy88u0oQvm7isMe3v7P88NlnPQKFKTi3TWIUzUTyzman8nOLJFOo6O8G7g2SkY4t2zMiDzergj4SjeLQuAymiIfMv76MZx+OR498XHh7O1Hqi8Qrjt94HkZcu01jj8OOB9Z2j0bxs72h4oAfA6wbv+lkWlyGBn+R90HvPyvyyAazICvWXRnmrLCKOvIBwDmQHRzrzOt5PItaYYSj2I2AUXvNDfcd7gV+Dj83q0w/ixn3Juq6Ua7nRXzd4+MUt50dzQ/2L6ft5Lcru86fUq6hMTkyfKzL9O8rz4w0GHFtFbbjKlohAF3H6VFsd+j+gmUZkf9bov53mWeQw902pQTNtpk+hOalxvnlYz5t27Ul435+PbNCZfmzm8gt67jWQFt05PB5PJzuEUxurorMxyXP1WAd39Rw05vN0ZMi5Xucf0ll8RXmcel+WpEmX0edX6s2t+Oc2/6vKS4NfYg+O8i09/yPlSwPlv/b7ZP/YtdZ+Mf0UdBlTJeVBrq6pTOu4N3gT18b7d1QnzksSe1imz113uWlzVvT5cf+z1/1TeSr/CeXJgP4XFNtLF99Yvg9MSErA/Z+pPX/gc7r49e+nz5sD3R9o+TcT7zjy9pyt/QgM02FvnFZyWELITbjsyLfjet8R3eSHXJAVVFtX/psRBvQIF58EwzxPJ0RnywOxzIc3Q1rjZxrPrPB3O/CregamH4eVMcajYVVBrDNU99z1+9o0bmn8MQxTYzGlWeMj8L9WWEP59APGO4y/NUEOC69RPoZRQnVEjKgWlrKwykKhcNYz5/MZaSvSpEfFwMoaYz+f82cvf8hop6EA3yz3+Qw2z/AjeyqNfldX3TzX8TmVZHbt+/+wMo9R/71b/tMuIJWBqexJRAOvq025Lvf7bwh1uSZyESdEY77jFuNhgj3c15XHxDQsj89srmW7VRzO08RzYh2Xmzgge173amuHHVvXyjHygToUch1vE2VdT1HxlHMw4AY7mZTRniFL6+h7M2jusa1F3NilBRCKDiF59De9QWWQIhmfZbqzK7NIumFhnHdoSYBWfe6WUlBTFjmgBVfiqnJYvC0LSsXhIDXqresaRoSYy4zai4N05jYd60MdxtrxhKm1go2o/TF/Y6wsrmfp9NAsYKu35UuUvo+HCFJc4ZlRVzlHIhIICBn9VoMiCC1odQ1kDtLg3C3pK8YNBYHmkXsLDdUDpYA0z6uumkptcxouwvLD4mgIh+iy3AOF1hprQMuvrbEISPGowljiSIkcs7OTVEAJt+YKjhrjtZTFDU+1sq5uPK9rdWVZP2fp5gDWxy7prEQE1Y632pigbpDfagt3skDncTZfYvcBQpFlGRnAZlkMUWI64vm6TIeCYfQj/zbw1ChDSaZTDuBhBg+ocx3pVLx//p42RfPPPBPoqV4qvl6HwmXar1LAcqy2axxwh7DgcWIZJSGkk0AO6yw9CURktTv46FIoSrwnp2HkbwdBDwu0NXK252HaZQTF03XUVn285jeZOVKHNXd/CHrq28PzyIuFE8jm6L6jbMFEu+MhNtmibaOsx4QFWBG645IYIkarCQUexo1SsLNFOGvrBruxBnLQ/b05Q2azumCamBzwvJ5jsft+GEunZiev2sjCO/lyqtfXtPNQd7Z4wN15OkcDOSPcuLwqOY4+Lp1jyIY5xPSbj93NER7SYJr0nICA3o5LteoemzFulorWNpxJ3OhIj05z5fUJ7pd474LJ2em9HUAcuFoF5PZZVxIZD329eE2RPiHmn+gdnbykADb1d5Zduow4xsAVqRoIFGXKkZkOUT6vKsXl+quizA3pZSFoOJ6FYVQXyosfkN8+BK0MRb5N6w8c6SBSg/QoXAt6bOdo7E3QeKUsvk9zGs3CMUbOMYcj3Ybogt6UDrXamgX/cuN5W135nUgcvjc6FhVL8XFZyoKEMU/UldFr8+htEcN9fLyPPbo9BeNUyqkGypX30gLZoDWhtUTXEqQZJwvjedtK5DnzZu4QsCjYurKu1R28lnBECGOlppNjOL2ttblEab6q3UmvRm53wZpSpHUe2CSWvIAchfUBeDi5ARSb/oOavGS6Nn9/wrqLGG3AvCedtUzoHsZs+vhpJzGxrTkjHMKZQ8NpQWIzGLVn+BAcYWRmwU5jXXavtYbhLOBqJ35tGEczHsy4q5N80N+TfYz7g68kJbvtr4wrJWlEpsBJPgHtU+0oO2LPvL9iwA1H7niwQfkmht/fMWDcp02aOcclrwcSTsoKkvIM3ckB4BBy7PH2GSLGaV07MpOPnCO2LRQOS6HoghbtfMpq4xxGpZ7xJ2TlQymsjS47abZMfNVoOrWqr1ltAa8syf8bVpMGuywix9sOs++Ot2OnmFgg3QVtN1hlkp1nOeozxefJ5boU9PbkcD8F+++txRrpcszguPuTjrOxwRddppFBMwOxo4kbf13mSE5gIfXNn+nv7O0Z4hPg+3y8Xcb9G9J/ve+bz22wnsvnx/1bKcCuqZY6CTCGwXpf3yx3GuPGIcNGs6Kylo7v1psLNpCLLPZD283zXm+SZyBwmtLrtxXVA9V+7nf7FhzIYQ+/nFneLH7tnbch7ZcVN5RlJPqv8dRLPBp8EgvJ9FfNDPupoX+XHgltZqw/j3QI6zyGU0/e2hs6b6bxLnn9I3tDPvPdY+W9Dih4/VFpv2y/n6PRMyf6p298x5dKOvb0vdDnd79hwzF1OtvsjWdxMdJr+IDk+XOWtVzO8p+2H/zvUWZx+msfSVpI0pQ7T2ASje1+zLIjEHnu/S4N/2uLWhfl/6NKOqdcQ5H4Ty17Xcs7quFmAAAgAElEQVTXlOGov73Wg5gmuhzfstnFEvxiZkKT8Vx70NSk49vzz92Z6qk8lafyeHkyoD8VvnB0+MbPKYna7vP++7+o2LV3769d/xxZBOMgKF2hmAe7QkYnZARVMsWdalkCNjMPNoCUULLE8CRyZyo2XtTGP9rK36qAGqsaL6zwcRGKsYFAHKdd620lFIldV09okDSYdIQA/jOULi9X+BD3v1fj0KorRNfIz1hKPwZbDowQ+RkLpbiy3BS0ViQUeJpQizaN8jTcvfnDchNj/uU1Y1HX5/j//qt9re/1L12d31C2yokvFYlIxRSYzq1yWEo3tiTM9KjP638R8/RBfJ08iyjLT4+I6a6MCg/YuOUeX88PCre5vvtbpgkTCcjP0b9uUoqF64ckJbOnPphxi3saHxd3BFH8oLhmNWaIKtYq6/nMUg4syxHWldZWBHg4nXqEfRruLoY5ejgfPLsBvI+z9LzKWY0bMqPtKptKU3HUD6X92fQsHe/KcekqqBCKe45XJGDjhaUs3ByPHA5HWquU4jC2CWEPbkQAo+jiyoli3Bxv+ngnxPdopyvo+6E92ifqkJ1pvM/vU0HXja5Xluw4Ckg/zLK7bXPlyrIblGKrNJgDSp8HUd1E0mKZiXGn3BpjnL9XPmEfn9MU2nM4HMKLvxWOFKqdaVW6wcbMkAewEkZwFegGlGGuPIiwdoV/c1jaJgHNHrBsDONlNXfYst0aEpuUdTGqM6woMh+8hlHRc3PWWE/pBBD37g5XeeCao6J7ZNY8Y8Oi20d2C/QZjG9SOXaF/Fzmg2A+aaEk78pa6bOZ+9ZMxh6Ofic/zv55FJENhVPw6jSezwYxGYx1o+jLqPy5rZaGkigtcuf68t/KPtYaomWsyU4Hd/eNLo5Rjv2phwUM1tVVibr4Z2uuqC9lYT2vblifpiedVUopU/S2hKFRWCNyCQKwJu7Jro7cxS7dzDM3qHPvQR+fRBJpBmrS4T7PFnM5OU15YzNaexikxLyCTRRryzmJKdWsL9pffeYysrI3KeY2HTl6i2N9btd2j6OZbn1MFj7lTE3XwiTmG3Z6ZgqJ74zjFCwvBZK8Z85EPYw17hYVdOLhRHpi9ogzU9ZaKbcy6uXgkQ9UzqvF2lCaVDdAm3rE3/CA9Lfkvpc1hu80KXEfukxRzeDOY1Ut+9FlO+l9TUcLoOcEtpMgN4pI8TVmw4i3pSib4R2/c/nQqM0jmQFHT79Xx209gRvL16jGsHbErGJWQmEPmGLtzFor7f5EqxW1BQ7K+nDv6zAMQU5HI3WSJE/L6+mkRNCi1VEzRD3nePUVMu8vCWOdRWSm5YHBcddpLHgEC92JRJgMJ12+CyN0yOcW+U0PNwen6wscz8apVdbqMO/n8+oRfxglnFlMKs18NFW1O1XOjoAimcQl323jnCM5c05bl9jva98AHsVuKE0Lx+KRwC4XhVNy7KSwYY40WJg74ISMZbjRXHEDTPL6u7tP1HPDilDPicJARM9HdLs4bZIW/Cb/s6TTPlMlaUciOwh9PIzm9FXdefNgQi0hT9kEkZ8yY/Ir9aeLHHtaGYlc82K+XtaHhy4vDmkCh9RvK60ZD2SEa+UGb/cnrGezuEF4sMGDc+vst1NusZw/iLRJ0/cPwE2MGcAqgjBowSpOBx6SD0q6qWzp5wt5hoP+fOr7JOX+sbH9GY25FtzxfNhGJMbfI7yf3z7n5nDEDI7HA61VXv3wys8xd59csWygNA7lGA62vu5yT1XxvLi1mUdrh6NAPa9YNWpdI4+3N6SFY1dRpSmUoqgpZr7n0/kxUQxQDeSKrROppuI7Ud8iDVWunx5JFp5IlpbeibZuJZdRZlo6X+Pizt1CiBudzkwy0hCW6A6HXRZsG/6eNMGXX06c9fUy6GbUaUNmld1n/zedMGcmQJfv+uLoHbscj99VdnJAH7+dscOmdtrlY49XnxZo2X6+qH/+LC7/pQMegjuL21xR8JnpuS5PxVw2M2x1hBkD6ru73lz//RLDc38rb3o9RZVVXiH82sX8jOzOKFMjINbFfyekeuENh7fuUXTzPwfAHbvazw3ewvpzRkZ7/vPfJAzyM7Eiqb/ReH/dMLcjcu+DOWT+8xny/XPRvJlGsf3iSB9pNH9h/vNJ4LkNw/kLc31dDcedxwzqsvsrl286yuc+aK1F4MCB4TjqSEFmHlE+P19Cv1Bbw5pQGWn5XJfnK1SHV5K/zdyhe60eaZ65wNulpL/7nOv1sRHcPXlx33ai8pMStFGERYZjjIVsenz5kvrhA4elsNbKoWjA0w/+C3A6nzbte6yZ+/bPOqp/RfkcXZ4jt/8Mf4Y/s/zPmzecfnnHzdu3mFX+8e79X90kL8mS9vxErt729Ssh5Z/gPyrbdb0vGXl+WY/XUvQzxKk3UrhWxVN5Kk/lj5UnA/pT+RPKpRg1yl9JybcGqfn6l8pgeXSlbxftQmdTsQ5B6M/sjOcyrrtyb1u3iIwDU3xh+CH4F2u8Pa88qHLIOjVhWGVUkhX29ydkn3kjNQ1z2tUR+bhDDQqtNlSN1zUOFuZ5U00NaUomOfb8cakPdeG0qCuMKJChN+e2gqxoeJiPjKyPDHQ/CFxX7Fwt83n5O5yNfzB3IPjPKPPkP3bH9h4BTueVw+IsIHUffpBum6U0e1JL8yhH2vWMRXkgzEeeGV15ehtzcosrKLsyeXpmdkrpouukmMFIW8poYBr9zg+05ciyHHw/Nof0tDjUWyhHW6s9ujqVySUU9aWUrgi79MQcrXosZ5DTgoDDzxyleZex3d/TM1lXRs912KXp3RfGZRk5SlOZDaXXA8rt4YZTDSWIueFsKUso8Lz2hERVKRyWw1DWZf5TpHu3N6sRiTy1XdzzubaEtzTMHD7ec4lG9ADX3GByPK9/y+7qldHz63v92PScQ0H6QpuSQXTa2se3P30D8oBx0+dXuaHxCewZ9mmlSWP5odCsAgulNJbixgxRoX6ssU9cJVqCaMb53XlIEF+zgIxVDTtV7ZFfbcrZ7jlaQ7HFNJ6phMUuTvp9nW74w9hPjjxwpkeoB1/ocOReyVDS4vtR8tkegpT1XkzQmKfetmkvy/h+s5eCp8z3p/JDok35dWsFiQhD7Tn8dvsy2pvEqJOTsLha/k0208dTeg7qYap3p4S5Zvp8EWOYBnqP+hi8OJlu1N7f7Xusd27s9eRlwWi9Hzsiqw6V2mx2J6Av7qKFoaRPoyA087ySFaeTzRpqQm1GQXpKgUGHZET12XAgvCbd2f7zbmkMqjibf3IArM91k3BPFHGHn5SbxMdh75w4JLN0mojBnq9tpLnpSRtXUwzZ1izTs9s3XpZ9b7PR8Wd77N7t/TIZ2nMOsgVpPE8IwJmCDkW7G1QqFao75nT6zhlTukHC97kzWIlw16QbgoRTAiGXurFsydHKyM8Yke40FW3UyFvtPitzT7JzE32Y6I0bXbIvYxENx6xRxbXvnd83JOBLRQS5MaQJemtwBpFbMmre+VajrnUyOhTMlFpPWCJ/HDT4mw103XTU6fw30FDMoEWkbO6aHanza7k6rUefjj1vPR2J85McQevjOQ15N+omIpUGSo6qulFXHJp+WTzFRZGCHRtaG2s5OJ+3T5zrOlporae2MIh0DEG9JFF6JmfBpJtiY6/a4EkzlegpQ0gHE1f2qy6RikP7oPk8O/j5PJYyrSgViTzpbrrTSD7ghlKHjsmULU3okYzN/BznS8viTDd2/tZ1jT5fabDFJKKafYdKGDRFhNr7OVA50uFSZ/QZUUe8qRVtUG4XpKQM63XZZBgZlEypNsfQQ3KeS5e7NF5vqdc9cLiQpcZnle31B6QjTJ0wjjMXn0isXBm7PdnzvifBkSQrMU7TTV2OG46n6eY5UxYVd2pfAo5dw5nxcLhFxfnbclg4FJf9xYxFF7836I+KO7ubKVWMfnoND5UWZ3ZHvklZINs1UEvc6bcGmRsG/pSrc01vxsMGR9xMAtMQ9QNvLgTp9Dr3hqRhdKzSTVXXeOHllV2xR77vLHfmk2MldicvRnct745H8r6ZXcr0z0bemM6FXYbYiEezfJYrZm7WJT//cplH5/OywJ57d5a1H+BHmzD4lt93ZdPMb8s1l+PQ+apM75gkhW7AmeQkC7r5S5pHW8DJeL1DhPlAjmiOfT9ryXAIAnhtIPYqdq6BvOc3gTe74V9+HHQwGB8I6NtAOhOwMJ4b8CrHbqrj5bSO/syo1le51mNOi73iBb8iDKN7BiBkkem34fqRu29oYw6X8/pwgitlrP8NnUwZaMjT6XgDuB6lDQ3FhaFu97mFLDlJeV/f8O9cku8SFNkdqGIhhNyX8vFSSjf4w0QFJ/n0P7W8aa8cTYxfOtrGl+Db/52KiHDz9m+AIfLfYY7qvOxqMN9nnpv2o+0+f+vzT+WpPJU/Xv47KNZTeSrfoXwO2iQj/WaPsaGQv/7ciLYdB8p+KLZJWMaF119apVjjb035sHj0xttq3Ak9N+WIRB/KOD+khyEsNXNqG6FZwgjTxCNIflX3301hdHjKN1pT0IRNDEVAzXNaRjEK0hwYT4pHnmOCNVcuVmnbzrMVZLuntl2eGa9PwFfc8xWP5avmCOq/olwcz3cXhse5Xr9/V2prLJr5vd2o0o2J/eER0TCf8tOD+taMj+LpCp7FQSXPrh8feXGRVDyO8gA8j/Z/Yq/WGWUogVzxu2jhvK601rgRRVpzxTwuHD4YyHpCVDmUhSJKuVk8b7StXdnUzFhwBa1DXoNZpag7D3Rje2xCkWls4l3DkD5a6yZrN0Gq5M/IO9SHe/L6T4O5qjIiykt/ZhM1PNGTVPCJOMSsyMhVJkhA2AbSReTHXusaCvQloNmSTikLUKVRm8OHas/NOqC/zcyNKhFjuoF1M2MpjmjgxvJGrU4La3VD3Wx4z/7nbzNDdQuf7W3rf23Ge0NSd3viYk9Pz2S+Rcn39veMCEt4iLqG4s/kASGMjCgrH6kfhEVeIC99fKo4dGp7b9y8Pjqs/V31g5LdR0N00+aH7Eg1h5xVw9RQc8h90bLhJw7BJ0PhlQoN20FiR8c7UsC8luY11VVp8WxzftH5xGjqNCd/oupkpwzruuGZCUwGchFxtBMb+6eUWLt9focCcRi/U9EYfCZgqzeGwDjkzsOaikKxzEmWvHtrhKcr1vKe2cgSirducNspSeNF63oe82aOotF8A3pfoUcYl8PiCDitQXNHGY+gbbG/IkrvcKBVA1mRNp5HfM/X1cDCGUGMh/W8cyyYpqCPx/idcNWpr8pY1PwZjk/WDVU51E5jw7i0xki79x/aJBxHvJLubDBSem6K1UnNl2tIbUSuJySqzfTGRmR9b/HUbzNaRoLLuHa1XBFaso8p1MzG/7EjvbEm2zr66xhyYV4XPJLMFateqwREdCoOBWFlRe98jMui2NIotvi36tbytg4jlKhRmtOanvRC3LnGsAma3CipXLWQRaObJPpKydzVNtAy+o/1vljsqeXZTcAkRx92qBsS+2tA4Pp3zRrShIJgGobbFHpCwC4UUMPuDJYHkEqny+2Btq7UtrKuK9ZuyJlqzSPRW2u0+7ue53taKmNiItJYMpVDlxkGHPxM54xRR9L27mAVxu+UXQTDUdoztYGv6RYJrnMNNDM39ocsIogjVYhwKIvnVD4cKCKUxZXwh2acq0ftnwNGvVmDGjnFM3VViIlplM+9WFSpEkZ6MzCX9a21kUM4x6SvV+IsQudGKiBaaEHLTT3f+opENqygo3HuUUpE6vt3q5ijXYnSKh3IYT1XCJlvxTDVyONqPSdwOivQnFc0hKU2TkGDwfqcYm6AV4kJizldlsXbsZ49AtkUC4j1vhZEPKJ4Mp6XIj0tjxK8Kg3Aqqz3JxDl2QvPtrtW70t7cLp0MkOs8ZD9MKdop5QPnEj08b9BJqh0X30THkY3jmfcYyerIv2+jGjPdZf7oDU48JzyQjl9+sDDjrdneqfcAAI08Vp/4DnyAuqnO04TxRsiTFJKp3M608r4U+N8+3B64LSeKaIsy0JZlh5hfjwcWIqjwFir/RnJ/asgzf+wxSIFmfMNR8CPzS8yHHnx/SRG0BALehWpoQR3gLCKgiN1JIx6nL/C/uUfY29InAEa1rGT0+GZaVys74/ZqSmH2aa/53KdX82wzZfPTPXmtEvuy91bYr46vxXdPC/9hf7bpkq6HDcTyf7eLWLY7FQ13zmcAPeE+nO9utLPx658qYr991sR81Ed0RA9Yh6+oFvan58Ip2ZJg2rbyqmqelW+c69Mp4vyutDevxvt3UggxJUW5yOhvbM4I8Kb+jo66tdu/+fAp3/+g9cGhzdvOb/7md+IaHRec/7lZ4TXwStXQCg/6pTKatvfvYH8tb0io+Lz97eUfa7zy13hwRWONgmLvfYc8f/0lDmLi6v87c1b1p8d7r7wBuV9FxNqkIpr0ee5So9LnqVtc72F444GnUjHycR8WorGmbuxBh/LtW9BZA3rjvGHpQR6xtjvBhvI/2bGWuOcEY5bX4o879ftS3fsvn10/Hf7Ns615wjk0LAe3wALzwEoz15w/vSRmoQ0ZKeihXPkbK9faURPZJ99A8eq/Hoa8r3KS4NVfqWEDLJfu19TrupT/kXlpQEh2/5/P//0yF1f4jy/t3x5sJLnXrv9W4da5j8m9JTHkFVbaxffzHDuqnr5UL5Cpj9C1nwynj+Vp/L9y5MB/ak8la8ss8FoPrjM1/aRq/MzMA5A2ICEByJiLaNuxhElfzvkkjPcfxblIKlwUH6o8EHVI7/nd4dYbaloEjYG9vSw9/d4TlNFMBla6WGU8mjSVyZ8LNVz+zmO41CGEko/FcQU1cj/VgN2jhYe/VtlWY5HvqeP1zfKTH+WqPV/Q+nrMrXSMA4Eky7XDZ11c1wxRvT4sziLUIofzq19dsBdJzTHBsFNNyAMBd397rlNpIAQUGUTzHxLxak/f9cdV4TT6R453iIiLAhaBLWFJpG1N5QJKm5MrhFl1cIwbQYa+KD7iPEOWz4Lqf26t9sN6A4dOkeT+3gMITidFdJ4nkq90qPjLw3os0LLldceVaMRQawRgS7qytmixWmHKGLNHSdUmdJjYziqhLWAiLswoOswiCA0aZH7MCKns5aiHEQcYtwaMxxlGtE3xskcNyEMHa0fDC4Uf7s1JrtoHdv93tcRTd/eN5GZ1O1uax0AoyO68R6z2+kA1Dj/tsJLYf2tUV4AJpzWs6c8Vyi2ugFzPvRM0FuZg9JUez56h4ZtiLa+5kaTI2ZHxjo0m3jNzIdkPOdjcKkGsM0A22Ycrjl+bD7/gZP3XPdXHfDmtgfvUpWw0UV22IxSF9n89NmNA6yE441Df48IsA4vzBjT6G2O+lYxm9/Oh+3+xPhLcvHJ/FAoxWfG5VqsybA7OU3UOhFqoElEbUmkqAgaGMnw8uAsKqhpwLNHe0SgI03QnVtEC4u4o0iODVyZZuNiLMB3/N4x0BiGzrK7v9uTUwoR2awFVQ0jZebvHn3wsYw32Ii2udZWhK48Hgr6Mc+b27+LNmmn8BuVx7fX6deVJzZXZZKa9m/oqsBp3VrSkVh/FuNouiJnQZag7ashc0SEgKBuaG7mBvB4t0fM5txFtHQMpGfx0NFDnXgVGkZtC9khZN1LwjvRPJ/fYWidOn3luWFM9neI5loOI5Zop43yTJBVom1e82pHmp1cAb2ucPQ873afRvQCTWk89Hyx27nL3MThUFv3SUK8DWzoXXRGxkz2fZEDTc6pY7rXGrI0AmHIT/jVjqphjVrDoVWkp2uitoC+DiNjKZRl6dupVOPcFpaHB+fZDdDqxvmcVzNac9rh62NQv270Y3LQ2shN0sdtPg8h9ChUz18/ZJAFoamiDT+fNIJ4J282OmRx1NtUI3BSIse0rzXDkS08zDKgtFFEmyM0IEibXGma33/E3CjR1/405xNcctKXQYvSCQrScCghdBfRuNZ8LKWgpfh1HAFFqQiFjFbP/eSkPhy8bhR7cH6fTi1coYUzbbuZv3hkP40duP9KNhDsN1wpMt6n3PKMBxIEOuudjfUq7pjb1yVCE6VHM/d1NQXExnWd1xGDTpSiXTYeBvMR0b8sCyoFxVjPEvRVnBbmXCp0DKGovzVBqTh6kAXs/uBuNgQI3wOGO7LnGvEVRw0DsKm4d4KIO41tZmD7Memu55enG3dmfnCB23TFUjIkncfLlSXx2bKh0V/4zqZ/OooebBHHyDU0SVdXWOoXxUfb8Vi5vqo3bZte9bslgi89mPqYffuHR8L1arvSRdhu8m3LbffvhWhk2995X3ufZ7dfsfevkMhWPnbvWBuDdLynvn+NoBzeFrC/8fCTJ+cQc/3Pp3/+oz8rwkhZOLVzL0dr8Cp3oBzR53NfXhkor2j8yq8Cr+wR6PZvLPvxSrhstTcoxvK2hAz/K9grhFeRRs1h7fsY5VTF58cCDrK0R6Zf8TQjOe0tHFbyvll2XsLR0b8Yndm/WrVgdeh8nHflrtyePFuzC+P5X1FEZOcwHnw5vGXXD5Xlh0IltBAx/tpTIn2bnN/36Pc4GnynUuw1Ju8x+X3G87+6/CbwDDj/dH6cafxFpZ8RvlO7culk2qEvLb3fvdTmBqe8MX3uznhPBvWn8lT+cHkyoD+Vp/IV5ZrBfP99Rp8/5iW8N64numMeJroyzgSjTRBnbkBvhsP8mvHKhKXBzyK8NeOZCB8mZYHXJ6EwMixyF7vWpXhkjM4RPLgiLj3hQ4gW8ejxEjnPP3rLMfGIlx9Wc+HNMh9awgw3Kg756Ma80hVwYnY9IjXakQq6/Yl7c5h9TLr4gwLu/uD8V5eL9uwupKHF805etjpvP0d+6hfHErkeZ4W0G4p1USxgfdfIRZoHvWfTdJgZ93VFRLmN68/jRXs4so/i+RJF3HjyYTosT6oxnonwIKGM9A65wJfroHfIuhLqjogbi4NRRsDciHJez9wen3XF5eFwg6pwXldKKdRWfa/E6aqGIvV4vKWu56ivjlzLaYxLJfDGODcUe9L/luv3jJOuj0nxaBjREUkuKqFYvRR202aZkGWbCPZwJ/Dm+WeHo1eE6pE3GnniRXtOMxPjsBwo1tw4ohLePX2yxoEiGtEj3sxhSpuZG0tEKCirORx+V4oIHdLdT/zzKhESujMN4xlJMw4yWweCa0eM/VIZ122jzDXonvu9BTJHK4OkApytksjbbkGrJZQJQvtwRrSgpsgtnH47UfTkiqOmnoO6GVp8/d6n8YGM9jZojSpGiUjgpoKa9UP/Zi3l2ciIKJOpvbl3st0yrdkck/hXkTFPk4F6E/U+jXvS5sHTLsd6dhKZvplG8jNFmKjCtO/ScIBHUmsZxvJSeqvDIFy684kPkV0qZaujJBhjXc3GcxhK6cHHW98Tmyj8WZPY7x8q7JYH5v2SDUvzcHbwzy0ck1TGg5bqrKBnfbXGIqjnc6+2tYaWEgaucDEyh63OCKV99Ls7EWkfU7+HoNHbuYdJwTd1J7s2q9e6K16OoYyuCxlJQzduSxt0UiRsfTg6xjwfLej2WPdnMuulcbjUUCS+YZA0z5s8dYTTNK/XHSXBdp8/U7rsNtOY6esr9fQ5MW/oVR2HMQe6jldF7nonTYYtgrXmue4nWqdm4WDh/TzjvC4VhB5NLIHaEnmjzRsvAYltAsdYJwkn7hDnjWPx9Vdbi+jzxRurJapRsEaLiKZUAIMht+HQKdDsHI5oB//Mhh1doG1oWNRUM41Djve0UCVzTg9UlfL8Ocvh4Ok2AFkrdn6Bnc9wPlLv7sAqUgIlpdxg1rBVEGk0O8VYxvqMlBYeYepjlUuPGOex1zu37us1c2GLiD8XfKkFwgyoG+wiX3DON3jKFM996++1Zpyb04XM69yqIUcBXdGqrG3lUPHIbvGf4CaUZeF4c0trlbWupOOhOwcwogLF+2GE82UmYI96tnQv+pvh4rHe05kwjdCqhWVZdrzLzx1MjhfdoGkW9CSit2UgE4FQo419YdTaZck+b5nKR6s7SZhh5jl3PeVKnt+SBvs1SXpsEXlp4fBsEbHeDJHibYcu12l8h7h8SspXMfcpH/ehM9Cjj0mNdBun+wcfwog0PzSPlE9a1R1KItXAjRn3SeNiXm7iHQ+xz2FrEJfpj5QQLgyvEmQiU0fEpFfusE8Os/uAcRv9KI5hxScdiB4icIqX3WLY3b2TjmkekyamG4ImIjTzGlJKrKXMMV9KoWjh5nj0cdfJSUMcGU1spVqlmaDpuNgRpPyty6LjfNRwNJdJtkj+HCScZVloZpzP5yRzPnrN5WchkVWETWdyys3X3pL9zpRK5nTWZbctn0k5wtlbi/GKye4yss3NnlfZ9qP06r6uTH0fsjRdPsrtI/MLxsDQpb+NYmCWy0bbxrlqesEsiI03bDsU/ek26MfK1LRBw7b1fH1Jo+RUQ8h315B8577adHV2qA7BKfrTZ3VfwxiRmO9NN2b+eGU8hNeUN4X6SwXx6O7EUPFdPkbXH30PvOH08zrONYanQZgiwitwG454QBi9f6XwivJWqT8PKVJVqbVe6IqEyJ8usPAGw43obwzeybdFn7+MuveGyMVeQdSV94jBWd4hwMJb1to4/vjW6fJPdchab4XzL+96fz/NPHNXNDbasSw9TQoiHX5cUjaVCArYRaAeDwdAaJFiJldDH688T2OsrXEIR/m1hoNDpMVb43xukjqICDQQn4+zhcPZF7bB/nz4GP14bPvJo9/N/MXva5bSl3/b+IhQON+VLjcIHm1+bmeo2c/Hy7692z1zvb1fuOW7l1XePzpOr+01lfdfDed+9azxJ5QfzHWAr8yPIf9499NIDfXZ8nUN/F7j3+WJL7Tia943PyMSjuxyrbaZjj9WmQQK0teXvQ7xWvk+TuNP5an8d5UnA/pTeSrfUD7HaD4XnT4MUIORTfoKIlUeQ8cSSqKsqqWi2y1pwJgAACAASURBVDXKv0jlLcZ5FX4q8AbhuSkfQkFY1KOHEr/UsIjIUTe4RMQaU5tccI8zmeFKuoYb6DpUuGXH+AF4h/GyCb/FtRT+26TA6TCPKIUwdFYbB8jLkex/jRyc1769Xr7l3v+e4gM5ox54mTzgrxq+tuVOmA5Fwwjvh9dH3hy6kQ+7G3YxZdsSQp9lBXkxSkauuJI/4MvVc1I/tIYKnNYHluWwUWp5jvMwIItQozOOkOCOHZSFRqOUBYmcqI8Zz2UaP2GYsEe01TTKk/Ezo86XUhzGMxTcw/BON4rPaIcWWuOMYOrR5xpvD21MHsj39CojATUM9ha50o/HBWtG0dqV732OzH+LXN+rBoO2hbIrHWRU3bGjNQFap4P7msxsByeY3r9pYOTi/s3anTVN1xRStqUFswFUhI7MsV1vvYubP4w7RJ5BRM2bGqstlGZYW1g/Bu206nlipWGU/hsRmobSNkYwjQ5JE0V9njCPNNLUcOiA8+1t722OOnZK2FyzOh/aLKEd82cHqSmpaJwM861tPoM7cnwOTuyrytBQP/p9Hmh9rQ+eNNMiyH0zOaoQsIdqHrwphNl82z86v4K8I7WsqaSJB/wXYzXk0tuBIkTbcQNKb2Py/QmTI43SrUW0ef+i60j7bpyh9dWd2zos57zCzYYxNSOQGfvOWqOF01CQflpbOSxHcmelS0G2eWrVUBJmf7Kr0z2zcmfabd7X/smNQfkpx2aMXxioOi/I4Zr6wroZcuw0fThM7bYuo1wTDC5p0v6PP1Zseu8FXdbhKPSlUmFjTI4awNIxziLCeyAfpJI+aUULZxCtjSrhrCEOMa06HD1bVJ17K1N6INpBNHz7BP2OkLJmYQ8ardvJZbkex/d23+B2OIkktO3G0CGM9AdmIAEEfaEkugeeB9+KRzeaLAYP16GQtmIstoy5KkvQ+RvgFAow701tFVqhWmOJca/ZlxB6ZocI9u2YNohMRn0RRQ9CW6dzBOaGPWu0VlANE0aTvq7HWPm7W2vUcIT0GgrURq2KyMpaCm2tLgM54dzAYi2lcDwucX/AR1tDat0i2FjIC503TPzdkvfaZv1vSho+c2zM5bEljIMpD0kS2aimI2SkJXAyYm6RLIYsNuj74APu9DBg9cMHAo0cAS15AbiMFfJRp1V5SJnmtiOIJG9gOACkQlMQR/vp6Xu8U9o1yjGeq9B0OFQThpQm6pDqnYcNWaLV1uWyfsaK+45m3BMytMBxNx030e4gHZN8m/v28XIPbiSfxn2e8gfgtss2XO5NGXcKcLaQq9OATjhZRqWJHOHsX7sTiBvMpSMpLZG2qEQqCeKcDIKEHNcrCnpjZoHUkMb4MFa3jsUBVKe1gV7T5da+HzvDmmTbaT/AZEgNOVdGugwYaBRdno/fYu7AecGevoFdjej1mVvD/uMXyzVBYbokmz8uv+/y08ynsup9ByfZdJYLBnLftLCu1P3VZS/0fHMZL31UhJD5DHPlOVIq8puGA+3WmW+cpWVzJSsZctgjfUkZH2jvB8MtPy6xNq9Ffk8y9mQcdxQHnV4IbYIwX+x179O1Ia4/G+VHpf5SKW8HYl795brR82Xvn32z4Xz/7n15p796rnPGzwd1QyBEGrja/Czdo7O3gTKN63Dtm9LX/XZ0Wxtw7SLWU/KUcIxNx/+UiVNX4Uh646VOv/y+Hpk+dXrjEMzY/n1tyrZPf3r5Svqz39Z7upGyWN5Xr+ge/lNLMU8HcM1I/l7e/+sb9JmS+yXbGiBp/5ble0Zn744c/4e9N92OG9m1hDcQZEryWK7bq7/3f7tvdZ9bHstSJhlA/8AQIDNTll2u4dyjqFVWJpMMxoBAILAx4CnU9xjph1PAN9+b8nDhAUUOjvIMnD+X5/Lj5RlAfy7P5YnlKZvN1XseUY4qPKJvPb8OZMQvYKNw6CL4DYq2ANIF/2qMSZqHbWaoNgsl5RbrKYTncTm8SeMf+4UJUA/BDsAUNxQCdwAppqhbFXjtErYS4Y0CH7z9b0F4H4oKbWiksBC5aqCSinl5eLj47bB97+n955f92/8+WW8cnh+/amNqnujX6zqtduBqZM4vQ0dpY87cAFXPC2lvIBhwfqfxRsJLNUX+qTXcKEYstgvz9hBKsgs9C4XXcXcUIkWCCqlB8jWRyvO45s9Gju9ISyDriuXhK7hNoPkAEkrFOaBYPeehRjh4Jsi6mqeQaAqrU2sJXFXlbCjWYvwoxsu7MjxY6Ow5bqaQM8+w5kq+lgYo7LnMq6ctMA7KoZxkB9jD01TTM9NuZmZIX0GNMLUJjafhfdNauPfgMN8ApODWQFCc+grt5kkoXdBVQN3WeRMGZAXEeYRb1IqG7xqcl1ACvmFEE5E61BV/A8AMr8Gtx3koI+iCBiw9+UoZvlHnKzapU7d3BFhq3mS6uYf1zhUn9xivc1UKPUBxC5UjQK+gAE5fVruHjxayWBTazCtNG+OezCuNxRXxqQwsynfAFfcWep9VgOZzHX0hH1/dHsri3KRJk1vaqx78ew/7bbnCf3eK0uvPP7Gc5Tbc1rSN8OD7GYVCyJXqoVjO9TgOjpLxpYHGoVRS9O4+C41zXwNCKQszFvBa9nt60keMH41ntwpzZP7tmgoie1h4mxmVdQRYpFLupABC3ct0ey42ozjVzbrp65IRH8w7kfyz5UXufTXv5Gy358pdTt4vq6+1ZkCc2nhNbLmNwxMlgMfIRVjFlTGHY3ZFR1hIhXm0+CzafmAxKt3jF+DVKKy725NGgBx42g3pY5xRXpRlHe3y3Muiwecc0EKEHneDGC3ySAJTY509WTopN0VY5dt5zloIwMOymlGH7ze5e4eiib2dAcxAMvqI7r1oCABbdk7LG46kMQV5KG/eebzZl64Kjh4KAZ47nCn2RwbxhGmy9oBj/Xn/ugP2zUKmT908LWqOcOLwzI2hCaHWeDApQY+ANMJ0O6XylggQPYIIaHzjyuGj57W+y2g6QCz1sS+z5SNJ3srkMrLvucQnNwKaHWxbwGS8YmmEw80vkE6Q+wcAB6MNUSykYNECLgOyiqdssX0ooozD64NyhhAPZRp0hMUnIvOcZfPmbpPRRXo9E4Y8kT6lOlITSIBq6vuYJv/vHoEIHehrx83NDGbF8eFokQMOlhuUJvNSFxj4aAaIFvLdxDx1b/V6LrH1IghZ/hxIH3tQjR4Q8pH1I6NrkHuaEwatxXUPiSAQiLKdK1TN2JFC9ip7XeHNdbVwszOOdPXc1AyB8cYwLorxawxA3SNdOhSEaTLVSY+ctBxxU4xgmWJ2zHAtgI/Yu6apAcrWDnioeSZYFJBiACnmjU6xvgLQFQFl6g1JAzyViAbkAn7IW87jj+ryTmFOZoJiIdkfRHEiC62a40UlUAdlLzfH06OP840R/xhnusV0N+F0/zvuQJjpDgpFp/vk+8D2bHwDwlFtDO6IPRIDsCCqZnBzmUBtf2fPEz9NM5ob97CnK2rsBqYlKkSmAgAhgvgHPQJBo4SZCi9hyjzyU7NIGioY4d5j/wDQpgZWYPHIMMwNqh2ktn7XdQUTG6AjKDzZzh5yOoEPN067Qw4SS7ye7WwuU8fyrjIekRkMG5uRMuPI30Me+taOVreM8zt1dOCKILiRyhXIaBzY7acX9CeXWkY53jo+bx4q33J/2df2rX4/JtUOGW+050Kb9/3ZPaBKHp1q3TyXc+irJAw89q2tJmjbbZ2CNQMVbL/Q3ZBtoIAmeG7h2hv9itNvPcGuvaxvd2+jFAk+4jMB7/AWQh89V7iRyAcAv8CuPfxrm8P8MwFv9RMYb0HU0N419N8E9KvRdXtHWN9v2z4eV3R8P2gYHux7EPKtAqRvIA7I7z3T40TexYwPT/93RfuVcfhfB5z+tUDeu5EWWRS+a7q/5me0uU3GF8u5I3YQUcLk8sHtjRmELsuCtVt0lExzBJcXXcaIKBx2DujljDmibiVfSbocMkcA7kzAKoNLfk/5pkft1eeweW4/ehvTyx24r4ClYFEF4wVW/YLkfteXwfa93w0sPsYrvqc8/b0f/6Dd+l9R/vcv/wUQ8H/eb3Ocf/iT2n5OJ098jsZ553JNP1gvgOZRkVQFi142AhoVb+XUS/V9850ps8SZgTYb1M80EHguz+U/uTwD6M/lufzEcsnjE3Ch7uwAtz1A1oNk4kVyvlWbkl6wuveZkKAJQ1gwoUHVwmU2NFP+wMM41/CseUBzzSaG1bsCCWyw12XWtRHi3QTuDwDeCUBoeEmE924FELncfxXGf5N4/abYBRiqBvBbwkFXzEEToCLAgKXvEGKLU8IY2J9YIvTQP7k8RTDaqkvi6EzjcKUWznw//Hf78YVtHg8iADXUI813lVB+p9zqLbzQFQIGXRJnLq69R7OrIU1g7SsObiVAKIoJV1Ku68nDxroytygipmlCl+5h0KPuuIPyOavPFae5gAlhsBLgcQWS2XOdt6kC6BPWvubBNsPNFqBivySybm+10gB/OoCuFuZx6auNXQsQoVleWzUl23RjuSHnwwTpgtYX9LVjWVZ07kBfITAFv5BAqSHDrYOArhbOsoSIDqOC4V0uCRSJjnDSG08cDI/zqgy073v1jfNNwrA2P7tj0ITqXnXsv+l4SusgK2DA+R44808qAATCgibd8qoCAB3NWCPBK7Xcv1AsSmBWMLkHKHMe2gxYUr9OYGFT8jIbIELDuAKF9vbeBACyzgBcQqFWFzYVBcp2Duo+tjt4Dc2gj/0fY4qPHVcHeD6+k/fNvMw5QbwKoDOTA1kl1KwKRCJEKtl3RYYQ3/RraDHTIXN3S1Hf2JfqeW2v24fbdDqO9ZHuuQ56iIxDbtL8TlYgg5k3yq8ycMWEJ+mDeRhD2dndI0l42H9yr2OjD/NUN1mFitJUzbAO7uFc8gNblImtNoQvbN37dbehLssEkV0fvPbaNq4DcAh6JrhhX1WpKjZvolAcwgG/sZo3854VRA3bH/bhw6808eLXiPKTtdL21vBghrexRbDiwtcDhAM3RLigrfpwdNnRXAObg2f48wq4RyyBBEkHHlzd6/UoDzoAc4FJcxGViFxRE3UhDNXE9kN1oClVQ7aIgT485LPttJ31zXaKuq+El67lZh99HmuC6Aiil6lUDuCpcduEcY/IFtwYjAnMJk9P8wSRA2S1kJ/m9WneveDV8ouTgZnVliEiRiRfDgUW+WgFIEeASi/9IYAJbWq2Eomgum7AD1ubBoaaPG5voqDrIBx/XYXNjG6Nd4go+trTUHFdCWABech9VQI1xuy5wWM/y/1YeiraPREGejc+NkLJR7vDIMdoYMfVCogHbI0Fg560nAeGYR1hhMK0cdlUvN0fKTjbMAK20K/i6ahs3GLJ5DD6a82ogrG6sWWC/bm/DLl1c84bm4m1ScNwmUoaHt+ny7vFjTg18ryThWwnjf2ugXvHurqBkPNkMxijNNiSAE7TqGEbASjfiaBN+PxvfwteFYuLYMY+VOoZ94zxb7ctZWvr9hGMG+MzGnsW4QaEk9e3gDJ3PcjBKmI0lw0p9u14u4ZMwAk0NfKoTkxmGMIEplbW0qDJECsjlHsaCRT53V5jXpyinlIHfmbgQodOB+SUNmTY8z2jkH2mSolQ7lRk42FAZQA+R51U5tfvtVdpTkgCo3HOSkDrCXvYTih7whPnRc/riR+cc2HboiJvlsfDmCUr1TFP42xgT+n+ea+ktj/22K0g8u3GX9v669782DjFK0cr1QycHxGjr9enuz/bCIfj6raeMzlMNfcW++3z+F2Bw39NuP9t+zzt67hQ3rMB2q/VRILYIj+QAdT9ynNRmGh7DxGANyDPg5734Q0U+kM5zxWXdTvWx09X+2aarLhX0X51I2mxz/Kbjea3cp3X9wU/qvIZIQzLUc7CUhwcrHQH0ylS2Xk6NsBlJk+BBV8ra99GxaLc9EKuKwa5P7by/9YSBoyrfvm3bP9j5Y3ih2j97yn6gxvHX1v+LE/sOGcAOJN8L7bj0bqePukhO1U9UZ4bUWTjK7qGZ5D9uTyXb5dnAP25PJcfKPsN5toG/NSwnADSa0A1FEZIIVg9ZqLpedx7LjY/B2fCS8OUcX7/CnBjHHh2JYZuNlcgDkOuKA3FRAjWbEDXAjGPolCQ+e8nNQ+NmSa8g+Vq/NgUnxpDFPj/+oSOFasq/tUY6uGjWcSBdnMts3/9CBiKqSvDVo7RF3+rU/GzxIA4YL1Ssyj+6wH1R0/6BfOzD0PYCvWEHa3Dkri1yRUxNtaNCYwAjAg3OsKkK0Zu86g1jm93CjxAcOvve6GmNP9yMZ7xeSEPTX2YDzj1JQHYQ7M82uZBbYr9OOwTCAcCjmQgdlcDVALIGbkBDRw6LSfT2TuQHqBlhLENzR+XQ+Q8z5jnGffHvlm/Z97kBZykGHciz986wPIAw+HttBDqW/CcG6OhofduyvxNfvOiDC4zcbaWXQtiuWyBrh2tzWDPfzzPM6bWMM8zCMB8uM1w7tM0YZ5mdDZQTKhnaFYRyxvpPlXGo1o9HDWEx1noWauQbsp7y5NLRIkUCSQ907ce50F5Y+xDUTaUVaFa85EgxU2MR9xTaC1qq9fkwjXgDqL39nuADrUSBUAerJQAEkXnr7DcrE5SZIpQQwYdNFXFLRpUBEcHtAKAjHC1sR6lK5Q9tQAJpFv/oBZGtwlb1YUcjJR3+fEoDD1iHxnAHZN5ZEnMCeBenXV8Y0/xbpd1iO3I7MplfnXpKiU4smn2RqmY643JwcABgMXvFXwNQLqReaBm+GGQewsayNNVba0xoae2Ti/u53uOGv+mKquAMPHOoa8v9WmRC3S/Xw01pSpwPB5xd3eLVISD8o2Rb3lgc+EB50p3UgfIGH0d3ubpnQyCdPNYvL25TU9FKeGYT+sJCqC5Ym7dzbh52Q5lXrQ/chAHWE2h7/ZxDI9Nhf2Qaxru+SJ2v5IbjsjJxlO6GRUGiYuax566J2aM6RW6VJcrpAB85p1tkTci32QrNCmqadg05qp4uRZ6QAJF2314JoaIutdQWU+2qBzgGUZT5uU6jGs8bjnWLq7ktHWwurc4MiJAQxcBkc0lWvBTRnj7QlHAGzeEcTmPVAHfc42mDPKcYKl/BL5nY9Tb3Suep9lCjrKiK4HVcqj33nF/PDrvMdqzFENkaYWiKTIiA4DMczM8qa2/N7CdlYAWgaIfXOa7cX5wHPsmMZQewG32kKcA6NY+0wOIZgCzz+sDgJZAuvpeJ6KQppim12ZMd/8AQkcL5RQ3A9BVwD6/Kh0kClLBNBuoRu6x32NBBBV5ihPyyC9EhObeaOTzCacLuDJbVTN3AsFEppCjkOcEe09r7CYGNldoZnexHBdoV8yzzZl0QQeB1tXPHLZ/dR3RqlJmkYal96R9cZpOT2gdhieXjkUW5SGWsM1+8PIABsnXHZHJG+R8LiIdRLVh0EsgCFmUHWMp+7Vp/zOsT5CeMkfkiR7rgjB7TtllPblxrvVrajYfjdl4VIAN8TxiH9bC211CIYDI8m6nkZN6ZB74Hsc2niMkfhg/KZQVSxpUr4AqunZbTwSsqmjhgR583M9XORYhx9d5UeC4k9cfilCUMhVGyo58cLORm5f4TZGofj8+JB8hEBYiwKFyYkqDghVwQL6lLGO5dxkLGcA8FRnfRCFJ2ZgATDwluM7k6ZQi5YsSAtAmNSPhLrafqCjmebIoBs0B+oj84dZdbfI1kROthao092Hb9yziw2ZncBqNCCchU8VEEJPbQsVTFljfdAEWGYFhoemrLNHXYeAbJiL5nOjG+HZbxlnnKdhBsQ8ZfdrXtfmBdn8o57X+YONBI4DZvmaiLY35LSbbjEaF4Vz1Q1cqD1aEG4Mj1DovlycMTr37yu3Do3zfHM2oJNtidyZv2r1gGyknZMna39JHHX/Hl+DPIQPFv/U7cHy/QN0bvRaB5R1f8eHsty8EvImUhBjUQRh5xA303oZbf1NYlCgg71e0X+2M3CNakj8jpU7Bpx8GFK/pcD6dHwrPnntV147fH7L3Su/j1Ge/O7840xvCn/F9J9I3wNdz831/Pty4nE0gaiBacypXzw9vfMXoojFn1JloE5EZArLvX8ycOdDhe3W82/rlexToaUaj+N7V8jPK2FvjKwEgfQnC73h4cotiXe35j/+a65Uu3pf3b2r7kfLtGljxKG3+3eWVjnX/9f1vdvFvau+FreNiOQOnr7T3qfPKACZqqcc49vXR+6tROnBOZ9+TJi8iPeXLKSSk5/JcnsvPLM8A+nN5Lt9ZNuAZxiZ3yZqrCsx7pe7Z5i4jw9xG4WFaS9jxsLxDAYV594haaPTQpjcyQKv5uR+qwzOMigIlwL/4h+tma5uvHcZNORYAehzs3ivhHQgTaSos3oLw0b9PAG7eTfj8HvgvUfwLo60m9K+AGuAfIDpguV3l4sFyc1w/v65/rqxW647wX/8u5TG5O00riDzUoQEMt7vxfChf7gm41TIXDjp8I0jRWbEDmrhXueflJcKBCKcyoe/evMGHz59NUUfmZaOkmLildWf1ag5jElHBsp7AYmD10hVzmxxQs3Zz0dMQmQJ1XVcQsY9N5Iw+B9CpXoer+B28C09z8gOrybMWVtKAuzbyoBNDyAAkJiog+sj1HH2L1tb3KgZIGKE+I3IET81zQzImNw7gRpjng4eyBW6mGdNhRl87OjEWEFq3sW1QULdB0lD6yFAcG7BtPCfB/NLoCE1PJKkMgT9redtMCZZW784f9l7n+2tVfxFXjwTcVkWaxm9bzhH3M+6cbxz9+r0pNjQAn21dpmC4AeHe76cM5RfvsfSp3i9hiHb3JLfh6Tr2j2maIOlJHe0EWMSi5HcGmoC6jWlel/AqiH3D+meh6FEAZ0aA+8ojioj1Y+TNC++uyAdf6WtLe+OzqOCaMuGbZQeAx7XNd1xec+yAY4RlBbTkXC6RC6Dm4Rw53/0qnOcEuSo3z/28TyFwtfGIPPLIOmMGoi9GOyrxvwyFTLe5QR1/14i5UymIMMDz3LRtHVlI2AImEVkIZ3jIYIowzlRoQzxs7Do8Oh3EgbqxklhUBYVkGFsi95AjstCIsdFe2IWHoraqYut82F5jGL7zBMABDqSMETk0FYvJHD1obaz19CaPd8d7XRmpWtWs13c/haep0VGPO1Ej9Iib+xVDEX+FRHT3N0EtV5nGrAjEQwBzht4WWNQe8VD2YYLDBM8L7iHf2XlFCnDI/ODkoKlo0JZ3w8c9ASWwy5fqax8eBtr3Y+m2j3DtzbYwEaiRgeHsCt6aboIZvCzoal60INj9qrBQvkHDBqAPRe4ACMAM4hXEhwGiEQGIvMSLgy3DWM32wJED2Rprob6Z2pgDtf6S+J7bGEzDoKmvgpUnsDD6acEKYOqwd8GAc1FPC8GMtdtYQBwUBjLPNTnB9qBNHWMYiq5VLOqIkwUosiM4oKpEoO7rqdse5ZGdUQEk8rGI9W/jJYa9NntOpIM6IB56XsiiGqiHTTcDF0ZjAjVT3qp0gBtW0TQIUBLzQA/AN7dNLW3fLhAjO3XAeZylQh6ULn5uiVQmlJEzBo/RHMbh+b1f52HM4/u5g8wR7lyhmWIhwP0wzsv1Veoae+M4kZ2d8sr5rT4eBpeIVC5sfJVJ3fbGgdmufrYTl7+A3tVDxsewqtOR2yOShRSGRzSJPseaV4rvW5lmgz5Eo/3rJY4ZW4ebaZV+0ti//cmbvD7WLGPIGCdyj35/wlISWT0Nlj7Joh7ZXUzINDsUMpSqg94mDzBs/WdkqeyPB5sWW6uqRrMqgsaMeeLsW/CYAGZ9F7swfk58foDIkVTkfh7glTp/xWYO/ePImDX+Lgo9BH/3V2l9R11Qo4+jXvKNsvyff87b8FjxLbWyrKeXsgVvQtU/9fGQ0VK6jhpKBBMaVzC+YvNzVAYUmv9rS5WaqvH1ZdHkEZklK3psHnXco8mZ/Jfy2cdEPilQwHL7O7zR92XFhzIXViognTJH+a6bb9vyicwzfd8V2YFL9X37z39l+ULALQH9N5OX51+HOl2wzXv+1DYOvYXTcRo+D62KZDh1xdJH6iR1WVKhEdwxaSv2Nb/LUvfJAA416KMIvUR1tf37FFsaX/D7z6zwH1BeqeU9/6fmDo/yhYYxTHz/TystIylROi09WrbMEcDgy9/rDZ5yWDlT/E3b3XN5Lv+jyzOA/lyeyxPLxiPvEWDhR0pVDFOGtxzX47Cl9fCd52M7nUeOPvGcai0BIGDhE8Rzwm3ACiKky5cCUNpazroyC+7gAoKFPAzrVgLeE+G/yBSnAWW+U+C/SfH/N8Wvn0wRskDQwPjfa8MndKxEeO9Ke1XCW1h4r+hcen5cmov9+P2h0X96+eyHkr9dKNzpuvYXzn7eFRPqCJPnZ17hpCAdkwIPqrgF4aF4ptzuBvlWB6D+AMUdyEB1EG5hcOT2Edr9HfO7ritA5B5oCLcqzArLj06M9x89xxlTASIGeA4gQalVuoVqDU801cxreUsEWhfMRDgyoxFhmuaNUvL+4R53L14Cy2LrZ+2p7Ij1OMK/DkVIIwKjuZe5ebS1NrzQ7UDLCQAOy1Ibk8YWQjZDysZh2hXcWtE12KRV7y1ShpLl5AQN76ZpmgzIbxaadpomTPNsIeS5obUAWxtag3vMAV1mH12CNgX3DlUBSUsFJAmgYBA3cG8bzUl4ebEDhXktDusOCgdwt6fYyyC6pkIyDAfYNXxTUaFZM3RTq6TKO+gPENzD/f82ykYKjWXRepE3Sune3qF3UHqwugId9/6TAMriIW4JEEUnA7S6FiUJxmef0uTLAZaTOKjXAc1cnpoeT6G9TfrkoTwOgwpbVpq5PFVxHkdRt8/vOUk1GiNXakOHN9ZeoXbOf85/ueSBvh0MFDofOdBNyfM4I+4OuDTvj7jH8lAje/jl1cePqOhYk4i3La/DEtrdTRe10BghgO/RTfsua+EjAQrUTd/32cBXkQAAIABJREFUXmuTZJ3GBxyAIyQInUrqnMQBcBAB1CZIX8GtYY5oHb2jC+O0rIAKpslyQa/SHQyzNRFQ9MyEUwGxousR/SY878e24fRijpJojVM+sZHQJAUCQSnCF3ej7c6AEBoYqpafPbzeM1JPTk4M8PCsSqIMjXNVPOu4r6vnIPV10TwweI5B0L1EmEzPL2so48iP63WIKzKT5wHmKb9RT8f6ByDd1igjQ6WTKsiNJ4kMbJ9bQ3fAlqTQf8h1Zu0AWdUvTwn6SCphFasbd/Bk62hj1EQ+F0WBI6Tm+C+C1oBlVTAL5mkeexgbGL7dG3kAUqIIT1TA977J5oxEAVbQTbO2PijoNiJFAKQBzq8gCIijbba3Uxv8KT3QHYxLb3eggOsTCGyRDYiz/+nx6HKD8UIG62LyA1uYZ+KGRh1dG6bJvJGnWbAuC7C6Adi6Fn5p8zi3CGltdHI8LQbSi+1hwuQ5uS2mi1ijgogBjLQJtOEzg6eRUorzSPuiiIzRQDND1w7t7r0K2xdJ3WuZGZgaFjcwbJl+puzQNLzhVQXL6nKBIulttKwkuCh7afC56j3Kse8oZ5h1tIZIEsRTs3c4qDKRGVwwRrhMInJnvpEmJs423SNVpJIxgf2x1xPg5xvNyAXNDTASbHJZMnJQa86zA/M+X7EzRBSYMGYxgHebRmCI8jrG1ibHoiz5WMci1VJ/7AEhFR88NQcpcD/cezE4uZWDr8VT3OIbSd3SlvxEOMQcIjDjuvcRbvz5Jfm684EQTmCy++wy3S1M3j9Bh9xMlDQHMtkl9quJW/IRdTqARw1h4vKe4LkCUTOkAdT3Lg+LnyikG4Zrx9RmPz+s2afID6YQM26JvZoJExq698m2IKMpk7udr3k9BMXqwD2xGcE0N5wKQ8ScT14BndIMyeghaGPMT4inVM5p0QZCrMU649ty7frZfbGdVtlnU/Y/bOW8zX5cbtnaclyQFjWiUVHK+iGTWHsCRK98EJnuJoSqM6lzbwjxVIRhLwvum/7IWG+rMZ2Hne0u3nHlQX8dUel79jrXY/Vc192HanS0jYxUPc1fo4Lnxhpeo9fw7lBMeIf2C+FfH3/bNDM8wt/qeF5h+pMA1/bdfp2iIGF9/xsIbzF5RJrT/7UzVqS4GafmN/hAn/AzylMcIl55238nu//0/rc8D5x+A+Zff738IO2/2oVGzdNCeFQW1wtMLXR1Q07n1vD1/mvKJGvvY40HH0v69IhEHi1uv/B6N+eD5sb5Q3a1pdA8FNnDsux4/K5UvgBsgH7raJFxsaO3JxTdrbcoe4/h0E1NeAnBF3zJhx6f0I1D0oXb9829Gmn00bf88fLSZZzIe17YzXP5jrKnhjP9wR9EmkOE6moOFf0b4HkYz9dtSHXQ2R5n+ENtK/jFc3kuz+WPl2cA/bk8l+8slza1ax5rtBMgz34vn0OHUQ/ScZ3LIRChJHAFlCnBLGRmhwJi3tzKiuZ5Amkl++6KQYDAjVIBqZ5XF64wToyBxvuF4qDuypxsn2JVxaQWBpIBdALeiuI9KZTJ3qsMVsb/mQiLMlaoe6Aofhln3Y2S4Kkg+rMg+ZOKKsCEGzqYUl/7xbG9JwvfHuXW5/0uj8qEWyBDaD1J4CcUv7Xx3C2z5VoHAWTGHuY1SDjMBxAzHk4PgMJCofcVBMVJxbxREKoF++8E4IYJyhMmVwxHSPdpnoF1xYu7O9w/PKD3defxtl3TGbI9FaOWX3wiBvOU4dHTGyyUjkVxCpgAbWHoCa0d0HhCa5yK1AAeMsd5AOZULMXJ0yCoDvDdvZwaMdo02/WJ0eaGaZ7QpslyoMf9rUGIwGqxANo0YwaBuENFMM3NQFjp6F3AraN399GP0OJJSorwcA5FthTloqqitZYe6IZh7F1x4lCvPk7JJY1dIcCedALynJnj2VBk16M9ZS31vs1bE3MbSvbxe8X0AwQ0hVjliwMYjZ5Z87dRGohpA4YRKD3YA0SPY1h4oHdSD1HsQBGRh5QdNBVK5QTWfGy6eJQC09gMZVRV5tc9Lgb6Tyh1TZ2HzzvfNb1n3j8u++LgOxaydiiPw7U2FIbintimSIxoB5IAx4Yy6kEWlTpDWaVD64RQY8WjmlURwmhBXVEGUGNXdA91rBSww+gqIsD4vosOZx/ZW/vHvxEyfHGNiGPe9aM/zOwe8QTyqBciw7hONXjKaFuMPVNP0Gvilu+INRPd3hRvnnTNCAl7ZTTggJEDFj1+J0tpQNqg1Ece4DI/m1fVa8NqIcd+/0yO8075F8p6zXmz+0LeWteOqTHqfhDwVJiU1FcFbx4D4nQPM4SByzrBs0TdvzrkMCezyEcfL9VCf1GnRWbQ9EjXbmNq+4e/O8lXPAxwqcPHroavJgfR0YfHfsirHOHhiWFe3wOsFjXDSSXJ6CwWkpwtZDIAirzZ4rAxC/So4BtLCxT0yA6oceFPmjMVfS8AfoR4JvLneRgHef+rkqvyT26x7+eIbNYVUcPEZIu5xVwCM5GHGo/6Bg2kLAETtZlXX/ODnslpwLyKGeTpmBIo8UU2ZHDryGbNVYTN77C8rR49SgQrOb+Qjk4E6pS51+FRSgQAJgJ73NCQldhB0VUtF/qIKBXzkMvYm+H1aZg+RputY+rvYuddTN286h2gBlvoc+R7fM3mYBaekGPk8wXj7xJ/y2+I1A8aj1RaGpF/xtrQ8n3QVQDoFj3C4z/U3O5JQYMm4h1hMBMRwjbcyXnB+C+658Tr65/U16ZPQBwPBcBMlo4pwsJf3MtLAwOUqwQVS4B0TCwBuIlfXQY9wQxBGHV8fG04L7L87y6NkwH0TeFRmQxQn4hBrSHyw4dhRSMzELWjqhsqUE13MOgvBDj1aCS25iT35ZAHYpgzEoVfHxQV0a7KeDCjCdCZMIGwqqc2Ix3ylqY0shEpcjFS8Pu6doqh3djSt2u7TGFS5XYL2JXxYr1w9XtK7cYPlUcf3hFdXNUYzpirARRf+j6uBi2PwdmP29lLzkd28/1q868sq0fvCyZwoSnbdz9e3/7esznWOvN68Rn5+Cl5qb3/Mwivo6H5t+E1AMLqodQVHf0DX+zHvsQtnwh4pwrgDeD1vFYPe/zOAOj1/fncAZ82r7Fl9HPAc+Bp0QQrhXwmAzabAoy3UHxMfvL1CXVF2a5dlyUdVEvZkMhTpdj713X1tFNhuqMX9w4lSRrYdsSjE6mB+PXtwZeJ+MK6+ueWBwIm/fLkvPP/LiUMTv4Q3/0biuAf4Gj0NxZV+eY9ex3H/jj7o2D30PnEWh585bk8l+fyc8ozgP5cnst3lI2SsYBYj4LnCUB8hwjkkvr+GMfNPXR62OIWhYErlCJcKESgQlBaTefBK3qEuOSGpgxiP/CzHUPDOjnynCsU3CYcDodUrKh2CIuFYXVF3kdVNFG8bZYnE6LoIpbp6qbhv4gxsYVhrKH1zOuc8JkULz3MMIjwVhUf4Xm542BQFEP7g3x834/X/5Ry/eB/+Yeh5L2cOyfAn/C06x42NELJKrnBhJqS7AEWGjteFa+9Uzu4PEDxCpHXFu4JbsA6AbjXkfePYED7w4W+HGB5idXpfHGF861/P6p6SHOPxrAcocw4EHC4e2nAY1/Rj/ee413x8tUrfP39d0xE6LA8mIsCBzWVMkDo7gG/ruZv83A8IoCVCKVr42kNrYrxrZGMh25vU/E+b64A5KsCrPGR5mDDhJubA5Z1hQKpVBye16FtI2AH7nNksedmXreZf50wzxPgwGtrM6apeR52y/HYqKHNE6Sb0npqE6apYe2Ch6PlII5cw2s3ULz3ji4da18hkVcS5k0uYl7/4TagPvYKzdyf4U1nAQeG0nkPWkS5xmsHCQ3PrOSZeGT9+G9H/3wXIJvfmw7/lycNSl9HO3f1Rz8NMQUIdwA9GDhS+tAybLXRlJKFKCf1kNoVRF8BbZEnuZtCuYWnpPNneP7PUGBXmiNKOo33oVUaokHbtOtNBS9iTENr86PnMo33Xp/TBBwiTCqNvnmXLuGo/pvRlNjGlQohM9pQHw/LOxxgRNBfAGCbfUbNICzDsFbFrHiYRKqgK7A8HDHfHBx38IgVFlc++Vj8VYlQvjE+mm2KMPSjMX5IJwWcj6eqk0Y/QxEXOXGZDADoquBpAqvitFjKFRHLp9icJrgLukiGDuZmckPzOVhdqXeWq5M4JyX2BChAkwFvNf0D0C2qQsgfMFWtTdkJ0Mnz1Yu9l8jyNUftBdQ8K7s2bPKiAhkCGQ5Gko+PeC5p8zBFpBgvHj72d+lm0DBzSxklxh2A50L3fW+jyM7O++spldfi/MvkMIE2S2mTMg6ZQSIocJght0WdQbdGV2KRAcKjVwE4aPhwPOb9ySsoljQlv2UyfsSs6DY7ECWc+gpWRuPhAUrNDNko8q+DQAywhEGP5dJmB8PYhQJl8zOWTgDbXqgnC7FMB1/npJt2Dtk66M4YBLkH1eB2yGfq0CsOICEs9w9o3KCTQifF9DKqY6gQ5F7Q19jTNGUDLqlYYs01tpytNTKNhelOcrX1CME0Tehd0NeezQc7ByeCOuGp9AwzPvpLzt+AxhGdylMtkO2Efe0I0BlkADURrM3dopoIu8wHi5DQPHx6j5RSpL4erc4GBasA2sHiYcZ7z8hVIZ9YbnhrMytArFh7SedSl0Do+1DWj8LSUrWGJha6Xj3yFTuYHjTPlX6TDqy/sUbI6U+hlvt6MIUBtEMLgID8HnLhPhdl90hJ2w1o7GfDIAspAxmA24b8iAjxb57vjBGyfKzrMVSV1xlPj3piB/B9RBVHRK7k3R7rLz958w4C80LnNGkYNHZGd/4cIt95eKlregbGWmPEerSWzcxYVbE6bzkwmZc2WUSPiZtHP/LUCxExIirwLpKqp72xfoLcYAchJ3sUBt83bNzG/tnAFjzExWiopWqQfhx8L4eKEAasQT9MsGgOCkAVsizoWM14jXRE2yDz5lzX1dYBm4Te+zrGODdHBOeH9gWZnsLbEFIdChsTp499FBrEHGrss9XYppLCdbmrlqDV7Ta7p/nx8rKsr5T9HWMx0Nl7YLwt6Wh4ood9n0bu6KinXLf7tDSGhixQX7R56X5cLo/T00av3h98YQJRg6L71NPm960ThV5uzoWXn+WqdtrYDctODtnVmx/N25wcNM/FFzwBBMEnMN5creOjvzdyn4eXueDTpgWfybzVT+9/cyq3Ou//9S//bPcH95Xy3B8p4SEf7XylBvr9IsAHHm3+TPbb50GmAMwT3b5YdDz6+H77Ar/xLMeyl65mEDo1k302t/laELVIPwCB46ytAumxxs9FoCADuTbNaqsg+GUUY1uKk66o8ng+d16T/yl8/8L9fzRCZ5SN0aSOcd2JdRda8IPtuV6xt8du+ln925dXvs6VLjfhR8n/WmvPAd3v69crBSZ/5NPT03b/5eXP8DwHMNbiN6qrxu2XK6TzNj61LVceewbPn8tz+bnlGUB/Lv9BZSijn35wPBcMf2wj2noj5WG3XKhR2JTKPXrhvaFA1LJh+l9TUAlUI6u4ACoQmLKvEYMng7MMRG9+wPawowoLN+qA2RQKDCbzGFID5khS1Qv3vcBHJbxy1Mms+RW/dMbHBqwOChER3oLwwcNr/tqBBYqPPgBxPHujZnMcqowKbG3P/yHEj787ddHlsr/pW9+/t+TB5upx9dHyo3T2+PesvfyLQjvuiRk5dolwTDB+CyaNHOh2sP6sgrtQBaiBh/dXxH4FcAejcwZwT+TeLBYG/QjgoIquHS3CunvdTC3zgIXRyHz7IlUQMN0VDlB0Jjw8HA2E1rTVBhNjgSn0CK6IZIB68dqTAXLtvd8sb7j7t1O0LHKoTpbbPMK4c/F6K9OSI0MBVAiYbUueZ0MMWmvo65pjjKoUgw4DiThYeu5zivD1BUC3XLDWlmluFsa9zeaR7p7q8zxD2wSRDmkC6oxZLSdvBdC7g+N9NQXl2hesfUWXjvDoFenovaE1Qe8ezrb3BER7p/SM7X11i11O8DG8zgNoD7AgrPOHunHQQeozyt9QICYoCgJw67/dlznZged7st2TMu0UXQRc8kIHXOGrHUIjjH2U7nlogw5CSdvJ51cVyqbw9WZCm6IRYVVgJkF3hTAN5BdhhUxJX9YuZjYv9P3etlP2b8elAOjRCO/H94a1q+HJrpWtUQpGXwAgQ98i+zUUK+PFGf6T6vUBkMQD6vcYYEK+H0r2N95jt/sAxPfgf4V2VMUAYlfYT/ME7R0BnovHM2cPox38R3r33NOuTCtjmG2JMAtlAwwMBxu6Q/Ku1poBQCH7uDaGW/M8wAb6KTnIruGhD4BG3vZ4QxgCKWCeqmWmYg3WhwgY3nuRXNw4KizUZIMh1OxrCMnDRQUiJwSAZ20aIW83vdbqo2nzENMVd9Z25r+682ALXrHp2SOlErqDh1XYiyQL18LfJsi734zJpDfuCrjBA3F4qlZZEO4ZGs/qdsw5orYU6pCdUi7kyFoHOSdLfiuQ7gARA4xmodR1KLbV+Rc1Shpq3NGopefoMOyyRRfeqtCI6uAmT1IayL5v+P6GsibDMC8+GzCPNLQDTCZuNO6xKAZHADdOY0Er/sI1+AoDaiHeRXqGeo4xUg2Qy3kau4ygJguMNkZOZfcW9mghjEhbQGONawCjw4h15Oh2Cab83XAKUaA5f3M6VAf8yQ2JCAR0sft6h5ABtt350xpUKx0dwERhRAHjFyLADEAIetL06s2dj7bho3PpexqH4Bj19GB9tgMN+eZL0iGtgbqgN5MdwJYTWxHzL34eGfudjQtyv0uQQTUjMAQn2Ac63uBpEeq7yB2bUs4ZNC4Naoi1VJcqeR5vGvMP4u19pQ22jqm8q/J/b7OHMO86IlaEpzdAmCgM9sb4JCCa1lqKAwHL+AFQ4MajTpx8YMLQ0O7i3DsnAjLoOREORFiATB2TMp/CI6BFcyxVkBlUEsjD9RObTNo8yg7xMIVR503cXSb0fkUUD+9iyqG2F5fxAqDsBosAIrx7793agME7Km/O6aQwbvHUMGopo1h5zF1ETPL74PJ9CFBE2KQySeLJdeuybMqjw7AxpjJVGd4ppRBmNK/9XWW71enZldyXY6sM41k936svVIhY2fUeH/HyQL17gO02sLSv8i8pdZ+q5VI7chy+0Ujd/a28TDI13zBY3I9veJ8/9prtqQZoeI0VnzxU+6cEnh8rMd6faIDSrxVo5maRXtyEtxmJjvy3bYutfPrG+/5IUYw2KgwY/BNft32x8xgzeh07VO+98LKxv9VyDRe8dERLlrhbZvtP/9RS+3rvn/+neJ+/VGBSMxzp9Fd7cu9X2tNLSBMf/sHg+T+9ZGTJP1DHXlf7XJ7Lc/n55RlAfy7/McWUTtsccJfKNcX+3ptvb0V2LUxKKJJUJJXLwxuX/DBHW+FXA8hDHqjrYSoUiVo8EBTDApmVLN9uPLcKhBhNCfBQd/DMggwYaODvs/DvptwxD0rBw+loOk3P7jfPDaoNa8mTGtb+H4nwloBGwCcifKGOtnQApjycuOFhBqbO+J0Ir3TFQRXvesfJQyx+8oPLGwU+FrRDiSznHUafqzIpgZ38dyhBLk/q+dfNpW9YYD5+cNwq9L+/0NmBqGhoNt+utVNKRnsTqii/A8B9767UNkUwEblXMFnObCJTHJfDWn1T5EAnckDc2/G75/TMnqQS1iTroysx7vzhFzBg78G/H1w5/MJBV54m/C7md3h7c4dVFizrihN8XR2PaPMB1FdMhxvo9Ap9XTB38zZaxNIb3PraW2AKu2VZh3JM7bfG7OGwGS/J2srNQqpza5afrLUE1OHelBaSlS3fODW0qYFohMhWxchhngqxCVNrxRu8obUJomJRH4hxOBxGRAgH5djHdAB59rt4buTwPG9thGifpgmHww3a1DDf3OD1q9dQ9bxrHLncbYaDXrhZLtJXPOHUV/cwRyoDQ8HfIVjWBcuyoobQFg/13vuKdbX/e+9YymdVRe8rlmVF76uFpYuQmP4O5ghvLUWpQBYe3wHh3nv46IzlQEGvQX8K1dvtGvF5uYGiOztl57WsN9ASK2Gz+oL1qlre4Tz4kIHddINOR19DANG90VhdgICDMzJC7keeb7bwvWYQ4cYQwmjcwMpQYjRWLBJ8i7IOdfBqyvy1vneJQIrycNBMLlQA1z0mgkTSUypBrzou13neBmwvwHyC1NHWkguVXZlOCD4VfFHL56F/tnYyRrqRsT6YuLSBAHJAy3MM2rPmm8Hs+dELMBsH001Y7xjLVFz6/bHvq+J4PIKYcbg5wMLJC5ZVUtkPcnArFO6lPsjwnBPR4YkPgqrlnVYH3EDu3R3j6oZD5uGoOJ1OEOmY6ZBjA2gaqax9cVA9QLEA/mzfX3sfCjwgNSYNBrI2bhkBh4ggq3uMmqhh67rn0+DZ5hOdnZfG2K4QZUBnsKrvYwTIZECsMkgXqPYClI3/Q7rqpS2K4dE7NjHyNAChfjciYnhKC+elNz4+p9XhxQAwrIbMgS4yaFxUBv+Je2mohgGAJwdgd+HjRTt0DdlQbe8hywUPB0KDLzKxeTKRA8+KzKub4cHTa9rIpEbAIAxPRiprSJyOY61tQhKKQtjAKW7uhSwTDpPJjr3D8oh7KPf5MLmxlI9ztzQAzA1gYJrmRJVEOoQtf6AIgE7wFPWgFcCNR0hK2SZArwBRR/h4MCA4gOQIQNH0HkoMohcguoXqMSdHVCCreZqfTkvmIFXlNEoVsT4jDL9EsazwkPlkHsk+ljbv3l+VfIeB5EapxIRGk4VIV2T7MzCrsuV/7wZms4c0z2gGAhDEQrDHfK4dOoWhAYOajlQA6sMc/EuA3sX2Ge0my7jBX4zLugjIUjJDtGHVk3vUdkTMIQZ5COzged3d3zwqh5h3e1eByjZihfFt5+Ox/3hbGR1KVq8QobFCuWFSBTWLmjOi7CDXQO+C7oZKsUepGxOQShoomxGkJt9BGSf4vgR1Ew8FZO2JBAVWmSBuWU8Tt3JcU5ezfA27rMfphW5nLA2+yICu0Qg/d3oEJvWIIkLItR3zme2FgdlEhFtYlIfu/NOMqjHOjD4PfWLcwEKRa/yuwLHQsQKW45yAxStYXAS9JRqGDf7fDIJ4pCELww5M0wQiCz0M2PbRivytkTrIUptjJbMOs3UQzfL5irQm3m/RlusDwe+08mrnDTCjAMIwvIOK5QVubNEzwJimZimh/KwtPl5h6BLor5B5zwftiSrWvkJF0JjRu6C1MLSxiDEiW0PJXA4S03MDvo1occOAlHlyuvL9M6IOpTwwgNJYW2Wzw/k3unh1K+heKxtJcHMtZeMhFZ1VP+SocZXO7kquZutMxlozewlN2il/vC4qVcSdbpC/Ax8tpUgRJEv7qjwb43lpWFLuIN9kARBNvsac36fBykglYA/HxJvxZl7W7cjle0NWru3a8NRKB1Vg0/ydqIRuh8LiAcat7lGNNwAGGGMAt3mH7zGyN3od1A7P7fBED/B8whuTnzx0u7x/6++LVB8jRHtMZfx9UwbmR8H0fYbi0OV85PNrAAq/2K2Xs3LtHLX9fuvfxX+KdZG5kZ2/LX5WlnLGz8EoZW/MrAjmt30v7T6o88muuTK/3cUL/Rnv3d7xpKqeUPa61kgjSNiC5495Tr/QEWI/pmcfAWJ8v1xfGlSHHLdv5zf68VK37X2ppo0VAE1fQ+iz/f84A36kPN6CPdffGqx/G3wl2s+q07Fe5o3/lPI9nudPcWC6Nu/Xxu+bnufjxu3ofqMtGaHHdSeBL9Q6/qwoCc/lufynlmcA/bn8R5WxiWwFsf0939qwvnczqsp205kUhUsF02vr9oJvOUwRzHNlY8GOlAYtz6vSJsQfxA5wXQAIgdjCcELdiwPDs2/sviZM9b4iPH9A5hkgqphgQpN0b5+al9RHJvwCU6BCxT0PgF+U8IG5MB41D1URU4CZ/ghvXEn0KUalWNdXj4wcq82H8WU/1ji/ZSMEJYaIp83xtw0tzw8v31P2dPhHhNPH6JopQn+60lvVvUAOWJYTVPZHzdEeBXCj5st7A5uqO6LhrULhrcF5UAugLH7PnIheqxaPsAA/XjDDgC0GTgtUgVcvX+P+4aspskTQZEU/AbcvX4FvbnD68hlQwslzpuc7XCFe3xlAi4Hoo4cvmLGwKdbaZJ7brblnOVx5KaYIa+E5497p4TkSylvAFJ+R97I54D5Ns/815ap9nhB5OCOPeAJeCTSSg6CmnIvQwwGkzg6gN/c4v725QWsBpE9oZB63xKGUB5Qt9cMkDp41BSbF1Cc8rOFnNPinkikrj6cF07QAGB5yEcY9wPN1XSx/22kx7/re3fPHg44Tgai7kqDnewI839Mxe97MvK7FEw4A6S2UCO0Fo//u+U5RDyd+twgenH6TxyaAeIeNp/qlUg5GGmsJ9yNnKMH4ltN69SDVbkCq5Z5XKIkp9utaUQdG2+BrwrD26QrLKwoosYW9ZWQe5NHVy3vdFtS2P7LVs5cqxpq9yB8vXDtT6hQliCa4G4dASn6Q0RP8QGg5TuPefd2KvXIFet6ciGywGX8ywAUEMyTzfqi60vZiPyrQPRQv2/GkAd5ALbXEmkiyv8P7IoqMoVCBylSE+o0JQNt2aPpz9a1xtEHcLd3sewiAAejkm3vwic2cuO5s9Bc+VuH9GGFsEerpsVak8Nfs1G7/oqFwsiC+k62+PgxPrE0rtiTpnvEToIt3XAXABPObPZ/nrefVAFM2fY174fuY8+X09gNczvHmh+d9ymU+nhrznpdr41MRajJbjEd4UuZtKXeFYj2MMBQK6mqhrF0MqmkphjGHGeFIAY+C/twh0poX3pzR7jI/QYJhKJKKREUaaxIhvR3VDShVFMoC8bQTmabAw7o3nizQgLctFYO+zqnZnglhiHgIawcUCQbEKZx/P3h/byTby0Ro2i7yJJX7ATDxiQohAAAgAElEQVQ134fb7p5YtwqTC4pCCtJyPsLjm7rNt4hFlvBBSZpIgyWN2Y11uW1f8mi/zETFmMHNOpxdlBMDNEIIFIPgXHtxF0Uedx3XJWAkZF+CX4jLXdQYJCZb0A1DtKMfFTgJegNEVgtpLwKdARJCP0rKOOr7aY5XpB+I8S3jEXJX0FgAT2KnEZeVYCmrAjBSBdEE+G/sZxYKj2U1+lQi9EzEXvgAhqI49MDmVawWdj6MWTTovaTmGNOZ6ycWTly2HPFWn+hYRRm5CPZ7GmCq8WjVCIO/PQsSTHZQlP1X1aOZbBWtWzryNqt6CqIt37P7xzpcAJAMQDqnQ4eRXPTmQMApvxHCMGi00cY29u6YnzzpFoW9/e/7QgBHoujoli4l9lr1caln6YiuAHLU3ahnzDnO+3ze9TTqYOXc75giYlswi4jONgxFxMO1x7nJABDC2o0nRO70AGJzL8doX7CZujb4dnjA77eUej4njM9n/YsNvfx7ZSieVC49+y2M4dH3ablBx5/sU76k3kJ5rW63Q3baPVsq2coilHu+M4CzFuewbsZ326P9lm9y/zaiDee5l6A7yHaz9yJk4AaVdTM8F3vkA0WINTuimAy63xlU4GzIN/1obxnyUQH3/FZ8ggHmcRYa4doZb/BGzQu9gsyvSsWXQqy/9fY1vE1+AADy3lox/cpYfhNUz/N9m/8IHX9Pib5snSR+3tuPsN7vFfFjLt3pwD/3kgd93wwaW+m3m+riTTg05PnrLxvZn1fu6emtfqMW5aCWclwZFX2Dr/3R8jsNg5OXCty+ewcmwvLfEf/n3Ljjry1XGan9uiO0GL8vZBziMWOav7s8Rb+/d5a7el+tt/z72LPfWmXVOOPResoZewOg+/+Pz+Dlup7Lc3kuTy/PAPpzeS5/sFRh4hqwQNhuUnVzVInAirrZPOt94SmQCk1XCIbCKRRsFVCPw18K27Q9jIQyAA7cgATQ8OGM/qA85MJ8OewR2EEf9TxkoXwmfGED6d9qKAPMA/QXVXxgoEGh2sAsIBYo/4JJ31vYeDVlxS9kYf8+ww5eH3yc5FytsPn+s48C1+TqEBJfKfDlJ77ve9tx7Y4zUGlXDth6mYDMq6F7LsaJkYBWKNsvRWGo+cy/wnJJ3xYl2QORhUQrbW/MmO9eGZD6+QMAt8hWxaLAkQh3/n4RA1k7M46nBzRV3BHhdP/F8rUzo0GBwy36csLD70cQdVcAdtyW9x5BuIXnfNzoVKj8NTpemTERoTX7PxSCtRARlMOTxpWEeahTV7SaoruyhuGZ494uk3u7kCskPYe6fQ4Pw3iW3GvC58EV1nBlJZN5Zk8OMLcpPNEnzPMNmseznefZvFRhIH1rjLWvxg80QH8PtjopXkyTeaFaxxHMIbwBo97w+Arg3zzh1+LVN3hiBUND+O8eGWF4WanT5VAsGG2dgwY+6qb4xQMUgHwdCnSF+ZQrLAUBKXCXId0fxvMAOn5PEtmSC8HCwPv9Gu/HUJTGbUoQBSa3DsoRzfVBAx8tp3kDwYY5QISftX5FKGC/R30G2BXKZGk71g4Pqzz4gbhH8xl4Vjuy/TPadGVvw+6+MSDbe/fPc9K3K/BaQ4JqQK6DTJlAgEVQZaetkTuYyDz/DEBBLL3sBUWfc0M0QwV1r9CGBgkPa8oZAID0+ggg5VxThbFP5noHiAmyCOZ5BgCs65r7eSv5dEsLN9qx0Rb7El5u6amq5pXCAe6UeagpK8oP/n54X20httagDBxwY/QlK0TVUyuQN8s8SEkIPFnbWvDKyQi7es1cKoKOBDzIwPMwBoqh7QC4zTa//QhgAhGwLguYZoxdBWA62LjIqYxjHYYt3bbwUHQF+uo5oiOkeADnMRd9p8SYWnMvfKvPvG6BSY2nhd9UKiTDWYjIw4ZvOUgoRJmo0GXIeRuqgKpiFbEoGr4mIhUDUwMTMld98JTwVk7AJYy+yBo2okcU+nHe7FtxkWnDwI4SXGKy/a5NzaJEeHxqpQYwQ0Hm0Uy2ZtWjInGb/FmTP1ukZfBY0Kpi3vZgCME9hG1diwpwq8NpL2hTuq1hcnieAe4+m0yA3kJ18b+2zuRhAL22bp1ONTwYNY0EfCJtTBQu9waoaqvMTeawMdjIFAuUhnNV5ndCLUD24FrqfJ3DA9lpcvDliGjge+dkYx1GWS2AVB3h1YNf5P4tFt9BJwArAQeCknnNavymarTGk914OFlkAHFjpPA+d7RfrfEJwHaXf8yWrLS/AotxpkHwrAC4deTm9sgHfVkgzNAmEBKP0MAQX8PizzdPWbMuC5QtEoyEzCGWm73X3FlwehfJ5u3lk5iX0YWt/BFARKwdX165ViIKikXSCFpJwstoIqoMYjdykMhlX+e+eIb68x2U4c6bKtaQ6RMtrjvioNsZhMUpkqCYNeR2m4ubqfn+M2Tkg9Nz93assS0q0HjkiyeyNABsG5bJLmxwXITxjzQOtgwpjYTGuMQKVAwycz9VdeMzIYBHmPTwynfyCYqyXhLGxML4YtOyjiLCm5psm4ZPwVOBAowbT+putGXpICwqx7IsltaIzGgt6gnDBzPAwZCHFSCaENB58I3WwvggyInOZatYV1V+KL85Ge72yMv79NnP9Ohd2/V8oeR7L/58oUXOECgMteq+GDyhjEH01sS2uB4bXwEYoo5oF2/35E1/Nf6U+sKI/5HW23d2+ullD8W3x1FWgNpu9ooIWN5i1W3PlHsDrRjLbLFfkI92phrjamB2/xgA7SfvxS8QfLA9CCabRVtufvkVpw/mSc4wPc0Xsv9rK14rMOs7tF/dkIgZq+9P/TePgPG+IzQ7FTyPJleDQeDngXMBjF8Gys8NA76UdVS9iLnwxculSJWqmdpibs3WOTt/iPqJME0Np8UA1bXXnOR1zus+VN5W5JLtfW7MBIvuZZ7uyNznt4cDVBQPyxG1fINLnN2x2R+/+ezTSvUcf1miUJ6lWrtSXutrrPiIrzTmabcN5PWM5Fn1CaV8y7nmKeTZ4WtHX2N5/97e6w+eRbXcf//moD7tgaqD2D495JanlMqfFJcNZ/4pJQz1f2bJ1XWl3jQ03ulQz/QhXFMYfm8b6Wwen8tzeS5/XnkG0J/Lc/mOcs2bDhiKxosgelG6p7ARpxsK0dif3yiR/BZ2pU6cRBPQHKey+jnPesivSPiIAtzycIRih0gGe264Es5s09gBdoXyLQ60oaAIJUUIKW/VhNCvjfBGTZAgVbwV4AMp3sJCCisxhBjiShdRNQWlj9lrJXyiUPMOUKkcS7Kf0fC/UpT4cq6Z+LcoJ+x0DaUE0HHTJhzhyh5XGF0b3AcYrHgP4MVABQEifIKFeT8CqSwmZnz6/ICXrugwHZsBELc+2wYMknsKRqjf4TF/mGZLHyCK1swnsXVAue+UThaOnWA0eUuEkyuo0tvD62QagMraDBzgzL1ctDYUKhqj2/QM13FQDUA+WkEEtMbpZT68z6cEXiz8Orune4Mqu3JE8/fhgY7UXEbeVXIwY6Lw7rOw8601zHOz0OwQC0XfLFT/7ErDaZ7Rl5Mp+SQUvdb63gRNJqwZclhd2WthUZGgoOZBQDy8uvWFipEAgdbVvYy752peC4hOBgQ7vVj40b6ptx4yAvwaajOnHQc6GLcgEASCG/3qT906PXh43Q39XyLzF4D+nlTurLgoEIMjDSWb8VxCV0ILpW7dK0Jp60trzKc1IBXGDk6Iqnle8QB3wj9ExPirqcE6WgOwrtCYF39e04tqgEePlgsHus1Bj4piGRjrfnf/vsScxZqs4HmA5kkr5X54X83QYtDUJiILebt9zala/nFjRz67YoZabaLMMWh2Ku71ETNYwAu1gXZluGY/dWhcY8gMPJhaGi2EIVKLmOYJgsSzZOupcK6h7N96GtXjcg2dF3Tbxeh6gFQKeBqZoFm1hw10JMLwuC97fYwlCNStfZa/fCNxIBR7m7Qyuzmn6BD52lbPVz0xaLX6Gs1OxwGGLWiHGU0PWI9VETyGLXpD2SqUOavfz5UXGx7iExe82+haNvTcuBkocomeoyWx9aUYZXXRhlZoLJEyXhuDSZ8n0gDELcRxRAaIdWcwz25NmubcZKnYqOq4XGi/yPCKDyCisKKkueplzWl8MKKuGC2YLBk8KoylVId8aICif2ZLd6JN0TS8Pod61CK9+DhizKGNjzWwO+dLmcbBfvt6b2Ge9QEit0ZbJSTzmdJXjaJyfcd4g8BTg2KFrgMwGaL3kPODl9eww/We9F4vgG1IXlLmKMV0tS1WlEElhDew5Y+2r7D1P/cO2gCBwd/0YOu+SzeP9VXdSIl8P7d0ACrOR0Sh2gANebCAmqX6IiHk+EWEKS3Xt4NeCgfhcfINUQV148HcI+S8Amj5N9pOzRePdPOq7wBTeOyTgfKeiNp9+iv7tiYQRkCQ4AUbJh9fzyWFmP+t5yuSfmnk6MIwOqp0IFCtksR5saeLlEuxQo2/hDTGANbdiSneQ/4bATiQtUCyP8brc706X1uIMQOWOsCvh/1FlU9j3SMiDGXLCw/SAOac3wCAsMtWFmI/4yzo2G8BeEj+kDk60JPJjfthAJESWVShnbd88A9m2p2ZQ1aLaR7MWp2/Bd+IlARhMNpdzhIH0tVp15rkfY9w/C67I//GFhk8Evn2Mc/AZbLQaPnFcp2Svl2uvvIven6stfNL2+/l34xYdL4+H22VXrhDz648obGPVDw2jO0dehkSvMQv67X9dj72MC2/D8Ep9iS78hHwEO4VvBZ8qC3NFFkCYPnwW8ruJG/B9DFDtOvu/var1dCanWM981m2hQDwO0Z/f+55XveKOvJvNbzk/xrAbg9q/ki+7ceAMSoyZpeO3tdyPgBybT9hEV0DeP2ohjDkqin+Nu34h5UXuv1LsD3j6xOb+kZfA99x/59VXinQ9C0iRcH0boK8XzdGAH+IR/4Dyj8ZPP/7yoVB2Z+Nd7qs+Lv/fO3axe3muTyX5/KnlWcA/bk8l7+ghAKonF/ycB6KuuGNokPT5iXy6yqQYZv3O+Y4Djnw6Er1jcewe5R06gaYSwV6BEzNtZEj3F7UTa6sNaWkXeWNgiGUElYfK/CFzSu1MaMJ8IFdXdTNA71NLZVzqr+DwGgADr+8w/rfCxQfYBia4i2ADxSe6GMYafP5cYXTX1/+GqmmHjCjvFDCV7r0y6XnUws1Rk/V8kiCcHf7El/vv4BRcgBeKQ8YVLOnPwbwggidgBMBn798cAiTcE+W0yoOkrlcFDiK4oYAXk/g7nN9ewcsJ2BZMiepnI6uEFPAPaU5lNQBYoAydBrV/xLYGcordgA7w8wSl1XhFJcCrQPvCK/ZCeY5zdhvtQGgz/MBh8MA0K0+JLAeedH3hjrhyT304cMDnPw3cAmFTWR5Gh1Yb9NsSgyo5Udv0T4HYA6HzLkWIT1JYcChA7iAuBJEoAjP4ZKHLxSQKli77AwGTpimGafllGHc13XFsiwJiC6LW+W7YnGAO4q+CtIhXx2IgStIYfxUATSPPbDgdwgdLf8p1L2bbiG4d8Z1Bzbq9vl9AfOXvU+6NcX/V5/1e6dw1+mWPoe3CYVm1ulZidCFkkcZffvvHv6T4aFExULABuBBRCOmG3l4WwCgCNNu74zQ/UH7qjqMLQpwOBS4Q6m7KfFeXCu7w15oufYPlOuXDMssPzclUM4wpb8ZsYwdKP5PkN7pSkTseU9B0otRhY2H5xntezDVuiiexkHXxfOYEgC2kMFleGMsLTT4GBvNsfJQ0yWXtSnOd2PFFfamVPQnz7M4/EOJSjGIY1oUAiJOpf1GgbzxQPJoA+5l0hfL8y5qhgeRz1UU6MtqwH7zENzcwKro6fFuNZrnOUPLxCoUEzeIWO7XBPOv0QNQgFbY3K3WE558/3ZPTNYDiHUAGW1NUNLmUdIgIeaXAuQrIcNzocJ5vitwo19xLUr3eQyP4Xh2DboghmrH1CZIj9QaYSBh+X7NcCYelzHP/j4o0EPyK0BpyoV1HuHRVMTAzkUFDNtDzKs4whYbffUuUMgAdtTes6492zMmhIKEixc+e4jo2Fcsx7fuxombeUcyrF2xUM0AAlByecEFSGrNDLJ8n2WaQY3zOYXxAmXxvNoM8pQyAKP7s3JvMqTceP++Gp9rLxggATszJWFoU/f+tz4KFKwmJ+DG6A8K6HF45JPfBzUv+iHwOB2si+19w7XV+FajwadohNMn5/9B8833W4nINNQwQnibFwqDvH73QtcI765giPUvxTvnld3X3mSPsrrHtC9Iqh6UDkbKg+UXN37rRrrMmCbCdDtZ9xqDWNBlgWjH+qADKEzv6BH6nKJuxdiTwzgoGSq2dD9ahmwe3FSHhqe2SPTLaMJchzX5d1MzCmQidOkgZUxtBnGHdAW5t7yqmCe0+r6sij10VberYeC2XZ87B3ZAkR6G0beQL5tzvtiTRT0ChpKD5UPoVaDs0WMd1yg1IyKJC0O+fkOcj8gkBLX0Dy7fzd65U/A/3ycXMUO/2u4DAYsoJqJ876TqKbeM7k5QHNQ9pWnI1I1byt5JhwQz2hLB6rQStC5itKysLnOZSQwx5xklacX5fEh72hlSfFXNOGAYecNlM6hYBA+M/SB2s5Dvre5u0Qp8TSjXs1HQkH02cpeMTiLShwEqgL6u6KpYlsXlFoNQQp7Z0MrBzhGtRQt1eLiWM0ykbbl63tX4oxevf1fR0b5Lj1ejDTtDfM8rr9Q6WCsC7i2kj5C5gMFvN5S7B8+LnJavCA90Xy8ZYSLkuBj3lNP8zWfNLTKdU9M+XPumaP6D7Sf/pmdXzu/MYRvjXd8efQKGpzdlBKxPm3GwWj6C8TafibG3EO4Wyj2e4AjtHgyTFSxvwe8Y+l7RyYF3Hc+sv61o/+uALgp5PzitrTBBf7+igufA457mH+nT9R+/s5x5/F4p+9tqFKmnPBfG+VNJOxbyLqB+rjNaz1QufoZfVvNCz5wum9ovr7Ahl6IsHOPT+TR5ugpmk2/1ezRo1+j0e54a5VvTEAYZT5yuLNMvrlv5NDjEY+3KM2R8z3PA7v6nWDPAohUwgMO7dwCA5bePIADvPwIvSmMyN3tcuNbQITBdatb5fbuKmB4fwew3rvR79ynlZtq+66nj82eXNCj+0ef9r175fq1Uz3Mqc7s33q5nw22bv6+V/0Dbl+fyXP7HlmcA/bk8lx8o3wzhc+GkVb2Cso5xIi+baAXTz3fEAWDuvd3D6jqUsnY1LH5DSQBXtmqH50G3t4dKwcKZAiM8ZO2Y69f8vRHC0rzaR19CyCU/yP5CjM/Nw14qIMQgkpIvkMCNALGQgEzA9GvD8ls5yCnwhoCPcVbPo/V4l0Lz799fooV/j1Tz9Uyz9+0SSqfx3cLbAqb0XVfLcf2tQiA8QN3nF7glYOWGBwXu1DzDbwg4JfimOOhQUj24AuPWlXYHVRwVuCMAegulI3A6WkheAIwDmlpwdoNMjQJOINyCcHLhMhSZ8Te8yuGKlvgPcaik8AS3XIhVMVql6TiAAn4fNbRmHuWh2K3h3wMYNxB9zs/wds3zjHmePSf62KbjgBK5oUdTDBi2kKVAeOqHIUBzAJW8LaoCtBndQUhl9ZzkKyKZ4zQx1nU1pTfUcd7w5utQtBE+XcVzVO9p3ZSEbbI809Gv02nCNC2YV/M2XdcVp9Mpw9gfj7aiB9AHhDc6swIN6EU/xaAMVR5ecQYqHEG4MwWtqnlMAWB94V55d2A0tDeM9VN3WO8FSNm9hrbTPXR352tAym/kPMzjfKYxSCiz3SYI4b0FOFjODBbx/Ob+rCtNxLAhCNFQzZECyrlmuxJIBMpsHlBkRiCmPxkgOgJE33fiQr8u73WuiCh51jd37fe9HVlYn/x4rgmFeLtirRYFaoAw0JwTkdgLY7fR87b6wMf4p5dbCXWdB0/y/vg4pWeqFGMDddBrT+fkii2ycLsqbvDBhN6XTWi2eC/x8CrbyAtuSBCyQgIAXjfRMKjZGAXkWFEq7sNL1cBLv545W83ggH08LFQwEpTRAOU89LZVY+/OdQYHdRIQZctFq9iEKM55IdudNxb0oItbSngf9lWBiXx490YYoYDYzzty3kMeiPmP5xsRerAKRq5b5P0+ojoIiPyrKUQ8JLN7pGd/aLQnFFCbWCg+p+r5c0FDVhtkMAxx6nXUfmAYgNRuiwoEI5dztLUq2ZH9GJSjxtHLqI5353r1NRJ7J+dnG4eMAqJOT/6SXMtkuYI3XhOx9ohCGI1hyveP3PHBR3WsJ1+jAnEjA2uvQNwgxfiveeIbcGfg86AdVWSUCOS4wGTlQp7qDWId96mO0OxjLgbgovEh+zPuIYosSgpVS9ViMph5nLdImaQWdr85yah6yoTYdTxyBjeX631YefLGn5yXGUGMuZ8BOW2NjmLMQL6XOI9RUchxNfCvgNCWRiQ8cMe+ogoHnioNXN9L9kWV0Dj2CfvPQl+L7f3/j703XYwbydEAPyDIlORDtntm3/8Bd6ZcPqVMMoD9gSNAZqYsV7mqa7YV3a5UMslgHAgEAh8OVagbqhDcg1gUEUCLGo9U96K2Qbdu8y4AlC0lBewsAo13BT+NuC6F7uoautKD2NPi7+D1bAyyAH0DFMw3BD3nGEj+tBucbKO96LxFNUqXemMoiRIJwOYTZBF+gnYA4OBtnf1zjeseJWYl++1WgYXMUJqAPNNFyogwEFPA58KML2Vds+0KMmNpIpdm9z7fBCrjYfOhCT41AhDpG8aD9v7w9qcIqmBpwBhIY4g8C3i9lg5j8PUx7Op0Do985YZo0PLdPmX/GeHddcz/aK8CailKKPnJ+O8fLWfn4SSI8zuxp6erQO6lyig/aaMP+IMl0fLzioKua5u03M/UUqazJtH1bj+3DJHsz5VnVrCV6q7dMMb5sinF9pqtlOvA86Wm1fvj/CfurR5jqvIJEQbeDMYAA96HToacG29Z1XVdzZ8e539gCXlXVEpknK1RR1yD78VmkFPT7WRt/v8LES+vvX/zmXFxfNm4ZPWLQM9LBtN/uk7/VDzfm/yNb379d0HZznGnAOMNvtFfm3zxtQJN73HzX5MZHP7WESLIqzI8f7d3/BOc5R9b8x8vOraTv7XEOdf+vrYvXvI+r3//yPv8nxg14qW8lP+/lxcA/aW8lGeWGj712YWGAi81auUUFsqlcWC19zDz2WZ/Fv6JQlFZ7vF/zRUH6b3p724ABATtAmEFw3KQm0e4P4tQWIZPpIN/PIDHeH94QjYy7830hPIwrgpT2nwm4IMaTP87KYRMpfwVhJUIt8xQSfgS6//+hoUUs76DQNE9D1dTwjsoPhHhrSg+lcEowXD/1vJGn7Jg/uMH918hE23Vztsr9Wrkhs1fTQsGBXBoM/pyRFPBYtrgotq6XLv6we4IC9t+IsLtfIOpzdDTNxy64KTAwRXzSuYhIyEcNouOECHhAeDG36Nk+bmOqgaWU4PCPJdFHnGEexj72J/IwrUTBZBOW1qmcbClsg7DEzqMPBKQzvbotj62XK7MDUyTg8HsYLlfd48HC2ce4PyU3yMc7jTNOBwOCbTntHg/4t7gR5ZLUS1sKRXB25+pykzrHmX+3Uex8RQVzPPBPWfZfmfzZjTPaE2F5NQMPO+ey/XUQ2Ecwr3meziMHFghamFiW2s4HA7ofUXvgmVdMU1HHI+Pg6YSJBy52oI3Jv/0zxtRrMwG6BOZ4j55I+HoqTEPXjcnENgwvWWAGHirOPC/DND/sgIKNHoN0W8wj3RA9Zu/9A4Rwj2BnOB33m9X5WZ+Y9IRIjSVfnEAkgEQgNnC7tpA5ryzICU2UwpjICZwgBFFcSFuoGQITaYXqGXPYirQuRngpJvtkxzzEc/G1rBnXqUf9rRRSniMNxCEDTAlwOhPBM15kPh+YmCuptefecyOtrH/YYY//l6tOdWHglx65BwMgMPyOkMBdX4YHriXRmAMw+DwAdwoIb29iedU9FNR4JDTKaDYeI7nmI++paKR7FNcSW8evuXRsjdTAbOW08kUrGqh0blNUJEM49gBcIBhohG52dYSERpaEV8Up7WDYHPPQHpszfM0AAURdOomW0zGw/riQPtEDpD7fKzWCVkXKASqDdIFbSLwwXMYK2CmBebd1ci8vS2fd3hg65jb+I4ADNUAOQCn1cFlH3dxz5vwzBgeoiafEQxwD0/34Wko6WUM+FK8BhYSMHHbaAHDgymMGDeynBY+ugkz7Z9kclzdx6y5Ne2F908j17yvE/L5cI90AyqdfskjWYBAHprcMSfLwe6KXSI2T3cXYRkKFtsnmXnnmeuSqehon7dDWMwwaBU0Vgdk7b6IkKAYy8JCI9toyQPOPYB3hYigj7CsDHdm1GH7iRuKPGrojpEgH3SkJEnAazD4yPtsIG+kx4iP4RFMBEsIDZiHs3oO+OSZ8c5Y683joPhcOL02VTRiA/UkomAotHPK+IAZm9gSDVDc294UmBTUBcoGmgOAnnyQJgUwezh932+m5jKCop/WpHVxPmFRFQQERVegiyZgbkBhmKGMzVp9/qBhuuSedhcA4Pyg3dWM0GEhzgMxJ2JQI3Az2aiB0JnQ1CzPhAwk7UpgNSU2i68mYrAHElcb+AL+JyEhDWS0eL/uWp5RY3xBpqEUeZQc4tyLuyoQqVgUTmvdPoOAztaR7zh+/tp6xHubdoeO4EgWVcIinSvgBnB2h4pk/4Bon/0WQDo5yNy98gMRVlUoM5q3ldnkqQMbz1ph584VcR5ULB4ZRVWh3fafxjZ3cWYGHL4mZBQyxHwEb4txI193SoUfjP2TYfMgGudZO9sKjUwBzHFWM/4jKiaXUYcSj0E1YQ7abR2KdKxdRjoIUazSPeWVtXXpAu09SXkkC/L59D2DDyPyTtBQnC+SpmJMFJZ3HTEshVZ11J30grGU9nIczr7r1a/n7LbWcf7ObfkBsy532Fp385hkvf7AB28AACAASURBVAGEDDkunhn06bqTGEeqLUwB9awLZs8W80uDxrwd513Yj+oT/dNNr/K+s7uzP7HOt1qN0QzF2dM6ntR9e2OLks/ZCheNtz0ghQHf5qUevzHeeYQuN92NeviD8Q0H1NePZmLT8AH8L8Lp4292/bf39pgI1t9sTyEwVnxEw717xHvV+HU5zv9sqefoMox/uKgqOjpmtGRzwXVE1XgogN6NF6vvt93PKpnuIRvle1TuE1uaGGej2G+LXOvtIVXn80DEwHlGTy5+q3T3K8DzN6UKk1gtbP+z857jLaZ3E1QVC34HgXCnwN37D1AA6+99k1v9h2TnN6QxwzPodMI9lD7j9PEtVv2SvAx4AjR/Lv2fs7FN2c9A9Tx/6hVnvyUdeT3+2WVb7yU6+JmSHHXH33/4XPDr3fVsl8s15/vfj9tzqfzo+WrgPsSZ0N8PPX709WwX/qPKXwrNykt5KS/lry4vAPpLeSk/UZ7teT4eQGzDNJK14Wyrjw2X/NBUgaAUlJEKGbgSypQEAZCPY5fkW/2wrzCPHIRiCJZH2m9JLUIt7omeh/gUwr2v5XscbutBU6EgGcqQjwDuVfFaHfguQ8WutCMiWKCqd4B8NKX3h4b1owMufhS4V8Un98gMxXEVjq4pt351eRI8pxib/zsiTaHWPJCtspqiTZ4ISXelpAe5g3pMBNy+QX/8BhIDYUBkivWYSLZA/sqmkDrCMlWHUgQwUJyIsKilApjYxnklU0bdgHDy58wgxLzROQXpkke8gue0VVKBMAABvy9W2dHrYzgA1xomntDajMYTmFt6kAdYTsVrr4LoESY+rs3zIT3TK4AOYAOgx6yJmMdd5tylGKphoZoHk6Ikj9DCp/WECTMAsrQKIg5Uk1njqLhS0TzAoJEzXNPrrFJRgCTh5RPKZ/MMYTRmiEz+T9GWJY2GEnzz05nluTaPc+YA0M1jLxWQxGDt2c9UVzlBpyIkFHIApjcNzdyWLGSze20zN7Q3gvWLeMDV166UimP7nfO0iHXwPd9FTmvheRm5L5m2yjbZtE8TSGfhnMc4FJJr98QcxEZhP6C5kVO8P8FqmEEKu1d1KO1pEMdlvhQKRISO5hIX9X4wQ0soACpjbd/P3xXriP1i3q1b5V/sg7bsw4PWZ1djv4i1Ufg9xeg297auudQ9VOG6mmLc3xkpEVKTiu3YD8O5ssByXMZhGbL1CBptovRyzvamspT8q2YfUyFQx95pqCqNdWz0pTlaE0z6Gtdsv8IjQyfNAeJ9JnLwzuNDD2M5B/t93CMkZOS0BIbHvq1BdQ/31cKGSoydv4c9hHvtXvxHbae3eZz8fXZU6egA6QDegaEFhns+7WSBrNaHJnSQ+eodfQeAolWmUnV4LeYBhR6fWbT+qUXWg4FmodEer8imGX6i+WyMd7Yl26bnTfJ+RGr67EMh3zoXBEI6PudYDbq2vTKCaV7opro3t7etYexHZmcxnot0FR19LCmnexXzch5em65AVo96ULuX+wunsWd87ou4EQlIoY8jwXUop/O/GmuwSL20/XsTCrOAXClDcA03HoYIhS+EnJ88Ui06k/9uvFtH+HAfJ8ugYmC447++7H2NQkEe/lqdUUT0iQgdvTmb6OQe/DZRFh0hQHBAVjPQ6zLA8y7qZw/7W90rvS6upJvYG8tay7DIl6ko1+v2TFWJO/j1kOEYFjVoGPIFIG7K1EyTwmzezExANzNgcdlwGA/7uuDd62O9UDkPbRTTmp6aoBEZZxhkuoGF89FNbuzzYdj8UQGdsSBpc3/W43Sw5YGax72RxEFHXQACJM/3kBktERngPIXEEeNZ9oiQNQ485L6Ye9tKNUHKWNuqfh0uF6pCOLyzx5rKDsrIDa8iiCPEMPqp8p+1Q4hAAjBH2iFLDQAlSJkP2+d8OEQhtEKp2fmUg1fX/OYAoUFlTQBdNAxL1Q2MKu8qBm++MKyfh7H/5TnEvl+gipxQwgVdwpVyeZ095249+0Xp4k+/pNSqf6bNtg+UsO0+gD/X76jsOR2rMk2U579tL3WEbHb5t/07U+TBXia0VkTKC78qwN7zXMv9+Qax0OxmfvQeEqHYidLYMOohwMFzRiS/CL43/3fD8j8dQoPvEAjrb4LpXw39N9tPGNt2yVnf/xnll7aJnE6DdspRIjV4ft7osW+nyc3g+XXtt4yCtD8MlD446TCPc1W99bl85N9RAjyPnfm5Ife/4AtefTIQ+zu5NzjeJmjZ8fkv9fx+o8D0oWH5+BaKL5sR/nfnY/8nlj9Kgf+UUPG1VIkwrPoutfNHZPBs7/MXenopL+VvLS8A+kt5Kc8o+43v+RZiwwo+wRLgh5LCtQOUlrYQIociEjiKImpKtwBuTHYmdPeLJJiioIt5ojd1TxYBhl+eKcW4Nf89vFo8ZLCG8iVbVoRyOzKJK0LR7aj0KYLzyVagCJB5Ibii+neQKFb9BPoINNxDAXyhz3jvYU//1YHfXLEcylfy41w9HP6V5ZIgH1azX/4NAs25h2m6Ej75nLrCO4IKs4MeXRWynHCYD6DpgAMxlr4UBam/55JgSIQjEW6g4PkVpjZ7yFkA0wFtPeLt/WtwY3z89DVzkYInyHIsfbBA3ATgxpWcESLyoKbEXeJc6fef/HPxf0a1SGVrHF/TK5cGsG46LPcIQVF+DnVptsu8Qyxs+0QNU2uY5oN5aNPW8zw+A8QbAPq5N7qFOp/ye82tDERY+Oix5ofRvRqfCUVStJlGyOhQzBk/EUCA08MK5iNuDgcc5jkVeQ0MEQPbSQRrgHMBdJB5D2UYS1XH291LzSYMFfhXbiARsIPg3CIMbnh19pL/HBBxpZGqh2r1PMP++wLFqoxbONhAxlOUBNBHvCKGqikp6bV5kU4tjBvMw3lZF/S+QrqFcp/eTOhfDKHkV4z+TQF9VcCHh6EUjnWEMR3hLQo4P3YwfajnkYr/2BssTLsp2dXnLO5jDU+1Bg8lAqUtVRK2PMCiMmw90C+F/dqoS3cA+uXiv8de5PczkdOdJpCaKnAitFB0Vw9N/yPaXnOf209t8w4C4zCZF98auQNpeIyHYimMQ5qvg2maLfcfE9o8+VyXdZUKaTJFdy4qyv6AIl2AZg5UJeOVqfwGirFFDioq0wxf4q1CbDcHOhRpdnH4rYXXcxizZA5cW9DjOQcwpnkGnMYBoHfPJQ67r5GlLBjrzcJfHw4HQBUPjw9QhaeZUBzmKV/HHLnf1XJDI+bA60fkf1PwxBkNAFDIyd9HERxYAW0GdmiDLCcoGtpsQD0rQTtBF84ckRCgaQOUseAIQNFCpavVB3aE3h3rZSijA0iKsL7kik6xhWZz7e8ckcYvyxrX5I/FjU0O0zTm1fcz1WHI4KwwjaQCgO4iuTbCg5Up1iG5MnZ0MLzQLf0IPCwxJd2zR2IZIUVttJZltesYxhzwKCwCdRlryBWRmxswo6Owl5jgfHDHSGpkB4WC+wAsw9jDQqpLAm4qw8tzM8a+7kaUGEbjliA6EwN3xn/kQZIvpdzoGuzgVeo00OMNAaDTkKQT9M6tdQB3Y1/GkCssGbjNb3iqxsQWeR4pbwCa4b5H7vOZgFUIJIJODIIZAXXxOXF+qKsAa0Q8UWiztpN6+ofmdL/aultPp5R3FAAdCH3tFj0DOnKjUgCH9p7VQ3Grp4IJ798wtBuh7n0dkuW5TiNe77iOP39QGGbx43JD7J8x9xyyxvaslItGfU8mA9tV1dOdWLSWMNAd5zY9I16l2K8x+Ha5hd1gC7CpZa8z5M+aGIuZALFoNRT1YvCjPB25hQR5n82omvxanLzCwHEMpuxc0dn/da83aTD27+BxTtoa/MGfbxwS9jYaWs4fca4FQfAb4w+kajnPxeiHu+VAt3OGgO3wafKihIyuKGnNbeTUDRIVmWc85iXmg6MDMG97VrOVMAMK9XFBJC1Lg7CIeBGezhZWvkMnAWmEXLac5quD49IFa18zP7044NVdhu2qEI9YEut+CiMCOD0qwLcemYBHail2Q7Mc65Dx5doOsy1j9mOutPCoUZ7GHwgbwqyfW/LKC4qnf8/37n8ud22pqxgl+f4wZFRPHRC81s9k1q8hXwG+T1Ltv+9ffYTq18KTt50d9T3bQzKGjWp/huwwNmr/T+7dtK0AQB47hjXV/o5yTZ+c00s0YG817/OOj+NGN9KyLwPstuo/gfD+rB7xFEJNrU7FJ+/tu5GPHeEsMahiO+//vrL3PN/Pxl7PEkZQP8otHRGIzBN9nJG09N6My21P79rP5zHPCkX+EnGeZxExcgOM1e/0F+B5GNPO04xlXZFRbHbvOiehy0T1o3XwY061La99GTAs/Pnhvy123PF/FhC9BfBlc/9To/5AANEXvNW3ePVfr6BqEe/ks/xhEPs5j4UecP34cegCy4PPqeO543atrnzts87zW778VH1B7xHRK+Y/bA03+pBnlP262a+za/R1TQ+fe8X2o/z+dPv2fOhn6Tf2+THt24bkeJU0jPnuovOJzx+B53kW+QH/eSkv5aX8uvICoL+Ul/ITRatyupSrgLofhiK0cFXgWIUo1tzbOqsCfPtD6N22SkxTcFGCGkqh7KEU0ZEbu4ECUAUJG0AgghUrGiY7N6lCXUCy/OQMZT9NaelveAGo96Ee8vLEH1a0xful9OsrAXdFKGDcQ9FBfmBTMsvodwr8ztaftwT36qtgwd7fuxwk/ybZ4isBr/+eV/3yQkXks/+7Aky6e1S7QtWBmKeKgZQTaJqh0oE2OQDKQGsADqnoiHXA1Bx+qUpGu4eJsTBwmG8ww0AgcsUcHCgmQtIAgXBDhBMhv4f6D0lrw2MhlNUBNiZwniE3a2B4e2XjhokdOJ9sfA7zPPLBEidovhlnIg/VvvVQD8B8mqZNaPcEQhFt9ZZQ9sivOTBXlEvkPw6Bm3J+QZFL1/ja2lfoScGNMWU4a7IoqUIAMxoapHd0hKeaQQ+htOndwnMGAE5EFlXA40KHR7DlhTY6aW3CPBud9X6DdV2xrj2f772jdwOxRARogxcHrTV2nhUKSbKc58AtZpinkb6C5+C1eeOp2b2eA345LWbJr0CXDr4ndLF5bvcW1n79srrC+hbQh4uHq/bmLfB1hehDXREX14gW2uPw3AzgLHmXolPxbAOB2LUMbthEKDngc38ZRk1XvdFRDpR7hSOe2Nvi/uS7g87QPEpAUbQ3FIOVvNf7UtqUynxqZ4dGhLLbVr7tS+qOhBIrQZOuzHCF3OAk1r2FZR4dD76B87ZZnFz3NIu2DQVxAN262c8GTe5DaVrE2Rgr+518nuJJ1dg+NdtUAXVRATeGqq0L9XcNCA9pTJDtiXC5Gbra7k1dMVHmRk+a1LyrkoTRGY9Qu9GHrgpWBcIYzztNLpOoV8LJgyxvNXxEoy0WVjLaEQCJAQvyqJA+vBMD7Kkjrxf+HrMSAzzkpKpNidmNPWUY8QzgvYo+2L3jqXIpvKUErW7aBoTX8wCCihyj8VENJc47PgAbTfog0EYjHPyk3pPtq/3c99lluIya4ECWskU6ChlzQe5Om/ew2DMm3g4zmxwDGHV0NUMYM1LarqegwwCYiAl8bODGoOaeyG3wk4QjXXlsxqxbKgkQTIlAoplSZoQ1GK75RLwdothWKfbjQVjKBmaacVfhuU5nTOzrQx3M4+wTQGiwcRC1vN5dAfLwS6E7i3Za+gID62ffJx3lhqBDtRz7h3ietA8Q5KhQFtBNpGPoZ/TUA8QLQF1G6oIIsR8gb8xdcKSrIVjLucho3nnHLndkjDE3uKw1DLMIoeDVkTKgLDILl+/rmRjAWvZPWIqQRgjUa/ANpIY411FMZMohVieXuc+59DZr8sC4xcZpnAs9UUW+Iuh3w6qwOUdGU3Jru86VNKrU7UmJAawcxgGUILWNge+dbNcoZA5//xxtJCDM5kKuBFwu8/lncUNM1RE2G/ZbTyDHgMxGBMh2rML4xfa4oLjgz+ppxcZoMcjSfCibkS7UMcFi8B11Bu/0hWHAP6Cdk2ZAJuOK9AyxPLzpjdalS/FSd6NJlRy78U6ft5v8K3nwpSm8Nqt68Zexe1/cB8s9f6r8dBXjgR89aqS4T2cX/JPG1yJH5l2l8pxnqt8uv+/syqV5OF96Pyy77Xu0Q8fadrZX6q6e5JfqK3xNz3581rRUvhJ79eY5idVZ6oumq9+QF8v4A6DMlR6f0UvCeNs/t/zJlXFWMhpZTr1H4Ij9LCwnUWSrC4VSbrOxb74HBr8de3l95vzvTNsBoO/zfvwDSpGUAAD8gdF//3Tt9h/UFXIZQz4r2ruGu08GsP/q8kqB+f0H9N8/bmSdVwo0vMMX+mN9+KtKngP/z5bKxf79xbaZnbQW+qpYo09sID8Lnu8d6F7KS3kpf315AdBfykt5ZknPlwLc/KjkcbhKKLQTDFMRc17ntXdJHrLcTl8F1Nis+8fR0g/tClbzqAn5PDyB2TUuXVx47wCwgrVByRR2EVeL2fy6mCaQ5zAHMPK3ig5D9TC5plCoBXg+wkKqe32IuYDiC1OC6EJfsNJqHiyuQ1nxeROE7AsB92oe57/lueyfIQl+Kwfgv/NYcifA9wy9O0J8DfHqXH0CwMHMUGV7uDaynK8GspqC6NWrV5inGd8fvmGVbsqgUOJfKF1WUCfc3tw5yNkAqAGo0x0+f/oCwMK0swIHM1nPvNkEZJhgbg1dVizLCa9uX6ORhXvs/eS6TYKHXUglxBHDyy5BZFc6sytmhkekKzczP/oI6zyA8KK8IcLUGt5ME9ZpwjTNmOYZ82HOA24UC+NIABjMIUCbd3qEaW/uEV09tVM43oEvqrRhF6GOIGqmbEYo/CmVoQmmAyPcbAEMQeZtrqJ4fDziMFsY99d3b7AuK5TVADuPStHFvBSJGad1MeXharkfM2+bK1pZOHN9MjcD2lBZn3kIiwjWteP29ib7zEwOqFtbxQ12IrL9CI9p/E1daQ+9A/grIBNEFdNbG8epTRaimDmt/bkNnrqulvddPLf41CxoaZvMa+2ov4Nx52oOH068Br0mrN++AgDWr1sLeeN3Ro9nxRHTAM5JkcBi9TyiDW9bEbE2qPwvwfhU6G8Pa6nAsZikZ00ZbGsoty7tPxuDEN+jqgfzJILOjOagKo1bbby8ztaaAQxZLwFoZxbpBm4wePbICx52tXH4TAIgM7Iwj3HbtAwsYHCz6A8D9BWodGhXN+LZrjEbQ3Xw3Na/smYHnNyQnqQ5Fsj3aox/Xbuu8Ix5i3QEW+OYiBSxUwZj5E6VvqaRxXjnVlYIoxsbA/vP4eYmvdtEBcuyuOLNxouI0JhsTZB5OKsIpmkGAJyWxUANapa3lS0UAnFD82g26rlfRbqDFkMRaM0Lz1FGZ1tjJG0sEmf8BEB1BlQgR+NnpGR5aWersOvqY2n7yqQHhHcPcMp5aDhAcARjdkzvZGthshQSI/8vJT/RxbzwCd4XAOBm+1Tw2KA+7+CKbZaFa2V4IOcFGx8TmFI5LgIQB1CO9BKPSAtEZS1S0JvXL0MSNE9syiUvIkkrRPBIINk6bKXIOnf1rghVDDCaewbHPhsgw5aWw0MzANYmBTgowzHGSEfYcWiuO2t08AUqe2bzHNgtPZLT0CLqdJCOMMDCAQw4nwSGocQY3pIiJVIh+P7KNP72OYr3qnrkDZhBF6vnP7VBNGAOIwS1q89NDiIzFFIY7TMZ5yf3XI72tEYZ6tUJAKowz3HYO/K4oacxN/uBd9tYhSnX9eE4xo4i7LZ6DHkPMatIULBXOVCNfwwfO5dbynzHy6+dpgZL8M3Zw9lTyDZwA0iOuXO6p5ALJIGIAP6zbjcKTFmPjY8QCBAZAFzspbTbj7n+nAsZ1Qgsrye9lF7ToGWCWFqLPmT3MQLY1JG1lgWZyXzcqLS+wxlDtC7/u58Iax+PJnvFlAasPlZs651LE3NYnB9ETu/Jx77D9i6RjkUsQki0KAzi4pxh3zyEMUVztoSqJVWKbWBueKjwCBnj7uCzI3KGjwGNVGcRtt23J0QUGqjNe18FYJhxijNoUfMstzOIyYtiDbB1IABLc2OBFQqXv6JNZU9MIyCf+jAMSp2Dn7G5yF3BJ8LwaSu/7N6Rz9Duu4928oYqL5a1opUodIzTRcZNg7788xoIfK3ErY1bzlglzK1cWs42LreajqGuw3hupL0CjF5R6trwh9qesUHsru3HKeCyYuia/w3JkMZzbpER7w+jlboOgNh3NCYdiF3hwrDG3hE+DPJRd7+XvQ3bqesO7OXI6j0IDMHv2Q4C8ImAtxrBIT6D8Q5xHmn/sk/+l+118rEaSsbnpxwlLf+u7QPPLW/110T+25+bouy5cooIV/SB5zLUmGdVxdptr2rOd0VGpDLF2IMGqQWtu7yjJm+sfXXZvUGpmXEPUNYEZSQ79g2TMEwf1l16vucuVdHn3vlzJWhhev8eTIzj/yxoHxjr7+sGkP7RVNf5+0pfQP9rZ732ztZnwz2Az1fn+6xdtb/ngsyQqVWx/P4R32KT9OfM4/3T2f1XPayvtePJVpZ2XKlx0K3tM5JxRy+/d/++fc7zfT+u5kQv9xEue2DX9/dd5MXaL8V+3PRqfdfqj0/Zf1dFA2345JPF21HXA5W/tnRDV/nFpo3PuOfs/t2W91Jeykv568oLgP5SXsofKD8SuM6u58EHSCEmc6v+6PB2JqWlYikURaZojDCcknWGkFyObF5/KCDUAS6BeHhEXZEhHi1srOU9ZBZwZ7QWAr8r/Fy6r7lHOXKquvJGxbxIEG2N/O3xfiI0YnwjwkKElQlvZeTWInVmVcL5gQhfoHhX3jsszDUH8oKc+5eX1+ogOv2ag+Fzy7MFvqvlvIIAXBSmcGitoU0TZPF8gheE/wD7zFOpo/eOeTqMdoYmfL4B9QWQjhkwxeXUPH/uEGuZCdN8gJxM0F/6grnNmJxWLDRxmXPXRN0SMpw7keVkJ6cx0PBgC8HTDqaWG3t4r3KGYM97PGToNE3o04TZPcbneTbAlYZ3daxTgNzLnDEF4D7NOBwmME8WXjoUwoV/pOdXKv+tNPdCHXql6AcNED0Uc6GIibaonoUqjKVjh3vJcM/4qjjMNzm2jSd06db3vnj+UwuD2PuKdV09V2oB0MlC1ZMypmnQSKUcZhuXw+EwcmMSYVkmrOtiYYXplArDOjYUgJA6X8UrAO71R4TD+8l4mRr4MPnYxXhI8dqaJjMQUg+TzQ4oinsbza/vId/WzYFT8Q367dXZOtisibz3fL04hm7hr8kNDsq9RDCAuhwguzoOHuFIybwuI4T66BFyntnnXZQtTHwBgGOPMM9HM2DhvdK+9PhS/4KmFgVmESi3BOsi4gA7wNlaQ6g0rbbmSmwHaVwZ2rh5nlIHT4YGNefc6D5yqIrBIExY1w4gAGpG5PhWMXBSVIHeE8gOULqutViK5Os5w0hL3EOeg3h4qFUP3Qq619HS1BpSAoM0LNCyT1GHiCnxA4SErNv5daXcWPf+k3Svx7zPIzx5hnvO9jktaBi4DYO4WrqIG8SY6sU6HAq4kG3GPKnC9n5gs0ENUNMD2Yp71IaMgDC4c8Wrjrl+ggLPG5y/HtLQBg5kENmUd5ixAXnFoVhPm4l47xVFV/xMhPQQvnhfQRwIbviDARyNzpX5FIAoQo/b3fXFEcZfaQzMoIPxN2nk1lafHyByo0eLhkI+FGBqStudPBt7GwrPEmEoia+l0OSUNuh4ONZQV8upDB+7uCW8tKj2NtpJZsgUe13sWeZxzohw3pHmZfRNseHZQ4A+0zply2l8R+yviPDKlMqw5kY4GV0hFakxPyHnRn2BypOPR+E1WtfGpuMlSkT0fezv6m1TdPDE0LUP41YXzhtN6LoCC6DTIOeIeKES+0zhB7A9QwXw+OsJpI91OvYSdZ5GuXA20zf44UZhW8ffjZe0LrkwGhnDRvU5tbQEnSzUvDh/VRoGExrjSvFGzTFj6vC8RfYZnthBIvs2xvoEztYGe9SAMP6gQsv7MmQ9m0NmAgnG/G5G5RywCM6R48IjRs2m6LhvzMqWj+R9WowAeOQ7JyJMzODkFzYGcb6ECDrG3idAng9EFSvc4EYEkiHpnVVoMRzxNc8X2mm/xzkXY25DxnUv8e05qNKSzXnsA4NFFf5UxjT5qBpprB6K3XLXG+BlYya5h6tIpqPa0Lj/2WH7yqDh7RoJutNAQDNfwFO7Gwa/LPOz9z/f75BnFEn7L3r2Z2WKtl/uZunaNnzl+vVdu5pBIPu3b2wajNb1ste/nC+9fGldF9fu+aPl0mufvkvPGlN24k251LS6VyoA+RiA9ecLd18vg+IIit83TVSM8NRRBJ8cRB8yWv/N1up21kYahGv9eN6YXS4BiP5Tyk6qGzK5FjnsKuK1X7sh6zCmZofoNs1QVUzThOPJjEIFcl4TsUc1GeeClBOvyLT/zuJS1DC0/mAy182/Dnj87Y/X296N6DBEwO/0a2lFoXirlu/8z9Dx31FSdtGQPugCl/lr3//vePa55ZIR8XNK6Pr+TNl7l9e/r13DL3jvS3kpL+X55QVAfykv5S8s++0sBENTvlAK0aFgA4bCyHQP9SR1vjmqYnhdhgDkyvJ4pPp8RG70fFdch+XYFTHwe+2WnYo6mSc6aYKIIgptk+WHdmURJJRJ1svoY37zPgZwHwpqkNstt2YeAtLAnhv5EwvuhSBk7WQF3ivwu2tdFIoPagqJ90pYofii4/D3VwhZ+wPRtfKt3PBXteVSedi3MLUp1y0zN20jIJS60e7mh7WgxS6Cm8MtmBoeHr8htYybSj3MroOxj6cHrH3BYTqACJgckOVpghLh7vgdgNHhuq64f/senz5bHrbeu4Fo0nFzuENrjIfHb5C+4u7mVXouq/axjpwIjrBD2A2AhQknkOsFqYA8prANQbQ1So9wA83DU5wRnujxPfKVtzZZ90oH3wAAIABJREFUCHe/P7wCDY8Li3FKL3MDiucE0uNdqt0yIrgyTtybSiQ8um0ODLCw0OMW7tKnLxjMZj62xyLVQRepfM/DfAEmfC09Hk/gNtkRq9kLmOBGNRN6P2JixrJajuV17RbCMq3gCa2pgRpK3qexSkNhy0RpXHBzuEF4hk3TjGU5obUlx8IAUEkFADMnAGY8kUCvGV++EG7wDfL5DiqK6b4B3fMaE2GeZ4gqHh8ecn4UhIns3afjEbJaP0Qs12X/tpb1/xqmsngA8D15T9FRGB34LNz4b9/Lcqt98CSdZ0qQ4S1pYYXJc1RnWFCLsQ+Q1bMH06KIKxrZweItUEy5ZrNtviYs72q57nN2iGsDGdoqVT3/utpCBrrXGVEfpglq8fhdCW0KxKSbiSEkmCOvrUqCY40DlDeNM5FFOWjUEKjHPJshTiP3svbQ0Za7NLwzYSkmQAg0UUOdr0jv8B4hWgvAi5i/ALZELHx9mbc0Vhtaye2KVDgYPfZFRXiVbXO0m0e5FjDV19BuhyEybzliAqMN3t17GlFA3ThBIh96zDkwpdHU6CMAzNNkN0mA3gqkIaB5lgvB8toWQDr63Rq7AYcD1JMp/Nfe7V0iUDKPdzmphw+Fe6oD09QsB7rrmdtk0SXWHmG+4TN3qq+FQiE45ViRmWtBFjMSmuYJQgbCqfSRToAZuqxgHIy29Zi8tcIGNMgfhOGFXmelgl+nbu+dW8v5NNFtyIDJwsMYRkwGU5eHoLtQ2KppTBO8mzDqjNDC1pZtGOGgpQFIV0V3mWPndqSELq68EfeOZ0EjW2+xRnVH7xtjDZ/DMEUK3mMeWDaSMytUCbK6h0wBI/N+b3fmDvY82EMejeGhpFPNa2Pfz3YBUFjKD44Zjf3c1wU8ek3jyHdN3rahoCbySCZi4dQJBKaWkWxoQ51Oo+HhKimx5zzEPXWxNvItgwnikTJubxuOj2Y2GPyjLz7u8+IVEeQkKeMpkNGeIjS2YgD7yZt126oAz6E74FJlM8aRqiCAVUKE778sSYdUEkYumaDCJ1XtmIMA/S1HuxNRGA34HCiAHmHc47xCMFkk1h4zqIfxh9F3iJHRnqgvweix1EYv1O+O9ZzjMaIRnGF7FIBxATiymbHnXpPjh7e1KtBcPrgEiuS+Xdtb2022/5AJlps0Lwn0EKMzcPABIIz6FLZHTrG+vC4zTuoWjSA6Lx56QuBRyODbr8uDbHnhZ7UwQyt6gt2xLwYtmIFPRGtSH3fOcOw+yBDAvMowZGv2Z2xdeVB336xFbZ/Sbv55okMe6AVYt+GLc63NSKSdeFgfMz2SqJrCLZk7ZZ/0QSB3EYqZ0MUivHGLdCvXi43HuQxg9W+oM+d/Q7y7uurFPAWOhXD+3BV629Z79qrz33d1hjMhpxxS5AY3wMAGQBg8/LInYnC68y4ptg2oe/umnTFs+3uTJ1P5+1qfFa3NKVeKdmQMpo1ch+TfIrqrobwneHBpkOIyeK67dj1FWbZN7DzS/bOVuoJ3iBqI3j+a08UWyL6HmVv+fvFdwUM+PU3qT5Z7HZ+fn6jnrRrQ/ukZ4OneUSbHrc73M0rcFk4BlBHPtvQ7eUox1cXk0TzbjIEOI30mxudvn0EE3My3RkfUUoaPnYPUjURD5lPgMM1QAKflNPb4Z/UEP33vz5TIfR71iwjm+eCp2WAyLu7xVm3u0sM72rWbryh3Ua8quir6Z6dRv+05HsFe8XiPFrrw994pQfH1rF1nHtvR3qz2cj+uNmP3/LXf9/QZ3w6tQWERB0GEx+X0rPf96Hr0Y2/CcTa+zxzv9gOPcv1BPWfjXJ8t3+NTNCLDUcplTzdAy3M/nsc0TnxG+VkP9B/JCS/lpbyUX1teAPSX8p9TtmfJZ5Qf3xxn4aHwrAqS/Xa9vVbBq6EicVi9nv432lRsDmspVuchthys1A721YsnDz0bjY8LPQGamhuKKbCYsCpAIu6J64KjkqODvKmOPCRQaL5S0ZltqWNjrbIcdeFBCQu76cpZbaGwIqxkIPo7LX0jYFLCCXrGzMwXH0OxcCYNXbEvHOff5x0Urt5E+fF8stu/9Y8dVW5V8Uj1+aeJX/d3OMjFnp9bxfJi19bM04THUGZeUN8MTaArpKRjWU7m4Ru/q0LJQBUOzRYRjscHEAHzdMC6LhYacV0h3LGuhMYTRARLXyy0aWsw/Lx7NANTtqQQWtZPVbrHT/UQG6FgW4LknCHVWwkRG7nK52lCmyxfeaOGWGDhwR71TRMneB7/tnnOGeuqUI18o65q1pFzMYrE+lAOTKGqh1IJaKxAs54NPZUDIABQY0xMLuQzOroDI4xv376CQbi9vTPPYRFMrWFdBfM047SccFpWHI8nC+HuwAEAVwKax/H2PLHRmPkcxFgNHmfjRAlITNOKvnY3KggQNECJ6L55CREIjyDcARB8w/rpNfDK8sBOU4TAttQCy2kBDkEfZijRpoZ1sVDXa+/oX/oYXjwAuAPhe9JXDUm47aErQuJadZEKAEIUFExrd24Mb0nyEPv2PwGIHWzpIGaLIqJFqR7/QhFjx0Pji+LcMfeL6m0GJFDhdY3c41ZmaCowfUGP2aTguxoN8FSm5OFd7TfLWz7y65ryyPtDDKHmh3wXVj03beTyHudrV7iSjQ848le7Ala8NSUXeIDhQTvMZa/wOtWSnxvwqEbTA0wCSs4SA8qgIz2BFkooH5R5vccEjbVens19f4BUVaHmvzhgFAqa8jxZePtzfxSfq8wrTD4eQHgzr0ZJDmZwyilBD10V3EeIc+PjcGVdc1om86akQQ+iAWL4npDNMc/Z6KsCoAPM+1phUXEA9EUydLLCFTUdAFmKCfSW3YNPD+HgHPDg6+boNxyh8Hy5SX+hZNScXpomoF/gsU+U8x1cN1t7zFPyKwej6hYdS0qDLlQLcBkKQWzryVEdIONoCKXcVJIqbNuqQ561ignph0HnbY8Q8wAAYYA7GAy1+NgpYY2IIqXuzUjFXkxlPZpcuKpgcV6eBjvetrp3m9w5/q5eGrbuYqkUWXnzduR6s//7HpvCbcllzR5mOSPYRFusjhq5o0ayIJdziUv0GxSPblJTzquDhGXMtfwVYLS9ixEplYiAZTEgWAJkhBmqxNMEpHerJFlaNACCQieCrJr8sfYheHl4dsfeEu0ZO5yN71aapWz/dd2ghbsn9XNAIfLgVZyEZFWaUbBaGNrVDcwszjhYR7+Nt/gcRqvI9yNy2hEAkeceZ9vwCPlfFOJDV64wuzw3Aon37tZo7PdJ8wr3WB6RIQY9jj8256xdu4K+IYQG2YgX+3KRf/n9wsWAEjaOze36pmKYF+PC2S7j3uxRWWKPFQW6dEDFDLSJIBrPjx4xAT2IJdetr0OKuSPn1pzMT3vwOM0FRvBrZXLU0x+ksQeCL1i9YSxCOwoWnz+BGbACJXKNn68INK75OiCNsz1SjrItNwyR/NdMaRAnZS3K+DK3SS5b+aSuZUSf4h0bHjfo/dK8a77IL25ANRpyTlzbVTt46vVy6dfN3uMDT0AxdKEcv8L5/f7Kn7e8JslIL7x3dy3/pn2/z+85lwFSCtvsITGemzms9SlAzOjr4obTkrXRpTaf9UHP/tTSsgDPz/pAlTtfqLb06uqr/TOOKUlSBKh+uth2wmco7s+uh8HjU+97bvlM5kjBDrDuQ7nfK8B4h1htbxT4+ite/AdK7ssuoI2zMcUODyPUQY9mi8+uD+j4fvqedZ0WSw4W55prxbn6GRv4Ib39TWW/v7XWcoURgEUEN/+aIPIBx98/PqvOOwUYb0C5r7tMiq+/rN1vFGDcQ+nLP2YsnyrBHZKu/sMKFV6/uf7nKn3We38GGH+u9/nQc/58s1/KS3kpf6y8AOgv5T+kbFU549ql+649t68jDuexd8ZGduVIUPbsUNj4U3mC3YBcT0hie0FTyYFoDU8X96CIMLPkyn0KC/wKZqsfrMi8BjBCUa5dUo4XZUzNBXAQgMm8fVwJZYolUwIxt5RVTZkR4Dwy1Hse94gwmSYA0hgshPdE+N9G+AzCGxnPp5IFrib2E9jsoUg/EPAxe2U578IXZjucdOGvXXlSEt4fNbe1vFU70P275JlHV3iEYDUA9W2LUuFQNPEEm0fmhnma3cvQ8sAyN7/fQMVpmrGsp1R8bBQY/je5AkRUoWReqP3hG6Zp8lyTRk0CwhGKWyiOpyOICIfDDW5ubvHt4Wt6vhkgZvQd+bDF3bbvmEHtgLd3d/j4eWvtHkpB/7L5TMMPogTHOcLBEmPkVzWwe24T2tRKKPYG5smVaUbZ4dE8TR7avXzG9SEA2zFmXYHIly5CCU6Idrded/BMyXO+82ZKU7Eex3AtM+KKbvUbA0iJxyc0qI+D5TeHGTeI53oE4URHTLOFng9DGxWgUcO6dvR1hXTB6h6W5s09oXn47sYW7rZ5OPygvWglU8PUnDP4uIisqdta147TyeZnXTuYzTBjKHGCJx/Rv93g7Zs3EBHI1w7gNYQkaZjIQnz3vmJqDZ1XrEvHNFsI/wj/bsQP6Ne9YkMBfE9rf6PhbdmYnGjNtTX4xwhv7DdEfNB9IUBZLd+skufTdGAKlseMEV6ilcdqmXOAIky8h00V9wYjHz9StnXJNh8APEMa4SZU5uQKz8grjp2CMN6vxTNqsBhAZwtjuprBi6hFFWD3OGcolG3/EvW0JJihCkw8ozGDJzajnnIQJmbz4tQS5h8B4Enmux574DBc23sHJpjte2g8K2VdpVKypEwJA4fNAb0yRwvfYHu1DA2r0bjXG0NWPNCr10ObJwCKdVmxNZdAKtBj9qW7MYIM4Goobc3zO0BG7QM0C097UsY8zQDMsAlkhiwdhJnbBtzfhKwXcflBwI0hCkwEELWx5n3RMMzQZhWgTS1ptpvTOKYb8xhfHhfooua5nuMC8OGAflqKrn92/nWC6gmEQ/a94eBRbQ5QtRcsq3nhTzlVIfRMgAKrHk0u8pUu0K3CH0X5rZUPJHSHkUxnlGPvqdQjAOgDnmYAh6lZKOSI5tFtsCIkp3laqnlqaOS8Zt8rYWuZFMvaR1YeeHhCRYmKb//zrQvse20iev7ggHGDZq2zwnHNZQe4sYTT9EgXED2Ptan5jvCUt4gXzUFmj5oQY1TuqV7cYcQTRnBGhm7EwW5I4tYcO7gD3uzc/wGPrKCK1d87MY+9IAw9axtoGB0l+OhrSFSsP4VQhtHcGB+GQIU9/YogjWo8pnfMEwrQJzARQNRDh0+2H8tKCdZn6HPv47p4BJiQ9SDp2Qkhj/yg8XV4s8W6DvDcDTpMph9q/7obxDqhIBhYyH6Ch7IepGU0X/ZSAkUa6iC+ZKM2luGiakAtKeHkOV55auBOGCaHcGOfYqCTsiCS1tVfQpnHWTFaJI7bjzz3VhM72Ovyms8/Y8hbudtHhBJRgMf+w4hQ6DYAgQlXMq3jGn7J6k0UB4yVAXWv7c0BRjeVjD0Z9RYFencZ0PrBRM5n4OC5EcTi43QDRoNFtGCXY7ogZZq1CwDb6zTZn2YEFCr8hTAMw+CjsmId92U3xGVfDKA8gH2ivLbRU8c8ljWYvIyMzs34zWWb8qhzXqhGCHrLey7EaDCPcdHVZBVEKHeTQQ58A9UTHl228+0MN35etnV8C6CjfxfgNYPd+Cz5EI3+7z0erSsm+8H5OTAijFC5qxICVcKK2R/LwVI22Iucj411eLWmjRw4aJ/GzVfLZlugMAwohhoO0IdnuWLPf63NnGfJYeyXbcsOahowbvsy1lS0eyPnbXo3DBjtvDzaic1z4w11dLosNnYEhMG01wAAbixthsx1rYbX+vn42WDvMaF96Pbaz9w/yjicU8V4poLNEcI9xil5OY3rANLuwj62nvC1LZd79fOl4xMa3mHCe3xQ13mBcfv/WPq44/+7gD8w+scVDfe4189Peqtne31g9+DXrQKPtO1LLXv6mtuQfYmA29tba5cD4LJ0KARL7xfmEoB2dAFOfZuz3PKbK1R7MZ4BJraINxa9CJmhpG+e/8Hi3IxDPPH8Z36mVAl51nuc/ncFsELoM+7+678hHzvwnrF+7hZNzcudN+f7rr47Beb792hMaeDEDPC7Bvr0DvQHQ7hXj+pbBZQJHV/xcOEsXMs+JVaNFGrfn/d+OnvP7o27rzdtKhxLU2ctarITE1mEmMG9n9eQK+VnQfk/+rZnLF0A232EwOjaN3wnx30jZ1wvG0P3J34fDaUi2/y4/CzQ/lJeykv5+8sLgP5S/gNK2YgKUGhfXYVB2/uGAvuJuqp4rE9vula9CzCu3EPJ85obrBJUIye53SeqeTDc1LlXtsOVTgUcjwOhVIVb3jsK768rUtlkHTMBNATvAERHyOBQ6LY88JNXxHCPnZLnzpTMceKzAygzHLQZ3gIKwWcC3sGUdawW5kvJLIpVNT3cmK3e90r4lL0+9wodoxXjWK/44WbjIfrExOYoF9rxb/cCfGlOGxtFnN21mdH4XTe37NpLf/C7S8uRXC9nOt59ThHhV7KsS4Ii3Fr+bvmx7Z7M07tpsDqQEzMwrnfpIBLIMryHD0XZ8ehAD8NCP5qX9mS0F8CLv6prz79HaFXCPE24f/0G3x6+I8KuE1lYygTImdDYwj3H70a74VcT4HnD1DzU+tRcwW95XrsALDZizQF2KLkXdQXYp/zemoV5b409t3aHakfvgnVdfI3ZeOaBxhKQ+t8KEUKcga2+c6vyHHHVDKm+dk0FIACLMsCeOxoEIfPsNhB8zYPAuq5gYtzd3uL2cIt+WM1qvls+SlUBgz3MvGu93fCgtYY2Nb8Pfs/quEkoLM2Lh3z8p2lCY0Xnht6be+gJ5nnFPM/oa4yX9ZFZMU8Ad4FDnFB5gH65Mc6nbmmjFr6tvQtPZcsf14hx9+oV1nUxMJQsIgI574q2Gk/8DvM8t3Xj6ub9qtqspKFg0VRK5h1Bv2XT2YcmI78OV0SLWijuHmANAegM5QDHCOnBFdTkB2RSNqV77Hl+gwEj9hwpD+9hz3t6A0InU+qREkjNoCnyFY8dyMfJZsavBXhLUMwABKoNvfcM+W1eYDI67ARhAQ/YQRr3aCMLa7nCwKUwsNC1G/0RZ4h/ETElUuwXKAYLNJQRomrvjGGxQbNIByIZPr2GvR/TogPwCt4XBhhE3l+f29j/Y7rjncx5rSpv/S5rbig+Fsk8xbIB2QXDEGDs36lgjb03jQJsrxNvv+GGNMBVB/dWyCZiA5Fxo/RyjVDRnuM2IiakIiYAep83scTelWyMu80jxPbYrYpvVchQJiBAjy5DEKHd3GD9fnJgO7wK6/gVYw5YSPf92tSQRTA7KAfnVUWxosMoj3TIVkFS1s8yv/mOPY/ey5K7/RMu6NAA1TeibAEQwpPYehHAK4Z77FjmhR+MNwFAd/AbuQTIQT6fVx53h3yQcqa4/CXkRj3N16j93tcw/oq+ettTLuRU6mHcAgDgRmC1PVmc19yEN3j0OgEmbEQZJQ+bGp6xvjdUF92IGmHgKSftAuzAqoaY6vuAQj3ShzpKY9M95lCzrxH2XeED6LKzuLdyTOY5/EwYfDGSE6i6MYAbAcWeIKJmXOGzy5PJxf2kHqZcAI9aw7OgnyQJwcAxcZmcfH+yfog6T/Iw12ZM5PSkwyBCItd4kH2cTXxIUmarIm/0EQEiw6N3hDEC/MDi8+UyzqDzGqxlrB3j4+wy93hXROuxuXZjX28Fk89pQwHetjI6ZSIWKrOEvHPI8LE/7MN6enSBHjQH75PRcuNmwLBODsQqxnqzetSjrjDc+AK2XsVBwVjXtsySa1xVzFeOSACWpP8Ak81YRHyfVGWLABL7KOD7RuyRsY+ohzlHYYDBM8YiVwesY7orCLcde6tjA7Tl1hK0QTn+8fvw7LVoFvaOMoe5P/temvUabS+ZGipAWYvUIGDjW5NVqoutURE3cNw3M+tUHPw7ASC+BW4B/WrRjJJvqSb9xhqhHMPBs4PlVLanREOW3AzgkDXzPdnIsr/VfagA6dth32xk2JOX7q7V71S/h9yW34fxvu1hEc2DkgjyzWXeq7xceU2+szTm0lLYsabNfVp+r/tn9EVqjS67J+BaJkdqpRZi40JrKrP0eb7Q4DOAZnPb+QOFdDa/fiUDw3fb5qbvcV8U87bdlqin7a7XCjd7wV9UzOv8Ez7oOwBAw4T2ryED8Qf7O4B21g/4oMBHfp4387487onmGcXZPgBKWVi6Gd+MtGTXn400PJG2K3i+OChYS+yXEaUBEHS1VB/Ph/P+nvJGt+tKSSH44t/f4vF//weEex+8r3igQV4PNED0Wub796OXe6L+kyXCwgMjksIfLpcY0C+soILn9Vru4X/29f9HSnP99M7+xFOR/twcJs88U7z9OQLbg+dPeZ/nG0Pou5Ai6KW8lJfy15QXAP2l/IeVclQY5+zzP6h8p1CGcNHQRV3lUUUqPfbHEcvv694hrmAIAJ3JQlA3Q49NzJUOrN29j8Q9YCmrruETsROKAvgJ5FihGU45DuXND6nhrdYDzCcqQDfsAE2msFGYNb70jqWvmGTCKivmacJhPoDc69xCr1v7Giz0X3PNiAFoii6rK+OGzSlBMRFjYeB3MqDvde/4yoxPBNyHshLm4Q0oPvEY+/s8iStAAazslDClXLSyLEYJ2/ufJ5XE8f6TT1V45gQ9GA3V9xKqoqu+ZkTxv6R+wPZ7nLhcyaBxYnYP0kdX7r2C4Huqq/yAr4TVlauTK76DNqY2YVlOIGZMbUpaPEx3YGasfUF/MKtpwJUZ7vFEUPc6qYMZgvx2XJXMO2NjAUuEeb6xPKNE+Pq9hscai5doeMpgmjA1xsfPn3wODRxfuGFqDa+YsbSGxpOHYvd/jpIG2A4gdNPmFT3d4Pb2xkBjB73XdQV1tbCZPOH2ZsLhcHAv8xnzPCVgzpEnFUgwz+qwf5Y7fBnjATGQ1MPIAwESBvBlyvQYh2mqIHpZ27DQpr13HE8nnI5HLOuC3gXULMLAYZ7BNzcQEvRlxWlZsBxPOB6POC4ny6UMYJpnfP38GfPhBv/14QOm6YCbuxtXcFlOtkYNHZbLbWoN83zAzc0MIQdVFObtKQ7msvFF4mb5YSNkPs0AGGs/oTuQLx0OoB/QV/FDEGFdgZuZoG3CcTlhWQSzque4/grgFaAjQodqx7KYgvjm7mCGDF1ApJinKYEcgYWnb836xTji4dMKxSvULOaxmqo3R1W4AZEd/dLBSrdbCuDhyUPpMz4VSFC5E7nneEQbMc9tUvIwHUlKW0UJheLF3m2072s+kRGA1UIC3zYGi+1LPUEM9TUHYBXzPiGA6AB2wFwdaFda/F2HbEAA7grNSAXTIfaO0s5Q+JEZyrADHALbG2i1dBCO/OSo254ouVYARe9VYRSeP16/hkX+AMcVGOCVg8sbb3qgKLv8vQg5ASM8vnckgI4yDeMQ3Br6ukLXFW2eAXIl2UaLZuqO7u0SrN7G1dc55/uhMkIMO38MXkYg9K5QWTN8vSogvTTPRRNVy1lOMO8WA0FtPiTkCnXPvL6i7GIAmRdd48nXOjClksLfSw6wusctOSqvsIgEsig2e0X8wQTtgi4AaAEwG60B0AZABegMzACdDgA8t7QCSj5u1GBomc1cEwFoAnT1NWxpQLoeocG7VbBG3lIa25pG49QM/EzuUSzl9+xDggP7nWyM3tjpFQ99gcI8l2ytxk3xlH2uqVQNWrG//DIUHAHynRbDkMNjS3gI6eiUeaFKIQoxb/aQcBy8Vm8PK4FlGIwQmdFBI1sLPSMhmSxpnqJsqVYaJ4CpzMj8xt08awnwtC+Uewa5TFA90qeQv1M+Vnt3D1nzTKgzXqoKrB2AGesYf/Bw2kQI4JuiXvbQ9Eoe1WEApVpAfYUaeD756nVGLxlqfBtdgkDo7o1oMkjDsh7NAIB1CCTJk9TDZCu0W47pzGE92Xs61mGctCrm2XKfLt09e3UAgxhk5eubPJbBGLa8N+5DnEG4CqxIg4AMUT1KSML7KxEum2FpI+xsMsYu6C6eCVl7gOjjdwvr7m8mW6ysJo8qW484oVSMUPwBkquAZEQr2AKSIyR37UJ87b2ji3r6HmSkINVu6046SNSMgJjQ2gyeGtrEODAwE2PlDoiYp7fGPu8phSY7K1JzIw5RrG70GLnngw9kw86iq3ijfSrFF3qbBCKWLzf4lsTeCCCMTOHj801WHETxIJZW59Q7VASzv1pAWMCYSPxZm4s8rhTmaPxiRISB7zFBp4DbAyl8v2CfXpvjNAKXEbFBna9pzLEKtFkGZ2oRTctAzzVSs/jrxfe1jNyiijVlAEFXArsBJ00TSBXy6MlPnPZW8dDKOvZzcr5re+w30DeA9C5pN/dH/wxZKT9z4Jz5EtB48rGIiEZ7RhfPlvNViHtD7AN0F70o2lzkCZuHMk9jCezoa1zLVBR64d78F7yTMupFkgdTRneJZ6rMHf8JjkpjoyxrddBCybvg9DX0KWodLvUg10n8S9kUo2PBC8MAi9T1OFFXHQslEPWczzjJpTFk8Ffpm8Gq87GPggTF1bznlRxiXAUjb3hcv3SGqeVt4XOEkbP8rY9P9+sRPj3AeZBdu9fxnn2I9V9Zpn+ZanueRq55qBmzrb/1+Aqljr2X/lNlH5HgdVholnPaJVB99qhncWabmp0zT8sJS+8Q7bn+zoofVkKmF5crzNAk6l1Hu3RE8kg6CV66m9GuA0kckavOy1nkgx/M3YVe/LB8pS19BXhurf6C+f2HTG9xiXYeaCtX3Cmgn828tX1gzBPj+NsKgeIrff5hH4CyZnff430/XXYVRgj/8ft25HRHXqOa4OPn7aqFU0ayCG+NGav0NDYjAqQ7V6PL5PfXluCN+93kj9Ry/nysAQZl6iQp+pXJ97E93fcrA7ExnL/Slq2oSKmffG75Udj2fYm1GftAje74Ul7KS/ljCDMBAAAgAElEQVTryguA/lL+g8peg0Dj2k5BMr7r2Jmo/I7d/dfeM2rJg1mpeVPTOOfFwdg3X67eNkUMDvBcS2sc3IBaeNgMnxjeRX76k6yNPCct4ts4hMZnHp6LN4RaODsQwMLo0i1npSuXWC1EaFdKxZU1NHLIreapFook7x83xiwNPbxWXen5Tk1pzQq8gwH5OZJ28sVnFwLfRn/U/+OHCaXtNO+t0uMQnf9R2s3kNamkHimpUIZuJzmAgrh/5yFz3qg4TVQKydZevr6RnLTUN0TtV9Ai/Hs9TnJDjLUbmJuH+7Vr8TdBsa4LTh6+fTThqXVRfyEPL2r3ny7crap4PD7gdDrh/u09DvNNhjq7WKcfTHtfvVuaa2icbwl3DpKvNMBz4gjXDhA1j4RgRgOtTaasA5sBjBgg17uiNbi3+eRg8S3mecI8e170BMDH4dbWsCla1r5iWRacliNOp1Pmim3NnuNmudjP+hre8zDAjcSsa+taFemQ1YDz4/GI0/GI4+nk4dgHKMHOY6SvWEE4LgtOxyNOx5OF0kcAI4x5tgzGp2UBiHFYJ3QidOmYDzNub1+ZothTAEzTjGluHrLTPUI74H5xDry2cZDUpA43OrAw970D8ySY5xscDgtklfRqBAwsVwgaNwh1NFIohffzEdoUkFs0HAG9NQW0KyeJYFE0HEyKFsRv1n/GYZ7R3644fV6guAPwUHLUjt1kszs4L6E9n94prsY+hAGo0/b7wA40FSoEWM7XVLyNVZTGFAXUsesZF9eUzY3OGhZGBN3RCQv9x660jjDRsYMMvhFbpbEu9XDOh9y1xg7m96tBGBHq3nJox6E2ZsIAM1B42toa6UJA78bidiHvxYGoDNXpKRi2pSqUAlB0sByUoHmkZBjz5+OfSlegouPiF2u+chSFZ4yU5Y8ssx98SkurHFgz3uw+A/nuAnzl/TEBlYhi3uO3scX18K4vitsYB5tHGluQ09ymH2T80Or0tqqBDwK37A8dEcEB8rrPej2r5371XM2yjPptPHwMAoChyHRw8DESrMfwBTMDAlkk5ZowZwgAxwhx8BzCCBsf46beIwRfKOt3G7VmzFmlwhnAslnLRd7Mlm2L7v6uTwDW/KC0oXTfqka13GvfRw1JJ9nY0Y7Kh/YAoclG4uSjgIYHrM2NaPBzyihKCPDHDc6imPGBMRUlZy7u+Wo0LW54F7SqQ7l7PoS5hpYyg82fWRRYdURpmMtYrqjSGplnLRwsC7kB5nUbY5Q2rBEuRalEAgheOCJiFLYOSOTnDoOc0ZYYR5UIAT2oFqrBVGwNhneyj00Y5IoaeC62sA0EjXQSPjaiC8K4KN4rOgDHzR4FQt/Rxz50ZYp+e0Kuz5RrfOH3MpV+vfKYYvbE231s/2BdvYygpSGVd5e9SSwiQPfoWUGjNXz4RozVQVfIfscEV/5r38PAy9LfsHu6lygIbnhFnQA0aLPoQpaWAZmOQYgwi23AynBZ0uRBi5jkvJLN0KWHV2vhTal81bFOrBtjHm0vYuPXEp75sc/Enhhnqogu4kakXbCIpReK1Cljd7f5nomwgi10P5lSvzuIvlf01ohw8c7KY/MfWVvI12DEALJ1sae6LcHYXjIMWrNqHXNc93BRcZ7mNGVbgq1PMTCeffVb88yoS+Vo32JBw6L4hM+yAiW4wiMUd4Ul0+Z/eS328LJyzryRk/lgswDNECUWOG0WXwWsYw3sRzG3MB2PO6Xk76jP+L1av2B8j/WZtxcvQPK+ZlSweKExoSIvUWnzeG22RLffFduxyvHWFE82P2bU901fNt05r2+82nnjNsz7aLCeP3epkgtlK/ft+NUzSuXNsU6B83GsxlMBhu+W7KbJF2kGl3ONv/UbfzWQHvXGrsfMDpoB628dKz6mpzrIQP17xbNCuf+o7MHzXK4YdJ9koBaNT1Wujp/fOD7TQMzCg419yeUOAKHvMv3AnsYGTdW1cMZD/gFlxUipRHrva5BwCUS8XjxeEFH+fSZD/ES5U+Bw/w6fvnz66Wef2pX+shK0F4Y3zH7Siet2Dyt75L6/v3l/7TvHXBOZwWsvhiIhI9Xyo/bUNtfoQufbMOUe9WR9u9/3oPn++qatuQ/s+cAvZqov5aW8lLPyAqC/lP/Qst9gnvP98jHtZ94ZluT2basQDCVh3ZzDE+WSBRt5HSE4x4Ec5Io+xchjCQXI8+WmMOmbrSsvyb+b8qKc9rxOJQBiR+ZGoaIyBe4q4nFxyEJ5rlYbg4AO94q3N3ZXSHfRYY0Ny3lJat748zyja8cDAOqrh2QfgsKbEkoS0PQ+/ww1u9UQGEcv8ruW3+OOtC3YnFnjBU/N9f43vXL92j37v6/V98zvVXHiv4+QpOp+s3Q2LvtwwZEygIlxc3PnYcZNoUGAAb7LycIpZ7NNs0RFgUNU+2iXmQg3bcLh7jXmecbp+IDH4ylzMUcRVZwWy4X+9dsX3NzcpkVtgN0ZSteFy6UvGUaOsq+j0kcAr/23GzjAwe7VRrZeWmNXUlrY9cbmRa6qWMXSGMzSscAPJNOM+XCLm9s73NzcuAe6GYOEd7CBDrZSQyHZu6DLiqUfcTod8Xg8YllOmHjGPE04iilWOUO0D6+71hrmeTKgvwEi5u1Env9SRdDXFafjCQ8P3/H9+wNOpyOWxSzV2zQZUNk7OllOy9V5yem0YDmdcDqZV/w0zW7FqzYe3h6VjsVjqIsqpmnGm9eMpa8WNYBtDBqbdxUEOK0LOrPnc3ce15rn56UMKW9eaITGM1iaWUnf3KBLx7reQlbFurrVPswL2nLuEoQZ3AQtMxY7ffME3L6HquL0aQXeGb2ak4iFEF6XFdM8oy8dq1o+d9HwnoIr8QGiBgN+7yC5qkb57nxzy2uG3myvMKPdGrF0HvbA/rPeaDxLM6foUKLEa8dDoWwOVMGijZi3WZQbAEcAtw6EdU8lYtFPLK9yo1C330Jw8i7cWAW3ABiQB9snprtb4FFBt2YVrY/WHr61Hg9I29V4vqaJPCcsWWjDaZoRIS9jnn3ziUHOmta1Yzmd/HDs+YZBiS3YQdpBIw1PLwxg2pXjCRxQRHzQzZ6nTlcZCE+RAMIA3yKlQezDMd+u4PN1MLlnaBKJ0wwzZ/5om8OSNVgFkU98lHMZZUStACxHYhgTmFfmqvUJA/gAj5YjBsQZ6RBm5wXdw9kfl6O1tVmYf10U1IAIOUtc5gnDg/VMEWAp3dHd69y6S6AZg2aB8T32ldXGYj06WEiC+eYGp4dHCHx8oJhuCMuDe5OreUwbyfnYkI0nZIYq0DEMtQxgilDYmvOHMU0I3CbmdfY7TjutyvAgw67sd+T4ZtcX6WCYB+S1sn/y2hvyW02CHjcMSzPjIX59SEJxcxiZ5IMw2c5T9jj/6j53mTLE26awNSFqBphCFmHCcGmCsr9R2NeaeWyHoZU28zCuRiTRNFELU5regGUo1tpV/2vj3UFUfrXrzMAWSSlDRsHTrb0W1WHwcPF0JkQj1YeqRYHI1yGWh25DtoeA6xXaLb3QnCI8W8XB8g4PUd69Lnfb1G58ytaXNXxA64MGUh7cjRLy3ph92twR8zuIbEfgofj3r7fzZPLd2uvPaHEm8joElIZGYchnY16AxVBUlnaEXBh8mUBpcEIqzpe2hhl5TCqLe0AUW/l4WzRuzz1AIKAwPkuvdgPPPRGI7U0QNxgRSz/ikYQauRFhGLcRpbFncxk8si2Q89ZYMtai8Mj2GSrGAQDSoDGu2MmtGB6r0aSoQD01QHeaVhVLwyOCVbpHmHDvd+eNJyM73LhhyQRbAwozytjSmTdcz6jGqQDZ1vgey3r8ZmuGEIY48YKQMwHSbnI9Yaw9H1vbok0+Umh6qvF0MKOUTO0iwKJo89hbAUL/ttpc3E5oaJBHgeKAkz6WtQs8ulxxo9vVRXQHAJBvgvaGPXyxtT+MjQFLpQS4MWPsNqqAn4difMhzhdf0LvYei4BWZYaMrAEUQNp5X6F12wfLJoftfMVclp+3wLPu7z2XVUJ2HSCCXQi5dhi2FuaJIA/nvdl6FEErvm75994gqHp2Y7dGEPLMhV5sUgJg7DtbOaeMjNMN09jDNuN3ZZtPEXIQ+Nj3rnif7xdVrXrs3PZZpMuxvs5bf1ZPPBcgdPVsrwB5UGPzv38FaL0vDe+w/mbe/Sf877YNF973mYB3eo93Cnza5cR+s5uHb+X51zq+R9S6ffWTG+025jxnMRGkmxdw42bj7Dl4BFIGdmxGYQg8zgURsWVPKOTva7lPprmO0yM7kAi4MdMOUPx3lNf+4jC0eK1GI7bP3QMEdFGLFlcMki4I0gCA+7fvXTSw34+/raB7guDLszzHCcCt7wUNQHv7DvKl4yt9xcOXT2Weh3x0XsOl67ufzy5vf/iRrcC1nyPiQSP21ADmfd579+NaGH2a3LCg75q9r/m5lPF0g5mQkhiTr4myX197+trb9xFSQv5jSgnx/2PvzdYbR3I24RcIUpLtXKq/fubkv/97m5P5pisX25LICPwHWAJBSbYzKyu7Z8ZRT6UligzGigDwYjG6rTonGdJYvl6/l8/GW3/zPbl5r8CN30cTrR/xPH8v7+W9/J9V3gH09/L/YNkeaj9yyP3ogZgE0ItDVwarMrF7/A0OnmelrSppJRgcryM/l1uaxd+QtdqowG5iKp7gSTs7MzAWrqiQ/t7WmuZNroTq+izRnJUQAZOGXiZ7h+pJDJCw0HtEmnjQwwIXYbTCmKcpckTfN+AbjcJlFsxcENtiCa7UzuOxFQQ32pwrM/zanN/khq+US+btdvm7xJnbbXCGM0LqAjqP7oVuTVJlHqGOTw7MpT6qYbFzrnIA2N09oFbNZ/14fEaxEOu19fBq/rxHYTgvZ7UmN4VxSWtYFUqW/5wnrE390V4rfR94+9lCZarnuectd4BVRJVpRxNGS5kwzzM+7mZ8mGfQrKHbNSx52tsBgiXBSjS87Lqummu+CtZzxVIXrPsZtar/lwOKXEqke5jnCSJ7RH73UC5zCEaAAmDrumI5n7EsK1qtKJMaqOymGfNuBw/jnNuyLtWELQXPpmnCvNthvztg3mloekA96P2d0zShzDscWMOYEjMmi57BhUMxudaKuq7h3cAWSrMjA7qOFLcgwAxqAGDf9ioI1WbvcIX6GWvTdVq4WS7VPtoqdJ/RnmfgoGDqui4orOkmmHVumRnrsqphQa2oq6q7uWhY2Ykm1A8V7dFbf4QCpTfWWmrHcM8LQFj83pGYEMyygC1ODM0b0rEw9zjz0sl5Wn+kYytE4JQPTECYIZofnTTiBLemgAkzSmsWVvlg9UoQjYAbhMAHDc9MAuDQs47ygewMANygBPA86j5WTqE5tcsVTK7whIXo1y9u+FRtbS3L2XIP67hPE9BaT8Gi4BahtZqUTH42uPddOu+kX4txd+UqWShyu1+jkmt/uv66e4cgzaSvCQ9fHHPj1bF6jbkCLXA8EEA9BLG3s8NiPjQ6H5prUT8LLP+utyRpuZv3tVGMs99YbbxdOa84NsV7muiZTlUuk2TGUSLxXrii2Uq3EzB+ZicxXoOFvTNCALDTSDsd7xacTydAJgXKqL9vujtgOZ/jvV5zHHqgAIC2+3nwhrx1fPet5SRsU95ynt+6Z+TxfpQzcCBiJAwUfNd47/UOdmDB/gzKIl/Tupc4K5qujsNGgSVuhGK0RshCcNvvNo+epoIqIOxt7xSjG8E4EJ33cvSwj0Nuhjc1D7KBlZq96bLN2N4P2zNEw3sLa1jI4AmEAgTUR6XvIQ/JGGB5uktgY4Top4PnzXiTZvdIE7QqajjkgUNyu/29ifYhUY9OWbxT+XlTWI4DMowxEbrif1PWul6cmz7O28WtOLR7kqWWcj8Ptzy909MAyEWNO0DGl1kOBnKPNj8XfA2wRRSQPCLWx1tHvbVD08TYOm5Kg4hIPdChv/kYNjNSYm5oQkBFyITsPSMAxm/3aGR5sfW/YVQg0nlBouvb0MFSOzfCU73XFHxHbT0EucpkzYDzBKADHWC9KDSssitSWIxiQInep80cjOsxr9HNXMH5CruT1Uib2dM1uUl3GkI71yVSg5mBg7VHzmpM0Px8PAO8J48VgRwhxg+lPkVjygY/S0gAkqc4MNrjPehDPidtH5GfQ73PG+nlonTPZ9nMrQPm9nCOXOT/yLauW0s//9L5m4HGSu+rbB512QrU136cV952G5t+/bLHmb+6ANGtXJ48l/cMkRqGB2Xz3t7Hjdh7td6hBDsz8kP992ywNHoUZjHJPzt4/sKrLj6/1sztfOdZpRvPAAo6b1vjedP9+o/yLz9S/qQv+EM+AaDQC91qq5cv9BWf5dNVT3TP757LwzV6+kJx3q1JQ4Wn3aKIhObpXM61Bf1+uT7gtVHsu1y/iaicm69vdup/THmkHkkABPDnHpZ6+fNP3Avw9NoEEKF+afnrm8HzB/mA8qmgflWmqX1r8dtegNOG17/2Ta9suarfWxqy05TRDChvACB4zt9VNMrO6NRiv+BXrMJ8HipYn01+PWrDj79tha7J3O4s+zq/79ffEtEhnzMvfb4mj4XOP3T/9G9bY+/lvfy/Wt4B9PfyXn5TcSzElUtAPiwl7unXLSejCeStJrHEOIDwQN8c2i4c96jt5l/QmgEtArfRC6dEb0pLDF80T3qYXOmW7cr8M6pBqVIAbrB8c+axVdXTjQ0gd8HQj31GCpsJAhcF0ScuqFyxgvA93DBhz1wZ3zQ24i+hf69wkJrx294H5GnLAV+vlUvB3OsREZyXIwBgv7tTcIV01qYyYS0rJmmRf/WiEisfHj7g+9P3AGBmEXx7/Ir7wz1OpyM+3H/A6XwCE+PTxz/w9fsXiOVGBqD5wtAVoaUU1NUsaS2POUHDiE+tAnvNbw6wAvdp8PekuiIhFYIeAJypezUxmwd6mQw0VgCduUR4dd9nHrp9t5vR5hl1mnCYJ8y7OVmeukLQVA6Uxtc8W+tasS4rzqcTWq04Ho84nZ6xP9zh+fgUOc80pLt6w9c6Wxu0vUQa7h2iQC883LbqbS3Epo5/KRP2+z32u516vkpDXTUM53lZsK6rgsjGmLsBw24/4x+f/0CVimmaUH3eW8NpOeP+n/8MJdbhcGc0qXZji9owlwnruuJEZwv72610Q0krAvWo4QhVqsYK6k3qFugCAR1dZ9Yga0MrqvCsYvmibbwPovcsckJ9mjB/KEYnKlptWM+LtsdeX9tqBgzq0aQey043GYDnEbsHySO6qisBEDeEqLcIV3toQ84XwpjtY1OKu1IVDuwCkSvPS3hYbjSJBACsoW29rHavg8+QqsC5PKjXboGBD7qWy8OdgcWu9zHK7sppyxHcc06aBzAp/dd2IfJx+wZhg0y4TBE6PmibzUMFILXq3Fj42GVZNR+gCGBequ41VNsK5mIAsMQZYUF37VyzOZS+1wP0NYRXpHtSC4ZjEX4wi1g2SO59aq3FXeznsa99i6YwCPbcvZrUG821zxL02RWtrmh24MiXQHiW+Zya52VtusenaYI0S33QGmZmiGjIYO23jRWSB21rpg0VzFwgJBHZQoEjgWVxQDWk3iOHsHmAd48rV0LYktrZWJnnnZ5ffZ2IKYSkVbSze3qdIM3o4VzQjsnDsYrxN6s9Zxscq/ao2ohb2lrhqiG53VUZFvJPYvUC2Aeg1wwkcZuVfP4KgHtr+9OGC9mSgKvAj/3SB4hjz/xsCX5x0wZJf33FdvqCUEM1Q+JCsSPblvt+NgAyLehruHwA501DUXPT2BYRUpt0rWloZwJV3c9CGnZSt1ffgBElwvet8aoS9wTjrC1tdga5UUiGCMxbJfZl0KjLPkTHfQxiXIxeGOBGDWjk/Hp/VqDGNr6nFSJv3XDGPdMCVBQDy1tESWmtA+naf+tJdXpB0R+f66BIm+Wma0DQkyD4vvSxoeF+wIy4Yleb0U8objO1B1ZL6TQoC6FBrMjPBjtTiPoseJWcHiKYFx0Q546HpY8z22QLl2NarMuuzFUS6iCDI/mCmxslrXxfIwA093wTqGVaMbs1r0eCj/RzsTXlvyCAFAvhzqMxJLGlGfI9hc4X6LrsTVT6P/L7nOb34pwBnInS+WAzSkprU/e07aXWAkRvVflGN/pAKUHrgQ6YKS3HhYGEX/K56nRU0vsR/bQPHQDwdbWJRsFMAeYrbxyxqyyCjcoHQV7dwbz0fSkien4IUM/KU9Ck53Y7KS/N+5QWRoB6fEJrgrPv/pR/uZPyFpcgCCNvX4kCQf3WUD6yGeMBVMy4gzzdkgJtmnpI+uLb7GMnY0Rsoefb0Bw3mohU305fQCHrOW8Ek4+UXLdx0cuVNXVxJZjE1FYCRKNn+V7Wej2dlr0gAUBBi4Eh1/n4vpG/yAOi454X4W0PXKe/Yxouq93bf7GpvM19rmMEtvOU2hAf0T0pO08sA8np8zS22b3PYxRusAuE6xoBz2FOUM/UP7mDx56jOpdPm++eC93v34ZH347v31X+NE/yH+GWsvd55G6H9imP1VXwvCvu7L2J3/XLAvM4N0O52jDtJjMU1HDuzoe3PtE3Wnv9uhsMMfHAM2QH9uYRtYBXwdOt009/u1/X3m6jAP1o8TXnnug9pcAn8GdNnyYQPP/3CSuAI9PNuX2QD1i/rJg+F0x/qHHO6cufOObgAkEWdON69/ZC2H/8hGLnQGOlAQseI6LLmfrjE7HqGkLuzaS4575eUq75v6P4aOynCSLAUkOAiTVYQwerPakWQQYYjgv9fkGfaPz9dkOG4vOo6QX7eeMnOws03Zat0a0+fFvttp1OXYMvDP0FoZCezUTAKSK3jEflrX78IR8AfEdtDSzASsADCN8zz7c9Q+DbTcLQ8S3lrfe99HwYtVJfC+/lvbyXv7e8A+jv5b38hjJ4WhjTeWHpbCHNPUS6CssqVq9rhXuih0X5xuz5kslFgOh6g4nNG+91MiY7hMveaKvEfzMlh92knhOsOaeloImgWAhvD/kMeIrd7p2UZcwIgBvAmTXV+sOWp7qDRGShv5KklkEOv5Q0t3+RP/k/tjwI4ZHk9RutXMy9hfq7ZGp1PRx2B2iG7HXMo7spf379Ew/3H9Rz+3TECQCJ4Pn4hPu7B+zmPZZ1AczjeZ52qE0Z3nnaqaDX6pUcxghws1mI1DOAcj6Cpx14Igs/2fcGbdhmAuEAwgKyPOiquCyFLVz5FAC1v2+aCpgZ99OM6XCH3W6PaZq7d1AaryauMFWlY6zvxOiq8ly9p+t6wrIuWNYFp+WMwgVVGipW1FrAXM0jnlDKimlasSzdCxwASmsaQp0oDAGmaYq53O/3uLu7w26eUaaCZVnNIGFUQBIUcNvNM/b7HaYyo0yMj4cPOK5ncFEldW2CIhOevj9iv9+rt1TRUO/SVCGsYd91nRT7jZoaPeQIGoOnr4wAPhFht9t1kKGpep+ZFQhZGySHREUHlck98wA0PKN9bxC5w/RxAjOwVkX81qoeydJE13Rrkf+XibC2hvpk+W+JQJpkIjSSQq4sHr2Nrn1+Sdtw9NV5oeDompCc6jOiXKczIa8vV0ybRnlY/7lUqPJFw19DwWZRcIvuGXIUCDPoXtdyqx4OV58vxAigwOaOYPNDDCELFtuSMpXc200PK7K9yExgKiHwS8yhgd8GREAq6rla3nMHXAklUFkCoGCxwSvwleA0K4AqrRiSc56Kn34GSpHeH0ouQoDrg95LJIA7BSYo1qyege7V4AKwg152Lpu0T0QgC23tHqbZUCPmkdxTs13Qu6x4aHDAXk9fZvVQJ6Lexw144ms7aqpiiRNsnIy25egH/Vnz+LdNoiPcoRXx8dn2Bw4QwDw5bUyqoBIBswBngXhma5sC2msbqBHk6PuhALLGbfC2xZjbimgNZGBLKMVyu4gAnAEcQAAKDuA7xvr8vGk/Lr6LjcXbilyp5deUn/FWCP2o7dlssJk90SNijK8uU4p1HET3prOVSqMl5q5Znmo3UCBQaPV9LzE0V3QrtsKkK5F6qFMMYLr2G8E2a9og55HNJ0bMkM5+i/+TsjWiL7wyjy3tHwgCoRJ7T3PaZPc1A8vDC126sU0AicaTtepAebXIEhlEr9F3B9KvzmdUO/J2fVc6ed4YhDnQNBxjfa122Gpr+PX6iuvN6V41Lns4HXGQPl2NmiVX5P/bnQ4yCozsUqezfm4KRNdyiiZybb9G3uqoH0H6lW6YEV9lSGndiCSdMeE1pPljorklKiPzOC83jTYu6AkNNwx79JoQlA2wfHyICAUFwoQC0RQMMazpXfm1ccZe8hPadYq5rRv+G8CQZxnDWdvv8zYOtPiiR4g14n0mVhnSeQqnKWHgJ80WvdGPuK5j06ShnS1NQjNDqrNA5KSvOt4hADF5hgh18FzGv/D3Qfm7fWoynB0CjKe8S3PnBoaaesTpWoDNfaC3Az+M3zBoee9fTsmm3LiBbt1z63N6LOkE/Gr2qnOjR58nynUFWSCMjRjfo0thMwi0ufPV8/hKP8jPrmt9v1Wu7D+4gcLrj1y7R178dbxv28JvBHzCZcAPv4+tfx9kzF++vXf7nl+dz/zfVa5142cg0OZ8K5JeQACIOrLUWi1FWwK9/0ohDxsvcYQBCGB38ES+oa/5d5RMlvLY8+cUhaw1CL5d5JnP5S4t0IlLRO+7/YwOzF4IEz5g+qS6ikjxxSfVLaUAigIxDvR2P9g4YJVf2uvk4ZeULj8CnSdupg/Sduk6rO02b/iryjCPTHGmusOLiATCLq1d3XM/Wxw8BxDRcX6kCL6rgT4AYuqpG35gyG4Zn+Rr27/599eA9ZG/e9sp9F7ey3v5deUdQH8v7+U3lQxGDuC5aXADRLLTMIN50mS0ZicA5ArE28emABoC1jQ8zK4g6Aoy4CUxFHAzeDGURuCWfgYOupArDU068M+kylWUCbOFzYMpUzMAIKZckiqggu5HLpUAACAASURBVMGlj4AI5SxEoKa5N8FkY3LZ95Ab6EXx9P/6MoLnppCiZEkPxPgQgIl5EPhExKxuofnOa8Vut1crassLPc2zKnS34mVaUMSEx+dHzZ1seYxdmDudTgAUKMNU8OfXf9kzZrndmtWsCrDCBbWu2O12mpfd2l+YUSyHMnjC/eEeTIzj6RnNvEEJhGdpKMIoIphck2Na8jD8MO8fZo6c3zBP5GkqmMoB94d73B32+Pz5H3h4uMfj8VG9ShMILbY/moO5SXmnymFKAq2Gcz+en/H502f897/+O8ZOVleUC0pTcGctRT3FVwXR11X3nbSmQOF+D/fanmcNM+/GOPvdDofDQXOow8CzNGFMBLJw8VQK5t0Os4WmX1tFE8FhfwAEOJ1PEFlx2B/QasXT0xPm3Q6CBmk77Pc77Hb78CjEuqI1wTwVzdvedAzWde1CtIHDDsCRzW8TjT4wzTPmtWK/2+taYqCuK9azeh9Xy/Gs/RITeEclrNKIR6zf70Fg1NrAD4SJ1eynNsFUGKfvC0QYTRrWiLrh7kr2R2D5SFWAbTeUINcE1jv/DQ6aD0/AVcYHnxvpK0kEUHxwNErCNaFMkrCWdYrWplDmgtDI8vMRodzdg4rl5KwNdLCQg63GHiGzJxADeBVENTCKATigGwpw0XC1ZOdIgBui6ROmEgYhxLY/bZ97TlZpDafTCXVdbCq05sIFBAS4O02TgkroQql7F9aalPRkcxegk5+3Pqd9nsQitEgyiJHeRD3L4crzNCeS5go1PPUaJIwQQtkpAqk1lA76hKeqsBySIhHVQ1oCzQPkMrDaQvz7WIuI5YFVGuSGPQrudzBHzBhO3BBAtuCG5niOFBNEkAmhuItchSSRx1qHRzrIEUe9RJv7eu3j5x5gnnueYHRqX8JIqQnQniqanIH9DnJM89MU1tA++6Q0iJiRgmiKEp7INMgMFulpAnz9hSpfdyvjgPbcFWSXSgyJf9/EiUj+071N36oakeH5/sEVqDmFq9c9GHcOJ8G2aT6fXTHsFZH/DoF6g/Z6nF8cFUJumNLBTYvVjUwfAkBJAF1rTXOgV4o9lL0wfH0JupKQ0jikzipAac9T9L7zApR4g2sgZGKkNkDZ+NdzngMy9MWf6dFtmoHf5uHq/InTihQJBUPYdvdAN9rkdGzbZKFYW+OK6uBV/Cp9/DN4jvy8pAFAp8N9LMbft+PDMRb5bp3HqyrqBKJv5Z549xY0S63ogLEtOecHwivY5Bxa4aKV8yC5zmHPyLg7fR6YWoqk0NvcabqmulqppqoFAuW9wAVABUpBVwePnufZwCFotc2d00lto5+xdq1pXvIqDtloLYUYwqRRC4jCmA7Qtdig14k1ugs3vVr5crYIwOL0OpGwQQ5O0xRtT6MZZyF8Hjo/IPY9VpodPP0c7JVwKX2+CWhSNe9w0xzETTQCjKw2th6m3sZKbNG080nfbXLnkzzCjcNin2hjEJMgUP7CaJ6XI4CdfXapjOke/KCycnjQp9Xn+97pVZmKGd74PKeBS+PVlfmeGMDbOZgvJD7E1pBFiSqlDHyNyjrXqAhivnNfY/oJ0DRZlHgiTUsFHg1pkQGCWF82t7Hcxs13eUrayTSQwit3DUB9XztEpiLd6EmE0qzEXrs0EroJggzkdAS+hkOcnM7qpbZpByBo/3KqmbzPba9n+udt85DkQsAXq8hDrHvdja6N0gim+3MAQk/gHup+29+R4/yl8rOv2xoKANr/72l88l8fQ8qEbXhWry0mexSLBhfryD4vdQW1OhjRvJXXy8WNhCaOHTgsgHx8Eyj4i9fKLY/gwN43fPyPFvc49/RjTzauxfKeT5MKFM//rfy2A5m3wEnGBz0T6BuOfwLPYYgzvtf3+h7AJA8QPkLkCevTAdXOftCi+4AIKDMIwHwFjKUmqnsCwvHJ3+DyZI/KkqnMJf388aJ17S1KY7zPOlzs3PNTpIryJhfOLs5TXOXH7BPd1qaOp7+eTdkbnEkdn7gTVhARJmhucnUaU71Cvu/yfLlgaO0d/Q7XwxGZfGpn/oXD2o3yUaAR7dJae3WWQrfwerkFnt8C0289/6O/vZf38l5+bXkH0N/Le/mN5UIPhaT4SMKRpENfQTd/LjGsJhhfeBRJ+pCUJp47lEggpq3MzFYO3za0GS5np/YBUG8aBala0zDTzriIEJrlEWQR82gskbdaklCf1SbeV2e6mCmED4GgEYOloSYFZyj3YnAzu9OZvnfW4nYZFFpJ2xAeAXbf+XwCc8Fu3kGBScI0zRAAa12u2HJsFNs+VfbO/X6va5BpSFHgih+CYAJBigLnrVXs5p2uN/NKFgimMqGrv339mCe1TOZhfK3jKnweiLCQAlTuta1e0+ND/r77+zt8eHjA3d0Bu90eS+sh50MpLl2R3cGHjVLen4HgtJwBIvzry//G3X6PdV0VeACDyLyqC3XAqFYN/76qBzpEsAAok6pbVbnmoC9CSbPWimVZAgQ5nU44Ho+ah93A/i7nWIhRe+Z4PKKuFR8ePuC8LlB9nlprPx2POJ+O2K0HzOsMuevjWSwMt4Z+rxBNOm5W99mYxuhHa2hE3SwjCWOFGWVSowC18ias5wXrbunAgY29h4V3BWhXOvsb1YNcqKJ+F1Tco3zgUKzPHycAhFqB+n3V0NKkwnzrKvs0i728xfP8dfFZ7/AUz3fQZfzsNFNGAc90bjZmG6WHLryLNb3HGGoVAhVmcYcmDewpPQoPuYf1HvXYdbpLKHoemGKWhM27GXAQl0JRSkGy4ywxpMA9VZt5duczqq4rzuczWq0BHGtoWzV0qNLU0IoLRIBpnjXXPQRVKsjWRE1CMkSB7FarDpuF9G7q7h3nccyI5bNVw4l+9LRk0CUGXANIsYltbbKG4w4dl+fqToBUs3Djeo9E3mPy8OrioHePBpPXjY5VCg3vSn3YhZbCyoufve75m97r+8fogsio8GVRxYzXAbGQhmIenX5nPvM3C3/YH8Ej6byWHt8VaA2NzNjGld4N0Nx6zUIzWwqNOzOyO/sAdFVS8BuW4kNQLjfjDWWEn4eEPSR2Zval29w/jP/PlCtM441yXd3pP1IocTPPOBpzej1dgTWCIVv+avOV/Kl0SWx/32hzBtRsKQ6VDm/z1zcoUEppTkUA50F9TUcIkqy4pLS+XN1H8XOcz71DY9t/ZB5jQCk9Np4LgadKN3gJgxJy0iD9PxGsBqR72HYyehDGLaIPZ8nA97PSrURvJO1L5/Ftw0aUDV8Pqe9RB/qM/wiPfXFvUoLmHy+U5U0g3BflAPp7DT7eiY/JL6LN/blk8P+q8tRpXyKlufZmdLYSgdE0okE6aGKsxML5i2A1xTZD6S2DUEoDmDCJaGosM1ol32PNafPl/+lgiQgRXGCRU6AR9+MOba+GQdX2QkQBZnFA085Y7ysRWAAQa4qhK+xNNqGh1KQsoo3A5uaM2oyrr7brlMRfQInPcCM8DoOx1tzYu6cC0qdXSDUYu6V5b62PKzqAebGnvK4tzydXPm9aTvn/Bw8UbPJPnDWINUt5xQ005e27r08BbS9sbrplhH7tgfH3QStB/dwF0p7d8qRpn1L6Tlde+TYynHqZ6cuVtr/Wo5sj/NqDr9XnG0OcFx7vufXsj74LuASJsbnuIdj9NsZ1cHn77Da0+5sa859UZOznxdqS8aMDv2/ti565aW1vdH4+8UQU9PfW+68VQk+vILGe+kwyRHV4tzL5/ZuKbx3vXg6dr6VfEKiH+Ut5zB/p+0X918q9EBgPcRMxgWgfjWk4oUqwy6/0wWl1p3rSPOqbyq45VH6n4b+u5LNpbFvnhQR+RHVjr1+Bt9KVb8XSpHVjboQXvF9Q2cIMwpnDU/xHl2jnYxxI1+hwHumpz8HrYtRHsUgTJgMgZBPnNa+vh7cC19fA8rd6qOd7c7SWjgG8l/fyXn5neQfQ38t7+a3lZUF3UCbmYgh62EmbEidw41FcHd4SwpAYUBJJzzODM743C74Mgochyt7JgPSUkgIIVTQiA8UIUP0PKjfLaWscfFIMCARI+W0hnt9cvY0bWfghEQsvrCoUBtDIjAGYQE1S2PasodkMwi/iMrbV/qqS84X9pbJpYDdWGC6n21WhtJ8UdMr2qRpmTOestgo04Pn4hMNB/WfZlJlzmbG415d4KGidD2VuGdlUglm9qEXUs3g37dTDvFUsdUFhzflNAJZ1gYeeOp3PIAB3h4PW0SrmSS2Ea1VPrMfjE3ZF83RP0wQyAL17oWa1FLCE1zlhmgumeUKZJgWmE0tfuOBumlCXE+4f/geWdUVZT/j48BGPz4+jDk1S0OIrXPcdgCd0Ia029fDfzTMIjLvDHR6fnzRNwqoBpZoISBpgHmdrrZjWCqJVv69r5GyfZR6WQxOBtIp1oTCEAIDj8ajAeIDtzqTruqmtYTGQnpjBKPj6/RsKF6UhYFQIvnz7grauWFvDru0ACApr2PV5nlFKwVor5tYg54aKBhH1aJ/NA+W0qpK2R0Kw9TqE158wlQqZZxADpRCW/YL1vAY47mNDpKHzn0SwNsHOll9QCukKVzEv5PpNQ8HXKigP6m018Q7rZ8L5y4omd1Dgfdw/wDUv8r73rhW//x6EO0jUekt/8gTBHl3psANwbE2DWBNwogSMgYa/HcwZKxd71n7Ua3QHoYbl2womRvlYzAVaLIQyo/GKwpMtLhPqXFNu9TULUct2ZjVR5XU3GXcDMb4gSnnfrAn0q3XFspyMxigLu7YGwqpGOAKLJNDQGtAWMYCZQBYSl4iwGgAfbxOjZUTw+G1cTDA1sCLaRtRDUNtkuHKCstbFlaKuvXBBV6R7SpIpkgVAANikgAcK6rLC9z5a6yGt07SxhW3sRZU6JaVuEPG0B+rh22Ahn4MOOu020MA0DmttKCVUQ3o+WKfJPOvcW85piBquNEwWrm9YaxinWkF7fc69BXQu0NcG1CjjdD5rvdNkiipnjZRuTA+Telg05TkaCWgnwHFncywArcoviMBFIMEK1zuq0mQCkYYC1L6eLvgjwemiZ5sZwGp/7wFUok41bpEEGn/u+lWdo+75M47jJYkZLzi31TYVx/r1+6jf60rBAUK8wUfpms0/Sb+JCJDL/T0870ha/Om1xRmKHhqTmvGhHgIyCPrGozI+ei5S8q3R+QBb/qGEvqLelDzeWYv2Vl5NuvYuA+m6jTpIl/OXK13Qv81oC4TMYK0brTRLD0MiCRj0biW5IKGVUZ/339pDDpjZrS21dexP77zrGvUV24V4OUCHueC0do/vuE/yfNGNp9EZJgJy6pqxnWReqio7BBdq60RSNT732Wghz5Hfn1/RDYyuddcVuB6eXCN+5Oga3nfNZW+PsaBVAkHTyBQpFvpUH2FhMDfvSeyzHKpfpEclycrWBgHXvq7XdL9SfpsP1nsj0kFtvlhCUetgucpjpGNMlyFhu5ezYMjJ7sbYfi6NQ23zInFr1NcXGXzdNle6M/c9KmL54mHgOUWYeB+BZge2YNEzpzbbWyftbqv6nqYebEdr044Yi50j3XDDZtMZAQCeAga2zw7YLBXyOfW+AaB7tMeG8oFjbXHigWN9ApjNSLYbAYw75Vpktj520YTR45Bgkb8sTQQ8Mk7vC7EDRD39TN7F2z5mOgEIpjIrX1KKjoEAGuFJ9zN7O2hM1+Xr0emzjn/v9+D5f80gzDu4LRtdy9Xz1GlNogMXx6AOZlwZluoLxVPUVDdkBAWvll+wNVDy71vv823J7c1N+U5j1z2Xed8nGo79LeB5Lv71d3uev7W4gcC23f79j/YZjb7cDKR+MRYyzve2+DxVu88NgXc8Wd7nvqd9jU5lwr6ugEgCi68vJKcOXDR62lQmrKumSosIOgBaMoTZroXbtd/+hT0lzSvr+6XykNbWB4y788P/9wAR4Pn5OXjf6TNjwh/gL3/i+6aurZHdVofqlOIghN2nT6iPliOcTxCTMaa7PU5P3+AHkZ9YFSYLJXapsEa5q62iFFI5GEBtK8SQ9yZK55h6RCaP1OUh1Kts+aCXi8/3rkwQIFLgZb6RCJHCz3ncpa2j3AY3/O7rD+h9ls16xXDWjeOaT5/JzlsBIv0m4BGW+nqPyEMEc54xQN3vv8FHusOXRyLTkPT6OxPBzKhBsDGBR2cANslixn7Y+75C16XzIN+p9zr4xdwqdmr59nILPH+rJ/otEP29vJf38nvLO4D+Xt7Lf0JJZ2UHgQQE9cSEsWCeI73n2pVRoZfKhVDrOdSBdOgKIqx3KAW62OWMSG6i5DqNFXPlisq0GtbdGZu1NaCuEFMAkYHswTZK9+V0ZrkUY+xaw2qehJCGxg3SGJBq7zARnr1lJlA4w9V+V/6hX1N+Js/Wrygaxbcz4D7XrhfwtbGb9zgvJ7TW8P3xG/b7O/OWKTiv502taZWQeqrXdYn1oyHYdT0s5kk9TZMCdswaMn7eqccyBOoN0QGm4+mIebfDbt4ZyLxirQuKqMCqqQsVCXNGPqseVaBBKFCJCIfkga6h3BHKbUCZ/bLbY97t8Pj1C3YPHwFSBQgzg9wZN96WlIShtNR/npIXea0raq2obQHzhNbO+PZoIDUsxL093FrTZ0rFuiw4mUDBFoIfAJZlCUZb61cv8moh1PH4FGNyPp1wOp3jWSITTFgB82VZMM8z1nXFcj7hsXzXUOo2TmSe+ufjCeuywHefPqOe61w0b7zU2j2QiSIktYdg9olR3eWoxghLbnu2WO44j2RQlzUWrpjAtqzpedF83cwEaYxCvgYIaIzGAMkzWrsD4RnEe9RHm/s7e+8DAd8JImr+0IEVSsqQvu5vep5vaJL7HO7RQfVbQpELj0LAyc4Az6kZ5wH6ng3l2wbAIVCA8TbsSZmtZ4w8qPebNEEzCyxCgzAg5qYtIHDhDuIKAsgJYE0YIAUWmNj157qbmULgZ2JdBwnYBihSIQDA+XRWwNz6urY1LP5NYoY0AdeqeU+5oLam4d2pohRV2La1hs7Tx03THJhwywwIp/Oun4UOKLQ02y5K9+h43et0NG5ToxP3rkdSkse8O91pXVGvY1ojJHsXsP2slYHOpBrV294iRXi45z68OSxwS3tMb5mKevU2kvDOg82thmdHBws8rL3nluXx+NVhTivNFLkaFCBds7FkYss53yN5NBEUkJ0HLRRgQNPg/KaFby0ZbR2szkZoy2QbTVJob9OQk0VFsEZ4ePogLFcUc9c+b4uHJfxZvXJWhvoYpT9vrgO4pCu3lL9OEfp82d/bD/Qiia78aKc3Gl63LQESTRNxbDTOb3+vGnXZntnOG2XlXb8nmWr1fzMQY4cT8ds640MmzptfGYRr5L1jcLbHpES/3QBG92gH3b14QpsAocTsgNJ71GAiH7R2zUbYTVkl/vFxzZWMtEzvuhZF6/rYFJ4gPSzEMGbiUSIGkSbRN+nz1vmpzfkGPVcIdL0Pib/NZQDRY5xkeLTfKz5FkR7Gda2keDLM7lcjmWx4YTcUAhxPlvBAD8MsNHDrBJRZDTw98pL3PY+7K6oB57H8rWN23Qy4OzYgEEhdISBUUX4xUhAZzfexgYzGGq8jKX1PClTx1NI8vCVLaYzxDaWzK/+ZGWBSr0Kgp4PyPlq/qyvYm++nkxmpKUA8ePfrYGGJkTJaNHTdxqdJpMR5Tvvhal+Q1k36PfjS3Ne0PocFh/z3J06YK/Tppdn0XZv78PKd/XscpZTvsU80fr9Ww5v6d4PevtTisZWburY3XHvfzZsue+A0d+AGBpp6u235+2vg+bWWvOUehp4bDjb/HeVn+aC/Wi9t/gKjkQCDQfIZQl+u3u8h3B83L7pW70vv95Q24imCgg+1NVoKltZQIFfAxE19iV8mKHjqdCtIhJ0Jv9rz+a+U7Rj67oyxTL8f/kujHKou6McLQUX4+dMnk69ORsM4jN3q09cslujvROb60/IwantFTF5tfZf7WU0EKklfFc+0lAbq5+eic2zoPJx0vmmM6KRGetkAC9hGlvo1pZhBkJ9f3TDUzk3x690Iw6O2Ofj9EtVRWUD6WrENwGYoUKUGfwUgrl+ErH+lfCUbQ99DN1v1+hxec4q7Bp7fAs6z9/m137Le/u+i1+/lvbyXy/IOoL+X9/Kby9UDFRgVdoLOeFh+xPF+Z8xesT4TqCbNFSimWBMARKxKdVeCUQfkg2nY1O3K/W6Zbp4KzrATQcBgj17LwFpXSCO0UsBFQRI2zXVh9aqSSfvvXsBiii9Bw1TZFDYANQ23LKLsVnidG6PUBZHOBLtXYh9ovMSj/VD5C2qLq2UrVPzse+P3zYcOUow1uGpGWtMQ4KpHUsYzabDZPIA9uPb5fFQhwiyecwhjzZV9h8KMtap3qAhw2B9wrisIhDLNqHXFYXfA6XREa4IqC+7v7i0n+AnuLa6h4pOHuzHry7qAiXB3uMPyfYEYYL22VYE5Cx9O1L1oYOCt7HZoxNgTozKhcMGHaYZMfjSq0nonGkabuGAuBbvDPcp+xl3p7/L1G+8Cq3cR9SyToei0vV2bhhlvtUGqGhGUAkirYGKczpoj3gFGkBqpFDAW7uq8uVWAC1YDWjSsu3narqsB9Rr6GoB5lOvIKjC+9Px6rMKMK7yIOcB5JgYXxlSKesvvZkzzBC4Tno/PVk8DEVDmCYU1h/w0FaysoOR6OumcNIHFo46xKeQeQ+aF1wQVAjKDGaeRxQD52ghlYrRVPYbUgMG8UwigM4UBA4uGJSWWEIljLQAaFhgNxM9ojQA8A3SH8lBizS3fVgieugDrtM8ASc9p/kSXtDP2pmhO8yN6bvNnqBf6Ezb7NJ7p60ZgYddNOHav1qPXK1lg7wRxPHfMkygJ2v6BANADwTMMN3ORK3ChV72KmSdQUfCciC03JyxHKoFFANE6FAS1M6YRwEr7wZb/kjzEuiAk8OiztlejMJhBSNP84NWszat5UpPNY7O1z03QWIGISn1PKE1qkFZDwQ6Yc7fvY2bL8dqV8MyM5XwGFbZQuDIoVHRc/XwFQJ7KAWlO1OOP/YaseYHrxV1wd0UHYZpnLCcJ2p1D0BJ0LPO5HZ6ssPtCIUoDTfcw+EJK3+FAXYTPZ6yyBiauUSmq0gbTS0T0Cmv7ZCBG7lde02QKimZ5nIkwAEP937QPCNjv9mi14ng+Kb2wHH8aql49GKQ5JKiDXlCwHo/mWWkjcJogWHoUAIGFpFYGSbAAQiBebehoaHsfPARflf6EItBjgFS7/d5o0elnGAZJSrcLfnBLa7Ya3lFZo8viBSbIGSjjrwJEl01HIZf1OH8Z39/CbGV+hDxQ0Y07O98bTn+Ry1fbKGXD6JGDaWmGXEkGMkO11IT0t0lPIRG3JCB9NP7clNbg3qjbn/V8a3bWXVOUS79PuvFKN2LBBZCePXpb3/Cptjx/kn8AoPRvVxh1Tekt0nOUjNp8jp1vTLVrlXQ5RgLg8XiO99PwVGqbjCtiUArDc8MTBsKKvtRurbhhXYKMJ8yvN05Yrbg0JUTuyrZ+yl76fdtgslhh1D3IgwfXjWx70A1ClT+p4p0QU9B3oydPh8Ms4YnrrXGQO9aGrx17R7QrxkmsXSr/EVJUAmK0VVP81Ayge9ul193XXhzwV8d69BgWrOLjo79zeibPXUyN79+Nklk2dA0wftX5cDPQDBA8KfVFdN0u3k9pYIvwUC3/uadRYUvpItmYnJL864vA5vUogp0IDkmxnQEOZ3GMFerj8KFHWsr0giOSi6T3Ku8lIur1GG9Cz2W+oSlbI6roh9M6A6hKSeHsU8Sizk+ynZf+W++/89RqVKNrYp6mTiyC9egX3CM9ECoa31eYB/kpIrKk+ei8zdDli3VvXR5x70wWN2zHzbriYq5sWy4JUjbSWWsdfszzJflBGZ+9BZ6LNXKgnem3j6k6Qs/lnX0zs+nqrRDuORc4oN7qL5VfDdRty2vslLf3WjtzCPqV/gXGp6se6h+vjIOXW/vs8j79+7yoHL4rkxnf6znRnE5ywUSE07oggHCvA5nnsPdBaUYzGW8qJQxl/RqRObNELb+2/Awg6/Pi/fhO6gH87X9+B4Fw9z/u4GnZ1lpRvzQ8pUX91nE/iOZHb8cK4AxhRhXRuuExLfu+ULlC0wBq9AsCSEbjS4u+V6io/kdg+bwRhlhTKZ0OSweNi8nM69ldZjYMxoYz8pSWpZQ4l3V/mrxpZ3xxD3A779ZWQwZ03a2O2zg+2zSe23JrWjm1cy4Tqp2DU1F+WuVyi3yVaNhk5xNI89yrwweCgNFmHPr79ftH698Tdc/zKrW3iaBzSghDucvRRdpb2hgRuYxucKPv/dfXqM/LZQuOv+Z5fu26DFThvbyX9/I7yjuA/l7ey28sXYjegujd21XvU+au1W5JSqb01rCOGm7RrRsFFJ4Lly8dv3ZGRYLZGnRtYiqdIdSvHdChWO2XR6VHF/tcR1+lojagQDAJg4sphgAAKjhTA5qwKRu7MlOZWAab96NwAwtDWCDNAPeGsBB1AXhkP4feXw7If3h5kLcD628tt0ahQcOgMxf0NJMCN8KobcXEE8AT1rYqCOxWwTHpo1S01gVr1XDPRITT+RSgWa3qInw6n7DfHbDUNcDa0/lsIHn3ONZVJAb6KPNNIOx26vOxm3fqGZNcjwsXzNMO81xwXpbwTNnNOwN4Z8utbQAMkYVcFBxFlVcTERox5mnCdNhDEwrMscaz3CEba9etYBkKPFNMzqZR8/9Op2eUacZqSkxAhbjCRYNFEGHBinkhnEXzNpdSwYVRJw09fDqdNPQ+K4AuWQkqDeuyhOK2rlXBRA8Fa0KJ06qgU9THcy2T5VKfUaYJXBjrWtGkYW0Np/MJ02lG4WL55Dny1oPIQNAVtZr1dg5DClWMek636wowvcrEADF2+10IQt5mBUoVwOdSsCwrJj5jZX0/Q0IArLYjWrMgwVQhxFjxhPVRIG2v+96GfQAAIABJREFU2k48J2DS2tSl+VBEvuR5fkC/JyvhniDYi1z1QO+fXU3Yhaa+33T/HkA4pteTKyad1ls5JFA9xthov3p4qkKfBKAipphTAJym/n6pLZRu4eMgZrhA5mtDFg7dz51SNJy6afvEjcRYhWBJ55J7wS3LYqFFVYHgIIp6oLtXdgfDSdRAQBrQuIUyHQBWozEiGr5V9bFdgCVqKCiANEtbQKHgLZOmhkA3wdBxAZBBBKcL2mcF0roSwQ+pUUF6oUgJZYhAlgVUGKyJvoMOKnYhYSgW9MeV0UlhG2tJvN3NUm209Jt0vYDo+U2wfL1QUEFMKcTZI9fWswr0g7+jnuteZezhDvawGemoE7jOq6RGrE1BokJqNDWV0ulFk1CeFA8VbnaBoZTYz6DTGe5VwHcMPO8BnDbKFeOjYk90PujaEaxKrFHp7PduVSupxp9XdNxQovx0dUFH+vdb7/RVfcE3bFnFi++0vR2Zl3TvehqupbZQroo29Wy/JUVUNAZjZInYe+7ZvPHsiJ/pwjW2A0/U78v1Dk0iAw3HMyuDOI0o0rMTcBF6WZWe0mnAIB+M+/vaeG2juAz1ypVrVoG3uh8XhGykMKyCa+fUNW36FaZz3CPXvnVVamBrGzCU7bOHtu/PX3QwUm9cLQJ4aBTnQbI8c1F8nWcSmPsKGuZz6P7GEEWQwifH+aF0c20NxeeEKiYCRDxVVgfNw8tqqJq80tEgwvsmFD0kAlYBUC3tCvVc4iOAnvg1ZgUBpa+/Yawkjs2LceB0nTa/DcMc/OdACIbf8p5nIoB6CNuR/5L43w3QmnugGx/jJuV+FrqX/tgw2w/OJPv9UP4uA9SSxmHLz/Y670EfafxBrIaYqlwn9XG9tZ5/pGzmpzch8QJX7h2eSnTz5ilFwxs2n7f3yO16hpsl9qJcecC39XBN8lqzByk9cOM1eOGWl8pVKmIN25LJl8jTj5a3PPOdegj3i70nQKFLwPxXlV9V3Wv10ObvS88Lvl697zu9/vxb35P/MhMKGI1a0BkmoLak9+uNg9NqwD3ZGVNRGcWB0FVDOv3thgtD+UXveiTgD6G+J81RR0SwvjHagpd7ARgfU+MWQBBGi52T0YF3IN2NJv2sYEvx12qXk8h4DjYlkEcBVJJp9zXn14wlcsqdwOy3FDa+eKv/0LO4H+dulN3MMKCJBI/fdVUv8DQ/WdwTX1kCPw/baBSal7HAA5+qHJ7a9XLReyoIhTrw77xPoR6VEFYn4TpfMTZpnIxbYPV4z+Vz/s7X6sp8y1vA87cU7+MvFhHfy3t5LzfKO4D+Xt7Lby5J5u7FDuN82UO8kkiEtdYKkjC9AUVuv3SUXd05TICuZKDeghbKOXvYn1XdRGfkmAFpnVGEqd+MkSMm1ArUuppCSHMoF862i/rexhomWMNemyeqqB+kez4qiN5zJLOI5kCXHhJ+YGy2A/27JAp/zS9gZl4Cz3/2NeFtbMo1r2hpDQuAgyK1g/KGQAqWs2C/v8MkM044YhExQGlsjQsg52XBVIqCqR7uu55jLpiL5jMnxrKuuL+7x9qqgbIrdtMOd4cDhIDHp+/4+PAJT8+PIPJQ5Qw+n7Ccz2AumIg1rDt6eOHzesZ+d4/7w50ufukej00qQAX38wHTPGPa78G7PdZ1wd495cuEXSnY7WYQKdB+KAWkQTeToKtKzzwpCgzYfPn6C2RNw0I6m98aUBtA1bzSExi/1ooC9cJ/aoJJBNwKKhHIgOr9HuqFDvUm8XxbNSnS1etzCe8aBc41pH6tHsa9704ChtxUmpt+RVkZy7TDPE04HA6YiMHTTr3G14rzsqBME6bzCWUqJly5Z0vD8/NJw0MDSWXfgTYFv9UX/rSakjbkRjFQVo1tdvMOE6mamZNQwlxQJgXQCy8oEBQhLLRCpOHu02f8ry9/Yi8CSAG4ognAKKjSwKaYFjpqCOs8fyYmezQBAfAswO6KNvKATnoIPYO6g+Xuue6e6I+SAE3r8bawCeJ36KF6mTQM7D0oFMEnAQ6mbT3ZAHq4dw8r7bAz4d4+GLgOCqMNAmGaJ0yT+tXGXJLOJwlBSAFkNi8w937z2rmoZztEDT8iqoKF9WfhUPy0pmO6nM8KniOFyoPm8faIFK7sHhVLupYqQSMP2JkBAAijHzv3LE9aeGuAtH3WjzI1vcfDzoVVuympjFzqspBIsRLKLjN268YWsCgHutpvCs5xRiPyxjMTNEF6Q3UlN8GAJVea2YND8GBvrymDWjXlihuxJMUKkYayTQp0AoXiyUPyteZhIvtbuqdDUMYY1wxqSarXvSu9nmYRBlYzsGIq4MJodYFIM8MZay0JmGc0URq5PD6BD2pQpYB7P5cIFSBgPR0hBJSNHksg2H24x/n7Y4wDpXu2KVbCkGfoVKrTXj15XfbDh/FnVBBO+JFyoer+oadh7YHkUNf5+vYt+YZLWhTAhbOS9HKL+m9pbogA6vvPgXUFRzeKw4vH/feyfYGeAw6oWf+cPmwbdOHhygAJxVjpRYm96J6Q7nVp1fffpBundGDUqxmNX6+NNgWI19spvbtDH3tX9LMblbxW7GiAGwUsVQ2DIL2uDoynwfLr5FzCZm+nkruXJYvXfGZC4Zxq737rWlPk9UxK00EmSmuntzcLYUkScTqdtsQ1UM6J/SBqyPhb9hzs82fvciVzGhSl82rURxa1oKKBqwIILEXTzjCBG0O4gyRNmhqhWT/d8MCOVzTznstN9DG10dOw81DTULZrblw1jC0EmtrE8o+DUOO8ia3R+xz0gOJ6Fzm1vuZntS0UTml+fO7yXGSPOR9jNuPXHs6UIrqKN6SZkWiTptEfWotIMg4ABF8gYvQIo3xLpJFrMp20zmqmn35gOF/ot3I/TvM0AHiCfP8A+uB9okjXltdn7COPZpBC9g/nWPKI7xdxMf/pJ7tutMNCS8ecRf9TJb74BeCpR+oZyCrN9tfnS81E/LvqOIYHxhb5wNl5MlIZxBw4D3RxNNlcOD3Lr+pjuRmMVI/km9N69MXdDZqGl17RyXS+QPw5b/tVnYRs2mB80Qth26/Vsu3Wrfu2Ocs/2es9AsetnOF/pfh8/oryWj2PpEYAt7zI89oidIMC2LVbud4vvm/WRU4f0WtDELKgX2ac6losgkZpLPAkRTCaYHvdeJqJCCiq7/C6zssSKSh0T1LoQQjX19tLa+Na2Vax3RevFX+f67Ye7Pu9aKQzAOA/fH+oUb6f3wdB5IbX+z/hO3/DnYx8UcEDBI9QGUhju9U2wU47m2s1f53MsxtMKMQopWgKEwPPe2QXLdNUcF5WTEUhlGa8ktMh3ni0T8WBdb2yqsIFlOZ3HBn9y8YDT9MMNzYGEBF/hNRL3vWpPfKIpjH0090B7qjaiV86R/19b5u/vmLcaF3E+gmgSY1z3uU7IsSY6vmbDN6Nr+jpQi92DADgzg2/CaihoyKABIWKGTpQGGIvtUJ1dCmXXyphEprmViOjvRzy/a8A3b+izku9f+Jh38t7eS+/pbwD6O/lvfwbyqUH+sUNg0Kbp/FeF7B/BBDOwqAggybG+IWwT9efg1sXJg0ILPRf5vvI2kYqgDUxoAkGjkOt/rPAAiJwW827DmBq6jloHn0qUFQLzattduWlNqdLx2Mfbozxj0oM/yHl7/BGv27RcfVGAKP30TzPgAhq7er/riRQhpmIMM8zWhULKWXKGTbUCRqGfSoTHu7u8O3xGz48fACBsJ93Gko+Qio2fP3+JUKuCgRMCtLDPBGZgcaka8oY6nma1Vt+XTDvdgPTX1uNcGmlFDw+P6GJqHDEE5iA3TxjnneY9zvsphn7eY7VtpcWHr86jO4FjWGsrhUFCQr2uz3OuwVonn+cIDJpaMaLPa4M/iodFCRa8LgWfGwVbZ3VYGEqYC5debUF0VtFW2uEmPb2hBdqbyRcaJ9YQFR6uGUTeNjmY2YNp72sK/h8RmFWEJx6CHhtiwKoZ9Fc1h5hIHuWO26h3kQeBn8UdCDQkPPTpGHZ2s5CcNYQgpgJBxDORDpmovSptYr6KPijfMKpfoGQgFGg2WRd+RwTCdeuNpHwgstegZelX3+2b/foStVr5e7G9ahRtK5DErpZBE9QGrxP4IIrXQ6bCvbAsN/dd1JwAH/gYS1ExBGokYaH+AaZMY1FLHAAXEF5Ve43Tl5gosI9CQGmkCd0Os1Nvelq7Z4BrTWs64p1VeFX12k3LGAkARyXgnAVGYB06SE1tMfm1aB9bLYmWpwtTQjcGoS1baUUsGcJdiAhhHgFFJw6OgCiuNu4ZsXzfYd3qkCsH7fIcMbuov3EIBa44UAVQJp58Edy93Rei42SpMzt1NsK+BwijZNGd+nRbbqiJdMJ98aA3cFJ+bv1AiDvJ5HtffMc8D3l+8PXHZGdFdofAnfgYDO2U2HI3SHq8H3MRMB+Rjv2vhMBjD1ETsEziAiWxye4p/owKeld/ummInU7f/b3IhS4/W22T38MRP+58jZPj8QXoiu0gs/7Ab4zv/cWz+v1h0eGdADd1L5XcY7xA5CVglFfjpJAt+fo+uaj1FWKNUrw/Iocz/rjA+hHFH3zMgCZ1uZmCk0i45Mvzgg3Etr219qFS14jezJHLVfA5QCfkNaG7b2xym1kiVzNdkf8FcZ6K3+MazBqdwNjlwPibrGjOtEnOHju6/ByPYa0lS1mQNHrC891Gx7adt0r6yJStJNILMWQ02d/1ug4CIUJE6nS3g1Tm9hu9PlL7wqP6irKCxkv5jQ2miaUuwXxNokBu6znBhNQI8pX62CAmDwmoga1TKDkkRf8Wh4GuZy7l7S84Q+/oeu9Q26I1XPPh7xH5oHp50Wm4ZCInOJGBwJPg+JrJZ1Xgr5eEnje152fa/0dB4yrP9qGdDF9179msKgcHAB2dhsd5PE9QHYEdh52GOtU71UycaNc26mZ9sdZvH3BtpLXZO5Xf3tLob5G4pLTKelNk3TH9jPdXov51qGPIpeXrrbv9iCNz6a9f4WvGJr+g+WlZ/4KVf7LJa3/v7oKfrR8kMt3frwyxnnqCX9fWw+2eau9qBuJaQu6cb+mdisWCjzoESHSujm9Z2asls6uws9GHniDnAv7P7Fsx1oAEBdgXVG/6FnzTKoHa9BUaQ/yFR+EsP/HP0KVdf5zidoaHhERwqyYzzNcXvNQ91wFrahjzjRNaozgPOUGsDzs91jOS/Cp214IxObIz08ZdDAQ4yHl0swZUEO04IH93L02ZnE8qj4tR/Pz9nTZzKKIbQf5pwtFdDYOMLxX6SHlQ7ZMr2wi0ExL19IXXW8aQ/Wf92bhWMwwYevJ3aB8S5ZLX+3JxRzfuu9N1d18x2Dsumn3rftfA9evHcnv5b28l7+3vAPo7+W9/JvKhUIxlFau5OrA1luVnq+/FMGlWlofey33d6If3INCjTy0kbfXrCfZwvo6k+TCv9VRxfI82juDWRRo+FxjgFoVVKqgCRB0T0RXjFRQKMPVOx2BQVx4skQbXhiH31E2QtpfYb4AZSCvgehZbH/L9fjdGWsHcGy+j5YjezfNNvUpz3ATrMsZa62Y59lyeHEAlrmvYiGualUPGQ3HVcFlggD4rz/+wPPxGeuqoOupnlFKwdfHr/j84TOejk9gqEXweV3USxEegUCVSU0aJhRdE62iioBEDTT2uz0IgrqumKaC3W6nucXXBWtbsZOmHrWiYP95WXBXZqznM2hHeHh4QCkTChr2ux3abgfsZtRSgFLUynetg+5IhTi2fNwmTCVAyj9QKSg8YTdrDqjChDJNaBAsywKBhtIXAw6ZzUrahT4BYIDZGQRm9dosdYWGdSsoE1sIdQ03T8wwd3O0VXOuO4DOTGHprN5MYsAAWdh7MUCewzLavYnXdcVunqyNFbVWnJ6fdb+aBfe6rtjv9wAz6vmMKrqOpmnSnFmkIfm59ByWmgyXsN/NKAAeLYe7K0w17D4ALuqdb8CaK0tVwcA4EaERYW+hoImAdSUITgoCF4+kYbuMWgdekZTUydjAxW+SHvbzkP4e82awz0/QfGzbfenKYM9r/iDq7fp8TVEJ4Bmq1D+IGDivNZ2AATCnVDegAH0oRO03BjB9+BB90nndCm8EijygMEWAaK5hEaAx1rpCmqAURq0KBBCzhmsPUMz62SRC9IsIGnpec4284NbovhaBWsczESwoGwDEv9UNSESGMGcPcoiMQLCdGURkOb452lrgiisfOOo5wwmQtuo68TzwUOV6fkSVCDAaYXn1TPkAa4OvN1dGOE112d7bT2hBZ0DS58NuplCVYKin7ysfrKRgyGATACL3MPeQgGlduWeege+rvd8jGiDonrWH+isdQCTSFAvZAEPD9a/+EhQ2rwLWiBqFuSuILs5wned50rySGlrYjDrYgiAf9mjPgt2dKbWefd73GnmCrkPYnqmUPaWGj2sgJtc13pzUld0YZTyPBcBsszXbu464Xu4x5it9vnHfLfbG50M/y02FEZF6Ow38ii9VAMMPcvHh4v19NdLFHUTjoBAhaI5fJgOPchQDyc/6Z3Jlnj6lKUNsX7uyz7lFQQBugPGSATj2d6fkQLa37N58LZSdI2CumN/IfQmcz0oKUaOPHZ6n5JU+Kk6vygK85YEF3DQsrD8TgF+8M0/dps7NAUXXl/dQuv4xze0GGLhmnOtiz3UudbNhBBENSa49ZjKBR7DwdzovIyYruHce+vQjFoUQwBIKVYEZG1MfJknPDwMUlxL987GxtlDhWD8Rdd7oGQOYJkYhjRxUzHOMqvIe3MzTnCzdhXtO14YmFSxlBM6Jok/ZY7qh9SgppOtRV12J7rSm6UuqczpiKTJEgX1qOp4sApgHXzew8Pe/tGLysDvfQTZPNQZO82jrez3qDUTflA2ShpUmAt9N3RBd4jwIHlcaahM16ESXh7w4eF6jGy3+kMu/1Peth4DnK90mQhhiUNT0BAAouEenri539zo51yPunY7oz0h7R6J9bVfFYu5H0khPjc41ky+6h6m/ST9QUZCiWsqseb+zpUfDc5ErHomXid+TkdILJCA+Sz8DtsXtBVMrL6vcANbxyObztXubGXPGOrza2Mu2dTbB1yTSfZlXvWgsgJc9z6++aPvezW3fM927UrYe6b+y9JP97y8ZOO97roPnfh24nA3GJ3yht4UMv7V8HTC9T4a+AuDZzmV2Ax7qbydmLOvZ+OMJTGwe2LqbhQTzNIHhsn3B2XKqexo15bM56PtaTWeQouHIlXV30f6bK+jXlAc/T+01PkoNX9G+AA6DH/75T0z/LNjJf2H+37YHIfho57ngO87/WiD0aM93Dk4ANZ726BhGJAQa2apJA2pVo6m5YL/b4XQ6xtbnkBk7nT3ZeBfWlII9lVU3Qvbw+oBYujCYPoRRRHUcz+eTPXV9R8xF89qvtWZSFPqa/Kyfaeqw5J7cmXvcGlp28Hu79iOqyYb9Si0Y6pu5xJkhaN0j3tZ9tXNkBmEhcxIxPS6JRk104/Xcjm1pIDwI8MwaXSx0wbZSXUdZSIH1c12u15MMGVzP03t1e6372eayxi/Ty/9EufRCfy/v5b38zvIOoL+X9/LG8pLC8WYxpcygbxwYIVfUbOREBy1IH2itYWmLMk3GNGhOWVUSSuvh6QSth19F9wbPQEpuh4PeYx87U6bt8fsViFIAu2vVVDmgqt0GQYBRScslAFZp4CqmRDCGy7wPW2soCxuARhFGUBU8yowV7vmI0BhSV9C6okpTbw3SjpJouF1iwjRNpggzYaUlXzqCO9FeMrHBbPfr1xiW0cMn3S7uddKv3RJao45X1tdWmfJayYrgl4oDEs5WcrGOiEQ+WPWeFAiph29hywkl6q29yHIxPs5Sg4AqZixhORWnMimTezoBRAH0TmVCWTgAFldiTaWgVg5mHNYmDbkkaYxdkQ2s6wqaJhx2cwiZD/cPuC8TqJhyErH4UVvFWlfMuzvUWrEsq9Ztua2YvZ2TWol7L10hMbQhz7cKCBpWnbEuC9bzitPpiOenZzw/P+G8LKhtDSWew2Bd4ScWWjEph/w9YLRacRIBrxpyvk0TJikKAHILZWRdK+q6Yq0VtXUwarV3aN06/8ys0aJrs5ygTYE1AVgYVc4QzChlwUqkikMi8KT5reu64ng6YakVp/MJx+NRjS2qKriXuqKUgrvDHmtr2LWGUjRv+TTP8I4K1C+ckNIPAD1Nmmj0AWJgnicAB0zThHXZY1kXPB+PmKYjIMCyrqoYTIo8JjaQrWoK0ADhBQFsGjhC1D3cIrRbgJY2byKai9znKtHap6yUE8+l1mmSe1dzp1LD8/GXRqBN7MYMsBk5dKepPm4OzOIOwgxKilLNF+x9LeBiQJQNWLWx085qPXVdsKx6Pi1Vwwu697eCzB7GzQR262M/G1o3DhH3Nu+Kbkjvg49U4QIpW3qZQiZSP2NiQEJu1n0zeW7ujd6zioCoWfjmFiklfJyZvU9uYKL0oTYP2S6AGdH4TtZnXbGcaT5Cq+ggV43DU9eWWHubA+/UQxoCyavUgW5xIMEXh4EgtuZbeNHZe/x8BMY1L8YfCEGowlrS179geN+QGsTXmivqTVnizyGthQinawBRNxzQM7wUQqsrRDj6mD0LmgEwbtDg6W4iVKrvXRGUB/PSFIE8CAQPGur3GWjmke7vjjqiLWNITr/naPccMk8VK63fO4Crmzr8WvHlkK77nBAiW0Bnrd5QmmjEj1wUVNyAqvl9qVFOD0al62bvSb4/8x6bXjs/wZk+mNeV3x08h92HHorfIyb42ag8nET4SjXaFFOsIfhAbyLdGLntfOkXAlsKC/2qf9kMu6ypcZ02zzNzTz0h/by54CPzHoHSDgf4WlMDI+fxO6/f+v68UPqZ0hZqfOe8+2B4EnuUrg3HOL1BHzeE0r6Pita3rsofKIIAGTQolbeBgapRiIZ2J5lj2xw3fHOvbjcahdNkTopJ8SdS3UD3Qu5viVJ8nG0B5xFrIsBqvAds7AUoRCg7BjNjnmdMzBqNpRl8vWr7mnEFDQ1SnUcAwASm0j2vrc9+pmpjEz1JfCqDUagbZSpAa+cOEYqvL1vEoVyHAMJYA1hgZPzZww37mZe90X3NxnkAX9c6pYJkjJVGsLVm4d3V+4y4KE1k88QM2Uvfl/mIFsaVPdx9T2OUjNAGIc6GF9jMcuqn15+vbT7nNSDpWjTXQR2B8eCdbyFrAFN/jsX4cV9nA4WVYX1dpWs3e4NLum6333wi7Z+XSvBZuKQiN6jv9XL58PVqxEcx79XLW7dzda26t+t9Ei9mFQz6Afh6setuQZPW7dgOX/feh0tvylhfdH1YrvXz317oRmN/cdnqSggjeL4tHqr9gx0cf7R/oNKf+PYTR9pDes8z36qANn99SytjUbigCWNmlyuAUorSKuM9zouC7SpTd6A2V2sUdvPm24Yov6vc3G8Y6WZ2Ntr/c8b5vxfw54L2xeVYDdeeaetQXzIA6t7nwGpyLzvfBcLj01O0oYSBjz1jY9vFrQ3tMzrpelo3ZvAfuzd6MxnvevHmNun0JLqQ5rfT087fZm/ufpJQ8D1vm/GXF7wd06Fn80FRvqqH4e93WysLYbIzV/ULFPoKJn5xTLxVT6TgueoHTR5LeisRUQAdowyVWxL1EYa59bN/G6nJHTHyg7fA6yEClRXXfXg92av8wgj4Sl3b8g6cv5f38u8v7wD6e3kvf2eRzqz1w7Af1q4Ezx4VQzg6K61WUwBoSGSQgsjBaFEFKiBUk1IbybIV6EJ5V64LVMEI88zUJgs8JPoQmtGAHnJlQRbo1aZQwwBC1AMwFCaAe6JT6+Hi9TmCUIOsDZVWtSpcOWAQLup9XEy56iAGmNCq5nkkAqRqSGopBKqsIeBFlUOaFlPf2ZpEzl4XZOFM1FVeJak50nzdnGpgYHjJlGhRldf6kzpG9zz/JNetxLP+wIUwICnMbqlRzHITpAopVUgLlrAcnQJcU7yjqlKHPZy35uE6L6cYg9YEh8Mep+UZba2DnodI6/j67St4mvDHp09gYvzr6xec1zMgwPl8xnI+Y553OC9nlGlCMLdWSZYT3SvIwb5iyrVlWbGsj5jnGft9wVob7u/uFOQls1A2hdpaqwmkrPeYELtCcCLBwTw4OUJTeX/c200V1hc6adWMYV1X1HWFVMHX719xPB7xdHyCCDCVCQRGoQaRoyoLmwtFCHB9CIvJJhzZPl8XDSk2TQmAFGi+TPTQ7XU18Lx5/m4BC+HcTirYuGco1CNymg0Qt2gDExgTTbq3RMcNOEMWpSdTmZReNMZyXrCuFWe40pPNg8e90ytOAKa5YT2fsdvvNFJAYfW0Il2pDUBhAiy1gwAgUXrgog2zWeVzgex3WNcVy7IAxDgAeDovOB4nCK3QvFhizylIo/X2/d6aC4W65p4B7PKU2nU39jE1aHg2jyC64F40K5t7jvt1y7gcHuzfbI5dCbNCcESnLZ2+5zWm3zOoTqIh222aQljdPTz4wjUDFFVMMxgkbLnj7YwxgyURDymLCN0uVT3GV/MabhUgFqy+B2xfuMW5k1NXEoWnNbqHUjYYyUYKPXy7kbUJaZP5hxrfLqO75K8KqjUHODYkvdi1ZmPYREDVjWL0OYQgrKHUS9HZX5cKngqYNKyu9pdiHcPalvmB5DrVVRymxLOFnpRBYgp3WPSXBGAxoVVT2gjgOUdh4fPjzEPf+1lr6+sq8grDhXyxbIHGU9jx7q1iA7qbGTs4khLnEVEHA0Xz1YFbytmnYKEYKMiWD31Zz+DGWBYLrc+Jv0n1+2cR9eCZuGAmwfPxpGvb+Kt2PAVNuzjHyUJnE2JNrNr4YZkJgHN+KYA7m4CTK9fy3EIjPxDBjJC6IZyDRFtFieeE5DT+PnYxDwD20KgTo8rsSpHO30VXbvEgQ9Nlc7OtU0nrMZ9HqZL4TjS0zxVuDp47kO4KtXx2Kp3giFaOIAIMAAAgAElEQVQBuBGJDoLTB+fh1LhJwsCTm4PnzqnmT9aupJzNv8ZQmAHQ0McEnmN4Qtvkod09HUuz9U0cWyNAkZYWM5F6z4g0NCINuepAufXVDU36vpFY+3ne+vnvfRp53Gt8bBiNeK82llfhOR10DIBchslMp1Q8vF1umR+8uD7URNHebtTi7TW+xulhbvuWB7t4t3SaBz/LdfYstmi83//NWyL30vBmCCx1SNq3yk/bE1n2EgWQp3lCMSO1uczYzTvNazoJWrUIRBMgtQXdapa6J/zMaDRQg8uYSdb0+ddbklzDuscIwNqU9k+AGQxqx7x/GqkMarSMAhH8/+y9e38bOY4u/ICskmwn6Tlnz57v/wXfOTPTiW1JRRLvH7gQpEq2k073TnaF/nUsqapYvIAAiCuyOXUlgNEzmZlzgPMLmBJ/2i+meDen70ahvhgN97nxglVRzwzSDDcpiWzZWM+CrRvLq+8ZOZt2pzzLKMKdrqCvpZ0PyHlenzPWhXwA4QWSFegpGGqMfZv898AiCz4EOuS4iGeAnxCZD6ugRF69pK+a6Qjcoc6cbt3BqyO/yaR2dhqgi7rTB5uHvvd6nwM1r6NZbm7fvot83Z9sdt52OWJ8f+e3EzW40f412Nt46l9ofG4rXDLaHF/PbPNB86M+slu/26fuAFuHy4ZLE/NF+5fN+O1IaCXBNy5e091vb9DFnw17yzMYj37Se6ydz/q+bySfv92INrAa71+n6/+LRbaS577i//6v/0Tj/0T+598B6LX3+IrCa/zi+2B8oc3DktIVthIDW7GMa0npZEOtm9912ey9o7O96HFU1mwNBPYzak7JjeluAGWjdcJjS23ipHVzf30f3JqvFxpveIq0ADKHnxkofy9OTwFIeZGvFS1JxPnxb/+B07+eh91z/O0zzr9/AwAseBLan05IDFDKUh876F83AngrOAC4GBkmcWUHtV6+C3beMhmQBnphGba4NTwcj0gp4fVVTvu1VXW+lH4uOaFoPwDgsC7Kr0XmayzR3Gi99Ju9m0iCSkzWbMyotTg97doI5f06fSZ/AzN17OsU2NgumHxzWLoJicFYFslIeVhXsAU1QZ379B7DPamo1gJvCXL4Fd7J7+cELJpdkQiuI9iqZQbJSAk4lYvqx0deaw4PNge/VUYhHjJyjHKzGb9tXsgDgK6M89z3lPd6Mpq7jBau3TKS3/p9D37OLr3DHe7wPXA3oN/hDr8IDLKF1swzGLzlwpFZLnaFwB6YYmI+LM+Hv7c+M9BtAOHgPt8fb3DxjntKxegdKnZ9RmJTHDdwE2WmC6xJjJk5Z1dcc1LvRp4Ed1IjBrMrI7xLN0IM+ObJ9DZEr/8/CwjiSd3wk2qiBwSZFVz2PpfeSRW5qr5b8iJ1qlTwL6Uf8Bo3HNYjWpXIbk8pCcKaF5y3C9Z8ANCjxACglAu2Iu2dL6/49OkLXk8vmsKdJOLIBNBJ4W1Rh3JYkWjslGXtJTWzrE/WyLfztmFdDxLdrQamrRRctg1Pj+Sp6pOmE47vkQOYTE5Tr3CZxAbkpBHsGlVZJbU5gdwxQVJeL8hLxqeHJ7ycTjifT2KkB4Csht127usSlXS+V6+FefZozuq5hi0Ssai3emu2pDJny9KtkmbcpJTQmgThJwIOi9ZYzwtSthTLIbUngJZYHQxEmZmkQWy1IjdG2baOTkTYloLDcZUU8vqfpXIHMhhNlaaqhlUjiR1gTekoB0vS/UxOG5acUZMYhlNOnsWCuTqlTCwm9RniDD9Akm4+xrUIxqRrmsc4ck+1bApw0jbmFMz2/HH6PUHSNxd8X51kM/bHqPT+Mtk7ZvyUqPFFnRzI96rhtxx2u3e2rYGkXte5QAMXBk5qbH5UoyrII0z9ME9AnRRKEo0clf9TRM9075tGoJ0DrT8L7nW6TRmi4Ol6m93ZDVTEABN5xAJDIkKkFmzS/ZBQS5FMLbkrsnSL9R7YhhaNSVCORIWqjslzturP2nmrp86mXeKkChwGt4rWxnakbUv3blEt3bDhc+MH/eDA4AyiR4d7v0MKQ2iN1iiDeMpknceGitRyV0QY/9W5tbVrTaMtldfkWGiXqNeknnmBKleWnDz9OrjXSJ0xgkP/3mKnH+XrZtg22GvTjOj7qqL+meM9QfHMEEP+R9g/0X7a2feUNBz+xdXnsMc4KMBUPu1KvLnFG++kW5dYcHRHaeVjiAoufavRtVvjuvWq6wv9RzFrdSyyPR2dYaUjo2xu/3eF3rTqhCmF+3gNAz1gb9fbD5dHY5c18JNgT6hXGjJe2Jf++yM0fbcPu5JngDfw5+ptb997CzqH+viVeIfLhiA3BJvjBFtpGTXQpzzNA8k/4tTcoGIVmIHCGcTs56L9aKXZyD9BXB7nsUAlLVMC6qR4bsas10qnRZkMyfal5zTnZ9TbNmc4cUQLCnP2f0L/pU2QyJ3kv+td1MsuJKf5keebd0qXDczwAFgCGnbZ+daKXuFRJ8BXV0/h++7cszhYcbj/YcJLufaC9u0T0pfusCE0Rs+r+hfgYe/3VSd3AIOef0GRauzsh53BX629TfxbuB+a7X3vz/EVfXi7uZ8DIcI2npOmRYqfbtEPHro9lyOJ7Vy34PPudLrjP01Pf8+kzKv51pN/+lT/YsDAVVT5Z93mST9n/AZAnD9isMIXlvTu0sbvw/N/VBcTDeGVxzJX8ZwZxFwdz3hWikcac1RsLrvY751uuiGZxsCdvxpeSIzo9hdQZwj8jowveq4Aqruc6x5jxvFv/xvnf/3D2zLjuUFFT8te1Zm01oacJdvPkjOoFRA+4cDP2ELtcuM3ouNx7ynJ/mnrRH2tKlvKdTvQyR+pYtiQ1Yg+yLSEgTcyGEkd1jwSPcq6cnp3OuDBIPYdQOQOPxui/GHOZ7XVTvmVP5t+2ebS9AYEcQCr7e1o/AgHDV6xu93l0fkri4PCe3Jf6PuieuGZw71n4L4Ft84pd7jDHf57wd2Afoc7/BJAg0zAjCm6XO8irY9GFukNlwzcRrpzwGfAI9GH9OzDCc3SjVEX5FSor5B0t54q04SmoJiWJsQAZvVlQeKRKHWEraMqOAIe/YfWJNWwmoJsCEm9+rRyX49MDUrOq0jEICzZlV0jSz/3Xs2xXx9+9+l8F3x6f1DO+pc+95nlQDcfBqP64iPQo5TG520SLrWAQFixuIKPCGitwIxROWepJw5g2yTSb9sunurcotdt8k+XM4iAh/WgnrNZaxolFDNQae3G55dnLDlj27auZAT8QEUaDW+R5ETAQmLgXXL3GG3MOF1OSDmhcsXfvvwN501Sz+eUUWr/nIjE6J8zjhohZCmbPfLPlePUtwVpRG0RZ4JSKtjTpUst81IKwIS0LFiYsWj6zXVZ8PX54ulXF1pQUbAsK7btLGNEVxSyKR1NpWN4pYpJZq0pTWb4bJ6avFY5lDdicAOWTFjy6gtkHrwJhKrG/8eHR6zrAeuyIC+LOhRoFDMYfHlFY61XnDNq0VRb6qmccwaTWO0vp5PTi227YCur1EgHI6eELW+glDXttDgEJFMoDtYWAtTADp8P0/cmWcuccMoLOCdwSgAlmRN5EpW7kdlog/0PwKM+CWL4ttdGErx3TF2UVn3Rtn53Vemwy/zTy9REj15ibU/68uKKwTAFkBTSBKmpKbMy7uvFFIKAGoNFyZ0oa9R58qwS4q09KiCJSCK6SgWjoakywRSDjRk4mSGNgFe9RqQ1lUPWiAcCcUwr3VODS3PBQB6V7jaAuEAIiqP4c5p/0J+JuhNVYIrH41GUWAzUWtFadeVFzovWBBXlFlXNyBHSR1s07LKuuFwuYFKaAVZeQq6kM8Y7GMu5R8WCentm6NZZEl5se0H3hvNwIRASna6lEpz26jurRjDK3rUdI3TFeCcRoZY61Av2vR4izE2B1fccgaRWB9gUSdyVyVJSoNdqzMvqWSUQlEWNpVwEACxZXEGe//ENrTEe/3bsPDswYnPi27bNeVfSuuklGFV8Xz8+oL68uvIqPT6ivjYAp51kqcAFMrajztd5R/FjotEx4NwLOm0BxBEHwPAOQqgPH4w7ji9Ejs6xLfn+NscnSsh599IuxH1oQoobatEdSuxmk7miU5nImzzUFve2qa9BvxA+BnHXo2cR+uSjHcdrMqiRHzOyWYp/Gp5Rw47JqdEBI3bJDIfoJQJ8ID7WsL8mVVyMAm8NQNvBGSslsTNGJ3lBiR73nW9r5qtnh1aYhjlN3k7PgDU65EV5cL/dK2fbEAmO6dNVfyYM9vMEzarM+bH+7DXWx+fmdsK63+jVbeA+6doUaz0MsnTnsVcuSFzjUwOQtKi2ZewyzBOapxG6TNiq4GtOjHUBatEOTBG9kYdxyBrgzl/zjLQxmt/K4zArTVJccxy336wR3UyEBCLjL9344sbzKgr1ptlJrHSX47K9Rtu1PcgauW9OnLDzALohIY6LoU4FPKWwtc8Wjc4WvS8/V50rNdWPpcz0vQMG2bqjjeiln195zDo0LLwiyAOL2WO4QzvU8Az+9oT8uRsBbF9KNhz5Wc7bdha1/AH63R0pKLQgnbStZS508/50/jgJUjd3pOFCM1ooEfGeKU5vMl1EN9jZ+/ab9OeiQTD8Nbo3OksKb+5tdv7Uv036iD7wqT+3vuucUfjN/r1BVCiMwzLfAQD/3qP36bdxHSTy/OvQytTj/o36Hbfo2lvX/nLgG59/ArjJlOXz53btJPONgK8YBRBL6y6r+5s6E/2O8/8DiH8bcsEn/m14znQv3zCeB3fhBr5b+mqji073VFRIZFnmQlxx2L6yDY2qsAcKECXfosRyRm+NcTwe/BlAzjpMUIOmGIBvdhiY9tTPBTOeE7oRnQEUfBUv/vBe+3v+/R/6faJ4esar+az0JynPkXPNly+ylvVrBRfGCzYA30AgHJYFias4IutcAqpzVGG6tQrLDtBaUwcxKSFVWsPr6RVLzr4BVV0iRnsWPZFkaJMzWaltoI2SBUDx0koU6dhiMEfV8kydXqrx18WWWeYc6eotmK8bR1nzorxQ+PG6SobKnHumQuujqG/lfbWKO3SCljQ0fo63pTI/o+YEyQDPbnjPVrZGGIJkP52oPYd2bJ4IwL/sUR7fbnotmBE9dGTO5PUeRCeVPwv+rej7He7wPwTuBvQ73OEXgKhAN2Z/FYVAFlHIIvBZZBkP+st+O8YDbDd6oysd+1XYQXioIRk49xxzNByO2f6xmyVFpdRM1tp3Ju21Jima1Gt2aQROBGp6sEimvJHI17wsIE2D1Kqc5UWR3utEzQd10vnykbjCq99ArB6jUfq6OvHPSoqrt/ypkLCfyv1HIU5BX2Vbe/3d8YTUwCOpo+xgtyyrpAmvRTIH6L2ZMgpXgMXAVDXt0teXZ6yXBbVVLHkBJyAvi+J56f0yPA6eoVGwZW5+yJHDpKYMTgcQAXnJgjokGQwyCOu64D//4//g99+/wpTh4tEqUZiNGxITUlo0gi/5weUBwIsaGVkVn3KIkHrIWytI3OtQinJLDLrHo6ivUyaUZUGGpZ8EjusRtciBaFkynp7+F06nMzJJfzaf1+Q6Wh43suzdxiBLaT0prIgSlhxSsWa4wRwMUFoAsBoQoftIHSF0T1mbFl1OrSHlpOkZpW1Pf6XtMoBSpJayney5NZTSvLY9aRr2pVbUbbtSmomCQCNSzTDYZA1MwSpNq/Ess0ehP2vGCo+etfUJtC7uZKOHQp76FQ439jRwfc+Y0SfW/7wVSX0LeHqfkChCYsYDgBP1a2aUGpWDo9oxfe7ORASjob32sETmi2JAsjH0liSTgcy/pWuX7mkKg5dO28V4pe9q8IM8SNX0hjgvQHq8Jl6j0Zz6x/k+mLI8qlw7pfK1m15BlK6ypQBiPJda3/I75YSUCe2ySTkBSLpYAEBjNbAT8qKpdKvgPzOwrgnLesB2uQDLItF0tlDk+mYfh/2O8JvsGx7nxO5vCT24Vh/kiLtjmlFmw8F+3ZTt1g/hd+R12wHZi0mN83IvoxXBH6/S3thpor7Z6S+CUtvtMXGgAFptqnhRxb46wc00zf7kp4RateQA9SgHn0fu+hRTKJbaruaQmcEvr2GC7Opo/tjAOAw7qyuu5kwR4x23lRp7LDtIR8P1nWzGfs9HWb/xrmEOdua3Nx65/5Ugd9XGGIGu9H+WT2/Ae/exyYb6+qvMEoMIrNk0FB89i0o04OP2vPm1eFOcJmcG+j7v1khrXYEXSZlugAbGUCw68Im9/tzGIp07tihbvr2+cb/N+wCRZ/Urlq597sFu1o+J3uyCL9cbODGt0y7sLuBbq3rd4ltdna8ZPtCNezheo75mZvKlIPsAPeuEm0iJlB+YYCUNqbioLzA8jm28sS+nq/GuOMOOn9DiJ4oQZLxicoiwfST65QSpoNON78mcVxguL7TWxGAPgiSwbVI3PbxH5EEpj0RJXmsp2aOMP6Qe9pT149kEKms5jR/WasyEMp93+oe+it8LV8ZzSHp3a+pEjEeeVyz24QX12yfkz7peHLr0VjF2wxtHyPlGxpVl/I9CmCuTpwcjNt3alZHTjVyPh09vvHbv944IU9fYXzFI+gH/x3Uf90kHwpUDzzudiW5nJo/w7YzsCl/fu8G786vCVYbAP9KW/v3MvY45IBHhX6bf9t5pspQ5STN+70EJ9PtE+3/XZ37D1wm/3xvPfN3t8twd2jDoNew+ScLORkfYnIxo2ELNdGnSUdmLIAxlboIRWkkGGFqmjDE4YL07kJ9ERm41/7337X032cb4E0MCBsBA+ao551R+jQ1spYR1YADNa2t3nao4E7fW1BlL1qTUpmn5Z77cTw+uF4FKgOEMZe1HmUqXXdmA6qq0hM1ARoGuG5va+FkQDdEyllgfXHh/SqJ/Mf2X6db2fNr3u9gHJXptO+ep3oYZS8p+F0Ocv9sHBmxyV9T7jOMLjnvTmeajsBe9Pqdvf+vZ74UJBe5whzv8yXA3oN/hDr8AuKAM+EEVAKaMppDC1ABxu5bAhva64mcWZMy4ECPRiRDCMC0CrTN5E9hGz3BTYsAjYodqmMxqRCe0xLCkpsySoZYhRs4KqZ0uBkZRwdghIBFJLVoQiBoqCGhVo2wxDHAWkIfJMEhBwUfQSA2f9mFOR6PkGIHyppIwzred63/wJPlh47njSxdI98BrWaZlt1MXNXqvWECpeYrishVcapF05DkjL+LDbfU617wAaFiWRQ0eYjQ5LKtHgqaUcFhXqadNhKenz/j2/E3qGUIjyFRpZqMwK5KnbiXCcTmCWwWzGLMZDUtesGiEfMoLHh8kBvD8ekYDe5r3L58+o1Qx5BNJ5PW6SlrxlJMYx0EefQ40dbIQA03OyQ30UrNWUqXb/EuEPcTQ3FbYwaKUAtZIdSLCw/ERpuBhBh4eH7AuC0rZUF+fZX2YUdscUaHKGj0INwJQWz8I2Orr4S3BFLdwozjrdUnHbk4z5PMu6N5rOTVmNEtVbzo6rmDO2MomEeAseFOLHICs9m/ZCqB1a7lYRGrG5bJgPaxYWWppOb6yGMozETJDa3dLhKlF4Ur3JJMBE0tkdRKczHnBhRIWEuGHdQ5NgaDIhEbk9Yo5/s+ioPBku+TL5H8r2OuQB5UZRgNHpINX2wysRnKLRH3R348atQswDiz1zo+wemJA0uTyjEifGemzpPbOqY8JjF4z0xTSWkPbcUkJeCkVVRUFvu6tgV+7YtLmHQzPDJEIUkfOfjfLpkGd00qP6qiogKBw2eqDsvG5MKuW7pxEMyRJ7gZaZgYrVaoQYV0PesDXmqK2FxprzTP1qDecIElXZ8oCYik3UIvWXuUqaROZ0bZNsjVEi7lqQ0wJI3NtcaCGA7ZOQalLZn62cgZ9RAygVakVaOUTjNHbPFbNJJI1YsDW3vqUEnmZB3t1Shnb5YJGDeu6hCFo1K5r/nrfLYLFeKO8x/ra3H7o0RuuiAGQMsCSbcKixms9o3HD+mlBqcXTkdvMVKWxZm4xBUutra82iyPIgE96c/70JP1Wg3rTG4rTYPZ1B6DOSX0pI3Yd9fdE0s7Z7yE86DXrxUXvd6WSvmdOQjgnjbUElkECw1vQnZhsxnQFdcmM9pkBisLouuLf+qJzGaxvjtIhstUVtm90TRS6qphylKVOUwmjQWYYVMSpkNKZaIhcNfyflVK2RlAu1wcBXxBzGDVxt4/H2rctZtWoO/5ZWxMHgMnvMV1noMpX86OWzL7iShiMPnuEvq3J3lyFMRv0lK5R6egcVF5lb+2sAII340t8m08102/3Yr7IiB5g7P0L/Qng0nZoqkuFFNZ2fNsbUzO8SfgIOm7vTWtkSDYEXYsUaGrOQpUulyop2Wun7VwYFkBlMlFlyQYEYlCVFahGL82gbAim69BmR6u3BuqX4zPUPzfgsK6olws21lMZpYEb2x6Tclk9tUVWBzzhm2JUIAISGmpSp+6A750ascrFynt1UkQmNWbca8uD+n73MUXjuWVasqhzK9WjZ49YngUcS4fJvLt/i5/1jAZNdGKc0FsTPYBlCeLpPgbgdgh6Rn3+JLvzk2XuYjVukftZkNJHEHnZFBB5KSWXg+xzOANAxzqAdSz8HHHlqt96KeWEKL0UMz4ZfTXHiymCVDKPWTY6+PmqRzCm4Z1XzlPccajfFMQRI5fchwd0fjIagvrz1Ds/jTrywRu01mk+PCNeUzkEDLSvAOib9x8A+F+f8abR3PCidfnT+4Ab63IDZiPznwHv2Zko/P9HYH7+WffFF+3AV5Kx/jaRRRt/rJnewQzk+9Dv/f3qnlvPdMflERZkp/0uTEDP1Jo1A5CMEwzGmrPiJ3W6xXG+NRuFNrVZBhAdvDjb9yjnrWyq55D3FIs8d5KxP6Lv1lt9pxX3JbT7xEDTF50T8BiaOuk4n1hCBXwf2FQmdZZWj+UW/4LxYjkLSDKDREmMuemZOelz3RE15yRn4tY0s2CXh02/UTUtfGfJlgXJ5CfJtGd1vL3vRn+4z2/Ws6QxT8nayUBTPWjKaLViSWkwZltt8D+qZ7TcV8JzusPyqvo800+nZGW55LlS+jmwtoqsugBzuDxvl+EtJoe6L4ESuqMG1FRuyMzYWHhF11GLMf1ctv0BTOjnWXYAjVjXHtg+ncpdxbrnHzGix/TvH00Ff8XbfgD+wKN3uMMdvhPuBvQ73OFXgMlA7QdaBszg5bfqd/Zn8MMnFaKgXFPhrZ+vx4bZ7kE84EKiQ8FdI6XjMM++CkJmq2sjivPKCcQVTElS9IBBVSKMMyA199Tgk4mQkkbPwfR4FYV7uqveyT3txT7cvDUoooef/a+q935lYeYdIZEgSjL1dPDBNq4gjTbPa8L5clYDSMW6Lm44MKG71AJQ8nrWLycxYCx5wcvpBcf1gEvZ0CTs0aOHm6ZNdoOSGdABXMoFnw5PEuHOhCWJ4VSiWyRy8/HxESmRpFluwLmccFhWHJYDHo6POJ1fUbnhcFjR+BCUpV0YNq9mcxJoraIUhLqVVVJwxbR9LPXBa6u4XC44n064bBsulw21bCiloZSCnBJeXl+xLqsI86o4ycuKz5++4PX1BVsrkq1BDxM1GIfMKMW1oKmxe06f6Mp+kqg9KeFuBxipHc4aVW6p3AFZy2WxA6Ma3FpDK0UURmTRh1IzuzEjc6+saUZvKzNhkd2s82iHebLTpB0yzXCgB8mWgFYZlQqoRa1Zp3mktEGiq+Xgm3NCTQl1Z4NOusNhO0jqsWkPhPneez4aSsa33IZ4f+zhMbzDf4MGJV0p/WI/zahESGlV8sX+EGVJcR873yN2zAgZxmhK6heGp4ZzJYHhWFA+cgXxGEHnY60tfKOrG2KWCY8a15knWDZk4zl6o6UxV4rQQJq0RCICmIGsuIHwV1KIdyUIwdL9dXIoehcGE6M0MZKTZuFoSTztU07YtktXdFE/fFtUHYz/mRJbFVtmRPJsGkLcOr+00bbJcSDQF3MGMWcHSll/q34929wGY6dr8Ks4H5njijjGeCVxmVcmNDREw2Pz/dcVUYZrFPBCbJGi7uoOHBqxyE34CnejrTmeWBspRjvwwN0dSquolf398z30ROCpXkJ7GY3rPtqu15zkLCCj+xUyeu1zgpT5GGqU7+D2EcCFCI/hfab0v1JeEu2O9aPg0Zo2l6roMgepMUK/R4wMmrwfhNGAzbCa5iGNwnD3IFcGur6nXPJSI6aoCgpk8n/m9sf5vRKRww/NnNQ83XuXKTslCnSD+vtdwY3JuD3zBB5xPfINMSP39K48/e91pXd4zZWB0X5Hx3FzXvCzgk2A09rr53e63hu2+bua1Pmm9377IEzvMXz+4ZaNJIdJ2h35zo82p40ZWY0czOIQelizyLs80gSujMYEziY7FXATQ8mcZUy2guGjTHJlc87Dd2zV4GCsbW2q1Dbcc+c/htJ6M9zqQwnIyFKuqA9nTK6wN1UmP+tJSZTgSTO+ZEdO55fAoLQHOl67cV0mWmVgibg0h8rWajdw+B6xtPRTJ3fn7oYDzw/CicSI/qp/h9fqFwZA/AwQoT0/qhGdwM+M9MknaOg/U5cFfU8zudP0kE2A+rj8+84YefpyaxoMl9wZg7u8Rm8i5fg7T4uy/9T+Ql33bVy3W12wfWNzcC1Hd9psX3nPoybwBbu/k3zuN+EbruGDEefwZfxuuLHE/yOAobW0+RZO/deApbOeDXPO36/wSb7nJCXIUOvQ3jw24+miD4x7X88SjQEtIzK+7d8HXgjqFt7p5R7Q9JfR9zyThecgROOPz59CZonhvMKsZbjIM+ptpWq5v0Bv534QxDm0mYxmARSWLVE6IWezzsbiec8dtp1I9TV1XjgEkSi/9MjvnwvmMC142+u4I5kejINDiIFlMpR0653XvYVtM6+Cp3u/MLCoU2JjOYfnlKZ3vg9DqdIbY406j49AlNVuGc3/iIH87Zf/Oc3e4Q532Ie7AYOiakUAACAASURBVP0Od/gFwIUrAHYwZFYjMouSzXQJzN2YKOlzf0As9sOvRqVpOj6y0CiNyGmqjDWh1B6tHrFn96vyL0i3En0kfa5NvD0pqSFdlf8MdmMBESGpkSNn8XRMpoTXuUB2iVYiVL1Wq74fIkD3tNejEqIrAW6sAUxZ0J+Lv7sMPE/kO8BTW38auC7FhPEbKgqN0uAsLKLjkNwvaZwJi+KbHDCSprOqQErIlPFwfMRWzuDacNk2jyBPbjiRNV7XAxo3HA9HjWKDe2AnNUJRzmhqtFrzAgZ7ymkT2gkJq6Z1WpcVKSUsa4aldgWLwvHv//g7AHlmoYSNGdvlgtfzGcfDATkvOByPWHgV3Jv/oy4Is465Vo02d2hez9fSi9faJD12Y5Sy4XQ64/V0wlYuEo3NwGXbkC0Fsh3OuGl9TJm/z58/4//TMYB6TeNOIrr3OlntaVV+St/VOGcpOJsYuJter2XDsh7w22+/4eu3b17bCpD03m6YYjHW1VL0sAnXoEoaL0iKdt3DVsuX9UAp6jVppzIjVYs2J1i9MkTUYyE9pVZkZlAmiQb1iNCO12w7MalDQMogEkP6s5aCeEmEjQgP3FPfdSUtfE5f9fcjM04s0eF+ulOFNkEiQ/d2+xx5fm0/kR+eYORS2nnW60dTmgtWYEVIoW1TI1pXuAY6gBuVEmFdV99/RT22cxLFtTmDyPpJxojGFbUVz3bAAPi5+UjjiMn0OUl+a07QdF30e3qS93fnLPmHtLarRbAjxdbNC97a7u1Chy68SEevvErWMTsOu6d3TvBs5a5gV6eYKkbjZV0kpWzTbAd6v3jWE2qraBdGPqxIVfpftqLsrqkSpBuzl2UVo2vuxnxXFbBFXaIbsMkHoEpxWYHW2P0EonGduvdOxwHd94mAZbXQWttjGTFbTCsFhISUGZYNBpAMHUjA+SwRAyknkCXWIHnaZA+ABjpobXQnp4S89AheSYcvjkaGLqVtYADLsiC1jPMmNQyXRRbVM0/o+M3BhjQVvDnOlG/PAB5w+KKR818+K01t4E+2hQnl+Rm2kwikNTDhtc5Ppl7kjom2F0Qxp1Gv0EOVDsQdXAxHydoTeFQj+quO+0nvfdX3PhE5mRbng7f59i0w+i8oRL3MRsja4fgf5Ev773uVUxGMLHGD0AXq2Xpmox/7GvDQgPW7D8gHNvBnM8hbf6MSzN43D8U4RTS8Woal7mByS06KFBhdfgyyoEW7Wrv2Lm7iEChiSS8/YllOrH22frNlLugG9WiYHxTubNEyfbo6JWbNrmKK2v6eYc59fH0KrJZlH78t3KSs/Uly7ChLz7+PV2e+O0qs+/fstQvE1Lryz5UUb3jruBNogq1HapIBqYnDFbcG3mLf4Z8YQCkQZ+MsUVFUetu2kLaHnfOy4JFHVE142qPLw/NxbgZBRMplgSEZR1Qmg9Ige9g/SwMiSxguauYvcRo15zoOf+V/OZeS+YWq/J5FnleCZ3ScfI+HtRy7LXS42h5qarRgzUTF0Cyybsi4woQJ0SzCs++Knfv/AFj5ndM0oAelQK8AHkmwg/AKeu7PMj6hfWtIn4LDkJ3DVSbtznYs82zn8SRYyqw0wPY9jfso+VkiDJTguoZ5AWzdVYxxWJbVcRbo9IQnvHInxiZylcmnPSKxO9rx3p7vTMz3i9DeiT77bdz3UpCfXKaPY9P2xgamr2F/Quc7GjxdTvk6Gc9nvsJXsz5evsp/TPMPt7r4R1H2Q/AjqqafCV+m+fvC8VqnfX/Tz7+n6/uAXtf8e2Ee/nvNNG7C6zfIOUMb8UjwoUHCZpHirQ2XzSzpTvEubzjFlbVRunrSyF8Gg4x/IKLj2POeFt7w/Psn6KNGyAhPNh4aCcspblcAL5M+a0kZIDnzCM2XzzlnXMplZ/9geD7K1xKFnn0MzNDyXdfjsjJ32QI9LBMId/0Ls5zDjda4sx6AnM1RjDyLHsCodXLiMhJMthaiEzWHihi00XA7C9SejHTzFwIO6+I6n5wS1mWVfqeEbduEfgdZ0vvAYfOBUFp1HUekzw8gXGTCQCAsy4JMes7WuV9yH3xtFQSg1IYN3Znkii9M/Zkv3TJ090CZ93F3Np7vtbUHt/XNH99jN9D5Dne4w58IdwP6He7wC0OPHrnSCvaPrpyMqpR32rXnoralvzS8RBQnczRPvDr07Eqg6T9qIB8SdcEqQVMEaopWRgJLuLkbt6JyJ2tOe9aI2hTqwPsLXckpQt0gv7SuPNnp7gg3JvOjc/xLwJ7G2X82oZhVKS5CO4EkNR9VLMsBx8MDtm2TNdR0raWKoWalDEoZh4Mkvk3qobGVC1rdYF6/EgFjQiVhXVYwiYLGaqmDGWtePCthTnmozWvQdVaM0hqqHUKIUVvBVsSrg2el8O70iDGrVokcB9RbeZozSSdccD5fsG0XXM5iMDcj+mW7oNaKlDIej0dsteLh8CAp51NCLWJcT5lwuWySrisvYowHXMgfFH+utVLllI5clPZVFW8WDSQ1hbPWeE5k2jLCp6dPOF/OPntW8yvnLE4LzBJ2T4zMXSHcNBoIRJ4Supkh35WuGPtv2Sb00JfMs9jWIxFykyj+GHWYLAwUXXnQFwkwQ4tEoC9YlgWXZcGihzLaeuqvE4CD4kRs6chvRyKNpDIYoaLSEG8rmcxL3jDvITyg+g837gEY+kfup99/sbrn4i+QvYRC39PBkMmApcI349q2bSj1gqapZA2v3Qw0DUYMqSFNK4fG9Xp6EnxIwRvdyUxjod1mPLYa6kiSzj4GH8dC4voaW2oGQE0UFSvlruQPWnhuLLyEoVF80pFaGtbjiu18ERxWXLD0dAC0bEOFJVhETVJKhO2wDHAVI3m1NpjAFUBa4RG4YFUgd4bTI7n72ruBvNl3KH2KkSvU7yVyw60ZpilnC6EP8zbGuKQkRlpq5oigZSJ0L7AUXEaijEoJREL/bOKJoGnSLdJZepVy9vqDqZHXxQNHXqzOC7p3amPksLxXigxTgmO8B0SaKpABTc1+rVAx5X2gk0RIj49or6cwmxG9rnlCTCls98+0PxF1BSW6HEbU39EVd/C1OcJw3+4nD9ieCx98FKIxI8JtBZHRPEac7O48pvLn9Pte+0MEOoLR2rMuXKdZj3cTjE7MSs/x85D9whrQrlvK9r13xN5pp/dln+neSMMwXeuzGqXh67kWMcr2EqM73zWvIe38pPHwF/rswPPf6HMf3vW9V3Owcz2K0t8LP1O/tzcmv0b7a3TrwdvYrxBwPFJbx7TQADlNUwW6GZ61yLjNoTh86hmHja8CpTShXfYuDv9HfGQAjSXLEVvbhMgkQyu74zLDiGcSYaFFtXF4N4Mz9TEayVPZDtxTm3q0XZs+WxkjU6QDIErIrM4FEGdLte+6rOHGc+N/U/9ZHVLcYOpG9LhX9Lr9H+6Pkon8YDxpmqkfwPUfgVP4/AqJvDRa6c49z88AHtGeGelT6rIWxZN4R3I35Brt1/tcHor3B174cejuqsPmiCLMREulG8E4PSws7zd0E266OQz3NFbHAH3HSL8GyoY4d2+/frzobYf2g1vTT4W32vyL0PWXg7jKhnKffZ1+Ln/6HmiQs7Pg6fevXi/nJPvsrTZ8z8XvvwAYT//QGhm/YAmyacpDzDHSM6fZ7f5vb11qeIvx3BxNzfm0vaMbipnTMMgi7HztKltQPA1Y0AO6EwQQUv3rCTw6ttZW/R0iGggd/SM43SPx5Zvx0DylON/K5vLnrIuurQ3jNvxs7tzU4RJlC5A6ibMb21OycibdiSQTvbseV+PaM5hf9QZX6/QRY7eNM2bJGTLm3Hj/He5wh18L7gb0O9zhF4B4xtRf9Hf5a5WKO3QhzO6mq6ffBqsDCm6aLttKCUnbHCQO1shHr2cZX8ShJuCgZdRDvCkuSCLXG8gNn+K52FzZXLkBpF6zKYGapRZUVXYipEZiyKOEql6JBGBP9vF0fv20KzMpxXvl2agsRtcDmCDXFUJ7QljUfvnAb8IP6S9+BHzd9H07l2W5VPFFEu2XHO/k/6qpeHMTwViUYARuGYmAbbtgWRYc1gOIRMg3pRcxodQKag0vL89ea/i3z7+hValb/nB8AAh4eX1Rozt55GHOGetywGE9oNWGvGRwrZKCWJWVKWUwyBXnduhYlkUM32UDwF67lajXbY9OFoAp4Jr+H5SUzCECvddBt9reYEbZCrZtw/l0xuvrK86XM06vr2ilorSCUhpaK3h8eAQz8PQgvtetVGBh5HVBhrTTWsPz6QVdXdaVgRK5rmk9DZdUKZlYIjSTpoUgkvpeIMJxPXiqZ8D2OHB8eMDf//F3SSWvOGE1wZiBZc3IIC+zUBapn+wGUGafSyJ4ii9i7inVeMJ36imRQeKFTcRa1kEGZMbzQj2SRDpIvp4NbdqsqrTNCUuWiORDY2yNcS7F98EjgEpWhoFwhtQuJkiixa4Q0wOurTOuiPSAIx/57XX67dGN5+PvNay5/CuGwsYvsIR3BKB9ZaQvlp7f0uOT72MzjLba18lwtrUqmTo0mkv2LzT6fMzs4UDdcCpLFeNvAXqUvuQlYV0WV2johDgNqLYnoUtKTRQobFFXSmesXZD30ZWwpsSwQ3CwHuacUUqF5lxwPFlyN7aDLK17D/thQJQpTRP6s1be01rszKawFt6VrF/KoblWUcJYenW3opIrKaLSflh3FgpGsIgIq+caDXMkdNDGaxHG+tX4qhkrff0UmRhi7JafrL6fzTDwcHgQhUZrOv+EnFR5E1FUcSCl5P+zvrdx9QgJKw8htB3KGwiJMhoVXMoGbox1Xb22vPCG7ONVbwYAkgnDykMkGTAAi6hjKVehSFIbexTJ+lki041uFcMrbj6OA4vcIQqxjlv58yfwM4M0IrA9v6gs8AjCq/AsxZ4KMZJ86urOruwL+PlI8r1XHjT+dBWC9jGIdET7/15UhRte0OVP9mu93/adwu+kP7ozIim9a+pkIeyxb32MBnaVJns/AsUhTkO9c0DxOs1y7ugwM4LtAwRja1fE+ffWgEaOUzfnahJ5h02nwqfJHnIl9brVzWQKM/DJ91a1nIHXcW5ulDRHGDPURnyIq0rhb+cY10pBmh6e5Vi/Xy/44xMOzXzqzUwJdPVhonfsNOld+Tlc9nfS9eXh9wFZePpLzs6FXvfrUomKvSkangvNMKNV0j512ZmA7nACAnECE/tv1ejM3B1Wx6awL+UWDvcyclxfmwoae+lZETisLauTpeJqaa3vYXUCk1oo6Wq4xKT1zRlc2fEVhttNcRm+HZx+yvyYLGu0rk8uKcKNhofugBNlTJsbiT5v/pd1nMaDOj0Mc6Kyzu5a/kHYa2KkVRT+7XCCOlFCaaQ/J6b2esogrIJHD51/eLYXok6m2c3cMo8Uztnq0OYOkkYHNQJyQLGd0TiaampdxPeS4Z/JYRBHBwKI5HxmKJiXUSVp2ZB6xrR96P0PjrkBT+wFsRwdI/YrZhwx2jqPLg7Um9G/1/TRcNFwlL+93Jy3W3DzOo03/AQU/UPwjijxV/QAwHXk+OewLP0uDObTWP/8Z9eH/6ihrHJF3Z3D+fkuj83Q0TWUTJrvsb3xwTG2Gb9v9Opng83bK/TszRp1PrF2G2eCpFZ3uV/3YdFSf4Du6tqGsfjzYZ1ySsKDTT8C+HmJiDxgg/xoKwItESRqXJ3+OdDiCOI4Tn7usfe7Q3n/x4MVAHaZV/qjepigo7KShomkVMyQeenWPL/xC6EHKKw5h8CJBYfDcn23jgHMKBowUWv1cjaUErZSpRyjwrVUp+db1dOAVSfM7Onzl7x67fRVz8GNx1IG3hp3/ZAtg517mce1medoz8nB2rTr89+3jOex3fh3DrD4EeP6W2t8hzvc4c+BuwH9Dnf4JaB71QvMSjMeoiAAY94SGfqRaNqbb6YeUege2ROPl/RxesEOkVNPUz/fh15jCqfSgy4ojLAbChMkSxFlqcVM+u7cdS8ivKaEBSJ4F65iyADLD80MGi3aVMYxm1Ehioi7AlVXkM7wpxvBPwBP2q2Xn9CXm02wRIaasqCp4k1qVzeUsoEgRisRsoXtNE3X3SAGmCVJavZ//uufOKyH8F6NNk6Swl3avAB0BK8qcOeMWounCCeS/VKb1J8UHJFDjjlz1Fo8xe4JZvDScZjCjc2gbsZz3sEB8aYtejgoRfde0rq+rWmd8wtOpxNOpxMu20VTXolycV1XtJbRWNJqF02JnpeMQz4i6QnAFTIKZvBZchajVs5otUm1Z2JNiykG6LysWPKCrMbjpMbCRZVWzA05LaK8ZwZzRc4Z//f//Cf++a9/oaGXWViWjIfDAetxRSKNWk+Swr+0hlYLSq2SeqtWicLlruz1kg9siioZX8cRqfFmZ0mihEwMgubThqWEr3EZwoETPcU0gFIKai1eDxOQDAVLbqgtqeG1HzhNcQ6IArNC06nf0BTNB5iRVocOTvCo+Pd8dQWDYaOFv67UoB6N3tV+gBjtPoHByF9yV6JS6IMqi5t6h4sSujs/uNJRGxYdOqM9q0PSLWIwG1RsTh9FGSEe/QlEUqMt6AoAgivCU0p6+IYmQugpy5EI6+HYZ1P3xUJWSqQrU7IqdNlYkzpaMRjLmvt0TClDuQFZMzywGsnNwE1EyGsCNcK2AQ0VtTZQyiB16Ai22yFSlABszJKabkmgwPxkiwceqsvlfFfHz8wgriAkTZnXFcGAllNQZQMSIWPUIKheuRvR3cBgTch3SpqanJW/gz0feU4ZDZqqlBsSkuNrbRo5YNlcSJXJ+nLSNYz4kVJyYyBBaGdGBphRUXtUezOJACrv6LiUX0umj2cs6QktTGPloFiD4MGSGZW68xQgijijO0TwjBomZ5gyrqPek8pYDfQK0CdCpicwnQCcnTbaxGdgyBPBCEo/hfiKrghN6IaI71dg+n6+ATcjYsygEJV3QE/9HPrt2zjpXAG9FENQfnqPLDsQusL3zTFMCq/dQdJEdxt8f8xPyu2sXdlTQTEwzLsa/6+MxvHlfZz+8S3NVuDnzWtlikxgjnzdCNjrnc91z6NRlULb2Bu3Wy+vh3s9svHGYHvcefwjKrzQniD/Xjf6vxM53HvnPMJ38enW+eWN/nfskE9x/2KaTq7yg/AuIbaZkjsMxjb7Kcfwq7dkEdQ2JuvebDx35+G3gMN0W6e1rcyMyoBJ3MyM4h6MoS/EbiSXNRkIVcdFFufFpuW2XJ5GkFGo81NrL6mczqF/9mmQE0KfzHjuBnPntex818sohWd8TDonHBwkhhf/G8AJfejH8Ds7Hm5gbqDXY8efh74POg9Rpj453OiVUYZlv7QL8xYiYCyL5ruF+78hhUPfN/aF/Dww0ISPrgH39TNeZ7hmOHgT5j0R23M+F/qNaa7Cm8kycBlNjl37ifAjTe71+b87fI+c9LON5/82QH1/Akrv/ks79H1wgmXi2AcJqjCHIQzyV+RTomvq5XEiDPRMzxM5lLuwA4EYvNmN13Ze9DOf62K6nsE5vNE11+VoFDl6yYouYwIMcVpLWs/czkiNm49pptPmAMSQvuw7ZbwP3fnKAqek1IA5Lru8FBSodp4nHwv7mZCSnHWj8fzWexOSOy5UtuAL8rm9bFreSwNB3pTbXHCQFY5L8GY/TNcWeMee7q878KYrY/meQf2j8ENG9F9sX9/hDr863A3od7jDLwA8n8RmBQb2FVgpkSpy3hY03gM7/CaVND31nynC9Qev0UkEoLmxmsB+NlZRph9XWY3v8dxsghepusqENFIjOleACVQ1FTWa10mDCluUMtDk4CBxbYxWGC0xUtOk4F5ItgUlCsKBuisgLEpqPxKd/IAt992ayXc0Ez5+H8ofguegv47wmQnfQvra3qsZpwws9E5rjutz1QwXRWqir1kj/nL3piUCyraBuQBaizipsZTVc5dbQ9kuwLqK0Xhd8Xo+Sw1iMI6HA7ZScNnYU7N7RBYB58sLWq0gZix5wYEWbHUDKmNdVlGsEYBKOK4LEiVceMNZJ9uUdo2lZiVUeelK7Fa9fvmyLN34pAJ844pSC8p2kfT1gBvxW2uStv2y4XI543w6Y6ubpnzXOSep91tbxcv5hCVLqu12OeFy2fBwfHChetsK1mVFKRWFixr5C3JKUt8LEolOSOIRneVAsq4HHB8esK4LDoejRmEngLrHNEMcC2ptaLXi+fUbaqlKb3p7IMKyLnh8eMJ6OCDlhIeHI7gBl8sZW6vYtgvKZROHAI0SrVrT3utsB+UmATisK46Hoxs+LfMF9IAMtnrv0HnXbBRaV15qk9V++FHsvZwv2MqGy0Xm3WoUhvN2B4IbXM4gLJB0mseghLUDKqmWriDo3OL+0R8/sezFrpeTD6/hc4RH73sfQ4LQ3ZP+akrpJzCyR+g8IX9JqF+1Vt7XCvpMWJcMr3tPnU5Z67UKjp81lb0d+rwERmO0565VdxOC7Z1bdEpP8I+H49UtZSs4PopKuNWGUmo/uEMO61UNR0tevF8pZ5RqfSHnhXagT1aXVZXx4liSVDmvhtgKgDVrBQNcu4OZ0RWPOlXFsOEsTHli0XWCiWjcxFBiRg9mgMRYvm1bn7vaUAAQrYCWIjDvN1bldj/4h7lWMGcGQu0GFgYGD7oq3iN50dp9NK2XOQyE6DwCumOLzmVWWteqZnMgKbPRLPMLCISMlhpIlU6ZtURHEqcpZa9gFvrZavU5rUWcdDyCXTqBapGA2p3Ltgnd0PmupeKwLGoQYOczEtH5oI40rzrnj6L4oajkMN4OtWrpbjidkCgYk7T24SMTEhouaqyyaNLlSxa5gk4APYFfXr124bUdgEQeQXeIuehaPzkuy//Z11zlLq8BO1d+/jjIGk9yoNEw6mn6qf8jk6NrvmfX6IZ0a26KfTJvgKaG8lC/cOxbl5sIhMSB8mmGj8F5YGqiKV9BiDaKskzPQNFlWbgMap/U6G/fSF9ByXn0GL3U56FTRRdwld74yof5oy4/WISlGR49PXtzxzMznjM0M47dw/29w3TGuUM3EvZ56PcY/+v2p/AkE654k5OHUW7sz0T5/yMQ5OEJv6Itrs/i+81FJfq7r33jmpPgEDltPMDdsALTj6+09KRJcacbO/v+T2GfLUTSppE9l1+EYDhewFaUnVcyd74J7WNX1sPxNuIjGMis+9fOVn6PnKdMOiB1avKUsNzJw5zJwOhznMphqlmysnDIjib1YHN3+gK5sWfc931+7P9WxXjeapV53TGqD8Zzn0f2ObGkvoy5s38c3mtupkSGJbMzvMGZCEcwaF0GJb8M8OTyA14BIqmoTg8i96Vg7DCJm1qCFV2K52zPVGPOqNN+nsgN3BHE6WzgZxAHVjN0WXtCd1j67GyCEQ3e8T7CJMfYSNiy5kRjR59Nzzoz9M2aYdkD5hzWCeGwPvNCek1fn0sM/em4pL8+v+h+Gfn6DB/Hl/3737tu8LOMxe8Zom4/+Mff/ZGGLCL9N12TbyRjt98tQv0b/XnGc0GD7+WLw9MBRj75/lO6f+wZo6XvtGGZ4ryV7zUAzv25hSgfbHaueZ6Q3Jk/ITjgqu6vBcMrIPooBlBLA4ZgIjOq2i6WutprXvQMKTwi5VWDAAg5LZpJkX05smbZMp4kXTHHWNJMVoFHq/HcaqXbX+dTQW4EQfQ0oCsdJQVH5EQp8Pc+Hr/5A2CcNqnhfMnJ6eqSs8vBlPQsY3KKzrX0hyUTJHfeUWuDOKJ3/jP2qGeg6dlHm9PSNUtN+/O2gRnI6qR7Khv2wEVHJ+2j8fsmPk98YM94HvEK6FnW7PPYXF/z+fN78L17jmHs7ScLMXe4wx124W5Av8MdfgngIOL1CKmZ0RvIdRUeAbSo7fvuN6MfQIdm+nFtz/ttNNoTKKQp9HuDsovtezj4dg0f+cFak7xKKiXNo5QhNU+9hrIpfPXZSuotujCoNamJ1Bq4iTKnMU0dsyFeCzHdiD5d0znuCvp/X2AAn5jcwP7xB98aV8fFViuS1tM25UerokCvlZEWSTuY8yJp+TN5BElKSdOgS5tWF/SwrthKgaVQJz3AcPDIFWG9omo6K2KIwplEEb0c5GDkNZt2+m7Kta7Ubm48n71QbVu0JorL8/mC5+evGpEKV4aXWlFKQdk2bGVTA1wFkQjfrVbQIgpNZkapG0jTkl22iwrtAFFCaUUjPsesEmZYdjNASkgELHnBsq44Hg/49PSE4+GAw/GIZRGjkqUcM4NgLRWlSuaAbdvAqxg3RVGVJPX58YBlWbAexCh/OBzw9PiIlLMaqs+4nM/YyobaGupWUFt1QzpM2ar140HwaPjj4YDj4YjD4SDOFp7yTNObMvqcQg5mrajBoRYxkHv0nignLxeZ99OrZAA4n8+4XC5ITdd1xy2dIOnjvhHhgSX98nwsBQk1Pu3Qv75lBP8/MfAN7x9wouHf4ASZtj1PfFPGs+4Xe5g+E/hbSJEe8JoCvkcvc+YGcmOd/FZ/tzrgQyff18LYnnzSQ7X/TChqqC9bASVC2Yo/YgphogzSyGFuDdnpSYVlV7H9inA4NX7Uo0ZlcRqaG8QP6wLADvaMmMJTWAajmrc8j3zWjW3T+GfjkWXiaLC07b3uW+MCooS8wCOjRTmhfIUxatGDHoQhPIyB0eAtTff7GUCFK2Z83aT3qqxp/lt4gdZ+J1sQVWSYYqdHSdh8JpZsI/DvGWymCQ4dY3s39+cVUk7d8GE0nYU+ZDf4M3Ka5p6kxRbIofTyAQ2vAF5R6qMqwjJyShBjpPTLFS2grqDHA4jOLkcJjZf3nqGZI3RPtG+vqqQ/hb1D3reAIH1ptY8ed2LGa5PZdO4Z5oCIIGPNLhUfgT42d2gkwI2krUGyL4YSDGrA42E/jeDoZjSHuhHa5yHQM1Ny7lHbsdWuMeUgg40kqJchcONgMKzEPuw5Bkr0I/XFgPXN9jr5+nfHgz4X0SFhM2TSHQAAIABJREFUsstcgw9H7k8k0VBeIqNZ5h51zKkhqpaDEd34pm6pzkuoD4OuJFP0fRj603WtH4Jb9831ROVe3sWXYW3H7k1f+M3b+507OMnoRrG42T7eLJTKWsINv7c3EU4205mGdV3MYEkIuKw3EpuvB5n/jq+b4ZeVyRkM02ENWOt1m3yEG3v0rREaIhk+7bnn+HsbwJmHc11WWrRpv1JKwmeZgCQ8N7WElsxzSBxy3PmKghMTpTi86/4GnGpQ5y+gp2r3/REcHVmx02gDszsCGE/7kWivPws+cnI8A3hSZIo0z3DHlotwRsIRODXggbQGeLhR9wkbLx/e/NacjL2c7/SdYcguiyHvsbt9jfr9XdwJxJQ6RkbM7PJM/xv3JkW+Mcgf17Pb2+1vYt672jPhIfQ7NmljguPZ0Ns7KBga/lVgK/CW48CvEIH+I92LtMHkg18J3upuQj+DuJwWdDTRaafV7kxl7ZqK0c6PopNK7jDKDaBEylMkeKPU0mkWxLk1q6OtnGua6x/JqWqQgTWYQ97fDa+Dk7bJtLDyUyaPR7lW5YypvJBllfsRQ+rARwDnl0TwKHhzqEMCymXz5yQ6nYKeTNYkJUIrfEUnDfx8A43EN9mYMYy3VNVBpdvnkRniLeJYcXtOZt67N397Rvi9KPRZF/BnG8/lmTunucMd/kq4G9Dv8F8AfzWZ/7UkxknXI7/ZyWxgrGa45n7dL5lnpQob7ccj0Aki9Jl3oaddU8WyCK/Wd4siUuFUa9aK/6Qorl1pg6gA0yMV6yHbBFsplOZZ50iHWbnBExcyA1mVUlUEWquXY0UwiRk1MVS9A+ImShgCoM+4kscWQbvVlUv9UndeCM4Dk+5JhGT2zx+e64/devP5PeDp+jNNv8zawElVMSeTZlX9JzV2seLaRWs6HXJGrRvWZVElusxTqQUgkuhrBg6HtXttkhhdai3459ffQUT4+z/+HwgJyyJpnxlWf1fS+76eXvDp8ZMYo5J4qabG4O2MjQhrXnEuZyxpQTpkoDG2bdN+qsOFDdnTissImRvWEIHemqYkN4VVxHs1+mzbBS8vWq+dTG/H+jx7BCZrdDrpeFjripdaQ31kzbIAoFSJUrq0y9UhgJmRKYsBii0jg6XOksieJScsyypG9Swp2NdlxcPxQdKaaap7AGJALxVly1jWBbUW/O3whPNFDOLruuJwOCDlLGmeCTgeD3j69IT1eEDZCi7nM17WV5RtQ6kFtVSNcBLDVdWa8aWKR7hF/C7LguWwYDmsOKyrrDO03jVr5CcBz2WTA5WtSamopXQnBTWmm5GsbHLtfDrjdD5hu0hE+qsaLhbu0dV2mBNlgxrRARS2yFR2epCIUAE8sv+MBOArWZyYwDf7HnWLYDwCsKrlAPCqV+zvAyRK3eAF7L/FnfoVz3hkINFnoWtowDfC8iV7rfDammTvaA2kHvmkjhM5L2IqK2qcTl0ZmD4T2nMb3qeIp4fcGUYOxi+MbSlIOSFBjOXLsnhUgCk2ulVW38LNP4vzRHMvf8N76BqBzXkKeoC191u7kv7ND/S6P3JOELt8SLUNBnNWRYB05Xy+yEE/a4S5KVzUE590PmptIcpKlCK19qg8SuJIxK1hu1zALNkwKElbZlRg5V0y/K5EEF6k7Rm7UiW6zJ06kCmBqpYmX8fBamxOZrolqPNIj0MznskN4P4SudoApB7hONj4NdUgwBoRJjSawKhmFFerM1dN068lF0qt+Pz4iNPrK8DQ2vENtYoCp3wTep2eEmpjJNIUi5YtxJBVp6F+ex4wkT4J/hAsSkNwpr00sBnKH8XIDgLy0yI4QQC/vsr9WkbiMTD6+vwKqAMSoEZ1ELqqnZxOqLlHyy7IxH1SBZoWCRBcA5BJaJ2NYjQU7pkN3wEaDUVsa2cOG1q70AzrAMSYLhwKZpkhQ5q9V3jDdlfkROw3+S3k0mRQMwJgmyvHesfBBgZRRg7v0Ud0TOyDswghc7wZYJJ3omHH6I21azI22X7UvphjDoFcydjrPNt+NXlY5FH301LDoW9bbba16sZz4ZPq3BOM543VicwM+JZ9JCrp2PZyX2vbxjbf9n6Ev9aTyLsA9KCtILsjfPqosnYSkcNMvQfkf968P4itMdp6+LvzlQwxrQ0yw/borGKuFAAhGd0Z2pP58W4o7jBo9I1CMHoinHfAHv0F5WPRIDlEvMsBS3AjQZX+He98XPopjrcxI7HIA1hXtLO2T0JnFwYu6PjM1ECsPEPfJY4g8pxn9CEp08KtIbFEPjdqzo8shZmMW6Pukk+Ez090FjBjQ0gM6/fU1jzNq+wTvUedAV2IMcO6Gd2NH+tc+Rz3g+y7MJ/V9h752K4YUS8+ZCnbL/E6aFAFMAilGcWUtXOjA85y9n4FEh7QHpKQ+ir0q1oGMMWPJAxMMs4Amnq34/Y1XvURDPOh/dla9evMJNlngM4jLGqSGOw13tToFem7Oud15zvuzThRoe7MQrrHwjWjoQCcN3jWOt9WHBsMvMl4mdFU9jXwc55dC0RBZAdg+fQZ5fQKcOnszN9ifOJ9Svi9+LT7ndVQ/NHG4qM/8EyE75ZbrnvwQ+1YxPkXlv+9VnpYiD/DeN5TfO83/t06uRt9vNV1w2T7+8jAK8V1vMW/6Q+v9dBaMCq+BWmap/jVeSXMiJpASQIJrFRQg5W4kfutPF1VmcpLRJk4QRL9nd2zSPuh7TLkzHM4HFBrxevphOPxiPPlDECeXZfFDd8mk1k5EpHXevr1TneE9j0cHwBA27PnZeDG3kfxmfR5ITyktL7quctKoJnB/6P4FeUEol4SsPEsJ4oe+HQ+S5/Uw5C5YTke8Xo6gZlRuGc36hnZ5ndOf5OUWQRB5V5p47CuuJQNYOg6AZdaAfSIdgMLF3DHOXmzyNbR+H01AZ3ez/fEYJrrx6j/b1kSA7+5fmD8+iadfoMf3CbfP3HT3uEOd3gT7gb0O/wXwB6bst9vfb86cnzHs78OhGxmEys0hYsqY1SAct35HAWih2JKBM1d/Qc6pX+8Vij7QZ+DdEXk2VD9YGuRBik2pIpHvokH00TYYda0gPqYRDoADQlV65kDSYVTAmVC4gYgg1qTuVPjidUGosZoCWC2lOPhkO2vCv0cnBTsuw8WbukPk+fK3WlK/8zvM3zW2mwvt3IDvtvKm6IeRpFOVVQsNchTykBrPd2UXIXVQU6knqcpwSLgmipeRPiuaJeK7Gmo5Z6kacmZtVSBad8UGjO2VrCkBQ1S2xkJKK2ih8xdD92PHsx45YYnNfZ6ymarwa1GN9LNEK+bB+7ssWrp6xtGoXwrBVRrxy8SA5Y45IrDB5DGQ4AfSi0KjkCcBqE+gUBN9yEzAEsvJgc/MWY1XM4XZI1STykjpYplXTSqW9LXHw4H5HXBsiw4rBJ9TimpQlXflxLyuiBzxbEdJWK9LChLAXzMEvVdS8WiddIBwpql7bQkNZ4npCzKNNn7pMa2otHxWte8VpRtU8P/BdvlgkuxSHRZy7IV1FpxOZ9xPl+wlYumcpc1ym2cV7L53NkHM1eKmC+Y0RW8cac4PdGz1QOrAw+mXRfOXi/T70clM9Gw3iCKVp4bmfoIQPdK/9z7xu50JBkk5KlEhPatG9U+oneb54aeCKUxjpmwlYrHR02xrYZkz6TAHMi+vslIvvIWj2BlU6gq3U6kxuqKlCSlZ0LCsq4giEHXjFjeL+9wWCf7h3o6tsZNDvGXDd2oL3xY6tNVeOSBZkDp27T5aMzxxsqGNGaUssGi6XNSh5REsHTj5oHPwXygGgutMavsVOvuAlXfpXs+k2bwAECElCVlrXRB/xMtB1gN9z0tN6NbzqzEg8RlDkriiODKA5ltjjisZueTlK6jkL99+4pE2Z+plvZ7B+tSTpgh7kWefgcgSvjppfSYgdMDQGfw6QTLxkAA2unV5RcGxDdBN+wJjAejr+jPOGaphdgqxIDgBtjZmS4+T0BwOJy58UQs9kTiG997xGucJ/uXleZQMATYKjQwsq+k7RSPwPa/UFz0+JigpJymXWVTdWcAYGmU+/xQuHlfCUjWUJ9FL4NgHe2R6Rbp08cf02pbWzP9UdmZNHp/Nh5xb032fMTTaeXmOQh39X0VZQ+ldSZL+L6HZqmRjsr2DPKn965HMNmb5+9gu3ue4Ti+PxHeElh/5JGdfTVy4B2wqaCO3QR46ScX8d+Bm7dwaMf2+LQPO6qJAtkj0wnjvrAmVUkvZMacJrrzxEdg0VsbM/iiXTgk4CLzULiJzMlhDq3kk6dpV0c1ZrCev1ImtCYpdiuapAhPGnHODGYxvMftZcYCdj7c8dGctZliJLLtc3ZZu3F1QhspVfP2ukR2zRt+JKPHXwNn/bvbPw50jKysAFCIRbHHAIg18lzn5dTQNKU7WHhaCy8QkmZ8gfpv7xKDLq/t3qt96V91NY22MbyuCZE5nJgcYp1jxxFvZ35V2Cje71sb2GW9yGNG+d7eYeW47A7jk8Jf4GNwYwsAfmkDE18eHrF9+4buzTSwr6tZi/LMfweI8sw+l/yfAXso+1eAVUlMHf2Gvgw85i/q00dhniOT53oWPtmT7rAQ7m3M/kOUSS3QxtKnE8S5nMEaxNBbMj4DAOfzWYy9KQenNe6BD+HtvV5551l23gN6fXMAEkRgfM77aRH18DZM99sd70xn9nGD+TWoVKy8WNrqJTUoZP0aZCIn0Qnn8znotDisEdygvwt63rFMbDZPpteLxvPGfOVkMTS12/y+84ativ8d7tNzSZS9EegWhUYAX3cyRwxuPZvZ0KlwuIlEcN6IfxD+3fbvHe7w3xHuBvQ7/HUwM4ZJAbVz8R2Yn33v+14n/lqICmX5PioFIluPKuYGuBGBSPS4USnH6EKN8e1GXWkq2hg75M5zwlcfZ54ftDc9ygFAUm1wjBAX+UGUEgmqHGlxfLFZlsgGHYwZwaEClAlrJsyyXkaVU0DTwygB7k1fQYBGqSFpGsaU5Pye5fnChKwpwy2FJjNcCI1K/HgAj0o1H+twGtYDtB2SpzWyqex4YJF/4xJw+MJh2oIovoMltw+m3ybFwycmNaaPC86usjONRtSsRAFSDdzQ+npd+wGAcalF1r8REjVJ78TiEWxRr2LMJXCtqMxIiT2FkwmzFtHIjVFKQdYo0q1cUGpC2TYcHh611mRGa5pS6rDiAMJWiqc8P51PgEbIQD2YsxvSVYVNEhFjUbyNxcBbW/Go6cYVrWU1NlqkizhodA2pHiQ4KFzCBk2Ap9C11K2Wgj2nBFajcm1ST7cRo8SVJjuMicHOPJwfjw9Y8oqGigSJ+E+ZcFyPeHh4wOPxEx4fD8hJ6gfXreihk7Qu/YKUJTKXmVGLGKyTpqRfsqRY50Q4LAsoZ6SkBhalSZRIDO2tgYumttpk3HIwqsgpo6aqnuGStWDJB+QlIWcxTLpHL1hTgDG2WrBtF5wvF2yXDaVuaKVgu1w8yryUItcsfTw3wbFapQ79tqHqtSdWg7d5jKPvf9Jin/KXQAk4VUIjxoNvavHSNtsaQ2geOzGzg3PcmIQnZrxYxE04kc4KjGFvm2JO733Q318S4ahNNzyDvz1i+dL3GYlVtNMdhqcGJpI617UWMDPWZcWlXJApw2LOOeCyH9h9LOP4Ok8Kx2XWfQLZ/6UWjTpvYdxCZ4yfWH/tH2I1srFFMNn/kjaO1UkEYORl0Ut9frnVTrDBQAVqkvrV83k2aAVghq2cCYfj2ks/qNaZ/LwsdcJb2yQFYOq10FMGwAmtFY3MYqSUO59uFcwVBQXrmsCc5RkfkfGgznxaqx4hTk33q/a5lCr0AE0M62FItUitvGIhGklxtQnPoqR4onUBpFZtcp2vXDNFUV9riZpnLS3RcZSdn2q/ax0iARMlcGKssLqCWkaisvMiECM/Jd1b4lRz/teG/EQ4risSZUmJj54eOypHAKA9vwBEyF8WaMoBzWbA4McEpifw6wvWT58ce/PjI9rrSe5FV0AyCJ+UNmWn9x0t/X77Th2njaNW7WOSQWGBKacIn6jPdSzNYK9ys+/Imvt3k8Wm69Ym2UUW7GaVl4SG61o14SsSo6p8Okom3ZoQycAAhrIMANlcEayj7FlYGokp3dszg7WuvRI96bumxmAiC2YNsx6FpGA+bRrlai9gSSMdh3F1NGFZr2Qhtkzet74asi9NYSjOPTYOrZWtqTyrlQvQ52tjpwWk3yVVO4IRpm86i6Y0qZphCl3pVyJbePI5MblDcCK2ZUDAUGYp8Kn4fWdtPwKz+xmFf739qfH5VVc2tKv29r7Ys0Fpa8wkGOPmhj16lQHSqGkOxi4Kz3HgjoqYYweHQwJQ0OfDsVUdlsQ1UuaiwsiyZTUQxxCnaL6J2fcBozswMtgzihCzHwCHeWZgY8aqTTVcACxIDOTDETgzGCe/OdJ5O5etkD6d51VlO2o2EDWRn1pvw+mXyVRmDEgYjaMuF/VJlS3DPka2crYMNLWfJ+p95DBd0dDim4C15yqHd2P9iE4qPl195/B9QLM/AKMeIP4uLznq9dN2QaDmih8Na85YILJS44YlOA0yzmhIoBOQHh4Aght9zIlBah8zEuXrScCcCQUeoWj9MFrd+63/stESm/vkjuWaJ1nfrxmQlLQZvxgiL9GXbzCMBD4xCdww+tyd4+UFVaNXY/kfp+Vx+DytjvMY+dzMoWl+rjUgEbbTK8YWRogGsuH36fvE6W5ej7/z1YddcvlGv77/uT1weUi/3Bjy3IMfeo/BEG0O+fyZgS86sK97jOVH4J2JsbMbEbkuD1D57402r+SS3Y7S2H/b1/ZMYB1nd3CMe7TLZuTvMP3b9624kdS5Pzzvx6lZiogxfO+/EyCZ9oi8pJOdjVpj55dWL5yIcDgc0FrD8+lF55M8YGPJWXU7ErgQgw5k/IT//R//gX/985+eFv24HsBoIEvZ3iRjIjfLyiJ7JueMWguWnF1/aRIDUcLnT5+RUsLlcvF5J01NzqxR19vmDgGtVuFveu4Q/mbGfnb5cliHq4W4hr6+gmxrliANC2qY18hK4/l5s5lMTChsQSaKUUGH1wb+G9+q5yB1YmjckJmHbGFmSPdU8kGuNbBzVXSgiCzeZTjjhS6QwB3K7dmr2C2XE6LjYhr/JuOh8t1jAqZVsPdPsWDO5/ruA+LaafxIh+n71fU73OEOfzrcDeh3+IthT+TnG9f2fov3zs++9d3e9V8D8bDHZOltyGuQ9RvNmDOdX9Xi1py5B/ZL+k/IRuYpzMxwnURoFIWDnWZ7LcUI3bMRcEXrMHWWrjLMNsu4LEDPFBYtRDVO4oJ8MoWFGXn8oMpavxUqqFh0kkogWcbALEqoqvPbUJGbxuwxsKSMJSdkkKSv1v8bVrm/NjGytYpaxGDKKoyLMFjhwX2jrOmHkl6HTuaz+fwS0iLC/N6B9nv+7u0SVyJgH25h+ycWVPm0G5VuOMU7DVy/qfdrvlkWThTk3QDXUGCKM1H4NTRO4FLBiYEkYdcpiQInkxxyGhWkvHiUrCluGhjb5ey1bVPOyE0OOIkbzmBXLBJXXOqGhIRWpKbygiyRnySRzoIfgouNG2orKG1D0b+VM2pdUAhoLWlK9oJEjHXJOKwL8pI1tXjTNMTNDx4+O9GjVxVYkhK0oVSpR6tXIUYhK0kQ9idRT0EI+KFlXRcs+SCHytMLjsuKh8MRD4cHPBwPWNIqkUJFHBfMCFBbVYWPRPYTCHwQI7wdctKSseSMh+OjHgYET9K6oLQNW8uaNp6wHBetbw0waTqwBjCyp5LPaGBeZC9V1oNsUiOYqJRbI5RaUcuGy3nD+fSK19MLLucihvBScD6fsF02OdAyo5WC+v+z96XbjeQ6mh/ICMl2Oqu7p9//EefMvVWZthURBOYHFoKhkNO51N1KzOOUFAtXEMQOy+fehFW5aUp0N+4hEIqztc4IqTtueAnXQuBS8KkWfEHV/cYAkeINN2pwZb8q2syS3Dlnu+YhyTR6AuGTKdEdf3gQ+RwBQ790gd6LCJ78mm2zT6gpdzMB8grgs50D3RMUdia4QCO8uSEAVVUaVAFthosdD6bw9sNe33Oxw943vPVEmKcaBh7KhHZBg4jDuL4VIT8TBysiZnhj55nt1XXbAFpBJJimGYUI0zT7JgHEw7X2s9YFtb4mEVFlCOGXMSwFt1sImGYVnCzLApdZuBe9R4aJNqmHrwMIzfYRYMJ/6p53qjgjrKvlRq9ThJ7WLe4h19NpEEoUU8wSIGCUiUzBwEgqGd3bEEhJqxmBacxTN3feYQVuFKaHvi1BCHG8W6MizvqGWOSY2i5kQShWUcxr0cLmu4A7C94IwDSpdVN9MgMe6LpUENhCB4swpudPer5/NcG1HeD89QUbfQIVw/e2XiwAPTz1NB7+Evt+gcGA4mo/w6oBEwNdCW10V6UuyCM3ijIFQiFVPn0i9PPQIZDCGQ8du7tQSr/pPUpjwxC+9lqJ4VCTFAyCmGshBmy/N+mwRYZnWFpS6o77Purzdfdx2DlVigo8C5U+t2mKvRJBMvh0DE2wKEoS1zr+AaTB1gOpbooZChqEPZS6LqQbnqWeIvAGHE9qu1QFQA9nGSJo8XXpodn3cRVEEk3otIiosZwabvbULs3SjgiLpVURz1AApwOyQFvpAO8wxWQ6rEpeqt3nHnO7sjHfCF5hfBJHZe/9PPQt2ugB+/dliPrky0mO03ZV0eHX4UenyfOABRELK+C0vxT7ROzsw249HekNT+O6hlLUezudBWL1IvY5xZI5/8LCqKwpiIxQghrpEMTSVXDgIhsfqXELmyJQIVWMr1R8HWGyo7eWFsNhF2q4JhC0t2aQJkZf6ujcwGcDq0EKRENue6SUIAnUKBncDHZZw+pSP4t1jvqn83iefkSNEYtPmhlc2blgRmPCdrZaiFwhmFFgx3GhlPRDQtDtW/J6ZRzk4/Bj/zt+39gaP1AIERs39os2dAlqxu87DOtKKt1JvQaCPis6bx45Sy7QcEYQsJDaIcL3mdeXB3S0AfV9O9LQj52DyZDhFTNa9fPOaH1JZxN6fJQwTE6h3I6nur8/fB4+7fwFAq+GwdKuxv1o9hgs7kk///W6GaGwwHKOHPb6n1H0LOzn6K3yy0Da2wVC2QR0OufqmXc6FMa832gH6Mpzz2/+/CsGdK3d/djSkhpZ54gPXZ5HQx1+/uXKPZXcdbUeCSneHCpxHB40dz+BdBrzeAxP5Ah5Ehu8804+jU/GS+fw974+vm9u78GPF69+8FJG54vdy1yjhrny1t4lnZ3TPKM11sh7MCX3RWly73OPbKU0qwjj8+fP+Prli7ZdBECN6GQrN4uiaOdg8Hti/JvWnem/YrKfdV3TuDQyS7XQ6c3kR32kfc9mw0DmbsrnDgA/PsE7T22yYzMJf3uKGJdzQg387Hx1HF5NmazR2byMOLA4NegGUtA6G4CzQc+KnsM+YE9GejN7xpP9Fps7px8dGMdzwY4aMuU8Oh3jRImeoQnofWuVghqp1yyCQU47ohr5TlMONMl4gpLBdB7F/iy6os1v/P7V+Ppe7uVebpe7Av1e/nmFgH4q7VF/ZviPfh+9e+u3//zHMzFHoxJjvIuzbrtu6QicdfOLmXDE/mG4Bfm+LdeDRh7qwhGGVED9RMfBzCSlNR0c1uQCfPTQ7YxEpBMAaRApQdiKdAYgfF8ElmOv3/EeikA94RpwJZy0PjIRCnemXKipB0cDSBqKiIVr6sL2ShUomhe1gtGEsJWGxgSmpkShEBpxGDwAnZjSdqR7pQWTIYB5B5FZpF71efidKCpBX/NM8CEt08jrfKPuY2j/Gvvu1m5wMQBdzXk8EVJ7M5SwmopkjwgEIbi0DQWESTRMsWjkb2OITIwhApHJFMkSzNI8VbCUsO4EgPNcQdDcT6UUbOuC1YTTc604zacQ7LmQBlTwcD5j2VY0C09JTftaa+17zICZYUpS1pDhW1uxbhXTVkMQoEpfzXusecUnnOeTTu+2AbJpPmqdtD5/bjJ7Ax05qgq4c4GvwV9JL3s4e7YQYJUK5ukEAvAwnVCmCdOsiu9a1NBAPXm6B3LhinmecJpPqmBjsVzpE854sKAQbIr/AlTC48OThlPnFY0EG2vO+FoJda6oXCGyokBQLd2CFMvnSqKCZlIYYWY06pbg4SG46ey1bcW6rFiWC5bLgrfXNyzLEnnPl7eLhdh2OFIhALemoaC3ZkqLhhxW+4vN5xPp3FYRbKJ8MoPwSgWnonOhvpoq4BVTyDRjxiYKH8rOsPkv537jrmK+FyI8Gs78YsL5Bxnzm/sbzvg9oFtKM/TZAs2hHqwXAfwHA8+a39uVxMqkK5NHtaASqdLGGVL7FAK21oKpv8YARzjhGpDpSXFBnas5GZF6oK8bJJTb/b2NW+CNWtSzvM4q/Ghbg4A0/QIE1BTGzidVmLsC3PW+LrQxtbadMbpXQe6lXFw0YYKP3htmHoQp7hHvluO1VrRlgZlNhVCjMIGmLo2mqjnQAagxlYgp9PQc9tQrdZqAZmHtsZl+xEKzCoGKnS8R6MMiddgImNnwhdVoAhulNwSqaTS4kdbPJlPqFEL3Rje6oCufuhGSG1xELtOoIgnbkMgSIARB4Y3QPBc6sC2b7i2i8EJY1xXTVC3EvQpg5FXr3R6bGiphMiMESxMyVU3HQurN6/hZl56G7egeKIWq9hsAueBLNPy/cFMFGqsiynThIO4KcRgt4TvaBTFdTWihCQE0O0/fdsr3C2Bh//V5pbd6X3vwdEr3R1qvG4TYa0MlqcQQJV4QqJIWXA03M8AectHPcYnozUdlT6H37/6/z1ffn/EcW8eLKwDdkEnhXY/JorSmHwvU8Z+SXBL4yw77UARFUyEI9hFJvou8atFnAaS40Y7eY3Gf/Ty/5M1ez3UyHtS9aBvY8A1bjnN2D3TA8mZ6nznNO8VnDdoyMJZ58Br1TYmINWCTAAAgAElEQVS+l+u1UUHsSEzm7vOV8jwww1DXtzzUBtgIaSauQjEPxRvaCUajtrED/cPO2RzyVNLzRD2kqtcXdPtIserdLO1MuC2fiG4whRDYkun5SrzqXRjocepblA32BBS0b14NVfvrU4UkAom5kDeTkRo0x/Gez4vjbZirtsCFyGKREOg0QwCUs0aN+lQeQVSwvb1hI5ihoALSBMGbAKcm4OLRj7T9s1gkHqMx3yJvRIdLHz+VbpBEZkjIslO0i+Ii7bae3xHBxBWWdk4K2AxC8/RJrAsI4Z2f++Tab8lINd2++u3bavf758ue29rvLjJlNcX+8dXXaS4OhhZlq2Jtm+KrUg2/mopFLsDlBDr36G9h3JGMcm3jxk82xqWncuuK/hGb+svUq0mf8aOMJkGevmDvyV3c43NAZp0+ccWN0yV9DNaTTM+kPnZjqFun1/i5A6sozKPqSl5kP3WHZUiFk64fnakfKfvn97+/6DboqWeu+jP+/kb3f6oIDsiUXQd+s5+/572W7rtC/OtuwmR33xW8hNEj/WdLPyt6/w6L9zvhfMBTK+zouajX6QrDnYVgnjS7qn0lKYzU3EBflecmaZRkuGpKyzBeQqeLNJ2h8c9aa9D4A+2GNO9xUcbPG3MRX7+xFgWEqRTM03wN26zyGQ+L7sIeKpoOTlP8zbgsC+ZpCpmSe5y3ppHvauCWESswM/72//6mPJgbfLAav6uhr4TsRbg7dRRnFuC8j4d3L5iqyrFeXl4g0IhvpXRvZuUVxfA4WXSyTv94iPmIRqfMXg/9LraG709rnkUQFZxndShq1p5G1esGgOCM1SWW104fdVCARWtDwdpY+dkBDnq0Iz1nLFc8aZ2cFM6L7wIxWLZIKm+brtneuCQuGjz8JsDvpdNd6iAhyYjEj7w0xn2dLlMYBkt2y4xJXPlvdIzXm6sZUEOmxXI/YPR6XBzpkWu6+/3f93Iv9/Lnl7sC/V7+Bco18/Ln/P4z2YHvL+8deD/S06P6Iuy7+BOEnM8rBI0HBG+EUZPdLIaMIh37pgByRbrntlQFuBEqVwYM1P9PDHwmObTakaH1l5xwEXTPfBdWA9qHxqpcN/rJ3lEiRr3elEhistBNBICMdKyMKmXXo94XD8VlrwDinxZi6Vvcwb9Q+SSEr1ee6N9DkhkJR05w7te6MyhknLNADRhgXmSFzNuZCaUKuBRMRUNgecgu93jxmqc6Q4RR6hQMEUsPleuemadJ82s35mB+QogIFytpME0yBW8oYrcWYcGnqpanEFWieYqCWgnAhPP5jIfHB1ApWNcVm4fQ3LauYEpt681rxiRmzN8xIWUp7h9kcCcqHGMWTNX2o90sVEAFmOcZ83zGaT5jniZTNqknSpnUG7xaTq/z+YSNGatsykCL5j7XOZ7RpOHx/GQKroatrbGBNcy95r0sRRnZUglFCiY6a75nJstFLw4uagRBqlxUL31lSiIaRNMw8stq+c2XCy4XVaRv24pta10payGr2RXoLKoMSwLwgNgk0M/ithL4hPAAoBmj9ESEr+ZJXap69BYpobAMHEHXu0eQryl8PkhX5T9CFeoFggchvGaka8DuVtlu2ELpnjNQseOeO8NPxbwvI19b7+iQ94s8tULH7T9a6EnbeXo8I8J/EmFbt9vv5MEYLlYlJ4FmXaF59sCz0gdL/T0C1NDDXaoGiQ/Bo5wIxAygnFHvT6tsWMCbCmNdke7mRKGII+oCFY63Q6Cf2/YQdl15TNZP3Q/MTfe2pRJpbYVIs5QVFZDWpY3x0QXpXVFmeGw4s/c0UDdkU0WaiT7c4cEUqxAJAU1MrisgmWPeyeY2BBPS51gvcBgEKI5jEwQaLktKj1IrzqVg21ZTMmaPG8I8FQsqrkNmeE48FbSUBpB5cYjts7639Yxxb2j11jOFejWlsZgXnyl1uHwC8DZuMJ//NC0OXsU9XCkJiJzOITJ41u++HynNayjkbAFjbdISUv4kX0WYEcleGBSLgoSh4lMV1aIe6NZ7IcXHXBTmiqgHrJiBS+AZwSAAD49Mghke9NZ8rvowshjroK8EoyMoxpPHe2M2dpezBGu3eKLwMHpOp/vpdRY7n3xNqI9Hq3LjGhquaRVk47Zzn7qXUvdW2o09xr3ft/vf6bsLkPuAhzeu7+RygOtvoP/bJ8I763nQ4wPycLh5HSx6/9J+ZHbVccw3O5zr6d91HdO5AIzhur85gGsIzxfy3gyUQmNtnqbLcfgewovhC/3zaD39bA+PQzvH9EdgFQCK6zYRzB76Fh4dqO8PNWcRnFBwgWAewv0zFsMf3MSMIRVnVgCvUsCk9BHI8VifthA6eyQmIlXwuKIc+bzo9PE4z4miMpwxuLRSH/716nz76j+27HDPcH38PULe8f3OaxM2CGanFXYaS18ThxWx9Gm6HjTid+xNh9J5c1CsmndLNmrK65kRracPSdTGANf6luw6kul9GT7e6c3Nx8Z5OsIHvU15fT30rD5u7bhrfzpEOnjIO2j4T2jSP98bn0AV338kknS3rQ+/79vx718TjVZwHdb9H1EG0VfCS/t0EcD1KRevUdEITMDg0ELxR8iysqAz7To73SJGE/u5kxoJskk8uh1DIqj52Oa+z7fu/Uzp+a5NqW08U0S+2tGDImrwWIxf9FD2fjZ6dEinvVSeYu+aEbKPqCt/KSIMsTIdhmPdGG+MZXFlqCNItL72K7zLyQ3HtF+OCT11odfhoVOCj7zat3RN+7xT+pI7DUyAjUfgCvnxvIgQ5wloalHjDA+r7grx/PxRu5Rob0JPnQe/T2qs6nI/cprhRtlHQGoHj+4ptpB9XPEAGK8dfR9osF6/fjo0XLefWji859+/dR78w8+Le7mXe7kqdwX6vdzLP6kkHuZdIvqb5ZtM6kF9RiQnbfh3n8IRAthyOAMSwmAJ+rCAUCwXKuDi7J6TbuyoC5g6saRUPpu3rPfRBbnqJ0oQC/kd3nfi1oaEBul28sQQttA70UcL5VrVkrQUNs8MApfeTxXmmBeSWzJKr8OLKuIF7MIMJMbkvZIrxAFnle/S1ZXD575V/LlRee53rsQWV2/2+07Ym7clMEqvrMOb5fmGKSomqaEQ7wIbVWSQKKNQUCxsNiDbgq0UzJZLHdIsusCEuVbL+T1hWxcNHWsE/bKteH7+jL/9/jdTGGuup5KYF5hSqDBDTJnYtg0bqYf7UqmHVmfBNM+YLCc7lYpKBafzCU9PT6i1YlkmLNVdF01EJC6w1KL5zxFerDpVnbkIdakzLz1WrCl+KgoVPH/6hKkQvr6+ojHjxIIyFUynGed5xlwnzKcZ83wCSFCmycKeKVM+n2ZM0wnTNEG2FahQSW0Btraah3sDCmHZLlg2FZYWUu/MaZpRp4omjCICsjkkC8e/bReVl9YyCKcbs3onts3GqsYJbF67bWtgbrgsCy6XCy6vF7y+vmK5XHC5LNjWNXKQhdDMFPHugR7pGDzcWYJLV1h9NXgVaMqBs0W0eCNlxh6gzO8TBI0KvhaAC+HRQmU36R6NAuBBBK/pd2ZtBcArAY+i9SteUqmKB1D9ZEzla+BpWDhlnbsXVxq60NyAosgTjD0FSND+YOAzaSh6ZvP0KurRnQXVAoQ3NFUIdS/oQ1zdZ9A+RyElgcxSnwN+Sy1DmyGADcOJXsrUBaUDc2kKP9i+QDDsPdQmmYRKV0TbL1QCvRIRlmXF+Xy6Yn4Blw2QyRTU4EaV6L5+SUwhKsnwMPcMwrZtIGrhmade1y3Y6qnMAYNuCiMioKqRLWBrs/GmAqNCkObCJDK+nQNmXAiTzw+JufVDTj+2bcNUJrixzm71ENEsXEAF6jidCsQ9z4sLbHxOR4G17zMPV7ltLfalG9s5nHLjCIm4LQtAGhGkFmAzjww8qxEURCCb9n2zxLdanec11xFN06z46vk5hC8E0nU0IkMAC7+nczsR0JjCS5GooD4T5LWEsVwdDGW68M29ecT2pP9zQS0BqlxyhTr1UI6UQmMmSFeaiXrIaU4K1yxWzIKouHdVoQxev30fWtSY4m0U1GL0FlcwqZu/NIJQCbi/pmccHyEIntDXmEGhVaUPGPDZWxoBgAApOQIJhaf2XtKc5123uwvCzMDDATO0+H3GAkcgtk+6ngZmaz0YGSXKdBh97D2rIa3b8Omes5KyaDv94R8CQDi1uRs0upBWh8k2nd5+PokQ8+KnB1mbTk7nZo50+n3c7wlnj+/EVZ9LryWmuPcxlKD5xV0faU+njsfONaGafyc6E1djGY0XCdIV5wmmhwbpWkgcZ2nCDYcdRr8vwy/zDfUtIt3ASHvvlsAJh4AAP99sm+zDz4cBh/3NOCuNferDYmFUTXYFfts0bDxpKp8Hq0O7IjibsF7P2gVAA5WCi+HxByIwWwSbAjDr+r6R4v8zgEsBHkg/AZjxmLbB0o24wHqOqeGV40UdnYZxT0PbTfODpCmH01kIWHt7B6Lzal2VQyTwblXfaMR35ljCpi0+r/k8guDx9AiBnu8QzSGrc0mYDU5YDFYEgMxWFwUs+T+Y8gJwaOxwHimjgvzJm2Q3FT7Xu+uBmtMOEG89zkcbreNmtlhCRosMu1c6XHpqDo/ckfHP2L/e3w+pnHqnh/PDowu5oYe8yWg477h3OzYc/UDL1t/j5997P9/7cgCbka7noJ0/q0j+rx/UV+UPe+T34cX+lW5NyG4AX5BgDsDf6PCx7ys3+vxeodJlQYIeivxWP4brfvaVnvt7eFZgMjhEZCQ7KSylhcOrK0ev24lLiTYPg1Cjr3KMBdm/h91S+AK5TOPomX47KcrH4qG1W9tQSlFje69eEGmB2HB6awyqhJfXF6Pt0llv73hLkc7R0uuJERpdoWwfolG7vPNcFMcQUY8ulul0QCO9QCLl2GmegtbfWjM+xXhyAmqdUIiwrIuevymiBVGxnOQIPOenu89uk35SjNTNAUGFnv7JTx02J4P8HNk8h2e4aBS7iYBNTKbgKb1sDRsLGgRjzvPeLtlc+XpX4zXdM9x53GZGq8VkYa8e7n4HJ573vhuj6v0sz8xGv+Jn3X4P+5ojg26Xr/gN5/OISI0G7R0BejrW/VmT6tjXl34M78jVlXu5l3v5Vyt3Bfq93MtfoGTyIvRX/qMIQkCZDv+4lDmQ9DuIhSC6/bEkZPISPPGxt/tVZ416UItPRk+WTvHMQIy4wiQre4yYbaKhEalWaF4eRiXA47IWAphMIQgCpFiIaUY1UpNheQZtUEwwBbyp/agTs+rBpxfa9/Na/xlFROf3xlrvicPiofycwXGlpwiYWPOUa6JDE5oViIeLJw3/qmGAqxLvpFbD8zxh3VQ5+7c//qY5piQJsUWV6MIMLgXUGDJ1xqYxULYNiys7rG/CwEkYmFXpXGrRtAAgPIkqcObpYh6kRRXJRBryOwnRAQ07KHbdnzsS0+t2kxDoN2Oymmwo5Rmvb5eBfSq1aMj2OmE6nTCVan01gZrVOs8zTucZ8zTrc2vF5aLZFsW5KOin5xYrBcHcTB62vu7D9LrAXhmLSgWgYvPdzBBF+8CiynIPHSB2Tz3MN1yWCy5vC5bLWyjPL8sFvG3YtgaCer27B68zxZrXXdKa8yFIOvPsXvcwhu5BgK8mVCSy3F4WUqyIYBKFG2d4xdbodYczvXiIdkCV6H1tFUG6d60LQB4AvJHgiT00bCyFCQUSAwegPBP4i1+xsSV2ettaMPLRdiieCqiawHRtGsnDXUo/IOojAPN/VZzmOQwgvGOlVlPQjaG/r5nU+A+uvC1Ur/GIMbEuIMnMaPZG8tsCwdtFc1I6s+2vqFf7gVDI59ZgqdQSZ6TmYFXlrliiYhWiNghTVBQeBSl1ybquqFWDc0eIDBY0E7LWqkIWQA1JLpdFDVvcWKIUoAhIXJjdjRzE9lOEVE8DI9L91NqG8/nclYc2P74OrXXlXdTLrOGsk1JRPfC7ot3nPcKluiAOCFw+hJA0HM0a/zDWjoSwMYdQaPvS8On/6BrxZt6TNj8lpiCtnsGGh2YEWY5Iw60oSJ4NXWiSFVTkpAYVVSTZNIbBFfqucGEQmdAR5AI1M9zz523fZcV5/p6LSEtRUACAkSMH7YsrPmIssTf6PhoV8Dbf0YYaOaIw2CKIMNSDlABL6+ErFOYZSYgnRtuh72HbKzE0yvCGwA0kMLdbAOa5LsWjOOiNI/lqF3m9UwKfODxnxGAlow+VhMUMWZeGtvz826Gd3hy8jn6Vcv5e20OON1RAKT1Kiu8fHJNPAr6+iGtcKjcSM9+iv0U+iul/rHTK5KBtTo0bIaj0/PUcI/WR9leOUhccd+RKtDzUHxelp9s5eoiGTr8/ecFz7erbj9H2b99M+llIlXOKZ4wmKSXCXu8rzXuzk2QSf2SGQk5rEQwf2NslwZPj7AiVHULvxZ4nYyPJyH4a+vGaegMRvIHCRuYswIUMs0hv370J+9nqRg2Os3bnzUdKeuwDkHJVHmWk2/7s8pH9mPeCK7qMnO1geVTJAwUe9tQYqqSW/kIYguyB9seKxGeHBfe7DHlDelpSsvlIt5Jrs7PE6Y3wpJfxGW/z2gDho9guPZmQUsfTAnm7xF7I0Vf+rEh030I1//LlF3XyW7O7b+YfuH17+xlwd8fGvj8Zk+d7xeQbHuUx1a5pPQhRsZMf2YiqQI0gcwS/oyWIlF+IOGdKE++M+o5w02hs+CvoCeefJNKkCCylg3BUXmCpTaBhzjutlg29+n71foaMyRapEIVSPuQzybhbSXHWUOxBBft5qLxZYAaBpaig4HUFLRwoalVHjpbqd2XviHM7Ldj5r5+a1N6e4zFTnu/JY+eDRCS8yy1gpNGr+l3njUx+0rF8HgUwKs+1jg5T6ghjxgICjRoKMzDe1bPv/83xweVcOyh0ON29f7M6o7ucX7tSpnt5R7Z9q6/7M+lPOi7u5V7u5ReXuwL9Xu7lL1TieCfqREn8h04wXz2/u7ijaKgUsxKXgcF07jws/3eehjeFeYnZdStDF6wRqAtcAQvFa8R0DnXEAndgK9XylRYX5GcZpxFHFqq0sOX2E6BwDY6GRHP9kAt9nRiPr97Hrsbch7//80oWo/yi6rIA5lbtrmgJQZsxHZDwFiCojcbwmj2/sir0VmYUEE6156PKzNfWtmD8CgTrtpnXoimDWcyzXHN9e2GLjuC5FlUQWQYhNpNAoJ7TKAA1AhXRfIpFsAGgtTMazAJpYvmptIcTzSiTKpMfyDwoa0WpFdVyia+nGa2ZtTMzttawrSs2IqBt2ETDQZOFwxwZUTLwsnkuarRB0L33+x9fcJpOACzfVkjQWFMVmLV1rQXV8scTBCBgqhXn0wPqPKHWCfM84/HxCdu2RSjkxpo3uU41vN5dqTzVCWXScPF9GxBQCGw5jGtinJxh3VqDmId4sxD5nsNw3TwkO2uO84uGb3+7LFiWBeu6oLUNbWuaA5kEZB5PbF7DzIyN2dqA5aLf4ycD9aQYY2H8YUJaV4t/hQrnWjF7HluHr1UZ4K10a/8M6pKYdgDhlZ4ZrScgPM0JSMY4ur6PArwWCaH0kY5AheFPaF9MhGd4kJ5NIc4CkRW1aq4zcs81G3swzsVSFKybKYNlxNE3EIHvVU2poExv12mqsEEVRTujGkKkXujwLVgvC07nU14he8ZaEs8rp5ugAFiWVeFxmiEQNWiRLgBuTb3CT+cTiAiXtwuA7j1ASVEaTL3hGLgw35ZO2PZ/zIv30QUcGmmB5cjzSNC2LjSAvSUsPQy3bSQRBjFj21bUOnUldJkQij7pzUdowy7GGQTIp9PZQJ9CsSnJoMilfS5cKLWCTbHvz2idFNpr937P3rY6N9LH57kKQ8CkXg+e+9z33xT5CD1yAeP02wSxvQ3R85e/WmSBzzUU+QJAmuZIJ8PvfX4JEMbyxwvq54JCn7vdH1GKkIPwDiEi8NdXABRh4FUZLyGMKwCKPEHwChTN1yjQ800VTH1OXADjuNO/a77KBB0qeYP7H37T4DCVUMiDAj8TkUlY+3kVDQrZPFgObSYQceA4AcND6PbTPeFOCRWC1duVHF10af0AYIEadgprG2oRe8g9RLy1bgyQS+y2FKHDFT5dgGoCwJ2YqhuMON0CM1CifmW3JlEv+RkAuDtX7l6nVfu8ODz4Jeam3kvU86BHfmfrt+OAjC/zWTL0KfDFTtGTnickj2kZ4apvfelrkgiwjyuaUkn199RKdHUvIvL4XuwD0LlO6SH2HrnX/dpDqL+wa3cQHPdL4vjPu5N+uxB+KBZRYzDcPZSAdljuv8Z+xhyYoTCld3iALzOydDyVYNX7XcQN8Zwn07HMeABBIGcEIUEikNZpdSICPVQUGG5avM9uFCcBnwzLTdsIqISpTXbu6TOeFuMcURJewXgE6BXUCNw+KQ1Kr0BreAtDRI7zzJUTEFhm3qQ8N+OTRwIa77nXkdS4Xo3vh+qfVZ7v27vq78F9evd+x74dpvzs0TKkMRGPy/MGvD7o04/BrQ4TRoFLJdBh90Tv9MUY6WA3LmOAr8+wdACIpdwSASz1judarwbjgedlwIB99HYxQh8nvOWnaX5jX5xOD0yTzyf0aemKpp6SQCCQlzftXpwhWhvvPc+/4ywfXjvo70eeO/I89/fzOfmPLu9HM+nlsxz30a/9sVsuQMO/x7i/tcEOMfGvK51usf0yBmCKqHt7r/B+4nU5nRMGGcsxq4ypkNGdQT+kgcaRR7Fv4XB6eFQJXD7YN8B4zsROimaSzCvTOl7PDYAt35j2yYxeL8YjTlRBloM8L53y/RIRqHrIdu57O85IivMjx4FR+lz5Vmnc51M6reih733fFzIFOLmMpUN2rQWe5ssVtm7Y/+npU+CSqarDQiONXub9QWpf+jLE9fzcvtDVXRqueznNM4SbyrrSA9XoMAFARWWnxejwZduCr3JDAp8rj8R2a2879zdPE4QFKzcAZLnhSWVCIqhV4Y0hkLYlmYdjfF/fka7qT1HAoe+ffibtlOe3lOHp+aw894hh+2f3Z9xHPM9zv++K83u5l3+vcleg38u9/EVLDxPtfO6PMXcAEpGZiP1+M6iDTMy825rxyx5qh0W6MmPQSnfCXX8ZsclKrBZRGZcQhadokk72/jgR5fUYg6GK1wIiQROoQEk8X6B1h7sg0+wE7Pc3R3kvqeSZCgUIdKlKSWHMBaDS0FgZGGFdE2FomFlh1GkCm7J6nk5ovClzUoDTfFKhBzPEQltr3msjyok0akGP2twJXWNiYYI7VwBRMYVIqZjn2YjsYtcK5mnGtp3RmE143rCum3pTLwuwWXi1UgcFjuwYhFoLmAXVDAJKqbCUymA0VChDl/N3wQT0LM28L6t5wJrV9FRQa8U8zSi1h0I+nU7Y2gZhVT7WaUKZq4XDphh/5MEiiby1bqHsSnKBhVeDXmutoW2bfa5ojfH28mIMpGDZmkZ82FQZvqwrtnXVvPLbhsYtlGZZmB6h2o1R5dbUU98Yad4Luu1lNxSIEKyuzEh/5gw1wmnCeR/e6TtGy4WyLlgJvNEl+sf3BzHUU8yCN9H5wxTylxtESkfCSTrjSr7Wtq5QfZep6zj90/8+mJDVjFmIUGoS9IikVB9dMJA2GGqpYe3fledp8PvWbX9s66bwZsx4axcICx4eH1BLxcvLC0CEWgvOD2ftT2Oczie01vDy+pKnDgAwzUoa11pRLXQ4moAsV7Z7DRA0LYXEUvn49iHsjkuHxx5iXs9SN3qwP/N491D0HtI0DN/E1ZUuyJCIaJHhAHCvAQXkwfMT/Vx0jYW0ruCGn/EeVps5PUvRdteuMKSmKTBhBll9IhwGdT5m7YWgNU8H42FSbYJNuUpEKJ+o0xXURRHbxqDJjJDsQN4LN3z93LCqmHBwEIwECiUbu98jcOtem4DRBaUY3hdIKfjKbOGiu5fF4PFOdAjXubzrLbx7tctG/WxIyvSiivBbQh9m9Tfae6BDCgiWA7yESj+Eq0FK2Tyr4RwA6moEmPAtU317yqgkwpCc+MvIvUu/djNxPH9ycGd/LYRrRuv5A11EZwqkkHbnigZ1y7vFSQYAESFF9wmH8ryx4ZS85/OLuI1JRHYjSz+THDuExsfv3ygx5jz47y/txnvfMg6R/Vzv1+LWe7vfbiwbU/NOu+OMd3WFn4/Hnfz54vwDkdG9wdlQeJm70kND9e6UGuTHlO0xX+5MnIiATvqgY+0CdIOfrPAhgrypUVfO/exg2UQUR/AbUM7g5soC66v4OSWhyCDZIPijR+oQTdkhtGqqHacP/J97qAl14bzBsZ953YNwvy7HeOA7qbV/iyIJvsNAPM7ENAOGp8nWCA/G80CjqwBdpQQxCtPP0GFn9J1wNZN+HsTspwgIB897nyPVR9Ao6ZwzeB0Xc8RnPXpHv+8oLxudHp4NDne0H11+z+HN6Cf0OfHjqpsT3Erh8GtLkCj/gLb+GeV7x/Us/9pz4fKhvC8p/elv2n36mQXL0009zZRcQ8CetoLRZMUM8/tV/0s7xjYcDfsoVb8D6s6Tjrf2DgA/WpgFG3r0Ls6yN3QDXUCNbTrJbnNnESwUJ/oglJ8gGjFBP+eT/IQkcKWjzO61rfybRs3vJjqQ8RkRwbJYFDEB5slTeI0GX5mX6MbaIz77ePkYvSZhBN5xrhus+vlaUi/dEx3wZ/ULm4zlmy2SRv8KhwXR39GeWGRDqMPH1rbBQ//Doz+QN3unB7jcKc/HCE6OyfP9cvhsfv5WX66n4l8ZU93LvdzLt8pdgX4v9/IXKSMhgcR9UXpAhhduyCUOC5uQuctqpAtwXZITobrNyyiaPmhsEKYY8xBeF6nfNh4RCk+3YkTPzfS9mWPRzgPQsIauVPA85/6YK3PVkVWZ9cgjlhImdkG24L8Z+H8lTfWN7vy6sp/En2zxox2X4QM5EBWQwlJbaNtR6EgBd5e2mWe1zbyBzhyKXeVvt+4AACAASURBVFPeaqIpsCfEIs0vu7UNEyrcC2yaJnglmqu8YNkWPJ4fsDVJocE6QczULKKCQNR1CqANsiUhTSauVeQDEcE0zZjqrIrlWgBRZTqfTqrQFfOQXldclkVDvJeCsibBpc2fiU47YW7Mai2q8Pa8WK4wcW96tA0sqqTGspiX44JpnoxBFmUePcxwKaZQY3AzBhpq6T3VCZgJ1XN9mddprRbpoXHkaUYToDrjaN6zzp6Z1z1EsG2bKsMXVYZz27AuF7y9vGLdNkDUO19Y8LqspgjXUO3MTb3TW8cXVEoIVGFMH5tCookp0k1Z5x5+MdU27dx4EJBlxbnX54x19+IbFeyj1b8L7xIjLB3udzxclDf7/ijAi8H++R2O1JmwpoHmMckz8JnQ/mgozxbWXjgxfARmoHiu4aFuwbauuCyXUGDeloGMCOGyrjifZrhSvNQaTLEbsgzeftoxCDd91iZCFdb1Zjv7sm2bCuILYT6ZRxURuDW8vb1ZDWrIcj4/QITA3IacddM0YV3Wod7sQbFZyHUA8EjsOu8lhaQvkBSm/eiUPJ1Ueb8s6vmuuEn31LZZznlO7woPxzEzhwceBKCqQgb/3b3DE7zZmRlrbYvqxgYiPKRN8LZLrZZmYdO24N5opPnPByMdmPDE2oadn7UbrJVC2ETTVSAZp7gwxpX0zSLJOP4++Rx5btOm3h71v0/wdBK6Ht4PHaPYd1fCO/yXz59AVK3/X1FP/21eJBtIzIuRALy+IcMeW18L3NDJZWAE0Jvh0IKvBSpkCSFUUvpA572UArB6VxRLnzOEeRXpIdclpZ/YaYkGtQRpX3SZJdr3s8H/XRW7VCyyRkEJJboKJNUbvUKA5tExuqEUQ9RzPc7D3peAJoIJK/uCXAkOnTgdPin9pvTwOAv+EeGH0WHA292HyO/TnTxUqM9ncWMTJKFs0MceWly6PlecVukKvrHDB2lEjD71iDQaNKlHSEIIJNM+wyioy56mA65O5Ff2YPLfGN7pHtQ+1dfCwB+jYHdi+F29iT4UhwNJktnrMhgyDvX7dYPDWP9du/sjD/m1PmnOmpiZUk+1ETA8tu5RKZj2Hd/v2d7b/KfGn3bPp8B4GkpwqMaSZTC+8bFqRb4X7c94lBknPYu9BxcBzYB4VB5ove3rBgahFgBlSrl6e+IAtnr87BA5W5h7AZcW49TzzHCYGRGRWCoOeoF6mOn5zTQD9GK51oGXtI90r2g/zyx4A3Dmrjx33OqUc57oa3TR8ZTvwT+zvEO6vXtfdp97D2ra4cNXoymGOhJNunLDGehRdjyP7wrAbRXJeQ0zhjNcR05XDDOsV/r5nvAr9X56buFOS+7xgV0zWG4WlSZumvKrmMFI27agY2NGHN1Kp9/Ds3WHSsiUjyzcezKgpD7zubuZNgoj/fyazR8s/DDvBQ9XL8i7sPdBdjvOLv/tntfuhf0s4/Ufw+K/sozGFF721/b9c0/z/7Zp9dn9nJ4t+br0d47KbwL8Ptz/1k7dl+PKx5DYR09SkDUOm8pJ+K7SGSrpWcTZiB4B0ek78rSDOq/Fzgynf5yAIrqlQO+wHDTJEdN3danvv8xGht+6yf4y1jiq9xY8esTCjZKMA2rUyWnrdJLYR2v8RBqn0sCdN/LnM38+VY3Kx8ZfOB3tLU21RC+cl9KMgm4UrAvF7OkDBcQEMoeKZVnAzHh6eIRANNe58bvCTVNSiRk8w6O1AR9SSh+UPd21LyfjzxUPWluU4NBerwZjnBT6RGTp+CzqnjA2Vj7xVrvVIm1Nlspts9R6U/LS56BBleLZ2mYe6nlcRpdJN7j2sldUE4DNx6MLh8HzHL6PMCrEE13l9/38GZ7d8Wz7cqU438Pk9eXj9+7lXu7lX7LcFej3ci9/gXKQ4twENrvDekcEvUeG7e8pwde55SwECNY7Cy2ShoZAJog9aMf6xITuSTIMJjEFg3JLv5o4O0d9v3q+e/oFN74TzokJSo3hEZdVSe+HvyfplTstdF0OhYz9GosLjLoBQ14nk2wCAAq5gM48yUvB1gCY57cqD1Qwc5pPlnMK2HjDNM0a6lsEMK/ZE4CNCA8CXIopaCqABohoWHFOoVZB6p3TwGiNMc+MhxPg8ZHrpHnH85hZBOuy4GQK9FII9aJQuoWykSNHZIczoKGBau2eOiKxt22XAFSwbhvm6aR5M9nCYZp3tvORmYhvzCDWd1zxQ1JCOV1tLvs4TMXvbUsE6zWhvkCa/rXW1BO8qQJ82xqW1zdcLgvatmBbN6zLgvXtDW/roooEC8G+rBtYOLzIm41BlfPKKDt+cKtmVTR2L1zmFgwac+tMd5LDcWML8W4QKUD3QB/DuWXBZFwfwHkvJDwSGr5fjh7J+dNvls8jYyZiYZ2h1tO1TiilplDhEv1nEct/DZsXAn9pR630NgDQs+ZyI5BFCqkIgw5XtJJGS9grUCKkt8HVfJqRcUEfyy6lQWJ2p1JQpiRiFlUAn89nEBGWdUEYR1i0CV+EqZqn+WPF69c+u+EBYAZVDaywBqiRCMFSR0DPGhMkd6i4Lh2H6e4ppUaqgVqr4hbPHU8Y4DPrRZo00EyobpXk+ME2dm9Hg7dq2EhJ+fks9CMBlj1whxcw5GwXQfLg8udGQWE2tvC++skedIFJDAt1wwPrNcog0KJQUPcIDxLr3YV0farim+emHvWl/R0AIg1znSDym6X+kH6uiIBfXkOBf6V0DmU0IGQRPEj3loZkv4bd8PIWRuGCJqx7kl0ROwpexYRSIhJK9EPBlC2MykvFlOBqNEPUhV2573vkE+OzOlR4W8xjHYAUlCIQKVAbElOlJXhz91Qhx8N2OhwIVqOtYd3i8vAZk/Md5Zoi/HZdiVzrffCz9503okqJKbhqIvYiuxFEN+Zq+VpESemGVu9jk+tz5f0y0lj6/vFT/4ji+y336LqHwxvYqUjfr//qy/hbji6mb75/9s+68UhOL++siOOyb/WP0OErGnDeYrc3XFA79DcZoQTNZed1Q4MRe71DgCpcBZjOeo0fCuRNUE4JvxIgxSJrkPFLRMNYs9Ja6S03jLPzmRMe83kRpUsFADyEcdBazUJfd5zr3c4e5j7BbgQgQE8vkyZH6Gj++w6XdOVnyhOAl5+s41cXR+/+ucf0wLjnBaY9vwjooaTzwkywBPHdVlj/pxF0cwklFR3c/EbJsgMf0IC2E88TCi4ZP4MXuLULEw3W+99/3Iyi53Bol+VV26SnxNcZTbOiK3JdTf+w68bX3WH3aTdX+6m7hVM+MsW3wrj/Mwrtvh/hy/0zR59e8nn/d1LFuZf3lOjyjfu/ugTGDuQ+nmV+z+mkIuiAb2cDkPZvv6V/dk5kI0BxBGzP1poNk7V4wG01btL9EyZVZvwCZMx5e3zAx+DxI0XtiD9Cs/VIQcP7xr/1KRzxf0ZQYehteMUVuF5cfuhv5agve/6gw3M/o+dZ5Uy5B0oziBlOa/oeEVdgd57pz6LHqFA6X9O5acMJ5yeXBSW07MpwAmEzB4VvdbRYJDSRHiWQSjewcF6nFvc816hMwFh1p4tS3YNB1e45f38nP7g9MaOhcfBmoUw/UJ5/Z7l7nt/LvfxnlLsC/V7u5T++dEIkk+0EDErrnjPG/V9/sCVR4qiAeohWD3lLYw5csudHeVLvk6ATyS54cs8zShJL8bCyQx1iCkD3xupj1Nx5PXzswHCbUtaZFiXwqIeOBdDM8jccBsUV9vreM5Sha1FDmh8A/2WMyp/P3N5axWvC//rq9QNH+Zf1vbGGJAMZKmBTfLpiO0JwDcQtoVkOXK+D22Zf2BQWOv+NlbivtYJIPR5L9bzKk4Zhp4KH86NZZyucbKuGhvr08GjWwcpovkrDBOBLAYqQChQhgKiCS7h2xaoJHc8AXrlh2zacN7WsrVW9dzxnuOdEJ+NE1nkacrVTUWX1uixYlhWCYu0BQNM0BKGIEctR5YJMUgYMGk4dAqzrCj4xynnWnOckGrq99LxQOrc6l55rcG1b5EtXw4KuSKvTFN7cZhge8+lW6NIGCZ2zgiHsbGvDuq5Y1hXL8qaK82XF5fKG9W3Bsq5g0dzlaIImrYeyhnRFhO852+fuALvZ/Ps9Zv/TkP+SjR9CLJjy0AakKnZgV2aEQFjSuK0Pu7QQDs6DIdLuvrbQN9WeH/Ow7p8MTzyJeqQ/Ga/6QnqNIXillBv2d/Usps+6zu4ZSyCUMkV+cDIFdxaEq8HCYjlpKQnHD3CIAOUZANRbrVBRIYEp56VxzJ3DkodnjwqQGFzx8ON2MUKLyxXzSxbRo60rpnlGmXKccMc/EukIzmcVX3r7jJ1iES50FZzOJyyXi62+5qSrU1XhqGsmLacdke6Jti5+BGC36qkFwrqsIaxyhUPbNjw8PpiXvp6bbN6o2So+QsIXC2u4qRJdPNQ5uvexw6kbs4hb+09T5Nt2xUZ002QQZL9HQTtStJiCyGua5y8pOODzKxYGnNxzxuCcCOfzKc5hNqMkAAGX26b1XCmkk0cbACx/3wB6BfCI+bOmAOCvLzj/13+l/RVgAWY9Vy68YKo9YoIbXwGE8ukJ8vIa4/JxioEXxQSWwHuW1hyf7NmvMHySFaI2H+rp4gJPvobFoE8kBEs6NzgsRJpLncGhRNc85qoIL+gh+N8rY4j/3FhBLZqLOnxyTSFHHh6T2cCCnEjT61ZPV0hb5AnLcRugRx421/8P0RrynrpNLl3Pob49AjVF5Al9bsrjFMHZlJVbElD7AEJQDfcJTvgqjgMa3ovUIKyeU6o4FzMEY7SmURfYcbDDisHPdUhJinpD2JvOmjGAVD/THN/E6Za2RoaL7AU0zK4B+ojRblOXe+6BxKnthMt39UEkeb/3Bejdk/T/HhL6OL0u7fItiBlH0pvQ+Vcol6hHjyTDcTZwT42SehtjuylfzYCc181fSMetR/sgXN3qP9xL2JXqRM6+gCCYQQBOKGdyiNUIIq8NRLCzswux8VQA4TAIwkXfUTsxD6cuRpv63tf5zzPKVh8ZzIn01dPvj9GujuNR+4UXCIAzBC8ieJJPasAmX2xSnvAgDOavaUo7zspz1cs1pL5G4z9WbsP9n1M62FD8DvwDoJrxFjs+vuqJ4ALlVfKmEthFO1OdbvC0CQ5jjtXUgMQuk/vJJlrCS3hQ6nVXhgRe7JBv3dPfhXKeZoJH62jcQKBQAg4pl2IgHa+07AEu7kGKZPhsTdiPYkeaK+McDx7jqlc4QLeX0qeTCJuY8TAEZxBIdMVeDDFHr3bT9fUAFrNS/RZc3ZIf+PWr+38WgH6g5L05GO5Jv59xKdD7T1CZyd9LP9uBa4W57N67Vb5XcU7DF8J1RJv9eXlcSURPoPFGpuHz+/7YJ6jBDqN7VxM06p5H5bvqh4xYgEBhOA3oXBWbceep1chTTcmFTBKYKhk92PerhX52xXmWz2y47Vc+3m8XylTICLjZCz0iAaFHntiM15triTSMgNFdV+PpkazY9q8rS31uh8gCkcgemKaedkzxl/IEDw+PKoMRxuXtDeeThvm4LBe4fJUAM1j3MxxYc/q0nyjX8zpecfxZqECoR9Xz9C+zAutAZ4I0zRqI8LYsQ323pMWVVObkuekbq8MKFZVVMSv9S9Aok40Fa2vYkoH1dTs0rOEeCgk94qUfYcdzdO1R7teA29eR9l/0yWC103+pR+n7Lc/zu9f5vdzLv1+5K9Dv5V7+CuUGFTEwy1BLwVHR8YPNiQTxkRkepTKSQMMYz0wRZQvQ6NnAF3RmtCIpDHZECxXzpyIj4NJ9D93dBVI8CMuzwCD/dmKykAqUC4mGbZT+dCgxAPxxgzD6nXp4NQ+3ti/XYcb+KqWvvX7pqwFSL9eKJPBQAIj8YO7dpEp09fAuVT0xGYxaJhARGm9Y1hWlVGzbEk0RlKnXvJAEsKBWgFnXu7AqCN07dW6Mtk4aCnpesa0bpvmEeZ5xwoxiOcdPp1N4A9ethqduIcI0T5jnGW8vryAQmnupueIJLTzWuDX1HZnnyAVOKJFjywl/zV9+QjD8ztNaHtZCzvTtrGtFdHykD6nXPqOtC2qptl15EABDumKSLa8WAdhYvc9ZPB95w7otWNcF62XB2+UNl7eLhnTfNs2L7t55zGim/POdmnMmQ9CFhSr1CgU/syvb2TzYxeqyOYxdiqRE7jgo9rGMgkDsfsf9DL0/yPt2Wd3YLxLBV3KZnd57TI08iIZ+f3AhQlKeg5SpL9XgDbZn3HvL+y4AN+n4Fu8oAaLYmeEBBynlMrO5c6UkQYbcbi4582EQ3Ptc13gfTk2/dqHM1jYzQNmxzqHo9TVKIpi8vjtG9+Wr+pNdLOy7MummRF83lOoGAgXkaQrs/3maAFnRIhGmQ08uEl7dtVZMdQK3Da64p0qY6ozlsoCooHsgj0o0F2RwY6xQ3OUe0FkoJaLwXtS3GyxixgCTzfu1HfzhcicB58GtcYxkIdopWfHb5iieZoEbxJWRdibPsxotMCQE715zDtXn7/DGcHWr0CsIj57ZRWH9+Vlr4E4TsHDKlwgQGR5jBnOnUzwUrYfvEyIV0AFhuEWGs/PYy272XKnjuX9FEWQIW3o/EO11nAIg7aH+LA20UZ92VZwU0f1VqgDinwVS5IdxUm67hvRT6xfDvww9J7JHC+wcEnL6KYfULgMOJVAoMkJY1yfyXSlrxyYj5Ta8Kv1cz/gBIDQIKsa1pPz+XpKdaNWb9ad7cRb5fm5+PunZzsxh4JWjDeTzZRSuyQgnWUA44Lv9qZRquAELt4Sgw8TsBJcfLc5R3BQMJ0VVTKrTdt9NA1/Dwsdek+G7hmd15axFnbJ6ldww3PQTe4t2n9q2/hXjn4rjfFdeIykCTVxcpJjCw3CTkKWcmIw3caG9GrCEgoB6iqBSCqQ2gEuE++0Gs0qBeRKRgFO+BTWWJiiNLguYr8YMNQwT0nZewJ2+S3uCQok/1vUKwdPN9f5J5PcvWvLWcBzxEXDMii+CqJHE2WgCcp6bEN/EWbAdRZMMTvczf7sP3sPbPQ2oCUMAxwMjXvRn91EIjDGJsWajg/GxDruSnsn3OogJ5O0N9PAAfsn1515TCFQrCG/vwuS3y1e69kz/TyjfojvH066Xv39gKj/qkHBL5vLt8uPrSeg80lWNJp4KRxFcP/MJwEvptGYphFqqKW31jNibEEn6b/BoJqe1PNaf4Ve2NCSthfFjptMytr/+jWDB8rU/C4Qdi+wp79Sb3g+CynKsR07GdYNflROy0bVUkCJKdV7G5QTOJ7ihK4AueykF67qpM8Mu7RLBldd2tpmxQt3N9Z9bMtbqcg+yMbgxURl4ZA3b/r39K8aYhaGyvV/D6EMV6HPxlG88Gj9dlf26Huyl3VMeqn58brePd0ryHr2S/HaXj93sWpefHff8+N278vxe7uXfs9wV6PdyL3+lshNQDhbnv5h2izBA6Mx2T0ruDLqEsBVJiZUFyoROyGTrvxAKJZmoiCpqNEecsxoqCHchOYuola0pmFxY1onDTkwJPDSqdlmJygJUJcK5EaiYxa5FT/xNACa5QS5ZP6FW0P9jOdK95Hd+J7O6/lPoqx8VMh6/1i+PD2QF2fBkUmyE90yqj5yhMwVQV55Zjimr09Vzm+UG0xxLqgwkwEJaOrNYLRS5GYqIhjpXxYnlebJwxxVN4aMBnj9LPTyKKipcqAfgdxFMTT3Q26bK2vOmIcu1bg3jrsqwasS4hr2eT7MS96VgqlMoO9mUyG3b0LzutmmubjGvTgPK0+mMWgq2bcVcZhQinOaTKuyrtl3rhKnOqkid1LuITDnk+7Czl3ADa8AUcWIX1TLYlSe+diND5tEg9LvlTieCUMFkf4vonpJNFewXyxEmrN7nwi3G2phTm+hwJap4cOt5D4HN0hUSzerSZ1x5nrzY0ZnirApXYXFiaEOgtlM8wwTbV+K5zhCPits+T3nONGewXjuz4I30XfdMeeDutdPbl8iN+ZRkiOH1I4IJFZLCRvg+2rY1fhdSRRIlAWUxT+fyDPCXd8ShrmAURqkT3BuAWYUMp/N5nBerf1kWXavWIBCcTie01kLJ7/tGv6dIIQI03lDNo6jUnrczTSiGH7vuB4ayOXblud+d5gnMzRTZXWArLCjEAJfwOGbzRq/ThFJVWbptK3LEEgFiHwCCOqnZV9sazg8Pw7lbq4Z1j2gw1KO4+Hci0vzihl+kFBD1kHuA4sRaJriYSdoKoYptXSHU55bMY2I/R95vivHD5thzp8vV8wAwzXMoCgEzaGkN0zyrcI0JtU5g3kD2XbgBZMooIvMiqX2xROHRtEgAKCKZnH77rHRAUpC7lw0RYfvyFd5z+vQJU51UaMQS+Q5VfG4CHUIooEBkecAtUgoVDV+IHsa2UuqmdKG/h+TOytM4x9Lc8U7ANihH+0UTzsi1oh1duCOiivQKgVgSSSkSBi77cqSMP34O3UAj8nfb20o6DhGjBzxkuMcNHDhyCVE/a3wQADx3eijr/XGnG92DHDeEs+LnmNOLYms6vpe9J9m/ALgYvep3/dynmENTyaTG/SwSEUsh0M8WV44P0RYiTYtF5TBvXljqkXxm7FNXHJ0l+UcY5CRhr4/Exx/zkOvazaSghzP16rOw+iOswh5HHPe9T6SuheJrva+N7vmSAV5ulH77uKdxdd9H76e370oHAYQGdYP2RBR75Jl0DHzVp/TZv9s/sX3svbA9X0zJrSxaD3/qxJCYwN5pMTeKZCpgCBptmAEUOgNSIlHw9NiNz6iQJzO19C7evAAkEWVLfJ87vcXXcxtwtD8fHP7oVedIPvnGCdypv54AAI/2fEMzPuDJ1uKr9SXDO/Boo3mB4DHxEgH99vzr9wDwO2W/uj9T3UfezUrgo3drLZYyR5SudoVMzIDx21VpgpgGXgA5Q14F5QmB2/v6STAD3cO/58S9ihDjZ5J9Dc/N8NKU4VHq7ux6zdplw+Ol9HMCALbWOiaLQ8DgMWAPsUDOx7PRiC4RGCNtKJ+g7RWD/RFQRKDK89dXOPK3nkKEsJFurZUbHkFgAZ5A4Xk+nInfUfZKdOcHvlex/pPg/gtK7oHBUaxROgUojuz4feVIkKr6g8ZQ7D4vX+y9fZS/z3KEmT9QDB48FPWPVUFhFLWrFsWdBGxiBk9VqIEQAMP5npvaAn6T0lduFBXnFYBPhli/AGGITiAlo1yJbrQWs0AqgUzBW6D7plje8ZAVakdsm1F88+sD+gi67hYEHk/mt+C1O9Jnw8yM73R/N1aOpYjOVTXtMEsGhJ4SwqNkdQVvJ/A50fHKf4wK1VIKzqcTSqmWqm4LvHlZLsq7tjbMBZWCCcC6bcO4vzVbsrvi131994YNfv98msLrWysSTOYJzjYPblTXIAnelfJ5W9dhnm8V9zx3+rW5oYGgR160Ts2lYmsKc012nufpnO9UBA6V2cZWjBBF17xqujXyzLEXELSXtzUUo83GszXdPgDpYT+n+4Nx/D/UiOJe7uVefrbcFej3ci9/4ZJDB35EmPq9JZToe0LGqZ2B6T2Qlmknw9t4X3dwXLD7zpAEYULhQSew0D4uFGM2xboRd4n46ow/oYkqWJ/NU62B8Tu5bbt5sIEhhSFN68gM329yWwnO9H4uriLAfwvwt2MZ+H9s2XtguZKRXGDiD5J71nRPdBXyUzCBjTXP4lQIgoJCwNJWzNOsCtv1glrP2HgBBKawpQg7WoqgiIX4JUFlDe3u1soijNaaKr+2pn/nhlNzj9PSQ7jrhSDCa604zeql3uYZpRTM84TWGKU1vK4r1m3Fum5YtxVsCmdxhRkKzvOMt2XBNM8gUY/x0zzjfD6bct3arprzeapT7MkmiNxnwgxYH0Pw5Jy4SMxpXh+/DWSvYf9Q4S5b3mkqBFTCXAqKqyQE6nVqjH4X1oopoHhIzxCCdcYQ/lmaekd56HDPM6se6CZojU9ft26V39M5uCDX8KHfz4rUDqXDcx+G7QM86/0a2kiKsny/w7+EIQmTGyp1BppM+0ClM4mDwRLGz1IKplLR+P2855lFJRPkuDBGhQSMaZ4tIkJi5BOOK4XQGiy9QcGyrDiZB7oXVWL3l7yqSvXGLN4o+3MHMLjVPj9+ehzyn/fX1OCl16F7QBWGun9LKdjcS5x070wge9cV8BIep2IhBFtrmCysn1afR9MVcF0QbTBgoy4omKYZ3DbLZ66KbfccBJJwQDSViXsDuFDB91I2QHDBpgtd3EucPYdfPrM/NPW7Zx3PwIynzGMd0RftwE7OmGcGbuzj9TvsItEI2SMPeET5FDMZgnKC9Mg0koWK6s1ZfyPgq+LYwcOHurAlKxDYwnQzc/wNea13cxKK18Btt+dV97J5hGblUVK0atjlsY6CkmCV9pUe9ynNtq+1CxZDu2Y4iA1CiXj4DUTAaH3f2o5kCwQIUVfwipgXu5o9Oqh2X8jUJX8fg0jtoNc+B3QNsSZAzcqSamc+yMWv6pmkyvaM8/pZElDm68jYrfX7HuhuICasnjdHSuf3BWv7s8fx/PUuTds8ntHPj+3n3evfVd7zPH9PIbHv8wdb+5GXdmcux/oqda/3mDo/ASB55ib4uNE6HXwOz151W5XnHiGISSzlFhvtIygWHcOVKQBwrlPQTG7cR1RQwICUELLr+5Sa7qbKVKwzhKCDBa8AZsNnLxBp8FDsMYQr+O3w1eEtH8MptH8812muke4Z22DHMek3yL3Rh150xfmvKj+zGW5U97P3Fa+qoRWn6/mbRw+IuEAkAN5AeAC/Cugx8eChMO/nquPcAffdaCt+HXT+Cp8Pz2Za2PlzfbZHiRJH4R3GckP5WIgUSSOmi7HEeZraTw9Fi682h9LPNhFggegZQ34m/jrQ+E/0QAdG+iyM0ej4dwGS+Zqvh/7/+cb8PEvfor8y1/mgZBvvfOBduqIZu6Ff/90NqfotT2gn8EhIxkPb+VCcKMVu4mFdvAAAIABJREFURwrwxfaG0qdiRiKCIjUmXPtlz0EjKWwA0NSRoDBrOsLMz6GfG/tlcF4wsVv/lCJ5I+NaDuk5x52uz040uQLzGUfnq1XeoMpmXxN/RdR5AjoPHhVvNIzsrfxKD+Ru4nR9DUCkw/Nnaimxp0TMcNUW1nkwumGA+14pSXkefKsgeBARDVc/lxoyl0ibcWNkw68D5fn+KXlHeX5de6bvzXCxjOMe6kpnZH+v15Xpnr3c+tYY8vW7Ev1e7uVfv9wV6PdyL3+xErz/zjrU5djjAX4tnNvXdXwnPWNEuwteAUS47Z6T0ggsohCeRKsHVnq5bqArVnuYU1Ois3uXZmKOweICJxmG6ExOhH5lsZBGolbNDJBU/B9hbCT4vRA+g1FZGQ4uDG7A/zKwQdCgFrCfbY72Idn3ivU8n79J907/lUzg7RbH1X5XRnRj4ftlJ8uv69ULDnPHLJZ7/1ZjaronlDMqus4NHuLcxCHGCfhvboKpCoTNF50mMAMTlVDk1OmEdVkAU7YWIVNKGSwJQyO5CypZ5ALjMBo1YAOkSihNmgkvCZrXaZ0mzNOCzbxlK/dckgRVolOpmKpa7Z5OM1pjbNsGWlcsy4JaF9S1otUNm3nNCzSv+cYN01RBUK/28/mE0+mMeZpBpMqiWgoK1ZBIeC5kYrUALqL7ZAJ5eltl7iKmfZ57CaZ7a+6R3sVG2TOdRSJHuHqEAysLaiWUol7SzfawGiSoR17kPU+MSIYTD+pOUCOTVZqGxHVGlV2R7vXsJXUuoPU6jxiW8fq18nwUDY/yu12bobDMl67bFFHvc4jgQbpw8MWEw66Q/WRo64sxuZ+g3inPbv4sRcNdC/c8dy4EOGjXFZCfnp/Rtg2Xy5vOseWOO5of+SKY/scjOvja63PTdE1aiksUANQ6ab56++fKc+buhe71ZZyvaRmAmkKWX7UTOaOzKEmuns+qOc19vmCae79DeQ4YPnDP+ty3PnY/a6gQyD2o2d+pEBFMp7ONgzGfsjexwaylV3AJlHvoCwhTnXC5aKqJaYZ5xFOEFvczLo/dFYTTNCUh+D4stM2DwZqHjVflewElRUtIVmKO0rr7Xk2PTHPVfN8Gd25soSBFketuWA8RTHWy1rif5QAaEYCGakZAnm6GAh9tcM8QAqE+P2dJnwlpbN5qxVTNm87WsFABCuH0X8+qSPeD+ytA9BbTVamEZ2hMtM+PIAx/wkhHfEkTrhBJgrVcR0wurpcpwUvCKeqdLoDshT6IM0Bzo+OwjMY5qe4kJzoS+BQRFVTZvfi9f87pOkgoqTHAFQxu3DuNol3H8/4+gKTELEiPYy+ypcGzy+6nJrNhRA7yGN4n1riHoxaDW/ecdPwvSKGlUz3cLG0IYLSBR0ZRz9qttasw2D49umfy9ezd1fe3v2xULo5KJCsSq2BPtw2wl4g7iW/DnR8tV0fPzkNz/532327Bbzx1XZ83fETPDnxGeq+K0aCQUJK70nmkWem9bg0dScdfvENxw9u3CEMm2p9AOFHFQgAxKzyLvqRKfsX5Z1GlaKUHgIAXvGFCwSwzMAs4jcfPgdh70ufHw9YKAfLmEKUdJDxCxDzl5EGNZjKoCJR2S+Pu4OkPPgAgNPlidP2noGU7uAkYXwE8KU5IcAh5tCe+gNAj5PpKPNrYXuyFhys+tuO5HymP9tpLBpafqC+KL8WunuHcPXjB17K5URr0LJtI8457+P/ZIq9srWEGzHA8VUuvIHqEvJly+EGNiSRrwgw/KxyP+EdhMfVud1bUpIwQG2emKjMtrnwGhfLJ6xMDMkk1ReSTNwaw9kg/7mFOBfT0AOKS9tgw5UErAIaXvwpQL0DQUxLry7ZrBcAChVRA+UndtQUXCHiX9yZm4zvB5Cg3OvAD4cfzZP+TC9FB5ALgijYhMgU59XRjv4nyjL/bM3uZSMwL9RR5X9KifykYDKBuTWMnF5x+6JX8sALd/nWDDr86NOVPDTWTw2D0XewoF4vqo/edRBQRPDXBH4ajI7WZnR2FashVHP6J1AjEjbKKiIciA5cCiugPebx7OM88RrruylR7vFxtiPEc3WPt27N747y/InAoaLAsU3DjckLnJbxef177nmh3uDyz02oPDw8AgMuy2Lk0yh2cpj6akza0+7Hi9RQjkAXduKjztSbjKaT4P7Wl8iCXl7FGrSIbNSMZYpNF9OMbqT13628GHZNFUfSISu6UUtDDqVcqJitTz/OhJse3DtNp4H0vJpjZA8gHjRLIrQTQeUhvg6gEnGS+a3gfGJy7sux8rzi/1aVfaUBxL/dyL/+4cleg38u9/IXKkRApKBCnBklAYhbVOwFa/PhOZiw8iXdKpeCMom73AnK+PTMwY31Dl664LxOtWl9FLIcUzHPDBDb+sAtunXBygXEprG7iJlT6QoJnFogUTAL8D8yjsGgOUhJtOARWoq//EdKyj5esbP+DfiZv179TSQuGHdwYoapfzfuW+jMuzvB1VOZShYckRcNqwcK8w3M0FtRCqPMZ67ZgQgFLs3csPYCtPTlDGf1sQRQLBJWsvaaCKyLNSz4tC5Zp0t8sqsxK8Op5jAHg0zxDhPFiYduXy2Ih2NWLfVtX9XRnBpgjfKfuG/U+J9LQ8MXeIYJ9tz+qodAgatiYcT7NONVqwuIMZK7Q0+/9f6gwa5Dgd48tZ0BJusW7yvYKaqlopQKkuTbhHtJiISiTtbYbGuiU78UKfQ8Lq9V3hHs3xm0fIjn6Hzhsp7zI6EgCwK7fz/NwVf8hlv1myUos/xAIXqHK9Ne8L3btM9xbRcB/qEATv+k6t7ZqvjxTOqIA0vZK1B7muE4VZamgwigM4JluhnHPPkp5mpbLBaeH8w639w+hgtP5AWwKccCUm++cKy09+95zw7COBNty/XW5LMONrDwHNLS6h2Jm23eKbyhJYmECglSPpRPhdu3V//b6hnlWI5fNQuOR7RWvMgQeUwllwfnhActyUS9+Zt1jtZgw6DjH4gCRgbSko1sbBwliv3p+vmJGFI5TaTfJOQ+g76nYV75FByFDJzX2Hu170sKjRxzhyyz8CNLFhYHw8NuqsHeBnu/NUmrkh5+mCeJiy1xH6cYJbJpUn0evV+0CHQ5cSMgRHSMLDWO+RP8LRbU9q/d6xB7ydekTG894HfCZdu90p1fUX0ijp1ABgy0c/egpM/TpGyVME/cK8q7x1edkVKIHXYWOt8TO1SPcfgWn4+zlJ4ar+u4xrqbde8Mv6ah+Px6BhUd12Kcd7pURXmNZEg5nW2M/L0W6UNtx/GgQ8Z3E9eF4ozc4mq9v19DRw/WdX1d+mJzdwdz3tJWVyAcVw+nIvM6/mux2w4zD5TGah0CYVNukNJyQKfD0PWGBFEQofgJQzxVUCh7fVjMkK+ClgWaLxmSDSurKGHcoU0i1TEICEMfzgS/4BcC5k0ep6xwGyz5Q2rWjtAlzs72yIXanItb03FcQPiXy0pWuX7RPA4ASXhO2/GmF9r9ZcYUN4OctYa4aHQdAKLgFwErATCMu1PIGXdfr3XG13Qxus4nFcFMoPZjx5fW6yACFAvlDUH7TlCSDAaXwQFvJV6/7BSjVePR+plBqb6TJ91SG91nrFLwC4sqTjuClP4Y1wZ3ji9s45V5yMSrwWqZ08DsryLMI5WgF9+VIViLp5R9ZrW5scXXn3fdUFlWGEO55LL1uDPe7sj/tkPhqO49Z85YDcXaoHILRLPy6G7LrqxUgHj3hg8YxmrMIBMmQ2dMd/duiVWc4+hX34FfDuG6o459+jg10sn8mwag7AQ2tCWvax4hlhETTO376WAql90qlAiZLQeE0tgE5ESEyLxnfWiMkuy6mQDx7i/KvpjTvziNdec4fOFN1Tp0PkitiWQC0JpZq0ZTrO+OrXKKvjtNp3DWHu27Pn3ygXImPyZ2yPpjmikbYuXuQ38u9/OeXuwL9Xu7lP7y40DTRTXEnCESndUJIYWWnQBqirhs96mnMknPE2L4glOIl+FElNpiVkCdTpHuuS7JQ20543iJIRk+71Car9zdYQAw8m1B3RcH/ouDvtYCkW97WWmCB2EDgEK6TKR3dk4khODPj/7IKgZ6bpb1Ewd+K4FkKChogyvythK7otb7t856/K+xJg/ou5fm3BLFXwsf9szRcvdn08WsBS11wTb0S6ayDC0iKWXs6We+cgJjyo0YY1c5IAgRhU3DYOyurB2K1GLAEzYNVTcncBBBmzQUuxUL5VoMBDX1ZoN/XbdNQ6QYZgOWsFQEsN6NaI7Na0xJhshySW9lQS8FyuWgbpWfPhIiFrq6W448As/hlU0adSo1w66eT5jNf1wXbumFdV7TWQgDPvEFErYrP8xnnacbjwwMeHtXb5zTPOJ1m9a6VHoBRw1Spct4ZsAYN98y2oaaqIdjJ6r9Y3uXa3XATLEgXhEpaI3FPcAZDLeGXprnOGzQnbOMNzBsQYWwlFC9AsVyxel0cT9hSeA5bojCYD+V5hIG3d5xVy9EoxIYRgjzpz7g6Hul+9ho+3gSxA965/+3ylvCpC4s/Sfa6EjwK8FoIFd7Xr2ABpudnm3edl2Y5z0UsCsI0wRU6ACzEMqFZdIOtraHQGT34dXHLs0644u9qx4SGJWZmgCZcXt9wfjj3GZC+g11RdBO353PGcMQ0TZpXDsCyrsAGLMsKIhis57nfzTv1c66XBgihbeoFOs3VFF3Qg8pKrQXbtoFbQ50mNDZlJAuoYozZmYRzMWNk8ytu1MGY3eN+p1gvhsvEDEF62G2CC2Mub2+otY6KWGZsGytOqTWUsDbLcM8xn09Xeg+hNEtJRgxqoiQakmMI9Zvn0EPS+3zndSVI4JG2bYAIapnsrK4G003DUBYKxSKoC7TUmK8rGyczEpA0l4pwGNvfGfVZJUae+/z/s/et3ZHbupYbpFR22+7uZGb+/++bNWvdk8SPtl0SgfmAB0GVynZ3Jzn33BSzOq5SSRQfIAlg4yG3Nx3EefyGq1++IAA0EjOssjZXsnDnovuxFCz3j6ifb6zNtg64YJVV92tL2bJarut7blhbMw9jYC+Eu85B/62fKaNybQCVk4Jmb710L5qioJRUq7uDYlw56s31BU10AkkVp/CpPifexqwwsnQ47Epar8PBtNG5J0K67y5V6vRKYWBJAw8VOc2DVZCRyUpuZvq7rsgxKoX+f8wRT6gOxECNSfxdzmeoN1iBEHeatfpYZBi/xk3DeSZ61dDtDR5tRdeNeygZn+HrCOP+6Gs+Wi/e1819yHPa03mIQ7CbRI3hOZYWeEl7xjn+75xy8RzNnyvnlMmy/STjjx182LxDZNNoHSO/b8iBHDJPWod+o3n2+bBMAJqNostUmVMmY0ICZKGxGURk6WwsNHtROce/T1Qw1QnVDKFezUAKsPCrxqeVUhQELYRDIRxu7oJO+YVRD9dgEbRva+wv2Rgx2pfOdYGSBR8loqmEJx2z9rsJRD7Z/HYPXQIpkMOi3uUEALcgeUo80w0g37SNw8z2Xa/Lfzd9XeepFIBwB8E3gMKcAM/Oo2+I7PkMfW5LBkTSdJ6Ub/b3E2s+9R/j7NJ7oU1mi+B0rr7T9ecjpnN+ND7C76sm6ziY8bIuEGi0qepzbfRALmsBAF5BuDJ+F5buzCNuWMj3xEZ5fCK/4IDHyVqO801LN7IQ8D3AeAgFRflyB/6j73H4ks+eUQYUeoE0M/ZQYUjPNwEwVb3z5Qh8uoo+Emy8nfdcYZrQI+j2ADxn2UaG/jkfPtv3o/2QPTsB4MjJ2BPdk/LfWny/+lmiRT+/83577izIvAxBDSCnWnvqLuRzRHemLwAeSn/Oa38UAVPBFxOCHqwz7lxwp2SKR9sK7nq1vT0CPOWY8G/2s6THR6PNbS/jU/q5EiHz4itb7mwbk+JGr6Aw1NsD2Ivx7CEHO8Bni9Hl2TvW6Cm/keDBno4sRaXGrgHoM+H9XKumdYh6K7IJsRifxAMjh3i3r0sJGeCUT42u7S4EpwPau3zyzEf4kjyK8zSj2ZokwGTWTbwa6l7onlM+jIlt3bsBsXe5mGboeDxGnzvQ7AaSwFSNJ3A51MDupY25z2Os3unnYdb0X8ICcDNHDwRNOM9fbZ0yq2zofBBsnooIVjsDCjxsuU6SiGDlFqmp8kl9WsjGlSINnMuXKzejb11LUy1Y2mIjtCnO6wy0k3ir7RgFWyjGn3s16Yw40+Kx5X3tZV44P73rKZ7u31wexai8/2zqGYzEcLpuLuVSLuW/Z7kA6JdyKf/TCwE5R14IwRLwkV7P3yn9ycpzqy9f8AhS50ooB0XCQnxbV4SK9pCbFiIJSbmYy0l+Ghh7J+oJHvmpLSTuKsAC4CgF/7cQKqunroKbBMGkQAHMY5DUyzByV5sQ9LUx1tZQ1gUuyzRRYa9yQSFGQ8FKptAgwhcZvcl/K/uDtWX13rJo9xxf50K8+ZhsWfNzdW55w58OK+SaoZMWIOY5iy9sYb8HUGf79+QdEkoQt5427QgApWUmQhEGe7Yrs9ZmCArr/KKquKjzTRBROFIBu6V3x8JQMSkwWYggrIrPaox0qzNwqKDWQMsyDGzQ8bV6gChdmYFGqQbIMLg1VTBMCp5DNPQit4ZlWbAuC9bWsK4Nx+OrKuhZvVC/3HzG7fU1DldXuP50rR7fdVJlbTUBjnVhU+lelmCBFAnlk4cnVmOEChbGGuCaKqvEkHIHzLswZDlsBQA0pL1ww7oyeLXQxpb3VVYNVd8WBSg9pBcBQCHFMQUAl1jfIZXCLKap6HgRWe6xVbFRyy+roE7fQ1gcPLfQpsKxJ20NiPSetP84TUvfc1Tc/Hn1WI+0cKoI9rDuHazpa+eKJTwQWAxIf2DQZ0J7EOBLtby7CpxHRADvp0iAwGFx7opzwBTl3hIbwwcB3RHE6gojhRSuHHBhsKsB9nY+77d7yopwKIbPlVqVPqdpwsvzC9Z1NQUB+thlXSs8HUefJ88Pq6ENm4ZC9EcTwMSrGkvpdVP9N10j6uWnlv45//HQTwcErc62NrT1FYCGjvf7yeiXiilukIBr29zcUKCtCtI6WA6oYqK1Bl51t2ukYcoLlTCQ8Jzm6kBdgtTaukJa6+dqnJ/mi1k0v7sCpWUIw+1tx0C6fZ0AFtHG+iEGWEee4fCcL5HaJa/C7RhgM8Ldq7cD6roub8BP3wAi1Nsb0N1NV4TBwUknfNLIMdzMmAsQNODmCo0fQe0GTDoWPZy3KdNYz5rWGAvamAPdDBWyEU8umbfJymgbIWxLB+ZGENw94olYaccsZwIHDEVusTDNBaX29DmSzmsAQYOu6FXFLUIZ2+uzubF7alFjrLyf+llxogDLdWRlk/0vdg1S48Zxi7W9ZHwU228xVlnBnda28n6ewzI6h5kKJEUgIOtLQYGDkczFDLbU6/8UMFYvME25YiGWs1FX0EZ+rp9/Gp57qNA7MN497LWb25MiMT+zUeHloQKSgv/kjjPKvb2+f0QP2NviHtB+rp7W+dbT77epr7HgFWH7QFKMRyF0bb+fI/ZMhQWlSorXHPqzbunNXq8eYYSK0tPqVP3sa7KWgkOZFJhs5kXIjMka3KyOaZpQasFkIMw8q0FWe1Y+URqB24rWGtbG6AFVyORB2x+Mno0lhLwAVJEMBxlNGlbn2boJYpwPzgOxPGGVZs8Bln03iQJPmRWw8s2+3oz73Zm5z3tI5hHKLmfxneWUXM6W5w/c870v/7Hqds4IZ8iR+RHbV5wYg951riLCFgDBK/B8AF37qvQZlpPXdd2A71u2Lyce4KSlmSe7Hy8IAL4XCJ6sPkDu00qnWwBPFgnMwrqXzT7ltMOSDJcTyRH6txUANP+aYALWV+uTGRDK2DaQhm7fli0I8neUH3mf7WhafpR+SWVCraLzNv59fJ/ui6XY/gcN7zzVCiFLUWRnhW+5RBpJ7VciPNQSvIQbXRA1zKQUOVlnqgBf0dtQbE8fVC3GPxI5QDqWPNf+G5lhZ+z1b5w3mR+LvpYKP0pVtjeANiLBVdSpmmdw9/yNNpDEmmJmrMsa/EcGG7uBnq3houdCQVHZxBohAJp4qjk14JNSUEQjMXk7agGoaT9WG7pS+m7g8zEMrf2V1D6/97zn/l9XtkeNR9IKeQUIeVvl+c6LR0S86ItW5CHT/Sz3ufG0YWGKt5EDFYynoPPt+P1I7wgUieych3ZeFlnfK5L0pZRbGRNXnPeSbjjJ4hEBe8/OFafYutEtEDQtjKqOGAV1NyrgXsl6CgDJ4GGf6xOTM1SG9FH6vhI8qAh24P2BJ87379b1HeR+Ac0v5VL+88oFQL+US/kHlqQP6iXkbkKOMege5vnZuN8uDN7nG+Aif9XqE1ARYjyDpCTg3JphCp4tQzQwuv4OAUApnBppvQzgXy5ns4Zvl0IoYHxtgj9QACwgruBi4B8RiF0oYZSpoKAYGCiaiwvKqGIypRo0ZyGvQDEV1Ff2vK3a+s/Gs/5sPvO/KpQ7pbbale+rIE+00cX4g9e6VeFuf48GAXB8T4LR7w+6JwHgYLoq/E1pDxfMe5h3oCvRhRlNGDSTGXFMqFOBsFrJKnicwFfSXJNsz3tEBYbRlYWnbM3eHUpYNepYW8OyLpjnA66uDqh1VsGVKDxANWcyRbi3HOq2em5pB1DKtXklFVwfrnBz/QnXV1c4zDPmw2zCsHobUzFFWQAXOjbqlS+QxpBCaDC3ypI8CuFCnwKcHLnnKW0Z/U5BN2JhVrCfW8O6LljbgtZWtLaqIUBb0VwR62kjfFybC+LmydlSDjPLHctwxYGJ66GEdxC4C8F5/wghMvqWhV7p7wlac1CoU6y4ALuh4wFATmDC6e/fpwhzg5lPqVk6h3rhm/1O8gh6AEhuNQ86E6QI1nUx4FejMIQniY0n4N6+ptQioFZC/WXG8tvxRCo8toYrIkgAsyagcx///e7Z+qlVvbBtaXZvT8T4DF4AqdRpwvPzCwii3u6frjuIrp0aPo95F/XH56fnk2Z5+PZqAGNrp14XCrw5TTGK1JM2Dq9Pv82HWT2yi3ouHK4OAWaOwEv6bABlpPiEoIdrtzEXimgA66qROIRZz7QygUqJlBSxF4q+pU4VBDNASZ7GEeWiiHq9s4DIvL6dQHK/Q0MrMYYa8r72dcisIdHFc+1hXJ+hsOzhAF3pTWmNMkvMEVEFfgFef7/XPe/u1sLh3+o9khQw0pWdsYcV3WOmST3kGzfgSVA+FxBu1FjkMYHCfWIjVHsRwZUA3yL3uc5TBs9Hb+K+B+QP2z1iJD3ptGFh24kAjqg51HPY2z2A7/tigG/RUO/ttN5+wcP1K12JGxmRK6ATaJhoVIAALQqzegFKDgq82bjsWo6WMFwjveYnd98r3ft0o9By/tNJuPSUA13BTVG384mmCovaWOx8cfpEV96pUZUbCfh5ZCEupa91NUjlITy/eyjpeYO0n44ADBlDq/Q6zk1XVqc1Z2ff3phsRv3kypugwO6zO/Tyw8VoeHgjzrz1jXa8c7sMH/IeLcOz8ZHQZ1yUroSAVyD4pmgu9Q9h20AY1q/TlvOEyo9ioDkYzYE6b8EQTDCcz18DYC4FlQjT1U2PbgIAB6gxh4VIx0E8CnvQR6az9tL0vWIK9iI995SY8txkHrFQP8479X5+A+MGghu432Me6mHIKQ/3DRRAv4mL3SDHx/6bPZPutfEUAM8UB+L4d1NO6HVPzJHzz//ZJb9KOnsf5azR8Ek92TPbx1qS/6j2fHYg2c/2ACNj994MhWhEdwboJtHXSatkaG/er4Yuba61e4bg8aQ/WsvTyXTGPiQKrLuRdORyD7oS0OEaOL6mjTIZdFlbor4JkAUAE2gC6qcbLIvmUpeWowIIPMlP772fxZrip4DwYp6VvdspL/VJb09G6d1yjk7euz+Jvn9KyTzKOeyHQGmvK+MJa1ExCnr6huDHSsE3B3LJIjKJnvd3ZrDq+qYv1q0HQ8o1jRXpdSI8UKJb2ezDw74/nr819iECUN5ch9sp0CgjiCgitagXLoiCzy/FItDVZERIHZyG9PPBeS01MqZOdWaAGjypCO5pk4DBz6ZdOrGxzPMXgLKH9hY4EL5Z0NgS1C5P8GHZdtzvTmqS4baP/BBXD9Ok815q0JEb1Ts4HHyb12p6j/BIN3rMsggAsDSTiUyOEOPEbFCnqoY+HcDW8SXRnYXI5CP71bHlc/v/1TzDZYpqThe1INJMgpRGqvV1aS2MIgDSyHLQNIaNGa0Jau3Gra6aFTMAbpuoU/uFcJimiCLZvfjJjDQIs8nlr607pOwVj5gH2N6Z2qUX3ZjVzoSBFzs1Yn1r2xv57b5Gzu6pMSfv0/TfbUx1KZdyKX9/uQDol3Ip/8Syq0BwDxAXE9PfLRdC22ff/n3roe7WmFkk1cCIG0+jpKQ/96rTYoKBfWvuZQaAiNGkoLCCha9C+AzBvailbgFpClGofSeLem1NrOA+s9njm9SnhtgVvwrAKGiymtUy8Jl7SCEA+IWBduGrfqJ8fPAai82NPkdJCHYlIouHZif1PCya57jUKYDq4/EVlTSCAYCueIIK15KUMYIerpzXhlVMJ2o5bpd1wfF4wLIcMM8HHI8HzLMB6EWt0F2ZVosqEjzEe9bvachjzQM8TwiB6Opwhev5CleHA6ZpRp0rIPqbhywMY/TSlRUOjHietBio1kPZIt7fc4UF+BADm8bDUHAPWauesZrXvf9T8JwtHUKqRlW9CXwWa5vqmLnnlIUB6BYK17eqUEREW9J1++55Tv2evq/0euP5pIDroLsM9yPVlf9ic9f4e46g4Aq/Dr6ds0x2enASP82w3XdBvmfgc9G7SOdQRBXztUwxf/6qUkt4gwNusEK4+vUKx9+X3o9HAd0Bx3XFVeRW63NFpeL15QXX19emaGcA/T4vDqLvKWBGr/ydDtqfIYR7Ukhr0zcdxGlV03yeFXbv82maYj9fjqoImOcIrpRtAAAgAElEQVTZPEkZjmXLjoV9KL4SSJoF8a0ayI05dK+yJCGRxiLrxfR8CrDTuksWYl4YpqzxkHpaH0WY4a78Aey5OKTUkKc1BrjBVmW8T/fVbmgBvyJiqS8o2shuACMd8CDqIQMjJYMv4BgaVyj2cSIAUymWl9zeaw0IAwyjx1rUNzEUWKmdrkpV5+2KMAaKuezz0x7ybjG0bADLn5GiXQSQivQ50aCMH/aA8zc9E4yv8hMog+jRVu+v9PMJYHBTo4E8dsNYWrt1xYqFHdd0O4UAWMhplAKxcyUAdBt/sbMFpqzMPFma3s2xLqeXol1nlLTbkm4JujY69JyXKDT225TV8LmKvESb1qQIAqe7idPBpi2xl6fLMv79qbIzht/DK/kTSE/9Gc3KxdXHOz49Oy35q5jksZdyQoz7t/tWEHMG9L1252HZTG7apcLAY4jeAGjIdKjnJFskLOVPBevQEARA40i+GO/DvveKgF/UoIOnvrfszbHwiymjr+M+FgWtGG7wYb/4HpafR6Z+D3DeL56no5v0+dvmOwDzQB4lvu09b77g+8qfTfDf8dq/4tVb/iK/q+7eD/ipKBAQvwC4BgTgJwHdvsWtvHFO7YHpAJDA84/0/9w9sl1+RODjS4TzJwjgOYrTIg6aPTbzvl8hrYBJozsclyOkVsBC4x+dCTH67/oLZObnw/35jy7SQTLnbbxsjT6VRTDw3I3t7Bk3hgyjNgP6NGpSB8kJlsYnDWyB6VacB7Q5eLJ97nY7NyL9/d6Gd5RJvYqPQGYjH6W8L42GC4SIZliKpW8r3Yi5v1NXarzV8iSEvG5RoVz/8Gb7afy+d/8gtxnfCuPVOYWN11Y5j7r7tjda8u9RfBHBUm7VSGXCOed2Mg7IPchj1WUsjjrjPu4yl4+Op2twAwiX8eFnup3bGs2oBb8NINJWniuZ/42ojbITkVO4vyv6knRXjeNFrTHqZBEQLJbLEHXv7RG2/28MtNIYeRqyj3jc7+HO3fElGetu/oLo7LjtLfN4zwXovpRLuZQfLBcA/VIu5R9RPs7EOmhBZxh0F7JBbg0onUvJYMUgPJwK86ZfR7h3ABEadlBOypjD0bRI9pokvBF1idoY4245q+CbAgeMOyGQFPxeGUUKfmmCe/PUVAWr2UavWm8rFbUW/D8LhfvFBYpSIxwYWUjOKoJHEK6l52f+QoAUwmQW1L8C+C0UY9T7iJFJPlfe0/392eXPf98JS7v/vo4yACAwBeyhv7vlaNKGCoDFQs4ezGK3cesKfvMiJxSsjU1o0fyOtVbURoCB1PM8q7WvQZTq4ScoJIAwmDyDqgr0TUQ970jbruGwG1gaWpvQDESe5wXLcsQ0KYBeSjFvSgOCShn+VQfSa+3CVp0w1YIyTZhKwfXhGnOtOMxXGiKuTqrAIEJFRRM2YUbDifmQz9OE1cFpE9w95BZiaLtoT+R0nVSxvgZiAgWtNSyrety3ZcG6rFiXBcfliNfjq+ZyXxa0ZUVbNY+8v488p6ErhJv9tdC3gHlFWV5zgbaJPW+zqHA7eP/5Xxeao6nZS8H7KfGb99tBsvy77jOUtr3xuQyGA8nLPX5PuRgT4Uv/uFt8aw1HS/t+K4InUk90EcE1nkAAZrmLfMgNAMsaYE+pFaVoDA1VmAimSUPCrusaUQcAoHxWIxN57A0VEbwuC+aox9ePhg5vFlFhPEr8eTVeOTE2kK6Q8vB0VApkBUCCdVXaEhZcf7qKtAQiSbGnD2+0Pa4s2cxvKEu6omRdxzk7Lma9P0/DvDZhtEU9THwNBwCelKpUKo7LEaVU89IlzAfzeB5yoVPPfe60kY4K/+CqC1eOOFGIaLhI93ZpazOFp4bwr9XWaYQ3dXBPQfrIi4iu1GEWtKVhMk91No+aASsibwbFGPt+USYDU2Gh4O19GinEgHVxniLlQM9HJCxPH3nY7e4V0kxpNX/9rG1OSlsQYbm/BwBMd3daXylAUe8g9e6Hgf76skIEfFZPOVAHhjKduqJsDNNu+4vtPVlpl3Od+7hv69wF2LcXTKHkPJpSgu4ADPPeN+90wI0mNJwnt14HcVe8DQpf2FzamLCoEYmY0SEToYpAagWxprqJkNYODLqCnMwIy/PdxLltXQqNoY/GRpnMTkAjf0A7n3K9/lOMBZKHWTHlJqknmHZV11jMqY33lQhe/TzC6RnA7p0L3w8SDYh7lHVDCgv42dfs8P3tsj2z9j6HB5M39mxdH7hu8xefv6MdXqrR3vpW2E4Z3yu+l/1EOXlbor14x+796TrBjI9s76F+3vq+Junz6fvsN/8UNKe8p3sXxhsZYNLUNgyNHrImRkDzr1uFNANSlF8jQnsxA7TZ0k8cDExnM16C78e2d7woLRJdj3uYqOGw0ytbXvNO0wieDEbjwK2N5w0gD/sT0Jd5fNeBuRnn3ukk7tvO0+Pm99P3pOG393YC+7Bx0pny/U/8eN1qiGbywHc+vTbd9w9TjchXAjXM1X0qzOcA+DDrOUyQZARodPyYUhwIgT77l80EbMaU753yHvf7uPn83r7Uo5Kgb+IAxHPA12p7H+I+T7uTWyovGk2JyQyI10WNiO0dsq5hlMqxV9uhCF2/YvwSgXBs6y5QI4JTkH93JN4u50n1r6TI88X3gb2SeYktUEVESabXe4sbcxtw7objGghDgCbG1QgeIAOfIlCw/LOoYcjvJoc+0chN3Jnn6uN2kowZ9fDeabdG/hC8w2ajH78KCtRoXQoZL1YAM3wlQL2Grb9FPTYgsAhiIgB6uHiGGit6ujg1MGBYGCFIgaZGGtx20ddFPlvEZWSJbvo8DT0QaIQo8UhkZojl/LnPidWzNQrdFpetz+OUm/ef3djjhuHnc3f7ScciqAV4WV57//IDIafphcn2j5VXFHT9ywieU0S8a8aDM48cRU3GICovqVGuG8ZV1+uYrMVi4f2NfosZqLqhnUe5GjziQZimGfNUsbJgWZcwrlhsP4xIUVYmiyLWbI7nasB5hKNX4lhCHn17fynwFH/q6S7ceWgWQSUdz5d3PM9PonGlt4u4o0taoQOfT7vgfDeI3qem7N3uctQFT7+US7mUj5YLgH4pl/IPLj2sqQscXdkYIDpU2ZJ5lM5sberaZab3RMt4aKOcgwlYtJF4TUiI3Nlvczp+h9vNsoilOdV3NRE8kqA0AlPDf4HwlYFHZ6QsB62wCjS1FtQ2oUxqPQwBxPKJUimoILTCeADjmglfG+G/iuAaI1MYYySas+uPC8P2lxQfcrfS3SrmPTifMvoEYlYgp/V86mT5KY3NxtoWZeSNYSdo2F4GUBwsYNJ8wgbucCGsrSlwPq1YpxV1WTDPE47HqYdwLxT5jAvI3q3h16eqedI0b21FKZrzu9aCaZ7w6foTrg7XICLMpeJwmDWUs+WegjCEkLzcJQQzVwLXWpLCNIdwRgclCaE13qjJIIIQCt3TtHnI9uOC5XjEsixYjgqgH1+PWJYj2qp5OqUxpHZfe9Hk5LBGqQKgmWI3A1WeW9b64creDGZla+psiZ29RO1H63W+F6F82APPfZzyGt/Wt71+8nvsbbbTSlYk9HZui/mUn+yudwJVNEXrXE8kESJN9UsrCmvuaRTNF+mepF5qLTi+LhASNNnzc9fCLDjKiqvJFD0wUNhzhdNk/ezPhMHQRxTZqU3rooqGTzefNPy7zc7x9YhPnz4FUKGh8Up69vQ9h6tDeJifFh05z/fYuGGqU+QxFBE8f3sBSL3TIQrsT1M1AFxz2GZPw2me0VbLNW7NWtsayigFNMWUKXpWTHVk0wOMS2d0v277kGQQ3aETnRdf3yQYIlx4g7Re7lEISgG5Is1zjLMp+0rptGuaMjZjpTx32cAkR15w4Jz1R4hAjZPSbIVHdK8QHlK7kEZMIBu/HJIWhPDucYMEV15WUxx5fng3zOuKGt03iJ4Hoxfvpl0AgFButTAG6KAppId4PxfCfVPdzpdxP8ha+RyavYd0H6MKBJhexvcTdeWr58t0YyA3ihTbexvbHi2mkHPP/qmCRD3fYecD2ZwDsLQmEsrwHBbbHxE/hIY9D32voF5fvrT9dPqt7zFZAa7hOEsozkCmiEZPIaJniIBJg0c/b+bgdM8af9NjhnfuS9s+OjC5V86BFLv3n5zJf03Z8vxx/Qwtq13Tj7RMkNSlm89/X9m24r3r23vGz7omC3XQCF6H+J6jiuciI21UIMDUOowJYl9xnpQttK8bFm55F34ZeWE/HwSIOvz86DxU3xPD4Cp4KUm1fS8hPgG43Xx/uzwD+ATgeW/wZfzwUXr9WxbPB8opzZx+/lA9RiuRRsmus2gO7znVSQZ4+Hx2ELEbjik3c9OB9gcCff7oXO+vkpP+xTnwxn1RVd/PIRnc35wN3C8Mc07ONXdeQ6SHyG7p/gABU0syYFPJUyy8oef4H1TUIOW0n5TmJEApymdwmhvj1YrxYLV22dY90ZkZDawRbhIYTOjgmIZqB+5J5R6fgTwTyj6YV3C61htOzogMcobfF7S5eUT/+h5O1m99ggoNACgJAS7jl/E9zm/09Wd7fgF05ycEkl4LqBlPzgxQAZluC26cEDyY/s/HwcFzp2YHg4M3Eudfle9jschDbkQFSWviY5T+95/Yp0XB4JF/zGWMHOB8ajE50uRx8d+LyQpigKvJMFRG+krfla9MMoXdo/KKjaMHybT1Ukxn5WHR/RxW3WRvb60VL6/H4Qzu+htfgwVuHK/GyZ0b0IhwDp7D5MPzcv62CFQ2OMxT6C0KaQSbSt2b/UdK6KbTYj6ZP3qbu9xK/rvr9lIu5VIu5QfKBUC/lEu5FABdD94Fof6bM3v62X8ePXsGr3WiCFfoHgBnQ2Gl6yHCi1hO6u7FA2jOICRFPtnvkP5+V4pmfY4q+t1TTfC7CR63IngqyoT9i4D/ZR7if5jKQdxCFAVNVHn1iyaSxR8TUFFQIfhfBu5/BeHV2vBVgFV5a7CoUL6aoKNtJvwCBfMf0uBmSOPfX7IYel5oOtva7QN07vIZRdeJ4JMVYz00VqEE5KRa19YsV30DgXComg8rCz0QRmumUC8N3AoazNjCPAyq5Q9euSlgQSnVgAg0XrwKSGgMLhbmrxFqBVgKiAWtCQiMBQ3MQCkNx6OC5R3M6gD6VGe1iraw2p7bvF5fo1LFYbpCLVOE3VbhS/MNo4mCc4UwkbqdBshkijBQwTxVDdNsl9ekzPX8dTk/uLiFurDm2hRV1x6myfIOKwC4LguOxwWvr684Hl+wvC44BpB+xMvrEcdFAfQmrMnYHSwTABb+vYPlYr8lMEo6GM7WP7Yc7ZxBv0Q1ej/3upA9yxwMl+EZ/5rBc7G/qjzxy/13/zMqHk5/H76ndSAiuMl6laEdvi66otwFdhbBJ7v9GwTXArw+PEAEmHALgECfCUDBcjyilYapTRBgzCEOQIRQp6oGCU3ADtnfnvZHiNC4af7ApPxvbcVppIj8jvMi8NYoq3v4rukdfSy/Pb/g06frDnJvXbeG8XOwzN9V4/Ne/nMRyy1uObVdOUACLMtiz1X19C8Fy+sRgOY8jzECDNQueH1+CU22g+el9NylzIxSiinB9bNw2omj4R4+T0zpgwCKvX/zPAUw6ooYpBQlef/Wtc/9nCKgzhNkXbCsCwpzANKyuAFDmi8AEA5F6BCuWLVz4WGue7HRvQH3K3fla2vclR5Qb2Yh3VsjPCG6Zw9b7kLfC5eHB4AIV7/8qnwDck5D3fM9jLz33ZoPfujGNw4YefjHrmiDenTY3t/ca8ciZQxe6BblI4hpM+ZvlQymOc9DxmPt5T1nG0+939dRV8Z5cQOCIgWliNFYytcoGsw5Qrib17qwAgfSNIKFzjeFItlnTAlSQpkbjFkiuFF9mZlOQNw7bcM4xF07Cu9tIQJITIk9mTGJqElJpJWAQY568KDaGjmK84ydTrN3blwzgy8Rtijvsjun55SJbB6fYZgaNC/dawyn50OcArlaSe9Oa2cYwNNR2r+c997Nu/c/90dVbbu75b9bfN8axzB9ppMPWc+692FTi9LlSdtsqAldpy1ACjfsz3evwvdGlGA5cQ1A0fC9tYPoaW2DDbj2c0/8bbqvHnDQ2g66zlzZLbOO9vptUSPIgxmAiK9hawsRcAXIq7OAyeAHMFCG1AuRFUDRvcz3MTbea5MChwUi35BIdfwbA32beCX7HgP2NNISAEWGBB7y+9mMq76dEzgkf3yfXs9N3s1mn3n8k8Sx710K0Vb6WAN0B9Xc0X3L3IwpgJVIlX/c+pxJcEW9Ptu31WDOjBvoVmt6APDZOIl755NOIAvkXvuv21QOnUbsHD5RNvTVJABoqmAqWJajH3C4gq1KUnokZQS0rlfLTe6pnixSkhpOA3R1rWS/tpN0SHmV15L4YyILJe6p2jJdSeoXvru8v2fm8f2R5/+80sFj+74BzvNvAAI0d6O9UgtqUfC8VM/XDDXSsyg4hSTykQMIQwrXmxSoMjuTDUFB9UcCin3X3+MEGMBjUOf7O5smwwjXHLEn9c2jIQUDbu+agl4SHxyDoUaXKqvoIiRrRwCnMZ5khqz2KHPowgqRGvAjqgWwMXLayJfON/igKH8j6tkuloauNXgY98EodHjHPp/jcluhMvy6t5310RCcpefNvefJn4bLvb/efzO89YiXTqubBhG6XBDR16gEL9zSeT3V1MfgVcVSPvYznE3u0XDyPRVeLapvqubxruOk47qyGld3eU5iXIkIy3JUEJ8BkGBtXZNRLL96kxY5yBu3GOUhwpu12iOhyckOvZkPQYD8U9W9tHFDNQ93T7mw8Pd6no93dsPXnYffAc/zc3F6pDXoHufFjcAv5VIu5VK+o1wA9Eu5lEuBgxsDH+FeTq6MTUokwGWO7ok+eMQ5l7bhmM/xKaess3TdydAmb0v/vAWbHSAQexyuTKCuHvgqgj+IcE8wZaoKSkcGJiJ8bsBvxpi6R0aRFSIFjQRrqfgMwhMxPhN5lC4EqG9MmhS1/BUyLxKYUTwR7iH4IkCl7PXVFQWX8l45L3Dl3wWCgrJDJ+zxNE0w1dywqyxqQYsKgpigr5a/hzpjXVa0tiho4wCRCcAaUlw90lmKAcoIpbsIo7Gp6z0cV1J2eRtLVWBLvc8nFCJM8wwIME+ad9m9rF1Qq5OG9AogQ6BheFlMWSwAlT5spG9bmEOgIhDmWrG01ULb97CGCCFaBTFmRltXsGh43wIFU0QEbW1YFgXMX15ecHx5wevxFcfXBeu6Ylk1nHtrzQR0RkuxDmUAnVwRnDzL0wxnr3IHzTPY4UKZf/K6AoxVYtA5sZrSzgevfQued0WsayCDsPKfdFnO/t57RMO9ua97RTaf98DoFwKuB3lYACEF+xwkXSnyoKVmaMhsA0vXdcW6EKSsaG1UjHq1a2OQgexUlGbWZUWd5lAOuYkQcB5Qou1BYTRb66RW988rnh4fcf1JTQWOR/U+f35+DtD73M7g1NBWzwveQ/QB++B5Ltw4Ii24Qi2s9kWwHJfh3cvrUaOUuHJOtWL2HKPWqlEYbCxqrXh91dy07ik9TbO+Q9xXWqm0FDohtMFzsRaQ5Xc/HleUUlGn7dhKnFuAKhS6Z7/fou2EiLW139sB+V5fEwZWthzkZvgGV6d3T4waAKmvM1dIZuO8fp7z47fweqfPt5EXXiAWYaNCgSWtzUEqTyFQxUF9haTIng+DAEikiAgFoe/r7F4cnYZ8zamhjkBoHzz3fTPTmc/VR0qA+PbZ+YUMmrv3uQ607v8RTYUKhFooVX1XYRIUoeDlGOyR/fv+yK1H8SjQiCCOjhJBuJlHVIHbsZkq2cpWCUabrWPL9/T9upczirQPKL5ijGjz3hh7BVH8zAlDhZh7sX3SW9uVot37N503ovxeNvzqyuzTOd+SQDcWcJUy9bp3FMbvkdDPcpIE817bKW/R79sq2D+/nLbkrNoW742KJFLxLjrJ51o0qtVYwlDYnyNKoFGJdD3FDHg0fDqfpHcJOoTzJN1LTATgo4AO3hZV6rPtvRpKtYPdgQo4T+x8kfM9/k7nYxlmKNlD+HYQpfNDIzh7A0VVz4z8uSEPtOMWOTd2H+WdMrJLOz9/P72+9Zr/nNLlbOd1z43Fq83tJ9AQVjsXvZzokPpJb5QUPPJ2KvLvvZadd+x9Tu0ZQqAbr8JEWNbFeHcO/gKJHep8Rz/bo5/sZqfGlzg/Fue0ywU7LaduPpO5gX9KOTHuTyBkN3brZ3o/om3/ooJKJUD0WqoagA8GpADAmrLNDBWE3PsXidg6r/BHGVsnAJ582yPgwTfOxDNs5YzRG3kvymLZGAo4EGfXEx+thvdqzL6BkeHsQLM9Voy393orwSKCWQts3REIYgxacb3VDvlFJDlBhBfPe1+OyNONW52XdYOpbjgpZoTVq3hHLt2M81vl/dP4Z8p4UHRq2ddHxplrBrbdaLVHmhqqJmBNBsVOfWLygBvXR0ovdGNXbwW7MYTzeOjv6u+jgT6SpuSEX0hTBED1i9krXdeSts1T+gES8u4q73NuPm4RsYtV1oPo2PGy/rDnufcxPp9pwEdrp9TgLXi+9/1E93Apl3Ipl7JTLgD6pVzKP6DsCalxzcFx6syfXo8bQpm3X2cXNCQ94h7o8fe9RlIX5FVuTYr5EHC7NSiAwRN923YCLNesKTrJBCAAf5gC6RaER+pM1r3nhxXBL9zzlIvJ4Syal5CgQvRaCEsaGBb1cmMSmHtYKBjurSuf7cJXY1z/IL12b3X8ysBvpTPcu+UdBdJHi1tov1/efuGHm/NRfdiJgGwM8PZ56gIHQBFiHUAo+gjAiqYguAAFBTPU21Qs4oACDx7KkABWr2gSgtQKMeG+UMHV1QHPL0pPDL1nrlfaDhaguWqmT75Wb95pBEgjNYsHwAPD7m0ngNh0nJqTmgCs64JlWdSTqS4qwLWGeZ4xTzOWesRcJ0yzetofDaRus+ZCLFRA1UKDkZgnlAqK6gGvCEj3ZnVvFs8zpYqnCgXTmMjC3xJaE4isEFbPdwXQX/H6+oKX1xccX19xPC5gbmqEsDa1vteJAjfuinoR8+hLALcrfZPaKq/7AK64g12uAB6oSZJnqT2bvbB8r4t90pWQsvk90WIW57ICL9pmwMre735PaiFueVQmChQIv7K95xsBn/L7XfDefP9k73sm4FqARVRBXSxV6eHLV/OgXSBLCVDOc6ArOag2Vr2rGUUK6lxxXJdxEKD0v6BZLjkKRcHL87OFNjd6I4roHqOAG5MEV/SHclQM3E2h5F+en3H96RoA8Pz8jE+fPqUc3jGAMZi+m7S11yHCIKrmfS/Rj964uBzW6uxpBXy8SwFzC8/q5goFf5xbjKUAAAvqpHvK2lrQt4h6EB4Oup8cX1/NwVzg+Nm66voHBI11wLoij6ydhLZyzCeASBGhiiGKdgcti4TiTGDp9KL7AmmMUium6YBvz0+4OlxBIFjXFZOH3yQADBQxbw12P0X3DNc21lDcpMGFejW7EQuzBPAN6/v85TOmUmKcHUz2vdnnrBRCY8Hh69e4ryuLXFlSwgPb74kUEPcMlieAb6DhDx8V6DIPDh+zR/J9wYCopsZAvhdpP8xjkxtks16+qwz72Dh2AbB5GNJQtunfCPGODurG72ZU0FjPxr4ViRpH+f0+N6JrxqYVhKJeJ0XPQuJk1LiZ4nzOb3blk997n+U8Y7HhVU8j1ozKOPFzJuVIFXHAU0O2QwTNJviaJoVYWGNv+FnO8LygSIrqbjihZxcClHdENk4W69cQlQDpTEgHTD6LnR/oZ0se0BPmKG1948h+VEe4hd8+4nn+txQ5+fCxx8SBaB4ej9FJ9DqA6ESxL2UfxZSUYCwWoYjgoYqrRRkyAH0IncoQKsHLZnplmDcXEWYRrPSKIoR6vA4lsoiAXzrQ3XOWs2XB8fVDve2JzfL2a/Qkv+45V5/0XONPyThRDFBJ90eTb9IgfMPe/IxXxpDtfTk7fKU7xTcaCP3sfrCVUr/X89wLkUL5t38jXfu5Amzamn57b9l6/2fj4cNTMgAzMw5E8qI0Pobk/LAQ0hzLE4g0cgA/+EOPJ8+mLSztz2N/8vdt3wiamukZ3bDfI41Ra3aeW+5qAQLQtug0nCp12SHYOhHzTtc38XLE6uvC9lo9MjWc85Z2RoPA1PKf3Ajff/ztG/6ufdh5puzF6mBhvj7cA0TaoKlOapxL1KOnpdDUWeby+aBC+IULfvddl2z/jXtUj6LGbBR0/UjAYxiaOr886hIyiBxtIMS6KclIoPOZPUx79M944Ov5SuWu5Rj1s6hcAOcLBZ3f5g7OqoxuwLpYNDmP+pFykbveyw0MvLlivEhrrXsUp45lD/8wtgc6b8jKt7MZmYQRaRog5wu6XNzPIh+v7Xs3FOSjbP933vyEAxzrCbbyLEO4eUsZrmfusJDLl7D83TKmfEo8lf7pEQ+n4voQ3wFGvtM922FjxzYPVLSOZW2Yaok6fd/OEdeywRqxRlD0yFlizXNZN2QXS6dHNpzk0agAo5FxXW7pvuc+3x/VE+PO0ucaArys7nE+cp25HoLK10lMGc7tkJGBzex1XcF3bXMZFN8By8/T0qVcyqVcyvlyAdAv5VL+AUX2PlNnht7UqDnzfAZgD+YSMtQpLqQkYPzNNrpSFyNjRc4tDlrR1JGd9sfbTJjW+nL79N8DEb6IClkuJHhN/yrOMFJSVgG/g/FL0zCfS9H8Z6Vpo9hBUumAB0AGUmurHkoH0UFk3vDAFyE8UAfP/47ySAqiP/1P4iE39OCjyYApUMS8shGe6V151IUWf7i1VcPaVhM+qeD66hpLU0/0qc44zAcQgGVtELGwiCyadxak3tU8ts/DrvWmdmUEiwrqK1awKDgFJqAIXo9Ho0XGuh5wOKxY1xnrNKPVGWspqPOk9TQVpLkVNLYwu0UVurDP1XJW11/O27gAACAASURBVFpR6oRSVMAptYS3Zyma8iAsjqUBnC3wYYpWQBpjbephvhyPWI5HvL684PX1FcuymOd6i5C3Mc7cOnDpm05S8vlfX/phxU0ErA6a93zDzF3hO5LHDni+A0pIoggMz/R6Oo1lepPh9/BK3Na7sydmi3Pa3PMp7U83Qa/pWYzbovfFW5YB+H6vKIBktIpVvZS5cISTg41xKQXTNMU4H6YZy7qGctLfzAwssqKWguqgLdSDfZp6fanynfa6Ms7V6P2eQgU3dxoK9tvjE16enw1QPh2P/GEr0p/L9bYsi4L8UFr2p7zvIhIRGACosUEBxKIpuGIgK48DLHHDCOGIDDGVkjw9JLRg67KEB/dyXFDrhHVdgQIsxwUiYspHVdz5fB1fjvFeMIXXWJ0muEcWmbatA6lkhi0LikXWyN7STvuldG/5l9cXXF9dY6pz1AcCqBIqCZjJAOfRql/rdxoYFU+Ap84goPZoEcvaDORli9jiSj+YstxzlgNTnaDRAWpXQkH3tFr7Hmsfxj6GstDBdIaIgee2p/h7RRRwjXWeAXNOXptxPRHFBxHMzKINSqag6a4EdNrx//w5wAy9iKJ/oRgk6Lpv+ozeJ+k+DeHufJAIFFQQ854CQCI6Jw7ek6stfX/2KCtd8TWqT0+/J138n1N8IFn5UokBFLgSk4DBw9KteUKZJ2bAKeJQTYRXb9JijoYxHsZR98i98+Pj/bA/FjXg36X7+ylDkP9O5WT8bM4JSX7B6WH7Zp1kwITOU7X0PGWqqGaISaVYLnOyd7GGlc48hb1XzwtNUWNwoSnvBUaOWB3syPuObzdpkTGUh5NPgDwHt2svTLyQwDzQrzSUewDqPW1BPlf3wdcbbAHyYSi3i36owJ/d43L27n+7fJReb0SNEwUdPP87KD1P0+6a/t798NzNZGdb60Dcs735hmjXm1WfS+ckESjyow8t7/d84Pu5exyol9S2oQNwfirL57ZeLXcxR19T7X4Y5ZPU+IN1A/z1UyD8qQNwy+BQ6BX+ScXlwTiMKP3pBpvnokipEaYB6LDUZeHokPYkZ5WsrkqaLu+rMP5IlWZe8IEEd0AYHXXngLSRO4FRb2O3z+l9GXjWAKtLRDXKnufK4/Sw6xrFST2TxSQYWLh25hbGWGrw3cyQ31pKYvy4G4BrqiVgwwNaQ+NMMT6LWUBuzMsjdeYoUyiJjxbjfxN4zvZdXDGGTPsS59LPlO9kh/+0UoxWuw6z96d41EBPj2LAeoRyV2tU9X8ggKiHZHdjDkk6JR+rAMetz2vj0L1k8iuFUhQ1ldWyzkCNXgnNDMk92pbz59aNcDYSAaoZqPj53gF/j/RV1Mj2DIC+Lfa2riMgoLGc3LMtsaueme8/0/P8pI4d8Bxu6LB596VcyqVcynvlAqBfyqX8Q8rWOv9cOWUk5OT3PYWEM2Obmw08J7zF+gzVmSIe4oyn36BSsjOUbh0OqLKnP9fBIbKQrgH+swvDKmh/FsF90bv1ccIXRlwrKPhFgD/Im6DKJeVvG25WQhPNY85kXpXMKM1ySLtXHmQYn4eibfksOp6/suC3TSxI90T/LNlLfJybWx49yH+EB3QP/C9iYc7eLEkb9xeUqP3kNTL+fvJ+/cUz1BaMgJrfzWbJfTQamQ4l6AxQUKBUgNhCr1UVfFcwGh9xZRbbdZ5wd3UF92ycqh6ltQpksnzRJnC5dXMTFZ577t1qua08rHAHGmpxj6WKeao4TAf9XieUQgqk2Thwa3h5fsHhMGOuc+RHm+YJy3GFSMPhcKUCYEEX+kuJUPGAAoR1mlDNU7hOE6bZhEfoeIhqbwFov5nUg4DE8gc2hnpsWg5OVgGPm6CtCpw7WOgKWw07KqEw0OnchKZ7R1BnSCh6GzPWlJeYLUS9UklWfhmwNSgGOqXJ9v5EgNljfPRCk+H398Dzk33UvkcgU1KlbrbEDlUQucIJrkYcc9ULYhXcmnD7SMC1SFxf7v8A4QbzF0sLUETpfRHUqaJCc2ebCyvqVHBdrvDt2zfLeUYx1/Ko76C7YnukKnHmOqnRBgrauqKhYTpMKW/gqeCd1LVn1rp2/Ob2Bt8enwARMxZZ465Sqik9xnes64rW1KJ/PhxiHritAAjzPPdX1Z6CgcS8CSuByqTKMKMvCCz8pNhjXUkHqHFK0p0YzSTwwuIDh5EGBHWeNMcnoPm9pen+1jrIwY2Bqh6NAGFZ1qi3CBmw7ntMCS9sX39khgdigH4GY/vYWVeo4PXlFSKCw+HKDH0EIMG6NkzTBKpmJGDXaapqeONnsym4IWpoQX7uThPaqkYX6hFsuQoJADGuDgXL2jS6C+tvtZrySQTt4Qn111/ie/euUA/PIiMNuYJS937dTwWIsMWtiYYu58cOSDWOHIPueQ70NR3gUoBNek+EfkzK97NARW+gzcv+z2FUYqB5D5gwtil4OU31PYLn0D3W29xYAb/B09kQOKpQPs7e02CAuY01k7fZFLSh+DPlt3vOoLNp2oaRZ/H0Dn0fVhp41wBzwziEJzo5ON777EpMG7q+F/t4AikqQR9NCQWlPc8Aaaxr+67GBj7G/WzpTbRlgZbOBG32yN/4hp73COmT3BXPNgduYzry39aXYf/0c2ccPp2DvOtu9uQM7A6fh5tO3nPKkFL6v51Z+OsLu/FgUhwD1soNPeo80c54eot1Dn3IhjMZEnupek1WM1g0Q00HKV22iWrtfQEGuSGP3nuFg+4lTLogROUdeRXILKCDgF80DGtjAaW8tVo0vKqnxvCdwqesNemK+ASc9PDt6P8gBswkXoOUPoW+6T3bDU5u414dpyf7knOi91Wvdd/gyTihGyOSs7nPN+WG+/iySH8uNUvkFCSncup1/tF3vlXe2+7fK832nfqugNfpWgAzKuvPNF7hRl1+nwc5/wYBdqq/lS1Phu69Prw1lW2HnZbPNN9v/0aC23RW31rEuOdAOZSGZ+gZ5ACO82BiUbsWEcwCNCLldUWwpvdNds3bM0EN4b1fh+qpabRxlUhT6yzqYXnkBUD37tz29/yetk8J7+OQP0tBf25Rb3M/YwFAgt8avDoHENpk7lI1GhUovGKJbMx8f3EaTQIOgfBQgNXD4KTiO92dPfJA407S2z3+czCREhCozd4YfZqMXGwvd+Cte7HqwzfzFYgKvh2fQ2bQ7VL30carps6yd7OIGvWlcE9CBUQNxITCBdQ42sWJByvOR4uHiLc5IbH29faziPFg7sXs9yLOCQfPwyveeSE3Ogl+sI8t0KdIkPaaNwg6bwG9iTsbxnAf7f663dZPJUXZXDf+1MPgF1XErX5eC4aUdx75wE+tqep5zswgM8ZlzqPR6aqJBMjtvHrwCsaXsnD0baqTRTGzJzJfLG6GQWluKEByGNcc7L7ZR2mKBKNPn0+YzsbohUDqJLIzZdtLbqTsBi0kjEWA1Y0NTqsYn+duyLu9fw/AHub1e8Fzl0mo99ONX7Zg+qVcyqVcyveWC4B+KZfyTyiuLdwr7zAQzmQE82KM5dYTvUvIEgohsvd2EN1vPSdIdibdi3uheV3elRMVl4hqQKgrJwne764lUyZWn74nBY7vo3+Ee5OlvgjhkQi/E8zqUxVcYiBdhOVk1nyZpjFm4ch7DvI3Ubw1mPoCPArwmXV8f2HB76UzdO6J/pAUfNvysfDr++VWRs/ze8IGrP9PLRkQdU9e+2aCdRO23FBdMxhCtABiYINkwUoUJMZEmGRCa2x5njVccIXS5FwP4OIAsYVeI/3MTUPdAvoOBbDNkte9vQPoAqap4urqGvM8Wz8YbZUQwL29APD09IS5TLEqKlU0UaDw6upg3nKigp8ANBVM5g0FAPM8Y5pnzPOsQPrhgIM01FpRXeCRMYwclaLgGBcc1xXcWgfghinRd6vwxz2/dIxRz70Wc4DzdO/FhdX+vHuAdo90z7cMIIWhtGeQlAJJEYD01+91fVsGzzHe2fs63NfvOgHO07vPlXivdxhpbIg0n2PqY67P++73X++0jfEEli8KxjBDqoHChA66WsQG28YxzzOW5Rj55gECbgF5ZMhDA91pOGkiwZEXTFPPTy0iOL4cMR8mwMA1LZvZFuwoMWwc0nFG1T0/FK5y5ciyvGKaZwD780BV9+K2rsieJVt0088aEVVghxKhECJYiI+N6JrgZMk/z/MJLcDGLZNSBimOR1XUtrWhTjX67t4P66oe8CU8dwQvz6/RXoBQZo1ckRV+OVQkgDBa6bnM0YE6if/BKbAU3TOPL+obpu8nC63PAJfETlAQrfj5yawHn1FknbsIUqcJwk1BfdcZEiCiOeqnouC8h8dnFlAVQAj18y0aPwDlDuTjktrhexKBYq7IwSTzDmZmrH800K1H0xAwX4HlyeaFIwx7SzSi8y5BV6PXOZ/87jSoczXS/KmxyPkygOhxrXukO13A52kTkj+335VyofyWfKelUSim5SY3NpRR4Yz+WEn9oFIg04RCbt7m/Y6H+14Gq7d/Hfbk7y3k9BfKXp+HPl4BzrsxT0L43ZggT5MqJ/tg+pnQQ1z72e97Dce8Dkpo3ztt3bWdPg788FY37QcD+eoc9/bvUQwK+rhv37/3/eS82tL1h998mlv8ryjZaGO4vvkuQAKxx+v58zC0b3SWiFBRNee57ZUk6JEQ0M/tUroHY6dPP/wtHDsAYk60IJAXAWaCzJqapHuh55Z47qCC4m3+BOAJPcw71AhNzHOx80hG3543Wnoqh84ijTxUHpeBjxu+3G6Pl8Rz2R8a6e2ju4DAPMkH5in9vqkvbkn3/XeKykXjNv9uiXlIhKp0Ne4lH+Gznwi4GfbI7y/nmv6RLsUckXkAQ72Ly9AWvWsVClpeQLFuBp4ECDDdI6U4EE7RzTF9UABTIkM9/9hCp56bPZQ5xe/On1L8p4baOYR7FJfVBN2YlPt5IsEyUNBtnHnUeefIdT6U9N2VABhn0QG3oR/+QwbM3QOdCBFrx58Jo93efoaBqcxYV00N5y0KXjG1t6ChCSkfywxQg6z6u8tzGhmlAEUsGs1mFZOdYzQa6pYEoqN4OqnEryQQPXi5HB3gRKbdGd9hTDvfsx3vf2dRfsDyjqfrnjJlkC9tLyilBvAs5GdiM1kCJ0wCS2if4vfBbC6d4YUK1ramtaS/ubzlekO2/aycGciuXxQz9qAeOcNpPoftT4c4f5DTJriBrC66SXgwTnrz2XMEQG9+xfeC56fVJ7B8A55fAPRLuZRL+ZFyAdAv5VL+CeVneATXPp3IjsEVjtclqfOI3vceOvvapDFMQo9eUnCmC9fuiZ652Q6SuTgkFpOR4YII4Z6g4DUhKbWUYbszgaVAN0vNd65hcYuYV7EAS1JqFVYAfbV2AsBn++3BWjJ48QBYCXiIPF1jTvSxvC3Ab/Ujb5Un6iD6nU3jYxgPvOeNvt+O7Uz/KNm9p6YIRa2c3pH0eift6IImYxXC0/KKAuAwTQA3zFPFVAuakZEKQZJCbWnNy7pgrhNqmZS6TNE4mVftJBUoCoSpAl1bQdU82CfNuSwhDbmXHAFkIRaJUKmi1gmuJW+tqcFG0QCgR27oeQAFz4vmnbyaDhAiTJZf7qlpvmq1mjYL5KVgsfawWAj3ecI8T5inCdPVAYfDQQH0qh7ooUw1sKUIOe5vnuUmqBNhMu/5eZowHWbUdUVtDSIrClmuTva/De53+J5Cb2s44Otc29UU6IKFxIZAAbKREsLTNxTAmXqyIteUG/a1e3g7/Y0ePgEkbECSEbCSzb1vdBaqCL5L61qpd2dc4GCO/v5C21DvgsmebUDsawRgvb8HcIv562QVmTK9MgQ1KRMAYVWCAZpOwBVlzAy+o/BEj76RYDWP71IVTBBirIspDKaKCCFngm1rzUjeVk4oek1F4Fv8eCwMZcqe5DZAHrnB6xaL1uAKEgeR93Iihsc1yMBzMUVVt8z3EOF1KuN5hXitNrsUzIeDej4nILyHTieNCFELXp5fMM1T5M/1mqQqbba1Wcj9Hg1gPkyoFq3Cte/MLehDPeIlQg92RVAO3b6lWVfCEQ5X11jXFeu6hNJRWEPb16lEJIqpVsv1aHTLlrvUvCI8cowf8VSqKa+6kkm9xfXttYgZxWi+bSlGDwJUuoOIYG0PKHKnyiMzDGgWhWKaRpGHW98juLGC58KQxhqWm586uMTdqzx7WAoEN6LA2L1pcXMY5S24/mcobK6F8EJifMzOGej7RVLSDetpe267clQ6+G436nPu4Ve0x+qBO4Zk9+9E6h3YrzOoAZI80OEKOOrPagh4z+9IfX2LhsonffXbJRpkSkHS6C81RfchUHiY5zHpPdHHc05WCECiZ0qBYBFErvPVgXPjhV0hLvbZFaeDgQX5FX3HCXjuR8Q2LOb2tu9h+N4qMg5tB+N33rX5nG/qxmenNAZAjQWRstm81aCfUplum+aEjDeVtSzDST3KPfCzXLk1rw65z86HmOGSMINriockgobWI2KYMjdCR3vudFGjXGoIEDvyoQPK0xCBZjsDns1oVzS/NW14jpB/vLW2D7XUPTe+kch1ZEaDYh6+EBB7O1y+60MlAApulLcIFmeT4zxaYzm0MT6v/4v4OxFS/aNe4O49/kQbGs1tSJcdJL+xqf5R0Dy/FzhPuVuj5Tv5SNSvxE/a93OPuIwiFrvZ4ZQCGowbPrqy/L4nwnBu+Xid7Ec77dmrUzCOg9MSAZHv/hMoQi9dK5Op5wPM41HGOVauSaJd15AIAd9BUf3XbDBW21+H0O1+PoHQzLPyuI4QUd8SZPf6Kem9vY//cJHhz7+h7PA0CTz3f2TnvXvyF1LD6xx0T0pBAaPbUNtZiS6r9Wt6R2oGQOZ5vtGtdFlN6SA46FhMXZgoCVzMQJt+Tb8Ff6X8V3X9k6iHuacUYta92FkJ36NDbUGk9qTbiB727OqGuDbG7PwkC4gYVAApyr+WUiEwvj6nMPPBKCUiUhVbR8P7nI9hjohGLj9sea+Tda4iRj4OzpT379gr7xkFDsf0G2UqBZPpMgBNuZfeMgDYbrCTa5Z+SIVx7Am7TIiod8pDFtNFWLQAG0y9t/h2E1FtNK2e6nc07R7Are/8tVDiKf2qLYDoZ42vnNZD9jy3DRQAcGy2n6b52ePhyHPaGCj/LJuQ7zJ+8FaNEUs2M0W+257eoSqBnwPPe9v7Hn8Bzy/lUi7lZ8sFQP83lu85FDKD8FFmYfv8pVzKbnmPicgcXr+Azh6dCjLJ1TPeoXzjjsC5Q8wDyBQgvOYYdwYo+3MPyiKRHq4UsPClPDC/wfkSDIQVfGYNrQ5YaHeyEOvQ/jQCqpDlEQSOACqzKqGooRLZM+4RSjG2DwA+g/AZwAMEX2QM5w6oJ/qD3f9IwOcmH1Ku/ExxJYZ7nfvrGD/ujf6ekuf950eCOFH2n60//+K5k8e7nQYo6Jk01LdJjOrdWIOuQFqL55wkEMhyANdSVTFaunJKQ7KpMLK6F6lZeKtSvvT8mADKNHVvB7i3u4ZrrmWyEGPWtsZo62oA14pmIb9KrSiVIE3Q1gUQmFethQ61NAKiKJPm5ZyKhvayUPHrat70pWA6HHCYJ8xLBtCLAbMmGBk4NaFgmgpKLQHGkVk9o1bwPGOe1Kt9ndVDXUOcEjwPNLPmQ08qrLTFjKoSB3lco2JBIJAt+cMT3cGKjCadKP6zN+JmLxH/3t/R70yt2krRMj7fL8tQ99CvD6ge93bdE3WEKz5EcCP9ueyd6LQXOhy48vEJIl+ivxShp7cvNQHUog908wRTttyNjRHbX5s0FDGQupTw5l7XBkjD1dWhKy/dat7bzhqtIdqf2vPp0zWen58BAC/fnnF982nI3753viiIpuBqnWrsMWGlDvPOjggGFDnkQOoJ3ZUMad9s/WW1aGQK32pilIwMvS9Opz1HtWBdF9RaFWAXD5GOoV8aFr2YwsZzdgumuec61+2oxXt9H2tNdB8hsvHu/UHaDx3sBLo3kED3l2aGQcKChhWQijpPtg71nY2VsnRc9J9GHHCjAQnloKT0LHmexjWLyDOv7SygKphKRSXC0hj8xCA8gABMX++GfIK16lwWIgulqWkm1tYMOAcEPQ8k0PcRNgCVmQcPdEAhH7E9SZWXgi1wHl1ICud3FYOurz3VOeGTEL6Rw7CbG08MQPpmkD3E+pbWAWDmpBAnhLFDV9r1NZjSiXrl/Zv9VsQU426tI10xBjsrSG+037xSUxSStw/Rjo8XS5YQw5LWuaUTGMfeFyrFe44QzHbQOIA5sJLxpNOJjDek3/Zb2NfVQAWbM2LnQzwfnPBwvNm62n2rlq0sOR5jmWbHv6dtHH/wqd4z9Pohb/PvmvNNO/c0s3mwt0tPNtfjkNVRpu1DHj8fsChUYvvACCwF8CNJoUxALdWO1b4uiYrKPKx1s4xnONveTuKeaRL8p+9DBqOGvOR9ixzTIsANqefng8Szvu+5Fyi7AaKQGSZu+Zs+IoKep13/3Q7zsLvLnREUvnPKowzg+aaSM5fxba9tWzrYfKdhLDeA8LlnoeDzk/1WAPwin/EvPLzTq+8rXTLur89Gndtybqzz9fzcI3VjAA/x/t7zXrIxxNk5JsILNEjCKxGuixqtJ99dVw0AsHQw6diYBANfWlDggZSsM8PrJlHj+DhvkzFwYvsBAFdCeLGz6rs6/j2/v1d26Gr47UP1b86XM6/Y/UW68Rel9Za90YmK5ecumnqMNBR6JU9rQREaHQCkNfAGpO4AuvRzF85bpV5YnzdXhzOzT72943wH4fqqiEqVitOdGsKRsQpae0u5sNmM55owNLMAR2Si/A5JALUb+LvjBzFjhUBEgW+XpdjlZYHx20XTx0Wfu6GB/6NCoFqUv7JzZjjYxcFzl0d69IC8z/URTaO61fdh/+uPlq3ovnvPB+vS1GMFYeBKPUVaMbrwVFfOKGR+nQpFpLyYTeu/Rw4k47MLlThXfcXktVLg574/pOtiqlWNzknP+ULeHr0ve/RbC609iNRoYbAbfSr9PtdRel0fnjYzYRdJ++v5kudkN/Un9bafK38SCXkjoi2RxmD3pX/qWy/lUi7lf2C5AOj/gSXL/pdyKX91+WkrPXKBy77iVMAHRktJoCsA4YIKAM/lF4JCkoM8h1ZXsiam3gQXBxZCYQxVMP7uAoU9c0/KIN+Lhmr/pRQwLHe1ECYUmK+HhvEVFfDuWHOik0WqDftMMhBdPGR8Zwy/JlnvcxqCP6z5/46w6o/GW7rn63nPjK2mqF+XmJweysr10t3K2+vov+e6XPAodOZ3j7e1UWsKN4BU0agW4qNWwSMDCCmw/Wq5k4kmrK1hntR783XRekTM2psZrayY6QCWFUsTVJ4wTxqmeWlHkJiyxgS1WrqHpQoQmqdShFEmNqVC0ZDusGgH88EUq4LWVrS2YmkrSilYl8Uiar9iniawNBzogFJUMath8AgwT2xiwmGe1Pp9ZbUiXi2cNmne59W8ThmCeT1iPRxwWBesx2PkSncvUB1f1lB804x5rpimKcJFE6mRQJmAKup9flgPWOcFbZ20PzYfqlRwz74EUtrknyjwHIwKJYGHE7X8s4n6TurIwJUpZDK1ys5zHUDe1JyVkaF1i//15/2ZoS9dcbVVYZ0722P929876QDFVtTrQvX+7wAGz49ULZb7FQTC/HWCezdrUVYxhwwnkOb9ZvXUoQIUzrlVh5UOZsGKBcSubLAQ45a2oglDWvYCKDH+TDrHoUcwcM2F8utr84g+Lnh9fsV00PYur8eTvk/zbMqEniNUWE4GXiBY11UB0aZGMGVWD30Nt6vtGLw0bDAVoJWBNBwwN62Z5dReB4UhoGur1orleMSyHtNvNc7NQt3IoJYKIoEU94K3ZBKexw8CkHlBiHrccxh5IebTD1YJRZ7NoEV6yTmYm+dQNwC/2lz6OSjsBkwWQtLCxLuHu+dV5CaYDkUB9qTcyOvO2ybCWFiw/rGiflXDHxL1WHr9/R71//wKD+Iy/3oHEaDxI9qDhtC8+9+/oElDJd0zuyrTwXNRgKgJmjzobsISSvcAwpO+6drOkRfL8eE13oju+U9Inug4r68ZSgJ5z5VvGwD/u0qAdMYHSe+bt5XI1yGFN6tAugLY+aviirzQYMO9zVw5KcQowijc32/a29ijSqxn58oiq+cAlAznAfqSzad7KJah79Z1Xm1dAgUlFGhhzEa+b6U5tj178rMGfT8VYTTRfukzHMYpfq+eMRxjxym1UKcJjvtP+udpD2Le+g1briveLclkcHN/UsFmzPdkLPfLPr2d84DnM/X57dfzDIHguKxjzdTv6+fj2dd/uGzZTOTv6QWeI3w89imEC/dCdBr3Svr/DexuDVSzZ6I+v9pfysPGBNQCBecFKAWFATagh0FoOEKkoeAKAGHFKwBBlSuE5zg0Ag9L2KIgTDXF0y7kE9nbUUC3CtZIA8wiGMMgOMDutMppEKlTvaex8ok+S1O085keARnNK743//hfEXZ9uzb2vmf5LP9+J+Nv/vnONpL7AggePkzfSj7no5iM8+t7p/Iiko0f9urFG/O189jT6aU3yxNt1uEbxX9+FTN2Mxp2j/AApIxcDgAghCMEBzjgVHBtjO4KJdliwFetk8oai0bmOtoz1SwzxYwO/f5ChJc8CBvQSdLlsW/jwP00LpOe/1lSjyhOm/LeOUCRDsJlOAe93atWUFBQyQDzogbY1bzOq0sfoQJQwog0Td0q2s5Q58Fs/xnAQ2cyAE2XdypnRb9sL/e0LHGdElAuaqhRd9aX7/uQ7uE7WWib1VL7ABUkwGQgaINGS3o9rhFlZvB8JWtX8egf/dQTgQLaKCA0iKhsLWy5tQVAU75fWGWYsImF8iiZTt1wFM5+9QmA5/zWcyTHh8mGlntcihNRP/uMkeu8YHpqNLk6X86d+1tDjXf3raEnxRxwgApNAVUsUFhEF6AN0GxvYHPd1wAAIABJREFUmKZJx0AyZyMofTVEUa9yHw9BRMJDl2mreYLX2vWZhYDD4Uqjjr28Rn89DaVGDfBUKq7Z6nwrADNYIY0GCDdURciLym/3NbS2ZsbS/m8cyT5fNFwLTcvJ/iHD5TE6xSmveM7zPHjVdwSmc+fZULK8k6v8Wb32pVzKpfyjywVA/3eU7b791hnQ9VK7z35AFtl9xeXo+CeWM1RwYhV4Tjgfmcp+u12Xnm/3RHC0H4aw7Gfv7q11BqzruVTBpJqBsSXuVdxFuVRX4vfI6xUogOrvinq6oPClKcP5RwF+MSBf/zHUkrnX7xamqsAiNOkhTf0dD6QA+hfRNj4Q8AcJPktqm9X5qxB+I3kzB/pZiTwLSN9RtgLKI8mbHgbjKxOjbJoSSYrG7rvTjRd6K8M+d7i6NyujunIbPs5fbQYTECjyPc5wfLZ56G3QljXLI6luOAryCQNSNCTbcV1wgIZvRwV4MTF3XQEWHOZZBSe2UMNO/wID7wlcFNBGqUCtqrwsAlBFgQlL0rAauNTWhoWXaCcRYWVRQJItP7EwEIp3A6KK4Hlp6sVrYN/Euo5YNBQtk4JirTU0C828zgdM0wyLQuap0nT4mDHPh8iZPs8Trq4OmOcZ7n+mYbk1BL2C7ZN5s08otKhe2sIxi/Tc1dQl9oEm47vPlYM/sHB5di0b4uRZt8pC36J19HsyeJ7/jrXpdd9DvH19H8jt9jo76N7Bp23b8rsoUXemVlsZ9qB7ZjoI1u/IK3/cCbf8AsW1G/v9G4AbhOdZW+KBUjz0nRmlVAVN13VBe1lDWRvW75xeYGPRmON4adxCwUaWI7bnKENS6CjQWormS9ccflDPWN/nRMKIY10WA87H/e9wdYXja1dMxD+LVkDpCZGeD5abhMdBW9TQphnQQrWgsEZ5UOAa4R1vW2Cf+7Wp53JEAyUD84qlMPBzVD28K/Uw8ARY3lwxBZgC0U5vnl835pyKeaTreFPqL8DhrU6kBmIgQmstwuhr3nQxj5RR4chNFUcRl1IEjVcAkxpUAJHPz5VSYm0qtZ+HXpYjmyJJIOHqov9T8tY9YllW8IMpwH39p537279+w9XXLzj8+hVCgtYa1vu+Ah/+6zfMteLw5XNolsTCZLpSUgRY/1ixQsNzU6JdDcmp4Ys/2by+UPc4GugKpwaC75X3PDF8rPXmdxRdJ3umna1vKI3ca14fJzuLAIgDdN3rpgsmfT8N1o4EkBL0X0BgAhKCbspgQil9lHQp68bGlEBASnThb/YmZIbJfhRnPxIpuRISxo/oOVjCYwhEEZbaPdbF3lNFeUCGG4f4HKvXYpxD6dhwesl8Z27mybmEzCGd+733PXifN+5NQ6BrObdFWWU4Z3aOV3xXQbkd/9MKzl7P+9detd7WvAdupvrNV+/dv/uORC/bczde78pX/2W7/oy8fK8Hw9Kf6LizpZwC9FwUM65SMiyJ1qHnQdF9JhBCiaNez1Frp4eCV1qV9JdiXrua3b755Ke2+4g4bZHtr57+CncCuRfFtlJagZFit582s7BdANtHP7Bdfkhh/pPlZO0AMZKAJODRJBnn7TGuRUIPz77fVSWYW/lYGPcoCTw69xhLn30dsvNxH7Yjut2DTiWx8fvWC91/f6S+Red3nbT5I8feST1jq4+Jzo5Qz/X/z96bNsaN42qjD0iV19hJz7n3///CMx1vSewSifcDVkoqu5w4Pd1nCjNpV6koiuIK4MECUkOexUZAgIC1DLV2kTHsYFSmEBeRZi8DFz4Dor737knvodfqtrM1d8oxbZMPdsbH56UHcZZAaLg7HXLaCA89rU8sbPsYoRaJxDSVikmjThEjUq9JXHW4QZLl9/DGjsBuPsNWJ5/L+HaqxbtEsVjJQLTT8pkzRbSODHQveTPjESJynT5LheTeu6c06k0jWeX25Pop9jWbq3aOMADqkhO9iruypxjiOBBAKOiaOMdlsMTPUQYR06J0D39OvclpdZGOkfWn9bEzWOwNzp7q0Vu/f78+loR7Ex1D90gB8puNc045wIDmgpcIYLVKrrrMtzAi4oqd3UWNMTv34dzO5z2I3KCkccpXrnJcAO4hQ4FIZdJRY+UGKCBP4xXXdW6rV7obTpPMmX1vbnx5zEgd43WeaQSthe+wWTMYVyx0LaYHWDpVLWkE6O1m+Lvb3hI/xdpbtRXvl9lOdKIT/ffSCUD/D9EmY4stQWH93e5ZCmuZfXxLeXCi/zLa5At4e2LwOOuITUHP+n8RSMz7l5PUZjLZoChQDjKYFmNs4nnEjE6LMJQqpJmnECACiilDWZWeznAqkwkgHBnUi8M8mC2slnxl02EkQUOBCGXC7ot4gH9hlesctBNm9U9lyf4A8BUShp0A7GsInHcE/NFu8WeRrOY5NPyt1vtAwI3esWOgEdBL9JE0Nw/iekAH5k/B+7LBKG5RrvqWgYcSVqoP+rhNpnNpXTq0JO9OFSaMy6zpgxcOpTze7AKteTHquxP8istvOZYzLXrFpe2GrnO1OENNafor4Atg32Z0Znw6P8fz3FAJmj9VlJoiNAOEjj0aSivo007yrJLkT6dKaG0vocnnEKzsGeZth24tEcUBgbCbxDu2YQcqBVOfBGAshN6aCGEoKFPVENFict6wR++iHCUqYtHu4dEBE30KVxQi7MFAKZh92UhfFYbm/31Bn2fsi+a/1txwvVsOL0Lbz5hKxXMtKFPB1eUlzs7PXVi358/zjP08o/eOUiQUd60VdS5opUi+6zRT8t6R/4FzWHYBuBrM4KFjnhvE5z6tlTQ/A3jI81ee2UTijSdvLDUX/BTg9/C4HCGv816yBORDpbOm5epxj2BXZKWqmHGXmtmZcb0haK6E0vSs4TP5LNTwyd/RH67RAey+SMQA6NhPmBSAUgOPJrnDL84vxMupd8xdwdOazwltbzpbiGTcWu8onSJ6gYPw8ZIMRu8ELmYoQihcVCMRWG4pBWfn5+DdTjzS93t9FmG/33tedCrF310s+qN/pV2shiQ9AAMGLDQ5UQEqgfcdc+myr3Q1AqniJVKgU4og3s2a65wLgecmcwhAZ8sYLXOqEGF3fi6eLJhU7yANMwMYy91t56J5dY8GHAZSEdzTlVkBQFEUl1Lw8vyMOu1UQaeKHnXlbhqhQ5R8NpEYtUxgSB8Boiya2x7nJF5Hu7pTsKVhPzec7SZoet98TEtYymix1yc2cnIezJqfjwiYvkwgAvrDE6bPBKIbUCGc/XELUi8nUm+is7OC6V83aO0R+wc5Ofa9ofQZrXXdz2R8X+4kNQZdATMeYd76An7p2lflKA8tjnOSmcUj3b3SgSuWdfK9RJktMkVmNh461/PheyQUXvFGq3pWEoMOGRjM5oETQLbfpfvKUJN6STI1XWCmAEv1m3EF6Wdn/qKXGByKcbtCkr2dO0uYS4KMW5dHmaGiKGWtzbpvKD9HVsaBceProjlQPs0V1YB4hfcCUMPcrG/0hJQkzwBEeVep4AeAM4RnckfTyARdjC56R+cmYbm7GKeY53lvYkQH421VuWnAmym52fb5YIp9v9yaM8sz0s8m5HlBccAhj01UEOdrmKJYL9t5a32+RWEgk1sl1IcxG+n7/sVmwlj/4lXjvdbn19Z3ex/jtpYKfW+RT9PxgWzT3L4kBazxSfKc/Eay5s1Ux3AL6nImUOlAD37XlrFnV7VhMiAp1W3nO/EE9CJhfQFUnAME9B8ycvWiAlyA77JWSNeQhKS1HMQ6PzJAovaWAsQXNIXmu70WC+zQHizdhe6JeAJwDcKTvsen6GAYzw6McX4WQ7zaqj6B6MF/+naQW1pW9H7ams3j0oj9jvMMs8kDjxfgczhvob4m9ftn/oR7evTvBpgzBGh++1Vi1i35ufz7VGsY7th+pyH4B97gwFN8SHhd5rXv+R3oiPLL74d2l3P9YZ9AnvE95HPVPb6q/C3TkEHTDldXV3j8egczCvlBwPnzs58TYOBM+/YHdSjuBQJwpS37DjOwtFWONMf1+/DiKc0JYt8Zdg3SPSr1wbJPjvmelxG98X3sXgNFvdHefIl7YUdH7IAC0imfRWknZAtHDVTddyYQdgoUTiBUSP5m618zePb80L1J3u/e0FhPUAoey2ZAyHd2ksb5w9oiSj2T390MrAtUTgb0PYQ5NYO6IQWU1yzyUVFj39Ya5raPtcaMroxOm5vz6MzscnpVucaiebhei+HGmn5m2jUAGgNeZKrW0eeGWgiVKna7Hc52Oz85WPmGCjEQrCB0ljRr5mneWkPvYsQ8t9kN2alA+sVlEwHru4PGxhTGfBhmJQNMrGfC+Otre9xqb9AL2/tC7AHH6rdMTzWpAXbTiEFuVICYB131JV35OgAoZQI3xs731zglQPCc5dnLGxxRNYV9DjDb8tBTIVzuJn//7z9+4PbzLerLs+hFVB7M6WBMNmYwznc7MQBmBc9bVx6BMClfXfT8t+gdRKQyVff2xRiNI2HrfjV2vPow1mP6kaQnGY0TafO+vKetHrmQbe1dxr/yHzOESNYwwQPZNRP2N8j2hvX1zcsnOtGJ/gvpBKD/DcjC6WVGY/i++F3l9RVjkg+dfAgN9/JhpuRE/4V0kKsdf/AcPCooyF+Icj4r5lzdEGB4KOeQOBAaFVWs6ggtL4w4wmIW9rn4M5aTOa8bZ7CYBGOxBWNRrew+QcU3eCn5cgvgsUqY9YmBP0mAbiYKcATAv7UBxrz6K7KA6gDwRw8Q3TzRi0reJqwW7Q4Rwxi3WtcDUr6izdFaqyckx+f7V/s9Adfa5jGv3yhwxLWtZ8TY8KBCWChYbJzR/YIwujVGmbw0TGDn/EjKoloS6mGKJILENoOXywoGuGWyKf4ktPJEkvOxM2EisawXwaijQcJbT6WIV20taDyjs+R4QzdLYQ11LZKphNdiVVgW80wC0EwmZVSawHsBmsEdzQBxlpBjYEJlAZ/Nk653ityrDtpTcmCSCe7CfiGUFmsZWr6AgN4x9659tZc+KiL4MUJo7aSh2EVrAnTN0a7zwiy1zSK6p1zEq/xTB/YhU5yM4HkoXiykrgAYzQPiLnQRAcbmZ+Xnu3t9CO8+vQbBz+q1PSv2m9UaTG3Pj12vVF6ViXtzubSv5btNYYpYYQFMrJ+5vSOM6mrGEwjX3m+97VFKRWspRDhI8/JpWPQuIC49E2b1XBePZMsfHQ0xJY/tlb0LqEZkWVu3W09cNN+lKLJIvdKhYeDN+h+lYHcmERKen58B36cY0+5M0waEAguwLUJBsrmpEqylcSVdQz3OFAWYmRn7PqMUwsQTinqjS5vtLBODAeo6vtYHlNQJLAYCrAYhZSooJEYvVKDAP/tzTYFj/RS6gezdOeat7QwBgkiUDBeXl2htP5xbMMURlTCA6NIThRkvLz/QesfZtJN84bqP9N5BFZqKQcZi0vmixzostDyQFE6Wc9y/QxV9UncoygRwRSUHymutqvjTx1iIeDvyH1gTrshznv78it3NlYfZF6XqDO6iIKV+js5Pi/0GCi0lZS6zGmbFnP4OxgXLaXKZ+QB67axEqkPqu+CI0xJK7sXaPZJ3s7YR9cDgD967rssj7ZjX3tASHr+v6lUld2dwWmvG7zGARl3D8XMYa+k+wKm/zLCmkJ3YcY64F06wi76HmKLS+rMr0L0cyzg1dE2D8J06CgqeIecrE7tCufUu57PmvOfeNM1Jd0V91+gJzjB7n8b5xBh+gnFM0sy0aaauDw8kIUv9MucuNqYymO+YT4iz386osQmHPVbHtgyMWLToAJ+6UQE2Jo03uy++59+3/kZZGtaal9NDyGfvgWauwTDl0zAC3JkCTIvxs6nWE3uaQdbivD4k/2+ayxJBSOvgF51HZ9oWjpDE9l+SNcGaVoPIDOJoWBc2zX0f6GMfuVciWFNQ5eg+dtOVrt8rNDbz17QXbnerP4c3Co5nPtJZtlHb0fvX4tmLoVvzYokfGA5XGr6z8QJDPWNtIz/1iFu+wV0yEDjUhtforbLusUf2PUC8TVpOZd7qk9/4/ZXj0OcDEdTsES8H3iMMo8d9ixj49u2bP/g5HVOkv1sbLER73lOWn5ff/fa0jpf3Lr/HiWln1/Kdj//+WpmhfcOT9bNFJTE2hbEqmdQ+DvgXggKAcQ6BoTnNZU+rIEwk4O0EMZ+vsP1JUuoIGN79nGPuDuR2TcnluiULMQ7jYRZnKcfJtmy79MXIe9hG4EZLpKG7U95vIJ5jfOBO+frem/KmmibNxrJoCqDWsZ/3nuPd5ghF1w99bnKWG9cvxhKspzfJgSIpBibUXcGuTjjfnWkI9+YGNKYv6xD/9KoWrL13NG3/3Bpab0N6JpOhPNKOy95jQrA1rJp/k+/23sxx9T9JRMYHsn93aVP506aGHECaS9xRi8ElyxWmn0yeTT8Tm05QilIRmbmSGDRImr4gZsbd3R0uz85R64R53kubm6wNVTuAdVSbptJrTaJnmf6RQGgQpw4C+fltBuOApPvD8JZv0XHlZMylE8wQpaTdb63DGJ8QgPvYL68B6PbZZEIq0rcYl9Na/loofn0u0EbZE53oRCdKdALQ/yb0kULJa7+djoQT/W4yJo9UWKJFsq0lc+RMzsjprAROBzxSufAoIVdSA2FJbBV4uCuK8vG7Mk2Zl9JnRPh0QifGHywg+q3KdZbPPOcuN1nhjgR4J8CBcyDKMjT9IQNf4La97plStE1f3VVFcupVRH701DvRmYmO1mPa3STh+Cws30eRGFFst3GhUvM7Fiy0/5cRXpHLOWJCG+caDLhwwZtBpSK0BzzUTwB+zDOIgLNa9Ylitc5AEkYk95kIpwISdWiO8dTxEjpLQjQ3BWm4VLUM1jmpVsatdTDt0WgGNcK+TpgKoVT1vHRlZRWvXQXQ3QK3m+EKJaGdVMEBcFFAvgOdNGGazUciN9yIztNcz03ATQYAy4NNjGIh+HrBj+/fsd/vpTcHsCBAqOyRPjcFKLuBq6w5NNM9UCVgj5B1vffxd7L8nDbTItTYq1PYhKdjF4m2cbyg1zI6LIO+WpnHVL++dmBdb17Fm29t5acb8RibHx7TWF0B+OafGY/Yf70GAOw+TwJkdgHDJH+5gNhG5pW+O9thYlM0yXihAQ2hABAsm4YXGOZMVk54GYIBOxl87qWJUqJqm0pJ2kPC+dmZzA/1AEc+RxhwAxy9p3fxphZAFyhUVXnkb3qgV6VN+3mPqs/yXOkwZY323wFBnju750qRBQ+GGLSUUoDSBUT3NdJzB+UK/f2BUIYNoRzBaG0PIIE2zHE2KupCabKxguU2VrN6jKu5lni2MKMWQqGq+dnJAW4iiVpAVY0dtB7722aBqS2ke6kS3rir90S7f0L5fIPy6RpgoFZyRTCxpLwgKphfJJJIf4hMrY2Bxk1A87sH7G6uwQBevs4o1zIZWmfwNYMfBETnnpQ1HLn/7Ei+ZAoP8TQbjC/5TozznzhHD/HpP3MkX7P5bxO+v7MG1vXhWlA/LuS/V0PI/VA6dWTPeVOALepWxTXpmpPQmbauX2sng1F16eqJroedNjEpzmXMqPPQ7kER71s341y/f5eG4BySB/cFAh5KBKPuCuXWzEOreQSObHjR9R/Z2WERI9K/6LG837/6+lFOz+wz9WKiPoMbsLeitJ4zmet59ZBKR9qxs2ZQIB9VXv4bBl/WG6x/9fk+rtLyHFg4Py7txEObObprfD6Nv+NAOflp7MxlC6Q/CZEbWMHzwpjVqId8HRgPW31+SHQfmV8GejLCWAQ4GycNETqeUegC/Yfmar4A2pNMYCICLq2FtBhr/eJhfnVPZ3knNwJ4UAMQfU2rp+MRDKCw8AfynVFwnXrH1lrsweS/P647GMfPMyMLHf7eXOnbz1zOpnz9re+vt/yeAI3ltXr2Me9sxhvbfnECWDJSyFsijYTByBvvm8/6mQPmNxEDeIYY7Bnw5fyIrg1L6bNv4jF9lgyBngm4ag2NgKL8m53FNoLfaIwlgeXvCZC3LdzUGcuuGuK6rPaJw9+Pog8dFw7ejmI/2vg5DG8W27rxkLa3SPhp/UuW81wAdNKN0Oa67m5QODxkP9tz0kltxvMr6cfKM8c5bm1D8CFmZBcG2ySR36z9ZoBnQPrC85wGHoH8Xbkx5j6jacS6SpLOaq8h3Szqw4+Xl+jrXtwIgVNbgbH9tp2s5kliGrzPNQw4pSLeBzpOUGNWK5T7ORsNrmiodFlGT7/FQSkgciqZztfNpyzP3yPpWHAzekbbWyRdlhsY6HUL275ve09vJdfj92ma8PwikSs6i2bEvJxdflGQ2yO0lS5R/Tjm26Rp7JavTES4upKYFy/7FxARLi+vQER4fJSzwyNowgz6IF7nTWTaSuqy4YZ4pKmn5J0tGtO83zt/mrpnRaMZQXw8xKeyybEmm8PiQYz83dZ8Ze0DTnWZ09ASQM+e56t/P7fDnuhEJzrRu+gEoP+XUShsTnSiD6TMxCu4aCD6Kuwn8PYkXOgksqI9hzl1ppzhnn4DeClcmVdKKniNxTgYr3BGHpj7rxCwnFjCuc8IRfknHhlBy81+k3jTGzYlivw1AN6ExKLPs3foWvcEAeHvtP5HGsH6Lfry+V+4u/v364UOUAbPnz50o+BtrWT8GsrMUdMHJIHTqmGkPFCqADSmeiWYIOaLCdEm0IQla3pWmr/NPGMBD2MuSn8R3EuVXMNozS3YiVt4hxZR4VvDStG2q4LLFJJULPpAB7cITcv8gl4KShev11LlyCZVxnMnkOVeBgBWwCkJWV2kdzAVcJO8sx1ApQKJgl1EOcCRW1P6FYD5IHEI5Rbymsw7VdsqIccO63oYoljos4DoXcG2bsA4lyFXs5c38DyDE3qtgWW9sMwDWTfSgggRqAqXTR1B7CtrgOfAmywKru7LCkte9uf6uvXN1vVD5Ze9fMy5vlVmEErBgOdCh38GBAQnlhDqIpRbaHNaLWsqhEITmBmlCig6TRN673h++ZHaExunr11X1izJRexQr7GGimeSCAy9o04Vldkt383LsoCA5BVuz4w9R9Z9V0t/88ggi3iSzx/XJtqBkxQCuk5ab+jUxUseRRUY7K/R5obO0l7mbGQWQLeFa4edeaqYGY0+rN/62I+2RvX33kXBQqV4OpPDKTniOqd92xSTBEgI9z4jDaGsfYLniydNfSENIDSoAkcLs63Z1tGYFUCStvWuIUT9NXWfvLlC547CojxkAL3PAKqCvUApjLnNaAk8t7Cf5jVEAObWUSuh3sg+3xuj37eIltAvYOCPeC1jZScDABedxjDrEM/lSw/rvDYUeIuGvSIpkI+7e6RHNWK8ZEQ0gXcQ+/m5Pl8NUDBg/jrlZL5kUoBCwObeF8ppYZaQoziwjrM8jkFDP+hfByLZo8YPaVOTUZiQerOrVtrmXaxHGxs7o1StzALg+O96/vTOAPXIbdolSoV4f8n5mBX8BvYAcP6T05ywtjtwMLT99fGyNPX7vRiyWB9UyMk9jlV8i9Ds8UDljIb6R/hoizZOnY018lrx12hZfCOY6Pj7W9P7jd85f0j73nhbvvL6ymRYkKvFfFNFc54bNvcMVGJs8CycvLO8ih8ALuTn79jc1/N5wVBPch7nZwbt7Xt+Dz7wmWzfH8Y98xXXyCC6kIZ8XwDp675+nRi/Bp6PlM6+Y+TT4cMxHNhIry2TXybjo96NTP2Oxnzcc5RzwQ6MF8SI5f3T6Ixlz64aqQoAfugGccE03HssLWw+hy/vnbuL238Lrevn9IPuJctD1pZA+puNWMMIU/jjQgLcFRLQvJQinz2EssxDkeO62xi5P7MaDFlY89XKSEuS7WDm4JWHKe7t5ACXzStV/+e5ivTl3KA0fZZnLeo2WbUxWp/RWkObJY0LipgPmQAsMr7Uz13z0qjX8MFB175fn3mpgL678+IEfy+Tp1xSIkvhIdFN4P2ne/3GDrQwO1v9vt24mDSUL9Oi3G/b7I4jGdPuup8CizwgcmHT9Dur+0jknThXw7NeFCxyZvcuY16xjGKga8U83FvDTiMGtJ70RsXmioaZn2fQ+YUYJYM1Ag0GJ6JCJVhz/VBh6yrmivETHjXhvefCof5cfHeeyXmn5SQ4MP0posfl37dA8/x9BaTD1nGUze1a1XOkIcaJTnSiEy3pBKCf6EQn+lCK3DcIEB1jDp9j69miDKI7S2vykHKr7EKGMJzcRiHRGTOKOi0PtT48CQfyN+cuNwXlUn1GUOvUQUBc82lLEL3r41oq95Ck+0+GwfJbQjfj693/4n++/H+4+/r11ZJb9Kjt/VjwPIgXnw5Zi2aA3JWNyzIb1wdhEyLqiGhLcQ8A9txWJuzodQ0PbWM49ybCTG+gQtiVSZ5CRcDwlnIPdwnpS2SwEYO6WCJPtbrCFKY8Z+C57ZOillSYAqY6iUc4EWAhYksB8x5MBZVZnHGpSOj0Jp6XhUWIN5DIvfzUwrpo3uNCBb1I9INeUp4ql9GlfQaGWd+aYG7KgRx+2sBwhgEbqZxpBlhA8da6AOgpVJp5/LqA39lzy3KXnOcGqHs9Ole6t1MVwpzmyEIRMhpfbM2+pEhYAF9r4JvH8vm3o8HwA20Yii0VGyGcZyWyRY0IRcYVWMOzn99+wv5eFNbzw2Pcz1YuRNxyIzO4PwgQu7+T/q23Ba29gFm8f3ZnO10OBliLUg0KjJpgK2G1ganswNyxbwL4VLXUp8FqiVN/JuVQOkNK0RQPDgJ0dNY2VB5AdOuQlQ6HA0gyI402i2LMtR46D8MjIQHz6v1t0SMAwjRVzxMLSK5BSjCUDRgVQkFBKRV1qnh5fpb37BaGXXYttnVdi/YjAPVmLIXEA1y7jbt4v1s7Wfu31IKzs8nXePRrmkkJzMlepITwAJB3LShF/Ap2ZUqe7RGqUhSW8DNYmixtbrpl8zzr/qbPIcJUjT9IUQ007GTJ46/zSfYITePADSDH6K9lAAAgAElEQVTZq/f7jue7R28PIOHX2cBP3aPa3Z1/l3mkXsm9g3GJCF1p408YACyo4ZuPrXz5Rmm87Todue55/PtdQ5geCqh9o97lT0cghxYD5hLv9ETPIJ++vHueQ0DuC5Kz41Hf/cqepefoc2dQ6pcrS38AM+oAKjO+ASilQ/SIBRkRNeNCmVVdt/qKDMAb75fJIz8Mh4DMgUtTMLOeLbC5JXuOZo3UW5LhVpeoKL1rrtYmId05zyNw2nCk41xxaXNOvfttH4+S+ryBsxw/ebQYABdnu9gfIPvZRKTRLOA5gfM8JP+n/FFlAEV4Gn2GK2NT2/K/JS3Lrkq9Me38fTM/n38f+nPNC+dTY7v+dxIffk/pra16DaSWni/dZAXdF3UuFojSvlAToIcAoipjpnuV8VM/OqP3F1zgzJ8BxJynePTAA7MHlCF/LiBnha2BrlFOOsQgUSJ3mBf89ouH3PUEgFD42sH3LTLPc0bwHZmMf7ni8ftb9HHg+e8hi1D2sxRAxOtUawlj1GxAtGJ6DhCvPqQKfj8Nu9wCfLFUM2BG4wYqwMwC2rYmE/KCWY21gi8mAN/QcA5y4DweyAE8bbZkVXy7VDoY39oPP5J+vV6VzYzno+WvpgLJXp36XyusQJ+Af0VTpRT3jDYdioB/LQ2yXPczRGVNGE/NUAN0HvOA675TKDjqAtkDnbPQMU2qE285Of8q0eJG4+EAzyUyHDTUfPe5wmAJW18K+l6aahGNzqaCs2mH7y8vqIWARiLTUNOUNDTw38sIVFVB0fW4yhXN+gRqzfVfRBoKvGyvUZO95efiRqTGl4Rx+fre/NtrfGuOGrb1Xosht85O9x+s+ih6e3eSOXu+E7lzbk1Abiq+rzAzXua9G5VJe+NM3dUz9N7w8tIgRhQR+YI1PZ2dp0hjzCqvEJuHu/RPnSZN/xNc1NxmUCe0NqOUgnk/AwQ8PkmEOItKRgY06zyN0PrwRcxQeZwh+dEhwLlFHct5z224to757Qt6Ly/u5w1zjIEX2Y6S4L8Osml67IEJIvKvhof3fUiBc19v63c5pFM+ea2f6EQnei+dAPQTnehEP03Ck6UQPQ6eB4iemZNjwPPsGXyIlp7oQGLMlLMLEDAENPNCWmkr82dXNEZbb1gA7QjELp7hW63MzWJIndSBGxqVKeZVbt7pt9q0jsiRPoon8fsx9K8v/4M/f9IT/e9APqdALpwA0bcO0vj19WiEVzpHPXYzolpOgpOVNRDdPeM6g4uB8SxpgovdS2jcIZGHSWzNSUNYUYSo7cyYqip+SH3RfK5ICGEBt0UgI815zgpKopOgNtwlh68aAnSWNhdUgDUXlgmBRCjd8j2r56daxKMApRd9TvSD4NEBGFhnsfaRL+O0nj0kO0K5PAo0lNYlJyFSqKnyRJQqXRUU3b2dWS3EOzcH7hxA15zPpvR1ZbEpytJ8ck+wYbJlsAJRjtM9qeyqXOqfZfnx1nxv1L0C5nmr/HjPe6hAwl8DgIHqVlsGOgFguiWJiECEdlsCZL43K3vGPL+A6w6lVQ+zHe2WuWhh6lysZ6CUSUBfKmhtj2k68zNijC7gN8b5QYRpkrnKmoO4N5lDXd2DO3eUVtCqKJYkhLjc3gEFqEOR4GCFrp8+i8KhJIMAeTRFSHYWoD2Hl3PlSZec7PNsYQLTPmZrAJYbmbE7KzGsyTEmRptQa3j8hEIqzlwPEe23k7cNy/N31GrIRw6lpOUINrWjA8eIOSpKnApGF4QNY7vsHdnqYjgoaYpMW9M5VzwDg9EDMwRg7NaHXZW0Mf/n3tRzoSgQBPT+iNbThFQFqwNXLPn/DMTqCTj3dvMT8OkKfB/eUcQE4rG9lBSIl0wwv3/bT869GaF4epXSgc/j1+3iC3bmIJGGo2WoOc07yOZdYmrMn/SKR8XYpd8Te2GjFG1FqXNEWSlggIoYiHVGR3EQfTC6JAt13TW3aEfvo7Isq+FyX6+3ez0/fG/o2i7xOh8NpsyER8FG80TXs66bh5CmGfAQoL55QKJ3oOv5F/0lg9xjISYA6OCYY80HPj3vcX2+8/udz9a93fLz2l4PSGjktNqk7bOC51MVXqZD311DMym4nj3To51/fyXkah68u4b1HemoSg+K/u+dUSBzJmQDBhcxhOwgdOrOr81FeJauuVhlG13wB7ktaZ9d7vds/3tiAdHTeZXnqYDnKTWOpUpB8FXgVJ+tN9vu8KR88zUyRatHD/SlMv3/KhXc4gsDX+n+7cK/QJHCSDbrbvmK/8EdLPMpzu3XdAcMOYuW3DUDa/D8I+gfPoEFWxUej5DXcfB4qSTMSMc9PBNoVUpJ0Y0UOC9hFMb5PDSmeDWWIbd5WonFYHo8HxIv2w6Try3ii/FkBoBGm0lfpZSCqlHc3MNc2+TguUVJYgJR7L+SO7wPaRQIBFLZ82W/10gjRVlAkeUt6g9hGyR8z5iNPDi5YbzpwrIsaQb5TIwCi5bT0xkw9P6rz36vvPn3I+s3gGBGFNC0ee0gX76rE2ot4gWuEYZs7RBMP6HOOkVD6ieDhp50DUSEUqtG/GPM84xpEhl5qtX1TE3TYol3uZ2/UMOOiDoAwM9pMzCS9VF8rhEYsxovmxwveqNfH8/guXXduZoudGjMxvez32RGFsY3ufPGov5wihjJAPP82QF1B9IXjUTe0xbXnWd+bw+c6EQn+m+mE4B+ohOd6GNIOahVqB0Tmt68PYDQ94LoXnvR7wwYkEAkoYeJycH0wTqRF3UmgcvYv8qMWy36QAJ6G5Z5BlG63pPmPFeeuZG8U4coKisDt1h7JDzo9wyiW5h2U3yqGDsoVm94K6ue0L+//i8q6lEGC/9J2vKwAtLYjhfX84i1bMotOtYWqkYGoyyyCJr1cHXArIPUqxtkQLiCVER4VuDMFAkTyhAiDtzBXFDJatdw8ZLIF70zXtQrzIGJ1AuFCJ2AthdPUvPmPK8TQOLBWYoKQCZEZ5CBm1ccYcoKOnVUrmAm1EJgUmFQQZ+iE8uAcwACZFruOtf6J6FmMRYWkt2/E8na51iHBigyQvgzUK+rdb00RZ7d3OtclLrdQXQDPqW9TZXANs6hCI7ePeRFLtfs9casX66MWCqwrTzFheU9yz76Oc/z4ZcDnwHbAS1yxCdrn+c0z3nhv6mi2/bJULhMt5FHvE4TsJ8lfyQB7baj3atS86ajtWdwbyiliie6KWzyHOjhecJgTNOkucoLpkk8QYjEKt9e3sIiw1plSjpXvMlIV2b02kS5oZb2BqZTY3AnNEu/sIEyMqewkibfQ5WAkPloyj4zJCGtrE6Tl2uzlBNL/yagvuMn+mAGmMJzxBSSL8/P+h3+DPO6BsSzjKi4ksFXD5tRTkVvs68b8zdt86xh1sXoJ4wQxj6w+RnrNheI08bO4/3LXhWmEpo+yi2AO0i0C5jyOzY7gAnTFKLHYP2f9HpECAAJoaAxkIjAEgq/kOYOlv6d75q3rOmcsAA0pXfUW8JZvcKPPx9l32DxBLX5U1jX+/0jyg3AfAXib+gP0h9miGW9wzDPSfbFa8pOguRZlbmw6NpXyDzKrzQM+iF6OBIceI0Fe80j3a8mMDiXfCIW4ELrHg1p4OvuohkUIjQX4BkdV1wkcgR18WTvBT/Qcc4VRIxnTRlxqWA6E0DEKBo1pZaO7wwxcPMHLl589U4xyWYS3s3CY0b5uI85vHeJEV4/xOAmn23Uu38eO9GARz9bcz9xXOjDc3ndnqR8NLLYHU/PL6j6/tNU0eem61R6pVQGz2l92YdJrhMq6iT311qBxmAS7rNqSg5STy7MbWiDGbKNvXzc3NwiO0NqAh02tvCjnmA9dnxrbJLbvpbGZFGvlDAjPc5bgJRnPa30PPPUICAU7uhVlOStm3EFgXoDQfOddtZ7GGdg/OBnABqwnc7d8Ivph/BQrO/Lxgnp2ucL8EOkFuhdzxsEWC88l/qi25ylyLsKAJ0j5Pp3MD7hJvqDtngcA87l+luRrf7uHuVLcvbvwO+/CpwvuyPWgsy+szr5GLKPUay9rb3ofbS84X0DtMVVvEWj7KZGH+gOFE6dMReRbWqVk/6HRjTqEEO278S4YAnVDgiIfsGEH9qibyTRRxz8Wh4bB6zUr1jP5jf68ed3vtdr+uh6hwgHwcYlUIm8c7LcC0svRHb2k/OfBOu/LIfpXsbmCUvI8n1eR9nwkthSwOh3mJGlANeFWcKTm6F34r+GV6XQy9Radb0ooIzwPgdlgDKnhZN9eO4NZ1DDdWKcTWdoZfa0ZrIJ634O40sSoHdgALe4lOE6j+eXe9Mn+d+Mj7WAv8uid7Wti7E50KgxCs5heq+eaVPceLV+K67veuR9hUx2gep5JuwUtO694+XlJepPfGQt5HJXa2HINlUBp1uPMOhuzGAGGJT6jSNtlYRol/O1lILziwvs9xLKoPUYF5HrhOfct4iBRFiMZxq3QgVzlz2wcUNR485n4w8Gc8voPLMzHvShmXj8sCyf9T0mm8Ud44U1N4Uk145zyPR/BqIvAfP8OesHTJZebugnz/MTnehEH00nAP1EJzrRL5P56IyWfenDOywesxc7sKWUCVp5oqum2LzL7DNxqNAMCOEklLi1JCVvelWKMRV8LcCXLoy7hXE3hnCvdQwh2aFe5N5QqOI/wPGHDd7NwsQbcA59hoWD/zgB+n308TnRj6fwraABCRiBleiZJSOer5ll7HDzVl0UCuYeYttYj2onuZuQJAK85HmrqFABgCgUnTr3RAkfQrq1XowyzOQCPuiNJAQ2d6B1uPeegUnR+IKwu2cN9SWgXKOO2gVMRy8oJGA/SNuSFW+u8GCYh+7wOzaUe4PCfwRMXAGQPBOlKLnQKKHaBQjtScHRFyC6hcr1cPGsHqaEQTGA9Hv2Erf2D21HlMn7wnAPj+Xtmpde3Dcq0odfVv223OI+yvMcALLHuXy/9k9Lnx0Bp6p7W5dCyDqZehuqHYbk+gYI834WBQEH4GvtFeVBUa1HUlYlYxZTYIAItVbP8zZ6oNpc1+DFxYRnQq8F8zwL6G3g5qqvkiKJsVIq1Fp90Cz0cSkWlr1ov1CcKWqgMu12aPOMeZ4dlLCQ9MOMML0gRT47a5UbbpUiUSGQDE7YoknouVYKWp9ln/GxMYOzmEutz6jT+eacGJ7t7ctrm1yBBsQewxDPibOz88inrVvyasZy6nOSDZVM86WgpBnULBeA5YgWcEfASoKkmyi9hGJMOtQ3ayoFZ19u8PL1Hp0Zs+3RECO46RZ4uWsAHqTdQHjds4LpzJhYDHJwzwA/Ybq9Rv30Df3eemHcR3zPWOwvnSMX+M/QsYrCo+o60IRXPdJpfd+y9JOuJ0ByoK9WHUm0EQIiV7x6jjdivPQGMOFandfOUcDUxRsHwLUZtDDju6bZuWKgMKEx4YxyiN6xwzYVxByejb2QzJHl/jpu9j7XmfVMV8+jnOIk32DnI6fPXldaV/B1lVlYTjUt+nLBtwCL/O9239ywR3iZEwCaxzoIAHYaUWEyvaO2p7NzEX3umGEGTW0w6Myf7ftH0vaoHkc/v3RsDS/VvYeL55J6YgWoDihfmMaVAVbjhg7xdHRPLBLDwwBG5fNLeoZEC3n2lprdY0pqBTkLJCWBPd/5JgsPr78Z/xVGiDp3e25zfP7uTx7DZp/or6Lof2XVkbjSn+IT/y6U90sT92J9EeZi+2rmTeKu7+msNeDcPudJ+j2tloOUl9OR28E/gdxJIF1BWsuA8dwK2pHt8PaHfNO3vaJzB1NR0DvOOfeiVYMgA6jNi5cAAS4TysypDrC1WHg9v1dDWKN3UCnOY/iEQZSVXOBqGKzpjVoDShH+MuQMwFJQGcW+KUbdM1mcIVJ5YBJjNSLMWiYrFELe+Vn5bZx2boxeAjh02XU1hpbohZSXDp7aAN5Mh9r3T9xPjJ8hwB0BzFGiJyMHABG+ncRhYjftRGfSZ9cl5Hmb50dV0Dyn92I1QrNrkmLD5CRGrVVShUGimfm5rnNxbh3GTfl7EFwvUtXb2s5nZjFOb/Ms4wuRkk36e07zoh+yDnqFLhDGR4CkZvqx3DyTLuoYYDobkg/XlJa6u4hutg7bnsHzbPQz8N5SSWouLS+t2nCiE53oRIfoBKCf6EQn+iUyfjIr2f2H+PMu5vw93uhbIHpRqcPCeZlgweqR2M0TRG8TZX4osEZoXf7eFeBLZ9yVAMG/6oNue+RFl9ICqLuiQyVFUibavNAtNHwm83CPu0cqqdxhgd4kz59jBpd62mPA808MPP4078mb3zK7OzRuyeSuNM2HniL/c090A8y0AvPgMhAdrJELAAWt4f9AwL43EEhyTIFwPlnIaAWd1fpYPGQ7XjTkOqnQpUW9vysmdAI8y1uXULfPrcH0GKQe3az/TINLHAoJ/y+ThMYFUDqg8rQoxtUkv7DlTsQi3J6FN04AegKZl4IPJevgdY8j1cmuFDayUGoeip0DRDdr72hL9/Z0A7qiehggN+Qv5gVIrQKxA14W2i79nskjQqc288b3Lfp15cPx9+ddi3CZQIArAN9AuNq8r9yWEUBhEfKJgP2L1Gz7cNe806J4Z3TWvOEkoegAU9zY3qwtIg1PR+E5ZOXM4zznv5brZoEudch/NeIEae5tktU8TRO4Sijvppb7AWgyQl8UgjmhoE4Vren88DlunjTyjGlS73pVWFsOPDsd6tmZhOTbTRrmWfbeqRbBd6MpAZaT5rOzMSjWJ7bFUfqua5IY2SubVQEjnv0FhB1aa6hTxFa3/HuZYnzCwj8r1Mzjxz7bPJ92O2CxTvL0FuUMgSiuZ6906HVi9drXMzLvK4UK9l9fwAbtunUFgzR6wY6uwbeEqZoIw95xvXeUG0K/Tw1jM/iQtA/f1ZDnqgO7T0B/AObUPwYM7j5f48fdE+b7J9RP0kf15hPaw6OOaQJLU0c0PT6+q2f8RScQA9/H6b0ihniED3j7R+hzfnIPMi5iee0QOf9jhWwalQDd5AxjQA0LZH4yWiMUic2q4CLjqkl4azMYu2gaZKh3dCIB1JPizkkVleFYnvbpxD88amiCMAAdy3utbAYdES7WeEhJDdFXnZXPB071DO1A911ts52Lzs4RT85BeNF5H/s+o04EogkXzKhTxf75ZcVdlWmSungGqKrnFPke3+YO8AxlV5IB59jP5v1ub1DAm3PGd94FY+evs4JzyJ+byRIoHKMCfmvG88YXv3b0mkvni92X+PIw5BMy5XWBeFDOLGA5VMFfyCJgpfuYvf/tid97xzkIz3q2nOsmVJjjzDf+rTPE4AMaBcmMEYMPs7ndKfNluh460MRy6A054NHvPVTuvTnOP5y2nsvIE/Fd9Kuc3ZLCUPDA78NuAQdLrC2NOzb5zdWln235e+9b78vvuteMr2pF4YDKdwyAO2YqmuM5+sVaaABPBs4v9e+TvkruR0D4ASDmp/XlDQuv8viGIdxHz4ePxi1vtcLKgIDR8v0OwL/4C/5NXwEEWJXBc1km5HucnF4sIcxBYhy5Migb5UmAQWIPKeNGhGLSeIlz2cfRwG8wOgtfqSeljB/D90tSOde5TY2UVAXdhHkI2ypa8tnAur+z0VFn8Qiek1GRRTrco4MbD+vPwNtsKHyQ/NAc+QUzDvfn6b+SjAK0l6WNnVHUyHCQxW1/14hbcrwszq7Fe9tvx8ivy3V0CIM8dj6vb6etPwPvMZaWPp9q8egAtWoKLohM9PzygqqGF+ZsM6l80bl7VDNmA2x1zrfuYzLVCt+VWPtL77H1IxHWdjir1Y28n1+eUYuA6K1HapdSikZ8UaPfEvO1tUgDs5/V6IOBOk1iELBv6NxwxsAPZlwAePF90bkKsEs37ON06Hi4APADwLckJwLA04I3zfK53B6Ava3lpb4o9MOHD4UMnh/KeZ690nO9r9HJ8/xEJzrRr9IJQD/RiU70Kh1ioEeQO9+wUIYteJWVknCjzmX5Y6wCqSTL4T4K04NSKynzki51AHvS09U4wL/iS2MJbQgDwBn3CM/0JXdPZB4jlodSwGbPqb7RvRb4j4gcZL/ZHoaj6IY/44Hu3i74C/Tz4Pk2bXmPA8r8poFbCm1bc+p9nugBFmbjCyTl5NbvJmw2zTfOXS2PIYpMAiVr91xXTIGik80FQx51sqzgFPE4S1V+A5m/vOo5LIcwCkBdc212SWngCtQOQddNqGbzfBrB874EmZHXBaMmIcfaZOsHqS42b/NUk4RRnhU0D6Vu1+c2mCd6KIPN27enuWAB2Nnqye+zWGiKR44XDnwdgPKhHK+uDfdtlF1fP1R+u/6t78v9UcDz+Caz8wpbqga6iVB3opMRWKS1JmDl2c6B7DZ3gJp4fZgVCaJ/Zgs5R03noU5mndei2JH6KQHpti7IkjGauo6ina5YJoT3s+0JVFAqgbuEg2ZIaHXbu6lUNbzoqjyTEOR1MuE7QkBauwWE5hQ+Hmq8kkcnevny6hLzPINKR2tdDBBcRTlCREUVsuJtGH0fY6mrnVJIfD9cQqk172cIKM2YX/ZJaUEodW3EEPsmb8zT4ZCM/db3TwMQ01vZOuuMzi0ZQMiG5NE10rsVIhk/TusUst8QqTGNh/61aDKL+Y8ntPtL0K3UXUigu2Z7co+6ZUyB6RaY72wviNnTHhhntwTcMeboAW/vxedrtP4Nlot9vn+AR3VwRaP1o43vOD9h/XusBpExgKUfQVuK0jfvsb7y+QMME3lBBpJfUoSFv/R5F3UCwJDTvOSc5gJSE5GkAXFQKQzHQJZaBdsKM4rG82Kuj32RG0XAsP/AV5MejgPvaN9D2SyKSe489FF+tjQrgQrQEN8cPMmxBlfmf0x69gKiqp9nBsFSwBTU3Q5tv0c2emvzHjRNIKowCx8Gi3KYO3jW1BsJnE894ZSjJB0qM9BSFnjzLcdxCtXvZnWbj9s+gd9Hxq29/wWWq854P5uTYhBIPQsNaf5RXF1uHz+Up2RA1oTva1p3N+CnC7Dl/FcO4wudx93TD8i/tYciL97lH6mEXk6cxTb9d6C35d3YhLPn+Wa0jX8wBetHvj379ZWc/jF0yLDjoyNr/B0o6zRAwL/LHV7vUwpjUL3R9jDfOBZ1Dt8hBlbEAqIDcoazWXY7b036m0YdQkFBBxUIiM7jPqhmp3I2EDw3OJQH9jDn6n0+nh+E5Q49ysDjP5GDuhr9WRQlGu6NtoVjh4WJ/wgaPG69veTrnxcyivFAZlDeex8M1b2OBQ2//UO3laXeBxD5YjftcGkh1AGAgLPpLM7bFiHa5X4pxF1OwUICSFs+766h2V1ecT0IuXHifr+XVCnMqKViP+9dBmSVTbmpzAb4MxhiGNHUGM5YXu7ATlNhWX77HWSvOscocUa6rZ5VZ2/Sj41r27eu9QrLq7YlvAWeD7o1/XsseB5OXKtKU8to6/JROuYTnehEJzI6AegnOtGJPpSWfEhmWI7xKI96xvveoqwgVIzG5WzqLpYBYPdEtxa6gswEwkHBwq7MFo/zELpuOQHbBAfSKzQHOqtnGwGTcpAGht/yOh/6Fj0QcNuDKewQAJ4gOdA/d+DrQSNn1jrEsvyGvwzf1zQ2aNnt/wkeczTQWGimDzRoCQ6Vsngv/d/KE51kdAuXkZGHgehibS9Ww+QCQUNHAeHHvAcx8DKr4DbTQmCAAjrsQgD7D0jKVLmHqHvYYwvbFiA6YVRikt/r1u9EnscUpQGtArWDZwBVBepSUHr0g3skqVedeWcvvdBX5AYspqJQJYQK7BY2zf5mnQsjPMtdJ8OMpsCmh3F3xYYpAPRJ3H2xs41vVoSk70jPJe/3BIws5onNoeH6AGpa2YXAeGB+Hq/k3C63ff+oGW4asr3gSn/5Bqy8z2WcShJIDayqRXz9BESuPs/mOmPe79HQfF1Zc1S0d6G/kORRJxKg1w0jenODkjbP+k4bwIgDyaEskvYxpt00ANuCfRFQgYqKWif02kRJ0WUuExGqqduKxJroTU0uNNVCoQIq0PD1FaUWX//W9zauBTF/jKy/as3KF0rzTNaUpIZXT3pTNlCU99zpOj42uRjy7FoKOjrOzs+8baWeRY7dMiohOuDKHnnXkjo8qRAdiOnDWulNcs074MJ5tKBKbgaby6rR6vwgcX/iUP4xA/O9hDMUwwYG4RrllsAPDLoh9/iufIWCgpmfQPQNfK/vdfPJDQ86s+YrH9fkfM84+/IJ85+PYJbQrsyMGYx2v15tDODl7glgxvT5E5ifMH26Rnt48rls5E5J2mff1JPT8q5+V+ZiCTptreTvYAegLz8IJPgZ8PxXKOdUd89zkL+wTiPJZa6K6U5VgD5VjImyXc5BUyhaPklmAddbWjNGg+JXFdi5pzMweAVC5wj7G2yGc5Jy1mrTLUKLmsspLsl6HsW5tO2oSB6hwcijp9iZC6vfGzuSHSkONEiRCLA+9kHf74MnTu+vuzn6HuBKKJj03WbhDdLzWG8247QtYoSfHdn7pLLLNqxreu1bXOHFb2/N6vx7wUb5o5ZF4hn83B8EhI1GrRgJuU17xf6J97kp31NIfLY5bXxgakU6/7vu8aTxYW0+WU7g4IGeZO61ywDPNbc5M2OmRwAM7jInO8T77ht0fi8m9LWe14/0OK69N3rSAMprLfi06MZNOmbAl9skL68f2Edp+YU2rh+m5X7xXgDb+RqsedLlcxjAVMKUzPZQQHIy/17P81+kI/tztQuY17lHRpD/ClhKPn85Vofeuv2e3w/Ntze75T/Ubx9EOe0cIHqHwTgnlQMsuh3jRr2+H4tz4tL/6YwaPJlDGJAHUOh/CshDS+fpYOmKhJ8v/iNr3YQOdAXIVX601Cl+rlhEt6K+tgacl4pabA8lVQzhMCissqace3auS8oWQIzjmRlFjeSbpt7oPPJYIvITLBEKe4St1PHDY6M9h5aKGAeUUe6xe61P0rw3o9fOEsWBm3mgxyQSy7UAACAASURBVPOyAeAWvbWfhUNCtHG7noNL8o36X693ednm2tkk6bgas84vkWmFrxTAer+f0bm717mwim6CL/2thhK219Bk8yderMNyl0cKtNx+C60ukdtET9Raw36ePWKbsQzGB4ghpUQUAeC50EVGIuWdiwPn+95wBvE8j37RaGAwUF5TD2R5dtmhPH4wj3fofX1jEA+dVwsJ0csy1uO2NBqzz4dynm96nm/Qsg2HjP5O4PmJTnSi99IJQD/RiU70S/Qm87Fgjo5lyo+qe+vegYlMz1sovTe4Ky+fmUy5iIHru2HGPUnUsWbABgQUvyPgC4sSrCteMEP+EQv47cD5K11xC3KvbsuNnsO939pr/R/k/fIcyUA2EH19yBM9Ey3H1OZGqmvwRAfAoJV4MYDo0KmT6nRrdIYr0216qQjtygdF+1w5Tf5UQuOO4vH+9V6RnNVyP3vhARa0zt+Gi7dNNU8atq6BuYCLhkEt4m1ZoU2h7u+QQWdouE9w5MzM/ZwV49y754snCq8YaP7y1ruEaW8NswPoKqhp+7teM5CjcfKa8l/y//KckYYcAs+3APR88wgE5594+OsPS9Mm641WZVN9o6e61bu1J248c3GP0WvKhdgJI+95uYlQ4cSs4evUI7xM+l6cAJF4QCkFu91OAJW5m35fAGroeioFVRVhpYgXiClzWtPQeKaoSGtg1WOc1ilrS7QpMzpqnYBJwg8PiBWrkq4UoE6Yeca+d1dqSeOberdaH0o7pzoNURRcUWXKLVXQWQMPKSDGMYm55TcUSoYxW+dcPjNTG0h/K4TClmc9KbCqeEWYoqP4C8btpdYht61XnpRCclbaV02v0FtSapriR72EWo89etirba+Ub6VWT3dBlDzomCGBVa/R8Q2FrtHunwBcSR5yXdedH4Fe/cyzPaRzd2Oo0Qso9qh6I2NPveNS765glBsB1wXLUg8pMKbba3BnVVQ9Yr5noD9q93xLI4XUX/Zf+fs957pf8hRp3JZkeclfzU/+Djqw6x11n58wv8BnHOLjZM+Wc/MbmhiwQBTlIMIlREn2Q73RrprFbJd53sCr/S/2ZOENbO8ZCujXZoCALnmvKq89IDgCn1t2nqSUJPl8cb4jqok9z07JRZntzjl4eVBFHqik2T6g/zi1j/aqYp0ZvYonVt/HDB1b+bH0MbP6jQq3Gn/Ug48wN7H+3njG1lo72BRWo80u3mWkYRUIcn4ViKK4Lya5GEWxDCSzpvKJtpnBoxlCsnqvdU2HQ/yo8/U6eD499zNnNXxOvPOqf7a05X8lHVxDBwp8sML8Vzy/kwhzuIz+7elCjMuvPf/vRsLiyJy2bsnemLnc/523/r1kRvsPFHqDFTHjwT8DTCQ6jnT0xzzsKuuOczAbFlvYaAm7XtDBGo5deL8CkqhlVBTcJJRakXdL4e0YXDSqVO+Y93tZBwamQflykuhWVACJSCXgpwDpwjN0wPfApRGkf9czvlukDh73wN4ZKB2FK5YzsJYqvEkJ43jhn4M3+HmiEUTUjrd0Wv6/hYzZe0Nvs4aXt388jtdrlJr+z8AZbWyh5ye5QTgRSRj1LinKKsoARAMGhKtMaAKu8r/cY7NmDkM0MygR2THOyWma1IDBUorJkV1LwVysHon8w5C15mHc7TceTRdt37OobSbrvSx6QdqvEd5+cuoFQP3676vrgI/BoXJbet781+TJ5b+8Bqzs0pDD6xjalJ+39Y6ZJz+dLCc60YlepxOAfqITnei30nt47oMM2Ts4dwvl7ncwO8BCLt+FVSZgdsIIULRvhNFLSgsBtMXj4x7AjcNHYcX9JwG3ChJMDPxZUpj3I+hBBddblhxlDwTcaK71rxTKbfNIt/Kv13nI8zy9JIBDNS0FqU8cnkcfHcJ92Zqf8UTPRZh5AJSkfsYlR748lXjRi5jcF7IQwgGACPZNARw6MKLeuD09QuPNmRW06bzVr2KIGEuqTe1mBGKCAUM84ksIzWQAAi2U3L259p4hwhgXRp8JpTCKh1KvKGB0rde9kDOIbsB5D+A8Kxhszdi7trlBIsJS+k0BB60vK3YtZKgBtmr4L0oTqHceW55zVeZ6GR0uCgWO/B09rwZwIxcEEriS7l8CXP4754vxh/K9MU+36Hd4nl9xmHSYZ0fMB/M4l5Z5SVMOEKGiSs68QJJhnrxiVd9jrlIBaxSAqU7ohbF/efb5bN5vptDanZ25h/fZ2RkEtxZFhXmkl0oRNtgAKF8fcNBJau2w8IRtNq/oKoqQqbogbfMEYJRasKOdC+TheQFfT7vdBAs9XksgaQQJNT4Y85giRTUhVp8B7bpcfRTiv4t9tRv0rCPUzDvAxiIJ9b4fWKSEsT6i/F3fLSsU0pnDgHvvSLtV4WOXFCQH0nrtEVLbvBYbqxeuL8RkMGP7GswQLd4zwnXn/iRMtxXALRgd/HCtbROjj3JD6A9Xuta+gfkCEj5dH02f0O468Dn2zXr7Cfu7B0zawAfqOL8HSrtD447zzwE/9i7K0kd0XHGk4rDp+PL1wV5xUCZ6f7P32LAXbxm/2LhcpnyugHisv0a8+Pt+OgIU/Giyc40IVMafzBFbjwYJ18o5lYOch991lC71TOvUY68C4ZzIvcej8hiP9BUguEe/ecU3O090XXlRrwPD+WHGdqZSt3lCzLpX2PtxvH+JvddPxY25Mfz10gf4sW7rfGz3kqw+8dSPUpUJtNNgEMzudW7si62NqGi7GUuyM4gh3vCHii+vW/UFB8Il/8zkXdzTFz/y+HW45fBrstdFgBtBDQGOEk8w7rxxEg81JtCJW+zNkhdY052kWvyfzkszzJR+F0/E5t7lXSMAWdj2J92ndP7SEwDGk65FyYHeo2/0w1WP/jIv3m92VuWp/c5xuuK/KB86DYPy62Qyh+8L43Myx2CXh+YgxnFLdKlqGlsLadqvJR9qnsAHgosvB/A/RLRcWAcLJn4HcU56+G0W0Na6nbSsAbGWJmsZKcGoL9mmtB6PoafFGP1ne/VniPGgfXNPwB8yecIgX+dVBtfvbY8A4VZlb2M/H/We6M7FeZb+CogN2IEvxp9AoYoKAc2regHXWgA1orP7hR+TPaxoNCllLGD8rwDWCVgTq2DYscddzufO5OnDmNc8UVNPX9aIZ9zN61zbj8yjw/UKALT9E2qV3OuSVqijt449JL3VEuh7F1C3ABL9fq2j9+A/cvvMcJ3NaN1loPfP4pA1Rj7Gh3dx7uU9jjDyYse+81HFVPLdVUnl1LmrjFs0EloFUXH+suj8mGeLrBXvkXUhSH1t0V7y6jedSJ4T1k+1So5zS1sHhBd1Z0YlzbWe0G2RsaGpV3i1v8u7WX8TWl/v/wRCLeY4YXxC8/ut3ds07osms7zH89zuX96xaXi3UV/2OF+C6Fvg+bL9ckZk+Xv89NY7nOhEJzrRMXQC0E90ohP9NB3FgCjnnD2AP/wZy3tKEZAiA+EJPBHNeQgfAqbhdY3foukPSVivEG+mzID+weJdIoop4I9u3urAZxZP9WPongQ4f6DRA/1BH/dAAmT/1XTN6sEMUShe81rR8BE0eL4kEMKEgaUn+ngv9N7DdX4js4xHKMW0vlztMsxU6NDMMz3NL/0wCF/6POT3iRvkTwbrCK4U6Ojufe51ankX9mw6s7XVUl9q3uHOCHMHABBwvTCB9TnFX18hgt4lrKcBnNZGzmK0Lg8q6E0AMibtv+0BTaOn1v6sz9DrBpiPoLrfIX9pVNSAE1jOCczI7U7jtlb68Fjemzvev3qVg7T948H60z3HeJ4DArxdg5K3uP3dyncOTJ+r5wgsVF2oJdWAjPO7ozdTnHW0eY86VVVCFDceAQCqBdQU/CokYewYDpbaPDfFgo2ThEpnyVcO9rz2RpYDnEBqGCW1dZ4BFqMN67dpmjT3ofYjK6Be5LeVEpo0VHuV/Iu5uzJIJ2vWrGI2FOI03mNKu7H7yduuKherHdC5b2MwFMci9HACB6WWcYxN2bwa+jf3ZVOW6rfOmF3plgxoenqHvG+lfSyeR0kBRKkwg6grcFrcPaI/pM2Wvmn9V+j3BCIJpc4goD+K16Yp0tEERLIQlqWgEmH6dIX54dGVht8BSWjAwPNX2SPqLWF/JwGLLyHzHADKJ9n75/vHxSpOHblQwIYueu3ZBCwUbKmvjz0yf+WIX54t76KNveF99yLmKcMVjpnfks9mnJZuVgM0P2GZ1ECLlLdinDPwY2VItb2PmidvZwYIeLIzeqGHJBhfI5M+QvRrnXp+uLGOvotHdrAyeSEv6JCx1nvGyfvtiFlkkdkrKwD84q8UKUwU8mrQSDVKazVlXDc/PFr8dqj81vXfSbbWGOO6+320Ps+jLeRGVgMIYn9dkU8O8Gxt5+PTJNQ6AbhQxTtg6ULYx9d4UAGT0vwbpmje10egyYFuZnyjX49O8FeMfTzsNzxtq84Peo7V0vOX/Bv3v7b//krSCW/yUlHDTeEXpEh4pNst/PoiyfTXbAJ/a7q3M0MPLzHsj6hTtgvZ5zsCbu0Kqxf2qhODd4UZfupBGtEEZNwKCY9WKYHn0yQGrKTyqj8hDKFL7+DWHEA0gNM8vu0ZxmUPxpCAGloAW62XJ0mfGLDJPIZFLxZifsELEYn3+W434ezsDEXfqfeGeY70VVkufS8ZSDt63LLzVCb/xsvou/cukb+8L8Z/UX/mbeG8zdhe/kn54veTLGtpbEkWm3GNgFLQWwOIFDgP726LWiZTVh0nyKK1hQ4lDC+i/4qm1shAbylF8p6bTKFpBnbTDs8vz54OwIw3Dbjvnf28jndA+mzn+5rvE4MBAdANSO79teQ7b/TpAZ7/NfD8UHmbNnn+LuvaAsa3vNCxUU/MZU781XqdvvkuSUd3ohOd6ESH6ASgn+hEJ/rLaKk0+qiySxJwhjzHIKDKedXQkik4qSSlKCXF57JCa9R4+bP9pMqpexIwu6mQXvRfh+XXFup4H4j+8EY5C82Wc6rnXvsd8s2TvmtFgDzXvPZEX4ae/xk6pID96XoWFXpfuQITAh6bYYXlW2IJLeu5WdkUoqGeZUQO1GUkgwDhD6iS1UggrJ2bC28S0lOFNRMmVNPU1Seqdx484Ik6SiF0kHrXmgDI4n0MggPpJEA6TBhXBYJ5oGbF6lJfxQB6b6Ai662U4kowBjTkPPk7GqTStZB7SSWg2IxP3Nsvnr4az+Xf3N95XPPXUV/wzxWYvlFEZrhlgsCE30Aetl2IbmQ0qFRMdQIVwrTboTd2IXvwREfFPO/RO9TLm9DbDBBh2k0AV5Qu+dF7FxAze1v23j2MouctVIFecoWHoBqgeh/C17knpyuP9PqsxljU0WZG7/J9YvGUj3WdFRxsm7UCTxEVYjCyosiNTjXNWcpzPk9uqzOtbavOlRcBmQPZO8AMU/JZp/0MgKik6AuMeZ5DKWnKF5L+yzTtJh8DbwfHeuDxP8MZG4COrMlY+9I2+5j707z14w3tneW9JMc5UG+rj6X3N+A5y70N/ukbxh8kGoVF7tgDAD1hR0C/u0a9JRB37Duja65yALjWaAHNPZikff1O92QIm2Bhrud7BvF99sWUPZ/lDbf8/hiSS5vBHhniCdvvJXsiPM3Lr9L1Io/L0ypnMeVOHfdQGnOWr4ixtC95H9k60cXmUU5SQ4bmc5ym9ntjA00kzySB8FCAaxbFZXcAfbHfp/e6RHjSXBDwQ8fSPLLsYWKwZu8rymcHxtXojXu8lmuZab2+zPNuCej71pHauWUQE2zKKxwQA0w5+sF2GaOZgR0NJjwJU4qCF7sdnvfzeHUxTSj9pVSEmSXCjRe0/e2VhuGA9/kr9NapPWzRm8/fqo9XFXN0UOBD6W++P02l4XqOObE26uU0DzWMKzPIjDd65PuMPTtqtnn0jS2lgPJkzLjgqLuzRHsZdlXOPbTReHy8l/iQ+/wY1iv1/0/REvA6UO1BPvJgtTqvs/EcNlfgUVSp5gPUxzjmb/IifbWBv9JZfyEtgRK9JoYm5HNWSM5vAGL0KJfc+9wvJPJdM/ODaXm/EfhlRX9Vr75X5zHkLk9kHuWEbV3DF/6M6Y8aohnkHed/N3zhr2jMeFBv3XuVM24ZuNY9xu57NF7aQC0998ivy3fbBx08p4JaCso0iYxRxHs7A8TMjGIAuoLSqOQn1/AMhhsimfxgfKxEMiNw0Tgpdp+/OQD1PLd0Za1JyHPjZ2s1z/IRgK6lYpomnJ2d4/ziHNMknui9Nby8vAiAzV3Ch/8COLcEDePs2J4zEUmpe5utX4+j4AoIAK9y02i7ooGbtWzaW2yQ759vGGtmWQoAdrWCAbTeJBUAleAB1Ri4tY79vN/kYUweqxSm6BbdB1B50IRFSKQC+7VUSWvWW1djbJG7Xua9A/RQPRIz8OP5WeYwRn4QzPjxMgZiP9RlSz7pEizGobWilIr9/IJaCvbzLHJO4re36xy5v1/xPN8qf+g9snHxr4Dn8Rb/kHPvRCc60T+eTgD6P5BM4ffz9/96G06hT050NG0oP7I38SFh8T0g+9YjwQCVAu4aTDKD5C5tpfYly1IiaC6kA55Xet8dxDL7ayryQAKst8StFqzzEHVInvP7N5aShXC39x36xRjKJCgPjfxIfnJh0HDNwGOx8G6iWH4kvZ5uexM813F5bbgNOFu+vz03rOmjnYtmr8YxPEYPNJDSnIE9Hw5aOUiexYeQU7TuPMX0U1ZY0vh07qZKxzBf5XsXL28F9h1YZ1IAwhQGIWAyAHSAioRyAwNc9BkKdBeIcFjNc9gb4xq8pOcMxYGJr6rGCGHdwl4zXEnhymY1BEBjk8j9vlD8huW7CX+h2DwgInFY+CPVcwwdmneH96XF9/Sc5adjPcmDZKZsznOff+Mdl0wOgDFf6bMvERnp5UrRIem9gUuFhCAHDNS25xCRApQyH5hZQuCB0EyBxQJUlxLzyLzFS1KAQecDiIASv7e5+1rysGyFQCwh5V3RuVTUOAjH2M/NZwd1dmUBabtdyZoXmCrywLru/XsaOWaAbLXaOEQ/0moceWOuyDzMEfYYgHmLGnAe6RHUm9/3QvY+tjaJ4Uv3PQJg2QeYMWtMbAJAhdCa7VkBnDMjPPw5WsXDX7hSztaR/ZoBG19ntvvR2M3d5iqgcKn2JkOUlAT/3eofIYjcZ+Fr5nuPP0/+2xggegLfAYQrlBsCXV+BH2xsvonRnO5boVCKDTvniKbVeEbY5jxXMsD+nRgXaS2+RgZaX9Jx5Yf+OOJ3C3m+FRqeD1x/89k/KTj4OntDeSvLzPo/Pc8MxZw/I3RiXHZCQxfv8zRPh/q03ReIFBPfoee3K0QX53+au3me5/qAFFXGnsvjM21hnIHw4nuEvEen3M60f2z00VG+voxkhLAlH5rHZrxbvDmhnk1oz3vbGgEAP172bz7ZQ5ljsyeH9r12eXnf8vpPzTzemGmvVMSAGiIc5vflI2/UY/stgMU68TMDG/3DeV8N6iwGCHPvqERxPgAI7+PFvYQE/sQ8/aanJEhT4ZiN5EZ70nboc/DNyGH5BY+g4/my2PN/bgIcT5z+wzT2w+arJb749zTITvj4/Fuf95+mDJoALtvk+Z3XEKX9zObJOQg/jumhd8zVfwodkrEDDvyMz6pFuDeGDUDxOCMhocq3AsJnVLrHFw7w/cb7jTwaAIhwAwHRb0HSlg3Qy5/KkEhGJc5hAlJkrORhzRAjdjsve0ctSW2tjGCcE8pJHtivyJnVkWE1nloMfRkdPfHm6Sx2AK+oPCvGTtM0YTftcH5xgbPzM/eIB1uUrdQPB/dS9n3ZGus+9WQezPZdVsHAJ+R+6x1NX9XyuDuDcugs3tCveN0HWvwu+tB1tyEnIKLxdX3fakY4rSV1hjgLFNWlrOuJT/4UnbhWr+1DpYiBOJGkImBmtDa7vBW3h3e5jVlz/tGcCd5DIZ/aEwoVzMxo84yqBnh+hqze73XKBiyJdR/0D0PEtQN1RIQ7Gu5ZljkEnh8qc1jvG88LqTHavqwbiHmfLhx4oxOd6EQnCjoB6P9Q+lllltz8a88+gecnehdlRjIxQcsQUgA2rx1ivrbKDOVZBAkqBcTmJQcYCAFjtNkYLxOY1szb5nrTS/fInujy15jhWQsVaBg013UFIPMFNFiHL9/znoDPXep8oPXvNww8FMIjpH4L7e5C00/RWrVJJoCoYoNYLNFBwJ8qvIAFPH/3HvHGfmYq4WXgQg/UlfsPtMksr9sUQOEgBSznYAbCLER0Umi6kKvCvsjo5IogEY66qyyE2vh8b+vyZVjfW9rREECT5d80IUz+m0O0G1gEgA0gaiAmUO+Rl12fW8skYbApFFhu3S+SOLjDvbFsdkXYvwAaOhhkRtukLaMC1ojNVBjQENFNrf7RAQmmrIIfW+5zxLXopGGMGYzeeiholvM+3/NBAtIomC7q3Nzb7O/G/jbMzZyqYFSQbK3pb8z41G19jB67sstdo9xI6PZKFURVvTzKoJwmIgmlzoyz87MYt1LCI7sQKk0K/jaUSgrYikW9gda9d72/hKGJAU89/DtL1Xb0APth+y/FfXWaBhVfnQp2DDz/+KHPFkB+npuHli+1OLBvFv+2Zmud5CxoWl+1UPPw9QuY54H84lEnbARsP3TttgEVpvRnN1rJHlNgmatmxNJ79wcbOOzaJg8xqCoi9XA2RQ6xqzhgmkTqQJstYPM4GzIgPrywKXyWW6SfV6quY0QhV/Ax9vcPufj4zFRVf4i5TiS7VewxQOVrMBGKRk9gegKZd7H2sYUgdoWZbLTatk9gdPEsd+UPgzEnZTxrxBSpR/IuH9gvFvrGpuBV2dhCLgAF3s2ARyoIwJKTp7gcoO8Bz1+jpW4yR4SJ50WZ14D7S2z9tt7PrpiOAuKZEefm0OKh+vxn2E9LKi6e9RHh5RMIlzonOzjtfjpnmHHFlh5E6rE1Ojxw1JT6GlwdFxzGlbmltnTM8WnJa+wY2EPTDOhgXbCAm+4xB8nRau0uaV1EE17p77RWfZqRcyfyXx4L33y5tdfC3f4OzGr4CemzEp1xkDKIDqy79rVv22UP3fV6gR0B++X+dvA21ueTf2dIyhsBRWi9qEIDn9LHCA9H6VAoBtBozdF7HJ54bijCYuCImENiHMloahTV55xj1fhL9kaQHJjCd7HlOofzQYx8lkKjAQEOzHZfLYvdOugQPx+GH9vlDukprru0NXu2vwsof32ywTT9K4X9otgwvGkTuoSAscvHrO5j3vz9LSLNcQ7IMBZa5DqHnVuxjx1s+PaFvzctxsVOhwBPc/os8tzFVUMsP2uEnugW9qg08m3xd5Dn0r8FvbsXj5RzN5cBQ0OnS0j1j6DlfD/7178AAP3Phop/gfEn/qXtKQAa/Yn+lbH743+Gs6KX/9VPBMJnEAn4LpHuCFMtzk8YeP8vljn8GYQHRdc/6/54X5TXA0lO8LmBpkny13OEjn/T85gIEiTNWhq8VvxlLytsRwWxphopBFD1tdZZcpT3Lv/M41xAZ/g+qRVqBCjCrorH+XS2w9nZGc7OzrHb7TDViloqOktu7f1+ljDeLYHYi9PJ13wPHosgBu1UqoDvyTPf0mKNOi946iJAjeUVOG+W/5ptT1n3te29S/0bEanl9WIfTeeJXnl13Mayh2k5/MtabdRFnyD7AUPzywOoGjFM9gt4jnBK94RRMgBNDwGwA+pEhKlOMic0LRlIvNtb774vERXUWlBrxcvLHmwHKS/4C9vf1RhDzmmgyOxFB6O1Mcx6AONZz5S5iWBOCIQ9wsh0KgVNn+OGJ7Ze9HbzLDcjGK93cf4gH8kul67HhwHXdflvqtcgYHNdL/VyyzLLfOev0WA8EuLp0fRLeMqJTnSi/0o6Aej/bXQ6J070Tvolg4kkzPDG59e+Z4vY/PeYthqv54opDU1Nxv2qhtmU8yACZW/BI56V6Q4BohMCQC+IEK3/fyf8IJYclNq2BxIP9s8cAPmh99qxPAOIZfxAEjLdbnskA9HfoYw6kkQVFw3skFCMtwfKH+U5dfTDQ0k4AKcH5sYhb/NV2/T68WCAzeHFs6Fe4N7AyPk0KnOWiluMawRJRKHxPvfCU+Vg9hAiLz7UENUoGJ0zgzWQG5YIzaAGBx2prKry9poXlgl1pugy5SxjfW9ukKkSJOK8ek2lHsqCvgPz+ix4v6+FpF8RhA7ee2ydWTnxE7cfSyvFx1ZTABCuRGlwW0UZQ4SqodtNiWAKAps7pRCKKg+GPRtI+cVTG1jD2Vk7NNiH66LVIAklDEsC7FTFhoHSrryhodPMk8OMSBwPIGgoeHYBvhQCasG8b2hzR7dNXcEoF7R1rdp7Wqhy1XaMa1Am/RjG2gDnxTgs90gL/SypHBZbMtt92cM11Wvzm9Ma0EawpyWx0TbNDaVrC0qKnREUTPMoT+C0vnioMu8x/4+9N+2O49bBhB+Q1ZItW5LtJHNnznn//0+bMzM3sXZZ6q4i3g8ASJDF6kWL49zbyInVVcV9xY5d9wzNf3kmjftqddl55TdR09x6HcAs3gmMe51azm1mPgPhTN89aBllXW8Da6PtDwbwRFChrcAPEgvnJ52PMy4hBIjEGvzRKQH8AOPjnnfj4tB2shOAexIhfX3nlAzZ8h00E5T32mRlPXZacogV+6vOZSrW3q1gdIL00cRRp5CeWr8+Mol3huyCfZcAXR91DxVsUhImxqLbX4Z8IwK46Ajh2QnNAeDE7s183vn9X8YqMWeG+CHQYgDyrG/zWVpEeOO4QYyr3PEBpMJb61PnonWQUMdL9+/9MPdKeMurcfPCwhaz9T5Q8z5LbXw2nikqsEvuXzBzpaTDdrHZfaR3oykrmXIokd00aoWoZtMpu+ot1onctGH+u5/upfj7GdTlO89pO1//G1IHc+C2L3tlyin3smR+Jci8Gr5rpwCa+/792/GrgKztYKgZGKxKvpS9adJgkwAAIABJREFUUIUtM/lj133U7t1XN3g/4c5WYOz0QHco+Calq6SnRFT88wvABMaVb0L+QRrmqxoquslh2JgZd0S41HPqngpNaQYCGVckMS64AApu7c6a4lWpD/bN7wNmFiVuty/YpW9GIo9FyDQpZfrZ8iQWgwoTnk9THfe8ByEGxCFitVphtToR4fkwZEHpOI5YrzfYbNbYbDaY0iTWx3YpNsWXcSgnVhl/O/cbK1zUZ7SyHYqgPNV09T6EqKdjKn6db5q27203k2/DNnRDPgQTluq/1hq7Izl7EIOmD4b6ZPwsKzCzKkViynRu4gQKlBl5FiLC8kcK+W7ebDZF4cLqtIp1zpJOPANIPOX5TE5hYdtoBrLZNmyuUJrmrt6UKzL+iGUepr39CKFnqm9UXLd7fleXr9Qrm+aW5/5b73lJwL4rfydT1a6jsd8RjnCE94KjAP0IRzjC+0KHmdJzobOvMHQfmDMRS5mmqc4sMa04aWw1ZkQKQqwbY6xpwzaGhrlz9/ESTQ5AARhZLd+I8JEvscGNWqRL/KIAJUCZsyA916t1xIpRB5xDXcbre+9q7W7fwdoKy/29137eEnChlju3OxUc3qRRqEmnlzPjrHcPwrVabF9LhBLVFnUJSZjnUMEuGo3iIj1aaMlixXtBEaZLWfP2FhKzFKwCOSXFjKhMnBAikFJANpxlrlzaccU05swMFIag2aVSro79/8ocVpu7XGaCI/Y1rTHOSnVKQG4Rou8YqPmYcvPX+vIKsGr2LuZARukZEyJEoNPIGrXes1y7ENlR45gPmchmrmOfM7MwDRji6ptIY2sbkQukMeWzM4SQhefFip7VpbuIVMTdO6qYdL5+m7yQY3jXo5ZdkDdjZTFHrT/juAFgbuUDhtUJwIz1+hlpYnCaQBSwOolgBp4en0QQoW2hsRDsfm+bZbq1LwvEtVE5RpzjnpQ7goplO8teS8pIgzK4vP0q5WLKGIxmmaD7w5g9WbKe6nNmGRh8tyuV332P3RSyrkJm76UskD6cnWYeJkrZhIkexEOGjkHQQyW6GqT7cwZebb3n3vH93MJcoTCK+uWUguT/wLXw/DFbkooA+pF4Jlj2z8RiNX1/iPC5+duDO+8S3P6SEySrsPyMRa3G2nSm5hq2+xLqmOwPJML2Mw0T0lqmH6J4VuNxTZ5KUwOzg9MLR86YsjKKu4KqdGeqSPIDCQmMMxRPLFnZIdfdFEQAawx7zu5VpDxyWaRflq8wSPN5xRKbPYBU8g4wMZ7hLdjhtrs15KCbow/cPmq5Os5G+D/++IEYCE/PP7BhZIXSs5MTIDF+rNfVPvDYAwCsHAufIcOUIIoNbTO2rpJDD49Xgrc8t/nqNWF+ylA9NQ2dYGcPuZMtz2aFfpVzxe7vjBuJq6CCRdnaICou5pOekWZCRinjZEV4XjPnGXD7zFVMs268Crrx0huNrUeiw+pry6R2JbafX0YXnKFu15KXjn3LLTa9sm4Gda1bFIKkrMQlTm0OgQTsMSk/eeMcCAvHef4QdP0GqPAHDgth9dvFQIwRAcCzejpawpftbTfO9BYk5b1GcRdaf3cAHuDhK4sq/RXdzN7Llg5gJJz+sQIYeP5zA6UEdC6+Qg6LKw2nQxi/T5iQIGGG9DsYAQGMqyxEB0Qw3qO7bu2g07H+zMLb+AzBMR40T1CLaqhHgYofBABGD7L7nwBOwMRT9rLhPaT0RrI6cq1pSnuK4FzmaDIadItA36oS7yQBIUaEoDHcScJsbCYRwI+bNdbrNdbrDcZxxJQmSCz21MGFqhpcXeWuyeRVk7YSMmYlhdQet83Sr3tY87rME2PdlqXbMSx140Bwve6uKztHQ+6zdHc9bkBEOIlDPk8ZEpPel208C/MIZkLtMk5yHscQAE4INOhbzvUzdP4pCJ0MYNyMbryQ8VJiFZAbfR0o07KBAtbjaC2zU7/qb7sKazy34GIyDgmBxBL+eVxX+T8YXtyUG9ymME9IVnLXQ94CdFdF527fVuY26/QjHOEIR/hV4ShAP8IRjvCOQA7RK4TDEhHh3+9rbb6z/uJDWBDZBLE2Nz+nAeIKNwiVElIS9lcfk99Kbd9SiRPGro0EqcdioYdvASf4ih/X17nfvknmlr1YI0mZFscYQI7Vd87F2ochxC0gwvj7n4SH3hLw5edUtRuYKwKyp7iR9Xc95eOLcJNMqLVatYq8pjVRxSxiGIOscQNLZZ6oqbsIFLkU6Akz2xt15yriROrlqj3gYr2RY6Ub79QYEwAoMSZMwjAhyGKbimtrVk19Y0BY/wLUY4RVR3VrrA2mDS/0elFS2cpCcgRjGQw3B9qGzBDOXe4x0OrKlphbtbtH7v2ck70LdfcEc1VfrB+tgk67HlsCtGH0zLXY6z4knhC4uFeXWH8pC7rN5XeIEaw+ZcXFexYLleHTuqZpEsYR8mboE8oEcV2seb2CkbWd3G+n4VSS+Vh1pPs7Sb0UTNDPgItNCBKL+xA4r11kobb8DlSs30OohefSxyQMM+NNaduNIdMh/W1z5/PZrEXM2mCaxiJQk8LqZQ4VZLEJ2qSudJd0r7pZlqDis1bsAlst9VT03P+3+R4ARBA+QXcxsKMF2/a3DpUDi9MslplJz0SZTtYzUFO6u9WK0GEVAUVmlM7j+ME9F0snE3RZn5rdlI8P3asvvFsZS27St+dxVVfgLcd/QAT4Z00s9h9s+6+UKEo4jHBByhg+R0qMzc2dWpFyLvMj1ENPy/BvF+4SNPfUvIN2hvQ+EahapWJlL6xiNG72S5s/JMrCqORwpB+td562Tnf9Up54eyGb2rP7bd14xRlgfl8XKzq453ZC3wZh810q13F5u7Efz2vwyarkc/dIryVWwgDAHNT4umSc+3dYv6HtvXUY7GslXc67gv/tU/G+FsDcPM3u49kaK/XbcmRrlw/bQaRrkECc5F4gEiE5EULStQk5Fz+w5HvkVNVj91XBu1437n8/vH/L36SGZnm2cWkNn0plRe4Uuv6nAanwnMiETHP6bZvl+ZaC/8kLfCswbnDdHRIGa1C5CTcg+pcI8vBvERDiKwRjvIJhjkHvs9W3iKfvf4LZC6YvM95DJDyFAAvPxbXHPH/e6912r20CRMlfcOYg4ZViKO7JFWnPdBWL1a95hjIcPTFnl+uAefIzxLz8MTy5HLMFp5MwF/J3SjVN68/GHgguT5lWEEUAFTonxjiKy/bN8xrrzRqbcSzhmhbKLV7s7N6tvTEVIXnNF5Mhk3ETtoHRwSpgzriHjcN25YAe/GoeMAqdXPArG69AIVuKkxtNSV8Uke2v0QqlcKuj8DzkrylxpGz5numy+iRHmaOyHUTRXLCimOeRqlx79BymhFWD+qEhwnrc9DJ2SqrhyQ9V06AlHmtw730aU4Laqx1bBOet9fkhv3+tFXuEIxzhPxWOAvQjHOEIPwVahKknRPfCzm3I+94aiiT/OBJLtUFrXnBUS0SxBKCsYdpt5w7C/JbEEj0hqPtLwPRNbwPwdQL+z801vlqMaMfMMssdAvA5lX7ekQrmlY8blag1AvZSn+3vLYS4fRt27H4wAThXQnBQ6cJ1E/qUGfjMwEMbEvXFUFijwALTt7POJE/tbhmAENNwDPIs5LJnR5BxIZLIEU5ZnisJyzf9N7+vrGQyV12ta+u2mUyxdafqnxkAUgLBKapYHSy9CqbVrkKpoAuKiDEiISTxhBDA4BQQsk9ajd8Js0A34lVF9hREGOPoSFMQ8JYE4mLUx4OTscvu7/Pc1EzGrvDZCzkWzorKkof9e1/aAnNjqcy85vrPS9l97w5h+8+b5VauMRLcd/n9CKgV+iTcKCRKmKZJztiUkBIjDqIlf3J66gogpMni5iVlnkmp0cU4J0LRsNd8RoizF9gRivt3G5QcfM1cb5e6czpdXwTqWBSxSyeEu+07KDNL2huVKRaQQtkXw+qk6Kqg7PF2HVi56/UaAGeLfLPUN2EREaEEuEVe7zZWSd1DjspQy/uQZfQqS3tmiWFXWYxz/paZhODquQe85al1zN1bbcs74GExzTYGRr3vBExYLv3TmH/smFAsymVmRVEYXSXGt2dLsROem5KOKS+Y1wqr386onNfNn7/mWQyzjI0FhugXfdbz/GGHJdlZI21/Tezz7bMo0LbnE1Ol5JDda18QwnABgDBONzhZfUW6JCQGzkG4uUu5jk+Yu303Yf0h7ty7kO80m5x8scKszzzcQ+ptcuGsagbjY9LY0PucuZT/KSUke60Fm+KLueQkey0/PgB4hjuTM85m66qp03y6+jtMhQ/Bn4u+iQeCL8P2hcHw4QOICNNUzr4VgPXTuij4NRBRhOd2l41Q3NU38A2Y7zz70X4v+9eS5SsE7ojlOn3bxgo96OD33hKtTs8VbQFGvnu67U25IRlati8bZ1+RG+mT4oW5bK2dXGgUZjxYRhM6qaVmXloarD3TWE15vwzsWugLzd1teS5fjPyIhjdAzolnHQ+7nz+qMGVkwZcstMGuhlv9qxD17ilrxn6b1flM2WIHfYk69T8EdFxCPT6BQnZ7TfmQt9jVRXXZYp4vnSk2K9xDMNrfu1//BNhesynhL4V0M+H5RXOcjHSLe5J45BGX+PH/nhEQEPAVBMKIv0AAPv7xh67FJHQgCY59+u13MIAhiiAsJUYgYMW/Cx/jewJwhfN//S8QAcP/fYQLLoH4LeD/Xf2V+1C1Xw/kEAgxRLHgpqiW6AUfNrwtJcYEVXxVHGBKKVugA4AJjynYaV9ugqyG5M7+xMCkwnOzQJ/SJK68U1q+spyCMztcx9bnNEkZm80am/UGT+tnbNYbjNNopEwFPS+LRtWRPuf/QZler5skdIgJUAVpVr5Tmlxl2m43DbkvucOmBP+2G8XOukzuNOXkHe81Bvx7/bUKMd+3Vi4R4SREpUMl1nsIgjOJjjRhPY2QNVDOHdMr8EHtAghRzyJTiAAor8UxJUcfSACcqoV5Lo3ulfFMYEyjKJoTgCdVVD90QG1lDzFimpL6VbLarZ9l4M6SeIJpLc9bfPlRiU6PI1WVdprZw0uBufB80X38DgF4z3X7QWXmf45whCMc4f3gKEA/whGO8H6QEeKC0SxZovfcuHth+kHxcBw3IjPXjbHGDAoAJzIeVYW4h9BDDz2BxovIpYE59LwLhHN2nhaJcBUTLpJqTythc0OM86ZYszYnCDFq1u0BwqwMCfhMFpvMEUbWkZ8MZu1+wQDhHIx7fOa5FbyP2f5eYIRaNeduPS1aoqOk35rOaUILQVbYqdQ0wPJ6IsXy+Dbl+qysapAoEzoV+eLSE0qsWP+/lCUrK3Eh0oUUdCw/FgZh4oTIEYlYGIxuTLJWP3MmigMJKZo0P4EKM4wK0zCpu/ZsbSNq4+LuTBLkxI6d7Ba3J56RN0e2al+Yw2pzuKlpmQWHWJ63Ty0TtC6qz8kra6zHF+QqTZvHhfSdM+Cbd3yXwBcA8wRwBNRygnl052LbRlmbFiM816ZcEFIqtV2/yHuBchl5QLxaftMn9mmALMAXi3hGvR9FASBbXthA6Bqx9emBgjiiJEifevo73ptENaRc6s3tnTSmeeLyLZAKgmW9BQrC6GPGOG6QNLaiKJAE9ZXNZYlbXgDplps5Ked65eGgx5VavJget37dlXsXLOWbtU7ba+62hQFYfrtDNeMNlNddYaoXK5Ky2oMOpLlnNIuibBWb16a1zfZTOUPlOTe2HD1OYOtX8UvustcInV+S106nsqQZE+zOmEAUEeIFGIzV6gse/vyOROKu3uoyoXwrRN+lPABgMW74vKHzhLKd56P8ALFEb9N6SHljSd+fWuvzNnNGButT1LPnvPKXtSsL1GGu4qW+qPd/lolq/06I8JxnJdU1UK/eF0Iznl6RwIYmBMLJ6gMenx/zWTzCC8kLDJ33jKL4+XfACs6iHu19/T6w+wwtKdzVNMM5qHkv57kbXY8b2t0GWxtUajLFI3dXAuUcKxb3TmDbCm736tnfAG+yEWrwVpwmfC1YcakvObozBFE02Q3SYIYLEaL/ZkG6niG/moXnzwDBOdWS19FHvTTM+0/9GcOp9f2zYUlw3oLxBErINztvRDgYvwbBeUvIczCAjeKiQVHXyfD9KQltoIrkFnuZRSyL4VtAuvqqOGvC6usA8zI1fWdERPwP/I4RV+AADKoIAcjdMZC41x6GiEgRIZo7bLs7OePMkyqtiNK1bJyUSiixWmGX4LQwcz8TM5BSvtcSA9NUlLoTs8bBthAYRYic16Q7K5jFK9U0TZimEeMYs0FGShPG9UYszzcjRhWqAygKxECXl1Xq41p4HsRK39yGt0JGE55TCPlCJ6qVfFSVyt0lWwTlPt8vczZxvkS9nqWNgXlXAWRtgABORWm2KamwZtzJEoyOJfMYKF7bDN/LXvfqJZHH3xTVJq7jsyfmylr7pRCIMj3Zzt7Uwb58GJUzLqETPOTbzl17+ZviIe062cfyfJuQuyck3/WuV99WF/BvjCsc4QhHOEIPjgL0IxzhCO8KM+LYCcgNWoFlm3ZW5gFIqbnQzUxco7uCWb4VQiwEKhrPrl2GoJcyDfksQhAPFn/8UonLW5J4YOeJcUeE28A4T+ayXTJnK3NWWaLGz2SIxfkXFovuSy60Ymb4a/4vWuY5F8G1//0z4JaAc9yBQN16PzuEvidgfxkY0TxnxOQUC4SrZ+C01sie8c9YCjtQCCrWuH0zy/ZcR0PQsRPAtW1shPAlkyfo5wxZ7qzHQixRLrduDasruySuvllcWiMF7RxVzAVzZyZlBgSaMKWQK8vuxlw7RMCuRCzpXAUCcQCSxIv1mvLGbTQLc98lGfPSz2Xhed2GHk+g1sRvEnle9hLTYYvwvElY/fLJZmKghXYamFBLiP4iSCrlnMGUNgrPwSxyGXGIYERMaUQIEevnZwDA6vQE43oEJ8awGhCHoRCzVo4yDHLbG0Unqy3vqSRWG5nR0/aZAFa3jOM4CsMoDIiDumWH5Su9ybHalQHmJBHVoPqY5bkfgbIlfi7X3Q35xgolv+W12MUmMDNmH7mYe35sGAlpmoTBogwZqU7mYcyuAOEszudMnzyDbBvC7fPO+ckdd+zWvXbdHc4mk0qX8jHqmNXVN3eGGBPMu7LOTCoVnhtTywQO5urV4NHm3dXOJAJLqcncZ2p/yTHh4O73WR8YWcJoQISgzmTP3H7bZ/x8zHEGdgrA/UrwZ8UZaC+BdQv3xDjTbZK0HQGOEUjCXN5MExjA8OUc4HskBs5uJV/QcnoW7x4+8byNPSFJnaDcSZZD/pR7sQeTzSvK3+R+PyLhI6vgfG9w54xdxdWMACkHive1zW8IU1gDM1YgrAGcgPCs58Z2Zh/DC1O3JfUy16V0+e7W5xUR0vOzeCiBWM9v8v1e21mZk/eCqWj/tDxjJIyHL82qTS+BvRyX+gOgAtvHbmwWzlT51LTUJKL+lrVzQ++Solrh2tE0q8IHaL4PylGkJw6VfeGVRH15VXtboXlPUeU9BCYtorMDzljPdH9hkR/dBdibHrR5NgGu4BhE4nVjaFTrEsSbiQgwKG93s0S33V+7GCcMMWQX0dI8xR9YFEnlt8c592v3Pw2C4nu2y4oARhaGiHllgotQqqz3TdZYqPtfWZwrvVGtG3SzzT6/nvRcwnO257pg9VTn9ivBYojvByY498J2U7C32OjnV2VtBnxBxDcwGDGoxfnpKZgZ9//7MY//8K21qpX9kY0Avgas12sQmQcHwvQ9IQIYr78DgbAiUbP6nShbyz8FuUdijAhBLM9FQBxyVea2PbHQA0lDLyV3blU0IlV/kHHpLBx3sc3Z3LeLxxg5ulOxPPe46dL5r+2axogxjDDLcbOY32zW2Gw2mKYRKU3I1uM7zicrByYQVyXn4IToPrwUUSmX8vgVnMUrmcpeMjF6ZwdwOftJ8wj+XbevPx7yt5B1dTqLfiV3IGWFjcVxaJ4HCvlAsH5ZP5jFuptRXKObt48R9bkxr7Io8BT6ljAMg+RIwsUZpynvlzKqfn+XEFGk9FgCG7tE2pJMXbU7gltPdilXdnDiNPOAMqkHCVdc+yML0/3xmDzuueVQ9LR91yOSKTEstH+Jd9vj87bvtwrJd7w/whGOcIT3hqMA/QhHOMLfDl1L3D3zLQHDPIORMyxShiYVVorQLWo9yKzCGbGK3eawrzBXl9nogcXQ8BwS0/xSOXSXINwQZwLaa5H7kjwvjyDC8wQgkshRgst7nvsof0xw/rNduQNS7/kCVu0t0BlvKUSfQ8s33WaJ3s8/T7dkiS7PhVCxHPYhE8hoV4vnFmoby2OeT/vHyuHqve8w5R75tUO5YSXmmno60/aLxj+Cuc2L4GDqAE4Tm20klHlLjEQBmKZMmNVu52p2sPGBiQiB1cKYAErTfBa8cLsRbBeGsk/ecsx49nOXILz36PMsMpq52btVul3527rb9WUMpH7VQD0SzajoO79mJG74Zr2WL8bopIDVyQk4JYybDVYnJ6UsO1uonNc0a58S2zGqEEFd4nnC39KWAxQgiYO5Wq0wTRNSkpjtotQxCZMIKKE1zPueBVRvB4Yox0qMMRQhu26EXI4xzTLfzI1cZ6yTWbNY3ESrNzW3gBOip8wAFGE9EbQ9dlhQJTxfOIny/yXlY7+Ry83fxV/eCrvS2vcl4Xk3T+c8Lmcpuz9ufeXneT3GWJP/LdyE33P16VuOlv65UVuSLjBx9uuqlPfKe46bv4fkS3pmRojFsI0gUcyC6Kp8+owQhKEug3iP80S4u9vuxvhBFXp6QvSXAHW2t4EX5p+pm/p2/T1S2n+O/KWJfIS5dWLPyhKm+TnvVQXYFWS797l3XuWKmwY0KbD4dbELs3H3W6E9t2v+trxbuffGRvbrZERZU/8c2Hc0d8FSfq7wgVaQXeWujiYTXtlHyhPK7DyuANBgUzN6odTGed2h+XfpHnjZDv058KZtU0TIFBCIAsjFuJX6GIGdgIzd+V02tv6l6k8lHM+0g5uZ91BW+MWAqJyDgQJqGp+yQMzQoOJthvZwlZ+3C167h9+T/lwCE5QfIjD3MHOPrnBHqM4IT/tf4hrAFxAgLqmJSjxwiLDXFATNm1JKjBiLQjgBWAUJrBSCefcLACUg3IEpIhAhBkKk3wAw/sA1bgPE0xjEAl2UZEN2zcd6EDKLgolZnk9TCfeVMT5T6NaFk7/qecsqOJ+gAnSHqyeGKlc29KwXnm8BW79TmkCjtD1lgwvOIZqY2a3neX77XbueJkF2SM95E56bkFxLLNbnhS+R8y7thYZ27iZBY37gh+Nd9seW9rp6HUtD3P9TwPM0uvki9VJgpW7DoYoHPrPsZ2ZVVgiujFy9Ko/It2A8GKUvktIWFKiOrkIicI6Jsd4xAtu7L/M+5fVZ3zf7TsssHRkexwsJC53kz3F79r+5835W3RYBOCnt30u/zevoVh7xUbB+hCMc4Z3hKEA/whGO8EvAW1ibv7ju/Nes3iBCpmQuOBeYkA7JlPd1uhul9T7r6wTgPEks9EuW75+5CMIDiltta5NYdAsMysS5JuCrEowRRVjd4PBZQL+vS7i3A1amxAIho+3quZZ6bb3105zQWLJE310alEjfbk1n89dl0VLJXfPiTABXGJ2eDV+ea0t2BjpcPVd6ZhQq0Ugk6c0iRrkOJrhKPEns8yCBAiLHsh8SMqPAxpCYkAgINGGcAJhGNCmZalrFxsjJZiaFuVCYwGO9f7iQdzMhuv1RhkMvtqiH1/Art4k09y3hNbAPs/WBGB8ZiJX4w1mBaxHiBrDMxTAMSCyxvadpEmtpZsRhwOr0FOvn58xAoECIwwAow0GsLoTRKS4NJ6yGFcIQMY1inWEVhxiRG0Jqwc6cBfdBLSoYYrWUEuPp8QeGlVjAb56FDbFaDeLWPdXMHrMMD8qQS9OUmVmbDWMYBqxWqxI7EchMkUo5wg1WtlK3vZISNpt17gP5ucnMOz9xOgvK3IlqVU9EYnHPQEiTCOO+FoZeSox0lyqGlkWiTm1bXwDb8lHznZv31PlmcIjgvGpPo4hRflvl7lZjz0qd11cxRL3wPDOg5o6pewo6/T1f3pkFeevOvAWzVGeSuOfb0n4EbbXuZojb8kPgDITIIty8R8In7fvJhRwCMV6AUfZPlgOpFVQM5a5ivgDoFpcXATe3cwHHZybcN+7egXpPnO3RRw8EBohBiZoP8/s3l9sUknUuqnK3ALtCyLZ7jd+ZNZgJ0q2TTyoIyJapWvepFtyGCqi1tKzO7XPclCBvFlzZV/xQBycgUGIEaRimp7K/GcBKr/y8W6hgFaz9YwAbrcgiey5W+N6wOGSdxVB9VQvhxfbWI7l0F+cZZ10TOd32uaycpzAASmpRKAKRxGR6V7ou7EHxP2pXQrlvekhP64WgtPF1OEqnohcVadZyZ1w/56Lsx4LF4yEQiLBWjxsrh574ETLc1DxzRMV7chn5wJR3xVLWMfohqg42LzWOu6uVbzwvPwlMEcGUbwUPQsE94SaWJcY8IFaWHpZ6z8xZdxLE1VL/xMD9AW29b5GerfUfdJMsgoVrs9w3+uMLX4JQLMiXYJmen7f4G3/Dd/pe4Xbj9xHhC2H8ISf32f84y2ubwXowqcUwE9bfNzj7/VTiLxOwWgW1SCVEEOIfp/j3dcTXIAL0FX1DpIhECUwrnJjAl00gSYqrUz7DTBhpLtWn7Fq97EhWvgypZXI+ZS0v692UxPsDcxKBNkEFnlQobXeo8I471+YquwxPnOOeT3EqbUzeit3RYlyUbVnxi7lwUDpobsEDilWuKDf0WrUdvMen3HMu/TCjEaCmp7IHOVeO75IPgbFvW+bgzsgm+8fhRBU8TElMx24z4keLCoIx5T627dB722FNBODDyQlA0LVhtFzCZjMpLVqyT1MCRcX39F8RHAcMQcZxTJMom6g3gGeNdX4CUUBcu7y/Zy3uAAAgAElEQVTboGAbpd0JCWSKXLOUS8/lrbBu5FelwOFw3PJzPo9Lx2Mb87yqdwvPYhaGoBGW78ObW0zzk9HOIxzhCP+9cBSgH+EIR3hXMEHONuF4a+mb8y6899+WahWc0VltdJIzUGGIFaNGsW3iJRRyN2T3tMz47Bi5vu1mPZ5xdgJu9O8Fc23JzeLOHQG40gxt7HSwaMqK9XuP8PrPBgbXPGhn1ZiNXrlviZ7LcPOzZLHes0T3bQC8cNgTeErMWPlNnlY5o22DJxJqYXqxLC+MVeEykDKZfJ1cD4i4P9PfxqAyAlY5f5XWPplbbhAmJiRMbkOZUDRkbfqgjA+RlZqA3fXN89Q6Qq1cfz3QwvxgNO959nNuibdAdFb8TV9O5zd18sylqMv5FZYUcHqW5712M4s98ic2gvkBhLPi6vI2IXwh0DgBQywM9kDI04b5vjDN8DDEignU61dKSVw7bkjdr7v+WVrXT2ZSDyGoPX2wWnqDsFmPODk9QQgBz+snXXcbUDACPICIxV0iEZgJ4ygu08c0Zheq4zRiHCdhcGgsQaYE7xaRmVWJIOmzuJAsa9zFTtf9UbtKLGvClrNZv8j4bDCmDU5WIrUKBPF9yOaWnDFNI0IA0kXIgnRZhQ+ubDf2navp0JvKrjqf1/6aUPyjEwi0jKAsOH/ZFTlvz2x9WydLDPtFhlFmtnJ5Zp7t/Vk9HcaS5S2tMO5hybZNIO5hn3T7ltW2YRsMDIRLQmDgK7s4heETQhhgY5sFwi4ed8jnNFwog3NwuMPFRcDNTdm1ZxALnLOO5Tngz3PgDPvFTa86+0LljFn9L85ffqfEoLzmZV22pbPeg4kEF3my903K7jTy0gf7uN97dm+NcV7ax/ksm544pwEXRjoBav8kwx8+nCI9PWfBxaY7pr8WB7N3khya/9171DSS/D9UJzKr85KXiycXyPqq7+mmqjc6o98b7MTPLt3fHEz5zwlYuODkWZ+Iaru/GX5m7XULpdBxnrBMh5zu/2yoBCRhtpS9ReMuvHa5Diu05PnEopDth/1XBRPkMWor9Ak3ICxbmL8ETLlH1vEVEoAJCeHqAoECwtdiAcppAkIUl9wkoUpM4P38158I+IYAIP5LehBNuBsC/r8//oXxKuHkt5WUGwKm6wmMASdub/T2kFiGi9LoxCo4T6kopFhmAAiFrs74HUOsdJnV9bvQBCmpFTpSsRCmiIykHzKOLPXGEJWnwJh4mit9zGhWPZfRP5er81zXr7hmp8qFOyADtRSGDgx1WW/PfZxg1sZuKqNrUP2ln7W5VJnazg9TLN509sRhJ2tR6AdDxhYka8Xm0RTGiZBY5jtpeDvWPAQLR8F5HZKdPW4+zfr8pSPm1X65TMsBvZ3/mj1uaZxP5tfdPjHPZ2U5Ybl/XhKktzy43u+2fACv9vJ1hCMc4Qj7wFGAfoQjHOH9gI1wexkKuSRYsm9v4QqPAXEzPDUuEQ1hJSBqXOiEFrFD1b7s0igLvuTvLeCEbRL/PAH4SsAVEUgFg0ZMGw6YXbPbb31vMdTsPQB8TeKmFRC+QisU8Xl+HmxnYdpQmhX+3ZtL+5WQXFDAmAvOOwR+J52UPLdEl6xz19Y5fyZItU3NfPdkOkSdNsHWmhfwuCq4WKqLJTCUUFRCL9R58l5iABqLHFyXz5zAlRW6Ev9ExXVCklLZmABZYG4x3cxdWiGgQiCkNKcNTVhemCSOAVH/yZYJLfSOh66QustsWGJC+0kq6ZbZFdvrX0rJnXU7z1szZR6ywBMgPGDA55wupYSJRrCaDRKAYbUSGS5zZZ09KENNBOEmUKuZJwxpX4wB4zhWTC3ejAhRXLITUS7bGHUxRjCboNz6RQhR0lII+PDxAzbrNZ6fnxEoYAgrPG+eATAGtQgIGsN8TBtZ4yGI5UnlT08YdOuk7AwCVjEiUFSBRHEv+rx5RrrzM+ItMxwD4dxc3tsX28vGyJISJnXvmO6MicnYYMTqywpnH89A05SZwQRgtVqBATw/P4FoAs4D0t2EiE+ZAUcEbHCfmWaHMlXaFdRadPSgti43//k/B8xCRljBCSGpFWav3VwYleWo2IEj7IlD7ErVWpsDy7HOX4O1mKBgP7BBkH02DBco7HtjWhFixk1CZlbL2RwBBjb8nGe8F/HwUefjjOcucXvn0yGtZ57fs+Qvx235lwSJO+pt5JbghklePhuep89JNqQJ2JlDhYx9gAjT69PJq9WVD3XXMrty4bnfOs8IN9yEGTg5OwXzGoFOkPgpCwSsNBMtBgB0CkzPwPT0rO7nt7RkpmC1a6H2ZmL34j50/7StKjVJXckY4SBFZbjJu9BpxZlaRckiHltot8/faSVzaHO4VM1+4NpTT9o2OG373wreuLzqfPMbozbALz+M+b5n+dzMV8aLERSvkXRJ90wkUQiszgEK1VlY9o93tU8ZTzIc1je71zIpa8+O7Ak0+/E+YMLxEEz1JgFkVrXFYn80z0VJAj/s2908+jzP9SBDjLtuzg7dwG+/DZbgCyPHAjdImAvJ2+f9BenL5+0VXQMoVu6A4CpMNwC+ga8Y0x+ThKxjgFLC6uQEgQg//u8zAODDbx9A+IDNXxsRIEOEjKaQimtC+D3i7PcVQoyIouGKIQaMiFi59pxNCTfZJtboHNlbUzLBd8LUFY0WmlnoQ3mYVNk1peb/HMaHkfR0J/BslHpD3HsXorj6lrrkUp14KsI/pYdJDTesTWaZnunlLngX7aHQx0Q5hFWNy3J15iAl4SNl+odBbMYE5eBvt47nVWSDD0vdHESGL74Udp1Dp1FWSkriyY6CrKPnzehbn++/mVJ8/i5gQvGgDI8hRPG2No5gADEGJJb1Y3yiKSU8T5u63SQ3fGIA04STTBcX5Q0AGM3yvCFPngwf3DlCdT/MRQ0HasZsN15LKO3KL+xvk33ZorsJrQmZk7b2fSzOPYRQ1ndPiL5U7i7huR0PP+tcP8IRjvDfC0cB+hGOcIR3BH4TQnWXe/dtFhcM4WFmoXaPKcXiTpiTuZLjzBA0N8PCBEk7BfctApeta3tZmPAVjKtAuEgi5PYEM4NxS+Lu3VuwE4S49gLx70Hym9tNBmFgYHxnpslbwH3Bf98EWkLLiKOW795a3HqG87Z0uyzRFy3bfbuaNpVEFXXbPmbB6sxKXioAwN3lluMFMlcfS9qWGM0kYm6WMC1KjLfc/yRCc9P+lT3HCGB1hwDEicFm6UABQYWXYGBmU8pFzJMF3Oz65RJz76Ubxr0E4aiHfafluUvllS5cyp35y8+aQPXpaoWKuu5tfXmECNF9P8abCemCMcQEGsWtuvFWONXre7Gumr+S0w7DIEyqKSEOQ16n4yhu+UMI6po9ZQaT8CLayLnFRerz0zPAYj3OKAogIMZmGqW8SUQfJjBPaUJy8cSXxmtzDpRI0DoIBJe35PFzmhkzd2qZfm6unGVPtXeDWZDXJzdhnCY8/LjHyepUmcs16ycOERgBxgi+0DG5k8EXppC0JckGqecD22EmMD/4cn4di+I1IVmEEVr6X7eqE9Nvy3vXoNkYdpNt+Xb2k8wezMPEPvCZgXhh9xQQ47mctxTAFmqDOcebffp+hQeSfCffvoKJEYK5pi5qQiak6+FAD/aj+fQWio4vhTerm+uTYO4xxpIVIVteWvkuQsdCRva106drvvVB3OHv3WR99qfMSu7xD7KfAxTvJYCfgHCqIrBnuZ/XHfxg6ZkWU/XznOqZsPaD5UqqsbNeuUu7ot+qba2rrrj2vlvozvz1ljdtk1jErCCASZQJQQlcuaZucb1acS7feIx6wS3B37cdXw/vwCFXPTwodtsZ96bCfIdR9Z3c+2qOnHXd33kWviu4Pnrl3UAWBoTKXfwTh+DviHHeQis8Z/QF4z2B+Wut0XuK8/cEnFdehWydikcn8zpGxAgQJTAiQgwDEMQqN8agrtgD4u8RQwgIIYpgXS+zNa4BpkwPnLNi3UqvZU9pDqcQa/Ta80O73cwyt1icS7z0IrA24TkyjUNtvAsHyyE8cmPrBjTj5r1PeR1Br8i5FfIeMQE6RIiugsagSvC2p+SXq5fFQhos+MdMgbTacvttvr/jmCLI3EfIXUjkwrO9RfmkQm4CIhHSlLLnAgDL9zs3FARDDRFEsWrT0LFr2kpx7A0dcnsr9NJW9Ja6SjmkdZX19x6W57332yzN/fddZeyuj4xptNCbIxzhCEd4GzgK0I9whCO8M8yJiJcw0X2eQ5kQpqvsCZ6KuDEN5UBZ+1Ur1b/yJ5AT+C0QR0awtZaqHu607HMG7kC4BOE2Ap8T4xxKMDNnq3IjuM0avae9/sVZ8RqjNjCw4guc4/ZvsD7vwZwVWn3Vz58hsd0nvE2cdNbCl0IBFEWM1MwpddPVZTuLINanjpCxu+aTUWI5YZsRqNZ9EaJ394MuPgaUEVL4qcY/YFGNr7pHKkT108MsllieYE/QOK5GzOcvZotTGGQi4CNQEg8LCEE08QmICUAQIXrikF31VfzKJPQemXI4/N8OQ7NpezWM7Ti5d61Cwb4C99n3zq9D8m9Lt6wgtOyu9QcBxBINMuJzHreUGBNG55aZcqxxieuXcgxzs0iI5vYdDGJH7CpBHmLEiiS2eTCrFEBjBSZs1mucnJ5gs9mo9TlnxYNxM+Z1GKNo9k/jiHHaFCYZu/iYzGDS2HBOQrVd+F1DuvMMDxUgnQe0+dod286xldPOgXc9Gc6DCNKzYIOR7gi4AJ43zxjCgCFGVTyQtgzDgBgHPD8xECZMyZRM5KyJ+KwM+nu04aH3sSh/HRzK1nnDmt16J3d2yQ+fpp6TrQxSK6Q5G9q103tn8ECMTwvuy98S9rkLz/SMDIDwk7LASdysGwssxojNuMmCcxuiewI+f78CQ6ylz//1ByJFMCesx1ushnMQ3eHignB7u72/n1j2grlhNgWA7K0C+1ml9zywAO+3Cmflz5StUv+e0fOyKCJNmSEOAE+qMOYQzCp/at+215x7YVb/JUdnxTJX+8LXl/gZgT6Um5tOQBCLw9XHDwAD4481Ehgb7AcrAJtOS3bBsx/Iakj68z6H5rzvLpB9WmV4CM1etRX404Kq8d9HSFqwJUFdBG8STzxe8NrJyZwXXptukTHO285A1py7MJiXQe8c3fYe6HR7R4MOPQcsvVnCieeaEsao4BqW2q9PEWilHMBevhOVkjPeYll0zubLYgFR/YeAWZxXwg/3zZ7MzffjZt3H3xX6fj4K9IRpfQF5SXffOad/FnzlC1zRLS6VxGi9xhlcaPsiLvGNA0ZcZZp/O+zu2BLdT7iUOwyEH3/9iUhfwLhBJMKEryIYV0tovhK37ye/D0hXDL5mxD8iCCSCcxKr6RACAgvOkb7bGadkAgvf48zhxgzODloSm9W5O4sq2ZggM6asmj0NQeKdJxaX7VOaSuikmWytHoy3wB/mtGgPX+H8V0imTs3WvixolGcTosshbvupnDQm3OVUzpiMA+fUXNXhDQNY8YTcJC70i3kMOxTa3ll7l1brx+E0o+AhjRhJPMH8WD9bL6v01j5vyNBvCOX0RMB6mjIfYURZD7xw8hjO5McrkNwVIMbJRmjUM9S47MHHzcIBRYa/7yjR36myl1p81e8nRxd1DDxsTGqMBl3L85eCF6IvCdV76Q95/x+rqHaEIxzhl4CjAP2/FF56tWREYlua5vvfw2r9lcBRcOTfdpg0frD8u18VF3hh27rIjWNA+FdegKeUU7fe6nvO79wbOiKmpC9tEaaHug0jFgGeUBw6f8axh9IycyStYlES1HUX+vOuZZ4zgEAZWSYAFwButaVBqzhH8WBImGumJ1LBpI2ba9pOMugVm3RhOrbCLqsA/+0TuziI1GwVasZ81jYjIRtCwbbjjn4vpVuyMJ/nL+kqQb0jVHa2eaER8zaYezazJjaiREaoOJFzNTCrBXdZpwSI9ZNaHVhqY21ITebk1ROwNTHLkDWYa00AYgDSlBcMU0BgEw2a1QHnxevfJvfGys/jQ8HV344lu2G0MSopcluaFexPDv929mreolnd9fvqH/jdM6+xU3f1vJuw9isOd4x0zmCeECMDIyEOIVughxAwsczXNE3CMAg+nnlvzUotIRBAEVlix8i/E094evoBoojNZpNd6iUGplTEMymNIASMaczzJd4IawF5OPfnfEK649n87RqX9mm6m2a9Wy7RdpKmKRyW/Bw+hxwnPV6E6q4wRZ2UGBsesZlGxHGDk9WJKBhA9nWIAygFMEbgQsZiysL/wuh4nzixPXibipbOzb2YHn4f2xhkpmWPVdeyguo22Drz48noKTz1nJcLfGLCfUcQ/G6o20Khn9r3CaBwjhiBAFVUUpcdps/x0GnkPeSO/vyvP2Qr6xm9Gs63H0ltM1lwj8/O9y7pv3bifdKLhwl4nImQ32X0XgzVGeN/cj0o7b3vv1lIFUlgd/NSfdu+tikXXs/2lFirBToBGAjhFMUVLEA4zce3/T8T7HfgRP8OKLE/Dz0tMn/3pcdM74rsVrJQ//yY2LPCZl00Z8e24vL0EAm+pBuTtxwefU8xy01sw/1Im35xypx3xEBfogH36FYZ8sLQiODskybfLZ6Yq+oOCJFFkNJ8N6GUx87mHormbfknQSUAAYpQLgucCBa2mRQ3tLRvCb+Cdfk2GCV4WxdTb+l3j31EfNEcN+/UMgLjFgmMSF9ceBYg4hsiSWzo+E2E6On7hETXWH//ig+/nyDciVB3CAEgYLpiUBCakUHAbwVnuAUUL1Zhb2KkTN8Vms3GJ7m9k68CIvFkBlIeDauVOSRkk7pUl9jpRbBuvcqhxHoTsY2Gz/tW/qbEYJoUd+rge+0xQaQhsoLiUZqHAZAXVtb8AHMzn3Xr8z8dysXwYbU8T+zDYi10K/9TzkydrkX0rmWDzVDq3vO+aByJ2/aQGERCN731uejp/8KHMT7G1pwACKcs63VgGeuT83NdloTnmw0SHnHGMos9WiAXdch7m/8lPIbrR18ehebt0jxVRZZTyC/m7OEQy7TbNl5Yi9JVz/NNo4k4/96KEpJveSnf/z3CEY5whLeGowD9CEf4KVBjO4Q5MWlus0CGDvQYv7/S8wy9Xkg7T7kvdL1ukX3gvTAkrv7l5q0T2uWvwlwO1RRIQ5hFg9hcahmiX7nSAjKTtNIEzbwaRywRcG+qtywa2l9BuA4AEmEixqBFDCxFmKt2DyZPSlQE7h4CX+AL3+I6AJcJuHnjELaG4Lqhyu/1VfV8T9u/++cHLe+S6zhuW+iAre08DF5Sy+FQ6OqXo/yeqC8u5y3qoMxQMsIcNl9UzZutadK/hT9YC7i9yLiIskJe1z6FWBjI1yklMAWIWTkhckJSrw91gEPOjBSQWiDnuhxjpGG1cEVtkkbRK+SXPwt8bVQ9+W/LooNeWcvsh/Zdj8uwK22n/OoYnpf9g4CPTJjwAAIj4hzpLolVdEogbIBR0EAiIMYhx4hLnLBancg6SspdIXNZnjSPhbfQNZCFkrYO6/4wT2BIzPIEAMnNqc4xUcqKTCyHrnOFLuVPdwkU5Bx+zZ5pYQsfw33XtdbJYzshXqoby+z2AdXdME2MSS3UiBmBZG+sxw1O1EUmAAwnGkP+xyOAlGMsz5UzfsZ93tb1Mni5C3cCuJxC3pLH8Vrcmmvr8VaC8zOg5KF8cjS5ey3K+T+CcuzzdlczXj5DHrYKlFyerE5EAAUR4qaUspUY0DB0O3BPQPzxJ2I4R4iiurce7wAGVkM56be1/pEYZ1zelJGXf6PP4Qbpkyp/7bJO31eR7aWw82RpEpQ1IO35wNK2pzZD6zZhodjtqXY0kOfjbVoT68cfGE4DiD5kxU1hoJ9oagbjGROAtWOq2qlzqs/PrgnP+r4Vnr9kvbf6xkt5Dob22OyAX4fz7G1mqt9aXrUALMuyuUG4LqF8YoAlSIU/NJY8nBSkzZVHzX44YGscPK57bZAlPGh5oH3vzhh47NErC3W3r/257E8tO+lBav3KQpkJKSYU+slqECFdtlyUuZ7SmFueUGJ7bzSmtzXXO5hi9v1qWvl2KIyWv+vFC8p0a0rcspfTxY8FQYWbKHjiUvd6OFR5o3SxnU0d2GZ5DrT458vhUs9SU13cZRlubtMtXVCVeA/mUc6U4uX/a5z+8Qce//3vhZJf36ELFjr6TgVsRDcgEC7V+pwADL9FxABM3xXfIhHpMq4xfo/4+D//lwjZAwEpYPhN4qFP3ycQIqbvExJflzXAjIvE+E7AjSAe0l8qPfKC8zakF2VTXDJUWly+azixKTn37SyC/AwaP5oMH0+u0gPxhtZDXT8MWMFJRLGEpA3MmMbJ0TvarqaOjLe5D5Ldh9myw4TyaInwnJBUiC7vtDlZ0aWlHJr7y/Z0CDlRrSq//f72OALB/2j7KC9P4oAhDkicME5JaFAirKc65nnBEdt7tEEU8td6XkJjqV5/X95TH7TgJ70RBpwBIKzOI0AQvJiB1cWAFS6wvr3Va7weJW5Gzdq9iw23NIa945CtXCrPS4jUNnzZU0eyFrcoeL7kgHWLKXtn8ot+15bc9t31/Y2v1CMc4QhHqOAoQP9vA2ru4wNvGcXFauTWinE377Zi34fV9WtCJSZXazxj4oaMReh3Jy3O8cIcIUCAuF8GCnNs4dmyveaZrc0tvg5BZNkEv1DLiWx5SBkfKnTK3P6hM1hd8HGVPacqZYaTIKicORSFU8FEIlDmJi601aX9yzHbfB3eakD/MQaKMdnEootnLpMESRSLzqquBlYU8AUS59w00pnVAj2IFvgNAV/NspwZf7DENU8ALmb1Fqv1wuS4A+ECAOESwK3g/lu19/N45nJLQvI/PPLb5s+/9yO+/DPcs1WxhsR1frQ16Q6xPCcQpDwsLqaF18aI76SxZU1Uf6ve74CuW+7MfPJnxJbvypFtDdIry9amjRBH18J24MKAsPyEIO4lc/Uh10XJrDB9p62eigrSI4IhnK4E9omV+GcCaCJwSEhMCDRhdNzFMSVhiJjYW4KyIgFIAdn9u41MsZoT1o4si1Q2p+1ZO8DavjD0fJ0rBtj3dm0Jw6YUw43g2GWr94n/O7s8uWK8lA9OOz4vTJtH9zo4et2dfdaIH0RFiGXFqZ9FBiPxCJrUXd+gTAGKwMSIUQTt4zRhGEIZD7KyVAUjn/WO5aF1JmZQCEhplPlktRhxB0Rh65DrNkvnstlIe6os4xk1g8Cvb2reaAp29c/e+/TNXsv7KeXNF87LhIcQ5bXFmNe1GUEgnpTZxdmyY0oJm80EOgm5D4kZIQwgBCSMiBfAdOtYMizn4v6u2/2aovn72W/37NfWCyGlXY5a4Rd0/dq1hcGKp8wOPUlVzY/+9vts6S7Idfjbp3z12ZglFvU9eZe/KHi2264NT+3g508MPJhZn/bdV/mJ69aFCwLRuVqBR9lK5pJTj8PVaoULJtwRZqNIANId8OG3AQkTCAGBgp69QIyEyy+S9vamXhpF0E94AOGsGbue+igDOOegzEF/aL58rb03tALSwOZJSJ+X8jjcpZMi/0rMIC72+sZAzveOPicN12JxXtnOX10TLRNcGpEQSSy+RNCXVAVOvdX8qDqoTaUu8nYCwTkZdgyaxSG66Zeeg/sUOojVe64Ef4NnD94FPVm6OUQw6pcpA+zuaLYLs8aKcq3JxsjOptDZHe1YVBLFvQ/+tuUvyvdu4PAqAVuxc68U3Dz77zNhRf7fBFqKwyAgIWRr1YmpagKDnVv32irWSme35pMTFtsZCagQvelm7/cLp/GnwLLFOar3fQUTAHustfqkp+rP3w3bMKMezE+J2246Ke8if2dgi/D8bYABfOVLMDNuSCzcL1F2Gym+CibES7kNpqu/EPAVwDUG+h2RAlYximX3oPQ2EwIiEk+Ypu8YmXGj2Fkg4WOEUPZYgvJTFPdmw19I3JZDvyUAaZrAk+7FpLHNOYGTULgyjiqsbidID+giuC6K3rs0LNr1nFIRoGdaipwL6u7qyMQRYizrOqgyY7aOJwl9FRAQIomCAultnJI7eFQ4ntz5Y3HPk5xDyZ7tP3KW+oBe1tKuIpMu5ye7vhRfQZ3zVXENsu/ts8vdHV8GNuNGXP9HmfPNtAd98BOBgGxZjnyHuDvZ/8ZcuE3uX+Rzck5deFQJO757nMSfm1lBmBhsa/6Aw6uqP/Ob9LbdJnR390N+F4LTE5WWBmUceNqs9CMjrFV7DO3stbQkNWJo+3o7whGOcIS3gqMA/b8U8vXS54csPvsLbU4kzPkt1Cb4L4aM4DvUiOoEyPgPxGZTEKAykpkdTO//3KLLNbaNYgHG2hNuZpyLdiFTn7R4KdS8FtO+9ciX/AiMHCO2ZVzZeGeedNtClnjB2XIQQhQEQFyVsbrxrTYEFy3QoDF9w3LPb7XeCxDuAuNCse97iNb7XQyIAG6J8ZVhKwInDKwVi7a4fXe6tM4BFY6SxCsGALpDYFEm+J0vMNItCKKN3temn7NCMiJbaIGyYFEIrJJ3ht52Sm8RYYFUlmHFkPLuZr3Shy/F4oi1tEMXuP/YnlukGiWtXK7azltBW9gTpHsBtiPG++1tG9F+75SrhLTkqlULqlkmsbzMY8lU9jCbrXoQQUy1ECR9msTCuOq1CvyJAJ7kb5qQ103bE1s3ttZSnn8GByDHdtOMpmlPIEQqDAPtDrIgIZfu1iRZXexE/pyTGmNChsJGpZDHbP+QzZv7YMehHwu/uFzHUxbelgStZX21S3JetXLL9Rhzh/P3irJmqICFgHsgXIZCyJKMQEoTgq6VGALGcQNmEaSDyB1lhaim3Dn96Bg3FAJCAMBTZt443wLdUybdixBaXLarU1XqpW2huN2en/VG4FvSZoJsHJYYanlZuDXrtP3tK2sa1nuHdAxk3YqbSQqEMARQCgjMSGmSuI1aynoUG87VySqXHFeDLJspYL1+Qugd3K4AACAASURBVDoPQBN/WpSLuqf27Ln0YgnLQ/+ZeY952AFviAeaEB1gj5oAKHOdrU+YS0iV/G87Dm0jqfOWqyQP1RkzL6JFixar2vZMojhGS2lsXlkYeEl/D6yYZBDm1ZjkEI4x6rHNOPv9N3wC4d/f/3QnTvk/BALxgMR3CBRBQY8TO9eTuweR8OlczsILALe3cl6aMB0wQb/8tpMggNSSU6zSoc9nCOrWffuiKZZIvf3/ljA7Waq/T8FuWHnzrO+r6JGGzLicrSAeUBwzTZVyT74JWETi2b8Mu13J7qxMwkQlc62rSC8zwE+E1fkABrB5uEP8CAzhMxiM8ccTENSnjFsQJxBFxjWAU3f9E4Bn/W5LgZP6u8kboN43Obd7rpnP+zmv3wsWC+L+Z+ZqmpZa4q7eDAQCBTdPBHghkaTRv1T2kpQnozlD8UyRSzdaoB7rhnefz91PvPThwHIOStCka5AiffcQ/Hv3XZU2awVPN0sZvyQ8g/FhdYqUGOM0AkRYhSjfQ1BBHAHEmCZ/mOl5aU8EdY/M+epPhnMowpr0Q9I2cG/J+2fDFd/owNpHmXf/wgqeENzdU/1VJe0SO97hng6Wr7iCLHev0IV7bhfskIvuhHPNb7TxNZX3u4o+d2jhRTP/3/gLvtN1tlAPAK7ptrJEB4Tefy+QPt0AYFxoW+9JhOgDvuH0twHjX5Mol2ACcIOIL2B8BwMYwyR4fYzga8LwLSBdSZgmQAS10/QJnBif+BqBxJDgfhCBcULCOctauQY7+keBzN2/eM1J0yQem9IkAmw95wDU+LrSYeUCQjaqYCdkb1ffIWAu0kk3LeXQBIQiGLS07Q8RmhMhe88KIQo9oEoDgUJJQ6SehBjISqfF2X6CKR0IjiC8KhWgm68EUuU5PdMmVUKvyHQ9u8qqDXlvw73NuEp+nD9Xuz/Po6QiuwNRyMVRQ3aFIF641tNYzUlRdJA/Fst8Bjsmcu5PSsA8Hdno/tB999EdyAHA6vJC5iOYAN0UrxIIAevrta4xzjQYaXsDHE9HmxGbTrQkAtyzb/mS2pzxHJeomZJH8ZImRe1PBLm9S+W0PKve3xAohyPLKGTROnHlF/4qcVlDgVx6X3duc6+vv5xa4BGOcIT/UDgK0I/wIn7e0nNLPrVp34+x9U+CZhQq7KkwlLL2YEVdL6FZ7/l8KEOmBcdJeMEC6BLWS99ycxvXvgtI99b1qUSHMU9m8hKfzj5yYWLsxczQPAMDlygutg3OE2ci/oqAb0ZIAFgxMLEgvwksRD9DrckI3xiI5jrODX/CbVYsGBj4whCX8b2G6c92j5N7R9WX94N78xZttVHz/K61ax1L2ritWvory/d1FHubhuhaqrL64JU/gNoTRL235zu9nnUpJy2fCB2mT71WuPpA1JZTOB+s3cjCVioWCpUILG8957bO2tswZsp7e+HJN/u1SDIunzlVuZ2vPPuR+zn/3Stj1/OuNIwfAD56Tj2AdDuCLsQaw2Qc0ziBQ4LFQw+BkBIjqBC4s9g6zwxkRof8DTFgSklO5bwY5wewxTkXl+2+1F27u09GL+2ZXeWGz1TFXM8Evr3I/BCvClQOJBOlM5QRMIirv5NhEAb7lICocf84gEaJ+y7jRtiMayRmrFaDutwWiHHAyeoUiZ+QLgC6PQfjPu+cjwjZXW3VUPfsmWP9dLTwF+Wu+yWgg0cBs75lBbcq4aF40O7qd35/LfK7Qzhs6zMCCJfnCBQQQ9QzWL4yWLzTAFkZaTNucH1725ttEXz/+R1nv/2WPyYGIpVaxRqMcX4hIUOYoUozjMvLgM1VEsU3TW+/z7gw7upeCCQCHiss41dZd/uAv3X3SF3d5QXJoypEZ31Xt6cXwZ977iuxW/Fqh6t3leEb8QMQ6SMKi1bvxkayZ+7ZT4Due7jvz+Q6tuVenT95BbK/l2LcKcKf3e1L7V3GrHrPe1S4O/e2a+CXhV5Dd5/VLR5ZnRomyCFkRchsK86pCH+B+u5gh0uCsucU1vvd68AkTrX1ndOm7KJ/vzi07trNm5mnfwSPUIyiFYLuKl//9sKi/CpgLtYJIux+DfiT7Ctf4orq2OZyO18g4Xane/hXNcLVB5DEaqYS8oUAteq+xkBfIULRCKJ7EA2I+ILVsBJFWmaEL6QW4QkJNwgBCMT48LvgC5srcYJNdIvTQLgNhHEaccMjPmtDKMzvGbAKgtVjlXhpMhpP2+m1U95xGX1iFPyFCIHNq6DnfHhvSL4f9f1nVrmBVCmFSNzmB/E4FVQBoMhbC42UqV5TUM5KBDoWOkbMDJiiqFMYZW3ffJceigvv/5zrIhOgN0qgZHNZpV6EN1UQUkhADltX1QXbF58QlQYLFJCY8fTXE+JFxMlqhcTmlv8Rd0547st5D8hkNOb8KPLzvIiaSAktDm7xzg+5rnoW6C+B7VyM/dMe4QhHOMJ7w1GAfoSDYB9cddfF9uuSTD8DFnrvkJwKneHXIyVvAQxGy+psgSrEuYe1vR7F6ZbgGMumiZmZ5vSK8csmVmYR68l+ykQeERAp6HNNRJGoUe60bLxSxPscQqxfsiD2ESLgNuuslJHeC0wQpvcpKFtsP1q9AG6JcKlpBle9INwXCLhVK0mtg6See8XMu4i0Utnsh+NVsH1NXE6tcF8a/JnFu4BnbDQ07Zu06u123luj9/OWCQ+rX4/Nl1ij1ex3/2yrq87pfue57wgHuoPFVfqqNOZmb7ai7EZoTYVpacpFeb+3K3UmHIdjODTMbBMm+J6TS9+bu1lft83v4aTfYevP9307g33EHQDCSvxU5O/MxiBmAAOGVVDrcQKQMGlMuqz04BU9IMJ2cZ9PMNeBWVJOLHHVJ0ZKo4b/qMtYaq+2bkffD4HlEfX3V7qbK1MYayQzLfKTK5qBdJtAn5HjmKcEEKkSgo6LWSgOUePPB4BGwpRGjCkhBMKYNsAmYbVaiaUcABOwR7WcCwgAzrUV95gY+ATqWKJ3+kvWi23jUz9nryu/HLuiN6+9vlj7l3O9NbxLHZnDWhzYPxDwWetLN3fSx0tx1Trd3qolErC6OEfihOer68wYzvzhTlWPBHxkBtElCDeV4lN2Ewng7pZxcSn4UsjxVYHwW0DYMO7u6jUzABhR9lKO264QM7FxOA75s2iOWT3c+dq5KhcyVNbm+SauiK4mfbI7vFRVfadU5lZ/fNQ9EFzDIn2EKWIm/oHEgmu2gnG4spiLIH2NYp1uz9XxvjSFW3AGniVezNApYt/zaTldr6YZU3oxtbuT2QsSFsqj5nlW/FK/eevj7P3CWux5gtmr3DcDf6sW+KR03EOziNvzaml8h7hSulCEVas4FKEN1KKc1L0xoDim0XulZAZL2ASd1vzdcG7DrXOEDF+G616n178imNeWTHqZhWM+jwVbHqepm38nhrtEpywOSH89vtX4tRbn7V+g0OTbav7KXzIdccE3mT49V1r1gq8AIFt+37h9P+Em13fJ5dtr+kSYe5gj+J3msV5Coms8X6nCBAEnv30AX6+Q6BaRCB9+/4AhDHJXMBApYf2dAbpRXkfEEAinH05BFPDxoyz86fsnTEh4oGsQxB37rTAipGbSMdLNxRDL9ARGatySz0BpNS9U7iR5MTy4zARkj4JdvpJXMq6E5yqoJHHNToTsFSiEKBbJWdGnwblz0VJO7VkOsBjz5XBKigTKmaWR0MCgYouzMCAvHafS5KDlyLo6Wa1AJOfE82at/fGewgR/tHOk5RtOqrQUaGbhcRB8ZMrW5VKPQLbr55Ku4KJnOP16ImG4dF0mZjx+v8L5H38gEOHp+VmVSe4wQsI5AeqVCgULMM9tPkSNh13jXvAOw/fKGrNQmgUvL/zGQGaUQ5165zxd4/nN6t8Dn2qtyz3O0lq0U/lQ9bFFE38GfXaEIxzhCC+BowD9CEf4mVC5nJozcrsWqH+zxdffXf8hQCrAKYZyO1xiY1lkwBDBRyUAJ8Dc/1IgYMq8hSo/Ezcl7Qd3AThPVfTjxoGpociEiEskusEzMyIJIRIhxPm9ajJbbNNvTYhWKzeREA+TposQ16tJkfBbMh72MuX1nszqtFBYG7vdXOs9KCOrCFDfApZYqZ4bWTP2XrplSJkBRDQ7C7ISS3uGzHhLy+ms/KpcR5SZJn1dXmFybDsLXvJt3sfy3hQCjDHSCrTnAvHGarkjMK+a4d/7HcZLv/t5+xav+9cxy/NO8AOMTw1Hl28ZfF7WrYQeTGCO+oYQYlDhijKwuDBBvCt/BkB5nsgxkwghRqxWwGYD8LTRIdM4h9kSfc523TYs7Ri2a9lKqPaCJ+rdvjbLFis3XASk2+ISX3jpyhbPTORyx7RTHqM45JzShAiAorYh303m+rUwOjgQOAUECEOMAHHtvk4Y4kpiBALq8jEiBoAugenGbojPkOAfwEdQY4leDdSWUd0NlfXd3wymFAS4+eT6zq7u/1/Kgv4w6OKDxjwD4cyfNQTcAfh0cyMMYD/lt3fl955DYXsbAG6uOcc4b8/Km2vG5aUbe/1nWAHn51QJ0U248Gl235T//+nwKkUT7tuLLVTUQ0e6YKd2+Aj8uH/Ax8+fSp7E4CdZP8/sLddreGbg1FXnhee+ntx/LumIJL9/P2/zUgcWM7wf7IXK1/d8xqHS/PvhlQN1X7fgWbvq+QduqofZNO/PWvdusbOrdda4yn60TFHahFJNXdtx272a8o8CuTLKgUKkgSl02BO3opf/fGAUq/TlNNcgfAHAiLjEF75Bq2Jg997FlnJeIzz/wpdIKML7bUXZtwsW3sMlVNinVtExBCAGIEQECljFlYZzElyUGYhfCdPVOQIHBHpQxduY6QYGYwoJia/xmRNCAh6doNnwmjsVUpqleUoJ05iy6/aUEjgp3mxLs0OTvie/ahsvKeOhM4aI3rckisbiqh3ZbTuJNH0mPM80b0PHcvOdVcicktANSccPSWgVhvJzXnH474FWVBAMzdb+pJQwhIgxpQpPEQU/0jykgn7glDVE4RvCBxCewPigtNEnrrGrTANDhOfiWl5EJJvNBptbCbh4cnmBcbPBarVCDIT1d1EufyDg09s2eSt4vpwPXTZbfq2QHLZ1moAGC8LzKm9HKO7X7T7GSktp/vtulCMc4Qj/ZDgK0I9whJ8EM4tLr616hIOBVJjtLWm98JGMEDxgjFteM6DIpjJfCEI7pkkw/RhF0GSxkgNlloMT6JQ27CTuWIj0LyzRf6+paJLn0NEAQDe4CsDnCbgLQlD+lggfmLAmFydKkeIxCOFusdbAd0LcaoeNScUQ6+47MhTbBsVR4yRp7jUtYy7QtqQvgc9cypu7zpuTchZPjgBcaAjDSNJPy/9Fs23QY8jtgmKbTG6cPCOvvFfm6Qv3tRdyt8R0JUTPFGgRUmYBX27x/KxpjxxfT6Ukgp5AqnybCSoXBeRbOtqAVzLvCc/tna9v2aqc67I6de5iKCx7jWglPjras4NjaUzatm5pw9YWlsw9eUQ3eeY93QM4lzm+A3Bh8wgQJXBKolwTAwgBNLBYjrPEJYwhNooXUFeOIoxerVZgMNIkZYUYEYdBrBFGwjhuMHESGXoWMvTI/+0jwniohqLsGWMofJrthXgugnsKpBb2wGachMkVAoKKregbsB4nTDcTwmcg3QHhnOQsIFUg0ANyuksI52Kx79tApPXArCj0bkKt0EIQDwAUAgYMmNKovH4Gk8RFH9KA1YlYdAyrATRFjNMa/IWQVIgecQ6AMeEBZ9jPEv2fDIsoVPPBxhLAPx7nau8FE/48Vv2VG+vR9vsrl8H379cgd0C3wnMPpmRDJDzcIV5gmm4Q4jztmV1j2t6ke+/hpet2YY4PZQC/FLr1vKgrGo5EY52XQ7LfA9Z/eq48faIP+tPcx56cfXBxZYHx6Rm12H6mnpLhGcvA1qYm1zo3tp/pA4AnAB9IFDuX67AayD2/HcyWtg1wri9VablK1xutHlXhn/Zpv69/a3F7w999Oyztx086pg855K8KWTTXUrtt3E+MLtOUmzRWFVr+NMn+Siw0XHVPZGBDr3PGT0ClmJRX4XLD6orfEJwx4qshhpAFK/P9RUYMY0ojerPX6otso3e367K1OPbWxz2gn8Mswfcpr6KfF+CagAu+zmlthMwKXKzQ5a/9lnuvpDnnudX4vnDOwEQ3e+W3JCbI/8pfcRNu8BXAin7Dh99XmK4Zp7+vMIT/iRgD+JqRCIhfZW7Xf8mNLVbVEavffsPJsEIcRIguPJCEdbgFpUsQf0dgxjf+CjAh4RoTgPtQFHQ/M+N6SkiTE55PCWZlbt7/AEf/LSyQMgyE9s1LoBuTuV3Enn5WGoEQJO65xjkXHYTgYp/XPKKM+3ulHs6dLvVyiSFv3jSMDmMqvLFKofGgDsufsLhL7LwVUYJZ1IcQkFLCehwBsHrMsrYCk4aVCQhOKSePGp5gOKSdRN0Lecs9IGCxzAOEf3CmuT41ue2kGySwAE6/nUBotYTn7xskTCBVP59uEkaeQN/McwljgtxZ9zvw1kPPLYv5nnkvZNyf4i+wrUCGscV/ayzOu20nTd+2bV9heFd4TvpMFbeqpFnAU//hpNkRjnCE/yI4CtCPcISfCDOrKBNO6XdCByE/wm4wS6wWMduGkO1gahCg8fP8O8FQJRaSxL0TDWDhVFMQZucLyZUM1wH4otwITwxfcHF1epmAGzWxuGAhwj/+8QWriYGrG9xTIcY9Qe/ZIgMDqfGdemdmG+bf3X37rGMVWdzNE0NjAs5YLS+GnjB+G3gh+x2ZAL2e1FHbFVDc6e0DXSEyPNOqthav9vVLwNWRlUAa8C7QrC5CyHlc4+uirdwdzFxfjzRJ9xYaa3fX763ghdmeaHWMACJCSCHvY0/4L1mjz+XYsxfd/vSE7TO3eT0B/EJfMrtxR7p5udxN/57wCMYZmRvy3q6VcRUG6QCOSawj9MxjMDi7ZyawCXqcZQglqsaULH46ZC0NKkgPU8JmXKvFC5BSNYCdVdnO50NhlC3ux1IaISCakBshryWAsYoRiRO0a1letYoR8VIYGeFSrNa0xrJmQtHlN6t8Y55Z7RSi3vMdhp/2/+R0JcIslr0wjiOmNEnseBKX7jSK8BwA4hDAPACYsiW6qdgYbLVEfwX8CjhKYTjqsdHsx3Jmv8oO+J8B26URAF45Zw2vbtlLB+PmBvjyVTIM8VKyh3ME3M2s0H3x/6mwddi3IUuZ6X3AvG0pj0AY3Of0yAhnP0DhbFbEWs9LT5ccXG0HPzAB+bxtAk8Qy/aWD32qaeZ5f9bOXsCRZq+XGPu7GOu7+sHN372L/kcCQ5R0XpLTjxQvzkcjaFgUnuvnvvymKWtrs94FaovAt6nIRFb2W+QgoViV7uzsHnX8Igf+obRqQw53wWhLs1Zvhdme9uzRoa+Ngb6f8JyMZQEN9oJLXAHi/wiMCes/CTzcIlxFUPwdCBqigO5A4XeAgYlHEIDwNWC6mTCOAZwYiVcgmtRLX8L6+RRjesZmWmPiCYmus/AtKj1nVuZX04hpnDBNgvtyMiHynH5j75b7J+GkS8ra9V40N+0h0wIxEGKI6kFKhY8qPA+hpt+NxrXY72iE6ZaGdNzEKSKDVdEAFEo+o9J4n9X7ohGBnReJAU4jiFYZDw9KH+U+ZeG5hvghkn42vhbfAjIrq/MtU2ck/Cx7jpdCqwWKePzzEQzGPd3jExMSgJOLS6RrRggR678mpT3eE0gRojrcwrwnwL4tqVZBR3jezVOtb6r+r9LopdFzD99vyy9yGRzhCEc4wgFwFKAf4Qh/A1RIt7OWqkQaHcT8CHPIriJpjl7up0Xpy/IiJZp9zyacBEQOIvShIKxGJrBaJgbLlwvkpixj/i+grmza7AUlFkE44TcG/iIRYIvQRoxIQcD192t8YXHFDiLcU0FPzZ07IMJ3c48eIG7bCVJnbp4FhnL9vyMdF59Omests3Vf5usSmFv2vQXqjpD5xLWleYI8W2w507rfJUg3gVlAs0+d4K6ngf5iomAm9J0TR3337rUL6i5oUUsu2tt62jftVuq5qnONaPLXzI/y9/9n783728Z5duELpJykWeyks9zPe77/d3vPMzNt9rSxReL8AYCbJC9Z2nRuob/GthaKpLgAuLDkOpNnINZ57gbgOZr2bVGabAPMy1tH3+FY0XbfAMgdhr0fvY7H6/OjwPOSAgkA7Q3kxoUObxWIOYI5YrPZiNeE88lLwiED5AQxeiAPQAFp531SW/vOZ+VYL1oKcg4dEbwXEDj2Eet+DRDgLiT/+BSVHufV8eJdgk8BeiqOM4gc/MppLjpV+KhZf2SGIzMQkf6wyCJgBhxAOr88nIR+VYU7OZ3rK8tvru9d1wDvCOvNWrx31OAqtwWSwzitF9J3oizrxdCgJ2zCJr+32MMFglePj8Wigw8Om34NvtC16Y5TeFpi4BOJ4USiwtPlJWRhFn82VREQiu2/AtI/AND/JrQPD7gHiP5iKhTY+dDUb8bmK+PoN0IIt8IruaXkGr4rNJUYgmSnzHgi4Izp5V7oGO7/qY4HlnPoLr46lzvW94zvW16HpdIYb2NWSG+rydjrZkRYotN6OyZ8SvcR/KkxAwDzE+K3fK2A1A7MWR6Je4wrrr7zYHyc6ConIHq7h1Ytw3ewmjjlOm17F1O9NWDNqDneMquTJdefcUwjXxU4VbNdZw+7P92y47JtO+rWm3/Y8lmDO095eFafw7vkTKcAlHMaMjoxBPKRxm96jcZPSudF1OBUoon2j0ax2taN7yTLv3QPp6JjyxDKnRNDQnAGtwAB/BwcvgXLY9zWI31L9drW1H2r/frtbHsBpUy8D5Xy4pJ3g9WEl3mU/3n1O/66/uewm7B/e8QoQsa+eXTfEeBY5kRkwFGEwwqAx1e6xiUczq7+A6LfEb6KnBZwC4ARvgKeHDb/OHjn0XkHBqGjzwghgGJEHyICnwt46jUnODwiIs75K26iRKyKISKEiD6I93lJTnU9lst7W+SxMZriC/alSQNopWRAS1CwXEKzW8h278UDnQgKpFPy1JX7VSaA7qEqa4BN9o3p2cycIvZQAsv1t4ZzL9c0AsCWjDt9FPEmzCEE1SU6lxnlyOqcS0YCzEAfIoiAhXdJpxmZcdQtAACbfo0QctIMfSIWfgGAEVMO9Lpvh+slN9eNvCQ9f8qonDsYRQ5yFo3JNwIuIqFbrfSdiazrFx3CJoAB3NODfoouYnXb4+hqgT70iO4OQesxNq5k3Tycj2x5qSwhlleYwqvgqVtHgOpuvaQoZyrnebp/zwW4BNNZH2JrTDVymvpNeZ7POu+ZZprpo9MMoM8000egUgM8096U7A8SS14iKcDL4Vu7W8Occ8Gkmi6GCOSg3pcOoKy8lGvHnm3sK0+cr6kM+WakwQhxjxGgVnnqawd8VovjFiS+YPU6hwjcZyye6AAKCWOv6uXmFlx5KYBZvrhDvcqtbuf78e87qRRultyEwz+E3nmejnpRAjDP9BbsbcH0GluuhdDknTv1jFSHodDKxf354fVVJRYw5WlePa55ruVwq9pSgNY5lN34/aM+yyMKjzH8eucrfaUm7yN47Bo96Rs+K4RbvmPQkjRkHGm4cagXRRF7Wed5GgtNv0X1li4t0BPY7jVaRxqX4tVOHaGLHRgbBSbGEAHGFHjeknmmOzpHt/LanlaxgBT60HYOIqdjTpuq4807l8ILMlk4Q83vSKK06tSDolQkE1hCWHeLau6s12t0XYe+F5Dc2mvKM3IE7714ljiHBRboNaR7iBHoN+IR5qS+4sXSwXvtvyWAu9yLxMApUQbRP9BYfEv6V7NQOhYH4duba4DhOsj8/uvPWPnrLwy3JCwWep4BvyLgbntdTtl4B9JUMi8jy9P+s+iEgaeJc49gAdFbPqvVXm+h6VcqhbbzoVQkhyeunsHUKmiHVTqEiGH2SThpGkOo85ECNaD+PcGaY616JY0V+soiXnLFWzzlx4HbH5vK9c4MXg04sHQsLZXX6Zf/UqL0N8sD9RWSIeywmfev3YcL2nfIvNSjvJX7Aexh8JPv5a3PNkPZojC9584xVvwVkT2O42cwSTjuGwd0X541GgGB2AzqrUQGxQgHxjIC90S4xDcgAhQJAUH46GJwRGbQJUBfIs77gC+xRx/6BJ6bPGEyiahihsZZtVH19r55LY0ZYGcA0SXw3HkHR+Jx7tXQVsLa6z3DgtO6xTHmT2uvGiKXTSy9zCtj8wY8n6IcO8sMGpKJQq4WSvhWfLqpfBcT+iwq7o4KqNuaDNNjaLFEBGKHY44gNAa/LyTzPp/iJQDgnAkO58lYiJxGluwj+rDBPd1X910wcPLbMThGrK83yQnlNUYZW0n1iMPip3SLO4oqf+/peT4oZ8T7fMwbfWc5r+fmZpppppl+Gs0A+kwz/QBqGf42d3Dpid7q0D4K+PIzrAKn2l6DguUNY0z8rmfU11ZPTCgEKaOfr2A97jwhRgl5ScbwJvyeJBdVymFZCl+crudSGlNJ1oQY8ZiWAk0gNk/qokNS8XcAfo/AjSNcopbUGDlfuNGD09DwrNiLaFNQyDeoSxjpQ0C1puU9dLCFf0tdWafReuQT5yzX3zoWj/w4VORsWLzzGQrq75haNs728USva/fyOZsEy7IeOtbK6TDmOZ1/DrXyLdg++WIMrEHdRhBV821gJV6Osx2g+aB/mMUtuq0KuCorgerW/1PjcRtw3q4prVdw2/16YMoDcxD+feK6ybDwW9rx3pRUH/QAvgf8xVKUVl4UJDEwCD3IeVXoqLLVaUg+9Zaw30SUlDwSNpDRLRaIMRRTlhJY7LwB9QSsgTVvMAy4N9E3rYKomB82N5hFARyjLAYtkJ76IIoXOtTjioOERYycc6N77zTPoIFTeq2VwTkvfAxBlFIOxTMpAd7r9QZgYB02ODo+qurOQWcfefiOJCT+BtiEDRwRucETUAAAIABJREFU+hDA/Iyjo0UybiBP8NQh8gbMQLe8AN8xegvQySOe6K+gj8ST7OWJXtCvGNC9NEapaMKIqL3sTH8frSykOuHL9fV+z27Xt0nldT7+qNsk7hhXV5kJIADLlSiUGUAMQH/LCei2T4s+c87Scokgs/97eyuF5pDL2E63D3LHKbQtPD1XHsbAu4IJ3eeZ1FSuNOCx9cboO5FELSIxwiQgASEMAfvJgHQenzu7WKaT4nsE8J1thdQ6FNcRgGcwTlR5P94RNfGuTkldOv7mhnWfyi3f3q8wA1fsRzpW3bllbaz5/DGadG2fRgNGKOeO3VbYFnqnJXIXEJDmTVkNHnZXmeucAfSa91fGrvDrBI20w9nDfGpS2R7+1vTe+6R5Ee96zGC4ETUjW6LuxBBSJ4rNEyFiCNzZF01eJl7rb0C7u+t9+vMlXuL7yLYmt5oh+dgzLhi4+PN/8P2vNb7SVwAQ7/OxwjkD62WZY4bqBODPz3/g768jnuyuALsq8Jnxn8s/8Hz9BWDGV76GZw8fhE//m76Ily4ERAdz2qtJUyC5eIkIxhkcnvFP2sui/gcRHK4AMI7+8NisN3CrS8S/viHytQLnQWQLnbOkzgpEBAQkuaPsl5JGdTl6/DVe6EkGbctVg2FHBp57zQWuwL8jOJUFCtVQUdkSBNf/hRe5geesdUj7nJ5PvK+VA672yvwoSsYyTu9hMDpySc0FNZiIui935HB8JJ7kwdYHSCSqGE3GohT9w/YpkQmR3iVBohTAiQe7edd75+E3G3QoePbBglXztVkn0b4I+TjTSJFmBM1ODIjPxNE9+Yk4PpO1z4m81S0WCJuA5/Uzvt7dSN9qr54zoaMVwIz1lw0CPRT1yIPiNXrStIpyWV45jrVzW6XlnuB5FsFf73k+BZ7LGGo37JaPpLHDs+f5TDPN9MvQDKDPNNNPoIE3Zz6xRbky0y6a4LuniYdfx1k9OTHMGyyvzDkB0c1+Fwwz3d+q85LXXTDLAMb8b0xIXrIA55dcCP2NVzBBQg1fMdATcBVFkZRAaJJyCOKJzRDFZE/ZopwHLLfQRRRx4pYG3VD1Y/sazvllXuiRNJL8AfeWofUI2Yu9Vc/uI0j/6Hnagq1ZEdqECR8B01O9moO1Ur0ocwQATs8HBn2+K4f6NJhf/5gEvdHeX4Ln+5fTlrHHRaIqGFVYTdR1T8XoXqHhfxI9gXGmAAqg8/6egQuScHvOwpo7+I4B5wHWsIOuHDNIkr8pHAABdWOI6De9hDBP70smtClYkrJWjTPcBRVh3G08Dr3PB93YzMmIR/S353BXC9VCSNg+Vwj+9n76wOh8hCMPyYcqa7gjkpD0MSKFfCVVRFHeDcz+zZQb3nXyW1N6EBU5DmWBFeAcGJ2HiUi8VjQSIvrYg0CIHNWTfSHh5hkgcvDOgSgixEIZZT3O2RP9NWPwo4DnwPj6vG1p/hXBc6BY/0eU3nW0j3zPaeRqf2vf229XV3uB6AY8jS+PU+tj/n59zfj9dwK5JZy7AwCEAFEoO+DoirAAcHuTb7onUVhK+4ReG9b9R9Jb1HIL3lc/Z+vDMvN0CsCfnQIOCA9P+AbgE4sy+Rvq9SevZzVXfGi7DFBvQ7Z/H/C49fmhGfG+1Naw/b1Xj07+brCmN6A9C+Hm819KVcSItLlOXZ0jI6XfugfrDp8myEfas96SpuTFfe4DCl4IAoYBuShlU5Jxy6+6d+5Dr807/lIyGf7+7/+711J3ySsQCJd80xwDGLdJ9k1FMfDH1e/4e1c4eB1CRIT/vf4HRISVgo8XkfFInKNLsfD2QUeeBHGXPUO255tU5kpB5Tt1JAABAYxzvgbiEm4j3uYhBLiVw9k/ETeRK57YwOmKfuJQrNQtCTx0cI7gyannuWvAc21BFtQrWT+tY5xzwUdLZ2aAOpA80oEsu8gSp9dt6ZhSjZKMevW9BxbdlYTul3YdWTqHsu/1ejOOtpVBPNIpgc1thzkFzIO2JXKOAYKQ62ePeA2dagmxWBafwDjjbMiRmyMbDJGXPPQ6B55vJfWQjfdzJpz99hkhRvQxItIDHhxw1tgNvSkAPFrWS8pvNJo7wPPxqmSZeZvneZkDfbo24+dm8HymmWb6lYh++/OPfy9XPNO7UJmz5yBSBsbtvPCdiH/e06eAsZZpyN6cH4eZSLjrAXXKodTL33toBNtyXqv4MCvmCSKgEsba6lX62uSVU9et9NbJ1sCclT/KhLfKnqLI/HDrNiJExPxbn5qszh3hknPO8sE4chKMi/QBlwxcF5csAdyVMa6KWnFVr1ocOo8MxwLIOwJuyrPMOFeB4tFAJhz8ykdpFYFbv33OyIf09VUEbtwLZvugslnwpYnj5X00Ur9DqQ3R3n4fhu2vUJICOGt6v+qn8nA+MPXs9LsASAfPHwOL9xTVxsPy1V9GPbtH+qdsx6jX97gLQf2zfe4IENUqecbaNFmHpvyXrnO7vEPb60i0AqLs0nqfwRXrnJpH8BkAoFuJFwUYks8PkuPu6OgI5Jx4SaQ7ufpuz2KOYPVUKBV1gClt5b5v356wCQFgRriPRUkT4PlgrKfGpq9iw3SOxapTD4m8LLM+P6oiyBGpJ4V6dRdeOqWyyLxoSFFF53wFVqe+4AxwkRpY9X2PGCPWG8kletQdwXed5lwvNyKqBovMj4j1eoPAoWqvJ4dusag8yNbrZ2lbZMS7iCgxOZLy6GGbp+MOMqXeT6eJuU8T65zRR6j6oURUj/Ex0PxTrE2bxrzVjy8v8fX2BoeRGYDUu+mY53lZn5bXXS4J9/fDzl9eiHdZjBg5L78FTJe0CISkc000Cay/ER99SCmfWHJrAhKits3jut9zclt1BaqvsE7eUTEz3LH859/TKzSDsZqnouJpkQGO2x5QjTYApQc6w9KqS87zmjKwPnEN21g+9P2Nj8nBVS9YA5LCf8u9xuMP9+F2LurnS5s3QZPy49YG5z147wdte37eBPXRBU+JvHZxYgjkgwPB3CbdoF9qPtvBgQnZy9E8oDWKjAE8DOOv6mIGrR19ZyMX7nnBVHfnfWpE/tuDbM6WpYzVe7DsNfuHRZoAkEJjE5HmP6/fl3ce69AXtS7W+OJdNizLKB0+795xs+aX5SdONMH3AwJqR9yORE7bn1qv9YtCDEketLiyygAAjn7vEDli0Xn0IeL713/wUNRxyYx70lzPpAkOSr0G2fwT0JOcwwqER+9Svm7nHDrnR9tOytuvIDoKMzQlIkNmsYkBZ30PZol2FWIAB0YfAtwl8Pz3Gl8ghn0lgG5GuyEExLB9T7WajRlXZglg253jNNDfab285gR3jkY8zzUyIZVPLkKsF57m0T4tdDugslP2SmfmkdR5dk1qZDVzjJPwvoNzLqewSPIPoes8QhTZwrnCaEGfwWD0oYj0kUomdJ1LhgR2X4wRm75XGYnkWZC6hxhljOl7fKZ2PRznKT8x4RuNRH2BGFy28tqwpPyGPV9g8ZsHab+QAujrzTP+ucmGpedM8HwBB4fFby55n98TJ6POPB6G5DG9TtgOOGCzBlbAXH3kxozoHZq2pt1dZf5DdQ2tbCXjmSb/27qY9oaiTrs8z1vnjplmmmmmj0qzB/pMM/0gGvdG/Pie6IWa45ekncxYoYscMts1MENFWcaM2ieDNSzWiE8AoQjDvaU+xY1j1rylJ3oLnleMLgAwp1DvN43M6CM0T9m4iiIrQzTcMjPOWYSB6Dhb7OvN5yw52Z3W34T9bV7nbY63bWH0IgGXCorvQ6z99BKv94kSMQIdw2ZHK6y99LFj4XHrdAU0rEmxVoyCmM117dJSjeHi3MALvgARUbb6BUDwpEDJwx9TIdH3fc6LhLGJez6a5/nk/nEAPUHz8aIYv/QI8CkAC9PHIGY4igA5UbQwZw8mVbiY8gdQXXjymNByQVn7x8U6Q4Tj4xPE79+wuenzBS+haj4AwAM2t2folgt4X7fTaOG7lHfc+wIQdy6VRwBYc/TJcUK/6cELzRPP0jdFY9PmmfAurdf5+QUA4OnpAY4dmF2ek4Umer1eY7E4UuWHw9HRAus10MeQZnbPAbxhhF6NHVIXEIgktz1uz8A5aDQ+4RXh3D+gcmNfT3TB/j9e/XeTMRBCZROYGaeqOK1aNtHOz6tDQXQe8ID7eJ6X1xKNg+cAcKfHTxm4WBLiHQ8iwzwQpzD0KOpis+2cNZUCTY/rMuKMlVX+3sWv7ENnXHs4vWasmaIaQPHl0PLym/tGDNO82xJjhlQtkd66A05Ae4WxmXbmpDhekmuOP0PWpBZon1Z/v/8cntDlv66wMSFjr0rsefkb8AMfhbbKnbVYhhyvmBPYI7/4RwyVH0Z5zoqBy1jjzhnosIRbKUhKxp+pwSIRbm5vQASc0Tl6PGFtBgTlGnsAmPEvGXJvRgTAYQXxz34ZmSxsYDwgr+eeNOUaAEZEaShtwHc7c0y2rte0DG0RkIAvAjIQBuDB0cDQIELkgXZsOM2Pfq+Aso27EiAOIWDdB0T+IoBqjIgcERBxzFc4/v0IV1+8PkeqaOnWJg1dfhA5iSOfxrtzLgHOrgTR9TpA50+p/7FjYAWwFUCPYiQrNsWW+1x5VikJZjJsv3N0iExt79g6ylb/JJPI+wCMHyiB4Py2EzCPvP6wjp8ympf9k+uiyCJaTNQ1OT1PTzwT41jX7mMe2//H6ZRzm8qoJSXvUfaFHUt8I2s6PtT6sxB6rK9v0oXnTDj9fIX1l4CTP4/w7a/vSY56i4hI0/sbpbYMW3dY2Vmmf6EupKoWDX4PAXR7fq2/PMTz/C3qOtNMM830njR7oM90MM0e6C949ATjPwp+TnkR/ERKQtWe9KM80HfViUMUr7yp+6Vy6XtVGqkXd0YUqybUnhRFOSqoZi/0Yr7EOpAx1HMiCSbIJ8e8d7NVsHxegXBD5TjK17ri+iR00QhQ3fDlXLYNdfj1JMBx0fZGcW8yhdkib3tDy0Lh/ECS2z1iCKQvOTfuvnFPGbSdgQvNnVqWs2zbXdB5MQbuxyo9IljWz7bzh8+VkkphdZeVbjpeCrsFiF1fR4Oxk8stnz+skygoh4rZ9nfUPJRj5e5qgwCvnCqwL2heCodTXuCTHuBTVNSBqsPNfC+ofP7UdZw0GfXx1+aPnIogMHbNmAc6gXAKqqNtaNvFaOIMBAe6UM8E0jDuZKHDCUfHR2BNpjtotym188uq11A9F0KP78/fsbnpGzXR0APd2tqOk7ExTsVPae85wIBfefgEjDOOjo5E0WJKZ80FWArz6WnqTZOUelAlmHSIKNPYlNx2DQBmrJ/XAAGLxQJP354AAItukbz6raOSsnH9DO88FkdH8E7Upuv1BqHv0bfe6M7De68e7Vkx9u3bE0Jk8J3064YllPZLFUBTypCfQlPrYrMvGHj+Kypm2vWtbcNpHmiFwrS+5uTy6gXe50YeVRoC+VZdwcVYH6//7qecMuCXki90c8N4qkMA4RQlf1Erh8tjEcLup/QUlFPB2PXlvdtUk6VC1uhpz+EfGgOi/Ui8z8Glh+S+ZTRzoFBip2MFoznYj9muJ8RYPLbphNHa6METAN/3FBHbrS+9R9o3ZHS9LrddXfKEu8rhva7bejcAHBRxALueuXf982WjvNDWMZj32v0qNU1THugVH1XJTcWaFjOPOqJST+UzGJ33CsoIBQ4ACEys85+rJsS6mAEd7oG+vX+muvulHujV+xzhIZlFhvF0gaPPC8nDTE55l6hlOCsMRITNZo2v6ml5ilM84TF1D6lXur2hPooMPUw9PcETb/95AL3PXn3BYvC94nGjqcl1pDm4r5x3xSswgBt6OaC+jSwlm6dLMN3i+PPvYGZsrnsQ7pKxvfH13nQb0LY14Dm57HFOziU+2Xhbp3xqGWHFwpZ3vkPXdSIneCfAsIYkDxxxujnD3/GLeFsjg8jMLHI+8or0oPzreZB630CiWZ0Wa+wDYXLduEAdrvohXTUQ8PfqZ2tj6RUvXrkeRBlQlxzzRelk/zXJHwtYbh7lErJdj43IqwzIPC70Ayjmnskw9rs0KNK3A0cO3eJIooY5wqbvU68575R3kjK8k4hYmxCy7JIfWfWavHMPkEMIYthrQDnrd04RQqQzXN/DuK6KB2OL3tPIWyyRfcw40vQ1EdkI8oKLnUzfT5Lljc9hhgPQ8RLus8h5jhy8X4CZ8fjXE27dvT6D4AGc/v47+tAjfGVE3CIU7/Ux2yNU9aXi02PIDGV+Rb5V+wK1XGluRx6m4+OVkPe6is+lkdD6e1K5xqW5r99L4Nx+28OrsZvKGi97Sncz00wzzfRRafZAn2mmmf5rqfTyaZnfhGoXlHjbMdJzrPfVgLiWpUrdVmlLBcOZ5Ltdml2InLQC4W6kKiWTXRY5AJFHyl9pyNQb2s8ra0c1p+9j2YQiSZj2QIDHEOQv671i7AyNN1afu6EuuSq//PxV6bUeb2Povc2R1rtp1NupFP6T0nP/CowJeW8pSFXzbKZET2CcElX50I0YjyCcI94xaCXCc1APCgdRCoW+RwRnoVrDvnMl+Evn21fVdIA5JqA4NhraKfC8KmIH1Wp6OcIAYoggLyA6q2LOYscSuVrPNiHgS4hKU1Qzyvzpbd1MAek7j9AHMIDTUwmV//37N/QhYOHUc4WBfr3GuhewPcSA8P0bTj9JVICu6+CI4INHHzZJYRVDn/rYFB0EMXgAAXEJxNushPsEOtgT/YW2QR+CPkz4+QNprMY2t06zNk6vHSofiYDvN9dYYomI+2pP/+3yCl9ududC/xH0RADu85qxWjr0t5wMPZ4gm9EpCAGW2zJzO2NzrsSbqDlX7vtj9+8zUk55f0D9x1OjiN11mX1vPlk/J+d+Wk+KT7bc6s2l/D778PgcaU62L7lt81tUYp8u3/d5v95S9a6UAdv6NwSWGgDn/0pq2nfGEo64u+rgvYMnAzI48QICVAYdngzvFui6Bf7nz/+AAWzWazzdGK9VgBq/qMHZLrrX7qnyhb8jmQf5RdGVY8bcKwYcLnFNhxm63ZGU7XALh0vl9wi46tBfZ0/4ZETOyLZSSoJtZvDcKS+agHRqxgVQ5epmxwBp9CZCMjKNLDnON6FH3/d4iN8QWQFjagycFfh8Uj7cMSMi4sGJobGFMz8kUowtxY8vVVIUZCHazQDZPM1br3Og3t8scpX3BujnsOxtznPZH8cra+JR+96miVS+kavsGQ4Sxt9k+IFKiGMyODUZzRElMFau4dxcHRMmcyCEBJ5D74lRnmWGG+X2uOt1WmSfU65doAw8N0CdYUaUOn4g91VgMud9w5GDdx2YIx7/+pbAcyPHy2R4FHGLSMA9MS4s4tGOeh9MZtC9d8/UNMbGJdn0HRa6bQD4TDPNNNO/mWYAfaaZfhJNhzHmJKR8CCoY5kOIpzSXH4jeolqVhzoK5pdcK0UJhoQMoqeQvxyzUrFGr9IzxsIR3gLJujm3SZnaEQXeUhl/E94531TRHcz/lhtBh4ozqQMyMHbA62ZwHZK9uOkyimHArR6zsHV3JOPwgoee6OVQSwYFpeJUf5Ye9fb4NmTsdJ0HVdVn5zPm9fkSaoeLkZXZhrbaZllcWzdPFyw/TSnCleV2fQ0wGIBN3auQXUmoNSFr2C+lMD4VAn57yoNhSPryvlEv8OrLRFu0HTnk3G6qPQdqRW+i1oVHHvZ2dGBZKbygAqmfijkUCwVJxAMYp2AFX/3Kw1RBRIz1Oorw7yQ/OkfUHigGKiegGckrZbPeYB02oky6jVkBpyoKwhkAgr/wcF5WtxAY4b5XBclDak8sxm96Z0QwbFzG2QMIZwj3EX5F0Cx1xSASjxhinQdqDJBIp5PkZMwjQ7zvJJlz8lxHXo9tnHaLBYgI39T7HBCwu99ssFgs0oUhhlR8jJK18Pv37zg6PhYFmFdvGEfo+w02IcDZfT1wdHSUKnty8gmbdY/15hmMiA7nAICeH3BKh4PoH4q0vwbrYlovf2Ld3op4YpVnxhNyePJTbrw9OQPIREAPURD+fnWVzgN1ePMpOo3D0OrvTbd32SBFNhSp8GPRGw+60ZxxVgQ7SNsGvsDNBk7NqTGlaLl72vWfWEDzU63aSbFuvgWY/vIh2+x3UdI4pHMEjO1mDJb1rrk2eYhzXsMqajTh3wZFj88/ju3+2NQbNS8xRdvYklFeo71hj44e5Unyye0VG+uvd6D2MTkq1u4GNuKLHhwrdeTeiQadm6iivGU5Xwk0Ud+x0ij9jWAsXKegkwA0AUVErJGxvbMF5Xvi8sDHIPNwBXJPCBgu58+Y0WGJ498XiMzoyHJTR1DpEQgALBExwBGPXx7x6eoYzHY94YQcvrGEnWDz8J2YJoO5uWMaHE4/5z1MTmdb3184f02ONU/x27KcYoOR4xk8n0prNnb8QeXhFW6w/vIZ3WcxAj3+7QirL0AsvVwbSp6kI+C5gfGV8TSyfFX9RzmVNGQ7M/oY0Pc9njebNFcjc9oHABnr4k2eZ/EFi8h0q0CzyRLmqU4AAjLvwkUfA8D9aMDJw15iuSo5cuptrVG8zBud3GBslLKm9Uy0VE0xe97HKNHXJLuC6Vxsf5RP8/hPMpdelVRCep1Xw1+CU9lV1tVF1yFC3isD2PS9gPpab+8cQujhvAfHiF4BcAs1T8hydhmBSM+IMTKRyimSzz71tVNe3AGLTUCk7GV+wsj53PW9nRbDs+Q37VUaIF52t0Ue8ipzeV2/gm75DzpmSj0WAei6BWLkBJ5bykMA8Poe1ps1+useUXmjJQMPFswD4zxjua1QWfcJ/Ue60t5n8/6rCEFjNKH/ICJZyxuVTv3saSoB8taIZhd4vk2FPRaBcAbhZ5pppl+JZgB9ppl+EB0UAv0jaX2nEKqdtzFA3IATP5bIETz89AUiJWRGNR0v2NgK1dwiflEOWc6kAo5ruUgL7cVVyORtb5uKf0wtU5uvKesgjDiL0FX0veVBW6mwdmv1LOpBVk4Bzhrgz2CYX6P9TuLeoJ006M8pak8HEqFjqc+9JwH1wQKOnzNwEVgA9WZsSf1d/bsQgwmTX5pCttQ3fRbjRhVwkccUgQfQyFzJ+tBWABtXhtT32lgeEd4K4N+uHQ2LPQUID+pZjiXrm3Hlext6vg0BfwiJdXvxbG6/1HXaZ33ddw1mHrn2B67fh7QlqTySAqoYK0S4B1I+9EKvp+P7Eax50cMN4JaiHCFdQ0kVN8/Pa3Sd5BSXtR957SqAQGZGCD02cSMeGHeqvEU7hhiLlYd3uV7UEbCUdX1zV6+fpQeu1Ft+t/PSXSjQigjnfQbVKKtnyDnEEOS8jeNGeyN5yru8Lquyi2NEiDH1cSp35HUdHx3DdzU7fnR0hO/P36u9KXDA07dHnCyONUy7GCl0WIDIoQ+99m1Ev+nhOy9KM2Z0C48QHXjlRXl5F9N+9cvrLgaGMjoGJrWavyBN1P2Uh+B3mrc0vpX9c914nDcXWU5wK+eRMni+y+P6PRRhpsg9xbSxxwMY5wb0QsO47ypXP63GEeNtO2uXdwiIHpFB409Nn/1siroGGaOZPebiABABdOUt9+9I0wrbfFM9dNoOHbl+5OvwMkbFw03RFAvHr0yLMkVtKg8eM4jDlvX0nQfHgBdJCvjhtdsMuFMklREaU5xb6PakaNc1wvLM+qKsGMU4jcFV+hrzTkz1gEA3rfGQSRwyv2OSQ1Dd/e8hk/28dwhB3ssZi3zksER3VfANmvrApblTADQkQJngKRt8+/qM088noE7CNfdEIxZHU3VKpc50IO3qs3JeJUBZD5kH+72T918C6aXh/OKzT/mp4QhMJEboyPK9U12EU1k7p2aq/5uFfsm3J57UOXg11LDwzkSkhhoKoPc9QgjoY0COEsEDdsYA5dKo+hpI4d2hOguCAO0Goneo17eUI36ko6XsDHbnvibwSJ1Kz3IiYNF1Gt5cHpqzIhTrlpWT9goN086MyBY2PUJCuAMRea1N+hTV3yRDsyg9Z4a0Wa/S1De/cnhQ4oGq8ln6q3MClpsOjAAJKR+HhufErAbDWoru+2YizBwRCq1IcaUYU7u8Ope7utnsfSPGie4bJQthPJU1td4H8nyYmlOMrEeSdgDd1SWICN53CCHg6Z+/cetEp1QattwS8PulR3/dg+ked5T1UdueuYtM7VLvv9krf+zavcpF3UfZoAFJGJ4Gu4fHpY88yv2+TQ8zzUOkZWNv+lA675lmmmmmHTQD6DPN9APoV7euO9j7vGDlXtP21/Zb8oIcU7CrFMBoAM/KYKAQV5ouGIVJKX8wcr9lgYerayk9QiyDDQTkyBIyqxEQUogsmHKc8g+YgFm0UT8rphfAHRFWqV71OajjPBdtNEU8s3h63YOxYsZNweGXfulUMuvZdHnYXxg/bKH1VnpuFaHhs+S3CdCSy655tyRW0aJcoCRolWHfziH50LjtgXa87Tn86jZwJQQeQgPv70OeS4d5v+91HQ+G/cF0CBD9uucMCxnzan+JoLZV2Z8e/jL60WJj3f783RS1D6SAkU5ngniByFiWWRP5DPE25wJ0Sw8QowPAxAh9XgjTcsq18i3GiE3fi7JN65JqU3xhPCDyJToAznfY9Bv1kiHJ673v+Kp6OgLUgcGQXOdBlAXOyW8NuQhWr40oHhQluG59uej8yD5FIOfhtM1RvQBEEe7huw7n5xeGFCGpPrKWEt57nByfgMEImwDLZggm9fgAnBOA3Ke8lMC638gaHnu4SMkrX/YBB+cYCJw8OQBZ0z9uGOpX0L9cKVMCu/K92csLOqQnHGSvvVwuAQbO7h5SGeU4uVpeggj4envz/kYYjJQTfcpjPqpCNpS3ETCwMxtoKnev8YQMsJ/repjBizHv69crBV9ztwCUnIAHkCjUiYdsTjlPsvey8Ua7X2yxIlb3tiDs0IiuuisfJ+zAz9s7RwCMURqeaNtXmHhVn225U0a7JkqOAAAgAElEQVR6P9IaabSZJttU19Fe1TJDleE+XJbVyBPNd4LsJQnAowLaZvFyDTEI3wCn5SH/LvZE4eQJJ4tO+AULc1zIGiZp5thYe8ybwQU8dvAdaWrkC11iqeGt1XdfI+84fwr3ySlALqAWgRBCxKLzALOEmHauKdsAGjl2cnWEELKXuSOHdei3vvfycF4jtl/30j6d8rx+L/pRbMJo6rFSJZDk+LoPVmr8aQaBK61wm5ZsyZIHvb+OWjQDdIt7RyBmlav1n8qLwtJmg/dRAL2uZgWgCy9uvLP0ZYzZgDQEAYvL9Ez1OmrzmBNQvmt8gbancbtXGeYcTQo6tj9UGJQpT1/UQx4h0Z3MMMDA9Ox1PqxAGyVODMN1PebC2Mf6lPSPg3ila+1MTrI5G9SIwLy0jbxukgs1vvVefvcbiV7lveiVYgzoumOs+77SETjXaT3FqM48yNMSDAPlKbUvtVP7I4KxCX1a74P2gSNbwxndJuIbAcfFaxAjIEaARfDJ+843spznQqf6XOP5jO91VjUVnczD2/KUm56IIHyPwxKOCEdHJ+jDBk///JPSHwCZrwOAk6vP2Hz9qs4wco2NubR6Wz82c6R2JMjzNv8dMqSTQ73o/ymi5tPeZVUy26m6rKm93DlXAejtNVPjv2I0aB/ucaaZZprp16MZQJ9ppplmOsTU8zXljz2nAKqSGmgL1zkI2z3B0Fa/jK9lVSiDcQdSZSoJUF3IkQzghoDW+4OgAimLhW62GNbg7ql9b8M2B6h1PADfCMR3qsgeU7ZIPrhMD5RDt98RcAH5/dYhaYfq3EPvH5hzHHAz760o/Wj0L8e5Pjy1a8eTy0oKRrF8pd+PYD5LY5XvIrAkBWwYhAjHhBiyoshyyXEsFfCygIj3+RZi8VzxRFh0CwT1tA63fd0O7FbZEs5hHl2isI/wvkt3MseMmCErszjo4aSglmtoC9LjnEt5B315X2NIVdc9ryJmMOWPvSpERLllOc2pWC2c0zbFEkzS4pMyzCNSTIZa6X3io+dynmmKpvawqb1o2ys2RaJfLXEJ4OZOk6FMjPHrOwk3+3l1ia+3h+VtfQ2V3vBAHrdPmZGqqTl21nhW74LPnmjcC/0jkxiPAgYWGIRWhoWeuk+/bOVFeAefV3oS7qxrafhh2u6DKI92a+u0SvqQ8rYf+reRpbxIvbfPhrq1wFwukKCrFBUFDBBTFos41yFJRAbKKa+Q3i5Rkpt+tVez4gu4lUtAnPWFczZnoM2/BDMngCZ5+suvZPDQdZbP2Pp1KEMWXQoAEsFGf4cY8JHonn48iA6Ih/bdzqvemJoBbMbebdsjsnf1NmLcgnClRRMIV1jyddUuw4zNML71Nt/+AC6M8hlRlQbEMa+7UdIFRA4SppzFzzoWBrQ/ggj1OLL0D2Sgv+fkde+oiVSoBgZOjQSonJvIMky9d5n+Rr3Irb0GgKdLFUpP/UHJgED+x3xV64TRNhD1HmtrJTPDsdSdicSwFlTYVzGYYgH2F8YD1TCQQSJym/x0umYFNeq19SmyyGh1N+boBd+pqDNqHtVAc6NvBJyqWNjyuI/GjylAG0d2AAeNtKinFp9lTjjn0IcNvv/9jEjZq7x8xMnVFcLXCKYclONNRu2Iru4tttiK1y8MOHZXpx67+3iXzzTTTDPNNAPoM800048g5VBfKjy9JzOXMV8VBMtntejxCzndJARNeKuQKodMwZSkl0ZAypbfdV1aYY5Sh+e6k4HneqrM0HvvkKSmCybcuQiKwJLFU9GyDHNqAxe/SxiGk1BT1q2yTE0CYW0sMDY0DCy/QAbRl8jgOUFCta1QhN9iztbphdHCfdFD9wAuUdr9Wuj712vJU4l8+O0D44jpK0eOlAL+L0pvVPmxPhx6or/Jo7Y+81egau2gbIDx5PIYO1PlCcPC7LGA6ABkdgqIziDgggD0iOsAT5IvsFt0ompTQJicWMhn73MjW1cetE6Sq9t7h+w1QwhBlDaLyw6bm/MqD/o+O4W/7NQrTpXOkcEOgIW8S6tjVl5ZTckN52gVdp7rscXMGgIeA4MkEAExat/msMt9H7XdjTeQVkZCLdrSlvesGAvlZvIyERMkIgAdEDcOkbR8LAEwety/kcnTTD+CTvdYasr3aYkRbKcuby8NJwxGubu7HZa05Zlfbt4DPG+UzITBov1YXrqFTnXdeiTGGRMiceKHnozx2lGWxqRIodvLS9tbPsJcMqCyOABbB2pFPgYVJjhNz0H1dVVhNR84fH7xHN52pe09xfX7ADkAajNJfZTyp8Pbi4W5OVms3jJTqvW7vebn06AuZSUr46wRPnFwzJT6ObyvmXHm3OI7iKZltOq48rfmec5UzKCo6EoBzh13C4QY0ceQvAsT0JOAp6ggCe2u6zsxxxWAMULWB1fLS4TbgIh74HaJ0z9OAAL6sBH5xi/giNRbV0JaO6IUxppZQiIHBeMsrU3fR3hHIF+DgPd//42LP/5IdWOti8iADs57bDZr/HPzdaJdtdw5aPD0gVfTjwbPgZ8AngODrrsfGcZ2SZmjeUzeuCPCBZow2fbFmExkD+Es9hfe54P61XtEnrEMZoIj9fy1MFW6BgWO4oUOzfPNMfO/rSw2NX6mtp89qRxDZwzcQ+QOab88wKI4OedEJihBRO1I50T+aA1NTGYqDV+IZV1jkjWNkEOp5zWqbLEYHpv/eU6XV+iLdH3zbphrHSBsYhBv8E3Q87LPhxgRCj6gD3Leq+d98lJOcontBekbAE6RvrTq6KOmf1JFlFNk3dYjzxEUGd+1pZY/vHyNY8a6FsUn5QpnSx1UX2wpLMyrP4KSk4TuIuqtv4S/knfniOD9AjH2+PbPPwDleZL6G0DHS2y+Sth2e28PI3WVfqK6vpOke1W6Lsts43fmvXjbptaoCXEIeF6XM5QztwHq275/JD5ppplmmum9aAbQZ5ppph9DxqF+QDK8wQTIBFSbQIhCIbgnhzjqB5Mf1KAs2Cks1larlIXVwXNRAWH5YNH9rNfArK8JIAdywDcidBHoIS6XHgJaR0BB6LqqpaBFKqS3gjhNMPZtD50z8Dji7GbPsSabVfk5I+WvWkX5PlD1Mle5cK2sa9TDcdtrveAdglRT1kuliDbc/kH3qvC9n+L5A9I7KDenhMk3fVRSfvy61KrNBmOwWK8Yed7KVQ9gBboZDNwx+FIVL2AQO8RIGi4wK4S8l8yo8W573/llV9VxvX7OgHOUEO+HtjaNC8pelqEPSB5eqhAqlYtgRmSA+z7lKy8Ng8yLzPovjTEicAhiPCCbC7I2sgE7Ykwe6wCwWfeioCOX1tDIQZWVSSUuyj3uFUDPSwCjXlPM88bFCF4B8bY2YJi90N+X3rJ/txWTR8bu68v6jHuzcz1mfxa9QRXM83zSU30LlbnXz352X+xBRLTV27z1nCtOyFl2AwC93E9lD0C1L+RzbMhMwXOOXYe03iZdcVIsH7KnFvWyMnZt8r+0peFhNMUSDsOzAsyZKx/j25OiHZT2y/3qkLlk27rK8cX2yhLQR7kOqMedShuIiEAy4P34FG4lD3S3WuF4cQTfZcM6+zSPXWZGCFG8Og0Auw+gMwI/KJh+IcBf13k4EL6vn9Pr6L89DSsAlROch/MeIQT8c/3ldY36dbr/3agEtidpz35q040BGQhewtKWTdM9AZ+5fCDDi4m5LMlsfK2MKWf8bmuoWRBX39kwchAxghmAshm2QDzQYaHbM09rIOxYhJD39Ew/a7Z72yMkpZGD9x26kXDVVcuJJtbDch3lYioL3yRtFw98p5CtpWNKXurIed5Z5UkzVK4eZ3JPFl8Kb/XSOMGAXahhlMou2iTLQ2/XZVFFHuC8guv2Tq11hQGw3D3+zmzkLfSZz6NX1XTC6qFe0FR0pdZAxMBzi1bo+AIEgv/sk3e8952IWJyNScvyIgDPFzj6fYHvX74kY9Ipnc9htEO+bmgv8Nyute8jY3OKh2qBcudc9XtbHXcdn7eDmWaa6b+BZgB9pplmeldKwgAdHr7rtZ7nzNNMpClqyOpIJRCqf1tOe5sSlwvmkaDWw3pxAWiYIFYp+ZwKsAMlI+vt6rlZgDUEkvsGGkmk0OxUsNltMHYqASJyYj3sXApVRiHgQTvlPDL8SNMdgFNVuN0X5rDU1NXqvssTfUpgMiHmfOL4A4kf7Iol9Hz1TH1W6ZVpgPpZlC68L0Iaj5F5tC95e+41AmA6hJdIEVOGBkNqrykUH7+oYvhFIPSER5mcGir9y1veup9+ZGjCH0Hl2vuob+dcTfIlDUTZ5w9gnKVfkWXNdwQwBfQbCSfcKfBsSqWF8+AlI94N334pjkuuvYh+swERVaECCec7QXSXVg6CX/p6rthaXDyVNVkwJUMkygY8DPR9D45R1ko9b8s9gcDq2UHkEEPIYyNKeMbNRkLPHx0tRPERASAihggODERGZM1JGhmjAVbTOlOCR5T2MQakjtSl4zESFosOIUgeeawc4m1Ehwsw7hEwg+g/mk6Vb3ik3VtGGUbcuIszHQcprOUElcuTebAzDnjXW9Y3S4/ytiTK/5R7mnivNVuU5YSHIgz4Y9uzr1yqk5JcNbkWBjSFitXrfuo0Isk9nSPTDPfK2mAo84ykmnq2Bhb9nrxSUyvFs7AGKIpQ6qT8dS6guK6uA8EBZEDAWO9NvTgqrsh85XC8FOu88oaRd6QP+dVoBBSXz3ElfvnX+PDSA32rwrwou5Q3qNpPyzguBtJwBYw7NTjTJCUiCyF7PnbeIzIjBujmLJAHsYY+rloxQo0X7VvR5Ggcec65CgXdyuPkSLIBhxCSsFDaVXe+A4jQ+czDOudwJMgo4iIUBnWZnygf3H06hdNIPz4Z7yGVxwyE0EuuYcrHR1u4bb3k7ac/Mr0Vy74TPAf27qQxD/SS7Ny2EPdf6RoA8BlXYDBu3Z2s6iyAKkFzlxvrW4BohCwfJxmqHTvaoKh8smQ90n+K1EaOYPU+Z/UUtnmfAugNZLO3eSEXTTHCD2S9iOU0997BO4/Oe/jOZ3CfMt/BrPVs+GwAcN43c50qpVFUYDzqf3YqF6DUhUmfcX5YAq47l42HmYHAUd8XJ10SiMSjnPPOJykyIhxLT0dti3mKm2Ed60pv67yzNFvMsnaEmJolJ7I+qSQbDwvWOsEBDngOQbm4IVm4dgfhXb8T8CmKx/nUOmQguR25pbyuAhKN0GEF/9lLOityiBzR+QWc5od3nUe8usL6+hqONfAJgI4lzuHzP19Uvt0SBYOFad89XG39HuMxpmf5tCFHKRXreAYA93LP8zTvGwOaMSB9n+/y++CqzDTTTDP9UjQD6DPNNNOPoSxX7H/LKzxy96HkCaEsKZXHUyX0mP2Z4FNTWaYIJwuVNwSHUrtMY1KC6eMySv0c+y5aUn1udULydomGMFWKi0JIPx05OBU2nCeAHBCB6ELKWfagjWtzngNm9Ut1MM0mxHx+7H6e6FP0QCIcE4ZgtuXNW/K4QmNsLJnSf98RFkeeCxRNNYHmhXqAV3mgq1A3EoTvv45+iOe5lVkpQ/7dVC5/jHY5fNDjZ+BbBlZmvAIwAmLMihrL1+l8B5rIvynlM+JdRLhy6Mhl8IYFVPZegPUtyzIAIOJBlWPnCHdB1qsrVTxBFBwEpx5tUr73HjFmEN3CPrKtuY70PBBjuS5z+htCDwvhLsBB1HB/st6HELVszV0KU7b1VVjAvE00ChQ9OfQ8yPXhBDhkUIPIgSiIkcOSNArAOaD9NNP7UAtWG5Bt4Pc2ELoEx60cOzalbhujx+bevag0BhyhtwfPx+qwtQqJrC9PQZXX+HvTR4RhB+E1TUnfKEotwkUCssmBA6TPmYUn1PXJlPmyhMXESw4885Kyl/Taej1L9aMcBUn0+7IWBrFi0jv2f49mGFpB+u3+/N+yX0/Ml21RCQyOZgz59bz/5LFix4fguVC55xcHp+tcAe4G7OQwuaz7qNVyX9nhZ9IZAx4X6K46LLwv5kwsvA1l7ycIPwGQ8CXKo0T19IXe9/2mR48nbCDv6vzsDPf3d1heLHFyLAC9Gf+Nr5sM7xd7LKm7uKuPSz8jj/qPol3tEoD0FrdUrLfKBTsn/+VXzVe2JFuA8d12zEJny0EDgCOzzE22+RoTeGsFOKegJdfPe6kMNWa8RwyE4liS80lkBvE619DtXpwGUkSNwvCaI1fyXZ3HXNsOKr5nj3Prk+RFXvaDwsoZpOe0vyaDQZCkakDJuSMZOLh0pJQ/5UrvHWJscX/ZtL3zyUkCALxz6EOQc94nOcTCvbO9J6JJY7NsaJGB+W1LxgnXEkmqCzTaX3Gv6XVQXF8W7fSejpcACO7KazQB6yFK4DkAhE2P8PUaHYC+0P+c/HGE739/SeNm62iksZq0l0zoul6pz6xWY9M17jF3WpB8CjzfFyTfdXymmWaa6d9MM4A+00wzvTuZdfJHIQtVJVQLH436Z8C1T/KLhYI3MbmqwCBgKC1YPUoQ3QRZk1rU4rd0xhE9pwE/KiAUAhGxKREdPIkwhKhh16pyRJCEEyDJQHRyBHhGDIbMqwWzgUQsAsudNvpJZZPLAljOgnZmsPfxRG9pDKy+J/E0H6N7kntWLPlcsxeamUgk35p0HMWvVRSh6pg1pJcq83pwskpmABeq272jspS61D31/QN6DRjbhrv8b6OhtzkX39svM22jsu+WjVLDDGnSuKf8mwAEBNAtASsviiMiOATE6CtB3byhA2KlBqcUEv5B5t/1BXDpVemX1xMiQnfpsbnZ7oWe5+cDxGOdsb7ewC89us7BkU9XiHe7KJIIApJ/X3/D6fEJNHEiYrC8q0DfF2MMFm5V1nQnGjtVnikYDwHWF0dHCOrh4Zwo62KMCNwjxHytdx62D9k7iaWhzch4ZjCOumN0XVcpckwB2PkOG86ZGaWP6rVwpvehsfzljN3guQHf51yD3wYYl8e2sSjlfXvRlgFR1usj0SMxrlaEp9vhuTMmLJaE/o4RCVtB9jMmPNKWDtB5lXLntjjtYdUeMJft/Tu7ugIp8xopp8Zqwwk4IFcD6cwAh8wz2vpe5fHEBDCaABkDA4zHQwW81uA56W/1LjbgvWz5nnt3WsnstmQAYMX8Gqvczlq2RgsTA2RMEV7z2/U+kN41aoPOMZB8G3huxaadnQDEtI3mGrSyFefgwFIHVfQ7BkcdJ1rLFI3rAxMB6C49FgbsMCNw0HMECZuf+9FyLXvXNe8079F38a4aH9f3t7haXqZjMQR0i6GKzzmHEATgc87B8TkYd7C+TE8iaGScMf5i+O0j0r8JPF+xpCgDkLrdgEXxWs/6g99whR63uHPGk9uE4wSYExxIf5cGVVJ+Haqbi4cySwByA4fNyJ45SpjwGEFkhqBoUVxEJjgzf9l3+Gx5jy3ftIpZDilvPGPgEQQin4FDjSAlhluqoyKNkBVF9yHRpGx9Uy9my3kumyw4/QeYo6ZeiLoFldFX9DoqQHUgbbKd71L6BtI10JETQ10POM4GThZdj0A4PjpGjDHlOo8xJrDbOZFlYmSJbIEyZLc81zvAd7LWhBDQ90HfZyxeH6PzWe8EAH0UY+TOS6wbWdcYrg/4pnv3Cefc5oB4npu0RbgAwFj2pOPsFg5L7ds7BBqC50AdERAQ8NxfSalHiwWcl+8x9CDyaV7EPqIPPXrl6cRj/QoA4/vfa0SdD9uiDEr7dw/c/SMJ7r9IpdQqFW+0z33F99LorQHT22va77vOVQ+bgfWZZprpX0wzgD7TTDP9V1OtIGqJ31VHMPBELx6bpMCkXGqURaXiERncBsQq1xNJCE/Hml+Qy8IEjCIHcup9roA6OSchhJ0HmTAHBjsRkqEC8CUzbimz9A9UOp7nPFNj3TdlnTvoH4yD6EHLHrM+t7Be5bPremShpX3fXLTBNbB4VRahCu9fnnsNvVav+6sohqfovayZf/Fu+eHURkIoc98B2PHdPNHPFcSBAjJxUC4AOPJwy4B4RyMl2hHG5qZHd9mhc9ScA/yqA9/uWqrPU93szngX0C8ZTkOlWihZJlFg9dyjow7MgO88+hBhHiWmMAxBQlWKci1pnVUhUSwSadkWRcVmvYb3nSrrAEZM+SRNqWEe8pElFKaA6fLbQULbM2mkEV1zPTk4lw0V5Jk2t+R/vU40ChLMYdzfmsr+LPt1DEwfoxKkTulM9N6DPMnfgJZ8gTu6T/X6qGPl+lY6pvREv1w6CbATUIV4n6LFJQG3I+uR7v8/2sv9IGKg9J77BMK3BEcXSlQU4LnLCtUYY1LWGt9pRoRSuKXeKQDXAkAv+VFT+JbGounZtt6p4ZHYtpo3+suaPjDaTAZI6YL/SqZgK39VyUG2aU+UUexRFXheFl+KM7EuKNZmEfrdjdQvxzFwJOPPUQYRJh734YggXqG2949RH/v0vfMLQO+xKDXpurDB4/U1Pmnrbf25Wl7i5OgYHANiCDqfxuticzjGiIAHtBNtxj4+FlmKkJZsBiwZuHeZ32Pc4sHVoDqp0YmBrymykpbUUgLQkxc1F78ljVJU2DNGA9KHubxLAyoAcIXX9mALfoNxxwQ4XoKyWVtVvrSZqj1CvMZTg1N7bd0iFfbzelf0hV5nwLd9j5FTSj55FGn+7aJPrE+16ZEDmAU0Z4h3uHcevaaBci7vuaZDiQz1FleQWPPOHy0WCJZKisVYwspkAH3o095uESv6vi/6pEgrIa2XHO6EZDghaQBc6s+g4+C5eI8leH7Kmq0Q57DR210utO0MxhXC16hGAvIOk56l2ZKWLOPH4xLWyc6YjsRjeJTEzFh/2QAkRid/Xv2GyIz++jqFcn9PGtvf9r4XxSwa35pHnyf9l/fsdHzi+3g9x8ueaaaZZvpvpRlAn2mmmX4YHaqzej2PlsNmDRi+Bt0dhDFjmJ306PVjlC5pr93SjtZLqFREEQTRNY9P88AcyJ2pfEoCsiOXcmMJQlM2FgqeqwBk3ucqDME5dM4hMiGCQWqRHQA4koDIpd8HaSUs/NYtiRLOeHeRZxqlpoHoVvmRwTHlQVCC5gYk5Pyj6m0P8RR3INw6uWjFJGA81zkYrSW3JILZVwd8jmJp7yAW04Ow8FQD+KygvUuC+HC47DWcX6rY3dMo4SPSdi+5w2kfz/O39tR/beSAt6QV21omdTLVrI1VA90eizljHgQGXgzao0qxBKCkv4U0n5Qt+jOtY7YMqdZDx6rrPJx36NhjvSUIsnmX9zfnwGUnSiDO+RQDZy8PhsxXRhtWuQTPcyvCXUQEwy0d+rsAtyRsrnuc/HasfQKcLI7x/LxJ4dcjAmKMMERJPMLlaSGoV6dz8A6F0lzXJc4rlPOyx8QYEKIqycipIkiVYRzTWPVe+ssFB7WKAgBs4gaAeLB47zU8JSXFHalhQFKyxZg8ZvIb42Q89BG9in9Vshznpbe2TZe2n9t52Xqal9QC6btzoMsostyT+4Pe9f6cx68+F3gn9ErmSB6jWeFstI8HvAFMZ0y4uR1PFzFFm+uIM2DghW5lnpbJYafokLU9GTk2zEMzbsbvG1KZBsL6ySJbgAByQ1Cv9ISVZzKqxbW+uDpegna23iT+LwGtSJ/Z61yfaaxvGmvFM8qbtxDbTaOX8ovZq7ekV1dhz0bs9jxH0acZ7CnDox/6nGFVubhuyHdlg2AkQCcBRSZnmLEFWJ01Lby5fi/q/5ZUsDWjtAfMAAA4urqS0MmNqBNCROfF87PznRgo217svPAy3rxK5abOL3B+dYWHr18BAKcQfmfRSfnf+x7HXSees76Z2yVAQuqJ2qznVj+T5cYjo7xdX//IMOvVtOF93t9PomZdHfOIJZD0WwOEXbB4qqeoDaURZVqDXQEko+qItAOp63H2OC/Os/DMpTGpSd6yXat3etkIK780xi1VEobUjvXDBJVj56IYqzfuvr6ZCj5B28sQsJspIgIgyqkmjDfOe5VL9bMdv/U4Z9WxMDMQ86oEpgzAW8oGrUfnF0kWiBzhvYcZEjETTo6PsVlv4B2n+S+ppcTYtg8Bjhw2fY+zkxOZ0+R1HQW87wAFw733CVDebDaIMWLhOxwdHysPwNj0vbxbBd6djhNv44yzbkWOy7MoRmw4atqVTJ/0+taUx7zru6sOne9Sqqv++hqEJSLdIQ1LWzN1eFhId8cAYQV3JXV0ZLnt1XjYu+TqzjGP5Z7usOBL/M9vHZ7/kQQYFmUnYr90RC/RV8gtWdY6ZPXJQ5cqcXv3faSx8oeAefs/15NG27fT81yPc1nhmWaaaaZ/Kc0A+kwzzfSu9Lq8zofpHw8lM1htwfPMQI5fv70sJCaS1FVpF8Ob+kiZ/KrJymu3acXH+rQE0r0TAJ0qyVcxHxWIiBzIm/eRAjeOADh438GxWlODECkCAQgOoGiZh1FZkVteqyQiUPE50gn7eqLvIgcBEu4LIYth4EIWVsoc5lPj0pQVPQGdyMIgAJcRuFFJ0DzcE3H+ZGBoWb8vvaYvCvDzV6PXrBHby504/oYKQFO4fCQaW6YI4wBb9hrUDzYFulC6R8GdmL5D1pDR56u3N1+mexkC3Dqv3mR67dHxMWKI6oVuvmnj/UkA4k2Av5J1IwS5LtzdJMVOea19Sth2OzasMUNyrQPQfODA9y/P8JcegUNSPJp6KCKCg6Z1YEJEhFOllZGPQB/FYy5q/guXvITMuIggEYuzckPCycuYCuqRQhAFe7eQkOzOSXyMGCWPumOCdxk8b5UiCQhICkHpFQm1Oeznj+pV/CtS63G+rV8fSfaWcz7HA02nJBij7eB5XZ99Pd/17szQKJVe6CWNRYR5TzrE0GNrKPYJckvC/f20Yc8T+MN6oZsiP4MxnAFu5vEllnWFZ9KoGM3exhrSttyri72gHGhszCaMN+ZKkQtAAHw018ivXOSB7SaiYYSgwmjzo4DoP5ImeavmeJaDOE/5kU219D4feHuDzusAACAASURBVJ7vqguykW8JkJR7YH5Ywc+mYUZqg+cyiD4xnD8CnTHUK5XhKbfJwSsyJQPVeS/h6ZVC6AEwvn25xsV//oRzkk7GAJTzz58BvdsMCr89P1fP7vseXdchRk5GeQlAVDnz8v/8H5yt1+gWR+j7TeZ1OOL57zUu+PbdAO6Lj/rSfjbt6pcxwxg1VnqkHJK5BM3NpoiAFLmuNMUvRFjNZa7guYGmBorr3mEAuchuXADjGWS157YPyZFBCh71QBlwyvBia9dJsxBdBCLBUUQISIarA+DQ+pJc2t8sNHrpaR5jSB7nPLIYSX9w6sNkSJN8+GVP8s6DWYDrXgHyRbcAeknzJKB5L97h+hCLWvX0/XvyJI8sKVBOFguEKCC71Wmz2YABHB8da7opoRDEuDDGJkoB8p4tbYsyfuBS+P6NRR4o6BNnnZWEagcChGeMuMPi8grOETb9BpuvXxHTNiKRA4hlS6DMRqT3beC5vxKjIa/AubMoNo3hkBmDPP71f7H8838QYp/A8w3dJYD/MN51/8XLDL2KI/vfi0KDdQA/lOZSsT9TsTZU1xTnds3BbeC5PW5e1meaaaZ/O80A+kwzzfTuJHmfDgeu9vWAeAm1HjHJkhsF8Auq8oYbQD5dZvml8G/esxnOuQQ2WTjhVJwpBfVcrYzkqj3E6oHunSib2NVcbZakIbnQTREmJzw5UCeCdGCCCySCpgM4QnJFKTjNjkCaTvdOy631bpzqVXpBHuKJvo2SBzg0N7vpcakQiFQ4v89vJNVhDMRfqgagp0KQA7CUtGa4I7nGMbAkbTdn8Nw+W9qnZTnA3SFk758O7b4PRK+oeKnEbw61HZLUPG/YUa8p6i3tBlZM1dyzVAdeP83AxSChZcwxNmpjF1v97Pqk+dKPEpCoMBod/5JrPN5F4CIL8IwIjg60IDgWpa/kTBRweRqqSup0dJdePSocPAHP118BzZlOKXx8oXRI9zea+Krm5XGCW2quv5iVgmW5jBzyMep8DQosEQBmCesuIdZVWQFG32ve9u4IRIQQ1LOEAYJDiAGEqCC65h+MGv4VLq2fFomECHAuousMNHcFSK4gQ9VelxQo1v9ghlsS4h3gcCHKvC355EtqPaTN27o89hZ0KKB/rmvwR/OkP//jDzz98/fO66z/rfpTir3ziXWnHftJKQ7py0rBvRdRmvu3Fhp1bH/jPCZe3/9Zpc+2sPxg1dzdvSiVz1j4wDGg/HFLnd6Mf233t0M2nHIw2H3Og8nGBMNFIFDICnMAMaIOvc1FYQVfWhVf7gfKBCV/9kJpmz0fqXzNVfvMm+nQ/VF4OuWI8pK+c79vz7+LQd/0w9/sGW29d3met8r91HfQPqHyFkqfJXg+AJ5GmiNAlDwqA3i5DA5ACNB3L4WcLBYIISBwBFP2NCdy8GAwOeEfiihdb0Fj5RhgV0a9WLHk6xVv3Pt032PxDh4JOO2cpF1RRMj26c4VKjgGouY+jwpuO9fh02+fcf+/sh9c/OccMTIW3UKno4KcMXNODsC673HUdXDOJ8/V9JcLGUEnr3Meod/IvGdZB7zzOPv/TvH4/zMM1HrrqE3vTecMDM28/h3UepcDOscb8JyqdTfLlu3yZmu58YSSwkPGSgpPrucNSBfWVoww08gwixZoxIh23Sn2kXI8WfQJq+tEqwGI7B0BXMVLXLsbAJYHXnilBK6PtNE+bX0zeSflJS/IqW7E1rhIEonPIjghath6Sf6uHuliKMNMCLp+Gj+/6JzuuSF58APAp6MTNVYQQD6gVyBdjHMj5Jmbvgcj6vpQyjMEOOB5/Szv2Tl0mvucyKFTz/bn9RrHR0f4/vwdfb8Bug5EDs/PwtnEEHRtllDtYqDMaT+3tH/WUcQRFBnHkZU/l+NnXPIGF6rTegCzJKh3vET/NaBHQKDbxAZEUhmVUQDqQrbCrSLgFDz3juCcx+LoCMInQvLaNyTv0OHT778jco+1gueR7lK0sn1WtmyAN7y6lLvre/YoeOp55SfRXnWs7nc5so/pC21uyRqxHTCf4iW2X0dpTs0000wz/VtpBtBnmmmmd6ckmH0whXaqDplXRMG0kioEk7V0IRtOlUX5uwUgLPSNO8kAXVFkmFc6YOgsaW4sUFJLJsDcFJlWT+echtgSC/HUJk30TZbwOzHXLusznUMHp4oZQtRY5pzq6BAgnpkGIKU2bGlf0Z3N8QLEnrpoDyJMK02YGUvQwGp9zPI9ajW86ZsLvaBdekfAirPizuTHpB/A4cP9NQoqhuZcewfF769GU8PnPRSAH0lQbFQqtQBenCspYyS5dyosA4AZ9dhnmqrN3LHlsVtdpvujgtBk9zMKYx3xilwcHYkCZfkd8a5+T1SVrQC078AQr5FudYnN7U3Vpnz3ud4ngP6wvyi1PANB4o1OyzH4KwMI1hdJWUC5D21M9OixoIWWmkGG0EeQMwBbFJQhhmLu2p5DotgDw/nsrQkyZSmDDAhH+Z4ZgAOjKi611XkPz+I5k0JTLgG+2z9sb0lW/Ht5rZvX9L7lMz4GeF7W+ZyBv/YAz4E61LvtaXl8ipJ4m8f5NvWzGTocRDuu//Pzn/jr619VWHmHNw7PW3bAD6aU85w+prf5GJ2C8A25zqVHWblBRg6J/2MLwcqAxUydcty3tbJ8L+n1FCCJ8cwOEDCHSvCHDMko4IRC+X4A75zqNcJLptCnCaDR9fgD7d3vQft6nrfX5/RLQ1BrCjxP1HRpeZ3TlFFmsCsAn3zvOSAEi26Qx45zhKAGulY7UpM+AsQwI24zvXs9XfAFHBxWDLiVw5GO2fXtzV77jJk11ksYpTzCgDS76xZYb9bpmhgDnJM4xBf/OW/KBEIM2PQBnc+5fiOA466r7ncGKrG9TwbIIYagxn4ZFCrTiHFkfPrPJ3T9ApsvG0TcjoYT/6j0bwXPAVtD9btMsLzGE1CGcDcwXa7N3wek4HkCy6OAtWZoFWHhzWWspGnXFGc6DLbP0mLDZOli7RVjqf15zzsCVlG8mv/z+Xf879d/qvOTPAeZusP6KH+OEjNiNNuviBjEKzztV9FA85z7PbWfCLGPqa0MRiiVA7lHsAm9eICz6n0cYeHFeMh7j77vq1ROpuPRKlZlMTN8ej8iZzjnwBHovE+GlDFGhBDgKBvhWBh0eQYhsCT/MsA+RK4eTBoavcxzfsKl7HkOiVTwgHsSr3SJ6neXQrJbvc3wAQACadj3hrcQ8HwJB9lDnPMpTD2zRtgpmYj03vNe3/eymfSF5zkP3soUbYleM6K3ysZpr1g0XwCcp1uh77McMECxLuxfr/3A85lmmmmm/w6aAfSZZprpnahgKGtc4KAi3kpfObBuTnzfxO8RTrwElgblIysbmcr7B8VMUgkSld7lp0x4IhFWyBkwIgCS3SjhskQEdY7gPcE7EqA86uNJPMYBiKUuWZsIyeNH22hWyF0Aeg8wMVyU8MvRrjehselCExlUDVb0US00A8V7KcCsMdo1DBjqfW4/inpZaFnLn/WQJd3Rws3/8gICojPlHOjm9XehTb+lXP5biBLSpe3Yq/toODYLIPM9lMJvOA/Hy6cUNeDFRWCsilx84/zJ7dmXPe9n06oIjxGRPc7bvuDms7yHFPxlzmAGEcHjHMz3ECXIQwKM2SYYA6JqB0iBapt4DEbnxQOq36zRRz2uoG2/6VVxzGDnwIiSC73rsFkG8J2p64QE/CYt2fKiyornNFwfA3Aaqr304JUySuUzFf3R9kj9Vi2cu1s6xDuGW4oCqXMeTAxyHfqwhgFQMQbNSyjliDdJAJEvgChTvoXkdSJdScmeCUBSmBEhhZe0NTv3tN2Qez+3keF0NMSUm1Dem+88/KJD/AYgbNCHiHAb07M7XOCM7yc9nw0YjpDPM5Zj28CEbQB4Cwa3b+WJihzOzXlCzuttxW+rt8ePyblq7bW63hPw5+9/4H+3gOiWhsRoqppTnufAcGd41PdURAfe2xDhanmpBTqs1Uhl/B0z/vz8B/76+heArAxlyLs1RSUBGu2AESbLGmtRo+J8uUbxZbepUrhBwPamw6s7seEesLc/aSlPKBSm0AgVFavA4inHMbcRwmsQTJk+/WhKBWUPYfPEIyKJUEQEdVcUJb2FxLVm2R+2FR6Jz6Vivx7je8Z+V6HaaXhZ6yht62jNi06Mt6of6hOpHYcOkrfirUZ40EZ6SUdKOYb0AA3uygPeQuJL+HQ5lfh9/W3YbFsBR5RSRDnnNOQuFfuaB4c1Qi8FnCyOAXAKEZxAKmSgzSnoJimm9EGtvNnStn4uztntFyxrZ3e5QOcd+hDhPaVu+XT1G07A2HztEXBXeZ6XBf319Qs+Ly/ReQnTbH3mDKjWvkvHIGPROQ/mWIHnBoYzS45j7zv0vQBdC++xCQHPmgcdLOWFPiRQ3MqGpqYxucF4BMnnLHOuW4hnJxiIVxHxekv/vYAG+7DNy/eUNZS2zdAVgNv3r8JeVNXThrcrgF9G8jQ1QHjJDg8u/4adA6X1lCHZ2rjo8zR907xTsJwVSLd7zaBW8yvbfGjF6VR3G9OA6CCimZPmsb4diBs5R/cIAP76ms+eMdDxBW79/ehdFo7dewn3Tc7BOwI4h2g3npuhc4JFNiIi9CFoagWk/aqs38J71Z+IUY9beI3ix3nd8g7Msnb1QebgZtNLigd9r33fY7PpcXryCRQhMk5Uw1sS54iokbuYGd75vK8b4EokUTuYsd6swYHRxyJfO4B+van6BiRGPX2Q1FFZbtAmc/5yBMK3RrI0vjTZVfADegD3iGm/YKCK6ljy6rYepHIoH8/pHuSgI5L0FCEiMsEtfMWf/T/23nW7bSXXGp1AUbIT2/Ilyerdvb8zzvu/1XfG7t2XtRLbsuUklliF8wNAXSjKlmMncVYTGY5EiiwWi0UUgIlLlllI7zOmHuuPEYDkGuvD6z5GD/GlttSNyVx2/SoXpf3cbg+pfm+ewwpJF5TcqDsSPvSuuTN4cdbeY3Ccx+TvyMFHP4CVTzTRRBP9cJoA9Ikmmug70rYhcJcQ+fD2iBXswe2niW21jFjMTGYtknb/gy1XCuTwb9jTWiwdbicpci9ACEQ4F8K1Wamoql2lAjqVWudwRVGVPga57XJg8QLAGuGYFXNTqLPnagIouMLMSKxpCMWukeu1D25g+MS2n9Fg0PY0kPqcODYNbEXjz3xYizV/FY1KqOtjPqQe3FIB0U9s29utlb0V6efdaCvDWbN7+zmGo5Lmlp4832rTqjxj+7H2x7a9x98S+foYDfs2Zt8d/o4nbL8G8mdAKCVv6xnGOEYqLiO57wVSFTMQ1b8JEm4N0F1lKLs1tgkYgu70VBV9M7YwSLNVkNb1POzeYrPZqAFqs4FI0rp9nUVUJ4smszp2QLTnRFBgfmUG7KDpXGPUiNAEwGqLi9dcz/ek911v672TtV3mWxmnss0WfU4LQrwZGAEEFhWux8y6OTa9pgRkYsw7QrTIHQgUUA+CQJ2NXaqiSYoZsdRg1H2hqoVeAwm1kSKfb/zdr0m5n3YUFQNpdZbWIE4MopSdBHTkoQ4UWD3IJ+6ofTfeSPtu+O9H0v6+63zvWz2nh9fetV23Nfzd2/ZI9qe+5/tsD6/9eXBvf6nA8315jh9XR3aPnTNGwz49ld6fnSMmwdXNNczqtvNYB87/9ttf8Y/f/wmgrI8+3gR9r5y6BeEU6qQy5Ms1sP5WHk6T/uelMWnz8VlzJIQ7cmcYS+VLgEmC5VgppyYzcKt4qQ9MjfLRnAf0rSxTYMgJhmRcNj9Yc+ykOn13dWbekCxTsqBK2z1Ou37L747xvea2qekhaiNvrp0+cgXy4zP3HMbM+/GPcaHvt01b165/x+hv9a/D7yK+YpbT/BiysSormL3o1SJls8Zq5hI6YhBpemFmBgcH1QPiJoLRo0oyDZhzmUjdt7x6Idj4JiKrP/yylAB0ONXyMjYvm3riRrPzDnR1Ck917t08MgeUzySItxHdmZdhGYm3tY2um2GzWdtOMUdB60+SEk0+Ql3Xoes6fLm/x33fm1N1UiDerihCCKHLQKA7IRAsIp7JAMYOgOD2H/+AQNSB+DUJvt+RBMAZgOvHDvxJlHmylWxSzl7etzsq3J6qf0DNLTT1urPGnIXA3yOPsoaUKHQp8wUOEAJw55sBt7DrIO8ltGnbn0NLqkHVmm639H8nItLST6ED2GtnM1wDlZSgS6GlqPd7trZijEgx5kF0F7MamFQgNVlKeMm6gAAIncr4yXUeyxxYHLf8XddSDuuN6hVdN9Pa5LaeKbDvgRbmEOBR7yLqpGRZKTy6XETQx1SuZ883AVqyD9r3KNBIeeuTL+H1qiMA7lF+B1TGt0Qh+EIq699RXtYB2DOpZNl9ao6zqPszi6ZuZxC6d7qO9H2vGU264A8kf/h9xk2PPvbwzBsJy2YGmniS7//ZRMNVtfrhSe08EzwH2kAcX5P1h7Y//pzQ6sU79a09b+U/UWqfaKKJ/jNoAtAnmmiiF6cWBKecWjorT4Ic8Vxv+3dgsC2iEX8u6e2UTy3imqqGdlCp82sxL40QWdncKs1hX4GwMQx+IyWxqHIClqLK05mQGjIsNVcx6InWjzJtJSVV3AIxhNwYSnmMNAKy1Nwa3liu20umpDODIQgSrKAyAVYzU5VBbUAVqBxDlD25y9iVZ+pj7dEXhUokUxnE2lxJuLGQl1NTQFdUPzHZUsxWpHXTvE5aaV5wLFSA+Fr5sY+VfV9A/3JaQPv9zr7eVfOkvpfyKY9uqwJe7qM1Uu/arsnGKEexlOZVYbczrYncUp7sO7abK+w+ftge+XcUI2i93fStHopqHIdG7V3b2ehDPm939M2v5ed47btqOLPSP9JX365513M8H+QZirsbwHwMGUcA7gA5BiAQWiHajC2covyxHCOcEjbLZb7nVHHvrRK4edAEhJMMvAsLOp4hpU1lrOP8POaHh4BotPjXr19BKSEmzZKRBDltYIpRnXoqHgycWFREn2uSry83mJ91WF/31ZtwnL/Dvtf3W5PfXxBgQ2qA9DSLADRCxIwPYWEGq2NBMiYbI4NII0vUaJVAImAKFkkSkDxShdTwDeqLocyjgWzSK1huqdylzx0OzDlaM9e1JE+zWNIJ1kZJN4RS5dTgB6Y8zywV/nwGkKBPvaVUFCTcIBl4vmVoMlrR7u0hG3TwfNhWQkklnlBSi3+hck4CcnrI+hWVqh3CtiFu+Lzr7TsqEet12/uev2u75sb19lsBjj58gEBwLLKVArduKw22h9Ho7iDzWE30eny+nTPt6qX3xo2gw3WoHQmGr88AbvUOTgCIOWtsF4BptxnAkW3dPfdmxm/jm07d97enUxk72dq3a7vsW1F9lq+DvlBsv4wuf9XRw+Q8pJLFqPo/X63pRjEbt2U97Akn98ZMIOKqBqetMyRIQkhJHahSva428ozPG+N1ec5QNWbjb0D+lcq5ZR0vv5FUqVpzE6Wt2hFrTAbz48VKbJQBa88HpKnTXnc9Oz81v1c5iEyYqvlhvg8bjvbx+EMushGbo60fq9Gp3n8a3F+JMGOTtz0riq41AFEcjIWtoaTOcTMDdhSgVeCcLBI9hgCaHRiwRRopSQxCMnlN54rfPIEgpHoJC5Ao6jru91E9MbJx2X5Pd+V6KjPq4P0B+hSBJLhaXuFYjvPvs/MZSm1pHfffzt+DAHy8vsQXOy6AcHDmpVwSgACGgl2wrPX1dA9hlgEfAIi9yjlEjNgn1Hey6XscHhyg7/sciU4AOnNOAPzZqEzmAApRKE6PpIBixwrwp9jjf//9j3ZgvgcNHkjrKDH+TF5i27/vurWbHfu/J7lTkUeMOzFIn1f17utLb9mJoDYPJoAdSqeS5cPe1Ny2CNw7KUeSt5HmljkpOXieGvDcI7TH2Z5s7c/8Scp2fVApG0HNdnN0tgVZP0TUtbawppLphk6wqpL3MzOOwfjCAHOHEGagEJogg8wzCBBSwDkmS9tnSpYAmjXK05iTvtcKVlsWrOQWEEIvSaPEBQjcWSkKBeDblZ3ycxK7t8DBzglgAu439xrJHvV9DSEYzybMuoC3B28AAjYbrZEOIo1Yd0deIqReIFF5R4Lx8FT0rAhR52R7mPU66r09SMDXStb39dPB88/wcVIbjNQ8t3qsgt1R38fVFApS1UW3Pz5nkDv5dCHPLx+/3F8RxL5XeUIE6VIgWJb08ChZBfPcHdAwS+I+lJ0p8qSn/AIMWxnuydfLwSmuI247cTdcjfK3cn2Crs1cua9QLUGgOomatgS0xYea46svtXSVZYv6YUw00UQT/QlpAtAnmmiiH0AFRKcBgpYFujGUCkV41ai/hxXfcm5tPdotyGUDWoOIYRCFsj+NiOCtIWtob9u5rZpudKWTfBw8HS+Bc3GuYjLSqFCAJGHT96CkacWkY7ApjYAqOBEx18Eqsr4J3Amgqq6gRj0EoDNFXxIoUjlfVPnKyox5RpfxhSlunM1yWSEfGlHg0bGVkg03w7bmrUSCANJaq7mglUZUojlyOyLd+7CCGwd0Ww16Pp5ZV8YttOZ5LifobVHxhB+vuVereI9vU54ww7lsb4oMfq/GRSBNerStF6VWfgf34UCz0DO2h+1V29ix3fSrfkaDvtZPP4PmtGN7cNs14J9/rxV6aT8J+22X1p6hLD4r7QBpemYzNAQkkLyxCBGNLMzOBT6Gtu1KrizF3jcBiUZyi7RjxjhW0EFWdiRAuIUk4PPHY4SzgFknFuWwzsbxlAK6WQehfAV0s5lGSVR9cUpJnX+A2mFGkJbXIIsy9+PvrwEHyvX2lEtUycoHn+1TI9E00mzpFHFCkBuAFkAkQvAWSSM3cksR6IJfT/l0KX5h/4tYqQsfLMlGMjeGwo4TABF9jjDP/SNSI1rgDJoTEYSgKZeBHC1a36mvqrbcqsHPO6bdVScJa4O5A1OHRD1owcDyJI+90GB6PrI9Vpe7XrMrexV85fLtt/blTTVffbu+Vk4/7vxnz77V2zlTyMjas9f2yLXr7bcoxkTIsUaeV2vMrr7d2u9e87yOxCaoM9exbPfLyXMw+HMQWCTQE/nT+7NzALDoc6ftNlYkg0ii1gXgw/k7/HFV1ydVXlk7WK7yWlbzUd1+a4P02Y3sI7fhThj7pqX/FqqNjie1w913p/qNeWi7HK8OgSmPsuNwtbNlK38MJuIWSa5Xqo8hu0dWsl4521PBsqYuQkpWM1aUtzMCmAWdAQ/MrLwvCWKKiIkg0bKUeNsG/iXx1LK2TojBAVbOA+x3KPa/f2rV7CIlwfQJKe8ioUQcit+nL4Rl3Ar7sXGoxDc9rbq2AMXtpV2BiDTCsRjNy3h7++WRUM4yUkeIebdqCdBB9dJHX0utvex1V+T0wFruKfWxioas5wNVmQwIGNQxdyHZDf9lLVNZOhCjY8as6xBCQNd1BtwXR91ZN0OgLjt/ETYAEVK0e7DnQ4A+Z5P5EhNmzIg9EFEyu/iyW88EkiLrOPnT4eZ+gYUsMH93kMf3aqn5y29Js7Is5Div9V+vrpr1bX29ximOscYKX1HWvk0f1SnO7kcbZ8s4VjmYG7jnY0kcICmij5rqOa/pdsb1v/6F4/fv8fnjR7As8Oa3OQCgt7rGBIt8R1T5QzR9tUQdq5gUoJ+HA/z9n//bjM+PpKGMANRPZFSd+eZtl8We3MHvQAU8rxwryaKbqQBf+d0XQYoJxFovO4hmMArkackdSNdOZ4eSDGiS8XSy6GiPUlaHemWtqcp8JFv9zSTl/dpn2rDf31hbe1CyeuMr4jweXi7mloCFtOA5M6OjgK5jA6W7XMYuCTQDlo2BiILM0e6dBNlpl1CCDkh0/LS2eARI16EY9Ty2d9oTuzAB677XwIdqkNy9wXl/iinL+EkSJAnWyeuoV+NrizGHTrNIdUH5PgsOujnW/RrrTY9k0fS6xmlesSjqKMPM6C0SPorkKPk2aXu5HLDtcOqfnv2pNeE9PdtADZ4DqtOW2IZT8HlACIxZNy+XGfTFt2IfkSSqE8FlQkJCT+NSz2P02Bwd+11tdq2gv0tqG54o9sxV76NKJhl518j5ZiUrUXGiIeKSUt/vf9jf7BDX7Mzbu/SgeiyL3DXQbSaaaKKJ/oQ0AegTTTTRd6PRSPTm14eMd9QaqYdCWTa8+u91BIxuNxr5vrTLQP1k5XnkBBr8kg1ZcNuXbVMVLYgcQXCl6pgpbIAi3V793Ex+jZ00m9WQRNBZXfOUkzKbAtcYzfIJTbcV0DFYyWqCxRjzp+qiDthRNqBlRwmhXKfdhf5s3BoYeN3o5z0aqO/5261J+CdQJXppEU0+kITtKUDVZ93uqWgNdZ9W9XEnUjymF9DjFrIdIXiSgNtGCRxebWy7qCEteO5W3bI99vv22NSadjsHdylCeZt2bA/m587jH2sfD9BT29rRF6n/r7R6BwGGDQ2m6X7XHvYd3822Nkp+/Y29Jeo0AwhWCgoTQDg2sBRgnKCNwFqpYUKq2shyrPNLTpAyQKSQXMKquWlPj56wAmGF/voYEQl8pvwhJtHoJgbSWsCskWlkRvoEIATWTBcVv+KOESKDF4J+qcDN/HSG3kBdWK31lPth7wURwkLrAKZrj/CoSxmUdajwXsosTqwtWug8CZWRjyhgFgjRDHc5LSOAwJbqkfQabtwTKIDu2VC8Nml1aRCQDVieErbjABBbmkmvlVp4YE7RHigb0QVq9HOjSf2g8jH2rKOlMsw1FI2feCRavQoQjnGc1GFhmF3jSGxfNSd8n0ePt5xN/4LfR35+1eMfvn8yUiP7oZfsWczn4RrtT75W3e6HN3hLb/DvP/7Yffxge2XjOJbm8qHbGP72mXb8sIOOBTg8P8fH66rY7XBMMhOlwU7CP37/Z07j/uH8/c7eaRS+DPaXT30Wov13WW6sL3hh4HxHWz4PjyzjzZEZvcccE45AXqZCtAAAIABJREFUL5RyfmiefKyzul2D+7J16kDOG56f19A6whougBq46cdIJWBR874TKkdDW1uHchiTy5RASoTEQND0MRp5TCra1mUtIrEal20O6tpW+pdHK8u+hUfC55wM9zVDk++61F5v56dU235FdfZzGXwIGwxdt2SgB0kev/aoMpat58jgGVI1Q8R5+VBONDBoS//S+3RoLhBBmKvoueoitsZ5WlgtD2VlR/SxQSTAS474MyEizAzcC7CU7Xb1LKqLaGreEBAlYRMjhNxZuIx8rtlcCX/1yPnKVZ6F/+CTcbAf2Br3sq9JJo+L8wtsLje4odsMnpO1PT87w2a5xLvFGS6vL7Ew+cjTHDMxrpdLHMSEHsAlCc5OTk32JDuGMJ8f5K5yYHM40UNCFzAnrWe+3tyrbJc0Wh9QcP7g4gKBre5x32PWdSBSx+nVv/+Fg3fvkJLg/uoStwS8P79QsNWmy//84+8jo/F9qV77hzxioH605zyyPbzGzt+eAOA+FW/fr80SHZ7fL38383umI+PPyXUW8phz0jJvDMrvF9eMYeBB7G5u7mDkSehS/q38G973kFNtsYqxexy550cGpd3eBeCTpffGAgwGcA3CCYhuM4Cotc4DjphwrzVEWudsKffrIHJ2FErOa9vZxbY+wewogpTtHQQ7jYD5fI6YlJ9RKtes+WhMEbEXeES8dgrFeQEJXTCOGcroz7p5fj6btTrApJTQ3/eqn1jfkyRzlFE+NDP+kGJJLa999tj09nEeCDKf/mr73ohkMB12v28F6JLqbDfmnOaOnKuq4iDQ2lMAtaX4DGU7J/ojJoBlAQZhPpvp2DHbmmOZy/o+r0MgQtxoJq8YddATEq74Bqc2z4dZoHZRduZqHD62pqPtLw4DlO1Pg3k7cg1fQ7L8sgN99utSljLK+TV4nh1wuLRZz/f8bm2B6K1kkaWnwXG7VJfMakZ7P9FEE03056IJQJ9oool+ID2k2j5+bh1b0doVH2rnFxbrqtuqbIQ4BePGheiczr02l6GxYoqG7SByBJJH46jWorXOU059XdKauThN+X8wNLIo0bhgTQRIQorWj6HiC1deyR4h5eijui6wX7GYQEcGpKI2HZhvDA2XD8++MTM1Vb+diCpeOdqc2uMECnbQENnd6+rP294eo19vvo+N/7e0sc++bznmtZEbvIZjViJ7FfwmwFKctueS/VjPFoFHxJV64ruvv6rejxWAY8RrzUJBp5zBZOaEZO+E9KVuX0qaQj0TEZg7dBzRV9kv1ssNYNeSKuIcUPMVQflZWvbeEEotwW3+U58LALzgzC9FNG06zFChWTug6dwTLJ2ltexGLghSBIhi4XnSRnJsYixZLcxoxayRmF4PccYBs/k812Ssa53mVJtlh91dbb6A8d/tt0hEo4tir+bRZKkb+6QpDlMyJ6bbNoJ413uxBWwPKMCMcoN2hgl+h9fZikqXcYD0SWD3nvSS7X2uXqrfP/6B3z58aGqgP0bZ8EjtPsLDY+9ODM/hpQ14/iDJoI+6/Y/f/4m//eWv2Kw3W8cCwG8XCqz/ftlGpi/kBDek0WOfBxHeFxYRf391hTvav37mS9Od9etIFPzTNLJtX39MvfZ9ZAN65PeHtmtyhmepYRupCINtN76KIRPSMBG36XIG3NUyX7eq0bkCCpxBpPxjYiT2vtiuUXlrGyhttwo3zbKyS5/+n+w6d5/t7f5kZKbaHjo81bR1V5X8P36sy+z+vCjf13Zf6zh2KfuYFcBwR63B3bFfiXSN9W0HygP5ulijRbqWZeBc9PGBzBlDBMIlh4vKIKjGR+eNR8v6OQCXeTYybs3slMH22DGD77d0C3wCutMZ5vMZNrFHdxpANxqFvpDj3L+47MF0hOXtssgYArwF4QuV8b4jwZEQTuQYgRnr6x60CJCbBFkQ/vH7v/Dff/kvAMDNP24xf+e1jwkdB8wP5ghdwAEfIsWkaaFjQvfhPW7/+Ig3F+fZqWR9dY2D3/6C9WaDzdUlBMD9p0/NbPh4dYmFAG8/vMe/Ptb8+MfQkEsNf3vO9vegIfD3XBrWJy77y27fS82fytAOtgf7ZAfR64uI/efOI/ZuiZWucltAq2u3TkCltveO+3jKPT/h2C0StCXXYIAraY9P7AK1kw+RZuliUUeBMNYhabd33WphaYQinkuVEQXFOVgEUZKVVVBeTELogkWnQ5pIY3VwLvwVUF1ELEDCSzgJEgIFrDf34BAw72Y5K6E7+KYUAZhDrznKZiCYyOwtkoM09Nlvg+cAcE/AoSjfPiQF0b8MHqLLqyNmoVEavkPOo1tHDSWWU53jF/rkWNN/ZUpZLimdj0nB83QpSIjY0E35+RkTkPJ7KiP7Ro5/oC1dwVwsGH+/vFb97v74fNH/mudsc25XkMO41PSwTey5UtBEE0000Z+FJgB9ookm+u60HV/xci3v//ue4t1PMMzue12vTXRjJxCpMbcY1QuQ4pknVVFOGpkaLfehICvfCKao+ekmzMcoZhgrSgJ5lD8zeCQKJEpST2sD7MfMg3WKOlU4ExIncGI9vzZsYp8n6NYGqQ6qDLQj7YzRitQwP0tVbSz/zT4Xg/xmC1MsExW1qrZZ7jfjnql2tLqjGUd8z/bofxN9Z82oNue+BGVl1I3BsM9KQ99KL/et7/1P1hqb96MxvJ3AZ2RW0vM5HkHue47hBnjdY+dW7Un1qcr/CZIVLQjwtN96fseMBEG8jpBTLjXOU9KUikzQ4HNNQSliLxIJuGOo/ad25Glrmg/vXiOpCbyo680CdTqOdCPghTNFUZCGlPelnGXXovG8Pi9b20wI1IGSgCVqPcLa4Yckd85ryurlxfgpzPhvQANzmZd2eFsXmNqb9RBOhxjyqaROTaz1VTebdTM2IQQD6BWoT9JXkS2AZyUQCOS29CfPp3aYM7nBrAZzPfrcox1qA9EQ7PRUjYQSDeXfa/L614IW4G7SuH8HehGAngZzlapa3o+0vfW7IAPHOfp//JI5xfuKnjY8x7L7t+aaezSqEejvABD++7/+lvf7/Pzy6SN+e/c+z+O7y4+44Vu8O7sox15tMqAOAJfXV/na3w0835eXl9fd5K9vXAT2uo9n3uxI18o6sKvfYmyyMtCOtFHETl9nxNotzCvLjmTAA3u0VKsXEADxKDwuMEe9bglFIDGExWRR2RZ8tmTh3eMwHI+t+8rfpfo+3kBZcrYdN9u2HqG85rZHt3Xlmx/ydgKQslG9OCbkpzH4rT4XQHaezYizKQXNeLjsPuAHvobp6TYXsvGfq+YUuGGBrrNgS+cvWCcxB1Sy1AIMSgIijfB8CwWmPiMBvv5Sm63rQRqZyO2zbn9fYYWjJZBwgoN3B+iR8hHdaQeIoL/useK7knHGzvN1nUHoU6lNrs5BK7xZEjocgwkIFx3+/ekTAE3HHuQE4Tyg7yPSVcLbvxxifnCQ+7Ve3+NgfgCBRqYDjJMP7xtHu6MP7yEGjzJOAQARSwQscEXL3NYNATd7Ona9JJ2I6lVj78T3Yu/PpRcFz6vZlj+raNcMANsb7K+cv59UyYoLML5kwNhbVyrOTCbnIeWsIFk98t8qQFX7sM99vCS54Ly77c9cIrU/mLxwbw4iKwZOsdLU7V5mAoSveb0p6a/13qt7dh6et4tbAcGzWqguICyIIgiWqt2zOYWOESggcEAfS710gfI1LVcCBc6zfEhW4anKOgXkchhaYz1o1LupDffre8xmc2gEtjrcJpGcWTDmh2rzBLaOGnC+SXEwwO36PbRfCJt6BsGb6owv9n1F0oDAOaX+IPJ8IW30d52yPesChOxYHWQBAqF7F8BMCF0HIiBurCxM0JIF3p9+s1FbV0qIl8r7It2AUAIgnkPik8fJ3rWtnDPSygtDmaKcSg87pwx0iFofK+VTvB3N7qJB+b5GF+llZ9mERq54rZx3ookmmuh10QSgTzTRRBP9QiQCy9ouOBZWb+wqZbmTC+YpCcAJnAigiFxM0ZQ21dYM7HaFUlRB9Nq7tQFUa6BLEdwBRBfkzQWZxFKWEUBS1Av3jGX3hGaAhYEIJE6g5GAaWjzczx9svzStCPAhGaNsBDRKUI92brScMXXp+5GINF7G2WDyC+lCWeHcx2LzDe1u7a+e4r6219dIWwZyAITjbdMclbk7brB0/sEaPb7UCIZiThu+eastsNONTABypJhAEJcRZr9FXCbgjLQ2Xa910omrzkFB38CMaFeo2zVTopmJCGHBBoxbPd3aI18IUaIZzAg4k+o+lbQmIhdnowygWyOZF6kRioMgRQIljQKJEjNIrrULq/rOInofIjlFeseaTtXTJUaLQNGa8cUg6gC680I3dOZoh/Kw7VpafzH2MT8tysaZZA5R0SJlUklbeaMDP3wF6qf9FCB50C0A26D42wrz8t/qa7ytwSj7ZIwDx2+rjr90RPpDQPVT6d8f/xitD1/TWFR1dlSw7bH+1Knzvxew7O0/ZTz+uFJA6L//8rdm/5dPmgi0iUC3dj9dX27tAww8f0XkgPmxLbxH9vnNQPorJOU32/eT+d1g24GGfFwG0JWDe+aRAgwVKiC7JhRn1nSz5UfPtgQIIli41DCvrP0eVfkrU7Ny07ZJu9keAG6aSaoFzjNonr2uimGd87PwNthSgKNC1xx4q65dtVEhe6Cgz4wlQaTI8n58gpjjrTr0Itn8iAnZdTY77TIOIQAfA0d6byDBpo94u1waL6JHo/ReghRcTJh1Hd6dnWska9D67JHucoptPxpAs2eMPkNwAkK/7BEu5lu/p6uI2bsOON9u5fDwDe4+f8bh/ADEhKv//QcAYPGXvwDQtNAigr5XoOzwtzm+/n4PAOjN/Xqin0vt/KCGd7o6nTdp8IU4l8AgItxBnTIdMB6beYIqLTjBSlpJ1vkLkFw+X6UKabd3koD7yzXIMlFQxY8UbNZP5yfFl1aqAdVtX6tqML2mzP2o/dHlaIv9RQgdUhJs+k2W7fU07YuYp673RwzJr/VeTzvPzKpHsT7bmFSG30QtzRC6TlOUkwLy8/kc9+uE6OC41A5Ryk8F8cFMArvoK5CB8/ox5O92jeOyFI/aaWoAeyFFs6zFDE/+EizynM91Xs+6OYi0TnxMG3VoZnXR9X2SRMfpSscg0RI3tF1b/TnkDsJ7g81uL9vx20PPIy/BW0JA0esbh+/s3La7b7tsLNsOezubmGiiiSb6j6cJQJ9oookmeoXkAPiYwCumdN2i1F08F8LS0gVqPa+EKAShHkGCKmzMYNYkf54SDNkQpZ7UgOHxURovbWIuiZEroZ+JIR5NalEYIgZzSZsqrFY+/dIJLtQX5d+VBiI02TTHdInWa1oa7HgM0HmMRCQrgoQ26iCbnuz3WzvoVLSf50K4GtznjyIZGrtH+7CrXz9ZW3JP6RccNxmZc62xZPv6vwp5OucyzzWi3EwlFeR9C8IxpDqyVDzdJjp16NQBkdIqUJuGT+CAieC2imTXXA1xeWzfLdJ9WZLNp+uIeAaI9MBaoza62UwBEAeawwz9WUJaxuqadZLBwivm5yEbNXLNVBufjruq36V9BlsEuhqzuHO+084/vzZV30KgUkNcGCIp881AIRvscj9E657CeDKDkSSijylfJHCwSLL24p4OHhDEPiJa/vgQOEfuC7yeYWrmN4HQ95vsBJFEcgSK3Ng4LBjpBvn+PKNAj4fBUq/RXYPdw3FjtCncfc4KxiPSgZL6vUfJCFKeA7ZA6LxJwNtqx3OBb4/2fi438ns++vABqz/+yED02HFj5znVEfs+dn7MatBXb6s+dpdBc0gPRdg9NaLd6X///Y/8/USOH73Or0S31Zp7JPT0aPSHDq2FnW+ciNuuMUbVvKg2q4sNwHCXQ0fAh9G104GFynhPROrkZE5E9Xk1tpvzvGeZsKw0eoxnSnHQR4pDUKJcU7vuS93D+p5TvVPKsUOj/o8mAgZOBs456209pgZJjilY1J9H+Y+v9QVrqiLXUMa9dlnL2UrQytoiMAdZ6445wPpq0gJy5thAmvnFPdYiFABi6RAoYE4nwImmR+5jRJ+ireWkGVT6CGCNRMcgrHKpF8mdaobnRUjXkhVuryxD1ekpAML6U49EK3z28c49EXgS7V7i6Pjreug13lf4+lHw27t3ODw8REoJt//U2OwuBBwczHJK6Hy+CN6+eWPfE44/fABzACAa7W663Hw2y6Pz5rdDrH5fvhree2sv4E98zX4u2fvZ7KLy3oIoZ2No+AGVVO25RnrtCJMdaKjIhGK1sCVZnXPTy+26mZdK9X3Y3YZfv/RT2xeMLIfeEnAitwAWuCGAGOhCwGdmdSYgBgXGGwG+VJHQyk+Mu2XGpmubAu6CGTTUu08RHj0OaIa9nF1DT9RxZy1oIZWDKhnvJCiPhQhmsxkggvt1DxFYNhbKGePY+PZ8NoPWR0+aBj5GrPseIMn3JlbGZL3Z4GA+x6bvcb9WJxnvky7ZAiR1WdrETSMLFq41ohM31NY89+NO4wk2fAuRhDsqq1QQ4Jq3W3F5nlGO5YptC4CAhfWMweeEwITZ7MBeCZ/vAWEWVJ9JCTFu0McEIqC/ugThFImWiHbNujTUt5DP/Xot9G09oLqBvE1ISJZdYDC/vb3q+67r5swH1XXUZ83edaLsOONAutixYs5tWauvr1V9bySNV7I+TDTRRBO9ZpoA9IkmmmiiV0oPReRKJawvQLg2bZChBipJAuGEmAggT3cIAAHBFE6yer+G9Fi7CVEU7CEhJPPy5aTpIYm3+0QES09m1w6s6oMkjRxJKYNb7U1UBkuox3TKRlMzApAYiC5besrWxjOF/wyc09MUriUBCwAhARcJuBxRHr8XmXlya88vRaaYvlQE+j6R578y1QaImmRrf0l9rqSKNp9WlqjysmXlOZxRZUzRLwqC19dSIwdhgZRNcQ6c1zXUVyiAu7MbM3zQBogzdJ1fX41O3axDl3psLGWqNE9O76E7Dwi1IQLKPxyg0fTlGjmWDWUGqBMK8KPXtO/G68rFkh/tNhHlWWxgOQR91DStKUU1WnExamrkt0bkefQPCGAKmAXCJkZreCxysgAQsY8aQW59E0lqRIMgSczni30q/6rMfCLQsrQeda6tp5vtMhv7vCFj0dK+bwh6A22UNNmxAVoTPVgpgNqIRmgjqofpxQU7QPIXNP48J5rb7/eO2r4/BJ7ve7167IdLX93+U/p/Yue9Pzt/Qg30p9Phu0N8/fT1p9Uw/57k9Y1/baplh3Y12eXMuasdsWK7DpYrX7QoSQPUtd36PMrrQAaBvSv+1WSFZMCQiCeqtsacfVPTatNMcxcywjZ+ophQg2WEAo4LaAvhyCAa1KnrK0lOf9saxbeBuvxJ5TpU8ZUiV9pK0oAH7lDh/VL4p+gRdh7Z6i3mYifF6H8kx+hOA5gIXRdA3IG521qLYooVCKHPPOJOZ2Ze1x8Cf16OVgTgZpmvSQZk+hoOlLlUoM9tOrL9DMab9+/1feAiy5z81RwiDRgZvntZ17Lx6GYzpJiw7nt0gdGnZE8ggWBg259E9v2zUINlVe+5/0b5Pa5wY39vMchY5Ee6M03DL1GizOHgeTKeSRBzdEd9nDtuvsblzO7tbdLSBHxGwFLlonsbF2ZG4IA3lk6OCebE76UlYHXRtUGXzdnGLkEdDxIUDEdVY7wm8iAEWC35PuXgBuerkMJHASDGaEC9344DpISu69CFzuwg6kSURKPKBar3sdVEj1HQR5P9U8ImqptudqiyecEc0Ccr3fTSj4IFMznJJSFqyQEocr6vsbHFgcGi+9h+70TBcwaDLzyrgjoWSxJQYHBQJ2WxSP8UI/pLc2A+JwScIeI6l+HzdPJPvffR1Oo0wtNH3xHK61ORomT73Cf3qWqdKAfBtFHouu0yUJZ5dshuz+3TRBNNNNF/Ik0A+kQTTTTRK6fHgPQbTx1cgReqeLlthwCwGWrE7Fjm4W7KZXJjpAASs0lSAXAAiZIqZVKE7hwJBBfqYaAWgVkUVEoJMUZQslqFUpR6D2qq9ZQtYx8GqZGBJi18OxgPj+OJPB5lVwOJD9WFrckjANckuOVfUSXZV7183Xe2pfDWUTsZCBg98TkX/e7W2xMDZhym9s+5nKhBzLaZCHzBxaCmHcwGBk2JV8CJrJCzG9Rd6dd3MxvIAS3PwO19Sk6mXkdlHOff9U04sSg1VeoVvNfrxJggsoakpKB5NwOR7leA2K+jrb25OMDXyzV4QRk8BzTSnC19rEfViWhEAnEwY4a2wiGABAo8i9n0UYxO1c0pCGSD4mMTY4TEZPUKlc/FJBYVAkgUjVIPDhL1YJ6j7yNi6uEpjx1E1zTw7aVjjNk4CjhoZCCG8eiEmB+xzWwz9nnmENsvQLxpDeh6xCrXHw/26duPRXCPgZ8OntcGXzf6eSRIhXcAOMGKbgHc4liA+ekZLm+uHwScfwboui/YW6c4r8dvRcDq4x+jrHOslrzT0H5db/sY7eoX7dFvrVEOfL38lPc9Bp4PudxTH8cflx9xhJdLjf+zaBe3dxD9xVK5/yDMKxtZB/tqJ6qcEcn3OJhTeXJK3RIVEFEdihQ897XHeVaRWTMXK05AbgVGlWo4KWDgmT8ykO4tEFpmOryn6m//kfm2n59Kebzsk32LyrOoM4z4Mcyca90Kxrw3R+PQt/aJiKZWr4A0kXpdKYjAVlScJI24I7Ioc+TnUCIANW35m3fvkARYX21ARFhTD4Ql5PANQjoAIOjTHVI6QHcUDMACNilivexxTxpdy2zlXIaA3xDJeSkam1Y2z0UMvAJjk/q8/tXk23dIOAZh/q7T6FQIOHSIfQQHlXti30N6XZHn88OydlYOzDGqu/HaIk+ZCJ9//8PW3QWO/s9bXP397zj68AEAMDu/AOoyGRP9FHL5vH7X/T13vTz/I2TZdAHCrYmktXwIajNIZFkQzuv0f31Xksl5Cp5rlLrr/inr5T+TyP+r+tHUzxagwwl6LIFroAuM+6DrS2DGCXf42jHWdiNaZk2duiQxQtAx0jWNEUgdevuka4rWNjflQDSjhEByjXIQAykZ0F2NG+uzm81mYGLEqO3FFDELHfrNpuILqjPockWYdTMczGaYHx5ic782pyP9R8zoiJFSRB9jAe2T6gBf7r8CUCc1AYCk562jpXOvCinVPClnDtvJJ6X9WVwu0D3XuGlAWretnAA4LUnHtLIfkFemiLIdBCCLOvd5Gi7UAXo2m1frOcEziKWYEOMaXz59QgQwwykAQX9FSFhmoN51jm+JZxhm/MhEFRg+fE/yxHWbGFc/DfTLffqAyh5mbWfnCHfSsDIFhpwDw+ts9ZGqn2hst23/4kL6RBNNNNF3pAlAn2iiiSZ6hfQUAVadq1UlFlEDVkwEQQ8SVSoJALGmHVaTDTVRD2IKdkopK1ZNOrdGh6CSXqoS3l0g7zoFl/rIgNfkAgCLosxNil8lNzxm1lPwzQ6iyrr6VPsYYaCI73H8U9oWqNL2qwMEfzb6M0Se0+CzGMayv7mCoJdqgIiXCd2FKtd87sb1EmXmRrxstKsu5MArCDn7gwPvaekG/HLtp4ARskROFS9CSEkARMhGEEKXoxSZitGnNjodXsw0laLxoBACyCJOmvGiQUr02sJOAqaQASExg0RKGnmCPB7lRR46+TigFJghwdIHJ0WQUxI1btvYegQZE+U65DnqzwyZ/abH/HDeRALqdT1CqETKNHdDdd9KJ33MvM55Ow6r5uingUq7qU4n7qCJ20Hra90QsJDb5lwvnVED8cO7esm65PvSvqD9c/pVg911qnsfvxobqqkeD8F+tdD/+u63HNH09fLTD0/p+5+wNr4oiP5TqXCFOgpWxU3JVlfnSGUVGQCo7NFSVekgd/QZ4Tpe+gco/NOzliRJSElydpFclsJbInWS+tWIBn91iuZ8ANCklmdCdkxg4u21w/8bsfUDyI6sfnQDmtsz1JTEFXieGx50HlDgj6qLVQD6iRxjdjaHALj9+BEgwtqd3oTQYY4jImzoKwSCSADRV2yWB5gtGBBCv4z4Qp/z9dtUyu0a/SOolsV0/ntEoP863iF1GDvPWWwAZAAuSUKKySJpAzabDcr7pLIFs7pWpD5i9fu/cfj+Pe4/bpCgkaCH79+bg2H1bAFsri53KjWPORdP9PJEDrFVkaPNPyrguZZsq850ByYHz40kH+HbxelSMxbpEaqHl3e7iTz/GTQG4BFwDNIoZrJI8tRmwgpEVXYT/UMwfaBinVGUz8RUcjOJJHVGrTI0MJOWRLLsU1rwTiHTaGWXiDxCXcexrTMOHM4PshNsSgyKaIQ5gkXEW/9CCAghQADcf/mCbjbHTBgxaBkLZoYQYb3uK/7sAQmSeb87nyUMQF98y2MdWZf3PDOX+rPPMZy5AOe6J5wHpKuE2ftg96PjgSSgAQIe40b1RmlBDKnA8/pawP68bWsdobK/cPYn2OZcLvpGQNplGvJO1Pa2CjzP/avX3wfoVwzzmGiiiSZ6LTQB6BNNNNFEr5RG00hV1HrJmuwsUdVyUuUwwDx2PZJSDCiHRvKwC9wRVpPOgDFCiT7xC6AypFI5JkdwcgHkQArUBwjgBk0BIBGKU3n9Qgfk9H+v5U1+fEb0xo2tQzPVqKHQPvcFzn1cb+qTHyA3bJyA0P00G0Q1F6jdfvlrvKzylbMLvJQF9JHI88dq/L1GEgCdlO9i6dmHz0QA9JcKeCfb4ffmKQpro0CpK6eJ4ZMkjciQqkBlBYYgiVlIhrDoA0o5AXzKiEs1VDkIz2dev1wqvqLgTOgCDi/mWPcbpBsgLAhfLzfgU8YsqENA180asCTzkmxxaXlU3aHs/FMN4RAkEqRc/xAiuL9fg1kjTPQ6mjqvAyFRRF/xSDW2idVLd6agYxaTILAbTEvfU0yV9UkQU2wADAfSs8HOnqWn56TSGAAgLiM82rwKkHNIAAAgAElEQVTavcUZIp4GbHpaxF1A7YrKMQlAtyCkm5LI0n/z1OEEIN4s8fbiAm8BfL68xIqKs9NYxHUdvf1QJPdrJu/vsbQg+lh6/Dsq4wWU1/hICnhetzlGf33/GwDgi0WdPxcw+T6rwa9NdyQ4FsKxFD7yM8D0B9fSHQBovZtJrIDGyPMVQaIqvko9ODP/5ZqHWvQY5drmDuzKAMDFgB9LvrrD41G8dq9GnkfRurTKV8psrO9jjOeRdTmvYFtD9cjz+s6PMztXkdYD90s2+BZVx4ARgjkoULl/Xy/GySNSkdeXaJ8e1Q/RlMTFcUu2BxJwgRPOlcjWthM6wfxshngd0UNwf/URX0hBf2IGRwWNmRgMwZfNOgNE0Rx536Y5mBj3/QZgASW2sk4MQszPEvA40UF3nkMPMLY6fbZnvekt4rOVywodC6HDMQ7fHVbPSI9V0JwQY0TXdTruSZ0Ks6OKyTEiguX/3CLiGgfv3mE+P0D3W4fb3xVAf/vmDUQE/9///h0LqMgWU3pQ/9m1FiyqRz485qmg+3Aq/setG5lFFYC8HoU6Jt31aCLCCciKFthxPAL05WvoO6+yl8tchYmIqMMmLD15kcrsKNrBk1/qnULdfutwU9KP61gcg9DhFEvWee3rzUKOEekWXzlgAcYxM+47zk4n96x8M5BmnwpBOcO6T0iUGj4q1XgBlv2ECZQ0zXqo1kC3awiSAbsMguDNwQGICOv1WuV1aG1yZsas65BizLqXj7mnYmcO6MIMgQPWm3swMfr4JcvOgRmbfpPTuXtfJJfKIAt6AGIe17TzMcnOjda+QnV7Mn6CoDi7CorTbPIGqrZIyq4OCwCM7oKt7JaWpODfZsUJwg+2UlUQQJIgxh4xJfSXEbPzCxCA/ioiqbUGQNE/vD/72n2A3ctlzdOL1kbNvmpW5/P4GeA5zOlav9p64/XOTfd0xxs/ppw7eGX3iDx/7TaQiSaaaKLXQhOAPtFEE030CqmpU2j0GMAoqdQm7FNEMBMTEwGJNM2i1dSiRJZ2mCApqSHSDKEYGnxHIlNqI5+QgMEZrFNgjiEBIOpawbwHQBGxMp66GqLKgKrJArH0yqrYu+roxtfmvHrcBtsP0SgQVEVWPZVuSSyB9Y9TRIoBpNquvNt/BRJITvP90u1u7fvRYUrfhY6r70WZ53NuFWIHkKFDy57O3A8Qi/rmUjsQ0BTiydIPiiTElEAG3NJFUBBj6Tn6tmu7bb2XUtdQF0tRWQEZIkBQ/sLk/RDM5nP0EoGFIN149IfdGZVor8ZwMcI3twwDw+iMKtoRzuMM6RE3RJDWOZ/NDpBSymPlfaqj0t0gp30rEE4V+5KNmgY5aCQ9lWcpkhB7B9BjBjCG/K7BNB4wiI0BSb79VOB5nzdoeAwvCHFQc73+rM07s9MznIugCwHvRbC51vqOCxEkrJo2dpXZGEZ1A68PYN9Vs3ysVvqu+yTsFyV/sTjDPz/+DkBTbE7Rht+PVgaiO487EXVmev1R6dJ+HenvsB5zzee21oEK5C31z43HCnLq27qxmodaI/l7lGTlhiRz091QwcNUr03DW/9Z5PPFo8/Z5Gj9TZAqcEuPJQQmBIu41Eh/qxlbgd5b0YgCy4JS1qOUBEmigejI0Y0OCI3KTVKtmaIOuQBwcXYOCgFxKfj86R63dAuXE/S+ElgM8AJDGGBJCDkK1lZHAVZYoYsLzMIMaRHx9voteom4wyqDyUKDjDHfWcbzbDJltS6ODmP01td6AsLCo84r2cnep1T1O8bYyBgA0G969LHH5lOPaNHms9Cp/GEdOP3b3+xowf/7t/9G30d8/vcXXNH1k+9zYd25pdZ5y4nwtIxeEymRgXsF+HJw1n5HK+OtyAFc+31gExgC8f6+elm2EmFu25RyJLZIMjl8z3emUSCeTi1I28roHk1PTDjDmUVVLy1Tg8lAdIKIW3QUcMKMGS9wFz4rH+QADpwjsr1kiF6X8sCKbUsq648vOXkcqmchVMozJGimCU3NpXp2HyPmsxneHL7BerNBCMqLDw4OEHuNRJfkOgayU24IHXJmFYuij1HTsseUAGbE1GtGqypKPnBxds6ZQiqdf9fj2eexjb7KrmftaOCW2hJNdVsEFyMWmUeHc9V1OtN58ho3mMf+3d8NsawzpSSZgueCZX6unsGKTXd7zkpQg9OlRz6fxuDysq8MwFMsUiPXd6cSIIPnWrKlAOl6bNEnBx0e7f9QJd5q509hJ5loookm+j40AegTTTTRRL841cKuZhEWMBEOhfCVHHxOFhVZUqoTcxUtJBANXAdJnZ4dkFTJ4dmuWSvxgCABkSCJACSA+nIdYnR1Ws3ePJVTUQBduarV69bQBNd8q73VGFRA8q5I2Pr4MwGWu/Sab1UeTDE+TgUoekmg4qFeNWDZM40c+/fkZW6uRM6+XKcdomzs89XGaJTFK6VOjpEsirgGz80kDT5nNeByHRGlxxCFrISHLsDrgxdDPCF0XQbYAf2UTpAsApo3vRrXzejGRKAzq/m9LAUfKIPO/i664VhnZxCra25Rcuk6gU7NcCbApjI+aV8SDueHWG/W6BdoiMyIBGwr/z49U0qNAaIauOZ9ccC7LVexDVYfvnlT0rz7qea0pKmJ1alAvE3KzFfTzAtB4ibzQo8o6cKsSuMoiH2058AahV7jSdXIRksZH2+G2Twa8+uLswIHbN1oVgPTMjjmRIB4U0AfAOgWp0g3S/Wlqs67v7wEcFKejT3zaDk+GMdmeD6prmdReRAcy2o0ivuOtqO8n0sv0dYYoL8L5K/NcEf1NMX4cxjSwXz+bZ3cg152NfhzkK8/PiaM1sj8I5w59jaCbh0mjYU1y1tD8HywXfbb6VKAXlupigxn4EWKVakORRcK+EsOqHvDpZyFY/vs/LYGl8ZDM0vnUBiql+vO53h44k+yH9cBn22GkrIPzW8FbM915kWQTAiUfM4wm5TkevLRUuNHcaCmRJ27Q6ZHSlc9HchXgtPTc8TLhM11BChiFe7ysX78cRLckSCQA1aqYKSkGVf8Et6nBEEfI0IAZt0M4TxgdfkFlOp4XR2JaGBgIAW6ok+SF3qWgbhZsMjlrbxr/EKfbb+//32M4BDyeRBo7XMRA9FsPbfmNusNBAlff19DsMTs4gLz8B6zbpaBP2bGyX/9VaM0JSLGHutNj/6qxzUtv+l+b0jX7zHw3Lr9IM//VnHeV/fbB4/6hYnarzT8VwNnBsDV4LkkaBaGGuyiwneLq6a6n/uWz8+UYOWGCng+nt1tAB66c9Mzade6UTvl39Jtjvi+wJkewOro8xUzvIEC5F/5Hh2pE3Aw4LzjkJ1clK85p/S/YOCzSo6+AqnOUThm4KDBBlDt5nA+gyZ0B/p+DUnAul9DBJgfHGJ9/xUAcHd3Bw6ML1++QrNR9ZbdDwDEHJ46pJTQhQ4xapkGMf4rvWaiipsIIe1lIMbGMlzcxz4vUd5mawt57AH4RyuX+zxK0h7XWldacsC6Hl8BqojzBQ4/zK3kit47k5b4a52ctfSKZ9NSEaTl37VTWMIS/dUCYpHny+riBK27/uwMS9YRB6v9vSorT0sl81mz95uvr84kxSk+l2mpo9BHAG8pDeR+llk9cp2xd/GF3vWJJppooj8jTQD6RBNNNNErpW/xBhUAHhv6mdxAmIAUAJjiZSmaiQICFyGciECBFRSqUFihIn6Pgo0iWVGHCKRPYIYCekQIRBDuYBZRPaU3j3ivka6NVyK+GQDEr13GgIhMyft2Af+avofBXxTmJGrq+b4UaLPrmm2kqTxu2XplJKZx71LwntzeyLz4lZVBm1WgBjxXChdsEeQhRyxpVBNyZLlHa5foNDUES1TPmBzpRMWY5lkkOksNG/seQF9qEIoxl1OFMJLZaPmMEZdaRsLrp3tKVTcWetSYQACriS5QQ5PiH4yuo9yvAzpASl/MCKMJCkM1CkOeVGq5WvrGbHgx44p5BGX+ShphEqNGeu+ahcUoJxohFrjAGBYVIEnArI5Epa5kFa9gRj2/RiBG13WaDcTeXbJo93bOFvSt7l+6qU2jQ2rB8ycZ2fagffia1pBUag8/gVf1FDvGj9UoPUK86Q12Kw4kYXGGeNNb26sScYJjBWh28Fude8cNyP4c+r48/WGq09bX+8boRI7x5uIgR58DU/T5jyB/RsO571LV95cLvpXGOcOWSJFR8h1HO69yg28lZ+b48aROWpmyQVgqua++ZBtNrfiKlvOAy3PmnLWLI9aUjf077/rHU4HRynYhaeaR8kZN4e7p2xmsGaEoGYhew+gmzwsAAzRSTOYclxDh0f32jKrxHspP7qdwijN73ILNVYRQAuQWn60vued2/q12yJQUBc9JGFESuHKOEEsfLyJYL5c4PD9DPQNr4LzeV0bt+U+0AXjqC2RZgh+MPB/SLQG4ucYiCQ7fv4cU9w9r1iIsrX7y+uMXAMDh+zkgwOGHOUL4K/q4wf0fG6R3gv5Tj+O/HeVWYuzRzWYACOuryxeLDn/gTX9x+tMC5w0ZUI7yB+zeBip5Ferg4lmhYGCXR/AWcLVA6aUcm+RIXqqO2bvXLre/MBER3p9dYDaf4Y+rT1l3ORbLlEc3YFoggLCgGZgJnwNhZk4tXk4h91EUbPdxICojmyRmvk8GSqaUIElrnzMF9DGi7zcm6yfMZjNsesKsm+dxXvf3EGjphdvbW7w5PDQnWqWuC9isN7alPQkcEFgB/K7rEIJm21LdQzN+CQSxqqAVWHUD6dtxl+r/l3oGdcu6c79L1GeyAOr9qs+EqQMH5emu21QXhTtxZ33O9mc5wtaavl9j8ykh0dLmtOpuyx3dfhGqQGinoSzkz2E3QP2NlybnERVYTiUKPTfegOe1A0LhHuXd2L5G/TnRRBNNNNHjNAHoE0000USvjjLc0uytvUJ3GbYqpEZFegYghISk0eHUI/UBiQVdAAAuKaFcWA9kQBlpPWLWyKF8zdoQ50q8R7UAkNhDJICENdLCDKgOegmx/SWN0pRaJRmaNam6YnuPW5nm9xvcnccTXi4l4a56thP9OErVA/av+wDpr+mRHcl2bbViOJEcUKfGIEI368BBwfTt+6DGICIO2tqBGl3t1xFLKw6QMEIXsFkT+s1aa3rXrRIBSODTth652u9LNoYNLaHRw6UTYt3yTBjMrAZgQU6VTpZePnmEmvGi5GC3GK+yNkJnEd6Whl6dCMpohMoIKCLZGFH4WxnPGigSQa57qAY3HTuB8qLAbhAXxC3uYhF2qE0aYsbPBBBbCly/lkVnPpApIS5Tvn7NzQq33A2GOd19A3o0TNdYg7d3zQUId9VxuV7iskTEOXiuRyulZULEbf6NcYKABXrcYM7n4LMZ+quovFW8wvsKJ3KMAMKJ3GYnsoBjLGmFWwCnQlAnlBV+KRp5PndoI9GPZBxEv8UKb3DQzKPvReNSy0vSz+XMTxlBfzbuFDKUaPyY11ZWwKmeLlu2VanTZle7swGcmpMc7MwAkIEDDnJkwzkRFJGUEk1Zy7MZcdLjtA625IvkiM2UtjJ2+Hdg5Fk8zC5/CuX157HjzLA+HHOnOh2+j0lycNojz6NGoUtJEND8Zbnezv/t/W/m8KUr3eaTgvAgzQiwCmTReL446ZHu9Pru4gOYNNrw5u4aEAKLRsP72p61CZGcipcBbFJEn1YQSTlF86ZXx2AH9zxK150xADTPdpikwMG3WmKqZ7frRRlFN2dPT28fH+Gt/l4cRdUHlgDw+z0Ofyu10GO/Qeg6pAisP30CYYHT/+cUt6sVEgTzgwP0fY8v91/RX10paHQJvDs/BxHh7vNnAMDx0RFAQIoaWfsUx9ETAAHAtfXKk/54deFTa2o52P/935tXyiSfQQXOrYAxB8wqoKyOSNcTCfllrOwBY7aBTCavyWDe1+D5toNMNeYvOPwFyAeGTtOfbq7AgXECxgwLsKjtIPEdmALu6A5vmHBPaq/oQlAw0eV+YtMJVDeI4mUjOKdQDyEg2KoRLaIbAvSxR99vdEQSsiOtOx9pNq6A3iLS79dfEbjDJiZsNhsIgNvVKq9bfYrKuxJUvhflL/NuZs834H69BhCw3qyRH5KNfRDg3tO5x2SOTQWcL7y5bO8z9vrZ7k/lgJGTdrddl8A7zVkKFzh4N9NyYUTgENQxGlaWKgm6MGuAdIFoBg7PRuPgsC3QIsBmfa8ZtyAIcgYt3nJTIs+hfRBs22+G/H5vMr6/7TBSS3EtUD3WxnPYo0ah1+C58weUa9aCTV7uXi4gYaKJJppoopYmAH2iiSaa6JVTHYn+oKJspKAUwdNfEqnS+lYEn6NFPwaVtjt0EAI6hKy052sqYqQCvEiV2qukd0y2DREkpBIZLkAgQKM09C8FAOiQgmhd5aQG0BKh6gJ/bd7UTzWQ2XeR5oh8zy9Ar8iGOtFEDdVKcQHT9V2LKQJMmUfoQbuV+vwOi2QEk+wctdF5LVo3JhFmMzV8bNb3WnMvUfZiCach4/N1f7fv4RaERe4/n3kZCUIXOjV2mYEwGwqSRm70Vn4iSkIQjRTJAEjFEPq+t9vfbUBIbjyzyPNdmTWI2fhb3qVRK9AsHl6fUUEf3SexRO4lSTlVe+6TFN6thqbhZS06E8mhC9S32Y6nDLYf/l7v+5Hg3Vhd75oInjlFoRJ/nAlAwi06S+y6uerRnXeIxXyf6ZZWOBYg4AR1MkUH/Pk0IC6vXzVw+a30Z7ufPwPRyHef17+qnCGGENCO7ZpKLPU214I08ZF5t3u+qBg5kurXAXS7ZqhAdT+yN9l1DDzPlx/2dRtn/XlUDdlDWajaFLi0NVZt+vWqDVunYkrZySymqGs+F7miiU61pi9OL+wxiQHPjHAmkGvNIXIbbnOq2XIfjPOz88ZBTSAgy+MutSwi/o6U+xVREIlZ05vf22/5+W5NL0+zqxKTjo/dlZ2QMYhquPMMoqptEXhqXs4/UD7vKfOldqbt3nXWL7KoU3UE+OfH33EGIFzo7yfHx9hsenz9+hV/XF3iRNoMIl0XIDDgHMDN31dY/J/j3L8FCDd79vIWBTR3qod2LEHxn43qV+h7+ZwVCZ625uBQlh3rXMN7m5/btMv5vaqB8upvrI2dff6OEaruAHQEoBMgMABagfkcTIxABMICR7TCF9YSUoEDyOudw/gRCJTUKauUoACAHiCAaYbexoPMMXe9vscm9g+Og9+58p9owC8hph7z2Rx97BUkh/MMPaPOkkcEdByywy6TOgDE2MN1B80kYs+RAeTyJi8b8++P8iXmN0OBa6UFGAy2CHuGZi7LEedUnB3qYAwylDwly6IgmjYdgGVL0OfZdYx4AfSXPRJuEKspeZJUdBi7pbH73CdF+Wia9qx3v6hfyY4ODCPP7fruKAhX5Ycr0W59sTS9yzbwgpNjookmmuhPShOAPtGTqfZofwrl5X5KFTPRM6k2BAGVkcl/dxVRqlRH33iNXbWSd9UN2urjN5J7o3sqS9/3ULtugIKZjkpwjyomK2vpWIAvSJYmrAcLI6VkxkhVcjLAZZHpIAJb89JbqjGBFlQzcgUwmagvSZD6CCRBYk19LEkNdgSt6SScIEJZ4S333o4vwx43eeUyU5j8/szq0BhsCaO8agt0chshuRLWXvsxjvXUdKzHhlluR7rL0+cNuaGkbH9TO99EL8PLS53Tl+/zPuMwTA2b+7VH+6XW28vTkTigWEgGarFcJeA8mA+LZPDVwx71Ncomt/K/otRgSw8IIBuKHZR3YNsql4O5s5pshPX9VwhplEfmlUmQlgnhNECuExIlA8xP8idA4LPaNJGQoEbkOc9BDIvYaNPHSkoQLySYgB69pkoHrO4rZYNDvk87P8YE9+TX7Wjp4Avv8rUi9b3VV7dxTglubS9Gdf2JxOWZcr1+0xvv1Qj1/FoSITCDQdjYdUOub0dmWNMa6CTW18YiZEYmwPhzOyvK/9sJUIcz+yXA1v3AAz3iyN6R7ZXYIoGgkW86IzXt/OzsDPfX1/k6S7rFqZzkax+cn2N1fbXVovLh2wzY+60GnCAtIwIWSEg4klUzDq83pTbgwM+QR92iimJ+gH9KevxJvSQ1S9F3afmp9MSeyHDzadc9Ens/jcdmQNio4jo7W3bR5VuXcT03NftGYe5Gpi0neySe+vuY42aOdi7ka4RH6Wa5TdR5qHdHJSgQWWf1YGKEEOA1sAFNTazLjzkvUcqALHMwObByVqq2s24qY0+sSIZicnTKeoL3UNOH7wsWDcGqMVLRuRqX6vvwN4bKExBbdpA0JXo93lzWOc8a5XV2kyiglMfGHbGq2vHJthU4j1pzV/S+k8sQgI2NjlUeIAIuby8BLPD+/AAe3cldp2tz0HTKCmYJFnKGW1oCEFxefcLF+XszAeg9fLr6qPPHQa+gv2kqel3SEwhBIphJ08zHPtcC7iQYMNXpfQB57dT7TXku6F1UpWpQZGamFmzwMWCwjrVojXmfo7q+13ledvDdB95dSYIesTg8EuHrx49YEHDw4T0IwP/9+/9snTcsv/Hvjx/xX+/fg4gRUwSfE67/foOIG8vhsj+dDO6kdlFbANhebX8UPbCivLA9aV9+O2oHq9/t/Fnz3Vo7FaQEBFa5MISgurbJ1zRcNFDNT4KVATKhtAL19NP5oTkgOr+E6u0um1qu7cEtjI/nbmf9x3lgfQdeTopA4EAGJjMWRDg4vwCTvnNpKVhiqXIzMY6wwhfzciJmhK7D8WyOQIyegD71WG82tn6UrBwCoOs6JANY2RxiYxJ8+fq5jFXytYSy/uFzKzDjzcGhRpyv75EVKwE2mx4C5aHJgxM07Z/qVpVjUJh3QAK+ru9BVDn6QudAtMwpnlGjHl0iQRrM/1arw/brkfWn4TNrj6dykfHj9nEuwCkOPsw1UCJFW7OtpJjVrp+FWdUyoetmqjPFHuv7NebzA50bzCa7EMBA6hNm3RzrzT02lz1g4LmJHjgxtXAovz9kL3twrlbvbFv+i9oxziXTAFTX2rITkg+hbL3Tw2vma/j6HqpU7f5ZrVfiHTBHkrZsWtFbH6OhTXWiiSaaaKLdNAHoE/0wqhXUiSZ6SdpOWaZWKAdMXqrdOrpzKCwPFc99PFz3oQIu7tFPB9DNqJZyl3Q/E5myJHgTCZ85maET4JSQ3MuVAzpLm+wAPrFJ4u7dnSqDZdVXIgISZZBO00SqJi9wA6mYQRQQBKQUs+DvxljrdWVspKLsuiJN0HZFoZjso1spDw8pgWPT5nZPhWNIx7J/YuBdQM23zBcdj2Eb8ksx2x8D9n8f+lHrGuGkKPW2B9X7onbukgJVwV09LpthKqMvgXIK1NRHbSD4YXVEhAHNzhss+qPrZths1k3kHhGBTxVupzMGlslAc1Qg+gIiAAdLm0qs6Q6hkeAgB5atTrunXuwCKNq9CNSY3kc7LuSHkPqUjQ0FEMLgIRFEYuZD+UcRcAjwlItihjKmwivcWKKR8pn5ZLCLSO8jVXPaI06YvDSGRtTP5nM3mTRrFTOB0GkaVnJDf2Wwr4x7Tvrbw+D5S79l+877IXDuj8PTrA/bYZzYGJQ+HwnQ4xaMY4gIvl5fP9iBbSeB29xOwHH+7rWqXz27HOGR+0bSf6sT4UTfTjrHH37jHvr12cu4VNHD+XoemdsIDKMglMsRUvXBeZ/zzSybsdbibmRg8fTsET0ATbkdrOar9YAJHQWkRABi40RZ/vfsQ2iuCRgwBK8fayBRjBlUr4HqYsSmvM0ijTNDGe/9hEDK49Tua7a9z5Xzweg+P1dR7AziFuyaMnjOxGDWTz1EwTiSBOEil7vTTQ2ka83z8pkdYLnIyzpM1dht3dUKn65V2n1/8Zuu2ecB/XWPhZzjhjUJ+BLXOBZSHqWLfZ5qn64+gtifYUQHBY/Yah87iNAD6OQEgQh92mBzHXXtJgIoaHkX05GSaB5hIkYggcRkfnU255MgO+GhvJ85gm9Lh9OjmFR3yk4FT5ZXa0HE7n95nd/PY+vSLQGnUFD8KfQvO/7ZTts79p88q9XvSAN+8ENpwF9rnlrXLgYVJ35ytpKQ3zsCIzCjcxA9hMYJacy5V8Hzdk3PsiHK+5/EyzVYLiORzDPVWagw91rP3r5XjE3hwXDsfje2nOEtq11g/wzoUPgZAMwvAg6XwCxpVowMnjv/C4wuaD3xSAmyyUoQEkq2POcNWtKKsel7bPoNNqmHO9HkKH3ZttkQKKccBzQFfN9v8vqmsLbqAyHos+xjb2ufgvGBA+ahw3q9wSyEZpyI0Kydtd6w3ZPyHIYqDQFVJr/B+Y88u8dpe1wWPnVEwfNwHhQ8l5Qd5WLq8/HqANVj8yni7V/e6PrMrHOwF8xmc13fTNkiLxsYY8kUYOB5omJDOd4BngMja7Prw4+A500bQxmqkivqhkf3Q2UjAlV6HAZ6OPJa15Zj8exkVDEOO51q7b++N2vHbAK/rlVlookmmuh10wSgTzTRRBO9emrE7S1qwPotBauI0cmMpTekESInwvjCqkinyjDK5sHqbShoVVAiCm6QaoV0sohK4tD01Q1PBAGDIKTpHsEBHn9IiBYRXzqvoHoZA1d08/Wqi7+4slCjN49QVt4mjeVPRd/rce7T7omUiDQHodvoc/3O59wo4arII0eouTE+m+kbRZ8yGKtR2akBKYpDCztukiMEFBAOarC3VBAigCwBOtXzgihYEs4I/XUyhx7tnyRz8KGEg/mBbqcI2QgkMLqZgssW+oUQAg5mc9xv7jO4tEk90GubzEEjAtyOVpPzxGSGQwPAPbUgM2G9XmM+n+f0jHqaGbViyg4CnoKdiBBFw1pCCPAoFAU6ApA0LbxAI+QArYGeUsqgAfcRs9ksR6h4rbvY9wARZvMZ1vcCkj7fRl2vsDtTZ4V+2Tfs6qXnrdc69Gus6HHw9sjnb9Uf77vv88wGMoAae9yC49mWkfP/BUcAACAASURBVEgf+wr31+XadT9O5RQJEbe025XpjoBjWYFxjGQuT/V9OJguGL+/fUHrH5Em/o72e9J3f3zZCxB8aXo9y+HD8lM57Pk9PqrSO9dzn3AMz66wR09eAfl9VGNSMdYapBYZmJlFna4IhJQYRAkioT4iG4kzX2UGS8r10evVLoNCNHxEI5ljKsCqOmpoBoc7mxYZs4C7e03cLeP80xxmda0oYHUe2YrX+t4SbU4V+KT1gR1ML16n0oDnHm2qnyl/7sq681T6ePk73p2/z5cP56EUyUbLAz9d/pFBDCKtU65bUvU7QSpwMI8FkekkLoTY+gtoGZUkINE8Ji6rMAV78q4bqQuJzwgpT7759I8+6braV315iByP9HZ3D2/7+20Fdiy/gTG8lAOqj/WZfffHOJba/UfQGYDrZs/r5J5joLOD53Ukev6FAaYOwZxRQ/C/rgHhXFZt2iUy5/U2MwVQzYPKAUcMSG+zdLzEXQ/u9wEQsX5eHnmewUL7iwLc3lyXo0nB73uzAzAxAtSp/3A20+hl+v/Ze9M2uW2dW3QBlKqduGd7Z+/z///bPed9d9yz7e6SCNwPAEhKperB7radRMjjdGmiOIgggYUBuIdgo4oHVZMPRKGS0SUzSBCxSZmz4OvD1yafeMxBfXTdJyIMecBGemTKGMex9K21mUo6qK7rkcWMervOHAM2fQ8ixnYYoZoxjLlEpjKbJcI2ZwA6iXDR1qjhYKXObT57E0na1H7TNuyLkNGW/9iVI++iW7Lfk/7BMQ4+9gBZFMHEHbJkjOMAUYuwMF4o0gdGnxL6D8HqBZItD3q/OShGU5q9tYSyjuVxwPBpLPKPwhwWWnnEK/Nog8IQ+SkKZ40wNpzK3SiTmfz3U/x35yrVJu4Dz+FGOGUjudJKK6200i9DK4C+0kor/Y0plERzEeQ7SiyWw/Ss86/xrn3HO1SAr1A6liftMkzICQvVW1IcZ8LnlMGSIERgVShXILt6OEeOL/XQnjQR8IvVPTGIkwFUVmlA3EMIcQ+BtSrAgIwMBoVHZ63y48LtRLII5dgjfaO1H9QVbXtf8eto/1f6h1EoB+b4mDZ/FUA6t/yAApjHOeCgeb2xVUDDFTYBJAOAiGAYBgzDtoTdIyKwK6CIY5bVaBQAkLrecqiO4Z1lL6QTKgI/nTL0qlXfHAG4heopQAwVwSgAIRsg4B4o4ygQ2aLrOg/ja23q+w1UgPv8YG8TYKsWjr3rgNRhooCY6z28VoWPzoGWHRC9KGZq7r4gEUN6IsSeeaAYSJ/AACuyiHvASMnVGGNHCgzjFlCAE1evuxmlLkGHXFQ6u8BN/Sbav4/9/laKMuYe24d+IRRZLXj+WDmMab1MV3QMxg3kekR3cgIAkGvLBS8NABkh2luA5poa5OYRuiPzoEk4wnu9nZRhAPv+uj8XFP9ROcmfA9TLQr74lX4MzYdmCqr/uNQBi56Fe/eqVssCK9J0X9uyVeNluwC6ZNtfMQtUCEptKNRaJyKCsIKFkWH356aDyj60XczKa5ajILGHQQ4AKYDZqPEcPG7BraJkfyYo2UakmoPoz5YFWo+0BWC+BcrJI0NF6OO4Fu8WXw9LtKYWPBd18LwBeXcrgz0XHq3/eGG5fAMIj049OznH5dWnybdG/kxz5K9UwL1AYx0/AiGdMAiEnBVf0meQNM/E+xTF2IPUTbLIofhoUouB+FgbELaMU9DkK//7U7R2Ds0eNX8DTFcsxbv5fop3xDuPgV929aoGF60MHMAXTY+b+xlsAC8nD9/OSKlDYq75BODgtxu1lnc6qrYP+I3Q7Sana0lVJCKVJ7xBHyyB/e1d5VfDr+I3qO67WBV33gcKhZKnlxApEbMiTcVgDYYC2IDxMGZkMQ9oJgYE6FOHz9svGCK8+5Pt2Z3t7/oDbPoeD+NoaRLciKHaIVs0qomRAtS81fNo7LBgwgHHqrUjeu8lg9JaehUU9m2JYOB5abLGXp0LiJw8x3t2g4K+S4Aqfv+PAeTjsEXElSKiYsA8Dluk1IOZsR0eoKroUgdOCWMeMOYMdXOeaxfZDnUGnge9wsc9nyGtIdv0wmNGI15WCHu1MBu2CR5PZV63gHqsaNTct0NLG8yVVlpppZXelFYAfaWVVlrpO2jfBvptwlLPIbRKc+WdIkLktueq1wv5zvyWBIeU8NXvFRBYxPJEsll+F58QhYVP90ICgOIGsCJmsIeiEw/zbtj1zKpaTVlWQH8FlLVElFxW7GkN9d7KJMVUdyaoLPRLvUw7glJQtEtk18q/vu+txnilvxrNv4LXkOnnz7SzmMDF81wJSA58l1CRkVubYp5zaG8A0OT7zTljOxggnTUDmu02B8YPNgfglJBSfPfquccZfd+DmDAOAyBini7UmLEQQGcWbLKdSfn6CtAjpBPbgg7jiEy5KBstF171ugvvwxL2lk2BFUq2rALKI4iAlLqJMZO6ArI9t8SvN5tN+c2uCFoE2p1vdl1CbpSjwZ84seVcV2u1qIJIMchQ9F3sIA+34IGap7u9i4q9j+nHyA0ktNwbin8r037s+86+lUsFMN4q1ltIoQWaCQZKY3bPUl0+E/DH+QcAhCwZn64ucaLHAAh8QtDrQwCELiWIKjYfeigU95+AjLu6huFxAPJE60qpzbutngbGd0VlX+k1Ac23AEgPw9Pomff/urndfzTtgnavTZ9Jcai09w1PrRVvTftq1oLICB6uBNoX5aAFfamm1rBL7kmsAJBApODJXonKWlLqRBadSGJnVnBRtSAkqmhyEjXVqJ6WVuUaFh1qIYtFBSxU8lYX/qTT/iCq+YJfahC7GL71Oc9GP4bBF4xnfPG1r4Ln9Z8Za0VkGLblnchSfqjndve88haufQaie94j1XZG+Hi0HfQkHeOPD78jay6PXVx/Ku36cPoRF1effCxqsSdyjOt0XV4UkeQ1kCbvk0MBSA/xrt8YAHgreA/CbQssqCIRQVPySDHucRvdi9qsknbKaXQAZ+/QvPiCv6cAJNMb2ynwK0oO+4DqAM1vn7jvNaj1dr+ChbQ/gfXXLwWk74DasbdEMQyah3In2OfNTOi7Dp0D6OxgegXRKqDKIcHT9F1hCBMUOwL73tXBdzR5z+Ou1//yqOFdsyuL97Z7+zB4UlV8CYEmGuYAs6oggbFJHQ76DbpE6IixhYKVMDJjK1vkbDtU9nRIxGRe500ocVtXrB9qyHY3nPJ+I+9wIhsnA8LN0LjveuScQW4Q1nHCwbsNvj7cAyDLg+48WiKcijPaiDqSCCBibEf3PF+IJgA0PMwFAZmPtw9nMYeml+0Ln0OHOo2QESA6AejPeySmYuShKsiSoVB0KRXP8mG7NVlTFH3X+wqPJke84Ov/3EMgeP/v35FlBIHNiz0L8qX1z1Ujhi3uaV+j4TrV70zW8Gaex/Wni9Pdes14B4WBdmt0g13DxfLMvgX6uQZ7K6200korfRetAPpKK630t6bv9UB/jsd5u9H+lUDVIljNqkTumSFiQuYXBd5D8VkFDIYQg9WEdHFwPLzJq2K1WhJb2GIu/ZC6BE4dOEuxHFeRySiYoMoAmvyVUBAy9siTrltrQl+iHReanHdJaOoZVNw1px2yI3f8QmO40j+PlgF4n28g8DmXj5aJLJc2mdd45A4HGq1H6MYVyHkEex7aUOpMXkQtAKrYbrcGlJN5v4XnFhFAidFzDwAYhgGk2RRgzSyMsrozRr6SOv9xi3x9NJlqfJIs5N8wInUdElC86AL66Dc9ADWFlTOUrAa+WE50Axba3hStgAIQ+fXCy42eDxrM+Wicdg+fnK2uIDM8YuJihBPRP5gZoq5IIsIwbKGaLOw7qNyvrmgFGJwZQlIUsNqMZ+vd9FZcK/h2KM4UQARkbsHsKe0C0+1z/3vxCR/PzpE44USPMeIGHQxEJ9i3sL0Y0J932I4jttdXk3d0OEJ/bt/e3eXFs+r/ufSVUUbNzz73aH8N4Pv9Gw1IFBteW0/R+ckZLq4v36YyK+1Q+9mQHk5O/MidxVzROveYLOfnpyOayfLtOxSGPhpgu9ZwtASx1Bp2wfZjdfkqILYSuVcbgygiFtn1MNx51HuygC6mjCZyfqsKZLU9LUkBV3233vSBtxk6zUP7yF6QFjqIpjfsfXZv/WHzmgvIxKBkUZ0sP7j9LZFiOLiykWh4nKoDGgrVjJzDQ1IaEGlWR/UxfOZH+q8P74pMQDOALuSDDycfyv0GptMkzHtZtdxi4kiO0CEhnXUAmaGaY+pQAr6yQ4ohB6iDkgpIMd7z/zd9WtapkNOgdZ+gET/ndeixYQ/DuL8a/Szw+hoGoC916ZGffwtP+Kdo1yscFTz3CBgT8DzkZNjesEudgbORkqFhiiYLO9drDI3aDysMfYJq+O7GA10jBzrMaKYYJn3fB7jribsM9C2NWnict+GqqV0MUHUqEW7+QMlTY3tUE2JsYZ78WTJkHD00u0yicdxvH4qX87SftPQP/KjuY6teo+86MyAmxjBsa938WWYL1T6OGYe/v8fnL1+w6T0yV4DlKSGPQ1kj2SN6vSSFxl77hDem1kD2yHuGyPhtolMkTx0Soegf/hzRnTP6rsMwjniXEu7u7nDQ99gOAzadpbJKvUEPqorsUQMO/ughkps5A8goGC4GCG4gbPPpWIGbN8aJW4OY59y373xZEvfi3VPwnF2+pujohfdUb/idwqbvnunJVlpppZVWej1aAfSVVlpppVegp0I5fW95rYAcVOVOnRwv79hbYdvDPltsNCgUNwqcIkEg+MrAmEcIMZLL9eHlGgCb7fHj2ME89qC8giIEpL6rEaxc45UBaM4YPbQ7lAFRKAlACUq5esfQPg/ypkUEV024cLx0/0I5bfi5luah3sgVwFrArVUsMWoHdqXvpfCYXe7NxvOcTJmcXOAGgNR1JXQtWr6gobS1sWLm8hJVyx3+/v2R5d1W4OvDVwsl6c93fY/OAXSgziMRLQr+viek1OH+/ot5gcXc1ZorkAAcnHYYL08xkuU6zGpqWXafo1AsjTJCBvPG5hRKbruBmdD3PcZxwDCackyuFPnMvCDGYQR3qRj1xKMRclH9HZpDsdZ6C8X9LQjQUDAdVdzfb9F1yUOv27NMGRlawmUC5q2fRdCnDqLmJd+nvpR/cPCu8YixsYpxzHkEwQwkMBC24+DfQfOREJBOkoXKpwpav4RDxXfXkjZ/A8CKfwb1H0FxO7lvev9tY4hhQHWHY/AJ48yvDBdDaUiHk+btDLkeIbjD/cW0bh2O0H/o0aceKdm3/J8Pf2A7Dni4uvSnp3WCv+W4ORHzTHCLE413C4619t/3Kuu+NYz7PCR+UIRrb8uNfPT73v/h5AyfVvB8RrN165XX85aHK92B5NAOlrM0vE0Y9xlS97TneXvSgaDm2O6lwgOCwjsOoLLP01LGnhdoTbdjYcebPN2oHsQVCNKyliy3oVEeN1ZF8X5mtggpzEjq/Lntn8memhb3intppuheeoqa+jwuI5AzL6p92nijAU1Y+lhhcm3vmC3EcPHEdlApZ4FKtn5diqpUyra9u84HeQ99/fMrDj4cFDBbQDjSY9ySresXV5+8+GlhF1du8OSetmaUpzgej7D5d4dN6kGJwZwgUIzjgLtP/3X5oMpFsU//Mm4neY3fdRuXb2wleBgHRDjoOuQVHYrUKHtHXHcPW/mjPDn7ZpY+oVdlNa9W1q8hz4TnefTvKWwvIc1120tYfa/3crUfQy1wDgTwV89NwHOqdSU2I/OUElLZO1Z+aGVNQVZ12bmAyyL1GoJX2lEJ1a4oxqd1j9msfWT3V/407c1qINSe3NcHbRmN3mLPt6VuTDrtF25kFpPoiQiSOigxOgKUGNRt0CmMf4him7fImkFkkaPGPGLM5nUuvp6Ilp5B7LW9Igjj1gJyJ8am36DvLCf9dtjaOALYDuZN3aWEvuvcSCHj9vMdEqfigR3jn5gxOpJKsMhZY1nPKh+f9A2mM7KNqFFumBy+MCy/Tv7svaHsSdSWpRuyvUqHY6TzuplRBbafRvQfLQ3B/f8OOPhXD8kZB5sDfP2fr/jtjwMk70/JUgwRREb03Qb2HbIbeAgetiPGywuMvqm49Xe9KXhOu3PAzk+/8RcUt9PHk2gVmEVioMovlt73Es/zF+1hVlpppZVWehGtAPpKK6200h5asvB+yhM96DXA9PkGeF7+czfIIV5V0dmPPUSnmLYJGQpSguQMZQv1qGJW1iHsFSVqCL7E5unhgg/AUBJTdiVCAoEL0ARAFaMIMkwBxiQWNp4JjARoRqYKhu8T9kJML+qGiEk/a/M8HFfriR5KiifVML+IIHLk1bh9SyFypV+GlABS87NJZwkIxUzj0WI5Uc2vtwXPbT7G7DAFvKjnEnRQ2kIR2gOp66CiODw0MD0iRpSwkj7bquMa1dCDXqe+22DQrQPsgrCBb8HVdEYYr3ZaCoAg1wI+IQvFmFCUafNbA3hmGvDgniEiiq2O2KQOOpgSTNUteRoFlt2bo9qlTRZqz/InVqVe0bCbUgzW5mlYP5TyLWSuuhKt9j9TRMIAchYwAV3XNSBJjOmsqc6qmBj9ZuMhZ8OzSKcs75SKV9+kWi8kXfhNqKC0HR8tli/N/fE8AehPTnfeIteKmgWdmvP+F3eTshiHFjKSElLqqlMrzKhi0/Wgs3OMlxm2ugDwMva1MYoQXAM4nKwD8etEgWt6Xq7x16AWDC9e8ah55SP34+c9dYrzAHB2fLqC5z+B7khxpMsfy3zexF1H+vrr+mPK4PbndK/qHsXlVOVLNH/wEeIC/NLkflVAKcLWOtAT4HmEGm7A0EmI9vk+rAWmyykP793eG95dAUg5eB4AVQEs6uJWOdJje78d8Gi5b9q6tX+xeH+s4RQo3Kz/1MPcyw4DFo/4JJPw7VLzoquHby9vquvcTqjZZywed7jBJn8AESOdMuRyRPXqrn0Za+f8fLu3fy9qHuRae2zIA+7/HJDJFrYvDBASSFtYNUpoDDjc4itx8u8s/EojndR+Oe45tDBipRYrfTvdAB6DxmiJT37rvua1qd2vtZE9Ym++eGw3F76YmD1SkZ2LKEtl31sAcp2yPjdgncj1hY9V8Dz2rRr8VOtuq8rv0zY837u85XvB55uHyi/aHTCvhLq+ofZn2ZGXc0wJZB0EBVl6CrJIWhDBNo9mHAtGztlyjjdrR/RX9KHG+xv5qLGlATPjt80BUjKdx8N2awbFRBhzBtTyqgPGb7NkDMOAruuRZSy8pUupgMVFdxKaF40oJ7/Cl/w0Hfse4AiWrm9z3hewN4sgXwg2H82A+/6/A4iAzcEGwzBgGEZsPnYmVwFFfjMZMaPrN7j7v3cAbvD+3/8HRISHPwcoriEE3Pk3cfwG+6M57dXZzYHsJ+ZDPbFwvTGIaw23ydf5Og8eaSw1UlPDa4CpNLXSSiuttNLb0Aqgr7TSSiv9gvR9Hu06/UW7usfYaBvkbeDaDYkJRqI4zIKvTFBW0KhA6tAnD0PnuRiLIJytRFEFKHuuSkKiBOosv1vqUrEwJxdEs+fOCiGCG92bkLnCEJkFeYloh6mHeO0jQps7bh+1hgdzo4h9SrR4346XgAs6ui/m/BP0Us+zWzJF+48IY7bSt9O3qkWufUxPJgUYeM4eLs9yJnb2z3Odi4MQJT52Qay1Rk9ogO/QIjG3IcZhiioAXd8hvMKKck61hEe0Oa8F4WViCIu/y5V1FKrOKtjnqwCuzXs5KPvvhGPka1eGnxG2D/dIqUO3sbx54l7j7Mqp1CV0mrDFCEAhV4rtyWjGOMoljHrR3Xt4WlEtZVUjhPDOF6hSAVWmUUCkgDldlwwc0FBIMkAWQlKKcpKKwlRh+RIHGfEwbi3vZUolXyOoybXuY5UST3hN3/cYByBLBimQrwVKinRizzEYwImHeVcobsoILH2T4ZEtk5GaAuft9YC8gVuLIuLXd2HwSgRArhXdWTJw51q9zOvyHXDxPUMBeNgDtPIJmacWsxkdAMhjxiiKvrfc6OF92KUE/mC+7pZz8RRylZtpsRzs1frnDsDhzrXg7BEunfAyRd5zgPcWNN8HzhgwrnvLase4hKHv+hfX5Z9Fb6PAfq8zT2S6s1Du7SnszrO3ANH30aNbywmoou2pqQFlAwjT5HECOIHgIWubfVPk5o0w3Ise6AgeYR6EBeieGVRFPUAeAh4AqYVtzw0PZsDCyPt6xiK1LuHNiZnBUzF6olLPaf/NlOpxLtbMaVfuAGttGS04GGBU2y7rEzLeqK2nfwXKADNay9L0pQjyrG/ndeP2IPYICuyx/9ihi6tP+OPDv5G1gmXHemoyBQlIE0jNu47PGJclR3pbioL1EHxiW4pxHHD//wZId1uqddOMgW1hGJ5YqkJTXuetjsX7NtpmXRT9P5UT5lDWPhlC2xto/41vb2/71wDevpVuYGBdUHyj7Tx5PHv9z6ddb26f30oFSKxobp18Nc1C5U8BKRfgsQDCjZwf5+DfX2MYVNKKN3w9ADxgxsvan0vXm/a1oHmEn7b7bcQOxYyx3n08x/9cfAKxgc5Q4FAJnR5B8QUPAM6Oz3F5e4nwPH9HDEodMkfZjN9+e2dezCIgFTP0FwWYIGPGdtxO6qjOE1XRrB9ajquhlskAiQiHv/0O8zofIJKLIVgWwTiOgCoSW37z0ceGEyNrLuPRJ8ub/uXrV5PBQG5Ea+tTbvQFE74zGcvGRGhHd/NCj/NS7p4CH6GjZslNAFhPytq0/XOEQtCdd2BOGLOFcN/0B4ACwzBivLpAd/6hGCQQoUQDY7aIAe/+dQCmfyPnoYDnSk0t6W3TNDwFnL+KN7ev5dzOvQY8L4aGRGhdOh6Ty2LPM6e/9+qw0korrfTzaQXQV1pppb8thdff92wp94Gsj3miP3bft7z7KdqpSwjj/j8FJgqyRuwGlKCeO1A8uS7BQJoMQoIDQpItj6TFVav96sJ6yTOsgNIILYKvKSQ7TqDEBZAT5iZXnFvkk0EdmhThYCMwUF8gJbzkDsjgSsbq1RL5jaceszvRAr5jbNrefilFiF7Cy5XmK4j+DyE1L990lpA6Lgr6zeYAxAng6j+GViHTggyu/Gk0vyX/N4hqyHc0gnoBSPy3olEkxOsaFc6Ev1oYPlIp51qhv/qBNc1sAAet2W4xXCj01AFkAlLqyjwPYKPkjDsB8pWVkq8y9ISRcxjnVPCCPbKFqnmhi68PpIQkCcwAMTyEvddWtfS95el1UIWn/VrDbVYew2ShIUMJKt6Xqe0YzPj3HBzZ6au2362vApQuUIK3qYxXuXNW3sK5Uqd4RfObZteXyotrjGMobkA4Qn+eJso780g0FXl3claMCCJvctexeR45ICVqXpXjMOD+U1WSDqdjGd+OE4iS58oUN5ZQpPMekXIgNx76S+1V3JV6txTAM82On0PPvW/e18Bu/87LYtSoJEGH5ftZPl5B9Lenz6R4r1PlptJyNISW3lTx2fCYiuPOQZ6p2nZpnxUF1Cgo5WoDFgdgZD+4KUjdQMkOBOFNKQ4aiSqUzAbTwu82HpXB+72KLWjeAs5ojU/JDaSahmtKiCgppJ4dWARCZvjQxD8q//ZNmblBQanf/J6iMPe1dNan7d9Qspc+g69D6qtnC6A14FDsb4tBgufijZQi7fcVK3GsuJWj7wgJT5KqIoGBs1SBv2uTLeDZnAXARnuc6Cmu6aq84DC+BTEGqyq4+58H3KQ7HAnjNsCFZjG0PreRUrQRE6rsJbEWNu0I2QPAtH+f2dYKXDy/b1Z6PoUZXU1Eg8a0brpGthFxfglqeeLe76PZRDR8Tf0D3pnTMdcDDKcmilpDZc5Fuag+z3W/GPM7ZrsZp0/XhSkvqrVeWCeafXUx+inGUnY/k3oYdsZ/Pv4L208DBIJBr6Gk6E96yM0hHvAZlzcX+A0JBMUDEQZipOR7dt9viyqSdQmUGAKL9DSOueQoDzrSQ1zjBlDgnSg+N3t0x85jRNB1HbqULIoRGVg+jAMSM1LqLKKU+j6z6zDK2PSL9wUIqhl96lzOAILHse/HFVKM8fftnWcdjxnr++HEaFI46TH68670kZl1mQx5/98tAMXBxx7MVAyzAQfK0a7JtU2SM5gSVAUPfw4WDYqqMfmh7osj9ePoKV3evn1UiM6mf3NZnGAyeHPs1gTxdHm2vL+Ui6Zcmp7E/KZvM7JYaaWVVlrpaVoB9JVWWmmlZ9D3eYT/QGoUSUYtoIZHFWPh6QJVfHbwTFRxMiq+dOZRIpnBEChSsZ41QdZzjUEAMWExueKOyICpVmlIzOiIIZwgXHOLE6eiABVVsAJZ1MCoqQ5g0uiQ20t4+ka+WBJAlzzRmdockwv9s6C4AFC9fPPjnugBet/RFDj/Fk/0lf4JREjJvKhT6uw3J3BK7lVic9tCss8Ua6G08bkUkIiI+jUHI5hc2a5IqQL1QCuwR97tqnwTMbAcrgBksrqZ90l4hk2pAhKuHo354+ez5822f0cYrxRyohg81Dy74s5y5sFySXLCu03C/ek95ErBJxYKviU+CeYjDZijbgjgv5MiqYKFQan2KTv/KAqg0IiEUlMU4zA6/5PSv6ZxY4zZPOLjtV1KIE7ufR4GDA4QiVZPodJ5dSy61EGyQrCdAQMV+FAoSBxeUMsaKnQ7YZsBuurkDWjAlCm47hE0J0B828M1m/y0z/O1eZjnbCHcA+gnENJpQpcSUuo9ugIgOfixWU+JjJ7n3s7na4Hizr+PQ4xXNRfAVH06pf7szPv5GAbLTcPDt/0gkxDH9i9hmj+dYH1Is2dbr7g2lHoNFV8Vkpjde6j1vnRy7O01IP+4HYyG5sv5fIy+fPovgLq2vEmu7ZUW6TMpfi9gavU6DKVqkDZ/f8TY7NvCLnlUl33V7J4JeB4ASnsdAdBMXyrueQbN3hcOaEgAQP6XbE0pwW9nALHbUS6nqAAAIABJREFUVCEMwYp3ua91OYyePFKSiIBSaurrz/s1i6BinunRBon3hnd67BerReYz+3sKntPCudpnzTg0PFrdODWaXPtD3BhMirGw5ZH1a4i/y2sxlfLtjP+pAPF8gVg4PtTj0h1M7NEDBOmEMF5ZznIGcIMbHF0eG5+nYzBucKTHYGV05wmblKBZcPu/nyHpDiMRrhwEn+/hw05Nqa4n80nFiIhYBiNGoxSAZi3PAvZdFm/1X5nm8sd3FvfH+UfcX/x3Zi7248lizUzXrxPUgEojaluna+e8B37dxe1Ya+2++t5dnN8IqIQyn058VCBsD/CK6VM7xzvgNzy9BhGIK2eofKjev6jvoJb/T4HziPZ05LGQrllxKLZvIxC0+wIdM77A9u4H1yOYGYdI+MLAAHv+HdtefyQGMWHj+33mhNR1yKrI2eQPHoH3736HvvsNcqO4oRsoFFd6jd8zoPoOt7grxgW2TvieGwCUMOQBAHD4+3sz5pItDvoNxuz5zP3LPNj0UDXD3TCUUgVGGc1JwCNj3T/cF5kpVhtVl2Nmo1VHlSaR9RQoDgM6ue/59D3Ae2t4yTDwfHNuEZ8YhPFiBGBRRbafRjNEOE/ouh4ignH0UO5nH9D1vfNXk2+y56e38hXDuLXy+Ka08EiBW/Y90Y9mzd+h52uNBKKsGpnBo4y5LDvZB7yAdz3lMV9+/0zLi5VWWmmlvzGtAPpKK630t6YKKr18M9kq7Yp3SViX7rFKfQ3P87acx8ra9TyPC6UQ35yrKywJ7sZSlYjl2QiE6GCFKpJFNAaRIuexGMsSerjYX5R0kFD0KVSygel5RB4TctchZXEFn4uVROCUkDxnY6m/CBI6kApYxLziSZAzwCwQ2SMXNKDfNATWbt7DvZ7o3yp0tGU8Qq3HeAuCB6D+sxVZK/1aFKH/NpuNKYs8d/kUuQuFe2NxTuRgrH/nbuBRw7VXIAQKD1+omHjPNNrMotxrUFgLYxiabHsnMyN15k0gIp4aYuqRZ++uIdxJtRSrzSvCe1muDHYsIDgBgtEMCZiB5O/l3zCcb7H1MIvtGx0BB6A7ClgJr+QTBZIBqHl0j/TEnrah9BhqeE3POevH2f8CQHLPuOy51vvUu2GBous67y5qalGGcHpihliIVuZHAPiUoGDodajrdg14as13c5Tv3jv9HWMxv79VdgclVICYcNyA5cc7Bg3lmQDPAciYIR4GU1xBKtctJB1AXajbqxe7cfk70EIIdgAYLi8BHKI/6zFeEqj4tUW9AlA/xJK/yxw3inNtP8xXjX1h2QW7/RlgfLnnOuZp2x7BPAT9PlAs3tkex7kwnrilb/NGXz3Yn09hGDGn+ak3M4jb8YyKv/PzlUeg/Iq1YAqEFxDYj0sUkKYAAiFieLTxRSISRIDdLYgO96BUWDoh4QJxFI9qAAU8r+uEgsUA7nKDbxLZPc1TsvQREREplNYsZkAmEA9bzuWdYWAmROadLgLQNDR/C4gvd/8ueL5PgV7GIRaBicFA4z0pUjzma0j8ANAJzFr2AlLK2IVfpvwhvDIriD6hR47v6Aa/6W8TI9Qs1pbNWcJwOQIEHLsxF5Rw7KGdN6cduo4hovifP/8XBI86ku0LIgmjAO/DiPoS/c5Nv832/AL1MfR1E3UfokzVm/8fTOPFiA6nAK6evPctab5GtX9jhG4BnM3O/WwKsU8R0SGWecGRTzSFyXqdAjlnJBBAFjocXPkAgCkA1+7tNS5X3qpxv05uqUW1/AUOPFM9nt9X+PhCW1rgHGT8jB3ojmtfiXGoQEdAIgXTV4gIEiewRkhzRqbPUGYkSjjEewh/RU+HGOmzR+EIsBrgZBHqsqdeynkEDVvIMEDfHWO4GfGZPpf15DC/B94D+XrEb1CMAL5iylNDNijGuQCIgawZ45jRpVSiIh1sNsh5tFDuvq+HAqoCTow+9YBHSiprSBhjOd+ej03T8zv9/LMo0hS185D0GN1ZhwB67y8+gegEBIZeKUy0Ifz+2+/48vUriIDxIuPgY191LoCFbneezZwwjFuIKMbLEUo3yLD5EXUoD2L/GvsaZAbmjdboBcZxi8eNLsoE6OlegIlK9MWybs2Fi+bc5C20p44Twd0KWYpWsdJKK6200vfTCqCvtNJKK+2hpc3ncz3Rf5rHOjXKMQoh288U4BiN1L1QBKGGKCbgggRJyS2L4W50lsOXCOapHjACVUFCoBhzBm8HEBG6xAAbwGavsPy2cTxmyzmmiUECCBEgAhWAWZGFQAxTmAIToOwpMWEfNt4KGeKK3DnQPn/HvNemnknPqMwC3X7jc0E/N6T7vp5Z6VvI5u4toCclp2nquSiTSkhbB7yLJ3UDrsb8zzlDxtHmagkTh+mEKN4tWgAKgs0HLgFtveTyjVZgJcJNMjP6fgMiwjiMyDJO5mp3msAAHq4M/CQIIlx2w6UaGNgAQwaQrwFx4FM8SXw3mo8SczKlHCccbBLwL1NsbQfjO4k9j2xpbvBBRjqz/gNFCPGIfiFIYqHEo7+YpXhMipr30Cij91lVwlnKCSA7aJOSeZy3RO7arqLIJdxh7WfTtUTIeXsfcwJxtvDs7AopItCpjUu+VAQsQOVXpWT4xaS/27cixn064p7f1u9XUzLGVxGgeTt+oTILJa/9vSnjmnCEfJUhHzMARkpWwjBm5KsKmvNJDWto4NOUv0gDwsl1gOKtWjLuPwJgirqoU3/eIWeGXosD6lH7atyBWYlzFj1n12nWr3PqvB46A+kDKA/v+gDx274MAOix97fjWeYwprnuWy/nbwHC45n3jZLzrTyn3xys/2G6xamRUA2P86Pev18nvLtH3bMRacHzVhHcACrUlEfFaKmuV9UgVWq0DdR7Wq29ihYPdOjs3uYvOUA6MUiK/VjezZScmlCppc6JocrVW1sNfBUH48VDwBcQ/RGl9D6ltfGvCp7H7yUQvl0DC2DuIMzvoriFA+lRxzBcbdre7gce+8wfuzZfH/YdP/z5gO40IV8JbugSCuDj2Ud0nDDqiO40FSAw9iCEczAzHv474JqvASGI5go0QEBkaZ6YGESKiNFRjRLY9zkowEwAY/ZdZETeeNWaNd1Nil8NRH8rjOLtwA8r9wKXb1T+8+gY8OgElVrP85gDcf3p2u5bEV+fSmQnnfLWAsxSBdVvyL65E7PSgbrnt2SxvOBMYLXw5Wj4AStFZoNavi/s5GVG5In2U6m8pALdpTfIjZuIMA/h3j675JFezjeAYIDnTDUlGxPhK4D/nJ7hy9UlPkMBNWOmkQkdOnsGyfaSmx6kAxISBF9BbKppm9NmOGy6DDPUR874+nAPyRkCgVxfeNj0ygOucQO5EWTNBaBUpbqe+F+ogtXSZnz+8tl4rwg2fQ/A9pw5mwFVlowxZ8T+PHUJhITtOGArD8juYc4ul42jCT9ZMyLgxdKee2eWP4NvP0YvZRth5HdHmEt7k7DtALC9/ATWUwAEPiNsry5BAH7/10fc/X9fAAgyXePw3/+nrG15NG91UZNd2HVAw6cM5SsI2xw51pkeI/rsjfRobbk7UUy+oywv0EqNtAZlzTK5rnqeT0knv2hWpRkzoJ0fk3e/2cK00korrfQPpxVAX+mH089c0mkmLtPOmdd+3/c+/VfZAP2V6vo8Wg7XHeEEW5DVri/vvV9n41+E8ih1nzI07o961hJQ1EZqd+6W0QjdzTvElYkg4FQUN5JBSUGaTElAqQk/1xTlgFTOGQNtTQDuEjgFeOUe6Gr50FUVrIIsQCIq4HnUX8FgNaVqi9RoqbNWZZq2QiCVEmr/VUG67VBCgIG115Z66FHSpScfo2bu0Lcrza7p7zX//mr0jSP+aFmRAzargguANn0y5ljOltOb2ZXzsG8pjxljHgAiHGwOzAOanBc0grbhGlonECy0eyZTagdw2tYyvAhRFHnkgHWCOlorNJY5FbdbaHk7QQ5YNtjJTt+UHHx+xTx0CfnU85x7BAviDgRC15myruuqIo5AxVMvPEm8FTs5TWtuSgFR47Xf4DHa3GfgCCGrReXIKhg9PGdqvQ1Cmdn0h3VtDWUcnaAKpGQdFqE+iYHkbcqSIZ6LMTEhlxC0NOnD6X7nCNDb0s/i7ebZve1YTH6Xwo78XB236XjdgB2UnnPf9v7tsEXf9UjJIhd0kk2DHvVyT8GiAJ4ZNlFZHgjpON5U/x8GDTLjqYkYMprimU9TbSMBKoDoKeS6ehJxREtwD/Vm+WnOB925/vywAOVEh1C9K/Wqz4fH+93kvPVh7a95HwcQHiB2C2DPvdkJ9tlW9fLrUBuiHngbsDvKaxW8fzWa7tx2+dtTbVqaN8+hpT0ilf/FfrDueya1e0SRXIETmv3mWr7hQ8bXEDiFAp7iQptIGjs1JIvyIQFmlw6b90Sd6QoHZ/2KRJgiZsDTf4iI87wAkJw7MZf9baQvsqVQ6/7T86MzeZjdhf4p/L0YZ029z7kxOmDmkpedGiAdMMBcRUo/1nVG8d77MfomwPOyZ2zqrGWvj1rfKcrmp6ZSwrfQDV0B11bksZ7hmi6R2GDQdx83bvzFkKz4dPnJ3x/9H+9uDQBsjwAGWAGwgDhZiH2PIhAyDLuwQpEr2Y35RE1mEAFAES2r7iFW+nEUcWJi1tzMjmNEPEbB64zQaw7znGmXiqvzKxgY7XvhyQahWQBuADcs8qgRRLCpziW/uZVvPCozWxS2tigKzk21LoUlNX60/j+i+hsuQwSAtxTC3Z/aOde2vQDnRAU8t2hNCRHF6r0C480Nfj89x9ebS7xT4IuKG0sCv4PxkID31JmRbmz0fMEYfO/MzG5QYcb4o4zIY4ZI9ggb7YDEuMANU3M1LqbWY7+R973XBIqOGXnM6Pu+yjO+Joy+JkXaKAKqUew4IEu2UfFlINhvRNdr+XlTzd2/7X20+xm/JfcKQ8v4ZFhPkM5SWX6Hq08gtX290CWGK+Dw478w5IxhFGS6tFDvZ+clJ33fWfStojNTQCHIeTTwHFPD/7I9+dH0AvD8Mc/zeSntHiDmTj0HtAZ3dSnWdibv1m1yvOeelVZaaaWV3oxWAH2lH0pKr6vEexERZkqbtiZzNddLjpcUO69V9msf/5Pquo+WpOF9x/O6tOfmv5fe89rvfqw8mpzdkd4DFIMD4n4PLfwNhZ824TazKP5kRQLjgwLXHUFGICVTABBpaLPca5WgmpEFDjxtIdqhI0XqOgtbJwrtDERXBVgylLQoOc0LnqDEILhAWzWqUyHDVWTL2ZeXaUc4bb14MM2JPv/S2h5vgZ02t2JrWKCkTx63FVIC6AXH8xYpgFM/vJrx3b/TLP+ZdcPsPuB13h0KswiBPo5bqCg27w4AqHuv+TOukNsODwUoTJzAxBjyUIV7Edzf34OYXKlBE6/onKv3V0rmMcbMtW2EAhZHZQn2HerMM488ZzswQgaboQXEJJupbS7op7hi9E2eewZfHYFAkBPPV+5tGEfnZt72lMybpOuSH5uvcB7FlUOKUUb3Lmn4nyvzg9v4xbqPMGZZgBXjF+R5dU3RFiD+Tv7eUN25d1weTQFnuRrNyyWPA7TpCRrNGKHk9UUMrfOrM4ZcFijC3kK3ID1CNTE6Qnj2JzXVdkAS2VXbAawT4KGN7e/m4xkiZDAAMJ+Yo+eVvUv8eXJP61oKHFBvR9MMIYaToYRWZmIc9F3T5qm5CHsb4r/EtHOPnfF3UvU8tGvekFI12pnkZHZhSGf2rZiS1lD9LjEUZ9heeM7Hs1RKLv2tp6iRHI7tLAFyBcw9z40q0N4C40AFqcm/mc0pYXulE/A84QgfTu8wXiquqfKP2mfVo09hYPScr30rMP2jQrm39TtR4PoHvfc1KMK4tzzNoL2ZOAJgV1EaD33/KrkLlkeJu/vHOoMwuVbONd5TFOA52R3+B0oROSP2kObFZ6Fste6pHOEpv529is467THSluPZcexbdQaew0FYADXssL+3RNUQAYmU3OrR3tiXtkaW1PRL22ftOfa2cWN4EOA5U1Wol3JjYaX6xQgU1ypuXDDjeURuaKATYyGa/Zio95/Rt0tr8FPH12R+wvd/bkEKXPOV13FSI1+P2pVQIA3nImWTG5JAxUA05c6NHaja+XmxxUbAGSBp8VdH9j3H96TzWnrurRz83trz/EfT7Z7zV5jOmZvZ8ffTEm975aJh32Nw3GK4QlQMcwo3Fj8QN/IgqWkJ4M/UyWq8JngONa8NMA5+gWbfDJXi6okweCrPN2WUu6b75qVuC37ZRoEwA1EGJ+dtzLgHAFX8dnsDJsYDFIkSIEDfd0gEHFPCA8FTUyk23oPbWATU9rb3eYTCZAyRSGdRIxBFBBR/pe3Z/a+lkGpWv4UpQPCc62MuzSZiN3KQAqTbfVx4/pcvXxCxZcJwAAAehsjxPTXGj+fi3JyPV4PkvVV9lJ5mG/tviH1jpwDhFN05lzozER4uL6AA+vPO16yPePhzxMN/ra2ZLg0IpxscXtq3e3D2oaz7dX+seLgcANxA1MBzDyg23de9Iava9Rb/Rv6wtODPr1PzbSyA51GfRZ6/x1hvpZVWWmmln0srgL7SD6e5B10oaIEQCGbHaPaUvqPThWefc9yqi0Izro2SgpT2HseTOitp+XgebtM32Tvb6YVjV4SU8+V4z/2Lx+17n6J9yrdvqOtLn//mur607LjcqrXadi8dL1EjAi3K5jtfrHePzu5ZOm5VcfPCdXqvNnWZa8lUQzaGIgCHthzXPGmUQDtFtG9Ul2UF6vF6FVsCjkRwTVqs71m5zoFkXuRZFKK5aPQVGUru2ZfMWzQxAX0HZkLqTGAWIkjOGPIAVYFmMXUbRQhORkZu8qG7grgBREJgnnqe++Wl7vRjDZ6gprxopdLFIZ/TpA8rDyl8ZOcYCECoPEfOJ4kaHmbK4F2etvv+KCljCp48d5bPuufFx0vlt+99iv4KdXvsuafqgsmxljEt9/tLFAq5FOQzAvXZvgn3sIJ/NyIZXx6+OrBqM1rcWyLuAaqwrqLYjlswKtBc6qQKpoTMGZuDTa1PZSgoK5kqPHcDVBTsLq6kwVEIxB36gw7b7RaknuNagHRCyJfaLB9HIFez7uN8y2NwCy150l2JeWLGPKZU85CxHqJ96h9g+WJVzaubhZGQsR23UBFk561tDr+Sr5u0nFMohqyTMe7cu7DrO6Sua9oS8zzKrKCJqmLUsfSxaut35HyCPQxthDcmVGD+cspDSiv1CHM+aK0/Bp8R5HKeF97XBZ0eL1NTvxMCXc99zayVNRQ7INeeA/Okgm4iGSl1SKlDHut3Ph99UV/PwpvFn6+3VY9XwNasVi8V86auuN53WuccmueBaaSZ4pHu7alOZ3U+AoBcZbRgeXwt0sxzViDhFiA3mPGyDoECroZX93vUb4trZZxuzCtIb/xolwJsD+But2cfoeeCOc8u8PvoGsB7eSXw/gfU2RT9u7u79t9jFJxC48FJCT6a1PrUYfar3dW2+/ZJLae8MV42UfjO/pX2KYSML0XCBsDSUhRv6fCSVvE5qVG8vztq2c7KcvhIzzzeewHgk3uQF49yVVBKUBHbuwZwRU1NiJCAxuPZzkuk72g5eTO+E2DJTnieYItEUvOwM1pFfpvPXMLgoDk36Us0L52MYl0P4lordZatP7VP7O5LHu/nx/q9Xrumy2l/Ngs7wQzHYnutaELWT1vjhmnG+6EZUDNqYFTjP4JCJUCJ6Bc35E0CZEIO477yhjiGGyBM9/orvZxsp7G8Bu2jl/b4Djt4pAB64jqA5+mPdPd4Xo/YP9DsuK3HZA2IJbzs5/0fzWXWmENUoq8tYWqVlzhfKhVp+Xect4uF79VTT1LsoQQCRirHCluXQYqvpDhUi+jxhaTwcQvfzWC4dzmA90p48NDqTASWd/gqX4zfQYBJfnUfC99E2VDY/2PqWgSh4Kd2r3r7Ym8YXC+e6VKEKNcS7cnWsBEibrDqshERoGIRpsJsK4ygyjvLKLQDbtWOvQDgPK/Jf6Szjbi2z8/PvxIdNdVMeoyEBDqnph1Wz5BGAGD7KaM/TwAEI93sRDfq9Qy//XEAkREWDcQiz+RrgcAMqgSWtu6w2RO/euNa2pmwuxd2nBQwGT67m+q4hEe9LyKYS5hhEDMB0Cf7LN8Etfv5pfY3a+fuJd+7lXWfyjPrarbSSiut9DZEH/7418pjV/qh9Bp6r1d5eySTQoTLa7ZKLzmOHVd73O58Q5lftk5zrdDs+EkrgCeef/IYL7j3hXV91bp9b10Xii7j8phCyAWyJ6pIzf+XvgFTyO0Ljrt0HN+jCWWtQm9eCdoZh2mRBHv1jqpLp4DCXgVDle4n1S0eNGCkBLwHg8H4wlqVA8T47cBCRSMEWU/kRgwQMzru0PU9NpsOfd+B0wZd1yGxCRoiwNevX3Fze4XPX77i/v4BqorUWT5hBmPMGdvhoeQnY7YwchbaOJdmub+TN6MJKVrOTJV24l73LbViT6sEmf9thZaiaAnQJxR2cexzJ9iFes48G92oFYGa4wAm9x23ioK2Xi85fnpmLB9Py6JvevfPqeu3HwNTgftb6uKTxH41AvyhmncpKSGdJXQdY/PuHZhsDgQ4MGxHbMdtEdLN6aXysOIV7owhWAqDi8fXDk8ggMDoUmfhDL22KcWctlnFbtBhdbeXEyxaRauoU1EM2y3GIUIdWu22FxmA1no0vkrzbt23UZ2zZwLAOCnHAdSa/sI6gKONJW+i9xEZDMSpKpDMe8Lb5p7/StYjYulVoTnqb3sJUgtJnpgtv64Yf8w5A2xjoYrinf5wf48sY1HAtR6OUGC8No9nCOHgY4/Rc2cGqJuY8XBxAdYAsCejOTtTe4zPfXxiDC9bLU7lbunc+2J2H5+Zl4rEc77mdGfGl6QtLqqjtg4kYnRdX99G5Hl9a3jn4sk9m4CmlEr+nTYhEBEmY9YoQc1DWsqT6qWp1/5dn1Zvm5QIOUeo0+a7cwOVUTxM/5UgnVDh1JZW4G7ynba55KEK9ve2hk3dKcEdsJBd15zSCZiAnK9xca1NeHR7/r3Ut9yRXU8wb54lDIi8n96XFWN3WBhHGHG7C0y7gv8l2FLrQR/vf6t85t9U7gva8j0Uc/m91jQJLQker7sn4phuMzV+1DtAEW628rp6Xcucr+YTkQk6OHFsQrxrPDcuAeCUbN/nfyftA4on+SSXtyrGcTTgFwBmxlz7iZzV7hr1vIQ0LCsb8Cg8vncMAcqe1mvAbHw7NtJa+UaWDMmCLO5NXxCPWlaXEpiTgz6eE9jTqhxqjaagilJGgPKiijGPzp8aPlb6sfwPR6q4joIQ+01FU6XFDctEZHtyHkxlkulxW/B8V9beO78efLrduwIlrn6799UK+rHzfG7HzIUccoGH4V6wbN8rFMjuATmOI0bJLh8INMLh+fcqudmRRZ/OmF5E+3kNilZOjlUnY/U6b/lxRM23/Szas3feW/7O9ep5vHjvTvm79yrqvpueOA5ncc8uUHkEwXkMNTwHxaAVqDwmvJ03lNCx81b33m4BtmKMB+etEXWKGQ/bB3z5/NmAYlReEUY4Gn0SAB7XOhE8zROx5R8vRlLW2GK8I+rhz7VEULGIPnX+pjAI6hI6ZnxmLvP1vQJfKGQO46eb1KEXYFSgJ0IGIeeMlHooMrKI87/oRrIUGyAwGW8241Gb08WwSABVM7yU7EZIkgEV76Pgj1SiNcWec9N16FKCqGLTdwAI9w8PtuwSoe973D/co0udhYRXKbnOg8sNZf8/3fBO5rc28zvW2XaTj8XpsPPJKh6ZX9Te9TI6FWDz4QO2nwaEtjKd2/g+/Dkg8w3uyOVSX0NuyAD4W3/vsZrXOTVtHC9G32HcAFSB86W2fWPVp0vSzjWLqGZOC2F8FWNBhafPt1Z1FWrWhfgOQR5tsTFC8e+1DecOuIMIz3d/9ETTtdxFIazOmrvYB5Mf+m19udJKK6200pO0eqCv9MNpvqY/JY4/ddyW9/SxzrZDVJVHTxzXd8+OC0CxfAxVj7JFjUQXW+89x/TE8VPPN21cPqbZuaXjb6zrS5/fW7fH6vpU2bMiCs2VOu1OfnpcgAZ6rG573qNV6N7d2O473q0rNb8ffXauiSlyffU/KV8loZHA5sdNMY0yJ6xnTRVrDRuVcMMCgpRQ5AQCqSArkMp7mzCeIiBiaMpQmPdP13foEmOz6bHpuxKeWCSj++qguk+41JlyM5GFYB4zQSTeXUPetQFI2d40nflUu2oi8nrfxbCV0Fq6O0uivS0vKCJ0dCsBE+9yRQHf4u52dOYCVJR3qBa2d1lA91YQZmU8nxs8edwK/Xvuf7V3fe/xj64rzb6Lx949r5vPPW1unH+PisiFDmhWoIsZ7Uq6hnWZToDAlKDhJUcVYGx1jQKB5BoGvL1on3zGVjKG4QGJzUODDgBmxjgOAIBN10/XucjdKgKFAQex9vV9D6iCMkE0Q0SRTgkq5EBmzYceXdP23T4dydL+YaL0uDLwgU+CmSkyop+8/aHcZHs2OTgLEMDV0y08JUQFGUDXO8SVtA5W8fSpxlPWJWIhIinebaGF8zgWD402zLsBsgB5vdXrfn/xCawnoDM2z7wLBX8k/PbhAx7+HJpeszal8zTtN3W+c1n5WgXOp73IZ1y+K6DojIDz+Fw8RPoHmgwOkY1AanlSM0iJE9pJw2yK1AJQ+LfISACjATLiy68e4BYCwXm65wYmmEdhCk2383+VDDAVIyY6pVKnWCtFqpFVVaZpWQtIgXxtoT7z9W1ZQ+I7bI+jiQyA9L2XdWeerQD6M1NIM52ACMW4ZHtxhf7sGESHOD+5w3ilONLqpRmh3SPBQoCwv/sNd9AZsGzfZBy/n3wQUefbco0wDZtelL/PpOJ73zC6twr3/qPCyH8L7cgCcd7/Ldd91s8ElAgHscyXzYhOb2veRfXTtu0B1W8UoAm4NN3YldCzAAAgAElEQVRhu7GE86kIyRt/o13hHa0O7rbGSSKCMebzUpv2UuVJ3zqs7Rut7W7sRARy78JJztIA1/04qae0YHg0FeM3woKE5OOgIOKSDz28zMBASgzmVABeyxFsAFgHwon32Y2q8Ss3ABU1YD5LRm5dEZ156qR1ZoQzMUhQTLfx89/t3uPR4aBHfj9nVPbdMz2vk/+r8fQ5GFr2vAoFIwAx+9Y8bVTIOqQQVrBwjRpAFgkL/kyzkvqz5O8gO36iDQG6/NM81cMs73bPcdCLu2WBMc6LeOyLm3yRe979LD6i9T565Lh9V42AY3fR7Fd1maDmHMoZM6pprsY8JwMiFVryQ5fnyY1Dypeshb8VA20H7mLfHcfU1NUiYtSQ620KMhaT361cMRDd258JSHoCduVGd7bBpkvIN7Y5eY/PANxwkAiZPCqWOxRsnA/1lJBEzRiR3BhYBDkPVr/gusFDrWGVP2j0rieC8sgckj1KR6nzdBNT9zF2vmPGpusxyFiMA1rwl4mwHbaeEosweE51kxXIQvE/8c03WyA3yKQSwWpuJfai6fOd+54w5mqNuoZPFlqdcGrGsf5NHnzosL2wd94RcK5n2HxI+A3A/ac/S3m/f/zD2qEZWRXjxYXLLfYvN+8qwHu7ef5WevJZExCIUCONuJ4pqmf1bp9YNvezvY4ftHOLuewFotDWAOQ5RAu/Yu/2JOnOj5VWWmmlld6IVgB9pZ9O+2T+H3Oszz5+yb3z4+qn9H21ff7xj+/Jbz9+y7IfU/rMzz92/JJ7/Tg8HL71+e+lEBj2lDhXyO3QxGiWoki3iHeZRz1NJIDfFfhqai4Mo4VeT2QeT+aA5AARCUS4gH392KPvDezjZN61shUwk3nAdj36frAQamAXrq3eTIzEJrzX3JLkIHoViBgGmi1RK7vthGx/RDqeKFYaBcSUWqUGFhTK0/snedyaMqY5apfnzq8lNr1EDbbSEt0RcKq3CHWlqprnA5PnDAyFGpcQ/xNFG5myX9TygidORXlUDWKyefzCRkggIDCSe86FN7CogBT4+vWLAQdis+nh4R5JgYODd0B5t83Lat1vzIKJ0W82SCIYtgOgWyuLBHxqIPVwlUE4hnGL3cyZ7Vc05/LtCjuWXNyV8nUcHxUFJEAVWAeBWUAEjHkszwVQDAB910MJSJ2B0rnkTI97rSamqMsFRFf34u36ZJ5w2UK1Y3iYepxrbRufMORaINeK7qTDeDn6+B4bL73MoLMEPmeMWdB3jHSWkC8z+CxBL6X0iRkh2XgWRes5IV/MuSKBzyogNGkXAR334MTlWJ3JRj+EZ1LXeR5zxYQnxndT+sXDYBJSDZ1JBkClxNVTPHtbNNv3iFyUrlAgu7FBhFYP44N0msBc14WULC0BiRktRPvGrEhJ3fGWwKRg7nD/5z0Ed+hOjl2pGorrO++tQz9z1/yu1xmH5Zvk03j2uIzzeOmeSyfZ661Q3IFxiHx5s/ONJx/PQ79wQ7tgOAE4PSaIe67HOUYFbPeBzgHSL+VEf8zTu/VC+qXpJy2SoSNu6XHgf8+ubUfRrLNbmjcpMNHQ+95rWmIjozR71VgfAlwOA6Pdavr81OrRLiBEhJKnPc7flkqqh+Cvs/1ddKd4+1gj3CyBlYv4QNDi/W9OpQxlA39KflwHt1LJvD2VPkhsH3coiltSC18iqEZDJbzHQjuwe+luCXT4XiBir7z0ffKLPnK9rNuNuFTDBdvV8HplGM82wwZFzXIeXx6aMVaXf9QAvPgHgCiAr3Zm7nbc2+Uif2t6nXof+995SPZ9Oc1/Nn3rEvStX/ci6y3WR773jRvLVji+QTP0YPVUD1zBtxuqHrGA8zEHgCN/euy99teyuULNHhW2F++6Dr7dKrLsYTY2JALkDPDJGbafthC6xujPKQne/fEODEa+EYwMCN+BiPDVLSwDH07EeEfmxcxKGMgiX5EQsgr6rrPQ3mLGQx5nosgLEcHD6m9lh0xSdAph8OjRe6C1W6KPzOi/9g8RYdNvkJgwyuj1EDwMW5OZoEicsB236JLt9bfjFiLmQjCKmDFzGfrHtSnqH0fwsXrjk1qYV6HYLy7t6xjAqRwDuEGmG7Az43wp6D8k460p4eDjR3x0wDl5XxKAg/MPOPs0gsCQnC0q2tWFtcvfd+N/j7wud9zwkO9es/ZTGPW1HuAm52KSzkVQ6/CYhqZdKWylpFAA+fUqAz8P9V5ppZVWWumvSCuAvtI/l374/mZJjbbS29NzFEI/+v3Pvf+lz06Vg9ASQ6G5Rcv1qiCimTBehYF6okrgrtYCgZDFFFKfCSBVZBCGPEIlQ1JngPYElAYUFtaLGNhue/TdFmOXkLIBL+KehJxM0O/6HqJiQjVg3kFsnosiBigGgE7q4e40VBA00TNPDVt2guFbnvF5lxJ2PLZaVeOjeWUJ1Zt/SVfXvKzU7YVAxb73voQeVRb+lfSIP6GuS2HcF2l+X+hS9o0VOXh+pdBzRdYRrKa0V/dK7PoOm7HDMA7mFREKeQAWrs4+PJHsc1qh7kFCxB6W14xbEvXQ8OLlCiKYs5xCdYRoLhU3tTUwbEdXULPNSc+Jq3DlXQH5LUQ2bTrkkTAMgwH17n3dcqvwRt+n3p7rXZb0MHMYyo5v/e+RKVOum7tOIhxfVfmbEkbdY1yhbHxOVCHZPO5T5wE9PWSnATc2p2TMJS2EhZ7MDgZX0NxVfOg6D4kuinyVS5+NVyPAt4AeT1qZL01xpVBkZKSzVEB0AEhnNvo5i0f2MGbGDFdYzonc2IKQuCv1CsOL1KfZGCnQeKbWfldXZLZe9drwGJmMFTOZ56AbhDCzK0XVQXdTskrOJc1FlAkAfOznyrFfF0EWG2M+IaSU0aUeXeoBAmQcS6QGyfBQ6uaFLnlAf5pAdOoRVFBCmkbYaksPQCCczBaRmkKgtNj7W65rNAQ+SWjHUydf7NFs7b4rV+JVR7MPvrzr2p7bnB5je3WDzxSRKuyOeYj1oFsvM7ySSg523Z1bS+99DGT/JbCon1SHyafx0mosMb69p2Je0vKt7X5vcr0C5WV6OSA8z9Mdfye/vewArOPczxzyti6TNtjFctyuG0IEFjMjU7Lc2wyuIZF9jTK9fAJ52a3RGLknYwHTPJePkoHnoor3AtyE976HSi4e/Q3Ass+Ae7KfnvfyY/u+x67pc256C5purCu2pDv3FO/Rwuoj+oghge2aHRiGhYGvIFzJW1tKfoK5/cPoCL4O/IyXzxnldxbxpvc7MEsxz+eAWf1Ud68XXI8tL3iLcMezaPaHZMaCJx6F4V6+rXNi78ARet0jOByJ7YqFLNKVGbAo5EKRzhPw5zESGJLEeJwwKFIlsEW5ui8GALY3OkBjgCVawHDf/JqBr5jslGX0+Uqlc4i5eqDPZORIeWHGvbbPK2C5Tg0MiigE4x/MjHebd16aPWdpOTJ8OwvNgiFn9G5kMOSMnEc335/qM57f883PudLhB9ASeH7szbjiG5z4WBBOi25n+DSiO7d1brwQdOfm+MAplbEiCORckS8E24sBSmZuo7Clr3iZo2n2Lmt/Q9KyH6l56tv1pBGXX1KZAM1j7s4MPWg+p1daaaWVVvrb0Aqgr7TSSiv9Dclkdp2d2yMgPCUQ7hEEqpLSikjEUPU8jiB0AnDn4eICiHMBWLPlJdxuHwyY6RKQLO9y8RrpEtKmwyb3Bvg4KKWRJI3ZIiyXcIwe2E0YQupAl6BAcwvNJP9ftDDPBGTHzwqITn6yFQTDUzIUd4uC2DcIinPP9e/x8jtceP+SUP02NFXc/61I304fMpLZ6Xd6jHwhoA+EYXhA11kQ6PB6e/fuHfiB8TA8OCCdTaEfEJxK8foVzRZCG/6dksMnFOBAKgo+UVOREBSUGIyNh2/36BaSAWJkGQG4Jb8owARWQko9uj4BOVuIROcBlCxnIogwjiMUA1SA7jTCpVunDpduQEC3iwD5Eoge9JiOxqDMCs6zA9N6WecunzHkUkAOQgspsm4BIfOYAbA52AAAttutAdUernccR8BBFQNOHSCZAMvTenfJjBUYloOdzy2sueUXpwKea+MPZu0/DvgLclmjCfAZI/sxn9k3IZfWGxk1WgEAdOedO0CaoUDizryUNo3HucLaBUXizgwBVE2Z5vh5tIlgAH2Edy59yh1E82zMCDLKJD9xzpHbcrRyQtHl/yMGHi4usDk7A1SxvbqyNjtwnc7MkGNwzxhAkS8FGQL9oB6S0wM3E6PvqBYOM0oB3NvJ50/7MaWzM583VJS1kygCzXqiAPJFhuAGpEcQuoVcH0JroHMwjkBlph3uUeQdenm3O/xGZ38JkVKY0J+e4IwI+bp+NwGOL1GsMbFevNedSKM7FEX9cuHUf0Fg7NsBmz3XC1i7g9E8q9ySC9zPxn6oIJDNvGyV0fZbSsWkBc8nxjI/lpYU5MBsrWgA8fLXPZeFCMi5AATKsbWsPRo/2cOzkuf+ZWLbbzo/sIVDzCiTzJPX6ifIWfC7CG48fLtKNRzdadOewd/p41/ke3/NamgzRgFe2XoMcHQxFgJmERDGCxZVhMGkIJL6Lc8qO/Fc/YFU59Tb0AlM2ffpGffewjzP517nKy3TEnYe31/wgDascyze7IAyN17WUZ79nX2jpLhWA9Enhu+IGyqdaAUwP1OdDrPqlcduXYAP2fpGFULAe7qEXApSOoLt+2xfNd5egZjxtcj2XOefR74bQOiIIQD6aDMSVAQpdVAVPLgBY2v8EnI8h2FmeLU3a0vsPa3axjuhvt/UaLz1YdtTfb9Bch4tktEli9KVJZc1jYix6XsQEe4f7ktfExiD5IY51Dm7K19UXjXlMTrlN3hbCkPIJTmf0HiGq/HTTk8AKC75GgBwJqfIFwo+B7pzxn+vLvCf839hGC1CV74UKK6MzXpZkxznAKCRkuAVohQtCYHt5flEJP/4fW8SRqxzhw6r5stHo7yO2qhdFTh/buj2J8tfaaWVVlrpl6IVQF9ppZVW+rtRYC6Npn0qNMy1Rg7UIoTFZevZOaBbcoQ7jWJeOyKC37PiAQBxBySzJC/aLscrRhHQOIC+foWKYhhG9JvePBAjvC8TUtcBIga+qBeiLmCrQqlDkazY4SQFFGTAvQgiXxop3GfTnwjlhbeNs5gSFVMlQ7lFyxUUD5hZ//yK9BhYfqyWn+z2zUX6vyc9Idd/M0WOuvK1ef69nLOFYOTqYddvOmTJGPJQlXeoBh+KmpM2wI7gEezeIzk7AOue1BSANzw/IICu66FZIXmEgkq4d3uXQBxkERVo3kKE0fWdefcF//B3c2Js0gbYEsbs4RPdu0YnE+4IeARExwvOR59O75srJOHWMlpyqAMAnZmhgcBAEckJOWeMMljbRmAIhkCAeOII0dDjmNJPCrBtwEu+EOjHmrcVanyLugQ5VwwXo9dyrtaOIKtq+cox50HT4LnNClD4X3eWMF4I+IzQJQOEUkrglEqqgIgOMOlf91YVD3ff6nTLd+YdUXKWMyGhQ/ZnmGp+eQPGqShIRxmhNZYvvEAz0PozY/PhDOPFAKh5i27OzjFejDj41wZMqSpZkUENx9/+KSBkC1XvdT3oDwACxpzdA8kVhCoO6OeiHJsCdDaWfM7IFwKQoIZt1fJb4tst3/Ad+pMT5GuPRjDjvO3X2CzhPp5HINwAOCrfw/xbz36uIzIvWSZsPpwgj9fI7p3+lPFUKDvbMPCH9dOe1Oupsn5aKOR/ynKmDasEpmysuSdOVL1vVfoSLA1O2RfxVBm8+84KpkcY8rlX+k8F0acnyt/gWwBsXXRANu6xIL3RFwT2yEfhXe6PIUK3TzzP3NCo5tktjL/yAhWPuGJ50CfguapFlpmAM8v79uke/hU67adT7aOQD9Dw2Vg/W5mj7N8fAaDNALb1Qvf9zN+j055F1y+8fwXPX05lPpJtA2wDN7upCTNu/JUb/lv3DWaX1DL0/5+9N21vG1e2hVcBpOwknmQn6bPPvf//l7337LO7Y8tDEkciUPV+qCoApCRPGTpJs/pJW6I4gCAAArVqrRIDgwXX4O1x1b76bDAQwKDyXiabWBac0wLYHWl24PwOzuzW6ctHAt4goEOn3TPcIYaIz7FDjNHm/jpWQnS+dwjCxgOBhNGBEIXQ0QHueVAZeABZ9NohtAzzBnycvHtYlIXPbAx0XSyUsZSZTcWDYYJP/mDQ9wt0XdTATBLklCa+C62bGEP9HgKczU6up7UDPN9lXwucfit7aF42BbODAM48r3nR2YKTunLr/3v1F96eniOvMph0ZPG6uG3P2TRfwZ5X1HOH4Ef29wDlXX4Y5rqO2+4+jxekKs/U/tp+DsEC6UDYcfnZZpttttl+I6OL9+/+OauI2Wb7m4xg2Z3mmdWPNdGa/7vsa2ScCLsXAg9bHc4DNJerbh0P8y2rY9fRTwXQd12eAEhmBAi6GNF1nUZ+d7HkHi55zERAIaDresQuogsRXd/j8OAACIScMjJnXRznjJQzhBWk45ztd/2NWUYp59ii0TMLBJpjjcUW3u7gdZCOWkBI83gV8FwAmjgr3RFBHu3eGBcvRVvv47osCzmXUS70g+keGNX3tD2MHImTI48ACxl4WL6tHCOCLNN868+1f974Rs2/72FHAhzIaWGBhvOASISuW+Dg8MD6UHXcb9ZrDDkZu8WAcCvh2FEFcBaIZDAEXeyrY1kU3HZwweEABbdFgVUGwJp3lIUNeO2Qc8YmbQw00AP7rkO/WMAlFCttR3cQUadWSoMqTTi7BC4hrqVOqwTgTpnse+rrudtbmwKDU/CZcGxlIWQA8bymlHD/mjuh9Jh6VV4xqj6F/q3ApyAuI7ouggAMfxnT+63GuIoAw+VQyie4VYff8qxhh1LJMb5913pkXt3o+GTWL5fGzNBdAgFdiMpA72pgRIyxwaCknDEbI0edmLpRmT2dyWwqeE0hIEQL0rC85URUxz+gtAdmNolIIA8bfPkrI16onKcGbmSk69T65+AAdDQGzes/XiMQYT2sAaBhoquFpb2HVnqGeK7fVbIzKKvJnKcx9FgPG2PmB2y9SwHklE0W1cE5bQObvwYIgFd/HGpwy1+auoSpVRE4QrfskK8yboIB4s04/0aADsfNcz+GiMtkOqCuUvAHFwfouoibf/+P+ugBxLNTDVyIwRox4cvlVXmGwPb7wYFyZ5TzCyVjv7v9pMWa2lT95eF3bHU3x/KEuDy7qfmWMAJ0qwu/BdANRynjEznLj4CIUIKqCnMLNdBmJM0uKj/usuMteA77neVvejgGtEyv3s6nS/9qvo/e4eJrtirNHkIDdFkde+CZM9AJQeeZni6Fttd8LQOdORc5YgWFMpiozGP3zdu/C/NcvJYeXy99yydrgssqCU06vmp6mibvMyrbHLB2Cwc1dJ7TdR1C1xV56th18FQ3IkDKCSln+9ukUgHgWWlKmSbvurp997rpZffdvL/aAICvmki+rFxLAKvm+7EV428F0u1Wppjc+HvTv2T79217WuWWU8ru7dMNZThpxwioktAIHLdPXYx4c/gKi9iVcbvm+Lbxgdn+SumaZBfbDAO+rNdljC3tpwxrVMoDUpUqD2MkksJ61xvksnbQNik4YtXHmb5PQgygGGq5m7ztIoLT4zOk2wQJjIx79IdvMNx/Qu56kAi6vtegyazBiSK5BBHUd47VvT2AomgCXcsPm7X6AcTk2x1YL+C5zoo6CuhiBAUqa3+PSYhRAzeZU6kvVxMBAV++fLF70olxyu28ept5vmsd7hvaX9o+/5J+/viw87L+76mA7kg/e9FuCVjyqc4lvX3iZuRnEUyAc7MKwjfWTtqfYuU6tY3t3G3aMb39A5B23tLs8pwAqhYUD6ac5goJnmKg/VzXZCjt92ts9hvPNttss/1cNjPQZ5ttttl+G5s469rtI5aGL54d0Jlsd0/rxGS6ctxhdVGpi+Kak0wACmUB705YEUFKCTllDCTohg6cM2IXR5cZyWOVaP/WoanXCMZ09zzoAQyWgBAAiDIEZUfS6tbJMZaDrJCaHrZ97Jazluj5i6YWuRNqNu7YVeTRRZX/2nA8y6J2mjv3rtm2c+E7215rH9v3NPc98BUDywDiATlHxNiB4DlbAxYHB8A6IOUNsoimVfD2LqG0Te9P7oTy/M5uOefigDB8XgFFAzcRgRCi0qsNlXVoeMwIU4Bgs95ofnQHG0y2UXFTUZUJAJSzAgtepjpM2QfN0rmvh0yfhTyy/aFt29/vrCwqLc9XJglI+87o26n55DfTOuJuwatTZaGT8vjJAHGigBgI9LbXfQXIrMB59Nzj8rBDKK9UZlEmlZCvMrqLDmw508N5BEhznY/uwMa9UdwDHESXKo3ImiNTZf5RnKMhkKXdaNpxzqXMUqjmghC64ksdsuDw3cJ4MKqUEAnAUvO/C+6sHMfolz3S6gpBzrAZNuhixOGB5rrs3mfc/7lGfxHt9SF2v6SKCVaHIaikp6cxEGhAQB8jYogY8lDqwp2jRApOxxCRChu/PovuXPPG58x4/V+vAAg+/ue2tkvR+hksXcPUNAf5bdPe/Z7b78cgBPzn8k8AwIlx0TJuwdc36E4JRKcgk1qdSq23cu6fqI7/bwSN0Pxsz7U3gq1x6qtl7ncMeLtApl2+63I8jcEnD+4NxpoUUGn/pfwNeD4CzJvPe4GEn8SmDOad7xC9SQCwXOgMCoBkY4sGg8ckQKDzWWIPmqpMcq1FsjljvZIHHbAwXrPg1sFz0cDQXZOJfczzI4s/8v76K8/d9D1f1wrUPpUnNqj21tu2OJ6LU7OP7/GLVto3MgZwDuDKvv+zawN1nvPEHX3/Oq7Y+FnWqfqeH7U1aeZjJdB+/xyyiUfdmutVMJzK2F62E5XxnXwbbK5m49QU5PN3fs1DTiVAkIIG8JIBiW01dSEgnPZY333B4vANKAS8OjrB3edPEIIqDxGhCxGcbaVdgEgqlS4iBrDr3FKDkhhZGImboIIJeA4QIkV0MSDGoOeAphPyB0EECNm6iAO6GCq8TTrH9LqT6YR53yzb6ryk7fhZX4B7rC3uHY0D/lbhRiXY/dk0x+x61xxbO90ZhvXcevEpRuOveY5vxcd+X9m+5LE4u9yv7eC5f3bw3D/v8lPNAPhss8022+9lM4A+22yzzfa72mjFYB7REaQkO7dLcfzts4dXieSgm4HoyJoVLAdl9Oh6g0CW75xz1kWxM3NElJUeNOKdmvMKkYEcrSwjmdPXgJEYFMTLlltXGCTKmiXSxRSL5XZt1jYO6Mmoitwp4XVEY0Z6W92lKse/Vwa5SSI7U5TGF58yzUeOkLZ+LTiADEBzae+yuDVndwBwM3Gu+gJ3ugC+pe0n6vLhX5277JvZL+aZ+Aamz0hzPEc5VWB1xZALwrAZQAeEruthDQhEhMVBj5AIw7DR/sXerlgBO4oFkCaEyqy1cSDEgL7r9JTmrFKWF436R0cBJCp97SCqKj/AOpOgix289zCL5SENoyAQZ0FS16Hre5VFHwZkJGXZGHvEuDoIZ2cgEDarq9p9q19yZNsusN3b2/2DALkBe1unkVbbDVpOSqzimZOrjK+k+he3o2u7X1UgyJkRughaBvDqGgFn5hiMngrSnHyWw14Alzxvr+fDRboSOI+MGmyGCeiX50hXVxguTyCkZcpXZwhvVdkjdgaiW/3rxwZE9/ooD1tznCceSkkCpDg5fUDizNYmNUhCDyVAWBlD0HF7k5MxuluATi8aKOD1fx/j832vz0gEfMVYXJwr+5AiEmdsNpvC0jp811tOc2DRmRpCDMakBTbDBp//9wte/XGI+/98aZ4jQSygobuIYBYsjKmeRRVQhg8JcZmBST5Tl9W/+/M/OH7/Hpu0weZyAxJNSeB5zYfLAQFHOBF1Xd827edIqpPax+xpAJTgDi2JMknLcAfytYCWt4jdCQSEt+fn+OvyquzTguRHDETRnOzX4aa0sR9h0z75Rn5sXvVvfb1P39pxOnkONsTCpz4eeOL/ptZuD83fYPO14H3RWNDszuoWIC+MwG1gdxus/LmtvIPagC+9idLzAQJlG/MMCFP2JQw4RwGSZCS7XLe3ALqz80UMPDcwnUVwZIPr3Y65mJe3tSmA8a3B85/7SVYJXf3avmdR5gz+bt1dob65ATZ/oP0sfYXtn9ss4b411D68oynPlDhVsoCa5hyuTOTzGXFQnPTXh68xgW7t4ygYqAGgCwO3gH0etApLaeYn4jq+N+M8RQ3664gQYtQATgPTgyKGICK8QTBW+xEYdxjuByAxQBts7gUby9cWgsq9MzOixdyazjwo0AiALFNCCdhw0uB6VuDc1eGEa3IgEKGPEQChCx1AgswZWRjMQJaqDuRvQH9Pnhwd63hss/mbW092oM/ImedT2HyqriLtPjuQ2if3chn9eXzHb2RtAFb7fXq16TzU94/2N4fdx48OfIJtKR3KePt0v2ZD2f6txlb3L/m5HTyvcu0EJ3JMc6CPnUmzzTbbbLP9LjYD6LPNNttsv51NAdw9e8nuz1T+95Dt3yGE6vTnzNiwoBcAgZU1SREui9UWTSXXMzBAgY0YEVjz8XohhdXrNY2aLwH8wYFqLg7MgAAQAxTMYSmIzbJ3DHc5cuarNjwSTPADbQS4jxdnu4rofhJf6B7J88BwrbvZHrU9/tmn2lNwlgri6icWzUMehggKESEEOHOQoKA6UcBms0aRYnegFgmRAgALxPDzOzDe5CXUvNR+cQMADJDP5ih0WXZmVmddIP0cCGw5ZEOMuk9mcGbEGJAgiFZ2oII1REDfq6R85lSCAMIyaP7wXQ6S4mRB8YfveiYTiGPrt+bw8o8nx7Rjhu5/C+AE2wLf08LdTpyqZcga+Zja5kDU1H+z0xSsap1O+aot2wncJe57BzlBa3rkiQL39hwD63PU42rra48owUvG/hEIutCDOYX3SQ8AACAASURBVDW3WbzEELEcwBYo1XfB8SoIlCkUYsQmDeb8Deas9KfCBTAnARYhlFGc3lq5rCHLRMY5NzKcg2yMVbVACAHDeo18lTXFiAjimd+plptXKtfPmbHouhLAECUo6LhUsW1mQVoN6C86pMvK6l+cnuL+f+/Rvetx8PYAm782evai1eydDXvN7+VEartpn8rHPQ3bx/vjawGWt4hRJTnfLs+xvrzCLY2Zq3cA3p33uL+6goi9M/YX61H7GkemCPBafhyI7u3wW9qz2Ud12jH58Mgxj+xHzTzGd60sdA/6aBzA5D26KZaD548905/EafykqpPa06ewiN+zgmG5MDEzBJQtHcnoXO5sL6ewc0/GUdFAM0Zbn1LLI5P9MelHe+btbsf4FZnoDihKBbzHL1n96ACGAxZACSRtb5lZg56EUIIU9AFtzxtk2uf+IXbcfP6n3fvXmvdNAikiHCY1KK7HZPu17wHr/8IMDmG8xpLt2dZ0jaznAzy4uxqVSSthDJ6rRLkeF6ONSKLKQJnzaFz31E+BHDQPFYwH4TUCghA6OgLjE4g+aZoZEnBYI4i+T5LdWbR+2oWozPDERWWpLX7JNk4Cgadc0HQYqlSXmwm6pm0gm/CLEBa9Bv1++pJMWYs18DdGnSNaADtZ/ThjnGR7PbHvDfZzvNm+j+17ZwiAj5amCtA5oQfXCzQgV6CBx7z7FM+quL0BT089/oXzD9oxCrbS7AAm4PkL5nezzTbbbLP98jYD6LPNNtts/xjbA+/sYUzvsqdIh+vi3QFx9VClrFK4h6FDFME6KqhGgIFoAmECs1j+NwGzRjdHWC5K6OJKnOUKGTkQnaHq/CGKAcEW0mD9hYgRDER3h3AuzkuVMxXAmO7OMPIF3ddGFLvzo97Lc+p277WbxZ0z0wmAMJdtABBJnWZ+lpZ5eMICRpVzv6MaWe6Otr+Pif4Tuy3kSfjFV5k7Nk5wAxIg4Az5ShCWhM2wAbOgX/RFBh3QthBjxOHhK2OHizquhJE5GRtXGelEytBwJQPPGeimOQO1r7HJKZLRWQKArlGCYNH83USAsICDIIYOObMyWUiDahIzYheVUZJzlYsMLompYMWQCGkYAIj+fq7sdV4xIs4M4DbHnznF3Dnm/evg7QJ9IHz+c6P3B4HgdiuXejDsouCZ5iSKUMdQanDOFsTMBIx5wxNnfrutAbKk+RyWAZ3lHc+rawDAZnWN128vquxvNilzGz+mjIu8ugHhBGyAecBJAdH1/B0CBdz/+Sfy1QkIJ9AgitNRuQWiwUcUAKogzwQXgrA9Z9HACQiZozKWQAYyr20IhJyyOXEJXRcLG3O4TAAIB+96gCrDnmXkgoYHWYRAWG82FgQCNJQqLBYL5Mwgrk5RZ5oOl8qO7y86iACD5TYPgXDwrkNKGff/+YJ4rm0xXWaEJZn0OyGEHhBBzoMFjkQQdTgIVfKe30cNBPA861cZQow3f7zBwJq7PZ53yFfHELpDkFMIZUACgpyC6QbHE+lQggY9eI50Z6C37e3IgCDCdk7KYwFeXZxj0S8AqlKqR+/f47UwCAFHFtjQdQswJxwulwgrBdhbxynw/cC5Fi9r2eAuhS74vmD6tz93e0c//nRlzlT67u73aAXNCYUJaCBDC5q3ucWnwTs/C5u2ZZU/67jm87R6a6oJgThwTtBgT9ThR0RGeYGB3XO6wkBlzTfM4ozK7bL4/lNrA1uORIOwvN9/bf/8O59kqzZSAz1QQEEH0EPz2ecK/j5UYIws0E91X3TeYiAhtwDN9569bd+bX/Xvtq8JjJpNzZnlDzYjA7XbNsfSANdB0/TA156T97vN8iAQHAtw3QB31Izs1MwH4YB3IEtrZiojAVjEDjFEiKdLShnJVIIEgkgeqGIAOvSF8FoIX4KuCwPpur2Pp5BuA4CRRUDoMHCGgLEAgUXgIQJEAWlQRrnmiw8QIWOmq6qPpsBgAJoWR3So1fpq0j91XcTR6zcK7n76jD5GfF7fa9AlG/Pd/AvuF3hj+99/+WyBojp+3368rWM8BMnm2XWbPY/H+u/WvOyhxEoPHfdz2JEocP4RdZ3iwZZHNoT65/b946bKgMBT72yLeb5n+7dknk9B8+1TazoA/7GqAjbS7aCt46zAP9XcaLbZZptttm9jM4A+22yzzfa72d4FmUdr1+9VgncMRosxQetxGJGep79tFUFQGKX+dyDCHQbE3OFIBBtAWY6N9KUypQx8gAIhyNBclLYYcRk3zYXGZaFS5LUQIKSLaCKAOICiHkdMyGAE4uL4JJkA8WQy7eWGG+8HoQBFbYVPlnw76+S7mZcVKGXW3LlasgrAGhiDcaS4AyOBBQ6lHRMwQMFDMUD971vh/7wLUAIKiP6i458Zwa5dpTr0cxawrAFIcUrBGW22uA9BQed+oUBfzh0267VJFDI6WgBZwJLVAZWlslZI/c0ulxi7AGK9diDN/6y5ymvgil5dAzKQgUgZAsKQWM9pxyRmdOTyl3Y0jx0hKk8PICWIMLL32WUAr1oXY+UE6f/dsajbN6yOdHemAadguGRj46yUktK9AOQRp+YCvJk4Qsc9fVyaMdA+3RdQwB44QVwqMydQ5bDH5SnaTOQj8KpcUD+lq+umDLdb1xqB+cIgnEKgYHtYEnil7P4Q1CmqzJ7meBtTctYyhGABCgZIaD57Kk5cMSpvceQG2ip7kfwXQXfRoY8dYhc17Ua9MEadS/R/bH/V2at1tlgs4FsVkPL6ElNnELx6f4jPf97DdUeykJLHQgBRxEHfIfx3KIEK8b0+E89trvdNhd0+5E15PXi9RXTIwwYwZj4tgS72ABE2HxL6tx0WXQd+F5DSGfquR5ZcGgznM+RVHkVZkLW+t8tzHPQLfFl/sesK8hXbuw4IZxG8YvzXu4Wx97mAToAC5+u8hvAdhmvBwXKJLgas/1pD6BaL83OkYYMvHzYgELrlGd4Gwv3VFT7SVwBzL3AgftJHVz+jMp9+GXbtt2AnvfzFMgZUHnoGIhpIhYqjl0vbuOxtvpV0Lzs3oPUusOHvsJcywxysbeek0/F713exnL3Ejax4GRW3reZmrSpIBTwTKUFcu5jnHiyD5jm1STx+RfOAWP//XiyygOahme9PnrcHfQAjlj+brHOz43e4k7/HjrEfED+GBVb9uOL880weZpzXDxbsmDWYMAafuVrQIY3njM2ABALpu4/J5vbVdDffruveykDXOZhvW/QHOOh65Jz0X0gIOWnAK6s6lJ5Pj432YtgAeE3RAmYVWIyRICGCaAGSNQRATwQOCsizBbRqwFHtfyK2vs8C6jpkzuigYD2DIJYeRwN+Neh90S8AiAYEBAXnh2EAEXC/+aIAfc6AzXkW/QKLvsN6vanz0lADa7zi6ij8BPsFANFvNUf6GMw3IONgJg+wB2ow5xQ8B6xdP6uqnvwUdh/9QvB8a63TWAhVxaH9/cH5xZ4AgOfaz97OZpttttn+qTYD6LPNNtts/yirk/kWPG/dgdJI7o5x2Sr1ueucVFwI7giTkVMVzEgIEGTcQRCS4A0FrI31BAPsooNfRIWhKhbtK7YCzwaiu7PRJX+94MW9QLDEb0AMgkyMKEDOQCCPmi8VUutmF3heTrjPKbqjaka/t/XSnvLrVrslQnsiW/wpEk5FwfJPgXBndfem8X8DyijYJb32lEV4u1g/Emw5dfiJ5/llTR52+H6fSzZsYBFIBhINwBegXywQYpVEJ2iQSkBQGWsDDBcHB+hyRkrKGAca0NnkZTkzQlRAHai5yr0UiWvuc7CqTGRJKJ5AA/szGCRBWeZBQUsJ+lvKjK7vAOvrwYDHGCOYLdK/6xFBSGkAUVYAlQi01HzwABCXodyDq2mmKwXuNx8S4tKCCc5DGddIzsArd57dIuAUA27QGSObbXtluFtVhVOI3FoyRyDg1J7KrR1nt2/9gZrvwAibAeEWIZyX+xYAr96/LeCnH5dXN3afpwWYZlPqCMszACjM9Xr6WzgjnVYnyOcqQxyXAWmlYDuvThCXHUKojIrFwcGI8Q5UVE2YwTxlllDTB1wq0wM61GHJnCqj3HL+5quM13+8Nga7BkCJKZMAQE5czuG5KoWzMZS07SdR6Gi9Xte3zrRDkrYLFsbhuwMwM4bLjP7CmO6sagwZKACYvjb098ViMWLBbJK1uaAgdbRn92X9BYv+AJEiEIGU1Pt4f3kFPjtDXGogS5aM9Ycr9MslsuTSR72/YQkLalDHdwyhyKgyq5JDsj7Zv43IOWBhag70vkOMurSLVn5hRsoJ6+FS+1M8wUe6wcfrFWrDBrC6LN//6+17MGd0XY/w9i0+Xn7AU+2Uz3ATrh/f8QlW3lXQ1tay0lt7KXv8qDnPT/2ekvHnndOwxghUUjBMo1d2u6mljlVlkxTQvEj8igfNjLzOIwe7A+9/l+1jfT/x4DqHlQpmlfetD4U0vsUCgPv7cOJon5ZJxNjnzbO4IwBkb3d5AE6YzLPadvszN+GHrQli3bG8qIFvJint0tdEFgBFhfHoz5rF2OcW3KAq7qxw2Rih/D539IP6wMmkpUzB9Jlp/uOtMNP9u006ydbXIjqPUosKG7tyGHyOaHNoaIBTXdLWtt5aTW1gn01q2oH0AAUE3/Y90uGh5hdPA1KMiCloQDpXlSAHognAKxAOTk4hHxlM96AYwP2ga2sigBIgEQLCq4OAYUiargkC2LyWBWUup2odsQD+wsA6bSAQpCEhcUIIAWnYWCCMXurN69emusW4/fixRB0JBEPSY4IBnswZ6zWj6zoF62Owa+t88/bTuGfkR5jn+95rddMz+/t3Gh6+dh5T5NltbX/U/CaorHPCRJWuaZ9PAc9dft9nDVMSQ6sgBWBnqo7nBDS0npspeL7vPU2hYaC3BzTnGcduyc75x0tsZq/PNttss/2cNgPos80222y/nU0n8L4Q2b33eHsF0vW38SIHkwVDAc8bJ6oYuK1OXl3A+0LZf89ZnVq3xAggHIWAe1G2oLIxFXhRRiGUmWgXcAY6iy/SpIBz0rDJFU+vCyVlLBKyOeEEYrLPsNzqUh1xDXjuztFvZQTN87blhf0OpgK9gjcsRbLd2enHe9a4QibfPmlGuyLb2+++zGxB86PffP33I8FzFTb06wpkxdVZfE5IGBByUKlpj5o3pjDIANLSh8nkq2ORkmwX/mz9k7OUrp9zLuABBAgk3sm0T3NCNueUBsKEghqTO7lD1FzhIiDr24o0F9dhZegEDckhArq+056YAQqMnAUhAHQRkK8Y+ZoVRKfapuO5MnLjuZ4nXkT4r3nF1VEJgHACAdDjVFlrpSaqJHoxUUltZ7A7AC+Tfcqf1nOzw6bwU2F5koKqPPYsKXuH2dgRBraIIC7PSkBBO4r350sFm69WUNn2tpi3yKtTYKl1E+P4V8BAB2MnOVgOc/AWgJtt7PQyAQWEVwCjgtjZ2xSA9WaNvusBaLqPaBL+Iqg52J1BaM5dd063jH0PFtH2UgGU4iAzpx5Bge/4LhTp5PEd1/4iehKEuKhOPFJAO7Myow76RQki6fq+1FqkCIn6ngsA0vUN+otzxBCQUgbhCGk12EUD4jIgxggRxqLvQe8JArZgA0bmjOEyI9MtPtZQgXHZ7etpPsbRv16PnH0pZaxuBOdnj49W56dnIBDuLy9xeHEBAnDGp7gON+Wd8ZCTVohxymfIdP3V4I2/qwBtMv65BczfyFjy/anWgvA/62vqKbe0A2+0f974LSjS3geuJrIFmO8yB83t82MO3UeGuh9nE0bys5zaDqLvuNeagxtACAqYG8Bb3sWAKhjZtQFoQCYwGhvb/rsvPc6RjFPttPZT1PM3slJd+x4TqRJHCCZLjWZOYf9Qgl5R0544eC6WtgmTNlwxyl/GpgC5TL4TVG1qZpx/X/N5yBQsrztUVno7/gg0TVl7DBEhCKMk25iMD2Uot7k1lYbb7lLBc5ClOQhkwSYm4U6EL12HV32v85J6RVBmiI9tDsLbfwMBb2IEnUYMH9eV1R6CpV0KQIAGAIr+JQoIzGBxFR+CjY7aTUUQQ0TO2RSWPChU++zalHaSqC8hQ3B5c4W+WwDkgZqElDMYghhjydPeStezZFU3EgFnzaPu6Te0RNVnsDdo6aUvtp/mhfg883XtSTP3cj/IsU3fR6zz9nX7BPB8vN945ye/q18AMI/73Ph6VDeM9veUe3uKsGXT9DYvJkjM4Plss802209pM4A+22yzzTbbxDzHeAUjFM/ZvRCo2zWDeGZR4CGQRYRbjkIzBUPMiWDOAM/r1vc9FgcHyiJNWSXfRHM4swHOfrywR+0HBASNaGc2cFoLTUEdbSICkggmVmnkkCEZBj7pX83XZospvxaoWTw+LDH21GVSXWDtYHN9hY1ZYXYF8iCIsfP2k3kN34gR9Am4juPznSleWZxzHnneCXBtj7OVc0Oz3/RzkYnHbrm3R+7M/v6zF5Q18t+ZxQ6Wav3kzMrEZalM9CawxZHP0qpN1rEwVQ0soRiMAa75zgsIgBphT+a/8yYnAPp+gd76CGdjDxcHCRUGewwuJT9ocE3T55SZEuzcCvi7iy92ESkN8HGpAOVLQl7VPu/bnV1OUpnqYxeZ39ctFudLDFcZ1e18gv484stqhSgnZT8AGOjWGDHer+70HiyHvBOLfBgqw1FzWX8mcXmGzeUlXr1/O2JcZBakq8vR8w/LUxCFknoiXaZSrv78AoAgngfkq2TAeVcAAs0ba2x0eP7zWiaX3weAnFKtoYZ9qsydWB1OUZ2oEID6YNKYJjcvMEUMxigQSUSlP0OAvOsqu5zVAZqzMtdDgDLdW+A6Rm2fDcoSiOozL+CJhkCUV44xEUtgFTkTvtzyNmAmJjEKBfld3cSB+9hFxE7bcYhNJyAgdh0+39+rrPuiB87OSpABkyCvFHSLZx3SddJ35iqDwaaQwIixN4cyYf3hz6Jq8JGAI3v++0C363CLw7RAb7L2IELXdV4Vpd1O7b/f/wv/8+e/AQDrYY0gJ4hE6PoF6B0Bl/WaF2cXuLy+3HmeW7rFEYAopwBtM9GfO/w7MO6sJ8IYMH8qcN7mUt91nP/+UzPRW2uc2/6hgIEOpEjdSdB8f8nlGgB9Vx7SrT70sxg9775LGyGqQDhQgoAgMLUkgg1Uui+ZYhIqAOF/qYC3wJE9sQB9NzxUso87AJh9/f4xe0rwy89mvj4YgYOooPkUQG/fV67QwnAQ3ebw37mJfu8+MA1Kmn6fgfOHbTp01XnB+PtD1qqs7QTPHzwWYBYkMDrAxg0GJDx4phbg03hTmvyO5vfaX4L1HRAQoHP7PnYIZfELQAQBGUyV5auCRKGc+Mv9PSgQ+sPDKg9vDPQQAw76A6ScIAJE1rl6BpDTANh8jEVzm3ek51YFLO/TNveVjPUwaGobEPrYgUIA5wSizvwKHTYmQS+ifoBojPtN2gDcjL0BoCEg508l7zkZWA8AWWogso/dAErKpx0Yr1dZ80SnD2tysp3HPdd2H3jKuuZ40tjezB/3mZ/jWKoyXQ29toCd9jplDv0c5nk9ts4pdNPWHMPXG/UENcj4CdZoyjRlGJdl+1pUvn4j98xss80222y/ic0A+myzzTbb97QXrpaqhPgLL4uxo3r3qXRhQcZqrBZA1Mj3lnOIAenSLDyaBY9feAK4McicjCiAtbsZhQEEZUgRgJSz5TUjcE7IDJBHraMupARVIjgEqs5jahiIDCALSHjkQ6UQEKHOyxTtvuB5aMcLwHLFBoUUKDAozb2PK/zpuby+FXhez1eLAwCfIXjzgIvnE2mUed7hABcAE0y9fD8RBcLbhfRDcu2/ktP2OUZUAdIfYR/JctmLuknFMlxmk/xW9nZCyAFAp33E2u9YMg/FPUTRWeQMZRWbBDeFwgjeatNSjlZw048HWW70aMCmAp6KOZgbxtDLEGJlDjs4I6Is+1BzuZfrsyB2HYaNSj06KOkOLhFpVS+BMwArDYzBmbLOp81Qjz5GNme73yVZcMvB2ZkB67bvyHEptmfjL3tCOx/5nojQnZ9t9btdFoImt3DHXlxGu6cTDFcDuqUC5mHZIa8y0lUuZ+zOHUCtXj0xML2M08IIPM4RmTNbrnNnDtnYTwqU56ztrl/0RerQHZMSgsqUChC6DmkYtHwUNUhCgJQHbRJE/kYoQ7DIFIwga6PWrhBQ5NxRwb3MjHSp9x6WsJdUlUV345Wgu1DGVBYBr7g4xAWiueldht6jFkTbcRe6Ubn8nZSGjH7R4fXhq6Ic0HedysavErLocwNpztP+vEe+zFp+aE7zcEGIUfvx+i91PnupPRDpoTcMEeHzhw84/e9/aZ2xoO86HeevBeFi+9gz1oCK81PNix4oKAt+MnHwgKnL60v8cfG+qAt8WD1d4v2l1r5iX/o6EewH3F8qA//9rI5tO/zV4882N2MPcBLthwQAZYy0ft0+0iYtDwHlMwyA5AaIHI1R0qS+8SCWnwk8f0JZ9jHM+YGx2H8j5hL84+PnFC/Z9XnXHEvaffxdR5MDd9gUW//pmu8zzN8pdX4w+rEE4XruZZek9glvActbAF0EgqbtlvdKrfEyd5iASjvb8s/Uvmd7se17jM95vAUsfNZ19Q1m0xFAWydIbI0Kn3fXIJEaYG1vP4KmmYH2GV8DFynpcqzlb2622ywfwzDgC91DOCENuYzxGpxYy6iDUGW8dyEUgFSEIUFA2VPuaEC8sM2fTNEtp4ycVJmKRZCyqgxlEQg0rU8XIhIzuk7Z6Oukec2LC0JqsHwXlHXOoipV0VO7oa6lBXUOqhsIQNJ3mgg6C37KjDIu+HFAGVIQsJ95/KCN8eE6xktVRPqWI4kQEATITwDPge2gdj9sGpg1zXPu97JzLS9Q4sITb2wXceBJ/Y+256T799VycVkjwLrQ+LoefDUO0oL5lsJX+WhG86QXHDvbbLPNNtvPZ3Tx/t08Qs8223c2AiwK+Fd2cfyCJlrzv6J9nfSTsVse2+2B0X+0AN3yaPnxrUNV9yJIAR0cyHZguz3bVlRxs3hxZ5o7DsQAFu9D6jQIxlRUZxoRCkuQhTXvbk4FYCv7hoAuRAgYnAVpGJCGhCEllY1u73rHM3Cghg1UqoyXenPF+emL5UnVTXN7leuFycJuq8YfseKE3H5aRwZifmrQXmk+vDFFgBZEOCsLZ8FqUpgzAVJzDsLzmVFH8lJG+hPt0dnNt5n+lNzYL7TndvPC5mdA5BjO0AKAsFSZ00W/UJZs7BTYbC7CnA0UhTnaYtPFBSnlvQt/AYqahLAyRIKB7A6+OBCup1PHVwVwGrCUpZyToGOOylgLQvRjqixkSglpGJBzUuCOpQAX6tcTyEoQzrU+FEAWxPOIfFVzpbcM3OEqFyn23nKJs7HZw5KUxR60hMw3pbzmZrS+bvsbq7uVfK9XOimfw7IqAwQKRYq9glSCIa8Kaz4sCYGWYFH43AMb3HEKoEiKa/kZYRnQxYjFwQE+/r9PAARhqRLhylC/sfKd6jNcBvRdRBd7rXt7VirlX59tYfwFFJWCKYtjn+PH5dFD8PQcKO0w5QFd7DGkAYtFD5emB1CY7crYlPK9tLFyAUYWxvBBwfNrWpWfjgSIOLGggdPGAa5ljstgADrDAwvcuvMOi26BLMrMj9RhSAM617snZaVzI+fMkhEoouuVVc+cwdA2nFcZuyyeK7v/cHEAYcF6WCOV9jket3eNtbuq/VSO0Z932HwYcBOUq7g81f53fSO2D/DqnSogfPrwAWXWJCdgukWUUwgJMm5H4/z56TkW/QJieej/vPyrXNcZ4t/DCdjKuLfy7j9jkJaDIU826/8kKIAH4HOrpwcQRAq1fTbzk3IOa7MhKiMwhqDzoxggRBjygCHnMq6UlDnN9Xfl9VaAkmsu8Idu9dE9fgKbtt9HXtb8xPa+Kx3O1pwNu9v0Y5d40bLB0QWEH/pcPHCIoktBCzKyZnURnWsEA84iKXs2GqjhfF0N5Mol4MPnGgKTZy6gn+qhVLapf4dKLX3tvTxjrCugWvMdwAujIH6JnvQ8m4B7/nn8vfGpyPbvUxvJqEuJ+3mytf2qnXkUQI7Ga1gNXKVy3AiYK+kIAjoihNjZWKxr1DCRjS7XE52fD+s1QoiIMaLrYlnb1t2sZ3FNqeRl60NEpIAgXhEymu/72E7Qeaa/G3qbm2d7R2UhdF1AFzuEEBFiB4iqVqWcMaSElBLWmwGJE/xyQ2ZV8DB1Oi2fzp82aVPCEVPW9UVKydbdjMPDQ2xSMvU6LdvBgc6X7j59LDVFpEHFfj8C0fcdCIPJyfu8ZdoEWjb65CFsPfuHTMr+/q/qFrzEnjWX2u2yGZnOiYGbJ4w5laHdnLdseph5Xnw6ZlsS55PtW1Lqvi5qwPNHfanmCxHWQNQy1Xew3H1GFoBR2qGpGJQgCnvfzDbbbLPNNpvbzECfbbbZZvuH2r41iAPW7ff9IHr7uUISETJaQFJ7bOu5KNepOzsgVotgy04vggBOAfdcyhqFPpYbLuBac5rqJAiIYEiI4CiI4sxHA/8KwE9tCUZFLQvH1rHyDAfYdwmokd1lYNIo9QcOQ8BYtq01Z5y7XVONTH+p/YyAx0vtR8ZGuZS7dkkFBL2l84qB84DNsEEvfQk0Ie/TDpgHVNaJs7jABeB8KPCIGla6+iSaXOdwgNzl281hUcorljOAS38uwLJJvLdgj48FsNgQCoSICGRAAptChfZbAoClg7iltKNhK68YdK6OOxGgOw8YrnSXvBLEJZW+7rLwYllo/TRts6dRf7MgBgNfw7KGMYVpcIw5//xzcfyZU3hB51jTZfmdQgBxHVNDiOhiV51RpM5AZkEwMHiNK6wBxOXFqORhGQGcW6BAbTfytgLnrlqgoPl47BaRws7JuWHVcEaINR86/Lk0jmMdkzWYicWYliJYLBbgLOhiV8JBdg0vDrwXjdps0gAAIABJREFUp5y0bklS1REiJKy2OmXGnZ35FipPUN89RIRwHu2Zj6FKBRQTGKqOEDtC3y+QOOleoux9d5oPnAxET0DS83Rdp/nQ+x7DOSFdpXL+uAwlMMyDcTKnEaMKo9Lutl1j0C3dQVaABCmg3epGcHZKODsjLMISMUQIFDz/SDrWx7NTXN3c2Ilvinx6a1c3V3h/8W60/f/86//i//37/6u19w0HxiKxbkMTAfhMFaz/jV4nX21tC9b+gvH8pwAXjdSvtV9x8McRj8aknbc1746Wif1bMXW/04u9nfvs7c/7tv/mDZ3snVPbqm5zNqDndG7bcpn3A037G8PU4vN7tGDWbP8U2w5k/jEXlQaQK5u9ACJgMqFwC3QiEQhVafjSZq3AgTTVWQgacOd/fc5W0iwBEO8zgM79AVUkIU+to1b2wfgdoQGeoQS9wvqipjAqtwhmRghskurAkAbNTc4ZBEEkQjIGOECIIYKFsR42erxkdP2i5Cb3rpsl66sGghA7ZZ4z1yBeKEiactJAAAPKYdvdkVAC8Ns73DeQjl6cvolKwO+L7Ae9E5u400ft2evvff6iB8BzLVNVuRlv333SFkAfAefPqsOJI2T0MmmY5uTM87GSQ1mzzLPK2WabbbbZJjYD6LPNNttssz1iT1y4+IIaCsK2ENzY7zp2vOp2Kg6uAJS85f4bYDnKbb9gwLkITDpMPcTMJkM3WmxJAd2lOA8UjIMExKiQPweAk0sEb991g9vXW7YVa8tEndbHU21ndPUTaBIFYHFPuWyjHS7l/hqEz6hgJwAcU0AiBgdCL54LXkFyADi2Gz61enEg3ZmIbT7aXTnRn2MtM2sXS+tZ9hji9PgOP7UpS1EZxGr1PoiUaZ6TAnExxgKI6q7al1BUG7RvDMMGnI2t3cXCcoEHxIhKZ4PEGCfmoIKMHExbvpHGGVIYBTssZ3WgpSQQzuj6vuQtBBG62CFTBmflj42w66Lfrt/jeVNuKMvYcaHclLUv+c8raD4yrqCy+tQEyig3cNxA+7y6tv1OEJYmMxt0rxg6uJysO/UCBZPAduayOfZF68FLMqwEr9/p/UkBrj2Xowe/BHDQ+ogUFAzni4KBETRAAALQMiBfDQWwd6Bfh80q0Q4o8J+tPQST1RcwKERTKRGkNBTpaMmCdMnKmo/KGiysTBEsFn1VCslcriViTdGConISxK7mVbfDrf2oA9XbI8RznIs5EHlr3Jh+P5JrAxmVlT6s9HO5lqkIEM7AVwwsQ3GsbdKmAOBx2eGg7wEAm5QgIugsN3rO6tDtew10CDHg478/4ybcAAF4f/G2BKIEY1dCBEPaYPNhQKZbZcmIvk+9Jl46Jo5Au2vBq7dv9bp9N/qdgQqe7zjWx+Uj0ZQr1pxxwqf4/PkTlqdLrG6U/d++Gx6zXfu227ytP3bMP9F2V4E5gcuPFREojmJYcA41f3cAC1MJ93b7ZMN3UR34J9rXzKN+FxsHenjbpHGI0yTQaMum8uy/6Hxvtt22b4m0Cx/9bkNTAQkftzpPsXea1PHVwyilWcNJM38CdN3axwWizYF2jdkFRC9AIBANJI8IBfz24HPfp62fo8NDODtXGd+ACIGtQ3lf1NQ9ocwFAAOvWTTFj9+fpwQRIA9ru67WWxc6ZcsDSCkjRE1xs16vsegXoBCRckayeTGJzjsBYL1ZW/CArmk8rUxvCixDzmBhJHlYZqLMYRvg3B0BrpTx8HN98Ofvat4HbDr5FSd6wvFtU3sEOG8P2p4XbPuA7EP9lWiihvhEs4qQpn37ufcC5pM+NCuGzjbbbLPNtstmAH222Wab7Xe1ly6kBGhXSXVNtb26qutMGf0u4rl6JzuLAyZjsK98NaeuNEkJHbhSaETP6VnRAc2HRrAc0KhgSrteq9HOJjdtZ4wAKHQgZEgIyNCo+QLMc42wbu/c79Sj/ps7f7BqW3tSnsUnrsoVWzJwck8uso8QvGHCa4yl3G+R8QaEyAImrZPW1TDNhTa1FsD4WqdvC9Q4SPPTM9V3V/d3tTsAS5MFZ+Hm+oJ8KaCLCIQGoCyFbLxD7mQQKU4KAlk+UUZmlaGOnadJUFDU9wOkoaE46DrtJd6EpRlSQgFaxHcwgD2QB84IKHZYrzfoF4sSeANSucu4AGQjoJCNnVDl1H28CI1TKZwHHTkcxG/alEq9047+65B2U104LqBziK0bX0AmAQ9YnuzYFSeQn4BIxyvODIpUwHNYPsbcOIvCmYLeAuD+zw+IyzN9DvaMMrPKaxIhIWNIGgTQ9Qut46ilL7kpzwi80mPiu0WROicyqfrzZsy3MsfOAPtJTsmUskmx63XZpfOJsHhblxaekxbleYwBNs/TzNn2MQY7CAW4L2WyJhRC0EAo1nbPwkhWBgBgXJdj9o0fH8unGxyL+0nHoHHAKbrzKq/fhVjKXLyswlhvNhqwEQIyCzZ/Dli867DoulLWnDLWwwYHbzvgUvB//+tfSCmj6zvklCGSkYaMzQcNbBC6dVGHAp6L38szB5u2vs/4GAfvFoihQ8ven9qJ1fUueU9nqd8SgOurUbf2Knwj+vU57wPCNiA+Pbz9zRnpv6c186PJv9ZahlQbsKiqIFRAkXYcUjavsQuNmRcax3INEHwEMEA7+u2Zz/xi9i3u4KvP8fs26gfM3uGl9lomIJVczyEo+Ne2e0Kd+5azTYJgd7fN3YDOz2jH0DnfbNv22LDzPYallzBTx0ChMtO9lXo6ARJBZkEgMSWQ8bEiOs+Ilgucmr5QRneb3ypJm8p0l+xlQOy51XUj2X7w4E6p63kvV4yxrCEimlQVBGOFDyAEDHmDjjrEEDCkhEAB67y2NQpD2NYEvjYAEG2iXvKad11hpb86ONDUN5xsne3qUVy6ayj15ApW+sKbBum376tdNpIpfxKSPDnh3/T6KzjvgzeH5wHjj9kT71UmY/Jj+4zLs1+y/dG5BtUiOjju/hp/r+yVcW/A9BlDn2222WabbWozgD7bbLPN9lvby1YArSurgcsm+4SJA14aENddBKOfbRE/WRAJUNACATKqfB0RkIWLBPUxAXciCEJgUra5ERct0p2NhY4RcAVRWI3AaJOUExTYcRm8wa4v5kQQEiOgevkat1wTKR1gRJfifHiBFSfJGMorpSV3obdwaf3Gwlomu8XKMqj7fm7z0rsR4aMwJOrWYwZ6AEdWjo+lGmmPsPf4nAIUUOprwG/P9X1sYMxTcrX9cJPHHTPfyxJuIBBEnFpR6nNIlxn92w7DMGiualTZw7brOVtDQfSs+c+NYSKWU5o3AFFE13cQYUjgEjii3SyYw06degowaolCDCoZKePyUbQew2L5zIE0JBy+PlSwFwEpa97EYRgwpAGvXr1WsJdZmfELgHIEF7a2lxuAFJ4MNMfjpDM0Ty2exwLkC1Byj1c7RtvvaKmsmxjjaBwrwL+PXZ47r3FI6ngTYFgsAAWKY9CxVAFXBss18kqQoQ5LAIgBiEGQueYQz5mRzd/TxWj53Y3F7UFIxQmlbPnhMqG/6KAhTkBeGXgGUkflAPR9X8Ybz4nOxuAJIRYgY7FYoO97fKJ7HPaHYMkGtk/fHhVML2C8RTewJXzWwACvP0HXBQxDDeVhFgR7M3lbSjnhy+WljjNNu/axY9f4cyJAtzxHXiXc0G0pqe87DRRyeeshZxDMgf12YYEmytLfXCZgqSkCuvOIlDJiHzU3rz2Hhcmu/uvtH0hDQowd1us1NlcbvHp3qKoDJOAGKinu9W8EFi/e9oixA1hMah5Yfx6AAJyeEm5uZGedTQMRbp9QmOeA529k+1m9kfGcY/r7P4V5vg88396nOn4DjecNBIzmXd6m679giiSTedkec4bjCKCc2ed/F4by25nPrENw6fYqJV3mMbXxjY6tbXD6NLafjuze/NPZDJ5v2xZpdPIcf9hQ9ASUzeM2R9tQZ6EsupbVuS2QQbbmRV16lnVnnWtXdjrKby6ZXfOpU1kLQhg8cEk5oy8KGp3Cv3z8cq+BoH2HPgIhBhCTT6l1J1HVNw0K3SAxY5O/IOeMlAYIi6aGAgAJCAEgV4sT2DvDQEtmHPSH2KQBDNbjxSTwA9m8UYNdVTlFb7iwr61CNfCSMOTNEx6eBQNsOTikNKAHm5H8wHY2NV+XP+X6+/Zp7/uhfZ4TKNCc04NPRz/vY3rvAMmfO59oA01qgEVVHqtKJg+D57N0+2yzzTbbbPtsBtBnm2222X5HE6Bxob7g4Cb6vQG+JpB4WSA5oDYFmrfyce9YD7VXIwPe29OQL34A3DCDgst6BVCwvxq+XxaTCiCbM1ma5ZAIHFdS+TpbjpvUsrIMCSIZwgBHBjIXWXMmMnC+Wag1Uf6lLpq6a8kxdYHX1tO4nqd1+2gFtnVoIOAuEvr0+2uhAqi3ZbqB4Fic2d8C9Dv8DDvOLIAJIANHPJZkf8xa1nnrNDzecT9PtkcPfLkHxJv83+FDKT4zcUjx1lreKQBlvSIKNus1+kWvfanJxS1soAdr7sKcsnmieHQ/6vzKGNYKXMOcc0wOptp5zalWlCAMSHVnhcZ3UOnPIQSVg5SqOPHx40ccHh6CKGieRNNCODg4QM7KaNF7VSdHNKlH9YHFIsMIKMtbmS/Gdueaj9IZ9YD1WXfUAaBzz10uI8dnvlJp8hiigqixs32mT79EnIyUNFiq3LWOGVScOrYFKeciBd+cyU53gxDeInMu95yuskmwA0y63Vn8rROJLR8kUcDioke6ynbdG5ClAQgxIBtIjKatEBEQLb0FXKrUwqOEkbMy3DObesee3uDS5inlcn6X/f+y+YLDxaE5uuoYKZIBhPrZBqHoeS6tJNMr7gJvL5bncInOzdUlAk6wPFsira5GgPCtjUGCa8jVKfrzTstq7QFskvuk9xCI0F2opP3h+74EpSQeRs82hIAhreHSkZu0QZaMeN4V1pSIBm1NgWMB8IZlJ9D8VDsSIIaIIQ0IIHy5vCr1dHZGCAE4WxKEgZubcY0+ds1p6o7ngtv79v9VQfI3TfW99B6a7rtlUwevOn6Nnds4gFtnNQGFdRhoItfeAO7iHvNdL/vCPNwuWXV4y9a1fzl7adF/ATD2ZzRp5tSAB3joe1hBdKrvbArWQp8HsLRwWFG/+QG2jz0+s8q/zkaPXl7QZZ87Pj2we8UAJ2s/+OSUmvLqO54MfPUUZBpopwGUHvQ0DjTXEzAIiapcut87BUKApg2KsUMMhFCCKu26TKayplpuEQQJVWXH84YLM4QySDRYUsjm6rafBkOyBmtHVSTinJE5gbOmj9IAQ3+LCWDB6KPs7jZf3wwDWBix6zVoflCgPAQD+UUD6WHz29AEb3lQTUrZzkqob6EnPEbzAYhXZFPk/Q/8kd+/p32r1+r+ycXue3vq/e7y8XznKINdfhINbg26jvEgQpsbhVDB8gKeB1X32tWXZ5ttttlmm81tBtBnm2222X5LMyfoS45sgKXp99HaShHjAqhgtGy1z3WVa1ul/rzjWmUpu+03AEEQESEsOAqEzwaic2CQ0GjB41KkEe6IEwVffOEPi/oP6nAIICAEhMjoQGAJEKW/l3zsKiFsQIc5RhwM9EU4Jg4PX5jvAtEfCx2fLgpLPRTZ7IlMZRuKQDC2JtBRpbtmAxQB4D4AryTg3h3eTd19spO8AeGElc37cTf9vB4p4/MA2+CBt8q2lVDzeZ/dUWWiBygP4TEWJE0+7K/up5Rgt9W2+ePtFoIjEWTTTdYczoRMNyA5AVYMLAHmNXIeELsF+q5T9ndzq1OQt302DviyuaUyK/s8szq0JQpEAogDECtYTkHzlQOkzrgGiHYmsjPfAwV9qB0QEcFZJeSD0SjbQBIxcL9xnyFYrkMCaZ5Ha2Ac2Zx6xogOUpg3gaI6T6I645M58JzxIh5o0/TrxVvNORmj5oWnoNLjbExeCsGCBrSzJyuz5zNfdF0DEmh+SIFKWFYg/Rb9+RIAsLlaVWULAMOlIFwkZeiT9u6wBNLqEoRTxGUEhJDBBs4L8mXLpmcIMjLd4vDde2w+JBCWiOcRhIa5k7TO+m6h+S3tecbYWd5Jk1AnZcxzZnQxYJMG9DFuO7MMi4tddKREnbCQIt1xuDgszlRvfMo+DxjSxoJ5CJHG4xkgiDgDGtn2qR0LsDg/L+oFw2plYO8tcA2cL5c4t4LmVQaPpNxr8IU7bVkE+YoRLS967ALSZUZ3EZFSUoyf7LlaW2cRbNKAvGII3SLIKeJ5QLb0ARkZ8TxsAaMf7b0hspsZ/lQ7EuDN2wuVR036fF6/vcAiM9JVhqxuQWeaDx4E8AkQbuvxxwIEOUWmm1IOas79rfM1u5T7VNLdg6t+ttzn+1IFfOsy7mNGkbEMAwVzBE+PQ0HQa+7PhnW1Y/+n8rCcfd6GsjzluJe/dWf7HvazPIfCAiSM2OeFjQ5vyr6m2AOIT+fb2P39e9mx/d0Hkn89eP6zPLFf156DkT22b6vu4TYF0YH6PteFkALnAQBz0LRLIF3P2kqJJu/bzBkY6srJ/98hAlHfATEE9H0soKBeWOebGxEktnWu5UMXK5iAS+Cpvid0TpYheHOwAEjns66+I8xASsg569zT1OLYAtD1XjMYpq4EW39TKMGtCp5r8OWn+092z4RsClSSpXkXBasVA/EBpE0qgZRa5/5AJg+odUcAyNPg9TI1l+2uNQWVX9T1vqK/7mp7Lz3dvhcvTT/bTT/1OpM6eox53vwAAJa//tuPaa7W4GVsmeYt87yVd/fy/tMVdWabbbbZZtu2GUCfbbbZZpvtWbY7QHk3QF7XLTLa18FeTLYXSHXHwkXx7AxCwJ0wjijg3he7pNH11Sms5yOQLczstGyACAEkgsiAUICAEaRG8CcJyjQMEZmz5oDLem2BMlbLvREpGNQA5k+1F/FgWtR53/lE4TJlo7LlzAOIAjY5lf3vIXhlitufd1zmEwSv91/uUZvmqSUoIOhM89YCqnxy+1uVkK/5gH3fbw3c/Gr2kYDTBsQvTiS6BeQMvGKEZUDKjMxr5DSg7xclCEMd07GkMGAOSMOmOKXNhVeks2HXcFAwc1Y5dWMXh2jsxqbHO6ziDglmKc48SJWRBxqnC/nnNg9eBfVLyvUC2FjuXqX0wNkkIcaaDJ2oyKFDVJJSGe1AH4I5AZ09k5HBmh84qMs+hIgYQy1jKWp1uHRdj5xSuZZAQF0cldVNGUPVeUkhoO/OS936aOjtnQF8+XAFiKA7X6LrOiTxfW6A1VlxNNIy2NUrgC64QcApCGdY/7VGWOoSQCxAJq8y4jIirzK68wjmhBD6Wl7AWPf6hbMgp2TMKQJfZeDd7mVFaJzHbT0EHzsbx1W5nrWXvusxpA2EBTFGrP8a9Njlduc/FmBhTPPCzicgXTFu6LreSGNX1ysAxtDGKQgncEn7jGuk1SkIAd0FIQbC+kNGXJo0aqwnGy61XIw7DcrAiT4DugPhGIy70m4T3YBXtSwkJ8hXufSVrwHLd9lHAuKHDcK7iC524MwYWAMeuncB9x+A1c2N1sGScEYEF7c/EQXWmW4Q5QzHuC7j7omcgHH7wJV328kp4XbCcm/NwfNd9+G//yx2tMPH/O2B8/2AtrfVUIBGTx3Bk70wdhSXs8L85A0A4f2R2uPqWPW724vvcPfk+B9hXzMfOxbgY/Pd5/HBFD4IrhhDozoeAectIOYKLP7d27bUXb2dfy8r7/bZZgNq46Nm/SsCMCEHBdF9DRuaMdpV30pTZZ/XVeBRg1BDGct1HisIxtoWm9eq2lTWOWoXECFgIhwJ4RNUNUrnv1q+EAhD0rl8sjn+kJMFxSoYnnNlrms6IrI5eFbp9aRzfWYF5hkRmTclxZF4UKvlNdI+XVcPgYLWTTvtFt0vt7j3Mx/HVvD+zqizp5znO78SnzNGPfb+edZ49wB4vus6T6qD/c6LrwHPp2B3WZP5fyWfnc9pKljeBmy155ttttlmm222XTYD6LPNNttss+20JzHRG3k4/6OM1rHzdmw1z+1YEr4CZrsWMJkBIgEJgyjizgCuYw74ZCtsXWw74FWj700lzxZ+YsUjlc/LDESTzoOCzD0xElSuPYQA5qz5nDM3cpPUlJpgFPVyzW/nbLZ7MKqAmPdvh7rf6BCBMs4ZQMoZr/sFQIS+W0AEGFIGi+Ce1BnySghfGvlgP/3nhvH+cDG392uBhBYQcUl2BwZbQL0KaOu/KbvPgfQOCh4/JR9vW7wH9njaiXYctevIxx/9t/G63BhecmZdLsrp6Py8UiZvPNc8grJZKxBqoG3sIjwvXNdFQIDNsK735GxhAEB1NHhLyZzAiSFREIuP2+EeLo7qCpQbrFsUFOw/cqlxB29ggTEYOWxCDEhDKkBRIOvHXkIDezy3oTLSW+8ICmCURYNjCMGY7IL1F00T4TLhRIS+X9SHzOoMlGxS3sEDA2zcs/N7EI/wBCC2+qycGmXDFBlvFpPYtOc5LjYSgFfmzOy7gPjuLb4YqAwAi3cdUmIMqysQFPy1FgKBoD9XZpKwIF0lZFxbGz5DXimbPl1l8BLYpIQ+RmPsK9gOZ5nbd4Hea3cRS550Ec3JzmKMqtCBsyhrnysgyFkQYs19XpQG4GOc5ZsPmiOc7PeEFeLqTEFxqnnNQ9BzpasEQJBXDA9TaMeRXYxh/X5Tfg84Rb88t3YmSMbmf/V+AQD48ucGGTdbvbiOXRVYZtyNrnfUjFtHAoBumzJ8H7uhO7zCIQDgy7DB1Y0GFFycLfH63TvcfvhTr3+td3QsQJQzXIfrUk4hxvH7/8YxgH//9T9g3G7df2v7mNm3N1L60z42+ScifWc8oU72XedBpvpXjs/+Ptu315GNOS99pn7r/k/fiz63aJ3FGiPk4LkG+Yzx83oey/3pAOXonKP/lTGLbD5GDlb+k5zLz73VJ7bX39G+Jpjxjuo7wd/ZZBLuFAgUUNVt7BhX96gKCDbuctsjKxjn6QVk/PN3s5vHd5ntF7YXg2yucmSzBBJCEJNIByH4QpU0XHt6HbGc48dC+KgDPxAaIBjWR9jm1AZ0s6VqSsYYFwgkMgIibk2dh5mBBkBnBqgDKAObQQNIg+g510Oy84qez+b3webfQ9Y5WN8tECgg5QSIYMgbsACB9QWlCm+MlDU8mk3CXpe5Wq4MXT+Awmiuv7P7Th6LM80b8aftIXofIPwAIL1/fVd/OBIgiq6Crp/bXJ46b2ldMLvKtO1+efw6j42L7XvuUbdAA16X2YZV7QtZ3lt9YuIzKnOn4O8PXwNRKco05/mWgsR3j4yYbbbZZpvtV7QZQJ9tttlmm+1B2ydltWttqfs+vFJ8ijDo/kWVAtU5a3Q7QsAtMk5zwC0BwaLXSbiUY7yulGaDGLCmEfQUGCAFlyBAUbpmRgco+BiBIIzMxskt0qUoC/MnLbmsnM9an1m59x7jTsQ9heDG0eiLxECExNXBeGA3cr/jET15oWv7tTK8HU7w6u0rCDRnMkEdGy42ewBBus7IuGm4FdUcXJ9gqU+v7+9kBJQmNbUfBaBX5qC7bE8nvwOEjHTFCOcBWUzJgVQqMrEysWOn+Q4RNLd55lRLKd5mWNUcDEhnD4URQcqptBHNTU5bpSidhM19KC7lDgX0vV2G6il3xW4H32PskBMXB4d4fyYxyD7X7e3V7TmNmQYoYDrZhq6PyIns9CY96WWTHf1AqjO/zT8s0DEjFueN34cYa1vlNkFUQFphlcjMq2vEJSGtxgEtBAXUU06IoSsVc/i2w5AYaZXx5U9BdxEBOUXGNfrlOXgl6N922HwYMFxmxGWt/265xEF/gPs/7w1uuAFwCpKAfMWQpaDvBF3Xq8PLAgdiFxEjYb0eIBAEy3HplnJC3y+K9Hlxavlz9aHYwT6yMZEZLGIpAKy+SfPdI2ccvOvR8wVEgHd0AWbBwcEh1us1hg+MBGWUe1COP+67drAQZ1aPgW7fT+V1b3B8BRy8fWvgftsOUViM+/yu03O2O96hfhdpQNYHhoSvlZMkInz5c43XfxyO3sHpKqF/3+FExsFIdwScCeGPi/f4z+WfiDgdle+Ul+guAr5cXeLklJCv5UXM64eOeer5vmfgwd9lD93SSOmmYVC5oghENAVNcy53X/sY5SA6ioRp8171bSEogO5/v8+t/u02u8l/rD3OVm/TC9Dope1zBWfBlmCzloGO8di8b+wU1J1+17Y92277mjig54DnO1XGpGo0aeAoF+U0tuBsAoGhc1yD9uz/PmGugF8gU2gorPAMw6ftuzLLM2f9TQRgDawtayo7Vlj7lvdBZkYmLqA754xcrqFBo0XS3crFkst5c05IWhFIzEg565zQ5Hhy1oBVV0vylGq5BNh6pU/m0ZO/2/Xux9n/pkzz6URt3/YX2khh7UXnrDSDH2KPXWbXHPUrivZU8Hyn72mHWtXou/1PU4A02j1U9x+D5y+5g9lmm2222f6JRhfv383rxtlm+85GgElyzbO0H2qiNf8rmk/uX2QCBGkWDS8rQUMoltHfcpmG9VEuDLZI9Dz1e8GdAvpx9wLo0fzgVB1r1C6QSHOAxqAAeCDN7RYpwgTgLLqeDfDSv4E0bzLMCdF1HSigOANYMlJWqWqGsm2zaB46ZnM4iJi0+PZSV9zRB2kcDMbG5d31unXLmNbV7nVru9iW0f7ueNG/C8sZzSzoja1GRJBhwGdzWbwW4HNz2Vei+eTvyNkPKNfZB168sfuLAA4v3mHRL5TFX9oWFYdN5gzO6pQZVgMybnYG1vvfT6ROWAVM9Ro3f8PwWkaYB4Gvx87y8mnYriAMd9x0cgKgBhk4Ezks27xvKOCL7wsKxaGWnSXSODsoBAU7vd3AMRxVfAgxIoaAru8NfFYHdzBnXEmjIFLYMerPMydiIGMeezvlOtY4fbmpOpeP//LlHgCw6Be1VhvcHvAyo/yl0Y1bH3Hvy+S5KCNOLEe7gHOpJUMRAAAgAElEQVQq919RfEw66HhMENHgn8ys0puBSj1mVvZ2CDoArT9cQV2cahnAyR/vcL/eQEQ0pzoUpOcGvM88bU/1XuocpDrneNXC2y6NXnsfr9QVGs9VtryLHVxmU51P7Tt2PKZRiCWwwIMiOFdZUQ8+IQIk6zg55IR0mSFgdMsOB4sDTQ0ABd0567UzG+uJLS/5KoFxizuqqSAIJ4AB5A/1Mv9t11h2cX6hju0sJUd6xClyA7xPwaBRCor/n703XW8cV9oE3wBISd4ky8469U33n7nUvtV55unp71SlLct2piWRQMyPiABAipLlJTOrTjGqnBJFEBuxBOKN5QALMi8A+NcA4NLK8s3Us6y5vV4CALarFWbLJc5mM2x3O7zcfT0Iai3iAtVNhXAfcf77GbbNBrvVPRjA7LdrAEAIazMyAgCs7g7t4a9W+OSmDVmYW9gQRr5X/lbuK9/0x+Mx1blTlr3bci+y+3L9gY1IJ4WB1QTZ2xwAl9xYS7qs9ONQeY+qqlBV8gkApTZLCu1QjIXs5tSWPAmDEQloQkAbZZ1qOSKmuLe8x68woGBmTG5Yy7JObvqbUn8udcGW/euT89lbe//6lEHkn39eMu8zUEtBEJL3l8o7eF/Be4/KOXjy+cEYhG/Ucdm2rYxR5GXS+HELOZP5dL3PnW36g+eltyk4dYBBnDre/n5j693Uwzrte/e6kKnw/v196p2j3NtkMv2krz7bYyGzq3BK59hOvqViE0qenAbaDjgSJdWlr1A7j++VWoiTS6G7MngeBdQOdm5lSGho4cuIZLtg1WbkKF6SanLwLu8rRMqDgdEGObM5Eh40RDnXisMyRhs5eQxiEnfrbWAELr1YCS5e2iXbma7RUGPReOiiA4bmTuyv3f35GHPfmeJs9x0dn1/Mhz3dzBlw+viD6+bDQOKXj5bQz7dXvz1X8wcyO7iWFMPv+IMDVXPFmWb/aNRNuz9RYF4LTyhquGo9xf9DAHrndx3b3le5L/rpirk2lMcYA32kkUYaaaQ+jRboI4000kj/8fR2wdCQcOC4Jbqd9izyX9awz+nyoeVQWUSk2u996Envl0IvkGruOzgHnLNDxYxvHMGOEQwMo1iAPCIBcBbL3LIqzqaUTtfSFucjmNVC1HkRFhswaOgP4smnQgEBP/9glkDGA6+7BA8AudiFmAQKjjkl+E7ATKuY3igBV0zJJZ7ld0ioYNbnjwS4ux38vypUdcF2kIAC7AAPn6yJ6kmN3bZC89CA8QiHKzCeOvKEC+62J6IEME7vs0+hX3jGHjrfZ3f4jwDme9UTQBQACG7pEFcB/kbdlUPmnYDMfdAVHSC6LD/FHycd397iG3JGrDsllBkWEpmyKB0PpiQTY9BwChnI8d6LNwqS0ASg3uug4rMQ3PWVg/aFQwOuM3WOkxPL/RAE3PfOd+dcIZDrCPpSfwLMa+zuGZPbZSpHlA26/dqHMx7//SdI18dwu0Rzt+qU4ZfXCKsHUM8Lgb1rZgPMcwxxc7Pul5RAcQGkgz4p74h17leesiBV/eszgMiha4lPBAoRVTXJYEbkJFCz/iYAHIFts0sAtXXjbgX4336DZ6/KN0ATGuy+tlkBAGs4zDvgucc1Ah5SfO4yRET5XXYs6at4wOnu9u4O9XIJIofqtgLzDcJ9PGpBeYpF9J789mjiz1tk7h5WuFlc4+LLLbyrwADqqsaOrwGLE9+jtVtjwYS1Y/iGMK1naDDHMz2qU3hkxbMIrFc/Z1Ecdv0un2XIEAO+LXn//ZyyZxDyvmN7W/nYj953hrMvlaEIYrvn4A2Q1AepAAhNeW0oXybh21qKKjQv3JsSDddBrd0JlACTkUZ6D3XHqGKN5Q8AwIwYOSl1xKD7zmCOB34dh+k/nD6mYH4S8H5wjLH9L/wqG0CeXa47yNqbkd7ML6Q54rpKsGJ9LjyZ8GUa01ytzxmqsArjmyDPxOx9hFV5yxQ8GkQQIiITQohwDrld6kVJQH+H6CMqpnQUZuj5WMOIxXRuUP5PeXWvQYpsX4o6vxNLbsr1Rzilk6czHfg+lK7HoB0Dz1OXfCYP8LPOsa913gEg/l10QIZ0jF41MOgYVZQAOgrX7SONNNJII430OTRaoI800k8gEdJSVwhwwjN/l8nZr+vPxq8OUgp6XdKP7tnPaf1nWKDbcfvNZRfa75pd+mKxadNxNuFPXFy0YIRO0ekrFfWiMokhKdliG9gXdGXBmisOTVpntVxxBEDveyJ48iJQJgJFiBW6AmTM2Y04MWEymcB7L4f9KO6qYwwILPGSQxT3y00UoYTdYzvwFwBeaU3P4KT5X17DhBXMcJTEKL33sf/N+iKVBYtLPzC2kwW6UEUeNYDW5dkQImPqKzgibNsWDQfMVRrQpmdNkGNCGwH42hgPW6EzkjVdfb3E2fQM9aTuvEv7wlHi6YkSBWO32+Hl6wbJdABIQLr9ydra7Z3IH4vH+TbiFLP9YIpXl5v3rUeseQ893QUIJbHDHHlNKBHjbJWe6kvmNQXp/XjnwRzRRnM/DhWIAM5rPuRR1ZVakFfiUtgL6A2zAgtiqehIY7KrC1ZWN5boCEQMlBOr5aqq0TZNp9fatoGDQ4wBk+lU3UpSxzuF0XazEQtNQoo1bko7vvJIAdeT5F4FlnsmKzrbNI+mbVA5j/JtiJCSwdre9l7idTcxK9t4AH4JeL9MwLXdtHjwYfWQxntEtuqplgSiBZjXcO4aL3erwXGSx+dChJ1LmTFmWc6I8MsKVeWw+3MHgFB/qeDI4fuff8BjierGyTpxH+FvpF8nvlKBLKc+ilxYqRbWHY7EmtAEp+WgZR10bWiw/bNBxEPn/RrgffnlXwCAb3/+YVvFAXnoHKyxuct16aoo00FWFVsnLtP7uEbEw/76ode/f/lXevtN2+L+4R5XTJ30JmhNzTxhLSrB/T1Ke8b7KAnY9/gJyfG3m1tUzmPXtGhphfXDfkmXDExub0BuhfuvjDkv8EiicDBf6Nx3wMMR4Nz65QKvgc20d9XnLz+Lg5P9SfKMWq/9qr21tA9sPgct0IW36aezda7yFeqqUit0sdr1ziXeCMBxnb1CKS6CsY0tduopQ7ztRFmry83Mnik9icQ4kPk7u6L4fso7/4wxsQeAvPFV/p0s0MuaclqofgzjdCjXBNp59WSim1XlvFqge3hfoXIueZJiA8+DuqMOMSvVFe1K+285TtFxzNA527yl7d3xOHxWeY3KunYy3q/dz6FfOXQPTPD+/t693rdAP/Z8/2nn9/fEYyPg5OM4733Zv1JvH1aqsNL5nGbXXU8h8s3pmm78daXrv7M93vgFlrMqB07KjbA5UZwUvStPd/mLZefhO9b6wuXa86KyxShCHMWAECJ2HICoHoLAaBEBOD0x5ZZXXvjJXZBzQEAY7PjOXC5u244z5H1NNnataXEmKvQSTpq3xrtccuYdn6kbisKA9Cfaf+9HLdCH2bLuJZXyhNfru5c/y3gqe4hOzavgIV5N2rMAB1QBnxmxAM9P5uF6L6dvJT4Ennfcs1M+w/JAPkMW6GWa0QJ9pJFGGmmkPvnzi4v/9asrMdJI/+lkAsy3aDz/NPznE+iDMqcfSEM1s9944P6PKPOduXwEQE/1yAfyt5VtoFEpUMya6x1wPR0Wi8/ypKpfkhM6ApKUrASoND1rFkPnlgz5le+xcHfHSJawIhAXYMelmHKAWVHJwcoV4JgKB5zGgUZ54LLjHhXCOIhwQE622YqgPD+WlYZiczbsqLi2Ay2V7erl0/umTSl6Ibd7n7rjgJhQQQQ4Vp2KXMc6wZNDrW19JkZdrF5ZoKN9AkYNYAqgBtAUlWgIqLUPwmaD8M2BpqQxsi3IfD74mttucgRfedTnFdzMIXwPYI1M3Gnzgb6qAew+MH0uuNuOQ0TF31+JdgRM9LuNS8IU/dljFDcAvzBoBsQVI74A/kzdKbLEtiYw+oB0mrQGdoPhnE8x0EvBW7JGB2XgmruxE53LQg+VA3Ys4ffcGILhnVihB46oq4m6godaQgNEDqFt0TYNnMv1YmZUdYXSDT55Jy7aYXPZYl+zCqEEJEldoM8l4WUpVlehWXMfEDePSTGhFCJFALxhhO8voOkU7f0K8WWD8LIBbzaIm03Z0533xhugujhH5S8AAvxshvCyQUndlXILYIP48h38MoVbOtAMoJmEvyByqM496ExjagKozi+AmQpSHYHOXKp/5evUCQxzKdotO0aGc4QIRoxBYikn4RXKbUD6ehIRNi+ddu5I/vy3GuF7A8Y2PV5hCWCqY3sLBqX7fTB6UnwnyC40KfLfEVBjgwrXqLDprh/6/dv3b/DfPKqLCpWvcHlxCZpN8fLy0qlv8Uj6MucrnPE5zq/PcDabYfoyxYa2nbp9ZM06RLbvHeInvr+8YFpPACJUdI56usF2202zI2B2tpFx8A0AptjRFvNrQlUBzgOr+8PCxtJF+hS534/U+MDV5661E2QFrOf+e3s3fV4ONk4JFgIh5524GiJ478R9b+X0u7jcdc6D1K0vueKPXF6bifK81N+CWjEaPyBLIHfHUA/wKQXzH/k71h8/nD462P7m8vYuz/txGubV9s9eeSwiKVw55+D1L/HqyGF/oiqviWJqBqT7JxIAnftlLbiTsMsnD9W0YN+P3n83/dUYyZ9FB9rd34K7131edP+5wzuJeuj4EQB6n/prQmbIDywX+wVR5+fC6hzQtRswFWpR+mZIOLXi1KxrPwA1brf5RvnsbNmSsQyyd6T66lkgg8+k9aH0rJQsdQkxA99JcUUVwSysj8VwjzGCqQsyZwt7yXwI0Dy45PYmqeVTnptPJeNVZhCPajsSwJwAbAu+hjXtJZ/Ayx3b8Iba8VHq5fMWJ3ineFwYct1uv5ts4UBVjmSqpws7kFEx79P47PIxLvE4xYseAMft92MA+kgjjTTSSCP1aXThPtJIP5Gyzm75m16bcF2vuXfdv7933c/vwDXekPbUsvt13bca/kWMKPValCrWPznkQ+bHr4dOy++kN2u/5rI4vSj5eG9LEpCUXK5lIKnzhEmizMd6oe1sh+vu+D80MrMFNqdKyJe+dRBzdi8uRap1CgBHAgKzjwjs01hwzNkyVQXC0eKhOwc4ylaVdnh3JG7pOMCLFAHOBAIxWvC4dELPfUko7cktv1iYDffjbfV7pCs4kZZml3bIoB6GR98QRTBeOOKMPXaACDFYLAtadcvnQdh5jzZGzCK0Tym9IQDJcr88nIZcMwDqRteeY0aDNfhPRrwNqOoadV1326wHWXJihe4mEzjvwTfA7n6R3CybW/f+emNfPUTAYTGkS8+Duagr/ewHGxBa9OZfUACfiz7QKoPA6M+hb73u+VGW6PlJ6tThqZAfyHt4TDKbUhDseG4QKOIq20moegjae7FUppti3ElxSRbIpkRCQNu04Mio6joVlj1XyHPOOX3WgWOb5pu5/zbgnCMn4brFU3eOoPbxaJoGIBawqPVodjt5PiIL5XSe+8qnGRnVoj20YpnThEZARAbq6RSscX9R9KE1vqq8xF+NQVxmhlbB8pjXDNaSYoRbPCE8MCY31wKY393LOoBu3u1qjc76t7ca2HuRb5Mloa482lbjwN4/YHJzjXD/gAd99Krb7el54AG8AgjX8De+sxqHEOEqGeFtkDY65/Dy9U94uoFXC/btbitghwplI9o8CouJGYK43mdIf2dLKRkXkSPqqgYRoao8WuR5TtqG2Zcv2P3Z4AGPyVr78rff8e2PPwBiPFIe/ZflANV+k9/y+mXfHIBLZgVPSa2KHuAwxyU/6e+c2rLgBQDC9o8tJr/V+bUUk7u/Fv/Xl9/T2vnt3y9oVhGePaa/1bhpFwiriOrGgxm4AeN+3XWjzgPf37OfX0burAllXe8eVriOC+DGYeKWAN917gNADPLDMxjAGlcReDzRVfu3skzOsce77cycQll2ybX1r8tY8291oW4u2J96nXW4Ra+1td/rb6cyh6HZb0o98kN3zKWfAcARnPOZJ+F+fpzyMKvprkWkCZaLcAyq1TTUOoLwB7IO7nvRKYs88kPKi43HIXTD9pzK5LybuPj3R5f1c6mzjgy9HuPvEx1eVWjgPg/cF7a4/3yZP+sem71eCV8ie7wdLJm1flwA5yF/N38NpRVq9slE6Yxg5fWW7AHesHtvaGYbp3Ro1r+2Nh8s8GcNul8wtvvTd+j6LbS31Rc3ji0V5fm1fC+nHrkTnzdUl4M/9G4Vi4yN1Rw+jJK+ko2y5Fqd7HmWo2mMaIngEOE4ewEiTYNi/SaCKL3HPFv3fIaYsYcy9zHxQJqexZuUc8JBMcs+UylPzwQwidt2kJzjgs5bOKByBHIC8gdm7GLs7vxpHx5apDjxv8VPBwZOd9NjYfmx0M+Wjnj8QbY6n2thjwQ8loc5zn13ycAjpYrjuWjHydTnP14dYAfotUnUK+etc26vuAPAORggJ8p4NoZtP+/UtZirKayevtOhNTUVV/IlJGU5G7uWNxW7z6F6Ik2Tblmj9flII4000kgDNALoI430E8gOO53r3v3y8Pae673yjly/Je1762b0Fqv7H0OHjutDvfLWnjx2/bF2v49514N2r3gump2EpEPXxYElxSsjJGw4HWgpnR97LzudbPRfE2gVvx8QnHcqpdaPpSU7a61MvGbCsFBYxwIMchL/M+pJnEMEESMwwWls0EAOngjOV+Ie1Yn7O8dihR1ClIOYeZQkCBhPEaI9zwXAF8FtBFhjhpLEQy7kM50+LA+LJuAwoYkJrZNleB+UySdBZBeuOc8Bw//BQ7JZjhMzJgnMYiBGVGDsyCGoAkLlPCi2YADftYBza4NVI1WL4CGAlwkmvuunxZ8V939PeLl/Qr2Q+M91LUAUM4MDq3CmSuPNe4/JdAL/m0fTVmCOaB/aFPe4BMf7w6t0r273HK5MXKVps1V2OVq5l5tLv++DESWAbk+VMXjTgzgWH/ntc55TPYdzsOvn4j2kNTulkVjpXSUDRryPII2TLfGxewWQCTyo0ymRAyiKpRg4u3eMEEGZI8ox01kA8thGuMoJYA4ZSxL/nJLVjMVDTzVkRl3XEkohAFVl6w3DJlFoG7i6Alggd7FwUcmXCuNCCKJp4QEmcQ/rIHUi9UZhoC9HRqAIxIjYtAgIKpgzAZGNKCFHhBgZfp5XLgOz6uUCEY+IK+4qAqE7v/aGCwnwGx+A8JtYidZVDfflFpEjggpKr3oDlbTPSgUcAuC9UwGSvmvvsfvaYPKlRl3VyXWzpyUiBwkPwvLuHRWzQseWI7FSD2qpzyzAua88IgfEIha9jBfGdrdVa8MKky8Rm6+56vXNbeqbYtVDYAZhAWbGBdZ41vY8psYW/QhZH58IuNQ8XLFonHMGeW2XSVaLJo9jcVWd5HMMBIh7/qjv1dJeaH4WSSWC8X/++G9wEW/itrkGE9DSGsRLEDPuHh9S3ijKNno3R8KiZGC/lXW163v3gMX9Fa7+xyW+LG/wx+rOHgVB9MQe7jn165oUwGYBr7nol7Lu/WvW6Vf2o/ESh+o2dG3xyMHAczEMCa/X5Rz6nvfecbf/+uv8jybjawhQYXC5H+W+F+GxFx6FJBZLiAyEkCwQxRMHKdtVeN7RXKnfZsp9Qeoym2N+aWwWgPpnLrOp/HPiVSaqZ5H9lu2vZ6+OYeqOAfSuja86dfwdu97b4/4B1F9XM4Jh13mAkCWgfCWZmCJGGqA9kLEYycWEt6Is9EBKreOUA6MNLYAgdWTxZMKREVqW3wvl1czTWAuEJ2Ai5dJiTlAORB78enAoDKV599r8F6J+lxxkVXs01J0lT11e2305W2XlhvdYBh+sT/8gMFDj2Kv4sSP33pQo/j2YfuA3hi2fOg5dzslZyA2iHFbsSBnMjDZGURBOQLm2g7mYDd1KRGZw8gYE8e7gHLKhufo86SyU6oKcGSAPBiOS7lMgDeek+uQAmMzFPADvQFHDlgV1Qc9ZUR2aO6yP01fuKNSCMo9a9goVvEfZz4ksVJl+Or7S/fUJ84IvAhQ01+/PZK0uc1Y37pzTXHCvDen99JpU8I6DQ40P3XvjrCj2819KhCTH6rSp2BfKeW+ewDgx3jKmffJaRWkM2LV8UMdLgpXRSX+gM0Yj85FGGmmkkd5KYwz0kUb6RdRn8j9yXTKjP+r6rXXL3ylZX/016Gf0pP1E3d9+IpEKVXNdPivj1/JT4WpHJHekn47eN9ehxVXq1+Jom03VNWaiS3VwZG9BLLK8xYzT776qUJFPwFzbNKKdr0IMi/MMBqBWp21o0bYtml2DtmnRhlZAJu/g6grsTYihAj9zpaegHTuLf65pyOx/pbIpjibnPmA2WYsJAxnEhd4+d3s1CYOhApJ+j6sAtNb4cwyAOGLHamEAwkSlIhGMJjImmuMLGGegrIGnwnWb50yEwBLtzoDbiyTUEQFOOucCmP/X/0guvwGIIgKAGMT9s8VUDiGgbcTKVYSqwO5+C2KCgMCFYC6NCAO+r9J9E8FYLdShINx11mAngsa7Z/Da4teZSNaeLkspBQXHxa7mit7ILCr2gPUD2ZQ/52iBPSnSESrjo5efNS/U6txlgBs2Ak29AxJD23XzNIsVEwQCgPcV6slE32353klimDJ3BH5tK60hl+OXA0Cza1DVlbp7VBeUTMn8g9WDhAnwsz0adYQ4MTAitypQceAQ0lut60pDMgBmgcOsQSDMc4Ro6ohQT60qGrU+J6hlOgp1Bs5W/NmaSC6iWg8xKMV+lzjpa0Syfic4BqolAJqjvX9I4K5bEsKKUd0spSCS8AccGbu7u87q+0TAtS4/kcV7BmGBFuvODkW4hs2QgIf0iidfvmThstadAdTeIcSI9i7CL7PLRIupCRXhljFos6UH9YRX8qysuQ5tbLH5+jW14ZmARbhGyzk++YKvQVrXp763GTCuOCtamYW5WBWxKvTY6slahlxfce7/ZIFe9Oic57j6H1fYNTuAGc3XFg/0kMvXZcEsmBZY5LWcHvM7xBxgQiR5D4+d/vhcsrqUZDLGckG5YODy9hYgwq5psHpcp3vzOeHxURJfL0Wo3a44WX7PWbyC7MWPP5FefexV3uM0Otc8vvcK7GdNxd9n0Gn55D3Gq6IfKU8FIPElpQtTi3Xu4JJw2TuHqvIAOX0mC54duULwbGANdZQUmtiijeLGPcQoe2/bSqiMELLyoPUR5XjrDAVTS74NeR3IfdHdLctPNiWrI+/8R1iIdTyl/E0pVf/QgMvDqbuyGQvRGfSlfx5TbLX1K2utsCqeAkggYAYujFei/hKdcp7WNab1NPW/YCgM5hzfPAZV2mBRWjK+AWCIOWx3sJTcS4YTY1GujkLlL/c7cKDj+uOxuH7XcOy8o5888Hp8YPmdf8B179Un18v97vwUGuxK6nzruHg+QCUv56j8/Q1yDe5finIhSDPVNdn4244VbefBbkbZ9bTxXgMHCO79rArnDPHEJgqqchZ2Tl2qpwVAQ3hEK1v5a13b7Z1WrkLlCu8PjHzmZe1nBrZ6bg4hpLrYulN2k32adXdMmww6yp8Hu1vzu1RGywDxyyjHlkd77czipYy54PNyPzM4nZWedW+7NJ6wSDPXV7kWsQPmDKwp91Hxwjprc/renyz934tnBht+ZJ0/hU4ZxaX1dun+fPB5U7RL1TDFUz2V0b5HOIK8Z/NukLRXSZSrSEO7AcLLpLFQ7jO27xR1Mx5ndMc+0kgjjTTSZ9FogT7SSL+I+rztR64/M6/PvP5rsqw/qyd/dev7IoufW7JQv/x3XHdOmfn+oWjfZfkMqHW6yCnkQB/BTAhQC6kQQd6EBFFcn+qBzBEDrGJCPbURAA4soLcLclgkJ4dEQE7S7FINmRikZ8KMFip4lCy4jiMDWZZpz78u2Dc8ydI4ZAGHnf/JKaAGKFAtRXg4BGY0WpYjgneAi1nH/gWsdtyWf+EKkFkE/ypMCAqwWysJprkvyTcvG8zOZtkCSRM9/L8ruIXD2dkZJpMJnHOYTCdwjhBCDTBj9n9NsX3ZIKwWIrTpgdNlmXL4Jvhrl609IMAlAHjnO5rsXl3zx1sBS02QyyjxY3VPV1gXxAeGv9Yx8dC1YZBaXPWun941U98rbn2mfUv0cgT2haByX8fC0iXZRHflFIUOmbIavKAvmEb5LuQqhkLQwjlsQowRVVWJlfl0ku4DhZAEhLZtBKDPmjJwZh2pQr8sjBRh/GQy1fclQhmLhw5yAEckDw2F4okULcoF3hPEu3tE5RzaGJIXCZtENpfEOj/HTDfhji+ET+yc1vcx/wYVMhHQPDAIa7glYVrdwFzSuxtWt/YywnZ/NohYw2EJQkRABj8fSC3SYWLQdfHdynxI30v9iOZrg/pLjRAi2vu79Dvd3KL2Hg3uEVYL+BsvSj3kkoUVAXDOC+jRGTUSH5PIQkPIgDSVBu8qTG5vsb2T8i4ZeKAHXBRKIgFrVLgGYQ61Oy+IEpB7yYQ5i+BUxj51PDIYcG4gcwH37OUJMKplJd4QIMpFbumAh73EqYy1Wx+YrI+AzsX3gs6nks35w94vhGzsefKI6wagHL/cwHNbt/uA0SM9Yc5XQG8NHun9ZHtLXocYkWyOUhJOO9KxqOkiIkJQK0KC7r8CkrC6ZXfkxD2vK8Ox2DJKA9b4/XnR2z1YPXDwwNzh1+X/793PRno/dfZ9h6x427lhe1X3zXeox0SkfZ8skBHSv2UmZslJlgeos7AwA0dHiK3XVPyAUn23dN+er0cSOnSO+IST25uufzq9doD6GeUPVECURvrKhcOUWaHM2JXPDclh9jzQIc8YRrb0tieNt0z8KCPHMi/zZUioLXPXHTlhoJUCnRzeNvPSclLWueSjD93X69IrDZB5n7I/Hun4vmPPmBv3offySMCiyORxCB3eo0O7YfkAv570r0Y98Fx/zMrDSv0UyS1/2cH2NQ7CWJAAACAASURBVP0mn0zICiNUvPCRRhpppJFG+gk0WqCPNNJIP5TEouwfyODum3L8VBrWSP8JNACavU6H67kHwA25BANgRzDnzJq8EJsZMKxC48o7sUYnj8oTPFXwXq2z4NTFnD4HShbK4qZS4w23LdrdDk3Tomka7NqA6ACuvQr1oIfJmMA8s5jpuMJXQUPqiaIrokoqnFnUxy4E1bHq5e5oY/uHINYFkHjJpqndhACQ0zh2YjXchoiAqLIdpwoIZlUk8zhyxC6IO82ZCdQVMLd6eQAtREMvFvWx76SAOseY6jy9vsXl1aW015mVMePu/7lL8oPZlynOzy8kfrXWSfIDQtNgs3lBeDAI7km7+EqAg4WAB3U1QVVXArjq+zAtdiOxKCY474p3p3Gz1dKKOag1NIvgGZzeF3PoWBxzjIiR0T7E/O47b7IPMj+BUVik9gY7p79sYfueteayl6/JmzzPIfDwWsFJUaqw0eeXTq2fXWecybgxKxYn3iAqj6qq4byTmOIQIX0MMo9iFGuyNCVcFh4657VP85pCQLIgJy5hXps7uQ+cc2jbJlutaLzUEFo47yWWOsuaAQAhNEU9ZGK0TVS9FRbPFkpiQR/AHNGEACJG5Ss4cti1u866VatiyK5dYVItYa4Kc52FLL5re7/K6wcAU32JLHHPnVsC5BDVDefm7q7z9v3yBt4Rdnd3STBVAnBlX3LvM9Wl7FcA1fJG2nB/h8nNLXb3uUyb1w5iEW5KFk7nmAllXbFGyLjJHkbK8s0yTKxcGc3qHgzgiSn12yUDHotU84i1uGdnWX8AcTFuVMaxtOcPgckWbsJhgTWtYYvrzfUNqiorVYh1LuN+ZUoFBzL8i7A/1uZjbMElA25BOKtusWtbrNSl/NWc8PT4tn19wdZ/w/SZ3XLO+xblHyXmbgiQt9L7nstz0yfrcAbZPm97HqmXDshaZVZWYpWoFo0maAaSZaNTrzJicejEGt0RfGnFSEDbttiFgICIECJiDAhtQAitXJvXj45VOaGYHEWT+jxb13Fvuc2lP0ddcORYj32iJToXe9HflVL1D/Udd78mgMzLWDil+X3lCrEQj1mPkGyvtjGYLQM71oyaV1VNUHtVlNMaReO9zP1zjGqcGEUpsxx7ZpYIAwML7iodA4bPEvn7+1785w2/nzzw0j73i+inW4Z2y7KY4IPEvdT8MQv0LivPqlSMNElsHU4eRtCr297QyGttNrbNQCNZmpzajrAAmScg3UPM+lzrULarf261+QjOiqk2x2f1BAQgRDkfbpsGABD0vBaZEUOLGHLU9XKN78xXKtYm3UuIALg8Zvoz9tjsMdfshBxizJQ89/aPwrockJjpUp/MPD0VO5jxi6SPPhJwERnPbr9ObNy8Md1F+w825MA58JT1/ejz/WRH0lE5V3vjPrV9EDzvnXIP1Ll8LHsWlEN05T3M81g51pMFejFXMr+T6zpaoI800kgjjfSZNFqgjzTSSCON9KlEBw5Sn5lXef7cpwy6kV4yCEGPrwLKBZADQnQAGjCLMNlVAJDdR4vgIIPo5DzAYq0cXQVyUePHBVhhZexskT10a2puTolI4rPxwCEeKA3OB5+3fjihQwCIpbVXIGtSeYQC2CKI62XWGHYmMDHAUgA81oNsAAHYaIHnAFo2t/dSDQPPGYVLdbPOhVgJd8B1Fjex3vtkiQwCbv/vW4Q24Pn5CZuvW2ywgV94xDXj4vdzEBHqqkY9qUWI+0VczTIvEdbyxqulgQXiBtzcxUdzQUtda2nr3xAEPI0hqLBP4wQ6V7ZKD+/qGpsIzN6Gjn6KwMnfthIbNpowCojrUliTRUI/47hfWqWWFum5PgDjEYQ5IhjVjYx9IrG7j1xYlzGgBugq9xBXq0SlV4E8oDut1fHvfI4Bmed9FqaUihMCKIkwLwtNkISQRA5RXaObMgNIlVFQIbStuNL24jshRhYLmhhSfYgIVUWFYoQJECMCB3i11rNmJcE9M+KaUd/U2h6xyA5rRnudne6XFvVOpbPOEarlNdrVQxK82hglMHYrhsc9/M0NmAntXdvpT49FEmwaHZOzuV6aUqZXCr7CKsAvZVzvCiv0rgxwDcZcYrovs7JO6da+/CTnBYgrKhhVycFcifqK4L58QfO1wRU/4hEoBJa6Lil4foweSUD0OR9eJi1fo9KC//bmFpXzYPU40RHyKc35CgTCmvrW8D+ervi4FbtZ4F8yksv1Q8QAXu62uPjtHAueY02PCTy/YAHYH5mxoOzSvU8XDPhrhxsscb9evbNVp9Op4PnFCe3/yxCX+4KuA8V4M8tzU0QhZAtwU3wzIieATYwaBsOASc/w8IguwpNP0nDOFUhzTfRhnMSSDWLlnlEZq6EV2Ck97yfc/d1a+Cr7MtIPoZJ/TN9fA1pSmhL1MAWPYo2nLpRH6T/LRBUwO6AYd8G6kofScvJsKIpHb8jlag3SPng+0j+NjmFq1F+QaOD+G8pJCicJiOXiJnXyHxqN/eKoTKiDP/OTmqKbbaozlw/1yPjY8ro7H/P8zGkYjl0634VgHrvyOSdntt83/W42K/mTcN/EIA8n7CsJA6974dl7nrpd/dwr65mE/7Kfuv7F+pV9J310iRpi7E8t55VqW/ipQ4stHRjbhwwH0vmlAMEHAfLXwPORRhpppJFG+gE0AugjjTTSSCN9Or3tEHM4rQFZJdiUfkd5IKPOM+VnAqIYCCQW4d4O/MGBycG5CO8kfrpDCR5LushI1lsOXsCnKsIHh1a1+MncwicgLeaqpQMsIWnvRz0sOkgc755Qz5klpllzqeBbsuwdFjnbI6MoqiMVZRHeeOc1dnM+/FoZnhyatsV0UqtlbY4vFjgCkXFW1wAIG7UwYMou3J/BOEtCdyuZUn+aVVEJngPAbr2Cdx7T6RTVpBLr9BRL22NxfY37h3tpORGAiOd/S3S7al5hVteYzmagupY49U1AvA1oQpsA2XpSw1eizU7adyEEsRAPDPIG2lWp7iEElSqJJIXBavGnIDmiHuAdSIVizldyJ1layCG/qidgZgFvQ0TkgHgjQHOzCiAIQGdW39cMMJ5w2Iaz14nvkBuYMKkE0UGPIACOFwCglujXaRi39xFu6RBW6vVh6XriuKzewTECXvuFsrt8IrluQ0zzKrQtqlrYUhmbRWAARzLQWOc1qftXIrXE9vApTp52h4Lne67kCdi1jVjbMIFdhTY0QAOcnZ2j2W2lSM7WxslFO0Tg71VJguBAuqY4HZdh9agx5JdgEDZ3XwFcweFK4xVTmgcp1ySAY/jKw93eoLnLLtWTi0MAbnmNyIywWgG0UEtsQsQDAtbwEHC9L5i0svzyGgAQVg9aYk7DxXVJjDWaAgcVNRqx9rZnpMQ1pl++AECKYe6xBC3FnXS5FDpn48KsSxwcRQSOkFCIEZFFucAvPXC3xLWZJ4E19rnkZYogJswcmgql9Xn52U/rMO+A4FcsClPBYkLftzj71xQvf24QsU4ZOHjUXzz+y/2O//7z3wM1+HE0DJ7nN/moQvVnOr5MPBNwsWZ4PGHXVrj4/Rztvx8T6PyNADxyJx76EH0j4Nt6Je7ef6I885KLUCI9sjlg69zfAUjv93CaOwnIyOuDwNsCopfgIwCQhlCQeLkR7B08+QII8QBFeM6KYVag9Zsz8DwygnOgqLFuUfAukTMgVIKilsYAJCDtqSVkM0KZH6RyTB8CQ/pgIArAUN0s80CaDvH+/eTVp3ggu/03i0GLfe0SXwnSvdrAcy6AtwEwvQ/UMKAKfNz5LSfrpU/ng0Mrxc+mcdT/KhqMNZ5v5q/cB82p/8Pp25zF17Ia9EB0Tv9SyndvG+0s0Rm9peI+wUBGlBlDwphBQpTpnIPOH2KYDzJNy91HGWme2q+RGQER7aYtH9lTTMme1yT/MuRXWUUrXUOtd2UJXNRFH72OQEsFMF4k74DlvfXgNaVDoBur25bOhTY9ID9vn0wae32PqFv5Xj33kpZ06Hx3bNnopx1i7vt9089PNwUqx+hAlpGPVSTnleQBR9J3LN31ueRdp2cB3wkpMmB53k8z0kgjjTTSSJ9B/vzi4n/96kqMNNJI/7mUmO9/HFHx9wtKHzjw/HXp9XoeGkN750TVVi4tVhLoBmQwHXq4KqxLCeLOmZjVElKsTRmAxXLMgDUEeFXL2KjCbB545SYozMIN6vyRus471LZDr7F/0KTewZTsHxWmWGw9c4kWtTNCcg2vrjKZE7BZHkjtviMH7witPldreR6AB+GFgIbkdwLgcQlCDUZzEKADAJpMUPlKgFA1TSjbuMUWYRvgZw5xEzG9maC+mIAjo71v0NBOLM2dg69EGaJyHm0McACmZ2eIIab45yBxZcsQy9eq8gqw2/wR8N7erc2p0IYUDx1qkcwx6Kf2ZcxWGjHm9ARxLS4uxF2yjq7OHGhGiJv+O5yi4h12g2OAupLuD873HQGT4tpjKmVgCgLDn4nFNb8weFPAphsGnVG2HgdQuUr6t6rUJX8Sn6T5GdqQFGTsWXGV7oH0u1mlu0KIkkTyYuXuPKrKp/eRQwCIhaSFdDBX7TEETKYTUBSlEHNHDDDa0GbliKQ40f/T1nBM7amcS/3ffH+Bv56jUkA/vLzALWbw5z4JCJ1ZT+i8lzG4BjCBt/6aThE3W1iBDJ1j5+cIKwYwlbjjZ07fxxSMLdzZGcgR4stLZ645ZPAcAOJm03n/1fIarL8RSh8L+6S2p+nTiLT97feX4vkJsJFxQ7Oc2rsUHCNbHZGE1EiWSQqgkCO4MweaORl/YDC2aV6U82NHwJYEKJ0U9+yaen/99j3RtnM9v72Fc04FhQw3AzZ3O1TLCuvtS0q3oQ2+v3zH1cUlLi8u8fz9W+6UH0yXjANrRKY5z7Gl3avLREPAbEGYVldgZuy+f0PTe2a3BeYLwnY7nIfVp/9cSQSxjN9+Yv/sin2n/wd0X8WxupV1fG/1PtqsQ2UPtUXWowPXZrVbAghcfJY8gv5myiKWJqnj6IRJVo6WXwdtAuD2HUPbntppABWAuuWme/NeI0d6nV7rrw67QJ0/MNIal5QG9bo71ihlZX8S+shCBxR/5paaXOLNun85fIDh2ZzGaw88t2sgg4elYm1mzfcW9TwVeODXfy59ZH37eOG/zoW7haQ6+Unq9pPraicf7UNbzmzJLP3x2LhNPHBvdbd52S9t77hYzANrG5GDNz5z4E0n3toOp1aXMlsUyqeFpxHuXPdvHwDO9V5xFH+d+u3s7w16ZukA4cV340MuGdgh8xwzLf81nmnayZYQKffkHviu11Pu510uTGU7jpe9R6emf2s67l720xwC0E8md/z5LGIo3LLr3mH7BNn5qhjPWYRSzJVepjndyEiMNNJII430OTRaoI800kgjjfR59KGDSvHskMU5HbZEz4dU7n7vnN3VhTtLrPPAEgecYxSjAM/woQXIKbAuztudi4DzIM85HjqgrttzHDmKPXi4OKBmt+1D7eYEFpftI60z7OzJ6UtOpxLtfnzHXu4IiHAgxAhQgxw/lQgRSGA4AwlUtvIFqBQL26i/MRNmlVipb2LsAK/n2u3Zre4zzrV6EqpS8+dcplEIAdvtDtOpxsNUF91N0yCuY6pTfV2jDQFn9RTEgPtS4eXrH9iS+A+4ms8BOFSVttVl4LuyflNLEDmkZ9faZvnOISbgu2l22N618NcOdVWJNV6Ud2Put33lusoaSnVdC1Cu5gwWS91XFciJq/G2bUAxwF9L2eEhaN88oqIrLAE0/FRYVPSRiH5Pfowo5ZbnV3OvMczTqLMyS8Ek0nyo6gpEIvjI41rin7MC3Qwgqqv8FCogmmvgCKJsVc5gEch7L/FWG31/lNeH9O5iVNewGiucKFmcETmENsJ5h9rV8N5jt9uCoXG6WRRiQog4m80Q2ibNOwwI4M2C2kSFZ19u0tXu/iEpX/gE7OtzzpYoaZcMiyd8+xrhGfDLBaqbBdr7VcK6qht1bw+Zl3EV0UIsySssAQDN6h4AMLm5RXuf46AHAO3qYU/RJsIsbdbpTUb9mywJtOL0vPkEKEeeB+CXhO1K8vXaLw+aaMFr2GrKKwBYoL7xSUHC+lXcfkYQRRAIta/QUosYzHWoepL44sHs0N5dY8EsVuAYEmjKD5cs63a1vEG7ahHpMbvhzAP5IE3qKXbtFl4VMEJgnP02Q9s2mPMcjz2X7f/nz/8ueufjZJby+65Hc8WH3ZJ2f3xyTyCc5sZ8/ciY3gT8cX93sBlVBSxvCKv7/Q60+gyVVV4+Hsj7Ym8Peb3e55xf51A6y/MbyffX8nuPjNue+5E0BAZGaIzeDvvR5ae4fEbjs1YAEDK/ROzEgj1GkEZXiADEEkweJC+u4JMNYczu3Lnkv6weZPC73mNWhZly3yKU3NNbdrKSF/wn03v6TMKhCEgXWMKXZAUJTVv8YzwjdUeX8EEDIEkBY2QFO0eQSM9Iioyy9+koYeNoC7fRKMC8lC63uA+aDwJ8Ngo/yfL8Hz7c/jPo0Hm1ByrSXtK9GfD6um9AIXLYIS7Avcxv25lO1so+d18qZA+NQZujFprrQNNSaglLZBbpuZ59T25JiSV5icjlkyZg9ABzZAtlUUjn/Xl6UENcP/TzSqf+U9EhV5Bd6JJzOKKSp3gmsRi3vp1zfk+vWZ/387J1cAHbE3uJWazPn1zvvRRW/GzPncIk9N/tofXmtbzywDkp2Z5iyUfA85QFpTMaYOe17v1SYdoVCsl786z3XPn50XqONNJII4000ms0WqCPNNJIP5RGC/Rf0/a/lwW60ev1fW0sZS1+HjxwpqcZCRhGNKtYFUrEKFbD6mabDUxnc0HMapwj7rdDjAK6kUTIPdSkjovLIWJ03FBS74s93xGklEUNFV1Ifiy9cy4LiFxphS1CcBO+mCg86hcPdATfTgHKNkb4blNB6Fr4Nfp8t949Uc52ivpigtlsip6BB7z3qC4qnC3OFexktOuA6syhaRpwjLi4vsHm7gW8AWIVUNcTOYx7tfgmp/HP0QHOTMDPMcI5n+LKbjZbvGw2aNoW7SrCXzuEh4hYR7Qh6HsPSagbg3ot0O/MjNgKCtG2Fltb+x8CnHvvxesBKBk7ExFo6sBbgJIVOBCxwwSEXZoDR5Cpd9KOxDpDsttCrM/tbT0C+psJg9K9DeDOpGOdI9RVJeNIXZan1Cr1M88NJm6zEQoqlDtKwJkKYSY5EHnNSpQcQJSs3bIiipQfowH/QmUsdeaIuq5RVQ5O30lU4U6IjLZt4b2AvAVklIiQJXKpHfp+duqCfbK8RlV5xBixuV+BplOYJYUJGx05MNeI6y0CZJ752QxEhPAiVuERAL8A8eUF1e0l4ouU/UgbzAAQZiDMwND0Ly/wWALY7M3N8jPVewO4JYE38tszAfVLvj/UfkAEl+6MEAuDdoJYBp1BrN7jZoMsCt4ivtTgKcE5iMW/WmCZ8C6qslPlaqBwSZ3WPgIwI8SXBxDE7foMM0wxRa2W6Q2RWFPzHIQZsAHWtMZuoA2H6PbmFt4RvK8KBQypa4yMh+3Dkaep8/Fe2tHrllIlXbJYTu2KvfKKcx6nWF5fMVCfn2NSz7DZbgbTuO+AP19g83LADP1AWac0pSH5O+ecxxRiXW7X5T0Dzy3vMp2RWZM1lD0RlB4Khug9r+6zuK7Sb8fRMpLVlgqnyYBKs9oqExvwoWkBmV921wDLKPMvP6prM0HAzzLbtJdyLm+AT7M9g/cE9Oh47um4D/+7sbC/ml7rL1uSDLBAsWcCwuMS4IwPdGJJ7tUisHJOQh05L3yVc/D6J2kpWaJ7Ku57p7yVKNfZPXJOldwYIXYiK2egrkTqcEDJohhTQ7hTF9QbkW+jHpv9kwv/tRbop5yRS16pq1TyNgB9LyWRrIM9TZX+2W7IdvyQ9TyB0vzzJOcY75zO5ZzK5gO5UhkTAGV+uxtOLH8pLdL7IDFhHzzv50PA/vQ7Yc0iEmUvKnihS2Q+1bxnPZH8LvyPpJtC+NYdJI0B7Ye5lkPVIMy1Lxn7fMMlTHHwlQb1X+gQwP0mbajPTbc3Jz86T4v95VB5Bp6b1bmEczLvYYnF6ZzxTgHPRwv0kUYaaaSRPpvo9l+/jSeJkUYa6YeRw9tcpf3HUJII/pq2/8cA6Htu4vatT4AkFi4O6Enfu0N2eDYBiEMWVngHVM7nWrAIjJ3z8M6h9h6+qhO4HJuANrRoY4u2adGEgIYlKmjHDemhOvcFEdy1JKd+2m52SKi/PkexEFbY8wPCbKfA3aSqE2jVhJAEONx5WBUG9JJZ3VVrRSpfoQ0tEBmbGDAF8NLr9xkDm6IKZ9y1ZBUrqHMA3zC9vkFdTzCZTtR9uoDMm+8vmEyn4BiTy/lv356TUEYgaYe6ruGcw/O/n3Hxr3NUdZ0sxDMI4MpLhCBW5m3TiHDXeZAXM4L14yOcE3A7PASc/XaOlz+/dQS9BAe/KFzWUoEpAJjWU31VjHpSw6mL8vLdOieKAKENaMMOITDC2myHGYwnEK4APKGFWEb05Mr70+cD3N0lA1XycjAHCrDXRHslgA4A/saLS1bnUU8m8L4CSOJHg4DQBphgPISI0LaSD0c475OQw0B3tliN5no9Bp3aEcQOxA6hbUXYou8ru8bnBJQn8FsRWGZGiCGlF4CcUNpWt02LbbOVNcIRKl+DOaANAc26AV06xG/fQJhisqgSaG/KKFJfRuSI3fpJ5socmNTX2LUtai8qJ21o0T5IzPnqegHvPYJ5smBGc/8AbTUeSaxpJrfLBIK1q4ByngJIFtlWj8nyBgAhrlo0/JAUgezdsbZcarQA6/NAtk4HxKKcmcUSqPjdynEA1ibc5HKtzfNB4qYvkli4uvWYVLWuhZzHGUvfMfJ8bVtGCIy4YrglAHII9y0CPaLiBeovFQiEr6uvEnsb2drYYwFEQqCHZB19yGLV4qlnYvzP//k/0e4aEAFN26hQl9B+bfFAx0B07M/LH0C/3/6Gf9/9id9vf8O3r18l1jkds14/Tgu+wuz3Cv/+QwLfzxcE75GszZc3hMovRGEIj7i/2+/LQ0WaN5Lv7+iX84FX9prcuZzd/JZy+TiIfWo7yjq/XnZO3FdK61PiMKl02yszS7yqeCSNOwXF8xquPI9XYbW606bkituEz6roY/sNlB+IUde3gDaIu/eon4nzKirP5V9meNL+xYTMJ/WefS+9biG8n4BLLZ2/GTEAckU8evvQz4QzGAjBXRfSHDLP3LEYLxQ0zDU0yKzRJTXAGg2pBwFSkZchYVTc1zRNE9A22QuQhRJKVq99QB3oKqsWGh3JBTy619xT/+qv/28FWT5ugf6LB1rBO/8S+sUA+pDHhETcXYII6LhNfy+AntZAJ2teaclcztPyXJolCTbnXFLyTd4amJO79sr5tP4n4FL54QhGi5jPkwUYn8vvApOlVzTzElSOfSoe5nJN1/larhEcgYsg/OcTvb7WD+0jqb90NzN+1G49DQzoubCU8ABmyxswgJf7O6lDfyIXbSmJQLgEqeW6niV6A8XYWOvf3pKYcywPiFSOjv2ve0TdL2R15d79/nUv73LuMVh9gpTldOfLuykpamhZA+uugefkXDpzJRlWGkdH6mBjdmAwjQD6SCONNNJIn0mjC/eRRhpppJH+umQg8d7PtH/wPZYNDp/TDQiMEWg5iiJ+EDfCEYDIoTlBiE5jNgYTRACAE1iaQj+ip5Qu7tu7dX6tDYfuD3UJdU7kpxAhhIhK3Y7XzqPlCHMzn0XZ2bWqA8HM3J2jZNlg/Wc0Y8KmZ0l/xsCLJvpOcm11jsxw9B3EwO6hQVwwnJc45qRSB2d9oQAtgTCfzxFCwObbCzgKsNmgAcC4/P0Sm+0Gu3aH6WSGuq5g7ujVX3Ui5xxCCOk7ADG7d4TFfI7Hp6eU9uXP73u9zIho11k4W4q9/LXDZreFcxIXPOVvaUhicnNktUZ3oIZAtANdA+0DA4gQ8ByAguiXfJoLwvfSMwHXnYbywAhLtisgAOE+gm6dgCiRQRXUClJbS0iWj0k8VQxk58RyrTty5Gq73cBcVwIAMcMlTY+u+/YYJc699x4htGXh2bqGpb8FDApgjpqHF0Fb5VEFj1YVNtp2C3IQ18aXBP4eQTQDsEGIamXPjN3jN8wWlyocLkAoIoTHiGYRUHtjvRlEWWwV+REc5p3+7dOagPndKgHb1c0SYRWL3lrvPWOAcxy4B4gQ92nvfec10y9lDVisuLPuZPUESVeC588kgs1hWd46Xbd3S9AtVEEh5gfUitGUHZxzotxEjHATEe7Fybxfengs0T602N7tUF1XuFmIgHT7IK7svxFwzmtUWMDxHBd4POq6ewhs/t//3//GVZKGMghzVMsK1a0H7g/n9TPo99vfOp9l/T3mWPdczB+iCwb8QpTKHh6fsP4j33tcyxtbXBuwJgoigOybh+ic3waU7ysvdOk77QPSF73rsuz+mvUe0P5YXU5NZ3U+xX0+kAETacAAD3BCubYys4Yqse27BAZiZDgX1XOKg4Mo/5HzGfhI61jOmZ1DpIgQCUBAG0jQiSj7dEzwhhAXfx0AgIo1ZZRxf4xe6T/mLl5o4LmB4lQVIF26n/cvAxxJeT8bFyASxcYQVPlSx0oCSDOPkL4YyGb/FFavGfDGQZR6P2RRnwu1Ng8HN/qnu/sfCYfBc7v1hiFybOqVZ08ufhDlpIHxyapQBHPnvn+/U3XDwqEW547kLKHzmjki2vqdJtZQtgn57rSqTP7avBluERWf3fNxPmsOZnbo+J/osrhX8g0lH3HFwqvWPMf0VpQ1m/v7t52ftO+eKX//vP3qFeD86Fg8FrzNHqeDKfM7x4/bf8s1uFSaMYVp22PUg0lHaQvUCXMw0kgjjTTSSL+aRgv0kUYa6YfSaIH+a9r+qy3Q31fygAAsfelBd3tW3SYtN03sLClIwkArBtuMagAAIABJREFUgfN1imnOZekSMzdZapK4oaycg6vUDaWisALwRITICLFFE4NYzgzUPcdg7LrBIxVAdtt9CDgvhNJdyYYAUH3QgIp2dTTO5R+xmJXT88SLBXEbsxUZQxQGWg4pP6+gnyNCZEargtNolkKa44zFGt36+kwrZUA6w4AFOeJ7AoguUV1VqKsak9lEhEJVpUBn8Y6TAFcsz4kZ3799Q+SYwHBS8N85wnQyRT2ZpL4lclmirO+r2e5QVZW4ygeSAsPz8zOiWhe3ISCsQyEoOiSRouIbob6pkrX8+fmFxnjLL5FZwFlXiXV6jBFt02DXijV6XIdUTsRTLpkzcHlw0r2Ty5unsSQZeJ6n7KxvS1mSW7ok/JhNp6iqGiB5fyCA1dIfzGhDi2bXKAgn78NXhdVMMUcMeBeLdcj7CYDToABmwe7UjayNt6ihFVI3aNkyPgj1pE7guVnihNAgRpkTlffYbLfJqpw5u4JnALvnp0Lwz3AX56i8xXaVlWVzv4afXyCuGdW1uLJt2iCCTu8klrvmGTmC+RmES7QrAbsjdQGFydKET0C4Z/iba3hf4Y+7r7jmBYKC5A5i7Q2I9XW1rLBb3WWrIHQtyM0695jFbepDJevZvnzPvj+TCDL7+dl9lz6v5X3c+gzUGGn7xUuEuBN25NGEBs1dC4KDu5E+Dw8BAWuc3/6Gtg1o1y2oUxIQEfBMz/Jd19zSbXyHTACr645ZHi14jjVJPy94juq2xt393eFO+8A2fMWvK8rMuRer8wP7/nK+RFi3eKSsNHQI9L1goFoS1g95nz2JOmjCjyUD162oU0Dv5A6e93StTs5jiC65GwJhOB/GhZa/cU5BD539A/2VrIRRAJwQRbDKFHXs+RRnOueVhdWZTyIQanPTXQi2U1xSrXc05aIYEGJAUAv0NmZrR2tT9qXSbWvUz87vnwxuvsUS/e9ogd7h9UqrUd5vu40XUwIlVVojECqv62vKrmt9Xo419MZNjBFN26rlZdcjwt45hM26PCvRNU1A0wa7bZyy/svo88xmoW7t7pfB1gcoR5kVP/yCX1s3//YW531i459/EZVg2s8psCiaOrziHvX4FuKuBTpAvetXQPRiH2IHsJMAGeV5yZZl6v1BT5vmXYTg4B3liaID0znxplT5SoF08aYWYgTHiPMQseKIoF7S4E4bkZ2zM6A8tfHovcScFbBtnl0y8AQWXpA59cWjWiVf6qP7inPZ81nqu+LuIirvqmtQgI5lLd/4pjkD0+UNSNyc4KsqVh7yZnfMAn0OUap/wnAaO5qm9Tc/nK/7YqFDL6E8XPXqUa6Pe8+/wl/1x/xetw/MiY+5cM/5suWl+wiReRzrxj5P3hfo4+uu7VsjjTTSSCON9Bk0WqCPNNJII430qfRDjioHTlLJSvtAoSZ0QBI+DBymGHsWBxECvNoBNkZGC4ZrAxzFFKcZyIdmJMFivmEWOUN150L4Ye7xhoXkp1iiv73XGUBQy1uAETgiGOpGYs1gMb3LhyI4H34T+FQ61JT8qHf4fxmoolnnGYhH/Ix2fYk4l/zOzmeIMddR4iVD41qLa3UmAQTPL87lPbWtgK0MtKFV8M2qxQhtANk7NAEvi9V7jAHeFawREc7Pz/Ht+7cECBywGxnoXRVmg9Hct3ALUcR4efkO7zwm00kWGKglHscogIVz8FWFGoBDg3YBdel+xNzzk6l03w2IMpS9e2n/IxiLIkUW3jdtC+crHR8mzM9inzwUOAniASCEULifzO4iicQqXIoRF3+IBI4ssVW9z/WOIdXDCswCeC68AMh1AlKrCs7XiLFNYRomk1rGC7oeJAgAzWaI375bASm0gVMXtwAwu1nIMzf2E6HyEg+d9LuFTyAmOD8HWKy+w4rhCtDtiYCrFePit1swEegmpnjB/7r9IsoI9wKil6MzYo1mlUH1DGtlWZ7dK9/5W1aUcvl8JnE1b9+Nrgq8oyTGA4AFmjuGX3rAZ9fRIshWC/7AIMdgYlTOo0GbABgmQrX0wGqBtlU3+4CO1gi38KLEsKiAp6Ky+vWykM72AeunQuB52Zv2Eg+aMOc5Hk+09D6VBKh/Pc/qeonrVURL60Hr7VOtngHAO8KqAM+Bw89+I3Rm/1+Jhly9n0plcyOG9633UMRp4DtrOq+8BKfJ1ROYU/ongQZlHqyjXyYCAY6RFDsPsUxRLNA5slqu6/pAXQtkAQIkjq8vqoQAOKdrNveqWtQNWiW57vFHPV5spB9ElAFxR6IY6RV0K6BGtSbXdTi9l2JvhYwXA/TI0gJZQUMpsqWTMACsYHrk2GORM0DVB8/3yOaGKQ8MJExjbrQ8H0npGKjWPw/ugZh7oOaRcuyf4pyYPDcknqjHkHQe3kdRGRmUT5a8zukcdqi8B1QxBgyEYi23v/5MOF2xpFgd+kfbAmw3b2ZgYKFnhxL+BYArff65XHQO9PveK3FzAI/wcQ64RzCLImGORS7kGNit7kFRwPb3Cigudft0OEGx8cjYeRMNPJuOsiem33++PKl/EnNzrLxyz6Du2EnxzguX7V1vN4N4fi/fwzTi5iONNNJII302jQD6SCONNNJIn04f0/jtAlWAaW7n03ppaZPLMpfSOQ0VabMGf0HFma4UGto9O6xGRI0h6hCJ4DhKjFEpQJ5wBMfiwroswED00n2qgecmIJRSO2LL1KIsQBSBi8V4hgkorMV88Fg9SETWp3LdhghHDrV3iJB48AEBgRmOsxV6RQTvnVqeS/9X3qE1Iar22YszUVFuS6f8so/0FwbA7hvi8wVe+DsiR5yfnakbNyfAoyM4J+65xUWhKDuEEOEcYTKZAJMaKvVFDGaZLxbzVVWhbRvECFRqBSz9oRb1bSvx19UtqXcetZ/g5etG2r+s0K7aTr2Lt1AQd+7FdYRbCjzZhAa7bztcXlxqTHQkgNYBaSyZlZgHga4dmB14PQfjMZW8YAE/3xrn+FRyDBDmybpZyp1ra9cA5gAc4iqqFTrALFYvTCQAdQKABPzeblpx0R/yXI+BC+t/KHBOCqJLGudkDDBE2B8RO27xyTlwyG7a5YOTJbqvzMI9IgaxmDPwvdk1YKjiDDh5hRC38nm+WV6TqgLPr5K7TWYGMaHlmMB0QEADmafOdDhA5ApPCalrEMIaAMPRAnQjMdBtzTLw9uVPsXaubpYAgN3XRmaZWqdbyVmlABCoc53A8kfK+Tn9s/Tm0r1PFmvyiYZdbRtofsnZ+r0ka8e695wA62vUS0K7moOXHnXl88Ks/ec7QUjLyNY+9aG/9ggPsVh3xJ10XLdgPCGsgTnmAAgtrROgKW7e5QkLltDHK60RgdcipAXwQA/4nf6F6qYCVgONHqDX3JRbmjU9SuxOrcPQMxb7/JgZ4Sng+YLnqJYe29X9mwW+hOyqfbBt1B2XKZyHpkueDE7euobBMSBbj9vvZdsv+HjfWxvsmXOWOr9FAeEYvcXlewJdKHMF5wx86yPfhGQaOaRH2N1zKXUy0XB/CzDDOSY5EajguSgpfCH9LlwR61oK+MCIVAIlw/t/+aa45Be5ByiNNEhDPWQ8RKns1X0L3bSmYFG6ae+PC7IFKHOvhfKDVSbzfsLLGFjW49Uh89329BCjfI/74+MweP7K2FDL9j4g+LrS4142H6RxDP/V6ZgFuukeAdhTBh569uDyXkzAzhnTrgs+g4o5dBA9LtZeI/H0J/zxDTnU5BF071jpZw3gmhl35VJb5EMK6Jcxz4XfVf68d/YmR2lO5zpS4r2zAiTwSIzLxI9lHv9ZKt9VWEhrC2WmUSoAIIcGWtEjGMAVPaaz+iXLdjgvurEl4NnlrMv3JNbxr9OclSd2xbrQP/ZZGw5N+0MDZCifgevS8rw4TvXyKR4unjupOj8QbRbjAOkg23eydxPsgeevewPhH1ndkUYaaaSRRjpI/vzi4n/96kqMNNJI/7mUGOV/HBH2j2s/sXSzrP0VZeP1A9DrOXxCPSjXpXRDR+lmPsiVriqTe8t0kCstweSEzADYLAiIU1+bV71UhhVaHKr3BHvZDOHofLF6Hhb6cCouP1RcDz1XKBWYsERk8gKSUwIPpf1JvqPgf+5X6pTTPdcff58tyV+dIC+AqAG4RtgEUC3uFp0XKQir22+nbrIdCLENCqZz7u9CMEzehDby6ZxHs9uhbVtN45JigoG0BIm37rxD27aIdQRvAUwBf+YQN/1ZTgN/uQ+q60pwP63g2exMwfxWQXR9f07qY/1s4DrA8N4BU0LcTABMpDLYwQHYfvJ0n3RaMgVhW7RnqmVv9W8irdoANNMXwID3Tq3QkygSIEj8cW1vG1p9l5RilwPZxXY55mOM8N6rpZwrlElKIYwK3VU5hMGd8SMhE0JSSoGFPujMrTyf8zUXcilbH+wvux4v195oAAEA73xqP4HQrFaImw1oOknrTnqneu3Pz0CzDXiTl5BHEu1XftnAnc303hr+7Bxh87Anw5Prbfo9Apj17ucWy/VuYCztCKhZPsv7l/qbeEvopi9pBrGsr16696b6GTcAsEXcvADTs6SoQE4sqWxtdRrXs/0ujqF5A7gzmy+AOyO4mQNNSeYrgGd6wsTK0THrsUCNCWrsUh2s/d8J2GkbGv2z5wncAWGrbzWmlxWm0zNULy/7fde7nmC//2bIs3mGOQjbTp1ooD8B4NvL973fTt1753yFGWa4urlA8/KA9XaD6YKw2wK//77Eo9vA7YDrJeHsnDCZEGZn8v4aknjozMBuK9cGXu+3XwWn2hG1/rWa7hDA9x7qvicpx+pmZTUHCur/XnNe/w498yPJed8BJxoiXDDQFGnS/pZAiQxaDoVOovI/6v4VRYnFOcQLjbk7ds7lOKX6PFsMcwNYWTzUcIwF3CoU0V2XjtE/8cTwYaLe3O8D4Sj2KnuvBc/rSVy4ky20gkInEJs1JEpkA70jYohpjxMXQoXHpwIQSVXSvEw5Mer3GE359UDlB6iTwhr3Wroj9E88p3a51J9d+M+WDRRrHL3iwr33RH942Ro7nPsr5CAorx1QAQxp68m7yecr0ZOyOdvLTs8q3ntcqkemR0fYqSINR0YdxdPDC2V8vjs3yv7J1/0uKhXSi4run/P0951eGt84YQW0949J+8+Xn7os2bmkRt7rrZ5lXZ+0vF3hcKpf3BBPVdIly/NbW1v7g+AU0qND71B8PP3gtWV0KF3JwZfJxGOYfdpvNPjsgSp9YJ4mIwEq+JWCpyjdtp8Cnr+H/olr+0gjjTTSSD+GxhjoI4000g8lgtndfSCPvyPz+1eIgf6L6CjI+7ac9qxoOtQBohXYVmGBuFyGAlFZEGDiiFxCztwEFns1Z07a74IF2GHQLIRzHPHIUdyfglWQbALmbG2eYsdxin4nwG3h+hlmRWSHz1SVIr1ZZBqQH6Nq/uf+6oglE8hf2uJIvc2awPUOuCaQb6NEmIvIsSc5uX9XwN15eAKCCmra0I+JLmm3Vq+eAMfuO1iM5gurHSbXE3hfYXY2S6+Po1gsV1pHcTcf0/t13u0LLpDFEMyM7WaLEFpcXFyqpbTUVWKQt6jruvN8CAG73Q5BXcgTEdqVOcaOSKZZqW89pre1PMstiLMphHPA+flVkb28rahuzEEMwRAZu+0OACPEgDZGNKugbVjDZF2r16bcB7m9uY4tc81LEBeKwLyQETm4pQiavCNM6inqSZ2ETxxZxxahbVpEBbKZ/3/23my7caTXGtyIoCRPsuzMqnP+7qt+1H7UvujV6z9fVdqW7fQgMYC+ABADSXnKobKqiFxOiRQZDMYc2NgAkBLDGfdhYETghiz+oIgwKGtkJrmYQl/Z6yn3uUXXgXMcc8oeDBz4yeOHjweU7WUAIjzvHrPnh/TwiMXZKQDBIiow3jLcikI0eblZdm0oQajbv/j34lK+Totli/11iYXuf3fWnNylpLtJj2id/efxQGQ0vvmxx3uuAXhBy0avGYH+rPr3c9F0GG1cbgC4EODmhTZ6IQCwgWCLgEskXOPo8295nGMGhH1sikicsPvT4UQducOnMt47m4qIcnz0IZPYY2QHnEMguKe7zESu3joX0mnlzaBmLul7XyB+CkhXCYxtfv+pqdDZ/AHn6C66SknMNp4L0s1NU4ceU/4Qg7o8p73g8+YSi67Ldbrv+9y29zfXTf2tzwl3t68PFOcbwnKxARFht79Bfy0jhnVttDbIYCNSz61o+8SkjBqwz0fTl9fu3H2+dyMJQNuAX9K8g7Xld61kWrTwPXe2DyagixFuUkZ5gBCcsObpqw0qOUwNijFcCOrKt17p+DyRr5b2mV42BGBBEZ2l4UZkIXaAgegEBcqTWOxzm5fYYqLv+17BUR8V7Xs59hlzYn0nop0dr69j3+KS++3VMAaxfqa8ms/XGqKBD1IVcE1odTtPCrpW0/jnBEJABLCIHToaunAv9edzY161ErKBX26HwdbFleGFrmP1Pk4JycDz/Jfn3FA9NT95koEuKIxYoF0K5DV2lVb1JoeL7wAA9Y+Vj4xv31P+AgC9gL9l/zZ9JUZYZW2QNNzZ+/cXGe3+VRNTA+x6f9d0Vv0a8phOcOMUZZtTzqPv2WKM6GJE7NTA1DuF9rMeJ72O0TckYLJQHVUWmQcvXK2D8+mqzg7GDq9On9k+t6xZdE8MUo9FU+vB3E8FEF+Ueh6rdOt16v2wMgjjbixtvR2KgX5u+dsOElirGzRdc2e9hLR1m6tS0/Ch2POVw5U0Gany3RyXXVX7OX6v5v58SFPb33F/f0MfPNSuhx4MxjcOnkNurK5r+BAoG8jW4Hmd1tvm+LeO7bPMMssss8zybTK7cJ9llll+nOR90McVEvPC92Pyl8b6ywrd75jkgec0V5AqXp0Z3W7IiuK4liZOsl3namfy3ytWsxJbHdDR7bwkNjBYIJmmLUU5XIFOw/y7EvubPAa4YtQ3qCjKBaoAs6xknDJKEL0giSCagiexft+zvl8XCaSByqHe2iVv0JO57HNXrIECArEx0uwdBeaKHQgIYHPm5/l4IsGRFOetjAcEnEAICpZd98BvhOVqoUxsKPiyF8EiqipQhDLAVSvMhpoEB9eWyyV2z8Djw2OJPW6AaEqMvn/CcrnMbQMgHB2fQEwJ/Pj0CDonMAs4eziv34rBiZCgQO7Rcol+3yOEgMWiQ9+zGU64ylggTEicDDgkEEV0yyWeHh+NsQXE84D+hgGcgXHXKJNeaiffIrm+c5fZ2tuW9iRgyBWpq/oMfEpW3LvnAklUAG9AmW2cW63do2xzB7kBVXoKGH2frN+5t4jSf7xu9vsdVqtVdiHPFZNOXcyG0iwIEK4cB5O6/mdRF+/cJ/TJGM/CwErTC6QGIwKe6OOauruqFRGk6y3i5aZRRIZi2WPlrC0hcfEJTgDCBuivRfuTXX9qvtIZGt+RpQDYCQpuX5Tha6Sjq4WrT0EFjDcKwjKW3aIAwYCCyFSlU7t8B4Ak0891d5tq+uKgMYOwwfOfexz9tjDgL1hb0XYSQ0S8FKTrHoDGg09XARyBcB6w6Dr05iY/bAJ4W8DS1nV7mx8CJkD0UhQ+jtVxMBUsv8H6ynWj51jLrSm8N4AQhPTNugtzlm/1n64SmLY5LXfb7jrWGuB+T5iGUwGWmwvEGHD35x/4WuU5uyUfpOfg+akAYfMCmC5A4i2IzhECsPxMeLj6C9ccL0hdj6cvZPGtLtan5ulDit+PrsPy2gMAiEt7IMJDtDbbDBvVc+2QwkQFv/jE0uZCNDYyFQCUDdgurts5j1V6rxo+RURIp9cnMzhhEQRprx+OBgeBmcHv+T3r6zJwMVE9v2aznJSprB6swYn3bEAwv8zbCRUATGxhliAgG3kjAhB9DUkZtPNBj4XB1SxCQGbS+rUey5ZCyO2PiCysUalftjkxiYLqoDiot7J2fpMMjEz/RlX+1wnl//4xMqUv8FM0iHMiMjR4bW94zy52BFQO8kH6QANUBSlVIGpeB8a8Fsz7VRlgkNB3DBQqAF33rOcgEAto1yOgx9bWnm7UrSG2GGuzK/ZQOnkdGuvn0Ljv+fgxRmpVsrVfue8rAadMxTZGYF649LYLADcHeqtHJBtm4wzKYHfbnTMZGBYOP6v73cU7QdfKU6GKhMa9wsMdvRj3/FV5783tPOn7z/c8hip9xejnD+obCglgPH835Alr226slQF0y0GOez7Mfr6f/IEfyucss8wyyyyz/AiZGeizzDLLj5Nqj/hR+X5s5p8sfzED/a8Ud/P5HVN8wzU6lbEkRWoo43cVeD7YUQ8t5kVZwZm3lQEfGe5lDVA9DIwDyDGUnSlzxoI7KkrBMd729um4Zi440zrHKoWDmVK9mzPTVcPM1f0e30+Mg+rqoy5GxKjlxg58CpCEEUhjPUOUCV9n3fvr0lzQ7nsFD3sDto9hAJ+zlKBpJU44QkkrK/NxAtfALC+XOFqtELvC2owhIj3vEBedFw4yM8Drnkq5+HkxxjqzYL/bYbFc6vuHkDf57AYUwIgZLCLodz2e988GNEABfHPZzVtG2IT8/EDA2dk5mDVWu+fN25iwKvRybEHSvpT6hL7vIZyQuAeEsE+MdLvXusFtZfzxBib6B8WVSHHiN33kGjDFe9hoeSy6BVarVVGoZ7aZVgJV/QEQcNIY9H3qsVwsG2WKtzNO5i5WWiMZj2W/WK0AEfR9cXYsIva7YLHsIOxRul2pr0wdEXUpr3lfZiY7hZDdvmueocdgY14mpK0bFGgU7e6iy4Y8IsDj9RWAoksser61lddAcUuaMRY3xdkiXVtbrAo+t2t4v1dxBvSFFHY5Jj7zo+yvZo6fSzk+BAh6TMpDIiiKR2eta7/egLFFxAV63OTrIzZ2TUD8FLCIHdRwgRBogef9M7oYLdSCoE8J6brUp4dJWH6KZjSB3E5EBP21stEFLQuZsIYYr9xH0gfXUucX1PpwZtVQphSsH50KvVyHTP6pdNs43eWH/+P3/8Zut8OX7RsDtFfyWuxvmvh2+XmN6+t7AGW8eDMwbVLgL6r+P3zda0BH3WZz/HVLof4YnNX1wNTzJ8Dy2lDPZQrMfF1KDw5wV72S+3nLNa+zVMqKAMQQ0EW3kR+Uo48ZgvY8/H0JixAQKSIC8PAmtRLcb2SIGhCxj1MKmrODo3AX3Qymct4Nmtjf140uidQIcsBAn9oDNOPRAGipL/+4/v3nqkccEBo+Nc8TwyLIU6OvNwVDEmm+z9YawzmGDCAPAFZdhyV16k1IFx8thmGGED4boQLIyYFzR/+CzXu+6hRdPyVW1rnO8cY+zwB6Ccci9gK1R5iqpJpyykZ51b3SXD0okIPy71OHRfxN99cHZGocBqr9X9WgD84fVLG+8/3vYKAPxywB3INI7XEjqwhAuW9S1U+nasXzFao8kj1rbd/vIFizrbu879n7nrGAAyBEuLXJrV6/RdHQKi8BxZ4zL79LW4ymgdELQ0HtpleNjJ6sL4tkWwb3SCPQvPn6JxtkhnJ7k/aBPG8ECAIcff4N+z/3SLRFEH3mdQDWrHnwdfk215HkhfFagPvQtp98TbVcMdvOloFev/4reZ0Un6fHjbr6Ivkzu2of3Pc9+nnN2ve/Ov1aX+frBQ+55WN6fW021iI099YdWEYeuWaZZZZZZpnlr5OZgT7LLLPMMss/RgI83pdKAc+nJetfpeyCJze9vketzikwU22oHSk7IO5i+fZQXlA2pNll30BJmvMqvk322LLS5DGrzGlKAVneQZUveq2mSIjkygllO6s+VHlK7uYdsHPSpqZusxV0TPYJ2xwj6XUU1DVtJJirT2CFiIddwhMAJsHxBBOd8YC+P8cuBBx3XX7X3fMug7paTgJlq3Iur+IC0RQ2rMwnfb5gsVxit9shBELXFbftwZTBEOTY6Aq8a1ztpYH5j4+PABGWi6VeGwl9t8/140qi7e0WpyenCLFrW6Vp1CiqizuSUp9WhBkMTMzgLQMUsbgIeL4pupQfqWpwF9IudZfwttT8CECEc4z3KObatUJzXVnIFoc8xIBFWCCkqHXEST0CiILr7dP0U0xhFRedstlGItYmDaTIChnJfTgD8RmUUffvhAL8c0pZdd/3CSCCSEK/TQC+5pwJ7kAA9jf+jmuETTyoTBPcgbdV+bGAsEG4dIWSvmu6FsTLC6Trm0ZlhsHnVHeX6m94z0tyCLytpXEBLuN0CYX5XAPpbB4MrukmnwPK+YhLpKuE+BshkPZwlh4xEPqUEKEs9FVYIv2m8XT3X/YQAHETEEMHTj08rEN/ndBdBMSLiIhPSDcJp6Ju3ZWJfoeANdw5ew0eD8HkkWL4O8tZNZzXRgxT8hLQ3fd7dDHi98tPeLi6ytdtLmgEOnrbuDXW+Uvg+SHp+/tRekPW/8+Sqfr550BFr0ut3B7/dugeACQK/ksPIUIgNTQjCerCHciTkoapQWVgJ03BN2NNPXxPPLgZmz6g7H9l+fWvkEPj/+S1ldEFAAgDEsxNe4CtBss1TLpWKgGLDDh3Twc189DWKmqoqQaUzBqCJjFbuHTSdY6H2plllp8sU+C5//LidaOEKgOg8U8gozUHT9sX9XYozdgo7c1VHghowHNUt935fSK4pcrNeQW03gXgpH0x3EHXXgEKnr8mQ/8OEoBe1Py6tsryuf9VrzkTv9fAeXnuAWD/hfTPBYiyge+PCYROLgAAOgplt2HYkoLtdbprWzTfhTeuHV4cx94zOr+SzORDx6D+IUOMj8iUy/sGMK++57jmze+2JvwHGezMMssss8zy75OZgT7LLLP8ODEl8Lcsl2cG+t9PqIm9+cE0Juv8pVRdecAKQBFATq2umADttZLBN48N7DEb6+sa5cZQwVEj1pkBrvfz4Dm+fc4W+hV7CkCO15xd9IWyAaXqPTQdRkps6VYZFFWwOADeMHiqFxEIuNI4C4DOQKpARvAVYLVYIHFS5U1UJvqeEyCaf7fKcm6PAAAgAElEQVQeZ3EX1u2GPZg3AkKJjd4FZbYtVwswM/YGesYQISJ47nssTKH+BMGppRjkBGEdsVgs0MUFlqtlfu1QAaAATemx2hoT4Pnp2WKcK8C6e95hn/Y4Wh4p4NvF5m283vq+r+rJoPva7589PPW9/sQlrrED7yEUl6XZpaq/SxfhDBlhQUo9ODH6fo9k4O/+JkFdBzDYWbOmoHAX3oL3uXx+r2yqpg9j72pcdHVT7XnpuoXGZ+w6CAQxdnh8eMTJ6Qlg71gYDfp+KTGedzu4MYwIsFwsELtOXbAzweMBtAwLsbIl3H+9w8nxCVKfrCw5XxNj4Zaq5/haOWSGCmkPFsGiW0GEkVKPfd+jv+kBfEWgU1VW0V0D/ngva4t+3YDeUtSdo8/saJTVjTmBQJd1ato30vVN44E0Qb0DvKSmc0e6U82iBtknXVseYKAPZd20C32fQ7HPN6KKy98uP2N/9SW7FfXfAi4hEAQQVr8tIaAMxjCAGHSs9CeyMPZXCYAgbPS8x1D3l2QbALzfpW1Cwm0F8OqXUyvcAA06nSyBIAm3NtS8BG5v8DYDhCmp3cMPZWpsm2Kgnwlw+ttvIATc//kffZcNIW0FX0lBdMc7b1lAd+N0J58PYC1r3NF9/TiAgLMzAt9qPPRvAUN/ptQxVwE01kih+cF/r8cbNN/rV/W1xXtz488L1TqkYJM1pAm7TttqbaCgscu7ct9ENmj0TTIDPQghQpmOgSiHN0EojDFQ8Z7CYgxEESR4yAoDTmtGurCtFWw90MAx8uKKeaos63nzNfnVmejfg4E+ycLPayPktWTtZpdEGZqL0GFBpJ4HvM6r+ZVtXkQGQqAGFXZNmT/KfO4eCISNvS6sHgukAtbz0r1aa1XtYrx+9fVNmbPbVjS5Qn/DVuzfpw77pzDQ27G4Ol9Xel4nmGSwt31/Bx3HDPQ2XRrcM8zH8Nrm+hCqPuOAp5QFIipWbjXeBhDOGSCRZq2EKv217Z3urM+LvetGdA1zbfHP1yhs7qFMrT+G6zoYa7zjcwhusbf+kw3E8zx6oF+RvrOOe5K7n4gogO5M83qIt4JcC7DgCzyHGyz5Artwg44Bwjnip8728pSNjq1EQQD4RvevR7+vcPef/61u77HBVdg2DzyDNGVAoiz/u2qvPzIm8PFRckWOxqa2EN8uVA/oGDPNy4X6kbUwPj98J+uyKdft/ul/IRQ//SHGrJNo1k5UrWao3F/nGcDMQJ9llllmmeWXknhyevp//9WZmGWWWf658pJC7E33/10B9Pzmf8e8f5voXv/b3vv9AHq5IjijFEX5MKqNAXhuJ0EUJhGKrFuncjzcPJdNYXtPfZ/pRioleLVRdKB9sBF15XXrIq24Bvd3RT6ulOzNfrRR4YzC/4mVXWfgIpEyPd29nkAV8yxsSesGPoaQlb+Dty6Mes+nK1sta7uUjMludxMhaiEAIugB7AEsQRDsIbsd0mMALbWucrnUyh27t7B3pyszxs7cpltapPHaUlIATgTFda3XL5CVAyLmSjwbNpRnqZt2rSPPo392XVeU3gNQMsRg6hFjPFv8QjaX415O/MQACdzldF3d/icAlgB2P2gIOiqPBbCzo2cQluAnQVhR9jCQ23WwlmpGNm4kUpTyVneB0Pd9pVBU/WcMUYEAqPcDL0utE61HsvohITzvn619isXcA0KI2k9zl9F8sbUZ79fMnNsAM2Pf75FuegD3IJxBgfPnNw7xOwh21ee0NEmJaPp4gjytwE83kKcn4GkFOibw0xNAbczyJyr1MiWFe1/+vK2wpfGt7WVnaSxR2uIxgAXGaT/bcff4iMXlZywfH/O5YzMe0PwKupMOMFBP42MS+i99fuHlcgXmhMXpAlgR0k2CPAPhuCgeiTQ0BVAAynBEoKcVFnjGAjrW7AnYE7DwUc6SeCDgiAVLAM/2Xk/227m0/e0IwMkl4enpfeXn7PND9TA1Ne6bc3pw+dvvgACPX/7I9fr8rNeen1s/tH63AmH3/Lb8ad52GDb8s7Uef90poO95eu9a4Ei0rbyFDfdDpJrAJ7PwRgD9Wx4+ZAe3a4bq087viZq81i5SgcOg7KFzBFhImErxTQQKKGsqc9Eqwc6TghZC4/i5Qj7K2DwpGpLBQfP2zcyAcGJebdJs0OLq7x8muVyG7zbVvyRXVS6PBuBAC54DOg4GG1eDHUdgYt0JW7s58zwgUMjzqs/hMKMJNTrTECfJ3Phn8ByDugMwFY96CvMZrjPfDAv9A9vGt0qo28PfWF523Y6qQzQ3NWN5w5ZFmR/LOhFNX6jvwwE9xRA897VqrIxTPFRH7oN2jX5GxBgQQ0QXOnQxYgXCtsqPi5gh0xN0bSIoptUgYAXtYr5e2ZGC6HmdUWV0au2xghvHaDqBYFY/zxBSY8G8hBiN/z72l/9HA38lu6mx3I438FAjKxx9OkM8CYirY9DTCvFTzPUVbPzqvzDkCaAjgK8tBBMJuqOA5ckpnh++Qug5rzsBMyAIw8cTdm/pK+RXv3bN++TN/ZRKu7Mbvxt4PszP8C/Uc0Y1R/jc0bxHno/a9Pw3AN9i9TbLLLPMMsssP0RmBvoss8zy40S+Xaf1twXQ/80M9Eox8aH78Y7NYhadykJFKhg7Y6/YKgMA3RV6sWIG6/V16pKBWjbLb1dPq6pZN62BAlClmTevrsy2GNnSGFYrSJqSAn3OQD+ngIcYsAbhawXkustrZgOKhQ1w1RLMzzY1irjC2qjw7lrT8yXSmgMIgKO4yKAiM4MhJfY5gEVUlnGq3GYP+WR+FCtFkZeaKogMEBPJYDoRoWfGMjojPWEFVK5DgYBTxLXGVlt0S0SCxTBHARsMVMggoZTfRKDsbk4goioGOkzxq+D1cnlUAHSv7ZqtbHUA0TohEJKB3d1i0SoAvF1lJbJKiAYWSFV+qolGv99jb0x2gsbn7q8ZDIbQbVviVFjIQAFWO+j5l+IafqucSXkuWSz0gIBgLNcu6pgQqUPsoim4DMg0IwUx9/hEhJT6bFCy2+8ACPZ/Jlz+X5d4fnoCWPuICLBYLLKhBoBcd/DaF2Df77BYLFF4ckUrWjM73NU7J4tjz2ztRbDb79Bf7yG4N7AfmtYUvfM94jEfKyWwAxGwZ4+rbgNgW0ALaH3fUssUGs5A9ZDT9I0XsvdaDPRD4vk43O70h3MpeVh++oR0xdmtOwBcyDkYt4hyASBi+VuXx3BmIG0TAELYFOW2x1zcfdkDcDY6FVbvIE8igv6mh+AOQupS+K42N/C6hmAtMkqijtP5I/sZ8JapVS/478+/4/7PPzIz/eKCSruVc20MQUMD3L1IP2/U3vnLGmcACPd0314ugovLc9xc3+brTwV4eCXjx9ZePEa5j2xjzvXH5LWWO2rbMoyB3s7jdUUcYqB/THyMqsYYtLVQjORUQnOsY2MMoTpTZ3/MiKyvI1EwJ1o6wcfqEBBjKIpxhLzMlZI19ebS95lpzsKZgS7CYDZwNbOSra7rtVtovbIM41wD4/qqmdgvlu676+XnqEm+mYHuCQzOuyFpPjcALMimsAUCFhTQWdtx482MIlodcH623W8e2JnN2wCsXhOjt3WpA+rKSp96eYBTc1jKYQjGWR5G6+upe+vvrw4g/z512Lcy0H+lvXmdlZZ5XtZ3h/I7PJ/Hx9yHbC6ojn0yrcF2l3rL5yBhsHBAhBrg9DZX90/KhqUhxAyow+5NfcJuvy/7yLynLQC3phuqPFEep1m4jNfvqL7f+QK9XGNvPW8h6m1qVwUlIwC3tl4aenbxUFptWUt+B5cz1vWuG3Tm2Oiia8UOG1svknpmsrFJY213YPQgBPx/X9Trzv/69Jvm848e3WVAf32FRJbP+tm2dnbfUCMD+WrP4IO1FCWApVUyWzQA9TkcLve2KTRPBorB53S+fK/fAuclX99/bJtinjd/FtqDvHNMrZtQDLPqNGsA/UfkfZZZZpllllk+KnMM9FlmmWWWWf45YvtbV1zUcmgj5mCMX1MUkv57fS2qjfHwd3OrVqVxSFtL+Y5yRhnV3CgY7kmVm/fB9936L1JUj4ShxCFVQIlzeoaVt4odUM6TM8gPibsLz27wKvAcUCU7Q0ps8EYD4Jt5czfNGrPbcqZ5IYGwbbZBWECBXoEqCxIX17XPVupHVquMr5DbEyQkpHXCqlsgJcbqaOUJABWTXXJ9FGU/BQX1BYSUEkJKCMZWjrGr2kvbktjA2focBQWHhRld6ExRRm3hex0Ec0ueQRI1uOgNKM8ZBSElMdf+yPUWNgG8HaaqEvOdrSv3A54av5vc0yB+IFSRLjdkCm8CbQiJGB0iYlyAU4/YBTUCEQ9ZoHeH2IG5B1iwWq2w3+0AJFz/P9c4/T9PM0gSYzDA3ID3PlUuu1X5ktgMEGxMEFMgkmkUmdmY8mq84kYpwlzCISSuwCzBcGx5SVp14dvvkcFfe347GkMcxK3jjEt1Ty13VABuGZw/lza9j4o/4zVQ+ZaKK/TN1RUI5/h8cYkvN9cAAMat9flbEDatV4sI4CIi3STwlsv7XmjbWH1e4vnLPoPsXGkvw0YNeNwDQXe5gPAl0lbby5ncvTkEwrlgGhj6C6VPPY4uL/H15loZ5wRYNAlACP32Bt1mA1zc1aFAJ+W0aiTRgPO6YZ+duQIUCKF46QCAkzc0+qOiw57lu4jk6Q9AXgu84TYVIhCCzZMK3sCMoGCsMpjx21AxTpQQWL2zCMwrCBGIGUkIBAYz9H5m9ORufPX5RN6/3bBP8lhdsIgSguFXAvH+cpkAI0icJYv2vIN/Ni+qkaMyyh08z+GYCDqHA2jNMxU0EhGkkct+BnPKrtuFJa+fmywTvdmoYbj2nmUWYHKZ/eIPI8B8cFkx2vLPiT0ltQBgsx+gai9JlJn+gQICHEz2JxTA0b1qBTNSitkDmaZDRHjGDtTvdU9TGWozxMKGeQ/hKv1R5g4U2AGx+yMusKNrXWPRrYU/MuDcgWUa9/HJvfd4E5zFY7jXshE1kA9UgHMWAV8x4qdgz1DDcqGyGkvMGtLEwPMbX5pY+rXB6e3UYhnV9S9ONaWtjE16Jt75XdOW3pANzSbuPQSef285BJwDaDyW6ImWVV6Xy3v2ULPMMssss8zyq8jMQJ9llll+nDiA9w1JzAz0v5/8pQx0OBtLmixkMLxinHvsZXWLrX+BYmYcZ7DVFYUAqGZqTygFQrONLUDcOKfICsW84XYQ2q3Yg7K/lH1e3KC54hNUlDfCjNQzIFy5Q5esOBeIAY3+DoXFQ14unsGJje5SgF2OSSfGRjc33O6iza5nntDWu7X+hBARlkTZ9fbeQPqaNaUMDlXYP/c9emYcw4BhAZZnaxAFdF2HbrFAjKGKw1YUGwBl5kaIwdqAsuI8VmfXLTLAXrOTMxjBCnaHqNSr1DMWi0UBXrWQcsU6Qz9Ecy1O6m6ckxko2HP9+r7fG5u9GC8wC3hb2hHDXbjflrZZlbmDkrWuZRgz8UeIu58uf2sAXpeEcOFtxuqUzA1sjpHuYp4PUp89RQBaliFEZaCj1K+3cUjp4w6gA6rYiV2EpJQNIPRWZbGHaNCA3+fKfmfOMSNxQt/v0W+31v80n4eG+Pq0ACBnRlo78HZIUrVNMu8WKOOCjzkySM9efSS5PQzy4fU/imVp8hpg/l4GussYQD/8oHNpr2qeJsYiB9BdfkIXQx6/kgjSNZvZxh0WFxdINwmn/32G/X6PxKwu3cFV2bTc5jpmOrOAr60kg3l7kDVICOESqhQnYP8lYRteQZ+/sxyeGsc//H75CSEEPP25w5ZuM5AOADcs+K/FZzz1V7i7HdfrUMF5Rmooc77WMY5v1RPIV/p6MK9HUlzGvnSN67QZaFypviSH9O8v6OUbOawnl5yZloHuDyjzkt/x/Vy4D3NWen7dVodzWstA17xFstxn8IMmxwUAbQgUAbpgYGoN7MSQXbSGDOqEPP76eiQlxnO/L2stX2/YWkuMkaxx0iWvJ1ha0Kmw+Eo6Pr5rNsc1WF93sHQ/rPX4seqSb2Wg19/d4MCB8yFonq8l5Bjoq9BhQQGRauCuGMI4QJ6kGEuKZczrk5u6tnUV3OtAqWt9X290BGIq616vPkJTWc5dd8jwkKOBQ3Pl4Wnn36sG+x4M9F9pez7NPPf23x5nXG/YMKiwxEu6hQHsx9q/WiARsHZdt20ybx4+bvq9dn8gH2fN3XVU5rnvP8p+Wvvr7vkZXx8fdd+Sx1djlvs+TgSgkMdlVP1ewGYQjRf6RCtrUeNcH8MJZpxra9e8dqwB9KpbeV9/CwO9jO/In5cMEDYAgMVvHVgE/RWDLmk0/qmXlA5PfzzqSdZ33uNWDdJHz5H8jne66WrO12k3Fmk5j3Xe67Sp/b0e1w6uh0u55faEUnb1LcP2WWUUQ/keLO5hOTtY7scjQF03es0eutErNF11sKaqynlmoM8yyyyzzPIrycxAn2WWWWaZ5Z8n1MIvB43uG237OC64/+RKiXpTX9+OA+dlSAM78HgCIKbwqOPFiQC3YBA7KytAvWpSielMAUxksbKpvLpreaAvT/UPUuf2ZWGIgRq+oS+b9wLwEboQDNh1Zli9cXetQXWc99ikcc7t2o41SrTX2TIAvQgEAWzstC4ECDMcCt3f3yHgDHzG6FOPLnZYHq2yO33XdomwAv759fVtVE8cQSEiu8I7hE4S0HUR+/3eQHDCw0OPrusASHZNLiJIfW9eAQjdQs/HGNUlfuLMns6qGP8uDiiY0mpbM/xdLVPcLtdVzmjZxz9T7mn47DsA65x3vkkQKFhJICQkECU4dB67aB4N9K1C6CxcgTJLYuzMrTqBE5sRQ3GNyOZ+P3HCslsixlAUZcmenetH86zGNMj9xZWQYjHQmXvzsACkrSvxFVx7aUhxOdjLrJAIyO4CqKq0SRBgcNwopKpzNWC9PpCBYfv4Ue7HnYn+lrRvD+Tb0/D23V9fgT590vj20NASchGQbszjxQ0jXkTc/889jj4v0cWA7nNASqp0di8FbMpu3jLSNik8f6EgevjsmQkg+uyqXrh9VZ8Y8TLiEz5hf3P1w123f0T+uL7Cuaxx/HkFfDnH9lbdrZ6fE/5r8Vkv2sqLA8VazsxsQQDcob8VPBhwcCqHwfO3Ch34Pksr7xrPRfFIcoW8AEyjS7Jknb6dLFClgqtErAlK+RQOoFB4yZ6SQMEmd/WdwVwRkHn/CBWDPLOWszEjdK52Xboo804NAsv7uLefklPkNP+N4gxXPUAG0BtX7pWlY2YN2nmNzRwVQCcC3IU7AHe/7GFV3LCvZr+mIaBXQT9q7FdANzH3/gIALIhmenpIZt75LO+SN6D6Ux6i2rAH9bUDwK+6Pu/LfI9JZWwlMva5gecxBBACgoiyqYPHO1cjUgfZs0VytXUcrQGrE1L/FRQ3p1Pvxd7bk/I6TFCFMDP36va7exCalGaP/U4hZZ4LgHgZwNeM/ZekBg2XBZB13DsGZZxz/6zzhggSbpR1PrHMqfcq7/e41OoYcgV8aBEzLpyhC/xmC23zOyAIZUA/+PhvmReHwPlLf/U1ue1VugLL5sH0Z5lllllmmeVXlxlAn2WWWWaZ5fvLR5WYP2IzVaHnNUuACHBnzFO5bVg2UrHFK0WEMyAB4JACUOpn1+yEyfzBd8aFuZ4BaUEIAHMARQGzAkEN0CZAiAoC5yDromm6e3JOynZ2kNIB+7zB9fer6mIlNGIS5nIgZbKwPa8LQYHMinnvLLLi6rAoyyNFiAA7CJYGbq1E8Gwaj71ppQIJklaG7s27ThUn+2R1eA++P9VnrQX9/R6LbonFcgEQIUZzC2suuz0mZ9bZW41rHShjP4bYKLH02arJWHRLpGDMf+zR7/eWUIIaLCjDXd+T8fzcT6jligeEOi91GfN2Sn18h6FmqsB9KlydA5Qd/laX1O+RYZL1M9T1850qvACoPwUC3zDCRstRBOj3vZZ3H7FYLk3hw1WbIXUJ7/2WWRluPSHELoM/BEIMESklLFZLK5pkxgxJjU1YFYtkyh2HBrlPYE7o+x4sgmj+8AXIbmnDJoKwQdoKciz0qh7KWFCkrj11PmBgvF2U3UYG60+j8eEwgA6adsVeyyFg96OA7+uxzQ89630PHKbvxx4q4PnqCh0u0H1Wg4hAhHAZQdfnEAjSjY4L+z6Zq2loqIUqH4sQtd99ithf9WAk4CaAQdY+bTwIamRB/h4kWC4WEGHs+4Tl5SecXV/9kP51SE6FcnzzlyThDrE7BbDL525vBcAXVSAT4RxrsBnkfB00YpF7AGvEdUS4JzxB3bK/9miCsslfvY4Ij9DwHPbE+vGvymv6+UO/H06f8kcNDR9WQNdXvZSTVo6tDH28LrpxQj2WjNvU8HnDbA8h7TKnHZK8tgHQBYUzWYBg8xNJwCIIJBESJ3AgXY8QWax1QtdFXScxECVCA7JoqpItgwKECAIGRcoeYJTZrJ4kilNisqURF7BckBntNZhesIYfCbQOy/zHPOujeBOBWq85UoHmlvAIUAcA0jlQwbuY2bDZjb6vcjOIJzmmOXsViLlsR1Md5T0cEGRb06BqjgLzaOR5doTIf5bms5TN23v0XyG/Vm6m5cBIAuBHte4fIy8zz6e+Ay07tr1mWC5DN+g+nNXgOenmDGa5VO370HjuiBTQIVhUDGOdh5Z1Lna/iO7zcngE6L6k8c6BQV1ZPxKq96z+PmUsAPAi4Dta501sX4kG6zQigM3YhnIHfltjmhpeRT0nXQDor3U9h6BjQUCEXAvIgPR0nTQEGG2zsZhQBYzb59qcfW0t7+v0Sl89+OPgxUZLAGnPDwd2GpyQwXWDPNTjuN4+7r0vvce3e5qg5vshFnp+1nSXnMzH6Ny/1AhulllmmWWWX19mAH2WWWaZZZbvKt8Ul7JmbH9bJl7cTeoG3xTEL1yoysFWcVf0fkWNp1vZF7QRdTpTdHgihBFg7xtr/TwTwr0wYlQ9TQwKPgoJzgTYOis9Kx/LJtZ0OqoKJT3hrAS94+UN6xMJjg3Yf5x4rwRGEH1+MC0Hu+qVCCQFMKzLKNimmzlp8FxzBy9ECPbeDjDvB2WWoKFZnVivVykjku9OQELg9TN67rFcrhCiKYUD5Sqo67fs+akuulIHw6olQgwdwoIRu4jnxyfUaGdKPbJbcU2kcrFYN4OKW26AefPoptXdVd/rshzX36+gwP1KCqKXPnMHwjkAd5GtuWQA4dLY4jtgsVwghmiKdQXPA0UFOFlAgbDoVgCA1Ce0XUsPtv+vutY+/19H1oZyJ1AGsqj7/L5POU66xkxP4FtB8lrzOsNdrqlQeB+NDEeACiPIrGex9/3qZMEfAP5MMb793GvtYujivbTN0g3+SvVW/WwGI7GCeG5c0V12xmpl9dywZfReb5sI3jLCRhXYCdqWCITlpwV2V3uwRftNW1fMC47/+9i+M552zzbOMmLo8HTzjHjZYXlxifOb62+OHf9W8b71Eoh+KubcICUsP3XAdfv7HQGX5xvsb7eT6ZyKttUIjSl/fnYOAOA7wT0p4H5sFfL4gfdeVa3x5dnznyEOmgNvg2MFaqxQl81by7leh72yHBo8X9CbwRDZ6kDdDGt6vXnDCdZvYuhAAWCpPHtYeBMXZXuapwgQNG520qgMYgsaW5skITAkjzPuMcTfKbt0Z3cTXgHs/2IhUuOxcqKcn3Td7mCHILNkER0QDIVFCAEx5/AibkzGzOqeXZDHW4Gu3dQqxO8HBGSgoxg4aF4OBnPNUCbd9P+toN1/tvxy5NEDGRoB5WhZs8Pbh8bQQwBdz0H7Su1qPQSQCMzpFJzlTkD28NCFiFWM6EgNlTzeOQAg1F4eEnpWw88+9UiSNFRNSuYRaQCeN/sryVsRKWcAG1cntmIjOWQgmdnMFZ7bDL22san3lV7Oa54wCHvDxEQArsJt9kKko9ylhoO4VlfuPW117fVKegFtOCsPd/Xd5KW0irLg9Yvra+27Gg78/E5XA+X18RQDfSjZWOUDz/23z+mzzDLLLLP8ejID6LPMMssss3x3+R7uwr7h4cMTlrbj85RPCwCq/CaXmOjjtBpG+lCNJwWkfj17Utjo1TMkKytLnEhAFSkAcBciyJSVqmBhBFa36bd2LRHhTKRAfRmtlayIGJaOK3nKq7b5OhZlKHEorrLb99H/EgGJi/vzGFXNkSzW9yIQ9qmY+7sioE89jo9OkPY7JCJ0q6Uq7S0WXd8nU9ZKk/kERhIghqjgt4jmkwK6o4j+7h7pDhCcgs8T+r5DFxcK2IvkOOm5OXhZubcBMsUvChMLgLHmBIRg72JAQrdAv99n0Nx/ceZ0U7SoAEkqbYLqi0xrUgwzBDCmqIKwkl2m1zXnvP+hLilCr/2ZLFmgAHynls+EWy0jQ46jxUmXK4FcBjDv0Pd7q5uAbqFL1axHCkGZbCkVBT+Q2zARsFwssPx9oe1Su0/DjvB49Skl9GlfvCWIIN3dgugMYU3Y397m9uExV0tU2GKUItWxwqyu5EM20HGPADeoPENUnx9VFb3VRbr//hrAeyidmulOaBlKLz//+ze4uqzSdYJAMhO9v+7RXUQQCGETINviCSNtb+xTDXDiZgNKASAH3wOIOjALdjdXCFjj6PMKnFJWlq8WC43xzILEOxz9tkKfGF+2V/j982/4lBi7m+/HRh97jigHrzHQO6yx+rzUcUEEG1lja8B3HZtyKh0C4YEU9E24B3ABooDn25uRN5LHau47Eh2x9gOk2Ec3n1+XKH3lCISd5SfHiPX+bGmQ5TlSQBJBz2mQ37oX6vEqm0Cg+fUJgjLayiAd2PmPClXf9PvJACicMhYoY4dY7sdQIYFyWoJS7j5TjNOfSkMvcHff7p0hergTIkRwjn+tbGHBrk+gENAZYBSEFPBBggih7/VJXRcRjZnpIE5igXACIAUcl2DvqGfcgC2IMZ51WbqkNnMAACAASURBVNIyoaUwz5k4k9y5YqlLgyr9SPn2lvKW1N9zA5lhWM0yByZA8wZQL27cW98FExki5DoQKFAoomszEQPHgWox7OvQAVuW2pap15TwKNWd5bNeO2Fc6u8fbn+RevtF5a2t+2PQ2A+QtzLPq/NjUHw8dvv30RScDW+rvkNTe1/KAGIIpOFkYodFiFVvM9a5LTKZExIzUt+jNwD9cnOB/7n6Q8FzmxjbflBNwk1mfYQdrlLzEnyc30Mi/jrlGt0LtZfUIHo5L2151w2szkeVzQsGrgm4tkX3HWk89IANnrfXkADd+24PZJtQDygAKvC8eubtoXy9IHn9kK13J55dv9Ow3IYL/4nr83Pse/BJ8SfKFPvc1wYvAeg+3vu6bWrNM8sss8wyyyx/N5kB9FlmmWWWWf6ZMrFjG4Hodh2ZQo+rTfOUEYDu9Q+cf8cO0VmtDZBuLB9xRaLUO2tTDJPFnhSGSECSZGzYClQJhDMG7oLgpAceggHgUsDtGuR9TR5Ny3L0gqpMKkAisSCQFSoI2bMhgEWMSBZPWiBZgfP49GCuY1UZ7ookEUGMUV2KqrbWmOPF0IFFkAB0RNlIoH96qnLGSLcEWe+RegVdYtdhv1dFVKCQLeqjub8PISK7ezdDgKINUEUXp14VY+SMuhoYrZS/AwXOEOTgGy2PeEHgCuwbluuweU1V31APNWRX/JUKjBqkO6ny5LHcCedI5qYxgRAuBTFoHXWLzpiIZnwSSlsM5kJY00Jb/sKm3DF/7N6X1D8xYoxInJBYkLa9KUrPICTob+/QnZ8j3d42qn7BUFGE0bG7hXdVpesIGT9Gfkb87QLU1SpYbV/fAkW8NT66s49afaPXzUXOXdxYXPSgtSAX+qn3XqiXgS2DcYd+u0UwAw4AiBcdAEYgwvLyk/ZP890eAezTHp2xPNNVQvgU0FFANPf7f1z9iU+bT+jkAmvcfJd6+QgQf3l+iS660pLw9OeTAucH0jpbE+7v2lr0PuqM5+4mocfdCDwfJvlM0jDL83WtpRJ2KAB3q79WhbEDu6N0AmFBhH7X+9Wa7OC6o3pMADQkyE+QwjIfz5eDqSB/J0yPI4fGi7rMptK0UQ4vjfi6/kCONZ7ETH14MAdJAUEp6bqDgjEZpcQ8VzY6QXrFQkMofjpiIPTMvtDKeawzru9UZjtnrjkbOoeaYVPNJ0CCIEgo8dH/5UI0iIOOMWg+dAUcoMYQFKb7WxZB47WHWSDMSPD1XPnP25RUfTC3Kl/yVkvfyYdNnp3557+S/IrgeXv6QP4G4Pn4PUqfmXyOGRoVdq19F4IQqVG2eflSYnoV6zxELIyJ3ng5FzUIFmYNUZQSUt9nBvrzf3b4dHGB/339B2CA5PC9hya4Dp573yRA92bvqblqoqEwWPsOvM3lEEs+uXhZve+J+Xk3g1s24mD6tjLWeSXflWQDYlI2PAjZ+Hz47ENpvFty/nKQsHLytbw3QPrH5VuICQ6WH2KdzzHMZ5lllllm+TcJff6v3+e9yCyzzPJjRL5x0Q9b+L9zgf5LLOdlCDPM8hb5+KZMp7KQlbFiXiQpVwOZ8jZDm1khaHCuCJKfRAGwpdqlS/OtfXyAsrgyswclnebqyo23vzNEwJJMOZwvU6V17gPmvs1i5sVg6mkKIBIEBJyB8JUK24cFgMWLBggnicEiuAdbHEvdoQtxMR6Q1jXgMdT95mMEjkQVIY8D6sKxaBxbfx+CurnuQjD3rsgx0tmVrNKWZHbnDsHxcqlgevW7gC2GpoLmUQQ7URCeRHCcFTY+bqy03k3TIkqAQ3ceiyKD3D1tMIZpQN/vsFgsNdYgCLFTBcJyeWRKXwW1EzN2TzuEaAA6S2aHOEOrbm8HlSX2k7pur1XEdbu5a5RizWdV3wJth4SisPbPdwFxU4jOdxSx/ndaadAzIG6fERvQJmQWooYHCGpQIVFj71b3h9jBmW4KkvuTUJR45n1AjDnndbXr90g3PQR3FaNEC2H16RJfr67hfMkgAFEoxdMoYkvR5djqdi4BeCBgqJ1jbpl3LxX86JefOL1k9ue7ZZzJ2mvCm0FmIawl5OvPpQbzL+xJhYmeDVrgSwjts2mrKtNuswFvGYx7AGcQfDUvF4zlxcYMNnSMACHHa6ZA2F1fIVgoAuKI8Ils/FKPGD0nQID+S8JNuHlHWb0uU3PjWoDV5SVCIDx+ucptzou5Nl6p7z+rh6VBOwbI2itwJur54oGAIwBPKP101S3yrd0R4fFRjZQcPHXGccOGrcZGT8fzHKB9JY+cdXdsctdmO5COweTzirFxIcUDyPOgXADg/OIU+/4r0r3+9lQpt2tvEy6SAUnk67xMz6oMqYeS+mmUx6KHcRWWxAAcc+FmRyrl56l9teedWrqPoTVEqMvbYcwgOh+DdP4K9na9pOpOASdu1mAhp63/RzufpAXal9Fs8gOhixGRYp4v9R593t7CZfj6Q92xs42VGh87kRigqzn171p8Yt4fEjgxEvdIKTUu3VGWce+Spl2ItsnX583vNFFOLBG8vkdZ8DZWGSR0XYfVcmXGZQaS1exBUFkH+71eq6IGiB2CeQ8o8W3VbTsbEzah73v0fY9k60q22OdAWWsLlX4CeL3aGpuT1SHyGrwDIVr70HcuhpL1vFiXz7isKJ9/6brRme88h/6ddnwRr++1DmJ8RGbk9Ou8ccM2t/+beSP3m4AYW8NjDO6t5yu3Byb/0daWMQSQGQq5a3OpxiBAjTQXXYeu67CIHVZxgaPYqSGee9Ow/Rgz6xolKWi+73v0nNAnNkNPD5PgKgbNlK1uzXDF936+LzDDcBsQY2Vk83LNTf+a+9lgD+hz7JqlYXT7VWt1ZTJY79lqPbuaqfbLMu7LsHfHxPkmy+20m59/R8C5TVt3lUHW4AnNns2fF3w+z67DhuNTyXPWITSZQt4TNkVbrSOAtg0Lisv27Ob/A5Lngfq5w3zUx1XZEQVr5+5lgfJe/dDY4XUo3kfMCP3gTHlgsp6N4maZZZZZZvnVZGagzzLLLL+svNUl9iyzuOge0JXPQFH7mlQKR5hiGuLW/EChkY93l+1mWOqfDubFP+u9/Gi7bptNBgCWrBjRD2U0+HFWIptSk0CAJAUPgip7z0D4ClVwNM8zxf2RAKdCDSQLAU7YFSPAQ/XbIwQnIByLsxE1HnoNoj+S4EjIwIfC0mURjY1OCihkN6ym2MpAM7IuCSDgeb/H8WqlrHMUy30hQYwdyBgaSwA9pFEkw5TyFJ4BWek4Ql4eCqDW7ouF1R1siMrCEhD6fY9uucjAemJVGscuKoBvoOfxybG5WlRX4E18wAr4kanvdonrNWqHA63i6K5pL0OdR/2X3SQPtEcyOB5plw620AlN1Hc6JjgQJBYnvc2rAJAtw1n4GrdaFeuRCAurC4i3N8p9WoRQiHgCIBTPDawgESMBItinVClqSkl6LkQEJ5cXeLy+zlc4QMEYg2xjdZz+PZCyeh9K0/vXykeY2cpUH7ZNbevRakIAMGv/4xuNdZ62NyCs0V12iCEgXJxDRAHXeNkh8RrJPD8ES2+/vcFic4EQOteIwkN9iAgiLtDLNSLOwZQg1xq7ufvUIZAgUlTmzmdgc3WOLU3ynN4sF7wB07ZpWxFriI3iAuDx+lqB8kHZng4bpIkzzL8eaI+nApyfbSB3Opt6u33CWLy39I+ChQh2qBTdogr8GMrx8G7A+4l6E1mA0Nuv46u9Z7aAh4+lA2qhe4bGc06vHY/2/Vc83Ou5oyrNkzNCJODrneBIMGLevya1i1ad1+TN8csfqbhwP8MQEAdOWD3LPAA4tbn5KQOl0hZaNedw5W43xKAeWKQ0GmcrhhAyUB5iaJ6fAfSeM5Dg9xIAEjVUUV07KaE9AERcvN+gtINiSDeu6Rb0Ld5zOHBmngPI50Vk3GDeKX47D45/pEw1ixenCbEy8U4G9y5UIuQSqSldOS61SOS/t8/wdy5EU51TWQCmYtDoAB4LIa8yK2NVz6O3e29/9dpnuJAZrrjhzxpf+g+X77HOeusa7teQqbr/Fmn6jrRTQrmmnieGF9hY6udp+Ev55jB8fqZ1Dgc/g13jfy5iQKxAvTkkTupNy8DznhnJPT0IV1VW+lN+Eypl6NHHN2IMbl8j1xuMby1sgj2lZMT3PnehmnCgRbu27L9n3fdSC538bWLArL0bvRTCaNhzbMnX9BbBuGf5XfWOYZg/go+rL7zRsHvCd9He/r6twiYB9OkmP/ruBswEUuMsqjyZ2ECey6UhC5R93L94qzPLLLPMMss/TGYG+iyzzPLDJS+e3zvaVAv3t6gGmmcdOP5pMjPQPyTf6hbM2We5xZjSMIPllfp99OGx0AVZGZs3hZlVTFnpYQ/IqTrzt+hcKO/E6zbaKHrZXexJuadWSujjdSttLHJ331dixQJnQniM7mItFybOBLhDYdqeMXBLxpSGAsHBlM/Hpox9IAUMHiA4FwUyBICof3U8DhBDvy+7erdjj2m7MBfbgVCxkIDOEJWeUwOqECmQHS2G6qLrzDMA0EWNd56YM0OJ9wlgQRRjX7sRBLsJxXGuFAKBToMqiB0gyMp5QYwLpJSwWC6Rkrr07roFgsVL9zaxe3rO7gxdEd33Ccp2BPap12dkxXFhWgQHIG4YnFUrd4iyUZDfLIdqIFmP7hqFjnOgGQCTAk8PdkUGFqQcqzLx8LEqjBy4ydHfUZxAupbOjlx5PzieevbUcQnW7oWkv5+ivT7Y70E2cCCdyIAc8yCgdRBA2XSA0HVxANYRUtpjzwn9l76Ubtb3fS0VBsqKSM7cWC95vYe9H1pXrp3Eo/pk+3vISs5WxVTKxcEky5lIk15pB3+NfJwN8iNU48hz7Lmwjb0XiJcR6phA8Hx9DQKwuNgAsHGEBf31lZVhQNiswdutJgcyYhnbzE2IFxttWyTwmNzBOnZKjN3NNe4J+Hz5Gf2XHom25s76HHETjbWjsr/6UuJvvlEu+ALL3yL+c/Xl8JxYzzeY0MWOKdw4lQKc+/fCVB3LqZwh4R4E4LlisAZStjEzY5/65vnRGFPDdlNcuduJIbAu7XFmOlavQ9Sm0xEAd/XNbDFD2n62Ayb6U/utPqKctUPlTqP3IyoxyocgZZ3+q0C6jQMnrsm3fPhtjwScoAVAhQjPGMa6LeMNwcKUBIV81J0wdHwXQs/JjPJ8bNX7vR4jBYRA5okBDXxChGyY1gV1U+ws4kDKdmdjmvuM5/cm8xDArCxMBFPUR00nhKggvu0FEicwGyO67zPgxHZ+1L5sXK2G1sk6ydc2v/gavoZQDh1zJie+V4a7BWp+qfc53vcAdRFdWnOMEV23hDvOCCihaXTMCpUBn1R5ZfMSEOCuqDVZzZGzah3MY+m1rljXcjn+eX7vyiAU2r7gJSYww7WqnAR5LUJ23K59Srrjc3UZ0ou/j1ftg2u/cZr6ttvrNjvM3QePzY34uL3ataRrlkPzyjimsZ+vc03tiQ/IsCeNHpKfVfKUveE0Uxs1n6Uv6QHZeCk2LlOowxkM5j5L2+eeYONmJFLPNNZ5yFOt9oo5T9Cxs4sR3WKBLnbqmSPEPHLncc9Z58JI5lWDmXHSM27A5tlKmeoigmQl5gZjYu/gQLpAPWhs3TtV1ac6igjBDJvIvH9UHUHHCjPGqZtlM7YJpht8GQfWdlMNmjNLHn/qra7vOfxZuSzLJXXjsGtKQU/1+eE4XOq2+lItOUryg/1M3v1UaxAIyJnrRHAz73pey8bMhyaEwbptMq+v9K2Dayv7nvuLX5+fWfou5ceQd7L8u25FyQyqyu/ucQHV6fycKktiab/Gnp+Z5rPMMssss/xdZGagzzLLLD9c6g3Qe1QB+fvEBuml4/FGaZZ/iwgNIWj/4bD6rVJ/I4ZOWVOisBczzMWbqSykPMPv8c2mbZfb9k5AcWYrpoSQotSFsvvYFM2+0SSCstFdbSqAUMApO4whWUEJIWwhCBwrV4ME6gLuoM9RkIQyCzuEAIaBj6LXP5sFQAThWZTZxizZFfVjEByBcGKPzQz0gS7lyQFPf2tTrBelL4zNacWUN/mlfIQBCsrg4JS0XAjoU4KAcXJ0ghg7PD49IHYBqbe4gcIKvA8V2aaYpLPC5O9ih6JUlqykR1J1yHK5Qt/32Pd7RA7olkuEEJD2PZarI+z3O1VmpdQ8jAjogrESclvKmmsIDLQXVeQJGIQ1QM4GLPkFHW6vhHNo/HDJymeqB03UY+Hbjqce5IrvRuNd5eOjx63SuMhXwBjp9nOlZAME6UZBngQgbAJACQVMkAxcMSc4p5IomrIyNcpEwS0ymwLOJGkVugYrFEBgkG2p/urjiJKY96GqGeQfm1I1Fs8w/brk/u7KprfGPJ+W6t2riV4AMG4gN+dYfIoQAu6C4EyAdJsQNxpKIhIgl+c+qmodX54j3SiIblHTS11vb5RRfnEBkVoJSEjXkvvbl+svWBPMCOYWjFvw1toQnyNeRhz/9ju6lLC7vsrvfybA8uISMYbsSrS4WAae/+zxn6svo1KoAfDR4slOnLhB1MS9tXg6xcNIK0dFT42nBpgo7XGoHvUxlgAs7cSuSqf9YofVPOCGCmPmNJXfUa7fC7CkatAgCwAiWpd7eCshUwgT+oEL8ml5wU3pxLnjKgTLofvewkI/EVNSo3iREVD2AHMiyIZsWm+FWe7rlHF+JQ9sOZyNj60OGNVKfzdAE3Mj2xHAfi/neUHBczTvHbuI5/1ejRkoQISx79UxPwNNvO3sCjxZqBkJBv7qNRRIw3bU5SkAkLILcQ+fAtHrQ14D2FqLjMlZT2perp73PPAP61xngjMrrHs3ymxmCSnl+IGNR5kzSqvWz5pR7nkZHPt8JEDqe4gENYqMsHkx5PmNKACSDAiX7PZehJEo5jlULFOarxICIc+dVmDi15N6dfH3n14p1DGAq/8JvsDAy6U3WLO8eNXbr/nrZ1NvQ/Xx8PePHtOBzxdyU80/baqEyR++QXJ9DyeFwTMcEM+9gwBOnkLJG1VtpAb5MkfcEqrXcKMwcdkYRGwc1f1SFzVueRdjNXCocYkkgaQE3wuFEAw877L79q7r1KAlkIHlbpii4HliZZ2zuWs/7Rm9cDZflWzgXXpXM9xUfuaJCHfk5dW+X4zqdp4oFTuzZk0Zcrgk348KRPejZkQzbEfrQScSAHehrhFLOXjoMK/nkvVSmzYktJfYAeV1RVnDS7OmXNtawQPn5N+GzbZycTh8BuUMuGcPZMMxvyNvmSb0AfV7e+inl9btdYn62ml4fnSPTKfpwLkbTwHI3g18fqseZHNsqAzJJ/rEKL+VIa+0dZyNVxqjx79+lJ1llllmmWWW7yEzA32WWWb5peVbYqBb6NK/RmYG+ofkWxnoReqpjQbHBx+u7ICgCl+PG5eZUeIMI6mUiOV5WtuVY9m8P6cqC5LvZxYDTRxAV8aQXQWPjZ6ZFn4/TKlZ6f8JynagDIwSKLZKfGfH3aWEUxH0pCxz05PDPH6CiLBiVXYSq1LmK+lTjwQgVpa6y0qquLFtcQIAjsVUCF1XAYAKbDi47mUolfLK4Y4udplZ4bHYWAQBAgoRYAL3nJ+5iPocPIuV0RMgxwinyk6NwWtKcHp27o9G3+9BFBC7iECElIrimE3TRCEgxIDdk0fTVYU9V9cmthjApqBgc7/I9m58y1heFIZeunEVmb917bJd3TQDQITmlVHcQQvUowBQFEUOkBXXzO/rSzXATKCmvX+I/zy65X1p1IBf3ccC1nZyhIDo75vQ3KhxHwsQ0G9vsoKqVfi3ymZX+3t3i1beNfwmKErAZOcefPgfDUXt+zeHRAb8l75bK59eU8T9mvL29vd+cF0LeC1lttW/c8RP7n691JRAwNfaf+LlOXjr/a24Q9frSr/yRvJflxd4/nKDePEJgIC3CrVvcasK5FE/s9Ykmh+SgHBZWF1djCDAmJ2M/oohpK6pmRhMd03scpcGPK+Oc78P7U2HinM4xx667lgI4Rx4uLNxZhNxv2WsOrXBTqLzY2Jj7psCekmhKLtF0ENjYTMEXezQp7YHZWYaCEtSwL2DYMcFtFsC6IMrhbMLCwDAytYNHvIEzFmNvYdk1+M14AioJxQR4Gm/z3lxaZhWB2TYGwWCY7HY4eZFBQCeBiVcj7EAcGyJPUJB8SeUeO5nUlqxu9IPL+SLJr/rt6XNp2TjYXaLnj226H/k7GIWLLsAoljybnMhAANgyzxOAILHPBV9B6KA5/0+A7khhPz+bECSxwAGmQea2OlcbOCTM0lT0tjnu36P/X6fjz0fwQHjDPqWubUOGQPxSyruICEvhAqYQ/n+4fGQlehumd8mLWqkc5pDfT6PlTL1vNZ1VBaZYuvHWMCvqCBeCGVdiWpN6QC6ssjNAT81WdLyooqhKsiM1VyqBqKn3j0JlYtLOu2ZURGJTMQifqu87b7hVT41j+7+mVs2AZB9V/1M0bYe6yf78PiTAPQmREIemguLvHk2lf6h94iC1s24U7xv5X1knW+EskAINkeUG5rder6DCBERXRex6CI6UlDcWeligLckDSkFa8PB8hCjAu4hBIQYdQ1KQM+Mc2Z8ARf37ezs82TGwAbO5+1fYbknKQHKNgL1bOOFlBFMDN7G3inqvCzmRcLLM2TQVePDa5lQfqaPGZxSTna4Fj1jYCWXCJfA/2yvRh2dxcdgr/zB2hZq8noutat1yf+TrSn01pL3M5R1Yx5j2uVBTmqQbNP28mmqJlxrGIWpT4MEaqHx4Eb13ODnSqv09wivsLSHcgg8b743ax0fq+v+YYB5CO3xG/RudRi0YXMje8dZZplllllm+afJzECfZZZZ/nEyxCtm+TfKsOZfbwnORNWNYYByg21jy4zCxUYGE8vWXr8HBwFoAtc7lE0hkFt7VHtztzB3VlB+lN/obrezsphAE/v35qQAp8iY0HS2ROOeq0JZ45+fMGWFyQMJToQaEH0YE70WRok9Hqx8FZcvFv2al+I+VIQgpgHxWO+uNFtQUGUxFCRJZqxSion0M3gZdYAQ+F5A6wB3Tr5cHsGV1EKCrluaIkmV/yGWNhO4aF6ICKujIzw/PWvNM2eXiO6inUVUEW9sCLGsuLI7scD1JWETwNvasa0Bw7hDDaaTAEwteO4qfQfPhmBaKd23SLlp5FZQDpz/CfJQPfI0K82AUjaSqxzlDGQQdjrlcjWpwIK2uNpOVP9ev33uqkN95SDPbx6KBgDf5HUfxRj+JvJ+ZnoBz/XIuj5uka426D5F9Dfugl/bC/vFGTwHCHcgrKEBL1RUiesdFxDZYnG5AUsCQAgbAm+jhskgNK3Lu7o/inELEJBu/Py5MaAFiba41ykHlhn9qBSQNWju/bs+rj8/IoIyZngZPhFwKqfA+gGQOj64YH1B2H+lVhlu9/lc5KOZkLk4dXBbBH3qByXkdyswwdDhW0CgYPMHa2z1YGmviLDzAitUapgP/4Pv6nNJVswXbT4Odc5jEB7f0fkeqWA0x2+9B3rtsaBi9Gt+vM5bkOe9Fe7AQ1GgK0GbmjKh4CZKjCDaX3Y9YxFDnmO1nt2zCixdsbldACmhSgRQzx+eCwcUmmxR+RHKUJTBP6+yGgTPsVm9PLLy39K2dxWR/LvntTpsgBVBmHTIcmggL+soyh6K3iZ+l6XWWlJlOGfMaaxv99/HgCF5E68nsGodmJdrBJDxJFNOWppv9VE9A9dZqVcPw3ccvtXU/T9aDk67PzEPL+fgr3z2z337g0+jl0bh8bW5rU8A4HVfGALkMvjM1+clWMhu2zuKiJ2C6B0FY6F36GIA9wwOCYl6MJEC6Fz6dQCyJzGWHgwFpHthPDHjCIItpHjgYPcOUbynlMLw8bs13CEifMYlrug6v8DU3FD2opL/HCwlM94OMZqRcsjjdzYkF9YxSpTlfRvKmCWioDdIwLjG7uZAJTYgcjm9FiDaTxqSaiLvtfigSxZfnYrxpbPhb4f31PfVz6/2Ac2Tpn6nidzUE9tLz/Q9FLWeOOp2/JKMwpy9Ztgn1f7aGjf5gRmy1Y1equte7IPV9fXr1dl5cx+eZZZZZplllr+ZzAz0WWaZ5ZeWjzDQ872NIvIny8xA/7BQCH9JqRFRdrMH+AZUskLY49VJ/V2vhLqLNQDdYz7n/XH7Ns48LnH8yi63fnb9mTfL5qZ0yORxZZEy5gAIwbyYthtbu/6EGWxAwx2zKiJMWR6IcAvBiQQ8kLIUTkUZdSyCe3v2qceIM1B9qjwB4NgQqSdjDh4ZkJKsNFKjGHAdFCNgsJEnjeW58th8MWpOGCDWq4UZsPZDbByx0EH2AgghnCi7IoaIrltgsVwWBQkXdm8wl8opJbg7vBCruhHNa98nZYlYWyAoQ86bRWa9Vd4LhtJvjXHssSrUCgPJEGB//4R2RHFY0FO8Hyh83j/2DAEl5Pf9LqznURIfSbNoohzwi4O2RwZlSsPkH0tddnUKBdhpC7QojKQoogRw5+6uHL0dggZVNdQK3MxYP1i24/PfrS5+ivycUXzIWt+MlOZnAIDlpwVEgL3FQE/5DnVRvbw4199vthX7qZXPFwSiC+yvrhEvNgDIWOwyZjzlBnM72c5qEZT+ewbCvek2HTS9pwnPEgfE5xCCul9/+mA1fL68wNX1DdYXAbsbweI8ov8KLE4JFFfY3T0r6JbZcoKzc8L9bZmznA07JUSExRGwfyqKXh9DA0q/aAHuIpvNGiDCjbnfX1rBRyI8QbAwxT+CzhNMsDmlzNoewxkiOieEgJQYy+Nj9F/vEUDo6BQJD2MvK690w2Hs9vdKGJTJR1Oqm2O00YsIOFos8xjIovN8IGfOl1kmJTX0YMBAFwdW9HsMyuD3WOlJREEYM5Zg6xiRAhLrXIgcZ5eUTensRgO2AUIMpKzNGNGZtwMiUqYmJ6Q+oe+TfrcwKmr0V8f6Rgaa/cDnMFCS3AAAIABJREFU+drmQj/12RLUg82ZIPfDuqrzsX1pjt1bQlVvLpUNXvN7DZyTlBj2NRt3ykmwiM9Ddj5GxBiz1wQiQoghhwZyA9Ham4yvZdjWYUn9AnlJ5fJp5h3JJg36cGeVVmvZ2qymnq4abyrtDy/ZvAzk2+a/uj9Mz/vflPz7RAAL9vKTRRtjLK2ptCMHYUO5FKj2Md+BWVqXew0Sty7Xi7hNTMNAVxdWGTz3ZGp2rd/s+6MMGFqfyHkh0xWQ7qHUBXssMcyjAujRDHeX3QJdF8G9er9IqYck3Qc4SFy/iQ5Bvq5n7Dmpu3bYmOfhwqTsL0WagGBt+dWdJb88NWXYiNt+D39T+rGOtSEidDoHhuABRJD3N6cikJRw5cx18ZrQdzu3cXVLXgRlPIAZ2uX51uTC52ic4zrclr0x2vfzvhqIgBCwFuDWxxryPAzKhgZDf1tMdcsfX1RdkT2lZI83JsNbXugWNfu83tPnfcQrUo+/Q/C8/j4cX32cjiEAlReSmmnuOrbRuTpvTXsbz0XD1/h2D4KzzDLLLLPM8mvKzECfZZZZZpllllqyEkelxC8mBJSNtDObXKHojPNhPLcMqE/ssIkqV6EvbDobIL1WuGJq61+7QRyAEEo/w30wRSoJ1lDlrseJI3uRB/s8NUXymSVxJkXx4Ir9U1EYsWahC0Td/9o1KwGeLfs9xGLcEozgn/PqCneBxlx/tnJZqZ4JHAQRBPTJdNamHkuMEKMq6A04UTQeoI4ghpgxCwgJvZEgu8VCFfmpR0qs8eE5ZZeizihzt7WqxNH6XCyCGVWoUkmEs+vguIhIfTKX3JX7cKuH0j5KncZLQrrJqmkAQMA5GLe5Nof43PD7KRvI9g/XYTiQ6Mzf8rrTwLkMrpPB57ul6udDZfyU0IHvs3ybHGatqwGN4A4EoE8XBvKtQZl5XgBbBwKTAOdAA6L//+y9aXdbua42+ADcku04zlB1z+3utfr//7e+7z2peLalTaA/ACDBLclxpqpUnY0sR9IeOBMk8WB45wLx+Q/F2e+Cs98Jz/977XpyIbh2wbkejgVTanqHUK/40lh5mx64o/777kRdL7UrC6qaB4TvAc8zqQLb9yZU3V4BKoDWZw+j0QzucAbC/ga4fMe4vwkgYAQBMqA8nRPq06Fi0QK3eXGycAJK1AXSAgPTNcWEjcQkC5jRBe8tVqiaMtnu8RF7qK9dD3j+uib7ftJDXr/kX9+QpK27IB/n0tuPzAuO5Zm9vyiqt9NoIY0GiATQHzbmQxgW32/E88SACrXKdbCD2jwc5kfsr8TUxexegGd9/loXpx2W3ztUBusZHLvf7pGtL1faQfRML/NyOnp9qUaywL1a4aLfA1syPa1cO01tkdLxP3fG7nPTnmDVwVPKAHB7Zg1QT3ePAeNtvlK8uFAETXQKFP/7KIH9B9Mv3kUD+BjY+HLWpftI92PVaHPC61rcGjtinZdSsJkmFDYX7gEylsnuCwhCxkeFPIRBWKA7aKpqSmaq5nq9imBX93jjikmffSUaFHnwcvPnc+NS+WBoIKIDRrQEYpnN1XyEzDAA3UNwQKFCEGJMKviDANorPkBxQ8BbsVjrSsCNM++8Thyw18ywAHymcL9+k3jCkXUGbqUOsyy/PX7w/So6aOVF2U5m8bX5pgUt893XguctmXzu9/dynHMARxT8/Z3hua8Ez0+Us3t/WFxfKHKsvH6llVZaaaV/Eq0A+korrbTSSr8WqX6FG8wfm6+oAm51nKkB126NLCIL1+5Ak3ovBQBHDs/fXkTtgpHkKpDg4IQG2EI9ou9CMAO3MlKTYOOe0VzsXoLwAHPbzn7wv+MQ/pJZ8YmY1QiHhUIHoS61C3YbaOFfWRXn3iAbYswuqS7EKGxuDVXdGhTAzt87F3c12DIrMMsTS5/EJR/F46qSSXTO3rzFPM+o+z1EK3gq0GcFnacIo8k6pZQJQEWJ+K3cAYGQrKgI9iIoUwERt7iBCkJxl+/b7RbzPAMKVFRM04T9PHt+br2RQfN3DLmuAAH1WlDem/XHfPOuAQYhBPcaW3t6294vJPMPPLqrbGOnve39kpUy0vUsxmqC/JTO8r0vCUgaaHYwpWlI7yR94f4SQH2rvdzAafuubDCc63jwvKdf/YGYV2/cAjBiTp9qlwwSoeWThGE8/Ezvnyi4018tl/pVjUyoKadYz946AK3Xn1EBTO8/Qq7fobhSyvThA+ZPn/H8v39g+u04+AU4MPuB8D+fzOL5LQWgHUJK+3irLlrMSjKKll+6NNA7BVg/ovxmA2L3+Q8UvMdbvT76fJ6wyyi6b3T8feG/H17osyVw/bS/xuUV4/5acfGWUAqwv9PWFvFZ3Jp4VrVDpQLvPl6h1nsAhEd/Z6OKvQtoJxDcoYd51ghltPR7E2CeK1c9j9MI19e32BJwRsAzDBwGgM2iXi1dDe8taIBhb0pCldksDrkABLAyGGjg+Qn2lTIa2w8EA/EX919DR8HdRTKvnX7t+cTnmT2WOMg9q2hr2L3MILX1WNI62/J0sDQsOGfx/dLc8xEVFI/3SzDeaDGACTude1q+Z4kLim6RSh6Pl9T2OuRtKaLgiLve/rw/NQK0hIeW3uHq+4dQgMxzM/P/AL6EgLsMfsQeBKd/tw1Ruq9ffH/s6Ix5LZVLon2B1C8Uz1rdGrh2gkEPluSqEG87kYoWkoEwKIfmsrT3FxaZy/1tLvZLlue53sv3jtOXRv5fvDD+6rQYN39b8vnWh3kH7kIpyH4ncJ0C+AvPKKNHHztHGZBeAkjnMli0E+wcMAPmnl0V4aUqW8MHL5AqQJ1Nwah2bx+ftULJFF5v6XCeRxJD7fp/+euRtqEIxD7w1/BAQUQgdQ8xbLHZ2/yDomr1Ncg8dlxWK/NVrfhUK65V8VapWYuHhXV4t4hM+xbF7NnbuuaHRkWq+4k2iM3GrVcp6tP2+MtXlm1yaqOqKaGxsPZx6gC1pIPz07gRyOeB5lXkKzfPzatCBrhxyFcP2y8Gv3lWiDZ/DXielVGWvP2Uy/nV8nyllVZaaaV/Oq0A+korrbTSSivB5R3u2jy06I+6SkuW6Mzs8eoMzqTlofxYPkcFol9Z1izY7vJQMBHuoHirOhzglexwfeWXb5FcH4fQR63cFyDcO4ieS/ZAinPtro+Lv3NHZmme5RADrkTJ/bhLZ0kVEGBP7i4dEWGeoATsXDlgB2ALd+kL4Im8btkCQ13sXgEU7ooFxHjz5g32ux12+x3qvAeVEvJ/iFaIFISQgZlNoFwDID/sF1VFKcWEYhDLsvizrQEI07SxOhVGrRVFFFUqoAxmaZZhcBC2vC+o1+GU3QV9HttP6fZAdtMdrf5c0hPfgRPCrl+AjsnTloLIU88MsrQuUTxKhOPWia+jBZpyrFD/4RS86pTV9Uu0bM5wgc4A6vXs883uzZ8+Y/rtA5gVT/++7kJaz/e394SpGF70v591SDOUNUYRqs3PY+V+l5aHZRkVAH80ofbzp09gXEFw/cWhEWUAzGr+LY6PScVpq/RzJewy0wZQioUBuXhr158dTQz5N4cb7iQvLm8I0/QG+/kOcg+oShPYPsNeZACVgKd7wdklY3oQX1OogREtzrVLyClPzlYfhSqhvCHog62HAeCPEzqE+eSgpXawM9Jy4LCKLFzO/zUC4SPV/WHEDFBEkk+ghfesA9NdoSFbLOZyDdfTfgO5/1pdDFTX1DcHdQyAwNNkpL2RdgWlAHWa1XPkq2jjZdwbjKBxPHqSusbjWMbF7wEHRsOEev6L+6d+Z3WfDE30rWTagzaQcEwru9UPZZqsa3kA2DTwvLtfV1FIoFWpbBnEPwaqv0TLPcKyH1b6C+gkEPinluK7iJZfkiLs8ByNX+J+4y1KIHRFEHbOGPHPC5G5uaceFgXqXsgSv2EikCsIsQOTAIAqmKnaGdHDPEWIKneOhZtjLmsi6bROJfZ6pEES3yB4iIzDsyWBUPysEt604o/8PKICwL2RGGjuITZEMDfeK1A163O4K/2hCol3EQAhV9g+UdehgmO12+9gvuQXNL13ao9k17+V1ywa/jDhxbN08PXI3XZ2/drpFqF5Dkq5WOPGsG/a19XlmPgCeJ4Vmo57z1v+PjHmknLkSiuttNJKK/3daQXQV1pppZVWWslJxEDwOFCeOuiGxYGIgKnAfIv7YV3FBBA/+czYBCp+MG7xDIlxbwgxFBa7NATONzALSYu95wLSqrh0APyWTSngjRJuyZyjRxzeELBc+zn+jWIAIhL8621kny3WcEiN2dyuM4AzVdT9DEyltdeWC2Yyt4eAgegAcE4G7ivQYo7DhUAh8KcqBqIrcHd/g/fv3uPs/Ayb7Ra1Vjzc3UF3ApwXi7k6V9RSUchaj5mx2z8boF6K16GPAPYxUditL5LLPBU14D09H3XiYrHX51qhAjDUlBoETYgN74/52qw/UEygJ7iC4qGZiEaa4S5/KVa50OOWpstLX4rP2wRyi9+vVfhogMcry9FwkOXEeb1pGoDTMaIDvIxUCroMlDBa8QaYltNb5n7P3Q1ofmAUYB0KtoJOWfC/Vtj0lc3yw+jPMjI57Zr9ZbrOiBeAd2HBxORxxG+g10DB+/Zc/SSY+da9eIwN+ula8U5xNC56xmmpeQR5B8YN3udxQcYfBX2cxXtxTQB8uv6Ef/32X2B8QPlA+HTd+W/QpfqYTBNTAahb1D3S4bOPdGiVnr8/k7oVGmHigs0b4Mktx8Mjg6uIAVAQGyDKRN2DBAHPj4rd4539ZLK4z17RM+eM4VmEAeweFJsygTZAfa5QX1BUgRmm+DWZexQUD5sRIB8T40kEV0z4+OE9/v3HH6gALiK2rfNUIsLey8cOorf7QzOadd4sVksmQgFjO00OJrjlsq9j6mm0WO0tVEsHREeAGK8kF0S7ctW3Ew0fvUw8XKsiaZ3TDsKSR4zXiHVuHHOjhD13l+Kd/3m81bDG9PsCbQ5XmityB0KKx9sVBfZiO4WNgztW4FRQn8cU8XeDz3p5l27E23qVgXd0vjs3RTsanm8hBxYLXwDSS3Z7yH715L3lflLRsK4+XpTS7wAlDgEKihuLvCzG/eLZBdMO8Fxqtf0HQqlP0/zozx5z4x73gr60L/jade3b6TsTWG58fjq9trwrCNWJFnxtAaATHcyZ/AQ3YBxQ7S6ACHad1TxwNQ8REUIi8F+iuNksecMblfE+o+qKwgrjKxUWA1x9wxkz+cDaGYnXJNC5saTg141pUFtUKSWWv6s/xoVtrdfeTjanBR9nOyt+hq9nqpir4ibKLdrchN/mAuVyp2tRPAYl/gT3MKet6LZBMu44+g9KxCnBIYexIHZmOlK4U9NnecD50vNx7whPBRIfTLcZVue2V3wh6VN0zPL8GE894PnU19l+3hnXlRjD8Hu5ake2xC+WbaWVVlpppZX+ybQC6CuttNJKK/169BdpLLcDZgLR/ZTZBbJAu1aI3MqOHR9OcAjFIfcnl7mhtHbSDdemgxVYCEGjfm6pfqU0yA+u1AQxAZ6/gVmeXyhhslrZM+iW5+cgPLrFwhulo3KIJzLB+TbuE/xkbk/QfsZEhJ0LGZgI6iC1qMUUF1UUL3sAMORuaAXUwK8GokPx+eYzzjZnOD+/wGazwfmbN3h6eopWAACIVJTkuHuz3WK/M9jeQHR/NiwXQ1xHABU25QQH9JsL1AAdSjEgabcDiHB+cYF5v4dUgYiYDbuKyefeA+atuQv6w6V9QA8hBHt4QbrzkpvmX5kCqPnZRIvP5XXARscpIH6lvxdlQew9dUt0BcDvCfoH0hP9nUzHwPOw/C5NqO4uzZUAvAdw7Wm9g+qNC1EtrXcpO0J3if5ePmD/acY1XeN3+g3/1+//wt3//p/2bI51HnRHwJVrL70F4THdExhwHvTSUhRCeVXF0717xkBa9y4I8pTmzxFBcaZmueRy/tmfa9Z/FHxNgX0WCo/p7ImwZTKlJQClBRQhXL6ZsJ3eImJ2tzr6Qv6IAIOT0Bge4/uIZDiUxEKCLA4oh6C5e34hf4wArThFr1v7qXH4fuVr3n8dxbqpMJAkV19t09PWuJat9n6O8u1IMcHCuQyFpL62HwOEADSQNp6HWD8wM0iAHJNXUuEkLJ/980wVDxkwd2WDvPYOZVsA68tmHWGYQ5vFDP7QK35/KxG6K2Ugz7EAxR3+oA4HRp4VOtaTFmm0ymhT/hM11+0iCmU0vYS8b2zvHAHOTwHor7U8X4ZRWGmlr6EOBGYH6wtgsD1HHWgnszQnBK+355oFOsyzCqmC3CI7PFs5Jg4ldwPvwG4oVVtIDGeurnQV64iIoKo4gNzn+rD31AUX8kDtmmZLc79NNLx8zENFPB/vFmILUxWTHbYeXKkpVddasbdK40oUnxLPNparh4wv8gzWHiBs++3snqgpJeQwbQRt59eo0OiZoz/Z8xzXzZGHpzd+6vn7eOJNUQxp3f2OxXzpuh1fSI/y2CDycCh5hnR+nV252+/x/qHi72Fe+fPgob9IlrPSSiuttNJKP4Po9//+17qyrbTSSr8sZc3Yr373iLD5TyONQ/kqFPpa+iu1mQctcurClqWW9uIt+xOBVkG4rQUMWPVvR612lvQlq1UcCFf8PQATT33EiTSBy1y75VyTK8OA8LsCvNduRSgE3JIJUi7BLZ6wAngsVp7zyFMNXIcq3ijZdxiI3uqDDhApzGqaCWAwzonNhTsRZhFsHCAXImzOtnieU0xOAHOt2JLFAh8ETlUBIWhhgC12YS8AA4Xdoo0xTRPm3R7vf/uIx/tbME9gJmzPzw2krxVPT88gALu6x9vLt+Y6L3AVZCAlBD1owv02fjiB7C6cmPd7KBTTNAEgzPMeu+fnZtGxmbbY7Z9N0HYjjXVEXQVm2VlbWy7GDr6PlmOqXW/KGN+b/mG6wCss0A9SOQVvnPr9Y+gkqLJs+JPZf6Fcx5CdZQppjB3ee/nd76a/6VIWXiP6eDP4XFTxUQDwO/B7Rv38uRl7KWVL9tP0ITweUwfBl67br7xfir6D4qbJgI/IoB2I7wncE/Dx3Uf8cfNHS+uWCR+uCJ9v+1oV1uW0SKugh88oxKaU5PdFBM8AttMEOGhWHVCLsjEbSFBAAI+zrxChOggXi8sEsxzPtRpcUDM1Ty2Zo4SFWruq3YMFE6FEnG5/DqrYMKFsgfpkc+IpQFYA5wCeoh1cNt8tA6krLSS+1sAJ2FhxiAPbMrX7AZ7HM1E+oLtYlQAmFzzzFAeNMvFyXRE1a+sDwbeXoWHE455gogJF5qtpTwOFaFrMQBZapCWsgHsW6KBU2jhgVHLK4+2CGE+RTBLIx3Bo4IuXmd1FMhezjttQMYU0Na8E+zq7pbQrm4mPkOa1xdZNu9c9wXi1nB9qG9vtN/o4VjRcrM8LH8utieI6DufX8jegi9Hf53jTM1jc59a0hMJTa1/m1OausJGvt71IPBUx62GASWFucecpuf9VEZu3tUKkooZLZrb9bczBQ7f3R9y5x/28R873Ft/zIrWcD382gL7cSbTvp4rxM9ZXBZCUN7/h5W9/l7KCVB/sHRAb38jW3d9LueRiiY95L2FTxwJ5uJ7OZ+md4+A5EGErGMarN1zsToC2ZHsDZvO2MZViPIqNn1Kej55+4dIsuktYdjOZQooK5v2M3X6H/W6P3X6HuVbMtUIIHp6p1yXSDj7VP4OH2ZyJ+UyZx6Z2ijPHsKARmWM0ANNUmjcRw8aNb6gILqvg2vmoiOCjAtfevh9A+GwL39GRl7MD+r4n+N01AVWN9zTWvES3W9r93BnKA7aodSBY0zvZ4nzYWXS9ui/vX3sXHP0trqTXZ4wOA3mpaJZDwby0b38NhXJGTutUevFsBtALlzZ+NZUVaY4cVdxyEtF07/hzyzQbfWfdV1pppZVWWulXotUCfaWVVlpppV+K/srDVhYOBmCugLkJTa75BqF2SC1cxk/hhhYCgQmEzYj557t1B/oB2WQjkg3EoNJ/3LG5cw/hkEDBaoC6CnBdtFk8miWjxUZ/hOIChALg0q+FlXprEwD3ZMA6o7vLvlTCAxQbKJ6h2BIDzNgyYV8r9gpsVLF/2llsdDLxsXqZdy5guWj5mCWDCYzU0CIWrz/BPAIIVAtU9phlxvb8DW6ur3F+dgYujM1m04VshbHZbiC1YtKCp6dHnJ2do7ggOtyth1CogVZN4cKFBYLuath8D4OnAhXFPM9JSF76eCfCZtri6d9PCHfCNo6iXS+huG/9caGHIPpKf2dygVdI5VaZ00+i3rB/MPAet8D1ld0hGK9WtyFP8+vKeeE1mQU5J0FrltMu6ZbMWl1xg7BGD/l2+CsZwNv07qWigedAz2d/o3gHY3cPZH8E4wmc0hrKlRTA9tBmER78Rxq/6a0kqtgkHDQLzyXeDSk31FylN+pgZdiKiegCBHG23QKpGxi3ASxmOkx4K1o9drcJhwuAsgWen3u9JgdbqygegSEXUQ+b0WuS1u5Uv/YEJTC2NVQHNVL6HcDUBlo327gXAMNO1lNMBSCGuKN8OMDSXMIPwFZyoT60c/7dr0f5WolDuJ6AM4SlIZGtqQACmqCkfae5jVqewAMEWwCzHlpGgnI2vR3E0xYNC2hFcYW16AOI71tCEO9zz1upgVYBqI/9s2wjbc9EeaL8vVQ89G+/OtLyfUq/xmt9Lh57p+djigSc+rlbnfcSN4XOVJLIlUSgoBaOAZFPUoILhQNTTOiKCAZoeVt8DXgen3QY6/aY5XmeB0usaqWVXkuGDS6BwOUzx++b9bmdTULZx+YVQMTdAj2sz9PCHLw5eJwprNhMVgBSBVWqWXLv99jv9tjPe+yrXRMV2GLWF9a+liRLej8vNp6uXp82/0fQE+hlGlHOKKPdYgrX9XFeASDAVVWIoCniqCg+ASj+PhPhN6IWwit4ZigdXhnjaKF3GGgK2ESmKCS5zAQstU/1cNnoISVib/YKZkHwo9+QeLr5I+jEch599KMpxxI/ZR0ewHkD3F2Rm5iaC/ehnEjDcFHmnMex6nzJ8ny5P1lppZVWWmmlfwKtFugrrbTSL02rBfpKfyUNLjQxHhqHuGGkLmdxQS8iVpwB2GKSiR7v+gv5fbsFukt61GLWNaG/dB19Ee1CFq/ef+s73PNdF+wqmmXhDSneCwETm4VilIFMkF2heEqH5DcOyj86gN7wB78fAHATYU/FJR6Ks80Gz/sZVRJwUwqIyOIJqqB6QrOYwJ5nAYSaZZaGZYZXT8hcJVLZAgpsL7YgYmzOzjrwDqBMZglU5wpVwfPzM96+vcI8zyaQLuN87mDFaAeiqZ9yH3IDBqwPap0hItjvd27x0S0L9LbbUahbngeAHnlUAE8/lL3EmFtc/YstCHT4NIH/QDTOhcM3f2w5Dn7T8funs//2cr2mL354V/1DlrBwm37DZJbcA3BoFlbT+/eof3wGgO6iOhEBrfsa2OT3QkkohLyCMY575N8u+XORRgMj6ZCfDOEEFvshXgo+Mbptb0xns2nAm0LNEkzNKgwwnhQWbkC3ADfhN2MqPFjFVVVsiTBHOcMSTHuWtBCoEizmNmBxOZf17PCn/RAHDn778A6Pn29QLgl39+LWfwESdsl4ldHCDejKVg+pTEwI+CSBF0sysL9bknXreNUAet3dry8jkdbEBY/7HaIBG3CBHOPVCrTsvza/pa8b8b7tMGQAMxv/aXuDoUlQNaBmwuLWuI/wF4m6haW2d6NbTRhval0G9k6lDJUnMIh7OSTKSlanALHDirKQeYiZymTeBsjc9UsVj29u/QpVzHNFhQxg7aUAs5oSn8Z+J4D0xX5pvN+BKfO+AI9T65Z+PrRCgSGDRXE/G1AqIXlXGLpmbHNPIw9d9f6dpglUSnsrxmsbITHOEiBI/l+4t88x0Adeod2yVMOqv72jAHFy467tnWinFwF0z+ukG/dXAOi/vAX6sQR+RCG+2QL9ewpi8/HvbIHeQeT+dJsvcQbwl2N8xedEjA2ZB4yWBpOB5xQWvGzrRPB5DoA9zn32Tlj3BsApIpjninmeMc977OcZda4QragxB5lSqAzqXijyctbWP5+fzruYCczlBYthSkc76hsLr7utaf3sFzy5elgpDW8exknAXKzupVg5vXzvgo85X/hMvawKuNJT8AEbX7MKanhEc2Y4zMHGD0ce0XgqAeDi16U9kK3BuweNlEC8mz+X35cUy2vsh+IMvVh34zk+xnNbvb7/DMX8sjQre8rjZKkPH5tMKQb6ibFzyvvfsvyvsTxvnKUptq200korrbTS359WC/SVVlpppZVWSnQ01lhY2ODI+Zvg1momgAEpyK0M7MwtTbhC/sLPOFDS4kAPuAy+mTF0YehSQPU/fIO3YNyR4lKpuVwnAB/E6h2ugBcyngaen4PwhG6NfqEWJ9UjAg7ECCFJclsrit3TM2iaMBVq4MlUBeIa9KACqeZylgDsAGxTmQjoAqcuITIopO4A3uL56RHEBWXaYNoU7xtARcz1aSmYZwMO7u/usN1uoYXgcvvW6bkdR0GwCeJDYB19LrWCSzHFAyaAJlCtqHOBoKKwgw0CyJVBLXIrILyF4g6KewSIHjU71x8Noq+00j+flm7WAZvDci0A3gG4AbtMNhSFMsCyNG66pe6yFHQ8/fyOBZTo1uiR/y0dyCFxqfYHdCD9rR7PI+jB750rsHNZ+bkxR1NA0u5iXJKkeQDP0C4DpJ1Pp/Vr5yA6VPHsa2Qw41htIt5spgAiiNAsxaitUQ4yO0B5dcV4uL6FAni870LsWaRlRyBz6Q7jvRRCdaDHhI8lQRWSQYsTRAG5hHxYXflgwCQV4RG97QEAzFJbO3Q5tnVueIFplnUHoIG2m4QumA+FM1EcKuId2ZiM4CANjw75DflrVzrNfeEZEPf9A/s61uKaRxuQgjWs3QjMlr80dwsjsqEe1gUBTkUTqEJ3sufkAAAgAElEQVSqODBtNZgKoc597BgAD5AqpugHD18DJAC94b0JkIr+i7Hq4LNSGfqHUh9T6p5ockq/AWnjeQDY4/nIazn2COae2N3at9dSPcduifHRFRTp2HgKhbxQfNRucR7KMG0T+wP3EUcB9igTxrG50krfRllRpK8D4yP9vr/RcVS136UBjw4UM7d51TxFOegc92xfoD6vgwEoZpnNTfu8x7yfDUSvtc83XwNETSFIfX6LLuYxwc4bSlBOfMMXlCVPGC1/u6LBwDfSt1irWttpWp+MYUNhhvIGoBd8ZMZtWjQf/KH3YkpaEzKvEVPGcbfxV+iu4Jl04IG0KFtcXeLe0SZeg9TJesC6XsVfvsTvUsGOWlGnS4O3utfk/Q0kIocK/MDwmYHz7I2AXYk8Pz+Ufbww/m6KlF94L64fm4MrgL7SSiuttNI/hFYAfaWVVlpppZWcDjweZMuZJZCu3VKL2I7OzOQCVgaLOJCaJOl/5kFyIV8PS4zCVk8JwXwSdr5V4JbM+fhbF2JUtvfuYILpS3jMWheyXPjrj2TSjQvtFlwhg1CYRfqFg/NAEjTUCq4EnRhcplae59ks7abtBtkGkMmszzfMECjmYhbsEgCP53smaqC/mhN4KQSSHYgMcn+4vQMYDpp73MNpgzIVlGnCBZdubX/Qb2MM9ACXhqdc0BVgAKiD6AEWMBecnZ9ht9uh1hmFTFGhKFAlGlEbcC4JPI8N3KX3w8MxeUaS6CztF6JfvpYimz9rJNPicyngkQbELF7UP7ekB7mdkqT9pHL9NNZyIMn8NSlbZQIJKFTFe+3u2N+JNrA6W6JfQ3GlN5iQwDFPKDft5xPtELzuFLAd19+qe+CgDtJHXm91YW0O+/3Wn7tUYPuRQLgCPt8AGGOFL+mJYGEyKCzMOy8LW/RmcQ63om/3jaZS2tKlqijF7kwR81sJSoqz7AkiGo4ItVkI2v+bqbQGJRDY06siFlc9AbdEhNu70eI6ytLE1S44Pru88PzNY8fuuistEAFnSnhSNWtBBIiBtmY3SmBLFvI3PuoKVw3EVlMHi36YePJ6Tm6dbuvAfq6AuuV6zs4XiQDGq7srZzKevXeFsf483BuLDmM8AF5bApsvGu8SOdwPnJjQVS1fc93bJ38ompk1G2EzleZNYKPA7PsKdU8qpTBU+xgjNtBdlLCfZ3PnzxQ4fWuL7h3BVqhaWxAXFC44mwzIiv3HkwM3xRoCtY0Pbxe/bruHZKWODKjDPxlhp1o9z3B9q33QjsMl/VY2DwHRxsNWcvE7hbe3ZZ4ihnLAX95LHPHYAxiBl2vcv3G4hQ4Qy63hw027uMcJGwtRlz4zV4hjpb8TtX0hjVea9Tn1+WIzOsY6uWKLItzFsHvTYOLE97uXMeYOTjIzZudPpK7oiwooMFcDzXf7GfN+b/HOHfgktxxXe9D4PGmzXoe6hxJ3ta4R26VN1cYkj4LnrT201/NYm6mae3YiBjMQ3vI+ALj2kFLvBQATbgthcgD9X//Pv/Dmfz7hk6/twTPvBXgrgt9V8EkECsF7ZVQANyxQUdhOJZ+fE/8hO6M1BtmYd+5WbxtSaDXFOXBj6weVJCCB7YnSWvOlfa3ll15dbLCzRfifsUVeWoD3MGA8/M6fB+dRYLF2/eKb+pVWWmmllVb6xWgF0FdaaaWVVlop6MghEzg8PBPQrIwBNU37ZKZo8oDxwPuz3Zg1CylEMQ7zU5g73rCYYhdOiCpuoLhSwlsl3JDiFmY+cOXi67dKuIXikYELCcGTAezhbhYwoBwA3mDUyL9QwiMpzj0uesAkBAONDUGY3WU7sCGzeKtSDbD3Z+ECFCKzODTZU7i21SYAE/JYqU3hAYAKyF0NAmwuV0kwz4BszP0izwWb7QZlmlCI8Xj/iO3ZFmG1Ga7YEX1MpwQRAfA42O4CogDRu25Fd0OproQhIiYgf0eQ296Kp8QdL4lBTNYUEYDzmNCDsT4ACy+mGPX76+mgFL9GsU7SEIt4pT+FcizzPFduFxPnliz2OYBR2AoM7puP0U0GW1+gDLBfocuKyf8u9RBEz+9s61t8ur35Qi6J/F1JlrchXs+rXQNfHSgF4G5rRy5RqzR+1WFsAxyzM+LgiQUe+9SvG/gs7hpdG5hdNCDODnwSOk8aqhTAYwMLpafDV/j0x02vqS/Tz9TdqAfvA+X03UVuwJc0uq0GXElBo8btrVYWa2cH5h3EKTBPNCoRZd7b3gFQJkpgvLYCqfq6iDFuvKqt2zXaK9rKK2QYRR+8B3uZ1H5W3rSfgb17jMPHe9Te63yMzwn6nNoy6gM160pVKCz8SiGL9R2ufKNODWBRi89N0tvUVusADEpXZmBGWJRr9IWweZPBOJ6if4+6J4/sAZDycP8grA5Ok4iYBecraHD/Dh8PDQVr/43PvPA7yhrAloHn5q69KSSoW6DD+7J98dZKShm5fV5Lq6velV5L2RV2KOZ0RdRDL1kH6yqNfOwYxXrGjriGy/oCAquFjyhsf+YWnRpfjgQCRDevG9QWFGmeLoLPKvazW53PM/a1Qmo1/1dUzOtMKL0A/d2XlFkWfKCv2ekpB6X9KOLr+OF5ofHtcHMFAMp4DzsfbBh4/1+/4/7//BtUbF16w4zriVGoYLOd8Nv/+3/j7v/7N4Ljqi3mmCrhs5o1/1Ul/FEEIupgPjXgPsp29LQU7I8oef1IZ2rStv70HUucIke+0/ca+mJ7vkRLbxmnzvB/BcfL4HkA+fE5nkXz3uB4GgeU6/gjAPZ1TVhppZVWWukfRGsM9JVWWumXpjUG+kp/Ni0Fpsvvh/G/HEQFUBo0LP0Arl3Q3y4cIcXCMmqRb3536X6VYMA4+7VIa3Rlnt4fztjhyrcL5AEHzKlbVr+DCRDuCvBGgKfCuISBvfdu1XShfcw3zNizeUjgeYjOGd09sjI1gZVQB5WbTJlgZtnMEFg8PQIBYlZ/+3mGqA5u66diVnIbdMiDES5jL7ztXOjMAG0jhpxZpG82W5RpStbm6rH9tPGlZonQhDOaPvsHjtwmJouPGILuuUJk9ny6paHciffrfev7JWdRxMgzsKjL4s2qZjMdiTncgJseb3HnwEYHIMZR5KPM4tUWi6oY/cNMmGuKcUzA825uAkNKwq4WYzk10NI19iFFLXObjukdTq8fs809BkRZ/q97vl1Pbf7yk8fpdJzCL7/7XQDH32Qp44XlzRIMfKcBqo0A+lVwiAzeLtLInzESCacB+tfQlS6AMS//EkTvGYw3jsVAz59n0wazCma3ZGagWSwRGaAJmFcPQFGoQGCgm8VAtZSmYh45Apsd4tVSH9eSxliBKTARgFIYc5Xmwjysl+Hl2Xq9923d1KF+rc39+tXVJVTvQXQJ1YfGM+/uA1DowGj2TNLDbmj7lcvcn8v7x74WxbrUdMbSVI6QHZqe3ZQUaTjtA7IHkwwEaMSkbTHQ4f3mfJZHQX7EsB/HfY9zu4RBD7chiqlMNj4Gt/h2L5a1WOeKW0QHOMHMOLtg7B59pSADaaTad/UxZpb3Ft/c2pMwQwwEIFubCpe2JwAAUrXxmdJQKM6mLe53O5sKFOAGmjKF6uFKkgH/VvO8RHu5a+1AssZ+Akd4Z7JwjTaP/n1dXNm0z0Pa/9E4zpcKLIfpRGORt7H2cqu4Bbp6m+gwBgHjPzeeZ4R1iPl8tNDfQS+B8cdhtZ9Hy53El9bz0wl9R7kVeH0M9C+1/df0jc3NF2Ogx1HGqbv8/v5+6mOtj90h76bohMGCnNKzxd1St+GfkooY5qUYwFjKhKlMmMhBczCKWMsHME4cbq5j5+tlJbS1MvLe7ffYWywJr4/z7GrKP1IF1UMliGovt/NoUbH9NvU2jbyH8040FgBKoU7IrydO1tqHmfGRPuKGbsBEbX7HAnq5m6EQFJ6wLQzigokLbifGe3BTBAy+WojxHoSb4mcj3y9End/NgqqKP6Si1tnqXitmqbaWVaurkq1V1i6LAZH2E3CgWmFtJ7Va+A8CuFgfhXMuUwjq66rxT+d/zsfbGqgASnLi392a+Zqf9wU4mE6dzdNw+zWzoZcvrdAvzKNj95ZW5kt37fnvaMEX5f5ZdDQE3korrbTSSiv9Q2i1QF9ppZVWWmmlRMcOfKeFoC6GawJXORBIHaRxKi2pR6+/mrTZaHs+Xox0KduWNQEAkaMBEpJbKIAbKN6rxcO7YW2uXd9qWGkownr6UsyW/NEl3+cJcIjQp29BuGeLsc4wQB0A3tT+3JMKLsAwr7oEJcIs1cBaWL4Ki9NaEEKcXsGwahQY8CAehG+vFisdLnAzq7tHkDqIToBWQJ9cLHTOUK0QfcJGNuAymcCCyYQ4MMUBkeZA3KwtmuVffAKD6aoCNdy4i8VL5cLensWFLG6ZyQqIt99b9njolwDujnZ/A3hAuOjZYQfFxq1wtI0Ts5brIFZqx1b8cHU8jkt2YZ8BHybIycL+sCCSAInDJW0DzKnPm6H8BIa+AkQ/Tn8XMc2PECh9j+vFf7pA6wj3Hq5mufSVjo/Fz6VlOvzZLDS9+fYuGNI8lsxJ8Pwb6LjVlJrCVVMWCwCWID4DC7G5FNfu5p3p0NpLVDq4mxCNAgvXEa2v0oGECLcxKIplQL6VcYTV4v2LC6DWe4vJrY/Y3wMQYPuOGsAgqSzhmcTAQR3yGcFzczNua0S3eOsAtzfWYp3tMur8TGp/B4A9mEjLi4hQpba9Q9Q7c8f+adfDsj2UxALAG8FgdeBnOb4I5Jb1rV8UqDL3ujC55WDw9AB3HYzweL2Dq1iN0Cra1of2jhKEzALdlDEYEzG4EDZaULU/V6X6M1F480LDbKBXuGauKgbEN8DL2xNqsYmPgJpd0WRABdtnrOMiyQV7atijgEkDvmy/0vJYjtslqAA0RRLr6wCLBHALcdFQZMvzZFGprJDB5HuHuNXv5bE0jC0FrgFcVcVnSoDmT1oi/myQfKXvoF9gm5CVUyhdoCVj08zTnB+xvVW4YCoF0zTZJzEmEFgULH3P3EBUP3s0BSx4GAT3XKWq2M/mnl3b3Ne2ZgxAKXXr667EAiAsh2lsZuM3h0dEiqpTfwaAe/YAmkIvxT7aFVyZcU8WjuO9EK4JuJ8EEMLHwridCn6nCdM0YVMKNkTYUtoxEfDRz3jFNO8wOYBeYcpet2zKcAHqQswNvZ3PxNYLiK0BwlDJQS7GWoaigsY+owpADJBAfG0GsSvm+SmW1BH16IkFtb4IzyIH2fZHX+B/RHYeXZzuXs3RjoHnp4DyY9eyhflSQesYeJ5joL/Ge8qPon/6+WKllVZaaaX/bFoB9JVWWmmllVb6u9KIDR2lpcXbwX2YMMKjzEGJ4B7acdOsqQiTAp9Z8R6EWxj4S1pxx4Q3IBQvyIULMiK/J1K8UQMW3qgd5oXQronnCQXeEKOq4qwqdkwAKzaltDiwJn43ecmGwmLR48u6kI1d0CKwWKrFBVU7VWzULenEBDIkD+6p4o1ByMRNEFNvBfqWIbID097d5RWUqcDiBxKKx/NVcUuTEoK+aNmQemn7Gfl7p7jAzCwrttstapkgYvFya62oUs0d4jtCvREQ3kIdRM8C8YKurAAF1C0UzolM2KRqVqYh9NMEisDdzyZgm6m0T2rjw8AL9XYGkQMODppXA52g3Q1nuBNuzpN9zLJanRmMwmRWi9DW1xk4eg2VBl70cQ24y8q/gI7ANSceWM7LryvvnyavOoog/ToU4GUHRmOO2UeM9Zsj44QAXKqOFumLdo17y+vfQzm/dzqCW0u69BtLcP2lGOiA8cHgi0slFoHNm5izhG4ZuFFgh5hXirlKs2oG+rqyKRNUe5zy4PthQR14c+2YAgoRVDymaRTU+yf6r3Bp4EO8d3ZO2Gze+OOC3c09HpKCz9NN95gSCgHNYwd1wBjo8vSmRGDFhKhi4mRtj1QvVVAIsj3PPM+bK/ZE+2qx3YVMQa2UycujEHWLfMoeNBwoD1fCAagilA6kt6vC44pb6TsAYOuOhFUeApTpeWQ3/OZGXhIrssSt5xUbLi3ur0DBGrHBLaTJ/tmsDhUwDyQKX099/fO1IKwEK8RcrUf/EgB30Stq4JLhVYJZCaiCyUGnLU8+niP2vHjlLJ1JCXvplvnL8Zq9yTRqa6AB6GGJrQGexfO+NzBQwufRwE9cudABLSaAfM9zsFcj78QG1IkBRW38RHsdsdhsgIh2AF9pGHua+h4+pwdQXdHyvqZFe6z0Av2iC+CXdxyve/0XJJtaiwJmFLPdduVO8rjQTB573P88fASk89lIzObyEpdX2++KW1Grzc8IidD2mOj7aencwv4IfR2KDDIQ2xTHfO2LCFHh6aqtQWjrUSnFPZWEwjbhPQAC454IN3yLj8woXHDtedwzMEFRpi0Iiicu2BbGY7EY5xObi/uPquZRx/NmmPL0OzFgfsvGS/6Pn0+0VlQPu2FnQkUhAk+TtRtbu1UooBVaAKi4dy1YuA0ihIm9llgzXFm3MIgtCFVj1Krd1b6D530fYddi6dEaqnNqB92Snkvtj2h/74yD6ZCUon7GVPkSqH7s/imr8/77F57UK6200korrfQ3pBVAX2mllVZaaaVfjHI8QCBpdYcQ/3uFZUdIgXbeJhrBEEJ3lQcortSE9p8JeNsM1xWXapYJBIvf6g5Fce/lvFAvvwLV8worQ3FBzSZc1EqFujRpwwbPVzX7SFbFLIpnKLaVUJVauYNKYZdVmYW0kmIGYbPdWF12O3MbH4IoBVSrxQu/d5H2XQVdksXwlQrmGbWyA+gMNrMMTNMEZnLrcm5g1LJ/NPv9pe4euYHWTAAxJrDFQS8FHG4RZQa9ZxPy315CF5boXZ4YYIVZbxARJjKAfIJijudDwH5CxpIF+VCgsIsFKd1PVjoxfDRABhhABsAVAnJrBMgAgMU1OMjj3C6RhpVWeh19UVxoEmsczEv/vFLg9kSaV9oB758xOnNYi7dpriwB82Mx0l9DQ3xk1QY4AAGXxhpjguRK5LJmU4Vp7miTpRsclCViaFgxA25lllpJkzv0EER7Gs2KjgwgkLAQT68Xbxd5FFw/Wg+dUozpGKI2gKKBK73KUdXmEp19zS3pgYClo07sz7YnmtLGceoAS0+32d9FH8c6COpufT2P5o2Dgqt3N+0DFsu2XrSLFO3jakzU3YsviYgaYJxd+wdYrFDs6twUDURthVdRnF0UyOxghlrp2LTxjKVnRErRPMgIYEpk1DHpKGtVBXsMcwOSDA2J0Cxzrd5nXnaJ9vHY3gpAxYHnDJG5QsARAD3ArvC40BQPNAPo6WlXPuFIz5U1JvI13htQQMkpTd61hdV931OJYugjyZnqWNZW+qE/BQpOoDkacG6Pagf90r2xbiut9OdR5mft2tKSFtQ29ofuodtLsaVGi1me/zxMRLhqR3Ovbp5SsuJQrHVQU86pVSBSIVrNW4avbQMf9nkl0AXP8fvGKBCFJDJe2AHb8NhFbRPd9N2o8yJ1BS6rE0wJyZH1O7ArCZiV+EQFYMZEls87Na85rhdrinOluGKSK8t6Gd4nEF1AmJpSmpdVYG0o5pJdqrSzRIsTzwywQKq1I6lAi0Krr0lKA2+i6Ec3OkfrRwPlNXhxYnAnTwrR1L6pGDyzpftLCqXf8dmX1/gfQUddr2ME1Y+FBTkGrA+f3l+rVfhKK6200kor/RhaAfSVVlpppZVW+gWIQMhCXTp18E2WhP7iD5OADkJ5zyeA1M+OgHyG4FJMUPJWgTsSvPd46ZfJmvbRf0fc8wBQ6kIgQS6MDqGXABBmj7VqFiCFGIXMDe6uVsxqbgm3nt8WwHMDji3x/RyxuE0AFbF+n5/3ZqUeTUcE0ScwnQP66JYSBKIL5PjeULgwvYJILBx7JQCMOs8oU8E0bdCsO8PiLVkshlKCIlkY+s1wYxyu1rkUcAE2m8liCu4L9vtniCr4ikH0HvPNDOB+sIwIYRFLWJ1VCBEKWV233s9PZILA7WxvPFIWM/Wxt5nMAn237wAZAFRUUyQgsw2pWt11pFusk7m1Z5jQcq5J7OiKEJBwp0+YCoNBON9MUFj/isJi86rFvB+Avi9Q1CUs05uz+j9ZmDSqSLzmgaUgbRV+vYa6kpF9RKzOoKXlaTwflqxL4PyYG/eXrn+NgNX45njtjkaQ/q1amu9GHBoM4L2agtIyjUzxWliCT2zxTJ9lBkAgbx8Jq7nWHgl4QDjL0CaIDXfo5Px4rhXm4rUYcFoNGC0OQuzQhbnkQEfHuLWVdacGQJwJ8ISwkDaOVkG4EKBcAWc3wAO0WUC3xSSBx8GrLW31WLiUAEtTxpq4pHYy0Jbd8j0ivTZBf4C9ScxOGmApGuhC8QQZPwuLwuaxI7ezAi3YMDmYY8tP6+vquTLC2jmNc0UDljWuwYvk7tJVBeFiOEDnaHQOYDpA9gAltOE4DmR0MCisypUIz8+KzWTKWqY4ZvkSIlQJmUcRMuUAcnBE1fo0xppC3XW+O7n3dsztZoA4Y68V7P7pozVI1dYPIsw6WwPOARincCKpjfo8SZakGjHQY73wFSeNm5aIr6cBhIMU1cOawAF4grYxj9TuiQtZH/oViTUb6VEkrzEIILzfjY4xQC14W85Dehnb+z3/dXX5En2Bs59a4L8VcXv9RuELz71cDnIX522etxvBRA7TJer3O46pi+djF3o841P7r+8JS0P+X1YAIuR1LMDEXsyqAvZ5aYpcUXKf/w6ezzJjrtVBdEEVUxiy85nXyf9XYJi7fZ1rlWznHI6FIRWK2rPUWYbokCjB1v9bf+a99rAet0SYqOAjFdwxg6lgYmuXBwAbwPmzhckiZo8lbwW4g+Wn3obvlFCC1zo4fzOZG3aeTaGsO7VSEBhlcoC/sCsTiStFVUgoQDnvF8CA9mieiOtN1A6M2hti5FbBk523RVNmrTNV7QfPSJfSb4wgfFJpQAbOv31kfplOuWSP78vPU/eO3Y/j+ElZwkorrbTSSiut9FW0AugrrbTSSiut9ItQk7GGTIpetkQfJS/4oUC6esIBHiQv5LhnNIE3AFyT4i0YldStCM1Fey5aWKSHC/ZHUpyrC1E0CY3d5bq4oIph7mWZDIQtZLZ6swuLN8yWuLpVNMHj7TZJiRk2hJUhBKJJaEGAKkPqEwgXUDzBhOaPAIDyeAmc95poKq8JyBUk1UHuimkzmfvhwmaZUY9H9a77irKZzNKc2AEfadYgg9SG2OKwVwHJrlli8NWEetNlRg1QgAPTbr0HAiQB9gRgAjXLTm+lIxY+0el8ILDhBgY5wCDqXgXEBVpemia7pAZo5IKE8NHiTAIq4sK1bjkagy8Lu1Za6Rj1MbIAvH4SZdD7tXQK+L5N8t0A1IOCf8b3AgPXM3dRAE8HaRtHmAy5xFYJu0GObFbgE1H3TtFfM+tiQRNsZ5fq8T4Q4GcAogA8VrYZk3ECB/yLNngSwBiL/ByEXaw9ljgeoHhHjIuP73ABxfP+Ho+PHfCIAh/wiOD9C8bRLBILmYePWqFE5rLW3eeOztpTgl8ke0YQbuDH+OvRXhLWdqeT8Hjk8TtiuevQloc8Mbx5dPfubsY4NI6oNEA80qptnfR/vs4yEzYg1LSyqpobX+YCqdWs4In6+iRmUQ6Ey10CSyiluQNiDaUxam6SQbFXSEASPHzIoOjBHeyHWUFWqYDas5JcuS8VbHrr9f/FrVIjjIEj1lCkqCvWKaMyQrShiCsuBDTTu5yGvkfzzhKbvXD/P1q3DjBcA+Z1uOTzUQBlGZ7N9/PnEqLv9DOhopV+NfpaTC0fP154yv/vsGT//5AyKH/givrEW9nteX/29DvBxwSKSgK4K3ZtYPG497VQDtrA8xZKSSuqKIoyqLh/FlrksyjRYP0cGC7R8EwDgHtCaR1zO31fTN8r4Y4AVuAqAdETE36ngsIFxS3LP3DBHY8tYu1tCmWxXjPRwJMIxnsLAbfM+OAhpm4LY2KGRPgRLYAYHw9+WEoC0Fnt7KACEsJeTJnKVMZMKdq1mwF11/vsDtfZzgLNU0acRYLhL86+pL3FxmFNyM3dxjwdexZtLP7Ic8ZLyiFLcPyUS/ZTVujH0ljeX9WkVlpppZVWWunH0Aqgr7TSSiuttNIvTK+xRP9ZYk/1/AkmXFHRJoAQFyJfwSwBH1hwHiCsCzlqKlsGNhho1upVDTgNsEU9v81EeH7eN5B59rLUOgOqOHfJ+o4QgWCBBOI0S79aMVO2sOMmtBMAtSq4wVCPJhirFUXfgAio8gA8kgPBZwYGEYHPXNDjgp0ZFSSCWmcwM8q0QWFGmSaPE57aVUwpQmaP983aLfgWZGCEuaQt04QNBA9//C+m9+/dUu8KjNtBUBcguv0wIbzQBoBiVkUBsHO3i9sj/W4KC8XaWwWo0gQyUZeani8en9Ys76X1tQJQxxQ0gToBBNnAGAVWDTJwsGBTzMLdrEUVz/PO6jPU7zR1Me4ocAsViK+WIn8jfXGO9qZZ6TtIjkr5deBDdnts8G/loXf0Y/hvWJq7R+qWZgDnZDLmNu+ql/9hkfkbbewKAFDAmAq7pw2FFMaZKp5FUJhQVAcQntyjBGBTYzMVKDswCWAzTYACe499yg0wDPeqDnoyQTV7+kCzfvWcgACrEz17wdlfCnfzKsDNtYD4ppUNgAMBYXyrHegMazNnKPt57gJ+z1+gFpxde2zyAC8E5PzVY3rTyCvCU0hYoTMIMrIY60fKFerrhRpK0cdrSltxyJZ62443FCNYZYB3tVi/qs3zSs1rX2r/iMHe0iN/VoHLS+Dh3tpx4glgwoYCwFe3zDQvJyG8n2uFOyFo1vNEMBCFeuzwUMY4JwWrKUztm6KDtHkwcWnjoIEv5BajbPF2lQCp2vZEda62V0l+0Af35d5yS1ZrlqfGLQK8DtxGGuDS25qbcqPCYpDbX1SaWuX7jA6X7eqWpVEuhSlcjKEPNH3k0nkMzwkAACAASURBVB6ziseoTZPz0mXZe3r5ygqfZ/rK1vhRjffFfcArNwqvLE9WJH35uTHdUXkEr9iH9fH2mi0OLb+/jNofz1MVImZJTnlySG1hhRjmTjyfTwQCFcUsBpxX33+LqLktZwKL+JoGPxv4LiM1Z6vniaKrDitvXG1rELd6u8cTAu4pQqsQbhn46HUozCil4GEqmErBf1EBM2NK3RN8m6CAEH6H8TUiO4fdpGIQgFu2dO+IwKWgkP1mtf0UE6N6uKlQ9M4grkINRBcAE6HM5rFKWDG1w2AH8UPJSmFx5iv87FNrUzBKB5vWVv13nNNM6UBAAIV7edtAFT/3LRUBl+PrZ/PCJdi9bLtj946l8eIn1uPESiuttNJKK/1IWgH0lVZaaaWVVvrFaCmTetkS/eeXR70MzHBhSb93B8Fb8weJJ9UOogMdPMnpALgntXjo/oy5ESZw6S4YRQEq5iKYHYkVoP1NTAaMO2BTOATY2toq2mkrimdSr4O55RWoYxqet7tAjbpSKjsFeEHPYL0AnVl9CC6Yav1lFnxVBFXMMm+rirKZQCBruwSmR3vEuwSLo05NmNQLMVidAZimCft574LJt/7Y/Zi2pvfRo+hGnpsmWAfOAOxg4DkAbF1it0cX9J8BeCZqQv8u2vOiOoARQtKlyEc8b0pml4M1UZM/anPtLlAUd/MY4MsPsahoDbTSP5n+alDomLv2Y3TrU+JSO8jA6PHO3/pzd4vfS3r0+2fOlMRdlxN1rxF7AHALaJB5o9h32f/wKaLNvXlXPunUBdGdYzqm6MBpAMLddXSPwY6BT7fE8/vp8kHm/dFBIN6SOwJCS0fYkeNSA/AY7/Gs5+1pMHWQ5ajROL3MTpZy/qECx8qa/voaeshVg6/HuqXe/qIdio37TJnfmvt29UXMhos0Jadzz2sAzshc3asqSik4P9vgebf3vhUfK4tCe3+oAGDz2KIANh4GRhWozRo71p9u+08O8AfYVFuZCBBxt+loaxxrtIoVpK+v47p7DECWtvosu0OPtPwS0rb/sz4IwfcObNbypFaOiDnfM9IOni8UKaJeSGs1VJvCyNHCpOcOHUsfL/tfzSdX+nOpD7PlaD8+Elx/5cvpelqnrMdbLgvFyeX14Xfsxwer20VZGwsxpiYqgBCIBIQZsxKUBcIWN0hVzFuWJI8aMVvc00UVgag4LzVrdQ2FrVCsQueveZHUXDwaPrpii/0wBWLvhthTKwHsCk9xJrKwHxEWyVIrIBQi3DtwflYmfGRTfr1lxhQKtKqNDwcn+UTAO5gHmpsFn7FFBFA/N5Eo4FbhzdqcGTRNfW0P5bA2Bnx9YQ/jVdjCqbS1wfo23MlHf1cxbzAWat14nS6UkK0wmgaQ9UrwfGn7kOV6Sa2b4pz3LcoZX0P57G7ZHYLlp67F9yV9CTxfaaWVVlpppZV+PNHv//2vVXq40kor/bLU4mF9y7t6QtD5Z5CGMHk9zPzzqQugIo5ek4R8TSqyiPGGQZbqv3X4zFkRsgC/AxVBYf0Vd5cgSI6KOYhcuxQeLeYceozZSPvKhUhPHJbehAulJhzK01hgMbit3ooL7dYWtN1iKoxaTaRc3YpMq6Cg25EIu1BJGdN0jv1uN4iH97V62dBjqlIX0hRHediBnxAAVVVMCYRnVw5gKEDnlk5l6AZwb5AGfKuAlFCuUsxzz4uJUMqEaZpQNlMX/Dh4xCZBasDTXGcDE8TAdBFBnWvqHYPCd/MO9drE/puPphP5/Pna2ke77KgAUGZoicCCAIlARPDkwAKBsCWP+h5uH4khasKshgyo4hnAuXfoY4BrgxhypBAKAj3ObuGwhhyBjLDomRJovptnXGy3UBHsXGlA0njFkMKSrFx1aXHS8nvdNnj51CC3+woKAO9krl+4sbRGeWXx/Vl9dX0P6B+2lNHyyy9yGjomAL0c8A27/8DjrGu3F7/PYa7Zt5sNRAWzSLPmIgLO2NScpAnpOeGfndfXCHaagLwANZoFWVKMmXx+7+bZXlGDNEXMEvlsOxl4Kg68dsl+44OpuoMyGaBpLTMq0R5NySzuKzaAKQ0c0AjeD0NAuwJYw0Eo3M/aA8fcqIar+FinTnmPCQv2ADmzcZ3APbOk98PSf9nDAazU6FMYIAHqXDce1JQXoJhKsXWmATodcGZo699cjtwWti7aHr2GlaAD6NlluhsW4owJewcttgD26Pt7Qnf5X7xfSHwMdm0LFCqtXZljbe5tzdr3OnmFqL4fCIv/th6k/U7AL6pooWX6eO/x4bNmB/kex0C+sJKMts9W6K2QvRzayxfgeVbIi+fzOGnvHONXmXdo+89psG1/YY3+z6C8x0X+frAw/ORCuD3x8Xsv0EHx+v4mhuAh6J0WO7J55rO7ZccNyBxTL+hz8GjxsoLHcLnvWwB05ZFUJE33s4JPXl8a2Im07qArU/azV7xjbsqZGFwsHjg734WDxpQWkcbjsqIXEjCM8NRy6Mehz/G8N6N0MIsroYSlbQBG2m29g6+lMID6AxHuPVb5O7/HCBAduHfL8N/YzhdnXFAK449C8JhIzSV9VYHU2gHdtLi2unql7La1XWH2+ORp3Qf1NNTOr6JqoTxcoSrqqV6U53lvCleU2w12vmgnJqDOZvk/zzPmOmOWisu5gohxEycg9vPswOe1hRGx83TaD1Dw1dYZh4P8J1FWMDgGeDP3EFnx/agiyYJOuXEf8oYr0y3n3UorrbTSSiut9NW0WqCvtNJKK6200q9ARIMFW1iSASN4MGizfysYdpB3++9oGY4JGplH8OHOX2SXjKgKHgBcCjfhdLxfYK6GCWZR9kCCc4G5BpxnPM8Al+JCMsVeBCSCJwAXMCsQE5wQqiho3oMJ2CcrhWirrccU30lI9q0MVdUs6tXK2sV2FstblFBE0BATJpA+ATiHcgWJuewVfQJCWIMLsCRhOcK6HphrxX7eY9pPKJMJu0IQaPHeBRpx/Nz6Zd7vvbxuBSPqwiGLKVs/VyjuobjE7o+9l+ENarNEtzaoADjiCTroQLCqnalZlVvnePpwwV4h6F6xI3MFrNawYFVIKaBqbjDDsnwYN6m/FeYxIBqfvF1KE6rC01eAkpNcB8u2pdi45xDYraKglb6TDoCSX3dM3efJRcMHLrRbnR+jPeBKRHLEQtpjWpN54FjoZSEgNWa4ZfH4QPNWrQ1eTLeNG6mDBAFINFm5V8KUlqQL7RMo0oTsnnaX+VNaG0eAptUsgRZVDSglxDrUyzq+14HsnncvV2+XI4LqpGmW3y/5ucS7qIGgxp/V14mjFmRkIPkg8E/joPFr0hbzvEM1HRQJN/BR132dm4IYNCzCfS3UDiIHuBL1JjhgRWQugEFgKlCtUCi2Uf9jVff9xM7L0IzP2/IQsdBjXCmiU1gZiDjfGsoYPVSMwj2XKDWvJdEfFJaj8bqa+4VQ1pA0fPVIF2hD+rwOlEZRWj57CIm+xjZQylMyUKOjP0Mftc80l+LZqDjG+62Wi3XxFGTy63K6lV5Nnd2Ml3X8jO9dWfHbQcPve/uQQjmn68d0EPAApMWCn8S9Vs/lfBGIMJRC8dTmrHh6Jd5N4KbNvaycpW2+B2AfTERSA0fYqQHhj8+0iLQu8M/G27L2lNeNneffs8Ud/4CCu0L4CHODzmQxyc+I8YEKtlNBKRM2hXFTCjaRjQPatQhQ1cHqtAq0uquH6Mq8XiDKEAd5QQSpFh6Emc2te7Icb2uFiLvBB0ynzvqq0ITt1vmkP6ek7Qw2lCWs/hGKSOY6/p0qrgmIUBmj4reaJbvqOFbbkSziq49r9J9Bp0DxL1man3o338s0KOz9SQoCK6200korrfSfQiuAvtJKK6200kq/IJ1yVX3g8nbELb49txACR5KqJ8sQz3WhkDYBc4XinQB3HtJboHggbQKMN+iA0IUaeGogkOVzMc8GrIugkllEFiqohTCpmptxUZxDIUxg5Q7COIkIiBlbMpC7NmCdBoUAdel3dvkeQMlmU7CfZ8wwC8YKAkRB9IRAYkww78CyCBSP2N8FQHLpQAOBrkySVqtAZAead2BiEDE2240BWFoGawSpFQRglrm7X0yCdP2jtnxMdPSAuEteN4aBMs9kFuNUzI2sAKgEKLOX0eoIMgv/AEeqKrQUbJix2+9xvt02K51dnd1rANxNszYh2lJscwaAZLTYjBjOITsUjKEBctx4+2pgyaYwRAiz1C7ghAMcwwBdAAwH4xt/KXUYa/nlS2+EVHaFQb6F2ih5fcP/WrS09PP5zAth6bk/8OQ+1CcHJjfeAhFrvDZLPBeEF+Nz6pZcIbzdThMU6p5B9CA/K5pZBatafOwob5RVIia1Ao/Pe8RsDPAheG9YtPtlAASl4KvjmhQWkwwDUkuk5eBMlMvc1buHjQQkdzwjWW+jA6Ed/6DG4woz5rl6uSkjVKDw8lENEJDcTqrN3rR7SDoH6TPUFYf2/ngJYDsVIluWimhTYms8zSskqgCFL/X+btR0AGvIrcYR7tO1WdEPIWN8/Ym2Z19LoACTtL47i37xd8PTDHnhbB1AICut3WOciCNqpIC6B5QotgYoA3KLfEmAeAbiFPMsHT9QwAwyCYUdkAmAmxgVCqkzQMClEPYAHpLbnFB0aK6Wvb2J0KwarV/UkPiElIViSaxP2gDzPPJOc6ExTnLut17vnspL9CUw5W/GB38a/SKg08EG4cT9+JnRQuex8f4A3C5GW7N8pf72keRPXgtqo/TExiqHxzhGX+N6ugHZ6Oeh2Hv2YtjpA2reodjnv73DvcI6ArhDe7e53S3giXzvGgyHenkGG/nYplmGHWDX2C/397Q9zu71hPCBCh6Y8TsXFCogB9IfC+MjF9wx44wMUC+FsSkT7qeCc2JsSnjpMNVW0eqMlaGszfuGF82Ac7E9t6h5pop2oJlAzKZcRQqZ7Ww1TROmSYGpNHfy0YYCgVQfZ9Us5YkY01RQUFC1YlZBrTCL+LninSo+qXi8eUB9/fwgtsH5dyE/B/V9QddB6mu1uiuC4vuQZu0e56o89l894r6P8pl9CZZzUkBYAurfSxEz/pu9Tq200korrbTSSgOtAPpKK6200kor/Sq0kIoGWLAUlrYDOdHgtv2bs815Y6GZH8JjLATq+VlKrgkB3Lgg+oEUD17wECcrCOdqVpMPMBfDD6S4cJnNAwnOlFBqRQFhT4qJCdNUAFXUeTaBjbpVNXEDbQMcn0rB7BbXQi44cdfBYXGmUQ+tIFjMxFy/Os9gB532ACDirt0zqGNC/Cy868KcOwenL4Gb3tLlig3AxgwQocrc3EoyF5xdnAMAmAv2c3WhlqfdhPcEumLITYW4tflB76sL6wnYKiAkHk+WelxCIswEdwlpGWRPAXOtIDKjPyLgafeMs83W2k4UNfcquRVrNxAEAJy38miz+pvJBIWSBJYhoDNABuitDItbT+FuNOSWIaGsXzXyfxHx+Eor/RC6PzGgn/z6eeMZnX9HDHTAFXMAbFQgYPNyAXgYhwwg2pwrhUGuDAScBu4IcKUmXxnamtGg3uHhvta5e9pYU44kP7ju9eckwOlYK3FEcBxASwLXqd8C0BWoIuZ5wkCMp4qiSm15UADYvh6LROgP47MHRThohScwnaOqKWaF+15QaiUXgneA2Hh2UQNzIu+og9VHcA7CU/u9KETU58AtAUXnoSkoBUiRHpUqrZzb5j2ETMGNFBc5xTRGo4gRC731O6gpZ6kSQLb6dhzRAXYHAJceAcTLR8Rt7ctTw0Kpp71UpOtt2ZtFBzf95173hwaF93ZiX1/bmw3MaTuEthvoVuYZMO99k8dzLuCBwuQPoHUN/CfT3wsso9i4H94ZgMTDJ/I93xuemCth8UzB/906HXC+EnxnsZp1Px4d5FZfP4iTglNwo8agU/Ey04bxPaubAen2nFl3M6i5mX8kxsQFhdiVahmFDVjfTBv8ToQ7Boqam/pbJvymka5xmHei+GzaAXZNdXB1Pxwdvf7ioZ1iHxD1ouI8sqp5oCKCMEHEPYMQdVfhOqTelhQGQSdCnT1+vCre7is+acXzXHGhis+hSCuKKy93aybta3qcBmLPEN5VumcXjIoLrUR0fLj9ZDpmZf4j4pa/tDb8vTjBSiuttNJKK/36tALoK6200korrfQL00uW6IOU+HtOy5RlWMcP84fx1PtvTdf9Ydy7YP5SO8gTYM0DKd6CcQ/FI0zo8kDAuRLO1AERT3lShfu4hRKZa3dYDHRRxUYJRbXFlO1CaovVfVZN5D4R8BxAg5e3MGE/CwiKwgXqZQHCgs6tEgFsN2d4en6CqqXVKsMOQnisQK21uXS3lO6HVq23IV8zC3VcMWrcpYrn/S7FajRLCnFrDL3pgLX9ux+6axgCi+s7L9G5MHakOBcCTQXbMpnFqIjFKE4IeLMyVWBTJpRSUHY73KtCIZi4uLUjYaqCZxdQnnn+NBTCBFzPMDihioCJuitM6WNQ1fqmx+0jzCJQFZxNxeI01w6cH4HkDtqBHZGSFwROuRGXT33p92vpx2EhP2Li/+fQPwY0GhHfNmliXJcjwtgnAja1QokwMaMgQlcAcFBxJ8CWtcUO3WzMCex+HqOHi3ToL0BVY4fGB8hNgg2w7BZf4XY2qAGiEiC+AbKcmQAZYF9FQAuXrc0KUYFZnZcgxSBfTrSFhWJBspoEmhJTsyTWcB5r71Tx3yH0zklHndSViqJrjq3dqu65I5QEzgEYeCIUMVCR8rSUuFj5dJ5RiZqywJTq1gAeAI+ieDq6c2gdYO0k/QlmB/AFnp/3oQpqi0duz4goztQsu6lEvuTucQWPEv1+mHHEGc+Np8N4Jkj0Tt6XNKUPxa72BMjBGwI18GjrpoexlygE7EAoxG2Ns/FnyhAbZggYu8nKdjZbeJIHRPzY3k7noVCWlRwWLa3pSqxjVwrcpdU7t8jJDsLLIPqPA4O6wszPpC+vf3/2evaLrwwnindkWr2czEL5NVySn4Kov3Z3sfRIootPOrjzcjn7tF+4Rz/6DhAxIJhzjQihakMp7V6K5cxLqHZkmsDXOFu0coYy6iKJo4tDrk9SzmJPgN3K2/64/b4j+/ygwDvfkxdfwz8ocMPmaep9FVRS3AqD3fvIH9IB8Soe/zzqPfDd/5+9N21sHMehRQ9A2Umqu5aeee/9//9370zXnsQWgfcBAAnKdpbaq4eY6YplSxQ3gRQOcKD9fcYbqwFke5e0SPQS9bP+VqXmnBD6loHm+kREvnZ7NHgFVBRSBVIFf6ugrhV/V3MW/lNMN75n4G+/eXbeihU5p8po7FfeniAPIcDSfQFtHoB+goZ5ACgf0hZ8I2Uez/h8M5gyZcqUKVO+rUwAfcqUKVO+mzz39eVBGOgXk1+trr+OEUxPPpwR777Wi4OFyN/+G5CXDalhxMkFPXSz8+NEOn7b8vsBIM9JFxFtEXkXwMLWyHoWSEdED2rLg/6JxI0rZuT+5Gdfu/3mljrda9T8KtP1iYCIcVDFQgRezLAkqwLEWPwceK6+QgwRxb0qrgDced2Dzp2ZURN4oCpGp6eezzyAVw1Du+D66gb3hzsDhajn913cTF8NNQIVB9IvjImN6UcAgHz4Y+xPqAHqYYx6VQAo5J2ivGbU9ysUnxBjvzVUAuPTcEeKKyXs2wmCvRsGVQTKcDr5bvtTNYTAm4OKClSgSsUewA7APSzn/MIMgeKeE5UmYE4EPl+P4bRAAciol9vbrA64RT0imiioPwM2a2Pj8zK3+0GNpOM5j2mvJ2u3Jzzn+dj696mFnynvV5GJc/xScsn4GpHo9nzlaK0uoedXKErS8M0Qq/1zRPpGjtWD9hUqpnuvS0STnwLalB6ODJk0Sm9XBCLqz/kW7OhRy0w9qkyBRI/u9PZ+7wrT5wEjBO37piOTvnGwtx31cs91dzhxtRZ2zBcKxTLooGhjFGRx0Ew9Tzt5+5tOhKL6+JEr1LjfYTCaP+/hjGosbAwEoY+jBwC0XLfx27X3MamtjQdmn1/cygzJlP/dLaGPvSKNnwZY1TuLFFBG2wBpA9OjxLgumGh0cI44EmFHhrEFMN+TugA9n65FpkZ5h21eXj8frY65nFQn9XmT+uBP7WOzXbO2z8/QgbqZ9ynacpSHR57Qwac43p7/I1T6U3eqP+oN4+e/xZwby+93p5917xMZdN/2p833FH/y9zp809YQ7cUH+G6OWZx+yE9hv4Boe490r+HFy8BOPdeEoa7xdHs9tNeFAQfLAWJGIfa/1MBzwEDzkp7WzJChoi29U9WKv/09jn3hCd0VILqIQHzvrL2rHt6PpinCTNgve5RitO3h7NVXMAPOmRhUtn1mrCVVFausqNX/k9rq9lIUf8f5EmmdLGUM1HRtG4H0jny2yjHe+ft4z37ilP+WOugsQB7zLc+7M3WzbtQzk23zUnNyPnKHfUXtp0yZMmXKlCnABNCnTJky5TtJvHWeg7W2RovnHF8yf33P41+5rr/KS+E5c2R8/5BZ8ClzpEEK/p00uwTly/T8tefvRUPp9k0YyD1foBKUIi91QOKSzh/LG833Xlu3RH8OwwUUH0mhEkYewa3/9kKBTylXusLA3xsl3JJFp5MKdm6EUo9IJ/J8f0wAFdxLhYiiFMZNYbesK669fw5eY8ux3Xu2qkVfRrssBTC1iJZ1PQI4YvEct5HjN3olzHKriOUZLmy5hKNPGsXgOKqKTyAARuze+5H4DygI6/v3fgzUD2TgdhoFJTOncavNOKo3GhS5dnxPQCEFlYLCFkmyrkcca7XjiApX8voExGTHBx+vhYqxATAbPb6uINUBrGpoyEItT+KiwNqAkD4/LeKF3MjIqFRtVrrhhx0UOdaK62WHfVmwVsHae+IEaEhT8gFr2OZZCTvWOaPUlCk/W7YTcRNt1PK8bk5bIbgRAIcDGMDNsuCg6jTrbpBXi+beAbi7v0crKADD8KgBgLIA6KAwuV4IGtdGQ646GOgDiBUHgas7LAU1fAAfkGiaGd1TwBko6OXdppyD56ItRL3iR/915wtnRG+v+fwoPSIMQQ1UUU8vUlo0mwHb1/tdA9vF1w5mautzVcECwipqjgRpvBjXEDqAitWCpKsoUm1rCnmicTUfJpDXg8T6tqZcvoM8tCXZfB9MBBrjgnMOD905KrCvlg/cr2fPO1sKg0WMNQR9bwEa4kEBKET756hYrB0Kcyu4QqdAP/hgN+p5tXnZigFBBbgjwY0jXHsBlI11gCXaYPPe2YRtfSKYg50qUCtWdOA8ancTQI4KBBunsU0/K6FRIX9s61HMIW9HdkCkvj94jpyoBOCLysllfa9du6uFJlmlxAmUzu97q17es94Q/H5ZR9hz5eNwYWH/1njTZZDysQd0PKbLPYvtc4TsGIvkmJTObnov9j2tvPglu6I8Rcb6PZp+4GI/PzIAaSLkFsWrRmsFEYh8bYkfNDEtIdIDdR1lj2bsKDvdeOwwmYvtS4dNYj5Odff3J2MICW1oDr4WTU5gXvAXMT4VNmCaSnt3KsFCUm29FCj+huB1NfB8hUCr4l4U92mMCX5+1D1SQTEaDX1+OF6KO06rrYuq9l6hahmoiAmlLLi+vvF0WtJmZKbAJ/bPvr/31QsvK3AvFf9XV6wiDqJ71Lkq3hLwjl25krVNxPYS1RdgYnvf6052qfdjXpMn5MjrWxqSE8aAHyEU85BaKoA2f0Pnp/l8qr8va/Szrzfd+w2+TZoyZcqUKVOmfAOZAPqUKVOmfA/Zvuvo9kO8EGm37sT37ZjOnI9nHJ+twDPOeUJdt79/k7p+Yd2a/Og35G4wyi/n1A4st/NwjABPx+N+vpuCFECLN4jf2QzRbrnveaG7ocxqYwadiELob+dxV7QX+2ZKa2NLLcIthL0uBqp3IzBRRA/3e8Jp2DUMBEpgtf65sQTcuFXtxg4At6T4M6j+QA6sh7kJuHfj1JWy5QpUu5V4GJyCPARCcbVfcDhUi75ma5s5BSSjtTdXU3+EsadFEmpEnVGLhB5GvtnjAvy2a48q2NECMLCKR4F46Vc+nvcOjFwpowPc/RPjc7u3/wSlESQWKDgZmBXaIiTdFjb8q3DKXYr+QKNsBoxW3Qx6Pg6pfxDmQ+0zrK5ry/O7jz7UEXIXAGUVHNjacvTIfabethaBTh4xCkEVBvk8LyDUAOZVcbcesVABmKC11y/+HUy4Oh6r6vh7O3+MpDUjav79vBYaNNnGpqpAyznZxiMdnyv7sWNormken8flq3Lpnrn0uXX/quPLNsQpT5CbNn5kjkkgXBFw57qtsz1YHus9gCMBO8cZDnqyCgHEbU8Qke3hgNQAQj8/gEbRHI3chX0NGv1euv7tpnhKuWPTkoV+XXueB/1OOJI6iO554Nsv7eNQTlsv0FbIBicx54hGW8sAtMg+ArAQQwEs7H0EGNirgPABBXtIK/cAboqhR8GHfmVSFF87yPcafM2g5ueQ9xXP0Al+rkVoRisVu6UgwBHL+W5jdxVRnUxg6frUqPirzYNqFMRLMcaXky1j9C22OclNOZKQUbA7mCXqwD4b88FRoxec2l+bWyFIxeeipYq5jr2IRj/5nTTWQwKIzTlBAagBUpHyJCSmxsiS4yN9Sa9q/2kYk3guGvDU73FS0uZ3AMFWPawrW905ftcn9rmanqxjm/s9dM62nO3xtm7bturm/HPXnzv/0lrxWDkX6/8z1pZ2Tx3+9INtzz12HOVuWkfDH/vUcnHT2XPyuZaU4cv3DuFcFTVthyf76QuDEI8Z8nuSpvUmCgx+i17zeJdpkdIKc0J1JqrGvBTOu23PH8+sXWwgvLZ3pvaO4O8/3UMjzcgU1U4BahNhIUv3FP9xWXDPjB0T3vh+963f/RMBfziy/Z4Uiwp2IvgvFJCKKoJXq+D/eoojE2cDiRaEHlKAl9LScwCKV37JOzK9IsR4RdxzoSiwY3OA3S8L651EDwAAIABJREFUdsuCUggqlNg5rL2ml+x9V0nN8UwFFQoVxVupqLWiakVVRfX3onf+btb3Cmk2p7kDOre2jVqzO2/reIoPdA5cj3VB05XtyUp1sKWorVBtbnlz01xLVc1PEMHB//E7bM45q1OpnzWw0WE8P/dA+/FCmVOmTJkyZcqULxP69//3/861dcqUKb+sRJ6xL7pWO93mT5fB7XljinLA8eLxWdPVpePHzEvnjp9xrx9et+fUNc79GZYw4Nzr7NaYTW5c+NLjQOjiBT8MQpSOOw2h3dvo8SpEYGCpWqgbwaIdyKO0pVuQ+72QiXO7SSkMwGFAEunwRoxLN+jbMUdfuNEr4h4jwu9PJXzwiHcC8IdfWfy/ey/xlgKEt++jLwSAUqdNDSCjeuTF1W5n+U7VIgP34ll32XTMQdGogIsCBzew7coC9kB2AA0oEpUGGnBDPjqtu2gFYBSHN7sr3B8PWEXa9GxODcmIGvnfgTDUd7rlPyLEzgfdjGWETwT8qUFZa/kR4SD2XSo7bhRmzIXMh3K/LE6TaCDIKuK0kkbFKA6gZIxA3SCoAF7gGh/0Fi98vG7dSCie45w8IrPW2gyJQAfMQrazjX08g+ayEAMMHI5HXO/2qHXFqoKjrM1wqcAAYreZq3DjG2CgixvOCG2+9fPDkHreOI/h3PH3SxprMMyl37a/P1bWaFQca/I12PiDsq1Q+vpbavZ8HKBi7rfhhGfIz1oNvlQeypP5xAIA9Jy0ZiR+fHLsijF57KtpklsorkBYW8R4T31hY9OhcgJhKaaN1xquQg4Utwh3A84LlUEHtjnQ6Hat1n++uMFhXXE4HIf6R2R0ax+FETzAgr72pu7wOsDTbShWmI5bYLSzYXCvMeE26rnpLvcZYObm2hbto80NByN36BkiZKctSZ+h2ijU4fou+rxpbmcguT/W5kRnTglW9rqubQVWKIpH7EXqkhPxShrgzZBafZx6y606hON6bFTI0lCZGBd/ZnnU6rEfiflgewB30tIO8ERP7cWuO1Cur5WwJ8Kh1SdYZOIMu3E4V6h3OCsbaOVpSarXjjliUm3WHcXYdda6otfmnCvC9hvCjcJZdtJZyRnxvEjrt22JDZTZrmM4Pe7X6uY4/05nzv/6Yzzj3MeOmTZl69eV1/dr+Qwr2J67Mw3Ihz944QiAs4/VU3cT6TiA3tRmVwsg32uDutZixD6s68uX1zfDPuW4VgCK+/Vg+jx097b+wx3zekEn5/l2bFjbW17wxNTQm2Hx4c1XKRUUPcAe4cvulBsRv60M3eggqSCK67gxJLXnNvQ/AUwFZbGocy62x7e9v7TzzQlNmqNY+1+xNc/201a/v6hgx+Zk9KkUlGVBYcZr+DMvwKoV76Q2ivZ4typlwW7Z4+W6osoKrBX/ZxXUukKk+msbozEHeH++rPbx/uYayy7cXaNv8luezaPXIHxk06vRR4UL9rvF9v7R/uQgRb04KFmOcxHFi1qxSsXdesRdXbFC8TfLSC0vPV2GQNOasBmXcw8m0zgfN2u+Ao2hpK838eT4u1M4uIUDRQLMNcYlHdtrYyhqamMeVcy/Afb+sgXvo7ynHVOrf+6BXDcg7UPStbkeU6ZMmTJlypQvlxmBPmXKlCk/QlrIVDe3Dsfb3x87/+Ix0jEeOM7fPfNe36RuD9X1ofo/UrZuy/6RcvrK242XVq+Wg60dj8ax09/HY7fANyNHRO12o02c3yMewGHUkmQ88HMABxP9HsmAF22g9DlalUdBzXRtBnUKuHw0yuVo+24g81LcCPap0bvambduLLhRj8JQu1fkElUQKoB7EuyVUGBGj1u1qLJd6TnOCwUCbjSFxY3nrOrRKYTrsDQqPLehGz7MXDJ0CzMB4pEWShBRLGHECeueesQJCPfrPbgwFjBWB0DcWpN6MqLst/Pb/kZsYfQlpd8/ev8YBKBjEReenaqdrl6hDuSEhdKdBGB564vTtFu8e6f4FQAVt/gD3fC0J6PZDYBdajhsYFMPDH3a5ocfddgt8ip2h6i74xELN1LkoZVtGj9yrOmix7Tl9pgufD53fEnozF/d/H5OMw4V+sGq7tLtztX9seseOodw2j95vH6aiv+J8mQQvQHLWc8+cLqPnpncnX3DI40PABbqZwLwnOanedQp/dvKTWFcmW2imZqpRwfnpTA+Xy0LDodDA8lT85oMxnDV3ly3Kg8GaFie94UDIDbFxL6uRqR3X26p6y6N6PgAhZMeIfu9aba8nOa6eoWj/4Z1NKLdRS3fN6NHOipQSkmAsa+jqp2il/LqmcfAQOlbwNOhnGozw8SdgYSKRQ16JDc7amVrXGlzhLQzFwCwlSHqHyVHdGb0GYVjnbV7IXImgD5uwTSzne1R5h7AgWxNjkhzyhcMg5MiMP38ECYGE3uEvJWeaeu38/kh+ZaOul++LtHl3x+aj19x/C3LaoD2hYXva+r2YFm/0loSe8cTOd0PPvw39GTXteeWD9MP4w6kqjmcFjY9QEzmfIt4H3laT19ar7aRuc2P1PWtPc8XBiU3U/s+IVi0cvR5Cy1OIPqwJrE5jJmzaK9v6OKmy9X0GETsZHEHBFG09BrxHtEqaCA+uxMqc+Q1NzD6lhlHLnhNhH8TIwjmnTQdb6nrQybgTwU+eDABEeGNCo5qOhmieCMV/6el1zKGMgSI75HPnz1vyZWnbsqcV6/cK+IdWRuIgE9BMd+cMrg5Qyi0rbXd8aN1cl/T/ez3UKxQ7Nzx+F1iRou+7v9Z5Dq268B2z9E2ifm9a6zHY7Kt+rnPp0/W9j7xDMWeJn+HPv8I6X3/4af8seO8bwDQotSjx9rcnTJlypQpU6Z8U5kA+pQpU6b8MPnW5qtvZkL6BY6/VVm/ymvjY2/z3+7YbERkBlLdGsosn56yRwUTW2TIEE6sbiSioSu1l35yb3tZT5G6DsBHpO/2/HOjzcl61gHcHlkYrWRVvEjVkP4RCwBWA9IjP+yVKm4h4HsjEi9LATQiIxW7Uix3tgqU2fMR2n9GPy5gJVy31hO0Vsv1DaONRQMOzIjGxDi2yDUzCBU3dq1mfcSL3YIKBapF50QkT4tAbHhXUEtS+p6c0L2PDDa5b1ssXoqgUSiITknd+5HicFwt+pAZFYpSzBqjTs9rwE1MLMWOGWXZ4fP9ARDBZwAviHoucgWumHAf1WRKwI+2uSLuMNHqNyBk1PLqRq7kFQKmTi1MALQCV8yWHxLA3aZ9bRKl8sfIVG2G+2R6RmvI+MP2jEe//9bHv4I8te3PKeN3aPfvJmFsDiN1UM6eApN23r3rr8gLXqigmYXJOEMMYLYSgsKc3VB/ezSg2xgt4LnQ0Z8fCojDv2MnmlUz2O+W3VC327s7c/nyLwuzG+xPI6kzSGuRrOr6L8DNxHxBFhW4BAV7VxCprIa9DOrDVPG4nnGisQ+da6eNBn/nO4mS+7fazzcje/EgURu3o+fkXlenRw/AJrrRjfUBZjd8nNGiMQ8MFGXc5zu74nPsHFeARZlLBy6K5zQPRpF2P6fuWNgcqtZqzC5MlCJ7dfjMyVliT0ahf8wODz5g10RQjz69h1q94PGULdc54cqvvR/2G+aUWHzNyZGb1fuiMLd5KCo41BWxBzkXb94lTWSkcYZFn5/osM0+qIq2tTyXc9kvZpyPv6vENi+380e0iTdeDScOP+Mw/HS57O/0yPuPz6mmzUjHCNg4f3PMMHB3z8XSQbizTDBVqAoKF9wfjsiuPn33f6YaZ6QBwS3C+3w7t8dPGRZTBQ4+Ew3PnK1d2hR56NfOOdG6rul1rwkkkodHO52dQpSgVTzKWztqqY04HC1aPkBz/+81GJ/IGKIWZixM+EyMv/x8uEPqew9Bjx5WInwsABHjDYx1y+nEAFVUGDj9WtFWmA9MeEOMj4XxF5vj0HsyMH0pe3Apvb9V8NEpmRiK18oG1qNH5zNzn1O+psc61NViXxeVBK+q7c+N1Qr4DxPeMfC5SmPdiP2BivYDxByOldvkZNVP98tz5UHVcmZLf+npOimHxo+NHTEcFZo+of5buuLc3uvcfb/X8ZQpU6ZMmTLl62UC6FOmTJkyZco3leda5L7Cgpes+6NZPl7y0V7woRZpxk67JwFGOFCZjUjdQL8xwoGSpWtr8aP87aNVRtxvc71FyfVTAjD/7HV74afHOX8mO1bU9IW75Itanj0mwkKE6pE0hQEIgauAFqckdAMRaTH6PgJIFGiR2gBLxZG7cSmoBlUVS7EIjft1NUN9KdgVxno4tG4qxc12wlCVMRsC5Q/6zI7sdO1/+DEDuAElGvcHymGACoOlAmrtImcuUP/MToEpUNTjoRuRAHyGRQbew4CYhpx4hOBThAOs4U6D32tgwLvhNj42bhCMeQ21vM6iY57axxv/TFNTNO15V32VnX5rKPyZxrEfjTf8Sm3/LSVN8aeBEn6BP2fskXo9UnBjMPaCI3KdiSEQV2HjHcNETlCoEEA6lOOQgZdvuWBrcFG0iLXLdU+QR7Lrs4PMVlFO0YZj/0SkWBjxz5XfaYG7I46vmQ20CmC166WgMzawhjvuAgAtPUigjAl49hC/+D2DgCMYCwc1Rpgh7hO6WtGB3LxeEoAjR15fZx0pC47HFZ37JIEa5HsDYlsfiRv8nPt28NMTQEg9tzmw8xocvKbs+eJXX1f3SrhCxKu3yYeDD5E6SLH38g/DTRmgSBrTZ1WUAZjDgShwZgJ+Nzl1cHxAvrWi/dGK28UfrbFrn7m3+SL5Se398XJuhXxC45PeAky/iqKl7inJA2FMR6Dp73PreVqveEcZiqOTDydfD1s86nq51zl+8n2kOwgQm4NNoSCv784AFg2tYFVnl9J0RkRLi0dk97uFM1m0pUedl/b3zt9BCrE513pEugJ4h0Qfroo/q/19h874QswoAN56w1+Kff+eCWshKNn+mdnK/1yKAfXEeM+EhQlEZXSU9vXlL1H8TcBrBT7kdRIMcgCeHEQ36nYH0L0ur9Tys7eVVxVvoRASvFRL4yWa0l5BmxOCpY+6PKceAs4flO1J1Nfcwf0jO7klp8PT244OGu29GoGjp/1A+m3KlClTpkyZ8s+RCaBPmTJlypQp/wDp/vsd/O55AAlgoyxXMGoVkAoscEzGQoANsH3+Xl9TT+AUEIvIxls/vvFoOs0JyAF8hOIPWN7RWwI+UjeHXGtUvcMDR6m4DnpdC43seeW5oChAtUILQQsDClQiLFSgqIjICK0eKel1Wh1Y70YV6+cX+z1UgUOtOFbBH/srAMCng4HOL/Z7eEg1qoMVQK9z0FGOx9jaEpvkiH0A+BS1aV9fGi0b96qM6hGEADzCu9d3vyzNySLqKR0P6pIMmAckUysZC0Kn780R+72dNUCm2gpEjxUKEB3NsCliUU0Ki35fAbzws3O9bpTwmU4dErZ+IP0HjD9cAOMvde/XYjB/qlHyT/nflJPn/kvLaeXZZ9no863eCJH2nBsIfisBcZqs1R5Q9phHZgPTS+TsbkZoNBrwMVINg64IXXJcjwPEkvHhXVkagwgAVOlOTdGuwtR+jz8WQQdn0uAWkV0KN4cAEWlG+dxFAd1CPXctp5qRR8+n+kbUewPUW5tN/4HYdJcDCFxc71p3oLAxa6x1TZh+j5Q/uo5ugPZG0dh4cuPcX2s1nUo9P3AG5NuycuJL4EB5RFiKty1FJQLwnMGKZfHUJKvlsV1qcsYj7x8vihygQqOSJ1z52nKA9Z2oYg9nS1Ybhwq0fPN7L1qdirmAcNvG3ajsLYq2TzhC0Cn3HMnrNvo9zm6AYu+T/GksFbh2Z8Ps9DeWaFIaY8xpeQqY0wnw0Lbrt5Cnq63HTux65Evu+9zrvnu/X2xuBqWf4FvQtoPjDvoMND0cGWBMuNotUDVGJvZymn+RHzMzDkfTx0dZB9DxYZaGDHJ/2fp1bt3b7um252/Bc2AE/cl1IBeLpl5KwX7ZNQebYOUKFg9V19Our6QKBJ6jW3r+a1O5Ac5zcz5g7gD5G2Z8ZDYnVCKwrydvnGXjHYWaFbyx1xOLRDcqleYoSgA+OIhuQDnwNwSkds/XZJHzzAwujI9lQSkFn5ixRB8RQSo8b3l/73sL4JU4TTwsIj63A8x4TRb9/l8yJwJbiwjKgreaZocvpKqWDuA/JKhkzhkizr4FJAduX2mJYLnbnQHg/GB/5btnmr2bB/4h8NxuPQLjff2k4e9JRPqUKVOmTJky5R8jE0CfMmXKlClTfntJ+deSGP0qtzx4HbCkBlyYDT9nnA6T3nkQvUPTmo6/zvp4Dsv8BOAPghnHqUeeCwifHEQPCWPFPQHXAtyx1f3aDRl3UNyoG0BUwGBosYgNZQLtFuhxBR0r4BEXCrOUEcjD4NWwXWZAKgoUBwckInJwVQWLRTwubHT5q4hFnHhdj7ViVwqUARVqgNXPFhEBM0PEjHBR36DxVYkoROsCVaPVDdOvRYwa/r3AusRSNHr8jgNVRNTBcvSxE+2G0jzHKID0KKdNdDNyEpnBl6rgFujOES5Xr16D3r/DpydHpf9cuQSe5375oTKAilOmmMS0EHVaX1LwZoYUTxmSn2d1UBQ0zudYahQBUPSovlrFQR57CkInAf5cKC7q0cCB1yoojETd7sZyogbqWrX67wa8cj+33RBQCgh9fEBG/ZUaBiubUoT7sixY1xowztn6p5L6x+19RB3QpnZ82g/naJe78b8xgMBTbjTHqVYAFGgUzwFaqTKWxcCpIgIUAhUGqrSxsenRQUL3YwNBcRd10d7HR2chAblTHDD09MH7YW/TzphWNruX3sbkQOD9QBExeqm7nyCxH/nshYRD32Py1PN+V+mRv+ePv/e9n3ufL7nmq+Rks/uMVb0/Qs+WmP+RWoPg6Qz8cWF3HhUVrKtp09Dd32PfEdHamo6bPjqzt/ej9DHWnXj3CX2kCG8oRQfY4TpuWQr2ux2u91cgAFWrAeRaLTpag5pce7R0EVRx5i4y56fCxersKSFaxLk7agX4fEeMnQPtDDJWK+kpOKDAS1W8I8V/Ja9Hl/rNAPUdCP8C8PfiAL4oSLXnLOeu7+w2VmZdBVIV23zt74hamo3GpOJr8Guvzn+pryOa/teOFJ6XXVBVobWiOpBuDAfVHchiL6BtSMnHLaZ4T23Cvf7A0G/tmMbj7VSxfhgB9EtA+UWJ/qE8NztobrfswPnXOkBOmTJlypQpU349mQD6lClTpkyZ8g8QImr5TIEAz7cv+x5tQqOx3kD00QOfHKjUZvg+D6Z/qYHt3DXZtshELRo96hUGsT+T+edaMdCU37rRHS2+pJfNMIP3lQhIPDpSFHUV0H5n964RdW5tFrLQCxEyYEcVlQw83jHjcLTolaA8FxVUC/zDUornhVXc7PcAFLeHA451xc2yR2EFVcJRquXSRTcURc7iEErtyMdbea7ZJoCbFQSIgMXmSVB4qiPbEXsR9SvMKU24Ym1G2dJoGZngeTUtMjCMk2GkC1rNGC0Ane4YveyIRBe1iBubw1YbgmApDMJiAE8ViApev36Dw7u3uH3/7myfbCO5JINO6QLVR3p0kyt9e/a3ND6fewq/e+TcI4bJKd9HTnP2PrHjn4hYhctUjO82In00r48G7Dg2wKI7b4kqVulpQaLeDPToPjJa9qJd38XpjP5shy5ZpXZQI4rV/twWAioUI5zdc25HVzBxc+rRKglQQmPJiOJp6D770Gl6G8l9i1A0fZkAi26lHzs9LqTep7vdDi3/uSqA1fWc3atKHSPjN/eHg0h9nbZzwlGgwqL/2JlaSuEBgADhZJ8QQNR+v8NxXQ1Q97HJdLtEjGWx2HACUNlBdGaU2DsE4OKDE+Nzk/TqHUb3AXGA6ZosBUlcc6WEey9k721d/dcdgAMRrq2mOHr7dwqsw9Q22mDLkR709OPvQBp/PT//PQMBrsFWp9auPoduCUPZN2rz9Q8AnzYLeszWFqi+AVh/l8j0rZ7qzA2jXAKwxv3n6XP48L37/R9Tl5ml6Nx9tmwWw03aCA8lPlBPbeN7AuxtbtDqv73tpaKbp8J4Nrve3S0720+HI2ToxoWw870aYA6UCmD150KxZS3Z7kAflm2E/NlzhqqfNo7Od5nvBmk4LwD4S/OKmVFKwVIW7HY7XF1dA1DUWlF5Ra2ESgaSA/a8MTswLAJmi1RX0QaSh2NyYaM6L8yNtj0i0MNRAPCtIgGKFVS1OaC+heJ1tXu99fF47e8wH0tvZ6Q4WsqCd6h4CeBfBFQQ3hZfdznPn3AIII86V2MKqeqnEZgUzNRyn7P3ZTg3EBTvIIMezCnLRQNGJ9OrWi21lYi/C0mjb68SI61tPsceAtqdCoI9rc+NPu7n3kYtpcfZYR/6orHjXD71gTKo7QHsC2rfp0P/TMNf4AsA+ylTpkyZMmXKLycTQJ8yZcqUKVN+d6EEgAi6oUDhxmKLfAtQ3CLOCEjRdhHlF2IAvJ3/EIj+PeScKTIbpQEzRl876PJCCQLBnRunPwfrOxFuRHHrzgOfw0yfjDMNZPFQJGID1YV6/kGFAeQBwhcA1fu2MDcwyercaYOrVIAKSmFIAPbRHjf4FY/2PuppBOKJoQjffwTCoGsB4+QRppa/3ZguY14o4HS41uYwRLNX1EEXAFTgRrQOqDQgwh09HjIwxRUBdhSPZo8OadHtMAbjFYz13dEBjId77EYJV69e47/v/s43/KXkoilaz305ZcqPkP4ci6IBvt3ITSfPXgM9kgKw3OmpVIWzYJjDTOifIYKY0rkKlEBQwgifwHMRgRKByeluSwezHKOwPO8DkNkrZBTvsRb0/OVQGcvx+jR8PD5E4zIFfLSDbQ0BlbbWMDNIu1Fegm73DJ43gpWmQ0V0uHVE+fUVyjUp9/ECuoMDxZrneMNSiqVRSWOqaaxFDYxZqwH9ZbdAHThWsmWguRl4vzAZ80pMgxZBnhp3pbYmC8W9yAEXy3tOAeCkXt0DcF7qwcCxKBqNcKzhrf80YKLnKdLwmzIQnXDrTonRn5eizD9Sj14/J1to9odHSP9i8iMj2J8muvl7CUj/Nnf50mZz05eC8Gmyx6/rVmPlcMchB0PNkdAdWr7T5AuANvRMbOVOidjbFae/UOwICWj/oe3XQ1ET9fQNFpnN9pfGcluEssYa4yCuwhyCCGAhKKMB5wGQ51znAZ4PNU7vY4C9OxyDNt51z98bR8wMItux612v5ysQ3hVCBUOjbuE07e8fhle7w1C1daT7WTHegPHR6/3RKeYt+Tn5vlpRKc8cG7dYjxrFvTpbgThgLulzrU5LL415Kkpse4R4zxxHpDnbxrtSfkfY7okzwdQQkU7PeyIvvYtkRwikenZHH9qc/8sorClTpkyZMmXKN5IJoE+ZMmXKlCm/vRiAwCCApEUDGBgBMItFUPP4wm8e9QFgyEmUUwDnjwGc30uyETGizK/DiBRGKTLTyx2nfNdJgs79jrqB/p56pFiUj+MKwCjICcBud+VGKMvFXlVRCFhhhsadWt7WHuVu/y6leL87bSEEJBZNKap4sbsCEXCodr8dFZSlgIUgYnSHPdvvaX9wPt5a25/Zpxd/V3UjlCEU5B2j1CmQI2A7t90kTIL2fZzHyUgGjZgV8vyTPdK1gVQtWmSTLEAU9yBce4QLMZrjAxOhkpnlPuMTbtSic0boykCXO58nt6S4/fAWL/EnFJ8hBNxBrN6EbYD55Q79SfJSCR/CoeFHyNda9qf8GNno6+2w+dP2KD6SqdEp/dsi0KFgAKsABAEvi1+RQE/qlLFRrVXqCBa3ejoVbOQH9yuZ8xpkdyYHtquDEUSei93LqZ6OAsDgvINCYLBHLrLnHQ/AQqPhBiAv/VU5wIIRYncYIDFYBHg8OhFoQkc19Ts7NbB9UYrR3ovTKFuOeQZ5hKKj7ghKXvL7HmK80rjnINtwmiO/R/Wc8mtQsoNRCgPidMQA9vuC4/0KUsWdyOAPADhIIHEvxRURruseTHe4d0c+6wPCMSMaAHZtPpj+v/F+O3jdApy/UgCkuHcnuL0D6hxgvPdDdK0ocA/FHgIGtf5YxTvc21s8VUtOO1CYAVFUVRxXW5850t+ozUtWAautG1cgrL43KjBg7uBAekEHsOLfWwL+VODUVS716ZnvfsTWazu2z79+81Q8olieCjBtT/tWwFR2yLG/8UvM0+0F8ef8/YNq+kS2e+qTYkf9d3q/s1+ffLP4Xr6w7YUWNqaJtVaAHBwlgH0HyZu5HwB6uNq00dxE7XanoedNltEhN768fP5jo5x/D+aBvG8EQt+Z/uRijqwWJe4gc/zPI6S1mtNrA84RusbPT2lFAAz07cQ8gOd9frUOAKDQamD23yKtJ0NeKfDeboX3HO1CcmRQdyrjlqqICkGFG8NI9E21ZOfG/hT08yIwbhDTVR+Z8C9YyiniBcSK96lWKmJOUKrNkYxKOJHZeRFdLgKIVIgIaq1YxSnxpdo5AJT6mo00TgKYY0I0NY3tc+cZgDEi/Qvekc7pmObE1Y4vnz/B8ylTpkyZMuWfKRNAnzJlypQpU/4xko0NDm8ozkSiZ0MAdUNNMm6N0ejhmZ/ucXqr7yaKbpS4c4P6jToNqtfzDzWg5YXn5s6AeTgAZKPpLVkkGGEEpUNa7m6PgtgVxioK1h79vBdBBTWa3FZf7ZTD6mVxROqJYhVFFBM3N4O+A9bqeQMv9QW+s1E9jX1QqvdIn26sZO0AW49OVO+esDL23IjRny3C5UzUfQO5NoAbgIHWVsMA3MAzG3dxYzFXchYBnHTWDmi5d3uTKeVJ9wn9k8HxS0IAXnr1PtDEsqd8mTzXtpzPz9eJ/6IOWA7MHQCM5t11L3VHLRHpOcZxRq9t5vY50EuaXk/Al9rzvDA5ANCXqEZpm8oOgCQ/84ozj78G8LLtgbHO6mCJaI3FywFYbQ4D4jAqF9edztjhBYCdtSTaWuHR9hH9t6lhj5H5AAAgAElEQVRdY+k4W61ONZ8dEeLvHoQjAGJCKTZWu+JgUa3RcdDIE5/ak27hgPlnUHkB0VsgnB9gOjf32TG6BYac7GFAT62CUhh31ZgDYkLc+N6DfP0XQwVbm9nXDfb23KvdfX9pgvt4S8emsNaKQgayrd6RnKLvBYqjO5ddK+GeLO+wwBw3CGjRrQFG1rxnwpk59YvI1+8nftWWfVs5BcC/nzyn7J6P2f7UpCMbLTfIHTlN9yxcPGJYWxkR6ft9HGbPAZPnv7dv6eIRNtf1VD92JrEBtVwKmLnnr/Z3geNaXd8cUdeKulYHgPt7AjG5w0F+RzoVdd0nqqDM5JX0V5yT9WZ2UACAd6mVEQG/BWMDzH6LoGfHMFaxSyciY2IhA7uVCCAGlwWFep8wCB9K9A23+tXQx57uQpzliaW4k4C/28Bo7aNea62oUrG6gyvEnIjbzpp5GEclAqm2fXr8L/hdVPNarH2JHqd7mgf+fazjF87bygnofQYUfwg0v/TdlClTpkyZMuWfIxNAnzJlypQpU357CRPD9gXejfVipg4Dz7kZAsIo1A01Qafdgx4CDBiMVQEun97qu0kzjLjh7JbN6HKjZgj6yAZA3Hj0GpLBqzsAdEPhjTepASt+hyBfrIeD0RnGvSvAhQExg6QwQcCoqFgc8CZQMyYtpVg5YZByCvca1OZet7vjioULVrGIt+vdzo1GirUKqtahr6ObTwxF6G17nnQqXqBTf7ZIxlScquJ+jTszQIyrpecOtuscCPKKXe/21g6xiFIRP4c6WNRqQqdRpq0+rRds4O40Mkia7NfqeSf96mUxquDIaa/mmAAY4PGnO1oEY8FH/hiNTP2QYKrA+jW65GkG5ksGvq+VD17wK2cIeOf99NLr956+1Z0uyHZCTvmmsnVy+mIJZR6HrVB0cPcZ0h1mMPyNB+RY5eQXANgVe+UsXFrEbtNraapGIGdcvVaLCFQJevER7Av9EOkxcsTfFugOwMLSabA3386S2vUnk1Opt6Lit1hLGCJ1dDILQAPZ4cg1yBCd3sETAkHWCuJxrPt/DJAAtYLLAq7VridCVXNA2PtAXomBGffJlwDwHNTqoJgY+EtsecsXr2NEh0tVkFj+9SMUxIwjsbUpeHG9rO1zfwWL/L4XBeMziBmLO44BwMH3Ezu/cOdOWAfjJMY9bAZdqY1z7R1i940+9MM7Aq5c9ykZM8yRDKgnMgr4eyjuUygipTKr81rvvchjOAiSzbddsQj1tVYDd8iOtSrY05SEU15mPWCwpYBBfu76oHza9FufFyaS5tqvKudAT35ihR9bD781CPXYKkibqOKTfdYTAbjLN3jw8KLw5sw9l8ayA3R9Wt1hqUqFqoIL4bhWMNv+c7cUEAj3zrD04qogmKXWKjisByjg+9fe/gDgY24nbfYsaY9tel4A0/PEhO1qEbTsutkXxm9ejX4+uS71PXOcG5TtzPYfcXy2teR4d2/gcF1RpUKqA77pvqwFKHC2EnuhsLWoU5g371uBOUxt56+D3FEuob9jeFNO25rWtNP5YnnbYyy214aWs7YToBXKZAxXTFiWHXbL0taYTyBPgeJrmNi6Ir5nr7VirauPIxkDB1GjeifY+UHdLrL2vOcSe/RgNaCeyoS6c1UJ4FyT84Y7Km378VH9ceZ78roHm80Z9dX7PP0wDCVtcqA/Q2b+8ylTpkyZMuWfIRNAnzJlypQpU/4BItJzxg3osR8GSEwp6rdHw4WxwqOI/Xc1e/lJFPAAVODbgYJPkQ6kW91vydr8h1oE8WdvtoHrYy7SAURHx0SDHv5K3aAP4EoJVI3C0ELKAE2gCYFRGFhXxRGEPREOsCiUXeHWPwvzYDgEgOp5beO7ta5OyZhzQhKWwpDVDJt108tRrT4OlzNIPtajCnrUAN6h69PvCRZBb7kPDchhN5RVESyFG4DObAbJKtqjRx3YDsPu2MrTTx1MBzJN8r0KrsBYCViwYSAgT2sginuyVACAMRZEO25PQOcNGvULyLlR4vT9RzIq0F8Yf5nyPykGjFr+6748dWz59Dkzuzc1hy0DH+KZHyV0Zpybo75Pyg3wI5x4nJWFN9Fxo1E9RQ5q7fosABsOxzT2aL2ky4ZIQtNLxfVjRDxG/vIA9ImcFl611QDMUAdPtk4RkUv2CoQjI0UnWjP2YKD4vkAE7FTmx9STIoIi2tqLKrbubLwcmM2BoEVvwwDw6FsRA6IWB9/EOhHq99ultWqHoHcnzyWuYF9nycu7Vnc4c0cohQH2MQtuY7gUuPfI04HCd/sx9kkxt9T2QASfj2qOW3HLLZOJqECpGJDuYyFI4wj0efgM+V10dnt0zu4Ipnw7yYCzzTVmbs9AMFQcpILdIQgg7HcLqgClORXpMFKFi4Oi9ns4bTw8X7/PPohCvVyYRmcdKtK2zEBVb18CnpkZhQhcLDVFS8UA25PKuiKo2+H7UHY2jBB2OvwMnhsIzCllB12ufGuDn+fPDRdzalDjPR+A8A7wbu7r60WsXSoVxviSQP/U/tQIMAAhA7+JXS810Nr7Ed3RVxMNe63SdD0AsLpjF1tfcbxTKZoTh5ysu85f5Y4MJ0Op/f5QS6HBDsBnwPuLUonlZTjutwHGew03r83ZifGBMZ4A+ZQpU6ZMmfK/IRNAnzJlypQpU353CUMQIloiIhnSKf5P5E5t3zZjFDUQd7A6KCx3HTpwns0FX5Kjbqg68KQSLkUeBDXjrVhu0hfE+OhWuVvqIG0Yano0ixnFb5Nx5T7d5K6FdiuulHDwMq4EAAQqFXfoTgtSGFdMEGrZfsFcABgtrjpgvDhV+7qasQrDOCluV8tmu3gE0R/X11gjSlGB++MRFdIAo7iboAd3SBq+S/0YuXwTrtPEwIDx/JFYHWb5JODgEafsFrb9ssDyD9v3VRSH9WjtZnIDnfVZgE/bOWA00Hb3/n2reXd+SCEph/gLG9fqUYBFzFDIux3UvUH2DnIcUt5IBfCvV4zP7xR3w1195sfjoPn758//M9397GtzPT76l6/V8mf2c7/mTlN+lvwwGtBmsB/v99y7Zxjh/C8mR89pfqjb8+zKnXGZOzsFsFAB6bjuGB7rkWtkBnlxPaO+wJ2AEdkI7mUQdUpfx5Pdoac2UNTy53IHLOB5cluEnJVZHeRiLShs5zMV9Ej0glZBB+yZOzBWioM6rkeDTrlw1N1TUahR31P3sDKK4mi7U67fOuX6lbej4Zyw6MJ+gUlEhB8yIE8A0QIphMVpecmjMC0isQ/ijWEebR2NNeiVvsR7fY8b9NzrCsUu6uJ08EcvZw/gwAxO/Q0YWH8nag5PRG1OwNcIQQdE1CsfqQMst68zHTj1fZ8M9udIcb629ANArKExD2IxJOydIUZUUTStT2rg0aHFzj9N77aWngDuI6Dzs0CaU3U0oE8XHe8e0yPb1jx1tbq4D4xx2+5THq1HwM59X/jQ/Z4ql67b1ndb06tlj5gVqhZBbiCmYGHGunpO8wS8qgKr7/9FBezRx6IRqU7YLZZE4bDaE3e/riigtM/rYDuQ92aadpmP92tzzz2ZrwEAU3tOo7Bch3ZPymOyXaPGsbLtrrb9fez3Leq8wFi3uFVLVbAe1z725P+diTAmJbwi4CMIpKbLRPrNSfv1Q6U27Y7GMhEWLoA7ktnrRHdq1lyhiJ6PSHQCVNTZAQJMps4WlR1108beWFUAoLg+dA3pYLWqQGrkMjfAvIpFukuttmf33mJhdyqwenHhoe45PQileqifS5HqIo2haMxlaxOLoMLHsunHk6E507un38dvzYlhc8IWOD9Hmw+6lBplypQpU6ZMmfK/JBNAnzJlypQpU35zsagvN1iwoKA0j/2cmxpAAxxCtl72XwuI/2jpgK6146Mb/F6o0XP/4ejLLdPJdTlK/Vp7JPr2vDuYYX2nYayjBgbc+1mGKShKUJoH5kodHInoDIJFbLMSjufygMOiOQgEEcFuWSy6Axa5SFqcCr5L4CJMjEJAbQDOZaPnFmePqcAacMdjJfRSIve5ldNLLczY7xYcjutQjMLnYjOU9vtQOutctOm5yvd5LhClSI+LI5lhbifSopAW2Fhcqd35lhQvlHD3TrEo8ALUqN2j9F8diM7g+YcLxr6Xevm3Kf9rMs7pnz0tRKUFbQcokQ3fEaENxxZEAarSHVuioAREtqjy3NQASxowaTpKnXYWZBGacV9Ro7DtjjO9bgG0qwK1Gt3tqSHe9LixflPSdVFrq18JnN0BdPYvtHoudTLgIxypFlOcDTTZAqz3zupxE/qT0CiTQ7VFNHgWi8SERasDzRGKiHqu5BgXsrbfoTs6RKRixQe8IAPxIAr19jP1iNdjuvcxemXbFv94S54H3QeT/XuJc85M4Bz1f6q+0wRIIg34MfCsAUDanTOC5l9aub/brumfIAHA9Z5nSmDiUyXphR8pXf/05xhEzRE2HBxFjDK7QnCUasC2GitCNCDrNwLZ3pJyNHVAzJcdMS71Gj3464+TB4dnO4b+7mOpOGgEoR1o7w46BpyXoCQ/g5R+8rICZGfS5BDV9YylGGnI7Em9XwnwsRBKWUAErAToCpA7Q0SZquoOYtTp5/0+QmKOY7WCRAxM92j0l6L4wDAno+wQkNplud8rlLStqaJG2W57Z21sZipin6F2PhSyWg6rcNJQLQiHLnHGlKZD4XVwAN8c10aWF4K9s9g16uw0vusnc1p4SLs+Z2a2t4wHwPPxAhrOO7n35ll6zMlp5kifMmXKlClTfm+ZAPqUKVOmTJnym4vlrrMoAcYCZcvTyZFQ1g1GEdm1NVA3akK4sYDcwNQiRHpuum0Enj5o3ujytcaDR+2cXn4Y1j8nCt1POYLeQdnbTUGK0RjTDEApEuc++gVm4BIorhuVo4IqgGrGMNktOEb+XrVo9AAYNJwYCFjAZsBSNBrYXifF58N9MvRY9Ap7c1XCkNoZCCI/bWnE3mZk68VaTzRowQGAAIUa2JLMRpmq97zJKsAFwioWHW+R6MBxXbFKxdVuj+N6bFf0qJkWb9UiOMe7OKVwszg7kBR25wZl9RliES1mfCvMcNZTm+u7xSgmBaC1giD4I9G41wDuNi3tVKraaKSjb6INz5EMof2pPZL8W8orr1KA6wzgTQKeCMC7r73vTwIgpnyltEgx1xvxvQO0T0npAIzz+Jw8Pi3syp7i2oCetVo+2d2yOFWxFWb5VQPEVWRzvETksuMbu6UYoK7o4DgZfW4p9lvQbTMDBQacqwrW6qDCtmUU2lOb41ooI7vW7h9gs6pazllEKg+0+nmtDTzw/LzwyHOVnkN28T5gBVa/biF0+mN0R66bkZ8WvbYEVAUVgi9e2IGwOjC8LwUC4FitD1+sK25Vey5h799rAGDCvRrF/G26U5YPUFwLsHM0+roqQL767gruDiuuwDiGY1vofY1+hO9hqOVj7mv2gBgO15uSt/ZWEbCnUDkVn1ABrLkOvyJLARIecETGBnNYV3NWgDkYHIOu+EzJ5yq27Z9tjVru5vZ7zJ+LN/imctK1NP7yp8+1rSPiyfUXfsmXNefCfFYCtWyf1BtOMDryDucqlrKAyXLUWwT2avucuMfF+mzv+7SF61K5tPkbO4NwwFl8T5NvQ4RGF746Dbs6W1KVimDIAIA1OV/2+3f9wxx9pg3UDMrviFAmAlapkKotP/VJtpoLopu/25b3fWdvm/19Yr/GRg69HQNgmeZizoGeVYCmr3L0ObFHPJ9UpVPaEzNKKViKRWfH+w8UBhqH05AzUbT6tnba378U0DRHCwh/U9o3ErAo8G8iX5eAVYD/skJC4SH279R6mCj2sB7x7SB3ZQbWFVorhMwB7L0KUK0eHCB0zAeY89Raj1iPq0e/i6dd0sYMJa7XxvGhtmbVugIVKGVB2wl7s0nh7FIKpWB4cZYKb8elecFqzsJPBc6/TCj+n9qX2pnbiz7fKI3jlClTpkyZMuV/VyaAPmXKlF9aIifWl0kCXaZM+QeLUekZ5TccABQRp2QP8DBB3Wc87RtQnO3SBYbQejQbitOWahj0cjRHgjybMTx/pyffPYa+nTNanDtzG1Wfz/vMHUSIf8LMlatSiHCjegKsZ7nWnm+1ARde/lUz7ho4afls4z6KRuwuYXTvxrlGOZvKaG0DwGHwU4WIUyGqRaOwqIHyYVoNYxepg+CMhTu1ae+dbZ7C88JuIJOtMUthCP6mvgHWF6+LOBCmRbArBXcHo6jnbJhz0KuKNKNV5FZsPaeWHzgMyFs7fja8EpVWqzzDBDbOTB6NtSfcOah/QqCrjbx9I3qKsJ8/8bJs5vVHMgr2J4HZT7zPKx0/BzBT8Tjo+dU3n/JNpTkt/Sj5idumeLQMJLdnLUDQDECLg7txTfRPZlE5riuWhR34AEopKAGopEh1K9fOq2KR5OP6Nj4zmiKx7WMCSV3nc2FYelrFcV2xowWFSwOceolGLa5SARTPL96BjYTu+noYTgKhF0/7byttDfK+Y7JUIxAxQ0DpLkHMQPFUFzcE3MM+r835zqq8XXEv3Rc+jhmIq2r9c1/F9WxExwKqfaWxviKUwi0qst3PoxqbL1/2JrDFEgpqEby60dHZcWw74RcAte2HxNZcJnO6Imo5fv+R2vCkUcbioyB8pi9XDRkUtWU/70377+H0qU6FH1dFlGqAcMGI8DPH4VxfxL4k2hH02Sd1JNNhomIgKbGlZwA6UJs0TwDD7JvKwQmBzMmjWH6Kdr5q6KEeaawYQV1o//sl/bjdo0dajLGpG7R5/LgtEWPPnq8VeRniNgLTFO6kxIzCBtgupYBL6fPKHaoY5mRgTgcefe7f2V0jCtudS8VA4dDD2TnR8tBrA5mj1gf3dGVivAaZc6azA7wnghYCo2ABQM5gEp1DbO90lr+dwYXxWgn/0YrjesSrVfE3FC89Qvy/AF4BeOuR4xWjXrSIc2BdBSIwBv3Q6d5uA8KLr3Guh9NQ2Ppgv+fUFhq3afOXLb0Ie/55svovy2LOYEPku7W7ei73WgWi0v7GeLXP8ba0nRbb+ZQXY0TKF2qOwtsJeC7KfDtHZ67zKVOmTJky5X9bJoA+ZcqUKVOm/OaSDT8hYVg6PfnUVDB43Te7nVvp2CPYtEehRyRWAxgSwKMBdGoY8fr3meY7V+1ZHv6b87YG1C04aOY4NkAAhM8BRhPhJSxS7oVadEZBp37XTXmAUbxTugOlvjyYFTg5IFRHW+y4rmG87IZjceNQbpZogmvcyBX5ABXAqhVYKxYHgrgwCgAWi1qsAeaoESIWLpYL3AeWnDI0DGy973z8Ny2viKg7GkD0MGRt+0lUwEo4oLboRRBwPK5meHNDZp+uCnF0Q2IuQZMxLt1PNRlobWSb0bkBHuN8EDhI49cFNX7U42qxnLZGkZ/M+tTnd68pAJ9LcZPWjs28jIjaE6NbclbJ7Xv/FHDCp8Y5vP6VG9QbUL4p7D3ZOZ82359m/bxw6weAikkN/+1EN/P5h4tPXHnk9ls9Thd+GOZMmuPbJ6C7xhhYF5S1pzSpdi4z9ehzRaLTti8smtCXMCaLMMyOYl5Xo64FlmK6vbBRp6/r6vcb25Hbu30eAgyM5dPAD3PwWtcVR12xLAUtWjRFMwa9edMyzKBCWNfVHYvQImxFYPngCTg6hTzU6Nh1E1oa64YzsuNOFDvPSe7hq4OHADtdR7hGFVWwErhWKBFu0zhdq0WFn+sLwNbLP2FR8xEYfw/FjoF69Du401Tu5VzewH4zDAC5Q4LtR2qK3GxFOQuNMQx47t9zg0bADhbFf6/Vch23uUKoaiB88TkkYsCaqKac22dnw4n4LmDYp6Tu7yvQN8ZqTh7nFOV69vzUl+FUmM+9eF0Dwu144dLGMBzXzsm23TsqXk7sS8n8OR3Yy06TopcdKC/Jc7t3u89ZXE8Ub2hmwrBo363LYexxbMQPVTa/pAhn9Ceh44A0gJYCS18RDkHDHjg5F6yrp6CI3U0b934HUvSUQFvQcNMPBvjb+8C5fNEtondbUNw39LLvx/TM2D0quWjtf18S8Nn3nMQOnJdiebrDg8aVdDB+vPE+LcT4SIQ3sDn41h/MV0D3zVFFoVYE3rk+eSWKVY3u/F3eUTsQ/hcYfxfCa2IUBf7DFUspAAwkjzWg7XsJAFkE/SswPhd2ha94VRV3hxX/8XPfwllUYA6YCneUaFHlnYZdvN+j/t3ZLBYhAnl1hAsove+FlBJOGhHZjrbg+Y7ZdGdzYDDHsbIU7HZ77K52Do5XrOuKlfw9yJkR1Onkqxig3vOjB8uVDYhu5tfJ/iP+xPMUdYr2f4ft1YxSnzJlypQpU/7ZMgH0KVOmTJky5TeXbID9EdKBDWpg+eaMsyB6zkka+PxzbQ4Boj75/FTnO7jRyOvz0XNf53zXL/T79OQQcYURvB7H71LGPROLSAequDHPDZGFCSgMXaUB7wGeLMVAX1WLxGMQhOqTjPQNGG+mthH6OleEQEHOEd4As7NhWCaFLFduIbgxMPLLnoIT2/EP9gM9M245Kl1UG285eQ5LAtB9RwiqnS74FMq51N7ttxka+fES1OyMrYOEff89wO4Jnk95kjxjoTI7ubvpuNNPfhIbW4cG8HAKygMjFf321mGQLwmYChBdi1GoE3mE+DOf5+rUzGUhjyq3NS9oaldVB9h7xGZgvuoOamtdsdbVa5XaEYun9lzJu0sVMaTcAWzFThVHkXZ+08+gRpfObACJKsBVcC+Ca19LmLgBGnep3mdvTWh6vRKAwrgKfIg6LqNpYmyniIjlfR9Xz7GPr9TLN2+JrpIduO/3OtXn0fnHVG4G2iXqOvS/ORowgENdL7T+IfnRO7YfI+PeIIDvDupZtgNO36NhmjGnxvLQzg1KZ5t/6iB6wII/VnItq+dwUUrzbtAWnXHCmifZ/25wnFD0FERDLm2fLjXYFND1HtBZe4KZwpyLek7vUoqlzyE06vZ43sMh4anyrTDCry7GnQqWxVNyEOHAjL1Tshcufe4lZiPA5mAp1scfmS3a2+tk4LnilffKW3IQnQkfmPAvIQhp6zd1kNc9iaGkzZnxQ3L+eA1CAeE9AUUVtdZGyx7nvAHjHcd7lX3/nhRUK16jovp1IuaeYTnMpf21qO7qzhPxvc/P9i/BEp9E+hLYL/GOtnEYyzqS0N8fyOsc7xhE3cGDySPPS+ljUYwd4Hg4GsuLqjmH+RpX62qR6NKdTIY1t70wnllvqGH4VnfC6QT756nbKVOmTJkyZcoPlgmgT5kyZcqUKb+7hAGhGaS/qIjh2i345pYU/1EHC3iO/h0B8yF4oZ0Tvw0BY08MudpGJZ5EKD7SrjD8hHxSwR8aVO9mtnnhJ3++jPme3K9HQJyvx0WhjVk/xjIOz1gsxf+tCiwIo5VFU7JHF3IpWKWaI4MAy1I8x7gZy1gJytoilQI4ZnCaAxELqg3UHuAoehjs70YtM7QthSBqNMl52CQZwSMokz3iJtNEAopV1mSnNkpXwIzLSGd6DQeAKM85YgPXDkeLxVe14/3ikW8wqt6j02ra8yCt+MvQ+ub+6dkYfx3lHLh3URJYGP34HgaOhwSAHvIq1fuV9rzo5+Sx36d8f/nekegneutLCzhXXvKMeqodu32vsfKws4IEMAQgrR0hLe/5BuKOqGajevfviBtlctyLgJQnu7dit+wgKjgeji0dhl1ymUVFNY0bbOyk2vFuWRrQogBQ1Sl72XLcFsvXG0BC3Kt4Ooo1RawujIbLXW2ANvUQyQA1AqSMnNLV85lzq7y2e4kKDkq4EtMfDAMjrgvj4KeWYvpWqunMK++IKC1SnADGKPIJpktVAfJo/x372qGWc/xIwI4YK7Tp8cKMHQgVaBH4cAAnjz0QQH6gg756ZjDTQcXTvcI2jjGVDQPEWKlFrwuMWjgifAWK652ZUlaPmqzQCyWabNO0sM/T1oNf/WBeEO+PS/rk4vcXixt/idQokSNaIj2Nwpll4AC4+ny062JVrJuxieFjtb3AqsdWx8KcnrNxJd7Wb2mAuybQ+bSbBxA6yeKR8KVQe94DlM37tFXrcF2ba7SpYd67AoMuUqDNH46ZQgyLuLV+O2jt/iGqWBH7JYuiXtjya4vrrMN6aIA9aY+ct0dH8Ji/qJ584uE4NfO8ZAcm6j3Ru2G7Q3+akBLIKdoLF/y7FHxyMJ0pOVhVcSdTbvu/SHn1hgjv2eZXjIOo4iUMxH0PBZjwgQj/BuP/ASALA2ttaZNe+n76rYPnqop33lYG8JpMZxEMjGcyJ6o3ILAC75h8K22pmRjdQdTSPZm+OVZbO/5TVxxVOnCOiN6WAUxX0R6trWp9AGopR4KhiPw+wfzU32O8D71u5G8CA1LtZxfvX2ZzPrOc7Z1+nnxtW6WiHi36vIpirdUA9HX1qHRtzgGxXrWI+VjltxM2VUXjOL2rDt+dA9anTJkyZcqUKVOeKBNAnzJlypQpU/7HJZtOwuDQDFwBDCAdNxMeNcvc1qDaDWvZzPgN6vpEoP3i9f43A9SfCbhRM6J+pq8r/zlyjqL4GRcDGKmLSykt0psIuC47rFItHyH1qBGBGfJUjKqZiEAO0DB3AKb5SUTEiXYadyZG4YLjAxScCouPKm65VBgYQciRe1tD+DhXhjzHcIphmBk3py0Q70vyvumAtZWpEKh45CD1cplhFPJu1C/RvQywEihxWZMyKrqh/Lzpfmz/97TXbcv+mL6IKKj3NALr0b7XOtY9oshf6qmd8SkzdNK4T2nyLUD/wJXiH3JlNEA6HRhLlv82f3u+5NAbm2sTIAzAwFE26J1guVsXB74DnKB8HwqgvOuiAA6ZA/INID9I0SNy9rw9P/Lx1nXta7IGeKdNjzevAG+SeGU8bbjh6wRwIJXQRkVMRJbPlwBPhmuOVmDs4eB5K56wwgD3iD60hrHj1M7+0dBF+3vth3cwMO86afi2JlUmGlEAACAASURBVBQDzaGKgwPnLSLTwXPgZNjRNWtezfVUUZGVk3Y2Ta7YOikcAy7pOKJYD3uscwabDJTSDk5/5f7ku8l3rlakRAHGLuhAufdfQ3Njbp8Dv8e/QeMMVWffsYjicM5biHCUerGQnIJmC9SHWIobakB4p36OOowA/Km73rYR/cnWC9/HXiW8b8Y1NyLSg1NG2zVt1vt1qt2pktSfUNVEf9/vGM+SUWQ/PXo/+US1e1/av57PJ51H9RtMRt/DlVKwWxZcLXv8UQres/eJGBV4pHggf0chBgoX/MXFI8/TmuDP9Tt3zIk9EsPylYMYCxOOJC33OaniLWI90VQ9aswJH4o9H3+RsRypCCoRhMhZGSxCXXxv+tpfwj5CUcUi2v+j1VOBGCW/iABizqdB2d7/anvOmvOZ95mtRQZMI9c5dGV+0fM1InSoJodZizhnLGQR/1y4g+cOpmePVVVBXVcc1qNF0otApJrTUa1+bDxX9rynStM4b058L2JJyufmKUjnVtopU6ZMmTJlypTnyQTQp0yZMmXKlH+KfIWNQHLkwwaQiC91MGT0v+TUeucqYIa3Uygx50Z/SDLt+wNnXfxlC5hvv4/fbsNkqQYGfuTndeZjJsGLpW3ApqfeNfcKQT1Sr2JP7OC2nbErC8gBlVUFa7VoPvZU3uyGwOI077ulmEFWjHI1cmNGNMoSwAlZDsc9F4tgl5FycYA2VFGroBJAHmN1tSwOJslwfgPM07wIUB9QFLgBPRnmAGBJtMMKN3xrRNb0OomqG/U7tepCPWd7z7E6Gp8XBwgWJkDMGBvtrsnI3dsxzohOyUotgjG3eyuPzfowCZ7DKv/0x+2jA16W9zyeNzPQbi+LCPUAwZ/y1IVkgH7aKb+tnNAaf6eI9DM3jjsOf06EHjx8skTk4H63eDS0PaerWMRlALeF4hmPaGUaSyFC8bzgVaTlSl/ripZj2A3qho0KVCz6b6HiDB3eEgeNNMDdZJiPz3U1wI2V+/08j7i6gq0eeQ00TAKF2QF+NCCK4YCjGpAuTmmbo21VTbdVx0h2DkDfq+IKhHvXh1de0Vil76MMp9k9ACgOHxUiMBcssHzlkWsdbIAKqyVd74CZWloQKJSLrRXVgI+goL7fTJv4ew+A1ooX6NG2oczUso/gSGSAi2xZBbafPIfvI3uI1ntk8+YqUCQAOw36dlOaDXSMfwPflFhrfB6WguKMBi0SVKXV7Kn7gRrnblChy9nCn1j+Vk8MDmUd5Hw88pw2xyYLFTAB11d7i8YXQVVBbUB2TIAA8kwaE4KzLGz3mcFitBCjZrYIl+rgYDiSWC5pYEcPm7Si3IJYx+1v8X1r1GvnpjGR2kB7hWL1Bjy+1BEeGp2LTpMXxkG3/25CvsNBKCL9j3VFdiCM+bwrSxvzCkWFuJPM+fENafHmNJ4nriN5s0/uw5lm0KbNmp+rL8TSA8BnLliWBZ/3O+yWBTvAgfPVwGXPpQ0Hdd8IYc8w6nbqTD2v0UHw1772vHPdzET4y9eVcOB85bQK/9UAriVXDm/Uqc7JcqBHXnD4nvpvAIsCb6SgeHsWZryB3Td6SlWxVmNeWms1+nOnce+gufj4G/Csov0VLVQWAVBqkfPqTinskfmhEWgzH8zpgNKzYHOKPfp/VwqWsmBZFqdr5z72qk4rb3Vc1xX3h4Ot7QjaecEqteVp121KAeqV8aWxf+993XvLfzi3MZ770ilTpkyZMmXKV8oE0KdMmTJlypQpT5IwDTbwMr4UblEecWY2mvXolaB4x+b3L7OibaNivqiM1g4zHd0o8JEfvuZXkSEiyP9WUYDcWJxOqMnAR0yek1Q7SOSgag1gl+CAspXBxHY+AYXYgRinRyVyeuIMIQ+2r3avMHxb7t5TCnbyhkWuz+F68qhSZGNaN7xHn2QIQn2eZeNzjszqALtFpxUuA9gQkZ8yAOIEY960mzHYI/EfMp5voaQvEzoDfp+7k8KA9FyjiFB/tyngpT5c8ylTvrcE9TOBHIz0Z7op+XjO4VFqWTv0mWu5bCncoQxkIH9uPE0xeS7huK8SsK615XBtdL6QBqg3dgvVlre81vGJKZ5PN0d81tWpnqlHTI6goKfUSPlwodqAyADzI4JSVA08T3pa1AFz17F7EO6h2Hv/3Kf+2bs+O3o/E1mkN4kYO0WvbItwFQ2Hq651xQFJcYcsijGi0Jmj3EMR4byhcwsMQA5fJmIDa3artPzqeUUZio3h394rqnEGbs9IbgBBh+ScAOT1A+nYgXrEWug00UxYj9054nfRn3+opad5qmz7w4BT/yWe0ySS1s9t/P/pkNk3GUdXtfU29gDnJGZifcQR7eS6pjIcyEevfy7DVvPT+49Pbr+m6Qd/prJmGq5R3XzX0M0zte16z87oG96T4Us33P4W9bF9l6ZbffleJID7sQrm+JL12+WUAV98axNvw59QXKviTjpLiIrpzwBoRcQYNpRQmfBfIVx78iMF8FIVf0PxSiP6/HTcCLaGxJqkULx13R1rxGsH3Zmp0ZoXNmp9sLF+vINiJQCqeFkVKAJowd/cdU2sCVDFH1XwX5EGnNdasa5rcwwIgDo+qz8/TATSYGUyRyglr7tRibizmTM6uUNC9AlrcGzo4LRBBCxsgPlut8P1fodl2WFJ65rWamD/2utcpeK4HrHWau8evoa33O2Ifk26IgHnbRRIz0yeUNpnlHcM3pQpU6ZMmTJlylfKBNCnTJkyZcqUf4h8qQH3FIY4cw4limyMQHqLEGh2lmwuTfV75Pfx3C24HscPVBKXDXZPEYUZlr+HveVstR+5140Ct5dOcLsWb9prhqmKWs1wtvNIG4vctosocsIKUCFuaDMgRKq2qEgDijtosJTSgJ1l2TWDrIhiYcV+2VlEtng+Q9WU87UbJkUV65pymace2pUFquJAe6eMB1GLig/gm4gaJavh9wbIl1Iswo3cHOiGeFXqVKykiABWRgfmAYv+7Ll4qUV2MRWQautLJsKyWD5WWdWBvREwODtw6JFbW/DlUUYGPA1Aj0jyoHJXkNOsnz5Hz6Fej2jzfM2kbv9x8q0j0k8AopPFYIsOngJiX1KPoIVdnCEj8hof6hGBm2dOi3jmLXItdFR3omkAgD8ghRjkOi2M8mF7DwBUARAzVKQDpWInlmL5dKvCwRePNGdumH4plkvXUkIUrBLRgAYwBrvGUriVZ3nJtTFnMBlyoqpY1wqPZbbnU2KtJIiM/RH09ff+hQB4Q69woPdGuQ7CQU9H6uDDdOV/gzr9AGAH8ghyBcwfCke/UuoYDc5ErTbhzMCgRm0i+eQzKi0A3BeBq5O16U60h4W2mdILOp2vHVAMZ4gAgrKEg9eVn3twEGsEytTohzdz3O5jR0ePnC5ScMSK9Rk02Ockmnpayv/P3puuyXHr2oILYETJ9vZ8+tzuH/3+79b3nr1tSR5UmUGgfwAgwYjIGqSSJdlc/qzKjIHB4AAysTA8vCvL+aSB475oLyf2+4TbnufjcfOO7VFtSilAjE9YVBtVDyOtUQKZ8Ql8DlDsLwhhqAhKRCF6z0aKleiZoRVOLCaf2v57edWel+ZPPp+vyYgw9MOZTMDvvK33oHwNjSHEc4/aXtuMZV6tq6WXSKv/16++wh/3f5r80DSCEh+v8PzUSLmv1T3rY+t+ZCmHr7T7O7wLAfsk6sSRJCaMZXV4Tsy3YxOlij8B4S3+RgR/iuKVhwI3At3DgtcNUj0cuAqqEn4FYRVt7dEkaSLP27uFNQ0Bv0BBEJAQrqS4IoX09/teE/AjAQUEZdvjvS7sBlctEDp+EjeCKkbCM2yffJBZovg1kedSBVKr/a+ZOO/rQQheier7QhlriqVa8H09MQrIvNC9jtxeHs04ACnlSKQ1We9WvLp7ha/u7rCsa1u/RSzKlVYL2X69XrG5l/m1btikQqFuOCXNG70bJsDXAgyDToEUAa3XsQ2dTKIPxycmJiYmJiYmXgaTQJ+YmJiYmJh4GM1FuTPltD+fMBLlRy3G4+dH5dtfjVyrb0D4471NEz4MN8lzx1muyUCoeCOsMIDmda6iWLl0r0b33GmlquUGTmphVO05xIO4JyJU99wECi61Yi0FRIyrCIo6KWWM9Y7+iXYeVbTi4dkleTu2fMJEEGlBb12B6wSTqhNqTs43BT383ePR5qVjen1yrkibwtnyHydiIn2uWrGAW4hjceVikDemqH4iodLYv94mL4EguH8wDgxvPoIScRLmf2P8RaIuCOtYOiJ1QjhIBiEQoXoDkphZm/pGBpTwmPZ5VSWHKNZ2nlMEC8A8z1WN5G5e8NxlFRNjXQhVCFXsWtpFKBG1VBgLcwtL7rZKKEtB4ZK8ubuHpoXHtedWqUbySHV5CecEyEKZh5deY8fGjiIAb+htI7S4EayEFZ5ygoDryPy1T6t/z2vfkB/c2zIiiFBr2yBqODoIRMCdCi7Q3taZqEwHNH19NzZr31Ykki9s74K3y+MoN8kgWnft1HJH784xUUtVIil0vsR+ZyB05JPtT6IG74tnGQl6f7f5BRslkfO8Sm17g24kl9q2eWMHiWhj4Fbb6dAv2u5vxHM/8yzs33dvnnDWHvlZe0POW5UwYtzLOzs/XtwibO8vzt7v99drS8nT9knqBou1mvART6mQ9lbHZ5+ZBHwY9u3Yjn+wi3mU02wtRqi1Qa0VhAsgFVuQ96pGnNfqctgNrqCw5mKIh7oHKV6fPTS9g6ri+62T5FIFP6ql0fh1d9trJizF1hkuFpadmJvc+lGB/2GCiu0zi5PwKgphwU8g/BLf3TBFakRCsf1sGKd2Vlnab7KHxrOlJS8ePYm7QctAnFP3hI9xXOL9zGN9XVas64pXr+6wrnduVAPItlmY9usF9/f32LYrrtfNDHoFqKjRdfa3VZKG7/uZdrjOP7bfDvt1YujL3X0TExMTExMTE++JSaBPTExMTEz8w9GU5nulZiLMuyJ0VER01cQ5UX6LJL91PpPnL0miP7eUuP53JGMBVXwFxjtocpa5pa403HDweXoFHr1sbNtQu5oi2pWpNUKpUss9vm3SQz0ym9dIUrHKVt0ztDRlmlNaUFW8u9yDwFgKQ5VQCqNeK67b1kZDcbK9ZTnXqCNDDj53drKGYrA1MCX3PEVhU5yFByl7ls51WS2krtTu0ULJU7KRIJFH2K4xr9TR+0eyO5pXZ+HSDT+05zhXiIc4tnZ55Xkg77fNQ1Xu4XRAlNV0gKOSL8LgEgHfSid8iva8pLnl3tLx80shz/u3BPdkv3HxQxrcib8Bdh0chGZMlDB22d11/G6K+80n21p66gToOH+ZaJgP4aGey2VmXK5bq9C6rAC0R5zwWoannEJBzLhbF7z78wIRMVnXIkOkya42/6FmRGO5uqM+JhuvW+2EA6HlxJUaOXh7uFx1o59Y3yzssRsRJNlHZPnTJYx0ACwiuHg73KXesMq4967nnF0AUDGPQ1ULy/sVRTQObycAGwEXN0wgNUnErV/tX1sDUuj8YV1WQCsyGPl+Go9TqrezYxeMjufxvuP7NSq1tz+C4LQPLQT/yfp5Z+y5ha6HkUYRwcTWMaBW67fqhlCS3zN9rDo+QM8uOkEb4n7dzz/8gP/59fVhfjy6/O+3arsPj+U432N/1eJr4rqYd+m1XrEwY5Nq85GkG7CAUUlgOZarEeStnpq8YK09b+wWh6OxVrdw8P63zSEvu5Fsh73ruKYO5GIm5Xc16NXWHXF+Vl+cd5SeHY7+wHGffVYEhYyw77kdiIB3l3dgYpMdzTjR21YtzDaTjWOTgZs/v7eJPWEUpI9V7XCadn+jvx2RMzze/ZTEH8TJ2DMhD/fB9GNPt9XaPM5LtmyS8WXi9wSzyWapAmWTaXmuhCd2vMP3as/6xZ/3o1ibFv0e0F/xndfrtb8ggy1iA1MznMrj7Nf8RRUCwY9CeFvs+b+kflaxtUE8HAhl2R3rmucyj6gGcU3saaM1I9KJpRkpux9xvfPNpsC95jnexxa2woxCjHVdsd7dYV3WFkEmjBkulwsu9/d49+4dtm2zKACwx1X2fbd/12YQozE4hjHhZ3b9vjvXjNF2976QAcfExMTExMTERGAS6BMTExMTExPPwl4pS9r+OVzbSXI8cB54jHkzvZIePM3+CmTF6ztXpP3llXgP7Hy5vN7JW4/6NZbjvHuIRMjXFi45CnIP8Xbe+7e6lwwzN29SEVNqNm9F8lyMELCm8Ow3aj/+7fVhNkqHnVBRwL1GXcEu0oh4I7YJSsmLJ9rCS6cgtPzfRppoUrZzfz7QPdujLTnIGVXzkndl6pM90o90UcNv1MkighHYoSqu6LnNsfv8kiCYMvljeLRP/E3wjLERXr3hPRyEGeJvJhLQZ8c+skSTVT5Xmdm8El3mqJPPOUVDVFYVuH93sbJdNnSjrfBA9icTW/QNn6NSK4IbqlWM7EDo7iO1g5Hi1cOfV6oohf0VfTYrPIQugwsgug1LS2H32nV5dklvcCXC0gSRv59aXQtqL0cxhIrer7SrmjzNZY/ojEXQH2ddnesdJP/4xPNyCYQ7vybXIYiWo2t54nza+UwYU787vCph4ehX7cYIQcxFuhCoh1Z+ZGX6u+AbvZ0LPTzMmcnDsysu24YlvE2bsYeNCfH5k1e7YU63K/vnUWCM15GPZ00kOtDlQSvtVkfp8WkxLFQVuiPedLzx08P3u+pWOTveFeHSTE1Wxr4GAFkmhULcDCVPJ+wHrOXNS/lw/LzQF+UzvX9ib6VEoFpR0aMcBH3cvamt80UAYTESXLxhua9DP7i8+J1tfXhLPdKQiOKiYoY+bhRSQPjFi/kZJsd/Z0YpC4gJP5NJ3tcUaST6bwdV4Aex4AE5FHx7TVVo5LdA3wMGmAAlbmX1kxp2bN2IxI0CSikovDYjsiq2dvVBzyAWgAoKLPUIM6MUMwwopWBxI1EbeoJtE1y3K+7fGXF+f2//V7Vw+ubybmtnkOntTdPrkRu33h6XO+Gfz7R+Tgf3130Bv9kmJiYmJiYmPl9MAn1iYmJiYmKikQdneNSLqSlAjiR497LTB88boaGNTA9lSvZCzyT6S+Fh2v7Gtdkzv919lkVzd0kCnXwaHvJU3PCEU4ow4/2MquL36z0AeJ5Xwlq4ta+R6EkZCzSPRnG9ciULl1zYCKVwHKmulH63mafTQowqCir2igLLjfjN3R1UCORh46sO6rQHqBYfA2ThmataaPoI08z+fpctQrybQrR6blYm6uFSByV8EHPu0SPj+Iq2qdUUsuxdXVUttLwr/MIj0YdvI9TvUJpnZRXBdvJm+c3j2d+66vOtE2f/UvMKZQIKAZsCiwK/7d3Rb2Js2cMQvoFcu/A6f5KH+3Mm1sT7I1tyvERxN44/Wnoi06BoYVfD0GY/HCLvbJDIcX4x6xhcPUJE5EhlZ9mZyMkLu14gTT4VZoCAu3XFuiyAKtZlad7dcDKDCkNFE9HukTYGb8nIV472MkSWs13VctGqGlHFxBA2skBhMuNytdQWy2LXh3fz5h7OBGBZSnsv1R4SPBuJNb4lN6AGoa6Q5qIquANaDnKEbHJiXwhOoFie88hpHpLwcrJAder5gW7feQgHXhGBlfYpknek5+MhpUeaE6cDkZzsihIJ8DD7PNwWRggCYHVyvZYCAnCpYbjwvJzaT0U2+Mj496+HANKtvsP1h/c+tIx9f4bH+Z8EfA3CPdDW0bVYMH+RCkulMoZj2cSM7Krs+30MHU7DXZn+i085HLtiiAFDycs8vZPmf+XhHjg9q8e9W3u7NOfy+ZfG88W1y1Pfz5ghkJPBKgjfc+eBXaZY1AmLpqB+zY0H7qf9I5xjlt/DER3H3vg5338sIa7JY2b4S50Qb/Xyfyzvt4C092VELWFi97yOKAjx3B5riSiRr0x4S+Te13wgu78VAfv+UOm1Ee+V8DMIC34AylswF/wXLQAxFmK8tg00vqu2nv3iL6Sq+Els/XpLhBJrjBtpkSRjACe74z2aVzu58dXtXxNDKxMIhQrWsqCKWLok2B685TtnAMIgtt8IhRlLWcC+Vtme37zSLd95xfV6xfV6xbt37/Du3TtcLxfcp2gwAIEK9XznBEiSBbbYaPuYka+6uQ5QOjAMtmEjj4mJiYmJiYmJD8Ek0CcmJiYmJiY+DK6A6srBc/bs1vljyPb4fixn1IN8GqXIXrH7leohf+unRPOSVFdAnZAcRiYrFjZlWqhhGaE074rDTCaZ0kwBEmglCFmYzm3zEL5BxjPwalmtbFVoVSxEUBEQM0p4Z4upeJ/kqd11tQAU1aLGWgpQ0eYtB1geym4Y4CpkMqXgaQ7WNNSyF0xW2SrMg4lBjTxv4eKbqs/HdHi1E9wzypTfEbL68VdN4S0B/O763+8VjYSvk5ye+BzxHuNSRS18LkI2Ofnq81lUfe5qIxA0roNiEzFyyfnZkAdQNSOi5LmuVRtZTgDK4j+Hg5CJeUxGNoP365K9oKhayHMGWI3CUhFwKfZsdDnDTGAuEDWP9LG9om5yNGSjTPng5pJ3F+eCxPcWIgR5DIBhHo3EUFQzhoJFBRmIiiCUcCInW5WD1Dw/H7nEMxp1enrcPMQPoZp1T+oRVgDXtsZpM3BQN7TYk8iaCumSOtFOCuxa4KPhQIx/BngFwuY1YycQt9ghuBGLYoz60IdFXqWO5OfISef9RzekGDmvPrcixUwm5uXGePxQfM78Wuy/GD3PeW73MHQhIhTPbV3dcKYQQ9o9u3KfOObPrmpe3a0P6fTCF/U8zzhWqJP4u4eO6QyMWP/J97qv2ds3X0PU2lNZQZvvHX0fyUSonsdcg+SmNyAqeL0WLEvBzx4y3Qwz+v5bYPPpB7H0Pq/JjD/Zn81O3Fc2maVO8LfIC5SNyJzspzYChgZSqO1D1e4nj0MiImZ0IBYmngGIds99Jkt7zjCjTbM7MCMMM8oQbBugKqgiuG4btusVl+sF21bNmJRSFxHcyE1RrZMg3E06lPLO2W/YceXqdWgH8sl2PY3HTsbHxMTExMTExMT7YhLoExMTf2vc+I390TD5jM8Bs9dfFE/QgGWlaVfy78KtN9IjFN7a9G8Uz2kuIZ28jetCtd6ULg/H+ns2njtC8qh6R/mIYnzx8wcE+dN1Pq7gf+orje5Sh/pH26kmxXW6J5RW4ZG+UgHIQgYzLAy7KHr+RTWvpqUUbLVi2zaEzw8RYy3mlcKRQ5e5EfEEYC2MKmJ5ismUhYUJd2vxsOdOlsC92XcNF98Z3JSQBIF4/k91a4FXZbH849VppEaedz8shudBRx5PGPR2KifdSHBCTpvDTG/9ROiktqbwhPLx+8pDYG5VjEyLsb6jHCJse4SnhrdNeNH/5td9C8vl++bmCH54ZD/mcQZYyHj1Zz87hPueWZn4OPhQBujZTMfZOns8HDP5tmeszxsoWnxXMnkhaop9wCNJdAoWg4mJP7NWcRnG2GoF+Rw2YqkEE9BIBCJCITZCxL8bAe/lm2tiktMmT8NYKCJwxOuXQoCHuG50cWuWJBdcvtVawcviYed76PbwOG9GP0y4U0J59Q3e/PF2aO9o7nAeDJLlTzdI+hr9HcwLvuIKq/8KdMc/v2YBENnMB+9FGuVTC+VO+/Pw/jRDnzU1AvXNgEUFgMlRBnDfnzSUc+DlVI1opyB807Xeb0G8mqenDEP7CsUdEa5OhPV5k2nakSwe3xu7E7f2lzvBd3N+Ht9X0/FmUKC766NNH3nsbRC+VqAuBQVmgLEB2GQDJMhCsXUZ6qlLjgR2fpymv22UDNV3Y7NUROztfLRDavXj1jfSVkYayntf3M5p/hnCPaltVANjgHwAagaQlBp/i5zo/p4XSe2Zb/X/94ktjnXwP60fcy+jpbbpW9/z8s7z0R8mmY+H3ufk73k2z/JvB0Y3zCHk59m4+gkEKOE3BogZb9i9qaFdzsec2hnh/ESEfxPhDRF+JHveqgQBQcmigFQi/LYwFrJnLVQAJvwMM3T8N1cY9yz4VgT/UVurWG1dMsMVz5lOsGth0QOgbu6jvjJRz9XOYMtVvjcc8KgsFnnF21BhUVLU/5fezoUAeLqlqEcrStUMs8jkgJHhRp5bVJUNW91Qt4oKsd8wxQRZTHdVxQax8yALidI6PHVcrLU7IzICxqgTu/PDQpzRF+DD+JmYmJiYmJiYeA4mgT4xMTEx8TfDnvHKx9/3+14rub/2nw4CKOhJbxsnANSVIqSedzIpMpJ63u7ce5w3baym5nZFEtFnowxttW7Kmr+yXsdnRc5L+9PYmHa9whWiiRQRV7zyYiHd1ZWSABoRrv55KcUUaa7SVd1QldEMI2Ce5ux9VNipHVIoqoWdJPMqNRIrwvV7lUQf8NROJAfyEOljIpTOOtzl9YIR4MGOt+voOKOHJtqV9XgvdFioVUakJYgwzoUYVesDd3Z8Y25I5qmUjntQ6o+an/ytT9t/fR7TbeKLwi2C8RzhaW5hiCNORpdfo5+dzehuYGWyrop4WF6Ai5EkIltPO5HqU6U2MsLI1v4EhbrXJxCGMyK1Rcvg4F8JKJlwQCcaJSn97TkMIvM0Z/eC37YrmBiFS8vhDo8gLNLf78/7P0xstVwUXRYMU1/NqziIGfV6hFfl3e7GK4DWYGokpURBIQRVD5xFb/Pcx3ZmSFWR3cgHQqPnPI+iF9WWP13HIhPXnbz0d0MrjKVA1IwkWp0phw3va8Kn5FVO1xycrzEvi71BgCINK/MUDX7TSc2HatS7ZrwuHx8fGDhftM72dp/Jdu/jI/bM6K0zvLr2viOKfYQZOooClo5GXsxbf5TgsbfKtXteWccybR4ykORMvyIT4va9zVw3UDRSfAhmnmTHD6r4lYES3uYMkBt8ds9zOImO/h3AjyD8mwk/Vra0SPyTrzqvQUSoAN6wlVOI8CNZHvTXC+FH34S/zj9nFHgj0nIrEaml5oF7rqUELwAAIABJREFUfhNBYYZdG2ARTuI3EGzfbmS5vW1hApgPkTdUGVAjq7XlXrf1TkVaG3Nrv9KIeWZ7h9ijixujiZqBjYiiSoV4KiWJKFOk1q5sIemrCLRW8zyXig1AhVm1KUd4+m4MMEQF8QYj7wyNTtmP6XTD/FU+MTExMTEx8TExCfSJiYm/MU4UPorBw5Me+N4VhPn7OZUa3/fPmz/m/mLQ7if04F0Uf+mB79hd/xBu3fvl9vpeaUlnCgs7Md7X2Y3zCdEUYv5H7MNZS9EQ/i8ryUMJnxSxJ83f88jm0h/pz/fQMwbp2uqdi6HsOXNbsWMhFjNJnZv28XE0ZvLuXaUpb2nkND+WNtDPptgCoW4WonGhpdUlCG5V8/Te1PIJA8BSGOL1r1Waxyepe8h4qMsCsrCQxTxutlpdaSZOikkLYRlKPXEyp3d50DWSstumFhCFsHmgru4J+uflYorGwo2IMw90984fR1qX64rBy7wPRW3PHr2qEiGRx7ujQsDKFtqZjHxbuECvQNWKPY0ez4jyfifzJFq8XPZxE/6o5oU1Eha3pm/Gd37+LQHfKvDbnqw6NsH7Yb9wTnxeOJWbL1Hsbg12Zfh+/rbrYTlZ/7xeQQDuloLajHCiPJcr6kRKzGPtXO3g8Q1yIlpBwT6ToqwF26Xium1GYLhhUKRCD4Oc5m2d2ifybqt7B27ZGAddjjMXbFvFskReZytfxDzmI2SukICZUUrxvOmKbdtw3cwz/d7bceECZTRP3gh1fZ+ZI+c+v1aCFpfwlAhjIBE4RqgLAZsCVydrjis8HezYAODO1+ar566/8xa4YIdYC0Xa3pqgWP3ar0Co3sbmDe1e6i6nFy47gQxv9xpvnY7n5wzVbaH717bqSNte7Muxar/v3mE/j06p0H4mk2xInsHPnI96+GBgd+VfS7GuV8XmRW9thPd9SH7toQn2BPkNj/RHKzRcQK0s5tFERtrzjvfn9eqLR3S8Dwby9ZyJcUhv48RvcaLV+m0Msx/k+a3fq+ODM+wKSRNCd6f3s/AhZHk8kOBk5GkIFQqZEyzzAWHe0c+F7CQm/KhGBr+O+5NxaLGGBBo5TPheFb/F44nw//z0f0F+BTb61bywPXrJa7KoR6UAvzLhu/pbW3fMLBL4mS23+JuFQWRE9I8VqGQGV9/Wiv9IRZXNvL5jsrFFbGL4/xFGXYECwhIyV20PHZ7oli+d+n6ZGVwKwkBUFe5pTii+w4bngldRRDh3IpMLFGUwAxz51T18vKcVUZgR1mXbUKV6aqaIoNTX9vhf1QxxhS2dwOZjKkLPt5FG8X/P6+6vZ71Ne1J996OrDbT4vvu1pbvvExMTExMTExPviUmgT0xM/G1hSrET5Y4+8fvOo+jsc3wfdB8TnxgHVWo6/tj3W+XcOrb//vcaATeVx48olbuSnfr30AcrLLxfFOXlqZ9r8zaxf6Fn289m9Uc0L5J2jR50K0/qzheEKYeSF9GNNuvq4aTBf+IwMhK45ys/V5PqeGr4mJRfu3khKmAwnBdpSjVppI0RO0F0kAILk3ukaPNwV0SYY6MEKhQLsyuHCeyKX+OXFJYUXbGQKSCrafubt6cCKGDP0TqS2ABcz6qmL0xe9CsVC/3eMoIyFK4A1P3bayPlaDgeEoNTqF2YV6n3B9FIMLScrtAWsji8f6oKiAmLlsdzwFPoGU15rj6oPdLn0JNW4aeFu41LvtPd/Tt859pOU2o+Xu75wz7ihJv4YvCc4RMEdRvrdnS8BmjzoeULdiIucpEvSzESEb60kBv2LIy6mVTgtlA4iachl7UbZnltxAla2u0T61ZNRrHlwI2I7pfLhlIY5OR5tEJ3pNZmoETFPPDv1jtEDmqpkta3FEqbktTfTS9RBVU4KULpWWiGW2FzyAosTmRcc2FOshwWEF+z9aYn+Hi5Pcvy0ceKF9uvO//e5Bv1l2JvJDvOQ5mqnss+vfjeA5pT/wTpqOj9Zs6Z2socPmgyZKKRv4/vsYO8db61xQPfjy21/3yCA++5N6c7xyaKOwD37rGc27QVdVLGcS/4cWR5GLW1dvVn7R+f16unEOktSsVHWIOeZnQ0XnO4RfvBIM/J92Ft/+X7YkbP0U1IZHnsoz/kZZ6Bs/d+OHJA7zTLs+09rOoGPRHRwst34WbzxXOKw9vAU2+A7Jm/oNp41vhNwLYvK4RfuOBHMoJ4cVm31Ypv3GrxNybc/58LCi8Qriiq0GKh2b8j6wkuBSsB79YFl8sVVSpKKfi5FPy2LChc8BUBd2Je3pftAtkq7qXiF634virexBtuZjy6oGDlgpUXrFxQQKDqUViqrUdFLaWRiDiJ7tFLiLAsjIXN4ApcQGQpOkQFmwLkwtbyqzOowNrQjVst9DuDSrRlb++27qhFpzIvcsFluzp5HhGoYuy1HkbEq4oIZMoEogJm6ik3srBt4p6GwTvIs51cHy5IY2tYW25eOzExMTExMTHxfEwCfWJi4m+N/W8m2h179Ds97XdXKC2ynuDvRaV+oaB9zzz2Hen42fc9QXnya3+ihW3v/6J/3ivdQjEyeI2gh3yPc4dnBMHuCvemOOtPHUjp4eZdnd4TeuNzLreNlJvv4sr7fFoBTtr1s6Fl3o+Cm7VohNJ5vc5LDgWs5+jVCtbF8xGHkUMot41Zr54bMTx5yEmY8IaunoNT1EK6gwlVK75a75woyWHJLezjuiy4XK+AKtZSTMkHUyzWuoGZsXL3uOnK9vCwAaRWMDO+uVubJymDsFVTJlb3oi/EuNQteW/7qCE9jt34S0Elo4W3FXttFLine7rGcsNHe1sLC4IcslzKr4RwkfDB7H3TnsuttKY4VwUK0Lzpo/aqlIglr+cDBD2he6B/6+W8xUhSRMbpn2Feqm9vuRDfwM0QvnOhfC98bs32aOQMevDsAUuLRGFRNKobCwX5GN56ba9FPaIEKcylmhW1hXbYQEQopTgpSo08BwFagU3tGhHzdiw+hwQWxjZIhTaX2NYdEWmGRTERN3/wFrHMycO5V8W6FmxV3MvcvNPb7PZ8ttet15fECPQeVwQtb7vK7c3mvTcQea7bLENibVzJTZs8lPAFHkqYi8nc3Rp6B7Q1O0/l1fsmPAbv4kS69sCdANiYsaTnXEHgwiYvCVjdwzZIm4hEIGph+ldaOlkT8mpgEc0Ao4qtlQK1MeAE3GXbkKnaQeanfYw4v9TkWPBN4ZYvIyeUyzKDjb7Gxe8KQorE0J4Ve5fHt5S5xkux/RCxh+z3m4NcrTFmVXCfy2/HwyCRhu8B6exUOz/i1sx+7C3Sni8mtK+PgOJfciTHv9VxvXqKF7q2gfGy2OfLfto9wDgb+hyOtT0QqWniRmr9bTLjUs1gR0X6XD3pi9tnDHLi4T3U7ayAw1b+RvsO4QzS3yFEju/hD9KizcDxgc0ScazYDwCghN+Kh2p3j/O3hXx/ZlcuvtP6Qc0Y8f/wL7Aw8pZigwVg9pznIPzq/fwTCNdSICD8thT8XgrWUvATmRHkLxBcpeJSr9jqZuuGCP4DNE9zIkIBYyXGypY3fYWluQIArQqI+hpn14JiRjCYLP3HwgVLWbCUrs5VmJFrlysmUyKykxqj3fbqRBEVqbeyqo0lW3ct17moYKuCrdYmS0zeo627sQeXPIao/x4k93aPNfyjYv4en5iYmJiYmHhhTAJ9YmLiH4UHeLRHvz/n2s9Nuf3Pxsfq5f332esfBFem5TyllJS6pv/Upuj50lq7vdMDRgG3sFdr7hWMHxOWS5ObJ5+CLASxExggC9UI8tzit/SthOaBre6lQ8RGhjWi2Y7LZUMppYUMbrmJSS3no5P15pVOvTWUoBwhaL2+YnVjZifRrekZkS8UeFUWC0GvelACD+9Cpmxl7QpHb6XhXQsVhEepHXdlLqh1e4QBBbTV444L7uU8J/pjCvBxkOxl2u2x8tgoeksjkf7XjbyJfzLCuzDiRQx0nnb+xTzq0IxeIICSKf5JwuwDKG4ExG6YRVDUrQIxJ8nkAZMZ2ijUo0IQVMTykmNHKlbtHs+PyXM1mRn5uZmBak6TNv+hYAig3IyRxJ9bq2SH8EbktwOPoJG11MPOIxG67SK41zrcG32ou3ZSvN1lgmvw+tYcKQDNSzsThICvBX68AlhcphrBRT3KxUCydTnE7jkdMjkMj8LMIHIC12Q4FEVttdr9Q9slGX7Slftmfqnvt+T6Y93abaNiQXHq0fu3Rwk5Gjvk1jwO2+Ma+JG4Zyv7dN708XSLHP/Wx9U+9cjnjD3Rnt+dnAx233Lbn+BoxMfo0TXCQzh2Egwaycvn1W63b/MZTvuRel7/m3gwckGP0HRrHIwB/dO8UTMeCnlqfyykPYjws5O1bzhybNt9AifRi0VB+i3qkIwTTIYJVAj/CSNdsbMXAG8Lg8uKwoQfwSABKiqudcNFKrZtw7+uG34VgcpouEhEWLlgISPAC1nudoi21Aqq1QxBRWxd8H02ioBRwAujlNUMjdgMKRRh3KWAR0cJ0pyYUTzMu1T/GdUXgNawjQhXtTzniTyvYuthRZfvIVeUuowJKSqDlOljafLaExMTExMTE18qJoE+MTEx8REwSYaJieeB0JV1+7mjRCCR7qExhGXF0Y5Bd+q+nRL+hJF+vwo/8H1f/EENmT2N4r3QedlRkRkqqBzicu99fuNBOw39o0QsQhFmV24q0A2WF5jcKxPqJISFGC3ElkfRlY0KdS/O/JwcrJ7MQ5Mi77l55oiYx7mqkz0EXK5XfPvN16i1QtXIFgJ5CGLy0O+e650AuGd8eFQRBz1v5+9lg4jgblnA0qk5Vcv1LuFBDmpEUyimyUOHRvhURfcOG6Md5LEWXvLhGahAeFKqGQSQe5xuqviqLLhWRT3k9vVV5WSc9TGFFpq5tbXXJ7ze9orqt17eDwqwfo+N3jTSHAR8B0CpX/fiCtBbE2XiLwG9Z4MfZHQYi+yI0ucOGDp8QCNRLF1BKPAFLSw5uVELyEMyjI+NMO5rKUakQ7He3eGPP941j08m83wOYoGc8N62qxkLBfHsJTMnAndHkowvHrIiQmaTe5UyShHUat7ly1pAxM37PbchM0HqKFMYKSuw7ql9N0DQkdgIAyd7RWp/KQQggFd+z1bddZ4Yd1AwldYvrTx0on1TRVHgooJ1fP0mErNkaitZ8+qHefT7Oy9sXpLVSagW/rwquBAKW33CuMrqowh2J+eDJgBfravV0w2UqgiqnNHLaU9BaNFV2ipyWPd9BrFL3Owom8dwD4+ze5CjGVv1k/l0EG3L0tulohOom0gjv6LR43eIAvhGgT9Im2f6Hm27oPZsldR4p3iU4n/k/PMQkVF+oyNZ/tsXQqKfRUSiYYxwI5RbaOyQAX68lJ6Wxua3Dfi62/fdbv2+1xxCcAcNr/37YzimILj1xH5h5uP3xHifAccNel8X0m8E2yha1A4QqDB+YwaxRRlhZhSfdz+o50dPjyAPDXE+bHoCn3iWAviVCCsxymIq1NdOeIsItm1DrRu2bcN/nAA3YygFO1leQCi8YGH2/0sz2LLHWAok9YgZBA9XX8jIcw/ZToXAXJpcERFABEIWbl5Emsd3IQIvS4u6Mc51NIMs8zo3Q9KqgloFFdXIcxFUDx8/kuPohHrsMXcaEGrn8LjYmJiYmJiYmJj4TDEJ9ImJiYmJiYlPir1XdoSBbVAFPG+2uodc9kZvrspWGE61iPvjH6TI2WkrH/DSeQiNYwil4A0vnPPPN0t7Vh0eh5G5IozihELOK8tkhHN4/EWYSHFyHUjkWtSQ0puo+vXWh9X7twrM2xzA/f2lKRiNeLawluaFySB3QW3kFBMKip9XV0y7IULzZC8Aq4dfVjCxE2U9j3KkhxUVz53rnk7oeYHD+4YxetfEaJPMYhBaSOoYvt0rzb0vibAWQOvOs9P7IlrxG7Wy/3hWd98eP68JAL3Bt2rkefbsy3fFuYmJj4pkL2L8bhqFQQz7XA+E56YGQezK/kYKpogQgBHTITPGDNLsXndi4dp19/x4HsXSxM1gKFCK5aQtZcHmOW9L4WbQoqqoVUw2tRzlFmrXiPttCDtNTW6kkM779spfH/AOXRXYPL0NtzUMjdQimKESYMTdRow1+F9K7Zdas0Bau2/e7ndEiCgbSQS2xxGApblSa4QA8NdxoyM1U4kuu13uuswOIU0woqobbnXDJVubPFJK6uankISNZLp9xfmhF5aRJdYkeMoAH9eRI7uv/t1MoR+39/5anrJePKVVPg3OQrl/UUvRrYaNvRPg4zT7+JqQIWIU9n2Pyw/Rh8blc6vz/JZ8yZHSUzLtYBMbAyG7k38EgIKMLuxkNTXvdFXFW09REdYxKupZPjwiSTNwsXvYjSVBwI8um1+7fPuJGW+ZPF2Q4F9bxb/r1Qj0rUKkIpYDIrgHePEyi9sJmae8QlEVIAEUthdV35MCblzK7BassL0tl4FAD2POKgKu1aOWVFRVTxPkBqYQcFlQaLE1LwhxhacIMU/zTSqqWKh2qYIKaR7plsqhR7iQQdZ16X5YouKn2nMGxcTExMTExMTEZ4RJoE9MTExMTEx8MpyTAXqTRG9e6KFsE8FBW0P7cJRxvV/3VNeZx+q+J9KfqYTM+buBoyEB0L07bpe8e/YNIiU8DuN7XMZn7b8vnUK5B2yb5dz8Zr0DM5nnWyJ6ReGhNYGv7+5wdc/xULd2oqnXo4a3DAhgaXpjqYR1Ke7lGVebt9GflwsA4NtXrwCwhT8GcLluUKh56cAId00eNXfLAqiFilftuWGXUqBCEGUEnUbwkKnNrRYIDqa6d5H6WLpzj6QIIbyU7lFq3judqCrUM67XIHycTL96qOiFjWyrfn842IYq+Q+6wdPQ8Kd5UXXPw0SYxQslBEkRHn/fqhFlr92Y4PbUeWxO6ROuedolT8XHJPtfvNhH5uHNs8lD8X2wHxaP4VY9mhHQB2rKg/Q0mdCLWcoyjNWQHjF/qf3DHkkieQ47WbpVdWMZguq9pzBXlxMFIgryyBDkxi7Vyy1OxngAjuahWzGS1UFyqpPBqoJSgvQFoNLXJwVMwrOTGdSMf6CKWiu2YMlSe8a9ee0wct5C72ZEfWJ4rbD3ehWNmLuL0HLapgKMtA0C2w2FGBbqvqp5PkdIdcvX2wIBoLjMCrmvNd7fx633jbpFkVHu9s6bCpgId8viucqBu6WgWqxjiNYWcv7Veodr3VqO9JzvPcZsGC5J8tx9DMf1cfy+JxGJ45rn7Ql6MGu7fnFv0bUUX3/DICs89+HGBWPNIjuxAvjKT/5JLtd9/Q+jkUcq9HGQm+YZuEWef3HGXNmDOn33L4k8t+8rG+FaPcT37/Vy2oRPMAUBkMaLxp7ur2nAHJBkT3+3OfSQYRB3krvRtE5yF2KUwlgKg8tinueFWzu1fadNflsTSAG1KEfssp2Indwm/AQL//4jjOh+y8BPMBL9NRGwBVG94X+2DVu10O1tPwczLqXCWEpB4YICwkIR8UOgwqikzbZXgSaf4v2ocCsnh5mnYoZX7JE6zJY05SYHoDVFMVKBIEK6+36aLLKJqBH2mwiqbNiqGIEutRHn4Xlu+dG9vrE+a3SK9S7lBSf1+edrmjMxMTExMTEx8TgmgT4xMTExMTHxWWAg03ckevcUdIVMVtAEKavnhPzea++oO34fxc6ZkvzDFERnRPptffPTnjk49ryA/iqK2ESwUsHC3HNxqjYFoirw7nI1RSYZ7a1QUClNU6gU5BaaF6h6rklo5D/u5D/Bc6cnurBW84qJ0PLMBFG0EOm9HRilWOh4UXFHo05bFCYIFahYYuLeusnjntQVzjGeukpwcaLecrI7vefhhUspECeAMgiWs9OUk1GatnPxnCEc9nP13bcGkOJBQ5IgLCL/efZG/1K80L+EOn44nkfUfQmI/OORDxgIgrx7jBNsrg33+fpgZC8G1iZIx1oF2vLievlOQFDMYfR0DUtZPP85vB4ui4rXStRCgSfDriD3CyzMuOUwD+JeQWTlr2vBtlmO8wgJH09hl6uFyHO1t8ax92MCpMtIkWPu6t5ufXSUvA4GuY0QBUYwX6HuDZvyA1MnrCwCgN3MGvmYjezOBl9tnY7rkaLHOMQ9b/MS5c7xKAAqFJft2mRgFUWVSB8CM6hj87BcyoIql95PqczcHu/J4T4DH156hKWv0B5OHeiex7sX6R8VX7sNWibTYwScGix+DDy07rwAImz7F43UF0a4UiNPATP+Kb53qrqhth5+IbzPfiJufcAA41lj7IHJ2GUPDTIonkEcIdE9xzcX+9xScYShkoKZ3ahJQdrlfkhdM5QEvidGAeNN8XQ9TlD/BMIbtihB324b/l03SLVIIUGcV6mWboIJRAVgwlIs7LrlI3fZKWIpLzyF0UEqEZnHOZuX+VLM47xw8b12pD7i1g6QiGbClu7KLMB8T+qWNlTBsXZCe6h2EWxanTyvTqSbgUDb17uRU0t5NPRxD3cPOun/tpn++JJ3YmJiYmJiYuJjYRLoExMTExMTE58UI7mdyO4zT3SgKcUAV+S0azoB2cmW0bHl8F3eR4t4gzh/rnL6EKJ7p09MBO+R9VeMyqiHFJr9PCVFV74r2nPvcXer1KoVsknTwRIsxOhdWXpOW1iY4si7SERYmNwTDhAyz6D2jughaQNSZVSkwryGvrq7ay9XWl0JFdXCoPq5GEsWTj5CzbN5kDvxTgAuTlIVDh9IBbTn/lV/J/I2VDJSfoGFcL54yGXL4a64XutovJD7gnpPXOsGUcVdWaAgXMWI9nUhMBhUjbTPNEghcsIMzRvo1hAOAi36tRN9D3Ruwv6y3w6uzv8shehHo5/0XIbceh7t+lN2/UC7605KGMvfXRbcdHgD38LB8/zBp+Xvt65PJJF2+k88J3fxsLrRXK+WtYdbh81z3vnj53zYgJGwVAXMRr4o2X2kJht86tvzSgG70Y9CsV2vXXa6tyizXSfuLZ6jnaiYzNk8CgURWjQNUnIDI24e3LVaPl3zJpdeZvRDsMtpuIRsarKYCK9iTdR+C1GPRNEoGwUowtQDuCDIPDd88osigsarxTwyr3XD1+sdtiogNQ90VUXx8L7k94uEBLFGpaVEJyAMxMSFVNTfyGGT4RGCOKfWMKK8oiXNEOD+evX6ejv6ugIfE4UtpP6r9Q7312trL+w80Z9LsO/H8dPvixv6umyynRs5Big2j0jSPM/TbeE9a+PeqK2vxI0ifLEiEP6lwNtYPxIBaeUcGPjnvcCte3R3wVP3Ro95xid8DjnPH6vtfr9F4z+2H/Frwwglj6p7N7zbx0u4/VzdfYv1/iinv1Pg94eXhwdf8DytRZ+r/dhZsdTCtp8NDUtp4eOUGZbhp4dlL0GgEzdyurAd57g/ZDCRGdmytQMp0l6S8KMSvvnpv/C/X/8Hr6FgKH4ShZLiV8TeExZuhGDh2qv0UOkitj6pyU12Qr+UxcLKc6T+SalHVFERHu8x/ajN2fw3xksjrV12Vd/EUe2piGp1Mj/kRbSht53Ac7OLrZm1Vlyrked1M6/z5oGuYmHqoc1QK8rMpHlfscfIXx9vszQxMTExMTEx8ddjEugTExMTExMTny1Mod7Jnqygawq88DbeefSYSid5R8AJh8wekzwezvSR+n1MNKo+GRV8KtzSsYcCbRPF1+tq4Xs9JCSD3QMoCJzu0Z378yGE0hFO1JACGzzsu2pTlGZFbISFl+E8g7gr9MNjPnt9SXjvuKawFPNcajk6vcyI1Btk09pINAtRvFUZhmQj5DxnvHgoZ2YGuwd/05UCLQQ0sxkntHoNLf609hvacpwmj+ItZaXp54/vvCn+Gd7nHxM6/Hnsyo/R3BHOPSPPZyAMQ3hQ8huJ3r0Wg3DOFGSQ3BFJIp6nUkcvx3ia/0PrOpRBRO556KHHyQxqmjf8EFLdyuISJCk1D0JVIy0gbuxzEmE8vOSD+G6kur/B140op0aixtNbOHokwkZbQSZjiXDnryomnJtxUqX+zDDr+uNywatlhRl69fcM2div9/XLjR8oPS9CxmdCmdxLs1MyXo4CStVJx8buWxD8MDajCDFvfb/VaqSWE2xVXE5vvYE/3YqKsIBo5BRBUXyljXo14mq4rbdLNrDI3vykwO+cBkgqNa+Zms5PfGRQJs6PO6pCloLiUmuTZy+JHD3mLT0h9ccTiPQHb98vDI99H46ThW5HkNg255kIZVnM69xluBlC+n8acr0boCqnmZFIdhDhLQHfLwv+3//+v/Hmf/9/eEMVm1995TpUkoBEnFdItYgYsQhaDnbzho8oJ4Dt51oaHzXjHtv3med71Itc7oIAJW1EOcPCpyOiFamnEHJZKR6ZIwyvwlO8eb77miNVsdUrRBQi1TzOa8UmFeLGW5vnT48c6QpbjlrUi/gcLerHiZLdzMTExMTExMTE3wz0X//rv+dPpomJiYkTxI/194IrsuZvyX8QmnZh9vpzsfdAP/3bLxiubSEKd2jHdtfvrwlvv+fVtV8foW/fK6+66kFF+tjoaWrzVu/33cbRgw98rB49b2TWpHWRGfcvXJqCM8JPZgR5LU6Q3yLpM4oyzOPdvEVDVo91Homr/bstpSBy71YxT7+WIkAV7ESYKSNNyWneRRgUk1vdABDu1tUUkIoW0n5hNiVr8vq+r1cA4ZFkoeaJqOcI9jrE8YUKrrXiKjXplKkbFeBsXO8/5Plj/4SH4mON3UbY2M04Kfnhcrx/n4v9CP/UZP5Hf/QTPdD75UEYjogxcfA03c+FTMTZh+GyHJFikMRtvocxzMM1bXKhdSahi47jXKXd97iR3WsvvPw2qY0AlPDDT+8entSAk9m5mklm9JDunawZDQM6qd7eNxmv7GWxOAERHtGNyEntQeS5z+GRN3yOnE2TKF5bhI7xuhbmm8z7POrU65ueC/NEV2uU4R1FLW/5IN/TOsXFbO/Fy9yfHa6YAAAgAElEQVSqYDcyjnXH2Owhu1SBqjKQvkA3Eog6AX0crmFAALQQxjGWapUm04kt3+9WKwiWR1208dUtAomF5zfZKyJ9PXdjiOeKrKdefuARRUFUzGiBuMn/TcQiLKimPqQmF18xQUXxu0TEE8XXCvxBTnrl/dPuocPS/ZHes28zbsuHs2Uo0vJ8KiXVk/sx74GQmvhMjjv5uyfOCWgRKDZJeaufUJ+zPcA+6sh3CvzGdDjHj0rth3HLA70bIMGIVdBuXVEnvhl9JOfztp6xy1hmapGDoq3u7laLKgFqeb2ZuIViRyLUx5f03wyi+F6BN0FY33iXsV5BhgvgBLRIpBuxZxZiI9H9b/eCB3xziAJrk8Lc6k1uXITUGpFiI4yszIMcblzk/5kwtTzmksaCk/HEBcUWTBARLtcN1616dBNBrdJCtouI72F7XvS8/4ufuL667o6HoVn6Dbxrvmb09T648TtvYmJiYmJiYuKvwvRAn5iYmJiYmPik2Id8fBBJ2RWEx5lapSuhUrk7BQw50fl8Ys+e2nVq8YyPr+A5vNcnUyodvUPHs07UiJHRQtZeDBrCTRdiy2FO5CSQk0iPPBswEoQTCyA+jnKX9BHSiUKF5XDvBLZCWBDuMwojU2o2UiCGQgA14t1CFgf5oI0AB3muY3GSSq0ORJbPlsmUqgrPGdxCHKN7A6KH8lUoSmFcpb4QexttoX/FcP0o+JAc7HHvl5LH/TnYE5UvVeZLI5PQRy/zSL2xN53opIyFPKd2LdTDhqt7Xru2PoxRgoQI45dmA6ApDK3Pw35t93jMLREe8HZnp36NmO5mDMZXlVZ19cgUUZoRHlsiwOIZRgCp9rDcmVS/SSJ4PQtb2hLWZPyw55BSyw68FozcYe3ljaR/yG57hvNbQ3SNSMExjMXWzumv980rv+rSaBngDoTrULMI3x7VyiPGPtUq/v7s+wlu1+YWU+0kJRNBmdo1DIZ6ypC/UjTGmIPXoRlwpDlw6L8USuRC+RjwZ3T7mYin3qft3Ed82e7pfkIyj9VqhGBbsSnGyser31+GRp4DQSMaGUw+b16AIDwZuN/dKPI7tbgdv72nkfhjde2ih4YD/XF9rzXUIDZvLoOI0QjmaC8znlqwlhIUeSeMm2DTVh6n8PUK2zdu1w3/49f8qMDrsZoI46ExBH8ew55eimzOwtclYmr7PRXx8PFORIsZC5WygEsBJUMZtLGuzbA3DDFzo6pKk3VBsLsAaV9y+HuLzEIgFYgC99sVl8vWDHA3J97Fw7qL3yFQT60R5af3z8dTo/WaHnciurtiYmJiYmJiYuJLwyTQJyYmJiYmJj45skLu1LMlzgFZC2fnTpSAdOLJvr9OiUBObDyztkePyp2C7UmlfKDCNNoiExWPodcwiJBQNJ4pvM7uiwNNa7+rVCgr7fim5jlNwS97SWspTUkZ+XPBlsu5h6E8q4l51pV0tnnbopPWgVI6qdUpHGoelBamUrCWBaqKazWPv8XDsVf3Tox8kBf3FP3zchlKvW47z7HUrMF1MHHL4Rw+w3dLyuCevFXDW0fVyHymM7Xk8xGEoT0rqzyDofvAB/wF+BDiO4evfQh/OcH+RBm09yhvf2/IRMU4vw9xGhLRAADMj9WDzv5gT8X2esTRLsFbCg6/x4glzrVt5EUP3RsitivrWzQLQs8VTjrIgyjrSBb6TEjGOqomfwjkoXVzGPheViQVV60Y59C+FajJsWH9ivcc2Hw0kkVVvR5A4YKg7EE9LHuLhKLh2GjXL5sZLFVQi1QB7REKIsQu+wsH5xZxQYQs124hv1G0yTAFoJt5/Ff0Pgn5pp5rXFRA/h4RQfwPjMT0V75ukY+3r1PsXyLCFcDCUWtyYhmNdLpWMz5g5HVdwbxiYcJl2yBVWxnmnW5e62splltcFUtZQFBsdYMSjGzq3W1GTilqyq31stX99Og5whs5aDqignVdrf9SahHydfoVOlne6rMsKJ6HOVKWtPF1QqjGOLNXeF76jzPs3/eY+3o0YXt4X9HnGnu/9bH1cRem9y29cYuHAr3vnCDl4foeYvwqG2oyKbxVj2ZY4GPx27P1SW3dIuzWOep1/N77/y26DHgROGHb5KV6z+/WnbYexDpz6/HmRu4OzXGvlcdEKEzm4a19D06apqVS6hvF90p4w7Y51GqRJ2JM/RJ1IrL7wvgm3imT9FG8Kog8cYh6Wik7AYEAwuhrsP1ryxhZWHoyr/lMftv60403I3pRGHcpUfMcbwQ/k0fiANoo8/mywQusW9snX68brtX2vFBFVRtTEb1F4WsAgMPATkYQmv/GOw4yUd9/Uk1MTExMTExMfIaYBPrExMTExMTEZ4PnKkqJ6KDnGZQ5ocjclRvhcs+Uuk94an8S5WOfRmOUFeJ24PF6OAX0/s98RtSAPYFE6KHbQ4nLxAC7h3oiB8NTcY8gjM5etXtFKmqNcMT5fCcX1RWmjayg7v1tim8j9sQ1hpGLd/dEU3ImRX9TLIZXuwKAQFiNDIJ7U3nFIoSruLdphCJWBQoIGl5qLzrGPt2Y/dzxd/NO/xwR+WuDqDDSIxHSLmNi/mo6nonoIAeQ/lL7R9FspKiPeHLtvw5CJJUqlvcbKn2NITTSJgwNbsdA8ZL2dgVZYDn5HUYFA7npN3RDokQUpXL2T+b+4tZ+bnmTqxHe7VBtOc4Bco9G6qGDQQDFO3iwZWJUxNpJ3fvc6xL13fyZK4B79HWWALzSHiK+1bYx/OpeneMEjIgAr9YVKoprNZkrQYrFekKMTVJEEDWvTTgRFrwdM5vMdmaS2aKGBEkWBgNBdr40gcvUx08QaxbOGYdOjdGeyfO+vmhrG3UjBfGSX1S2P1RcW15zGOeRXI55ukccY09n0PnPTkrKC7f9X4WQXXkkMzEKE0TQ3u8pb7dfjt4S8B3SOvWwZcLhXmgfQ8O1z23qTD6nA41wvkGg30bKZR6Ec3xu5dmejZlBzf7VXqjZN6X3afLSchqYp7WHKicmz5kOuGA3mY/weieEd3uQ9+KGQbXJC9+z+X6NCBCqoFKSzO7EvIVrt3I17U3VPc7FDUgtz7pCxcw4m0GlpwbhQiha+nqW2lvVQrNLFfdmt7+bWL37She5zuNbdMNJR6W6HsjzAee71DQyJiYmJiYmJia+OEwCfWJiYmJiYuKT4ZZi+vl5ydP3dH/LF9pZ1X6Pe2091fsz1c5URBoEfmjJnlfOQwrl91EzPYVI3+kW+3OCyDncQf10qhjduHp/LIiCyLkdwY+t7bkRY1UrSuGmo1uYvUol1HwAYLnK/d3CCCA874yU5qbItMsqhHou5Oa5GbpAvy5oKhsWAi4LllJw2cxTR9zblLwu2aMWgJNKKRe1BmkQof4JtX3W9sz7unk9T9pr365Nofx0tHKSknZAGysYrhuDzZ7hyyQ1Pjs8W/aco3uie7E3unmPxz3O/f7nVujWDQNx6CFwmVHYKNg2d9P0UqiFmXVlvznkjTI34ilkb+T8r4kfaiRLnIvxHaHZGR4Fw0liM+hxSlLNI/yybbhbg2DuBE9+7SBUAEVtCce757kGzbmbf2fNRje/AFrtxm/cY1d8mSsuV9nv0WAwve24yZIgntHI44Ak5j3WO3GhGdEySpC30uUnACxscltgJHqUy/6ZVKxe4e3ojPUFQUTZvcyR8sKqen+9tnorzDszjKVAwLvLu05IBwnLnVi6urwtXJoXrKJ2goytdBHgX1+9wv31ChCj1up547s3euq2hiCCZXe8z79GCVo7FUtHYPcRahWLduJzoSYDit5M3dv1cr16l2ozxiiFsYm0/QlwlPs9T/VOzj9R3NP+XJCMPodKKW2KXrZrTydwuK3P1xiNCs9H72t0kJafA+jk0+Ga8A5O71yIwWz9e62W0z7jZrM3j/NOPyoszcJ+jAFGjscW56zib86q/YFNm8cSQUGayNzYI3fn6Pav+kfNR0P2+3xs8rXJR/P8Jnhodp+vpEA4dANJdrkseUPkDWYpdpZlcQLd9qBhzJWJ8rxGtaZSbca48TtDRNt8jVoSGCwWkYOZQMwoSHnOnSiPV40drqjN/6qK6t7s8S4mD4GFVpdpnYy3sqQZYtXwYq+R77yi72B7tBeFOomvffPgNRpXUrS2yd3Uh462vyGj8nWtXV5muzMxMTExMTEx8ZdjEugTExMTExMTXzYoq2j6sUaiN3JpRz+2ELF/L3Sy+znh3T+ugjpIjaRmA6CNuAJMudyIKFdcBpm2eGjgwgx3KBxIgVDQc+S0DeItlKgRnFnVPYOCfjeSrBHuTgRFjtnCBFGA9P28EEPJGG/evJrS+fP7zs+8rAc6sFdxxtd2dHd6YuJD0IhU6uQEgbrHMKX/EWRqELgP50POTpDcKXV/Xjw416QTxIye35vBbZ4RE0jat0ZeblsQ4CarOELpotf7utVGPAPj3G0emUOr2FWnLIMep6LurlWXl5nY0Gxs0KuS6uTETD7ciPLh8a3exqN0eUsAarqW/Lik52UiNwhkdwhtsvwKC8UfZFsQw2ZA4eMlCDl4TvvWBEHiOX3F1CJ2mGd5rgxQpYKZ3dvTCXSvELsb+B/391iXYh6nbMTwVhP5t/sExDpUrDDVod1yC3EzHjFh28lyQoTwz9FXaDdENMloQkQyMNQq7cQxWkoUESP6w4R78xKmHqbcqwjADN5ur3Ed4sYqMc9jDYq3pF0DfCZ8uoF6O4bXeRiBsH9f2EjVDfWZ+wgr97eQh370B+1/X39YF34Q9oYYZ+cptU/eVPRm6GQtgrjuJQyGFCE7cjQOgqeccNln8t/C1b+OkR6/AdQMLtd18QvH3wCNt0/H+l4oyojjfW0SUYjGCkJgVhCZmpW5oCwFJdJJXDdUVbCKrzVWWnVSvaqlDmpO8zEXFOCy4O7urj/f97iqCq1Ot6u697q0kO/V85uDFxDvYk9Fo1E2DDjpz7QuU2oH76VmBJDJ8/jew+vPzeTExMTExMTEl4lJoE9MTEzcQMtp9kGYPxb/WZj9/VzcCo968/it6/YKZozE5fnDASolkQfa9OzHu/TkYKZEzs4fMbwT0amC+ymBuvd1vDXy9gTGXvM8fut+x0HD7BXtcbvlEH9cRrZM5q4gNwIZWJcFzedMESyK53MkFC4oTNi2DSCgMKOKEVrx7AhnGR6IzBbOcgyPm5WcYt5sUj0igRhx5hpTBoE8Z3pVgVbCUhikhEJGql23ipYZvTUeDWMI8ToAIix19nQF5XYbiRXJrEj0hcZ156NiP1eIYF6vSLlk4xynerRHHMPxtxonUrJ/SN5JnxOR8SXhPV2xjhEE4sR44LHij+dp+LMv/oEKnd4f94WBTJAoxQmVdYmfoEY+gAjLUnB/uXYFvHbyQ5wpjamh/hJ5WA7O52n+EBnB2NN9DBRzjz4RxwlOeJGFA9dO+F+uVyMymLGuK3oqEMa7+2vzyA7nSVWXWe4RXAofw7KTrz25MzW/hnvuaScoqnueF+6EU1sGnQt5p4pFgSsUX3m0j8i729YdJz4jt/plM8Iz5Nmd16H1lnvERrjwWIcYFoXj3l8hTAnuvJ+jLapUMAg1rlMjjTf3Yt/zNjHeq5jxVPcstTILmae7RTDw8MbeFkFKw0T9QKSFN3B0RCkWEnq7XNt5kBH6fWwA61L8PWzdKR4Kfl3KQPuxdGKxr6bwvPTaDLXEc8y3a70+Vbp/cR7OZ/PaDAHChGFcp/s6NN6zl/aNvD4jqm8sPTl9zv4SqT3sNFEQ40eidR8piIlwlb1vtTZvZv92MKB7aewjzJxeQwRiasRoCntjEQ4AXD2P9fGdzqE+Xvu7nuP1YPHyPlB8Lw+kKrm1gDT5fvTOJlCzVBo88Gl3c3pED8neSWqCuv2JywNiwCM1lGXBwgVlXbAspUdeke7HHmvEbwwUsMlFsT0dE3CNPOJO+4ZBjpHRfS9E8Dzru71zldpzqIeBl69zTHZPYQZzGe6XZpwZ+1EL9W7HbB0ywtsjraBPYvI1QgBsLswsGou2emu7Dy1EvYi0Y+r9MnYDtecPJ+j4G2QvR/JvkME4zPejfT1O42RuGCcmJiYmJia+UEwCfWJiYuIBvK+Cpilp309HPvElgrLSbeK5uEWiP/XerOjtBEsnFbqiZ3iCKbooUZyaywwFmfsdhma+3z6U2XVEN+TGgfyy0I77eygqjlEx9SHo/NpDXun7773lzmrxHPGoagQLQ8DElvPbWKEWotXygobuVrE5ScREjVAozJ5v14gtgnvsuaIQYAiMWLLnEpQUqh5G1J+pXl71lyMiiJP7Qf4ILPyyeZh6exQGuOAqAk0qxCBncjjSIABVqfejmOIzlJmmP+73PNiGD5zbzxXzztRRwZ1IiDzOvRK7h93Q4JMOp5+F9yCNo2afSwjfvxyP8zifPbJHmqh7e2snLuIdt626l3E2OUkSUHfSsAsLJzHs+pG3sYWhkz001Cg+caLmjQwpweikUvojs9HKVisWAHfrim27dlIHdl0V8RDD1Dyq93uFwUNTx2lKu8/7oRB5zInMi57UpukrNfm2giBBVsX/Q7sCW6x3jrtWo7663VoJ1M8uAKCEC/ergjYs7okLYQ9FHGSxkUECJ8v83SN+wPic8YitKU4Nib+/dC/QgQ/yslvobBnTF6gCl3oFwchrcsa/E/qj3BP3Lo6yjajvbTb2nx1lCgKdICw+4py4aykKDs07bDv2ItTmVDy7D5wQ9YfivFni/ZrFRaylh4u1X5K3PtSNIvY8qSKiZXdDK4Ktw3tEBJgYkVFe4qKPd3xiWRjzKLzLgSBQ7Ryjz/XnF/7w6e+0k97fKfD25DzhnBj/TrsnO2Dt/Z2OYd1v/YYhHo8HWdz2LvF3f12TucdyCdZOhQhgBhMgVXx/pIAolARaLMXBsixY1hXrsuLVuoDdeMWI9oqYrBTlxbiKeawEiEBlw7t376BknuhUGIXYSeja3mkpRoADnpqBbN+4bRsu95f2Hi1EeylYSkEpC7jYHreliRDpnuJ5dfMUFEbo27u0qEnedtkIR1Tw7v4eMbMl3i//j+NzQMf9ZhsHu0mnrXfO52v/fPsXQzdCSF2/W2MmJiYmJiYmJr4kTAJ9YmJiYmLiJfGenoX/WCQPpPdBeM4NRe4+PKiySd4moRJS7Z4aES7cdNOZzmgFAPC8j+jv8pCi6EPCp97k5lNtHi0jrs1tPijP0Oqfc5cOV8Qfetpb5Fy/AsVlu5onEVvO2HVZwQs8R2jFZdtABHz96mtctw2v7u7wx7t3gApECYWKKejJ8tkKc1IiCq7VFbRcTKlNgMK8B0WNxFfsFI5a3ZOSnIAnI2gUTvoTlmKehizc8kw2ReWuLTpfp5av09uTPHRw9uIKpeO+tRvjgSBLujKVMrPS7rLv5cYYzM+JcKaRq7ldk74e+Nv31H/enN874wHdj6+4DPhnKl8fe+Xd+acmpWiknn1pIaD3xGVcV4i7F3EQHAAaRTaQMH1Ycpr3gELIZfamzUsxPNQzSmEUNa89JU3EshMHboSyf/9cTCMvFS0suGj1+pHPewR/iDB/YSJstfa5S0Dk5I7c3uEBa57oi3kz14oIwY0wECBgIfZMtkZw5hDxe/axke9D+2l6TyfoSs9jWwEUBUi05RgPYwMiwkbAwgwixqVuqX964xW1e4vf3/L8kpE0W1r9giTOJYTIYCi+1k76oFb8SQCkttfcAHwtBYUIQgVEwJ2//+h33bHVCugYIj8b1XBPL9y8WZtRhVpY5Gi9dl66KYOVDwvnHr1Dffyb57ti4dKeKSqNtKvV349Czge5bLmv2Qm87MFv8txetYVvf2Q1Hfsg/gb1ndYKEbxaV1y3zfolJ4iO+2h/4Cjvx31NuthDJ0SxCjdOaEy/t10jmM89sCP3dHs/jVnr46u7rn4k4nxcf07PU6y3u7qmEooLGFFBBbDVbbjmMTTP89YRIZjGEggWmryJBL/8J/keBMZGvz70JgPe0EPvva+gl5GMRswAlM6v2x+/UZ5WgbDJG01GFjE+ubCtBaU07/OFXcqpN4KPmZBIVRVce4oIZ6h7SgffNzJbPZfwFodClfsQLn01FRWoh2lnsugjQN9DEdkeMY4Fgd086RHkcf8NEUag6ntICYI59qSprcKQR7FP7+Ae8H0XimjAvrYluXDWXena1DVPGrxdOvQjt3p+XDEmJiYmJiYmJr4sTAJ9YmJiYmJi4p+LQYc8etmREpDzrAaBE54uyKSn4kwd+SDpl923noWX8eQYiLJGdO3L7Wrio7KsX/HUt4hrI7xu5KsNfSsRsBbG5t+rVJTC2LaKb776CpfLPbaqTXHZ+sr/3XvIiFQjEIKsI8LiYX/DI4iwfwf3AoJ5x4HIQ8VbuPfipAjAXek5tJKX0t6JGqnFQaign7Mn7Vvw2NKU3nBPtHXegvIXP/c5Ky2HGTf1q0/Frcn43GJ8PG+JuswEaRDgketaSLEo4yr1UNZzIE4UMDGIzACphXoG0Pg2J+LMoKmTaBpjJR2LWkdQc0rz7wxm9NJuamSekSTUCUEyIjQbRlX3GLxjwuW6Iec+BrSFdQ6P6ET9Ov+4Z6+O8nVvvDQS133+91D3YztcCFiJsFDKz56IZ4V7mmv32g/ipqRyvBta/QS3h1/OPH/rmnbc1z9FIp6H1gh+THFHhIt7hhNoIM/jmra2NIIXibhC+r6T9ehe0HtkozkbG3FzL3+4z58lXl6Q9YxYMyI/dmob8igrid3ar0m5HXV/rK1B6Soi3F+vrd85d2S++ewBSGMtCLjh3BiWPto/SM9hLe0Tdnxeemwv52gMCXya9Ss8p83JuhucBbkZxnJMlm5Gh/DceAYzHQ8cPz5kSKEYPcy/V0DxBuvP/4X6y+hRnvGGLGf62fns2X6rXqffz/Ckd1drM1KIEBgC2d1nHv5s6XxKcfK8YCkLaD8LNMq0MEYevMgiO4jYvsmNoCLCBLOHgy8LSilNVoRMzXtiVduLqqiR+hE+/uR69XcTcm/2dA0IyZgr5FYnz/N+chhH2ueZaMyWtA+MuUP92m6QoenzuKbk57zvNHuhrcjExMTExMTExGcN+q//9d9zzzMxMTHxwjCFGd1U3E78HUGg7v818Qx8iII0vEre78HxJynYswIrabmzIl49zypgevruN5aV9sfykJRdgJMEexmxU/bvDrXnn6jRB7zvKDwjA/KZwdMtEzZ+4z41514/34nj7rFDsFzjABrxdN0q1ImoV+va8kcaIcD4890FCsVdWVqrSygX9eER0QjtpBjfoq9pVDM2MigR8O6rBFLL5bxVMQ9GAEo71Td1YqwRRWfrwl5bOpyg8SiNilOgjzNxZW30XTwqCKd9kOHexaHkld14c0Vt8yRMyt306ab9xQeijfLm1YWRbEif87Mfq8/Npflj/yp65p7gfecx33wODedXDzO7Lguu24aqRv1ZymzP3Q3gblkHBX8Q6K196ewp6ftjBF776jLBFf7dsMbrzdnHXlv9bMhLy3VezEXSvAxpJFyBNM7DrR7mZRxkfSMpNEjQLqs6SdHLJDay57oZmR65yTcxj/ewWL/6fF6JLIu47odcl+udEk2UpAAruhwVCtERcsaJPTGf90vM950HcDzllX9ocllj/zpeRwAEN7ttuKYQtcgkeZV6N5CEhDvtcrW6F+darKWu2xWLAuJGFcWJWQlCavfsWHNbSG0/Xvy7eL7gOBfjJu6O3Oqc1/NbYhqxRuyJ5eN6wT52xCOZtAghbHHuI8+xVYd3ERvSc3cNHzEgpHm029P797EI8Xv3xPwRNxj1HZ4qJvd7u3FpsclVPHpM38ulNWpPwN94/nN/a+nhA7x9Omm+exEnzLmt4QTPR40H9rC7crrB3iMvFIef1h27Rx7bonuOk4d+V+dVFd8r8HaIRkCH+46fYUZFg6c5pefsnr/bUwAAREGeKYM09kb99zMzo1DBuixY1zvcLQuWsqAUtggZIQcEIJiHOMRHUOy7VT2nuLbxJPCoHUvBut6hLAVlMZMhjRzkeYcj0gh0qYJ1XbEsi3ul2/UWjcLGc4+q0o24sqETsUc/QezZrHwR6fPXZcWwE4x1x6Ov5J1Y+96miw7ypu8dC0Dcjub9FU4+73vtVlSjVr+HkH8LTUxMTExMTEx8YZge6BMTExMTEy+EhxWTE2f4HBQqWRFOFDmzNU660tP+UyiIuClUO+HqalFVj745aryf9J5PIs8PqmO8JOs36JMf8EpvzUP04OMVN/LZqoWCJldab9VzjZPnwnTCQ0WxbeaFvpaCbasQCTLflO8WzrlTXEpquS7zu6Q6dI/NdEXv7sMcDsUhhZcRqXukAiqKtTCqjCF8kRTW+3y8nRPQ4RmPgYDRAgEwraXXK3J0Wsl+vI3ZIzETRgQRNjdOJk5x1wq38amm8a3nPlafNL3/0RCYt3ENQlHhRiA2r5pXXRtL0sK9f0yoswGN5IY2b17AiFKBy2sngrR5+1moeAY5GSKNeO9ESicZgE7aRHjcJu+pEx1eo7TQU7uXQJBqbbhAIUrN01DR14d2RC3Mt/tG5jdv9US6g6IttJMl5rFPnXgiBqoR9lUV16jvQ+2MMez/wfAhfWbkEOvHcqJZzjzUCcDXCgvn7riQk9UaBBqgHDKWcIU6Ad0J+YgIYtEDemHRXkF+xng2Iy31O8Pb8/wdsuw/W2UzwkBWx2oM4zOMxKLmrS/U60WASm0GT5TkNFE3YYi5YMf72hfZ3mN8mdR/eL+hu7978EkDHEfnyQHqf/JYryf7k3xk4dIIQas3QBRv1Cd8nqsviSMp3A00hrHv4694ru6aQnM/h7w/v/LGHu5sMr5EG3g5uaubB/qNdzl9Rzp8eFYVbG/UR2/UqXmeE2NhtjZvKQgEIoB6rvR4MoVs1NgDBfGtu321PXfhCAvv/xePucHsXuu1k967DVEpxdJ2iJjMpwpUtMk9CJgAACAASURBVPDzt9DCsKtaOnZoN6BRaWlJxOt92DPTbl3Ie0qczFNC2we2z/tr8IzfYM34Y8RTe//T/9KbmJiYmJiYmHh/TAJ9YmJiYmLiJRAK/09dj4mn40zzo2iK2wjZ20L3Nu2Rk6hNCalgV/qq9hy4prgaQwwfnzeeHL3h82VHNfao1HzayGtK0ydc3i4Jj+2z+5x8Dd0hked1TVULQqUr1wEKQkFNiSiunNs28dzoBYW7R+G1VqhWXGvFykujyy/b1UJhQi2XpZNKKGXwyra69cCf2SM1642zInLPJSgAcu8kJgWYUV2huxTGygVXCe8gJ+HYCJ8I8bzV2kk87BSiKk0JPPRCIuMhPNQ1e89+q8BvRP0dmF2Z3BXAveggYFLobicFI0eokRnsfXrLe+jM3ODzx8sR54+U9LEZ+vd0/Y/xV1VQq3ksWzoFm1dGVJZGRF42y+mbo0bsvbrH8r168Z3G7+kFWnkjDZvIQfcaJF9jCzt5WXu0hJyOIW43QwAnwn2Yh8GPIIxM0Ma7yf3/n703bZPcxrWED0hFZq1237nP3P///2bet9uuqqzKDBGYDwBIkJIyIpfaunn82BmSKO6LjIOlp5MTWWxnZ3eGJt/e3IC54OHs/UPglMCloBSx/hQ8BJ/0RBoHvPEtgsXW3XmHOIn96USe7j1ols6icb5XABBBqe+N54sS2c1Vet+kUkdE72YQMoAzeqLdR8nPwLqLUD/GIxH5xs8Jq5lapUtNvJ5brHTAY0sTlqxzoYYUsCF5sBAduRQQCF/NA4i/f177WNQewzynrPPAxmWxfiXrv6aUYFWzbXhUvGGY9ehG4SH26BYPpb+fbCTOq99fu1wSkaYpejcvCYkSipglNHMlJcXqq5b7rsXRfzM0Ir5v12jB37nKFyeZ22/fH2L7/Rtg77wgOPEMnHLGkhMKt1AHLUxCW5MSX97+3LlxsMv4GkeblzWGde3nFMa+9dG5aCz54rHNryXNh3nRvA95vXxjtHp13wNjXtcV+Rj+kODCnQASwud63dr0B6i6dO+UDFKsd1xpQ+U2de3bmeFhJaQqTIDUc4jOyYycNLwIEQEro4hAKIEEYCPQU05qre5jKG1ca3n27eXfYCAdP0ppoyTq66bWmggJCZJFv+WyIC8ZlBKSAJIESZJtSEGhhrYe6HL41i2iJDnD5r55DBEWuHeU5kti26dbMjzU2r+BIeG6T1t/y/7vLu/h/tEX3wX9Aefxf5MvxImJiYmJiYmJHpNAn5iYmJiYmPiPRRRyVZIcJiAUF0g3Er2Lu+3yKXFiRoW+TiZIfdauryW6jpMNwqxa/esEuqG1T+LcqpBsl7CTKtBzkmPjOhJOj5krVKC6bgWUyAM8FiyD2Si1pELPU8pYg9tor8aSMlgYZxaszHhzOgXLIROUinRWPXsCwF0r+fB77DeBCj41lqYKS8/CKmQVrWNKCbD6U3LCQyBsQnhTsvB6eb03taj3CDkDgtT1rvf1pyBWpUTBenfM0oX4VN8n8rGIc32ns6YE9BfDSwdDVwSbBawGoqXKlrorcwdL3N1eG9T9rqQIUOdiMmJLrfWaoocMq9UtfPc3OZvnpkTiZNWYhztRr+Qi1CK9I4hFkFNGomIuqAFhxkLAOSijeJ7+24n9pAVDIFih7tkB4CH0yCkoFMTwE27lDAEKBMXi/QZKZLeXo4V4xuNLWix9JNwj9t6NClPxGlDC/PaRqTMS0K5YVV2um4l0tr0zsSv26P030ruK39TZkmYii32uOz/ZYZ7gnBvVsx9AHfdOaeQVl8C4zrrKxudOMO76S9bRIEAtdkX/itj4UZt/uVMUAZja+RvPQ4p/yQl3gisGSs1Hlb+KsCmc7FeveQowAjUS+UBQdvMeaPPeeyT2S32X+utxHu3NVM9F+0vbsVDuzj1hdPPL9G+eZHW+jwvvH/DSL0WLf64/PtrVSJZ/glqlf06t3X3lXtZ+MstygoS52Uhu9S6U7VtRPZ/ICjAKIIJSirqAXzIyEZaUVdkvlOFKDokIOWdVQtGYHqo8mNp68BBBAqku2x1q/Z7g3oRS6BP//pPq/whdmloXAZgEZJbmHm5I7NuUEb5R7UDqwkmFrm9eYdow7H6rDsowMrz0Wt6/ankXsuv2klcpeWJiYmJiYmLix2ES6BMTExMTExP/sRAgSpywJ2TdM5/sRIg0Cm2DkGr3mnoWuLOGdsK+536aZdbLJKuvQbdZhVqbQ0XZhH9p7LIg0RYAZylIbMJGNIF+TgmFnRxT4f8qanV6Wk5YWF1I3+QFBML9egYAnMyycC2lFpVMoEpEyEuq8cEFotZD6K2q9wTvUfgYx7yNvYR3TAifCSxqDX+znJByxkMpSDlh4QK4u1CRTpAKEXVPOg5SmHdaX+7mbSUlxtcC2ScUrKM6rkbnG2sg0Z0OGGxYL06g7yT5fyKODLNfSntcndPrFfQ4nNy9ktAZk0VCqs0sAbnFdny3Po959cL4Riz5nOwLdIrD3d22fa5fh+7C2q1BY/sKM7LFHK+u59GmtTlrB4U2iWu9DHV2MiyS3NFDhCtHbda94eHhrIRsUiq2FDURXqHWlCsXs5BMSNJolo7wIFLLc5GOOCci3JgiAEX7b1KiMQlA5zPc2nAdVAAA4Nb6I9uDZmFuy93uey96OnfX7laSTka5y/+92RaHUUjdtQvEXLc3ovSemiX6SKb7HuskODOrVX+xrLngVggrmqV5bAdhS6LHU/MsmtHa8fFGpIsqIRDUQvSaNbzd5ejg/uM5xK+D/RI0ZIE3tJhF9ClnnfdVEU3/JvfGYt8uOZnLeKinCRZGDTsDPSvF2x1KzmT5sH6TZNJztC3cPv2Scneujl4qaugTEZyLKp1E6/Nxnfl+wt0Z15Rrjvp5O3Q99e7vu2KbK+fdm3LbNoOhpGsVITf18pGWx7P5Qcfnp6M5Tk6e+4fcMDfjggO29U3DdftYgYZtECXAnYQ2cjtZXPUEnXdVWxFAEYCE214OaFgd82ZECN/UtmNSSppvIqSUkRKpdwQuEBawFJC7fK8KjZYDwYj+jCVnpKTu3rm0WOUeXiKnuD/3/aRN1Xqrcig3C3TzaCSspDrs7FEL9O5DrbarzeRQTH3qgSq2z+r7w6Q7JNL9/pVzMU6lcSf7uV+DExMTExMTExMvxyTQJyYmJiYmJv4tsGuUdQHubtFyQBT7VDFUYyFbMrtfhfgEUHXfTr3AMVw3d/CBeBoEbpFED7c76/cfx9Ado/FRQ79gv5ZRQA5SYX8iczcsjGSk02lZakxxdYnPVciXcsIJuZJnVSBdu8Z6T4ykk0bEu+AcaLGNnbweY04+1tMEJSgoqftQSir0dSKnxtglAoORkJEXtbgSztauZmlEzBp3E2rBThvWNxB+sa4u2x5YUY8hHPFetL2fQ37REj3GSm+eFsIa+O0koL8Gkf/vAhflH/ItV25Hbp3nxLcreYxrbc+CLyYorDWqZIHvD2j5OQlNttaIYoxzvc7V8tHaKNu2+trIiZCyqgAwKylSbLGf1wKyvSunhPvzA9ZAzGi8do8r33Jvnku0DkqoxH61tUzuil41bNSFebPtPur+ewBvuv7fx94JmHfuEXqL9D2i5Cv1caG/0j4tXMnv4T4A3ArhnhoJG/Pz+zeytYwXPO07oCkQqAU1VfL399g/ipGQzYLd92v/3tBL50LFbMtdkSzCiTsAWEzJi9B73olhUTrlM6LqHQIglFICtd6UKyiWKoK1FJzyYopk3BHj47dDXSd9S4c27MFyC+8vdnazLfhXMsZ9Ih5TAXj91x7N0iaKu3j3a9+GpX5phXVx9Tqj7hfZ61quuXOnhJwWZLI9Nux3zDbfWMln5lK/O5OIWnabgknzIGFnjeWVcjYiPQNSsArUXTrrvHOiO87pbNbtRIScF5xOC5bTCQ/3DyjnFoIhfm9FhTE/mzwWe2FGkYLV22Gp2MhzV9yqf7E3zFLHYX/+N8WxnYdPx1OGOWDvm/k7TNuJiYmJiYmJiR+GSaBPTExMTEy8AqT/z8QT8VSXmN7LTpy+qNevlJ5GK8UoBHTBMkwAJ57C46ITVVfu0bK6Iyqj2QtQ3cNXS8jKeTYB5nNioMfUjxFiT8kHns9A+CPes7ZDVCgr0DYtlNWtOZRAvj8/wONOpqSiwEQq0F9LMWFlwrIkCAluloyHtZh7Ze95AiWrQ1LLprWo0LWwWhZG17G5Ws05idDIgdqkwEtkJ+QFoKzWRypDTfD4lW5ZDyi58fbmBktO4OUEZrW+W8uKwmrNJGwxPqsVUig3kBfF42VGnQXqrYqkWro2fKFhe1IGEe9NDvwJQWBOhLfGfnymRnQGY9+N1dJmHv9k/Cr1eC7o6Me4TwzvuaXm1iL90kofFSXGfUn/FLts+ff7094+RIDFsgVgXiGcIE8p2RxvFE3MyffTtcQY7BJiLrcJTUDnLCTQ1HBPETTkyyI45WxEJGG1mNm17ikDYCxZlWDM4TcEBTknnNfVrBu1pLUUrKWAiyrDZPJ9zBRUSushazYKbFhFSWHtJj03WMxa0/YYJ9DdUjH22C2oKgA4yeyW3pHM7Dt5fBIJIHSaEYLm2ru6vrf/3nXzkeo8HWfdLYBv9u9usRKCgYQDak+R5yS9Rb1g6769a8vOdW2DdVySfWrq+t1kPPiGp94vw+NL+e8pIAiAYsR/9RxRy2laC29vbrCaRT2LKnQx8UYxgZjqOnQFtlM+gUhjyRMIObsL+VYzQeuz6AEmtmnTG2G8z2XtiPP6flAudML0Ul9FpQ/A94tWZhHtqW9hnae0MZfuvu2eg735RhjPpWeeUa90tNHORSTPu5VQlUpC4Xv1oOHZwXe9fmMZ5Z1VISgDSnTnjCSmUGTUOLHOBUlAqqMM8yDQCm1+KVDJa0oEKQAJI9n3VrE92r+93BJcm0A1Nw/RwUtz6y62X8TvRYQaeH+xkfNcGIULChespkyl+2evwNk8pWzJc/G+NcWAUZd36F074za3e4L/4BtpM0eHZFf/v5oMM+al/7MxMTExMTExMfETMQn0iYmJiYmJV4GJYn9v3uaH4+WxJGHWxM8oG1cSbaOFb6XIHxcukTEkyWJ9i1mXqyWU1Vvae11d3BI4kBEh064N469rsHX2+8o4qA6FsVIBKZv7y2bpVsBgFLDArNITciYsecFauGaQUwYz482NOW0WJaZBQKIMgQo9/R0hJe6YxdKo1VLhoq5nqQnwhZqlHoKQVACszEgJFj/X29KiqDvBLYXUZW1Sy9KSgJvTom5BzysgN/h6vldrVl6xsKAMBL4HntW5ysC6oqC3AN3r+zgPe/faQdgrqDHiP5iE9s4UHe4S4R3HuSbbOTrxA6BjVkfBhvDXk0WPzEl/112xxxQiaJbo9clAog9E+bhvRUKgumIPpFufupFAGt9aK7GWAkq0u5jU8JVM2YWUSE+EZcmdck0ysju+SPCYvsmsHPWRk77e5gwNUyGBOImW1Xqt+bmb39i3gBLk9zsTY4carD0RM3FCNL4eCc34O5I7X2n73mPYEOcHdbsmv3WoV4K6hL//9RbHD4dboi45q9KLACCNK61knlJ4mZSM5KAdFdeYunpv9329ejgUf+KhHYgIi4VhOYyFDtQJRGHl648whwnVW0R1GT96TwlebXy9eX5E7qqd1BvEYDUf8dzv0GvOwz2i+nt/fl1EXbfDt63vnZtvXn/hUj/tbQg7K9r2MfUQ0vbJnBJy0nueEcP3dgKQVMvF78H2fBELMzF4RhACGCDidjaYIqIT29Ele8zXyfElZ5RVSXSfQyLNLftovV6VMFlQyoq1FBQvSwSSTTmq/j+jVEL90PKc/FPQyPPquiWS96h18Xx3x+Zo8o3pXRtrUNpra/cytmfwxMTExMTExMTviUmgT0xMTExMvBImt/R0RCvsH172hedHtYqEwmGaQHQgCJe7clkGeeSBtU5MIbEGR6kuw8nQo7eeOiKVFN+5T3vpTAhYRFCkVFeZAJCRcHtzi2/339RqDIK7+3skSliykunFLN1uTifknPDwcAYR4WbRPAq723cTqlrh6o5T06SUQKJEfClF5fPJxkksHrs4824WrKIEOQB1De2WS8TIlPGwnit54cZvKkxliBCYM1LS2LU5ZdzkBUUY5/MZ57XgoawQNAvzJrwERDKWBUgs+nwQ2AIWA1esblfMiTsTRrcCFe+NgfhoygCfE3UExOhiuwpV6/2e6HCMMXF/P1xYGS/cyjavbyyt/fZwbS+musc4yeqEyNPqUcsbiJZx2J1syCCNXVtd/yqx4USd1zn+Bnribsi51qTduUKBo/I8SjAoL0IdYV65OACUcyWzKRGWfAKL4Hx2i3ddxzfLWwCClRlrEZTzGQCU7AFhLe7St5F87ppXY7arBfnZ2JFMWoFiRMxizVqClsG99XfOCcKCVdTtb4FSlrHBvT14Q41t7rUL5LtyI/2AlvBM07V8BcBdc43S/R33q3G6eT6HZ/3I3eyn6vCVgLeW0NWXjizQNQ775Txfb3faPxGf+6kzruejA9dPPPcqnRPhfr3Xu9xyEhHc3tzgfF6VPIwKe0CL6WzfCEvw0uIlOUENaBRqAIiu3bUeuj7KxtPB2MDQ8/Wjobmg97wcKeeO/HWi39OsrK4eLp03Hr7kueBxXLwJI7H5K4AOfvutODkjCf2k/hn2h/E7xm5lIiyUcEoJS8o4ZYszTqmVx6hzTtjI3KAkAei554oaUkpXxv5hHM4iFhSLhe7/H0LJQywBXPQb8oFSszZnxsPDGeu6VtfvNY55Y661+maB3qzdNayBSLL9tCmeNM9HfW2bM4Cm2FDPNrTv+G0reyLeTwlqi2vskuFadu63/1e7ljxvnrcmJiYmJiYmJn5vTAJ9YmJi4jviKf/T+Dtpav/KdR3r9qPrOsf86fkCW4Loejy/VpWL3kPH+qpAjcKzKoY6EtAOluidbNJ+l4G8IOpdd8d41HsisuMKX4EfSGSO6xGI1kM0pJMq1H578wbreu4EgcyCh7JioYxEpJY9RUkqIjIXtepWPZv9ZWFuLm5DN7mbfRGphLDHRAU0rvGSc3ANr/VnI82UFLM4yoIam9MFoSIAZdHxF0GGWlgtKYNJ1Ko0J2WtjBBQN+1Dr0WBqQl4GbZmRN2AMutvsfaAjewPTNeRcDboGdQxuvM5mkjJ9OdiVzj7CviRG+cLSfFXxcgr/wKHiJPP6qo8rFUZXK2H+XisvHPc2SE4BgRO5rsFohPCStb63t4i9+oeWi34ScACdfEL24/YXGLXqrR32y1VwIlkyYakG5UboGkWJyWpDRuRerJYjUA5hfdOlpCLeekQYCFCEuDhsJd6fCO1yo5wsvmxqfPost15aavu8Ep4JMO3w7PHKNqvF/K6ssiKF28Ju4W8vPf8S8EjI5zXFdkU1URadGQC8O3bPZZlgTBwYzGi7x/OSrxH1+cgiDBI/Huktd8JT4HGcva5n6DKNM2g3JTRHmmjr4d24EtVyHFLY133VM92TSUgpOoFQgQAX/lF+cKBfAn5/mq4dAb4h0u89h8dIarfQ/qx4fPEB3to56AMWp/6thgUH3brRskUIjOWvGj885S7jYSFIUVjnkcX6616Use5EtzBM0GtUiWEmxt2Iqrxz6tSIJI1377DpNRNhYV7d+ylhPjsbok+7KvSXLizWIgeAEgMNu9HkdA/ApmSihPn/v8Dqgi29Qzkn7CdTwlbhzKGSon/EyQhA7tBO9W6esZ7X9f/WZqYmJiYmJiY+H0xCfSJiYmJ74QQgnDiPwAS/qug4elLrn8kfuW67pV96fljdYvPN6LAK2u0FQrXq0vWdim1mLbdO9KEhKNVUOdG8fsxZ8/rjevzdZo80ub+RCD4+vCtCuYBwsncvKeUwaXofaLqUjYls7Fkbq4urbsSEc6runZXV52C2+UENit17WYV0JMIyFzuU054c3sDEPDt6wPcAsnTAEAmtZoqUqrgn0B4c3NCpgxxzsxczZ7Lij8/fMC6FjycHyqpKKKE/Clns1Zv8TFBULaQNJ67yrRFCXMIiAWJzA0pE9SCvbcWfFxfQoLgvN37KMDfKanHVCmdt4htDPRGDlqC3ZK2sbk3NdnN/+fhwgp4MQHzRAzdMgq4ZVi5vUz8srePq+tTlS/UdW5hRuEwvrY+uvjC0iw2PYtKsA/Ex1hNnw7RYl0jMei8JXtnyboPFLP+dv6HjNBzhRnfG5qXCs277gWmJMPMKNA4zVrnZEyEk/Reb99DlMi7PZ1QhNUK3Swdz6vUdCv6vj7Z9Z31z1tXpnESojAkEZDcjbvunXs0IQF4N84LlqooEOvdPBYYOenbTRsyy5P7I4f65xCpijZfOsKuH8ijVR3z2XuwnZeCO3vyTgCm16Ey29l9nOatAN82LTlqJw+pho4L6who8/6oNUf9R/EcA1ns7+biOieyM1ZzOJfVXGUDN2kBF0EpBTmpte15LdUiPaWEnDNyDhUo6gfBvbX4uoyENwBT+AIgrIobYd7VeWjrUAAsOYUxDySorXO3jD+vam185rXrl0unxuVTZT9F7+/hJ59TI2G+V4Ww/iJFDopfXdR/eoZe9F3x2u/Ao/RiF25XrnsL4ZQzbpcTlqwkes4L0rLAnZgXYVOO1NjhEN2Timn/KPktgHBVmhBX0DAr7RqyRvSsgO3HugfrZK7ehCjpN5Z9ZwJie7d+i61FUFhQatx0sWeMwtLK1l20Cy2gfZBA5I7aqZ7HdQeXYRj9ZbLd2M4NP+iqklhn3t1y8K/quDAEO3KJMGhx79vbhrtt/RpYPs8NsTUxMTExMTEx8SthEugTExMT3xHN7WK8Z9eBrzB5bHc9Pt9cj/kdXOMJaa8t+2Jdn1G316rrWLcfVVdgJ4MqtAoVAWCmoU2gSSZl8Bc7AdmuSOr7XXd1lZ26DnV7YV2d7LSrTti3vXYhn5MHES68qo0ANs/36nJJ9LozC7r27lAYl0gqFzJzAYiqVaQ/q8KrjfkHhb8qPOzr/Vi/H83u8f3veW13bcwl1CmFMdY3o60cUFiqRVtKan9WirY/p2T8MoHZiKeihE9OCSklFLOgcyu1ZHaYLuB/KKW6XOcYE9n8PS/m6vksZ8gqcDHrkhMoJVBRK/CzFBs/swoSs5wzC3EI4dPdV9wkdVn67fxg1uOMlVuMWY+DrsJVUYvybK51U0KyqJnMuiaYYFJ+BrOVWdfy0LPW7RvZP9l/REeGoVPwzkaKbPBk9+UA0edtveq9XfK22zzDGq6mYqjX4zZz3Wx7BYzL6ZdE3CmBuHPK5unrgoUrYcDiJJqvXivZvShw5QA6fSCvXZwj3blA/rdN3rr7WgNJWmvdUrZHXyeblM19LyXIZk+N6bts6noA0Lmu9+SuWLPnvtqXptffCdBbqHU5I+6TYk1mECk5k4Q6ZQTHrRzHPY/Vl+E61qur406a74GwzLfPhuNrXOd3BLx9UmnD+IrfEUSnMEfH+Fev00uwu3mN3xLH5/m42se3ElTZzPdfdR3NNodIzy9SV9LR7TpbVsyiZHYs2c5DkeappdrR+nqsa7qtPz9zIajl5KQnGPycBYU1rC6+vS7Re4Wwel9haaEhai+Ez+unXF+DMel+z78ijgqgx59vY5d7Old2aL0mpPsOAIsfHtKTn/i+Mvr9zvNsL/Xl1vRhbJ3sFQCUE5bTCTkTcsqgnMPcYhRmrKx7Z+HS8rdYEVLJbW6eTsQKNEXDpqJpyogsYClQpRB7Yv2SSOOSu+sGrYcqYhVRJUWWgrWstRgxq3Qp7oVEAAISsipgJVgdks21BFBbJ20Gj6D6R0CAKXeGj7DQy2E/F1XErM/qA+o21mE7bXs8DQkEXf3q7Ws3P/E2+L+tvhMTExMTExMTvxvov//nf8/vmImJiYnvgEuymUvC/x9GDuzgV67biF+qro0rUtGNSqhU8P+ia88PT5cODtfqws+unZSo18+ta6p1e1ZdEa8tb2UVttdCjVSgRrE3S/Ao+BuvQ1n+XPbSh2SPCq2lCiCfM6kaSeoCYnRCSTFJW0ek1pcBWAxGeqTdKm/btr2PtziK1GLbA3laxZHhtd1+rSUfPm+C2P45hX52cVstW1wgCZdVauxlUjKJ0CxQs1mRO25vbiAi+OvuCzIlnBaNNpxSqlZ3TqatzGaxB4hQF0+8sLoVTdaGxQgtjWmecDot+NffX3A6ZRABp3wyATFhyRlv3r7FaTlBhHEugrWsKOuKUhjnUrByMXefpba+9kMCKGekrG1OKSmhZqNS2FyMlhXrupr1llpZOclZLfUHpZ1qc1YtWzmsDYW7IQXQ+pbCLPE5Jc2tKYX50MU3tVLaZCIrQ2PbV+sx+y9LW+GXVvnRNcK9S+ezp5Dtre3vZ+C5r19b78O71xZs6dJIx9L+JXX/QN25B7Kl8zxAABcdTzYCjuw/Pj+qZbQTe3bu+F7YXPr2+02yde8hGZzQa66I6yvDmXEZsnMl0j8Y3elWA8F4tAQrUPc0UbdFe+7u3pOyMEpCsoBXs4S3Mr7RXq30xy2aRbk/E+iyvq/32vtv/SEBi7GXX4b834qFd7BM3xUP96DpPjKARPhsoR+87Nv/9V9gZvzzr7/wKIZz1ELF13rXa1M8S/Va0+QD19J+/dbCY9x1Qy6mOIG2cWCYFXv34pyyQtI4l7hv0KEHCPLxid8Tsfb9jqZRxwmk8UFwogUpZeSc9R6alSuF9Gt5sE8Hy5NI9fB04qlSWmhrMSt09+7gNVFvDYIzt7jTtf6CRqgP65Og7uHFDnC28/WUcp2fiZo3iNVim7f8t1906pWFHv3M9PkDke65QMfM07b1c90HnX/D/XDUvWSrLtNPyXF/a/MrUTKlQd+r/XsR9l3pxK3OE2qF6rnuVuBh34Z5yMmU6jeSE8D1bADw5nSDN8uNzQeveAKJxw1nrKWoFbh599FvNGuRlTrhngAAIABJREFUNYMxetepsyJ8m/i3jq1zAghmgW7nipLurlyofSHBvTtgz5O3wv4fxBVDatn2/0NeeK2D1Y4Exd4VD9lUFb/C7KY2du3s6td1vxq4jbX4Vfh/O0ut52JbizWrDrL78+DGMeLejbbeJiYmJiYmJiZ+R0wL9ImJiYnvhPF/FGnn3nOvR6Hga1//ynX7pesa5FRuAde07sM1Dc/H6zE9WoFVIFkFfk+7rmKZneur6rpbN+nq9uS6hj6DC7QeuW7CK8BJ9uh+8vG/6K+rYOqZs6j5XH0yyKRKLuRTuaVZxXgpVQIlqGabJidzQV4knfudhg7++vh5O0Yhq6aNJOZIiFfiP6Qf3t7k59gX2qF/3r3R5yUumDNBIWpdCJCCRAQSQk7tPS6CcylVuHiTFzysK87rikLqolbp3YSblALh3PpCIOAH7TtmjWFewFiQkUjJGxHgj7fv8PX+qxISwmBi5JKAzCjLSUk+BoQLeC1VWFyKus0tvFar1TYzRc0ImZElIWUVEC9EagFPAJAAkWqBrnMkjBP1e1Tr1uDWlcId6ccsSTLipV/r0TK4uhI2aytIqama6NZnXJir4YGLp1u67Sygneu9v0dpr93b473dhxMAbG92OT80vqyfHwQCu+tdQvDGgBaTlXS6OIERLddZuJsr7RwAamp7T+cwVScqTsSr1wka1kA/Mwg93ymQ4BlDhmEfJmzsh/C4zt86MSN57q6F/ZG7otfEqiBDtqZ7os6zuxXC/YFFIEk/rwUaE/0xfDUFu3cAvu6kvaPt9XtpPenH6YehStH1/iXUIxnDCIX2qDvw7bOur0Nevptcan98sVvu1E7bUL3BY8IOgZ76jmgeFLBJF3vIvZh0O+Cw//h6ISI9v8yDgrASZTkFS1u2dWceS+rEI1dAI5Sy/Q5wV+uVpLaYz+yfIdS+vMgXXXc29DmyCLQ0bYiTrBzOu2J7Q+X1h64a93glPlMYk6G7qD9H4/NxGI6G5wg/O9TIpek8ztc4Po1c9xO7jVZN7+c6hV4nPc27L0Db+72v6z6e+o8Orw8DWKEKqIUZPiWrVbcNjrtL9252S+/koTRA8TNl0yP+9Vo3BlIFQq4bBVUvWAWom4qvefWQQOGd1k49YICoiAhCbwUO//LR/hZbL65a6OdVv2522hA+QnoCvXvY9bKvsTaGfeo4duP7ez+rguQz8XNXysTExMTExMTEyzAJ9ImJiYkfhPF/Hl9y/Zp5/SfVbbz+/mXJq12/Zl7/bnX7maP+UqHQKMxygZpEUrjK40xiDjHZd7Pr6uVcl1mCXhB2RfrD9/fF2zJc9zSDbNK3cmhI1b8v4b9AjE2qbxQBiqg1d6JU3RyfssZsfXdzCyLCw7qqNTnUNacQsCQgkVrC5ZwhArx7e4tPd3cag12UJE95AZPmfHtakCnjXFawALeUUUSQ0mI1Nes/EzqvIkgMsKxKipEAiTXuObES7tZEsfd1TpjwkguwMsQsqCAqTCZQtfoGAZQIWTwOtROLMIs1nVdS3er2I/BOpLMyBZQYYjRrsRpzWKISg79DyND6isUapfawjW8ot8XGVTG+OPHugngX/koTYFO4jojXoyUzDYk2hNdO3V4TF1daP9E7suy7lHcEK8/dtR5ZztZqks7VUletD5it5Dic9qIrutQMoMQ3JXfBC6zVfa9ZtIb5qvMgtXjKAT43ncRPgT0QxFjsTUGrEZhKOAKCddhbnVhpfFK/A9OBRXjcwqvL4QHRnTCcwSVdE6sUsAhWAMtjp0549I2Ad67wYha62zdb676GrflbamEcYr7v2WKc2/VH9wgQsyPN60NYm0eW55tjJFQwnhSbv3USDOdHJV+HeWhvj+1/Ky1XAfAl+Xkb6Wy1knbfN+02bTYKHuo/rppo0VprZASejn1sY6s3AFOISPWhE3+ZcrUI15AlwGnxfVTsbEt69pDWkZJ6NAC7JSwBSBCjrWNLCbB40M1jRF2T0uatjIMECycQxsN12uLXI4Dm2WSnz2J/tpL9YvtlIaHz6vkZz5rw93q1jp+M3U7x8A7hYdUu9CR7B8r4DabvadgI38fIvi/pcEAk7Kv1WzQoCHmxkbh1TyIZhEXcTX/GKmvzyMQ2bn4dWuC//RvpKYifILvnxc71XtO13SHl+FExXtfynDR37wyPfbkcXR9/O1++7vHcT5ynvLcz0yYmJiYmJiYmfktMAn1iYmJiYuJ74BJz8TRZx8/Fr1y33xhRIFiFoSaUj89U8NcPAgHBYrPPtacM+h+NRhzt/3vEFENOIa+XTIynidV6seFeC4e/FIX9wFqKERSMJWfcnE4QCO4fzijMOBfGWgQ3i1ndMZBThojgw9u3uLu/BwG4OS04n884LRlLXiCscdRv0w1yzrg93eBUCr59U8IhUQLc5XpORnAQwEmJcxCKJBBZHGkTSpeOnHHrUzHyTQlqSIJkQZZcXUf7zElEQE5R0tt1jxIrlq9ZeLk4/o7GPtb5oMZYIWCAkTPJBMPVNS7EYqo6yb4jLpYj4WobPy+nzcNG6zwm4O7rLcP1UMzO+ulL2uX2vh/GQn6y9Pn5AvCx9/yu3s819IDdt7lLZsLIzEgpIaWEwlyJdrdYj5af/ittB7O1I3jTEAmuvrt9US29u0z3dkEJsdhHQiY+G94bCaHxOaER7InMApcFlLK5WxYUURfAiyglmQDcCOHhgoYFWSEeK3zPunzEGxDuwioEjDwH8FF0vXPfDbUtAPCZmiX6h7FbsT+vvuzcu37+9Wp98d2jNez98Maa6epFdbeqLzpR1hO2nQW6hOuDSjdubUuupURVGWRTe51A6BRT/Fok8KQMkVR17ZgtTdL1oQpKGmM6NpGN3gy79p5+QHtWU3KnmNGowbC6qZ0Nlb4NxKtUxcAXUIJjRUc2/9Ik8m791di+TYOH+WfXdZVuCPPDjC6W1whnqaPZb23NL4fOIXQBPyT0fbcnkirgfS1nzVvC3ij2Xr32e32b9nfRK2CNGGnoPSVdPWe8AdbXgro3Pxf9d/9TUUfiQqpxf9nW4Tl40nv0knZOTExMTExMTPxamAT6xMTExMTExMQvgBbbPThMb9LDThiVUrPeJBPyuaxvwxLaPdlKDQ9xSfBVw9JfSDfm1wiE69KPNwnS3NpTy2YUaI4Eq0DAEHBhPDCD1hUEtcw7LRk5ZRRmPKxr7atEK9ZSkBKQkpLUCQm3twtEVogAN29usKSMh/UMEca3+3sQCHk5YXEGIiUlwMy6VF1JJyAZWZbELGnFSOqC5BaCAEjUepTF5wObpa9ZpScZJdsgysgEJLdI9/E3olItvcx61C3go9i1WvA1AT1AleT3GMwizdUugEbYM1uZXjeXpjpr07sD3ZZrQnmJc2GcwOO9nWklB/drcRdm+gvZ82vXx3NBI2HyQon1SP5WGmqzgHcvN+/5yhwVMordzxbDd8lZyT4yy/Rg2Z1TVhfPgm5ejpSbW8L2tYjPG1ESPWg4gSLSaL+RsOlTN6Qag1jTFvZ6jHXjkOqohjBykyBEWHJWjxTFLYsTMquXia8EnATIsJjCxmR/HYl0VxRA+59+BvDG9xazTP9qNXtnG+m93ftTgL9Cnu+kHR0ekxwEZEtSCHjz33/iXSKc/89fWG2PduJdAPxpZfxlXffeOnwR4E/LP/1XT0SXf+mPm//+L92n//mXEog2kJ+o7912zvQjWVN03ST4YiMRx0Lzj4QlVUWAL8nd7TflhD7j/ZXRknlIC72TE1m8++h+OexPZG3xQ16ULE3VIJ1Aop5TcvWjbXblbgaudHfd/yMyZbhb6Xh46h4sLXpMt8b8W0W/XNjr2ylzWVb9cNq9FnLhWuzt111ZR90/XIfPqvqedB1/dZWejr1vr90uiGTpljTd20uae46xIePGTXXs9LLfTb20ZHcp/PKElIIiE/VrR0SV+E6U8ObmFgBw5oKHsgIiuD8/qBJVpyQYyfOhPd2+Ld2331MQlo9lQJue9Tsy9J2rC3TfSc8sP2T7tPd/OQ2PiYmJiYmJiYn/DEwCfWJiYmJiYmLiJyG6pgYCiY49cozqO2QC0Grx4+SPBOG4kx1OVgaB3Xj9GA6Fdi+SIj7j5UG6O8qhH5N992JYtZUSACuzWv4ByFnd3AKNJBASMAhcCk7LgpQJKzNIMiSJ5SEQNrErWTzy6tI0G6esFuiViCcCWK1KkwhSMtfx1hBibKzKSQRlZYvnrK7qkQBJUucEmetrmDtgWBxln1dsBBwASFYSnRiQJRmJ7iT9Xh9GYrMRMqkmp+ZSfXBtbbRNHQGdf4Tq+v1grH66uPgJ6+Rn4AWy+F8C7EQiJZwWjXnrpLSGVwAg0mIki7Q5hn7/FEgldKkSe9ue6UgU8IHuwXbmUZz/tv+0EAFGrdT6tH1kly+z++7Kvadp29qP6b2dxW6fA3F9BJ++sQ5OjPl+w2GO31F77vgoSlD/IQeKSpZx/i+C/FMJVOa/wQN57nkxtbp8FNX/Wf6LsP7TRoSAv/6S+hxAbwBOf29cgb8H8Lm2OVhk1zlweSep56qVQ+gpdQJwZwUnUj77vWV75x4OYicLdmZfKC/8VYoy7q9hH6zzkzREgJG9TmkmpBpqwXNLBAgDzAVAQk7ZFMGSxUo/d5XQGOIJHgIk8KQaLMT2aZ9vPj/Z7rN9d4zzdtvmbY8chYd4rM+2Z8YzTgoK/Cz639/l4Nlr5gFx3trZKwo96zjqXhpJ4UeqUSnj4zKPxs73sJQSvjx8C+XolwNDlfbi/hEHoCk6bQdCRLr18WTUcbdFbMt2q3zV2hLPCBmePwXd+/ufWRMTExMTExMTE78gJoE+MTExMTExMfELgUBmZb1nUYkgUqXgttjEcqRkTnUV7ATNICzedTP8DOuWpxJ4LyX8Nty79D/HfGPE1pjOiTshATOBeUUiwrKYBR+p+1tWszsIK4n3+ZsS2O9vbgAC1gdGJkKmRUkdgrpRFQEnUsvCpBaliTIokbnWbfFAExJy8nESEBOYyMg1F7cKCrO5s0ZTIBCuDJgQqctns0xUC0VCjdlsVooANQbN0ogwhFKzAqOCdyz43NQ5QNB47s05vkR2R2tpdd541EUjWMbBi0k9Vq570t5YRFfL976AQ8+1T4Xl427pJdxXwT+MoO2St/qNV1fW57nrgS6t2av7pRG03d1AGF+T/VE7tgEjKDwDzuczclblExZGdbMrHuVX0+eU6jt9AWH1ixF+FBoUKhb3xXg/1j0lrUtCMsIl7L3D2NsyAkBYMoVhb15Bcsrt/dgflm+zZN/mLQDOpVS33BSI7Dv07XgbluM32rpqFwBvQj36TunxVoC/QjL3NEFG4JIAklqLUv4Tt/+TsPK/UP6lRHh1yU6eB1WC/g+7zwQ8/AUgaUxkAvDBXvuUBO+ltfnb//dPCHqCH2hx2bceBh6f+L1r6RbzmXaeKynY37+DxXqn4O7ZynVOXdOnLp9UH/T3nazz3z2p29xKk+2xehYwTvnG6sBKhouGBMlZPavwupoinY5iMuvhlJVQZyQAqhzGpkBFMM8rIBQpANSKWKu42elcv28gSyMRednifNzX67qrr/Trp6tAe7y9v3O7I88vpH8y9vbd+IGy0wUxbEhM2lXJv+usQ8Z1IJu+7efz/q9tf1L4Z8xu7/JEGSmlOgceygoWwbf1vDnDCTDvOqrwVNv5na2rW9967/a25E0BpJ+icpDuOeV358LExMTExMTExMRvg0mgT0xMTExMTEz8BERrrU5gJ4FEx1bW6sJ1tUJPqBI/cQvMJn71SyV5gpt3y6gJL9FcqtqNRh4O7PtL8QzhY4dQlTGro75ygWnNQhDEqAIGK2lbSIlvUvLb++ReCoiAnAkLCGdhLJSwpIRkaSFUhciJEhZyi3MV1bZ45L17W5DHSgeIFxAxJCUlk52MI0HiAhZGKaXlIR5XOQh1k9IzlNSikAZ3A94fZGycEKnSBUyIzdoXd1Zm6yunRKjGLW3jITZHBCMzEV3jjrNoJF0ikTGmfXzW9OP72ojC72tq8z3r8u8Kd+FOCaB+edSF7ntm9WY9EMh+x2eDDBOpswivbGjdIGtWydIlW7PFyMuUKJAnviqM0K4EbnP1m2LdfI8mwhpjrdPxbHISNRLD19AvCUqAe8pvoYBvlvHb0HVvZUu2+/U7Ucv0GtPcyXNCoPyMJBZRy2eo5fJ72W9bgZLe78Ne8YW2CgYQLfcIe7HVH0UoQ+tMdejJFKdcGcL+hFepI3I/wOdKexbrEY7hDREfKlCfE9AmUkzb/Fkbse1eGERDgwBgXtXK3JSlWAilFAi4zhkO3wmAVVwIKzh4ONAwIu7BQWOyu6V5G8yOfN3rfJ/rG8a1tbf/2+crm1eu+GagvYvvTMpuNI4eSTzMpQtJuuv9VjxmIT4oIhymewUQIeWMb+tDN88f90jAkNIT6GOej+MZ41rXp58AVEMO1LuBRI9zffPd8vTSq9LG/DKYmJiYmJiYmPj9MAn0iYmJiYmJiYlfCC7jjjHR9X4TfjuBvkemuMC8kX6d/L3dlU6iGzJAtaIeK/Vawr9raciIa9Lu5RvbHLmsPazCoAKcLf2SzVEuER5KwZKyuiDmAhBhLSsSNF56TgveLadGtBnZlkltt2FdWpgr1+zcMiVCkqR/1bFypPstBnqGCLCmVS3GRa0Fxd2y+/gwKynOFn9apFqmVaKkltts2ETMxXtKIIES9mlRgp7VctHpRzJX2tVUXFjdwZuShk+dDwJ8Mmv3jwL8HZjROE8b3PLb8+nHbUS9/1oKHpYND+vHLaLTFTS+/h2Zpp4YHGP2Hlm0bWP7aro6aheJBtr70/aFI0v+7vXmUaDNn36ltecXqjP0X+sPJZspZeSU8O7tO5zPZ5zPD0hEYLOoLWYB66Sz2B6WjvqvEpiX6jXUzghNDrHCYdcCwSknAAkP69nqb6/ZjyWrxXmykAorF0AEa9E1ybHfBSgoXTtks9cO82YHt2iOJfwN9RexT9p8HUj02I4275U89xQEqeS51rOl/fp//39TliHc/COj/CVIJDj9g1CpdgEe/pI6YdxC3V2h75JtB01+L20f++BE+5jW+vO9mJV6nQiNDG9u03W/Nh4dHxHJe193bSLdCPC3KVh4+Z09OR0QoIJqkU7hXt1L0caZKmFOlawHKJzP4poManWOBIhbolN9L3pikdYFIFMWKxYXoIZMcB8j0mo0NGHzm9xrCgViksO8DQokW3I1EJoDesv+RzB28iNJ5DDFBVzL69Lw94DA3tRh6wJkyKad33sF+hIYz6nWbj9PW3r9dyfGObUJ7Gslg1TZj/Q7pggDIvi2Powtsea0mtbvVQH0NXXh3ilLeXuPBucFypeNFK8/+udX5rO3zUxMTExMTExMTPx7YxLoExMTExMTExM/CUcuqiOJPrygJEYUyLosvfc7iWgC50I/JZ225VahNgChZkEZKtYq9RtjS7BvxaHxqhgJfbvc4HSzgAgoDDxA8MArMiWANM64EPDAjFNKSEnjzqrLabXYJiKswhCmFtPZCTrYmKQosW61FFIX8syMRBr/nLmASkGxNkRhtZQCSWoRyjEOuo0tyMkiqtdObjBrXGgmApWi3E5Nq7HSQdqmVjb6uWE/P4Xu/RT72Jq3sciSRm4cytAP7v84fH8R+qhUsKU2n9cLr1rrfR7iWXBiL5tF7bquOJ1OuH+4r6EM0kD2XmTBfLPDsYJCSxo0DKTd0yXUnP4iKdVUmA/zFChxDui7LLAQEIItMd6Dn7u/unvv0AQnc90afbQwB4CvJHgr2qZ3xmvvpQMayQ00gsuPHR8KL/uff0sbqL/aSfKPPwgLlND12OpAiJP+hPn0ZUi76brGkNe0W4vncDKSeR6gsKd5ldwjQdyTU8un0uGBMCW0Meh4aAr18NRifdoRyqEp9pdZneATRF3qW12b4o+G9KixzL1doud5Skpiqit2HRcuOkdVOYR35ufjc9L7oHqxieT4wRoZx8EVYb7358WYfb1+wT7Wuarf5LNPnD8Hx18p2ys5KLFzRY4QyeVS4WT7HkTd+cuBsssjiLHLe+81Q5pBMbT7BhZXyKCjqXWhEjVT+7v9vt79lB6zeeE8fam7+ue4kJ+YmJiYmJiYmHg+JoE+MTExMTExMfEL4khG1kWmlJbWSXQK6QTSLM7ErXt2BNvRMgyBTDciwa3fo6vX7vVa5tPwnPecM7gm38vl9hZZR2/flzOkwMgPddOec0ZOGVwKmAtWYWNCTkBRd+uyqnv2U0o45QUntyAWda9eovt1ckLKqBqPL2xkM0uB5AUJGou2iCghTtLxLi5iZlZWhiBINmuY1C1vMsk5keA9UbUyTQSknFEKQMJIOUNYLUkJagEvKQEMcFKr9MJN4SJajMvYlUMX+6M/BPib6m39O4zxRu69HdLvCxfcJ7I+vbYeW0UVvdsTSMdvRYWKa0u5rmYAQOmadLTJLg33nmp53u7qfYYgC4F5hRCB77/h6zc2F9Uam1mCq3WC1FjNACph2Ix4JfwXINZycvK/C5ZMqiCzs1l4fkvOYFblFUiLVe4WtSkJMlG1KF6LWpJ/e3DLdO7qcYSLzy/pTxiL7cuG4yP79w2Ar4NCwXs/E6CW5k69NYKGanu/UJsvbrm+DHVnAF+JektsNH8aHbG+h47Yfpxoqlbn3fvb9bZPmrcbTkJTGEci7Y9Uj8repTsJ8Dmhpv/Cgo8s1Qo+mYaBx3TfEObou4GAQUGEun4VJ8DdKliAhdQSnYhQhLFyMQ8GVD1ouEU4iypCoZhLdlN5OJuCFCQP+iiP0+h1Ou4QoPqXD8aujWvUx9sQ2a9EpB9lI+OzIxaZxost8SvdyzKk0wlwOI135muf77CPDSdPVKSMlLO/9ZjHlD6HoTqiaz2ZVwERQRnq9xxI/5+fA12Qu+R5+BOSv+bXhnx/LZGJiYmJiYmJiYlXxyTQJyYmJiYmJiZ+EVwjoBzJc7/oSPTBXaqmCGz7ACFsiHJxgoos7x1LoOdiYwF/7XuAEb84dvN5AVun4TBrPr+uP4zctq42BkWMHVq5gMRINlFHyaUICCuIgIRFyQoueCiMh/OKm0UJ8Ewen1yzXcFIkXYyi3EiZ3AEmRI4Z8AE2khqDV7F7M46mwxf3azreL7TG/iSBCKptkeEcWcu21tvCJK5kicoCa9ZZnPzLmAiMJM6nnbOgBgfWfCvgW/dDFMgy8XI81i8y9e7CANT5nyIH65M8B3gSjvm3EDnPYCckm9BmoaUxBYwSKRabOtcakTW0XTxOOvMBQ9shHBInOBWus2FuwDIlEGpWZ77/rWkhEQJbHVh9pjTeLQer41b7HOPTtR+2VlAo/v296KE75EFeoSneSs9iU5QS3bAXb8/bX6OtZS9RsFCQxyQ5zTcew/gLnraCL+dFPcRb8Q2VZ6t5YWapuqPmCcOISChKZh1RGTNbXvGUPg3WZ7Vut+JezubhVAVrWoaXx8QyIrqrcEVFuK6IGqhKSDDeR7qtMcmH/HLoWvgMdKlHZYYNT7a2pHOcr13Fb9PVD8HV7/+GMkN75sQcKRvVugb33/8wdMb0FPme89aD+338liXK9fgcA6rK/9Hku99R174LvTvt5DJxbodqWE8a2r4mvK+2SgweLLx/lDLF3z/tjX5dEzL84mJiYmJiYmJn4NJoE9MTExMTExM/MLYE5qpIPKCEG60entE+CZmCe2WldUDLBq5hUAQIBDzXT579bwCT3mPRunxUzEQXCpTHeiESpC0v7Vi5mJUANzzivtyVtfTRJDEAAO3RpCDYW6cVRR9922FmGUYmbVgTgRQwh8f3uPbwwMESoSQs/rqBb659K/WUy7xjuJerbDmn6qA+s4eaVZiGgMAEwApSMXSanhT5JTN/3CcQ0rwq8vfgrIy/igJf6UCnFdYN+IfUMH73yQd0RX7PI737u9kxNQPttZyi9IRfazeRpA8V6D9UjH4SNi8tODx9nPX8fXFNnIHsHlJ7pbXvB1A8GDzCoQaB33lFXEvGkdGk48EYGuREna6Hsf4u2vpWeUlm0VyOtmyS0qS2wxQy0wO25G1QUpXj63j9sdoskcwdOQbyyANSQhAIeDr8CKRkt4pFMwIRFK1HtcEf7Dgr8Akx3Xw3vIptkfe/oNw/qvl+16Az97yyCjHdux3y05/9dhYntdm9g8+AvgSrU2dwHWyGoQPqFssvsCVlryabf97B/XUEei3mmcmwh2AZAen16JG5BjrKS2UhidIlHXf9uJrlcm2eq+0WZiTKmIBAJhQwFWhhGDjir6L27UeKC21dGk21R2fGSkflfM8Nwn7diTGq7v50CP+lnCkap+2KmKs7muz2Ey7o++JqswwvEH9j805ddG1yFFhXXCe7WvwMWxhfPZyi+fS4d4d1sGLN/gr0SILWEiYR8ZJ6n8GhM+f58JD7lhVhuz3z/bXIK81BvwLyPfgBWpiYmJiYmJiYuLHYRLoExMTExMTExM/CVcLw0aBaBBc034ye17feDz7+EsEanXcrN+M10KM9/lcMWCTIT9TEGjC7udw6HsxiKPNW6zSYAsHATrXxOxWdKIxyTMSRApYgLuHe7xZbnCTM4iB+7JCWGPYZne9C0JOCaUIcibc398jmVvgUgBx0rAQQNyRFGbG5I0yYt1G21wROyGpMUW3negeBlgShBgpkbJhKZmrYLXGdWt4IGlbwUhMwFJwB+CPAvwzq8veTznhDxH8bb33hQR/ilqZvxfp46CjDeCmfnuD+4O49JfoZvwI/Mp1ezp0UNl+NvKwEWopUbM0l2Zb6/uS90e2Nfk4BtJdGhHV7Q2WN4vvCerNwdPUv81nfFMGSATh9Px45s/ASHDeHUySd0OVvJer1bn084sfIari7U8E/Df+AOFv/E1xHz1gyr/nIgv5fgY1q+eqoGEkuN3/YmfoHwJ8EMIXq2DQG9D7lb8WvBd57at7AAAgAElEQVRSYh7UlD8GIjpWZ9PUwPkSNPZ6ToRse6y7ao8Ka054wvZzSZpOAMgKnP10NrJdayNDseH83py/e+fEEeJBudNmokfJvjYOaUsqjmzxhWoIfBTi/XBOXou9OfnsOXpQfq8/sHlw9DjejwT7ayyhH3HedaFdBHXt0f6SaWkfe/hsItnXVryzT5Zv5q99EL9kZ/9xp8LExMTExMTExMRrYRLoExMTExMTExO/CaIAlQehK7Av/xUa7/dSS7cQdM5KyPgrqnaWqCLGKvmWZ0sCt/V5wrv292eQiIJmbclWiWjxB3PJDhEIM76tD/h2NjftZvr37rSAQEiU1F00KYl+FsFaVqxnwbJkvL25ATNQuKAIg0mt2BkWWzb+iyCgNvK8I76Dr9zeEtffLUZ46HvJTLNSIqSU9S8lvOOExEBJBasQCgF/ZcFXCBYsWm4p+AxBBpBN0PyF9PedqNtt1dHYnzzj3Rg7OP77vRCVQ6SWv52w+3bqT8EBsViftjEjoBfkuwJJtHYdXOFWy86htKfW7unpjhiosSbxut+LlGSRSiASEW6XpXKIpQCFV6jlr8VuthjlhYt5fOjUTWq5stMj1SNE91zTJBBKYRQptY8TCEV07ZdhHhMErMbnYPCG2Bvrc2kTFQHeyNbNsdfzG433t3DSPK4d7/VsOb0VJdHfic5tJ9S/EOEP2fEiQXrPa/anAA9//Y1PkJ6Rq9099K89f2+EfbQo99jm70X3jhHvQyO/0P71XSDAInnu6yiZgpHWS5RWZuCO3JU7Vb7a822tJXylZrXeLNKrY49wah6vJULjeTMRlpTVk4nnmVq9G4Hu/3oGCUJAYenK9Z6WYUYL2hiMM3cPPFia7yoIuOKWkfNEAB/4/u4s0r22m0Dqj1TriJAeHrwaSXmUUTiXAIRwIyMR+3j2NPxqvdzvU3vnzW7VfnHr5Kr0RPrts9eKTpeC9j0dvQjB+txudH/addgAZOf6GZjk+cTExMTExMTE74lJoE9MTExMTExM/CTsCQd3rbbUbGekvbfJPI8oyB3llEYG9ByWNBLOyQJpsVTrPVIheZEQw5TQueKM1zW/gbfSZu/QSQSQDHV/DE+USI5un2MdNzRVYJuqYFsaCVGpc2pUSX0movGSjZBya++Hh6LEeS5KolMGi2BZFhCAU0p4e3uDh4fVLAStZPZhYrCxE5QS8pIB0njkPpWcKHLyvLnGpg1XEfEewFdL/95I/yzqptm9uTMBXxKBhbBKPzw0/PUJkqDvxfjBH60if9GWHHR0Vb0gRP9ojzdxkV8FhyzK9yhst3S35kxOrEHHuGgUenXlHKZLEd4hhH9F6NrpY0u3GOMpKbWtocoF6yoQYaSU7LmvSfOWYXQoLBa5G4jv0DSHNXH4/pZTqv3fYpwzeKdr266g1sSPxRC+Bm+E6n4q0P3x/glj6gR1pD8Ftieh8bAJSp77CfNGGon+iY5XAOy9SzUaaMXqQl+MLI9Eu5Ppe+R5xJeddB+kjRvZ3vIBbj3e5llUzPFWfyEBidQ9/gNrH9QTY9dvtJPAaIdDeLLZE62NgK7lnJQwzzljyYsqPvm+SgRKpgyVUp3zQkrUsymKcJHanz6DZaxIhODF87JrSjjU3aKcksBM4Xffqd84T92e9ubET+GM95QQ9u703xtH+gDjPNmqA2wb+ZrN9v0teg0Yv01HMvt1iG3qGxJjBwGNuB49FFSPD0+DdEuYNsqcfU83/05tTfVlPvbtu3f9UrzEffuPDoczMTExMTExMfHvBPrv//nf82tqYmJiYmJiYuI3AgEmZY3Suvhw61CWBJ3lTX8t/ftDtlFsxxDwWlBKeVp9Q34e89QFmFUYGuoeX4yRQSkQPd8bTaDt5DggqfWb1yvZ70SEjGapSqBKRDsxon+14SkBCQk36QQhYMkLlqzxx52vYVZX7gIBs0VctmcuW2ZmrKXo88I1XjTMGj2l3Ll0VwvH1AzWBHjLFsMXUBfspOShvpOQaEFCQrEyzuuK2/WMshb8Swq4FJRg+UtEeCdKuAvcKljJ9A+icdI/kd57z+p6+LONK7P01pzaCR0p9T3hbu+jG25vEyhYBF4p0I68gBLh7TesL0JqKMGm/V77IKRwF89OMHs1isXnTlZaTql7r/NUEOtG/XbC4r3vyiD9e0teQE5ei6AU9YzAgWbYp33GfhkoJEKte7cHWDInEbMrE5EYUe4xzWlDMkS3697ErSV6I773r61fWq4Y4xB36bw+I3XsJNTw2lifSHbcQpWZ4hw4sjz/EAa7AMixbPRzqH/T3rFy0/C07re96Sa+mjLHW3uc0daOIFqW62z4KIIUyvGcPwcr5pS2fRq5H7dQr/XbiT9NNo8oJVAifBTdLBdTQlltDatigo0l6x5ForUnmCv8xsjXmObeHb4eEmBEtnTuqf2cji2ilJBTqnt9TgkpZRsrqvscCKCckPOCZclYlgUgQoHgfF5xf77Hw8MZ9w8P6r1kXS2efVPw8ljpcRR8Hx46DUDbK7Zcm3R/d7m4ZxJ0LHqudcVcCd0Dtmu+Yp+RHqcxxm1o8/4mI9q9u3ntwv2a22DRvn1x/8keyX2cxfbZUZzva9IeEbKPxQ739ZBSQt4pQ+J3aL1XC/QM1YPEzj5xFWxhylCv7lvZi9whxP277vhbev9a2/I6361PIdLbypVeAeJVajIxMTExMTEx8Z+BaYE+MTExMTExMfGbwQ1zqqhvh60aBWQboXF3Te39Id0oqktQ4SMlwih3vuaaRHrr6r32dBWIbMnr4DnWS16FSjQ6iW351VjK3WBIR8BIUQvWTBpTmZkAYpxlBUmGyBkrr0ZuJ5AIcs6VLAeUPKWsxLuYEJmZlVwpBKICFCNxjDzPKdUMUiJkShAyskpUNr0Y/SkseM+Cr1DiWseKgexWo+pO/p0wVhH8DcY7Vq8En4f+uquMdyMIiJQAEwQ3zUZovbdB/lT71buOOuHzaJT2O0Fs/idTZEgpgdwi1+aOrw63OG8kuhIMlTxw8lvEXOLa+KApqvSz0fJ3orR6KhhIvjqXtZ5OCKc6hyxVJRiVMTgXJ449n6dSBkrCE4KKTHBhzqyKIaVuLM1i2BofXNtTR5q3tiH0MjbPxz4AEGKr973k6S61slrU20LmC9Ha3wjhm7Eu98bAvpH4fEuiaz11Hblqk4+9q0P0Nd+p5/B3rKPHVt/wjEShX7f5uSXn3xB8FN8vgRUqjFA37IQ7OtibzQTfLer7o6utBX9+p1o/tRwnvT4R8AeAxTZyDrGyCcBixNoXG9U0LIzaHqk8XPO24mR6amWnoABT86gEeka2vTm5NgrZuSyhPF9j/q8pKbEIChesRcN8+Ew/5L6HcZHN88gUHmUiB8+fCRqI2KOJ91p4Jue68zU1ZCjDU+qeXsptfPbcah7FnX+MGH9O3o9ZM8dnG6t2oCprPRrffLiU9oFYFQuf2pZLfX50vfvs0W/px64fnxc/Cr/pp9PExMTExMTExE/DJNAnJiYmJiYmJiaehGhlHLEhVnauoxC1ETZ7pEksry/bH18igl4TLjglbAWkx+U3wXHNhxhuT0pMYCKIFICUHCQhJFHLb4aAGDgljfVMFo8cwmBSl+/MDKSExZhwFTBrjN+cElJWC0ct3JkfQk5uSaXvfRGzBiTBOxK8FcEX2NgIgaWASUnM90Wtkt1i/LMRT2Ixc0HqVv1v9V+PP4zkzPgABnCv0ZKry/UvlRAmS9f32TvtLdwZkfZc8jxarz4Gt1p2JKJdofq182yU9XsYBM8swS1WKZDahGyWrA+lgACc8gKBYDWieslK3t6va62Pj2lbm0atOdEsGp377e0tvtx/1XfKvuVvfdHyWVlX6smiZztZUozYVstf4PbmBBa9z8xGbPu+0StChF7a/HZX4/G2QNSttfWRVlGMZDFFBG571Jaooa6/YyU8Lq9a3EuYZ1uirN2RzXzsXFRTs6r3Z9msfSMhy6F37mmMfa73vxFwCyOAx76BEtxvoGEX2pvbGMq1T6pVp7U/tM2VMO4ILayGKAGejHCWTHU/T1BCvKDFB39vc+6LsczvWQnnv7Ndi77zxWqVDlaUu7An9Ot3nD5fjWz2f/4QnQufUqM03bvGRwCfrFyCgBJhySoaWaDhNzz0BpmikUMVSKQ7E2J89UxKlGusdVQivobVgO2/df7avC2i3jacJTSL+MIMlAKQeucopYCZUYTNgptRwG3f8rV+sKarVwZLKLUnaZOuu30tu3spTeTj4+8L7+2eu4+9cy3vPTT/SMGu7494yu8To3yQPrz4+K0XEN6/KnSYBYymGHYJNIzLcxUBXoU4/vcbkomJiYmJiYmJiQuYBPrExMTExMTExO+O1xbqXRJKuxvNKwWZMZWQgI2geCr2jOWeiuqu+qnlPkr2Ufjl//V7zrpHsk2Jbg8TKwIks0onAGktztJU0oQyITGQST/fMynR1zgIAlICMZAyK02YNXZuymTuto3kDCRtJS5I3cWLCD6J4J0Ab1jJpju41bSAGWr5yDvUZOjbv6nFR7bmQwAUo91j7ONIJNa8wu87auTJB2Bj6X4tPtP1JDrw4/gLnRduy6yxhMmUHVJKuF0Wq4/OiebqulmHez76wzqXwjwkIy5EiXi3evVxEVYr9urin5xoo8pg1nE0RQmyjCl4lKjzGRaPvCofmGW59K7QYS3yvylcusU7Bxfyej91nJSAVDFFrH+c4BR0c7RO9WCRmUjJ7JwyRAo0jnMBECzYvfyO0t4j59GnG4gzrsym1P6IeW1dy7eyvlGzQr8UHxxoygd77Y8W6b57ebpi11/D1gAA74WQRTQEBRG4ZkBV4cXnhoTrO2rr2r1NOGo7Wgjv3c35fdwXHmuznUl1njD6ERNd/1Ex46NoPTIlnNJiexjXeOjw+NAhj9R+1v+kRNBQF6oEk4xA99894do3lzUOhymC+NoiVQRZV6jCjXYSi2AtKwqzKXqY9XlHnmvdqfMjPcxX6WeH7LDTWwUStAV+hIMx3IUrKQxFPJa+K+NaMv+Z3xrH2T/nYDjI8dp2XMA1bteveffonb3717qQj6FD9HqvAP+zXSf2cvf32Z+AYxUvddHe8+eO16sw+BMTExMTExMTEz8ak0CfmJiYmJiYmJh4ElJKSoI/g2EkASilXvj6DJPikRy6Fj2VYXW6VBb1f6OIt5K/4d8osx8JrJgmXhU2wlAIhQBw6Yj3JIScMzLO1v8JGaIEoAiKshFQvlNdf1e3v06IkpF2lZwngKWSmgIxS0bGJyNkPGa7CFBAeCeCvyAQYrxhJV4+WRkfGCimHPCZGkHWxkrJczGdgo9iFqhVNk6NlNoMkpJKd9RitTsh9N4IuCNiPJLm15LnQJiWpMRVdZN+4Mo2PXk9xHwaSasx7E3hoDBEssayd6bR6vP14b4r12Omt/o7cWE5EyElYOUzzt/OGiPdOtyJx0QEZgbbuBMBN/kEJ5RbTHSvr/eLhhaAwN6PMVdtPnqMaGMfl3wCEeG8rhraIKfqCpuM1CzCkMQ4LSeUwl27ai8mgCQhZyPQrT/WUrp6sHCN2w60GPFi5aWUwcxYcgaBsHIBgXBa2jgRkVoEDwS9sLQ48F39BKVapPv4+eqvtGwHgXQu2m/tr5Po72y9fiWxEfCxALI0d+qRlwaahbnHRpc6/1Dbl6Ek+jsBMqqvjFpLIVTynOzlf1Ijov9kwWrPv9T9a9PAfRyQiYtomY+tLp2rfWzkvzNqBQTAB1P6+SsBf9gm9NmVHJKea5SoEs9kayNadoO0x2O/AYIlZSXNrZbJlJeWlJuyGdk8ASBcIKzW4/6vW7xXrQY2Ml6yzWkCQ1DWFeeyqlcQwJRUBuJxp7MKj6ED2vhLbWAg2uvkln0iOh5+CL/37j+GSIwf1L2vz86zWL+9A14Cgeu3H5lQPgTdvSOC2P7yuC8dkdH1r03qH6Cpdc232kvI8z0cuZSvz/H4kLXvl1qRi2VOTExMTExMTExMvDYmgT4xMTExMTExMfEk1NjNzxBoiggScxX4i5F3ewLZa4S0Twc9WRBLaKTvYNQ3WHLS5r361wXlHuu2S6mWvhq/WUJh+gykpKRArcSTkT0lJVDoR3WBrvFxkxHqAv3twnomzcRdWCupqHHN1eW2/nbrQPIWCANC+MvKYhGsIngDwXs2ks3aKML4II3E835g+/eLXScAJyjBDahl+RFPE+fayLN9Dj6q9yzMP0M2959iiQ4Ecv/g2WuBpVlquzU4u0txdwltf4daVPLZ0dXXLVuJqktpMWUH7800uGfwMABKsKmTceaeICZ7p3nvp0okuet7ZpuLQwd625xoEWaIEfkZBCa1vC0rQ+SMnLOmTb5WWj6uVBDJQwGCVe8W2RRJiimRiOi6EvO8oOtClJi1ejFLG49Ne/bn70uRRF2zC6E6F9iLgQ609SYwl+ZoFtyxXnuvU/j3BIDhxKy9aeNJAiDp7wSdA+pRQvCvBHw0ktjL/Wyktq/zsY+caCdQcyNPjaB2UvoTbd3Re0uIgJw0BnkkhD9wezdDy/hTdL9Sjwua50IZOaemDBKZ/6gEIFK9M7SJZgR6No8Poh4ick7IlJDyEjhxAZeCImju1y2OOdzjQxgsXdOmOGI9V0rRvdrWZKQi9zlms0i39zdqG0KoFuzo29oN2GZiW45hLT5SiX08dsYfsavbajz+3mb+ew88nvGl4g/0PQ7x2vTvtYT3NTHQr8lrTPN9vs9COYFAr7fQFIaenC9sTCcPPzExMTExMTEx8QRMAn1iYmJiYmJiYuJJIGOSj2KFPv4ylAE2liOShVW0LxsRv5Jz30dee1kcS8dWfXtCdNr59ditasFWr3tRP5nrZF5Xs5Q1cjPnxhEEC8IiMNfBBBGNn55SUsLQ3XRXQlCtH4vH1A2uhDsBOVOtoNGHEAE+kwC5WTEyBO+48S0CmDWzphUQ3nFrpbf5K2HDwfwpwBnA3diFLlRvvF7F3UCyOVE+3r+z8v4hwD8vzAC3QK3ltor01xewTSe7D6rigilECAmECYSiiitZiYT3t7cQAb6eH4zwM2JcoFbZtVyNi+4EeE5qKl5dqpvlayEnvtXJNYtASsHNcmrW6Qk4r+d+ftifJWecS0FOqXFuwQr9tGScLV47ANyv50E5opGHTGpNfZMWrIsShQ/rueuu03ICILg/n7v+cwL/Zsm4PS1mMa9KKF6OACilWHrgbEojes34+P6DWrxbQzjsSYmMpIX05BSRKqeYsovHmHY3+1uS6nGK7o1p6zit+hVKpBPUKp2EzArd6w186YhR/eOKIuN4dQoIUKvzBPXwsEL7X6iy0cHTAaGEfP90gllQlQ8+kXqGiEoq/rt1w3b9RC7W//5do1nsE4P+jJDgGk5G9eMLadz2/8XAv7KOEYGQSBUoEilpv2R1uZ5TYO73hqXO574vM+WqwJJyDIWglF8l5uva1rXFToazW5PXxln+BKxSi3alDg5eKzxefb/nxsjmtn9tqfM6j6sCV9fBfVP3+qKR7QdpnoLDci7cH/us03ho912JoSnvKXgYb0JUlgqKMuF57JrqAWLwTHJ4LtBmIXw3vLbl+WuX3aWPX062n7qiX5ef9N9ITyxkYmJiYmJiYmJi4kmYBPrExMTExMTExG+Ip1o/vTZG75pPeHMj+lRC3lok9UZnhrhDqT9daO8S9BcIhiORbpTI5q9f1aJcPp8I4EbjSpfpQJwTOnJCyCx1RcBMyAlAKa2PQj8xjERP7m4aoJTUNXUVTFO1/HcCXUpBEanxeCN4x4K4awcZMSHAl9RI536eap/ckeb1UdqQvDNqw8mgL6SupL+SEoXPneyfRzJlwL/C+PwqcIJv13Uu2lIBlJz1VCyMhKSEGIdpHomfOiHNJbuRexYS3cpoBJCWxzVWeEe+Qcc5B+v8U84opYQ455aTCAozck5gdlvaRjzpuupjsCdze51Tqu6nW+2Bwjb/D8awMOPrwwNulhMAWCzqUH9JSjTa3E5J529Cwt23O1PsAdxC1ztSlUcagerTsxF0jTwXU1QYjPv7gdnB2+CKPSKJrotvELx5ZQLuLngweC9AISALIEQQMmWWRPgger+6S2cl3pmort+KHWvYIwKdYEougycFf+reEuKzmFeiRm0KWbxzMZvVTMheNiUNiUAetgBIpG77vfIfRQn/zquDb/4y1twUlupdqpNU99dGYDMXlML6LzPWwihcwDD3/2PLpYUt8PVaH6GtQZ9z3G13EtI14n8zr3xTeXSDH/Cr7ZsCVI2qRz6Oxj3sKM34CwhE7oX3R08gdvPCW6+DPYvxI4v0p+YTry+5Z3/U6p363/W7yQlz/0YZ7ncaHfLC/nzm6y+Z8pO7n5iYmJiYmJj4PTEJ9ImJiYmJiYmJ3xQ/RX4drLmqYdZThcN7Am5S6zwh6N+BTK+iUwkU/DMJ/OdiU+UgUE923cVYj8yQtYVyEEy79Z/zNu6fORQkfs0ENnoqqYkhSmqsJ5lVolTLfoCZALeyNJLcSSMyU3ZPH2PxukWeE4KAuuUu4mRgpMS9ntQRGGTEvqDJumt3iBJyapHeaJ73ov0oUALPrcRHQ8P/1967NUluI9uay8EoSd0tqfeecx5m/v+PGxubPfvYUaukqsogfB7cHXCAZFyzKrNa62tTRvAGgACIqObyS+ub1I5/aM+l/p8KfEHf/iV16W+pkNaeI6F62p4b0SIl+PXb8NL30SQuiZzLq5drHfHDYv/XbSkWJv/zy7m1PfJ5A96/rqBnQbrncnavWA933W8sROo+YALg5bxCseLHDycIpIU+L6U0cXCtqwnjg7dw5Am33ow0BDHGp2VBVcVpOaFI8oSvLiUuVspSxFIXSA7dLs3LdvF5XJLne3su0oDV5GUOaadYf4YoLmIe+ilUfATKHox5/I+J54Ja13Zn6mNWJeTko/D/RzPbjoR3uXmb2/4/XBj+WU2s/jsEUvt6WGEe5Ln0/D0bIUR5OTO2ACgCfPR19x8KfFCrf5GCP9Ja/Es87l0vxr+SxvV7Ge9rjjTQwzLHp604BZMAOQuS2eAi7Su+Nv1DFb9D8IcAWIBf1NMCFLEc57AUJL9KwccCN1YpaGHbJXnLR/ukr3v5mWrVR1+oAughOFQEigqBtJznqhV1PWM9ryaou4CuBaia+qgZLaXnqK2pewJleOwGMQ+SkJ4mRcjxNU+UzLw/je0wdd9SSJcQWYef2fuKCM/x2DF5kG9+H9K/gezz/Umjz3iPP3rtraHjD/szied9vz93+ZJXmm+PFPPodH9/M4QQQgghhNwKBXRCCCGEEHI/g3pwx+vB/AZ/57r2EtwPt1yz8Wa8VHOvfpSuCj9RxCggZyG9+U3JdKzdy9SW3BjR/W0FUNTkec/BO96DeW7X8CJ0j2ARQGrFKoLq32uIqqVYQnW4kOL5z83TMWUudyFN/fvc85uRaPfURYg9x8a9IWhjr5Gv+EI9Ex+nAn+A5Vr/GTIISL9qF9H/7iL9eyTPhBBsz2tFKRZ23zyauyf0Wit+ONn/tTuvq4sUo1CZZ24IwuZNiCTWwTyLQ0QSwSqKImgGGCG8xzO6VhMMixuHtHQCAhcsvRz3PC8+JhFSvWqFap8zSylYltImg3nqriZow404ICb8pnZq1eT53qVi1b63iTQIIbQTgnz2gFQRe05E+vPVOrU/92U5YV3X5iWc27aZvXcKVJ8A/A0Wvh3oec6bwUYqbkFOBbG1VSp+frQ88pLbFFBPpeDj2Kwh7P61Av9HNeOXZoAg5qkuftqvEPxmFjQAgF8gzZP7Z7XoFFZzX1/ETy8unrc86L3DmlDavNBnUQ02b0QKPkFxghka2AwQ/F6AE1xA9zXwz1LwTy/zY1qf+yyLn53cEmnzpgzjqJvhHtMcmDjfUmasa/uubjhm5hZhrOFlRtku7ocvezy7TVBHnmXpWxjNzL8/7bnp93sROfge228hok/teL4J8+/v0wV+M76253n+ru13Q286f6/e3TYm8bznQbf/hvD48vyE+9bTdc/e5DuaXoQQQgghf2kooBNCCCGEkLt4NjfmhYK7MJDq6l6ngIaAA9ydE72FLZ/3T9u3Fpt17D0Pz/kT870gaWwuELVyspjuH8XFpj3XQJGe07oJLWrikYmcCtUV5n0pKFoGIS880SPHLqBJIJLNPe7SPLL7NXHlUXTg3Pd/THXM9gRx7B9TWbN4/r9St/0hlk/77wp8APC/pXurh3iej93D/ByE536Zn4/88h/3vziP2121oq5oYfmLlHhk+nkKfFhOO0YWQHVX0yHlr0aodIG6QB4e5uZdrs27fa0Va26XWsjon04nLD+ccF7NV3tZSptHH04fIBCc1xd8WJYhjHp4bnexpKDWii/nM3AGTqcFp2XBua4oi4WmX2RBPFWaw7qH4UgKmd2MOFbrjNBnRKzvsqAYYe+hwA8fTlikNIOA6kKya6D4/PIFquZBr254UCP9gZeWhZKtYKLD/u028Gla3P6MwYLgb9pk1OG6otrE6Ir+XAwiOfr4L6nGEgdLmONYiz8izfOiVlYTkG33KcoXC5n+T4W3wwx3/gnBosDq1/3i69xHLyDWtUWsHREMvdlxzAYPYh74xcX5X/ycIqWVaX3YjSA+iEcJEVv3LHS74JP3a1GLohDVCWKdLqgKlBJreBL/DwiDlJYjXNWMO7RCq5rH+bna/FWL+LF6MJEeAj97n8dzO84v85qHh38fWpDO7wZE437f3MTcx/EP4jyRj34Irh2/lWkdjcgVkyx8OBrXbmven406bmnPe+SSWP3ItXv7rwn01+qLf4dduv7Wsm5m598R3xoK54QQQggh3ycU0AkhhBBCvjPe6gVgZuM5dNfFim0Oy1D1Lr8ALqpNiLn3ReThi987y4lrchtK2sr726dIC2Ht2jb86/gpIXR1K4GQXUcZO9HezEao7i8Pq14AACAASURBVC6OAuGFaAKOSA8ynwVqqzP+F/uS4OtiTRs2RXKQ191mzV5r8zkmfE79nzpkiGg/eIF2Psrl8Ytr/4DiFzUP9AoTFSNM83v1Qt8jxkkwhSSHQNbaRL++X5vgma9v1yAEf8uDLtLFb/VoB0tZ0L3d1Y0x+jxvAm6xPSGKFyyoteLHH39qdYe+GSLecvqAl/MXQIHT8gGlCKTYfVWt+PxlHYRTeHuAyIEeDdjLGR5SpB3REHaLWL54F0PDC1/gnsBabd+qHjYe3h9oIeeXskC1tr7q2QtMhQ4jlNdF0l9svivMWATo4vnf0/M190+Fi8pJ2fkFwO/J+3P2vo5yxdepn7Wfs0KhxT3KFailR+Ko3s+/ShfNf0WfDx/FPM8jDLtA8LMbU/3u4x4Zzn+FRNx1/AeA34q14XRacJKC/6xWzn8vaAI60L3vez+mHknh0rtVhoSi7ykEABVFFfUQ/dJKaf+5hYZ4mdXFc0j11AqxDqZnULQ9sip93WtBGYbfrS5+N4MIjHOtzff81Hvh2gpGt6ToXbLP/GN2jUenfV6khi/jL9+bCJHvUDx/VMC+VtY9nuS37p+/31vWHL3nkXvU+AcHnluZH54Jm/lNCCGEEEK+ByigE0IIIYSQ29lRrptn7Y0vNXffHx6+UO3VQtFDkN9U005hO/Xc+z5zFs/n7fHMsZ46CB3juT2Mrx/XLpGMpe0I1smVPcStoZZ2SXiZV/NgbuLELMNMoaLFc1AjC7Dz7YYwE6HhU9tqkm2zCD+cl0R1twTIdhZx7uxxvmlGuvPc0n9dmzSt/Y+94Z49z3MueeD+HOmDUKTahUB12a6Jiva9qp1XYZEGVCJnvYf99x4UMbUu9HfL3w1XRdc2CPFcfzlnv3NgcVV0WUpr54uHpI5rSilYXJk9v3xuN1S1z5/iRiXN413PAIAPS4GItLDt59Xm008/fBjaYcYgNnNFzBs+jEXGEewe1V6RfUhOtQCI1xuRIHo0Bvg9SfOsBmqax4rTaYmvWLUC6wqF70OdBKBRSdnMtkOhxXZ8jAbX8bSf0+5/pGcrj95H6cfCNzmMdgBgSauMQMY2pAUvdv8uGK5QUQ/H78st+prbPU9T+SKhUQPaEmBAAPzRPN0Fv6jlVBcIPhbBL3E9gP+QAikFX05m2BAGMT/6GWFUIHkNBEzYdjG7GTxo5LWfxkDQDDBiHW/Pu/+ulGbo0XOki1pUhlW13Vfu09ZHALTEWKQw7v7c5rgNcQdh1KJVMUdTGNqOuLWKeUqFIczukjevl/M5jwqCefwvHD8i7uKax/i2+TH6sl+N7ygiw3P/PXCvIP3stbd4uj/rqf6q+DOtYWH4RDmEEEIIIeSvBQV0QgghhJDvle/wZd4cTrbTRZdhr0wvu7OAnl/g5+sOt1+vw7pgHlJU2ha0G8m5ZU20cXE5tNok2mreblf0r+bpOsvC+bzLwpxIMQ/PIhb+d/Iu3VwVYpGMQo9doKE39RGt6vc9SiOWM3lH9L/0LjvEZ0UTtBSHWslc7FzMw7wbGWXy5q/Qlkt8spiIs5o4WJqgGcJTyhSepo5EUuvmjQvUMKNI5Vf3TI+Q8IAOodmj4Aq0/Wt1r+52O4JzhMzGmFYhnu9umOP1+rMTXr5bUXpSDHeODWf48xT54sPQIEKIz8tFUau3VjNQqK4+rrVirRU/fvhgHvsowIJuUKAmrq4bk44bGE5Pz/fOMvr73qnpnL8D+Ll2w5K4NGJShJje1y7jZ3+eP05N2xNA0+UIKbyvCHFFFspdUG+GCeYFn+JkuAGPe7DDPNJ/h30XCFAEHxfgh1JQ3JDBirQSFtEWVl2gHl3dekCHzOMC+ByIJ8W8ti3yiRlq2LGC0nLAQytOZQGkAMWFdBfRixZUCVOks0U3UIFoAUr1uabdtqutkwrpLvPjgPqcGgZ3nv/JWACart772VU3GjlaW+/df3Te9gepLUCXnuSZPPWvnTteN0auObruuxDP27TYF6fn7+N14/7ox0NB+8hgcXjOe1t606TVN1zvxibt5AvdPXue9wF89N9yO+W9EV9jlt367BBCCCGEkNuhgE4IIYQQQr4tN7ygnr2U8kvZ/Do2v0s91Mlf+SVpewHf3ASN6u+Lq475WqVI81qsmkwIpna11LSq7WV0nCwu+qhW9ETn0g/mXtnobMljr3j+XwiA4tdmQSa/grW31er/Ffc4Rq1+iYv+caMRj1myQYG3vQgkPGabh3rccOuBV3nDe62IQwHllYWT2SN9NnN4lDCymPyqW0j90OCGZ8gtHUI2HO80+t3GvkSpAhQt7Zy4NgTvc13NIAOCVVeUUtyrfBQgIea9/XI+j/MFNs2XskBrbZ6ldW1X9/bDPbvn5jpVteWG30ZImJ6PMDqA+DPldxbPWuvZ8OC3XPNVAEne1UUEpYiJp97OljdeCoqHil/XaHcdBwzj5qbV40KzmT+9D+bnCPhHSoqd1wXJ/TNpWBE+/Rd0Ad31VRSYsA2gh3x3Ft9effFdvHubp68bHgyiOYBFRwG9eF3/ki7E/4xQloFfpOBj6WvqR09HoVpRFFgWwbKUdn/Fc9fDPa9VfXx0beOugO/rvdtyjvuMt+dJUk52oGIFNFZ5RQnjJCmQIv4sFF+vBSpJiI/yqwCoUFEPDw8oqn0OD7ek/7xNO7O8H9+bUQezTL1ciTHbyJ3p1GmezVrkNeumK4erdnOzeW2L9cx+tTxChIyhwK9FwnlDrfSrk0f9KYOHW/7tJD5HNgL6vD3+261dG+Mm+adfxxMv/FPg33kcCSGEEELI+4MCOiGEEELI98qbuZMcBvG+5dLLoUHTeflLD7sqkCV5u+pWNpi9cCSVonVPjOrhy0WnbYwvbMXlNXGhJa4XF9dyTmW7QF1AcgG9iczTbaILZjodaYIoAEjpx0J58qPaXlwPr9MBVOSwwr5nEMK0lVfiqH2X3q7VPYZ7+6WLeHV8AW4tk+5kGIK7KuoU0lpa23omefPc7aJm3OVgZHCBYY41904roOk/qRvn8jalP/HWfhPC9sbrrt3jTHWxr4eKNiWzCUvoItRYtDRxNR4WrRqRzpugXlxmVUTO7yS0qnmbi5jXuoiYgFlM6gvDkXaZD4mEFFjs+Vl9HmnVJqKVEBzDy30IV32o5w1C4JD2IS8YyVCletmK7qtqOaOr7UnzRfysutocL6W056tWF/Olnw81QbdqUrb32BnyWfocRMXNpfb3o/Tj/2gdNM3DEKrTymnPmIWn/5fEemFn/JJCxsc6IyjNICeGR4Y1uZcRntlxD8Wfy0XSvIDZ4fwC9fXAQraLj5W4KD5ExHCF/1xX1LM/NwJEqoII+m1fFbVWVK3NKz3E9E3eev8tgJhoW7C0sS9tAvsMluI50f1S0839d8Jl31JRlgLVExQVxZ5YP1nb89p6PNbAbsoAoHZxUeP5yW0VN7bKv3uxiOe5N86FHInikCvLUf+lvm+x1PTfsH/6Id8cB4aeyc/D3rOytz3sfIBb1uhrIctj7h/+SqR/MuhOY3PKAU3P67bs6e61H+97baPkH4S8cLbnUPrcm0oWzO2Z77cb3g1jlrpy30CktzlPjfvGfCr1vp9Y4KhdN5DnadR9S9tzfYfb0svbP/+Jf7MTQgghhPzFoYBOCCGEEPKd8cT73tehv7Efd9+QC12uHN+vK30Rk/Jaef5Od/ZYw862QoG6orYXuNqERvXPuCaX11/whkdq96YcmieAiIXMrkmYM10jwm3vv7NtXSo6NzoJVqUpI/2F+N6r5N458Tq8SWXiPaHeH60xXpZUQJapPAsZfhxuHe2letulYyhkFcuPHOFxu3gt7kkY+acjh7JCsba83iqRP9vvOHlyjre87QM0IRAtPzNUsTcNbxJE2rnWnpKGOh+P9jwqoN/anuxRbBJbv6YLES6/aAoxPbUbGvXZ8QXi92YetacIx67VQ7KPAmz4kC+LtGcBojhXb1GJJ0ZauxU9h3ObG/Gc2OVd9vPQ6cM9+72FQUvbI3aOmwtgKaV5h5+kWF5snea0b5RhHns7c9nqURxcTAVgXuZ+yqks+HAqzSO+Fje2UcEiCyK8fVSQc5D3OxrvDkBb9eJYtsWZ5dEs1PyRxnlYMdr64OPnYu0/XJj9B9wr3S/Ooa0/CvCrz4+PpbjxRPYy7+0U9LzrITwLgD99Hv6cbkoFWArwZ4jxHitDin9v49rbH/Wc6wrUtR13mRuqq9+0GwjEeFak8dfBuGGMLiKWMkErSvFnQoobANhxtZ22RlULDV+lG1jZb8cCSxPQ0wZE+Rrh/iXN7EFBnjJ4N/uM5o/dGt4Fxugfd9tHMr5Ka3vvL01rQCKa0ebbwQqmva259zY/HOny9vsAQIq035J22lTVUNK87opszpmfq73rX4OjdXoTSSevLfHvkNycFtp8+s3Y/JtD+79bgCn1y1iEpu02rTWtEQpfy4BmdCU+zrJtk619MrTxUlemqdO+97V+PC/K2vTL5vh+nJFbtx8e+oN/+9586Y3H7t7W8V+CfQ14tLWEEEIIISSggE4IIYQQQr5b7n3RGELK8Kp97+VzLiO550kWnebLkoCZvbubF/bOS99NO3dOGDzQN627Z3v06N7U0/7OtcnBFanR2nNUt+vihbvnmbawrebBXIr78Yt55kqJvi1d2KwLZAmxUdGCM4uJmOGlnlqxvXvVQbSYX8bn/eNd3/bi+VrPvC3hJ23/y7mZo9+BcVZahIYQwLv3eZZ9TqXgtBSsSdCuYU2AECi9LAE0PICnST5HE9jry3lMsHeOavNMzvc+n1nVhPRVazPMAHqe9uIKU/P5FfRoEnOEAhf8c3/G2rBqxbr27RCbstGKqBuEiEBRh9ZmaXW+o73tEEnmO55F7N74aXva+F0UpXTDj5+bwGYL2b+kzwiBCeBLlFvNs/vPUD9F8DMEfxbBLypYPMx/EcGPHhq/uCXAWSt+w9rWUSvS+8bCA7ggHuPTQ+0DGOeA9P2KOlgXRMj+EBHbZ7f4GTxnY+0SF82XZbFnqRTrFxEUWYYBqVBI7YK01oqqilpXVPeCX2FRHqI5Mg/gPDjat4eoGbMqPDxn+foj2fDKKjarnFfUx+unxK9vL7h1/dHkP6pr52f4WyIe4SM+b7vIP6fTL/XbxX/XDP9+kfZxeE6aaJL3JaE8i+cyH4dcbs+V7Xmtuva7+9rb74nXvLe9fiWEEEIIIc9DAZ0QQgghhLwqd4XXfo36rh1Pnq3xzVvS24SuLxyF8+7vj2XasW3PIJXr4anXuSqe31rMpV6axfLBvADXethEKB37OQuUYuG8LT+wxTZunqUuPhQP16xubSCiKIuJlAWWf3ptEQPM/bKqe6t7XdciHwziokhr93hiD39+dNdt/1SdTCc0B9X901+NW8QqcUEzIigUKR5OesWnLy+tfwq6iPz3Dz9iEfHQ/doE8Z//9hP+98c/m2d5rdUFFzFPYTGP3eqZAFTXJvJmQjBr4iykhaDvXujZI/d4Hlddx7K1X2952e0z/HMXtw6Y54XdZypj6uFx/eiGA63/pIuqYeARwutp6T7kVRXrurpXfBg6GBEv4roQMotgtqe29nSBdVhD2vo1ld92jzPq1//5f0IE+P2//h+ICn5t7fQx888/pfdHUZintRZ8KhbN4JNHMRApWBbLEV6KYHUB/Us9Q9YKmUbZHu8QvX0EsvdtrDPL0tcATfeVjWzCVTMfi4kopR/bGOb4gRLrWEFZFixi0RliDQJgucJVPbd6tXQELpyrVgshDwU0Yjb0HOmhW3aklSti6908LyOqSI9REC2WoX9in0ZYeOlzxNbCEE1xTBZms6c4oixJ39LviMjU7aPRiwLmgT7cWT/Xijho2Fsq6BhF9FvZe6aH36eD48P+wTBMtrun8YkxUPcyH36bkkC+63keovpRW+7kexK5vyfYj4QQQgghrw8FdEIIIYQQ8pcgRL62PQnmJi7YgdE7rr+IDsnoXu7NZ71bBoYArndffdSEEFdnQ4EmgAiw7N1zLm+JXMKwcMQSIrr1WYSIDbEwdCyBYBGTDEUEkkO8J52oeMNMky2huMByzNvJEeIdLlz2+9nJf73thX5A+57Y+xYvprMY+Bze30k4FReuv5zHqAEVig9SoBDLKQ3BaVkw+rcJfv3HT/j46QWfX17adRHSunu9j4F2owRJ26GJKsxoYrzdJySamG8CTz/QxzbJRH5eFoa2nV2bgLdt0bxdPfl1hOkO0X5Vha792SrFvbGLop7t6au4kh/9CXajSKQ5EYJnG2Exj3ERYCm2/6MAFg6je9YvIjgVj27g+8Svj/sXsRDvYURj3u1lyInePIlN2+vGOPEsa0+7EfuHc5KxxExee0Ok3vQDRoGwd1zcT+8f5HsrFj3DIjf09q5rNa/zdUVdXTRXC+0eKQtiXantf7HWZIE8C9z5+RjvyX+2hut27D+6vUC6b/VQ84cO6mOxw+b2hJ3fx2lMtD+EwylHy9xFw6hXNsa7hzZ37/ZAT0L2o3UfrI1d887/zplMMuY+S8J5vn4W1d+wqwkhhBBCCHkzKKATQgghhJBvyi250i9x62WahC/bRhM/hvKSEBPize4L6u17/4v17nH3PWdNVx73+7JQwVujgLbd/qC/NJdREJmF9d5G9RDJJgJqKeZ1KdVzP4e3ahZPu8ctqo4RZP3v2V2BzaPXcv22LL5iomPkNNcKF2DNg3jwXB5aHfl+hzvvfdtEKhn7ZDr9EmNEXemh0g/m/SAo5+0Yr9zETHPgPBBTWokeorx4LvPlhPN6xqfPn22/RAhza8RZzSjBUkd3YXfxPPX/+uNPlFKgqvjhdAIgqFrx5bx6OZ4L2jtQpKBqbWPXWzUM+NQL9j1FG970T7rR7aVzSenRaQKkhmy8fd6HvOdJZB4KbIYZJqaWkgRomMf5efVnAMDp5B7SqpAieKlnCwOPMW/99du7LLz13OjJYAJiBietM9Lz7Z8h4MYtf/K85p/++//1cgvC8qXAxq8ILGpECMzujW3iOCDw/OjhuS3iXtzA7NU63J50kVzVQp7n7UFI9wuWRVFDid2xF9jt2za2PTpD9Nm83gu6kCiR992NAdTXOkB7iPb1bFEGztWiONTJoCRZZAwexK0b+vMviJUrnut5DUne3L6W6WSQ0ULfe772KL+lCBHv9731PTVuzOPdjw/6fbqnzRIqZTM0owHAfbyliB71X/JAz89ZFqUj2spzde/XNXzf/N7Mgvq2nXFgFtUJIYQQQgj5q0EBnRBCCCGE/CUIL0Jgem/tXqJN3MoCwSA6A0nTuOpBNh+/y0ttbjuA2sS+xxg8MYf7FJgnNw5VjCKCguJCdxIEWoEA1EKua/WwxVqBWgchK+Tr5n8Zx8I7M5UFF8cUJp6rJC9JF92j/dE/VkOForiQtA2J7XecGzUd6SL74Av6yvqB5M8dMaV7oEfO530hpG6MAuYa4J7EFiYfqlhSuOQc6jvODUlOpLT9K2wsFyl4Wc9YygKFunctPCDA2MZazcc2e5h2Z3DdnW4mPi84r+fjMdvbL7t7fXMyqAjRENsQ6htcLB+FxJ7sQJJ4PstTsWYogLWu5s0vgvOqWGs1sTXE/K+gTx17qm73x/00Mbzt62YB47mWiCGE50UKluXUvNDRypBh7UWtWAGsWN2h3cZm1dXEcv+fAn0daWuLrx3DWgZAFHVdIbI04VjGaY0ITd0+Y0ibYl3NIMfPCSOAkta5SGVQseIMQKqdW1WBap7mWquN7bpiPa/2fNRq4dy9Qe3R9hV9RTeiEPRn2u6vmXw0Y4zhxg7Y+72RfN9NmQ8P9H3BOx7pWRC/bPKxc/SiJ/lN9g47170PUTd7o+/tD/FcZDJe8PN0OncqxM8d1/N7PMt3dl8U2zdGc++knwkhhBBCCPnWUEAnhBBCCCFvwiOe6Lece0u5+VB4nIeHetuPyatMR4/YWeC4qV3PvIjeOh7efmkSpAEggsG3XOCOqEJllMxEzNt0SSJAD88sQz9UVehaocWF9OLeotW3m1AiJlg1f+CUN72GcO4tq90LukrKvZxFTQFkGpjwdBSICXVZiNZZMB2kjG3/ySR4Twiw8RCvURfm+bito7iit0gxz3tVLEvBuq4osgyenjXq8zIWQQuRXYoJ379/+bQJZ31e3SN1XSEAPizL7FzqrVPPRR4GCNLVVe0hzV/O5kF9On3Aur7YfhGohQPoYp1fuPeUjIYsvf4v67nvlvBqn0Qn3SmjndDPFRQXXXt5mgTdvfH88YcfUVebny/rGeNDb/dTQ2zVirqG6NrzaJ/XFYDgw7I0Adk8zm0dOS0LVlEUzyW/+hyfIw/cw2F6iSyWlbJbfDZIicHrYd3bijGeL5K80QU/fPhg3ubq86imKyK8ea2oWu158Wd9hZ1YizT5XCOHuFpofK1dOM/j2SwUSoG6CO97B2ItQEnmAR6SPpon0s6CmwyhlKWFa49+qQBQbXxFYPd0Xn2NCSFdscLzniP5g7e1RPq9uJTe27n9XYntWnd+30RaJJWI7BDrT/s9LDLMrbbGl9Ilb9kxqGli6v6KuW8FU7b7JjaP7Xeo0c5GCruGKdPvpu8dfntlvj4/r5OYfVjXgYHV3nXZE/7o/EsC/WukpCGEEEIIIeR7gAI6IYQQQgj5y9BeHO+8ALbdaf/sctyEjxA6JF3n+5sIP7g2vuYtPFSa+QFP3nEHZTURPQ6Gl6hWQAqKqIsuKScwksZaiovnxYV7L6SkUObq3qWoLq4rVMyTOUTYivAsd/HbGxw5tnXV1MtJEJfSdM7wLBb00chCdxOr4viO6hbi+aV+nyVxhXvtS1few9u1h7PvucUFJoIDQFGx0NAQ/HT6CWs9u5eyuCdu7YYBIlgWF0R9HD6fX4b8xwIMwo0PmQm+xcKvZ4p7/A86mvY+CEMJkYLTsuDLyxeY3J7CnrtBhMYd5s6Rqa9umNA1nZQNO3av3apSPojdeGSU9KXtD6OZIgVf1i/DPW0Fq7FKO3dF5AjXCOle11ZnlFEib/hi3sdmZFLM81j0pj55hGsGSPlZGP7TfrTNPcA90O1IkYJlKZCyxESx8A+1woIXpBDsq89jN1JYUV3Y9zXCFgh/+C24/CgwSxeBk9esAFiT8UScj2irWMh109FdSAxBXUs6ZiHal7IApRsLtRJVsdb+gJzPZ6y1NiMlrZ7TvBkDpc6FGQLFncQz0p6VnXHZREKZxutoLOOCjWd01DVXdmF67E6dV1K9v0c5dhTEHxSVkwHanmied98qmM+HdoVw2aZPuHoNIYQQQgghf0EooBNCCCGEkDflm3ozxYtj2YZRtcMyiIADPZZtFGW7dUdER88d+tTdzU14orCNNqxdXFaEwJhvyr5K07IUpShUiu1YQrgK8SqJQZIyXksXz1vZIaCr+Waa16agiAlqVSNPMnBGhHHGMFghp+X7yl50mrYh4rmhNfQvP79fXZvYP/ZWeApekxDy9AhRv2oId55DHJaHPBQshW48xUMQX1Wx1heICE6QllO8aHHvXJdtVwuRjmK57n/+6ScXuStezis+nV8gHrJ/KT2vrc114FQWq7d0T23xdq1Vsa6e27xYp/7wtw/49PkzqirOdW39U1JvttDYSSwPv2fpHbSLiZltw7pKt6HWQwDcrh/jturaxsWO6nTmNJNU8efnP3t7RIbrsbO1V16t2oRlwMLmxxpR1+yVanVUtT7/2+knAMDLi3n4r1hbyoV9aXhvqzV+ex954UqnRNktLHsSx/vped+OoFcWLMVzpXu4CUu9UMMBvRuBrBbmXP0e5bSYQUf4a/u5u1ESfF7YnHMx3c+NeSjTNWbMUjyigYnltiZEfvbiXub2rJbFojrI0mYuIlJGhGmHGwS8nF+wnte2BkS0i95wbWMftgVadBy0cVgabX63NWsav+h7mQvo8yTmV/xQNVE/WaOMgfdzB34j8fTOat6DF/QtwvLG+1z6b2Y6K52/X/ZRCo8jz/RLgnv8Blwsn6I5IYQQQgghFNAJIYQQQshfkxBEZlfWENE3OWRDY0YX3+P8YPDqawKHtM39QNYXGznyoGZwc5h56KaOqoDUaqJQLYBU65uqzVO6yCjsRDmqQBFgKUuP6hsqezEhrYpC6zrkOw6PcxUB6gpVy2zeBEptGvQgtraP7NmXFXP0C2ysuhRYRDykdO4C3Y7B1T6c+8/aW2U1ca8qlmXBsmTTgxDdtPVjCcF1Cl1uYrk0D9gQ4MXzmq/rik8vLy7UpXkKoNZqXraIuawQtfl8XlcTFyE4nRac19XDkMeNlFbXTz/+iD8/fcaHAlSN50GGvmufe/13UUAfWUSgUx1BiLobwTI9abOciGn/s6QkBu1vrjs8/LV244U4KtptVRQYoiOUUoBaoTBR9zxFCrirjQdi2OB1qv2LaBLK03M1eO2HwUmsi6rQdW3zMq7vYcMt4oGiYFFtqQiqi+UqxYRGFURQcRULEW99I71QF4xLW7v9/DwPpoEv7n0uRZqHeaxfUgqKnLrYWQoWEaDYnI8xNc/yHssjDFXWWu1Z8TUr91tG3XBrWLdwPBcP1+1L6/lBaIYie8+JN3SwOPj2wmkYPN13zdaz/luSherdfy9gK56b97f//GG7Vu6K3zvjkdeRQ+H7ioc6BXJCCCGEEEKuQwGdEEIIIYR8Vzzz4je/eDbhKonoQXoZPudA76rtzkvt6aW0xjVBrQdq4m1k79tH1L9tyNbx3tT7psnUqi3cuNbqYl6FiolKtWjzoI3wyK2elKtYXDxfZDFhO9QjNU/zKhW6Alq62Bhu/SoCrGeohzGv2kNqVxcgW2eEmJfD0yZ9rY9H+MrbNZGvufcT0PKni4dbli5mtXJG3XR3XoqM/W7h6CvW81YMjfPCU/10MpE82lZD3G9CqqS/gHoe7g+nBWVZcF6rhcb28SqluBe5ecMuS7FQ+RVeTIwgvwAAIABJREFUX2m3Vav2nOnRdrUQ++dPXVTvXsnjvSsUJxHzwHfR6Fxrj9KA6dHQ2p7NUhY3yrCHrUQqgPCe1QgPb0YWJXl2z0YDMVaKPP7D0V1k87cfkdBxfbznCALJzGOoZjD48A0FcCqlewjXyLkOoFoEA8ANH47Mb+ZpdyCobYW2qQAXwkUBCRG9NRoth7fNEW2CsopFLtBacT6f3ePeBWud6i2CxX3ci1RL24AK1WrPuouNqlZmhRvrhHju7S5SoGIRFVo36zivWuh9mHFJhG8vxfOau5Au3v9FFsA9z9tz62tJpC2orvSqxvpVLUrAuuJcPdJBEUSYBYF4iPjU3yq9/2zHZkjzvN0c03GGbcR6lf6s5PH137k2q6X36bcWzefaYq393pjF80te3D33eNvRj40X+T6ZT9st+8jT/FqI9qN/R/Xn6O2MEwghhBBCCHkvUEAnhBBCCCHkBi6+Tg4VI0Rc36XpJbUCJqI/gGj3bJUH32vfYniwCR88i9S+twKQunroY4G64Gb12OlNe6srylrM5W4QuLs4HBdJBPouCKUMH4qp2BXAGnmTVVHripBytXmhmnBQAHh85sHzP5+V72nQEsObdrpr8XbGZ+6joYxE2dl3bRTUc5zXdYGIthDrZ7Xszi/ay21CSPLCNS9zK6c0Idpauq7VhE0IPiwLFAvOZ+tF9bnZxOlsl2ADuekTpO1uW9LD+UfVtXbv4Ln/cw52VeC0nHyqmCi11mrXuLq/eH/00uyzjfF8H2mo1b2Jke4n20HksZ0FqJkQvofc2PFX0Yw9VKJd1sIYj8ixXeuKGukMqnum7ohY7fm/2KqRi57nB+tI9kRvsdI12oWWDmBomNj9rucVWtT149LDwQuatzckMjqY6K6qLqJb/1QUk861Qqp79ebbcM/zUgQR1mIQkXUUoMOwKXLbl6WgFIsAEcYlkAJNaSO8dSaSV7u3Wk0sr+uKtVas1cPPe7QM+Jo1iMHRfdLnhbb/bQ13ojsPRXXotI2mhQ8PImw17c9GKmcz+G+vXD/igf7WXPNA3/cmRzJiyKvgvth9V1j1QZCXvd3XyyCEEEIIIYQMUEAnhBBCCCHfDSKyfSP8zRuxs6u98R6386ktB+1D1XUF/SGhQY7lwCbK7XicKdDzeHsO7EGMCc9hzR5z25rO62qe0yFitTAAo4gEmCZWpPgXFyq1YFWT1lTWlpdb69oEXnVxorQ2hLffKBZFf2qSL/L+fuZRb43MkQfaN7Vw7LozF47r6GLXS12tb+qYw7sL1TYhRC1OQISEXzzf/MnFxQg4rei5kBWKT18+tzsXAf7244/Qqvj85QsAwamYB7lroRYtQIGffvgRHz/9sdszZnugWMoCBSyct1aUIjh5PukQI0NQLChYloK///BDE+7P5xr2D1hK6SJoqm+ts4g+CeCDqpojT6gLXtbGJrj737W7MCMVFA68OFeb81XsnJf1xfrbc2UXmMf8h9NpmNvaUhhY/1cFzuvZIwt0wTz+i3otQkYf+9zfR1z2hI0vZbjP0I6jXIUbaqT+aF7d2q/XdKyqJVooUoBSWySH4ut2SUqpAtDF5wfMUGLVClEL7i61oBQ32khqcRfEPaJCiwRQ2n3OBggWlh0unJuAHmHcI4LBWq1REc2gGX1oxVpHAb2qmjGPG0hom2ux5ghQen72dr9JPM9mPQK0aANjBvc8YJOhSP+xaVEekEVc9dJa543fWw2S6/g2zIYgg9HBrWXseHy/Fdc80Fso92EVx9gJ6fzh+1wm9mNRHHmc3yrCzx7n1zzQ30vfE0IIIYQQ8jWhgE4IIYQQQsgT3PLSG4gX3++A2QERo6DRDiWxBUVaSOYZTReFPjYbDtTzC84u9IgUE0VzAdplJakFWBTigq95jZ5Q1hVFK9YkgasWD/+8FaNDtp4cM6fj+/cRx28dr0FsGObAQajcFA5+PLrds2njtN28Wdfw1Ib3m51zakKpjcVZzxCYB2+I7eEdXUME8vaV/rV5+QuAH08fAD/fbxbwrNZrElNPZbGc0GKh1gWCsxs9mFipLVT7y7riw2nxNhSsbjiwlMUj+sdYWnj5MJIYPNvFWyji99Rzyrc6vZQaOeS9D5oHaa1doBIgoiJAFIsUFCn4sFg6grWueFkFf//hg4uA3qcKvIQwX63i6KsuksfYJQ98AJIE7a/NPMdV1Y1hmv5qf1KEB7ixigeUSO20nOXSnmV7KEuBh0n3vg61tPVHpNEAoBauvapApKJWMU906eMYz1T3/rfPZSmpNb2v45wQy01EtxDuUhaU4uL5esaqcK/4alEB6trF8xDQI0JE3Ge0YVm6Lip9zrVxRx/z1MIHBy71hqTflYfCbr+9EPqIB/p7yYGet29rTzLw2ft3wvRviD3Tt1lEf1Y8J4QQQgghhOxDAZ0QQgghhHw3qOpTr/tV4o9vN3fIR4WM9HUjno+vtWdP5bsxdW3czm2YtiPs++hqiEkv0e2HYOgPy2NeILKk/drrixDGTa7sQqsdVqx1dUdHE8RbuGRIE9BbKwugtUCWilILyikJvauJdFoKFl1MFMYoYI/iGswDPAv8UyjxHIL9aBZM0+Yu9qeWbIYNCPG097Egh1JPDdA+uLXdnH2eQ0ify/bPRRYTP1VQV8VpKZAiWF/OfSg0+knbvujPz18+A2l/M31I5xS4WBqGDWKh2f/88gWLWDQBa5T1/8u5Yl2B1dtj4v6CL+cVFebB/BKh5v3aCh3GfR08yffYPyJrF6qkCfBoxgj5mVt1BSD4sq6tP384Wb755unvwnwIpzWN52xsYsdT81Sb4UMW1i/fV7qXQc72z501U/wZ34SdVh2XGE0mKPmYAlriObLnXyJWvti4V59HIchHOHd4PnKFh4XHAkWFaAHWFaoFBStqLZCiKHW1eZYiApTopBDmRQApyeBj9AgWkbbeSPFnuVmbFEDN+32t1UK219VF8xXrauHkzSO9ovpK0cbbF5Mi0kK1q/d77U8HJNaqNJIxvVrADA1xVNyDPa2zHj2iV5rHU/qE0sk/Oe2PRU6nw19LWL1JUB4iRtxf9qMi+mvc8xzx4NYyQzzfPX8Szo/sry7lOL+lLcxxTgghhBBCyHUooBNCCCGEkO+KZ178mn4wXn9zeQfvoyd5rHmQJumpXS9lLyv2FUJl0XUQUVNk6SZSztuSt6e25C9N+4/zJ5dAEyvXLip6TVF2Nxlw8XwWeJYI9yxoMmcWzjWpOhHCebUbWOqKk56aF6hq5PkWnE4nb38XzbOwEt/P53PqtyQy7ogwPT8xAJWej/1GruXO7vXs7HPP0iahNE9TU98iS/QkweVZkb6pe1n7Pbov9SpnVBRI7eNs9Zjg+GFZug1FiHHVPKgrek7v3IIQhguAswKL+LkhDja1XVEWQZEFX17OALpn9qoV67nitBb88GHBh7Lgx9MJ59rzRa/r2v4P7OJKf8jMZ4z8lDzPv8juUzDdRwjc1cY9xqA92VGGNrE9d3mIvF0yncu/jaPzbru+e2pnI4pteGZ07TgE9hC6Q8DrVhF2UfJ6ju8K+DNpIe0XEahUoJpYXkRQS8Hq4fsXWVAWC9m/lAVYLJ2DlILVw/qHp7ZFga/QpZhRQmjmIZZ7VAz10O1aqxsFxH378+9Ly1oVghWrrhC8JKGy4FwrXr6sWDWMViw/e8xh1cjVPhra+IqfjBUwzJZ4OOKpTaYKw4haqoM0aEnlHkcTrnjjcDvsGIZzdGd/K1/uWd5uYu8nVfNaH9Uficg316ObuZ25VrbcWP/eObdee1RGKaWZm80GDdfLurnaAYrmhBBCCCGE3AcFdEIIIYQQ8pfhuRfIMnwc1rHzza57QKjomp2LqzoeQ3qZfuP27GotR9uprRXunbrXRMEU2l03+k4pS69WFWsTiCYhPX8NvUVgeYarhU8e2xqhmcsgoMd/1b2S9zwF9+ZCl7iycUAODX2dWwX04+unbbEcze6uC/Pl3c4tAO4FbNdYX/WBbF67dmITK6OPmkC6oguqWRmMr+lTvcFNLITlP19VZp0Oa6344XRqRf304eSCZPciXmuIsis+1zOqKooqzgq7H2yF8h+9wB8AfBbgJzUhN/qowvZFez9fGZ6fUPAJFfv+7Nvn71ZlvJ2WBPftGTk6wl3FHzILdzHv/0MBrG6AoMC/fAwEBf+j/or/VX4brhcI/q//8T/xf//3f/n+fkMmyFespUC0y4K2blSssP1LqVhQoHKCFsHJRfbwSi/ujV4VKKt5tteYiG4VZFEsLBWERGoJmOFGFq8j0gRCSG/CeDcOCWV5VYuC0HzqVdvjFv0TZXUh3I0I/LmK/d1Rvu+PMPLQ3pY2HtDUlmn9cE/9S97FLZLHcEIecGTLqHY4pyl4lHmtaz0j4/zeE8/bPHfP+Ed+mq/9nl/Lk350LEcuODrvYeFf4GutQMrGPOLdwHDvhBBCCCGEUEAnhBBCCCHk3RPeegMbpfXK9qA833ltEiBnZv1G5vNcjdVRtklnjaXOdaxagdUEliagq5roBmn5u1uYZjXhpCYBvZWbGhfhlkdFs1sPSJd43pTsZdnFtkQLm54EGREULS2/N3B8J5vw9wr3ur6iaE3TKcqxUOq6Kffk3akwb+UWEl/My7eKeM7pFbUqfnJh9IuaJ/CPVfBZFH9LnuUA8KeX8zc1ofyTz7dHBKAfXQj+O4CPrzj092iDz1QruO4VG0dfYPf4TwVO+BX/1N/aPf93+W3Tjl8U+Nf/919hVbIr9MfTMx4z0XnxWVX9P9GKVYtFtqhmCHP6cDKjCayooqi6ArWiSm0ac1WgoqJAIWuYSVh0gqp1zDKRBOvwbIcL7dIepUg9YaHTY50Ip/DoNNFktiJ9DvbSx3Gu6bmt+Znds44QAMnoBINAvv99Oi0VP+XHdnF6E67/wIjoHqLn4nvbf2exOk+mm665XsmeAH6LGP7odbegQnGaEEIIIYSQ7wUK6IQQQgghhNzBsx6hdzG7cuNunaHxTLs18ucelOuamp+7FXa6N+/ciu4FqcOudJ6HdoaL4s0relVIsRDO0NVd3UP5cqGuhR1PbTtqSRPXu4j+5qR8xkM+5Eb3Do5RCGdXOZovUzHttrV/2ZsreZ/mwUqOrBE2ezCNcEH7k64mgO6VuTHAUHycGvGp2I4/0b208zj+kYT0P+W6wBbn5cb8ObVlbGR4144C/sxhvbcIfulTp31zc/YE7AoLVDAIfwd1/Sl27m8CQP8FgeA/FVi8rN+ayYuV8b/zGKVbGTTgtE7kdATihh/qYfzXGq1dUVVQ1Iw/ynLCoiuqFuBUoWuxulqqBc81XxUr0PN3K3Be124wozEX0eps/uheXjxPPqoQWZrHu+UU7z2sKhYFQ9PYx31GPU3K9/2H491WynHftNYP4xbbMo9n7E97VZv5T6unDeR0XovMcdDUW5DUr4lNeoy9iB/NXf/JNsxNOvAg3xPKbxHPj+p4SAiXZOxFCCGEEEIIeddQQCeEEEIIIeROvqWI3kU1aULKve/eWz7gJ7gkB82CtGy+Tx6Ys0dmaCyYw8QrVgXKWvs9hNorAlRBgVoYZRFTwUMwU3UtfRK2mlgjLqxrPyBRvjfqkhB9oT+eYZbXQphsAmXsT6G1m+dxEmdUs3iFVmr3ut3uq6FnueYmScjLou4ee164kgwj9kwSjvvquLbY+4NGHm7b88kL+/PGATg6L7zY92TOr809Zht7ffmIqGfXwcVkaWL54BW8U+TGzMQfv1nUt3Psm0KBWgFZ7TlcYSHfPbm4lOL5xivW1Qxg1lpRq3qu9S58d8sNa+y6rhb9YEoHob7emDd6v67r8gpIQfGO6B7cKbd5zLJhrcpzvovFeb7cEMcBzehl2CXzKfOX8bz4nK2XtEf+2C4sIZ4/O8OnFXvo/2PxfD7ntZ6zLIDPz8Otwvp8/t72I8/aPc83IYQQQggh5O2hgE4IIYQQQsgFDl/sf4s34d1Br3kfPlStPugt51TRQw1kFgU2+W/976b2JOiohDeotnts16nnFx7EM6C5k0uBVr+qXejCVQqjDCB5mc9tyXJgF9SbPnVHrz+bA72X00W5LKL347NYlEQjmMds3YhTO/fp3wVT52Qv2BTuOYTEZoQwed72GlJrQ9/DjfM3e/8enNJzmW8NHO4SBbMYC+ATxrbLVM+1SBCbum9sy3jW8Sya9+ckBVsThp0LJyE1hGWBeaOXdL4CkBIXjfctxduYdGwRgbS0AXlG+BOpChVxL/IKLTDvcwCyrsBLQcXqAnq1CBLrauHQax1DoWfDF1h6h5pqHcRbHcXtHtY9lzU/K6P43fo51kIdz4ry95JUZFr3D90zC7XzNftCb9vucdr7wdhOlhACX2sxnvaa7t+PCPKvGcJ9Fs4vCepH1+997p1zLztDTQghhBBCCHnHUEAnhBBCCCHk3eMC6cNX676acwfXLs+6XNOj0z5NG5PPYpOuNJ0f29LE9348F19VUbJ4lAT0rMvM0lvbHsSnJP2KNo/Ut0AglvMdl0UpwVY8R+QybyJQP79HTZZhX9uaBOW4QKbtPgiCngv5ssftbL9wrJsdWTp8DV63nudzS9833/r8FoiUrfoa5HHL14fxhQIFfb7/U80TvYm3m/r2G7Pd7/NHBQLLUV5WoCz+iFWr/6wVsp5daK9Y19WjKNSUy3ysbJjX8V88x2k9CKOPPrcnUyQR1GwNMN2jCfM74n3UmULEH/bNpvU7+24Qzjfi7Syip/PUw7QPkSsgV57S+3jeg/312BPPLwnqR2XsfT8651708UsJIYQQQggh3xgK6IQQQgghhNzCW774nlzX7m2KidqP3YCJT6M4cxOTuDV4CKdtPfjEvD2r8omWYz0XMol5w5XZq3gSz4fT5hDJN3DV0ODGsja5xOP6uYwdQU3sJCxY7m5D6IjrukJrbeYL4XkrYp7Eg1yeckM3abK77+9UsM8oQY7C7a3cK+h1r2T/InEPR0K0n3Zwe5Fz+9Z6M5uxvQMBUERQjtp9GBY8bWs/8JsbZfTnz0quyaBCpZcbRhz5zjYCtwJSK0pRyKqQWu26gpSvvI4e4oM4HYZE27XwqMc1rAN0/hwLUL+foRydzHu0n4the4rQca1Rw0m+5Wu8TDslf44nj0XptD97oEtqUBrjb2ekchnZNby4do2vOW4ksCeUl1Lu8kB/RlS/veFo7SaEEEIIIYS8byigE0IIIYQQ8h0QAssTJTxRt5hweqHkofTX1Aay2D154mcha9DDpHv6ZafTkGXHkMFJZFKYuIYLAuo3ZM+LdBCEMAo7eXspC8pShuMAmoe67dt6ZIaA/vnzZ7y8vKC48qldpfOQ/tYuqLpOZ8faOMhW0+sVbL7Cq3Wh9dhY4hYueYFv9k5e+tc8VK/WXcr9xiZxrRXweKSJ4mr0DQxeydkOIonEksTXMOjIz9eldioUdVKjzfs5xmY1f3cFUL38WpGD0s8iN6AWOj4ZOWwNbg7GfbCRSTfq83S9UEY2ZbnliMQt3Lhmt7V9VMn79bv750IwTO643/lRevLReozpWZLhkOyvEzfQ1iB0gTy+H4nntzzXR6HynxbPAQrohBBCCCGEfEdQQCeEEEIIIeQGjjykvx0bmfoO9OFLQ3A+9M67tq8p2Jev2dQ57RFXzURD3M5Kn31JfqpDA3Le3+aAmSvJqjy6oNiOvSFZRM/7bqFMIb1DMB9CvQtQPG917rfz+Yy6rl1cjRzPHjJfIxf0LKa3yno7ctjiW1qu2UP4Tub+mou5pf57hLKtgIuLc+bqbd1rKJOEOHVjhlvYiIReVozVUTFD+6cxLumsZgwxXR0GGv3TN2pNomL3co8/TbjftCYE/po81q+0PC0d/b85g/z0LbdtqmA3xPy8TgVXBkjn0+Rg/+61+/L+3v5vtartPUvdjkGeWl73hO5ZKA8hfV4/9wTsI6H8tQT0ZsD1Tjz/CSGEEEIIIZehgE4IIYQQQsiNvMVr7yHi7lsxhxDOh27Yp0lEnyOxD4LnTq5eQRJESojbvT2qAOpOuHNX3CL08ixARb9K+m4bk4fnW2kdIl3I3xGg5xFRT2Qe+80DuLbt8P4F9IoQZOcUKSjL4gYLXSQMIb1GaG1V++5ieqt9R6C6tSuf7f5n8pA/K5I9c72kv49d/7iVTLZzac/WXmuk/zc+a0DdlZ/3RO+8JqjNMRGPmLCV3cfKZ2Mmbd7reiieT4SAnry0VWYB3U/Uaf1KRfQ1qM93m3v9mdk1VNj53qqYOnyvjN1bmuZ7bB/uv1ri41wy9onIFHar0tME3Dl15/va8zA/yn8e34coDF9ZPCeEEEIIIYR8f1BAJ4QQQggh5B6+5Xv0JPYOgs0D5Twl7O0qaV1L29ufCXGoex5O3qCuqgxepm1bkoe4NJG4yUAqg6dlF95LU8f3JLnQyWcR8Nq9PM/l0ZOs8LfvW0/WHW3dDyhUBYqKFUlUDW9zEWh1+UoAKbGdxCL/syyLhfHWUZBTVYgL6E1cHAR2geRQ3Bjnb2v/1PgsSDY5+cYBGATbFHr8kfF7TbFsHu1rJc/P1DVDgLmpz7Q9PP/z3MrTsJ031b0vm0eZY5j1jcTtUQtKASz8/Hauz17fmvaF57gZcdR2fO6Fee00gTsCxhePUiGDEcDc4haNIe2P1uZUCxFAoW0DzQhpjG6RGxo530dxdxNRYUrlkPfdKqLPHfPa6Sq66DxXlQRswNIdhHHWA03Y64trOc/n3OnX7mH+TgghhBBCCPnrQAGdEEIIIYSQf3tkUm7uoGmRshXMD4o80htEs3w1FiDD335eiN/DlWLil+13Ac3F3CJdRN+7Plc/aNQX2v5o1z2CpC/Zm1zdsmAWIHvb0n4BLJ30eSg1BKXiRgkSInrbRuuAAsFSyhjCPf0HmOe5uGBYfY6ZMFlR1y6E7hl+7BpZtGM+fg/qVm8teD1nrPLEZHv6vvuYHRqWSP8vzpkF93k7s3d31U0ujkIP5PJqfrJjDVCbc80D3dcHQRjKbHOlR7k6fNeN2YdM5/QnMmvfW6FasE29cMS8Ps2C+V4ah7w/13skom/q9P0Fz4VR3/fi9u08oFmQjm1fi/aMaW7hmrc4RXBCCCGEEELIM1BAJ4QQQggh5LvhG4trOl620dL2FLI4L4TX7o45lNvkKNGth3sKo66iXWCDebRCpHk/D8KXKioE4iJ6E/Q2nrLRzmNhLd/vnkfr12MrOg2inc4eveMXlS7CNnGrGRWY4F5F3alfmnhu9XQBTE4nlGVplgoSXucesr24iG7j63nRm6NwGfKY5zHYo4mese3q59e0W/haZef+BO6bN2Gs8Mxce0oM3dluj/jGm3h79WTacVMfxzlVFeda295ZS+/PYsxtDB7omAX44bscPtQmsodYPbVK5z4Z7/EoHHrsvdWze3cNSikZslgeRcZ+WwcPRHPZKXPcAZXnBPTjiRENnT7T9yICKdIMHaxNU5E3b6fenlOOzD892G7P589GIHtd9FCaCOr4hBBCCCGEfDdQQCeEEEIIIeS74NvKuEAXyOWSICgHHtqhm6iLIxFWu4lA/v2ggOxJGiG5Z29QhXmkVqiL5wrLoiwoTcaaRK/UvE2tWePR3obW/J3b/Go0HVZaBPcWrH6nv9t9uSgGhJjrhR1QXYnMvRtb5h3aO0C1upguUK02bLktYjL9WvtQ++6hjZtblXF2H9hl3MRoCnDMUflhkPEoe2Gjb7puaMRj9T+dvx039Ps1Q4gHa65VUSNigsQMzOJuFlqb5Yw/o2rhwJFle+nbs6Caz4g15sGW5/lyLPpvBdrYf0v587gM62AyUrlUal4H7XHetvlemmFFNt5BWk2mqBbNUKdtShu31pbZ1uHe7ZnU15sxSF11769rTxtyWOT+tu5fSwghhBBCCHl/UEAnhBBCCCHkHt7grXf3Av3GlV8QameOxIfsvWoiRVap4SLY5AuePQazC6D4dvJuNg/GAg2vaAnhuExC/Q2tlSz+AKhdHstOrDfzyHAlRUxLQQ9G7w0Ubf3WBLrQyeGh3puXbjJQiMsi33y4fCZxPntwrrUC62plNrFSAQ+VXTWaWlNo98lYomtjF8WpWbwSV993r7mlTy88J+9FtKp1DBYeuvBtIdxl+Mh7n8pnHc/pXkjwiAqgXoegGUyMzcnP95FsreM5Hnq9Vm1j14wpNP54fnRVv+RInp7rPOoPabe1W8x0taa2zvcnQyiO0RO6GwEIdGfYZuOeVlS2JkEy6kiqdTcm8Odd+tSfDW00Hc9rcozjI4Q4LuOedr978zP2CwCU7W9BXJ/bf+/2rrXC3I+7NxOGBj6vYz1D+/npV/t6FwJ+7tdbtt/LOkQIIYQQQgg5hgI6IYQQQgghN7AJM/6t627ult+Oe6q7JFkOIvqeuAEXrnd0btEuEA11NQFPsEjbmy60XVKwI6DfhornEn+YbdtvRSCA1i7SQUada9TsuoDUviu01o0HZBOwsneoePlxngJfXhRlNT9+1chtrn0atvDVPYR083J1L+wQFgddq4WX37+VoGCfrHce9u2FR+XqaByIf+3wTn7lW2h95J+7Ajq6UJcNJIZ24bBpPoZPLFLFhT7tubU1C7TRZIF7Fwsil7XEnJLLodv37kBFsGpFe9QF6J7jIagfLcBdgPfShppiMmjeznXHHoEZlUya7ub7zrhrWZrpShu/GImhEGn3m8db0xqn/bRNP0YPjGHs+3URJSOepzh/f8n18SvyuIAuBaXsRVzYVc73StjtZH2l7f0R3z+e16AhNLv29Q/T+e34VPhd24QQQgghhJB3CwV0QgghhBBCLjC8ZOeb710u2RZ0b7vrIs1unuwjLTN7Pm6Uql6e1CcERcHTg/7I1RH2Pver6r7vZAjnEa69i0Aenn3sJHSVXZE9arNwJwC0Kqr2nNTdMV43+8bvrUGt3qHlKYz/NiVz3lGw13vQozjYAAANIElEQVQi2oRC3bieXufSbIh5uidg3iOc7+VGnr26W07rW9o55ag/aseTEdw3DOL5DV3cwq7fVUcXeaUk+VdGObovBOlzKAHJsmZs1dF2X5t6MbJTxrV+NYF1LLelJZgu1vaQSbv2pkrGZl49Z4tsvwmaAcRDCIBSbmjRheuTwcV8b49s48L2Zl9eLzGJ6F95mxBCCCGEEPL+oYBOCCGEEEIIeZojYUAvHLuZZ5TBh2KvOwWe7/vBAh7NhT0IhcdcFIxkNEiYi1LMx8KHNsSeumvRcDEEso7nPeoN3b3tt33fhP7wChVYu5+dZEmnnYV0YCugtxzSNwrqV89TMzVoEvQwdvvi/V6Zz+Rvj7DU4X2+h7joaWPUvY8ffUJj2hQRqJTNetHCgbftI0H8sfu+JMA+wrUydls7h4a/hxQ+/nbTgXRtM1R4jNcWhK+J4LeI5F+r7NfeJoQQQgghhLxvKKATQgghhBByA6/s3Elu5vGeN+1NjuOBX6MCKNLzhd97ea13h/oO9sLZX75g3Bz1OBmFYd81e0Xm4Ns6F5KUv+b5Oe2L7b47N0I333R3vzZxtovlqbydRNKXg4bfRvbAHwvfF2/vGdc90X0Q1bWPwHRl+jj6PomyjwqxSMK5plHx/u86q38J8TW0/mfd3y+J8VlgPqrnFtfsudi49ILBQBT91ZGtucnN2zvXboo/3C/u+U8IIYQQQgghJEMBnRBCCCGEEPJVedrB8gke94OG5U+v5SnriTnX9U314vn7PixkFtqTs/Mgd+sYdnzOD31Jr7RT+xmzV3QX0Of9IZJOYrZ7nM9yf2toj739Cth8mW0mHjWEOKxlDuHutzDU0rzi58ZMn4mH9XP1kP97BQyiffc8N/28N2aaIrdW68UWLKVHrNg0Q2QzX/4teHJePZXzHjjIYX5r5fJ0/YQQQgghhBDyXqGATgghhBBCCPnqPBeF/QkvdN2KoXdcDZT6sDabQ1zfWauhtzvWziHFzUF4e+Vue3aF2NErdw7JbgJwfN+5Pv3tZW7bO38frx+Pb85r+dtfxwM9vrWQ8C7cZ7E7e47fM7Z79zDcTxrrJknr2IsadbY25f1bo4e7Ud305SCQ7onnR+L+vbjBR78899PlNtvHc573r0lPcy7TfhlPiP3PRNk4eM5vv35nDG+9dkpzQAghhBBCCCH/TlBAJ4QQQgghhLxbnvX8lT134psvBiDFhMwHNLZHBfSBJ8S9Z+rWHW/k7i08hSB/pOw7jt8inD+rgYbnM4Duzb5T5qW25/44uodbDAeyiJ6b067Z7fdtvvh7uHrtgXj+2p75vboL97PTh68tgj/KI+L5s8ZFzwnoj+a3eIUoGYQQQgghhBDyjqGATgghhBBCCPlqvIbA9nwZz3jlSsr/fB+iglIeF6hQ7293DoltSdyBbeP3yt3ELN94tWPzeXDtUNMYplx1LLuVd0E079+nrOq6PfdZtpHDZeuNP3ml5/OGsq4ZAuzsF+1ivkVO72HrW7fP4fUvic13UKFDVIGouXkpx87Uvtfo+RxlQbWPcfew12HHvjHCc214TsSOz+ui+ext/u/gQf61jCgIIYQQQggh5C2hgE4IIYQQQgj5t+VVxPcHPdhlKdAHc6A/Ua0XIgAOxPsrYmP3xL5TOJ/6Wqe85eqXhIiOAxFdMYmjcf3c7q/gfbyt4nax/JIH+tH+7XYSk+Fh3L3c1m/Qsau1h9d/eL67cL0J4L4Rz6WJ6ln4fpRsGiEe9EBxXTR/bYfzr2LoE6H+h9QH22ueqvuJPOTPiveEEEIIIYQQ8u8MBXRCCCGEEELIu+UZD8tQ2Z4RFa2Axy9/Kgf6g57vOyVdPzN7nAOQIk3Bz7dwJNTO26PwHEKiC6XNi1nyBb2iW9TRJ8XzQ4E7/sj+uZfC198amv44NPlRe9I89n6aI7lHjvpHQ+v3yAX+iR6yHXLsqTzfy+Nh/e0emoj/DcO0Py0k7wjl06Gh/COh/aGqX8GL/GulYiCEEEIIIYSQ7xkK6IQQQgghhJCvznfr6fiMuPWggB4Xm2Dqm3dertmVGZPYJbLNH549YVWxyHJDG7fhqKM8afsm7+2cq1umNs2xu9M1cf6s2b3+vNI9Hfu7IET0Rxk9pUfx/GkP96to8z4/bF/zxNfdx/I9enLPYdyP6ngrEfwt66QATwghhBBCCHnPUEAnhBBCCCGEfFWeFne+V6HlGT1PpXugP3D7Gw/xyYt3FrKH0yex71ZJeRC6sxh7dMEm4bjvKKW1dzhdtbXlqfD2e3W3/WOHXxVGL5xzJBDueevbgdGm4MhAYZtH+/XDj8/i+VGbYzz2znktrkU78J3PGQ88pb3v3PtO3vNXF/0JIYQQQgghhHw1KKATQgghhBBCvj7PhlF/A56u+cF7HrRsDyf+tF4s05cUYj3EzzlUuZTSzh3KujYmikEJ1lnwvXQdvNsmL/lo+yysPxzC/WB0FYqctf5IvH1EQL8pFHka6yOh/FCsfc1nZRLPs/d3oEgRAeQ573ekUOQbu4pNP+w19+sJ+FfZEe/3cp3nz9fiXXhxP7HOvYv2E0IIIYQQQsgOFNAJIYQQQggh75rvWWR5RjALB/RXaUcSOnum83Bw1+QF7ftLSeGn7aMXIT0HefydPKdFk3fyRhiVLuCn62Pb9PMkoLcPHTzP7VzZKq4XaB74h+OiKJMhQWbvulvHeE+EHrbHiPbIY5T+zB/tmwqAetAZ90QyEGn1hSf60N75fLWIA89EBUh3umlK/34sQouUp2x0ngncfykP+abNeye+8fr2zPpKD3pCCCGEEELIvysU0AkhhBBCCCHkK7AnPt51PdLlz2psGwE1QqFLE9ctFbqJpyKCEh7oLnCnAOruIe6S56T/piO2T/t+jbbsSKZZPM8Cci6oO7Z7WYOQ/zpcEgVfwwP9nvqA1AsiY6/J2ItV67GIfc80TFqvNDEdSMMKhXe9KmqLMZBOuJedR+VIfN4LiV5KefhZ01pR6/XzjngmB7r6s/Rw3fi+DYwIIYQQQggh5L1CAZ0QQgghhBDyVVHVN/eyfIRnW6zQ3VzetyAKVIxyZBO65Xi7C9TTdmpGF7rjiwyhw9t5O4LsXnnz9Roe5jqfm0RnTWK6Zm94uEfzhIcTj9Tw9sUr0OFruBT3fgGg1b3Xs8HA1I/XvLSf9bbNgvBV0XM2nJBJep3H1PsnwhYMxg2xLdP2dLzkMOhzfV7nEKxcFboAxQspz/RP6SkDhjl/xSu9N+W5NeZrOVL36AIRcWHbxu9ZAP9e13ZCCCGEEEIIuQYFdEIIIYQQQgi5xBPi2t3SUg7jnTd1/A7cvz0UDLnYNm1i9N7RHbV9OGqCqoYIm8Nwz83YodYKDZfgSSjOInATV2VbsOpUfskGA1P96XZeMyT1LZ7sewxdfsWjfLRNEJRFBrG8ddcN2yagl17eDZP3pt7aGFyMdUeohR7x4NvzLUKRf89COSGEEEIIIYT81aCATgghhBBCCCHvjI2X+Leu/ymxT59yStUULH4j4t5Q7l7d9wikb9XnwJ1B0OcTdwwD7tvOHug7Ze+I4MO5R578B+1sX2crC0IIIYQQQggh5I2hgE4IIYQQQgghF/imfqNz+HV8JX3xa+qVr9Fhj3oEqz4XjvuNnYTfUkuWLKDvteOe7XuvJYQQQgghhBBC3hEU0AkhhBBCCCHkBr6Ftkpd8cYc4ccXP1k33lREn3POf0tMQH+buhncnBBCCCGEEELIe4ICOiGEEEIIIYQk9sS8lqv5a9c95+7+TnlGiFV9Pif1w9fr0xr8w7Tw7W/lgQ55s5t/Y7sFQgghhBBCCCFkgAI6IYQQQgghhJB3g0B6DvRHrhcxMfixyt/MgOGtReS3MhwghBBCCCGEEELeGxTQCSGEEEIIIWQPCoqP8awSq/qUB7rgiVDkb50D/S3nnLydBzoeDdlPCCGEEEIIIYR8BSigE0IIIYQQQsg75q8mLarguWTggqeE4LfUsN8yBzpd0AkhhBBCCCGEEIMCOiGEEEIIIYTs8JbCdeTDjjb85aTNZ274CU/q+apv0e95nj1rO/A0bymi0wudEEIIIYQQQsg7obx1AwghhBBCCCHkvaL49kK6AoD89TzPg2fCtz/LW/f5W9dPCCGEEEIIIYQQeqATQgghhBBCyGW+pZ7rdam6M7Arqt+TsCr+Rx7sOH0yBzrweH+JGy7IG3R4eJ6/1VjLG9b+Pc1vQgghhBBCCCH//lBAJ4QQQgghhBDyaqg860Weg9eTb8Xb9jjHmxBCCCGEEELI+4ECOiGEEEIIIYS8V77r5OcPNl4iA/xjqN4feL/Vli/TbyTrRuVTwvs3kZTfUMf+rqc6IYQQQgghhJB/K5gDnRBCCCGEEELeG1QTvynqf0I/1m8pJOd6p+2/DH+5GyaEEEIIIYQQ8p6hBzohhBBCCCGEkHfDo7nTAUAfVWJdtJZx1zexYwjRfPA8/1aVE0IIIYQQQgghZMP/D1OUEcqSMlumAAAAAElFTkSuQmCC","consoleMessages":[{"text":"Unrecognized Content-Security-Policy directive 'prefetch-src'.","level":"error","timestamp":1724495172542},{"text":"[.WebGL-0x16b401efa300]GL Driver Message (OpenGL, Performance, GL_CLOSE_PATH_NV, High): GPU stall due to ReadPixels","level":"warning","timestamp":1724495182310},{"text":"[.WebGL-0x16b401efa300]GL Driver Message (OpenGL, Performance, GL_CLOSE_PATH_NV, High): GPU stall due to ReadPixels","level":"warning","timestamp":1724495188327},{"text":"[.WebGL-0x16b401efa300]GL Driver Message (OpenGL, Performance, GL_CLOSE_PATH_NV, High): GPU stall due to ReadPixels","level":"warning","timestamp":1724495188662},{"text":"[.WebGL-0x16b401efa300]GL Driver Message (OpenGL, Performance, GL_CLOSE_PATH_NV, High): GPU stall due to ReadPixels (this message will no longer repeat)","level":"warning","timestamp":1724495192850}],"screenshotDelay":10000},"timestamp":1724495172091},"created_at":"2024-08-24T10:26:52.938+00:00","updated_at":"2024-08-24T10:26:52.939+00:00"}